Split (1)

train · ~9.11M rows (showing the first 93.5k)

identifier stringlengths 11 32	pdf_url stringlengths 17 4.62k ⌀	lang stringclasses 120 values	error stringclasses 1 value	title stringlengths 2 500 ⌀	source_name stringlengths 1 435 ⌀	publication_year float64 1.9k 2.02k	license stringclasses 3 values	word_count int64 0 1.64M	text stringlengths 1 9.75M
W4253177391.txt	https://zenodo.org/records/1912283/files/article.pdf	de		Litterarische Berichte	European journal of forest research	1,900	public-domain	5,389	318 gitterari~e ~3eri~te. IlL {itter~rffdl~ ~idlt~. 91r. 41. $~fiologi~e ll.~erfu~uuge, fiber ~i~e.ton~tum . . b @ol~;= qunlit~t Iron Pinus siDestris. 18mr ~rofdfo~ Dr. ~c~voar~. ~it 9 ~ga~ein unb 5 ~e~tfiguren. ~e~itn, ~Se~ag~uc~l)anb~un~ ~ctui ~a1:r 1899. g~. 8 o. 371 \| girei~ ~0 de. ~m: mir Iieg* dn !Suit), ba~ One ~ei~e ~on ~rennenben unb [unb~= mentale, ~gert bet ~)[io~ogie unierer &oI~gem~cI)fe unt) mit bieier bet gl~eorte bet for[ilic~en ~3robu~tion~le~re I~e~anbdt. ~r meine ~e~:ctufgat~e 5ringt e~ mit riot), bag fib: "mic~ bet ~n~ait be~ !Su@e~ I)eI~)nber~ mic~tig er(c~eint. ~5er e~ 8u beurtei~en er[orbert ni~t nut ein ~c~ritt~dten mit ben ~umeiF* [icl) miber$prect)enben Cr~einttn~en bet giite~atur, fonbe~m art4 eigene ~orf~ungen auf bMem ~ebiete. ~on biden 5eiben ~iorberungen mii~te ict) g[au~en menig[ien~ hie edte [i4er ~u e~fiiIIen unb buu~ fie in ben \| gdet~t ~u {etn, itge~ hie roi~-ti~fen ~:ge~nige l)er \| el)m a~:~ict)en ~or~4un~en in t~)rer ~tu}anroenbun~ fib: hie prct~tiigoe ~orftmirtict)a[t ~eric~t ~u er[t~tten. I. geiI. ~a~ ~ i f f e n l ! ~ t l t m . 1. Ra~ite~: ~)ie Bur ~e[iim-mun9 be~ ~)i/tenma/~iume~ angeroenbe/e ~et0~)be. ~uv ttnte~:= iu~ung 9danglen 51 \| ~. Rapitd: ~ie groge ~eriobe be~ ~ic~enmacI)~tume~. ~n ben e~Fen~a~ett be~ ~a4~tume~ einer ~r it~erroiegt hie bu~& inhere llr~ac~en (2n~omelIung bet ~u/~gri~ge) ~ebingte \| ~e~ 3uroa4ie~ hie ~invoir~un~ ~tu~erer {~a~toren, roelct)e nut au~na~m~-roeife ~elr~icljtli~ere \| I)er~or~u~ent~nnen. 7)ie r ~Safa~-i~eige ~eigt {d}on eine ~erminberung beg 8umad}ie~, ro~i~renb bie oBere, jfinge~e ~ e i ~ e noc~ Fteigenben ~umac~ au[meift. ~)iefe \| ~ger~ (11r~aa~e bet ~olIboI~igMt) fab~t &a~tig au[ 15Nere ernabrung bet ~amI~iallagert an ~ogo~e~ronten~t~tmmen ~m:fic~; ben unteren ~geilen n~I)men hie ~)Iaeren:gei[e hie !Saul'to,re gIeic~[am ~inmeg; au~ ntit bet ~fimage ge~e, fagt &artig, biefe 8uroa4~gr/ige ~OardIel~. ~eBer ftelIt ~obann hie ~3eDaupmng aug bag nac~ ~ufftc~[egtmg eine~ ~ugenbftgbium~ hie ~a/~tttmglei[tttttgen itmer~alI~ gemiger g}eriobert ~i~ in~ t)/~/~[ie ~IIIer ~i~ g~ei~ bIeiben. ~ct)ma~ ftellt bMem ~at~e gegenftBer einmctI ba~ ~ort)~mbenMn ether grogen g}eriobe be~ ~ac~tume~ in ~icte tmb g~inge, atq roeI~e ein ~b{~mung erMge; ~)i[fe~:en~en im ~l~ic~enSuma/~g I~e~uDn auf ~d}m~nhmgen in be~: :~em~eratur, {Regenmenge unb in \| rote {Rcmpenfrag; bMe~: ~et~tere g}unt~t roi~:b im 3. ~apite[ ~itteratiI~e Netid}te. a19 ~e~anbeIt. ~a1:tig I~e~au~tet, ba~ am ~uge bet ~a[a~iurae be~ ge= ftdgerte guwaG~ be~ gjauptfGafie~ ~on ben {Releruefto~en ab~'tamme unb hie 9.Iigmi[ation-~o~obu~te grS~tentd~ im oSe~en ~3aumtei~e ~Serwenbung ftnben. ~6)war~ ~agt, be~ Suwa~ gel)e e~ft im n/iGfteu ~abre ft/ider ~urti~ aIg im ~ragjal)te. ~3ie gn[egung in bet oberert \| M Die ~oige beg bur/~ hie ~rttnabeIung geftfirten ~leiaw in bet meGaniiGert ~ean~pruGung; \| ftellt fig auf bert ~tartbpun~t, bag be~ ~aum bura3 entfpreGenbert ~[aGensumaGg bie gC[eiGgemiGtg, Iage alIer \| a[g ~r/iger einer grogen ~aff ~ersuftellert ffrelat. 4:. Rapitd: ~irtf[ug bet {gempetatur unb 9tegenmenge auf ~r~ge be~ ~ic~enwaa3gtrtmeg in ben ein~eIrten ~a~)ren. ~utG etne ~ergIeitbung b.eg~em~oetatutgange~ unb beg ~IaGenroa6)gtume~ roa~renb 17 ~a~ren fanb ~Gwar~, bag fib: bie ~ttmme beg ~ttmaGfe6 m~t~venb eine~ ~aDeg hie ~gempetatm: bet ~onate ~anttar, ~ebvuat unb ~ar~ ent~Geibenb Men berart, bag bet ~uwad)~ bet foIgenben ~egetatton~, ~eit um ~o griiger ~ei~ ie ro/irmer unb ~onffantet warm bie ~Is ~anuat, ~elatua~ unb g2~tt~ Men. ~rt bet ~et)~8a~i bet ~alIe tti~t Dieg in bet ~g~at ~u. 9.Iu~naI)men, Iagt \| l'dert burg grDgere ~roc~enpettobert w/il)tenb bet ~3egetationg~eit, burg Male ober inbi~oibrtelle ~etl'Gteben~eitert t)ettmrgentlert. ~ie ~3obentemperatut tlanrt, wertn fie iilaet~aupt einen ~ingug ~ifit, bie{en nut in bert ~onatert ~ot bern ~3ege= taiionglaegintt ~dugern. ~aG ~to/~enpetioben Ialeibt bie ~enge bet \| ~o[~bi[btmg ira 9.Iuguff ~rttfi~, tnbem bag ~?i~enwaGgtum fttit)er ~um gbfGIuge ge[angt. Nr~igere ~ieberjGiage ro/i~tenb bet ~egetationgseit befiStbetrt bie Nreite be~: ~a~tt[nge; boG fte~t bet ~tngrtg, ben bie {~euGtigtMt ftbt, bemienigen burg ~empetatut na~. ~iingere ~ffartsen finb ben \| meniget unterwotfert aI~ ii[tete. ~aume auf nagem ~3oben se[gen gri~gere ttnregelm/igig~etten biettrt aig M4e auf ttoc~enem ~3oben. ~a~ 5. Rapitd b@anbelt hie vetiGiebertert 9.In~Gau-ungen fiSer hie bei bet ~ertd[urtg be~ :DteeenwaG~tumeg wag, gebenben ~atltorert. \| fii~rt hie ~erjGieben~eitert in bet ~a~trirtggSiiburtg auf meGaniIGe gcdet~e 8uril@, meiGe ben ~3artm a[g einert ~Er~tger g[eiGen ~iber~'tanbe~ aug~ubi~bert t't~eben. ~iele~ ~ie[ roi~:b etrei/~t quantitati~ burg grdgete ~uroaa3gffeigetung an bet ft/h:fe~: IaeanfpruGtert \| obey: qua[itati~ burg Nu~l~iibttrtg bifferert, fefferen @ol~eg, \| ~ie quantitative ~inmidung burg gug unb ~tuc~ 5e~anbelt bann ba~ 6. unb 7. Ra~itel augIfi~r[kl}. ~trtroithtng ~on ~inb, ~cl)nee, ~tet[urtg beg ~Galteg ~abert einen e~5~ten ~ttffttg yon 9la~ttmg ~u~ ~o~ge, um be~: t)iJ~eten ~pannurtg im Iongt-- tubindert ~n~/~ {Re,hung Su ttagen. 9.Iu~ gMd0em gC~:unbe ~eien bie a20 ~itterariI~e ~eri~te. \| an einem ~erg~cmoe ctuf her ~ergMte mit ftSffe~er &o[sBiibung ~er~e~en. ~te ~efffir~ung bet Ram~ia~sellen bu~e~ ~ruc~ auf bet ~on, taken \| be~ ~aume~ mir~t a[~ ~ei~ ~u~ ~3e~me~rung unb ~Serbigung her ~rgane. ~ae~ ~une~menbe ~iSenroac~lum im untere,, ~ctfttei[e ~reige~ieliter ~anme mi~b bementbrec~enb barau~ 8urfic~ge~fi~rt, bag nac~ bet ~eittel~u,g bet ~aum bure~ ~erftr Sufu~ ~ n ~Ra~rnng im unteren ~afttei~e hie ~ei~gemi@t~[age gegeniil~er gem ~inbe ~c. toiebemm ~e~Su[felIen ffl:ebt, g)artig ffi[)rt bie \| im ~umac~ auf er~)/5~te ~obent~)~tig~eit, auf ein ~uf~e~en be~ ange~ammdteu ~a~, rung~fto~e, radc~e eigent~ic~ bet -~erjfingung 8u gute foremen iolIten, 8u~fid. ~m 8. Rapite~ ,,~er~/i~tni~ bet ~ruffmi~ung ~u anberen, ba~ ~ic~enmag)~tum 5eeinf[uiienben ~a{torert" raenbet ~'ia3 ~3e~c{ctiie~: gegen &artig'~ ~n~c~auun~, bag bet ~erfct)iebene ~Seginn bet Ram~ial-t~/itig~eit im \| 5gemperaturbi~eren~en 8u~ui~)reiben M. \| Salt, bag bu~ ba~ ~8oranei~en be~ ~tgenroa4~tume~ in ben o~eren \| hie {~om be~ \| d~ 5~r/iger g[eic~en ~ibetRcmbe~ a~terim fei; hie {~o~ge id bet D/itere \|162 be~ unteren \| teiie~; au~) bet metteren ~;Dorte ghartt~'~, ba~ bet ~eiftelIung bet ftaffere 8uraetc~ art bet ~Scffi~ bet erD}teu ~obertt~attg~ett ~u}u{~reiben iei, roiberf~oric~t~ractr~. ~inen &aupttei~ be~ ~u~e~ l~i~be, bie ~p/it~o[sbi[bung. II. {geiL r ift nu~ ~u ~eg~figen, bag auc~ ~ m a r ~ hie ~e~ei&ungen ~rfi~, ja~-- unb Qer~N)oI8 ober ga~ hie Qa~tig'~'c~en 11nter~iebe {~fi~jd)r~, ~o[~, \| unb g~erbft~o[~ ~alIen I/i~t. ~ ent~pfi/~t nic~t br ~ir~i~eit; benn hie {~rii~ia~bt~bun~ fiilIt in {~rii~ia~r unb ~ommer, hie QerbrtD~$13t~bung fetlIt Stoat in hie &erl3ftferien bet &erren {~or~er, ni~t a~er in ben Rdenber~)erI~t, bet ~ier dIein ma~geI~enb ~ein mug ~a~ einer ~ritiSt~en ~dpred)ung bet a~t g$gpot~e~en, roei~e 5i~ jel~t iige~: hie @ntrte~ung ~aon {~rii~)-- unb ~p/it~o[~ aufgdteIIt rourben, geI~t \| tiger 8u~ ~egffmbung einer neunten. ~ie \| ift nac~ .~nfi~t be~ ~e~fdfer~ eine ~u~ bert ~ruc~rd~ ~u~fiffSuffi~renbe 8r~d~einung, roobei f~[ec~te ~rn/i~rtmg, ~angd ~ort \| niebere 5gem~oeratur hie {Rei~laa~eit t~eeintr/i~ti~en ober gan~ rmi~egen. ~nt~goeibenb ~ii~:b~e IBrgge bet \| ift be~ tlmftanb, bag Bir {~[ii~oenroa~tum~una~me ni~t inMge griSge~e~ ~tifimi[ation~t~tig~eit be~ R~one, ~onbern infoIge bet g~tigeren ~ruc~: roir~ung ~or fid~ gent. ~er gefteigerten ~ct#o~tttm~energie roirtt im {~r'a~ia~re ein ge[tdgerter ~ruc{ entgegen. ~@ \| irt uuala~angig son bet {Ringlarette; Bet grSgerer ~a~o~tumgenergie ent~/i[t in bet 9tegd Des ~m/t[ere {Ring ba~ gr/Sgere \| mi~tenb get gerirtger ~itterariI~e ~eri~te. 321 ~a/~gtumgenergtr be~ Iardtere {Ring md)r ~!~itt)o[~ entD~i{t. ~ie ~[tte.~ung @nbe ~uts ~n~ang ~ugu.rt Iaeein~Iu~t eben~alI~ bie ~oiit~oI~biIbung. ~araug effI&ren [i/~ ~er[g0ieben~eiten in bet te~ni~/~en ~ua[ifftt beg g.~o[seg in ben ~eri~iebenen ~u6)~gegieten bet ~ii~re. @ntnabetung bur~ ~n~etetenfrag ~at eine geringere ~u~bi[bung ~on ~l~it[)o[~ 8n~ ~o[ge. ~@renb ~ruffrei~ Iaig~er aIg hie 11ria~e ~on &a~t~oISbilbtmg ,,{Rot, ~o[~=5~ru~one" edannt murbe, ~erallgemeinert \| biden Ne~ielIen ~alI, inhere er die Gp/ifl)~I~lailbung auf ~irhmg be~ ~ru&ei~e~ ~ur gOefftdIung ber (S3[etd)gemid0tg[agegeim g{u~Mu beg ~3aume~ ~ufii/~fi~rt. ~it \| lit \| bet gnfi@, bag bag l~efte Riefer@o[~ bern Piteh-Pine-&o[se (Pinus australis ober palustris) gIeid~{ommenober bagMge iogar fibertre[ien ~oII. ~r ~Rateria[ ~on Pinus palustris mag bern un{erer ~ r e gMa'~ommen, ager beg meirteng ~u un~ ge-tbra~le I~egere ~aterid iFt im {!aesiftI~Oen(Beroi~te, in g~arte, in &a~ao gd)dt unb bamit in ben ~igenia~@en fiIaerIegen, roei~)e {eine ~ermen-bung bebingen. ~fir ~orf~)e: unb :getter aN bern Negiete bet gl~Ian~enp~)z)fiol!ogie, bet ~o[~meghmbe, beg ~aIbMueg unb bet ~orrtI~enut~ung ift ba~ ~3u~j ~on gr@ter ~ebeutung; bir llrI)eger bet ~on \| angegri~enen ~Dofieen roerben alSer mit bern ~rinsi~ bet ~gnorierung be~ ~/~marS= ~[~)en~3u~e~ nut ben ~ulammenI~ru~ iOrer eigenen ~eorieen eingefteDn. ~Rr. 43. ~ar[tliatanifdlr ~qer~lintb. fRa~Ometg bet ~ea@engmerten unb ~u {a~fi}enben u r m f i ~ i g e n \| ~ t u m e uttb ~3eftanbe im RiJnigret~ ~reugen. I. ~ro~in8 ~eripreugen. ~ i t 33 glaI~iIbuugen. #erauggegeben auf ~eran[agung be~ ~ini[ierg far ganbmirtf~aft, ~om~iuen unb ~or[ten. ~3erlin, ~ebrfiber ~3ornt~/iger. 1900. 94 ~. ~)ag laorliegenbe, ~on ~rofegor Dr. gonmenl} in ~an~ig BearBdtete ,~or(iIaotanif/~e ~ertlau/~" granbet fig auf ~eoM~tungen, rod/~e bet ~erfager Mt me~r benn 10 ~@ren gemacl)t ~at unb fielIt eine ~n-ventarffierung bemertengmerter urmfiaS[iger -- a[io ni~t tlanffli~ an; geMu~er -- ~tr/iuct)elc, ~3~umeunb ~3e[iiinbein bet ~ro~in~ ~e(~!areu[3en b~tr, attf melee burd~ bag ~3a~[ein aufmed[am gema~t unb ~u beren ~dju} unb ~r0a[tung baburc~ I~eigetragen me,ben {oII. I~ finb drier, ieitg laefonberg a[te tmb m~ic~tige~iume, auF meId)e bte gufmergamtMt ge[entt roirb unb mel~)e 8urn gel[ abbiIbli/~ bargefidlt firth, anbererleitg 5oi~e won abno~mem ~U~g, enbli~ ~e[tenere @em/i~[e; won erfieren [inb Ne~ielI fiaffe ~id}en unb gtnben ~u erm@nen, ~on her 8meiten 322 gitterari[@ ~e~:i~te. (~rmat~e ,,~rodgdnige" ~ig)en, ~ud3en, Rie~ern, ~og. RnolIen: unb ~3eut-~iefem, :grauedig)te, yon bet ~et~ten6Jntvpe ~iSe, ~Iaeere, {g)mebiia3e ~e~l~eere. ~Iaen{o roirb auf ein~e[ne ~eNinbe unb ~a[bpa~tieen ~in-gemielen, melee ~on be~ &anb beg ~Nen%~en hog) menig Be~ii~rt ben g~arafter bet ll~mfi/~figMt an fia5 tragen. -- ~3elonberegu~med~am~eit ~)at bet ~e~fager be~ ~ibe 8ugemenbet, hie nod} an t~erfg)iebenen\| lid) in ~Mnerer unb gr@erer ~aD[ gnbet, beren ~erBreitung aBe~ ~r@er eine rid bebeutenbere war, mie einer~eitg ftade gagu@~4e in ~ooren, anbe~er~eitg hie ~3enennung verf~iebene~~aiborte, in benen'bie ~ibe iegt ~er.~d~munben if, nad)mei~en. ~ine ~bgebi[bete ~i~e bdiI~t 1,56 m llm~ fang unb 10 ra g)@e, allo [e~r re{pet~tnbIe~iment'ionen[ ~ag ~3e~treBenbeg ~e~:~age~, ~o[g)e ~aturbenfm/ile~ in ~o~t nnb ~i[b feft~u~a[ten, ebeMo abet au~ ~u beren mirEi~en ~r~a[tun~ l~ei-~utragen, ift gemig ~e~r [Sb[id), ~at barum aug) lInterffii~ung t)@ern 9 gelunben unb eg ift mo[)[ 8u [)o~en unb ~u mfin~daen,bag {i~)nEg)e ~eft~ebungen aug) anberen Crtg ftat/finben. ~g mSge bei bMer gCe-iegen~eit au~ ba~ im gnfi~ag beg eibgenSffi~d~en~epartementg beg ~nnern t)e~auggege{~ene ,,~auma[bum be~ \| ~) ~ingemie{en Mn, bag @n~Iig)e s ~effo[genb 25 bet fg)i~nfien unb g~@ten, besm. Dittorifd} inte~Nanten ~3iiume be~ \| aul grogen Zafdn /aietet unb al{o gIei~e ~me~e ~effo~gt. ~ie gugfiattung beg mit 22 N65ilbtmgen gesierten ~3tig)~eing i}l eine ~e~ gute, Mn {~m:mat ein {ii~ ben Zoudtten bequemeg. Dr. ~iil: ft. ~V. 43. ~nnblmO ~e~ ~eul~Oen ~finen6mte~. ~m ~u~trag be~ ~g~. ~eu~. ~tni~'teriumg bet 5~engig)en ~rbeiten unb unter ~ttroidung ~on Dr. ~oD. g~romeit, ~I~iftent am 6ot. ~nftitut unb 6tarten in R~nigg-berg, g}au~ ~3oc~, {Regte~unflg,unb ~offtrat in ~6nig~Berg, Dr. N[~ f~eb ,~ent~{g), ganbeggeologe unb ~rofegor in ~er[in, Demuggegeben ~aon g}aul (~e~)a~bt, ~Regierung~ unb ~aurat in R/Jni~gl~erg. -92~it 445 in ben %egt gebmc~ten gbBi~btmgen. ~erlin, ~edagggu~, ~)anbhmg ~au~ ~avet) 1900. 656 ~. ge5. 28 ./Z. ~in mit beut~g)em {~[eig unb beuffg)er gCrfinbE~oMt 15eargdteteg ~ e d [iegt in bern ttattE~en ~anbe ~or ung! ~ie bey ~inMtung ~u entneDmen, ift hie Nnregung Su~ &emuggage begMlaen~on D@ere~ \| auggegangen, unb nut mit beren llntert:tfil~ungmar ro@[ aua~ hie g~tinb~ 1) ~e~'g[. ~r[tt~. ~r 1897, \| 386. ~3ittermci{g0e ~3e~:id)te. 323 ~ic~e ~Sem:~eitung, bie reic~e ~u~fiattung be~ ~u~e~ m/~g[kg ~em ~erf., bern Mb[t eine ~angiii~jfigr ~/itigfeit im ~iinenbau ~ur \| [te~t, ge.iang e~ in ben brei im ~Eitd benannten 8erren b~ei'~pesidi[ten fiir bie yon ibnen ~u bearbeitenben ~/bfg)nitte: ~ie ~eo~ogie bey 2)finen, hie ~finenf~om unb hie .~uffor[ttmg bet ~finen -- 8u ftnben, e~ murbe bern Mben hie ~ereifung bet beutf~en ~orb; unb ~ftfedfiften burg) amt~i~)e,,t P/tqtrctg e~:m6gli~t unb ipebielI bet S~erau~geber bur4~ ~tberroeifung eine~ ~teg~ertreter~ enflaftet, um [ir gans bet ~ead)eitung be~ ~ede~ fomie bet ~O/ifig~eit [fir bie ~u~[tetIung be~ ~)finenbaue~ in ~gnri~ mibmen ~u ~nnen. ~ben~o murben ~dne ~ittd ffir relate ~u~[tattung be~ ~er.te~ nit 9.Igbi[btmgen gefpa~t -- me~r a~ 50 2bbiibungen ~on ~finenp[Iansen, hie bi~)er no~ nic~t ~u~ IDafftelIung gdommen maren, murben auf \| Mien angefertigt, unb augerbem meift bag ~u4 eine grofie 8a~[ fd)r ic~/~r~ au~geffi~rter ~ollbiIbe~ nacl) p~otograp~i~/~en gufna~men beg ~e~cf. rtn~, Ni[ber, hie ~ura ~Se~:t't/tnbnig beg ~egte~ in t)ot)em @rabe beit~agen unb eine ~ierbe be~ ~3uc~e~ [inb, !8on ben 7 ~rai~nitten, in mek~e fi/~ ba~ ~u~ gIiebert, I~efagt lid3 bet e~:[te son Dr. ~enl}[d) 5eavbeitete mit bet @eologie bet ~finen. ~a~ einer ~tnIeitung, in me[a~e~: ~3egfif~ unb ~Serbreitung bet ~finen e~/5~tert merben, roi~:b ~uer[t bag ~ a t e ~ i n l bet ~)fmen bdproc~en, hie gCe[teine beg ~[t= tmb ~Rorb{eebec~en~, beren ~e~mitterung unb ban barau~ ~er~orge~enbe ~aterinl, hie (~dSge be~: \| hie ~ineralien be~ ~finen~anbe~ unb begen tmtergeorbnete unb ~uf~tllige ~3ertcmbtd[e. ,~m roeitetn roirb bann hie ~eftcdtung bet ~finen, role fie unter bern ~in-[Iug ,on gginb unb ~dIen erfo[gt, erSrtert: hie ~i[bung won \| m~iIIen, ~e~rungen, &affen, won ~8orbfinen unb ~cmberbfinen unb hie mannigfad)en @r[goeinungen 1Set beren ~3i[bung -- hie [ogertannten ~inb~ fi~0peImm:ten, bet gef~t~did}e ~fiebfanb, hie \| in ben ~)finen gnben i~re @d[/i~cung, eben~o ~e~gOiebene au{falIenbe ~t~u~turert mtb gtegenergOeinungen. :Die ~e~p~:ed3ungbet Nebingungen be~ ~B c~c~ tumg bet ~finen, be~ ~inguge~, ben ~aterini, ~inb- tmb Rfiftenfifl)tung, Riima unb ~gartsenbeffe auf ba~Mbe firae,, {omie berett rtatt~rii~e~ ~er: get)en inMge {oiler ~inmirhmgen biibet ben \| biefe~ gb[~)nitte~. ~er 2. grafc~nitt, yon ~. 13e~:I)a~bt, beDanbeIt Rfiftenftr/Smungen tmb bag ~anbe~:n bet ~finen, befpfia3t ~uefft hie ~3emegung be~ ~anbe~ an bet Rfi[te aIg ~o[ge bet 2~emtoeratur,, gibe: unb ~inb~ t'tr6mungen unb ~obann ba~ medmfirbige ~cmbe~:n bet ~?finen in bet {Ri~tung beg Derr~enben ~inbe~, verIang~ctmt bur~ hie ~iffung 8eit-roeilig entgegen me~enbe~: gginbe, f/~ilbe~:tbie ~ntfte~ung bet ~turgbiinen, ba~ flbermeOen ton ~dbMt/tnben, hie gan~ alIm~tO[i~) tiefer unb tiefer - - 3~4 ~itterari~0e ~3eri@e. einge~anbet roerben, nod5 ~ange fort~egefierenb, aSer enb~i~ boc~ aSf'ted~enb; ba~ s mcn~ct)tic~er ~@nfteitten, auf benen hie ~3em@ner in ~(i~)er ~tn~ng[iaSteit bern eattbe {o iange gro} 5ieten, ct~ irgenb mSg-iic~, 5i~ enb[ict) bet in die {R~iume bringenbe feine \| ~um ~anbem 8roingt. ~ t ~/5rfer finb auf ~o[4r ~eife cmf bet Rurt{d~e~ ~e~vung ~er~c~munben 5esm. gemanbert. ~ie &oI~Bautert merbett a@e5ro&en unb an anberer [i~erer \| mieber mqgebau,; na~ [angen ~s@ren, menn hie ~Dfinen fiber hie f~@eren ~@nftatten geroanbert, ~omnten ienMt~ berMSen hie ma~g~en ffCrunbIxmtert etma bet Rifle mteber ~um ~or-~ein, e~enfo wie hie Nei'te verf~fitteter ~atbungert. ~itten medmfirbigen gnbli~ gem@rt hie ~blfi[bung ~e~ auf bet \| ~u ~age tretenbett au~gero@ten ~ird@ofe~ beg ~orfe~ ~[t--~Ribben, fiber bert hie ~)fine ~in-- weggegangen! ~e naa3 S2rt[ic~Mt ~etr/igt ba~ {~m:fi~reiten bet ~fme j~rIir 4--8 m, be/~ audt me~r: iel~ft 10, jet 17 m finb ~.onrtatiert ram:ben. ~3donbere~ ~nterege bietet be,: 3. gb[~)nitt ,,~finen~Iora" ~ort Dr. gbromeit bern ~3otani~er. ~er ~erf. ~@[bert ~uer~'t ben g~ctra~ter bet 5~finen~eflelation, i~re Nn~agung an bie eigentfim~i~en ~er~/fltnige beg ~fmen, beren augerorbent[idoe ~rm/irmung unb ra[d~e ~Ifa~a~[ung, beren ~ai~eg unb fiefe~ gu~troffnen, @nli~ rote in ~fi[ien unb \| bert ftei[ett unb Iaemeg[i~en \| hie ftetige ggir~ung be~ ~inbeg. ~ie gn!actgung an ~o[~e mif3[i~e ~er~/i[tniite gieSt fic~ ~u er-{ennen in f~)mden, bi~en, oft etma~ ffeif4igen ~3~Sttern, in [eberattige~ ~onfif• bi~te~ ~e~aarung, ma~artigen fIraer~figen berMI~en, im @in-rollen bet ~3[attr/inber ~ur ~erminberung be~ ~I~erga~e; in rtiebfigert \| unb \| am ~3oben ~inIiegenben ~ften; in tidgeDnben ~ur~e[n, in triedOenbe gtu~i~ufer tret~enben ~ur~e[[tSc~en (~fir ~eftigung bet 5Dfinen ~oon Mmtbe~er ~ebeutung!). gud0 hie ~aI~e ~ntmi/Mung be~ einj@rigen q3~lansen im {~fi@a~r, beren 8eitige \| i~r gl5~'tevSm im ~ei~en \| unb ~eimen bet \| 5eveit~ im ~)e~cIfft i~'t vott ~ebeutung. ~e~f. gliebert iobann bie ~3itnengora in bie ~Segefation be~ ~anb, ftranbe~ mit nut menigen g}gansen, bee weigen ~ber ~anber,~fine mit egenfalI~ no~ geringer ~Segetation }~oeCftfd)e~:\| mit ~ur~e[, au~[gufern, unb enbIi/~ bet grauen, fdfliegenben ~fine mit :~er~i[tni~-m@ig ret~er ~ [ o r ~ , hie nun eing@enbe ~3e{tared)ung ftnbet; ~@[reia~e gl)bilbungen, ~um gr@en ~gei~~rigina[e, finb bielem ~I~i~nilt I~eigegeben. 5~ie NeI>re/~ung bet ~ur ~)finenI~inbung bienenben ~uItuWgan~en -- be~ ~flnengraM: unb ~o~gero~t@e - - hi,bet ben ~ [ u g bieie~ ~II~i~nitt~. Set IV. gtb~nitt, ~om ~e~:f. M~ft ~ear~eitet, BeNri~t ~me~ unb ~itteratiI~e ~e~:i~te. 3~5 @ef~ic~te be~ ~iinenbaue~. ~Iuf~a~e be~feI~en i~L bur~ ~e~tle~un~ bet ~Siinen hie ~iit'ie ~u ~m:n, ba~ ~anb - - ~/i~ber, ~dber, ~o~n(i/itten - - ~e~en ben mcmbernben ~anb ~u fc~iil~en~ hie $$afen unb {~uf3~iufe often ~u ~alten; biefe ~uf~age routbe ~roar, rote 9~ien au~ bent ~ctD:e 1583 5emeiien, i~on {ti~eitig mc~annt, a~et et[t in bern 18. ~af)r~un~ert ftnben fi~ hie 9.Inf/inge 8u einet {~ert~egung bet ~)iinen burc~ ~ta~: Vgan~ungen, ~ufti~tun~ ~on 8iiunen u. bergL ~netgiic~er mutbe bide gt)/itigreit ~u @nbe be~ 18. ~cd)t~)unbert~ an bet Ruriic~en ~e~tung au~= genommen, bur~ hie ~r Rriege in bebauerii~er ~eife untet= broc~en, urn ~cmn D/itet roieber eifriget fietriegen ~u wetben; in~beionbete {anb and) hie 9.~uffodtung eine ftet~ fteigenbe ~nmenbung. @tgenen~e-amten, ~3fmenini~e~toren, untet i~nen ~rmenctuffebern, iFt hie Rgetroct~)un~ bet ~ftnen, hie geitun~ bet 8u beten ~eftigun~ ntitigen ~tbeiten an~et-trauL ~:ei4Iic~e~ittd mutben iiit Iegtete gem/i~tt,, hie im ~an~e bet 8dt 9eictmmdten gtfabrungen entiprecbenb vermerte~, unb ic~/Sne ~rDIge finb bereit~ etsie~t mo~ben. ~ie ~eg~egung ~e~ ~ftnen{anbe~ -- ~on .$. (~e~)atbt ira V. 9~gic~nitt beiprocl.3en -- tann mit bctuetnbem ~rfoI~ nut butch eine Iebenbe ~3ec~unq ge~e0en, bn abet bet Ret~ bemeflIic~e \| ba~ 9..Iu{-~ommen einer, fSe~etcttion ~er.~inbetn mu~, io etfg)eint e~ notroenbi~, bie ~emegungen be~ \| (o Ian~e im 8aura ~u balten, bi~ hie gu[tut~ ~cmsen yon bet ~ug~anbftelle ~efit~ ergriffen bergen -- unb bie~ ge-ic~iet~t bm:r hie tote ~ebec~ung. ~iefei~e ift entmeber dne fteI~enbe, ~uta~ auftea)t geftelIte g, egenft~inbe, ~ie g~eic~fam ~anbe gilbert, ober dne lie~enbe. ~I~ fte~)enbe ~ec~ung mntben ~uetft ~teIen-- unb \| benu~t, bann F l e ~ t s a u n e ~etia~iebenet Ronfttu~tion, votmiegenb au~ Riefetnreifig; mefent~tcb nieb~iger, a~ bieie 8~tune, abet bern 8mec~ and} no4 geniJgenb, ift bct~ nut etma %3 m ~o~e ~eftet~ ctu~ ~iefetntett'ig, {Ro~t, &eibdraut, fe[bft \| (\| mtt meic~em hie ~Ittc~e in ~nabraten ~on 4 m \| ft~etsogen mitb. - - 9.Ii~ Iie g en b e ~obenbec~e bient Rielenfftrau6;, ~eetang, &eibe~raut, ba~ mit \| befct~roett rottb. 9.II~ s ~8obenbe(~ung i~esielI bet ~orbiine, auf rodc~et etne ~uffoffiung nig;t miSgIic~ tft, btenen \| &eIrrt ober \| gra~, Ammophfla arenari~ unb \| Elymus arenarius, ~owie eini~e minbet roig)ti~e ~rten; bie~dben entmi/tefn lid) um ~o [t/ir~et, ie ~efttqer bet \| tit, ia3ro/id)en hie ~idun~ be~ ~tnbe~, ~a~ten ben ~anb Smti~en ben &a~men felt. ~eren 9~n~u@t etfoI~t buv~ ~gansun~ in en~em ~erbanb, unb Store: a~ RIemmp~cm~un~ mit &life eine~ 326 ~itterari~d)e ~er@te. ~r/ifti~en \| ober ei~e~ \| tei~ a~ ~er~fipfIan~ung, m~t ~e[[erem ~rfo~g no~ im ~rii~j@r (~ai). 5~a~ n6tige ~ffan~enmateria~ wirb tei[~ att~ be~eit~ gut be~toSten ~c~en, tei[~ in fogenannten ~anb~ gra~@rten get~mmem ggie ~Ibf~nitt 3 far ben ~3otani~er, ~o ~at g~bl/~nitt VI. -- ~ttf, forl'tung bet ~ n e n , yon ~orftrat ~3o~ -- far ben ~ort'tmann fiber= miegenbeg ~nterege. ~m ein[eitenben WetI mirb angegeben, bag bie RilF/en bet ~Fi[r m@~ in fra~eren ~aI)r~unberten alIent~a[ben bema[bet gemefen, mie ja nua~ iet3t no/~ bet ~a[b ~idfa~) ang liter beg ~eere~ ~erantritt; art bet ~id ftarmif(oeren 91orb[ee ift bie6 nirgenbg bet Jag, atff ben Ftorbiee,,~n[dn feI)[t n@e~tt ieber ~3aummua~g. eg merben {o, bantt bie fri~eren, nut tet[metfe ~)on ~rfo[g gegleiteten gufforFtung~, ~)er[ttd)e, ~u gn~ang beg 19. ~@rDunbertg auf bet ~rild)en unb ~uri[d)en ~@rung au~gdfit)rt,.[omie hie tr~eren RuIturverf@ren, bei bench hie \| eine gro(3e ~olIe ipidten, beNro~en unb [obann bern ber~dtigen Nufforfttmg~erf@ren eing@nbe ~3elprec~ung gemibmet. ~er Riiftenmalb iFt in jeber g)infi/Ot a[~ \| ~u betrad0ten, jebe aug i~m ~tt entne~menbe ~ut3ung iFi nut gteben~a/~e unb hie ~e~ren bet ~orftmirtldjaft finben nut be~cI)r/intte~.Inmenbuttg ant ben R@enma[b, begen ~roec~ alIein ~effung beg ~3obeng tmb ~r0a[tung beg~elben ir~ bauernb befeFiigtem ~uftanb ift. ~r MI bern b@inter liegenben ~anbr ~ t t ~ gegen ~erlanbung, gegen hie (i/inbigen rauOen \| geBert tmb babur~ auc~ in pt)9[ifa[i~er ~3eCeDung ganFiig roiffen. ~einbe be~ ~a[beg, bet ~uf~orFtung finb hie \| unb \| burd) i~re peitI~enbe unb reibenbe ~idung, in~befonbere a6er au~ no/~ bur/~ hie ~arfen \| unb enbIi~) hie ~igtlrt)FtatIe, melee f~e mit fia~ fa~ren unb bttr~ me[/~e ~meige, ~abeht tmb ~3[titter, Rnofpett be, f~tibigt nab get6tet merben, fpeCelI ntq bet ~inbMte beg Naume~ ~ur~e, gebnmgene ~3aumformen, etnMtige ~3eaFtung gab hie ~oIgen. ~I[~ @oI~nrten fiir hie ~Iuffodiung bienten unb bienen ingbefonbere Riefer, ~3ide unb f/it feua~tere \| hie \| ~u il)nen gefelIt Fi~ Mt 1871 hie ~ergfider (P. mont. var. uncinata), hie ~eigfk~te (Picea alba), hie ~i/~tr (P. exeelsa), hie \| (P. austriaea) unb enb~ Ii~ P. rigida. (~enfigfamMt in i~ren ~3obenanfprfi/Oen, m@ii~Fte llnempfinb[i6)te[t gegen hie oben bem@rten ~ct)~btgungen bur~ ~tnbe, ~turmff/inbigfeit unb bie ~@igMt fi~ ge[d)[ogen ~u ~a[ten unb ben ~3oben burd0 s unb ~abdabfa~I ~u be[[ern, ba~ Finb hie ~igen[d)afte~b hie ~on ben an, ~u%nenbert g)oI~ar/en ~erlangt roerben. ~ielen 9Xn[pr~/~en gentigt in ~olIftem ~age auf ~@em, troSnen gitterari{~e ~erid}te. 3~7 ~d~nbe hie ~ e~g~ie~e~:, ctu~ ga~em, {euc~ten hie ~/~roa~e~Ie; i~nert Mgen bie ~d}on mdent~i4 emp~inblic~e~e gem. Rie~er unb ~ i ~ e , ben ~d}Iu~ bilben bie beiben ~i4ten. ~a~ hie Ru~tu~met~oben anIMangt, D ~at man hie ~aat au~ nn~diegenbem @nmbe ver~a{~ert, hie ~ganbung g~[t n~ 91egeI. ~iir bie gie~ern{u~turen, benen bie erfte ~RolIe 8u~/illt, gdten ~oIgenbe @~unb~it~e: ~enu~ung bet nattMi~en ~obenIoffer~eit, e~ent, tiele ~obenlot~e~un~ im Serbft, m/Sg~id}f~ enger ~erbanb, ~eitige~ ~gansert im ~rii~ja~r, s~er~ roenbung {r~iftigen ~gangmaterideg, {orgf/iItige 9lad}begerung, ~d}ul~ gegen trdbenben \| unb room/Jg[id} ~)iingung be~ ~Iart~toHi!~e mit ~umu~dtigem gut ~erfet~ten ~e~m. ~ie ~Ianbung Mbft e~Ioigt ~miid}ert {Rd~ig-- ober {Ro~rbefte/~ am beften im ~rii~ia~r burd} R[emrnpgansung mit ljg~rigen Riefern ober 2ig~rigen ~erg~Mern in bie mo~i~o~bereiteten, e~ent, gebiingte~:g}f[au~pISl~e in 1 m ~e~banb, rooraei au~ ieben ~3~a~ ~ g}~Ian~en gdet~t me,ben. ~)ie g3~Ian~en me,ben teil~ ~om ~eftlanb be~ogen, neuerbingg aud} in ge~d}~t ge~egenen ~gan~g~irten auf bet ~iine Mbft er~ogert. ~ag bie Roften eine~ Ioid}en NuIttt~: ~3e[to/~ung, ~)iingung, ~Ian~ung ~e~ ~ e [inb .unb ~ein miigen, Ieud}tet ein: fie betragen im ~ittel etma 1~00 d/ ~o~o &e~tar. ~3erf. befpdd}t im roeitem nod} hie roenig giinftigen 9Ju~fid}ten fitr 9.Iu~orftungen an ben 9lorbieeNften, hie rid} ~urt/i~ft nod} ira 91abmert bee~ ~3eriud}e~ bemegen, fomie enbiid} hie \| be~ ~ii[ienmdbe~, unte~ benert au~alIenberroei~e and)Liparis dispar eine ~.RoIIe~piett, ~len, ~ir~en, ~i/~tert unb su[e~t Mbft Riefe~ unb ~erg~iefe~ ~ab~ f~e~enb, guf bet ~u~tfd}en 91ebrung gebfi~t ba~u ba~ ~Id}milb, ba~ [i~ auf berMbert cngef{ebdt unb au~ etma 30 ~ttit{ vemebrt ~at unb bu~d} ~e~beigen unb ~d}~i[en in ben ~oftipieligen 9.Iu~o~ftungen ftellenmeife fd}me~en ~d}aben anrid}tet -- gIeid}mo~ abet tm .3nte~ege be~ @r~dtung biele~ intere[~anten ~i~bart in iebe~ ~ei.fe ge~egt roi~b. ~)e~ VII. gb{d}nitt ,\| ~on ~. @e~a~:bt {ii~t au~, bag bie ~3orbiinert unb helen lXnter~dttmg fti~ bert Riiften, id)u~ nid}t au~reid}en, bag ie had} Sage be~ ~tranbe~, {Rid}tung be~ gginbe unb be~ ~ilftenft~/~mungen 9Agb~iid}e er~oIgen, bie bann bag ~anb gef~t~ben. ,~n I)o~em @tab interegant firth bte beg~dIfigert ~d}i/~[a[e be~ o[t~rieNd}en .~nM ~angerrog, burd) gbrailbungen au~ ben ~a~ren 1780, 1829, 1843, 1866 unb 1891 e~l~iute~t unb geigenb, in todd}era ~tRag be~ ~ortbe[ianb bet ~nM bu~d} fo~tma~ertbe 9.Ibbriid}e get~i~rbet rourbe. ~n eingeDnber ggeije roirb unter ~etgabe ~ie[e~ 92bbi~bungen gesetgt, roie burd} llferid}ut~roer~e ~e~Id}iebenrte~: Ronrinfftiort -- g3fa~[, 328 ~itterarilC~e ~3eri~te. unb \| \| ~3~[d)ung~p~Iaftet,~elle,tbred)er u. bergL - bet n/Jfige \| angeftrebt tmb, roenn and) mit grogen Rofien, r with. ~tber and) hie 11let bet gribgern &~e, fo ~pe~ielI be~ fri{d~en unb ~uri~d)en g)affe~, bebfiden \| gegert ~ellen~ag unb ~i~(d)iebungen, bet ~ier aufser burd) dnfad)ete ~Su~nen burd) ~agetgem/i4~e, ~ganSungen mit ~Ro~r, ~infen, \| unb am 11fer mit ~eiben er~Mt with. - bud) ftir ben fetrtet \| I)ietet ba~ umfangreid)e ~ e d ~nter= eg,e, in boppe[tem ~age mirb bie~ bet ~aII far jeben {ein, bet in bet ~@e be~ ~.Reere~ Mnen ~@nfi~ ~at ober bern e~ ~ergOrmt ift, 8eiten-melee efma am ~eet ~on ben ~@en be~ ~Imte~ aug~u~ttOen: er mitb hie mangoetId @r[d)einungen, hie i~m bott in ~eftdt yon llferbauten, ~)fmenSefdtigtmgen unb ~ufforfttmgen entgegentteten, .,it botopdtem ~nter= ege unb mit ~erft/inbni~ ffir i~re ~3ebeutung betrad)ten, llnb be~a[b mi~d)te id) bn~ gan~ vot~iig[id) au~geftattete ~er~ auf~ ~efte empfe~ien, Bate i~m barum aud) bMe eing@enbere ~3e[pred)ung gemibmet. D r . ~arft. ~r. 44. ~or[i[/ntifiij~e tl~it/eilungen nu~ ~i~iirttemlierg [iir bn~ ~aljr 1897. \| g)evau~gege~en yon bet ~g[. ~orftbive~tion. 16. ~@rgang. ~ruc~ unb ~}er[ag ~on $0~. ~d)eu~e~e 1899. 100 ~eiter~ ~unrt. ,~n einev g~@en ~n~aO~ son ~nBelIen unb ttBerfid)ten 9ielat hie ,~orffbirdfion dn an~c~au~id)e~ ~i[b von bet 5g0/itigMt unb ben ~r-gelbni~en bet ~iirttembergii@en {~orft~etrodtung. ~ie mitgetei~ten 8a~ert finb angegeben filr iebe~ {Re~ier, johann far iebe~ ~offtamt unb ~tm \| ieben ~IggOniite~ 8u~ammen~efielIt na4 5 ~dbgebieten 0Inter= Ianb, ~.I~Ib\| ~agft~esi~ unb ~e~:f4roa~en) unb had) 2 &aul~t, gruppen ,,gaul)~)oI~geBiete, ~R~be~Do[Negiete", hie in i~te~ ~ummierung harm hie 8@~en {iit ba~ gartSe ~anb nad)mei~en. Bur ~erg~ei~urt~ finb bann ftet~ hie ent[pred)enben3a~l~en bet vorau~gegangenen 4 ,~@re fieige~figt. galSe[[e I entDii[t hie {tberj'i@ filer hie ~/id)e be~ in bet ~er-mdlung bet {Reviedimtet fieDnben \| unb meift nac~ 189 689 ha ertrag~f@ige ~I/i~e 5269 , hi@ ettrag~f@ige ~[/i~e 194958 ha @damtg/id)e. ~a hie ~@[ bet ~or[t/imter 16, bet {Re~iet~imter 140 bett/igt, [o ~itterafiI~e ~efic~te. 329 ttifft auf ein ~orftamt 12185 ha, au,~ ein {Re~ieramt 1392 ha bttrc~= i~nitflig)e }~ia3e. ~)ie ~3ergM~un~ mit bert votau~eDnbert ~at~[ert ~e~gt eine ftetige ~teigerung bet \| urtb laetnt~ erftete in ben iet~tert 5 ~a~ert 456 ha. a 5 e ~~e II ~ giebt bie ~tber~ig)t tibet ba~ ~tgebni~ bet ~oI~/illurtgert in ben \| ~ mutbe im ~d)r 1897 genu~t ~et~)o~ an &auptnu}ung 752252 fro. pro &dtar 4.05 fm ,, ~mi~g)enmt}ung 158336 . . . 0,85 ,, in ~a. 910 588 fm . . 4,90 fm irt~L ~Ret~ig 5,98 fm ~ii~ bie gaugDisge5iete bett~igt bte 9tut~urtg 4,02 tefp. 5,41 im . . 92abdD~gebiete . ,, . 5,41 ,, 6,31 . 5Der ff~elamirtul~DigtnMI ~iir ~erb~o~ 5e~i~ert fktj attf 54pgt., unb be-triigt im ~aubOorsge~{et 26,9, in, aabdOoINebiet 65,5!~gt., hie {traet~ ~egen~eit be~ 928beI~oi~e~ a[~ ~Ru~)o~ bdeug)tertb. gabel~e III, ~;Ibetfi/~t fiber bert ~tanb bet & o I ~ a u e f l i S ~ n e ~eigt, ba~ Ie!~tete in bert 5 ~a~ren 1893--1897 ~a[t urtvetiinbett ge-b~ieben finb - - hie ~teigentng be~iffe~t nut roenige ~3~enrtige. ~ e t ~gabe[~e IV: ~ac~roeifun9 bet butg)[g)nitflig)ert 9Ittfftteig)~, efl/~le au~ ein~einen \| ift 8u en/ne~men, bag bie ~?urd~g)nitt~-eff/ge im ~a~: 1897 betntgea ftit ~id)en,gtrtt~oI~ 34,97 ~ pro {~dtmetet - - in bert Ie~lert 5 ~a~rert [aft un,etartbett; fiit 9labe[ftamm~o[~ 18,26 d / p r o {~ertmetev - - Ieit 1893 (mit 15,o3 ~) in ftetigem ~teigert, fat ~ug)en.-\| urtb ~tiige[D[~ ~o {Raummetet 6,84 ~ -- eht gefinge~ {Rac~gang, ~iit 9labd--, \| unb ~tfigei~oI~ pro 9taummete~ 5,63 .//r - - eirt geringe~ \| {~fi~ ~ig)ert,IN[anginbe - - hie be~fafltigert ~a~[en bfitften angefig)t~ bet btennenbert \| vart ~nterefie Mn! - - Bettugen hie ~tet~e 9to gentnet ~ort 1 8 9 3 - - 1 8 9 7 : 4 , 8 8 ./r 4,80 ./$, 4,99 MZ, 4,93 MI, 4,56 ./#. gabeg~e V ertt~[t hie 928d~meiNng fiber hie au~geffi~tert Ru[turert. ~te ~etgt ba~ l~tSermieger~ bet ~f~artSung gegerttibe~ bet ~aat, be~ 9~abe[, ~o[~e~ gegerttibet bern ~aub~d~e ilt ~riigrtantet ~et[e. ~3ie burg) \| aufgefodtete g:l~ia~e besi~ett 135,9 ha ueue ~tt[tut, 8,0 ha ~iebet~olung, hie ~ganstu[turen umfafien bagegen 1525,8 ha 330 2itter~vi~ffge ~e~id~fe. neue Ruftur, 391,1 ha ~ieber~ofung, roo5ei an ~abe[~ofbp~Ian~en 12 756 000 ~tfi~, an ~au~of~ 1 622000 \| verroenbet ron~ben. ~ie 9.Iu~offtung~l~often 5etragen ~iir 1 ha ~aaffu~tur 45,82 Jr ~iir 1 ha %~an~ung 69,75 JZ. ~fi~ 193,8 ha .~an~gartert rourben 145 787 ~#, iona~ pro ~e~Im: 752 ~ ~ermenbet; bet (~efamtaulmanb ~iir RuIturen bebi~ert ~ff5 auf 3 4 2 888 Jz, vooSd nDct) bemer~t ~ein m/Sge, bct~ hie ~agdbOne 1,98 {fir einen ~ann, 1,16 ~ flit eine ~vau im ~ur~d)nitt toetragen. ~la~ ~abe~[e VI 5etutg bet ~ufmanb fik ~ a I b m e g e 284866 JZ au~ ~euMuten, 337686 , ,, lInter~a[tuttg, 622552 ~ ~m gansen, unb iibedteig/ ben 9.IuDvanb [ft~ Ru~fuven na~e~u um~ ~oppdte - - dn ~3eroei~ fik bie ri/~tige @rtenntni~ be~ ~erte~, roe[djen gute ~ege far \| bet ~aIbvente 5di~en. ~ie ~abeI[e VII giebt bie llbeffid)t beg $elbertrageg boa \| ~)e~:[eIbe besi[fert pro 1897 au~ bern ~oi$e~trag 12814330 ./// ,, ,, Ncbertttut~urtgen . 319 337 ,, . ,, ~onfiigen ~inna~men 102 39~ ,, ~a. 13236059 ~)ieien ~innaOmen fteDn gtu~ga~en gegentiSe~ ira gCelamtbetrag sor~ 4869949 Jr ~o ba[~ sin {Reine~traS son 8366110 .//d unb Ioe~ro. Don 42,91 ../r p~:o @dtar ~oerbleiSt; hie ~u~gaSen 5eSiffem 36,8 Vgt. br r ~)ie ~:t~/igni[[e be~ ro~ttemI~ergi~/~ett \| finb, rote bie no/~ ange~figtefISerg@ ftber bea @eibertvag bet ~m:fi, unb ~agb.va:mdtung in ben ~at)rett 1853--1897 nac~meift, in [tetem er{reu~i/~en \| tmb ~a~en ~peCelI im ie~}ten ~ct~re na~e~u 1 ~ilIion reed be.t~agen, aB ira ,~a~ 1896, gab im Ie~ten ,3a~)~e~rtt um ~ei~[ic~ 3 ~illionen geftiegen unb biJrlen rooIfl a[~ ein ~eroei~ bet inten~it~en ~irticI)alt I~etrac~tet mermen, ba:en fi~ hie ~taatewdbungen ~tirttem, Iaerg~ erfreuen. ~)ie ~[are unb iiIaedi/~tli~e ~adegtmg bet wbctI~a[tR/~en ~er~a~t.nigh, role fie im ~)odiegenben 16. ,~ct~rgang bider fodtftatifii~c~ert Nit, tei[ungen geI~oten ifi, mug mie yon bern mfi~ttemtoergWoen~o~:~'tperfonaI, b au& yon ienem anberer \| ban{I~ar begtiigt roerben. Dr. ~firft. s ~3etig]te. 331 ~lt. 45. ~ a ~ ~fiv~tenmm ~i~/en~tein unb bet gefamte ~fitt't ~oI)ann yon unb ~u gi/~ten~'tein'fc~e(gfitergefi~. \| batgef/elIt van ~tans Rrat~t, fiJdtL ~orftrefetenten. 6. ~nfiage. ~3rann, \| ~e~Iag beg ~erfagetg. gtad~bem bet ~erfa~'e~: Sum edtenma[e ira ~ t 1873 eine ~tatiFfi~ bet f~t~iI. ~iaStenftein'fctlen ~efi~ungen in einem ~iems un~ein~aren CCeroanbe ~atte er[~einen [agen, wa~: er nun in bet erfreu~i~)en ~age, hie 6. gufIage ~einer grr~eit in ff~efta[t eineg fear eIegant auggefiatteten ~fic~ieing bern ~ubiffum ~or~uIegen. ~agM5e -- ge~iett mit einet farbigen ~c~ppentafeI, 6ne~ ~atte beg ~firfientumg, einem ~on-- unb 4 ~e~tbiibern -- giegt ~un~i~'t hie ~3e~a~:eibung beg ggappeng, hie g)ofr~el~/~rbenunb gbminirtrationen, eine ~Ma}reigung beg iouoetanen ~fi~:j'tentumg gi~tenftein unb ~obann etne ftatifiif00e li5edic~t beg tei~en f/irf/s gtaterbeFi~eg, bet in ben ve~:= ir ~r~nI~inbevn ~t'tetrei~g, au~ teiImei~ein \| unb ~reugen geIegen, 138 914 ha forfiroirtk~a[tIi~en unb 47301 ha s ii~en Ne[it~eg, ira gansen [~)in 186248 ha umlagt. Pin biefe \| fg)Iief~t fi~ ~obann ein ~ematigmug f/imt~ic~ergCiitet, 35 an bet ~a~[, rnit fur~en ~iftotif~en ~itteiiungen, ~obann Pingabe bet IBtgge be~ Ianb, unb fot[troLttf~aftItaSen~e%e~ unb beg gdamten berseitigen ~e~fonale, - bag gtameng~erseiaw roes ben ~/~tug ~is meirt nkt)t roeniget aB 55~ ~amen auf. ~g ift ein tet~e~ unb fc~)/~net~efi}, md~er ~om ~et, lager t)ie~: in iibetfi/~tii6) georbnetet ~eife votgefii~?tt roitbl I-I. ~r. 46. ~ e ~ ~ a g ~ a @ t ~ e r t r a g . ~ntrourf ne~ft ~rI~uterun~en ~um ~ [ ~ u ~ eineg ~rivatjagb-- unb eineg ~emeinbejctgb~!~aa~tvertrageg ne~t ben al~gemeinen ~ebingungen ffit hie ~er~a~lung fig~alifc~er ~agben. ~on \| ~ o I ef ~8au et, ~erfalfet yon ,,hie ,~ctgbgefe~e~rettgeng u u.a. ~eubamm 1899. ~erlaa ~on ,~. ~eumann. ~tei~ I)rofaS. 1 ~n einem ~uftet~eii~ieI fi~t ben ~ac~t~etttag mit eL,era ~i~aten unb er~enfo mit einer (3emeinbe fu/~t bet ~erfd[e~: bag, wag auf bMem ff~eSieteeine~eitg aglid) unb nnbetetMtg notroenbig ift, um ben gnNract)en beg ~i~terg mie beg ~erl)5/~ierg 8u geniigen, nieber8uIegen unb baburd) ~igOelIigMten unb ttn~iarOeiten sroifa}en beiben RontraOenten~otsubeugen. ,3n beigeffig~en ~flaute~:ungen witb au~ hie einia)idigigen gefe~Ii~en ~e, ffimmungen bingeroiefen. -- ~i~t o~ne ~ntereffe far ~i~t~reu~en finb hie ,,glIgemeinen ~3ebingungenffit bie ~erpac~tung forFtfig~aiif~er~agben", ~N~iiienf~aftliOc~ ~cnt~all~Iatt. 1~00. 23 aa2 ~toti~en. mdg)e ba~ preugiig)e ~inifterittm far ~anbmirtI4aft, ~ora~nen unb ~orften tmterm 14. \| 1896 eflagen bat• burg) mdg)e bet g}/tg)ter mang)erM ~elg)r/irttltmgett Mner ~agbbefugnt~ lid) aufer~egert ttrtb in~, bdonbere bern gdamten {~orfiperfonal (einlg)Ifi~fig bet ~t)eren ~eamtert) hie 9.iu~fibtmg bet ~agb auf {Rau~ettg, ~?ag)[e, ~aninct)ert, ~ager~fi~ner, ~ei~er, Rormora,,e, ~nten, ~n~,e, ~ag)tdn, \| ~ecdrinett, 5Drogdrt urtb bereft 9.Ineiflnung o~rte ~3e~a~Iung geFtatten mug. ~r. 47. ~nlbe~ran~d~r ~ga[b, unb ~agbiiebm: ,on Rar[ g}re~er. 9leu-harem, ~er[ag yon ~. 91eumann. 110 ~. ~rei~ t~art. ~ ,.#. ~nt f~egen~al~ ~u mand~en ben g[eig)en \| umfa~'{enbe~,\| Iungert ~on IBebig)ten anberer finb e~ ~ter au~[g)Iieg[t~ eigene ~3i~, /tmgen, bie bet ~erfager in bent ~ebr ~)iilS[g) augge~tatteten ~3~irtb~ert bern 2efer badaietet. ~ie ~reube urtb 2uft an be~ 9~atur in i~rer ~g)iJne, am ~a~b: unb ~eibmert ~9tig)t au~ bie[en ~ig)tungen, fie Ipreg)ert ~dc~e {~rettbe [aft burg)aug in 7g)~ner, ~um {get[ fieNoefi[g)er ~orm aug unb werben barum bet alien, hie gleig) bern ~}erM~ev bern ~ d b , bet ~agb ~ugetbcm finb, freunb[i~e ~ufrtaDme [inben, hie wit benMbert ~ier-mit mfin~en! 2/ufruf art die ;~ac~geuoffert in 23ayern. 9ktc~ I~merert ~el~at - - f~ barf man ~o~1 fagen - - ~at bet ~eut[c~e ~orft~ ~r ira ~origctt .qa~re ottf bet beatld~ert ~orft~erfammhutg ~tt \| ba~ ~i~t bet ~elt erl~Iit~t. :~er @r hie bentJt~en {~orftm~inner itt einem gro~ert ~erein ~ttlammen 3~ fagfen, gent ~arii~ aaf hie .qa[)re 1881 gab 1882, ctttf hie ~orft~er[ammlungen ~lt g)atm~er and ~ol~nrg; hie {~rage war bamaI~ noc~ ~tid)t Ilarad~reif tmb wurbe ~ertagt. \| taac~te maI~ nene auf im ~at)re 1897 ttnb bet ~er[u~ ~a i/)~er ~i~Iun8 r~urbe ~emod~t bart~ hie ~iem~ff~ un~ermittelte ~rihtbung be~ beut[a3en Nteid~[orft~erein~ anf bet ~r~erlammhtttg ~tt ~tuttgart im 9~ugult 1897 - - a~er ber~ell~e t~tntte ~eittett ret~ten ~3obert get~httten: ~ei e~, tmeil hie ~al~tutgen aab itt~be[ottbere hie ~iele ugh ~Weffe be~ ~ereine~, ~ie fie ~umaI im erlten ~al~uag~entratr[ 15e~ei~ttet waren, ~eittett 9In~lang faabea, [ei e~, rodl hie ~er[ctramhtagen beutI~er {~orftm~inner in 30;[a~rigem ~3elteben bo~ Sit tie[e ~ttr~dtt gelaNagert batten, aI~ ba~ bet ~d~forft~ereirt lie eia~aa3 {fiitte bei~elte Id}ielgen ~isn~en. g~efieaeiaaaber abet l}attett ~dd)~f~r[i~ereia uab beutI~e ~o~[l~erlomm~urtg offenbar ni~t ~lat~ ira bent[t~en ~ei~e. ~rft bet ~erlamm~ luttg ~tt ~3rel~lau im ~a[~re 1898 fldaag e~, bert re,ten ~eg ~ar ~}erItt)meI~tmg5dber ~u {ir~bert tmb hie 8eroh~tigert ~ebentert roertigftent~ bet 9 na6~ ~t~ ~erft~:caert, roel~e einem ~entJd)en ~or[t~erein emgegen [tanben: :Die ~eben~en, ba~ lbd ange-Migenber ~eteiligt~rtg bet beutId}en ~orftleute art bern neuen ~}erein hie l~i~tjer ftet~
https://openalex.org/W4388158825	https://asdj.journals.ekb.eg/article_321849_848d8e9d1875f0a49c75379c91f01835.pdf	English	null	ASDJ Preface	Deleted Journal	2,022	cc-by	138	ASDJ DENTAL JOURNAL AINSHAMS DENTAL J O U R N A L AIN SHAMS Official Publication of Ain Shams Dental School March 2022- Vol. (25) March 2022- Vol. (25) Editor In Chief Dr. Hatem Saifeldin Associate Editors Dr. Ahmed osama Dr. Dina Mohamed Abdel Khalik Dr. Ramy Gaber Dr. Mohamed Mokhtar Nagy Dr. Mohamed Kandil Dr. Ahmed Mohsen Foad Dr. Eman Moheb Dr. Reham Abo El Fadl Dr. Shaimaa Abuelsadat Dr. ZainabMohamed Diaa Dr .Ahmed Amro Dr. Noha Ibrahim Abdelrahman Dr Marwa Salah hatemsaifeldin@dent.asu.edu.eg Assoc. Prof. of Orthodontics Prof.of Removable Prosthodontics Assoc. Prof. of Oral Biology Lecturer of Oral&Maxillofacial Surgery Prof.of Endodontics Assoc. Prof.of Dental Biomaterials Lecturer.of Fixed Prosthodontics Lecturer.of Fixed Prosthodontics Assoc. Prof.of Pedodontics Assoc. Prof. of Oral Radiology Assoc. Prof. of Operative Dentistry Assoc. Prof. of Oral Medicine and Periodontology Assoc. Prof.of Orthodontics Lecturer of Orthodontics
https://openalex.org/W1751215550	https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0135189&type=printable	English	null	DMD Mutations in 576 Dystrophinopathy Families: A Step Forward in Genotype-Phenotype Correlations	PloS one	2,015	cc-by	11,628	RESEARCH ARTICLE DMD Mutations in 576 Dystrophinopathy Families: A Step Forward in Genotype- Phenotype Correlations Jonas Juan-Mateu1☯, Lidia Gonzalez-Quereda1☯, Maria Jose Rodriguez2, Manel Baena2, Edgard Verdura2, Andres Nascimento3, Carlos Ortez3, Montserrat Baiget1, Pia Gallano1* 1 Genetics Department, Hospital de la Santa Creu i Sant Pau, U705 CIBERER, Barcelona, Spain, 2 Genetics Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain, 3 Neuromuscular Unit, Hospital Sant Joan de Deu, Esplugues de Llobregat, Spain Jonas Juan-Mateu1☯, Lidia Gonzalez-Quereda1☯, Maria Jose Rodriguez2, Manel Baena2, Edgard Verdura2, Andres Nascimento3, Carlos Ortez3, Montserrat Baiget1, Pia Gallano1* 1 Genetics Department, Hospital de la Santa Creu i Sant Pau, U705 CIBERER, Barcelona, Spain, 2 Genetics Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain, 3 Neuromuscular Unit, Hospital Sant Joan de Deu, Esplugues de Llobregat, Spain 1 Genetics Department, Hospital de la Santa Creu i Sant Pau, U705 CIBERER, Barcelona, Spain, 2 Genetics Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain, 3 Neuromuscular Unit, Hospital Sant Joan de Deu, Esplugues de Llobregat, Spain ☯These authors contributed equally to this work. * pgallano@santpau.cat ☯These authors contributed equally to this work. * pgallano@santpau.cat a1111 a11111 Abstract Recent advances in molecular therapies for Duchenne muscular dystrophy (DMD) require precise genetic diagnosis because most therapeutic strategies are mutation-specific. To understand more about the genotype-phenotype correlations of the DMD gene we per- formed a comprehensive analysis of the DMD mutational spectrum in a large series of fami- lies. Here we provide the clinical, pathological and genetic features of 576 dystrophinopathy patients. DMD gene analysis was performed using the MLPA technique and whole gene sequencing in blood DNA and muscle cDNA. The impact of the DNA variants on mRNA splicing and protein functionality was evaluated by in silico analysis using computational algorithms. DMD mutations were detected in 576 unrelated dystrophinopathy families by combining the analysis of exonic copies and the analysis of small mutations. We found that 471 of these mutations were large intragenic rearrangements. Of these, 406 (70.5%) were exonic deletions, 64 (11.1%) were exonic duplications, and one was a deletion/duplication complex rearrangement (0.2%). Small mutations were identified in 105 cases (18.2%), most being nonsense/frameshift types (75.2%). Mutations in splice sites, however, were rel- atively frequent (20%). In total, 276 mutations were identified, 85 of which have not been previously described. The diagnostic algorithm used proved to be accurate for the molecu- lar diagnosis of dystrophinopathies. The reading frame rule was fulfilled in 90.4% of DMD patients and in 82.4% of Becker muscular dystrophy patients (BMD), with significant differ- ences between the mutation types. We found that 58% of DMD patients would be included in single exon-exon skipping trials, 63% from strategies directed against multiexon-skipping exons 45 to 55, and 14% from PTC therapy. A detailed analysis of missense mutations pro- vided valuable information about their impact on the protein structure. Background Dystrophinopathies are the most common forms of muscular dystrophy in childhood. They are caused by mutations in the X chromosome-linked DMD gene [OMIM: 300377] [1, 2]. DMD gene is the largest known human gene, spanning 2.22 Mb in the region Xp21, and it has 79 exons and 8 promoters. In addition, most of these small mutations are unique and one- third are sporadic. This gene encodes the protein called dystrophin, a key element in stabilizing the sarcolemma during muscle contraction [3]. There are two main phenotypes: Duchenne muscular dystrophy, a severe form that has an incidence of 1:3500 male births [OMIM # 310200], and Becker muscular dystrophy, a mild form with an incidence of 1:20000 male births, [OMIM # 300376]. One-third of the mutations are de novo [4]. Clinical severity depends on whether or not the reading frame of the gene is maintained: DMD is mostly caused by out- frame mutations while BMD is caused by in-frame mutations [5]. Mutations in the DMD gene can be associated with X-linked dilated cardiomiopathy, in which case patients present only with heart problems. [OMIM # 302045], [6]. Since the gene was discovered in 1986, many mutations have been described. Mutational studies have traditionally focused on the detection of exonic deletions, representing 65% of all mutations. The observation that some exons were more frequently deleted led to the imple- mentation of multiplex PCR as a standard diagnostic method [7]. This technique can detect up to 98% of deletions, but it does not delimit the extent of the deletions or detect exonic duplica- tions, which represent up to 10% of the mutations. Moreover, multiplex PCR is unable to detect mutations in carrier women. To detect duplications, it is necessary to analyse the number of exonic copies. The recent introduction of dosimetry methods based on PCR MLPA (multiplex ligation-dependent probe amplifcication) has significantly improved the detection of large intragenic rearrangements in the 79 exons that constitute the gene [8, 9]. The remaining mutations are small mutations and they account for approximately 25–30% of the molecular pathology of the DMD gene. The analysis of these small mutations has historically been a difficult task, mainly due to the gene’s size. The search for rapid and economical detection of these mutations led to the development of several techniques [10–13]. OPEN ACCESS OPEN ACCESS Citation: Juan-Mateu J, Gonzalez-Quereda L, Rodriguez MJ, Baena M, Verdura E, Nascimento A, et al. (2015) DMD Mutations in 576 Dystrophinopathy Families: A Step Forward in Genotype-Phenotype Correlations. PLoS ONE 10(8): e0135189. doi:10.1371/journal.pone.0135189 Editor: James M. Ervasti, University of Minnesota, UNITED STATES Received: May 11, 2015 Accepted: July 17, 2015 Published: August 18, 2015 Copyright: © 2015 Juan-Mateu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Funding: The study is sponsored through a governmental grant of the Instituto de Salud Carlos III (PI 11/02586) which is co-funded by FEDER. Competing Interests: The authors have declared that no competing interests exist. Citation: Juan-Mateu J, Gonzalez-Quereda L, Rodriguez MJ, Baena M, Verdura E, Nascimento A, et al. (2015) DMD Mutations in 576 Dystrophinopathy Families: A Step Forward in Genotype-Phenotype Correlations. PLoS ONE 10(8): e0135189. doi:10.1371/journal.pone.0135189 Competing Interests: The authors have declared that no competing interests exist. 1 / 21 PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 A Deep Molecular Analysis in 576 Dystrophinopathy Families Background In recent years, the affordable cost of Sanger sequencing and the development of massive sequencing systems (Next Generation Seguencing, NGS) has made DMD gene analysis affordable. Flanigan and co-workers described a semi-automatic technique for direct sequencing of the 79 exons and flanking intron sequences in genomic DNA called SCAIP (single-condition amplification/internal first) [14]. This technique, that also detects deletions, has a higher sensitivity than the screening methods based on conformational analysis or heteroduplex. In 2007, Deburgrave et al. described another diag- nostic strategy based on the use of muscle biopsy, combining protein analysis by Western-blotting and multiplex mutational study by direct sequencing of mRNA [15]. This technique is highly effi- cient, since the detection rate is almost 100% in patients with altered quantitative or qualitative Western-blot for dystrophin. Furthermore, it can detect virtually all types of mutations. It pro- vides a comprehensive correlation between genotype and protein expression, helping to predict clinical phenotype. In this paper we describe 576 dystrophinopathy families and discuss the muta- tional spectrum associated with the DMD gene and its impact on the dystrophin structure. Genetic analysis DNA from patients and their relatives was obtained from samples extracted from peripheral blood according to standard procedures. Before studying the small mutations, we analysed exonic deletions and duplications using MLPA of the 79 DMD exons (P034 and P035 Sauce Kit, MRC-Holland) following the manufacturer's instructions. If a deletion of a single exon was identified, an alternative method was required (PCR, QF-PCR or real-time qPCR, exon sequencing) to rule out a point mutation, rare variant or polymorphism altering the normal MLPA pattern. Small mutations were detected in most patients by direct sequencing of the 79 exons and flanking intron regions by SCAIP [14]. When muscle tissue was available, muta- tional analysis was performed on cDNA and subsequently confirmed in genomic DNA. Muscle mRNA was extracted using 30 mg of muscle with the RNeasy Fibrous Tissue Mini Kit (Qiagen, Hilden, Germany) and retrotranscribed to cDNA by RT-PCR using polythiamine primers (Invitrogen, Carlsbad, USA). The full DMD transcript was amplified and sequenced in 20 over- lapping amplicons with our own primers and others described previously [15]. Sequence analy- sis was performed by Sanger sequencing method (Big Dye 3.1 chemistry and equipment 3500xL ABI, Applied Biosymtems, Foster City, USA). The impact of the DNA variants detected on mRNA splicing and protein functionality was evaluated by in silico analysis using computational algorithms. Altered splicing sites were ana- lyzed using positional weight matrices included in the Human Splicing Finder and Alamut softwares. Pathogenicity of amino acid substitutions was evaluated using Polyphen-2 [16] and SIFT [17] algorithms. All substitutions with a Polyphen-2 score below 1 and a SIFT score below 0.05 were considered damaging substitutions. Moreover, when an aminoacid substitu- tion was detected in any of the 100 healthy controls, pathogenicity was rejected. In addition, we used LOVD database (Leiden Open Variation Database: www.dmd.nl) as a reference to deter- mine if the substitution consisted in a missense mutation or a non-synonymous SNP. The nucleotide position was determined according to the DMD reference sequence (RefSeq NM_004006.2) and mutation nomenclature followed the guidelines of the Human Genome Variation Society (HGVS). The mutation rate per nucleotide and per generation for each mutation type was calculated according to the formula μx = mnx / Ntx, as previously described [18]. MARCOIL program was used to predict the existence and location of potential coiled-coil domains in protein sequences[19]. Patients Patients with DMD/BMD were grouped into four categories: Duchenne muscular dystrophy (DMD), Becker muscular dystrophy (BMD), intermediate muscular dystrophy (IMD), and pure cardiac X-linked dilated cardiomyopathy (XLCM), based on clinical presentation, family PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 2 / 21 A Deep Molecular Analysis in 576 Dystrophinopathy Families history, age of onset of symptoms, disease progression, and age of loss of ambulation (DMD <13, BMD 16, IMD 13 and XLCM <16). To avoid bias, we included only one case for each family. A histopathological study was performed prior to molecular analysis in all cases for which a muscle biopsy was available. Dystrophin expression was analysed using monoclonal antibodies against N-terminal epitopes (DYS3), rod domain (DYS1) and C-terminus (DYS2) (Novocastra, Newcastle upon Tyne, UK). Other sarcolemmal proteins, such as sarcoglycans α, β, γ and δ, caveolin-3, dysferlin, utrophin and emerin, were also analysed by IHC. Written informed consent was obtained from all patients. In those cases where patients were minors, written informed consent was authorised and signed by their parents. Adult patients authorised and signed their own informed consent. The studies were approved by the Ethics Committee at Hospital de la Santa Creu I Sant Pau (HSPSC). Exonic deletions We identified 471 (81.8%) intragenic rearrangements, 406 (70.5%) of which were deletions and 64 (11.1%) duplications. In one DMD patient, we detected two apparently independent rear- rangements (Del Pb>29 and Dup 37>43; S1 Fig). Both deletions and duplications had a non- random distribution with two hot spots. We found that 73.2% (298/407) of deletions started between introns 43 and 55 (distal hot spot), whereas 18.7% (72/407) started between introns 1 and 20 (proximal hot spot). This shows that deletion breakpoints were mainly concentrated in a few introns at the distal hot spot, while proximal breakpoints were more dispersed (Fig 2). Considering the 814 breakpoints, intron 44 was clearly that most frequently involved in dele- tions (19.9%, 162/814) and mostly as a 5' breaking point (87.6%), followed by introns 47 (10.3%, 84/814) and 50 (9.1%, 74/814). The proportion of 3’ breakpoints respect to 5’ break- points tended to gradually increase from intron 46 to intron 55. In the proximal region of the gene, introns 7 (4.7%, 38/814) and 2 (2.8%, 23/814) were the most involved. Intron 2 only pre- sented one 5’ breakpoint while intron 7 equally presented 5’ and 3’ breakpoints. The large length of introns 2, 7 and 44 (170 Kb, 110 Kb and 248 Kb, respectively) must be taken into account when considering the frequency of breakpoints. Deletions affecting only regions outside the two hot spots were unusual: 4.4% (18/407) were located between the two hot spots (introns 21–42), 2% (8/407) starting at 5' end of DMD gene, and 1.7% were located between introns 55 and 79. Only seven cases showed deletions that included the two hot spots (1.7%). Furthermore, 8 deletions started in regions at 5' end of exon 1, deleting brain and muscle promoters. One of them, associated with the DMD phenotype, deleted the entire DMD gene and 5’ flanking genes (GK [OMIM: 300474] and OTC [OMIM: 300461]). Three deletions associated with DMD were limited to the promoter region. In our cohort of mutations, 131 deletions were identified, of which more than half (56.4%, 74/131) were detected only once, in agreement with the high allelic heterogeneity described in the DMD gene. In contrast with findings in a previous paper [20], we observed a greater diver- sity at the distal hot spot (60 deletions) than at the proximal hot spot (46 deletions). Results We identified DMD mutations in 576 unrelated families, 564 of which affected males (360 DMD, 7 IMD and 176 BMD) and 12 affected isolated symptomatic female carriers. We were 3 / 21 PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 A Deep Molecular Analysis in 576 Dystrophinopathy Families unable to assign 21 male patients to a phenotypic category, either because clinical data were lacking or because the patients were too young. Of the 576 independent mutational events, 471 (81.8%) were major rearrangements (exonic deletions and duplications) and 105 (18.2%) were small mutations. The frequency of deletions, duplications and small mutations differed depending on the phenotypic group. BMD patients had more deletions (80%, 141/176) than DMD/IMD patients (66%, 242/367), while the frequency of mutations in BMD patients was lower (9.1%, 16/176) than that in DMD/IMD patients (22.6%, 83/267) (Fig 1, Table 1). Exonic deletions Further- more, deletions starting at the proximal hot spot had an average larger extension (14 deleted exons) than those starting at the distal hot spot (6 deleted exons). Deletions associated with BMD presented lower heterogeneity since the 10 most frequent deletions accounted for 76%. In contrast, in DMD, 12 recurrent deletions represented 46% of all deletions. Exonic duplications Duplications accounted for 11.1% of all identified mutations. Unlike deletions, duplications had a more dispersed distribution and were slightly more frequent in the proximal hot spot (41.5%, 27/65) than in the distal hot spot (32.3%, 21/65) (Fig 2B). Like deletions, duplications presented a great heterogeneity because 36 of the 47 identified duplications were detected only once. Unlike deletions, duplications had more diversity in the proximal hot spot (25 duplica- tions) than in the distal hotspot (13 duplications). Breakpoints were concentrated at the proxi- mal hot spot, in intron 2 (10%, 13/130), intron 7 (7.7%, 10/130), intron 1 (7.7 / 10/130) and 4 / 21 PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 A Deep Molecular Analysis in 576 Dystrophinopathy Families Fig 1. Identified mutations and phenotypic groups. doi:10.1371/journal.pone.0135189.g001 Fig 1. Identified mutations and phenotypic groups. doi:10.1371/journal.pone.0135189.g001 Fig 1. Identified mutations and phenotypic groups. doi:10.1371/journal.pone.0135189.g001 doi:10.1371/journal.pone.0135189.g001 Table 1. Number of identified mutations. Table 1. Number of identified mutations. Table 1. Number of identified mutations. Table 1. Number of identified mutations. Type of mutation DMD/IMD BMD DMD/BMD Isolated carrier Total % Exonic deletion 242 141 18 5 406 70.5% In-frame 18 127 15 158 Frameshift 220 14 3 5 244 Others 4 4 Exonic duplication 41 19 3 1 64 11.1% In-frame 7 12 2 1 22 Frameshift 34 7 1 42 Others 0 Complex rearrangements 1 1 0.2% Nonsense 46 5 3 54 9.4% UGA 19 3 22 UAG 15 1 1 17 UAA 12 1 2 15 Indels 21 3 2 26 Frameshift insertion 6 1 7 Frameshift deletion 11 2 1 14 Framshift indel 3 1 4 In-frame deletion 1 1 Missense 3 1 4 0.7% Splice Site 13 6 1 20 3.5% Pseudoexon 1 1 0.2% Total Mutations 367 176 21 12 576 100% doi:10.1371/journal.pone.0135189.t001 PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 5 / 21 PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 5 / 21 A Deep Molecular Analysis in 576 Dystrophinopathy Families intron 9 (4.6%, 6/130). Distal breakpoints in duplications were less frequent than in Fig 2. Distribution of intronic breakpoints in large intragenic rearrangements in the DMD gene. (A) Breakpoints in deletions. (B) Breakpo duplications. 5’ breakpoints in grey and 3’ breakpoints in white. doi:10.1371/journal.pone.0135189.g002 Fig 2. Distribution of intronic breakpoints in large intragenic rearrangements in the DMD gene. (A) Breakpoints in deletions. (B) Breakpoints in duplications. 5’ breakpoints in grey and 3’ breakpoints in white. Fig 2. Distribution of intronic breakpoints in large intragenic rearrangements in the DMD gene. (A) Breakpoints in deletions. (B) Breakpoints in duplications. 5’ breakpoints in grey and 3’ breakpoints in white. doi:10.1371/journal.pone.0135189.g002 doi:10.1371/journal.pone.0135189.g002 intron 9 (4.6%, 6/130). Distal breakpoints in duplications were less frequent than in deletions. Intron 7 presented similar breakpoints frequency between deletions and duplications with analogous proportions for 5' and 3' breakpoints. g p p p No significant difference was observed in the size of the duplication between the proximal and distal hot spots. The most frequent duplication was that of exon 2, 7.7% (5/65), and it was associated with DMD in all cases. Duplications of exons 3–7, 5, 8–9, 50 and 56–62 were identi- fied three times (4.6% all). No significant difference was observed in the size of the duplication between the proximal and distal hot spots. The most frequent duplication was that of exon 2, 7.7% (5/65), and it was associated with DMD in all cases. Duplications of exons 3–7, 5, 8–9, 50 and 56–62 were identi- fied three times (4.6% all). 6 / 21 PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 A Deep Molecular Analysis in 576 Dystrophinopathy Families Nonsense mutations Nonsense mutations represented 51.4% (54/105) of the small mutations and 9.4% (54/576) of the total mutations. The UGA stop codon was the most frequent (42.6%), followed by UAG (29.6%) and UAA (27.8%). The DMD gene (Dp427m muscle isoform) has a total of 1,500 trip- lets that can be mutated into stop codon by a substitution of a single nucleotide. Transitions (77.8%) were more frequent than transversions (22.2%), and the C> T transition was the most common (90.5%). Small mutations We identified 98 mutations in 105 unrelated individuals (18.2%, 105/576), 55 of which have not been previously identified in the LOVD database. We identified a variety of mutations: 54 nonsense mutations, 15 microdeletions, 11 insertions/duplications, 20 splice site mutations, 4 missense, and one deep intronic mutation. The frequency of mutation types differed according to the clinical phenotype (Fig 3). The vast majority of DMD patients presented frameshift or nonsense mutations, causing a premature stop codon and a truncated protein rapidly degraded by the NMDA process. (81%). Nonsense substitutions are the most common type in patients with DMD/IMD (56.1%). However, most mutations in BMD patients affected mRNA splicing process (43.8%), while nonsense and frameshift mutations accounted for 31.25% and 18.75%, respectively. No recurrent mutations or hot spots were identified because they are distributed throughout all DMD exons involving all dystrophin domains (Figs 4 and 5). Table 2 specifies the rate and mutational target size for each type of small mutation. Single base substitutions were 2.4 times more frequent than small deletions or insertions, presenting a 15.4 times higher rate. The mutational rates per nucleotide 6.02x10-9 (all single nucleotide substitutions) and 0.39x10-9 (insertions/deletions small) were slightly lower than those published in a previous study [18]. Frameshift mutations Frameshift mutations were identified in 23.8% (25/105) of patients with small mutations. They were caused by deletion, insertion or deletion-insertion events (generally involving 1–5 nucleo- tides). Only two exceptions were observed: a deletion of 35 bp in exon 45 and an insertion of 18 bp in exon 11. Most identified mutations in our cohort have not been previously described. Only two posi- tions were recurrent although the mutations located therein were not identical: c.6127del and c.6128_6131del in exon 43 and c.10231_10235del and c.10235del in exon 71. PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 Splicing mutations Twenty splice site mutations were identified in 21 unrelated patients, representing 20% (21/ 105) of small mutations and 3.6% (21/576) of total mutations. Most of these changes were located in the canonical dinucleotides AG/GT of natural splice sites (65%, 13/20); while muta- tions located in less conserved positions were rare (Fig 6). Mutations affecting donor sites (5' ss) were slightly more frequent (52.4%, 11/21) than those affecting acceptor sites (3' ss) (38.1% 21/08). Two mutations were located outside natural splice sites. The deep intronic mutation C.9225-647A located in intron 62 was detected through muscular cDNA analysis. This muta- tion activated a cryptic donor site that, along with a cryptic acceptor, caused the inclusion of a 67 bp pseudoexon at the mature mRNA level. The second mutation was an apparent missense mutation at exon 38, c.5444A> G/ p.Asp1815Gly. The cDNA analysis showed that the muta- tion caused a 5 bp deletion due to the creation of a new donor site. The splicing pattern of 14 PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 7 / 21 A Deep Molecular Analysis in 576 Dystrophinopathy Families Fig 3. Distribution of identified point mutations and phenotypic groups. doi:10.1371/journal.pone.0135189.g003 Fig 3. Distribution of identified point mutations and phenotypic groups. doi:10.1371/journal.pone.0135189.g003 splice site mutations was determined. In most cases (78.6%, 11/14) splicing mutations caused complex patterns with levels of more than one transcript [19]. doi:10.1371/journal.pone.0135189.g004 Missense and in-frame mutations Only four missense mutations and one in-frame deletion of a single amino acid (4.8% of point mutations and 0.9% of total mutations) were identified. Four of these mutations were associ- ated with DMD and IMD phenotypes, while only one was associated with an atypical BMD patient. Two of the four were located at the N-terminal actin binding domain (ABD1): p. Leu53Arg in a DMD patient with irregular dystrophin reduction and p.Gly166Val in an IMD Fig 4. Distribution of point mutations distribution along the dystrophin domains. Mutations in DMD in red, in IMD in green, and in BMD in blue. Mutations detected in female isolated carriers in black. CH1-2: calponin homology domains binding actine ABD1; H1–H4: hinge regions; R1-24: spectrin-like repeats; WW: domain containing two tryptophans; EF-1-2: putative calcium binding sites; ZZ: zinc-finger domain. Fig 4. Distribution of point mutations distribution along the dystrophin domains. Mutations in DMD in red, in IMD in green, and in BMD in blue. Mutations detected in female isolated carriers in black. CH1-2: calponin homology domains binding actine ABD1; H1–H4: hinge regions; R1-24: spectrin-like repeats; WW: domain containing two tryptophans; EF-1-2: putative calcium binding sites; ZZ: zinc-finger domain. doi:10.1371/journal.pone.0135189.g004 8 / 21 PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 A Deep Molecular Analysis in 576 Dystrophinopathy Families Fig 5. Distribution of point mutations identified at DMD exons. Asterisks indicate exons containing CpG codons. doi:10 1371/journal pone 0135189 g005 Fig 5. Distribution of point mutations identified at DMD exons. Asterisks indicate exons containing CpG codons. Fig 5. Distribution of point mutations identified at DMD exons. Asterisks indicate exons containing CpG codons. doi:10 1371/journal pone 0135189 g005 Fig 5. Distribution of point mutations identified at DMD exons. Asterisks indicate exons containing CpG codons. doi:10.1371/journal.pone.0135189.g005 doi:10.1371/journal.pone.0135189.g005 doi:10.1371/journal.pone.0135189.g005 doi:10.1371/journal.pone.0135189.g005 patient without muscle biopsy. A double aminoacid change, p.Met450Ile_Asp451Tyr, located at R2 of central rod domain, was identified in an IMD patient with irregular dystrophin reduc- tion. Two mutations were identified in the distal domains. The p.Pro3320Ser mutation, located in ZZ domain (zinc-finger) of the cystein rich region (CRD), was identified in a BMD patient with near normal dystrophin levels. This patient presented an atypical phenotype with micro- phthalmia in the right eye, vitreous hyperplasia and severe cognitive delay. The deletion p. Glu3367del located in the C-terminal domain was identified in a DMD patient without immu- nohistochemistry data. The small mutations identified in this work will be submitted to LOVD database. Discussion This is the third largest series of dystrophinopathy patients described to date, with 576 unre- lated patients [18, 20, 21]. The results illustrate the high allelic heterogeneity of the DMD gene. d type of mutation. Mutational type target was calculated in nucleotides according to muscular isoform Dp427m r nucleotide and per generation for each mutation type. Table 2. Mutation rate per nuclotide and type of mutation. Mutational type target was calculated in nucleotides according to muscular isoform Dp427m (NM_004006). μx is the mutational rate per nucleotide and per generation for each mutation type. Mutation type Number of mutations Target (nt) μx mutational rate (x10-9) One base substitution 66 1812 6.02 Substitution at splice sites 12 312 6.36 Nonsense substitution 54 1500 5.95 Transition at CpG sites 20 29 114.03 Transversion at CpG sites 0 7 0.00 Transition at not CpG sites 22 380 9.57 Transversion at not CpG sites 12 1091 1.82 Small indels 27 11370 0.39 Indels at CDS 26 11058 0.39 Indels at splice sites 1 312 0.53 doi:10.1371/journal.pone.0135189.t002 Table 2. Mutation rate per nuclotide and type of mutation. Mutational type target was calculated in nucleotides according to muscular isoform Dp427m (NM_004006). μx is the mutational rate per nucleotide and per generation for each mutation type. ble 2. Mutation rate per nuclotide and type of mutation. Mutational type target was calculated in nucleotides acco M_004006). μx is the mutational rate per nucleotide and per generation for each mutation type. PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 9 / 21 A Deep Molecular Analysis in 576 Dystrophinopathy Families Fig 6. Distribution of the splice site mutations according to exon/intron boundaries. Nucleotide positions in x axis. Donor sites (in black) from +1 to +9 positions. Acceptor site (in grey) from -1 to -9 position. Number of mutations identified in each position in y axis. doi:10 1371/journal pone 0135189 g006 Fig 6. Distribution of the splice site mutations according to exon/intron boundaries. Nucleotide positions in x axis. Donor sites (in black) from +1 to +9 positions. Acceptor site (in grey) from -1 to -9 position. Number of mutations identified in each position in y axis. doi:10.1371/journal.pone.0135189.g006 Fig 6. Distribution of the splice site mutations according to exon/intron boundaries. Nucleotide positions in x axis. Donor sites (in black) from +1 to +9 positions. Acceptor site (in grey) from -1 to -9 position Number of mutations identified in each position in y axis. PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 Discussion doi:10.1371/journal.pone.0135189.g006 We identified 276 different mutations, 85 of which have not been previously described. One hundred and thirty-one were exonic deletions, 46 were exonic duplications, one was a complex rearrangement deletion/duplication, and 98 were small mutations. g The diagnostic algorithm used consisted of the analysis of the exonic copy number, followed by the analysis of small mutations by sequencing genomic DNA or cDNA from muscle biopsy when available, for negative exonic deletions/duplications. Our results confirm that it is an accurate algorithm for the molecular diagnosis of dystrophynopathies. Despite the study of muscle cDNA requires an invasive method as muscle biopsy, it allows: 1) detection of all types of mutations, including deep intronic mutations, 2) assessment of the impact of DNA variants on pre-mRNA splicing to identify splice sites (ss) abnormalities or regulatory elements (SRE), and 3) evaluation of the reading frame conservation that determines the phenotypic severity. An example is the mutation c.5444A> G, which could have been classified as a non-pathogenic missense change (p.Asp1815Gly) when in fact it caused aberrant splicing, generating a frame- shift transcript. However, care must be taken in the study of point mutations in mRNA; some splicing mutations in BMD patients can induce significant levels of normal transcripts, making it difficult to detect aberrant mRNA variants. This is the case of the mutation c.3603 + 2dupT in which the anomalous transcript only represented 17% of total transcripts. The frequency for each mutation type was similar to that described previously [22] and dif- fered between DMD and BMD phenotypes (Figs 1 and 3). BMD patients had fewer point muta- tions and more exonic deletions than DMD patients. These differences were more pronounced in the point mutations. In DMD patients, we found most point mutations were frameshift or nonsense type, according to the reading frame. However, our BMD patients had a high fre- quency of splicing mutations, although they presented many exceptions to the reading frame law, as up to 50% of mutations were frameshift or nonsense type. In accordance with previous studies [18, 20, 23, 24], we noted that large deletions and dupli- cations had a non-random distribution with the presence of two hot spots. In our cohort, as in PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 10 / 21 A Deep Molecular Analysis in 576 Dystrophinopathy Families a previous study [25], the intronic size was not the only factor determining deletional profiles. Discussion Several mechanisms involved in the development of genomic rearrangements have been reported [26–28]. The non-allelic homologous recombination (NAHR, non-allelic homologous recombination) is a mechanism described in numerous genetic disorders that can cause dele- tions and duplications in the same frequency [29–31]. The Alu repeats crosslinking by the NAHR mechanism have been considered a cause of deletions in several genes, including the DMD gene [32]. Analysis of breakpoints in the DMD gene shows that exonic deletions and duplications present different frequencies, caused by different mechanisms. If both, deletions and duplications were the result of NAHR, we would expect similar deletion and duplication frequencies for each intron. It has also been suggested that duplications could arise at different times in the cellular cycle. Like point mutations, the deletions are predominantly maternally inherited, while duplications descend from the paternal germ line [26,33,34]. It has been reported that the duplication of exon 2 is caused by the non-homologous end joining mecha- nism (NHEJ) involved in the double strand DNA break repair [24]. Unlike deletions/duplications, point mutations have no hot spots and are distributed along the entire gene (Fig 4). The only exceptions are missense mutations that mainly concentrate in the N- and C-terminal ends of binding protein domains, in agreement with previous publica- tions [20]. Half of the identified mutations in our study were not previously described, con- firming the necessity to study the whole gene in molecular diagnosis. PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 Genotype/phenotype correlation The phenotypic severity depends mainly on the reading frame rule [4]. This rule postulates that mutations destroying the reading frame cause absence of dystrophin in skeletal muscle and the DMD phenotype, whereas mutations preserving the reading frame permit the expres- sion of semifunctional dystrophin and BMD phenotype. The workflow (MLPA, sequencing, in silico analysis and mRNA analysis) used in this study has allowed us to better find exceptions to the reading frame rule and to better understand the genotype-phenotype correlation. In our cohort, the reading frame rule was fulfilled in 90.4% of DMD patients and in 82.4% of BMD patients. Exonic deletions were the mutational group that had fewest exceptions to the rule (8.4%, 32/379), while exonic duplications and point mutations presented exceptions in similar proportions, 23.3% (14/60) and 19.2% (19/99) respectively. Several mechanisms explaining the exceptions to the reading frame law have been described. It is assumed that duplications occur in tandem, without having an mRNA study to support this in most cases. It seems certain that most are tandem duplications [35] because noncontigu- ous rearrangements cases have been described causing complex effects at the mRNA level [24]. Furthermore, it is unknown how large in-frame duplications can affect the dystrophin func- tion. Regarding deletions several considerations can be made. In DMD patients, 44% (8/18) of the identified exceptions were deletions causing partial or total loss of a binding protein domain that would compromise the protein function. In 7 patients, the mutation affected the ABD domain and in one patient it affected the CRD region (Fig 7). Deletions affecting the brain and muscle promoters were associated in all cases with the DMD phenotype. According to previous descriptions, the two frameshift deletions at the 5’ end (3>6 and 3>7) accounted for 36% of the exceptions associated with BMD. Several mechanisms seem to be involved in the rescue of dystrophin expression in frameshift mutations located at the 5' end. These mecha- nisms include alternative translation initiation in exon 6 or 8 [36,37] and patterns of alternative splicing [38]. Small mutations also present numerous exceptions to the reading frame rule, especially in BMD patients, in whom most exceptions are due to alterations in the normal splicing pattern PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 11 / 21 A Deep Molecular Analysis in 576 Dystrophinopathy Families [39]. PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 Protein domains changes: missense and in-frame mutations Missense mutations are exceptions to the reading frame rule and often cause an unusual com- bination of severe phenotypes with dystrophin expression. According to previous publications [18, 20], missense mutations are rare (0.9%) and most are located in protein-protein interac- tion domains. However, missense DMD mutations have proven to be valuable in the analysis of pathological dystrophin alterations. In our cohort, we identified two mutations in the N-terminal F-actin binding domain (ABD1). This domain is composed of two calponin homologous (CH1-2) modules with three actin-binding regions (ABS1-3). The domain ABD1, along with an additional domain located at the rod domain (ABD2), allows dystrophin to combine with actin filaments, forming bun- dles and networks and avoiding the depolymerization of filaments [43] (Fig 4). It has been reported that missense mutations in the ABD1 domain decrease the thermodynamic stability of dystrophin, causing misfolding and aggregation into amyloid-like structures [44]. We identi- fied the mutation p.Leu53Arg in the CH1 module in a DMD patient, whereas the mutation p. Gly166Val in the CH2 module was identified in an IMD patient. The difference in clinical severity between the two mutations suggests they affect the structure of ABD1 domain and its ability to interact with actin differently. The domain ABD1 was the first protein domain in which the crystal structure was determined (S2A Fig) [45]. The p.Leu53Arg mutation in CH1 introduces a charged residue on a hydrophobic region that is structurally closer to the actin binding sites (ABS1-3) (S2B Fig). Hypothetically, the mutation could compromise the binding with actin and cause a DMD phenotype even without altering the dystrophin expression. According to this hypothesis, a mutation in the adjacent residue (p.Leu54Arg) has been described in a DMD patient [46]. However, the mutation in CH2 (p.Gly166Val) is not structur- ally located close to ABS3, indicating it does not interact with actin. This mutation replaces a small neutral residue with a hydrophobic residue at the beginning of an alpha helix where mutations associated with BMD have been described (Asp165, Ala168 and Ala171) [47]. This suggests that this region is critical for CH2 stability (S2C Fig). Our data concerning the location of the mutated residue in relation to phenotype correlate with functional studies by Henderson and co-workers [48]. These authors suggested that missense mutations located in CH1 are associated with severe phenotype due to the combined effect of alterations in actin binding and induction of thermodynamic instability. A Deep Molecular Analysis in 576 Dystrophinopathy Families often cause complex splicing patterns which may include skipping of one or more exons, acti- vation of cryptic splice sites and intronic retention. Concerning altered splicing patterns, two types of Alu retrotransposon insertions have been described in the DMD gene: one in an XLCM patient, and the other in a DMD patient [41,42]. In both cases, the insertion of the Alu element occurred inside the intron, modifying the splic- ing pattern. This altered pattern caused the skipping of a closer exon in one case and the inser- tion of the Alu element in the mature mRNA in the other case. Patient #1990 presented an insertion of 18 bp in exon 11. This inserted fragment showed a high sequence homology with part of the retrotransposon elements of the Alu J family. In our patient, we were unable to determine whether the insertion altered the splicing because no muscle biopsy was available for mRNA analysis. Genotype/phenotype correlation All nonsense or frameshift mutations associated with BMD are located in in-frame ex (exons 9, 28, 37, 71 and 74). In these mutations, the alteration of splicing regulatory eleme (SRE) can increase the levels of transcripts with in-frame skipping leading to the rescue of Fig 7. Exceptions to the reading frame rule in large intragenic rearrangements. (A) In-frame mutations in DMD patients. (B) Frameshift mutations i BMD patients. Asterisk indicates mutations identified in both phenotypes. doi:10.1371/journal.pone.0135189.g007 Fig 7. Exceptions to the reading frame rule in large intragenic rearrangements. (A) In-frame mutations in DMD patients. (B) Frameshift mutations in BMD patients. Asterisk indicates mutations identified in both phenotypes. Fig 7. Exceptions to the reading frame rule in large intragenic rearrangements. (A) In-frame mutations in DMD patients. (B) Frameshift mutations in BMD patients. Asterisk indicates mutations identified in both phenotypes. doi:10.1371/journal.pone.0135189.g007 [39]. All nonsense or frameshift mutations associated with BMD are located in in-frame exons (exons 9, 28, 37, 71 and 74). In these mutations, the alteration of splicing regulatory elements (SRE) can increase the levels of transcripts with in-frame skipping, leading to the rescue of the phenotype [40]. In severe DMD or IMD patients, all exceptions are missense mutations located in critical domains for protein function. Previous publications [18] assumed that mutations in natural splice sites always cause exon-skipping. mRNA analysis shows that these mutations [39]. All nonsense or frameshift mutations associated with BMD are located in in-frame exons (exons 9, 28, 37, 71 and 74). In these mutations, the alteration of splicing regulatory elements (SRE) can increase the levels of transcripts with in-frame skipping, leading to the rescue of the phenotype [40]. In severe DMD or IMD patients, all exceptions are missense mutations located in critical domains for protein function. Previous publications [18] assumed that mutations in natural splice sites always cause exon-skipping. mRNA analysis shows that these mutations PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 12 / 21 Protein domains changes: missense and in-frame mutations They observed that p.Leu54Arg decreases the actin binding affinity four-fold and induces aggregation and thermal denaturation. In contrast, p. Asp165Val, p.Ala168Asp and other mutations located in CH2, associated with BMD, increase protein aggregation and denaturation without altering the actin binding affinity [48]. In our cohort, a mutation consisting in two amino acid substitutions in the central rod domain (p.Met450Ile_Asp451Tyr) was identified in IMD patient #1215. To our knowledge, PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 13 / 21 A Deep Molecular Analysis in 576 Dystrophinopathy Families several missense mutations have been described in this domain in the literature [49,50] and in LOVD. The rod domain consists of 24 repeats similar to spectrin (R1–R24) and 4 hinge regions (H1–H4) [51] (Fig 4). It is believed that the dystrophin acts by protecting the membrane from damage caused by muscle contraction. Spectrin-like repeats participate in this biomechanical function, acting as springy units that can be deployed when they are subjected to strength [52]. Initially, it was thought that the spectrin-like repeats had a very low importance in the overall function of dystrophin, since in-frame deletions removing large portions of the rod domain were observed in mild phenotypes [53]. However, several studies suggest that the rod domain has a more complex role than a purely mechanical function. The study of therapeutic mini-dys- trophin in mdx mice revealed that 3 or more repeats are required to retain the protein function- ality [54, 55]. Moreover, several repeats interact with ligands such as F-actin, sinemin, Par-1, nNOS and phospholipids [56–60]. Although the repeats of the spectrin protein family (spectrin, dystrophin, utrophin, α-acti- nin, etc) exhibit a relatively low homology they present a heptade periodic pattern that is char- acteristic of coiled-coil structures (S3A Fig). This pattern consists of seven hydrophobic and hydrophilic residues represented by the letters a to g. The “a” and “d” residues are mostly hydrophobic and ensure the antiparallel folding of three alpha helices (HA, HB and HC) form- ing a supercoiled bundle or coiled-coil [61]. The other positions are usually occupied by hydro- philic or charged residues, so that the helix is coiled between them, hiding the hydrophobic residues inside the bundle and exposing the hydrophilic/charged residues outside the bundle (S3B Fig). PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 Protein domains changes: missense and in-frame mutations It is believed that dystrophin adjacent repeats are joined by a connector that ensures the helicoidal continuity of the last helix in the first repeat (HC) with the first helix in the next repeat (HA) [62]. The double change p.Met450Ile_Asp451Tyr identified in IMD patient #1215 is located at the beginning of the HA helix of the R2 repeat (S3C Fig). Dystrophin immunos- taining shows dystrophin and presence of negative fibers since the change induces instability or folding defects leading to dystrophin degradation. According to this hypothesis, the align- ment of repeats indicates that the mutated residues are located in heptad positions “a” (Met450) and "b" (Aps451), suggesting that the mutation alters the coiled coil structure of R2 repeat (S3A Fig). Several algorithms have been described to predict coiled coil domains. One of these algo- rithms, MARCOIL, establishes the tendency to form coiled coils in a certain heptade position for each residue [63]. The MARCOIL analysis of the wild-type dystrophin and p.Met450I- le_Asp451Tyr dystrophin shows that the mutation causes a dramatic change in the probability of forming coiled coils of 434–477 residues, corresponding to HC helix of R1 and HA helix of R2 (S3D Fig). These data suggest that the mutation changes the protein microenvironment of R1–R2 leading to misfolding and/or thermodynamic instability of the protein. Recently it has been described the presence of p.Leu427Pro mutation in R1 repeat in two brothers with mild BMD phenotype. The patients have a weak immunostaining in N-terminal region of dystro- phin (ABD1 and H1) and the mutation would originate a partial misfolding. These authors suggested that the mutation affects the dynamic properties of the entire N-terminal region [49]. Moreover, it has been described that the combination of two polymorphic variants (p. Glu2910Val and p.Asn2912Asp) in the R23 repeat causes DMD due to the destabilization of repeat [50]. These changes, along with the mutation identified in our patient, correlate with mini-dystrophin studies [54] and a BMD patient who presented minimal muscle involvement and in-frame deletion of exons 14 to 48 (R3–R19) [53]. These data suggest that regions R1-3 and R20-24 are essential for the proper function of dystrophin. Some authors have hypothe- sized that these regions contribute to the stabilization of the adjacent N- and C-terminus domains involved in protein-protein interactions [49,50]. Protein domains changes: missense and in-frame mutations PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 14 / 21 A Deep Molecular Analysis in 576 Dystrophinopathy Families In the cysteine-rich region, the mutation p.Pro3320Ser at ZZ domain (zinc-finger domain) (Fig 4) was identified in a patient with atypical BMD phenotype. This patient, #1497, presented mild muscle weakness, microophthalmia,vitreous hyperplasia, severe cognitive delay and, interestingly, almost normal dystrophin expression in skeletal muscle. ZZ domains are small protein motifs that have up to four conserved cysteines allowing zinc binding or other metals (S4A and S4B Fig) [64]. The zinc binding induces conformational changes permitting binding to specific ligands, such as DNA or other proteins [65]. The cysteine rich region of dystrophin (CRD) has been implicated in binding to β-dystroglycan [66–68]. The CRD region comprises several modular domains: a WW domain, two putative calcium binding sites (EF-hand 1 and 2) and one ZZ domain. The WW domain contains two conserved tryptophans (W) that allows the binding of dystrophin with the last 15 C-terminal residues of β-dystroglycan (S4C Fig). Some studies demonstrate that WW domain is not sufficient by itself to establish the union with β-dystroglycan and requires the presence of both EF and ZZ domains for a stable interac- tion [69–71]. In 2007, Hnia and co-workers identified two zinc-binding regions and one point interacting to β-dystroglycan in the ZZ domain (S4B Fig) [70]. The p.Pro3320Ser mutation, identified in patient #1497, is located in the first zinc-binding region, adjacent to the Cys3319 residue (S4B Fig). This location suggests that the change alters the ability to bind zinc in the first region and consequently alters the conformation of the ZZ domain involving the interac- tion with β-dystroglycan. The BMD phenotype indicates that the mutation does not completely destroy interaction with β-dystroglycan, as expected by a severe DMD phenotype. We observed that mutations located in the first zinc-binding region are mainly associated with the BMD phenotype, whereas those located in the second zinc-binding region, which includes the anchor point to β-dystroglycan, are associated with the DMD phenotype (S4B Fig). The patient’s severe mental retardation correlates with the location of the mutation in the C-terminal end of the gene, affecting all DMD isoforms including Dp71. Dp71 is the most abundant form in fetal and adult brain [72] and has been described as the main factor determining the severity of cog- nitive impairment. Mutations in Dp71 are associated with severe mental retardation [73, 74]. Protein domains changes: missense and in-frame mutations The atypical clinical presentation of the patient, microphthalmia and vitreous hyperplasia which are not associated with dystrophynopathy, encompass some forms of congenital muscu- lar dystrophy caused by glycosylation defects of α-dystroglycan. The fact that the mutation alters the interaction with β-dystroglycan questions whether the structural changes are caused by dystrophinopathy or whether there are two separate pathologies. In the C-terminal domain, we identified a deletion of a single amino acid (p.Glu3367del) associated with the DMD phenotype. The mutation is located 13 residues from the ZZ domain in a region with unknown function, although it is one of the most conserved dystrophin regions. This mutation has been previously described in two IMD and one DMD patients. Becker and co-workers suggested that the deletion of the Glu3367 residue causes a torque and/ or translation of an α-helix that may induce alterations in the conformation or function of the ZZ domain [75]. Conclusions The diagnostic algorithm described in this work was accurate for the molecular diagnosis of dys- trophinopathies. It analyzed the exonic copy number and point mutations by sequencing cDNA from muscle biopsy or genomic DNA for negative deletions/duplications. There were no hot spots for small insertions/deletions. The study of the mutated sequences showed that repeated motifs were implied in the etiology in most cases. A detailed analysis of missense mutations con- tributed significantly to understanding their impact on the protein structure and to explain the non-fulfilment of the reading frame law regarding genotype/phenotype correlation. Variability of DMD gene X-linked diseases provide data on the human genome mutation rate [76,77]. Direct and indi- rect measures suggest that the genomic mutation rate is 1-2x10-8 per nucleotide. The rate per nucleotide mutation observed in our sample was 0.6x10-8, slightly lower than described to date. This could be due to enrichment with large rearrangements respect to point mutations in our sample. According to spontaneous deamination of methylated cytosines [78], CpG transitions in the CGA codon (arginine) represent 37% of total nonsense identified mutations although this odon represents only 2% of the target codons. The 11.9-fold difference in the number of PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 15 / 21 A Deep Molecular Analysis in 576 Dystrophinopathy Families CpG transitions compared to non-CpG transitions is similar to that obtained by measuring the divergence between humans and chimpanzees, observed to be 10 times higher for CpG sites [79]. According to previous publications [39], there are no hot spots for small insertions/dele- tions, although the study of the mutated sequence reveals that in most cases the presence of repeated motifs is implicated in the etiology of such mutations. The sequencing of the coding and flanking intron regions allowed us to identify 119 SNPs (S1 and S2 Tables), 21 of which had not been previously described in LOVD database, dbSNP and HapMap. The study of haplotypes obtained by sequencing reveals the variability in the DMD gene. Just as the point mutations study reveals that 56% are private mutations, study of the SNPs shows that the vast majority of unrelated families present a unique haplotype for DMD locus. This probably reflects the high rate of DMD recombination linked to its large size. Of the 119 identified SNPs, 93 are located in intron regions and 26 in coding exons. Of these 26, 11 were synonymous and 15 were non-synonymous changes, involving the substitution of one amino acid for another. Two non-synonymous SNPs, p.Lys1491Thr and p.Met1483Val, have not been described previously. Both are located in exon 32, corresponding to the R11 repeat of rod domain. However, we can not affirm whether they are rare variants or whether they have a pathogenic effect. Supporting Information S1 Fig. Complex rearrangement in #1612 DMD patient: del Pb>29 and dup 37>43. (A) MLPA results. (B) Diagram of DMD mutated gene in this patient. (TIF) S1 Fig. Complex rearrangement in #1612 DMD patient: del Pb>29 and dup 37>43. (A) MLPA results. (B) Diagram of DMD mutated gene in this patient. (TIF) S2 Fig. Missense mutations in N-terminal acting binding domain (N-ABD1). (A) Tridimen- sional structure of N-ABD domain with calponin-like domains (CH 1–2). ABS1: residues from 17 to 26; ABS2: residues from 102–114; ABS3: residues from 130–146. (B) Module CH1 with the Leu54 residue that reduces four times the actin binding affinity, (C) Module CH2: muta- tions associated to BMD phenotype leading to thermodynamic instability and not altering actin binding. S3 Fig. Double missense mutation at R2 in rod domain and its impact on dystrophin. a. R1 and R2 tridimensional structure: mutated residues and the three helix HA,HB and HC show antiparallel coiled-coil formation. b. HA alienation with seven spectin-like repeats from other proteins. Residues with sequence homology are coloured. Heptade pattern with hydrophobic residues at “a” and “d” positions. c. Diagram showing a trimeric coiled-coil: hydrophobic resi- dues at the nucleus and hydrophilic/loaded residues outside. d. MARCOIL result for coiled coils in residues 420–527: wild type protein (in blue) and mutated p.Met450Ile_Asp451Tyr protein (in red). (TIF) S3 Fig. Double missense mutation at R2 in rod domain and its impact on dystrophin. a. R1 and R2 tridimensional structure: mutated residues and the three helix HA,HB and HC show antiparallel coiled-coil formation. b. HA alienation with seven spectin-like repeats from other proteins. Residues with sequence homology are coloured. Heptade pattern with hydrophobic residues at “a” and “d” positions. c. Diagram showing a trimeric coiled-coil: hydrophobic resi- dues at the nucleus and hydrophilic/loaded residues outside. d. MARCOIL result for coiled coils in residues 420–527: wild type protein (in blue) and mutated p.Met450Ile_Asp451Tyr protein (in red). (TIF) 16 / 21 PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 A Deep Molecular Analysis in 576 Dystrophinopathy Families S4 Fig. Missense mutation at ZZ domain. (A) Murine CBP ZZ domain residues coordinating zinc binding in yellow. (B) Diagram of dystrophin and β-dystroglican binding. (C) Dystrophin ZZ domain diagram showing the two zinc-binding regions. Zn-co-ordinating residues In yel- low; Pro3320 mutated residue in red and the second interaction point site with β-dystroglican in orange. Supporting Information Arrows indicate missense mutations described in LOVD database: DMD patients in black and BMD patients in blue. (TIF) S1 Table. SNPs in coding region. Asterisks indicate previously nondescribed changes with unknown pathogenic effect. (DOC) S2 Table. SNPs in non-coding regions. Asterisks indicate previously nondescribed changes with unknown pathogenic effect. (DOC) S2 Table. SNPs in non-coding regions. Asterisks indicate previously nondescribed changes with unknown pathogenic effect. (DOC) S2 Table. SNPs in non-coding regions. Asterisks indicate previously nondescribed changes with unknown pathogenic effect. (DOC) Acknowledgments The authors thank all patients and their family members for their participation in this study. We thank Carolyn Newey for her kind language assistance and Laura Alías for the images edit- ting support. The study is sponsored through a governmental grant of the Instituto de Salud Carlos III (PI 11/02586) which is co-funded by FEDER. Author Contributions Conceived and designed the experiments: JJM LGQ PG. Performed the experiments: JJM MJR MB EV LGQ. Analyzed the data: JJM LGQ PG. Wrote the paper: JJM LGQ PG. Clinical Char- acterization: AN CO. Intellectual Discussion Support: MBB. PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 References Bennett RR, den Dunnen J, O'Brien KF, Darras BT, Kunkel LM. Detection of mutations in the dystrophin gene via automated DHPLC screening and direct sequencing. BMC Genet 2001; 2: 17. PMID: 11710958 12. Dolinsky LC. Denaturing gradient gel electrophoresis (DGGE) for mutation detection in duchenne mus- cular dystrophy (DMD). Methods Mol Biol 2003; 217: 165–175. PMID: 12491931 13. Hofstra RM, Mulder IM, Vossen R, de Koning-Gans PA, Kraak M, Ginjaar IB, et al. DGGE-based whole-gene mutation scanning of the dystrophin gene in duchenne and becker muscular dystrophy patients. Hum Mutat 2004; 23 (1): 57–66. PMID: 14695533 14. Flanigan KM, von Niederhausern A, Dunn DM, Alder J, Mendell JR, Weiss RB. Rapid direct sequence analysis of the dystrophin gene. Am J Hum Genet 2003; 72 (4): 931–939. PMID: 12632325 15. Deburgrave N, Daoud F, Llense S, Barbot JC, Récan D, Peccate C, et al. Protein- and mRNA-based phenotype-genotype correlations in DMD/BMD with point mutations and molecular basis for BMD with nonsense and frameshift mutations in the DMD gene. Hum Mutat 2007; 28 (2): 183–195. PMID: 17041906 16. Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, et al. A method and server for predicting damaging missense mutations. Nat Methods 2010; 7 (4): 248–249. doi: 10.1038/ nmeth0410-248 PMID: 20354512 17. Kumar P, Henikoff S, Ng PC. Predicting the effects of coding non-synonymous variants on protein func- tion using the SIFT algorithm. Nat Protoc 2009; 4 (7): 1073–1081. doi: 10.1038/nprot.2009.86 PMID: 19561590 18. Flanigan KM, Dunn DM, von Niederhausern A, Soltanzadeh P, Gappmaier E, Howard MT, et al. Muta- tional spectrum of DMD mutations in dystrophinopathy patients: Application of modern diagnostic tech- niques to a large cohort. Hum Mutat 2009; 30 (12): 1657–1666. doi: 10.1002/humu.21114 PMID: 19937601 19. Delorenzi M, Speed T. An HMM model for coiled-coil domains and a comparison with PSSM-based predictions. Bioinformatics 2002; 18(4): 617–25 PMID: 12016059 20. Tuffery-Giraud S, Beroud C, Leturcq F, Yaou RB, Hamroun D, Michel-Calemard L, et al. Genotype-phe- notype analysis in 2,405 patients with a dystrophinopathy using the UMD-DMD database: A model of nationwide knowledgebase. Hum Mutat 2009; 30 (6): 934–945. doi: 10.1002/humu.20976 PMID: 19367636 21. Bladen CL, Salgado D, Monges S, Foncuberta ME, Kekou K, Kosma K, et al. The Treat NMD Global Database: Analysis of more than 7000 Duchenne Muscular Dystrophy mutations. Human Mutation 2015; 36: 395–402 doi: 10.1002/humu.22758 PMID: 25604253 22. References 1. Hoffman EP, Brown RH Jr, Kunkel LM. Dystrophin: The protein product of the duchenne muscular dys- trophy locus. Cell 1987; 51 (6): 919–928. PMID: 3319190 1. Hoffman EP, Brown RH Jr, Kunkel LM. Dystrophin: The protein product of the duchenne muscular dys- trophy locus. Cell 1987; 51 (6): 919–928. PMID: 3319190 1. Hoffman EP, Brown RH Jr, Kunkel LM. Dystrophin: The protein product of the duchenne muscular dys- trophy locus. Cell 1987; 51 (6): 919–928. PMID: 3319190 2. Koenig M, Monaco AP, Kunkel LM. The complete sequence of dystrophin predicts a rod-shaped cyto- skeletal protein. Cell 1988; 53 (2): 219–228. PMID: 3282674 2. Koenig M, Monaco AP, Kunkel LM. The complete sequence of dystrophin predicts a rod-shaped cyto- skeletal protein. Cell 1988; 53 (2): 219–228. PMID: 3282674 3. Ervasti JM. Costameres: The achilles' heel of herculean muscle. J Biol Chem 2003; 278 (16): 13591– 13594. PMID: 12556452 4. Monaco AP, Bertelson CJ, Liechti-Gallati S, Moser H, Kunkel LM. An explanation for the phenotypic dif- ferences between patients bearing partial deletions of the DMD locus. Genomics 1988; 2 (1): 90–95. PMID: 3384440 5. Muntoni F, Torelli S, Ferlini A. Dystrophin and mutations: One gene, several proteins, multiple pheno- types. Lancet Neurol 2003; 2 (12): 731–740. PMID: 14636778 6. Miller LA, Romitti PA, Cunniff C, Druschel C, Mathews KD, Meaney FJ, et al. The muscular dystrophy surveillance tracking and research network (MD STARnet): Surveillance methodology. Birth Defects Res A Clin Mol Teratol 2006; 76 (11): 793–797. PMID: 17036307 7. Beggs AH, Koenig M, Boyce FM, Kunkel LM. Detection of 98% of DMD/BMD gene deletions by poly- merase chain reaction. Hum Genet 1990; 86 (1): 45–48. PMID: 2253937 8. White S, Kalf M, Liu Q, Villerius M, Engelsma D, Kriek M, et al. Comprehensive detection of genomic duplications and deletions in the DMD gene, by use of multiplex amplifiable probe hybridization. Am J Hum Genet 2002; 71 (2): 365–374. PMID: 12111668 9. Schwartz M, Duno M. Improved molecular diagnosis of dystrophin gene mutations using the multiplex ligation-dependent probe amplification method. Genet Test 2004; 8 (4): 361–367. PMID: 15684864 10. Mendell JR, Buzin CH, Feng J, Yan J, Serrano C, Sangani DS, et al. Diagnosis of duchenne dystrophy by enhanced detection of small mutations. Neurology 2001; 57 (4): 645–650. PMID: 11524473 PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 17 / 21 A Deep Molecular Analysis in 576 Dystrophinopathy Families 11. PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 References Tuffery-Giraud S, Saquet C, Chambert S, Echenne B, Marie Cuisset J, Rivier F, et al. The role of mus- cle biopsy in analysis of the dystrophin gene in duchenne muscular dystrophy: Experience of a national referral centre. Neuromuscul Disord 2004; 14 (10): 650–658. PMID: 15351422 35. Hu XY, Ray PN, Worton RG. Mechanisms of tandem duplication in the duchenne muscular dystrophy gene include both homologous and nonhomologous intrachromosomal recombination. EMBO J 1991; 10 (9): 2471–2477. PMID: 1868831 36. Winnard AV, Mendell JR, Prior TW, Florence J, Burghes AH. Frameshift deletions of exons 3–7 and revertant fibers in duchenne muscular dystrophy: Mechanisms of dystrophin production. Am J Hum Genet 1995; 56 (1): 158–166. PMID: 7825572 37. Gurvich OL, Maiti B, Weiss RB, Aggarwal G, Howard MT, Flanigan KM. DMD exon 1 truncating point mutations: Amelioration of phenotype by alternative translation initiation in exon 6. Hum Mutat 2009; 30 (4): 633–640. doi: 10.1002/humu.20913 PMID: 19206170 38. Gualandi F, Rimessi P, Trabanelli C, Spitali P, Neri M, Patarnello T, et al. Intronic breakpoint definition and transcription analysis in DMD/BMD patients with deletion/duplication at the 5' mutation hot spot of the dystrophin gene. Gene 2006; 370: 26–33. PMID: 16439068 39. Juan-Mateu J, González-Quereda L, Rodríguez MJ, Verdura E, Lázaro K, Jou C, et al. Interplay between DMD point mutations and splicing signals in Dystrophinopathy phenotypes. PLoS One 2013 8 (3):e59916 40. Juan-Mateu J, Paradas C, Olive M, Verdura E, Rivas E, Gonzalez-Quereda L, et al. Isolated cardiomy- opathy caused by a DMD nonsense mutation in somatic mosaicism: Genetic normalization in skeletal muscle. Clin Genet 2012; 82 (6): 574–578. doi: 10.1111/j.1399-0004.2011.01814.x PMID: 22092019 41. Ferlini A, Galie N, Merlini L, Sewry C, Branzi A, Muntoni F. A novel alu-like element rearranged in the dystrophin gene causes a splicing mutation in a family with X-linked dilated cardiomyopathy. Am J Hum Genet 1998; 63 (2): 436–446. PMID: 9683584 42. Sedlackova J, Vondracek P, Hermanova M, Zamecnik J, Hruba Z, Haberlova J, et al. Point mutations in czech DMD/BMD patients and their phenotypic outcome. Neuromuscul Disord 2009; 19 (11): 749– 753. doi: 10.1016/j.nmd.2009.08.011 PMID: 19783145 43. Rybakova IN, Humston JL, Sonnemann KJ, Ervasti JM. Dystrophin and utrophin bind actin through dis- tinct modes of contact. J Biol Chem 2006; 281 (15): 9996–10001. PMID: 16478721 44. Singh SM, Kongari N, Cabello-Villegas J, Mallela KM. References Takeshima Y, Yagi M, Okizuka Y, Awano H, Zhang Z, Yamauchi Y, et al. Mutation spectrum of the dys- trophin gene in 442 Duchenne/Becker muscular dystrophy cases from one japanese referral center. J Hum Genet 2010; 55 (9): 379–388. 23. Aartsma-Rus A, Van Deutekom JC, Fokkema IF, Van Ommen GJ, Den Dunnen JT. Entries in the leiden duchenne muscular dystrophy mutation database: An overview of mutation types and paradoxical cases that confirm the reading-frame rule. Muscle Nerve 2006; 34 (2): 135–144. PMID: 16770791 24. White SJ, den Dunnen JT. Copy number variation in the genome; the human DMD gene as an exam- ple. Cytogenet Genome Res 2006; 115 (3–4): 240–246. PMID: 17124406 25. Zhong M, Pan SY, Lu BX, Jiang L, Li W. Cloning and sequencing of the junction fragment of dystrophin gene with exons 3 to 5 deletion. Nan Fang Yi Ke Da Xue Xue Bao 2006; 26 (6): 757–759. PMID: 16793593 26. Hu XY, Ray PN, Murphy EG, Thompson MW, Worton RG. Duplicational mutation at the duchenne mus- cular dystrophy locus: Its frequency, distribution, origin, and phenotype genotype correlation. Am J Hum Genet 1990; 46 (4): 682–695. PMID: 2316519 27. Shaffer LG, Lupski JR. Molecular mechanisms for constitutional chromosomal rearrangements in humans. Annu Rev Genet 2000; 34: 297–329. PMID: 11092830 28. Helleday T. Pathways for mitotic homologous recombination in mammalian cells. Mutat Res 2003; 532 (1–2): 103–115. PMID: 14643432 29. Ji Y, Eichler EE, Schwartz S, Nicholls RD. Structure of chromosomal duplicons and their role in mediat- ing human genomic disorders. Genome Res 2000; 10 (5): 597–610. PMID: 10810082 30. Emanuel BS, Shaikh TH. Segmental duplications: An 'expanding' role in genomic instability and dis- ease. Nat Rev Genet 2001; 2 (10): 791–800. PMID: 11584295 31. Stankiewicz P, Lupski JR. Molecular-evolutionary mechanisms for genomic disorders. Curr Opin Genet Dev 2002; 12 (3): 312–319. PMID: 12076675 32. Deininger PL, Batzer MA. Alu repeats and human disease. Mol Genet Metab 1999; 67 (3): 183–193. PMID: 10381326 18 / 21 PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 A Deep Molecular Analysis in 576 Dystrophinopathy Families 33. Grimm T, Meng G, Liechti-Gallati S, Bettecken T, Muller CR, Müller B. On the origin of deletions and point mutations in duchenne muscular dystrophy: Most deletions arise in oogenesis and most point mutations result from events in spermatogenesis. J Med Genet 1994; 31 (3): 183–186. PMID: 8014964 34. PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 References Missense mutations in dystrophin that trigger muscular dystrophy decrease protein stability and lead to cross-beta aggregates. Proc Natl Acad Sci U S A 2010; 107 (34): 15069–15074. doi: 10.1073/pnas.1008818107 PMID: 20696926 45. Norwood FL, Sutherland-Smith AJ, Keep NH, Kendrick-Jones J. The structure of the N-terminal actin- binding domain of human dystrophin and how mutations in this domain may cause duchenne or becker muscular dystrophy. Structure 2000; 8 (5): 481–491. PMID: 10801490 46. Prior TW, Papp AC, Snyder PJ, Burghes AH, Bartolo C, Sedra MS, et al. A missense mutation in the dystrophin gene in a duchenne muscular dystrophy patient. Nat Genet 1993; 4 (4): 357–360. PMID: 8401582 47. Hamed SA, Hoffman EP. Automated sequence screening of the entire dystrophin cDNA in duchenne dystrophy: Point mutation detection. Am J Med Genet B Neuropsychiatr Genet 2006; 141B (1): 44–50. PMID: 16331671 48. Henderson DM, Lee A, Ervasti JM. Disease-causing missense mutations in actin binding domain 1 of dystrophin induce thermodynamic instability and protein aggregation. Proc Natl Acad Sci U S A 2010; 107 (21): 9632–9637. doi: 10.1073/pnas.1001517107 PMID: 20457930 49. Acsadi G, Moore SA, Cheron A, Delalande O, Bennett L, Kupsky W, et al. Novel mutation in spectrin- like repeat 1 of dystrophin central domain causes protein misfolding and mild becker muscular dystro- phy. J Biol Chem 2012; 287 (22): 18153–18162. doi: 10.1074/jbc.M111.284521 PMID: 22453924 50. Legardinier S, Legrand B, Raguenes-Nicol C, Bondon A, Hardy S, Tascon C, et al. A two-amino acid mutation encountered in duchenne muscular dystrophy decreases stability of the rod domain 23 (R23) spectrin-like repeat of dystrophin. J Biol Chem 2009; 284 (13): 8822–8832. doi: 10.1074/jbc. M805846200 PMID: 19158079 51. Broderick MJ, Winder SJ. Spectrin, alpha-actinin, and dystrophin. Adv Protein Chem 2005; 70: 203– 246. PMID: 15837517 52. Bhasin N, Law R, Liao G, Safer D, Ellmer J, Discher BM, et al. Molecular extensibility of mini-dystro- phins and a dystrophin rod construct. J Mol Biol 2005; 352 (4): 795–806. PMID: 16139300 19 / 21 PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 A Deep Molecular Analysis in 576 Dystrophinopathy Families 53. England SB, Nicholson LV, Johnson MA, Forrest SM, Love DR, Zubrzycha-Gaarn EE, et al. Very mild muscular dystrophy associated with the deletion of 46% of dystrophin. Nature 1990; 343 (6254): 180– 182. PMID: 2404210 54. Sakamoto M, Yuasa K, Yoshimura M, Yokota T, Ikemoto T, Suzuki M, et al. References Micro-dystrophin cDNA ameliorates dystrophic phenotypes when introduced into mdx mice as a transgene. Biochem Biophys Res Commun 2002; 293 (4): 1265–1272. PMID: 12054513 55. Harper SQ, Crawford RW, DelloRusso C, Chamberlain JS. Spectrin-like repeats from dystrophin and alpha-actinin-2 are not functionally interchangeable. Hum Mol Genet 2002; 11 (16): 1807–1815. PMID: 12140183 56. Amann KJ, Renley BA, Ervasti JM. A cluster of basic repeats in the dystrophin rod domain binds F-actin through an electrostatic interaction. J Biol Chem 1998; 273 (43): 28419–28423. PMID: 9774469 57. Bhosle RC, Michele DE, Campbell KP, Li Z, Robson RM. Interactions of intermediate filament protein synemin with dystrophin and utrophin. Biochem Biophys Res Commun 2006; 346 (3): 768–777. PMID: 16777071 58. Yamashita K, Suzuki A, Satoh Y, Ide M, Amano Y, Masuda-Hirata M, et al. The 8th and 9th tandem spectrin-like repeats of utrophin cooperatively form a functional unit to interact with polarity-regulating kinase PAR-1b. Biochem Biophys Res Commun 2010; 391 (1): 812–817. doi: 10.1016/j.bbrc.2009.11. 144 PMID: 19945424 59. Lai Y, Thomas GD, Yue Y, Yang HT, Li D, Long C, et al. Dystrophins carrying spectrin-like repeats 16 and 17 anchor nNOS to the sarcolemma and enhance exercise performance in a mouse model of mus- cular dystrophy. J Clin Invest 2009; 119 (3): 624–635. doi: 10.1172/JCI36612 PMID: 19229108 60. DeWolf C, McCauley P, Sirorski AF, Winlove CP, Bailey AI, Kahana E, et al. Interaction of dystrophin fragments with model membranes. Biophys J 1997; 72: 2599–2604. PMID: 9168035 61. Burkhard P, Stetefeld J, Strelkov SV. Coiled coils: A highly versatile protein folding motif. Trends Cell Biol 2001; 11 (2): 82–88. PMID: 11166216 62. Legrand B, Giudice E, Nicolas A, Delalande O, Le Rumeur E. Computational study of the human dys- trophin repeats: Interaction properties and molecular dynamics. PLoS One 2011; 6 (8): e23819. doi: 10.1371/journal.pone.0023819 PMID: 21901138 63. Delorenzi M, Speed T. An HMM model for coiled-coil domains and a comparison with PSSM-based pre- dictions. Bioinformatics 2002; 18 (4): 617–625. PMID: 12016059 64. Ponting CP. Novel domains in NADPH oxidase subunits, sorting nexins, and PtdIns 3-kinases: Binding partners of SH3 domains? Protein Sci 1996; 5 (11): 2353–2357. PMID: 8931154 65. Legge GB, Martinez-Yamout MA, Hambly DM, Trinh T, Lee BM, Dyson HJ, et al. ZZ domain of CBP: An unusual zinc finger fold in a protein interaction module. J Mol Biol 2004; 343 (4): 1081–1093. PMID: 15476823 66. Campbell KP, Kahl SD. PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 References Association of dystrophin and an integral membrane glycoprotein. Nature 1989; 338 (6212): 259–262. PMID: 2493582 67. Suzuki A, Yoshida M, Yamamoto H, Ozawa E. Glycoprotein-binding site of dystrophin is confined to the cysteine-rich domain and the first half of the carboxy-terminal domain. FEBS Lett 1992; 308 (2): 154– 160. PMID: 1499724 68. Jung D, Yang B, Meyer J, Chamberlain JS, Campbell KP. Identification and characterization of the dys- trophin anchoring site on beta-dystroglycan. J Biol Chem 1995; 270 (45): 27305–27310. PMID: 7592992 69. Ishikawa-Sakurai M, Yoshida M, Imamura M, Davies KE, Ozawa E. ZZ domain is essentially required for the physiological binding of dystrophin and utrophin to beta-dystroglycan. Hum Mol Genet (2004) 13 (7): 693–702. PMID: 14962982 70. Hnia K, Zouiten D, Cantel S, Chazalette D, Hugon G, Fehrentz JA, et al. ZZ domain of dystrophin and utrophin: Topology and mapping of a beta-dystroglycan interaction site. Biochem J 2007; 401 (3): 667– 677. PMID: 17009962 71. Huang X, Poy F, Zhang R, Joachimiak A, Sudol M, Eck MJ. Structure of a WW domain containing frag- ment of dystrophin in complex with beta-dystroglycan. Nat Struct Biol 2000; 7 (8): 634–638. PMID: 10932245 72. Tokarz SA, Duncan NM, Rash SM, Sadeghi A, Dewan AK, Pillers DA. Redefinition of dystrophin iso- form distribution in mouse tissue by RT-PCR implies role in nonmuscle manifestations of duchenne muscular dystrophy. Mol Genet Metab 1998; 65 (4): 272–281. PMID: 9889014 73. Desguerre I, Christov C, Mayer M, Zeller R, Becane HM, Bastuji-Garin S, et al. Clinical heterogeneity of duchenne muscular dystrophy (DMD): Definition of sub-phenotypes and predictive criteria by long-term follow-up. PLoS One 2009; 4 (2): e4347. doi: 10.1371/journal.pone.0004347 PMID: 19194511 20 / 21 PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 A Deep Molecular Analysis in 576 Dystrophinopathy Families 74. Moizard MP, Toutain A, Fournier D, Berret F, Raynaud M, Billard C, et al. Severe cognitive impairment in DMD: Obvious clinical indication for Dp71 isoform point mutation screening. Eur J Hum Genet 2000; 8 (7): 552–556. PMID: 10909857 74. Moizard MP, Toutain A, Fournier D, Berret F, Raynaud M, Billard C, et al. Severe cognitive impairment in DMD: Obvious clinical indication for Dp71 isoform point mutation screening. Eur J Hum Genet 2000; 8 (7): 552–556. PMID: 10909857 75. Becker K, Robb SA, Hatton Z, Yau SC, Abbs S, Roberts RG. PLOS ONE \| DOI:10.1371/journal.pone.0135189 August 18, 2015 References Loss of a single amino acid from dystro- phin resulting in duchenne muscular dystrophy with retention of dystrophin protein. Hum Mutat 2003; 21 (6): 651. 76. Sommer SS. Recent human germ-line mutation: Inferences from patients with hemophilia B. Trends Genet 1995; 11 (4): 141–147. PMID: 7732592 77. Kondrashov AS. Direct estimates of human per nucleotide mutation rates at 20 loci causing mendelian diseases. Hum Mutat 2003; 21 (1): 12–27. PMID: 12497628 78. Krawczak M, Ball EV, Cooper DN. Neighboring-nucleotide effects on the rates of germ-line single- base-pair substitution in human genes. Am J Hum Genet 1998; 63 (2): 474–488. PMID: 9683596 79. Consortium CSaA. Initial sequence of the chimpanzee genome and comparison with the human genome. Nature 2005; 437 (7055):69–87. PMID: 16136131 79. Consortium CSaA. Initial sequence of the chimpanzee genome and comparison with the human genome. Nature 2005; 437 (7055):69–87. PMID: 16136131 21 / 21
https://openalex.org/W2911542067	http://www.scielo.br/pdf/tce/v27n4/en_0104-0707-tce-27-04-e4190017.pdf	English	null	FATORES ASSOCIADOS AO ALEITAMENTO MATERNO NA PRIMEIRA HORA DE VIDA EM UM HOSPITAL AMIGO DA CRIANÇA	Texto & contexto enfermagem	2,018	cc-by	5,772	Original Article Original Article http://dx.doi.org/10.1590/0104-07072018004190017 ABSTRACT Objective: to evaluate the factors associated with the practice of breastfeeding in the first hour after delivery. ve cross-sectional study whose sample consisted of 244 postpartum women hospitalized at the Obstetric Wards an t the Hospital das Clínicas, Recife, Brazil. Method: a quantitative cross-sectional study whose sample consisted of 244 postpartum women hospitalized at Rooming-in Wards at the Hospital das Clínicas, Recife, Brazil. Results: the rate of breastfeeding in the first hour of life was 28.7%. Among sociodemographic variables, not one presented a protective factor for breastfeeding in the first hour postpartum with p-value>0.05. By adjusting the final Poisson model, it was observed that the factors associated with this practice were the presence of the nurse in the delivery room (p <0.001), the weight of the newborn being equal to or greater than three kilos (p 0.05) and skin-to-skin contact between mother and child (p 0.003). Conclusion: in the first hour of life after delivery, the practice of breastfeeding fell short of what is recommended by the World Health Organization, despite the institution considered as a baby-friendly hospital. The main factors associated with this practice were vaginal delivery, the nurse, and skin-to-skin contact between mother and child. DESCRIPTORS: Breast feeding. Delivery rooms. Obstetric nursing. Women’s health. Milk. human FACTORS ASSOCIATED WITH BREASTFEEDING IN THE FIRST HOUR OF LIFE IN A BABY-FRIENDLY HOSPITAL1 Juliane Lima Pereira da Silva2, Francisca Márcia Pereira Linhares3, Amanda de Almeida Barros4, Auricarla Gonçalves de Souza5, Danielle Santos Alves6, Priscyla de Oliveira Nascimento Andrade7 1 Article extracted from the final course assignment - Breastfeeding in the first hour of life in a baby-friendly hospital, presented to the Nursing Residency Program of the Hospital das Clínicas da Universidade Federal de Pernambuco (UFPE), in 2017. g 5 Nursing Student. UFPE. Recife, Pernambuco, Brazil. E-mail: aury.kk@hotmail.com g 5 Nursing Student. UFPE. Recife, Pernambuco, Brazil. E-mail: aury.kk@hotmail.com g y 6 M.Sc. in Health Sciences. Professor of the Nursing Faculty of UFPE. Recife, Pernambuco, Brazil. E-mail: angeldannyalves@gmail.com 7 M.Sc. in Nursing. Substitute Professor of the Nursing Faculty of UFPE. Recife, Pernambuco, Brazil. E-mail: pricila_nas@yahoo.com.br INTRODUCTION to breastfeeding in the first hour of life after delivery for healthy mothers and newborns between 0 and 29% as ‘very poor’, between 30 and 49% as ‘bad’, 50-89% as ‘good’ and 90 to 100% as ‘very good’.7 The Ministry of Health recommends that breastfeeding should take place exclusively from birth to six months of age and continue in asso ciation with other foods up to two years of age or older.1-2 This recommendation is based on the benefits that breast milk can bring to the health of the child, the woman, the family and the environ ment. For the child’s health, breast milk has an immunological protection factor, since it contains Immunoglobulin A, which protects the newborn against intestinal infections, allergies and other conditions.3 Many strategies are being implement ed by international organizations with the objective of promoting, encouraging and supporting breast feeding. The United Nations Children’s Fund to gether with the World Health Organization (WHO) set up the Baby-Friendly Hospital, whose initiative recommends ten steps to successful breastfeeding. Among these steps, it is worth noting the fourth step that recommends placing newborns (NBs) in contact with their mothers immediately after birth for a period of at least one hour.1 There are still barriers that impede the effec tiveness of this fourth step and its implantation in health institutions. Thus, care for the newborn has been established as one of the practices that hinder skin-to-skin contact of the mother-baby binomial, and consequently, breastfeeding.8 The type of deliv ery also influences breastfeeding. Cesarean section is considered a risk factor for women as it performed under anesthesia, which prevents the mother from full arm movement and thus limits the contact be tween mother and baby.9 Thus, all the health care professionals who work in the delivery room are responsible for the act of early breastfeeding, among them, the nursing professional. This professional has the role of facili tator with regard to early breastfeeding, especially when providing information and assisting in the management of breastfeeding in the delivery room. The nurse must encourage the other health profes sionals present at the birth, to understand more about the awareness, information and integration regarding the program and support breastfeeding in the first hour of life. RESUMO bjetivo: avaliar os fatores associados à prática do aleitamento materno na primeira hora pós-parto. Método: trata-se de um estudo quantitativo, do tipo transversal, cuja amostra foi constituída por 244 puérperas internadas no Centro Obstétrico e Alojamento Conjunto do Hospital das Clínicas, Recife, Brasil. Resultados: a taxa de amamentação na primeira hora de vida foi de 28,7%. Dentre as variáveis sociodemográficas, nenhuma se apresentou como fator de proteção para a amamentação na primeira hora pós-parto com p-valor>0,05. Através do ajuste do modelo de Poisson final observou-se que os fatores associados a esta prática foram a presença do enfermeiro na sala de parto (p<0,001), o peso de recém-nascido ser igual ou maior que de três quilos (p 0,05) e o contato pele a pele entre mãe e filho (p 0,003). Conclusão: a amamentação, na primeira hora pós-parto, ficou aquém do recomendado pela Organização Mundial de Saúde, mesmo a instituição estudada sendo considerada como Hospital Amigo da Criança, e, que os principais fatores associados a esta prática foram o parto vaginal, enfermeiro prestador da assistência ao parto e o contato pele a pele entre mãe e filho. DESCRITORES: Aleitamento materno. Salas de parto. Enfermagem obstétrica. Saúde da Mulher. Leite humano Texto Contexto Enferm, 2018; 27(4):e4190017 Silva JLP, Linhares FMP, Barros AA, Souza AG, Alves DS, Andrade PON 2/9 RESUMEN Objetivo: evaluar los factores asociados a la práctica de la lactancia materna en la primera hora posparto. Objetivo: evaluar los factores asociados a la práctica de la lactancia materna en la primera hora posparto. Método: se trata de un estudio cuantitativo del tipo transversal cuya muestra fue constituida por 244 puérperas inter Método: se trata de un estudio cuantitativo, del tipo transversal, cuya muestra fue constituida por 244 puérpera Obstétrico y Alojamiento Conjunto del Hospital de las Clínicas, Recife, Brasil. Resultados: la tasa de lactancia en la primera hora de vida fue de 28,7%. Entre las variables sociodemográficas, ninguna se presentó como factor de protección para la lactancia en la primera hora postparto con p-valor> 0,05. A través del ajuste del modelo de Poisson final se observó que los factores asociados a esta práctica fueron la presencia del enfermero en la sala de parto (p<0,001), el peso de recién nacido ser igual o mayor que de tres kilos (p 0,05) y el contacto piel a la piel entre madre e hijo (p 0,003). Conclusión: la lactancia, en la primera hora postparto, quedó por debajo de lo recomendado por la Organización Mundial de la Salud, incluso la institución estudiada siendo considerada como Hospital Amigo del Niño, y que los principales factores asociados a esta práctica fueron el parto vaginal, enfermero prestador de la asistencia al parto y el contacto piel a piel entre madre e hijo. DESCRIPTORES: Lactancia materna. Salas de parto. Enfermería obstétrica. Salud de la mujer. Leche humana. Texto Contexto Enferm, 2018; 27(4):e4190017 METHOD A transversal quantitative study. Data col lection was performed at the obstetric wards and rooming in accommodation of a University Hospital accredited with the Baby-Friendly Hospital title. The research participants were hospitalized women in the immediate post-partum period, between May and September 2016. For the purpose of data analysis, a database was created using the 3.5.2 version of the EPI INFO® program, where the database was validated (double entry for later comparison and correction of di vergences). After the validation, the database was exported to version 18 of the SPSS® software, where the analysis was performed. In order to evaluate the personal profile, the characteristics of gestation, the characteristics of the prenatal care, the profile of the birth and the characteristics of the NB, the percentage frequencies were calculated and their distributions were constructed. The chi-square test was used to compare the percentage found in the levels of the evaluated factors and to compare the proportion. All conclusions were made consider ing the significance level of 5%. For the purpose of multivariate analysis the factors that presented sig nificance of up to 10% in the bivariate analysis were included. The Poisson model with robust variance to analyze the risk of breastfeeding of the newborn in the first hour of life after delivery was also applied. For the permanence of the factors in the model the significance level of 5% was estimated. In addition, the confidence intervals for the prevalence ratio and the Wald test were used for the comparison of the risks of breastfeeding the NB in the first hour of life after birth between the levels of the evaluated fac tors. The present study was approved by the ethics committee in research with humans with CAAE number 52519916.0.0000.5208 and protocol number 2,062,869. All participants in the study received the Informed Consent Form. For the mothers who were under the age of 18 , their Term of Assent and the respective Informed Consent Form were conferred by their guardian. INTRODUCTION In order to achieve this goal, it is necessary to acquire scientific knowledge, technical ability and communication.10 Breastfeeding in the delivery room enables the NB to better adapt to extrauterine life, glycemic, car diorespiratory and thermal regulation.4 For mothers, early attachment stimulates the pituitary gland and the production of oxytocin and prolactin, increasing breast milk production. A study carried out with 10,947 infants showed that when breast milk is given on the first day of life, 16% neonatal deaths were avoided, which could reach 22% if breastfeeding is anticipated for the first hour after childbirth.6 This study contributes to the knowledge regarding the main factors that impede the imple mentation of early breastfeeding, and may be the starting point for institutions to start improving the incidence of this practice in hospital settings. This article aims to evaluate the factors associated with the practice of breastfeeding in the first hour of life after delivery. In addition, breastfeeding in the first hour of life is considered an indicator of breastfeeding excel lence. The WHO ranks the percentage of adherence Texto Contexto Enferm, 2018; 27(4):e4190017 Factors associated with breastfeeding in the first hour of life in... 3/9 breastfeeding in the first hour of life after delivery. The completion of some variables related to delivery care (type of delivery, weight of the newborn, Apgar in the first and fifth minutes and cord clamping) were verified by consulting the medical records. METHOD Women who were incapacitated and/or pre vented from breastfeeding due to one or more of the following characteristics were excluded from the study: NB with low birth weight (weight less than 2500g); gestational age <37 weeks (according to first- trimester ultrasonography); newborn hospitalized in the intensive care unit (ICU); mother hospitalized in the ICU; positive serostatus for HIV in the pre natal card or the rapid test performed at maternity hospital; positive for syphilis, hepatitis B and five minute apgar score less than seven. The sample calculation was performed, taking into account the number of participants which was determined by the equation of the sample calculation for the study of the proportion in finite population. Considering a confidence level of 95%, the sample error of 5% and the number of puerperae equal to 660 (the average number of deliveries in one month was 220, so in three months the estimated number of deliveries is 660), it was shown that the required sample size was 243 mothers, thus, 244 interviews were collected. The average of deliveries was calculated using the records of the procedure book of the obstetrical center of the mentioned in stitution. The mothers who entered the service on the pre-defined days for collection were selected until the necessary sample size was reached. The outcome: breastfeeding in the first hour of life after delivery (yes/no) was obtained through an inter view with the mother, through a 24-hour recall and by consulting the medical records. Breastfeeding in the first hour after birth was considered as offering the breast within up to sixty minutes after birth. Independent variables were selected for analysis: personal characteristics (schooling, marital status, parity), gestational characteristics (desire to become pregnant, maternal age, support received by the partner), prenatal care (receiving information about breastfeeding, information about breastfeed ing in the first hour of life after delivery, number of consultations), hospital care (type of delivery, birth weight, newborn Apgar score, neonate given to the mother after delivery, attendance in the delivery room, cord clamping and place of RN care). Sub sequently, the dependent variable was questioned: RESULTS The age of the post-partum women ranged from 11 to 39 years of age, with 54.1% of the women being between 20 and 29 years of age . The majority of the women attended high school (97; 39.8%), were in a civil union (143, 58.6%). Not one sociodemo graphic variables presented as a protective factor for breastfeeding in the first hour of life after delivey with a p-value>0.05 (Table 1). Texto Contexto Enferm, 2018; 27(4):e4190017 Silva JLP, Linhares FMP, Barros AA, Souza AG, Alves DS, Andrade PON 4/9 Table 1 - Distribution of breastfeeding in the first hour of life after delivery according to age, schooling and marital status. Recife, PE, Brazil, 2016. (n = 244) Table 1 - Distribution of breastfeeding in the first hour of life after delivery according to age, schooling and marital status. Recife, PE, Brazil, 2016. (n = 244) Evaluated factor Breastfed in the first hour postpartum p-value* Yes No Age 11 -19 years old 15(31.2%) 33(68.8%) 0.409 20 - 29 years old 37(28.0%) 95(72.0%) 30 - 39 years old 15(25.4%) 44(74.6%) Older than 39 years old 3(60.0%) 2(40.0%) Schooling Illiterate 3(100.0%) 0(0.0%) 0.088 1st grade incomplete 17(27.0%) 46(73.0%) 1st grade complete 20(25.6%) 58(74.4%) 2nd grade complete 30(30.9%) 67(69.1%) 3rd grade complete 0(0.0%) 3(100.0%) Marital status Single 14(29.8%) 33(70.2%) 0.898 Married 17(32.1%) 36(67.9%) Divorced 0(0.0%) 1(100.0%) Civil Union 39(27.3%) 104(72.7%) * p-value of the Fisher´s exact test. * p-value of the Fisher´s exact test. statistically significant (p-value> 0.05). The support received by the companion and the characteristics related to the performance of prenatal care, did not have a significant association with the outcome of the study (Table 2). According to the study, primiparous women presented a higher prevalence of early breastfeeding (29.3%), but with very close percentages to that of multiparous and grand multiparous women, with 28.8% and 25%, respectively, and were therefore not Texto Contexto Enferm, 2018; 27(4):e4190017 Table 2 - Distribution of breastfeeding in the first hour of life after delivery according to the gestational characteristics. Recife, PE, Brazil, 2016. Texto Contexto Enferm, 2018; 27(4):e4190017 RESULTS (n = 244) Evaluated factor Breastfed in the first hour postpartum p-value Yes No Parity Primiparous 34(293%) 82(70.7%) 0.913* Multiparous 30(28.8%) 74(71.2%) Grand multiparous 6(25.0%) 18(75.0%) Received support from companion Yes 60(27.3%) 16(72.7%) 0.139* No 10(41.7%) 14(58.3%) Performed pre-natal care Yes 69(28.8%) 171(71.3%) 1.000† No 1(25.0%) 3(75.0%) Number of pre-natal consultations Table 2 - Distribution of breastfeeding in the first hour of life after delivery according to the gestational characteristics. Recife, PE, Brazil, 2016. (n = 244) ion of breastfeeding in the first hour of life after delivery according to the gestational cife, PE, Brazil, 2016. (n = 244) Texto Contexto Enferm, 2018; 27(4):e4190017 Factors associated with breastfeeding in the first hour of life in... Factors associated with breastfeeding in the first hour of life in... Factors associated with breastfeeding in the first hour of life in... 5/9 Up to 3 consultations 3(20.0%) 12(80.0%) 0.698* 4 - 6 consultations 18(27.7%) 47(72.3%) More than 6 consultations 48(30.0%) 112(70.0%) Received orientation regarding breastfeeding during pre-natal Yes 45(30.4%) 103(69.6%) 0.472 No 24(26.1%) 68(73.9%) Received orientation regarding the importance of breastfeeding in the first hour after birth Yes 31(32.3%) 65(67.7%) 0.322* No 38(26.4%) 106(73.6%) * p-value of the Chi-square test; † p-value of Fisher’s exact test. very (p 0.009). In addition, the nurse as a caregiver (p 0.001), skin-to-skin contact between mother and child (p 0.001) and late clamping of the umbilical cord, (p.0.011) (Table 3). very (p 0.009). In addition, the nurse as a caregiver (p 0.001), skin-to-skin contact between mother and child (p 0.001) and late clamping of the umbilical cord, (p.0.011) (Table 3). Among the characteristics of the delivery and the newborn, the ones that presented as protection factors for the fourth step of the Baby-Friendly Hos pital Initiative (BFHI) were the type of vaginal deli Table 3 - Distribution of breastfeeding in the first hour of life after delivery according to characteristics of delivery and newborn. Recife, PE, Brazil, 2016. Texto Contexto Enferm, 2018; 27(4):e4190017 RESULTS (n=244) Evaluated factor Breastfed in the first hour postpartum p-value Yes No Type of delivery Vaginal 45(35.4%) 82(64.6%) 0.009 Cesarean 23(20.2%) 91(79.8%) Professionals in the delivery room Nurse 7(77.8%) 2(22.2%) 0.003† Doctor 63(26.8%) 172(73.2%) Companion present Yes 31(33.3%) 62(66.7%) 0.208* No 39(25.8%) 112(74.2%) Newborn weight Less than 3000g 10(18.9%) 43(81.1%) 0.074* 3000g or more 60(31.4%) 131(68.6%) 1st minute Apgar < 7 2(11.8%) 15(88.2%) 0.171† 7 2(18.2%) 9(81.8%) 8 13(22.0%) 46(78.0%) 9 47(33.1%) 95(66.9%) 10 6(40.0%) 9(60.0%) 5 minute Apgar 8 2(11.1%) 16(88.9%) 0.058* 9 15(22.4%) 52(77.6%) 10 53(33.3%) 106(66.7%) Newborn and mother skin to skin contact Table 3 - Distribution of breastfeeding in the first hour of life after delivery according to characteristics of delivery and newborn. Recife, PE, Brazil, 2016. (n=244) eastfeeding in the first hour of life after delivery according to characteristics Recife, PE, Brazil, 2016. (n=244) Texto Contexto Enferm, 2018; 27(4):e4190017 Silva JLP, Linhares FMP, Barros AA, Souza AG, Alves DS, Andrade PON 6/9 Yes 55(36.7%) 95(63.3%) 0.001* No 15(16.0%) 79(84.0%) Umbilical cord clamping Early 24(20.9%) 91(79.1%) 0.011* Delayed 46(35.7%) 83(64.3%) Place of newborn care In contact with the mother 2(66.7%) 1(33.3%) 0.199† Away from the mother 68(28.2%) 173(71.8%) * p-value of the Chi-square test; † p-value of Fisher’s exact test. * p-value of the Chi-square test; † p-value of Fisher’s exact test. the risk of the event occurring when the nurse is the professional who provides care during childbirth, when the weight of the infant is equal to or greater than 3000g and when there is skin-to-skin contact between the mother and child. (Table 4). the risk of the event occurring when the nurse is the professional who provides care during childbirth, when the weight of the infant is equal to or greater than 3000g and when there is skin-to-skin contact between the mother and child. (Table 4). Table 4 shows the adjustment of the final Poisson model with the variables that showed sig nificance for the breastfeeding of the NB in the first hour of life after delivery. It is observed that the Wald test was significant; indicating an increase in Table 4 - Adjusted Poisson model for newborn breastfeeding in the first hour of life after delivery. Recife, PE, Brazil, 2016. Evaluated factor difficulties related to the practice of breastfeeding in the first hour post childbirth are expected. RESULTS (n = 244) Evaluated factor PR* CI†(95%) p-value Professionals in the delivery room Nurse 2.41 1.72 - 3.37 <0.001 Doctor 1.00 - - Weight of the newborn Less than 3000g 1.00 - - 3000g or more 1.80 1.00 - 3.24 0.050 Newborn and mother skin to skin contact Yes 2.17 1.30 - 3.64 0.003 No 1.00 - - *RP=Prevalence Ratio; †CI= Confidence interval; p-value of the Wald statistic (if -value <0.05 the risk adhesion is significantly higher than the reference group. Table 4 - Adjusted Poisson model for newborn breastfeeding in the first hour of life after delivery. Recife, PE, Brazil, 2016. (n = 244) son model for newborn breastfeeding in the first hour of life after delivery. n = 244) Texto Contexto Enferm, 2018; 27(4):e4190017 DISCUSSION It is worth emphasizing that support from social net works may be a relevant factor in the explanation of the higher prevalence of early breastfeeding.14 known that this type of delivery delays the woman’s journey to the rooming-in accommodation.11 The proportion of caesarean sections from the current research was 46.7%; (10 to 15%).16 Although this type of delivery is associated with maternal death, infections and prematurity, its occurrence remains high and is of worldwide concern.13 In this study, the presence of a companion in the delivery room was also not relevant in the signif icant association with breastfeeding in the first hour of life after delivery. The presence of a companion in the delivery room is understood as a strategy to reduce the time of the first breastfeeding,14 however, this practice remains scarce, especially in surgical deliveries, due to the professionals not allowing the companions to enter, justifying their decisions because of the risk of infection; even if the rights of these women are assured by the Companion Law Number 2.418 of December 2, 2005.17 The presence of nurses in the delivery room, as a protective factor for early breastfeeding, concurs with a study carried out in Teresina, whose objective was to describe the perception of the new mother regarding the promotion of breastfeeding in the first hour of life after delivery by the professionals of nursing. The aforementioned study confirms that the nurse is the professional who ensures the accom plishment of the fourth step of the BFHI, since they play an essential role in the preparation of the new mothers, helping them to breastfeed and overcome the adversities that comes with this practice.18 It was observed that the primiparous women had a higher rate of early breastfeeding, different from another previous study, where multiparity was shown to be a protective factor, since these women already had previous experience with breastfeed ing and, consequently, they had less doubts and insecurities about this practice.14 Prenatal care in this study was not associated with the outcome, which differs from previous research, where women were heavily protected re garding breastfeeding their children in the first hour of life after delivery. DISCUSSION The issues related to the success of breastfeed ing should be seen from a variety of angles such as: culture, knowledge about the subject, family support among others.11 Although breastfeeding in the first hour of life is an indicator of excellence in breastfeeding practices, being a factor of protection for the survival and development of children in the first months of life remains a recent goal, and it is understandable that their results have not been reached as expected.12 Thus, the data analyzed in this study need to be contextualized . As the study was performed in a hospital, with a high demand for complicated obstetric cases (medium and high risk), In the present study, the rate of breastfeed ing in the first hour of life was 28.7%, similar to a survey conducted in Vitória, where the rate was 30%.12 However, the rate as lower than the studies conducted in Rio de Janeiro and Fortaleza, which indicated a prevalence of 50.8% and 63.5%, respec tively.11-13 The possible hypothesis for this higher rate is mentioned in the mentioned studies may be related to the greater number of beds in the rooming-in accommodation in those services.11 Age, schooling and marital status were not independent determinants in this study; probably Texto Contexto Enferm, 2018; 27(4):e4190017 Factors associated with breastfeeding in the first hour of life in... 7/9 due to their effects mediated by factors closer to the outcome. Women over the age of 39 showed increased breastfeeding in the first hour of life of the child, similar to the results of a systematic review, which showed the delayed initiation of breastfeed ing in younger women, a fact that may be related to the lack of experience and confidence among these women.13 According to the present study, illiterate women presented higher rates of early breastfeed ing related to those who had higher schooling, cor roborating the event with other studies, which call attention to the accomplishment of the procedure of the cesarean section, which may explain the de lay of this practice in women with higher levels of education,13-14 being aware that in the present study the relationship between schooling and the type of delivery was not analysed. According to a study in Rio de Janeiro, married women were more likely to initiate breastfeeding in the delivery room. Texto Contexto Enferm, 2018; 27(4):e4190017 DISCUSSION Prenatal care should encom pass comprehensive care (promotion, prevention of illness and recovery of health) and as well receiving information on breastfeeding, allowing the mother to be prepared for this act in the delivery room.14-15 Nursing care, in this first contact with breast feeding, is advisable because the professional acts as a facilitator, demystifying beliefs, myths and taboos surrounding the act of breastfeeding. The nurse is considered the professional who becomes the closest with the woman, having an important role in health education, encouraging and supporting the act of breastfeeding through her actions, giving mothers confidence in their ability to breastfeed. The com mitment of nursing becomes a determining factor to consolidate the right to breastfeed in the first hour of the child’s life. Nursing is responsible for humanized care, reducing discomforts and making the breastfeeding experience pleasant for the dyad.18 The type of delivery had a significant as sociation (p-value 0.009) with the outcome; and vaginal delivery was considered a protective factor. This finding confirms the results of other studies, where there is agreement that in vaginal delivery, the woman is able to participate more actively and is more likely to put the newborn in direct contact with her body, and be able to recognize when the child is ready to breastfeed.13-15 Skin-to-skin contact is advocated by WHO, and act facilitates breastfeeding in the first hour of life, is helps the neonate to be alert, and thus, can suck more effectively. Therefore, the NB creates a bond with the mother, they are warmed and receive the colostrum which serves as the first type of im munization. This contact should be encouraged as, in addition to the benefits for the child, this moment Caesarean section was seen as an obstacle to the initiation of breastfeeding due to the effect of anaesthesia, since women do not have an adequate position to support the child, in addition to the postoperative care routine, which delays skin-to- skin contact between mother and child.13 It is also Texto Contexto Enferm, 2018; 27(4):e4190017 Silva JLP, Linhares FMP, Barros AA, Souza AG, Alves DS, Andrade PON 8/9 routine still encounters several barriers that need to be overcome. Thus, it is recommended that future studies consider the use of direct observation of the practice of breastfeeding in the first hour of life within the delivery room. DISCUSSION is also of prime importance to the woman as it will be remembered as a positive experience.18 The pres ent study also agrees with another study, which demonstrated a positive association between joint accommodation with early breastfeeding, as skin- to-skin contact is more easily done in this type of accommodation. Mothers who were put in the same room as their baby were nine times more likely to feed their baby in the first hour of life.12 REFERENCES 1. Ministério da Saúde (BR) Iniciativa Hospital Amigo da Criança: diretrizes de ação para o SUS. Brasília, (DF): MS; 2008. 1. Ministério da Saúde (BR) Iniciativa Hospital Amigo da Criança: diretrizes de ação para o SUS. Brasília, (DF): MS; 2008. 2. Guimarães CMS; Conde RG; Brito BC, Sponholz FAG, Oriá MOB, Monteiro JCS. Comparação da autoeficácia na amamentação entre puérperas adolescentes e adultas em uma maternidade de Ribeirão Preto, Brasil. Texto Contexto Enferm [Internet]. 2017 Mar [cited 23 Nov 2017]; 26(1). Available form: http://www.scielo.br/scielo. php?pid=S010407072017000100310&script=sci_ arttext&tlng=pt 2. Guimarães CMS; Conde RG; Brito BC, Sponholz FAG, Oriá MOB, Monteiro JCS. Comparação da autoeficácia na amamentação entre puérperas adolescentes e adultas em uma maternidade de Ribeirão Preto, Brasil. Texto Contexto Enferm [Internet]. 2017 Mar [cited 23 Nov 2017]; 26(1). Available form: http://www.scielo.br/scielo. php?pid=S010407072017000100310&script=sci_ arttext&tlng=pt The limitation of this study is the lack of ob servation of the studied phenomenon, and that the study was based on the memory of the post-partum woman. 3. 3. Boccolini CS, Carvalho ML, Oliveira MIC, Escamilha RPA. Amamentação na primeira hora de vida e mortalidade neonatal. J Pediatr [Internet]. 2013 Mar/Abr [cited 23 Nov 2017]; 89(2):131. Available form: http://www.scielo.br/scielo.php?script=sci_ arttext&pid=S0021-75572013000200005 Acknowledgements We would like thank the Hospital das Clínicas of the Universidade Federal de Pernambuco, in par ticular rooming-in accommodation and obstetric departments. The weight of the NB being equal to or greater than 3000 grams was also positively associated with the outcome of breastfeeding in the first hour of life after delivery. A survey conducted in Rio de Janeiro found similar findings and showed that low-weight babies were less likely to breast-feed compared to children of adequate weight. The need for special care could justify these results, however, it is important to note that unnecessary practices are performed in the hospital environment, making it difficult to comply with the fourth step of BFHI, and neonates with health problems were excluded from the sample in this study.14 The weight of the NB being equal to or greater than 3000 grams was also positively associated with the outcome of breastfeeding in the first hour of life after delivery. A survey conducted in Rio de Janeiro found similar findings and showed that low-weight babies were less likely to breast-feed compared to children of adequate weight. The need for special care could justify these results, however, it is important to note that unnecessary practices are performed in the hospital environment, making it difficult to comply with the fourth step of BFHI, and neonates with health problems were excluded from the sample in this study.14 CONCLUSION The protective factors of the practice of breast feeding in the first hour of life were the presence of the nurse professional in the delivery room, the weight of the RN being equal to or greater than 3000 grams and the skin-to-skin contact between mother and son. Therefore, it is concluded, that breastfeeding in the first hour of life after delivery was below the WHO recommendation, despite that the institution is certified as a Baby-Friendly Hos pital. It must be emphasized that this action needs to be maximized only when it is possible and safe. Precautionary factors such as delayed release of the HIV test result should be monitored. The results also showed the importance of an adequate indication for caesarean section delivery and the encourage ment of vaginal delivery by institutions, as the rates for caesarean section were high compared to the WHO recommendations. 4. Esteves TMB, Daumas RP, Oliveira MIC, Andrade CAF, Leite IC. Fatores Associados à amamentação na primeira hora de vida: revisão sistemática. Rev Saude Publica [Internet]. 2014 Ago [cited 23 Nov 2017]; 48(4):697-703. Available form: http://www.scielo.br/scielo.php?pid=S0034- 89102014000400697&script=sci_arttext&tlng=pt 5. Monteiro JCS, Gomes FA, Nakano AMS. Percepção das mulheres acerca do contato precoce e da amamentação em sala de parto. Acta Paul Enferm [Internet]. 2006 Ago [cited 23 Nov 2017]; 19(4):427- 32. Available form: http://www.scielo.br/scielo. php?pid=S0103-21002006000400010&script=sci_ abstract&tlng=eses 6. Edmond KM, Zandoh C, Quigley MA, Amenga- etego S, Owusu-agyeis, Kirkwood BR. Delayed breastfeeding initiation increases risk of neonatal mortality. Pediatrics [Internet]. 2006 Mar [cited 23 Nov 2017]; 117(3):380-6. Available form: http:// pediatrics.aappublications.org/content/117/3/e380 Educational actions aimed at guiding and sensitizing the professionals who attend women during childbirth should be a practice instituted by the health services. Although there is scientific evidence and recommendations regarding mother and baby proximity directly after delivery, this 7. World Health Organization. The optimal duration of exclusive breastfeeding. Geneva (CH): Report of an Expert Consultation; 2001. 8. Moreira MEL, Gama, SGN, Pereira APE, Silva, Texto Contexto Enferm, 2018; 27(4):e4190017 9/9 Factors associated with breastfeeding in the first hour of life in... AAM, Lansky S, Pinheiro RS, Gonçalves AC, Leal, MC. Práticas de atenção hospitalar ao recém- nascido saudável no Brasil. Cad Saúde Pública [Internet]. 2016 [cited 23 Nov 2017]; 30(1). Available form: http://www.scielo.br/scielo.php?script=sci_ arttext&pid=S0102-311X2014001300019 AAM, Lansky S, Pinheiro RS, Gonçalves AC, Leal, MC. Práticas de atenção hospitalar ao recém- nascido saudável no Brasil. Cad Saúde Pública [Internet]. 2016 [cited 23 Nov 2017]; 30(1). CONCLUSION Available form: http://www.scielo.br/scielo.php?script=sci_ arttext&pid=S0102-311X2014001300019 13. Esteves TMB, Daumas RP, Oliveira MIC, Andrade CAF, Leite IC. Fatores associados ao início tardio da amamentação em hospitais do Sistema Único de Saúde no Município do Rio de Janeiro, Brasil, 2009. Cad Saúde Pública [Internet]. 2015 Nov [cited 23 Nov 2017]; 31(11):2390-400. Available form: http:// www.scielosp.org/pdf/csp/v31n11/0102-311X- csp-31-11-2390.pdf 9. Vieira F, Salge AKM, Bachion MM, Munari DB. Diagnósticos de enfermagem da nanda no período pós-parto imediato e tardio. Escola Anna Nery Rev Enferm [Internet]. 2010 Jan/ Mar [cited 23 Nov 2017]; 14(1):83-9. Available form: http://www.scielo.br/scielo.php?script=sci_ arttext&pid=S1414-81452010000100013 14. Pereira CRVR, Fonseca VM, Oliveira MIC, Souza IEO, Mello RR. Avaliação de fatores que interferem na amamentação na primeira hora de vida. Rev Bras Epidemiol [Internet]. 2013 [cited 23 Nov 2017]; 16(2):525-34. Available form: http://www. scielo.br/scielo.php?script=sci_arttext&pid=S0102- 311X2014001300019 10. Strapasson MR, Fisher ACS, Bonilha ALL. Amamentação na primeira hora de vida em um hospital privado de Porto Alegre/RS- Relato de experiência. Rev Enferm UFSM [Internet]. 2011 Set/Dez [cited 23 Nov 2017]; 1(3):489-96. Available form: https://periodicos.ufsm.br/reufsm/article/ view/2824 15. Esteves TMB, Daumas RP, Oliveira MIC, Andrade CAF, Leite IC. Fatores Associados à amamentação na primeira hora de vida: revisão Sistemática. Rev Saúde Pública [Internet]. 2014 Ago [cited 23 Nov 2017]; 48(4):697-703. Available form: http://www.scielo.br/scielo.php?pid=S0034- 89102014000400697&script=sci_arttext&tlng=pt 11. Will TK, Arndt JG, Torres GG, Andrade JR, Pereira TSS, Molina MDCB. Fatores de proteção para a amamentação na primeira hora de vida. Rev Bras Promoc Saude [Internet]. 2013Abr/Jun [cited 23 Nov 2017]; 26(2):274-80. Available form: http://www. redalyc.org/articulo.oa?id=40828920016 16. World Health Organization. Infant and young child feeding: a tool for assessing national practices, policies and programmes. Geneva (CH): WHO; 2003. 17. Brasil. Portaria N 2.418, de 2 de dezembro de 2005: dispõe sobre a presença de acompanhante para mulheres em trabalho de parto, parto e pós-parto imediato nos hospitais públicos e conveniados com o SUS. Diário Oficial da República Federativa do Brasil. 12. Belo MNM, Azevedo PTACC, Belo MPN, Serva VMSBD, Filho MB, Figueiroa JN, et al. Aleitamento materno na primeira hora de vida em um Hospital Amigo da Criança: prevalência, fatores associados e razões para sua não ocorrência. Rev Bras Saude Mater Infant [Internet]. 2014 Jan/Mar [cited 23 Nov 2017];14(1):65-72. Available form: http://www.scielo.br/scielo.php?script=sci_ arttext&pid=S1519-382920140001000 18. Leite MFFS, Barbosa PA, Olivindo DDF, Ximenes VL. Promoção do aleitamento materno na primeira hora de vida do recém-nascido por profissionais da enfermagem. Arq Cienc Saúde UNIPAR [Internet]. 2016 Mai/Ago [cited 23 Nov 2017]; 20(2):137-43. Available form: http://revistas.unipar.br/index. CONCLUSION php/saude/article/view/5386 Correspondence: Juliane Lima Pereira da Silva Rua Indianópolis, 116 54768-190 – Timbi, Camaragibe, Pernambuco, Brasil E-mail: juliane_lps@hotmail.com Correspondence: Juliane Lima Pereira da Silva Rua Indianópolis, 116 54768-190 – Timbi, Camaragibe, Pernambuco, Brasil E-mail: juliane_lps@hotmail.com Texto Contexto Enferm, 2018; 27(4):e4190017 Texto Contexto Enferm, 2018; 27(4):e4190017
https://openalex.org/W2141050680	https://dr.ntu.edu.sg/bitstream/10356/106735/1/MicroRNA%20miR-124%20Controls%20the%20choice%20between%20Neuronal%20and%20Astrocyte%20Differentiation%20by%20Fine-tuning%20Ezh2%20Expression.pdf	English	null	MicroRNA miR-124 Controls the Choice between Neuronal and Astrocyte Differentiation by Fine-tuning Ezh2 Expression	Journal of biological chemistry/The Journal of biological chemistry	2,014	cc-by	13,084	Neo, Wen Hao; Yap, Karen; Lee, Suet Hoay; Looi, Liang Sheng; Khandelia, Piyush; Neo, Sheng Xiong; Makeyev, Eugene V.; Su, I‑hsin 2014 Neo, W. H., Yap, K., Lee, S. H., Looi, L. S., Khandelia, P., Neo, S. X., et al. (2014). MicroRNA miR‑124 controls the choice between neuronal and astrocyte differentiation by fine‑tuning Ezh2 expression. Journal of biological chemistry, 289(30), 20788‑20801. Neo, Wen Hao; Yap, Karen; Lee, Suet Hoay; Looi, Liang Sheng; Khandelia, Piyush; Neo, Sheng Xiong; Makeyev, Eugene V.; Su, I‑hsin Neo, Wen Hao; Yap, Karen; Lee, Suet Hoay; Looi, Liang Sheng; Khandelia, Piyush; Neo, Sheng Xiong; Makeyev, Eugene V.; Su, I‑hsin 2014 Neo, W. H., Yap, K., Lee, S. H., Looi, L. S., Khandelia, P., Neo, S. X., et al. (2014). MicroRNA miR‑124 controls the choice between neuronal and astrocyte differentiation by fine‑tuning Ezh2 expression. Journal of biological chemistry, 289(30), 20788‑20801. Neo, W. H., Yap, K., Lee, S. H., Looi, L. S., Khandelia, P., Neo, S. X., et al. (2014). MicroRNA miR‑124 controls the choice between neuronal and astrocyte differentiation by fine‑tuning Ezh2 expression. Journal of biological chemistry, 289(30), 20788‑20801. When a correction for this article is posted • https://hdl.handle.net/10356/106735 © 2014 by The American Society for Biochemistry and Molecular Biology, Inc. Creative Commons Attribution Unported License applies to Author Choice Articles. Downloaded on 24 Oct 2024 12:48:00 SGT Xiong Neo, Eugene V. Makeyev and I-hsin Su Liang Sheng Looi, Piyush Khandelia, Sheng Wen Hao Neo, Karen Yap, Suet Hoay Lee, Expression Differentiation by Fine-tuning Ezh2 between Neuronal and Astrocyte MicroRNA miR-124 Controls the Choice Neurobiology: doi: 10.1074/jbc.M113.525493 originally published online May 30, 2014 2014, 289:20788-20801. J. Biol. Chem. 10.1074/jbc.M113.525493 Access the most updated version of this article at doi: . JBC Affinity Sites Find articles, minireviews, Reflections and Classics on similar topics on the Alerts: When a correction for this article is posted • When this article is cited • to choose from all of JBC's e-mail alerts Click here http://www.jbc.org/content/289/30/20788.full.html#ref-list-1 This article cites 62 references, 20 of which can be accessed free at by guest on August 21, 201 http://www.jbc.org/ Downloaded from by guest on August 21, 201 http://www.jbc.org/ Downloaded from Alerts: Wh ti f thi When this article is cited • MicroRNA miR-124 Controls the Choice between Neuronal and Astrocyte Differentiation by Fine-tuning Ezh2 Expression* Wen Hao Neo‡, Karen Yap‡, Suet Hoay Lee‡, Liang Sheng Looi‡, Piyush Khandelia‡, Sheng Xiong Neo‡, Eugene V. Makeyev‡§, and I-hsin Su‡1 From the ‡Division of Molecular Genetics and Cell Biology, School of Biological Sciences, College of Science, Nanyang Technological University, 60 Nanyang Drive, Singapore 637551, Singapore and the §Medical Research Council Centre for Developmental Neurobiology, King’s College London, New Hunt’s House, Guy’s Hospital Campus, London SE1 1UL, United Kingdom Background: Molecular mechanisms underlying reduced expression of Ezh2 during neural differentiation are poorly understood. Background: Molecular mechanisms underlying reduced expression of Ezh2 during neural differentiation are poorly understood. Results: miR-124 directly down-regulates Ezh2 expression to promote neuronal differentiation. Conclusion: Ezh2 is an important target of miR-124 in the context of neuronal differentiation. Significance: Our report represents a significant advance in understanding the contribution of a microRNA/epigenetic regu- latory circuitry to cell fate determination in the neural lineage. miR-124 directly down-regulates Ezh2 expression to promote neuronal differentiation. Results: miR-124 directly down-regulates Ezh2 expression to promote neuronal differentiation. Conclusion: Ezh2 is an important target of miR-124 in the context of neuronal differentiation. ts: miR-124 directly down-regulates Ezh2 expression to promote neuronal differentiation. usion: Ezh2 is an important target of miR-124 in the context of neuronal differentiation. y g p p on: Ezh2 is an important target of miR-124 in the context of neuronal differentiation. Conclusion: Ezh2 is an important target of miR-124 in the context of neuronal differentiation. Significance: Our report represents a significant advance in understanding the contribution of a m latory circuitry to cell fate determination in the neural lineage. nce: Our report represents a significant advance in understanding the contribution of a microRNA/epi uitry to cell fate determination in the neural lineage. by guest on August 21, 2014 http://www.jbc.org/ Downloaded from Polycomb group protein Ezh2 is a histone H3 Lys-27 histone methyltransferase orchestrating an extensive epigenetic regula- tory program. Several nervous system-specific genes are known to be repressed by Ezh2 in stem cells and derepressed during neuronal differentiation. However, the molecular mechanisms underlying this regulation remain poorly understood. Here we show that Ezh2 levels are dampened during neuronal differen- tiation by brain-enriched microRNA miR-124. Expression of miR-124 in a neuroblastoma cells line was sufficient to up-reg- ulate a significant fraction of nervous system-specific Ezh2 tar- get genes. On the other hand, naturally elevated expression of miR-124 in embryonic carcinoma cells undergoing neuronal differentiation correlated with down-regulation of Ezh2 levels. Xiong Neo, Eugene V. Makeyev and I-hsin Su Liang Sheng Looi, Piyush Khandelia, Sheng Wen Hao Neo, Karen Yap, Suet Hoay Lee, Expression Differentiation by Fine-tuning Ezh2 between Neuronal and Astrocyte MicroRNA miR-124 Controls the Choice Neurobiology: doi: 10.1074/jbc.M113.525493 originally published online May 30, 2014 2014, 289:20788-20801. J. Biol. Chem. 10.1074/jbc.M113.525493 Access the most updated version of this article at doi: . JBC Affinity Sites Find articles, minireviews, Reflections and Classics on similar topics on the Alerts: When a correction for this article is posted • When this article is cited • to choose from all of JBC's e-mail alerts Click here http://www.jbc.org/content/289/30/20788.full.html#ref-list-1 This article cites 62 references, 20 of which can be accessed free at by guest on August 21, 2014 http://www.jbc.org/ Downloaded from by guest on August 21, 2014 http://www.jbc.org/ Downloaded from Xiong Neo, Eugene V. Makeyev and I-hsin Su Liang Sheng Looi, Piyush Khandelia, Sheng Wen Hao Neo, Karen Yap, Suet Hoay Lee, Expression Differentiation by Fine-tuning Ezh2 between Neuronal and Astrocyte MicroRNA miR-124 Controls the Choice Neurobiology: doi: 10.1074/jbc.M113.525493 originally published online May 30, 2014 2014, 289:20788-20801. J. Biol. Chem. Expression Differentiation by Fine-tuning Ezh2 between Neuronal and Astrocyte MicroRNA miR-124 Controls the Choice gy Expression Differentiation by Fine-tuning Ezh2 between Neuronal and Astrocyte MicroRNA miR-124 Controls the Choice gy by guest on August 21, 2014 http://www.jbc.org/ Downloaded from by guest on August 21, 2014 http://www.jbc.org/ Downloaded from 10.1074/jbc.M113.525493 Access the most updated version of this article at doi: When a correction for this article is posted • When this article is cited • When a correction for this article is posted • to choose from all of JBC's e-mail alerts Click here http://www.jbc.org/content/289/30/20788.full.html#ref-list-1 This article cites 62 references, 20 of which can be accessed free at THE JOURNAL OF BIOLOGICAL CHEMISTRY VOL. 289, NO. 30, pp. 20788–20801, July 25, 2014 © 2014 by The American Society for Biochemistry and Molecular Biology, Inc. Published in the U.S.A. THE JOURNAL OF BIOLOGICAL CHEMISTRY VOL. 289, NO. 30, pp. 20788–20801, July 25, 2014 © 2014 by The American Society for Biochemistry and Molecular Biology, Inc. Published in the U.S.A. Author’s Choice MicroRNA miR-124 Controls the Choice between Neuronal and Astrocyte Differentiation by Fine-tuning Ezh2 Expression* Importantly, overexpression of Ezh2 mRNA with a 3-untrans- lated region (3-UTR) lacking a functional miR-124 binding site, but not with the wild-type Ezh2 3-UTR, hampered neuronal and promoted astrocyte-specific differentiation in P19 and embryonic mouse neural stem cells. Overall, our results uncover a molecular mechanism that allows miR-124 to balance the choice between alternative differentiation possibilities through fine-tuning the expression of a critical epigenetic regulator. logical processes in a large fraction of eukaryotic organisms (1, 2). There are estimated to be over 1000 miRNAs in the human genome, and more than 50% of human genes are predicted to be miRNA targets (3, 4). Mature miRNAs regulate their cognate mRNAs as a part of an miRNA-induced silencing complex con- taining an Argonaute protein subunit (5). In plants, miRNAs often bind to fully complementary target sites typically located in the mRNA 3-UTRs, which leads to gene repression through Argonaute-dependent mRNA “slicing” (6). On the other hand, animal miRNAs tend to be partially complementary to their target sequences, which affords regulation of target mRNAs through translational inhibition and slicer-independent desta- bilization (7, 8). miRNAs are known to be crucial for neuronal differentiation, because conditional ablation of the endoribonuclease Dicer, an essential component of the microRNA maturation pathway, in neural stem cells or progenitors leads to dramatic defects in survival and differentiation of newborn neurons (9–11). One of the most abundant and perhaps best studied miRNAs in the brain is miR-124 (12–16). miR-124 is derived from three inde- pendent genes (miR-124-1, miR-124-2, and miR-124-3) con- tributing to the increased mature miR-124 levels during neuro- nal differentiation (4, 17, 18). Interestingly, however, knock-out of just the miR-124-1 gene in the mouse resulted in visible reduction of mature miR-124 levels, defective neuronal sur- vival, and axonal outgrowth as well as smaller brain size (19). Since their discovery in 1993, microRNAs (miRNAs),2 19–25-nucleotide-long non-coding RNA molecules, have emerged as versatile regulators of developmental and physio- miR-124 may regulate hundreds and possibly thousands of distinct target genes (18, 20–23). Important examples include genes encoding the SCP1 subunit of the global repressor of NS-specific genes REST, transcription factors Sox9 and cAMP- response element-binding protein, Notch ligand Jagged1, and the BAF53a subunit of a chromatin remodeling complex (24– 27). We have previously shown that miR-124 also targets mRNA of Ptbp1 (polypyrimidine tract-binding protein), a global regulator of pre-mRNA splicing (11). * This work was supported by research funding from National Medical Research Council Grants NMRC/IRG/1269/2010 (to W. H. N. and I. S.) and NMRC/CBRG/0028/2013 (to E. V. M.) and National Research Foundation Singapore Grant NRF-RF2008-06 (to E. V. M.). Author’s Choice—Final version full access. 1 To whom correspondence should be addressed. Tel.: 65-65138687; Fax: 65-67913858; E-mail: ihsu@ntu.edu.sg. 2 The abbreviations used are: miRNA, microRNA; NS, nervous system; H3K27, histone H3 Lys-27; 3meH3K27, H3K27 trimethylation; N2a, Neuro2a; NSC, neuralstemcell;RT-qPCR,quantitativeRT-PCR;qPCR,quantitativePCR;RA, retinoic acid; EGFP, enhanced GFP. * This work was supported by research funding from National Medical Research Council Grants NMRC/IRG/1269/2010 (to W. H. N. and I. S.) and NMRC/CBRG/0028/2013 (to E. V. M.) and National Research Foundation Singapore Grant NRF-RF2008-06 (to E. V. M.). miR-124 Controls Ezh2 Expression during Neurodifferentiation Interestingly, overexpression of miR-124 in hepatocellular carcinoma cells, where it is normally present at negligibly low levels, has been shown to reduce Ezh2 expression (32). How- ever, whether miR-124 contributes to down-regulation of Ezh2 expression during neurogenesis has not been investigated. p g g g To this end, we first expressed miR-124 in mouse neuroblas- toma Neuro2a (N2a) cells and showed that this treatment was sufficient to up-regulate a significant fraction of neuron-spe- cific Ezh2 target genes. We further found that in P19 cells undergoing neuronal differentiation, the Ezh2 protein level was significantly reduced in an inverse correlation with increasing expression of mature miR-124. Importantly, miR-124-specific antisense inhibitor restored Ezh2 expression in differentiating P19 cells, whereas disruption of the putative miR-124 target site in exogenously expressed Ezh2 3-UTR abolished the miR-124- mediated down-regulation and led to reduced neuronal differ- entiation. A similar effect of miR-124-regulated Ezh2 expres- sion on neurogenesis was also observed in differentiating embryonic mouse neural stem cells. Thus, our results implicate Ezh2 as an important miR-124 target in the context of neuronal differentiation. by guest on August 21, 2014 http://www.jbc.org/ Downloaded from Cell Culture, Nucleofection, and Differentiation of Neural Stem Cells (NSCs)—NSCs were obtained from cortices of mouse embryonic day 14 and maintained in the form of neuro- spheres in complete NeuroCult NSC proliferation medium supplemented with 20 ng/ml recombinant human epidermal growth factor (rhEGF, StemCell Technologies). To overexpress EGFP, Ezh2 with artificial 3-UTR (Ezh2), or Ezh2 with wild- type Ezh2 3-UTR (Ezh2 WT 3-UTR) in NSCs, 1.6 106 cells were co-nucleofected with 0.5 g of pmaxGFP (Amaxa) together with 2 g of the respective expression construct and plated onto poly-D-lysine-coated wells. 24 h postplating, the medium was changed to neurobasal medium containing N2 supplement for differentiation. Upon 72 and 120 h of differen- tiation, cells were harvested for RNA isolation and analyzed using quantitative RT-PCR. Semiquantitative and Quantitative RT-PCR Analysis—Total RNA was purified using TRIzol (Invitrogen) as recommended. Reverse transcription (RT) was performed using SuperScript III (Invitrogen)withrandomhexamer.cDNAwasamplifiedwithspe- cific primers for Ezh2, Suz12, Eed, and Hprt. The abundance of transcripts of the housekeeping gene Hprt was used as a loading control. Quantification of PCR product was done using image processing software, ImageJ (National Institutes of Health). miR-124 Controls Ezh2 Expression during Neurodifferentiation P19 Stable Cell Line—P19 stable cell lines were generated as described (33). For stable cell line selection, 2 g/ml puromycin was added to the medium for 5 days. To turn on the Tet-induc- ible expression, doxycycline (Clontech) was added to a final concentration of 2 g/ml. at high levels in non-neuronal cells and neuronal precursors, where it suppresses the utilization of neuron-specific alterna- tive exons. During neuronal differentiation, Ptbp1 expression is reduced by miR-124, which triggers a switch in alternative splicing patterns among a wide range of transcripts. Ptbp1 addi- tionally controls the abundance of several neuron-specific mRNAs through nuclear and cytoplasmic RNA quality control mechanisms (11, 23, 28). Collectively, these studies demon- strate that miR-124 regulates several molecular pathways crit- ical for proper progression of neuronal differentiation. at high levels in non-neuronal cells and neuronal precursors, where it suppresses the utilization of neuron-specific alterna- tive exons. During neuronal differentiation, Ptbp1 expression is reduced by miR-124, which triggers a switch in alternative splicing patterns among a wide range of transcripts. Ptbp1 addi- tionally controls the abundance of several neuron-specific mRNAs through nuclear and cytoplasmic RNA quality control mechanisms (11, 23, 28). Collectively, these studies demon- strate that miR-124 regulates several molecular pathways crit- ical for proper progression of neuronal differentiation. g Neuronal and Astrocyte Differentiation of P19 Cells—To dif- ferentiate P19 cells into neuron and astrocyte, we adapted a protocol as described before (34). Briefly, 1 105 cells/ml P19 cells were allowed to aggregate in a bacterial grade Petri dish (Fisher) and treated with 1 M all-trans-retinoic acid (Sigma). The medium was changed at day 2. Cell aggregates were disso- ciated into a single cell suspension with 0.25% trypsin-EDTA (Invitrogen) at day 4. Cells were seeded onto a tissue culture grade Petri dish (Corning Inc.) at 1 105 cells/ml in neurobasal medium with N2 supplement (Invitrogen) and 0.4 mM L-gluta- mine (Invitrogen). To obtain neuron and astrocyte, cells were further cultured until day 6.5 and day 12, respectively, for immunofluorescence staining. For protein and RNA assays, cells were cultured until day 10 or 12, and samples were col- lected at the indicated time points. Neuron-specific genes are frequently modified by Ezh2- mediated H3K27 trimethylation (3meH3K27) in stem cells, whereas both the Ezh2 levels and the density of 3meH3K27 marks are down-regulated upon neuronal differentiation (29– 31). miR-124 Controls Ezh2 Expression during Neurodifferentiation The primer sequences were as follows: mEzh2 forward, 5-AACA- CCAAACAGTGTCCATGCTAC-3; mEzh2 reverse, 5-CTAA- GGCAGCTGTTTCAGAGAGAA-3; mEeD forward, 5-CAAC- ACCAGCCACCCTCTAT-3; mEeD reverse, 5-GAGAA- GGTTTGGGTCTCGTG-3; mSuz12 forward, 5-AAACGAA- ATCGTGAGGATGG-3; mSuz12 reverse, 5-CCATTTCCTG- CATGGCTACT-3; mHprt forward, 5-GCTGGTGAAAA- GGACCTCT-3; mHprt reverse, 5-CACAGGACTAGAACAC- CTGC-3. For quantitative RT-PCR (RT-qPCR), cDNA was amplified with specific primers using an ABI StepOnePlus real- time PCR system (Applied Biosystems) and KAPA SYBR Fast ABI Prism 2x qPCR master mix (KAPA Biosystems). Data were nor- malized to the expression levels of the Hprt mRNA. The primer sequences were as follows: mEzh2 forward, 5-TCCATGCAAC- ACCCAACACAT-3; mEzh2 reverse, 5-GGGTCTGCTAC- MicroRNA miR-124 Controls the Choice between Neuronal and Astrocyte Differentiation by Fine-tuning Ezh2 Expression* Ptbp1 is expressed VOLUME 289•NUMBER 30•JULY 25, 2014 VOLUME 289•NUMBER 30•JULY 25, 2014 20788 JOURNAL OF BIOLOGICAL CHEMISTRY JULY 25, 2014•VOLUME 289•NUMBER 30 FIGURE 1. miR-124 up-regulates neuron-specific Ezh2 target genes. A, hierarchical clustering analysis of gene expression microarray data sets. miR-124- overexpressing N2a cell lines generated a distinctive gene expression pattern compared with non-transfected controls. Hierarchical clustering analysis (uncentered Pearson’s correlation) of 16 samples and 24,288 genes separated untransfected samples from miR-124-transfected ones. A1, Argonaute-2 kinase- dead/Argonaute-1 reconstituted; A2, Argonaute-2 kinase-dead/Argonaute-2 reconstituted; WT, wild type; NT, non-transfected; 22, 22-mer miR-124-trans- fected. B, a heat map was generated by performing unsupervised hierarchical clustering of 1669 differentially expressed genes with a p value cut-off of 0.001 and a -fold change (FC) range of 1.5 FC 0.67. Expression values for each gene in an individual array were calculated as log2 of the -fold change relative to the mean expression value in each array, which is represented as 0-fold in the black. The intensity of induction or repression is signified by the saturation of red or green, respectively. C, a significant fraction of miR-124-up-regulated genes are direct target genes of Ezh2. The Venn diagram shows that 414 genes are up-regulated (FC 1.5 and p 0.001) by miR-124 expression, 194 of which are CNS-specific genes, and 52 of them are Ezh2 target genes that are significantly enriched in the miR-124-up-regulated CNS-specific gene list, as determined by Fisher’s exact test (p 7.03 105). D, selected genes from the miR-124-up- regulated CNS-specific gene list were validated by RT-qPCR. Their expression is further down-regulated by simultaneous expression of miR-124-resistant Ezh2. Significant differences between the indicated pairs were determined by two-tailed Student’s t test with equal variance (, p 0.05; , p 0.01; *, p 0.001). A representative result with experimental triplicates from three independent experiments is shown. Data shown are mean ( ) S.D. of triplicates. EXPERIMENTAL PROCEDURES Plasmids—To generate the EGFP reporter construct for miRNA screening, 3-UTR of Ezh2 was PCR-amplified from RP24–191K13 BAC clone and subcloned into the NotI site of pEGFP-N1 vector (Clontech). miRNA expression vectors were modified from pEM157 vector (11). A 500-bp DNA fragment flanking precursor miRNA sequence of interest was PCR-am- plified from human genomic DNA and subcloned into the SpeI and NotI site of the intronic region of dsRed2 in pEM157 vector. Various Ezh2 donor plasmids were modified from pRD- RIPE plasmid (33) by replacing EGFP with Ezh2 or Ezh2-3- UTR at AgeI and BglII sites. The QuikChange site-directed mutagenesis kit (Stratagene) was used to destroy the miR-124 target site in Ezh2 3-UTR (32). Cells—HEK293T cells were cultured in DMEM/high glucose (PAA Laboratories, GmbH) supplemented with 10% fetal bovine serum (FBS), 1 mM sodium pyruvate, 2 mM L-glutamine, 100 units/ml penicillin, 100 g/ml streptomycin, and 55 M 2-mercaptoethanol (all from Invitrogen). P19 cells were rou- tinely propagated in -minimal essential medium (HyClone) supplemented with 2.5% FBS, 7.5% bovine calf serum, 100 units/ml penicillin, and 100 g/ml streptomycin. JULY 25, 2014•VOLUME 289•NUMBER 30 JOURNAL OF BIOLOGICAL CHEMISTRY 20789 miR-124 Controls Ezh2 Expression during Neurodifferentiation p g 20790 JOURNAL OF BIOLOGICAL CHEMISTRY VOLUME 289•NUMBER 30•JULY 25, 2014 by guest on August 21, 2014 http://www.jbc.org/ Downloaded from VOLUME 289•NUMBER 30•JULY 25, 2014 20790 JOURNAL OF BIOLOGICAL CHEMISTRY miR-124 Controls Ezh2 Expression during Neurodifferentiation TGTTATTCGGAA-3; mL1cam forward, 5-GGACAGCTTG- AGGGTAGTAGA-3; mL1cam reverse, 5-CTGAAGAC- CACAACTCTCCCA-3; mSyp forward, 5-CGGCACATAGG- CATCTCCT-3; mSyp reverse, 5-GAGAGAACAACAAAG- GGCCAA-3; mGfap forward, 5-ACCGCATCACCATTC- CTGTAC-3; mGfap reverse, 5-TGGCCTTCTGACACGG- ATT-3; mS100b forward, 5-TGGTTGCCCTCATTGATGTCT- 3; mS100b reverse, 5-CCCATCCCCATCTTCGTCC-3; mHprt forward, 5-CCAGACAAGTTTGTTGTTGGA-3; mHprt reverse, 5-TTTACTAGGCAGATGGCCACA-3; mAscl1 forward, 5- GCAACCGGGTCAAGTTGGT-3; mAscl1 reverse, 5-GTCG- TTGGAGTAGTTGGGGG-3; mAtf3 forward, 5-GAGGAT- TTTGCTAACCTGACACC-3; mAtf3 reverse, 5-TTGACG- GTAACTGACTCCAGC-3; mDusp8 forward, 5-TGACCC- AAAACGGAATAAGC-3; mDusp8 reverse, 5-CCTGTATG- CGTCGTCAGAAG-3; mEn2 forward, 5-GCTGGCACTA- CCGAAGGAG-3; mEn2 reverse, 5-ACCGTGAAGTG- ATAGCGTCTT-3; mSypl2 forward, 5-CGCACCTCGGAC- AAGTCTC-3; mSypl2 reverse, 5-CCCGAAGGCGAAAAT- AGCAAA-3; mTpm1 forward, 5-GGGCTGAGTTTGCAG- AGAGA-3; mTpm1 reverse, 5-TCAGCTGGAGAGCAG- ACAGA-3. Immunoblotting—Whole cell lysates were prepared by resus- pending cells in Nonidet P-40 buffer (50 mM Tris-HCl, pH 8.0, 500 mM NaCl, 1 mM EDTA, 1% Nonidet P-40, 10% glycerol) and sonicated (Bioruptor). Protein concentration was determined using the Bio-Rad DC protein assay (Bio-Rad) and analyzed by a Tecan infinite F200 plate reader (Tecan). Protein samples were subjected to SDS-PAGE. Antibodies used in the study were anti-Ezh2 (Cell Signaling Technology), anti-Tuj1 (Cova- nce), anti-Erk1/2 (Sigma), anti-Suz12 (Abcam), and anti-Eed (Millipore). Immunofluorescence—Immunofluorescence staining was per- formed according to a standard protocol. Anti-Tuj1 antibody was purchased from Covance. Anti-Gfap (ab4674) antibody was pur- chased from Abcam. Slides were mounted with mounting medium (Ibidi, GmbH) containing DAPI (Invitrogen). Locked Nucleic Acid Antisense Oligonucleotide Transfec- tion—Differentiated P19 cells (day 6) were seeded in 6-well plates at 3 105 cells/well in 2 ml of antibiotic-free medium and transfected with 1, 5, or 30 pmol/ml miR-124 locked nucleic acid antisense oligonucleotide (Exiqon) using Lipo- fectamine 2000 (Invitrogen). Total protein and RNA were iso- lated 96 h post-transfection. miR-124 Controls Ezh2 Expression during Neurodifferentiation miR-124 Controls Ezh2 Expression during Neurodifferentiation miR-124 Controls Ezh2 Expression during Neurodifferentiation miR-124 Controls Ezh2 Expression during Neurodifferent miR-124 Controls Ezh2 Expression during Neurodifferentiation 20792 JOURNAL OF BIOLOGICAL CHEMISTRY VOLUME 289 NUMBER 30 JULY 25 2014 by guest on August 21, 2014 http://www.jbc.org/ Downloaded from by guest on August 21, 2014 http://www.jbc.org/ Downloaded from by guest on August 21, 2014 http://www.jbc.org/ Downloaded from by guest on August 21, 2014 http://www.jbc.org/ Downloaded from Site-directed Mutagenesis—The predicted miR-124 binding site was mutated by base pair changes using DpnI-mediated site-directed mutagenesis (Stratagene). The primer sequences were as follows (32): miR124-Del forward, 5-GTTTTAAAAT- CAACTTTTTATCTCACCAGCTGCAAAGTGTTTTG-3; miR124-Del reverse, 5-CAAAACACTTTGCAGCTGGT- GAGATAAAAAGTTGATTTTAAAAC-3; miR124-Sub for- ward, 5-CAACTTTTTATACGGAACTCACCAGCTGCAA- AGTGTTTTG-3; miR124-Sub reverse, 5-CAAAACAC- TTTGCAGCTGGTGAGTTCCGTATAAAAAGTTG-3. p Microarray Analyses—N2a cell pools expressing different Argonaute paralog blends were described previously (35). Of these, N2a-WT cells containing the EGFP(shLuc) transgene had a native Argonaute expression dominated by Ago2, N2a-A1 cells containing the Ago1(shAgo2-3-UTR) transgene expressed pre- dominantlyAgo1,andN2a-A2cellscontainingtheAgo2(shAgo2- 3UTR) transgene overexpressed Ago2 (35). All three cell pools were cultured in DMEM (HyClone) containing 10% FBS (HyClone, characterized grade), 1 mM sodium pyruvate (Invitro- gen),100IU/mlpenicillin,100mg/mlstreptomycin(Invitrogen),5 g/ml puromycin, and 2 g/ml doxycycline (antibiotic-contain- ing complete DMEM) for 72 h prior to siRNA/miRNA duplex transfections. One million cells were seeded per well of a 6-well plate in 2 ml of antibiotic-free complete DMEM and allowed to adhere for 1 h. 100 pmol of corresponding siRNA/miRNA duplex mixed with Lipofectamine 2000 and OptiMEM I (Invitrogen) was then added per well as recommended. Medium was changed 5 h post-transfection to antibiotic-containing complete DMEM, and the incubation was continued for another 24 h. Total RNAs were extracted with TRIzol (Invitrogen) and cleaned up using an RNeasy kit (Qiagen). The RNAs were hybridized with Agilent Mouse SurePrint G3 8 60K Gene Expression Microarrays as recommended.ThedatasetswerenormalizedusingRobiNA(36), and genes showing consistent miR-124-induced up- or down-reg- miRNA Northern Blot Analysis—Five g of total RNA sam- ples were separated on a 15% denaturing polyacrylamide gel containing 8 M urea and 1 TBE. They were electrotransferred to Hybond N membrane (Amersham Biosciences) in 0.5 TBE at 2.5 mA/cm2 for 30 min. RNA was cross-linked to the membrane by UV irradiation (0.15 J/cm2), and the membrane was blocked with 6 SSC, 7% SDS at 42 °C for overnight. Hybridization probes were prepared by labeling the appropri- ate oligodeoxyribonucleotides using T4 polynucleotide kinase (New England Biolabs) and [-32P]ATP (PerkinElmer Life Sci- ences). The 32P-labeled probes were purified using Sephadex G-25 microspin columns (Geneaid) and added to the blocking solution. The hybridization was carried out for overnight at 42 °C. The membranes were washed four times with 3 SSC, 0.1% SDS at 42 °C and exposed to phosphorimaging plates. JULY 25, 2014•VOLUME 289•NUMBER 30 20791 JOURNAL OF BIOLOGICAL CHEMISTRY 20791 miR-124 Controls Ezh2 Expression during Neurodifferentiation RESULTS Overexpression of miR-124 in Neuroblastoma Cells Up-regu- lates Neuron-specific Ezh2 Target Genes—To better under- stand miR-124 functions in the neural lineage, we transfected three N2a cell populations expressing distinct blends of Argo- naute paralogs (N2a-WT, N2a-Ago1, and N2a-Ago2; see Ref. 35 for details) with either a synthetic siRNA-like duplex designed to deliver mature 22-mer miR-124 or a non-targeting siRNA control and analyzed the samples by Agilent gene expression microarrays. N2a cells were chosen because they express endogenous miR-124 at negligibly low levels (11, 35). Hierarchical clustering of the microarray data suggested that all three cell populations responded to miR-124 in a largely similar manner (Fig. 1A). This allowed us to pool individual popula- tion-specific data sets and focus on highly reproducible gene expression changes. In line with previous studies suggesting that this miRNA may directly regulate hundreds distinct mRNA targets, miR-124 consistently down-regulated 1255 genes (1.5-fold, p 0.001; t test). Analysis of this subset by gene set enrichment analysis (37, 38) showed a dramatic over- representation of predicted miR-124 targets (p 0; data not shown). g y g g miR-124 Is a Potent miRNA Regulator of Ezh2 Expression— To examine the extent of miRNA-dependent regulation of Ezh2 expression, we co-expressed an EGFP-Ezh2 3-UTR reporter construct with each of the 30 miRNAs (including miR-124) predicted to interact with Ezh2 3-UTR by five miRNA target prediction algorithms (Target Scan, PicTar, miRBase, miRNA.org, and MicroInspector) or nervous sys- tem-specific miRNA miR-9 (41) lacking the predicted bind- ing sites in the Ezh2 3-UTR. FACS analysis showed that the miR-124-induced down-regulation of the EGFP-Ezh2 3-UTR expression exceeded that of most other miRNAs and was comparable with the effects induced by miR-26a and miR- 101 (Fig. 2, A and B), two miRNAs previously reported to reg- ulate Ezh2 expression and contribute to tumorigenesis (42, 43). Moreover, overexpression of miR-124, as well as miR-26a and miR-101, caused a noticeable down-regulation of endogenous Ezh2 protein level in HEK293T cells (Fig. 2C). The miR-9 con- trol had no effect on the EGFP-Ezh2 3-UTR expression and the expression of endogenous Ezh2 protein, as expected. These findings were further confirmed by a secondary screen with a luciferase Ezh2 3-UTR reporter co-transfected with miR-124 or several other high scoring miRNA candidates (Fig. 2D). Notably, disruption of the predicted evolutionarily conserved miR-124 target site in the Ezh2 3-UTR (Fig. FIGURE2.miR-124regulatesEzh2expressionbytargetingEzh23-UTR.A,screeningformicroRNAsregulatingEzh2expression.AnEGFPdrivenbytheCMV promoter was fused to Ezh2 3-UTR and used as a reporter in our fluorescence-based screening system. Individual miRNAs were expressed by dsRed2 containing vector pEM157. Both reporter and miRNA expression vectors were transfected into HEK293T cells and analyzed by FACS. miR-26a and miR-101 expression constructs were used as positive controls, and miR-9 was used as a negative control. EGFP mean fluorescence intensity (MFI) of the EGFP dsRed2 population was assayed 48 h post-transfection. Relative mean fluorescence intensity was calculated after normalization against that of the empty vector (EV) control. B, miR-124 targets Ezh2 3-UTR. Indicated miRNA expression vectors were co-transfected with EGFP reporter constructs in HEK293T cells. C, endoge- nous Ezh2 expression was analyzed by Western blot, and Tubulin was used as a loading control. The -fold change of Ezh2 was normalized to EV control and is shown below the Ezh2 blot. Data shown are representative of three independent experiments. D, the indicated miRNA expression vectors were co-transfected with luciferase reporter construct in HEK293T cells. Luciferase assay was performed 48 h post-transfection. Relative luciferase activity was normalized against Renilla luciferase activity. Relative -fold change was calculated relative to relative luciferase activity of the EV control. E, the miR-124 target site in Ezh2 3-UTR is highly conserved among vertebrates. Alignment of the predicted miR-124 binding site in Ezh2 3UTR of different species is shown (Mmu, Mus musculus; Hsa, Homo sapiens; Rno, Rattus norvegicus; Ocu, Oryctolagus cuniculus; Ptr, Pan troglodytes; Cfa, Canis familiaris; Oga, Otolemur garnettii; Mml, Macaca mulatta; Eca, Equus caballus; Bta, Bos taurus). F, miR-124 target sites in Ezh2 3-UTR was analyzed by luciferase reporter. Mutations of the miR-124 target site in Ezh2 3-UTR specifically abolish miR-124-mediated down-regulation of the luciferase reporter. The seeding region of the miR-124 target site in Ezh2 3-UTR was either mutated by deletion (Del 3UTR) or substitution (Sub 3UTR) or left intact (WT 3UTR). The -fold change was calculated relative to the relative luciferase activity of the reporter with wild-type Ezh2 3-UTR in the absence of additional miRNA expression (EV). All data shown in the bar graph are mean S.D. (error bars) of at least three independent experiments. The differences between groups were first determined by analysis of variance (B and D), and the significance of miRNA-mediated down-regulation compared with the control was determined by a two-tailed Student’s t test with equal variance (, p 0.05; , p 0.01; , p 0.001). 20792 JOURNAL OF BIOLOGICAL CHEMISTRY VOLUME 289•NUMBER 30•JULY 25, 2014 miR-124 Controls Ezh2 Expression during Neurodifferentiation ulation were shortlisted in Excel using appropriate -fold change and t test p value cut-offs. the miR-124-up-regulated Ezh2 target genes were further vali- dated by RT-qPCR, and their expression levels were down-reg- ulated by simultaneous expression of miR-124-resistant Ezh2 (Fig. 1D). These results suggested that miR-124 might regulate extensive subsets of genes by targeting Ezh2. the miR-124-up-regulated Ezh2 target genes were further vali- dated by RT-qPCR, and their expression levels were down-reg- ulated by simultaneous expression of miR-124-resistant Ezh2 (Fig. 1D). These results suggested that miR-124 might regulate extensive subsets of genes by targeting Ezh2. RESULTS 2E) by substitution or deletion (32, 44) abolished the miR-124-mediated down-reg- ulation effect (Fig. 2F). We concluded that miR-124 is among the most efficient miRNA regulators of Ezh2 expression. by guest on August 21, 2014 http://www.jbc.org/ Downloaded from miR-124 Controls Ezh2 Expression during Neurodifferentiation A, Ezh2 and Tuj1 protein levels were analyzed by Western blot, and Erk1/2 served as a loading control. B, expression of Ezh2 mRNA level was determined by semiquantitative RT-PCR. Hprt served as a loading control. C, increased miR-124 expression level during P19 neuronal differentiation. miR-124 expression levels were determined by Northern blot, and U6 RNA served as a loading control. A repre- sentative figure of two independent experiments is shown. This observation is shown in an earlier report (41). D, Suz12, Eed, and Tuj1 protein levels were analyzed as described above. E, expression of Suz12 and Eed mRNA levels was analyzed by semiquantitative RT-PCR. HPRT served as a loading control. F–H, miR-124 inhibitor up-regulates endogenous Ezh2. miR-124 inhibitor was transfected into differentiating P19 cells at day 6 after the start of RA treatment. The levels of miR-124 and PRC2 members were analyzed at day 10. F, down-regulation of miR-124 expression level by inhibitor was confirmed by Northern blot analysis. A representative figure of two independent experiments is shown. The miR-124-specific inhibitor has been tested and published previously (11). G, Ezh2 protein expression was up-regulated upon miR-124 inhibitor treatment. H, Suz12 protein level was not altered upon miR-124 inhibitor treatment, whereas Eed protein level was below the detection limit of the Western blot assay. Ezh2, Suz12, Eed, and Tuj1 protein expression levels were normalized to Erk1/2. Their -fold changes were calculated relative to the protein levels at day 0 (Ezh2 and Suz12), day 10 (Tuj1), or in non-transfected controls (G and H) and indicated below their respective blots. N.D., not detectable. All data shown, unless otherwise stated, are representative of at least three independent experiments. Because, unlike Ezh2, the Suz12 and Eed 3-UTRs lacked putative miR-124 target sites, we hypothesized that miR-124 may directly down-regulate Ezh2 during neuronal differentia- tion, whereas Suz12 and Eed are probably regulated by distinct post-transcriptional mechanisms. To test this prediction, we disrupted the activity of endogenous miR-124 with a miR-124- specific locked nucleic acid antisense oligonucleotide in differ- indicating possible involvement of a post-transcriptional regulatory mechanism. Indeed, we found that miR-124 expression was inversely correlated with Ezh2 expression during P19 neuronal differentiation (Fig. 3C). Interestingly, mRNA and protein expression dynamics of two other PRC2 components, Suz12 and Eed, showed similar trends (Fig. 3, D and E). indicating possible involvement of a post-transcriptional regulatory mechanism. miR-124 Controls Ezh2 Expression during Neurodifferentiation A–E, inverse expression patterns of PRC2 members and miR-124 during P19 neuronal differentiation. Neuronal differentiation of P19 cells was induced by 1 M all-trans-RA treatment for 4 days. Cell aggregates were dissociated into single cell suspensions at day 4 and recultured in neurobasal medium with N2 supplement. Cells were further cultured and collected at the indicated time points. A, Ezh2 and Tuj1 protein levels were analyzed by Western blot, and Erk1/2 served as a loading control. B, expression of Ezh2 mRNA level was determined by semiquantitative RT-PCR. Hprt served as a loading control. C, increased miR-124 expression level during P19 neuronal differentiation. miR-124 expression levels were determined by Northern blot, and U6 RNA served as a loading control. A repre- sentative figure of two independent experiments is shown. This observation is shown in an earlier report (41). D, Suz12, Eed, and Tuj1 protein levels were analyzed as described above. E, expression of Suz12 and Eed mRNA levels was analyzed by semiquantitative RT-PCR. HPRT served as a loading control. F–H, miR-124 inhibitor up-regulates endogenous Ezh2. miR-124 inhibitor was transfected into differentiating P19 cells at day 6 after the start of RA treatment. The levels of miR-124 and PRC2 members were analyzed at day 10. F, down-regulation of miR-124 expression level by inhibitor was confirmed by Northern blot analysis. A representative figure of two independent experiments is shown. The miR-124-specific inhibitor has been tested and published previously (11). G, Ezh2 protein expression was up-regulated upon miR-124 inhibitor treatment. H, Suz12 protein level was not altered upon miR-124 inhibitor treatment, whereas Eed protein level was below the detection limit of the Western blot assay. Ezh2, Suz12, Eed, and Tuj1 protein expression levels were normalized to Erk1/2. Their -fold changes were calculated relative to the protein levels at day 0 (Ezh2 and Suz12), day 10 (Tuj1), or in non-transfected controls (G and H) and indicated below their respective blots. N.D., not detectable. All data shown, unless otherwise stated, are representative of at least three independent experiments. FIGURE 3. miR-124 down-regulates Ezh2 expression during P19 neuronal differentiation. A–E, inverse expression patterns of PRC2 members and miR-124 during P19 neuronal differentiation. Neuronal differentiation of P19 cells was induced by 1 M all-trans-RA treatment for 4 days. Cell aggregates were dissociated into single cell suspensions at day 4 and recultured in neurobasal medium with N2 supplement. Cells were further cultured and collected at the indicated time points. by guest on August 21, 2014 http://www.jbc.org/ Downloaded from Interestingly, 414 genes were consistently up-regulated (1.5-fold, p 0.001; t test) in miR-124-transfected N2a cells, presumably as a result of indirect effects (Fig. 1B). Strikingly, gene set enrichment analysis of this group uncovered a highly significant enrichment of genes previously identified as targets of 3meH3K27 histone modification or Suz12 either by ChIP- on-chip or ChIP-sequencing (data not shown), indicative of possible regulation of these genes by the PRC2 complex con- taining Ezh2 as a catalytic histone methyltransferase subunit. Notably, when we compared the list of the miR-124-up-regu- lated central nervous system (CNS)-specific genes (39) with genes known to be regulated by Ezh2 in stem cells (40), a highly significant overlap was detected (p 7.03 105; Fisher’s exact test) (Fig. 1C). On the other hand, the overlap between the corresponding subsets of miR-124-down-regulated CNS-spe- cific genes and Ezh2 target genes could be explained by random sampling (p 0.56; Fisher’s exact test) (data not shown). Six of miR-124 Down-regulates Expression of Ezh2 but Not Other PRC2 Components during Neuronal Differentiation—To exam- ine whether physiological levels of miR-124 could regulate Ezh2 expression during neuronal differentiation, we took advantage of the retinoic acid (RA)-induced P19 embryonic carcinoma in vitro differentiation model (45, 46). We found that the Ezh2 protein level was noticeably down-regulated in P19 cells undergoing neuronal differentiation (Fig. 3A), whereas Ezh2 mRNA levels remained virtually unchanged (Fig. 3B), thus JULY 25, 2014•VOLUME 289•NUMBER 30 JOURNAL OF BIOLOGICAL CHEMISTRY 20793 JULY 25, 2014•VOLUME 289•NUMBER 30 miR-124 Controls Ezh2 Expression during Neurodifferentiation d bl l f l l k h h d d l k d FIGURE 3. miR-124 down-regulates Ezh2 expression during P19 neuronal differentiation. A–E, inverse expression patterns of PRC2 members and miR-124 during P19 neuronal differentiation. Neuronal differentiation of P19 cells was induced by 1 M all-trans-RA treatment for 4 days. Cell aggregates were dissociated into single cell suspensions at day 4 and recultured in neurobasal medium with N2 supplement. Cells were further cultured and collected at the indicated time points. A, Ezh2 and Tuj1 protein levels were analyzed by Western blot, and Erk1/2 served as a loading control. B, expression of Ezh2 mRNA level was determined by semiquantitative RT-PCR. Hprt served as a loading control. C, increased miR-124 expression level during P19 neuronal differentiation. miR-124 expression levels were determined by Northern blot, and U6 RNA served as a loading control. A repre- sentative figure of two independent experiments is shown. This observation is shown in an earlier report (41). D, Suz12, Eed, and Tuj1 protein levels were analyzed as described above. E, expression of Suz12 and Eed mRNA levels was analyzed by semiquantitative RT-PCR. HPRT served as a loading control. F–H, miR-124 inhibitor up-regulates endogenous Ezh2. miR-124 inhibitor was transfected into differentiating P19 cells at day 6 after the start of RA treatment. The levels of miR-124 and PRC2 members were analyzed at day 10. F, down-regulation of miR-124 expression level by inhibitor was confirmed by Northern blot analysis. A representative figure of two independent experiments is shown. The miR-124-specific inhibitor has been tested and published previously (11). G, Ezh2 protein expression was up-regulated upon miR-124 inhibitor treatment. H, Suz12 protein level was not altered upon miR-124 inhibitor treatment, whereas Eed protein level was below the detection limit of the Western blot assay. Ezh2, Suz12, Eed, and Tuj1 protein expression levels were normalized to Erk1/2. Their -fold changes were calculated relative to the protein levels at day 0 (Ezh2 and Suz12), day 10 (Tuj1), or in non-transfected controls (G and H) and indicated below their respective blots. N.D., not detectable. All data shown, unless otherwise stated, are representative of at least three independent experiments. miR-124 Controls Ezh2 Expression during Neurodifferentiation by guest on August 21, 2014 http://www.jbc.org/ Downloaded from by guest on August 21, 2014 http://www.jbc.org/ Downloaded from FIGURE 3. miR-124 down-regulates Ezh2 expression during P19 neuronal differentiation. miR-124 Controls Ezh2 Expression during Neurodifferentiation Indeed, we found that miR-124 expression was inversely correlated with Ezh2 expression during P19 neuronal differentiation (Fig. 3C). Interestingly, mRNA and protein expression dynamics of two other PRC2 components, Suz12 and Eed, showed similar trends (Fig. 3, D and E). 20794 JOURNAL OF BIOLOGICAL CHEMISTRY VOLUME 289•NUMBER 30•JULY 25, 2014 VOLUME 289•NUMBER 30•JULY 25, 2014 miR-124 Controls Ezh2 Expression during Neurodifferentiation FIGURE 4. Generation of doxycycline-inducible P19 cell lines expressing Ezh2. A, targeting strategy for the generation of doxycycline (Dox)-inducible P19 cell lines expressing Ezh2. The diagram shows the targeting construct and the acceptor locus before and after Cre-recombinase-mediated recombination. The empty and filled arrowheads indicate the LoxP2272 and LoxP sequence, respectively. B, schematic presentation of various targeting constructs that were used to generate Dox-inducible P19 cell lines expressing Ezh2 with various 3-UTRs. EGFP was used as a control for the inducible system. Filled black boxes denote artificial -globin 3-UTR (EGFP control and Ezh2). Filled gray boxes designate Ezh2 3-UTR (Ezh2 WT 3UTR). Black star, mutation in the miR-124 target site of wild-type 3-UTR (Ezh2 Sub 3UTR). Puromycin was used as a positive selection marker for the screening of Cre-recombinase-mediated recombination events in P19 HILO-RMCE acceptor cell line (33). EF1, elongation factor-1 promoter; TRE, tetracycline response element; rtTA3, reverse tetracycline transactivator. miR-124 Controls Ezh2 Expression during Neurodifferentiation by guest on August 21, 2014 http://www.jbc.org/ Downloaded from FIGURE 4. Generation of doxycycline-inducible P19 cell lines expressing Ezh2. A, targeting strategy for the generation of doxycycline (Dox)-inducible P19 cell lines expressing Ezh2. The diagram shows the targeting construct and the acceptor locus before and after Cre-recombinase-mediated recombination. The empty and filled arrowheads indicate the LoxP2272 and LoxP sequence, respectively. B, schematic presentation of various targeting constructs that were used to generate Dox-inducible P19 cell lines expressing Ezh2 with various 3-UTRs. EGFP was used as a control for the inducible system. Filled black boxes denote artificial -globin 3-UTR (EGFP control and Ezh2). Filled gray boxes designate Ezh2 3-UTR (Ezh2 WT 3UTR). Black star, mutation in the miR-124 target site of wild-type 3-UTR (Ezh2 Sub 3UTR). Puromycin was used as a positive selection marker for the screening of Cre-recombinase-mediated recombination events in P19 HILO-RMCE acceptor cell line (33). EF1, elongation factor-1 promoter; TRE, tetracycline response element; rtTA3, reverse tetracycline transactivator. entiating P19 cultures (47) (Fig. 3F). This treatment successfully restored Ezh2 but not Suz12 and Eed expression in a dose-de- pendent manner (Fig. 3, G and H). Although the amount of miR-124 was significantly reduced by treatment with a high dose inhibitor, the remaining miR-124 was still sufficient to partially suppress Ezh2 expression. 20794 JOURNAL OF BIOLOGICAL CHEMISTRY It is therefore difficult to achieve more profound changes in Ezh2 protein levels through treatment with miR-124 inhibitor. These results, however, suggested that Ezh2 is the only PRC2 member directly regulated by miR-124. ulate Ezh2 protein level and cause this inhibitory effect (Fig. 5, B and C). Moreover, the efficiency of P19 neuronal differentiation was significantly reduced by the Ezh2 Sub 3-UTR transgene lack- ing the miR-124 target site in its Ezh2-derived 3-UTR. Our RT- qPCR and immunoblot analyses confirmed that these biological effects were accompanied by corresponding changes in the Ezh2 expression levels (Fig. 5C). Similarly, transient expression of recombinant Ezh2 in mouse embryonic neural stem cells under- going neuronal differentiation down-regulated neuronal markers L1cam and Syp (Fig. 5D). On the other hand, expression of Ezh2 with WT 3-UTR lowered expression of these genes to a lesser extent, an effect that was especially obvious for L1cam (Fig. 5D). Thus, down-regulation of Ezh2 protein expression by miR-124 is critical for efficient neuronal differentiation. y y y miR-124-regulated Ezh2 Expression Is Critical for Efficient Neuronal Differentiation—To address functional significance of miR-124-induced Ezh2 down-regulation during neuronal differentiation, we generated several transgenic P19 lines stably expressing doxycycline-inducible Ezh2 mRNAs with various 3-UTRs (Fig. 4, A and B). To avoid position effects caused by random integration, we utilized a site-specific transgene inte- gration procedure developed earlier (33). This well character- ized P19 HILO-RMCE acceptor cell line, where all constructs are targeting to the same locus, provides a superior experimen- tal system for comparing the effects of various Ezh2 constructs on neuronal differentiation. An additional cell line expressing EGFP with Globin 3-UTR (EGFP) was generated as a control. Using the expression of neuronal Tubulin III (Tuj1 immu- nofluorescence; Fig. 5, A and B) and expression of neuron-spe- cific mRNAs, L1cam and Syp, as a readout (Fig. 5C), we found that expression of the Ezh2 transgene (Ezh2) lacking its natural 3-UTR reduced the efficiency of P19 neuronal differentiation. Conversely, the Ezh2 transgene with the Ezh2 3-UTR contain- ing the miR-124 target site (Ezh2 WT 3-UTR) failed to up-reg- miR-124-regulated Ezh2 Expression Is Critical for Efficient Neuronal Differentiation—To address functional significance of miR-124-induced Ezh2 down-regulation during neuronal differentiation, we generated several transgenic P19 lines stably expressing doxycycline-inducible Ezh2 mRNAs with various 3-UTRs (Fig. 4, A and B). To avoid position effects caused by random integration, we utilized a site-specific transgene inte- gration procedure developed earlier (33). miR-124 Controls Ezh2 Expression during Neurodifferentiation Significant differences between indicated pairs in all panels were determined by two-tailed Student’s t test with equal variance (, p 0.05; , p 0.01; , p 0.001). fluorescence staining and further verified by RT-qPCR for the expression of astrocyte-specific gene S100b (Fig. 6C). A similar astrogenesis-promoting effect was observed in cultured embry- onic mouse neural stem cells expressing miR-124-resistant Ezh2 as well (Fig. 6D). Although Ezh2 is reported to prevent premature astrocyte differentiation in neurogenic phase by repressing astrocyte-specific genes in a Chd4-dependent man- ner (51), the Chd4 expression level was down-regulated at this late stage of P19 culture (Fig. 6E). The elevated recombinant Ezh2 expression at this stage therefore did not suppress but rather promoted astrocyte generation. Our results suggest that miR-124-dependent regulation of Ezh2 expression might be critical for a balanced production of astrocytes and neurons. miR-124 Controls Ezh2 Expression during Neurodifferentiation C, RT-qPCR analysis for the expression of Ezh2, L1cam, and Syp in the indicated P19 stable cell lines. Data are normalized against Hprt expression and corresponding cell lines without Dox treatment. Relative mRNA expression levels of the indicated genes were calculated as -fold change compared withthegeneexpressionincellsexpressingEzh2WT3-UTR.Arepresentativeresultwithexperimentaltriplicatesfromthreeindependentexperimentsisshown.Data shown are mean S.D. of triplicates. Ezh2 protein levels (far right) in cells expressing various Ezh2 constructs were normalized to Tubulin, and -fold change was calculated relative to the Ezh2 protein level in cells expressing EGFP control. Data shown are mean S.D. of quantifications from three Western blots. D, RT-qPCR analysis for the expression of L1cam and Syp in cultured embryonic mouse neural stem cells. Data are normalized against Hprt expression. Relative mRNA expression levels of the indicated genes were calculated as -fold change compared with the gene expression in EGFP control cells. A representative result with experimental triplicates from three independent experiments is shown. Data shown are mean S.E. (error bars). Significant differences between indicated pairs in all panels were determined by two-tailed Student’s t test with equal variance (, p 0.05; , p 0.01; , p 0.001). by guest on August 21, 2014 http://www.jbc.org/ Downloaded from by guest on August 21, 2014 http://www.jbc.org/ Downloaded from IGURE5.miR-124-regulatedEzh2expressionisimportantforP19neuronaldifferentiation.Neuronaldifferentiationofv f d d f ll d b h dd f h f h ll l d xpressionisimportantforP19neuronaldifferentiation.NeuronaldifferentiationofvariousstableP19celllineswasinduce f f f FIGURE5.miR-124-regulatedEzh2expressionisimportantforP19neuronaldifferentiation.NeuronaldifferentiationofvariousstableP19celllineswasinduced by RA treatment for 4 days and followed by the addition of Dox to promote the expression of Ezh2. Cells were analyzed at day 6.5. A, expression of miR-124 uncontrollable Ezh2 (Ezh2 or Ezh2 Sub 3UTR) inhibited neuronal differentiation. Neuronal population was defined by Tuj1 staining (red), and total cell number was determined by DAPI staining (blue). Representative images are shown. Scale bar, 50 m. B, statistical analysis of neuronal differentiation. The efficiency of neuronal differentiation was calculated relative to that of Ezh2 WT 3-UTR-expressing cells. The differences between groups were first determined by analysis of variance, and thesignificantdifferencebetweenindicatedpairswasdeterminedbyatwo-tailedStudent’sttestwithequalvariance.Datashownaremean S.D.(errorbars)ofthree independent experiments. C, RT-qPCR analysis for the expression of Ezh2, L1cam, and Syp in the indicated P19 stable cell lines. Data are normalized against Hprt expression and corresponding cell lines without Dox treatment. Relative mRNA expression levels of the indicated genes were calculated as -fold change compared withthegeneexpressionincellsexpressingEzh2WT3-UTR.Arepresentativeresultwithexperimentaltriplicatesfromthreeindependentexperimentsisshown.Data shown are mean S.D. of triplicates. miR-124 Controls Ezh2 Expression during Neurodifferentiation Ezh2 protein levels (far right) in cells expressing various Ezh2 constructs were normalized to Tubulin, and -fold change was calculated relative to the Ezh2 protein level in cells expressing EGFP control. Data shown are mean S.D. of quantifications from three Western blots. D, RT-qPCR analysis for the expression of L1cam and Syp in cultured embryonic mouse neural stem cells. Data are normalized against Hprt expression. Relative mRNA expression levels of the indicated genes were calculated as -fold change compared with the gene expression in EGFP control cells. A representative result with experimental triplicates from three independent experiments is shown. Data shown are mean S.E. (error bars). Significant differences between indicated pairs in all panels were determined by two-tailed Student’s t test with equal variance (, p 0.05; , p 0.01; , p 0.001). FIGURE5.miR-124-regulatedEzh2expressionisimportantforP19neuronaldifferentiation.NeuronaldifferentiationofvariousstableP19celllineswasinduced by RA treatment for 4 days and followed by the addition of Dox to promote the expression of Ezh2. Cells were analyzed at day 6.5. A, expression of miR-124 uncontrollable Ezh2 (Ezh2 or Ezh2 Sub 3UTR) inhibited neuronal differentiation. Neuronal population was defined by Tuj1 staining (red), and total cell number was determined by DAPI staining (blue). Representative images are shown. Scale bar, 50 m. B, statistical analysis of neuronal differentiation. The efficiency of neuronal differentiation was calculated relative to that of Ezh2 WT 3-UTR-expressing cells. The differences between groups were first determined by analysis of variance, and thesignificantdifferencebetweenindicatedpairswasdeterminedbyatwo-tailedStudent’sttestwithequalvariance.Datashownaremean S.D.(errorbars)ofthree independent experiments. C, RT-qPCR analysis for the expression of Ezh2, L1cam, and Syp in the indicated P19 stable cell lines. Data are normalized against Hprt expression and corresponding cell lines without Dox treatment. Relative mRNA expression levels of the indicated genes were calculated as -fold change compared withthegeneexpressionincellsexpressingEzh2WT3-UTR.Arepresentativeresultwithexperimentaltriplicatesfromthreeindependentexperimentsisshown.Data shown are mean S.D. of triplicates. Ezh2 protein levels (far right) in cells expressing various Ezh2 constructs were normalized to Tubulin, and -fold change was calculated relative to the Ezh2 protein level in cells expressing EGFP control. Data shown are mean S.D. of quantifications from three Western blots. D, RT-qPCR analysis for the expression of L1cam and Syp in cultured embryonic mouse neural stem cells. Data are normalized against Hprt expression. Relative mRNA expression levels of the indicated genes were calculated as -fold change compared with the gene expression in EGFP control cells. A representative result with experimental triplicates from three independent experiments is shown. Data shown are mean S.E. (error bars). 20794 JOURNAL OF BIOLOGICAL CHEMISTRY This well character- ized P19 HILO-RMCE acceptor cell line, where all constructs are targeting to the same locus, provides a superior experimen- tal system for comparing the effects of various Ezh2 constructs on neuronal differentiation. An additional cell line expressing EGFP with Globin 3-UTR (EGFP) was generated as a control. Ezh2 Regulation by miR-124 Balances Neurogenesis Versus Astrogenesis—miR-124 has been shown previously to promote neurogenesis and hinder gliogenesis using an in vitro differen- tiation model (48). Similarly, Ezh2-deficient neural progenitor cells are known to possess higher neurogenic and lower astro- genic potentials than their wild-type counterparts (49). To determine whether the miR-124/Ezh2 circuitry could control the choice between the two differentiation scenarios, we fol- lowed an established P19 astrogenesis protocol (50) and allowed transgenic P19 cells to differentiate for 12 days. We found that the efficiency of astrocyte differentiation was signif- icantly enhanced in P19 cells expressing the miR-124-resistant Ezh2 Sub 3-UTR transgene but not the miR-124-repressible Ezh2 WT 3-UTR transgene (Fig. 6, A and B). The efficiency of astrocyte differentiation was determined by Gfap inmmuno- JULY 25, 2014•VOLUME 289•NUMBER 30 20795 JOURNAL OF BIOLOGICAL CHEMISTRY miR-124 Controls Ezh2 Expression during Neurodifferentiation miR-124 Controls Ezh2 Expression during Neurodifferentiation DISCUSSION Neuron-enriched miRNA miR-124 provides a compelling example of a non-coding RNA modulating cellular gene expres- sion at multiple levels (23). Importantly, this miRNA targets miR-124 Controls Ezh2 Expression during Neurodifferentiation miR-124-regulatedEzh2expressionisimportantforP19neuronaldifferentiation.NeuronaldifferentiationofvariousstableP19celllineswasinduce atment for 4 days and followed by the addition of Dox to promote the expression of Ezh2. Cells were analyzed at day 6.5. A, expression of miR-12 lable Ezh2 (Ezh2 or Ezh2 Sub 3UTR) inhibited neuronal differentiation. Neuronal population was defined by Tuj1 staining (red), and total cell number w ed by DAPI staining (blue). Representative images are shown. Scale bar, 50 m. B, statistical analysis of neuronal differentiation. The efficiency of neuron ation was calculated relative to that of Ezh2 WT 3-UTR-expressing cells. The differences between groups were first determined by analysis of variance, an cantdifferencebetweenindicatedpairswasdeterminedbyatwo-tailedStudent’sttestwithequalvariance.Datashownaremean S.D.(errorbars)ofthre ent experiments. C, RT-qPCR analysis for the expression of Ezh2, L1cam, and Syp in the indicated P19 stable cell lines. Data are normalized against Hp n and corresponding cell lines without Dox treatment. Relative mRNA expression levels of the indicated genes were calculated as -fold change compare eneexpressionincellsexpressingEzh2WT3-UTR.Arepresentativeresultwithexperimentaltriplicatesfromthreeindependentexperimentsisshown.Da e mean S.D. of triplicates. Ezh2 protein levels (far right) in cells expressing various Ezh2 constructs were normalized to Tubulin, and -fold change w d relative to the Ezh2 protein level in cells expressing EGFP control. Data shown are mean S.D. of quantifications from three Western blots. D, RT-qPC or the expression of L1cam and Syp in cultured embryonic mouse neural stem cells. Data are normalized against Hprt expression. Relative mRNA expressio he indicated genes were calculated as -fold change compared with the gene expression in EGFP control cells. A representative result with experiment from three independent experiments is shown. Data shown are mean S.E. (error bars). Significant differences between indicated pairs in all panels we ed by two-tailed Student’s t test with equal variance (, p 0.05; , p 0.01; , p 0.001). 24 Controls Ezh2 Expression during Neurodifferentiation FIGURE5.miR-124-regulatedEzh2expressionisimportantforP19neuronaldifferentiation.NeuronaldifferentiationofvariousstableP19celllineswasinduced by RA treatment for 4 days and followed by the addition of Dox to promote the expression of Ezh2. Cells were analyzed at day 6.5. A, expression of miR-124 uncontrollable Ezh2 (Ezh2 or Ezh2 Sub 3UTR) inhibited neuronal differentiation. Neuronal population was defined by Tuj1 staining (red), and total cell number was determined by DAPI staining (blue). Representative images are shown. Scale bar, 50 m. B, statistical analysis of neuronal differentiation. The efficiency of neuronal differentiation was calculated relative to that of Ezh2 WT 3-UTR-expressing cells. The differences between groups were first determined by analysis of variance, and thesignificantdifferencebetweenindicatedpairswasdeterminedbyatwo-tailedStudent’sttestwithequalvariance.Datashownaremean S.D.(errorbars)ofthree independent experiments. miR-124 Controls Ezh2 Expression during Neurodifferentiation erexpression promotes P19 astrocyte differentiation. Neuronal differentiation of various stable P19 cell lines was induced as described in the ells were analyzed at day 12. A, expression of miR-124 uncontrollable Ezh2 (Ezh2 or Ezh2 Sub 3UTR) promotes astrocyte differentiation. Astrocytes fap staining (red), and total cell number was determined by DAPI staining (blue). Representative images are shown. Scale bar, 50 m. B, statistical te differentiation. The efficiency of astrocyte differentiation was calculated relative to that of Ezh2 WT 3-UTR-expressing cells. The differences ere first determined by analysis of variance, and the significant difference between indicated pairs was determined by a two-tailed Student’s t test e.Datashownaremean S.D.(errorbars)ofthreeindependentexperiments.C,RT-qPCRanalysisfortheexpressionofEzh2,Gfap,andS100binthe ecelllines.DataarenormalizedagainstHprtexpressionandcorrespondingcelllineswithoutDoxtreatment.RelativemRNAexpressionlevelsofthe erecalculatedas-foldchangecomparedwiththegeneexpressionincellsexpressingEzh2WT3-UTR.Arepresentativeresultfromthreeindepend- ithexperimentaltriplicatesisshown.Datashownaremean S.D.oftriplicates.D,RT-qPCRanalysisfortheexpressionofGfapandS100bincultured neural stem cells. Data are normalized against Hprt expression. Relative mRNA expression levels of the indicated genes were calculated as -fold with the gene expression in EGFP control cells. Data shown are mean S.E. (error bars) of three independent experiments. E, down-regulation of ting P19 cells at the indicated time points was analyzed by RT-qPCR and normalized against Hprt. A representative result with experimental independent experiments is shown. Data shown are mean S.D. of triplicates. Significant differences between indicated pairs in all panels were o-tailed Student’s t test with equal variance (, p 0.05; , p 0.01; , p 0.001). by guest on August 21, 2014 http://www.jbc.org/ Downloaded from FIGURE 6. Ezh2 overexpression promotes P19 astrocyte differentiation. Neuronal differentiation of various stable P19 FIGURE 6. Ezh2 overexpression promotes P19 astrocyte differentiation. Neuronal differentiation of various stable P19 cell lines was induced as described in the legend to Fig. 5. Cells were analyzed at day 12. A, expression of miR-124 uncontrollable Ezh2 (Ezh2 or Ezh2 Sub 3UTR) promotes astrocyte differentiation. Astrocytes were defined by Gfap staining (red), and total cell number was determined by DAPI staining (blue). Representative images are shown. Scale bar, 50 m. B, statistical analysis of astrocyte differentiation. The efficiency of astrocyte differentiation was calculated relative to that of Ezh2 WT 3-UTR-expressing cells. The differences between groups were first determined by analysis of variance, and the significant difference between indicated pairs was determined by a two-tailed Student’s t test withequalvariance.Datashownaremean S.D.(errorbars)ofthreeindependentexperiments.C,RT-qPCRanalysisfortheexpressionofEzh2,Gfap,andS100binthe indicatedP19stablecelllines.DataarenormalizedagainstHprtexpressionandcorrespondingcelllineswithoutDoxtreatment.RelativemRNAexpressionlevelsofthe indicatedgeneswerecalculatedas-foldchangecomparedwiththegeneexpressionincellsexpressingEzh2WT3-UTR.Arepresentativeresultfromthreeindepend- entexperimentswithexperimentaltriplicatesisshown.Datashownaremean S.D.oftriplicates.D,RT-qPCRanalysisfortheexpressionofGfapandS100bincultured embryonic mouse neural stem cells. Data are normalized against Hprt expression. Relative mRNA expression levels of the indicated genes were calculated as -fold change compared with the gene expression in EGFP control cells. Data shown are mean S.E. VOLUME 289•NUMBER 30•JULY 25, 2014 VOLUME 289•NUMBER 30•JULY 25, 2014 20796 JOURNAL OF BIOLOGICAL CHEMISTRY 20796 VOLUME 289•NUMBER 30•JULY 25, 2014 miR-124 Controls Ezh2 Expression during Neurodifferentiation miR-124 Controls Ezh2 Expression during Neurodifferentiation (error bars) of three independent experiments. E, down-regulation of Chd4 in differentiating P19 cells at the indicated time points was analyzed by RT-qPCR and normalized against Hprt. A representative result with experimental triplicates of three independent experiments is shown. Data shown are mean S.D. of triplicates. Significant differences between indicated pairs in all panels were determined by two-tailed Student’s t test with equal variance (, p 0.05; , p 0.01; *, p 0.001). What could be a molecular mechanism underlying this effect? Ezh2 is known to limit neurogenic competence of neural progenitor cells and repress expression of several neurogenesis-promoting genes (30, 31, 49, 52), including master regulator for neuronal lineage commitment and dif- ferentiation Ascl1/Mash1 (53, 54). Up-regulation of this gene is sufficient to promote neuronal differentiation (55, 56). Notably, Ascl1 is one of the genes consistently dere- pressed by miR-124 in N2a neuroblastoma cells (Table 1), and our future studies will determine the functional signifi- cance of this effect. several master regulators of elaborated transcriptional and post-transcriptional programs, including transcription factor Sox9 (24), transcriptional co-repressor SCP1 (26), chromatin remodeling component BAF53A (27), and RNA-binding pro- tein Ptbp1 (11). Here we expand this list by showing that in cells undergoing neural differentiation (P19 as well as embryonic mouse neural stem cells), miR-124 represses the expression of a critical epigenetic factor, lysine methyltransferase Ezh2. We provide evidence that Ezh2 down-regulation by miR-124 in this context promotes neuronal and counters astrocyte-specific dif- ferentiation route. several master regulators of elaborated transcriptional and post-transcriptional programs, including transcription factor Sox9 (24), transcriptional co-repressor SCP1 (26), chromatin remodeling component BAF53A (27), and RNA-binding pro- tein Ptbp1 (11). Here we expand this list by showing that in cells undergoing neural differentiation (P19 as well as embryonic mouse neural stem cells), miR-124 represses the expression of a critical epigenetic factor, lysine methyltransferase Ezh2. We provide evidence that Ezh2 down-regulation by miR-124 in this context promotes neuronal and counters astrocyte-specific dif- ferentiation route. JOURNAL OF BIOLOGICAL CHEMISTRY 20797 20797 JULY 25, 2014•VOLUME 289•NUMBER 30 JULY 25, 2014•VOLUME 289•NUMBER 30 miR-124 Controls Ezh2 Expression during Neurodifferentiation TABLE 1 miR-124-up-regulated Ezh2 target genes Among miR-124-up-regulated genes (-fold change 1.5 and p 0.001), 74 genes are Ezh2 target genes, and 52 of them are CNS-specific genes as defined in Ref. 39. FC, -fold change. Enrichment of PRC2 at all three miR-124 loci nervous system (16). Interestingly, Ezh2 is known to be up-reg- ulated in activated lymphocytes and play an essential role in this process (59, 60),3 and it would be interesting to examine the role of Ezh2 in the context of microglia activation, which contrib- utes to pathogen clearance in health or the progression of neu- rodegenerative and neoplastic diseases (61). Our analysis also revealed that more than 1800 Ezh2 target genes are not up-regulated in miR-124-overexpressing cells. Non-CNS-specific genes (634 genes) are probably associated with silent chromatin in neuronal progenitors and therefore could not be up-regulated simply by miR-124-mediated Ezh2 down-regulation. A small fraction of Ezh2 target genes with predicted miR-124 target sites could potentially be down-reg- ulated by miR-124 (81 genes; 7 non-CNS and 74 CNS-specific), but only 12 CNS-specific genes were down-regulated in miR- 124-overexpressing cells, which is not statistically enriched. The remaining 1242 CNS-specific genes may require additional CNS-specific activators that are not expressed just 24 h after miR-124 transfection. Although our current analysis already revealed a significant overlap between Ezh2 target genes and the miR-124 up-regulated gene list, more Ezh2 target genes could be up-regulated by persistent miR-124 overexpression in differentiating neurons. Although we show here that miR-124 represents one of the most potent miRNA regulators of Ezh2 expression, our data are also consistent with the possibility of combinatorial regulation by miRNA. Other than miR-124, miR-26a, and miR-101, six additional miRNAs consistently down-regulated the expres- sion of Ezh2 3-UTR reporter genes (Fig. 2D). Of these, only miR-20a, miR-26a, and miR-124 are known to be up-regulated in differentiating P19 cells (62), which predicts possible syner- gistic effects of these three miRNAs on Ezh2 abundance. How- ever, miR-124 is likely to be the major regulator of Ezh2 expres- sion in differentiating neurons, because it is the most abundant miRNA in the brain (12) and is also highly up-regulated in dif- ferentiating P19 cells (20 times for miR-124 versus 2 times for miR-20 and miR-26a) (62). The binding sites of these miRNAs are not overlapping. Other miRNAs identified in our study do not appear to be relevant for differentiating neurons. Enrichment of PRC2 at all three miR-124 loci by guest on August 21, 2014 http://www.jbc.org/ Downloaded from Interestingly, examination of published genomic maps of the Ezh2-specific 3meH3K27 modifications suggests that pro- moter regions of all three mouse miR-124 genes are associated with this repressive mark as well as Suz12, a component of the PRC2 complex, in ES cells (Table 2) (52). It is therefore possible that Ezh2 controls miR-124 levels in stem cells, synergizing with the repressive effect of REST (57). During the neurogenic phase, the H3K27-specific demethylase Jmjd3 is up-regulated, leading to derepression of neuron-specific genes, possibly including miR-124 (58), that can now dampen Ezh2 expression. This hypothetical double-negative feedback between miR-124 and Ezh2/PRC2 would be similar to the previously reported relationship between miR-124 and SCP1/REST (26). In conclusion, our study suggests that miRNA control of an important epigenetic regulator can be used as a regulatory par- adigm for modulating the choice between alternative differen- tiation scenarios. Acknowledgment—We thank Weijun Dai for helpful discussions. miR-124 Controls Ezh2 Expression during Neurodifferentiation Gene symbol Gene name FC CNS-specific Morc4 Microrchidia 4 2.932 No Tpm1 Tropomyosin 1, 2.705 Yes Col8a2 Collagen, type VIII, 2 2.494 No Dusp8 Dual specificity phosphatase 8 2.371 Yes Atf3 Activating transcription factor 3 2.244 Yes Prlr Prolactin receptor 2.128 Yes Mt1 Metallothionein 1 2.102 Yes Smox Spermine oxidase 2.096 Yes Klhl22 Kelch-like 22 (Drosophila) 2.070 Yes Plxna2 Plexin A2 2.054 Yes Fbn2 Fibrillin 2 1.990 Yes Sema7a Sema domain, immunoglobulin domain (Ig), and GPI membrane anchor, (semaphorin) 7A 1.989 Yes Igfbp6 Insulin-like growth factor-binding protein 6 1.946 Yes Igfbp5 Insulin-like growth factor binding protein 5 1.925 Yes Atp1a3 ATPase, Na/K transporting, 3 polypeptide 1.892 Yes Chrm3 Cholinergic receptor, muscarinic 3, cardiac 1.862 No Tgfb3 Transforming growth factor, 3 1.852 Yes Adora2b Adenosine A2b receptor 1.841 Yes Ap3m2 Adaptor-related protein complex 3, 2 subunit 1.839 Yes Shroom3 Shroom family member 3 1.830 Yes Oxt Oxytocin 1.816 Yes Gnao1 Guanine nucleotide-binding protein, O 1.780 Yes Kcnk9 Potassium channel, subfamily K, member 9 1.777 No Crhbp Corticotropin-releasing hormone-binding protein 1.768 Yes Slc35f1 Solute carrier family 35, member F1 1.749 Yes Faah Fatty acid amide hydrolase 1.746 Yes Nphs2 Nephrosis 2 homolog, podocin (human) 1.743 No Pax7 Paired box gene 7 1.729 No Sypl2 Synaptophysin-like 2 1.718 Yes Gpc5 Glypican 5 1.714 Yes Kcne3 Potassium voltage-gated channel, Isk-related subfamily, gene 3 1.707 No Sp7 Sp7 transcription factor 7 1.705 Yes Epha5 Eph receptor A5 1.703 Yes Gpc4 Glypican 4 1.701 Yes Itpka Inositol 1,4,5-trisphosphate 3-kinase A 1.691 Yes Gprc5c G protein-coupled receptor, family C, group 5, member C 1.682 No Irx6 Iroquois-related homeobox 6 (Drosophila) 1.680 No Hhat Hedgehog acyltransferase 1.678 No Gpr45 G protein-coupled receptor 45 1.678 Yes Celsr2 Cadherin, EGF LAG seven-pass G-type receptor 2 (flamingo homolog, Drosophila) 1.664 Yes Kirrel3 Kin of IRRE like 3 (Drosophila) 1.662 Yes Cyp46a1 Cytochrome P450, family 46, subfamily a, polypeptide 1 1.661 Yes Hoxc12 Homeobox C12 1.656 No Tcfap2b Transcription factor AP-2 1.640 No Nkx1-2 NK1 transcription factor-related, locus 2 (Drosophila) 1.638 No Nol3 Nucleolar protein 3 (apoptosis repressor with CARD domain) 1.632 Yes Rab15 RAB15, member RAS oncogene family 1.630 Yes Nuak2 NUAK family, SNF1-like kinase, 2 1.629 No Tmem28 Transmembrane protein 28 1.628 Yes Hmx1 H6 homeobox 1 1.625 No Spryd3 SPRY domain-containing 3 1.624 Yes Btbd11 BTB (POZ) domain containing 11 1.613 Yes Adamtsl5 ADAMTS-like 5 1.610 No C1qtnf4 C1q and tumor necrosis factor related protein 4 1.607 Yes Cacna2d2 Calcium channel, voltage-dependent, 2/ subunit 2 1.603 Yes Dpp10 Dipeptidylpeptidase 10 1.594 Yes Zmiz1 Zinc finger, MIZ-type-containing 1 1.591 Yes Hoxa9 Homeobox A9 1.589 No Calb1 Calbindin 1 1.585 Yes Pstpip2 Proline-serine-threonine phosphatase-interacting protein 2 1.583 Yes Plagl1 Pleiomorphic adenoma gene-like 1 1.581 Yes Nkx2-6 NK2 transcription factor related, locus 6 (Drosophila) 1.579 No Trim54 Tripartite motif-containing 54 1.562 No Gpr6 G protein-coupled receptor 6 1.552 Yes Apln Apelin 1.547 Yes Snx22 Sorting nexin 22 1.534 Yes Alx4 Aristaless-like homeobox 4 1.534 No Nxph4 Neurexophilin 4 1.526 No En2 Engrailed 2 1.522 Yes Tmem25 Transmembrane protein 25 1.520 Yes Tubb2b Tubulin, 2B 1.513 Yes Ybx2 Y box protein 2 1.506 No Il12 b1 I l ki 12 1 1 505 Y by guest on August 21, 2014 http://www.jbc.org/ Downloaded from miR-124-up-regulated Ezh2 target genes VOLUME 289•NUMBER 30•JULY 25, 2014 20798 JOURNAL OF BIOLOGICAL CHEMISTRY TABLE 2 Enrichment of PRC2 at all three miR-124 loci ChIP-seq data were selected from a previous publication (52), which shows the enrichment of Oct4, Sox2, Nanog, Tcf3, Suz12, and 3meH3K27 at different miR-124 loci. 3 W. H. Neo and I.-H. Su, unpublished data. Acknowledgment—We thank Weijun Dai for helpful discussions. miR-124 Controls Ezh2 Expression during Neurodifferentiation Loci Positions of miR-124 promoter Positions of Pre-miR-124 Suz12 binding sites Other transcription factors or histone modification associated with miR-124 loci mmu-mir-124-1 chr14:63540450–63546275 chr14:63544772–63544848 () chr14:63540776–63544525 Oct4 Nanog 3meH3K27 mmu-mir-124-2 chr3:17986635–17986835 chr3:17987829–17987903 () chr3:17985751–17988075 Oct4 Sox2 Nanog Tcf3 3meH3K27 mmu-mir-124-3 chr2:180819000–180825000 chr2:180823445–180823520 () chr2:180820551–180823275 Oct4 3meH3K27 miR-124 Controls Ezh2 Expression during Neurodifferentiation miR-124 Controls Ezh2 Expression during Neurodifferentiation miR-124 Controls Ezh2 Expression during Neurodifferentiation TABLE 2 JULY 25, 2014•VOLUME 289•NUMBER 30 by guest on August 21, 2014 http://www.jbc.org/ Downloaded from 36. Lohse, M., Bolger, A. M., Nagel, A., Fernie, A. R., Lunn, J. E., Stitt, M., and Usadel, B. (2012) RobiNA: a user-friendly, integrated software solution for RNA-Seq-based transcriptomics. Nucleic Acids Res. 40, W622–W627 16. Ponomarev, E. D., Veremeyko, T., Barteneva, N., Krichevsky, A. M., and Weiner, H. L. (2011) MicroRNA-124 promotes microglia quiescence and suppresses EAE by deactivating macrophages via the C/EBP--PU. 1 pathway. Nat. Med. 17, 64–70 37. Mootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., Houstis, N., Daly, M. J., Patterson, N., Mesirov, J. P., Golub, T. R., Tamayo, P., Spiegelman, B., Lander, E. S., Hirschhorn, J. N., Altshuler, D., and Groop, L. C. (2003) PGC-1-responsive genes involved in oxidative phosphor- ylation are coordinately downregulated in human diabetes. Nat. Genet. 34, 267–273 17. Deo, M., Yu, J.-Y., Chung, K.-H., Tippens, M., and Turner, D. L. (2006) Detection of mammalian microRNA expression by in situ hybridization with RNA oligonucleotides. Dev. Dyn. 235, 2538–2548 18. Conaco, C., Otto, S., Han, J.-J., and Mandel, G. (2006) Reciprocal actions of REST and a microRNA promote neuronal identity. Proc. Natl. Acad. Sci. U.S.A. 103, 2422–2427 38. Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., and Mesirov, J. P. (2005) Gene set enrichment analysis: A knowledge- based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. U.S.A. 102, 15545–15550 19. Sanuki, R., Onishi, A., Koike, C., Muramatsu, R., Watanabe, S., Muranishi, Y., Irie, S., Uneo, S., Koyasu, T., and Matsui, R. (2011) miR-124a is required for hippocampal axogenesis and retinal cone survival through Lhx2 sup- pression. Nat. Neurosci. 14, 1125–1134 20. Chi, S. W., Zang, J. B., Mele, A., and Darnell, R. B. (2009) Argonaute HITS-CLIP decodes microRNA-mRNA interaction maps. Nature 460, 479–486 39. Cahoy, J. D., Emery, B., Kaushal, A., Foo, L. C., Zamanian, J. L., Chris- topherson, K. S., Xing, Y., Lubischer, J. L., Krieg, P. A., Krupenko, S. A., Thompson, W. J., and Barres, B. A. (2008) A transcriptome database for astrocytes, neurons, and oligodendrocytes: a new resource for under- standing brain development and function. J. Neurosci. 28, 264–278 21. Hendrickson, D. G., Hogan, D. J., McCullough, H. L., Myers, J. W., Her- schlag, D., Ferrell, J. E., and Brown, P. O. miR-124 Controls Ezh2 Expression during Neurodifferentiation in sight? Nat. Rev. Genet. 9, 102–114 R. M., Chevalier, B., Johnstone, S. E., Cole, M. F., and Isono, K. (2006) Control of developmental regulators by Polycomb in human embryonic stem cells. Cell 125, 301–313 R. M., Chevalier, B., Johnstone, S. E., Cole, M. F., and Isono, K. (2006) Control of developmental regulators by Polycomb in human embryonic stem cells. Cell 125, 301–313 in sight? Nat. Rev. Genet. 9, 102–114 9. De Pietri Tonelli, D., Pulvers, J. N., Haffner, C., Murchison, E. P., Hannon, 9. De Pietri Tonelli, D., Pulvers, J. N., Haffner, C., Murchison, E. P., Hannon, G. J., and Huttner, W. B. (2008) miRNAs are essential for survival and differentiation of newborn neurons but not for expansion of neural pro- genitors during early neurogenesis in the mouse embryonic neocortex. Development 135, 3911–3921 30. Bracken, A. P., Dietrich, N., Pasini, D., Hansen, K. H., and Helin, K. (2006) Genome-wide mapping of Polycomb target genes unravels their roles in cell fate transitions. Genes Dev. 20, 1123–1136 10. Kawase-Koga, Y., Otaegi, G., and Sun, T. (2009) Different timings of Dicer deletion affect neurogenesis and gliogenesis in the developing mouse cen- tral nervous system. Dev. Dyn. 238, 2800–2812 31. Boyer, L. A., Plath, K., Zeitlinger, J., Brambrink, T., Medeiros, L. A., Lee, T. I., Levine, S. S., Wernig, M., Tajonar, A., and Ray, M. K. (2006) Poly- comb complexes repress developmental regulators in murine embryonic stem cells. Nature 441, 349–353 11. Makeyev, E. V., Zhang, J., Carrasco, M. A., and Maniatis, T. (2007) The MicroRNA miR-124 promotes neuronal differentiation by triggering brain-specific alternative pre-mRNA splicing. Mol. Cell 27, 435–448 32. Zheng, F., Liao, Y. J., Cai, M. Y., Liu, Y. H., Liu, T. H., Chen, S. P., Bian, X. W., Guan, X. Y., Lin, M. C., and Zeng, Y. X. (2012) The putative tumour suppressor microRNA-124 modulates hepatocellular carcinoma cell ag- gressiveness by repressing ROCK2 and EZH2. Gut 61, 278–289 12. Lagos-Quintana, M., Rauhut, R., Yalcin, A., Meyer, J., Lendeckel, W., and Tuschl, T. (2002) Identification of tissue-specific microRNAs from mouse. Curr. Biol. 12, 735–739 33. Khandelia, P., Yap, K., and Makeyev, E. V. (2011) Streamlined platform for short hairpin RNA interference and transgenesis in cultured mammalian cells. Proc. Natl. Acad. Sci. 108, 12799–12804 13. Colin, A., Faideau, M., Dufour, N., Auregan, G., Hassig, R., Andrieu, T., Brouillet, E., Hantraye, P., Bonvento, G., and De´glon, N. by guest on August 21, 2014 http://www.jbc.org/ Downloaded from (2009) Concordant regulation of translation and mRNA abundance for hundreds of targets of a human microRNA. PLoS Biol. 7, e1000238 40. Margueron, R., Li, G., Sarma, K., Blais, A., Zavadil, J., Woodcock, C. L., Dynlacht, B. D., and Reinberg, D. (2008) Ezh1 and Ezh2 maintain repres- sive chromatin through different mechanisms. Mol. Cell 32, 503–518 22. Lim, L. P., Lau, N. C., Garrett-Engele, P., Grimson, A., Schelter, J. M., Castle, J., Bartel, D. P., Linsley, P. S., and Johnson, J. M. (2005) Microarray analysis shows that some microRNAs downregulate large numbers of tar- get mRNAs. Nature 433, 769–773 41. Sempere, L. F., Freemantle, S., Pitha-Rowe, I., Moss, E., Dmitrovsky, E., and Ambros, V. (2004) Expression profiling of mammalian microRNAs uncovers a subset of brain-expressed microRNAs with possible roles in murine and human neuronal differentiation. Genome Biol. 5, R13 23. Makeyev, E. V., and Maniatis, T. (2008) Multilevel regulation of gene expression by microRNAs. Science 319, 1789–1790 42. Varambally, S., Cao, Q., Mani, R. S., Shankar, S., Wang, X., Ateeq, B., Laxman, B., Cao, X., Jing, X., and Ramnarayanan, K. (2008) Genomic loss of microRNA-101 leads to overexpression of histone methyltransferase EZH2 in cancer. Science 322, 1695–1699 24. Cheng, L. C., Pastrana, E., Tavazoie, M., and Doetsch, F. (2009) miR-124 regulates adult neurogenesis in the subventricular zone stem cell niche. Nat. Neurosci. 12, 399–408 43. Sander, S., Bullinger, L., Klapproth, K., Fiedler, K., Kestler, H. A., Barth, T. F., Mo¨ller, P., Stilgenbauer, S., Pollack, J. R., and Wirth, T. (2008) MYC stimulates EZH2 expression by repression of its negative regulator miR- 26a. Blood 112, 4202–4212 25. Rajasethupathy, P., Fiumara, F., Sheridan, R., Betel, D., Puthanveettil, S. V., Russo, J. J., Sander, C., Tuschl, T., and Kandel, E. (2009) Characterization of small RNAs in aplysia reveals a role for miR-124 in constraining synap- tic plasticity through CREB. Neuron 63, 803–817 44. Bartel, D. P. (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116, 281–297 26. Visvanathan, J., Lee, S., Lee, B., Lee, J. W., and Lee, S. K. (2007) The microRNA miR-124 antagonizes the anti-neural REST/SCP1 pathway during embryonic CNS development. Genes Dev. 21, 744–749 45. McBurney, M. W., Jones-Villeneuve, E. M., Edwards, M. K., and Ander- son, P. J. (1982) Control of muscle and neuronal differentiation in a cul- tured embryonal carcinoma cell line. Nature 299, 165–167 27. Yoo, A. S., Staahl, B. T., Chen, L., and Crabtree, G. R. REFERENCES p Although further work will be needed to address the miR- 124-Ezh2/PRC2 cross-regulation model, the results of our pre- liminary studies are consistent with this possibility. Indeed, induction of Ezh2 expression following RA treatment led to dramatic down-regulation of miR-124 expression in differenti- ating P19 cultures (data not shown). Thus, it is possible that the stimulatory effect of miR-124-resistant Ezh2 on astrocyte gen- eration observed in our study might be caused by Ezh2-medi- ated down-regulation of miR-124 expression. Underscoring the biological relevance of these regulatory events, miR-124 is nat- urally expressed in neurons but not in astrocytes (15), and it is predicted to directly down-regulate a number of astrocyte-en- riched genes (22, 39). 1. Lee, R. C., Feinbaum, R. L., and Ambros, V. (1993) The C. elegans hetero- chronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75, 843–854 2. Ivey, K. N., and Srivastava, D. (2010) MicroRNAs as regulators of differ- entiation and cell fate decisions. Cell Stem Cell 7, 36–41 3. Lewis, B. P., Burge, C. B., and Bartel, D. P. (2005) Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120, 15–20 4. Griffiths-Jones, S. (2006) The microRNA sequence database. Methods Mol. Biol. 342, 129–138 5. Kim, V. N. (2005) MicroRNA biogenesis: coordinated cropping and dic- ing. Nat. Rev. Mol. Cell Biol. 6, 376–385 6. Ender, C., and Meister, G. (2010) Argonaute proteins at a glance. J. Cell Sci. 123, 1819–1823 7. Pasquinelli, A. E. (2012) MicroRNAs and their targets: recognition, regu- lation and an emerging reciprocal relationship. Nat. Rev. Genet. 13, 271–282 In addition to its role in balancing neurogenesis versus astro- genesis, the miR-124/Ezh2 circuitry may function in other bio- logical scenarios. For example, it has been recently proposed to control aggressiveness of hepatocellular carcinoma (32). Another recent study showed that miR-124 may prevent the activation of microglia, immune cells residing in the central 8. Filipowicz, W., Bhattacharyya, S. N., and Sonenberg, N. (2008) Mecha- nisms of post-transcriptional regulation by microRNAs: are the answers 8. Filipowicz, W., Bhattacharyya, S. N., and Sonenberg, N. (2008) Mecha- nisms of post-transcriptional regulation by microRNAs: are the answers JULY 25, 2014•VOLUME 289•NUMBER 30 JOURNAL OF BIOLOGICAL CHEMISTRY 20799 VOLUME 289•NUMBER 30•JULY 25, 2014 miR-124 Controls Ezh2 Expression during Neurodifferentiation (2009) Engineered lentiviral vector targeting astrocytes in vivo. Glia 57, 667–679 34. Yeo, M., Lee, S. K., Lee, B., Ruiz, E. C., Pfaff, S. L., and Gill, G. N. (2005) Small CTD phosphatases function in silencing neuronal gene expression. Sci. Signal. 307, 596 14. Åkerblom, M., Sachdeva, R., Barde, I., Verp, S., Gentner, B., Trono, D., and Jakobsson, J. (2012) MicroRNA-124 Is a Subventricular Zone Neuronal Fate Determinant. J. Neurosci. 32, 8879–8889 35. Juvvuna, P. K., Khandelia, P., Lee, L. M., and Makeyev, E. V. (2012) Argo- naute identity defines the length of mature mammalian microRNAs. Nu- cleic Acids Res. 40, 6808–6820 15. Smirnova, L., Gra¨fe, A., Seiler, A., Schumacher, S., Nitsch, R., and Wulc- zyn, F. G. (2005) Regulation of miRNA Expression during Neural Cell Specification. Eur. J. Neurosci. 21, 1469–1477 20800 JOURNAL OF BIOLOGICAL CHEMISTRY by guest on August 21, 2014 http://www.jbc.org/ Downloaded from (2009) MicroRNA- mediated switching of chromatin-remodelling complexes in neural devel- opment. Nature 460, 642–646 46. Staines, W. A., Craig, J., Reuhl, K., and McBurney, M. W. (1996) Retinoic acid treated P19 embryonal carcinoma cells differentiate into oligoden- drocytes capable of myelination. Neuroscience 71, 845–853 28. Yap, K., Lim, Z. Q., Khandelia, P., Friedman, B., and Makeyev, E. V. (2012) Coordinated regulation of neuronal mRNA steady-state levels through developmentally controlled intron retention. Genes Dev. 26, 1209–1223 47. Koshkin, A. A., Singh, S. K., Nielsen, P., Rajwanshi, V. K., Kumar, R., Meldgaard, M., Olsen, C. E., and Wengel, J. (2012) LNA-based oligonu- 29. Lee, T. I., Jenner, R. G., Boyer, L. A., Guenther, M. G., Levine, S. S., Kumar, miR-124 Controls Ezh2 Expression during Neurodifferentiation cleotide electrotransfer for miRNA inhibition. Mol. Ther. 20, 1590–1598 mitter identity of neurones derived from expanded adult neural stem cells. Eur. J. Neurosci. 25, 2581–2590 cleotide electrotransfer for miRNA inhibition. Mol. Ther. 20, 1590–1598 48. Krichevsky, A. M., Sonntag, K.-C., Isacson, O., and Kosik, K. S. (2006) Specific microRNAs modulate embryonic stem cell-derived neurogenesis. Stem Cells 24, 857–864 56. Geoffroy, C. G., Critchley, J. A., Castro, D. S., Ramelli, S., Barraclough, C., Descombes, P., Guillemot, F., and Raineteau, O. (2009) Engineering of dominant active basic helix-loop-helix proteins that are resistant to neg- ative regulation by postnatal central nervous system antineurogenic cues. Stem Cells 27, 847–856 49. Hirabayashi, Y., Suzki, N., Tsuboi, M., Endo, T. A., Toyoda, T., Shinga, J., Koseki, H., Vidal, M., and Gotoh, Y. (2009) Polycomb limits the neuro- genic competence of neural precursor cells to promote astrogenic fate transition. Neuron 63, 600–613 57. Singh, S. K., Kagalwala, M. N., Parker-Thornburg, J., Adams, H., and Ma- jumder, S. (2008) REST maintains self-renewal and pluripotency of em- bryonic stem cells. Nature 453, 223–227 50. Kazama, H., Kodera, T., Shimizu, S., Mizoguchi, H., and Morishita, K. (1999) Ecotropic viral integration site-1 is activated during, and is suffi- cient for, neuroectodermal P19 cell differentiation. Cell Growth Differ. 10, 565–573 58. Jepsen, K., Solum, D., Zhou, T., McEvilly, R. J., Kim, H.-J., Glass, C. K., Hermanson, O., and Rosenfeld, M. G. (2007) SMRT-mediated repression of an H3K27 demethylase in progression from neural stem cell to neuron. Nature 450, 415–419 51. Sparmann, A., Xie, Y., Verhoeven, E., Vermeulen, M., Lancini, C., Gar- giulo, G., Hulsman, D., Mann, M., Knoblich, J. A., and van Lohuizen, M. (2013) The chromodomain helicase Chd4 is required for Polycomb-me- diated inhibition of astroglial differentiation. EMBO J. 32, 1598–1612 59. Su, I.-H., Dobenecker, M.-W., Dickinson, E., Oser, M., Basavaraj, A., Mar- queron, R., Viale, A., Reinberg, D., Wu¨lfing, C., and Tarakhovsky, A. (2005) Polycomb group protein ezh2 controls actin polymerization and cell signaling. Cell 121, 425–436 52. Marson, A., Levine, S. S., Cole, M. F., Frampton, G. M., Brambrink, T., Johnstone, S., Guenther, M. G., Johnston, W. K., Wernig, M., and New- man, J. (2008) Connecting microRNA genes to the core transcriptional regulatory circuitry of embryonic stem cells. Cell 134, 521–533 60. Su, I.-H., Basavaraj, A., Krutchinsky, A. N., Hobert, O., Ullrich, A., Chait, B. T., and Tarakhovsky, A. VOLUME 289•NUMBER 30•JULY 25, 2014 20800 JOURNAL OF BIOLOGICAL CHEMISTRY JULY 25, 2014•VOLUME 289•NUMBER 30 miR-124 Controls Ezh2 Expression during Neurodifferentiation (2003) Ezh2 controls B cell development through histone H3 methylation and Igh rearrangement. Nat. Immunol. 4, 124–131 53. Parras, C. M., Schuurmans, C., Scardigli, R., Kim, J., Anderson, D. J., and Guillemot, F. (2002) Divergent functions of the proneural genes Mash1 and Ngn2 in the specification of neuronal subtype identity. Genes Dev. 16, 324–338 61. Saijo, K., and Glass, C. K. (2011) Microglial cell origin and phenotypes in health and disease. Nat. Rev. Immunol. 11, 775–787 by guest on August 21, 2014 http://www.jbc.org/ Downloaded from 54. Fode, C., Ma, Q., Casarosa, S., Ang, S.-L., Anderson, D. J., and Guillemot, F. (2000) A role for neural determination genes in specifying the dorso- ventral identity of telencephalic neurons. Genes Dev. 14, 67–80 62. Huang, B., Li, W., Zhao, B., Xia, C., Liang, R., Ruan, K., Jing, N., and Jin, Y. (2009) MicroRNA expression profiling during neural differentiation of mouse embryonic carcinoma P19 cells. Acta Biochim. Biophys. Sin. 41, 231–236 55. Berninger, B., Guillemot, F., and Go¨tz, M. (2007) Directing neurotrans- JULY 25, 2014•VOLUME 289•NUMBER 30 JOURNAL OF BIOLOGICAL CHEMISTRY 20801
https://openalex.org/W2623141293	http://jurnal.unissula.ac.id/index.php/jai/article/download/855/692	Indonesian	null	ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI MINAT MAHASISWA AKUNTANSI UNTUK MENGIKUTI PENDIDIKAN PROFESI AKUNTANSI DITINJAU DARI GENDER DAN STATUS AKREDITASI PROGRAM STUDI	Jurnal Akuntansi Indonesia	2,016	cc-by-sa	3,523	JUR Jurnal Akuntansi Indonesia, Vol. 2 No. 1 Januari 2013, Hal. 17-25 JUR Jurnal Akuntansi Indonesia, Vol. 2 No. 1 Januari 2013, Hal. 17-25 Keywords: motivation, gender, accredition, Accounting Profession. Keywords: motivation, gender, accredition, Accounting Profession. Abstract Abstract The purpose of this research to analyze the influence of career motivation, motivational qualities, economic motivation, motivation degree, the motivation to follow Certification Exam Certified Public Accountants, the cost of education and a long interest in the education of accounting students to follow the Accounting Profession. Population in this research that students majoring in accounting at a private college in Semarang, purposive sampling technique used for sample retrieval and obtained a sample of 50 respondents, the data analysis techniques used multiple linear regression These results indicate that the economic motivation, motivation and motivation to follow quality Certification Exam Certified Public Accountants significantly influence accounting students’ interest to follow Accounting Profession. Career motivation, degree of motivation, education costs and length of education did not significantly affect student interest in accounting to follow the Accounting Profession. Other results showed that no significant differences in student interest in accounting to follow the Accounting Profession in terms of gender, and there is also no significant difference in student interest in accounting to follow the Accounting Profession in terms of accreditation status JURNAL AKUNTANSI INDONESIA maka pemberian gelar akuntan bukan lagi monopoli Perguruan Tinggi Negeri (PTN) tertentu yang diberi hak istimewa oleh Depdiknas akan tetapi tidak menutup kemungkinan PPAk diselenggarakan oleh Perguruan Tinggi Swasta (PTS) yang memiliki kesetaraan dengan Perguruan Tinggi Negeri. Dengan demikian diharapkan para akuntan di masa akan datang, khususnya dalam era globalisasi ekonomi abad 21, akan menjadi akuntan yang profesional dan siap menghadapi persaingan di tingkat global. maka pemberian gelar akuntan bukan lagi monopoli Perguruan Tinggi Negeri (PTN) tertentu yang diberi hak istimewa oleh Depdiknas akan tetapi tidak menutup kemungkinan PPAk diselenggarakan oleh Perguruan Tinggi Swasta (PTS) yang memiliki kesetaraan dengan Perguruan Tinggi Negeri. Dengan demikian diharapkan para akuntan di masa akan datang, khususnya dalam era globalisasi ekonomi abad 21, akan menjadi akuntan yang profesional dan siap menghadapi persaingan di tingkat global. Widyastuti, dkk (2004) menyatakan bahwa motivasi karir merupakan faktor yang paling signifikan mempengaruhi minat mahasiswa untuk mengikuti PPAk, sedangkan motivasi kualitas dan motivasi ekonomi tidak signifikan. Suranta dan Syafiqurrahman (2006) menyatakan bahwa motivasi karir dan motivasi kualitas berpengaruh signifikan terhadap minat mahasiswa untuk mengikuti PPAk, sedangkan motivasi ekonomi tidak berpengaruh signifikan terhadap minat mahasiswa untuk mengikuti PPAk. Gender dalam kebudayaan timur merupakan faktor yang erat hubungannya dalam karir dengan batasan wanita untuk beraktivitas. Pandangan masyarakat luas, status wanita umumnya dianggap lebih rendah dari pria. Peran wanita dalam berkarir dihalangi oleh persoalan budaya dan kodrat wanita yang menuntut peranan yang lebih dalam rumah tangga dibandingkan dalam bekerja. Wanita juga sering kali kurang mendapat kesempatan dan penghasilan yang sama dikarenakan adanya kesalahan persepsi terhadap kemampuan mereka (Ancok, 1995). Penelitian yang dilakukan Sudaryono, dkk (2005) menyatakan bahwa tidak ada perbedaan yang signifikan minat mahasiswa akuntansi dalam mengikuti PPAk ditinjau dari segi gender. Hasil ini didukung oleh penelitian yang dilakukan Machfoedz (1998) yang menyatakan bahwa minat mahasiswa mengikuti USAP tidak dipengaruhi oleh gender. Setiap Perguruan Tinggi atau bahkan setiap program studinya memiliki status akreditasi yang tidak sama. Baik itu untuk Perguruan Tinggi Negeri maupun Perguruan Tinggi Swasta. Penelitian yang dilakukan Sudaryono, dkk (2005) menyatakan bahwa tidak ada perbedaan minat yang signifikan antara mahasiswa yang berasal dari program studi yang terakreditasi A dan B. Sedangkan perbedaan minat mengikuti PPAk terjadi antara mahasiswa yang berasal dari program studi yang terakreditas A dan C, dan juga antara mahasiswa yang berasal dari program studi yang terakeditasi B dan C. JURNAL AKUNTANSI INDONESIA Dengan menjadikan penelitian sebelumnya yang telah dilakukan oleh Benny dan Yuskar (2006) sebagai acuan, penelitian ini akan mencoba merumuskan mengenai faktor-faktor apa saja yang mempengaruhi minat mahasiswa akuntansi untuk mengikuti Pendidikan Profesi Akuntansi (PPAk) ditinjau dari gender dan status akreditasi program studi. Lisnasari dan Fitriany (2008) melakukan penelitian untuk mengetahui faktor-faktor yang mempengaruhi minat mahasiswa akuntansi untuk mengikuti Pendidikan Profesi Akuntansi (PPAk) dengan analisis regresi linier berganda. Hasil yang didapat yaitu motivasi karier dan motivasi mengikuti USAP merupakan faktor yang secara signifikan mempengaruhi minat mahasiswa untuk mengikuti PPAk. PENDAHILUAN Seorang sarjana lulusan akuntansi dituntut untuk lebih profesional pada era globalisasi saat ini. Hal ini disebabkan adanya tuntutan dari dunia bisnis dan ekonomi yang semakin meningkat. Perkembangan profesi akuntan mempunyai hubungan erat dengan tata nilai dan budaya yang berkembang di tengah masyarakat. Hal ini mengakibatkan profesi akuntan tidak bisa lepas dari perkembangan yang terjadi di negeri ini. Oleh karena itu, profesi akuntan dituntut untuk dapat menjawab tantangan yang ditimbulkan oleh perubahan lingkungan. Konsekuensi dari adanya perubahan lingkungan dan perkembangan dunia usaha pada dasarnya menuntut peningkatan kualitas diri dari akuntan dalam memberikan jasa profesionalnya. Mahasiswa yang mengikuti Pendidikan Profesi Akuntansi (PPAk) adalah calon akuntan yang nantinya berhak mengikuti Ujian Sertifikasi Akuntan Publik (USAP). Ujian ini merupakan syarat penting untuk mendapatkan ijin praktik sebagai akuntan publik. Dengan mengikuti ujian ini, diharapakan calon akuntan di masa depan tidak hanya mahir secara teknis namun juga mahir secara profesional. Dengan demikian, lulusan PPAk nantinya akan memiliki daya saing sebagai akuntan yang lebih tinggi dibandingkan dengan sarjana ekonomi dari jurusan akuntansi yang tidak mempunyai predikat akuntan. Pendidikan Profesi Akuntansi (PPAk) di Indonesia mulai berdiri sejak September 2002. Adanya PPAk ini 17 KUNTANSI UNTUK MENGIKUTI PENDIDIKAN PROFESI AKUNTANSI TINJAU DARI GENDER DAN STATUS AKREDITASI PROGRAM STUDI Edy Suprianto & Mifkhatun Nikmahi Korespondensi dengan penulis: Edy Suprianto & Mifkhatun Nikmahi Fakultas Ekonomi Universitas Islam Sultan Agung Semarang UNTANSI UNTUK MENGIKUTI PENDIDIKAN PROFESI AKUNTANSI NJAU DARI GENDER DAN STATUS AKREDITASI PROGRAM STUDI Edy Suprianto & Mifkhatun Nikmahi Korespondensi dengan penulis: Edy Suprianto & Mifkhatun Nikmahi Fakultas Ekonomi Universitas Islam Sultan Agung Semarang UNTANSI UNTUK MENGIKUTI PENDIDIKAN PROFESI AKUNTANSI NJAU DARI GENDER DAN STATUS AKREDITASI PROGRAM STUDI Edy Suprianto & Mifkhatun Nikmahi Korespondensi dengan penulis: Edy Suprianto & Mifkhatun Nikmahi Fakultas Ekonomi Universitas Islam Sultan Agung Semarang 17 Jurnal Akuntansi Indonesia Minat Minat adalah keinginan yang didorong oleh suatu keinginan setelah melihat, mengamati dan membandingkan serta mempertimbangkan dengan kebutuhan yang diinginkannya (Widyastuti, dkk, 2004). Minat juga dapat diartikan sebagai kecenderungan bertingkah laku yang terarah terhadap objek kegiatan atau pengalaman tertentu (Ensiklopedia Indonesia IV, 1998:2252). Secara garis besar minat adalah kecenderungan seseorang yang menunjukkan perhatian terhadap suatu subjek tertentu, dalam hal ini berhubungan dengan minat mengikuti Pendidikan Profesi Akuntansi (PPAk). Hipotesis 2: Motivasi kualitas mempengaruhi minat mahasiswa akuntansi untuk mengikuti PPAk. Hipotesis 3: Motivasi ekonomi mempengaruhi minat mahasiswa akuntansi untuk mengikuti PPAk. Profesi Akuntan Menurut International Federation of Accountants yang dimaksud profesi akuntan adalah semua bidang pekerjaan yang mempergunakan keahlian di bidang akuntansi, termasuk bidang pekerjaan akuntan publik, akuntan intern yang bekerja pada perusahaan industri, keuangan atau dagang, akuntan yang bekerja di pemerintah, dan akuntan sebagai pendidik. Ciri yang sangat menonjol dari profesi adalah adanya pengakuan atas tanggung jawabnya kepada masyarakat. Bagi profesi akuntansi (para akuntan), IFAC mengidentifikasikan ruang lingkup masyarakat yang menjadi tanggung jawab akuntan meliputi: klien, kreditur, perusahan pemberi jasa, karyawan, investor, pemerintah, masyarakat keuangan dan dunia usaha pada umumnya. Hipotesis 4: Motivasi gelar mempengaruhi minat mahasiswa akuntansi untuk mengikuti PPAk. Hipotesis 4: Motivasi gelar mempengaruhi minat mahasiswa akuntansi untuk mengik JURNAL AKUNTANSI INDONESIA suatu tindakan dengan tujuan tertentu. Motivasi juga merupakan usaha-usaha yang dapat menyebabkan seseorang atau kelompok orang tertentu tergerak melakukan sesuatu karena ingin mencapai tujuan yang dikehendakinya atau mendapat kepuasan dengan perbuatannya (Kamus Besar Bahasa Indonesia,1998). suatu tindakan dengan tujuan tertentu. Motivasi juga merupakan usaha-usaha yang dapat menyebabkan seseorang atau kelompok orang tertentu tergerak melakukan sesuatu karena ingin mencapai tujuan yang dikehendakinya atau mendapat kepuasan dengan perbuatannya (Kamus Besar Bahasa Indonesia,1998). Widyastuti, dkk (2004) menyatakan bahwa motivasi seringkali diartikan sebagai dorongan. Dorongan atau tenaga tersebut merupakan gerak jiwa dan jasmani untuk berbuat, sehingga motivasi merupakan suatu tenaga yang menggerakkan manusia untuk bertingkah laku didalam perbuatannya yang mempunyai tujuan tertentu. Hipotesis 1: Motivasi karir mempengaruhi minat mahasiswa akuntansi untuk mengikuti PPAk. Motivasi Karir Motivasi adalah dorongan yang timbul pada diri seseorang, sadar atau tidak sadar untuk melakukan Jurnal Akuntansi Indonesia Jurnal Akuntansi Indonesia 18 18 Vol. 2 No. 1 Januari 2013 JURNAL AKUNTANSI INDONESIA BAP dikeluarkan oleh Ikatan Akuntan Indonesia (IAI). Akuntan dengan sebutan BAP akan memperoleh pengakuan atas kompetensi dalam bidang akuntansi keuangan, auditing, dan bidang-bidang terkait seperti perpajakan dan sistem informasi. Dengan demikian diharapkan akuntan publik BAP mempunyai kualifikasi sebagai akuntan publik yang handal dalam menghadapi persaingan di pasar global. Oleh karena itu, dapat dihipotesiskan sebagai berikut: Hipotesis 5: Motivasi mengikuti USAP mempengaruhi minat mahasiswa akuntansi untuk mengikuti PPAk. Pendidikan Profesi Akuntansi (PPAk) Keputusan Mendiknas Nomor 179/U/2001 menyebutkan Pendidikan Profesi Akuntansi adalah pendidikan tambahan pada pendidikan tinggi setelah program sarjana Ilmu Ekonomi pada program studi akuntansi. Pendidikan profesi akuntansi bertujuan menghasilkan lulusan yang menguasai keahlian bidang profesi akuntansi dan memberikan kompensasi keprofesian akuntansi. Lulusan Pendidikan Profesi Akuntansi berhak menyandang sebutan gelar profesi akuntan yang selanjutnya disingkat Ak. Pendidikan profesi akuntansi yang menghasilkan akuntan dari perguruan tinggi merupakan produk hasil proses belajar mengajar. Salah satu indikator peningkatan profesionalisme adalah adanya kurikulum yang memadai dan adanya standar profesionalisme melalui ujian profesi. Seorang akuntan harus memperhatikan standar teknik profesi dan etika serta berupaya terus untuk meningkatkan kemampuan. Machfoedz (1998) mengemukakan bahwa profesionalisme ditandai dengan adanya tiga indikator, yaitu Pengetahuan (knowledge), Keterampilan (skill), dan Etika. Hipotesis 6: Biaya pendidikan mempengaruhi minat mahasiswa akuntansi untuk mengikuti PPAk. Hipotesis 6: Biaya pendidikan mempengaruhi minat mahasiswa akuntansi untuk mengikuti PPAk. Hipotesis 7: Lama pendidikan PPAk mempengaruhi minat mahasiswa akuntansi untuk mengikuti PPAk. Hipotesis 7: Lama pendidikan PPAk mempengaruhi minat mahasiswa akuntansi untuk mengikuti PPAk. Gender Pengertian gender menurut Fakih (1996) adalah suatu sifat yang melekat pada kaum laki-laki maupun perempuan yang dikonstruksi secara sosial maupun kultural. Sedang menurut Squire dalam Suhapti (1995) gender adalah perbedaan peran antara perempuan dan laki-laki yang mengakibatkan perbedaan perlakuan antara perempuan dan laki-laki di masyarakat. Palupi dan Setiawan (2003) menunjukkan bahwa ada perbedaan etika antara akuntan pendidik laki-laki dan wanita dalam hal keadilan, relativism, dan utilitarianism. Oleh karena itu, dapat dirumuskan hipotesis sebagai berikut: Hipotesis 8: Tidak ada perbedaan yang signifikan pada minat mahasiswa akuntansi dalam mengikuti PPAk ditinjau dari gender. Hipotesis 8: Tidak ada perbedaan yang signifikan pada minat mahasiswa akuntansi dalam mengikuti PPAk ditinjau dari gender. Hipotesis 9: Tidak ada perbedaan yang signifikan pada minat mahasiswa akuntansi dalam mengikuti PPAk ditinjau dari status akreditasi program studi Ujian Sertifikasi Akuntan Publik (USAP) Ujian Sertifikasi Akuntan Publik (USAP) adalah ujian yang harus diikuti oleh semua sarjana jurusan akuntansi yang ingin memperoleh atau menyandang sebutan akuntan publik. USAP dilaksanakan berdasarkan Keputusan Menteri Keuangan RI No. 43/KMK.017/1997 tertanggal 27 Januari 1997. Ujian Sertifikasi Akuntan Publik (USAP) merupakan strategi pengembangan profesi akuntan di Indonesia menghadapi era perdagangan bebas. 19 ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI MINAT MAHASISWA AKUNTANSI UNTUK MENGIKUTI PENDIDIKAN PROFESI AKUNTANSI DITINJAU DARI GENDER DAN STATUS AKREDITASI PROGRAM STUDI Akuntan yang telah lulus USAP akan memperoleh sebutan “Bersertifikat Akuntan Publik (BAP)”. Sertifikat 19 ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI MINAT MAHASISWA AKUNTANSI UNTUK MENGIKUTI PENDIDIKAN PROFESI AKUNTANSI DITINJAU DARI GENDER DAN STATUS AKREDITASI PROGRAM STUDI Edy Suprianto & Mifkhatun Nikmahi Akuntan yang telah lulus USAP akan memperoleh sebutan “Bersertifikat Akuntan Publik (BAP)”. Sertifikat Akuntan yang telah lulus USAP akan memperoleh sebutan “Bersertifikat Akuntan Publik (BAP)”. Sertifikat Akuntan yang telah lulus USAP akan memperoleh sebutan “Bersertifikat Akuntan Publik (BAP)”. Sertifikat 19 JURNAL AKUNTANSI INDONESIA JURNAL AKUNTANSI INDONESIA berdasarkan kriteria tertentu. Kriteria sampel yaitu: Mahasiswa akuntansi di Perguruan Tinggi Swasta yang memiliki status akreditasi program studi A dan B. Mahasiswa akuntansi semester 7. Teknik pengumpulan data menggunakan kuesioner, yaitu dengan membagikan kuesioner kepada responden langsung untuk meyakinkan bahwa kuesioner sampai pada responden yang diinginkan dan responden merasa dihargai sehingga mengisi kuesioner dengan lengkap dan jujur. Data yang diperoleh berupa jawaban kuesioner yang dapat menggambarkan kinerja responden. berdasarkan kriteria tertentu. Kriteria sampel yaitu: Mahasiswa akuntansi di Perguruan Tinggi Swasta yang memiliki status akreditasi program studi A dan B. Mahasiswa akuntansi semester 7. Statistik Deskiptif Sampel yang diperoleh dengan teknik pengambilan sampel purposive sampling adalah sebanyak 50 responden, yaitu dari UNISSULA dan UDINUS yang mewakili akreditasi A dan akreditasi B. Berikut ini hasil analisis statistik deskriptif, variabel motivasi karir memiliki rata-rata (mean) sebesar 43,16 dan standar deviasi 4,460. Variabel motivasi kualitas memiliki rata-rata (mean) sebesar 41,82 dan standar deviasi 4,552. Variabel motivasi ekonomi memiliki rata-rata (mean) sebesar 43,88 dan standar deviasi 4,955. Variabel motivasi gelar memiliki rata-rata (mean) sebesar 4,34 dan standar deviasi 0,798. Variabel motivasi mengikuti USAP memiliki rata-rata (mean) sebesar 4,04 dan standar deviasi 0,755. Variabel biaya pendidikan memiliki rata-rata (mean) sebesar 3,80 dan standar deviasi 0,857. Variabel lama pendidikan memiliki rata-rata (mean) sebesar 3,20 dan standar deviasi 1,030. Variabel minat mengikuti PPAk memiliki rata-rata (mean) sebesar 19,80 dan standar deviasi 3,097. METODE PENELITIAN Populasi dari penelitian ini adalah mahasiswa jurusan akuntansi pada perguruan tinggi swasta di Semarang. Teknik pengambilan sampel dilakukan melalui teknik purposive sampling, yaitu teknik pengambilan sampel 20 Jurnal Akuntansi Indonesia Vol. 2 No. 1 Januari 2013 Jurnal Akuntansi Indonesia 20 JURNAL AKUNTANSI INDONESIA pada jaman sekarang faktor ekonomi menjadi sangat penting dalam kehidupan sehari-hari. Secara teoritis penghargaan finansial merupakan salah satu bentuk sistem pengendalian manajemen. Untuk memastikan bahwa elemen karyawan dapat mengarahkan tindakannya terhadap pencapaian tujuan perusahaan, maka manajemen memberikan balas jasa atau reward dalam berbagai bentuk, termasuk di dalamnya financial reward atau penghargaan finansial. Motivasi gelar tidak mempunyai pengaruh yang signifikan terhadap minat mahasiswa akuntansi untuk mengikuti PPAk, hal ini dibuktikan dengan signifikansi 0,553 > 0,05. Kondisi ini terjadi karena pendidikan Akt tidak menunjukkan jenjang pendidikan yang lebih tinggi. Gelar Akt lebih menunjukkan kualifikasi dan spesifikasi seseorang yang berprofesi di bidang akuntansi dibandingkan dengan sesorang lulusan S1 akuntansi yang bergelar SE. Motivasi mengikuti USAP mempunyai pengaruh yang signifikan terhadap minat mahasiswa akuntansi untuk mengikuti PPAk, hal ini dibuktikan dengan signifikansi 0,001 < 0,05. Kondisi ini terjadi karena USAP merupakan suatu ujian profesi yang berfungsi sebagai sebuah sistem saringan yang baku bagi mereka yang akan berpraktik sebagai Akuntan Publik. Akuntan yang telah lulus untuk semua mata ujian berhak memperoleh sebutan ”Bersertifikasi Akuntan Publik (BAP). Setifikat akuntan publik merupakan salah satu persyaratan utama untuk mendapatkan izin praktek. USAP hanya diikuti oleh mereka yang memiliki gelar akuntan yang hanya diperoleh setelah menempuh PPAk. Biaya pendidikan tidak mempunyai pengaruh yang signifikan terhadap minat mahasiswa akuntansi untuk mengikuti PPAk, hal ini dibuktikan dengan signifikansi 0,158 > 0,05. Kondisi ini terjadi karena bagi mahasiswa untuk memperoleh gelar akuntan, dengan biaya pendidikan berapapun tidak menjadi masalah, sehingga mereka tetap mengikuti PPAk. Hal tersebut dikarenakan mahasiswa ingin meningkatkan kualitas atau kemampuan di bidang akuntansi. Lama pendidikan tidak mempunyai pengaruh yang signifikan terhadap minat mahasiswa akuntansi untuk mengikuti PPAk, hal ini dibuktikan dengan signifikansi 0,244 > 0,05. Kondisi ini terjadi karena pendidikan profesi akuntansi hanya ditempuh dalam kurun waktu 1 tahun, sehingga untuk menempuh pendidikan tersebut tidak terasa lama. Apabila mahasiswa yang sudah bekerja ingin mengikuti PPAk, hal tersebut masih bisa dilakukan, karena ada pendidikan profesi akuntansi yang membuka kelas malam. Minat mahasiswa akuntansi untuk mengikuti PPAk ditinjau dari gender tidak menunjukkan perbedaan yang signifikan. Kondisi ini terjadi karena mahasiswa laki-laki dan perempuan mempunyai minat yang sama mengikuti PPAk. Di era globalisasi gender bukan menjadi masalah, sebab antara laki-laki dan perempuan memiliki kesamaan kesempatan untuk berkembang dan maju. Minat mahasiswa akuntansi untuk mengikuti PPAk ditinjau dari status akreditasi program studi tidak menunjukkan perbedaan yang signifikan. Kondisi ini terjadi karena setiap perguruan tinggi atau program studi memiliki akreditasi yang berbeda. Pengujian Hipotesis Motivasi karir tidak mempunyai pengaruh yang signifikan terhadap minat mahasiswa akuntansi untuk mengikuti PPAk, hal ini dibuktikan dengan signifikansi 0,132 > 0,05. Kondisi ini terjadi karena dari hasil penelitian, responden atau mahasiswa yang diteliti menganggap bahwa motivasi karir bukan faktor yang mempengaruhi minat mahasiswa mengikuti PPAk. Suatu perusahaan dalam mencari calon karyawan tidak mengharuskan seseorang memiliki gelar akuntan ataupun beregister. Hanya perusahaan tertentu saja, seperti BUMN yang menuntut calon pegawainya memiliki gelar akuntan, sehingga motivasi karir tidak berpengaruh terhadap minat mahasiswa mengikuti PPAk. Motivasi kualitas mempunyai pengaruh yang signifikan terhadap minat mahasiswa akuntansi untuk mengikuti PPAk, hal ini dibuktikan dengan signiifkasi 0,017 < 0,05. Kondisi ini terjadi karena mahasiswa berkeinginan untuk meningkatkan kualitas diri, sehingga bisa menghadapai persaingan dunia kerja yang semakin kompetitif. Secara teori motivasi kualitas sebagai dorongan yang timbul dalam diri seseorang untuk memiliki dan meningkatkan kualitas diri dan kemampuannya dalam bidang yang ditekuninya sehingga dapat melaksanakan tugas dengan baik dan benar. Motivasi ekonomi mempunyai pengaruh yang signifikan terhadap minat mahasiswa akuntansi untuk mengikuti PPAk, hal ini dibuktikan dengan signifikansi 0,029 < 0,05. Kondisi ini terjadi karena mahasiswa menginginkan kerja keras mengikuti PPAk bisa menambah nilai tambah yang besifat ekonomis, karena 21 Jurnal Akuntansi Indonesia JURNAL AKUNTANSI INDONESIA Status akreditasi A dan B tidak jauh berbeda, karena untuk mengikuti PPAk mahasiswa tidak memandang status akreditasi program studi, baik itu A maupun B. Sedangkan yang berbeda adalah akreditasi A dan C. Jurnal Akuntansi Indonesia 22 22 SIMPULAN, KETERBATASAN DAN SARAN Berdasarkan hasil penelitian dan pembahasan di atas, maka dapat ditarik kesimpulan sebagai berikut : pertama, Tidak ada pengaruh antara motivasi karir terhadap minat mahasiswa akuntansi untuk mengikuti pendidikan profesi akuntansi. Kedua, Ada pengaruh antara motivasi kualitas terhadap minat mahasiswa akuntansi untuk mengikuti pendidikan profesi akuntansi. Ketiga, Ada pengaruh antara motivasi ekonomi terhadap minat mahasiswa akuntansi untuk mengikuti pendidikan profesi akuntansi. Keempat, Tidak ada pengaruh antara motivasi gelar terhadap minat mahasiswa akuntansi untuk mengikuti pendidikan profesi akuntansi. Kelima, Ada pengaruh antara motivasi mengikuti USAP terhadap minat mahasiswa akuntansi untuk mengikuti pendidikan profesi akuntansi. Keenam, Tidak ada pengaruh antara biaya pendidikan terhadap minat mahasiswa akuntansi untuk mengikuti pendidikan profesi akuntansi. Ketujuh, Tidak ada pengaruh antara lama pendidikan terhadap minat mahasiswa akuntansi untuk mengikuti pendidikan profesi akuntansi. Kedelapan, Tidak ada perbedaan yang signifikan minat mahasiswa akuntansi untuk mengikuti PPAk ditinjau dari gender. Kesembilan, Tidak ada perbedaan yang signifikan minat mahasiswa akuntansi untuk mengikuti PPAk ditinjau dari status akreditasi program studi. Keterbatasan dalam penelitian ini adalah: Lingkup penelitian ini hanya 2 Perguruan Tinggi Swasta (Unissula dan Udinus), sehingga penelitian selanjutnya sebaiknya menggunakan lebih dari 2 Perguruan Tinggi, sehingga bisa membandingkan antara status akreditasi A dan C. Penelitian ini dilakukan di lingkup kota Semarang dengan sampel sebanyak 50 responden, untuk penelitian selanjutnya bisa menambah jumlah responden dengan memperluas daerah penelitian misalnya Yogyakarta, Bandung atau Jakarta. Variabel motivasi gelar, motivasi mengikuti USAP, biaya pendidikan dan lama pendidikan hanya terdiri dari 1 indikator saja, sebaiknya untuk penelitian selanjutnya ditambah beberapa indikator lagi. DAFTAR PUSTAKA D. 1995. Nuansa Psikologi Pembangunan. Pustaka Pelajar, Yogyakarta. Ancok, D. 1995. Nuansa Psikologi Pembangunan. Pustaka Pelajar, Yogyakarta. Benny dan Yuskar. 2006. “Pengaruh Motivasi terhadap Minat Mahasiswa Akuntansi Untuk Mengikuti Pendidikan n Yuskar. 2006. “Pengaruh Motivasi terhadap Minat Mahasiswa Akuntansi Untuk Mengikut Benny dan Yuskar. 2006. Pengaruh Motivasi terhadap Minat Mahasiswa Akuntansi Untuk Mengikuti Pendidikan Profesi Akuntansi (PPAk)”. Simposium Nasional Akuntansi IX. k h d d b h k l k Profesi Akuntansi (PPAk)”. Simposium Nasional Akuntansi IX. Fakih M 1999 Gender dan Perubahan Organisasi Pustaka Pelajar Yogyakarta Lisnasari dan Fitriany, 2008. “Faktor-Faktor yang Mempengaruhi Minat Mahasiswa Akuntansi Untuk Mengikuti Pendidikan Profesi Akuntansi (Studi empiris di Universitas Indonesia)”. The 2nd Accounting Conference, 1st Doctoral Colloquium, and Accounting Workshop Depok. Lisnasari dan Fitriany, 2008. “Faktor-Faktor yang Mempengaruhi Minat Mahasiswa Akuntansi Untuk Mengikuti Pendidikan Profesi Akuntansi (Studi empiris di Universitas Indonesia)”. The 2nd Accounting Conference, 1st Doctoral Colloquium, and Accounting Workshop Depok. Machfoedz, M. 1998. “Survey Minat Mahasiswa Untuk Mengikuti Ujian Sertifikasi Akuntan Publik (USAP)”. Jurnal Ekonomi dan Bisnis Indonesia, Volume 13 No.4. IAI, Penegakan Etika Profesi Upaya Menciptakan Akuntan yang Profesional. Media Akuntansi, 28 September 2002. IAI, Penegakan Etika Profesi Upaya Menciptakan Akuntan yang Profesional. Media Akuntansi, 28 September 2002. Palupi dan Setiawan. 2003. “Pengaruh Perbedaan Gender terhadap Etika Akuntan Pendidik”. Working paper jurusan akuntansi, Fakultas Ekonomi, Universitas Sebelas Maret. Palupi dan Setiawan. 2003. “Pengaruh Perbedaan Gender terhadap Etika Akuntan Pendidik”. Working paper jurusan akuntansi, Fakultas Ekonomi, Universitas Sebelas Maret. Suranta dan Syafiqurrahman, 2006. “Pengaruh Motivasi terhadap Minat Mahasiswa Untuk Mengikuti Pendidikan 23 23 JURNAL AKUNTANSI INDONESIA Profesi Akuntansi di Karesidenan Surakarta”. Jurnal Empirika, Volume 19 No.1, Juni 2006. Sudaryono, dkk. 2005. “Minat Mahasiswa Akuntansi dalam Mengikuti Pendidikan Profesi Akuntansi (PPA) Ditinjau dari Gender dan Status Akreditasi Program Studi”. Jurnal Akuntansi dan Investasi. Vol. 6 No.2, Juli 2005. Sudaryono, dkk. 2005. “Minat Mahasiswa Akuntansi dalam Mengikuti Pendidikan Profesi Akuntansi (PPA) Ditinjau dari Gender dan Status Akreditasi Program Studi”. Jurnal Akuntansi dan Investasi. Vol. 6 No.2, Juli 2005. Suhapti, R. 1995. Gender dan Permasalahannya. Buletin Psikologi, tahun III, No.1. Suhapti, R. 1995. Gender dan Permasalahannya. Buletin Psikologi, tahun III, No.1. Widyastuti, dkk. 2004. “Pengaruh Motivasi terhadap Minat Mahasiswa Akuntansi Untuk Mengikuti Pendidikan Profesi Akuntansi”. Simposium Nasional Akuntansi VII. Profesi Akuntansi”. Simposium Nasional Akuntansi VII. 24 24 ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI MINAT MAHASISWA AKUNTANSI UNTUK MENGIKUTI PENDIDIKAN PROFESI AKUNTANSI DITINJAU DARI GENDER DAN STATUS AKREDITASI PROGRAM STUDI Edy Suprianto & Mifkhatun Nikmahi JURNAL AKUNTANSI INDONESIA JURNAL AKUNTANSI INDONESIA Lampiran Tabel 1 Hasil Regresi Berganda Coefficientsa .896 4.415 .203 .840 -.148 .096 -.213 -1.535 .132 .310 .110 .333 2.820 .017 .169 .075 .270 2.266 .029 .307 .512 .079 .599 .553 2.220 .602 .441 3.685 .001 .654 .455 .181 1.437 .158 .412 .349 .137 1.181 .244 (Constant) Motivasi karir motivasi kualitas motivasi ekonomi motivasi gelar motivasi mengikuti USAP biaya pendidikan lama pendidikan Model 1 B Std. Error Unstandardized Coefficients Beta Standardized Coefficients t Sig. Dependent Variable: minat mahasiswa mengikuti PPak a. Tabel 1 Hasil Regresi Berganda Tabel 1 Hasil Regresi Berganda 25 Edy Suprianto & Mifkhatun Nikmahi
https://openalex.org/W2960681423	https://www.econstor.eu/bitstream/10419/240248/1/1669426637.pdf	English	null	Partnering for sustainability in agri-food supply chains: the case of Barilla Sustainable Farming in the Po Valley	Agricultural and food economics	2,019	cc-by	5,992	Partnering for sustainability in agri-food supply chains: The case of Barilla Sustainable Farming in the Po Valley Agricultural and Food Economics Provided in Cooperation with: Italian Society of Agricultural Economics (SIDEA) Suggested Citation: Pancino, Barbara et al. (2019) : Partnering for sustainability in agri-food supply chains: The case of Barilla Sustainable Farming in the Po Valley, Agricultural and Food Economics, ISSN 2193-7532, Springer, Heidelberg, Vol. 7, Iss. 1, pp. 1-10, https://doi.org/10.1186/s40100-019-0133-9 Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Documents in EconStor may be saved and copied for your personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. https://creativecommons.org/licenses/by/4.0/ https://creativecommons.or Pancino, Barbara et al. © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. RESEARCH Open Access Abstract 1Department of Economics & Management (DEIM), Università degli Studi della Tuscia, Via del Paradiso 47, 01100 Viterbo, Italy Full list of author information is available at the end of the article The objective of the paper is to understand the process of designing a multi- stakeholder partnership in the adoption of sustainable innovations in value chains. More specifically, the focus is on the design of feasible types of horizontal agreements and contractual formulas to be implemented in the agri-food supply chain in order to introduce sustainable agricultural practices. To this purpose, the Barilla Sustainable Farming initiative, which is currently in the first phase of designing an MSP, is used as a case study. Keywords: Supply chain protocols, Sustainability, Crop rotation, Horizontal agreements, Contract design (2019) 7:13 Pancino et al. Agricultural and Food Economics (2019) 7:13 https://doi.org/10.1186/s40100-019-0133-9 Agricultural and Food Economics Agricultural and Food Economics Pancino et al. Agricultural and Food Economics https://doi.org/10.1186/s40100-019-0133-9 Partnering for sustainability in agri-food supply chains: the case of Barilla Sustainable Farming in the Po Valley Barbara Pancino1* , Emanuele Blasi2, Anne Rappoldt3, Stefano Pascucci4, Luca Ruini5 and C Introduction Another relevant element in shaping a MSP is the organizational and human resources and capabilities (Dentoni et al. 2012). In addition, Hartwich et al. (2008) argue that the objective or common interest of the different stakeholders is a determinant of how the partnership is formed (Hartwich et al. 2008). In order to have successful partnerships, there are some basic and simple preconditions that should be taken into account. First, a successful partner- ship requires overlapping agendas and motivations between all the involved stake- holders (Heldeweg et al. 2015). Moreover, trust is an important element, which is based on past experiences or previous relations between the stakeholders (Glasber- gen et al. 2007). In addition, the allocation of responsibility and authority is needed (De Schepper et al. 2014) by a contractual agreement, for example (Glasbergen et al. 2007). Partnerships also imply a new form of governance (Backstrand 2006). The literature illustrates a wide spectrum of governance structures for MSPs. It can vary by several different characteristics. For instance, Waring et al. (2013) differentiate between tight and loose partnerships, where tight arrangements refer to horizontal resource sharing and collaboration, and loose arrangements include vertical contracting between a pub- lic purchaser and a private provider. Tight/loose differentiation is made based on char- acteristics of financing and risk sharing, collaboration in strategic planning and design, and level of resource sharing. Waring et al. (2013) also explore the relationship between “upstream” tight or loose arrangements and “downstream” service and workforce man- agement. Furthermore, Keast et al. (2007) define three forms of horizontal integration modes for policy and service in a level of integration continuum: cooperation, coordin- ation, and collaboration. Cooperation is conceptualized as a starting point of inter- organizational relationships and is characterized by small efforts and low levels of rela- tionship intensity, while organizations remain independent and autonomous. It involves low risk because no changes are required in existing practices. Organizations take into account each other’s goals, and relations are short term and informal. Coordination is found in the middle of the continuum—between cooperation and collaboration—and implicates that there is a shared goal between the partners and they work together ac- cording to more structured mechanisms than in case of cooperation. Although there is a shared goal, there is no loss of individual autonomy of the different partners. Introduction Complex and urgent sustainability issues are caused by interaction of a number of vari- ables that impact efficiency and sustainability of local agriculture. First, there is a de- crease in the amount of arable land available as a result of urbanization, salinization, desertification, and environmental degradation (Ronald 2011). Other variables are cli- mate change (Kesavan 2015), eating habits, (BCFN 2011), increases in food prices and fuel costs, pesticide pollution, and pest adaptation and resistance (Lichtfouse et al. 2009). Moreover, the agricultural activities of the last 50 years have been focussed on maximizing productivity through the adoption of new technologies and modernization of production techniques, such as high-yielding plant varieties, practice of monocul- ture, and mechanization and use of agrochemicals (BCFN 2011; Bernstein 2014; Stew- art et al. 2014). On the one hand, these activities resulted in a period of high productivity repeatedly associated with low food prices and, on the other hand, also in intensive and often irreversible exploitation of the natural resources as an effect of soil erosion and decreased fertility, water contamination, deforestation, and loss of bio- diversity (BCFN 2011; Kesavan 2015; Lichtfouse et al. 2009). Within this context, as Aiking and De Boer (2004) argue that only a few corporations are in charge of the food production system; thus, multinationals should hand over some form of control to stimulate democratic multi-level governance to make food production more sustainable. For instance, they can be promoters of the so-called multi-stakeholder partnerships. Page 2 of 10 Page 2 of 10 Pancino et al. Agricultural and Food Economics (2019) 7:13 Pancino et al. Agricultural and Food Economics “Multi-stakeholder partnership’ (MSP) is an overarching concept which highlights the idea that different groups can share a common problem or aspiration, while nonetheless having different interests or ‘stakes’” (Brouwer et al. 2015). MSPs range from short consultation processes to multi-year arrangements that may evolve through many phases. Some MSPs are extremely systematized and fi- nanced by formal actions, while others are much more specific and simple. Differ- ent groups will take the lead in initiating MSPs, but the common key element seems to be the motivations. Partnership motivations are the existence of assump- tions of risks (Johnston and Gudergan 2007; Roehrich et al. 2014) or strategic is- sues, such as assessment of opportunities and threats and use of own strengths to decrease them (Dentoni et al. 2012). Introduction The partnerships focus on the fulfilment of tasks or activities that are managed to drive a specific outcome (Keast et al. 2007). In addition to information sharing, it requires joint planning and possible joint funding. Increase of effort and commitment can lead to Pancino et al. Agricultural and Food Economics (2019) 7:13 Page 3 of 10 Page 3 of 10 Pancino et al. Agricultural and Food Economics growing shared benefits and shared risks. Collaboration is the ideal type found at the other side of the spectrum and goes beyond the instrumental process of joint task fulfil- ment. Collaboration deals with high intensive relationships, connections, and resources; thus, even boundaries between agencies can become blurred. Collaboration is charac- terized by shared goals and goal setting, high level of commitment and contribution, and high level of trust. In addition to the joint instrumental approach that is associated with coordination, also new forms of engagement, structures, and processes are devel- oped over time. Moreover, collaboration has the potential to achieve greater efficiencies of scale and outcomes than cooperation and coordination, but it is difficult to develop and to sustain. This integration form also involves the highest degree of risk. Therefore, coordination is often considered safer, requires less time to establish, and lies within the comfort zone. The three integration modes differ in the level of connection and in- tensity. Keast et al. (2007) argue that the ‘3C’’ are complementary and not competitive; they are the key to select the right mix. Moreover, multinationals are in business to make profits, so they will barely partici- pate in sustainability practices if there is a ‘win-win’ situation—meaning that there is a business advantage in addition to the social and environmental advantages (Rondinelli and Berry 2000). An example of this type of ‘win-win’ process is the Barilla Sustainable Farming (BSF) initiative, which is carried out by the Barilla Group (Blasi et al. 2015). Indeed, in 2013, Barilla introduced a sustainable agriculture practice by establishing horizontal agreements between three of its main input suppliers: Co.Pro.B. for sugar beet, Cereal Docks for oilseeds, and Casalasco Tomato Consortium for tomato (BCFN 2015). The agreement entails that the supply chains become integrated by means of a crop rotation system with the wheat crops, sugar beet, rapeseed, and sunflower (Barilla 2014). Introduction Currently, these horizontal agreements are bilateral, which means that the Ba- rilla Group has a specific agreement with each one of the supplier. The idea is to step forward passing from bilateral agreements to a multilateral one. The objective of the paper is, indeed, to understand the process of designing a multi- stakeholder partnership (MSP) in the adoption of sustainable innovations in value chains, like the one of defining feasible types of horizontal agreements and contractual formulas to be implemented in the agri-food supply chain in order to introduce sus- tainable agricultural practices. The BSF initiative, which represents a perfect case study for this purpose, is currently in the first phase of designing an MSP; therefore, the initi- ating phase will be the main focus of the analysis. The results will then permit to iden- tify the main features necessary to make the shift from an agreement to a proper contract, which has already been pointed out as the main critical point for a wider im- plementation of these type of agreements (Pancino et al. 2015). Research strategy and case study This research aims to understand the process of designing a multi-stakeholder partnership in the adoption and diffusion of sustainable innovations in food value chains, promoted and facilitated by private actors. The theoretical framework developed in the literature study in the previous section forms the basis for the empirical analysis. The BSF initiative is currently in the first phase of designing an MSP; therefore, the initiating phase will be Pancino et al. Agricultural and Food Economics (2019) 7:13 Pancino et al. Agricultural and Food Economics Page 4 of 10 the main focus of the empirical analysis. The governance structures are established in the third phase of the design process, so this research will only reflect on the rationales that are found during the initiating phase. A schematic representation of Barilla with its suppliers and the other stakeholders in- volved in the BSF initiative is schematized in Fig. 1. Horizontal agreements, or supplier-supplier relations, extend the concept of a supply chain towards a supply net- work (Johnsen et al., 2008; Lamming et al., 2000, cited in Wilhelm 2011), where supply chains are seen as “connected strings of organizations involved in the production and supply of a particular product or product family” (Johnsen et al., 2008; cited in Wilhelm 2011, p. 664). Supplier-supplier relationships within a supply network can be competi- tive, or cooperative, or there is the possibility of lack of ties. In these relations, cooper- ation and competition can exist next to each other, but one is likely to be stronger (Wilhelm 2011). Co.Pro.B., Cereal Docks, and Casalasco Tomato Consortium are sup- pliers with cooperative ties since they provide Barilla with different crops. The aim of the horizontal agreement is to facilitate farmers in engaging a multi-year crop rotation system which will lead to new market opportunities deriving from the different value chains involved. In the analysed case, tomato, durum wheat, and oilseed crops (sun- flower, maize, or sorghum) are consciously rotated to improve soil fertility as well as to reduce the input amount per land unit. In this path, the nitrogen fixer crops play a crit- ical role, where these are not feasible with the structural and pedo-climatic features of the farms within the macro-region investigated. Data collection This research consisted of three phases of data collection: documentation, interviews, and participant observations. Documentation and interviews were part of the diagnostic stage, and the participant observation during a design exercise with the stakeholders was part of the therapeutic stage of the research, which involves collaborative change experiments (Baskerville 1997). First, scientific articles and company documents were sources for the documentation. For the literature study, scientific articles and books were used. In addition, company docu- ments were used for the case description. The theoretical framework that is developed in the literature study formed the basis for the empirical analysis and the interview questions. Fig. 1 Designing a MPS: the supply network of Barilla. Source: our own elaboration Pancino et al. Agricultural and Food Economics (2019) 7:13 Page 5 of 10 Page 5 of 10 Pancino et al. Agricultural and Food Economics (2019) 7:13 Pancino et al. Agricultural and Food Economics Then, in February 2016, four interviews were conducted with representatives from the organizations Barilla, Casalasco, Co.Pro.B., and Cereal Docks. The choice of inter- viewing sub-supplier like elevators, cooperatives, and PO instead of farmers is due to the greater bargaining power they have in favouring the contract signature by their as- sociated farmers. The interviews were semi-structured and consisted of open questions. A standardized interview protocol was designed, but probes and follow-up question were used. Each interviewee was granted permission to make an audio recording of the interview, and also, the transcripts were checked and validated by the interviewees. The interviews took approximately 45 min and were recorded, transcribed, and analysed. The interviewees were selected because they represent the organizations that are in- volved in the BSF initiative. The empirical analysis of this research focused on the initiating phase of designing a MSP, because this is most relevant for the BSF initiative. The interviews provided a first understanding of the current situation and therefore focused on the first three steps of the initiating phase: clarify reasons, initial situation analysis, and mobilize champions. The first part consisted the introduction in which the researcher explains the context of the research and the goal of the interview. In addition, the structure and the ex- pected duration of the interview were explained and the interviewee was asked permis- sion to make an audio recording of the interview. Results and discussion The interview round focused on the analysis of the first three steps of the initiating phase as presented in the theoretical framework: clarify reasons, initial situation ana- lysis, and mobilization of champions. The attitude of the stakeholder towards a MSP in general was also included by asking for preference for the option to design a MSP or to develop contracts based on the existing horizontal agreements. The shared objective of the BSF initiative mentioned during the interviews is well aligned among the different stakeholders. The objective can be defined as a long-term program of 4 or 5 years for stabilization of prices and stabilization of the market. Stabilization is seen as a win-win situation for both farmers and manufacturers. First, the farmers will face less volatile prices in the market and engaging in the rotation system en- sures outlet to the crops that they produce. For the industry, it involves an increase in quality and sustainability—such as Good Agricultural Practices (GAP)—standards. There are more benefits of the rotation system pointed out by the stakeholders. First, production becomes more efficient. Better quality and fertility of the soil require less input leading to lower production costs and improved quality of the products, and therefore an increase in competitiveness. Moreover, less volatility in the market reduces the economic risks for both the farmers and the manufacturers. This win-win situation only provides security for long-term production, because it provides on the one hand a stable income and on the other hand a stable supply. Stabilization means a change of the total free market system, but aims to find a right compromise in between a free market and a protected market. Moreover, conflicting interest can cause problems be- cause the stakeholders that are involved in this collaboration are indirect competitors. Even negotiation of prices in a contract with multiple stakeholders is a conflict of inter- est per definition. Quality, quantity, timing, and price must all be negotiated. The existing relationships between the different stakeholders can be described as fol- lows. First, Barilla is in the centre of the collaboration. Barilla has strong ties with Casa- lasco and Co.Pro.B. since they are already existing suppliers of Barilla, and is only starting a relationship with Cereal Docks in this rotation initiative. However, between Casalasco, Co.Pro.B., and Cereal Docks, there are no current or existing linkages. Data collection The second part of the interview aimed to undertake an analysis of the current situation of the BSF initiative to understand the context of the initiative in terms of processes, in- volvement, motivations, interests, and expectations of the different stakeholders. Questions for analysis of the current situation of an inter-organizational collaboration targeted for example roles of the different stakeholders, contributions, relationships, and reasons for collaboration (Butterfield et al. 2004). The third part of the interview aimed to understand preferences for structuring or or- ganizing the collaboration. Therefore, the questions in the second part targeted prefer- ences about how to collaborate and in terms of management, structure, and coordination mechanisms. Finally, the last sections contained a final statement which is offered to the inter- viewee in which two options were presented: (1) to establish a multi-stakeholder part- nership or (2) to directly design a contract for the crop rotation system based on the existing horizontal agreements. Here, the attitude of the stakeholders towards collabor- ation in an MSP was analysed. After the interviews, a multi-stakeholder meeting was organized in Parma (Italy) on the 8th of March 2016. During this meeting, the first findings of the interviews were presented followed by an open discussion. Attendants of the meetings were representa- tives from Barilla, Casalasco, Co.Pro.B., Tuscia University of Viterbo, and Wageningen University. The multi-stakeholder meeting contained an experimental design exercise with the stakeholders involved in the BSF initiative to take action in the first steps for designing the MSP and negotiate the first pilot contracts. The design exercise was built upon the information gathered during the literature study and the interviews and consists of an experimental design exercise during a multi-stakeholder meeting. During the design exercise, the findings of the literature study and the interviews were presented, followed by an open discussion to confirm or complement the findings. Moreover, the design exercise focused on the next steps of Pancino et al. Agricultural and Food Economics (2019) 7:13 Page 6 of 10 Pancino et al. Agricultural and Food Economics the initiating phase: establish an interim steering body, build stakeholder support, es- tablish scope and mandate, and outline the process. Results and discussion Barilla can thus be seen as the institutional entrepreneur, thus an agent who mobilize own resources to create institutions (Pacheco et al. 2010), that facilitates and takes the lead in changing the institutional environment. The involvement of the public party that is foreseen by the four partners is first for pro- viding funding and support. Furthermore, the local administration will guarantee that all parties respect the contract, as this will be legally binding. Inter-organizational collabor- ation in a MSP involves maximization of resources and expertise. All four companies have knowledge and experience in crop rotation, and existing relationships with universities and agronomists make a good understanding of agronomic practices of rotation. Indeed, the involvement of research institutes and local public authorities in the partnership con- tributes to the creation of a learning network, and the legitimacy of the initiative can help to facilitate the adoption of changing practices through support and embedding within existing regulatory frameworks. To this regard, it is important to note that in all the Pancino et al. Agricultural and Food Economics (2019) 7:13 Page 7 of 10 Page 7 of 10 Pancino et al. Agricultural and Food Economics regions where the four companies provide their raw materials, rural development pro- grams defines agro-climate-environmental measures (measure 10) where crop rotation schemes are included as a mandatory requirement of integrated pest management schemes. In this case, the farmers can voluntary apply to these pluriannual schemes and receive per hectare subsides by the CAP second pillar budget. The win-win process is then guaranteed. First, the farmers will face less volatile prices in the market and engaging in the rotation system ensures outlet to the crops that they produce, as well as comply with public subsided schemes. For the industry, it involves an increase in quality and sustainability—such as Good Agricultural Practices (GAP)—stan- dards. There is an increased demand from large clients such as processors, wholesalers, and retailers for GAP manners and sustainability practices in agricultural production. Alignment of the objectives between the stakeholders is a strength of this collaboration. The tool to reach the objective is to design contracts for the farmers. At the moment, the four partners share horizontal agreements, thus a ‘mutual interest in supporting spe- cific activities’. However, the existing horizontal agreement is not binding and entails that the four stakeholders Barilla, Casalasco, Co.Pro.B., and Cereal Docks have their own pro- gram in sustainable production. Results and discussion Agricultural and Food Economics (2019) 7:13 Page 8 of 10 Page 8 of 10 Pancino et al. Agricultural and Food Economics In this path, considering the greening crop diversification commitments and CAP reform (European Commission 2018), where crop rotation is proposed to be linked to the direct payments, MSP could be useful to increase farmers capabilities to accomplish the new CAP regulatory framework and connect direct payments distributions. The member states will probably account in the climate and environmental eco-schemes (Art. 18, COM (2018)392) and more ambitious environmental practices, as well as crop rotation that include nitrogen fixer crops or green manure crops in arable land management. At the same time, further contracts will be used to improve data collection about suitable crop rotation implementa- tion, supporting public monitoring activities and CAP impact evaluations. Acknowledgements Thi h b This paper has been selected as a best paper of the 53rd SIDEA Conference in San Michele all'Adige and Bolzano (22- 24 September 2016). It has been accepted for publication in this journal following the usual revision process. Conclusions The multi-stakeholder partnership seems to be the answer for implementing sustain- able innovations in value chains. From our research, it emerges that it is not possible to design a single standard contract that also includes variation for different locations or division of output between the stakeholders. Moreover, besides engagement of the farmers, the stakeholders must also be committed and other requirements such as in- formation sharing, communication, and evaluation are important requirements to es- tablish the rotation system which is the objective of the multi-stakeholder partnership. Thus, to implement the crop rotation system proposed in the case study, a two-level ap- proach is suggested. The first level is the contract, which aims to engage the farmers and exists of specifics for the rotation practices such as price, quantity, quality, amount of land, number of years, and locations. A set of contracts is required for the rotation system because it is not possible for one contract to include all elements. The set of contracts could, for instance, consist of contracts between the cooperatives and the farmers. The second level, instead, refers to the partnership and contains specifics for collab- oration between the stakeholders in the partnership, such as the conversion of rotation practices, coordination of procurement, and coordination of stakeholders at a horizon- tal level. This level is required to integrate the supply chains and targets the engage- ment of the partners and collaboration between them, which is required to develop a set of contracts that can be offered to the farmers. The aim of this level is to develop a set of contracts, the engagement of partners, and the management of different con- tracts for different locations. Authors’ contributions BP contributed to write introduction, results and discussion, conclusions. EB contributed to write method:research strategy and case study, results and discussion, conclusions. AR contributed to write introduction, method: data collection. SP contributed to write method: research strategy and case study, conclusions. LR contributed to write method: research strategy and case study. CR contributed to write method: data collection. All authors read and approved the final manuscript. Funding g This work is supported by the H2020 project Diverfarming—Grant Agreement 728003. Availability of data and materials l bl Not applicable Results and discussion To integrate and align these different programs into a crop rotation system is going to be the challenge. To do so, the horizontal agreement is not sufficient and it is needed to establish a contract, which is explained as ‘something that obliges you to respect the conditions’. A contract is more specific and includes that a certain amount of a crop will be purchased by the organization and, on the other side, that the farmer commits himself to produce a certain amount. Thus, the key is to base the Sustainable Farming Initiative on a two-level approach: the protocol level, which defines the agreement among the industrial partnership, and the contract level that defines the terms to be respected between suppliers and purchasers. In order to define a general protocol, which defines the terms of the agreement, we firstly examined the different cultural practices, production regulations, and monitoring and control systems already implemented by the four partners. The analysis has permit- ted the identification of the actual grade of compatibility between the single systems and the consequent draft of the general aspects to be included in the protocol. These are the commitments to the conversion of rotation practices, a common disciplinary of production, coordination of procurement, information sharing and communication, and coordination of the stakeholders involved in the different locations at a horizontal level. The protocol has been then sharped through a series of meetings, interviews, and exchange of information and with the industrial partners involved. Based on the general aspects specified in the protocol, a series of supply con- tracts to be submitted to the evaluation of farmers participating in the project has been shaped. The elements of the contracts, which aims at engaging farmers in implanting crop rotations, are price, quantity, amount of land, number of years, options, and locations. However, it is not possible to design a single standard con- tract to offer to the farmers to determine how the output is shared for multiple lo- cations. The specific contract terms must be therefore defined, within the general protocol, but in accordance with the specific rotations and locations. The submis- sion of a set of potential contracts to a sample of farmers potentially interested in experiencing the contract and the introduction of the rotation is the objective of the third phase of the project. Pancino et al. Agricultural and Food Economics (2019) 7:13 Pancino et al. Competing interests Competing interests The authors declare that they have no competing interests. g The authors declare that they have no competing interests. Page 9 of 10 Page 9 of 10 Pancino et al. Agricultural and Food Economics (2019) 7:13 References Int Food Agribusiness Manage Rev 15(B):1–12 g g European Commission, (2018) COM/2018/392 final - 2018/0216 (COD) Proposal for a regulation of the european parliament and of the council establishing rules on support for strategic plans to be drawn up by Member States under the Common agricultural policy (CAP Strategic Plans) and financed by the European Agricultural Guarantee Fund (EAGF) and by the European Agricultural Fund for Rural Development (EAFRD) and repealing Regulation (EU) No 1305/2013 of the European Parliament and of the Council and Regulation (EU) No 1307/2013 of the European Parliament and of the Council European Commission, (2018) COM/2018/392 final - 2018/0216 (COD) Proposal for a regulation of the european parliament and of the council establishing rules on support for strategic plans to be drawn up by Member States under the Common agricultural policy (CAP Strategic Plans) and financed by the European Agricultural Guarantee Fund (EAGF) and by the European Agricultural Fund for Rural Development (EAFRD) and repealing Regulation (EU) No 1305/2013 of the European Parliament and of the Council and Regulation (EU) No 1307/2013 of the European Parliament and of the Council Glasbergen P, Biermann F, Mol AP (eds) (2007) Partnerships, governance and sustainable development: reflections on theory and practice. Cheltenham, UK : Edward Elgar - ISBN 9781847204059 - 315 Hartwich F, Tola J, Engler A, González C, Ghezan G, Vázquez-Alvarado JM, Silva JA, Espinoza JJ, Gottret MV (2008) Building public-private partnerships for agricultural innovation. Food security in practice technical guide series. International food policy research institute, Washington, DC p y , g , Heldeweg MA, Sanders M, Harmsen M (2015) Public-private or private-private energy partnerships? Toward good energy governance in regional and local green gas projects. Energy, sustainability and society 5(1):1–12 http://www.barillacfn. p y , g , Heldeweg MA, Sanders M, Harmsen M (2015) Public-private or private-private energy partnerships? Toward good energy governance in regional and local green gas projects. Energy, sustainability and society 5(1):1–12 http://www.barillacfn. Heldeweg MA, Sanders M, Harmsen M (2015) Public-private or private-private energy partnerships? Toward good energy governance in regional and local green gas projects. Energy, sustainability and society 5(1):1–12 http://www.barillacfn. com/wpcontent/uploads/2011/12/pp_nuovi_modelli_agricoltura_eng.pdf governance in regional and local green gas projects. Energy, sustainability and society 5(1):1 12 http://www.barillacfn. com/wpcontent/uploads/2011/12/pp_nuovi_modelli_agricoltura_eng.pdf com/wpcontent/uploads/2011/12/pp_nuovi_modelli_agricoltura_eng.pdf Johnsen T, Johnsen RE & Lamming RC (2008) Supply relationship evaluation: The relationship assessment process (RAP) and beyond. European Management Journal. 26. 274–287. Author details 1 ut o deta s 1Department of Economics & Management (DEIM), Università degli Studi della Tuscia, Via del Paradiso 47, 01100 Viterbo, Italy. 2Department for Innovation in Biological, Agro-food and Forest systems (DIBAF), Università degli Studi della Tuscia, Via S. Camillo de Lellis snc, 01100 Viterbo, Italy. 3Wageningen University, Hollandseweg 1, 6707 KN Wageningen, The Netherlands. 4University of Exeter Business School, Penryn Campus, G16 The SERSF Building, Cornwall, UK. 5Barilla G&R Fratelli SPA, via Mantova 166, 43122 Parma, Italy. Received: 8 October 2018 Accepted: 11 June 2019 References Johnston J, Gudergan SP (2007) Governance of public—private partnerships: lessons learnt from an Australian case? Int Rev Adm Sci 73(4):569–582 Keast R, Brown K, Mandell M (2007) Getting the right mix: unpacking integration meanings and strategies. Int Pub Manage J 10(1):9–33 Kesavan PC (2015) Shaping science as the prime mover of sustainable agriculture for food and nutrition security in an era of environmental degradation and climate change. Curr Sci 109(3):488–501 Kesavan PC (2015) Shaping science as the prime mover of sustainable agricult environmental degradation and climate change. Curr Sci 109(3):488–501 Lamming R, Johnsen T, Zheng J, Harland C (2000) An Initial Classification of Supply Networks. International Journal of Operations & Production Management. 20. 675–691. Lichtfouse E, Navarrete M, Debaeke P, Souchère V, Alberola C, Menassieu J (2009) Agronomy for sustainable agriculture: a review. In: Sustainable Agriculture. Springer, Netherlands, pp 1–7 Pacheco DF, York JG, Dean TJ, Sarasvathy SD (2010) The coevolution of institutional entrepreneurship: a tale of two theories. J Manag 36(4):974–1010 g Pancino B, Pascucci S, Blasi E, Ruini L, Ronchi C (2015) The role of network creation and actor engagement in the adoption and diffusion of sustainable innovations in food value chains Proceedings of Sidea Congress 2015 Pancino B, Pascucci S, Blasi E, Ruini L, Ronchi C (2015) The role of network creation and actor engagemen and diffusion of sustainable innovations in food value chains, Proceedings of Sidea Congress 2015 Pancino B, Pascucci S, Blasi E, Ruini L, Ronchi C (2015) The role of network creation and actor engagement and diffusion of sustainable innovations in food value chains, Proceedings of Sidea Congress 2015 Roehrich JK, Lewis MA, George G (2014) Are public–private partnerships a healthy option? A systematic literature review. Soc Sci Med 113:110–119 Ronald P (2011) Plant genetics, sustainable agriculture and global food security. Genetics 188(1):11–20 Ronald P (2011) Plant genetics, sustainable agriculture and global food security. Genetics 188(1):11–20 Rondinelli DA, Berry MA (2000) Environmental citizenship in multinational corporations: social responsibility and sustainable development. Eur Manag J 18(1):70–84 Rondinelli DA, Berry MA (2000) Environmental citizenship in multinational corporations: social responsibility and sustainable development. Eur Manag J 18(1):70–84 Stewart D, Kennedy A, Pavel A (2014) Beyond nutrition and agriculture policy: collaborating for a food policy. References Aiking H, De Boer J (2004) Food sustainability: diverging interpretations. Br Food J 106(5):359–365 B k d K (2006) M l i k h ld hi f i bl d l hi ki l i i Aiking H, De Boer J (2004) Food sustainability: diverging interpretations. Br Food J 106(5):359 365 Backstrand K (2006) Multi-stakeholder partnerships for sustainable development: rethinking legitimacy, accountability and effectiveness. Eur Environ 16(5):290–306 Barilla (2014) Barilla signs sustainable farming project with Italian Tomato Consortium, http://www.barillagroup.com/ corporate/en/home/media/company-news/barilla-signs-sustainable-farming-project-with-italian-tomato-consortium.html Barilla (2014) Barilla signs sustainable farming project with Italian Tomato Consortium, http://www.barillagroup.com/ corporate/en/home/media/company-news/barilla-signs-sustainable-farming-project-with-italian-tomato-consortium.html Baskerville RL (1997) Distinguishing action research from participative case studies. J Syst Inf Technol 1(1):24–43 BCFN (2011) New models for sustainable agriculture BCFN (2015) Good for you, good for the planet. http://www.barillagroup.com/sites/default/files/Barilla_2015_Report_EN_1.pdf Bernstein H (2014) Food sovereignty via the ‘peasant way’: a sceptical view. J Peasant Stud 41(6):1031–1063 y y Blasi E, Monotti C, Ruini L, Landi C, Avolio G, Meriggi P (2015) Eco-innovation as a driver in the agri-food value chain: an p y y ( ) p g Brouwer H, Woodhill J, Hemmati M, Verhoosel K, van Vugt S (2015) The MSP guide. How to design and facilitate multi- y y g Brouwer H, Woodhill J, Hemmati M, Verhoosel K, van Vugt S (2015) The MSP guide. How to design and facilitate multi- stakeholder partnerships. Centre for Development and Innovation, Wageningen stakeholder partnerships. Centre for Development and Innovation, Wageningen Butterfield KD, Reed R, Lemak DJ (2004) An inductive model of collaboration from the stakeholder’s perspective. Bus Soc 43(2):162–195 Butterfield KD, Reed R, Lemak DJ (2004) An inductive model of collaboration from the stakeholder’s perspective. Bus Soc 43(2):162–195 De Schepper S, Dooms M, Haezendonck E (2014) Stakeholder dynamics and responsibilities in public–private partnerships: a mixed experience. Int J Proj Manag 32(7):1210–1222 mixed experience. Int J Proj Manag 32(7):1210 1222 Dentoni D, Hospes O, Ross RB (2012) Managing wicked problems in agribusiness: the role of multi-stakeholder engagements in value creation. Int Food Agribusiness Manage Rev 15(B):1–12 p j g Dentoni D, Hospes O, Ross RB (2012) Managing wicked problems in agribusiness: the role of multi-stakeholder engagements in value creation. Int Food Agribusiness Manage Rev 15(B):1–12 Dentoni D, Hospes O, Ross RB (2012) Managing wicked problems in a in value creation. References Br J Nutr 112(S2):S65–S74 Waring J, Currie G, Bishop S (2013) A contingent approach to the organization and managem Wilhelm MM (2011) Managing coopetition through horizontal supply chain relations: linking dyadic and network levels of analysis. J Oper Manag 29(7):663–676 Page 10 of 10 Page 10 of 10 Page 10 of 10 Pancino et al. Agricultural and Food Economics (2019) 7:13 Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
https://openalex.org/W2567668914	https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0167837&type=printable	English	null	FFA2 Contribution to Gestational Glucose Tolerance Is Not Disrupted by Antibiotics	PloS one	2,016	cc-by	9,196	RESEARCH ARTICLE FFA2 Contribution to Gestational Glucose Tolerance Is Not Disrupted by Antibiotics Miles Fuller1, Xiaoran Li1, Robert Fisch1, Moneb Bughara1, Barton Wicksteed1, Petia Kovatcheva-Datchary2, Brian T. Layden1,3,4* 1 Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America, 2 Wallenberg Laboratory, Department of Molecular and Clinical Medicine, University of Gothenburg, Gothenburg, Sweden, 3 Jesse Brown Veterans Affairs Medical Center, Chicago, Illinois, United States of America, 4 Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, United States of America a11111 * blayde1@uic.edu * blayde1@uic.edu Data Availability Statement: All relevant data are within the paper and its Supporting Information file. Funding: BTL is supported by the National Institutes of Health under award number, R01DK104927-01A1, The University of Chicago DR&C (P30DK020595) and Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Career Development (Grant no. 1IK2BX001587-01). MF is supported by the American Heart Association under award number 15PRE25750015. The funders had no role in study design, data collection Abstract During the insulin resistant phase of pregnancy, the mRNA expression of free fatty acid 2 receptor (Ffar2) is upregulated and as we recently reported, this receptor contributes to insulin secretion and pancreatic beta cell mass expansion in order to maintain normal glu- cose homeostasis during pregnancy. As impaired gestational glucose levels can affect met- abolic health of offspring, we aimed to explore the role of maternal Ffar2 expression during pregnancy on the metabolic health of offspring and also the effects of antibiotics, which have been shown to disrupt gut microbiota fermentative activity (the source of the FFA2 ligands) on gestational glucose homeostasis. We found that maternal Ffar2 expression and impaired glucose tolerance during pregnancy had no effect on the growth rates, ad lib glu- cose and glucose tolerance in the offspring between 3 and 6 weeks of age. To disrupt short chain fatty acid production, we chronically treated WT mice and Ffar2-/- mice with broad range antibiotics and further compared their glucose tolerance prior to pregnancy and at gestational day 15, and also quantified cecum and plasma SCFAs. We found that during pregnancy antibiotic treatment reduced the levels of SCFAs in the cecum of the mice, but resulted in elevated levels of plasma SCFAs and altered concentrations of individual SCFAs. Along with these changes, gestational glucose tolerance in WT mice, but not Ffar2-/- mice improved while on antibiotics. Additional data showed that gestational glucose tolerance worsened in Ffar2-/- mice during a second pregnancy. Together, these results indi- cate that antibiotic treatment alone is inadequate to deplete plasma SCFA concentrations, and that modulation of gut microbiota by antibiotics does not disrupt the contribution of FFA2 to gestational glucose tolerance. OPEN ACCESS OPEN ACCESS Citation: Fuller M, Li X, Fisch R, Bughara M, Wicksteed B, Kovatcheva-Datchary P, et al. (2016) FFA2 Contribution to Gestational Glucose Tolerance Is Not Disrupted by Antibiotics. PLoS ONE 11(12): e0167837. doi:10.1371/journal.pone.0167837 Editor: Marcia B. Aguila, Universidade do Estado do Rio de Janeiro, BRAZIL Received: May 1, 2016 Accepted: November 21, 2016 Published: December 13, 2016 Copyright: © 2016 Fuller et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Citation: Fuller M, Li X, Fisch R, Bughara M, Wicksteed B, Kovatcheva-Datchary P, et al. (2016) FFA2 Contribution to Gestational Glucose Tolerance Is Not Disrupted by Antibiotics. PLoS ONE 11(12): e0167837. doi:10.1371/journal.pone.0167837 Citation: Fuller M, Li X, Fisch R, Bughara M, Wicksteed B, Kovatcheva-Datchary P, et al. (2016) FFA2 Contribution to Gestational Glucose Tolerance Is Not Disrupted by Antibiotics. PLoS ONE 11(12): e0167837. doi:10.1371/journal.pone.0167837 Editor: Marcia B. Aguila, Universidade do Estado do Rio de Janeiro, BRAZIL Copyright: © 2016 Fuller et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All relevant data are within the paper and its Supporting Information file. Antibiotics and FFA2-Dependent Gestational Glucose Tolerance changes during pregnancy and drive metabolic changes in the host [3]. However, the mecha- nisms by which the gut microbiota mediate metabolic change including during pregnancy remain unknown. A g-protein-coupled receptor (GPCR), free fatty acid 2 receptor (FFA2; GPR43), expressed in pancreatic beta (β) cells contributes to glucose stimulated insulin secre- tion (GSIS) [4,5], and Ffar2 levels in islets are elevated during pregnancy suggesting a potential role for FFA2 in the β cell response to gestational insulin resistance [6,7]. The ligands for FFA2, short chain fatty acids (SCFAs), are the products of fermentation by the gut microbiota [8,9]. These data suggest that FFA2 may be mediating gestational glucose homeostasis and this function may be regulated by changes in the gut microbiota. and analysis, decision to publish, or preparation of the manuscript. and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. Due to this relationship, our group recently investigated the role of FFA2 in gestational glu- cose homeostasis using genetic FFA2 global knockout (KO; Ffar2-/-; Gpr43-/-) mice. We showed that at the peak of gestational insulin resistance in mice, gestational day 15 (G15) [10], FFA2 is necessary to maintain glucose tolerance, glucose stimulated insulin secretion and β cell mass expansion [11]. We also observed that at phylum level the gut microbiota composi- tion is influenced by pregnancy with consequential changes in cecum and blood SCFA levels [11]. These data suggested a relationship between FFA2, gut microbiota and SCFAs during pregnancy that regulates gestational glucose homeostasis. These above published findings have raised multiple important avenues of investigation, two of which are explored here. Maternal hyperglycemia during pregnancy is associated with abnormally high insulin resis- tance, fetal hyperinsulinemia and overgrowth [12]. These changes, which are associated with the diagnosis of gestational diabetes, complicate pregnancies by increasing the occurrence of hypertensive disorders, necessity for cesarean section, presence of macrosomia in newborns, risk of shoulder dystocia and prenatal mortality. In the long-term, it increases the likelihood that the mother will develop type 2 diabetes mellitus (T2DM), cardiovascular disease (CVD), and metabolic syndrome [13]. Similarly, maternal hyperglycemia during pregnancy places the offspring at increased risk for T2DM, obesity and metabolic syndrome [14]. Therefore, we first explore if maternal hyperglycemia during pregnancy due to Ffar2 deletion is sufficient to lead to aberrant metabolic health in their offspring. Introduction The gut microbiota is now well described to influence different metabolic states [1,2]. Of importance to this study, the human gut microbiota has been shown to undergo dynamic PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 1 / 17 PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 Antibiotic Treatment for Adult Study At 8 weeks of age, mice were given water supplemented with antibiotics (1g/L of neomycin, ampicillin and metronidazole; Sigma) [17]. Antibiotic solutions were made fresh and replaced every 3 days. After 3 weeks of antibiotic treatment, WT and Ffar2-/- females were mated with Ffar2+/- males. Following copulation, the male breeders were removed and the experimental mice were housed individually. Upon delivery, the experimental mice were taken off the anti- biotic treatment and their microbiota was reconstituted with 50μL of the fecal suspension via oral gavage. To generate the fecal suspension, ~3g of fresh fecal pellets were collected from the Ffar2+/- breeding pairs used to generate the experimental mice, homogenized and suspended in 10mL of PBS, aliquoted in 200μL and were stored at -80˚C until ready for use. Two weeks after reconstitution, the experimental females were mated with an antibiotic-treated male breeder. Breeders were once again removed following copulation and pregnant females were housed individually. Plasma from blood, fecal and cecal samples were collected at the defined time points and stored at -80˚C until further use. Breeding approach for Offspring Study For the offspring study, WT x WT, Ffar2+/- x Ffar2+/- and Ffar2-/- x Ffar2-/- breeding pairs were used and had glucose tolerance evaluated (see Fig 1). The offspring included two control groups; WT mice and Ffar2-/-, and the experimental Ffar2-/- group, respectively, generated from these breeding pairs (see Fig 2A). From these same breeding pairs, the offspring were fol- lowed and metabolically assessed, as reported in Fig 2 and Table 1. Animals Ffar2+/- mice were bred to generate Ffar2-/- mice and wild-type (WT) mice as previously described [18]. In brief, the Ffar2 has 3 exons, a portion of exon 1 was replaced by a targeting sequence resulting in a frame shift mutation of the downstream amino acid sequence. Geno- type was determined by PCR, where genomic DNA was amplified by PCR using multiplex primer pairs as before [11]. Male and female mice were studied between 3 and 25 weeks of age as indicated in the results section. All animal experiments were approved by the Institutional Animal Care and Use Committee at Northwestern University. For the following experiments, mice were euthanized with CO2 exposure followed by decapitation as confirmation. Newborns were considered to die after birth if discovered in the first 1–2 days following observing a new litter. All mice were on a standard chow diet (3.1 Kcal/g) from LM-485 Harlan laboratories, which includes % kcal from protein (25%), carbohydrate (58%), and fat (17%). Our earlier report [11] suggested that the gut microbiota-SCFAs-FFA2 relationship is nec- essary to maintain maternal glucose homeostasis where absence of the sensor, FFA2, was responsible for impaired gestational glucose in mice. This raises the possibility that a void in stimuli (SCFAs) or stimuli producers (gut microbiota) can modulate the contribution of FFA2 to glucose homeostasis. Several methods exist to study the contribution of gut microbiota to host functions. For example, gnotobiotic mice are used to determine the impact of specific microbial cohorts [15]. While gnotobiotic mice allow for the highly controlled study of gene function in the presence of known gut microbes, antibiotic ablation is an alternative approach to evaluate the impact of the gut microbiota on host health [16] that can be easily applied. Studies have shown that chronic, broad-range antibiotic treatment effectively depletes the gut microbial population in mice and such antibiotic knockdown has been used to explore effects of the gut microbiota on various metabolic parameters [17]. Considering that FFA2 is required for normal gestational glucose homeostasis and activated by gut-derived metabolites, we also examined the role of the gut microbiota in gestational glucose homeostasis through antibiotic knockdown of the gut microbiota. Therefore, here, we conducted two studies: 1) an offspring study, where the metabolic health of progeny from WT and Ffar2-/- mothers with or without impaired gestational glucose toler- ance was evaluated and 2) an adult study, in which the glucose tolerance of mice were evalu- ated at G15 after antibiotic knockdown of the gut microbiota. This study aims to provide new insights into how disruption of the gut microbiota-SCFAs-FFA2 relationship affects glucose 2 / 17 Antibiotics and FFA2-Dependent Gestational Glucose Tolerance homeostasis in mothers and determine if this relationship impacts the metabolic health of the offspring. homeostasis in mothers and determine if this relationship impacts the metabolic health of the offspring. GLP-1 Measurements For measuring glucagon-like peptide 1 (GLP-1) secretion, 2 g glucose/kg of body wt OGTT was performed with blood samples collected at 0 and 30 min using heparin capillary tubes (Drummond, Broomall, PA) and stored in microcentrifuge tubes containing 50μM DPP-IV inhibitor (EMD Millipore, St. Charles, MO). Samples were then centrifuged for 10 minutes at 7,000 x g and plasma separated for storage at -80˚C until analysis [11]. The ELISA kit for active GLP-1 was from Immuno-Biological Laboratories (Minneapolis, MN). Antibiotics and FFA2-Dependent Gestational Glucose Tolerance Fig 1. Ffar2+/- mice exhibit normal glucose tolerance at gestational day 15 (G15). (a) Plasma glucose concentrations from WT, Ffar2+/- and Ffar2-/- female mice during an IPGTT at G15. (b) The corresponding area under the curve (AUC) for the IPGTT. WT circles and white bars; Ffar2+/-, squares and gray bars; Ffar2-/-, triangles and black bars. Data in (a) were compared by 2-way ANOVA with Bonferroni post-hoc analyses. Data in (b) were compared by Student’s t-test (, p<0.05; , p<0.01; *p<0.001), n = 4–5 mice/ group. Fig 1. Ffar2+/- mice exhibit normal glucose tolerance at gestational day 15 (G15). (a) Plasma glucose concentrations from WT, Ffar2+/- and Ffar2-/- female mice during an IPGTT at G15. (b) The corresponding area under the curve (AUC) for the IPGTT. WT circles and white bars; Ffar2+/-, squares and gray bars; Ffar2-/-, triangles and black bars. Data in (a) were compared by 2-way ANOVA with Bonferroni post-hoc analyses. Data in (b) were compared by Student’s t-test (, p<0.05; , p<0.01; p<0.001), n = 4–5 mice/ group. doi:10.1371/journal.pone.0167837.g001 (ALPCO). Insulin tolerance tests (ITT) were performed on mice fasted for 6 hrs, by intraperi- toneal injections of 1.0 U/kg insulin and glucose levels followed over 120 min. Results are pre- sented as percentage of blood glucose before insulin injection. Organic Acids Extraction and Analysis Gas chromatography-mass spectrometry (GC-MS) was used for measurement of organic acids in mouse plasma collected from inferior vena cava and cecal samples as fully described in Fuller et al. [11]. Both the cecum and plasma samples were processed and extracted including the addition of internal standards as before [11], and an aliquot of the resulting derivatized material was injected into a gas chromatograph (Agilent Technologies 7890 A) coupled to a mass spectrometer detector (Agilent Technologies 5975 C) for analysis. For the cecal analysis, both SCFAs (acetate, propionate, and butyrate), and the SCFA precursors (lactate and succi- nate) were measured and reported. For the plasma metabolites, only the SCFAs (acetate, propi- onate, butyrate) were measured and reported. Glucose and Insulin Tolerance Tests Intraperitoneal glucose tolerance tests (IPGTTs) were done on mice fasted overnight with glu- cose given by intraperitoneal injection (2g glucose/kg of body weight). Blood was obtained from tail veins for glucose determination (measured with a One-Touch Ultra Glucometer). Glucose levels were measured at multiple time points (from 0 to 120 min) during the IPGTT. For the IPGTT, area under the curve (AUC) values were calculated by standard approaches using the trapezoidal rule and are represented as mean ± SEM. Blood obtained from tail veins at 0, 5 and 15 mins during the IPGTT was used to measure insulin levels by ELISA assay 3 / 17 PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 Antibiotics and FFA2-Dependent Gestational Glucose Tolerance Table 1. Litter size and morbidity rate Breeding Group Newborn No. Newborns That Died After Birth Total no. No./litter Total no. No./litter Ffar2+/+ x Ffar2+/+ 36 5.1 ± 0.9 2 0.15 ± 0.08 Ffar2+/- x Ffar2+/- 32 5.6 ± 1.1 2 0.08 ± 0.06 Ffar2-/- x Ffar2-/- 31 6.2 ± 1.0 1 0.04 ± 0.04 Values are means ± SE. Table 1. Litter size and morbidity rate Water (Certified DNA Free), 10μl PerfeCTa SYBR Green FastMix (2X), 1μl of Forward Primer (0.25μM final concentration), 1μl of Reverse Primer (0.25μM final concentration), and 1μl DNA template (0.0625ng DNA for 16S V2 and V6, 25ng DNA for mouse genomic DNA). The PCR parameters were as follows: 3min activation step (95˚C); then 40 cycles of 3 s denatur- ation (95˚C), 30 s annealing and extension (60˚C for 16S-V2 and mouse genomic, 55˚C for 16S-V6). For each sample, the number of 16S DNA copies was related to the number of mouse genomic DNA copies. Samples with a threshold more than 35 cycles for the genomic PCR were regarded as poorly amplifiable and excluded from analysis. Bacterial 16S DNA Expression DNA was isolated from fecal samples using the PowerSoil kit (MoBIO) according to Earth Microbiome Project (EMP) standard protocols (http://www.earthmicrobiome.org/emp- standard-protocols/dna-extraction-protocol/) and quantified by spectrophotometry at 260 nm. Primers for V2 and V6 region of bacterial 16S rRNA genes and mouse genomic DNA were used as previously described [19]. Each 20μl PCR reaction contained 7μl of MoBio PCR 4 / 17 PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 Antibiotics and FFA2-Dependent Gestational Glucose Tolerance Fig 2. WT, Ffar2-/- and Ffar2-/- mice exhibit similar weight gain, random glucose levels and glucose tolerance at 6 weeks of age. (a) Breeding scheme to generate these offspring is shown. For b-g, changes in body weight (b-c), ad lib plasma glucose concentrations (d-e) and plasma glucose concentrations during an IPGTT (f-g) with male (b, d and f) and female (c, e and g) WT, Ffar2-/- and Ffar2-/- offspring are shown. Inserts for f and g represent the area under the curve for the IPGTT. WT, circles and white bars; Ffar2-/-, squares and gray bars; Ffar2-/-, triangles and black bars. Data are represented as mean ± SEM (p 0.05), n = 3–12. Data in (b-g) were compared by 2-way ANOVA with Bonferroni post- hoc analyses. doi:10.1371/journal.pone.0167837.g002 Fig 2. WT, Ffar2-/- and Ffar2-/- mice exhibit similar weight gain, random glucose levels and glucose tolerance at 6 weeks of age. (a) Breeding scheme to generate these offspring is shown. For b-g, changes in body weight (b-c), ad lib plasma glucose concentrations (d-e) and plasma glucose concentrations during an IPGTT (f-g) with male (b, d and f) and female (c, e and g) WT, Ffar2-/- and Ffar2-/- offspring are shown. Inserts for f and g represent the area under the curve for the IPGTT. WT, circles and white bars; Ffar2-/-, squares and gray bars; Ffar2-/-, triangles and black bars. Data are represented as mean ± SEM (p 0.05), n = 3–12. Data in (b-g) were compared by 2-way ANOVA with Bonferroni post- hoc analyses. PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 5 / 17 Statistical Analysis Values are reported as the mean ± SEM. P values were calculated by Student’s t-test (two-tailed) and 2-way ANOVA with Bonferroni post-hoc analyses. P < 0.05 was considered significant. PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 Impaired glucose tolerance in Ffar2-/- mice does not lead to acute metabolic effects on their offspring Previously, we observed that female Ffar2-/- mice exhibit impaired glucose tolerance during pregnancy, at a time of heightened insulin resistance, as compared to control mice [11]. Since gestational diabetes mellitus (GDM) in humans significantly increases the likelihood of adverse effects on the offspring’s metabolic health [1], we assessed whether the glucose toler- ance impairment in the Ffar2-/- mothers impacted the glucose homeostasis of their offspring. To evaluate this question, a comparison in metabolic parameters of offspring from the follow- ing breeders (WT x WT, Ffar2+/- x Ffar2+/- and Ffar2-/- x Ffar2-/-) was done, specifically com- paring both female and male WT, Ffar2-/- and Ffar2-/- offspring from each of these breeding pairs, respectively. This approach allowed us to examine the influence of genotype (WT versus Ffar2-/-) as well as maternal glucose tolerance on the offspring (see Fig 2A). Therefore, we first determined if glucose tolerance was altered in Ffar2+/- as compared to WT and Ffar2-/- moth- ers during pregnancy (at G15). Confirming our previous results, Ffar2-/- mice had significantly impaired glucose tolerance relative to WT mice during pregnancy (Fig 1A and 1B) at G15, and Ffar2+/- female mice had similar glucose tolerance to the WT mice during pregnancy. These later data suggest that one copy of the Ffar2 gene is sufficient to maintain normal gesta- tional glucose tolerance in mice. Because the Ffar2+/- female mice do not develop impaired glu- cose tolerance, this allows us to assess the influence of impaired maternal glucose tolerance on the metabolic health of the Ffar2-/- offspring. To determine the impact of impaired glucose tolerance on the early life of offspring in this model, we further bred WT x WT, Ffar2+/- x Ffar2+/- and Ffar2-/- x Ffar2-/- breeding pairs and we compared the litter size and survival rates of their offspring (Table 1). The mean litter sizes and stillbirth rates were similar across each of the breeding pairs (Table 1). These results 6 / 17 PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 Antibiotics and FFA2-Dependent Gestational Glucose Tolerance suggest that maternal impairment in glucose tolerance due to FFA2 deletion does not influence litter size or survival. To investigate whether impairment in maternal glucose tolerance affects growth of the progeny, we examined both female and male WT offspring from WT x WT pairs and Ffar2-/- offspring from Ffar2+/- x Ffar2+/- and Ffar2-/- x Ffar2-/- breeding pairs (Fig 2A). Impaired glucose tolerance in Ffar2-/- mice does not lead to acute metabolic effects on their offspring As apparent, female and male KO mice (Ffar2-/-) from Ffar2-/- x Ffar2-/- breeding pairs that were exposed to impairment in maternal glucose tolerance had similar body weights from the weaning date (21 days after birth) to sexual maturity (42 days after birth) as compared to KO offspring (Ffar2-/-) from Ffar2+/- x Ffar2+/- and WT offspring from WT x WT breeding pairs (Fig 2B and 2C). Thus, impaired maternal glucose tolerance in the Ffar2-/- mice does not influence offspring body weight or growth during this period. As weight or growth may not be the only parameters influenced by altered maternal glucose tolerance, we next evaluated its effects on glucose homeostasis in the offspring by measuring blood glucose ad libitum and during an IPGTT (at 6 weeks of age). When comparing WT off- spring from WT x WT pairs and Ffar2-/- offspring from Ffar2+/- x Ffar2+/- and Ffar2-/- x Ffar2-/- breeding pairs, ad libitum blood glucose measurements was similar in male and female offspring between days 21 and 42 across each group (Fig 2D and 2E). IPGTTs were conducted at 42 days of age to more rigorously assess glucose tolerance and showed no significant differ- ence in the blood glucose levels between groups in either sex (Fig 2F and 2G). These results verify that Ffar2 deletion impairs maternal glucose tolerance, but this impairment does not affect the growth, random glucose levels or glucose tolerance of the offspring in the first 6 weeks of life. PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 Antibiotics and FFA2-Dependent Gestational Glucose Tolerance Fig 3. Antibiotic treatment significantly reduces cecum metabolites concentrations. Antibiotic treatment significantly reduced cecum bacterial populations for the V2 regions (a) and V6 regions (b) with both WT and Ffar2-/- mice, where the copies of 16S V2 and V6 DNA copies (which reflects the amount of bacteria) was relative to the copies of mouse genomic DNA. Total metabolite levels, which includes both the SCFAs (acetate, propionate, and butyrate) and intermediates in SCFA synthesis (succinate and lactate) in cecum samples are shown from Ffar2-/- and WT mice before pregnancy (c) and at G15 (d) under control and antibiotic-treated conditions. WT, white bars; Ffar2-/-, black bars. Data are represented as mean ± SEM (p 0.05), n = 4–8 for a-b, n = 6–8 for c-d. Data (for a-d) were compared by Student’s t-test. (, p<0.05). doi:10 1371/journal pone 0167837 g003 Fig 3. Antibiotic treatment significantly reduces cecum metabolites concentrations. Antibiotic treatment significantly reduced cecum bacterial populations for the V2 regions (a) and V6 regions (b) with both WT and Ffar2-/- mice, where the copies of 16S V2 and V6 DNA copies (which reflects the amount of bacteria) was relative to the copies of mouse genomic DNA. Total metabolite levels, which includes both the SCFAs (acetate, propionate, and butyrate) and intermediates in SCFA synthesis (succinate and lactate) in cecum samples are shown from Ffar2-/- and WT mice before pregnancy (c) and at G15 (d) under control and antibiotic-treated conditions. WT, white bars; Ffar2-/-, black bars. Data are represented as mean ± SEM (p 0.05), n = 4–8 for a-b, n = 6–8 for c-d. Data (for a-d) were compared by Student’s t-test. (, p<0.05). reduced SCFA production would result in less SCFA-FFA2 signaling. On antibiotics, prior to pregnancy, Ffar2-/- and WT mice responded similarly to an intraperitoneal glucose challenge (Fig 4B and 4F); however, antibiotic treatment improved glucose tolerance compared to mice not treated with antibiotics (see Fig 4F) in agreement with a previous study [17]. During preg- nancy, treatment with antibiotics resulted in statistically lower plasma glucose levels during an IPGTT in WT mice at multiple time points relative to Ffar2-/- mice (Fig 4C and 4G). Overall, pregnant Ffar2-/- mice had significantly impaired glucose tolerance relative to the pregnant WT mice on antibiotics (see Fig 4G). PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 Antibiotic disruption of the gut microbiota leads to improved glucose tolerance independent of FFA2 Our lab recently described a link between pregnancy-associated changes in the gut microbiota, plasma SCFA levels and β cell specific Ffar2 expression [11] in the maintenance of gestational glucose homeostasis. Since high-dose antibiotic treatment has been shown to significantly deplete the gut microbial load [17], we tested whether antibiotic knockdown of the gut micro- biota could disrupt this novel relationship. Thus, we first assessed if our approach, of giving drinking water supplemented with antibiotics, successfully knocked down the gut microbiota, where we observed that WT and Ffar2-/- mice had dramatically depleted the bacterial popula- tion of the gut microbiota by 16S DNA expression (Fig 3A and 3B, respectively). We next examined whether our antibiotic treatment sufficiently lowered cecum SCFAs, which included the SCFAs and intermediates in SCFA synthesis (see Methods), in our mouse model to test the relationship between the gut microbiota and FFA2 during pregnancy. Cecum samples were collected from mice prior to pregnancy (baseline) and during pregnancy (G15). As expected, we observed a significant difference between the baseline cecum SCFA concentrations in both WT and Ffar2-/- mice with nearly a 50% reduction in total cecum SCFAs in response to antibi- otics (Fig 3C). Similarly, during pregnancy, antibiotic treatment resulted in roughly a 50% reduction in SCFA concentrations in both Ffar2-/- and WT mice (Fig 3D). These data confirm that broad range antibiotic treatment significantly reduces cecum SCFA concentrations. To study the impact of the gut microbiota on glucose tolerance, we knocked down the gut microbiota and cecal SCFA levels in Ffar2-/- and WT mice with antibiotics, and assessed FFA2-dependent glucose tolerance before pregnancy and at G15, and subsequently reconsti- tuted the gut microbiota to reverse any antibiotic effect (Fig 4A). As we reported before [11], Ffar2-/- and WT mice have similar glucose tolerance at baseline, but at G15, Ffar2-/- mice exhibit impaired glucose tolerance (Fig 4F and 4G). We hypothesized that during pregnancy depletion of gut microbiota with antibiotics would impair glucose tolerance in WT mice, as 7 / 17 Antibiotics and FFA2-Dependent Gestational Glucose Tolerance antibiotic-treated and gut microbiota reconstituted WT and Ffar2-/- mice prior to pregnancy (f) and at G15 (g). (h) Area under the curve (AUC) values for plasma glucose concentrations during an IPGTT in WT and Ffar2-/- mice on G15 of their first and second pregnancy. WT, circles and white bars; Ffar2-/-, triangles and black bars. Data in (b-e) were compared by 2-way ANOVA with Bonferroni post-hoc analyses. Data in (f-h) were compared by Student’s t-test. (, p<0.05; , p<0.01; p<0.001), n = 7–16, mice/group. antibiotic-treated and gut microbiota reconstituted WT and Ffar2-/- mice prior to pregnancy (f) and at G15 (g). (h) Area under the curve (AUC) values for plasma glucose concentrations during an IPGTT in WT and Ffar2-/- mice on G15 of their first and second pregnancy. WT, circles and white bars; Ffar2-/-, triangles and black bars. Data in (b-e) were compared by 2-way ANOVA with Bonferroni post-hoc analyses. Data in (f-h) were compared by Student’s t-test. (, p<0.05; , p<0.01; p<0.001), n = 7–16, mice/group. doi:10.1371/journal.pone.0167837.g004 the glucose tolerance of WT and Ffar2-/- mice before pregnancy, which almost completely dis- appeared after gut microbiota reconstitution in WT mice (Fig 4D and 4F). However, the gut microbiota reconstitution did not completely reverse the improved glucose tolerance of Ffar2-/- mice (Fig 4D and 4F). During pregnancy (Fig 4E), impaired glucose tolerance in Ffar2-/- mice following gut microbiota reconstitution once again occurred and was signifi- cantly impaired glucose tolerance as compared to pregnant WT mice following gut microbiota reconstitution. Interestingly, the glucose tolerance of these Ffar2-/- mice was worse than the antibiotic-treated and control Ffar2-/- mice during pregnancy (see Fig 4G). This later observation led us to examine if multiple pregnancies in Ffar2-/- mice leads to a worsening of glucose tolerance. Using a separate cohort of mice in serial pregnancies, we observed that the glucose tolerance of Ffar2-/- mice did worsen in the second pregnancy (see Fig 4H). Together, these data suggests that 1) under non-pregnant conditions, antibiotic treat- ment promotes FFA2 receptor-independent improvement in glucose tolerance, 2) FFA2 con- tribution to gestational glucose tolerance in WT mice is not disrupted by high dose antibiotics, and 3) the impairment in glucose tolerance in Ffar2-/- mice becomes further impaired with subsequent pregnancies. To further investigate the overall improvement of glucose tolerance while on antibiotics, an effect which was independent of pregnancy, we explored if insulin tolerance was influenced in these mice (non-pregnant), where surprisingly, no difference between non-antibiotic treated WT mice or Ffar2-/- mice compared to antibiotic treated mice was observed (Fig 5A and 5B). As insulin tolerance tests lack overall sensitivity, we measured insulin secretion during the IPGTT at 0, 5 and 15 mins. For WT mice and Ffar2-/- mice (Fig 5C and 5D, respectively), lower insulin levels were observed while on antibiotics as compared to non-antibiotic treated, which is consistent with the overall improved glucose tolerance. As antibiotics disrupt SCFA levels through altering the gut microbiota which could possibly impaired GLP-1 secretion through a FFA2 dependent mechanism [9], we investigated if GLP-1 levels in these mice were altered at 0 min and 30 min post-glucose IPGTT. As seen in (Fig 5E and 5F), GLP-1 levels were profoundly elevated in antibiotic-treated mice, regardless of genotype, consistent with a previous report [20], where this elevation is possibly a major contributor to the improved glu- cose tolerance occurring in the antibiotic-treated mice. These data suggest that antibiotics improved glucose tol- erance independent of FFA2 expression before pregnancy, and in the WT mice at G15, but this effect was absent in pregnant Ffar2-/- mice at G15. Following the antibiotic treatment, we reconstituted the gut microbiota of these mice before they were mated a second time to reassess their glucose tolerance. Prior to pregnancy following the gut microbiota reconstitution, the glucose tolerance of WT and Ffar2-/- mice were similar (Fig 4D and 4F). Interestingly, antibiotic treatment promoted nearly a 50% improvement in 8 / 17 PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 Antibiotics and FFA2-Dependent Gestational Glucose Tolerance Fig 4. Effects of antibiotic treatment on gestational glucose tolerance before and during pregnancy. (a) Timeline of antibiotic treatment, pregnancy and reconstitution of the gut microbiota of female mice, where the control group was WT (Ffar2+/+) mice and the experimental group was Ffar2-/- mice. (b-c) Plasma glucose concentrations during an IPGTT in antibiotic-treated mice at G0 (b) and at G15 (c). (d-e) Plasma glucose concentrations during an IPGTT in mice after gut microbiome reconstitution at G0 (d) and G15 (e). (f-g) Comparison of AUC values for plasma glucose concentrations during an IPGTT administered to control, e.0167837 December 13, 2016 9 / 17 Fig 4. Effects of antibiotic treatment on gestational glucose tolerance before and during pregnancy. (a) Timeline of antibiotic treatment, pregnancy and reconstitution of the gut microbiota of female mice, where the control group was WT (Ffar2+/+) mice and the experimental group was Ffar2-/- mice. (b-c) Plasma glucose concentrations during an IPGTT in antibiotic-treated mice at G0 (b) and at G15 (c). (d-e) Plasma glucose concentrations during an IPGTT in mice after gut microbiome reconstitution at G0 (d) and G15 (e). (f-g) Comparison of AUC values for plasma glucose concentrations during an IPGTT administered to control, PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 9 / 17 Antibiotics and FFA2-Dependent Gestational Glucose Tolerance Fig 5. Antibiotic treatment substantially alters GLP-1 secretion independent of the mouse genotype. Insulin sensitivity, as measured by the insulin tolerance test in control female WT (a) and female Ffar2-/- mice (b), treated with antibiotics (open circles) or untreated (filled circles), where the y axis shows the relative glucose level at each time point as compared to the glucose level at 0 min. (c-d) The serum insulin response to a glucose challenge in antibiotic treated mice (open symbols) compared with control mice (filled symbols) in both WT mice (c) and Ffar2-/- mice (d). Plasma GLP-1 levels in antibiotic treated mice (white bars) compared to control mice (black bars) at 0 min and 30 min for the WT (e) and Ffar2-/- mice (f). Data are represented as mean ± SEM. Data in (a-d) were compared by 2-way ANOVA with Bonferroni post-hoc analyses. Data in (e, f) were compared by Student’s t-test. (, p<0.05; , p<0.01; p<0.001), n = 5–8 mice/group. Fig 5. Antibiotic treatment substantially alters GLP-1 secretion independent of the mouse genotype. Insulin sensitivity, as measured by the insulin tolerance test in control female WT (a) and female Ffar2-/- mice (b), treated with antibiotics (open circles) or untreated (filled circles), where the y axis shows the relative glucose level at each time point as compared to the glucose level at 0 min. (c-d) The serum insulin response to a glucose challenge in antibiotic treated mice (open symbols) compared with control mice (filled symbols) in both WT mice (c) and Ffar2-/- mice (d). Plasma GLP-1 levels in antibiotic treated mice (white bars) compared to control mice (black bars) at 0 min and 30 min for the WT (e) and Ffar2-/- mice (f). Data are represented as mean ± SEM. Data in (a-d) were compared by 2-way ANOVA with Bonferroni post-hoc analyses. Data in (e, f) were compared by Student’s t-test. (, p<0.05; , p<0.01; p<0.001), n = 5–8 mice/group. doi:10.1371/journal.pone.0167837.g005 doi:10.1371/journal.pone.0167837.g005 antibiotic treatment as compared to the control (Fig 6A). Also, during pregnancy while on antibiotics, plasma SCFA levels were elevated in WT mice, but not Ffar2-/- mice (Fig 6B). Importantly, these data suggest that while antibiotic treatment reduces gut SCFA concentra- tions, this does not translate to lower SCFAs in the blood. In β cells, the FFA2 receptor is primarily stimulated by circulating SCFAs, in particular acetate and, to a lesser degree, propionate and butyrate [21,22]. Thus, we next investigated whether antibiotics increased all blood SCFAs or if a restructuring of the relative abundance of individual SCFAs occurred. Interestingly, after antibiotic treatment, the percent of circulating acetate increased and became similar between both Ffar2-/- and WT mice (Fig 6C). During pregnancy while on antibiotics, the percent of circulating acetate in WT mice remained ele- vated, but was not increased in Ffar2-/- mice (Fig 6D). As opposed to acetate, the relative abun- dance of propionate in circulation decreased in Ffar2-/- and WT mice at baseline on antibiotics (Fig 6E). During pregnancy, propionate remained decreased in WT mice on antibiotics, which did not occur with antibiotic-treated Ffar2-/- mice (Fig 6F). The same pattern seen with propionate occurred with butyrate before and during pregnancy while on antibiotics (Fig 6G and 6H). Together these data indicate that broad-spectrum antibiotics increase total SCFAs in the blood, but differentially impact the concentrations of individual SCFAs, and these changes are also influenced by pregnancy. Antibiotic-mediated disruption of the gut microbiota elevates total plasma SCFAs and unequally influences individual SCFAs Antibiotic suppression is a commonly used approach to disrupt the gut microbiota in order to assess the relationship between the gut microbiota and aspects of metabolism. As we antici- pated, disruption of gut microbiota by antibiotic suppression led to lower cecal metabolites, SCFAs and intermediates in SCFA synthesis (succinate and lactate), in the cecum (see Fig 3). We expected this would translate to lower SCFA levels in circulation, where the effect of SCFAs on FFA2 function is occurring. To verify this, we next evaluated systemic SCFAs by measuring SCFA levels in plasma from blood prior to and during pregnancy in mice treated with antibiotics compared to untreated (control) mice. Unlike baseline cecum metabolites, plasma SCFA concentrations were higher in both WT and Ffar2-/- mice in response to PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 10 / 17 Antibiotics and FFA2-Dependent Gestational Glucose Tolerance Antibiotics and FFA2-Dependent Gestational Glucose Tolerance OS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 11 / 17 PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 11 / 17 Discussion It is well known that gestational diabetes can lead to adverse metabolic outcomes for both the mother and the child [12,13,14]. Our previous report established that FFA2 is involved in maintaining gestational glucose homeostasis [11]. Kahraman et al. recently showed that mater- nal insulin resistance and transient hyperglycemia lead to hyperglycemia in male and female offspring that becomes prominent (nearly 0.5-fold increase relative to wildtype controls) just 10 days after birth [23]. Because of the known influence of elevated glucose levels on fetal health, we examined if the impaired glucose tolerance in our female Ffar2-/- mice during preg- nancy influenced the metabolic fitness of their offspring. However, no overt metabolic effects on the offspring occurred. Unlike the liver specific insulin receptor knockout (LIRKO) mouse used in the previous study [23], our Ffar2-/- mice do not exhibit elevated plasma insulin con- centrations (see [11]) suggesting possibly that maternal hyperinsulinemia may be driving the early-age metabolic impacts in the offspring. It is also possible that the degree of maternal hyperglycemia in Ffar2-/- mice is not sufficient to induce acute metabolic effects on the off- spring [23], as the degree of impairment in the LIRKO mice is more severe than that of the Ffar2-/- mice during pregnancy. As apparent, this model establishes that FFA2 contributes to gestational glucose homeostasis, but the metabolic health of the offspring over the first 6–7 weeks of life is not influenced. An important question is why we do not see altered weight gain with our Ffar2-/- mice as compared to WT mice, as reported by others [24]. In their report, genetic deletion or overex- pression of FFA2 in adipose tissue resulted in either obese mice on normal diets or lean mice on high fat diets, relative to WT mice. While this study suggests a role of FFA2 in fat accumulation, PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 12 / 17 Antibiotics and FFA2-Dependent Gestational Glucose Tolerance Fig 6. Antibiotics alter the relative abundance of individual SCFAs in circulation during pregnancy. Total plasma SCFA levels which includes acetate, propionate, and butyrate measured in WT and Ffar2-/- mice at G0 (a) and G15 (b) under control vs antibiotic-treated conditions. (b-h) Relative abundance of individual SCFAs (acetate, c-d; propionate, e-f; and butyrate, g-h) in Antibiotics and FFA2-Dependent Gestational Glucose Tolerance 71/journal.pone.0167837 December 13, 2016 13 / 17 Fig 6. Antibiotics alter the relative abundance of individual SCFAs in circulation during pregnancy. Discussion Total plasma SCFA levels which includes acetate, propionate, and butyrate measured in WT and Ffar2-/- mice at G0 (a) and G15 (b) under control vs antibiotic-treated conditions. (b-h) Relative abundance of individual SCFAs (acetate, c-d; propionate, e-f; and butyrate, g-h) in PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 13 / 17 Antibiotics and FFA2-Dependent Gestational Glucose Tolerance WT and Ffar2-/- mice at G0 (c, e and g) and G15 (d, f and h) under control vs antibiotic-treated conditions. WT, white bars; Ffar2-/-, black bars. Data are represented as mean ± SEM n = 6–15, and were analyzed by Student’s t-test (p 0.05). WT and Ffar2-/- mice at G0 (c, e and g) and G15 (d, f and h) under control vs antibiotic-treated conditions. WT, white bars; Ffar2-/-, black bars. Data are represented as mean ± SEM n = 6–15, and were analyzed by Student’s t-test (*p 0.05). doi:10.1371/journal.pone.0167837.g006 doi:10.1371/journal.pone.0167837.g006 multiple other groups [4, 5, 25] have not observed a role of FFA2 in adiposity (see [26] for com- plete discussion). The discrepancies in these studies are likely due to the complexity of FFA2 sig- naling, the existence of other SCFA receptors, and the unclear influence of the gut microbiota, which is known to be unique between animal facilities. In this study, long-term treatment with antibiotics resulted in a sizeable reduction in cecum SCFAs in non-pregnant and pregnant mice, and this was likely from a reduced gut bacterial content, as observed here. Our data also shows that antibiotic treatment promotes FFA2-inde- pendent improvement in glucose tolerance under non-pregnant conditions as previously described [17], which was reversed upon reconstitution of the gut microbiota. This effect of improved glucose tolerance has been observed by others with gut microbiota knockdown through antibiotics and also under germ free conditions [17,27]; however, it is not clear how this is occurring. While our data with the antibiotic treated mice does not indicate improved insulin tolerance, possibly due to the lack of sensitivity of this test, we observed profoundly ele- vated GLP-1 levels regardless of genotype while the mice were on antibiotics, consistent with a previous report [20]. Moreover, with the antibiotic treated mice, insulin levels were lower in our report and the previous one [20], indicating improved insulin resistance. As GLP-1 is known to improve insulin sensitivity, this may be an important reason why antibiotic-treated mice and possibly germ-free mice have improved glucose tolerance. PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 To answer this first question, the post-antibiotic treated community of gut microbes must be definitively established, along with SCFA production levels from each treatment. These data will help to validate antibiotic approaches to modulate these factors. Moreover, these data will be helpful in understanding how the gut microbiota ultimately drives circulat- ing SCFA levels. Addressing the second question will rely on the interrogation of the mecha- nisms that regulate cecum SCFA transport, including thickness of the protective mucus layer, colonic absorption rates, etc. One likely possibility is that antibiotic treatment leads to thinning of the gut’s epithelial lining, as shown in a similar study [33], allowing for increased absorption of gut-derived metabolites into circulation. Overall, our study provides new directions for additional investigation to understand the impact of antibiotics on circulating gut-derived metabolite concentrations and SCFA receptor signaling. In this study, we also determined that subsequent pregnancies lead to further worsening of glucose tolerance impairment in the Ffar2-/- mice during pregnancy. This result can also occur in humans where GDM patients exhibit a higher rate of developing GDM in subsequent preg- nancies and also T2D later in life [36]. Our data also demonstrate that antibiotic perturbation of mouse gut microbiota leads to improved glucose tolerance before and during pregnancy possibly from increased acetate concentrations in the circulation. Insights into the mechanism through which plasma acetate levels are elevated during antibiotic treatment could provide clues for future strategies to improve glucose tolerance. In sum, these data have added to our understanding of the role of FFA2 in gestational regulation of glucose and provide insight into needed further investigation. Supporting Information S1 Fig. This file contains the data for each figure. (XLSX) Antibiotics and FFA2-Dependent Gestational Glucose Tolerance result of increased plasma acetate levels led to improved gestational glucose tolerance in WT mice while on antibiotics. Interestingly, Ffar2-/- mice did not have elevated blood SCFA levels during pregnancy (and WT mice did have elevated SCFA levels), making it complicated to interpret our results on the role of SCFAs/FFA2 signaling during pregnancy in Ffar2-/- mice. To address this in a different manner, we adapted an approach from Chen et al. [35], where we supplemented the drinking water of WT and Ffar2-/- mice with 1% sodium acetate to directly test the effect of increased acetate levels on FFA2-dependent β cell function. Unfortunately, oral acetate supplementation alone was not sufficient to elevate plasma acetate concentrations in this model to test this question (data not shown). To help understand how SCFA levels influence different aspects of glucose metabolism in an FFA2 dependent and independent manner may require a venous infusion approach to regulate blood SCFA levels in the future. The results of this study raise two major questions: 1) what changes are occurring in the gut microbiota composition and its SCFA production abilities from antibiotic treatment, and 2) do antibiotics impact the factors regulating the transport of SCFAs from the cecum into the blood? To answer this first question, the post-antibiotic treated community of gut microbes must be definitively established, along with SCFA production levels from each treatment. These data will help to validate antibiotic approaches to modulate these factors. Moreover, these data will be helpful in understanding how the gut microbiota ultimately drives circulat- ing SCFA levels. Addressing the second question will rely on the interrogation of the mecha- nisms that regulate cecum SCFA transport, including thickness of the protective mucus layer, colonic absorption rates, etc. One likely possibility is that antibiotic treatment leads to thinning of the gut’s epithelial lining, as shown in a similar study [33], allowing for increased absorption of gut-derived metabolites into circulation. Overall, our study provides new directions for additional investigation to understand the impact of antibiotics on circulating gut-derived metabolite concentrations and SCFA receptor signaling. The results of this study raise two major questions: 1) what changes are occurring in the gut microbiota composition and its SCFA production abilities from antibiotic treatment, and 2) do antibiotics impact the factors regulating the transport of SCFAs from the cecum into the blood? Discussion While we expected that antibiotic ablation of the gut microbiota and the corresponding reduction in cecum metabolites would translate into reduced SCFAs in the plasma, we observed the opposite, that antibiotics led to increased total plasma SCFA concentrations and relative plasma acetate levels in WT mice, indicating that antibiotic treatment, at least the pro- tocol used in our study, is not sufficient to suppress circulating blood SCFAs. In addition to bacterial fermentation, the gut microbiota also determines intestinal architecture and modu- lates intestinal barrier function by maintaining a 50μm thick mucus layer and intestinal epithe- lial cell junctions, which can limit the absorption of microbial and luminal contents [28–32]. A recent study reported that antibiotic perturbation of the microbiota leads to a reduction in the thickness of the colon wall and protective mucus layer [33], providing a potential mechanism through which increased transport of SCFAs from the lumen of the gut may be occurring and enter the surrounding vasculature. Interestingly, metronidazole, one of the antibiotics used in our study, have been shown to alter both microbiota and goblet cell function resulting in lower mucin-2 expression and subsequent thinning of the mucus layer [33]. Our data raised the important concern that gut microbiota ablation with antibiotics may not always be sufficient to lower blood SCFA levels. Additionally, this increase in plasma levels of SCFAs was not observed in pregnant Ffar2-/- mice on antibiotics, which may be for a multitude of reasons. For example, SCFA transport is a highly regulated process within the intestinal epithelium [34], where nutrient sensing receptors such as FFA2 may contribute to SCFA transport. Addi- tionally, the gut microbiota of the Ffar2-/- mice could have been influenced differently during pregnancy than the WT mice, and/or the influence of the antibiotics on the gut microbiota during pregnancy may have been unique between the mouse genotypes. Moreover, energy intake and/or demand could also be influenced in these pregnant Ffar2-/- mice, through unclear mechanisms. Future studies will require gnotobiotic mouse models to definitively determine the function of FFA2 in intestinal SCFA transport. In our study, the altered plasma SCFA profile was associated with improved baseline glu- cose tolerance. We expect, that during pregnancy, the effect of FFA2 signaling in the β cell as a 14 / 17 PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 References 1. Kelder T, Stroeve JH, Bijlsma S, Radonjic M, Roeselers G. Correlation network analysis reveals rela- tionships between diet-induced changes in human gut microbiota and metabolic health. Nutr Diabetes. 4:e122, 2014. doi: 10.1038/nutd.2014.18 PMID: 24979151 2. Sommer F, Backhed F. The gut microbiota–Masters of host development and physiology. Nature Reviews Microbiology 11: 227–238, 2013. doi: 10.1038/nrmicro2974 PMID: 23435359 3. Koren O, Goodrich JK, Cullender TC, Spor A, Laitinen K, Backhed HK, et al. Host remodeling of the gut microbiome and metabolic changes during pregnancy. Cell 150:470–480, 2012. doi: 10.1016/j.cell. 2012.07.008 PMID: 22863002 4. Priyadarshini M, Villa SR, Fuller M, Wicksteed B, Mackay CR, Alquier T, et al. An Acetate-Specific GPCR, FFAR2, Regulates Insulin Secretion. Mol Endocrinol 29: 1055–1066, 2015. doi: 10.1210/me. 2015-1007 PMID: 26075576 5. Tang C, Ahmed K, Gile A, Lu S, Grone HJ, Tunaru S, et al. Loss of FFA2 and FFA3 increases insulin secretion and improves glucose tolerance in type 2 diabetes. Nat Med 2: 173–177, 2015. 6. Layden BT, Durai V, Newman MV, Marinelarena AM, Ahn CW, Feng G, et al. Regulation of pancreatic islet gene expression in mouse islets by pregnancy. J Endocrinol 207: 265–279, 2010. doi: 10.1677/ JOE-10-0298 PMID: 20847227 7. Rieck S, White P, Schug J, Fox AJ, Smirnova O, Gao N, et al. The transcriptional response of the islet to pregnancy in mice. Mol Endocrinol 23: 1702–1710, 2009. doi: 10.1210/me.2009-0144 PMID: 19574445 8. Brown AJ, Goldsworthy SM, Barnes AA, Eilert MM, Tcheang L, Daniels D, et al. The Orphan G-protein- coupled receptors GPR41 and GPR43 are activated by propionate and other short chain carboxylic acids. J Biol Chem 278: 11312–11319, 2003. doi: 10.1074/jbc.M211609200 PMID: 12496283 9. Layden BT, Angueira AR, Brodsky M, Durai V, Lowe WL Jr. Short chain fatty acids and their receptors: new therapeutic targets. Trans Res 161: 131–140, 2013. 10. Karnik SK, Chen H, McLean GW, Heit JJ, Gu X, Zhang AY, et al. Menin controls growth of pancreatic beta-cells in pregnant mice and promotes gestational diabetes mellitus. Science 318: 806–809, 2007. doi: 10.1126/science.1146812 PMID: 17975067 11. Fuller M, Priyadarshini M, Gibbons SM, Angueira AR, Brodsky M, Hayes MG, et al. The short chain fatty acid receptor, FFA2, contributes to gestational glucose homeostasis. Am J Physiol Endocrinol Metab 309: E840–851, 2015. doi: 10.1152/ajpendo.00171.2015 PMID: 26394664 12. Buchanan TA, Xiang AH. Gestational diabetes mellitus. J Clin Invest 115: 485–491, 2005. doi: 10. 1172/JCI24531 PMID: 15765129 13. Pedersen J. Writing – original draft: BTL MF. Writing – review & editing: BTL MF. Author Contributions Conceptualization: BTL MF. Formal analysis: BTL MF. Funding acquisition: BTL. Investigation: MF XL BW RF MB PKD. Conceptualization: BTL MF. Formal analysis: BTL MF. Funding acquisition: BTL. Investigation: MF XL BW RF MB PKD. PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 15 / 17 Antibiotics and FFA2-Dependent Gestational Glucose Tolerance Methodology: BTL MF. Resources: BTL PKD. Supervision: BTL. Writing – original draft: BTL MF. Writing – review & editing: BTL MF. Writing – original draft: BTL MF. PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 References The pregnant diabetic and her newborn. Problems and management. Arch Dis Child 43: 391, 1968. 14. Ornoy A, Reece EA, Pavlinkova G, Kappen C, Miller RK. Effect of maternal diabetes on the embryo, fetus, and children: congenital anomalies, genetic and epigenetic changes and developmental out- comes. Birth Defects Res C Embryo Today 105: 53–72, 2015. doi: 10.1002/bdrc.21090 PMID: 25783684 15. Karlsson F, Tremaroli V, Nielsen J, Ba¨ckhed F. Assessing the human gut microbiota in metabolic dis- eases. Diabetes 62: 3341–3349, 2013. doi: 10.2337/db13-0844 PMID: 24065795 16. Ellekilde M, Selfjord E, Larsen CS, Jakesevic M, Rune I, Tranberg B, et al. Transfer of gut microbiota from lean and obese mice to antibiotic-treated mice. Sci Rep 4: 5922, 2014. doi: 10.1038/srep05922 PMID: 25082483 17. Carvalho BM, Guadagnini D, Tsukumo DM, Schenka AA, Latuf-Filho P, Vassallo J, et al. Modulation of gut microbiota by antibiotics improves insulin signaling in high-fat fed mice. Diabetologia. 55: 2823–34, 2012. doi: 10.1007/s00125-012-2648-4 PMID: 22828956 16 / 17 PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 Antibiotics and FFA2-Dependent Gestational Glucose Tolerance 18. Maslowski KM, Vieira AT, Ng A, Kranich J, Sierro F, Yu D, et al. Regulation of inflammatory responses by gut microbiota and chemoattractant receptor GPR43. Nature 461: 1282–1286, 2009. doi: 10.1038/ nature08530 PMID: 19865172 19. Reikvam DH, Erofeev A, Sandvik A, Grcic V, Jahnsen FL, Gaustad P, et al. Depletion of murine intesti- nal microbiota: effects on gut mucosa and epithelial gene expression. PLoS One 6: p. e17996, 2011. doi: 10.1371/journal.pone.0017996 PMID: 21445311 20. Hwang I, Park YJ, Kim YR, Ka S, Lee HY, Seong JK, et al. Alteration of gut microbiota by vancomycin and bacitracin improves insulin resistance via glucagon-like peptide 1 in diet-induced obesity. Faseb J. 29 (6): 2397–11, 2015. doi: 10.1096/fj.14-265983 PMID: 25713030 21. Brown AJ, Goldsworthy S.M., Barnes A.A., Eilert M.M.,Tcheang L., Daniels D., et al. The orphan g pro- tein-coupled receptors GPR41 and GPR43 are activated by propionate and other short chain carboxylic acids. J. Biol. Chem. 278: 11312–11319, 2003. doi: 10.1074/jbc.M211609200 PMID: 12496283 22. Le Poul E, Loison C, Struyf S, Springael JY, Lannoy V, Decobecq ME, et al. Functional characterization of human receptors for short chain fatty acids and their role in polymorphonuclear cell activation. J. Biol. Chem. 278: 25481–25489, 2003. doi: 10.1074/jbc.M301403200 PMID: 12711604 23. Kahraman S, Dirice E, De Jesus DF, Hu J, Kulkarni RN. References Maternal insulin resistance and transient hyper- glycemia impact the metabolic and endocrine phenotypes of offspring. Am J Physiol Endocrinol Metab 307: E906–E918, 2014. doi: 10.1152/ajpendo.00210.2014 PMID: 25249504 24. Kimura I, Ozawa K, Inoue D, Imamura T, Kimura K, Maeda T, et al. The gut microbiota suppresses insu- lin-mediated fat accumulation via the short-chain fatty acid receptor GPR43. Nat Comm. 4: 1829, 2013. 25. McNelis JC, Lee YS, Mayoral R, van der Kant R, Johnson AM, Wollam J, et al. GPR43 potentiates β- cell function in obesity. Diabetes 64(9): 3203–17, 2015. doi: 10.2337/db14-1938 PMID: 26023106 26. Priyadarshini M, Wicksteed B, Schiltz GE, Gilchrist A, Layden BT. SCFA receptors in pancreatic β cells: novel diabetes targets? Trends Endocrinol Metab. 27: 653–4, 2016. doi: 10.1016/j.tem.2016.03.011 PMID: 27091493 27. Backhed F, Ding H, Wang T, Hooper LV, Koh GY, Nagy A, et al. The gut microbiota as an environmental factor that regulates fat storage. Proc Natl Acad Sci USA 101: 15718–23. 2004. doi: 10.1073/pnas. 0407076101 PMID: 15505215 28. Round JL, Mazmanian SK. The gut microbiota shapes intestinal immune responses during health and disease. Nat Rev Immunol 9:313–323, 2009. doi: 10.1038/nri2515 PMID: 19343057 29. Caballero S, Pamer EG. Microbiota-mediated inflammation and antimicrobial defense in the intestine. Annu Rev Immunol 33: 227–256, 2015. doi: 10.1146/annurev-immunol-032713-120238 PMID: 25581310 30. Vaishnava S, Yamamoto M, Severson KM, Ruhn KA, Yu X, Koren O, et al. The antibacterial lectin RegIIIgamma promotes the spatial segregation of microbiota and host in the intestine. Science 334: 255–258, 2011. doi: 10.1126/science.1209791 PMID: 21998396 31. Gallo RL, Hooper LV. Epithelial antimicrobial defense of the skin and intestine. Nat Rev Immunol 12: 503–516, 2012. doi: 10.1038/nri3228 PMID: 22728527 32. Hendrickx APA, Top J, Bayjanov JR, Kemperman H, Rogers MRC, Paganelli FL, et al. Antibiotic-Driven Dysbiosis Mediates Intraluminal Agglutination and Alternative Segregation of Enterococcus faecium from the Intestinal Epithelium. MBio. 6: e01346–15, 2016. 33. Wlodarska M, Willing B, Keeney KM, Menendez A, Bergstrom KS, Gill N, et al. Antibiotic treatment alters the colonic mucus layer and predisposes the host to exacerbated Citrobacter rodentium-induced colitis. Infect Immun 79: 1536–1545, 2011. doi: 10.1128/IAI.01104-10 PMID: 21321077 34. Borthakur A, Priyamvada S, Kumar A, Natarajan AA, Gill RK, Alrefai WA, et al. A novel nutrient sensing mechanism underlies substrate-induced regulation of monocarboxylate transporter. Am J Physiol Gas- trointestinal Liver Physiol. 303: G1126–33, 2012. 35. Chen Y, Du J, Zhao YT, Zhang L, Lv G, Zhuang S, et al. PLOS ONE \| DOI:10.1371/journal.pone.0167837 December 13, 2016 References Histone deacetylase (HDAC) inhibition improves myocardial function and prevents cardiac remodeling in diabetic mice. Cardiovasc Diabetol 14: 99, 2015. doi: 10.1186/s12933-015-0262-8 PMID: 26245924 36. Bellamy L, Casa J, Hingorani A, Williams D. Type 2 diabetes mellitus after gestational diabetes: a sys- tematic review and meta-analysis. Sci Dir: The Lancet. 373: 1773–1779. 17 / 17
https://openalex.org/W3203173679	https://bmchealthservres.biomedcentral.com/track/pdf/10.1186/s12913-021-07048-1	English	null	Ophthalmic services in Shanghai 2017: a cataract-centric city-wide government survey	BMC health services research	2,021	cc-by	6,795	Zhu et al. BMC Health Services Research (2021) 21:1043 https://doi.org/10.1186/s12913-021-07048-1 Zhu et al. BMC Health Services Research (2021) 21:1043 https://doi.org/10.1186/s12913-021-07048-1 Open Access Ophthalmic services in Shanghai 2017: a cataract-centric city-wide government survey Xiangjia Zhu1,2†, Yu Du1†, Wenwen He1†, Jinhui Dai1†, Minjie Chen1, Peijun Yao1, Han Chen1, Hui Ren1, Yuan Fang1, Shensheng Tan2 and Yi Lu1,2* Abstract Background: Demand for eye care has increased in recent decades in China due to rapid socioeconomic development and demographic shift. Knowledge of output and productivity of ophthalmic services would allow policymakers to optimize resource allocation, and is therefore essential. This study sought to map the landscape of ophthalmic services available in Shanghai, China. Methods: In 2018, a government-led survey was conducted of all 86 tertiary/secondary hospitals and five major private hospitals providing eye care in Shanghai in the form of electronic questionnaire, which encompassed ophthalmic services (outpatient and emergency room [ER] visit, inpatient admissions, and surgical volume) and service productivity in terms of annual outpatient and ER visits per doctor, inpatient admissions per bed, and surgical volume per doctor. Comparisons were made among different levels of hospitals with categorical variables tested by Chi-square analysis. Results: The response rate was 85.7%. The Eye and Ear, Nose, and Throat (EENT) Hospital was the largest tertiary specialty hospital, and alone contributed to the highest 21.0% of annual ophthalmic outpatient and ER visits (visits per doctor: 5460), compared with other 26 tertiary hospitals, 46 secondary hospitals and five private hospitals (visits per doctor: 3683, 4651 and 1876). The annual inpatient admission was 20,103, 56,992, 14,090, and 52,047 for the EENT Hospital, all the other tertiary hospitals, secondary hospitals and five private hospitals, respectively. Turnover rates were highest for the EENT Hospital and private hospitals. The average surgical volume at the EENT Hospital was 72,666, exceeding that of private (15,874.8) and other tertiary hospitals (3366.7). The EENT Hospital and private hospitals performed 16,982 (14.2%) and 55,538 (46.6%) of all cataract surgeries. Proportions of both complicated cataractous cases and complicated cataract surgeries at the EENT Hospital was the highest, followed by other tertiary and secondary/private hospitals (P < 0.0001). * Correspondence: luyieent@163.com †Xiangjia Zhu, Yu Du, Wenwen He and Jinhui Dai are Co-first authors. 1Eye Institute of Eye and Ear, Nose, and Throat Hospital of Fudan University; Key Laboratory of Myopia, Ministry of Health; Key Laboratory of Visual Impairment and Restoration of Shanghai, Fudan University; Key NHC key Laboratory of Myopia, Fudan University; Chinese Academy of Medical Sciences, 83 Fenyang Road, Shanghai 200031, China 2Shanghai Medical Quality Control Management Center, 1477 West Beijing Road, Shanghai 200040, China Participating hospitals We considered it essential to collect data from all 86 ter- tiary and secondary hospitals with an ophthalmology de- partment and from five major high-volume private eye hospitals. Background China, as the most populous country in the world, has achieved remarkable progress in transitioning from a centrally planned economy towards a market-oriented economy over the last 40 years. However, the efficiency and equity of China’s healthcare system, which poten- tially affects the lives of nearly 1.40 billion people, have developed unsatisfactorily [1, 2]. With the rapid demo- graphic shift towards an aging population and the simul- taneous epidemiological change of the disease burden into predominantly non-communicable diseases, espe- cially age-related diseases, it is imperative for China to revamp the existing healthcare delivery system to meet the increasing demand for medical services [3]. Despite rapid development, public hospitals are strug- gling to cater for the rising numbers of patients. There- fore, the government has implemented numerous favorable policies to facilitate the growth of private ser- vices to expand access to healthcare and to alleviate the burden of healthcare delivery [4, 5]. In 1980, China first issued a policy that encouraged qualified medical profes- sionals to engage in private practice [6]. In 2010, the State Council published a policy document that further encouraged social capital investment in healthcare [7]. By 2017, the number of private hospitals in China had increased to 447,160 [8], and these hospitals address the shortage of public healthcare services. Nevertheless, careful attention should be given to the efficiency of hos- pitals to evaluate their performance and to improve the coordination of different sectors. Methods This was an observational, cross-sectional, questionnaire survey of hospitals providing specialty eye care in Shang- hai. This study involved the analysis of data acquired from a government-led questionnaire survey, which did not involve any human participants, personal identifiable information or animal experiments. Thus, according to the Ethics Committee at the EENT Hospital of Fudan University, this study involved no ethical issues, and was reviewed and deemed exempt from formal ethics ap- proval or consent forms from the participating hospitals. Via emails or telephone calls with the administrative of- fices at the target hospitals, we explained the purpose of the survey and asked for their participation. Only those who agreed to participate completed the questionnaire. Impaired vision is a high-priority public health issue, and population aging in China is causing a dramatic in- crease in the burden of age-related ocular diseases, such as cataracts and macular degeneration [9–11]. To im- prove eye care services in China, data are needed on the current availability and use of ophthalmic services. Shanghai is the economic center and the second most populous city in China, and faces tough challenges asso- ciated with an aging society. In 2016, 13.0% of the regis- tered population was over 65 years old, a percentage that increased to 21.8% in 2017 according to data provided by the Shanghai Municipal Statistics Bureau. © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Zhu et al. BMC Health Services Research (2021) 21:1043 Page 2 of 10 Conclusions: In Shanghai, public providers dominate ophthalmic services especially for complicated cases, with almost one fifth of services provided by the EENT Hospital alone, while private sectors, though not large in number, still effectively help meet large proportions of eye care demand. Optimization of hierarchical medical system is warranted to improve the efficiency and standardization of ophthalmic services. Keywords: Ophthalmic service, Cataract surgery, Public hospital, Private hospital, China period of healthcare reform could be very meaningful. However, few studies have addressed this issue to date. In 2018, the Shanghai Quality Control Center of Clin- ical Ophthalmology, an evidence-based center that con- ducts clinical care evaluations of ophthalmology, launched the first electronic questionnaire survey to ob- tain baseline information about the characteristics of eye care providers and their practices in Shanghai. The sur- vey investigated the distribution of the ophthalmic ser- vices across different subspecialties. It paid particular attention to cataract surgery because it was classified as the prioritized eye disease to be addressed in China in the 13th 5-Year National Plan of Eye Health launched by the National Health Commission in 2016. Measures and analysis The responses to the questions were summarized as pro- portions or means. Hospital output was assessed in terms of the number of outpatient and emergency room (ER) visits, the number of the inpatient admissions, and surgical volume. Service efficiency was measured as the annual outpatient and ER visits per doctor, annual in- patient admissions per bed, and the annual surgical vol- ume per doctor. Information pertaining to the demographic data of Shanghai in 2017 was extracted from China’s Health Statistics Yearbook 2018. Compari- sons among categorical variables among different levels of hospital were conducted by Chi-square analysis (Prism Version 9.9.1, GraphPad Software, LLC). The survey recorded 1492 beds for hospitalized oph- thalmic patients in Shanghai in 2017. Of these, 10.1, 50.7, and 16.2% were at the EENT Hospital, other ter- tiary hospitals, and secondary hospitals, while the five private hospitals had 23.1% of beds. On average, the number of beds at the EENT Hospital (150) exceeded the mean number of beds at private hospitals (68.8), ter- tiary hospitals (29.1), and secondary hospitals (5.2). In terms of the distribution of medical personnel among hospitals, the EENT Hospital was the best equipped, with the most comprehensive ophthalmic ex- aminations available, followed by private hospitals (Table 2). Unsurprisingly, the secondary hospitals lacked complex or advanced equipment, such as fluorescence angiography, confocal microscopy, vitrectomy instru- ments, and femtosecond lasers, compared with tertiary hospitals. Among the tertiary hospitals surveyed in this study, one stood out, the EENT Hospital of Fudan Univer- sity, as the largest hospital specialized in ophthalmol- ogy and otolaryngology in China. The EENT Hospital treats a much greater number of ophthalmic patients than other hospitals in Shanghai. Therefore, its data were analyzed separately from those of other tertiary hospitals. Questionnaire The questionnaire (Supplementary file) was developed by a panel of eye doctors in Shanghai based on previous published reports of other countries and was sent to the eligible hospitals in 2018 to collect information of oph- thalmic services for the 2017 fiscal year. Data collection was completed in October 2018. The questionnaire had two main parts: the basic characteristics of the hospital and the level of ophthalmic specialty services, which Considering these data, the future demand for eye care services is likely to outpace the available resources. Thus, periodic assessment of the availability and productivity of ophthalmic services in Shanghai during the current Page 3 of 10 Page 3 of 10 Page 3 of 10 Zhu et al. BMC Health Services Research (2021) 21:1043 hospital beds, and equipment In 2017, there were over 3000 doctors, nurses and tech- nicians providing eye care in Shanghai, representing ap- proximately 0.49 ophthalmologists per 10,000 population. Overall, 83.7% of eye doctors worked in pub- lic hospitals, which included 14.8% at the EENT Hospital and 47.8% at the other 26 tertiary hospitals (Table 1). The mean number of eye doctors with senior titles (chief physician and associate chief physician) was greatest at the EENT Hospital (67), followed by private hospitals (19.6), other tertiary hospitals (8.0), and secondary hos- pitals (2.0). Results included (1) outpatient and inpatient services, (2) profes- sional staff, (3) ophthalmic equipment, (4) volumes of different types of ophthalmic procedures, and (5) specific data on cataract surgery. Since the questionnaire used in this survey only included data collection of objective subjects without any subjective judgement, validation was not necessary. Participating hospitals Among 91 eligible hospitals, 78 hospitals responded (re- sponse rate of 85.7%), of which 27 were tertiary hospitals (EENT Hospital plus 26 other tertiary hospitals), 46 were secondary hospitals, and five were major high-volume private hospitals. All the tertiary hospitals and private hospitals responded while 13 secondary hospitals did not. The questionnaires were sent by standard mail to all eligible hospitals by the Shanghai Quality-control Center of Clinical Ophthalmology. The correspondence in- cluded a clear explanation of the survey’s purpose and the questionnaires were to be completed by an appropri- ate person in the administrative office at each hospital to ensure accuracy. Deadline was October 2018 with a re- minder email sent to the hospitals if they did not return the questionnaire. Measures and analysis Table 1 Total number and composition of professional and allied staff at each hospital level Staff Number Chief Physician Associate Chief Physician Attending Physician Resident Ophthalmic Nurse Theater Nurse Ordinary Nurse Optometrist Total EENT Hospital 28 39 39 70 145 109 36 20 486 Other tertiary hospitals 95 (3.7) 113 (4.3) 150 (5.8) 209 (8.0) 275 (10.6) 97 (3.7) 178 (6.8) 112 (4.3) 1229 (47.3) Secondary hospitals 44 (1.0) 47 (1.0) 115 (2.5) 44 (1.0) 131 (2.8) 56 (1.2) 75 (1.6) 41 (0.9) 553 (12.0) Private hospitals 57 (11.4) 41 (8.2) 43 (8.6) 52 (10.4) 263 (52.6) 56 (11.2) 207 (41.4) 41 (8.2) 760 (152.0) Total 224 240 347 375 814 318 496 214 3028 Numbers in brackets represent the mean number of staff at each hospital level. EENT Hospital Eye and Ear, Nose, and Throat Hospital of Fudan University Table 1 Total number and composition of professional and allied staff at each hospital level Zhu et al. EENT Hospital Eye and Ear, Nose, and Throat Hospital of Fudan University, NCT non-contact tonometer, Nd Yag neodymium-doped yttrium aluminum garnet, UBM ultrasound biomicroscope, ICG indocyanine green, OCT optical coherence tomography Ophthalmic service output and productivity having performed 72,666 procedures, which greatly exceeded that of private hospitals (15,874.8) and other tertiary hospitals (3366.7). The annual surgical volume per doctor was also greatest at the EENT Hospital (412.9), followed by private hospitals (411.3) and other tertiary hospitals (154.4). The output of ophthalmic services was evaluated in terms of the number of outpatient and ER visits, the number of inpatient admissions, and surgical volume. g The annual number of ophthalmic outpatient and ER visits in 2017 was 4,574,143, of which 21.0% were pro- vided by the EENT Hospital alone and 45.7% by other tertiary hospitals (Table 3). Private hospitals accounted for just 7.9% of the total number, which was relatively low considering they accounted for 16.3% of the total number of eye doctors. Generally, 31.7% of outpatient and ER visits in Shanghai were due to non-local patients. This percentage was the highest at the EENT Hospital (61.0%) followed by other tertiary hospitals (30.6%), whereas secondary and private hospitals mostly served local patients (over 80%) (P < 0.0001, Chi-square ana- lysis). Regarding the productivity of outpatient services, the number of outpatient and ER visits per eye doctor varied considerably among hospitals: 5460 at the EENT Hospital, 3683 at other tertiary hospitals, and only 1876 at private hospitals. y p ( ) In terms of the type of ophthalmic procedures, differ- ences among procedure compositions of EENT Hospital, other tertiary hospitals, secondary hospitals, and private hospitals were significant (P < 0.0001, Chi-square ana- lysis). Generally, cataract surgery was the most common (44.3%), followed by small incision lenticule extraction (SMILE, 12.0%) and vitreoretinal surgery (7.6%). At the EENT Hospital, SMILE was the most frequent proced- ure (25.8%), followed by cataract surgery (22.2%), anti- vascular endothelial growth factor injection (11.3%), lac- rimal duct reconstruction (11.0%) and vitreoretinal sur- gery (10.2%). At private hospitals, cataract surgery accounted for 70.2% of procedures and SMILE accounted for 13.9% (Fig. 1). At secondary hospitals, the percentage of extraocular procedures, particularly con- junctival surgery such as pterygium surgery (45.7%), was much greater than that at tertiary hospitals and private hospitals. Complicated eye surgeries, such as vitreoret- inal surgery and corneal transplantation, were mostly performed in tertiary hospitals. Private hospitals per- formed just 12.2% of these procedures, even though they had sufficient senior doctors, adequate hospital beds, and comprehensive equipment. Measures and analysis BMC Health Services Research (2021) 21:1043 Page 4 of 10 Table 2 Availability of ophthalmic equipment at each hospital level Ophthalmic Equipment Coverage Rate (%) Public Private hospita EENT Hospital Other tertiary hospitals Secondary hospitals Slit lamp 100 100 100 100 Direct ophthalmoscopy 100 100 95.7 100 Indirect ophthalmoscopy 100 76.9 15.2 60 Tonometer Applanation 100 34.6 4.3 20 Schiotz 100 15.4 21.7 20 NCT 100 100 97.8 100 Tonopen 100 11.5 0 40 Perimeter Static 100 73.1 50 100 Goldman 100 19.2 10.9 80 Autorefractor 100 88.5 89.1 100 Fundus camera 100 84.6 84.8 100 Nd Yag laser machine 100 73.1 39.1 80 Laser treatment machine of fundus 100 88.5 47.8 100 Biometry A-ultrasound 100 76.9 71.7 100 IOLmaster 100 69.2 34.8 100 B-ultrasound 100 76.9 73.9 100 UBM 100 53.8 13 100 Lenstar 100 30.8 4.3 0 Ophthalmic operating microscope 100 100 67.4 100 Fluorescence angiography equipment 100 69.2 47.8 100 ICG angiography equipment 100 30.8 13 20 Corneal topographer 100 61.5 23.9 80 OCT Anterior-segment 100 42.3 26.1 50 Glaucoma 100 38.5 21.7 80 Fundus 100 84.6 71.7 100 Visual electrophysiology examination machine 100 61.5 15.2 100 Specular microscope of cornea 100 76.9 47.8 100 Confocal microscope 100 15.4 2.2 20 Wavefront aberrometer 100 26.9 0 20 Contrast sensitivity device 100 26.9 2.2 50 Corneal thickness measuring device 100 46.2 26.1 20 Lens box 100 96.2 84.8 100 Comprehensive refractometer 100 88.5 67.4 100 Quick sterilizer 100 61.5 39.1 100 Excimer laser instrument 100 26.9 2.2 100 Femtosecond laser equipment For refractive surgery 100 23.1 0 100 For cataract surgery 100 3.8 0 80 Phacoemulsification instrument 100 80.8 67.4 100 Vitrectomy instrument 100 61.5 28.3 100 EENT Hospital Eye and Ear, Nose, and Throat Hospital of Fudan University, NCT non-contact tonometer, Nd Yag neodymium-doped yttrium aluminum garnet, UBM ultrasound biomicroscope, ICG indocyanine green, OCT optical coherence tomography Table 2 Availability of ophthalmic equipment at each hospital level Page 5 of 10 Page 5 of 10 Page 5 of 10 Zhu et al. BMC Health Services Research (2021) 21:1043 EENT Hospital Eye and Ear, Nose, and Throat Hospital of Fudan University The numbers in brackets represent the percentage of the total number for all hospitals Ophthalmic service output and productivity The total number of ophthalmic inpatient admissions in Shanghai was 143,232, of which 14% were at the EENT Hospital, 39.8% at other tertiary hospitals, and 36.3% at private hospitals (Table 3). The turnover rate, measured as the annual inpatient admissions per bed, was higher at the EENT Hospital and private hospitals (134 and 151, respectively) than at other tertiary hospi- tals and secondary hospitals (75 and 58, respectively). Ophthalmic procedures are another major aspect of eye care provided to the public. A total of 265,365 oph- thalmic procedures were performed in 2017. The EENT Hospital, other tertiary hospitals, and the private hospi- tals each provided about 30% of the total surgical vol- ume (Table 3). On average, the EENT Hospital was ranked first in terms of the annual surgical volume, Cataract surgery service In 2017, totally 119,264 cataract surgeries were per- formed in Shanghai, of which EENT Hospital alone con- tributed 14.2%, the other 26 tertiary hospitals contributed 30.7%, 46 secondary hospitals contributed 8.5% and private hospitals contributed 46.6% (Table 4). Table 3 Ophthalmic services provided at each hospital level Table 3 Ophthalmic services provided at each hospital level Output of ophthalmic services EENT Hospital Other tertiary hospitals Secondary hospitals Private hospitals Outpatient and emergency room visit Local 374,768 1,449,000 984,600 315,700 Non-local 586,175 639,400 178,200 46,300 Total 960,943 (21.0%) 2,088,400 (45.7%) 1,162,800 (25.4%) 362,000 (7.9%) Average visit 960,943 80,323.1 25,278.3 72,400.0 Inpatient admission Total inpatients 20,103 (14.0%) 56,992 (39.8%) 14,090 (9.8%) 52,047 (36.3%) Average inpatients 20,103 2192 306.3 10,409.4 Surgical volumes Total volumes 72,666 (27.4%) 87,533 (33.0%) 25,792 (9.7%) 79,374 (29.9%) Average volumes 72,666 3366.7 560.7 15,874.8 The numbers in brackets represent the percentage of the total number for all hospitals EENT Hospital Eye and Ear, Nose, and Throat Hospital of Fudan University Zhu et al. BMC Health Services Research (2021) 21:1043 Page 6 of 10 Fig. 1 Comparison of the surgical volume for different subspecialties at each hospital level. EENT Hospital: Eye and Ear, Nose, and Throat Hospital of Fudan University; ICL: implantable collamer lens; SMILE: small incision lenticule extraction Fig. 1 Comparison of the surgical volume for different subspecialties at each hospital level. EENT Hospital: Eye and Ear, Nose, and Throat Hospital of Fudan University; ICL: implantable collamer lens; SMILE: small incision lenticule extraction Based on the data provided by Shanghai Municipal Bureau of Statistics, there were around 24.18 million res- idents in Shanghai in 2017. Ophthalmic service output and productivity The cataract surgical rate (cataract operations done per million populations per year) might be around 4932.3 (119,264/ 24.18) in 2017 in Shanghai. However, given that the total number of cataract surgeries included a certain proportion of sur- geries performed on non-residents, this number was higher than the 4251 reported by the National Cataract Surgery Information Reporting System. were for complicated cataracts such as highly myopic cataract, traumatic cataract, and congenital cataract, re- quiring multi-subspecialty eye care, significantly higher than other hospitals on an average level. By comparison, this percentage was only 31.7% at private hospitals des- pite the large volume of cataract surgery (Table 4). g g y Regarding surgical techniques, standard phacoemulsifi- cation was the predominant cataract surgical technique (mostly > 95%). Of all femtosecond laser-assisted cata- ract surgical procedures (FLACS), 83% (1358) and 15% (251) were performed at private hospitals and the EENT Hospital, respectively. Meanwhile, the EENT Hospital performed 33.0% (325) of more difficult cataract proce- dures, such as scleral fixation of an intraocular lens (IOL) (Table 4). The proportion of complicated cataract surgery in the EENT Hospital was the highest (7.7%), followed by other tertiary hospitals (4.3%), secondary hospitals (2.7%), and private hospitals (1.7%) (P < 0.0001, Chi-square analysis). At the EENT Hospital, only 43.9% of cataract pro- cedures were performed as inpatient surgery. This value increased to 76.9 and 80.3% at secondary and private hospitals, respectively. The mean wait time for cataract surgery ranged from 0.3 to 8 weeks. The daily number of cataract surgical procedures ranged be- tween 20 and 80 at private hospitals, 68 at the EENT Hospital, and 20–65 at other tertiary hospitals. On average, the annual surgical volume per cataract sur- geon was greatest at private hospitals (2136.1), followed by the EENT hospital (1306.3), and other tertiary hospitals (359.1). A greater number of advanced IOLs, such as toric IOLs and multifocal IOLs, were implanted at the EENT Hospital (386), followed by private hospitals (mean 363.6), accounting for 2.4 and 3.3% of all IOL implanted at these hospitals. However, capsular tension ring (CTR) and modified CTR implantation were predominantly used at the EENT Hospital (74.1%, Table 4), followed by other tertiary hospitals (20.5%) and private hospitals (5.2%). Patient selection for cataract surgery showed clear trends among hospitals. The proportion of complicated cataractous patients varied significantly among EENT Hospital, other tertiary hospitals, secondary hospitals, and private hospitals (P < 0.0001, Chi-square analysis). Ophthalmic service output and productivity The numbers in brackets in the total row represent the percentage of the total number of procedures performed at all hospitals EENT Hospital Eye and Ear, Nose, and Throat Hospital of Fudan University, FLACS femtosecond laser-assisted cataract surgery, IOL intraocular lens, CTR capsular tension ring The numbers in brackets represent the percentage of the total number of procedures performed at each hospital level. The numbers in brackets in the total row represent the percentage of the total number of procedures performed at all hospitals EENT Hospital Eye and Ear, Nose, and Throat Hospital of Fudan University, FLACS femtosecond laser-assisted cataract surgery, IOL intraocular lens, CTR capsular tension ring Ophthalmic service output and productivity At the EENT Hospital, 58.0% of cataract procedures Zhu et al. BMC Health Services Research (2021) 21:1043 Page 7 of 10 Table 4 Cataract surgical procedures provided at each hospital level Table 4 Cataract surgical procedures provided at each hospital level Data on cataract surgery EENT Hospital Other tertiary hospitals Secondary hospitals Private hospitals Total Cataract type Age-related cataract 7132 (42.0%) 20,747 (56.6%) 6959 (68.8%) 37,949 (68.3%) 72,787 (61.0%) Highly myopic cataract 5604 (33.0%) 8494 (23.2%) 1346 (13.3%) 9654 (17.4%) 25,098 (21.0%) Diabetic cataract 2377 (14.0%) 5362 (14.6%) 1428 (14.1%) 7214 (13.0%) 16,381 (13.7%) Traumatic cataract 672 (4.0%) 938 (2.6%) 66 (0.7%) 29 (0.1%) 1705 (1.4%) Congenial cataract 664 (3.9%) 845 (2.3%) 67 (0.7%) 28 (0.1%) 1604 (1.3%) Others 533 (3.1%) 244 (0.7%) 248 (2.5%) 664 (1.2%) 1689 (1.4%) Total 16,982 (14.2%) 36,630 (30.7%) 10,114 (8.5%) 55,538 (46.6%) 119,264 Surgical techniques used in cataract surgery Standard phacoemulsification 15,425 (90.8%) 35,019 (95.6%) 9840 (97.3%) 53,216 (95.8%) 113,500 (95.2%) FLACS 251 (1.5%) 28 (0.1%) 0 (0.0%) 1358 (2.4%) 1637 (1.4%) Extracapsular cataract extraction 130 (0.8) 334 (0.9%) 238 (2.4%) 316 (0.6%) 1018 (0.9%) Intracapsular cataract extraction 15 (0.1%) 19 (0.1%) 0 (0.0%) 2 (0.0%) 36 (0.0%) Scleral fixation of IOL 325 (1.9%) 305 (0.8%) 36 (0.4%) 320 (0.6%) 986 (0.8%) Others 836 (4.9%) 925 (2.5%) 0 (0.0%) 326 (0.6%) 2087 (1.7%) Total 16,982 (14.2%) 36,630 (30.7%) 10,114 (8.5%) 55,538 (46.6%) 119,264 IOL used in cataract surgery Monofocal IOL 15,866 (97.6%) 35,023 (98.1%) 9891 (99.9%) 53,322 (96.7%) 114,102 (97.5%) Multifocal IOL 247 (1.5%) 379 (1.1%) 11 (0.1%) 1064 (1.9%) 1701 (1.5%) Toric IOL 139 (0.9%) 276 (0.8%) 1 (0.0%) 722 (1.3%) 1138 (1.0%) Toric multifocal IOL 0 (0.0%) 19 (0.1%) 0 (0.0%) 32 (0.1%) 51 (0.0%) Total 16,252 (13.9%) 35,697 (30.5%) 9903 (8.5%) 55,140 (47.1%) 116,992 CTR used in cataract surgery CTR 228 (51.7%) 93 (76.2%) 1 (100.0%) 26 (83.9%) 348 (58.5%) Modified CTR 213 (48.3%) 29 (23.8%) 0 (0.0%) 5 (16.1%) 247 (41.5%) Total 441 (74.1%) 122 (20.5%) 1 (0.2%) 31 (5.2%) 595 The numbers in brackets represent the percentage of the total number of procedures performed at each hospital level. Discussion greatly in recent years [12]. The creation of the China Pilot Free-Trade Zone (Shanghai) in late 2013 provided an effective platform for foreign direct investment into the healthcare sector. According to the Annual Report on the National Health Service in China 2017, published by the National Health Commission of the People’s Re- public of China, the number of patient visits to private hospitals increased by 17.0% in 2017 versus that in 2016, as compared with 4.2% in public hospitals. Moreover, China’s Health Statistics Yearbook 2018 reported that by the end of 2017, private providers accounted for nearly 50% (447,160/986,649) of all healthcare institutions in China [8]. Shanghai, the most economically developed city in China, has attracted significant private investment in healthcare and has seen a remarkable increase in the number of private hospitals in recent years. This paper provides detailed information about eye care providers in Shanghai in 2017, with the aim to understand the availability and productivity of oph- thalmic services and to provide a foundation for qual- ity control of ophthalmic care in the future. No government-led electronic questionnaire survey of this kind, enrolling nearly all eye care hospitals in Shang- hai, has been performed previously. The ophthalmic services were evaluated in terms of the basic charac- teristics of the hospitals, as well as their service out- put and efficiency. The survey had a particular emphasis on cataract surgery to investigate differences in its provision, independently of the disparity in productivity among different hospitals. With the revitalization of privatization in China, the number of private healthcare providers has expanded Page 8 of 10 Page 8 of 10 Zhu et al. BMC Health Services Research (2021) 21:1043 Zhu et al. BMC Health Services Research (2021) 21:1043 Our findings capture some typical features of the pub- lic and private ophthalmic services in Shanghai. Most hospitals offering ophthalmic services were still public, similar to the characteristics of other provinces of China, such as Guangdong [13]. This was possibly due to his- torical reasons. Before the implementation of supporting policy and the revitalization of privatization, there were hardly any standard private sectors in realm of health- care. Thus, patients tend to trust more in the reliability of public hospitals. However, in terms of the basic char- acteristics of the hospitals, the private sector has now greatly developed to an extent comparable with that of public hospitals of the highest accreditation. Discussion Similar to the medical systems of other countries, the private clinics tended to optimize non-clinical factors, such as facilities and wait times, more than public providers [14]. Social investment in private hospitals allowed them to employ many reputable doctors, construct larger- scale hospitals, and procure up-to-date equipment to at- tract patients [13, 15, 16]. This may help explain why the five private hospitals in Shanghai were better equipped than most of the public hospitals in Shanghai. Nevertheless, the EENT Hospital was still the best equipped with the highest percentage of senior doctors, the most beds and highest availability of almost all com- mercially available equipment for ophthalmic examina- tions and procedures. similar value of 10.9% was found at other tertiary hospi- tals, but this dropped to 1.9% at secondary hospitals, due to their lower technical level. Meanwhile, this value was also low, 3.2%, at private hospitals despite their extensive staff and facilities. Private hospitals performed 29.9% of the total surgical volume in Shanghai, but 70.2% of this was due to cata- ract surgery. One possible explanation is that the accu- mulated experience at tertiary hospitals, and greater support from local government and affiliating univer- sities, mean that their professional capabilities had reached a level similar to that in most developed coun- tries [17], and they were able to provide comprehensive eye care across multiple subspecialties. However, unlike the social objectives of public hospitals, the private hos- pitals tended to provide services with a high profit mar- gin. Cataract surgery and refractive surgery, two highly cost-effective ophthalmic procedures, have a huge poten- tial market considering cataract and refractive error are the two major causes of visual impairment worldwide. The types of cataract procedures also demonstrate the clear distinction between high-volume public hos- pitals and private hospitals. Advanced cataract tech- niques, including FLACS and implantation of advanced IOLs, were mostly performed at the EENT Hospital and private hospitals. However, private hos- pitals tended to perform fewer procedures in patients with complicated cataracts and performed fewer com- plex surgical techniques such as scleral fixation or implantation of CTR. Despite this, the private hospi- tals still provide an important aspect of eye care in Shanghai. The five major high-volume private hospi- tals performed over 46% of all cataract surgeries in 2017 in Shanghai, and contributed to the increase in the number of cataract surgeries from 2313 in 2012 to 4251 in 2017. Discussion Accordingly, private hospitals helped alleviate the imbalance between medical supply and demand, accelerating the achievement of universal coverage planned in China’s new round of healthcare reform. Nevertheless, appropriate supervision and management by the government is necessary to en- sure standardization of healthcare services and to re- duce the profit-driven focus in healthcare. Although there were gaps in the objective characteris- tics between hospital levels, the disparity in productivity was more concerning. The productive efficiency of hos- pitals is crucial to their future development, as a guaran- tee of their potential to meet the ever-increasing demand for healthcare. We found that 20.7% of the an- nual outpatient and ER visits were served by 14.8% of eye doctors at the EENT Hospital. In contrast, private hospitals contributed to just 7.8% of the total volume, despite employing 16.2% of the registered workforce, in- dicating an obvious disparity in technical efficiency. Similar findings were identified in terms of inpatient ad- missions and surgical volumes among the levels of hos- pitals. The turnover rate at the EENT Hospital was almost two to three times higher than that at other ter- tiary and secondary hospitals. Moreover, the EENT Hos- pital performed 27.4% of all ophthalmic procedures in Shanghai, whereas the average volume at other hospitals was less than a quarter of this number. Collectively, it is not difficult to perceive the high out- put and productivity of the EENT Hospital for providing comprehensive eye care to people in Shanghai. The EENT Hospital, alone, provided nearly one fifth of eye care services in Shanghai. It also treated a huge number of non-local patients. However, this high productivity could be a double-edged sword as it allowed easier ac- cess to high-quality ophthalmic care to more patients, but this overload may overburden the doctors and im- pair the quality of the service they provide [18]. Among the five private hospitals, the surgical volume per doctor was very close to that at the EENT Hospital, which may suggest a much greater efficiency at private hospitals than at most public hospitals. Nevertheless, the difficulty levels of eye care differed markedly among these hospitals. At the EENT Hospital, vitreoretinal sur- gery, one of the most complicated ophthalmic proce- dures, accounted for 10.2% of its surgical volume. A Page 9 of 10 Zhu et al. BMC Health Services Research (2021) 21:1043 Zhu et al. Abbreviations ER: Emergency room; EENT: Eye and Ear, Nose, and Throat; SMILE: Small incision lenticule extraction; FLACS: Femtosecond laser-assisted cataract sur- gery; IOL: Intraocular lens; CTR: Capsular tension ring ER: Emergency room; EENT: Eye and Ear, Nose, and Throat; SMILE: Small incision lenticule extraction; FLACS: Femtosecond laser-assisted cataract sur- gery; IOL: Intraocular lens; CTR: Capsular tension ring Funding Publication of this article was supported by research grants from the National Natural Science Foundation of the People’s Republic of China (81870642, 81970780, 81470613, and 81670835), Shanghai High Myopia Study, the Shanghai Talent Development Fund (201604), the Shanghai Youth Doctor Support Program (2014118), and the Outstanding Youth Medical Talents Program of Shanghai Health and Family Planning Commission (2017YQ011). The funders were not involved in the study design, data collection, data analysis, data interpretation or preparation of the manuscript. Nevertheless, the wait time for a consultation in China was relatively short. In Toronto, patients undergoing diagnostic testing for uveitis waited > 40 days [20]. In China, some patients with serious dis- eases might benefit from the current system, but the medical resources in tertiary hospitals were exhausted, and largely wasted at lower-level hospitals. In the long term, only an effective referral triage process could address the seemingly uneven distribution of medical resources. Availability of data and materials The data are available from the authors upon reasonable request and with permission from the Shanghai Medical Quality Control Management Center. Acknowledgements Not applicable. Acknowledgements Not applicable. Authors’ contributions XJD, YD, WWH, and JHD contributed equally to this work, and are co-first au- thors. XJD, YD, WWH, and JHD conducted the literature search. XJZ, SST, and YL designed the study. WWH, MJC, PJY, HC, HR, and YF collected the data. YD, WWH, JHD, MJC, PJY, HC, HR, and YF conducted the data interpretation. YD, WWH, and JHD prepared the figure and Tables. YD and XJZ wrote the first draft of the manuscript. SST and YL revised the manuscript. All authors have read and approved the manuscript. Consent for publication Not applicable. Consent for publication Not applicable. Conclusion p g The authors declare that they have no competing interests. The authors declare that they have no competing interests. We performed a city-wide questionnaire survey that pro- vides an overview of the eye care services available in Shanghai. Notwithstanding the rapid development of private sectors, public hospitals still provide the bulk of ophthalmic services. In the hierarchic public system, the EENT Hospital provided almost one fifth of eye care ser- vices in Shanghai. The city’s services were largely supple- mented by private hospitals, which help meet the growing medical demands for treating common diseases. However, further optimization of the hierarchic medical system with proper policy guidance is still necessary to standardize and improve the efficiency of current oph- thalmic services. Received: 22 October 2020 Accepted: 17 September 2021 Received: 22 October 2020 Accepted: 17 September 2021 Discussion BMC Health Services Research (2021) 21:1043 The high productivity at a single hospital may be due to a combination of internal and external factors. Owing to its large scale, professional staffing and the most com- prehensive equipment, the EENT Hospital is ranked sec- ond nationally in the field of ophthalmology. These features mean it attracts many patients from neighboring provinces, or further field in China [19]. Another explan- ation may relate to an ineffective referral triage process. Unlike the process of seeing a doctor in an established medical system, such as in the United States, patients in China do not need to obtain a referral from a family doctor and can bypass the primary healthcare system. Patients flocking to large tertiary hospitals, whether ne- cessary or not, forced the passive increase in efficiency at these hospitals. The over-influx of patients with minor ailments, which could be treated in primary or second- ary hospitals, led to the aggravation of the so-called “three long, one short” problem at these large hospitals [1], comprising long registration times, long wait times, long payment queue times, and short visit times, result- ing in the pseudo-proposition of difficult access to health services. Overall, a deficit of ophthalmologists remained in Shanghai, with a density of only 0.49 oph- thalmologists per 10,000 population, far below the values of 2.56 in Greece, 1.93 in Switzerland in 2017, and 0.60 in United States in 2014. Ethics approval and consent to participate Our study was reviewed and deemed exempt from formal ethics approval or consent forms by the Ethics Committee at the EENT Hospital of Fudan University. Supplementary Information The online version contains supplementary material available at https://doi. org/10.1186/s12913-021-07048-1. The online version contains supplementary material available at https://doi. org/10.1186/s12913-021-07048-1. Additional file 1. References Comparing public and private providers: a scoping review of hospital services in Europe. BMC Health Serv Res. 2018; 18(1):141. 15. Aggarwal A, Lewis D, Mason M, Purushotham A, Sullivan R, van der Meulen J. Effect of patient choice and hospital competition on service configuration and technology adoption within cancer surgery: a national, population- based study. Lancet Oncol. 2017;18(11):1445–53. 16. Klein DJ, Brown AD, Detsky AS. Investing wisely in health care capital. JAMA. 2016;316(15):1543–4. 16. Klein DJ, Brown AD, Detsky AS. Investing wisely in health care capital. JAMA. 2016;316(15):1543–4. 17. Zhang X, Beckles GL, Chou CF, Saaddine JB, Wilson MR, Lee PP, et al. Socioeconomic disparity in use of eye care services among US adults with age-related eye diseases: National Health Interview Survey, 2002 and 2008. JAMA Ophthalmol. 2013;131(9):1198–206. 18. Ward NS, Afessa B, Kleinpell R, Tisherman S, Ries M, Howell M, et al. Intensivist/patient ratios in closed ICUs: a statement from the Society of Critical Care Medicine taskforce on ICU staffing. Crit Care Med. 2013;41(2): 638–45. 19. Tang C, Xu J, Zhang M. The choice and preference for public-private health care among urban residents in China: evidence from a discrete choice experiment. BMC Health Serv Res. 2016;16(1):580. 20. Felfeli T, Christakis PG, Bakshi NK, Mandelcorn ED, Kohly RP, Derzko- Dzulynsky LA. Referral characteristics and wait times for uveitis consultation at academic tertiary care centres in Toronto. Can J Ophthalmol. 2018;53(6): 639–45. References 1. Dai J, Wang X, Ayala FJ. Medical informatics and the "three long, one short" problem of large urban hospitals in China. JAMA. 2016;316(3):269–70. 2. Yip W, Fu H, Chen AT, Zhai T, Jian W, Xu R, et al. 10 years of health-care reform in China: progress and gaps in Universal Health Coverage. Lancet (London, England). 2019;394(10204):1192–204. 3. Wang Y, Li X, Zhou M, Luo S, Liang J, Liddell CA, et al. Under-5 mortality in 2851 Chinese counties, 1996–2012: a subnational assessment of achieving MDG 4 goals in China. Lancet (London, England). 2016;387(10015):273–83. 4. Yip WC, Hsiao W, Meng Q, Chen W, Sun X. Realignment of incentives for health-care providers in China. Lancet (London, England). 2010;375(9720): 1120–30. 5. Lancet T. China's health-care reform: an independent evaluation. Lancet (London, England). 2019;394(10204):1113. 6. Meng Q, Liu X, Shi J. Comparing the services and quality of private and public clinics in rural China. Health Policy Plan. 2000;15(4):349–56. Page 10 of 10 Zhu et al. BMC Health Services Research (2021) 21:1043 Zhu et al. BMC Health Services Research (2021) 21:1043 7. Pan J, Zhao H, Wang X, Shi X. Assessing spatial access to public and private hospitals in Sichuan, China: The influence of the private sector on the healthcare geography in China. Soc Sci Med (1982). 2016;170:35–45. 8. Ma X. China's Health Statistics Yearbook 2018. China; 2018. (in Chinese) 9. Zhang JS, Xu L, Wang YX, You QS, Wang JD, Jonas JB. Five-year incidence of age-related cataract and cataract surgery in the adult population of greater Beijing: the Beijing eye study. Ophthalmology. 2011;118(4):711–8. 10. Tang Y, Wang X, Wang J, Huang W, Gao Y, Luo Y, et al. Prevalence of age- related cataract and cataract surgery in a Chinese adult population: the Taizhou eye study. Invest Ophthalmol Vis Sci. 2016;57(3):1193–200. 11. Song P, Du Y, Chan KY, Theodoratou E, Rudan I. The national and subnational prevalence and burden of age-related macular degeneration in China. J Glob Health. 2017;7(2):020703. 12. Xu J, Liu G, Deng G, Li L, Xiong X, Basu K. A comparison of outpatient healthcare expenditures between public and private medical institutions in urban China: an instrumental variable approach. Health Econ. 2015;24(3): 270–9. 13. Eggleston K, Lu M, Li C, Wang J, Yang Z, Zhang J, et al. Comparing public and private hospitals in China: evidence from Guangdong. BMC Health Serv Res. 2010;10:76. 14. Tynkkynen LK, Vrangbaek K. Zhu et al. BMC Health Services Research (2021) 21:1043 Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. published maps and institutional affiliations.
https://openalex.org/W3101744020	https://publikationen.bibliothek.kit.edu/1000123855/87816787	English	null	Refractive displacement of the radio-emission footprint of inclined air showers simulated with CoREAS	European physical journal. C, Particles and fields	2,020	cc-by	11,717	Refractive displacement of the radio-emission footprint of inclined air showers simulated with CoREAS Felix Schlüter1,2,a, Marvin Gottowik3,b, Tim Huege1,4, Julian Rautenberg3 1 Karlsruher Institut für Technologie, Institut für Kernphysik, Karlsruhe, Germany 2 Universidad Nacional de San Martín, Instituto de Tecnologías en Detección y Astropartículas, Buenos Aires, Argentina 3 Bergische Universität Wuppertal, Wuppertal, Germany 4 Vrije Universiteit Brussel, Astrophysical Institute, Brussels, Belgium Felix Schlüter1,2,a, Marvin Gottowik3,b, Tim Huege1,4, Julian Rautenberg3 1 Karlsruher Institut für Technologie, Institut für Kernphysik, Karlsruhe, Germany 2 Universidad Nacional de San Martín, Instituto de Tecnologías en Detección y Astropartículas, Buenos Aires, Argentina 3 Bergische Universität Wuppertal, Wuppertal, Germany 4 Vrije Universiteit Brussel, Astrophysical Institute, Brussels, Belgium Received: 14 May 2020 / Accepted: 7 July 2020 © The Author(s) 2020 Received: 14 May 2020 / Accepted: 7 July 2020 © The Author(s) 2020 1 Introduction . . . . 3 Displacement of the radio-emission footprints . . . . . 4 Interpretation of the displacement as due to refraction 5 Conclusions . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . a e-mail: felix.schlueter@kit.edu (corresponding author) b e-mail: gottowik@uni-wuppertal.de 0123456789().: V,-vol 1 Introduction Abstract The footprint of radio emission from extensive air showers is known to exhibit asymmetries due to the super- position of geomagnetic and charge-excess radiation. For inclined air showers a geometric early-late effect disturbs the signal distribution further. Correcting CoREAS simulations for these asymmetries reveals an additional disturbance in the signal distribution of highly inclined showers in atmospheres with a realistic refractive index proﬁle. This additional appar- ent asymmetry in fact arises from a systematic displacement of the radio-emission footprint with respect to the Monte- Carlo shower impact point on the ground. We ﬁnd a displace- ment of ∼1500 m in the ground plane for showers with a zenith angle of 85◦, illustrating that the effect is relevant in practical applications. A model describing this displacement by refraction in the atmosphere based on Snell’s law yields good agreement with our observations from CoREAS simu- lations. We thus conclude that the displacement is caused by refraction in the atmosphere. Radio detection of inclined air showers is a powerful tech- nique for the detection of ultra-high energy cosmic rays. It has been demonstrated that the detection of these particles is possible with sparse antenna arrays [1]. The radio emis- sion, which originates from the electromagnetic component of an air shower, experiences almost no attenuation while propagating through the atmosphere and hence provides an accurate and precise energy estimator [2]. Combined with a measurement of the muonic shower component, e.g. by a particle detector, measurements of inclined air showers also provide a high mass-composition sensitivity [3], which will be in particular a target of the large-scale radio detector of the upcoming upgrade of the Pierre Auger Observatory [4]. Therefore, inclined air showers have a high relevance and a detailed understanding of the signal distribution of their radio emission is crucial to accurately reconstruct the cosmic-ray properties of interest. The radio signal distribution is affected by a strong asym- metry arising from the superposition of the geomagnetic and charge-excess emission caused by their individual polariza- tion patterns [5]. For inclined showers with a zenith angle larger than 60◦an additional early-late asymmetry becomes relevant [6]. Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . 2 Apparent asymmetry in the signal distribution of air- shower radio emission . . . . . . . . . . . . . Eur. Phys. J. C (2020) 80:643 https://doi.org/10.1140/epjc/s10052-020-8216-z Eur. Phys. J. C (2020) 80:643 https://doi.org/10.1140/epjc/s10052-020-8216-z Regular Article - Experimental Physics a e-mail: felix.schlueter@kit.edu (corresponding author) b e-mail: gottowik@uni-wuppertal.de Contents However, many next generation radio experiments [12,13] aim to cover higher frequencies and a larger band, e.g. 50 to 200 MHz for the proposed GRAND experiment [12]. In Sect. 3.4 we will therefore address the comparability of our results with this frequency band. Fig. 1 Lateral distribution of the radio emission of a 85◦air shower along the positive and negative v × (v × B) axes with respect to the MC impact point. The energy ﬂuence is expected to be symmetric on both axes. This is fulﬁlled for a constant refractive index n (blue lines), independentofitsexactvalue.Iftherefractiveindexchangeswithheight (orange lines), the LDF is not symmetric with respect to the MC shower axis. On closer look, a displacement of the symmetry axis rather than an asymmetry is observed. Figure updated from [7] ≲20%. In inclined air showers the radio emission above the shower axis travels over longer distances between source and observer than below axis. The intensity of the expanding radio emission scales with this geometrical distance. Con- sequently below the shower axis, i.e., early in the shower, observers at ground measure a higher signal intensity than observers late in the shower and thus an early-late asymmetry is imprinted in the radio-emission footprint. A geometrical correction consisting of a “projection into the shower plane” assuming a point source of the radio emission located at the shower maximum Xmax can resolve this asymmetry within 2% [16]. This article is structured as follows: In the following sec- tion we show that the additional apparent asymmetry in the lateral distribution of inclined showers found in [7] can be explained with a displaced radio symmetry center. In Sect. 3 we present a method to determine the symmetry center of the lateral distribution of the radio emission. Using a set of CoREAS showers, we establish a systematic displace- ment of the radio symmetry center with respect to the MC impact point. Furthermore, we investigate differences in the Cherenkov radius for geomagnetic and charge-excess emis- sion. In Sect. 4 we present a model based on Snell’s law that successfully describes the displacement, and we discuss the treatment of the propagation of radio emission in CoREAS. Finally, we draw our conclusions in Sect. 5. In addition to these nowadays well-known asymmetries, a further apparent asymmetry was observed in [7]. Contents In [7] a previously unknown apparent asymmetry in the radio-emission footprint of inclined CoREAS simulations was observed which was presumed to be related to refrac- tion of the radio emission in the atmosphere. In this paper we explain and resolve this apparent asymmetry with a system- atic offset of the radio-emission footprint with respect to the Monte-Carlo (MC) air shower impact point, i.e., the inter- section between the MC shower axis and a ground plane. We express this offset as a displacement of the center of symme- try of the dominating geomagnetic radio emission from the 12 3 Eur. Phys. J. C (2020) 80:643 643 Page 2 of 11 643 Page 2 of 11 Fig. 1 Lateral distribution of the radio emission of a 85◦air shower along the positive and negative v × (v × B) axes with respect to the MC impact point. The energy ﬂuence is expected to be symmetric on both axes. This is fulﬁlled for a constant refractive index n (blue lines), independentofitsexactvalue.Iftherefractiveindexchangeswithheight (orange lines), the LDF is not symmetric with respect to the MC shower axis. On closer look, a displacement of the symmetry axis rather than an asymmetry is observed. Figure updated from [7] Monte-Carlo impact point. We develop a method to deter- mine the radio symmetry center without implying detailed knowledge of the lateral distribution function (LDF) of the radio-emission footprint. Furthermore, we present a model successfully describing the radio symmetry center displace- ment by the refraction of electromagnetic waves propagating through a refractive atmosphere based on Snell’s law. In [8] the inﬂuence of the refractive index on the radio- emission footprint and thus the reconstructed depth of the shower maximum Xmax was studied. An important correla- tion of the reconstructed Xmax with the refractivity at the shower maximum was found. Focusing on vertical showers, effects on signal propagation were, however, neglected. The effect presented here is crucial in order to gain a more detailed understanding of the signal distribution of radio emission from inclined air showers. Implications arise for the modeling and reconstruction of air showers as well as the interpretation of the reconstructed geometries. Our investi- gation mainly refers to the frequency band of the radio emis- sion from 30 to 80 MHz. This frequency band is used by most current-generation large scale radio detector arrays [9–11] as well as the radio detector of the upgrade Pierre Auger Obser- vatory [4]. Contents To further investigate this ﬁnding, we simulated one air shower with a zenith angle of 85◦arriving from South for four differ- ent atmospheric refractivity proﬁles using the CoREAS code [17]. In Fig. 1 the lateral distribution of the radio signal along the v × (v × B) axis is shown in terms of the energy ﬂuence f with the unit eV/m2. In our notation the vector v points in the direction of movement of the shower particles, i.e., the direction of the primary particle and the magnetic ﬁeld vector B points to the north and upwards direction with an inclina- tion of ∼36◦. Thus observers along the positive (negative) v × (v × B) axis are early (late). Along this axis the geo- magnetic and charge-excess contributions are decoupled by their polarisation [2] and after a correction for geometrical early-late effects no asymmetry is expected. If the refrac- tive index is set to a constant value of n ≡1 or n ≡1.00003 3 Displacement of the radio-emission footprints We now analyse the apparent asymmetry introduced by the refractive index proﬁle of the atmosphere in detail using a set of 4308 inclined showers simulated with CORSIKA [18] (pre-release version of the package V7.7000) and its CoREAS extension [17]. The simulations contain proton and iron primaries with energies 18.4 ≤log10 (E/eV) ≤20.2 in log10(E/eV) = 0.2 steps, zenith angles from 65◦to 85◦with a step size of 2.5◦, and 8 equidistantly spaced azimuth angles φ, i.e. coming from geomagnetic East (φ = 0◦), North-East (φ = 45◦), North (φ = 90◦), etc. For each simulation the simulated pulses are located on a star-shaped grid along the v × B and v×(v×B) axes andtheir bisections, i.e. onconcentricrings in the shower plane projected onto the ground. In the following we will refer to the pulses with the same polar angle in the shower plane as “arms” of the star-shaped grid. The spacing is denser close to the shower axis to sample the energy ﬂuence distribution in the 30 to 80 MHz band precisely, and sparser outside, cf. Figs. 1, 2. fgeo = fv×B −cos Φ \| sin Φ\| · fv×(v×B) 2 (1) fce = 1 sin2 Φ · fv×(v×B) (2) (1) (2) where Φ denotes the polar angle of the pulse position in the shower plane with respect to the positive v × B axis count- ing counterclockwise. Equations (1) and (2) are only valid if the pulses of geomagnetic and charge-excess emission arrive at ground almost simultaneously, i.e., without a signiﬁcant phase shift giving rise to a circularly polarized signal com- ponent. Following the analysis presented in [25] we ﬁnd an average time delay of ≲1ns for pulses within and around the Cherenkov ring. Given pulse widths of tens of nanoseconds this delay is negligible independent of the relative strength of the charge-excess emission or the considered frequency band.1 Therefore, Eqs. (1) and (2) are valid within the scope of our analysis. where Φ denotes the polar angle of the pulse position in the shower plane with respect to the positive v × B axis count- ing counterclockwise. Equations (1) and (2) are only valid if the pulses of geomagnetic and charge-excess emission arrive at ground almost simultaneously, i.e., without a signiﬁcant phase shift giving rise to a circularly polarized signal com- ponent. 1 For pulses in the hundreds of MHz or GHz regime this might no be true anymore as such pulses can be considerably shorter. 3.1 Fitting the Cherenkov ring So far there is no established LDF for horizontal air showers that can be used to ﬁt the radio symmetry center. New mod- els are currently being developed, e.g. [16], but the results are still being validated. We therefore use a purely geomet- rical approach that exploits the Cherenkov compression of the radio signal for the estimation. At a certain angle, the Cherenkov angle, a large fraction of the emission, released during the complete shower evolution, arrives at the same time at ground and enhances the signal strength on a ring around the shower axis, the so-called Cherenkov ring. We here estimate the radio symmetry center by a ﬁt of a ring to this feature and deﬁne the center of this ring as our radio symmetry center. This approach also yields an estimator for the radius of the Cherenkov ring. Its radius depends on the geometrical distance to the source region and on the refrac- tivity in this region [8,24]. Since geomagnetic and charge- excess emission were found to originate from slightly differ- ent regions in the atmosphere [2] it is expected that both emission contributions exhibit an independent Cherenkov ring. Hence, in the following we will describe the radio- emission footprint in terms of the geomagnetic energy ﬂu- ence fgeo and charge-excess energy ﬂuence fce separately. Both can be calculated from the energy ﬂuence in the v × B and v × (v × B) polarisation fv×B, fv×(v×B) for a given symmetry center position via (derived from [15]) 2 Apparent asymmetry in the signal distribution of air-shower radio emission It seems that for these simulations the symmetry axis is dis- placed from the MC shower axis in the direction of the pos- itive v × (v × B) axis rather than exhibiting an additional asymmetry. In the next section we will show that this dis- placement of the radio-emission footprint with respect to the MC impact point is eminent in all simulations. Thereby we will illustrate the nature of this displacement which hints towards refraction of the radio emission. In Sect. 4 we will compare this displacement with a model calculation employ- ing refraction of the radio emission in the atmosphere. [22] as high- and low-energy hadronic interaction models and set a thinning level of 5 × 10−6 with optimized weight limi- tation [23]. [22] as high- and low-energy hadronic interaction models and set a thinning level of 5 × 10−6 with optimized weight limi- tation [23]. 3.1 Fitting the Cherenkov ring 2 Apparent asymmetry in the signal distribution of air-shower radio emission For vertical air showers, several LDF models exist which take the interference between geomagnetic and charge-excess emission into account [14,15]. It is assumed that the geo- magnetic and charge-excess radiation, independently, have a rotationally symmetric emission pattern around the shower axis. However, [2] reports relative deviations in the energy ﬂuence of the sub-dominant charge-excess contribution of 123 Page 3 of 11 643 Eur. Phys. J. C (2020) 80:643 (approximately the value of n(hmax) at the shower maximum for an air shower with a zenith angle of 85◦) throughout the atmosphere, the signal distribution in the shower plane is symmetric along the positive and negative v × (v × B) axes with respect to the MC shower axis. The exact value of the refractive index is not important for symmetry, but changes the shape of the LDF. With a changing refractive index fol- lowing the density gradient in the atmosphere, an apparent asymmetry is observed, the LDF is not symmetric anymore with respect to the MC shower axis. This is enhanced when doubling the refractivity n −1 throughout the atmosphere. It seems that for these simulations the symmetry axis is dis- placed from the MC shower axis in the direction of the pos- itive v × (v × B) axis rather than exhibiting an additional asymmetry. In the next section we will show that this dis- placement of the radio-emission footprint with respect to the MC impact point is eminent in all simulations. Thereby we will illustrate the nature of this displacement which hints towards refraction of the radio emission. In Sect. 4 we will compare this displacement with a model calculation employ- ing refraction of the radio emission in the atmosphere. (approximately the value of n(hmax) at the shower maximum for an air shower with a zenith angle of 85◦) throughout the atmosphere, the signal distribution in the shower plane is symmetric along the positive and negative v × (v × B) axes with respect to the MC shower axis. The exact value of the refractive index is not important for symmetry, but changes the shape of the LDF. With a changing refractive index fol- lowing the density gradient in the atmosphere, an apparent asymmetry is observed, the LDF is not symmetric anymore with respect to the MC shower axis. This is enhanced when doubling the refractivity n −1 throughout the atmosphere. 3 Displacement of the radio-emission footprints The impact of the underlying interpolation function and the spacing of interpolated points used to ﬁnd the max- ima on each arm is found to be negligible for the obtained results. The displacement between the radio symmetry cen- ter and MC impact point is estimated to be 125 m in the shower plane. This is a small effect compared to the ﬁtted Cherenkov ring radius of 1198 m, however, due to the high inclination this corresponds to a displacement of 1428 m on ground. The maximal difference between the Cherenkov radii, found on the individual arms, amounts to 40 m. The ﬁt yields an uncertainty of the symmetry center displacement in the shower plane of 21 m. Fig. 2 Comparison of the geomagnetic, charge-excess and total energy ﬂuence (cf. Eqs. 1, 2) for a shower coming from North with a zenith angle of65◦.Thiscorrespondstoa geomagnetic angle withsin α ≈0.19. The charge-excess contribution is multiplied by a factor of 3. Observers are shown on an axis with Φ = 315◦, negative values corresponds to the Φ = 135◦axis. The found maxima are marked by black vertical lines on the LDF. For the geomagnetic energy ﬂuence, a non-physical behavior can be seen close to the axis. This is an artifact of using the MC impact point as the radio symmetry center in the calculation In Fig. 2 an example shower with a small geomagnetic angle α (angle between the magnetic ﬁeld axis and shower axis) is shown. For such showers with a weak geomagnetic emission the interference between geomagnetic and charge- excess emission impacts the position of the maximal ﬂuence and can even completely suppress the Cherenkov ring in the negative v × B half-plane. Note that since the amplitudes of the electric ﬁeld traces are interfering, the resulting asymme- try in energy ﬂuence, e.g., the squared sum of the amplitudes, is accentuated. For the total ﬂuence no ring can be estimated for signals with Φ = 135◦. In contrast, the geomagnetic and charge-excess energy ﬂuences individually exhibit a clear maximum. Note that for Fig. 2 the MC impact point was used for the calculation of the geomagnetic energy ﬂuence which does not describe the true radio symmetry center as we will see later. The LDF described by fce exhibits a broader Cherenkov ring than fgeo which motivates to describe both features independently. 3 Displacement of the radio-emission footprints Following the analysis presented in [25] we ﬁnd an average time delay of ≲1ns for pulses within and around the Cherenkov ring. Given pulse widths of tens of nanoseconds this delay is negligible independent of the relative strength of the charge-excess emission or the considered frequency band.1 Therefore, Eqs. (1) and (2) are valid within the scope of our analysis. The simulation settings match the ambient conditions of the Pierre Auger Observatory [19] which will measure the radio emission from inclined air showers after the upcom- ing deployment of a large-scale radio detector [4]. The ground plane is set to an observation level of 1400 m above sea level. The atmospheric model ﬁts the average condi- tions of Malargüe (location of the Pierre Auger Observa- tory) in October [20]. The refractivity at sea level is set to n0−1 = 3.12×10−4. We use QGSJetII-04 [21] and UrQMD 12 3 3 Eur. Phys. J. C (2020) 80:643 643 Page 4 of 11 643 Page 4 of 11 Fig. 2 Comparison of the geomagnetic, charge-excess and total energy ﬂuence (cf. Eqs. 1, 2) for a shower coming from North with a zenith angle of65◦.Thiscorrespondstoa geomagnetic angle withsin α ≈0.19. The charge-excess contribution is multiplied by a factor of 3. Observers are shown on an axis with Φ = 315◦, negative values corresponds to the Φ = 135◦axis. The found maxima are marked by black vertical lines on the LDF. For the geomagnetic energy ﬂuence, a non-physical behavior can be seen close to the axis. This is an artifact of using the MC impact point as the radio symmetry center in the calculation tion process we employ a least squares method with equal weights for each ring position. The calculation of fgeo and fce following Eqs. (1) and (2) becomes nonphysical for small values of sin Φ, hence the v×B axis is excluded. We note that pulses along this axis will not remain at Φ = 0◦respectively Φ = 180◦for the ﬁtted center position and therefore the above equations could provide reasonable energy ﬂuences using the true radio symmetry center position. However, a varying number of data points during the ﬁt could result in a bias. An example ﬁt to the geomagnetic emission for an event with a zenith angle of 85◦coming from North-West is shown in Fig. 3. 3 Displacement of the radio-emission footprints Thus, in the following we will ﬁt the Cherenkov ring to the individual footprints of the geo- magnetic or charge-excess emission contributions. However, following Eqs. (1) and (2), the calculation of fgeo and fce depends on the location of the radio symmetry center via the polar angle Φ. Thus it is not possible to ﬁnd the locations of the Cherenkov ring on each arm of the star-shaped grid inde- pendently. Therefore, we ﬁt the ring in an iterative process recalculating fgeo and fce in each step of the minimization. The Cherenkov ring is described by the position along each arm of the star-shaped grid, for which the ﬂuence is maximal. These positions are found using a cubic spline interpolation along each arm of the star-shaped grid. For the minimiza- Having two different Cherenkov rings, i.e., the ring in fgeo and fce, encoded in the total signal of fv×B and fv×(v×B) with asimilarstrength,i.e.,forshowerswithasmallsin α,makesit challenging to disentangle them. Hence, in the following we will ﬁt the Cherenkov ring and evaluate a displacement of the emission footprint of the dominating geomagnetic emission and only for showers with a larger geomagnetic angle. For a subset of showers with a small geomagnetic angle we will compare the Cherenkov radii independently for both emis- sion contributions. 3.2 Investigation of the radio symmetry center displacement for showers with a large sin α Bottom: 1D lateral distribution of the geomagnetic energy ﬂuence for each polar angle of the star-shaped grid except for the v × B axis. Colored points denoted the calculated geomagnetic energy ﬂuence for the simulated pulses. Their interpolation is shown by the dashed lines for each arm, the position of the maximum geomagnetic energy ﬂuence is marked by the colored vertical line. The blue line and box denote the ﬁtted radius of the Cherenkov ring and its uncertainty. The axis distances displayed on the x-axis are calculated using the ﬁtted radio symmetry center Fig. 3 Result of the the iterative ﬁt procedure to estimate the radio symmetry center. The geomagnetic energy ﬂuence is normalized to the maximum along each arm. For the ﬁt, only the position of the Cherenkov ring along the arm, and not its signal strength, is used. Top: 2D visual- ization of the ﬁtted Cherenkov ring. For illustration purposes the back- ground constitutes the cubic interpolation of the geomagnetic energy ﬂuence from signals around the Cherenkov ring (signals on or close to the v × B-axis are recovered using the found radio symmetry cen- ter.). In red the ﬁtted Cherenkov ring and its center, the radio symmetry center, are shown. The black star marks the position of the MC impact point, grey dots show the positions of the simulated pulses. The posi- tions of maximal geomagnetic energy ﬂuence found for each arm of the star-shaped grid are denoted by the black diamonds. Bottom: 1D lateral distribution of the geomagnetic energy ﬂuence for each polar angle of the star-shaped grid except for the v × B axis. Colored points denoted the calculated geomagnetic energy ﬂuence for the simulated pulses. Their interpolation is shown by the dashed lines for each arm, the position of the maximum geomagnetic energy ﬂuence is marked by the colored vertical line. The blue line and box denote the ﬁtted radius of the Cherenkov ring and its uncertainty. The axis distances displayed on the x-axis are calculated using the ﬁtted radio symmetry center ﬁrst order dmax scales with the zenith angle, and only in second order with Xmax. For a displaced radio symmetry center, the geometrical distance between this point and the shower maximum is smaller. However the deviation is of the order of ≲1% and therefore negligible for our pur- poses. In Fig. 3.2 Investigation of the radio symmetry center displacement for showers with a large sin α For the ﬁt, only the position of the Cherenkov ring along the arm, and not its signal strength, is used. Top: 2D visual- ization of the ﬁtted Cherenkov ring. For illustration purposes the back- ground constitutes the cubic interpolation of the geomagnetic energy ﬂuence from signals around the Cherenkov ring (signals on or close to the v × B-axis are recovered using the found radio symmetry cen- ter.). In red the ﬁtted Cherenkov ring and its center, the radio symmetry center, are shown. The black star marks the position of the MC impact point, grey dots show the positions of the simulated pulses. The posi- tions of maximal geomagnetic energy ﬂuence found for each arm of the star-shaped grid are denoted by the black diamonds. Bottom: 1D lateral distribution of the geomagnetic energy ﬂuence for each polar angle of the star-shaped grid except for the v × B axis. Colored points denoted the calculated geomagnetic energy ﬂuence for the simulated pulses. Their interpolation is shown by the dashed lines for each arm, the position of the maximum geomagnetic energy ﬂuence is marked by the colored vertical line. The blue line and box denote the ﬁtted radius of the Cherenkov ring and its uncertainty. The axis distances displayed on the x-axis are calculated using the ﬁtted radio symmetry center Fig. 4 Top: displacement of the rad the MC impact point in the ground pl Bottom: displacement of the radio s MC impact point in the shower plan the Cherenkov ring as function of d color-coded cosine of the azimuth (cos φ = 1) West (cos φ = −1) asym ﬁrst order dmax scales with t second order with Xmax. For center, the geometrical distanc shower maximum is smaller. the order of ≲1% and ther poses. In Fig. 4 we summarize between MC impact point and ground plane we ﬁnd a displace the highly inclined showers (t as the spacing of the detector of the Pierre Auger Observato Eur. Phys. J. C (2020) 80:643 Page 5 of 11 643 Eur. Phys. J. C (2020) 80:643 Page 5 of 11 643 Fig. 3 Result of the the iterative ﬁt procedure to estimate the radio symmetry center. The geomagnetic energy ﬂuence is normalized to the maximum along each arm. For the ﬁt, only the position of the Cherenkov ring along the arm, and not its signal strength, is used. 3.2 Investigation of the radio symmetry center displacement for showers with a large sin α Top: 2D visual- ization of the ﬁtted Cherenkov ring. For illustration purposes the back- ground constitutes the cubic interpolation of the geomagnetic energy ﬂuence from signals around the Cherenkov ring (signals on or close to the v × B-axis are recovered using the found radio symmetry cen- ter.). In red the ﬁtted Cherenkov ring and its center, the radio symmetry center, are shown. The black star marks the position of the MC impact point, grey dots show the positions of the simulated pulses. The posi- tions of maximal geomagnetic energy ﬂuence found for each arm of the star-shaped grid are denoted by the black diamonds. Bottom: 1D lateral distribution of the geomagnetic energy ﬂuence for each polar angle of the star-shaped grid except for the v × B axis. Colored points denoted the calculated geomagnetic energy ﬂuence for the simulated pulses. Their interpolation is shown by the dashed lines for each arm, the position of the maximum geomagnetic energy ﬂuence is marked by the colored vertical line. The blue line and box denote the ﬁtted radius of the Cherenkov ring and its uncertainty. The axis distances displayed on the x-axis are calculated using the ﬁtted radio symmetry center shower axis in the direction of Xmax. For inclined show- Fig. 4 Top: displacement of the radio symmetry center with respect to the MC impact point in the ground plane as function of distance to Xmax. Bottom: displacement of the radio symmetry center with respect to the MC impact point in the shower plane normalized to the ﬁtted radius of the Cherenkov ring as function of distance to shower maximum. The color-coded cosine of the azimuth arrival direction illustrates an East (cos φ = 1) West (cos φ = −1) asymmetry ﬁrst order dmax scales with the zenith angle, and only in second order with Xmax. For a displaced radio symmetry center, the geometrical distance between this point and the shower maximum is smaller. However the deviation is of the order of ≲1% and therefore negligible for our pur- poses. In Fig. 4 we summarize the observed displacement between MC impact point and radio symmetry center. In the ground plane we ﬁnd a displacement of more than 1500 m for the highly inclined showers (top). This is of the same order as the spacing of the detector stations for the radio upgrade of the Pierre Auger Observatory [4]. 3.2 Investigation of the radio symmetry center displacement for showers with a large sin α To put the magnitude of the displacement into context we also express the off- set in the shower plane as a fraction of the ﬁtted radius of the Cherenkov ring which can go up to 15% (bottom). The procedure to estimate the radio ergy ﬂuence is normalized to the nly the position of the Cherenkov trength, is used. Top: 2D visual- r illustration purposes the back- Fig. 4 Top: displacement of the radio symmetry center with respect to the MC impact point in the ground plane as function of distance to Xmax. Bottom: displacement of the radio symmetry center with respect to the MC impact point in the shower plane normalized to the ﬁtted radius of the Cherenkov ring as function of distance to shower maximum. The color-coded cosine of the azimuth arrival direction illustrates an East (cos φ = 1) West (cos φ = −1) asymmetry Fig. 4 Top: displacement of the radio symmetry center with respect to the MC impact point in the ground plane as function of distance to Xmax. Bottom: displacement of the radio symmetry center with respect to the MC impact point in the shower plane normalized to the ﬁtted radius of the Cherenkov ring as function of distance to shower maximum. The color-coded cosine of the azimuth arrival direction illustrates an East (cos φ = 1) West (cos φ = −1) asymmetry Fig. 3 Result of the the iterative ﬁt procedure to estimate the radio symmetry center. The geomagnetic energy ﬂuence is normalized to the maximum along each arm. For the ﬁt, only the position of the Cherenkov ring along the arm, and not its signal strength, is used. Top: 2D visual- ization of the ﬁtted Cherenkov ring. For illustration purposes the back- ground constitutes the cubic interpolation of the geomagnetic energy ﬂuence from signals around the Cherenkov ring (signals on or close to the v × B-axis are recovered using the found radio symmetry cen- ter.). In red the ﬁtted Cherenkov ring and its center, the radio symmetry center, are shown. The black star marks the position of the MC impact point, grey dots show the positions of the simulated pulses. The posi- tions of maximal geomagnetic energy ﬂuence found for each arm of the star-shaped grid are denoted by the black diamonds. 3.2 Investigation of the radio symmetry center displacement for showers with a large sin α Forshowerswithalargegeomagneticangle,fulﬁllingsin α > 0.25, we determine the radio symmetry center displacement by a ﬁt to the Cherenkov ring. This condition excludes 120 showers coming from North with a zenith angle below 70◦, which we will discuss separately in Sect. 3.3. In total 4185 ﬁts yield an accurate result and are analyzed in the following. We interpret our results as function of the geometric dis- tance dmax from the MC impact point to Xmax, given by Xground −Xmax = dmax 0 ρ(ℓ) dℓ (3) (3) The atmospheric slant depth measured along the shower axis of the ground plane is denoted by Xground, ρ(ℓ) denotes the atmospheric density at the distance ℓalong the MC 123 123 Eur. Phys. J. C (2020) 80:643 Fig. 3 Result of the the iterative ﬁt procedure to estimate the radio symmetry center. The geomagnetic energy ﬂuence is normalized to the maximum along each arm. For the ﬁt, only the position of the Cherenkov ring along the arm, and not its signal strength, is used. Top: 2D visual- ization of the ﬁtted Cherenkov ring. For illustration purposes the back- ground constitutes the cubic interpolation of the geomagnetic energy ﬂuence from signals around the Cherenkov ring (signals on or close to the v × B-axis are recovered using the found radio symmetry cen- ter.). In red the ﬁtted Cherenkov ring and its center, the radio symmetry center, are shown. The black star marks the position of the MC impact point, grey dots show the positions of the simulated pulses. The posi- tions of maximal geomagnetic energy ﬂuence found for each arm of the star-shaped grid are denoted by the black diamonds. Bottom: 1D lateral distribution of the geomagnetic energy ﬂuence for each polar angle of the star-shaped grid except for the v × B axis. Colored points denoted the calculated geomagnetic energy ﬂuence for the simulated pulses. Their interpolation is shown by the dashed lines for each arm, the position of the maximum geomagnetic energy ﬂuence is marked by the colored vertical line. The blue line and box denote the ﬁtted radius of the Cherenkov ring and its uncertainty. The axis distances displayed on the x-axis are calculated using the ﬁtted radio symmetry center Eur. Phys. J. C (2020) 80:643 Fig. 3 Result of the the iterative ﬁt procedure to estimate the radio symmetry center. The geomagnetic energy ﬂuence is normalized to the maximum along each arm. 3.3 Investigation of the Cherenkov radius in the geomagnetic and charge-excess emission for showers with a small sin α For simulations with a small geomagnetic angle, i.e. sin α < 0.25, the charge-excess contribution is relatively strong. This allows for an independent analysis of the Cherenkov radius from the charge-excess and geomagnetic emission. As mentioned earlier, for those showers it is not possible to accurately determine the symmetry center. Therefore, the ring center is ﬁxed to the MC impact point and just the ring radius is ﬁtted with the method given above. For simulations with a small geomagnetic angle, i.e. sin α < 0.25, the charge-excess contribution is relatively strong. This allows for an independent analysis of the Cherenkov radius from the charge-excess and geomagnetic emission. As mentioned earlier, for those showers it is not possible to accurately determine the symmetry center. Therefore, the ring center is ﬁxed to the MC impact point and just the ring radius is ﬁtted with the method given above. that the found displacement depends on the shower arrival direction. The displacement is strongest for showers com- ing from West and weakest for East (given the inclination of the magnetic ﬁeld of ∼36◦both directions translate to the highest sin α values). This dependency is further inves- tigated in Fig. 5 where we show the position of the ﬁtted radio symmetry center on ground with respect to the MC impact point in the coordinate origin. We observe a displace- ment in the direction from which the shower is incoming, i.e., a displacement towards the shower maximum with a small rotation. The previously described scatter manifests as an East-West asymmetry. As the atmosphere in CoREAS simulations is rotationally symmetric these asymmetries in the displacement cannot be cause by atmospheric proper- ties. An intuitive explanation is provided by the deﬂection of the charged particles in the Earth’s magnetic ﬁeld. Given that the majority of shower particles is negatively charged, one can assume that the shower’s particle bary-center is dis- placed from the MC axis in the direction of the Lorentz Force for a negatively charged particle. Thus, the particle bary-center for showers from west would be displaced below the shower axis, i.e., towards west, while showers from east would be displaced above the shower axis, i.e., also towards west. Hence, this additional displacement already in the particle cascade would add up with the displacement due to refraction and could cause the observed asymmetry. However, further investigations are needed to establish this cause. Already in Fig. 3.2 Investigation of the radio symmetry center displacement for showers with a large sin α 4 we summarize the observed displacement between MC impact point and radio symmetry center. In the ground plane we ﬁnd a displacement of more than 1500 m for the highly inclined showers (top). This is of the same order as the spacing of the detector stations for the radio upgrade of the Pierre Auger Observatory [4]. To put the magnitude of the displacement into context we also express the off- set in the shower plane as a fraction of the ﬁtted radius of the Cherenkov ring which can go up to 15% (bottom). The presented displacement exhibits a pronounced scatter. The cosine of the azimuth angle, denoted by the color, shows shower axis in the direction of Xmax. For inclined show- ers the integral can only be solved numerically as the atmo- spheric curvature needs to be taken into account. In the 12 3 Eur. Phys. J. C (2020) 80:643 643 Page 6 of 11 643 Page 6 of 11 643 Fig. 5 Displacement of the radio symmetry center in the ground plane relative to the MC impact point in the coordinate origin. North is deﬁned as geomagnetic North. The radio symmetry center is always displaced into the incoming direction of the showers. Hence, the clustering of points originates from the binned MC arrival direction of our set of simulations. For the two most inclined bins their MC zenith angle is annotated in the plot Fig. 6 Fitted Cherenkov radius of the geomagnetic and charge-excess emission contributions individually as function of the distance to the shower maximum. Only showers with sin α < 0.25, i.e., coming from North are used here 3.3 Investigation of the Cherenkov radius in the geomagnetic and charge-excess emission for showers with a small sin α Fig. 5 Displacement of the radio symmetry center in the ground plane relative to the MC impact point in the coordinate origin. North is deﬁned as geomagnetic North. The radio symmetry center is always displaced into the incoming direction of the showers. Hence, the clustering of points originates from the binned MC arrival direction of our set of simulations. For the two most inclined bins their MC zenith angle is annotated in the plot Fig. 6 Fitted Cherenkov radius of the geomagnetic and charge-excess emission contributions individually as function of the distance to the shower maximum. 3.2 Investigation of the radio symmetry center displacement for showers with a large sin α Only showers with sin α < 0.25, i.e., coming from North are used here Fig. 6 Fitted Cherenkov radius of the geomagnetic and charge-excess emission contributions individually as function of the distance to the shower maximum. Only showers with sin α < 0.25, i.e., coming from North are used here Fig. 5 Displacement of the radio symmetry center in the ground plane relative to the MC impact point in the coordinate origin. North is deﬁned as geomagnetic North. The radio symmetry center is always displaced into the incoming direction of the showers. Hence, the clustering of points originates from the binned MC arrival direction of our set of simulations. For the two most inclined bins their MC zenith angle is annotated in the plot 3.3 Investigation of the Cherenkov radius in the geomagnetic and charge-excess emission for showers with a small sin α 4.1 Description of refraction using Snell’s law We study the propagation of a single electromagnetic wave through the Earth’s atmosphere described by a curved tra- jectory undergoing refraction according to Snell’s law. For this purpose we assume discrete changes of the refractive index along the edges of imaginary layers throughout the atmosphere. The propagation within a layer with an upper edge height hi is described by a straight uniform expansion with the phase velocity cn = c0/n(hi) given the refractive index as function of the height above sea level n(h). We adopt the refractive index as frequency-independent (i.e., non-dispersive) in the band from 30 to 200 MHz that we consider here. The change of direction between two layers with n1 and n2 is described in terms of the incidence angle (ϑ) from ϑ1 to ϑ2 following Snell’s law 3.4 Comparison of the radio symmetry center displacement for different frequency bands So far we have analysed the radio-emission for frequen- cies in the 30 to 80 MHz band. This band is used by most current-generation radio experiments and in particular also by the upcoming large-scale Auger radio detector [4]. We now determine the displacement of the symmetry center for footprints in the 50 to 200 MHz frequency band. This is the target frequency band of the GRAND experiment [12], cur- rently being in a proposal state, which is also focused on radio measurements of inclined air showers. In Fig. 7 the ﬁtted symmetry center displacement (top) and Cherenkov radius (bottom) are shown for the two frequency bands. Fig. 7 Top: displacement of the radio-emission footprint at ground for two different frequency bands. Bottom: ﬁtted radius of the Cherenkov ring in the geomagnetic emission for the two different frequency bands We ﬁnd no difference in the average behaviour of the sym- metry center displacement between the two frequency bands. The spread is smaller for higher frequencies as the Cherenkov ring is more pronounced and thus easier to ﬁt. On average the ﬁtted Cherenkov radius is ∼5% larger for the higher frequency band. This trend is in agreement with [24] which showed the Cherenkov radius increasing with the frequency for vertical showers. This might be caused by differences in the geometrical distribution of the shower particles which primarily contribute to the radio signal in the considered fre- quency ranges. However, the exact origin of this deviation needs future investigations which are beyond the scope of this paper. model simulating the propagation of a single electromagnetic wave. Furthermore we summarize and validate the treatment of the refractivity in CoREAS and discuss the validity of our model. 3.3 Investigation of the Cherenkov radius in the geomagnetic and charge-excess emission for showers with a small sin α 2a difference in the Cherenkov radii found for the geomagnetic and charge-excess contributions is visi- ble. This is conﬁrmed for the 120 showers with sin α < 0.25 as shown in Fig. 6. As the center is ﬁxed, all showers are ﬁt- ted successfully and no further selection is applied. The esti- mated radius of the Cherenkov ring is systematically larger for the charge-excess contribution than for the geomagnetic emission. Assuming that the radio emission originates from a point source at an altitude h, the Cherenkov angle is given by θCh = arccos(1/n(h)). Hence, one can estimate the height h of the emission region for the given Cherenkov radius. We ﬁnd that the charge-excess originates from higher up in the atmosphere than the geomagnetic emission. This is in agreement with the results found in [2]. In [25] it is reported that the charge-excess induced current peaks deeper in the atmosphere. A possible explanation for this seeming contra- diction is that the coherent emission which arrives at ground does not primarily originate form the location of the highest current due to interference effects. Further studies are needed to clarify this question. A rotational asymmetry in the charge-excess emission was reported in [2] for one example event. Here, we investigate 3 3 Eur. Phys. J. C (2020) 80:643 Page 7 of 11 643 g Fig. 7 Top: displacement of the radio-emission footprint at ground for two different frequency bands. Bottom: ﬁtted radius of the Cherenkov ring in the geomagnetic emission for the two different frequency bands thecharge-excessemissionof120showerswithlowsin α and compare the energy ﬂuence found on the Cherenkov ring for all arms of the star-shaped grid (except of the v × B axis) normalized to the average energy ﬂuence over all arms on an event-to-event basis. We ﬁnd deviations from rotational symmetry with a standard deviation of 9% in energy ﬂuence. We do not ﬁnd a convincing proof of a preferred orienta- tion of this asymmetry, but due to the low event number we can also not exclude one. A random spread could possibly be introduced by air-shower sub-structure originating in the hadronic cascade. We note that indications for a possible ran- dom deviation from rotational symmetry in the charge-excess emission of inclined air showers have been noticed before.2 3.4 Comparison of the radio symmetry center displacement for different frequency bands 3.4 Comparison of the radio symmetry center displacement for different frequency bands 2 Private communication with F. Briechle. 4 Interpretation of the displacement as due to refraction The star illustrates the source, e.g., the shower maximum. The dashed black line illustrates the MC shower axis, it’s intersection with the ground plane deﬁnes the MC impact point. The solid blue line illustrates a curved trajectory with same initial direction as the MC axis, the blue dotted blue line a straight line between source and an observer. The intersection of the curved tra- jectory with the ground deﬁnes the radio symmetry center. The arising curvature and symmetry center displacement are over-emphasized N(h) = N0 ρ(h) ρ(0). (6) N(h) = N0 ρ(h) ρ(0). (6) We employ an atmospheric model with four exponential lay- ers and one linear layer as used in CORSIKA/CoREAS, implementation from [26,27]. The thickness of each layer is set to 1 m assuring a high accuracy of the calculation.3 squares). In the bottom frame we show the absolute resid- uals between CoREAS displacement and refractive model. For their calculation we interpolated the model prediction along the orange squares to match the actual slant depth of the shower maximum of the simulated air showers. The resid- uals show no strong correlation with depth of shower max- imum and increase up to ∼250 m for the most inclined showers. Furthermore, our model predicts a displacement always towards the shower incoming direction. This corre- sponds to a refraction towards the ground, i.e., decreasing angle of incidence, which is given by a radially symmetric atmosphere (cf. Fig. 8). In Fig. 5 this behaviour was also observed for CoREAS simulations as the simulated showers exhibit a radio symmetry center displacement almost entirely in the incoming direction of the shower. As emphasised ear- lier, an East-West asymmetry as seen in CoREAS simula- tions, cf. Figs. 4 and 5, cannot be described by refractivity. g g y To predict the magnitude of a symmetry center displace- ment by refraction, we simulate the propagation of an electro- magneticwavealongabenttrajectorywithaninitialdirection aligned to the MC axis for a shower with a given zenith angle, towards the ground plane. The intersection between the bent trajectory and the ground plane is compared to the inter- section between the ground plane and the MC axis. Given these two points, the symmetry center displacement can be inferred as depicted in Fig. 8. In Fig. 3 Since we account for the curvature of the Earth this does not equal 1 m in change of height between two layers. 4 Interpretation of the displacement as due to refraction We have shown that for simulations in an atmosphere with a varying refractive index the radio symmetry center is system- atically displaced from the MC impact point. In this section we show that this displacement is in agreement with refrac- tion of radio waves in a refractive atmosphere as described by Snell’s law (cf. Eq. (4)). For this purpose we develop a 12 3 3 643 Page 8 of 11 Eur. Phys. J. C (2020) 80:643 643 sin ϑ2 sin ϑ1 = n1 n2 . (4) sin ϑ2 sin ϑ1 = n1 n2 . Fig. 8 Illustration for refraction in the atmosphere. The star illustrates the source, e.g., the shower maximum. The dashed black line illustrates the MC shower axis, it’s intersection with the ground plane deﬁnes the MC impact point. The solid blue line illustrates a curved trajectory with same initial direction as the MC axis, the blue dotted blue line a straight line between source and an observer. The intersection of the curved tra- jectory with the ground deﬁnes the radio symmetry center. The arising curvature and symmetry center displacement are over-emphasized (4) The refraction is calculated in a curved atmosphere. The rela- tionship between the geometrical distance from ground dg and height above ground hg is given for a zenith angle θ, observation level hobs and the Earth’s radiusrearth = 6371km by The refraction is calculated in a curved atmosphere. The rela- tionship between the geometrical distance from ground dg and height above ground hg is given for a zenith angle θ, observation level hobs and the Earth’s radiusrearth = 6371km by d2 g + 2(rearth + hobs)(dg cos θ −hg) −h2 g = 0. (5) (5) By solving this quadratic equation, one can calculate the height above sea level for every given distance to the ground By solving this quadratic equation, one can calculate the height above sea level for every given distance to the ground by h = hg(dg, θ) + hobs. The refractivity N ≡n −1 at a given height is calculated according to the density proﬁle of the given atmospheric model and the given refractivity at sea level (N0), by h = hg(dg, θ) + hobs. The refractivity N ≡n −1 at a given height is calculated according to the density proﬁle of the given atmospheric model and the given refractivity at sea level (N0), Fig. 8 Illustration for refraction in the atmosphere. 4 Interpretation of the displacement as due to refraction 9 the predicted symme- try center displacement along the ground plane is shown as function of the geometrical distance along the MC axis for shower geometries with a zenith angle between 65◦and 85◦. The orange line symbolises the displacement for a source at a ﬁxed slant depth of 750 g/cm2 (e.g., shower maximum, average depth of maximum of our set of simulated showers). For a given slant depth, this distance translates to a zenith angle (top x-axis). Our model predicts a displacement of the order of 1.5 km for the most inclined showers at θ = 85◦. In orange squares the displacement is shown for different slant depths between 620 and 1000 g/cm2 (typical range in our set of simulated showers) along the MC axis for 5 differ- ent zenith angles (θ = 65◦, 75◦, 80◦, 82.5◦, 85◦). The model predictions are compared to the displacements determined from the CoREAS simulation set (colored circles: cf. Sect. 3, Fig. 4). The displacement is reasonably described by our model in terms of the overall magnitude (orange line) as well as the slope as function of the source’s slant depth (orange We veriﬁed that the impact of the atmospheric model, i.e. the density proﬁle, is below 3% between the US Stan- dard Atmosphere after Keilhauer and the Malargüe October atmosphere [20]. Comparing different observer altitudes we ﬁnd no difference for the displacement as function of dmax. As already shown in Fig. 1, the refractivity at sea level has an inﬂuence on the predicted displacement. The yearly ﬂuc- tuations of the air refractivity at the site of the Pierre Auger Observatory amount to 7% [2]. Varying N0 over a range of ±15% we ﬁnd the displacement to scale linearly with N0. 4.2 Refraction and its treatment in CoREAS For the numerical calculation of the radio emission of an extensive air shower for an observer at ground, the refractive 12 3 Page 9 of 11 643 Eur. Phys. J. C (2020) 80:643 Fig. 9 Comparison between model-predicted and CoREAS-derived displacement of the radio symmetry center. The displacement is expressed within the ground plane. The orange line constitutes our model prediction for a source at a ﬁxed slant depth of Xmax = 750 g/cm2 (translation to zenith angle on the top x-axis). The orange squares show the displacement as function of the source slant depth (e.g. Xmax) for each given zenith angle (cf. top x-axis). The colored circles show the displacement determined from the CoREAS simulation set, cf. Fig. 4. The residuals are shown in the bottom frame ﬁnd that the average refractivity and consequently the light propagation time is overestimated along straight trajectories. We stress that the description of the propagation of the radio emission along straight trajectories in CoREAS is not in contradiction with the above-established refraction of the radio emission and the resulting displacement of the radio symmetry center in CoREAS simulations. In fact, the refrac- tion of radio waves is a consequence of the fact that the prop- agation velocity changes with the refractive index cn. It is in fact possible to achieve a displacement of the whole coher- ent signal pattern at ground by an accurate description of the light propagation time along straight trajectories, as we will demonstrate below. Fig. 9 Comparison between model-predicted and CoREAS-derived displacement of the radio symmetry center. The displacement is expressed within the ground plane. The orange line constitutes our model prediction for a source at a ﬁxed slant depth of Xmax = 750 g/cm2 (translation to zenith angle on the top x-axis). The orange squares show the displacement as function of the source slant depth (e.g. Xmax) for each given zenith angle (cf. top x-axis). The colored circles show the displacement determined from the CoREAS simulation set, cf. Fig. 4. The residuals are shown in the bottom frame To verify if the calculation along straight trajectories between source and observer is sufﬁciently accurate to calcu- late the radio emission seen from a full extensive air shower, we determine the geometrical distance and light propagation time following bent and straight trajectories (cf. Fig. 8) for several geometries. 4.2 Refraction and its treatment in CoREAS We simulate the propagation of an elec- tromagnetic wave given incoming direction and atmospheric depth along a bent trajectory towards the ground plane. Once the trajectory intersects with this ground plane the process is stopped and dcurved and tcurved are calculated via a sum of di, tni over all layers. Given the intersection and the initial start- ing point in the atmosphere, a straight trajectory is deﬁned and dstraight and tstraight are calculated for comparison. index has to be taken into account for two processes: ﬁrst, in the generation of the radio emission for each particle; and second, in the the propagation of each electromagnetic wave fromasourcetoanobserver.InCoREAS,theformerisrealis- tically included in the calculation of the radio emission from each particle using the endpoint formalism [17,28,29]. How- ever, the treatment of the propagation is approximated. Since electromagnetic waves in the radio regime do not suffer from any signiﬁcant attenuation effects while propagating through air, this propagation is described entirely by two quantities. First, the geometrical distance (d), that the radio wave passes between source and observer, as the intensity of the emission scales with this distance. And second, the light propagation time (tn) between source and observer which is of crucial importance as it governs the coherence of the signal seen by an observer from the full air shower. In CoREAS, tn is calculated taking into account a refractive index dependent (phase-) velocity of the emission index has to be taken into account for two processes: ﬁrst, in the generation of the radio emission for each particle; and second, in the the propagation of each electromagnetic wave fromasourcetoanobserver.InCoREAS,theformerisrealis- tically included in the calculation of the radio emission from each particle using the endpoint formalism [17,28,29]. How- ever, the treatment of the propagation is approximated. Since electromagnetic waves in the radio regime do not suffer from any signiﬁcant attenuation effects while propagating through air, this propagation is described entirely by two quantities. In Fig. 10 (Top) the geometrical distance is compared between curved and straight trajectories in absolute terms of dcurved −dstraight, given the ambient conditions used for the above introduced simulation set. The comparison is shown as function of the geometrical distance along the straight tra- jectory between source and observer. The source positions are set to be at an atmospheric depth of X = 750 g/cm2 for incoming directions with zenith angles between 65◦and 85◦. 4.2 Refraction and its treatment in CoREAS Figure 10 (bottom) shows σt for different geometries and conﬁgurations of P1 and P2. The timing error σt between two sources which are located on one axis with a zenith angle between 65◦and 85◦and depths of 1000 and 400 g/cm2 is shown by the orange line. This range of atmospheric depths covers the bulk of the radi- ation energy release from the longitudinal development of an extensive air shower [2, Fig. 5]. In the most extreme case, the error in the relative arrival times for a source at the begin- ning of the shower evolution and a source at the end of the shower evolution, estimated using straight tracks, amounts to σt ≲0.1 ns. This is well below the oscillation time of electromagnetic waves in the MHz regime. The blue line in the same ﬁgure demonstrates the errors made for sources lat- erally displaced by a shift of ±655 m above and below the shower axis along an axis perpendicular to the shower axis at a depth of 750 g/cm2. This value was chosen such that it matches the Molière radius expected for a shower with θ = 85◦at Xmax = 750 g/cm2 [30]. The errors due to the straight-line approximation are even much smaller. While it may seem paradoxical on ﬁrst sight that a calcu- lation approximating propagation of electromagnetic waves alongstraighttrackscanyieldrefractiveraybending,wehave shown that the relevant calculation of relative arrival times is described well within the needed accuracy, i.e., is fully adequate for this purpose. We note that, similar to our ﬁnd- ings, it was already found based on analytic calculations in reference [31, cf. Fig 9] that a straight-line approximation is sufﬁcient for the calculation of relative arrival times of radio waves in extensive air showers. Fig. 10 Top: difference in geometrical distance between a source at a depth of X = 750 g/cm2 and an observer at ground level for a straight- track calculation and curved-track calculation for zenith angles from 65◦to 85◦. Bottom: difference in the relative arrival times calculated with curved and straight-track propagation σt = Δtcurved −Δtstraight arising for two source positions and one observer position. Distance to Xmax is calculated using a ﬁxed depth of Xmax = 750 g/cm2 Additionally the refractive ray bending changes the incoming direction of the radio emission. 4.2 Refraction and its treatment in CoREAS We obtain a maximal error of around 4cm for the most inclined geometries with a path distance of ∼150 km. With a relative deviation of less than 1 × 10−6 this approximation is therefore completely suitable. For the light propagation time, the relative difference for two source positions and one observer position between curved and straight trajectories σt = Δtcurved−Δtstraight is of relevance as it governs the coherence of the total signal seen by a given observer. We do not have an analytic description for curved trajectories, however we can employ our model to determine the observer position at ground O(P, ˆθ) for every given source position P and initial direction ˆθ. Hence, to ﬁnd two sources connected with curved trajectories to one observer at ground we have to ﬁnd the initial direction ˆθ2 for a given second source which deﬁnes a trajectory that con- nects this source to an observer given by the ﬁrst source and direction O1(P1, ˆθ1). For this purpose we employ a root- ﬁnding algorithm that solves the following equation for ˆθ2: O2(P2, ˆθ2) −O1(P1, ˆθ1) = 0 (P1, P2, ˆθ1 are ﬁxed). When tn = 1 c observer source n(h(ℓ)) dℓ. (7) (7) Tocalculatebothquantities,CoREASassumesastraightpath between source and observer (cf. Fig. 8: dashed line). This approximation has implications for the geometrical distance between source and observer as a straight line underestimates the real distance along a curved trajectory. For the calculation of the light propagation time an additional implication arises from the fact that the average refractivity along a straight line varies from the refractivity along a curved trajectory. We 12 3 3 Eur. Phys. J. C (2020) 80:643 Page 10 of 11 643 Fig. 10 Top: difference in geometrical distance between a source at a depth of X = 750 g/cm2 and an observer at ground level for a straight- track calculation and curved-track calculation for zenith angles from 65◦to 85◦. Bottom: difference in the relative arrival times calculated with curved and straight-track propagation σt = Δtcurved −Δtstraight arising for two source positions and one observer position. Distance to Xmax is calculated using a ﬁxed depth of Xmax = 750 g/cm2 the correct ˆθ2 is found, i.e., O = O1 = O2, the propagation between P1 or P2 and O is evaluated for curved and straight trajectories and σt is calculated. 4.2 Refraction and its treatment in CoREAS This has impli- cations for the reconstruction of the radio emission with real radio antennas as their response pattern is direction- dependent. We ﬁnd a maximum change of direction of ∼0.14◦, which is in agreement with [32]. This is below current experimental accuracy as well as the change in the incoming direction between early and late observers on the ground plane, estimated as O(1◦) for a 85◦shower. We have also discussed the validity of approximations made in CoREAS and shown that they are adequate to describe refractive effects in air-shower radio simulations. We have found indications that there are secondary effects causing additional scatter in the displacement of the radio symmetry center which is not related to the refractive index of the atmo- sphere or the atmosphere in principle but could be caused by the geomagnetic ﬁeld. comparing/combining results across different detection tech- niques. 9. E. M. Holt., Recent Results of the Auger Engineering Radio Array (AERA). PoS(ICRC2017)492 (2017). https://doi.org/10.22323/1. 301.0492 10. P. Schellart et al., Detecting cosmic rays with the LOFAR radio telescope. Astron. Astrophys. 560, A98 (2013) Acknowledgements We would like to thank our colleagues involved in radio detection within the Pierre Auger Observatory for very fruit- ful discussions. We are grateful to F.G. Schröder and O. Scholten for their valuable comments on our manuscript. Financial support by the BMBF Verbund-forschung Astroteilchenphysik is acknowledged. Felix Schlüter is supported by the Helmholtz International Research School for Astroparticle Physics and Enabling Technologies (HIRSAP) (Grant number HIRS-0009). Simulations for this work were performed on the supercomputer ForHLR at KIT and on the pleiades Cluster at University of Wuppertal. ForHLR is funded by the Ministry of Science, Research and the Arts Baden-Württemberg and the Federal Ministry of Educa- tion and Research. Pleiades is supported by the Deutsche Forschungs- gemeinschaft (DFG). 11. P.A. Bezyazeekov et al., Measurement of cosmic-ray air show- ers with the Tunka Radio Extension (Tunka-Rex). Nucl. Instrum. Methods. A 802, 89–96 (2015) 12. J.Álvarez Muñiz et al., The giant radio array for neutrino detection (GRAND): science and design. Sci. China Phys. Mech. Astron. 63(1), 219501 (2020) 13. T. Huege et al., Ultimate precision in cosmic-ray radio detection— the SKA. EPJ Web Conf. 135, 02003 (2017) 14. A. Nelles et al., A parameterization for the radio emission of air showers as predicted by CoREAS simulations and applied to LOFAR measurements. Astropart. Phys. 60, 13–24 (2015) 15. C. Glaser, S. de Jong, M. Erdmann, J.R. Hörandel, An analytic description of the radio emission of air showers based on its emis- sion mechanisms. Astropart. Phys. 104, 64–77 (2019) Data Availability Statement This manuscript has no associated data or the data will not be deposited. [Authors’ comment: The data are available from the authors upon request.] p y 16. T. Huege, F. Schlüter, L. Brenk. Symmetrizing the sig- nal distribution of radio emission from inclined air showers. PoS(ICRC2019)294 (2019). https://doi.org/10.22323/1.358.0294 Open Access This article is licensed under a Creative Commons Attri- bution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, pro- vide a link to the Creative Commons licence, and indicate if changes were made. comparing/combining results across different detection tech- niques. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indi- cated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permit- ted use, you will need to obtain permission directly from the copy- right holder. To view a copy of this licence, visit http://creativecomm ons.org/licenses/by/4.0/. 17. T. Huege, M. Ludwig, C.W. James, Simulating radio emission from air showers with CoREAS. AIP Conf. Proc. 1535(1), 128 (2013) 18. D. Heck et al. CORSIKA: a Monte Carlo code to simulate extensive air showers. FZKA Report 6019, Forschungszentrum Karlsruhe (1998) 19. The Pierre Auger Collaboration, The Pierre Auger cosmic ray observatory. Nucl. Instrum. Methods A 798, 172–213 (2015) 20. D. Heck, T. Pierog, Extensive air shower simulation with COR- SIKA: a user’s guide (2019) 21. S. Ostapchenko, Monte Carlo treatment of hadronic interactions in enhanced Pomeron scheme: QGSJET-II model. Phys. Rev. D 83, 014018 (2011) 22. M. Bleicher et al., Relativistic hadron-hadron collisions in the ultra- relativistic quantum molecular dynamics model. J. Phys. G 25(9), 1859–1896 (1999) Funded by SCOAP3. 23. M.Kobal,Athinningmethodusingweightlimitationforair-shower simulations. Astropart. Phys. 15, 259–273 (2001) 24. K.D. de Vries, O. Scholten, K. Werner, The air shower maximum probed by cherenkov effects from radio emission. Astropart. Phys. 45, 23–27 (2013) 5 Conclusions These ﬁndings have several implications towards the observation of cosmic rays with the radio detection tech- nique. For the development of reconstruction algorithms, assuming the MC impact point as symmetry center of the radio-emission footprint will disturb its lateral distribution, causing a mismodelling of the signal distribution. In obser- vations the refractive displacement primarily has to be taken into account in the interpretation of the reconstructed shower geometry. Considering hybrid detection and reconstruction, refractive displacement has to be taken into account when We have established that the radio symmetry center is dis- placed with respect to the MC impact point in CoREAS sim- ulations of inclined air showers. This displacement shows no signiﬁcant dependence on the considered frequency band for non-dispersive refractivity. We have developed a model which reproduces this displacement quantitatively, describ- ing it as a result of refraction of the radio waves during prop- agation in an atmosphere with a refractive index gradient. 12 3 Page 11 of 11 643 643 Eur. Phys. J. C (2020) 80:643 643 comparing/combining results across different detection tech- niques. References 25. O. Scholten et al., Measurement of the circular polarization in radio emission from extensive air showers conﬁrms emission mecha- nisms. Phys. Rev. D 94, 103010 (2016) 1. A. Aab et al., Observation of inclined EeV air showers with the radio detector of the Pierre Auger Observatory. JCAP 1810(10), 026 (2018) 26. C. Glaser. Absolute energy calibration of the Pierre Auger Obser- vatory using radio emission of extensive air showers. Ph.D. Thesis, RWTH Aachen (2017) 2. C. Glaser et al., Simulation of radiation energy release in air show- ers. JCAP 1609(09), 024 (2016) 27. A tool package for cosmic-ray and neutrino radio detectors. https:// github.com/nu-radio/radiotools. Revision from 10 Dec 2019 3. E.M. Holt, F.G. Schröder, A. Haungs, Enhancing the cosmic-ray mass sensitivity of air-shower arrays by combining radio and muon detectors. Eur. Phys. J. C 79(5), 371 (2019) 28. M. Ludwig, T. Huege, REAS3: Monte Carlo simulations of radio emission from cosmic ray air showers using an ’end-point’ formal- ism. Astropart. Phys. 34, 438–446 (2011) 4. B.Pont.,ALargeRadioDetectoratthePierreAugerObservatory— Measuring the Properties of Cosmic Rays up to the Highest Ener- gies. PoS(ICRC2019)395, (2019). https://doi.org/10.22323/1.358. 0395 29. C.W. James, H. Falcke, T. Huege, M. Ludwig, General descrip- tion of electromagnetic radiation processes based on instantaneous charge acceleration in ‘endpoints’. Phys. Rev. E 84, 056602 (2011) 5. T. Huege, Radio detection of cosmic ray air showers in the digital era. Phys. Rep. 620, 1–52 (2016) 30. M.T. Dova, L.N. Epele, Analisa G Mariazzi, The effect of atmo- spheric attenuation on inclined cosmic ray air showers. Astropart. Phys. 18, 351–365 (2003) 6. T. Huege, L. Brenk, F. Schlüter, A rotationally symmetric lateral distribution function for radio emission from inclined air showers. EPJ Web Conf. 216, 03009 (2019) 31. K. Werner, O. Scholten, Macroscopic treatment of radio emis- sion from cosmic ray air showers based on shower simulations. Astropart. Phys. 29, 393–411 (2008) 7. M. Gottowik., Measurements of Inclined Air Showers with the Auger Engineering Radio Array at the Pierre Auger Observatory. PoS(ICRC2019)274 (2019). https://doi.org/10.22323/1.358.0274 32. D. Kuempel, K.-H. Kampert, M. Risse, Geometry reconstruction of ﬂuorescence detectors revisited. Astropart. Phys. 30, 167–174 (2008) 8. A. Corstanje et al., The effect of the atmospheric refractive index on the radio signal of extensive air showers. Astropart. Phys. 89, 23–29 (2017) 12 3
https://openalex.org/W2598785105	https://www.biorxiv.org/content/biorxiv/early/2017/01/04/071282.full.pdf	English	null	Canu: scalable and accurate long-read assembly via adaptive<i>k</i>-mer weighting and repeat separation	bioRxiv (Cold Spring Harbor Laboratory)	2,016	cc-by	21,278	. CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint Canu: scalable and accurate long-‐read assembly via adaptive k-‐mer weighting and repeat separation Sergey Koren1, Brian P. Walenz1, Konstantin Berlin2, Jason R. Miller3, Nicholas H. Bergman4, Adam M. Phillippy1† Sergey Koren1, Brian P. Walenz1, Konstantin Berlin2, Jason R. Miller3, Nicholas H. Bergman4, Adam M. Phillippy1† Brian P. Walenz1, Konstantin Berlin2, Jason R. Miller3, Nicholas H. Bergman4, 1 Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA 2 Invincea Labs, Arlington, VA USA 3 J. Craig Venter Institute, Rockville, MD USA 4 National Biodefense Analysis and Countermeasures Center, Frederick, Maryland USA † Corresponding author: adam.phillippy@nih.gov Keywords: de novo assembly, single-molecule sequencing, nanopore sequencing Keywords: de novo assembly, single-molecule sequencing, nanopore sequencing 1 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint Abstract Long-read single-molecule sequencing has revolutionized de novo genome assembly and enabled the automated reconstruction of reference-quality genomes. However, given the relatively high error rates of such technologies, efficient and accurate assembly of large repeats and closely related haplotypes remains challenging. We address these issues with Canu, a successor of Celera Assembler that is specifically designed for noisy single-molecule sequences. Canu introduces support for nanopore sequencing, halves depth-of-coverage requirements, and improves assembly continuity while simultaneously reducing runtime by an order of magnitude on large genomes versus Celera Assembler 8.2. These advances result from new overlapping and assembly algorithms, including an adaptive overlapping strategy based on tf-idf weighted MinHash and a sparse assembly graph construction that avoids collapsing diverged repeats and haplotypes. We demonstrate that Canu can reliably assemble complete microbial genomes and near-complete eukaryotic chromosomes using either PacBio or Oxford Nanopore technologies, and achieves a contig NG50 of greater than 21 Mbp on both human and Drosophila melanogaster PacBio datasets. For assembly structures that cannot be linearly represented, Canu provides graph-based assembly outputs in graphical fragment assembly (GFA) format for analysis or integration with complementary phasing and scaffolding techniques. The combination of such highly resolved assembly graphs with long-range scaffolding information promises the complete and automated assembly of complex genomes. 2 2 . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint Results Canu is a new single-molecule sequence assembler that improves upon and supersedes the now unsupported Celera Assembler (Myers et al. 2000; Miller et al. 2008). Recently, we introduced the MinHash Alignment Process (MHAP) to overcome the computational bottleneck of overlapping noisy, single-molecule sequencing reads (Berlin et al. 2015). Combining this technique with PBcR (Koren et al. 2012) and Celera Assembler, we demonstrated near-complete eukaryotic assemblies from PacBio sequencing alone (Berlin et al. 2015). Building on this work, we developed Canu to (1) integrate our methods into a single, comprehensive assembler, (2) support both PacBio and Oxford Nanopore data, (3) lower runtime and coverage requirements, and (4) improve repeat and haplotype separation. As a result, Canu improves runtime by an order of magnitude for mammalian genomes and outperforms hybrid methods with as little as 20× single-molecule coverage. At higher coverage, reference-quality de novo assemblies are possible, including the complete assembly of euchromatic chromosomes from either PacBio or Nanopore sequencing. In addition, Canu’s improved graph construction algorithm separates closely related repeats and alleles based on a statistical model of read error, which will be important for future work on diploid, polypoloid, and metagenomic assembly. Canu source code and pre-compiled binaries are freely available under a GPLv2 license from https://github.com/marbl/canu. Introduction CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint improve the quality of the single-molecule reads prior to assembly (Chin et al. 2013; Koren et al. 2013). Finally, direct methods attempt to assemble single-molecule reads from a single overlapping step without any prior correction (Li 2016; Tørresen et al. 2016). All three approaches are capable of producing an accurate final assembly. However, our goal is the complete reconstruction of entire genomes, so we focus here on the hierarchical strategy because it has produced the most continuous de novo assemblies to date (Berlin et al. 2015; Chakraborty et al. 2016). Introduction The goal of genome assembly is to reconstruct a complete genome from many comparatively short sequencing reads. Overlapping reads that originate from the same region of the genome can be joined together to form contigs, but genomic repeats longer than the overlap length lead to ambiguous reconstructions and fragment the assembly (Phillippy et al. 2008; Nagarajan and Pop 2009). There are two strategies for overcoming this fundamental limitation— increasing the effective read length, and separating non-exact repeats based on copy-specific variations. Recently, single-molecule sequencing has revolutionized assembly by producing reads longer than 10 kbp (Gordon et al. 2016), which has significantly reduced the number of unresolvable repeats (Koren et al. 2012) and enabled the complete assembly of microbial genomes (Chin et al. 2013; Koren et al. 2013; Koren and Phillippy 2014). These long reads also aid assembly phasing (Chin et al. 2016), where the conserved alleles in a diploid, polyploid, or meta-genome can be thought of as a special kind of repeat. However, in contrast to improved read length, single-molecule sequencing is less accurate than past technologies (Eid et al. 2009; Schneider and Dekker 2012), requiring sensitive alignment methods and limiting the discrimination of divergent alleles and non-exact repeats. Nevertheless, PacBio single-molecule real-time (SMRT) sequencing exhibits a largely unbiased and random error model (Ross et al. 2013), enabling assemblies that exceed short-read data both in terms of quality and continuity (Chin et al. 2013; Koren et al. 2013). Oxford Nanopore strand sequencing can also produce highly continuous assemblies, but current biases in base calling prohibit an accurate consensus sequence without the addition of complementary data (Loman et al. 2015). The increased read length and error rate of single-molecule sequencing has challenged genome assembly programs originally designed for shorter, highly accurate reads. Several new approaches have been developed to address this, roughly categorized as hybrid, hierarchical, or direct. See (Koren and Phillippy 2014) for a review. Hybrid methods use single-molecule reads to reconstruct the long-range structure of the genome, but rely on complementary short reads for accurate base calls (Koren et al. 2012; Hackl et al. 2014; Lee et al. 2014; Salmela and Rivals 2014; Antipov et al. 2016; Ye et al. 2016). Hierarchical methods do not require a secondary technology and instead use multiple rounds of read overlapping (alignment) and correction to 3 . Architecture To improve usability and performance on single-molecule sequence data, Canu introduces several novel features including computational resource discovery, adaptive k-mer weighting, automated error rate estimation, sparse graph construction, and graphical fragment assembly (GFA) (Li 2016) outputs. The Canu pipeline consists of three stages—correction, 4 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint trimming, and assembly (Figure 1)—each of which can run independently or in series (e.g. only read correction, or assembly without correction, etc.). When running in a parallel environment, Canu will auto-detect available resources and configure itself to maximize resource utilization. It is currently the most efficient single-molecule read assembler available for large genomes, requiring approximately 20,000 CPU hours to assemble a human genome, compared to ~60,000 required for Falcon (Chin et al. 2016) and >250,000 required for Celera Assembler v8.2 (Berlin et al. 2015). In addition to these runtime improvements, the resulting assemblies are significantly more continuous than prior versions. contig sequences assembly graph read layouts Raw Reads generate corrected read consensus choose overlaps for correction global scores estimate corrected read lengths read IDs to correct corrected reads Build read and overlap databases output reads trim reads split reads trimmed reads detect errors in reads recompute overlap alignments errors in reads adjusted error rates construct contigs (bogart) generate contig consensus generate outputs Build read and overlap databases Build read and overlap databases gkpStore ovlStore ovlStore ovlStore tigStore gkpStore gkpStore trim reads Correct Trim Assemble Raw Reads generate corrected read consensus choose overlaps for correction global scores estimate corrected read lengths read IDs to correct corrected reads Build read and overlap databases gkpStore ovlStore Correct Figure 1. A full Canu run includes three stages: correction (green), trimming (red), and assembly (purple). Canu stages share an interface for binary on-disk stores (databases) as well as parallel store construction. Architecture In all stages, the first step constructs an indexed store of input sequences, generates a k-mer histogram, constructs an indexed store of all-vs-all overlaps, and collates summary statistics. The correction stage (green) selects the best overlaps to use for correction, estimates corrected read lengths, and generates corrected reads. The trimming stage (red) identifies unsupported regions in the input and trims or splits reads to their longest supported range. The assembly stage (purple) makes a final pass to identify sequencing errors;; constructs the best overlap graph;; and outputs contigs, an assembly graph, and summary statistics. Correct Assemble Adaptive MinHash k-‐mer weighting Adaptive MinHash k-‐mer weighting Optimal handling of repeats is a challenge, because in addition to fragmenting assemblies, repeats also cause computational bottlenecks during overlapping. Read overlapping typically proceeds in two stages, first building a list of read pairs that share some similarity and Optimal handling of repeats is a challenge, because in addition to fragmenting 5 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint then performing a more direct comparison of those read pairs (e.g. dynamic programming) (Sutton et al. 1995). Candidate overlaps are typically found in the first stage by identifying shared k-mers (length k substrings) between all pairs of reads. However, repeats reduce the entropy of the k-mer distribution compared to random sequence, and the frequent occurrence of some k-mers significantly increases the number of candidate overlaps that must be processed by the more expensive second stage. A common solution is to mask low-complexity sequence or ignore highly repetitive k-mers during indexing (Ning et al. 2001), as is done by many assemblers including Celera Assembler (Myers et al. 2000), Falcon (Chin et al. 2016), and Miniasm (Li 2016). However, depending on how many repeating k-mers are ignored, some fraction of correct overlaps will not be detected. Canu takes a more resilient approach to handling repeats that probabilistically reduces, but does not eliminate, the chance a repetitive k-mer will be selected for overlapping. This weighting is achieved via a MinHash overlapping strategy. Adaptive MinHash k-‐mer weighting It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint uninformative, repetitive overlaps that are identified during sketch comparison, significantly improving both runtime and memory usage. Importantly, this is achieved via a probabilistic process so no repeat masking is required and true overlaps between repetitive reads will still be recovered. Alternative weighting schemes are also possible with this technique (e.g. to increase the probability of selecting haplotype-specific k-mers), but we focus our evaluation on the tf-idf statistic. We evaluated tf-idf weighting on a Bacillus anthracis genome sequenced with the Oxford Nanopore MinION (Supplementary Note 1–2). The B. anthracis Sterne strain makes a useful test because it possesses a single plasmid often present in multiple copies relative to the main chromosome. In this case, the pXO1 plasmid presented at approximately 6-fold higher coverage than the chromosome (487× vs. 76×). This variable sequencing depth challenges traditional k- mer filtering strategies based on a fixed, all-or-nothing threshold. Additionally, it is critically important to recover such plasmids during sequencing, because increased copy number has been previously associated with virulence in other species like Yersinia pestis (Wang et al. 2016). As expected, MHAP overlap sensitivity for the plasmid is low (26%) when repetitive k-mers are filtered via a fixed threshold. Similarly low sensitivity is seen from Minimap (Li 2016) and DALIGNER (Myers 2014)—17% and 60%, respectively—which both employ a k-mer count threshold by default (Supplementary Table S1). Manually increasing this threshold to include plasmid k-mers improves Minimap and DALIGNER sensitivity to 94% and 76%, respectively. However, Minimap suffers a drop in positive predictive value (PPV), reporting more false, repeat-induced overlaps. DALIGNER performs a dynamic programing check to confirm all candidate overlaps, so its PPV remains high, but it suffers both a memory (1.6-fold) and runtime (2-fold) penalty. In contrast, Canu’s adaptive tf-idf weighting scheme requires no parameter adjustment and achieves 89% sensitivity and maintains high PPV (99.5%) with no added runtime or memory penalty. Adaptive MinHash k-‐mer weighting Rather than comparing individual k- mers to identify potential read overlaps, Canu uses the previously described MinHash Alignment Process (MHAP) to compare compressed sketches of entire reads (Berlin et al. 2015). Because each MinHash sketch contains a fixed-size subset of k-mers selected from a read, the probability of including particular k-mers in a sketch can be adjusted. For instance, a repetitive k-mer occurring many times throughout the genome should have a reduced weight, because it carries relatively little information regarding the origin of the read. In contrast, a relatively unique k-mer occurring multiple times in a single read should have an increased weight, because it represents a larger fraction of the read’s length. The combination of these terms represents the relative importance of a k-mer, and in natural language processing this is known as a tf-idf weight (term frequency, inverse document frequency). Application of tf-idf weighting to MinHash sketches is straightforward (Chum et al. 2008). Applied to the read overlapping problem, the weighting is a multiplicative combination of the number of occurrences of a k-mer inside a read (the document) and the overall rarity of the k- mer among all reads (the corpus). For document similarity, the intuition is that a rare word that occurs multiple times in a single document is a good candidate to identify similar documents. For read overlapping, this statistic has the desirable property that repetitive k-mers receive low weights. By reducing the occurrence of repetitive k-mers within sketches, the frequency distribution of indexed k-mers becomes more uniform. This reduces the number of 6 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. Best overlap graph Canu uses a variant of the greedy “best overlap graph” (BOG) algorithm from (Miller et al. 2008) for constructing a sparse overlap graph. Loading the full overlap graph into memory, as required by string graph formulations (Myers 2005), can be costly for large, complex genomes. In contrast, the greedy algorithm loads only the “best” (longest) overlaps for each read end into 7 7 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint memory. This greedy approach is optimal when the read length is sufficiently long (Bresler et al. 2013), and a best overlap graph can be built using just 64 GB of memory for a mammalian genome. However, the greedy algorithm can be misled by repeats that are longer than the overlap length and is therefore prone to mis-assemblies. Canu’s new “Bogart” algorithm addresses this problem by statistically filtering repeat-induced overlaps and retrospectively inspecting the graph for potential errors. In the original BOG method, the best overlaps were selected from a pool of all overlaps below a user-specified error rate threshold, where the overlap error rate is defined as the edit distance divided by the length of the overlap alignment. Thus, this threshold must be set low enough that repeats do not result in false overlaps, yet high enough to account for sequencing error and detect true overlaps. In the new Bogart method, the optimal overlap error rate parameter is automatically estimated from the data, both globally and locally. However, this presents a challenge for raw single-molecule data, which has a sequencing error rate between 10–20% that blurs the distinction between noise and repeat-induced overlaps. Therefore, Canu performs multiple rounds of read and overlap error correction prior to graph construction. After these corrections, the residual read error is estimated from the distribution of all longest overlaps. Best overlap graph This full overlap set is then filtered to include only those overlaps within some tolerance of the global median error rate (Figure 2a), and the longest overlaps are recomputed using only this subset. Compared to prior versions of BOG that used a 5% default overlap error rate, Bogart will typically discover an overlap error rate below 2% for corrected single-molecule data. This low threshold effectively removes most false overlaps, allowing the greedy method to construct a clean best overlap graph. From this graph, initial contigs are constructed from the maximal non- branching paths. To evaluate this repeat separation, we compared Canu, Falcon, and Miniasm on a simulated dataset containing two repeat copies with known divergence varying from 0% to 15% and without any spanning reads (Supplementary Note 3). Canu was able to resolve the repeat when the divergence between copies was 3% or higher, without any manual parameter tuning (Supplementary Table S2). In contrast, Falcon could only resolve the repeat at 5%, after it had diverged beyond the default overlap error rate used for corrected reads. Because it lacks a correction step, Miniasm could not resolve the repeat until 13% divergence, higher than the 8 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint simulated sequencing error rate. This observation may explain why Miniasm is less continuous than Canu and Falcon assemblies on large genomes. Figure 2. An illustration of overlap error rate estimation, repeat identification, and splitting. A) A histogram of all best edge error rates with the auto- selected threshold shown as a dashed line for the D. melanogaster PacBio dataset. All overlaps up to 4% error were computed. However, the modal error rate is 0.25% (0.25% median, 0.15% MAD) and Canu chose to use only overlaps below 1.6% error for graph construction on this dataset. Best overlap graph C) The contig is shown as a black line with arrows on both sides, indicating Bogart extends a path in both the 5’ and 3’ directions until encountering no overlaps or a read that is already incorporated in another contig. Repeat regions annotated by conflicting reads are shown above the contig. The reads align to part of the contig (the repeat) but indicate a different boundary sequence. A single read (blue line) spans the full repeat region, indicating the contig reconstruction is correct. D) Repeat regions annotated by conflicting reads as before. In this case, no single read spans the full repeat region, and the initial contig was built using the overlap between two blue reads. The contig is split if the overlap between the two blue reads is not significantly better than the overlap from either blue read to the conflicting red read. making an assumption of uniform read error across the assembly. C) The contig is shown as a black line with arrows on both sides, indicating Bogart extends a path in both the 5’ and 3’ directions until encountering no overlaps or a read that is already incorporated in another contig. Repeat regions annotated by conflicting reads are shown above the contig. The reads align to part of the contig (the repeat) but indicate a different boundary sequence. A single read (blue line) spans the full repeat region, indicating the contig reconstruction is correct. D) Repeat regions annotated by conflicting reads as before. In this case, no single read spans the full repeat region, and the initial contig was built using the overlap between two blue reads. The contig is split if the overlap between the two blue reads is not significantly better than the overlap from either blue read to the conflicting red read. Despite careful correction and overlap filtering, exact or near exact repeats within the error rate tolerance can still add false edges to the graph, resulting in potential mis-assemblies that incorrectly join distant parts of the genome. To guard against this, each initial contig is inspected to identify and correct potential errors. First, the expected overlap error rate for each position of the contig is locally computed using the best overlaps (Figure 2b). Next, all non-best overlaps to reads outside the contig within some deviation of the expected error rate are collected. Best overlap graph B) The dashed line shows the global error rate threshold (1.6%), and the profile shows the locally computed error rate for the largest contig in this assembly. Only overlaps consistent with this local error rate are considered as potential alternate paths when supplementing the initial best overlap graph. By adjusting the error rate for each contig, Canu can separate diverged repeats without making an assumption of uniform read error across the assembly. C) The contig is shown as a black line with arrows on both sides, indicating Bogart extends a path in both the 5’ and 3’ directions until encountering no overlaps or a read that is already incorporated in another contig. Repeat regions annotated by conflicting reads are shown above the contig. The reads align to part of the contig (the repeat) but indicate a different boundary sequence. A single read (blue line) spans the full repeat region, indicating the contig reconstruction is correct. D) Repeat regions annotated by conflicting reads as before. In this case, no single read spans the full repeat region, and the initial contig was built using the overlap between two blue reads. The contig is split if the overlap between the two blue reads is not significantly better than the overlap from either blue read to the conflicting red read. Figure 2. An illustration of overlap error rate estimation, repeat identification, and splitting. A) A histogram of all best edge error rates with the auto- selected threshold shown as a dashed line for the D. melanogaster PacBio dataset. All overlaps up to 4% error were computed. However, the modal error rate is 0.25% (0.25% median, 0.15% MAD) and Canu chose to use only overlaps below 1.6% error for graph construction on this dataset. B) The dashed line shows the global error rate threshold (1.6%), and the profile shows the locally computed error rate for the largest contig in this assembly. Only overlaps consistent with this local error rate are considered as potential alternate paths when supplementing the initial best overlap graph. By adjusting the error rate for each contig, Canu can separate diverged repeats without making an assumption of uniform read error across the assembly. Best overlap graph This excludes sufficiently diverged repeats and haplotypes, while retaining overlaps that are compatible with the local error profile. These overlaps are used to annotate potential alternative branches within the contig and flagged for further inspection. If a branching region is spanned by at least one read (Figure 2c) (Ukkonen 1992) or there is no alternate overlap of similar quality (Figure 2d), it is confirmed as correct. Otherwise, the region is split into at least three new contigs and labeled as an unresolved repeat. 9 . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint 2 3 X Y 4 X X 2L 3L 2L 2L 2L 3R 2R 3R 4 X X X A) B) Chromosome 2L Histone Gene Cluster TE Repeats Centromere Figure 3: Canu GFA output localizes complex repeat regions, allowing for improved scaffolding. A) Bandage (Wick et al. 2015) plot of D. melanogaster compared to the karyotype (Stevens 1912;; Metz 1914) from FlyBase (Attrill et al. 2016). Nodes are contigs sized by length and edges indicate unused overlaps between contigs. The largest contigs are colored randomly and labeled with their chromosome based on alignment to the reference. B) The callout shows chromosome 2L from positions 3.07 Mbp to 23.12 Mbp, redrawn with the centromere at the top (indicated by a filled circle). Unique contigs are shaded black while repeat contigs are shaded red. While the 2L chromosome scaffold is composed of 10 individual contigs, they are all linked in the output graph. Best overlap graph Nodes are contigs sized by length and edges indicate unused overlaps between contigs. The largest contigs are colored randomly and labeled with their chromosome based on alignment to the reference. B) The callout shows chromosome 2L from positions 3.07 Mbp to 23.12 Mbp, redrawn with the centromere at the top (indicated by a filled circle). Unique contigs are shaded black while repeat contigs are shaded red. While the 2L chromosome scaffold is composed of 10 individual contigs, they are all linked in the output graph. The two red regions correspond to reference gaps at positions 2L:21,485,538, which consists of 100–200 copies of the histone gene cluster spanning over 500 kbp and 2L:22,420,241 which is bordered by several TE repeats (Hoskins et al. 2015). The break in the bottom left of chromosome 2L could not be confidently identified but is next to a feature labeled “FlyBase transposable element” so it is likely a transposable element insertion site. Even though Canu is unable to fully resolve these large repeat arrays, the graph indicates large-scale continuity across chromosome 2L and could enable resolution with secondary technologies. Figure 3: Canu GFA output localizes complex repeat regions, allowing for improved scaffolding. A) Bandage (Wick et al. 2015) plot of D. melanogaster compared to the karyotype (Stevens 1912;; Metz 1914) from FlyBase (Attrill et al. 2016). Nodes are contigs sized by length and edges indicate unused overlaps between contigs. The largest contigs are colored randomly and labeled with their chromosome based on alignment to the reference. B) The callout shows chromosome 2L from positions 3.07 Mbp to 23.12 Mbp, redrawn with the centromere at the top (indicated by a filled circle). Unique contigs are shaded black while repeat contigs are shaded red. While the 2L chromosome scaffold is composed of 10 individual contigs, they are all linked in the output graph. The two red regions correspond to reference gaps at positions 2L:21,485,538, which consists of 100–200 copies of the histone gene cluster spanning over 500 kbp and 2L:22,420,241 which is bordered by several TE repeats (Hoskins et al. 2015). The break in the bottom left of chromosome 2L could not be confidently identified but is next to a feature labeled “FlyBase transposable element” so it is likely a transposable element insertion site. Best overlap graph The two red regions correspond to reference gaps at positions 2L:21,485,538, which consists of 100–200 copies of the histone gene cluster spanning over 500 kbp and 2L:22,420,241 which is bordered by several TE repeats (Hoskins et al. 2015). The break in the bottom left of chromosome 2L could not be confidently identified but is next to a feature labeled “FlyBase transposable element” so it is likely a transposable element insertion site. Even though Canu is unable to fully resolve these large repeat arrays, the graph indicates large-scale continuity across chromosome 2L and could enable resolution with secondary technologies. 2 3 X Y 4 X X 2L 3L 2L 2L 2L 3R 2R 3R 4 X X X A) B) Chromosome 2L Histone Gene Cluster TE Repeats Centromere A) B) anu GFA output localizes complex repeat regions, allowing for improved scaffolding Figure 3: Canu GFA output localizes complex repeat regions, allowing for improved scaffolding. A) Bandage (Wick et al. 2015) plot of D. melanogaster compared to the karyotype (Stevens 1912;; Metz 1914) from FlyBase (Attrill et al. 2016). Nodes are contigs sized by length and edges indicate unused overlaps between contigs. The largest contigs are colored randomly and labeled with their chromosome based on alignment to the reference. B) The callout shows chromosome 2L from positions 3.07 Mbp to 23.12 Mbp, redrawn with the centromere at the top (indicated by a filled circle). Unique contigs are shaded black while repeat contigs are shaded red. While the 2L chromosome scaffold is composed of 10 individual contigs, they are all linked in the output graph. The two red regions correspond to reference gaps at positions 2L:21,485,538, which consists of 100–200 copies of the histone gene cluster spanning over 500 kbp and 2L:22,420,241 which is bordered by several TE repeats (Hoskins et al. 2015). The break in the bottom left of chromosome 2L could not be confidently identified but is next to a feature labeled “FlyBase transposable element” so it is likely a transposable element insertion site. Even though Canu is unable to fully resolve these large repeat arrays, the graph indicates large-scale continuity across chromosome 2L and could enable resolution with secondary technologies. Figure 3: Canu GFA output localizes complex repeat regions, allowing for improved scaffolding. A) Bandage (Wick et al. 2015) plot of D. melanogaster compared to the karyotype (Stevens 1912;; Metz 1914) from FlyBase (Attrill et al. 2016). Best overlap graph Even though Canu is unable to fully resolve these large repeat arrays, the graph indicates large-scale continuity across chromosome 2L and could enable resolution with secondary technologies. After construction and validation, Canu provides a representation of the final assembly graph in the Graphical Fragment Assembly (GFA) format (Li 2016). This representation is equivalent to a sparse read overlap graph, simplified to remove unambiguous paths and contained reads. Figure 3 shows the Canu assembly graph for Drosophila melanogaster sequenced using PacBio. Some chromosome arms are assembled into single contigs, but the graph reveals the structure of the more complex, unresolved repeats in the assembly. For 10 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint example, chromosome 2L is assembled as a single component in the graph, but is broken towards the end due to a large array of transposable elements and the histone gene cluster, which spans over 500 kbp (Hoskins et al. 2015). These elements also correspond to unfinished gaps in the D. melanogaster reference. Canu’s graphical output localizes this complex structure to a specific chromosome arm and location. However, the size of the repeats precludes complete assembly. Combining the Canu assembly graph with supplementary long-range information, such as from optical (Hastie et al. 2013) or chromatin contact mapping (Burton et al. 2013; Kaplan and Dekker 2013), could help identify the correct path and resolve such structures. Low-‐coverage hierarchical assembly The ideal assembly corresponds to the green reference line. The commonly used NG50 metric corresponds to the vertical dashed line. Canu quickly gains continuity with increasing coverage, approaching the limit with 50× PacBio on this genome. In contrast, while making a large gain from Illumina-only to 10× PacBio, SPAdes continuity plateaus by 30×, and the Canu 20× assembly is comparable to the hybrid SPAdes assembly using 150× PacBio. Low-‐coverage hierarchical assembly It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint Figure 4: A comparison of A. thaliana assembly continuity for Canu and SPAdes. Each set of contigs is sorted from longest to shortest and plotted versus a cumulative percentage of the genome covered. Assemblies with larger contigs appear in the top of the plot. The ideal assembly corresponds to the green reference line. The commonly used NG50 metric corresponds to the vertical dashed line. Canu quickly gains continuity with increasing coverage, approaching the limit with 50× PacBio on this genome. In contrast, while making a large gain from Illumina-only to 10× PacBio, SPAdes continuity plateaus by 30×, and the Canu 20× assembly is comparable to the hybrid SPAdes assembly using 150× PacBio. 10 Mbp 5 Mbp 1 Mbp 500 kbp 100 kbp 50 kbp 10 kbp NG0 NG20 NG40 NG60 NG80 NG100 Arabidopsis thaliana Ler-0 PacBio P5-C3 Reference Canu 150x Canu 50x Canu 20x SPAdes ILMN+150x SPAdes ILMN+10x SPAdes ILMN Canu 10x NG fraction Contig size SPAdes ILMN+30x Arabidopsis thaliana Ler-0 PacBio P5-C3 NG fraction A comparison of A. thaliana assembly continuity for Canu and SPAdes. Each set of Figure 4: A comparison of A. thaliana assembly continuity for Canu and SPAdes. Each set of contigs is sorted from longest to shortest and plotted versus a cumulative percentage of the genome covered. Assemblies with larger contigs appear in the top of the plot. The ideal assembly corresponds to Figure 4: A comparison of A. thaliana assembly continuity for Canu and SPAdes. Each set of contigs is sorted from longest to shortest and plotted versus a cumulative percentage of the genome covered. Assemblies with larger contigs appear in the top of the plot. The ideal assembly corresponds to the green reference line. The commonly used NG50 metric corresponds to the vertical dashed line. Canu quickly gains continuity with increasing coverage, approaching the limit with 50× PacBio on this genome. In contrast, while making a large gain from Illumina-only to 10× PacBio, SPAdes continuity plateaus by 30×, and the Canu 20× assembly is comparable to the hybrid SPAdes assembly using 150× PacBio. g p y y contigs is sorted from longest to shortest and plotted versus a cumulative percentage of the genome covered. Assemblies with larger contigs appear in the top of the plot. Low-‐coverage hierarchical assembly Canu substantially lowers the coverage requirements for single-molecule de novo assembly. Previously, at least 50× coverage was recommended for hierarchical assembly methods (Berlin et al. 2015; Chakraborty et al. 2016). However, as sequencing lengths and algorithms have improved, so have the minimum input requirements. To quantify performance and determine when a hybrid method may be preferred, we randomly subsampled 10–150× of PacBio P5-C3 coverage from Arabidopsis thaliana Ler-0 (Kim et al. 2014) and compared Canu assemblies to both Illumina-only and hybrid assemblies using SPAdes (Antipov et al. 2016). At 20× single-molecule coverage, the Canu assembly is more continuous than the hybrid SPAdes assembly of 20× PacBio combined with 100× Illumina. Although making efficient use of low coverage PacBio data, the hybrid method plateaus after 30×, and the continuity of the Canu 20× assembly is comparable to the best hybrid assembly given 150× of PacBio (Figure 4, Supplementary Note 4, Supplementary Table S3, Supplementary Figure S1). In contrast, Canu continues to improve with increasing PacBio coverage, reaching its maximum assembly continuity around 50×. The amount of improvement is a function of the repeat content and sequence length. PacBio sequence lengths follow a log-normal distribution (Ono et al. 2013), and additional coverage increases the probability of spanning a long repeat. Thus, we would expect continued improvement with higher coverage for larger, more complex genomes. Currently, we recommend the hierarchical method whenever single-molecule coverage exceeds 20×. However, consensus accuracy from low coverage single-molecule data is limited, and polishing (Walker et al. 2014) with short reads is recommended after assembly (Supplementary Table S3). 11 . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. PacBio sequence assembly We assembled bacterial and eukaryotic genomes recently released (Kim et al. 2014) and available from PacBio DevNet (https://github.com/PacificBiosciences/DevNet/wiki/Datasets). Table 1 shows that Canu produces the most continuous assembly on three of the four eukaryotic genomes tested, while maintaining high accuracy (Supplementary Figure S2–S6). In the one case that Miniasm produces a higher NG50 (Caenorhabditis elegans), both Falcon and Miniasm introduce large-scale structural rearrangements not present in the Canu assembly (Supplementary Figure S5). For initial assembly, Miniasm (Li 2016) is an order of magnitude faster than Canu and Falcon (Supplementary Note 8, Supplementary Table S4–S7). However, in contrast to Canu and Falcon, Miniasm does not perform a gapped alignment for either overlapping or consensus generation. Instead, Miniasm generates a string graph (Myers 2005) directly from approximate read overlaps and labels the edges of this graph with the raw read sequences. Thus, the average identity of the resulting assembly is equal to the identity of the input sequences, and the approximate overlap positions can leave large insertions and deletions in the assembly at the boundaries of the read segments. As a result, the Miniasm assemblies have both low base accuracy (<90%) and a higher frequency of large insertions and deletions, which can be difficult to remove during polishing. Therefore, Miniasm requires four rounds of Quiver polishing (Chin et al. 2013) before the assembly quality converges, whereas Canu requires only a single polishing round and is ultimately fastest to generate a polished assembly (Table 1, Supplementary Note 9, Supplementary Table S8–S11). To test if Miniasm polishing could be accelerated using a different algorithm, we tested the recently released Racon tool (Vaser et al. 2016), which was designed for this purpose. However, on C. elegans, two rounds of Racon required 60 CPU hours and produced a lower quality consensus than a single round of Quiver, which required a comparable 110 CPU hours. Supplementary Note 9, Supplementary Table S8–S11). To test if Miniasm polishing could be accelerated using a different algorithm, we tested the recently released Racon tool (Vaser et al. 2016), which was designed for this purpose. However, on C. elegans, two rounds of Racon required 60 CPU hours and produced a lower quality consensus than a single round of Quiver, which required a comparable 110 CPU hours. Assembly evaluation We evaluated Canu on a variety of microbial and eukaryotic genomes, and compared with Falcon (Chin et al. 2016), Miniasm (Li 2016), and hybrid SPAdes (Antipov et al. 2016) using both PacBio and Oxford Nanopore sequencing data (Supplementary Note 5–7). Continuity was measured using maximum and NG50 contig size, where NG50 is the longest contig such that contigs of this length or greater sum to at least half the haploid genome size. Accuracy was computed via alignment to the nearest available reference genome using MUMmer (Kurtz et al. 2004), and reported using the GAGE (Salzberg et al. 2012) metrics, which evaluate both base (single nucleotide) and structural breakpoints (inversions, relocations, and translocations). An ideal assembly has high continuity, low breakpoints, and high base accuracy, with 99.99% 12 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint (Phred QV40 (Ewing and Green 1998)) commonly defined as the minimum quality for a “finished” sequence (Felsenfeld et al. 1999; Schmutz et al. 2004). PacBio sequence assembly Canu shows good scaling to mammalian genomes, completing a polished human assembly tenfold faster than Celera Assembler 8.2, which was used to assemble the first human genome from PacBio data alone (Berlin et al. 2015), and threefold faster than the more recent Falcon assembler (Supplementary Table S4–S5). Canu runtime improvements come from recent optimizations to the initial overlapping and read correction process (Methods), which have 13 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint traditionally been the slowest step in hierarchical assembly. Read correction is now the fastest step of the Canu pipeline. As a result, Canu is often able to generate a complete assembly in less time than Falcon requires for its initial DALIGNER (Myers 2014) overlapping stage (Supplementary Table S4–S5). On the human genome, where the upfront cost of building MHAP sketches is most effectively amortized, Canu’s initial overlapping step is also faster than Minimap (Supplementary Table S6), but Miniasm failed to assemble this dataset due to its in- memory string graph construction, which exceeded 1 TB of memory. Canu’s greedy algorithm required less than 36 GB for the same dataset. Table 1: Canu is fastest for generating a high-quality polished assembly from PacBio data Genome Asm/Polish Max (Mbp) NG50 (Mbp) % Ref # Breakpoints Time (CPU h) % Idy E. coli Canu+Quiver 4.68 4.68 100% 0 12.25 99.9999% Falcon+Quiver 4.64 4.64 100% 2 25.14 99.9998% Miniasm+Quiver 4.64 4.64 99.99% 2 31.93 99.9998% SPAdes 4.64 4.64 100% 0 4.09 99.9972% D. melanogaster Canu+Quiver 25.78 21.31 97.47% 1,025 1,396.52 99.9795% Falcon+Quiver 23.08 9.84 96.12% 1,054 2,305.92 99.9813% Miniasm+Quiver 15.85 5.84 96.51% 752 1,484.33 99.9813% A. thaliana Canu+Quiver 15.95 8.31 82.94% 220 925.31 99.0710% Falcon+Quiver 15.94 8.17 82.72% 222 1,132.25 99.0710% Miniasm+Quiver 11.61 5.07 82.88% 205 976.43 99.0710% C. PacBio sequence assembly elegans Canu+Quiver 5.34 2.35 99.70% 139 410.07 99.9745% Falcon+Quiver 4.99 1.88 98.82% 138 397.40 99.9735% Miniasm+Quiver 5.85 2.96 99.44% 141 526.16 99.9706% CHM1 Canu+Quiver 80.08 21.95 86.84% 1,105 22,749.71 99.8081% Falcon+Quiver 52.34 9.46 86.58% 1,082 68,789.00 99.8086% Genome: the genome being assembled. Asm/Polish: software tools used to generate an initial and polished assembly. Max: the maximum contig size, in Mbp. NG50: N such that 50% of the genome is contained in contigs of length >=N where the genome size is set to the reference length (excluding alternates in Ref38). % Ref: the percentage of the reference covered by assembly alignments;; # Breakpoints: GAGE structural differences compared to the reference. Time: total time to generate a finished assembly, including time to polish consensus with Quiver (Chin et al. 2013). % Idy: identity to the reference of the final polished assembly. Multiple rounds of Quiver were run until the identity converged. This translated to a single round for Falcon and Canu and four rounds for Miniasm due to its low initial base quality. We estimate that substituting Racon for Quiver would reduce the Miniasm C. elegans runtime to 350–475 CPU hours. Miniasm on CHM1 required over 1 TB of memory and could not complete. SPAdes results on E. coli are without Quiver, making it faster than polished assemblies. However, the initial SPAdes assembly has similar quality to Canu (QV45 vs. QV47 respectively) in equivalent runtimes (4.09 SPAdes vs. 4.26 Canu CPU hours) (Supplementary Table S8, S11). Quiver polishing of the Canu assembly exceeds QV58, beating the best SPAdes polished assembly. Based on SPAdes benchmarking on A. thaliana above, it was excluded from eukaryotic runs. A. thaliana and CHM1 differ from the reference, leading to lower identity and reference coverage for all assemblers. For CHM1, all assemblers used only the P6-C4 chemistry data. Genome: the genome being assembled. Asm/Polish: software tools used to generate an initial and polished assembly. Max: the maximum contig size, in Mbp. NG50: N such that 50% of the genome is contained in contigs of length >=N where the genome size is set to the reference length (excluding alternates in Ref38). % Ref: the percentage of the reference covered by assembly alignments;; # Breakpoints: GAGE structural differences compared to the reference. Time: total time to generate a finished assembly, including time to polish consensus with Quiver (Chin et al. 2013). PacBio sequence assembly % Idy: identity to the reference of the final polished assembly. Multiple rounds of Quiver were run until the identity converged. This translated to a single round for Falcon and Canu and four rounds for Miniasm due to its low initial base quality. We estimate that substituting Racon for Quiver would reduce the Miniasm C. elegans runtime to 350–475 CPU hours. Miniasm on CHM1 required over 1 TB of memory and could not complete. SPAdes results on E. coli are without Quiver, making it faster than polished assemblies. However, the initial SPAdes assembly has similar quality to Canu (QV45 vs. QV47 respectively) in equivalent runtimes (4.09 SPAdes vs. 4.26 Canu CPU hours) (Supplementary Table S8, S11). Quiver polishing of the Canu assembly exceeds QV58, beating the best SPAdes polished assembly. Based on SPAdes benchmarking on A. thaliana above, it was excluded from eukaryotic runs. A. thaliana and CHM1 differ from the reference, leading to lower identity and reference coverage for all assemblers. For CHM1, all assemblers used only the P6-C4 chemistry data. Canu also represents a dramatic improvement over the latest version of Celera Assembler (Berlin et al. 2015). Our previous PacBio P5-C3 human (CHM1) assembly required >250,000 CPU hours with Celera Assembler, resulting in a contig NG50 of 4 Mbp (Berlin et al. 2015). The re-assembly of this same dataset with Canu required <25,000 CPU hours and the NG50 14 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint increased to over 7 Mbp. Improvements to PacBio chemistries are also resulting in impressive assembly gains. An updated assembly using the more recent PacBio P6-C4 chemistry requires the same runtime, yet increases the NG50 5-fold to over 20 Mbp. This de novo Canu assembly has comparable assembly size, contig counts, and continuity to the human reference assemblies before NCBI Build 34 (ca. PacBio sequence assembly 2003), which is the release immediately prior to the “finished” human genome (International Human Genome Sequencing 2004). The contig sizes of this Canu human assembly are also comparable to the scaffold sizes generated by Celera (Istrail et al. 2004), which used Sanger sequencing with a range of insert sizes and BACs. Since CHM1 is effectively a haploid sample, we also tested Canu on the recently released diploid Chinese human genome (HX1) (Shi et al. 2016). This data has a similar read length distribution to the CHM1 P5-C3 data (Supplementary Figure S7), albeit at twice the coverage, so one would expect a slight continuity improvement. As expected, the Canu HX1 assembly achieved an NG50 of 9.00 Mbp (Supplementary Figure S8), improving on the published Falcon assembly NG50 of 7.61 Mbp (Shi et al. 2016) and thereby demonstrating that Canu performs equally well on diploid human genomes. However, due to the relatively low level of heterozygosity, Canu will currently collapse human haplotypes and would require dedicated phasing to generate a haplotype-resolved human assembly. Nanopore sequence assembly Currently, the Oxford Nanopore MinION can read either one or both strands of a double- stranded DNA molecule. The “1D” mode sequences only the template strand, whereas the “2D” mode sequences both the template and complement strands via a hairpin adapter. This technique is similar to PacBio circular consensus sequencing (CCS) (Travers et al. 2010). Because the 2D mode provides two independent observations of each base, the per-read accuracy is improved (e.g. from 70% to 86% for R7.3 chemistry (Figure 5a)). To date, all assembly evaluations have focused on the more accurate 2D sequences (Loman et al. 2015; Judge et al. 2016; Sovic et al. 2016). While more accurate, the library preparation for 2D sequencing is more complex, reduces the effective throughput of the instrument (each molecule must be read twice), and currently produces shorter sequences. Thus, we designed Canu to assemble both 2D and the noisier 1D sequences, which benefit from increased read length and throughput, both key factors for genome assembly. 15 . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint Table 2: Canu consistently assembles complete genomes from only Oxford Nanopore data Genome Asm/Polish # Contigs Max (Mbp) % Ref # Breakpoints Time (CPU h) % Idy E. coli MAP005 Canu+Nanopolish (1) 4.64 99.98% 2 376.87 99.43% Falcon+Nanopolish 105 0.42 23% 2 106.2 99.41% Miniasm+Nanopolish 3 3.40 99.96% 0 2,344.02 99.36% E. coli MAP006-1 Canu+Nanopolish (1) 4.63 99.80% 0 167.04 99.81% Falcon+Nanopolish (1) 4.63 99.86% 0 207.45 99.78% Miniasm+Nanopolish (1) 4.66 99.97% 2 1,801.02 99.72% E. Nanopore sequence assembly coli MAP006-2 Canu+Nanopolish (1) 4.64 99.91% 2 168.69 99.78% Falcon+Nanopolish (1) 4.64 99.94% 2 196.16 99.76% Miniasm+Nanopolish (1) 4.65 99.70% 4 1,482.95 99.69% E. coli MAP006-PCR-1 Canu+Nanopolish (1) 4.64 99.95% 0 164.08 99.84% Falcon+Nanopolish (1) 4.63 99.80% 2 168.37 99.82% Miniasm+Nanopolish 3 2.15 99.96% 0 1,338.28 99.77% E. coli MAP006-PCR-2 Canu+Nanopolish (1) 4.64 99.99% 2 206.09 99.85% Falcon+Nanopolish (1) 4.64 100.00% 2 212.89 99.84% Miniasm+Nanopolish (1) 4.65 99.98% 0 1,669.83 99.81% B. anthracis Canu+Nanopolish (2) 5.20 99.77% 0 894.40 99.14% Falcon+Nanopolish 31 0.47 86.29% 0 795.93 99.17% Miniasm+Nanopolish 4 5.22 97.21% 0 5,094.90 99.05% Y. pestis Canu+Nanopolish (4) 4.67 99.97% 11 254.25 99.76% Falcon+Nanopolish (4) 4.68 99.97% 12 295.01 99.72% Miniasm+Nanopolish 9 2.69 99.91% 11 2,000.16 99.65% Columns defined as in Table 1. Since the maximum contig size is usually the NG50 size of these bacterial genomes, the # of contigs over 2 kbp in length is included to indicate assembly completeness. Genomes where the number of contigs matches the number of chromosomes and plasmids in the reference are marked with parentheses, indicating they are complete. Multiple rounds of Nanopolish were run until QV converged. This was one round for Falcon and Canu and three rounds for Miniasm. Nanopolish suffers a large performance penalty on high-error inputs, leading to significantly longer runtimes on initial Miniasm inputs. Calling consensus with Racon prior to Nanopolish would likely reduce the runtime of Miniasm to a time comparable with other assemblers. The B. anthracis and Y. pestis genome were not the same strain used for validation, leading to higher error counts and lower identity. In the case of Y. pestis, all assemblers agreed on three large inversions with respect to the reference (Supplementary Figure S15). nu consistently assembles complete genomes from only Oxford Nanopore data Table 2 shows Canu assemblies of seven recent 2D Nanopore sequencing runs: http://lab.loman.net/2015/09/24/first-sqk-map-006-experiment/ and http://lab.loman.net/2016/07/30/nanopore-r9-data-release/ (Loman et al. 2015). Consistent with independent evaluations (Judge et al. 2016; Sovic et al. 2016), Canu produces highly continuous assemblies from Nanopore data alone, and the continuity of Canu assemblies was equal to or better than all assemblers tested. Miniasm was again extremely fast and produced structurally correct and continuous assemblies (Supplementary Note 10, Supplementary Table S12–S14, Supplementary Figure S9–S15), except for B. anthracis, where it failed to assemble the high- copy plasmid pXO1 due to its stringent k-mer filtering. As with PacBio, the initial Minimap assemblies also have low base accuracy. Nanopore sequence assembly For Nanopore data, Minimap assemblies were less than 90% accurate, whereas Canu assemblies typically exceeded 99%. Consensus polishing using the Table 2 shows Canu assemblies of seven recent 2D Nanopore sequencing runs ://lab.loman.net/2015/09/24/first-sqk-map-006-experiment/ and 16 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint Nanopore signal data with Nanopolish (Loman et al. 2015) further improved the accuracy of all assemblies to as high as 99.85%, but polishing the lower quality Miniasm assemblies to comparable accuracy was 750% slower (Supplementary Table S12–S14). Nanopore signal data with Nanopolish (Loman et al. 2015) further improved the accuracy of all assemblies to as high as 99.85%, but polishing the lower quality Miniasm assemblies to comparable accuracy was 750% slower (Supplementary Table S12–S14). Table 3. Nanopore assemblies exceed hybrid methods in continuity and match their quality when polished with Illumina data Genome Asm/Polish # Contigs Max (Mbp) % Ref # Breakpoints Time (CPU h) % Idy E. coli MAP005 Canu+Pilon (1) 4.65 99.99% 2 10.98 99.9873% Falcon+Pilon 105 0.42 23.04% 2 4.36 99.9550% Miniasm+Pilon 3 3.40 90.62% 42 3.15 97.3878% SPAdes (1) 4.64 100.00% 0 3.61 99.9989% E. coli MAP006-1 Canu+Pilon (1) 4.63 99.82% 0 5.89 99.9995% Falcon+Pilon (1) 4.63 99.86% 0 7.3 99.9964% Miniasm+Pilon (1) 4.66 96.97% 21 3.14 99.6118% SPAdes (1) 4.64 100.00% 0 3.65 99.9965% E. coli MAP006-2 Canu+Pilon (1) 4.64 99.94% 2 3.92 99.9987% Falcon+Pilon (1) 4.64 99.94% 2 3.93 99.9933% Miniasm+Pilon (1) 4.64 97.98% 26 2.73 99.6336% SPAdes (1) 4.64 100.0% 0 3.56 99.9965% E. coli MAP006-PCR-1 Canu+Pilon (1) 4.64 99.95% 0 4.15 99.9993% Falcon+Pilon (1) 4.63 99.80% 2 3.55 99.9969% Miniasm+Pilon 3 2.16 98.41% 12 2.15 99.6734% SPAdes 2 3.95 100.00% 0 3.56 99.9965% E. coli MAP006-PCR-2 Canu+Pilon (1) 4.64 100.00% 2 6.16 99.9992% Falcon+Pilon (1) 4.64 100.00% 2 9.22 99.9963% Miniasm+Pilon (1) 4.65 98.57% 20 2.69 99.6734% SPAdes (1) 4.64 100.00% 0 4.00 99.9965% B. anthracis Canu+Pilon (2) 5.21 99.77% 1 65.01 99.8476% Falcon+Pilon 31 0.48 86.31% 0 14.95 99.8888% Miniasm+Pilon 4 5.25 79.36% 44 4.9 92.2732% SPAdes 6 4.13 100.00% 0 8.47 99.9948% Y. Table 2 shows Canu assemblies of seven recent 2D Nanopore sequencing runs ; https://doi.org/10.1101/071282 doi: ioRxiv preprint comparisons to hybrid SPAdes (Table 3). Pilon aligns Illumina reads against an assembled sequence and corrects base errors and small insertions and deletions (Indels). As with Nanopolish, this process was iterated until consensus quality converged, except for hybrid SPAdes, which did not require additional polishing. Combined assembly and polishing times for all assemblers were comparable. Canu, Falcon, and SPAdes routinely exceeded 99.99% polished base accuracy, but Miniasm was unable to exceeded 99.9% after many rounds of polishing (Supplementary Table S15). The residual Miniasm errors were large (average >500 bp) expansions or collapses in the draft assembly (Supplementary Figure S16), which are difficult to correct using short-read sequences. Hybrid SPAdes was typically most accurate, both in terms of base and structural accuracy. However, on the repetitive Y. pestis genome, it was significantly less continuous than hierarchical methods, and on the newer high-quality Nanopore datasets, the polished Canu accuracy exceeded SPAdes (Supplementary Note 11, Supplementary Table S16– S19, Supplementary Figure S17–S23). Table 2 shows Canu assemblies of seven recent 2D Nanopore sequencing runs pestis Canu+Pilon (4) 4.66 99.83% 23 17.92 99.8946% Falcon+Pilon (4) 4.64 99.65% 26 10.63 99.8715% Miniasm+Pilon 9 2.70 93.76% 42 8.68 98.7866% SPAdes 29 0.37 95.99% 15 17.08 99.9559% Columns defined as in Table 1. Hybrid assembly using Oxford Nanopore and Illumina data was tested across the assemblers from Table 2 with the addition of SPAdes. Polishing on all assemblies, except SPAdes, was done with three rounds of Pilon and total times reported. As in Table 2, Canu is most consistent at producing closed genomes for Oxford Nanopore data. SPAdes runtime is comparabled to polished Canu runtimes with both exceeding 99.99% identity on the majority of genomes. SPAdes has higher identity on the older MAP005 data, B. anthracis, and Y. pestis. However, Canu polished identities exceed SPAdes identities on the remaining datasets. Table 3. Nanopore assemblies exceed hybrid methods in continuity and match the polished with Illumina data e assemblies exceed hybrid methods in continuity and match their quality when i d t Columns defined as in Table 1. Hybrid assembly using Oxford Nanopore and Illumina data was tested across the assemblers from Table 2 with the addition of SPAdes. Polishing on all assemblies, except SPAdes, was done with three rounds of Pilon and total times reported. As in Table 2, Canu is most consistent at producing closed genomes for Oxford Nanopore data. SPAdes runtime is comparabled to polished Canu runtimes with both exceeding 99.99% identity on the majority of genomes. SPAdes has higher identity on the older MAP005 data, B. anthracis, and Y. pestis. However, Canu polished identities exceed SPAdes identities on the remaining datasets. Generating a finished-quality (>99.99%) consensus sequence from Nanopore reads required polishing with complementary short-read data. We repeated the above evaluation, but substituted Pilon (Walker et al. 2014) for Nanopolish (Loman et al. 2015), and included 17 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. Nanopore 1D sequence assembly We evaluated the performance of Canu on noisy 1D data using only the template sequences from the Escherichia coli MAP006-1 dataset, which averaged a raw 1D accuracy of just 70% (Figure 5a). To deal with this high error, we exploited the modularity of Canu to run ten rounds of correction, with the output of each round fed as input to the next (Supplementary Note 12). The corrected reads were then assembled into ten contigs with an NG50 of 619 kbp and a maximum contig size of 1.22 Mbp covering 89% of the reference at 85.52% identity versus a single circular chromosome for 2D data (Figure 5b-c). In contrast, the Miniasm assembly of this data covered less than 10% of the reference at 76.76% identity (Supplementary Figure S24). Polishing the Canu assembly with Nanopolish converged on a 1D consensus accuracy of 98% identity, and short-read polishing with Pilon improved the assembly to 93.83% coverage and 99.72% identity. Thus, despite their high error, we conclude that 1D sequences as low as 70% identity can be assembled, albeit at reduced consensus quality. However, more recent Nanopore sequencing chemistries are producing 1D reads with 85% accuracy, for which only a single round of correction is necessary. 18 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint Figure 5: Canu can assemble both 1D and 2D Nanopore E. coli reads. A) A comparison of error rates for 1D and 2D read error rates versus the reference. Template 1D and 2D reads from the MAP006-1 E. coli dataset were aligned independently to compute an identity for all reads with an alignment over 90% of their length (95% of the 2D reads and 86% of the 1D reads had an alignment over 90% of their length). The 2D sequences averaged 86% identity and the 1D reads averaged 70% identity. Nanopore 1D sequence assembly B) Bandage plot of the Canu best overlap graph for the 2D data. The genome is in a single circle representing the full chromosome. C) The corresponding plot for 1D data. While highly continuous, there are multiple components due to missed overlaps and unresolved repeats (due to the higher sequencing error rate). Figure 5: Canu can assemble both 1D and 2D Nanopore E. coli reads. A) A comparison of error rates for 1D and 2D read error rates versus the reference. Template 1D and 2D reads from the MAP006-1 E. coli dataset were aligned independently to compute an identity for all reads with an alignment over 90% of their length (95% of the 2D reads and 86% of the 1D reads had an alignment over 90% of their length). The 2D sequences averaged 86% identity and the 1D reads averaged 70% identity. B) Bandage plot of the Canu best overlap graph for the 2D data. The genome is in a single circle representing the full chromosome. C) The corresponding plot for 1D data. While highly continuous, there are multiple components due to missed overlaps and unresolved repeats (due to the higher sequencing error rate). Few eukaryotic Nanopore datasets are currently available due to the low throughput of 1D 2D E. coli K12 MAP006-1 A) C) (1D) # reads 0 500 1000 1500 0 20 40 60 80 100 Identity (%) B) (2D) 1D 2D E. coli K12 MAP006-1 A) C) (1D) # reads 0 500 1000 1500 0 20 40 60 80 100 Identity (%) B) (2D) Few eukaryotic Nanopore datasets are currently available due to the low throughput of the initial MinION instruments. However, as previously demonstrated using PacBio data, Canu easily scales to mammalian-sized genomes, and as Nanopore throughput improves it is expected that highly continuous eukaryotic assemblies will be possible. For an early test, we assembled the Saccharomyces cerevisiae genome from available R6 and R7 MinION data (Goodwin et al. 2015). This older dataset contains only 20× coverage of 2D reads and an average identity of 70% (Figure 6a), significantly lower than produced by newer chemistries. Despite this, Canu was able to assemble the dataset using the same iterative correction strategy as for 1D reads (Figure 6b, Supplementary Note 13, Supplementary Figure S25). Nanopore 1D sequence assembly The resulting assembly comprises 41 contigs, with a majority of chromosomes in one or two contigs and an NG50 of 469 kbp covering 95.22% of the reference at 94.33% identity. Illumina polishing with Pilon improved the assembly to 96.86% coverage at 99.83% identity. Prior to Canu, this dataset could only be assembled via a hybrid approach. Newer Nanopore chemistries are not expected to require an iterative correction strategy, and improved instrument throughput will enable fully assembled yeast chromosomes (Istace et al. 2016). Few eukaryotic Nanopore datasets are currently available due to the low throughput of 19 19 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint Figure 6: A highly continuous S. cerevisae assembly from noisy 1D and 2D MinION reads. A) A histogram of read error rates (1D and 2D) versus the reference. Alignment identity was computed only for reads with an alignment over 90% of their length. The majority of reads were below 75% identity with an overall average of 70%. B) Assembled Canu contigs were aligned to the reference and all alignments over 1 kbp in length and >90% identity were then plotted using the coloredChromosomes package (Böhringer et al. 2002). Alternating shades indicate adjacent alignments, so each transition from gray to black represents a contig boundary or alignment breakpoint. White regions indicate regions missing from the assembly. Most chromosomes are in less than 3 contigs, indicating structural agreement with the reference. B) S. Nanopore 1D sequence assembly Most chromosomes are in less than 3 contigs, indicating structural agreement with the reference. Nanopore 1D sequence assembly cerevisae S288c Read Identity 1D 2D I II III IV V VI VII VIII IX X XI XII XIII XIV XV XVI A) Identity (%) # reads 0 20 40 60 80 100 0 1000 2000 3000 4000 B) S. cerevisae S288c Read Identity 1D 2D I II III IV V VI VII VIII IX X XI XII XIII XIV XV XVI A) Identity (%) # reads 0 20 40 60 80 100 0 1000 2000 3000 4000 S. cerevisae S288c Read Identity B) S. cerevisae S288c Read Identity B) Figure 6: A highly continuous S. cerevisae assembly from noisy 1D and 2D MinION reads. A) A histogram of read error rates (1D and 2D) versus the reference. Alignment identity was computed only for reads with an alignment over 90% of their length. The majority of reads were below 75% identity with an Figure 6: A highly continuous S. cerevisae assembly from noisy 1D and 2D MinION reads. A) A Figure 6: A highly continuous S. cerevisae assembly from noisy 1D and 2D MinION reads. A) A histogram of read error rates (1D and 2D) versus the reference. Alignment identity was computed only for reads with an alignment over 90% of their length. The majority of reads were below 75% identity with an overall average of 70%. B) Assembled Canu contigs were aligned to the reference and all alignments over 1 kbp in length and >90% identity were then plotted using the coloredChromosomes package (Böhringer et al. 2002). Alternating shades indicate adjacent alignments, so each transition from gray to black represents a contig boundary or alignment breakpoint. White regions indicate regions missing from the assembly. Most chromosomes are in less than 3 contigs, indicating structural agreement with the reference. g g y y y ) histogram of read error rates (1D and 2D) versus the reference. Alignment identity was computed only for reads with an alignment over 90% of their length. The majority of reads were below 75% identity with an overall average of 70%. B) Assembled Canu contigs were aligned to the reference and all alignments over 1 kbp in length and >90% identity were then plotted using the coloredChromosomes package (Böhringer et al. 2002). Alternating shades indicate adjacent alignments, so each transition from gray to black represents a contig boundary or alignment breakpoint. White regions indicate regions missing from the assembly. Discussion Canu is able to generate highly continuous assemblies from both PacBio and Nanopore sequencing, but signal-level polishing is required to maximize the final consensus accuracy. Such algorithms use statistical models of the sequencing process to predict base calls directly from the raw instrument data, which is a richer source of information than FASTQ Phred quality values. Currently, a PacBio base accuracy of 99.999% (QV50) is achievable with Quiver polishing (Chin et al. 2013; Koren et al. 2013), but Nanopore is limited to at most 99.9% (QV30) with Nanopolish (Loman et al. 2015) due to systematic sequencing errors (Goodwin et al. 2015). Both tools are technology specific and must be trained on each new chemistry, so future improvements are possible. Alternatively, complementary short-read sequencing can be used for consensus polishing with Pilon. On recent Nanopore sequencing data, Illumina-polished Canu assemblies can reach QV50 and exceed the base accuracy of hybrid SPAdes assemblies. Thus, the combination of Nanopore and Illumina sequencing provides a new alternative for the 20 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint generation of finished microbial genomes. However, due to the difficulty of mapping short Illumina reads to repeats, signal-polished PacBio assemblies currently deliver the highest overall quality. Canu assembly followed by either single-molecule or short-read polishing is an efficient method for generating high-quality assemblies. Our results indicate that while Miniasm (Li 2016) can rapidly produce continuous and structurally accurate assemblies, the multiple rounds of polishing needed to produce an accurate consensus sequence becomes a computational bottleneck. Additionally, Canu is the only tool capable of assembling low-accuracy 1D Nanopore data, while scaling to gigabase-sized genomes—an important application given the pending release of high-throughput Nanopore sequencers. Combined with Canu’s adaptive k-mer weighting strategy, the assembly of repetitive heterochromatic sequence may be possible with high-coverage, long-read nanopore sequencing. Discussion Ultimately, because Hi-C provides megabase-scale linkage information, the integration of this technology with Canu assembly graphs could lead to complete de novo assemblies that span entire mammalian chromosomes from telomere to telomere, as was recently demonstrated for the domestic goat genome (Bickhart et al. 2016). 2016) or Hi-C (Selvaraj et al. 2013) could be used to guide walks through the Canu graph. Ultimately, because Hi-C provides megabase-scale linkage information, the integration of this technology with Canu assembly graphs could lead to complete de novo assemblies that span entire mammalian chromosomes from telomere to telomere, as was recently demonstrated for the domestic goat genome (Bickhart et al. 2016). Discussion Canu currently splits haplotypes into separate contigs wherever the allelic divergence is greater than the post-correction overlap error rate. This threshold is typically 1.5% for recent PacBio data. This splitting results in an assembly size larger than the haploid genome size. Although these regions are kept separate in the assembly graph, no effort is currently made to annotate such regions or phase multiple bubbles into larger haplotype blocks. Less diverged haplotypes, such as human, are collapsed, as demonstrated by the HX1 dataset. Currently, only abundance is considered for k-mer weighting, which avoids the consideration of false, repetitive overlaps. However, this same scheme could be used to improve the discrimination of minor variants between repeats and haplotypes by preferring haplotype-specific k-mers during sketch construction. This would increase the power of Canu’s statistical overlap filter, which prevents the merging of diverged repeats and haplotypes. For further improved haplotype reconstruction, it would be possible to apply an approach like Falcon-Unzip (Chin et al. 2016) to the Canu assembly graph to generate phased contigs based on linked variants identified within the single-molecule reads. For repeat structures, the current algorithm can resolve any repeat copy with more divergence than the post-correction overlap error rate. In the future, similar repeats could be resolved using more sophisticated graph traversals. For example, if one copy of a two-copy repeat is spanned, a correct reconstruction of the unspanned copy can be inferrered given that the other copy is correctly assembled (Ukkonen 1992). Alternatively, secondary information from technologies like 10x Genomics (Zheng et al. 21 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint 2016) or Hi-C (Selvaraj et al. 2013) could be used to guide walks through the Canu graph. Architecture Canu is a modular assembly infrastructure comprised of three primary stages— correction, trimming, and assembly (Figure 1)—that can be run on a single computer or multi- node compute cluster. For multi-node runs, recommended for large genomes, Canu supports Sun Grid Engine (SGE), Simple Linux Utility for Resource Management (SLURM), Load Sharing Facility (LSF), and Portable Batch System (PBS)/Torque job schedulers. Users without access to an institutional compute cluster can run large Canu assemblies via a cloud-computing provider using toolkits such as StarCluster (http://star.mit.edu/cluster/). As a Canu job progresses, summary statistics are updated in a set of plaintext and HTML reports. The primary data interchange between stages is FASTA or FASTQ inputs, but for efficiency each stage stores input reads in an indexed database, after which the original input is no longer needed. Each of the three stages begins by identifying overlaps between all pairs of input reads. Although the overlapping strategy varies for each stage, each counts k-mers in the reads, finds overlaps between the reads, and creates an indexed store of those overlaps. By default the correction stage uses MHAP (Berlin et al. 2015) and the remaining stages use overlapInCore (Myers et al. 2000). From the input reads, the correction stage generates corrected reads; the trimming stage trims unsupported bases and detects hairpin adapters, chimeric sequences, and other anomalies; and the assembly stage constructs an assembly graph and contigs. The individual stages can be run independently or in series. For distributed jobs, local compute resources are polled to build a list of available hosts and their specifications. Next, based on the estimated genome size, Canu will choose an appropriate range of parameters for each algorithm (e.g. number of compute threads to use for computing overlaps). Finally, Canu will automatically choose specific parameters from each 22 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. Architecture ; https://doi.org/10.1101/071282 doi: bioRxiv preprint allowed range so that usage of available resources is maximized. As an example, for a mammalian sized genome, Canu will choose between 1 to 8 compute threads and 4 to 16 GB memory for each overlapping job. On a grid with ten hosts, each with 18 cores and 32 GB of memory, Canu will maximize usage of all 180 cores by selecting 6 threads and 10 GB of memory per job. This process is repeated for each step, and allows automated deployment across varied cluster and host configurations, simplifying usage and maximizing resource utilization. MinHash Overlapping It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint q observed across all reads. Specifically, for all k-mers in the input read set, let 𝑓() be the maximum observed frequency, 𝑓(+, be the minimum observed frequency, and 𝑓" be the frequency of a specific k-mer q. By default, only 0.0005% of the most abundant k-mers are recorded, and all others are assigned 𝑓(+,. We define 𝑖𝑑𝑓" as: 𝑖𝑑𝑓" = 𝑇log( 𝑓()* 𝑓" −𝑎) (2) (2) The parameter 𝑎∈0,1 controls how strongly less common k-mers are preferred in relation to the more common ones, and T linearly transforms the values between 1 and 𝑖𝑑𝑓(), the maximum allowed weight. The minimum possible value is computed by plugging the maximum observed frequency of the most popular k-mer into formula (2), and the maximum possible value is computed by plugging in the filter cutoff value provided to MHAP (5×10-6 being the default). The idf values are then linearly rescaled to fall in the range [1, 𝑖𝑑𝑓()]. Any k-mer that does not exist in the filter file is assigned 𝑖𝑑𝑓(). For a general positive floating point number, (Chum et al. 2008) provided a formula for directly computing the w-weighted hash value for MinHash ranking. However, this formula requires computing 𝑠∙𝐿 logarithms to generate a sketch, which is computationally expensive (where s is the sketch size and L is the read length). As in the original MHAP implementation, we compute the initial hash value using the MurmurHash3 hash (http://code.google.com/p/smhasher/wiki/MurmurHash3), while the subsequent 𝑠−1 hashes are computed from a pseudorandom number generator (Berlin et al. 2015). We discretize the tf-idf to a limited range using rounding, which requires at most (𝑠−1) ∙𝐿∙𝑤() random number computations, where 𝑤()* is the maximum weight computed by MHAP, which is comparatively faster. We use 𝑖𝑑𝑓()* = 3 and 𝑎= 0.9 by default as a compromise between speed and performance. Recall that MinHash selects which k-mers will be included in the sketch on the basis of their hash value. MinHash Overlapping Canu uses an updated version of the MinHash Alignment Process (MHAP) for computing all-versus-all overlaps from noisy, single-molecule sequences (Berlin et al. 2015). MHAP has been further optimized for both speed and accuracy since the initial version. As described below, the most substantial algorithmic changes involve the sketching and filtering strategies. MHAP uses a two-stage overlap filter, where the first stage identifies read pairs that are likely to share an overlap and the second stage estimates the extent and quality of the overlap. For the first stage, MHAP now implements tf-idf weighting to prefer informative, non-repetitive k-mers. This increases sensitivity to true overlaps, while reducing the number of false, repetitive overlaps considered. For the second stage, MHAP now implements a “bottom sketch” strategy similar to Mash (Ondov et al. 2016), which significantly decreases memory usage and runtime. The Mash distance formula is also used to estimate the error rate (quality) of the identified overlaps directly from the sketches, without the need for a gapped alignment (Ondov et al. 2016). Engineering improvements include a switch to the FastUtil (http://fastutil.di.unimi.it) hash table implementation, which resulted in a 3-fold speedup, and an increase in the maximum k-mer size from 16 to 128 to support greater specificity on low-error datasets. Overall, the new MHAP version is 10-fold faster, on average, and over 40-fold faster on mammalian genomes that the original version, while maintaining similar accuracy. There have been several tf-idf formulations proposed for document and image retrieval (Manning et al. 2008), but for our purposes we use: There have been several tf-idf formulations proposed for document and image retrieval (Manning et al. 2008), but for our purposes we use: 𝑤" = 𝑡𝑓"𝑖𝑑𝑓" (1) 𝑤" = 𝑡𝑓"𝑖𝑑𝑓" " 𝑓" 𝑓" (1) (1) For each read, 𝑡𝑓" is the number of occurrences of k-mer q in the read, and 𝑖𝑑𝑓" is the inverse document frequency function for q, which logarithmically scales the inverse overall frequency of 23 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. MinHash Overlapping In the original MHAP implementation, a set Γ of s hash functions is defined for a sketch S of size s. Each sketch entry Si is defined as the minimum-valued k-mer after applying the hash function Γi to all k-mers in the read. The resulting set of s minimum-valued k-mers, or min-mers, comprise the sketch. Given a discrete tf-idf weight wq for each k-mer, we now modify 24 . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint the MinHash computation by applying wq hash functions {𝛤+,C, … , 𝛤+,EF} per entry, rather than the single Γi as before. For each sketch entry Si, the min-mer is then chosen as the minimum hash value computed across all functions. Because highly weighted k-mers are hashed more times, this increases the chance that they will be chosen as a min-mer. In order to properly match the same k-mers with different weights, we index k-mers using their fixed MurmurHash3 hash values, and the weighted values are only used to determine inclusion in the read sketches. The tf- idf approach replaces the previous approach, based on traditional all-or-nothing filtering of repetitive k-mers. We evaluated multiple scoring approaches including tf-idf, idf only (down- weighting common words), and no weighting on several bacterial and eukaryotic genomes. Both tf-idf and idf outperformed unweighted comparisons in terms of the resulting assembly continuity and accuracy, and were comparable to each other. We therefore utilize tf-idf by default due to its common use in the natural language field and other MinHash applications (Chum et al. 2008). The updated MHAP version also implements bottom sketching for the second-stage filter (Ondov et al. 2016). In contrast to the first-stage filter, which uses multiple hash functions (Broder et al. 2000), bottom sketching uses a single hash function, from which the s minimum values are retained as the sketch (Broder 1997). MinHash Overlapping The former approach has the advantage that the Jaccard similarity can be estimated for 1 versus N reads by a series of s hash table lookups. In bottom sketching, each comparison requires an O(s) merge operation, but as a benefit, any substring of the original string can be sketched by simply eliminating the min-mers from the original sketch that do not occur in the substring. For the bottom sketch, we now store a constant number of k-mers per read (default 1,500), and directly estimate the overlap error rate from these sketches using the Mash distance. The overlapping region is estimated as previously (Berlin et al. 2015), but also using the bottom sketch k-mers. Parallel Overlap Sort and Index The size of a bucket is chosen such that each contains the same number of overlaps, and no bucket is larger than some specified maximum size. In parallel, each file of compressed overlaps is rewritten to a set of uniquely named buckets, and overlaps are duplicated and added to the appropriate bucket (e.g. read A overlaps B; and read B overlaps A). Note that as each input file creates its own set of buckets, no synchronization is needed between jobs. When all overlaps are copied into buckets, each bucket is loaded into memory, sorted, and output to a uniquely named file. Each bucket holds all of (and only) the overlaps for the range of assigned reads. Finally, an index describing the file and offset location for each read is created. Parallel Overlap Sort and Index The downstream algorithms require efficient access to all overlaps for a single read, so the overlaps are organized using an indexed on-disk structure where all overlaps for a single read are listed sequentially. Canu parallelizes overlap computation into multiple jobs, each generating a compressed file of binary encoded overlaps and a file recording the number of overlaps for each read in that file. These files are combined into the master structure using a parallel bucket sort (Supplementary Figure S26). Since each read will have a different number of overlaps, and 25 . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint all overlaps for a given read must be in the same bucket in order for the bucket to be sorted, the number of overlaps per read is used to compute the ranges of reads assigned to each bucket. The size of a bucket is chosen such that each contains the same number of overlaps, and no bucket is larger than some specified maximum size. In parallel, each file of compressed overlaps is rewritten to a set of uniquely named buckets, and overlaps are duplicated and added to the appropriate bucket (e.g. read A overlaps B; and read B overlaps A). Note that as each input file creates its own set of buckets, no synchronization is needed between jobs. When all overlaps are copied into buckets, each bucket is loaded into memory, sorted, and output to a uniquely named file. Each bucket holds all of (and only) the overlaps for the range of assigned reads. Finally, an index describing the file and offset location for each read is created. all overlaps for a given read must be in the same bucket in order for the bucket to be sorted, the number of overlaps per read is used to compute the ranges of reads assigned to each bucket. Read Correction It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint Before computing the corrected sequence, the all-pair overlaps are used to predict the expected length of each read after correction (i.e. accounting for reads with partial or no overlaps). From these estimates, the longest reads up to a user-specified coverage depth are processed for correction. Corrected reads are generated using a modified implementation of the “falcon_sense” algorithm (Chin et al. 2016), which parallelizes the pairwise alignment step and removes and maximum read length limits. For a given read to be corrected, overlapping reads are aligned to it using Myers’ O(ND) algorithm (Myers 1986). A directed acyclic graph (DAG) is created from the alignments, and the highest weight path is followed to generate a corrected sequence (Chin et al. 2016). Edges with weight less than four are omitted, which will split the original read when there is insufficient evidence for correction. Read Correction Canu uses all-versus-all overlap information to correct individual reads. However, simply computing a consensus representation for each read using all overlaps could result in masking copy-specific repeat variants. Therefore, Canu uses two filtering steps to determine which overlaps should be selected to correct each individual read. The first is a global filter where each read chooses where it will supply correction evidence, and the second is a local filter where each read accepts or rejects the evidence supplied by other reads. This strategy attempts to overcome biases due to sequence quality and repeats. For example, reads with higher than average sequencing quality would tend to dominate the correction, regardless of if they were from the correct repeat copy. To prevent this, each read is only allowed to contribute to the correction of C other reads, where C is the expected read depth. The global filter scores each overlap (overlap_length * identity), and keeps only the C best overlaps for each read, thereby clustering repetitive reads with others likely to have originated from the same copy. When errors are uniformly distributed, we expect that reads are more likely to be grouped with reads from the same repeat copy, as they would have fewer total differences than reads from diverged repeat copies. A small fraction of mis-assigned reads is tolerable, as they will be outvoted during consensus correction. This strategy was first introduced by PBcR for the hierarchical correction and assembly of single-molecule reads (Koren et al. 2012). From this list, the local filter then selects the 2C best overlaps to each read for use in correction. The second filter is primarily a computational optimization. 26 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. Overlap Based Trimming After correction, reads are trimmed by re-computing overlaps for the corrected reads and removing sequence that is not supported by other reads. The prior correction stage also trims low-coverage regions, but these initial overlaps are constructed without constructing a gapped alignment, which can result in imprecise trim points. When overlapping the corrected reads for trimming, a gapped alignment is computed for each overlap, and the trim points can be identified more precisely. Overlap-based trimming (OBT) was first described by Miller et al. (Miller et al. 2008) and Prüfer et al. (Prüfer et al. 2012), which focused on trimming Sanger, 454 and Illumina reads. Long reads with uniform error allow the algorithm to be simplified. Each read is trimmed to the largest portion covered to at least depth C by overlaps of at most E error and minimum length L. The parameters are technology specific and set to empirically derived defaults. Once reads are trimmed, a second pass is made to detect any technology specific flaws, e.g. undetected hairpin adapters and chimeras (Eid et al. 2009; Jain et al. 2015). A hairpin adapter is detected by identifying when multiple reads have both forward and reverse overlaps around a common (short) sequence and there are few reads spanning this region. A chimeric junction is similarly detected by identifying a region with few, if any, spanning reads. In both cases, the original read is trimmed to the largest supported region. 27 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint Overlap Error Adjustment After trimming and before graph construction, Canu recomputes overlaps and makes a final attempt at detecting sequencing errors. This algorithm was first used in Holt et al. (Holt et al. 2002). The intuition is to improve separation between true sequencing differences (e.g. diverged repeats or haplotype) and false differences due to random sequencing error. Each read is corrected by a majority vote of its overlapping alignments, preserving differing bases only if there is sufficient support from other reads for this variation. The read sequence itself is not changed (doing so would invalidate the computed overlaps), but the reported error rate for each overlap is adjusted based on the alignment that would be generated had the sequencing errors been resolved. The algorithm requires two passes through the overlaps, the first pass detects probable sequencing errors in reads and the second pass applies those changes temporarily to reads to re-compute alignments and update the computed error rates. Graph Construction The Bogart module builds an assembly graph using a variant of the “best overlap graph” strategy from (Miller et al. 2008). Overlaps are described as containment, if all bases in one read are aligned to another read, or dovetail, if involving only the ends of both reads. By definition, at least two read ends must be present in the alignment. A “best” overlap is the longest dovetail overlap to a given read end. Each read has two best overlaps, one on the 5’ end and one on the 3’ end. In the original method, best overlaps were picked from all overlaps up to a user supplied overlap error rate cutoff. In Bogart, best overlaps are picked after several filtering steps remove abnormally high-error overlaps, potential chimeric reads, and reads whose overlaps indicate a possible sequence anomaly. This results in a cleaner and more accurate graph construction. After correction, trimming, and overlap error adjustment, all computed overlaps are used to pick an initial set of best edges. This set of best edges is used to compute the median and median absolute deviation (MAD) of the overlap error rate. This distribution represents the residual read error left after all prior corrections, and a low average overlap error rate cutoff indicates good sequencing data and successful correction. A maximum overlap error rate cutoff is automatically computed from this distribution as six MADs away from the median, and overlaps with an error greater than this cutoff are not used during graph construction. This cutoff, which is typically less than 2% for good PacBio data (average median 0.232% and average MAD 28 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint 0.138% for PacBio datasets in this paper), determines the ability of the algorithm to separate closely related repeats and haplotypes. Graph Construction In addition to filtering poor overlaps, Bogart filters suspicious reads that may have evaded proper trimming and correction. First, reads that are not fully covered by overlaps below the overlap error rate cutoff are flagged as potentially chimeric and excluded from graph construction. Second, best overlaps are usually mutual, i.e. the best overlap from A is to B and the best overlap from B is to A. For a pair of reads, non-mutual best overlaps are often caused by Indels, making the overlap length slightly longer or shorter compared to the mutual best overlap. Thus, reads with a large overlap size difference are also excluded (Supplementary Figure S27). The resulting set of reads and best overlaps define the best overlap graph. Initial contigs are then constructed from the best overlap graph as in (Miller et al. 2008), and an error rate profile is generated for each contig from the error rate of overlaps used to build it. A median and MAD value is computed for each window in the contig based on the overlaps falling in it to generate an error profile. This error profile is recomputed after each phase of the algorithm, and is used to determine if external reads have valid overlaps to the contig. Bogart next attempts to include contained (Fasulo et al. 2002) and previously filtered reads into the contigs. All overlaps to these reads are used to compute a set of potential contig placements, scored by the average overlap error rate. If this average error rate exceeds the pre- computed error profile for the contig region the read is likely from a diverged repeat or a heterozygous variant, and the placement is rejected. The placement with the lowest average error is accepted, and the read is placed. This strategy differs from the original strategy from (Miller et al. 2008) that placed contained reads based on the highest quality containment overlap, which could incorrectly place a read when the true location had no containing read. Reads that remain unplaced after this phase are output as “unassembled.” An assembly bubble occurs when there is more than one reconstruction of a specific locus caused by haplotype differences (Fasulo et al. 2002; Zerbino and Birney 2008; Koren et al. 2011; Nijkamp et al. 2013; Chin et al. 2016). Contig Consensus Canu generates a consensus sequence for each contig using a modified version of the “pbdagcon” algorithm (Chin et al. 2013). Briefly, a template sequence is constructed for each contig by splicing reads together from approximate positions based on the best overlap path. This template is accurate within individual reads, as they have previously been error-corrected, but may have Indel errors at read boundaries due to inaccuracy in the overlap positions. To correct this, all reads in the contig are aligned to the template sequence in parallel using Myers’ O(ND) algorithm (Myers 1986) and added to a DAG. The DAG is then used to call a consensus sequence as in (Chin et al. 2013). Graph Construction Small differences, tens of base pairs in size, are typically not detectable from overlaps alone because the difference is insignificant compared to the size of the overlap. Larger differences can result in two, mostly redundant, contigs covering the same locus. The haplotype with more reads is often reconstructed in a large contig spanning the locus, and the haplotype with fewer reads as just the variant region (the bubble). Currently, 29 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint contigs with fewer than a minimum threshold of reads, or with more than 75% of the reads with an overlap to some other contig, are considered potential bubbles. Reads in these contigs are then placed, using the mechanism for placing unplaced reads as above, into all other contigs where possible using heuristics. Improved mechanisms for resolving bubbles within the assembly graph, and ultimately producing a fully phased assembly, is an area of ongoing research and left for future work. Despite careful filtering, the greedy construction algorithm remains prone to error and the graph will be missing edges compared to a full string graph representation, so a final step is required to add missing edges and break incorrectly assembled contigs. Using the all-pairs overlap information, every assembled contig is annotated with compatible read placements, again using the read placement mechanism and all reads from non-bubble contigs. Only overlaps that meet the global and local contig error rate thresholds are considered. The resulting annotated regions indicate alternative branch points in the full overlap graph, and a correct contig reconstruction is confirmed by the presence of spanning reads or overlaps. Unresolved regions are marked as repeats, the contig is split, and additional edges are added to form the final assembly graph. Data Access The Bacillus anthracis Sterne 34F2 sequencing data has been deposited at NCBI under BioProject PRJNA357857 and the Yersinia pestis 195/P sequencing data under PRJNA357858. All other sequencing was obtained from external sources and listed in Supplementary Note 2. Attrill H, Falls K, Goodman JL, Millburn GH, Antonazzo G, Rey AJ, Marygold SJ, FlyBase C. 2016. FlyBase: establishing a Gene Group resource for Drosophila melanogaster. Nucleic acids research 44: D786-792. Assembler Versions 0.4.1 as of 2016-03-16 (commit c602aad3667b3fd49263028dac44da8e42caa17c). Falcon v0.4.1 as of 2016-03-16 (commit c602aad3667b3fd49263028dac44da8e42caa17c). Minimap/miniasm as of 2016-03-16 (commit 1cd6ae3bc7c7a6f9e7c03c0b7a93a12647bba244 30 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available unde The copyright holder for this preprint (which was no this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a ertified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: ioRxiv preprint minimap, 17d5bd12290e0e8a48a5df5afaeaef4d171aa133 miniasm). SPAdes v3.7.1. Canu v1.3 (Supplementary Note 5). Antipov D, Korobeynikov A, McLean JS, Pevzner PA. 2016. hybridSPAdes: an algorithm for hybrid assembly of short and long reads. Bioinformatics 32: 1009-1015. Acknowledgements We thank Celera and Pacific Biosciences for open source software that was critical for the development of Canu, and also John Urban and all other Canu users who provided early testing and feedback on the software. We thank Shaun Jackman and the other reviewers for their considered reviews, and one anonymous reviewer for providing a motivating example on repeat separation. This research was supported in part by the Intramural Research Program of the National Human Genome Research Institute, National Institutes of Health, and under Contract No. HSHQDC-07-C-00020 awarded by the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) for the management and operation of the National Biodefense Analysis and Countermeasures Center (NBACC), a Federally Funded Research and Development Center. The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the DHS or S&T. In no event shall the DHS, NBACC, S&T or Battelle National Biodefense Institute (BNBI) have any responsibility or liability for any use, misuse, inability to use, or reliance upon the information contained herein. DHS does not endorse any products or commercial services mentioned in this publication. This work utilized the computational resources of the NIH HPC Biowulf cluster (http://hpc.nih.gov). References Antipov D, Korobeynikov A, McLean JS, Pevzner PA. 2016. hybridSPAdes: an algorithm for hybrid assembly of short and long reads. Bioinformatics 32: 1009-1015. Attrill H, Falls K, Goodman JL, Millburn GH, Antonazzo G, Rey AJ, Marygold SJ, FlyBase C. 2016. FlyBase: establishing a Gene Group resource for Drosophila melanogaster. Nucleic acids research 44: D786-792. 31 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint Berlin K, Koren S, Chin C-S, Drake JP, Landolin JM, Phillippy AM. 2015. Assembling large genomes with single-molecule sequencing and locality-sensitive hashing. Nat Biotech 33: 623-630. Bickhart DM, Rosen BD, Koren S, Sayre BL, Hastie AR, Chan S, Lee J, Lam ET, Liachko I, Sullivan ST. 2016. Single-molecule sequencing and conformational capture enable de novo mammalian reference genomes. bioRxiv doi:10.1101/064352. Böhringer S, Gödde R, Böhringer D, Schulte T, Epplen JT. 2002. A software package for drawing ideograms automatically. Online J Bioinformatics 1: 51-61. Bresler G, Bresler M, Tse D. 2013. Optimal assembly for high throughput shotgun sequencing. BMC bioinformatics 14 Suppl 5: S18. Broder AZ. 1997. On the resemblance and containment of documents. Compression and Complexity of Sequences 1997 Proceedings: 21-29. Broder AZ, Charikar M, Frieze AM, Mitzenmacher M. 2000. Min-wise independent permutations. Journal of Computer and System Sciences 60: 630-659. Burton JN, Adey A, Patwardhan RP, Qiu R, Kitzman JO, Shendure J. 2013. Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions. Nature biotechnology 31: 1119-1125. Chakraborty M, Baldwin-Brown JG, Long AD, Emerson JJ. 2016. Contiguous and accurate de novo assembly of metazoan genomes with modest long read coverage. References CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint R, Dong L, Smith A, Finklestein J, Lam ET, Huo N, Cao H, Kwok PY, Deal KR, Hastie AR, Dong L, Smith A, Finklestein J, Lam ET, Huo N, Cao H, Kwok PY, Deal KR, Dvorak J et al. 2013. Rapid genome mapping in nanochannel arrays for highly complete and accurate de novo sequence assembly of the complex Aegilops tauschii genome. PLoS One 8: e55864. Holt RA Subramanian GM Halpern A Sutton GG Charlab R Nusskern DR Wincker P Clark AG Ribeiro JM Wides R et al. 2002. The genome sequence of the malaria mosquito Anopheles gambiae. Science 298: 129-149. Hoskins RA, Carlson JW, Wan KH, Park S, Mendez I, Galle SE, Booth BW, Pfeiffer BD, George RA, Svirskas R et al. 2015. The Release 6 reference sequence of the Drosophila melanogaster genome. Genome research 25: 445-458. g g International Human Genome Sequencing C. 2004. Finishing the euchromatic sequence of the human genome. Nature 431: 931-945. Istace B, Friedrich A, d'Agata L, Faye S, Payen E, Beluche O, Caradec C, Davidas S, Cruaud C, Liti G et al. 2016. de novo assembly and population genomic survey of natural yeast isolates with the Oxford Nanopore MinION sequencer. bioRxiv doi:10.1101/066613. Istrail S, Sutton GG, Florea L, Halpern AL, Mobarry CM, Lippert R, Walenz B, Shatkay H, Dew I, Miller JR et al. 2004. Whole-genome shotgun assembly and comparison of human genome assemblies. Proceedings of the National Academy of Sciences of the United States of America 101: 1916-1921. Jain M, Fiddes IT, Miga KH, Olsen HE, Paten B, Akeson M. 2015. Improved data analysis for the MinION nanopore sequencer. Nat Methods 12: 351-356. Judge K, Hunt M, Reuter S, Tracey A, Quail MA, Parkhill J, Peacock SJ. 2016. Comparison of bacterial genome assembly software for MinION data and their applicability to medical microbiology. Microbial Genomics 2. gy Kaplan N, Dekker J. 2013. High-throughput genome scaffolding from in vivo DNA interaction frequency. Nature biotechnology 31: 1143-1147. Kim KE, Peluso P, Babayan P, Yeadon PJ, Yu C, Fisher WW, Chin C-S, Rapicavoli NA, Rank DR, Li J et al. 2014. References Nucleic acids research 44: e147. Chin CS, Alexander DH, Marks P, Klammer AA, Drake J, Heiner C, Clum A, Copeland A, Huddleston J, Eichler EE et al. 2013. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat Methods 10: 563-569. Chin CS, Peluso P, Sedlazeck FJ, Nattestad M, Concepcion GT, Clum A, Dunn C, O'Malley R, Figueroa-Balderas R, Morales-Cruz A et al. 2016. Phased diploid genome assembly with single-molecule real-time sequencing. Nat Methods 13: 1050-1054. Chum O, Philbin J, Zisserman A. 2008. Near Duplicate Image Detection: min-Hash and tf-idf Weighting. BMVC 810: 812-815. Eid J, Fehr A, Gray J, Luong K, Lyle J, Otto G, Peluso P, Rank D, Baybayan P, Bettman B et al. 2009. Real-time DNA sequencing from single polymerase molecules. Science 323: 133- 138. Ewing B, Green P. 1998. Base-calling of automated sequencer traces using phred. II. Error probabilities. Genome research 8: 186-194. Fasulo D, Halpern A, Dew I, Mobarry C. 2002. Efficiently detecting polymorphisms during the fragment assembly process. Bioinformatics 18 Suppl 1: S294-302. Felsenfeld A, Peterson J, Schloss J, Guyer M. 1999. Assessing the quality of the DNA sequence from the Human Genome Project. Genome research 9: 1-4. Goodwin S, Gurtowski J, Ethe-Sayers S, Deshpande P, Schatz MC, McCombie WR. 2015. Oxford Nanopore sequencing, hybrid error correction, and de novo assembly of a eukaryotic genome. Genome research 25: 1750-1756. Gordon D, Huddleston J, Chaisson MJ, Hill CM, Kronenberg ZN, Munson KM, Malig M, Raja A, Fiddes I, Hillier LW et al. 2016. Long-read sequence assembly of the gorilla genome. Science 352: aae0344. Hackl T, Hedrich R, Schultz J, Forster F. 2014. proovread: large-scale high-accuracy PacBio correction through iterative short read consensus. Bioinformatics 30: 3004-3011. 32 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . References Miller JR, Delcher AL, Koren S, Venter E, Walenz BP, Brownley A, Johnson J, Li K, Mobarry C, Sutton G. 2008. Aggressive assembly of pyrosequencing reads with mates. Bioinformatics 24: 2818-2824. f Myers EW. 1986. An O(ND) difference algorithm and its variations. Algorithmica 1: 251-266. Myers EW. 1986. An O(ND) difference algorithm and its variations. Algorithmica 1: 251-266. Myers EW. 2005. The fragment assembly string graph. Bioinformatics (Oxford, England) 21 Suppl 2: ii79-85. Myers EW. 2005. The fragment assembly string graph. Bioinformatics (Oxford, England) 21 Suppl 2: ii79-85. Myers EW, Sutton GG, Delcher AL, Dew IM, Fasulo DP, Flanigan MJ, Kravitz SA, Mobarry CM, Reinert KH, Remington KA et al. 2000. A whole-genome assembly of Drosophila. Science 287: 2196-2204. Myers G. 2014. Efficient Local Alignment Discovery amongst Noisy Long Reads. Algorithms in Bioinformatics 8701: 52-67. Nagarajan N, Pop M. 2009. Parametric complexity of sequence assembly: theory and applications to next generation sequencing. J Comput Biol 16: 897-908. Nijkamp JF, Pop M, Reinders MJT, de Ridder D. 2013. Exploring variation-aware contig graphs for (comparative) metagenomics using MaryGold. Bioinformatics 29: 2826-2834. Ning Z, Cox AJ, Mullikin JC. 2001. SSAHA: a fast search method for large DNA databases. Genome research 11: 1725-1729. Ondov BD, Treangen TJ, Melsted P, Mallonee AB, Bergman NH, Koren S, Phillippy AM. 2016. Mash: fast genome and metagenome distance estimation using MinHash. Genome Biol 17: 132. Ono Y, Asai K, Hamada M. 2013. PBSIM: PacBio reads simulator--toward accurate genome assembly. Bioinformatics 29: 119-121. Phillippy AM, Schatz MC, Pop M. 2008. Genome assembly forensics: finding the elusive mis- assembly. Genome biology 9: R55-R55. Prüfer K, Munch K, Hellmann I, Akagi K, Miller JR, Walenz B, Koren S, Sutton G, Kodira C, Winer R. 2012. The bonobo genome compared with the chimpanzee and human genomes. Nature. Ross MG, Russ C, Costello M, Hollinger A, Lennon NJ, Hegarty R, Nusbaum C, Jaffe DB. 2013. Characterizing and measuring bias in sequence data. Genome Biol 14: R51. Salmela L, Rivals E. 2014. LoRDEC: accurate and efficient long read error correction. Bioinformatics 30: 3506-3514. Salzberg SL, Phillippy AM, Zimin A, Puiu D, Magoc T, Koren S, Treangen TJ, Schatz MC, Delcher AL, Roberts M. 2012. GAGE: A critical evaluation of genome assemblies and assembly algorithms. Genome research 22: 557-567. Schmutz J, Wheeler J, Grimwood J, Dickson M, Yang J, Caoile C, Bajorek E, Black S, Chan YM, Denys M et al. 2004. References Long-read, whole-genome shotgun sequence data for five model organisms. Scientific Data 1. g Koren S, Harhay GP, Smith TP, Bono JL, Harhay DM, McVey SD, Radune D, Bergman NH, Phillippy AM. 2013. Reducing assembly complexity of microbial genomes with single- molecule sequencing. Genome Biol 14: R101. Koren S, Phillippy AM. 2014. One chromosome, one contig: complete microbial genomes from long-read sequencing and assembly. Curr Opin Microbiol 23C: 110-120. Koren S, Schatz MC, Walenz BP, Martin J, Howard JT, Ganapathy G, Wang Z, Rasko DA, McCombie WR, Jarvis ED et al. 2012. Hybrid error correction and de novo assembly of single-molecule sequencing reads. Nature biotechnology 30: 693-700. Koren S, Treangen TJ, Pop M. 2011. Bambus 2: Scaffolding Metagenomes. Bioinformatics 27: 2964-2971. Kurtz S, Phillippy A, Delcher AL, Smoot M, Shumway M, Antonescu C, Salzberg SL. 2004. Versatile and open software for comparing large genomes. Genome biology 5: R12-R12. Lee H, Gurtowski J, Yoo S, Marcus S, McCombie WR, Schatz M. 2014. Error correction and assembly complexity of single molecule sequencing reads. bioRxiv doi:10.1101/006395. assembly complexity of single molecule sequencing reads. bioRxiv doi:10.1101/006395. Li H. 2016. Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences. Bioinformatics 32: 2103-2110. Li H. 2016. Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences. Bioinformatics 32: 2103-2110. 33 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint Loman NJ, Quick J, Simpson JT. 2015. A complete bacterial genome assembled de novo using only nanopore sequencing data. Nat Methods 12: 733-735. y p q g Manning CD, Raghavan P, Schütze H. 2008. Scoring, term weighting and the vector space model. Introduction to Information Retrieval 100: 2-4. Metz CW. 1914. Chromosome studies in the Diptera. Journal of Experimental Zoology 17: 45- 59. . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint References Quality assessment of the human genome sequence. Nature 429: 365-368. Schneider GF, Dekker C. 2012. DNA sequencing with nanopores. Nature biotechnology 30: 326- 328. 34 . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint . CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 4, 2017. ; https://doi.org/10.1101/071282 doi: bioRxiv preprint Selvaraj S, J RD, Bansal V, Ren B. 2013. Whole-genome haplotype reconstruction using proximity-ligation and shotgun sequencing. Nature biotechnology 31: 1111-1118. Shi L, Guo Y, Dong C, Huddleston J, Yang H, Han X, Fu A, Li Q, Li N, Gong S et al. 2016. Long-read sequencing and de novo assembly of a Chinese genome. Nat Commun 7: 12065. Sovic I, Krizanovic K, Skala K, Sikic M. 2016. Evaluation of hybrid and non-hybrid methods for de novo assembly of nanopore reads. Bioinformatics doi:10.1093/bioinformatics/btw237. , , , y y de novo assembly of nanopore reads. Bioinformatics doi:10.1093/bioinformatics/btw237. Stevens NM. 1912. The chromosomes in Drosophila ampelophila. Proceedings of the 7th International Zoological Congress, Boston: 380-381. Stevens NM. 1912. The chromosomes in Drosophila ampelophila. Proceedings of the 7th International Zoological Congress, Boston: 380-381. Sutton GG, White O, Adams MD, Kerlavage AR. 1995. TIGR Assembler: A New Tool for Assembling Large Shotgun Sequencing Projects. Genome Science and Technology 1: 9- 19. Tørresen OK, Star B, Jentoft S, Reinar WB, Grove H, Miller JR, Walenz BP, Knight J, Ekholm JM, Peluso P et al. 2016. An improved genome assembly uncovers a prolific tandem repeat structure in Atlantic cod. bioRxiv doi:10.1101/060921. Travers KJ, Chin CS, Rank DR, Eid JS, Turner SW. 2010. A flexible and efficient template format for circular consensus sequencing and SNP detection. Nucleic acids research 38: e159. Ukkonen E. References 1992. Approximate string-matching with q-grams and maximal matches. Theoretical Computer Science 92: 191-211. p Vaser R, Sovic I, Nagarajan N, Sikic M. 2016. Fast and accurate de novo genome assembly from long uncorrected reads. bioRxiv doi:10.1101/068122. Walker BJ, Abeel T, Shea T, Priest M, Abouelliel A, Sakthikumar S, Cuomo CA, Zeng Q, Wortman J, Young SK et al. 2014. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS One 9: e112963. Wang H, Avican K, Fahlgren A, Erttmann SF, Nuss AM, Dersch P, Fallman M, Edgren T, Wolf- Watz H. 2016. Increased plasmid copy number is essential for Yersinia T3SS function and virulence. Science 353: 492-495. Wang H, Avican K, Fahlgren A, Erttmann SF, Nuss AM, Dersch P, Fallman M, Edgren T, Wolf- Watz H. 2016. Increased plasmid copy number is essential for Yersinia T3SS function and virulence. Science 353: 492-495. Wick RR, Schultz MB, Zobel J, Holt KE. 2015. Bandage: interactive visualization of de novo genome assemblies. Bioinformatics 31: 3350-3352. Wick RR, Schultz MB, Zobel J, Holt KE. 2015. Bandage: interactive visualization of de novo genome assemblies. Bioinformatics 31: 3350-3352. g Ye C, Hill CM, Wu S, Ruan J, Ma ZS. 2016. DBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies. Sci Rep 6: 31900. Ye C, Hill CM, Wu S, Ruan J, Ma ZS. 2016. DBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies. Sci Rep 6: 31900. Zerbino DR, Birney E. 2008. Velvet: Algorithms for de novo short read assembly using de Bruijn graphs. Genome research 18: 821-829. Zerbino DR, Birney E. 2008. Velvet: Algorithms for de novo short read assembly using de Bruijn graphs. Genome research 18: 821-829. Zheng GX, Lau BT, Schnall-Levin M, Jarosz M, Bell JM, Hindson CM, Kyriazopoulou- Panagiotopoulou S, Masquelier DA, Merrill L, Terry JM et al. 2016. Haplotyping germline and cancer genomes with high-throughput linked-read sequencing. Nature biotechnology 34: 303-311. 35
https://openalex.org/W1851866557	https://seer.ufs.br/index.php/revtee/article/download/2962/2607	Portuguese	null	Gênero, sexualidade e educação: perspectivas em debate	Revista Tempos e Espaços em Educação	1,969	cc-by	11,204	1 Mestre em Educação pela Universidade Federal de Sergipe, Espe- cialista em Didática e Metodologia do Ensino Superior pela Faculdade São Luiz de França, graduada em Serviço Social pela Universidade Ti- radentes, Aracaju/SE. Assistente Social do Núcleo de Práticas jurídicas da Universidade Tiradentes. Tutora do Centro de Educação a Distância da Universidade Federal de Sergipe. Participa do Grupo de Pesquisa do CNPq: “Educação, Formação, Processo de Trabalho e Relações de Gêne- ro”. Aracaju/Sergipe/Brasil. E-mail: anab.santana@hotmail.com 151 151 151 Gênero, sexualidade e educação: perspectivas em debate Anabela Maurício de Santana11 Resumo: O presente artigo analisa a reprodução das relações de gênero no âmbito da relação homoafetiva, possibilitan- do uma reflexão acerca do que é ser homem e do que é ser mulher e seus respectivos papéis na sociedade e na família e problematiza as relações existentes entre gêne- ro e sexualidade na educação. A pesquisa tem por ob- jetivo problematizar as relações existentes entre gênero e sexualidade na educação, a partir da perspectiva dos Estudos Culturais e dos Estudos Feministas, tendo como marco teórico a abordagem pós-estruturalista de análise e adota-se como ideias norteadoras a mulher lésbica na relação homoafetiva, o que ela anseia e as maneiras que tem encontrado para driblar o preconceito, a rejeição, a agressividade e o decesso às políticas públicas para essas mulheres. A pesquisa teve como sujeitos quatro mulhe- res que se intitulam lésbicas e com o intento de fazer esta investigação foram utilizados os meses de setembro, ou- tubro e novembro de dois mil e dez, tendo como locus o município de Itaporanga d’ Ajuda/Se. Palavras-chave: Gênero, Educação, Sexualidade. Palavras-chave: Gênero, Educação, Sexualidade. 152 GÊNERO, SEXUALIDADE E EDUCAÇÃO Palabras clave: género, educación, sexualidad. Introdução Por mais que a sexualidade seja uma temática que na escola sempre esteja vinculada às aulas de ciências ou então de educação física, é necessário considerar sua vertente social, e, sobretudo, histórica. Contudo, sendo a sexualidade, entendida como uma construção social, histórica e cultural, sente-se a necessidade de ser discu- tida na escola por todos/as aqueles que dela fazem par- te, pois a escola é espaço privilegiado para o tratamento pedagógico desse desafio educacional contemporâneo. Nesse sentido, o presente artigo – que é um recorte de uma pesquisa concluída em 2010 sobre educação sexual, familiar e religiosa e a homoafetividade em Itaporanga d’ Ajuda/Se – tem por objetivo problematizar as relações existentes entre gênero e sexualidade na educação, a partir da perspectiva dos Estudos Culturais e dos Estudos Feministas, tendo como marco teórico a abordagem pós- -estruturalista de análise. Isso posto, percebe-se não ser mais necessário ressaltar a importância que as dimensões de gênero e sexualidade adquiriram na teorização social, cultural e política con- temporânea, visto que desde o final dos anos 70 do séc. XX, uma ampla, complexa e profícua produção acadê- mica vem ressaltando a impossibilidade de ignorarmos relações de gênero e sexualidade quando buscamos analisar e compreender questões sociais e educacionais. O universo da pesquisa foi constituído por quatro mu- lheres lésbicas residentes em Itaporanga d’ Ajuda. Os instrumentos metodológicos utilizados foram: a entre- vista – semi-estruturada –, complementada pelo ques- tionário e a observação. O feminismo pós-estruturalista, aproximando-se de te- orias como as desenvolvidas por Michel Foucault, por exemplo, adota que gênero remete a todas as formas de construção social, cultural e linguística implicadas com processos que distinguem mulheres de homens, abar- cando aqueles processos que produzem seus corpos, distinguindo-os e nomeando-os como corpos dotados de sexo, gênero e sexualidade. Nas entrevistas, reconstituímos a história de vida de quatro mulheres participantes. A escolha dos sujeitos foi por acessibilidade, dependendo apenas da disponi- bilidade de tempo das respondentes em contribuir com a investigação. Dessa forma, cabe salientar que as mu- lheres respondentes formam dois casais homoafetivo que convivem maritalmente. Resumen This paper analyzes the reproduction of gender relations within the homo-affective relationship, allowing a reflec- tion on the idea of men and women and their roles in society and in the family,discussing the relationship be- tween gender and sexuality in the educational field. The research aims to problematize the relationship between gender and sexuality in education, from the perspective of Cultural Studies and Feminist Studies, with a theoreti- cal framework based on poststructuralist approach of analysis and adopting, as the guiding ideas,the lesbians in the homo-affective relationship, their desires and the ways they have found to circumvent prejudice, rejection, aggression and the demise of public policies for these women. The researchwas held in Itaporanga d’Ajuda/SE, in September, October and November of two thousand and ten, and it wasbased on four women who called themselves lesbians. En este trabajo se analiza la reproducción de las relaciones de género dentro de la relación homo-afectiva, lo que per- mite una reflexión sobre lo que significa ser hombre y ser mujer y sus respectivos papeles en la sociedad y en la fami- lia, y problematiza las relaciones existentes entre género y sexualidad en la educación. La investigación tiene como objetivo problematizar las relaciones existentes entre gé- nero y sexualidad en la educación, desde la perspectiva de los Estudios Culturales y los Estudios Feministas, cuyo marco teórico es el enfoque postestructuralista de análisis y se adopta como las ideas orientadorasla mujer lesbiana en la relación homo-afectiva, lo que anhela y las formas en que se ha encontrado para eludir el prejuicio, el rechazo, la agresividad y la desaparición de las políticas públicas para estas mujeres. La investigación tuvo cuatro mujeres como sujetos que se dicen lesbianas y con la intención de hacer esta investigación se utilizaron los meses de septiembre, octubre y noviembre de dos mil diez, teniendo comolocus el municipio de Itaporanga d ‘Ajuda/Se. Keywords: Gender, Education, Sexuality. Palabras clave: género, educación, sexualidad. Anabela Maurício de Santana 153 153 mulher, homem, dominação masculina e subordinação feminina, dentre outros, para tornar visíveis os mecanis- mos e estratégias de poder que instituem e legitimam estas noções; 5) explorar a pluralidade, a conflitualidade e a provisoriedade dos processos que delimitam possibi- lidades de se definir e viver o gênero em cada sociedade e nos diferentes segmentos culturais e sociais. Feminismo e a Construção da Categoria Gênero Nesse sentido, os Estudos Feministas sempre estiveram preocupados com as relações de poder entre mulheres e homens. A princípio, tais estudos procuravam chamar a atenção para as condições de exploração e dominação a que as mulheres estavam submetidas. Como refere Guacira Louro (1995), além de uma ferramenta teórica potencialmente útil para os estudos das ciências sociais, o gênero despontava como uma importante categoria analítica para a História, em especial para a História da Educação. O caráter político destes estudos pode ser considerado uma de suas marcas mais significativas: O Feminismo foi, sem dúvida, um importante movi- mento social que começou a ter visibilidade no final do século XIX com o sufragismo1. No final da década de 60, o movimento, no processo que passou a ser con- siderado como segunda onda do feminismo, ampliou- -se para além do seu sentido reivindicatório, exigindo não só a igualdade de direitos, em termos políticos e sociais, mas constituindo-se também em crítica teó- rica. Outrossim, este não foi um movimento isolado, pois somou-se a outros movimentos igualmente im- portantes, como os movimentos estudantis, negros e outros, principalmente nos Estados Unidos, Inglaterra, Alemanha e França. Objetividade e neutralidade, distanciamento e isenção, que haviam se constituído, convencio- nalmente, em condições indispensáveis para o fazer acadêmico, eram problematizados, sub- vertidos, transgredidos. Pesquisas passavam a lançar mão, cada vez com mais desembaraço, de lembranças e de histórias de vida; de fontes iconográficas, de registros pessoais, de diários, cartas e romances. Pesquisadoras escreviam na primeira pessoa. Assumia-se, com ousadia, que as questões eram interessadas, que elas tinham origem numa trajetória histórica específica que construiu o lugar social das mulheres e que o estudo de tais questões tinham (e tem) preten- sões de mudança (LOURO, 2010, p. 19). Stuart Hall (1997) mostra que o Feminismo introduziu aspectos completamente novos na sua luta de contes- tação política, à medida que passou a abordar temas como família, sexualidade, trabalho doméstico, o cui- dado com as crianças, entre outros. Além disso, Hall salienta que: Enfatizou, como uma questão política e social, o tema da forma como somos formados e pro- duzidos como sujeitos generificados. Isto é, ele politizou a subjetividade, a identidade e o processo de identificação (como homens/mu- lheres, mães/pais, filhos/filhas). [...] aquilo que começou como um movimento dirigido à con- testação da posição social das mulheres, expan- diu-se para incluir a formação das identidades sexuais e de gênero (HALL, 1997, p. 49-50). Introdução A salienta que: Enfatizou, como uma questão o tema da forma como somos duzidos como sujeitos gene ele politizou a subjetividade, processo de identificação (co lheres, mães/pais, filhos/filhas começou como um moviment testação da posição social das diu-se para incluir a formação sexuais e de gênero (HALL, 199 Cabe salientar que o conceito de gênero estudiosas feministas para se contrapor à cia, recusando, dessa forma, qualquer ex da no determinismo biológico, que pude comportamentos de mulheres e homens do assim uma visão naturalizada, unive dos comportamentos. Para tanto, tal det viu muitas vezes para justificar as desig ambos, a partir de suas diferenças físicas. na perspectiva das relações de gênero, é cessos de construção ou formação histó e social, instituídas na formação de mulh meninas e meninos. 154 GÊNERO, SEXUALIDADE E EDUCAÇÃO Feminismo e a Construção da Categoria Gên O Feminismo foi, sem dúvida, um importante m mento social que começou a ter visibilidade no f do século XIX com o sufragismo1. No final da déc de 60, o movimento, no processo que passou a ser c siderado como segunda onda do feminismo, ampl -se para além do seu sentido reivindicatório, exigi não só a igualdade de direitos, em termos polític sociais, mas constituindo-se também em crítica rica. Outrossim, este não foi um movimento isola pois somou-se a outros movimentos igualmente portantes, como os movimentos estudantis, negr outros, principalmente nos Estados Unidos, Inglate Alemanha e França. Stuart Hall (1997) mostra que o Feminismo introd aspectos completamente novos na sua luta de con tação política, à medida que passou a abordar te como família, sexualidade, trabalho doméstico, o dado com as crianças, entre outros. Além disso, salienta que: Enfatizou, como uma questão política e so o tema da forma como somos formados e duzidos como sujeitos generificados. Ist ele politizou a subjetividade, a identidade processo de identificação (como homens/ lheres, mães/pais, filhos/filhas). [...] aquilo começou como um movimento dirigido à testação da posição social das mulheres, ex diu-se para incluir a formação das identid sexuais e de gênero (HALL, 1997, p. 49-50). Cabe salientar que o conceito de gênero brotou entr estudiosas feministas para se contrapor à ideia de es cia, recusando, dessa forma, qualquer explicação pa da no determinismo biológico, que pudesse explica comportamentos de mulheres e homens, empreend do assim uma visão naturalizada universal e imut GÊNERO, SEXUALIDADE E EDUCAÇÃO 154 Introdução Nessa perspectiva, trabalhar com o conceito de gênero segundo Meyer (2003), supõe e demanda: 1) assumir que diferenças e desigualdades entre mulheres e ho- mens são social, cultural e discursivamente construídas e não biologicamente determinadas; 2) deslocar o foco de atenção da “mulher dominada, em si” para a relação de poder em que as diferenças e desigualdades são pro- duzidas, vividas e legitimadas; 3) explorar o caráter rela- cional do conceito e considerar que as análises e inter- venções empreendidas neste campo de estudos devem tomar como referência, as relações – de poder – e as mui- tas formas sociais e culturais que, de forma interdepen- dente e inter-relacionada, educam homens e mulheres como “sujeitos de gênero”; 4) “rachar” a homogeneidade, a essencialização e a universalidade contidas nos termos Quanto aos relatos orais, estes foram gravados e trans- critos logo após a realização dos mesmos, para ga- rantir maior fidelidade. Procuramos também registrar mensagens não-verbais e as condições nas quais as entrevistas ocorriam. O questionário foi utilizado para nos auxiliar a traçar o perfil do universo estudado. Quanto à observação, esta se deu no cotidiano duran- te as visitas aos seus domicílios. Este trabalho, no entanto, apresenta apenas a análise dos relatos orais colhidos nas entrevistas. Inicialmente, será abordada a escolaridade e as dificuldades enfrentadas na escola. Em seguida, será tratado acerca da profissão, mercado de trabalho e a relação com a família. 154 GÊNERO, SEXUALIDADE E EDUCAÇÃO Feminismo e a Construção da Categ O Feminismo foi, sem dúvida, um imp mento social que começou a ter visibi do século XIX com o sufragismo1. No f de 60, o movimento, no processo que pa siderado como segunda onda do femin -se para além do seu sentido reivindica não só a igualdade de direitos, em term sociais, mas constituindo-se também e rica. Outrossim, este não foi um movim pois somou-se a outros movimentos ig portantes, como os movimentos estud outros, principalmente nos Estados Uni Alemanha e França. Stuart Hall (1997) mostra que o Feminis aspectos completamente novos na sua tação política, à medida que passou a como família, sexualidade, trabalho do dado com as crianças, entre outros. Feminismo e a Construção da Categoria Gênero Destarte, devemos considerar, porém, que grande parte da produção brasileira atrelada aos Estudos Feministas nos últimos anos se concentrou no estudo das mulhe- res. Questões ligadas à feminização do magistério, bem como outras ocupações vinculadas ao trabalho femini- no, compuseram o maior número das pesquisas. Muitos destes trabalhos procuraram descrever a situação da mulher em termos de opressão e desigualdade social. Entretanto, atualmente as pesquisas neste campo têm se voltado para o caráter relacional dos gêneros, enten- dendo que mulheres e homens, meninas e meninos são formados em relação, uns com os outros e também no entrecruzamento de outras categorias, como classe so- cial, religião, etnia, nacionalidade, geração (LOURO, 2010; MEYER, 1998; FELIPE, 1998). Cabe salientar que o conceito de gênero brotou entre as estudiosas feministas para se contrapor à ideia de essên- cia, recusando, dessa forma, qualquer explicação pauta- da no determinismo biológico, que pudesse explicar os comportamentos de mulheres e homens, empreenden- do assim uma visão naturalizada, universal e imutável dos comportamentos. Para tanto, tal determinismo ser- viu muitas vezes para justificar as desigualdades entre ambos, a partir de suas diferenças físicas. O que importa, na perspectiva das relações de gênero, é discutir os pro- cessos de construção ou formação histórica, linguística e social, instituídas na formação de mulheres e homens, meninas e meninos. Os estudos de gênero não se limitam, portanto, aos es- tudos de/sobre mulheres, mas incluem também a dis- cussão em torno da construção das masculinidades, pro- blematizando de que forma elas têm sido colocadas em 1 Anabela Maurício de Santana Anabela Maurício de Santana 155 discurso, como apontam os trabalhos de Connel (1995), Corrigan, Connel e Lee (1985), Louro (1995) e Peres (1995), entre outros. discurso, como apontam os trabalhos de Connel (1995), Corrigan, Connel e Lee (1985), Louro (1995) e Peres (1995), entre outros. A noção de estereótipo, ao contrário da no- ção de representação enfatizada pela análi- se cultural, está focalizada na representação mental. Nesse movimento individualizante, deixa-se de focalizar, precisamente, aquilo que na análise cultural é central: a cumpli- cidade entre representação e poder... Nessa perspectiva, o estereótipo é combatido por uma terapêutica da atitude. Sem negar que a mudança de atitude possa ter algum papel numa estratégia política global, o interesse da análise cultural está centrado nas dimen- sões discursivas, textuais, institucionais da representação e não nas suas dimensões indi- viduais, psicológicas (SILVA, 2011, p. 21). Feminismo e a Construção da Categoria Gênero Não podemos abordar o conceito de gênero sem lem- brar de Butler (2003), que basilarmente, nos aponta o gênero como culturalmente construído, diferenciando de sexo (biologicamente natural). Essa compreensão é que abre as possibilidades de reflexão com vistas à su- peração do preconceito de gênero, da visão do ser fe- minino como frágil e submisso. Homens podem até ter maior força física, mas as mulheres podem também ter mais energia (o que seria uma diferenciação biológica), porém, a diferença não pode significar desigualdade. Ho- mens e mulheres podem ser diferentes biologicamente, mas devem ter socialmente os mesmo direitos e deveres, pois ambos apresentam a mesma potencialidade inte- lectual e amorosa, que pode ou não ser desenvolvida, dependendo das oportunidades e possibilidades ofere- cidas pela família, pela sociedade, pela cultura. Assim, Butler (2003, p. 26) afirma que “[...] não a biologia, mas a cultura se torna o destino”. É importante assinalar que a categoria “gênero” tem passado por significativas transformações, possibilitando-lhe assim um caráter mais dinâmico. A princípio, vinculada a uma variável binária arbitrária, que reforçava dicotomias rígidas, passou a ser compreendida como uma categoria relacional e contextual, na tentativa de contemplar as complexidades e conflitos existentes na formação dos sujeitos. Para Harding (1993) é possível aprender a aceitar a inconstância das categorias analíti- cas e encontrar nelas a almejada reflexão teórica acerca de determinados aspectos da realidade política em que vivemos e pensamos e, por conseguinte, usar as próprias instabilidades como recurso de pensamento e prática. No entanto, faz-se mister salientar que o conceito de gê- nero tem sido utilizado de diversas maneiras, às vezes de forma equivocada ou mesmo banalizada. Alguns traba- lhos, por exemplo, apresentam enfoques neutralizantes e fixos, colocando o conceito de gênero como sinônimo de papéis sexuais, estereótipos sexuais ou de identida- des sexuais. Outrossim, muitas autoras e autores por sua vez têm assegurado a limitação do conceito de papéis, visto que os mesmos não permitem uma discussão mais extensa a respeito de poder, violência e desigualdade (SCOTT, 1990; LOURO, 2010). Um dos problemas relacio- nados à abordagem de papéis é que estes se reduzem a formas muito específicas, como por exemplo, o papel de esposa, de mãe, sendo utilizado para referir-se a um ideal normativo de comportamento ou mesmo assinalar estereótipos de papéis em relação ao homem e à mulher. Nesse sentido, segundo Machado (1998, p. Feminismo e a Construção da Categoria Gênero 26) “o concei- to de gênero supera o de papel sexual, por sua demar- cação mais frontal contra o determinismo biológico”. O mesmo pode ser dito em relação ao conceito de estereó- tipo, assim Tomaz Tadeu da Silva em seu artigo A poética e a política do currículo como representação assinala que: Construindo identidades de gênero e identidades sexuais A instabilidade ora mencionada nos remete também ao conceito de identidade, pois este tem sido estabelecido a partir de distintas abordagens teóricas. Algumas inter- pretações que tendem a buscar explicações de como se produzem as identidades de gênero ou mesmo as iden- tidades sexuais, baseiam-se em estruturas de interação muito restritas, por exemplo, a esfera familiar, ignorando o fato de que as relações de gênero estão atreladas a ou- tros sistemas sociais, econômicos, políticos ou de poder, como salienta Scott (1990). Alguns autores e autoras que se aproximam dos Estudos Feministas e dos Estudos Culturais têm concebido a iden- GÊNERO, SEXUALIDADE E EDUCAÇÃO 156 156 tidade, de forma mais ampla, como um processo flexível, plural. Dessa forma, Hall critica o conceito de identidade marcadamente fixa, unificada e estável, ao dizer que: identidade de gênero, nossa orientação sexual não pode ser determinada pela visão hegemônica de heterossexu- alidade como único padrão “normal”. O sujeito assume identidades diferentes em di- ferentes momentos, identidades que não são unificadas ao redor de um “eu” coerente. Dentro de nós há identidades contraditórias, empur- rando em diferentes direções, de tal modo que nossas identificações estão sendo continua- mente deslocadas (HALL, 1997, p. 13). Precisamos superar essa visão da heteronormatividade. É urgente entendermos que a sexualidade deve ser vi- vida naturalmente não dentro de padrões normativos, mas de uma forma que nos torne mais humanos e mais felizes, porém conscientes de nossas responsabilidades éticas e afetivas. O autor observa ainda que tais concepções remetem ao fato de que não existe uma identidade prévia, inata, mas processos identificatórios que vão se estabelecendo ao longo da existência, cujos processos são influenciados pelos diversos atravessamentos que constituem os sujei- tos - classe social, raça, etnia, religião, gênero, entre ou- tros. Assim, por estar sempre em formação a identidade, caracteriza-se pela incompletude. No entanto, mesmo estando todo o tempo em processo, a tendência é de imaginá-la como “resolvida”, “acabada”, “unitária”. Tanto as identidades de gênero quanto as identidades sexuais podem ser caracterizadas pela instabilidade, sen- do, portanto, passíveis de transformações. Dessa forma, torna-se arriscado constituir um momento determinado para que as identidades de gênero e as identidades se- xuais sejam “instaladas” ou “assentadas” nos indivíduos (LOURO, 2010). Relatos, análise e discussões Com o objetivo de fazer avançar a proposta da pesquisa, nota-se que a sociedade contemporânea, mediante polí- ticas públicas, vem sugerindo intervenções diferenciadas acerca da educação, das relações de gênero, da sexuali- dade aliadas ao debate étnico-racial, mercado de traba- lho, geração, entre outros. É uma discussão polêmica que evidencia um despertar da sociedade concernente à in- serção dessa discussão no âmbito da educação. Todavia, a questão é maior e mais profunda; inclui a inserção da discussão desde o ensino infantil, passando pelo ensino fundamental e médio, para então aportar na universida- de, que reflete os aspectos de ordens social, econômica e cultural de cada sociedade. A abordagem dessa temática deve ocorrer em um clima de confiança e de empatia. Sendo assim, durante a pes- quisa com os dois casais de lésbicas, houve a preocupação em criar uma atmosfera de confiança/segurança para que as respondentes pudessem expor seus pontos de vistas. A entrevista abordou os temas ligados à idade, escolariza- ção, profissão, trabalho, configurando o seguinte quadro: As respondentes apresentam entre 26 a 42 anos de idade e relatam que mantém união estável homoafetiva, mas que passaram por diversos problemas no município de Itaporanga d’Ajuda. Foram ofendidas por muito tempo, no entanto, para elas, as piores ofensas partiram da família. Até há pouco tempo, imagens e textos que retratassem a homossexualidade e/ou a lesbianidade de forma me- nos estereotipada eram raridade. Assim, a amostra foi composta por quatro mulheres lésbicas, residentes em Itaporanga d’ Ajuda/Se, independentemente do nível de escolaridade, profissão, trabalho, idade e filhos. São elas3: Samanta, Sandra, Simone e Suely. Fui rotulada de louca por minha própria famí- lia. Confesso que cheguei a pensar que tinham razão, pois foi difícil aceitar que gostava de mu- lher, tive medo. Cheguei a frequentar igrejas evangélicas [...] nos momentos de descobertas, pensei ou é loucura ou é coisa do diabo [...] e pensava: estou possuída e preciso de ajuda, sou pecadora. Foi horrível, minha família falava que eu estava vendo muita novela e que tudo era também efeito da modernidade da globaliza- ção, mas hoje estou feliz, mesmo diante de todo o preconceito (Samanta). Samanta tem 42 anos, graduada em Contabilidade. Ela trabalha em um escritório de contabilidade na ci- dade de Aracaju/Se e presta serviços particulares de contabilidade para algumas pessoas na cidade de Ita- poranga. Construindo identidades de gênero e identidades sexuais O fato de nascermos com um determi- nado sexo biológico feminino e/ou masculino não é sa- tisfatório para determinar a maneira como iremos sentir, expressar e viver nossa sexualidade, ou construir nossa Assim, podemos apontar a necessidade de que pais, mães, professores/as, psicólogos/as infantis e demais profissionais voltados para o cuidado/educação de Anabela Maurício de Santana 157 Suely tem 38 anos, com ensino médio completo e cursos profissionalizantes de: Assistente administrativo e servi- ços de secretariado. Trabalha na secretaria de uma escola particular em Aracaju/Se e convive maritalmente com Samanta e não tem filho/a. Suely tem 38 anos, com ensino médio completo e cursos profissionalizantes de: Assistente administrativo e servi- ços de secretariado. Trabalha na secretaria de uma escola particular em Aracaju/Se e convive maritalmente com Samanta e não tem filho/a. crianças tenham uma visão de infância/criança que dê conta dos efeitos da cultura popular em suas autoima- gens e suas visões de mundo. Examinar os materiais didáticos e paradidáticos voltados para as crianças pe- quenas, bem como os diversos objetos culturais, brin- quedos, filmes, entre outros, são fundamentais para perceber de que forma eles trazem concepções de gênero, sexualidade, raça/etnia, geração, nacionalida- de pautadas muitas vezes pela desigualdade. Em um mundo marcado pela diversidade, é fundamental não compactuarmos com a ideia de que as diferenças sejam transformadas em desigualdades. Sandra tem 32 anos, com ensino médio completo e cur- so técnico em enfermagem. Trabalha em dois hospitais particulares na cidade de Aracaju/Se, convive marital- mente com Simone há seis anos aproximadamente e re- side em casa própria, tem um filho com 16 anos. Simone tem 26 anos, é estudante de Educação Física de uma Universidade pública do Estado de Sergipe, no mo- mento encontra-se desempregada, mas antes trabalha- va como técnica em enfermagem. Convive maritalmente com Sandra e não tem filho/a. Construindo identidades de gênero e identidades sexuais Desde que nascemos, estamos nos for- mando como sujeitos, com múltiplas identidades, de gê- nero, de etnia, religiosas, sexuais, entre outras, embora muitas vezes estes aspectos sejam ignorados, sendo vis- tos apenas sob a perspectiva essencialista. Isso indica que a identidade de gênero refere-se à forma como alguém se sente, identifica-se, apresenta-se para si próprio e aos que o rodeiam, bem como relaciona-se à percepção de si como ser “feminino” ou “masculino”, ou ambos, independentemente do sexo biológico ou de sua orientação sexual, ou seja, da sua maneira subjetiva de ser feminino ou masculino, de acordo com condutas ou papéis socialmente estabelecidos. Dentro da perspectiva dos Estudos Culturais, cabe às professoras e aos professores ultrapassar seus papéis de meros transmissores/as de informação, uma vez que eles/as são produtores/as culturais profundamente im- plicados/as nas questões públicas, como tem afirmado Giroux (1995). É necessário, pois, ampliar a definição de pedagogia e currículo, não se limitando simplesmente ao domínio de técnicas e metodologias. Outro ponto importante reside no fato de que a linguagem deve ser estudada não como um mero dispositivo de expressão, mas como “uma prática histórica contingente, ativamen- te envolvida na produção, organização e circulação de textos e poderes institucionais” (GIROUX, 1995, p. 95). É importante analisar como a linguagem funciona para incluir ou excluir significados, assegurar ou marginalizar formas particulares de comportamentos. Nesse sentido, os textos não podem ser entendidos fora de seu contex- to de produção histórica, social e cultural. No que concerne a orientação sexual, entendemos que esta se refere ao sexo das pessoas pelas quais sentimos atração física, desejo e afeto. A sexualidade não se re- duz a instintos, impulsos, genes, hormônios, genitálias, ato sexual, nem se resume somente à subjetividade ou às possibilidades corporais de vivenciar prazer e afeto. A forma como vivemos e entendemos nossa sexualidade é construída historicamente, através de um processo con- tínuo, por meio do qual construímos nossa identidade pessoal e sexual, que emerge nos desdobramentos his- tóricos e culturais. Relatos, análise e discussões Convive maritalmente com Suely há quinze anos aproximadamente e reside em casa própria e não tem filho/a. Meu pai não falava nada, mas eu percebia que ele achava estranho meu comportamento, já GÊNERO, SEXUALIDADE E EDUCAÇÃO 158 ser entendido como uma variante natural da expressão sexual humana, um comportamento determina não uma maneira de viver diferente, mas igual. minha mãe, ela não perdoava [...] criticava e xin- gava (Simone). A minha própria família era a primeira a ofen- der com apelidos, quando eu saia de casa e ia para a escola [...] lá ouvia dos colegas os mes- mos apelidos (Suely). O preconceito torna-se um importante desafio/ enfrentamento fazendo com que, muitas vezes, es- tas mulheres vivenciem uma invisibilidade lésbica. Como aponta Godoy (1997, p.100) “as lésbicas vivem homoeroticamente no ‘pacto do silêncio’ e na clan- destinidade, contingência do fato de estarem inseri- das numa sociedade hegemonicamente patriarcal e heterossexual”. Ou seja, o fato de não haver uma acei- tação social e, principalmente, familiar faz com que muitas continuem escondendo ou não assumindo a sua orientação sexual em decorrência do preconceito e das situações que este pode levar na vida destas mulheres. Como o isolamento e enfretamento fami- liar; mudança de cidade e estado; não aceitação pelo pai e o distanciamento da mãe. Eu não nasci mulher, nunca enxerguei uma menina, na adolescência olhava no espelho e só via um menino, um belo rapaz, e fui per- cebendo que gostava de meninas e não de meninos (Sandra). Como nos revela Beauvoir (1967), em sua obra O Segundo Sexo, ninguém nasce mulher: torna-se mulher, visto que a fêmea humana assume o sexo que lhe é imposto, este castrado e colocado na condição de inferior ao homem. Essa autora afirma ainda que entre meninas e meninos, o corpo é, primeiramente, a irradiação de uma subjetivida- de, o instrumento que efetua a compreensão do mundo: é através dos olhos, das mãos e não das partes sexuais que apreendem o universo. Nesse sentido, é oportuno destacar que a lesbofobia, portanto, é uma prática social que naturaliza a hostili- dade, possibilitando práticas de aversão e repulsa con- tra mulheres não heterossexuais, bem como legitima os comportamentos de agressão – física, psicológica e insti- tucional – contras essas mulheres. A lesbofobia compõe o rol da discriminação caracterizado por “preconceito de gênero”, expressões da legitimação do patriarcado. Relatos, análise e discussões Relatam que percebem a intenção e que infelizmente muitas vezes acabam internalizando e, por conseguinte, respondem atra- vés de comportamentos masculinos3 por meio da fala (vocabulário tido como masculino), na maneira de sentar e de vestir-se. Para ele, “a lésbica é vítima de uma violência particular, de- finida pelo duplo desdém que tem a ver com o fato de ser mulher e homossexual” (BORRILLO, 2010 p. 26). A negação do papel atribuído às mulheres, principalmente ao papel da maternidade, provoca certo espanto, bem como uma repulsa da sociedade que não se conforma que a mulher não seja simples objeto adestrado para a passividade, sub- missão e procriação. Assim, a situação da mulher lésbica implica negar toda essa condição que tem sido imposta a suas vidas. Contraditoriamente, as mulheres são rotuladas e discriminadas em menor quantidade que os homens gays, só que esta constatação deve ser compreendida além da aparência de tolerância e aceitação. Segundo Goffman (1982), muitas vezes, o estigma está extremamente impregnado, tendo em vista que o indivíduo reproduz o estigma a ele atribuído, tor- nando-o identidade. A pessoa estigmatizada, inde- pendentemente do motivo, carrega em sua história de vida “identidades” atribuídas por outros indivídu- os. Outrossim, o estigmatizado (in)conscientemente procura uma identidade ou tenta afirmar sua identi- dade ou identidades. Se as lésbicas foram, visivelmente, menos perseguidas que os gays, tal comprovação não deve ser interpretada como indício de uma maior tolerância ao homossexua- lismo feminino, visto que essa indiferença nada mais é do que o sinal de uma atitude que manifesta um desdém muito maior. A sexualidade feminina é um instrumento do desejo masculino, assim torna impensáveis as rela- ções erótico-afetivas entre mulheres como assim expres- sa Borrillo (2010). São nessas condições que as mulheres lésbicas são exploradas e oprimidas pela desigualdade de gênero, de orientação sexual e identidade sexual e de gênero. São invisíveis na constituição da família, no acesso à saúde pública especializada e na previdência social. São rotuladas e estigmatizadas pelo preconceito que se expressa na lesbofobia e no machismo, sendo ca- racterizadas como “sapatão”. São vítimas no cotidiano do estupro “corretivo”, agressões físicas e psicológicas. Nes- se sentido, Brasil (2004) aponta que as mulheres lésbicas são alvo de atitudes de violência e discriminação: por se- rem mulheres e por serem lésbicas. No que concerne ao medo, as mulheres respondentes ressaltam que houve uma redução do sentimento de culpa sobre seus ombros. Relatos, análise e discussões Nes- se caso, os comportamentos machistas, sexistas, homo- fóbicos, transfóbicos, entre outros. Portanto, a lesbofobia configura-se como um instrumento de legitimação de uma hierarquia em torno da sexualidade e da identidade de gênero, sendo, portanto, um mecanismo responsável pela manutenção da ordem social patriarcal. Ter um relacionamento com alguém que tem um corpo, um órgão sexual que não te atrai é horrível, forçar a barra, forçar uma relação sexu- al sem desejo é frustrante. [...] tentei ser mulher, ser bissexual, cheguei a ter filho, mas não deu, pois me sentia castrada o tempo todo. Gosto de mulher e o feminino me atrai (Sandra). Sei que não sou aceita, ou melhor, que não so- mos aceitas, somos toleradas, mas penso que devemos viver, pois a vida é curta, devemos fa- zer o que gostamos e devemos nos relacionar com pessoas que desejamos, mesmo que para isso seja necessário pagar um preço (Samanta). Ela tem razão, pagamos um preço alto, mas acho que estamos certas em viver. Essa é a minha orientação sexual e devo ser respei- tada (Suely). Borrillo, por sua vez expande a compreensão dessa forma de discriminação como apenas ódio ou aversão, perpetrado por um determinado indivíduo. Identifica que essa conduta vai além do ato individual e caracte- rizando-a como “lesbofobia/homofobia geral”, que se- gundo o autor, Atestamos, portanto, que as pessoas que vivem um re- lacionamento homoafetivo certamente experimentam formas de sofrimento não pelas “escolhas” que fizeram, mas sim pela dor que é originada da intolerância, do estigma e do injusto preconceito social em virtude da orientação sexual. O comportamento homoafetivo deve [...] nada é além de uma manifestação do sexis- mo, ou seja, da discriminação de pessoas em razão do seu sexo (macho-fêmea) e, mais par- ticularmente, de seu gênero (feminino/mas- Anabela Maurício de Santana 159 e historicamente como masculinos ou femininos e assim constroem suas identidades de gênero. culino) Essa forma de homofobia é definida como a discriminação contra as pessoas que mostram, ou às quais são atribuídas, determi- nadas qualidades (ou defeitos) imputados ao outro gênero (BORRILLO, 2010 p. 26). Assim, as respondentes relatam que até hoje carre- gam o estigma e que ainda ouvem a expressão “mu- lher macho”, dentre outras. Relatos, análise e discussões O maior medo delas era a não aceitação de suas famílias, a rejeição de seus amigos, de seus colegas de trabalho, enfim, de todos, salientando que o medo muitas vezes faz com que a pessoa homos- sexual passe a viver em grupos sociais muito fechados, isto porque o medo e a visibilidade social só lhe trazem um desgaste emocional extremo. Quando questionadas acerca da escolaridade e da pro- fissão duas das quatro respondentes relatam que brin- caram muito no tempo de escola e que só concluíram o ensino médio e, por conseguinte, cursos profissiona- lizantes, mas que se arrependem. Tal arrependimento se dá em decorrência das dificuldades de inserção no mercado de trabalho por não ter uma graduação e nem qualificação suficiente. Quanto as outras respondentes, observa-se que uma é graduada em Contabilidade e a outra é estudante de Educação Física. Isso posto, Louro (2010) destaca que suas identidades sexuais constituir-se-iam, pois, através das formas como vivem sua sexualidade com parceiros/as do mesmo sexo, do sexo oposto, de ambos os sexos ou sem parceiros/as. Por outro lado, os sujeitos também se identificam social Fui uma grande boba, não estudei como deve- ria, brinquei o tempo todo [...] é uma pena, mas tenho que arcar com as consequências (Suely). GÊNERO, SEXUALIDADE E EDUCAÇÃO 160 Dessa feita, “a educação é um processo “natural” que ocorre na sociedade humana pela ação de seus agentes sociais como um todo, configurando uma sociedade pe- dagógica”, como salienta Pimenta (2010, p. 64). Não obs- tante, faz-se necessário destacar que: Estou muito feliz, com ela, só tenho o ensino médio, mas ela irá se formar este ano em edu- cação física. [...] acho tudo isso muito legal, estou feliz (Sandra). Estou muito feliz, com ela, só tenho o ensino médio, mas ela irá se formar este ano em edu- cação física. [...] acho tudo isso muito legal, estou feliz (Sandra). Estarei realizando um sonho, minha formatura é um sonho nosso, irei colar grau e ela será minha madrinha, entrará segurando minha mão e não estou nem ai para o que irão falar, [...] sei sim que seremos vítimas de olhares intolerantes, mas não estou preocupada, pois quero mais é ser feliz (Simone). A educação está presente em casa, na rua, na igreja, nas mídias em geral e todos nos envol- vemos com ela, seja para aprender, para ensi- nar e para aprender-e-ensinar. Relatos, análise e discussões Para saber, para fazer, para ser ou para conviver todos os dias misturamos a vida com a educação. Com uma ou várias. (...) Não há uma forma única nem um único modelo de educação; a escola não é o único lugar em que ela acontece; o ensino es- colar não é a única prática, e o professor pro- fissional não é seu único praticante (BRANDÃO apud PIMENTA, 2010, p 64). Sofri muitos e muitos preconceitos na escola, era chamada por colegas de mulher macho, entre outros apelidos que no fundo nos inco- moda. [...] as professoras demonstravam alguns olhares, gestos preconceituosos, inclusive che- guei a ouvir de uma professora a seguinte fra- se: não quer ser apelidada, não seja assim, não tenha comportamentos feios. Mas, aqui estou e não desisti dos estudos, fui em frente, hoje sou contadora, tenho minha própria vida e pago mi- nhas contas (Samanta). Os sujeitos que circulam o espaço da escola e do magis- tério diversificam-se e segundo Arroyo (2004), a escola influencia bastante nossas vidas. É dela que levamos há- bitos como gestos, formas de compartilhar, formas de raciocínio, levamos valores e também sentimentos. Cabe salientar que no Brasil4, a sociedade patriarcal de- lineou um perfil do que é ser homem e mulher. Deter- minadas características ao longo da história separaram o que é próprio de homem e de mulher; ou seja, o gê- nero determina não apenas quem faz o quê, mas tam- bém quem toma as decisões, uma vez que tanto homens quanto mulheres desempenham um papel produtivo e comunitário nas esferas familiar, cultural, educacional e social. Contudo, o homem comumente ostenta o papel de representação pública, ao passo que a mulher desem- penha um papel organizador fundamental, embora seja menos visível, o que favorece, dessa forma, o sexo mas- culino em detrimento da subordinação feminina5. Assim, Louro (2001) propõe, como possibilidade de ruir com o contexto de discriminação e homofobia, a adoção de uma pedagogia que escape dos enquadramentos, na qual o questionamento, a desnaturalização e a incerteza sejam estratégias para pensar a sexualidade polimorfa dirigida a múltiplas dimensões da existência, ou seja, uma pedagogia onde faltem proposições do modo de agir, a determinação do que transmitir, rompendo com binarismos e pensando a sexualidade, o gênero e os cor- pos de uma forma plural, múltipla e cambiante. Relatos, análise e discussões Confesso que é duro ver os olhares preconceituosos, o machismo dos cole- gas e das colegas também. Quando comecei na área, era bem pior, melhorou um pouco. Ser mulher já é difícil e mulher lésbica ainda mais. É duro sobreviver no mercado de trabalho, mer- cado ainda dominado por homens (Sandra). Tendo em vista a construção das relações sociais de gênero, é necessário explicitar o papel da divisão sexu- al do trabalho na conformação de desigualdades entre homens e mulheres. Não se tem a pretensão de abor- dar as formas pretéritas de configuração da divisão se- xual do trabalho em seu percurso inicial da existência humana, mas como no processo de desenvolvimento da humanidade, bem como das forças produtivas. Esta divisão perpetuou uma relação em que as mulheres vi- vem sob a órbita do trabalho reprodutivo e os homens no campo do trabalho produtivo. O mercado de trabalho é cruel, muito cruel e exigente. Hoje encarar o mercado de trabalho sem uma formação superior é horrível. Não basta ter um curso aqui ou ali, é preciso ter a formação e ser qualificado. Observo ainda que, sendo mulher, fica difícil e, sendo mulher lésbi- ca ainda pior (Suely). Ser mulher e encarar o mercado de trabalho já é complicado, a mulher tem que ser formada, ou seja, tem que ter uma profissão e ser qualificada. Ela tem que provar o tempo toda sua inteligên- cia e capacidade para os homens. Agora, sendo mulher lésbica [...], ela precisa provar ainda mais e em todos os lugares – para os homens e para as mulheres. Não podemos falhar em nenhum momento, pois se falharmos a culpa é por ser- mos mulheres e lésbicas (Simone). As relações sociais, por sua vez, têm uma base material dada pelo trabalho e estas se expressam através da di- visão social do trabalho entre os sexos. Logo, a divisão sexual do trabalho é a forma de divisão do trabalho so- cial que transcorre das relações sociais de sexo, sendo modulada histórica e socialmente. Contudo, vale citar que tradicionalmente ela atribui uma designação prio- ritária dos homes à esfera produtiva e das mulheres à esfera reprodutiva. Em nossa sociedade historicamente, o patriarcado tem se configurado como um sistema opressor manifestan- do-se em práticas de machismo, lesbofobia, homofobia e sexismo. Relatos, análise e discussões Esta é uma possibilidade real, à medida que: Não podemos mudar nossos padrões sexuais por decisão de um ou de muitos, assim como não podemos “desaprender” a língua em que aprendemos a falar. Mas se não podemos “de- saprender” nossas linguagens e sexualidades maternas e paternas, podemos aprender outras línguas (COSTA, 1992, p. 38). Abordar esse assunto desvenda a dinâmica da sociedade brasileira e como se anunciam as relações sociais, especi- ficamente de gênero, as quais, de forma permanente, (re) fazem-se seus componentes culturais e ideológicos, que essencialmente demandam funções sociais da educação formal e sua analogia com o mercado de trabalho. Logo, para falarmos sobre a educação6, devemos considerar a educação no sentido lato (informal ou social) e a educação no sentido exato, desenvolvida pela instituição escolar. A inserção da mulher na esfera pública do trabalho é extremamente importante no processo de democratiza- ção da vida social e, por sua vez, abrange a ampliação Anabela Maurício de Santana 161 Para Louro (2010), ao nos inserirmos nesta discussão, devemos ter em mente o reconhecimento acerca da existência de uma amplitude de divisões sociais, que provoca lutas e solidariedades bastante distintas e mui- to incertas e efêmeras. O mesmo sujeito pode vivenciar ocasiões de subordinação e dominação, ou, simultane- amente várias condições de subordinação e domina- ção. Logo, aceitar isso não sugere desconsiderar que alguns grupos, como os de mulheres, negros e negras e homossexuais, por exemplo, tenham vivido histórias mais longas, mais dolorosas e mais persistentes de subordinação do que outros grupos sociais. Significa considerar que dominações e subordinações não se so- mam de forma linear e ascendente, que elas ajustam-se de formas especiais e particulares e que necessitam ser versadas e discutidas em sua especificidade. da cidadania e dos direitos das (os) trabalhadoras (es). A participação feminina no mercado de trabalho brasilei- ro foi uma das mais importantes transformações sociais ocorridas no país a partir de 70, ampliando-se de for- ma acentuada e diversificada entre 1985 e 1995 (CRUZ, 2009, p. 107). Assim, as respondentes quando questio- nadas acerca do mercado de trabalho e profissões, rela- tam satisfação, angústia e medo. Tenho apenas o ensino médio e curso profissio- nalizante, sou técnica em enfermagem, traba- lho em dois hospitais em Aracaju e é do meu trabalho que tiro nosso sustento, no momento sou a única que contribuo com as despesas da casa, pois ela estuda. Relatos, análise e discussões Este sistema está baseado na lógica de subordi- nação das mulheres, prescrevendo normas e comporta- mentos a serem desempenhados por homens e mulhe- res, estabelecendo privilégios aos homens, em especial, os heterossexuais e conformando uma estrutura de su- balternidade do comportamento feminino. Na contemporaneidade a divisão sexual do trabalho é alia- da prioritária da concretização da mulher no espaço pri- vado. Ela manifesta-se no trabalho doméstico, tido como invisível, mas sem o qual seria impensável a reprodução da família, em que mulheres diariamente são responsabi- lizadas pelas tarefas do lar. A inserção da mulher no mun- 162 GÊNERO, SEXUALIDADE E EDUCAÇÃO 162 A negação desses padrões estabelecidos à mu- lher, em especial, no que diz respeito ao gênero e a sexualidade, vai conformar uma relação de opressão e controle duplicada. A negação da heteronormatividade será um elemento essen- cial para percebermos como as mulheres bis- sexuais e, sobretudo, as mulheres lésbicas são duplamente oprimidas e silenciadas no bojo da sociedade capitalista. A negação desses padrões estabelecidos à mu- lher, em especial, no que diz respeito ao gênero e a sexualidade, vai conformar uma relação de opressão e controle duplicada. A negação da heteronormatividade será um elemento essen- cial para percebermos como as mulheres bis- sexuais e, sobretudo, as mulheres lésbicas são duplamente oprimidas e silenciadas no bojo da sociedade capitalista. do do trabalho se dá prioritariamente nos espaços dos empregos precários, de baixos salários, de tempo parcial com forte exploração da força de trabalho. Além disso, as mulheres na atualidade têm combinado o trabalho dupli- cado/triplicado, no qual tem ocupado postos de trabalho do âmbito da produção da riqueza e da reprodução social. Devemos considerar que além da exploração do traba- lho, a estrutura patriarcal adere um modelo de compor- tamento sexual, tachando a sexualidade e impondo um comportamento heterossexual. Assim, tende a forjar um comportamento sexual dominante, abarcando em sua lógica a heteronormatividade que nega toda a constru- ção da diversidade sexual. Quanto aos sonhos e perspectivas, percebe-se que as mulheres apresentam o desejo de formalizar a união. Para duas das quatro respondentes foi relatado o sonho em adotar uma criança e, se possível, duas crianças. Estamos amadurecendo a ideia há dois anos e penso que agora é o momento certo. Acredito que seremos mães responsáveis. A ausência paterna não será problema, pois seremos mães presentes e participativas (Samanta). Relatos, análise e discussões Destarte, faz-se necessário ressaltar que a sexualidade, ainda que pereça um atributo biológico, relacionado ao sexo de cada indivíduo, também remete a uma cons- trução histórica, política e cultural, sendo praticamente impossível apreender a sua complexidade remetendo apenas a genitália de homens e mulheres, ou até mes- mo, o papel imposto às mulheres de serem exclusiva- mente agentes da reprodução. Logo, para construirmos uma abordagem sobre sexualidade é necessário fazer menção a símbolos, crenças, culturas relações de poder e visibilidade. Para isso, desnaturalizar a sexualidade é o caminho para apreendê-la para além dos determinismos biológicos. Assim, Prado destaca que: Temos a intenção de adotar, mas antes quere- mos ter um filho ou filha nossa. Ela irá conceber a criança, ou seja, ela será a mãe que irá gerar e eu serei a mãe que também irei gerar, mas de uma forma diferente [...]. Engraçado, a criança terá duas mães e um pai é claro. A presença dele será importante, não será negada a paternida- de, a criança irá conhecer (Sandra). A maternidade, independentemente da “expressão sexu- al” da mulher, permanece sendo um elemento de realiza- ção e afirmação do papel feminino. Para a mulher lésbica, a maternidade sempre é um desafio, pois esbarra não só nas limitações biológicas, mas também socioculturais e jurídicas7. O depoimento a seguir ratifica essa ideia: Nossos hábitos sexuais dependem exclusiva- mente da construção social das relações entre/ pelos seres humanos, relações que não existem em contextos abstratos, mas que estão sempre amalgamados pela concretude dos contextos culturais, geopolíticos padrões morais e posi- ções sociais (PRADO, 2008, p. 15-16). Ser mãe sempre foi o meu sonho, não nego que senti medo de não poder ter filho, pois tenho consciência de que na relação homoafetiva isso não seria possível. Agradeço a Deus todos os dias por ter colocado ela em meu caminho [...]. É uma pessoa maravilhosa, como qualquer casal, temos problemas e discutimos, porém os problemas fortalecem nossos sentimentos. Sei que, com a chegada da criança, nossas famílias ficarão mais próximas e [...] também é claro, eu acho [...] que a sociedade terá mais respeito por Feita essas considerações sobre a concepção de sexuali- dade, cabe ressaltar que essa se expressa em diversas for- mas. Acreditamos que a sexualidade compõe a chamada diversidade sexual, ou seja, partimos do pressuposto que não existe um modelo ou formato pronto para o com- portamento sexual humano. Relatos, análise e discussões Acreditamos que o campo de estudo da diversidade sexual amplia a compreensão sobre o comportamento e identidade sexual, negando a heteronormatividade. 1 Anabela Maurício de Santana Anabela Maurício de Santana 163 nós e aceitará melhor. Graças a Deus ela tam- bém sempre sonhou em ser mãe (Simone). É duro ser mulher. Agora ser mulher e ser lésbica ainda é mais difícil. A mulher é tratada como in- ferior na família, na sociedade, no mercado de trabalho, sinto na pele o tempo todo. Sou dis- criminada inclusive por mulheres, o que não deveria acontecer, pois elas também sofrem preconceitos (Samanta). nós e aceitará melhor. Graças a Deus ela tam- bém sempre sonhou em ser mãe (Simone). Esse relato indica um forte desejo de ser mãe e de realiza- ção do casal. Aponta também a maternidade como uma estratégia que visa sensibilizar as famílias, que até então rejeitam a relação homoafetiva, mostrando à sociedade a seriedade da união, humanizando, quem sabe, aqueles que permanecem rejeitando esses casais, Sei que quando estiver atuando em minha pro- fissão, professora de educação física, nas esco- las serei olhada, observada. Irei concorrer e te- nho que conquistar meus espaços no mercado de trabalho, pois sou mulher e lésbica (Simone). A educação familiar, religiosa e escolar reproduz, pois, as relações de gênero e suscita o debate sobre o respeito ao diferente e à pluralidade. A vida da mulher brasileira homossexual não é tão diferente da vida da mulher he- tero, uma vez que a discriminação social – que esta sofre é levada para o âmbito familiar, social e profissional –, representada pela baixa remuneração, pouca oferta de empregos, desprestígio profissional e exclusão familiar. Sempre estou passando por situações precon- ceituosas no trabalho. Trabalho na secretaria de uma escola, trabalham homens e mulheres, mais mulheres, porém somos o tempo todo co- locadas como inferiores. [...] os homens se sen- tem superior o tempo todo (Suely). Numa sociedade onde o valor de referência é derivado do eu, a família é importante à medida que vier possibi- litar meios para cada membro constituir-se como sujeito autônomo. Portanto, esta função da família põe em evi- dência suas contradições internas, pois, ao mesmo tem- po em que os laços de dependência são necessários, eles podem ser negados. Relatos, análise e discussões Assim, os relatos ora mencionados nos remete ao empode- ramento, no qual Horochovski e Meirelles (2007), com esme- ro, registram que a definição de empoderamento é próxima da noção de autonomia, pois se refere à capacidade de os indivíduos e grupos decidirem sobre as questões de respeito. Empoderar é o processo pelo qual indivíduos, organizações e comunidades angariam recursos que lhes permitam ter voz, visibilidade, influência e capacidade de ação e decisão. Sendo assim, o poder é adquirido no processo de socializa- ção, no qual o primeiro passo esta na socialização primária, ou seja, na família e depois na secundária (a sociedade) e, por conseguinte, é pertinente salientar que todas as pessoas tem condições de buscar, conquistar e garantir o poder, mas o po- der limitado não significa a destituição do poder. Diante do exposto, percebe-se que o modelo tido como tradicional de família – composta por pai, mãe e filhos – vem sofrendo inúmeras alterações. Estas modificações são capazes de modificar sua configuração, o seu funcio- namento e os papéis desenvolvidos pelos seus membros no contexto familiar, ou seja, as mudanças alteram além da composição familiar, porque é na família, bem como fora dela, que os indivíduos agregam valores/normas para o alcance da cidadania, que por séculos as mulheres foram excluídas. Assim, conforme Cruz (2009), a passa- gem das mulheres da exclusão para a inclusão, mesmo que parcialmente completa, deixa várias tensões não re- solvidas no que se refere à cidadania, que de forma resu- mida pode ser identificada como tensão entre direitos in- dividuais e direitos comunitários. Desse modo, a análise de gênero considera as diferenças como potencialmente inseparáveis da capacidade da cidadania, historicamente construídas e questionadas como norma de igualdade. Meu pai sempre demonstrou ter poder, minha mãe sempre o obedecia. A família o respeitava e obedecia, sempre respeitei meu pai e também minha mãe. Entretanto, para eles eu faltei com respeito, e meu pai vive dizendo que deveria ter tido mais poder (Suely). Minha mãe era quem mandava e desmandava nos filhos e filhas, mas obedecia meu pai, ela ti- nha medo dele, o cara mandava e desmandava nela e ela não tomava nenhuma atitude, não quero isso para minha vida. Quero respeitar e ser respeitada (Simone). 164 GÊNERO, SEXUALIDADE E EDUCAÇÃO 164 Isso posto, podemos enfatizar que muita coisa fica assim invisível. Relatos, análise e discussões Uma delas é a apropriação que o pai e a mãe acabam desenvolvendo sobre a vida de seus filhos/as. Depois de nascidos e registrados com o sobrenome da família, os/as filhos/as deverão obediência e respeito a eles. Os pais e as mães deverão cuidar deles/as e poderão então cobrar submissão. Assim, podemos enfatizar que muitos dos problemas familiares e dos conflitos entre eles/as e filhos/as, devem-se ao fato de os pais e as mães pensarem-se como responsáveis sempre por sua cria, pois ele/as sentem-se na obrigação de responder à so- ciedade pela educação que dão a seus filhos/as e isto os pressiona a comportamentos autoritários. Esta realidade fragiliza e esconde relações de parceria que poderiam se desenvolver no grupo familiar. A infância e a adolescên- cia têm sido conceituadas, significadas e mesmo vividas a partir de noções como estas. Conflitos entre pais/mães e filhos/as tornam-se cada vez mais freqüentes conforme os/as filhos/as conquistam sua autonomia. Em oposição, os pais/mães se colocam como proprietários deles/as e assim a rebeldia é produzida neste espaço familiar e nas relações que ali se constituem. mentos da história da sociedade que estão incorporados na forma de organização da família. O lugar da mulher, por exemplo, na família é determinado pelo seu lugar na sociedade e nas significações sociais. Na vivência familiar, tanto as mulheres como os homens constituir-se-ão a partir dessa referência, oferecendo parâmetros importantes para a constituição das iden- tidades femininas. O machismo é outro exemplo, uma vez que a cultura brasileira é machista e esses valores são reproduzidos nas relações familiares que se cons- tituem como aspectos importantes dos sujeitos que ali se constituem. O modelo para as relações afetivas tam- bém está ali na família. Relações de posse ou de parce- ria são fundamentais para a construção das subjetivi- dades. Assim, sujeito/subjetividade, família e sociedade estão no âmbito de um processo histórico que deve ser compreendido na sua dinâmica e na sua totalidade, para que se possa romper com leituras naturalizadoras e dar visibilidade às relações e à construção social das famílias e dos sujeitos/subjetividades. Notas As respondentes deste estudo relatam que o fato de não acharem necessário tornar pública sua orientação sexu- al, não significa que não achem importante a visibilidade que se tem ao se assumir. A exclusão e marginalização a que as mulheres lésbicas estão sujeitas reafirma a impo- sição da vivência clandestina e silenciosa das emoções, o não compartilhar seus amores, sonhos e seu cotidiano com a família, com os amigos. Este silêncio é uma ten- tativa de eliminar as diferenças, como se a sociedade, negando a lesbianidade e a homossexualidade, pudesse impedir, sua existência. 1 O sufragismo, movimento no qual as mulheres reivindicavam o direito ao voto, é considerado por muitos autores e autoras como a primeira onda do feminismo. Sobre a história dos deba- tes em torno das questões feministas, ver o artigo de YANNOU- LAS, Silvia, Iguais Mas Não Idênticos. In: Estudos Feministas, Rio de Janeiro, n. 1, 1994. 2 Os nomes das participantes foram trocados para garantir a privacidade delas. 3 Observa-se que para responder às ofensas, manter a “ordem” e o “respeito”, elas passam a reproduzir compor- tamentos tidos como não femininos, legitimando que a mulher deve ser feminina, doce, sensível, não fazer uso de palavrões e grosserias, pois estes comportamentos são es- pecíficos do homem. A pesquisa aponta a necessidade de trabalhar a dife- rença como uma ferramenta analítica, capaz de prover elementos que, além de descritivos, possam nos ajudar a articular o nível micro e macrossocial. De maneira que possamos por em causa os processos que marcam cer- tos indivíduos e grupos como distintos, e como, a partir da experiência da diferença, enquanto desigualdade, os sujeitos se constituem subjetivamente. 4 Observa-se que no Brasil a escola é, a priori, masculina e reli- giosa, visto que os jesuítas, para além da catequização dos ín- dios, investem na formação dos meninos e jovens brancos da elite. Logo, as primeiras escolas brasileiras regidas pelos jesuí- tas constituem-se, pois, num espaço marcadamente masculino, tendo como objetivo a formação de um católico exemplar. Não obstante, faz-se necessário salientar que esse modelo de ensi- no continua no país durante um longo tempo, mesmo depois de oficialmente afastado, ao final do século XVIII, como assim destaca Louro (2010). Breves apreciações conclusivas Outra questão importante é que as famílias estão sob a pressão social para equiparar-se ao padrão, mas, sem dúvida, constituem-se com suas idiossincrasias. Assim, as famílias não são todas iguais, mas todas elas serão anali- sadas e avaliadas a partir do padrão dominante. Em suma, sem a intenção de querer esgotar a temática em questão, percebe-se que a multifacetada sexualidade humana dificilmente será simplificada em apenas dois grupos: homossexuais e heterossexuais, uma vez que, certamente, a questão é extremamente mais complexa. Não me sentia bem com a minha família, achava que era um lar cheio de regras e mais regras. No entanto, também percebia a ausência do meu pai. [...] ele sempre estava nas ruas com amigos e amantes, enquanto minha mãe estava em casa, não trabalhava fora e a vida dela era cuidar da casa, dos filhos e do esposo (Suely). A complexidade dos relatos, muitas vezes, intrigantes, esclarecedores e emocionantes apontam para a impor- tância da realização de estudos sobre a questão da Les- bianidade, não só para visibilizar a temática, mas prin- cipalmente, para visibilizar as lésbicas, que vivenciam e expressam o seu desejo sexual e afetivo – assumindo ou não publicamente sua orientação sexual. Os relatos rati- ficam que é um desafio viver sem o reconhecimento, a aceitação social e a proteção legal. Que se assumir, por sua vez, implica uma vida de lutas, com dificuldades, me- dos, rejeições e aceitações parciais. Os relatos ainda mos- tram, o quanto é difícil ser lésbica numa sociedade hete- ronormativa, preconceituosa e discriminatória, onde as lésbicas são invisibilizadas por desejarem sexualmente Respeito minha família, mas nunca desejei con- tinuar tendo uma vida onde não tinha direito a nada, desejei uma vida diferente (Samanta). As formas de pensar o mundo e de nele se viver estão diretamente relacionadas às formas de pensar e agir do grupo familiar. É ali, o primeiro espaço de organização da subjetividade e não são apenas os aspectos pessoais dos/as pais/mães e irmãos e irmãs que se integram ao que o sujeito é. Há na constituição, como sujeitos, ele- Anabela Maurício de Santana 165 com seus pares? O que eles pensam sobre suas atitudes? O que leva uma família a rejeitar seu próprio membro? Que direito temos de dizer ao outro como deve conduzir sua vida afetiva? Como se dá o processo de aceitação da sexualidade? Breves apreciações conclusivas E o que leva o indivíduo a dizer “chega” para a opressão e a violência? e sentimentalmente outras mulheres, contradizendo a norma androcêntrica de um mundo, no qual as mulhe- res devem estar disponíveis para serem desejadas e para atenderem ao desejo dos homens. Uma vez identificado como ‘homossexual’ o sujeito difi- cilmente consegue proteger sua privacidade sexual do espaço público, pelo simples fato de ser sistematicamen- te interpelado em nome de sua preferência erótica. Notas Discutir as relações homoafetivas requer discutir cida- dania, relações de gênero, família, geração, religiosida- de e identidade, priorizando a discussão nas relações homem/mulher, mulher/homem, mulher/mulher e ho- mem/homem enquanto sujeitos com perspectivas, so- nhos e sentimentos individuais. 5 Todavia, mesmo diante do surgimento de uma nova mulher, ainda permanecem as divisões nas atividades que são ineren- tes ou de competência de cada gênero e que caracterizam a condição subordinada da mulher. Cabe lembrar que embo- ra ela desempenhe papéis diferenciados na sociedade atual, permanece de certa forma submetida à função de reprodu- tora da espécie. Ainda que a mulher contemporânea tenha uma educação que não reforça a subordinação ao homem no ambiente familiar e que esteja sendo preparada para partici- par, pensar e defender os seus direitos, não se submetendo ao poder masculino, deparamo-nos com a inexistência de uma política que garanta igualdade de direitos, remuneração, oportunidades de promoção e capacitação, conforme expres- sam Matos e Santana (2010). Assim, os momentos passados com as mulheres durante as entrevistas trazem mais dúvidas do que conclusões e remetem-nos a pensar no que de fato é ser homem e mulher. Além disso, diversas interrogações pairam acerca do que é ser mãe e pai! Qual é o papel da mulher e do homem na relação conjugal? O que leva os indivíduos a terem comportamentos preconceituosos e agressivos 166 GÊNERO, SEXUALIDADE E EDUCAÇÃO 166 ________________ O poder político e as mulheres nas eleições em Sergipe. In: Candeeiro. Revista de Política e Cultura da Se- ção Sindica dos Trabalhadores da UFS – ANO X v. 15 e 18, Jan./ dez 2009. 6 Segundo Matos e Santana (2010), a educação é transversal a toda a sociedade; apresenta-se no organismo social, ten- do como viés a sociedade, a história, a religião, o trabalho, o gênero, dentre outros. A família, a Igreja, a comunidade, os meios de comunicação, a escola, são algumas das faces da educação; algumas mais enfatizadas que outras, devido ao papel determinante na sociedade, mas em níveis diferentes, importantes e presentes na vida do indivíduo e no seu pro- cesso de socialização. ELIAS, Norbert. A sociedade dos indivíduos. Rio de Janeiro: Jorge Zahar, 1987. FELIPE, Jane. Sexualidade nos livros infantis: relações de gênero e outras implicações. In: MEYER, Dagmar (org.). Saúde e sexua- lidade na escola. Porto Alegre: Mediação, 1998. 7 Observa-se que é nesses novos arranjos familiares que surge a “família homoparental” – neologismo criado em 1997 pela As- sociação de Pais e Futuros Pais Gays e Lésbicas (APGL), em Paris, condição na qual pelo menos um adulto que se autodesigna ho- mossexual é e/ou pretende ser pai ou mãe de, no mínimo, uma criança – no qual vínculo afetivo se dá entre pessoas do mesmo sexo incluindo os casos da parentalidade de travestis e transexu- ais. Não obstante, tais uniões não possuem capacidade procria- tiva (no sentido biológico), embora seus componentes possam tê-la individualmente, conforme aponta Zambrano (2006). GIROUX, Henry. Praticando estudos culturais nas Faculdades de Educação. In: SILVA, T. T. (org.). Alienígenas na sala de aula: uma introdução aos Estudos Culturais em Educação. Petrópolis: Vozes, 1995. GIROUX, Henry. McLAREN, P. Por uma pedagogia crítica da representação. In: SILVA, T. T.; MOREIRA, A F. (org.). Territórios contestados: o currículo e os novos mapas políticos e culturais. Petrópolis: Vozes, 1995. GODOY. R.M. A voz das mulheres lésbicas: o discurso oculto ao desvendamento das vivências e do imaginário erótico. In: Revista do Núcleo de Estudos da Sexualidade. Florianópolis: NES, v.1, n.1, ago./dez.1997. Referências GOFFMAN, Erving. Estigma: notas sobre a Manipulação da Identidade Deteriorada. Rio de Janeiro: Zahar, 1982. ARROYO, Miguel G. Oficio de Mestre: Imagens e Auto-Imagens. Petrópolis, RJ: Vozes, 2004. HALL, Stuart. Identidades culturais na pós-modernidade. Trad. Tomaz Tadeu da Silva, BEAUVOIR, Simone de. O segundo Sexo. São Paulo: Difusão Européia do Livro, 1967. Guacira Lopes Louro. Rio de Janeiro: DP&A, 1997. BORRILLO, Daniel. Homofobia: História e crítica de um precon- ceito. Tradução Guilherme Joao de Freitas Teixeira. Belo Hori- zonte: Editora Autêntica, 2010. HARDING, Sandra. A instabilidade das categorias analíticas na teoria feminista. In: Estudos Feministas.Rio de Janeiro, n. 1, p. 7-32, 1993. BRASIL. Ministério da Saúde. Brasil sem Homofobia: Progra- ma de Combate à Violência e à Discriminação contra GLBT e Promoção da Cidadania Homossexual. Brasília: Ministério da Saúde, 2004. BRASIL. Ministério da Saúde. Brasil sem Homofobia: Progra- ma de Combate à Violência e à Discriminação contra GLBT e HOROCHIVISKI, Rodrigo Rossi. MEIRELLES, Giselle. Problema- tizando o Conceito de Empoderamento. In: Anais II Seminá- rio Nacional Movimentos Sociais, Participação e Democracia. UFSC, Florianópolis, 25 a 27 de abril de 2007. Promoção da Cidadania Homossexual. Brasília: Ministério da Saúde, 2004. BUTLER, Judith. Problemas de Gênero, Feminismo e subver- são da identidade. Rio de Janeiro: Civilização Brasileira, 2003. LOURO, Guacira Lopes. Gênero, sexualidade e educação: uma perspectiva pós-estruturalista. 11 Ed. Petrópolis, RJ: Vozes, 2010. CONNELL, R. Políticas da masculinidade. In: Educação e Reali- dade20(5): p. 185-206, jul./dez. 1995. ______. Produzindo sujeitos masculinos e cristãos. Veiga- -Neto, A. (org.). Crítica pósestruturalista e educação. Porto Alegre, Sulina, 1995. ______. Produzindo sujeitos masculinos e cristãos. Veiga- -Neto, A. (org.). Crítica pósestruturalista e educação. Porto Alegre, Sulina, 1995. CORRIGAN, T., CONNELL, R. & LEE, J. Toward a new sociology of masculinity. In: Theory and Society(5), 1985, p. 551-603. COSTA, J. F. A inocência e o vício: estudos sobre o homoerotis- mo. Rio de Janeiro: Relume-Dumará, 1992. ______. Gênero, história e educação: construção e desconstru- ção. In: Educação & Realidade, 20(2):101-132. 1995. ______. Gênero, história e educação: construção e desconstru- ção. In: Educação & Realidade, 20(2):101-132. 1995. CRUZ, Maria Helena Santana. Cidadania, crise do trabalho e i CRUZ, Maria Helena Santana. Cidadania, crise do trabalho e i CRUZ, Maria Helena Santana. Cidadania, crise do trabalho e gênero: desafios para estabilização dos direitos. Neves, Pau- lo S. C. (Org.). In: Educação, Cidadania e Questões Contemporâ- neas. São Paulo: Cortez , 2009. ______. Currículo, gênero e sexualidade. Porto Alegre: Porto Editora. 2001. 167 Anabela Maurício de Santana Anabela Maurício de Santana MACHADO, Lia Z. Gênero, um novo paradigma? In: Cadernos Pagu. Trajetórias do gênero,masculinidades... n. 11, Pagu – Nú- cleo de Estudos de Gênero. Campinas, Unicamp, 1998. MACHADO, Lia Z. Gênero, um novo paradigma? In: Cadernos Pagu. Trajetórias do gênero,masculinidades... n. 11, Pagu – Nú- cleo de Estudos de Gênero. Campinas, Unicamp, 1998. MATOS, Cândida Margarida de Oliveira; SANTANA, Anabela Mauricio de. A Influência da socialização Religiosa e do Gênero no Universo Acadêmico. In: IV Colóquio Internacional Educa- ção e Contemporaneidade. São Cristóvão/SE: UFS, 2010. MEYER, Dagmar. Gênero e Educação: teoria e política. In: LOU- RO, Guacira Lopes; NECKEL, Jane. Felipe; GOELLNER, Silvana Vilodre. (Org.) Corpo, gênero e sexualidade:um debate con- temporâneo na Educação. Petrópolis: Vozes, 2003, p. 9-27. MEYER, Dagmar. Alguns são mais iguais que outros: etnia, raça e nação em ação no currículo escolar. In: SILVA, L. H. (org.) A escola cidadã no contexto da globalização. Petrópolis: Vozes, 1998. PERES, Eliane T. “Templo de Luz”: os cursos noturnos mas- culinos de instrução primária da Biblioteca Pública Pelotense (1875-1915). Porto Alegre, 1995. (Dissert. de mestrado) PPGE- DU/UFRGS. PIMENTA, Selma Garrido. Docência no ensino superior. 4 Ed. São Paulo: Cortez, 2010. PRADO, Marco Aurélio Máximo. Preconceito contra homosse- xualidades: A hierarquia da invisibilidade. São Paulo: Cortez, 2008. SCOTT, Joan W. Gênero: uma categoria útil de análise histórica. In: Educação e Realidade. 16(2): 5-22, jul/dez. Porto Alegre, 1990. p. 05-22. SILVA, Tomaz Tadeu da. A produção social da Identidade e da diferença. In: SILVA, Tomaz Tadeu da(Org.). Identidade e Dife- rença: a perspectiva dos estudos culturais. 10 ed. – Petrópolis, RJ: Vozes, 2011. ZAMBRANO, Elizabeth. Parentalidades “impensáveis”: pais/ mães homossexuais, travestis e transexuais. In: Horizontes an- tropológicos. Porto Alegre, ano 12, n. 26, 2006, p. 123-147. Recebido em: 24/02/2014 Aceito em: 10/04/2014 Publicado em: 30/04/2014 Publicado em: 30/04/2014
W2802062429.txt	https://zenodo.org/record/2318692/files/article.pdf	en		85. Abstracts of Papers Presented to Section H at the British Association Meeting, 1916	Man	1,916	public-domain	5,861	85. Abstracts of Papers Presented to Section H at the British Association Meeting, 1916 Author(s): F. B. Jevons, Barbara Freire-Marreco, M. A. Murray, Professor Ridgeway, W. G. Collingwood, Hugh A. Fraser, R. R. Marett, Katherine Routledge, W. Scoresby-Routledge, M. A. Czaplicka, A. Trevor-Battye and I. H. N. Evans Source: Man, Vol. 16 (Sep., 1916), pp. 135-143 Published by: Royal Anthropological Institute of Great Britain and Ireland Stable URL: http://www.jstor.org/stable/2787531 Accessed: 27-06-2016 05:11 UTC Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at http://about.jstor.org/terms JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. Wiley, Royal Anthropological Institute of Great Britain and Ireland are collaborating with JSTOR to digitize, preserve and extend access to Man This content downloaded from 137.99.31.134 on Mon, 27 Jun 2016 05:11:46 UTC All use subject to http://about.jstor.org/terms Sept., 1916.) MAN. [No. 85. PROCEEDINGS OF SOCIETIES. Abstracts of Papers presented to Section H at the British 8 Association Meeting, 1916. Magic and Religion. By Dr. F. B. JEvoNs. Those proceedings alone are regarded as magical by any community which the community resents and condemns. Proceedings practised for the good of the community are ilot regarded by the community as magical. There is no reason to believe that there has ever been an " age of magic "-an age in which proceedings of the one kind alone were practised. If, then, ceremonies practised for the good of the commuinity are not magical, we ought to term them religious ; and since such ceremonies need not, and in some cases do not, conitain any reference to beings superior to man, we should set aside the definition which describes religion as belief in personal beings superior to man. Nevertheless, belief in such beings is essential in most forms of religion. The fact that no definitioni of an acorn can be a definaition of the full-grown oak does not disprove the continuity of the process whereby the acorn becomes an oak. "Tree" is a term which includes, or is applicable to, all stages in the process of growth, from the first to the last-to the acorni, the sapling, and the oak alike. Anid so, too, religion is a term which includes, or is applicable to, all stages in the one process, and not to the stage of monotheism alone, or polytlheism alone, or merely to stages in which there is reference to personal beings. Each of the stages is a stage in tiie process of religion, but no one stage is by itself the whole process. To assumie that belief in beinigs superior to man existed in the earliest stage of the evolution of religion is open to exactly the same objections as is the notion that the oak exists, "preformed," in the acorn. The evoluition of religion has been a process both of change and of continuity -of change in continiuity and of conitinuity in change-a process in which the very differences postulate similarity, and the similarity implies differences. Tlle earlier stages of religion would not have been practised unless they had been thought worth while-unless they were felt to have some value. And the value of religion is felt mainly, if not wholly, in the frame of mind, or state of spirit, produced. Such a state of mind or spirit is felt (e.g., by the Australian black-fellows) to be the highest of all. Its value, we may say, is felt to be supreme. Acceptinag Sir James Frazer's view that between magic and religion there is "a fundamental distinction anid even opposition of principle," we cannot hold with Dr. Marett that it is "best to treat all magico-religious rites as generically akin." Magic and religion are generically different. Amongst the Australian black-fellows, as everywwhere else, magic, in the opinion of the community, belongs to the class of tbitigs bad; and in every community religion belongs to the class of things good, and is suprenme in that class. From the point of view of tribes that believe in magic, there are rites which are magical and rites which are religious; but there are no rites which are " magico-religious," for to such tribes magic means what is condemiled by the community, while what is approved by the community belongs to the sphere of what we call religion. Personal Experience as an Elemnent in Folhtales. By BARBARA FREIRE-MARRECO. Psychologists have pointed out strikinig resemblances between dreams-especially childreni's dreams anid those of aduLlts of "infantile" mentality-and the myths of uncivilized peoples. There is a tendency to account for them by assuming that "' myths are the dreams of the race" or that "dream-thinking is an archaic form of thinkina." [ 135 This content downloaded from 137.99.31.134 on Mon, 27 Jun 2016 05:11:46 UTC All use subject to http://about.jstor.org/terms No. 85.J MAN. [Sept., 1916. On the coutrary, the writer believes that these resemblances are to be explained, not by a semi - mystical analogy between the childhood of individuals and a "childhood of the race," but by supposing that very many folk-tales are fournded on reported dreams, day-dreams, and trance-experiences. Some stories are professedly derived from personal experiences of this kindi; others bear internal evidence of such an origin. Examples of such types are given from American folklore-Visits to the Dead; Visits to the Stin; Sky-journey; Bridge of Souls; Symplegades; Cinderella; Beanstalk, etc. Some of these folk-tale incidents, founded on reports of personal experience of a fairly common type, naturally reappear in every gernerationi in all unscientific societies. Hence their geographical distribution is no evidence for the diffusion of cultures. But these incidents are re-handled, elaborated, systematized, combined with other incidents and put illto artistic form; and it may sometimles be possible to trace the diffusion of the more elaborate versions and combinations. Organisations of Witches in Great Britain. By M. A. MURRAY. One of the chief difficulties in the study of witcherafl is the lanLguage in which the records of the trials is couched. Another difficulty lies in some of the statements made by the witches themselves. But in spite of these difficulties it is clear that the vitches professed and practised a definite form of religion, with dogmas, rites, ceremonies, and festivals. The chief festivals or Sabbaths were held four times a year: at Candlemas, Roodmas, Lammas, anid Hallowmas, i.e., the four quarter days of the May-November year. Tlle master or chief of the witches, called by the Christian writers " The Devil," was regarded by the witcll-community as the incarnate god, incarnate in a mian or, when disguised in the skinl of ani animal, incarlnate irn that animal. The ritual of admission into the society is given with great particularity ; it consisted of renunciation of any previous religion, dedicationi of body and soul to the god of the convert's new religion, vows of absolute obedience, baptism anid the giving of a new lname, and finally either the sigining of a contract or being marked upon the body, possibly by tattooing. By the sixteenth and seveiiteenth centuries the whole ritual and religion were decadent, thougl in Scotland they remained in force till a later period than in England. The Origini of the Actor and the Mask. By PROFE.SSOR RIDGEWAY, Sc.D., F.B.A. An examination of the Greek drama and its descendants in Europe, arid also a survey of the dramas and dramatic dances of non-European races from Western Asia to Japan, through the Indian Archipelago, Australia, Melanesia, Polynesia, East and West Africa, South and North America (including the Eskimo) leads to the conclusion that tragedy and other serious drama originated in the bonouring or commemoration of the dead; such pantomimic dances, representing, the events in the life of the dead (as in anicient China), beinig, like funeral games, dirges, athletic contests, panegyrics. &c., a means of keeping the dead in remlembrance, and thus propitiating their favour. 1. The wearing of masks has been, and is, a concomitant of such m-iimetic dances ; as in Torres Straits, Ceram, and in the dances of the secret societies of Melanesia, Polynesia, West Africa, the object of which is the cult of the spirits of the dead, whilst masks are also used by the American Iindians and Eskimo in like ceremonies, as they are and were in the more hiahly developed dramatic performances of Java, China aiid Japan, Ancienit Greece and Rome. 2. In the cases cited the masks represent usually the spirit (often of some deified chief) in whose honour the ceremony is hield, and this holds true of the masks used by the Chinese and Japanese. [ 136 ] This content downloaded from 137.99.31.134 on Mon, 27 Jun 2016 05:11:46 UTC All use subject to http://about.jstor.org/terms Sept., 1916.J MAN. [No. 85. 3. But there are cases in which the dramatisation of the dead takes place even before the burial. Amongst the Tangkuls of Manipur the dead persoll is not only represented by some living member of the community, who dresses in the clothes of the dead, and takes his place at the family table, until the last rites are performed, but is actually regarded as the residence of the spirit of the defunct until its final send-off to the spirit-lanid. In other words, the Thilakapo is a medium. Again, in Burma, in the festivals of the thirty-seven official Nats (many of whom are individuals who lived only a few ceinturies ago), each Nat is supposed to enter for the time being the individual who personates him or her-in other words a medium. In ancient China the spirit of the ancestor when worshipped was supposed to enter a living persoin, usually a boy ; later replaced by an image of the dead, in its turn replaced by the well-known tablet, into which the ancestral spirit is supposed to enter when worshipped. In the Japanese Kagura (from wlhich arose Japanese Tragedy), which is an essenitial part of the Shinto ritual in honour of the dead, the spirit who is being honoured is supposed to enter the Miko (virgin priestess), who performs the sacred dance, whilst among the niumerous savage communities cited above it is geuerally held that the spirit of deity invoked enters the masked shaman or other performers. In the Hindu religious plays the actors are usually Brahmans, because for the time being they are taken to be equivalent to gods, a statemenit which points to a like idea as that found elsewhere. 4. Ancient Rome supplies a close analogue to the Thilakapo of Manipulr, for at funerals the dead man wvas personated bv an actor (mimus), dressed and masked to represent the dead, who even imitated his peculiarities of gait and speech. Moreover, attendants wearinig the masks (imagines) of the dead man's ancestors (which vere carefully preserved in Roman houses), and dressed to represent them, and if they had been consuls, etc., accompanied by lictors, etc., brought the dead nman to the family grave. Was the mimus once regarded as the mediurnm of the dead, and were the masked men also once regarded as the temporary receptacles of the aricestral spirits ? 5. Finally, Thespis, who first lifted Greek Tragedy from being a mere ritual at a tomi) into a great artistic and literary form, never wore any buit white masks. But as the Greeks represented by white paint the complexion of ghosts, for this reason Thespis probably wore only masks of this hue. If the actor was still regarded as the temporary abode of the hero's spirit, Solon's anger against Thespis is explained. 6. We are thus led to the conclusioln that the actor originally was not merely an actor but rather a medium. Early Christian Monuments in Northunzbria. By W. G. COLLINGWOOD, M.A., F.S.A. In the North of England anld South of Scotland there are about a thousand fragments representing monuments of types nleither Roman (anid earlier) nor Norman (and later). They include crosses, shrines, tombs, grave-slabs, and pieces of archlitectural detail, ornamented chiefly with plaits and scrolls, in miotives commion to Christendom, but applied in forms peculiar to the British islands. In classing them we lhave there- fore only occasional help from comparison with Continelntal art ; but whlen they are arranged in series, their development and dating can be cliecked from point to point by evidence of various kinds. At the beginninig of the series we may place the Whithorn giroup of unshaped stones with chi-rho monogram and early Latini inscriptions resembling those of the early Welsh Christians. These connect with St. Ninian's church and may date fifth [ 137 I This content downloaded from 137.99.31.134 on Mon, 27 Jun 2016 05:11:46 UTC All use subject to http://about.jstor.org/terms No. 85.] MAN. [Sept., 1916. or sixth century; but, like that church, the type disappears, leaving no immediate successor. On the other hatnd, monuments like the cross of Gosforth, Cumberland, must be of the late tenth or early eleventh century, because they bear allusions to the Norse edda, which was not current at that time; and they do not bear the late or Scandinavian runes seen on the Manx crosses of the late eleventh and twelfth centuries, otherwise analogous. A considerable series of Aniglo-Danish and AngloNorse monurnents connects with this group, and is marked by vigorous design and sketchy handling, rude figures of men and anlimals, simple plaitwork, usually zoomorphic, and the absence of foliage and flowers. It resembles stone-carving in Denmark and Scandinavia of the tenth and eleventh centuries ; but contains occasional Irish motives, explained by the connection of the Vikings in England with those of Irelanid. To the first-mentioned group was Welsh-Celtic, so some of these may be called more or less Gaelic-Celtic ; and the fact partly justifies the popular naame of Celtic applied to all such crosses, which were first known at Iona and in Ireland before the English examples were studied. But there remain many stones differing in their ornament from any Celtic and Scandinavian monuments, and of still greater interest, as finer forms of art and earlier in date. These bear fairly well-drawn saints and angels, elaborate symmetrical plaits, and leaf-scrolls like those of continental design in the eighth century. A close analogy is the Ormside cup, which can be shown to be earlier than 900 A.D. Eighthcentury coins of York bear figures of beasts such as occur in one group of this class. The inscriptions, in Latin and Anglo-Saxon, use, when runes are used, the older runes, which disappear in the tenth century; aind personal names are never of Danish, still less Norman, form. The acanthus of the eleventh century is absenit; all evidence points to a pre-Daniish date for this series, of which there were very fine examples at Easby, Cundall, Otley, &c., now reduced to fragments; and the much-disputed crosses of Beweastle and Ruthwell appear to be instances, better preserved, of the same series. In this series, schools and lines of development can be traced; the general form, the scrolls, and the plaits, &c., all show transition from continental models to the stock-patterlns of English carvers. By such hints the place of each can be approxi- mately found in the series, which went forward in full progress, from severity to floridity, until the Danish invasion of 867. The heathen Danes, rapidly converted, did not entirely destroy monumental art, but used it; at first continuing the English traditions, but naturally in a state of decline. Many examples remain of the transition from the pre-Danish Anglian to the Viking Age style, showing how the latter is an adaptation of the former by the gradual debasement of figure-drawing, the simplifying of interlaced patterns, and the conversion of scroll-work, foreign to Viking taste, into the dragonesquie ornament of the tenth century. In this process the Leeds cross is a link between the debased Anglian and nascent Scandinavian, dating about 920 A.D. The history of Northumbrian sculpture can, therefore, be stated broadly, and illustrated step by step, though much remains to be worked out in detail. Starting from the Tyne valley. where the free-staniding ornamented cross appears to originate after the building of Hexham, Jarrow, and Monkwearmouth clhurches, the art spread along main (old Roman) routes in every direction over the old kingdom of the northern Angles, from the Forth to the Humber, and in the later eighth and the ninth centuries influenced neighbouring countries. When the Danes and Norse came they accepted anid gradually adapted the art, transforming it to their own taste. During the eleventh century it disappeared from Northumbria, though surviving in Ireland and Scotland, and was followed in England only by the boundary, market and station-crosses of the post-Conquest periods. [ 138 ] This content downloaded from 137.99.31.134 on Mon, 27 Jun 2016 05:11:46 UTC All use subject to http://about.jstor.org/terms Sept., 1916.] MAN. [No. 85. Artificial Islands in the Lochs of the Highlands of Scotland. Excavation Work on the Crannog in Loch Kinellan, Strathpeffer. By HUGH A. FRASER, M.A. In the 1913 Report a grant was made by the Carnegie Trust to Dr. Munro for the excavation of the island in Lochi Kinellan. In August 1914 I started work on the island, anid was fortunate in having the assistance of the Rev. Odo Blundell at the outset, and later on the advice of Dr. Munro, who visited the island, and stayed in the vicinity for a week. The work done in 1914 established the island as artificial, a point on which there was previously some doubt. Pits dug over the surface of the crannog revealed in every case a platform of logs or brushwood, or compact occupation debris, underneath a superinicumbent mass of earth, clay, and stones somne 4 feet thick. Unfortunately, digging was greatly impeded by water percolating through the structure of the island from the loch. This not only delayed the work, but caused additional labour, which exhausted the grant before the work had reached anything like a conclusive stage. Persuaded that more could be gleaned from a careful examination of the pits than was learned in 1914, I started work again in 1915. On examining the woodwork with care, I found quite a number of logs with checks, mortise holes, &c. In no instance, however, did the most careful examination reveal these checks and mortise holes as serving any primary purpose. Everything drove one to the con elusion that some at least of the wood used for strengthening the structure of the island had previously been used for some other purpose. At the east end of the island the overlying mass of earth and stones appears to rest on a platform of brushwood; in the centre and at the west end it rests on wooden platforms. Two pits at the east end, duig to the base of the island, showed underneath the surface material successive layers of occupation de6bris right down to the original lake bottom, some 7 feet below the present surface. In selected pits situated at the centre and west enid of the island, the wooden platLorms were pierced and were found to consist of three layers of logs or tree stems. Underneath the platforms there seems to be a succession of layers of habitation debris corresponding to those found at the east end of the island. In course of the excavations bones, whole and broken, and other kiaids of food refuse were found in profusion, as were also pottery shards in the upper strata. The bones have been examined and discussed by Professor Bryce, of Glasgow University, while the pottery has been described by Mr. Curle, Director of the Royal Scottish Museum. The pottery is at present being compared with the pottery found in the Glastonbury Lake Dwellings. The archebological relics include a number of stone implements, one or two whorls, and an ivory playing piece. Late in the season a dug-out was discovered supportinig the logs in one of the pits. A length of 20 feet was exposed when the late autumn floods stopped work for th e year. From the poinit of view of structure the results obtaiined have been interesting, and if continued may prove very valuable archveologically. Any approximation to the date of the island, or the dates of its various eras, can onily be made after careful comparison of the results with those obtained at other sites-work that involves much labour anld time. While further work on the island is very desirable, such work to be of value must be on a more ambitious scale than the funds available have hitherto permitted. The facts that continuous layers of occupation refuse exist right up from the original bed of the lake, and that much of the woodwork overlying these layers, and supporting the surface material, shows signs of having been previously used structurally, would point to the site's having been originally the location of a pile dwelling [ 139 ] This content downloaded from 137.99.31.134 on Mon, 27 Jun 2016 05:11:46 UTC All use subject to http://about.jstor.org/terms No. 85.] MAN. [Sept., 1916. or palifite, the de6bris from which formed the basis of the more modern crannog. While this suggestion is made tentatively, the theory was not sought, but was reached as a possible and very probable explanation of many circumstances noted in course of the investigation. Recent Arch&rological Discoveries in the Channel Islands. By R. R. MARETT, M.A., D.Sc., President of Section H. The most important finds of the year have been due to the continiued excavation of the cave kniown as La Cotte de St. Brelade, in Jersey, the expenses of the work being borne partly bv the British Association and partly by a Government grant provided through the mediation of the Royal Society. Very good results were obtained in 1915, the remains of twenty-eiglht quaternary species being determined, and many flake implements of a characteristic Mousterian facies being collected. Moreover, along the eastern wall of the cave, where the implementiferous bed is 10 feet thick, two clearly marked horizons were distinguished, the lower stratum containing coarse implements in association with Elephas ? trogontherii, and the upper finer and more elongated implemenits in association with Elephas prirnigenius anid with a rich rodent bed in which Myodes torquatus is the only lemming represented. On September 3, after some two months' steady digging, the roof of the cave collapsed, obliterating the workings for the time being under about 500 tons of rock rubbish, an amount increased to 700 tons by the winter rains. During the spring the intrusive matter was cleared away, an affair of eight weeks' work, and the bed was again attacked in July. Good progress has been made along the western wall, which is more sheltered, and masses of fresh bone and flint await analysis. The floor level, which up to 45 feet from the entrance rises only about 4 feet, would seem suddenly to become steeper, as if the back of the original cave were being approached, though the limit of the bed lhas not yet been reached. Moreover, the rodenit remains, which mark the top of the bed, now appear in some places as high as 35 feet above floor level. Only when the eastern side has been cleared, will a theoretical reconstruction of the whole site be possible. In the meantime, one cannot wonider enough at the extent and richness of the human deposit. Apart from this major operation, there has been much archinological enterprise shown in both Jersey and Guernsey. In the latter island certain dolubtful indications of palmaolithic inhabitants have appeared, while in Jersey an industry thought to be Magdalinian has been recovered from several sites. Some interesting Neolithic finds have also been made. Altogether, the islands have proved worthy of their reputation as happy hunting grounds for the archmeologist. Recent Culture on Easter Island and its Relation to Past History. By KATHERINE ROUTLEDGE. Native culture lasted on Easter Island till about the years 1863 and 1864. On the former date half the population was carried off by Peruvian slave raiders, and the following year Christian missionaries arrived. In 1914 about a dozen old men still survived who possessed some knowledge of old institutions. The island, according to these authorities, was divided between ten clans, who practised cannibalism and were constantly at war, and legendary lore largely deals with these conflicts. Little information was forthcoming with regard to the statues, although the last one which remained standing on the terraces was apparently overthrown as recently as about 1830. Knowledge still, however, survives of the custom of distending [ 140 ] This content downloaded from 137.99.31.134 on Mon, 27 Jun 2016 05:11:46 UTC All use subject to http://about.jstor.org/terms Sept., 1916.] MAN. [No. 85. the lobe of the ear, and of tatooing a ring on the back, both of which customs are seen on the statues. Large wooden images in honour of certain persons were, within living memory, erected temporarily in front of the terraces. The small wooden images are still made, though now only for sale. Belief existed in a large number of supernatural beings, but there were few ceremonies in their honour. A special sanctity attached to the Miru clan, which was the only one which bad an "Ariki" or chief. This Ariki was the authority on tbe tablets, and gatherings, at which they were read, were held till the Peruvian raid. One old man was interviewed who had had some knowledge of one of the scripts. The "white men who came in ships" were regarded as gods, and ceremonies held in their honour were traced back tbree generations. The whole life of the island turned on the finding of the first egg of a certain migratory sea-bird. The rites coinnected with it show some slight connection with both the tablets and the images, and survived in an attenuated form even after the introduction of Christianity. Megalithic Remains on Easter Island. By WV. SCORESBY-ROUTLEDGE. The investigations of the Expedition extended over sixteen months, and the printed statements and explanations of former passing visitors were considered and checked on the spot. The Terraces exist principally along the coast, but a few are fouind inland. They were discovered to vary in type, and only a limited number of them have been constructed to carry images. All have been used for the disposal of the dead. The statues upon them have invariably faced inland and have generally worn crowns. A portion of one image only is now standing and the Terraces are largely in ruins. The mountain, with its quarries whence the great monoliths were derived, was surveyed and much excavating done, with the result that it is possible to speak definitely as to the method of sculpture and the tools employed. Certain prostrate and scattered images, generally supposed to have been abandoned in process of removal, were found to have beeln originally erected on three main roads converging on the mountain. The village of Orongo, colnsisting of special stone houses of peculiar construction, conniected with the Bird Cult, was accurately surveyed, and the large rock masses which adjoin the village, and which are engraved and sculptured, were mapped and photographed. Contribution to the Study of the Physical Type of the Northern Tungus. By Miss M. A. CZAPLICKA. All that Chinese historians tell us about the Tungus (who are kniown under various names), in the era before Christ and in early historical times, is that they have occasionally given dynasties to some parts of China and Mongolia. In this case, inter-marriage between the Tungus and foreigners was restricted to the royal family and the families of the chiefs. Occasionally we hear of Chinese migrations into Tuungus country, as for instance to Korea, but the mixture of Tungus with Chinese and Mongol assumed large proportions oiily in the seventeenth century, when the Manchu dylnasty was reigning over both China and Mongolia. Only the Tungus who migrated from the Amur country before that tilne (probably as a consequence of the Jinghis Kan migrations) escaped contamination. By migrating to the inhospitable lands of the northern taiga and tutndra they preserved their physical type comparatively pure. This applies chiefly to the North Central Tuiigus, between the Yenisei and the Lena, for the North-eastern Tungus have been more affected by contact with the Palkeo-Siberians and the Yakut. Even in the study of the comparatively pure type of the Tuiigus of North Central Siberia, however, we have to take into account their contact with the Yakut along the [ 141 ] This content downloaded from 137.99.31.134 on Mon, 27 Jun 2016 05:11:46 UTC All use subject to http://about.jstor.org/terms No. 85.J MAN. [Sept., 1916. Yessei-Khatonga line, and also the influence of environment. This latter is most clearly seen in their religious and social customs and in their technique. The anthropological study undertaken by our Expedition deals with the Tungus whose genealogical table shows no foreign admixture for several generations back, as well as with the TUDn,IgS who have inter-married with the Yakut. The Tungus metises we have divided into three groups 1. The Ttungus-Yakut, or people with Yakut father or mother. 2. The Dolgan, or people who have mixed with the Yakut for so long that they have formed a new nation and forgotten their origin. 3. The Yakut of Tungus territory, or TunguLsized Yakut, who have a straini of Tungus blood in them and are called Tungus by the Yakut of the Yakut territory. In the present paper we make an analysis of four standard measurements(1) The stature, (2) The cephalic index, (3) The facial index, (4) The nasal index, and compare our measurements on North Central Tungus with those on Northeastern Tungus taken by the Amnerican Jesup Expedition. In their cephalic, facial, and nasal indices the North-eastern Tungtus approach the Palaeo-Siberians, and the Southern or Baikal Tungus approach the Mongol type, while the North Central Tungus approach the North-eastern, but not so closely the Palieo-Siberian. In other words, the North-eastern Tungus stand between the North Central Tungus and the Palmo-Siberians. It would be premature lo draw any synthetic conclusions about the original physical type of the Tungus, as the material available for the Southern Tungus is insufficient, and as the only data on the North Central Tungus are those collected by our Expedition, and that only in the region within the Arctic Circle. Numerous tribes of Sub-Arctic Tungus between the Yenisei and the Lenia remain yet uLntouched3. The analysis of the measurements taken by our Expedition may be useful niot only in defining the physical type of the Tungus, but also in showing that while the first generationl of Tungus-Yakut mixture approaches nearer to the Yakut type, the Dolgan, who are the result of many generations of mixture, approach nearer to the Tungus type. Summer and a Winter Among the Natives of Arctic Siberia. By Miss M. A. CZAPLIC'KA. The start in spring 1914. The journey by the Trans-Siberian Railway and by steamer to tle mouth of the Yelnisei. The anthropological work of summer 1914 among the Samoyed-Tavgi, Samoyed-Yurak, Dolgani, and Ostyak. Some native customs connected with marriage, and clan and family life. Shamanistic cerernonies of the Samoyed. Winter 1914-15 spent in journeying with reindeer sledges among the Tungus of the Northern Tunguska, Khatonga, and Kheta Rivers and the Lake Districts of the northern tundra between the Yenisei and the Lena. Methods of investigation. Tungus clan and family life. The shamanistic beliefs existing under the cloak of Russialn orthcdoxy. The migration of the Arctic Tungus from the Amur country. The journey south, summer 1915. An archoeological excursion to the burial places (kurgany) along the Southern Yeniisei. [ 142 1 This content downloaded from 137.99.31.134 on Mon, 27 Jun 2016 05:11:46 UTC All use subject to http://about.jstor.org/terms Sept, 1916.] MAN. [Nos. 85-86. The Gurkha and his Mountain Home. By A. TREVOR-BATTYE, M.A. F.L.S. The writer visited Nepal with Mr. H. J. Elwes in the winter 1913-14, at the invitation of the resident and with the pernmission of the Maharaja. Nepal may be described as consisting of three zones-a niorthern mountain area containing the world's highest peaks, a central highly cultivated valley, and a southern forest area, known as the Tarai. Each has its special faunia, flora, and other characters. The bulk of the inhabitants occupy the central valley, whichl is terraced as far as possible for purposes of cultivationi. The population numbers some 500,000, made up of elements from various races. On the Sikkim border are the Lepchas, to the north the Bhotias or Thibetans, while the central valley is occupied mainly by Gurkhas and Newars. The Gurkhas claim to be the descendants of Rajputs, and appear to have first obtained a footing in the country in the year 1559, though it was not till 1768 they completed its conquest. The race they conquered, the Newars, were of Mongolian affi-nities, an industrial and not a warlike people. These characters are still preserved-the Gurkhas being the fighters, the Newars the traders, agriculturists, and craftsmen of Nepal to-day. Intermarriage with the Newars has changed the facial appearance of the Gurkha from the Rajput to the Mongoliani type. In religion the Gurkha may be broadly described as Hindu, the Newar as Buddhist. The Gurkha language is of an Aryan type, with Sanskrit as a basis, while the Newar has a distinct tongue and alphabet of his own. There are over 2,000 temples and shrines in the sparsely-inhabited country. Two distinct types of tenmple may be recognised: the stupa or chaitya form, which is Indiaii, although it has taken on a local character ; and the pagoda form, obviously derived from the Chinese. These are characterised by the wealth of detail in their carvings. The domestic architecture of Nepal is most varied inl design and workmaniship, the Newars from time immemorial have been great craftsmen in wood anid metal. Sakai Religion and Beliefs. By 1. H. N. EVANS. It is doubtful whether the Sakai have any original knowledge of a Stupreme Being, though one group of theem admits that it has a belief in a Deity. There seem, however, to be some grounds for thinking that their ideas on this subject may be derived from the Malays, or, at any rate, in part. Somewhat vaguie animist beliefs play a part in the everyday life of the Sakai, and various means are adopted for placating, or exorcising, spirits, who are, or may be, evilv-inclined towards them. Rites with these ends in view are ofteni performed by the Halak, or nmagician, aided by his familiar spirit. In addition to beliefs which may be classed as animistic, the Sakai have many other curious superstitions, which are less easy to classify. ANTHROPOLOGICAL NOTES. ACCESSIONS TO THE LIBRARY OF THE ROYAL ANTHROPOLOGICAL INSTITUTE. (Donor indicated in parentheses.) AlIy Yoruba Alphabet. By R. E. Delnnett. 81 x 51. 45 pp. Macmillani and Co. Is. 6d. net. (Ptublislers.) 86 Outlines of Jainism. By JagmanderIal Jaini, M.A. Edited (with Preliminary Note) by F. W. Thomas. 71 x 5. xi + 146 pp. Cambridge University Press. 4s. net (Jain Literature Society.) [ 143 1 This content downloaded from 137.99.31.134 on Mon, 27 Jun 2016 05:11:46 UTC All use subject to http://about.jstor.org/terms
https://openalex.org/W4377104555	https://www.frontiersin.org/articles/10.3389/fnmol.2023.1142852/pdf	English	null	Bibliometric and visual analysis of microglia-related neuropathic pain from 2000 to 2021	Frontiers in molecular neuroscience	2,023	cc-by	16,921	OPEN ACCESS EDITED BY Silke Neumann, University of Otago, New Zealand REVIEWED BY Yayun Wang, Air Force Medical University, China Livio Luongo, University of Campania Luigi Vanvitelli, Italy 1 Lanzhou University Second Hospital, Lanzhou, China, 2 Orthopaedics Key Laboratory of Gansu Province, Lanzhou, China Background: Microglia has gradually gained researchers’ attention in the past few decades and has shown its promising prospect in treating neuropathic pain. Our study was performed to comprehensively evaluate microglia-related neuropathic pain via a bibliometric approach. Zhang SB, Zhao GH, Lv TR, Gong CY, Shi YQ, Nan W and Zhang HH (2023) Bibliometric and visual analysis of microglia-related neuropathic pain from 2000 to 2021. Methods: We retrospectively reviewed publications focusing on microglia- related neuropathic pain from 2000 to 2021 in WoSCC. VOS viewer software and CiteSpace software were used for statistical analyses. Front. Mol. Neurosci. 16:1142852. doi: 10.3389/fnmol.2023.1142852 © 2023 Zhang, Zhao, Lv, Gong, Shi, Nan, Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Results: A total of 2,609 articles were finally included. A steady increase in the number of relevant publications was observed in the past two decades. China is the most productive country, while the United States shares the most-cited and highest H-index country. The University of London, Kyushu University, and the University of California are the top 3 institutions with the highest number of publications. Molecular pain and Pain are the most productive and co-cited journals, respectively. Inoue K (Kyushu University) is the most-contributed researcher and Ji RR (Duke University) ranks 1st in both average citations per article and H-index. Keywords analyses revealed that pro-inflammatory cytokines shared the highest burst strength. Sex differences, neuroinflammation, and oxidative stress are the emerging keywords in recent years. Conclusion: In the field of microglia-related neuropathic pain, China is the largest producer and the United States is the most influential country. The signaling communication between microglia and neurons has continued to be vital in this field. Sexual dimorphism, neuroinflammation, and stem-cell therapies might be emerging trends that should be closely monitored. microglia, neuropathic pain, bibliometric analysis, CiteSpace, VOSviewer, visual analysis TYPE Original Research PUBLISHED 18 May 2023 DOI 10.3389/fnmol.2023.1142852 TYPE Original Research PUBLISHED 18 May 2023 DOI 10.3389/fnmol.2023.1142852 © 2023 Zhang, Zhao, Lv, Gong, Shi, Nan, Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Bibliometric and visual analysis of microglia-related neuropathic pain from 2000 to 2021 OPEN ACCESS EDITED BY Silke Neumann, University of Otago, New Zealand REVIEWED BY Yayun Wang, Air Force Medical University, China Livio Luongo, University of Campania Luigi Vanvitelli, Italy CORRESPONDENCE Hai-Hong Zhang zhanghaih_1968@163.com RECEIVED 12 January 2023 ACCEPTED 28 April 2023 PUBLISHED 18 May 2023 CITATION Zhang SB, Zhao GH, Lv TR, Gong CY, Shi YQ, Nan W and Zhang HH (2023) Bibliometric and visual analysis of microglia-related neuropathi pain from 2000 to 2021. Front. Mol. Neurosci. 16:1142852. doi: 10.3389/fnmol.2023.1142852 Frontiers in Molecular Neuroscience frontiersin.org KEYWORDS Introduction Neuropathic pain is a more common but rather severe and intractable disease than any other chronic pain disease (Torrance et al., 2006), which often presented as spontaneous but persistent pain, nociceptive hyperalgesia, and allodynia (Zhao et al., 2017). The widely accepted definition of neuropathic pain is caused by an injury or disease of the somatosensory system (Jensen et al., 2011). Unlike nociceptive pain which protects against noxious stimuli, neuropathic pain is a Frontiers in Molecular Neuroscience Frontiers in Molecular Neuroscience 01 frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 and reflect the current research hotspots and frontiers (Wu et al., 2022). Thanks to advances in visualization technology, we used bibliometric software packages [CiteSpace (Chen, 2006) and VOSviewer (van Eck and Waltman, 2010)] to analyze and visualize potential trends in microglia-related neuropathic pain. We searched and collected relevant literature from the Web of Science core collection (WoSCC). A comprehensive analysis of this literature’s annual output, authors, countries/regions, affiliations, journal-related information, keywords, and references was also conducted (Chen and Wang, 2020). The contributions of academic groups and prominent researchers were objectively assessed to identify a fundamental overview of the field. Secondly, we identified the body of knowledge on the research topic by reviewing and analyzing the co-cited references. Finally, keyword co-occurrence and clustering analyses were used to detect hotspots and their evolution from 2000 to 2021. And CiteSpace’s Burst Detection function is used to identify emerging topics that may evolve into research hotspots in the future (Yang et al., 2022). maladaptive response to injury of the nervous system (Costigan et al., 2009). Common causes of this disorder include postherpetic neuralgia, trigeminal neuralgia, analgesic radiculopathy, diabetic neuropathy, autoimmune diseases, cancer, and neurological damage from chemotherapy or trauma (Freeman, 2009). Even more problematic is the persistence of neuropathic pain. Numerous animal studies based on peripheral nerve injury have shown that neuropathic pain results from neural plasticity. In the peripheral nervous system (PNS) and central nervous system (CNS), it is manifested as peripheral sensitization and central sensitization, respectively (Ji et al., 2003; Basbaum et al., 2009). The persistence of neuropathic pain has continued to be an intractable and debated issue, which lacks effective therapeutic modalities (Costigan et al., 2009). Analgesic modalities such as acetaminophen, NSAIDs, or weak opioids are not effective in patients with neuropathic pain (Colloca et al., 2017). Frontiers in Molecular Neuroscience Method For a long time, research on chronic pain has generally been centered on neurons (Grace et al., 2021). However, accumulating evidence has suggested that microglia play a key role in the development and maintenance of neuropathic pain by interacting with neurons (DeLeo and Yezierski, 2001). Microglia are macrophage- like cells in the central nervous system (Du et al., 2017). Injured tissues or neurons release various mediators that lead to microglia activation, causing morphological changes and the release of pro-inflammatory and pro-injurious mediators (e.g., pro-inflammatory cytokines and chemokines) involved in the development and maintenance of neuropathic pain (Austin and Moalem-Taylor, 2010). These mediators increase excitatory currents or decrease inhibitory currents by activating key signaling pathways (e.g., MAP kinase pathways; Detloff et al., 2008), ultimately producing neuropathic pain. Although the specific mechanisms by which microglia produce neuropathic pain have not been fully elucidated, the available evidence suggests that targeting microglia for neuropathic pain remains promising, including targeting the MAPK signaling pathway [ERK (Inoue, 2006), p38 (Ji and Suter, 2007), JNK (Ji et al., 2009)], antagonizing upstream activators of microglia [e.g., P2X4 (Inoue, 2006) and MMP-9/2 (Li et al., 2016)], targeting downstream mediators released by microglia [e.g., TNF-α, IL-1β, IL-6 (Yang et al., 2020) or BDNF (Coull et al., 2005)] and secreting anti-inflammatory (Tao et al., 2016) and analgesic mediators (Huang et al., 2017) via microglia. Introduction The traditional approach to managing patients with neuropathic pain remains through conservative medication, with first-line management including tricyclic antidepressants, pregabalin, and gabapentin (Finnerup et al., 2015; Colloca et al., 2017; Moisset et al., 2020). However, these pharmacological treatments have been proven to be effective in less than half of patients with neuropathic pain and various adverse effects have been observed (Finnerup et al., 2015; Moisset et al., 2020), so there is an urgent need to develop new therapeutic options that are safe and provide long-term relief (Rasche et al., 2006; Morgalla et al., 2017). Basic studies and clinical trials may find drugs that target new mechanisms of action and hold promise for alleviating neuropathic pain through new therapeutic targets (Hone et al., 2018). Among these, new strategies for modulating neuron–glia interactions in neuropathic pain conditions hold considerable promise (Ahmad et al., 2021; Ruiz-Cantero et al., 2021). Reading publications on microglia in neuropathic pain, including reviews, basic research, and clinical trials, allows us to keep abreast of the latest advances and the most outstanding contributions to the field. However, the hotspots and frontiers in this field are constantly updated, so a concise summary of the relevant areas is lacking. Consequently, a comprehensive analysis and summary of the current state of research, key areas, and research perspectives on microglia- related neuropathic pain will give researchers new insight into the academic framework for grasping microglia-related neuropathic pain and help them to formulate future scientific work. frontiersin.org Data acquisition and cleaning Researchers can use co-occurrence analysis to identify trends and hot spots in a subject. Small (1973) initially proposed a method of co-citation analysis in 1973 to analyze the relationships and structure of academic fields. Unlike citation analysis, which evaluates the quality of a topic by the number of citations, co-citation analysis helps scholars quickly discover the structure and characteristics of a target field of research by screening out a representative selection of documents for analysis and then using citation network analysis to display them into various clusters (Liao et al., 2018). Currently, the co-citation analysis has been widely used to reveal the relationships between authors, articles, and journals (Liao et al., 2018). Burst analysis is an algorithm developed by Kleinberg to understand the rapid growth in the popularity of references or keywords over a defined period of time (Kleinberg, 2003). Citation Burst analysis enables researchers to understand how fast-changing literature transforms the knowledge landscape of a scientific field and reveals the cutting-edge research junctions that are active today (Chen, 2006). FIGURE 1 Flowchart describing the literature selection process. analysis. The cleaned data were then imported into VOSviewer for bibliometric analysis. VOSviewer, developed by Eck and Waltman, uses a probabilistic- based approach to data normalization and provides a variety of visualization views in the areas of co-authorship, co-citation, keywords, etc., including Network Visualization, Overlay Visualization, and Density Visualization, which provides easy mapping and beautiful graphics for large bibliometric maps, as well as powerful features for co-occurrence analysis, co-citation analysis, and bibliographic coupling analysis (van Eck and Waltman, 2010). VOSviewer software was used to systematically analyze and visualize the distribution and collaboration of countries/regions, institutions, journals, authors, and co-occurrence of keyword clusters. In VOSviewer maps, the node’s size indicates the total number of co-citations, co-authorship, co-occurrence, or bibliographic coupling for that item. Larger nodes indicate more contributions for that item; the largest nodes are highlighted in red. A line between two nodes indicates that both items have been cited in the same document, and a shorter line indicates a closer relationship between the two items. The thickness of the line generally indicates the degree of co-occurrence, co-citations, and co-authorship (Gu et al., 2017). CiteSpace (5.6.R3) software, a bibliometric visualization tool developed by Chen, is widely used to analyze metrics such as countries, institutions, authors, journals, keywords, etc. (Chen et al., 2012) and is particularly known for its Burst Detection feature. Data acquisition and cleaning In this study, CiteSpace was used to extract Citation Bursts for references and keywords to help identify research hotspots, current research status, and trends in the field (Chen, 2004). In the citation bursts for references and keywords, the blue line indicates the period in the graph, while the red line represents the period in which the reference burst occurred. Frontiers in Molecular Neuroscience Data acquisition and cleaning The Web of Science (WoS) core database from Clarivate Analytics was used for the bibliometric analysis. To avoid bias resulting from daily database updates, all articles related to microglia in neuropathic pain from 1 January 2000 to 31 December 2021 were retrieved and downloaded from the WoS Core Collection (WoSCC) database on 10 November 2022. Using the following search strategy: TS = (Microglia) AND TS = (“Neuropathic Pain” OR “Trigeminal Neuralgia” OR “Postherpetic Neuralgia” OR “Pain After Peripheral Nerve Injury” OR “Painful Polyneuropathy” OR “Painful Radiculopathy” OR “Painful Diabetic Neuropathy” OR “Diabetic Painful Neuropathy” OR “Chemotherapy Induced Peripheral Neuropathy” OR “Chronic Inflammatory Demyelinating Polyneuropathy” OR “Neuropathic Cancer Pain” OR “Spinal Cord Injury Pain” OR “Central PostStroke Pain”). Only research and review articles written in English were selected and other document types, such as letters, briefings, and meeting abstracts, were excluded (Figure 1). Two researchers (Zhang Shun-Bai and Zhao Guang-Hai) collected the main data separately. Any disagreements were discussed and negotiated. The search results were chosen as “Full Record and Cited References” and exported as a “Plain Text file” with download_*. txt format for storage. We create a VOSviewer thesaurus file to perform synonym merging (e.g., author name, organization name, country name), correct spelling differences, and remove meaningless words before importing the data into VOSviewer (version 1.6.18) for Bibliometric research uses quantitative methods such as mathematics and statistics to process the characteristics of literature, which can, to a certain extent, describe, evaluate and predict the current research status and development trend of a specific subject 02 frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 FIGURE 1 Flowchart describing the literature selection process. mapping in this article, each of which has its characteristics and can complement the other. Thanks to the development of the tools mentioned above, it is possible to help researchers create a knowledge structure, to understand the current state of research from a macro perspective, and to identify hotspots in target research fields. The most common types of research methods include cluster, co-occurrence, co-citation, and burst analysis. Cluster analysis is a statistical method of categorizing data according to their degree of similarity and aims to reveal the specific distribution of study content on a given topic (Ai et al., 2022). Briefly, co-occurrence analysis refers to two words frequently occurring in the same article and which may be more closely related than others. Countries A total of 66 countries/regions were covered in the 2,609 articles, of which 27 countries/regions published more than 10 articles (Figure 2B). The top 10 most influential countries/regions are listed in Table 1, along with their total number of publications (NP), total citations (NC), average citation frequency (AC), and H-index. The top 10 countries/regions published 87% (2,279/2609) of the publications. China was the leading country in terms of total publications (32.5%, 847/2609), followed by the United States (27.9%, 727/2609) and Japan (12.5%, 326/2609). The top three countries with the highest total number of citations were the United States (52,361), China (20,243), and Japan (15,970). The top three countries with the highest average citation frequency were the United Kingdom (84.76), Canada (82.07), and Australia (71.37). The top three countries in the H-index were the United States (Peng et al., 2021), the United Kingdom (Clark et al., 2007), and Japan (Milligan et al., 2004), with China (Zhuang et al., 2007) following closely behind. Annual publication trends for the top 10 countries in terms of output from 2000 to 2021 are shown in Figure 2C. Research on microglia-related neuropathic pain in the United States is central to global research, and research in China has become more active in the last decade. China initially lagged behind the US in the annual output of publications, but publications in this area have grown rapidly since 2012, overtaking the US in 2014, and will continue to grow rapidly through 2021. In addition, the US and Japan show a “fluctuating upward trend” in the annual output of publications. FIGURE 2 (A) Annual productions and citations in studies of microglia- associated neuropathic pain from 2000 to 2021. (B) Global distribution of national publications and intercountry cooperation related to microglia-associated neuropathic pain from 2000 to 2021. (C) The country’s annual trend publications related to microglia- associated neuropathic pain from 2000 to 2021. (A) Annual productions and citations in studies of microglia- associated neuropathic pain from 2000 to 2021. (B) Global distribution of national publications and intercountry cooperation related to microglia-associated neuropathic pain from 2000 to 2021. (C) The country’s annual trend publications related to microglia- associated neuropathic pain from 2000 to 2021. Figure 2B also illustrates the mapping of national collaborations. Bibliometric analysis and visualization maps This study was based on a bibliometric analysis of the number of publications and citations, H-index, year of publication, country/ region, institution, journal, author, citations, references, and keywords in the literature related to microglia in neuropathic pain. In general, the total number of publications (NP) and the total number of citations (NC) are widely used as the two main perspectives to reflect the level of productivity and impact (Wang et al., 2021). H-index is increasingly used as a useful indicator to assess researchers’ scholarly contribution and predict future scientific achievement (Eagly and Miller, 2016). Currently, H-index is used to evaluate individual scholarly achievement and is now extended to evaluate the scholarship of a country or region, an institution, or a journal (Jones et al., 2011). In addition, the WOS Website’s online “Citation Report” function is used to obtain the latest journal impact factors (IF), which are used to measure the quality and impact of the target journal (Chen, 2006). Microsoft Excel 2019 software and GraphPad Prism (version 8.0.2) were used to collate and plot data for the annual publications. We combined Scimago Graphica (version 1.0.23), a visualization tool for exploring and communicating data (Liu et al., 2022), with VOSviewer (version 1.6.18) to map the global distribution of national publications and inter-country collaboration (Figure 2B). In addition, VOSviewer and CiteSpace (version 6.1 R4) were used for knowledge 03 frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 FIGURE 2 (A) Annual productions and citations in studies of microglia- associated neuropathic pain from 2000 to 2021. (B) Global distribution of national publications and intercountry cooperation related to microglia-associated neuropathic pain from 2000 to 2021. (C) The country’s annual trend publications related to microglia- associated neuropathic pain from 2000 to 2021. consistently increasing trend, as shown in Figure 2A. The H-index is 151, which indicates a considerable number of highly cited articles in this research field. consistently increasing trend, as shown in Figure 2A. The H-index is 151, which indicates a considerable number of highly cited articles in this research field. Annual trend of publications The total number of annual publications (NP) over a period of time provides an objective indicator of the overall trends in a field. A total of 2,609 publications on microglia in neuropathic pain were published in the WoSCC from 1 January 2000 to 31 December 2021, including 2,234 papers (85.63%) and 375 reviews (14.37%). The literature covered 66 countries or regions and 1754 institutions. Figure 2A shows the NP on microglia in neuropathic pain. From 2000 to 2003, the number of articles published on related research was low. From 2004 to 2009, the NP increased rapidly as more scholars focused on the research mechanisms in this field, with the NP reaching 104 in 2009. What is striking is that in 2012 and 2016, there was a “boom” in article production. But with the end of these two “booms” came a slowdown in article production. The number of articles published yearly has increased from 106 in 2010 to 279 in 2021, and the growth rate has remained relatively stable. The 2,609 publications have been cited 120,112 times to date, excluding self- cited articles numbered 91,295, with an average citation frequency of 46.04 per article. Annual citations from 2000 to 2021 show a Frontiers in Molecular Neuroscience Countries It can be seen that China has established international cooperation with several countries/regions, with the US being the most collaborative, followed by Japan, Germany, the United Kingdom, Canada, Australia, and South Korea. The countries/regions with the highest number of publications (China, United States, Japan, United Kingdom, and Canada) also cooperate more closely. Funding source Cross-institutional collaboration can facilitate in-depth research in the field. Analysis of the institutional collaboration network mapping shows that the 119 institutions with more than 10 occurrences (threshold >10 papers) are distinguished into 8 clusters by different colors (Figure 3). According to the clustering analysis, the University of California System (Inoue, 2006), Harvard University (Detloff et al., 2008), the University of Toronto (DeLeo and Yezierski, 2001), the University of Texas System (DeLeo and Yezierski, 2001), the University of London (Grace et al., 2021), Fudan University (Ruiz-Cantero et al., 2021), Shanghai Jiao Tong University (Hone et al., 2018) and Kyushu University (Rasche et al., 2006) have collaborated and communicated extensively on the mechanisms of microglia in neuropathic pain. Adequate financial support plays a vital role in the development and advancement of science. Table 3 summarizes the top 10 funding agencies and sponsors in this field. The National Natural Science Foundation of China (NSFC) is the major funding agency in China. Half of the top 10 funding agencies, including the US Department of Health and Human Services (HHS), the National Institutes of Health (NIH), the NIH National Institute of Neurological Disorders Stroke (NINDS), the National Institute on Drug Abuse (NIDA) and the National Institute of Dental Craniofacial Research (NIDCR), are from the US. Meanwhile, Japanese research funding agencies, including the Grants in Aid for Scientific Research (KAKENHI) and Science and the Japan Society for the Promotion of Science (JSPS), reflect the strong research capacity of Japanese research institutions in this field. It is worth noting that the European Commission provides major funding support for European countries (including the United Kingdom, Italy, Germany, etc.). With sufficient funding, the US has maintained a leading position in microglia and neuropathic pain research. It is evident that the above institutions not only publish a large number of articles but also appear to have more widespread collaborations with others. US institutions often conduct their research with a transnational approach. Strong collaborations exist between the University of Toronto, the University of London, Shanghai Jiao Tong University, and Kyushu University. In contrast, cross-institutional collaboration in other countries is mainly through intra-national work. In China, for example, there is close collaboration between the Fourth Military Medical University, Capital Medical University, Wenzhou Medical University, and Fujian Medical University (Figure 3). Frontiers in Molecular Neuroscience Institutions Over 1755 institutions contributed to this field, with 110 publishing more than 10 papers. Table 2 summarizes the top 10 most impactful institutions, from China (3/10), the United States (3/10), the United Kingdom (2/10), Japan (1/10) Canada (1/10). The University of London (Bennett et al., 2016), Kyushu University (Soliman et al., 2021), University of California (Clark et al., 2009), and Shanghai Jiao Tong University (Clark et al., 2009) are the top 4 institutions in terms of the number of papers published, which is representative of the research capacity of the scientific institution in its field of study. The top 3 institutions in average citation frequency were Harvard University (AC = 161.23), the University of Colorado System (AC = 121.89), and the University of Toronto (AC = 111.64). And the top 3 research institutions in terms of H-index were the University of London (Tsuda et al., 2004), Kyushu University (Chen, 2004), and Harvard University (Small, 1973). 04 frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 TABLE 1 Top 10 most productive countries in microglia-related neuropathic pain from 2000 to 2021. TABLE 1 Top 10 most productive countries in microglia-related neuropathic pain from 2000 to 2021. Rank Country NP NC AC H-index Number of cooperating countries 1 China 847 20,243 23.9 65 22 2 United States 727 52,361 70.02 117 30 3 Japan 325 15,970 49.14 66 13 4 England 148 12,531 84.67 67 25 5 Canada 144 11,818 82.07 61 20 6 Korea 125 3,879 31.03 36 7 7 Italy 120 5,798 48.32 45 17 8 Germany 100 5,399 53.99 40 18 9 Taiwan 86 2,683 31.2 28 7 10 Australia 84 5,995 71.37 37 14 TABLE 2 Top 10 productive institutions in microglia-related neuropathic pain from 2000 to 2021. TABLE 2 Top 10 productive institutions in microglia-related neuropathic pain from 2000 to 2021. Rank Institution Country NP NC AC H-index 1 University of London England 85 8,220 96.71 51 2 Kyushu University Japan 82 7,771 94.77 45 3 University of California System USA 62 3,538 57.06 32 4 Shanghai Jiao Tong University China 62 1,239 19.98 22 5 Harvard University England 60 9,674 161.23 40 6 University of Toronto Canada 58 6,475 111.64 38 7 Fudan University China 58 2,839 48.95 28 8 University of Colorado System United States 55 6,704 121.89 35 9 University of Texas System United States 55 3,002 54.58 29 10 Sun Yat-sen University China 53 2,476 46.72 24 frontiersin.org Journals and co-cited journals A total of 540 journals published articles on microglia and neuropathic pain. Of these, 111 journals contributed at least five 05 frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 FIGURE 3 Analysis of the clustering of publications from different institutions. FIGURE 3 Analysis of the clustering of publications from different institutions. TABLE 3 The top 10 funding sources with the most publications. Rank Funding source Country NP NC AC H-index 1 National Natural Science Foundation of China (NSFC) China 526 12,761 24.26 54 2 United States Department of Health and Human Services (HHS) USA 471 40,838 86.7 108 3 National Institutes of Health (NIH) USA 470 40,861 86.84 108 4 European Commission EU 267 22,400 83.9 85 5 NIH National Institute of Neurological Disorders Stroke (NINDS) USA 232 24,740 106.64 85 6 Ministry of Education Culture Sports Science and Technology Japan (MEXT) Japan 186 6,546 35.19 46 7 NIH National Institute on Drug Abuse (NIDA) USA 148 13,652 92.24 62 8 Japan Society for The Promotion of Science (JSPS) Japan 135 4,079 30.21 37 9 NIH National Institute of Dental Craniofacial Research (NIDCR) USA 99 14,941 150.92 62 10 Grants in Aid for Scientific Research (KAKENHI) Japan 94 2,488 26.47 27 TABLE 3 The top 10 funding sources with the most publications. journal (10,958), followed by the Journal of Neuroscience (10,337), Glia (3,625), Neuroscience (3,573), and Proceedings of the National Academy of Sciences of the United States of America (3,223), all five journals with publishers from the US. Nature has the highest impact factor (69.504) among the top 10 co-cited journals. Additionally, five of the top 10 co-cited journals are in the Q1 JCR division, two in the Q2 JCR division, and the remaining three in the Q3 JCR division. papers. The top 10 most influential journals are listed in Table 4. The research interests of these journals focus on pain, inflammation, and immunity. Seven publishers are located in the United States; the remainder is from the Netherlands, United Kingdom, and Ireland. Molecular pain was the most prolific journal (109 articles, 4.178%), followed by Pain (107 articles, 4.101%) and the Journal of Neuroscience (81 articles, 3.105%). Brain Behavior and Immunity had the highest impact factor (19.227), followed by the Journal of Neuroinflammation (9.587) and Pain (7.926). Journal of Neuroscience had the highest total citations (10,549) and average citation frequency per article (130.23). Frontiers in Molecular Neuroscience Journals and co-cited journals Furthermore, five of the top 10 journals are in the Q1 JCR division, two are in the Q2 JCR division and the remaining three are from the Q3 JCR division. Co-cited reference and reference burst University has the highest average citation frequency (AC = 206.44) and the highest H-index (Gu et al., 2017). It is worth noting that the top two authors in terms of publications both belong to Kyushu University and have collaborated many times. Table 8 shows the top 10 most frequently co-cited articles, with “Quantitative assessment of tactile allodynia in the rat paw” (495 citations) published in the Journal of Neuroscience Methods (IF = 2.987) being the most co-cited article. In addition, two of the top 10 articles were written by Tsuda M and published in different journals. Overall, four of the top 10 co-cited articles were review articles and six were basic studies. The chronological distribution in Table 8 gives a general picture of the progression of microglia in neuropathic pain research. The majority of the top co-cited articles were published between 1980 and 2018, and those with >300 co-citations were written before 2010. Co-cited authors are two or more authors cited simultaneously in one or more papers (Xu et al., 2022). Figure 4A illustrates the network mapping of co-cited authors. The most prominent nodes are associated with the most frequently cited authors. Table 7 shows that among the 45,695 cited authors, 126 authors (grouped into 4 clusters in the map) were cited more than 100 times. In comparison, only 4 authors were cited more than 1,000 times, namely Tsuda M (1879 citations), Ji RR (1,368 citations), Watkins LR (1,207 citations) and Milligan ED (1,036 citations).h A total of 72,619 references were analyzed using VOSviewer software, with a minimum total number of citations set at 100, and a total of 80 references were included. The co-citation correlations were analyzed and visualized in Figure 5. In addition, VOSviewer divided the 80 references into 3 clusters, represented by red, green and blue. The red cluster consisted of 27 papers that examined the neuroimmune role of microglia in neuropathic pain; the green cluster consisted of 27 papers that focused on the intracellular signaling mechanisms of microglia in neuropathic pain, and the blue cluster consisted of 26 papers that mainly focused on the molecular mechanisms of microglia in neuropathic pain. The co-occurrence of authors was mapped using VOSviewer to identify collaborative relationships between authors (Figure 4B). Authors and co-cited authors Over 8,964 authors have published in this field of research. Of these, 81 authors have contributed over 10 papers to the field. Table 6 summarizes the top 10 academics regarding the number of publications. Inoue K from Kyushu University is the most prolific author (NP = 61, NC = 6,223, H-index = 42), and Ji RR from Duke VOSviewer found that 121 of the 5,916 co-cited journals reached the threshold (minimum number of citations >200). Of these, 32 journals had more than 1,000 co-citations and 14 had more than 2,000. According to Table 5, Pain was the most co-cited 06 frontiersin.org frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 Frontiers in Molecular Neuroscience 07 frontiersin.org Co-cited reference and reference burst Rank Author Affiliations Country NP NC AC H-index 1 Inoue K Kyushu University Japan 61 7,223 118.41 42 2 Tsuda M Kyushu University Japan 60 6,389 106.48 39 3 Watkins LR University of Colorado System United States 53 6,665 125.75 35 4 Ji RR Duke University United States 50 10,322 206.44 43 5 Mika J Polish Academy of Sciences Poland 48 2,371 49.4 27 6 Maier SF University of Colorado System United States 41 5,095 124.27 31 7 Zhang Y University of Colorado System United States 39 1,278 32.77 18 8 Malcangio M University of London England 35 3,746 107.03 27 9 Makuch W Polish Academy of Sciences Poland 34 1,433 42.15 22 10 Rojewska E Polish Academy of Sciences Poland 34 1,496 44 23 Rank Author Affiliations Country NP NC AC H-index 1 Inoue K Kyushu University Japan 61 7,223 118.41 42 2 Tsuda M Kyushu University Japan 60 6,389 106.48 39 3 Watkins LR University of Colorado System United States 53 6,665 125.75 35 4 Ji RR Duke University United States 50 10,322 206.44 43 5 Mika J Polish Academy of Sciences Poland 48 2,371 49.4 27 6 Maier SF University of Colorado System United States 41 5,095 124.27 31 7 Zhang Y University of Colorado System United States 39 1,278 32.77 18 8 Malcangio M University of London England 35 3,746 107.03 27 9 Makuch W Polish Academy of Sciences Poland 34 1,433 42.15 22 10 Rojewska E Polish Academy of Sciences Poland 34 1,496 44 23 FIGURE 4 The visualization map of co-citing and co-occurring authors for microglia-associated neuropathic pain. (A) Visualization map of co-citing authors. (B) Visualization map of co-occurring authors. The visualization map of co-citing and co-occurring authors for microglia-associated neuropathic pain. (A) Visualization map of co-citing authors. (B) Visualization map of co-occurring authors. total link strength = 7,678), “spinal cord” (occurrence = 666, total link strength = 4,256), “activation” (occurrence = 535, total link strength = 3,908), “rat”(occurrence = 509, total link strength = 3,177), “peripheral nerve injury”(occurrence = 385, total link strength = 2,503), “mechanical allodynia”(occurrence = 377, total link strength = 2,555), “inflammation”(occurrence = 318, total link strength = 1961), “dorsal-root ganglia”(occurrence = 298, total link strength = 1862), all topped the list, suggesting that the mechanism of microglia in neuropathic pain has been a continuous hotspot in the last two decades. Co-cited reference and reference burst The map shows that in the field of microglia-related neuropathic pain, there are several collaborative sub-networks with the scholars mentioned above as the core, with varying degrees of connectivity outside the sub-networks, but with strong collaborative links between the scholars within the sub-networks. It can be seen that the Watkins LR sub-network is less collaborative with the other sub-networks, with the reduction of clinically relevant pathological pain being the main focus of this sub-network. TABLE 4 The top 10 productive journals of microglia in neuropathic pain research. TABLE 4 The top 10 productive journals of microglia in neuropathic pain research. TABLE 4 The top 10 productive journals of microglia in neuropathic pain research. Rank Journal Country NP NC AC H-index IF (2021) Quartile in category 1 Molecular pain United States 109 4,078 37.41 38 3.370 Q3 2 Pain United States 107 8,189 76.53 50 7.926 Q1 3 Journal of Neuroscience United States 81 10,549 130.23 57 6.709 Q1 4 Brain Behavior and Immunity Netherlands 77 3,916 50.86 34 19.227 Q1 5 Journal of Neuroinflammation England 76 2,505 32.96 33 9.587 Q1 6 Neuroscience United States 76 3,623 47.67 35 3.708 Q3 7 Neuroscience Letters Ireland 53 1,224 23.09 22 3.197 Q3 8 Experimental Neurology United States 50 3,015 60.3 33 5.62 Q2 9 Journal of Pain United States 43 1941 45.14 27 5.383 Q1 10 Plos One United States 43 1,516 35.26 26 3.752 Q2 TABLE 5 The top 10 co-cited journals of microglia in neuropathic pain research. TABLE 5 The top 10 co-cited journals of microglia in neuropathic pain e top 10 co-cited journals of microglia in neuropathic pain researc p j g p p Rank Co-cited journal Country Citation IF (2021) Quartile in category 1 Pain United States 10,958 7.926 Q1 2 Journal of Neuroscience United States 10,337 6.709 Q1 3 Glia United States 3,625 8.073 Q1 4 Neuroscience United States 3,573 3.708 Q3 5 Proceedings of the National Academy of Sciences of the United States of America United States 3,233 12.779 Q1 6 Brain Research Netherlands 3,112 3.61 Q3 7 Nature England 2,840 69.504 Q1 8 Experimental Neurology United States 2,775 5.65 Q2 9 Molecular pain United States 2,636 3.370 Q3 10 Journal of Neurochemistry England 2,560 5.546 Q2 07 frontiersin.org frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 TABLE 6 The top 10 contributed authors in microglia-related neuropathic pain from 2000 to 2021. Co-cited reference and reference burst CiteSpace performed a burst analysis of the key references and keywords in our study. The top 25 references were ranked according to the strength of their burst, as shown in Figure 6. The reference with the earliest year of burst (burst years, 2012 to 2014) was published by Milligan ED and Watkins LR in 2009 (Milligan and Watkins, 2009). The strongest burst reference was a review article entitled “Microglia in neuropathic pain: cellular and molecular mechanisms and therapeutic potential” published in 2018 (Inoue and Tsuda, 2018), with a burst strength of 42.64 and a burst year of 2019–2021. Notably, among the top 25 references, Ji RR et al. wrote four articles with strong burst values. A keyword co-occurrence network map was constructed, including a cluster map, a time overlay map, and a density map (Figure 7A). A total of 90 high-frequency keywords (≥50 occurrences) were detected by VOSviewer, of which 5 keywords had >500 occurrences. The nodes with the same color belong to a cluster, which shows that the research directions in this field are divided into 4 categories. The red clusters (37 items) are mainly related to cellular and molecular mechanisms of microglia in neuropathic pain, such as “central sensitization of pain,” “activation of glial cells,” “p38MAPK,” “tumor necrosis factor-α,” etc.; the green clusters (22 items) mainly related to inflammation in the CNS, e.g., “spinal cord injury,” “inflammation,” Frontiers in Molecular Neuroscience Co-cited reference and reference burst TABLE 6 The top 10 contributed authors in microglia related neuropathic pain from 2000 to 2021. Rank Author Affiliations Country NP NC AC H-index 1 Inoue K Kyushu University Japan 61 7,223 118.41 42 2 Tsuda M Kyushu University Japan 60 6,389 106.48 39 3 Watkins LR University of Colorado System United States 53 6,665 125.75 35 4 Ji RR Duke University United States 50 10,322 206.44 43 5 Mika J Polish Academy of Sciences Poland 48 2,371 49.4 27 6 Maier SF University of Colorado System United States 41 5,095 124.27 31 7 Zhang Y University of Colorado System United States 39 1,278 32.77 18 8 Malcangio M University of London England 35 3,746 107.03 27 9 Makuch W Polish Academy of Sciences Poland 34 1,433 42.15 22 10 Rojewska E Polish Academy of Sciences Poland 34 1,496 44 23 FIGURE 4 The visualization map of co-citing and co-occurring authors for microglia-associated neuropathic pain. (A) Visualization map of co-citing authors. (B) Visualization map of co-occurring authors. General information on microglia-related neuropathic pain research From 2000 to 2021, a total of 2,609 original research and reviews were obtained by searching the WoSCC database. In terms of annual NP, a general upward trend was observed, but after 2009 and 2012 there were 2–3 years of stagnant growth. The lack of ground-breaking research is the primary reason for the stagnation. Between 2016 and 2021, annual NP enters a period of steady growth. It is expected that the literature in this field will likely continue to grow, and the research will become more in-depth (Figure 2A). The evolution of keywords over time was analyzed to obtain a comprehensive picture of the frontiers and hotspots in microglia- related neuropathic pain. The average time of the appearance in the document was overlayed on the keyword co-occurrence network to obtain a time overlay map (Figure 7B). The different colored nodes represent the average time that the keywords appeared in the literature, and the evolution of the research trends over time can be observed through this color variation. Clusters with more cyan nodes indicate the hotspots in this area around 2012, and clusters with more green and yellow nodes represent the latest research hotspots. Of the top-ranked countries, China ranks 1st in publication output (Figures 2B,C and Table 1). The United States, on the other hand, has been the driver of the highest academic contribution in this field for the past 22 years, as demonstrated by the combined performance of NP, AC, and H-index. Consistent with its economic strength, three US affiliates, five US funding agencies, and four US authors rank among the top 10 affiliates, funding sources, and authors, respectively, in studies of microglia-associated neuropathic pain (Tables 2, 3, 6). This indicates that the US has the best institutions, adequate financial support, and elite scholars, which largely account for the US being a leader in this field over the last 22 years. Similarly, Japan (AC = 49.14, H-index = 66) and the UK (AC = 84.67, H-index = 67), and Canada (AC = 82.07, H-index = 61) consistently maintain world-leading levels of academic productivity, suggesting that, in addition to adequate research funding, these countries keep a sustained focus and interest in the field. Compared to the countries mentioned above, China has seen a dramatic increase in NP over the past 22 years and has been No. 1 since 2014 when it overtook the US. Frontiers in Molecular Neuroscience Discussion Discussion “neuroinflammation,” “activation of microglia,” “CNS,” “Alzheimer’s disease,” “cytokines,” etc.; the blue clusters (18 items) mainly related to pathophysiological mechanisms of neuropathic pain, such as “hypersensitivity,” “hyperalgesia,” “allodynia,” “mechanisms,” etc.; the yellow clusters (13 items) focus on microglia and ATP receptors, such as “release,” “up-regulation,” “ATP,” “P2X4 receptors,” “P2X7 receptors,” “neurotrophic factors,” etc.h frontiersin.org Keyword co-occurrence, clusters, and burst As an important part of the article, keywords embody the core ideas of academic research and enable us to quickly grasp the highlights and directions of the research (Li et al., 2016). By cleaning the keywords based on VOSviewer, 7,641 were retrieved from 2,609 documents. The keywords were prioritized by occurrence and link strength, as shown in Table 9, such as “microglia”(occurrence = 1,256, 08 frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 TABLE 7 The top 10 co-cited authors in microglia-related neuropathic pain from 2000–2021. TABLE 7 The top 10 co-cited authors in microglia-related neuropathic pain from 2000–2021. Rank Author Affiliations Country Citation Total link strength 1 Tsuda M Kyushu University Japan 1879 8,604 2 Ji RR Duke University United States 1,368 8,452 3 Watkins LR University of Colorado System United States 1,207 6,736 4 Milligan ED University of New Mexico United States 1,036 5,489 5 Raghavendra V Dartmouth Medical School United States 748 4,327 6 Clark AK University of London England 712 4,180 7 Inoue K Kyushu University Japan 614 2,888 8 Zhuang ZY Harvard University United States 579 3,937 9 Woolf CJ Harvard University United States 575 3,397 10 Mika J Polish Academy of Sciences Poland 559 2,498 General information on microglia-related neuropathic pain research Its relatively low AC, however, suggests that scholars from Chinese institutions may require more in-depth work to enhance the quality of their research to reinforce their international impact. Density visualizations are uniquely useful in helping to understand the overall structure of the map and in quickly noting the most critical areas of the map. Each node in the keyword density map is colored according to the density of the items around that node. The density size is dependent on the number of surrounding items and the weighting of those items. Blue indicates low-density areas, and red represents high-density areas. It is obvious from Figure 7C that the highlights of microglia in neuropathic pain include the study of neuropathic pain, microglia, activation, inflammation, injury, and activation of glial. Figure 8 shows the top 25 keywords with the citation burst strength. The keywords with the highest burst strength before 2010 included “thermal hyperalgesia,” “glial activation,” “substance P,” “proinflammatory cytokine,” “HIV-1 envelope glycoprotein,” “tactile allodynia,” “primary sensory neuron,” “tumor necrosis factor,” “MAP kinase,” and “peripheral nerve injury.” Focusing on the keywords that appeared after 2010, we identified emerging trends in microglia- related neuropathic pain, including “transcription factors,” “sex difference,” “neuroinflammation,” “oxidative stress,” “proliferation” and “molecular mechanism.” In addition, the keyword with the highest burst strength was “expression of pro-inflammatory cytokines”; the keyword with the longest burst duration was “thermal hyperalgesia.” The top 10 productive institutions in microglia-related neuropathic pain were all from the top 5 countries in terms of publications (United States, China, United Kingdom, Japan, and Canada), indicating that the 5 countries play a leading role in the academic development of the field. At 9,674 total citations and 161.23 average citations, Harvard University is well ahead of the other institutions (Table 2). Much of the credit goes to the three highly cited authors (Table 7), Ji RR, Zhuang ZY, and Woolf CJ, who listed 09 frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 TABLE 8 The top 10 co-cited references for microglia research in neuropathic pain. TABLE 8 The top 10 co-cited references for microglia research in neuropathic pain. General information on microglia-related neuropathic pain research Rank Title Journal IF (2020) First author Publication time Country Co-Citation Quartile in category 1 Quantitative assessment of tactile allodynia in the rat paw Journal of Neuroscience Methods (IF = 2.987) Chaplan SR July, 1994 United States 495 Q3 2 P2X4 receptors induced in spinal microglia gate tactile allodynia after nerve injury Nature (IF = 69.504) Tsuda M August, 2003 Japan 479 Q1 3 BDNF from microglia causes the shift in neuronal anion gradient underlying neuropathic pain Nature (IF = 69.504) Coull Jeffrey AM December, 2005 Canada 391 Q1 4 Inhibition of microglial activation attenuates the development but not existing hypersensitivity in a rat model of neuropathy Journal Pharmacology Experimental Therapeutics (IF = 4.402) Raghavendra V August, 2003 United States 375 Q2 5 The neuropathic pain triad: neurons, immune cells and glia Nature Neuroscience (IF = 28.771) Scholz J November, 2007 United States 371 Q1 6 Neuropathic pain and spinal microglia: a big problem from molecules in “small” glia Trends Neuroscience (IF = 16.978) Tsuda M February, 2005 Japan 364 Q1 7 p38 mitogen-activated protein kinase is activated after a spinal nerve ligation in spinal cord microglia and dorsal root ganglion neurons and contributes to the generation of neuropathic pain Journal Neuroscience (IF = 6.709) Jin Shan-Xue May, 2003 United States 362 Q1 8 Pathological and protective roles of glia in chronic pain Nature reviews Neuroscience (IF = 38.755) Milligan ED January, 2009 United States 360 Q1 9 Glial activation: a driving force for pathological pain Trends Neuroscience (IF = 16.978) Watkins LR August, 2001 United States 308 Q1 10 Minocycline attenuates mechanical allodynia and proinflammatory cytokine expression in rat models of pain facilitation Pain (IF = 7.926) Ledeboer A May, 2005 United States 300 Q1 countries. All these reasons are probably the primary contributors to the rapid and sustained growth of NP in China over the last two decades. Predictably, China’s influence on global academic productivity will be growing. Harvard University as an affiliation of their own in many of the articles. Notably, Shanghai Jiao Tong University is the most productive university in China, ranking fourth among the Top 10 productive institutions, with the lowest average citation rate among the top 10 institutions, keeping with China’s performance on national academic influence. Pain and the Journal of Neuroscience are in the top three regarding both NP and co-citations, implying a significant role in microglia-related neuropathic pain (Tables 4, 5). Frontiers in Molecular Neuroscience frontiersin.org Frontiers in Molecular Neuroscience The general structure of knowledge in microglia-related neuropathic pain pain, which means that the study of this field is still mainly focused on basic research, namely translational research from basic to clinical has not yet become a mainstream research direction. VOSviewer was used to examine the top 10 co-cited references and to construct a visual map. Six of the top 10 co-cited articles were basic studies, while the remaining four were review papers (Table 8). In particular, the article titled “Quantitative assessment of tactile allodynia in the rat paw” (495 citations) was the most cited (Chaplan et al., 1994). We found that almost all of the 10 highest co-cited articles were associated with microglia activation. Three of these studies revealed that microglia is key in initiating neuropathic pain (Jin et al., 2003; Raghavendra et al., 2003; Ledeboer et al., 2005). Indeed, among the interactions between neurons and glial, astrocyte-mediated neuroinflammation is a key mechanism for maintaining chronic pain such as neuropathic pain, whereas microglia activation may act in the earliest stages of neuropathic pain (Ji et al., 2013). The most co-cited article found that blocking spinal P2X4 receptors (P2X4Rs) by intrathecal injection of an antagonist reversed tactile allodynia caused by peripheral nerve injury (Tsuda et al., 2003). Notably, a review published by Milligan (Milligan and Watkins, 2009) in 2009 systematically summarized the simultaneous pathological and protective role of the glial in chronic pain. The authors shift their focus from reducing the glial activation to increasing the protective role of the glial, and discussing how the protective and anti-inflammatory effects of glial can be used in the future to develop new pharmacological targets to reduce neuropathic pain (Milligan and Watkins, 2009). In the authors and co-cited authors analysis (Tables 6, 7), Inoue K and Tsuda M from Kyushu University were the top 2 most prolific authors with 61 and 60 articles respectively, Watkins LR from the University of Colorado System contributed 53 relevant studies, and Ji RR and Mika J with 50 and 48 articles ranked 4th and 5th, respectively. Among the co-cited authors, the top 5 authors, except for Tsuda M from Kyushu University, all work in different institutions from the US, indicating that the US possesses the leading researchers in microglia-related neuropathic pain. Tsuda M is the highest co-cited scholar, and their team focuses on the cellular and molecular mechanisms of microglia in neuropathic pain. Frontiers in Molecular Neuroscience General information on microglia-related neuropathic pain research And papers published in high IF journals such as Nature, Brain Behavior and Immunity, Proceedings of the National Academy of Sciences of the United States of America, and Journal of Neuroinflammation, this means that there will be more co-citations, potentially providing a theoretical basis for more extensive and in-depth research. It is notable, however, that among these journals, the most highly Scientific research strength is built on an economic foundation. As the second-largest economy, financial support for medical research in China is continuing to increase alongside its rapidly growing economy. The National Natural Science Foundation of China (NSFC) contributed to most publications (Table 3). In addition to financial factors, the role of international academic cooperation is also crucial, with China ranking third in the number of cooperating 10 frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 FIGURE 5 A visualization map of co-cited references on microglia-associated neuropathic pain. FIGURE 6 CiteSpace visualization map of the top 25 references involved in microglia-associated neuropathic pain with the strongest citation bursts. E 6 pace visualization map of the top 25 references involved in microglia-associated neuropathic pain with the strongest citation bursts. published journal, Molecular pain, has a low impact factor (3.370), as well as 40% of the highest-published journals and 30% of the highly co-cited journals with an impact factor of <4. In addition to impact factors, we should therefore include indicators other than citation-based ones to complement the appraisal of scientific accomplishment in assessing the academic value of journals (Ioannidis et al., 2014). These influential journals include a considerable amount of basic research on microglia in neuropathic 11 frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 TABLE 9 Top 20 keywords of microglia in neuropathic pain research. TABLE 9 Top 20 keywords of microglia in neuropathic pain research. Rank Keyword Occurrences Total link strength Rank Keyword Occurrences Total link strength 1 Neuropathic pain 1884 10,456 11 Nerve injury 291 1919 2 Microglia 1,256 7,678 12 Pain 256 1,549 3 Spinal cord 666 4,250 13 Astrocytes 246 1735 4 Activation 535 3,098 14 Glial activation 238 1,677 5 rat 509 3,177 15 Hyperalgesia 237 1,598 6 Expression 478 2,860 16 Neuroinflammation 233 1,368 7 Peripheral nerve injury 385 2,503 17 Allodynia 221 1,494 8 Mechanical allodynia 377 2,555 18 Mechanisms 218 1,276 9 Inflammation 318 1961 19 Model 212 1,273 10 Dorsal-root ganglia 298 1862 20 Neurons 211 1,417 The general structure of knowledge in microglia-related neuropathic pain The general structure of knowledge in microglia-related neuropathic pain Tsuda M’s team found that activation of P2X4Rs in spinal microglia triggered the release of BDNF from microglia and that pretreatment with interfering RNAs targeting BDNF could block the microglia–neuron signaling pathway to produce therapeutic effects (Coull et al., 2005). In addition, their team found that phosphorylation levels of p38 mitogen-activated protein kinase (p38MAPK) increased in ipsilateral dorsal horn microglia after nerve injury, revealing that activation of p38MAPK in spinal microglia is necessary for the development of tactile allodynia after nerve injury (Tsuda et al., 2004). Ji RR’s group has also made outstanding contributions in this area. They focused on the critical role of mitogen-activated protein kinases (MAPKs) in microglia signaling under neuropathic pain conditions. Ji RR’s team found in an earlier study that early activation of p38 in microglia in the ipsilateral dorsal horn of the spinal cord was induced by spinal nerve ligation (SNL) in adult rats, which facilitated the development of neuropathic pain (Jin et al., 2003). With outstanding contributions from Tsuda M’s and Ji RR’s teams, their study has the important significance of establishing a causal role for spinal microglia in neuropathic pain. Combining Table 8 with the density map (Supplementary Figure S1), the highly co-cited 80 articles obtained were divided into 3 phases. In the initial phase (1980 to 2003) the neuroimmune action of microglia in neuropathic pain was the primary focus of research, and in the intermediate phase (2004 to 2009) neuron–glia interactions became a key mechanism for understanding the development and maintenance of neuropathic pain. According to current research (2010 to 2018), effectively addressing neuroinflammation may be critical to alleviating neuropathic pain. Furthermore, immune-targeted therapies have shown promising early evidence of success in treating neuropathic pain (Hutchinson et al., 2013). Not surprisingly, research into the mechanisms of microglia in neuropathic pain has gradually moved from basic research to the clinic. In the end, our visualization shows (Figure 4B) a low level of collaboration among core authors (or core teams) in microglia-related neuropathic pain studies. Collaborative research is a driving force for scientific progress and is an essential trend today. With continued research in this area, there is an opportunity for further collaboration and discussion between the different institutions and between the authors. 12 frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 FIGURE 7 The visualization map on keywords of microglia-associated neuropathic pain. (A) Cluster analysis according to the occurrence of keywords. (B) Keyword timeline view. Identification of research hotspots and emerging topics rodents can be delayed or alleviated by intrathecal administration of neutralizing antibodies against FKN or CX3CR1 in different types of animal models of peripheral nerve injury (Milligan et al., 2004; Clark et al., 2007; Zhuang et al., 2007). And the downstream mechanism of FKN/CX3CR1 signaling may be mediated by microglia p38MAPK. By inhibiting CX3CR1, phosphorylation of p38MAPK in microglia is reduced, and ultimately the release of pro-inflammatory cytokines is reduced (Zhuang et al., 2007). In addition, deficits in neuropathic pain were observed in CX3CR1 knockout mice undergoing partial sciatic nerve ligation (PSNL) (Staniland et al., 2010). The evidence above suggests a specific strategy to inhibit microglia activation may hold considerable promise for the therapeutic administration of neuropathic pain. However, a more complex interaction exists between microglia and neurons. Visualization by a cluster of keywords analysis, time overlay maps, and density views (Figure 7). It can be seen that “activation of glial cells,” “MAP kinase,” “proinflammatory cytokine,” “central sensitization of pain,” “nociceptive hypersensitivity” and “neuroinflammation” are the main research directions for microglia in neuropathic pain. Pain is considered to be an immune disorder. Microglia interact with cells such as neurons as immune cells of the central nervous system (Austin and Moalem-Taylor, 2010). Stimulation of increased levels of the pro-inflammatory cytokine IFN-γ (IFN-γR) after nerve injury resulted in the conversion of resting microglia into activated cells (Figure 6) and the generation of tactile allodynia. In particular, the authors suggest that decreasing IFN-γR-mediated signaling in spinal microglia may be a potential treatment for neuropathic pain (Tsuda et al., 2009). In addition, many studies have shown that chemokines play a key role in neuron–microglia communication in neuropathic pain. Among them, the most attention has been paid to the key signaling pair of fractalkine (FKN) and its receptor CX3CR1 (Verge et al., 2004; Clark et al., 2009; Yang et al., 2012). Thus, for physiological/pathological processes in the CNS, allowing the FKN/ CX3CR1 signaling pair to be ideally located for regulating neuron– microglia communication. Studies have shown that chronic pain in It is known that macrophages can polarize into M1 cells with pro-inflammatory effects or M2 cells with anti-inflammatory functions (Wang et al., 2014). Similar to macrophage polarization, the polarization process of microglia is divided into an M1 phenotype, which expresses pro-inflammatory cytokines, or an M2 phenotype (David and Kroner, 2011), whose primary function is to alleviate inflammation and tissue repair (Orihuela et al., 2016). The general structure of knowledge in microglia-related neuropathic pain (C) Density visualization map of keywords. FIGURE 7 The visualization map on keywords of microglia-associated neuropathic pain. (A) Cluster analysis according to the occurrence of keywords. (B) Ke ord timeline ie (C) Densit is ali ation map of ke ords FIGURE 7 The visualization map on keywords of microglia-associated neuropathic pain. (A) Cluster analysis according to the occurrence of keywords. (B) Keyword timeline view. (C) Density visualization map of keywords. 13 Frontiers in Molecular Neuroscience Frontiers in Molecular Neuroscience frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 FIGURE 8 CiteSpace visualization map of the top 25 keywords involved in microglia-associated neuropathic pain with the strongest citation bursts. FIGURE 8 CiteSpace visualization map of the top 25 keywords involved in microglia-associated neuropathic pain with the strongest citation bursts. Frontiers in Molecular Neuroscience frontiersin.org Identification of research hotspots and emerging topics In addition, activation of CB2 receptors reduces nociceptive signal production and transmission by inducing a switch from the M1 phenotype to the M2 phenotype (Landry et al., 2012; Ma et al., 2015; Wu et al., 2019; Soliman et al., 2021). And 2-AG expression is significantly upregulated when microglia are converted to the M2 phenotype under pathological conditions (Mitrirattanakul et al., 2006; Mecha et al., 2015). A study elegantly confirmed that the endocannabinoid system is essential for the transformation of the M2 phenotype of microglia. It showed that cannabinoid receptor antagonists block microglia M2 polarization and that M2 polarization is dampened in CB2 receptor knockout mice (Mecha et al., 2015). the literature, we should understand what the authors are trying to convey in context rather than conflating it with the “activation” of microglia. Taking into account the changes in the annual number of publications, we can broadly divide the evolution of keywords into two stages: Before 2009, the keywords “proinflammatory cytokine” (Ledeboer et al., 2005), “release of cytokines,” “spinal glial” (Wei et al., 2008), and “substances P” indicated the initial stage of studying microglia in neuropathic pain. From 2009 to 2015, the keywords “astrocytes” (Ji et al., 2013), “activation of glial” (Mika et al., 2013), “p38 MAPK” (Trang et al., 2009), “minocycline” (Ledeboer et al., 2005), and “opioid receptors” (Vacca et al., 2013) are extended directions based on previous research. From 2015 to 2021, the keywords “neuroinflammation” (Ji et al., 2018), “sex-differences” (Sorge et al., 2015), “satellite glial” (Lim et al., 2017), “NLRP3” (Grace et al., 2016), “mesenchymal stem cells” (Yang et al., 2020) have emerged as new research hotspots. According to the timeline analysis, it is clear that with the breakthroughs in new technologies in the biological sciences, research in this field is gradually shifting from cellular and molecular mechanisms to the exploration of new therapeutic techniques.l Burst analysis of references also reflects the hotspots and frontiers in a research field (Figure 6). The highest citation burst article is the 2018 review by Inoue K and Tsuda M in Nature reviews neuroscience (Inoue and Tsuda, 2018) (42.64, 2019–2021) highlighting spinal microglia’s pivotal role in developing pain hypersensitivity after nerve injury. The longest burst duration of basic research came from a landmark study published by Sorge et al. Identification of research hotspots and emerging topics (2015) (24.8, 2016–2021), which found different dependencies of the pain hypersensitivity response on microglia and T cells between male and female mice through multiple experiments. In female mice, mechanical pain hypersensitivity is not exclusively microglia-mediated but is most likely mediated by the adaptive immune system (T lymphocytes). In previous pain studies, males have been used directly to denote both sexes, but research based on epidemiological and laboratory evidence indicates that chronic pain occurs more often in females (Mogil, 2012). This differentiated mechanism from the conventional view may help us understand why women have a higher risk of chronic pain. More importantly, microglia, T-lymphocytes, and other immune cells have been implicated to varying degrees in many neurological diseases, such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis. Consequently, by transferring the concept of sexual dimorphism to the study of other neurological disorders, new insights into treating these diseases will be provided. However, as multi-omics and single-cell techniques are increasingly used, the classical M1/M2 phenotypic classification may not fully explain the broad transcriptional state of microglia (Bennett et al., 2016). This landmark study (Bennett et al., 2016) showed that activated microglia clearly exhibit distinct phenotypes, but cannot be accurately distinguished by these phenotypes regarding the production of pro-inflammatory or anti-inflammatory mediators. This is due to the more complex biological properties of microglia, including region- specific, sex-dependent, and disease-specific activation properties (Kwon, 2022). Furthermore, multiple intermediate phenotypes can result from microglia function, depending on the microenvironment, the region, and the stage of the disease (Chiu et al., 2013). The M1/M2 phenotypes of activated microglia are typically mixed with one another, rather than showing a segregated condition, as seen in the pro-inflammatory effect of the M1 phenotype or the anti-inflammatory effect of the M2 phenotype. Microglia should therefore be considered dynamic cells that are plastic and strongly dependent on the context. New imaging tools and reporters will be needed in future studies to track changes in microglia over time, throughout their lifetime, and with treatment under different neuropathological conditions (Tay et al., 2017; Jordão et al., 2019). A similar terminological aspect also involves “neuroinflammation” in this article (Figures 7A, 8). The meaning of the term “neuroinflammation” has often been equated with microglia “activation.” However, in practice, the definition of “neuroinflammation” often varies considerably between authors (Graeber, 2010). In fact, inflammation related to the CNS is usually a highly elaborated local reaction. Identification of research hotspots and emerging topics Therefore, “neuroinflammation” may not directly refer to microglia “activation” (Woodburn et al., 2021). Moreover, the functions represented by the numerous transcriptional states of glial (including microglia, astrocytes, and oligodendrocytes) in the CNS are still not fully understood (Cahoy et al., 2008; Medina et al., 2022). In addition, “neuroinflammation” often implies deleterious effects (Aramideh et al., 2021). However, this terminology wrongly ignores the active role played by microglia in physiological functions. As a result, when we see the term “neuroinflammation” in Frontiers in Molecular Neuroscience Identification of research hotspots and emerging topics Therefore, the desirable way is to exert the anti-inflammatory and tissue repair capacity of microglia themselves by reducing the existence of the M1 microglia and/or converting them to the M2. Recent studies have demonstrated that some natural compounds such as parthenolide 14 frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 (Popiolek-Barczyk et al., 2015), dehydrocorydaline (Huo et al., 2018), and naringenin (Ge et al., 2022) could inhibit microglia-mediated neuroinflammation by stimulating the polarization of microglia to the M2, thereby attenuating allodynia and neuropathic pain in rats with bone cancer pain and rats with neuropathic pain. In addition, the endocannabinoid system and its ligand, 2-arachidonoylglycerol (2-AG), appear to be involved in the M1/M2 phenotypic switch in microglia during neuropathic pain. It was shown that the expression of CB2 receptors in microglia exhibited a consistency with the activation of microglia (Zhang et al., 2003; Racz et al., 2008; Guasti et al., 2009; Luongo et al., 2010). In addition, activation of CB2 receptors reduces nociceptive signal production and transmission by inducing a switch from the M1 phenotype to the M2 phenotype (Landry et al., 2012; Ma et al., 2015; Wu et al., 2019; Soliman et al., 2021). And 2-AG expression is significantly upregulated when microglia are converted to the M2 phenotype under pathological conditions (Mitrirattanakul et al., 2006; Mecha et al., 2015). A study elegantly confirmed that the endocannabinoid system is essential for the transformation of the M2 phenotype of microglia. It showed that cannabinoid receptor antagonists block microglia M2 polarization and that M2 polarization is dampened in CB2 receptor knockout mice (Mecha et al., 2015). (Popiolek-Barczyk et al., 2015), dehydrocorydaline (Huo et al., 2018), and naringenin (Ge et al., 2022) could inhibit microglia-mediated neuroinflammation by stimulating the polarization of microglia to the M2, thereby attenuating allodynia and neuropathic pain in rats with bone cancer pain and rats with neuropathic pain. In addition, the endocannabinoid system and its ligand, 2-arachidonoylglycerol (2-AG), appear to be involved in the M1/M2 phenotypic switch in microglia during neuropathic pain. It was shown that the expression of CB2 receptors in microglia exhibited a consistency with the activation of microglia (Zhang et al., 2003; Racz et al., 2008; Guasti et al., 2009; Luongo et al., 2010). Possible breakthrough for the roles of microglia in neuropathic pain Old ideas are often overturned by technological advances. The above-mentioned debate about the M1/M2 phenotype of microglia is a typical example of this (Paolicelli et al., 2022): monolithic dichotomies are now perceived as overly simplistic and uncritical. Genomic, proteomic, spatial transcriptomic, and single-cell technologies have allowed us to better understand microglia function. Most current research on transcriptional changes in microglial heterogeneity focuses on neurodegenerative diseases (Masuda et al., 2020). In mouse models of Alzheimer’s disease (AD), there have been 15 frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 several different states of context-dependent microglia, also known as disease associated microglia (DAM) (Keren-Shaul et al., 2017). In the context of AD, microglia respond to amyloid pathology by transforming into DAM, downregulating genes such as Cx3cr1, Tmem119 and P2ry12 and upregulating genes such as Trem2, Apoe, and Ctsb have been observed (Keren-Shaul et al., 2017; Krasemann et al., 2017; Sala Frigerio et al., 2019). Despite this, little research has been conducted on microglial heterogeneous transcriptional changes in chronic or neuropathic pain. While DAM occurs in AD, microglial transcriptomic data have little or no correlation with the genes involved in DAM in neuropathic pain conditions (Denk et al., 2016; Jeong et al., 2016; Krasemann et al., 2017). Sideris-Lampretsas and Malcangio (2021), however, presented a different viewpoint, suggesting that microglia located near the ends of damaged nerve fibers are better able to adapt to neuronal changes, while microglia in adjacent neurons maintain a balanced state. Taking this perspective, it is exciting that microglia features associated with neuropathic pain have been identified. After peripheral nerve injury, microglia proliferate in the medial dorsal horn of the spinal cord and upregulation of specific genes (e.g., Ctss, Cx3cr1, Itgam, and Bdnf) related to neuropathic pain mechanisms occurs (Clark et al., 2007; Staniland et al., 2010; Guan et al., 2016). Nevertheless, more research is needed to investigate the transcriptional features of neuropathic pain-associated microglia in relation to their function. A unique microglial transcriptional profile that tends to completely represent neuropathic pain-related conditions may be uncovered by introducing advanced technologies and refining microglial studies across age, gender, region, disease, and species in the future. In the context of neuropathic pain, microglia will likely be investigated more thoroughly to enable new clinical therapeutic targets to be identified. spinal cord injury by reducing the levels of p-p38 mitogen-activated protein kinase and extracellular signal-regulated kinase (p-ERK1/2) in spinal cord microglia (Watanabe et al., 2015). Possible breakthrough for the roles of microglia in neuropathic pain It has also been found that interleukin 1β-pretreated BMSCs inhibit spinal microglia activation through CCL7 mediation, thereby reducing neuropathic pain (Li et al., 2017). In addition, several studies have shown that BMSCs regulate spinal microglia by paracrine mechanisms to produce analgesia. The specific mechanisms involved may include the downregulation of P2X4R (Teng et al., 2019), the activation of the TLR2/MyD88/NF-κB pathway (Yang et al., 2020) and M2 phenotype microglia polarization in spinal microglia (Zhong et al., 2020). In another study, however, repeated intrathecal injections of MSCs after partial sciatic nerve ligation (PSNL) in rats did not produce a significant analgesic effect nor inhibit microglia activation in the ipsilateral spinal cord (Schäfer et al., 2014). It can therefore be speculated that the reasons for the uncertain therapeutic efficiency of MSCs may be related to their administration route. However, the risks of stem cell therapy are not limited to the uncertainty of the therapeutic outcome, as MSCs have the potential to cause pulmonary thrombosis or endogenous tumor formation (Jeong et al., 2011; Hua et al., 2022). In contrast, MSCs-derived extracellular vehicles (EVs), including exosomes, have the advantage of being readily available and stored and under few ethical restrictions compared to MSCs (Moghadasi et al., 2021). In addition, EVs/exosomes combine the advantages of cellular and nanotechnology in drug delivery (Liu et al., 2021). MSCs-derived EVs/exosomes in the cell-free treatment of neuropathic pain largely involve the participation of MicroRNAs. Intrathecal injection of MSC-EVs carrying miR-99b-3p reduced microglia activation in the spinal cord’s dorsal horn and mechanical allodynia in chronic constriction injury (CCI) rats by stimulating autophagy (Gao et al., 2023). Li et al. (2022) showed that the BMSC- derived exosomal miR-150-5p attenuates mechanical allodynia by targeting NOTCH2 in microglial. In addition to the beneficial action of MicroRNAs, Huc-MSCs-derived exosomes may exert analgesic effects on neuropathic pain by inhibiting activation of the TLR2/MyD88/ NF-κB signaling pathway in spinal microglia (Gao et al., 2023). Possibility of clinical translation Combined with our research and findings, we believe introducing new therapeutic methods will largely change the paradigm of microglia research in neuropathic pain. Current treatments for pain rarely treat the disorder’s etiology; therefore, treatments for neuropathic pain often focus on reducing clinical symptoms (Gilron et al., 2015). However, current pharmacological and non-pharmacological treatments can only provide long-lasting pain relief for a very narrow range of patients (Alles and Smith, 2018), and these treatments are often coupled with various adverse effects (Moore et al., 2015). As a result, new therapeutic options, such as stem-cell therapy, are increasingly attracting the attention of scientists. Even though relevant studies are at a very early stage of clinical application, thanks to advances in technology and the increasing experimental data combined with clinical evidence to support them, we believe that stem-cell therapy and MSC-derived EVs/exosomes hold promise as potential treatment options for the clinical management of neuropathic pain. Frontiers in Molecular Neuroscience References Basbaum, A. I., Bautista, D. M., Scherrer, G., and Julius, D. (2009). Cellular and molecular mechanisms of pain. Cells 139, 267–284. doi: 10.1016/j.cell.2009. 09.028 Basbaum, A. I., Bautista, D. M., Scherrer, G., and Julius, D. (2009). Cellular and molecular mechanisms of pain. Cells 139, 267–284. doi: 10.1016/j.cell.2009. 09.028 Ahmad, K. A., Shoaib, R. M., Ahsan, M. Z., Deng, M. Y., Ma, L., Apryani, E., et al. (2021). Microglial IL-10 and β-endorphin expression mediates gabapentinoids antineuropathic pain. Brain Behav. Immun. 95, 344–361. doi: 10.1016/j.bbi.2021.04.007 Ai, Y., Xing, Y., Yan, L., Ma, D., Gao, A., Xu, Q., et al. (2022). Depression: a bibliometric analysis from 2001 to 2021. Front. Cardiovasc. Med. 9:775329. doi: 10.3389/ fcvm.2022.775329/full Ai, Y., Xing, Y., Yan, L., Ma, D., Gao, A., Xu, Q., et al. (2022). Depression: a bibliometric analysis from 2001 to 2021. Front. Cardiovasc. Med. 9:775329. doi: 10.3389/ fcvm.2022.775329/full Bennett, M. L., Bennett, F. C., Liddelow, S. A., Ajami, B., Zamanian, J. L., Fernhoff, N. B., et al. (2016). New tools for studying microglia in the mouse and human CNS. Proc Natl Acad Sci U S A 113:E1738-46. doi: 10.1073/pnas.1525528113 Bennett, M. L., Bennett, F. C., Liddelow, S. A., Ajami, B., Zamanian, J. L., Fernhoff, N. B., et al. (2016). New tools for studying microglia in the mouse and human CNS. Proc Natl Acad Sci U S A 113:E1738-46. doi: 10.1073/pnas.1525528113 Alles, S. R. A., and Smith, P. A. (2018). Etiology and pharmacology of neuropathic pain. Pharmacol. Rev. 70, 315–347. doi: 10.1124/pr.117.014399 Cahoy, J. D., Emery, B., Kaushal, A., Foo, L. C., Zamanian, J. L., Christopherson, K. S., et al. (2008). A transcriptome database for astrocytes, neurons, and oligodendrocytes: a new resource for understanding brain development and function. J. Neurosci. 28, 264–278. doi: 10.1523/JNEUROSCI.4178-07.2008 Aramideh, J. A., Vidal-Itriago, A., Morsch, M., and Graeber, M. B. (2021). Cytokine signalling at the microglial penta-partite synapse. Int. J. Mol. Sci. 22:13186. doi: 10.3390/ ijms222413186 Chaplan, S. R., Bach, F. W., Pogrel, J. W., Chung, J. M., and Yaksh, T. L. (1994). Quantitative assessment of tactile allodynia in the rat paw. J. Neurosci. Methods 53, 55–63. doi: 10.1016/0165-0270(94)90144-9 Austin, P. J., and Moalem-Taylor, G. (2010). The neuro-immune balance in neuropathic pain: involvement of inflammatory immune cells, immune-like glial cells and cytokines. J. Neuroimmunol. 229, 26–50. doi: 10.1016/j.jneuroim.2010.08.013 Chen, C. (2004). Searching for intellectual turning points: progressive knowledge domain visualization. Proc. Natl. Acad. Sci. 101, 5303–5310. doi: 10.1073/ pnas.0307513100 Ayala-Cuellar, A. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Limitation This study is based on bibliometric analyses, using NC, NP, and H-index as the main research indicators and through visual analysis to help readers quickly grasp the current status of research and research trends as well as academic frontiers in this research field. Although our research is the initial bibliometric study of microglia- related neuropathic pain, there are a few limitations, as follows: (1) The WoSCC database is the most frequently accessed database during the scientometric analysis, and our search was therefore limited to literature in the WoSCC database, so some articles not included in the WoSCC were artificially omitted. Such limitations are also present in other bibliometric studies (Li et al., 2022; Wei et al., 2022). (2) Readers identify the most core content by a limited number of keywords (Ji et al., 2003; Basbaum et al., 2009; Costigan et al., 2009; Freeman, 2009; In recent decades, stem cells have shown remarkable anti- inflammatory and tissue repair efficacy (Peng et al., 2021), and their therapeutic effects may be associated with paracrine actions (Baraniak and McDevitt, 2010). Mesenchymal stem cells (MSCs) have become the preferred cells for cell therapy due to their high proliferative capacity, ability to differentiate into various tissue types and paracrine secretion of many factors with immunomodulatory properties (Ayala-Cuellar et al., 2019). Siniscalco et al. (2011) pioneered using human mesenchymal stem cells (hMSCs) to treat mice after nerve injury and systemic treatment with hMSCs administered via the tail vein produced an anti-nociceptive effect against injury. Following this, it has been shown that BMSCs transplantation reduces neuropathic pain caused by 16 frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 Conclusion This study provides a bibliometric analysis and visualization of the literature focusing on the role of microglia in neuropathic pain from 2000 to 2021. We found that this field began to attract scholarly attention in 2004, and relevant research has been increasing yearly, especially in the last 5 years. It can be seen that the number of publications will be consistently increasing in the future. China and the United States are the top contributors in this area. The University of London is the highest publisher. The most productive author is Inoue K. Journal of Neuroscience is the journal with the highest total citations and average citations per article. In addition, current studies are focused on microglia activation, MAP kinase, and pro-inflammatory cytokines. The signaling between microglia and neurons is a core element of research in this field. Sexual dimorphism, neuroinflammation, and stem-cell therapy are possible frontiers in this field. Breakthroughs in these future key subjects will offer considerable promise for the clinical treatment of neuropathic pain. Overall, this study provides insights into the trends and characteristics of microglia-related neuropathic pain from a macroscopic perspective and offers valuable reference information for subsequent in-depth studies by other researchers. Data availability statement The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnmol.2023.1142852/ full#supplementary-material The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. Publisher’s note All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. Funding This work was supported by the National Natural Science Foundation of China, Natural Science Foundation of China (31960175), Natural Science Foundation of Gansu Province (18JR3RA331), Fund Project of the Second Hospital of Lanzhou University (CY2017-MS06), and Gansu Youth Science and Technology Fund (20JR10RA752). Author contributions Jensen et al., 2011; Finnerup et al., 2015; Colloca et al., 2017) in the literature, which may lead to absent content extraction. (3) Citation indicators are time-dependent, which means that some of the best articles published more recently may lead to exclusion because they are less frequently cited. Consequently, there is a delay in reflecting up-to-date research. Despite all these limitations, it does not change the hotspots and trends revealed in this study. In conclusion, our research has unearthed useful information that may help researchers efficiently understand the research topics, trends, and academic hotspots of microglia in neuropathic pain. Jensen et al., 2011; Finnerup et al., 2015; Colloca et al., 2017) in the literature, which may lead to absent content extraction. (3) Citation indicators are time-dependent, which means that some of the best articles published more recently may lead to exclusion because they are less frequently cited. Consequently, there is a delay in reflecting up-to-date research. Despite all these limitations, it does not change the hotspots and trends revealed in this study. In conclusion, our research has unearthed useful information that may help researchers efficiently understand the research topics, trends, and academic hotspots of microglia in neuropathic pain. ZS-B designed the study. ZS-B and ZG-H searched and downloaded the data. ZG-H and LT-R re-checked the data. ZS-B and GC-Y analyzed the data. ZS-B drafted the manuscript. SY-Q, NW, and ZH-H reviewed the manuscript. All authors contributed to the article and approved the submitted version. References P., Kang, J. H., Jeung, E. B., and Choi, K. C. (2019). Roles of mesenchymal stem cells in tissue regeneration and immunomodulation. Biomol. Ther. 27, 25–33. doi: 10.4062/biomolther.2017.260 Chen, C. (2006). CiteSpace II: detecting and visualizing emerging trends and transient patterns in scientific literature. J. Am. Soc. Inf. Sci. Technol. 57, 359–377. doi: 10.1002/ asi.20317 Chen, C. (2006). CiteSpace II: detecting and visualizing emerging trends and transient patterns in scientific literature. J. Am. Soc. Inf. Sci. Technol. 57, 359–377. doi: 10.1002/ asi.20317 Baraniak, P. R., and McDevitt, T. C. (2010). Stem cell paracrine actions and tissue regeneration. Regen. Med. 5, 121–143. doi: 10.2217/rme.09.74 Frontiers in Molecular Neuroscience 17 frontiersin.org Zhang et al. Zhang et al. 10.3389/fnmol.2023.1142852 Chen, C., Hu, Z., Liu, S., and Tseng, H. (2012). Emerging trends in regenerative medicine: a scientometric analysis in CiteSpace. Expert Opin. Biol. Ther. 12, 593–608. doi: 10.1517/14712598.2012.674507 Guan, Z., Kuhn, J. A., Wang, X., Colquitt, B., Solorzano, C., Vaman, S., et al. (2016). Injured sensory neuron-derived CSF1 induces microglial proliferation and DAP12- dependent pain. Nat. Neurosci. 19, 94–101. doi: 10.1038/nn.4189 Chen, Y. M., and Wang, X. Q. (2020). Bibliometric analysis of exercise and neuropathic pain research. JPR. 13, 1533–1545. doi: 10.2147/JPR.S258696 Guasti, L., Richardson, D., Jhaveri, M., Eldeeb, K., Barrett, D., Elphick, M. R., et al. (2009). Minocycline treatment inhibits microglial activation and alters spinal levels of endocannabinoids in a rat model of neuropathic pain. Mol. Pain 5:1744-8069-5-35. doi: 10.1186/1744-8069-5-35 Chiu, I. M., Morimoto, E. T. A., Goodarzi, H., Liao, J. T., O'Keeffe, S., Phatnani, H. P., et al. (2013). A neurodegeneration-specific gene-expression signature of acutely isolated microglia from an amyotrophic lateral sclerosis mouse model. Cell Rep. 4, 385–401. doi: 10.1016/j.celrep.2013.06.018 Hone, A. J., Servent, D., and McIntosh, J. M. (2018). α9-containing nicotinic acetylcholine receptors and the modulation of pain. Br. J. Pharmacol. 175, 1915–1927. doi: 10.1111/bph.13931 Clark, A. K., Gentry, C., Bradbury, E. J., McMahon, S. B., and Malcangio, M. (2007). Role of spinal microglia in rat models of peripheral nerve injury and inflammation. Eur J Pain 11, 223–230. doi: 10.1016/j.ejpain.2006.02.003 Hua, T., Yang, M., Song, H., Kong, E., Deng, M., Li, Y., et al. (2022). Huc-MSCs- derived exosomes attenuate inflammatory pain by regulating microglia pyroptosis and autophagy via the mi R-146a-5p/TRAF6 axis. J. Nanobiotechnol. 20, 1–18. doi: 10.1186/ s12951-022-01522-6 Clark, A. K., Yip, P. K., Grist, J., Gentry, C., Staniland, A. A., Marchand, F., et al. (2007). References 15, 1771–1781. doi: 10.1016/j.celrep.2016.04.063 Jensen, T. S., Baron, R., Haanpää, M., Kalso, E., Loeser, J. D., Rice, A. S. C., et al. (2011). A new definition of neuropathic pain. Pain 152, 2204–2205. doi: 10.1016/j. pain.2011.06.017 Detloff, M. R., Fisher, L. C., McGaughy, V., Longbrake, E. E., Popovich, P. G., and Basso, D. M. (2008). Remote activation of microglia and pro-inflammatory cytokines predict the onset and severity of below-level neuropathic pain after spinal cord injury in rats. Exp. Neurol. 212, 337–347. doi: 10.1016/j.expneurol.2008.04.009 Jeong, J. O., Han, J. W., Kim, J. M., Cho, H. J., Park, C., Lee, N., et al. (2011). Malignant tumor formation after transplantation of short-term cultured bone marrow mesenchymal stem cells in experimental myocardial infarction and diabetic neuropathy. Circul. Res. 108, 1340–1347. doi: 10.1161/CIRCRESAHA.110.239848 Du, L., Zhang, Y., Chen, Y., Zhu, J., Yang, Y., and Zhang, H. L. (2017). Role of microglia in neurological disorders and their potentials as a therapeutic target. Mol. Neurobiol. 54, 7567–7584. doi: 10.1007/s12035-016-0245-0 Jeong, H., Na, Y. J., Lee, K., Kim, Y. H., Lee, Y., Kang, M., et al. (2016). High- resolution transcriptome analysis reveals neuropathic pain gene-expression signatures in spinal microglia after nerve injury. Pain 157, 964–976. doi: 10.1097/j. pain.0000000000000470 Eagly, A. H., and Miller, D. I. (2016). Scientific Eminence: where are the women? Perspect. Psychol. Sci. 11, 899–904. doi: 10.1177/1745691616663918 Finnerup, N. B., Attal, N., Haroutounian, S., McNicol, E., Baron, R., Dworkin, R. H., et al. (2015). Pharmacotherapy for neuropathic pain in adults: a systematic review and meta-analysis. Lancet Neurol. 14, 162–173. doi: 10.1016/S1474-4422(14)70251-0 Ji, R. R., Berta, T., and Nedergaard, M. (2013). Glia and pain: is chronic pain a gliopathy? Pain 154, S10–S28. doi: 10.1016/j.pain.2013.06.022 Freeman, R. (2009). Not all neuropathy in diabetes is of diabetic etiology: differential diagnosis of diabetic neuropathy. Curr. Diab. Rep. 9, 423–431. doi: 10.1007/ s11892-009-0069-7 Ji, R. R., Gereau, R. W., Malcangio, M., and Strichartz, G. R. (2009). MAP kinase and pain. Brain Res. Rev. 60, 135–148. doi: 10.1016/j.brainresrev.2008.12.011 Ji, R. R., Kohno, T., Moore, K. A., and Woolf, C. J. (2003). Central sensitization and LTP: do pain and memory share similar mechanisms? Trends Neurosci. 26, 696–705. doi: 10.1016/j.tins.2003.09.017 Gao, X., Gao, L.-F., Kong, X.-Q., Zhang, Y.-N., Jia, S., and Meng, C.-Y. (2023). Mesenchymal stem cell-derived extracellular vesicles carrying miR-99b-3p restrain microglial activation and neuropathic pain by stimulating autophagy. Int. Immunopharmacol. 115:109695. doi: 10.1016/j.intimp.2023.109695 Ji, R. References Inhibition of spinal microglial cathepsin S for the reversal of neuropathic pain. Proc. Natl. Acad. Sci. U. S. A. 104, 10655–10660. doi: 10.1073/pnas.0610811104 Huang, Q., Mao, X. F., Wu, H. Y., Liu, H., Sun, M. L., Wang, X., et al. (2017). Cynandione a attenuates neuropathic pain through p38β MAPK-mediated spinal microglial expression of β-endorphin. Brain Behav. Immun. 62, 64–77. doi: 10.1016/j. bbi.2017.02.005 Clark, A. K., Yip, P. K., and Malcangio, M. (2009). The liberation of fractalkine in the dorsal horn requires microglial cathepsin S. J. Neurosci. 29, 6945–6954. doi: 10.1523/ JNEUROSCI.0828-09.2009 Huo, W., Zhang, Y., Liu, Y., Lei, Y., Sun, R., Zhang, W., et al. (2018). Dehydrocorydaline attenuates bone cancer pain by shifting microglial M1/M2 polarization toward the M2 phenotype. Molecular Pain. 14:1744806918781733. doi: 10.1177/1744806918781733 Colloca, L., Ludman, T., Bouhassira, D., Baron, R., Dickenson, A. H., Yarnitsky, D., et al. (2017). Neuropathic pain. Nat. Rev. Dis. Primers. 3:17002. doi: 10.1038/nrdp.2017.2 Costigan, M., Scholz, J., and Woolf, C. J. (2009). Neuropathic pain: a maladaptive response of the nervous system to damage. Reviews 32, 1–32. doi: 10.1146/annurev. neuro.051508.135531.Annual Hutchinson, M. R., Buijs, M., Tuke, J., Kwok, Y. H., Gentgall, M., Williams, D., et al. (2013). Low-dose endotoxin potentiates capsaicin-induced pain in man: evidence for a pain neuroimmune connection. Brain Behav. Immun. 30, 3–11. doi: 10.1016/j. bbi.2013.03.002 Coull, J. A. M., Beggs, S., Boudreau, D., Boivin, D., Tsuda, M., Inoue, K., et al. (2005). BDNF from microglia causes the shift in neuronal anion gradient underlying neuropathic pain. Nature 438, 1017–1021. doi: 10.1038/nature04223 Inoue, K. (2006). The function of microglia through purinergic receptors: neuropathic pain and cytokine release. Pharmacol. Ther. 109, 210–226. doi: 10.1016/j. pharmthera.2005.07.001 David, S., and Kroner, A. (2011). Repertoire of microglial and macrophage responses after spinal cord injury. Nat. Rev. Neurosci. 12, 388–399. doi: 10.1038/nrn3053 Inoue, K., and Tsuda, M. (2018). Microglia in neuropathic pain: cellular and molecular mechanisms and therapeutic potential. Nat. Rev. Neurosci. 19, 138–152. doi: 10.1038/ nrn.2018.2 DeLeo, J. A., and Yezierski, R. P. (2001). The role of neuroinflammation and neuroimmune activation in persistent pain. Pain 90, 1–6. doi: 10.1016/ S0304-3959(00)00490-5 Ioannidis, J. P. A., Boyack, K. W., Small, H., Sorensen, A. A., and Klavans, R. (2014). Bibliometrics: is your most cited work your best? Nature 514, 561–562. doi: 10.1038/514561a Denk, F., Crow, M., Didangelos, A., Lopes, D. M., and McMahon, S. B. (2016). Persistent alterations in microglial enhancers in a model of chronic pain. Cell Rep. References R., Nackley, A., Huh, Y., Terrando, N., and Maixner, W. (2018). Neuroinflammation and central sensitization in chronic and widespread pain. Anesthesiology 129, 343–366. doi: 10.1097/ALN.0000000000002130 Gao, X., Gao, L.-F., Zhang, Y.-N., Kong, X.-Q., Jia, S., and Meng, C.-Y. (2023). Huc- MSCs-derived exosomes attenuate neuropathic pain by inhibiting activation of the TLR2/MyD88/NF-κB signaling pathway in the spinal microglia by targeting Rsad 2. Int. Immunopharmacol. 114:109505. doi: 10.1016/j.intimp.2022.109505 Ji, R. R., and Suter, M. R. (2007). p38 MAPK, microglial signaling, and neuropathic pain. Mol. Pain 3:33. doi: 10.1186/1744-8069-3-33 Jin, S. X., Zhuang, Z. Y., Woolf, C. J., and Ji, R. R. (2003). p38 mitogen-activated protein kinase is activated after a spinal nerve ligation in spinal cord microglia and dorsal root ganglion neurons and contributes to the generation of neuropathic pain. J. Neurosci. 23, 4017–4022. doi: 10.1523/JNEUROSCI.23-10-04017.2003 Ge, M. M., Li, D. Y., Wang, L., Zhang, L. Q., Liu, D. Q., Tian, Y. K., et al. (2022). Naringenin promoted spinal microglia M2 polarization in rat model of cancer-induced bone pain via regulating AMPK/PGC-1α signaling axis. Biomed. Pharmacother. 149:112912. doi: 10.1016/j.biopha.2022.112912 Jones, T., Huggett, S., and Kamalski, J. (2011). Finding a way through the scientific literature: indexes and measures. World Neurosurg. 76, 36–38. doi: 10.1016/j. wneu.2011.01.015 Gilron, I., Baron, R., and Jensen, T. (2015). Neuropathic pain: principles of diagnosis and treatment. Mayo Clin. Proc. 90, 532–545. doi: 10.1016/j.mayocp.2015.01.018 Grace, P. M., Strand, K. A., Galer, E. L., Urban, D. J., Wang, X., Baratta, M. V., et al. (2016). Morphine paradoxically prolongs neuropathic pain in rats by amplifying spinal NLRP3 inflammasome activation. Proc. Natl. Acad. Sci. 113, E3441–E3450. doi: 10.1073/ pnas.1602070113 Jordão, M. J. C., Sankowski, R., Brendecke, S. M., Sagar, N., Locatelli, G., Tai, Y. H., et al. (2019). Single-cell profiling identifies myeloid cell subsets with distinct fates during neuroinflammation. Science 363:eaat7554. doi: 10.1126/science.aat7554 Keren-Shaul, H., Spinrad, A., Weiner, A., Matcovitch-Natan, O., Dvir-Szternfeld, R., Ulland, T. K., et al. (2017). A unique microglia type associated with restricting development of Alzheimer’s disease. Cells 169, 1276–1290.e17. doi: 10.1016/j. cell.2017.05.018 Grace, P. M., Tawfik, V. L., Svensson, C. I., Burton, M. D., Loggia, M. L., and Hutchinson, M. R. (2021). The Neuroimmunology of chronic pain: from rodents to humans. J. Neurosci. 41, 855–865. doi: 10.1523/JNEUROSCI.1650-20.2020 Graeber, M. B. (2010). Changing face of microglia. Science 330, 783–788. doi: 10.1126/ science.1190929 Kleinberg, J. (2003). Bursty and hierarchical structure in streams. Data Min. Knowl. Disc. 7, 373–397. References doi: 10.1023/A:1024940629314 Gu, D., Li, J., Li, X., and Liang, C. (2017). Visualizing the knowledge structure and evolution of big data research in healthcare informatics. Int. J. Med. Inform. 98, 22–32. doi: 10.1016/j.ijmedinf.2016.11.006 Krasemann, S., Madore, C., Cialic, R., Baufeld, C., Calcagno, N., El Fatimy, R., et al. (2017). The TREM2-APOE pathway drives the transcriptional phenotype of Frontiers in Molecular Neuroscience 18 frontiersin.org Zhang et al. 10.3389/fnmol.2023.1142852 exosomes in regenerative medicine. J. Transl. Med. 19:302. doi: 10.1186/ s12967-021-02980-6 dysfunctional microglia in neurodegenerative diseases. Immunity 47, 566–581.e9. doi: 10.1016/j.immuni.2017.08.008 Kwon, M. S. (2022). Advanced therapeutic strategies targeting microglia: beyond neuroinflammation. Arch. Pharm. Res. 45, 618–630. doi: 10.1007/s12272-022-01406-1 Mogil, J. S. (2012). Sex differences in pain and pain inhibition: multiple explanations of a controversial phenomenon. Nat. Rev. Neurosci. 13, 859–866. doi: 10.1038/nrn3360 Landry, R. P., Martinez, E., DeLeo, J. A., and Romero-Sandoval, E. A. (2012). Spinal cannabinoid receptor type 2 agonist reduces mechanical allodynia and induces mitogen- activated protein kinase phosphatases in a rat model of neuropathic pain. J. Pain 13, 836–848. doi: 10.1016/j.jpain.2012.05.013 Moisset, X., Bouhassira, D., Avez Couturier, J., Alchaar, H., Conradi, S., Delmotte, M. H., et al. (2020). Pharmacological and non-pharmacological treatments for neuropathic pain: systematic review and French recommendations. Rev. Neurol. (Paris) 176, 325–352. doi: 10.1016/j.neurol.2020.01.361 Ledeboer, A., Sloane, E. M., Milligan, E. D., Frank, M. G., Mahony, J. H., Maier, S. F., et al. (2005). Minocycline attenuates mechanical allodynia and proinflammatory cytokine expression in rat models of pain facilitation. Pain 115, 71–83. doi: 10.1016/j. pain.2005.02.009 Moore, R. A., Derry, S., Aldington, D., Cole, P., and Wiffen, P. J. (2015). Amitriptyline for neuropathic pain in adults. Cochrane Database Syst. Rev. 2015:CD008242. doi: 10.1002/14651858.CD008242.pub3 Morgalla, M. H., Bolat, A., Fortunato, M., Lepski, G., and Chander, B. S. (2017). Dorsal root ganglion stimulation used for the treatment of chronic neuropathic pain in the groin: a single-center study with long-term prospective results in 34 cases. Neuromodulation 20, 753–760. doi: 10.1111/ner.12713 Li, H., An, H., Wang, Y., Huang, J., and Gao, X. (2016). Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: based on two-mode affiliation network. Phys. A Stat Mech Appl. 450, 657–669. doi: 10.1016/j. physa.2016.01.017 Orihuela, R., McPherson, C. A., and Harry, G. J. (2016). Microglial M1/M2 polarization and metabolic states. Br. J. Pharmacol. 173, 649–665. doi: 10.1111/ bph.13139 Li, J., Deng, G., Wang, H., Yang, M., Yang, R., Li, X., et al. (2017). References doi: 10.1016/j.jpain.2005.02.001 Rasche, D., Ruppolt, M., Stippich, C., Unterberg, A., and Tronnier, V. M. (2006). Motor cortex stimulation for long-term relief of chronic neuropathic pain: a 10 year experience. Pain 121, 43–52. doi: 10.1016/j.pain.2005.12.006 Liu, J., Gao, J., Niu, Q., Wu, F., Wu, Z., and Zhang, L. (2022). Bibliometric and visualization analysis of mesenchymal stem cells and rheumatoid arthritis (from 2012 to 2021). Front. Immunol. 13:1001598. doi: 10.3389/fimmu.2022.1001598 Ruiz-Cantero, M. C., González-Cano, R., Tejada, M. Á., Santos-Caballero, M., Perazzoli, G., Nieto, F. R., et al. (2021). Sigma-1 receptor: a drug target for the modulation of neuroimmune and neuroglial interactions during chronic pain. Pharmacol. Res. 163:105339. doi: 10.1016/j.phrs.2020.105339 Liu, W.-Z., Ma, Z.-J., Li, J.-R., and Kang, X.-W. (2021). Mesenchymal stem cell-derived exosomes: therapeutic opportunities and challenges for spinal cord injury. Stem Cell Res Ther 12, 1–15. doi: 10.1186/s13287-021-02153-8 Sala Frigerio, C., Wolfs, L., Fattorelli, N., Thrupp, N., Voytyuk, I., Schmidt, I., et al. (2019). The major risk factors for Alzheimer’s disease: age, sex, and genes modulate the microglia response to Aβ plaques. Cell Rep. 27, 1293–1306.e6. doi: 10.1016/j. celrep.2019.03.099 Luongo, L., Palazzo, E., Tambaro, S., Giordano, C., Gatta, L., Scafuro, M. A., et al. (2010). 1-(2′,4′-dichlorophenyl)-6-methyl-N-cyclohexylamine-1,4-dihydroindeno [1,2- c]pyrazole-3-carboxamide, a novel CB2 agonist, alleviates neuropathic pain through functional microglial changes in mice. Neurobiol. Dis. 37, 177–185. doi: 10.1016/j. nbd.2009.09.021 Schäfer, S., Berger, J. V., Deumens, R., Goursaud, S., Hanisch, U. K., and Hermans, E. (2014). Influence of intrathecal delivery of bone marrow-derived mesenchymal stem cells on spinal inflammation and pain hypersensitivity in a rat model of peripheral nerve injury. J. Neuroinflammation 11, 1–15. doi: 10.1186/s12974-014-0157-8 Ma, L., Jia, J., Liu, X., Bai, F., Wang, Q., and Xiong, L. (2015). Activation of murine microglial N9 cells is attenuated through cannabinoid receptor CB2 signaling. Biochem. Biophys. Res. Commun. 458, 92–97. doi: 10.1016/j.bbrc.2015.01.073 Sideris-Lampretsas, G., and Malcangio, M. (2021). Microglial heterogeneity in chronic pain. Brain Behav. Immun. 96, 279–289. doi: 10.1016/j.bbi.2021.06.005 Masuda, T., Sankowski, R., Staszewski, O., and Prinz, M. (2020). Microglia heterogeneity in the single-cell era. Cell Rep. 30, 1271–1281. doi: 10.1016/j. celrep.2020.01.010 Siniscalco, D., Giordano, C., Galderisi, U., Luongo, L., de Novellis, V., Rossi, F., et al. (2011). Long-lasting effects of human Mesenchymal stem cell systemic administration on pain-like behaviors, cellular, and biomolecular modifications in neuropathic mice. Front. Integr. Neurosci. 5:79. doi: 10.3389/fnint.2011.00079/full Mecha, M., Feliú, A., Carrillo-Salinas, F. J., Rueda-Zubiaurre, A., Ortega-Gutiérrez, S., de Sola, R. G., et al. (2015). References Interleukin-1β pre- treated bone marrow stromal cells alleviate neuropathic pain through CCL7-mediated inhibition of microglial activation in the spinal cord. Sci. Rep. 7:42260. doi: 10.1038/ srep42260 Paolicelli, R. C., Sierra, A., Stevens, B., Tremblay, M. E., Aguzzi, A., Ajami, B., et al. (2022). Microglia states and nomenclature: a field at its crossroads. Neuron 110, 3458–3483. doi: 10.1016/j.neuron.2022.10.020 Li, S., Huang, C., Tu, C., Chen, R., Ren, X., Qi, L., et al. (2022). Bone marrow mesenchymal stem cell-derived exosomes shuttling miR-150-5p alleviates mechanical allodynia in rats by targeting NOTCH2 in microglia. Mol. Med. 28, 1–16. doi: 10.1186/ s10020-022-00561-x Peng, X., Guo, H., Yuan, J., Chen, Y., Xia, Y., Wang, L., et al. (2021). Extracellular vesicles released from hiPSC-derived MSCs attenuate chronic prostatitis/chronic pelvic pain syndrome in rats by immunoregulation. Stem Cell Res Ther 12:198. doi: 10.1186/ s13287-021-02269-x Li, C., Shu, X., and Liu, X. (2022). Research hotspots and Frontiers in post stroke pain: a Bibliometric analysis study. Front. Mol. Neurosci. 15:905679. doi: 10.3389/ fnmol.2022.905679 Popiolek-Barczyk, K., Kolosowska, N., Piotrowska, A., Makuch, W., Rojewska, E., Jurga, A. M., et al. (2015). Parthenolide relieves pain and promotes M2 microglia/ macrophage polarization in rat model of neuropathy. Neural Plast. 2015:e676473, 1–15. doi: 10.1155/2015/676473 Li, J., Xu, L., Deng, X., Jiang, C., Pan, C., Chen, L., et al. (2016). N-acetyl-cysteine attenuates neuropathic pain by suppressing matrix metalloproteinases. Pain 157, 1711–1723. doi: 10.1097/j.pain.0000000000000575 Racz, I., Nadal, X., Alferink, J., Baños, J. E., Rehnelt, J., Martín, M., et al. (2008). Crucial role of CB (2) cannabinoid receptor in the regulation of central immune responses during neuropathic pain. J. Neurosci. 28, 12125–12135. doi: 10.1523/ JNEUROSCI.3400-08.2008 Liao, H., Tang, M., Luo, L., Li, C., Chiclana, F., and Zeng, X. J. (2018). A Bibliometric analysis and visualization of medical big data research. Sustainability. 10:166. doi: 10.3390/su10010166 Raghavendra, V., Tanga, F., and DeLeo, J. A. (2003). Inhibition of microglial activation attenuates the development but not existing hypersensitivity in a rat model of neuropathy. J. Pharmacol. Exp. Ther. 306, 624–630. doi: 10.1124/ jpet.103.052407 Lim, H., Lee, H., Noh, K., and Lee, S. J. (2017). IKK/NF-κB-dependent satellite glia activation induces spinal cord microglia activation and neuropathic pain after nerve injury. Pain 158, 1666–1677. doi: 10.1097/j.pain.0000000000000959 Lindia, J. A., McGowan, E., Jochnowitz, N., and Abbadie, C. (2005). Induction of CX3CL1 expression in astrocytes and CX3CR1 in microglia in the spinal cord of a rat model of neuropathic pain. J. Pain 6, 434–438. References doi: 10.1002/glia.10308 Yang, Z., Lin, J., Li, H., He, Z., Wang, K., Lei, L., et al. (2022). Bibliometric and visualization analysis of macrophages associated with osteoarthritis from 1991 to 2021. Front. Immunol. 13:1013498. doi: 10.3389/fimmu.2022.1013498 Tsuda, M., Shigemoto-Mogami, Y., Koizumi, S., Mizokoshi, A., Kohsaka, S., Salter, M. W., et al. (2003). P2X4 receptors induced in spinal microglia gate tactile allodynia after nerve injury. Nature 424, 778–783. doi: 10.1038/nature01786 Yang, H., Wu, L., Deng, H., Chen, Y., Zhou, H., Liu, M., et al. (2020). Anti- inflammatory protein TSG-6 secreted by bone marrow mesenchymal stem cells attenuates neuropathic pain by inhibiting the TLR2/MyD88/NF-κB signaling pathway in spinal microglia. J. Neuroinflammation 17, 1–21. doi: 10.1186/s12974-020-1731-x Vacca, V., Marinelli, S., Luvisetto, S., and Pavone, F. (2013). Botulinum toxin a increases analgesic effects of morphine, counters development of morphine tolerance and modulates glia activation and μ opioid receptor expression in neuropathic mice. Brain Behav. Immun. 32, 40–50. doi: 10.1016/j.bbi.2013.01.088 Yang, J. L., Xu, B., Li, S. S., Zhang, W. S., Xu, H., Deng, X. M., et al. (2012). Gabapentin reduces CX3CL1 signaling and blocks spinal microglial activation in monoarthritic rats. Mol. Brain 5:18. doi: 10.1186/1756-6606-5-18 van Eck, N., and Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84, 523–538. doi: 10.1007/ s11192-009-0146-3 Zhang, J., Hoffert, C., Vu, H. K., Groblewski, T., Ahmad, S., and O’Donnell, D. (2003). Induction of CB2 receptor expression in the rat spinal cord of neuropathic but not inflammatory chronic pain models. Eur. J. Neurosci. 17, 2750–2754. doi: 10.1046/j.1460-9568.2003.02704.x Verge, G. M., Milligan, E. D., Maier, S. F., Watkins, L. R., Naeve, G. S., and Foster, A. C. (2004). Fractalkine (CX3CL1) and fractalkine receptor (CX3CR1) distribution in spinal cord and dorsal root ganglia under basal and neuropathic pain conditions. Eur. J. Neurosci. 20, 1150–1160. doi: 10.1111/j.1460-9568.2004.03593.x Zhao, H., Alam, A., Chen, Q., Eusman, M. A., Pal, A., Eguchi, S., et al. (2017). The role of microglia in the pathobiology of neuropathic pain development: what do we know? Br. J. Anaesth. 118, 504–516. doi: 10.1093/bja/aex006 Wang, N., Liang, H., and Zen, K. (2014). Molecular mechanisms that influence the macrophage M1–M2 polarization balance. Front. Immunol. 5:614. doi: 10.3389/ fimmu.2014.00614/full Zhong, Z., Chen, A., Fa, Z., Ding, Z., Xiao, L., and Wu, G. (2020). References Endocannabinoids drive the acquisition of an alternative phenotype in microglia. Brain Behav. Immun. 49, 233–245. doi: 10.1016/j.bbi.2015.06.002 Small, H. (1973). Co-citation in the scientific literature: a new measure of the relationship between two documents. J. Am. Soc. Inf. Sci. 24, 265–269. doi: 10.1002/ asi.4630240406 Medina, S., Ihrie, R. A., and Irish, J. M. (2022). Learning cell identity in immunology, neuroscience, and cancer. Semin. Immunopathol. 45, 3–16. doi: 10.1007/ s00281-022-00976-y Soliman, N., Haroutounian, S., Hohmann, A. G., Krane, E., Liao, J., Macleod, M., et al. (2021). Systematic review and meta-analysis of cannabinoids, cannabis-based medicines, and endocannabinoid system modulators tested for antinociceptive effects in animal models of injury-related or pathological persistent pain. Pain 162, S26–S44. doi: 10.1097/j.pain.0000000000002269 Mika, J., Zychowska, M., Popiolek-Barczyk, K., Rojewska, E., and Przewlocka, B. (2013). Importance of glial activation in neuropathic pain. Eur. J. Pharmacol. 716, 106–119. doi: 10.1016/j.ejphar.2013.01.072 Milligan, E. D., and Watkins, L. R. (2009). Pathological and protective roles of glia in chronic pain. Nat. Rev. Neurosci. 10, 23–36. doi: 10.1038/nrn2533 Sorge, R. E., Mapplebeck, J. C. S., Rosen, S., Beggs, S., Taves, S., Alexander, J. K., et al. (2015). Different immune cells mediate mechanical pain hypersensitivity in male and female mice. Nat. Neurosci. 18, 1081–1083. doi: 10.1038/nn.4053 Milligan, E. D., Zapata, V., Chacur, M., Schoeniger, D., Biedenkapp, J., O’Connor, K. A., et al. (2004). Evidence that exogenous and endogenous fractalkine can induce spinal nociceptive facilitation in rats. Eur. J. Neurosci. 20, 2294–2302. doi: 10.1111/j.1460-9568.2004.03709.x Staniland, A. A., Clark, A. K., Wodarski, R., Sasso, O., Maione, F., D’Acquisto, F., et al. (2010). Reduced inflammatory and neuropathic pain and decreased spinal microglial response in fractalkine receptor (CX3CR1) knockout mice. J. Neurochem. 114, 1143–1157. doi: 10.1111/j.1471-4159.2010.06837.x Mitrirattanakul, S., Ramakul, N., Guerrero, A. V., Matsuka, Y., Ono, T., Iwase, H., et al. (2006). Site-specific increases in peripheral cannabinoid receptors and their endogenous ligands in a model of neuropathic pain. Pain 126, 102–114. doi: 10.1016/j.pain.2006.06.016 Tao, L., Ding, Q., Gao, C., and Sun, X. (2016). Resveratrol attenuates neuropathic pain through balancing pro-inflammatory and anti-inflammatory cytokines release in mice. Int. Immunopharmacol. 34, 165–172. doi: 10.1016/j.intimp.2016.02.033 Moghadasi, S., Elveny, M., Rahman, H. S., Suksatan, W., Jalil, A. T., Abdelbasset, W. K., et al. (2021). A paradigm shift in cell-free approach: the emerging role of MSCs-derived 19 Frontiers in Molecular Neuroscience frontiersin.org Zhang et al. Zhang et al. 10.3389/fnmol.2023.1142852 reduced inflammatory cell recruitment. Stem Cells 33, 1902–1914. doi: 10.1002/ stem.2006 Tay, T. References L., Mai, D., Dautzenberg, J., Fernández-Klett, F., Lin, G., Sagar, N., et al. (2017). A new fate mapping system reveals context-dependent random or clonal expansion of microglia. Nat. Neurosci. 20, 793–803. doi: 10.1038/nn.4547 Wei, F., Guo, W., Zou, S., Ren, K., and Dubner, R. (2008). Supraspinal glial–neuronal interactions contribute to descending pain facilitation. J. Neurosci. 28, 10482–10495. doi: 10.1523/JNEUROSCI.3593-08.2008 Teng, Y., Zhang, Y., Yue, S., Chen, H., Qu, Y., Wei, H., et al. (2019). Intrathecal injection of bone marrow stromal cells attenuates neuropathic pain via inhibition of P2X4R in spinal cord microglia. J. Neuroinflammation 16:271. doi: 10.1186/ s12974-019-1631-0 Wei, N., Xu, Y., Li, Y., Shi, J., Zhang, X., You, Y., et al. (2022). A bibliometric analysis of T cell and atherosclerosis. Front. Immunol 13:948314. doi: 10.3389/fimmu.2022.948314 Torrance, N., Smith, B. H., Bennett, M. I., and Lee, A. J. (2006). The epidemiology of chronic pain of predominantly neuropathic origin. Results from a general population survey. J. Pain 7, 281–289. doi: 10.1016/j.jpain.2005.11.008 Woodburn, S. C., Bollinger, J. L., and Wohleb, E. S. (2021). The semantics of microglia activation: neuroinflammation, homeostasis, and stress. J. Neuroinflammation 18:258. doi: 10.1186/s12974-021-02309-6 Trang, T., Beggs, S., Wan, X., and Salter, M. W. (2009). P2X4-receptor-mediated synthesis and release of brain-derived neurotrophic factor in microglia is dependent on calcium and p38-mitogen-activated protein kinase activation. J. Neurosci. 29, 3518–3528. doi: 10.1523/JNEUROSCI.5714-08.2009 Wu, J., Hocevar, M., Bie, B., Foss, J. F., and Naguib, M. (2019). Cannabinoid type 2 receptor system modulates paclitaxel-induced microglial dysregulation and central sensitization in rats. J. Pain 20, 501–514. doi: 10.1016/j.jpain.2018.10.007 Wu, K., Liu, Y., Liu, L., Peng, Y., Pang, H., Sun, X., et al. (2022). Emerging trends and research foci in tumor microenvironment of pancreatic Cancer: a Bibliometric and visualized study. Front. Oncol. 12:810774. doi: 10.3389/fonc.2022.810774 Tsuda, M., Masuda, T., Kitano, J., Shimoyama, H., Tozaki-Saitoh, H., and Inoue, K. (2009). IFN-γ receptor signaling mediates spinal microglia activation driving neuropathic pain. Proc. Natl. Acad. Sci. 106, 8032–8037. doi: 10.1073/ pnas.0810420106 Xu, Y., Zhang, Z., He, J., and Chen, Z. (2022). Immune effects of macrophages in rheumatoid arthritis: a bibliometric analysis from 2000 to 2021. Front. Immunol. 13:903771. doi: 10.3389/fimmu.2022.903771/full Tsuda, M., Mizokoshi, A., Shigemoto-Mogami, Y., Koizumi, S., and Inoue, K. (2004). Activation of p38 mitogen-activated protein kinase in spinal hyperactive microglia contributes to pain hypersensitivity following peripheral nerve injury. Glia 45, 89–95. Frontiers in Molecular Neuroscience References Bone marrow mesenchymal stem cells upregulate PI3K/AKT pathway and down-regulate NF-κB pathway by secreting glial cell-derived neurotrophic factors to regulate microglial polarization and alleviate deafferentation pain in rats. Neurobiol. Dis. 143:104945. doi: 10.1016/j.nbd.2020.104945 Wang, S., Zhou, H., Zheng, L., Zhu, W., Zhu, L., Feng, D., et al. (2021). Global trends in research of macrophages associated with acute lung injury over past 10 years: a Bibliometric analysis. Front. Immunol. 12:669539. doi: 10.3389/fimmu.2021.669539 Zhuang, Z. Y., Kawasaki, Y., Tan, P. H., Wen, Y. R., Huang, J., and Ji, R. R. (2007). Role of the CX3CR1/p38 MAPK pathway in spinal microglia for the development of neuropathic pain following nerve injury-induced cleavage of fractalkine. Brain Behav. Immun. 21, 642–651. doi: 10.1016/j.bbi.2006.11.003 Watanabe, S., Uchida, K., Nakajima, H., Matsuo, H., Sugita, D., Yoshida, A., et al. (2015). Early transplantation of mesenchymal stem cells after spinal cord injury relieves pain hypersensitivity through suppression of pain-related signaling cascades and 20 20 frontiersin.org Frontiers in Molecular Neuroscience
https://openalex.org/W2503623791	https://www.intechopen.com/citation-pdf-url/51016	English	null	Oligoastrocytoma: A Vanishing Tumor Entity	InTech eBooks	2,016	cc-by	8,737	Additional information is available at the end of the chapter Additional information is available at the end of the chapter http://dx.doi.org/10.5772/63240 Selection of our books indexed in the Book Citation Index in Web of Science™ Core Collection (BKCI) Interested in publishing with us? Contact book.department@intechopen.com Numbers displayed above are based on latest data collected. For more information visit www.intechopen.com Open access books available Countries delivered to Contributors from top 500 universities International authors and editors Our authors are among the most cited scientists Downloads We are IntechOpen, the world’s leading publisher of Open Access books Built by scientists, for scientists 14% 191,000 210M TOP 1% 154 7,200 Chapter 14 Oligoastrocytoma: A Vanishing Tumor Entity Marta Mellai, Laura Annovazzi, Marta Mazzucco and Davide Schiffer Additional information is available at the end of the chapter http://dx.doi.org/10.5772/63240 Marta Mellai, Laura Annovazzi, Marta Mazzucco and Davide Schiffer Additional information is available at the end of the chapter © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, Keywords: oligoastrocytoma, 1p/19q co-deletion, IDH, ATRX, prognosis 1. Introduction In the 2007 World Health Organization (WHO) classification of the central nervous system (CNS) tumors [1], oligoastrocytoma (OA) was considered as a mixed glioma with an astro‐ cytic and an oligodendroglial component [2, 3]. It could be easily recognized if the two components were clearly separated, as it rarely happened. Usually, the two cell types were found intermingled and the differential diagnosis towards astrocytomas and oligodendro‐ gliomas was difficult and, frequently, it remained undefined. Since its first recognition [4] and confirmation [5], its definability was poor and the tumor was even considered as an oligoden‐ droglioma with reactive astrocytes [6]. The poor tumor definability explains why the preva‐ lence of OAs in the various collections of the literature has been so variable and it accounted for the need to establish criteria useful for the recognition of the tumor. It was suggested to rely on the occurrence of at least 10% neoplastic oligodendrocytes in astrocytic gliomas [7] or 10% neoplastic astrocytes in oligodendroglial gliomas [8], provided that oligodendrocytes were neoplastic and not normal, and that astrocytes were tumor and not reactive. These criteria, however, were too vague in the clinical practice and the definition of the tumor remained a subjective matter. In particular, the recognition of normal from tumor oligoden‐ drocytes, especially in slightly infiltrating or diffuse growth where the cell density is low, remained unsolved [9]. As a matter of fact, the diagnostic uncertainties of OA were also due to the lack of a reliable marker for tumor oligodendrocytes in tissue sections. The prevailing diffuse and infiltrating growth of both oligodendrogliomas and the oligodendroglial component of OAs led to find the coexistence in the same tumor area of tumor and normal oligodendrocytes to the point that it was even difficult to establish, in some cases, whether a tumor infiltration existed or not. On the other hand, the difficulty to recognize a mild oligodendroglial infiltration in oligodendro‐ gliomas themselves was already known, even exploiting the occurrence of abnormal nuclei or crowding of tumor cells along capillaries or around neurons. Another critical point was the difficulty to distinguish reactive from tumor astrocytes and to recognize the real nature of minigemistocytes [10], glial fibrillary oligodendrocytes (GFOC) [11–13], real gemistocytes, and perineural satellites. Abstract Oligoastrocytoma (OA) was a glioma recognized in the current World Health Organization (WHO) classification of the central nervous system (CNS) tumors as a mixed tumor with an astrocytic and an oligodendroglial component. Its definability was, however, poor so that its prevalence varies in the various collections. A series of contributions of the literature and the “International Society of Neuropathology (ISN) – Haarlem Consensus” recently denied its existence as a tumor entity on the basis of 1p/19q, isocitrate dehydrogenase (IDH) and α-thalassemia/mental retardation syndrome X-linked (ATRX) status. Most tumors previously diagnosed as OAs were, therefore, reclassified as either oligodendro‐ gliomas or astrocytomas. We revised 40 OAs from our glioma series initially diagnosed with stringent histologic criteria. After the revision based on the above mentioned molecular markers, most of them changed diagnosis falling into the categories of oligodendroglioma or astrocytoma. Only one fulfilled the stringent criteria of the current classification system, whereas two cases remained undefined. Since ATRX is constitutively expressed in microglia/macrophages, their number in the histologic sections has a paramount importance in recognizing the oligodendroglial component. The double ATRX/GFAP, ATRX/IDH1R132H and ATRX/Iba-1 immunostain‐ ings greatly conditions the recognition of the oligodendroglial and astrocytic tumor cells. Keywords: oligoastrocytoma, 1p/19q co-deletion, IDH, ATRX, prognosis © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, Neurooncology - Newer Developments 340 2.4. Clinical features The most common symptoms were seizure, headache, and personality changes. 1. Introduction The origin of the tumor was referred to a progenitor stage preceding the astrocytic and oli‐ godendroglial differentiation and, therefore, tumor suppressor protein p53 (TP53) mutations were searched for in the astrocytic component and the 1p/19q co-deletion in the oligoden‐ droglial one and a genetic analysis was suggested [14]. Anyway, the variability of OA prev‐ alence in the various collections remained high. It was observed that the absence of 1p/19q co-deletion, typical of oligodendrogliomas, entailed the occurrence of TP53 mutations [15], but also that it could be present or absent in both tumor components and that all tumor cells seemed to share the same genetic aberrations [14]. Oligoastrocytoma: A Vanishing Tumor Entity http://dx.doi.org/10.5772/63240 341 2.2. Etiology Common risk factors in the development of OA included family history of brain tumors, ionizing radiation, and allergic diseases. 2.3. Location OA preferentially developed in the cerebral hemispheres with a frequency that correspond‐ ed to the relative size of the cerebral lobes (frontal, temporal, parietal, and occipital) [1]. It commonly arose in the supratentorial regions. Occasional locations were insula, diencepha‐ lon, and spinal cord whereas cerebellar location was very uncommon. 2.1. Incidence OA was the third most common glioma. It accounted for 1% of all brain tumors and 5–10% of all glial neoplasms. The incidence of OA was approximately 0.03 per 100,000 individuals in the United States. Young and middle-aged adult population was affected. The median age of diagnosis was 42 years. Males were more commonly affected than females; the male to female ratio was approximately 1.43–1. OA usually affected individuals of the Caucasian race with a higher incidence rate in developed countries [1]. 3. Histopathology According to the current WHO classification system [1], OA was classified in two subtypes: grade II OA (OAII) and grade III OA (OAIII). 3.1. Macroscopic appearance On gross pathology, OA was characterized by a soft, well-defined, grey-tan, mucoid or hemorrhagic, calcified mass with or without necrosis that may expand the gyrus, and cause blurring of the grey white matter junction. 2.5. Neuroradiological features On magnetic resonance imaging (MRI), OA was described as characterized by a mass which is typically hypointense on T1-weighted images and hyperintense on T2-weighted images. No enhancement is observed on Gadolinium enhanced T1-weighted images (Figure 1A, B). Figure 1. Magnetic resonance imaging (MRI) of 20-years old woman. A – OA, T1-weighted sequence after gadolinium contrast enhancement (arrow); B – Id, hyperintensity in T2-weighted sequence. Figure 1. Magnetic resonance imaging (MRI) of 20-years old woman. A – OA, T1-weighted sequence after gadolinium contrast enhancement (arrow); B – Id, hyperintensity in T2-weighted sequence. Neurooncology - Newer Developments 342 3.2. Microscopic appearance On histopathologic analysis, OA was characterized by highly cellular lesions composed of both tumor astrocytes and oligodendrocytes that could be separated or intermingled [5], i.e. the tumor could be defined as “biphasic” (Figure 2A–C) or “diffuse” (Figure 2D). Astrocytic tumor cells scattered within oligodendroglial cells had to be recognized as neoplastic and not reactive/ hypertrophic astrocytes. Figure 2. Histopathologic features of OA. A – OAII with separated astrocytic and oligodendroglial components, x100; B – Id, astrocytic component, x400; C – Id, oligodendroglial component, x400; D – OAII with intermingled astrocytic and oligodendroglial cells, x200; E – OAIII, x200. All hematoxylin and eosin (H&E). Figure 2. Histopathologic features of OA. A – OAII with separated astrocytic and oligodendroglial components, x100; B – Id, astrocytic component, x400; C – Id, oligodendroglial component, x400; D – OAII with intermingled astrocytic and oligodendroglial cells, x200; E – OAIII, x200. All hematoxylin and eosin (H&E). OAII. The tumor showed a moderate cellularity with no or low mitotic activity. Microcalcifi‐ cations and microcystic degeneration could occur. Reactive astrocytes are present in all gliomas, OA included; in the latter, their distinction from tumor astrocytes was the most important problem since the protean appearance of reactive Oligoastrocytoma: A Vanishing Tumor Entity http://dx.doi.org/10.5772/63240 343 astrocytes, with large cytoplasms, and thick and long processes or with small cytoplasms with short processes and in variable number, did not allow a clear-cut distinction from tumor astrocytes. An important bias was the occurrence of minigemistocytes, GFOC, and true gemistocytes. Both minigemistocytes and GFOC were regarded as either transitional forms between oligoden‐ drocytes and astrocytes, corresponding to a bipotential glial progenitor cell [16], or as glial fibrillary acidic protein (GFAP) expressing oligodendrocytes [12], remnants of myelin forming glia of the developmental period [13]. A high frequency of minigemistocytes could confer an astrocytic aspect to the tumor. OAIII. The tumor was mainly characterized by a significant or brisk mitotic activity (≥ 6 mitoses per 10 high power field [HPF]) and a high Ki-67/MIB-1 proliferation index, nuclear atypia, necrosis, and apoptotic cells (Figure 2E). The malignant transformation was considered as proceeding either from the one or the other cell component. In the differential diagnosis towards glioblastoma (GBM), the occurrence of circumscribed necroses was decisive; the presence of microvascular proliferations (MVPs) would indicate the grade III when occurring in the oligodendroglial part and the grade IV when in the astrocytic one. 3.3. Immunohistochemistry (IHC) IHC was practically based only on GFAP expression. No specific immunohistochemical marker was available for oligodendrocytes [17, 18], although MAP2, OLIG2, Cyclin D1, and alpha-internexin (INA) immunopositivity could be found in the oligodendroglial compo‐ nent. Approximately one third of OAs showed nuclear p53 accumulation, more commonly in the astrocytic cells [19]. 4. Molecular genetics As in all gliomas, the origin of the tumor proceeds from the step-wise accumulation of genetic/ epigenetic alterations. Thirty-fifty percent of OAs exhibited loss of heterozygosity (LOH) on chromosomes 1p and 19q [20, 21], while approximately 30% of them harboured TP53 muta‐ tions. In particular, OAs of the temporal lobe more frequently exhibited TP53 mutations, and less commonly, 1p and 19q losses [22, 23]. OAII typically exhibited the type and distribution of genetic alterations observed in grade II gliomas [22]. OAIII showed genetic alterations commonly involved in the progression of astrocytic and oligodendroglial tumors, including loss of 9p with homozygous deletion of the cyclin-dependent kinase inhibitor 2A (CDKN2A) (p14ARF) gene, allelic loss on chromosome 10q and epidermal growth factor receptor (EGFR) gene amplification [24]. 344 Neurooncology - Newer Developments 6. New criteria for glioma diagnosis after the “ISN-Haarlem Consensus” Our knowledge on the nature of OA underwent a profound change after the “International Society of Neuropathology (ISN)-Haarlem Consensus” guidelines led to the official recogni‐ tion of the indispensability of the genetic analysis in order to obtain an “integrated” diagno‐ sis of gliomas [28]. Referred to grade II and III adult gliomas, this new approach would involve a combination of histologic and molecular data based on the 1p/19q, isocitrate dehydrogen‐ ase (IDH) 1/2 and α-thalassemia/mental retardation syndrome X-linked (ATRX) status. 5. Treatment and prognosis OAs responded less favourably to chemotherapy (CHT) due to the chemoresistance of their astrocytic components [25]. Studies have shown that the standard of care for 1p/19q co-deleted oligodendroglial tumors should be the combination of CHT and radiotherapy (RT). In OA, a favourable prognosis was associated to young age, grade II and extent of resection [26]. Compared to astrocytomas, OAs shared with oligodendrogliomas a more favourable prog‐ nosis and an improved response to adjuvant therapy. The NOA-04 prospective trial on anaplastic gliomas reported virtually identical outcomes for patients with oligodendroglio‐ mas or OAs [27]. 6.1. 1p/19q chromosomal status The genetic hallmark of oligodendroglial tumors is a combined chromosomal deletion of the short arm of the chromosome 1 (1p) and the long arm of the chromosome 19 (19q). Com‐ bined 1p and 19q losses were described in 80–90% of grade II and in 50–70% of grade III tumors [22, 24]. The 1p/19q chromosomal status was recognized as an important diagnostic biomarker in the clinical practice. The 1p/19q co-deletion was reported in 60–70% of oligodendrogliomas with a classical histologic phenotype (perinuclear “halo” and “chicken wire” vascular pattern). Partial 1p or 19q deletion occurred in approximately 75% of the cases [29, 30]. Oligodendro‐ glial tumors with 1p/19q co-deletion were observed to typically arise at an extra-temporal location, whereas tumors with intact 1p/19q at the temporal lobe [22]. In contrast, childhood oligodendrogliomas only rarely exhibited chromosomal abnormalities. Importantly, the occurrence of 1p/19q co-deletion supports the diagnosis of oligodendroglio‐ ma, especially when histology is atypical. However, its absence does not exclude this diagno‐ sis, leaving unsolved the question of oligodendrogliomas with intact 1p/19q. In OA, the frequency of the 1p/19q co-deletion was approximately 50% [22]. Virtually, it was mutually exclusive with LOH of chromosome 17p13 and TP53 mutations, both typical of astrocytic tumors. In OA, the 1p/19q co-deletion was referred to the oligodendroglial compo‐ nent, whereas TP53 mutations to the astrocytic one. Oligoastrocytoma: A Vanishing Tumor Entity http://dx.doi.org/10.5772/63240 345 345 6.1.1. Mechanism of the combined loss of the chromosomes 1p and 19q The mechanism of the combined loss of the two chromosomal arms is an unbalanced t(1;19) (q10;p10) translocation of 19p to 1q. A centromeric or pericentromeric translocation of chromosomes 1 and 19 results in two derivative chromosomes, der(1;19)(p10;q10) and der(1;19)(q10;p10), followed by the loss of the derivative chromosome containing the short arm of chromosome 1 and the long arm of chromosome 19 [31, 32]. The extent of the 1p/19q co-deletion has important diagnostic and prognostic implications. The chromosomal arm 1p is entirely deleted only in pure oligodendroglial tumors and the whole- arm 1p deletion has a strong favorable prognostic significance. Small telomeric (1p36) or interstitial 1p deletions are frequent as well, but with an opposite prognostic significance; they associate neither with deletion on the chromosomal arm 19q [33] nor with response to CHT [34]. 6.1. 1p/19q chromosomal status While the total 1p/19q co-deletion is almost completely exclusive of oligodendrogliomas, partial 1p deletions are frequent in GBMs and isolated 19q loss in mixed and astrocytic gliomas in relation to the malignant transformation [35, 36]. Currently, there is a general agreement to diagnose the classical oligodendroglioma only in presence of a whole-arm 1p/19q co-deletion [37, 38]. Most oligodendrogliomas with 1p/19q co-deletion harbor IDH1/2, telomerase reverse transcriptase (TERT), homolog of the Drosophila capicua (CIC) and far upstream element- binding protein 1 (FUBP1) somatic mutations, and O6-methylguanine-DNA methyltransfer‐ ase (MGMT) or CDKN2A (p14ARF) promoter hypermethylation [37, 39–41]. 6.1.2. Methods for the detection of 1p/19q chromosomal status Different methods for the detection of the 1p/19q chromosomal status are employed in the routine diagnostics. Fluorescent in situ hybridization (FISH) is a single-locus technique, limited to the 1p36 locus and thus not regarded as a suitable tool due to the high risk of false-posi‐ tive results [34, 37, 42, 43]. On the other hand, LOH analysis is generally carried out with a low number of microsatellite markers covering only a small chromosomal region. In contrast, multi-locus techniques, as comparative genomic hybridization (CGH) or multi‐ plex ligation-dependent probe amplification (MLPA) detect gene copy number changes on the whole chromosome and distinguish whole-arm from partial 1p deletion [44]. Additionally, they can reveal putative gain of functions on both 1p and 19q chromosomes [45, 46]. In particular, MLPA has been validated as a high-resolution gene dosage assay for the screening of large deletions and duplication/amplification events in human cancers. In gliomas, three independent studies validated MLPA to assess the 1p/19q status by compar‐ ing MLPA data with CGH data obtained on the same tumor series, mainly composed of oligodendroglial tumors [47–49]. In the authors’ experience, MLPA is a reliable and power‐ ful tool to assess the 1p/19q status on formalin fixed and paraffin embedded tumor samples. Neurooncology - Newer Developments 346 6.2. IDH1/2 mutations IDHs catalyze the oxidative decarboxylation of isocitrate to α-ketoglutarate with production of NADH/NADPH and they are involved in the Krebs cycle. Recurrent somatic point mutations affect the arginine (Arg) residue at codon 132 in the IDH1 gene on chromosome 2q33.3. Less frequently, they occur at the homolog Arg (R) residue at codon 172 in the IDH2 gene on chromosome 15q26.1. The IDH1/2 mutation rate is in the range of 70– 80% in OII and OIII [50–53] and less in OAII and OAIII, with a higher frequency in 1p/ 19q co-deleted tumors [37]. IDH1 mutations prevail in astrocytic tumors whereas IDH2 mutations are more common in oligodendroglial tumors [51, 54]. In low grade gliomas, they are prognostic favorable factors [53, 55, 56]. The c.395G>A (p.R132H) mutation can be easily detected by a anti-IDH1R132H mutation-specific antibody by immunohistochemical techniques [53, 57]. Tumor cells show IDH1R132H immuno‐ positivity in their cytoplasms, whereas reactive astrocytes and normal glia cells are negative. This is particularly evident in the picture of cortical perineuronal satellitosis where positive (tumor) and negative (normal) satellites can be found, at the beginning of invasion. 6.2.1. ATRX mutations The ATRX gene is located on chromosome Xq21.1, contains 35 exons, and encodes a 2,492 amino acid protein. ATRX belongs to the H3.3-ATRX-DAXX chromatin remodeling path‐ way, involved in chromatin stabilization [58]. ATRX and its binding factor death-associated protein 6 (DAXX) incorporates the histone protein H3.3 into the nucleosome at telomeres and pericentric heterochromatin [59, 60]. Alterations of this function lead to loss of structural integrity at telomeres leading to tumorigenesis. In fact, ATRX or DAXX protein loss is associated to the alternative lengthening of telomeres (ALT), a telomerase-independent mechanism of telomere lengthening [61–66]. Germline ATRX mutations give rise to a syndrome characterized by severe mental retarda‐ tion [67] and to α-thalassemia. Somatic ATRX mutations occur in gliomas of different types and histologic grades [38, 61–65, 68–70]. They are more frequent in grade II (67%) and in grade III (73%) astrocytic tumors and in secondary GBMs (57%), as well as in mixed gliomas (25% in grade II and 27–53.8% in grade III tumors) [64, 65, 69, 70]. In contrast, they are rare in primary GBMs (4%), pediatric GBMs (20%) and in pure oligodendroglial tumors (<10%) [63, 64, 68]. Very importantly, ATRX mutations do not affect pilocytic astrocytomas [64]. ATRX mutations occur in 70% of IDH mutant and intact 1p/19q low grade gliomas [62, 64, 65]. Restricted to IDH mutant tumors, they are significantly associated to TP53 mutations and nuclear p53 overexpression and to astrocytic differentiation; they are mutually exclusive with 1p/19q co-deletion [71, 72]. ATRX and IDH1/2 mutations occur in association and they may represent early genetic alterations in the development of gliomas affecting progenitors before their differentiation along the two lineages. Oligoastrocytoma: A Vanishing Tumor Entity http://dx.doi.org/10.5772/63240 347 In pediatric gliomas, all ATRX mutations cluster near the C-terminal helicase domains; in adult tumors, they are evenly distributed across the gene, mainly as frameshift mutations leading to truncated proteins [63, 64, 69]. The relatively large size of the ATRX gene makes the mutation analysis difficult to be applied in the routine diagnostic procedures. The immunohistochemical evaluation of the ATRX protein expression could represent an alternative method to assess the ATRX status. Although studies reported concordant results between the mutation analysis and IHC [38, 72], tumor heterogeneity in the ATRX expression and concurrent normal non-tumor cells with constitu‐ tive ATRX expression may explain possible discrepancy. 6.2.2. ATRX and prognosis Patients harboring ATRX mutations would show a better outcome [65]. ATRX has important prognostic implications in anaplastic gliomas [65]. ATRX loss is a prognostic factor in IDH mutant and non 1p/19q co-deleted low grade gliomas [62, 65]. In GBMs, ATRX loss affects younger patients [72]. 6.2.1. ATRX mutations As a matter of fact, ATRX muta‐ tions/ATRX protein loss characterizes astrocytic gliomas, whereas retained ATRX immunoreactivity characterizes oligodendroglial gliomas. Referred to OA, the former is typical of the astrocytic component while the latter of the oligodendroglial one [71]. 7. Nosograhic position of OA after the “ISN-Haarlem Consensus” The “integrated” diagnosis provided for grade II and III adult gliomas covers the diagnostic uncertainties between astrocytoma and oligodendroglioma and, mainly, of OA. It has been found that OAs more frequently exhibited the molecular signature of either pure oligodendroglioma (IDH1/2, 1p/19q co-deletion, CIC, FUB1, and TERT promoter mutations) or pure astrocytoma (IDH1/2, TP53, and ATRX mutations) with almost total exclusivity [71]. A recent study proved that most low grade gliomas (including 74 OAs) with IDH1/2 muta‐ tions and intact 1p/19q harbored a high frequency of TP53 mutations (94%) and ATRX mutations (86%) [73]. In 31 of 43 OAs (72.1%), the absence of ATRX mutations, associated with IDH1/2 mutations and total 1p/19q co-deletion, reclassified them as oligodendrogliomas; 11 of 43 (25.6%), with concurrent ATRX protein loss and TP53 mutations were reclassified as astrocytomas. The astrocytes within the tumor were, therefore, interpreted as reactive [71]. These results were similar to a previous one [64] and were confirmed in a large collection of cases [38]. The conclusion is that OA should be removed from the WHO classification as a distinct tumor entity, although rare instances of clearly biphasic OAs exhibiting morphologic and molecu‐ lar heterogeneity have been described. Mixed areas of the tumor could show heterogeneous ATRX immunoreactivity with positive reactive astrocytes and negative tumor astrocytes [74, 75]. As ATRX is ubiquitously expressed in normal cells (endothelial cells, reactive astrocytes, microglia cells, and lymphocytes) [38, 71], the real problem in the diagnosis of OA according Neurooncology - Newer Developments 348 to the 2007 WHO classification seems to ascertain the occurrence of ATRX-negative and IDH1R132H -positive astrocytes in the tumor. The astrocytic and oligodendroglial components have been found to share the same molecu‐ lar signature, but with a sheer cell differentiation [71]. They should be regarded as “morpho‐ logically ambiguous” rather than “mixed” tumors, as conventionally referred. 1p/19q co- deletion and TP53 mutations represent distinct mechanisms of oncogenesis but they do not provide evidence for a genetic signature specifically related to OA [76]. The “ISN-Haarlem Consensus” suggested considering OA or tumors with ambiguous histolo‐ gy as diffuse astrocytoma when harboring IDH1/2 mutations, intact 1p/19q, and ATRX loss; as oligodendroglioma when harboring IDH1/2 mutations, 1p/19q co-deletion, and intact ATRX and as diffuse astrocytoma when harboring wild type IDH. In the absence of molecular data, the tumor should be diagnosed as oligodendroglioma or diffuse astrocytoma not otherwise specified (NOS). 7. Nosograhic position of OA after the “ISN-Haarlem Consensus” Finally, the denomination of OA would be only maintained when molecu‐ lar testing does not solve tumor diagnosis [27]. Anyway, there is no doubt on the usefulness of the ATRX IHC [72] and of the double ATRX/ IDH1R132H immunostaining [77] in the diagnosis of adult diffuse gliomas. Based on molecular data from the above mentioned markers on 54 OAs, it has been concluded that OA repre‐ sents a morphological grey zone rather than a group of truly “mixed” or “intermediate” gliomas [78]. Importantly, it remains unsolved how to explain IDH mutant diffuse gliomas with ATRX expression and intact 1p/19q (neither merely astrocytic nor oligodendroglial lesions) or, more rarely, cases with loss of ATRX protein expression and total 1p/19q co- deletion (both astrocytic and oligodendroglial lesions). 8. Observations on personal OA series Our analysis started from the established principles that 1p/19q co-deletion is typical of oligodendrogliomas, but that it occurs in a low percentage only of tumors with a classical oligodendroglial phenotype (“honeycomb” appearance and “chicken wire” vessels). Our 40 OA cases had been initially diagnosed according to stringent histologic criteria, so that their number is slightly lower compared to others’ series. The current revision has been carried out on the basis of 1p/19q chromosomal status, as detected by MLPA, IDH1/2 mutation status by IHC and sequencing analysis, and ATRX expression by IHC. The key points were: 1) the retained expression of ATRX by tumor oligodendroglial nuclei and by reactive astrocyte, microglia/macrophage, endothelial cell, lymphocyte nuclei, and the ATRX protein loss in tumor astrocytic nuclei; 2) IDH1/2 mutations, present in low grade gliomas with a higher frequency in oligodendrogliomas than astrocytomas [52, 79] (Figure 3A–D); 3) therefore, although they reveal the tumor nature of cells, IDH1/2 mutations can lack both in oligoden‐ droglial and astrocytic tumor cells. As, beside reactive astrocytes, ATRX is expressed in microglia/macrophage nuclei, Iba-1, CD68, CD16, and CD163 IHC has been performed on parallel serial tumor sections, as well as the double ATRX/GFAP, ATRX/Iba-1, and ATRX/ IDHR132H immunostaining. Microglia/macrophages can reach in the tumor sections a frequen‐ Oligoastrocytoma: A Vanishing Tumor Entity http://dx.doi.org/10.5772/63240 349 cy of 50–130 x 40 HPF (personal data); ATRX expressing nuclei could be, therefore, referred to tumor oligodendrocytes only if their number encompasses the number of microglia/macro‐ phage nuclei. The occurrence of microglia/macrophages is, in our experience, the main bias to recognize the oligodendroglial component in OA (Figure 4A–H). Normal oligodendrocytes do not express ATRX and they can be distinguished in this way from tumor oligodendro‐ cytes; moreover, they express Cyclin D1 that, in contrast, is not expressed by tumor oligoden‐ drocytes unless they are cycling cells (Figure 5A–D) [80]. Figure 3. Immunohistochemistry (IHC). A – Oligodendroglioma, ATRX-positive cells, DAB, x200; B – Id, IDH1R132H - positive perinuclear rim in tumor cells, DAB, x200. C – Gemistocytic astrocytoma, ATRX-negative and GFAP-positive tumor astrocytes, double IHC with DAB and Fast Red, respectively, x400; D – Id, IDH1R132H -positive cells, DAB, x400. Anti-IDH1R132H mouse monoclonal antibody (clone H09, Dianova GmbH, Hamburg, Germany) and anti-ATRX rabbit polyclonal antibody (HPA001906, Sigma Aldrich Co., St. Louis, MO, USA). DAB, 3,3'-Diaminobenzidine. Figure 3. Immunohistochemistry (IHC). 8. Observations on personal OA series A – Oligodendroglioma, ATRX-positive cells, DAB, x200; B – Id, IDH1R132H - positive perinuclear rim in tumor cells, DAB, x200. C – Gemistocytic astrocytoma, ATRX-negative and GFAP-positive tumor astrocytes, double IHC with DAB and Fast Red, respectively, x400; D – Id, IDH1R132H -positive cells, DAB, x400. Anti-IDH1R132H mouse monoclonal antibody (clone H09, Dianova GmbH, Hamburg, Germany) and anti-ATRX rabbit polyclonal antibody (HPA001906, Sigma Aldrich Co., St. Louis, MO, USA). DAB, 3,3'-Diaminobenzidine. Figure 4. Immunohistochemistry (IHC). A – Diffuse astrocytoma, GFAP-positive cells, x200; B– Id, scattered ATRX- positive nuclei, the frequency of which corresponds to the frequency of CD68 positive-cells (C), both x200; D – Diffuse astrocytoma, apparent OA with GFAP-positive astrocytes and possible oligodendroglial nuclei, x200; E – Id, scattered ATRX-positive nuclei, x200; F – Id, Iba-1-positive cells covering the number of ATRX-positive nuclei, x200; G – Oligo‐ dendroglial infiltration, ATRX-positive and ATRX-negative nuclei, x200; H – Id, Iba-1-positive cells, x200 in 40 x high power field. All 3,3'-Diaminobenzidine (DAB). Figure 4. Immunohistochemistry (IHC). A – Diffuse astrocytoma, GFAP-positive cells, x200; B– Id, scattered ATRX- positive nuclei, the frequency of which corresponds to the frequency of CD68 positive-cells (C), both x200; D – Diffuse astrocytoma, apparent OA with GFAP-positive astrocytes and possible oligodendroglial nuclei, x200; E – Id, scattered ATRX-positive nuclei, x200; F – Id, Iba-1-positive cells covering the number of ATRX-positive nuclei, x200; G – Oligo‐ dendroglial infiltration, ATRX-positive and ATRX-negative nuclei, x200; H – Id, Iba-1-positive cells, x200 in 40 x high power field. All 3,3'-Diaminobenzidine (DAB). Neurooncology - Newer Developments 50 Figure 5. Immunohistochemistry (IHC). A – Oligodendroglioma, mild infiltration with several ATRX-negative normal oligodendrocytes and few ATRX-positive nuclei (tumor muclei or microglia/macrophage cells?), DAB, x200; B – Id, Cy‐ clin D1-positive normal oligodendrocytes, DAB, x200; C – Oligodendroglioma, ATRX-positive endothelial cells, DAB, x400; D – Gemistocytic astrocytoma, microglia/macrophage cells, Iba-1- and ATRX-positive cells, double IHC with Fast Red and DAB, respectively, x400. DAB, 3,3'-Diaminobenzidine. Figure 5. Immunohistochemistry (IHC). A – Oligodendroglioma, mild infiltration with several ATRX-negative normal oligodendrocytes and few ATRX-positive nuclei (tumor muclei or microglia/macrophage cells?), DAB, x200; B – Id, Cy‐ clin D1-positive normal oligodendrocytes, DAB, x200; C – Oligodendroglioma, ATRX-positive endothelial cells, DAB, x400; D – Gemistocytic astrocytoma, microglia/macrophage cells, Iba-1- and ATRX-positive cells, double IHC with Fast Red and DAB, respectively, x400. DAB, 3,3'-Diaminobenzidine. 8. Observations on personal OA series The diagnosis of the 40 OA cases changed in 87.5% of them (35/40): 22/40 (55%) were reclas‐ sified as astrocytomas due to the absence of total 1p/19q co-deletion, the occurrence of IDH1/2 mutations, and the loss of ATRX expression in GFAP-positive, phenotypically look‐ ing tumor astrocytes (Figure 6A–D); 11/40 (27.5%) were reclassified as oligodendrogliomas due to IDH1/2 mutations, retained ATRX expression, total 1p/19q in 2/11 (18.2%) cases and partial 1p or 19q deletions in 9/11 (81.8%) cases. In 2/40 (5%) cases the diagnosis changed into reactive gliosis due to retained ATRX expression in GFAP-positive reactive astrocytes and to the lack of ATRX-positive oligodendrocytes (Figure 6E–F). Among the remaining five cases, in one case with partial 1p/19q co-deletion, ATRX-negative and GFAP-positive astro‐ cytes co-existed with a number of ATRX-positive and GFAP-negative oligodendrocytes; both cell components showed IDHR132H immunopositivity by double ATRX/IDH1R132H immu‐ nostaining. Importantly, by the double ATRX/Iba-1 immunostaining, it was possible to veri‐ fy that the number of ATRX-positive oligodendroglial nuclei was higher than the number of Iba-1-positive cells. The diagnosis of OA in this case was thus confirmed (Figure 7A). Two wild type IDH cases without total 1p/19q co-deletion and with heterogeneous ATRX expres‐ sion were regarded as ambiguous since the tumor nature of the two cell components could not be ascertained. In the other two cases, one with partial 1p/19q deletion and one with intact 1p/19q, the diagnosis of OA could not be maintained since it was technically impossi‐ ble to perform IDH1R132H IHC. Oligoastrocytoma: A Vanishing Tumor Entity http://dx.doi.org/10.5772/63240 351 Figure 6. Immunohistochemistry (IHC). A – Gemistocytic astrocytoma, GFAP-positive cells, DAB, x200; B – Id, ATRX- negative cells, DAB, x200; C – Anaplastic astrocytoma, GFAP-positive cells, DAB, x200; D – Id, ATRX-negative cells, DAB, x200; E – Oligodendroglioma, reactive astrocytes with GFAP-positive thick cytoplasms and long processes and ATRX-positive nuclei, double IHC with Fast Red and DAB, respectively, x400. F – Reactive gliosis, reactive astrocytes with GFAP-positive large cytoplasms and short processes and ATRX-positive nuclei, double IHC with Fast Red and DAB, respectively, x400. DAB, 3,3'-Diaminobenzidine. Figure 6. Immunohistochemistry (IHC). A – Gemistocytic astrocytoma, GFAP-positive cells, DAB, x200; B – Id, ATRX- negative cells, DAB, x200; C – Anaplastic astrocytoma, GFAP-positive cells, DAB, x200; D – Id, ATRX-negative cells, DAB, x200; E – Oligodendroglioma, reactive astrocytes with GFAP-positive thick cytoplasms and long processes and ATRX-positive nuclei, double IHC with Fast Red and DAB, respectively, x400. 8. Observations on personal OA series F – Reactive gliosis, reactive astrocytes with GFAP-positive large cytoplasms and short processes and ATRX-positive nuclei, double IHC with Fast Red and DAB, respectively, x400. DAB, 3,3'-Diaminobenzidine. Figure 7. Immunohistochemistry (IHC). A – OA, ATRX- and IDH1R132H -positive astrocytes, double IHC with DAB and Fast Red, respectively, x630; B – Oligodendroglial minigemistocytes with ATRX-positive nuclei and GFAP-positive cy‐ toplasms, double IHC with DAB and Fast Red, respectively, x1000; C – Oligodendroglioma, satellitosis with ATRX-pos‐ itive nuclei, DAB, x200; D – Normal cortex, ATRX-positive neurons with ATRX-negative satellites, DAB, x400; E – Oligodendroglial cortical infiltration, ATRX-positive neurons with ATRX-positive and ATRX-negative satellites, DAB, x400; F – Id, ATRX-positive pericapillary tumor cells, DAB, x200. DAB, 3,3'-Diaminobenzidine. Figure 7. Immunohistochemistry (IHC). A – OA, ATRX- and IDH1R132H -positive astrocytes, double IHC with DAB and Fast Red, respectively, x630; B – Oligodendroglial minigemistocytes with ATRX-positive nuclei and GFAP-positive cy‐ toplasms, double IHC with DAB and Fast Red, respectively, x1000; C – Oligodendroglioma, satellitosis with ATRX-pos‐ itive nuclei, DAB, x200; D – Normal cortex, ATRX-positive neurons with ATRX-negative satellites, DAB, x400; E – Oligodendroglial cortical infiltration, ATRX-positive neurons with ATRX-positive and ATRX-negative satellites, DAB, x400; F – Id, ATRX-positive pericapillary tumor cells, DAB, x200. DAB, 3,3'-Diaminobenzidine. Neurooncology - Newer Developments 352 The distinction of reactive from tumor astrocytes has always been a crucial point in the diagnosis of OA. Their recognition as reactive is a point of reference in denying the existence of such tumor category. Reactive astrocytes retain nuclear ATRX protein expression, as tumor oligodendrocytes, while tumor astrocytes lack ATRX expression. The distinction of reactive from tumor astrocytes has always been a crucial point in the diagnosis of OA. Their recognition as reactive is a point of reference in denying the existence of such tumor category. Reactive astrocytes retain nuclear ATRX protein expression, as tumor oligodendrocytes, while tumor astrocytes lack ATRX expression. By comparing our results with those of the literature, it is noteworthy that the change of diagnosis from the initial to the current analyses of cases, largely depends on the criteria used in the initial recognition of OAs. Upon the reclassification of the 35 cases as astrocytoma, oligodendroglioma, or reactive gliosis, only one could deserve the dignity of OA among the remaining five cases. 8. Observations on personal OA series It must be incidentally remark that total 1p/19q co-deletion occurred in 43/113 (38.1%) of our oligodendroglioma series (selected by the typical morphology of honeycomb appearance and chicken wire vessel distribution); partial 1p and/or 19q deletions occurred in 36/82 (43.9%) of oligodendrogliomas and in 12/24 (50%) astrocytomas. Referring to the 40 cases with initial diagnosis of OA, two had total 1p/19q co-deletion, 14 partial 1p/19q deletion, 12 intact 1p/19q, and one a gain of function on the chromosome 19q. For the remaining 11 cases, the 1p/19q status was not available. It is widely accepted that partial 1p/19q deletions may occur in other gliomas, but one wonders how tumors with an oligodendroglial phenotype with partial deletions or intact 1p/19q can be classified. 9. Conclusions By applying the “integrated” approach to the revision of our OA series, we conclude that, OA could no longer be regarded as a separate tumor entity. However, rare cases might retain the OA denomination [74, 75, our case], indicating that tumors can differentiate in oligodendro‐ glial and astrocytic sense, even maintaining the same molecular genetics [71], or that they can arise from progenitors before differentiation in the two lineages. Two points must be emphasized: one is the importance of the double immunostaining to recognize the astrocytic nature of tumor cells, especially the association between IDH and ATRX expression, considering that IDH1/2 mutations prevail in oligodendrogliomas in comparison to astrocytomas [52, 79]. In supposed mixed tumors with the two separate components, it has been observed that these share the same molecular asset and that astro‐ cytes in the tumor are reactive cells [71]. However, in tumors with the two cell types inter‐ mingled, tumor cells can be distinguished from reactive astrocytes by the double ATRX/GFAP immunostaining. It must be remarked that in rare instances 1p/19q co-deletion can be associated with ATRX mutations/ATRX protein loss [64] and that, since a quota of astrocyto‐ mas do not harbor IDH1/2 mutations, tumor astrocytes with wild type IDH may be found. Minigemistocytes show definitely the oligodendroglial nature due to their ATRX-positive nuclei (Figure 7B). The other point is the great influence that microglia/macrophage occurrence may exert in the recognition of tumor oligodendrocytes due to their nuclear ATRX positivity. In cases where Oligoastrocytoma: A Vanishing Tumor Entity http://dx.doi.org/10.5772/63240 353 the number of microglia/macrophages is very high to reach the number of ATRX-positive nuclei, if tumor astrocytes are demonstrable, the tumor should be reclassified as astrocyto‐ ma. In order to recognize an oligodendroglial tumor infiltration, often result of a biopsy, it is still mandatory that the number of ATRX-positive nuclei in a given area encompasses the number of microglia/macrophages (personal data). ATRX-negative nuclei in infiltration areas correspond to normal oligodendrocytes. Only the double ATRX/Iba-1 immunostaining can reveal the occurrence of normal oligodendrocytes, beside their Cyclin D1 expression. In IDH1R132H mutant cases, the double ATRX/IDH1R132H immunostaining unequivocally identi‐ fies oligodendroglial tumor cells. The coexistence of normal and tumor oligodendrocytes by ATRX IHC can be demonstrated in perineuronal satellitosis: in its initial phases, ATRX-positive and ATRX-negative nuclei are found around neurons; in later phases, all nuclei are ATRX- positive (Figure 7C–E). 9. Conclusions The same can be said for pericapillary satellitosis (Figure 7F). The last point to be discussed is the possibility to find a false “honeycomb” appearance mimicking the typical perinuclear “halo” with ATRX-positive nuclei. This aspect cannot be interpreted as suggestive of an oligodendroglial origin of the tumor, being expressions of a water disturb/edema of unspecified nature, as it may happen for instance, in pilocytic astro‐ cytoma [81]. Disclosure of Potential Conflicts of Interest: Authors declare no potential conflicts of interest. p y p g g We thank Fondazione Cassa di Risparmio di Vercelli (Vercelli, Italy) for the support to the elaboration of this chapter. Disclosure of Potential Conflicts of Interest: Authors declare no potential conflicts of interest. Author details Marta Mellai, Laura Annovazzi, Marta Mazzucco and Davide Schiffer* Address all correspondence to: davide.schiffer@unito.it Research Center/Policlinico di Monza Foundation, Vercelli, (Italy) We thank Fondazione Cassa di Risparmio di Vercelli (Vercelli, Italy) for the support to the elaboration of this chapter. Acknowledgements We thank Dr. M.C. Valentini (Neuroradiology Department / Città della Salute e della Scienza Hospital, Turin, Italy) for providing the MRI figures. Author details Marta Mellai, Laura Annovazzi, Marta Mazzucco and Davide Schiffer *Address all correspondence to: davide.schiffer@unito.it Research Center/Policlinico di Monza Foundation, Vercelli, (Italy) 354 Neurooncology - Newer Developments References [1] Louis DN, Ohgaki H, Wiestler OD, Cavenee WK. WHO Classification of Tumours of the Central Nervous System. 4th ed. Lyon, France: International Agency for Research on Cancer (IARC); 2007. p. 309. [2] Von Deimling A, Reifenberger G, Kros JM, Louis DN, Collins VP. Oligoastrocytoma. In: Louis DN, Ohgaki H, Wiestler OD, Cavenee WK, editors. WHO Classification of Tumours of the Central Nervous System. 4th ed. Lyon, France: International Agency for Research on Cancer (IARC); 2007. pp. 63-65. [3] Von Deimling A, Reifenberger G, Kros JM, Louis DN, Collins VP. Anaplastic oligoas‐ trocytoma. In: Louis DN, Ohgaki H, Wiestler OD, Cavenee WK, editors. WHO Classification of Tumours of the Central Nervous System. 4th ed. Lyon, France: International Agency for Research on Cancer (IARC); 2007. pp. 63-67. [4] Cooper ERA. The relation of oligocytes and astrocytes in cerebral tumours. J Pathol. 1935;41:259-266. [5] Hart MN, Petito CK, Earle KM. Mixed gliomas. Cancer. 1974;33:134-140. [6] Daumas-Duport C, Varlet P, Tucker ML, Beuvon F, Cervera P, et al. Oligodendroglio‐ mas. Part I: Patterns of growth, histological diagnosis, clinical and imaging correla‐ tions: a study of 153 cases. J Neurooncol. 1997;34:37-59. [7] Coons SW, Johnson PC, Scheithauer BW, Yates AJ, Pearl DK. Improving diagnostic accuracy and interobserver concordance in the classification and grading of primary gliomas. Cancer. 1997;79:1381-1393. [8] Krouwer HG, van Duinen SG, Kamphorst W, van der Valk P, Algra A. Oligoastrocy‐ tomas: a clinicopathological study of 52 cases. J Neurooncol. 1997;33:223-238. [9] Schiffer D. Brain Tumor Pathology: Current Diagnostic Hotspots and Pitfalls. Dordrecht, Netherlands: Springer Verlag; 2006. p. 272. [10] de Armond SJ, Eng LF, Rubinstein LJ. The application of glial fibrillary acidic (GFA) protein immunohistochemistry in neurooncology. A progress report. Pathol Res Pract. 1980;168:374-394. [11] van der Meulen JD, Houthoff HJ, Ebels EJ. Glial fibrillary acidic protein in human gliomas. Neuropathol Appl Neurobiol. 1978;4:177-190. [12] Herpers MJ, Budka H. Glial fibrillary acidic protein (GFAP) in oligodendroglial tumors: gliofibrillary oligodendroglioma and transitional oligoastrocytoma as subtypes of oligodendroglioma. Acta Neuropathol. 1984;64:265-272. [13] Choi BH, Kim RC. Expression of glial fibrillary acidic protein in immature oligoden‐ droglia. Science. 1984;223:407-409. Oligoastrocytoma: A Vanishing Tumor Entity http://dx.doi.org/10.5772/63240 355 [14] Fuller CE, Schmidt RE, Roth KA, Burger PC, Scheithauer BW, et al. Clinical utility of fluorescence in situ hybridization (FISH) in morphologically ambiguous gliomas with hybrid oligodendroglial/astrocytic features. J Neuropathol Exp Neurol. 2003;62:1118-1128. [15] Maintz D, Fiedler K, Koopmann J, Rollbrocker B, Nechev S, et al. References Molecular genetic evidence for subtypes of oligoastrocytomas. J Neuropathol Exp Neurol. 1997;56:1098-1104. [16] Raff MC, Williams BP, Miller RH. The in vitro differentiation of a bipotential glial progenitor cell. EMBO J. 1984;3:1857-1864. [17] Blümcke I, Becker AJ, Normann S, Hans V, Riederer BM, et al. Distinct expression pattern of microtubule-associated protein-2 in human oligodendrogliomas and glial precursor cells. J Neuropathol Exp Neurol. 2001;60:984-993. [18] Matsumura N, Nobusawa S, Ikota H, Hirato J, Hirose T, et al. Coexpression of cyclin D1 and alpha-internexin in oligodendroglial tumors. Brain Tumor Pathol. 2015;32:261-267. DOI: 10.1007/s10014-015-0228-2. [19] Yaziji H, Massarani-Wafai R, Gujrati M, Kuhns JG, Martin AW, et al. Role of p53 immunohistochemistry in differentiating reactive gliosis from malignant astrocytic lesions. Am J Surg Pathol. 1996;20:1086-1090. [20] Kraus JA, Koopmann J, Kaskel P, Maintz D, Brandner S, et al. Shared allelic losses on chromosomes 1p and 19q suggest a common origin of oligodendroglioma and oligoastrocytoma. J Neuropathol Exp Neurol. 1995;54:91-95. [21] Okamoto Y, Di Patre PL, Burkhard C, Horstmann S, Jourde B, et al. Population-based study on incidence, survival rates, and genetic alterations of low-grade diffuse astrocytomas and oligodendrogliomas. Acta Neuropathol. 2004;108:49-56. [22] Mueller W, Hartmann C, Hoffmann A, Lanksch W, Kiwit J, et al. Genetic signature of oligoastrocytomas correlates with tumor location and denotes distinct molecular subsets. Am J Pathol. 2002;161:313-319. [23] Eoli M, Bissola L, Bruzzone MG, Pollo B, Maccagnano C, et al. Reclassification of oligoastrocytomas by loss of heterozygosity studies. Int J Cancer. 2006;119:84-90. [24] Reifenberger J, Reifenberger G, Liu L, James CD, Wechsler W, et al. Molecular genetic analysis of oligodendroglial tumors shows preferential allelic deletions on 19q and 1p. Am J Pathol. 1994;145:1175-1190. [25] Smith JS, Perry A, Borell TJ, Lee HK, O'Fallon J, et al. Alterations of chromosome arms 1p and 19q as predictors of survival in oligodendrogliomas, astrocytomas, and mixed oligoastrocytomas. J Clin Oncol. 2000;18:636-645. 356 Neurooncology - Newer Developments [26] Chen R, Ravindra VM, Cohen AL, Jensen RL, Salzman KL, et al. Molecular features assisting in diagnosis, surgery, and treatment decision making in low-grade gliomas. Neurosurg Focus. 2015;38:E2. DOI: 10.3171/2015.1. [27] Wick W, Hartmann C, Engel C, Stoffels M, Felsberg J, et al. NOA-04 randomized phase III trial of sequential radio chemotherapy of anaplastic glioma with procarbazine, lomustine, and vincristine or temozolomide. J Clin Oncol. 2009;27:5874-5880. DOI: 10.1200/JCO.2009.23.6497. [28] Louis DN, Perry A, Burger P, Ellison DW, Reifenberger G, et al. References International Society Of Neuropathology-Haarlem consensus guidelines for nervous system tumor classifi‐ cation and grading. Brain Pathol. 2014;24:429-435. DOI: 10.1111/bpa.12171. [29] Burger PC, Minn AY, Smith JS, Borell TJ, Jedlicka AE, Huntley, et al. Losses of chromosomal arms 1pand 19q on the diagnosis of oligodendroglioma. Study of paraffin-embedded sections. Mod Pathol. 2001;14:842-853. [30] McDonald JM, See SJ, Tremont IW, Colman H, Gilbert MR, et al. The prognostic impact of histology and 1p/19q status in anaplastic oligodendroglial tumors. Cancer. 2005;104:1468-1477. [31] Griffin CA, Burger P, Morsberger L, Yonescu R, Swierczynski S, et al. Identification of der(1;19)(q10;p10) in five oligodendrogliomas suggests mechanism of concurrent 1p and 19q loss. J Neuropathol Exp Neurol. 2006;65:988-994. [32] Jenkins RB, Blair H, Ballman KV, Giannini C, Arusell RM, et al. A t(1;19)(q10;p10) mediates the combined deletions of 1p and 19q and predicts a better prognosis of patients with oligodendroglioma. Cancer Res. 2006;66:9852-9861. [33] Idbaih A, Marie Y, Pierron G, Brennetot C, Hoang-Xuan K, et al. Two types of chro‐ mosome 1p losses with opposite significance in gliomas. Ann Neurol. 2005;58:483-487. [34] Barbashina V, Salazar P, Holland EC, Rosenblum MK, Ladanyi M. Allelic losses at 1p36 and 19q13 in gliomas: correlation with histologic classification, definition of a 150-kb minimal deleted region on 1p36, and evaluation of CAMTA1 as a candidate tumor suppressor gene. Clin Cancer Res. 2005;11:1119-1128. [35] Hartmann C, Johnk L, Kitange G, Wu Y, Ashworth LK, et al. Transcript map of the 3.7- Mb D19S112-D19S246 candidate tumor suppressor region on the long arm of chromo‐ some 19. Cancer Res. 2002;62:4100-4108. [36] von Deimling A, Bender B, Jahnke R, Waha A, Kraus J, et al. Loci associated with malignant progression in astrocytomas: a candidate on chromosome 19q. Cancer Res. 1994;54:1397-1401. [37] Labussière M, Idbaih A, Wang XW, Marie Y, Boisselier B, et al. All the 1p19q codelet‐ ed gliomas are mutated on IDH1 or IDH2. Neurology. 2010;74:1886-1890. DOI: 10.1212/ WNL.0b013e3181e1cf3a. Oligoastrocytoma: A Vanishing Tumor Entity http://dx.doi.org/10.5772/63240 [38] Reuss DE, Sahm F, Schrimpf D, Wiestler B, Capper D, et al. ATRX and IDH1-R132H immunohistochemistry with subsequent copy number analysis and IDH sequencing as a basis for an "integrated" diagnostic approach for adult astrocytoma, oligodendro‐ glioma and glioblastoma. Acta Neuropathol. 2015;129:133-146. DOI: 10.1007/ s00401-014-1370-3. [39] Bettegowda C, Agrawal N, Jiao Y, Sausen M, Wood LD, et al. Mutations in CIC and FUBP1 contribute to human oligodendroglioma. Science. 2011;333:1453-1455. DOI: 10.1126/science.1210557. References [40] Yip S, Butterfield YS, Morozova O, Chittaranjan S, Blough MD, et al. Concurrent CIC mutations, IDH1/2 mutations, and 1p/19q loss distinguish oligodendrogliomas from other cancers. J Pathol. 2012;226:7-16. DOI: 10.1002/path.2995. [41] Sahm F, Koelsche C, Meyer J, Pusch S, Lindenberg K, et al. CIC and FUBP1 muta‐ tions in oligodendrogliomas, oligoastrocytomas and astrocytomas. Acta Neuropathol. 2012;123:853-860. DOI: 10.1007/s00401-012-0993-5. [42] Ichimura K, Vogazianou AP, Liu L, Pearson DM, Bäcklund LM, et al. 1p36 is a preferential target of chromosome 1 deletions in astrocytic tumours and homozygous‐ ly deleted in a subset of glioblastomas. Oncogene. 2008;27:2097-2108. [43] Leeper HE, Caron AA, Decker PA, Jenkins RB, Lachance DH, et al. IDH mutation, 1p19q codeletion and ATRX loss in WHO grade II gliomas. Oncotarget. 2015;6:30295-30305. DOI: 10.18632/oncotarget.4497. [44] Idbaih A, Kouwenhoven M, Jeuken J, Carpentier C, Gorlia T, et al. Chromosome 1p loss evaluation in anaplastic oligodendrogliomas. Neuropathology. 2008;28:440-443. DOI: 10.1111/j.1440-1789.2008.00863. [45] Jeuken JW, Sprenger SH, Wesseling P, Macville MV, von Deimling A, et al. Identifica‐ tion of subgroups of high-grade oligodendroglial tumors by comparative genomic hybridization. J Neuropathol Exp Neurol. 1999;58:606-612. [46] Jeuken JW, Sprenger SH, Boerman RH, von Deimling A, Teepen HL, et al. Subtyping of oligo-astrocytic tumours by comparative genomic hybridization. J Pathol. 2001;194:81-87. [47] Jeuken J, Cornelissen S, Boots-Sprenger S, Gijsen S, Wesseling P. Multiplex ligation- dependent probe amplification: a diagnostic tool for simultaneous identification of different genetic markers in glial tumors. J Mol Diagn. 2006;8:433-443. [48] Natté R, van Eijk R, Eilers P, Cleton-Jansen AM, Oosting J, et al. Multiplex ligation- dependent probe amplification for the detection of 1p and 19q chromosomal loss in oligodendroglial tumors. Brain Pathol. 2005;15:192-197. [49] Franco-Hernández C, Martínez-Glez V, de Campos JM, Isla A, Vaquero J, et al. Allelic status of 1p and 19q in oligodendrogliomas and glioblastomas: multiplex ligation- Neurooncology - Newer Developments 358 dependent probe amplification versus loss of heterozygosity. Cancer Genet Cytoge‐ net. 2009;190:93-96. DOI: 10.1016/j.cancergencyto.2008.09.017. dependent probe amplification versus loss of heterozygosity. Cancer Genet Cytoge‐ net. 2009;190:93-96. DOI: 10.1016/j.cancergencyto.2008.09.017. [50] Yan H, Parsons DW, Jin G, McLendon R, Rasheed BA, et al. IDH1 and IDH2 muta‐ tions in gliomas. N Engl J Med. 2009;360:765-773. DOI: 10.1056/NEJMoa0808710. [51] Hartmann C, Meyer J, Balss J, Capper D, Mueller W, et al. Type and frequency of IDH1 and IDH2 mutations are related to astrocytic and oligodendroglial differentiation and age: a study of 1,010 diffuse gliomas. Acta Neuropathol. 2009; 118: 469–474. DOI: 10.1007/s00401-009-0561-9. References [52] Balss J, Meyer J, Mueller W, Korshunov A, Hartmann C, et al. Analysis of the IDH1 codon 132 mutation in brain tumors. Acta Neuropathol. 2008;116:597-602. DOI: 10.1007/ s00401-008-0455-2. [53] Mellai M, Piazzi A, Caldera V, Monzeglio O, Cassoni P, et al. IDH1 and IDH2 muta‐ tions, immunohistochemistry and associations in a series of brain tumors. J Neuroon‐ col. 2011;105:345-357. DOI: 10.1007/s11060-011-0596-3. [54] Gravendeel LA, Kloosterhof NK, Bralten LB, van Marion R, Dubbink HJ, et al. Segregation of non-p.R132H mutations in IDH1 in distinct molecular subtypes of glioma. Hum Mutat. 2010;31:E1186-1199. DOI: 10.1002/humu.21201. [55] Sun H, Yin L, Li S, Han S, Song G, et al. Prognostic significance of IDH mutation in adult low-grade gliomas: a meta-analysis. J Neurooncol. 2013;113:277-284. DOI: 10.1007/s11060-013-1107-5. [56] Wang XW, Ciccarino P, Rossetto M, Boisselier B, Marie Y, et al. IDH mutations: genotype-phenotype correlation and prognostic impact. Biomed Res Int. 2014;2014:540236. DOI: 10.1155/2014/540236. [57] Capper D, Reuss D, Schittenhelm J, Hartmann C, Bremer J, et al. Mutation-specific IDH1 antibody differentiates oligodendrogliomas and oligoastrocytomas from other brain tumors with oligodendroglioma-like morphology. Acta Neuropathol. 2011;121:241-252. DOI: 10.1007/s00401-010-0770-2. [58] Clynes D, Higgs DR, Gibbons RJ. The chromatin remodeller ATRX: a repeat offender in human disease. Trends Biochem Sci. 2013;38:461-466. DOI: 10.1016/j.tibs.2013.06.011. [59] Goldberg AD, Banaszynski LA, Noh KM, Lewis PW, Elsaesser SJ, et al. Distinct factors control histone variant H3.3 localization at specific genomic regions. Cell. 2010;140:678-691. DOI: 10.1016/j.cell.2010.01.003. [60] Lewis PW, Elsaesser SJ, Noh KM, Stadler SC, Allis CD. Daxx is an H3.3-specific histone chaperone and cooperates with ATRX in replication-independent chromatin assem‐ bly at telomeres. Proc Natl Acad Sci U S A. 2010;107:14075-14080. DOI: 10.1073/pnas. 1008850107. Oligoastrocytoma: A Vanishing Tumor Entity http://dx.doi.org/10.5772/63240 359 [61] Heaphy CM, de Wilde RF, Jiao Y, Klein AP, Edil BH, et al. Altered telomeres in tumors with ATRX and DAXX mutations. Science. 2011;333:425. DOI: 10.1126/science.1207313. [62] Kannan K, Inagaki A, Silber J, Gorovets D, Zhang J, et al. Whole-exome sequencing identifies ATRX mutation as a key molecular determinant in lower-grade glioma. Oncotarget. 2012;3:1194-1203. [63] Schwartzentruber J, Korshunov A, Liu XY, Jones DT, Pfaff E, et al. Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma. Nature. 2012;482:226-231. DOI: 10.1038/nature10833. [64] Jiao Y, Killela PJ, Reitman ZJ, Rasheed AB, Heaphy CM, et al. Frequent ATRX, CIC, FUBP1 and IDH1 mutations refine the classification of malignant gliomas. Oncotar‐ get. 2012;3:709-722. References [65] Wiestler B, Capper D, Holland-Letz T, Korshunov A, von Deimling A, et al. ATRX loss refines the classification of anaplastic gliomas and identifies a subgroup of IDH mutant astrocytic tumors with better prognosis. Acta Neuropathol. 2013;126:443-451. DOI: 10.1007/s00401-013-1156-z. [66] Nguyen DN, Heaphy CM, de Wilde RF, Orr BA, Odia Y, et al. Molecular and morpho‐ logic correlates of the alternative lengthening of telomeres phenotype in high-grade astrocytomas. Brain Pathol. 2013;23:237-243. DOI: 10.1111/j.1750-3639.2012.00630. [67] Villard L, Toutain A, Lossi AM, Gecz J, Houdayer C, et al. Splicing mutation in the ATR-X gene can lead to a dysmorphic mental retardation phenotype without alpha- thalassemia. Am J Hum Genet. 1996;58:499-505. [68] Khuong-Quang DA, Buczkowicz P, Rakopoulos P, Liu XY, Fontebasso AM, et al. K27M mutation in histone H3.3 defines clinically and biologically distinct subgroups of pediatric diffuse intrinsic pontine gliomas. Acta Neuropathol. 2012;124:439-447. DOI: 10.1007/s00401-012-0998-0. [69] Liu XY, Gerges N, Korshunov A, Sabha N, Khuong-Quang DA, et al. Frequent ATRX mutations and loss of expression in adult diffuse astrocytic tumors carrying IDH1/ IDH2 and TP53 mutations. Acta Neuropathol. 2012;124:615-625. DOI: 10.1007/ s00401-012-1031-3. [70] Sahm F, Reuss D, Koelsche C, Capper D, Schittenhelm J, et al. Farewell to oligoastro‐ cytoma: in situ molecular genetics favor classification as either oligodendroglioma or astrocytoma. Acta Neuropathol. 2014;128:551-559. DOI: 10.1007/s00401-014-1326-7. [71] Ikemura M, Shibahara J, Mukasa A, Takayanagi S, Aihara K, et al. Utility of ATRX immunohistochemistry in diagnosis of adult diffuse gliomas. Histopathology. 2016. DOI: 10.1111/his.12927. [72] Cryan JB, Haidar S, Ramkissoon LA, Bi WL, Knoff DS, et al. Clinical multiplexed exome sequencing distinguishes adult oligodendroglial neoplasms from astrocytic and mixed lineage gliomas. Oncotarget. 2014;5:8083-8092. Neurooncology - Newer Developments 360 [73] Cancer Genome Atlas Research Network. Comprehensive, integrative genomic analysis of diffuse lower-grade gliomas. N Engl J Med. 2015;372:2481-2498. [74] Huse JT, Diamond EL, Wang L, Rosenblum MK. Mixed glioma with molecular features of composite oligodendroglioma and astrocytoma: a true “oligoastrocytoma”? Acta Neuropathol. 2015;129:151-153. DOI: 10.1007/s00401-014-1359-y. [75] Wilcox P, Li CC, Lee M, Shivalingam B, Brennan J, et al. Oligoastrocytomas: throw‐ ing the baby out with the bathwater? Acta Neuropathol. 2015;129:147-149. DOI: 10.1007/s00401-014-1353-4. [76] Bai H, Zou Y, Lee AM, Tang X, Zhang P, et al. Does morphological assessment have a role in classifying oligoastrocytoma as "oligodendroglial" vs. "astrocytic"? Histopa‐ thology. 2015. DOI: 10.1111/his.12891. [77] Cai J, Zhu P, Zhang C, Li Q, Wang Z, Li, et al. References Detection of ATRX and IDH1-R132H immunohistochemistry in the progression of 211 paired gliomas. Oncotarget. 2016. DOI: 10.18632/oncotarget.7650. [78] Hewer E, Vajtai I, Dettmer MS, Berezowska S, Vassella E. Combined ATRX/IDH1 immunohistochemistry predicts genotype of oligoastrocytomas. Histopathology. 2016;68:272-278. DOI: 10.1111/his.12743. [79] Mellai M, Caldera V, Annovazzi L, Schiffer D. The distribution and significance of IDH mutation in gliomas. In: Lichtor T, editor. Evolution of the Molecular Biology of Brain Tumors and Therapeutic Implications. Rjieka, Croatia: InTech; 2013. pp. 299-342. [80] Bosone I, Cavalla P, Chiadò-Piat L, Vito ND, Schiffer D. Cyclin D1 expression in normal oligodendroglia and microglia cells: its use in the differential diagnosis of oligoden‐ drogliomas. Neuropathology. 2001;21:155-161. [81] Prayson RA. Oligodendroglioma look-alikes: the histopathologic differential diagno‐ sis. In: Reeves C, editor. Oligodendrogliomas (ODs): Diagnosis, Outcomes and Prognosis. New York: Nova Biomedical; 2016. pp. 83-118.
https://openalex.org/W2559605011	https://cris.maastrichtuniversity.nl/files/7943246/7177451.pdf	English	null	Assessing Microstructural Substrates of White Matter Abnormalities: A Comparative Study Using DTI and NODDI	PloS one	2,016	cc-by	8,383	Document status and date: Published: 21/12/2016 Document status and date: Published: 21/12/2016 DOI: 10.1371/journal.pone.0167884 Document Version: Publisher's PDF, also known as Version of record Document Version: Publisher's PDF, also known as Version of record Please check the document version of this publication: • A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. p • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication Link to publication General rights i h d General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal y y p g y • You may freely distribute the URL identifying the publication in the public portal. If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license above, please follow below link for the End User Agreement: www.umlib.nl/taverne-license www.umlib.nl/taverne-license Citation for published version (APA): Timmers, I., Roebroeck, A., Bastiani, M., Jansma, B., Rubio-Gozalbo, E., & Zhang, H. (2016). Assessing Microstructural Substrates of White Matter Abnormalities: A Comparative Study Using DTI and NODDI. PLOS ONE, 11(12), Article e0167884. https://doi.org/10.1371/journal.pone.0167884 Take down policy Take down policy If you believe that this document breaches copyright please contact us at: repository@maastrichtuniversity.nl providing details and we will investigate your claim. providing details and we will investigate your claim. Download date: 24 Oct. 2024 RESEARCH ARTICLE OPEN ACCESS OPEN ACCESS Citation: Timmers I, Roebroeck A, Bastiani M, Jansma B, Rubio-Gozalbo E, Zhang H (2016) Assessing Microstructural Substrates of White Matter Abnormalities: A Comparative Study Using DTI and NODDI. PLoS ONE 11(12): e0167884. doi:10.1371/journal.pone.0167884 Editor: Pew-Thian Yap, University of North Carolina at Chapel Hill, UNITED STATES Received: February 12, 2016 Accepted: November 22, 2016 Published: December 21, 2016 Copyright: © 2016 Timmers et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: Data is available on Neurite orientation dispersion and density imaging (NODDI) enables more specific charac- terization of tissue microstructure by estimating neurite density (NDI) and orientation disper- sion (ODI), two key contributors to fractional anisotropy (FA). The present work compared NODDI- with diffusion tensor imaging (DTI)-derived indices for investigating white matter abnormalities in a clinical sample. We assessed the added value of NODDI parameters over FA, by contrasting group differences identified by both models. Diffusion-weighted images with multiple shells were acquired in a group of 8 healthy controls and 8 patients with an inherited metabolic disease. Both standard DTI and NODDI analyses were performed. Tract based spatial statistics (TBSS) was used for group inferences, after which overlap and unique contributions across different parameters were evaluated. Results showed that group differences in NDI and ODI were complementary, and together could explain much of the FA results. Further, compared to FA analysis, NDI and ODI gave a pattern of results that was more regionally specific and were able to capture additional discriminative voxels that FA failed to identify. Finally, ODI from single-shell NODDI analysis, but not NDI, was found to reproduce the group differences from the multi-shell analysis. To conclude, by using a clinically feasible acquisition and analysis protocol, we demonstrated that NODDI is of added value to standard DTI, by revealing specific microstructural substrates to white matter changes detected with FA. As the (simpler) DTI model was more sensitive in identifying group differences, NODDI is recommended to be used complementary to DTI, thereby add- ing greater specificity regarding microstructural underpinnings of the differences. The find- ing that ODI abnormalities can be identified reliably using single-shell data may allow the retrospective analysis of standard DTI with NODDI. Assessing Microstructural Substrates of White Matter Abnormalities: A Comparative Study Using DTI and NODDI Inge Timmers1,2, Alard Roebroeck1,3, Matteo Bastiani4, Bernadette Jansma1,3, Estela Rubio-Gozalbo5, Hui Zhang6 1 Department of Cognitive Neuroscience, Maastricht University, Maastricht, the Netherlands, 2 Department of Rehabilitation Medicine, Maastricht University, Maastricht, the Netherlands, 3 Maastricht Brain Imaging Center (M-BIC), Maastricht, the Netherlands, 4 Oxford Centre for Functional MRI of the Brain (FMRIB Centre), University of Oxford, Headington, Oxford, United Kingdom, 5 Department of Pediatrics and Laboratory Genetic Metabolic Diseases, Maastricht University Medical Center, Maastricht, the Netherlands, 6 Department of Computer Science and Centre for Medical Image Computing, University College London, London, United Kingdom a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 inge.timmers@maastrichtuniversity.nl OPEN ACCESS Citation: Timmers I, Roebroeck A, Bastiani M, Jansma B, Rubio-Gozalbo E, Zhang H (2016) Assessing Microstructural Substrates of White Matter Abnormalities: A Comparative Study Using DTI and NODDI. PLoS ONE 11(12): e0167884. doi:10.1371/journal.pone.0167884 Editor: Pew-Thian Yap, University of North Carolina at Chapel Hill, UNITED STATES Editor: Pew-Thian Yap, University of North Carolina at Chapel Hill, UNITED STATES Copyright: © 2016 Timmers et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Introduction the publication fees and can be contacted via openaccess@ucl.ac.uk. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. the publication fees and can be contacted via openaccess@ucl.ac.uk. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Diffusion-weighted imaging (DWI) can be used in vivo to assess properties and potential abnor- malities of tissue microstructure. A variety of parameters can be estimated by measuring the dif- fusion of water, exploiting the fact that the diffusion is influenced by tissue microstructure. A variety of models are used to model water diffusion. Widely used–perhaps even the default model- is the single compartment diffusion tensor model [1], with fractional anisotropy (FA) as its most commonly used parameter. This straightforward marker has been studied in the context of brain development and aging [2], and has been found to be reduced in numerous neurologi- cal and neurodegenerative diseases [3,4]. Reductions in FA have been linked to axonal degenera- tion (e.g., in amyotrophic lateral sclerosis, ALS [5]), to myelin breakdown (e.g., in multiple sclerosis, MS [6]), or to a general state of decreased white matter integrity. Although FA is a sen- sitive measure, it is inherently non-specific [7]. A reduction in FA could be caused by reduced neurite density, increased dispersion of orientation, and several other factors. Related markers derived from the eigenvalues of the diffusion tensor are radial (perpendicular, d?) and axial (parallel, d\|\|) diffusivity (RD and AD, respectively), and mean diffusivity (MD). It has been sug- gested that changes in RD reflect de/dysmyelination [8], while AD changes are more related to axonal damage [9], but the interpretation of these markers has been a topic of controversy [10]. Competing Interests: The authors have declared that no competing interests exist. Competing Interests: The authors have declared that no competing interests exist. Recently, neurite orientation dispersion and density imaging (NODDI) was developed to enable more specific characterisation of tissue microstructure using a clinically feasible proto- col [11]. NODDI distinguishes three tissue compartments (intra-, extra-neurite, and cerebral spinal fluid—CSF) that are each modelled in a biologically informed manner, enabling several parameters to be estimated and analysed individually. Two main resulting indices are neurite density (NDI) and orientation dispersion (ODI). Comparing White Matter Pathology Using NODDI and DTI Data Availability Statement: Data is available on figshare with the DOI 10.6084/m9.figshare. 3843372. Data Availability Statement: Data is available on figshare with the DOI 10.6084/m9.figshare. 3843372. Funding: The current study was funded by a Galactosemia Research Fund (GOF) from the Dutch Patient Organisation (GVN), the School for Oncology and Development Biology (GROW), and Maastricht University Incentive (“Women in higher positions in science”). HZ would like to thank the generous support from UK EPSRC (EP/L022680/ 1). The Open Access team from UCL is covering 1 / 15 PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 Introduction Measures of density and orientation disper- sion in the brain have shown great correspondence to histological measures (i.e., neurite den- sity to optical myelin staining intensity [12] and orientation dispersion to quantitative Golgi analysis [13]). Abnormalities in the morphology of neurites have been observed in diseases. For instance, axonal loss was found in MS as reflected by reductions in axonal density and area, while the WM appeared normal [14]. The correlation between FA and axonal density, however, is relatively weak. NDI, as a more specific estimate of density, might therefore be a more sensitive marker of axon pathology than FA. In vivo quantification of neurite density and orientation dispersion has been shown in previ- ous studies as well [11,15]. Recently, NODDI has been demonstrated to be useful in several applications, ranging from localisation of malformations, to characterisation of WM and GM in diseases and normal development [16–26]. Although NODDI has been thoroughly described, tested and applied, to our knowledge group inferences based on NODDI have not been explic- itly compared to group inferences resulting from standard DTI. NODDI enables more specific quantification of microstructure compared to DTI, but it is very important and relevant to explicitly investigate whether this benefit manifests in a clinical study, as NODDI is potentially less sensitive due to the addition of model parameters (compared to standard DTI). Hence the value of analysing NODDI parameters has yet to be demonstrated in the context of population- based clinical studies. Therefore, the present work assesses the added value of NODDI parame- ters for identifying and investigating white matter abnormalities over DTI-based markers, by explicitly comparing results from NODDI and DTI analyses as applied to a clinical sample, the inherited metabolic disease classic galactosemia. In this disease, WM pathology has mainly been described in terms of diffuse signal hyperintensities on T2-weighted images [27] and has been linked at least partly to myelin abnormalities, caused by deficient galactosylation of galactocer- ebrosides (important building stones of myelin) [28]. The interpretation of the results in the context of the disease is published elsewhere [20]. Here, more specifically, we compared group 2 / 15 Comparing White Matter Pathology Using NODDI and DTI differences using the DTI-derived (FA, RD, AD, MD) and NODDI-derived (NDI, ODI) mark- ers and evaluated the extent to which the markers identified coinciding and unique differences in the results. NODDI model NODDI allows the differentiation of three compartments in the brain–it distinguishes 1) intra-neurite space, modelled as restricted diffusion (collection of sticks forming a Watson dis- tribution); 2) extra-neurite space, modelled as hindered, but not restricted diffusion (aniso- tropic Gaussian diffusion); and 3) a cerebral spinal fluid (CSF) compartment, modelled as isotropic Gaussian diffusion. The full normalised signal A is represented as follows: A = (1- vfiso) (vfin Ain + (1-vfin) Aen) + vfisoAiso, where vf stands for volume fraction; in for intra-neur- ite; en for extra-neurite; and iso for the isotropic CSF compartment (see [11] for a more exten- sive description of the model). The intra-neurite volume fraction (vfin) represents the neurite density index (NDI; typically high in WM, low in GM). The other main parameter from the NODDI estimation is the orientation dispersion index (ODI), which quantifies the angular variation of neurite orientation (ranging from 0 for perfectly coherently oriented structures to 1 for isotropic structures; typically high in GM, low in WM). Data acquisition Data on eight patients with an inherited metabolic disease (classic galactosemia; see [20]) [16– 21 years of age] and eight healthy controls [15–20 years of age] were acquired on a 3-T Siemens Trio whole body scanner (Siemens Medical System, Erlangen, Germany), using a 32-channel head coil. The DWI data were obtained using a double-refocused single-shot spin echo EPI sequence. 64 slices with isotropic voxels of 2.2 mm3 were obtained (TR = 8500 ms; TE = 97 ms) in an anterior to posterior direction. Data were acquired at two different b-values: b = 1000 s/ mm2 with 64 diffusion-encoding gradient directions and b = 2000 s/mm2 with 64 diffusion directions. In addition, 5 b = 0 images were collected, two of which were acquired using a reversed phase encoding direction (posterior to anterior), to allow the estimation of susceptibil- ity induced distortions. The diffusion encoding directions spanned the entire sphere. Total acquisition time of the DWI data was approximately 22.5 minutes. Participants were screened for MRI compatibility, and gave written informed consent (in case of minors, both parents/ caregivers also gave written informed consent). The Medical Ethical Committee of the Maas- tricht University Hospital/Maastricht University gave ethical clearance for this study. Introduction By comparing DTI- and NODDI-derived group differences, this study further adds to the important practical question whether it is worthwhile to invest more imaging time to acquire multi-shell diffusion data in the context of a clinical study. In addition, we aimed to determine whether standard single-shell DTI-quality DWI data can be used for investigating white matter abnormalities based on NODDI-based tissue quantification. Comparing White Matter Pathology Using NODDI and DTI [31,32]). Concurrently, the b-vectors were rotated to account for the corrections (using Python; http://www.python.org). The diffusion tensors were estimated from one shell of the corrected DWI data (b = 1000 s/ mm2) using a linear fitting algorithm (dtifit, implemented in FSL). DTI-TK (publicly available; http://www.nitrc.org/projects/dtitk) was used for tensor-based spatial normalization of the volumes to an iteratively optimized population-specific template [33]. This algorithm applies a deformable registration to the tensor images, which has shown to lead to improved registra- tion, as compared to FA-based registration algorithms [34,35]. The resulting normalized images were averaged, and high-resolution FA, RD, AD and MD maps (1 mm iso-voxel) were derived. By thinning the mean FA images, a mean FA skeleton was created that represented the centres of all tracts common to the group (tract based spatial statistics [TBSS] of FSL [36]). The aligned FA data from each subject was projected onto this skeleton using the calculated distance maps. Using the same distance maps, the RD, AD and MD maps were projected onto the FA skeleton as well. The resulting data were fed into the statistical analysis. In parallel, neurite orientation dispersion and density imaging (NODDI) was applied to the pre-processed data, both on the multi-shell and on the single-shell DTI-quality (b = 1000 s/ mm2) data (publicly available in a Matlab toolbox, http://nitrc.org/projects/noddi_toolbox). The output scalar images from NODDI (NDI, ODI, fiso [CSF volume fraction], fmin [fitting objective function values, proportional to the fitting residuals]) were normalized to the -already defined- study-specific common group space using the transformation fields as calcu- lated per participant during the tensor-based registration. Then, the normalized data were pro- jected onto the -already calculated- mean FA skeleton using the original distance maps (using an adapted code from TBSS). On the skeletonised FA, AD, RD, MD, NDI, ODI, fiso, fmin maps, permutation-based statis- tics were carried out (using randomise of FSL; 5000 permutations) using a design with group as a between-subjects factor and age as a covariate. P-values were corrected by means of the Threshold-Free Cluster Enhancement (TFCE) option [37]. A corrected alpha of 0.05 was used as the significance level. Resulting statistical group maps were compared across measures by evaluating overlap of discriminating voxels by means of dice coefficients [2 (A ˄ B) / (A + B)] [38], and by evaluating unique contributions voxel-wise. NODDI revealed more specific group differences The FA analysis showed the most group differences, as compared to the other indices (see Fig 1 and/or Table 1). The NODDI analysis revealed several group differences in NDI and ODI that give a more specific regional pattern of white matter changes as compared to the general pattern of FA findings (Fig 1): NDI changes were found mainly in bilateral anterior regions, while ODI changes were left lateralized and more posterior (more descriptive data on the clus- ters can be found in [20]). A pipeline of the data analysis procedure can be found in the Supporting Information (S1 File). Data analyses Data pre-processing was initiated with estimation of susceptibility induced distortions. From the pairs of images acquired using reversed phase-encode directions (i.e., with distortions going in opposite directions), the susceptibility-induced off-resonance field was estimated using a method similar to the one described in Andersson et al. [29] (topup of FMRIB Software Library [FSL] [30]). In addition, eddy current-induced distortions and head motion were esti- mated, and all distortions were corrected by simultaneously modelling the effects of diffusion eddy currents (using a Gaussian process) and movements on the image (using FSL’s eddy 3 / 15 PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 Comparing White Matter Pathology Using NODDI and DTI Fig 1. Comparison of statistical group results. Presented are the voxels discriminating across the groups by the different parameters (i.e., DTI-based: mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD], and fractional anisotropy [FA]; NODDI-based: neurite density index [NDI], and orientation dispersion index [ODI]). A selection of slices is presented from the superior to inferior parts of the brain. In green, the mean FA skeleton is overlaid. Note that images are in radiological convention (left is right). doi:10.1371/journal.pone.0167884.g001 Fig 1. Comparison of statistical group results. Presented are the voxels discriminating across the groups by the different parameters (i.e., DTI-based: mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD], and fractional anisotropy [FA]; NODDI-based: neurite density index [NDI], and orientation dispersion index [ODI]). A selection of slices is presented from the superior to inferior parts of the brain. In green, the mean FA skeleton is overlaid. Note that images are in radiological convention (left is right). doi:10.1371/journal.pone.0167884.g001 Fig 1. Comparison of statistical group results. Presented are the voxels discriminating across the groups by the different parameters (i.e., DTI-based: mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD], and fractional anisotropy [FA]; NODDI-based: neurite density index [NDI], and orientation dispersion index [ODI]). A selection of slices is presented from the superior to inferior parts of the brain. In green, the mean FA skeleton is overlaid. Note that images are in radiological convention (left is right). doi:10.1371/journal.pone.0167884.g001 Fig 1. Comparison of statistical group results. Presented are the voxels discriminating across the groups by the different parameters (i.e., DTI-based: mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD], and fractional anisotropy [FA]; NODDI-based: neurite density index [NDI], and orientation dispersion index [ODI]). A selection of slices is presented from the superior to inferior parts of the brain. In green, the mean FA skeleton is overlaid. Note that images are in radiological convention (left is right). doi:10.1371/journal.pone.0167884.g001 doi:10.1371/journal.pone.0167884.g001 explain much of the FA results, supported by a substantial overlap between the discrimina- tive voxels identified by NODDI and FA (dice coefficient = 0.52; Table 1). Further, it can be noticed that the AD group differences overlap with ODI changes (dice coefficient = 0.55), while RD changes overlapped more with NDI changes (dice coefficient = 0.48). MD changes also overlapped more with NDI (dice coefficient = 0.29) than ODI (dice coefficient = 0.04). Group differences in NDI and ODI are complementary and overlap with DT indices The group differences in NDI and ODI were complementary, supported by a minimal over- lap in results (dice coefficient = 0.07). Further, the combination of NDI and ODI could 4 / 15 PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 Comparing White Matter Pathology Using NODDI and DTI Table 1. Overlap in number in discriminative voxels across parameters, expressed in dice coefficients and number of voxels. FA # (23.994) a AD # (1.512) RD " (19.550) MD " (6.742) NDI # (12.597) ODI " (3.283) NDI+ODI (15.481) FA # (23.994) 0.10 (1.275) 0.76 (16.578) 0.30 (4.553) 0.43 (7.770) 0.21 (2.855) 0.52 (10.236) AD # (1.512) 0.04 (425) 0 (0) 0.00 (22) 0.55 (1.319) 0.16 (1.324) RD " (19.550) 0.44 (5.720) 0.48 (7.742) 0.14 (1.641) 0.52 (9.074) MD " (6.742) 0.29 (2.768) 0.04 (175) 0.26 (2.928) NDI # (12.597) 0.05 (399) n.a. ODI " (3.283) n.a. NDI+ODI (15.481) ber in discriminative voxels across parameters, expressed in dice coefficients and number of voxels. Table 1. Overlap in number in discriminative voxels across parameters, expressed ODI estimations from single-shell data can be used for group inferences A comparison between the multi-shell and single-shell fittings can be found in Fig 4, where the averaged group maps are presented. The NODDI analysis using single-shell data (b = 1000 s/ mm2) could estimate ODI sufficiently well to be used for group inference, supported by similar ODI maps and a large overlap in the voxels discriminating across groups in single-shell and multi-shell ODI estimations (dice coefficient = 0.74) (Fig 5). NDI could not be reliably esti- mated using single-shell data as can be observed in the maps (e.g., no clear distinction between WM and GM), and the group results showed little overlap with the multi-shell NDI results (dice coefficient = 0.09). NODDI indices identify unique group differences The NODDI parameters identified voxels discriminative across the groups that were not cap- tured by the FA analysis: 38.3% and 13.0% of significant voxels in NDI and ODI, respectively, were not captured by the FA analysis (see Fig 2). In comparison, the AD and RD group analy- ses resulted in 15.7 and 15.2% not-captured-by-FA discriminative voxels, respectively. Checks of potential confounds Analysing the fmin maps, which are proportional to the fitting residuals, did not yield any sig- nificant group differences. In addition, the CSF volume fraction (fiso) differed only in a very small number of voxels (168 out of the 82.379 voxels of the entire WM skeleton). Here, patients showed increased fiso in the body of the corpus callosum (see Fig 3). explain much of the FA results, supported by a substantial overlap between the discrimina- tive voxels identified by NODDI and FA (dice coefficient = 0.52; Table 1). Further, it can be noticed that the AD group differences overlap with ODI changes (dice coefficient = 0.55), while RD changes overlapped more with NDI changes (dice coefficient = 0.48). MD changes also overlapped more with NDI (dice coefficient = 0.29) than ODI (dice coefficient = 0.04). 5 / 15 PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 Discussion Using a metabolic disease as an example, we demonstrated that the multi-compartment model neurite orientation dispersion and density imaging (NODDI) can be of added value to standard diffusion tensor imaging (DTI) for investigating WM abnormalities. NODDI reveals more specific microstructural substrates to white matter changes detected with fractional anisotropy (FA) that can be analysed independently. Also, the single-shell NODDI index of orientation dispersion (ODI) gave a very similar pattern of group differences compared to the multi-shell data. 6 / 15 PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 Comparing White Matter Pathology Using NODDI and DTI Fig 2. NODDI discriminative voxels not captured by FA analysis. Presented are voxels that were of discriminative value in the group NDI (red) and ODI (blue) analysis, but not in the FA analysis. Voxels are overlaid on averaged FA maps and the mean FA skeleton (green). A selection of slices is shown from anterior to posterior direction (top row), and from superior to inferior regions of the brain (bottom row). In the boxes, corresponding tensor illustrations are presented. Fig 2. NODDI discriminative voxels not captured by FA analysis. Presented are voxels that were of discriminative value in the group NDI (red) and ODI (blue) analysis, but not in the FA analysis. Voxels are overlaid on averaged FA maps and the mean FA skeleton (green). A selection of slices is shown from anterior to posterior direction (top row), and from superior to inferior regions of the brain (bottom row). In the boxes, corresponding tensor illustrations are presented. doi:10.1371/journal.pone.0167884.g002 doi:10.1371/journal.pone.0167884.g002 Fig 3. Group differences in CSF volume fraction (fiso). Presented are voxels that showed a significant group differences in fiso. Voxels are overlaid on averaged group maps. Slices are selected to optimally show the limited number of voxels showing a group difference. doi:10.1371/journal.pone.0167884.g003 Fig 3. Group differences in CSF volume fraction (fiso). Presented are voxels that showed a significant group differences in fiso. Voxels are overlaid on averaged group maps. Slices are selected to optimally show the limited number of voxels showing a group difference. doi:10.1371/journal.pone.0167884.g003 Fig 3. Group differences in CSF volume fraction (fiso). Presented are voxels that showed a significant group differences in fiso. Voxels are overlaid on averaged group maps. Slices are selected to optimally show the limited number of voxels showing a group difference. doi:10.1371/journal.pone.0167884.g003 Fig 3. Group differences in CSF volume fraction (fiso). Comparing White Matter Pathology Using NODDI and DTI Fig 4. Comparison of multi- and single-shell NODDI parameter maps. Presented are the averaged NODDI parameter maps, estimated using multi-shell data, single-shell data. A selection of slices is presented from the superior to inferior parts of the brain. Visual inspection of the maps shows that ODI and fiso maps are very similar across the multi- and single-shell estimations, but single-shell NDI maps are very different–more noisy–compared to multi-shell NDI maps. doi:10 1371/journal pone 0167884 g004 Fig 4. Comparison of multi- and single-shell NODDI parameter maps. Presented are the averaged NODDI parameter maps, estimated using multi-shell data, single-shell data. A selection of slices is presented from the superior to inferior parts of the brain. Visual inspection of the maps shows that ODI and fiso maps are very similar across the multi- and single-shell estimations, but single-shell NDI maps are very different–more noisy–compared to multi-shell NDI maps. Fig 4. Comparison of multi- and single-shell NODDI parameter maps. Presented are the averaged NODDI parameter maps, estimated using multi-shell data, single-shell data. A selection of slices is presented from the superior to inferior parts of the brain. Visual inspection of the maps shows that ODI and fiso maps are very similar across the multi- and single-shell estimations, but single-shell NDI maps are very different–more noisy–compared to multi-shell NDI maps. Fig 4. Comparison of multi- and single-shell NODDI parameter maps. Presented are the averaged NODDI parameter maps, estimated using multi-shell data, single-shell data. A selection of slices is presented from the superior to inferior parts of the brain. Visual inspection of the maps shows that ODI and fiso maps are very similar across the multi- and single-shell estimations, but single-shell NDI maps are very different–more noisy–compared to multi-shell NDI maps. Fig 4. Comparison of multi- and single-shell NODDI parameter maps. Presented are the averaged NODDI parameter maps, estimated using multi-shell data, single-shell data. A selection of slices is presented from the superior to inferior parts of the brain. Visual inspection of the maps shows that ODI and fiso maps are very similar across the multi- and single-shell estimations, but single-shell NDI maps are very different–more noisy–compared to multi-shell NDI maps. doi:10.1371/journal.pone.0167884.g004 doi:10.1371/journal.pone.0167884.g004 By using a biologically informed tissue model, NODDI is capable of estimating more spe- cific indices compared to FA: neurite density (NDI) and orientation dispersion (ODI), two key contributors to FA. Discussion Presented are voxels that showed a significant group differences in fiso. Voxels are overlaid on averaged group maps. Slices are selected to optimally show the limited number of voxels showing a group difference. doi:10.1371/journal.pone.0167884.g003 7 / 15 PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 In the current study, we analysed differences in the main white matter tracts across a metabolic patient group (classic galactosemia; see [20]) and a healthy control 8 / 15 PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 Comparing White Matter Pathology Using NODDI and DTI Fig 5. Comparison of statistical group results across multi-shell and single-shell NODDI parameter estimations. Presented are voxels that could discriminative across the groups, derived from NODDI analyses on multi- and single-shell data. A selection of slices is presented from the superior to inferior parts of the brain. In green, the mean FA skeleton is overlaid. As can be observed, there is large overlap in multi-shell and single-shell ODI discriminative voxels (dice coefficient = 0.74). Further, minimal overlap is found in NDI discriminative voxels (dice coefficient = 0.09). doi:10.1371/journal.pone.0167884.g005 Fig 5. Comparison of statistical group results across multi-shell and single-shell NODDI parameter estimations. Presented are voxels that could discriminative across the groups, derived from NODDI analyses on multi- and single-shell data. A selection of slices is presented from the superior to inferior parts of the brain. In green, the mean FA skeleton is overlaid. As can be observed, there is large overlap in multi-shell and single-shell ODI discriminative voxels (dice coefficient = 0.74). Further, minimal overlap is found in NDI discriminative voxels (dice coefficient = 0.09). d i 10 1371/j l 0167884 005 Fig 5. Comparison of statistical group results across multi-shell and single-shell NODDI parameter estimations. Presented are voxels that could discriminative across the groups, derived from NODDI analyses on multi- and single-shell data. A selection of slices is presented from the superior to inferior parts of the brain. In green, the mean FA skeleton is overlaid. As can be observed, there is large overlap in multi-shell and single-shell ODI discriminative voxels (dice coefficient = 0.74). Further, minimal overlap is found in NDI discriminative voxels (dice coefficient = 0.09). doi:10.1371/journal.pone.0167884.g005 9 / 15 Comparing White Matter Pathology Using NODDI and DTI group by integrating NODDI analysis with a standard voxel-wise group inference technique TBSS. The aim was to compare overlap in group results between the standard DTI and NODDI analysis. The NODDI parameters showed little overlap in the voxels that were identi- fied as discriminative across groups, indicating the parameters complemented each other. Taken together, however, NDI and ODI results showed a substantial overlap with FA results. In addition, we showed that these group results are not driven by NODDI model misfitting. One concern might be that there are differences in intrinsic diffusivity across groups, leading to biased estimation of the indices in one of the groups. Recently, however, it has been shown that variations in intrinsic diffusivity are reflected in the fitting residuals [39]. It is therefore important to inspect these residuals when using NODDI in group comparisons. In the current study, we did not observe any group differences in the fitting residuals, making it reasonable to conclude that intrinsic parallel diffusivity is comparable between the groups. Also, the CSF volume fraction (fiso) only differed minimally across groups, making it unlikely that this has biased our findings. Hence, we hereby demonstrate a conceptual disentanglement of FA into these two major contributing factors in the context of a clinical study. Further, we observed that NDI and ODI gave results that were more regionally specific compared to FA, giving more support for the idea to separately analyse these indices. Note that there is no ground truth here, but the observed regional patterns are in line with the known cognitive profile of this disease, namely higher order cognitive impairments (i.e., the anterior, bilateral profile of NDI changes), and language production and (speech) motor impairments (i.e., the predomi- nant left-hemispheric, more posterior ODI changes; see [20] for more information on the interpretation of the results, on the clusters and correlations with behaviour) [40–43]. Further- more, reduced NDI in this patient population is consistent with abnormal myelin associated with the disorder [27], which is linked to deficient galactosylation of galactocerebrosides (mye- lin building stones). From a modelling point of view, abnormal myelin increases in the extra- neurite space, which (indirectly) leads to a reduction in the (relative) volume fraction of the intra-neurite space (vfin). NDI can, however, also be affected by other processes, such as neuro- nal loss as this would also increase the extra-neurite space. The finding that the patients also showed increased ODI in left-lateralized regions indicates that the WM pathology is more diverse and complex than previously hypothesized. Interestingly, different brain regions reveal different WM microstructural changes, questioning which exact mechanisms underlie these findings (i.e., the left-lateralized profile of ODI fitting with motor and language problems, versus the bilateral anterior nature of NDI in line with more general higher order cognitive abnormalities). PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 Comparing White Matter Pathology Using NODDI and DTI less statistical power. It is recommended, therefore, to use both analyses in a complementary fashion. It could be argued that radial and axial diffusivity (RD and AD, respectively) already give more specific information as compared to FA. It has been suggested that RD reflects de/dys- myelination, while AD changes reflect axonal damage [8,9]. Although the interpretation of these parameters has been discouraged in the literature [10], we made a direct comparison between these and the NODDI parameters as well. The results revealed a comparable profile with the NODDI parameters: RD and AD group results were complementary with little over- lap, but together showed high overlap with FA (higher than NDI and ODI). This is not unex- pected, however, as AD and RD are simply based on the eigenvalues of the diffusion tensor, and FA is computed from these same eigenvalues (and hence FA and AD/RD are not indepen- dent). In addition, NDI results showed large overlap with RD (or perpendicular diffusivity), but minimal overlap with AD (or parallel diffusivity). This was also expected, since increased neurite density would lead to decreased radial diffusivity. Further, in the NODDI tissue model, parallel diffusivity is primarily influenced by ODI [11]. Indeed, ODI results showed large over- lap with parallel diffusivity (AD), but little overlap with perpendicular diffusivity (RD; for more details on the modelling aspects one can refer to [11]). It thus seems that although RD and AD give more information to complement FA, the variations can well be explained by NDI and ODI, and in a more specific and biologically informed manner. Further, RD and AD are still–like FA- based on the diffusion tensor, and thus suffer from the same weaknesses that more advanced models try to overcome using a physical model (i.e., by modelling multiple compartments, eliminating free water contamination). And, in the current study RD and AD were not as capable as NDI to capture additional discriminative voxels that FA missed. Hence, we demonstrated that NODDI parameters also have added value over the use of RD and AD. The second main finding is that group differences in ODI could be identified reliably using standard single-shell DTI data (i.e., using one non-zero b-value in addition to the b = 0 data). The ODI maps estimated by multi-shell and single-shell (b1000) data were very comparable, as demonstrated before [11]. PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 It warrants the need for further investigations to elucidate what causes these changes, and simultaneously demonstrates the added value of decomposing FA into these two separate indices to learn more about underlying pathologies. In addition to overlap with FA findings, we observed that NDI and ODI were capable of identifying discriminative voxels that were not captured by the FA analysis. More specifi- cally, almost 40% of the voxels that showed a significant group difference in NDI were not captured by the FA analysis, and 13% of the ODI discriminative voxels. From the location of these unique contributions (see Fig 2), it appears that this occurs at least partly in regions where there is fanning or crossing of fibres, such as in the corona radiata (but also in other regions). Previous studies have already shown that FA is weak in regions with complex fibre organisations [44]. Although NODDI does not explicitly takes crossing fibres into account, the data does suggest that NODDI analysis is of important added value in the investigation of changes in white matter microstructure in regions with more complex fibre organisa- tions. It should be noted, however, that the FA analysis was most sensitive, or at least identi- fied most group discriminative voxels. This could be explained by the fact that NDI and ODI each contribute to explain part of the detected FA changes, but separately they have 10 / 15 Further, the group results showed the same regional pattern, illus- trated by a high overlap in discriminative voxels. This indicates that retrospective analysis of standard single-shell DTI data with NODDI is possible and might provide valuable additional insights on angular variation in the neurites. Note that also single shells with higher b-values can be used, as they contain higher angular resolution. Examining orientation dispersion is rel- evant in many respects, both in white and in grey matter. For instance, the dispersion in orien- tation distribution is associated with development and aging of the brain (i.e., increase and reduction, respectively), and changes in the morphology of neurites can be linked to several neurological and neurodegenerative disorders. As already demonstrated before [11], NDI could not be estimated in a reliable manner using single-shell data, as it requires both a low b- value and a high b-value shell (in addition to b = 0 images). Also in the current assessment, the maps were mainly composed of noise (i.e., no WM and GM distinction) and the group analysis did not yield any overlapping results with the multi-shell NODDI analysis. could not be estimated in a reliable manner using single-shell data, as it requires both a low b- value and a high b-value shell (in addition to b = 0 images). Also in the current assessment, the maps were mainly composed of noise (i.e., no WM and GM distinction) and the group analysis did not yield any overlapping results with the multi-shell NODDI analysis. Finally, with this study we also demonstrated the feasibility of integrating NODDI analysis with standard DWI analysis tools, such as in this case DTI-TK (for tensor-based spatial nor- malisation) and TBSS (for voxel-wise group inferences). The pipeline of the data analysis is available and can be found in the Supporting Information (S1 File). To sum up, previous work has demonstrated the new insights into microstructure that NODDI can provide in a range of applications. The present study went one step further by conducting a systematic comparison between group differences determined by standard DTI and NODDI analyses. This helps clarifying the added value of NODDI analyses when making group inferences, complementary to standard DTI analysis, providing support for the 11 / 15 Comparing White Matter Pathology Using NODDI and DTI adoption of a longer, multi-shell diffusion imaging protocol in clinical samples. Supporting Information S1 File. Analysis pipeline for the TBSS analysis of DTI and NODDI data. (DOCX) Acknowledgments We kindly acknowledge the Dutch Galactosemia Patient Organization (GVN) for logistic sup- port. We further thank the participants and their parents for their time, effort and cooperation, and the anonymous reviewers for their useful suggestions. It shows that using a clinically feasible acquisition protocol and analysis pipeline, more specific substrates of white matter (compared to DTI) can be estimated and analysed separately. The NODDI parameters complemented each other, showed little overlap, and together showed substantial overlap with FA, indicating (conceptual) disentanglement of FA into two key contributors. Results further showed that compared to FA analysis, NDI and ODI gave a pattern of results that was more regionally specific and were able to capture additional discriminative voxels that FA failed to identify. Note again that FA was still the most sensitive to group differences, as expected from the simplicity of the model, even though fitted with less data (single shell) com- pared to NODDI (multi-shell). NODDI therefore is recommended to be used in addition to DTI, therewith adding greater specificity. Finally, we demonstrated that retrospective analysis of the angular variation of neurites (ODI) using standard DTI-quality datasets is viable. Future analyses further need not to be limited to the WM but can extend to evaluate neurite morphol- ogy and potential changes herein in the GM as well, and could include more recent extensions of the NODDI model to include anisotropy of the orientation dispersion (Bingham-NODDI) [45]. PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 References 1. Basser PJ, Mattiello J, Bihan DL (1994) MR diffusion tensor specstroscopy and imaging. Biophysical Journal 66: 259–267. doi: 10.1016/S0006-3495(94)80775-1 PMID: 8130344 2. Westlye LT, Walhovd KB, Dale AM, Bjørnerud A, Due-Tønnessen P, Engvig A, et al. (2010) Life-Span Changes of the Human Brain White Matter: Diffusion Tensor Imaging (DTI) and Volumetry. Cerebral Cortex 20: 2055–2068. doi: 10.1093/cercor/bhp280 PMID: 20032062 3. Filippi M, Rocca MA (2010) Diffusion tensor MRI in Multiple Sclerosis. In: Jones DK, editor. Diffusion MRI: Theory, Methods, and Applications. Oxford, United Kingdom: Oxford University Press. 4. Sullivan EV, Pfefferbaum A (2010) Diffusion tensor imaging in aging and age-related neurodegenera- tive disorders. In: Jones DK, editor. Diffusion MRI: Theory, Methods, and Applications. Oxford, United Kingdom: Oxford University Press. 5. Chapman MC, Jelsone-Swain L, Johnson TD, Gruis KL, Welsh RC (2013) Diffusion tensor MRI of the corpus callosum in amyotrophic lateral sclerosis. Journal of Magnetic Resonance Imaging 6. Roosendaal SD, Geurts JJG, Vrenken H, Hulst HE, Cover KS, Castelijns JA, et al. (2009) Regional DTI differences in multiple sclerosis patients. Neuroimage 44: 1397–1403. doi: 10.1016/j.neuroimage. 2008.10.026 PMID: 19027076 7. Pierpaoli C, Jezzard P, Basser PJ, Barnett A, Chiro GD (1996) Diffusion tensor MR imaging of the human brain. Radiology 201: 637–648. doi: 10.1148/radiology.201.3.8939209 PMID: 8939209 8. Song SK, Sun SW, Ramsbottom MJ, Chang C, Russell J, Cross AH (2002) Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. NeuroImage 17: 1429–1436. PMID: 12414282 9. DeBoy CA, Zhang J, Dike S, Shats I, Jones M, Reich DS, et al. (2007) High resolution diffusion tensor imaging of axonal damage in focal inflammatory and demyelinating lesions in rat spinal cord. Brain 130: 2199–2210. doi: 10.1093/brain/awm122 PMID: 17557778 10. Wheeler-Kingshott CAM, Cercignani M (2009) About "Axial" and "Radial" Diffusivities. Magnetic Reso- nance in Medicine 61: 1255–1260. doi: 10.1002/mrm.21965 PMID: 19253405 11. Zhang H, Schneider T, Wheeler-Kingshott Ca, Alexander DC (2012) NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain. NeuroImage 61: 1000–1016. doi: 10. 1016/j.neuroimage.2012.03.072 PMID: 22484410 12. Jespersen SN, Bjarkam CR, Nyengaard JR, Chakravarty MM, Hansen B, Vosegaard T, et al. (2010) Neurite density from magnetic resonance diffusion measurements at ultrahigh field: comparison with light microscopy and electron microscopy. Neuroimage 49: 205–216. doi: 10.1016/j.neuroimage.2009. 08.053 PMID: 19732836 13. Conceptualization: IT AR MB BJ ER HZ. Data curation: IT. Formal analysis: IT AR MB HZ. Funding acquisition: IT BJ ER. Investigation: IT. Methodology: IT AR MB HZ. Project administration: IT. Resources: IT AR MB ER HZ. Resources: IT AR MB ER HZ. Software: IT AR MB HZ. Software: IT AR MB HZ. Supervision: AR BJ ER HZ. Validation: IT. Visualization: IT. Writing – original draft: IT. Writing – review & editing: IT AR MB BJ ER HZ. PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 12 / 15 Comparing White Matter Pathology Using NODDI and DTI PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 References Jespersen SN, Leigland LA, Cornea A, Kroenke CD (2012) Determination of axonal and dendritic orien- tation distributions within the developing cerebral cortex by diffusion tensor imaging. IEEE Trans Med Imaging 31: 16–32. doi: 10.1109/TMI.2011.2162099 PMID: 21768045 14. Evanglou N, Esiri MM, Smith S, Palace J, Matthews PM (2000) Quantitative pathological evidence for axonal loss in normal appearing white matter in multiple sclerosis. Ann Neurol 47: 391–395. PMID: 10716264 15. Assaf Y, Basser PJ (2005) Composite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain. Neuroimage 27: 48–58. doi: 10.1016/j.neuroimage.2005.03.042 PMID: 15979342 16. Billiet T, Ma¨dler B, D’Arco F, Peeters R, Deprez S, Plasschaert E, et al. (2014) Characterizing the micro- structural basis of "unidentified bright objects" in neurofibromatosis type 1: A combined in vivo multicom- ponent T2 relaxation and multi-shell diffusion MRI analysis. Neuroimage Clinical 4: 649–658. doi: 10. 1016/j.nicl.2014.04.005 PMID: 24936416 17. Kunz N, Zhang H, Vasung L, O’Brien KR, Assaf Y, Lazeyras F, et al. (2014) Assessing white matter microstructure of the newborn with multi-shell diffusion MRI and biophysical compartment models. Neu- roimage 96: 288–299. doi: 10.1016/j.neuroimage.2014.03.057 PMID: 24680870 18. Owen JP, Chang YS, Pojman NJ, Bukshpun P, Wakahiro MLJ, Marco EJ, et al. (2014) Aberrant White Matter Microstructure in Children with 16p11.2 Deletions. The Journal of Neuroscience 34: 6214–6223. doi: 10.1523/JNEUROSCI.4495-13.2014 PMID: 24790192 19. Winston GP, Micallef C, Symms MR, Alexander DC, Duncan JS, Zhang H (2013) Advanced diffusion imaging sequences could aid assessing patients with focal cortical dysplasia and epilepsy. Epilepsy Research: http://dx.doi.org/10.1016/j.eplepsyres.2013.1011.1004. 20. Timmers I, Zhang H, Bastiani M, Jansma BM, Roebroeck A, Rubio-Gozalbo ME (2015) White matter microstructure pathology in classic galactosemia revealed by neurite orientation dispersion and density imaging. Journal of Inherited Metabolic Disease 38: 295–304. doi: 10.1007/s10545-014-9780-x PMID: 25344151 13 / 15 PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 Comparing White Matter Pathology Using NODDI and DTI 21. Adluru G, Gur Y, Anderson JS, Richards LG, Adluru N, DiBella EVR. Assessment of white matter micro- structure in stroke patients using NODDI; 2014 26–30 Aug. 2014. pp. 742–745. 22. Colgan N, Siow B, O’Callaghan JM, Harrison IF, Wells JA, Holmes HE, et al. (2016) Application of neur- ite orientation dispersion and density imaging (NODDI) to a tau pathology model of Alzheimer’s disease. NeuroImage 125: 739–744. doi: 10.1016/j.neuroimage.2015.10.043 PMID: 26505297 23. Kelly CE, Thompson DK, Chen J, Leemans A, Adamson CL, Inder TE, et al. References (2016) Axon density and axon orientation dispersion in children born preterm. Hum Brain Mapp 37: 3080–3102. doi: 10.1002/ hbm.23227 PMID: 27133221 24. Chung AW, Seunarine KK, Clark CA (2016) NODDI reproducibility and variability with magnetic field strength: A comparison between 1.5 T and 3 T. Hum Brain Mapp. 25. Chang YS, Owen JP, Pojman NJ, Thieu T, Bukshpun P, Wakahiro ML, et al. (2015) White Matter Changes of Neurite Density and Fiber Orientation Dispersion during Human Brain Maturation. PLoS One 10: e0123656. doi: 10.1371/journal.pone.0123656 PMID: 26115451 26. Caverzasi E, Papinutto N, Castellano A, Zhu AH, Scifo P, Riva M, et al. (2016) Neurite Orientation Dis- persion and Density Imaging Color Maps to Characterize Brain Diffusion in Neurologic Disorders. J Neuroimaging 26: 494–498. doi: 10.1111/jon.12359 PMID: 27214558 27. Nelson MD, Wolff JA, Cross CA, Donnell GN, Kaufman FR (1992) Galactosemia: Evaluation with MR Imaging. Radiology 184: 255–261. doi: 10.1148/radiology.184.1.1319076 PMID: 1319076 28. Haberland C, Hof EG, Perou H, Brunngraber M (1971) The neuropathology of galactosemia. A histo- pathological and biochemical study. Journal of Neuropathology & Experimental Neurology 30: 431– 447. 29. Andersson JLR, Skare S, Ashburner J (2003) How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging. Neuroimage 20: 870–888. doi: 10.1016/ S1053-8119(03)00336-7 PMID: 14568458 30. Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TEJ, Johansen-Berg H, et al. (2004) Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23: 208–219. 31. Graham MS, Drobnjak I, Zhang H (2016) Realistic simulation of artefacts in diffusion MRI for validating post-processing correction techniques. NeuroImage 125: 1079–1094. doi: 10.1016/j.neuroimage. 2015.11.006 PMID: 26549300 32. Andersson JLR, Sotiropoulos SN (2016) An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. NeuroImage 125: 1063–1078. doi: 10.1016/j. neuroimage.2015.10.019 PMID: 26481672 33. Zhang H, Yushkevich Pa, Alexander DC, Gee JC (2006) Deformable registration of diffusion tensor MR images with explicit orientation optimization. Medical image analysis 10: 764–785. doi: 10.1016/j. media.2006.06.004 PMID: 16899392 34. Keihaninejad S, Zhang H, Ryan NS, Malone IB, Modat M, Cardoso MJ, et al. (2013) An unbiased longi- tudinal analysis framework for tracking white matter changes using diffusion tensor imaging with appli- cation to Alzheimer’s disease. NeuroImage 72: 153–163. doi: 10.1016/j.neuroimage.2013.01.044 PMID: 23370057 35. Wang Y, Gupta A, Liu Z, Zhang H, Escolar ML, Golmore JH, et al. (2011) DTI registration in atlas based fiber analysis of infantile Krabbe disease. PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 45. Tariq M, Schneider T, Alexander DC, Gandini Wheeler-Kingshott CA, Zhang H (2016) Bingham- NODDI: Mapping anisotropic orientation dispersion of neurites using diffusion MRI. Neuroimage 133: 207–223. doi: 10.1016/j.neuroimage.2016.01.046 PMID: 26826512 42. Potter NL, Nievergelt Y, Shriberg LD (2013) Motor and Speech Disorders in Classic Galactosemia. JIMD reports 11: 31–41. doi: 10.1007/8904_2013_219 PMID: 23546812 References Neuroimage 55: 1577–1586. doi: 10.1016/j.neuroimage. 2011.01.038 PMID: 21256236 36. Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, et al. (2006) Tract- based spatial statistics: Voxelwise analysis of multi-subject diffusion data. Neuroimage 31: 1487–1505. doi: 10.1016/j.neuroimage.2006.02.024 PMID: 16624579 37. Smith SM, Nichols TE (2009) Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage 44: 83–98. doi: 10.1016/j. neuroimage.2008.03.061 PMID: 18501637 38. Dice LR (1945) Measures of the Amount of Ecologic Association Between Species. Ecology 26: 297– 302. 39. Guerrero JM, Adluru N, Kecskemeti SR, Davidson RJ, Alexander AL (2016) Investigating the effects of intrinsic diffusivity on neurite orientation dispersion and density imaging (NODDI). International Society for Magnetic Resonance in Medicine (ISMRM). Singapore. 40. Doyle CM, Channon S, Orlowska D, Lee PJ (2010) The neuropsychological profile of galactosaemia. Journal of Inherited Metabolic Disease 33: 603–609. doi: 10.1007/s10545-010-9154-y PMID: 20607611 41. Potter NL, Lazarus JAC, Johnson JM, Steiner RD, Shriberg LD (2008) Correlates of language impairment in children with galactosaemia. Journal of Inherited Metabolic Disease 31: 524–532. doi: 10.1007/s10545-008-0877-y PMID: 18649009 14 / 15 PLOS ONE \| DOI:10.1371/journal.pone.0167884 December 21, 2016 Comparing White Matter Pathology Using NODDI and DTI 42. Potter NL, Nievergelt Y, Shriberg LD (2013) Motor and Speech Disorders in Classic Galactosemia. JIMD reports 11: 31–41. doi: 10.1007/8904_2013_219 PMID: 23546812 43. Waisbren SE, Potter NL, Gordon CM, Green RC, Greenstein P, Gubbels CS, et al. (2012) The adult galactosemic phenotype. Journal of Inherited Metabolic Disease 35: 279–286. doi: 10.1007/s10545- 011-9372-y PMID: 21779791 44. Alexander AL, Hasan KM, Lazar M, Tsuruda JS, Parker DL (2001) Analy- sis of partial volume effects in diffusion-tensor MRI. Magn Reson Med 45: 770–780. PMID: 11323803 45. Tariq M, Schneider T, Alexander DC, Gandini Wheeler-Kingshott CA, Zhang H (2016) Bingham- NODDI: Mapping anisotropic orientation dispersion of neurites using diffusion MRI. Neuroimage 133: 207–223. doi: 10.1016/j.neuroimage.2016.01.046 PMID: 26826512 15 / 15
https://openalex.org/W4213113494	https://link.springer.com/content/pdf/10.1007/978-1-4302-5990-9.pdf?pdf=button	English	null	Efficient Learning Machines	Apress eBooks	2,015	cc-by	129,802	—Eric Hoffer, Reflections on the Human Condition —Eric Hoffer, Reflections on the Human Condition Machine learning (ML) is a branch of artificial intelligence that systematically applies algorithms to synthesize the underlying relationships among data and information. For example, ML systems can be trained on automatic speech recognition systems (such as iPhone’s Siri) to convert acoustic information in a sequence of speech data into semantic structure expressed in the form of a string of words. ML is already finding widespread uses in web search, ad placement, credit scoring, stock market prediction, gene sequence analysis, behavior analysis, smart coupons, drug development, weather forecasting, big data analytics, and many more applications. ML will play a decisive role in the development of a host of user-centric innovations. ML owes its burgeoning adoption to its ability to characterize underlying relationships within large arrays of data in ways that solve problems in big data analytics, behavioral pattern recognition, and information evolution. ML systems can moreover be trained to categorize the changing conditions of a process so as to model variations in operating behavior. As bodies of knowledge evolve under the influence of new ideas and technologies, ML systems can identify disruptions to the existing models and redesign and retrain themselves to adapt to and coevolve with the new knowledge. The computational characteristic of ML is to generalize the training experience (or examples) and output a hypothesis that estimates the target function. The generalization attribute of ML allows the system to perform well on unseen data instances by accurately predicting the future data. Unlike other optimization problems, ML does not have a well-defined function that can be optimized. Instead, training errors serve as a catalyst to test learning errors. The process of generalization requires classifiers that input discrete or continuous feature vectors and output a class. The goal of ML is to predict future events or scenarios that are unknown to the computer. In 1959, Arthur Samuel described ML as the “field of study that gives computers the ability to learn without being explicitly programmed” (Samuel 1959). He concluded that programming computers to learn from experience should eventually eliminate the need for much of this detailed programming effort. According to Tom M. Contents at a Glance About the Authors....................................................................................................xv About the Technical Reviewers.............................................................................xvii Acknowledgments..................................................................................................xix Chapter 1: Machine Learning ■ ■ ................................................................................ 1 Chapter 2: Machine Learning and Knowledge Discovery ■ ■ .................................... 19 Chapter 3: Support Vector Machines for Classification ■ ■ ....................................... 39 Chapter 4: Support Vector Regression ■ ■ ................................................................ 67 Chapter 5: Hidden Markov Model ■ ■ ........................................................................ 81 Chapter 6: Bioinspired Computing: Swarm Intelligence ■ ■ .................................... 105 Chapter 7: Deep Neural Networks ■ ■ ..................................................................... 127 Chapter 8: Cortical Algorithms ■ ■ .......................................................................... 149 Chapter 9: Deep Learning ■ ■ .................................................................................. 167 Chapter 10: Multiobjective Optimization ■ ■ ........................................................... 185 Chapter 11: Machine Learning in Action: Examples ■ ■ .......................................... 209 Index..................................................................................................................... 241 v v Machine Learning Nature is a self-made machine, more perfectly automated than any automated machine. To create something in the image of nature is to create a machine, and it was by learning the inner working of nature that man became a builder of machines. —Eric Hoffer, Reflections on the Human Condition —Eric Hoffer, Reflections on the Human Condition Mitchell’s definition of ML: “A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.” Alan Turing’s seminal paper (Turing 1950) introduced a benchmark standard for demonstrating machine intelligence, such that a machine has to be intelligent and responsive in a manner that cannot be differentiated from that of a human being. 1 Chapter 1 ■ Machine Learning The learning process plays a crucial role in generalizing the problem by acting on its historical experience. Experience exists in the form of training datasets, which aid in achieving accurate results on new and unseen tasks. The training datasets encompass an existing problem domain that the learner uses to build a general model about that domain. This enables the model to generate largely accurate predictions in new cases. • accuracy (aka error rate). The rate of correct (or incorrect) predictions made by the model over a dataset. Accuracy is usually estimated by using an independent test set that was not used at any time during the learning process. More complex accuracy estimation techniques, such as cross-validation and bootstrapping, are commonly used, especially with datasets containing a small number of instances. Key Terminology To facilitate the reader’s understanding of the concept of ML, this section defines and discusses some key multidisciplinary conceptual terms in relation to ML. • classifier. A method that receives a new input as an unlabeled instance of an observation or feature and identifies a category or class to which it belongs. Many commonly used classifiers employ statistical inference (probability measure) to categorize the best label for a given instance. • confusion matrix (aka error matrix). A matrix that visualizes the performance of the classification algorithm using the data in the matrix. It compares the predicted classification against the actual classification in the form of false positive, true positive, false negative and true negative information. A confusion matrix for a two-class classifier system (Kohavi and Provost, 1998) follows: • confusion matrix (aka error matrix). A matrix that visualizes the performance of the classification algorithm using the data in the matrix. It compares the predicted classification against the actual classification in the form of false positive, true positive, false negative and true negative information. A confusion matrix for a two-class classifier system (Kohavi and Provost, 1998) follows: • accuracy (aka error rate). The rate of correct (or incorrect) predictions made by the model over a dataset. Accuracy is usually estimated by using an independent test set that was not used at any time during the learning process. More complex accuracy estimation techniques, such as cross-validation and bootstrapping, are commonly used, especially with datasets containing a small number of instances. • accuracy (aka error rate). The rate of correct (or incorrect) predictions made by the model over a dataset. Accuracy is usually estimated by using an independent test set that was not used at any time during the learning process. More complex accuracy estimation techniques, such as cross-validation and bootstrapping, are commonly used, especially with datasets containing a small number of instances. 2 Chapter 1 ■ Machine Learning Accuracy (AC) = + + + + TP TN TP TN FN FP (1-1) Precision (P) = + TP TP FP (1-2) (1-1) (1-2) Recall R true positive rate , ( ) = + TP TP FN (1-3) F Measure - = + ( )× × × + b b 2 2 1 P R P R , (1-4) where b has a value from 0 to infinity (∞) and is used to control the weight assigned to P and R. • cost. Key Terminology The measurement of performance (or accuracy) of a model that predicts (or evaluates) the outcome for an established result; in other words, that quantifies the deviation between predicted and actual values (or class labels). An optimization function attempts to minimize the cost function. • cross-validation. A verification technique that evaluates the generalization ability of a model for an independent dataset. It defines a dataset that is used for testing the trained model during the training phase for overfitting. Cross-validation can also be used to evaluate the performance of various prediction functions. In k-fold cross-validation, the training dataset is arbitrarily partitioned into k mutually exclusive subsamples (or folds) of equal sizes. The model is trained k times (or folds), where each iteration uses one of the k subsamples for testing (cross-validating), and the remaining k-1 subsamples are applied toward training the model. The k results of cross-validation are averaged to estimate the accuracy as a single estimation. • cross-validation. A verification technique that evaluates the generalization ability of a model for an independent dataset. It defines a dataset that is used for testing the trained model during the training phase for overfitting. Cross-validation can also be used to evaluate the performance of various prediction functions. In k-fold cross-validation, the training dataset is arbitrarily partitioned into k mutually exclusive subsamples (or folds) of equal sizes. The model is trained k times (or folds), where each iteration uses one of the k subsamples for testing (cross-validating), and the remaining k-1 subsamples are applied toward training the model. The k results of cross-validation are averaged to estimate the accuracy as a single estimation. • data mining. The process of knowledge discovery (q.v.) or pattern detection in a large dataset. The methods involved in data mining aid in extracting the accurate data and transforming it to a known structure for further evaluation. • data mining. The process of knowledge discovery (q.v.) or pattern detection in a large dataset. The methods involved in data mining aid in extracting the accurate data and transforming it to a known structure for further evaluation. • dataset. A collection of data that conform to a schema with no ordering requirements. In a typical dataset, each column represents a feature and each row represents a member of the dataset. • dimension. A set of attributes that defines a property. The primary functions of dimension are filtering, classification, and grouping. Key Terminology • induction algorithm. An algorithm that uses the training dataset to generate a model that generalizes beyond the training dataset. • instance. An object characterized by feature vectors from which the model is either trained for generalization or used for prediction. • knowledge discovery. The process of abstracting knowledge from structured or unstructured sources to serve as the basis for further exploration. Such knowledge is collectively represented as a schema and can be condensed in the form of a model or models to which queries can be made for statistical prediction, evaluation, and further knowledge discovery. 3 3 Chapter 1 ■ Machine Learning model. A structure that summarizes a dataset for description or prediction. Each model can be tuned to the specific requirements of an application. Applications in big data have large datasets with many predictors and features that are too complex for a simple parametric model to extract useful information. The learning process synthesizes the parameters and the structures of a model from a given dataset. Models may be generally categorized as either parametric (described by a finite set of parameters, such that future predictions are independent of the new dataset) or nonparametric (described by an infinite set of parameters, such that the data distribution cannot be expressed in terms of a finite set of parameters). Nonparametric models are simple and flexible, and make fewer assumptions, but they require larger datasets to derive accurate conclusions. model. A structure that summarizes a dataset for description or prediction. Each model can be tuned to the specific requirements of an application. Applications in big data have large datasets with many predictors and features that are too complex for a simple parametric model to extract useful information. The learning process synthesizes the parameters and the structures of a model from a given dataset. Models may be generally categorized as either parametric (described by a finite set of parameters, such that future predictions are independent of the new dataset) or nonparametric (described by an infinite set of parameters, such that the data distribution cannot be expressed in terms of a finite set of parameters). Nonparametric models are simple and flexible, and make fewer assumptions, but they require larger datasets to derive accurate conclusions. online analytical processing (OLAP). An approach for resolving multidimensional analytical queries. Such queries index into the data with two or more attributes (or dimensions). Key Terminology OLAP encompasses a broad class of business intelligence data and is usually synonymous with multidimensional OLAP (MOLAP). OLAP engines facilitate the exploration of multidimensional data interactively from several perspectives, thereby allowing for complex analytical and ad hoc queries with a rapid execution time. OLAP commonly uses intermediate data structures to store precalculated results on multidimensional data, allowing fast computation. Relational OLAP (ROLAP) uses relational databases of the base data and the dimension tables. schema. A high-level specification of a dataset’s attributes and properties. • schema. A high-level specification of a dataset’s attributes and properties. • supervised learning. Learning techniques that extract associations between independent attributes and a designated dependent attribute (the label). Supervised learning uses a training dataset to develop a prediction model by consuming input data and output values. The model can then make predictions of the output values for a new dataset. The performance of models developed using supervised learning depends upon the size and variance of the training dataset to achieve better generalization and greater predictive power for new datasets. Most induction algorithms fall into the supervised learning category. • supervised learning. Learning techniques that extract associations between independent attributes and a designated dependent attribute (the label). Supervised learning uses a training dataset to develop a prediction model by consuming input data and output values. The model can then make predictions of the output values for a new dataset. The performance of models developed using supervised learning depends upon the size and variance of the training dataset to achieve better generalization and greater predictive power for new datasets. Most induction algorithms fall into the supervised learning category. unsupervised learning. Learning techniques that group instances without a prespecified dependent attribute. This technique generally involves learning structured patterns in the data by rejecting pure unstructured noise. Clustering and dimensionality reduction algorithms are usually unsupervised. • unsupervised learning. Learning techniques that group instances without a prespecified dependent attribute. This technique generally involves learning structured patterns in the data by rejecting pure unstructured noise. Clustering and dimensionality reduction algorithms are usually unsupervised. • feature vector. An n-dimensional numerical vector of explanatory variables representing an instance of some object that facilitates processing and statistical analysis. Feature vectors are often weighted to construct a predictor function that is used to evaluate the quality or fitness of the prediction. Key Terminology The dimensionality of a feature vector can be reduced by various dimensionality reduction techniques, such as principal component analysis (PCA), multilinear subspace reduction, isomaps, and latent semantic analysis (LSA). The vector space associated with these vectors is often called the feature space. 4 Chapter 1 ■ Machine Learning Chapter 1 ■ Machine Learning Developing a Learning Machine Machine learning aids in the development of programs that improve their performance for a given task through experience and training. Many big data applications leverage ML to operate at highest efficiency. The sheer volume, diversity, and speed of data flow have made it impracticable to exploit the natural capability of human beings to analyze data in real time. The surge in social networking and the wide use of Internet- based applications have resulted not only in greater volume of data, but also increased complexity of data. To preserve data resolution and avoid data loss, these streams of data need to be analyzed in real time. The heterogeneity of the big data stream and the massive computing power we possess today present us with abundant opportunities to foster learning methodologies that can identify best practices for a given business problem. The sophistication of modern computing machines can handle large data volumes, greater complexity, and terabytes of storage. Additionally, intelligent program-flows that run on these machines can process and combine many such complex data streams to develop predictive models and extract intrinsic patterns in otherwise noisy data. When you need to predict or forecast a target value, supervised learning is the appropriate choice. The next step is to decide, depending on the target value, between clustering (in the case of discrete target value) and regression (in the case of numerical target value). You start the development of ML by identifying all the metrics that are critical to a decision process. The processes of ML synthesize models for optimizing the metrics. Because the metrics are essential to developing the solution for a given decision process, they must be selected carefully during conceptual stages. It is also important to judge whether ML is the suitable approach for solving a given problem. By its nature, ML cannot deliver perfect accuracy. For solutions requiring highly accurate results in a bounded time period, ML may not be the preferred approach. In general, the following conditions are favorable to the application of ML: (a) very high accuracy is not desired; (b) large volumes of data contain undiscovered patterns or information to be synthesized; (c) the problem itself is not very well understood owing to lack of knowledge or historical information as a basis for developing suitable algorithms; and (d) the problem needs to adapt to changing environmental conditions. Developing a Learning Machine The process of developing ML algorithms may be decomposed into the following steps The process of developing ML algorithms may be decomposed into the following steps: 1. Collect the data. Select the subset of all available data attributes that might be useful in solving the problem. Selecting all the available data may be unnecessary or counterproductive. Depending upon the problem, data can either be retrieved through a data-stream API (such as a CPU performance counters) or synthesized by combining multiple data streams. In some cases, the input data streams, whether raw or synthetic, may be statistically preprocessed to improve usage or reduce bandwidth. 2. Preprocess the Data. Present the data in a manner that is understood by the consumer of the data. Preprocessing consists of the following three steps: i. Formatting. The data needs to be presented in a useable format. Using an industry-standard format enable plugging the solution with multiple vendors that in turn can mix and match algorithms and data sources such as XML, HTML, and SOAP. ii. Cleaning. The data needs to be cleaned by removing, substituting, or fixing corrupt or missing data. In some cases, data needs to be normalized, discretized, averaged, smoothened, or differentiated for efficient usage. In other cases, data may need to be transmitted as integers, double precisions, or strings. iii. Sampling. Data need to be sampled at regular or adaptive intervals in a manner such that redundancy is minimized without the loss of information for transmission via communication channels. 5 5 Chapter 1 ■ Machine Learning 3. Transform the data. Transform the data specific to the algorithm and the knowledge of the problem. Transformation can be in the form of feature scaling, decomposition, or aggregation. Features can be decomposed to extract the useful components embedded in the data or aggregated to combine multiple instances into a single feature. 4. Train the algorithm. Select the training and testing datasets from the transformed data. An algorithm is trained on the training dataset and evaluated against the test set. The transformed training dataset is fed to the algorithm for extraction of knowledge or information. This trained knowledge or information is stored as a model to be used for cross-validation and actual usage. Unsupervised learning, having no target value, does not require the training step. 5. 5. Test the algorithm. Evaluate the algorithm to test its effectiveness and performance. Developing a Learning Machine This step enables quick determination whether any learnable structures can be identified in the data. A trained model exposed to test dataset is measured against predictions made on that test dataset which are indicative of the performance of the model. If the performance of the model needs improvement, repeat the previous steps by changing the data streams, sampling rates, transformations, linearizing models, outliers’ removal methodology, and biasing schemes. 6. 6. Apply reinforcement learning. Most control theoretic applications require a good feedback mechanism for stable operations. In many cases, the feedback data are sparse, delayed, or unspecific. In such cases, supervised learning may not be practical and may be substituted with reinforcement learning (RL). In contrast to supervised learning, RL employs dynamic performance rebalancing to learn from the consequences of interactions with the environment, without explicit training. 7. Execute. Apply the validated model to perform an actual task of prediction. If new data are encountered, the model is retrained by applying the previous steps. The process of training may coexist with the real task of predicting future behavior. Machine Learning Algorithms Based on underlying mappings between input data and anticipated output presented during the learning phase of ML, ML algorithms may be classified into the following six categories: • Supervised learning is a learning mechanism that infers the underlying relationship between the observed data (also called input data) and a target variable (a dependent variable or label) that is subject to prediction (Figure 1-1). The learning task uses the labeled training data (training examples) to synthesize the model function that attempts to generalize the underlying relationship between the feature vectors (input) and the supervisory signals (output). The feature vectors influence the direction and magnitude of change in order to improve the overall performance of the function model. The training data comprise observed input (feature) vectors and a desired output value (also called the supervisory signal or class label). A well-trained function model based on a supervised learning algorithm can accurately predict the class labels for hidden phenomena embedded in unfamiliar or unobserved data instances. The goal of learning algorithms is to minimize the error for a given set of inputs (the training set). However, for a poor-quality training set that is influenced by the accuracy and versatility of the labeled examples, the model may encounter the problem of overfitting, which typically represents poor generalization and erroneous classification. • Supervised learning is a learning mechanism that infers the underlying relationship between the observed data (also called input data) and a target variable (a dependent variable or label) that is subject to prediction (Figure 1-1). The learning task uses the labeled training data (training examples) to synthesize the model function that attempts to generalize the underlying relationship between the feature vectors (input) and the supervisory signals (output). The feature vectors influence the direction and magnitude of change in order to improve the overall performance of the function model. The training data comprise observed input (feature) vectors and a desired output value (also called the supervisory signal or class label). ll i d f i d l b d i d l i l i h p ( p y g ) A well-trained function model based on a supervised learning algorithm can accurately predict the class labels for hidden phenomena embedded in unfamiliar or unobserved data instances. The goal of learning algorithms is to minimize the error for a given set of inputs (the training set). Machine Learning Algorithms Because the labeling process of acquired data requires intensive skilled human labor inputs, it is expensive and impracticable. In contrast, unlabeled data are relatively inexpensive and readily available. Semi-supervised ML methodology operates somewhere between the guidelines of unsupervised learning (unlabeled training data) and supervised learning (labeled training data) and can produce considerable improvement in learning accuracy. Semi-supervised learning has recently gained greater prominence, owing to the availability of large quantities of unlabeled data for diverse applications to web data, messaging data, stock data, retail data, biological data, images, and so on. This learning methodology can deliver value of practical and theoretical significance, especially in areas related to human learning, such as speech, vision, and handwriting, which involve a small amount of direct instruction and a large amount of unlabeled experience. • Semi-supervised learning uses a combination of a small number of labeled and a large number of unlabeled datasets to generate a model function or classifier. Because the labeling process of acquired data requires intensive skilled human labor inputs, it is expensive and impracticable. In contrast, unlabeled data are relatively inexpensive and readily available. Semi-supervised ML methodology operates somewhere between the guidelines of unsupervised learning (unlabeled training data) and supervised learning (labeled training data) and can produce considerable improvement in learning accuracy. Semi-supervised learning has recently gained greater prominence, owing to the availability of large quantities of unlabeled data for diverse applications to web data, messaging data, stock data, retail data, biological data, images, and so on. This learning methodology can deliver value of practical and theoretical significance, especially in areas related to human learning, such as speech, vision, and handwriting, which involve a small amount of direct instruction and a large amount of unlabeled experience. Reinforcement learning (RL) methodology involves exploration of an adaptive sequence of actions or behaviors by an intelligent agent (RL-agent) in a given environment with a motivation to maximize the cumulative reward (Figure 1-2). The intelligent agent’s action triggers an observable change in the state of the environment. The learning technique synthesizes an adaptation model by training itself for a given set of experimental actions and observed responses to the state of the environment. In general, this methodology can be viewed as a control-theoretic trial-and-error learning paradigm with rewards and punishments associated with a sequence of actions. The RL-agent changes its policy based on the collective experience and consequent rewards. Machine Learning Algorithms However, for a poor-quality training set that is influenced by the accuracy and versatility of the labeled examples, the model may encounter the problem of overfitting, which typically represents poor generalization and erroneous classification. p ( p y g ) A well-trained function model based on a supervised learning algorithm can accurately predict the class labels for hidden phenomena embedded in unfamiliar or unobserved data instances. The goal of learning algorithms is to minimize the error for a given set of inputs (the training set). However, for a poor-quality training set that is influenced by the accuracy and versatility of the labeled examples, the model may encounter the problem of overfitting, which typically represents poor generalization and erroneous classification. 6 Chapter 1 ■ Machine Learning Figure 1-1. High-level flow of supervised learning Figure 1-1. High-level flow of supervised learning • Unsupervised learning algorithms are designed to discover hidden structures in unlabeled datasets, in which the desired output is unknown. This mechanism has found many uses in the areas of data compression, outlier detection, classification, human learning, and so on. The general approach to learning involves training through probabilistic data models. Two popular examples of unsupervised learning are clustering and dimensionality reduction. In general, an unsupervised learning dataset is composed of inputs x x x xn 1 2 3 , ,  , but it contains neither target outputs (as in supervised learning) nor rewards from its environment. The goal of ML in this case is to hypothesize representations of the input data for efficient decision making, forecasting, and information filtering and clustering. For example, unsupervised training can aid in the development of phase-based models in which each phase, synthesized through an unsupervised learning process, represents a unique condition for opportunistic tuning of the process. Furthermore, each phase can act as a state and can be subjected to forecasting for proactive resource allocation or distribution. Unsupervised learning algorithms centered on a probabilistic distribution model generally use maximum likelihood estimation (MLE), maximum a posteriori (MAP), or Bayes methods. Other algorithms that are not based on probability distribution models may employ statistical measurements, quantization error, variance preserving, entropy gaps, and so on. 7 Chapter 1 ■ Machine Learning • Semi-supervised learning uses a combination of a small number of labeled and a large number of unlabeled datasets to generate a model function or classifier. Machine Learning Algorithms RL seeks past actions it explored that resulted in rewards. To build an exhaustive database or model of all the possible action- reward projections, many unproven actions need to be tried. These untested actions may have to be attempted multiple times before ascertaining their strength. Therefore, you have to strike a balance between exploration of new possible actions and likelihood of failure resulting from those actions. Critical elements of RL include the following: The • policy is a key component of an RL-agent that maps the control-actions to the perceived state of the environment. The • critic represents an estimated value function that criticizes the actions that are made according to existing policy. Alternatively, the critic evaluates the performance of the current state in response to an action taken according to current policy. The critic-agent shapes the policy by making continuous and ongoing corrections. The • reward function estimates the instantaneous desirability of the perceived state of the environment for an attempted control-action. • Models are planning tools that aid in predicting the future course of action by contemplating possible future situations. 8 Chapter 1 ■ Machine Learning Figure 1-2. High-level flow of reinforcement learning Figure 1-2. High-level flow of reinforcement learning • Transductive learning (aka transductive inference) attempts to predict exclusive model functions on specific test cases by using additional observations on the training dataset in relation to the new cases (Vapnik 1998). A local model is established by fitting new individual observations (the training data) into a single point in space—this, in contrast to the global model, in which new data have to fit into the existing model without postulating any specific information related to the location of that data point in space. Although the new data may fit into the global model to a certain extent (with some error), thereby creating a global model that would represent the entire problem, space is a challenge and may not be necessary in all cases. In general, if you experience discontinuities during the model development for a given problem space, you can synthesize multiple models at the discontinuous boundaries. In this case, newly observed data are the processed through the model that fulfill the boundary conditions in which the model is valid. Machine Learning Algorithms Inductive inference estimates the model function based on the relation of data to the entire hypothesis space, and uses this model to forecast output values for examples beyond the training set. These functions can be defined using one of the many representation schemes, including linear weighted polynomials, logical rules, and probabilistic descriptions, such as Bayesian networks. Many statistical learning methods start with initial solutions for the hypothesis space and then evolve them iteratively to reduce error. Many popular algorithms fall into this category, including SVMs (Vapnik 1998), neural network (NN) models (Carpenter and Grossberg 1991), and neuro-fuzzy algorithms (Jang 1993). In certain cases, one may apply a lazy learning model, in which the generalization process can be an ongoing task that effectively develops a richer hypothesis space, based on new data applied to the existing model. 9 9 Chapter 1 ■ Machine Learning C4.5 C4.5 classifiers are one of the most frequently used categories of algorithms in data mining. A C4.5 classifier inputs a collection of cases wherein each case is a sample preclassified to one of the existing classes. Each case is described by its n-dimensional vector, representing attributes or features of the sample. The output of a C4.5 classifier can accurately predict the class of a previously unseen case. C4.5 classification algorithms generate classifiers that are expressed as decision trees by synthesizing a model based on a tree structure. Each node in the tree structure characterizes a feature, with corresponding branches representing possible values connecting features and leaves representing the class that terminates a series of nodes and branches. The class of an instance can be determined by tracing the path of nodes and branches to the terminating leaf. Given a set S of instances C4 5 uses a divide and conquer method to grow an initial tree as follows: If all the samples in the list • S belong to the same class, or if the list S is small, then create a leaf node for the decision tree and label it with the most frequent class. Otherwise, the algorithm selects an attribute-based test that branches • S into multiple subbranches (partitions) (S1, S2, …), each representing the outcome of the test. The tests are placed at the root of the tree, and each path from the root to the leaf becomes a rule script that labels a class at the leaf. This procedure applies to each subbranch recursively. Each partition of the current branch represents a child node, and the test separating • S represents the branch of the tree. Each partition of the current branch represents a child node, and the test separating • S represents the branch of the tree. S represents the branch of the tree. This process continues until every leaf contains instances from only one class or further partition is not possible. C4.5 uses tests that select attributes with the highest normalized information gain, enabling disambiguation of the classification of cases that may belong to two or more classes. Popular Machine Learning Algorithms This section describes in turn the top 10 most influential data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) in December 2006: C4.5, k-means, SVMs, Apriori, estimation maximization (EM), PageRank, AdaBoost, k–nearest neighbors (k-NN), naive Bayes, and classification and regression trees (CARTs) (Wu et al. 2008). 2. Update: Each cluster centroid is recalculated to the center (mean) of all data points assigned to it. These two steps are alternated until a stopping criterion is met, such that there is no further change in the assignment of data points. Every iteration requires N × K comparisons, representing the time complexity of one iteration. k-Means The k-means algorithm is a simple iterative clustering algorithm (Lloyd 1957) that partitions N data points into K disjoint subsets Sj so as to minimize the sum-of-squares criterion. Because the sum of squares is the squared Euclidean distance, this is intuitively the “nearest” mean, J = - Î = å å \| \| , xn n S j K j j 1 2 m (1-5) J = - Î = å å \| \| , xn n S j K j j 1 2 m (1-5) where xn= vector representing the nth data point mj = geometric centroid of the data points in Sj 10 Chapter 1 ■ Machine Learning The algorithm consists of a simple two-step re-estimation process: The algorithm consists of a simple two-step re-estimation process: 1. Assignment: Data points are assigned to the cluster whose centroid is closest to that point. 2. Update: Each cluster centroid is recalculated to the center (mean) of all data points assigned to it. Apriori Apriori is a data mining approach that discovers frequent itemsets by using candidate generation (Agrawal and Srikant 1994) from a transactional database and highlighting association rules (general trends) in the database. It assumes that any subset of a frequently occurring pattern must be frequent. Apriori performs breadth-first search to scan frequent 1-itemsets (that is, itemsets of size 1) by accumulating the count for each item that satisfies the minimum support requirement. The set of frequent 1-itemsets is used to find the set of frequent 2-itemsets, and so on. This process iterates until no more frequent k-itemsets can be found. The Apriori method that identifies all the frequent itemsets can be summarized in the following three steps: 1. Generate candidates for frequent k + 1-itemsets (of size k + 1) from the frequent k-itemsets (of size k). 2. Scan the database to identify candidates for frequent k + 1-itemsets, and calculate the support of each of those candidates. 2. Scan the database to identify candidates for frequent k + 1-itemsets, and 2. Scan the database to identify candidates for frequen calculate the support of each of those candidates. 2. Scan the database to identify candidates for freque calculate the support of each of those candidates. 3. Add those itemsets that satisfy the minimum support requirement to frequent itemsets of size k + 1. Thanks in part to the simplicity of the algorithm, it is widely used in data mining applications. Various improvements have been proposed, notably, the frequent pattern growth (FP-growth) extension, which eliminates candidate generation. Han et al. (Han, Pei, and Yin 2000) propose a frequent pattern tree (FP-tree) structure, which stores and compresses essential information to interpret frequent patterns and uses FP-growth for mining the comprehensive set of frequent patterns by pattern fragment growth. This Apriori technique enhancement constructs a large database that contains all the essential information and compresses it into a highly condensed data structure. In the subsequent step, it assembles a conditional- pattern base which represents a set of counted patterns that co-occur relative to each item. Starting at the frequent header table, it traverses the FP-tree by following each frequent item and stores the prefix paths of those items to produce a conditional pattern base. Finally, it constructs a conditional FP-tree for each of the frequent items of the conditional pattern base. Each node in the tree represents an item and its count. Support Vector Machines Support vector machines (SVMs) are supervised learning methods that analyze data and recognize patterns. SVMs are primarily used for classification, regression analysis, and novelty detection. Given a set of training data in a two-class learning task, an SVM training algorithm constructs a model or classification function that assigns new observations to one of the two classes on either side of a hyperplane, making it a nonprobabilistic binary linear classifier (Figure 1-3). An SVM model maps the observations as points in space, such that they are classified into a separate partition that is divided by the largest distance to the nearest observation data point of any class (the functional margin). New observations are then predicted to belong to a class based on which side of the partition they fall. Support vectors are the data points nearest to the hyperplane that divides the classes. Further details of support vector machines are given in Chapter 4. Figure 1-3. The SVM algorithm finds the hyperplane that maximizes the largest minimum distance between the support vectors Figure 1-3. The SVM algorithm finds the hyperplane that maximizes the largest minimum distance between the support vectors 11 11 Chapter 1 ■ Machine Learning Apriori Nodes sharing the same label but residing on different subtrees are conjoined by a node–link pointer. The position of a node in the tree structure represents the order of the frequency of an item, such that a node closer to the root may be shared by more transactions in a transactional database. 2. Maximization (M): Find the parameter that maximizes this quantity: q q q q ( ) arg max ( \| ( )). t Q t + = 1 (1-7) (1-7) q q q q ( ) arg max ( \| ( )). t Q t + = 1 (1-7) q q q q ( ) arg max ( \| ( )). t Q t + = 1 q q q q ( ) arg max ( \| ( )). t Q t + = 1 PageRank PageRank is a link analysis search algorithm that ranks the elements of hyperlinked documents on the World Wide Web for the purpose of measuring their importance, relative to other links. Developed by Larry Page and Sergey Bin, PageRank produces static rankings that are independent of the search queries. PageRank simulates the concept of prestige in a social network. A hyperlink to a page counts as a vote of support. Additionally, PageRank interprets a hyperlink from source page to target page in such a manner that the page with the higher rank improves the rank of the linked page (the source or target). Therefore, backlinks from highly ranked pages are more significant than those from average pages. Mathematically simple, PageRank can be calculated as r P r Q Q Q Bp ( ) ( ) \| \| , = Îå (1-8) r P r Q Q Q Bp ( ) ( ) \| \| , = Îå (1-8) r P r Q Q Q Bp ( ) ( ) \| \| , = Îå where r(P) = rank of the page P Bp= the set of all pages linking to page P \|Q\| = number of links from page Q r(Q) = rank of the page Q where r(P) = rank of the page P Bp= the set of all pages linking to page P \|Q\| = number of links from page Q r(Q) = rank of the page Q AdaBoost (Adaptive Boosting) AdaBoost is an ensemble method used for constructing strong classifiers as linear combinations of simple, weak classifiers (or rules of thumb) (Freund and Schapire 1997). As in any ensemble method, AdaBoost employs multiple learners to solve a problem with better generalization ability and more accurate prediction. The strong classifier can be evaluated as a linear combination of weak classifiers, such that H x h x t t t T ( ) ( ), = × =åb 1 where H(x) = strong classifier ht(x) = weak classifier (feature) H x h x t t t T ( ) ( ), = × =åb 1 where H(x) = strong classifier ht(x) = weak classifier (feature) where H(x) = strong classifier ht(x) = weak classifier (feature) The Adaboost algorithm may be summarized as follows: Input: Data-Set I x y x y x y x y m m = ( ) ( ) ( ) ( ) { } 1 1 2 2 3 3 , , , , , , , ,  , Base learning algorithm L Number of learning rounds T P Input: Data-Set I x y x y x y x y m m = ( ) ( ) ( ) ( ) { } 1 1 2 2 3 3 , , , , , , , ,  , Base learning algorithm L Number of learning rounds T Process: 1 1 i D m = // Initialize weight distribution FOR (t = 1 to T) DO // Run the loop for t = T iterations ht = L(I, Dt) // Train a weak learner ht from I using Dt Î = - å t t i t i i i D h x y \| ( ) \| // calculate the error of ht Estimation Maximization The estimation–maximization (EM) algorithm facilitates parameter estimation in probabilistic models with incomplete data. EM is an iterative scheme that estimates the MLE or MAP of parameters in statistical models, in the presence of hidden or latent variables. The EM algorithm iteratively alternates between the steps of performing an expectation (E), which creates a function that estimates the probability distribution over possible completions of the missing (unobserved) data, using the current estimate for the parameters, and performing a maximization (M), which re-estimates the parameters, using the current completions performed during the E step. These parameter estimates are iteratively employed to estimate the distribution of the hidden variables in the subsequent E step. In general, EM involves running an iterative algorithm with the following attributes: (a) observed data, X; (b) latent (or missing) data, Z; (c) unknown parameter, q; and (d) a likelihood function, L(q; X, Z) = P(X, Z\|q). The EM algorithm iteratively calculates the MLE of the marginal likelihood using a two-step method: 1. Estimation (E): Calculate the expected value of the log likelihood function, with respect to the conditional distribution of Z, given X under the current estimate of the parameters q(t), such that (1-6) Q t E L X Z Z X t ( \| ( )) log ( ; , ) . \| , ( ) q q q q = [ ] 12 Chapter 1 ■ Machine Learning Input: Input: Data-Set I x y x y x y x y m m = ( ) ( ) ( ) ( ) { } 1 1 2 2 3 3 , , , , , , , ,  , Base learning algorithm L g g Number of learning rounds T END Output: H x sign h x t t t T ( ) ( ) = æ èç ö ø÷ =åb 1 // Strong classifier H x sign h x t t t T ( ) ( ) = æ èç ö ø÷ =åb 1 // Strong classifier The AdaBoost algorithm is adaptive, inasmuch as it uses multiple iterations to produce a strong learner that is well correlated with the true classifier. As shown above, it iterates by adding weak learners that are slightly correlated with the true classifier. As part of the adaptation process, the weighting vector adjusts itself to improve upon misclassification in previous rounds. The resulting classifier has a greater accuracy than the weak learners’ classifiers. AdaBoost is fast, simple to implement, and flexible insofar as it can be combined with any classifier. Input: p Training object (x, y) Î I and test object ˆ (ˆ, ˆ) x z x y = Training object (x, y) Î I and test object ˆ (ˆ, ˆ) x z x y = the number of nearest neighbors ( • k) To classify an unlabeled object, the distances between it and labeled objects are calculated and its k-nearest neighbors are identified. The class labels of these nearest neighbors serve as a reference for classifying the unlabeled object. The k-NN algorithm computes the similarity distance between a training set, (x, y) Î I, and the test object, ˆ (ˆ, ˆ) x z x y = , to determine its nearest-neighbor list, Iz. x represents the training object, and y represents the corresponding training class. ˆx and ˆy represent the test object and its class, respectively. The algorithm may be summarized as follows: Process: 13 13 Chapter 1 ■ Machine Learning bt t t = -Î Î æ è ç ö ø ÷ 1 2 1 ln // calculate the weight of ht t i t i t y h x D D Z e t i t i + - × × = × 1 ( ( )) b // Update the distribution, // Zt is the normalization factor END bt t t = -Î Î æ è ç ö ø ÷ 1 2 1 ln // calculate the weight of ht t i t i t y h x D D Z e t i t i + - × × = × 1 ( ( )) b // Update the distribution, // Zt is the normalization factor END // calculate the weight of ht t i t i y h x D D Z e t i t i + - × × = × 1 ( ( )) b // Update the distribution, t i t i t y h x D D Z e t i t i + - × × = × 1 ( ( )) b // Update the distribution, // Zt is the normalization factor Process: Compute distance ˆ (ˆ, ) x d x x = between z and every object (x, y) Î I. Compute distance ˆ (ˆ, ) x d x x = between z and every object (x, y) Î I. Select I I z Í , the set of k closest training objects to z. Select I I z Í , the set of k closest training objects to z. Output (Majority Class): ˆ arg ( ) ( , ) y max F v y v i x y I i i Z = = ∈ ∑ k-Nearest Neighbors The k-nearest neighbors (k-NN) classification methodology identifies a group of k objects in the training set that are closest to the test object and assigns a label based on the most dominant class in this neighborhood. The three fundamental elements of this approach are an existing set of labeled objects • a distance metric to estimate distance between objects • the number of nearest neighbors ( • k) Naive Bayes The naive Bayes model is surprisingly effective and immensely appealing, owing to its simplicity and The naive Bayes model is surprisingly effective and immensely appealing, owing to its simplicity and robustness. Because this algorithm does not require application of complex iterative parameter estimation schemes to large datasets, it is very useful and relatively easy to construct and use. It is a popular algorithm in areas related to text classification and spam filtering. Classification and Regression Trees A classification and regression tree (CART) is a nonparametric decision tree that uses a binary recursive partitioning scheme by splitting two child nodes repeatedly, starting with the root node, which contains the complete learning sample (Breiman et al. 1984). The tree-growing process involves splitting among all the possible splits at each node, such that the resulting child nodes are the “purest.” Once a CART has generated a “maximal tree,” it examines the smaller trees obtained by pruning away the branches of the maximal tree to determine which contribute least to the overall performance of the tree on training data. The CART mechanism is intended to yield a sequence of nested pruned trees. The right-sized, or “honest,” tree is identified by evaluating the predictive performance of every tree in the pruning sequence. Output (Majority Class): F(.) = 1 if argument (.) is TRUE and 0 otherwise, v is the class label. F(.) = 1 if argument (.) is TRUE and 0 otherwise, v is the class label. The value of k should be chosen carefully. A smaller value can result in noisy behavior, whereas a larger value may include too many points from other classes. The value of k should be chosen carefully. A smaller value may include too many points from other classes. 14 Chapter 1 ■ Machine Learning Naive Bayes Naive Bayes is a simple probabilistic classifier that applies Bayes’ theorem with strong (naive) assumption of independence, such that the presence of an individual feature of a class is unrelated to the presence of another feature. Assume that input features x x xn 1 2 ,  are conditionally independent of each other, given the class label Y, such that P x x x Y P x Y n i n i ( , \| ) ( \| ) 1 2 = =1P (1-9) (1-9) For a two-class classification (i = 0,1), we define P(i\|x) as the probability that measurement vector x x x xn = { , } 1 2 belongs to class i. Moreover, we define a classification score P x P x f x P f x P P P j n j j n j j n ( \| ) ( \| ) ( \| ) ( ) ( \| ) ( ) ( ) ( ) 1 0 1 1 0 0 1 0 1 1 1 = = = = Π Π Π f x f x j j ( \| ) ( \| ) 1 0 (1-10) P x P x f x P f x P P P j n j j n j j n ( \| ) ( \| ) ( \| ) ( ) ( \| ) ( ) ( ) ( ) 1 0 1 1 0 0 1 0 1 1 1 = = = = = Π Π Π f x f x j j ( \| ) ( \| ) 1 0 (1-10) ln ( \| ) ( \| ) ln ( ) ( ) ln ( \| ) ( \| ) , P x P x P P f x f x j n j j 1 0 1 0 1 0 1 = + =∑ (1-11) (1-10) ln ( \| ) ( \| ) ln ( ) ( ) ln ( \| ) ( \| ) , P x P x P P f x f x j n j j 1 0 1 0 1 0 1 = + =∑ (1-11) (1-11) where P(i\|x) is proportional to f(x\|i)P(i) and f (x\|i) is the conditional distribution of x for class i objects. where P(i\|x) is proportional to f(x\|i)P(i) and f (x\|i) is the conditional distribution of x for class i objects. Distributed Data Mining and Mining Multi-Agent Data In a distributed data sensing environment, it can be challenging to discover distributed patterns and correlate the data streamed through different probes. The goal is to minimize the amount of data exchange and reduce the required communication bandwidth. Game-theoretic methodologies may be deployed to tackle this challenge. Mining Sequence Data and Time Series Data Efficient classification, clustering, and forecasting of sequenced and time series data remain an open challenge today. Time series data are often contaminated by noise, which can have a detrimental effect on short-term and long-term prediction. Although noise may be filtered, using signal-processing techniques or smoothening methods, lags in the filtered data may result. In a closed-loop environment, this can reduce the accuracy of prediction, because we may end up overcompensating or underprovisioning the process itself. In certain cases, lags can be corrected by differential predictors, but these may require a great deal of tuning the model itself. Noise-canceling filters placed close to the data I/O block can be tuned to identify and clean the noisy data before they are mined. Scaling Up for High-Dimensional Data and High-Speed Data Streams Designing classifiers that can handle very high-dimensional features extracted through high-speed data streams is challenging. To ensure a decisive advantage, data mining in such cases should be a continuous and online process. But, technical challenges prevent us from computing models over large amounts streaming data in the presence of environment drift and concept drift. Today, we try to solve this problem with incremental mining and offline model updating to maintain accurate modeling of the current data stream. Information technology challenges are being addressed by developing in-memory databases, high-density memories, and large storage capacities, all supported by high-performance computing infrastructure. Mining Complex Knowledge from Complex Data Complex data can exist in many forms and may require special techniques to extract the information useful for making real-world decisions. For example, information may exist in a graphical form, requiring methods for discovering graphs and structured patterns in large data. Another complexity may exist in the form of non—independent-and-identically-distributed (non-iid) data objects that cannot be mined as an independent single object. They may share relational structures with other data objects that should be identified. State-of-the-art data mining methods for unstructured data lack the ability to incorporate domain information and knowledge interface for the purpose of relating the results of data mining to real-world scenarios. Challenging Problems in Data Mining Research Data mining and knowledge discovery have become fields of interdisciplinary research in the areas related to database systems, ML, intelligent information systems, expert systems, control theory, and many others. Data mining is an important and active area of research but not one without theoretical and practical challenges from working with very large databases that may be noisy, incomplete, redundant, and dynamic in nature. A study by Yang and Wu (2006) reviews the most challenging problems in data mining research, as summarized in the following sections. 15 15 Chapter 1 ■ Machine Learning Summary This chapter discussed the essentials of ML through key terminology, types of ML, and the top 10 data mining and ML algorithms. Owing to the explosion of data on the World Wide Web, ML has found widespread use in web search, advertising placement, credit scoring, stock market prediction, gene sequence analysis, behavior analysis, smart coupons, drug development, weather forecasting, big data analytics, and many more such applications. New uses for ML are being explored every day. Big data analytics and graph analytics have become essential components of cloud-based business development. The new field of data analytics and the applications of ML have also accelerated the development of specialized hardware and accelerators to improve algorithmic performance, big data storage, and data retrieval performance. ealing with Nonstatic, Unbalanced, and Cost-Sensitive Data Data is dynamic and changing continually in different domains. Historical trials in data sampling and model construction may be suboptimal. As you retrain a current model based on new training data, you may experience a learning drift, owing to different selection biases. Such biases need to be corrected dynamically for accurate prediction. Data Mining Process-Related Problems Autonomous data mining and cleaning operations can improve the efficiency of data mining dramatically. Although we can process models and discover patterns at a fast rate, major costs are incurred by preprocessing operations such as data integration and data cleaning. Reducing these costs through automation can deliver a much greater payoff than attempting to further reduce the cost of model-building and pattern-finding. 16 Chapter 1 ■ Machine Learning Security, Privacy, and Data Integrity Ensuring users’ privacy while their data are being mined is critical. Assurance of the knowledge integrity of collected input data and synthesized individual patterns is no less essential. References Agrawal, Rakesh, and Ramakrishnan Srikant. “Fast Algorithms for Mining Association Rules in Large Databases.” In Proceedings of the 20th International Conference on Very Large Data Bases (VLDB ’94), S t b 12 15 1994 S ti d Chil Chil dit d b J B B M tthi J k d C l Z i l Databases.” In Proceedings of the 20th International Conference on Very Large Data Bases (VLDB ’94), September 12–15, 1994, Santiago de Chile, Chile, edited by Jorge B. Bocca, Matthias Jarke, and Carlo Zaniolo San Francisco: Morgan Kaufmann (1994): 487–499. g f f y g September 12–15, 1994, Santiago de Chile, Chile, edited by Jorge B. Bocca, Matthias Jarke, and Carlo Zaniolo. San Francisco: Morgan Kaufmann (1994): 487–499. Breiman, Leo, Jerome H. Friedman, Richard A. Olshen, and Charles J. Stone. Classification and Regression Trees. Belmont, CA: Wadsworth, 1984. Carpenter, Gail A., and Stephen Grossberg. Pattern Recognition by Self-Organizing Neural Networks. Massachusetts: Cambridge, MA: Massachusetts Institute of Technology Press, 1991. Freund, Yoav, and Robert E. Schapire. “A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting.” Journal of Computer and System Sciences 55, no. 1 (1997): 119–139. Han, Jiawel, Jian Pei, and Yiwen Yin. “Mining Frequent Patterns without Candidate Generation.” In SIGMOD/PODS ’00: ACM international Conference on Management of Data and Symposium on Principles of Database Systems, Dallas, TX, USA, May 15–18, 2000, edited by Weidong Chen, Jeffrey Naughton, Philip A. Bernstein. New York: ACM (2000): 1–12. Jang, J.-S. R. “ANFIS: Adaptive-Network-Based Fuzzy Inference System.” IEEE Transactions on Systems, Man and Cybernetics 23, no. 3 (1993): 665–685. Kohavi, Ron, and Foster Provost. “Glossary of Terms.” Machine Learning 30, no. 2–3 (1998): 271–274. 17 Chapter 1 ■ Machine Learning Lloyd, Stuart P. “Least Squares Quantization in PCM,” in special issue on quantization, IEEE Transactions on Information Theory, IT-28, no. 2(1982): 129–137. Samuel, Arthur L. “Some Studies in Machine Learning Using the Game of Checkers,” IBM Journal of Research and Development 44:1.2 (1959): 210–229. Turing, Alan M. “Computing machinery and intelligence.” Mind (1950): 433–460. Vapnik, Vladimir N. Statistical Learning Theory. New York: Wiley, 1998. Vapnik, Vladimir N. Statistical Learning Theory. New York: Wiley, 1998. Wu, Xindong, Vipin Kumar, Ross Quinlan, Joydeep Ghosh, Qiang Yang, Hiroshi Motoda, Geoffrey J. McLachlan, Angus Ng, Bing Liu, Philip S. Yu, Zhi-Hua Zhou, Michael Steinbach, David J. Hand, and Dan Steinberg. “Top 10 Algorithms in Data Mining.” Knowledge and Information Systems 14 (2008): 1–37. References Yang, Qiang, and Xindong Wu. “10 Challenging Problems in Data Mining Research.” International Journal of Information Technology and Decision Making 5, no. 4 (2006): 597–604. 18 Machine Learning and Knowledge Discovery When you know a thing, to hold that you know it; and when you do not know a thing, to allow that you do not know it—this is knowledge. —Confucius, The Analects —Confucius, The Analects The field of data mining has made significant advances in recent years. Because of its ability to solve complex problems, data mining has been applied in diverse fields related to engineering, biological science, social media, medicine, and business intelligence. The primary objective for most of the applications is to characterize patterns in a complex stream of data. These patterns are then coupled with knowledge discovery and decision making. In the Internet age, information gathering and dynamic analysis of spatiotemporal data are key to innovation and developing better products and processes. When datasets are large and complex, it becomes difficult to process and analyze patterns using traditional statistical methods. Big data are data collected in volumes so large, and forms so complex and unstructured, that they cannot be handled using standard database management systems, such as DBMS and RDBMS. The emerging challenges associated with big data include dealing not only with increased volume, but also the wide variety and complexity of the data streams that need to be extracted, transformed, analyzed, stored, and visualized. Big data analysis uses inferential statistics to draw conclusions related to dependencies, behaviors, and predictions from large sets of data with low information density that are subject to random variations. Such systems are expected to model knowledge discovery in a format that produces reasonable answers when applied across a wide range of situations. The characteristics of big data are as follows: • Volume: A great quantity of data is generated. Detecting relevance and value within this large volume is challenging. • Variety: The range of data types and sources is wide. • Velocity: The speed of data generation is fast. Reacting in a timely manner can be demanding. • Variability: Data flows can be highly inconsistent and difficult to manage, owing to seasonal and event-driven peaks. • Complexity: The data need to be linked, connected, and correlated to infer nonlinear relationships and causal effects. 19 19 Chapter 2 ■ Machine Learning and Knowledge Discovery Chapter 2 ■ Machine Learning and Knowledge Discovery Modern technological advancements have enabled the industry to make inroads into big data and big data analytics. Affordable open source software infrastructure, faster processors, cheaper storage, virtualization, high throughput connectivity, and development of unstructured data management tools, in conjunction with cloud computing, have opened the door to high-quality information retrieval and faster analytics, enabling businesses to reduce costs and time required to develop newer products with customized offerings. Big data and powerful analytics can be integrated to deliver valuable services, such as these • Failure root cause detection: The cost of unplanned shutdowns resulting from unexpected failures can run into billions of dollars. Root cause analysis (RCA) identifies the factors determinative of the location, magnitude, timing, and nature of past failures and learns to associate actions, conditions, and behaviors that can prevent the recurrence of such failures. RCA transforms a reactive approach to failure mitigation into a proactive approach of solving problems before they occur and avoids unnecessary escalation. • Dynamic coupon system: A dynamic coupon system allows discount coupons to be delivered in a very selective manner, corresponding to factors that maximize the strategic benefits to the product or service provider. Factors that regulate the delivery of the coupon to selected recipients are modeled on existing locality, assessed interest in a specific product, historical spending patterns, dynamic pricing, chronological visits to shopping locations, product browsing patterns, and redemption of past coupons. Each of these factors is weighted and reanalyzed as a function of competitive pressures, transforming behaviors, seasonal effects, external factors, and dynamics of product maturity. A coupon is delivered in real time, according to the recipient’s profile, context, and location. The speed, precision, and accuracy of coupon delivery to large numbers of mobile recipients are important considerations. Shopping behavior analysis: A manufacturer of a product is particularly interested in the understanding the heat-map patterns of its competitors’ products on the store floor. For example, a manufacturer of large-screen TVs would want to ascertain buyers’ interest in features offered by other TV manufacturers. This can only be analyzed by evaluating potential buyers’ movements and time spent in proximity to the competitors’ products on the floor. Such reports can be delivered to the manufacturer on an individual basis, in real time, or collectively, at regular intervals. Chapter 2 ■ Machine Learning and Knowledge Discovery 20 Chapter 2 ■ Machine Learning and Knowledge Discovery Workload resource tuning and selection in datacenter: In a cloud service management environment, service-level agreements (SLAs) define the expectation of quality of service (QoS) for managing performance loss in a given service-hosting environment composed of a pool of computing resources. Typically, the complexity of resource interdependencies in a server system results in suboptimal behavior, leading to performance loss. A well-behaved model can anticipate demand patterns and proactively react to dynamic stresses in a timely and optimized manner. Dynamic characterization methods can synthesize a self-correcting workload fingerprint codebook that facilitates phase prediction to achieve continuous tuning through proactive workload allocation and load balancing. In other words, the codebook characterizes certain features, which are continually reevaluated to remodel workload behavior to accommodate deviation from an anticipated output. It is possible, however, that the most current model in the codebook may not have been subjected to newer or unidentified patterns. A new workload is hosted on a compute node (among thousands of potential nodes) in a manner that not only reduces the thermal hot spots, but also improves performance by lowering the resource bottleneck. The velocity of the analysis that results in optimal hosting of the workload in real time is critical to the success of workload load allocation and balancing. Knowledge Discovery Knowledge extraction gathers information from structured and unstructured sources to construct a knowledge database for identifying meaningful and useful patterns from underlying large and semantically fuzzy datasets. Fuzzy datasets are sets whose elements have a degree of membership. Degree of membership is defined by a membership function that is valued between 0 and 1. The extracted knowledge is reused, in conjunction with source data, to produce an enumeration of patterns that are added back to the knowledge base. The process of knowledge discovery involves programmatic exploration of large volumes of data for patterns that can be enumerated as knowledge. The knowledge acquired is presented as models to which specific queries can be made, as necessary. Knowledge discovery joins the concepts of computer science and machine learning (such as databases and algorithms) with those of statistics to solve user-oriented queries and issues. Knowledge can be described in different forms, such as classes of actors, attribute association models, and dependencies. Knowledge discovery in big data uses core machine algorithms that are designed for classification, clustering, dimensionality reduction, and collaborative filtering as well as scalable distributed systems. This chapter discusses the classes of machine learning algorithms that are useful when the dataset to be processed is very large for a single machine. Chapter 2 ■ Machine Learning and Knowledge Discovery The reports may prompt manufacturers to deliver dynamic coupons to influence potential buyers who are still in the decision-making stage as well as help the manufacturer improve, remove, retain, or augment features, as gauged by buyers’ interest in the competitors’ products. Shopping behavior analysis: A manufacturer of a product is particularly interested in the understanding the heat-map patterns of its competitors’ products on the store floor. For example, a manufacturer of large-screen TVs would want to ascertain buyers’ interest in features offered by other TV manufacturers. This can only be analyzed by evaluating potential buyers’ movements and time spent in proximity to the competitors’ products on the floor. Such reports can be delivered to the manufacturer on an individual basis, in real time, or collectively, at regular intervals. The reports may prompt manufacturers to deliver dynamic coupons to influence potential buyers who are still in the decision-making stage as well as help the manufacturer improve, remove, retain, or augment features, as gauged by buyers’ interest in the competitors’ products. Detecting fraudulent behavior: Various types of fraud related to insurance, health care, credit cards, and identity theft cost consumers and businesses billions of dollars. Big data and smart analytics have paved the way for developing real-time solutions for identifying fraud and preventing it before it occurs. Smart analytics generate models that validate the patterns related to spending behavior, geolocation, peak activity, and insurance claims. If a pattern cannot be validated, a corrective, preventive, or punitive action is initiated. The accuracy, precision, and velocity of such actions are critical to the success of isolating the fraudulent behavior. For instance, each transaction may evaluate up to 500 attributes, using one or more models in real time. Detecting fraudulent behavior: Various types of fraud related to insurance, health care, credit cards, and identity theft cost consumers and businesses billions of dollars. Big data and smart analytics have paved the way for developing real-time solutions for identifying fraud and preventing it before it occurs. Smart analytics generate models that validate the patterns related to spending behavior, geolocation, peak activity, and insurance claims. If a pattern cannot be validated, a corrective, preventive, or punitive action is initiated. The accuracy, precision, and velocity of such actions are critical to the success of isolating the fraudulent behavior. For instance, each transaction may evaluate up to 500 attributes, using one or more models in real time. Collaborative Filtering Collaborative filtering (CF) is the process of filtering for information or patterns, using collaborative methods between multiple data sources. CF explores an area of interest by gathering preferences from many users with similar interests and making recommendations based on those preferences. CF algorithms are expected to make satisfactory recommendations in a short period of time, despite very sparse data, increasing numbers of users and items, synonymy, data noise, and privacy issues. Machine learning performs predictive analysis, based on established properties learned from the training data (models). Machine learning assists in exploring useful knowledge or previously unknown knowledge by matching new information with historical information that exists in the form of patterns. These patterns are used to filter out new information or patterns. Once this new information is validated against a set of linked behavioral patterns, it is integrated into the existing knowledge database. The new information may also correct existing models by acting as additional training data. The following sections look at various machine learning algorithms employed in knowledge discovery, in relation to clustering, classification, dimensionality reduction, and collaborative filtering. Clustering Clustering is a process of knowledge discovery that groups items from a given collection, based on similar attributes (or characteristics). Members of the same cluster share similar characteristics, relative to those belonging to different clusters. Generally, clustering involves an iterative algorithm of trial and error that operates on an assumption of similarity (or dissimilarity) and that stops when a termination criterion is satisfied. The challenge is to find a function that measures the degree of similarity between two items (or data points) as a numerical value. The parameters for clustering—such as the clustering algorithm, the distance function, the density threshold, and the number of clusters—depend on the applications and the individual dataset. Chapter 2 ■ Machine Learning and Knowledge Discovery Chapter 2 ■ Machine Learning and Knowledge Discovery Dimensionality Reduction Dimensionality reduction is the process of reducing random variables through feature selection and feature extraction. Dimensionality reduction allows shorter training times and enhanced generalization and reduces overfitting. Feature selection is the process of synthesizing a subset of the original variables for model construction by eliminating redundant or irrelevant features. Feature extraction, in contrast, is the process of transforming the high-dimensional space to a space of fewer dimensions by combining attributes. Classification Classification is central to developing predictive analytics capable of replicating human decision making. Classification algorithms work well for problems with well-defined boundaries in which inputs follow a specific set of attributes and in which the output is categorical. Generally, the classification process develops an archive of experiences entailing evaluation of new inputs by matching them with previously observed patterns. If a pattern can be matched, the input is associated with the predefined predictive behavioral pattern. If a pattern cannot be matched, it is quarantined for further evaluation to determine if it is an undiscovered valid pattern or an unusual pattern. Machine-based classification algorithms follow supervised-learning techniques, in which algorithms learn through examples (also called training sets) of accurate decision making, using carefully prepared inputs. The two main steps involved in classification are synthesizing a model, using a learning algorithm, and employing the model to categorize new data. 21 Machine Learning: Classification Algorithms Logistic Regression Logistic regression is a probabilistic statistical classification model that predicts the probability of the occurrence of an event. Logistic regression models the relationship between a categorical dependent variable X and a dichotomous categorical outcome or feature Y. The logistic function can be expressed as P Y X e e X X ( \| ) . = + + + b b b b 0 1 0 1 1 (2-1) 22 Chapter 2 ■ Machine Learning and Knowledge Discovery The logistic function may be rewritten and transformed as the inverse of the logistic function—called logit or log-odds—which is the key to generating the coefficients of the logistic regression, logit P ( ( \| )) ln ( \| ) ( \| ) . Y X P Y X P Y X X = - æ è ç ö ø ÷ = + 1 0 1 b b (2-2) (2-2) As depicted in Figure 2-1, the logistic function can receive a range of input values (b0 + b1X) between negative infinity and positive infinity, and the output (P(Y \|X) is constrained to values between 0 and 1. As depicted in Figure 2-1, the logistic function can receive a range of input values (b0 + b1X) between negative infinity and positive infinity, and the output (P(Y \|X) is constrained to values between 0 and 1. Figure 2-1. The logistic function Figure 2-1. The logistic function The logit transform of P(Y \|X) provides a dynamic range for linear regression and can be converted back into odds. The logistic regression method fits a regression curve, using the regression coefficients b0 and b1, as shown in Equation 2-1, where the output response is a binary (dichotomous) variable, and X is numerical. Because the logistic function curve is nonlinear, the logit transform (see Equation 2-2) is used to perform linear regression, in which P(Y \|X) is the probability of success (Y) for a given value of X. Using the generalized linear model, an estimated logistic regression equation can be formulated as logit( ( \| , , )) . 3. At each node of the tree: 3. At each node of the tree: – m predictor variables (or subset of features) are selected at random from all the predictor variables (random subspace). – The predictor variable that provides the best split performs the binary split on that node. – The next node randomly selects another set of m variables from all predictor variables and performs the preceding step. 4. Given a new dataset to be classified, take the majority vote of all the B subtrees. By averaging across the ensemble of trees, you can reduce the variance of the final estimation. Random forest offers good accuracy and runs efficiently on large datasets. It is an effective method for estimating missing data and maintains accuracy, even if a large portion of the data is missing. Additionally, random forest can estimate the relative importance of a variable for classification. Chapter 2 ■ Machine Learning and Knowledge Discovery Chapter 2 ■ Machine Learning and Knowledge Discovery Machine Learning: Classification Algorithms Logistic Regression P Y X X X X X n k k k n = = + =å 1 1 2 3 0 1  b b (2-3) (2-3) The coefficients b0 and bk (k = 1, 2, ..., n) are estimated, using maximum likelihood estimation (MLE) to model the probability that the dependent variable Y will take on a value of 1 for given values of Xk (k = 1, 2, ..., n). Logistic regression is widely used in areas in which the outcome is presented in a binary format. For example, to predict blood cholesterol based on body mass index (BMI), you would use linear regression, because the outcome is continuous. If you needed to predict the odds of being diabetic based on BMI, you would use logistic regression, because the outcome is binary. 23 23 Random Forest Random forest (Breiman 2001) is an ensemble learning approach for classification, in which “weak learners” collaborate to form “strong learners,” using a large collection of decorrelated decision trees (the random forest). Instead of developing a solution based on the output of a single deep tree, however, random forest aggregates the output from a number of shallow trees, forming an additional layer to bagging. Bagging constructs n predictors, using independent successive trees, by bootstrapping samples of the dataset. The n predictors are combined to solve a classification or estimation problem through averaging. Although individual classifiers are weak learners, all the classifiers combined form a strong learner. Whereas single decision trees experience high variance and high bias, random forest averages multiple decision trees to improve estimation performance. A decision tree, in ensemble terms, represents a weak classifier. The term forest denotes the use of a number of decision trees to make a classification decision. The random forest algorithm can be summarized as follows: 1. To construct B trees, select n bootstrap samples from the original dataset. 2. For each bootstrap sample, grow a classification or regression tree. Markov chain property: • P P ( \| , , , ) ( \| ) q S q S q S q S q S q S t j t i t k t j t i + - + = = = = = = = 1 1 0 0 1  Hidden Markov Model Attributes of an HMM Figure 2-2. Attributes of an HMM The three fundamental problems addressed by HMMs can be summarized as follows: • Model evaluation: Evaluate the likelihood of a sequence of observations for a given HMM (M = (A,B,p)). • Path decoding: Evaluate the optimal sequence of model states (Q) (hidden states) for a given sequence of observations and HMM model M = (A,B,p). • Model training: Determine the set of model parameters that best accounts for the observed signal. HMMs are especially known for their application in temporal pattern recognition, such as speech, handwriting, gesture recognition, part-of-speech tagging, musical score following, partial discharges, and bioinformatics. For further details on the HMM, see Chapter 5. HMMs are especially known for their application in temporal pattern recognition, such as speech, handwriting, gesture recognition, part-of-speech tagging, musical score following, partial discharges, and bioinformatics. For further details on the HMM, see Chapter 5. Hidden Markov Model A hidden Markov model (HMM) is a doubly stochastic process, in which the system being modeled is a Markov process with unobserved (hidden) states. Although the underlying stochastic process is hidden and not directly observable, it can be seen through another set of stochastic processes that produces the sequence of observed symbols. In traditional Markov models, states are visible to an observer, and state transitions are parameterized, using transition probabilities. Each state has a probability distribution over output emissions (observed variables). HMM-based approaches correlate the system observations and state transitions to predict the most probable state sequence. The states of the HMM can only be inferred from the observed emissions—hence, the use of the term hidden. The sequence of output emissions generated by an HMM is used to estimate the sequence of states. HMMs are generative models, in which the joint distribution of observations and hidden states is modeled. Hidden Markov Model To define a hidden Markov model, the following attributes have to be specified (see Figure 2-2): Set of states: { • S1,S2...,Sn} Sequence of states: • Q = q1,q2,...,qt Markov chain property: • P P ( \| , , , ) ( \| ) q S q S q S q S q S q S t j t i t k t j t i + - + = = = = = = = 1 1 0 0 1  Markov chain property: • P P ( \| , , , ) ( \| ) q S q S q S q S q S q S t j t i t k t j t i + - + = = = = = = = 1 1 0 0 1  Markov chain property: • P P ( \| , , , ) ( \| ) q S q S q S q S q S q S t j t i t k t j t i + - + = = = = = = = 1 1 0 0 1  24 Chapter 2 ■ Machine Learning and Knowledge Discovery Set of observations: • O = {o1,o2,o3,...,oM} Transition probability matrix: • P = { }, ( \| ) p p q S q S ij ij t j t i = = = + P 1 Emission probability matrix: • B = = = = { ( )}, ( ) ( \| ) b k b k x o q S j j t k t j P Initial probability matrix: • p p p = = = { }, ( ) i i i q S P 1 HMM: • M = (A,B,p) Set of observations: • O = {o1,o2,o3,...,oM} Transition probability matrix: • P = { }, ( \| ) p p q S q S ij ij t j t i = = = + P 1 Emission probability matrix: • B = = = = { ( )}, ( ) ( \| ) b k b k x o q S j j t k t j P Initial probability matrix: • p p p = = = { }, ( ) i i i q S P 1 HMM: • M = (A,B,p) Set of observations: • O = {o1,o2,o3,...,oM} Transition probability matrix: • P = { }, ( \| ) p p q S q S ij ij t j t i = = = + P 1 Emission probability matrix: • B = = = = { ( )}, ( ) ( \| ) b k b k x o q S j j t k t j P Initial probability matrix: • p p p = = = { }, ( ) i i i q S P 1 HMM M (A B ) Figure 2 2 Attributes of an HMM Figure 2-2. Multilayer Perceptron A multilayer perceptron (MLP) is a feedforward network of simple neurons that maps sets of input data onto a set of outputs. An MLP comprises multiple layers of nodes fully connected by directed graph, in which each node (except input nodes) is a neuron with a nonlinear activation function. The fundamental component of an MLP is the neuron. In an MLP a pair of neurons is connected in two adjacent layers, using weighted edges. As illustrated in Figure 2-3, an MLP comprises at least three layers of neurons, including one input layer, one or more hidden layers, and one output layer. The number of input 25 Chapter 2 ■ Machine Learning and Knowledge Discovery neurons depends on the dimensions of the input features; the number of output neurons is determined by the number of classes. The number of hidden layers and the number of neurons in each hidden layer depend on the type of problem being solved. Fewer neurons result in inefficient learning; a larger number of neurons results in inefficient generalization. An MLP uses a supervised-learning technique called backpropagation for training the network. In its simple instantiation the perceptron computes an output y by processing a linear combination of weighted real-valued inputs through a nonlinear activation function,   neurons depends on the dimensions of the input features; the number of output neurons is determined by the number of classes. The number of hidden layers and the number of neurons in each hidden layer depend on the type of problem being solved. Fewer neurons result in inefficient learning; a larger number of neurons results in inefficient generalization. An MLP uses a supervised-learning technique called backpropagation for training the network. In its simple instantiation the perceptron computes an output y by processing a linear combination of weighted real-valued inputs through a nonlinear activation function, y w x b i i i n = +     =∑ j 1 , (2-4) y w x b i i i n = +     =∑ j 1 , (2-4) where w represents the weights vector, x is the input vector, b is the bias, and j is the activation function. Generally, MLP systems choose the logistic sigmoid function 1/(1+e–x) or the hyperbolic tangent tanh(x) as the activation functions. 5. Repeat step 2. 5. Repeat step 2. To influence the convergence rate and thereby reduce the step sizes at which weights undergo an adaptive change, a learning parameter h (< 1) is used. The i-th weight connected to j-th output can be updated by the following rule: w t w t E O t ij ij j ( ) ( ) ( ( )). + - = 1 h (2-6) (2-6) Equation 2-6 represents an iterative weight adaptation, in which a fraction of output error at iteration (t + 1) is added to the existing weight from iteration t. Equation 2-6 represents an iterative weight adaptation, in which a fraction of output error at iteration (t + 1) is added to the existing weight from iteration t. MLPs are commonly used for supervised-learning pattern recognition processes. There is renewed interest in MLP backpropagation networks, owing to the successes of deep learning. Deep learning is an approach for effectively training an MLP, using multiple hidden layers. With modern advancements in silicon technology, deep learning is being developed to unlock the enormous big data analytics potential in areas in which highly varying functions can be represented by deep architecture. 4. For each node n in the output layer: 4. For each node n in the output layer: a. Calculate the error on output node n: E(On(t))=Tn–On(t). b. Add E(On(t)) to all the weights that connect to node n. b. Add E(On(t)) to all the weights that connect to node n. b. Add E(On(t)) to all the weights that connect to node n. 5. Repeat step 2. Multilayer Perceptron These functions offer statistical convenience, because they are linear near the origin and saturate quickly when moved away from the origin. Figure 2-3. The MLP is fed the input features to the input layer and gets the result from the output layer; the results are calculated in a feedforward approach from the input layer to the output layer Figure 2-3. The MLP is fed the input features to the input layer and gets the result from the output layer; the results are calculated in a feedforward approach from the input layer to the output layer The MLP learning process adjusts the weights of the hidden layer, such that the output error is reduced. Starting with the random weights, MLP feeds forward the input pattern signals through the network and backpropagates the error signal, starting at the output. The backpropagating error signal is made up of of the difference between actual (On(t)) and desired (Tn) values. Error function may be summarized as E O t T O t n n n ( ( )) ( ). = - (2-5) E O t T O t n n n ( ( )) ( ). = - (2-5) The goal of the learning process is to minimize the error function. To find the minimum value of the error function, differentiate it, with respect to the weight matrix. The learning algorithm comprises the following steps: 1. Initialize random weights within the interval [1, –1]. 2. Send an input pattern to the network. 26 Chapter 2 ■ Machine Learning and Knowledge Discovery 3. Calculate the output of the network. 3. Calculate the output of the network. 3. Calculate the output of the network. Machine Learning: Clustering Algorithms k-Means Clustering k-means clustering is an unsupervised-learning algorithm of vector quantization that partitions n observations into k clusters. The algorithm defines k centroids, which act as prototypes for their respective clusters. Each object is assigned to a cluster with the nearest centroid when measured with a specific distance metric. The step of assigning objects to clusters is complete when all the objects have been applied to one of the k clusters. The process is repeated by recalculating centroids, based on previous S = {S1,S1,...,Sk} allocations, and reassigning objects to the nearest new centroids. The process continues until there is no movement of centroids of any k cluster. Generally, a k-means clustering algorithm classifies objects according to their features into k groups (or clusters) by minimizing the sum of squares of the distances between the object data and the cluster centroid. For a given set of d-dimensional observations vectors (x1,x2,...,xn), k-means clustering partitions n observations into k(£n) cluster sets so as to minimize the sum of squares, argmin \|\| \|\| , S x -mmi S i k i 2 1 xÎ = å å (2-7) (2-7) where mi is the mean of the points in Si. where mi is the mean of the points in Si. i i The k-means clustering algorithm is easy to implement on large datasets. It has found many uses in areas such as market segmentation, computer vision, profiling applications and workloads, optical character recognition, and speech synthesis. The algorithm is often used as the preprocessing step for other algorithms in order to find the initial configuration. 27 27 Chapter 2 ■ Machine Learning and Knowledge Discovery Fuzzy k-Means (Fuzzy c-Means) Fuzzy k-means (also called fuzzy c-means [FCM]) (Dunn 1973; Bezdek 1981) is an extension of the k-means algorithm that synthesizes soft clusters, in which an object can belong to more than one cluster with a certain probability. This algorithm provides increased flexibility in assigning data objects to clusters and allowing the data objects to maintain partial membership in multiple neighboring clusters. FCM uses the fuzzification parameter m in range [1, n], which determines the degree of fuzziness in the clusters. Whereas m = 1 signifies crisp clustering, m > 1 suggests a higher degree of fuzziness among data objects in decision space. The FCM algorithm is based on minimization of the objective function J w x c x m k m j j C x = − =∑ ∑ ( ) \|\| \|\| , 2 1 (2-8) (2-8) where x is the d-dimensional data object, cj is the d-dimensional centroid of the cluster j (see Equation 2-10), and wk(x) is the degree of membership of x in the cluster k dependent on the fuzzification parameter m, which controls the weighting accorded the closest centroid: where x is the d-dimensional data object, cj is the d-dimensional centroid of the cluster j (see Equation 2-10), and wk(x) is the degree of membership of x in the cluster k dependent on the fuzzification parameter m, which controls the weighting accorded the closest centroid: w x c x c x k k j m j C ( ) \|\| \|\| \|\| \|\| . /( ) = - - æ è çç ö ø ÷÷ - =å 1 2 1 1 (2-9) (2-9) With FCM the d-dimensional centroid of a kth cluster (ck) is the mean of all points, weighted by their degree of membership to that cluster: c w x x w x k k m x k m x = å å ( ) ( ) . (2-10) (2-10) The c-means clustering algorithm synthesizes cluster centers and the degree to which data objects are assigned to them. This does not translate into hard membership functions. FCM is used in image processing for clustering objects in an image. Streaming k-Means Streaming k-means is a two-step algorithm, consisting of a streaming step and a ball k-means step. A streaming step traverses the data objects of size n in one pass and generates an optimal number of centroids—which amounts to k log(n) clusters, where k is expected number of clusters. The attributes of these clusters are passed on to the ball k-means step, which reduces the number of clusters to k. Streaming Step A streaming-step algorithm steps through the data objects one at a time and makes a decision to either add the data object to an existing cluster or create a new one. If the distance between the centroid of the cluster and a data point is smaller than the distance cutoff threshold, the algorithm adds the data to an existing cluster or creates a new cluster with a probability of d/(distancecutoff). If the distance exceeds the cutoff, the algorithm creates a new cluster with a new centroid. As more data objects are processed, the centroids of the existing clusters may change their position. This process continues to add new clusters until the number of existing clusters reaches a cluster cutoff limit. The number of clusters can be reduced by increasing the distance cutoff threshold. This step is mainly used for dimensionality reduction. The output of this step is a reduced dataset in the form of multiple clusters that are proxies for a large amount of the original data. 28 Chapter 2 ■ Machine Learning and Knowledge Discovery Machine Learning: Dimensionality Reduction Machine learning works through a large number of features to train most regression or classification problems. This compounds the complexity, raises the computational requirement, and increases the time needed to converge to a solution. A useful approach for mitigating these problems is to reduce the dimensional space of the original features by synthesizing a lower-dimensional space. In this new, lower-dimensional space the most important features are retained, hidden correlations between features are exposed, and unimportant features are discarded. One of the simplest, most straightforward, and least supervised feature-reduction approaches involves variants of matrix decomposition: singular value decomposition, eigen decomposition, and nonnegative matrix factorization. The following sections consider some of the methods commonly used in statistical dimensionality reduction. Ball K-Means Step For each ˆci, create a ball of radius ˆ\|\| ˆ ˆ \|\|/ c c c 1 2 3 - around it. 6. Recompute the new centroids c c 1 2 , by using the elements of X contained within the ball. 6. Recompute the new centroids c c 1 2 , by using the elements of X contained within the ball. This algorithm is particularly useful in applications with a large number of data objects. The algorithm reduces the dimensionality of the original dataset by employing the streaming operation and replacing that data with a reduced proxy data composed of k·log(n) centroids of the original data. The reduced data act as input to the ball k-means algorithm, which synthesizes and refines k centroids for their respective clusters. Ball K-Means Step A ball k-means algorithm consumes the output of a streaming step (X = set of centroids > k) and performs multiple independent runs to synthesize k clusters by selecting the best solution. Each run selects k centroids, using a seeding mechanism, and runs the ball k-means algorithm iteratively to refine the solution. The seeding process may invoke the k-means++ algorithm for optimal spreading of k clusters. The k-means++ seeding algorithm is summarized as follows: A ball k-means algorithm consumes the output of a streaming step (X = set of centroids > k) and performs multiple independent runs to synthesize k clusters by selecting the best solution. Each run selects k centroids, using a seeding mechanism, and runs the ball k-means algorithm iteratively to refine the solution. g g g y The seeding process may invoke the k-means++ algorithm for optimal spreading of k clusters. The k-means++ seeding algorithm is summarized as follows: 1. Choose center c1 uniformly at random from X. 1. Choose center c1 uniformly at random from X. 2. Select a new center ci by choosing xÎX with probability, P(x), and add it to X , 2. Select a new center ci by choosing xÎX with probability, P(x), and add it to X , P x D x D i i X ( ) ( ) ( ) , = Îå 2 2 P x D x D i i X ( ) ( ) ( ) , = Îå 2 2 where D(x) is the distance between x and the nearest center that has already been chosen. 3. Repeat step 2 until k centers c c c X k 1 2 , , ,  ∈ are selected. 3. Repeat step 2 until k centers c c c X k 1 2 , , ,  ∈ are selected. 4. Randomly pick two centers ˆ ,ˆ c c X 1 2 ∈ with probability proportional to ˆ \|\| ˆ ˆ \|\| cnorm c c 1 2 2 − . 4. Randomly pick two centers ˆ ,ˆ c c X 1 2 ∈ with probability proportional to ˆ \|\| ˆ ˆ \|\| cnorm c c 1 2 2 − . 5. For each ˆci, create a ball of radius ˆ\|\| ˆ ˆ \|\|/ c c c 1 2 3 - around it. 5. Chapter 2 ■ Machine Learning and Knowledge Discovery Chapter 2 ■ Machine Learning and Knowledge Discovery Once you identify the points with distinct variations, you can approximate original data points with fewer dimensions. You can define thresholds below which variations can be ignored, thereby leading to a highly reduced dataset without degradation of the information related to inherent relationships and interests within data points. If M is an m × n matrix , then you can break it down into the product of three matrices U, ∑, and V T with the following characteristics: • U is a column-orthogonal matrix. The columns of U are orthonormal eigenvectors of MM T. • V T is a transpose of orthogonal matrix V. The columns of V are orthonormal eigenvectors of M TM. ∑ is a diagonal matrix, where all elements except diagonal are 0. ∑ contains square • roots of eigenvalues from U or V, in descending order. In its exact form, M can be rewritten as In its exact form, M can be rewritten as M U V T = å . (2-11) (2-11) M U V T = å . In the process of dimensionality reduction, you synthesize U and V, such that they contain elements accounted for in the original data, in descending order of variation. You may delete elements representing dimensions that do not exhibit meaningful variation. This can be done by setting the smallest eigenvalue to 0. Equation 2-11 can be rewritten in its best rank-l approximate form as ˆ , , , M u v i i i T i l l = × × ³ ³ å l l l l 1 2  (2-12) ˆ , , , M u v i i i T i l l = × × ³ ³ å l l l l 1 2  (2-12) where ui and vi are the ith columns of U and V, respectively, and li is the ith element of the diagonal matrix ∑. Singular Value Decomposition Singular value decomposition (SVD) performs matrix analysis to synthesize low-dimensional representation of a high-dimensional matrix. SVD assists in eliminating less important parts of matrix representation, leading to approximate representation with the desired number of dimensions. This helps in creating a smaller representation of a matrix that closely resembles the original. SVD is useful in dimensionality reduction, owing to the following characteristics: SVD transforms correlated variables into a set of uncorrelated ones that exposes • corresponding relationships between the data items. SVD identifies dimensions along which data points exhibit the most variation. • 29 29 Principal Component Analysis When you have a swarm of points in space, the coordinates and axes you use to represent such points are arbitrary. The points have certain variances, relative to the direction of axes chosen, indicating the spread around the mean value in that direction. In a two-dimensional system the model is constrained by the perpendicularity of the second axis to the first axis. But, in three-dimensional cases and higher, you can position the nth axis perpendicular to the plane constructed by any two axes. The model is constrained by the position of the first axis, which is positioned in the direction with the highest variance. This results in a new feature space that compresses the swarm of points into the axes of high variance. You may select the axes with higher variances and eliminate the axes with lower variances. Figure 2-4 illustrates the new feature space, reduced from a dataset with 160 featuresto 59 components (axes). Each component is associated with a certain percentage of variance, relative to other components. The first component has the highest variance, followed by second component, and so on. 30 Chapter 2 ■ Machine Learning and Knowledge Discovery Chapter 2 ■ Machine Learning and Knowledge Discovery Figure 2-4. The percentage of variance of a principal component transform of a dataset with 160 features reduced to 59 components Figure 2-4. The percentage of variance of a principal component transform of a dataset with 160 features reduced to 59 components Principal component analysis (PCA) is a widely used analytic technique that identifies patterns to reduce the dimensions of the dataset without significant loss of information. The goal of PCA is to project a high-dimensional feature space into a smaller subset to decrease computational cost. PCA computes new features, called principal components (PCs), which are uncorrelated linear combinations of the original features projected in the direction of greater variability. The key is to map the set of features into a matrix M and synthesize the eigenvalues and eigenvectors for MM T or M TM. Eigenvectors facilitate simpler solutions to problems that can be modeled using linear transformations along axes by stretching, compressing, or flipping. Eigenvalues provide a factor (length and magnitude of eigenvectors) whereby such transformation occurs. Eigenvectors with larger eigenvalues are selected in the new feature space because they enclose more information than eigenvectors with lower eigenvalues for a data distribution. The first PC has the greatest possible variance (i.e., the largest eigenvalues) compared with the next PC (uncorrelated, relative to the first PC), which is computed under the constraint of being orthogonal to the first component. Essentially, the ith PC is the linear combination of the maximum variance that is uncorrelated with all previous PCs. PCA comprises the following steps: PCA comprises the following steps: 1. Compute the d-dimensional mean of the original dataset. 2. Compute the covariance matrix of the features. 3. Compute the eigenvectors and eigenvalues of the covariance matrix. 4. Sort the eigenvectors by decreasing eigenvalue. 5. Choose k eigenvectors with the largest eigenvalues. Lanczos Algorithm The Lanczos algorithm is a low-cost eigen-decomposition technique identical to truncated SVD, except that it does not explicitly compute singular values/vectors of the matrix. The Lanczos algorithm uses a small number of Lanczos vectors that are eigenvectors of M TM or MM T, where M is a symmetrical n × n matrix. Lanczos starts by seeding an arbitrary nonzero vector x0 with cardinality equal to the number of columns of matrix M. The mth (m<<n) step of the algorithm transforms the matrix M into a tridiagonal matrix Tmm. The iterative process can be summarized as follows: Chapter 2 ■ Machine Learning and Knowledge Discovery Chapter 2 ■ Machine Learning and Knowledge Discovery PCA is one of the most widely used multivariate methods for uncovering new, informative, uncorrelated features; it reduces dimensionality by rejecting low-variance features and is useful in reducing the computational requirements for classification and regression analysis. Algorithm FOR i m = - 1 2 3 4 1 , , , , , ,  u Mq i i = ai i H i q u = u u v v i i i i i i = - - - - b a 1 1 bi iu =\|\| \|\| u u v v i i i i i i = - - - - b a 1 1 bi iu =\|\| \|\| IF bi = 0, then STOP v u i i i + = 1 b 5. Choose k eigenvectors with the largest eigenvalues. Eigenvector values represent the contribution of each variable to the PC axis. PCs are oriented in the direction of maximum variance in m-dimensional points. Eigenvector values represent the contribution of each variable to the PC axis. PCs are oriented in the direction of maximum variance in m-dimensional points. 31 31 END END After m iterations are completed, you get ai and bi, which are the diagonal and subdiagonal entries, respectively, of the symmetrical tridiagonal matrix Tmm. The resulting tridiagonal matrix is orthogonally similar to M: Tmm m m m = æ è ç ç ç çç ö ø ÷ ÷ ÷ ÷÷ a b b b b a 1 2 2 0 0     . (2-13) (2-13) The symmetrical tridiagonal matrix represents the projections of given matrices onto a subspace spanned by corresponding sets of Lanczos vectors Vm. The eigenvalues of these matrices are the eigenvalues of the mapped subspace of the original matrix. Lanczos iterations by themselves do not directly produce eigenvalues or eigenvectors; rather, they produce a tridiagonal matrix (see Equation 2-13) whose 32 Chapter 2 ■ Machine Learning and Knowledge Discovery eigenvalues and eigenvectors are computed by another method (such as the QR algorithm) to produce Ritz values and vectors. For the eigenvalues, you may compute the k smallest or largest eigenvalues of Tmm if the number of Lanczos iterations is large compared with k. The Lanczos vectors vi so generated then construct the transformation matrix, V v v v v m i m = ( , , , , ), 2 3  which can be used to generate the Ritz eigenvectors (Vm·um), the approximate eigenvectors to the original matrix. which can be used to generate the Ritz eigenvectors (Vm·um), the approximate eigenvectors to the original matrix. Machine Learning: Collaborative Filtering Collaborative filtering (CF is used by recommender systems, whose goal is to forecast the user’s interest in a given item, based on collective user experience (collaboration). The main objective is to match people with similar interests to generate personalized recommendations. Let’s say, for instance, that there are M items and N users. This gives us an M × N user–item matrix X, where xm,n represents nth user recommendations for item m. The following sections discuss some of the CF systems used in recommender systems. Item-Based Collaborative Filtering The rating of an item by a user can be estimated by averaging the ratings of similar items evaluated by the same user. User-Based Collaborative Filtering User-based CF forecasts the user’s interest in an item, based on collective ratings from similar user profiles. The user–item matrix can be written as X u u u =[ , , , ] 1 2  N T X u u u =[ , , , ] 1 2  N T un = = [ , , ] , , , , , . , , , x x x n N n n M n T 1 2 1 2 3   un = = [ , , ] , , , , , . , , , x x x n N n n M n T 1 2 1 2 3   The first step in user-based CF is to evaluate the similarity between users and arrange them according to their nearest neighbor. For example, to evaluate the similarity between two users, you may use a cosine similarity matrix un,ua: sim x x x x m n m a m M m n m M m a m M ( ) . , , , , u ,u n a = × = = = å å å 1 2 1 2 1 (2-14) (2-14) Finally, the predicted rating ˆ , xm a of test item m by test user a is computed as ˆ ) , ( )( ( ) , , x u u sim x sim m a a n m n n N n N = + - = = å å u ,u u ,u n a n a 1 1 (2-15) (2-15) and ua denote the average rating made by users n and a, respectively. As seen from where un and ua denote the average rating made by users n and a, respectively. As seen from where un and ua denote the average rating made by users n and a, respectively. As seen from Equations 2-14 and 2-15, processing CF is a compute-intensive job function and may require large resource pools and faster computing machines. Therefore, it is recommended that you leverage a Hadoop platform for better performance and scalability. 33 33 Chapter 2 ■ Machine Learning and Knowledge Discovery Item-Based Collaborative Filtering Item-based CF computes the similarity between items and selects the best match. The idea is to isolate users that have reviewed both items and then compute the similarity between them. The user–item matrix is represented as X = [ , , ] i i i 1 M 2  T im = = [ , , ] , , , , , , , , x x x m M m m m N T 1 2 1 2   X = [ , , ] i i i 1 M 2  T im = = [ , , ] , , , , , , , , x x x m M m m m N T 1 2 1 2   where im corresponds to an item’s ratings by all users m, which results in item-based recommendation algorithms. The first step in item-based CF is to evaluate the similarity between items and arrange them according to their nearest neighbor. For instance, you may use the cosine similarity matrix to evaluate the similarity between two items im,ib. To remove the difference in rating scale between users when computing the similarity, the cosine similarity is adjusted by subtracting the user’s average rating xn (Sarwar 2001) from each co-rated pair: sim x x x x x x x x m b m n n b n n n N m n n n N b n n ( , ) ( )( ) ( ) ( , , , , i i = − − − ⋅ − = = ∑ ∑ 1 2 1 ) . 2 1 n N =∑ (2-16) (2-16) Finally, the predicted rating ˆ , xm a of test item m by test user a is computed as Finally, the predicted rating ˆ , xm a of test item m by test user a is computed as Finally, the predicted rating ˆ , xm a of test item m by test user a is computed as ˆ ) . ( )( ( ) , , x sim x sim m a b m b a b N b m b M = = = å å i ,i i ,i 1 1 (2-17) (2-17) The rating of an item by a user can be estimated by averaging the ratings of similar items evaluated by the same user. Chapter 2 ■ Machine Learning and Knowledge Discovery Chapter 2 ■ Machine Learning and Knowledge Discovery where nu x and ni y represent the number of ratings of user u and item i, respectively. The regularization term l(...) avoids overfitting the training data. The parameter l depends on the data and is tuned by cross- validation in the dataset for better generalization. Because the search space is very large (multiple users and items), it prevents application of traditional direct optimization techniques, such as stochastic gradient descent. where nu x and ni y represent the number of ratings of user u and item i, respectively. The regularization term l(...) avoids overfitting the training data. The parameter l depends on the data and is tuned by cross- validation in the dataset for better generalization. Because the search space is very large (multiple users and items), it prevents application of traditional direct optimization techniques, such as stochastic gradient descent. The cost function assumes a quadratic form when either the user–factor or the item–factor is fixed, which allows computation of a global minimum. This in turn allows ALS optimization, in which user–factors and item–factors are alternately recomputed by fixing each other. This algorithm is designed for large-scale CF for large datasets. Pearson Correlation Coefficient Pearson correlation measures the linear dependence between two variables. The Pearson correlation coefficient is the covariance of the two variables (X and Y) divided by the product of their standard deviations: r X X Y Y X X Y Y i i i n i i n i i n = - - - - = = = å å å ( )( ) ( ) ( ) . 1 2 1 2 1 (2-19) (2-19) The Pearson correlation coefficient ranges from −1 to 1. A value of 1 validates a perfect linear relationship between X and Y, in which the data variability of X tracks that of Y. A value of −1 indicates a reverse relationship between X and Y, such that the data variability of Y is opposite to that of X. A value of 0 suggests lack of linear correlation between the variables X and Y. Although the Pearson coefficient reflects the strength of the linear relationship, it is highly sensitive to extreme values and outliers. The low relationship strength may be misleading if two variables have a strong curvilinear relationship instead of a strong linear relationship. The coefficient may also be misleading if X and Y have not been analyzed in terms of their full ranges. Machine Learning: Similarity Matrix A similarity matrix scores the similarity between data points. Similarity matrices are strongly related to their counterparts: distance matrices and substitution matrices. The following sections look at some of the commonly used similarity calculation methods. Alternating Least Squares with Weighted-l-Regularization The alternating-least-squares with weighted-l-regularization (ALS-WR) algorithm factors the user–item matrix into the user–factor matrix and the item–factor matrix. This algorithm strives to uncover the latent factors that rationalize the observed user–item ratings and searches for optimal factor weights to minimize the least squares between predicted and actual ratings (Zhou 2008). If you have multiple users and items, you will need to learn the feature vectors that represent each item and each user in the feature space. The objective is to uncover features that associate each user u with a user–factor vector xu f Î, and each item i with an item–factor vector yi f Î( )  . Ratings are described by the inner dot product p x y ui u T i = of the user–factor vector and the item–factor vector. The idea is to perform matrix factorization, such that users and items can be mapped into common latent factors, whereby they can be directly compared. Because the rating matrix is sparse and not fully defined, the factorization has to be done using known ratings only. The quality of the solution is measured not only with respect to the observed data, but also with respect to a generalization of the unobserved data. You have to find a set of user and item feature vectors that minimizes the following cost function: ( ) \|\| \|\| \|\| \|\| , , p x y n x n y ui u T i u x u u i y i i u i - - + æ èç ö ø÷ å å å 2 2 2 l (2-18) (2-18) 34 Euclidean Distance The Euclidean distance is the square root of the sum of squared differences between the vector elements of the two variables: d X Y i i i n ( ) . ( ) X,Y = - =å 2 1 (2-21) (2-21) A Euclidean distance is valid if both variables are measured on the same scale. You can transform the distance in Equation 2-21 to an inverse form (see Equation 2-22), such that it returns a value of 1 if X and Y (X – Y = 0) are similar and trend to 0 if the similarity decreases: ˆ( ) ( ). d d X,Y X,Y = + 1 1 (2-22) (2-22) You can verify that ˆ( ) d X,Y calculates to the value of 1 if the distance d(X,Y) = 0 (indicating similarity), and ˆ( ) d X,Y decreases to 0 if d(X,Y) increases (indicating dissimilarity). Chapter 2 ■ Machine Learning and Knowledge Discovery Chapter 2 ■ Machine Learning and Knowledge Discovery The sign of the Spearman correlation coefficient signifies the direction of the association between the dependent and independent variables. The coefficient is positive if the dependent variable Y increases (or decreases) in the same direction as the independent variable X. The coefficient is negative if the dependent variable Y increases (or decreases) in the reverse direction, relative to the independent variable X. A Spearman correlation of 0 signifies that the variable Y has no inclination to either increase or decrease, relative to X. Spearman correlation increases in magnitude as X and Y move closer to being perfect monotone functions. Spearman correlation can only be computed if the data are not truncated. Although less sensitive to extreme values, it relies only on rank instead of observation. Spearman Rank Correlation Coefficient rman correlation coefficient performs statistical analysis of the strength of a monotonic The Spearman correlation coefficient performs statistical analysis of the strength of a monotonic relationship between the paired variables X and Y. Spearman correlation calculates Pearson correlation for the ranked values of the paired variables. Ranking (from low to high) is obtained by assigning a rank of 1 to the lowest value, 2 to the next lowest, and so on, such that r d n n S i = - - å 1 6 1 2 2 ( ) , (2-20 (2-20) where n is the sample size, and d is the distance between the statistical ranks of the variable pairs given by d x y i i i = - . d x y i i i = - . 35 Chapter 2 ■ Machine Learning and Knowledge Discovery Chapter 2 ■ Machine Learning and Knowledge Discovery Jaccard Similarity Coefficient The Jaccard similarity coefficient gauges similarity between finite sample sets X and Y by measuring overlapping between them. Sets X and Y do not have to be of same size. Mathematically, the coefficient can be defined as the ratio of the intersection to the union of the sample sets (X, Y): J X Y X Y X Y J X Y ( , ) , ( , ) = Ç È £ £ 0 1 (2-23) J X Y X Y X Y J X Y ( , ) , ( , ) = Ç È £ £ 0 1 (2-23) J X X ( , ) . =1 (2-23) J X X ( , ) . =1 The Jaccard distance measures the dissimilarity between sample sets and is obtained by subtracting the Jaccard coefficient from 1: d X Y J X Y J( , ) ( , ). = - 1 (2-24) (2-24) The Jaccard coefficient is commonly used in measuring keyword similarities, document similarities, news article classification, natural language processing (NLP), and so on. 36 Chapter 2 ■ Machine Learning and Knowledge Discovery Chapter 2 ■ Machine Learning and Knowledge Discovery Summary The solution to a complex problem relies on intelligent use of machine learning techniques. The precision, speed, and accuracy of the solution can be improved by employing techniques that not only reduce the dimensionality of the features, but also train the models specific to a unique behavior. Distinct behavioral attributes can be clustered into phases by using one of the clustering techniques, such as k-means. Reduced data points corresponding to each cluster label are separated and trained to solve a regression or classification problem. In a normal posttraining operation, once phases are identified, the trained model associated with that phase is employed to forecast (or estimate) the output of the feedback loop. Figure 2-5 summarizes a process control system capable of sensing a large number of sensors in order to control an environmental process (e.g., cooling in the datacenter). The first step is to reduce the dimensionality of the data. The new data are fed into clustering methods, which discover a group’s items from a given collection, based on similar attributes and distinctive properties. Data corresponding to each cluster label are segregated and trained individually for classification. Phase identification allows the application of a model function, which associates with the identified phase. The output of the phase-specific model triggers the process control functions, which act on the environment and change the sensor outputs. Additionally, this procedure lets us actively predict the current phase duration and the upcoming phase and accordingly forecast the output for proactive control. Figure 2-5. Machine learning–based feedback control system: features are transformed and fed into phase detectors; the data classification process employs models trained on the detected phase Figure 2-5. Machine learning–based feedback control system: features are transformed and fed into phase detectors; the data classification process employs models trained on the detected phase 37 37 Support Vector Machines for Classification Science is the systematic classification of experience. —George Henry Lewes This chapter covers details of the support vector machine (SVM) technique, a sparse kernel decision machine that avoids computing posterior probabilities when building its learning model. SVM offers a principled approach to machine learning problems because of its mathematical foundation in statistical learning theory. SVM constructs its solution in terms of a subset of the training input. SVM has been extensively used for classification, regression, novelty detection tasks, and feature reduction. This chapter focuses on SVM for supervised classification tasks only, providing SVM formulations for when the input space is linearly separable or linearly nonseparable and when the data are unbalanced, along with examples. The chapter also presents recent improvements to and extensions of the original SVM formulation. A case study concludes the chapter. References Bezdek, James C. Pattern Recognition with Fuzzy Objective Function Algorithms. Norwell, MA: Kluwer, 1981. Breiman, Leo. “Random Forests.” Machine Learning 45, no. 1 (2001): 5–32. Dunn, J. C. “A Fuzzy Relative of the Isodata Process and Its Use in Detecting Compact Well-Separated Clusters.” Cybernetics 3 (1973): 32–57. Dunn, J. C. “A Fuzzy Relative of the Isodata Process and Its Use in Detecting Compact Well-Separated Clusters.” Cybernetics 3 (1973): 32–57. Sarwar, Badrul, George Karypis, Joseph Konstan, and John Riedl. “Item-Based Collaborative Filtering Recommendation Algorithms.” In Proceedings of the 10th International Conference on the World Wide Web, 285–295. New York: ACM, 2001. Sarwar, Badrul, George Karypis, Joseph Konstan, and John Riedl. “Item-Based Collaborative Filtering Recommendation Algorithms.” In Proceedings of the 10th International Conference on the World Wide Web, 285–295. New York: ACM, 2001. Zhou, Yunhong, Dennis Wilkinson, Robert Schreiber, and Rong Pan. “Large-Scale Parallel Collaborative Filtering for the Netflix Prize.” In Algorithmic Aspects in Information and Management, Proceedings of the 4th International Conference, AAIM 2008, Shanghai, China, June 23–25, 2008, edited by Rudof Fleischer and Jinhui Xu, 337–348. Berlin: Springer, 2008. Zhou, Yunhong, Dennis Wilkinson, Robert Schreiber, and Rong Pan. “Large-Scale Parallel Collaborative Filtering for the Netflix Prize.” In Algorithmic Aspects in Information and Management, Proceedings of the 4th International Conference, AAIM 2008, Shanghai, China, June 23–25, 2008, edited by Rudof Fleischer and Jinhui Xu, 337–348. Berlin: Springer, 2008. 38 SVM from a Geometric Perspective In classification tasks a discriminant machine learning technique aims at finding, based on an independent and identically distributed (iid) training dataset, a discriminant function that can correctly predict labels for newly acquired instances. Unlike generative machine learning approaches, which require computations of conditional probability distributions, a discriminant classification function takes a data point x and assigns it to one of the different classes that are a part of the classification task. Less powerful than generative approaches, which are mostly used when prediction involves outlier detection, discriminant approaches require fewer computational resources and less training data, especially for a multidimensional feature space and when only posterior probabilities are needed. From a geometric perspective, learning a classifier is equivalent to finding the equation for a multidimensional surface that best separates the different classes in the feature space. SVM is a discriminant technique, and, because it solves the convex optimization problem analytically, it always returns the same optimal hyperplane parameter—in contrast to genetic algorithms (GAs) or perceptrons, both of which are widely used for classification in machine learning. For perceptrons, solutions are highly dependent on the initialization and termination criteria. For a specific kernel that transforms the data from the input space to the feature space, training returns uniquely defined SVM model parameters for a given training set, whereas the perceptron and GA classifier models are different each time training is initialized. The aim of GAs and perceptrons is only to minimize error during training, which will translate into several hyperplanes’ meeting this requirement. 39 SVM Main Properties Deeply rooted in the principles of statistics, optimization, and machine learning, SVM was officially introduced by Boser, Guyon, and Vapnik (1992) during the Fifth Annual Association for Computing Machinery Workshop on Computational Learning Theory. [Bartlett (1998) formally revealed the statistical bounds of the generalization of the hard-margin SVM. SVM relies on the complexity of the hypothesis space and empirical error (a measure of how well the model fits the training data). Vapnik- Chervonenkis (VC) theory proves that a VC bound on the risk exists. VC is a measure of the complexity of the hypothesis space. The VC dimension of a hypothesis H relates to the maximum number of points that can be shattered by H. H shatters N points, if H correctly separates all the positive instances from the negative ones. In other words, the VC capacity is equal to the number of training points N that the model can separate into 2N different labels. This capacity is related to the amount of training data available. The VC dimension h affects the generalization error, as it is bounded by   w where w is the weight vector of the separating hyperplane and the radius of the smallest sphere R that contains all the training points, according to: h R w < 2 2   . The overall error of a machine learning model consists of e = eemp + eg, where eemp is the N [ ] ( ) å 1 1 ining error, and eg is the generalization error. The empirical risk of a model f is eemp f N [ ]= å 1 1 2 The lower bound for risk is e e h f f N h N h emp [ ]≤ [ ]+         + − 1 2 1 4 ln ln where 1−h is the probability of his bound’s being true for any function in the class of function with VC dimension h, independent of the data distribution. The lower bound for risk is e e h f f N h N h emp [ ]≤ [ ]+         + − 1 2 1 4 ln ln where 1−h is the probability of his bound’s being true for any function in the class of function with VC dimension h, independent of the data distribution. Chapter 3 ■ Support Vector Machines for Classification Chapter 3 ■ Support Vector Machines for Classification If many hyperplanes can be learned during the training phase, only the optimal one is retained, because training is practically performed on samples of the population even though the test data may not exhibit the same distribution as the training set. When trained with data that are not representative of the overall data population, hyperplanes are prone to poor generalization. If many hyperplanes can be learned during the training phase, only the optimal one is retained, because training is practically performed on samples of the population even though the test data may not exhibit the same distribution as the training set. When trained with data that are not representative of the overall data population, hyperplanes are prone to poor generalization. Figure 3-1 illustrates the different hyperplanes obtained with SVM, perceptron, and GA classifiers on two-dimensional, two-class data. Points surrounded by circles represent the support vector, whereas the hyperplanes corresponding to the different classifiers are shown in different colors, in accordance with the legend. 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 x2 x1 0 0.2 0.4 0.6 0.8 1.2 1.4 1.6 1.8 2 1 Class 1 Class 2 Support Vectors SVM Perceptron 1 Perceptron 2 GA 1 GA 2 Figure 3-1. Two-dimensional, two-class plot for SVM, perceptron, and GA hyperplanes Figure 3-1. Two-dimensional, two-class plot for SVM, perceptron, and GA hyperplanes Note SVM vs. ANN ■ ■ Generally speaking, SVM evolved from a robust theory of implementation, whereas artificial neural networks (ANN) moved heuristically from application to theory. Note SVM vs. ANN ■ ■ Generally speaking, SVM evolved from a robust theory of implementation, whereas artificial neural networks (ANN) moved heuristically from application to theory. SVM distinguishes itself from ANN in that it does not suffer from the classical multilocal minima—the double curse of dimensionality and overfitting. Overfitting, which happens when the machine learning model strives to achieve a zero error on all training data, is more likely to occur with machine learning approaches whose training metrics depend on variants of the sum of squares error. By minimizing the structural risk rather than the empirical risk, as in the case of ANN, SVM avoids overfitting. SVM does not control model complexity, as ANN does, by limiting the feature set; instead, it automatically determines the model complexity by selecting the number of support vectors. 40 Chapter 3 ■ Support Vector Machines for Classification The upper bound for the number of support vectors is half the size of the training dataset, but in practice this is rarely the case. The SVM model described mathematically in this chapter is written as a weighted sum of the support vectors, which gives the SVM framework the same advantages as parametric techniques in terms of reduced computational time for testing and storage requirements. SVM is a kernel technique. SVM uses the kernel trick to map the data into a higher-dimensional space before solving the machine learning task as a convex optimization problem in which optima are found analytically rather than heuristically, as with other machine learning techniques. Often, real-life data are not linearly separable in the original input space. In other words, instances that have different labels share the input space in a manner that prevents a linear hyperplane from correctly separating the different classes involved in this classification task. Trying to learn a nonlinear separating boundary in the input space increases the computational requirements during the optimization phase, because the separating surface will be of at least the second order. Instead, SVM maps the data, using predefined kernel functions, into a new but higher-dimensional space, where a linear separator would be able to discriminate between the different classes. The SVM optimization phase will thus entail learning only a linear discriminant surface in the mapped space. Of course, the selection and settings of the kernel function are crucial for SVM optimality. SVM is a maximum margin separator. Beyond minimizing the error or a cost function, based on the training datasets (similar to other discriminant machine learning techniques), SVM imposes an additional constraint on the optimization problem: the hyperplane needs to be situated such that it is at a maximum distance from the different classes. Such a term forces the optimization step to find the hyperplane that would eventually generalize better because it is situated at an equal and maximum distance from the classes. This is essential, because training is done on a sample of the population, whereas prediction is to be performed on yet-to-be-seen instances that may have a distribution that is slightly different from that of the subset trained on. 1Established in the 1970s, Lagrangian relaxation provides bounds for the branch-and-bound algorithm and has been extensively used in scheduling and routing. Chapter 3 ■ Support Vector Machines for Classification What makes SVM an attractive machine learning framework can be summarized by the following properties: What makes SVM an attractive machine learning framework can be summarized by the following properties: • SVM is a sparse technique. Like nonparametric methods, SVM requires that all the training data be available, that is, stored in memory during the training phase, when the parameters of the SVM model are learned. However, once the model parameters are identified, SVM depends only on a subset of these training instances, called support vectors, for future prediction. Support vectors define the margins of the hyperplanes. Support vectors are found after an optimization step involving an objective function regularized by an error term and a constraint, using Lagrangian relaxation.1 The complexity of the classification task with SVM depends on the number of support vectors rather than the dimensionality of the input space. The number of support vectors that are ultimately retained from the original dataset is data dependent and varies, based on the data complexity, which is captured by the data dimensionality and class separability. The upper bound for the number of support vectors is half the size of the training dataset, but in practice this is rarely the case. The SVM model described mathematically in this chapter is written as a weighted sum of the support vectors, which gives the SVM framework the same advantages as parametric techniques in terms of reduced computational time for testing and storage requirements. • SVM is a sparse technique. Like nonparametric methods, SVM requires that all the training data be available, that is, stored in memory during the training phase, when the parameters of the SVM model are learned. However, once the model parameters are identified, SVM depends only on a subset of these training instances, called support vectors, for future prediction. Support vectors define the margins of the hyperplanes. Support vectors are found after an optimization step involving an objective function regularized by an error term and a constraint, using Lagrangian relaxation.1 The complexity of the classification task with SVM depends on the number of support vectors rather than the dimensionality of the input space. The number of support vectors that are ultimately retained from the original dataset is data dependent and varies, based on the data complexity, which is captured by the data dimensionality and class separability. SVM Main Properties Note ■ ■ There are 2N different learning problems that can be defined, as N points can be labeled in 2N manners as positive or negative. For instance, for three points, there are 24 different labels and 8 different classification boundaries that can be learned. Thus, the VC dimension in R2 is 3. SVM elegantly groups multiple features that were already being proposed in research in the 1960s to form what is referred to as the maximal margin classifier. SVM borrows concepts from large-margin hyperplanes (Duda 1973; Cover 1995; Vapnik and Lerner 1963; Vapnik and Chervonenkis 1964); kernels as inner products in the feature space (Aizermann, Braverman, and Rozonoer 1964); kernel usage (Aizermann, Braverman, and Rozonoer 1964; Wahba 1990; Poggio 1990) and sparseness (Cover 1995). Mangasarian (1965) also proposed an optimization approach similar to the one adopted by SVM. The concept of slack, used to address noise in data and nonseparability, was originally introduced by Smith (1968) and was further enhanced by Bennett and Mangasarian (1992). Incorporated into SVM formulation by Cortes (1995), soft-margin SVM represents a modification of the hard-margin SVM through its adoption of the concept of slack to account for noisy data at the separating boundaries. (For readers interested in delving into the foundations of SVM, see Vapnik 1998, 1999, for an exhaustive treatment of SVM theory.) Known for their robustness, good generalization ability, and unique global optimum solutions, SVMs are probably the most popular machine learning approach for supervised learning, yet their principle is very simple. In his comparison of SVM with 16 classifiers, on 21 datasets, Meyer, Leisch, and Hornik (2003) showed that SVM is one of the most powerful classifiers in machine learning. Since their introduction in 1992, SVMs have found their way into a myriad of applications, such as weather prediction, power estimation stock prediction, defect classification, speaker recognition, handwriting identification, image and audio processing, video analysis, and medical diagnosis. 41 41 Chapter 3 ■ Support Vector Machines for Classification 1Established in the 1970s, Lagrangian relaxation provides bounds for the branch-and-bound algorithm and has been extensively used in scheduling and routing. Lagrangian relaxation converts many hard integer-programming problems into simpler ones by emphasizing the constraints in the objective function for optimization via Lagrange multipliers. (For a more in-depth discussion on Lagrangian relaxation, see Fisher 2004.) Chapter 3 ■ Support Vector Machines for Classification Lagrangian relaxation converts many hard integer-programming problems into simpler ones by emphasizing the constraints in the objective function for optimization via Lagrange multipliers. (For a more in-depth discussion on Lagrangian relaxation, see Fisher 2004.) 42 Chapter 3 ■ Support Vector Machines for Classification SVM uses structural risk minimization (SRM) and satisfies the duality and convexity requirements. SRM (Vapnik 1964) is an inductive principle that selects a model for learning from a finite training dataset. As an indicator of capacity control, SRM proposes a trade-off between the VC dimensions, that is, the hypothesis of space complexity and the empirical error. SRM’s formulation is a convex optimization with n variables in the cost function to be maximized and m constraints, solvable in polynomial time. SRM uses a set of models sequenced in an increasing order of complexity. Figure 3-2 shows how the overall model error varies with the complexity index of a machine learning model. For non- complex models, the error is high because a simple model cannot capture all the complexity of the data which results in an underfitting situation. As the complexity index increases, the error reaches its minimum for the optimal model indexed h* before it starts increasing again. For high model indices, the structure starts adapting its learning model to the training data which results in an overfitting that reduces the training error value and increases the model VC however, at the expense of a deterioration in the test error. best model overfitting underfitting error structure test error VC (confidence term) training error/empirical error h (model index) Figure 3-2. Relationship between error trends and model index Hard-Margin SVM The SVM technique is a classifier that finds a hyperplane or a function g x w x b T ( ) = + that correctly separates two classes with a maximum margin. Figure 3-3 shows a separating hyperplane corresponding to a hard-margin SVM (also called a linear SVM). best model overfitting underfitting error structure test error VC (confidence term) training error/empirical error h (model index) Figure 3-2. Relationship between error trends and model index overfitting best model error test error VC (confidence term) training error/empirical error (model index) structure Figure 3-2. Relationship between error trends and model index Hard-Margin SVM The SVM technique is a classifier that finds a hyperplane or a function g x w x b T ( ) = + that correctly separates two classes with a maximum margin. Figure 3-3 shows a separating hyperplane corresponding to a hard-margin SVM (also called a linear SVM). 43 43 Chapter 3 ■ Support Vector Machines for Classification Figure 3-3. Hard-maximum-margin separating hyperplane Figure 3-3. Hard-maximum-margin separating hyperplane Figure 3-3. Hard-maximum-margin separating hyperplane Mathematically speaking, given a set of points xi that belong to two linearly separable classes w1, w2, the distance of any instance from the hyperplane is equal to g x w ( )   . SVM aims to find w, b, such that the value of g(x) equals 1 for the nearest data points belonging to class w1 and –1 for the nearest ones of w2. This can be viewed as having a margin of 1 1 2       w w w + = , 1 1 2       w w w + = , whereas w x b x T + = ∈ 1 1 for w , and w x b x T + = − ∈ 1 2 for w . 1 2 This leads to an optimization problem that minimizes the objective function J w w ( ) = 1 2 2  , subject to the constraint subject to the constraint y x b i N i wi T + ( ) ≥ = 1 1 2 , , , . . ., . When an optimization problem—whether minimization or maximization—has constraints in the variables being optimized, the cost or error function is augmented by adding to it the constraints, multiplied by the Lagrange multipliers. In other words, the Lagrangian function for SVM is formed by augmenting the objective function with a weighted sum of the constraints, w b w w w x b y T i N i i T i , ,λ λ ( ) = − + ( )−   =∑ 1 2 1 1 where w and b are called primal variables, and li’s the Lagrange multipliers. where w and b are called primal variables, and li’s the Lagrange multipliers. These multipliers thus restrict the solution’s search space to the set of feasible values, given the constraints. max , , λ λ λ λ i N i i j i j i j j y y x x i =∑ ∑ −       1 1 2 Hard-Margin SVM In the presence of inequality constraints, the Karush-Kuhn-Tucker (KKT) conditions generalize the Lagrange multipliers. 44 Chapter 3 ■ Support Vector Machines for Classification The KKT conditions are The KKT conditions are 1. Primal constraints − + ( )−  ≤ ∀= y w x b i i T i 1 0 1,...,N 2. Dual constraints li i N ≥ ∀= 0 1,..., 3. Complementarity slackness 3. Complementarity slackness λi i N y w x b i T i + ( )−  = ∀= 1 0 1, ..., 4. Gradient of the Lagrangian (zero, with respect to primal variables) 4. Gradient of the Lagrangian (zero, with respect to primal variables) ∇( ) = − −               = = = ∑ ∑ w b , ,λ w y x y i N i i i i N i i 1 1 0 l l Based on the KKT conditions, w y x i N i i i = =∑ 1 λ , i N iy i =∑ = 1 0 λ . Based on the KKT conditions, Note ■ ■ Appearing in a study by Kuhn and Tucker (1951), these conditions are also found in the unpublished master’s thesis of Karush (1939). Since most linear programming problems come in pairs, a primal problem with n variables and m constraints can be rewritten in the Wolfe dual form with m variables and n constraints while the same solution applies for both primal and dual formulations. The duality theorem formalizes this by stating that the number of variables in one form is equal to the number of constraints in the complementary form. The complementary slackness is the relationship between the primal and dual formulation: when added to inequalities, slack variables transform them into equalities. The dual problem of SVM optimization is to find max , , λ λ λ λ i N i i j i j i j j y y x x i =∑ ∑ −       1 1 2 subject to subject to 45 45 Chapter 3 ■ Support Vector Machines for Classification Note ■ ■ This last constraint is essential for solution optimality. At optimality, the dual variables have to be nonnegative, as dual variables are multiplied by a positive quantity. Hard-Margin SVM Because negative Lagrange multipliers decrease the value of the function, the optimal solution cannot have negative Lagrange multipliers. Active or binding constraints have a corresponding nonzero multiplier, whereas nonbinding ones are zero and do not affect the problem solution. SVM hyperplane parameters are thus defined by the active, binding constraints, which correspond to the nonzero Lagrange multipliers, that is, the support vector. Solving the duality of the aforementioned problem is useful for several reasons. First, even if the primal is not convex, the dual problem will always have a unique optimal solution. Second, the value of the objective function is a lower bound on the optimal function value of the primal formulation. Finally, the number of dual variables may be significantly less than the number of primal variables; hence, an optimization problem formulated in the dual form can be solved faster and more efficiently. Soft-Margin SVM When the data are not completely separable, as with the points marked by a X in Figure 3-4, slack variables xi are introduced to the SVM objective function to allow error in the misclassification. SVM, in this case, is not searching for the hard margin, which will classify all data flawlessly. Instead, SVM is now a soft-margin classifier; that is, SVM is classifying most of the data correctly, while allowing the model to misclassify a few points in the vicinity of the separating boundary. Figure 3-4. A few misclassifications, as part of soft-margin SVM Figure 3-4. A few misclassifications, as part of soft-margin SVM Figure 3-4. A few misclassifications, as part of soft-margin SVM 46 46 max , λ λ λ λ i N i i j i j i j i j y y x x =∑ ∑ −       1 1 2 , i N i iy =∑ = 1 0 λ , 0 1 2 ≤ ≤ = λi C i N , , ,..., . where j(x) belongs to the Hilbert space. where j(x) belongs to the Hilbert space. ∫∫ g p In other words, K x u g x g u dxdu g x g x dx , , ( ) ( ) ( ) ≥ ∀( ) ( ) <+ ∞ ∫ ∫∫ 0 2 where . Some popular kernel functions include ( ) ( ) ( ) ∫∫ Some popular kernel functions include • Linear kernel: K x u u T , . ( ) = x • Linear kernel: K x u u T , . ( ) = x • Polynomial function: K x u ax u c q T q , , ( ) = + ( ) > 0 • Polynomial function: K x u ax u c q T q , , ( ) = + ( ) > 0 • Hyperbolic tangent (sigmoid): K x u x u T , tanh ( ) = + ( ) b g • Hyperbolic tangent (sigmoid): K x u x u T , tanh ( ) = + ( ) b g • Gaussian radial basis function (RBF): K x u x u , exp ( ) = − −       2 2 s • Gaussian radial basis function (RBF): K x u x u , exp ( ) = − −       2 2 s • Laplacian radial basis function: K x u x u , exp ( ) = − −     s • Laplacian radial basis function: K x u x u , exp ( ) = − −     s • Randomized blocks analysis of variance (ANOVA RB) kernel: • Randomized blocks analysis of variance (ANOVA RB) kernel: K x u x u k n k k d , ( ( ) ) ( ) = − − =∑ 1 2 exp s • Linear spline kernel in 1D: K x u x u , . .min , (min( , ) ( , ) ) ( ) = + ( )− + + 1 2 1 3 2 3 x u x u x u x u min Kernel selection is heavily dependent on the data specifics. For instance, the linear kernel—the simplest of all—is useful in large sparse data vectors. However, it ranks behind the polynomial kernel, which avoids zeroing the Hessian. Chapter 3 ■ Support Vector Machines for Classification Chapter 3 ■ Support Vector Machines for Classification The problem in primal form now is a minimization of the objective function J w b w C i N i , , , ξ ξ ( ) = + =∑ 1 2 2 1   subject to these two constraints: y b i N i wi T ix i +  ≥− = 1 ξ , , ,..., , 1 2 ξi i N ≥ = 0 1 2 , , ,..., . y b i N i wi T ix i +  ≥− = 1 ξ , , ,..., , 1 2 The regularization term or box constraint, C, is a parameter that varies, depending on the optimization goal. As C is increased, a tighter margin is obtained, and more emphasis is placed on minimizing the number of misclassifications. As C is decreased, more violations are allowed, because maximizing the margin between the two classes becomes the SVM aim. Figure 3-5 captures the effect of the regularization parameter, with respect to margin width and misclassification. For C C 1 2 < , fewer training points are within the margin for C2 than for C1, but the latter has a wider margin. Figure 3-5. The box constraint effect on SVM performance Figure 3-5. The box constraint effect on SVM performance In dual form the soft margin SVM formulation is subject to 47 47 Chapter 3 ■ Support Vector Machines for Classification The soft-margin dual problem is equivalent to the hard-margin dual problem, except that the dual variable is upper bounded by the regularization parameter C. Kernel SVM When a problem is not linearly separable in input space, soft-margin SVM cannot find a robust separating hyperplane that minimizes the number of misclassified data points and that generalizes well. For that, a kernel can be used to transform the data to a higher-dimensional space, referred to as kernel space, where data will be linearly separable. In the kernel space a linear hyperplane can thus be obtained to separate the different classes involved in the classification task instead of solving a high-order separating hypersurface in the input space. This is an attractive method, because the overhead on going to kernel space is insignificant compared with learning a nonlinear surface. p g A kernel should be a Hermitian and positive semidefinite matrix and needs to satisfy Mercer’s theorem, which translates into evaluating the kernel or Gram matrix on all pairs of data points as positive and semidefinite, forming K x u x u r r r , , ( ) = ( ) ( ) ∑ϕ ϕ where j(x) belongs to the Hilbert space. The polynomial kernel is widely used in image processing, whereas the ANOVA RB kernel is usually reserved for regression tasks. The Gaussian and Laplace RBFs are general-purpose kernels that are mostly applied in the absence of prior knowledge. A kernel matrix that ends up being diagonal indicates that the feature space is redundant and that another kernel should be tried after feature reduction. p Note that when kernels are used to transform the feature vectors from input space to kernel space for linearly nonseparable datasets, the kernel matrix computation requires massive memory and computational resources, for big data. 48 Chapter 3 ■ Support Vector Machines for Classification Figure 3-6 displays the two-dimensional exclusive OR (XOR) data, a linearly nonseparable distribution in input space (upper-left) as well as in the feature space. In the latter, 16 points (for different sets) are created for the four inputs when the kernel is applied. The choice of the Gaussian RBF kernel-smoothing parameter s2 affects the distribution of the data in the kernel space. Because the choice of parameter value is essential for transforming the data from a linearly nonseparable space to a linearly separable one, grid searches are performed to find the most suitable values. Figure 3-6. Two-dimensional XOR data, from input space to kernel space Figure 3-6. Two-dimensional XOR data, from input space to kernel space The primal formulation of the kernel SVM is The primal formulation of the kernel SVM is min , , w T i N i w w C ξ ξ 1 2 1 + =∑ subject to y w x b i T i i ϕ ξ ( )+ ( )≥− 1 and ξi i ≥ ∀ 0, , where j(xi) is such that K x x x x i j i j , . ( )= ( ) ( ) ϕ ϕ . subject to y w x b i T i i ϕ ξ ( )+ ( )≥− 1 and ξi i ≥ ∀ 0, , ( ) ( ) ( ) ( ) subject to y w x b i T i i ϕ ξ ( )+ ( )≥− 1 and ξi i ≥ ∀ 0, , where j(xi) is such that K x x x x i j i j , . ( )= ( ) ( ) ϕ ϕ . where j(x) belongs to the Hilbert space. j j ( ) ( ) Again, the SVM solution should satisfy the KKT conditions, as follows: N 1. w y x i N i i i = ∑ =1λ ϕ( ) 2. ∑ = = i N i iy 1 0 λ 3. C i N i i − − = = µ λ 0 1 2 , ,..., 4. λ ϕ ξ i i T i i y w x b i N ( ) , ,..., + ( )−+  = = 1 0 1 2 5. µ ξ i i i N = = 0 1 2 , ,..., 6. µ ξ i i , , ,..., > = 0 1 2 i N 49 49 Chapter 3 ■ Support Vector Machines for Classification As mentioned earlier, the dual formulation of this problem is more efficient to solve and is used in most implementations of SVM: max , λ λ λ λ i i j i j i j i N i N y y x x = = ∑ ∑ −     1 1 1 2 λi i iy ∑ max , λ λ λ λ i i j i j i j i N i N y y x x = = ∑ ∑ −     1 1 1 2 λi i iy ∑ max , λ λ λ λ i i j i j i j i N i N y y x x = = ∑ ∑ −     1 1 1 2 subject to subject to Note ■ ■ For a dataset size of N, the kernel matrix has N2 entries. Therefore, as N increases, computing the kernel matrix becomes inefficient and even unfeasible, making SVM impractical to solve. However, several algorithms have alleviated this problem by breaking the optimization problem into a number of smaller problems. Multiclass SVM The early extensions of the SVM binary classification to the multiclass case were the work of Weston and Watkins (1999) and Platt (2000). Researchers devised various strategies to address the multiclassification problem, including one-versus-the-rest, pair-wise classification, and the multiclassification formulation, discussed in turn here. • One-versus-the-rest (also called one-against-all [OAA]) is probably the earliest SVM multiclass implementation and is one of the most commonly used multiclass SVMs. It constructs c binary SVM classifiers, where c is the number of classes. Each classifier distinguishes one class from all the others, which reduces the case to a two-class problem. There are c decision functions: w x b w x b T i c T i c 1 1 j j ( )+ ( )+ ;...; . The initial formulation of the OAA method assigns a data point to a certain class if and only if that class has accepted it, while all other classes have not, which leaves undecided regions in the feature space when more than one class accepts it or when all classes reject it. Vapnik (1998) suggested assigning data points to the class with the highest value, regardless of sign. The final label output is given to the class that has demonstrated the highest output value: classof x max w x b i c i T i arg ( ( ) ). ,. . ., ≡ + =1 j classof x max w x b i c i T i arg ( ( ) ). ,. . ., ≡ + =1 j Proposed by Knerr, Personnaz, and Dreyfus (1990), and first adopted in SVM by • Friedman (1996) and Kressel (1999), pair-wise classification (also called one-against- one [OAO]) builds c(c – 1)/2 binary SVMs, each of which is used to discriminate two of the c classes only and requires evaluation of (c – 1) SVM classifiers. For training data from the kth and jth classes, the constraints for (x y t t , ) are Proposed by Knerr, Personnaz, and Dreyfus (1990), and first adopted in SVM by Friedman (1996) and Kressel (1999), pair-wise classification (also called one-against- one [OAO]) builds c(c – 1)/2 binary SVMs, each of which is used to discriminate two of the c classes only and requires evaluation of (c – 1) SVM classifiers. For training data from the kth and jth classes, the constraints for (x y t t , ) are w b kj T kj kj t ϕ ξ xt ( )+ ( )≥− 1 , for y k t = , w b kj T kj kj t ϕ ξ xt ( )+ ( )≤−+ 1 , for y j t = , w b kj T kj kj t ϕ ξ xt ( )+ ( )≥− 1 , for y k t = , w b kj T kj kj t ϕ ξ xt ( )+ ( )≤−+ 1 , for y j t = , ξkj t ≥0. ξkj t ≥0. 50 Chapter 3 ■ Support Vector Machines for Classification The • multiclassification objective function probably has the most compact form, as it optimizes the problem in a single step. The decision function is the same as that of the OAA technique. The multiclassification objective function constructs c two-class rules, and c decision functions solve the following constraints: The • multiclassification objective function probably has the most compact form, as it optimizes the problem in a single step. The decision function is the same as that of the OAA technique. The multiclassification objective function constructs c two-class rules, and c decision functions solve the following constraints: w b w b y T y m T m i m i i ϕ ϕ ξ x x i i ( )+ ≥ ( )+ + − 2 , ξi m ≥0 . For reasonable dataset sizes, the accuracy of the different multiclassification techniques is comparable. classof x max w x b i c i T i arg ( ( ) ). ,. . ., ≡ + =1 j For any particular problem, selection of the optimal approach depends partly on the required accuracy and partly on the development and training time goals. For example, from a computational cost perspective, OAA and OAO are quite different. Let’s say, for instance, that there are c different classes of N instances and that T(N1) represents the time for learning one binary classifier. Using N1 examples, OAA will learn in cN 3, whereas OAO will require 4(c – 1)N 3/ c2. Although the SVM parametric model allows for adjustments when constructing the discriminant function, for multiclass problems these parameters do not always fit across the entire dataset. For this reason, it is sometimes preferable to partition the data into subgroups with similar features and derive the classifier parameters separately. This process results in a multistage SVM (MSVM), or hierarchical SVM, which can produce greater generalization accuracy and reduce the likelihood of overfitting, as shown by Stockman (2010). A graphical representation of a single SVM and an MSVM is presented in Figure 3-7. SVM C1 C2 Cn MSVM C1 MSVM C1 C3...Cn C2, C3, … ,Cn Single Multiclass SVM Multistage SVM . . . Figure 3-7. Single multiclass SVM and MSVM flows Single Multiclass SVM Multistage SVM Figure 3-7. Single multiclass SVM and MSVM flows With a multistage approach, different kernel and tuning parameters can be optimized for each stage separately. The first-stage SVM can be trained to distinguish between a single class and the rest of the classes. At the next stage, SVM can tune a different kernel to further distinguish among the remaining classes. Thus, there will be a binary classifier, with one decision function to implement at each stage. Hierarchical SVM as an alternative for multiclass SVM has merit in terms of overall model error. SVM accuracy approaches the Bayes optimal rule as an appropriate kernel choice and in smoothing metaparameter M values. Also, by definition, for a multiclass problem with M ci classes, and an input vector x, i M i P c x =∑( ) = 1 1 \| , because classes should cover all the search space. When the classes being considered are not equiprobable, the maximum P c x i\| ( ) has to be greater than 1/M; otherwise, the sum will be less than 1. classof x max w x b i c i T i arg ( ( ) ). ,. . ., ≡ + =1 j Thus, the cumulative error for the hierarchical task is expected to converge asymptotically to a lower value than with a flat multiclassification task. 2 a lower value than with a flat multiclassification task. a lower value than with a flat multiclassification task. classof x max w x b i c i T i arg ( ( ) ). ,. . ., ≡ + =1 j Let’s say, for example, that the probability of correct classification is P P x R c P c p x c dx c i M i i i M i R i i = ∈ = ( ) ( ) = = ∑ ∑ ∫ 1 1 ( , ) , \| 51 51 Chapter 3 ■ Support Vector Machines for Classification where Ri is the region of the feature space in which the decision is in favor of c i. Because of the definition of region Ri, where Ri is the region of the feature space in which the decision is in favor of c i. Because of the definition of region Ri, P P x c p x dx M p x dx c i M R i i M R i i = ( ) ( ) ≥ ( ) = = ∑∫ ∑∫ 1 1 1 \| , ➩P M c ≥1 ; P P x c p x dx M p x dx c i M R i i M R i i = ( ) ( ) ≥ ( ) = = ∑∫ ∑∫ 1 1 1 \| , hence, the probability of multiclassification error is hence, the probability of multiclassification error is P P M M M e c = − ≤− = − 1 1 1 1. As the number of classes M increases, Pe increases for a multiclassification flat formulation. a hierarchical classification the multiclassification task is reduced at each stage to a binar one As the number of classes M increases, Pe increases for a multiclassification flat formulation. or a hierarchical classification the multiclassification task is reduced at each stage to a binary on As the number of classes M increases, Pe increases for a multiclassification flat formulation. For a hierarchical classification the multiclassification task is reduced at each stage to a binary one, with Pe = 1 2 . Thus, the cumulative error for the hierarchical task is expected to converge asymptotically to e rchical classification the multiclassification task is reduced at each stage to a binary one, For a hierarchical classification the multiclassification task is reduced at each stage to a binary one, with Pe = 1 2 . Thus, the cumulative error for the hierarchical task is expected to converge asymptotically to l l h h fl l l f k with Pe = 1 2 . SVM with Imbalanced Datasets Sensitivity (also called true positive rate [TPR] or recall rate [RR]) is a measure of how well a classification algorithm classifies data points in the positive class: Sensitivity TP TP FN = + . Sensitivity TP TP FN = + . Specificity (also called true negative rate [TNR]) is a measure of how well a classification algorithm classifies data points in the negative class: Specificity TN TN FP = + . Receiver operating characteristic (ROC) curves offer another useful graphical representation for classifiers operating on imbalanced datasets. Originally developed during World War II by radar and electrical engineers for communication purposes and target prediction, ROC is also embraced by diagnostic decision making. Fawcett (2006) provided a comprehensive introduction to ROC analysis, highlighting common misconceptions. p The original SVM formulation did not account for class imbalance during its supervised learning phase. But, follow-up research proposed modifications to the SVM formulation for classifying imbalanced datasets. y g Previous work on SVM addressed class imbalance either by preprocessing the data or by proposing algorithmic modification to the SVM formulation. Kubat (1997) recommended balancing a dataset by randomly undersampling the majority class instead of oversampling the minority class. However, this results in information loss for the majority class. Veropoulos, Campbell, and Cristianini (1999) introduced different loss functions for the positive and negative classes to penalize the misclassification of minority data points. Tax and Ruin (1999) solved the class imbalance by using the support vector data description (SVDD), which aims at finding a sphere that encompasses the minority class and separates it from the outliers as optimally as possible. Feng and Williams (1999) suggested general scaled SVM (GS-SVM), another variation of SVM, which introduces a translation of the hyperplane after training the SVM. The translation distance is added to the SVM formulation; translation distance is computed by projecting the data points on the normal vector of the trained hyperplane and finding the distribution scales of the whole dataset (Das 2012). Chang and Lin (2011) proposed weighted scatter degree SVM (WSD-SVM), which embeds the global information in the GS-SVM by using the scatter of the data points and their weights, based on their location. Many efforts have been made to learn imbalanced data at the level of both the data and the algorithm. SVM with Imbalanced Datasets In many real-life applications and nonsynthetic datasets, the data are imbalanced; that is, the important class—usually referred to as the minority class—has many fewer samples than the other class, usually referred to as the majority class. Class imbalance presents a major challenge for classification algorithms whenever the risk loss for the minority class is higher than for the majority class. When the minority data points are more important than the majority ones, and the main goal is to classify those minority data points correctly, standard machine learning that is geared toward optimized overall accuracy is not ideal; it will result in hyperplanes that favor the majority class and thus generalize poorly. When dealing with imbalanced datasets, overall accuracy is a biased measure of classifier goodness. Instead, the confusion matrix, and the information on true positive (TP) and false positive (FP) that it holds, are a better indication of classifier performance. Referred to as matching matrix in unsupervised learning, and as error matrix or contingency matrix in fields other than machine learning, a confusion matrix provides a visual representation of actual versus predicted class accuracies. ACCURACY METRICS A confusion matrix is as follows: Predicted/Actual Class Positive Class Negative Class Positive Class TP FP Negative Class FN TN Accuracy is the number of data points correctly classified by the classification algorithm: Accuracy TP TN TP TN FN FP = + + + + . Th iti l i th l th t i f t t i t t th d i d ll i th ACCURACY METRICS ACCURACY METRICS Accuracy is the number of data points correctly classified by the classification algorithm: The positive class is the class that is of utmost importance to the designer and usually is the minority class. 52 Chapter 3 ■ Support Vector Machines for Classification True positive (TP) (also called recall in some fields) is the number of data points correctly classified from the positive class. False positive (FP) is the number of data points predicted to be in the positive class but in fact belonging to the negative class. True negative (TN) is the number of data points correctly classified from the negative class. False negative (FN) is the number of data points predicted to be in the negative class but in fact belonging to the positive class. Chapter 3 ■ Support Vector Machines for Classification Chapter 3 ■ Support Vector Machines for Classification resampling methods outperform the known oversampling methods. The synthetic minority oversampling technique (SMOTE) algorithm (Chawla et al. (2002) oversamples the minority class by introducing artificial minority samples between a given minority data point and its nearest minority neighbors. Extensions of the SMOTE algorithm have been developed, including one that works in the distance space (Koknar-Tezel and Latecki 2010). Cost-sensitive methods for imbalanced data learning have also been used. These methods define a cost matrix for misclassifying any data sample and fit the matrix into the classification algorithm (He and Garcia 2009). Tax and Duin (2004) put forward the one-class SVM, which tends to learn from the minority class only. The one-class SVM aims at estimating the probability density function, which gives a positive value for the elements in the minority class and a negative value for everything else. By introducing a multiplicative factor z to the support vector of the minority class, Imam, Ting, and Kamruzzaman (2006) posited that the bias of the learned SVM will be reduced automatically, without providing any additional parameters and without invoking multiple SVM trainings. Akbani, Kwek, and Japkowicz (2004) proposed an algorithm based on a combination of the SMOTE algorithm and the different error costs for the positive and negative classes. Wang and Japkowicz (2010) also aggregated the different penalty factors as well as using an ensemble of SVM classifiers to improve the error for a single classifier and treat the problem of the skewed learned SVM. In an attempt to improve classification of imbalanced datasets using SVM standard formulation, Ajeeb, Nayal, and Awad (2013) suggested a novel minority SVM (MinSVM), which, with the addition of one constraint to the SVM objective function, separates boundaries that are closer to the majority class. Consequently, the minority data points are favored, and the probability of being misclassified is smaller. SVM with Imbalanced Datasets Preprocessing the data before learning the classifier was done through oversampling of the minority class to balance the class distribution by replication or undersampling of the larger class, which balances the data by eliminating samples randomly from that class (Kotsiantis, Kanellopoulos, and Pintelas 2006). Tang et al. (2009) recommended the granular SVM repetitive undersampling (GSVM-RU) algorithm, which, instead of using random undersampling of the majority class to obtain a balanced dataset, uses SVM itself—the idea being to form multiple majority information granules, from which local majority support vectors are extracted and then aggregated with the minority class. Another resampling method for learning classifiers from imbalanced data was suggested by Ou, Hung, and Oyang (2006) and Napierała, Stefanowski, and Wilk (2010). These authors concluded that only when the data suffered severely from noise or borderline examples would their proposed 53 Improving SVM Computational Requirements 2006) were developed on various parallel programming platforms, including graphics processing unit (GPU) (Catanzaro et al. 2008), Hadoop MapReduce (Alham et al. 2010), and message passing interface (MPI) (Cao et al 2006) of SMO (Zeng et al. 2008; Peng, Ma, and Hong 2009; Catanzaro et al. 2008; Alham et al. 2010; Cao et al. 2006) were developed on various parallel programming platforms, including graphics processing unit (GPU) (Catanzaro et al. 2008), Hadoop MapReduce (Alham et al. 2010), and message passing interface (MPI) (Cao et al. 2006). Using the Cholesky factorization (Gill and Murray 1974), Fine (2002) approximated the kernel matrix by employing a low-rank matrix that requires updates that scale linearly with the training set size. The matrix is then fed to a QP solver to obtain an approximate solution to the SVM classification problem. Referred to as the Cholesky product form QP, this approach showed significant training time reduction, with its approximation of the optimal solution provided by SMO. However, if the training set contains redundant features, or if the support vectors are scaled by a large value, this method fails to converge (Fine and Scheinberg 2002). Instead of decomposing the optimization problem, Lee (2001a) reformulated the constraint optimization as an unconstrained, smooth problem that can be solved using the Newton-Armijo algorithm in quadratic time. This reformulation resulted in improved testing accuracy of the standard SVM formulation (Vapnik 1999) on several databases (Lee 2001). Furthermore, Lee (2001) argued that this reformulation allows random selection of a subset of vectors and forces creation of more support vectors, without greatly affecting the prediction accuracy of the model. Margin vectors were identified by Kong and Wang (2010) by computing the self and the mutual center distances in the feature space and eliminating the statistically insignificant points, based on the ratio and center distance of those points. The training set was forced to be balanced, and results were compared with those found using reduced SVM (RSVM) on three datasets from the University of California, Irvine, Machine Learning Repository (Frank and Asuncion 2010). The authors found that the model resulted in better generalization performance than with RSVM but that it required slightly more training time, owing to the overhead of computing the ratios and center distances. Zhang (2008) identified boundary vectors, using the k-nearest neighbors (k-NN algorithm. Improving SVM Computational Requirements Despite the robustness and optimality of the original SVM formulation, SVMs do not scale well computationally. Suffering from slow training convergence on large datasets, SVM online testing time can be suboptimal; SVMs write the classifier hyperplane model as a sum of support vectors whose number cannot be estimated ahead of time and may total as much as half the datasets. Thus, it is with larger datasets that SVM fails to deliver efficiently, especially in the case of nonlinear classification. Large datasets impose heavy computational time and storage requirements during training, sometimes rendering SVM even slower than ANN, itself notorious for slow convergence. For this reason, support vector set cardinality may be a problem when online prediction requires real-time performance on platforms with limited computational and power supply capabilities, such as mobile devices. Many attempts have been made to speed up SVM. A survey related to SVM and its variants reveals a dichotomy between speedup strategies. The first category of techniques applies to the training phase of the SVM algorithm, which incurs a heftier computational cost in its search for the optimal separator. The intent of these algorithms is to reduce the cardinality of the dataset and speed up the optimization solver. The second category of techniques aims to accelerate the testing cycle. With the proliferation of power-conscious mobile devices, and the ubiquity of computing pushed from the cloud to these terminals, reducing the SVM testing cycle can be useful in applications in which computational resources are limited and real-time prediction is necessary. For example, online prediction on mobile devices would greatly benefit from reducing the computations required to perform a prediction. To reduce the computational complexity of the SVM optimization problem, Platt (1998) developed the sequential minimal optimization (SMO) method, which divides the optimization problem into two quadratic program (QP) problems. This decomposition relieves the algorithm of large memory requirements and makes it feasible to train SVM on large datasets. Therefore, this algorithm grows alternately linearly and quadratically, depending on dataset size. SMO speeds up the training phase only, with no control over the number of support vectors or testing time. To achieve additional acceleration, many parallel implementations 54 Chapter 3 ■ Support Vector Machines for Classification of SMO (Zeng et al. 2008; Peng, Ma, and Hong 2009; Catanzaro et al. 2008; Alham et al. 2010; Cao et al. Improving SVM Computational Requirements With this method the distance between each vector and all other vectors is computed, and the vectors that have among their k-NN a vector of opposing class are retained. For linearly nonseparable problems, k-NN is applied in the kernel space, where the dataset is linearly separable. The preextract boundary vectors are used to train SVM. Because this subset is much smaller than the original dataset, training will be faster, and the support vector set will be smaller. Downs, Gates, and Masters (2002) attempted to reduce the number of support vectors used in the prediction stage by eliminating vectors from the support vector set produced by an SMO solver that are linearly dependent on other support vectors. Hence, the final support vector set is formed of all linearly independent support vectors in the kernel space obtained by using row-reduced echelon form. Although this method produced reduction for polynomial kernels, and RBF with large sigma values, the number of, support vectors reduced could not be predicted ahead of time and was dependent on the kernel and the problem. Nguyen (2006) reduced the support vector set by iteratively replacing the two nearest support vectors belonging to the same class, using a constructed support vector that did not belong to the original training set. The algorithm was applied after training the SVM on the training set and obtaining the support vector set. The algorithm was tested on the United States Postal Service database (Le Cun 1990) and achieved significant reduction in support vector set cardinality, with little reduction in prediction accuracy. Rizk, Mitri, and Awad (2013) proposed a local mixture–based SVM (LMSVM), which exploits the increased separability provided by the kernel trick, while introducing a one-time computational cost. LMSVM applies kernel k-means clustering to the data in kernel space before pruning unwanted clusters, based on a mixture measure for label heterogeneity. Extending this concept, Rizk, Mitri, and Awad (2014) put forward knee-cut SVM (KCSVM) and knee-cut ordinal optimization–inspired SVM (KCOOSVM), with a soft trick of ordered kernel values and uniform subsampling to reduce the computational complexity of SVM, while maintaining an acceptable impact on its generalization capability. 55 55 Chapter 3 ■ Support Vector Machines for Classification Case Study of SVM for Handwriting Recognition Automated handwriting recognition (HWR) is becoming popular in several offline and online sensing tasks. Developing robust yet computationally efficient algorithms is still a challenging problem, given the increased awareness of energy-aware computing. Offline sensing occurs by optically scanning words and then transforming those images to letter code usable in the computer software environment. Online recognition automatically converts the writing on a graphics tablet or pen-based computer screen into letter code. HWR systems can also be classified as writer dependent or writer independent, with dependent systems’ having a higher recognition rate, owing to smaller variance in the provided data. Because isolated-letter HWR is an essential step for online HWR, we present here a case study on developing an efficient writer-independent HWR system for isolated letters, using pen trajectory modeling for feature extraction and an MSVM for classification (Hajj and Awad 2012). In addition to underlining the importance of the application, this case study illustrates how stationary features are created from sequential data and how a multiclass task is converted into a hierarchical one. Usually, hidden Markov models (HMM) are better for modeling and recognizing sequential data, but with an appropriate feature generation scheme, an SVM model can be used to model variable sequence length for moderate handwriting vocabularies. The proposed HWR workflow is composed of preprocessing; feature extraction; and a hierarchical, three-stage classification phase. where Dx, Dy, and Ds are defined as where Dx, Dy, and Ds are defined as where Dx, Dy, and Ds are defined as ∆x t x t x t ( ) = − ( )− + ( ) 1 1 , ∆y t y t y t ( ) = − ( )− + ( ) 1 1 , ∆ ∆ ∆ s t x t y t ( ) = ( ) + ( ) 2 2 . • Curvature: Defined by the sine and cosine of the angle defined by the points (x(t - 2), y(t - 2)); (x(t), y(t)); and (x(t + 2), y(t + 2)). Curvature can be calculated from the writing direction, using the following equations: • Curvature: Defined by the sine and cosine of the angle defined by the points (x(t - 2), y(t - 2)); (x(t), y(t)); and (x(t + 2), y(t + 2)). Curvature can be calculated from the writing direction, using the following equations: cos cos cos sin sin , b a a a a t t t t t ( ) = − ( ) + ( )+ − ( ) + ( ) 1 1 1 1 sinb a a a a t t t t t ( ) = − + ( )− − + cos ( )sin sin ( )cos ( ). 1 1 1 1 • Aspect of the trajectory: Computed according to the equation • Aspect of the trajectory: Computed according to the equation A t y t x t y t x t ( ) = ( )− ( ) ( ) ( )+ ( ) ( ) ∆ ∆ ∆ ∆ . • Curliness: Describes the deviation of the points from a straight line formed by the previous and following points in the sequence by the equation C t L t x y ( ) = ( )− ( )/ , , max ∆ ∆ 2 where L(t) represents the length of the trajectory from point (x(t - 1), y(t - 1)) to point (x(t + 1), y(t + 1)). In addition to the previous functions, the following global features are computed: • Linearity: Measured by the average distance from each point of the sequence to the straight line joining the first and last points in the sequence: LN N di = ∑ 1 . Preprocessing The UJIpenchars database can be transformed into a sequence of points suitable for feature extraction in a way similar to preprocessing performed a step typically found in many HWR systems. The preprocessing comprises correcting the slant; normalizing the dimensions of the letter; and shifting the coordinates, with respect to the center of mass. To correct the slant, the input, consisting of a sequence of collected points, is first written in the form of a series of vectors with polar coordinates, and then only vectors with an angle equal to or less than 50 degrees with the vertical are considered. The slant is computed by averaging the angles of the significant vectors. Next, the letter is rotated by the slant angle, and the data are normalized so that all letters have the same dimensions. Finally, the shifting of the coordinates, with respect to the center of mass, fits the letter into a square of unit dimension with a centroid with the coordinates (0, 0). Figure 3-8 shows two letters before (left) and after (right) the preprocessing stage. Figure 3-8. Examples of letters before (left) and after (right) preprocessing Figure 3-8. Examples of letters before (left) and after (right) preprocessing 56 56 Chapter 3 ■ Support Vector Machines for Classification Feature Extraction To obtain different representations of the letters, a set of feature vectors of fixed length should be computed. The preprocessed data, consisting of strokes of coordinate pairs [x(t), y(t)], can be modeled, using a pen trajectory technique (Jaeger 2008), and the set of features is obtained after averaging the following functions: • Writing direction: Defined by cos ; sin , a a t x t s t t y t s t ( ) = ( ) ( ) ( ) = ( ) ( ) ∆ ∆ ∆ ∆ Using OAA SVM, with a simple majority vote, the third stage identifies the letter • as one of the 52 classes (or subclusters). Figure 3-9 displays the hierarchy of the three-stage system. Chapter 3 ■ Support Vector Machines for Classification • Cumulative distance: The sum of the length of the segments of line joining consecutive points of the sequence. • Average distance to the center, The mean of the distances from each point of the sequence to the center of mass of the letter. where Dx, Dy, and Ds are defined as • Slope of the sequence: Measured by the cosine and sine of the angle formed by the straight line joining the first and last points in the sequence and a horizontal line. • Ascenders and descenders: Describes the number of points of the sequence below (descenders) or above (ascenders) the baseline (the straight horizontal line on which the letter is written), each weighted by its distance to the baseline. • Variance of coordinates (for both dimensions): Measures the expansion of the points around the center of mass. • Ratio of variances: Represents the proportion of the width to the height of the letter. 57 57 Chapter 3 ■ Support Vector Machines for Classification Chapter 3 ■ Support Vector Machines for Classification Chapter 3 ■ Support Vector Machines for Classification Input letter Lower or Upper Case Lower case Upper case C1 - C8? C9 - C15? C 2 . . . C 10 C 15 . . . a, e, c, o? a e c o . . . A, B, P, R? A B R . . . STAGE 1 SVM P STAGE 2 SVM STAGE 3 SVM . . . C 1 . . . C 9 Output letter C 8 Figure 3-9. Hierarchical, three-stage SVM Input letter Lower or Upper Case Lower case Upper case C1 - C8? C9 - C15? C 2 . . . C 10 C 15 . . . a, e, c, o? a e c o . . . A, B, P, R? A B R . . . STAGE 1 SVM P STAGE 2 SVM STAGE 3 SVM . . . C 1 . . . C 9 Output letter C 8 Figure 3-9. Hierarchical, three-stage SVM Experimental Results Experimental results, implemented with the MATLAB R2011a SVM toolbox, showed (using a four-fold cross-validation) an average accuracy of 91.7 percent—or, an error rate of 8.3 percent, compared with an error rate of 10.85 percent, using 3NN (Prat et al. 2009). The three stages of the classifier achieved, respectively, 99.3 percent, 95.7 percent, and 96.5 percent accuracy. The kernel used for the three stages was an RBF with parameters tuned using a grid search algorithm. Our proposed preprocessing helped improve the general accuracy of the recognizer by approximately 1.5 percent to 2 percent. Figure 3-10 presents a confusion histogram demonstrating the occurrence of the predicted classified labels, along with their true labels. For example, in the first column, of the six letter a’s, five were correctly recognized, and one was mistaken for c. Generally, no particular trend was observed in this confusion matrix, and the error may be assumed to be randomly distributed among all classes. Lower or Upper Case Figure 3-9. Hierarchical, three-stage SVM Figure 3-9. Hierarchical, three-stage SVM Hierarchical, Three-Stage SVM After the preprocessing and feature extraction stages, a three-stage classifier recognizes one of the 52 classes (26 lowercase and 26 uppercase letters). Using a binary SVM classifier, the first stage classifies the instance as one of two • classes: uppercase or lowercase letter. Using OAA SVM, the second stage classifies the instance as one of the manually • determined clusters shown in Table 3-1. Table 3-1. Lower- and Uppercase Clusters Table 3-1. Lower- and Uppercase Clusters Lowercase Clusters Uppercase Clusters Cluster 1: a c e o Cluster 2: b d l t Cluster 3: f h k Cluster 4: g z j Cluster 5: p q Cluster 6: i r s Cluster 7: u v w x Cluster 8: m n Cluster 9: A B P R Cluster 10: C D G O Q Cluster 11: E F I L Cluster 12: J K T Cluster 13: M N H Cluster 14: S Y Z X Cluster 15: U V W 58 58 Experimental Results Experimental results, implemented with the MATLAB R2011a SVM toolbox, showed (using a four-fold cross-validation) an average accuracy of 91.7 percent—or, an error rate of 8.3 percent, compared with an error rate of 10.85 percent, using 3NN (Prat et al. 2009). The three stages of the classifier achieved, respectively, 99.3 percent, 95.7 percent, and 96.5 percent accuracy. The kernel used for the three stages was an RBF with parameters tuned using a grid search algorithm. Our proposed preprocessing helped improve the general accuracy of the recognizer by approximately 1.5 percent to 2 percent. Figure 3-10 presents a confusion histogram demonstrating the occurrence of the predicted classified labels, along with their true labels. For example, in the first column, of the six letter a’s, five were correctly recognized, and one was mistaken for c. Generally, no particular trend was observed in this confusion matrix, and the error may be assumed to be randomly distributed among all classes. 59 59 Chapter 3 ■ Support Vector Machines for Classification Figure 3-10. Confusion plot for classified label versus true label Figure 3-10. Confusion plot for classified label versus true label Because a flat SVM architecture may seem computationally less expensive, it was compared with the proposed three-stage SVM, using OAO and OAA SVM techniques. Table 3-2 shows the recognition rates obtained using the proposed architecture, compared with a flat SVM technique as well as the3NN algorithm. The accuracy attained ranged from 65 percent, using OAA, to 82 percent, using OAO, whereas the hierarchical SVM structure reached 91.7 percent. This is due to the fact that, with a three-stage SVM, both the metaparameters of SVM (i.e., the regularization parameter between the slack and hyperplane parameters) and the kernel specifics can be better modified independently during each phase of training and better tailored to the resulting data subsets than a flat SVM model can be for the whole dataset. Table 3-2. Recognition Rate Comparison Architecture Recognition Rate (%) Flat SVM OAA 65 Flat SVM OAO 82 3NN (Prat et al. 2009) 89.15 Three-Stage SVM 91.8 Table 3-2. Recognition Rate Comparison 60 Chapter 3 ■ Support Vector Machines for Classification Complexity Analysis Tables 3-3 and 3-4, respectively, provide the required operations for the preprocessing and feature extraction stages of the three-stage SVM, where a letter is represented by a sequence of strokes of length N, with M being the number of significant vectors, and K, the data size. Table 3-3. Required Operations for the Preprocessing Stage Step Total Operations Representing letter in a sequence of vector 8N Computing slant M + 1 Rotating letter N Normalizing dimensions 2N Shifting to center of mass 4N + 2 Table 3-3. Required Operations for the Preprocessing Stage Table 3-4. Required Operations for the Feature Extraction Stage Feature Total Operations Writing direction 7N Curvature 6N Aspect 2N Curliness 14N Linearity 6N + 1 Slope 7 Ascenders and descenders 6N Variance 8N + 4 Ratio of variances 1 Cumulative distance 5N - 5 Average distance 4N Table 3-5 compares the required operations for the classification process using three-stage SVM and the 3NN algorithm . Both SVM optimal hyperplane coefficients and support vectors were computed during the training process. Given an input pattern represented by a multidimensional (11) vector x and a w vector representing the decision boundary (hyperplane), the decision function for the classification phase is reduced to a sign function. 61 61 Chapter 3 ■ Support Vector Machines for Classification Table 3-5. Comparison of Three-Stage SVM and 3NN Classifiers Classifier Decision Function Total Operations Three-Stage SVM C w w x x T ( ) = + 0 12 operations per classifier; in total, 168 operations (the class requiring the most classifiers) 3NN (Prat et al. 2009) D x z x z x z , ... ( ) = − ( ) + + − ( ) 1 1 2 50 50 2 150 operations per distance measure; in total, 3 50 * K = 150 * K Table 3-5. Comparison of Three-Stage SVM and 3NN Classifiers 12 operations per classifier; in total, 168 operations (the class requiring the most classifiers) 150 operations per distance measure; in total, 3 50 * K = 150 * K The online classification task is much costlier using a 3NN classifier compared with a hierarchical SVM. In fact, every classification task requires the Euclidian distance calculation to all points in the dataset, which would be an expensive cost to incur in the presence of a large dataset. Complexity Analysis Additionally, with the lack of a classification model, the k-NN technique is a non parametric approach and requires access to all the data each time an instance is recognized. With SVM, in contrast, separating class boundaries is learned offline, during the training phase, and at runtime the computational cost of SVM training is not present. Only preprocessing, feature extraction, and a simple multiplication operation with the hyperplane parameters are involved in the online testing process. An advantage of 3NN, however, is that no training is required, as opposed to the complex SVM classification step. References Aizerman, M., E. Braverman, and L. Rozonoer. “Theoretical Foundations of the Potential Function Method in Pattern Recognition Learning.” Automation and Remote Control 25 (1964): 821–837. Ajeeb, N., A. Nayal, and M. Awad. “Minority SVM for Linearly Separable and Imbalanced Datasets.” In IJCNN 2013: Proceedings of the 2013 International Joint Conference on Neural Networks, 1–5. Piscataway, NJ: Institute for Electrical and Electronics Engineers, 2013. Akbani, Rehan, Stephen Kwek, and Nathalie Japkowicz. “Applying Support Vector Machines to Imbalanced Datasets.” In Machine Learning: ECML 2004: 15th European Conference on Machine Learning, Pisa, Italy, September 2004 edited by Jean François Boulicaut Floriana Esposito Fosca Giannotti and Dino Pedreschi Akbani, Rehan, Stephen Kwek, and Nathalie Japkowicz. “Applying Support Vector Machines to Imbalanced Datasets.” In Machine Learning: ECML 2004: 15th European Conference on Machine Learning, Pisa, Italy, September 2004, edited by Jean-François Boulicaut, Floriana Esposito, Fosca Giannotti, and Dino Pedreschi, 39–50. Berlin: Springer, 2004. Datasets.” In Machine Learning: ECML 2004: 15th European Conference on Machine Learning, Pisa, Italy, September 2004, edited by Jean-François Boulicaut, Floriana Esposito, Fosca Giannotti, and Dino Pedreschi, 39–50. Berlin: Springer, 2004. Alham, N. K., Maozhen Li, S. Hammoud, Yang Liu, and M. Ponraj. “A Distributed SVM for Image Annotation.” In FSKD 2010: Proceedings of the Seventh International Conference on Fuzzy Systems and Knowledge Discovery, edited by Maozhen Li, Qilian Liang, Lipo Wang and Yibin Song, 2983–2987. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2010. Aronszajn, N. “Theory of Reproducing Kernels.” Transactions of the American Mathematical Society 68, no. 3 (1950): 337–404. Bartlett, P. and J. Shawe-Taylor, “Generalization Performance of Support Vector Machines and Other Pattern Classifiers”, Advances in Kernel Methods: Support Vector Learning, 1999. Ben-Hur, Asa, and Jason Weston. “A User’s Guide to Support Vector Machines.” Data Mining Techniques for Life Sciences, edited by Oliviero Carugo and Frank Eisenhaber, 223-239. New York: Springer, 2010. Bennett, Kristen P., and O. L. Mangasarian. “Robust Linear Programming Discrimination of Two Linearly Inseparable Sets.” Optimization Methods and Software 1, no. 1: (1992): 23–34. Boser, Bernard E., Isabelle M. Guyon, and Vladimir N. Vapnik. “A Training Algorithm for Optimal Margin Classifiers.” In COLT ’92: Proceedings of the Fifth Annual Workshop on Computational Learning Theory, edited by David Haussler, 144–152. New York: ACM, 1992. 62 Chapter 3 ■ Support Vector Machines for Classification Cao, L. J., S. S. Keerthi, Chong-Jin Ong, J. Q. Zhang, U. Periyathamby, Xiu Ju Fu, and H. P. Lee. References “Parallel Sequential Minimal Optimization for the Training of Support Vector Machines.” IEE Transactions on Neural Networks 17, no. 4 (2006): 1039–1049. Catanzaro, Bryan Christopher, Narayanan Sundaram, and Kurt Keutzer. “Fast Support Vector Machine Training and Classification on Graphics Processors.” In ICML ’08: Proceedings of the 25th International Conference on Machine Learning, edited by William Cohen, Andrew McCallum, and Sam Roweis, 104–111. New York: ACM, 2008. Training and Classification on Graphics Processors.” In ICML ’08: Proceedings of the 25th International Conference on Machine Learning, edited by William Cohen, Andrew McCallum, and Sam Roweis, 104–111. New York: ACM, 2008. Chang, Chih-Chung, and Chih-Jen Lin. “LIBSVM: A Library for Support Vector Machines,” in “Large-Scale Machine Learning,” edited by Huan Liu and Dana Nau, special issue, ACM Transactions on Intelligent Systems and Technology 2, no. 3 (2011). Chawla, Nitesh V., Kevin W. Bowyer, Lawrence O. Hall, and W. Philip Kegelmeyer. “SMOTE: Synthetic Minority Over-Sampling Technique.” Journal of Artificial Intelligence Research 16 (2002): 321–357. Cover, Thomas M. “Geometrical and Statistical Properties of Systems of Linear Inequalities with Applications in Pattern Recognition.” IEEE Transactions on Electronic Computers 14 (1995): 326–334. Das, Barnan. “Implementation of SMOTEBoost Algorithm Used to Handle Class Imbalance Problem in Data,” 2012. www.mathworks.com/matlabcentral/fileexchange/37311-smoteboost. Downs, Tom, Kevin E. Gates, and Annette Masters. “Exact Simplification of Support Vector Solutions.” Journal of Machine Learning Research 2 (2002): 293–297. Duda, Richard O., and Peter E. Hart. Pattern Classification and Scene Analysis. New York: Wiley, 1973. Fawcett, Tom. “An Introduction to ROC Analysis. “Pattern Recognition Letters 27 (2006): 861–874. Feng, Jianfeng, and P. Williams. “The Generalization Error of the Symmetric and Scaled Support Vector Machines.” IEEE Transactions on Neural Networks 12, no. 5 (1999): 1255–1260. Fine, Shai, and Katya Scheinberg. “Efficient SVM Training Using Low-Rank Kernel Representations.” Journal of Machine Learning Research 2 (2002): 243–264. Fisher, Marshall L. “The Lagrangian Relaxation Method for Solving Integer Programming Problems. “Management Science 50, no. 12 (2004):1861–1871. Frank, A., and A. Asuncion. University of California, Irvine, Machine Learning Repository. Irvine: University of California, 2010. www.ics.uci.edu/`mlearn/MLRepository.html. Friedman, J. “Another Approach to Polychotomous Classification.” Technical report, Stanford University, 1996. Hajj, N., and M. Awad.” Isolated Handwriting Recognition via Multi-Stage Support Vector Machines.” In Proceedings of the 6th IEEE International Conference on Intelligent Systems,” edited by Vladimir Jotsov, Krassimir Atanassov, 152–157. Piscataway, NJ: Institute for Electrical and Electronic Engineers, 2012. He, Heibo, and Edwardo A. Garcia. References “Learning from Imbalanced Data.” IEEE Transactions on Knowledge and Data Engineering 21, no. 9(2009):1263–1284. Gill, Philip E., and Walter Murray. “Newton-Type Methods for Unconstrained and Linearly Constrained Optimization.” Mathematical Programming 7 (1974): 311–350. Imam, Tasadduq, Kai Ming Ting, and Joarder Kamruzzaman. “z-SVM: An SVM for Improved Classification of Imbalanced Data.” In AI 2006: Advances in Artificial Intelligence; Proceedings of the 19th Australian Joint Conference on Artificial Intelligence, Hobart, Australia, December 4–8, 2006, edited by Abdul Sattar and Byeong-Ho Kang, 264–273, 2006. Berlin: Springer, 2006. S. Jaeger, S. Manke, J. Reichert, A. Waibel, “Online Handwriting Recognition: the NPen++ Recognizer”, International Journal on Document Analysis and Recognition, vol.3, no.3, 169-180, March 2008. 63 Chapter 3 ■ Support Vector Machines for Classification Jin, A-Long, Xin Zhou, and Chi-Zhou Ye. “Support Vector Machines Based on Weighted Scatter Degree.” In Artificial Intelligence and Computational Intelligence: Proceedings of the AICI Third International Conference, Taiyuan, China, September 24–25, 2011, Part III, edited by Hepu Deng, Duoqian Miao, Jingsheng Lei, and Fu Lee Wang, 620–629. Berlin: Springer, 2011. Karush, William. “Minima of Functions of Several Variables with Inequalities as Side Constraints.” Master’s thesis, University of Chicago, 1939. Knerr, S., L. Personnaz, and G. Dreyfus. “Single-Layer Learning Revisited: A Stepwise Procedure for Building and Training a Neural Network.” In Neurocomputing: Algorithms, Architectures and Applications; NATO Advanced Workshop on Neuro-Computing, Les Arcs, Savoie, France, 1989, edited by Françoise Fogelman Soulié and Jeanny Hérault, 41–50. Berlin: Springer, 1990. Koknar-Tezel, S., and L. J. Latecki. “Improving SVM Classification on Imbalanced Data Sets in Distance Spaces.” In ICDM ’09: Proceedings of the Ninth IEEE International Conference on Data Mining, edited by Wei Wang, Hillol Kargupta, Sanjay Ranka, Philip S. Yu, and Xindong Wu, 259–267. Piscataway, NJ: Institute for Electrical and Electronics Engineers, 2010. Kong, Bo, and Hong-wei Wang. “Reduced Support Vector Machine Based on Margin Vectors.” In CiSE 2010 International Conference on Computational Intelligence and Software Engineering,” 1–4. Piscataway, NJ: Institute for Electrical and Electronic Engineers, 2010. Kotsiantis, Sotiris, Dimitris Kanellopoulos, and Panayiotis Pintelas. “Handling Imbalanced Datasets: A Review.”GESTS International Transactions on Computer Science and Engineering 30, no. 1 (2006): 25–36. Kressel, Ulrich H.-G. “Pairwise Classification and Support Vector Machines.” In Advances in Kernel Methods: Support Vector Learning, edited by Bernhard Schölkopf, Christopher J. C. Burges, and Alexander J. Smola, 255–268. Cambridge, MA: Massachusetts Institute of Technology Press, 1999. Kuhn, H. W., and A. W. Tucker. References “Nonlinear Programming.” In Proceedings of the Second Berkeley Symposium on Mathematical Statistics and Probability, edited by Jerzy Neyman, 481–492. Berkeley: University of California Press, 1951. Le Cun, Y., B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard and L. D. Jackel. “Handwritten Digit Recognition with a Back-Propagation Network.” In Advances in Neural Information Processing Systems, edited by D. S. Touretzky, 396–404. San Mateo, CA: Morgan Kaufmann, 1990. Lee, Yuh-Jye, and O. L. Mangasarian. “SSVM: A Smooth Support Vector Machine for Classification.” Computational Optimization and Applications 20 (2001a): 5–22. Lee, Yuh-Jye, and Olvi L. Mangasarian. “RSVM: Reduced Support Vector Machines.” In Proceedings of the First SIAM International Conference on Data Mining, edited by Robert Grossman and Vipin Kumar, 5–7. Philadelphia: Society for Industrial and Applied Mathematics, 2001b . Liu, Xin, and Ying Ding. “General Scaled Support Vector Machines.” In ICMLC 2011: Proceedings of the 3rd International Conference on Machine Learning and Computing. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2011. Mangasarian, O. L. “Linear and Nonlinear Separation of Patterns by Linear Programming.” Operations Research 13, no. 3 (1965): 444–452. Meyer, David, Friederich Leisch, and Kurt Hornik.” The Support Vector Machine Under Test.” Neurocomputing 55, nos. 1–2 (2003): 169–186. Napierała, Krystyna, Jerzy Stefanowski, and Szyman Wilk. “Learning from Imbalanced Data in Presence of Noisy and Borderline Examples.” In Rough Sets and Current Trends in Computing: Proceedings of the 7th RSCTC International Conference, Warsaw, Poland, June 2010,edited by Marcin Szczuka, Marzena Kryszkiewicz, Sheela Ramanna, Richard Jensen, and Qinghua Hu, 158–167. Berlin: Springer, 2010. 64 Chapter 3 ■ Support Vector Machines for Classification Nguyen, Duc Dung, and Tuo Bao Ho. “A Bottom-Up Method for Simplifying Support Vector Solutions.” IEEE Transactions on Neural Networks. 17, no. 3 (2006): 792–796. Ou, Yu-Yen, Hao-Geng Hung, and Yen-Jen Oyang, “A Study of Supervised Learning with Multivariate Analysis on Unbalanced Datasets.” In IJCNN ’06: Proceedings of the 2006 International Joint Conference on Neural Networks, 2201–2205. Piscataway, NJ: Institute for Electrical and Electronic Engineers, 2006. Peng, Peng, Qian-Lee Ma, and Lei-Ming Hong. “The Research of the Parallel SMO Algorithm for Solving SVM.” In ICMLC 2009: Proceedings of the 2009 International Conference on Machine Learning and Cybernetics, 1271–1274. Piscataway, NJ: Institute for Electrical and Electronics Engineers, 2009. Platt, John C. “Sequential Minimal Optimization: A Fast Algorithm for Training Support Vector Machines.” Technical report MSR-TR-98-14, 1998. Platt, John C., Nello Cristianini, and John Shawe-Taylor. References “Large Margin DAGs for Multiclass Classification.” In Advances in Neural Information Processing Systems 12 (NIPS ‘99), edited S. A. Solla, T. K. Leen, and K.-R. Müller, 547–553. Cambridge, MA: Massachusetts Institute of Technology Press, 2000. Poggio, Tomaso, and Federico Girosi. “Networks for Approximation and Learning.” Proceedings of the IEEE 78, no. 9 (1990): 1481–1497. Prat, Federico, Andrés Marzal, Sergio Martín, Rafael Ramos-Garijo, and María José Castro. “A Template- Based Recognition System for On-line Handwritten Characters.” Journal of Information Science and Engineering 25 (2009): 779–791. Rizk, Y., N. Mitri, and M. Awad. “A Local Mixture Based SVM for an Efficient Supervised Binary Classification.” In IJCNN 2013: Proceedings of the International Joint Conference on Neural Networks, 1–8. Piscataway, NJ: Institute for Electrical and Electronics Engineers, 2013. Rizk, Y., N. Mitri, and M. Awad. “An Ordinal Kernel Trick for a Computationally Efficient Support Vector Machine.” In IJCNN 2014: Proceedings of the 2014 International Joint Conference on Neural Networks, 3930–3937. Piscataway, NJ: Institute for Electrical and Electronics Engineers, 2014. Schölkopf, B., John C. Platt, John C. Shawe-Taylor, Alex J. Smola, and Robert C. Williamson. “Estimating the Support of a High-Dimensional Distribution.” Neural Computation 13, no. 7 (2001):1443–1471. Smith, F. W. “Pattern Classifier Design by Linear Programming.” IEEE Transactions on Computers, C-17. no. 4 (1968): 367–372. Stockman, M., and M. Awad. “Multistage SVM as a Clinical Decision Making Tool for Predicting Post Operative Patient Status.” IKE ’10: Proceedings of the 2010 International Conference on Information and Knowledge Engineering. Athens, GA: CSREA, 2010. Suykens, J. A. K. Suykens, and J. Vandewalle. “Least Squares Support Vector Machine Classifiers.” Neural Processing Letters 9, no. 3 (1999): 293–300. Tang, Yuchun, Yan-Qing Zhang, Nitesh V. Chawla, and Sven Krasser. “SVMs Modeling for Highly Imbalanced Classification.” Journal of Latex Class Files 1, no. 11 (2002). www3.nd.edu/~dial/papers/SMCB09.pdf. Tang, Yuchun, Yan-Qing Zhang, N. V. Chawla, and Sven Krasser. “SVMs Modeling for Highly Imbalanced Classification.” Systems, Man, and Cybernetics B: IEEE Transactions on Cybernetics 39, no. 1 (2009): 281–288. Tax, David M. J., and Robert P. W. Ruin. “Support Vector Domain Description.” Pattern Recognition Letters 20 (1999): 1191–1199. Tax, David M. J., and Robert P. W. Duin. “Support Vector Data Description.” Machine Learning 54 (2004): 45–66. Vapnik, Vladimir N. The Nature of Statistical Learning Theory. New York: Springer, 1995. Vapnik, Vladimir N. Statistical Learning Theory. New York: Wiley, 1998. 65 65 Chapter 3 ■ Support Vector Machines for Classification Vapnik, Vladimir N. Zhuang, Ling, and Honghua Dai. “Parameter Optimization of Kernel-Based One-Class Classifier on Imbalance Text Learning.” Journal of Computers 1, no. 7 (2006): 32–40. —Jeff Hawkins Rooted in statistical learning or Vapnik-Chervonenkis (VC) theory, support vector machines (SVMs) are well positioned to generalize on yet-to-be-seen data. The SVM concepts presented in Chapter 3 can be generalized to become applicable to regression problems. As in classification, support vector regression (SVR) is characterized by the use of kernels, sparse solution, and VC control of the margin and the number of support vectors. Although less popular than SVM, SVR has been proven to be an effective tool in real-value function estimation. As a supervised-learning approach, SVR trains using a symmetrical loss function, which equally penalizes high and low misestimates. Using Vapnik’s e-insensitive approach, a flexible tube of minimal radius is formed symmetrically around the estimated function, such that the absolute values of errors less than a certain threshold e are ignored both above and below the estimate. In this manner, points outside the tube are penalized, but those within the tube, either above or below the function, receive no penalty. One of the main advantages of SVR is that its computational complexity does not depend on the dimensionality of the input space. Additionally, it has excellent generalization capability, with high prediction accuracy. This chapter is designed to provide an overview of SVR and Bayesian regression. It also presents a case study of a modified SVR applicable to circumstances in which it is critically necessary to eliminate or strictly limit underestimating a function. Support Vector Regression The key to artificial intelligence has always been the representation. References The Nature of Statistical Learning Theory, Second Edition. New York: Springer, 1999. Vapnik, Vladimir N. The Nature of Statistical Learning Theory, Second Edition. New York: Spri Vapnik, V., and A. Chervonenkis. “A Note on One Class of Perceptrons.” Automation and Remote Control 25 (1964). Vapnik, V., and A. Lerner. “Pattern Recognition Using Generalized Portrait Method.” Automation and Remote Control 24 (1963): 774–780. Veropoulos, K., C. Campbell, and N. Cristianini. “Controlling the Sensitivity of Support Vector Machines.” In IJCAI ‘99: Proceedings of the 16th International Joint Conference on Artificial Intelligence, edited by Thomas Dean, 55–60. San Francisco: Morgan Kaufmann, 1999. Wahba, Grace. Spline Models for Observational Data. CBMS-NSF Regional Conference Series in Applied Mathematics 59. Philadelphia: Society for Industrial and Applied Mathematics, 1990. Wang, Benjamin X., and Nathalie Japkowicz. “Boosting Support Vector Machines for Imbalanced Data Sets.” Knowledge and Information Systems 25, no. 1 (2010): 1–20. Weston, J., and C. Watkins. Support Vector Machines for Multi-Class Pattern Recognition. In ESANN 1999: Proceedings of the 7th European Symposium on Artificial Neural Networks, Bruges, Belgium, 21–23 April 1999, 219–224. 1999. https://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es1999-461.pdf. Zeng, Zhi-Qiang, Hong-Bin Yu, Hua-Rong Xu, Yan-Qi Xie, and Ji Gao. “Fast Training Support Vector Machines Using Parallel Sequential Minimal Optimization.” In ISKE 2008: Proceedings of the 3rd International Conference on Intelligent System and Knowledge Engineering, edited by Shaozi Li, Tianrui Li, and Da Ruan, 997–1001. Piscataway, NJ: Institute for Electrical and Electronics Engineers, 2008. Zhang, Li, Ning Ye, Weida Zhou, and Licheng Jiao. “Support Vectors Pre-Extracting for Support Vector Machine Based on K Nearest Neighbour Method.” In ICIA 2008: Proceedings of the 2008 International Conference on Information and Automation, 1353–1358. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2008. Zhang, Xuegong. “Using Class-Center Vectors to Build Support Vector Machines.” Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop, edited by Yu-Hen Hu, Jan Larsen, Elizabeth Wilson, and Scott Douglas, 3–11. Piscataway, NJ: Institute for Electrical and Electronic Engineers, 1999. Zhuang, Ling, and Honghua Dai. “Parameter Optimization of Kernel-Based One-Class Classifier on Imbalance Text Learning.” Journal of Computers 1, no. 7 (2006): 32–40. 66 SVR Overview The regression problem is a generalization of the classification problem, in which the model returns a continuous-valued output, as opposed to an output from a finite set. In other words, a regression model estimates a continuous-valued multivariate function. SVMs solve binary classification problems by formulating them as convex optimization problems (Vapnik 1998). The optimization problem entails finding the maximum margin separating the hyperplane, while correctly classifying as many training points as possible. SVMs represent this optimal hyperplane with support vectors. The sparse solution and good generalization of the SVM lend themselves to adaptation to regression problems. SVM generalization to SVR is accomplished by introducing an e-insensitive region around the function, called the e-tube. This tube reformulates the optimization problem to find the tube that best approximates the continuous-valued function, while balancing model complexity and prediction error. More specifically, SVR is formulated as an optimization problem by first defining a convex e-insensitive loss function to be minimized and finding the flattest tube that contains most of the training instances. Hence, a multiobjective function is constructed from the loss function and the geometrical properties of the tube. 67 67 Chapter 4 ■ Support Vector Regression Then, the convex optimization, which has a unique solution, is solved, using appropriate numerical optimization algorithms. The hyperplane is represented in terms of support vectors, which are training samples that lie outside the boundary of the tube. As in SVM, the support vectors in SVR are the most influential instances that affect the shape of the tube, and the training and test data are assumed to be independent and identically distributed (iid), drawn from the same fixed but unknown probability distribution function in a supervised-learning context. SVR: Concepts, Mathematical Model, and Graphical Representation SVR problem formulation is often best derived from a geometrical perspective, using the one-dimensional example in Figure 4-1. The continuous-valued function being approximated can be written as in Equation 4-1. For multidimensional data, you augment x by one and include b in the w vector to simply the mathematical notation, and obtain the multivariate regression in Equation 4-2. y f x w x b w x b y b x w j j M j M = = < >+ = + ∈ ∈ = ∑ ( ) , , , , ,   1 (4-1) f x w b x w x b x w T T M ( ) , =        = + ∈ + 1 1  (4-2) (4-1) (4-2)   SVR formulates this function approximation problem as an optimization problem that attempts to find the narrowest tube centered around the surface, while minimizing the prediction error, that is, the distance between the predicted and the desired outputs. The former condition produces the objective function in Equation 4-3, where   w is the magnitude of the normal vector to the surface that is being approximated: min . w w 1 2 (4-3) Figure 4-1. One-dimensional linear SVR Figure 4 1 One dimensional linear SVR Figure 4-1. One-dimensional linear SVR SVR formulates this function approximation problem as an optimization problem that attempts to find the narrowest tube centered around the surface, while minimizing the prediction error, that is, the distance between the predicted and the desired outputs. The former condition produces the objective function in Equation 4-3, where   w is the magnitude of the normal vector to the surface that is being approximated: SVR formulates this function approximation problem as an optimization problem that attempts to find the narrowest tube centered around the surface, while minimizing the prediction error, that is, the distance between the predicted and the desired outputs. The former condition produces the objective function in Equation 4-3, where   w is the magnitude of the normal vector to the surface that is being approximated: min . w w 1 2 2 (4-3) (4-3) min . SVR: Concepts, Mathematical Model, and Graphical Representation w w 1 2 2 68 Chapter 4 ■ Support Vector Regression To visualize how the magnitude of the weights can be interpreted as a measure of flatness, consider the following example: f x w w x x w i i M i M ( , ) , , . = Î Î = å   1 Here, M is the order of the polynomial used to approximate a function. As the magnitude of the vector w increases, a greater number of wi are nonzero, resulting in higher-order solutions, as shown in Figure 4-2. The horizontal line is a 0th-order polynomial solution and has a very large deviation from the desired outputs, and thus, a large error. The linear function, a 1st-order polynomial, produces better approximations for a portion of the data but still underfits the training data. The 6th-order solution produces the best tradeoff between function flatness and prediction error. The highest-order solution has zero error but a high complexity and will most likely overfit the solution on yet to be seen data. The magnitude of w acts as a regularizing term and provides optimization problem control over the flatness of the solution. The constraint is to minimize the error between the predicted value of the function for a given input and the actual output. SVR adopts an e-insensitive loss function, penalizing predictions that are farther than e from the desired output. The value of e determines the width of the tube; a smaller value indicates a lower tolerance for error and also affects the number of support vectors and, consequently, the solution sparsity. Intuitively, the latter can be visualized for Figure 4-1. If e is decreased, the boundary of the tube is shifted inward. Therefore, more datapoints are around the boundary, which indicates more support vectors. Similarly, increasing e will result in fewer points around the boundary. Because it is less sensitive to noisy inputs, the e-insensitive region makes the model more robust. Several loss functions can be adopted, including the linear, quadratic, and Huber e, as shown in Equations 4-4, 4-5, and 4-6, respectively. As demonstrated in Figure 4-3, the Huber loss function is smoother than the linear and quadratic functions, but it penalizes all deviations from the desired output, with greater penalty as the error increases. SVR: Concepts, Mathematical Model, and Graphical Representation 69 Chapter 4 ■ Support Vector Regression L y f x w y f x w y f x w otherwise e e e , , , ; , , ( ) ( ) = - ( ) £ - ( ) - ì íï îï 0 (4-4) L y f x w y f x w y f x w otherwise e e e , , , ; , , ( ) ( ) = - ( ) £ - ( ) - ( ) ì íï îï 0 2 (4-5) L y f x w c y f x w c y f x w c y f x w y f x w c , , , , , , ( ) ( ) = - ( ) - - ( ) > - ( ) - ( ) £ ì í 2 2 2 1 2 ïï î ï ï (4-6) Figure 4-3. Loss function types: (a) linear, (b) quadratic, and (c) Huber L y f x w y f x w y f x w otherwise e e e , , , ; , , ( ) ( ) = - ( ) £ - ( ) - ì íï îï 0 (4-4) L y f x w y f x w y f x w otherwise e e e , , , ; , , ( ) ( ) = - ( ) £ - ( ) - ( ) ì íï îï 0 2 (4-5) L y f x w c y f x w c y f x w c y f x w y f x w c , , , , , , ( ) ( ) = - ( ) - - ( ) > - ( ) - ( ) £ ì í 2 2 2 1 2 ïï î ï ï (4-6) (4-4) (4-5) y f x w c y f x w c , , - ( ) > - ( ) £ (4-6) Figure 4-3. Loss function types: (a) linear, (b) quadratic, and (c) Huber ASYMMETRICAL LOSS FUNCTIONS Some researchers have proposed modification to loss functions to make them asymmetrical. Shim, Yong, and Hwang (2011) used an asymmetrical e-insensitive loss function in support vector quantile regression (SVQR) in an attempt to decrease the number of support vectors. SVR: Concepts, Mathematical Model, and Graphical Representation The choice of loss function is influenced by a priori information about the noise distribution affecting the data samples (Huber 1964), the model sparsity sought, and the training computational complexity. The loss functions presented here are symmetrical and convex. Although asymmetrical loss f ti b d t d t li it ith d ti ti ti ti th l f ti h ld b Figure 4-2. Solutions with various orders Figure 4-2. Solutions with various orders Figure 4-2. Solutions with various orders The constraint is to minimize the error between the predicted value of the function for a given input and the actual output. SVR adopts an e-insensitive loss function, penalizing predictions that are farther than e from the desired output. The value of e determines the width of the tube; a smaller value indicates a lower tolerance for error and also affects the number of support vectors and, consequently, the solution sparsity. Intuitively, the latter can be visualized for Figure 4-1. If e is decreased, the boundary of the tube is shifted inward. Therefore, more datapoints are around the boundary, which indicates more support vectors. Similarly, increasing e will result in fewer points around the boundary. Because it is less sensitive to noisy inputs, the e-insensitive region makes the model more robust. Several loss functions can be adopted, including the linear, quadratic, and Huber e, as shown in Equations 4-4, 4-5, and 4-6, respectively. As demonstrated in Figure 4-3, the Huber loss function is smoother than the linear and quadratic functions, but it penalizes all deviations from the desired output, with greater penalty as the error increases. The choice of loss function is influenced by a priori information about the noise distribution affecting the data samples (Huber 1964), the model sparsity sought, and the training computational complexity. The loss functions presented here are symmetrical and convex. Although asymmetrical loss functions can be adopted to limit either underestimation or overestimation, the loss functions should be convex to ensure that the optimization problem has a unique solution that can be found in a finite number of steps. Throughout this chapter, the derivations will be based on the linear loss function of Equation 4-4. SVR: Concepts, Mathematical Model, and Graphical Representation The authors altered the insensitivity according to the quantile and achieved a sparser model. Schabe (1991) proposed a two-sided quadratic loss function and a quasi-quadratic s-loss function for Bayes parameter estimation, and Norstrom (1996) replaced the quadratic loss function with an asymmetrical loss function to derive a general class of functions that approach infinity near the origin for Bayesian risk analysis. Nath and Bhattacharyya (2007) presented a maximum margin classifier that bounds misclassification for each class differently, thus allowing for different tolerances levels. Lee, Hsieh, and Wang (2005) reformulated the typical SVR approach into a nonconstrained problem, thereby only solving a system of linear equations rather than a convex quadratic one. Pan and Pan (2006) compared three* different loss functions for economic tolerance design: Taguchi’s quadratic loss function, inverted normal loss function, and revised inverted normal loss function. Adopting a soft-margin approach similar to that employed in SVM, slack variables x, x* can be added to guard against outliers. These variables determine how many points can be tolerated outside the tube illustrated in Figure 4-1. Based on Equations 4-3 and 4-4, the optimization problem in Equation 4-7 is obtained; C is a regularization—thus, a tuneable parameter that gives more weight to minimizing the flatness, or the error, for this multiobjective optimization problem. For example, a larger C gives more weight to minimizing the error. This constrained quadratic optimization problem can be solved by finding the Lagrangian (see Equation 4-8). The Lagrange multipliers, or dual variables, are l, l, a, a and are nonnegative real numbers. 70 Chapter 4 ■ Support Vector Regression min , * 1 2 2 1   w C i i i N + + = å x x (4-7) (4-7) y w x i N i T i i - £ + = e x * ... 1 w x y i N T i i i - £ + = e x 1... x x i i i N , ... SVR: Concepts, Mathematical Model, and Graphical Representation * ³ = 0 1 w w C y w x i i i N i i N i T i , , , , , , * * * * * x x l l a a x x a e ( ) = + + + - - = = å å 1 2 2 1 1   - ( ) + - + - - ( )- + = = å å x a e x lx l x i i i N i T i i i i i i i N y w x * * * 1 1 (4-8) (4-8) The minimum of Equation 4-8 is found by taking its partial derivatives with respect to the variables and setting them equal to zero, based on the Karush-Kuhn-Tucker (KKT) conditions. The partial derivatives with respect to the Lagrange multipliers return the constraints, which have to be less than or equal to zero, as illustrated in Equation 4-9. The final KKT condition states that the product of the Lagrange multipliers and the constraints is equal to zero (see Equation 4-10). The Lagrange multipliers that are equal to zero correspond to data inside the tube, whereas the support vectors have nonzero-valued Lagrange multipliers. The solution is written in terms of the support vector only—hence, the solution sparsity. The function approximation is represented in Equation 4-12. By replacing Equation 4-9 in Equation 4-8, the dual form of the optimization problem can be written as shown in Equation 4-13. SVR: Concepts, Mathematical Model, and Graphical Representation d d a a d dx l a d dx l a d    w w x C C i i i i N i i i i i i = - - = = - - = = - - = = å ( ) * * * * 0 0 0 1     dl x d dl x d da e x d da i i i N i i i N i i T i i y w x * * * * = £ = £ = - - - £ = = å å 0 0 0 1 1 i i T i i y w x = - + - - £ e x 0 (4-9) a e x a e x l x l x i i T i i i i T i i i i i i y w x y w x i - + - - ( ) = - - - ( ) = = = " 0 0 0 0 * * * * , (4-10) w x i i i i NSV = - ( ) = å a a * 1 (4-11) d d a a d dx l a d dx l a d    w w x C C i i i i N i i i i i i = - - = = - - = = - - = = å ( ) * * * * 0 0 0 1     dl x d dl x d da e x d da i i i N i i i N i i T i i y w x * * * * = £ = £ = - - - £ = = å å 0 0 0 1 1 i i T i i y w x = - + - - £ e x 0 (4-9) a e x a e x l x l x i i T i i i i T i i i i i i y w x y w x i - + - - ( ) = - - - ( ) = = = " 0 0 0 0 * * * * , (4-10) w x i i i i NSV = - ( ) = å a a * 1 (4-11) (4-9) (4-10) w x i i i i NSV = - ( ) = å a a * 1 (4-11) (4-11) 71 Chapter 4 ■ Support Vector Regression f x x x C i i i T i i i NSV ( ) = - ( ) Î = å a a a a * * , , [ , ] 0 1 (4-12) f x x x C i i i T i i i NSV ( ) = - ( ) Î = å a a a a * * , , [ , ] 0 1 (4-12) max , * * * * * a a e a a a a a a a a - + ( )+ - ( ) - - ( ) - = = å å i i i N i i i i N i i j SV SV y 1 1 1 2 j i T j i N j N x x SV SV ( ) = = å å 1 1 , (4-13) max , * * * * * a a e a a a a a a a a - + ( )+ - ( ) - - ( ) - = = å å i i i N i i i i N i i j SV SV y 1 1 1 2 j i T j i N j N x x SV SV ( ) = = å å 1 1 , subject to subject to subject to a a a a i i i i i NSV * * , , , - ( ) = Î[ ] = å 0 0 1 C At the beginning of this section, the weights vector w was augmented with the scalar b, and the derivation of the SVR’s mathematical formulation was carried out, disregarding the explicit computation of b (see Equation 4-2). SVR: Concepts, Mathematical Model, and Graphical Representation However, b could have been calculated from the KKT conditions, as shown next. Training data that belong to the outside of the boundary of the tube will have nonzero ai or ai ; they cannot both be zero, because that would mean that the instance (xi, yi) belongs to the lower and upper boundary, which is not possible. Therefore, the corresponding constraints will be satisfied with equality, as demonstrated in Equation 4-14. Furthermore, because the point is not outside the tube, xi = 0 , leading to the result in Equation 4-15 when a Î( , ) 0 C . Equation 4-16 computes b. Performing the same analysis for ai , one gets Equations 4-17 and 4-18. y w x b i T i i - - - - = e x 0 (4-14) y w x b i T i - - - = e 0 (4-15) b y w x i T i = - -e (4-16) - + - - = y w x b i T i e 0 (4-17) b y w x i T i = - + -e (4-18) y w x b i T i i - - - - = e x 0 (4-14) y w x b i T i - - - = e 0 (4-15) b y w x i T i = - -e (4-16) - + - - = y w x b i T i e 0 (4-17) b y w x i T i = - + -e (4-18) y w x b i T i i - - - - = e x 0 (4-14) y w x b i T i - - - = e 0 (4-15) b y w x i T i = - -e (4-16) - + - - = y w x b i T i e 0 (4-17) b y w x i T i = - + -e (4-18) Instead of using the KKT conditions, one could have also computed b, while solving the optimization problem, using the interior-point method, which can converge to an optimal solution in logarithmic time by navigating along the central path of the feasible region. The central path is determined by solving the primal and dual optimization problems simultaneously. Kernel SVR and Different Loss Functions: Mathematical Model and Graphical Representation The previous section dealt with data in the feature space, assuming f (x) is linear. For non linear functions, the data can be mapped into a higher dimensional space, called kernel space, to achieve a higher accuracy, using kernels that satisfy Mercer’s condition (see Figure 4-4), as discussed previously for classification. Therefore, replacing all instances of x in Equations 4-1–4-18 with k(xi, xj) yields the primal formulation shown in Equation 4-19, where j(.) is the transformation from feature to kernel space. Equation 4-20 describes the new weight vector in terms of the transformed input. The dual problem is represented in Equation 4-21, and the function approximation f (x) is in Equation 4-22, where k(.,.), the kernel, is as illustrated in Equation 4-23. 72 Chapter 4 ■ Support Vector Regression min , * 1 2 2 1   w C i i i N + + = å x x (4-19) subject to y w x i N i T i i - ( ) £ + = j e x * ,..., 1 w x y i N T i i i j e x ( )- £ + = ,..., 1 x x i i i N , ,..., * ³ = 0 1 w x i N i i i SV = - ( ) =å ( ) * 1 a a j (4-20) max , * * * a a e a a a a - + ( )+ - ( ) - = = = = å å å i N i i i N i i i j N i N SV SV SV SV y 1 1 1 1 1 2 å - ( ) - ( ) ( ) a a a a i i j j i j k x x * * , (4-21) a a a a i i SV i N i i C i N SV , , , ,..., , * * Î[ ] = - ( ) = =å 0 1 0 1 f x k x x i N i i i SV ( ) = - ( ) ( ) =å , * 1 a a (4-22) k x x x x i i , . Kernel SVR and Different Loss Functions: Mathematical Model and Graphical Representation ( ) ( ) = ( ) j j (4-23) 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 Figure 4-4. Nonlinear regression min , * 1 2 2 1   w C i i i N + + = å x x (4-19) min , * 1 2 2 1   w C i i i N + + = å x x (4-19) subject to y w x i N i T i i - ( ) £ + = j e x * ,..., 1 w x y i N T i i i j e x ( )- £ + = ,..., 1 x x i i i N , ,..., * ³ = 0 1 w x i N i i i SV = - ( ) =å ( ) * 1 a a j (4-20) max , * * * a a e a a a a - + ( )+ - ( ) - = = = = å å å i N i i i N i i i j N i N SV SV SV SV y 1 1 1 1 1 2 å - ( ) - ( ) ( ) a a a a i i j j i j k x x * * , (4-21) a a a a i i SV i N i i C i N SV , , , ,..., , * * Î[ ] = - ( ) = =å 0 1 0 1 f x k x x i N i i i SV ( ) = - ( ) ( ) =å , * 1 a a (4-22) k x x x x i i , . Kernel SVR and Different Loss Functions: Mathematical Model and Graphical Representation ( ) ( ) = ( ) j j (4-23) w x i N i i i SV = - ( ) =å ( ) * 1 a a j (4-20) (4-20) max , * * * a a e a a a a - + ( )+ - ( ) - = = = = å å å i N i i i N i i i j N i N SV SV SV SV y 1 1 1 1 1 2 å - ( ) - ( ) ( ) a a a a i i j j i j k x x * * , (4-21) a a a a i i SV i N i i C i N SV , , , ,..., , * * Î[ ] = - ( ) = =å 0 1 0 1 f x k x x i N i i i SV ( ) = - ( ) ( ) =å , * 1 a a (4-22) k x x x x i i , . ( ) ( ) = ( ) j j (4-23) 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 Figure 4-4. Nonlinear regression max , * * * a a e a a a a - + ( )+ - ( ) - = = = = å å å i N i i i N i i i j N i N SV SV SV SV y 1 1 1 1 1 2 å - ( ) - ( ) ( ) a a a a i i j j i j k x x * * , (4-21) a a a a i i SV i N i i C i N SV , , , ,..., , * * Î[ ] = - ( ) = =å 0 1 0 1 f x k x x i N i i i SV ( ) = - ( ) ( ) =å , * 1 a a (4-22) k x x x x i i , . ( ) ( ) = ( ) j j (4-23) 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 Figure 4-4. Nonlinear regression 73 73 Chapter 4 ■ Support Vector Regression Bayesian Linear Regression Unlike SVR, Bayesian linear regression is a generative, as opposed to discriminant, method, that builds linear regression models based on Bayesian inference. After specifying a model, the method computes the posterior distribution of parameters and model predictions. This statistical analysis allows the method to determine model complexity during training, which results in a model that is less likely to overfit. For simplicity, assume that a single output yp Î are predicted using the model parameters w learned from a set of predictor variables X sized k´1 and observations Y sized n´1. The observations Y are assumed to have the distribution in Equation 4-24, where s 2 is the variance of the uncertainty in the observations: P Y w X Xw I \| , , ~ , s s 2 2 ( ) ( )  (4-24) (4-24) Once the model has been specified, the model parameters’ posterior distributions can be estimated. This is done by first assuming a prior distribution of the model parameters (see Equation 4-25). Given the model variance and observations, the posterior distribution of the model parameters (which is Gaussian) is as shown in Equation 4-26, with the mean computed in Equation 4-27, and the standard deviation scale factor, in Equation 4-28. The mean is simply the Moore-Penrose pseudoinverse of the predictive variables multiplied by the observations. Given some observations, the posterior probability of the model variance is computed, and an inverse chi-squared distribution (see Equation 4-29), with n k - degrees of freedom and a scale factor s2 (see Equation 4-30), is obtained. The scale factor is the error between the model’s predicted output and an observation. Bayesian Linear Regression P w,s s 2 2 1 ( ) µ (4-25) (4-25) P w,s s 2 2 1 ( ) µ P w Y P Y w X P w P Y w v E w \| \| \| s s s s s 2 2 2 2 2 , \| , , ~ , ( ) = ( ) ( ) ( ) ( )  (4-26) w X X X Y E T T =( ) -1 (4-27) v X X w T =( ) -1 (4-28) P Y P Y P P Y inv n k s s s s 2 2 2 2 2 \| \| ( ) = ( ) ( ) ( ) - - ( ) ~ ,  (4-29) w X X X Y E T T =( ) -1 (4-27) v X X w T =( ) -1 (4-28) P Y P Y P P Y inv n k s s s s 2 2 2 2 2 \| \| ( ) = ( ) ( ) ( ) - - ( ) ~ ,  (4-29) s Y Xw Y Xw n k E T E 2 = - ( ) - ( ) - (4-30) (4-30) The marginal posterior distribution of the model parameters, given the observations, is a multivariate Student’s t-distribution, shown in Equation 4-31 and computed in Equation 4-32, with n k - degrees of freedom, wE mean, and s2 scale factor, as P w Y \|s 2, ( ) has a normal distribution, and P Y s 2\| ( ) has an inverse chi-squared distribution. (4-31) P w Y t n k w s E \| ( ) - ( ) ~ , , 2 (4-31) P w Y P w Y P Y d \| \| \| ( ) = ( ) ( ) ò s s s s 2 2 2 2 , (4-32) (4-32) 74 Chapter 4 ■ Support Vector Regression Given the model parameter probability distributions and a set of predictive variables Xp, the marginal posterior predictive distribution Yp, which is a multivariate Student’s t-distribution (see Equation 4-33) can be determined. The mean is computed in Equation 4-34, and the variance, in Equation 4-35. The predictive distribution variance depends on the uncertainty in the observed data and the model parameters. Bayesian Linear Regression (4-33) P Y Y t n k E Y Y var Y Y P p p \| \| \| ( ) - ( ) ( ) ( ) ~ , , , s 2 (4-33) E Y Y X w p p E \| ( ) = (4-34) var Y Y I X v X p p w p T \|s s 2 2 , ( ) = + ( ) (4-35) (4-35) The concept of Bayesian regression is displayed in Figure 4-5, in which the sample input data available during training would have been generated by a Gaussian distribution. If these instances represent their population well, the regression model is expected to generalize well. Figure 4-5. One-dimensional regression example illustrating the Gaussian conditional probability distributions of the output on the input and model parameters Figure 4-5. One-dimensional regression example illustrating the Gaussian conditional probability distributions of the output on the input and model parameters DISCRIMINANT VS. GENERATIVE MODELS A generative approach models the joint probability distribution of the data and class labels p(x, Ck), based on the prior probability distributions of the class labels p(Ck) and the likelihood probability distribution p x Ck \| ( ). The joint distribution computes the posterior probability distributions p C k k\| ( ), which will be used to map datapoints to class labels. A discriminant approach directly computes the posterior probability distributions p C x k\| ( ) without computing the joint probability distribution p(x, Ck). A discriminant approach produces a mapping from the datapoints to the class labels without computing probability distributions. Therefore, this approach performs the inference and decision stages in one step. 75 75 Chapter 4 ■ Support Vector Regression Advantages Disadvantages Generative Robust to outliers • Can easily update decision model • Allows combination of classifiers trained • on different types of data by applying probability rules Can improve prediction accuracy by • measuring confidence in classification based on posterior distributions and not making predictions when confidence is low Computationally demanding • Requires a lot of training data • Suffers from the curse of • dimensionality Discriminant Computationally less demanding • Simple to implement • Sensitive to noisy data and outliers • Requires retraining for any changes • in the decision model Sensitive to noisy data and outliers • Requires retraining for any changes • in the decision model Requires retraining for any changes • in the decision model Asymmetrical SVR for Power Prediction: Case Study Justification: In many instances of approximation, there is an uneven consequence of misprediction, based on whether the error is above or below the target value (Stockman et al. 2012a, 2012b). For example, in power prediction an incorrect low estimate may be of much more concern than an overestimate. Underpredicting can lead to insufficient cooling of datacenters, inadequate uninterruptible power supply (UPS), unavailable processor resources, needless powering down of chip components, and so on. In the case of forest fire behavior prediction, a lower estimate of the threat can lead to greater property damage as well as loss of life, owing to a lack of adequate supply of personnel and equipment. In these instances, it is crucial to minimize misestimates on one side of a boundary, even at the risk of reducing the accuracy of the entire estimation. It is necessary to restrict the loss function so that a minimal number of under- or overestimates occur. This leads to an asymmetrical loss function for training, in which a greater penalty is applied when the misestimate is on the wrong side of the boundary. Approach: Asymmetrical and lower-bounded SVR (ALB-SVR) was proposed by Stockman, Awad, and Khanna (2012a). This approach modifies the SVR loss functions and corresponding error functions, such that the e-tube is only above the function, as demonstrated in Figure 4-6. The penalty parameter C is split into C+ and C- so that different penalties can be applied to the upper and lower mispredictions. Figure 4-6. (a) SVR and (b) ALB-SVR (Source: Intel, 2012) Figure 4-6. (a) SVR and (b) ALB-SVR (Source: Intel, 2012) 76 Chapter 4 ■ Support Vector Regression ALB-SVR uses the Huber insensitive loss function (Popov and Sautin 2008). This function is similar to the e-insensitive loss function; however, it increases quadratically for small errors outside the e-bound but below a certain threshold ¶ > e and then linearly beyond ¶. This makes it robust with respect to outliers. The Huber insensitive loss function is represented by: , L t y if t y t y if t y t y HuberSVR e e e e e ¶ ( ) = - £ - - ( ) < - < ¶ ¶ - ( ) - - 0 2 2 ¶ - ( ) - ³ ¶ ì í ïï î ï ï e if t y . ALB-SVR modifies the Huber insensitive loss function as follows: ALB-SVR modifies the Huber insensitive loss function as follows: Thus, the solution is: max ( ) ( ) ( , , a a a a ea a a + - = + - = + - + å å å - - - - - i L i i i i L i i i j i t C 1 1 2 2 1 2 1 2 a a a i i i i j - + - - × é ë ê ê ê ê ê ù û ú ú ú ú ú )( ) , x x Thus, the solution is: max ( ) ( ) ( , , a a a a ea a a + - = + - = + - + å å å - - - - - i L i i i i L i i i j i t C 1 1 2 2 1 2 1 2 a a a i i i i j - + - - × é ë ê ê ê ê ê ù û ú ú ú ú ú )( ) , x x Thus, the solution is: max ( ) ( ) ( , , a a a a ea a a + - = + - = + - + å å å - - - - - i L i i i i L i i i j i t C 1 1 2 2 1 2 1 2 a a a i i i i j - + - - × é ë ê ê ê ê ê ù û ú ú ú ú ú )( ) , x x and the resulting optimization problem: and the resulting optimization problem: x ( ) ( ) ( , , a a a a ea a a + - - - + - + = + - = + - + å å å i L i i i i L i i i j i t C 1 1 2 2 1 2 1 2 - - × é ë ê ê ê ê ù û ú ú ú ú - + - a a a i i i i j )( )x x - £ - £ = + - C C i L i i ( ) .. a a 1 1 0 L i i å + - - = ( ) . ALB-SVR modifies the Huber insensitive loss function as follows: L t y if t y t y if t y t y HuberALB SVR e e ¶ - ( ) = ³ - ( ) £ - ( ) - ( ) < - , ( ) 0 0 0 2 - ( ) < - < ¶ ¶ - ( ) - -¶ - ( ) - ³ ¶ ì í ï ïï î ï ï ï e e e e 2 2 if t y t y if t y ( ) . L t y if t y t y if t y t y HuberALB SVR e e ¶ - ( ) = ³ - ( ) £ - ( ) - ( ) < - , ( ) 0 0 0 2 - ( ) < - < ¶ ¶ - ( ) - -¶ - ( ) - ³ ¶ ì í ï ïï î ï ï ï e e e e 2 2 if t y t y if t y ( ) . ALB-SVR modifies the Huber insensitive loss function as follows: a a max ( ) ( ) ( , , a a a a ea a a + - - - + - + = + - = + - + å å å i L i i i i L i i i j i t C 1 1 2 2 1 2 1 2 - - × é ë ê ê ê ê ù û ú ú ú ú - + - a a a i i i i j )( )x x - £ - £ = + - C C i L i i ( ) .. a a 1 1 0 L i i å + - - = ( ) . a a By substituting the new loss function, ALB-SVR’s empirical risk becomes R y L L t y emp i L ALB SVR i i ( ) = = - - å 1 1 e ( , ). The maximum additional empirical risk for ALB-SVR can be computed as i y t L i y t L y t Î - ( )£ Î - ( )> å å - ( ) + e e e. Validation: ALB-SVR was tested on a dataset used by David et al. (2010) and Stockman et al. (2010) that consists of 17,765 samples of five attributes of memory activity counters, with the actual corresponding power consumed in watts, as measured directly by a memory power riser. The memory power model attributes are activity, read, write, CKE = high, and CKE = low. ALB-SVR was implemented with a modified 77 77 Chapter 4 ■ Support Vector Regression version of LIBSVM (Chang and Lin 2011) for ALB-SVR. Simulation results (see Figures 4-7 – 4-9) took the average of ten runs of threefold cross-validation of a radial basis function (RBF) kernel, with a combination of grid search and heuristic experimentation to find the best metaparameters e, g, C+, and C–. Figure 4-8. Power estimates for running average power limit (RAPL) data with Huber insensitive SVR (Source: Intel, 2012) Type % Error % Out of Bound Huber insensitive SVR 512 – 128 0.1 1.0e-06 1.03 67.07 Huber insensitive ALB-SVR 10,000,000 1,000 128 0.1 1.0e-06 1.50 0.24 Figure 4-7. ALB-SVR modifies the Huber insensitive loss function as follows: Comparative results of SVR versus ALB-SVR (Source: Intel, 2012) Type % Error % Out of Bound Huber insensitive SVR 512 – 128 0.1 1.0e-06 1.03 67.07 Huber insensitive ALB-SVR 10,000,000 1,000 128 0.1 1.0e-06 1.50 0.24 Figure 4-7. Comparative results of SVR versus ALB-SVR (Source: Intel, 2012) Figure 4-7. Comparative results of SVR versus ALB-SVR (Source: Intel, 2012) Figure 4-8. Power estimates for running average power limit (RAPL) data with Huber insensitive SVR (Source: Intel, 2012) Figure 4-8. Power estimates for running average power limit (RAPL) data with Huber insensitive SVR (Source: Intel, 2012) 78 Chapter 4 ■ Support Vector Regression Figure 4-9. Power estimates for RAPL data with Huber insensitive ALB-SVR (Source: Intel, 2012) Figure 4 9 Power estimates for RAPL data with Huber insensitive ALB SVR (Source: Inte Figure 4-9. Power estimates for RAPL data with Huber insensitive ALB-SVR (Source: Intel, 2012 In SVR, support vectors are those points that lie outside the e-tube. The smaller the value of e, the more points that lie outside the tube and hence the greater the number of support vectors. With ALB-SVR the e-tube is cut in half, and the lower e -bound is dropped. Therefore, for the same g and e parameters, more points lie outside the tube, and there are a larger number of support vectors. This means that the number of support vectors is greater for ALB-SVR than for SVR. This increase in the number of support vectors indicates that using ALB-SVR has some negative effects on the complexity of the estimating function. Although the percentage relative error data set was higher (5.06 percent), this is acceptable, because the main purpose was to reduce the number of underestimates and this was achieved. References Chang, Chih-Chung, and Chih-Jen Lin. “LIBSVM: A Library for Support Vector Machines,” in “Large-Scale Machine Learning,” edited by C. Ling, special issue, ACM Transactions on Intelligent Systems and Technology 2, no. 3 (2011). www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdf. David, Howard, Eugene Gorbatov, Ulf R. Hanebutte, Rahul Khanna, and Christian Le. “RAPL: Memory Power Estimation and Capping.” In Proceedings of the 2010 ACM/IEEE International Symposium on Low-Power Electronics and Design (ISLPED), August 18–20, 2010, Austin, TX, 189–194. Piscataway, NJ: Institute for Electrical and Electronics Engineers, 2010. Huber, Peter J. “Robust Estimation of a Location Parameter.” Annals of Mathematical Statistics 35, no. 1 (1964): 73–101. Huber, Peter J. “Robust Estimation of a Location Parameter.” Annals of Mathematical Statistics 35, no. 1 (1964): 73–101. Lee, Yuh-Jye, Wen-Feng Hsieh, and Chien-Ming Huang. “e-SSVR: A Smooth Support Vector Machine for e-Insensitive Regression.” IEEE Transactions on Knowledge and Data Engineering 17, no. 5 (2005): 678–685. Lee, Yuh-Jye, Wen-Feng Hsieh, and Chien-Ming Huang. “e-SSVR: A Smooth Support Vector Machine for e-Insensitive Regression.” IEEE Transactions on Knowledge and Data Engineering 17, no. 5 (2005): 678–685. Lee, Yuh-Jye, Wen-Feng Hsieh, and Chien-Ming Huang. “e-SSVR: A Smooth Support Vector Machine for e-Insensitive Regression.” IEEE Transactions on Knowledge and Data Engineering 17, no. 5 (2005): 678–685. 79 79 Chapter 4 ■ Support Vector Regression Nath, J. Saketha, and Chiranjib Bhattacharyya. “Maximum Margin Classifiers with Specified False Positive and False Negative Error Rates.” In Proceedings of the Seventh SIAM International Conference on Data Mining, April 26–28, 2007, Minneapolis, MN, 35–46. 2007. http://dblp.uni-trier.de/rec/bibtex/conf/ sdm/NathB07. Norstrom, Jan Gerhard. “The Use of Precautionary Loss Functions in Risk Analysis.” IEEE Transactions on Reliability 45, no. 3 (1996): 400–403. Pan, Jeh-Nan, and Jianbiao Pan. “A Comparative Study of Various Loss Functions in the Economic Tolerance Design.” In Proceedings of the 2006 IEEE International Conference on Management of Innovation and Technology, June 21–23, 2006, Singapore, China, 783–787. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2006. Popov, A. A, and A. S. Sautin. “Loss Functions Analysis in Support Vector Regression,” 9th International Conference on Actual Problems of Electronic Instrument Engineering, September 23–25, 2008, Novosibirsk, Russia, 198. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2008. Schabe, H. “Bayes Estimates Under Asymmetric Loss.” IEEE Transactions on Reliability 40, no. 1 (1991): 63–67. Shim, Joo Yong, and Chang Ha Hwang. “Support Vector Quantile Regression Using Asymmetric e-Insensitive Loss Function.” Communications for Statistical Applications and Methods 18, no. 2 (2011): 165–170. Vapnik, Vladimir N. Statistical Learning Theory. New York: Wiley, 1998. Hidden Markov Model The best thing about the future is that it comes one day at a time. —Abraham Lincoln Real-time processes produce observations that can be discrete, continuous, stationary, time variant, or noisy. The fundamental challenge is to characterize the observations as a parametric random process, the parameters of which should be estimated, using a well-defined approach. This allows us to construct a theoretical model of the underlying process that enables us to predict the process output as well as distinguish the statistical properties of the observation itself. The hidden Markov model (HMM) is one such statistical model. HMM interprets the (nonobservable) process by analyzing the pattern of a sequence of observed symbols. An HMM consists of a doubly stochastic process, in which the underlying (or hidden) stochastic process can be indirectly inferred by analyzing the sequence of observed symbols of another set of stochastic processes. HMM comprises (hidden) states that represent an unobservable, or latent, attribute of the process being modeled. HMM-based approaches are widely used to analyze features or observations, such as usage and activity profiles and transitions between different states of the process, to predict the most probable sequence of states. The HMM can be represented as a stochastic model of discrete events and a variation of the Markov chain, a chain of linked states or events, in which the next state depends only on the current state of the system. The states of an HMM are hidden (or can only be inferred from the observed symbols). For a given model and sequence of observations, HMM is used to analyze the solution to problems related to model selection, state-sequence determination, and model training (for more details, see the section “The Three Basic Problems of HMM”). The fundamental theory of HMMs was developed on the basis of pioneering work • by Baum and colleagues (Baum and Petrie 1966; Baum and Eagon 1967; Baum and Sell 1968; Baum et al. 1970; Baum 1972). Earlier work in this area is credited to Stratonovich (1960), who proposed an optimal nonlinear filtering model, based on the theory of conditional Markov processes. A recent contribution to the application of HMM was made by Rabiner (1989), in the formulation of a statistical method of representing speech. The author established a successful implementation of an HMM system, based on discrete or continuous density parameter distributions. References Stockman, Melissa, Mariette Awad, and Rahul Khanna. “Asymmetrical and Lower Bounded Support Vector Regression for Power Prediction.” Intel Technology Journal 16, no. 2 (2012a). Stockman, Melissa, Mariette Awad, Rahul Khanna, Christian Le, Howard David, Eugene Gorbatov, and Ulf R. Hanebutte. “A Novel Approach to Memory Power Estimation Using Machine Learning.” In Proceedings of the 2010 International Conference on Energy Aware Computing (ICEAC), December 16–18, 2010, Cairo, Egypt, 1–3. Piscataway, NJ: Institute for Electrical and Electronics Engineers, 2010. Stockman, Melissa, Randa S. El Ramli, Mariette Awad, and Rabih Jabr. “An Asymmetrical and Quadratic Support Vector Regression Loss Function for Beirut Short Term Load Forecast.” In2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), October 14–17, 2012, Seoul, Korea, 651–656. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2012b. Vapnik, Vladimir N. Statistical Learning Theory. New York: Wiley, 1998. 80 Hidden Markov Model The fundamental theory of HMMs was developed on the basis of pioneering work • by Baum and colleagues (Baum and Petrie 1966; Baum and Eagon 1967; Baum and Sell 1968; Baum et al. 1970; Baum 1972). Earlier work in this area is credited to Stratonovich (1960), who proposed an optimal nonlinear filtering model, based on the theory of conditional Markov processes. A recent contribution to the application of HMM was made by Rabiner (1989), in the formulation of a statistical method of representing speech. The author established a successful implementation of an HMM system, based on discrete or continuous density parameter distributions. This chapter describes HMM techniques, together with their real-life applications, in • such management solutions as intrusion detection, workload optimization, and fault prediction. This chapter describes HMM techniques, together with their real-life applications, in • such management solutions as intrusion detection, workload optimization, and fault prediction. 81 Chapter 5 ■ Hidden Markov Model Discrete Markov Process Statistically, you may define a random walk as a sequence Qt of random variables that increments, using independent and identically distributed (iid) random variables S, such that (backward movement), with a 50 percent probability for each value. Statistically, you may define a random walk as a sequence Qt of random variables that increments, using independent and identically distributed (iid) random variables S, such that Q q Q n t t n = = =å 1 0 0 ; , where expectation E(Qn) = 0, and variance E Q n n ( ) 2 = . If S S SN 1 2 , , ,  is the sequence of integers, where expectation E(Qn) = 0, and variance E Q n n ( ) 2 = . If S S SN 1 2 , , ,  is the sequence of integers, then where expectation E(Qn) = 0, and variance E Q n n ( ) 2 = . If S S SN 1 2 , , ,  is the sequence of integers, then = 0, and variance E Q n n ( ) 2 = . If S S SN 1 2 , , ,  is the sequence of integers, then   ( \| , , ) ( \| ). q S q S q S q S q S t j t i t k t j t i + - + = = = = = = 1 2 1  (5-1)   ( \| , , ) ( \| ). q S q S q S q S q S t j t i t k t j t i + - + = = = = = = 1 2 1  (5-1) (5-1) This equation tells us that the probability that the random walk will be at Sj at time t + 1 depends only on its current value and not on how it got there. Formally, the discrete Markov process admits three definitions, described in the following sections. This equation tells us that the probability that the random walk will be at Sj at time t + 1 depends only on its current value and not on how it got there. Formally, the discrete Markov process admits three definitions, described in the following sections. Definition 1 A Markov chain on W is a stochastic process {q0, q1,...,qt}, with each qi ÎW, such that    ( \| , , , ) ( \| ): ( , ) q S q S q S q S q S q S i j t j t i t k t j t i + - + = = = = => = = = 1 1 0 0 1  : . = pij (5-2) (5-2) You construct W × W transition matrix P, whose (i, j) th entry represents ( , ) i j , with the following properties: " Î ³ " Î = Îå ( , ) , ( , ) , ( , ) i j i j i i j j W W W   0 1 A matrix P with these properties is called a stochastic matrix. Definition 2 The (ij) th entry Pn(i, j) of the matrix Pn gives the probability that the Markov chain, starting in state i, will be in state j after n steps. Discrete Markov Process A system may be described at any time as being in one of the states S1, S2, Sn (see Figure 5-1). When the system undergoes a change from state Si to Sj at regular time intervals with a certain probability pij, this can be described by a simple stochastic process, in which the distribution of future states depends only on the present state and not on how the system arrived at the present state. The matrix P, with elements pij, is called the transition probability matrix of the Markov chain. In other words, we can describe a discrete Markov process as a phenomenon evolving in regularly spaced intervals, such that, for a given present state, past and future are statistically independent. Conventionally, a time-evolving phenomenon in which only the present state affects the future state, is called a dynamic system. The exclusive dependence of future states on present states allows us to model the solutions, using random variables instead of deterministic objects. A random variable defines a set of possible outcomes (the sample space W) and a probability distribution that associates each outcome with a probability. P (1,2) P (2,1) P (4,3) P (3,4) P (3,3) P (5,4) P (2,5) P (5,5) P (4,5) P (1,1) S1 S2 S4 S3 S5 P (1,2) P (2,1) P (4,3) P (3,4) P (3,3) P (5,4) P (2,5) P (5,5) P (4,5) P (1,1) S1 S2 S4 S3 S5 P(1,1) P(1,2) P(1,3) P(1,4) P(1,5) P(2,1) P(2,2) P(2,3) P(2,4) P(2,5) P(3,1) P(3,2) P(3,3) P(3,4) P(3,5) P(4,1) P(4,2) P(4,3) P(4,4) P(4,5) P(5,1) P(5,2) P(5,3) P(5,4) P(5,5) (Transition Matrix) P = Figure 5-1. Markov chain with five states (S1–S5) with selected state transitions P(i, j) P (3,4) Figure 5-1. Markov chain with five states (S1–S5) with selected state transitions P(i, j) A simple example of a discrete Markov process—a Markov chain—is a random walk in one dimension. In this case, an individual may move forward or backward with a certain probability. Formally, you can define independent random variables q q 1 2 , , where each variable is either +1 (forward movement) or −1 82 Chapter 5 ■ Hidden Markov Model (backward movement), with a 50 percent probability for each value. Definition 3 Let u(0) be the probability vector that represents the starting distribution. Then, the probability that the chain is in state j after n steps is the jth entry in the vector: u(n) = u(0)P(n) If you want to examine the behavior of the chain under the assumption that it starts in a certain state i, you simply choose u to be the probability vector, with ith entry equal to 1 and all other entries equal to 0. The stochastic process defined in the following sections can also be characterized as an observable Markov model, because each state can be represented as physical event. 83 Chapter 5 ■ Hidden Markov Model Introduction to the Hidden Markov Model The previous sections discussed a stochastic process characterized by a Markov model in which states correspond to an observable physical phenomenon. This model may be too restrictive to be of practical use in realistic problems in which states cannot directly correspond to a physical event. To improve its flexibility, you expand the model into one in which the observed output is a probabilistic function of a state. Each state can produce a number of outputs, according to a unique probability distribution, and each distinct output can potentially be generated at any state. The resulting model is the doubly embedded stochastic model referred to as the HMM. The underlying stochastic process in the HMM produces a state sequence that is not directly observable and that can only be approximated through another set of stochastic processes that produces the sequence of observations. Figure 5-2 illustrates an extension of a discrete Markov process into a doubly stochastic HMM. The new HMM allows observation symbols to be emitted from each state, with a finite probability distribution. This lets the model be more expressive and flexible than the simple Markov chain. Additionally, as illustrated in Figure 5-3, you can model physical processes through a sequence of observed symbols that is true in most practical cases. The key difference from a conventional Markov chain is that, in analyzing the sequence of observed states, you cannot say exactly which state sequence produced these observations; you can, however, calculate the likelihood of a certain state sequence’s having produced them. This indicates that state sequence is hidden and can only be observed through a sequence of observed states or symbols. Figure 5-2. Hidden Markov model with four hidden states and three observed states Figure 5-2. Hidden Markov model with four hidden states and three observed states Figure 5-2. Hidden Markov model with four hidden states and three observed states 84 Chapter 5 ■ Hidden Markov Model Figure 5-3. Hidden Markov model: trellis representation Figure 5-3 Hidden Markov model: trellis representation Figure 5-3. Hidden Markov model: trellis representation The Three Basic Problems of HMM The preceding section described the model for HMM. This section identifies the basic problems that need to be solved to apply the model to real-world problems. These basic problems fall into three categories: Problem 1. Evaluation: Given the observation sequence X x x x xt = 1 2 3 , , , ,  and an HMM model ll pp = ( , , ) P B , how do we compute the probability of X? The solution to this problem allows us to select the competing model that best matches the observation sequence. Problem 2. Decoding: Given the observation sequence X x x x xt = 1 2 3 , , , ,  and an HMM model ll pp = ( , , ) P B , how do we find the state sequence Q q q q qt = 1 2 3 , , , ,  that best explains the observations? The solution to this problem attempts to uncover the hidden part of the stochastic model. Problem 3. Learning: How do we adjust the model parameters ll pp = ( , , ) P B to maximize ( \| ) X ll ? The solution to this problem attempts to optimize the model parameters to best describe the observation sequence. Furthermore, the solution allows us to adapt the model parameters, according to the observed training data sequence. Problem 3. Learning: How do we adjust the model parameters ll pp = ( , , ) P B to maximize ( \| ) X ll ? The solution to this problem attempts to optimize the model parameters to best describe the observation sequence. Furthermore, the solution allows us to adapt the model parameters, according to the observed training data sequence. Consider the problem of failure prediction, which assesses the risk of failure in future time. In a typical system, components have underlying dependencies that allow an error to propagate from one component to another. Additionally, there exist health states that cannot be cannot be measured but that can induce errors among dependable components. These health states progress through normal performance state, subperformance state, attention-needed state, and, ultimately, failure state. It is therefore essential to identify the operational states accurately to avoid a reactive shutdown of the system. In this scenario, health states correspond to hidden states, and observations correspond to a sequence of error conditions. Essentials of the Hidden Markov Model 85 85 Chapter 5 ■ Hidden Markov Model Essentials of the Hidden Markov Model A complete specification of the HMM (Rabiner 1989) requires formal definition of the following elements: A complete specification of the HMM (Rabiner 1989) requires formal definition of the following elements: • Number of hidden states: (N) in the model. Individual states are represented as S S S S SN = { , , , , } 1 2 3  ; the state at time t is represented as qt. • State transition probability distribution: P = { } pij , to represent state transition from state i to state j, where p q S q S ij t j t i = = = + ( \| ) 1 , 1 0 £ £ ³ i j N pij , , . This property is similar to Definition 5-1 of a Markov chain. • Observation symbol probability distribution: ( B = { ( )} b k j ) for state j, where b k x o q S j N k M j t k t j ( ) ( \| ), , = = = £ £ £ £  1 1 . • Initial state distribution: (pp = { } pi ), where pi i q S i N = = £ £ ( ), 1 1 . • Initial state distribution: (pp = { } pi ), where pi i q S i N = = £ £ ( ), 1 1 . Once the HMM parameters are defined for a physical process by appropriate values of N, M, P, B, p, you can analyze an observation sequence (output) x x x 1 2 3 , , ,, in which each xt is one of the symbols from observation matrix O at time t. Formally, an HMM can be defined by specifying model parameters N and M, observation symbols O, and three probability matrices P, B, and p. For simplicity, you can use the compact form, (5-3) ll pp = ( , ), P B, (5-3) ll pp = ( , ), P B, to indicate the complete parameter set of the model. The HMM described here makes two assumptions: • Markov assumption: The current state is dependent only on the previous state; this represents the memory of the model. • Independence assumption: Output observation ot at time t is dependent only on the current state; it is independent of previous observations and states. Solution to Problem 1 The solution to Problem 1 involves evaluating the probability of observation sequence X x x x xt = 1 2 3 , , , ,  given the model l; that is, ( \| ) X ll . Consider a state sequence Q q q q qt = 1 2 3 , , , ,  , where q1 and qt are initial and final states, respectively. The probability of an observation X sequence for a state sequence Q and a model l can be represented as   ( \| , ) ( \| , ) ( ). ( ). ( ) ( ). X Q x q b q b q b q b q t t t n x x x x n n ll ll = = =Õ 1 1 2 3 1 2 3  (5-4) (5-4) From the property of a Markov chain, you can represent the probability of the state sequence as ( \| ) . , , , Q p p p q q q q q q q n n ll = × × - p 1 1 2 2 3 1  (5-5) ( \| ) . , , , Q p p p q q q q q q q n n ll = × × - p 1 1 2 2 3 1  (5-5) Summation over all possible state sequences is as follows:      ( \| ) ( , \| ) ( \| , ). ( \| ) ( \| ) ( ) , X X Q X Q Q X b q p Q q x q q ll ll ll ll ll = = = × × å p 1 1 1 2 1 × × - å b q p b q p b q x q q x q q x n Q n n n 2 2 3 3 1 2 3 ( ). ( ) ( ). , ,  (5-6) (5-6) Unfortunately, direct computation is not very practical, because it requires 2nNn multiplications. At every t n =1 2 3 , , , ,  , N possible states can be reached, which turns out to be a large number. Solution to Problem 1 For example, at n = 100 (number of observation sequences) and N = 5 (states), there can be 2 100 5 10 100 72 × × » possible computations. Fortunately, an efficient approach, called the forward algorithm, achieves the same result. Solutions to the Three Basic Problems of HMM The following sections present the solutions to the three fundamental problems of HMM. The solutions to these problems are critical to building a probabilistic framework. The Three Basic Problems of HMM This lets the system administrator schedule preventive maintenance ahead of a complete system failure. Because faults are hidden (and so cannot be measured) and produce symbols corresponding to errors, you can model the problem of failure prediction to an HMM. For the sake of simplicity, you may assume that faults can be predicted by identifying unique patterns of errors that can be measured, using system counters. Although the complete system can be modeled, using a normal state and failed states, such models do not provide component-level granularity for tracking the progression of failure through dependent components. For this reason, system architects categorize failure into multiple domains to attribute the prediction of a failure to a specific component and thus avoid a system-level catastrophic shutdown. The first task is performed by using the solution to Problem 3, in which individual models for each failure domain ( LL = ll ll 1 2 , ,) are constructed through a training process. This process assigns the HMM parameters to the descriptive model that enables an optimal match between error patterns and the corresponding transition to a fault state by the system. In a computer system this training can be supported by system event-log information, which contains error information as well as failure descriptions. To understand the physical meaning of the model states, you identify the solution to Problem 2. In this case, the statistical properties of error counters translate into the sequence of observations occurring in each health state of the models. The definition and the number of states are dependent on the objectives and characteristics of the application. This process allows us to fine-tune the model to improve its capability to represent the various states that characterize system health. Normal state and failure state are the two end states of the HMM; intermediate states are added as needed to help predict the progression of the faulty behavior. Adding intermediate states affords modeling of predictive and critical scenarios that facilitate incorporation of repair mechanisms in anticipation of an actual failure. Once you have the set of HMMs (L) designed and optimized, recognition of a component health state is performed by using the solution to Problem 1. 86 Chapter 5 ■ Hidden Markov Model Forward Algorithm Consider a forward variable at(i) that represents the probability of a partial observation sequence up to time t, such that the underlying Markov process is in state Si at time t, given the HMM model l: at t t i i x x x x q S ( ) ( , , , , , \| ). = =  1 2 3  ll You can compute at(i) recursively via the following steps: You can compute at(i) recursively via the following steps: 1. Initialize the forward probability as a joint probability of state Si and initial observation x1. Let a p 1 1 ( ) ( ) i b x i i = for 1 £ i £ N. 2. Compute an(j) for all states j and t = n, using the induction procedure, substituting t n =1 2 3 , , , ,  : a a t t ij i N j t j i p b x t n j N + = = é ëê ù ûú £ £ - £ £ å 1 1 1 1 1 ( ) ( ). ( ), ( ), . 3. Using the results from the preceding step, compute ( \| ) ( ). X j n j N ll = =åa 1 3. Using the results from the preceding step, compute ( \| ) ( ). X j n j N ll =åa 1 j 1 The total number of computations involved in evaluating the forward probability is N2n rather than 2nNn, as required by direct computation. For n = 100 and N = 5 the total number of computations is 2,500, which is 1069 times smaller in magnitude. 87 87 Chapter 5 ■ Hidden Markov Model Backward Algorithm For the forward algorithm you can also define a backward variable bt(i) that represents the probability of a partial observation sequence from time t + 1 to the end (instead of up to t. as in the forward algorithm), where the Markov process is in state Si at time t for a given model l. Mathematically, you can represent the backward variable as bt t t n t i i x x x q S ( ) ( , , , \| , ). = = + +  1 2  ll You can compute at(i) recursively via the following steps: You can compute at(i) recursively via the following steps: 1. Define bn(i) = 1 for 1 £ i £ N. N 2. Compute b b t ij j t j N t i p b x j ( ) ( ) ( ). = + = + å 1 1 1 2. Compute b b t ij j t j N t i p b x j ( ) ( ) ( ). = + = + å 1 1 1 Scaling A practical impediment in modeling long sequences of HMMs is the numerical scaling of conditional probabilities. Efficient computation of conditional probabilities helps in estimating the most likely sequence of states for a given model. For a sufficiently large sequence the probability of observing a long sequence tends to be so extremely small that numerical instability occurs. In most cases, the resulting computations exceed the precision range of essentially any machine (including double-precision). The most common approach for mitigating this situation is to rescale the conditional probabilities, using efficient scaling mechanisms. For example let’s revisit the forward variable equation For example, let’s revisit the forward variable equation, a a t t ij i N j t j i p b x + = = × é ëê ù ûú å 1 1 ( ) ( ) ( ). In the case of forward variable at(i), you obtain the new value at+1(i) by multiplying by pij and bj(xt). These probabilities tend to be small and can underflow. Logarithms may not be helpful, because you are dealing with the sum of products. Furthermore, logarithms require computation of the logarithm and exponential for each addition. Basic scaling procedure multiplies at(i) with the scaling coefficient, with the goal of keeping the scaled at(i) within the dynamic precision range of the machine. At the end of computation, scaling coefficients are canceled out. The scaling coefficients need not be applied at every t-step but can be used whenever necessary. Solution to Problem 2 Unlike the solution of Problem 1, identifying the optimal state sequence is a complex problem, because there can be many criteria. Part of the complexity originates from the definition of the measure of optimality, in which several unique criteria are possible. One solution is to identify the states qt that are most likely to occur individually at time t. This solution attempts to maximize the expected number of correct individual states. To implement the solution to Problem 2, you define the variable gt(i) as the probability of being in state Si at time t, given the observation sequence X and model l, such that g t t i i q S X ( ) ( \| , ). = =  ll Using the definition of conditional probability, you can express this equation as Using the definition of conditional probability, you can express this equation as g t t i t i t i i N i X q S X X q S X q S ( ) ( , \| ) ( \| ) ( , \| ) ( , \| ) . = = = = = å     ll ll ll ll (5-7) (5-7) 88 Chapter 5 ■ Hidden Markov Model You can rewrite Equation 5-7, using the forward-backward variable, as You can rewrite Equation 5-7, using the forward-backward variable, as You can rewrite Equation 5-7, using the forward-backward variable, as You can rewrite Equation 5-7, using the forward-backward variable, as g a b a b t t t t t i N i i i i i ( ) ( ). ( ) ( ). ( ) , = å (5-8) (5-8) where at(i) defines the probability of partial observation x x x xt 1 2 3 , , , ,  and state Si at time t, and bt(i) defines the remainder of the probability of observation x x x x t t t n + + + 1 2 3 , , , ,  and state Si at time t. Solution to Problem 2 Using gt(i), you can solve for the individually most likely state qt * at each time t by calculating the highest probability of being in state Si at time t, as expressed by the following equation: (5-9) q argmax i t n t i N t * ( ) = [ ] " £ £ 1 g for =1 .  q argmax i t n t i N t * ( ) = [ ] " £ £ 1 g for =1 .  (5-9) Although this equation maximizes the expected number of correct states by choosing the most likely state at each time interval, the state sequence itself may not be valid. For instance, in the case of the individually most likely states in the sequence qt = Si and qt+1 = Sj, the transition probability pij may be 0 and hence not valid. This solution identifies the individually most likely state at any time t without giving any consideration as to the probability of the occurrence of the sequence of states. One way to address this issue is to maximize the occurrence of a sequence of more than one state. This allows automatic evaluation of valid occurrences of states, while evaluating for the most likely sequence. One widely used scheme is to find the single most likely sequence of states that ultimately results in maximizing ( , \| ) X Q ll . This technique, which is based on dynamic programming, is called a Viterbi algorithm. To find the single best state sequence, you define a variable dt(i) that represents the highest probability along one state sequence (path) that accounts for first t observations and that ends in state Si, as follows: dt q q q t i t i max q q q S x x x t ( ) ( , , , , , , , \| ). State Sequence Backtracking State Sequence Backtracking q q t n n n t t t * * ( ); , , , , = = - - - + + y 1 1 1 2 3 1  q q t n n n t t t * * ( ); , , , , = = - - - + + y 1 1 1 2 3 1  q q t n n n t t t * * ( ); , , , , = = - - - + + y 1 1 1 2 3 1  q q t n n n t t t * * ( ); , , , , = = - - - + + y 1 1 1 2 3 1  The Viterbi algorithm is similar to the forward procedure, except that it uses maximization over previous states instead of a summation. Recursion d d y t i N t ij j t t j max p b x j N t n j argmax ( ) ( ); ; ( ) = × éë ùû × £ £ £ £ = £ £ - 1 1 1 1 2 £ £ - × éë ùû £ £ £ £ i N t ij i p j N t n d 1 1 2 ( ) ; ; Termination Termination P max i q argmax i i N n n i N n * * ( ) ( ) = [ ] = [ ] £ £ £ £ 1 1 d d State Sequence Backtracking q q t n n n t t t * * ( ); , , , , = = - - - + + y 1 1 1 2 3 1  Solution to Problem 2 , , , = = - 1 2 1 1 2 1 2    ll You can compute dt+1( j) by induction, as You can compute dt+1( j) by induction, as You can compute dt+1( j) by induction, as d d t i i ij j t j max i p b x + + = × éë ùû × 1 1 ( ) ( ) ( ), from which it is clear that to retrieve the state sequence, you need to track the state that maximizes di(i) at each time t. This is done by constructing an array yt+1( j) that defines the state at time t from which a transition to state Sj maximizes the probability dt+1( j). Mathematically, this can be represented as from which it is clear that to retrieve the state sequence, you need to track the state that maximizes di(i) at each time t. This is done by constructing an array yt+1( j) that defines the state at time t from which a transition to state Sj maximizes the probability dt+1( j). Mathematically, this can be represented as y d t i N t ij j argmax i p + £ £ = × éë ùû 1 1 ( ) ( ) . 89 89 Chapter 5 ■ Hidden Markov Model Chapter 5 ■ Hidden Markov Model The complete procedure for finding the best state sequence consists of the following steps: Initialization d p 1 1 1 0 ( ) ( ); ( ) i b x I N i i i = × £ £ d p y 1 1 1 1 0 ( ) ( ); ( ) i b x I N i i i = × £ £ = Solution to Problem 3 å å (5-12) 90 Chapter 5 ■ Hidden Markov Model As defined by Equation 5-8, gt(i) is the probability of being in state Si at time t, given the observation sequence and model. Using this equation, you can relate gt(i) to gt(i, j) by summing over j as g g t t j N i i j ( ) ( , ). =å By summing gt(i) over time t, you can quantify the number of times state Si is visited or, alternatively, the expected number of transitions made from state Si. Similarly, summation of gt(i, j) over time t reveals the expected number of transitions from state Si to state Sj. Given gt(i), gt(i, j), and the current model l, you can build the method to reestimate the parameters of the HMM model (ll). The method can be broken down as follows: 1. At time t = 1 the expected frequency at state Si is given by p g i i i N = " = 1 1 2 3 ( ) ( , , , , ).  1. At time t = 1 the expected frequency at state Si is given by p g i i i N = " = 1 1 2 3 ( ) ( , , , , ).  2. The probability of transiting from state Si to state Sj, which is the desired value of pij, is given by p i j i i j N ij t t n t t n = " = = - = - å å g g ( , ) ( ) , ( , , , , ). 1 1 1 1 1 2 3  The numerator is the reestimated value of the expected number of transitions from state Si to state Sj; the denominator is the expected number of transitions from Si to any state. 3. The probability of observing symbol k, given that the model is in state Sj, is given by b k j j k M j t t x k n t t n t ( ) ( ) ( ) ( , , , ). Solution to Problem 3 The solution to Problem 3 involves a method for adjusting the model parameters (P,B,p) to maximize the probability of an observation sequence for a given model. In practice there is no well-known method that maximizes the probability of observation sequence. However, you can select l = (P,B,p), such that P(X\|l) is locally maximized, using an iterative method, such as the Baum-Welch algorithm. To specify the reestimation of HMM parameters, you define the variablegt(i,j) as the probability of being in state Si at time t and in Sj at time t + 1 for a given model l and observation sequence X, such that g t t i t j i j q S q S X ( , ) ( , \| , ). = = = +  1 ll (5-10) (5-10) Using the definition of the forward-backward algorithm, you can rewrite Equation 5-10 as Using the definition of the forward-backward algorithm, you can rewrite Equation 5-10 as g a b t t ij j t t i j i p b x j X ( , ) ( ) ( ) ( ) ( \| ) = × × × + + 1 1  ll (5-11) g a b a b t t ij j t t t ij j t t i j i p b x j i p b x ( , ) ( ) ( ) ( ) ( ) ( ) ( = × × × × × × + + + + 1 1 1 1 j j N i N ) . å å (5-12) g a b t t ij j t t i j i p b x j X ( , ) ( ) ( ) ( ) ( \| ) = × × × + + 1 1  ll (5-11) (5-11) g a b a b t t ij j t t t ij j t t i j i p b x j i p b x ( , ) ( ) ( ) ( ) ( ) ( ) ( = × × × × × × + + + + 1 1 1 1 j j N i N ) . Solution to Problem 3 , = " = = = = å å g g 1 1 1 2  The numerator of the reestimated b k j( ) is the expected number of times the model is in state Sj with observation symbol k; the denominator is the expected number of times the model is in state Sj. With this method, you use the current model l(P,B,p) to reestimate the new model ll pp ( , , ) P B , as described by the previous three steps. The reestimation process is an iterative method consisting of the following steps: 1. Initialize l(P,B,p) with a best guess or random value, or use the existing model. 2. Compute at(i),bt(i),gt(i),gt(i, j). 3. Reestimate the model ll pp ( , , ) P B . Continuous Observation HMM The previous sections considered a scenario in which observations are discrete symbols from a finite alphabet, enabling use of the discrete probability density for each state in the system. For many practical implementations, however, observations are continuous vectors. Although it is possible to quantize continuous vectors via codebooks, and so on, quantization may entail degradation. Therefore, it is advantageous to have an HMM with continuous observations, whose probability density function (PDF) is evaluated as a convex combination of other distribution functions—a mixture distribution, with an associated mixture weight. The number of components is restricted to being finite. For a given pool of observations, mixture distributions are employed to make statistical inferences about the properties of the subpopulations without requiring the label identifying the subpopulation to which the observation belongs. The number of components M (subpopulations) depends on the number of observation clusters (learned through unsupervised algorithms, such as k-means) that group the pool of observations. Generally, each mixture component represents an m-dimensional categorical distribution, where each of the M possible outcomes is specified with the probability of each outcome. Each mixture component follows the similar distributions (normal, log-normal, and so on) and represents a unique qualification for classifying the set of continuous observations at any time instance as a unique symbol (similar to discrete observations). Mixture components that are trained using the EM algorithm are able to self-organize to fit a data set. The continuous observation model produces sequences of hidden clusters (or a mixture symbol) at each time step of the HMM state transition, according to a state-to-cluster-emission probability distribution. Clusters (or mixture symbols) can be considered the hidden symbols embedded in the hidden states. For example, a hidden state may represent a specific workload, and a symbol may represent a specific attribute of the workload, based resource utilization. You start with the representation of the probability density function (PDF) that allows its parameters to be reestimated in a consistent manner. 4. If   ( \| ) ( \| ) X X ll ll > , repeat step 2. 4. If   ( \| ) ( \| ) X X ll ll > , repeat step 2. The final result of this reestimation process is called the maximum likelihood estimation (MLE) of the parameters of the HMM. The forward-backward algorithm yields only the local maximum. 91 91 Chapter 5 ■ Hidden Markov Model Continuous Observation HMM It can be shown (Liporace 2006; Hwang 1986) that reestimation of the coefficients for mixture density (cjm,mjm,Ujm) can be represented as 92 Chapter 5 ■ Hidden Markov Model c j k j k j k x j k jk t t n t k M t n jk t t t n t = = × = = = = å å å å e e m e e ( , ) ( , ) ( , ) ( , 1 1 1 1 ) ( , ) ( ) ( ) ( , ) , t n jk t t jk t jk T t n t t n U j k x x j k = = = å å å = × - × - 1 1 1 e m m e (5-14) (5-14) where (Xt–mjk)T represents the vector transpose, and et( j, k), the probability of being in state j at time t with the kth mixture accounting for Xt: where (Xt–mjk)T represents the vector transpose, and et( j, k), the probability of being in state j at time t with the kth mixture accounting for Xt: e a b a b m t t t t t j N jk t jk j k j j j j c X U ( , ) ( ) ( ) ( ) ( ) ( , , = é ë ê ê ê ê ù û ú ú ú ú À =å 1 jk jm t jm jm m M c X U ) ( , , ) . À é ë ê ê ê ê ù û ú ú ú ú =å m 1 (5-15) (5-15) The reestimation formula for pij is similar to that defined for discrete observation density. The reestimation formula for cjk is the ratio of the expected number of times the system is in state j, using the kth mixture component to the expected number of times the system is in state j. p p y j To reduce computational complexity, an alternate approach is semicontinuous HMM (SCHMM), which is a special form of continuous observation HMM (CHMM). SCHMM uses state mixture densities that are tied to a general set of mixture densities. All states share the same mixture, and only the mixture density component weights cjk remain state-specific states. Continuous Observation HMM The most general form of PDF that can be used for the reestimation process is given by a multivariate normal distribution or a mixture of Gaussian distributions: b X c X U j N j jm jm jm m M ( ) ( , , ) , = À £ £ =å m 1 1 (5-13) where X = observation vector ( x x x xD 1 2 3 , , , ,  ) X = observation vector ( x x x xD 1 2 3 , , , ,  ) M = number of mixture densities M = number of mixture densities cjm = weight of the mth mixture in the jth state À = any elliptically symmetrical density function (e.g., a Gaussian) mjm = mean vector for the mth mixture in the jth state Ujm= covariance matrix for the mth mixture and jth state c j N m M c j N b x dx j N jm jm m M j ³ £ £ £ £ = £ £ = £ £ - -¥ ¥ å ò 0 1 1 1 1 1 1 1 , , , ( ) , In statistics a mixture model is a probabilistic model in which the underlying data belong to a mixture distribution. In a mixture distribution the density function is a convex combination (i.e., a linear combination in which all coefficients or weights sum to 1) of other PDFs. Multivariate Gaussian Mixture Model In the CHMM, bj(X) is a continuous PDF that is often a mixture of multivariate Gaussian distributions of L-dimensional observations. Gaussian mixture model (GMM) density is defined as the weighted sum of Gaussian densities. The choice of the Gaussian distribution is natural and very widespread when dealing with a natural phenomenon. For the Gaussian mixture, À in Equation 5-13 can be substituted by Gaussian distribution to take the mathematical form of an emission density, b X c U X U X j jk k M L jk jk T jk jk ( ) ( ) \| \| exp / / = - - ( ) - ( ) æ è = - å 1 2 1 2 1 1 2 1 2 p m m ç ö ø÷ æ è çç ö ø ÷÷. (5-16) (5-16) Each Gaussian mixture is defined by its set of parameters, which includes the mixture distribution cjk, the mean vectors mjk, and the covariance matrices Ujk. Note that a CHMM with finite mixtures of Gaussian PDFs as conditional densities is equivalent to one with simple Gaussian PDFs as conditional densities. Using a Gaussian mixture PDF, you can transform a state with a mixture density into a net of multiple single-density states. Figure 5-4 depicts a scenario in which the state S2, corresponding to a two-component mixture PDF, has been expanded into two states S2a and S2b with single-component PDFs and adjusted transition probabilities. 93 Chapter 5 ■ Hidden Markov Model Figure 5-4. Two-component Gaussian mixture model for state S2 expanded into single-component Gaussian model with two new states (S2a, S2b) Figure 5-4. Two-component Gaussian mixture model for state S2 expanded into single-component Gaussian model with two new states (S2a, S2b) Example: Workload Phase Recognition Recent computer architecture research has demonstrated that program execution exhibits phase behavior that can be characterized on the largest of scales (Perelman et al. 2002). In the majority of cases, workload behavior is neither homogeneous nor totally random; it is well structured, with a class of phases. As you transition between phases, you can initiate a reconfiguration by reusing configuration information for recurring phases. Trends in datacenter and cloud computing pose interesting challenges related to power optimization and power control in a server system. A system can be represented as a set of components whose cooperative interaction produces useful work. These components may be heterogeneous in nature and may vary in their power consumption and power control mechanisms. A server system with several central processing unit (CPU), memory, and input/output (I/O) components may coordinate power control actions, using embedded controllers or special hardware. The accuracy and agility of control actions are critical in proactive tuning for performance. Observing how variations in a workload affect the power drawn by different server components provides critical data for analysis and for building models relating quality of service (QoS) expectations to power consumption. Therefore, you need an autonomous system that can extract the workload features and proactively tune the system, according to the phase of operation. The 94 Chapter 5 ■ Hidden Markov Model following sections present one such approach that uses performance data in a server platform to model the runtime behavior of a system. We describe a trained model that analyzes the behavioral attributes of a workload and that identifies the present and predicts with reasonable accuracy the future phase of workload characteristics, using a CHMM. Predictive systems are devised for recognition of workload patterns and early detection of phases for characterization. The knowledge base (model) recommends appropriate actions. These systems are self- correcting and require continuous training to adapt to the previously known as well as evolutionary behavior over a period of time. The phase detection model can assist in predicting performance states and proactively adapts by tuning its parameters to meet system constraints. Monitoring and Observations Monitoring and measuring events from system activities is the basis for characterizing system phases and predicting the future. Modern processors have built-in performance-monitoring counters that measure real-time access patterns to processor and memory events and that help in designing analytical intelligence for a variety of dynamic decisions. Trends such as memory access patterns, rate of instruction execution, and pipeline stalls can be studied statistically for patterns, hidden correlations, and time-dependent behaviors. Measured events (resource utilization, temperature, energy consumption, performance) can be considered multiple dimensions of observed emissions. Extracted phases can be seen as predictable system characteristics, based on dynamic models that maximize the probability of the sequence of observations. Once you identify the current workload phase of operation and the most likely future phase, you can tune and provision the system with adequate resources and avoid reactive resource allocation. The CHMM-based phase characterization process uses built-in performance counters and sensors. Additionally, synthetic counters are used to abstract time-varying behavior of the workload. Workload and Phase Workloads are applications with specialized objectives (queries, searches, analysis, and so on) that undergo phases of execution, while operating under multiple constraints. These constraints are related to power consumption, heat generation, and QoS requirements. Optimal system operation involves complex choices, owing to a variety of degrees of freedom for power and performance parameter tuning. The process involves modeling methodology, implementation choices, and dynamic tuning. Phase detection in a workload acts as an essential ingredient, capturing time-varying behavior of dynamically adaptable systems. This ability aids in reconfiguring hardware and software ahead of variation in demand and enables reuse of trained models for recurring phases. Phase identification also helps predict future phases during workload execution, which prevents reactive response to changes in workload behavior. In this context a phase is a stage of execution in which a workload demonstrates similar power, temperature, and performance characteristics. CHMM-assisted methodology identifies a phase’s boundaries, which are represented by a latent component of Gaussian density mixture function in the presence of system sensors and performance counters. A state’s variable can be used as a process control parameter that is fed back to the process control loop. For instance, you can feed back the workload phase (or behavioral attributes) to control thermal behavior proactively, because the physical dynamics of the temperature can be represented as a function of utilization of various system components. In general, the HMM is particularly useful, as it can exploit the underlying pattern in a sequence of events and perform state-space analysis. You may use Gaussian observations as an indicator of correctly identifying phase boundaries in a time-varying workload behavior. These phase boundaries can further be used to extract the relationship with various states of physical phenomena, such as server demand projection and thermal variation projection. Figure 5-5 for example displays a test of CPU utilization versus a workload phase that is estimated statistically at regular intervals. This function can be expanded by using more than one variable. 95 Chapter 5 ■ Hidden Markov Model Figure 5-5. CPU utilization versus phase model. The workload is composed of eight phases with phase-specific power, thermal, and performance characteristics. The red line (bottom graph) identifies the phase number that corresponds to the running average power limit (RAPL) (blue line) for each instance of workload. For example, average utilization of 65–70 percent results in phase 1 Figure 5-5. CPU utilization versus phase model. Workload and Phase The workload is composed of eight phases w power, thermal, and performance characteristics. The red line (bottom graph) identifies the Figure 5-5. CPU utilization versus phase model. The workload is composed of eight phases with phase-specific power, thermal, and performance characteristics. The red line (bottom graph) identifies the phase number that corresponds to the running average power limit (RAPL) (blue line) for each instance of workload. For example, average utilization of 65–70 percent results in phase 1 Compared with aggregate workload analysis, CHMM-assisted analysis is more accurate and informative. In general, effective tuning of system hardware and software helps in building efficient systems that minimize power and thermal dissipation for given performance constraints. Various attributes of systems can benefit from phase identification: For a given performance constraint, you can tune the system components (CPU, • memory, I/O) for minimum power usage. Upon identifying a new phase, power is allocated (or deallocated) in a manner such that performance degradation is minimized. Proactive compensation for anticipated performance variation aids in avoiding • reactive state changes and thus reactive latencies, improving performance. Available power is distributed to system components in a way that maximizes overall • performance. One strategy may involve individual allocation (or deallocation), according to each component’s share in performance gain. Activity vectors are employed to perform thermally balanced computing, thus • preventing hot spots. Activity data can also be used to coschedule tasks in a contention-free and energy-efficient manner. You can profile task characteristics related to (1) task priority, (2) energy and thermal • profile, and (2) optimization methodology regarding latency targets proportional to task priority. 96 Chapter 5 ■ Hidden Markov Model Workload phases can be exploited for adaptive architectures, guiding performance and power optimization through predictive state feedback. Because HMM uses and correlates observations with objective oriented states (such as average temperature or utilization), it may very well be a consideration in system design. Observation points can be characterized by using a reasonable set of system-wide performance counters and sensors. Hidden states that predict a control objective (such as server temperature) are measured by extracting workload phases, using feature extraction techniques. Furthermore, states share probabilistic relationships with these observations. These probabilistic relationships (also called profiles), harden and evolve with the constant use of the workload over its lifetime. Workload and Phase If you consider a normal workload behavior to be a pattern of an observed sequence, an HMM should be appropriate for mapping such patterns to one of several states. Furthermore, it is essential to build an adaptive strategy, based on embedding numerous policies that are informed by contextual and environmental inputs. The policies govern various behavioral attributes, enhancing flexibility to maximize efficiency and performance in the presence of high levels of environmental variability. HMM- based approaches correlate the system observations (usage, activity profiles) to predict the most probable system state. HMM training, using initial data and continuous reestimation, creates a profile that consists of component models, transition probabilities, and observation symbol probabilities. CHMM aids in estimating workload phases by clustering the homogeneous behavior of multiple components. Workload phases can be interpreted by a d-dimensional Gaussian (observation vector) model of k mixtures by maximizing the probability of the sequence of observations. Mixture Models for Phase Detection The foremost objective of HMM-based methodology is to predict the state of the process by establishing various phase execution boundaries in the presence of time-varying behavior. Unlike traditional approaches, which study aggregate behavior, HMM-based methods can extract representative phases and workload classification, using Gaussian mixture models (GMMs). For instance, HMM can be modeled by training itself against workloads and the corresponding phases that are characterized by an inherent behavioral pattern. These phases can be considered latent symbols (as they cannot be observed directly) that are embedded in the hidden states, which, in this case, is a workload. In a trained model these latent phase patterns can be identified through sets of observed phenomena modeled through a combination of individual mixture component probability densities, along with the presence of a hidden state (evaluated using a state transition matrix). The observations exist in the form of synthetic counters and sensors that measure the performance and power characteristics of the system as well as system components. Various functional blocks that assist in workload phase detection are described in turn in the following sections. Sensor Block In autonomic system instrumentation, endpoints (sensors/controllers) are spread all over the platform (see Figure 5-6), and the characteristics of these endpoints can differ from one platform to another. In typical server management architecture a sensor block comprises a mix of performance counters and temperature, airflow, and power sensors. These sensors are accessed through a variety of interfaces, such as PCI Express, SMBus, PECI Bus, and CPU model specific registers (MSR). The output of the sensors is statistically processed and used as feedback. The relative importance of instrumentation may vary, according to the user requirements. In some cases, because of cost constraints, instrumentation is synthesized in lieu of physical sensors by correlating the sensor data with a different set of variables. In other cases, the instrumentation accuracy of physical sensors may vary over the operating region, outside of which it may be highly inaccurate. In such cases, sensitivity is not constant over the entire operating range of the sensor, and nonlinearity results. Nonlinearity depends on the deviation of the sensor output from the ideal behavior over the full range of the sensor. It may be necessary to calibrate the sensor within the linear operating range and then use the calibrated parameters and functions for the rest of the nonlinear operating region. Sensor data 97 Chapter 5 ■ Hidden Markov Model can also observe long-term drift, owing to the aging of sensor properties over a long period of time. With digital sensors, you can also have digitization error, because the measured data are an approximation of the actual data. Additionally, limitations on sampling frequency can lead to dynamic error in the measured data. The ability of an application to measure or control an aspect of the platform depends significantly on where it is hosted and its connectivity to the instrumentation endpoint. Figure 5-6. Instrumentation telemetry in a typical Intel Xeon server platform Figure 5-6. Instrumentation telemetry in a typical Intel Xeon server platform Power, thermal, and performance variations in a system can result in suboptimal behavior that may need correction for platform policy compliance. This behavior must be predicted well in advance so that corrective action can be employed within a window of opportunity. Such conditions can be predicted, using a set of sensors that together can act as component Gaussians to model the overall feature density. Sensor Block In a platform these sensors are available as activity counters; temperature, power, and performance monitors; and so on. Classes of sensor data are as follows: • CPU performance counters: These are special-purpose hardware counters that are built into modern microprocessors to store the counts of hardware-related activities within a CPU context. The output of these counters is used to forecast common workload behaviors, in terms of CPU utilization (cache, pipeline, idle time, stall, thermal). • Memory performance counters: Memory performance counters identify memory access patterns, bandwidth utilization, dynamic random access memory (DRAM) power consumption, and proportions of DRAM command activity (read, write), which can be useful for characterizing the memory-intensive behavior of a workload. It is possible to characterize workload patterns by observing the proportion of read/ write cycles and time in the precharge, active, and idle states. 98 Chapter 5 ■ Hidden Markov Model • I/O performance counters: Three major indicators of I/O power are (1) direct memory access (DMA), (2) uncacheable access, and (3) interrupt activity. Of these the number of interrupts per cycle is the dominant indicator of I/O power. DMA indicators perform suboptimally, owing to the presence of various performance enhancements (such as write combining) in the I/O chip. I/O interrupts are typically triggered by I/O devices to indicate the completion of large data transfers. Therefore, it is possible to correlate I/O power with the appropriate device. Because this information cannot be obtained through CPU counters, it is made available by the operating system, using performance monitors. • Thermal data: In addition to the foregoing performance counters, you may also consider using thermal data, which are available in all modern components (CPU, memory, and so on) and accessible via PECI Bus. • Workload performance feedback: Control theoretic action initiates a defensive response, based on hysteresis, to reduce the effects of variation in resource demands. This response needs to be corrected if it interferes with the performance requirements of useful work. Excessive responses can slow down the system and negatively impact the effectiveness of the control action. State feedback communicates the optimal fulfillment of performance demands (or service-level objectives) at a given time. This feedback has to be estimated by forecasting the attributes of the fitness function that is related to the behavior of the work being performed and its dynamic requirements. Sensor Block Continuous state feedback trains the system-specific control actions and saves the recipe for those actions by relating it to a unique state-phase fingerprint that can repeat in the future. Model Reduction Block A model reduction block (MRB) is responsible for reducing the dimensionality of a dataset by retaining key uncorrelated and noncolinear datasets. This allows us to retain the most significant datasets—those that are sufficient to identify the phases of workload operation that demonstrate time-varying behavior. Input to the MRB model is time series data related to microarchitectural performance counters, workload performance counters, and analog sensors (measuring power, temperature, and so on). These data can be collected, using one of the many interfaces (PCI Express, SMBus, PECI Bus, and so on) illustrated in Figure 5-6. y p g You can use principal component analysis (PCA) for reducing the dimensionality of data without loss of information (see Chapter 2). The resulting output variables are the principal components, which are uncorrelated. For example, PCA transforms N inputs Y y y y yN = ( , , , , ) 1 2 3  to M principal components X x x x xM = ( , , , , ) 1 2 3  , with very little information overlap Cov x x K L , ( ) = ( ) 0 . Furthermore, variance of each principal component is arranged in descending order Var x Var x Var xM ( ) ( ) ( ) 1 2 ³ ³ ³ ( )  , such that x1 contains the most information, and xM, the least. Each principal component defines the dimensionality of an observation. Emission Block An emission block (EB) is responsible for collecting noncorrelated emissions as time series data. The raw data that are collected from sensors are noisy and have to be filtered to extract quantifiable information. The noise-reduction procedure identifies a simple dynamic system that is a good representation of the data. During the training cycle the noise reduction scheme consists of a representative distribution that fits the incoming data for a modeling window of dt. Sensor data streaming to the receiving blocks (see Figure 5-7) are delayed by a configurable time period dt. The behavior of data within the dt period is governed by the underlying equation, which is trained to reject (or reconstruct) the datapoints. 99 Chapter 5 ■ Hidden Markov Model Figure 5-7. Phase detection model, using GMM Figure 5-7. Phase detection model, using GMM The output of a sensor block is processed into an EB, which processes the sequence of polled sensor data to generate a continuous observation sequence. Additionally, an MRB scales down the number of sensor inputs by synthesizing those that are significant and providing independent characteristics. You may use a discrete set of weighted Gaussian PDFs, each with their own mean and covariance matrix, to enable better modeling of phase detection features, using continuous emission. The Gaussian mixture forms parametric models, whose parameters are estimated iteratively from training data, using Equations 5-14 and 5-15. In workload phase detection a d-dimensional Gaussian (independent emission) of k mixtures is modeled as a weighted sum of Gaussian densities (see Equation 5-16). Training Block Dynamic systems are characterized by temporal features, whose time-varying properties undergo changes during the operational period. These systems produce a temporal sequence of observations that can be analyzed for dynamic characteristics. A training block (TB) facilitates the construction of a forecast model by feeding it with metric vectors and the corresponding forecast variable for workloads with varying characteristics (such as system power). A TB performs unsupervised classification and builds data structures by partitioning the data into homogeneous clusters, such that similar objects are grouped within the same class. In the simplest case, you may use the k-means clustering algorithm, which partitions the d-dimensional emissions into k clusters, such that each emission belongs to the cluster with the nearest mean. For a given a set of emissions ( , , , ) x x xn 1 2  , the k-means clustering algorithm partitions the emissions into k sets G G G G Gk = ( , , , , ) 1 2 3  by finding the minimum distance to observation of all the k clusters: arg min x G j i x G i k j i     \|\| \|\| . - Î = å å m 2 1 100 Chapter 5 ■ Hidden Markov Model Each G element acts as a single-component Gaussian density function for k single-density states, each representing a distinctive workload phase; mi represents the mean of cluster i. Parameter Estimation Block You can use GMM to represent feature distributions in a workload phase prediction system, in which individual component densities model an underlying set of latent classes. A parameter estimation block (PEB) is responsible for estimating the parameters of the model lk that fits the data for that model. In the beginning, the model’s input data are the output sensor data from the TB, which classifies (labels) the observations as a cluster number? The classifier uses the minimum distortion, or nearest-neighbor, approach to classify the input vector, which selects the best Gaussian component from the mixture. Once the training data are buffered for each model for a time interval dt, they are used to estimate the Gaussian mixture parameters of that model. In the absence of an a priori model, a PEB initializes the number of mixtures and estimates the model parameters (ck,mk,Uk). You can use the estimation maximization (EM) method, which maximizes the likelihood ( \| ) X ll of the cluster-tagged data (see Chapter 1). The fundamental idea behind the EM algorithm is to introduce a variable (a Gaussian mixture component) that will simplify the maximization of likelihood. The EM algorithm is a two-step method: 1. E-Step: Estimate the probability distribution of each Gaussian mixture component for a given emission (X) and model (l). 2. M-Step: Estimate the joint probability distribution of the data and the latent variable (Gaussian mixture component). This step modifies the model parameters of the Gaussian mixture component to maximize the likelihood of the emission and the Gaussian component itself. Beginning with an initial model l, the EM algorithm estimates a new model ll, such that   ( \| ) ( \| ) X X ll ll ³ . The new model then becomes the starting model for the next iteration, and the process is repeated until a convergence threshold is reached. For a given sequence of d-dimensional emission vector sequences X x x xn = ( , , , ) 1 2  , the a posteriori probability for the kth mixture component is given by p k x c G U x c G U x t k k k t k k k t k M ( \| , ) ( , )( ) ( , )( ) . Parameter Estimation Block ll = × × =å m m 1 The formula used in reestimation of the model parameters is The formula used in reestimation of the model parameters is Mixture weights Mixture mean : ( \| , ) : ( \| , ) c n p k x p k x k t t n k t = = =å 1 1 ll ll m t n t t t n x p k x = = å å × 1 1 ( \| , ) ll k t t U p k x x = × - : ( \| , ) ( ll Diagonal variance mk t k T t n t t n x p k x ) ( ) ( \| , ) . × - = = å å m 1 1 ll k t t U p k x x = × - : ( \| , ) ( ll Diagonal variance mk t k T t n t t n x p k x ) ( ) ( \| , ) . × - = = å å m 1 1 ll 101 Chapter 5 ■ Hidden Markov Model This block aids in categorizing the sequence of observations to the kth Gaussian component. You can expand a single-state GCHMM into a single-density, multistate GCHMM. Phase Prediction Model Workload patterns that can be represented as application phases exhibit certain repetitive behaviors. You need methods to identify and predict repetitive phases to apply feasible dynamic management responses proactively. With a phase predictor block (PPB), you can estimate the observation sequence ahead of time by a configurable period dt (see Figure 5-8). Figure 5-8. Prediction of an observation vector for twelve phases, using an exponential smoothing function Figure 5-8. Prediction of an observation vector for twelve phases, using an exponential smoothing function PPB analysis is of particular interest when the workload is operating at phase boundaries, and control action has to be optimized for an anticipated phase. To build a simple prediction model, you estimate the future d-dimensional observation vectors, using the observation vector exponential smoothing model. Exponential smoothing can generally be represented as y x y t t t t + + - £ £ > 1 =a a a ( ) ; ; 1 0 1 0 y y t t t + + Î 1 = a( ) where Î = - t t t x y , where yt represents the predicted output of the smoothing function at instance t – 1, and xt (our standard notation) represents the raw emission from various sensors. Ît represents the prediction error at instance t. Exponential smoothing takes into account all past data, but the proportional contribution of older samples is diminished geometrically. This allows us to tune the value of a for two different models. In Figure 5-7 this is illustrated by the “Predict T + t” block. Figure 5-9 demonstrates the prediction process, in which a control process consumes the estimated phase signature and associates with a control action. The same action is repeated if the phase appears in the future. where yt represents the predicted output of the smoothing function at instance t – 1, and xt (our standard notation) represents the raw emission from various sensors. Ît represents the prediction error at instance t. Exponential smoothing takes into account all past data, but the proportional contribution of older samples is diminished geometrically. This allows us to tune the value of a for two different models. In Figure 5-7 this is illustrated by the “Predict T + t” block. Figure 5-9 demonstrates the prediction process, in which a control process consumes the estimated phase signature and associates with a control action. Phase Prediction Model The same action is repeated if the phase appears in the future. 102 Chapter 5 ■ Hidden Markov Model Figure 5-9. Phase prediction block; control processes use the prediction model and sensor observations to tune the process variables proactively Figure 5-9. Phase prediction block; control processes use the prediction model and sensor observations to tune the process variables proactively State Forecasting Block In the context of workload characterization, a state represents an interesting attribute of a feedback function that, when forecasted, triggers a corrective response proactively to avoid reactive action. Reactive response lags the control action during which the function performs housekeeping and identifies the cause of behavioral change. To prevent performance degradation, you identify a key process variable that, if predicted, can generate a proactive response. A phase represents that unique behavioral characteristic of a workload that varies with time and that needs to be predicted to avoid reactive tuning. System Adaptation The preceding sections examined a systematic approach for detecting workload phases in dynamic systems with time-varying properties. Now, the question remains as to why we need to detect system phases. Typically, workloads are subjected to arbitrary performance and environmental stresses, which are compensated for by using adaptive systems. Adaptation may have to serve functions that are mutually hostile and that pull in different directions. This results in needing to make compromises among solutions to maximize the fitness of the overall solution. An adaptation function will optimize power in a manner that delivers the desired performance, as perceived by the application. The desired performance may not necessarily be the highest performance. In real systems it is impossible to improve all aspects of the target policy to the same degree simultaneously. Therefore, systems develop various feedback control schemes that operate in hardware, software, or software-assisted hardware scenarios. Control objectives include Monitoring resource conditions in a continuous mode • Determining how and when adaptation should be performed by modeling feedback • control behavior 103 Chapter 5 ■ Hidden Markov Model Identifying real-time constraints and resource requirements for a given workload • behavior Identifying choice of available execution paths for a given autonomic element • Provisioning future resource requirements of a server, based on current resource • usage and work behavior Discovering inherent phase dependencies on component power and performance • tuning The QoS profile governs an appropriate level of resource reservation by indicating the output quality levels in a dynamic fashion. In general, the QoS maximization process starts with an initial resource allocation, which it revises, according to changing application demands and satisfaction levels. In the scenarios we have described here, it is noteworthy that intelligent control action requires an understanding of workload behavior; because workload behavior is characterized by a discrete phase, you can use this information as feedback on any control loop action. Various process control applications within a system can optimize their work function by building custom learning functions that relate the phase activity to the control action. The resulting decisions steer each control loop model to train itself dynamically, based on the historical trends, with respect to quantifiable phase behaviors. Chapter 6 Chapter 6 —John M. Allman, Evolving Brains Natural systems solve multifaceted problems using simple rules, and exhibit organized, complex, and intelligent behavior. Natural process control systems are adaptive, evolutionary, distributed (decentralized), reactive, and aware of their environment. Bioinspired computing (or biologically inspired computing) is a field of study that draws its inspiration from the sophistication of the natural world in adapting to environmental changes through self-management, self-organization, and self-learning. Bioinspired computational methods produce informatics tools that are predicated on the profound conceptions of self-adaptive distributed architectures seen in natural systems. Heuristics that imitate these natural processes can be expressed as theoretical methods of constrained optimization. Such heuristics define a representation, in the form of a fitness function. This function describes the problem, evaluates the quality of its solution, and uses its operators (such as crossover, mutation, and splicing) to generate a new set of solutions. Ashby’s (1952) book Design for a Brain discusses the mechanisms that shape the concept of adaptive behavior, as demonstrated in living organisms, and the adaptive behavior of the brain. The author defines adaptation as a form of behavior that promotes stability and that maintains the essential variables, within physiological limits. Additionally, stability is expressed as a combined function of multiple fields with changing dynamics. Therefore, stability is assumed to be associated with a coordination function between various fields. As the system and feedbacks become more complex, the achievement of stability becomes more difficult, and the likelihood of instability, greater. Biologically, an important factor in the survival of an organism is its ability to maintain its essential variables, within viable bounds. Otherwise, the organism faces the possibility of disintegration or loss of identity (dissolution, death), or both. Adaptation provides an organismic stability criterion that contributes to the maintenance of the essential variables, within viable limits; an adaptive system is a stable system (Harvey et al. 2005, the region of stability being that part of the state space where all essential variables are within physiological limits. In the natural world the brain exhibits the properties of a highly efficient informatics tool that gathers data (sensor function), infers and stores useful patterns in the data (knowledge base, memory), uses that data for planning and anticipating future actions (decision making), executes those actions (control functions), and learns from the consequences of those actions (learning). The brain acts as an information processing machine that enables a fast and adequate response to environmental perturbations by filtering disrupting triggers. Bioinspired Computing: Swarm Intelligence Brains exist because the distribution of resources necessary for survival and the hazards that threaten survival vary in space and time. —John M. Allman, Evolving Brains —John M. Allman, Evolving Brains References Baum, Leonard E. “An Equality and Associated Maximization Technique in Statistical Estimation for Probabilistic Functions of Markov Processes.” Inequalities 3 (1972): 1–8. Baum, Leonard E. “An Equality and Associated Maximization Technique in Statistical Estimation for Probabilistic Functions of Markov Processes.” Inequalities 3 (1972): 1–8. Baum, Leonard E., and J. A. Eagon. “An Inequality with Applications to Statistical Estimation for Probabilistic Functions of Markov Processes and to a Model for Ecology.” Bulletin of the American Mathematical Society 73, no. 3 (1967): 360–363. http://projecteuclid.org/euclid.bams/1183528841. Baum, Leonard E., and J. A. Eagon. “An Inequality with Applications to Statistical Estimation for Probabilistic Functions of Markov Processes and to a Model for Ecology.” Bulletin of the American Mathematical Society 73, no. 3 (1967): 360–363. http://projecteuclid.org/euclid.bams/1183528841. Baum, Leonard E., and Ted Petrie. “Statistical Inference for Probabilistic Functions of Finite State Markov Chains.” Annals of Mathematical Statistics (1966): 1554–1563. http://projecteuclid.org/euclid.aoms/1177699147. Baum, Leonard E., and Ted Petrie. “Statistical Inference for Probabilistic Functions of Finite State Markov Chains.” Annals of Mathematical Statistics (1966): 1554–1563. http://projecteuclid.org/euclid.aoms/1177699147. Baum, Leonard E., and George Sell. “Growth Transformations for Functions on Manifolds.” Pacific Journal of Mathematics 27, no. 2 (1968): 211–227. http://projecteuclid.org/euclid.pjm/1102983899. Baum, Leonard E. “An Equality and Associated Maximization Technique in Statistical Estimation for Probabilistic Functions of Markov Processes.” Inequalities 3 (1972): 1–8. Juang, Bing-Hwang, Stephen E. Levinson, and M. Mohan Sondhi. “Maximum Likelihood Estimation for Multivariate Mixture Observations of Markov Chains (Corresp.).” IEEE Transactions on Information Theory 32, no. 2 (1986): 307–309. Liporace, L. “Maximum Likelihood Estimation for Multivariate Observations of Markov Sources.” IEEE Transactions on Information Theory 28, no. 5 (1982): 729–734. Sherwood, Timothy, Erez Perelman, Greg Hamerly, and Brad Calder. “Automatically Characterizing Large Scale Program Behavior.” ACM SIGARCH Computer Architecture News 30, no. 5 (2002): 45–57. Rabiner, Lawrence. “A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition.” Proceedings of the IEEE 77, no. 2 (1989): 257–286. Stratonovich, R. L. “Conditional Markov Processes.” Theory of Probability and Its Applications 5, no. 2 (1960): 156–178. 104 Applications Bioinspired computing systems confront complex problems by exploiting the design principals and computational techniques encountered in natural processes. These systems possess a deep understanding of the distributed processes that exist in nature and use the concepts of theoretical biology to produce informatics tools that are robust, scalable, and flexible. Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Jacob, Lanyon-Hogg, Nadgir, and Yassin (2004) conceptualized autonomic computing as analogous to the autonomic nervous system (ANS), which constitutes an essential element of the peripheral nervous system. Autonomic computing resembles the ANS, insofar as the latter is composed of a hierarchy of numerous self-governing components that give monitoring and control functions the ability to transmit messages to various organs at a subconscious level. While the ANS monitors the “operating environment,” it also maintains the required equilibrium by enacting the optimal changes at a subconscious level. In general, the ANS is responsible for controlling various actions related to digestion, perspiration, heart rate, respiration, salivation, pupil dilation, and other such functions. The ANS facilitates such control systems by actively monitoring, integrating, and analyzing input stimuli via sensory channels and distributing electrochemical impulses via motor channels to generate control responses to various environmental conditions. The brain and the ANS inspire us with design principles abstracted to informatics tools, such as artificial neural networks (ANNs) and autonomic computing. But, nature motivates us with many more naturally occurring and highly efficient computational phenomena that, when modeled effectively, can improve the use of computers in solving complex optimization problems. Such phenomena exist in the form of social interactions, evolution, natural selection, biodegradation, swarm behavior, immune systems, cross-membrane molecular interactions, and so on. Software- or field programmable gate array– (FPGA-) based agents can model these natural forms of computational and collective intelligence as evolutionary algorithms, swarm intelligence (SI), artificial immune systems, artificial life, membrane computing, DNA computing, quantum computing, and so on. The abstractions derived from natural processes formalize the distributed computing paradigm, in which independent entities improve their reactive behaviors by interacting with other entities, using a well-defined protocol, and fine-tuning their control actions. —John M. Allman, Evolving Brains 105 Evolvable Hardware Evolvable hardware (EHW) is a novel field, in which practical circuits that exhibit desirable behaviors are synthesized, using evolutionary algorithms. In their rudimentary configuration, such algorithms—such as genetic algorithms (GAs)—influence a population of existing circuits to synthesize a set of new candidate circuits targeted to fulfill the design specifications. The quality of the circuit is evaluated, using a fitness function that ascertains if all the design requirements are met. Such techniques are useful when design specifications merely specify the desired behavior or when hardware needs to adapt dynamically and autonomously to changing operating conditions. In both cases, design specifications lack adequate information to warrant the use of conventional methods. An evolvable circuit can be synthesized, using a simulation tool (such as SPICE), a physical device (such as an FPGA), or a configurable logic. In an evolutionary design approach it is not necessary to have a priori knowledge of the problem domain. In many cases, it may be either too complex or too expensive to acquire such information. As the complexity of the circuitsgrows, it becomes increasingly challenging to comprehend the dynamics between the various components of the circuit. EHW envisages evolutionary design techniques that facilitate development of online hardware that adapts its architecture, according to environmental changes or perturbations. An example of this technique is cache quality of service (CQoS) logic (Iyer 2004), which performs dynamic partitioning of the cache among selected cores to improve the performance of the system. The automation methodology employs central processing unit (CPU) performance counter feedback in a GA to evolve an optimal cache distribution scheme. The GA chromosome contains all the building blocks for a solution to the problem at hand in a form that is suitable for the genetic operators and the fitness function. 106 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence where N is the number of workloads, and (fk) is the miss rate of each workload (see Equation 6-2), attempts to maximize the average performance (Favg) of all workloads. The contribution of each workload k can be weighted (lk), based on the effect of throughput by individual workload. F avg k k k N k k N 1 1 0 1 0 1 1 = - × = = = å å . , . l f l (6-1) fk k miss k miss k hit LLC LLC LLC = + (6-2) (6-1) (6-2) The workload-dependent function (see Equation 6-3) biases the characteristic behavior of a workload and tries to improve performance, based on that characteristic. This function, where (fk) is the fraction of the miss rate of each workload over the total miss rate of the cores, and (yk) is the fraction of the cache size allocated to each core over the total cache size, allows us to identify certain characteristics that may be capable of boosting the service-level objectives for a given environment. As shown in Equation 6-3, a certain bias can be generated to build pressure for allocation of cache sizes (Sk) for each core k that is proportional to the LLC miss rate ratio of that core (see Equation 6-4). F abs avg k k N k k 2 1 0 1 0 1 = - × - æ è ç ö ø ÷ =å . . l j y (6-3) j f f k k j j N = =å 1 (6-4a) y k k j j N S S = =å 1 (6-4b) (6-3) (6-4b) Finally, the overall fitness (see Equation 6-5) can be defined as the weighted proportion of each individual fitness, as given in Equations 6-1 and 6-3: F F F avg avg avg = × + - × a a 1 1 2 ( ) . (6-5) (6-5) Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Each CPU core node is represented by an n-bit binary number, called a gene. These n-bit genes define the representation, in which each bit and its position correspond to an individual cache slice slot of the total last-level cache (LLC). The GA-based evolutionary algorithm dynamically partitions the cache into private and shared regions, without prior knowledge of the workload profile, and allows sharing among the cores. The advantages of evolutionary methodology in partitioning the cache are that it is practical and significantly reduces the overall miss rate of the cache, at the cost of a small evaluation (training) time overhead. This methodology ensures optimal cache partitioning, with a view to increasing the instructions per cycle (IPC) and reducing the cache miss rate, thus ultimately enhancing overall performance. Each slot is assumed to host the same-sized cache partition. Figure 6-1 depicts a chromosome structure with an 80-bit string (20 bits per core) that represents the association of each core with a 1MB cache slot. Figure 6-1. The chromosome structure of the cache clustering, based on workload behavior, using four cores and 20 cache slots sized 1MB. For example, for core 1 cache slots, 0, 1, and 4 are private, and cache slot 5 is shared with core 2. The complete string describes the cache association of each core with a cache slot The cache-clustering fitness function is a weighted function capable of measuring the quality or performance of a solution—in this case, a cache-partitioning scheme that improves workload performance among CPU cores. This function is maximized by the GA system in the process of evolutionary optimization. A fitness function must include and correctly represent all or at least the most important factors that affect the performance of the system. You may need functions that represent workload-independent and workload-dependent characteristics. The workload-independent function in Equation 6-1 executes the global fair allocation of cache, without biasing the characteristic behavior of a workload. This function, 107 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence where N is the number of workloads, and (fk) is the miss rate of each workload (see Equation 6-2), attempts to maximize the average performance (Favg) of all workloads. The contribution of each workload k can be weighted (lk), based on the effect of throughput by individual workload. Bioinspired Networking Communication and network technologies have gained a lot of traction in recent years, owing to advancements in cloud-based networking (CBN), networked embedded systems, wireless sensor networks (WSNs), the Internet of Things (IOT), software-defined networking (SDN), and so on. Furthermore, enterprise-class networking solutions are being developed to deliver high resiliency, high availability, and high reliability through capacity planning, traffic engineering, throughput management, and overlaying of multitenant applications, using the existing Internet infrastructure. As the network scales, the search space for the optimal route increases dramatically. The number of routing tables and the amount of traffic overhead overwhelm network bandwidth. Ideally, we would like to have efficient, self-organizing networks with low route-finding latencies (or overhead) and high probabilities of successful transmission. Nevertheless, significant challenges prevent us from realizing the practical implementation of new networking paradigms. In addition to the need for scalability, availability, and survivability, these challenges arise from resource constraints, absence of centralized architecture, and the dynamic nature of networking. However, similar phenomena are also found in natural processes that are successfully dealt with through adaptation in biological systems. Biological communication paradigms are evolutionary; resilient to failure; adaptive to environmental conditions; and collaborative, on the basis of a simple sets of rules. 108 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Bioinspired networks self-organize by apprehending the mutual interactions of components that produce complex patterns. These interactions facilitate behavioral responses through information transfer between interacting components as well as through the interaction of components with the environment. Gianni, Ducatelle, and Gambardella (2005) presented the AntHocNet design for stigmergy-driven shortest-path discovery, based on a self-organizing behavior exemplified in ant colonies. Similar routing algorithms exist for packet-switched networks, such as AntNet (Di Caro and Dorigo 1998), and circuit- switched networks, such as artificial bee colony (ABC) (Schoonderwoerd et al. 1997). The AntHocNet algorithm inserts limited routing information in “Hello” messages so that the information regarding existing paths can propagate throughout the network, using node-to-node information exchange. This process is equivalent to collective ant learning behavior, in which ants swarm together to gather and maintain updated information. Artificial ants instigate the stigmergic communication process by acting as autonomous agents that update and follow the pheromone table (path). Similar to routing ants, the pheromone table explores the high-probability paths that can be used for routing data packets. Additionally, ants put their limited resources toward optimizing global behavior to identify the food source in a cost-effective manner. Bioinspired Networking This behavior inspires resource-efficient networking techniques. Given their dynamic nature and lack of infrastructure, networks are also prone to failure and delay. Therefore, networks should have capability to self-organize and self-heal in real time. Dynamic networks (especially mobile ad hoc networks) may use the bioequivalent of epidemic models both to describe and to adapt information dissemination. Papadopouli and Schulzrinne (2000) described a simple stochastic epidemic model that estimates the delay until data diffuse to all mobile devices. Carreras et al. (2006) proposed an epidemic spreading mechanism for efficient information dissemination in clustered networks and for opportunistic routing in delay-tolerant networks. The authors used eigenvector centrality (EVC) as an objective fitness measure of the ability of nodes to spread an epidemic (information) within the network. The resulting topology built using EVC defines the regions in which the epidemic spreads extremely fast. Infection fronts (information) spread toward highly connected neighborhoods (EVC), because spreading is fastest there. ( ) p g y g ( ) p g Resource-constrained sensors, such as wireless sensors, are limited in energy, bandwidth, storage, and processing capabilities. Large numbers of such sensors create a sensor management problem. At the network layer the solution entails setting up an energy-efficient route that transmits the nonredundant data from the source to the sink to maximize the battery’s and sensors’ lives. This is done while adapting to changing connectivity resulting from the failure of some nodes and the powering up of new nodes. Khanna, Liu, and Chen (2009) demonstrated that the GA-based approach optimizes the sensor network to maximize energy usage as well as battery conservation and route optimization. Each sensor is encoded with a gene that identifies it and any other specific information it may contain. This information may be related to sensor objectivity, next hop, cluster domain, and so on. The GA adaptation process evolves optimal cluster boundaries, in terms of addition, deletion, or modified sensor objectives. The process also discovers optimal routes from cluster heads to the sink. Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Chapter 6 ■ Bioinspired Computing: Swarm Intelligence One way to optimize power in a datacenter is to regulate or redistribute the load of a rack-level server unit autonomously through management of job admission, distribution, and continuous balancing. One way to optimize power in a datacenter is to regulate or redistribute the load of a rack-level server unit autonomously through management of job admission, distribution, and continuous balancing. Barbagallo et al. (2010) put forward self-organizing architectures for dynamic workload distribution, using a decentralized approach built on top of SelfLet architecture. SelfLet architecture (Devescovi et al. 2007) is a bioinspired system that possesses the capability to change and adapt its internal behavior dynamically, according to variations in the environment. SelfLet uses autonomic reasoning to facilitate self-management capabilities. SelfLet itself represents a service framework built using a self-sufficient piece of code that interacts with a group of other SelfLet individuals and that cooperates through high-level functions. Each SelfLet either offers or consumes a service and interacts via a communication framework. The authors used self-organization algorithms based on the principles of collective decision making in animal colonies. Self-organizing in these colonies is characterized by scouting, evaluating, deliberating, and decision-making functions. Self-organization in a datacenter can be summarized using similar entities, as follows: • Colony: A collection of virtual machines (VMs) residing on the same server. • Scout: Explores multiple physical servers and compares them with the original one. A scout can be characterized by its current location, lifetime, and information stored related to each server class that it examined. • Scout: Explores multiple physical servers and compares them with the original one. A scout can be characterized by its current location, lifetime, and information stored related to each server class that it examined. • Server manager: Communicates with the scouts and makes decisions related to the movements of VMs. • Server manager: Communicates with the scouts and makes decisions related to the movements of VMs. Based on the collective data from multiple scouts, a decision is made either to permit or to inhibit migration. As in biological systems, the decision whether to migrate is not deterministic and follows a probability distribution. This avoids a reactive migration, which could result in instability and oscillatory behavior. Furthermore, like biological systems, individual servers may propagate an inhibitor flag to prevent migration in the middle of critical operations. Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Li and Parashar (2003) developed AutoMate architecture to investigate bioinspired conceptual models and implementation designs for developing and executing self-managing (i.e., configuring, healing, optimizing, and protecting) grid applications, while dealing with the challenges of complexity, dynamism, and heterogeneity. AutoMate architecture is built on three operative principles: Separating policies from the mechanisms related to algorithms, communication • protocols, and so on that drive those policies Applying context-, constraint-, and aspect-based composition techniques • to applications to synthesize dynamic requirements for compute resources, performance guarantees, and QoS Developing proactive- and reactive-component management to opti • utilization and application performance in dynamic environments Datacenter Optimization The size and complexity of modern distributed datacenter systems are expanding every day. The volume of information that must be processed in real time has been growing geometrically over the past few years, requiring peak processing capabilities to rise in concert. Despite the superior performance per watt that newer platforms deliver, handling peak loads continues to call for higher power delivery and heat dissipation capacities per cubic meter in enterprise information technology (IT) and datacenter facilities, with 63 percent of the total cost of ownership going toward powering, cooling, and electricity delivery infrastructure. In contrast to the traditional focus on delivering the highest throughput or lowest response time, unconstrained by power, these realities have made it a more compelling proposition to minimize the amount of energy consumed, relative to computational work performed, while meeting responsiveness targets. In particular, dynamically conserving power when some machines do not need to be in full use translates directly into cost savings and creates greater allowance for other, more power-constrained servers. 109 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Chapter 6 ■ Bioinspired Computing: Swarm Intelligence and defining operators to produce a set of new solutions. Broadly, bioinspired algorithms can be divided into three major classes: evolutionary algorithms, swarm-based algorithms, and ecological algorithms. These classes are further divided into subclasses, based on their inspiration from specific cases of naturally occurring processes involving ants, fireflies, bacteria, bees, birds, and so on. and defining operators to produce a set of new solutions. Broadly, bioinspired algorithms can be divided into three major classes: evolutionary algorithms, swarm-based algorithms, and ecological algorithms. These classes are further divided into subclasses, based on their inspiration from specific cases of naturally occurring processes involving ants, fireflies, bacteria, bees, birds, and so on. Swarm Intelligence Swarm intelligence (SI) is a type of artificial intelligence based on the collective behavior of decentralized, self-organized systems. The term was introduced by Beni and Wang (1989), in the context of cellular robotic systems. SI typically comprises a collection of unsophisticated agents, called boids, that interact locally with other agents as well as with the environment, using extremely elementary rules. No centralized control infrastructure governs an individual agent’s behavior or interactions. Instead, local and random interaction between participating agents leads to an intelligent global behavior unattributable to individual agents. In other words, collective interaction at peer level leads to a sophisticated phenomenon globally. Natural examples of SI include ant colonies, bird flocking, animal herding, bacterial growth, and fish schooling. SI-inspired systems include positive feedback, negative feedback, amplification of fluctuations, and multiple interactions between multiagents. g Autonomic computing and SI are closely related. For example, through the tuning of system parameters, the self-configuration aspect can be achieved autonomically rather than manually. In the natural world the local process indicators can change, be reinforced, or reach a threshold, reflecting the actual dynamic swarm situation. Clearly, system performance can be optimized through interaction between multiple local agents. Also, system robustness can be guaranteed through this kind of parallel multiagent interaction. Finally, security and load balancing can be fulfilled with careful parameter and rule design. The appropriate tradeoff between the purely reactive behavior promoted by traditional stigmergy and the purely cognitive behavior promoted by artificial intelligence approaches has to be determined. Stigmergy is a mechanism occurring in many social animal societies that contrives to solve complex problems using a decentralized approach in a self-organized system. This system rewards positive feedback, while penalizing the negative. As a result, the system enables a complex, intelligent infrastructure that needs no planning, control, or complex interactions between the agents. The social aspects support efficient collaboration between elementary agents, which lack memory, intelligence, and even awareness of each other. Bioinspired Computing Algorithms Bioinspired computing methods are metaheuristics that imitate methods for solving optimization problems in natural processes. These heuristics deliver a robust and decentralized compute engine that can perform in noisy ecosystems and yet deliver a desired behavior, while operating within time, energy, and power constraints. Such computing methods have been used in almost all areas of optimization, knowledge discovery, and big data analytics, including computer networks, image processing, WSNs, security, control systems, biomedical systems, and robotics. The following sections give a brief overview of bioinspired optimization algorithms that are computationally efficient alternatives to the traditional deterministic approach—an approach that does not scale well and that requires massive computational effort. Designing bioinspired algorithms involves identifying a suitable representation of the problem, developing a fitness function to evaluate the quality of solution, 110 Ant Colony Optimization Algorithm In the natural world, ants wander randomly until they find a path that leads to food. This behavior has inspired a variant of SI called the ant colony optimization (ACO) algorithm. In the ACO scenario (Dorigo, Di Caro, and Gambardella 1999) ants communicate with other ants to exchange status information regarding food sources through changes in the environmental medium by depositing pheromones. The status information is exchanged within a local scope, and the context is transferred only to ants at the location of pheromone deposition. After finding food, these ants return to the colony, while laying down pheromones for other ants to follow. Upon discovering the food trail, the other ants abandon their random food search and follow the pheromone trail, thereby reinforcing the original path. Over time, however, the pheromone trail tends to evaporate and lose its attractive property. If the round-trip time between the ant colony and the food source is great, the pheromone can evaporate faster than it can be reinforced. In contrast, a short pheromone trail has a greater pheromone density and can be reinforced faster than it evaporates. The pheromone evaporation process is analogous to avoiding convergence to a local optimal; the process avoids strengthening the nonoptimal solution, while aiding the unconstrained exploration of the solution space. In general, variation in the pheromone quantity on the edge allows for the choice of a specific edge. A stable system is a network of strong edges that adapt to active variations and environmental changes. Because of dynamic variations in the interactive environment, 111 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence certain edges are reinforced through positive feedback, whereas others are weakened because of negative feedback. A slight variation in the edges can result in an alternate route that remains valid until other edges exhibit stronger traits. For instance, if the pheromone trail to a single food source is reinforced, it will take much longer to discover alternate sources that may be optimally suited for the colony, in terms of distance or abundance. ACO attempts to find a path to the solution that is likely to be followed by other agents, thereby building positive feedback that eventually leads to a single path to the solution. certain edges are reinforced through positive feedback, whereas others are weakened because of negative feedback. Ant Colony Optimization Algorithm A slight variation in the edges can result in an alternate route that remains valid until other edges exhibit stronger traits. For instance, if the pheromone trail to a single food source is reinforced, it will take much longer to discover alternate sources that may be optimally suited for the colony, in terms of distance or abundance. ACO attempts to find a path to the solution that is likely to be followed by other agents, thereby building positive feedback that eventually leads to a single path to the solution. ACO methodologies differ from evolutionary algorithms in one main regard. In evolutionary algorithms, such as GA, all knowledge about the problem is contained in the current population, whereas in ACO algorithms a memory of past performance is maintained in the form of pheromone trails Dorigo, Di Caro, and Gambardella (1999) represented ants as playing the role of environmental signals, and the pheromone update rule, the role of the automaton learning rule. In ACO the environmental signals/ants are stochastically biased, by means of their probabilistic transition rule, to direct the learning process toward the most interesting regions of the search space. That is, the whole environment has a key, active role in the learning of good state-action pairs. The basic ACO rule can be defined by the following process (Engelbrecht 2006; Wang et al. 2007): 1. Create nr global ants; each ant visits each food source exactly once. 2. Evaluate the fitness of each food source; a distant food source has a lesser probability of being chosen. 3. Update the ants’ pheromone and the age of weak regions. 4. Move local ants to better regions, based on the pheromone intensity, to improve their fitness; otherwise, choose new random search directions. 5. Update the ants’ pheromone to all the regions they traversed. 6. After each iteration, evaporate the ants’ pheromone. Ants are attracted to the regions, based on the intensity of the pheromone at time t. As the pheromone evaporates, that region becomes less attractive to the ant and is finally abandoned. Ant Colony Optimization Algorithm The probability of an ant k transitioning from region i to region j at time t is P i j t t d t t d t j N k i j i j i n i n n N i k i k ( , , ) ( ) ( ) ( ) ( ) , , , , , = × × Î Îå t t a b a b if , (6-6) (6-6) where ti,j(t) = pheromone trail region, represented by edges i and j at time t di,j(t) = distance between source (i) and destination (j) locations Ni k = feasible neighborhood of ant k at source i a = relative significance of the pheromone trail b = relative significance of the distance between source and destination ACO techniques can be used for knowledge discovery corresponding to learning the functional relationship between variables, changes in data pattern, and data classification. The social behavior of the ants suggests the notion of formulating an infrastructure that fosters the concept of self-organization, using natural interactions and local information to solve complex computational problems. Dorigo, Di Caro, and Gambardella (1999) described a solution to the Traveling Salesman Problem (TSP), in which m artificial ants concurrently build a tour of the TSP. Initially, k ants are placed on randomly selected cities. At each step the kth ant applies a probabilistic action choice rule to resolve which city to visit next. The probability that an ant chooses to travel from city i to city j ( J Ni k Î ) is given in Equation 6-6, where Ni k defines a potential neighborhood of k cities when the ant is in city j. If a = 0, the closest cities are more likely to be selected; if b = 0, then only pheromone amplification is used, without any heuristic bias. Each ant k retains a memory area, where it generates the tour, computes the length of the tour, and retraces the path to deposit the pheromone to the arcs of the tour. Pheromone trails are updated after all ants have constructed their tour. This is done by decreasing the pheromone by a constant factor on all arcs (evaporation) and then successively adding the pheromone to the arcs crossed by ants in their tours. Pheromone evaporation and updating are implemented in Equation 6-7. Arcs that are part of a short route and are visited by many ants receive more pheromone and are therefore more likely to be chosen by ants in future iterations of the algorithm. b = relative significance of the distance between source and destination b = relative significance of the distance between source and destination The positive parameters a and b define the relationship between pheromone and heuristic information. Therefore, the probability of a trail that is chosen by ant k is a function of distance and the density of the pheromone that already exists on that trail at time t. The significance of intensity and distance to the cost function is determined by a and b, respectively. Thus, the better the region is, the more attraction it has to the successive ants. The pheromone concentration in the region is updated as a function of constant evaporation (p) and new deposits (Dtk) by the ants attracted to this region, such that 112 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence t t t i j i j k i j k m t p t t , , , , ( ) ( ) ( ) + = × + =å 1 1 D (6-7) if i j S L k k i j k i j ( , ) : , , , , , Î = Dt 1 (6-8) (6-7) (6-8) where where p = evaporation constant, whose value can be set between 0 and 1 and represents the rate at which the pheromone evaporates p = evaporation constant, whose value can be set between 0 and 1 and represents the rate at which the pheromone evaporates p = evaporation constant, whose value can be set between 0 and 1 and represents the rate at which the pheromone evaporates Lk,i,j = length of the tour by ant k, with shorter tours resulting in higher pheromone density Dtk,i,j = amount of pheromone deposited by ant k in region (i, j). The probability of local ants’ selecting a region is proportional to its pheromone trail. The pheromone is affected by the evaporation rate, ant age, and growth of fitness. Thus, this pheromone-based selection mechanism is capable of promoting the solution candidate update, which is suitable for handling the changing environments in optimization. ACO techniques can be used for knowledge discovery corresponding to learning the functional relationship between variables, changes in data pattern, and data classification. The social behavior of the ants suggests the notion of formulating an infrastructure that fosters the concept of self-organization, using natural interactions and local information to solve complex computational problems. Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Chapter 6 ■ Bioinspired Computing: Swarm Intelligence PSO can search a large solution space, while making no assumptions regarding the problem being optimized. PSO looks for an optimal solution by moving the particle in the solution space, relative to its current position, at a certain velocity and guided by a fitness function: a particle’s movement is controlled by changing its velocity (accelerating), guided by its current best position (pbest) and the best position found in its neighborhood (gbest)up to that point. The gbest solution is iteratively updated as better positions are found. The combined (collective) exploration of all the particles moves the swarm toward the best solution. In their quest for the global optimum, particles in the swarm realign to cluster around the suboptimal. Once a particle is close to the global optimum, other particles are attracted to it, with a high probability of finding the best solution. In each iteration k, particle i updates its position and velocity, according to the following equations: v x x i k i k i k + + = - 1 1 (6-9) x x v c r pbest x c r gbest x i k i k i k i k i k i k i k + = + + - + - 1 1 1 2 2 ( ) ( ) (6-10) v v c r pbest x c r gbest x i k i k i k i k i k i k + = + - + - 1 1 1 2 2 ( ) ( ), (6-11) (6-9) v x x i k i k i k + + = - 1 1 where xi k= particle i position for the kth iteration xi k= particle i position for the kth iteration vi k = particle i velocity for the kth iteration r1,r2 = random numbers between 0 and 1 r1,r2 = random numbers between 0 and 1 The PSO algorithm is composed of the following steps for iteration k: 1. Initialize the swarm by allocating a random position xi 0 to each particle i of the swarm bounded by the problem space. 2. Evaluate the fitness of each particle i, relative to its current position xi k. 3. Particle Swarm Optimization Particle swarm optimization (PSO) is a stochastic computational technique that iteratively optimizes the candidate solution of a problem until it attains the target fitness (or quality) (Kennedy and Eberhart 1995). This technique is biologically inspired by the social behavior of bird flocking and fish schooling. Owing to its simplicity and computational efficiency, PSO has been successfully applied to many engineering research and optimization applications. Particle in PSO denotes an individual member of a population that searches for optimal behavior when subjected to velocity and acceleration in a large search space. Each particle in the swarm explores the coordinates of the solution space and records the following four vectors, relative to the best solutions (fitness) achieved in that process: Particle’s current coordinates • Particle’s velocity, with respect to magnitude and direction • Coordinates (position) associated with the particle’s local best solution achieved up • to that point (pbest) Coordinates (position) associated with the particle neighborhood’s best solution • achieved up to that point (gbest) 113 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Compare the particle i fitness with its pbesti k-1; if the current fitness is greater than the pbest, set the pbest value (pbesti k) to the current fitness value. 4. Select the particle j with the best fitness (pbest j k); mark this fitness gbesti k. 5. Evaluate the new position xi k+1 of particle (i), using Equations 6–10. 6. Evaluate the new velocity vi k+1 of particle (i), using Equations 6–11. The process repeats until the stopping criteria are met, or the best solution is found. Unlike evolutionary algorithms, such as GA, particles improve the PSO algorithm’s fitness, using the current global optimum, without evolutionary operators. Because of its distributed nature and ability to operate under noisy conditions, PSO can prove to be a useful technique for workload balancing, with respect to power consumption, heat generation, and QoS requirements in cloud computing. The workload has to be distributed in such a manner that power consumption is minimized, thermal hot spots are eliminated, and performance targets are fulfilled. Dynamic placement of the workload in a system (or cluster of compute machines) triggers dynamic variations in the availability of compute, memory, network, input/output (I/O), and storage resources. Optimal system operation results in complex workload distribution choices, owing to the many degrees of freedom for allocating the load in a dynamically varying resource pool. The PSO solution continuously searches for the dynamically shifting optimum to identify the placement target of the new or upcoming load. 114 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Yassa et al. (2013) proposed DVFS multiobjective discrete particle swarm optimization (DVFS-MODPSO) for workload scheduling in a distributed environment. DVFS-MODPSO implements the multiobjective optimization of several conflicting goals—minimizing execution time, execution cost, and energy consumption—and produces a set of nondominated solutions to offer flexibility in choosing a schedule that meets the QoS targets. DVFS-MODPSO defines a triplet <Ti, Pj, Vk> that characterizes the position of a particle and that represents a reasonable solution to the workload scheduling problem. Each triplet allocates the task Ti to a processor Pj with a voltage scaling Vk. The results demonstrate that DVFS-MODPSO generates a set of Pareto optimal solutions for execution time, execution cost, and power consumption. Solving a global optimization problem using a traditional approach involves precise function description and gradient evaluation, which may be expensive, time-consuming, hard to achieve, or impossible. Artificial Bee Colony Algorithm The artificial bee colony (ABC) algorithm is a swarm-based metaheuristic inspired by the foraging behavior of the honeybee that was proposed by Karaboga, Dervis, and Basturk (2007). The model consists of three groups of honey bees that facilitate an optimal search for food sources. Employed bees attach themselves to a specific food source and share the information regarding its profitability through waggle dancing to recruit new bees. An onlooker bee is an unemployed bee that evaluates the quality of the food source by observing the waggle dances on the floor and deploys itself toward the most profitable food source. A scout bee searches for new food sources randomly and presents information associated with their quality through a waggle dance. The employed bee whose food source has been exhausted transforms itself into a scout bee and searches for new food sources. The principal components of the ABC algorithm are as follows: • Food sources: A food source represents the candidate solution to an optimization problem. To select an optimal food source, an employed bee evaluates the overall quality of a food source, as measured by its proximity to the hive, the quantity and quality of the food (nectar), and the level of difficulty in extracting the food. • Employed bees: Employed bees are employed at a specific food source, which they exploit to gather nectar. The bees collect information related to the distance, direction, and quality of the food source and share it with other bees, waiting on the dance floor. An employed bee attempts to improve its solution (food source) by reevaluating the coordinates in the neighborhood of its memorized coordinates, using multiple trials. • Unemployed bees: Scout bees and onlooker bees are both in this category. They evaluate the profitability of potential food sources, either through random scouting or through information shared by employed bees. This evaluation helps convert an unemployed bee to an employed bee by facilitating selection of the most profitable food source. • Measure of quality (fitness): The quality of the food source—characterized by its proximity to the hive, the quantity and quality of its nectar, and the relative difficulty of extracting the nectar—can be summarized, using a single quantity: fitness. • Knowledge exchange: Knowledge exchange is the critical element of the ABC algorithm. Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Compounding the problem, many complex optimization problems exhibit a noisy behavior that renders methods such as implicit filtering and evolutionary gradient search almost ineffective. In contrast, PSO algorithms operate in a stable and efficient manner, even in the presence of noise. In many cases, noise can be beneficial, because it helps avoid local minimum solutions and converge faster to the globally optimal solution. Owing to their simplicity, PSO algorithms have also been proposed as an alternative to gradient-based techniques for detecting Pareto optimal solutions to multiobjective optimization problems. Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Chapter 6 ■ Bioinspired Computing: Swarm Intelligence The ABC algorithm can be used as a technique for load balancing in a datacenter. Load balancing attempts to optimize resource utilizationresponse time, throughput, and thermal hot spots. Load balancing can be implemented by reallocating existing tasks or allocating new tasks to an existing compute node. These compute nodes act as potential candidates for hosting the workload, which, when loaded effectively, can improve the efficiency of the datacenter. Each compute node advertises its prevailing characteristics (or fingerprint) related to utilization, operational phase, time spent in that phase, cache behavior, temperature, and power consumption. The fitness function defines a compute node’s ability to host new work at a future time. For example, a candidate node that can compensate for the forecasted thermal variance in its neighborhood will have a higher fitness, compared with other nodes with similar characteristics but existing in a fully balanced cluster. Each server consists of management microcontrollers that act as idle, employed, onlooker, or scout bees. Scout bees are appointed in a random manner, whereas employed and onlooker bees follow the swarm behavior that is influenced by the fitness outcome. While an employed bee (management node) records the benefits of hosting the load on the existing node, an onlooker bee (waiting in a work queue), in its effort to become employed, analyzes the collective information delivered through scout and employed bees. Once the compute target is selected, the onlooker bee attempts to host the queued work on that target. The technique of load balancing using ABC deploys the following agents: • Scout bee: Acts as a random agent that constitutes approximately 2 percent of the total compute nodes in a datacenter. These agents execute the scout function, using the management agent corresponding to the compute node tagged as scout bee. Scout agents collect neighborhood-specific information related to hot spots, average power consumption, and availability of compute resources. • Employed bee: Acts as an agent that assists in loading and collecting the operational statistics of the load that is executing on the compute node tagged as employed bee. These statistics include usage, memory bandwidth, noisy behavior of the cache, and I/O contention. • Onlooker bee: Acts as an agent of the potential workload waiting in the queue. Each agent identifies the best target to host this workload. Each agent identifies the best target to host this workload. Artificial Bee Colony Algorithm Knowledge is shared within the staging area, called the dance area; here, bees exchange information related to the fitness and coordinates (angle, distance) of the food source through the waggle dance. 115 2. Repeat. Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Two principal factors that attract bees to a specific node or neighborhood, in this example, are the availability of thermal variance and compute resources. As the thermal variance or compute resource diminishes, that node becomes less attractive and is eventually abandoned. While a node remains attractive, an employed bee repeatedly visits that location and encourages onlooker bees to host work in its neighborhood. Scout bees identify additional targets or neighborhoods with high fitness that can be exploited by unemployed bees. The main steps of the ABC algorithm are generalized as follows The main steps of the ABC algorithm are generalized as follows: 1. Random food sources are allocated to each employed bee. Repeat: a. Each employed bee visits the food source, according to the information stored in the bee’s memory. The bee evaluates the quantity and quality of the food (nectar) and performs the waggle dance in the hive. b. Each onlooker bee observes the waggle dance of the employed bees, and some of them select the food source, based on the information communicated through the dance. c. Once the food source is abandoned, new sources are identified by the scout bees. d. The new food source is identified by the scout bees and attracts the swarm, depending on the quality of the nectar. e. Requirements are met. 2. Repeat. 116 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence where where q i( j,k,l) = position of the ith bacterium in the jth chemotactic, k th reproductive, and lth elimination–dispersal step q i( j,k,l) = position of the ith bacterium in the jth chemotactic, k th reproductive, and lth elimination–dispersal step vi( j) = step size in a random direction during the tumble Bacterial Foraging Optimization Algorithm The bacterial foraging optimization (BF0) algorithm (Passino 2002) models the microbiological phenomenon of organized behavior in a bacterial colony. The BFO algorithm for modeling the social foraging behavior of Escherichia coli (E. coli) can be used to solve real-world numeric optimization problems. BFO is primarily composed of three processes: chemotaxis, reproduction, and elimination–dispersal. Chemotaxis is defined as cell movement in response to a chemical stimulus. This method is used by many single- and multicellular organisms to discover their food. Bacterial chemotaxis represents the signal transduction system, which stimulates the behavior of bacterial movement. Reproduction characterizes natural selection, which favors the best-adapted bacteria with a higher likelihood of survival than the less-adapted bacteria. Natural selection allows the selected population in each generation to transfer the genetic material to successive generations. Elimination–dispersal promotes the low probability of the elimination and dispersal of randomly selected parts of the bacterial population. This fosters diversity in the bacterial population and prevents the global optimal solution from being trapped in a local minimum. E. coli alternates between two modes of movement, called swim and tumble, throughout its entire life. Swimming action allows the bacterium to move in the current direction of increasing nutrient gradient; tumble action allows change in orientation when the nutrient gradient is no longer attractive. The alternating mode of bacterial movement enables a bacterium to locate the position of the optimal nutrient source. After a certain number of complete swims, the bacterial population undergoes reproduction and elimination, according to the fitness criteria. Each bacterium position has an associated cost and represents a possible solution. BFO simulation keeps track of the cost of current and previous positions to estimate the quality of gradient improvement or worsening. In each generation the health of the bacterium factors into its likelihood of being retained for reproduction (making replicas) or elimination. If q i represents the position of the ith bacteria, the successive movement of the bacterium is (6-12) q q f i i i i j k l j k l v j j ( , , ) ( , , ) ( ) ( ), + = + × 1 q q f i i i i j k l j k l v j j ( , , ) ( , , ) ( ) ( ), + = + × 1 f i( j) = random direction of movement after the tumble f i( j) = random direction of movement after the tumble For the given position of the ith bacterium, q i( j,k,l), Ji( j,k,l) represents the fitness of the bacterium at that location. If the fitness of ith bacterium at location q i( j+1,k,l) is better than that at q i( j,k,l), such that Ji( j+1,k,l) is better than Ji( j,k,l), then vi( j+1) = vi( j), and fi( j+1) = fi( j). If the reverse is true, then vi( j+1) takes a different step, in a random direction. Munoz, Lopez, and Caicedo (2007) proposed a BFO algorithm for searching the best actuators in each sample time to obtain a uniform temperature over the temperature grid platform. The idea is to compensate for the cold spots by allocating or deallocating additional resources. Similar techniques can be applied to load balancing in a cluster of compute servers, as in a datacenter. Server load balancing techniques employ bacterial searches to locate the regions of nonuniform thermal behavior (high temperature variance). The fitness of the newly identified location can be evaluated by modeling the thermal variance in the temperature grid resulting from adding or subtracting quantities of unit load. 117 117 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Artificial Immune System The artificial immune system (AIS) is a bioinspired optimization algorithm (Dasgupta 1999) based on the principles of the vertebrate immune system. The algorithm emulates several characteristics of the human immune system: that it is highly distributed, that it is parallel, and that it uses adaptive learning and memory to solve problems related to pattern recognition and classification. The AIS algorithm learns to categorize relevant patterns through a pattern detector that associates previously -seen patterns with existing ones. The algorithm formulates a different response mechanism to deal with the effects of each pattern. The adaptive immune system in the human body uses many agents that perform diverse functions at different locations, primarily employing negative selection and clonal selection mechanisms. Negative selection mechanisms exploit the immune system's ability to detect unknown antigens, while not reacting to self. Clonal selection mechanisms promote the proliferation of cells that possess the ability to recognize an antigen over those that do not. Therefore, self-reacting cells are eliminated, and mature cells are allowed to proliferate. The learning mechanism involves bolstering by the cloning process of those lymphocytes within a given population that contribute to the identification of an antigen. New cells are copies (clones) of their parents, but cloning is subject to a high rate of mutation (somatic hypermutation). This mutation process mimics the mechanism that reallocates the resources needed for recognition of new antigens versus previously identified antigens. The reinforced learning mechanism rebalances the population of diverse lymphocytes to promote optimal detection and mediation of pathogens. The properties of the immune system have the following attributes (Castro, Nunes, and Von Zuben 19 The properties of the immune system have the following attributes (Castro, Nunes, and Von Z The properties of the immune system have the following attributes (Castro, Nunes, a • Exclusivity: The immune system is exclusive to each individual, with its own vulnerabilities and capabilities. • Recognition of foreigners: The toxic elements or molecules that are foreign to the individual’s body are identified, categorized, and labeled for future detection. • Anomaly detection: The immune system learns to classify the unidentified foreign element as a pathogen and attempts a remedial action. • Distributed detection: The cells are distributed throughout the body and are not subject to centralized control. • Imperfect detection (noise tolerance): Pathogens are first classified as unidentified foreign elements, and their absolute recognition is not essential. Artificial Immune System x k m x y k x i ji i j j n i = - æ è çç ö ø ÷÷ =å 1 1 2 , (6-13) x k m x y k x i ji i j j n i = - æ è çç ö ø ÷÷ =å 1 1 2 , (6-13) where n = number of antigens n = number of antigens xi = concentration of antibody i yj = concentration of antigen j mji = affinity function representing the correlation between antibody i and antigen j k1 = rate of antibody production k2 = death rate xi = concentration of antibody i yj = concentration of antigen j yj = concentration of antigen j mji = affinity function representing the correlation between antibody i and antigen j mji = affinity function representing the correlation between antibody i and antigen j k f ib d d i mji = affinity function representing the correlation between antibody i and antigen j k1 = rate of antibody production k2 = death rate k1 = rate of antibody production k2 = death rate Equation 6-13 represents the iterative change in the antibody concentration, contingent on the net outcome of cloning due to antigen recognition and death in the absence of correlation. 4. Mutation: Antigen–antibody interaction, coupled with somatichypermutation, forms the basis of an AIS. Mutation introduces diversity in the population and facilitates effective response to antigens. AIS uses an adaptive population of antibodies to facilitate intelligent behavior by synthesizing diverse subset solutions for a given problem domain. AIS has been applied in areas related to network security and anomaly detection. Artificial Immune System • Reinforcement learning and memory: The immune system continuously learns the structure of the pathogen to formulate an increasingly effective response. Similar to that of the GA, AIS architecture comprises the following four steps (Aickelin, Dasgupt and Gu 2014): Similar to that of the GA, AIS architecture comprises the following four steps (Aickelin, Dasgupt and Gu 2014): 1. Encoding: Encoding is binary, numeric, or nominal representation of antigens or antibodies. An antigen represents the solution to a problem domain that needs to be tested for an intrusion. Antibodies represent previously identified patterns that can be used later. 2. Similarity measure: A similarity measure quantifies the affinity between an antigen and its candidate antibodies. The matching algorithm measures the extent of agreement, disagreement, or correlation between a candidate antibody and its target antigen. Candidates with strong agreement or disagreement may be selected for further processing (cloning or mutation). 118 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence . Selection: The selection process follows an iterative procedure, in which the concentration of antibodies is regulated by cloning or removal at each step, depending on the antibody–antigen affinity measure. Upon adding a new antibody, the iterative process changes the concentration of that antibody, continuing until the AIS achieves stability. AIS iteration can be represented by the following equation (Farmer, Packard, and Perelson 1986): Selection: The selection process follows an iterative procedure, in which the concentration of antibodies is regulated by cloning or removal at each step, depending on the antibody–antigen affinity measure. Upon adding a new antibody, the iterative process changes the concentration of that antibody, continuing until the AIS achieves stability. AIS iteration can be represented by the following equation (Farmer, Packard, and Perelson 1986): 3. Distributed Management in Datacenters Datacenters are complex environments that deal with key challenges related to power delivery, energy consumption, heat management, security, storage performance, service assurance, and dynamic resource allocation. These challenges relate to providing effective coordination to improve the stability and efficiency of datacenters. The fluctuating demands and diverse workload characteristics of a large datacenter make complex the tasks of upholding workload performance, cooling efficiency, and energy targets (discussed in the following sections). In such large clusters of systems, multiple objectives compete to accomplish service-level goals by avoiding actuator overlapping and exhausting a complex combination of constraints, timing granularity, type of approach, and sequence of controls. However, the combinatorial solution space can be extremely large and may not converge to a global optimal in a bounded time. Therefore, a centralized datacenter management system may not scale well in constrained time and hence may not deliver an optimal management solution. 119 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence SI has emerged as a promising field that can be exploited to construct a distributed management methodology leading to scalable solutions without centralized control. The following sections present a control system that identifies suitable targets for workload placement, with these fundamental control elements: • Controlled process: The controlled process implements the feedback control loop, which constrains the temperature and power of compute clusters, such as server racks, for a given policy. An optimal process operates within policy constraints and provisions sufficient energy to operate a workload at highest performance efficiency and lowest cooling. • Fitness function: The fitness function estimates the most favorable placement of the workload, based on the existing knowledge base’s expected demand and availability of resources. • Knowledge base: The knowledge base acts as a finite database made up of survey data conducted by the sensor agents. This knowledge assists in identifying the most probable placement of the workload. As the dynamics of the system changes, newer data replace the old data, according to a custom data retention policy. The knowledge database increases the retention of data likely to boost the fitness of the solution and deprecates the data less likely to improve the existing solution. • Control parameters: Control parameters define the optimal decision boundaries that result in placement of the workload on the selected compute node. • Swarm agents: Swarm agents participate in the system optimization process by executing specific roles in a decentralized and self-organized system. Workload Characterization Because workloads undergo phases of execution, phase boundaries are fundamental attributes for predicting workload behavior for scheduling or migration between clusters of servers. Additionally, phase identification enables reuse of past configurations of recurring phases to improve performance. These configurations enforce a policy for scheduling new workloads, migrating existing workloads, and eliminating thermal load imbalances between compute nodes or clusters of compute nodes. Distributed Management in Datacenters These agents coordinate with each other and with the environment, ultimately leading to the emergence of intelligent global behavior. Thermal Optimization Given the highly dynamic environment in a datacenter, hot spots are created as a result of temporal events (such as increased workload on a set of servers) or spatial events (such as inefficiency of the computer room air-conditioning [CRAC]) units in delivering the requisite cooling to a particular region in the datacenter). Figure 6-2 depicts a thermal snapshot of a datacenter with hot and cold spots. Hot spots may trigger overcooling, degrading the power usage effectiveness (PUE) of the datacenter operations. Traditional cooling control solutions operate using reactive schemes, which depend on the instantaneous temperatures of racks or blades. These schemes have a fundamental disadvantage, inasmuch as the corrective action is completed long after the component’s thermal or performance threshold has been crossed. In a datacenter with a large number of nodes, it is almost impossible to perform optimal workload balance in real time using a reactive approach without causing hysteresis. In the presence of dynamic variations in a cluster of configurable hardware and software, the ability to initiate a timely response to reduce temperature variance (hot spots) between clusters is essential. 120 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Figure 6-2. Thermal snapshot of a datacenter Figure 6-2. Thermal snapshot of a datacenter Load Balancing Load balancing is a method for distributing workload among a cluster of compute nodes in a manner that allows fulfillment of a given policy. Load balancing optimizes resource usage, maximizes throughput, and minimizes response time. Load balancing is realized through active load migration between compute nodes, which also governs the hot-spot mitigation scheme, using workload tradeoffs and power distribution. Hot spots can be attributed to uneven load distributions leading to imbalanced compute utilization. Hot spots result in inefficient cooling and higher datacenter operating costs. In a swarm-based optimization scheme thermal variance can be equated with foraging for a source of nutrients. Regions of high thermal variance act as a source (or target) of load migration, attracting increased surveillance from the swarm agents. r = impact decay coefficient r = impact decay coefficient As described in function 6-14, whenever a compute cluster or node hosts a workload successfully, it improves its impact score by receiving incremental credits. At the same time, the feedback function sheds a percentage of its score at a rate defined by the impact decay coefficient r. The decay coefficient lets the rate of adaptation be adjusted. At any one time, only a finite number of worker agents is allowed to operate. A worker agent transitions to a free agent when its fitness score falls below a certain threshold. Once this occurs, the worker agent can attach itself to a new cluster, based on feedback from scout agents and worker agents. Whereas scout agents identify new and promising regions for exploration, worker agents help in characterizing desirable neighborhoods close to their current operating region. At all times, these agents evaluate the cluster’s fitness, a measure of its ability to host a new workload. This fitness score allows the respective agents to participate in a bidding process to host the workload in the region they represent. The fitness evaluation assesses the following characteristics: Severity of the thermal imbalances in the attached region, as compared • with other regions Availability of the resources needed to execute a workload successfully • Degree of contention with respect to available resources shared among • compute nodes (e.g., shared cache) Figure 6-3 depicts the architectural interfaces of a compute node that facilitate optimal workload distribution. Worker and scout agents gather node-specific performance and environmental data, using instrumentation APIs provided by the server manager. The agents explore the viability of using the node to host a workload by measuring the node’s impact score (see Equation 6-14), evaluating its resource requirements, forecasting shared resource contention, and predicting the temperature behavior that may lead to thermal imbalances. Once the node is ascertained to be a potential host, its impact score is updated for future analysis. Cold regions with sufficient availability of resources identify themselves as the preferred localities for exploration. Worker agents analyze the compatibility of each region with the workload; incompatibilities may arise, owing to lack of exclusive resources or historical evidence of noisy behavior, with respect to the sharing of resources with other workloads. Algorithm Model The algorithm model consists of a server manager, a scout agent, worker agents, free agents, and a load controller. The server manager administers each server node and presents programming interfaces for interpreting the sensor data and synthesizing the useful metrics. The server manager exerts control at multiple levels of timing granularity, which can eventually result in heterogeneous sampling requirements specific to each one of those elements. For instance, the server manager records the performance data and processes them to synthesize the workload phase distribution by exercising built-in sensors. In a hierarchical scheme the server manager manages a cluster of compute resources and identifies the compute resource capable of hosting a candidate workload. Externally, each cluster represents a set of compute units that is managed locally, without exposing its local hierarchy. Scout agents are randomly generated proxy instruments that evaluate their surroundings and peer clusters to identify possible sources of hot and cold spots. Owing to the dynamic nature of the systemutilization, newer sources are identified, and past sources are slowly forgotten. Scout agents employ fitness criteria to determine the suitability of the region to host the work assignment. 121 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Worker agents are floating entities that use a feedback function to quantify the significance of the compute region and that attach themselves to a node that they select for foraging. At each scheduling instant a feedback function measures the historical impact by either boosting or shedding the node’s credibility, based on the most recent scheduling decisions and preceding outcomes. If the compute region continues to host workloads successfully, it boosts its credibility; if, however, the compute region loses its bid to host or hosts infrequently, then the credibility declines. Worker agents are finite in number and can only be reused if one is released, owing to either its low impact score or its migration to newer regions. The feedback function is (6-14) b r b t n k n k n k + = - + 1 1( ) , where bn k = impact score of cluster (or node) k at instance n bn k = impact score of cluster (or node) k at instance n t n k = incremental credit boost of cluster (or node) k at instance n t n k = incremental credit boost of cluster (or node) k at instance n r = impact decay coefficient The worker agent ranks the host it is attached to and makes a decision as to whether to participate in the bidding process to host the workload on that node. If it participates and wins the bid, the agent updates the feedback function; if it does not win the bid, the agent sheds a percentage of its impact score b. Once the impact score drops below a certain threshold, the worker agent transitions to a free agent. A free agent transitions its role back to worker agent by attaching itself to a new cluster (or node), based on an evaluation score received from the scout agents and worker agents. 122 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Figure 6-3. Compute node: architectural interfaces for interpreting sensor data for evaluating feedback function and fitness function Figure 6-3. Compute node: architectural interfaces for interpreting sensor data for evaluating feedback function and fitness function de Castro, Leandro Nunes, and Fernando José Von Zuben. “Artificial Immune Systems: Part I–Basic Theory and Applications.” Technical report, Universidade Estadual de Campinas, 1999. References Aickelin, Uwe, Dipankar Dasgupta, and Feng Gu. “Artificial Immune Systems.” In Search Methodologies, 187–211. New York: Springer, 2014. Ashby, W. Ross. “Design for a Brain.” New York: Wiley, 1952. https://archive.org/details/ designforbrainor00ashb. Barbagallo, Donato, Elisabetta Di Nitto, Daniel J. Dubois, and Raffaela Mirandola. “A Bio-Inspired Algorithm for Energy Optimization in a Self-Organizing Data Center.” In Self-Organizing Architectures: First International Workshop, SOAR 2009, Cambridge, UK, September 14, 2009, edited by Danny Weyns, Sam Malek, Rogério de Lemos, and Jesper Andersson, 127–151. Berlin: Springer, 2010. Beni, Gerardo, and Jing Wang. “Swarm Intelligence in Cellular Robotic Systems.” In Robots and Biological Systems: Towards a New Bionics?, edited by Paolo Dario, Giulio Sandini, and Patrick Aebischer, 703–712. Berlin: Springer , 1993. Carreras, I., D. Miorandi, G. S. Canright, and K. Engo-Monsen. “Understanding the Spread of Epidemics in Highly Partitioned Mobile Networks.” In Proceedings of the 1st IEEE Conference on Bio-Inspired Models of Network, Information and Computing Systems, 1–8. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2006. Dasgupta, Dipankar. Artificial Immune Systems and Their Applications. Berlin: Springer, 1999. de Castro, Leandro Nunes, and Fernando José Von Zuben. “Artificial Immune Systems: Part I–Basic Theory and Applications.” Technical report, Universidade Estadual de Campinas, 1999. 123 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Devescovi, Davide, Elisabetta Di Nitto, Daniel Dubois, and Raffaela Mirandola. “Self-Organization Algorithms for Autonomic Systems in the SelfLet Approach.” In Proceedings of the 1st International Conference on Autonomic Computing and Communication Systems. Brussels: Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, 2007. Di Caro, Gianni, and Marco Dorigo. “AntNet: Distributed Stigmergetic Control for Communications Networks.” Journal of Artificial Intelligence Research 9 (1998): 317–365. www.cs.cmu.edu/afs/cs/project/ jair/pub/volume9/dicaro98a.pdf. Di Caro, Gianni, Frederick Ducatelle, and Luca Maria Gambardella. “AntHocNet: An Adaptive Nature-Inspired Algorithm for Routing in Mobile Ad hoc Networks.” European Transactions on Telecommunications 16, no. 5 (2005): 443–455. Dorigo, Marco, Gianni Di Caro, and Luca Gambardella. “Ant Algorithms for Discrete Optimization.” Artificial Life 5, no. 2 (1999): 137–172. ngelbrecht, Andries P. Fundamentals of Computational Swarm Intelligence. Chichester, UK: Wil Farmer, J. Doyne, Norman H. Packard, and Alan S. Perelson. “The Immune System, Adaptation, and Machine Learning.” Physica D: Nonlinear Phenomena 22, no. 1 (1986): 187–204. Harvey, Inman, Ezequiel Di Paolo, Rachel Wood, Matt Quinn, Elio Tuci, and Elio Tuci. “Evolutionary Robotics: A New Scientific Tool for Studying Cognition.” Artificial Life 11, no. 1–2 (2005): 79-98. Iyer, Ravi. Papadopouli, Maria, and Henning Schulzrinne. “Seven Degrees of Separation in Mobile Ad Hoc Networks.” In Proceedings of the 2000 IEEE Global Telecommunications Conference, 1707–1711. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2000. Munoz, Mario A., Jesus A. Lopez, and Eduardo Caicedo. “Bacteria Swarm Foraging Optimization for Dynamical Resource Allocation in a Multizone Temperature Experimentation Platform.” In Analysis and Design of Intelligent Systems Using Soft Computing Techniques, 427–435. Berlin: Springer, 2007. References “CQoS: A Framework for Enabling QoS in Shared Caches of CMP Platforms.” In Proceedings of the 18th Annual International Conference on Supercomputing, 257–266. New York: ACM, 2004. Karaboga, Dervis, and Bahriye Basturk. “Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems.” In Proceedings of the 12th international Fuzzy Systems Association World Congress on Foundations of Fuzzy Logic and Soft Computing, IFSA 2007, Cancun, Mexico, June 18–21, 2007, edited by Patricia Melin, Oscar Castillo, Luis T. Aguilar, Janusz, Kacprzyk, and Witold Pedrycz, 789–798. Berlin: Springer, 2007. Kennedy, J., and R. Eberhart. “Particle Swarm Optimization.” In Proceedings of the 1995 IEEE International Conference on Neural Networks, 1942–1948. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 1995. Khanna, Rahul, Huaping Liu, and Hsiao-Hwa Chen. “Reduced Complexity Intrusion Detection in Sensor Networks Using Genetic Algorithm.” In Proceedings of the 2009 IEEE International Conference on Communications, 1–5. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2009. Jacob, Bart, Richard Lanyon-Hogg, Devaprasad K. Nadgir, and Amr F. Yassin. “A Practical Guide to the IBM Autonomic Computing Toolkit.” Armonk, NY: IBM, 2004. www.redbooks.ibm.com/redbooks/pdfs/ sg246635.pdf. Li, Zhen, and Manish Parashar. “Enabling Autonomic Grid Applications: Dynamic Composition, Coordination and Interaction.” In Unconventional Programming Paradigms: Proceedings of the International Workshop UPP 2004, Le Mont Saint Michel, France, September 2004; Revised and Selected Papers, edited by Jean-Pierre Banâtre, Pascal Fradet, Jean-Louis Giavitto, and Olivier Michel, 270–285. Berlin: Springer, 2005. Munoz, Mario A., Jesus A. Lopez, and Eduardo Caicedo. “Bacteria Swarm Foraging Optimization for Dynamical Resource Allocation in a Multizone Temperature Experimentation Platform.” In Analysis and Design of Intelligent Systems Using Soft Computing Techniques, 427–435. Berlin: Springer, 2007. Papadopouli, Maria, and Henning Schulzrinne. “Seven Degrees of Separation in Mobile Ad Hoc Networks.” In Proceedings of the 2000 IEEE Global Telecommunications Conference, 1707–1711. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2000. 124 Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Passino, Kevin M. “Biomimicry of Bacterial Foraging for Distributed Optimization and Control.” IEEE Control Systems 22, no. 3 (2002): 52–67. Schoonderwoerd, Ruud, Owen E. Holland, Janet L. Bruten, and Leon JM Rothkrantz. “Ant-Based Load Balancing in Telecommunications Networks.”Adaptive Behavior 5, no. 2 (1997): 169–207. Wang, Xiaolei, Xiao Zhi Gao, and Seppo J. Ovaska. “A Hybrid Optimization Algorithm Based on Ant Colony and Immune Principles.” International Journal of Computer Science and Applications 4, no. 3 (2007): 30–44. Yassa, Sonia, Rachid Chelouah, Hubert Kadima, and Bertrand Granado. Deep Neural Networks I think the brain is essentially a computer and consciousness is like a computer program. It will cease to run when the computer is turned off. Theoretically, it could be re-created on a neural network, but that would be very difficult, as it would require all one’s memories. —Stephen Hawking, Time magazine Proposed in the 1940s as a simplified model of the elementary computing unit in the human cortex, artificial neural networks (ANNs) have since been an active research area. Among the many evolutions of ANN, deep neural networks (DNNs) (Hinton, Osindero, and Teh 2006) stand out as a promising extension of the shallow ANN structure. The best demonstration thus far of hierarchical learning based on DNN, along with other Bayesian inference and deduction reasoning techniques, has been the performance of the IBM supercomputer Watson in the legendary tournament on the game show Jeopardy!, in 2011. This chapter starts with some basic introductory information about ANN then outlines the DNN structure and learning scheme. References “Multi-Objective Approach for Energy-Aware Workflow Scheduling in Cloud Computing Environments.” Scientific World Journal 2013 (2013): 350934. www.hindawi.com/journals/tswj/2013/350934/. Chapter 6 ■ Bioinspired Computing: Swarm Intelligence Passino, Kevin M. “Biomimicry of Bacterial Foraging for Distributed Optimization and Control.” IEEE Control Systems 22, no. 3 (2002): 52–67. Schoonderwoerd, Ruud, Owen E. Holland, Janet L. Bruten, and Leon JM Rothkrantz. “Ant-Based Load Balancing in Telecommunications Networks.”Adaptive Behavior 5, no. 2 (1997): 169–207. Wang, Xiaolei, Xiao Zhi Gao, and Seppo J. Ovaska. “A Hybrid Optimization Algorithm Based on Ant Colony and Immune Principles.” International Journal of Computer Science and Applications 4, no. 3 (2007): 30–44. Yassa, Sonia, Rachid Chelouah, Hubert Kadima, and Bertrand Granado. “Multi-Objective Approach for Energy-Aware Workflow Scheduling in Cloud Computing Environments.” Scientific World Journal 2013 (2013): 350934. www.hindawi.com/journals/tswj/2013/350934/. 125 Early ANN Structures One of the first ANN attempts dates back to the late 1940s, when the psychologist Donald Hebb (Hebb 1949) introduced what is known today as Hebbian learning, based on the plasticity feature of neurons: when neurons situated on either side of a synapse are stimulated synchronously and recurrently, the synapse’s strength is increased in a manner proportional to the respective outputs of the firing neurons (Brown et al. 1990), such that w t w t x t x t ij ij ij i j + ( ) = ( )+ ( ) ( ) 1 h , where t represents the training epoch, wij is the weight of the connection between the ith and the jth neurons, xi is the output of the ith neuron, and hij is a learning rate specific to the synapse concerned. j The Hebbian rule is an unsupervised-learning scheme that updates the weights of a network locally; that is, the training of each synapse depends on the weights of the neurons connected to it only. With its simple implementation the Hebbian rule is considered the first ANN learning rule, from which multiple variants have stemmed. The first implementations of this algorithm were in 1954, at the Massachusetts Institute of Technology, using computational machines (Farley and Clark, 1954). gy g y The 1950s also saw the introduction of the perceptron, a two-layer neural network model for pattern recognition, using addition and subtraction operations (Rosenblatt 1958). The model consists of four components, as depicted in Figure 7-1. The retina, or input region, receives stimulus through sensory units. The connections are called localized because their origin points tend to cluster around a certain point or in a certain area. Although units in the projection area are identical to those in the association area, the projection area receives input through localized connections, whereas input to the association area emerges from the projection area through random connections; as if the input is generated from scattered areas. The A-units receive a set of transmitted impulses that may be excitatory or inhibitory. If the stimulus exceeds a certain threshold, the units respond by firing. The random connections between the association area and the response units are bidirectional. The feedforward connections transmit synapses from the association area to the responses, whereas the feedback connections transmit excitatory synapses to the source points in the association area from which the connection is generated. Introducting ANNs ANNs have been successfully used in many real-life applications, especially in supervised-learning modes. However, ANNs have been plagued by a number of notable challenges and shortcomings. Among the many challenges in supervised learning is the curse of dimensionality (Arnold et al. 2011), which occurs when the number of features and training points becomes significantly large. Big data thus makes ANN learning more difficult, owing to the overwhelming amount of data to process and the consequent memory and computational requirements. Another challenge in classification is the data nonlinearity that characterizes the feature overlap of different classes, making the task of separating the classes more difficult. Primarily for these reasons and the heuristic approach to select the appropriate network architecture, ANNs lagged through the 1990s and 2000s behind the widely adopted support vector machines (SVMs), which proved to be, in many respects, superior to ANNs. Note ■ ■ SVM offers a principled approach to machine learning problems because of its mathematical foundations in statistical learning theory. SVM constructs solutions as a weighted sum of support vectors, which are only a subset of the training input. Like ANN, SVM minimizes a particular error cost function, based on the training data set, and relies on an empirical risk model. Additionally, SVM uses structural risk minimization and imposes an additional constraint on the optimization problem, forcing the optimization step to find a model that will eventually generalize better as it is situated at an equal and maximum distance between the classes. 127 Chapter 7 ■ Deep Neural Networks With advancements in hardware and computational power, DNNs have been proposed as an extension of ANN shallow architectures. Some critics consider deep learning just another “buzzword for neural nets” (Collobert 2011). Although they borrow the concept of neurons from the biological brain, DNNs do not attempt to model it as cortical algorithms (CAs) or other biologically inspired machine learning approaches do. DNN concepts stem from the neocognitron model proposed by Fukushima (1980). Broadly defined as a consortium of machine learning algorithms that aims to learn in a hierarchical manner and that involves multiple levels of abstraction for knowledge representation, DNN architectures are intended to realize strong artificial intelligence (AI) models. These architectures accumulate knowledge as information propagates through higher levels in a manner such that the learning at the higher level is defined by and built on the statistical learning that happens at the lower-level layers. Introducting ANNs With such a broad definition of deep learning in mind, we can construe the combinations of the backpropagation algorithm (available since 1974) with recurrent neural networks and convolution neural networks (introduced in the 1980s) as being the predecessors of deep architectures. However, it is only with the advent of Hinton, Osindero, and Teh’s (2006) contribution to deep learning training that research on deep architectures has picked up momentum. The following sections give a brief overview of ANN, along with introducing in more detail deep belief networks (DBNs) and restricted Boltzmann machines (RBMs). Early ANN Structures Inhibitory synapses complement the source points in the association areas that do not transmit to the response concerned. 128 Chapter 7 ■ Deep Neural Networks Fi 7 1 A R bl tt t t t Figure 7-1. A Rosenblatt perceptron structure Figure 7-1. A Rosenblatt perceptron structure Classical ANN The basic structure of an ANN is the artificial neuron shown in Figure 7-2, which resembles the biological neuron in its shape and function (Haykin 1994). Figure 7-2. An artificial neuron Figure 7-2. An artificial neuron Note ■ ■ In the human body’s nervous system, neurons generate, transmit, and receive electrical signals called action potential. A typical biological neuron has the following three basic components: Cell body • : Can have a variety of sizes and shapes • Dendrites: Numerous, treelike structures that extend from the cell body and that constitute the receptive portion of the neuron (i.e., the input site) • Axon: A long, slender structure, with relatively few branches, that transmits electrical signals to connected areas The inputs (X) are connected to the neuron through weighted connections emulating the dendrite’s structure, whereas the summation, the bias (b), and the activation function (q) play the role of the cell body, and the propagation of the output is analogous to the axon in a biological neuron. 129 Chapter 7 ■ Deep Neural Networks Chapter 7 ■ Deep Neural Networks Mathematically, a neuron is equivalent to the function: Mathematically, a neuron is equivalent to the function: Mathematically, a neuron is equivalent to the function: Y W X b i n i i = + æ èç ö ø÷ =å q 1 , which can be conveniently modeled, using a matrix form, which can be conveniently modeled, using a matrix form, Y W X b = + ( ) q . , where W W W Wn =[ ] 1 2  , and X X X Xn = é ë ê ê ê ê ù û ú ú ú ú 1 2  . Y W X b = + ( ) q . , where W W W Wn =[ ] 1 2  , and X X X Xn = é ë ê ê ê ê ù û ú ú ú ú 1 2  . Y W X b = + ( ) q . , The activation function shapes the output or state of the neuron. Classical ANN Multiple activation functions can be used, the most common of which are as follows: • Hard limiter: q a if a if a ( ) = < > ì í î 0 0 1 0 • Hard limiter: q a if a if a ( ) = < > ì í î 0 0 1 0 • Saturating linear function: q a if a a if a if a ( ) = < £ £ > ì íï îï 0 0 0 1 1 1 • Log-sigmoid function: q a e a ( ) = + - 1 1 • Hyperbolic tangent sigmoid function: q a e e e e a a a a ( ) = - + - - The bias shifts the activation function to the right or the left, as necessary for learning, and can in some cases be omitted. A neural network is simply an association of cascaded layers of neurons, each with its own weight matrix, bias vector, and output vector. A layer of neurons is a “column” of neurons that operate in parallel, as shown in Figure 7-3. Each element of this column is a single neuron, with the output of the layer being the vector output, which is formed by the individual outputs of neurons. If an input vector is constituted of N inputs and a layer of M neurons, Wij represents the weight of the connection of the jth input to the ith neuron of the layer; Yi and bi are, respectively, the output of and the bias associated with the jth neuron. 130 Chapter 7 ■ Deep Neural Networks Figure 7 3 A layer of neurons Figure 7-3. A layer of neurons Figure 7-3. A layer of neurons Figure 7-3. A layer of neurons A layer of neurons can be conveniently represented, using matrix notation, as follows: A layer of neurons can be conveniently represented, using matrix notation, as follows: A layer of neurons can be conveniently represented, using matrix notation, as follows: W W W W W M N NM = ¼ ¼ é ë ê ê ê ù û ú ú ú 11 1 1    . W W W W W M N NM = ¼ ¼ é ë ê ê ê ù û ú ú ú 11 1 1    . Classical ANN The row index in each element of this matrix represents the destination neuron of the corresponding connection, whereas the column index refers to the input source of the connection. p Designating by Y the output of the layer, you can write Y Y Y Y W X b W i N j M j j j M i = é ë ê ê ê ê ê ê ù û ú ú ú ú ú ú = + æ è çç ö ø ÷÷ = = å å 1 1 1 1 1    q q j j i j M Nj j N X b W X b + æ è çç ö ø ÷÷ + æ è çç ö ø ÷÷ é ë ê ê ê ê ê ê ê ê ê ê ê ê ù û ú ú ú ú =å  q 1 ú ú ú ú ú ú ú ú = + ( ) q W X b . , Y Y Y Y W X b W i N j M j j j M i = é ë ê ê ê ê ê ê ù û ú ú ú ú ú ú = + æ è çç ö ø ÷÷ = = å å 1 1 1 1 1    q q j j i j M Nj j N X b W X b + æ è çç ö ø ÷÷ + æ è çç ö ø ÷÷ é ë ê ê ê ê ê ê ê ê ê ê ê ê ù û ú ú ú ú =å  q 1 ú ú ú ú ú ú ú ú = + ( ) q W X b . , 131 Chapter 7 ■ Deep Neural Networks where = é ë ê ê ê ù û ú ú ú b bN 1  . where = é ë ê ê ê ù û ú ú ú b bN 1  . To aid in identifying the layer corresponding to a particular matrix, superscript indexes are used. Thus, Wij k represents the weight of the connection between the jth neuron in layer k–1and the ith neuron in layer k, and k Yi k is the output of the ith neuron of the kth layer. Classical ANN The network output is the output of the last layer (also called the output layer), and the other layers are called hidden layers. A network with two hidden layers is illustrated in Figure 7-4. For generalization purposes, you designate by Nk the number of hidden neurons in the kth layer. Figure 7-4. A three-layer ANN Figure 7-4. A three-layer ANN The function achieved by this network is Y Y Y Y W Y b W W Y b i N 3 1 3 3 3 3 3 2 3 3 2 1 2 = é ë ê ê ê ê ê ê ù û ú ú ú ú ú ú = + ( ) = + ( )+   q q q b W W W X b b b 3 3 2 1 1 2 3 ( )= + ( ) ( )+ ( )+ ( ). q q q Y Y Y Y W Y b W W Y b i N 3 1 3 3 3 3 3 2 3 3 2 1 2 = é ë ê ê ê ê ê ê ù û ú ú ú ú ú ú = + ( ) = + ( )+   q q q b W W W X b b b 3 3 2 1 1 2 3 ( )= + ( ) ( )+ ( )+ ( ). q q q Y Y Y Y W Y b W W Y b i N 3 1 3 3 3 3 3 2 3 3 2 1 2 = é ë ê ê ê ê ê ê ù û ú ú ú ú ú ú = + ( ) = + ( )+   q q q b W W W X b b b 3 3 2 1 1 2 3 ( )= + ( ) ( )+ ( )+ ( ). q q q 132 Chapter 7 ■ Deep Neural Networks Note ■ ■ For the sake of simplicity, the same activation function q has been adopted in all layers. However, multiple activation functions can be used in different layers in a network. Also, the number of neurons per layer may not be constant throughout the network. The optimal number of layers and neurons for best performance is a question yet to be answered decisively, because this number is application dependent. A layer of hidden neurons divides the input space into regions whose boundaries are defined by the hyperplanes associated with each neuron. The smaller the number of hidden neurons, the fewer the subregions created and the more the network tends to cluster points and map them to the same output. The output of each neuron is a non linear transformation of a hyperplane. The function achieved by this network is In the case of classification, this separating curve formed by weighted inputs coming from the previous layer contributes, with other neurons in the same layer, in defining the final classification boundary. With a large number of neurons, the risk of overfitting increases, and the generalized performance decreases, because of overtraining. The network must be trained with enough data points to ensure that the partitions obtained at each hidden layer correctly separate the data. ANN Training and the Backpropagation Algorithm To enable an ANN to recognize patterns belonging to different classes, training on an existing dataset seeks to obtain iteratively the set of weights and biases that achieves the highest performance of the network (Jain, Mao, and Mohiuddin 1996). In a network with M inputs, N output neurons, and L hidden layers, and given a set of labeled data—that is, a set of P pairs (X, T), where X is an M-dimensional vector, and T is an N-dimensional vector—the learning problem is reduced to finding the optimal weights, such that a cost function is optimized. The output of the network should match the target Ti and minimize the mean squared error, E Y T i P i i = - =å 1 2 1 2 , where Yi is the output obtained by propagating input Xi through the network. where Yi is the output obtained by propagating input Xi through the network. where Yi is the output obtained by propagating input Xi through the network. l f l f h d h ANNs can also use entropy as a cost function. Training requires at least a few epochs to update weights according to a weight update rule. It is to be noted that the backpropagation algorithm is widely adopted. It consists of the following steps: 1. Initialization: This step initializes the weights of the network in a random, weak manner; that is, it assigns random values close to 0 to the connections’ weights. 2. Feedforward: The input Xi is fed into the network and propagated to the output layer. The resultant error is computed. 3. Feedback: The weights and biases are updated with: W t W t E W ij k ij k ij k + ( ) = ( )- ¶ ¶ 1 a b t b t E b i k i k i k + ( ) = ( )- ¶ ¶ 1 a , where a is a positive, tunable learning rate. The choice of a affects whether the backpropagation algorithm converges and how fast it converges. A large learning rate may cause the algorithm to oscillate, whereas a small learning rate may lead to a very slow convergence. where a is a positive, tunable learning rate. The choice of a affects whether the backpropagation algorithm converges and how fast it converges. ANN Training and the Backpropagation Algorithm The weights and biases are updated according to the following gradient descent: W t W t Y ij k ij k i k j k + ( ) = ( )- 1 ad -1 b t b t i k i k i k + ( ) = ( )- 1 ad . W t W t Y ij k ij k i k j k + ( ) = ( )- 1 ad -1 b t b t i k i k i k + ( ) = ( )- 1 ad . The network error is eventually reduced via this gradient-descent approach. For instance, considering a one-dimensional training point that belongs to class 1 (+1) and that is wrongly classified as class 2 (–1), the hyperplane should be moved away from class 1. Because, the hyperplane will be shifted to the left (decrease in Wij k) if di k j k Y - > 1 0, and it will be shifted to the right (increase in Wij k) if di k j k Y - < 1 0. ANN Training and the Backpropagation Algorithm A large learning rate may cause the algorithm to oscillate, whereas a small learning rate may lead to a very slow convergence. 133 Chapter 7 ■ Deep Neural Networks Because the update of the weights necessitates computing the gradient of the error (the cost Because the update of the weights necessitates computing the gradient of the error (the cost function), it is essential for it to be differentiable. Failure to satisfy this condition prevents from using the backpropagation algorithm. g g The computation of the gradient in the backpropagation algorithm can be simplified, using the chain rule, which calls for the following steps: 1. For each output unit i N = ¼ 1 2 , , , (in output layer L of Figure 7-4), the backpropagated error is computed, using . , di L i L i i L d Y t dt T Y t = ( ) ( ) - ( ) ( ) where, Ti is the desired output; and, for the sigmoidal function, where, Ti is the desired output; and, for the sigmoidal function, d Y t dt Y t Y t i L i L i L , ( ) ( ) = ( ) - ( ) ( ) 1 resulting in the following expression: resulting in the following expression: . di L i L i L i i L Y t Y t T Y t = ( ) - ( ) ( ) - ( ) ( ) 1 2. For each hidden unit h Nk =1 2 , ,..., (in a hidden layer k with Nk hidden units), and moving from layer L–1, backward to the first layer, the backpropagated error can be computed as shown: 2. For each hidden unit h Nk =1 2 , ,..., (in a hidden layer k with Nk hidden units), and moving from layer L–1, backward to the first layer, the backpropagated error can be computed as shown: d d h k h k k k q N qh k q k Y t Y t W k = ( ) - ( ) ( ) = + å 1 1 1 +1 . 3. The weights and biases are updated according to the following gradient descent: 3. DBN Overview DBNs, a deep architecture widely seen in the literature since the introduction of a fast, greedy training algorithm (Hinton, Osindero, and Teh 2006), are a network of stochastic neurons grouped in layers, with no intralayer neuron connections. The first two layers of the network contain neurons with undirected connections, which form an associative memory, analogous to biological neurons, whereas the remaining hidden layers form a directed acyclic graph, as displayed in Figure 7-5. 134 Chapter 7 ■ Deep Neural Networks Figure 7-5. DBN architecture Although a DBN can be viewed as an ANN with more hidden layers, training a DBN, using backpropagation, does not produce a good machine learning model, because the explaining-away phenomenon makes inference more difficult in deep models. When training a network, the simplifying assumption that layers are independent. Explaining away (also called Berkson’s paradox or selection bias), makes this assumption invalid; the hidden nodes become anticorrelated. For example, if an output node can be activated by two equally rare and independent events with an even smaller chance of occurring simultaneously (because the probability of two independent events’ occurring simultaneously is the product of both probabilities), then the occurrence of one event negates (“explains away”) the occurrence of the other, such that a negative correlation is obtained between the two events. As a result of the difficulty of training deep architectures, DBNs lost popularity until Hinton and Salakhutdinov (2006) proposed a greedy training algorithm to train them efficiently. This algorithm broke down DBNs into sequentially stacked RBMs, which is a two-layer network constrained to contain only interlayer neuron connections, that is, connections between neurons that do not belong to the same layer. As shown in Figure 7-6 connections between neurons in layer 1 are not allowed and the same goes Figure 7-5. DBN architecture Figure 7-5. DBN architecture Although a DBN can be viewed as an ANN with more hidden layers, training a DBN, using backpropagation, does not produce a good machine learning model, because the explaining-away phenomenon makes inference more difficult in deep models. When training a network, the simplifying assumption that layers are independent. Explaining away (also called Berkson’s paradox or selection bias), makes this assumption invalid; the hidden nodes become anticorrelated. DBN Overview For example, if an output node can be activated by two equally rare and independent events with an even smaller chance of occurring simultaneously (because the probability of two independent events’ occurring simultaneously is the product of both probabilities), then the occurrence of one event negates (“explains away”) the occurrence of the other, such that a negative correlation is obtained between the two events. As a result of the difficulty of training deep architectures, DBNs lost popularity until Hinton and Salakhutdinov (2006) proposed a greedy training algorithm to train them efficiently. This algorithm broke down DBNs into sequentially stacked RBMs, which is a two-layer network constrained to contain only interlayer neuron connections, that is, connections between neurons that do not belong to the same layer. As shown in Figure 7-6, connections between neurons in layer 1 are not allowed, and the same goes for layer 2; connections have to link a neuron from layer 1 to a neuron in layer 2 only. In a DBN the first two layers are allowed to have bidirectional connections, whereas the remaining layers have just directed connections. Therefore, interest in deep architectures was renewed, as training them became feasible and fast, involving training RBM units independently before adjusting the weights, using an up–down algorithm to avoid underfitting (Hinton, Osindero, and Teh 2006). 135 Chapter 7 ■ Deep Neural Networks Following is list of the DBN nomenclature adopted here: Figure 7-6. Weight labeling Figure 7-6. Weight labeling Following is list of the DBN nomenclature adopted here: Figure 7-6. Weight labeling Figure 7-6. Weight labeling Figure 7-6. Weight labeling Following is list of the DBN nomenclature adopted here: Following is list of the DBN nomenclature adopted here: DNN Nomenclature Wi j r , : Weight of the edge connecting neuron i in layer r to neuron j in layer; r is suppressed when there are only two layers in the network Wi r: Weight vector of all connections leaving neuron i in layer r Wr : Weight vector connecting layer r to layer r +1 m: Learning rate k: Number of Gibbs sampling steps performed in contrastive divergence n: Total number of hidden layer neurons m: Total number of input layer neurons Q(.\|.): Conditional probability distribution hr: Binary configuration of layer r p(hr): Prior probability of hr under the current weight values v0: Input layer datapointv j t( ) : binary configuration of neuron j in the input layer at sampling step t Hi: Binary configuration variable of neuron i in the hidden layer at sampling step t hi t( ) : Binary configuration value of neuron i in the hidden layer at sampling step t bj: Bias term for neuron j in the input layer ci: Bias term for neuron i in the hidden layer Wi j r , : Weight of the edge connecting neuron i in layer r to neuron j in layer; r is suppressed when there are only two layers in the network 136 Chapter 7 ■ Deep Neural Networks Chapter 7 ■ Deep Neural Networks Restricted Boltzmann Machines Boltzmann machines (BMs) are two-layer neural network architectures composed of neurons connected in an interlayer and intralayer fashion. Restricted Boltzmann machines (RBMs), first introduced under the name Harmonium, by Smolensky (1986), are constrained to form a bipartite graph. A bipartite graph is a two-layer graph, in which the nodes of the two layers form two disjoint sets of neurons This is achieved by restricting intralayer connections, such that connections between nodes in the same layer are not permitted. This restriction is what distinguishes BMs from RBMs and makes RBMs simpler to train. An RBM with undirected connections between neurons of the different layers forms an autoassociative memory, analogous to neurons in the human brain. Autoassociative memory is characterized by feedback connections that allow the exchange of information between neurons in both directions (Hawkins 2007). Boltzmann machines (BMs) are two-layer neural network architectures composed of neurons connected in an interlayer and intralayer fashion. Restricted Boltzmann machines (RBMs), first introduced under the name Harmonium, by Smolensky (1986), are constrained to form a bipartite graph. A bipartite graph is a two-layer graph, in which the nodes of the two layers form two disjoint sets of neurons This is achieved by restricting intralayer connections, such that connections between nodes in the same layer are not permitted. This restriction is what distinguishes BMs from RBMs and makes RBMs simpler to train. An RBM with undirected connections between neurons of the different layers forms an autoassociative memory, analogous to neurons in the human brain. Autoassociative memory is characterized by feedback connections that allow the exchange of information between neurons in both directions (Hawkins 2007). RBMs can be trained in a supervised and unsupervised fashion. The weight vector is updated, using Hinton’s contrastive divergence (CD) algorithm (Hinton 2002). CD is an algorithm that approximates the log-likelihood gradient and that requires fewer sampling steps than the Markov chain Monte Carlo (MCMC) algorithm (Hinton 2002). CD performs k steps of Gibbs sampling and gradient descent to find the weight vector that maximizes the objective function (Hinton 2010), which is the product of probabilities. As k increases, the performance of the learned model improves, however at the cost of a longer training time. A typical value for this parameter is k = 1 (Hinton 2010). The workflow of the training algorithm is shown in Table 7-1. RBMs can be trained in a supervised and unsupervised fashion. Restricted Boltzmann Machines The weight vector is updated, using Hinton’s contrastive divergence (CD) algorithm (Hinton 2002). CD is an algorithm that approximates the log-likelihood gradient and that requires fewer sampling steps than the Markov chain Monte Carlo (MCMC) algorithm (Hinton 2002). CD performs k steps of Gibbs sampling and gradient descent to find the weight vector that maximizes the objective function (Hinton 2010), which is the product of probabilities. As k increases, the performance of the learned model improves, however at the cost of a longer training time. A typical value for this parameter is k = 1 (Hinton 2010). The workflow of the training algorithm is shown in Table 7-1. Table 7-1. RBM Training Algorithm Workflow, Using CD (Fischer and Igel, 2012) 1. Initialize the weights to 0. 2. For each sample from the training batch: a. Apply the sample to the network input. b. For 0 to k-1 sampling steps, i. for each hidden layer neuron from 1 to n, sample h p h i t i t ( ) ( ) ( ) ~ \|v ; ii. for each input layer neuron from 1 to m, sample v p v j t j t ( ) ( ) ~ . ( ) \|h c. For each input and hidden layer neuron, compute i. D = D + = ( ) - = ( ) ( ) ( ) w w p H v v p H v v ij ij i j i k j k 1 1 0 0 \| \| ( ) ( ) ii. D = D + - b b v v j j j j k ( ) ( ) 0 iii. D = D + = ( )- = ( ) ( ) c c p H v p H v i i i i k 1 1 0 \| ( \| ) 1. Initialize the weights to 0. 2. For each sample from the training batch: a. Apply the sample to the network input. b. For 0 to k-1 sampling steps, i. for each hidden layer neuron from 1 to n, sample h p h i t i t ( ) ( ) ( ) ~ \|v ; ii. for each input layer neuron from 1 to m, sample v p v j t j t ( ) ( ) ~ . ( ) \|h c. DNN Training Algorithms Backpropagation is one of the most popular algorithms used to train ANNs (Werbos 1974). Equation 7-3 displays a simple formulation of the weight update rule, used in backpropagation: Backpropagation is one of the most popular algorithms used to train ANNs (Werbos 1974). Equation 7-3 displays a simple formulation of the weight update rule, used in backpropagation: w w w 1 1 1 r r r J new old ( ) = ( )- ¶ ¶ m (7-3) (7-3) (7-3) However, as the depth of the network increases, backpropagation’s performance degradation increases as well, making it unsuitable for training general deep architectures. This is due to the vanishing gradient problem (Horchreiter 1991; Horchreiter et al. 2001; Hinton 2007; Bengio 2009), a training issue in which the error propagated back in the network shrinks as it moves from layer to layer, becoming negligible in deep architectures and making it almost impossible for the weights in the early layers to be updated. Therefore, it would be too slow to train and obtain meaningful results from a DNN. Because of backpropagation’s shortcomings, many attempts were made to develop a fast training algorithm for deep networks. Schmidhuber’s algorithm (Schmidhuber 1992) trained a multilevel hierarchy of recurrent neural networks by using unsupervised pretraining on each layer and then fine-tuning the resulting weights via backpropagation. Interest in DNNs was renewed in 2006, when Hinton and Salakhutdinov (2006) proposed a greedy, layer-by-layer training algorithm for DBNs that attempts to learn simpler models sequentially and then fine-tune the results for the overall model. Using complementary priors to eliminate the explaining-away effect, the algorithm consists of two main steps: 1. A greedy layer-wise training to learn the weights by a. Tying the weights of the unlearned layers. b. Applying CD to learn the weights of the current layer. 2. An up-down algorithm for fine-tuning the weights 2. An up-down algorithm for fine-tuning the weights Instead of learning the weights of millions of connections across many hidden layers at once, this training scheme finds the optimal solution for a single layer at a time, which makes it a greedy algorithm. This is accomplished by tying all the weights of the following layers and learning only the weights of the current layer. Tying weights also serves to eliminate the explaining-away phenomenon, which results in poorly trained deep networks when adopting other training algorithms. Restricted Boltzmann Machines For each input and hidden layer neuron, compute i. D = D + = ( ) - = ( ) ( ) ( ) w w p H v v p H v v ij ij i j i k j k 1 1 0 0 \| \| ( ) ( ) ii. D = D + - b b v v j j j j k ( ) ( ) 0 iii. D = D + = ( )- = ( ) ( ) c c p H v p H v i i i i k 1 1 0 \| ( \| ) Based on the Gibbs distribution, the energy function or loss function used to describe the joint probability distribution is denoted in Equation 7-1, where wij, bj, and ci are real-valued weights, and hi and vj can take values in the set (Aleksandrovsky et al. 1996): E v h w hv b v c h i n j m ij i j j m j j i n i i , . ( ) = - - - = = = = åå å å 1 1 1 1 (7-1) (7-1) The joint probability distribution is thus computed using Equation 7-2: (7-2) p v h e e E v h E v h , . , , ( ) = - ( ) - ( ) å å 1 h v (7-2) p v h e e E v h E v h , . , , ( ) = - ( ) - ( ) å å 1 h v 137 Chapter 7 ■ Deep Neural Networks DNN Training Algorithms E v h h v h 0 0 0 0 0 , log log ( ) = - ( )+ ( ) ( ) p p \| (7-4) logp v0 ( ) E v h h v h 0 0 0 0 0 , log log ( ) = - ( )+ ( ) ( ) p p \| (7-4) logp v0 ( ) ³ ( ) ( )+ ( ) ( ) å Q h v p h p v h all h 0 0 0 0 0 0 \| \| log log - ( ) ( ) å Q h v Q h v all h 0 0 0 0 0 \| \| log (7-5) ¶ ( ) ( ) ¶ = ( ) ( ) å log log p v w Q h v p h ij allh 0 0 0 0 0 \| (7-6) (7-4) ³ ( ) ( )+ ( ) ( ) å Q h v p h p v h all h 0 0 0 0 0 0 \| \| log log - ( ) ( ) å Q h v Q h v all h 0 0 0 0 0 \| \| log (7-5) ¶ ( ) ( ) ¶ = ( ) ( ) å log log p v w Q h v p h ij allh 0 0 0 0 0 \| (7-6) (7-5) (7-6) Once the weights have been learned for each layer, a variant of the wake–sleep algorithm with the CD weight update rule is used to fine-tune the learned parameters. The up–down algorithm is used to backfit the obtained solution to avoid underfitting—an important concern when training in an unsupervised and greedy fashion. The up–down algorithm subjects lower-level layers, whose weights were learned early in the training, to the influence of the higher-level layers, whose weights were learned toward the end of training. In the bottom-up pass the generative weights on directed connections are adjusted by computing the positive phase probabilities, sampling the states, using the CD weight update rule, and running Gibbs sampling for a limited number of iterations. The top-down pass will stochastically activate each of the lower layers, using the top-down connections. This is done by computing the negative phase probabilities, sampling the states, and computing the predictions of the network. DNN Training Algorithms As illustrated in Figure 7-7, the weights W0 between layers 1 and 2 are learned. The weights between all the following layers are tied to W0. Once CD learning has converged, the weights W1, between layers 2 and 3, are learned by tying the weights of all the following layers to W1 and fixing the weights between layers 1 and 2 that were learned in the previous stage to W0. Similarly, when the CD converges to the optimal values for W1, the weights of the third RBM block are untied from the second RBM block, and CD is used to learn the final set of weights W2. Figure 7-7. Sequential training Figure 7-7. Sequential training 138 Chapter 7 ■ Deep Neural Networks This process of tying, learning, and untying weights is repeated until all layers have been processed. DBNs with tied weights resemble RBMs. Therefore, as mentioned earlier, each RBM is learned, using CD learning. However, this algorithm can only be applied if the first two layers form an undirected graph, and the remaining hidden layers form a directed, acyclic graph. The energy of the directed model is computing, using Equation 7-4, which is bounded by Equation 7-5. Tying the weights produces equality in Equation 7-5 and renders Q v (.\| ) 0 and p v h ( \| ) 0 0 constant. The derivative of Equation 7-5 is simplified and equal to Equation 7-6. Therefore, tying the weights leads to a simpler objective function to maximize. Applying this rule recursively allows the training of a DBN (Hinton, Osindero, and Teh 2006). Table 7-2. Up–Down Algorithm Workflow (Hinton and Salakhutdinov 2006) Table 7-2. Up–Down Algorithm Workflow (Hinton and Salakhutdinov 2006) 1. In the bottom-up pass: a. Compute positive phase probabilities. b. Sample states. c. Compute CD statistics, using the positive phase probabilities. d. Perform Gibbs sampling for a predefined number of iterations, based on the associative memory part of the network. e. Compute negative phase contrastive divergence statistics, using information from step 1d. 2. In the top-down pass: a. Calculate negative phase probabilities. b. Sample states. c. Compute predictions. 3. Update generative parameters. 4. Update associative memory part of the network. 5. Update inference parameters. Despite its limitations when applied to DNNs, interest in the backpropagation algorithm was renewed, because of the surge in graphics processing unit (GPU) computational power. Ciresan et al. (2010) investigated the performance of the backpropagation algorithm on deep networks. It was observed that, even with the vanishing gradient problem, given enough epochs, backpropagation can achieve results comparable to those of other, more complex training algorithms. It is to be noted that supervised learning with deep architectures has been reported as performing well on many classification tasks. However, when the network is pretrained in an unsupervised fashion, it almost always performs better than the scenarios where pretraining is omitted without the pretraining phase (Erhan et al. 2010). Several theories have been proposed to explain this phenomenon, such as that the pretraining phase acts as a regularizer (Bengio 2009; Erhan et al. 2009) and an aid (Bengio et al. 2007) for the supervised optimization problem. DNN-Related Research The use of DBN in various machine learning applications has flourished since the introduction of Hinton’s fast, greedy training algorithm. Furthermore, many attempts have been made to speed up DBN and address its weaknesses. The following sections offer a brief survey of the most recent and relevant applications of DBN, a presentation on research aimed at speeding up training as well as a discussion of several DBN variants and DNN architectures. DNN Training Algorithms Appropriate adjustments to the generative and inference parameters as well as the top-layer weights are performed in a contrastive form of the wake–sleep algorithm, because it addresses issues in the sleep phase of the algorithm. The workflow for this algorithm is shown in Table 7-2. 139 Chapter 7 ■ Deep Neural Networks Table 7-2. Up–Down Algorithm Workflow (Hinton and Salakhutdinov 2006) DNN Applications DNN has been applied to many machine learning applications, including feature extraction, feature reduction, and classification problems, to name a few. Feature extraction involves transforming raw input data to feature vectors that represent the input; raw data can be audio, image, or text. For example, DBN has been applied to discrete Fourier transform (DFT) representation of music audio (Hamel and Eck 2010) and found to outperform Mel frequency cepstral coefficients (MFCCs), a widely used method of music audio feature extraction. Once features are extracted from raw data, the high-dimensional data representation may have to be reduced to alleviate the memory and computational requirements of classification tasks as well as enable 140 Chapter 7 ■ Deep Neural Networks better visualization of the data and decrease the memory needed to store the data for future use. Hinton and Salakhutdinov (Hinton and Salakhutdinov 2006; Salakhutdinov and Hinton 2007) used a stack of RBMs to pretrain the network and then employed autoencoder networks to learn the low-dimensional features. Extracting expressive and low-dimensional features, using DBN, was shown to be possible for fast better visualization of the data and decrease the memory needed to store the data for future use. Hinton and Salakhutdinov (Hinton and Salakhutdinov 2006; Salakhutdinov and Hinton 2007) used a stack of RBMs to pretrain the network and then employed autoencoder networks to learn the low-dimensional features. Extracting expressive and low-dimensional features, using DBN, was shown to be possible for fast retrieval of documents and images, as tested on some ever-growing databases. Ranzato and Szummer (2008) were able to produce compact representations of documents to speed up search engines, while outperforming shallow machine learning algorithms. Applied to image retrieval from large databases, DBN produced results comparable to state-of-the art algorithms, including latent Dirichlet allocation and probabilistic latent semantic analysis (Hörster and Lienhart 2008). Transferring learned models from one domain to another has always been an issue for machine learning algorithms. However, DNN was able to extract domain-independent features (Bengio and Delalleau 2011), making transfer learning possible in many applications (Collobert and Weston 2008; Glorot, Bordes, and Bengio 2011; Bengio 2012; Ciresan, Meier, and Schmidhuber 2012;Mesnil et al. 2012). DNNs have also been used for curriculum learning, in which data are learned is a specific order (Bengio et al. 2009). DNN Applications g p g DBN has been applied to many classification tasks in fields such as vision, speech, medical ailments, and natural language processing (NLP). Object recognition from images has been widely addressed, and DBN’s performance exceeded state-of-the-art algorithms (Desjardins and Bengio 2008; Uetz and Behnke 2009; Ciresan et al. 2010; Ciresan, Meier, and Schmidhuber 2012). For instance, Ciresan et al. (2010) achieved an error rate of 0.35 percent on the Mixed National Institute of Standards and Technology (MNIST) database. Nair and Hinton (2009) outperformed shallow architectures, including SVM, on three-dimensional object recognition, achieving a 6.5 percent error rate, on the New York University Object Recognition Benchmark (NORB) dataset, compared with SVM’s 11.6 percent. Considering speech recognition tasks, deep architectures have improved acoustic modeling (Mohamed et al. 2011; Hinton et al. 2012), speech-to-text transcription (Seide, Li, and Yu 2011), and large-vocabulary speech recognition (Dahl et al. 2012; Jaitly et al. 2012; Sainath et al. 2011). On phone recognition tasks, DBN achieved an error rate of 23 percent on the TIMIT database—better than reported errors, ranging from 24.4 percent to 36 percent, using other machine learning algorithms (Mohamed, Yu, and Deng 2010). DBN produced classification results comparable to other machine learning algorithms in seizure prediction, using electroencephalography (EEG) signals, but reached those results in significantly faster times—between 1.7 and 103.7 times faster (Wulsin et al. 2011). McAfee (2008) adopted DBN for document classification and showed promise for succeeding on such databases. Generating synthetic images—specifically facial expressions—from a high-level description of human emotion is another area in which DBN has been successfully applied, producing a variety of realistic facial expressions (Susskind et al. 2008). NLP, in general, has also been investigated with deep architectures to improve on state-of-the-art results. Such applications include machine transliteration (Deselaers et al. 2009), sentiment analysis (Zhou Chen, and Wang 2010; Glorot, Bordes, and Bengio 2011), and language modeling (Collobert and Weston 2008; Weston et al. 2012)—including part-of-speech tagging, similar-word recognition, and chunking. The complexity of these problems requires a machine learning algorithm with more depth (Bengio and Delalleau 2011) to produce meaningful results. For example, machine transliteration poses a challenge to machine learning algorithms, because the words do not have a unified mapping, which leads to a many- to-many mapping that does not exist in dictionaries. DNN Applications Additionally, the large number of source-to-target language-pair character symbols and different sound structures leading to missing sounds are just a few properties of transliteration that make it difficult for machines to do well. Deep Networks Similar to DBN One variation of DBN, called modular DBN (M-DBN), trains different parts of the network separately, while adjusting the learning rate as training progresses (Pape et al. 2011), as opposed to using one training set for the whole network. This allows M-DBN to avoid forgetting features learned early in training, a weakness of DBN that can hinder its performance in online learning applications in which the data distribution changes dynamically over time. y Sparse DBN learns sparse features—unlike Hinton’s DBN, which learns nonsparse data Sparse DBN learns sparse features—unlike Hinton’s DBN, which learns nonsparse data representations—by adding a penalty in the objective function for deviations from the expected activation of hidden units in the RBM formulation (Lee, Ekanadham, and Ng 2007). representations—by adding a penalty in the objective function for deviations from the expected activation of hidden units in the RBM formulation (Lee, Ekanadham, and Ng 2007). Convolutional DBN integrates translation invariance into the image representations by sharing weights between locations in an image, allowing inference to be done when the image is scaled up by using convolution (Lee et al. 2009). Therefore, convolutional DBN scales better to real-world-sized images without suffering from computational intractability as a result of the high dimensionality of these images. DBNs are not the only deep architectures available. Sum product network (SPN) is a deep architecture represented as a graph with directed and weighted edges. SPN is acyclic (contains no loops), with variables on the leaves of the graph, and its internal nodes consist of sum and product operations (Poon and Domingo 2011). SPN trains, using backpropagation and expectation maximization (EM) algorithms. These simple operations result in a network that is more accurate, faster to train, and more tractable than DBN. Deep Boltzmann machines (DBMs) are similar to but have a more general deep architecture than DBNs. They are composed of BMs stacked on top of each others (Salakhutdinov and Hinton 2009). Although more complex and slower to train than DBNs, owing to the symmetrical connections between all neurons in the BM network, the two-way edges let DBMs propagate input uncertainty better than DBNs, making their generative models more robust. The more complex architecture requires an efficient training algorithm to make training feasible. The DBN greedy training algorithm was modified to achieve a more efficient training algorithm for DBM by using an approximate inference algorithm. Parallel Implementations to Speed Up DNN Training Sequentially training a DBN layer by layer becomes more time-consuming as the layer and network sizes increase. Stacking the layers to form networks, called deep-stacking networks, and training the network on CPU clusters, as opposed to one supercomputer (Deng, Hutchinson, and Yu 2012), exploit the inherent parallelism in the greedy training algorithm to achieve significant training-time savings. 141 Chapter 7 ■ Deep Neural Networks However, this method does not speed up the training time per layer. This can be achieved by parallelizing the training algorithm for the individual RBM layers, using GPUs (Cai et al. 2012). However, this method does not speed up the training time per layer. This can be achieved by parallelizing the training algorithm for the individual RBM layers, using GPUs (Cai et al. 2012). However, use of the large and sparse data commonly employed to train RBMs creates challenges for parallelizing this algorithm. Modifying the computations for matrix-based operations and optimizing the matrix–matrix multiplication code for sparse matrices make GPU implementation much faster than CPU implementation. As opposed to speeding up training via software, attempts have been made to speed up training via hardware, using field-programmable gate arrays (FPGAs). Ly and Chow (2010) mapped RBMs to FPGAs and achieved significant speedup of the optimized software code. This work was extended to investigate the scalability of the approach by Lo (2010). Arnold, Ludovic, Sébastien Rebecchi, Sylvain Chevallier, and Hélène Paugam-Moisy. “An Introduction to Deep Learning.” In Proceedings of the 19th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges, Belgium, April 27–29, 2011, edited by Michel Verleysen, 477–488. Leuven, Belgium: Ciaco, 2011. Deep Networks Similar to DBN However, this rendered DBM training approximately three times slower than DBN training (Salakhutdinov and Larochelle 2010). References Aleksandrovsky, Boris, James Whitson, Gretchen Andes, Gary Lynch, and Richard Granger. “Novel Speech Processing Mechanism Derived from Auditory Neocortical Circuit Analysis.” In Proceedings of the Fourth International Conference on Spoken Language, edited by H. Timothy Bunnell and William Idsardi, 558–561. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 1996. Arnold, Ludovic, Sébastien Rebecchi, Sylvain Chevallier, and Hélène Paugam-Moisy. “An Introduction to Deep Learning.” In Proceedings of the 19th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges, Belgium, April 27–29, 2011, edited by Michel Verleysen, 477–488. Leuven, Belgium: Ciaco, 2011. 142 Chapter 7 ■ Deep Neural Networks Bengio, Yoshua. “Learning Deep Architectures for AI.” In Foundations and Trends in Machine Learning 2, no. 1 (2009): 1–127. Bengio, Yoshua. “Learning Deep Architectures for AI.” In Foundations and Trends in Machine Learning 2, no. 1 (2009): 1–127. Bengio, Yoshua. “Deep Learning of Representations for Unsupervised and Transfer Learning.” In ICML 2011: Proceedings of the International Conference on Machine Learning Unsupervised and Transfer Learning Workshop, edited by Isabelle Guyon, Gideon Dror, Vincent Lemaire, Graham Taylor, and Daniel Silver, 17–36. 2012. http://jmlr.csail.mit.edu/proceedings/papers/v27/bengio12a/bengio12a.pdf. Bengio, Yoshua. “Deep Learning of Representations for Unsupervised and Transfer Learning.” In ICML 2011: Proceedings of the International Conference on Machine Learning Unsupervised and Transfer Learning Workshop, edited by Isabelle Guyon, Gideon Dror, Vincent Lemaire, Graham Taylor, and Daniel Silver, 17–36. 2012. http://jmlr.csail.mit.edu/proceedings/papers/v27/bengio12a/bengio12a.pdf. Bengio, Yoshua, and Olivier Delalleau. “On the Expressive Power of Deep Architectures.” In Algorithmic Learning Theory, edited by Jyrki Kivinen, Csaba Szepesvári, Esko Ukkonen, and Thomas Zeugmann, 18–36. Berlin: Springer, 2011. Bengio, Yoshua, Pascal Lamblin, Dan Popovici, and Hugo Larochelle. “Greedy Layer-Wise Training of Deep Networks.” In NIPS ’06: Proceedings of Advances in Neural Information Processing Systems 19, edited by Bernhard Schlkopf, John Platt, and Thomas Hofmann, 153–160. Cambridge, MA: Massachusetts Institute of Technology Press, 2007. Bengio, Yoshua, Jérôme Louradour, Ronan Collobert, and Jason Weston. “Curriculum Learning.” In ICML ’09: Proceedings of the 26th Annual International Conference on Machine Learning, edited by Léon Bottou and Michael Littman, 41–48. New York: ACM, 2009. Brown, Thomas H., Edward W. Kairiss, and Claude L. Keenan. “Hebbian Synapses: Biophysical Mechanisms ad Algorithms.”Annual Review of Neuroscience 13, no. 1 (1990): 475–511. Cai, Xianggao, Zhanpeng Xu, Guoming Lai, Chengwei Wu, and Xiaola Lin. Deselaers, Thomas, Saša Hasan, Oliver Bender, and Hermann Ney. “A Deep Learning Approach to Machine Transliteration.” In Proceedings of the Fourth Workshop on Statistical Machine Translation, e233–241. Stroudsburg, PA: Association for Computational Linguistics, 2009. g f p oudsburg, PA: Association for Computational Linguistics, 2009. References “GPU-Accelerated Restricted Boltzmann Machine for Collaborative Filtering.” In Algorithms and Architectures for Parallel Processing: Proceedings of the 12th International ICA3PP Conference, Fukuoka, Japan, September 2012, edited by Yang Xiang, Ivan Stojmenovic´, Bernady O. Apduhan, Guojun Wang, Koji Nakano, and Albert Zomaya, 303–316. Berlin: Springer, 2012. Ciresan, Dan Claudiu, Ueli Meier, Luca Maria Gambardella, and Jürgen Schmidhuber. “Deep, Big, Simple Neural Nets for Handwritten Digit Recognition.”Neural Computation 22, no. 12 (2010): 3207–3220. Ciresan, Dan Claudiu, Ueli Meier, and Jürgen Schmidhuber. “Transfer Learning for Latin and Chinese Characters with Deep Neural Networks.” In Proceedings of the 2012 International Joint Conference on Neural Networks, 1–6. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2012. Collobert, Robert. “Deep Learning for Efficient Discriminative Parsing.” Recorded April 2011. AISTATS video, 21:16. Posted May 6, 2011. http://videolectures.net/aistats2011_collobert_deep/. Collobert, Ronan, and Jason Weston. “A Unified Architecture for Natural Language Processing: Deep Neural Networks with Multitask Learning.” In ICML ’08: Proceedings of the 25th International Conference on Machine Learning, edited by Andrew McCallum and Sam Roweis, 160–167. New York: ACM, 2008. Dahl, George E., Dong Yu, Li Deng, and Alex Acero. “Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition.” IEEE Transactions on Audio, Speech, and Language Processing 20, no. 1 (2012): 30–42. Deng, Li, Brian Hutchinson, and Dong Yu. “Parallel Training for Deep Stacking Networks.” In Interspeech 2012: Proceedings of the 13th Annual Conference of the International Speech Communication Association. 2012. www.isca-speech.org/archive/interspeech_2012. Deselaers, Thomas, Saša Hasan, Oliver Bender, and Hermann Ney. “A Deep Learning Approach to Machine Transliteration.” In Proceedings of the Fourth Workshop on Statistical Machine Translation, e233–241. Stroudsburg, PA: Association for Computational Linguistics, 2009. 143 Chapter 7 ■ Deep Neural Networks Desjardins, Guillaume, and Yoshua Bengio. “Empirical Evaluation of Convolutional RBMs for Vision.” Technical report, Université de Montréal, 2008. Erhan, Dumitru, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, and Samy Bengio. “Why Does Unsupervised Pre-Training Help Deep Learning?” Journal of Machine Learning Research 11 (2010): 625–660. Erhan, Dumitru, Pierre-Antoine Manzagol, Yoshua Bengio, Samy Bengio, and Pascal Vincent. “The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training.” In Proceedings of the 12th International Conference on Artificial Intelligence and Statistics, edited by David van Dyk and Max Welling, 153–160. 2009. http://machinelearning.wustl.edu/mlpapers/paper_files/AISTATS09_ErhanMBBV.pdf. Farley, B. G., and W. Clark. “Simulation of Self-Organizing Systems by Digital Computer.” IEEE Transactions of the IRE Professional Group on Information Theory 4, no. 4 (1954): 76–84. Fischer, Asja, and Christian Igel. References “An Introduction to Restricted Boltzmann Machines.” In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: Proceedings of the 17th Iberoamerican Congress, CIARP 2012, Buenos Aires, Argentina, September 3–6, 2012, edited by Luis Alvarez, Marta E. Mejail, Luis E. Gomez, and Julio E. Jacobo, 14–36. Berlin: Springer, 2012. Fukushima, Kunihiko. “Neocognition: A Self-Organizing Neural Network Model for a Mechanism of Pattern Recognition Unaffected by Shift in Position.” Biological Cybernetics 36 (1980): 193–202. Glorot, Xavier, Antoine Bordes, and Yoshua Bengio. “Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach.” In ICML ’11: Proceedings of the 28th International Conference on Machine Learning, 513–520. 2011. www.icml-2011.org/papers/342_icmlpaper.pdf. Hamel, Philippe, and Douglas Eck. “Learning Features from Music Audio with Deep Belief Networks.” In ISMIR 2010: Proceedings of the 11th International Society for Music Information Retrieval Conference (ISMIR 2010), August 9–13, 2010, Utrecht, the Netherlands, edited by J. Stephen Downie and Rembo C. Veltkamp, 339–344. International Society for Music Information Retrieval, 2010. http://ismir2010.ismir. net/proceedings/ISMIR2010_complete_proceedings.pdf. Hawkins, Jeff, and Sandra Blakeslee. On Intelligence. New York: Macmillan, 2007. Haykin, Simon. Neural Networks. Upper Saddle River, NJ: Prentice Hall, 1994. Hebb, Donald. The Organization of Behavior. New York: Wiley, 1949. Hebb, Donald. The Organization of Behavior. New York: Wiley, 1949. Hinton, Geoffrey E. “Training Products of Experts by Minimizing Contrastive Divergence.” Neural Computation 14, no. 8 (2002): 1771–1800. Hinton, Geoffrey E. “To Recognize Shapes, First Learn to Generate Images.” Progress in Brain Research 165 (2007): 535–547. Hinton, Geoffrey E.. “A Practical Guide to Training Restricted Boltzmann Machines.” Momentum 9, no. 1 (2010). Hinton, Geoffrey E., Li Deng, Dong Yu, George E. Dahl, Abdel-rahman Mohamed, Navdeep Jaitly, Andrew Senior, et al. “Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups.” IEEE Signal Processing Magazine 29, no. 6 (2012): 82–97. Hinton, Geoffrey E., Simon Osindero, and Yee-Whye Teh. “A Fast Learning Algorithm for Deep Belief Nets.” Neural Computation 18, no. 7 (2006): 1527–1554. Hinton, Geoffrey E., and Ruslan R. Salakhutdinov. “Reducing the Dimensionality of Data with Neural Networks.” Science 313, no. 5786 (2006): 504–507. 144 Chapter 7 ■ Deep Neural Networks Hochreiter, Sepp. “Untersuchungen zu dynamischen neuronalen Netzen.” Master's thesis, Technical University of Munich, 1991. Hochreiter, Sepp. “Untersuchungen zu dynamischen neuronalen Netzen.” Master's thesis, Technical University of Munich, 1991. Hochreiter, Sepp, Yoshua Bengio, Paolo Frasconi, and Jürgen Schmidhuber. References “Gradient Flow in Recurrent Nets: The Difficulty of Learning Long-Term Dependencies.” In A Field Guide to Dynamical Recurrent Neural Networks, edited by John F. Kolen and Stefan C. Kremer, 237–244. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2001. Hörster, Eva, and Rainer Lienhart. “Deep Networks for Image Retrieval on Large-Scale Databases.” In Proceedings of the 16th ACM International Conference on Multimedia, 643–646. New York: ACM, 2008. Jain, Anil K., Jianchang Mao, and K. M. Mohiuddin. “Artificial Neural Networks: A Tutorial.” Computer 29, no. 3 (1996): 31–44. Jaitly, Navdeep, Patrick Nguyen, Andrew W. Senior, and Vincent Vanhoucke. “Application of Pretrained Deep Neural Networks to Large Vocabulary Speech Recognition.” In Interspeech 2012: Proceedings of the 13th Annual Conference of the International Speech Communication Association. 2012. www.isca-speech.org/ Jaitly, Navdeep, Patrick Nguyen, Andrew W. Senior, and Vincent Vanhoucke. “Application of Pretrained Deep Neural Networks to Large Vocabulary Speech Recognition.” In Interspeech 2012: Proceedings of the 13th Annual Conference of the International Speech Communication Association. 2012. www.isca-speech.org/ archive/interspeech_2012/. Neural Networks to Large Vocabulary Speech Recognition. In Interspeech 2012: Proceedings of the 13th Annual Conference of the International Speech Communication Association. 2012. www.isca-speech.org/ archive/interspeech_2012/. Lee, Honglak, Chaitanya Ekanadham, and Andrew Y. Ng. “Sparse Deep Belief Net Model for Visual Area V2.” Proceedings of NIPS 2007: Advances in Neural Information Processing Systems, edited by J. C. Platt, D. Koller, Y. Singer, and S. T. Roweis. 2008. http://papers.nips.cc/paper/3313-sparse-deep-belief-net-model- for-visual-area-v2.pdf. Lee, Honglak, Roger Grosse, Rajesh Ranganath, and Andrew Y. Ng. “Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations.” In ICML ’09: Proceedings of the 26th Annual International Conference on Machine Learning, edited by Léon Bottou and Michael Littman, 609–616. New York: ACM, 2009. Lo, Charles. “A FPGA Implementation of Large Restricted Boltzmann Machines.” In Proceedings of the 18th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), May 2–4, 2010, Charlotte, NC, 201–208. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2010. Ly, Daniel L., and Paul Chow. “High-Performance Reconfigurable Hardware Architecture for Restricted Boltzmann Machines.” IEEE Transactions on Neural Networks 21, no. 1 (2010): 1780–1792. McAfee, Lawrence. “Document Classification Using Deep Belief Nets,” 2008. Mesnil, Grégoire, Yann Dauphin, Xavier Glorot, Salah Rifai, Yoshua Bengio, Ian J. Goodfellow, Erick Lavoie, et al. References “Unsupervised and Transfer Learning Challenge: A Deep Learning Approach.” In ICML 2011: Proceedings of the International Conference on Machine Learning Unsupervised and Transfer Learning Workshop, edited by Isabelle Guyon, Gideon Dror, Vincent Lemaire, Graham Taylor, and Daniel Silver, 97–110. 2012. http://jmlr.csail.mit.edu/proceedings/papers/v27/mesnil12a/mesnil12a.pdf. Mohamed, Abdel-rahman, Tara N. Sainath, George Dahl, Bhuvana Ramabhadran, Geoffrey E. Hinton, and Michael A. Picheny. “Deep Belief Networks Using Discriminative Features for Phone Recognition.” In Proceedings of the 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, 5060–5063. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2011. Mohamed, Abdel-rahman, Dong Yu, and Li Deng. “Investigation of Full-Sequence Training of Deep Belief Networks for Speech Recognition.” In Interspeech 2010: Proceedings of 11th Annual Conference of the International Speech Communication Association, edited by Takao Kobayashi, Keikichi Hirose, and Satoshi Nakamura, 2846–2849. 2010. www.isca-speech.org/archive/interspeech_2010/i10_2846.html. 145 Chapter 7 ■ Deep Neural Networks Nair, Vinod, and Geoffrey E. Hinton. “3D Object Recognition with Deep Belief Nets.” In NIPS ’09: Proceedings of Advances in Neural Information Processing Systems 22, edited Yoshua Bengio, Dale Schuurmans, John Lafferty, Chris Williams, and Aron Culotta, 1339–1347. 2009. http://machinelearning.wustl.edu/ mlpapers/paper_files/NIPS2009_0807.pdf. Pape, Leo, Faustino Gomez, Mark Ring, and Jürgen Schmidhuber. “Modular Deep Belief Networks That Do Not Forget.” In Proceedings of the 2011 International Joint Conference on Neural Networks, 1191–1198. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2011. Poon, Hoifung, and Pedro Domingos. “Sum-Product Networks: A New Deep Architecture.” In Proceedings of the 2011 IEEE International Conference on Computer Vision Workshops, 689–690. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2011. Ranzato, Marc’Aurelio, and Martin Szummer. “Semi-Supervised Learning of Compact Document Representations with Deep Networks.” In ICML ’08: Proceedings of the 25th International Conference on Machine Learning, edited by Andrew McCallum and Sam Roweis, 792–799. New York: ACM, 2008. Representations with Deep Networks. In ICML 08: Proceedings of the 25th International Conference on Machine Learning, edited by Andrew McCallum and Sam Roweis, 792–799. New York: ACM, 2008. Rosenblatt, Frank. “The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain.” Psychological Review 65, no. 6 (1958): 386–408. Sainath, Tara N., Brian Kingsbury, Bhuvana Ramabhadran, Petr Fousek, Petr Novak, and Abdel-rahman Mohamed. “Making Deep Belief Networks Effective for Large Vocabulary Continuous Speech Recognition.” In Proceedings of the 2011 IEEE Workshop on Automatic Speech Recognition and Understanding, edited by Thomas Hain and Kai Yu, 30–35. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2011. Susskind, Joshua M., Geoffrey E. Hinton, Javier R. Movellan, and Adam K. Anderson. “Generating Facial Expressions with Deep Belief Nets.” In Affective Computing: Focus on EmotionExpression, Synthesis and Recognition, edited by Jimmy Or, 421–440. Vienna: I-Tech, 2008. References Salakhutdinov, Ruslan, and Geoffrey Hinton. “Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure.” In Proceedings of the 11th International Conference on Artificial Intelligence and Statistics, edited by Marina Meila and Xiaotong Shen, 412–419. 2007. http://jmlr.csail.mit.edu/ proceedings/papers/v2/salakhutdinov07a/salakhutdinov07a.pdf. Salakhutdinov, Ruslan, and Geoffrey Hinton. “Deep Boltzmann Machines.” In Proceedings of the 12th International Conference on Artificial Intelligence and Statistics, edited by David van Dyk and Max Welling, 448–455. 2009. www.jmlr.org/proceedings/papers/v5/salakhutdinov09a/salakhutdinov09a.pdf. Salakhutdinov, Ruslan, and Geoffrey Hinton. “Deep Boltzmann Machines.” In Proceedings of the 12th International Conference on Artificial Intelligence and Statistics, edited by David van Dyk and Max Welling, 448–455. 2009. www.jmlr.org/proceedings/papers/v5/salakhutdinov09a/salakhutdinov09a.pdf. Salakhutdinov, Ruslan, and Hugo Larochelle. “Efficient Learning of Deep Boltzmann Machines.” In Proceedings of the 13th Annual International Conference on Artificial Intelligence and Statistics, edited by Yee Whye Teh and Mike Titterington, 693–700. 2010. www.dmi.usherb.ca/~larocheh/publications/ aistats_2010_dbm_recnet.pdf. Salakhutdinov, Ruslan, and Hugo Larochelle. “Efficient Learning of Deep Boltzmann Machines.” In Proceedings of the 13th Annual International Conference on Artificial Intelligence and Statistics, edited by Yee Whye Teh and Mike Titterington, 693–700. 2010. www.dmi.usherb.ca/~larocheh/publications/ aistats_2010_dbm_recnet.pdf. Schmidhuber, Jurgen. “Learning Complex, Extended Sequences Using the Principle of History Compression.” Neural Computation 4 (1992): 234–242. Seide, Frank, Gang Li, and Dong Yu. “Conversational Speech Transcription Using Context-Dependent Deep Neural Networks.” In Interspeech 2011: Proceedings of 11th Annual Conference of the International Speech Communication Association, edited by Piero Cosi, Renato De Mori, Giuseppe Di Fabbrizio, and Roberto Pieraccini, 437–440. 2011. www.isca-speech.org/archive/interspeech_2011. Smolensky, Paul. “Information Processing in Dynamical Systems: Foundations of Harmony Theory.” In Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Vol. 1, edited by David E. Rumelhart, James L. McClelland, and the PDP Research Group, 194–281. Cambridge, MA: Massachusetts Institute of Technology Press, 1986. Susskind, Joshua M., Geoffrey E. Hinton, Javier R. Movellan, and Adam K. Anderson. “Generating Facial Expressions with Deep Belief Nets.” In Affective Computing: Focus on EmotionExpression, Synthesis and Recognition, edited by Jimmy Or, 421–440. Vienna: I-Tech, 2008. 146 Chapter 7 ■ Deep Neural Networks Uetz, Rafael, and Sven Behnke. “Locally-Connected Hierarchical Neural Networks for GPU-Accelerated Object Recongition.” In Proceedings of the NIPS 2009 Workshop on Large-Scale Machine Learning Parallelism and Massive Datasets. 2009. Werbos, Paul. “Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences.” PhD thesis, Harvard University, 1974. Weston, Jason, Frédéric Ratle, Hossein Mobahi, and Ronan Collobert. Cortical Algorithms If you just have a single problem to solve, then fine, go ahead and use a neural network. But if you want to do science and understand how to choose architectures, or how to go to a new problem, you have to understand what different architectures can and cannot do. —Marvin Minsky1 Computational models inspired by the structural and functional properties of the human brain have seen impressive gains since the mid-1980s, owing to significant discoveries in neuroscience and advancements in computing technology. Among these models, cortical algorithms (CAs) have emerged as a biologically inspired approach, modeled after the human visual cortex, which stores sequences of patterns in an invariant form and recalls those patterns autoassociatively. This chapter details the structure and mathematical formulation of CA then presents a case study of CA generalization accuracy in identifying isolated Arabic speech using an entropy-based weight update. Cortical Algorithm Primer Initially developed by Edelman and Mountcastle (1978), and inspired by the visual human cortex, CAs are positioned to be superior to the early generations of artificial neural networks (ANNs), which do not use temporal and spatial relationships in data for building machine learning models. The CA model consists of a multilayered network, with the cortical column as the basic structure. The network is trained in a two-stage manner: the first learning stage is unsupervised and trains the columns to identify independent features from the patterns occurring; the second stage relies on supervised feedback learning to create invariant representations. 1Marvin Minsky, “Scientist on the Set: An Interview with Marvin Minsky,” in HAL’s Legacy: 2001’s Computer as Dream and Reality, by David G. Stork (Massachusetts Institute of Technology Press, 1998), p. 18. References “Deep Learning via Semi-Supervised Embedding.” In Neural Networks: Tricks of the Trade, Second Edition, edited by Grégoire Montavon, Geneviève Orr, and Klaus-Robert Müller, 639–655. Berlin: Springer, 2012. Wulsin, D. F., J. R. Gupta, R. Mani, J. A. Blanco, and B. Litt. “Modeling Electroencephalography Waveforms with Semi-Supervised Deep Belief Nets: Fast Classification and Anomaly Measurement.” Journal of Neural Engineering 8, no. 3 (2011): 036015. Zhou, Shusen, Qingcai Chen, and Xiaolong Wang. “Active Deep Networks for Semi-Supervised Sentiment Classification.” In Proceedings of the 23rd International Conference on Computational Linguistics: Posters, edited by Chu-Ren Huang and Dan Jurafsky, 1515–1523. Stroudsburg, PA: Association for Computational Linguistics, 2010. 147 Cortical Algorithm Structure Nomenclature conventions for the weight , , , Wi j k r t During the learning process a connection is disabled by assigning to it a zero weight. If the network is fully connected, each neuron j in the column is connected to all the columns in the previous layer. All connections are elastic; that is, if a connection is disabled during the feedforward process, it can be restored during the feedback learning, and vice versa. The weight matrix representing the state of a column composed of M nodes during the training epoch t is defined by Wi r t, , , , , , , , , . = ¼ ¼ éë ùû W W W W i r t i r t i j r t i M r t 1 2 (8-1) Wi r t, , , , , , , , , . = ¼ ¼ éë ùû W W W W i r t i r t i j r t i M r t 1 2 (8-1) (8-1) The weight vector Wi j r t , , of the connections entering neuron j of column i in layer r, composed of Lr columns, is given by The weight vector Wi j r t , , of the connections entering neuron j of column i in layer r, composed of Lr columns, is given by Wi j r t , , , , , , , , , , , , , , , = ¼ ¼ éë ùû - W W W W i j r t i j r t i j k r t i j L r t r 1 2 1 ¢ (8-2) (8-2) where Lr-1 is the number of columns in the layer (r-1), Lr represents the number of columns in the layer r, and the superscript ' stands for the transpose operator. Cortical Algorithm Structure The human brain is a six-layered structure consisting of a very large number of neurons strongly connected via feedforward and feedback connections. An important property of the neocortex is its structural and functional uniformity: all units in the network seem similar, and they perform the same basic operation. Like this brain architecture, CA architecture has minicolumns of varying thickness (Edelman and Mountcastle 1978). A minicolumn is a group of neurons that share the same receptive field: neurons belonging to a minicolumn are associated with the same sensory input region. The minicolumn is the basic structure in a cortical network, in contrast to neurons in a classical ANN. An association of minicolumns is called a hypercolumn or layer 149 Chapter 8 ■ Cortical Algorithms (in what follows, the terms column and minicolumn are used interchangeably). Connections in a CA network occur in two directions: horizontally, between columns in the same layer, and vertically, between columns of consecutive layers. Although connections between nonconsecutive layers are present in the human cortex, these connections are omitted in CA, for the sake of simplicity. (in what follows, the terms column and minicolumn are used interchangeably). Connections in a CA network occur in two directions: horizontally, between columns in the same layer, and vertically, between columns of consecutive layers. Although connections between nonconsecutive layers are present in the human cortex, these connections are omitted in CA, for the sake of simplicity. Figure 8-1 displays a representation of a cortical network. The lateral inhibiting connections are not shown explicitly in the figure because their functionality is not physical; that is, these connections do not represent data propagated between neurons, but serve as a means of communication between the columns. Figure 8-1. Schematic of cortical network connectivity Figure 8-1. Schematic of cortical network connectivity Figure 8-1. Schematic of cortical network connectivity The notation adopted hereafter is given in Figure 8-2, whereWi j k r t , , , represents the weight of the connection between the jth neuron of the ith column of layer r and the kth column of the previous layer (r-1) during the training epoch t. Bold variables stand for vector entities, underlined variables represent matrices, and italic variables represent scalar entities. 150 Chapter 8 ■ Cortical Algorithms Figure 8-2. Nomenclature conventions for the weight , , , Wi j k r t Figure 8-2. Chapter 8 ■ Cortical Algorithms Cortical Algorithm Structure the output of the jth neuron of the ith column in the rth layer at the training epoch t, given by Zi j r t , , is the output of the jth neuron of the ith column in the rth layer at the training epoch Z Z Z f W Z i r t j M i j r t i j r t k L i j k r t k r t r , , , , , , , , , ; = = æ è ç ö ø = = - å å - 1 1 1 1 ÷. (8-5) (8-5) Zi j r , is the output of the jth neuron constituting the ith column of the rth layer, and f W Z k L i j k r t k r t r = - - å æ è ç ö ø ÷ 1 1 1 , , , , is defined by Zi j r , is the output of the jth neuron constituting the ith column of the rth layer, and f W Z k i j k r t k r t r = - å æ è ç ö ø ÷ 1 1 1 , , , , is defined by f W Z W Z k L i j k r t k r t k L i j k r t r r = - = - - å å æ è çç ö ø ÷÷ = + 1 1 1 1 1 1 1 , , , , , , , exp k r t k L i j k r t k r t r W Z T - = - - å æ è çç ö ø ÷÷ - æ è çç ö ø ÷÷ ì íï îï ü ý 1 1 1 1 , , , , , . Cortical Algorithm Structure j ï þï æ è çç ö ø ÷÷ = - = - = - - å å j k L i j k r t k r t k L i j k r r r W Z if W 1 1 1 1 1 2 , , , , , , ,t k r t k L i j k r t k r t Z W Z otherwise r - = - = ì í ïï î ï ï ì í ï ï ï ï - å 1 1 1 1 1 , , , , , , ï î ï ï ï ï ï (8-6) (8-6) where T is a tolerance parameter empirically selected and constant for all epochs and columns. It is assumed that all weights are normalized and bounded between –1 and 1. where T is a tolerance parameter empirically selected and constant for all epochs and columns. It is assumed that all weights are normalized and bounded between –1 and 1. The nonlinear activation function is analogous to the propagation of the action potential through an axon in the neural system. Training of Cortical Algorithms Connectivity within the columns is modeled through the value of the synaptic weights. Initially, there is no specific connectivity between cortical columns. It is assumed that the network is fully connected before training. Also, all synaptic weights are initialized to random values that are very close to 0 to avoid preference to any particular pattern. The training process, as introduced by Edelman and Mountcastle (1978) and developed further by Hashmi (2010), is described in the following sections, according to its main phases: unsupervised feedforward, supervised feedback, and weight update. Cortical Algorithm Structure E di W r t i ld y p p Expanding Wi r t, yields W W W W W W i r t i r t i j r t i M r t i k r t i j k r , , , , , , , , , , , , , , , , = 1 1 1 1 1         t i M k r t i L r t i j L r t i M L r t W W W W r r r         , , , , , , , , , , , , 1 1 1 1 - - - é ë ê ê ê ê ê ê ê ù û ú ú ú ú ú ú ú . (8-3) (8-3) The output vector Zr,t of layer r for epoch t is given by The output vector Zr,t of layer r for epoch t is given by The output vector Zr,t of layer r for epoch t is given by Z r t, , , , . , , , , , , = ¼ ¼ éë ùû Z Z Z Z r t r t i r t L r t r 1 2 ¢ Z r t, , , , . , , , , , , = ¼ ¼ éë ùû Z Z Z Z r t r t i r t L r t r 1 2 ¢ (8-4) (8-4) where Zi r t, is the output of column i in the layer for the same training epoch. where Zi r t, is the output of column i in the layer for the same training epoch. 151 Chapter 8 ■ Cortical Algorithms Considering the output of a neuron to be the result of the nonlinear activation function f(.), in response to the weighted sum of the connections entering the neuron, the output of the column is defined as the sum of the outputs of the neurons constituting the column. Considering the output of a neuron to be the result of the nonlinear activation function f(.), in response to the weighted sum of the connections entering the neuron, the output of the column is defined as the sum of the outputs of the neurons constituting the column. Supervised Feedback Feedforward learning trains columns to identify features of the data, such that the hierarchical network starts to recognize patterns. When the network is exposed to a variation of a pattern that is quite different from the previous one, the top layer of columns that are supposed to fire for that pattern do not, and only some of the columns in the hierarchy may fire, which leads to a misclassification. Through the CA feedback mechanism, the error occurring at the top layer generates a feedback signal that forces the column firing for the original pattern to fire, while inhibiting the column that is firing for the variation. Over multiple exposures the top layer should reach the desired firing scheme (also called stable activation). More specifically, designated columns in the top layer learn to fire for a particular pattern. Once the columns start to give a stable activation for pattern variations, the feedback signal is propagated back to the previous layers. Each layer is then trained until a convergence criterion, expressed as an error term in function of the actual output, and a desired output (firing scheme) are reached. The feedback signal is sent to the preceding layers only once the error in the layer concerned converges to a value below a certain, predefined tolerance threshold. The excitatory and inhibiting signals follow the same update rules as for the feedforward learning. Wh d f h f db k l i f h k CA b i d b h f ll i When used for the feedback learning of the network, CA can be summarized by the 1. Following the feedforward unsupervised batch learning (i.e., after the training data are entirely propagated through the network), a desired output scheme per layer is formed by averaging the column outputs. If Zi r k is the output of the ith column in the rth layer of the network for a certain training instance denoted by k and given N instances in total; the desired output for this particular column Zi r d is given by: 1. Following the feedforward unsupervised batch learning (i.e., after the training data are entirely propagated through the network), a desired output scheme per layer is formed by averaging the column outputs. Unsupervised Feedforward , , , + - - = + + + 1 1 1 1 r ( ) ( ) è ç ç ç ç ø ÷ ÷ ÷ ÷ W Wi r t, , (8-8) where W(Wi j r t , , ) is given by W W C W C if W other i r t i j k r t i j k r t i j k r t i j k r t , , , , , , , , , , , , , ; ( ) = = > 1 0 e wise k L j M r ì íï îï = = - å å 1 1 1 (8-9) where W(Wi j r t , , ) is given by where W(Wi j r t , , ) is given by W W C W C if W other i r t i j k r t i j k r t i j k r t i j k r t , , , , , , , , , , , , , ; ( ) = = > 1 0 e wise k L j M r ì íï îï = = - å å 1 1 1 (8-9) W W C W C if W other i r t i j k r t i j k r t i j k r t i j k r t , , , , , , , , , , , , , ; ( ) = = > 1 0 e wise k L j M r ì íï îï = = - å å 1 1 1 (8-9) (8-9) and where r is a tuning parameter, and e is the firing threshold chosen empirically to be constant for all epochs and columns. With repeated exposure the network learns to extract certain features of the input data, and the columns learn to fire for specific patterns. Layers in the network extract aspects of the input in increasing complexity. Thus, lower layers detect simple features, whereas higher stages learn concepts and more complex abstractions of the data. Unsupervised Feedforward , , , + - - = + + + 1 1 1 1 r ( ) ( ) æ è ç ç ç ç ö ø ÷ ÷ ÷ ÷ W Wi r t, , (8-8) where W(Wi j r t , , ) is given by W W C W C if W other i r t i j k r t i j k r t i j k r t i j k r t , , , , , , , , , , , , , ; ( ) = = > 1 0 e wise k L j M r ì íï îï = = - å å 1 1 1 (8-9) (8-7) • Strengthening: W Z W C e i j k r t k r t i j k r t i j k r t W T i j k r t , , , , , , , , , , . . , , , + - - = + + + 1 1 1 1 r ( ) ( ) æ è ç ç ç ç ö ø ÷ ÷ ÷ ÷ W Wi r t, , (8-8) (8-8) W Z W C e i j k r t k r t i j k r t i j k r t W T i j k r t , , , , , , , , , , . . Unsupervised Feedforward Feedforward learning trains columns to identify features via random firing and repeated exposure. When a pattern is presented, the input is propagated through the network. Each column has a small probability of firing, which means that most of the columns in a particular layer stay inactive. When the random firing of a particular column coincides with a particular input pattern, this activation is enforced. In other words, when activation is enforced, the column firing strengthens its weights, according to the strengthening weight update rule. At the same time, the column firing inhibits neighboring columns in the same layer from firing by weakening the weights, as presented in the inhibiting update rule. 152 Chapter 8 ■ Cortical Algorithms The weight update rules are as follows: ght update rules are as follows: The weight update rules are as follows: • Inhibiting: • Inhibiting: W Z W W i j k r t k r t i j k r t i j r t , , , , , , , , , . + - = - ( ) ( ) 1 1 W (8-7) • Strengthening: W Z W W i j k r t k r t i j k r t i j r t , , , , , , , , , . + - = - ( ) ( ) 1 1 W (8-7) W Z W W i j k r t k r t i j k r t i j r t , , , , , , , , , . + - = - ( ) ( ) 1 1 W (8-7) • Strengthening: W Z W C e i j k r t k r t i j k r t i j k r t W T i j k r t , , , , , , , , , , . . Supervised Feedback If Zi r k is the output of the ith column in the rth layer of the network for a certain training instance denoted by k and given N instances in total; the desired output for this particular column Zi r d is given by: Z avg Z N Z id r i r i r k N k k = ( ) = = å 1 1 . (8-10) Z avg Z N Z id r i r i r k N k k = ( ) = = å 1 1 . (8-10) 153 Chapter 8 ■ Cortical Algorithms 2. Starting with the last layer, compare the measured output of each column as a response to each instance k, Zi r t, with the desired value of Zi r d . If the desired output of a column is a firing state, whereas the actual is different, the column is strengthened (see Equation 8-8; the column is inhibited (see Equation 8-7) if the opposite occurs (i.e., if the actual output is firing, whereas a nonfiring state is desired). 3. Repeat step 2 until the error threshold is met. 3. Repeat step 2 until the error threshold is met. 4. Follow the same procedure for the previous layers, one layer at a time. Weight Update In CA, good accuracy is taxed with computationally expensive and lengthy training. This cost is mainly due to the computation of the exponential function invoked during the weight update process for each neuron while the weights of the network are learned. g For a particular node , , , Wi j k r t , Equation 8-8 may be written as: For a particular node , , , Wi j k r t , Equation 8-8 may be written as: W W W W W i j k r t i j k r t i j k r t i j k r t i , , , , , , , , , , , , . exp + = + ( ) ( ) = + 1 1 1 a q q b , , , , , , , , . , . j k r t k r t k r t k r t i j k T Z Z Z C - é ë ê ê ù û ú ú + = = = - - - W d a b r d 1 1 1 r t, ì í ï ï ïï î ï ï ï ï (8-11) W W W W W i j k r t i j k r t i j k r t i j k r t i , , , , , , , , , , , , . exp + = + ( ) ( ) = + 1 1 1 a q q b , , , , , , , , . , . j k r t k r t k r t k r t i j k T Z Z Z C - é ë ê ê ù û ú ú + = = = - - - W d a b r d 1 1 1 r t, ì í ï ï ïï î ï ï ï ï (8-11) W W W W W i j k r t i j k r t i j k r t i j k r t i , , , , , , , , , , , , . exp + = + ( ) ( ) = + 1 1 1 a q q b , , , , , , , , . , . Weight Update j k r t k r t k r t k r t i j k T Z Z Z C - é ë ê ê ù û ú ú + = = = - - - W d a b r d 1 1 1 r t, ì í ï ï ïï î ï ï ï ï (8-11) (8-11) Here, a, b, and d are variables that depend on the training epoch as well as the column considered; therefore, a suitable nomenclature would be in the form , ck r t -1 . For the sake of simplicity, one can omit the subscripts and superscripts for these variables, referring to W(Wi r t, ) as Ω. i As demonstrated in Equation 8-11, the parameters of the exponential weight update rule—a, b, d, Ω, and T—depend on the state of the column considered. Therefore, it can be inferred that the strengthening rule is a family of exponential functions with varying parameters for each column. The update of a column requires the computation of the exponential function for each of the nodes—hence, the lengthy training. Figure 8 3 shows a plot of q with respect to the value of the neuron weight for a random node As demonstrated in Equation 8-11, the parameters of the exponential weight update rule—a, b, d, Ω, and T—depend on the state of the column considered. Therefore, it can be inferred that the strengthening rule is a family of exponential functions with varying parameters for each column. The update of a column requires the computation of the exponential function for each of the nodes—hence, the lengthy training. Figure 8-3 shows a plot of q, with respect to the value of the neuron weight for a random n 154 Chapter 8 ■ Cortical Algorithms 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Value of neuron Amount of strengthening added Figure 8-3. Plot of q Wi j k r t , , , ( ) versus Wi j k r t , , , Chapter 8 ■ Cortical Algorithms 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Value of neuron Amount of strengthening added Figure 8-3. Weight Update Plot of q Wi j k r t , , , ( ) versus Wi j k r t , , , The computational cost involved in the strengthening rule also comes from the calculation of the exponential function. For example, MATLAB software uses the binomial theorem (see Equation 8-12) to compute the approximate value of an exponential, and this approximation is computed up to orders ranging from 5 to 10 (Mohler 2011): e x x x x n x i x n i i = + + + + + + = =å 1 2 3 2 3 0 ! ! ! ! .   ¥ (8-12) (8-12) The number of operations required to compute the exponential function is summarized in Table 8-1. The number of operations required to compute the exponential function is summarized in Ta Table 8-1. Required Operations for Exponential Function Expression Operations Total Number of Operations i ! 2 * 3 * … * i i-two multiplications xi x * x * x * … i multiplications x i i ! x x x i * * ¼ * ¼ 2 3 2i-one operation ex i n ix i =å 0 ! i n i n n n =å - + = + 0 2 2 1 ( ) Table 8-1. Required Operations for Exponential Function Expression Operations Total Number of Operations i ! 2 * 3 * … * i i-two multiplications xi x * x * x * … i multiplications x i i ! x x x i * * ¼ * ¼ 2 3 2i-one operation ex i n ix i =å 0 ! i n i n n n =å - + = + 0 2 2 1 ( ) Table 8-1. Required Operations for Exponential Function 155 Chapter 8 ■ Cortical Algorithms Figure 8-4. Training of a cortical network The workflow for CA training is displayed in Figure 8-4. Figure 8-4. Training of a cortical network The workflow for CA training is displayed in Figure 8 Figure 8-4. Training of a cortical network Experimental Results Experimental results for various pattern recognition databases obtained from the University of California, Irvine, Machine Learning Repository (Bache and Lichman 2013) show CA superior performance, as detailed for the following datasets: • Letter Recognition dataset: This dataset consists of a collection of 20,000 black-and-white images to be classified as one of the 26 capital letters of the English alphabet (Slate 1991). Each instance is represented by a set of 16 features of integer type, normalized into a range of 0-15 representing aspects of the image, such as horizontal and vertical position, and width and length. The best accuracy reported for this dataset is 97.58 percent (Bagirov and Ugon 2011). 156 Chapter 8 ■ Cortical Algorithms • Image Segmentation dataset: This dataset is collection of images sized 3 × 3 each, represented by 19 attributes describing features of the image, such as average intensity, saturation, and hue (Vision Group 1990). The dataset is divided into a training set consisting of 210 instances and a testing set of 2,100 instances; each image belongs to one of 7 classes. Dash et al. (2003) achieved an accuracy of 98.6 percent. • ISOLET (Isolated Letter Speech Recognition) dataset: The task in this experiment is to classify a collection of isolated spoken English letters as one of 26 classes (A-Z). The dataset is composed of 2,800 instances uttered by 150 speakers, each instance represented by a set of 617 features, including spectral coefficients, contour features, sonorant features, presonorant features, and postsonorant features (Cole and Fanty 1994). The reported accuracy of this database is 96.73 percent (Dietterich 1994). • ISOLET (Isolated Letter Speech Recognition) dataset: The task in this experiment is to classify a collection of isolated spoken English letters as one of 26 classes (A-Z). The dataset is composed of 2,800 instances uttered by 150 speakers, each instance represented by a set of 617 features, including spectral coefficients, contour features, sonorant features, presonorant features, and postsonorant features (Cole and Fanty 1994). The reported accuracy of this database is 96.73 percent (Dietterich 1994). • PENDIGITS (Pen-Based Recognition of Handwritten Digits) dataset: This experiment consists of pen-based recognition of handwritten digits. The database collects 10,992 samples from 44 writers, each sample being a sequence of (x, y) coordinates representing the trajectory of the pen during the writing process. Experimental Results The sequences have been resampled to obtain a fixed-length attribute vector equal to 16 (eight pairs of (x, y) coordinates) and normalized to eliminate the effect of artifacts resulting from different handwritings. The 10,992 samples are divided into a training set of 7,494 instances and 3,498 instances for testing. The accuracy of this dataset reached 98.6 percent (Alpaydin and Alimoglu 1998). • Multiple Features dataset: This dataset consists of 649 features, for a total of 2,000 patterns of handwritten numerals (`0'--`9') extracted from a collection of Dutch utility maps (Duin 2013). These digits are represented in terms of six feature sets: 76 Fourier coefficients of the character shapes; 216 profile correlations; 64 Karhunen-Loève coefficients; 240 pixel averages, in 2 × 3 windows; 47 Zernike moments; and six morphological features. The best accuracy achieved is 98 percent (Perkins and Theiler 2003). • Abalone dataset: The task for this dataset is to classify the age of a collection of 4,177 abalones from a total of eight physical measurements, such as height, weight, diameter, and length. This dataset is characterized by a highly unbalanced class distribution and has achieved an accuracy of 79.0 percent (Tan and Dowe 2003). Table 8-2 compiles the recognition rate, training time, and total number of required iterations for convergence, based on a fourfold cross-validation, using the mean squared error (MSE) and the well-formed cross-entropy (CE) cost functions at the output layer. Two experiments were performed: • Experiment 1: CA with the exponential weight update rule and MSE as a cost function • Experiment 2: CA with the exponential weight rule and CE as a cost function 157 Chapter 8 ■ Cortical Algorithms Table 8-2. On average the CE cost function results in better classification accuracy. However, this is achieved at the expense of an increase in computational complexity and training time. Modified Cortical Algorithms Applied to Arabic Spoken Digits: Case Study Because CAs have not been extensively implemented for automatic speech recognition (in particular for the Arabic language), the following sections show how CA strengthening and inhibiting rules originally employed during feedback were modified with weighted entropy concepts that were added to the CA cost function and the weight update rule. Experimental Results Experimental Results Dataset Measure Experiment 1 Experiment 2 Letter Recognition % Accuracy 98.3 98.8 Training time (min) 223 235 Number of epochs 237 225 Number of operations 8.9 * 1012 1.1 * 1013 Image Segmentation % Accuracy 99.3 99.7 Training time (min) 45 52 Number of epochs 77 69 Number of operations 22 * 1012 2.5 * 1012 ISOLET % Accuracy 98.1 98.7 Training time (min) 54 67 Number of epochs 147 131 Number of operations 2.6 * 1012 3.2 * 1012 PENDIGITS % Accuracy 99.8 100 Training time (min) 135 154 Number of epochs 94 82 Number of operations 6.5 * 1012 7.4 * 1012 Multiple Features % Accuracy 98.7 99.1 Training time (min) 35 42 Number of epochs 66 53 Number of operations 1.4 * 1012 2.0 * 1012 Abalone % Accuracy 91.8 92.2 Training time (min) 56 68 Number of epochs 70 62 On average the CE cost function results in better classification accuracy. However, this is achieved at the expense of an increase in computational complexity and training time. 158 Chapter 8 ■ Cortical Algorithms Note ■ ■ Despite their superior hypothetical performance, CAs remain less widely used than ANNs, owing to their longer and more expensive training and computational requirements. These make them unattractive for online learning, energy-aware computing nodes, and large datasets with stringent restrictions on the training duration. Entropy-Based Weight Update Rule During the feedback learning stage of a CA, the output of each layer is compared with a desired state of firing, and the weights are updated until an error term is reduced to a minimum threshold value. Using the least squares criterion, large error values influence the learning process much more than smaller ones. For a class of problems, the gradient descent algorithm, with the MSE as a criterion for weight updates, can be trapped in a local minimum and so it will fail to find the optimal solution. In contrast, the well-formed CE criterion, employing a gradient descent algorithm, guarantees convergence to the optimal solution during learning (Wittner and Denker 1988). ( ) ( ) three properties of a well-formed error function of the form J W h W i j k r t i j k r t , , , , , , ( ) ( ) =å are as follows g The three properties of a well-formed error function of the form J W h W i j k r t i j r t , , , , , , ( ( ) =å For all • Wi j k r t , , , the derivative of h Wi j k r t ( ) , , , , defined as h Wi j k r t ’ , , , ( ) , must be negative. There must exist an • > 0 , such that - ( ) ³ h Wi j k r t ’ , , , for all Wi j k r t , , , £ 0 . For all • Wi j k r t , , , the derivative of h Wi j k r t ( ) , , , , defined as h Wi j k r t ’ , , , ( ) , must be negat There must exist an • > 0 , such that - ( ) ³ h Wi j k r t ’ , , , for all Wi j k r t , , , £ 0 . Entropy-Based Weight Update Rule i j k , , i j k ( ) , , , i j k , , ( ) , There must exist an • > 0 , such that - ( ) ³ h Wi j k r t ’ , , , for all Wi j k r t , , , £ 0 . The function • h must be differentiable and bounded. CE as a cost function criterion can be written as J Z Z Z r t di r i r t di r i Lr , , ln , = = å 1 where Zdi r is the desired output of the ith column of layer r at epoch t. where Zdi r is the desired output of the ith column of layer r at epoch t. 159 Chapter 8 ■ Cortical Algorithms If you adopt the same procedure for the feedback learning, and assume that training convergence of each layer happens when the entropy measure falls below a predetermined threshold value, the weight update rule becomes: • Inhibiting: W J Z Z W W i j k r t r t i r t k r t i j k r t i r t , , , , , , , , , , . + - = - ( ) ( ) 1 1 D D W (8-13) (8-13) • Strengthening: ng: W J Z Z W C i j k r t r t i r t k r t i j k r t i j k r t , , , , , , , , , , , , . . . + - = + + + 1 1 1 1 D D r exp , , , , W T W i j k r t i r t - ( ) é ë ê ê ù û ú ú æ è ç ç ç ç çç ö ø ÷ ÷ ÷ ÷ ÷÷ W (8-14) One advantage of using the proposed gradient descent weighted rules is that the CE cost function diverges if one of the outputs converges to the wrong extreme; hence, the gradient descent reacts quickly. In contrast, the MSE cost function approaches a constant, and the gradient descent on the least square will wander on a plateau, even though the error may not be small. Experimental Validation Using a CA of six hidden layers, starting with 2,000 columns of 20 nodes for the first hidden layer and decreasing the number of columns by half between consecutive layers, four experiments, employing the weighted entropy weight update rule, were performed based on a fivefold cross-validation: • Experiment 1: CA trained using the MSE cost function and the original weight update rule • Experiment 2: CA trained using the MSE cost function and the proposed weight update rule • Experiment 3: CA trained using the CE cost function and the original weight update rule • Experiment 4: CA trained using the CE function and the proposed weight update rule Simulations were executed, using MATLAB R2011a software on an Intel i7 at 2GHz and 6GB RAM on a Windows 7 Home Premium operating system, using a modified central nervous system (CNS) library. Developed at the Massachusetts Institute of Technology, by Mutch, Knoblich, and Poggio (2010), the CNS library is a framework for simulating cortically organized networks. Simulations were executed, using MATLAB R2011a software on an Intel i7 at 2GHz and 6GB RAM on a Windows 7 Home Premium operating system, using a modified central nervous system (CNS) library. Developed at the Massachusetts Institute of Technology, by Mutch, Knoblich, and Poggio (2010), the CNS library is a framework for simulating cortically organized networks. The database was obtained from the UCI Machine Learning Repository and consists of a collection of 13 Mel frequency cepstral coefficient (MFCC) frames representing 8,800 spoken Arabic digits—one of ten classes (0-9), uttered by 88 different speakers, obtained after filtering the spoken digits, using a moving Hamming window. Several techniques were validated on this database; the best achieved result shows a 97.03 percent recognition rate, based on a threefold cross-validation, using a multiclass SVM classifier (Ji and Sun 2011). 160 Chapter 8 ■ Cortical Algorithms TREE REPRESENTATION FOR ARABIC PHONEMES As the first language in 22 countries, Arabic ranks fifth among the most spoken languages in the world (Mosa and Ali 2009). Although applications treating speech recognition have increased significantly (e.g., iPhone 4S Siri interface), implementation for the Arabic language is limited, mainly because of its morphological complexity. For Arabic automatic speech recognition, the recognition of phonemes constitutes an important step in continuous speech analysis. Most research proceeds by extracting isolated phonemes or small phonetic segments (El-Obaid, Al-Nassiri, and Maaly 2006; Awais 2003; Gevaert, Tsenov, and Mladenov 2010; Al-Manie, Alkanhal, and Al-Ghamdi 2009) for analysis of longer speech signals (Abushariah et al. 2010) and broadcast news (Al-Manie, Alkanhal, and Al-Ghamdi 2009), using several techniques, such as ANN (Essa, Tolba, and Elmougy 2008), fuzzy HMM (Shenouda, Zaki, and Goneid 2006), fuzzy logic, concurrent self-organizing maps (Sehgal, Gondal, and Dooley 2004), and HMM (Satori, Harti, and Chenfour 2007; Bourouba et al. 2010; Biadsy, Moreno, and Jansche 2012). Spoken in the Middle East and North Africa, Arabic has different dialects. However, Literary Arabic (also called Modern Standard Arabic) is the official form used in documents and for formal speaking in all Arabic-speaking countries. One of the differences between spoken and written Arabic is the presence in the latter of diacritics (marks used to indicate how a letter should be pronounced). The complexity of Arabic is the result of its unusual morphology: words are formed using a root-and-pattern scheme, in which the root is composed of 3 consonants, leading to several possibilities from one root. Phonetically, Arabic has 28 consonant segments and 6 vowels (Newman 1984). Phonemes can be grouped according to the articulation of the lips and tongue during speech, as shown in the classification of Arabic phonemes. 161 Chapter 8 ■ Cortical Algorithms Note ■ ■ MFCCs can model the acoustic content of speech independently of the source (speaker). MFCCs are calculated by mapping the logarithm of the spectrum into the Mel scale and converting the obtained signal back to the time domain, using discrete cosine transform (Klatau 2005). For consistency, the first experiment with the data used the 13 MFCCs provided and then added the first and second derivatives of the MFCCs, that is, coefficients with a feature vector of size 39. Tables 8-3 and 8-4 show a comparison of the results obtained for all experiments with the average recognition rate obtained, training time, and number of epochs required for convergence. TREE REPRESENTATION FOR ARABIC PHONEMES Confusion matrices for the Image Segmentation dataset: left, exponential rule; right, linear rule 65 11.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 100% 0.0% 0 0.0% 98 17.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 100% 0.0% 0 0.0% 0 0.0% 77 13.3% 0 0.0% 1 0.2% 0 0.0% 0 0.0% 98.7% 1.3% 2 0.3% 0 0.0% 0 0.0% 79 13.7% 1 0.2% 0 0.0% 0 0.0% 96.3% 3.7% 0 0.0% 1 0.2% 1 0.2% 1 0.2% 91 15.6% 0 0.0% 0 0.0% 97.8% 2.2% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 87 15.1% 0 0.0% 100% 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 75 13.0% 100% 0.0% 97.0% 3.0% 100% 0.0% 98.7% 1.3% 98.8% 1.2% 97.8% 2.2% 100% 0.0% 100% 0.0% 99.0% 1.0% 1 2 3 4 5 6 7 1 2 3 4 5 6 7 Confusion Matrix Output Class Target Class 65 11.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 100% 0.0% 0 0.0% 98 17.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 100% 0.0% 0 0.0% 0 0.0% 77 13.3% 0 0.0% 1 0.2% 0 0.0% 0 0.0% 98.7% 1.3% 1 0.2% 0 0.0% 0 0.0% 80 13.9% 1 0.2% 0 0.0% 0 0.0% 97.6% 2.4% 0 0.0% 1 0.2% 0 0.0% 0 0.0% 91 15.8% 0 0.0% 0 0.0% 98.9% 1.1% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 87 15.1% 0 0.0% 100% 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 75 13.0% 100% 0.0% 98.5% 1.5% 100% 0.0% 98.7% 1.3% 100% 0.0% 97.8% 2.2% 100% 0.0% 100% 0.0% 99.3% 0.7% 1 2 3 4 5 6 7 1 2 3 4 5 6 7 Confusion Matrix Output Class Target Class Confusion Matrix Confusion Matrix Figure 8-5. Confusion matrices for the Image Segmentation dataset: left, exponential rule; right, linear rule Figure 8-6 compares the CE cost function with the training epochs obtained while training the cortical network using the entropy cost function for the proposed and the regular weight update rules. Note that the proposed weight update converges to a smaller MSE value, compared with the regular update, which is consistent with the recognition rates obtained earlier. Figure 8-6. Entropy cost function comparison for regular and proposed weight update rules Figure 8-6. TREE REPRESENTATION FOR ARABIC PHONEMES Table 8-3. Results for the Spoken Arabic Digit Dataset, Using 13 MFCCs Experiment 1 Experiment 2 Experiment 3 Experiment 4 Recognition rate (%) 97.4 98.4 97.9 99.0 Training time (min) 90 110 100 115 Number of epochs until convergence 240 232 235 220 Table 8-3. Results for the Spoken Arabic Digit Dataset, Using 13 MFCCs Table 8-4. Results for the Arabic Spoken Digit Dataset, Using 39 MFCCs Experiment 1 Experiment 2 Experiment 3 Experiment 4 Recognition rate (%) 98.2 99.1 98.6 99.7 Training time (min) 125 142 137 156 Number of epochs until convergence 335 298 322 280 Table 8-4. Results for the Arabic Spoken Digit Dataset, Using 39 MFCCs Tables 8-3 and 8-4 demonstrate that training of the cortical network, using the entropy cost function and the proposed weight update rule, performed better than the original training parameters. This improvement is achieved at the expense of a small worsening of the required training time. Despite the lengthy training time, however, the proposed weight update rule requires fewer training epochs to converge, compared with the original weight update rule. This is because the amount of strengthening added using the proposed rule is proportional to the gradient of the cost function, meaning that fewer training epochs are necessary to reach convergence. The proposed weight update rule involves computing the entropy gradient, which is computationally more expensive, compared with the original weight update rule. The confusion matrices in Figure 8-5, obtained for the image segmentation dataset using both cost functions, demonstrate that although a significant trend is observed in the confusion between classes 1, 7, and 8 with the classical distance measure, the proposed entropy-based update rule was able to correct this trend partially. TREE REPRESENTATION FOR ARABIC PHONEMES 162 Chapter 8 ■ Cortical Algorithms 65 11.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 100% 0.0% 0 0.0% 98 17.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 100% 0.0% 0 0.0% 0 0.0% 77 13.3% 0 0.0% 1 0.2% 0 0.0% 0 0.0% 98.7% 1.3% 2 0.3% 0 0.0% 0 0.0% 79 13.7% 1 0.2% 0 0.0% 0 0.0% 96.3% 3.7% 0 0.0% 1 0.2% 1 0.2% 1 0.2% 91 15.6% 0 0.0% 0 0.0% 97.8% 2.2% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 87 15.1% 0 0.0% 100% 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 75 13.0% 100% 0.0% 97.0% 3.0% 100% 0.0% 98.7% 1.3% 98.8% 1.2% 97.8% 2.2% 100% 0.0% 100% 0.0% 99.0% 1.0% 65 11.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 100% 0.0% 0 0.0% 98 17.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 100% 0.0% 0 0.0% 0 0.0% 77 13.3% 0 0.0% 1 0.2% 0 0.0% 0 0.0% 98.7% 1.3% 1 0.2% 0 0.0% 0 0.0% 80 13.9% 1 0.2% 0 0.0% 0 0.0% 97.6% 2.4% 0 0.0% 1 0.2% 0 0.0% 0 0.0% 91 15.8% 0 0.0% 0 0.0% 98.9% 1.1% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 87 15.1% 0 0.0% 100% 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 75 13.0% 100% 0.0% 98.5% 1.5% 100% 0.0% 98.7% 1.3% 100% 0.0% 97.8% 2.2% 100% 0.0% 100% 0.0% 99.3% 0.7% 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 Confusion Matrix Confusion Matrix Output Class Output Class Target Class Target Class Figure 8-5. TREE REPRESENTATION FOR ARABIC PHONEMES Confusion matrices for the Image Segmentation dataset: left, exponential rule; right, linear rule 65 11.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 100% 0.0% 0 0.0% 98 17.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 100% 0.0% 0 0.0% 0 0.0% 77 13.3% 0 0.0% 1 0.2% 0 0.0% 0 0.0% 98.7% 1.3% 2 0.3% 0 0.0% 0 0.0% 79 13.7% 1 0.2% 0 0.0% 0 0.0% 96.3% 3.7% 0 0.0% 1 0.2% 1 0.2% 1 0.2% 91 15.6% 0 0.0% 0 0.0% 97.8% 2.2% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 87 15.1% 0 0.0% 100% 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 75 13.0% 100% 0.0% 97.0% 3.0% 100% 0.0% 98.7% 1.3% 98.8% 1.2% 97.8% 2.2% 100% 0.0% 100% 0.0% 99.0% 1.0% 65 11.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 100% 0.0% 0 0.0% 98 17.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 100% 0.0% 0 0.0% 0 0.0% 77 13.3% 0 0.0% 1 0.2% 0 0.0% 0 0.0% 98.7% 1.3% 1 0.2% 0 0.0% 0 0.0% 80 13.9% 1 0.2% 0 0.0% 0 0.0% 97.6% 2.4% 0 0.0% 1 0.2% 0 0.0% 0 0.0% 91 15.8% 0 0.0% 0 0.0% 98.9% 1.1% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 87 15.1% 0 0.0% 100% 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 75 13.0% 100% 0.0% 98.5% 1.5% 100% 0.0% 98.7% 1.3% 100% 0.0% 97.8% 2.2% 100% 0.0% 100% 0.0% 99.3% 0.7% 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 Confusion Matrix Confusion Matrix Output Class Output Class Target Class Target Class Figure 8-5. TREE REPRESENTATION FOR ARABIC PHONEMES Entropy cost function comparison for regular and proposed weight update rules 163 Chapter 8 ■ Cortical Algorithms References Abushariah, Mohammad A. M., Raja N. Ainon, Roziati Zainuddin, Moustafa Elshafei, and Othman O. Khalifa. “Natural Speaker-Independent Arabic Speech Recognition System Based on Hidden Markov Models Using Sphinx Tools.” In Proceedings of the 2010 International Conference on Computer and Communication Engineering, Kuala Lumpur, Malaysia, May 11–12, 2010, 1–6. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2010. Awais, M. M. “Recognition of Arabic Phonemes Using Fuzzy Rule Base System.” In Proceedings of the 7th International Multitopic Conference, Islamabad, Pakistan, December 8–9, 2003, 367–370. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2003. Bache, K., and M. Lichman. “University of California, Irvine, Machine Learning Repository.” Irvine: University of California, 2013. http://archive.ics.uci.edu/ml/index.html. Bagirov, A. M., J. Ugon, and D. Webb. “An Efficient Algorithm for the Incremental Construction of a Piecewise Linear Classifier.” Journal of Information Systems 36, no. 4 (2011): 782–790. Biadsy, Fadi, Pedro J. Moreno, and Martin Jansche. “Google's Cross-Dialect Arabic Voice Search.” In Proceedings of the 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, Kyoto, Japan, March 25–30, 2012, 4441–4444. Piscataway, NJ: Institute of Electrical and Electronic Engineering, 2012. Bourouba, H., R. Djemili, M. Bedda, and C. Snani. “New Hybrid System (Supervised Classifier/HMM) for Isolated Arabic Speech Recognition.” In Proceedings of the 2nd Conference on Information and Communication Technologies, Damascus, Syria, April 24–28, 2006, 1264–1269. Piscataway, NJ: Institute of Electrical and Electronic Engineering, 2006. Cole, Ron, and Mark Fanty. “ISOLET Data Set.” University of California, Irvine, Machine Learning Repository. Irvine: University of California, 1994. https://archive.ics.uci.edu/ml/datasets/ISOLET. Dash, Manoranjan, Huan Liu, Peter Scheuermann, and Kian Lee Tan. “Fast Hierarchical Clustering and Its Validation.” Data and Knowledge Engineering 44, no. 1 (2003): 109–138. Dietterich, Thomas G., and Ghulum Bakiri. “Solving Multiclass Learning Problems via Error-Correcting Output Codes.” Journal of Artificial Intelligence Research 2, no. 1 (1995): 263–286. Duin, Robert P. W. “Multiple Features Data Set.” University of California, Irvine, Machine Learning Repository. Irvine: University of California, 2013. http://archive.ics.uci.edu/ml/datasets/ Multiple+Features. Edelman, Gerald M., and Vernon B. Mountcastle. The Mindful Brain: Cortical Organization and the Group- Selective Theory of Higher Brain Function. Cambridge, MA: Massachusetts Institute of Technology Press, 1978. Essa, E. M., A. S. Tolba, and S. Elmougy. “A Comparison of Combined Classifier Architectures for Arabic Speech Recognition.” In Proceedings of the 2008 International Conference on Computer Engineering and Systems, Cairo, Egypt, November 25–27, 2008, 149–153. Piscataway, NJ: Institute of Electrical and Electronic Engineering, 2008. Gevaert, Wouter, Georgi Tsenov, and Valeri Mladenov. Klautau, Aldebaro. “The MFCC,” 2012. www.cic.unb.br/~lamar/te073/Aulas/mfcc.pdf. References “Neural Networks Used for Speech Recognition.” Journal of Automatic Control 20, no. 1 (2010): 1–7. Ji, You, and Shiliang Sun. “Multitask Multiclass Support Vector Machines.” In Proceedings of the 11th International Conference on Data Mining Workshops), Vancouver, BC, December 11, 2011, 512–518. Piscataway, NJ: Institute of Electrical and Electronic Engineering, 2011. Klautau, Aldebaro. “The MFCC,” 2012. www.cic.unb.br/~lamar/te073/Aulas/mfcc.pdf. 164 Chapter 8 ■ Cortical Algorithms Hashmi, Artif G., and Mikko. H. Lipasti. “Discovering Cortical Algorithms”. In Proceedings of the International Conference on Fuzzy Computation and International Conference on Neural Computation, Valencia, Spain, October 24–26, 2010, 196–204. Hashmi, Artif G., and Mikko. H. Lipasti. “Discovering Cortical Algorithms”. In Proceedings of the International Conference on Fuzzy Computation and International Conference on Neural Computation, Valencia, Spain, October 24–26, 2010, 196–204. Manie, Mohammed A. Al-, Mohammed I. Alkanhal, and Mansour M. Al-Ghamdi. “Automatic Speech Segmentation Using the Arabic Phonetic Database.” In Proceedings of the 10th WSEAS International Manie, Mohammed A. Al-, Mohammed I. Alkanhal, and Mansour M. Al-Ghamdi. “Automatic Speech Segmentation Using the Arabic Phonetic Database.” In Proceedings of the 10th WSEAS International Conference on Automation and Information, Prague, Czech Republic, March 23–25, 76–79. Stevens Point, Wisconsin: World Scientific and Engineering Academy and Society, 2009. Segmentation Using the Arabic Phonetic Database. In Proceedings of the 10th WSEAS International Conference on Automation and Information, Prague, Czech Republic, March 23–25, 76–79. Stevens Point, Wisconsin: World Scientific and Engineering Academy and Society, 2009. Mohler, Cleve. “Exponential Function.” Chap. 8 in Experiments with MATLAB. MathWorks, 2011. www.mathworks.com/moler/exm/chapters/exponential.pdf. Mosa, Ghassaq S., and Abduladhem Abdulkareem Ali. “Arabic Phoneme Recognition Using Hierarchical Neural Fuzzy Petri Net and LPC Feature Extraction.” Signal Processing: An International Journal 3, no. 5 (2009): 161–171. Mutch, Jim, Ulf Knoblich, and Tomaso Poggio. “CNS: A GPU-Based Framework for Simulating Cortically-Organized Networks.” Technical Report, Massachusetts Institute of Technology, 2010. Newman, Daniel. “The Phonetics of Arabic.” Journal of the American Oriental Society 46 (1984): 1–6. Obaid, Manal El-, Amer Al-Nassiri, and Iman Abuel Maaly. “Arabic Phoneme Recognition Using Neural Networks.” In Proceedings of the 5th WSEAS International Conference on Signal Processing, Istanbul, Turkey, May 27–29, 2006, 99–104. Stevens Point, Wisconsin: World Scientific and Engineering Academy and Society, 2006. Perkins, Simon, and James Theiler. “Online Feature Selection Using Grafting.” In Proceedings of the Twentieth International Conference on Machine Learning, Washington, DC, August 21–24, 2003, 592–599. Menlo Park, CA: Association for the Advancement of Artificial Intelligence, 2003. Deep Learning Any fool can know. The point is to understand. Any fool can know. The point is to understand. —Albert Einstein Artificial neural networks (ANNs) have had a history riddled with highs and lows since their inception. At a nodal level, ANNs started with highly simplified neural models, such as McCulloch-Pitts neurons (McCulloch and Pitts 1943), and then evolved into Rosenblatt’s perceptrons (Rosenblatt 1957) and a variety of more complex and sophisticated computational units. From single- and multilayer networks, to self-recurrent Hopfield networks (Tank and Hopfield 1986), to self-organizing maps (also called Kohonen networks) (Kohonen 1982), adaptive resonance theory and time delay neural networks among other recommendations, ANNs have witnessed many structural iterations. These generations carried incremental enhancements that promised to address predecessors’ limitations and achieve higher levels of intelligence. Nonetheless, the compounded effect of these “intelligent” networks has not been able to capture the true human intelligence (Guerriere and Detsky 1991; Becker and Hinton 1992). Thus, Deep learning is on the rise in the machine learning community, because the traditional shallow learning architectures have proved unfit for the more challenging tasks of machine learning and strong artificial intelligence (AI). The surge in and wide availability of increased computing power (Misra and Saha 2010), coupled with the creation of efficient training algorithms and advances in neuroscience, have enabled the implementation, hitherto impossible, of deep learning principles. These developments have led to the formation of deep architecture algorithms that look in to cognitive neuroscience to suggest biologically inspired learning solutions. This chapter presents the concepts of spiking neural networks (SNNs) and hierarchical temporal memory (HTM), whose associated techniques are the least mature of the techniques covered in this book. References Satori, Hassan, Mostafa Harti, and Nouredine Chenfour. “Introduction to Arabic Speech Recognition Using CMU Sphinx System.” In Proceedings of the Information and Communication Technologies International Symposium, Fez, Morocco, April 3–5, 2007, edited by Mohammad Essaaidi, Mohammed El Mohajir, Badreddine El Mohajir, and Paolo Rosso, 139–142. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2007. Sehgal, M. S. B., Iqbal Gondal, and Laurence Dooley. “A Hybrid Neural Network Based Speech Recognition System for Pervasive Environments.” In Proceedings of the 8th International Multitopic Conference, Lahore, Pakistan, December 24–26, 2004, 309–314. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2004. Shenouda, Sinout D., Fayez W. Zaki, and A. M. R. Goneid. “Hybrid Fuzzy HMM System for Arabic Connectionist Speech Recognition.” In Proceedings of the Twenty-Third National Radio Science Conference, Monufia, Egypt, March 14–16, 1–8. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2006. Slate, David J. “Letter Recognition Data Set.” University of California, Irvine, Machine Learning Repository. Irvine: University of California, 1991. http://archive.ics.uci.edu/ml/datasets/Letter+Recognition. Tan, Peter J., and David L. Dowe. “MML Inference of Decision Graphs with Multi-Way Joins and Dynamic Attributes.” In AI 2003: Advances in Artificial Intelligence; Proceedings of the 16th Australian Conference on AI, Perth, Australia, December 3–5, 2003, edited by Tamás Domonkos Gedeon and Lance Chun Che Fung, 269–281. Berlin: Springer, 2003. Alpaydin, E., and Fevzi Alimoglu. ”Pen-Based Recognition of Handwritten Digits Data Set.” University of California, Irvine, Machine Learning Repository. Irvine: University of California, 1998. https://archive. ics.uci.edu/ml/datasets/Pen-Based+Recognition+of+Handwritten+Digits. Vision Group. “Image Segmentation Data Set.” University of California, Irvine, Machine Learning Repository. Irvine: University of California, 1990. https://archive.ics.uci.edu/ml/datasets/Image+Segmentation. Wittner, Ben S., and John S. Denker. “Strategies for Teaching Layered Networks Classification Tasks.” In Neural Information Processing Systems: Denver, CO, 1987, edited by Dana Z. Anderson, 850–859. Berlin: Springer, 1988. 165 Overview of Hierarchical Temporal Memory HTM aims at replicating the functional and structural properties of the neocortex. HTM incorporates a number of insights from Hawkins’s book On Intelligence (2007), which postulates that the key to intelligence is the ability to predict. Its framework was designed as a biomimetic model of the neocortex that seeks to replicate the brain’s structural and algorithmic properties, albeit in a simplified, functionally oriented manner. HTM is therefore organized hierarchically, as depicted generically in Figure 9-1. All levels of hierarchy and their subcomponents perform a common computational algorithm. 167 Chapter 9 ■ Deep Learning Figure 9-1. An HTM network’s hierarchical structure Figure 9-1. An HTM network’s hierarchical structure Deep architectures adopt the hierarchical structure of the human neocortex, given the evident existence of a common computational algorithm in the brain that is pervasive throughout the neocortical regions and that makes the brain deal with sensory information—visual, auditory, olfactory, and so on—in very similar ways. Different regions in the brain connect in a hierarchy, such that information flowing up coalesces, building higher and more complex abstractions and representations of the sensory stimuli at each successive level. The brain’s structure, specifically the neocortex, evolved to gain the ability to model the structure of the world it senses. At its simplest abstraction the brain can be viewed as a biological data processing black box that discovers external causes in an environment that imposes massive amounts of data on its inputs (senses). The causes of this continuous stream of information are by nature hierarchical, in both space and time. These causes serve as a collection of smaller building blocks that combine to form a larger picture of the world. For instance, speech can be broken down into sentences, sentences into word utterances, word utterances into phonemes, and so on. With digital imagery, pixels combine into edges, edges into contours, contours into shapes, and, finally, shapes into objects. Every sensed object in the world reveals a similar structure perceived at varying levels of granularity. It is this hierarchically organized world that the neocortex and therefore HTM, by imitation, aim at modeling. This modeling happens in HTM at every level. In HTM the lowest-level nodes of the network are fed sensory information. This information can be raw or preprocessed, depending on the task the network is performing. Overview of Hierarchical Temporal Memory The nodes learn the most basic features of the data stream by discerning repeatable patterns and the sequences in which these patterns occur and storing them either via local memory structures or via connectivity configurations. These basic patterns and sequences are then used as building blocks at higher levels to form more complex representations of sensory causes. As information travels up the hierarchy, the same learning mechanics are used as higher and higher abstractions of the input patterns are formed. Information can also flow down the hierarchy. This enables the network to act as a generative model, in which higher levels bias lower levels by communicating their internal states to fill in missing input data or resolve ambiguity, or both (Hawkins 2007). Hierarchical Temporal Memory Generations HTM has seen so far two generations during its evolution. The underlying implementation in the first generation of computational algorithms, called Zeta 1, is strongly rooted in the Bayesian belief propagation (BBP) and borrows many of its computations and rules of convergence from that theory. In this earlier version, which is now sunset, HTM used a variation of BBP. BBP is used in Bayesian networks, whereby, under certain topological constraints, the network is ensured to reach an optimal state in the time it takes a 168 Chapter 9 ■ Deep Learning Chapter 9 ■ Deep Learning message to traverse the network along the maximum path length. Thus, BBP forces all nodes in a network to reach mutually consistent beliefs. The state of these nodes is encoded in probabilistic terms, and Bayesian theory is used to process and fuse information. HTM can be thought of as a Bayesian network with some additions to allow for handling time, self-training, and discovery of causes. message to traverse the network along the maximum path length. Thus, BBP forces all nodes in a network to reach mutually consistent beliefs. The state of these nodes is encoded in probabilistic terms, and Bayesian theory is used to process and fuse information. HTM can be thought of as a Bayesian network with some additions to allow for handling time, self-training, and discovery of causes. The second-generation algorithms were created to make the framework more biologically feasible. Functionally, many of the concepts of invariant representation and spatial and temporal pooling were carried over by reference to principles of sparse distributed representation (SDRs) and structural change. Nodes were replaced with closer analogues of cortical columns with biologically realistic neuron models, and connectivity was altered to allow strong lateral inhibition (Edelman and Mountcastle 1978). Cortical columns are a collection of cells characterized by common feedforward connections and strong inhibitory interconnections (Edelman and Mountcastle, 1978). Second-generation algorithms—initially referred to as fixed-density distributed representations (FDRs) and now simply called HTM cortical learning algorithms (CLAs)—replace Zeta 1. In lieu of the “barrel” hierarchy, with its clean-cut receptive fields, each level in the updated framework is a continuous region of cells stacked into columns that act as a simplified model of Edelman and Mountcastle’s (1978) cortical columns. Figure 9-2 depicts the structure of HTM, with cells organized into columns, columns into levels, and levels into a hierarchy of cortical regions. Figure 9-2. Hierarchical Temporal Memory Generations HTM structure Whereas Zeta 1 was strongly rooted in Bayesian theory—specifically, in belief propagation—CLA is founded on the principles of SDR. To understand the underlying implementation of CLA, a discussion of SDR and how it is fundamental to HTM theory is necessary. The architecture suggested for the first-generation HTM model was strongly influenced by the Bayesian rules it implemented. It benefited from the structural characteristics of the neocortex, namely, its hierarchical organization; however, nodes diverged from their biological counterparts. In short, functional modeling was the emphasis. In CLA, HTM abandons these roots and adheres more strictly to neocortical structural guidelines. The result is a neuron model, known in this context as an HTM cell. Figure 9-3 depicts the model put forward by Hawkins, Ahmad, and Dubinsky (2011). These cells are more realistic and biologically faithful than those used in traditional ANNs. Figure 9-2. HTM structure Figure 9-2. HTM structure Whereas Zeta 1 was strongly rooted in Bayesian theory—specifically, in belief propagation—CLA is founded on the principles of SDR. To understand the underlying implementation of CLA, a discussion of SDR and how it is fundamental to HTM theory is necessary. Whereas Zeta 1 was strongly rooted in Bayesian theory—specifically, in belief propagation—CLA is founded on the principles of SDR. To understand the underlying implementation of CLA, a discussion of SDR and how it is fundamental to HTM theory is necessary. h h d f h f d l l fl d b h The architecture suggested for the first-generation HTM model was strongly influenced by the Bayesian rules it implemented. It benefited from the structural characteristics of the neocortex, namely, its hierarchical organization; however, nodes diverged from their biological counterparts. In short, functional modeling was the emphasis. In CLA, HTM abandons these roots and adheres more strictly to neocortical structural guidelines. The result is a neuron model, known in this context as an HTM cell. Figure 9-3 depicts the model put forward by Hawkins, Ahmad, and Dubinsky (2011). These cells are more realistic and biologically faithful than those used in traditional ANNs. 169 Chapter 9 ■ Deep Learning Chapter 9 ■ Deep Learning Figure 9-3. An HTM cell/neuron model Figure 9-3. An HTM cell/neuron model HTM cells have two types of incoming connection structures: proximal dendrites and distal dendrites. Dendritic segments of both types are populated by synapses that connect them to other neighboring cells. Hierarchical Temporal Memory Generations These synaptic connections are binary, owing to the stochastic nature of real neurons. Because Hawkins, Ahmad, and Dubinsky (2011) posited that any algorithm that aims at emulating the brain cannot rely on the precision or fidelity of individual neurons, HTM cells were modeled to have binary, nonweighted synapses; meaning, they are either connected or not. To account for a real neuron’s ability to retract and extend to form connections, HTM cell synapses are assigned a parameter, called permanence. Permanence is a scalar value between 0 and 1 that is incremented or decremented, based on a synapse’s contribution to activity. When permanence is above a predefined threshold, a synapse becomes connected. Therefore, all synapses in CLA are potential synapses. They are dynamic elements of connectivity. Proximal dendrites are responsible for feedforward connectivity between regions. These dendrites are populated by a set of potential synapses that are associated with a subset of an input to an HTM region. The dendrites are shared by all the cells of a column (shared feedforward connectivity) and act as linear summation units. Distal dendrites are responsible for lateral connections across a single region. Several segments are associated with a distal dendrite. These segments act as a set of threshold coincidence detectors, meaning that, when enough connections are active at one time, they trigger a response in the receiving cell. It is enough for one segment to be active to trigger a response in the cell (OR gate). Each segment connects an HTM cell to a different subset of neighboring cells. The activity of those cells is monitored and allows the receiving cell to enter a predictive state. This is essentially the root of prediction in an HTM network: every cell continuously monitors the activity of surrounding cells to predict its own. Finally, an HTM cell has two binary outputs. The first output, owing to proximal connections, forces the cell into an active state if enough activation is present. The second output, owing to distal connections, forces the cell into a predictive state if enough neighbor activity is present; the cell expects to be activated soon. This enables HTM to act in a predictive manner and react to sequences of input. Finally, the output of the HTM cell is the OR of these two outputs. This is what regions higher up in the hierarchy receive as input. Sparse Distributed Representation CLA borrows many of its principles of operation for its biological analogue. The neocortex is made up of more than 1011 highly interconnected neurons. Yet, it is still capable of reacting to stimuli with relatively sparse activation levels. This is made possible by the vast amount of inhibitory connections. Inhibition guarantees that only a small number of neurons are activated at any one time. Furthermore, CLA implements the same encoding strategy as SDR. Using lateral synaptic connections, strongly stimulated neural columns inhibit nearby activity, thus reducing the number of active columns and yielding a sparse internal representation of the input pattern or stimuli. This internal representation is also distributed, that is, spread out across a region. Because active bits are sparse, knowledge of a subset of them still carries information about the input pattern, in contrast to other representations, such as ASCII code. With ASCII code an individual bit is meaningless; SDR, therefore, injects a representational quality into individual activations. Because only a tiny fraction of possibly a large number of neurons are active, whatever semantic meaning a single neuron gains becomes specific to a limited number of similar patterns. Consequently, even a subset of the active neurons of a pattern can be a good indicator of it. The theoretical loss of information that results from enforcing this kind of sparseness does not have a practical effect (Hawkins, Ahmad, and Dubinsky 2011). Hierarchical Temporal Memory Generations Figure 9-4 shows an example of activation of cells in a set of HTM columns: at any point, some cells will be active, as a result of feedforward input (dark gray), whereas other cells, receiving lateral input from active cells, will be in a predictive state (light gray). 170 Chapter 9 ■ Deep Learning Chapter 9 ■ Deep Learning Figure 9-4. HTM columns Figure 9-4. HTM columns Figure 9-4. HTM columns Algorithmic Implementation Contrary to the first generation, separation of the learning phase from the inference phase does not offer much insight into the rules of operation of HTM. In CLA, learning, inference, and—most important— prediction occur harmoniously. Each level of the hierarchy is always predicting. Learning by the lower nodes can be turned off when they stabilize; it occurs online in tandem with prediction, when activated. 171 Chapter 9 ■ Deep Learning Therefore, it is best to consider the operation of CLA in terms of its pooling functions. The following two sections discuss the theory behind spatial and temporal pooling in second-generation algorithms and show how they are implemented in the cortical network, as suggested by Hawkins, Ahmad, and Dubinsky (2011). Spatial Pooler The role of the spatial pooler is the same in CLA as in Zeta 1. Input patterns that are spatially similar should have a common internal representation. The representation should be not only robust to noise, but also sparse to abide by the principles of SDR. These goals are achieved by enforcing competition between cortical columns. When presented with input data, all columns in an HTM region will compute their feedforward activation. Columns that become active are allowed to inhibit neighboring columns. In this way, only a small set of strongly active columns can represent a cluster of similar inputs. To give other columns a fair chance at activation and ensure that all columns are used, a boosting factor is added. This enables weak columns to better compete. For each of the active columns, permanence values of all the potential synapses are adjusted, based on Hebbian learning rules. The permanence values of synapses aligned with active input bits are increased, whereas permanence values of synapses aligned with inactive input bits are decreased. Figure 9-5 shows a flow chart of the phases involved. Figure 9-5. Spatial pooler flowchart Figure 9-5. Spatial pooler flowchart Figure 9-5. Spatial pooler flowchart 172 Chapter 9 ■ Deep Learning The spatial pooling operations are as follows: The spatial pooling operations are as follows: • Phase 0 (corresponding to initialization): Each column is randomly assigned a random set of inputs (50 percent of the input vector), which is referred to as the potential pool of the column. Each input within this pool is represented by a potential synapse and assigned a random permanence value. The choice of permanence value is decided according to the following criteria: Values are chosen from within a small range around the permanence threshold. • This enables potential synapses to become connected (or disconnected) after a small number of training iterations. Each column has a natural center over the input region, and the permanence • values have a bias toward this center, with higher values near the center. • Phase 1 (corresponding to overlap): The overlap for each column is computed as the number of connected synapses with active inputs multiplied by its boost. If this value is below a predefined threshold (“minOverlap”), the overlap score is set to 0. Spatial Pooler • Phase 2 (corresponding to inhibition): The number of winning columns in a local area of inhibition (neighborhood of a column) is set to a predefined value, N. A column is a winner if its overlap score is greater than the score of the Nth highest column within its inhibition radius. A variation of this inhibition strategy that is significantly less computationally demanding is picking the columns with the highest overlap scores for every level of the hierarchy. • Phase 3 (corresponding to learning): During this phase, updates to the permanence values of all synapses are performed as necessary as well as to the parameters, such as boost and inhibition radius. For winning columns, if a synapse is active, its permanence value is incremented; if inactive, it is decremented. There are two separate boosting mechanisms in place to help a column learn connections. If a column does not win often enough, its overall boost value is increased; alternatively, if a column’s connected synapses do not overlap well with any inputs often enough, its permanence values are boosted. This phase terminates with updating the inhibition. Temporal Pooler With winning columns calculated by the spatial pooler, the HTM network gains insight into what pattern it may be seeing at its input. What it lacks is context. Any one pattern can occur as part of a large number of sequences, that is, in multiple contexts. Essential to HTM theory is the ability to predict through the learning of sequences. In CLA sequential learning happened using multiple cells per column. All the cells in a column share feedforward activation, but only a subset (usually a single cell) is allowed to be active. This means that the same pattern, represented by the same set of columns, can be represented by different cells in each column, depending on the context in which the pattern occurs. On a cellular level each of a cell’s dendritic distal segments has a set of connections to other cells in the same region, which is used to recognize the state of the network at some point in time. Cells can predict when they will become active by looking at their connections. A particular cell may be part of dozens or hundreds of temporal transitions. Therefore, every cell has several dendrite segments, not just one. There are three phases involved with temporal pooling. In the first phase each cell’s active state is computed. Phase 2 computes each cell’s predictive state. In Phase 3, synapses are updated by either incrementing or decrementing their permanence values. Following is the general case, in which both inference and learning are taking place, with the caveat that the learning phase in CLA can be switched off. 173 Chapter 9 ■ Deep Learning • Phase 1: For every winning column the active state of each of its cells is computed here. Also, a cell is designated a learning cell. If any of the cells is in a predictive state, owing to its lateral connections, it is put in an active state. If a learning cell contributed to its lateral activation, the cell is chosen as a learning cell, too. In contrast, if no cell in the column is in a predictive state, all the cells are turned active to indicate that the context is not clear—a process called bursting. Additionally, the best matching cell becomes the learning cell, and a new distal segment is added to that cell. Temporal Pooler Phase 2: Once all the cells in the winning columns are updated, their states can be used for prediction in the cells of other columns. Every cell in the region computes its lateral/distal connection. If any of a cell’s segments are activated, owing to feedforward activation in other cells, the cell is put in a predictive state. The cell then queues up the following changes: Reinforcement of the currently active segment by incrementing the permanence • values for active synapses and decrementing the values for synapses that are inactive Reinforcement of a segment that could have predicted this activation, that is, a • segment that has a (potentially weak) match to activity in the previous time step • Phase 3: This is the phase in which learning occurs, by deciding which of the queued-up updates are to be committed. Temporary segment updates are implemented once you have feedforward input and a cell is chosen as a learning cell. Thus, you update the permanence of synapses only if they correctly predicted the feedforward activation of the cell; otherwise, if the cell stops predicting for any reason, the segments are negatively reinforced. Related Work Zhituo, Ruan, and Wang (2012) used multiple HTMs in a content-based image retrieval (CBIR) system, which leverages the categorical semantics of a query image, rather than low-level image features, for image indexing and retrieval. Using ten individual HTM networks with some training and testing datasets of size 50 each, recall rates greater than 95 percent were achieved for four of the five categories involved and greater than 70 percent for the fifth category. Bobier (2007) recreated a handwritten digit recognition experiment on the United States Postal Service database reported by Numenta (Hawkins’s company) to have achieved a 95 percent accuracy rate. The digit images were binarized and fed to the network at varying parameters to reach a maximum rate of 96.26 percent—which, the authors noted, was not up to par, compared with other classifiers, such as support vector machine (SVM), which delivered higher rates in a fraction of the computational time. Kostavelis, Nalpantidis, and Gasteratos (2012) presented a biologically inspired object recognition system. Saliency maps were used to emulate visual fixation and reveal only the relevant parts of the image, thus reducing the amount of redundant information presented to the classifier. The authors chose to substitute the temporal pooler with a correlation-based alternative, using the ETH-80 and supervised learning at the top node. The system outperformed other HTM-based implementations with both SVM and k-NN as top-level supervisors. Sinkevicius, Simutis and Raudonis (2011) explored using HTM for human traffic analysis in public spaces. Two HTM networks were designed: one for human detection, the other for direction of movement detection. An experiment involving use of an overhead camera, mounted on a doorway, was performed, and detection performance was evaluated, using multiple scenarios of varying difficulties. The average accuracy achieved was 80.94 percent for pedestrian detection and 73.44 percent for directional detection. 174 Chapter 9 ■ Deep Learning Boone et al. (2010) used HTM as an alternative to traditional computer vision techniques for diabetic retinopathy. HTM primarily detected the optic nerve on retina images. The images were segmented into fragments the size of an optic nerve and presented with labels (0 or 1) to HTM. Following supervised training the HTM network was able to correctly classify 77.44 percent of the optic nerves presented, leading the authors to conclude that HTM is not competitive with traditional techniques, despite its promise. Zhuo et al. Related Work (2012) supplemented state-of-the-art image classification techniques with locality- constrained linear coding (LLC), spatial pyramid matching (SPM), and HTM for feature pooling. Image descriptors were extracted and encoded using LLC. The LLC codes were then fed to HTM and multiscale SPM to form an image vector. The system was evaluated using a Caltech 101 dataset and UIUC-Sport dataset, with linear SVM as the classifier. Results showed an increase in accuracy for both datasets (73.5 percent versus 71.2 percent and 86.7 percent versus 84.2, respectively), compared with the original LLC model. Gabrielsson, Konig, and Johansson (2012) aimed at leveraging HTM to create a profitable software agent for trading financial markets. A supervised training scheme was used for HTM, with intraday tick data for the E-mini Standard and Poor’s 500 futures markets. The tuned model was used as a predictor of market trends and showed at least comparable results when evaluated against ANNs. Note ■ ■ Most of the work making use of HTM has been carried out by the developer community established by Numenta. Annual “hackathons” have produced multiple demos, in which CLA was employed for traffic prediction, human movement prediction, tic-tac-toe simulation, infrared (IR) sensor prediction, and so on. One of the more impressive demos, on music analysis and prediction, shows the use of MIDI note sequencing for training; a melody was learned after 25 epochs (http://numenta.org/blog/2013/06/25/hackathon-outcome. html#jin-danny-stan). Currently, research is being undertaken on a CLA model for use in natural language processing (NLP). An example is available on the GitHub web site (https://github.com/chetan51/linguist). However, more research and validation are needed to compare HTM performance with the state-of-the-art machine learning approaches the model claims to be superior or similar to. With HTM reported performances, the community has yet to see where HTM has the upper hand. I(t) is the input current caused by the presynaptic potentials I(t) is the input current caused by the presynaptic potentials gNa, gK, gL are the conductance parameters for the sodium and potassium ion channels and the leak per unit area, respectively ENa, EK, EL are the equilibrium potentials ENa, EK, EL are the equilibrium potentials m, n, h are dimentionless variables that are governed by three other differential equations Because of the complexity of these equations, caused by the nonlinearity and four-dimensionality of the data, several simpler forms were proposed for practical implementation. We discuss some of these proposals in the following sections. Overview of Spiking Neural Networks SNNs are biologically inspired networks and belong to the third generation of ANNs. It seems for ANNs that any improvement on the performance should be based on the neuron model. The neuron model in the second generation of ANNs is based on a simplified model of the actual neuron which ignores the actual way of encoding the information between neurons and the type of this information. SNNs are similar to the ANNs architecture which consists of one or more layers of connected neurons, but differ in the neuron’s model and the type of the activation function. In contrast with the second generation of ANNs which utilize time-missing continuous activation functions, SNNs rely on the spike timing in their learning and activation phases. SNNs strive to mimic human neurons, in using spikes to transmit and learn the spatio- and spectrotemporal data (SSTD) that are encoded with the location of the synapses, for the spatial data, and with the spiking-time activities, for the temporal data. SNNs and their variants have been used in many applications, such as character recognition (Gupta and Long 2007), sign language recognition (Schliebs, Hamed, and Kasabov 2011), visual and auditory pattern recognition (Wysoski, Benuskova, and Kasabov 2006, 2007), image clustering (Meftah et al. 2008), car crash identification (Kasabov et al. 2013), human behavior recognition (Meng, Jin, and Yin 2011), breast cancer classification (O’Halloran et al. 2011), human localization in sensor networks (Obo et al. 2011), intrusion detection (Budjade 2014; Demertzis and Illiadis 2014), electroencephalography (EEG) spatio-/spectrotemporal 175 Chapter 9 ■ Deep Learning pattern recognition (Kasabov et al. 2013), and taste recognition (Soltic and Kasabov 2010). Generally, SNNs are not as popular as other methods of machine learning, owing to their high computational cost. pattern recognition (Kasabov et al. 2013), and taste recognition (Soltic and Kasabov 2010). Generally, SNNs are not as popular as other methods of machine learning, owing to their high computational cost. To understand how SNNs differ from ANNs, it is necessary to examine the most common models of human neurons: the Hodgkin-Huxley model, the integrate-and-fire model, the leaky integrate-and-fire model, the Izhikevich model, and Thorpe’s model. These models are covered in the following sections. Hodgkin-Huxley Model The Hodgkin-Huxley model formulates the propagation of action potential in neurons and may be considered the basis of the other models. Hodgkin and Huxley modeled the electrochemical information of natural neurons after the giant axon of the squid. The model consists of four differential equations describing the change in electrical charge on the part of the neuron’s membrane capacitance as functions of voltage (Vm) and current (I(t)), C du dt g m h u E g n u E g u E I t Na Na K K L L = - - ( )- - ( )- - ( )+ 3 4 ( ) t t t n m h dn dt n n u dm dt m m u dh dt h h u = - - ( ) éë ùû = - - ( ) éë ùû = - - ( ) éë ù 0 0 0 , , û, where Integrate-and-Fire Model The integrate-and-fire model is derived from the Hodgkin-Huxley model but neglects the shape of the potential actions. This model assumes that all potential actions are uniform but differ in the time of occurrence. As a result for the previous simplification, all the spikes have the same characteristics such as shape, width, and amplitude. The membrane capacitance and postsynaptic potential (PSP) are given by the equations C du dt R u t u I rest = - - ( )+ 1 ( ) ( )t u t with u t f f ( ) ( ) , ( ) = ( ) > J ‘ 0 C du dt R u t u I rest = - - ( )+ 1 ( ) ( )t where urest is the membrane potential of the neuron at the initial state J is the threshold value at which the neuron fires t( f ) is the spike firing time t( f ) is the spike firing time I(t) is the input current, caused by the presynaptic potentials 176 Chapter 9 ■ Deep Learning Chapter 9 ■ Deep Learning where where tm is the time constant of the neuron membrane urest is the membrane potential of the neuron at the initial state I(t) is the input current, caused by the presynaptic potentials R is the equivalent resistance of the neuron model. R is the equivalent resistance of the neuron model. Leaky Integrate-and-Fire Model The leaky integrate-and-fire model differs from the integrate-and-fire model, in that the membrane potential of the neuron decays over time if no potentials reach the neuron. When the membrane potential u(t) of the neuron reaches a specific threshold J at time t, called the spiking time t( f ), and the u(t) satisfies the u`(t( f )) > 0 condition, the neuron emits a spike immediately. Then, the neuron goes under an absolute refractory period uabs which means that the neuron will neglect any effect of the arriving spikes during this period. The refractory period lasts for a specific time dabs; the membrane potential of the neuron during this period is u(t) = –uabs, where uabs is the refractoriness potential. where uabs is the refractoriness potential. When dabs expires, the membrane potential returns to the urest value. The membrane potential is given by: tm du dt u u t RI t = - ( )+ rest ( ), Izhikevich Model The Izhikevich model is a tradeoff between biological plausibility and computational efficiency. This model uses the following two differential equations to represent the activities of the membrane potential: du dt u t u t w t I t = ( ) + ( )+ - ( )+ 0 04 5 140 2 . ( ) du dt u t u t w t I t = ( ) + ( )+ - ( )+ 0 04 5 140 2 . ( ) dw dt a bu t w t = ( )- ( ) ( ). dw dt a bu t w t = ( )- ( ) ( ). dw dt a bu t w t = ( )- ( ) ( ). The after-spiking action is described by the term below where membrane potential and recovery variable are reset if u ³ J, then u ¬ c, and w ¬ w + d. Here, u represents the membrane potential, and w represents a membrane recovery variable that provides –ve feedback to u. a, b, c, and d are the dimensionless parameters. Due to the simplicity of this model, large number of neurons can be simulated of a compute machine. 177 Chapter 9 ■ Deep Learning The weights in this model are updated according to D = w mod ji orderj . Thorpe’s model makes stronger connections with the connected neurons that fire and reach the current neuron early. Spiking occurs whenever PSPi reaches a threshold value PSPqi. After the spiking, PSPi is immediately set to 0, such that: PSP PSP P when PSP PSP wh i i ji i i = + < q 0 en PSP PSP i i . ³ ì í î q This method allows a fast and real-time simulation of large networks. Thorpe’s Model Thorpe’s model is a variation of the integrate-and-fire model that takes into consideration the order of the spikes as they reach the neuron. Thorpe’s model is suitable for many applications, because it uses the simple mathematical representation: PSP w mod i ji orderj =å * , Information Coding in SNN Information coding in neurons has long been the subject of lively debate, in terms of whether the information in the neuron is coded as rate coding or spike coding. Recent studies have shown that the information is encoded as spike coding, because rate coding is insufficient as a representation of the ability of neurons to process information rapidly. Rank coding is very efficient and can achieve the highest information coding capacity. Rank coding starts by converting the input values into a sequence of spikes, using the Gaussian receptive fields. The Gaussian receptive fields consist of m receptive fields that are used to represent the input values n as spikes. Assuming that n takes values from the range [ , ] I I min n max n , the Gaussian receptive field for the neuron i is given by its center ui, u I i I I M i min n max n min n = + - - - 2 3 2 2 * , and the width s, s b = - - 1 2 * I I M max n min n , u I i I I M i min n max n min n = + - - - 2 3 2 2 * , s b = - - 1 2 * I I M max n min n , u I i I I M i min n max n min n = + - - - 2 3 2 2 * , u I i I I M i min n max n min n = + - - - 2 3 2 2 * , wji is the weight or efficiency of synapsis between neuron j and neuron i wji is the weight or efficiency of synapsis between neuron j and neuron i wji is the weight or efficiency of synapsis between neuron j and neuron i mod is a modulation factor Î[0,1] orderj is the firing order of the presynaptic neuron j, where j Î[1, n–1], and n is the number of presynaptic neurons connected to neuron i orderj is the firing order of the presynaptic neuron j, where j Î[1, n–1], and n is the number of presynaptic neurons connected to neuron i The weights in this model are updated according to The weights in this model are updated according to and the width s, and the width s, where b is a parameter that controls the width of the receptive field with 1 £ b £ 2. where b is a parameter that controls the width of the receptive field with 1 £ b £ 2. Unlike the common learning methods, which depend on the rate of spiking, SNNs use a variant of Hebb’s rule to emphasize the effect of the spikes’ timing. The weight-updating mechanism is based on the interval between the firing time of the presynaptic and postsynaptic neurons. Two types of neurons are involved in the weights updating process; the neurons before the synapses of the current neuron (the presynaptic neurons) 178 Chapter 9 ■ Deep Learning and the neuron after the synapses (the postsynaptic neuron). If the postsynaptic neuron fires right after the postsynaptic neuron, then the connection between these two neurons is strengthened, such that the neuron’s weight is given by: and the neuron after the synapses (the postsynaptic neuron). If the postsynaptic neuron fires right after the postsynaptic neuron, then the connection between these two neurons is strengthened, such that the neuron’s weight is given by: if Dt ³ 0, then wnew ¬ wold + Dw, where new old Dt is the difference in firing time and it is equal totpost – tpre. Dt is the difference in firing time and it is equal totpost – tpre. If the presynaptic neuron fires right after postsynaptic neuron, then the connection between these two neurons is weakened, such that if t then w w w new old D < ¬ - D 0, . if t then w w w new old D < ¬ - D 0, . When the firing time of the postsynaptic neuron does not occur immediately after the firing time of the presynaptic neuron, the weights are not updated. The preceding discussion addresses the excitatory connection. The inhibitory connection uses a simple process, as it does not take into account the interval between the firing time of the presynaptic and postsynaptic neurons. Where t is the membrane constant. SNN Variants and Extensions Variants and extensions of SNNs are reviewed in the following sections. Variants and extensions of SNNs are reviewed in the following sections. Learning in SNN • Convergence is compromised owing to the insufficient spike response function. • Learning in SNN 179 Chapter 9 ■ Deep Learning Weights updating from the output layer to the hidden layer is given by D = - = = w y ij k i k t t t t j i i j j h.d . \| ,   where d j j t t j j x x E t t x j j j j = ¶ ¶ ¶ ¶ = =   . = - ¶ ¶ = = = Î å å T t w t y j j ij l i l t t t t l m i i i j j j    ( ) , 1 G D = - = = w y ij k i k t t t t j i i j j h.d . \| ,   where d j j t t j j x x E t t x j j j j = ¶ ¶ ¶ ¶ = =   . = - ¶ ¶ = = = Î å å T t w t y j j ij l i l t t t t l m i i i j j j    ( ) , 1 G Weights updating from the hidden layers to the input layer is given by D = - = = w y hi k i h k t t t t i i h h h. . \| , d   Where di i t t i i x x E t t x i i i i = ¶ ¶ ¶ ¶ = =   . = ¶ ¶ ¶ ¶ = = = Î = å å d j ij l i l t t t t l m j hi l h l t t t w t y w t y i i j j i i i ( ) ( ) , ,    1 G h h i t l m h = = Î å å  1 G The weaknesses of the SpikeProp algorithm include the following: The weaknesses of the SpikeProp algorithm include the following: The membrane potential of neurons is calculated at fixed time-step intervals. • There is no method for selecting the initial weights and the thresholds. • A reference neuron that spikes at t=0 is required. Learning in SNN The most popular algorithms developed for SNN are the SpikeProp and the Theta learning rule. SpikeProp is similar to the backpropagation algorithm that was designed to adjust the weights in the second generation of the neural networks. The Theta learning rule uses the quadratic integrate and fire (QIF) neuron model. Both of these algorithms are very sensitive to the parameters of the neuron model, and sometimes these algorithms suffer spike-loss problems. Spike loss occurs when the neuron does not fire for any patterns and hence cannot be recovered by the gradient method. Another approach for training SNNs is using evolutionary strategies that do not suffer from the tuning sensitivity, but these are computationally intensive and costly. Assume H, I and J are the input layer, the hidden layer and the output layer respectively. Each neuron from a specific layer is represented by the lower cases i, h and j. The set of neurons that are preceding the neuron i are denoted by Gi while the neurons that are succeeding the neuron i are denoted by Gi. Each connection between two neurons in the consecutive layers is consisted of m Î{1..m} subconnections where each has a constant incremental delay dk and a weight wij k with k Î{ .. } 1 m . ti, th and tj represent the spike time of the neuron in the respective layers, while t t i h , and t j represent the actual spike time in the respective layers. , j The response function of the neuron i is given by: y t t d i k i k t t i i = - - ( ) = e \|  with: with: e t t t t e t ( ) = - 1 x t w y t j i k m ij k i k t t j i i ( ) = Î = = åå ( ) \| G 1  e t t t t e t ( ) = - 1 x t w y t j i k m ij k i k t t j i i ( ) = Î = = åå ( ) \| G 1  Where t is the membrane constant. Reservoir-Based Evolving Spiking Neural Networks Reservoir computing (RC) is a framework of randomly and sparsely connected nodes (neurons) used to solve complex dynamic systems. RC is divided into echo state machine (ESM) (Jaeger 2007) and liquid state machine (LSM) (Maass, Natschläger, and Markram 2002; Maass 2010) types. g y The LSM is a real-time computation model that accepts continuous streams of data and that generates a high-dimensional continuous output stream. The LSM can be seen as a dynamic SVM kernel function. The architecture of the LSM consists of a liquid and a readout function. A liquid may be seen as a filter that has a trained architecture and that is used for general-purpose problem solving, such as recognizing different kinds of objects from the same video stream. In contrast, a readout function is specific purpose, such that different readout functions are used to recognize different objects from the same liquid. The readout function should be a linear-discriminant and memory-less function. Dynamic Synaptic Evolving Spiking Neural Networks Dynamic synaptic evolving spiking neural networks (deSNNs) are a class of eSNNs that use dynamic weight adjustments throughout the learning process (Kasabov et al. 2013). The dynamic updating of weights makes the model more efficient at capturing the complex patterns of a problem. In deSNN the weights continue to change slightly, according to the spikes arriving at the connection, as opposed to eSNN, in which the weights are updated once. Evolving Spiking Neural Networks Evolving spiking neural networks (eSNNs) are a variant class of SNNs that have a dynamic architecture (Schliebs and Kasabov 2013). eSNNs use Thorpe’s model and a population rank coding to encode information. eSNNs combine evolving connectionist system (ECoS) (Kasabov 2007) architecture and SNNs. Compared with SNNs, eSNNs have three advantages. First, eSNNs have a lower computational cost, as they are dependent on a light neuron model, namely, Thorpe’s model. Second, the learning algorithm in eSNN is more effective than those in SNNs, which are unable to converge 20 percent of the time (Thiruvarudchelvan, Crane, and Bossomaier 2013). Third, eSNNs are online learning models, which gives them a clear advantage over other techniques. 180 Chapter 9 ■ Deep Learning Conclusion This and the preceding two chapters have covered four learning algorithms that relate to deep learning: deep neural networks (DNNs), cortical algorithms (CAs), hierarchical temporal memory (HTM), and spiking neural networks (SNNs). DNN is an established technique developed from a traditional AI perspective and has shown robust results in many applications. CA, SNN, and HTM are biologically inspired techniques that are less mature but that are regarded by advocates of biologically inspired computing as highly promising. Traditional AI exponents, however, argue that DNN-related approaches will be the future winners in the learning area. Which vision will prevail is a hotly contested issue. But, instead of asking who is right and who is wrong, we might do better to frame the question in terms of the context and aim of the learning sought. Are we seeking to create a universal form of machine intelligence that replicates the capability of human intelligence to learn by inference from a few instances for a wide variety of applications? Or, are we after computationally efficient learning frameworks that can crush with brute force the big data collected from the Internet of Things (IOT) to develop models capable of predictive and descriptive tasks? As researchers have yet to agree on a unique definition of AI or on a golden metric for evaluating learning algorithms, the intention of the present work is to provide readers with a general background and a snapshot in time of this rapidly expanding subfield of deep learning. Dileep, George. “How the Brain Might Work: A Hierarchical and Temporal Model for Learning and Recognition.” PhD diss., Stanford University, 2008. Probabilistic Spiking Neural Networks The neural model of the probabilistic spiking neural network (pSNN) (see Figure 9-6) uses three types of probabilities (Kasabov 2010): Pcj,i(t), the probability that a spike emitted from neuron nj reaches neuron ni at a time moment t through the connection cj,i between nj and ni. Pcj,i(t), the probability that a spike emitted from neuron nj reaches neuron ni at a time moment t through the connection cj,i between nj and ni. Psj,i(t), the probability that synapse sj,i contributes to the PSPi(t) after receiving a spike from neuron nj . Pi(t), the probability that neuron ni emits a spike after its PSP reaches the emitting thresholds. pj (t ) pi (t ) pcji (t ) psj,i (t ), wji (t ) ni ni Figure 9-6. The pSNN model 181 Chapter 9 ■ Deep Learning The PSP of neuron ni is given by: The PSP of neuron ni is given by: PSP t e g P t p f P t p w i p t t j m j cj i sj i j i ( ) = - ( ) - ( ) ( ) = ¼ = å å 0 1 , , ,.., , , , ) ( ( ), t PSP t e g P t p f P t p w i p t t j m j cj i sj i j i ( ) = - ( ) - ( ) ( ) = ¼ = å å 0 1 , , ,.., , , , ) ( ( ), t where References Bobier, Bruce. “Handwritten Digit Recognition Using Hierarchical Temporal Memory,” 2007. Boone, Aidan R. W., T. P. Karnowski, E. Chaum, L. Giancardo, Y. Li, and K. W. Tobin Jr. “Image Processing and Hierarchical Temporal Memories for Automated Retina Analysis.” In Proceedings of the 2010 Biomedical Sciences and Engineering Conference. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2010. Budjade, Gaurav. “Intrusion Detection Using Spiking Neural Networks.” Master’s thesis, Rochester Institute of Technology, 2014. Demertzis, Konstantinos, and Lazaros Iliadis. “A Hybrid Network Anomaly and Intrusion Detection Approach Based on Evolving Spiking Neural Network Classification.” In E-Democracy, Security, Privacy and Trust in a Digital World: 5th International Conference, E-Democracy 2013, Athens, Greece, December 5–6, 2013, Revised Selected Papers, edited by Alexander B. Sideridis, Zoe Kardasiadou, Constantine P. Yialouris, and Vasilios Zorkadis, 11–23. Cham, Switzerland: Springer, 2014. Dileep, George. “How the Brain Might Work: A Hierarchical and Temporal Model for Learning and Recognition.” PhD diss., Stanford University, 2008. References Bobier, Bruce. “Handwritten Digit Recognition Using Hierarchical Temporal Memory,” 2007. Boone, Aidan R. W., T. P. Karnowski, E. Chaum, L. Giancardo, Y. Li, and K. W. Tobin Jr. “Image Processing and Hierarchical Temporal Memories for Automated Retina Analysis.” In Proceedings of the 2010 Biomedical Sciences and Engineering Conference. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2010. Budjade, Gaurav. “Intrusion Detection Using Spiking Neural Networks.” Master’s thesis, Rochester Institute of Technology, 2014. Budjade, Gaurav. “Intrusion Detection Using Spiking Neural Networks.” Master’s thesis, Rochester Institute of Technology, 2014. Demertzis, Konstantinos, and Lazaros Iliadis. “A Hybrid Network Anomaly and Intrusion Detection Approach Based on Evolving Spiking Neural Network Classification.” In E-Democracy, Security, Privacy and Trust in a Digital World: 5th International Conference, E-Democracy 2013, Athens, Greece, December 5–6, 2013, Revised Selected Papers, edited by Alexander B. Sideridis, Zoe Kardasiadou, Constantine P. Yialouris, and Vasilios Zorkadis, 11–23. Cham, Switzerland: Springer, 2014. Demertzis, Konstantinos, and Lazaros Iliadis. “A Hybrid Network Anomaly and Intrusion Detection Approach Based on Evolving Spiking Neural Network Classification.” In E-Democracy, Security, Privacy and Trust in a Digital World: 5th International Conference, E-Democracy 2013, Athens, Greece, December 5–6, 2013, Revised Selected Papers, edited by Alexander B. Sideridis, Zoe Kardasiadou, Constantine P. Yialouris, and Vasilios Zorkadis, 11–23. Cham, Switzerland: Springer, 2014. Dileep, George. “How the Brain Might Work: A Hierarchical and Temporal Model for Learning and Recognition.” PhD diss., Stanford University, 2008. 182 Chapter 9 ■ Deep Learning Dileep, George, and Jeff Hawkins. “Towards a Mathematical Theory of Cortical Micro-Circuits.” PLoS Computational Biology 5, no. 10 (2009). http://journals.plos.org/ploscompbiol/article?id=10.1371/ journal.pcbi.1000532. Edelman, Gerald M., and Vernon B. Mountcastle. The Mindful Brain: Cortical Organization and the Group- Selective Theory of Higher Brain Function. Cambridge, MA: Massachusetts Institute of Technology Press, 1978. Gabrielsson, Patrick, R. Konig, and Ulf Johansson. “Hierarchical Temporal Memory-Based Algorithmic Trading of Financial Markets.” In Proceedings of the 2012 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, 1–8. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2012. Guerriere, Michael R. J., and Allan S. Detsky. “Neural Networks: What Are They?” Annals of Internal Medicine 115, no. 11 (1991): 906–907. Gupta, Ankur, and Lyle N. Long, “Character Recognition Using Spiking Neural Networks.” In IJCNN 2007: Proceedings of the 2007 International Joint Conference on Neural Networks, 53–58. Piscataway, NJ: Institute of Electrical and Electronic Engineers. Hawkins, Jeff. On Intelligence. New York: Times Books, 2007. Hawkins, Jeff. On Intelligence. New York: Times Books, 2007. References Hawkins, Jeff, Subutai Ahmad, and D. Dubinsky. “Hierarchical Temporal Memory, Including HTM Cortical Learning Algorithms.” Technical report, Numenta, 2011. Jaeger, Herbert. “Echo State Network.” Scholarpedia 2, no. 9: (2007): 2330. Johnson, Stephen C. “Hierarchical Clustering Schemes.” Psychometrika 32, no. 3 (1967): 241–254. Kasabov, Nikola. Evolving Connectionist Systems. London: Springer, 2007. Kasabov, Nikola. “To Spike or Not to Spike: A Probabilistic Spiking Neuron Model.” Neural Networks 23, no. 1 (2010): 16–19. Kasabov, Nikola, Kshitij Dhoble, Nuttapod Nuntalid, and Giacomo Indiveri. “Dynamic Evolving Spiking Neural Networks for On-Line Spatio- and Spectro-Temporal Pattern Recognition.” Neural Networks 41 (2013): 188–201. Kohonen, Teuvo. “Self-Organized Formation of Topologically Correct Feature Maps.” Biological Cybernetics 43.1 (1982): 141–152. Kostavelis, Ioannis, Lazaros Nalpantidis, and Antonios Gasteratos. “Object Recognition Using Saliency Maps and HTM Learning.” In Proceedings of the 2012 IEEE International Conference on Imaging Systems and Techniques, 528–532. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2012. Maass, Wolfgang. “Liquid State Machines: Motivation, Theory, and Applications.” In Computability in Context: Computation and Logic in the Real World, edited by S. Barry Cooper and Andrea Sorbi, 275–296. London: Imperial College Press, 2011. Maass, Wolfgang, Thomas Natschläger, and Henry Markram. “Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations.” Neural Computation 14, no. 11 (2002): 2531–2560. McCulloch, W. S., and W. H. Pitts. A Logical Calculus of the Ideas Immanent in Nervous Activity. Bulletin of Mathematical Biophysics 5 (1943): 115–133. Meftah, B., A. Benyettou, O. Lezoray and W. QingXiang. “Image Clustering with Spiking Neuron Network.” In IJCNN 2008: Proceedings of the IEEE International Joint Conference on Neural Networks, 681–685. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2008. 183 Chapter 9 ■ Deep Learning Meng, Yan, Yaochu Jin, and Jun Yin. “Modeling Activity-Dependent Plasticity in BCM Spiking Neural Networks with Application to Human Behavior Recognition.” IEEE Transactions on Neural Networks 22, no. 12 (2011): 1952–1966. Misra, Janardan, and Indranil Saha, “Artificial Neural Networks in Hardware: A Survey of Two Decades of Progress.” Neurocomputing 74, nos. 1–3 (2010): 239–255. Obo, Takenori, Naoyuki Kubota, Kazuhiko Taniguchi, and Toshiyuki Sawayama. “Human Localization Based on Spiking Neural Network in Intelligent Sensor Networks.” In Proceedings of the 2011 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, 125–130. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2011. O’Halloran, Martin, Brian McGinley, Raquel C. Conceição, Fearghal Morgan, Edward Jones, and Martin Glavin. References “Spiking Neural Networks for Breast Cancer Classification in a Dielectrically Heterogeneous Breast.” Progress in Electromagnetics Research 113 (2011): 413–428. Rosenblatt, Frank. “The Perceptron: A Perceiving and Recognizing Automaton.” Project Para Report No. 85-460-1, Cornell Aeronautical Laboratory, 1957. Schliebs, Stefan, Haza Nuzly Abdull Hamed, and Nikola Kasabov. “Reservoir-Based Evolving Spiking Neural Network for Spatio-Temporal Pattern Recognition.” In Neural Information Processing (2011): 160–168. Schliebs, Stefan, and Nikola Kasabov. “Evolving Spiking Neural Network—a Survey.” Evolving Systems 4, no. 2 (2013): 87–98. Sinkevicius, S., R. Simutis, and V. Raudonis. “Monitoring of Humans Traffic Using Hierarchical Temporal Memory Algorithms.” Electronics and Electrical Engineering 115, no. 9 (2011): 91–96. Soltic, Snjezana, and Nikola Kasabov. “Knowledge Extraction from Evolving Spiking Neural Networks with Rank Order Population Coding.” International Journal of Neural Systems 20, no. 6 (2010): 437–445. Tank, D. W. and J. J. Hopfield. “Simple ‘Neural’ Optimization Networks: An A/D Converter, Signal Decision Circuit, and a Linear Programming Circuit.” IEEE Transactions on Circuits and Systems 33, no. 5 (1986): 533–541. Thiruvarudchelvan, Vaenthan, James W. Crane, and Terry R. Bossomaier. “Analysis of Spikeprop Convergence with Alternative Spike Response Functions.” In Proceedings of the 2013 IEEE Symposium on Foundations of Computational Intelligence, 98–105. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2013. Wysoski, Simei Gomes, Lubica Benuskova, and Nikola Kasabov. “On-Line Learning with Structural Adaptation in a Network of Spiking Neurons for Visual Pattern Recognition.” In Artificial Neural Networks– ICANN 2006: Proceedings of the 16th International Conference, Athens, Greece, September 10–14, 2006, edited by Stefanos D. Kollias, Andreas Stafylopatis, Włodzisław Duch, and Erkki Oja, 61–70. Berlin: Springer, 2006. Wysoski, Simei Gomes, Lubica Benuskova, and Nikola Kasabov. “Text-Independent Speaker Authentication with Spiking Neural Networks.” In Artificial Neural Networks–ICANN 2007: Proceedings of the 17th International Conference, Porto, Portugal, September 9–13, 2007, edited by Joaquim Marques de Sá, Luís A. Alexandre, Włodzisław Duch, and Danilo Mandic, 758–767. Berlin: Springer, 2007. Zhituo, Xia, Ruan Hao, and Wang Hao. “A Content-Based Image Retrieval System Using Multiple Hierarchical Temporal Memory Classifiers.” In Proceedings of the Fifth International Symposium on Computational Intelligence and Design, 438–441. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2012. Zhituo, Xia, Ruan Hao, and Wang Hao. “A Content-Based Image Retrieval System Using Multiple Hierarchical Temporal Memory Classifiers.” In Proceedings of the Fifth International Symposium on Computational Intelligence and Design, 438–441. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2012. Zhuo, Wen, Zhiguo Cao, Yueming Qin, Zhenghong Yu, and Yang Xiao. Zhuo, Wen, Zhiguo Cao, Yueming Qin, Zhenghong Yu, and Yang Xiao. “Image Classification Using HTM Cortical Learning Algorithms.” In Proceedings of the 21st International Conference on Pattern Recognition, 2452–2455. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2012. —Aristotle —Aristotle Multiobjective optimization caters to achieving multiple goals, subject to a set of constraints, with a likelihood that the objectives will conflict with each other. Multiobjective optimization can also be explained as a multicriteria decision-making process, in which multiple objective functions have to be optimized simultaneously. In many cases, optimal decisions may require tradeoffs between conflicting objectives. Traditional optimization schemes use a weight vector to specify the relative importance of each objective and then combine the objectives into a scalar cost function. This strategy reduces the complexity of solving a multiobjective problem by converting it into a single-objective problem. Solution techniques for multiobjective optimization involve a tradeoff between model complexity and accuracy. Examples of multiobjective optimization can be found in economics (setting monetary policy), finance (risk–return analysis), engineering (process control, design tradeoff analysis), and many other applications in which conflicting objectives must be obtained. One of the prerequisites of multiobjective optimization is to determine whether one solution is better than another. However, no simple method exists for reaching such a conclusion. Instead, multiobjective optimization methods commonly adopt a set of Pareto optimal solutions (also called nondominated solutions), which are alternatives with different tradeoffs between the various objectives. In the solution defined by a Pareto optimal set, one objective cannot be improved without degrading at least one other objective in the set. It is up to the decision maker to select the Pareto optimal solution that best fits preferred policy or guidelines. Pareto graphs illustrate the attributes of the tradeoff between distinct objectives. The solution can be represented in the shape of a curve, or a three-dimensional surface that trades off different zones in the multiobjective space. This chapter discusses machine learning methodologies for solving Pareto-based multiobjective optimization problems, using an evolutionary approach. The goal is to find a set of nondominated solutions with the minimum distance to the Pareto front in each generation. Successive solutions are built as part of the evolutionary process, in which one set of selected individual solutions gives rise to another set for the next generation. Solutions with higher fitness measures are more likely to be selected to the mating pool, on the assumption that they will produce a fitter solution in the next generation (next run), whereas solutions with weaker fitness measures are more likely to be discarded. Multiobjective Optimization All men seek one goal: success or happiness. The only way to achieve true success is to express yourself completely in service to society. First, have a definite, clear, practical ideal—a goal, an objective. Second, have the necessary means to achieve your ends: wisdom, money, materials, and methods. Third, adjust all your means to that end. References “Image Classification Using HTM Cortical Learning Algorithms.” In Proceedings of the 21st International Conference on Pattern Recognition, 2452–2455. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2012. Zhuo, Wen, Zhiguo Cao, Yueming Qin, Zhenghong Yu, and Yang Xiao. “Image Classification Using HTM Cortical Learning Algorithms.” In Proceedings of the 21st International Conference on Pattern Recognition, 2452–2455. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 2012. 184 Chapter 10 —Aristotle Such solutions possess several attributes that make them suitable for problems involving (1) a large and complex search space and (2) mutually conflicting objectives. 185 Chapter 10 ■ Multiobjective Optimization Formal Definition A multiobjective optimization problem deals with a finite number of objective functions. In an optimization problem with n objectives of equal importance, all need to be minimized (or maximized) to serve a performance criterion. Mathematically, the problem can be expressed as a vector of objectives fi(x) that must be traded off in some manner, F x f x f x f x f x x m ( ) min ( ), ( ), ( ), , ( ) , = Î éë ùû 1 2 3  X (10-1) (10-1) where X (see Equation 10-2) is a set of n decision vectors (a decision space) that represents parameters for the values selected to satisfy constraints and optimize a vector function, X =[ ] x x x xn T 1 2 3 , , , ,  (10-2) x x x i n i low i i high £ £ =1 2 3 , , , , .  (10-3) X =[ ] x x x xn T 1 2 3 , , , ,  x x x i n i low i i high £ £ =1 2 3 , , , , .  (10-3) x x x i n i low i i high £ £ =1 2 3 , , , , .  (10-3) x x x i n i low i i high £ £ =1 2 3 , , , , .  (10-3) The relative significance of these objectives cannot be determined until the tradeoffs between them are distinctly understood. Because F(x) is a vector, competing objective functions will prevent it from achieving a unique solution. You can associate each solution x in a decision space X with a point in objective space Y, such that f x y y y ym T ( ) , , , , . = =[ ] Y 1 2 3  (10-4) (10-4) In multiobjective optimization the sets X and Y are known as decision variable space and objective function space, respectively. Figure 10-1 illustrates the mapping of the search space to the objective space. Every iteration of search space leads to a set of objective vectors that defines the objective space, in which several optimal objective vectors may represent different tradeoffs between the objectives. 186 Chapter 10 ■ Multiobjective Optimization Figure 10-1. Formal Definition Multiobjective optimization problem: mapping the search space to the objective space Figure 10-1. Multiobjective optimization problem: mapping the search space to the objective space Pareto Optimality Pareto optimality is a concept built on multiobjective optimization that facilitates optimization of a vector of multiple goals through tradeoffs between combinations of multiple objectives. Tradeoffs are formulated to improve the performance of one objective at the cost of one or more other objectives. As displayed in Figure 10-1, each point in the objective space represents a unique set of model variables, such that Pareto optimality categorizes multiple Pareto optimal solutions. The term honors Vilfredo Pareto (1848–1923), an Italian economist who demonstrated that income follows a power law probability distribution. For an ideal case the optimal solution of a multiobjective problem is generally denoted as a Pareto set X X * Í . The corresponding outcome, or objective vector, is represented by a Pareto front Y X Y * * ( ) + Í f . In practice an ideal solution is nonexistent, and solving multiobjective optimization does not typically produce an optimally unique solution. Instead, we use Pareto optimal solutions, in which one objective cannot be improved without degrading at least one of the other objectives. Therefore, when using evolutionary techniques, knowledge of the optimal Pareto set (X, Y) assists in finding a best-compromise solution. Dominance Relationship A solution x1 dominates another solution ( ) x x x 1 2 2  if the following conditions A solution x1 dominates another solution ( ) x x x 1 2 2  if the following conditions are met: 1. For all objectives, solution x1 is better than or equal to x2, such that f x f x i m i i ( ) ( ) , , , , . 1 2 1 2 3 £ " Î  2. For at least one objective, solution x1 is strictly better than x2, such that f x f x j m j j ( ) ( ) , , , , . 1 2 1 2 3 < $ Î  187 Chapter 10 ■ Multiobjective Optimization If either of these conditions is violated, then x1 does not (Pareto) dominate the solution x2. The dominance relationship is nonsymmetrical. For example, if the solution x1 does not dominate the solution x x x 2 1 2 ( ), / that does not imply that x2 dominates x x x 1 2 1 ( );  therefore, both solutions can be nondominated. However, the dominance relationship is also transitive. For instance, if x x 1 2  and x x 2 3  , then x x 1 3  . This property allows us to identify which solutions are not dominated (Xˆ) by any member of the solution set X. These nondominated sets (Xˆ) of the entire feasible search space are called globally Pareto-optimal sets. Generating a Pareto set can be computationally expensive. Therefore, you need to select a computationally efficient method for determining the Pareto-optimal set of a multiobjective optimization algorithm. Although you may employ many different approaches to solve a multiobjective optimization problem, much work has been done in the area of evolutionary multiobjective optimization on the approximation of the Pareto set. Machine Learning: Evolutionary Algorithms Generating the Pareto set can be computationally expensive, because multiobjective optimization problems no longer have a single optimal solution, but a whole set of potential solutions. Classical optimizers (Marler and Arora 2004) include weighted-sum approaches, perturbation methods, Tchybeshev methods, goal programming, and min–max methods. Although these methods can be used for multicriteria optimization, you can only obtain a single solution for each simulation run; simulation needs to execute multiple times, with an expectation that one of the solutions may lead to the Pareto-optimal solution. Evolutionary algorithms (EAs) are well suited to solving multiobjective optimization problems, because they mimic natural processes that are inherently multiobjective; a number of Pareto-optimal solutions can be captured in a single simulation run. Additionally, EAs are less sensitive to the shape or continuity of the Pareto front. These algorithms have been successfully applied to a wide range of combination problems, in which information from multiple sources is brought together to achieve an optimal solution. Such algorithms are particularly useful in applications involving design and optimization, in which there are a large number of variables and in which procedural algorithms are either nonexistent or extremely complicated. Generally, evolutionary methods are population-based, metaheuristic optimization algorithms that mimic the principles of natural evolution. These methods use the initial population of a solution and update in each generation to converge to a single optimal solution. Although EAs do not guarantee a true optimal solution, they attempt to find a good approximation, representing a near-Pareto-optimal solution. EAs are typically classified into four major categories: (1) genetic algorithms (GAs), (2) genetic programming (GP), (3) evolutionary programming (EP), and (4) evolution strategy (ES). Although these algorithms employ different approaches, they all derive inspiration from the principle of natural selection. Fundamental processes involved in EAs are selection, mutation, and crossover. The first stage of an EA entails applying a fitness factor to evaluate the population in the objective space (which represents the quality of the solution). Next, a mating pool is created by selecting the population from previous step, using a random selection or likelihood-based selection criterion. Once the mating pool is organized, it is subjected to recombination and mutation, which produce a new population set. The recombination process performs an n-point crossover, with a configurable probability that allows fragments of one parent to combine with fragments of another parent to create an entirely new child population. Performance Measure To evaluate the performance of a solution, it is essential to develop a measurement scheme that quantifies the quality of the nondominant Pareto front. The general performance criteria for multiobjective optimization algorithms can be summarized as follows: 1. Convergence (g): Estimates the proximity of the candidate nondominated (Pareto) solutions to the best-known prediction or known set of Pareto optimal solutions. For each solution obtained using an algorithm, you can use the minimum Euclidian distance (Deb, Pratap, and Agarwal 2002) to the Pareto optimal front. The average distance can be used as the convergence measure. A smaller g value indicates a better convergence. 2. Diversity (D): Provides a decision maker with efficient choices. Because you are interested in the solution that covers the entire Pareto-optimal region, you need to evaluate the degree of spread between the solutions obtained. 3. Displacement (D): In the case of algorithmic approximations or the presence of a discontinuous Pareto-optimal front, only a portion of true optimal front may be reflected. Displacement is used to overcome this limitation. Displacement measures the relative proximity of the candidate solution set to a known set of Pareto-optimal solutions. Mathematically, displacement can be expressed as 3. Displacement (D): In the case of algorithmic approximations or the presence of a discontinuous Pareto-optimal front, only a portion of true optimal front may be reflected. Displacement is used to overcome this limitation. Displacement measures the relative proximity of the candidate solution set to a known set of Pareto-optimal solutions. Mathematically, displacement can be expressed as D P d i j J Q i P = × [ ] = =å 1 1 1 * min ( , ) , * (10-5) where, * = Uniformly spaced solutions from the true Pareto-optimized front P* = Uniformly spaced solutions from the true Pareto-optimized front Q = Final solution Q = Final solution d(I, j) = Euclidean distance between the ith solution of P* and jth solution of Q A lower displacement value represents better convergence and coverage. Each algorithm may select one or more performance criteria to test the quality of a solution. In many cases, the performance criteria may depend on the availability (or nonavailability) of a known collection of Pareto-optimal sets. The rest of this chapter looks at various multiobjective optimization solutions based on evolutionary learning methodologies. 188 Chapter 10 ■ Multiobjective Optimization Machine Learning: Evolutionary Algorithms Mating selection is a critical step in the EA process, inasmuch as it attempts to select promising solutions, on the assumption that future mating pools derived as a consequence of a high-quality selection tend to be superior. A mutation operator modifies individuals by making small changes to the associated vectors, according to a given mutation rate. Given the probabilistic nature of the mating and mutation processes, certain populations may not undergo any variation and simply replicate to the next generation. ( Analogous to natural evolution, individuals represent possible solutions, and a set of individuals (or possible solutions) is called a population. Each individual is encoded, using a problem-specific encoding scheme that can be decoded and evaluated by a fitness function. The mating process iterates through the process of modifying an existing population via recombination and mutation to evolve a new population. Each loop iteration is called a generation, which represents a timeline in the evolutionary process. Early work in the area of multiobjective EAs is credited to David Schaffer, who implemented the vector- evaluated GA (VEGA) (Schaffer 1985). Goldberg(1989) proposed calculating individual fitness according to Pareto dominance. Many variants of multiobjective EAs have since been suggested (of which this chapter considers some of the more popular). 189 Chapter 10 ■ Multiobjective Optimization Figure 10-2. Basic flow of a GA Figure 10-2. Basic flow of a GA Figure 10-2. Basic flow of a GA Genetic Algorithm GAs follow the principle of natural selection (see Figure 10-2), in which each solution is represented as a binary (or real) coded string (chromosomes) and an associated fitness measure. Successive solutions are built as part of the evolutionary process, in which one set of selected individual solutions gives rise to another set for the next generation. Individuals with a high fitness measure are more likely to be selected to the mating pool, on the assumption that they will produce a fitter solution in the next generation. Solutions with the weaker fitness measures are naturally discarded. Typically, you can use roulette-wheel selection to simulate natural selection, in which elimination of solutions with a higher functional fitness is, although possible, less likely. In this method each possible selection is assigned a portion of the wheel that is proportional to its fitness value, followed by a random selection, analogous to spinning a roulette wheel. A small likelihood also exists that some weaker solutions will survive the selection process, because they may include components (genes) that prove useful after the crossover process. Mathematically, the likelihood of selecting a potential solution is given by P F F i i j j N = =å 0 , (10 P F F i i j j N = =å 0 , (10-6) where Pi represents the likelihood of ith solution’s being selected for the mating pool, Fi stands for the operating fitness of ith individual solution, and N is the total number of solution elements in a population. GAs have proven useful in solving complex problems with large search spaces that are less understood by reason of little domain knowledge. The chromosomes of a GA represent the building blocks (alleles) of a solution to the problem that is suitable for the genetic operators and the fitness function. Candidate solutions undergo modification, using crossover and mutation functions, and result in new candidate solutions that undergo evaluation for candidacy in new mating pools. where Pi represents the likelihood of ith solution’s being selected for the mating pool, Fi stands for the operating fitness of ith individual solution, and N is the total number of solution elements in a population. GAs have proven useful in solving complex problems with large search spaces that are less understood by reason of little domain knowledge. Chapter 10 ■ Multiobjective Optimization Chapter 10 ■ Multiobjective Optimization Genetic Algorithm The chromosomes of a GA represent the building blocks (alleles) of a solution to the problem that is suitable for the genetic operators and the fitness function. Candidate solutions undergo modification, using crossover and mutation functions, and result in new candidate solutions that undergo evaluation for candidacy in new mating pools. 190 Multiobjective Optimization: An Evolutionary Approach In single-objective optimization, to evaluate the quality of the solution, you simply measure the value of the objective function. In the case of multiobjective optimization, it may not be possible to evaluate the quality of the solution relative to optimal Pareto approximations, because you may not possess the relevant information, with respect to objective space or coverage, and thus may not be able to define the quality of solution, in terms of closeness to the optimal Pareto set and diversity of coverage. Even if one solution dominates the other solution, you may still not be able to quantify the relative improvement, because relative distance and diversity alone are not sufficient to quantify the Pareto set approximation. This brings us to the fundamental requirements for defining the strategy for implementing multiobjective EAs. These requirements can be summarized as follows: • Fitness: Guiding the solution closer to the Pareto set. This requires constructing a scalar fitness function that fulfills multiple optimization criteria. • Diversity improvement: Improving coverage by selecting a diverse set of nondominated solutions. This avoids a situation in which identical solutions exist, relative to objective space and decision space. • Elitism: Preventing nondominated solutions from being eliminated. Most EAs differ in the manner in which they handle fitness, diversity, and elitism. Listed here are some of the most popular multiobjective EA (MOEA) approaches: Most EAs differ in the manner in which they handle fitness, diversity, and elitism. Listed here are some of the most popular multiobjective EA (MOEA) approaches: • Weighted-Sum approach • Vector-Evaluated GA (VEGA) (Schaffer 1985) • Multiobjective GA (MOGA) (Fonseca and Fleming 1993) • Niched Pareto GA (NPGA) (Horn, Nafpliotis, and Goldberg 1994) • Nondominated sorting GA (NSGA) (Nidamarthi and Deb 1994) • Strength Pareto EA (SPEA) (Zitzler and Thiele 1999) • Strength Pareto EA II (SPEA-II) (Zitzler, Laumanns, and Thiele 2001) • Pareto archived evolutionary strategy (PAES) (Knowles and Corne 1999) • Pareto envelope-based selection algorithm (PESA) (Corne, Knowles, and Oates 2000) • Pareto envelope-based selection algorithm II (PESA-II) (Corne et al. 2001) • Elitist nondominated sorting GA (NSGA-II) (Deb, Pratap, and Agarwal 2002) • Elitist nondominated sorting GA (NSGA-II) (Deb, Pratap, and Agarwal 2002) These approaches are presented in turn in the following sections. These approaches are presented in turn in the following sections. Genetic Programming GP is an evolutionary technique that expands the genetic learning paradigm into an autonomous synthesis of computer programs that, when executed, lead to candidate solutions. Unlike GAs, in which populations are fixed-length encoded character strings representing candidate solutions, in GP, populations are programs represented by syntax trees (also called parse trees). GP iteratively evolves the populations of programs, transforming one set of programs into another set by exercising the genetic operations crossover and mutation. Crossover function is implemented by exchanging subtrees at a random crossover point of two parent individuals (selected according to fitness criteria) in the population. Crossover creates an offspring by replacing the subtree at the crossover point of the first parent with the subtree of the second parent. In subtree mutation (the most commonly used form of mutation) the subtree of a randomly selected mutation point is replaced by the subtree of a randomly generated tree. Figure 10-3 demonstrates the general flow and crossover operation of a GP methodology using two variables x and y and prefix notation to express mathematical operators. Parent 1 [+((x, y),2)] crosses over with parent 2 [(+(x,1),/(y,2))] and produces an offspring represented by [+(/(y,2)),2)]. It is customary to use such prefix notation to represent expressions in GP. Figure 10-3. Basic flow of GP with crossover operations; after selecting random crossover points on both parents, a portion of parent 1 attaches to a portion of parent 2 to create an offspring Figure 10-3. Basic flow of GP with crossover operations; after selecting random crossover points on both parents, a portion of parent 1 attaches to a portion of parent 2 to create an offspring 191 191 Chapter 10 ■ Multiobjective Optimization Weighted-Sum Approach The weighted-sum method for multiobjective optimization delivers multiple solution points by varying the weights consistently. Different objectives are merged into a single objective, and the composite function is minimized, using configurable weights. Mathematically, the weighted-sum approach can be represented as F w f x for w and w i i i i m i i m = ³ = =å å . ( ) . 0 1 1 (10-7) F w f x for w and w i i i i m i i m = ³ = =å å . ( ) 0 1 1 (10-7) 192 Chapter 10 ■ Multiobjective Optimization For positive weights, minimizing F can result in a Pareto optimal solution. Although this method is computationally efficient, the major drawback is that it cannot determine the weights that can optimally scale the objective functions for a problem with little or no information. Multiobjective Genetic Algorithm MOGA is another variant of SGA, differing in the way fitness is assigned to a solution. In this scheme, rank R is assigned to each solution, using the expression (10-8) R x t n t i i ( , ) ( ), = + 1 where ni is the number of solutions that dominate the ith solution xi in generation t. Once the ranking process is completed, the fitness of individuals is assigned by interpolating between the best rank (1) and the worst rank (£m) via a user-defined function. The fitness of individuals of the same rank is averaged, allowing sampling at the similar rate, while maintaining selection pressures. The fitness of certain individuals may degrade more than others, depending on the size of the ranked population. Ranking guides the search to converge only on global optima. Solutions exhibiting good performance in many objective dimensions are more likely to participate in the mating process. Although the ranking process assigns the nondominated solutions the correct fitness, it does not always guarantee sampling uniformity in the Pareto set. When dealing with multiple objectives, genetic drift triggers a suboptimal behavior, in which a large number of solutions tend to converge on a lesser number of objectives, owing to an imperfect selection process. To prevent premature convergence and to diversify the population, a niche-formation method is adopted to distribute the population over the Pareto region, in the objective space. If the fitness of two individuals is closer than a certain niching distance, they are considered part of same niche (i.e., sharing the same fitness). Niche formation discourages convergence to a single region of the fitness function by introducing competitive pressures among niches that reduce the fitness of such locally optimal solutions. Niche formation leads to discovery of diverse regions of the fitness landscape. In nature a niche is regarded as an organism’s task in the environment, and a species is the collection of organisms with the same features. Niching segments the GA population into disjoint sets in such a manner that at least one member in each region of fitness function covers more than one local optimal. In one such method, you define a parameter niche radius (sradius). Any two individuals closer than this distance are considered part of the same niche, sharing the same fitness value. Vector-Evaluated Genetic Algorithm VEGA is a population-based algorithm that extends the selection operator of a simple GA (SGA), such that each generation produces a number of disjoint subpopulations, as a result of a proportional selection scheme, and is governed by different objectives. For a problem with m objectives and a total population of size N, m subpopulations of size N / m are generated by their respective fitness functions. As depicted in Figure 10-4, these subpopulations are shuffled together to generate a new population of size N. The scheme is efficient and easy to implement, because only the selection method of SGA is modified. Figure 10-4. Basic flow of a VEGA Figure 10-4. Basic flow of a VEGA Figure 10-4. Basic flow of a VEGA Because of proportional selection, the shuffling and merging operations of all the subpopulations in VEGA result in an aggregating approach. The drawback of this scheme is its inability to find a large number of points on the Pareto optimal front because each solution executes its own objective function. VEGA is prone to finding extreme solutions, owing to the parallel search directions of the axes in the objective space or simultaneous execution of multiple-objective functions. 193 Chapter 10 ■ Multiobjective Optimization Multiobjective Genetic Algorithm Niching lets the GA operate on the new shared fitness instead of on the original fitness of an individual. Niching reduces interspecies competition and helps synthesize a stable subpopulation around different niches. In multiobjective optimization problems, a niche is ordinarily represented by the locale of each optimum in the search space, with fitness as the resource of that niche. Niched Pareto Genetic Algorithm NPGA is a tournament selection scheme based on Pareto dominance, in which a comparison set of randomly selected individuals participates to determine the winner between two candidate solutions. Each of the candidates is tested to determine dominance. The candidate that is nondominated by the comparison set is selected for the mating pool. If both candidates are either dominated or nondominated by the comparison set, then they are likely to belong to the same equivalence class. As shown in Figure 10-5, for a given niche radius (sshare) the selection for the mating pool is determined by the niche class count. Candidates with the least number of individuals in the equivalence class (least niche count) have the best fitness. In this example, because both candidates are nondominated, Candidate 1 is selected to the mating pool, on the basis of lower niche class count. 194 Chapter 10 ■ Multiobjective Optimization Figure 10-5. Equivalence class sharing; candidate 1 (niche class count = 3) is a better fit than candidate 2 (niche class count = 4) Figure 10-5. Equivalence class sharing; candidate 1 (niche class count = 3) is a better fit than candidate 2 (niche class count = 4) MOGA and NPGA suffer from similar drawbacks; both methods are highly sensitive to selection of niche radius (sshare). MOGA and NPGA suffer from similar drawbacks; both methods are highly sensitive to selection of niche radius (sshare). where e is a small positive number. NSGA shares the same drawback as other algorithms in this category: high sensitivity to the niche radius sshare. Nondominated Sorting Genetic Algorithm Mathematically, this process can be explained as follows: for k individuals with a dummy fitness of fp and niche count of m i p, as part of p nondominance level, the shared fitness of each individual i can be calculated as always lower than that of individuals in the lower levels. This process continues until all individuals in the entire population have been assigned their shared fitness. Once all the fitness values have been assigned, traditional GA processes related to selection, crossover, and mutation apply. Mathematically, this process can be explained as follows: for k individuals with a dummy fitness of fp and niche count of m i p, as part of p nondominance level, the shared fitness of each individual i can be calculated as ˆf f m p i p i p = ˆf f m p i p i p = (10-9) (10-9) ummy fitness for individuals in the subsequent nondominance level is given as (10-10) ˆ min ˆ , f f f p i k i p = ( )- = - 1 1 e (10-10) where e is a small positive number. Nondominated Sorting Genetic Algorithm NSGA is another Pareto-based nonelitist approach that differs from SGA in the manner in which the selection operator is used. All the nondominant solutions are selected first and classified as the first nondominant front in the population. To determine the members of the second nondominant front, members of the first nondominant front are eliminated from the evaluation process, and the search for nondominance continues with the remaining population. This process of level elimination and nondominance search within a shrinking population continues until all the individuals of the population have been categorized to a level of nondominance. Levels of nondominance range from 1 to p. Fitness is assigned to each category of the subpopulation proportionally to the population size. Solutions belonging to the lower levels of nondominance have higher fitness than those belonging to higher levels. This mechanism maintains the selection pressure to select individuals to the mating pool with higher fitness (members of lower levels of nondominance), in a direction toward the Pareto-optimal front. In the first step the initial dummy fitness, equal to the population size, is assigned to individuals in the first level of the nondominance front. Based on the number of neighboring solutions (niche class count for a given niche radius sshare) sharing the same front and the same level, the fitness value of an individual is reduced by a factor of the niche count, and a new shared fitness value is recomputed for each individual in this level. For the individuals in the second nondominance level, a dummy fitness smaller than the lowest shared fitness of the first nondominance level is assigned. Similarly, individuals that are members of the third and all subsequent levels are assigned fitnesses in decreasing order, relative to the lowest fitness of the lower levels. This guarantees that the fitness of individuals belonging to higher levels of nondominance is 195 Chapter 10 ■ Multiobjective Optimization always lower than that of individuals in the lower levels. This process continues until all individuals in the entire population have been assigned their shared fitness. Once all the fitness values have been assigned, traditional GA processes related to selection, crossover, and mutation apply. Strength of P Solutions Each solution is assigned a strength Si Î[ ) 0 1, . Si is proportional to the number of individuals j P Î , such that i dominates j. The fitness of the solution in an external nondominated set P is given by f S n N i i = = +1, (10-11) (10-11) f S n N i i = = +1, where n is the number of individuals in P dominated by i, and N is the total population of P. where n is the number of individuals in P dominated by i, and N is the total population of P. Strength Pareto Evolutionary Algorithm SPEA implements elitism and nondominance by merging several features of previous implementations of multiobjective EAs. Elitist selection prevents the quality of good solutions from degrading, from one generation to the next. In one of its variants, the best individuals from the current generation are carried to the next, without alteration. Zitzler et al. (2001) defined the characteristics of SPEA by referencing the following at 1. Creates an external and continuously updating nondominated population set by archiving previously found nondominated solutions. At each generation the nondominated solutions are copied to the external nondominated set. Unlike other EAs, in SPEA the relative dominance of one solution by other solutions within the population is irrelevant. 2. Applies external nondominated solutions from step 1 to the selection process by evaluating an individual’s fitness, based on the strength of its solutions that dominate the candidate solution. 3. Preserves population diversity, using the Pareto dominance relationship. This EA does not require a distance parameter (such as niche radius). 4. Incorporates a clustering procedure to prune the nondominated external set without destroying its characteristics. s stated, this algorithm implements elitism explicitly by maintaining an external nondominan ation set ( ) P . The algorithm flow consists of the following steps: As stated, this algorithm implements elitism explicitly by maintaining an external nondominant population set ( ) P . The algorithm flow consists of the following steps: 1. Initialize the population P of size n. 2. Initialize an empty population P representing an external nondominant solution set archive. 3. Copy the nondominated solutions of P to P. 4. Remove solutions contained in P that are covered by other members of P (or dominated solutions). 196 Chapter 10 ■ Multiobjective Optimization 5. If the number of solutions in P exceeds a given threshold, prune P, using clustering. 6. Compute the fitness of each member of P and the strength of each member of P. 7. Perform binary tournament selection (with replacement) to select individuals for the mating pool from the multiset union of P and P(P P + ). Tournament selection creates selection pressure by holding a “tournament” among randomly selected individuals from the current population (P P + ). The winner of each tournament (the individual with the best fitness) is inducted into the mating pool. Strength Pareto Evolutionary Algorithm The mating pool has higher average fitness, compared with the average population fitness, and helps build selection pressure, which improves the average fitness of successive generations. 8. Apply problem-specific mutation and crossover operators, as usual. 9. Go to step 3, and repeat (unless termination criteria are reached). Fitness of P Solutions The fitness of solution j P Î is calculated by summing the strength of all external nondominated solutions i P Î ( ) that cover (or dominate) j. The fitness of a solution in set P is given by f S j i i P i j = + Îå 1 , ,  (10-12 f S j i i P i j = + Îå 1 , ,  (10-1 f S j i i P i j = + Îå 1 , ,  (10-12) with 1 added to the fitness to maintain better fitness of the external nondominant solution. Because the fitness is minimized, lower fitness results in a higher likelihood of being selected to the mating pool. Clustering In SPEA the size of the external nondominated solution set ( ) P is key to the success of the algorithm. Because of its participation in the selection process, an extremely large nondominated solution set may reduce selection pressure and slow down the search. Yet, unbalanced distribution in the population may bias the solutions toward certain regions of the search space. Therefore, a pruning process is needed 197 Chapter 10 ■ Multiobjective Optimization to eliminate individuals in the external nondominated population set, while maintaining its diversity. Zitzler, Laumanns, and Thiele (2001) used the average linkage method (Morse 1980) to prune the external nondominated solution set. The clustering steps are as follows: to eliminate individuals in the external nondominated population set, while maintaining its diversity. Zitzler, Laumanns, and Thiele (2001) used the average linkage method (Morse 1980) to prune the external nondominated solution set. The clustering steps are as follows: e individuals in the external nondominated population set, while maintaining its diversity. 1. Initialize a cluster C, such that each individual i P Î ( ) in the external nondominated solution set is a member of a distinct cluster. 2. Calculate the distance between all possible pairs of clusters. Let dm,n be the distance between two clusters cm and c C nÎ ; then, d c c i i m n m n m n i i m n , , . . , = - å 1 (10-13) d c c i i m n m n m n i i m n , , . . , = - å 1 (10-13) where i c i c i i m m n n m n Î Î - , , is the Euclidian distance between the objective space of two individuals, and ck is the population of cluster ck. where i c i c i i m m n n m n Î Î - , , is the Euclidian distance between the objective space of two individuals, and ck is the population of cluster ck. 3. Merge two clusters with minimum distance dm,n into the larger cluster. 4. Identify the individual in each cluster set with the minimum average distance to all other individuals in the cluster. 5. Cycle steps 2–4 until reaching a threshold of maximum number of allowed clusters ( ) C N £ . SPEA introduces elitism into evolutionary multiobjective optimization. Clustering One advantage that stands out is that this algorithm is not dependent on niche distance (sradius), as are MOGA or NSGA. The success of SPEA largely depends on the fitness assignment methodology, based on the strength of the archive members. In the worst-case scenario, if the archive contains a single member, then every member of P will have the same rank. The clustering process also remains the critical consideration for the success of the algorithm. Although essential for maintaining diversity, this technique may not be able to preserve boundary solutions, which can lead to nonuniform spread of nondominated solutions. Strength Pareto Evolutionary Algorithm II After the fitness evaluation is completed, the next step is to copy all nondominated individuals from archive ( ) Pt and population (Pt) to the archive of the next generation ( ), Pt+1 P i i P P F t t t i + = Î + Ù < { } 1 1 ( ) . (10-18) P i i P P F t t t i + = Î + Ù < { } 1 1 ( ) . (10-18) If the number of nondominated solutions is less than the threshold N, then the N Pt - +1 best-dominated solutions ( ) Fi >1 from the sorted list of the previous archive ( ) Pt and population (Pt) are moved to the new archive ( ) Pt+1 . If, however, the number of nondominated solutions exceeds the threshold N, then the truncation process takes place by removing P N t+ - 1 individuals with minimum distance, relative to each other. In the case of a tie, the second-smallest distances are considered, and so on. Also unlike SPEA, in which binary tournament selection (with replacement) selects individuals for the mating pool from the multiset population of Pt and Pt , SPEA-II selects individuals from the archive population Pt+1 only. Strength Pareto Evolutionary Algorithm II SPEA-II is an enhanced version of SPEA. In SPEA-II each individual in both the main population and the elitist archive is assigned a strength value (Si) representing the number of solutions it dominates, (10-14) S j j P P i j i = Î + Ù ( ( )) .  (10-14) On the basis of the strength value Si, the raw fitness value Ri is calculated by summing the strengths of the individuals that dominate the existing one i, R S i j j =å , (10-15) R S i j j =å , where j P P j i Î + ( ), .  where j P P j i Î + ( ), .  Unlike SPEA, in which fitness is determined only by the cumulative strength of the dominating archive members, in SPEA-II, fitness is determined by the cumulative strength of the dominating members in both the archive and the population. Because the fitness is minimized, a higher fitness value signifies that the candidate individual is dominated by a large number of individuals. 198 Chapter 10 ■ Multiobjective Optimization To distinguish individuals with identical raw fitness scores, SPEA uses the k–nearest neighbors (k-NN) method (Silverman 1986) for estimating additional density information for each individual. Here, k is calculated as the square root of the combined sample size of P and P. Each individual i measures, stores, and sorts its distance in objective space, relative to all other individuals j in the archive and the population. The kth element (distance) of the sorted list, in increasing order, is represented by s i k. Density Di is given by Di i k = + 1 2 s , (10-16) Di i k = + 1 2 s , where Di £1. Finally, adding Ri (raw fitness) and Di yields the fitness of individual i, represented by i Finally, adding Ri (raw fitness) and Di yields the fitness of individual i, represented by F R D i i i = + . (10-17) (10-17) F R D i i i = + . Unlike SPEA, SPEA-II maintains a constant number of individuals in the archive. Pareto Archived Evolutionary Strategy Initialize a parent, evaluate its objective function, and add it to the archive. 2. Mutate the parent, generate a child, and evaluate its objective function. 3. Compare the parent and child. a. If the parent dominates the child, discard the child, and go to step 2. b. If the child dominates the parent, accept the child as a parent for the next generation, and add it to the archive. 4. Compare the child with members in the archive. 4. Compare the child with members in the archive. a. If any member of the archive dominates the child, discard the child, and go to step 2. b. If the child dominates any member of the archive, accept the child as a parent for the next generation, add it to the archive, and remove all dominated solutions in the archive. 5. If the child does not dominate any solution in the reference archive, then check the child for proximity to the solutions in the archive; accept the child as a parent in next generation if it resides in a less crowded region in the parameter space. Copy the child to the archive. 6. Go to step 2, and repeat until a predefined number of generations is reached. 6. Go to step 2, and repeat until a predefined number of generations is reached. Pareto Archived Evolutionary Strategy PAES is a simple multiobjective EA capable of generating diverse Pareto-optimal solutions. It is a single- parent, single-child EA that resembles (1+1)-Evolutionary Strategy. PAES uses binary representation and bitwise mutation operators to fulfill local search and create offspring. A bitwise mutation operator flips the bits (genes) of the binary coded solution (chromosomes) with a fixed probability, thereby creating a new solution. A reference archive stores and updates the best nondominated solutions found in previous generations. The best solution is the one that either dominates or remains nondominated in a less crowded region in the parameter space. This archive is used for ranking the dominance of all the resulting solutions. First, a child is created, and its objective functions are computed. Next, the child is compared with the parent. If the child dominates the parent, the child is accepted as a parent for the next generation, and its copy is added to the archive. If the parent dominates the child, the child is discarded, and a new mutated solution is generated from the parent. In the event that the parent and the child are nondominating, with respect to each other, then both are compared with the archive of best solutions to make an appropriate selection. If any member of the archive dominates the child, the child is discarded, and a new mutated solution is generated from the parent. If the child dominates any member of the archive, the child is accepted as a parent for the next generation, and all dominated solutions in the archive are eliminated. If the child does not dominate any solution in 199 Chapter 10 ■ Multiobjective Optimization the reference archive, then the child is checked for its proximity to the solutions in the archive. The child is accepted as a parent in the next generation if it resides in a less crowded region in the parameter space. A copy of the child is also added to the archive. the reference archive, then the child is checked for its proximity to the solutions in the archive. The child is accepted as a parent in the next generation if it resides in a less crowded region in the parameter space. A copy of the child is also added to the archive. The PAES algorithm consists of the following steps: The PAES algorithm consists of the following steps: The PAES algorithm consists of the following steps: 1. 6. Go to to step 3, and repeat. The crowding methodology in PESA forms a hypergrid that divides objective space into hyperboxes. Each individual in the external archive is associated with a particular hyperbox in objective space. An attribute defined as the squeeze factor represents the total number of other individuals that reside in the same hyperbox. The squeeze factor narrows down the choice of solutions from among randomly selected solutions (from the external archive) by picking the ones with lower squeeze factors. The squeeze factor drives the search toward an emerging Pareto front by selecting members of the under represented population. The squeeze factor is also used to regulate the population of the external archive. When the archive population \|PE\| exceeds a certain threshold, a random individual from the region with a maximum squeeze factor is chosen to be removed. Pareto Envelope-Based Selection Algorithm II PESA-II is an extension of PESA that exercises a region-based selection approach, in which the selection criteria are satisfied using a hyperbox instead of random individuals in the hyperbox. A sparsely populated hyperbox has a higher likelihood of being selected than a crowded one. Once the cell is selected, individuals with the cell are randomly selected to participate in the mating and mutation processes. Although this algorithm is computationally efficient, it requires prior information about the objective space to tune the grid size. Pareto Envelope-Based Selection Algorithm PESA is a multiobjective EA that uses features from both SPEA and PAES. The difference is attributed to the part of the algorithm in which PESA integrates selection and diversity, using a hypergrid-based crowding scheme. Like SPEA, PESA employs a smaller internal population and larger external population. Whereas the external population archives the existing Pareto front approximation, the internal population comprises new candidates competing for inclusion in the external archive. Similar to PAES, to maintain diversity, PESA uses the hypergrid division of objective space to measure the scale of crowding in distinct regions of the external archive. Like PAES and SPEA, PESA’s solution replacement scheme (archiving the best nondominated solutions) for the external archive is based on the crowding measure; however, unlike PAES (which uses parent mutation) and SPEA (which uses the fitness measure, based on the strength of the dominating solutions), the selection scheme in PESA is also based on the crowding measure. The PESA algorithm uses two population sets: PI representing the internal population and PE representing the external population (also called archive population). The steps of PESA are as follows: g p p I p g p p E representing the external population (also called archive population). The steps of PESA are as follows: 1. Initialize the external population (PE) to an empty set. 2. Initialize the internal population ( ) PI =f . 3. Evaluate each individual in the internal population. 200 Chapter 10 ■ Multiobjective Optimization 4. Update the external population archive PE. 4. Update the external population archive PE. a. Copy the nondominated solution (in PI and any member of PE) of PI into PE. b. Remove the solution of PE that is dominated by the newly added nondominated solution of PI. c. If the solution of PI neither dominates nor is dominated by PE, then add the solution to PE. d. If \|PE\| exceeds a threshold, randomly choose a solution from the most crowded hypergrids to be removed. 5. Check the termination criteria. 5. Check the termination criteria. a. IF a termination criterion has been reached, STOP; return PE. b. OTHERWISE, 1. Delete the internal population PI =f. 2. Repeat (until a new PI is generated). a. Select two parents from PE, from the less crowded hypergrid (based on the density information). b. Create new offspring, based on crossover and mutation. Elitist Nondominated Sorting Genetic Algorithm NSGA-II improves the nonelitist nature of NSGA with a crowded tournament selection scheme that uses crowding distance to facilitate selection. In NSGA-II, once the population is initialized, individuals in the population undergo nondominated sorting and ranking, as in NSGA. To find the first nondominated front, each individual in the population is compared with every other individual in the population to find if that individual is dominated. The nondominated individuals in the first front are removed from the population and placed in temporary (level 1) storage. To find the next front, the procedure is repeated with 201 Chapter 10 ■ Multiobjective Optimization the remainder of the population. The process continues until all the members of the population are assigned a front. In the worst-case scenario, each front contains only one solution. Each individual in each front is given a fitness value (or rank), based on the front it belongs to; for instance, an individual in the nth front is given a fitness of n. Additionally, crowding distance is measured for each individual. Crowding distance represents the measure of an individual’s proximity to its neighbors, which drives the population toward better diversity. Parents are admitted into the mating pool, using binary tournament selection, based on rank and crowding distance. On completion of the nondominated sort, a crowding distance value is assigned to each individual. If two solutions are compared during tournament selection, the winning solution is selected, based on the following criteria: If the solutions belong to two different ranks, the solution with the better rank wins • the selection. If the solutions belong to the same rank, the solution with the higher crowding • distance (or lesser crowding region) wins. Once the mating pool is populated, crossover and mutation operators are applied to generate the offspring population. To implement elitism, the parent and child populations are combined, and the nondominated individuals from the combined population are propagated to the next generation. The NSGA-II algorithm is summarized as follows: Initialization 1. Initialize a random population P0 of size N. 2. Sort and rank the population by creating nondomination fronts. 3. Assign fitness, according to the ranks of the population. 4. Create offspring Q0 of size N, using crossover and mutation operators. Selection 5. Elitist Nondominated Sorting Genetic Algorithm The start of each generation has a combined population of R t P t Q t ( ) ( ) ( ) = - È - 1 1 size 2N . 6. Sort and rank the population by creating nondomination fronts (F1(t), F2(t), F3(t),…,Fn(t)). 7. Select fronts F1(t) to Fn(t) until the sum of the combined population of selected fronts exceeds N. 8. Copy the entire populations of selected fronts F1(t) to Fn-1(t) to the mating pool of the next generation. 9. Sort the population of the last selected front Fn(t) in decreasing order, by crowding distance. 10. Select the best individuals from the last front Fn(t) needed to fill the mating pool slot of N. 11. The mating pool now comprises the entire population of fronts F1 to Fn-1 and the partial population (sorted by crowding distance) of front Fn to create a parent population (mating pool) of population N. 11. The mating pool now comprises the entire population of fronts F1 to Fn-1 and the partial population (sorted by crowding distance) of front Fn to create a parent population (mating pool) of population N. 12. Use crossover and mutation operators to create N offspring. 202 Chapter 10 ■ Multiobjective Optimization Figure 10-6. NSGA-II procedure: the nondominated fronts F1(t), F2(t), and F3(t) are included fully in the mating pool P(t + 1); the crowding distance–sorted front F4(t) is included partially in the mating pool P(t + 1) Figure 10-6. NSGA-II procedure: the nondominated fronts F1(t), F2(t), and F3(t) are included fully in the mating pool P(t + 1); the crowding distance–sorted front F4(t) is included partially in the mating pool P(t + 1) The crowding distance guides the selection process toward a uniformly spread-out Pareto optimal front. The crowding distance of the ith solution D[i] is calculated as the sum of individual distance values corresponding to each objective m. Each objective function is normalized before calculating the crowding distance. The following steps summarize the crowding distance computation of all solutions in a nondominated set I: 1. l = I Number of solutions 2. I = {0} Initialize all solutions to 0 ---------[For all objectives k = 1 to k = m]---------- 3. I = Sort (I,k ) Sort by the kth objective 4. D D [ ] [ ] i l = = ¥ --------[For i = 2 to i £ (l −1) ]----------------------- 5. Elitist Nondominated Sorting Genetic Algorithm D D I I [ ] [ ] . . max min i i i k i k f f m m = + + [ ] - - [ ] ( ) - 1 1 (10-19) f m m m N m m max max . , . , . , . = [ ] [ ] [ ] [ ] ( ) I I I I 1 2 3  f m m m N m m min min . , . , . , . = [ ] [ ] [ ] [ ] ( ) I I I I 1 2 3  1. l = I Number of solutions 2. I = {0} Initialize all solutions to 0 ---------[For all objectives k = 1 to k = m]---------- 3. I = Sort (I,k ) Sort by the kth objective 4. D D [ ] [ ] i l = = ¥ --------[For i = 2 to i £ (l −1) ]----------------------- 5. D D I I [ ] [ ] . . max min i i i k i k f f m m = + + [ ] - - [ ] ( ) - 1 1 (10-19) f m m m N m m max max . , . , . , . = [ ] [ ] [ ] [ ] ( ) I I I I 1 2 3  f m m m N m m min min . , . , . , . = [ ] [ ] [ ] [ ] ( ) I I I I 1 2 3  1. l = I Number of solutions 2. I = {0} Initialize all solutions to 0 ---------[For all objectives k = 1 to k = m]---------- 3. I = Sort (I,k ) Sort by the kth objective 4. D D [ ] [ ] i l = = ¥ --------[For i = 2 to i £ (l −1) ]----------------------- 5. D D I I [ ] [ ] . . max min i i i k i k f f m m = + + [ ] - - [ ] ( ) - 1 1 (10-19) f m m m N m m max max . , . , . , . Elitist Nondominated Sorting Genetic Algorithm = [ ] [ ] [ ] [ ] ( ) I I I I 1 2 3  f m m m N m m min min . , . , . , . = [ ] [ ] [ ] [ ] ( ) I I I I 1 2 3  3. I = Sort (I,k ) Sort by the kth objective 4. D D [ ] [ ] i l = = ¥ --------[For i = 2 to i £ (l −1) ]----------------------- 5. D D I I [ ] [ ] . . max min i i i k i k f f m m = + + [ ] - - [ ] ( ) - 1 1 (10-19) f m m m N m m max max . , . , . , . = [ ] [ ] [ ] [ ] ( ) I I I I 1 2 3  f m m m N m m min min . , . , . , . = [ ] [ ] [ ] [ ] ( ) I I I I 1 2 3  Step 5 is a recursive operation, in which each successive iteration evaluates the crowding distance of the sorted solutions, based on the objective fitness. Step 5 is invoked for each objective fitness. Here, I[i].k represents the kth objective function value of the ith individual in the set I. The crowding distance is the Euclidian distance between each individual in the m–dimensional hyperspace. The individuals in 203 Chapter 10 ■ Multiobjective Optimization the boundary are always selected, because they have infinite distance assignment. To ensure elitism, the offspring and parent populations of the current generation are combined to select the mating pool of the next generation. The population is subsequently sorted by nondomination. As illustrated in Figure 10-6, the new population for the mating pool is generated by filling the populations of each front Fj (low to high) until the population size exceeds a threshold size of the parent population. If by including individuals in the front Fj the total population exceeds N, then individuals in the front Fj are selected in descending order of crowding distance until the population of size N is reached. This concludes the creation of the mating pool for the next generation. Elitist Nondominated Sorting Genetic Algorithm In the figure the nondominated fronts F1(t), F2(t), and F3(t) are included fully, and the crowding distance–sorted front F4(t) is included partially, in the mating pool P(t + 1). Example: Multiobjective Optimization Cloud computing allows us to host workloads with variable resource requirements and service-level objectives or performance guarantees. Furthermore, the cloud enables us to share resources efficiently, thereby reducing operational costs. These shared resources primarily relate to compute, memory, input/ output (I/O), and storage. Variability of resources creates thermal imbalances, over- or underprovisioning, performance loss, and reliability issues. If these problems remain unchecked, their cumulative effect can increase the cost of running a datacenter as well as degrade workload performance, owing to unplanned provisioning and unanticipated demands. The solution for efficient datacenter management rests in satisfying multidimensional constraints that may be dynamic in nature and mutually conflicting. Environmental stresses vary from time to time and create resource pressures, which may be either global or regional, creating dynamic constraints that result in revised goals that need to be achieved. As illustrated in Figure 10-7, the operational constraints in this example can be classified as four objective functions: Figure 10-7. Multiobjective optimization in a datacenter with four objective functions, related to power, performance, temperature, and usage Figure 10-7. Multiobjective optimization in a datacenter with four objective functions, related to power, performance, temperature, and usage 204 Chapter 10 ■ Multiobjective Optimization 1. Reducing thermal stresses (FT): Thermal stresses occur when one or more devices approach their throttling limit or generate hot or cold spots, relative to other devices (or clusters of systems). Thermal stresses can be relieved by regulating fan speed, input airflow, or resource utilization. 2. Meeting power targets (FP): Power targets are set by an external management agent, according to fair usage and availability of maximum power. System power targets can be regulated by resource utilization; fan speed; or hosting workloads that do not exceed power demands and that are nonnoisy, relative to other workloads already running on different cores. 3. Meeting performance guarantees (FS): Performance guarantees are the fitness matrices defined by applications to measure service-level objectives (SLOs). For example, query response time is a measure that can quantify the quality of service when hosted on a system or cluster of systems. Performance guarantees are delivered via regulated resource utilization or by hosting workloads that are nonnoisy, relative to other workloads running on different cores. 4. Meeting resource utilization targets (FU): Resource utilization targets are enforced to maximize the server usage in a unit volume of rack space, leading to a reduction in idle periods. Example: Multiobjective Optimization In some cases, resource utilization is regulated to deliver service assurance or reduce thermal hot spots. Resource utilization enforcement is generally realized by using an appropriate distribution of workloads in different cores in a manner that ultimately leads to the most efficient resource utilization with the least amount of mutual noise (cache, prefetching) or contention. The multiobjective optimization problem can be represented as a function of these four objectives, ltiobjective optimization problem can be represented as a function of these four objectives, F x f F x F x F x F x T P s U ( ) min ( ), ( ), ( ), ( ) , = ( ) where x represents the parameters for the values selected to satisfy thermal, power, utilization, and performance constraints. These parameters can be summarized as follows: where x represents the parameters for the values selected to satisfy thermal, power, utilization, and performance constraints. These parameters can be summarized as follows: Fan speed ( • x1) Fan speed ( • x1) Central processing unit (CPU) power limit ( • x2) Memory power limit ( • x3) Input airflow ( • x4) Workload type ID ( • x5) Objective Functions Individual objective functions measure the quality of solutions. Multiobjective optimization methods trade off the performance between various objectives. Here, a suitable tradeoff between power, thermal, performance, and utilization objectives is sought, using the EAs. Equations 10-21–10-24 represent the objective functions for these objectives. Each of the objectives is contingent on the values of parameters (decision vectors) that define the search space to satisfy the vectors of multiple goals through tradeoffs between combinations of multiple objectives, F N f T T for T f x f T T T d T d d N d T d d T d = ( ) = £ ( ) £ =å 1 0 1 1 , ( ) ; , (10-21) F f P P for P f x f P P P T P T = ( ) = £ ( ) £ , ( ) ; , 0 1 (10-22) F f Q Q forQ f x f Q Q s T Q T = ( ) = £ ( ) £ , ( ) ; , 0 1 (10-23) F N f U U forU f x f U U U d T d d N d U d d T d = ( ) = £ ( ) £ =å 1 0 1 1 , ( ) ; , (10-24) where Td and Ud are temperature and utilization of device d, respectively; TT d and UT d are the respective temperature and utilization thresholds; P is the current power consumption of the complete system; and Q is the service-level agreement (SLA), or performance score, of the workload running on the system. The solution x impacts the process output, represented by the corresponding functions f x f x f x f x T d P Q U d ( ), ( ), ( ), ( ) , ( ) which influence the output of the objective functions. (Note that power and performance are system specific and not device specific in this context.) The solution x evolves by maneuvering multiple dimensions of the decision space and anticipating an optimal tradeoff between all four objectives. Forinstance, setting a higher fan speed (x1) will improve cooling (FT) but increase power consumption, thereby degrading FP . Similarly, the CPU power limit (x1) may regulate power consumption but degrade performance (FS). Number of CPU cores ( • x6) Number of CPU cores ( • x6) These parameters x = (x1, x2, x3, x4, x5, x6) regulate the operating states of the resources, which result in environmental as well as system-specific perturbations that may need to be corrected as part of exploring a true Pareto-optimal front or stable system. 205 Chapter 10 ■ Multiobjective Optimization Objective Functions Therefore, the goal of the EAs is to synthesize a near- optimal solution that attempts to fulfill the inherent and often conflicting constraints of all the objectives. Solutions should reflect optimal decisions in the presence of tradeoffs between the four objectives. These decision vectors match certain workloads on specific systems, such that there is the least amount of conflict between objectives. Additional controls regulate the fan speed, CPU and memory power limits, input airflow, and allocation (or deallocation) of additional CPU cores. Figure 10-8 displays the process of selecting the best compute node (from among a large number of nodes) for workload hosting. 206 Chapter 10 ■ Multiobjective Optimization Figure 10-8. Node selection for workload hosting, using multiobjective evolutionary optimization gure 10-8. Node selection for workload hosting, using multiobjective evolutionary optimization Whenever a new workload is staged for hosting on one of the compute nodes, it undergoes fingerprinting. This process involves matching the distinctive attributes of multidimensional features to a preexisting database. Fingerprints correlate resource utilization patterns and estimate resource requirements. Swarm intelligence acts as a mechanism whereby a few candidate host nodes are selected from hundreds of possible host nodes for further evaluation. Some nodes are eliminated because of the low likelihood of their ability to deliver enough contention-free resources. Once shortlisted, the candidate nodes represent compute resources that can host incoming workloads, although with varying degrees of resource handling. All the shortlisted nodes are evaluated for quality of hosting the new workload by running MOEA in parallel, in an effort to generate multiple Pareto-optimal fronts, one for each node. The node corresponding to the best solution is selected for hosting the workload. The MOEA evaluates the solutions (see Equation 10-20) by measuring the collective efficiency of power, performance, utilization, and temperature and iterates toward finding the tradeoff representing the best solution. The process repeats each time a new workload appears in the staging queue to be serviced by one of the compute nodes. Deb, Kalyanmoy, Amrit Pratap, Sameer Agarwal, and T. Meyarivan. “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II.” IEEE Transactions on Evolutionary Computation 6, no. 2 (2002): 182–197. Corne, David W., Joshua D. Knowles, and Martin J. Oates. “The Pareto Envelope-Based Selection Algorithm for Multiobjective Optimization.” Parallel Problem Solving from Nature—PPSN VI: Proceedings of the 6th International Conference, edited by Marc Schoenauer, Kalyanmoy Deb, Günter Rudolph, Xin Yao, Evelyne Lutton, Juan Julian Merelo, and Hans-Paul Schwefel, 839–848. Berlin: Springer, 2000. References Corne, David W., Nick R. Jerram, Joshua D. Knowles, and Martin J. Oates. “PESA-II: Region-Based Selection in Evolutionary Multiobjective Optimization.” In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001). San Francisco: Morgan Kaufmann, 2001. Corne, David W., Joshua D. Knowles, and Martin J. Oates. “The Pareto Envelope-Based Selection Algorithm for Multiobjective Optimization.” Parallel Problem Solving from Nature—PPSN VI: Proceedings of the 6th International Conference, edited by Marc Schoenauer, Kalyanmoy Deb, Günter Rudolph, Xin Yao, Evelyne Lutton, Juan Julian Merelo, and Hans-Paul Schwefel, 839–848. Berlin: Springer, 2000. Deb, Kalyanmoy, Amrit Pratap, Sameer Agarwal, and T. Meyarivan. “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II.” IEEE Transactions on Evolutionary Computation 6, no. 2 (2002): 182–197. Deb, Kalyanmoy, Amrit Pratap, Sameer Agarwal, and T. Meyarivan. “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II.” IEEE Transactions on Evolutionary Computation 6, no. 2 (2002): 182–197. 207 Chapter 10 ■ Multiobjective Optimization Fonseca, Carlos M., and Peter J. Fleming. “Genetic Algorithms for Multiobjective Optimization: Formulation Discussion and Generalization.” In Proceedings of the 5th International Conference on Genetic Algorithms, edited by Stephanie Forrest, pp. 416–423. San Francisco: Morgan Kaufmann, 1993. Goldberg, David E. Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addison-Wesley, 1989. Horn, J., N. Nafpliotis, and D. E. Goldberg. “A Niched Pareto Genetic Algorithm for Multiobjective Optimization.” In Proceedings of the First IEEE Conference on Evolutionary Computation, IEEE World Congress on Computational Intelligence, 82–87. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 1994. Knowles, J. D., and D. W. Corne. “The Pareto Archived Evolution Strategy: A New Baseline Algorithm for Pareto Multiobjective Optimisation.” In Proceedings of the 1999 Congress on Evolutionary Computation, 98–105. Piscataway, NJ: Institute of Electrical and Electronic Engineers, 1999. Marler, R. Timothy, and Jasbir S. Arora. “Survey of Multi-Objective Optimization Methods for Engineering.” Structural and Multidisciplinary Optimization 26, no. 6 (2004): 369–395. Morse, J. N. “Reducing the Size of the Nondominated Set: Pruning by Clustering.” Computers and Operations Research 7, nos. 1–2 (1980): 55–66. Nidamarthi, Srinivas, and Kalyanmoy Deb. “Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms.” Evolutionary Computation 2, no. 3 (1994): 221–248. Schaffer, J. David. 1985. “Multiple Objective Optimization with Vector Evaluated Genetic Algorithms.” In Proceedings of the 1st International Conference on Genetic Algorithms, edited by John J. Grefenstette, 93–100. Hillsdale, NJ: L. Erlbaum, 1985. Silverman, B. W. Density Estimation for Statistics and Data Analysis. London: Chapman and H Zitzler, E., M. Laumanns, and L. Thiele. —Bill Gates Machine learning is an important means of synthesizing and interpreting the underlying relationship between data patterns and proactive optimization tasks. Machine learning exploits the power of generalization, which is an inherent and essential component of concept formation through human learning. The learning process constructs a knowledge base that is hardened by critical feedback to improve performance. The knowledge base system gathers a collection of facts and processes them through an inference engine that uses rules and logic to deduce new facts or inconsistencies. As more and more data are expressed digitally in an unstructured form, new computing models are being explored to process that data in a meaningful way. These computing models synthesize the knowledge embedded in the unstructured data and learn domain-specific trends and attributes. More sophisticated models can facilitate decision support systems, using hierarchies of domains and respective domain-specific models. Machine learning plays an important role in automating, expanding, and concentrating procedures for unearthing learnings in ways that traditional statistical methods are hard-pressed to match. This chapter presents examples in which machine learning is used as the principal constituent of a feedback control system. We discuss machine learning usage in areas related to datacenter workload fingerprinting, datacenter resource allocation, and intrusion detection in ad hoc networks. These examples demonstrate an intelligent feedback control system based on the principles of machine learning. Such systems can enable automated detection, optimization, correction, and tuning throughout high-availability environments, while facilitating smart decisions. Furthermore, these systems evolve and train themselves, according to platform needs, emerging use cases, and the maturity of the knowledge data available in the ecosystem. The goal is to create models that act as expert systems and that automatically perform proactive actions that can later be reviewed or modified, if necessary. A traditional system uses a collection of attributes that determine a property or behavior in current time. An expert system uses machine learning to discover the nature of the change resulting from the learning process and analyze the reasoning behind better adaptation of the process. Such a system can be either history determined or state -determined. A state-determined system can be described in terms of transitions between states in consecutive time intervals (such as first-order Markov chains). The new state is uniquely determined by the previous state. References “SPEA2: Improving the Strength Pareto Evolutionary Algorithm.” Technical report, Swiss Federal Institute of Technology, 2001. Zitzler, E., and L. Thiele. “Multiobjective Evolutionary Algorithms: A Comparative Case Study and the Strength Pareto Approach” IEEE Transactions on Evolutionary Computation 3, no. 4 (1999): 257–271. 208 Chapter 11 Chapter 11 Machine Learning in Action: Examples A breakthrough in machine learning would be worth ten Microsofts. Chapter 11 ■ Machine Learning in Action: Examples Chapter 11 ■ Machine Learning in Action: Examples Figure 11-1 illustrates an autonomic system that is constructed by using modular functions to enact an intelligent feedback control system. Machine learning plays a significant role in modeling the knowledge function, which is used to store the rules, constraints, and patterns in a structured manner. New knowledge is synthesized, using the elements of existing structures and new learnings. The collective knowledge enacts a feedback control loop, which enables a stable and viable system. The supporting functions that facilitate an intelligent feedback control system are as follows: A • sensor function to sense any changes in the internal or external environment (such as component temperature, power, utilization, and aberrant behavior). A • motor function to compensate for the effects of environmental disturbances by changing the system elements, thereby maintaining equilibrium. An • analytical function to analyze the sensor channel data to ascertain if any of the essential variables are operating within viable bounds, or limits. A • planning function to determine the changes that need be made to the current system behavior to bring the system back to the equilibrium state in the new environment. A • knowledge function that contains the set of possible behaviors that can be applied to the new environment. The planning tool uses this knowledge to select the appropriate action to nullify the disturbance; the motor channel applies the selected behavior. The knowledge function is synthesized, using the generalization process, which can be an ongoing task that effectively develops a richer hypothesis space, based on new data applied to the existing model. MOTOR CHANNEL SENSOR CHANNEL KNOWLEDGE Monitor Analysis Planning Execute Managed Element CHANNE C N N E C N N NEL NE N Figure 11-1. Modular functions as fundamental elements for building autonomics architecture Planning Execute Monitor MOTOR CHANNEL CHANNE C N N E C N N Managed Element Figure 11-1. Modular functions as fundamental elements for building autonomics architectur These functions enable key elements to model a practical system by using an abstracted cybernetic description (regulation theory). This description abstracts a set of interrelated objects that can receive, store, process, and exchange data. Cybernetic systems can be represented by means of control objects and control systems. Control systems transmit the control information to the controlled objects via sets of effectors. —Bill Gates To adapt, the organism, guided by information from the environment, must manage its essential variables, forcing them to operate within the proper limits by manipulating the environment (through the organism’s motor control of it), such that it then acts on the variables appropriately. 209 Chapter 11 ■ Machine Learning in Action: Examples The state information on a controlled object is received through a set of receptors and is transmitted back to the control system, thereby creating a feedback loop. This feedback loop is capable of developing 210 Chapter 11 ■ Machine Learning in Action: Examples an autonomic system that operates an effective control system through adaptive regulation. The model comprises the following five necessary and sufficient interacting subsystems, which, collectively, constitute an organizational structure that affords system viability: an autonomic system that operates an effective control system through adaptive regulation. The model comprises the following five necessary and sufficient interacting subsystems, which, collectively, constitute an organizational structure that affords system viability: • Infrastructure to interact with the operational environment, which is controlled by the management process. • Coordination to promote the dissemination of policy data that allow collaboration and coordination. • Control for intervention rules as well as policy adherence, resource compliance, accessibilities, and responsibilities. • Intelligence for planning ahead in anticipation of changes in the external environment and capabilities. Intelligence aids in capturing a complete view of the system environment and benefits the system in formulating alternate strategies, which are necessary for adapting to changing conditions to keep the system viable. • Policy to steer the organization toward a purposeful goal by formulating policy functions that lead to planning activities. Viable System Modeling Controlled systems may demonstrate a high degree of dynamism in their interactions that may result in unpredictable behaviors. Viable system modeling facilitates a framework that allows coordination, coevolution, and survivability, using monitoring, control, and communication abstractions. Such modeling helps the system survive in a constantly changing and unpredictable environment; the modeling is built to outlast external stresses and demands variability, and it adapts to any unexpected stimuli. You abstract the framework in such a manner that variability in the usage model does not interfere with stabilizing the system within its viable limits. Unpredictable behavior, intermittent failures, and scattered knowledge generate a sizeable uncertainty, which can cause reactive or suboptimal decisions as well as rendering ineffective traditional programming paradigms, which operate on the principals of independence and static behavioral models. Programming strategies need to be built to characterize and optimize runtime patterns, using dynamic policies. This requires autonomous instantiation of mechanisms that respond to changing dynamics. Additionally, programming models must take into account the separation between policy management, activation mechanisms, computation, and runtime adaptation. Isolation can be realized using abstractions that make it possible to hide the implementation choices. Abstractions establish a common view of a component model to allow interoperability via communication semantics. Intelligent feedback control implementation facilitates adaptation, which lets the controlled process change its configuration over time by dynamically adapting to specific needs and requirements. Adaptation is typically triggered by the rule engine, owing to faulting, or changing behavior, of a resource in platform, and is achieved through changes in the set of resources, components, or dependencies. A necessary condition for adaptation is the preservation of the existing semantics, with an ability to reconfigure and adapt to the new environment. This is supported by implementing adding, plugging, and unplugging component controllers dynamically, thereby adding or removing the functional aspect of a component. The two categories of adaptation are as follows: • Functional adaptation adapts the architectural behavior of the component to new requirements or environments. • Nonfunctional adaptation adapts the nonfunctional architecture of the container to the new requirements or environment (e.g., changes in security policy or communication protocol). 211 Chapter 11 ■ Machine Learning in Action: Examples Adaptation functions require the ability to identify dynamically changing patterns and behaviors with these properties: The ability to evaluate when and how much. Heuristics are built to identify • appropriate conditions that demand reconfiguration. Viable System Modeling Adaptation function of a server system; based on the feedback, the cost function block reevaluates the function weights, whereas the resource control block reevaluates resource allocation Viable System Modeling Reactive reconfiguration or tuning can easily lead to oscillation. Additionally, the amount of reconfiguration depends on the application-specific optimization function (also called the cost function), which is maximized for a given policy. A weighted cost function to evaluate the significance of specific objectives in cases in • which multiple objective functions race for adaptability. Low-latency evaluation and optimization of the cost function to satisfy the handling • of control function in real time. The ability to identify and resolve resource conflicts and oscillations resulting from • competing objectives. The ability to log resource attributes and behavioral patterns to aid in establishing a • rational reasoning process for future optimizations and conflict resolutions. Knowledge synthesis through pattern identification plays a pivotal role, modeling several behavioral trends that recur over time. These patterns are appealing for proactive analysis, which paves the way for monitoring and analyzing the process by focusing on the most significant activities. Pattern analysis is commonly used to determine workflow behavior as well as the correspondence between related actions. Pattern analysis is also used to predict the choices that are more likely to yield the desired policy compliance, thereby supporting the selection of the best action to be activated from among a set of possible candidates. The framework execution model is responsible for collecting two types of information: raw data logged during the execution of workload and processed data derived from the raw data, which are synthesized to describe behavioral patterns. Figure 11-2 conceptualizes an adaptation framework for a server system, in which subfunctional components are isolated into discrete and independent blocks. The monitor function monitors the performance parameters and corresponding resource utilization. This is logged into the knowledge base, which traces the relationship between resource utilization and various performance attributes. The drift detector evaluates the deviation between measured performance and desired performance. A deviation (positive or negative) triggers a correction to the cost function as well as to the resource control block. Whereas the cost function manipulates the relative coefficients of the fitness equation, the resource control mechanism reevaluates resource allocation, based on rational reasoning and fuzzy logic. This process continues until all the objectives are met. 212 Chapter 11 ■ Machine Learning in Action: Examples Figure 11-2. Adaptation function of a server system; based on the feedback, the cost function block reevaluates the function weights, whereas the resource control block reevaluates resource allocation Figure 11-2. Example 1: Workload Fingerprinting on a Compute Node Datacenter power consumption has increased drastically in recent years, and controlling the power intake of servers has become critical. To develop efficient servers, server platforms require online characterization to determine platform parameters for the tuning required for various system features because of the complex dependencies among them. Feedback-directed optimization of servers with insights gained from workload observation has proven to be more effective than static configurations. The server processor and chipsets expose software-configurable margins and range limits, called control parameters, which can be tuned to achieve a balance between power and performance. Some of these parameters are set by the platform’s basic input/output system (BIOS) once at boot time and remain static throughout. One-time configuration at boot time renders the system nonresponsive to load variation. The example given here describes a dynamic characterization technique using machine learning algorithms that determine tuned values from runtime program phases. A self-correcting workload fingerprint codebook accelerates phase prediction to achieve continuous and proactive tuning. Parameters such as memory and processor power states can be set dynamically, based on observed demand variations, by the operating system or the hardware modules. Autonomous systems then trade off system margins to gain power or performance advantages, depending on the use case. Proactive tuning prepares the system to tune itself in advance and avoids the response lag characteristic of reactive systems. Various machine 213 Chapter 11 ■ Machine Learning in Action: Examples learning techniques, such as clustering, classifiers, and discrete phase predictors, are applied to the data collected from subsystems of the processor. Additionally, it is crucial to ascertain the appropriate algorithms and operations, while considering extrapolative efficiency at the least computational cost. learning techniques, such as clustering, classifiers, and discrete phase predictors, are applied to the data collected from subsystems of the processor. Additionally, it is crucial to ascertain the appropriate algorithms and operations, while considering extrapolative efficiency at the least computational cost. Performance-monitoring units facilitate measurement of fine-grained events through hardware counters. These counters allow application profilers to reveal the application’s time-varying phase behaviors that repeat in a defined pattern over their lifetime. A program phase can be described as a discontinuity in the time in which observable characteristics vary distinctively enough to effect an equally measurable system impact variation. The phase characteristics and probabilistic sequence of known phases are represented as a fingerprint. Example 1: Workload Fingerprinting on a Compute Node Fingerprints facilitate proactive models for load balancing, thermal control, and resource allocation within a collection of servers in a datacenter. The steps employed in the learning process can be summarized as follows: 1. Execute the workload in the server system(s). 2. Identify relevant process control parameters, and relate them to process goals (workload throughput, server power, thermal variance, and so on). 3. Synthesize the attributes of a phase and phase sequence. 4. Build a phase prediction model to forecast future behavior of the workload. 5. Tune the system control parameters proactively. Workload fingerprinting allows proactive self-tuning, which avoids a lag between the feedback and the control (or the reactive control) by learning the underlying relationships between operational workload phases and corresponding application behavior, thereby facilitating dynamic adaptation in changing environments. Understanding application behavior has also been a key source of insight for driving several new architectural features, such as built-in memory power control, thermal throttling, turbo boosting, processor cache size adaptation, and link configurations. The feature-specific controls that constitute the decision space are dynamically tuned to the current and future phases through a multiobjective coordinated tuning process to achieve globally optimal results. Traditionally, the decision space of a process is defined by control parameters, which are tuned, based on insights derived from offline empirical analysis of data collected by running well-known benchmarks and establishing the average case. These control parameters are then statically programmed at boot time by the system BIOS. A better approach is to program dynamically the parametric values synthesized by proactive simulation, using a machine learning method that exploits an intelligent feedback-based self-tuning process. Phase Determination It is quite common to employ well-understood benchmark tools as models that approximate real-world workload behavior, because they have a finite completion time, while exhibiting unique resource usage patterns. A program phase has been defined and extended in many ways by researchers, based on the goals to be achieved. This example defines a program phase as a variable time interval during execution in which a set of observable characteristics exhibits spatial uniformity and distinctiveness. The example uses a multivariable phase determination technique consisting of multiple dominant variables that are both externally observable and related to the platform control variable. The measured variables mi are the values of performance events obtained from hardware counters when running a range of bootstrap workloads. The elements of this initial dataset M ( \| , ) m m M i N i i Î £ serve as the building blocks of the phase model. The motivation to choose N variables to be measured comes from the objective of the study. The feature selection process is commonly applied to large datasets to filter out correlations and vastly reduce the computational complexity of algorithms in subsequent stages. To improve classifier accuracy and efficiency, special tools, such as the correlation-based feature selection (CFS) algorithm, are applied to reduce the dataset’s dimensionality. CFS is a best-first search heuristic algorithm that ranks the worth of subsets rather 214 Chapter 11 ■ Machine Learning in Action: Examples than individual features. The algorithm filters out the features that are effective in predicting the class, along with the level of intercorrelation among features in the subset, by calculating the feature–class and feature– feature matrices. The features selected by CFS exhibit a high degree of correlation to the reference class, but redundant variables are removed. Given a subset S consisting of k features, the heuristic score is given as than individual features. The algorithm filters out the features that are effective in predicting the class, along with the level of intercorrelation among features in the subset, by calculating the feature–class and feature– feature matrices. The features selected by CFS exhibit a high degree of correlation to the reference class, but redundant variables are removed. Phase Determination Given a subset S consisting of k features, the heuristic score is given as Merit kr k k k r s cf ff k = + + ( ) , 1 (11-1) (11-1) where rcf is the average feature–class correlation, and rf is the average feature–feature intercorrelation. CFS transforms the measured variable set M to a reduced variable set D, yielding ( \| , ) d d D j N j j Î £ , f where rcf is the average feature–class correlation, and rf is the average feature–feature intercorrelation. CFS transforms the measured variable set M to a reduced variable set D, yielding ( \| , ) d d D j N j j Î £ , f where rcf is the average feature–class correlation, and rf is the average feature–feature intercorrelation. CFS transforms the measured variable set M to a reduced variable set D, yielding ( \| , ) d d D j N j j Î £ , D = CFS(M), and N N £ . The next step is to build the phase model by using the selected features and applying the simple k-means algorithm to group the uncorrelated variable instances. The k-means algorithm is an unsupervised machine learning algorithm that partitions the input set into k clusters, such that each observation belongs to a cluster with the nearest mean (the Euclidean distance). The objective f D = CFS(M), and N N £ . The next step is to build the phase model by using the selected features and applying the simple k-means algorithm to group the uncorrelated variable instances. The k-means algorithm is an unsupervised machine learning algorithm that partitions the input set into k clusters, such that each observation belongs to a cluster with the nearest mean (the Euclidean distance). The objective function of the k-means algorithm can be represented as J d c m l l m j l k = - = = å å \|\| \|\| , ( ) 2 1 1 (11-2) (11-2) where cl is the chosen centroid of cluster l and dm l( ) represents mth datapoint in lth cluster. You consider each cluster a phase f. This example, with k = 5, produces a model that has the mean and standard deviation of the 12 filtered variables (see Figure 11-3). Figure 11-3. Phase model: cluster mean and standard deviation Phase Determination where cl is the chosen centroid of cluster l and dm l( ) represents mth datapoint in lth cluster. You consider each cluster a phase f. This example, with k = 5, produces a model that has the mean and standard deviation of the 12 filtered variables (see Figure 11-3). 215 Chapter 11 ■ Machine Learning in Action: Examples Once the phase model is trained, it can be tested against subsequent runs of the workload data. A classifier algorithm from a related class of machine learning algorithms can generate a tree, a set of rules, or a probability model to identify quickly the correct phase. One example is the tree representation obtained from a decision tree classifier algorithm upon training with the cluster data, as illustrated in Figure 11-4. This classifier achieves approximately 99 percent accuracy in phase identification. Figure 11-4. Decision tree representation of the model The initial training data set of 37 workloads results in five clusters, with each cluster representing a workload phase (see Figure 11-5). In each phase the 12 dominant features display a diverse variation pattern, with at least one feature being the primary predictor. As mentioned earlier, a phase transition can be identified by the classifier tree, using the feature-specific threshold values. Figure 11-4. Decision tree representation of the model The initial training data set of 37 workloads results in five clusters, with each cluster representing a workload phase (see Figure 11-5). In each phase the 12 dominant features display a diverse variation pattern, with at least one feature being the primary predictor. As mentioned earlier, a phase transition can be identified by the classifier tree, using the feature-specific threshold values. The initial training data set of 37 workloads results in five clusters, with each cluster representing a workload phase (see Figure 11-5). In each phase the 12 dominant features display a diverse variation pattern, with at least one feature being the primary predictor. As mentioned earlier, a phase transition can be identified by the classifier tree, using the feature-specific threshold values. The initial training data set of 37 workloads results in five clusters, with each cluster representing a workload phase (see Figure 11-5). In each phase the 12 dominant features display a diverse variation pattern, with at least one feature being the primary predictor. As mentioned earlier, a phase transition can be identified by the classifier tree, using the feature-specific threshold values. Chapter 11 ■ Machine Learning in Action: Examples Chapter 11 ■ Machine Learning in Action: Examples Phase Determination 216 Chapter 11 ■ Machine Learning in Action: Examples Figure 11-5. Phase transition diagram for various workloads Figure 11-5. Phase transition diagram for various workloads Figure 11-6 shows the workload–phase boundaries, with seven clusters found in four workloads. Each workload is characterized by a unique composition of workload phases. Once the workload is identified, it is phase characterized by its resource utilization and time series pattern. Whereas workload 3 consists mainly of phase 7, workload 1 is a complex mix of phases 3, 5, and 6. These phases discover the characteristic that is unique to a workload instance at any given time. Figure 11-6. Workload and phase dependency graph; a workload may share phase characteristics with other workloads and can cater to one or more phases Figure 11-6. Workload and phase dependency graph; a workload may share phase characteristics with other workloads and can cater to one or more phases 217 Size Attribute The size attribute is useful in proactive provisioning of resources. Using the size dimension provides answers to the following questions: What is the shape of the distribution? Which resources are more popular than • others? Is there a significant tail? What is the spatial locality in accesses to the groups of popular objects during spikes? • Fingerprinting Workloads undergo phases of execution, while operating under multiple constraints. These constraints are related to power consumption, heat generation, and quality of service (QoS) requirements. Optimal system operation involves complex choices, owing to a variety of degrees of freedom, with respect to power and performance parameter tuning. The process involves modeling methodology, implementation choices, and dynamic tuning. Fingerprinting acts as an essential feature that captures time-varying behavior of dynamically adaptable systems. This ability is used as a statistical output that aids in reconfiguring hardware and software ahead of variation in demand and that enables the reuse of trained models for recurring phases. Pattern detection also assists in predicting future phases during the execution of workloads, which prevents reactive response to changes in workload behavior. As part of the workload fingerprinting process (see Figure 11-7), individual performance characteristics are collected at a given interval, classified, and aggregated to establish patterns representative of an existing workload or collection of workloads. System control agents, such as I/O schedulers, power distribution, and dynamic random access memory (DRAM) page policy settings, can use this information to tune their parameters or schedule workloads in real time. Fingerprinting can roughly be attributed using three properties: size, phase, and pattern. The machine learning process facilitates synthesis of these properties by measuring or data mining performance characteristics over a finite period. Generally, the feature selection process allows automatic correlation of performance matrices with occurrences of unique workload behaviors, thereby aiding in speedy diagnosis and proactive tuning. Fingerprinting data can be combined with simple statistical functions, such as optimization, visualization, or control theory, to create powerful operator tools. Furthermore, fingerprints help contain prolonged violation of one or more specified service-level objectives (SLOs), which involves performing proactive actions to return the system to an SLO-compliant state. Figure 11-7. Workload fingerprint: a quantifiable form of characterization Figure 11-7. Workload fingerprint: a quantifiable form of characterization 218 Chapter 11 ■ Machine Learning in Action: Examples Forecasting The workload forecasting module detects trends in the workload and makes predictions about future workload volume. If the target workload demonstrates a strong periodic behavior, a historic forecast can be incorporated into workload forecasting. This allows the policy decision to react proactively to the workload spikes ahead of time. This also helps you take advantage of the heterogeneous compute and I/O resources offered by cloud computing providers. Furthermore, based on the extracted patterns, you may distribute the workloads in a manner that creates different performance models. Chapter 11 ■ Machine Learning in Action: Examples Chapter 11 ■ Machine Learning in Action: Examples Pattern Attribute A pattern is defined as a sequence of phases that repeats. Once a sequence is identified, it can be used to predict future phases and the duration of current phases. In the time series operations, you construct the vocabulary for the time series pattern database. Each alphabet in the vocabulary is represented by the operating phase of the workload. This phase is measured in a fixed interval of length (T). The pattern matrix can be represented as Mij, where i represents the pattern, and j stands for the frequency of that pattern. As new patterns are identified, they are updated into the pattern matrix, and old and infrequent patterns are deprecated. You can use a discrete time Markov chain (DTMC) (see Equation 11-3) to identify underlying patterns in a time series sequence of changing phases, (11-3)   ( \| , , ) ( \| ), q S q S q S q S q S t j t i t k t j t i + - + = = = = = = 1 2 1  (11-3) where qt represents the current state, and Si represents one of the phases of operation. In this model a state transition (phase change) follows the Markov property and then creates transitions between states (phases), based on a learned model for forecasting. You can use a moving window to monitor real-time data and produce an autoregressive model for recently observed data, which is then matched to the state of the learned Markov model. The model also makes corrections, if necessary, to adapt to the changes. By tracing the time series progression from one phase to another, you can build a transition function of the Markov model (see Figure 11-8c). Phase Attribute A phase represents a unique property that characterizes the behavior of an ongoing process. In this example the phase demonstrates unique power, temperature, and performance characteristics. As described previously (see the section “Phase Determination”), this example employs a simple k-means algorithm to synthesize exclusive behaviors in the form of clusters, represented as phases. This process is executed once all the relevant feature vectors are identified. These vectors are observations that directly or indirectly reflect the unique behavior in the form of resource usage. The phases are compressed representative output that can be used in conjunction with any other statistical parameter for prediction of behavior. Sequences of phases can be seen as patterns. Patterns represent a unique time-varying characteristic of the workload. Figure 11-8a illustrates the phase sequence during one execution of a workload. Figure 11-8b displays the encoded representation of the phase sequence. 219 Chapter 11 ■ Machine Learning in Action: Examples Figure 11-8. (a) Test workload phases, (b) run-length encoded phase sequence, and (c) pha likelihood matrix and workload–phase dependency matrix; the workload 1 phase dependen Figure 11-8. (a) Test workload phases, (b) run-length encoded phase sequence, and (c) phase transition likelihood matrix and workload–phase dependency matrix; the workload 1 phase dependency is highlighted Figure 11-8. (a) Test workload phases, (b) run-length encoded phase sequence, and (c) phase transition likelihood matrix and workload–phase dependency matrix; the workload 1 phase dependency is highlighted 220 Chapter 11 ■ Machine Learning in Action: Examples Chapter 11 ■ Machine Learning in Action: Examples The term power optimization denotes the act of targeting and achieving high levels of power-normalized performance at the application level. For a software application, such as a business transaction service or content retrieval service, the significant performance metrics include the number of requests serviced (throughput) and the turnaround delay (response time) per request. Optimizing power entails multiple dynamic tradeoffs. Typically, a system can be represented as a set of components whose cooperative interaction produces useful work. These components may be heterogeneous or presented with heterogeneous loads, and they may vary in their power consumption and power control mechanisms. At the level of any component—such as a processing unit or a storage unit—power needs to be increased or decreased on an ongoing basis, according to whether that component’s speed plays a critical role in the overall speed or rate of execution of programs. In particular, different application phases may have different sensitivities to component speed. For instance, a memory-bound execution phase will be less affected by central processing unit (CPU) frequency scaling than a CPU-bound execution phase. With the execution reordering that most modern processors employ, the degree to which a program benefits from out-of-order execution varies from one phase to another. Moreover, the rate at which new work arrives in a system changes, and, as a result, the overall speed at which programs have to execute to meet a given service-level expectation varies with time. Thus, the needed power performance tradeoffs have to occur on a continuous basis. Arguably, given the self-correcting and self-regulating aspects common in systems today, software- driven power performance should be unnecessary. For example, in power control algorithms, CPUs and DRAMs transition into lower frequencies or ultralow power modes during low-activity periods. Although circuit-level self-regulation is highly beneficial in transitioning components to low-power states, software needs to wield policy control over which activity should be reduced, and when, to facilitate the transition of hardware into power-saving modes. Harnessing power savings on less busy servers is a delicate task that is hard to delegate to hardware- based recipes. Servers are typically configured for handling high rates of incoming work requests at the lowest possible latencies. Therefore, it is not uncommon for servers to have many CPUs and a large amount of physical memory over which computations and data remain widely distributed during both high- and low-demand periods. Chapter 11 ■ Machine Learning in Action: Examples Owing to the distributed nature of activities, slowing down a single CPU or DRAM can have unpredictable performance ramifications; it can be counterproductive to push part of a server into ultralow power operation. At the other extreme, when power approaches saturation levels, hardware is ill positioned to determine or enforce decisions about which software activities can tolerate reduced performance and which must continue as before. Thus, software must share with hardware the responsibility of determining when and in which component power can be saved. Here, we consider an autonomic solution for fine-grained control over power performance tradeoffs for server configurations. The solution consists of ingredients for observing, analyzing, planning, and controlling the dynamic expenditure of power in pursuance of an application- level performance objective that is specified as an SLO. This solution uses a time-varying database query workload, in which the learning machine simultaneously changes the power allocation to CPUs and DRAM and gathers performance and power readings via a set of distributed physical and logical sensors in the server. Through these observations, models are trained for various phases of the workload. Based on these models, the optimization heuristic redistributes the power to maximize the overall performance per watt of the server. Experimental measurements demonstrate that a heuristic improves performance and power, as needed or as permitted by the performance objective. Example 2: Dynamic Energy Allocation Controlling the amount of power drawn by server machines has become increasingly important in recent years. The accuracy and agility of three types of action are critical in power governance: Selecting which hardware elements must run at what rates to meet the • performance needs of the software Assessing how much power must be expended to achieve those rates • Adjusting the power outlay in response to shifts in computing demand • Observing how variations in a workload affect the power drawn by different server components provides data critical for analysis and for building models relating QoS expectations to power consumption. This next example describes a process of observation, modeling, and course correction in achieving autonomic power control on an Intel Xeon server machine meeting varying response time and throughput demands during the execution of a database query workload. The process starts with fine-grained power performance observations permitted by a distributed set of physical and logical sensors in the system. These observations are used to train models for various phases of the workload. Once trained, system power, throughput, and latency models participate in optimization heuristics that redistribute the power to maximize the overall performance per watt of the server. 221 Learning Process: Feature Selection The primary role of a learning process is to identify relationships between the total power expended (P) and two measures of performance: response time (R) and throughput (T). These relationships are synthesized as models, and optimization techniques use these models to achieve better power performance efficiency. 222 Chapter 11 ■ Machine Learning in Action: Examples The process of generalization requires a classifier that inputs a vector of discrete feature vectors and outputs an operating phase, which can be summarized as follows: Fine-grained and time-aligned component-level power readings at multiple power • rails of the primary components (CPU and dual inline memory module [DIMM]) System-level readings corresponding to three quantities, each averaged over a small • time interval: (1) P, the total system power; (2) T, the application-level throughput; and (3) R, the response time experienced by requests The component-level power readings are aligned with the {P, T, R} tuples. This entire data collection is then used to divide the {P, T, R} space into classes (phases). Within each class or phase a linear function can relate P, T, and R to the component-level power readings. These linear relationships are used in optimization planning, whose objective may be to minimize P (total system power) or maximize T (application-level throughput), subject to R’s (response time) not exceeding a specific threshold. Learning continues online. Therefore, as the workload evolves, the models and optimization planning adapt. The support vector machine (SVM) technique may be employed to divide the {P, T, R} space into different phases and to obtain linear relationships governing the {P, T, R} variables in each phase. As discussed previously, SVM is a computationally efficient and powerful technique; invented by Boser, Guyon, and Vapnik (1992), it is employed for classification and regression in a wide variety of machine learning problems. Given a data collection relating a set of training inputs to outputs, an SVM is a mathematical entity that accomplishes these tasks: 1. The SVM describes a hyperplane (in some higher dimension) whose projection into the input space separates inputs into equivalence classes, such that the inputs in a given class have a linear function mapping them to outputs that is distinctive for that class. 2. The hyperplane whose projection is the SVM maximizes the distance that separates it from the nearest samples from each of the classes, thus maximizing the distances between classes, subject to a softness margin. 3. CPU Power Readings (2) Memory Power Readings (4) CPU Power Readings (2) Memory Power Readings (4) CPU Power Readings (2) Memory Power Readings (4) P t K V t V t R t j P J PK iJ CPU i P iJ DIMM i DRAM CH i CPU i j ( ) ( ) ( ) ( ) - = + - = = å å a b K V t V t T t K R J RK iJ CPU i R iJ DIMM i DRAM CH i CPU i j T J = + - = = = å å a b a ( ) ( ) ( ) TK iJ CPU i T iJ DIMM i DRAM CH i CPU i V t V t ( ) ( ) + = = å å b (11-4) P t K V t V t R t j P J PK iJ CPU i P iJ DIMM i DRAM CH i CPU i j ( ) ( ) ( ) ( ) - = + - = = å å a b K V t V t T t K R J RK iJ CPU i R iJ DIMM i DRAM CH i CPU i j T J = + - = = = å å a b a ( ) ( ) ( ) TK iJ CPU i T iJ DIMM i DRAM CH i CPU i V t V t ( ) ( ) + = = å å b (11-4) Learning Process: Optimization Planning Learning Process: Optimization Planning Energy and performance models have a number of degrees of freedom and conflicting objectives that are difficult to optimize collectively. For example, consider the following objectives: Best performance per watt • Staying within a power limit • Response time • £ a service-level agreement (SLA) threshold Conflicts can manifest themselves among these objectives, with considerations such as How to obtain a given throughput within a • system power budget How to obtain a given throughput under a • response time threshold In the common case, P (total system power) is affected by both performance targets—throughput and response time. Also in the general case, performance is influenced by the power spent in both processors and DIMM modules. Thus, optimization planning must grapple with meeting a compound objective: one in which power expended toward one objective generally comes at the cost of another. Once the coefficients of the linear estimation model for power, throughput, and response time are synthesized, these models can be used as a synthetic feedback in a multiobjective optimization through a feedback control loop. This example uses an adaptive weighted genetic algorithm (AWGA) method to search for the global optimal in a scenario with multiple goals. In this machine learning technique a successful outcome is defined as one that redistributes power in such a way that power, response time, and the reciprocal of throughput all meet the viable limits. More generally, a set of fitness functions { fn}, one per objective n, determines the optimality of a candidate setting (i.e., a vector describing the distribution of power among components) for each of the objectives. In AWGA, for a population f of candidate settings {x}, F f x x n max n = Î max( ( )\| ) f ) and Fn min = min(fn(x)\|x Î f), you compute, respectively, the fitness bounds for each of a set of n = 1, 2, . . . , N objectives, where each x in f is a vector whose fitness function represents a feasible power distribution among components, such as CPUs and DIMMs. You may then choose an N objective fitness function F that evaluates an aggregate fitness value. For example, in the case of AWGA, F can be chosen as Fn min = min(fn(x)\|x Î f), you compute, respectively, the fitness bounds for each of a set of n = 1, 2, . . . Learning Process: Feature Selection The SVM creates a softness margin that permits a bounded classification error, whereby a small fraction of the inputs that should be placed on one side of the projection are instead placed within a bounded distance on the other side (and are therefore misclassified); this margin allows a pragmatic tradeoff between having a high degree of separation between classes (i.e., better distinctiveness) and having too many outliers. Equation 11-4 expresses each element of {P, T, R} as a linear function of the five power readings per processor within each given class or phase. Whereas (VCPU) yields power going into the processor, VDIMM measures power in memory modules that are connected to and controlled from the processor. The variable J represents a given class, {PJ(t),RJ(t),TJ(t)} represents a tuple from a sample numbered t in the training set, and the various power readings associated with that sample are represented by V(t). The phases J; constants KP, KR, KT; and coefficients a* * and b* * are all estimated through the SVM regression technique. 223 Chapter 11 ■ Machine Learning in Action: Examples Learning Process: Monitoring Achieving power-efficient performance and abiding by power and performance constraints call for real-time feedback control. An autonomic system implements continuous feedback-based course correction, with the following provisions: • Monitoring infrastructure to sample or quantify physical and logical metrics, such as power, temperature, and activity rates, and to obtain statistical moments of the metrics • Analysis modules to distill relationships between monitored quantities (e.g., between power, temperature, and performance) and to determine whether one or more operational objectives are at risk A • planning element to formulate a course of action, such as suspending, resuming, speeding up, or slowing down various parts of a system, to effect a specific policy choice (e.g., to limit power or energy consumed or to improve performance) A capability to • execute the formulated plan and thereby control the operation of the system Usually, a knowledge base supplements analysis and planning. The knowledge base may be an information repository that catalogs the allowable actions in each system state, or it may be implicit in the logic of the analysis, planning, and control capabilities. In a system designed for extensibility, the knowledge base typically incorporates an adaptive mechanism that tracks and learns from prior decisions and outcomes. For intelligent feedback control processes, fine-grained and lightly intrusive power performance monitoring is a key element of the adaptive power management infrastructure. The ideal monitoring mechanism operates in real time (i.e., reports data that are as recent as possible) and is not subject to the behavior(s) being monitored. In this configuration logical sensors at the operating system and software levels offer a near real-time information stream consisting of rates at which common system calls, storage accesses, and network transfers proceed. These logical sensors are supplemented with power sensing through physical sensors. ( ) ( ) A telemetry bus is used to collect data from physical (hardware) and logical (software) sensors and send them to a monitoring agent. In particular, power sensing is accomplished by sensing voltage regulator (VR) outputs at each processor chip. The monitoring agent, to which the telemetry data are sent, processes the data, organizes them as a temporally aligned stream of power and performance statistics, and transmits the stream to a remote machine for further storage or analysis. The monitoring infrastructure provides the ability to obtain distinct power readings for each processor. Learning Process: Optimization Planning , N objectives, where each x in f is a vector whose fitness function represents a feasible power distribution among components, such as CPUs and DIMMs. You may then choose an N objective fitness function F that evaluates an aggregate fitness value. For example, in the case of AWGA, F can be chosen as F f F N F F n n min n max n min n N = - × - =å ( ) ( ). x 1 (11-5) (11-5) An evolutionary algorithm (EA) selects parents from a given generation of f (usually employing an elitism process that allows the best solution[s] from the current generation to carry over unaltered to the next), from which to produce power-feasible offspring as new candidates for the next generation. In the objective space, Fn min and Fn max represent extreme points that are renewed at each generation. As the extreme points, fitness bounds {( F F n min n max , )\|n = 1, 2, . . . , N} are renewed at each generation, and the contribution (weight) of each objective is also renewed accordingly. 224 Chapter 11 ■ Machine Learning in Action: Examples Learning Process: Monitoring Learning Process: Monitoring Each processor controls distinct memory channels, with multiple DIMMs per channel; each pair of memory channels furnishes one VDDQ signal; and summing those VDDQ readings gives the power expended in the memory subsystem for each processor. The data collected by these sensors are refined through a succession of transformations (see Figure 11-9): • Sensor hardware abstraction (SHA) layer: This layer interacts with the sensors and communication channels. It uses adaptive sampling, such that measurements are only as frequent as necessary, and it eliminates redundancies. • Platform sensor analyzer: This layer removes noise and isolates trends, which makes it easier to incorporate recent and historical data as inputs in further processing. • Platform sensor abstraction: This layer provides a programming interface for flexible handling of analyzed sensor data through the control procedures implemented above it. • Platform sensor event generation: This layer makes it possible to generate signals. Signals facilitate event-based conversations from control procedures, thereby allowing further control to be hosted in a distributed set of containers (such as local or remote controller software and operating system modules). The prior successive refinements bridge the gap between the raw data that sensors produce and the processed, orderly stream of performance and power readings and alerts that software modules can receive and analyze further. 225 Chapter 11 ■ Machine Learning in Action: Examples Chapter 11 ■ Machine Learning in Action: Examples Figure 11-9. Sensor network model: sensor network layered architecture (S1, S2, . . . , Sn) represents platform sensors (CPU/DIMM power, thermal, performance, and so on). Source: A Vision for Platform Autonomy: Robust Frameworks for Systems (Intel, 2011) Figure 11-9. Sensor network model: sensor network layered architecture (S1, S2, . . . , Sn) represents platform sensors (CPU/DIMM power, thermal, performance, and so on). Source: A Vision for Platform Autonomy: Robust Frameworks for Systems (Intel, 2011) Although a machine can be readily furnished with a metered power supply to sense total power, an instrumentation capability that yields the fine-grained decomposition of power requires nontrivial effort. Moreover, adding many physical power sensors in production machines is neither necessary nor practical, in terms of cost. Event-counting capabilities in modern machines offer a potent alternative means of estimating component power when direct measurement is not practical. One simple yet accurate way of estimating the power draw for recent CPUs is to project it on the basis of usage and power-state residencies, using trained models. Learning Process: Monitoring Such training can be made more accurate by including execution profiles that capture what fraction of the instructions falls into each of a small set of categories, such as single instruction, multiple data (SIMD); load/store; and arithmetic logical unit (ALU). DRAM power can similarly be estimated on the basis of cache miss counts, or DRAM operations that are counted at the memory controllers and tracked through processor event monitors. DRAM power estimation permits measurement of DRAM energy at DIMM granularity with sufficient accuracy to enable efficient control of DRAM power states. Efficient control of DRAM energy allows us not only to reduce the cost of hardware infrastructure, but also to improve energy efficiency by reducing the guard bands required to compensate for underprediction. Furthermore, overprediction can also be reduced to avoid performance degradation. Decision space that facilitates optimal distribution of power among competing components is obtained by process control methods, in which privileged software can modify its power draw. The first method, which is commonly used in Intel-based processors, is to change the P-states and C-states (Siddha 2007). The second method is to change the average power level, using a control known as running average power limit (RAPL) capability for CPUs and DRAM modules. CPU RAPL provides interfaces for setting a power budget for a certain time window and letting the hardware meet the energy targets. Specifying the power limit as an average over a time window allows us to represent physical power and thermal constraints. Privileged software can use the RAPL capability by programming to an interface register the desired average level of power to which the hardware can guide the processor via its own corrective frequency adjustments 226 Chapter 11 ■ Machine Learning in Action: Examples over a programmable control window. The window size and power limit are selected, such that, at either a single-machine level or a datacenter level, correction to a machine’s power is driven quickly. In practice the window size can vary between milliseconds and seconds—the former to satisfy power delivery constraints, the latter to manage thermal constraints. The RAPL concept extends to memory systems as well, aided by the integration of the memory controller into each multicore processor in several recent versions of Intel platforms. Learning Process: Monitoring Although CPU and memory energy can be regulated individually, it is possible to build a coordinated self-tuning approach, in which power regulation is part of a joint optimization function supported by the machine learning technique discussed in the following section. Model Training: Procedure and Evaluation For the model training the data collection module collects time-aligned readings from the power-monitoring sensors. Additionally, it gathers response times and requests completion rates from a database performance module. These readings provide the input–output training vectors { ( ), ( ), ( ), ( ),} * * * P t R t T t V t CPU i and (see Equation 11-4). The training data are obtained through a cross-product of two sets of variations: • Variation of demand: This parameter controls how long each of a number of threads in the workload driver waits between completion of a previous request and issuance of a new request. • Variation of demand: This parameter controls how long each of a number of threads in the workload driver waits between completion of a previous request and issuance of a new request. • Variation of supply: This control varies the CPU and memory RAPL settings, thereby varying the supply of power to CPU and DRAM. In this example the workload uses time-varying think time varying from 0 to 100. For each think time, CPU RAPL limits are varied between 20W and 95W. SVM model training on the basis of these data is then used to categorize the data into distinct phases (J), following which the SVM model parameters for each phase { , , , , , , , , } K K K P J R J T J P iJ R iJ T iJ P iJ R iJ T iJ a a a b b b are evaluated. The SVM-based classification yields decomposition into three phases, as shown in Figure 11-10. Figure 11-10. Model tree depicting three phases (P0, P1, P2) in a workload characterized by throughput and response time Figure 11-10. Model tree depicting three phases (P0, P1, P2) in a workload characterized by throughput and response time 227 Chapter 11 ■ Machine Learning in Action: Examples Accordingly, three different sets of modeling parameters (i.e., for J = 0, 1, 2) in Equation 11-4 relate CPU RAPL parameters to total system power, throughput, and response time outcomes. Figure 11-10 demonstrates how the total wall power estimated on the basis of the RAPL parameters in Equation 11-4 compares with that actually measured. Figures 11-11 and 11-12 illustrate the close agreement between estimated and measured results from the training. g Figure 11-11. Model Training: Procedure and Evaluation Wall power, measured versus estimated (as function of component power) Figure 11-12. CPU power, measured versus estimated; estimated CPU power is phase wise and based on the throughput and target latency requirements On average a machine learning regression function supported by SVM delivers accuracy between 97 percent and 98.5 percent. Each phase is trained for its own performance and latency model coefficients. Figure 11-13 depicts an example consisting of four possible workload conditions on a server. On the x Figure 11-11. Wall power, measured versus estimated (as function of component power) Figure 11-11. Wall power, measured versus estimated (as function of component power) Figure 11-12. CPU power, measured versus estimated; estimated CPU power is phase wise and based on the throughput and target latency requirements On average a machine learning regression function supported by SVM delivers accuracy between 97 percent and 98.5 percent. Each phase is trained for its own performance and latency model coefficients. 97 percent and 98.5 percent. Each phase is trained for its own performance and latency model coefficients. Figure 11-13 depicts an example consisting of four possible workload conditions on a server. On the x axis, tt00, tt10, and tt20 stand for think times of 0.0ms, 10.0ms, and 20.0ms, respectively. The y axis shows response times. The red multisegment line in the figure connects four workload points (W1, W2, W3, W4). Figure 11-13 depicts an example consisting of four possible workload conditions on a server. On the x axis, tt00, tt10, and tt20 stand for think times of 0.0ms, 10.0ms, and 20.0ms, respectively. The y axis shows response times. The red multisegment line in the figure connects four workload points (W1, W2, W3, W4). 228 Example 3: System Approach to Intrusion Detection In an era of cooperating ad hoc networks and pervasive wireless connectivity, we are becoming more vulnerable to malicious attacks. These sophisticated attacks operate under the threshold boundaries during an intrusion attempt and can only be identified by profiling the complete system activity, in relation to a normal behavior. Many of these attacks are silent in nature and cannot be detected by conventional intrusion detection system (IDS) methods, such as traffic monitoring, port scanning, or protocol violation. Intrusion detection may be compared to the human immune system, which, through understanding of the specifications of normal processes, identifies and eliminates anomalies. Identifiers should be distributed throughout a system with identifiable and adaptable relationships. We therefore need a model that, in each state, has a probability of producing observable system outputs and a separate probability indicating the next states. Unlike wired networks, ad hoc nodes coordinate among member nodes to allow exclusive use of the communication channel. A malicious node can exploit this distributed and complex decision-making property of cooperating nodes to launch an attack on, or hijack, the node. This inherent vulnerability can disable the whole network cluster and further compromise security through impersonating, message contamination, passive listening, or acting as a malicious router. An IDS mechanism should be able to detect intrusion by monitoring unusual activities in the system via comparison with a user’s profile and with evolving trends. Although they may not be sufficient to prevent malicious attacks if the attacker operates below the threshold, threshold-based mechanisms can be modified to monitor trends in the related system components to predict an attack. This is similar to an HMM (see Chapter 5), in which the hidden state (attack) can be predicted from relevant observations (changes in system parameters, fault frequency, and so on). Observed behavior acts as a signature or description of normal or abnormal activity and is characterized in terms of a statistical metric and model. A metric is a random variable representing a quantitative measure accumulated over a period of time. Observations obtained from the audit records, when used together with a statistical model, analyze any deviation from a standard profile and trigger a possible intrusion state. , y y p gg p This example discusses an HMM-based strategy for intrusion detection, using a multivariate Gaussian model for observations that are in turn used to predict an attack that exists in the form of a hidden state. Chapter 11 ■ Machine Learning in Action: Examples Chapter 11 ■ Machine Learning in Action: Examples As you can see, new workload points (shown in diamonds) result from proactive power performance control through the use of a trained SVM model. Additionally, new RAPL settings (higher CPU power) computed using the trained model reduce the response times for W1 and W2 from their previous values (by 15 percent and 7 percent, respectively) to new values that are much closer to the SLA. Similarly, the model training produces lower CPU power settings for W3 and W4, which leads to power savings at the cost of higher response times and to 11.5 percent improvement in energy efficiency. Incidentally, the new setting for W4 misses the SLA target by a small but not negligible margin, which could force a recomputation of the CPU RAPL setting in the next iteration. Note that to reduce frequent course correction, a control policy may permit overshooting the SLA target by a small margin in either direction. Here, because the new RAPL settings for W1 and W2 reduced response times, phase-aware CPU power scaling yields significant power reduction at all performance levels, relative to isolated tuning. Chapter 11 ■ Machine Learning in Action: Examples These points are randomly selected perturbations in supply and demand ; for example, W1 results from setting a think time of 20.0ms and a CPU RAPL value of 40W; W2 results from a think time of 0.0ms (driving a higher arrival rate than W1) and a CPU RAPL value of 50W, and so on. Figure 11-13. Response time at four arbitrarily selected points, reflecting four possible workload and server conditions Figure 11-13. Response time at four arbitrarily selected points, reflecting four possible workload and server conditions If none of the response times for W1, W2, W3, and W4 were to exceed a desired performance 1 2 3 4 objective—for instance, an SLA target of R = 20.0ms—then it would be desirable to save power by reducing performance, so long as the higher response times were still below the target of 20.0ms. However, if at any of these workload points the response time were to exceed a desired threshold, then it would be preferable to improve performance by increasing the power to meet the SLA. Generally, an SLA may spell out throughput and response time expectations and may include details, such as the fraction of workload that must be completed within a threshold amount of response time under differing levels of throughput. For ease of description, this example has a simple SLA setting: that the response time, averaged over small time intervals (1s), not exceed a static target value of 14.0ms; this is displayed in Figure 11-14 by the solid line, R = 0.014. Figure 11-14. Illustration of improvement in response time, using proactive control of CPU power employing CPU RAPL Figure 11-14. Illustration of improvement in response time, using proactive control of CPU power employing CPU RAPL 229 Modeling Scheme Parameters for HMM modeling schemes consist of observed states, hidden (intrusion) states, and HMM profiles. HMM training, using initial data and continuous reestimation, creates a profile that involves transition probabilities and observation symbol probabilities. HMM modeling involves the following tasks: Measuring the • observed states, which are analytically or logically derived from the intrusion indicators. These indicators are test points spread throughout the system. Estimating the • instantaneous observation probability function, which indicates the probability of an observation, given a hidden state. This density function can be estimated using an explicit parametric model (multivariate Gaussian) or, implicitly, from data via nonparametric methods (multivariate kernel density emission). Estimating the • hidden states by clustering the homogeneous behavior of single or multiple components. These states are indicative of various intrusion activities that need to be identified to the administrator. Estimating the • hidden state transition probability matrix, using prior *knowledge or random data. Prior knowledge, along with long-term temporal characteristics, indicates an approximate probability of the transitioning of state components from one intrusion state to another. Chapter 11 ■ Machine Learning in Action: Examples Chapter 11 ■ Machine Learning in Action: Examples relationships (also called profiles) are hardened and evolve with the constant usage of the multiple and independent systems. If observation points can be standardized, then the problem of intrusion predictability can be reduced to profiling the existing and new, hidden states to standard observations. relationships (also called profiles) are hardened and evolve with the constant usage of the multiple and independent systems. If observation points can be standardized, then the problem of intrusion predictability can be reduced to profiling the existing and new, hidden states to standard observations. b v c exp v v j jk M jk jk T jk jk ( ) ( ) \| \| ( ) ( ) / / = - - - é ëê ù ûú é - 1 2 1 2 2 1 2 1 p s m s m ë ê ê ù û ú ú =å , k M 1 (11-6) Example 3: System Approach to Intrusion Detection The model comprises a self-organizing network for event clustering, an observation classifier, a drift detector, a profile estimator (PE), a Gaussian mixture model (GMM) accelerator, and an HMM engine. This method is designed to predict intrusion states, based on observed deviation from normal profiles or by classifying these deviations into an appropriate attack profile. An HMM is a stochastic model of discrete events and a variation of the Markov chain. Like a conventional Markov chain, an HMM consists of a set of discrete states and a matrix A = {aij} of state transition probabilities. Additionally, every state has a vector of observed symbol probabilities, B = bj(v), which corresponds to the probability that the system will produce a symbol of type v when it is in state j. The states of the HMM can only be inferred from the observed symbols—hence, the term hidden. HMM correlates observations with hidden states that factor in the system design, in which observation points are optimized, using an acceptable set of system-wide intrusion checkpoints (ICs); hidden states are created using explicit knowledge of probabilistic relationships with these observations. These 230 Chapter 11 ■ Machine Learning in Action: Examples Chapter 11 ■ Machine Learning in Action: Examples It is the responsibility of the IC engine to reestimate the ljk parameters dynamically for all matrices and all possible attack states. Various matrices that represent dimensions of an observation are as follows: • Resource activity trend: The measure of a resource activity that is monitored over a larger sampling period and that has characteristics that repeat over that sampling period. Each period of activity can be thought of as an extra dimension of activity measure. • Event interval: The measure of an interval between two successive activities (e.g., logging attempts). • Event trend: The measure of events monitored over a larger sampling period, with the objective of calculating the event behavior with a built-in repeatability (e.g., the count of logging attempts in a day). Observed (Emission) States Observed states represent competing risks derived analytically or logically, using IC indicators. Machine intrusion can be considered a result of several components’ competing for the occurrences of the intrusion. In this model the IC engine derives continued multivariate observations, which is similar to the mean and standard deviation model, except that the former is based on correlations between two or more metrics. These observations bj(v) have a continuous probability density function (PDF) and are a mixture of multivariate Gaussian (normal) distributions, expressed (Lee, Kawahara, and Shikano 2001) as b v c exp v v j jk M jk jk T jk jk ( ) ( ) \| \| ( ) ( ) / / = - - - é ëê ù ûú é - 1 2 1 2 2 1 2 1 p s m s m ë ê ê ù û ú ú =å , k M 1 (11-6) b v c exp v v j jk M jk jk T jk jk ( ) ( ) \| \| ( ) ( ) / / = - - - é ëê ù ûú é - 1 2 1 2 2 1 2 1 p s m s m ë ê ê ù û ú ú =å , k M 1 (11-6) where ×( ) T denotes transpose, and where ×( ) T denotes transpose, and cjk ³ 0 & c jk = =å 1 1 k M sjk= covariance matrix of the kth mixture component of the jth state mjk = mean vector of the kth mixture component of the jth state v = observation vector M = number of dimensions of an observation with a multivariate Gaussian distribution M = number of dimensions of an observation with a multivariate Gaussian distribution qjk = (sjk, mjk) = Gaussian components qjk = (sjk, mjk) = Gaussian components hjk = drift factor of the kth mixture component of the jth state ljk = (qjk, cjk, hjk) = user profile components ljk = (qjk, cjk, hjk) = user profile components 231 Hidden States (Source: Khanna and Liu 2006) Hidden States Hidden states S = - { , , , , } S S S S N N 1 2 1  are a set of states that are not visible, but each state randomly generates a mixture of the M observations (or visible states O). The probability of the subsequent state depends only on the previous state. The complete model is defined by the following probabilities: transition probability matrix A = aij, where aij = p(Si\|Sj); observation probability matrix B = (bi(vm)), where bi(vm) = p(vm\|Si); and an initial probability vector p = p(Si). Observation probability represents an attribute that is observed with some probability if a particular failure state is anticipated. The model is represented by M = (A,B,p). A transition probability matrix is a square matrix of size equal to the number of states and stands for the state transition probabilities. p y p p p y ( , ,p) A transition probability matrix is a square matrix of size equal to the number of states and stands for the state transition probabilities. p The observation probability distribution is a nonsquare matrix whose dimensions equal the number of states by number of observables. This distribution represents the probability of an observation for a given state. The IDS depicted in Figure 11-15 uses these states: • Normal (N) state indicates profile compliance. • Hostile intrusion attempt (HI) indicates a hostile intrusion attempt that is in p This is typical of an external agent trying to bypass the system security. • Friendly intrusion attempt (FI) denotes a nonhostile intrusion attempt that is in progress. This is typical of an internal agent trying to bypass the system security. • Intrusion in progress (IP) signals an intrusion activity that is setting itself up. This includes attempts to access privileged resources and acceleration in resource usag • Intrusion successful (IS) signifies a successful intrusion. Successful intrusion will be accompanied by unusual resource usage (CPU, memory, I/O activity, and so on). 232 Chapter 11 ■ Machine Learning in Action: Examples Figure 11-15. HMM model, with five intrusion states and four Gaussian distributions for each state; each Gaussian distribution can be represented as the mixture component of an observation. (Source: Khanna and Liu 2006) Figure 11-15. HMM model, with five intrusion states and four Gaussian distributions for each state; each Gaussian distribution can be represented as the mixture component of an observation. Chapter 11 ■ Machine Learning in Action: Examples Chapter 11 ■ Machine Learning in Action: Examples At the same time, software instrumentation is also required to sample software- related measurements, such as session activity, system call usage between various processes and applications, file system usage, and swap-in/swap-out usage. Most operating systems support these hooks in the form of process tracking (such as process ID [PID], in UNIX). Combinations of these fast-acting hooks with sampling capability are clustered to enact an observation. Data clustering: Observation data are dependent on the aggregation of events that are active. For instance, a resource fault event generated by a resource usage engine is further categorized as a fault type, such as a page fault. Page faults count, and invalid page faults in a sampled interval represent instances of measurement (m1,m2). An observation (emission) can be a set of correlated measurements but is represented by a single probability distribution function. Each of these measurements carries different weights, as in multivariate Gaussian distribution. For example, disk I/O usage may be related to network I/O usage because of the network file system (NFS). Such a relationship is incorporated into the profile, for the completeness of the observation, and reduces the dimensionality, for effective runtime handling. Classifier: Observation data are analyzed for the purpose of subclassification as an appropriate attack state in a profile driven by different probability distribution parameters. Once the appropriate attack state is identified, an attention event is generated to initiate a corrective or logging action. Observations are also analyzed for concept drift to compensate for changes in user (or attack) behavior. Therefore, one of the objectives of the IC engine (see Figure 11-16) is to build a classifier for j (attack states) that has a posterior probability p(j\|v) close to unity for one value of j and close to 0 for all the others, for each realization. This can be obtained by minimizing the Shannon entropy, given observed data v, which can be evaluated for each observation as (11-7) E p j v p j v j M = - =å ( \| )log( ( \| )). 1 Each IC engine samples its observations independently of other observations (or emissions). Whenever it suspects an abnormal activity, it triggers an alert, which causes an evaluation of the most likely state. Intrusion Detection System Architecture In ad hoc networks an IDS is deployed at the nodes to detect the signs of intrusion locally and independently of other nodes, instead of using routers, gateways, or firewalls. In this section, we define components of the IDS that cooperate with each other to predict an attack state. p p After the model is trained, it enters a runtime state, in which it examines and classifies each valid observation. The model then decides to add the observation to a profile update, reject it, or mark it “unclassified.” This decision is important, because a drift in the user’s normal behavior may represent an attack situation. An unclassified observation is monitored for classification in the future. This observation will later be rejected as a noise or classified as a valid state, based on the trending similarity between unclassified states tending toward a certain classification and on feedback from the state machine resulting from other, independent observations. Various components of an IDS are as follows: Profile estimator (PE): The PE is responsible for maintaining/reestimating user profiles, classifying an observation as an attack state, triggering an alert upon detecting a suspicious observation, or acting on the HMM feedback for reestimation of a profile. User profile data consist of PDF parameters l s m h jk jk jk jk jk c = ( , , , ) , where j represents the intrusion state, and k stands for the GMM mixture component. A new observation is evaluated against this profile, which results in its classification and drift detection. Instrumentation: Instrumentation produces event data, which are processed and used by a clustering agent to estimate the profile. Component identification and measurements involve setup to discern whether events should be sampled at regular intervals or whether notification (or an alert) should be generated as an event vector upon recording changes in pattern. The sensor data should be able to analyze data, either as they are collected or afterward, and to provide real-time alert notification for suspected intrusive behavior. This will require fast-acting silicon hooks that are capable of identifying, counting, thresholding, timestamping, eventing, and clearing an activity. Examples of such hooks are performance counters, flip counters (also called transaction counters), header sniffers, fault alerts (page faults, and so on), and bandwidth usage monitors. 233 Chapter 11 ■ Machine Learning in Action: Examples As the system changes its active behavior, the profile corresponding to that behavior is updated to avoid false-positive evaluations by reevaluating the model parameters, using continuous estimation mechanisms in real time. New HMM parameters are evaluated again against the historical HMM parameters by comparing the entropy of the old and the retrained models. The expectation maximization (EM) algorithm (Moon 1996) provides a general approach to the problem of maximum likelihood estimation (MLE) of parameters in statistical models with variables that are not observed. The evaluation process yields a parameter set, which the algorithm uses to assign observation points to new states. The computational complexity of the EM algorithm for GMMs is O(i × ND2), where i is the number of iterations performed, N is the number of samples, and D is the state dimensionality. A common implementation choice is the k-means algorithm, in which k clusters are parameterized by their centroids, with a complexity of O(kND). A number of other algorithms can also be used, including x-means clustering (Pelleg and Moore 2000), which reduces the complexity to O(D). 234 Chapter 11 ■ Machine Learning in Action: Examples Figure 11-16. IC engine. Reestimation of the profile uses an observation classifier and HMM feedback to the profile. The profile manager triggers an attention event if the observation classifies as an attack state or cannot be classified (U). An attention event initiates an HMM state sequence prediction, based on other, continuous observations (dotted arrows), extracted in conjunction with profiles and state transition probabilities. (Source: Khanna and Liu 2006) Figure 11-16. IC engine. Reestimation of the profile uses an observation classifier and HMM feedback to the profile. The profile manager triggers an attention event if the observation classifies as an attack state or cannot be classified (U). An attention event initiates an HMM state sequence prediction, based on other, continuous observations (dotted arrows), extracted in conjunction with profiles and state transition probabilities. (Source: Khanna and Liu 2006) Concept drift detector (CDD): This module detects and analyzes the concept drifting (Widmer and Kubat 1996) in the profile, when the training dataset alone is not sufficient, and the model (profile) needs to be updated continually. When there is a time-evolving concept drift, using old data unselectively helps if the new concept and old concept still have consistencies and if the amount of old data chosen arbitrarily happens to be right (Fan 2004). Chapter 11 ■ Machine Learning in Action: Examples Chapter 11 ■ Machine Learning in Action: Examples where ajkt is the KL divergence measure, q jkt ’ is the new Gaussian component, and qjkt is the old Gaussian component of the kth mixture of the jth state at time t. You can evaluate divergence via a Monte Carlo simulation, using the law of large numbers (Grimmett and Stirzacker 1992), which draws an observation vi from the estimated Gaussian component q jkt ’ , computes the log ratio, and averages this over M samples as a q q jk i M j i jkt j i jkt M b v b v » æ è çç ö ø ÷÷ =å 1 1 log ( \| ) ( \| ) . ’ a q q jk i M j i jkt j i jkt M b v b v » æ è çç ö ø ÷÷ =å 1 1 log ( \| ) ( \| ) . ’ (11-9) (11-9) KL divergence data calculated in the temporal domain are used to evaluate the speed of the drift (also called the drift factor) (0 £ h £ 1). These data are then used to assign weights to the historical parameters, which are in turn used for reprofiling. Feedback engine (FE): This component is responsible for feeding back the current state information to the PE. The current state information is reevaluated using the current PDF model parameters. This reevaluated state information is then used for improving the descent algorithm for finding the MLE. Chapter 11 ■ Machine Learning in Action: Examples This requires an efficient approach to data mining that aids in selecting a combination of new and old data (historical) to make an accurate reprofiling and further classification. The mechanism used is the Kullback-Leibler (KL) divergence (Kullback and Leibler 1951), in which relative entropy measures the kernel distance between two probability distributions of generative models. The KL divergence is also the gain in Shannon information that occurs in going from the a priori to the posteriori, expressed as (11-8) a q q jkt j jkt j jkt KL b v b v = ( ( \| ), ( \| )), ’ 235 Profiles and System Considerations In this section, we look at events that form input to the profile structure. We define the features as processed observations derived from one or more temporal input events, using a processor function. Exploiting temporal sequence information of events leads to better performance (Ghosh, Schwartzbard, and Schata 1999) of the profiles that are defined for individual users, programs, or classes. Abnormal activity in any of the following forms is an indicator of an intrusion or a worm activity: • CPU activity is monitored by sampling faults, interprocessor interrupt (IPI) calls, context switches, thread migrations, spins on locks, and usage statistics. • Network activity is monitored by sampling input error rate, collision rate, remote procedure call (RPC) rejection rate, duplicate acknowledgment (DUPACK), retransmission rate, time-out rate, refreshed authentications, bandwidth usage, active connections, connection establishment failure, header errors and checksum failures, and so on. • Interrupt activity is monitored by sampling device interrupts (nontimer). • I/O utilization is monitored by sampling the I/O requests’ average queue lengths and busy percentages. • Memory activity is monitored by sampling memory transfer rate, page statistics (reclaim rate, swap-in rate, swap-out rate), address translation faults, and pages scanned and paging averages over a short interval. • File access activity is monitored by sampling file access frequency, file usage overflow, and file access faults. • System process activity is monitored by sampling processes with inappropriate process priorities, CPU and memory resources used by processes, processes’ length, processes that are blocking I/Os, zombie processes, and the command and terminal that generated the process. 236 Chapter 11 ■ Machine Learning in Action: Examples • System fault activity represents an illegal activity (or a hardware error) and is sampled to detect abnormality in the system usage. Rare faults are a result of bad programming, but spurts of activity indicate an attack. • System call activity involves powerful tools for obtaining computer system privileges. An intrusion is accompanied by the execution of unexpected system calls. If the system call execution pattern of a program can be collected before it is executed and is used for comparison with the runtime system call execution behavior, then unexpected execution of system calls can be detected. During real-time operation a pattern-matching algorithm is applied to match on the fly the system calls generated by the process examined with entries from the pattern table. Profiles and System Considerations Based on how well the matching can be done, it is decided whether the sequence of system calls represents normal or anomalous behavior (Wespi, Dacier, and Debar 1999). • Session activity is monitored by sampling logging frequency, unsuccessful logging attempts, session durations, session time, and session resource usages. • Session activity is monitored by sampling logging frequency, unsuccessful logging attempts, session durations, session time, and session resource usages. Sensor Data Measurements Sensor data are collected and statistically processed so that they can be used to measure historical trends, capture unique patterns, and visualize abnormal behavior. The data are classified and then analyzed for use in prediction of abnormal activity. Sensor data measurements comprise various components that perform either a statistical processing function or an infrastructure function (such as generating priority events), as follows: Sensor data measurement (SDM) hooks reduce system complexity and increase the possibility of software reuse (see Figure 11-17). SDM accelerates the combined measurement of the clustered components with an ability to send alerts, using a system’s policy. Hardware and software act as glue between transducers and a control program that is capable of measuring the event interval and the event trend and of generating alerts upon deviation from normal behavior, as defined by system policy. The SDM hardware exists as a multiple-instance entity that receives alert vectors from various events spread throughout the system. A set of correlated events that forms a cluster is registered against a common SDM instance. This instance represents the Bayes optimal decision boundaries between a set of pattern classes, with each class represented by an SDM instance and associated with a reference vector. Each SDM instance can trend and alert and integrates the measurements from the event sensors into a unified view. Cluster trending analysis is very sensitive to small signal variations and capable of detecting the abnormal signals embedded in the normal signals via supervised self-organizing maps (Kohonen 1995), using learning vector quantization (LVQ). The strategy behind LVQ is to effectively train the reference vectors to define the Bayes optimal decision boundaries between the SDM classes registered to an SDM instance. 237 Chapter 11 ■ Machine Learning in Action: Examples Chapter 11 ■ Machine Learning in Action: Examples Figure 11-17. Illustration of the relationship between events (circles), sensors (SDM), and classifiers (ODC). Clusters of events (marked by common colors) are registered to an SDM. Upon evaluating the event properties, the SDM generates an event to ODC, which is responsible for classification, trend analysis, and drift calculation. Classification feedback acts as a mechanism for reestimation. (Source: Khanna and Liu 2006) Figure 11-17. Illustration of the relationship between events (circles), sensors (SDM), and classifiers (ODC). Clusters of events (marked by common colors) are registered to an SDM. Summary As more and more data are expressed digitally in an unstructured form, new computing models are being developed to process that data in a meaningful manner. Machine learning methods can be applied to synthesize the fundamental relationship between the unstructured datasets and information through systematic application of algorithms. Machine learning exploits the power of generalization that is an inherent and essential component of concept formation through human learning. The machine learning methodology can be applied to develop autonomous systems, using modular functions to enact an intelligent feedback control system. This approach can play a critical role in modeling the knowledge function, which is used to enact a stable and viable system. This chapter presented three examples of techniques used in machine learning. The first example employed the concept of workload fingerprinting, using phase detection to establish observable characteristics exhibiting spatial uniformity and distinctiveness. The second example was based on the concept of optimal, dynamic energy distribution among multiple compute elements. This example proposed phases as compressed representative output that can be used in conjunction with any other statistical parameter to predict future behavior. The last example suggested use of the IDS mechanism for detecting intrusions by monitoring unusual activities in the system with reference to the user’s profile and evolving trends. Each example used an application-specific grouping of machine learning techniques to achieve the desired goals. Chapter 11 ■ Machine Learning in Action: Examples Chapter 11 ■ Machine Learning in Action: Examples Sensor Data Measurements Upon evaluating the event properties, the SDM generates an event to ODC, which is responsible for classification, trend analysis, and drift calculation. Classification feedback acts as a mechanism for reestimation. (Source: Khanna and Liu 2006) Observation data classifier (ODC) hooks accelerate the classification of an observation alert generated by SDM. This is multiple-instance hardware capable of handling multiple observations in parallel. Each registered observation instance of the ODC hook consists of Gaussian probability distribution parameters for each state. Upon receiving an SDM alert, the corresponding observation is then classified as a specific state. Reclassification of observed data may cause changes in the probability distribution parameters corresponding to the state. ODC can maintain the historical parameters, which are used to calculate concept drift properties, such as drift factor and drift speed, using the KL drift detector. The GMM calculator calculates the probability of the Gaussian mixture for each state, using the current observation. During system setup, event vectors are registered against SDM instances. These events are clustered and processed in their individual SDMs. The processing includes trigger properties, which initiate an observation. These observations then act as single-dimensional events that are registered to their ODC. Upon receiving the trigger, ODC performs reclassification of the observation derived from the trigger and calculates the concept drift. This hardware is activated upon a trigger by its parent. 238 References Becker, Suzanna, and Geoffrey E. Hinton. “Self-Organizing Neural Network that Discovers Surfaces in Random-Dot Stereograms.” Nature 355, no. 6356 (1992): 161–163. Boser, Bernhard E., Isabelle M. Guyon, and Vladimir N. Vapnik. “A Training Algorithm for Optimal Margin Classifiers.” In COLT ’92: Proceedings of the Fifth Annual Workshop on Computational Learning Theory, 144–152. New York: ACM, 1992. Fan, Wei. “Systematic Data Selection to Mine Concept-Drifting Data Streams.” In KDD ’04: Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 128–137. New York: ACM, 2004. Ghosh, Anup K., Aaron Schwartzbard, and Michael Schatz. “Learning Program Behavior Profiles for Intrusion Detection.” In ID’ 99: Proceedings of the 1st Conference on Intrusion Detection and Network Monitoring. Berkley, CA: USENIX, 1999. Grimmett, Geoffrey, and David Stirzaker. Probability and Random Processes. Oxford: Clarendon, 1992. Khanna, Rahul, and Huaping Liu. “System Approach to Intrusion Detection Using Hidden Markov Model.” In Proceedings of the 2006 International Conference on Wireless Communications and Mobile Computing, 349–354. New York: ACM, 2006. Kohonen, Teuvo. “Self-Organizing Maps, Third Edition.” Berlin: Springer, 1995. Kullback, Solomon, and Richard A. Leibler. “On Information and Sufficiency.” Annals of Mathematical Statistics 22, no. 1 (1951): 79–86. Lee, Akinobu, Tatsuya Kawahara, and Kiyohiro Shikano. “Gaussian Mixture Selection Using Context- Independent HMM.” In Proceedings of the 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing, 69–72. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2001. Moon, Todd K. “The Expectation-Maximization Algorithm.” IEEE Signal Processing Magazine 13, no. 6 (1996): 47–60. 239 Chapter 11 ■ Machine Learning in Action: Examples Chapter 11 ■ Machine Learning in Action: Examples Pelleg, Dan, and Andrew W. Moore. “X-Means: Extending K-Means with Efficient Estimation of the Number of Clusters.” In ICML ’00: Proceedings of the Seventeenth International Conference on Machine Learning, 727–734. San Francisco: Morgan Kaufmann, 2000. iddha, Suresh. “Multi-Core and Linux Kernel.” Technical report, Intel Open Source Technology C Wespi, Andreas, Marc Dacier, and Hervé Debar. “An Intrusion-Detection System Based on the Teiresias Pattern-Discovery Algorithm.” In EICAR Proceedings 1999, edited by Urs E. Gattiker, Pia Pedersen, and Karsten Petersen, 1–15. Aalborg, Denmark: Tim-World, 1999. Widmer, Gerhard, and Miroslav Kubat. “Learning in the Presence of Concept Drift and Hidden Contexts.” Machine Learning 23, no. 1 (1996): 69–101. 240 Index See Asymmetrical and lower-bounded SVR (ALB-SVR) Alternating-least-squares with weighted-l- regularization (ALS-WR), 34 Ant colony optimization (ACO) algorithm, 111 Apriori, 12 Arabic automatic speech recognition, 161 Arabic Spoken Digit Dataset, 162 Arithmetic logical unit (ALU), 226 Artificial bee colony (ABC) algorithm employed bees, 115 load balancing, 116 onlooker bee, 115 principal components, 115 principal factors, 116 scout bee, 115i training and backpropagation algorithm chain rule, 134 feedback, 133 feedforward, 133 initialization, 133 Asymmetrical and lower-bounded SVR (ALB-SVR) Huber insensitive loss function, 77 power estimates, 78 validation, 77 Asymmetrical and lower-bounded SVR (ALB-SVR) Huber insensitive loss function, 77 power estimates, 78 validation, 77 Autoassociative memory, 137 AutoMate architecture, 110 Autonomic nervous system (ANS), 106 Autoassociative memory, 137 AutoMate architecture, 110 Autonomic nervous system (ANS), 106 Index A AdaBoost, 13 Adaptive weighted genetic algorithm (AWGA) method, 224 ALB-SVR. See Asymmetrical and lower-bounded SVR (ALB-SVR) Alternating-least-squares with weighted-l- regularization (ALS-WR), 34 Ant colony optimization (ACO) algorithm, 111 Apriori, 12 Arabic automatic speech recognition, 161 Arabic Spoken Digit Dataset, 162 Arithmetic logical unit (ALU), 226 Artificial bee colony (ABC) algorithm employed bees, 115 load balancing, 116 onlooker bee, 115 principal components, 115 principal factors, 116 scout bee, 115 Artificial immune system (AIS) attributes, 118 clonal selection mechanisms, 118 encoding, 118 mutation, 119 negative selection mechanisms, 118 reinforced learning mechanism, 118 selection, 119 similarity measure, 118 Artificial neural networks (ANNs), 40, 106 activation function, 130 basic structure of, 129 bias, 129 dendrite’s structure, 129 hidden neurons, 133 layer of neurons, 131 matrix notation, 131 network output, 132 Rosenblatt perceptron structure, 128 three-layer ANN, 132 A AdaBoost, 13 Adaptive weighted genetic algorithm (AWGA) method, 224 ALB-SVR. See Asymmetrical and lower-bounded SVR (ALB-SVR) Alternating-least-squares with weighted-l- regularization (ALS-WR), 34 Ant colony optimization (ACO) algorithm, 111 Apriori, 12 Arabic automatic speech recognition, 161 Arabic Spoken Digit Dataset, 162 Arithmetic logical unit (ALU), 226 Artificial bee colony (ABC) algorithm employed bees, 115 load balancing, 116 onlooker bee, 115 principal components, 115 principal factors, 116 scout bee, 115 Artificial immune system (AIS) attributes, 118 clonal selection mechanisms, 118 encoding, 118 mutation, 119 negative selection mechanisms, 118 reinforced learning mechanism, 118 selection, 119 similarity measure, 118 Artificial neural networks (ANNs), 40, 106 activation function, 130 basic structure of, 129 bias, 129 dendrite’s structure, 129 hidden neurons, 133 layer of neurons, 131 matrix notation, 131 network output, 132 Rosenblatt perceptron structure, 128 three-layer ANN, 132 training and backpropagation algorithm chain rule, 134 feedback, 133 feedforward, 133 initialization, 133 Asymmetrical and lower-bounded SVR (ALB-SVR) Huber insensitive loss function, 77 power estimates, 78 validation, 77 Autoassociative memory, 137 AutoMate architecture, 110 Autonomic nervous system (ANS), 106 A AdaBoost, 13 Adaptive weighted genetic algorithm (AWGA) method, 224 ALB-SVR. Backpropagation, 26 p p g , Bacterial foraging optimization (BFO) algorithm chemotaxis, 117 E. coli, 117 Ball k-means algorithm, 29 Basic input/output system (BIOS), 213 Bayesian belief propagation (BBP), 168 Bayesian linear regression discriminant vs. generative models, 75 Gaussian conditional probability distributions, 75 model parameters, 74 Moore-Penrose pseudoinverse, 74 multivariate Student’s t-distribution, 74 Berkson’s paradox, 135 Big data characteristics, 19 detecting fraudulent behavior, 20 dynamic coupon system, 20 failure root cause detection, 20 shopping behavior analysis, 20 standard database management systems, 19 workload resource tuning and selection, 21 Bioinspired computing AIS (see Artificial immune system (AIS)) ANS, 106 p p g , Bacterial foraging optimization (BFO) algorithm chemotaxis, 117 E. coli, 117 Ball k-means algorithm, 29 Basic input/output system (BIOS), 213 Bayesian belief propagation (BBP), 168 Bayesian linear regression discriminant vs. G Gaussian mixture model (GMM), 93, 230, 238 Genetic algorithm (GA), 190 Genetic programming (GP), 191 Gibbs distribution, 137 Graphics processing unit (GPU), 55, 140, 142 H Backpropagation, 26 generative models, 75 Gaussian conditional probability distributions, 75 model parameters, 74 Moore-Penrose pseudoinverse, 74 multivariate Student’s t-distribution, 74 Berkson’s paradox, 135 Big data characteristics, 19 detecting fraudulent behavior, 20 dynamic coupon system, 20 failure root cause detection, 20 shopping behavior analysis, 20 standard database management systems, 19 workload resource tuning and selection, 21 Bioinspired computing AIS (see Artificial immune system (AIS)) ANS, 106 , Artificial immune system (AIS) attributes, 118 clonal selection mechanisms, 118 encoding, 118 mutation, 119 negative selection mechanisms, 118 reinforced learning mechanism, 118 selection, 119 similarity measure, 118i ( ) y Artificial neural networks (ANNs), 40, 106 activation function, 130 basic structure of, 129 bias, 129 dendrite’s structure, 129 hidden neurons, 133 layer of neurons, 131 matrix notation, 131 network output, 132 Rosenblatt perceptron structure, 128 three-layer ANN, 132 Artificial neural networks (ANNs), 40, 106 activation function, 130 basic structure of, 129 bias, 129 dendrite’s structure, 129 hidden neurons, 133 layer of neurons, 131 matrix notation, 131 network output, 132 Rosenblatt perceptron structure, 128 three-layer ANN, 132 241 ■ index BFO algorithm (see Bacterial foraging optimization (BFO) algorithm) datacenter optimization AutoMate architecture, 110 SelfLet architecture, 110 self-organization algorithm, 110 datacenters algorithm model, 121 control system, 120 load balancing, 121 thermal optimization, 120 workload characterization, 120 evolvable hardware (EHW), 106 heuristics, 105 networking advancements, 108 AntHocNet algorithm, 109 epidemic spreading mechanism, 109 resource-constrained sensors, 109 SI (see Swarm intelligence (SI)) Body mass index (BMI), 23 Boltzmann machines (BMs), 137 Bioinspired computing (cont.) BFO algorithm (see Bacterial foraging optimization (BFO) algorithm) datacenter optimization AutoMate architecture, 110 SelfLet architecture, 110 self-organization algorithm, 110 datacenters algorithm model, 121 control system, 120 load balancing, 121 thermal optimization, 120 workload characterization, 120 evolvable hardware (EHW), 106 heuristics, 105 networking advancements, 108 AntHocNet algorithm, 109 epidemic spreading mechanism, 109 resource-constrained sensors, 109 SI (see Swarm intelligence (SI)) Body mass index (BMI), 23 Boltzmann machines (BMs), 137 Bioinspired computing (cont.) Bioinspired computing (cont.) exponential function, 155 image segmentation dataset, 157 ISOLET dataset, 157 letter recognition dataset, 156 multiple features dataset, 157 neuron weight, random node, 154 PENDIGITS dataset, 157 exponential function, 155 image segmentation dataset, 157 ISOLET dataset, 157 letter recognition dataset, 156 multiple features dataset, 157 neuron weight, random node, 154 PENDIGITS dataset, 157 Cortical learning algorithm (CLA) SDR, 171 spatial pooler, 172 temporal pooler, 173 Cross-entropy (CE) cost functions, 158–159 Cortical learning algorithm (CLA) SDR, 171 spatial pooler, 172 temporal pooler, 173 C (C ) f i Cross-entropy (CE) cost functions, 158–159 Cross-entropy (CE) cost functions, 158–159 D C Cache quality of service (CQoS), 106 C4.5 classifiers, 10 Classification and regression tree (CART), 15 Cloud-based networking (CBN), 108 Collaborative filtering (CF), 22 Concept drift detector (CDD), 235 Content-based image retrieval (CBIR) system, 174 Continuous observation HMM (CHMM), 93 Contrastive divergence (CD), 137 Correlation-based feature selection (CFS) algorithm, 214 Cortical algorithms (CAs), 158 confusion matrices, 162 entropy-based weight update rule, 159 experimental validation, 160 structure cortical network connectivity, 150 hypercolumn, 149 minicolumn, 149 nomenclature conventions, 151 nonlinear activation function, 152 weight matrix, 151 training supervised feedback, 153 unsupervised feedforward, 152 workflow for, 156 weight update process abalone dataset, 157 computational cost, 155 Cache quality of service (CQoS), 106 C4.5 classifiers, 10 Classification and regression tree (CART), 15 Cloud-based networking (CBN), 108 Collaborative filtering (CF), 22 Concept drift detector (CDD), 235 Content-based image retrieval (CBIR) system, 17 Continuous observation HMM (CHMM), 93 Contrastive divergence (CD), 137 Correlation-based feature selection (CFS) algorithm, 214 Cortical algorithms (CAs), 158 confusion matrices, 162 entropy-based weight update rule, 159 experimental validation, 160 structure cortical network connectivity, 150 hypercolumn, 149 minicolumn, 149 nomenclature conventions, 151 nonlinear activation function, 152 weight matrix, 151 training supervised feedback, 153 unsupervised feedforward, 152 workflow for, 156 weight update process abalone dataset, 157 computational cost, 155 weight update process abalone dataset, 157 computational cost, 155 242 ■ Index leaky integrate-and-fire model, 177 postsynaptic neuron, 179 presynaptic neuron, 179 pSNN, 181 rank coding, 178 reservoir computing, 181 spike coding, 178 SpikeProp, 179–180 SSTD, 175 Thetalearning rule, 179 Thorpe’s model, 178 F False negative (FN), 53 False positive (FP), 53 Feature extraction, 22, 140 Feature selection, 22 Feedback engine (FE), 236 Field-programmable gate arrays (FPGAs), 106, 142 Fingerprinting, 207 Fixed-density distributed representation (FDR), 169 Fuzzy c-means (FCM). Backpropagation, 26 See Fuzzy k-means Fuzzy datasets, 21 Fuzzy k-means, 28 False negative (FN), 53 False positive (FP), 53 Feature extraction, 22, 140 Feature selection, 22 Feedback engine (FE), 236 Field-programmable gate arrays (FPGAs), 106, 142 Fingerprinting, 207 Fixed-density distributed representation (FDR), 169 Fuzzy c-means (FCM). See Fuzzy k-means Fuzzy datasets, 21 Fuzzy k-means, 28 curriculum learning, 141 definition, 128 feature extraction, 140 Hebbian learning, 128 implementations, 141 training algorithms layer-wise training, 138 sequential training, 138 up–down algorithm, 138, 140 Degree of membership, 21 Discrete Fourier transform (DFT), 140 DVFS multiobjective discrete particle swarm optimization (DVFS-MODPSO), 115 Dynamic random access memory (DRAM), 218, 226 Dynamic synaptic evolving spiking neural network (deSNN), 181 G Gaussian mixture model (GMM), 93, 230, 238 Genetic algorithm (GA), 190 Genetic programming (GP), 191 Gibbs distribution, 137 Graphics processing unit (GPU), 55, 140, 142 H E Echo state machine (ESM), 181 Epidemic spreading mechanism, 109 Error matrix, 2 Error rate, 2 Euclidean distance, 36 Evolutionary algorithms (EAs), 224 diversity improvement, 192 elitism, 192 fitness, 192 GA, 190 GP, 191 mating selection, 189 MOGA, 194 NPGA, 194 NSGA, 195 PAES, 199 PESA, 200 SPEA, 196 VEGA, 193 weighted-sum method, 192 Evolving spiking neural network (eSNN), 180 Expectation maximization (EM) algorithm, 12, 234 E E Echo state machine (ESM), 181 Epidemic spreading mechanism, 109 Error matrix, 2 Error rate, 2 Euclidean distance, 36 Evolutionary algorithms (EAs), 224 diversity improvement, 192 elitism, 192 fitness, 192 GA, 190 GP, 191 mating selection, 189 MOGA, 194 NPGA, 194 NSGA, 195 PAES, 199 PESA, 200 SPEA, 196 VEGA, 193 weighted-sum method, 192 Evolving spiking neural network (eSNN), 180 Expectation maximization (EM) algorithm, 12, 234 243 ■ index evaluation backward algorithm, 88 forward algorithm, 87 scaling, 88 features, 81 health states progress, 86 hidden states and observed states, 84 IDS, 230, 232 learning, 86 Baum-Welch algorithm, 90 maximum likelihood estimation (MLE), 91 model evaluation, 25 model training, 25 monitoring and observations, 95 parameters, 85 path decoding, 25 phase detection emission block (EB), 99 model reduction block (MRB), 99 parameter estimation block (PEB), 101 phase predictor block (PPB), 102 sensor block, 97 state forecasting block, 103 system adaptation, 103 training block (TB), 100 trellis representation, 85 workload phase recognition CHMM, 95 CPU utilization vs. phase model, 96 feature extraction techniques, 97 optimal system operation, 95 predictive systems, 95 program execution, 94 systems attributes, 96 ( ) idden Markov model (HMM) (cont.) evaluation backward algorithm, 88 forward algorithm, 87 scaling, 88 features, 81 health states progress, 86 hidden states and observed states, 84 IDS, 230, 232 learning, 86 Baum-Welch algorithm, 90 maximum likelihood estimation (MLE), 91 model evaluation, 25 model training, 25 monitoring and observations, 95 parameters, 85 path decoding, 25 phase detection emission block (EB), 99 model reduction block (MRB), 99 parameter estimation block (PEB), 101 phase predictor block (PPB), 102 sensor block, 97 state forecasting block, 103 system adaptation, 103 training block (TB), 100 trellis representation, 85 workload phase recognition CHMM, 95 CPU utilization vs. phase model, 96 feature extraction techniques, 97 optimal system operation, 95 predictive systems, 95 Hidden Markov model (HMM) (cont.) synaptic connections, 170 temporal pooler, 173 HMM. See Hidden Markov model (HMM) Hodgkin-Huxley model, 176 Hyperbolic tangent, 26 Hidden Markov model (HMM) (cont.) Independent and identically distributed (iid), 39 Integrate-and-fire model, 176 International Conference on Data Mining (ICDM), 10 Internet of Things (IOT), 108 Intrusion checkpoints (ICs), 230 Intrusion detection system (IDS) method ad hoc nodes, 230 architecture CDD, 235 classifier, 234 data clustering, 234 FE, 236 IC engine, 234 instrumentation, 233 profile estimator, 233 runtime state, 233 valid state, 233 hidden states, 232 HMM, 230, 232 malicious node, 230 metric, 230 observed states, 231 Isolated Letter Speech Recognition (ISOLET) dataset, 157 Item-based collaborative filtering, 34 Izhikevich model, 177 J Jaccard similarity coefficient, 36 K Karush-Kuhn-Tucker (KKT), 44, 71 Kernel SVR, 72 k-means, 10 k-means clustering, 27 k-nearest neighbors (k-NN), 14 Knee-cut ordinal optimization–inspired support vector machine (KCOOSVM), 55 Knee-cut support vector machine (KCSVM), 55 Knowledge discovery classification, 21 clustering, 22 collaborative filtering, 22 Machine learning Kullback-Leibler (KL) divergence, 235 L Lagrangian relaxation, 42 Lanczos algorithm, 32 Leaky integrate-and-fire model, 177 Learning vector quantization (LVQ), 237 Liquid state machine (LSM), 181 Literary Arabic, 161 Locality-constrained linear coding (LLC), 175 Local mixture–based Support vector machine (LMSVM), 55 Logistic regression, 22 Logistic sigmoid function, 26 M Machine learning (ML) accuracy, 2 algorithms AdaBoost, 13 Apriori, 12 CART, 15 C4.5 classifiers, 10 expectation–maximization (EM), 12 inductive inference, 9 k-means, 10 k-nearest neighbors (k-NN), 14 naive Bayes model, 15 PageRank, 13 process, 5 RL methodology, 8 semi-supervised learning, 8 supervised learning, 6 SVMs, 11 transductive learning, 9 unsupervised learning algorithms, 7 analytical function, 210 autonomic system, 210 characteristics, 1 classification algorithms HMM, 24 logistic regression, 22 MLP, 25 random forest, 24 classifier, 2 clustering algorithms fuzzy k-means, 28 k-means clustering, 27 streaming k-means, 28 collaborative filtering ALS-WR, 34 item-based, 34 user-based, 33 confusion matrix, 2 cost, 3 cross-validation, 3 cybernetic systems, 210 data mining, 3 data mining research problems, 15 dataset, 3 definition, 1, 209 dimension, 3 dimensionality reduction Lanczos algorithm, 32 PCA, 30 SVD, 29 dynamic energy allocation adjusting, 221 assessing, 221 autonomic solution, 222 feature selection, 222 Intel Xeon server, 221 less busy servers, 222 monitoring, 225 optimization planning, 224 power optimization, 222 selecting, 221 self-correcting, 222 self-regulating, 222 feature vector, 4 goal, 1 GMM calculator, 238 IDS (see Intrusion detection system (IDS) method) induction algorithm, 3 instance, 3 knowledge base, 209 knowledge discovery, 3 knowledge function, 210 model, 4 model training CPU power, 228 SLA, 229 SVM, 227 variation of demand, 227 variation of supply, 227 wall power, 228 workload conditions, 228 motor function, 210 ODC, 238 OLAP, 4 planning function, 210 profiles and system considerations CPU activity, 236 file access activity, 236 core machine algorithms, 21 dimensionality reduction, 22 machine learning. Machine learning Kullback-Leibler (KL) divergence, 235 core machine algorithms, 21 dimensionality reduction, 22 machine learning. Machine learning Kullback-Leibler (KL) divergence, 235 core machine algorithms, 21 dimensionality reduction, 22 machine learning. Machine learning Kullback-Leibler (KL) divergence, 235 L L Lagrangian relaxation, 42 Lanczos algorithm, 32 Leaky integrate-and-fire model, 177 Learning vector quantization (LVQ), 237 Liquid state machine (LSM), 181 Literary Arabic, 161 Locality-constrained linear coding (LLC), 175 Local mixture–based Support vector machine (LMSVM), 55 Logistic regression, 22 Logistic sigmoid function, 26 adjusting, 221 Independent and identically distributed (iid), 39 Integrate-and-fire model, 176 International Conference on Data Mining (ICDM), 10 Internet of Things (IOT), 108 Intrusion checkpoints (ICs), 230 Intrusion detection system (IDS) method ad hoc nodes, 230 architecture CDD, 235 classifier, 234 data clustering, 234 FE, 236 IC engine, 234 instrumentation, 233 profile estimator, 233 runtime state, 233 valid state, 233 hidden states, 232 HMM, 230, 232 malicious node, 230 metric, 230 observed states, 231 Isolated Letter Speech Recognition (ISOLET) dataset, 157 Item-based collaborative filtering, 34 Izhikevich model, 177 J Jaccard similarity coefficient, 36 K Karush-Kuhn-Tucker (KKT), 44, 71 Kernel SVR, 72 k-means, 10 k-means clustering, 27 k-nearest neighbors (k-NN), 14 Knee-cut ordinal optimization–inspired support vector machine (KCOOSVM), 55 Knee-cut support vector machine (KCSVM), 55 Knowledge discovery classification, 21 clustering, 22 collaborative filtering, 22 Independent and identically distributed (iid), 39 Integrate-and-fire model, 176 International Conference on Data Mining (ICDM), 10 Internet of Things (IOT), 108 Intrusion checkpoints (ICs), 230 Intrusion detection system (IDS) method ad hoc nodes, 230 architecture CDD, 235 classifier, 234 data clustering, 234 FE, 236 IC engine, 234 instrumentation, 233 profile estimator, 233 runtime state, 233 valid state, 233 hidden states, 232 HMM, 230, 232 malicious node, 230 metric, 230 observed states, 231 Isolated Letter Speech Recognition (ISOLET) dataset, 157 Item-based collaborative filtering, 34 Izhikevich model, 177 J Jaccard similarity coefficient, 36 K Karush-Kuhn-Tucker (KKT), 44, 71 Kernel SVR, 72 k-means, 10 k-means clustering, 27 k-nearest neighbors (k-NN), 14 Knee-cut ordinal optimization–inspired support vector machine (KCOOSVM), 55 Knee-cut support vector machine (KCSVM), 55 Knowledge discovery classification, 21 clustering, 22 collaborative filtering, 22 y p , training block (TB), 100 trellis representation, 85 workload phase recognition CHMM, 95 CPU utilization vs. phase model, 96 feature extraction techniques, 97 optimal system operation, 95 predictive systems, 95 program execution, 94 systems attributes, 96 workload phase recognition CHMM, 95 CPU utilization vs. phase model, 96 feature extraction techniques, 97 optimal system operation, 95 predictive systems, 95 program execution, 94 systems attributes, 96 y , Hierarchical temporal memory (HTM) algorithmic implementation, 171 Bayesian theory, 169 BBP, 168 binary outputs, 170 CBIR system, 174 cell/neuron model, 170 diabetic retinopathy, 175 distal dendrites, 170 FDR, 169 human traffic analysis, 174 LLC, 175 neocortex, 167 permanence, 170 proximal dendrites, 170 saliency maps, 174 SDR, 169, 171 spatial pooler, 172 support vector machine, 174 J Jaccard similarity coefficient, 36 K Karush-Kuhn-Tucker (KKT), 44, 71 Kernel SVR, 72 k-means, 10 k-means clustering, 27 k-nearest neighbors (k-NN), 14 Knee-cut ordinal optimization–inspired support vector machine (KCOOSVM), 55 Knee-cut support vector machine (KCSVM), 55 Knowledge discovery classification, 21 clustering, 22 collaborative filtering, 22 244 ■ Index core machine algorithms, 21 dimensionality reduction, 22 machine learning. M M Machine learning (ML) accuracy, 2 algorithms AdaBoost, 13 Apriori, 12 CART, 15 C4.5 classifiers, 10 expectation–maximization (EM), 12 inductive inference, 9 k-means, 10 k-nearest neighbors (k-NN), 14 naive Bayes model, 15 PageRank, 13 process, 5 RL methodology, 8 semi-supervised learning, 8 supervised learning, 6 SVMs, 11 transductive learning, 9 unsupervised learning algorithms, 7 analytical function, 210 autonomic system, 210 characteristics, 1 classification algorithms HMM, 24 logistic regression, 22 MLP, 25 random forest, 24 classifier, 2 clustering algorithms fuzzy k-means, 28 k-means clustering, 27 streaming k-means, 28 random forest, 24i classifier, 2 clustering algorithms clustering algorithms fuzzy k-means, 28 k-means clustering, 27 streaming k-means, 28 245 ■ index objective function space, 186, 187 Pareto optimality, 187 performance guarantees, 205 performance measurement, 188 power targets, 205 reducing thermal stresses, 205 resource utilization targets, 205 Multistage support vector machine (MSVM), 51 objective function space, 186, 187 Pareto optimality, 187 performance guarantees, 205 performance measurement, 188 power targets, 205 reducing thermal stresses, 205 resource utilization targets, 205 Multistage support vector machine (MSVM), 51 system fault activity, 237 schema, 4 SDM, 237 sensor function, 210 similarity matrix Euclidean distance, 36 Jaccard similarity coefficient, 36 Pearson correlation coefficient, 35 Spearman rank correlation coefficient, 35 state-determined system, 209 supervised learning, 4 unsupervised learning, 4 user-centric innovations, 1 viable system modeling, 211 workload fingerprinting (see Workload fingerprinting) Markov chain Monte Carlo (MCMC) algorithm, 13 Mating process, 189 MATLAB software, 155, 160 Maximum likelihood estimation (MLE), 23, 234 Mel frequency cepstral coefficients (MFCCs), 140, 160, 162 Membership function, 21 Message passing interface (MPI), 55 Modular DBN (M-DBN), 142 Multidimensional OLAP (MOLAP), 4 Multilayer perceptron (MLP) activation function, 26 deep learning, 27 definition, 25 error function, 26 fundamental component, 25 input features, 26 learning algorithm steps, 26 supervised-learning technique, 26 Multiobjective genetic algorithm (MOGA), 194 Multiobjective optimization, 185 decision space, 186 decision variable space, 186 definition, 186 dominance relationship nonsymmetrical, 188 transitive, 188 evolutionary algorithms (see Evolutionary algorithms (EAs)) objective functions, 206 Naive Bayes, 15 Natural language processing (NLP), 36, 141 Niched Pareto genetic algorithm (NPGA), 194 Niche-formation method, 194 Nondominated sorting genetic algorithm (NSGA), 195 NSGA-II, 201 initialization, 202 selection, 202 steps, 195 O Observation data classifier (ODC), 238 One-against-all (OAA), 50, 60 One-against-one (OAO), 50, 60 One-versus-the-rest. M See One-against-all (OAA) Online analytical processing (OLAP), 4 ( ), Multilayer perceptron (MLP) activation function, 26 deep learning, 27 definition, 25 error function, 26 fundamental component, 25 input features, 26 learning algorithm steps, 26 supervised-learning technique, 26 Multiobjective genetic algorithm (MOGA), 194 Multiobjective optimization, 185 decision space, 186 decision variable space, 186 definition, 186 dominance relationship nonsymmetrical, 188 transitive, 188 evolutionary algorithms (see Evolutionary algorithms (EAs)) objective functions, 206 Quadratic integrate and fire (QIF) neuron model, 179 Quality of service (QoS), 21, 218 246 ■ Index ■ Index R Random forest, 24 Recall rate (RR), 53 Receiver operating characteristic (ROC), 53 Reinforcement learning (RL) methodology, 8 Relational OLAP (ROLAP), 4 Restricted Boltzmann machines (RBMs) autoassociative memory, 137 CD, 137–138 Rosenblatt perceptron structure, 129 Running average power limit (RAPL), 226 R g y g ( ) algorithm flow, 196 clustering process, 198 definition, 196 fitness of solutions, 197 SPEA-II, 198 strength of solutions, 197 Structural risk minimization (SRM), 43 Sum product network (SPN), 142 Supervised-learning technique, 6, 26 Support vector data description (SVDD), 53 Support vector machines (SVMs), 11, 67, 127, 141, computational requirements, 54 geometric perspective, 39 hard-margin, 43 HWR complexity analysis, 61 feature extraction, 57 grid search algorithm, 59 hierarchical, three-stage, 58 label vs. true label, 59 OAA, 60 OAO, 60 offline sensing, 56 online recognition, 56 preprocessing, 56 recognition rate, 60 writer dependent, 56 writer independent, 56 imbalanced datasets confusion matrix, 52 error matrix/contingency matrix, 52 GS-SVM, 53 GSVM-RU, 53 majority class, 52–53 matching matrix, 52 minority class, 52 MinSVM, 54 ROC, 53 SMOTE, 54 SVDD, 53 WSD-SVM, 53 machine learning problems, 39 model training, 227 multiclass hierarchical SVM, 51 OAA, 50 OAO, 50 single, 51 properties error trends vs. M model index, 43 kernel technique, 42, 48 maximal margin classifier, 41 maximum margin separator, 42 S S Schmidhuber’s algorithm, 138 SelfLet architecture, 110 Semicontinuous HMM (SCHMM), 93 Semi-supervised learning, 8 Sensor data measurement (SDM), 237 Sensor hardware abstraction (SHA) layer, 225 Sequential minimal optimization (SMO) method, 54 Service-level agreements (SLAs), 21, 224, 229 Service-level objectives (SLO), 218 Session activity, 237 Single instruction, multiple data (SIMD), 226 Singular value decomposition (SVD), 29 Software-defined networking (SDN), 108 Sparse distributed representation (SDR), 169, 171 Spatio-and spectrotemporal data (SSTD), 175 Spearman Rank Correlation Coefficient, 35 Spiking neural network (SNN) applications, 175 deSNN, 181 eSNN, 180 Hodgkin-Huxley model, 176 integrate-and-fire model, 176 Izhikevich model, 177 leaky integrate-and-fire model, 177 postsynaptic neuron, 179 presynaptic neuron, 179 pSNN, 181 rank coding, 178 reservoir computing, 181 spike coding, 178 SpikeProp, 179–180 SSTD, 175 Thetalearning rule, 179 Thorpe’s model, 178 Streaming k-means ball k-means step, 29 streaming-step algorithm, 28 247 ■ index ■ index slack concept, 41 sparse technique, 42 SRM, 43 VC theory, 41 soft-margin, 46 Support vector quantile regression (SVQR), 70 Support vector regression (SVR) concepts, 68 graphical representation, 68 kernel, 72 mathematical model, 68 overview, 67 Support vectors, 42 Swarm intelligence (SI) ant colony optimization (ACO) algorithm, 111 artificial bee colony (ABC) algorithm, 115 boids, 111 particle swarm optimization (PSO), 113 stigmergy, 111 Syntax trees, 191 Synthetic minority oversampling technique (SMOTE), 54 system process activity, 236 T Telemetry bus, 225 Thermal stresses, 201–2 Thorpe’s model, 178 True negative (TN), 53 True negative rate (TNR), 53 True positive (TP), 53 True positive rate (TPR), 53 U Unsupervised learning algorithms, 7 User-based collaborative filtering, 33 Support vector machines (SVMs) (cont.) slack concept, 41 sparse technique, 42 SRM, 43 VC theory, 41 soft-margin, 46 Support vector quantile regression (SVQR), 70 Support vector regression (SVR) concepts, 68 graphical representation, 68 kernel, 72 mathematical model, 68 overview, 67 Support vectors, 42 Swarm intelligence (SI) ant colony optimization (ACO) algorithm, 111 artificial bee colony (ABC) algorithm, 115 boids, 111 particle swarm optimization (PSO), 113 stigmergy, 111 Syntax trees, 191 Synthetic minority oversampling technique (SMOTE), 54 system process activity, 236 T Telemetry bus, 225 Thermal stresses, 201–2 Thorpe’s model, 178 True negative (TN), 53 True negative rate (TNR), 53 True positive (TP), 53 True positive rate (TPR), 53 U Unsupervised learning algorithms, 7 User-based collaborative filtering, 33 Support vector machines (SVMs) (cont.) V Vapnik-Chervonenkis (VC) theory, 41 Vapnik’s e-insensitive approach, 67 Vector-evaluated genetic algorithm (VEGA), 193 Viable system modeling, 211 Voltage regulator (VR), 225 V Vapnik-Chervonenkis (VC) theory, 41 Vapnik’s e-insensitive approach, 67 Vector-evaluated genetic algorithm (VEGA), 193 Viable system modeling, 211 Voltage regulator (VR), 225 W system control agents, 218 U Unsupervised learning algorithms, 7 User-based collaborative filtering, 33 U U X, Y, Z X-means clustering, 234 248 Theories, Concepts, and Applications for Engineers and System Designers Theories, Concepts, and Applications for Engineers and System Designers Mariette Awad Rahul Khanna Efficient Learning Machines: Theories, Concepts, and Applications for Engineers and System Designers Mariette Awad and Rahul Khanna ApressOpen Rights: You have the right to copy, use and distribute this Work in its entirety, electronically without modification, for non-commercial purposes only. License for Distribution of the Work: This Work is copyrighted by Apress Media, LLC, all rights reserved. Use of this Work other than as provided for in this license is prohibited. By exercising any of the rights herein, you are accepting the terms of this license. You have the non-exclusive right to copy, use and distribute this English language Work in its entirety, electronically without modification except for those modifications necessary for formatting on specific devices, for all non-commercial purposes, in all media and formats known now or hereafter. While the advice and information in this Work are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. ISBN-13 (pbk): 978-1-4302-5989-3 ISBN-13 (pbk): 978-1-4302-5989-3 ISBN-13 (electronic): 978-1-4302-5990-9 ISBN-13 (electronic): 978-1-4302-5990-9 Trademarked names, logos, and images may appear in this book. Rather than use a trademark symbol with every occurrence of a trademarked name, logo, or image we use the names, logos, and images only in an editorial fashion and to the benefit of the trademark owner, with no intention of infringement of the trademark. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Efficient Learning Machines: Theories, Concepts, and Applications for Engineers and System Designers Managing Director: Welmoed Spahr Lead Editors: Jeffrey Pepper (Apress); Steve Weiss (Apress); Patrick Hauke (Intel) Acquisitions Editor: Robert Hutchinson Developmental Editor: Douglas Pundick Technical Reviewers: Abishai Daniel, Myron Porter, Melissa Stockman Coordinating Editor: Rita Fernando Copyeditor: Lisa Vecchione Managing Director: Welmoed Spahr Distributed to the book trade worldwide by Springer Science+Business Media New York, 233 Spring Street, 6th Floor, New York, NY 10013. Phone 1-800-SPRINGER, fax (201) 348-4505, e-mail orders-ny@springer-sbm.com, or visit www.springeronline.com. For information on translations, please e-mail rights@apress.com, or visit www.apress.com. What Is ApressOpen? ApressOpen is an open access book program that publishes • high-quality technical and business information. ApressOpen eBooks are available for global, free, • noncommercial use. ApressOpen eBooks are available for global, free, • noncommercial use. ApressOpen eBooks are available in PDF, ePub, and Mobi formats. • The user-friendly ApressOpen free eBook license is presented on the copyright page • of this book. iii iii To my family, and especially Edwin, my sunshine.—Mariette To my family, and especially my mother, Udesh, who always believed in me.—Rahul Contents About the Authors....................................................................................................xv About the Technical Reviewers.............................................................................xvii Acknowledgments..................................................................................................xix Chapter 1: Machine Learning ■ ■ ................................................................................ 1 Key Terminology............................................................................................................... 2 Developing a Learning Machine....................................................................................... 5 Machine Learning Algorithms.......................................................................................... 6 Popular Machine Learning Algorithms........................................................................... 10 C4.5......................................................................................................................................................10 k-Means...............................................................................................................................................10 Support Vector Machines......................................................................................................................11 Apriori...................................................................................................................................................12 Estimation Maximization......................................................................................................................12 PageRank.............................................................................................................................................13 AdaBoost (Adaptive Boosting)..............................................................................................................13 k-Nearest Neighbors............................................................................................................................14 Naive Bayes..........................................................................................................................................15 Classification and Regression Trees.....................................................................................................15 Challenging Problems in Data Mining Research............................................................ 15 Scaling Up for High-Dimensional Data and High-Speed Data Streams................................................16 Mining Sequence Data and Time Series Data.......................................................................................16 Mining Complex Knowledge from Complex Data..................................................................................16 Distributed Data Mining and Mining Multi-Agent Data.........................................................................16 vii ■ Contents Data Mining Process-Related Problems...............................................................................................16 Security, Privacy, and Data Integrity.....................................................................................................17 Dealing with Nonstatic, Unbalanced, and Cost-Sensitive Data.............................................................17 Summary........................................................................................................................ 17 References..................................................................................................................... 17 Chapter 2: Machine Learning and Knowledge Discovery ■ ■ .................................... 19 Knowledge Discovery..................................................................................................... 21 Classification........................................................................................................................................21 Clustering.............................................................................................................................................22 Dimensionality Reduction.....................................................................................................................22 Collaborative Filtering...........................................................................................................................22 Machine Learning: Classification Algorithms................................................................. 22 Logistic Regression..............................................................................................................................22 Random Forest.....................................................................................................................................24 Hidden Markov Model...........................................................................................................................24 Multilayer Perceptron...........................................................................................................................25 Machine Learning: Clustering Algorithms...................................................................... 27 k-Means Clustering..............................................................................................................................27 Fuzzy k-Means (Fuzzy c-Means)..........................................................................................................28 Streaming k-Means..............................................................................................................................28 Machine Learning: Dimensionality Reduction................................................................ 29 Singular Value Decomposition..............................................................................................................29 Principal Component Analysis..............................................................................................................30 Lanczos Algorithm................................................................................................................................32 Machine Learning: Collaborative Filtering...................................................................... 33 User-Based Collaborative Filtering.......................................................................................................33 Item-Based Collaborative Filtering.......................................................................................................34 Alternating Least Squares with Weighted-l-Regularization................................................................34 viii Machine Learning: Similarity Matrix............................................................................... 35 Pearson Correlation Coefficient............................................................................................................35 Spearman Rank Correlation Coefficient...............................................................................................35 Euclidean Distance...............................................................................................................................36 Jaccard Similarity Coefficient...............................................................................................................36 Summary........................................................................................................................ 37 References..................................................................................................................... 38 Chapter 3: Support Vector Machines for Classification ■ ■ ....................................... 39 SVM from a Geometric Perspective................................................................................ 39 SVM Main Properties...................................................................................................... 41 Hard-Margin SVM........................................................................................................... 43 Soft-Margin SVM............................................................................................................ 46 Kernel SVM .................................................................................................................... 48 Multiclass SVM .............................................................................................................. 50 SVM with Imbalanced Datasets...................................................................................... 52 Improving SVM Computational Requirements ............................................................... 54 Case Study of SVM for Handwriting Recognition .......................................................... 56 Preprocessing.......................................................................................................................................56 Feature Extraction ...............................................................................................................................57 Hierarchical, Three-Stage SVM.............................................................................................................58 Experimental Results............................................................................................................................59 Complexity Analysis..............................................................................................................................61 References..................................................................................................................... 62 Chapter 4: Support Vector Regression ■ ■ ................................................................ 67 SVR Overview................................................................................................................. 67 SVR: Concepts, Mathematical Model, and Graphical Representation............................. 68 Kernel SVR and Different Loss Functions: Mathematical Model and Graphical Representation............................................................................................................... 72 ix ■ Contents Bayesian Linear Regression .......................................................................................... 74 Asymmetrical SVR for Power Prediction: Case Study..................................................... 76 References..................................................................................................................... 79 Chapter 5: Hidden Markov Model ■ ■ ........................................................................ 81 Discrete Markov Process................................................................................................ 82 Definition 1 ..........................................................................................................................................83 Definition 2...........................................................................................................................................83 Definition 3...........................................................................................................................................83 Introduction to the Hidden Markov Model ..................................................................... 84 Essentials of the Hidden Markov Model...............................................................................................85 The Three Basic Problems of HMM.......................................................................................................86 Solutions to the Three Basic Problems of HMM...................................................................................87 Continuous Observation HMM........................................................................................ 92 Multivariate Gaussian Mixture Model...................................................................................................93 Example: Workload Phase Recognition.................................................................................................94 Monitoring and Observations................................................................................................................95 Workload and Phase.............................................................................................................................95 Mixture Models for Phase Detection.....................................................................................................97 References................................................................................................................... Contents 104 Chapter 6: Bioinspired Computing: Swarm Intelligence ■ ■ .................................... 105 Applications.................................................................................................................. 106 Evolvable Hardware............................................................................................................................106 Bioinspired Networking......................................................................................................................108 Datacenter Optimization.....................................................................................................................109 Bioinspired Computing Algorithms............................................................................... 110 Swarm Intelligence...................................................................................................... 111 Ant Colony Optimization Algorithm.....................................................................................................111 Particle Swarm Optimization..............................................................................................................113 Artificial Bee Colony Algorithm...........................................................................................................115 x Bacterial Foraging Optimization Algorithm................................................................... 117 Artificial Immune System............................................................................................. 118 Distributed Management in Datacenters...................................................................... 119 Workload Characterization.................................................................................................................120 Thermal Optimization.........................................................................................................................120 Load Balancing...................................................................................................................................121 Algorithm Model.................................................................................................................................121 References................................................................................................................... 123 Chapter 7: Deep Neural Networks ■ ■ ..................................................................... 127 Introducting ANNs........................................................................................................ 127 Early ANN Structures..........................................................................................................................128 Classical ANN......................................................................................................................................129 ANN Training and the Backpropagation Algorithm..............................................................................133 DBN Overview.............................................................................................................. 134 Restricted Boltzmann Machines................................................................................... 137 DNN Training Algorithms.............................................................................................. 138 DNN-Related Research................................................................................................. 140 DNN Applications................................................................................................................................140 Parallel Implementations to Speed Up DNN Training..........................................................................141 Deep Networks Similar to DBN...........................................................................................................142 References................................................................................................................... 142 Chapter 8: Cortical Algorithms ■ ■ .......................................................................... 149 Cortical Algorithm Primer............................................................................................. 149 Cortical Algorithm Structure ..............................................................................................................149 Training of Cortical Algorithms...........................................................................................................152 Weight Update.............................................................................................................. 154 Experimental Results .........................................................................................................................156 xi xi ■ Contents Modified Cortical Algorithms Applied to Arabic Spoken Digits: Case Study................. 159 Entropy-Based Weight Update Rule....................................................................................................159 Experimental Validation......................................................................................................................160 References... ............................................................................................................... 164 Chapter 9: Deep Learning ■ ■ .................................................................................. 167 Overview of Hierarchical Temporal Memory................................................................ 167 Hierarchical Temporal Memory Generations................................................................ 168 Sparse Distributed Representation.....................................................................................................171 Algorithmic Implementation ..............................................................................................................171 Spatial Pooler.....................................................................................................................................172 Temporal Pooler..................................................................................................................................173 Related Work................................................................................................................ 174 Overview of Spiking Neural Networks.......................................................................... 175 Hodgkin-Huxley Model.......................................................................................................................176 Integrate-and-Fire Model...................................................................................................................176 Leaky Integrate-and-Fire Model.........................................................................................................177 Izhikevich Model.................................................................................................................................177 Thorpe’s Model...................................................................................................................................178 Information Coding in SNN.................................................................................................................178 Learning in SNN..................................................................................................................................179 SNN Variants and Extensions..............................................................................................................180 Conclusion.................................................................................................................... 182 References................................................................................................................... 182 Chapter 10: Multiobjective Optimization ■ ■ ........................................................... 185 Formal Definition.......................................................................................................... 186 Pareto Optimality................................................................................................................................187 Dominance Relationship.....................................................................................................................187 Performance Measure........................................................................................................................188 xii ■ Contents Machine Learning: Evolutionary Algorithms................................................................. 189 Genetic Algorithm...............................................................................................................................190 Genetic Programming.........................................................................................................................191 Multiobjective Optimization: An Evolutionary Approach............................................... 192 Weighted-Sum Approach....................................................................................................................192 Vector-Evaluated Genetic Algorithm...................................................................................................193 Multiobjective Genetic Algorithm........................................................................................................194 Niched Pareto Genetic Algorithm........................................................................................................194 Nondominated Sorting Genetic Algorithm..........................................................................................195 Strength Pareto Evolutionary Algorithm.............................................................................................196 Strength Pareto Evolutionary Algorithm II...........................................................................................198 Pareto Archived Evolutionary Strategy...............................................................................................199 Pareto Envelope-Based Selection Algorithm......................................................................................200 Pareto Envelope-Based Selection Algorithm II...................................................................................201 Elitist Nondominated Sorting Genetic Algorithm................................................................................201 Example: Multiobjective Optimization.......................................................................... 204 Objective Functions...................................................................................................... 206 References................................................................................................................... 207 Chapter 11: Machine Learning in Action: Examples ■ ■ .......................................... 209 Viable System Modeling............................................................................................... 211 Example 1: Workload Fingerprinting on a Compute Node............................................ 213 Phase Determination..........................................................................................................................214 Fingerprinting.....................................................................................................................................218 Forecasting.........................................................................................................................................221 Example 2: Dynamic Energy Allocation........................................................................ 221 Learning Process: Feature Selection..................................................................................................222 Learning Process: Optimization Planning...........................................................................................224 Learning Process: Monitoring.............................................................................................................225 xiii ■ Contents Model Training: Procedure and Evaluation................................................................... 227 Example 3: System Approach to Intrusion Detection.................................................... 230 Modeling Scheme...............................................................................................................................231 Intrusion Detection System Architecture............................................................................................233 Profiles and System Considerations............................................................................. 236 Sensor Data Measurements......................................................................................... 237 Summary...................................................................................................................... 239 References................................................................................................................... 239 Index..................................................................................................................... Contents 241 xiv xiv About the Authors Mariette Awad is an assistant professor in the Department of Electrical and Computer Engineering at the American University of Beirut. She was also a visiting professor at Virginia Commonwealth University, Intel (Mobile and Communications Group), and the Massachusetts Institute of Technology and was invited by the Computer Vision Center at the Autonomous University of Barcelona, Google, and Qualcomm to present her work on machine learning and image processing. Additionally, she has published in numerous conference proceedings and journals. Prior to her academic position, she was with the IBM Systems and Technology Group, in Essex Junction, Vermont, as a wireless product engineer. Over the years, her technical leadership and innovative spirit have earned her management recognition and several business awards as well as multiple IBM patents. Mariette holds a PhD in Electrical Engineering from the University of Vermont. Rahul Khanna is currently a principal engineer working as a platform architect at Intel involved in the development of energy-efficient algorithms. Over the past 20 years he has worked on server system software technologies, including platform automation, power/thermal optimization techniques, reliability, and predictive methodologies. He has authored numerous technical papers and book chapters on energy optimization, platform wireless interconnect, sensor networks, interconnect reliability, predictive modeling, motion estimation, and security and has coauthored a book on platform autonomy. He holds 33 patents. He is also the coinventor of the Intel Interconnect Built-in Self-Test (IBIST), a methodology for high-speed interconnect testing. His research interests include machine learning–based power/ thermal optimization algorithms, narrow-channel high-speed wireless interconnects, and information retrieval in dense sensor networks. Rahul is a member of the Institute of Electrical and Electronic Engineers and the recipient of three Intel Achievement Awards for his contributions in areas related to the advancement of platform technologies. xv xv About the Technical Reviewers Abishai Daniel is a staff reliability engineer with Intel’s Datacenter Group. He works in the areas of device, component, architectural reliability, and input-output (I/O) signal integrity, with a focus on statistical predictive model development based on reliability data and the application of machine learning techniques to reliability modeling. He has served as both program committee member and session chair for various Institute of Electrical and Electronic Engineer conferences, mainly on the topics of reliability and design for reliability, and has published more than 15 papers. Abishai has an AB from Wabash College and an MSEE and a PhD from the University of Michigan. Myron Porter has served in a variety of roles at Intel, including systems programmer, manager, board validation program manager, and technical writer. Previously, he had positions at other Fortune 500 companies. He has lived in Bush Alaska and Sakha (Russian Yakutia) but was raised in the Ozarks. He got his start in business selling Christmas cards door-to-door at the age of eight. Myron later sold fireworks and has worked as a cabdriver, a pollster/political interviewer, a grant writer, a cook, a substitute teacher, a fuel truck deliveryman, a college English instructor, a copywriter, a restaurant manager, an ESL teacher, and a technical contractor. Additionally, he has done volunteer work for a veterinarian and two college radio stations and as technical support to a regional women’s shelter. Melissa Stockman is currently in the Division of Surgery at the American University of Beirut Medical Center, focusing on the analysis of medical data. She also worked as a senior software engineer in the United States and was the director, for more than 10 years, of Information Technology Infrastructure and Support at the Lebanese American University. She holds a PhD in Electrical and Computer Engineering from the American University of Beirut as well as a BA in Mathematics from New York University and an MA in Computer Science from George Mason University. Melissa’s research areas include machine learning, support vector machines, and computer architecture. xvii Acknowledgments Many thanks to Yara Rizk (Chapter 7), Nadine Hajj (Chapter 8), Nicolas Mitri (Chapter 9), and Obada Al Zoubi (Chapter 9) for their contributions to this book. We would also like to thank Kshitij Doshi, Christian Le, John J. Jaiber, Martin Dimitrov, and Karthik Kumar, who helped develop the concepts of phase detection and workload fingerprinting detailed in Chapter 11 Many thanks to Yara Rizk (Chapter 7), Nadine Hajj (Chapter 8), Nicolas Mitri (Chapter 9), and Obada Al Zoubi (Chapter 9) for their contributions to this book. We would also like to thank Kshitij Doshi, Christian Le, John J. Jaiber, Martin Dimitrov, and Karthik Kumar, who helped develop the concepts of phase detection and workload fingerprinting detailed in Chapter 11. xix
https://openalex.org/W2898762430	https://figshare.com/articles/journal_contribution/Characterizing_the_DNA_Damage_Response_in_Fibrosarcoma_Stem_Cells_by_i_in-situ_i_Cell_Tracking/7268570/3/files/13692914.pdf	English	null	Characterizing the DNA damage response in fibrosarcoma stem cells by in-situ cell tracking	International journal of radiation biology	2,018	cc-by	239	Figure S1. Representative image of 53BP1-GFP background level in mock-irradiated HT1080 cells. Spontaneous 53BP1 foci (green) and Hoechst 33342 nuclear stain (blue) are shown. Scale bar = 20 μm. Figure S1. Representative image of 53BP1-GFP background level in mock-irradiated HT1080 cells. Spontaneous 53BP1 foci (green) and Hoechst 33342 nuclear stain (blue) are shown. Scale bar = 20 μm. Figure S1. Representative image of 53BP1-GFP background level in mock-irradiated HT1080 cells. Spontaneous 53BP1 foci (green) and Hoechst 33342 nuclear stain (blue) are shown. Scale bar = 20 μm. Figure S2. The number of 53BP1 IRIF per nucleus at 30 min post γ-irradiation at dose of 0.5 Gy and 1 Gy. Representative images were shown in upper left corner. Scale bar = 5 μm. Figure S2. The number of 53BP1 IRIF per nucleus at 30 min post γ-irradiation at dose of 0.5 Gy and 1 Gy. Representative images were shown in upper left corner. Scale bar = 5 μm. Figure S3. Cell synchronization. (A) Example of cell cycle distribution of 2h release after synchronization. The region of G1 phase was filled with gray. (B) The percentage of HT1080 cells in G1 phase at indicated time after 2h release from synchronization. Figure S3. Cell synchronization. (A) Example of cell cycle distribution of 2h release after synchronization. The region of G1 phase was filled with gray. (B) The percentage of HT1080 cells in G1 phase at indicated time after 2h release from synchronization.
https://openalex.org/W3170934511	https://www.researchsquare.com/article/rs-582546/latest.pdf	English	null	Open Review and Open Science in The Social Sciences and Humanities: A "Double Blind" Gold Standard	Research Square (Research Square)	2,021	cc-by	12,499	Open Review and Open Science in The Social Sciences and Humanities: A "Double Blind" Gold Standard Univeristy of Jyväskylä https://orcid.org/0000-0003-3709-5341 Hans-Joachim Backe IT University of Copenhagen: IT-Universitetet i Kobenhavn Research Keywords: Ethics, Journalology, Open Science, Peer Review, Social Sciences and Humanities Posted Date: June 9th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-582546/v1 This work is licensed under a Creative Commons Attribution 4.0 International License. Read Ful Version of Record: A version of this preprint was published at Research Integrity and Peer Review on November 18th, 2021. See the published version at https://doi.org/10.1186/s41073-021-00116-4. Page 1/17 Abstract Openings of research results, datasets, and scientific practices in general are currently being implemented across fields. Especially strongly data-driven areas like medicine are discussing publishing transparency too – in a context where open review formats now dominate. Social sciences and humanities (SSH), in turn, still rely on closed systems. In this study, we draw on 12 semi-structured interviews with chief editors of leading journals in SSH fields to better understand the transparencies of such review processes. We find that, within SSH, ‘double blind’ peer review represents a gold standard that credible journals follow by default. However, the actual review processes of these journals are multi-stage and largely open with the authors’ names standardly visible to decision-making peers, with ‘double blind’ principles forming but part of it. We recommend journals to communicate the transparencies of their review in more detail, also and especially if they are ‘double blind’. Introduction In a recent special issue on open science, nine scholars (Crüwell et al. 2019) review the current introductory and consensus best practices from the open science perspective: open access, open data, preregistration, reproducible analyses, replications, and open science teaching. In such recommendations for universal regulations and practices, distinct fields are often singled out as potentially requiring different solutions, for instance, disciplines within social sciences and humanities (SSH) (see Nosek et al. 2015; Morey et al. 2016). Our goal in this article is to shed light on a topic that is rarely included in lists like the above (cf. Munafò et al. 2017) despite its direct connection to open science transparency principles: peer review of scientific publication in the SSH. In comparison to the relatively recent emergence of organized open science approaches, the discussion and study of scientific peer review (sometimes referred to as ‘journalology’) is old and widespread (e.g. Burnham 1990; Bornmann 2008). Already in the early 2000s, Garfield (2004) found no less than 3.720 publications focused on the peer review process alone. Such a number of studies naturally covers a great range of subtopics, but the key question remains unsolved to date: how to verify scientific quality in a way that is ethical, reliable, and possible to carry out in practice? Whereas so-called open peer review processes have been a long-term solution in strongly data-driven fields like medicine, many SSH publications rely on the closed system of ‘double blind’ peer review. Despite these disciplinary tendencies, the debate about the advantages and disadvantages of open review processes continues also in medical fields (van den Eynden et al. 2016), while some social science research vocally champions open review practices (Risam 2014). Our study was set up to qualitatively chart the reasoning of SSH peer review processes and the transparencies behind them. With chief editors being expected to guarantee timely and smooth publication of journals – “they just want me to get the stuff on time, keep the trains running”, as one interviewee put it – the policies they implement may be conservative and pragmatic, but what reflections and considerations take place under the surface? How transparently do SSH journals conceptualize and carry out their peer review processes? How do chief editors negotiate peer review policies, ethics, and pragmatics? And how do the chief editors situate their own powerful role in the process? Introduction We answer these questions by means of 12 semi-structured interviews with chief editors of leading SSH academic journals. The article is divided in four sections. In the first section we review relevant previous literature and establish a context. In the second section we introduce our qualitative method and data. The third section presents the results, and the fourth section is reserved for discussion. 1.1. Literature on Peer Review Although signing appears to make reviewers more likely to recommend publication and less likely to recommend rejection of papers, it is important to remember the role of the Editor in this process [moreover] junior reviewers may hinder their career prospects by criticising the work of powerful senior colleagues (Walsh et al. 2000). While some studies have also reported less clear or no differences between signing and non-singing reviews (e.g. Godlee et al, 1998; van Rooyen et al, 1999), the current consensus points at the exact benefits and deficits originally indicated by Walsh’s group (see e.g. Shanahan & Olsen 2014; Moylan et al. 2014). These open review findings have been studied further still, with various sub focuses such as reviewer bias. Manchikanti and colleagues (2015) cite evidence for at least six unique biases that have been found to corrupt the peer review process: confirmation bias (supporting existing beliefs), conservative bias (resistance against new methods/theories), bias against interdisciplinary research (applying single discipline criteria to multidisciplinary studies), publication bias (preference for positive results), bias of conflicts of interest (judgment based on personal benefits), and content-based bias (numerous biases produced by a subjective position – including ‘ego bias’ that makes reviewers favourable for work that cites the reviewer). The scholars entertain transparency via open peer review formats as an antidote to these issues; however, they also repeat the previously noted challenges that come along with open review: increased difficulties related to recruiting reviewers and having honest criticism. Moreover, in the case of public open review, the review process can be complicated with commentators or critics who may not qualify as experts. In addition to the above, a mutual problem that concerns both open and closed peer review formats is what Gorman (2007) has coined the “Oppenheim effect.” This refers to a certain known-author syndrome according to which some editors and/or peer reviewers tend to provide established scholars with special treatment (“We both know that we are going to publish it anyway”). Recently, this theoretical concept has received strong empirical support, as Tomkins and associates (2017) had half a thousand papers in an annual computer science conference peer reviewed by two experts who were disclosed with the authors’ names and two other experts who did not see the authors’ names (i.e. four reviewers per paper). 1.1. Literature on Peer Review We start by reviewing previous findings related to peer review practices and their transparency elements in particular. Although the respective histories of different disciplines seem to have standardised various understandings of ‘open peer review’ and ‘closed peer review’ (blinded peer review), it is worth highlighting that both open and closed peer review practices have many forms. Ford’s (2013) list of eight open peer review formats, based on 35 earlier studies, provides a useful illustration. Signed review reveals the identity of the reviewer to the author. In disclosed review both the author and the reviewer are identified to each other. Editor-mediated review reveals the editor(s) as a decision-making or reviewing entity for the author. Transparentreview occurs in a public (typically online) environment with authors, reviewers, and editors all disclosed. Crowd-sourcedreview additionally Page 2/17 Page 2/17 allows community members to participate in the public review. Pre-publicationreview takes place during an extra preliminary review stage, as a work is evaluated in an open environment (e.g. preprint server) before entering the actual publication process. Post- publicationreview enables direct public commenting and criticism of a work after its publication on the journal platform. Synchronous review enables a work to be published in a dynamic format with continuous public review and editing. Ford’s (2013) list is not exhaustive and lacks, for instance, one relatively common form of open review: a single blind review where the authors’ identities are revealed to the reviewer, but not the other way around. Regardless, the above suffices to demonstrate that the notion of ‘open review’ is multifaceted and complex, and that there are several dimensions of openness that all potentially influence the review process in diverse ways. These potential influences have been studied respectively in detail too. In a large-scale experiment carried out by Walsh and colleagues (2000) with the British Journal of Psychiatry, the scholars asked the peer reviewers of 408 manuscripts to sign their review reports and disclose their identities to the authors. A total of 76% agreed to sign, and their review reports were found to be of higher quality, more courteous, took longer to complete – and they were more likely to recommend publication. The scholars conclude: time commitment involved in reviewing might be too arduous for referees if the peer review process were opened up, especially when one considers the increased workload resulting from the loss of reviewers who refuse to sign their names. 1.2. Social Sciences and Humanities Q2: How do the chief editors position their journal’s review and publication practice between polic RQ2: How do the chief editors position their journals review and publication practice between policy, ethics, and pragmatism? RQ3: How do the chief editors situate their own powerful role in the peer review process and in what way is that role negotiating open science principles of the peer review process? RQ3: How do the chief editors situate their own powerful role in the peer review process and in what way is that role negotiating open science principles of the peer review process? Since the research questions are explorative, we avoid exact hypotheses. However, before data collection, we did entertain and pre- register some expected trends (https://osf.io/wjztp). Since the goal of this study was not to test or falsify these trends but to answer our nonconfirmatory research questions, we do not discuss the expectations but rather aim at filling out the blanks of the SSH journal review processes in order to explore the issues of transparency that may lie within. 1.1. Literature on Peer Review Peer reviewers were much more likely to accept papers from famous authors and top institutions, compared with their double blind counterparts. The same study also found a statistically significant bias against women authors – one more bias that has been known to handicap academia for decades (see Wennerås & Wold 1997). In summary, the academic world – represented by 28,094 scientific journals that publish some 2 million scientific articles annually (Ware and Mabe 2015) – has come to employ multiple diverse review strategies in their publication processes in order to assure quality and fight biases. These peer review strategies have several transparency elements that surface at different stages of the publication process. Depending on the aspect, such transparencies (open or closed) resonate with various sought-after positives and to-be-avoided negatives. The general consensus is that fully closed peer practices are good for providing reviewers a safe anonymous space to criticize candidly, which also facilitates the speed of the review process. Fully open review processes, in turn, are generally good at motivating the reviewers and holding them accountable, thus increasing the overall quality of feedback and making biases as well as conflicts of interest visible. Page 3/17 Page 3/17 Page 3/17 1.2. Social Sciences and Humanities The previously cited literature on peer review transparency and open science has been published and discussed mainly in data-driven academic domains such as medicine and natural sciences. This makes sense, as many of the open science principles derive from issues of closed or limited datasets, and the peer review of such studies can be part of both the problem and the solution. Moreover, when biases like conflicts of interest potentially have a strong direct clinical impact (e.g. via medicine testing and production), open peer review practices can be used to secure transparency and accountability. But what about fields such as those of the humanities, which do not necessarily rely on empirical samples? The challenges in developing universally applicable procedures for open research and review appear to be at least partially rooted in conceptual differences such as the meaning of originality. For instance, Guetzkow and colleagues (2004) conducted a qualitative interview study with peer reviewers from diverse fields and found that whereas natural sciences conceive of originality very narrowly as the “production of new findings and theories”, for social sciences and humanities peer reviewers, originality could also be associated to novel elements in the approach, method, data, topic, or simply the fact that the research was linked to an understudied area. In addition, whereas topics such as research replication can, to some degree, address the humanities too (see Peels & Bouter 2018), it is evident that not all research designs can be based on one and the same reproducibility principle – and their peer review should not expect that either. In the light of the above, there are good reasons to believe that social sciences and humanities maintain and evolve with a relatively different set of principles and strategies compared to, for instance, physical and life sciences. These differences, we expect, are reflected by the transparencies of the peer review processes, which journals in these fields/disciplines employ. Accordingly, this interview study was set up to answer the below three research questions. RQ1: How do highly ranked SSH journals perceive open peer review processes and do these perceptions materialize in the actual processes they employ? RQ2: How do the chief editors position their journal’s review and publication practice between policy, ethics, and pragmatism? 2. Method And Materials Due to our research questions being explorative and qualitative, we chose semi-structured interviews with chief editors of leading SSH journals as a method. We use the term ‘leading journals’ here to indicate that our focus is on publications that are respected in their fields and recognized as quality academic platforms (e.g. excluding so-called ‘predatory journals’). We did not choose the journals based on metrics such as impact factor, albeit many of the interviewed journals did rank very high according to these figures. We considered it important to include journals with not only different scholarly domains, but different profiles and sizes: the smallest journal from the most narrowly defined field publishes only around 15 articles per year, whereas the three biggest journals all publish more than five times this volume. These boundaries give our anonymous materials an identity and save the reader from speculating with the relevance of interviewee responses. The study followed the Finnish National Board on Research Integrity guidelines, according to which the local ethics committee should not be applied for a statement because the methods and themes do not represent risks that are higher than those that would occur in everyday interaction. Before reaching out for participants, however, we created an interview structure and work plan that were stored in the Open Science Framework on June 25, 2020 (https://osf.io/wjztp) The idea was that registering questions and general objectives of the research beforehand would build up both credibility as well as trust, and thus facilitate approaching busy chief editors who presumably receive dozens of emails and contact requests daily. That said, further details such as the complete question list and outcome expectations were not disclosed but embargoed, as we did not want to influence the interviewees’ responses. Page 4/17 Page 4/17 The goal was to balance the 12 interviews so that diverse geographical regions, content orientations, and chief editor genders would be represented by the participating journals – with the caveat that each journal should be part of the SSH scientific domain. Notably, all interviewed chief editors characterized their journal as multi- or interdisciplinary, even if their journal has a focus on or origin in a singular discipline. We created a list of journals that we would approach by personal email one by one so that when our invitation would be ignored or rejected, a new journal with similar representation was selected. 2. Method And Materials An open call for participation was also distributed in social media. We had no trouble finding volunteers, as chief editors were generally interested in discussing the topic and willing to make time in their schedules within a short notice. Some journals were represented by multiple chief editors. We do not disclose further details about the editors or their journals in order to protect their privacy. Many of the interviewees explicitly wanted to remain anonymous. The interviews were carried out by using Zoom remote communication software. Only the audio part of the video call was stored for analysis. A protected university cloud service was used for storing the data. The participants were informed of research details via email before the interview and in more detail at the beginning of the interview. Informed consent was collected in written PDF format. Both researchers participated in the interviews equally. The average interview length was 70 minutes, the shortest one being 55 minutes and the longest one 90 minutes. The preregistered interview structure was followed systematically in each interview; however, if and when the interviewees opened new relevant themes that we could not foresee, follow-up questions were posed from outside the plan. The interviews were transcribed into text format by using a General Data Protection Regulation compliant service (Konch.ai). The text was proofread with the help of a research assistant, as approximately 10% of the automated transcription was unreadable. The proofread text files were uploaded to a university-supported Atlas.ti system, which we used for software-based text analysis. The analysis was carried out by the first author exploratively coding all text without a predesigned coding scheme (533 codes overall) and the second author reading the data. Coding reliability was tested by, first, having an external assistant unitize 17% of the data (see Hodson 1999). Since the assistant did not have experience of the academic peer review, we did not pursue high numeric interrater reliability but negotiated a coding agreement (see Campbell et al 2013). After merging overlapping codes and coding negotiation, 510 codes remained. We did not pursue themes or a manual for new coding rounds, but discrepancies regarding the codes were discussed and solved by the research team, i.e. reconciling differences via consensus (Syed & Nelson 2015). Because both researchers participated in the development of the interview structure and actual interviews, analytical agreement was reached in single one-day session. 2. Method And Materials This produced 11 code families, which included descriptive information (e.g., how does the peer review process operate) and non-descriptive information (e.g., what do the editors personally think about the peer review process). These code families are: Authors: comments related to the authors who submit to the journal. Decision: comments related to manuscript publication decisions. Decision: comments related to manuscript publication decisions. Editing: comments related to the work of journal editing in general. Editing: comments related to the work of journal editing in general. Editors: comments related to the chief editor’s personal beliefs or role. Editors: comments related to the chief editor’s personal beliefs or role. Interview: comments related to the interview in question. Interview: comments related to the interview in question. Journal: comments related to the chief editor’s journal. Open science: comments related to open science in general. Publisher: comments related to the publisher of the chief editor’s journal. Review: comments related to the review process in the chief editor’s journal. Reviewers: comments related to external peer reviewers of the chief editor’s journal. Reviewers: comments related to external peer reviewers of the chief editor’s journal. Science: other comments related to the scientific world and its developments. The second author then examined the data in the light of the families, not systematically re-coding but selecting relevant sections and units that related to our three research questions. Based on this we report the findings in two overlapping parts: Page 5/17 Page 5/17 a. Descriptive: in this part we describe the actual journal peer review processes and the transparency issues related to it. This includes mainly the content of the families Decision, Editing, Journal, Review, and Reviewers. a. Descriptive: in this part we describe the actual journal peer review processes and the transparency issues related to it. This includes mainly the content of the families Decision, Editing, Journal, Review, and Reviewers. b. Non-descriptive: in this part we move to the editors’ personal views. This includes mainly the content of the families Authors, Editors, Open Science, Publisher, Science. The family Interview will not be discussed in this article. b. Non-descriptive: in this part we move to the editors’ personal views. This includes mainly the content of the families Authors, Editors, Open Science, Publisher, Science. The family Interview will not be discussed in this article. 2. Method And Materials Last, to address an issue that some readers will likely consider relevant: we do not numerically present the number of instances of specific coded events. We acknowledge that a quantitative approach to similar qualitative data can be fruitful; however, in such case the target journals should have been selected with even narrower inclusion criteria for them to be clearly representative (of a selected small subfield that could be well represented by 12 journals). Again, the present goals are not confirmatory, in which case qualitative analysis of the qualitative data, we assert, is more fitting. Once more, due to the privacy concerns expressed by some interviewees, we do not share our data via an open repository. Parts of specific interest can be made available by request to the corresponding author, however. 3.1. How do the editors employ open science and peer review in practice? In this section, we outline the SSH review processes, as described by the interviewees. Although some experienced readers might consider this section not adding new knowledge to the field, we consider it important to provide a detailed description in order to empirically illustrate what many believe these processes are—we were not able to find previous studies that would have systematically analysed SSH review processes—moreover, this this baseline will also enable us to later pinpoint exceptions and reflect on the chief editors’ personal views. All interviewed journals employed multiple stages for reviewing their submissions. We start by summing up the general protocol that was similar in all journals: 1. Screening. When submission arrives at a journal, editorial body X (sometimes with Y) will screen the submission and decide if it will be reviewed. Negative decisions lead to desk rejection. 2. External review. Based on the screening and pre-review, X and/or Y look for appropriate external reviewers Z and invite them to review the submission. 3. Revisions. Based on the combined feedback of X, Y, and Z, the authors are asked to revise their submission and resubmit. Steps 2 and 3 are repeated until the submission is accepted or rejected. 3. Revisions. Based on the combined feedback of X, Y, and Z, the authors are asked to revise their submission and resubmit. Steps 2 and 3 are repeated until the submission is accepted or rejected. 4. Post-review. Accepted submissions are typically followed by copyediting and various debriefing procedures related to the review process. 4. Post-review. Accepted submissions are typically followed by copyediting and various debriefing procedures related to the review process. Screening Sometimes the chief editors were responsible for all screening themselves, but often these decisions were informed by or entirely delegated to other parties such as assisting editors, associate editors, editorial boards, or the managing editor. The amount of personnel involved varied dramatically, from a sole editor to teams with more than ten people. The number of desk rejections at the end of this process varied even more, ranging from as low as 15% to over 85% of all submitted manuscripts. The average overall rejection rate lies at about 70%, with the lowest rejection rate at 33% and the highest at 95%. Five unique reasons were identified as causing a desk reject: lack of fit with journal scope, poor overall quality, ignoring relevant literature, narrowness or low impact, and instances where too many similar manuscripts were already in review or published. In one exceptional case, the chief editor noted almost all desk rejections to derive from the fact that the journal’s name was similar to other journals with different profiles, which made authors constantly submit manuscripts that address out-of-scope topics. The screening processes had combinations of closed and open elements. In the most common scenario, the chief editor and/or staff would screen the manuscript with the authors’ names visible. In other words, the most common methods in the screening phase were disclosed or single-blind review where the reviewer saw the authors but not always the other way around, i.e. the authors might not know if they had been (desk) accepted or rejected by a chief editor, assistant editor, associate editor, editorial board, managing editor, or someone else. The interviewees’ felt that double sided anonymity at this stage would be both impossible and impractical. One Page 6/17 Page 6/17 Page 6/17 interviewee, for instance, was ready to let assistants make desk decisions, but in a way that would allow the chief editor to supervise the process in an open format: That has to be open. For example, you would never assign a reviewer who's in the same department as the author. So you need to know where the other is. You also want to avoid assigning a reviewer who was likely to have been the author's advisor. So that really can't be blind, or you'll end up just sending things to coauthors or work colleagues. I am much less concerned with the anonymity of authors than the anonymity of reviewers. Screening But if it goes further, then two members of the editorial board read the text and assess whether it's good to go to review or not. We might not desk reject, but send ‘OK, didn’t go to review yet, but if you do these changes, we’ll reconsider.’ Summary: Screening is carried out by one or more editors. The full manuscript may be read or not, and feedback is optional. Since this phase is editorial, the main transparency issue is whether the authors’ know who contributes to the desk decision, and based on what criteria. Screening One journal practices a system that inverses the dynamic of the screening stage: a significant proportion of submissions are first informally suggested to the chief editor, who then seeks input from experts in the field to support authors in developing proposals. Only then proposals are submitted and subjected to a double blind peer review, which then has a very high acceptance rate. To this chief editor, nurturing promising submissions from the start strengthens the quality of the journal while guaranteeing a steady stream of high-quality publications – a desirable strategy because “we are in the business of publishing, not punishing.” This feed-forward form of curation creates less need for critical feedback (and rejection) in the later review stages: “I like to think that we do a good job prior to the submission, so the author can confidently send an article and receive a positive, constructive feedback.” The described process reminds one of the “registered report” article format (Chambers 2017), which was not explicitly used by any of the 12 SSH journals (not even those that were psychologically inclined). In some journals, screening was supplemented with full editorial review. In these cases, one or more persons of the editorial staff read the entire manuscript and provided (signed or anonymous) decision feedback before moving to external review: Sometimes we get articles from [country] that are 1.5 page – then it's a desk rejection. But if it's a full article, the editorial manager will assign it to one of the other editors. And then it's the editor's task to go through the article. Sometimes we get articles from [country] that are 1.5 page – then it's a desk rejection. But if it's a full article, the editorial manager will assign it to one of the other editors. And then it's the editor's task to go through the article. Chief editors have a look at the first round, we can then give a desk reject right away. But if it goes further, then two members of the editorial board read the text and assess whether it's good to go to review or not. We might not desk reject, but send ‘OK, didn’t go to review yet, but if you do these changes, we’ll reconsider.’ Chief editors have a look at the first round, we can then give a desk reject right away. External review I try my best to balance reviewers and also to sometimes avoid using harsh reviewers on material that I personally don't think is the strongest. So I might reserve my harshest reviewers for things that I myself find to be of very high quality. And then there are my sort of super reviewers. They are people whom I have just learned to trust. Who will first of all do it if they say they'll do it, but also are good at sort of sifting through, reading and picking things up. These are often people who have been journal editors or just have a track record. And if I had a structure of associate editors, these are people who would be associate editors. And then there are my sort of super reviewers. They are people whom I have just learned to trust. Who will first of all do it if they say they'll do it, but also are good at sort of sifting through, reading and picking things up. These are often people who have been journal editors or just have a track record. And if I had a structure of associate editors, these are people who would be associate editors. The role of external review was somewhat polarized among the journals. On one side, certain journals consider the external review to be advisory instead of decision-making. The editors of these journals define their roles rather as curatorial or akin to editors in book publishing. Beyond assuring high quality publications, they see their responsibility in stimulating innovative impulses to developing fields and helping authors bring their concepts to full fruition in a collaborative process. we don’t follow the peer review slavishly, but then again, the issue of not recognizing what the reviewer was saying has not really arisen – we end up reading every single piece submitted and everything, and then every piece that is published in the journals, we go over each one of us, more than once. At the other extreme, however, chief editors were utterly clear about operating as nothing but ‘mediators’ between reviewers and the reviewed submissions. These journals pursued first and foremost the assurance of scientific quality, and in this picture, the external blind reviewers served as ‘objective’ measures. At the other extreme, however, chief editors were utterly clear about operating as nothing but ‘mediators’ between reviewers and the reviewed submissions. External review These journals pursued first and foremost the assurance of scientific quality, and in this picture, the external blind reviewers served as ‘objective’ measures. If I'm in doubt as the editor, I will send it out to reviewers who can then make that decision for me. So the idea is that not one person, in cases of doubt, will make the decision. I don't make the decision, the reviewers do. I tend to view myself as an umpire. I'm not qualified to make these decisions. My job really is to try and ensure that the reviewers are appropriate and that the reviews are fair, to the extent that I can. And I'm sure there are mistakes. It is worth noting that sometimes editorial review was merged with the external review. In these scenarios, internal editorial reports could be delivered based on either double or single blinded principles. None of the chief editors expressed concerns or policies regarding the disclosure of these internal processes, but we also did not inquire directly about them. the disclosure of these internal processes, but we also did not inquire directly about them the disclosure of these internal processes, but we also did not inquire directly about them. We have an editorial board. We have this board to kind of draw on in cases if we need a second opinion or third reviewer. But then they would also work as a blinded reviewer. Sometimes it gets complicated and then the person I ask will be somebody on our editorial board who has been fairly helpful in the past, because you're asking them basically to follow through the entire editorial history of this. I'll send them the whole thing, like, ‘here's the history, here are the reviews, what do you think.’ Summary: For research articles, the general practice of disclosed external review was a rare outlier in our data. A consensus among the chief editors was that double blind review was the fairest and most objective means to carry out the process. Sometimes the process included internal review procedures, which could be non-blinded. External review All editors participating in the study characterized the external review phase as crucial. Here we find the strictest adherence to double blinded review practices. Virtually all interviewees supported the view that double blind external peer review was considered a standard by the academic community as a whole. With one exception, all journals employed strict double blind external peer review, with between two and four reviewers per submission for original submissions. Other formats, e.g. book reviews, are often treated differently. The journals had several means for recruiting reviewers. This could be done by the chief editor or another staff member, or as a collective effort. Higher volume journals had reviewer databases with hundreds of potential experts; smaller journals would mainly recruit via the personal networks of the editorial staff. All editors agreed that academic qualifications were the primary selector, supported by a whole range of other criteria. It's because they're considered experts. It's because sometimes we know them personally. It is because they are more committed, because they're on the board. And it is also because they are familiar with the journal, the direction of the journal, the expectations and the level of quality of the journal. Altogether, nine unique criteria were considered relevant in choosing the reviewers: age (“the issue is how do you find the really bright young people who are doing really thoughtful work”), biases (“we try to give papers to reviewers that are perhaps on different sides of a divide”), commitment (“because you know they are more committed”), diverse perspectives (“we certainly try to find both reviewers from close to the paper’s discipline and also from outside”), distance (“connection or lack of connection to the author”), expertise (this was mentioned by all interviewees in many ways), nationality (“you need someone who will pick up on the local nuances”), personal preferences (“I would be hesitant to send something to somebody who I didn't feel I knew”), and recommendations (“we also make very Page 7/17 Page 7/17 good use of the suggestions we receive”). Additionally, two journals were proud to have ‘harsh’ or ‘super’ reviewers who could be used for the most challenging tasks: I try my best to balance reviewers and also to sometimes avoid using harsh reviewers on material that I personally don't think is the strongest. So I might reserve my harshest reviewers for things that I myself find to be of very high quality. Post-review In the post-review phase, most journals draw strongly on their editorial assistants for technical quality assurance such as checking the integrity and completeness of the citations. In the post-review phase, most journals draw strongly on their editorial assistants for technical quality assurance such as checking the integrity and completeness of the citations. In this phase, pragmatic differences, primarily relating to the ways in which the journals are financed, emerge. The journals that are primarily or exclusively financed by universities report dwindling subsidies, whereas journals with strong ties to associations or publishers appeared more stable. Relations to publishing houses were characterized unanimously as harmonious and unproblematic, except for some unease in cases of journals facing an upcoming periodic review of viability. One chief editor, addressing manuscript transformations into PDFs with DOIs, positively admits: I think the press handles all that, I've not been involved in any of that ... We've discussed occasionally whether [volume number should increase]. Other than that – cover design, occasional changes, that's always collaborative. Only one journal employed technical means to assure quality control beyond peer review. They had recently started using software for an originality check, which would make sure that plagiation of all sorts could be detected before final publishing (“now we run all papers through a system to see a possible relapse”). Transparency-wise, however, perhaps the most critical question at this phase was whether author or reviewer identities could be opened after a positive publication decision. When I send an acceptance notice and say ‘dear so-and-so we've accepted your article’ I send that to the reviewers as well. It seems to me at that point I can include the name of the author. I mean, we've made the decision. But sort of automatically I take it out. But I keep thinking, why am I taking out the name of the author? Finally, some chief editors perceived the articles that they publish in the larger continuum of scientific evolution. Namely, the peer review of a publication is not something that takes place in or by the journal alone; rather, journal review is one evaluative event in an article’s life, which continues post-publication as peers read and review it in academic forums: Finally, some chief editors perceived the articles that they publish in the larger continuum of scientific evolution. Revisions With few exceptions, all research that had been published in the interviewed journals went through revision (“I don't think I've ever experienced a situation where a text would’ve been good to go”). The revision process was either conducted between authors and editorial bodies, or via additional external (blind) reviews after the first revision. One editor explicitly stated that a manuscript which had not sufficiently improved after a revision would not benefit from further revisions and was rejected. Other editors described an iterative process that could go through as many as eight revisions. A common method was to ask the same external (blind) reviewers to review the manuscript a second or more times. Despite collectively following and agreeing on the previously discussed benefits of closed external review, several editors voiced doubts regarding this phase in particular. These doubts derive from the nature of the revision process, namely, these interviewees felt that Page 8/17 Page 8/17 Page 8/17 initial blind processes would benefit from increased transparency after the necessary ‘gatekeeping’ had been cleared out: initial blind processes would benefit from increased transparency after the necessary ‘gatekeeping’ had been cleared out: [blind review] is not the gold standard that people often perceive it to be, and in fact, often what’s far more useful is a sort of semi- collaborative editorial process that follows after double blind peer review. That's where the improvements are really made. This is just a kind of initial gatekeeping, and sometimes it’s useful and sometimes tokenistic. In cases such as the above where chief editors expressed a personal liking for disclosing external reviews or revisions, they systematically cited institutional requirements that would not index their journal as a proper scientific journal without ‘blindness’ involved. For instance: A completely open process, I think, is far more plausible. But then the issue is also that I've been on review committees where people have said, well, if this has not gone through a double blind review, it doesn't count as much. So I still think there's a huge hurdle to overcome in terms of how we can get the academy as a whole to value anything other than that kind of traditional double blind review. Summary: All journals include a revision stage, which is internal, external, or a combination thereof. The transparencies in the revision process generally follow those of earlier stages, yet with increased open editorial input. 3.2. What are the editors’ personal opinions about open science and peer review? In this section we move more explicitly toward the chief editors’ subjective perspectives concerning the review process. After that, we discuss the results via our research questions. Post-review Namely, the peer review of a publication is not something that takes place in or by the journal alone; rather, journal review is one evaluative event in an article’s life, which continues post-publication as peers read and review it in academic forums: So if the paper is not good, it will be lost in history, it won’t get citations. If it's really influential but problematic, there will be some dialogue, there will be some criticism, there will be some contrasting results presented and so on. So if the paper is not good, it will be lost in history, it won’t get citations. If it's really influential but problematic, there will be some dialogue, there will be some criticism, there will be some contrasting results presented and so on. Summary: The post-review phase consists mainly of technical tasks such as copyediting. Some interviewees considered a positive publication decision as a potential reason for disclosing otherwise closed identities. Public review of articles starts after publication. Summary: The post-review phase consists mainly of technical tasks such as copyediting. Some interviewees considered a positive publication decision as a potential reason for disclosing otherwise closed identities. Public review of articles starts after publication. 3 2 What are the editors’ personal opinions about open science and peer review? Peer Review “So of course, I remove that – it’s unnecessary and insulting, and I rephrase it.” In other words, the respectful tone of the reviewers that was characterized as central for their journal’s review process is, at least in some cases, the result of an editorial process. Three other journals reported a similar policy, according to which a respectful tone was maintained by systematic review report editing. For some chief editors, the author’s identity was also relevant in the decision making process. Against the majority who considered anonymous double blind processes fair and objective, a minority felt that genuine fairness meant evaluating each submission in the context of the author’s current career stage and background: We get senior scholars, well known people, and we get graduate students. And I think that work is going to be assessed in part in relationship to the identity of the author. And so I think it's important for me, who's going to be making some decisions about that, to know that. Now that then also means that I have to be conscious, as conscious as I can about my biases and so on, and I try to do that. This was also the only one of our journals in which disclosed review practices were strongly present. At the other extreme, chief editors considered all transparency unethical and pursued complete anonymity at the screening phase too: We wanted to have a double blind review process, because that is, as far as one can tell, the most fair way of selecting what gets published. When I screen a manuscript, I also have them screened without any information about the authors. There might be a surname attached, but I normally will not look up who that person is before I screen it. Considering that all but one of the 12 journals were running completely closed double blind peer review processes, a common problem was that sometimes peer reviewers wished to disclose their identities to the authors. When asked, three journals reported such instances to be somehow linked to the Peer Reviewers’ Openness Initiative. The chief editors handled these requests in opposing ways: either allowing the reviewers to sign their reports, or denying disclosure. One chief editor felt that this transparency would challenge their values: I've pushed back on that, in the sense of we've stated very clearly that our journal is a double blind peer review journal. Peer Review Page 9/17 Page 9/17 A majority of the editors expressed, if not misgivings, then at least doubts about the universal viability of double blind peer review. The same chief editors likewise considered fully or partially disclosed open reviews problematic. For both sides, we identified seven unique but connected problems, which are presented in Table 1. In addition to these format-specific problems, five chief editors mentioned the general issue of external peer reviewers sometimes being too hasty and either providing little or no feedback to the authors. In these instances, the review reports were usually discarded and new reviewers were recruited. Our space does not allow discussing all 14 identified problems respectively, but it is worth dovetailing some selected concerns. First, we highlight the notion listed as ‘institutional discredit’, which some chief editors considered a key obstruction that makes even thinking about moving to open peer review not worth the time. Despite the fact that several world-leading journals such as those in the Nature- series support open review formats, many interviewees recognized the double blind as a ‘gold standard’ that they could not move away from without sacrificing credibility. The pedigree of these standards appeared important particularly for new burgeoning journals: We did not want to be innovative or be radical in any way. We wanted to have a journal that would be regarded and identified as a very standard traditional scientific scholarly journal, because we wanted to establish [our subfield] as a typical, solid, and traditional. Journals with a narrower regional or thematic focus likewise had a reason of their own for keeping the peer review process closed. Drawing on smaller numbers of authors and reviewers, anonymization was perceived essential to reduce conflicts of interest when virtually all experts are acquainted. One editor argued that, particularly in small, closely knit fields, peer-to-peer accountability based on disclosure of names might quickly devolve into “interpersonal as well as disciplinary conflicts.” The same editor mentioned a frequent need to revise the language of reviewers, because their observations seemed addressed to the editors rather than the authors, and formulated in a “language that would be shared among friends”, i.e. not always respectful. Peer Review The problems with these formats, particularly for those in early career stages, were connected to the fact that scholars have to live up to quality criteria about their publication styles and venues, with double blind peer review as a universal criterium. To create something that isn't going to provide people with a line they can put on their CV, under peer reviewed journal publication, that's a very tough thing to ask of people. And this is, to me, an incredible frustration because doing things like creating a podcast or blogging – or any number of things that we can think of that have happened over the last 15 years that would be valuable contributions to the scholarly conversation – are not going to count. Several voices echoed the above reality contributing to their lack of motivation to create something new, or anything that would not be traditional peer review. Reviewer Management The chief editors widely agreed on some central issues, the most fundamental of them being an unanimous satisfaction with the work of their peer reviewers, describing this collective contribution in downright enthusiastic terms. Three journals estimated the prevalence of ‘bad’ review reports numerically, saying them to be but 1%–2% of all received reports. In order to maintain high quality in their review processes and make sure that the review system would work in the future as well, the interviewees disclosed systematic and non- systematic means by which they keep track of both internal and external reviewers. we’re, of course, monitoring quality. We can tell reviewers that we don't find the quality of their review high enough. We will quietly not use those reviewers if they over time display signs of lacking diligence. It's a very simple method and it also works well. we’re, of course, monitoring quality. We can tell reviewers that we don't find the quality of their review high enough. We will quietly not use those reviewers if they over time display signs of lacking diligence. It's a very simple method and it also works well. We actually have this internal system, and most of us remember to rate the reviewer. When you go out and look for a reviewer, if you look in our system, you would see if one of the other editors had rated the reviewer very low. The concept of quality in the above and other cases was rarely a matter of content alone, but also reliability and speed. Reviewers who did not respect deadlines or were difficult to communicate with could likewise be classified bad quality, even though their feedback was appropriate. The concept of quality in the above and other cases was rarely a matter of content alone, but also reliability and speed. Reviewers who did not respect deadlines or were difficult to communicate with could likewise be classified bad quality, even though their feedback was appropriate. Related to the transparency of the peer review process, the interviewees listed miscellaneous elements that they considered topical. Peer Review When they submit their work, that is the practice that we're going to function under. I believe that if there is a desire on the part of the reviewer to want to make his or her name known to the author, that's actually pushing on a value system that the author may not agree. In line with the above, a majority of the editors described the conduct of their own journal as dependent on the context or conventions of their respective academic domain, suggesting that different fields needed different approaches to reviewing. For instance: Page 10/17 Ultimately we all want to publish the best of possible articles. So if one way works for an editorial board, fine. If another way works for a different journal, fine. In the end, people will read the final works published that contribute to scholarship. All the roads lead to Rome Page 10/17 Page 10/17 as far as I’m concerned. One chief editor, representing the humanities, explicitly called out the entire field lagging behind and lacking proper peer review to begin with. According to them, “there's too little blind review or even peer review in humanities ... we’ve been leaning on this curatorial model way too much, which also gives editors way too much power – that’s something where we have a lot to learn from other fields.” Another chief editor, speaking on behalf of communication studies, diagnosed open research practices as a reaction to bad research practices in other fields, and since “we have not encountered that type of difficulty, we can go about having a real discussion about what are the upsides and downsides.” Meanwhile, one interviewee felt that openness, as such, was not considered relevant within the SSH: authors seem to have very little interest in open science. I've also spent some time for an open data initiative and I'm surprised – the extent to which I don't see very many people actually interested. I just see a shrug of the shoulders. A kind of ‘Eh, this doesn't really apply to us, why would I want to do this? It’s just more work, it's more effort.’ Almost every journal also supported publication formats that were not peer reviewed or peer reviewed differently. Publication Metrics A further complicating matter in the picture were journal metrics, which for some served as a means to self-assess their own performance, yet at the other end of the spectrum, such numerical values were considered flawed and irrelevant. A half of the chief editors would indicate interest in the statistics, usually provided by the publisher. Only those whose journals were up for review through publishers felt that clicks, subscriptions, and other metrics mattered in practice. When asked specifically about the impact factor, replies ranged from moderate interest (“it's important for the publisher for sure – but it's also important for us”) to complete defiance (“fuck the impact factor”). Although all chief editors, except one, professed to be aware of the impact factor among similar metrics, there were no attempts at influencing journal policy from publishers or affiliated academic associations. On the other hand, the editors often admitted being pleased about their journal’s success, and since this success was typically validated by high journal rankings and peer recognition within the field, some felt that careful self-reflection was needed when assessing potential ‘high impact’ manuscripts. The thing goes back to the idea of rankings and stuff. So maybe I should publish more canonical stuff if I want to get higher. I don't want to think that way, but I know that. So how is that going to affect my practice? Again, the question was conventionally tied to the reality of academic careers and work. Even if the editors did not consider the impact factor relevant, many of their submitters did. In this way, the metrics had a direct impact on the journal’s profile and prestige, and whenever such metrics were not disclosed, the editors could receive requests to make them transparent. We occasionally get a request from an author for what our journal impact factor is. That typically comes up when an author is up for review, promotion or tenure. And I've written letters back to them saying it’s not our job to participate in the tenure review. To sum, the chief editors’ personal viewpoints regarding the review process, its management, and related journal metrics were occasionally in conflict with the values they acknowledged or how their journal operated in practice. By and large, the chief editors were aware of this and often actively pursued solutions, which nonetheless were difficult to implement. Reviewer Management For instance, one chief editor talked about marking submission, revision, and acceptance dates in the final article as a feature that can remove doubts about the process, however, it may also turn against the journal: I see on some journals now the notation ‘manuscript submitted on such and such a date, accepted such and such a date, published such and such a date’. I don't think that's a very revealing statistic or data point for a journal like ours where, in my opinion, so much of that timeline is outside my control. But it's part of greater transparency. We should also add that none of the journals provided financial compensation for their external peer reviewers who do all such work as free service. In general, finding external reviewers was one of the core challenges for journal editing, as multiple editors noted how it would not be unusual to ask up to 15 people to review before finding two who would agree. The trend was occasionally described as increasing (“there's a momentum building up”), in which case the chief editors felt unequipped to solve the problem due to lacking means for compensating the review work that they still needed to run the journal: “How do you reward reviewers? Because this whole Page 11/17 Page 11/17 gift economy depends on reviewers’ unpaid labor.” Systems like Publons were mentioned as possible solutions, with the caveat that they would not remove the original problem of volunteer work. gift economy depends on reviewers’ unpaid labor.” Systems like Publons were mentioned as possible solutions, with the caveat that they would not remove the original problem of volunteer work. Some journals actively pursued editorial diversity, for instance, by carefully managing the board with ethnicity, gender, and regions in mind. A few expressed surprise that such diversity should even be considered. In the external review process, the defining diversity concerns were about disciplinary or methodological domains, i.e. many chief editors felt that having ‘both sides of the coin’ would benefit the review, especially in polarized topics. RQ2: How do the chief editors position their journal’s review and publication practice between policy, ethics, and pragmatism? Given recent discussion of research ethics and calls for stricter fact checking in academic publications, questions of quality assurance were a key area highlighted in the interviews. There was a consensus that the existing (closed) structures and methods of their journals were tried and true, adequate means, given the various levels of oversight already in place. The practices of peer review, reviewer selection, and editorial oversight were contextualized by editors as a part of an overarching system. In this system, journals play a small part for the articles they publish. Studies will have been vetted by university ethics boards and national or international grant givers. The journal then assesses through peer review the relevance and innovation of the research, while at the same time itself being subjected to oversight by a publisher or other funder, mostly based on quantitative success criteria like the impact factor, number of downloads etc. Emerging binding guidelines like Plan-S and best-practice recommendations by institutions such as the Committee on Publishing Ethics (COPE) complicate the ‘system’ still. Within the above structures, especially the chief editors of our interdisciplinary journals leaning toward qualitative methods expressed satisfaction with the means and the degree of quality assurance done in their field, and particularly their own publication. One journal had begun using a software tool to verify integrity and originality, yet the chief editor stressed that the results required cautious interpretation because of a high amount of false positive results. Ultimately though, such structures were deemed safeguards of good scientific standards, and will not protect against hoaxes or conscious fraud. By and large, our study witnessed a view that editorial work and peer review serve not merely research publishing, but in the process elevate the quality of said research: “I think if we didn't believe that, we wouldn't do it – there's something valuable about vetting things.” Before conducting the interviews (https://osf.io/wjztp), we expected smaller and younger publications to adhere more strongly to changing standards in publication practices and enforce open practices more vehemently than more established journals. We were wrong. As mentioned before, only one journal clearly practiced an open form of review, and this journal was not young, but an average age in our journal sample and does not adhere to other open science principles (also representing paywalled access). 4. Discussion RQ1: How do highly ranked SSH journals perceive open peer review processes and do these perceptions materialize in the actual processes they employ? Our findings show a mixed pool of perspectives that highlight pros and cons equally in both open and closed peer review practices. Whereas the review process in all journals consisted of multiple stages from screening and review proper to revisions and post-review, most of the concerns centered on the externally recruited reviewers in a context that was fully closed, i.e. double blind (one partial exception). To wit, the chief editors connected several benefits and problems to review transparency, but applied transparent strategies mainly with regards to their own editorial work in which being able to identify the authors supposedly made the review more reliable and fair. It would be incorrect to present a simple or single reason for why the journals relied on the double blind peer review process – regardless of acknowledging numerous benefits in the open peer review forms that have been in dominant use in other fields beyond the SSH. Whereas the majority of the chief editors considered the double blind approach a ‘gold standard’ and had never given a serious thought to any other review formats, sometimes such opinions were also accompanied by a strong belief that open peer review could never be carried out without losing institutional support and academic credibility. That said, we may also speculate with the Page 12/17 Page 12/17 possibility that the SSH domain, defined by its humanistic and social roots, might just value the protective benefits of closed review more than other scientific fields and disciplines do. possibility that the SSH domain, defined by its humanistic and social roots, might just value the protective benefits of closed review more than other scientific fields and disciplines do. possibility that the SSH domain, defined by its humanistic and social roots, might just value the protective benefits of closed review more than other scientific fields and disciplines do. RQ3: How do the chief editors situate their own powerful role in the peer review process and in what way is that role negotiating open science principles of the peer review process? Few journals aimed at regulating editorial power. Several of our interviewees are founding members of their journal and perceive a strong identity between themselves and the journal. Only in two cases, interviewees reported fixed chief editorial tenures, whereas multiple had been in their function for one or more decades. One of the former said: “this is the association's journal and certainly isn’t mine – I just happen to be granted this opportunity to have a certain role at the time.” The same editor would also highlight that for the duration of their tenure as a chief editor, they had the final word in what gets published, potentially overruling external reviewers and associate editors, “so ultimately, the decision is mine.” In similar ways, almost all editors expressed in detail their awareness of their power, sometimes with strategies for managing it. Our findings indicate that SSH editors are aware of their power and try to moderate it through (often simple) self-policies, such as “I publish things I disagree with but I think are really important.” Journals with large editorial boards and shared editorial duties may have fine-tuned means for power management that our interviews were not able to chart; future research may shed more light on those. We must stress, however, that several chief editors were currently in a process of introducing or considering new open science principles (like data sharing) to their journals, and if necessary at some future time, there seem to be no technical limitations for extending such rework to the peer review process too. Conclusions Page 13/17 Page 13/17 Page 13/17 The pragmatics of organizing scientific journal peer review are difficult to completely align with the professional ethics generally striven for. If nothing else, then the necessity of selecting qualified reviewers that will not have an obvious conflict of interest is a step in the process practiced by all journals we spoke to, and one that can be assumed to be, in some form, practiced universally: “Their papers do go to referees, but then editors choose referees” (Macdonald & Kam 2007). Even though the issue itself is universal, our interviews showed that there are different strategies in place for addressing it. Reviewer selection can be shared, distributed, and delegated, editors can act as collectives, and individuals can rotate out of their position of power periodically, all in order to safeguard the integrity of the editorial process through infrastructure. Other journals implement none of these procedures and instead entrust their review process to a seasoned editor-in-chief whose experience, reputation, and integrity assure quality in a very different – some might say more traditional – manner. Furthermore, journals operate with bodies of reviewers ranging from a small circle of fixed members to an ever-growing, systematically curated network, often correlating with the volume of submissions to be processed. One of the small journals in our study operates with a fixed board of two dozen reviewing members, while the largest holds a database of 15.000 external reviewers. In all cases, editors were confident that the constituency of their authors and readership is satisfied with this organization, often arguing with widely held practices of their field. Based on our study, we cannot identify any method as better or worse for dealing with possible biases and other problems with reviewers or their selection (see Table 1). With reference to fact that many chief editors considered blind review as something that they need, not least to meet institutional gold standards, our study yields evidence for the SSH double blind process typically having a) the majority of submissions accepted or rejected non-blindly via editorial desk decisions, b) accepted or rejected non-blindly by reviewing editorial staff in post-screening phases, and c) accepted or rejected non-blindly by a combination of editors, or the chief editor, with double blind reports as material to consult in their final decision. Declarations Funding The work received funding from Academy of Finland (312397). Conflicts of interest/Competing interests. We have no conflicts of interest regarding this manuscript. Consent Written informed consent was collected from all participants. Availability of data and material. The data will remain closed due to the requests of some interviewees. Parts of the data may be shared e.g. for peer review purposes. Authors' contributions To be completed for publication. Authors' contributions To be completed for publication. Acknowledgements We thank all the participants for sharing their valuable time and making this research possible. Page 13/17 In rare instances are the authors communicated about the one-sided transparencies of this largely open process – which is called ‘double blind’ because one or two of the four review phases includes selected closed reports. A key outcome of our study is a brief policy recommendation for all journals to communicate the transparency elements of their peer review processes stage by stage – also and especially if they are ‘double blind’. All our interviewees took pains to explain the intricacy of the process of selecting and editing submissions for the profile of the journal. Although these profiles are found explicitly stated on the websites of all journals as a matter of course, the subtleties of the selection processes that inform the all-important early stages of screening and editorial review were difficult to articulate even for the seasoned editors we spoke to, and are accordingly not easily formalized in written, generalizable form. Some globally recognized multidisciplinary journals (e.g. Nature Human Behavior 2019) have already initiated efforts to clearly and comprehensively verbalize review transparency policies – however, to our knowledge, no journal has yet met the gold standards for communicating their transparencies of the actual multi-phase review process, the identification of which is hopefully easier after this article. References 1. Bornmann, L. (2008). Scientiﬁc peer review: An analysis of the peer review process from the perspective of sociology of science theories. Human Architecture: Journal of the Sociology of Self-Knowledge, 6(2), 3. 1. Bornmann, L. (2008). Scientiﬁc peer review: An analysis of the peer review process from the perspective of sociology of science theories. Human Architecture: Journal of the Sociology of Self-Knowledge, 6(2), 3. Page 14/17 Page 14/17 2. Burnham, John C. (1990). "The Evolution of Editorial Peer Review". JAMA: The Journal of the American Medical Association. 263 (10): 1323. 2. Burnham, John C. (1990). "The Evolution of Editorial Peer Review". JAMA: The Journal of the American Medical Association. 263 (10): 1323 3. Campbell, J. L., Quincy, C., Osserman, J., & Pedersen, O. K. (2013). Coding In-depth Semistructured Interviews: Problems of Unitization and Intercoder Reliability and Agreement. Sociological Methods & Research, 42(3), 294–320. https://doi.org/10.1177/0049124113500475 4. Chambers, C. (2017). The Seven Deadly Sins of Psychology: A Manifesto for Reforming the Culture of Scientific Practice. Princeton University Press. 5. Crotty, D. (2020). Two Steps Forward, One Step Back — The Pandemic’s Impact on Open Access Progress. Scholarly Kitchen, Aug. 4. https://scholarlykitchen.sspnet.org/2020/08/04/two-steps-forward-one-step-back-the-pandemics-impact-on-open-access- progress/ 6. Crüwell, S., Stefan, A.M. & Evans, N.J. Robust Standards in Cognitive Science. Comput Brain Behav 2, 255–265 (2019). https://doi.org/10.1007/s42113-019-00049-8 7. Ford, E. (2013). Defining and characterizing open peer review: A review of the literature. Journal of Scholarly Publishing, 44(4), 311- 326. 8. Garfield, E. (2004). Historiographic mapping of knowledge domains literature. Journal of Infor 8. Garfield, E. (2004). Historiographic mapping of knowledge domains literature. Journal of Information Science, 30(2), 119–145. 9. Godlee, F., Gale, C. R., & Martyn, C. N. (1998). Effect on the quality of peer review of blinding reviewers and asking them to sign their reports: a randomized controlled trial. Jama, 280(3), 237-240. 10. Gorman, G. E. (2007). The Oppenheim effect in scholarly journal publishing. Online Information Review. Vol. 31 No. 4, pp. 417-419. https://doi.org/10.1108/14684520710780386 11. Guetzkow, J., Lamont, M. & Mallard, G. (2004). “What Is Originality in the Humanities and the Social Sciences?” Am Sociol Rev 69 (2): 190–212. doi:10.1177/000312240406900203. 12. Hodson, R. (1999). Analyzing Documentary Accounts. Thousand Oaks, CA: Sage. 12. Hodson, R. (1999). Analyzing Documentary Accounts. Thousand Oaks, CA: Sage. 13. Macdonald, S., & Kam, J. (2007). Ring a ring o’roses: Quality journals and gamesmanship in management studies. Journal of Management Studies, 44(4), 640-655. 14. Manchikanti, L., Kaye, A. D., Boswell, M. References Nepotism and sexism in peer review. Nature, 387(6631), 341-343 28. Wold, A., & Wennerås, C. (1997). Nepotism and sexism in peer review. Nature, 387(6631), 341-343. 25. Van Rooyen, S., Godlee, F., Evans, S., Black, N., & Smith, R. (1999). Effect of open peer review on quality of reviews and on reviewers' recommendations: a randomised trial. Bmj, 318(7175), 23-27. M., & Mabe, M. (2015). The STM report: An overview of scientific and scholarly journal publishing 26. Walsh, E., Rooney, M., Appleby, L., & Wilkinson, G. (2000). Open peer review: a randomised controlled trial. The British Journal of Psychiatry, 176(1), 47-51. References V., & Hirsch, J. A. (2015). Medical journal peer review: Process and bias. Pain Physician, 18(1), E1 15. Morey, R. D., Chambers, C. D., Etchells, P. J., Harris, C. R., Hoekstra, R., Lakens, D., Lewandowsky, S. et al. (2016). “The Peer Reviewers' Openness Initiative: Incentivizing Open Research Practices Through Peer Review.” Royal Society open science 3 (1): 150547. doi:10.1098/rsos.150547. 16. Moylan, E. C., Harold, S., O’Neill, C., & Kowalczuk, M. K. (2014). Open, single-blind, double-blind: which peer review process do you prefer?. BMC Pharmacol Toxicol 15, 55 (2014). https://doi.org/10.1186/2050-6511-15-55. 17. Munafò, M., Nosek, B., Bishop, D. et al. A manifesto for reproducible science. Nat Hum Behav 1, 0021 (2017). https://doi.org/10.1038/s41562-016-0021 8. Nature Humam Behavior, 3, 1127–1128 (2019). https://doi.org/10.1038/s41562-019-0778-0 19. Nosek, B. A., Alter, G., Banks, G. C. , Borsboom, D. , Bowman, S. D., Breckler, S. J., Buck, S. et al. (2015). “Promoting an Open Research Culture.” Science (New York, N.Y.) 348 (6242): 1422–25. doi:10.1126/science.aab2374. 20. Peels, R., Bouter, L. (2018). “The Possibility and Desirability of Replication in the Humanities.” Palgrave Commun 4 (1). doi:10.1057/s41599-018-0149-x. 21. Risam, R. (2014). “Rethinking Peer Review in the Age of Digital Humanities.” Ada: A Journal of Gender, New Media, and Technology, Number 4 (4). doi:10.7264/N3WQ0220. 22. Shanahan, D. R., & Olsen, B. R. (2014). Opening peer-review: the democracy of science. Journal of Negative Results in Biomedicine 13, 2 (2014). https://doi.org/10.1186/1477-5751-13-2. 23. Tomkins, A., Zhang, M., & Heavlin, W. D. (2017). Reviewer bias in single-versus double-blind peer review. Proceedings of the National Academy of Sciences, 114(48), 12708-12713. 24. van den Eynden, V., Knight, G., Vlad, A., Radler, B., Tenopir, C., Leon, D., Manista, F., Whitworth, J., Corti, L. (2016). “Survey of Wellcome Researchers and Their Attitudes to Open Research.” https://doi.org/10.6084/m9.figshare.4055448.v1 Page 15/17 Page 15/17 25. Van Rooyen, S., Godlee, F., Evans, S., Black, N., & Smith, R. (1999). Effect of open peer review on quality of reviews and on reviewers' recommendations: a randomised trial. Bmj, 318(7175), 23-27. 26. Walsh, E., Rooney, M., Appleby, L., & Wilkinson, G. (2000). Open peer review: a randomised controlled trial. The British Journal of Psychiatry, 176(1), 47-51. 26. Walsh, E., Rooney, M., Appleby, L., & Wilkinson, G. (2000). Open peer review: a randomised controlled trial. The British Journal o Psychiatry, 176(1), 47-51. 27. Ware, M., & Mabe, M. (2015). The STM report: An overview of scientific and scholarly journal p Wold, A., & Wennerås, C. (1997). ennerås, C. (1997). Nepotism and sexism in peer review. Nature, 387(6631), 341-343. Tables Table 1. Open and closed peer review problems. Asterisk indicates that the referenced process is not fully open/closed. Page 16/17 Closed (blind) review problems easy to abuse by editors difficult to credit reviewer facilitates unwanted gatekeeping lack of accountability enables bad language use difficult or impossible to carry out in practice slows down communication Example “I know it can be abused, and that's what I am here to stop” “I mean, obviously a position like mine can be abused in that way. Without question, it would be very easy to do so. ” “one of the issues with blind peer review is, people never get credit for it. And increasingly, institutions are saying to faculty, tell us what you're doing in your annual reviews. And we were getting requests to say, can you write a letter saying that I did the peer review” “reviewers riding hobby horses about their own views” “I've seen cases where it seems to me, even though you try to avoid it, that a reviewer has a disagreement or a grudge against something, just has a fixation on whatever. Has a indefensible opposition to something,” “reviewer is grinding an axe behind the veil of anonymity” “the degree to which people have axes to grind or want to engage in some form of harassment or inappropriate behavior, a kind of single- sided process is probably not optimal at this point in time” * “review is shameful or aggressive or unprofessional or unethical” “the tone of the work has been more critical and constructive in a way that is not productive” “newly minted academics are sometimes a little too severe ... Square occasionally as well.” “Sometimes they say ‘I heard a paper at a conference two years ago and this looks like it’ and my response to that is: that's fine.” “I'm increasingly impatient with the norms for anonymizing, which almost becomes a game for reviewers to then try and figure out” “Reviewer sends his/her comments to the editor who sends it over to the author who responds to the editor who decides whether s/he is able to evaluate or sends it back to the reviewer and then they send comments again. Tables I don’t know if you could follow me” Open (disclosed) review problems institutional discredit doesn’t protect reviewers doesn’t protect authors reviewers cannot review candidly facilitates biases would hinder finding reviewers editorial challenges Example “that academic articles are double blind peer reviewed, it's sort of taken often blindly as a gold standard” “[Blinding] protects the reviewer and the author from any personal issue that might arise” “the standard reason is that the reviewer whose identity is protected has a license to be more candid” “I don't know if it would be a very fair system to young researchers, for example” “it’s established as a research fact that e.g. women would have a greater chance of being published if they were going through a double blind peer review”. “It has issues with what you dare to do as a reviewer” “The anonymity of reviewers is important, because you'll get honest reviews” “to me the core is having it read by somebody who can be candid.” “the prestige of the author might blind the reviewers, or the fact that you've never heard of the person” “[only blind] will protect people from unfair biases by the reviewers.” “it would even reduce the willingness of reviewers to participate” “it isn’t uncommon for me to go through maybe 12 declines before I find 2 reviewers. I'm not sure doing away with a blind review system’s the best thing. “somebody who's writing about queer studies may say ‘I think that a true peer is somebody who is queer’ but I will not ask somebody what their sexual orientation is” Page 17/17 Page 17/17
https://openalex.org/W2953327088	https://ora.ox.ac.uk/objects/uuid:e022a996-a91e-4c0b-a99a-4a114119caf0/download_file?safe_filename=nqz072.pdf&file_format=application%2Fpdf&type_of_work=Journal+article	English	null	Hematological parameters and prevalence of anemia in white and British Indian vegetarians and nonvegetarians in the UK Biobank	The American journal of clinical nutrition	2,019	cc-by	10,672	Am J Clin Nutr 2019;110:461–472. Printed in USA. Copyright © American Society for Nutrition 2019. All rights reserved. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. 461 http://www.isrctn.com/ as ISRCTN10125697. Am J Clin Nutr 2019;110:461–472. http://www.isrctn.com/ as ISRCTN10125697. Am J Clin Nutr 2019;110:461–472. http://www.isrctn.com/ as ISRCTN10125697. Am J Clin Nutr 2019;110:461–472. Background: There may be differences in hematological parameters between meat-eaters and vegetarians. Objective: The aim of this study was to perform cross-sectional analyses of hematological parameters by diet group in a large cohort in the United Kingdom. Keywords: UK Biobank, vegetarian, vegan, hematology, blood count, anemia, ethnicity Methods: A complete blood count was carried out in all UK Biobank participants at recruitment (2006–2010). We examined hemoglobin, red and white blood cell counts, and platelet counts and volume in regular meat eaters (>3 times/wk of red/processed meat consumption, n = 212,831), low meat eaters (n = 213,092), poultry eaters (n = 4815), fish eaters (n = 10,042), vegetarians (n = 6548), and vegans (n = 398) of white ethnicity and meat eaters (n = 3875) and vegetarians (n = 1362) of British Indian ethnicity. Downloaded from https://academic.oup.com/ajcn/article-abstract/110/2/461/5490685 by Said Business School user on 15 October 2019 Introduction Vegetarian and vegan diets are associated with lower BMI, blood pressure, and blood cholesterol concentrations (1–3). At the same time, the long-term exclusion of animal foods may lead to inadequate intakes of some essential nutrients that are not easily obtained from plant sources, especially without fortification (4, 5), and this may in turn affect hematological parameters. For example, red meat is a good source of heme iron, and poultry and fish also contain heme iron, which is more bioavailable than plant sources of iron; therefore, lack of meat or fish consumption may increase risk of iron-deficiency anemia (6). Indeed, several small studies reported that vegetarians and Results: In both white and British Indian populations, compared with regular meat eaters (or meat eaters in Indians), the other diet groups had up to 3.7% lower age-adjusted hemoglobin concentrations (difference not significant in white vegan women) and were generally more likely to have anemia (e.g., 8.7% of regular meat eaters compared with 12.8% of vegetarians in white premenopausal women; P < 0.05 after Bonferroni correction). In the white population, compared with regular meat eaters, all other diet groups had lower age- and sex-adjusted total white cells, neutrophils, lymphocytes, monocytes, and eosinophils (P-heterogeneity < 0.001 for all), but basophil counts were similar across diet groups; in British Indians, there was no significant difference in any of the white blood cell counts by diet group. Compared with white regular meat eaters, the low meat eaters, poultry eaters, fish eaters, and vegans had significantly lower platelet counts and higher platelet volume, whereas vegetarians had higher counts and lower volume. Compared with British Indian meat eaters, vegetarians had higher platelet count and lower volume. This work was supported by the UK Medical Research Council (MR/M012190/1), Wellcome Trust Our Planet Our Health (Livestock, Environment and People, LEAP 205212/Z/16/Z), and Cancer Research UK (C8221/A19170). KEB is supported by the Girdlers’ New Zealand Health Research Council Fellowship. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. The UK Biobank is an open-access resource. Bona fide researchers can apply to use the UK Biobank data set by registering and applying at http: //www.ukbiobank.ac.uk/register-apply/. Hematological parameters and prevalence of anemia in white and British Indian vegetarians and nonvegetarians in the UK Biobank Tammy YN Tong,1 Timothy J Key,1 Kezia Gaitskell,1,2 Timothy J Green,3 Wenji Guo,1 Thomas A Sanders,4 and Kathryn E Bradbury1,5 1Cancer Epidemiology Unit, Nuffield Department of Population Health, and 2Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom; 3Discipline of Paediatrics and Reproductive Health, School of Medicine, University of Adelaide, Adelaide, Australia; 4Department of Nutritional Sciences, King’s College London, London, United Kingdom; and 5National Institute for Health Innovation, School of Population Health, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand First published online June 13, 2019; doi: https://doi.org/10.1093/ajcn/ nqz072. Introduction Supplemental Methods, Supplemental Figure 1, and Supplemental Tables 1–10 are available from the “Supplementary data” link in the online posting of the article and from the same link in the online table of contents at https: //academic.oup.com/ajcn/. Conclusions: In the UK Biobank, people with low or no red meat intake generally had lower hemoglobin concentrations and were slightly more likely to be anemic. The lower white blood cell counts observed in low and non-meat eaters, and differences in mean platelet counts and volume between diet groups, warrant further investigation. This observational study was registered at First published online June 13, 2019; doi: https://doi.org/10.1093/ajcn/ nqz072. 461 462 Tong et al. Participants were included for analyses if they self-identified as “white” or as “Asian or Asian British” and subsequently as “Indian.” For consistency, participants are subsequently referred to as “white” or “British Indian.” The white population was included because it made up the majority of the UK Biobank population (∼94%), and the British Indian population was included due to the large proportion of vegetarians in this population group (24.6% compared with 1.7% in the overall cohort). The number of vegetarians in the other ethnic groups was small; therefore, other ethnic groups were excluded from these analyses. vegans had higher rates of anemia and lower hemoglobin or red blood cell counts compared with nonvegetarians (7–11). Vitamin B-12 is only present in animal foods; vegetarians, or vegans who exclude all animal foods from their diet, generally have a higher prevalence of vitamin B-12 deficiency (4, 12). Vitamin B-12 has a crucial role in various cellular processes, including the maturation of red blood cells (13), and may play a role in the platelet life cycle (14–16). Intake of dietary protein, or specific amino acids, which may be low in vegetarian diets (17), may also have a role in supporting the immune system, including production or activation of white blood cells (18, 19). Other nutrients, such as zinc, vitamin A, and riboflavin, which are less bioavailable in plant-based diets (5, 20), have also been linked to blood cell or hemoglobin production (21–25). Study design and participants The UK Biobank is a prospective cohort of >500,000 people aged 40–69 y, who were recruited in 2006–2010 across the United Kingdom (26). The scientific rationale and design of the UK Biobank study have been described in detail elsewhere (27). In brief, people who lived within traveling distance (∼25 km) of 1 of the 22 assessment centers across England, Wales, and Scotland were identified from National Health Service registers and invited to participate in the study. Permission for access to patient records for recruitment was approved by the Patient Information Advisory Group (now the National Information Governance Board for Health and Social Care) in England and Wales and by the Community Health Index Advisory Group in Scotland. Overall, ∼5.5% of the invitees attended a baseline visit (28) during which they gave informed consent to participate in UK Biobank using a signature capture device and completed a touch-screen questionnaire that asked about sociodemographic characteristics, lifestyle exposures [including diet, supplement use (e.g., formulations containing B vitamins, folic acid, multiple micronutrients, or iron), and smoking status], and general health and medical history. All participants also completed a computer- assisted personal interview and had physical measurements and blood samples taken. In addition to a self-administered questionnaire, additional dietary information was collected using a Web-based 24-h dietary assessment tool (29), which was administered ≤5 times in a large subsample of participants (∼210,000). This study was registered at http://www.isrctn.com/ as ISRCTN10125697. Blood measurements and hematological assays Blood sampling was performed by either a phlebotomist or a nurse in all participants except for a small proportion (0.3%) who declined, were deemed unable to undergo sampling, or where the attempt was abandoned for either technical or health reasons. Nonfasting blood samples were taken from a vein in the inner elbow using an 18-G vacutainer needle and barrel or, if that appeared unsuitable, from a vein on the back of the hand using a 21-G Safety Lok butterfly needle (BD) connected to a vacutainer barrel (27). For hematological assays, blood was collected into a 4-mL EDTA vacutainer and dispatched to the central processing laboratory in temperature-controlled shipping boxes (at 4◦C) (32). Complete blood cell counts were conducted using a Coulter Counter (Beckman Coulter), typically within 24 h of blood collection (32, 33). Because the hematological assays were performed throughout a long recruitment period (∼5 y), variation in blood count caused by laboratory drift cannot be ruled out despite efforts in quality control (further details are provided in the Supplementary Methods) (32), but any possible variation should be independent of diet group. Diet group classification There is limited robust evidence on the influence of vegetarian diets on hematological parameters, which might be reflective of anemia or immune status. Here, we examine the associations between varying degrees of animal source food exclusion and hematological indices in a large population-based cohort of ∼500,000 participants in the United Kingdom who self-identified as white British or British Indians. To determine the classification of diet groups, we used methods previously described (1, 30). Briefly, participants were asked their frequency of consumption of processed meat, beef, lamb or mutton, pork, poultry (e.g., chicken or turkey), oily fish, other types of fish, eggs or foods containing eggs, and dairy products, in 6 categories of frequency ranging from “Never” to “Once or more daily.” Based on these questions, 6 diet groups were defined for the white British population: regular meat eaters (red and processed meat consumption >3 times/wk), low meat eaters (red and processed meat consumption ≤3 times/wk), poultry eaters (participants who ate poultry but no red or processed meat, regardless of whether they ate fish, dairy products, or eggs), fish eaters (participants who ate fish but no red or processed meat or poultry), vegetarians (participants who did not eat meat, poultry, or fish), and vegans (participants who further excluded dairy products and eggs). Two diet groups were defined for the British Indian population: meat eaters (ate any combination of red or processed meat or poultry) and vegetarians (excluding vegans). Information collected from the Web-based 24-h dietary assessment tool was used to estimate food and nutrient intakes (e.g., iron and vitamin B-12) in each diet group, based on McCance and Widdowson’s The Composition of Foods and its supplements (29, 31). Results article-abstract/110/2/461/5490685 by Said Business School user on 15 October 2019 After excluding participants who had no hematological data (n = 24,336), reported other or unknown ethnicities (n = 21,851), or did not answer a sufficient number of questions to be classified into a diet group (n = 3393), 447,726 white British and 5237 British Indian participants were included in this analysis. Of the white British participants, 212,831 were classified as regular meat eaters, 213,092 as low meat eaters, 4815 as poultry eaters, 10,042 as fish eaters, 6548 as vegetarians, and 398 as vegans. Of the British Indian participants, 3875 were classified as meat eaters and 1362 as vegetarians. A participant flowchart of the inclusion and exclusion criteria of this study is shown in Supplemental Figure 1. Statistical analyses Baseline characteristics of the cohort were tabulated by 6 diet groups in white British participants and by 2 diet groups in British Indian participants. The primary outcomes of this research were blood counts and prevalence of anemia, and the secondary outcomes were prevalence of subtypes of anemia and prevalence of low platelet counts and elevated platelet volume. Linear regressions were modeled to estimate the adjusted mean levels (95% CIs) of each hematological parameter of interest, including hemoglobin, red blood cell count, reticulocyte percentage, immature reticulocyte frac- tion, total white blood cell count, neutrophils, lymphocytes, monocytes, eosinophils, basophils, platelet count, and platelet volume. Figure 1. Classification of anemia, low platelet count, and elevated platelet volume Classification of anemia, low platelet count, and elevated platelet volume “Do you have any long-standing illness, disability, or infirmity?” to remove the possible confounding effect of chronic illnesses on white cell or platelet count. Anemia was defined as hemoglobin concentrations of <130 g/L and <120 g/L for men and women, respectively, based on WHO criteria (34). Anemia severity was classified as mild (hemoglobin 110–129 g/L in men and 110–119 g/L in women), moderate (80–109 g/L in both sexes), and severe (<80 g/L in both sexes). To adjust for the effect of smoking on hemoglobin, when using hemoglobin levels to define anemia, 3 g/L was subtracted for all participants who indicated they were smokers (35), but original values of hemoglobin were used in all other analyses. If anemia was present, it was further defined as microcytic or macrocytic, based on a mean corpuscular volume of <80 fL or >100 fL, respectively (36). Secondarily, we also tested for any differences in the classification by correcting for hemoglobin levels using more detailed categorization of smoking status (<10 cigarettes smoked per day, no adjustment; ≥10 and <20 cigarettes smoked per day, −3 g/L; ≥20 and <40 cigarettes smoked per day, −5 g/L; ≥40 cigarettes smoked per day, −7 g/L; and unknown amount, −3 g/L). For classification of anemia, low platelet count, and elevated platelet volume, numbers and percentages of people in each diet group were reported as observed, based on criteria as previously described. For anemia, we additionally restricted the analyses to people who reported no iron or B vitamins supplement use. For each baseline characteristic and each hematological parameter of interest, post hoc pairwise comparisons based on linear regression models were used to test for significant differences between diet groups. For the white population, Bonferroni correction for multiple comparisons between the 6 diet groups was applied, and results reported here represent significant differences after Bonferroni correction, and by using regular meat eaters as the reference group, unless otherwise stated. All statistical analyses were performed using Stata release 15.1 (StataCorp), and 2-sided P values <0.05 were considered significant. For platelet count and volume, low platelet count was defined as <169.06 × 109 cells/L, and elevated platelet volume was defined as >11.24 fL, both as specified by the manufacturer’s reference range (33). Ethnicity classification On the touch-screen questionnaire, participants were asked to identify their ethnicity from options of “White,” “Mixed,” “Asian or Asian British,” “Black or Black British,” “Chinese,” “Other ethnic group,” “Do not know,” or “Prefer not to answer.” 463 Blood count and anemia in UK vegetarians Participant characteristics To estimate mean levels of hemoglobin, red blood cell count, reticulocyte percentage, and immature reticulocyte fraction, the regression model was stratified by sex and menopausal status (men, premenopausal women, and postmenopausal women) and adjusted for age of recruitment (5-y age groups from <45, 45– 49, 50–54, 55–59, 60–64, and ≥65 y). We additionally adjusted for smoking status (never, previous, current <15 cigarettes per day, current ≥15 cigarettes per day, and unknown) in a second model. There was little difference in reticulocyte percentage and immature reticulocyte fraction by sex and menopausal status; thus, we combined the 3 groups and adjusted for sex in the regression model for our main results and presented the stratified results secondarily. Characteristics of UK Biobank participants are shown in Tables 1 and 2. In the white population, low or non-meat eaters (fish eaters, vegetarians, and vegans) were more likely to be women, and non-meat eaters were younger. Except for vegans, low and non-meat eaters were less likely to report current smoking and the presence of long-standing illness. Non-meat eaters had a higher reported use of some specified supplements (formulations containing B vitamins, folic acid, multiple micronutrients, or iron), and low and non-meat eaters had on average higher total iron intake from foods (but lower or no iron intake from red or processed meat) and lower vitamin B-12 intake from foods (especially in vegetarians and vegans). Regarding the British Indian participants, vegetarians were slightly older and more likely to be women. They were less likely to report current smoking, more likely to report specified supplement use [formulations containing B vitamins, folic acid, multiple micronutrients, or iron (significant in women only)], and had lower mean vitamin B-12 intake from foods. To estimate mean levels of white cells (total white blood cell count, neutrophils, lymphocytes, monocytes, eosinophils, and basophils) and platelets (platelet count and platelet volume), the regression model was adjusted for age and sex and subsequently for smoking status. In addition, as a third model, we restricted the analysis to participants who answered “No” to the question 464 Tong et al. Participant characteristics TABLE 1 Baseline characteristics of white British participants by diet group in the UK Biobank1 Meat eaters Characteristics Regular consumption (>3 times/wk) (max n = 212,831)2 Low consumption (≤3 times/wk) (max n = 213,092)2 Poultry eaters (max n = 4815) Fish eaters (max n = 10,042) Vegetarians (max n = 6548) Vegans (max n = 398) P-het3 Age, y 56.8 ± 8.1a 56.9 ± 7.9b 56.7 ± 8.0a,b 54.2 ± 8.0c 52.8 ± 7.9d 54.3 ± 7.9c <0.001 Women, n (%) 91,398 (42.9)a 135,635 (63.7)b 3741 (77.7)c 7253 (72.2)d 4418 (67.5)e 232 (58.3)b <0.001 Premenopausal 20,791 (22.7) 29,570 (21.8) 810 (21.7) 2287 (31.5) 1636 (37.0) 76 (32.8) Postmenopausal 67,145 (73.5)a 101,184 (74.6)b 2797 (74.8)a,b 4643 (64.0)c 2583 (58.5)d 149 (64.2)a,b,c,d <0.001 Smoking status, n (%) Previous 76,402 (36.0) 74,826 (35.2) 1675 (34.9) 3705 (37.0) 2213 (33.9) 157 (39.5) Current 25,980 (12.2)a 18,852 (8.9)b 360 (7.5)c 719 (7.2)b,c 512 (7.8)c 31 (7.8)a,b,c <0.001 Has a long-standing illness, n (%) 71,900 (34.6)ha 63,876 (30.7)b 1498 (31.8)b 2703 (27.5)c 1835 (28.7)c,d 140 (35.8)a,b,d <0.001 Regular supplement user, n (%) B vitamins 7541 (3.5)a 9369 (4.4)b 449 (9.3)c 739 (7.4)d 541 (8.3)c,d 76 (19.1)e <0.001 Folic acid 3985 (1.9)a 4883 (2.3)b 214 (4.4)c 335 (3.3)d 199 (3.0)d 19 (4.8)c,d <0.001 Multiple micronutrients 40,911 (19.2)a 48,649 (22.8)b 1561 (32.4)c,d 3122 (31.1)c 2248 (34.3)d,e 155 (38.9)e <0.001 Iron, in men 2333 (1.9)a 1615 (2.1)a 50 (4.7)b 160 (5.7)b,c 134 (6.3)c 15 (9.0)c <0.001 Iron, in premenopausal women 1226 (5.9)a 1888 (6.4)a 76 (9.4)b 300 (13.1)c 236 (14.4)c 7 (9.2)a,b,c <0.001 Iron, in postmenopausal women 1667 (2.5)e 2749 (2.7)e 152 (5.4)d 327 (7.0)c 215 (8.3)b 23 (15.4)a <0.001 Mean dietary iron intake, mg/d (95% CI)4 13.7 (13.7, 13.8)a 13.5 (13.5, 13.5)b 13.9 (13.7, 14.1)b 14.6 (14.5, 14.7)c 14.6 (14.4, 14.7)c 16.9 (16.4, 17.4)d <0.001 From red or processed meat4 1.42 (1.41, 1.43)a 1.02 (1.01, 1.03)b — — — — <0.001 From poultry and fish4 0.56 (0.55, 0.56)a 0.60 (0.59, 0.60)b 0.74 (0.71, 0.76)c 0.48 (0.46, 0.49)d — — <0.001 Mean dietary vitamin B-12 intake, μg/d (95% CI)4 6.74 (6.71, 6.77)a 6.48 (6.45, 6.51)b 6.42 (6.23, 6.60)b 6.03 (5.91, 6.14)c 2.96 (2.82, 3.10)d 0.88 (0.31, 1.45)e <0.001 1Values are means ± SDs unless otherwise indicated; n = 447,726. Hemoglobin levels, red blood cell counts, and prevalence of anemia low meat eaters, poultry eaters, fish eaters, and vegetarians (12.8% of vegetarians compared with 8.7% of regular meat eaters in premenopausal women and 5.8% of vegetarians compared with 3.4% of regular meat eaters in postmenopausal women) were more likely to have anemia. In British Indians, vegetarian men and postmenopausal women were more likely to have anemia compared with meat eaters (12.6% of vegetarian men compared with 7.6% of meat eaters and 19.2% of vegetarian post- menopausal women compared with 13.3% of meat eaters), but there was no statistically significant difference in premenopausal women (26.6% of vegetarian premenopausal women compared with 20.5% of meat eaters) (Table 4). Results were similar when we restricted the analyses to participants who did not report taking iron or B vitamin supplements and also when we applied more detailed correction for smoking; proportions of participants with microcytic or macrocytic anemia were small in all subgroups (Supplemental Tables 7 and 8). low meat eaters, poultry eaters, fish eaters, and vegetarians (12.8% of vegetarians compared with 8.7% of regular meat eaters in premenopausal women and 5.8% of vegetarians compared with 3.4% of regular meat eaters in postmenopausal women) were more likely to have anemia. In British Indians, vegetarian men and postmenopausal women were more likely to have anemia compared with meat eaters (12.6% of vegetarian men compared with 7.6% of meat eaters and 19.2% of vegetarian post- menopausal women compared with 13.3% of meat eaters), but there was no statistically significant difference in premenopausal women (26.6% of vegetarian premenopausal women compared with 20.5% of meat eaters) (Table 4). Results were similar when we restricted the analyses to participants who did not report taking iron or B vitamin supplements and also when we applied more detailed correction for smoking; proportions of participants with microcytic or macrocytic anemia were small in all subgroups (Supplemental Tables 7 and 8). Mean hemoglobin concentration, red blood cell count, reticu- locyte percentage, and immature reticulocyte fraction are shown in Figures 1 and 2 and Supplemental Tables 1–6. In white British participants, compared with regular meat eaters, all other diet groups had lower hemoglobin concentrations [e.g., 150.3 g/L (95% CI: 150.2, 150.3 g/L) in regular meat-eating men compared with 144.8 g/L (95% CI: 143.2, 146.3 g/L) in vegan men], but the difference was not statistically significant in vegan women (Figure 1 and Supplemental Tables 1–6). Downloaded from https://academic.oup.com/ajcn/article-abstract/110/2/461/5490685 by Said Business School user on 15 October 2019 1Values are means ± SDs unless otherwise indicated; n = 5237. max, maximum. 2Represents P for heterogeneity across the 2 diet groups, estimated by regressing each baseline characteristic against 3 2Represents P for heterogeneity across the 2 diet groups, estimated by regressing each baseline characteristic against diet group. ep ese ts o ete oge e ty ac oss t e d et g oups, est ated by eg ess g eac base e c a acte st c aga st d et g oup. 3Estimated based on a subsample who completed ≥1 Web-based 24-h dietary assessment and based on intakes from food sources only. Assessments were averaged for participants who completed >1 assessment. The numbers of British Indian participants who completed ≥1 dietary assessments were as follows: 1333 meat eaters, 397 vegetarians, and 248 vegans. Estimates were adjusted for age at recruitment (<45, 45–49, 50–54, 55–59, 60–64, and ≥65 y). p g y g p y g g g g p 3Estimated based on a subsample who completed ≥1 Web-based 24-h dietary assessment and based on intakes from food sources only. Assessments were averaged for participants who completed >1 assessment. The numbers of British Indian participants who completed ≥1 dietary assessments were as follows: 1333 meat eaters, 397 vegetarians, and 248 vegans. Estimates were adjusted for age at recruitment (<45, 45–49, 50–54, 55–59, 60–64, and ≥65 y). Hemoglobin levels, red blood cell counts, and prevalence of anemia All other diet groups also had lower red blood cell counts, lower reticulocyte percentages (not significant in vegans), and lower immature reticulocyte fraction (not significant in vegan men and premenopausal women who were low meat eaters, poultry eaters, or vegans). In British Indians, vegetarians had lower mean hemoglobin [e.g., 147.2 g/L (95% CI: 146.7, 147.7 g/L) in meat- eating men compared with 145.2 g/L (95% CI: 144.1, 146.2 g/L) in vegetarian men], reticulocyte percentage (not significant in premenopausal women), and immature reticulocyte fraction (not significant in premenopausal women), but similar red blood cell counts. In all populations, results were similar with or without adjustment for smoking. Participant characteristics Groups that do not share a superscript letter were significantly different at the 5% level from post hoc pairwise comparisons based on linear regression models and after Bonferroni correction for multiple comparisons. max, maximum. 2Includes participants who consume any red or processed meat (beef, lamb, pork, and processed meat), regardless of whether they consume poultry, fish, dairy, or eggs. Cutoffs of regular and low consumption were determined based on consumption of red and processed meat as reported on the touch-screen questionnaire. 3Represents P for heterogeneity across the six diet groups, estimated by regressing each baseline characteristic against diet group. 4Estimated based on a subsample who completed ≥1 Web-based 24-h dietary assessment and based on intakes from food sources only. Assessments were averaged for participants who completed >1 assessment. The numbers of white British participants who completed ≥1 dietary assessments were as follows: 87,525 regular meat eaters, 93,513 low meat eaters, 2165 poultry eaters, 5486 fish eaters, 3745 vegetarians, and 232 vegans. Estimates were adjusted for age at recruitment (<45, 45–49, 50–54, 55–59, 60–64, and ≥65 y). Downloaded from https://academic.oup.com/ajcn/article-abstract/110/2/461/5490685 by Said Business School user on 15 October 2019 Blood count and anemia in UK vegetarians 465 TABLE 2 Baseline characteristics of British Indian participants by diet group in the UK Biobank1 p p y g p Characteristics Meat eaters (max n = 3875) Vegetarians (max n = 1362) P-het2 Age, y 53.7 ± 8.4 55.0 ± 7.9 <0.001 Women, n (%) 1621 (41.8) 877 (64.4) <0.001 Premenopausal 565 (34.9) 229 (26.1) Postmenopausal 980 (60.5) 615 (70.1) <0.001 Smoking status, n (%) Previous 530 (13.8) 87 (6.4) Current 350 (9.1) 30 (2.2) <0.001 Has a long-standing illness, n (%) 1170 (31.5) 385 (29.5) 0.18 Regular supplement user, n (%) Vitamin B 198 (5.1) 89 (6.5) 0.047 Folic acid or folate 133 (3.4) 67 (4.9) 0.014 Multivitamins ± minerals 971 (25.1) 387 (28.4) 0.015 Iron, in men 82 (3.6) 23 (4.7) 0.25 Iron, in premenopausal women 79 (14.0) 46 (20.1) 0.032 Iron, in postmenopausal women 77 (13.6) 38 (16.6) 0.033 Mean dietary iron intake, mg/d (95% CI)3 11.8 (11.6, 12.1) 11.6 (11.1, 12.1) 0.34 From red or processed meat3 0.72 (0.65, 0.78) — — From poultry and fish3 0.60 (0.56, 0.63) — — Mean dietary vitamin B-12 intake, μg/d (95% CI)3 5.20 (4.95, 5.44) 2.55 (2.10, 3.00) <0.001 1 White blood cell count Total and specific (neutrophils, lymphocytes, monocytes, eosinophils, and basophils) white blood cell counts are shown by diet group in Figure 3 and Supplemental Tables 9 and 10. In the white population, compared with regular meat eaters, all other diet groups had lower mean counts of total white cells [e.g., 7.02 × 109 cells/L (95% CI: 7.01, 7.03 × 109 cells/L) in regular meat eaters compared with 6.22 × 109 cells/L (95% CI: 6.01, 6.43 × 109 cells/L) in vegans], neutrophils, lymphocytes, monocytes, and eosinophils; basophil counts appeared similar across diet groups, although counts were low overall. In the Indian population, there was no significant difference in any of the white blood cell counts between meat eaters and vegetarians. Numbers and proportions of people with anemia are reported in Tables 3 and 4. In white men, the proportion of people with anemia was significantly higher in fish eaters compared with regular meat eaters (3.9% compared with 2.9%, respectively), and although proportions with anemia were also higher in poultry eaters, vegetarians, and vegans, the difference was not statistically significant (Table 3). In both white premenopausal and postmenopausal women, compared with regular meat eaters, 466 Tong et al. FIGURE 1 Hemoglobin concentration and red blood cell count by diet group and ethnicity in the UK Biobank. Point estimates represent adjusted mean levels (95% CIs), estimated based on linear regression models. All estimates were adjusted for age at recruitment (<45, 45–49, 50–54, 55–59, 60–64, and ≥65 y) and smoking (never, previous, current <15 cigarettes/d, current ≥15 cigarettes/d, and unknown). Total numbers of men, premenopausal women, and postmenopausal women, respectively, in the diet groups were as follows: white regular meat eaters: 121,433, 20,791, 67,145; white low meat eaters: 77,457, 29,570, 101,184; white poultry eaters: 1074, 810, 2797; white fish eaters: 2789, 2287, 4643; white vegetarians: 2130, 1636, 2583; white vegans: 166, 76, 149; Indian meat eaters: 2254, 565, 980; Indian vegetarians: 485, 229, 615. P for heterogeneity across the diet groups (stratified by ethnicity and estimated by regressing each variable against diet group) was 0.01 for hemoglobin in British Indian premenopausal women, >0.5 for red blood cell count in all British Indians, and <0.001 for all other variables. et al. White blood cell count 466 Downloaded from https://academic.oup.com/ajcn/article-abstract/110/2/461/5490685 by Said Business School user on 15 October 2019 Downloaded from https://academic.oup.com/ajcn/article-abstract/110/2/461/5490685 by Said Business School user on 15 October 2019 FIGURE 1 Hemoglobin concentration and red blood cell count by diet group and ethnicity in the UK Biobank. Point estimates represent adjusted mean levels (95% CIs), estimated based on linear regression models. All estimates were adjusted for age at recruitment (<45, 45–49, 50–54, 55–59, 60–64, and ≥65 y) and smoking (never, previous, current <15 cigarettes/d, current ≥15 cigarettes/d, and unknown). Total numbers of men, premenopausal women, and postmenopausal women, respectively, in the diet groups were as follows: white regular meat eaters: 121,433, 20,791, 67,145; white low meat eaters: 77,457, 29,570, 101,184; white poultry eaters: 1074, 810, 2797; white fish eaters: 2789, 2287, 4643; white vegetarians: 2130, 1636, 2583; white vegans: 166, 76, 149; Indian meat eaters: 2254, 565, 980; Indian vegetarians: 485, 229, 615. P for heterogeneity across the diet groups (stratified by ethnicity and estimated by regressing each variable against diet group) was 0.01 for hemoglobin in British Indian premenopausal women, >0.5 for red blood cell count in all British Indians, and <0.001 for all other variables. classified as having low platelet count or elevated platelet volume (Supplemental Tables 7 and 8). Results were similar with or without adjustment for smoking and when including only people who reported having no long- standing illness (n = 295,590 in white British participants; n = 3465 in British Indian participants). Discussion The current study, with >450,000 participants, is the largest study ever conducted to examine hematological parameters by degrees of animal food consumption in white British and British Indian individuals. In the white British population, compared with regular meat eaters, low or non-meat eaters generally had lower hemoglobin concentrations and were more likely to have anemia, and they had lower white blood cell counts. Vegans had lower mean platelet count and higher mean platelet volume, whereas the reverse was true for vegetarians. In British Indians, vegetarians had lower mean hemoglobin, were more likely to be anemic, and had higher platelet count but lower platelet volume compared with meat eaters. In addition to hematological conditions such as anemia or low platelet count, differences in blood count could be related to future risk of diseases (e.g., cardiovascular disease) or mortality (37–39). Platelet count and volume P for heterogeneity across the diet groups (stratified by ethnicity and estimated by regressing each variable against diet group) was >0.2 for reticulocyte percentage and immature reticulocyte fraction in British Indian premenopausal women and <0.001 for all other variables. Downloaded from https://academic.oup.com/ajcn/article abstract/11 Downloaded from https://academic.oup.com/ajcn/article-abstract/110/2/461/5490685 by Said Business School user on 15 October 2019 Downloaded from https://academic.oup.com/ajcn/article-abstract/110/2/461/5490685 by Said Business School user on 15 October 2019 FIGURE 2 Reticulocyte percentage and immature reticulocyte fraction by diet group and ethnicity in the UK Biobank. Point estimates represent adjusted mean levels (95% CIs), estimated based on linear regression models. All estimates were adjusted for age at recruitment (<45, 45–49, 50–54, 55–59, 60–64, and ≥65 y), sex, and smoking (never, previous, current <15 cigarettes/d, current ≥15 cigarettes/d, and unknown). Total numbers of participants in the diet groups were as follows: white regular meat eaters, 212,831; white low meat eaters, 213,092; white poultry eaters, 4815; white fish eaters, 10,042; white vegetarians, 6548; white vegans, 398; Indian meat eaters, 3875; and Indian vegetarians, 1362. P for heterogeneity across the diet groups (stratified by ethnicity and estimated by regressing each variable against diet group) was >0.2 for reticulocyte percentage and immature reticulocyte fraction in British Indian premenopausal women and <0.001 for all other variables. reported lower white blood cell counts (including lymphocytes and neutrophils) (7, 14, 40, 41) or platelet counts (41) in vegetarians or vegans compared with nonvegetarians. The only study that included British Indian vegetarians (n = 23) found that they had lower hemoglobin but higher platelet count compared with “Caucasian” vegetarians (n = 22) (11), which appeared consistent with our results. On the other hand, a few studies reported that compared with nonvegetarians, vegetarians or vegans had similar levels of hemoglobin (42) or white blood cell counts (8), or higher red blood cell counts (43). Overall, because these previous studies were small, they may lack sufficient statistical power to detect potential differences. blood cells and a higher risk of anemia (51). However, as shown in Tables 1 and 2, low or non-meat eaters were more likely to take iron supplements, as well as multivitamins that may contain iron, which could help prevent or correct anemia. For example, anemia in vegans in the UK Biobank seemed to occur mostly in those who were not taking iron supplements, although numbers were too small to make valid conclusions. Platelet count and volume Mean levels of platelet count and platelet volume are plotted in Figure 4 and shown in Supplemental Tables 9 and 10. Compared with white regular meat eaters (mean: 254.5 × 109 cells/L; 95% CI: 254.2, 254.7 × 109 cells/L), the low meat eaters, poultry eaters, fish eaters, and vegans (mean: 238.2 × 109 cells/L; 95% CI: 232.5, 243.9 × 109 cells/L) had lower mean platelet counts, whereas vegetarians had higher counts (mean: 258.2 × 109 cells/L; 95% CI: 256.8, 259.7 × 109 cells/L). On the other hand, vegetarians had lower mean platelet volume (mean: 9.27 fL; 95% CI: 9.24, 9.29 fL), whereas the other diet groups, especially vegans (mean: 9.73 fL; 95% CI: 9.63, 9.84 fL), had higher platelet volumes compared with regular meat eaters (mean: 9.31 fL; 95% CI: 9.31, 9.32 fL). In British Indians, vegetarians had higher mean platelet count (mean: 266.7 × 109 cells/L; 95% CI: 263.3, 270.0 × 109 cells/L) but lower mean platelet volume (mean: 9.24 fL; 95% CI: 9.18, 9.30 fL) compared with meat eaters (mean: 256.1 × 109 cells/L; 95% CI: 254.1, 258.1 × 109 cells/L; mean: 9.39 fL; 95% CI: 9.36, 9.43 fL). Results were consistent when participants were Only a few small existing studies (n vegetarians <100) have reported on blood cell counts in different diet groups, but our findings corroborate their results. Studies have reported that compared with nonvegetarians, vegetarians or vegans had lower hemoglobin levels (7, 9, 10) or lower red blood cell count (8, 11), but the sample sizes of these studies were too small to accurately assess differences in anemia. Other studies have also 467 Blood count and anemia in UK vegetarians Blood count and anemia in UK vegetarians 467 FIGURE 2 Reticulocyte percentage and immature reticulocyte fraction by diet group and ethnicity in the UK Biobank. Point estimates represent adjusted mean levels (95% CIs), estimated based on linear regression models. All estimates were adjusted for age at recruitment (<45, 45–49, 50–54, 55–59, 60–64, and ≥65 y), sex, and smoking (never, previous, current <15 cigarettes/d, current ≥15 cigarettes/d, and unknown). Total numbers of participants in the diet groups were as follows: white regular meat eaters, 212,831; white low meat eaters, 213,092; white poultry eaters, 4815; white fish eaters, 10,042; white vegetarians, 6548; white vegans, 398; Indian meat eaters, 3875; and Indian vegetarians, 1362. Platelet count and volume TABLE 3 Anemia prevalence in white British participants by diet group in the UK Biobank1 Meat eaters Classification2 Regular consumption (>3 times/wk) (total n = 212,831)3 Low consumption (≤3 times/wk) (total n = 213,092)3 Poultry eaters (total n = 4815) Fish eaters (total n = 10,042) Vegetarians (total n = 6548) Vegans (total n = 398) P-het4 Anemia in men, n (%) 3517 (2.9)a 2200 (2.8)a 43 (4.0)a,b 108 (3.9)b 83 (3.9)a,b 11 (6.6)a,b <0.001 Mild 3239 (2.7) 2049 (2.6) 38 (3.5) 104 (3.7) 78 (3.7) 9 (5.4) Moderate 261 (0.2) 142 (0.2) 5 (0.5) 4 (0.1) 5 (0.2) 1 (0.6) Severe 17 (0.0)a 9 (0.0)a 0 (0.0)a,b 0 (0.0)a 0 (0.0)a,b 1 (0.6)b <0.001 Anemia in premenopausal women, n (%) 1804 (8.7)a 2888 (9.8)b 105 (13.0)c 309 (13.5)c 209 (12.8)c 6 (7.9)a,b,c <0.001 Mild 1346 (6.5) 2097 (7.1) 81 (10.0) 230 (10.1) 146 (8.9) 4 (5.3) Moderate 442 (2.1) 766 (2.6) 23 (2.8) 75 (3.3) 63 (3.9) 0 (0.0) Severe 16 (0.1)a 25 (0.1)b 1 (0.1)b,c 4 (0.2)c 0 (0.0)c 2 (2.6)a,b,c <0.001 Anemia in postmenopausal women, n (%) 2300 (3.4)a 3838 (3.8)b 154 (5.5)c 248 (5.3)c 149 (5.8)c 6 (4.0)a,b,c <0.001 Mild 1974 (2.9) 3331 (3.3) 140 (5.0) 218 (4.7) 129 (5.0) 5 (3.4) Moderate 315 (0.5) 494 (0.5) 13 (0.5) 30 (0.6) 20 (0.8) 0 (0.0) Severe 11 (0.0)a 13 (0.0)b 1 (0.0)c 0 (0.0)c 0 (0.0)c 1 (0.7)a,b,c <0.001 TABLE 3 Anemia prevalence in white British participants by diet group in the UK Biobank1 Meat eaters Classification2 Regular consumption (>3 times/wk) (total n = 212,831)3 Low consumption (≤3 times/wk) (total n = 213,092)3 Poultry eaters (total n = 4815) Fish eaters (total n = 10,042) Vegetarians (total n = 6548) Vegans (total n = 398) P-het4 Anemia in men, n (%) 3517 (2.9)a 2200 (2.8)a 43 (4.0)a,b 108 (3.9)b 83 (3.9)a,b 11 (6.6)a,b <0.001 Mild 3239 (2.7) 2049 (2.6) 38 (3.5) 104 (3.7) 78 (3.7) 9 (5.4) Moderate 261 (0.2) 142 (0.2) 5 (0.5) 4 (0.1) 5 (0.2) 1 (0.6) Severe 17 (0.0)a 9 (0.0)a 0 (0.0)a,b 0 (0.0)a 0 (0.0)a,b 1 (0.6)b <0.001 Anemia in premenopausal women, n (%) 1804 (8.7)a 2888 (9.8)b 105 (13.0)c 309 (13.5)c 209 (12.8)c 6 (7.9)a,b,c <0.001 Mild 1346 (6.5) 2097 (7.1) 81 (10.0) 230 (10.1) 146 (8.9) 4 (5.3) Moderate 442 (2.1) 766 (2.6) 23 (2.8) 75 (3.3) 63 (3.9) 0 (0.0) Severe 16 (0.1)a 25 (0.1)b 1 (0.1)b,c 4 (0.2)c 0 (0.0)c 2 (2.6)a,b,c <0.001 Anemia in postmenopausal women, n (%) 2300 (3.4)a 3838 (3.8)b 154 (5.5)c 248 (5.3)c 149 (5.8)c 6 (4.0)a,b,c <0.001 Mild 1974 (2.9) 3331 (3.3) 140 (5.0) 218 (4.7) 129 (5.0) 5 (3.4) Moderate 315 (0.5) 494 (0.5) 13 (0.5) 30 (0.6) 20 (0.8) 0 (0.0) Severe 11 (0.0)a 13 (0.0)b 1 (0.0)c 0 (0.0)c 0 (0.0)c 1 (0.7)a,b,c <0.001 1n = 447,726. Platelet count and volume Groups that do not share a superscript letter were significantly different at the 5% level from post hoc pairwise comparisons based on linear regression models and after Bonferroni correction for multiple comparisons. 2Anemia is defined as hemoglobin <130 g/L for men and <120 g/L for women. Mild anemia, hemoglobin 110–129 g/L in men and 110–119 g/L in women; moderate anemia, hemoglobin 80–109 g/L (both sexes); and severe anemia, hemoglobin <80 g/L (both sexes). For defining anemia and all subtypes of anemia, hemoglobin is adjusted by −3 g/L in current smokers. 3Includes participants who consume any red or processed meat (beef, lamb, pork, and processed meat), regardless of whether they consume poultry, fish, dairy, or eggs. Cutoffs of regular and low consumption were determined based on consumption of red and processed meat as reported on the touch-screen questionnaire. 4Represents P for heterogeneity across the 6 diet groups, estimated by regressing each row variable against diet group. TABLE 3 Anemia prevalence in white British participants by diet group in the UK Biobank1 3Includes participants who consume any red or processed meat (beef, lamb, pork, and processed meat), regardless of whether they consume poultry, fish, dairy, or eggs. Cutoffs of regular and low consumption were determined based on consumption of red and processed meat as reported on the touch-screen questionnaire. 4 f h i h 6 di i d b i h i bl i di of the current study, which aimed to assess the differences across diet groups. classify anemia were not available. Hence, it was not possible to determine how these factors affected the distribution of anemia subtypes in different diet groups. A high white blood cell count has been proposed as an early marker of inflammation, and in prospective studies it has been associated with a higher risk of chronic diseases or death (37–39). Evidence linking vegetarian diets to risk of chronic inflammation is limited, but some studies suggest that long-term vegetarianism is associated with lower concentrations of other inflammatory biomarkers, such as C-reactive protein (55, 56). On the other hand, a low white blood cell count may also be an indication of an impaired immune system or abnormal bone marrow pathology (57). Platelet count and volume In addition, zinc is a catalyst in iron metabolism (21) and is less bioavailable in vegetarian diets (5), and low serum zinc levels have been associated with anemia (21, 22). Vegetarians or vegans also tend to have lower intakes of other micronutrients, such as vitamin A or riboflavin (20), which might also have roles in blood cell or hemoglobin production (24, 25). Low or non-meat eaters in the UK Biobank would have little or no intake of heme iron (estimated to be ∼40% of iron from meat sources) (44), which is more easily absorbed than non-heme iron (present in plant foods such as cereals, vegetables, pulses, and fruits) (45, 46). Although vegetarian and vegan diets are usually high in vitamin C (47), which enhances iron absorption, plant-based diets also contain significant amounts of phytates and tannins, which inhibit non-heme iron absorption (45). Previous studies showed that vegetarians had lower non-heme and total iron absorption, as well as lower ferritin concentrations, compared with nonvegetarians, despite similar or higher total dietary iron intake (11, 41, 48–50). Given the crucial role of iron in hemoglobin synthesis and red blood cell production (34), it would be expected that compared with regular meat eaters, low or non-meat eaters may have lower levels of hemoglobin and red Another explanation for differences in red blood cell count is that given the crucial role of vitamin B-12 in erythropoiesis, deficiency in this nutrient in vegetarians or vegans may result in red blood cells that do not develop normally and are too large to leave the bone marrow (13, 52, 53), which subsequently manifests as lower counts of reticulocytes and mature red blood cells in these diet groups. For subtypes of anemia, macrocytic anemia can be induced by vitamin B-12 deficiency but can be masked by the simultaneous presence of microcytic anemia in cases of severe iron deficiency or high folate intake (11, 14, 54); previous studies have shown that all 3 exposures are likely in vegetarians (11, 12, 41). Numbers for anemia subtypes were small in this study, however, and serum levels of relevant nutrients and other parameters that would be used in a clinical setting to 468 Tong et al. as hemoglobin <130 g/L for men and <120 g/L for women. Mild anemia, hemoglobin 110–129 g/L in men and 110–119i g g g g g a, hemoglobin 80–109 g/L (both sexes); and severe anemia, hemoglobin <80 g/L (both sexes). For defining anemia and all 1n = 5237. Anemia is defined as hemoglobin <130 g/L for men and <120 g/L for women. Mild anemia, hemoglobin 110–129 g/L in men and 110–119 g/L in women; moderate anemia hemoglobin 80–109 g/L (both sexes); and severe anemia hemoglobin <80 g/L (both sexes) For defining anemia and all e anemia, hemoglobin 80–109 g/L (both sexes); and severe anemia, hemoglobin <80 g/L (both sexes). For defining anemia l bi i dj t d b 3 /L i t k Platelet count and volume Vitamin B-12 deficiency is a reversible cause of bone Although anemia might also be caused by β-thalassemia (52), there is no reason to suspect this genetic condition should vary by diet group, but ethnic differences are possible (53). The prevalence of anemia in British Indians in our cohort was much higher than in the corresponding white British groups; iron intake, especially iron from red or processed meat in the meat eaters, and dietary vitamin B-12 intake were also lower in British Indians. However, detailed comparisons of hematological characteristics across different ethnicities are beyond the scope TABLE 4 Anemia prevalence in British Indian participants by diet group in the UK Biobank1 Classification Meat eaters (total n = 3875) Vegetarians (total n = 1362) P-het2 Anemia in men, n (%) 172 (7.6) 61 (12.6) <0.001 Mild 157 (7.0) 59 (12.2) Moderate 15 (0.7) 2 (0.4) Severe 0 (0.0) 0 (0.0) 0.002 Anemia in premenopausal women, n (%) 116 (20.5) 61 (26.6) 0.061 Mild 80 (14.2) 38 (16.6) Moderate 35 (6.2) 23 (10.0) Severe 1 (0.2) 0 (0.0) 0.042 Anemia in postmenopausal women, n (%) 130 (13.3) 118 (19.2) 0.002 Mild 106 (10.8) 92 (15.0) Moderate 24 (2.4) 24 (3.9) Severe 0 (0.0) 2 (0.3) <0.001 1n = 5237. Anemia is defined as hemoglobin <130 g/L for men and <120 g/L for women. Mild anemia, hemoglobin 110–129 g/L in men and 110–119 g/L in women; moderate anemia, hemoglobin 80–109 g/L (both sexes); and severe anemia, hemoglobin <80 g/L (both sexes). For defining anemia and all subtypes of anemia, hemoglobin is adjusted by −3 g/L in current smokers. 2Represents P for heterogeneity across the 2 diet groups, estimated by regressing each row variable against diet group. TABLE 4 Anemia prevalence in British Indian participants by diet group in the UK Biobank1 Blood count and anemia in UK vegetarians 469 Blood count and anemia in UK vegetarians 469 FIGURE 3 White blood cell counts by diet group and ethnicity in the UK Biobank. Point estimates represent adjusted mean levels (95% CIs), estimated based on linear regression models. All estimates were adjusted for age at recruitment (<45, 45–49, 50–54, 55–59, 60–64, and ≥65 y), sex, and smoking (never, previous, current <15 cigarettes/d, current ≥15 cigarettes/d, and unknown). Platelet count and volume Total numbers of participants in the diet groups were as follows: white regular meat eaters, 212,831; white low meat eaters, 213,092; white poultry eaters, 4815; white fish eaters, 10,042; white vegetarians, 6548; white vegans, 398; Indian meat eaters, 3875; and Indian vegetarians, 1362. P for heterogeneity across the diet groups (stratified by ethnicity and estimated by regressing each variable against diet group) was >0.1 for all variables in British Indians and <0.001 for all variables in white British participants. Downloaded from https://academic.oup.com/ajcn/article-abstract/110/2/461/5490685 by Said Business School user on 15 October 2019 Downloaded from https://academic.oup.com/ajcn/article-abstract/110/2/461/5490685 FIGURE 3 White blood cell counts by diet group and ethnicity in the UK Biobank. Point estimates represent adjusted mean levels (95% CIs), estimated based on linear regression models. All estimates were adjusted for age at recruitment (<45, 45–49, 50–54, 55–59, 60–64, and ≥65 y), sex, and smoking (never, previous, current <15 cigarettes/d, current ≥15 cigarettes/d, and unknown). Total numbers of participants in the diet groups were as follows: white regular meat eaters, 212,831; white low meat eaters, 213,092; white poultry eaters, 4815; white fish eaters, 10,042; white vegetarians, 6548; white vegans, 398; Indian meat eaters, 3875; and Indian vegetarians, 1362. P for heterogeneity across the diet groups (stratified by ethnicity and estimated by regressing each variable against diet group) was >0.1 for all variables in British Indians and <0.001 for all variables in white British participants. deficiency (14). Studies have documented that low platelet counts in vitamin B-12-deficient patients have responded to vitamin B- 12 therapy (16, 65). This fits with the observations of low platelet count and large platelet volume in the vegans in this study, but it does not explain the reverse pattern in vegetarians, who also have relatively low vitamin B-12 intakes. marrow failure (58), and some case reports have suggested a link between vitamin B-12 deficiency (more likely in vegetarians and vegans) and pancytopenia (low counts of red blood cells, white blood cells, and platelets) (59, 60). Differences in intake of other nutrients between the diet groups might also explain the differences in white blood cell count. Some evidence, largely from in vitro or animal studies, suggests that dietary proteins or specific amino acids might be integral to proper functioning of the immune system, including the production of blood cells (18, 19, 61, 62). Platelet count and volume Parallel evidence from large-scale human studies is lacking, but previous studies do show differences in dietary and serum amino acids between different diet groups (17). Alternatively, zinc deficiency has also been linked to impaired growth and functioning of immune cells (23). Note that although there were differences between the diet groups, all groups had mean white blood cell counts within the normal range (38, 57). Strengths of this study include the large sample size of ∼450,000 white and 5000 British Indians in the United Kingdom with complete blood counts; thus, this is the largest study ever conducted on the hematological and associated parameters by degrees of animal food consumption. In the white population, 6 distinct diet groups were included, which allowed the comparison of characteristics across varying degrees of consumption of ani- mal source foods, and we were also able to explore hematological indices separately in British Indians. As with all observational studies, some self-selection bias may be present, and only a modest proportion (5.5%) of invited participants agreed to take part, but a representative cohort is not necessary for making valid assessments of exposure–outcome associations (28). Because the study is cross-sectional, it was not possible to determine causality, and generalizability to other populations, especially ethnic groups other than white British or British Indians, might be limited. The findings would have been enhanced by the inclusion of various relevant indices, including serum ferritin, serum vitamin B-12, and other related markers, which were not In addition to their role in blood clotting, platelets are also believed to be involved in chronic inflammation, via interactions with endothelial cells and white blood cells (63, 64); hence, it might be reasonable that diet groups with a low white blood cell count should also have a low platelet count. Alternatively, due to the relatively high vitamin B-12 content in platelets compared to red blood cells (15), it has been suggested that vitamin B-12 has a prominent role in the platelet cell life cycle, and low platelet count and large platelet volume can be a symptom of vitamin B-12 470 Tong et al. FIGURE 4 Platelet count and volume by diet group and ethnicity in the UK Biobank. Point estimates represent adjusted mean levels (95% CIs), estimated based on linear regression models. Platelet count and volume All estimates were adjusted for age at recruitment (<45, 45–49, 50–54, 55–59, 60–64, and ≥65 y), sex, and smoking (never, previous, current <15 cigarettes/d, current ≥15 cigarettes/d, and unknown). Total numbers of participants in the diet groups were as follows: white regular meat eaters, 212,831; white low meat eaters, 213,092; white poultry eaters, 4815; white fish eaters, 10,042; white vegetarians, 6548; white vegans, 398; Indian meat eaters, 3875; and Indian vegetarians, 1362. P for heterogeneity across the diet groups (stratified by ethnicity and estimated by regressing each variable against diet group) was <0.001 for all variables. 470 Downloaded from https://academic.oup.com/ajcn/article-abstract/110/2/461/5490685 by Said Business School user on 15 October 2019 Downloaded from https://academic.oup.com/ajcn/article-abstract/110/2/461/5490685 by Said Business School user on 15 October 2019 Downloaded from https://academic.oup.com/ajcn/article-abstract/110/2/461/5490685 by Said Business School user on 15 October 2019 FIGURE 4 Platelet count and volume by diet group and ethnicity in the UK Biobank. Point estimates represent adjusted mean levels (95% CIs), estimated based on linear regression models. All estimates were adjusted for age at recruitment (<45, 45–49, 50–54, 55–59, 60–64, and ≥65 y), sex, and smoking (never, previous, current <15 cigarettes/d, current ≥15 cigarettes/d, and unknown). Total numbers of participants in the diet groups were as follows: white regular meat eaters, 212,831; white low meat eaters, 213,092; white poultry eaters, 4815; white fish eaters, 10,042; white vegetarians, 6548; white vegans, 398; Indian meat eaters, 3875; and Indian vegetarians, 1362. P for heterogeneity across the diet groups (stratified by ethnicity and estimated by regressing each variable against diet group) was <0.001 for all variables. available in this study. In addition, we did not determine the prevalence of genetic hemoglobin disorders, which can affect hemoglobin concentrations. 2. Appleby PN, Davey GK, Key TJ. Hypertension and blood pressure among meat eaters, fish eaters, vegetarians and vegans in EPIC-Oxford. Public Health Nutr 2002;5:645–54. 3. Bradbury KE, Crowe FL, Appleby PN, Schmidt JA, Travis RC, Key TJ. Serum concentrations of cholesterol, apolipoprotein A-I and apolipoprotein B in a total of 1694 meat-eaters, fish-eaters, vegetarians and vegans. Eur J Clin Nutr 2014;68:178–83. 90685 by In conclusion, in this large population study in the United Kingdom, people with low or no red meat intake generally had lower hemoglobin concentrations and were slightly more likely to be anemic. In the white population, but not the British Indians, low or non-meat eaters also had lower white blood cell counts. Platelet count and volume Both white and British Indian vegetarians had higher mean platelet counts and lower mean platelet volumes compared with meat eaters, whereas white vegans had lower mean platelet counts but higher platelet volumes. Future studies should investigate the mechanisms that explain these differences because they might be related to chronic disease risk. 4. Pawlak R, Lester SE, Babatunde T. The prevalence of cobalamin deficiency among vegetarians assessed by serum vitamin B12: a review of literature. Eur J Clin Nutr 2014;68:541–8. Said Bu 5. Hunt JR. Bioavailability of iron, zinc, and other trace minerals from vegetarian diets. Am J Clin Nutr 2003;78:633S–9S. sines 6. Gibson S, Ashwell M. The association between red and processed meat consumption and iron intakes and status among British adults. Public Health Nutr 2003;6:341–50. ss Schoo 7. Pongstaporn W, Bunyaratavej A. Hematological parameters, ferritin and vitamin B12 in vegetarians. J Med Assoc Thai 1999;82: 304–11. ol user o This research was conducted using the UK Biobank Resource under application 3037. The authors’ responsibilities were as follows—TYNT, TJK, and KEB: conceived and designed the research question; TYNT and KEB: analyzed the data; TYNT, TJK, and KEB: wrote the first draft of the manuscript; KG, TJG, WG, and TAS: provided input on data analysis and interpretation of results and reviewed subsequent drafts; and all authors: revised the manuscript critically for important intellectual content and read and approved the final manuscript. The authors report no conflicts of interest related to the study. 8. Elorinne AL, Alfthan G, Erlund I, Kivimäki H, Paju A, Salminen I, Turpeinen U, Voutilainen S, Laakso J. Food and nutrient intake and nutritional status of Finnish vegans and non-vegetarians. PLoS One 2016;11:1–14. 9. Gear JS, Mann JI, Thorogood M, Carter R, Jelfs R. Biochemical and haematological variables in vegetarians. Br Med J 1980;280:1415. ober 2 10. Li D, Sinclair AJ, Mann NJ, Turner A, Ball MJ. Selected micronutrient intake and status in men with differing meat intakes, vegetarians and vegans. Asia Pac J Clin Nutr 2000;9:18–23. 11. Reddy S, Sanders T. Haematological studies on pre-menopausal Indian and Caucasian vegetarians compared with Caucasian omnivores. Br J Nutr 1990;64:331–8. References High compliance with dietary recommendations in a cohort of meat eaters, fish eaters, vegetarians, and vegans: results from the European Prospective Investigation into Cancer and Nutrition-Oxford study. Nutr Res 2016;36:464–77. 10/2/461/549 25. García-Casal MN, Layrisse M, Solano L, Barón MA, Arguello F, Llovera D, Ramírez J, Leets I, Tropper E. Vitamin A and β-carotene can improve nonheme iron absorption from rice, wheat and corn by humans. J Nutr 1998;128:646–50. 48. Hunt JR, Roughead, ZK. Nonheme-iron absorption, fecal ferritin excretion, and blood indexes of iron status in women consuming controlled lactoovovegetarian diets for 8 wk. Am J Clin Nutr 1999;69:944–52. 90685 by S 26. Collins R. What makes UK Biobank special? Lancet 2012; s R. What makes UK Biobank special? Lancet 2012;379:1173– 27. UK Biobank Coordinating Centre. UK Biobank: Protocol for a Large-scale Prospective Epidemiological Resource [Internet]. 2007. Available from: http://www.ukbiobank.ac.uk/wp-content/uploads/201 1/11/UK-Biobank-Protocol.pdf. 49. Haider LM, Schwingshackl L, Hoffmann G, Ekmekcioglu C. The effect of vegetarian diets on iron status in adults: a systematic review and meta- analysis. Crit Rev Food Sci Nutr 2018;58:1359–74. Said Bus 28. Fry A, Littlejohns TJ, Sudlow C, Doherty N, Adamska L, Sprosen T, Collins R, Allen NE. Comparison of sociodemographic and health- related characteristics of UK Biobank participants with those of the general population. Am J Epidemiol 2017;186:1026–34. 50. Pawlak R, Bell K. Iron status of vegetarian children: a review of literature. Ann Nutr Metab 2017;70:88–99. siness 51. WHO. Blood Donor Counselling Implementation Guidelines [Internet]. 2014. Available from: http://www.who.int/bloodsafety/voluntary_don ation/Blooddonorcounselling.pdf. s Schoo 29. Liu B, Young H, Crowe FL, Benson VS, Spencer EA, Key TJ, Appleby PN, Beral V. Development and evaluation of the Oxford WebQ, a low- cost, web-based method for assessment of previous 24 h dietary intakes in large-scale prospective studies. Public Health Nutr 2011;14:1998– 2005. 52. Karimi M, Cohan N, De Sanctis V, Mallat NS, Taher A. Guidelines for diagnosis and management of β-thalassemia intermedia. Pediatr Hematol Oncol 2014;31:583–96. ol user o 53. Galanello R, Origa R. β-Thalassemia. Orphanet J Rare Dis 2010; 5:11. on 15 30. Bradbury KE, Tong TYN, Key TJ. Dietary intake of high-protein foods and other major foods in meat-eaters, poultry-eaters, fish- eaters, vegetarians, and vegans in UK Biobank. Nutrients 2017;9: 1317. 54. Kwok T, Cheng G, Woo J, Lai WK, Pang CP. Independent effect of vitamin B12 deficiency on hematological status in older Chinese vegetarian women. Am J Hematol 2002;70:186–90. October 31. References [The effect of vegetarian diet on selected biochemical and blood morphology parameters]. Rocz Panstw Zakl Hig 2007;58:23– 7. 18. Daly JM, Reynolds J, Sigal RK, Shou J, Liberman MD. Effect of dietary protein and amino acids on immune function. Crit Care Med 1990;18:S86–93. 41. Haddad EH, Berk LS, Kettering JD, Hubbard RW, Peters WR. Dietary intake and biochemical, hematologic, and immune status of vegans compared with nonvegetarians. Am J Clin Nutr 1999;70: 586–93. 19. Li P, Yin Y-L, Li D, Kim SW, Wu G. Amino acids and immune function. Br J Nutr 2007;98:237–52. 20. Kristensen NB, Madsen ML, Hansen TH, Allin KH, Hoppe C, Fagt S, Lausten MS, Gøbel RJ, Vestergaard H, Hansen T, et al. Intake of macro- and micronutrients in Danish vegans. Nutr J 2015;14:1–10. 42. Harvey LJ, Armah CN, Dainty JR, Foxall RJ, Lewis DJ, Langford NJ, Fairweather-Tait SJ. Impact of menstrual blood loss and diet on iron deficiency among women in the UK. Br J Nutr 2005;94:557. 21. Kelkitli E, Ozturk N, Aslan NA, Kilic-Baygutalp N, Bayraktutan Z, Kurt N, Bakan N, Bakan E. Serum zinc levels in patients with iron deficiency anemia and its association with symptoms of iron deficiency anemia. Ann Hematol 2016;95:751–6. 43. Sambol SZ, Stimac D, Orli´c ZC, Guina T. Haematological, biochemical and bone density parameters in vegetarians and non-vegetarians. West Indian Med J 2009;58:512–7. p.com/a 22. Houghton LA, Parnell WR, Thomson CD, Green TJ, Gibson RS. Serum zinc is a major predictor of anemia and mediates the effect of selenium on hemoglobin in school-aged children in a nationally representative survey in New Zealand. J Nutr 2016;146:1670–6. 44. Cross AJ, Harnly JM, Ferrucci LM, Risch A, Mayne ST, Sinha R. Developing a heme iron database for meats according to meat type, cooking method and doneness level. Food Nutr Sci 2012;3:905–13. 45. Hallberg L, Hulthén L. Prediction of dietary iron absorption: an algorithm for calculating absorption and bioavailability. Am J Clin Nutr 2000;71:1147–60. cle-abstr 23. Prasad AS. Zinc in human health: effect of zinc on immune cells. Mol Med 2008;14:353–7. 46. Wallace DF. The regulation of iron absorption and homeostasis. Clin Biochem Rev 2016;37:51–62. ract/1 24. Powers HJ, Hill MH, Mushtaq S, Dainty JR, Majsak-Newman G, Williams EA. Correcting a marginal riboflavin deficiency improves hematologic status in young women in the United Kingdom (RIBOFEM). Am J Clin Nutr 2011;93:1274–84. 47. Sobiecki JG, Appleby PN, Bradbury KE, Key TJ. References 12. Gilsing AMJ, Crowe FL, Lloyd-Wright Z, Sanders TAB, Appleby PN, Allen NE, Key TJ. Serum concentrations of vitamin B12 and folate in British male omnivores, vegetarians and vegans: results from a cross- sectional analysis of the EPIC-Oxford cohort study. Eur J Clin Nutr 2010;64:933–9. 1. Tong TY, Key TJ, Sobiecki JG, Bradbury KE. Anthropometric and physiologic characteristics in white and British Indian vegetarians and nonvegetarians in the UK Biobank. Am J Clin Nutr 2018;107: 909–20. Blood count and anemia in UK vegetarians 471 13. Koury MJ, Ponka P. New insights into erythropoiesis: the roles of folate, vitamin B12, and iron. Annu Rev Nutr 2004;24:105–31. 35. Sullivan KM, Mei Z, Grummer-Strawn L, Parvanta I. Haemoglobin adjustments to define anaemia. Trop Med Int Heal 2008;13:1267–71. 14. Obeid R, Geisel J, Schorr H, Hübner U, Herrmann W. The impact of vegetarianism on some haematological parameters. Eur J Haematol 2002;69:275–9. 36. Buttarello M. Laboratory diagnosis of anemia: are the old and new red cell parameters useful in classification and treatment, how? Int J Lab Hematol 2016;38:123–32. 15. Weiss HJ, Kelly A, Herbert V. Vitamin B12 and folate activity in normal human platelets. Blood 1968;31:258–62. 37. Danesh J, Collins R, Appleby P, Peto R. Association of fibrinogen, C- reactive protein, or leukocyte count with coronary heart disease. J Am Med Assoc 1998;279:1477–82. 16. Andrès E, Affenberger S, Zimmer J, Vinzio S, Grosu D, Pistol G, Maloisel F, Weitten T, Kaltenbach G, Blicklé JF. Current hematological findings in cobalamin deficiency: a study of 201 consecutive patients with documented cobalamin deficiency. Clin Lab Haematol 2006;28:50–6. 38. Shah AD, Thornley S, Chung S-C, Denaxas S, Jackson R, Hemingway H. White cell count in the normal range and short-term and long-term mortality: international comparisons of electronic health record cohorts in England and New Zealand. BMJ Open 2017;7:e013100. y p in England and New Zealand. BMJ Open 2017;7:e013100. 39. Kabat GC, Kim MY, Manson JE, Lessin L, Lin J, Wassertheil- Smoller S, Rohan TE. White blood cell count and total and cause- specific mortality in the Women’s Health Initiative. Am J Epidemiol 2017;186:63–72. 17. Schmidt JA, Rinaldi S, Scalbert A, Ferrari P, Achaintre D, Gunter MJ, Appleby PN, Key TJ, Travis RC. Plasma concentrations and intakes of amino acids in male meat-eaters, fish-eaters, vegetarians and vegans: a cross-sectional analysis in the EPIC-Oxford cohort. Eur J Clin Nutr 2016;70:306–12. 40. Nazarewicz R. References Holland B, Welch A, Unwin I, Buss D, Paul A, Southgate DAT. McCance and Widdowson’s the Composition of Foods. 5th ed. Cambridge (UK): Royal Society of Chemistry; 1991. 55. Jaceldo-Siegl K, Haddad E, Knutsen S, Fan J, Lloren J, Bellinger D, Fraser GE. Lower C-reactive protein and IL-6 associated with vegetarian diets are mediated by BMI. Nutr Metab Cardiovasc Dis 2018;28:787–94. r 2019 32. Elliott P, Peakman TC. The UK Biobank sample handling and storage protocol for the collection, processing and archiving of human blood and urine. Int J Epidemiol 2008;37:234–44. 56. Haghighatdoost F, Bellissimo N, Totosy De Zepetnek JO, Rouhani MH. Association of vegetarian diet with inflammatory biomarkers: a systematic review and meta-analysis of observational studies. Public Health Nutr 2017;20:2713–21. 33. Sheard SM, Froggatt J. UK Biobank Haematology Data Companion Document [Internet]. 2017. Available from: https://biobank.ctsu.ox.ac .uk/crystal/docs/haematology.pdf. 57. Osei-Bimpong A, Mclean R, Bhonda E, Lewis SM. The use of the white cell count and haemoglobin in combination as an effective screen to predict the normality of the full blood count. Int J Lab Hematol 2012;34:91–7. 34. WHO. Haemoglobin Concentrations for the Diagnosis of Anaemia and Assessment of Severity: Vitamin and Mineral Nutrition Information System Background [Internet]. 2011. Available from: https://www.who.int/vmnis/indicators/haemoglobin/en/. 472 Tong et al. in a model of protein-energy malnutrition. Nutrition 2010;26: 1021–8. in a model of protein-energy malnutrition. Nutrition 2010;26: 1021–8. 58. Stabler SP. Vitamin B deficiency. N Engl J Med 2013;368:149–60. 59. Randhawa J, Ondrejka SL, Setrakian S, Taylor H. What should I know before ordering a bone marrow aspiration/biopsy in patients with vitamin B12 deficiency? BMJ Case Rep 2013;2013:12–4. 63. Stokes KY, Granger DN. Platelets: a critical link between inflammation and microvascular dysfunction. J Physiol 2012;590: 1023–34. 60. Braza JM, Bhargava P. Medical mystery: a 71-year-old man with pancytopenia—the answer. N Engl J Med 2008;359:1941. 64. McNicol A, Israels SJ. Beyond hemostasis: the role of platelets in inflammation, malignancy and infection. Cardiovasc Hematol Disord Drug Targets 2008;8:99–117. 61. Cunha MCR, Lima F da S, Vinolo MAR, Hastreiter A, Curi R, Borelli P, Fock RA. Protein malnutrition induces bone marrow mesenchymal stem cells commitment to adipogenic differentiation leading to hematopoietic failure. PLoS One 2013;8:e58872. 65. Bolaman Z, Kadikoylu G, Yukselen V, Yavasoglu I, Barutca S, Senturk T. Oral versus intramuscular cobalamin treatment in megaloblastic anemia: a single-center, prospective, randomized, open-label study. Clin Ther 2003;25:3124–34. 62. References Fock RA, Blatt SL, Beutler B, Pereira J, Tsujita M, de Barros FE, Borelli P. Study of lymphocyte subpopulations in bone marrow Downloaded from https://academic.oup.com/ajcn/article-abstract/110/2/461/5490685 by Said Business School user on 15 October 2019
https://openalex.org/W3186699625	http://ejurnal.iaipd-nganjuk.ac.id/index.php/j-kis/article/download/188/135	Indonesian	null	Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL	Jurnal Komunikasi Islam	2,021	cc-by-sa	5,732	Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) 1Fitrianingsih, 2M. Alfin Fatikh 1Universitas Dr. Soetomo, 2Institut Pesantren KH. Abdul Chalim Pasuruan 1fitrianingsih.mikom@gmail.com, 2Muhammad.alfinfatikh@gmail.com 1Fitrianingsih, 2M. Alfin Fatikh 1Universitas Dr. Soetomo, 2Institut Pesantren KH. Abdul Chalim Pasuruan 1fitrianingsih.mikom@gmail.com, 2Muhammad.alfinfatikh@gmail.com ABSTRACT Indonesia citizenship nowdays is a citizens who are in transitional condition which is growing up from agraris citizenship who full with spiritualistic become modern industrial citizenship who materialistic. Even they have different personal act to communicate or socialize. The socialitation we can be using a social media. For the example in media telecommunication. Telephone which at the start were statistic media changes to be better, smarter, easier with mobile to reach the internet. To connect to internet mobile of course we need a provider who has internet data connection. For the experience of internet data researchers are using 3 providers which is Telkomsel, Indosat and XL. Telkomsel, Indosat and XL some of celluler telecomunication company operator in Indonesia. But the one which make it different is price, quality and signal. For the signal check we can see it from BTS (Base Transceiver Station) and for theory that been used for analysis of this researchers which have been choosen by the researchers is Uses and Gratifications Theory. Keywords: Considerations, Consumers, Providers ABSTRAK Untuk saat ini masyarakat Indonesia adalah masyarakat yang berada dalam kondisi peralihan berkembang dari masyarakat agraris yang penuh dengan spiritualistik menjadi masyarakat industri modern yang materialistis. Bahkan mereka memiliki tindakan pribadi yang berbeda untuk berkomunikasi atau bersosialisasi. Bersosialisasi dapat dilakukan dengan menggunakan media sosial. Sebagai contoh di media telekomunikasi, Telepon yang pada awalnya merupakan media statistik yang berubah menjadi lebih baik, lebih pintar, lebih mudah dengan handphone untuk akses internet. Untuk koneksi ke internet, pada handphone tentunya kita membutuhkan provider yang memiliki koneksi data internet. Untuk pengalaman data internet Periset menggunakan 3 provider yaitu Telkomsel, Indosat dan XL. Telkomsel, Indosat dan XL merupakan beberapa operator perusahaan telekomunikasi di Indonesia. Tapi yang membuatnya berbeda adalah harga, kualitas dan sinyal. Untuk pemeriksaan sinyal kita dapat melihatnya dari BTS (Base Transceiver Station) dan untuk teori yang digunakan untuk analisis Penelitian ini yang telah dipilih oleh peneliti adalah Teori Uses and Gratifications. Keywords: Considerations, Consumers, Providers 15 Volume 02, Nomor 01, Juni 2021 Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) PENDAHULUAN Masyarakat terus bergerak dan tumbuh dari masyarkat tradisional menuju masyarkat modern, hal ini dibenarkan dengan mengutip pendapat Vinna Sri Yuniarti (Perilaku Konsumen Teori dan Praktek, 2015: 17) menjelaskan saat ini masyarakat Indonesia berubah dan berkembang dari masyarakat yang sedang berada dalam keadaan transisional yakni bergerak dari masyarakat agraris tradisional yang penuh dengan suasana spiritualistik menuju masyarakat industri modern yang materealistik. Sehingga menurut Vinna dalam terminologi tersebut ia menjelaskan bahwa keadaan Indonesia ini dikategorikan sebagai masyarakat yang sedang bergerak dari bentuk masyarakat yang penuh solidaritas organik. Dalam kondisi inilah dimungkinkan akan muncul fenomena kegalauan budaya pada tingkat individu dan tingkat sosial. Tuntutan zaman seperti yang disampaikan oleh Vinna (2015; 19) menitikberatkan pada zaman yang semakin maju mau tidak mau menyebabkan masyarakat juga turut berpartisipasi/mengikuti. Karena asumsi publik menyatakan jika orang tidak mengikuti trendsetter, maka ia akan dianggap katrok atau ketinggalan zaman. Hal itulah yang membuat masyarakat saat ini mau tidak mau harus mengikuti kemajuan dan perkembangan teknologi dan komunikasi. Para pakar dan praktisi teknologi informasi sudah sepakat, bahwa sekarang dan masa yang akan datang adalah era perangkat mobile. (Thomas Joseph, Apps The Spirit of Digital Marketing 3.0, 2002: 128) Berbicara mengenai perkembangan teknologi dan komunikasi, dengan teknologi mobile (handphone), konsumen dapat melakukan aktivitas apa saja, mulai dari chatting, perbankan, pesan barang, sampai berjejaring sosial. Biaya telekomunikasi dapat menjadi lebih murah dan setiap orang menjadi lebih terakses. Dampaknya antara lain dapat dilihat dari memudarnya usaha wartel dan warnet yang sempat booming beberapa waktu yang lalu. Nurudin, Sistem Komunikasi Indonesia (2010:187). Income dan teknologi telah berubah, demikian pulalah perilaku dan gaya hidup. Dalam telekomunikasi, telepon yang semula statis berubah menjadi mobile dan pergi mengikuti kaki melangkah. Telepon seluler tak hanya digunakan untuk menelpon tetapi juga untuk berkirim SMS (Short Message Service) dan foto. Ponsel kemudian menjadi (lebih) cerdas dan dengan mudah terhubung ke Internet. Dapat dilakukan mengirim dan menerima surel (surat elektronik). Memudahkan terjadinya sosial media atau jejaring sosial. Untuk terkoneksi ke jejaring sosial atau jaringan Internet pada mobile tentu diperlukan provider yang menyediakan kuota data. Untuk kuota data pada penelitian ini menggunakan 3 provider yaitu Telkomsel, Indosat dan juga XL. Tiga provider tersebut dipilih karena menempati posisi provider yang paling banyak dipergunakan oleh konsumen. Menurut pendapat Prof. Rhenald Kasali, Ph.D. PENDAHULUAN Untuk update jumlah pengguna Telkomsel, Indosat dan XL tahun 2014 dapat diihat pada tabel dibawah ini: Operator Seluler Pengguna Q1 Pengguna Q3 Telkomsel 132,7 Juta 139, 2 Juta XL Axiata 62,9 Juta 58,3 Juta Indosat 69,7 Juta 54,3 Juta Tabel 1.2 Jumlah Pengguna Provider Telkomsel, Indosat dan XL Sumber dari situs id.techinasia.com dan ditulis oleh Ketut Krisna Wijaya, tgl 25 November 2014 Tabel 1.2 Jumlah Pengguna Provider Telkomsel, Indosat dan XL Sumber dari situs id.techinasia.com dan ditulis oleh Ketut Krisna Wijaya, tgl 25 November 2014 Sumber dari teknoliputan6.com dapat dilihat dibawah ini daftar paket dari tiga provider, yaitu Telkomsel, Indosat dan juga XL Axiata sebagai perbandingan harga dan jumlah kuota yang didapatkan konsumen adalah sebagai berikut: 17 Volume 02, Nomor 01, Juni 2021 No Telkomsel (Simpati) Indosat (Freedom Combo) XL Axiata (XTRA Combo) 1 47.500.-/30 hari 59.000.-/30 hari 59.000.-/30 hari 2 Flash 3G (1GB) 24 jam kuota 3G (2GB) 24 jam kuota 3G (2GB) 3 Flash 00-07 MDS 2GB 24 jam kuota 4G (3GB) 24 jam kuota 4G (4GB) 4 HOOQ+VIU/30 Free Spotify bulan 1st 24 jam kuota Youtobe Volume 02, Nomor 01, Juni 2021 17 Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) hari (2GB) 5 Video Max 1GB Free 1GB kuota Stream On 10 Apps On 01.00-06.00 WIB kuota Youtobe Unlimited 6 - - Nelpon all opr 20’’ 7 - Akses aplikasi populer TANPA KUOTA dengan APPS ON Gratis berlangganan Genfix, Yonder, Tribe/30 hari Tabel 1.3 Perbandingan Harga dan Fitur Tiga Provider yaitu Telkomsel, Indosat dan XL. Sumber: teknoliputan6.com Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) Tanggal 28 April 2017, peneliti mendapatkan beberapa informasi terkait dengan Web dari Telkomsel yang diretas oleh Hecker. Hecker tersebut komplain mengenai harga dari kuota Telkomsel yang dikatakan mahal karena perbandingan harga dapat dilihat pada tabel diatas. Untuk jumlah kuota yang didapatkan lebih sedikit, tidak sebanding dengan harga yang ditawarkan oleh para pesaingnya dan respons masyarakat terkait dari kasus tersebut bermacam-macam. Baik itu mendukung aksi hacker dan ada pula yang mendukung Telkomsel. Untuk meneliti pertimbangan konsumen memilih Provider Telkomsel daripada Indosat dan XL adalah dengan menggunakan teori Uses and Gratifications dan teori SOR. PENDAHULUAN posisi tiga besar operator ponsel pada tahun 2006 adalah sebagai berikut: 16 Volume 02, Nomor 01, Juni 2021 p-ISSN 2723-4703 e-ISSN 2797-1619 http://ejurnal.iaipd-nganjuk.ac.id/index.php/j-kis/ Operator Jumlah Pelanggan Q2 (2006) Telkomsel 29,3 Juta (56, 8%) Indosat 13,9 Juta (26,9%)* XL 8,4 Juta (16,3%)**** Total 3 Besar 51,6 Juta (100%) Tabel 1.1 Posisi Tiga Besar Operator Ponsel oleh Prof. Rhenald Kasali, Ph.D. Tabel 1.1 Posisi Tiga Besar Operator Ponsel oleh Prof. Rhenald Kasali, Ph.D. Keterangan: * Kuartal ke-2 tahun 2006 Telkomsel (Juli 2006). Laporan Keuangan (Unaudited) Kuartal ke-2, 2006 * PT Indosat Tbk. (Juni 2006). Ikhtisar Laporan Keuangan Kuartal Ke-2, 2006 **** PT Excelcomindo Pratama Tbk. (Juni 2006). Laporan Pertumbuhan Pendapatan Kuartal Ke-2, 2006. * Kuartal ke-2 tahun 2006 Telkomsel (Juli 2006). Laporan Keuangan (Unaudited) Kuartal ke-2, 2006 * PT Indosat Tbk. (Juni 2006). Ikhtisar Laporan Keuangan Kuartal Ke-2, 2006 **** PT Excelcomindo Pratama Tbk. (Juni 2006). Laporan Pertumbuhan Pendapatan Kuartal Ke-2, 2006. PENDAHULUAN Teori Uses and Gratifications lebih menekankan pada pendekatan manusiawi dalam melihat media massa dan teori S-O-R adalah Stimulus-Organism-Respon yang melihat pada komponen-komponen sikap, opini, perilaku, kognisi, afeksi, konasi yang menjadi acuan dari penelitian tersebut. METODE PENELITIAN Metode penelitian yang dipergunakan oleh peneliti adalah case study (studi kasus). Mengutip pendapat Drs. Cholid Narbuko dan Drs. H. Abu Achmadi (2009: 46) menjelaskan bahwa ciri-ciri penelitian kasus merupakan penelelitian yang mendalam mengenai kasus tertentu yang hasilnya adalah gambaran lengkap dan terorganim mengenai para Informan dalam mempertimbangkan dalam memilih menggunakan provider Telkomsel dibandingkan dengan menggunakan provider Indosat dan juga XL. Karna itulah peneliti menggunakan penelitian kualitatif dengan pola deskriptif. Peneliti lebih memfokuskan kualitas penelitian dengan cara melakukan pendalaman dari kasus tersebut. Berdasarkan latar belakang masalah dan tujuan penelitian perlu adanya sebuah batasan di dalam melakukan penelitian ini agar tidak melebar. Maka dari itu peneliti membuat fokus penelitian sebagai berikut: Penelitian ini ada pada bidang komunikasi massa yang lebih fokus kepada komunikan yang menerima pesan dari media massa, Objek penelitian mengenai pertimbangan konsumen memilih provider Telkomsel daripada Indosat dan XL. Sehingga peneliti menggunakan 2 informan dari 19 Informan yaitu mahasiswa 18 Volume 02, Nomor 01, Juni 2021 p-ISSN 2723-4703 e-ISSN 2797-1619 http://ejurnal.iaipd-nganjuk.ac.id/index.php/j-kis/ Universitas DR. Soetomo Gedung H lantai IV Jl. Semolowaru 84, Surabaya 60118, Program Studi Magister Ilmu Komunikasi dengan minat studi Public Relations mahasiswa semester 3. Universitas DR. Soetomo Gedung H lantai IV Jl. Semolowaru 84, Surabaya 60118, Program Studi Magister Ilmu Komunikasi dengan minat studi Public Relations mahasiswa semester 3. Sumber data yang digunakan ada 2 macam yaitu sumber data primer dan sumber data sekunder. Mengutip pendapat Lofland dan Lofland (1984: 47) yang dituliskan oleh Dr. Lexy J. Moeleong M.A. pada buku Metodologi Penelitian Kualitatif (2002: 112) menjelaskan bahwa sumber data utama (primer) dalam penelitian kualitatif ialah kata-kata dan tindakan Maria Magdalena dan Fauziyah sebagai informan dan selebihnya adalah data tambahan (sekunder) seperti dokumen dan lain-lain. 1. Konsumen berperilaku sebagai respon yang rutin 1. Konsumen berperilaku sebagai respon yang rutin Pada tingkat ini, kedua pengguna provider baik itu Maria Madalena dan Fauziyah sudah mempunyai pengalaman mengenai ketegori produk dan serangkaian keriteria yang mereka tetapkan dengan baik untuk menilai berbagai merek yang mereka gunakan. Dalam beberapa situasi informan kemungkinan mencari informasi tambahan dan dalam situasi lain mereka hanya meninjau kembali apa yang sudah mereka ketahui mengenai provider yang mereka gunakan saat ini. Seberapa mendalam tugas pemecahan masalah mereka bergantung pada seberapa baik kriteria pemilihan yang telah mereka tetapkan, seberapa banyak informasi yang telah dimiliki mengenai provider yang mereka jadikan pertimbangkan dan seberapa terbatas rangkaian merek yang akan dipilih. Jelas bahwa untuk pemecahan masalah yang luas. Kedua informan harus mencari informasi yang lebih banyak untuk melakukan pilihan jika mereka menjadi konsumen yang tidak rutin menggunakan provider atau tidak loyal pada merek tersebut. Akan tetapi, informasi yang telah didapat menunjukkan bahwa ke dua informan baik Maria Magdalena dan Fauziyah memiliki perilaku respon yang rutin. Dimana, mereka hanya memerlukan sedikit informasi tambahan yang diperlukan. 2. Distribusi dan strategi pemasaran Telkomsel Dari situs resmi Telkomsel (http://www.telkomsel.com) Telkomsel Perluas Saluran Distribusi Layanan Menggandeng E-Commerce. Jakarta, 22 Desember 2016 - Telkomsel menggandeng 14 perusahaan e-commerce ternama di Indonesia untuk memperluas jaringan distribusi layanan. Kerjasama ini akan membuat pelanggan lebih mudah untuk memperoleh layanan Telkomsel melalui saluran daring (online channel) yang dimiliki Tokopedia, Kaskus, Alfacart, Blanja, Lazada, Go-Jek, Mataharimall, Traveloka, Bhinneka, Blibli, JD.id, Grab, Bukalapak, dan Dinomarket. 2. Distribusi dan strategi pemasaran Telkomsel Dari situs resmi Telkomsel (http://www.telkomsel.com) Telkomsel Perluas Saluran Distribusi Layanan Menggandeng E-Commerce. Jakarta, 22 Desember 2016 - Telkomsel menggandeng 14 perusahaan e-commerce ternama di Indonesia untuk memperluas jaringan distribusi layanan. Kerjasama ini akan membuat pelanggan lebih mudah untuk memperoleh layanan Telkomsel melalui saluran daring (online channel) yang dimiliki Tokopedia, Kaskus, Alfacart, Blanja, Lazada, Go-Jek, Mataharimall, Traveloka, Bhinneka, Blibli, JD.id, Grab, Bukalapak, dan Dinomarket. 3. Distribusi dan strategi pemasaran Indosat Bersumber dari (http://seemewendy.blogspot.co.id/p/blog- page_75.html) blog online yang ditulis oleh Wendy Ariesta menjelaskan bahwa Indosat memasarkan produk dan jasa selular dengan cara pemasaran langsung dan juga melalui agen penjualan. Persentase terbesar pendapatan usaha selular berasal dari agen-agen penjualan dalam kemitraan yang saling menguntungkan. HASIL DAN PEMBAHASAN Pada gambaran objek penelitian ini, peneliti menjelaskan lebih lanjut terkait dengan tiga provider yang digunakan oleh konsumen. Tiga provider itu dipilih karena merupakan provider dengan jumlah terbanyak untuk pengguna di Indonesia. Provider itu ang peneliti maksudkan terdiri dari Telkomsel, Indosat dan juga XL. Untuk perbandingan harga serta jumlah kuota yang didapatkan sudah peneliti bahas pada latar belakang dan hal menarik lainnya adalah mengenai Apa yang menjadi keistimewaan provider telkomsel, padahal telah diketahui sebelumnya bahwa harga dan kuota sangat jauh berbeda dengan para pesaingnya. Akan tetapi dengan melihat tabel jumlah pengguna provider pada tahun 2014 yang diambil oleh peneliti menjelaskan produk Telkomsel masih menempati urutan pertama dengan jumlah pengguna pada Quartal pertama ada 132,7 Juta pengguna dan untuk Quartal ketiga mengalami kenaikan dengan jumlah pengguna sebesar 139,2 Juta. Untuk provider kedua ditempati oleh XL Axiata dengan jumlah pengguna pada Quartal pertama sebanyak 62,9 Juta, lalu naik pada Quartal ketiga menjadi 58,3 Juta pengguna. Dan untuk provider terakhir ditempati oleh Indosat dengan jumlah pengguna sebanyak 69,7 Juta dan untuk Quartal ketiga sebanyak 54,3 Juta pengguna. Untuk Indosat dan XL pada Quartal kedua tahun 2006 data yang diambil oleh Prof. Rhenald Kasali, Ph.D. menjelaskan bahwa Indosat dan XL saling kejar mengejar dalam hal menempati posisi kedua dan ketiga karena untuk jumlah pengguna Indosat ada sebanyak 13,9 Juta sedangkan XL ada sebanyak 8,4 Juta pengguna. Sedangkan untuk Telkomsel masih menempati urutan pertama dengan jumlah pengguna 29,3 Juta. Meskipun sumber ini didapatkan baik itu dari tahun 2006 dan tahun 2014, pada tahun-tahun tersebut menjelaskan bahwa Telkomsel adalah provider yang paling banyak diminati oleh pengguna provider di tanah air meskipun harga yang ditawarkan berbeda dengan provider Indosat dan juga XL. Untuk temuan data di lapangan, peneliti akan menjelaskan beberapa hal yaitu sebagai berikut: 19 Volume 02, Nomor 01, Juni 2021 Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) 1. Konsumen berperilaku sebagai respon yang rutin Menurut Wendy Indosat ini memiliki lebih dari 325.000 Points of Sale (POS) yang dapat dibagi menjadi 280.000 outlet tradisional, lebih dari separuhnya bergabung dalam komunitas outlet Indosat; outlet modern dan perbankan yang terdiri dari 14.000 outlet retail modern seperti Indomaret, Alfamart, Carrefour, dsb, plus 30.000 POS berupa ATM bank; dan berbagai pusat penjualan dan layanan pelanggan terpadu yang dinamakan Galeri Indosat, Griya Indosat, dan KILAT. Wendy juga menjabarkan beberapa POS dari Indosat yang terdiri dari Galeri Indosat dikelola oleh Indosat, Griya Indosat dimiliki oleh agen 3. Distribusi dan strategi pemasaran Indosat Bersumber dari (http://seemewendy.blogspot.co.id/p/blog- page_75.html) blog online yang ditulis oleh Wendy Ariesta menjelaskan bahwa Indosat memasarkan produk dan jasa selular dengan cara pemasaran langsung dan juga melalui agen penjualan. Persentase terbesar pendapatan usaha selular berasal dari agen-agen penjualan dalam kemitraan yang saling menguntungkan. Menurut Wendy Indosat ini memiliki lebih dari 325.000 Points of Sale (POS) yang dapat dibagi menjadi 280.000 outlet tradisional, lebih dari separuhnya bergabung dalam komunitas outlet Indosat; outlet modern dan perbankan yang terdiri dari 14.000 outlet retail modern seperti Indomaret, Alfamart, Carrefour, dsb, plus 30.000 POS berupa ATM bank; dan berbagai pusat penjualan dan layanan pelanggan terpadu yang dinamakan Galeri Indosat, Griya Indosat, dan KILAT. Wendy juga menjabarkan beberapa POS dari Indosat yang terdiri dari Galeri Indosat dikelola oleh Indosat, Griya Indosat dimiliki oleh agen 20 Volume 02, Nomor 01, Juni 2021 p-ISSN 2723-4703 e-ISSN 2797-1619 http://ejurnal.iaipd-nganjuk.ac.id/index.php/j-kis/ penjualan, sedangkan KILAT (Indosat Sales & Service Kiosk) dimiliki dan dikelola oleh mitra perorangan Indosat. Pada akhir tahun 2011 tercatat 150 Galeri Indosat, 44 Griya Indosat dan 81 KILAT. penjualan, sedangkan KILAT (Indosat Sales & Service Kiosk) dimiliki dan dikelola oleh mitra perorangan Indosat. Pada akhir tahun 2011 tercatat 150 Galeri Indosat, 44 Griya Indosat dan 81 KILAT. 4. Distribusi dan strategi pemasaran XL Dari situs (https://www.xl.co.id/business/id/mengapa-xl/tentang.html) dari blog resmi dari XL Axiata menjelaskan bahwa XL Axiata berfokus pada 2 aspek bisnis utama, yaitu Consumer Solutions, yang ditujukan untuk pelayanan telepon seluler berkualitas tinggi dan Business Solutions yang ditujukan untuk penyediaan solusi data dan komunikasi yang sangat efisien dan terpercaya untuk pasar korporat. Pada blog resmi XL Axiata tersebut dapat diketahui bahwa XL Axiata mengawali tahun 2015 dengan dimulainya strategi baru dalam arah bisnis melalui implementasi Agenda Transformasi XL yang disebut dengan “3R Strategy”, yaitu: a) XL Axiata mengubah model bisnis pencapaian jumlah pelanggan (dari “volume” ke “value”), strategi distribusi serta meningkatkan profitabilitas produk. 1. Konsumen berperilaku sebagai respon yang rutin b) Dari blog resmi XL Axiata dapat diketahui bahwa mereka akan lebih fokus kepada peningkatan nilai brand XL dengan menggunakan dan melalui strategi dual- brand dengan AXIS untuk menyasar segmen pasar yang berbeda. c) XL Axiata Membangun dan menumbuhkan berbagai inovasi-inovasi bisnis. 5. Loyalitas Konsumen Vinna Sri Yuniarti, S.E., M.M. (Perilaku Konsumen, 2015:242) mengutip pendapat Tjiptono (2002) menjelaskan enam indikator yang dapat digunakan untuk mengukur loyalitas konsumen, yaitu: a) Pembelian ulang b) Kebiasaan mengonsumsi merek tersebut 5. Loyalitas Konsumen Vinna Sri Yuniarti, S.E., M.M. (Perilaku Konsumen, 2015:242) mengutip pendapat Tjiptono (2002) menjelaskan enam indikator yang dapat digunakan untuk mengukur loyalitas konsumen, yaitu: a) Pembelian ulang b) Kebiasaan mengonsumsi merek tersebut c) Selalu menyukai merek tersebut d) Tetap memilih merek tersebut e) Yakin bahwa merek tersebut yang terbaik f) Merekomendasikan merek tersebut kepada orang lain 5. Loyalitas Konsumen Vinna Sri Yuniarti, S.E., M.M. (Perilaku Konsumen, 2015:242) mengutip pendapat Tjiptono (2002) menjelaskan enam indikator yang dapat digunakan untuk mengukur loyalitas konsumen, yaitu: a) Pembelian ulang b) Kebiasaan mengonsumsi merek tersebut c) Selalu menyukai merek tersebut d) Tetap memilih merek tersebut e) Yakin bahwa merek tersebut yang terbaik f) Merekomendasikan merek tersebut kepada orang lain Teori Uses and Gratifications dan SOR Nurudin (Pengantar Komunikasi Massa, 2007; 191-195) menjelaskan bahwa Herbert Blumer dan Elihu Katz adalah orang pertama yang memperkenalkan teori ini. Teori Uses and Gratifications (Kegunaan dan Kepuasan) ini dikenal pada tahun 1974 dalam bukunnya The Uses on Mass Communications: Current Perspective on Gratifivations Research. Teori Uses and Gratifications milik Blumer dan Katz ini mengatakan bahwa pengguna media memainkan peran aktif untuk memilih dan menggunakan media tersebut. Sehingga Nurudin pada teori 21 Volume 02, Nomor 01, Juni 2021 Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) tersebut lebih menekankan pada pengguna media adalah pihak yang aktif dalam proses komunikasi. Pengguna media berusaha untuk mencari sumber media yang paling baik untuk memenuhi kebutuhannya. Sedangkan Teori S-O-R adalah sebagai singkatan dari Stimulus-Organism-Respon, ini semua berasal dari psikologi. Mengutip pendapat Onong Uchajana Effendi (Ilmu Teori dan Filsafat Komunikasi, 2003: 255) yang menjelaskan mengenai teori SOR bahwa teori ini mendasarkan asumsi penyebab terjadinya perubahan perilaku tergantung kepada kualitas rangsangan (stimulus) yang berkomunikasi dengan organisme. Elemen-elemen dari model ini adalah pesan (stimulus), komunikan (organisme), efek (respon). Model S- O-R dapat digambarkan sebagai berikut: Bagan 1.1 Model SOR( Effendy, 2003:255) STIMULUS ORGANISM (PERHATIAN, PENGERTIAN, PENERIMAAN) RESPONS (PERUBAHAN SIKAP) Bagan 1.1 Model SOR( Effendy, 2003:255) Proses diatas mengambarkan perubahan sikap dan bergantung kepada proses yang terjadi pada individu. Menurut Dr. Saifuddin Azwar, M.A. (Sikap Manusia Teori dan Pengukurannya, 1995: 6) menjelaskan pendapat Petty & Caciopo 1986 bahwa secara historis, istilah sikap (attitude) adalah evaluasi umum yang dibuat manusia terhadap dirinya sendiri, orang lain, objek, ataupun isu-isu. Seperti yang telah diketahui sebelumnya bahwa komunikasi adalah penyampaian pesan oleh komunikator kepada komunikan. Jika membahas komunikasi itu sendiri menurut peneliti, maka peneliti menitikberatkan pada pemaknaan pesan yang diterima oleh komunikan. Untuk komunikator baik itu personal sampai ke komunikasi massa ketika pesan tersebut dapat diterima dan dapat dimaknai oleh komunikan maka komunikasi tersebut dapat peneliti katakan termasuk ke dalam kategori komunikasi yang efektif meskipun hanya bersifat satu arah (seperti analisa menggunakan teori jarum hipodermik) karena tidak adanya feedback (umpan balik ke media massa tersebut). Teori Uses and Gratifications dan SOR Jika diaplikasikan dalam menganilisa dan meneliti kedua informan baik itu Maria Magdalena dan Fauziyah maka kedua informan tersebut tidak sebegitu memanfaatkan informasi yang disampaikan oleh media massa seperti iklan hal ini dikarenakan peran gender yaitu kesibukan yang mereka lakukan. Yang dimaksudkan dengan peran gender disini adalah pengambilan tanggung jawab serta posisi dari kepala rumah tangga karna penelirian dari si peneliti ini adalah wanita. Maka lebih fokus pada kegiatan yang dilakukan oleh informan setiap harinya. Dari mulai peran ibu rumah tangga, mahasiswa, dan juga sebagai wanita karir. Karena penelitian ini bukan bersifat generalisasi seperti kuantiatif maka untuk peran gender tidak menjadi pembahasan lebih lanjut. Serta usia juga menjadi alasan kenapa 22 Volume 02, Nomor 01, Juni 2021 p-ISSN 2723-4703 e-ISSN 2797-1619 http://ejurnal.iaipd-nganjuk.ac.id/index.php/j-kis/ p-ISSN 2723-4703 e-ISSN 2797-1619 http://ejurnal.iaipd-nganjuk.ac.id/index.php/j-kis/ penelitian ini memilih dua informan dengan batasan usia 35-54 tahun karena Schieffman dan Leslie (2008: 44) menjelaskan bahwa pada usia tersebut individu ketika menggunakan produk mereka cenderung hanya digunakan untuk menghilangkan atau mengatasi setress. Dan hal itu terbukti benar jika diterapkan kepada kedua informan. Bentuk hiburan yang dipilih oleh Maria magdalena dan juga fauziyah yaitu penggunaan sosial media (sosmed) seperti WhatsApp, Instagram, dll Teori uses and gratifications ini melihat kedua informan sebagai pemilik kehendak bebas. Kedua informan menunjukkan kehendak bebas yang mereka miliki. Jika di kelompokkan dalam Pengelompokan psikografi maka pengelompokan ini bisa dilihat pada status sosial, gaya hidup dan kepribadian kedua informan tersebut. Menurut Drs. Ujam Jaenudin, M.Si. (Psikologi Kepribadian, 2012: 101) menjelaskan bahwa kepribadian adalah kesan yang diberikan seseorang kepada orang lain yang diperoleh dari sesuatu yang dipikirkan, dirasakan, diperbuat yang terungkap melalui perilaku seseorang. Sedangkan pengelompokan yang berkaitan dengan perilaku adalah mengelompokkan konsmen menurut frekuensi pembelian, manfaat produk, status pengguna, tingkat penggunaan, status kesetiaan. Sehingga peneliti dalam menganalisa informan melihat pesan dari media massa dapat berupa selective expossure, attentions, defense ataupun blocking. Akan tetapi karena faktor peran gender tersebut, lantas mereka mimilih tetap menggunakan provider telkomsel karena motif yang mereka miliki berupa kepuasaan koleksi nomer cantik untuk Maria Magdalena dan harga ekonomis serta kualitas signal dari provider Telkomsel untuk Fauziyah. Kedua informan sama-sama melakukan blocking iklan dari semua provider melalui media massa yang berupa televisi karena kesibukan mereka. Untuk kedua informan pada tahap persepsi akan dapat diketahui dengan adanya stimulus (rangsangan) dari luar yang akan mempengaruhi proses dalam menentukan dan menggunakan kelima alat indera mereka, yaitu pengelihatan, pendengaran, penciuman, perasaan dan sentuhan. Teori Uses and Gratifications dan SOR Stimulus tersebut diseleksi, diorganisasi, dan diinterpretasikan oleh diri mereka sendiri dengan cara masing- masing. Proses persepsi ini diawali dengan adanya stimuli yang mengenai panca indera yang disebut sensasi. Stimuli ini beragam bentuknya dan akan selalu memborbardir indera informan. Jika dilihat dari asalnya, stimuli pada konsumen ada yang berasal dari individu (seperti aroma, iklan, dan lain-lain) serta yang berasal dari dalam diri individu, seperti harapan, kebutuhan, dan pengalaman. Para informan sebagai konsumen mengambil keputusan membeli dan menggunakan provider Telkomsel deipada Indosat dan XL tersebut melalui beberapa tahapan, yaitu sebagai berikut: 1) Pengenalan kebutuhan (needs recognition) untuk menggunakan Provider; proses pengambilan keputusan informan untuk membeli dan menggunakan 1) Pengenalan kebutuhan (needs recognition) untuk menggunakan Provider; proses pengambilan keputusan informan untuk membeli dan menggunakan 23 Volume 02, Nomor 01, Juni 2021 Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) produk tertentu, buatan perusahaan tertentu, atau dengan merek dagang tertentu dimulai sejak informan merasakan kebutuhan tertentu. Rasa membutuhkan provider tersebut dapat terangsang menjadi dorongan membeli produk apabila mendapat pengaruh dari dalam atau dari luar informan. 2) 2) Penilaian berbagai macam informasi yang terkumpul (alternative evaluation); informan menggunakan informasi produk yang mereka kumpulkan sebagai bahan pertimbangan dalam memilih. Keputusan pemilihan produk dengan merek tertentu juga mengikuti suatu proses. Sebelum menjatuhkan pilihan, informan menilai keunggulan atribut suatu produk yang datanya telah mereka kumpulkan. Langkah berikutnya dari beberapa merek produk yang masih diminati, informan menentukan atribut yang paling cocok dengan keinginan mereka. 3) Keputusan membeli (purchase decision); apabila tidak ada faktor lain yang mempengaruhi, informan membeli produk dengan merek yang menjanjikan paling banyak atribut, yang sesuai dengan kebutuhan dan keinginan mereka. Akan tetapi, sering pada saat informan akan memutuskan pembelian muncul faktor-faktor yang menghambat keputusan pembelian. 4) Evaluasi setelah pembelian (post purchase evaluation); evaluasi informan pasca pembelian mempunyai arti penting bagi produsen. Seperti dengan adanya SMS Survei, sangat membantu produsen untuk feedback fitur-fitur yang mereka pasarkan kepada informan. Pengalaman informan mengonsumsi produk (positif atau negatif) berpengaruh dalam pengambilan keputusan membeli lagi produk yang sama pada saat mereka membutuhkannya lagi. Kesediaan informan membeli kembali produk merupakan salah satu sarana yang diperlukan perusahaan untuk mempertahankan kegiatan bisnisnya. Teori Uses and Gratifications dan SOR 4) Evaluasi setelah pembelian (post purchase evaluation); evaluasi informan pasca pembelian mempunyai arti penting bagi produsen. Seperti dengan adanya SMS Survei, sangat membantu produsen untuk feedback fitur-fitur yang mereka pasarkan kepada informan. Pengalaman informan mengonsumsi produk (positif atau negatif) berpengaruh dalam pengambilan keputusan membeli lagi produk yang sama pada saat mereka membutuhkannya lagi. Kesediaan informan membeli kembali produk merupakan salah satu sarana yang diperlukan perusahaan untuk mempertahankan kegiatan bisnisnya. Bagan 1.2 Kerangka Konseptual Pertimbangan Konsumen Memilih Provider Pengetahuan Produk Persepsi Konsumen Keputusan pembeli Konsumen Bagan 1.2 Kerangka Konseptual Pertimbangan Konsumen Memilih Provider Menurut Vinna Sri Yuniarti, S.E., M.M. (Perilaku Konsumen Teori dan Praktek, 2015: 30) menjelaskan bahwa pemenuhan kebutuhan memang penting 24 Volume 02, Nomor 01, Juni 2021 p-ISSN 2723-4703 e-ISSN 2797-1619 http://ejurnal.iaipd-nganjuk.ac.id/index.php/j-kis/ p-ISSN 2723-4703 e-ISSN 2797-1619 http://ejurnal.iaipd-nganjuk.ac.id/index.php/j-kis/ untuk mengantarkan individu pada kehidupan yang selaras dengan lingkungannya. Pada umumnya, setiap orang akan melakukan kegiatan konsumsi dan menyenangi terhadap hal-hal yang bersifat konsumtif, seperti kegemaran berbelanja. Vinna juga mengutip pendapat Chumidatus Sa’diyah (2007) menjelaskan dalam ilmu ekonomi konsumsi ini merupakan kegiatan manusia yang mengurangi atau menghabiskan guna barang atau jasa yang ditunjukkan langsung untuk memenuhi kebutuhan hidupnya. Dan untuk Maria Magdalena dapat peneliti aplikasikan mengenai perilaku konsumtif yang gemar mengoleksi nomor cantik. Vinna (2015: 30-31) menjelaskan jika perilaku individu bersifat konsumtif maka tindakan membeli barang yang ia lakukan kurang atau tidak diperhitungkan sehingga sifatnya menjadi berlebihan. Yang dimaksudkan oleh penulis mengenai pola perilaku konsumtif adalah pola pembelian dan pemenuhan kebutuhan yang lebih mementingkan faktor keinginan daripada kebutuhan dan cenderung dikuasai hasrat keduniawian dan keinginan semata. Gejala hasrat ini berhubungan dengan gerak dan perbuatan yang berpusat pada kejasmanian. (Drs. Abu Ahmadi dan Drs. M. Umar M.A., Psikologi Umum edisi revisi, 1982: 71) Untuk motif pembelian provider berkaitan dengan waktu dan uang yang dihabiskan selama melakukan kegiatan tersebut. Motif belanja yang dilakukan oleh Maria Magdalena dan Fauziyah mempengaruhi pembelian aktual. Jika membahas mengenai pembelian aktual maka hal ini berkaitan dengan loyalitas mereka terkait dengan provider yang mereka gunakan. Misalnya untuk nomer simpati yang merupakan salah satu produk dari Telkomsel. Kartu ini ada masa aktif dan masa tenggang begitupula dengan provider yang lain. Masa aktif yang dimaksudkan disini adalah ketika Maria Magdalena dan Fauziyah masih dapat melakukan panggilan keluar ataupun panggilan masuk (telpon). Selain itu mereka juga dapat melakukan pengiriman dan penerimaan SMS, serta aktivasi paket Internet. Akan tetapi ketika informan memasuki masa tenggang, maka panggilan keluar dan mengirim SMS tidak dapat mereka lakukan. Volume 02, Nomor 01, Juni 2021 Teori Uses and Gratifications dan SOR Mereka harus melakukan pembelian atau pengisian pulsa terlebih dahulu untuk menambah masa aktifnya baru untuk Telpon, SMS dan mengaktifkan paket Internet bisa mereka lakukan. Infroman hanya dapat menerima panggilan masuk saja bukan panggilan keluar jika memasuki masa tenggang. Dan jika informan sudah melewati masa tenggang maka kartu provider tersebut akan hangus dan tidak bisa dipergunakan kembali. Membahas mengenai loyalitas pelanggan dapat kita telaah kembali dari pernyataan yang informan sampaikan bahwa Maria Magdalena sudah menggunakan provider ±10 tahun dan Fauziyah ±5 tahun. Informan melakukan pembelian produk Telkomsel secara berulang, yaitu melakukan isi ulang pulsa yang bukan hanya digunakan untuk menambah masa aktif kartu mereka saja, akan tetapi juga mereka gunakan untuk pembelian paket Telpon, SMS dan pembelian paket Internet. 25 Volume 02, Nomor 01, Juni 2021 Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) Keputusan informan membeli provider yang mereka gunakan saat ini adalah karena dari segi harga dan kualitas masing-masing provider. Informan akan memilih harga yang ekonomis dan memilih hal yang praktis. Ekonomis dan praktis dapat dilihat dan didengar dari pernyataan Maria Magdalena yang tidak peduli dengan adanya kuota malam. Kuota yang dipilih adalah kuota yang bisa dipakai 24 jam dan kuota yang harganya lebih murah. Sedangkan untuk Fauziyah lebih kepada kepastian kuota yang didapat dan kualitas signal yang bisa dipergunakan di lokasi dimana ia berada yaitu daerah Lumajang. Menurut Onong Uchajana Effendi (Ilmu Teori dan Filsafa komunikasi, 2003), Jika dianalisa menggunakan stimulus respon (SOR) ini, maka efek yang ditimbulkan adalah reaksi khusus terhadap stimulus, sehingga informan dapat mengaharapkan dan memperkirakan kesesuaian antara pesan dan reaksi apa yang harus mereka lakukan yaitu berupa tanggapan positif dengan tetap loyal pada produk Telkomsel dan tanggapan negatif yaitu dengan menggunakan produk selain dari provider Telkomsel. Jadi unsur-unsur dari model ini adalah: Pesan (stimulus,S) bisa berupa iklan provider baik itu melalui media massa, cetak, dan sebagainnya lalu diterima oleh komunikan (Organism, O) atau informan baik itu Maria Magdalena dan Fauziyah. Dimana pada tahapan ini, informan akan melakukan perhatian, pengertian, penerimaan pesan tersebut, lalu timbulah efek (respon, R) seperti perubahan sikap membeli ataupun tidak membeli provider yang diiklankan. Sikap yang dimaksudkan oleh Effendi mengandung aspek evaluatif artinya mengandung nilai menyenangkan atau tidak menyenangkan ketika menggunakan suatu produk, dan yang dimaksudkan peneliti disini adalah provider Telkomsel, Indosat dan juga XL. SIMPULAN DAN SARAN Dari studi kasus pertimbangan konsumen memilih provider Telkomsel daripada Indosat dan XL, peneliti dapat menyimpulkan bahwa Maria Magdalena dan Fauziyah, kedua informan tersebut tidak sebegitu memanfaatkan informasi yang disampaikan oleh media massa karena peran gender yaitu kesibukan yang mereka lakukan. Dari mulai peran ibu rumah tangga, mahasiswa, dan sebagai wanita karir. Teori uses and gratifications ini melihat kedua informan sebagai pemilik kehendak bebas. Mereka dapat menentukan kehendak bebas yang mereka miliki maka mereka dapat menentukan sendiri apakah pesan dari media massa berupa selective expossure, attentions, defense ataupun pesan media yang mereka blocking. Akan tetapi karena faktor peran gender tersebut, lantas mereka mimilih tetap menggunakan provider Telkomsel karena motif yang mereka miliki berupa kepuasaan koleksi nomer cantik untuk Maria Magdalena dan harga ekonomis serta kualitas signal dari provider Telkomsel untuk Fauziyah. Kedua informan sama- sama melakukan blocking iklan dari media televisi. 26 Volume 02, Nomor 01, Juni 2021 Jika dianalisa menggunakan Stimulus Organism Respon (SOR) ini, apapun motif yang dimiliki oleh Maria Magdalena dan Fauziyah, kedua informan bukan lebih banyak mendapatkan stimulus dari media massa. Seperti yang penulis sampaikan sebelumnya bahwa kenyataanya para informan lebih banyak mendapatkan stimulus dari orang terdekat yaitu suami, teman dan counter (lokasi terdekat dimana para informan tinggal) yang merekomendasikan provider Telkomsel, Indosat dan XL kepada mereka. Jadi, saran yang bisa peneliti sampaikan adalah karena konsumen sangat aktif mengenai kemajuan teknologi dan komunikasi. Apalagi televisi bukan satu- satunya sarana untuk para pemasar provider. Maka untuk para pemasar harus lebih aktif mencari tahu kebutuhan konsumen agar produk yang mereka tawarkan dapat terus dipergunakan dan dipilih oleh konsumen (loyal). Promo memang memiliki andil dalam mempengaruhi konsumen dalam pembelian akan teatpi dengan harga dan kuota yang lebih setabil serta didukung dengan jaringan yang kuat (signal) maka konsumen akan lebih loyal kepada provider yang mereka pergunakan. Agar iklan-iklan dari provider tersebut menarik perhatian pengguna, maka harus didapatkan karakter yang kuat dari provider sebagai pembeda produk mereka dengan produk yang lain. Perhatian pemasar ke konsumen juga dapat meningkatkan kepercayaan konsumen. Sehingga dapat disimpulkan bahwa untuk jumlah kuota, harga dan jumlah BTS (signal) juga menjadi bahan pertimbangan bagi informan dalam memilih provider Telkomsel, Indosat dan XL. Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) DAFTAR PUSTAKA Azwar, Saifuddin. 1995. Sikap Manusia Teori Dan Pengukurannya. Yogyakarta: Pustaka Belajar. Dewi, Irra Chisyanti. 2015. Pengantar Psikologi Media. Jakarta: Prestasi Pustaka Publisher. Hall, Calvin S. 2000. Libido Kekuasaan Sigmund Freud. Yogyakarta: Tarawang Press. Jaenudin, Ujam. 2012. Psikologi Kepribadiani. Bandung: CV Pustaka Setia. Joseph, Thomas. 2011. Apps The Spirit of Digital Marketing 3.0. Jakarta: PT Gramedia. Kanuk, Leslie Lazar dan Leon Schiffman. 2008. Perilaku Konsumen Edisi Ketujuh. Indonesia: PT Macanan Cahaya Cemerlang. Kasali, Rhenald. 2011. Cracking Zone Bagaimana Memetakan Perubahan Di Abad Ke 21 & Keluar Dari Perangkap Comfort Zone. Jakarta: PT Gramedia Pustaka Utama. Moleong, Lexy J. 2002. Metodologi Penelitian Kualitatif. Bandung: Remaja Rosdakarya. 27 Volume 02, Nomor 01, Juni 2021 Pertimbangan Konsumen Memilih Provider Telkomsel Daripada Indosat, XL (Penerapan Teori Uses And Gratifications Magister Unitomo) Mulyana, Deddy. 2003. Komunikasi Suatu Pengantar. Bandung: PT Remaja Rosdakarya. Mulyana, Deddy. 2003. Komunikasi Suatu Pengantar. Bandung: PT Remaja Rosdakarya. _____________. 2007. Komunikasi Suatu Pengantar. Bandung: PT Remaja Rosdakarya. Narbuko, Drs. Cholid dan Drs. H. Abu Achmadi. 2009. Metodologi Penelitian. Jakarta: Bumi Aksara. Nurudin. 2010. Sistem Komunikasi Indonesia. Jakarta: RajaGrafindo Perkasa. _______. 2007. Pengantar Komunikasi Massa. Jakarta: RajaGrafindo Perkasa. Rakhmat, Jalaluddin. Psikologi Komunikasi Edisi Revisi. Sambas, Syukriadi. 2015. Sosiologi Komunikasi. Bandung: CV Pustaka Setia. Sami’an, dkk. 2004. Insan Media Psikologi. Surabaya: Fakultas Psikologi Universitas Airlangga. Sugiyono. 2014. Metodologi Penelitian Kuantitatif Kualitatif dan R&D. Bandung: Alfabeta. Suprapto, Tommy. 2011. Pengantar Ilmu Komunikasi. Yogyakarta: Caps Umar, M. Dan Abu Ahmadi. 1982. Psikologi Umum Edisi Revisi. Surabaya: PT Bina Ilmu. Yuniarti, Vinna Sri. 2015. Perilaku Konsumen Teori dan Praktek. Bandung: Pustaka Setia. _____________. 2007. Komunikasi Suatu Pengantar. Bandung: PT Remaja Rosdakarya. Narbuko, Drs. Cholid dan Drs. H. Abu Achmadi. 2009. Metodologi Penelitian. Jakarta: Bumi Aksara. Nurudin. 2010. Sistem Komunikasi Indonesia. Jakarta: RajaGrafindo Perkasa. _______. 2007. Pengantar Komunikasi Massa. Jakarta: RajaGrafindo Perkasa. Rakhmat, Jalaluddin. Psikologi Komunikasi Edisi Revisi. S b S k i di 2015 S i l i K ik i B d CV P t k S ti Rakhmat, Jalaluddin. Psikologi Komunikasi Edisi Revisi. Sambas, Syukriadi. 2015. Sosiologi Komunikasi. Bandung: CV Pustaka Setia. Rakhmat, Jalaluddin. Psikologi Komunikasi Edisi Revisi. Sambas, Syukriadi. 2015. Sosiologi Komunikasi. Bandung: CV Pustaka Setia. Sami’an, dkk. 2004. Insan Media Psikologi. Surabaya: Fakultas Psikologi Universitas Airlangga. Sugiyono. 2014. Metodologi Penelitian Kuantitatif Kualitatif dan R&D. Bandung: Alfabeta , g Sambas, Syukriadi. 2015. Sosiologi Komunikasi. Bandung: CV Pustaka Setia. Sami’an, dkk. 2004. Insan Media Psikologi. Surabaya: Fakultas Psikologi Universitas Airlangga. Sugiyono. 2014. DAFTAR PUSTAKA Metodologi Penelitian Kuantitatif Kualitatif dan R&D. Bandung: Sami’an, dkk. 2004. Insan Media Psikologi. Surabaya: Fakultas Psikologi Universitas Airlangga. Sugiyono. 2014. Metodologi Penelitian Kuantitatif Kualitatif dan R&D. Bandung: Alfabeta. Suprapto, Tommy. 2011. Pengantar Ilmu Komunikasi. Yogyakarta: Caps Suprapto, Tommy. 2011. Pengantar Ilmu Komunikasi. Yogyakarta: Caps Umar, M. Dan Abu Ahmadi. 1982. Psikologi Umum Edisi Revisi. Surabaya: PT Bina Ilmu. Umar, M. Dan Abu Ahmadi. 1982. Psikologi Umum Edisi Revisi. Surabaya: PT Bina Ilmu. Yuniarti, Vinna Sri. 2015. Perilaku Konsumen Teori dan Praktek. Bandung: Pustaka Setia. Yuniarti, Vinna Sri. 2015. Perilaku Konsumen Teori dan Praktek. Bandung: Pustaka Setia. 28 Volume 02, Nomor 01, Juni 2021
https://openalex.org/W2990208928	http://old.scielo.br/pdf/rbca/v21n3/1516-635X-rbca-21-03-eRBCA-2018-0941.pdf	English	null	Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers	Brazilian Journal of Poultry Science	2,019	cc-by	8,335	Author(s) The objective of this study was to compare characteristics and properties of breast meat from spent Lohmann Brown layers (SP, 90 weeks old, n = 24) and those of commercial broilers (BR, 6 weeks old, n = 24). The breasts of both SP and BR were collected from a local processing plant, vacuum-packed in a plastic bag, and stored at -18ºC until further analyses. The SP showed a greater water-holding capacity, tougher and chewier texture (p<0.05). Both raw and cooked SP breasts comprised the greater total collagen but lower soluble collagen than those of BR (p<0.05). Muscle fibers of the SP, observed under scanning electron microscope, were small, with average fiber diameter of 37.85±1.40 μm, densely packed and surrounded by complex networks of connective tissue. The lower myofibril fragmentation index and alkaline-soluble protein fractions of the SP (p<0.05) suggested lesser degree of postmortem fragmentation and protein denaturation in SP compared to BR. Based on differential scanning calorimetry, multiple endothermic transitions were observed in both raw BR and SP breast samples. While BR thermograms comprise five transitions at 57.7ºC, 64.2ºC, 67.6ºC, 72.3ºC and 77.6ºC with total ΔH of 15.31 J/g dry meat, the SP samples exhibited four transitions at 55.1ºC, 62.1ºC, 70.5ºC and 77.7ºC and total ΔH of 17.62 J/g dry meat. Overall, the findings indicated that cooked meat toughness of SP was attributed by the high total and heat-stable collagen content, densely packing of small muscle fibers, and the superior myofibril integrity. Mail Address Corresponding author e-mail address Yuwares Malila 113 Phahonyothin Rd., Khlong Neung, Khlong Luang, Pathum Thani, 12120, Thailand. Phone: +662.117.8031 Email: yuwares.mal@biotec.or.th Yuwares Malila 113 Phahonyothin Rd., Khlong Neung, Khlong Luang, Pathum Thani, 12120, Thailand. Phone: +662.117.8031 Email: yuwares.mal@biotec.or.th Original Article g Author(s) Limpisophon KI https://orcid.org/0000-0001-5435-4902 E-tun SI https://orcid.org/0000-0002-2664-0968 Koeipudsa CI https://orcid.org/0000-0002-8479-1086 Charoensuk DII https://orcid.org/0000-0002-4884-4160 Malila YII https://orcid.org/0000-0001-5950-5319 I Department of Food Science and Technology, Faculty of Agro-Industry, Kasetsart University, 50 Ngamwongwan Rd., Chatuchak, Bangkok, 10900, Thailand. II National Center for Genetic Engineering and Biotechnology (BIOTEC), 113 Thailand Science Park, Phahonyothin Rd., Khlong Nueng, Khlong Luang, Pathum Thani, 12120, Thailand. INTRODUCTION The spent laying hens are the massive by-products of the poultry industry. Although the meat is inexpensive and nutritious (Suriani et al., 2014; Lakshani et al., 2016), it has been underutilized for human consumption due mainly to its undesirable tough texture. As the hens are spent at considerably long age (approximately 90 weeks), their meat comprises heat-stable cross-linked connective tissues which required an extreme cooking condition to be degraded (Fletcher, 2002). In addition to the prolonged slaughter age, commercial layers have been selectively bred with an emphasis only on egg quality and production efficiency. The hens are relatively small in size in order to minimize energy requirement and feed consumption. Those two factors, age and genetics, certainly manifest muscle composition and arrangement within the spent hen meat, which in turn affect eating quality of its meat (Tang et al. 2009; Chen et al., 2016). Keywords Muscle fiber, physicochemical properties, protein fractionation, technological properties, thermal properties. Submitted: 14/January/2018 Approved: 26/March/2019 Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers II National Center for Genetic Engineering and Biotechnology (BIOTEC), 113 Thailand Science Park, Phahonyothin Rd., Khlong Nueng, Khlong Luang, Pathum Thani, 12120, Thailand. Corresponding author e-mail address Yuwares Malila 113 Phahonyothin Rd., Khlong Neung, Khlong Luang, Pathum Thani, 12120, Thailand. Phone: +662.117.8031 Email: yuwares.mal@biotec.or.th Brazilian Journal of Poultry Science Revista Brasileira de Ciência Avícola Keywords Muscle fiber, physicochemical properties, protein fractionation, technological properties, thermal properties. Muscle fiber, physicochemical properties, protein fractionation, technological properties, thermal properties. Previous studies demonstrated plausible applications of the meat as raw materials for canned products (Chuaynukool et al., 2007) or for comminuted products (Jin et al., 2007; Sorapukdee et al., 2016). Still, the use of the whole muscle, i.e. whole breast or drumstick, has been of interest for poultry industry. Development of tenderization approach of 1 eRBCA-2018-0941 Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Limpisophon K, E-tun S, Koeipudsa C, Charoensuk D, Malila Y broilers (BR) and spent commercial laying hens (SP), respectively, were used in this study. All samples were purchased from the commercial processing plant without either experimental treatments or scientific procedures directly subjected to the living animals. In this regards, according to BIOTEC Institutional Animal Care and Use Committee, the ethical approval was not required. which the meat is still in the intact form, however, has been a great challenge. Several attempts have been addressed in order to improve tenderness of spent layer meat mostly using enzymes (DeVitre & Cunningham, 1985; Kang et al., 2012) or using marinade treatments with salt and phosphate solutions (Chueachuaychoo et al., 2011). Alteration of collagen thermal stability, with an attempt to tenderize spent hen meat, was also demonstrated in the study of Sams (1990) in which layers (72 weeks of age) were fed with diets containing 0.18% β-aminopropionitrile (BAPN), a nucleophilic compound inhibiting formation of collagen cross linking, up to 64 days prior to slaughter. Although increased collagen solubility was found in the BAPN- treated samples, the shear force values of the treated samples did not differ from those of the control. Advanced technology, such as high-pressure process, has offered alternative method for meat tenderization. Nonetheless, an effective feasible technique for the industry has not been successfully developed. All chickens were raised and processed due to the routine standard practice of a local industrial abattoir (Saraburi, Thailand).The detail of the processing includes the fasting for 12 h followed by the manual neck cutting, 3-min bleeding, scalding at 70ºC for 2min, plucking in a rotary drum for 30 s, and advanced to an evisceration. Myofibril fragmentation index The value of MFI was determined as described by Hopkins et al. (2000). In brief, 0.5 g of chopped raw meat sample was homogenized, on ice, with 30 ml of ice-cold MFI buffer (25 mM potassium phosphate buffer, pH 7.0 containing 0.1 M KCl, 1 mM EDTA and 1 mM sodium azide) at 13,500 rpm for 2 min (30 sec on followed by 30 sec rest, 2 cycles). The homogenate was filtered through two layers of gauzes and rinsed with 10 ml cold MFI buffer. The filtrate Moisture content and pH Moisture of raw and cooked samples were evaluated according to AOAC (2000). The pH of raw meat was measured by directly inserting a spear-shape electrode coupled to a pH meter (model Seven Easy, Mettler- Toledo, Switzerland) into the meat. Keywords The eviscerated carcass was chilled using water immersion method at approximately 0.6ºC for 75 min, and subsequently cut and deboned. Visible skin, extra fat and connective tissue were trimmed from the breast samples. At the end of the processing line, the sample was randomly collected, individually vacuum- packed in a plastic bag and stored at -18ºC for 6h. The frozen meat was stored on ice while transported back to Food Biotechnology Laboratory, BIOTEC (Pathum Thani, Thailand). Upon arrival, the samples were stored at -20ºC until further analyses. Prior to any experiment, the meat was thawed overnight at 4ºC. Lohmann Browns are one of the commercial layers that provide large brown-shell eggs. Originally developed in Germany, the birds have been widely used in the egg industry as the birds begin to lay eggs at 14 weeks of age which is earlier than other layers and provide high egg productivity. Similar to other breeds, at the end of the laying cycles, the most spent Lohmann Brown hens are used as low-priced animal feed. The idea of producing whole-muscle processed food productions from the spent Lohmann hens are also of interest, yet a challenge as some characteristics of the spent Lohmann hens muscle fiber that has not been revealed. Characterization of the spent Lohmann breast meat in accompanied with those consumer-accepted meat of broilers might offer additional comprehension which could lay foundation in improvement of meat tenderness of both spent Lohmann and the others. The objective of this study was to investigate technological quality, physicochemical and thermal properties as well as muscle fiber of breast meat between spent commercial Lohmann Brown layers (90 weeks of age) in comparison to the meat collected from commercial Ross 308 broilers (6 weeks of age), one of the most raised and consumed broilers. Of twenty-four, five breasts were subjected for determination of moisture, pH, myofibril fragmentation index (MFI), collagen, and protein fractionation. Ten pieces of the breast meat were for water-holding capacity (WHC) and texture analyses. The other five were for evaluation of microscopic images, leaving the other four for thermal properties. MATERIALS AND METHODS Samples and sample collection Water-holding capacity (WHC) Herein, drip loss, cooking loss and expressible water were used as indicators of WHC and determined consecutively in each breast sample as previously addressed (U-chupaj et al., 2017). Briefly, each breast meat was weighed and subsequently packed in a plastic bag and hung at 4ºC for 24 h. Drip loss was calculated as a percentage of weight loss relative to initial weight of the meat after it was hung at 4ºC for 24 h. Afterwards, the sample was individually re- packed in a plastic bag and cooked at 95ºC by water immersion until internal temperature of the thickest part of the sample, monitored using a thermocouple, reached 85ºC (U-chupaj et al., 2017). After cooling in ice-cold water until the core temperature reached 10ºC, the meat was rested for 2 h at 4ºC, then removed from the bag, blotted dry and reweighed. Cooking loss was expressed as a percentage of weight loss after cooking. Each cooked breast was cut parallel to muscle fiber alignment into two cubes (1 cm × 1 cm × 1 cm) and one rectangular cuboid (10 mm × 15 mm × 10 mm). While one of the cubes and the cuboid were used in the texture analysis (described in the following section), the other prepared cube was weighed, placed between two sheets of Whatman filter paper and subjected to a compression at 70% strain under a force of 50 g for 60 seconds using a TA-XT2i texture analyzer (Stable Micro Systems, Godalming, UK) equipped with a 50-mm aluminum cylinder probe. Apparent expressible water and expressible water of each sample were calculated as follows. Texture analysis Texture of the cooked samples was evaluated following Warner-Bratzler shear test and texture profile analysis (TPA) using a TA-XT2i texture analyzer (U-chupaj et al., 2017). The samples, subjected to the WBS and TPA, were the cooked breast samples prepared into the rectangular cuboids and the cubes, respectively, as mentioned above. All textural parameters were automatically calculated by Texture Expert version 1.0 software (Stable Micro Systems). The operational condition for WBS test was set as follows; crosshead speed 1 mm/s, working distance 25 to 30 mm, and trigger force 0.2 N.As for TPA, the operating parameters consisted of a double compression cycle with test speed 1 mm/sec, holding time 1 sec, working distance 30% strain, surface sensing force 99 g, threshold 30 g and time interval between the first and the second stroke 1 sec. Samples and sample collection Twenty-four breasts of commercial Ross 308 broilers (6 weeks of age) and twenty-four breasts of Lohmann Brown layers (90 weeks of age), representing commercial 2 eRBCA-2018-0941 Limpisophon K, E-tun S, Koeipudsa C, Charoensuk D, Malila Y Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers was subsequently centrifuged at 1,000×g for 10 min at 2ºC. The resulting pellets of myofibrils were re- suspended in 10 ml of cold MFI buffer. The extraction was repeated twice and the pellet was finally re- suspended in 10 ml of cold MFI buffer. The protein concentration of the suspensions was determined using the Pierce Bicinchoninic acid (BCA) Protein Assay kit (Thermo Scientific, Rockford, Illinois, USA) following manufacturer’s recommendation. Absorbance of the diluted myofibril suspensions, diluted in MFI buffer to a final protein concentration of 0.5 mg/ml with a total volume of 2 ml, was determined at 540 nm using MFI buffer as blank. MFI was calculated by multiplying the average absorbance with 200. Total collagen content and soluble collagen Total collagen content and soluble collagen was determined after acid hydrolysis as described by Kittiphattanabawon et al (2010) with a modification. Briefly, for total collagen, 0.5 g of chopped raw and cooked samples was hydrolyzed with 5 ml of 6 N HCl at 110ºC for 24 h. The neutralized hydrolysate (pH 7.0 ± 0.05) was filtered and diluted with distilled water to a final volume of 50 ml. Ten microliters of the hydrolysate or hydroxyproline standard was reacted with 10 μl of oxidizing reagent (one volume of 7% w/v of chloramin T in aqueous solution and four volumes of 1 M acetate/citrate buffer, pH 6.0), 20 μl of isopropanol and 139 μl of Ehrlich’s reagent. After incubation at 60ºC for 25 min, absorbance at 558 nm of the mixture was measured. Concentration of hydroxyproline was converted to collagen content using the factor of 7.25. For soluble collagen, 7 g of either raw or cooked meat was homogenized with 28 ml of 25% Ringer’s solution. The homogenate was then heated at 77ºC for 70 min and centrifuged for 30 min at 1600×g, 4ºC. The resulting supernatant was collected and hydrolyzed with 10 volumes of 6 N HCl at 110ºC for 24 h. Soluble collagen content was then determined as stated in the protocol for total collagen determination. All measurements were done in triplicates. The amount of total collagen and soluble collagen were expressed as milligrams of collagen per gram of dry meat. Collagen solubility was calculated as follow. al weight (g) t (g) ter (%) ple (%) Initial weight (g) - Final weight (g) Statistical analysis Statistical analysis was conducted using R version 3.2.1 (Mangiafico, 2015). Independent t-tests were carried out to compare the means between SP and BR samples. The additional independent t-tests were also performed to evaluate the effects of cooking on collagen contents and collagen solubility within the group of SP and BR samples. The significant level for all analyses was set at α=0.05. Initial weight (g) - Final weight (g) Initial weight (g) Apparent expressible water (%) 3 eRBCA-2018-0941 Limpisophon K, E-tun S, Koeipudsa C, Charoensuk D, Malila Y Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Limpisophon K, E-tun S, Koeipudsa C, Charoensuk D, Malila Y Limpisophon K, E-tun S, Koeipudsa C, Charoensuk D, Malila Y Collagen solubility (%) = Soluble collagen mg g dry meat x 100 Total collagen g dry meat mg Collagen solubility (%) = Protein fractionation Protein components of BR and SP breast meat were fractionated (Visessanguan et al., 2004). All steps were conducted at 4ºC. Three grams of choppedraw meat samples were homogenized with ten volumes of phosphate buffer (pH 7.5), containing 15.6 mM Na2HPO4 and 3.5 mM KH2PO4, at 9,500 rpm for 1 min. After centrifugation at 5,000×g for 15 min, the pellet was discarded. The supernatant was mixed with cold 50% trichloroacetic acid to a final concentration of 10% and re-centrifuged at 5000×g for 15 min. The resulting pellet from the second centrifugation was collected as a water-soluble fraction while the supernatant was labeled as a non-protein nitrogen (NPN). The pellet was then extracted with ten volumes of phosphate buffer (pH 7.5), containing 0.45 M KCl at 9,500 rpm for 1 min and centrifuged at 5000×g for 15 min. The supernatant was classified as a salt- soluble fraction. The obtained pellet was continuously stirred with ten volumes of 0.1 M NaOH for 4 h, and subjected to centrifugation at 5000×g for 15 min. The supernatant and the residue were alkali-soluble and alkali-insoluble fractions, respectively. The nitrogen content of all fractions was determined using the Kjeldahl method (AOAC, 2000). Microstructure Thermal properties of the raw chicken breast meat were evaluated using a differential scanning calorimeter (DSC) model 822E (Mettler-Toledo GmbH, Switzerland) according to the method of Visessanguan et al. (2000). In brief, approximately 12 mg of chopped raw breast samples were hermetically sealed in a 40-µl aluminum DSC pan. Thermal transitions of the samples were monitored during heating the samples from 25ºC to 105ºC at a scanning rate of 5ºC/min. An empty DSC pan was used as a reference. Onset temperature (Tonset), peak temperature (Tpeak), final temperature (Tfinal) and enthalpy (ΔH) were analyzed using the STARe Thermal Analysis software 14.00. The value of ΔT, the difference between Tfinal and Tonset, for each transition was subsequently calculated. The measurements were carried out on four replicates and reported as the average. Microstructure of raw chicken breast (n = 5) was observed under a scanning electron microscopy (SEM). The sample (1 cm x 1 cm x 0.5 cm) was fixed in 2.5% glutaraldehyde in 0.1 M phosphate buffer and dehydrated in ethanol solution with a serial concentration of 25%, 50%, 75%, 95% and 100%. Microscopic views of the dried specimen, sputter- coated with gold, were observed at 70x and 1,000x magnification under a field-emission SEM (model SU5000, Hitachi, Hitachi Europe Ltd., Germany) using an acceleration voltage of 10 kV. The microscopic images were processed using ImageJ software. The fiber density was estimated by counting total fiber number (TFN) in nine 70x fields per specimen (modified from Alves et al., 2012). The average fiber diameter was calculated from the mean cross-sectional area of the fiber, which was obtained by dividing total cross- sectional fiber area with TFN within each field. RESULTS Physicochemical properties and technological qualities of BR and SP breast meat samples are shown in Table 1. The SP samples exhibited lower moisture in raw meat but greater moisture in cooked samples compared to those of BR (p<0.05). The values of pH and MFI of SP breasts were also lower than those of BR. Drip loss, cooking loss and expressible water of the SP were lower than those of the BR (p<0.05), indicating superior WHC of the SP samples over the BR ones. Despite no differences in hardness and springiness, the greater values of shear force, shear energy, cohesiveness and chewiness of the SP were detected (p<0.05). The current WBS and TPA data supported the tougher and chewier textural characteristics of the cooked SP breast meat in comparison to those of the BR. 4 eRBCA-2018-0941 Limpisophon K, E-tun S, Koeipudsa C, Charoensuk D, Malila Y Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Table 1 – Technological quality of breast meat collected from commercial broilers (BR) and spent Lohmann Brown layers (SP)1 Properties BR SP Significant difference2 Moisture content (%) Raw meat 75.36±0.49 74.45±0.30 * Cooked meat 64.42±0.10 68.58±0.30 * pH 6.01±0.13 5.85±0.03 * Myofibril fragmentation index (MFI) 19.89±1.74 5.71±3.36 * Water-holding capacity Drip loss (%) 2.81±0.35 1.99±0.19 * Cooking loss (%) 7.70±1.49 3.75±0.31 * Expressible water (%) 24.33±0.63 22.57±0.78 * Textural characteristics of cooked meat Shear force (N) 39.64±7.49 65.47±7.77 * Shear energy (N.s) 307.18±46.61 519.85±52.93 * Hardness (N) 23.35±0.91 26.43±6.41 NS Springiness 0.63±0.05 0.65±0.02 NS Cohesiveness 0.34±0.01 0.46±0.01 * Chewiness (N) 5.07±0.45 7.91±2.26 * 1Data are presented as mean ± standard deviation, where n = 5 for physicochemical property determination and n = 10 for analyses of water-holding capacity and texture. 2p<0.05, NS = not significant (p≥0.05) Limpisophon K, E-tun S, Koeipudsa C, Charoensuk D, Malila Y cooked SP and BR samples could be solubilized to the greater extent (p<0.05), indicating the breakdown of collagen networks in both samples during cooking. Still, solubility of the collagen in the SP was lower than that of the BR (p<0.05). Considering collagen content in the breast samples (Table 2), the SP samples composed of a significantly greater total collagen. Additionally, collagen networks of the SP increased in thermal stability as reflected by the lower soluble collagen content and collagen solubility (p<0.05). RESULTS 5 eRBCA-2018-0941 Limpisophon K, E-tun S, Koeipudsa C, Charoensuk D, Malila Y Limpisophon K, E-tun S, Koeipudsa C, Charoensuk D, Malila Y Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Lohmann Brown Layers in Comparison to Commercial Ross Broilers Figure 3 – Thermograms of breast meat collected from commercial broilers (BR, n=4) and spent Lohmann Brown hens (SP, n=4). The arrows and numbers indicate the endo- thermic transitions observed in each sample. (Visessanugan et al., 2004), was the main fraction of both samples. The particular fraction was more pronounced in BR compared to that of SP (p<0.05). Besides, the NPN fraction highly varied among the BR samples. The results suggested that the meat proteins in the BR has been undergone denaturation and degradation to the greater extent. Figure 2 – Protein fractionation in breast samples (n=5) of commercial broilers (BR) and spent Lohmann Brown layers (SP). Bars and error bars illustrate mean and standard deviation, respectively. NPN = non-protein nitrogen. Asterisk indicates statistical diffe- rence between chicken types (p<0.05). Figure 2 – Protein fractionation in breast samples (n=5) of commercial broilers (BR) and spent Lohmann Brown layers (SP). Bars and error bars illustrate mean and standard deviation, respectively. NPN = non-protein nitrogen. Asterisk indicates statistical diffe- rence between chicken types (p<0.05). Focusing on DSC thermograms (Figure 3), broad endothermal transitions were present in both raw BR or SP breast samples. Thermograms of the BR samples comprise five thermal transitions, occurring at around 57.7ºC, 64.2ºC, 67.6ºC, 72.3ºC and 77.6ºC with total ΔH of 15.31 J/g dry meat (Table 3). For the SP samples, the overall thermal profile shifted towards lower temperature with four apparent transitions at 55.1ºC, 62.1ºC, 70.5ºC and 77.7ºC and total ΔH of 17.62 J/g dry meat. The third transition was more likely merged with the second peak. The declined Tonset and Tpeak of SP in comparison to those of BR were significant in peak 1 and peak 2 (p<0.05). Additionally, in the second transition, although Tonset and Tpeak were significantly lower in the SP, the endothermic event underwent to the greater extent in the SP samples, leading to the significant increased ΔT (p<0.05). RESULTS Once cooked, collagen in both t of breast meat collected from commercial broilers (BR) and spent Lohmann Brown layers (SP)1,2 Table 2 – Collagen content of breast meat collected from commercial broilers (BR) and spent Lohmann Brown layers (SP)1,2 Chicken Total collagen (mg/g dry meat) Soluble collagen (mg/g dry meat) Collagen solubility (%) Raw meat Cooked meat Raw meat Cooked meat Raw meat Cooked meat BR 16.43b±3.02 10.96a±2.02 3.24a±1.15 7.60b±4.55 19.72a±5.98 58.88b±24.54 SP 34.82a±19.13 39.68a±10.96 2.14a±0.71 3.44b±0.93 7.52a±3.38 12.07b±2.74 Significant difference3 ** * * 1Data are presented as mean ± standard deviation, where n = 5. 2Different letters indicate significant difference (p<0.05) of the same collagen type between raw and cooked breast samples within the same row. 3* p<0.05, p<0.001 within the same column. Table 2 – Collagen content of breast meat collected from commercial broilers (BR) and spent Lohm Figure 1 – Transverse sections of breast meat collected from commercial broilers (BR; a, c) or spent Lohmann Brown layers (SP; b, d) observed under scanning electron microscope with magnification of 70x (a, b) or 1000x (c, d). Cross sections of muscle fibers from the SP and BR were observed under SEM (Figure 1). The average fiber diameters of the SP and BR were 37.85±1.40 μm and 42.18±2.35 μm, respectively. Not only were the SP fibers smaller, the SP fibers were more densely packed (304 ± 55 fibers per mm2) than those of the BR (223 ± 68 fibers per mm2) (p<0.05) and apparently surrounded by connective tissue (Figure 1c, d). Proteins of the breast samples were fractionated based on their solubility into five fractions, including NPN, water-soluble, salt- soluble, alkali-soluble and alkali-insoluble fraction (Figure 2). Interestingly, the alkali- soluble fraction, representing collagen and the denatured myofibrillar proteins Figure 1 – Transverse sections of breast meat collected from commercial broilers (BR; a, c) or spent Lohmann Brown layers (SP; b, d) observed under scanning electron microscope with magnification of 70x (a, b) or 1000x (c, d). RESULTS In term of energy required for the thermal transitions, SP samples showed significantly less ΔH in the first transition but greater ΔH values in the second and fifth transitions compared to those of BR (p<0.05). Figure 3 – Thermograms of breast meat collected from commercial broilers (BR, n=4) and spent Lohmann Brown hens (SP, n=4). The arrows and numbers indicate the endo- thermic transitions observed in each sample. of overall meat quality between BR and SP is more likely confounded by those combined with other different extrinsic factors, i.e. feeding regime and rearing management. However, in this study, the used BR samples were initially aimed to be benchmark in determination of the SP muscle fibers. Ultimately, by characterizing the BR alongside, it has become clearer which aspects of the SP fibers that can be modified to improve the tenderness of the cooked SP meat. The tougher and chewier texture of the cooked spent Lohmann Brown breast meat in comparison to those of the commercial Ross 308 were as expected. The current observation was consistent with the previous experiment of Dawson et al. (1991) in which texture of cooked meat of spent Leghorn hens (20 to 24 months of age) and broilers (6 to 7 weeks of age) were compared. Tang et al. (2009) also reported that cooked breast meat of two commercial broiler lines, Avian (7 weeks of age) and Lingnanhuang (8 weeks of age), required lower force to cut through DISCUSSION (1996) investigated the effects of muscle fiber size (diameter below or above 60 μm) on force required to fracture the porcine longissimus muscle and reported the less force to fracture the fibers having diameter larger than 60 μm. Later, Johnston et al., (2000) found significant positive correlations between muscle fiber density and chewiness as well as firmness of cooked meat of Atlantic salmon. On the contrary, the increased meat toughness associated with small muscle fiber diameter was previously investigated in caponized and indigenous chickens. Lin & Hsu (2002) reported a significantly smaller muscle fiber diameter as well as a greater toughness in caponized chicken breast meat compared to that of normal cockerels (p<0.05). In Thai indigenous chicken, the diameter of all muscle fiber types was smaller compared with the imported meat-type breeds (Jaturasitha et al., 2008). An et al. (2010) found a significantly negative correlation between shear force and muscle fiber density when myofibers of White Leghorns (6-week-old, 18-week- old) and broilers (6-week-old) were compared. The discrepancies were suggested to be the impact of muscle membrane combined with different fiber sizes in comparison to 16-week-old Hy-Line Brown layers. Similar observation was documented in the study of An et al. (2010) in which meat quality indices and muscle characteristics of broilers (6 weeks of age) and White Leghorn chickens (6 and 18 weeks of age) were examined. The cooked breast meat of 18-week-old White Leghorn exhibited the greatest shear force and shear energy. Recently, Chen et al. (2016) compared technological properties of the meat collected from 560-day-old (approximately 74 weeks) Hy-Line Brown layers and those of 40-day-old (nearly 6 weeks) Acres broilers and reported a comparable trend. in comparison to 16-week-old Hy-Line Brown layers. Similar observation was documented in the study of An et al. (2010) in which meat quality indices and muscle characteristics of broilers (6 weeks of age) and White Leghorn chickens (6 and 18 weeks of age) were examined. The cooked breast meat of 18-week-old White Leghorn exhibited the greatest shear force and shear energy. Recently, Chen et al. (2016) compared technological properties of the meat collected from 560-day-old (approximately 74 weeks) Hy-Line Brown layers and those of 40-day-old (nearly 6 weeks) Acres broilers and reported a comparable trend. DISCUSSION Many aspects influence overall meat quality. Between broilers and spent layers, differences in breeding purposes and animal age are among those key players. It is worth noting that a direct comparison 6 eRBCA-2018-0941 Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Table 3 – Thermal parameters of breast meat collected from commercial broilers (BR) and spent Lohmann layers (SP)1,2 Table 3 – Thermal parameters of breast meat collected from commercial broilers (BR) and spent Lohmann layers (SP)1,2 Parameter BR SP p-value Significant difference3 Peak 1 Tonset(ºC) 50.11 ± 1.48 42.38 ± 2.93 3.28‘ 10-3 Tpeak(ºC) 57.71 ± 0.28 55.10 ± 0.11 2.41‘ 10-6 * DT (ºC) 14.82 ± 1.74 16.17 ± 2.73 0.44 NS DH (J/g dry sample) 6.62 ± 0.27 1.66 ± 0.29 2.58‘ 10-7 * Peak 2 Tonset(ºC) 62.55 ± 0.30 59.64 ± 0.16 2.63‘ 10-6 * Tpeak(ºC) 64.21 ± 0.35 62.10 ± 0.21 4.56‘ 10-5 * DT (ºC) 3.05 ± 0.22 4.76 ± 0.61 1.92‘ 10-3 ** DH (J/g dry sample) 0.15 ± 0.05 0.45 ± 0.21 0.04 * Peak 3 Tonset(ºC) 66.17 ± 0.51 n.a. n.a. n.a. Tpeak(ºC) 67.63 ± 0.29 n.a. n.a. n.a. DT (ºC) 3.12 ± 0.40 n.a. n.a. n.a. DH (J/g dry sample) 0.06 ± 0.03 n.a. n.a. n.a. Peak 4 Tonset(ºC) 70.57 ± 0.19 68.34 ± 3.02 0.19 NS Tpeak(ºC) 72.31 ± 0.09 70.52 ± 2.46 0.20 NS DT (ºC) 3.35 ± 0.26 3.84 ± 0.74 0.25 NS DH (J/g dry sample) 0.10 ± 0.03 0.07 ± 0.05 0.26 NS Peak 5 Tonset(ºC) 74.61 ± 0.14 74.58 ± 0.08 0.69 NS Tpeak(ºC) 77.62 ± 0.22 77.69 ± 0.08 0.56 NS DT (ºC) 5.06 ± 0.28 5.18 ± 0.14 0.48 NS DH (J/g dry sample) 1.06 ± 0.05 1.46 ± 0.30 0.04 * Overall DT (ºC) 40.51 ± 3.05 48.44 ± 3.07 0.01 NS DH (J/g dry sample) 15.31 ± 1.20 17.62 ± 2.85 0.19 NS 1Data are presented as mean ± standard deviation, where n = 4. 2n.a. = not applicable. 3* p<0.05, p<0.01, * p<0.001, NS = not significant (p≥0.05) 3* p<0.05, p<0.01, * p<0.001, NS = not significant (p≥0.05) Influences of muscle fiber size and density on meat tenderness have been previously discussed. Mutungi et al. DISCUSSION Texture of cooked meat depends mainly upon muscle composition, muscle fiber size and arrangement, as well as postmortem biochemical events in the muscle (Fletcher, 2002; An et al., 2010).Considering muscle fiber of spent Lohmann breast, the current findings were in accordance with numbers of previous studies (Cooke et al., 2003; Koomkrong et al., 2015; Buzala & Janicki, 2016).The smaller fibers in the SP samples occupied less space, resulting in the densely packed fibers in comparison to that in the BR samples. The difference in muscle fiber size and density has obviously been the consequences of breeding selection for divergent purposes of those two chicken lines. 7 eRBCA-2018-0941 Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Limpisophon K, E-tun S, Koeipudsa C, Charoensuk D, Malila Y Lakshani et al. (2016). It is worth noting that the pH of both broilers and spent hen breast samples in the study of Lakshani et al. (2016) were somewhat high. The increasing pH could likely be due to activity of amine/amide producing bacteria as the samples were collected from a local market without the information regarding manufacturing date. (An et al., 2010). Besides of the previous explanation, the inconsistent trend regarding the myofiber size and density on texture of the cooked meat could be due to the influences of divergent composition and maturity of endomysium and perimysium among species and animals (An et al., 2010). Apart from muscle fiber, connective tissue has been considered as the background contributor to meat texture (Purslow, 2005). As animals advance in age, stability of the collagen fibers increased theoretically through covalent cross-links within or between collagen molecules (Smith-Mungo & Kagan, 1998). Highly cross-linked collagen networks exhibited stability to thermal denaturation as well as tensile strength of the collagen networks (Snedeker & Gautieri, 2014); as a result, it reduced tenderness of the meat as currently observed in the SP breast samples collected from spent Lohmann Brown fowls. In addition to the superior collagen thermal stability, total collagen contents of the raw and cooked SP samples were greater than that of the BR. DISCUSSION The findings herein corresponded to the previous studies revealing the tendency of decreased collagen content in poultry meat in accordance with breeding selection for fast-growing meat-type birds (Sirri et al., 2011; Funaro et al., 2014; Chen et al., 2016). As illustrated in the present SEM micrographs, the interspaces between the SP fiber bundles were markedly occupied by thick networks of connective tissues. In the study of An et al. (2010), the markedly thicker perimysium, mainly consisting of collagen, was observed in the breast muscle of 18-week-old White Leghorns compared to those of 6-week-old White Leghorns and broilers. In general, breast muscle of meat-type birds comprises a greater extent of fast-twitch glycolytic fibers when compared to that of layers (Aberle et al., 2001). The glycolytic fibers possess to rapid postmortem metabolic rate (Dransfield & Sosnicki, 1999); thus, the lower ultimate pH in the fast-growing birds can be anticipated. However, in this study, the BR samples exhibited the greater degree of pH than that of SP corresponding to the growing numbers of recent reports pointing out the greater ultimate pH of the fast- growing birds in comparison to that of slow-growing ones (Berri et al., 2007; Vaithiyanathan et al., 2008). This aberrantly high ultimate pH has been consistently observed among modern commercial broilers affected with an emerging defect, known as white striping abnormality (Mazzoni et al., 2015; Alnahhas et al., 2016; Malila et al., 2018). Such abnormal condition has been hypothesized to be a detrimental consequence of breeding selection for accelerated growth rate and enlarged breast muscle which triggers the imbalance between muscle fiber and vascularization (Kuttappan et al., 2013; Petracci et al., 2013). An exertion of the growth-induced myopathy on a decrease in protein functionality has been extensively observed (Petracci et al., 2013; Baldi et al., 2018), corresponding to the greater drip loss, cook loss and expressible water of BR over SP samples. The reduced protein functionality, particularly WHC, of the abnormal meat potentially attributed by protein denaturation (Mudalal et al., 2014) may explain the markedly increased alkaline- soluble protein fraction in the BR. On the other hand, neither white striping nor other quality abnormalities have been observed in breast meat of any spent hens. In addition to collagen content, the amounts of water retained within cooked meat influenced its tenderness and mouthfeel (Tyszkiewicz et al., 1997). As observed herein, the cooked SP samples contained higher moisture than cooked BR. DISCUSSION The greater juiciness of the SP could be implicated but the impact of water content might not be sufficient to overcome the effects of structure of muscle fiber combined with collagen stability. Postmortem proteolytic activities of endogenous proteinases on target muscle proteins also play roles in meat tenderness (Kemp et al., 2010). As the structural proteins responsible for lateral and longitudinal integrity are degraded into fragments, the myofibrils tend to break more easily under force. By determining proteolytic capacity within breast muscle samples of 6-week-old chickens, Schreurs et al. (1995) indicated that White Leghorns showed the greater calpain activities but lower calpastatin activities compared to those of fast-growing broilers. As regards, the greater MFI value of SP samples was anticipated as the higher Another key determinant of ultimate meat tenderness is the postmortem biochemical events within the muscle. Anaerobic glycolysis, the major metabolic process responsible for ATP production at the early postmortem stage, led to accumulation of lactic acid, lowering muscle pH to ultimate meat pH. The obtained pH value of SP was comparable to those reviewed by Kondaiah & Panda (1992) and Rizzi et al. (2007) but slightly lower than those shown by 8 eRBCA-2018-0941 Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Limpisophon K, E-tun S, Koeipudsa C, Charoensuk D, Malila Y the proteolytic rate could bring about the rupture of myofibrils into fragments to the greater extent (Taylor et al., 1995). However, the current observation exhibited the opposite trend. The MFI of the SP samples was approximately 3.5-fold lower than that of the BR, indicating that the BR proteins were fragmented to the greater extent in comparison to that of SP, which was consistent with large variation of NPN fraction in the BR. The contradiction could be the effect of animal age as declined activities of μ- and m-calpains in turkey breast muscle were observed when slaughter age of the turkeys was extended from 5 weeks to 9 weeks (Northcutt et al., 1998). Another possibility could be related with development of white striping condition within the fast-growing broilers. Increased degree of fiber degradation, resulting in small protein fragments, has been observed within the breast showing white striping condition (Mudalal et al., 2014). DISCUSSION In conclusion, the present study suggested the tough texture of the cooked spent Lohmann breast meat was associated with the high total and heat-stable collagen content accompanied with dense organization of small muscle fibers and the less postmortem degradation of myofibril integrity. Since collagen generally provides background toughness to the meat, tenderization of the spent Lohmann meat could potentially be achieved by disrupting myofibril structure while preserving meat protein functionality, particularly WHC. The process of disintegrating muscle fibers without disturbing water retention in Lohmann breast meat are under investigation. The success of this findings could lay foundation in preparing the whole-muscle products from spent Lohmann fowls; hence, utilization of the spent hens could be maximized. ACKNOWLEDGEMENTS Thermal behaviors of BR and SP samples were consistent with ones of raw breast meat previously reported (Kijowski & Mast, 1988; Fernández-Martín et al., 2000; Kuo et al., 2005). It is interesting to observe that, in the SP samples, the first and the last denaturation temperatures (55.1ºC and 77.7ºC, respectively) were matched with the thermogram of water-washed myofibrils reported in the study of Kijowski & Mast (1988). On the other hand, the first peak of the BR samples was consistent with the denaturation temperature of isolated myosin. The current DSC results supported the superior myofibril integrity of SP meat while the myofibrils of the BR might undergo fragmentation to the greater extent, resulting in increasing free myosin molecules in the meat. The fifth transition is usually associated with denaturation of actin (Kijowski & Mast, 1988). The significantly greater DH of such peak in the SP samples suggested that the actin in SP samples might denature to the lesser extent in comparison to that of the BR, corresponding with a lower alkali-soluble protein fraction observed in the SP. The peak transition temperature of connective tissues previously reported was varied between 59ºC to 70ºC, depending on the ratio between endomysium to perimysium, structure and heating rate (Purslow, 2018). Herein, the broad thermal change around 62.1ºC accompanied with the absence of the peak at 67.6ºC in the SP may imply interactions of the connective tissue either at intra- or inter-molecular levels, supporting heat stability of the SP connective tissue. Fernández-Martín et al. (2000) also observed multiple endothermic transitions with a slight shift toward higher temperature of chicken breast meat. The authors are grateful for chicken samples from Sun Food International Company, Ltd. and experimental facilities at Food Biotechnology Research Unit, BIOTEC (Thailand). This research was financially supported by Young Scientist and Technologist Program (YSTP, grant number YSTP: SP58-824), National Science and Technology Development Agency (Thailand) to YM, SI and KL. Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Kondaiah N, Panda B. Processing and utilization of spent hens. World’s Poultry Science Journal 1992;48:255-268. Kondaiah N, Panda B. Processing and utilization of spent hens. World’s Poultry Science Journal 1992;48:255-268. Chen Y, Qiao Y, Xiao Y, Chen H, Zhao L, Huang M, et al. Differences in physicochemical and nutritional properties of breast and thigh meat from crossbred chickens, commercial broilers, and spent hens. Asian- Australasian Journal of Animal Science 2016;29:855-864. Chen Y, Qiao Y, Xiao Y, Chen H, Zhao L, Huang M, et al. Differences in physicochemical and nutritional properties of breast and thigh meat from crossbred chickens, commercial broilers, and spent hens. Asian- Australasian Journal of Animal Science 2016;29:855-864. Koomkrong A, Theerawatanasirikul S, Boonkaewwan C, Jaturasitha S, Kayan A. Breed-related number and size of muscle fibres and their response to carcass quality in chickens. Italian Journal of Animal Science 2015;14:638-642. Chuaynukool K, Wattanachant S, Siripongvutikorn S. Chemical and physical properties of raw and cooked spent hen, broiler and Thai indigenous chicken muscles in mixed herbs acidified soup (Tom Yum). Journal of Food Technology 2007;5:180-186. Kuo HL, Chen MT, Liu DC, Lin LC. Relationship between thermal properties of muscle proteins and pork quality. Asian-Australasian Journal of Animal Science 2005;18:427-432. Chueachuaychoo A, Wattanachant S, Benjakul S. Quality characteristics of raw and cooked spent hen Pectoralis major muscles during chilled storage: Effect of salt and phosphate. International Food Research Journal 2011;18:601-613. Kuttappan VA, Shivaprasad HI, Shaw DP, Valentine BA, Hargis BM, Clark FD, et al. Pathological changes associated with white striping in broiler breast muscles. Poultry Science 2013;92:331–338. Cooke VE, Gilpin S, Mahon M, Sandercock DA, Mitchell MA. A comparison of skeletal muscle fibre growth in broiler and layer chickens. British Poultry Science 2003;44:S33-34. Lakshani P, Jayasena DD, Jo C. Comparison of quality traits of breast meat from commercial broilers and spent hens in Sri Lanka. Korean Journal of Poultry Science 2016;43:55-61. Dawson PL, Sheldon BW, Miles JJ. Effect of aseptic processing on the texture of chicken meat. Poultry Science 1991;70:2359-2367. Lin CY, Hsu JC. Effects of surgical caponization of growth performance, fiber diameter and some physical properties of muscles in Taiwan country chicken cockerels. Asian-Australasian Journal of Animal Sciences 2002;15:401-405. DeVitre HA, Cunningham FE. Tenderization of spent-hen muscle using papain, bromelin, or ficin alone and in combination with salts. Poultry Science 1985;64:1476–1483. Mangiafico SS. Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers An R companion for the handbook of biological statistics. Version 1.3.3 [cited 2017 Nov 1].. New Brunswick: Rutgers Cooperative Extension; 2015 Available from: https://rcompanion.org/ rcompanion/d_02.html. Dransfield E, Sosnicki AA. Relationship between muscle growth and poultry meat quality. Poultry Science 1999;78:43-746. Fernández-Martín F, Fernández P, Carballo J, Jiménez-Colmenero F. DSC study on the influence of meat source, salt and fat levels, and processing parameters on batters pressurisation. European Food Research and Technology 2000;211:387-392. Malila Y, U-chupaj J, Srimarut Y, Chaiwiwattrakul P, Uengwetwanit T, Arayamethakorn S, et al. Monitoring of white striping and wooden breast cases and impacts on quality of breast meat collected from commercial broilers (Gallus gallus). Asian-Australasian Journal of Animal Science 2018;31:1807-1817. Fletcher DL. Poultry meat quality. World’s Poultry Science Journal 2002;58:131-145. Mazzoni M, Petracci M, Meluzzi A, Cavani C, Clavenzani P, Sirri F. Relationship between pectoralis major muscle histology and quality traits of chicken meat. Poultry Science 2015;94:123–130. Funaro A, Cardenia V, Petracci M, Rimini S, Rodriguez-Estrada MT, Cavani C. Comparison of meat quality characteristics and oxidative stability between conventional and free-range chickens. Poultry Science 2014;93:1511-1522. Mudalal S, Babini E, Cavani C Petracci M. Quantity and functionality of protein fractions in chicken breast fillets affected by white striping. Poultry Science 2014;93:2108-2116. Hopkins DL, Littlefield PJ, Thompson JM. A research note on factors affecting the determination of myofibrillar fragmentation. Meat Science 2000;56:19-22. Mutungi G, Purslow P, Warkup C. Influence of temperature, fibre diameter and conditioning on the mechanical properties of single muscle fibres extended to fracture. Journal of Science and Food Agriculture 1996;72:359–366. Jaturasitha S, Srikanchai T, Kreuzer M, Wicke M. Differences in carcass and meat characteristics between chicken indigenous to northern Thailand (Black-Boned and Thai native) and imported extensive breeds (Bresse and Rhode Island Red). Poultry Science 2008;87:160-169. Northcutt JK, Pringle TD, Dickens JA, Buhr RJ, Young LL. Effects of age and tissue type on the calpain proteolytic system in turkey skeletal muscle. Poultry Science 1998;77:367–372. Jin SK, Kim IS, Jung HJ, Kim DH, Choi YJ, Hur SJ. The development of sausages including meat from spent laying hen surimi. Poultry Science 2007;86:2676-2684. Petracci M, Mudalal S, Bonfiglio A, Cavani C. Occurrence of white striping under commercial conditions and its impact on breast meat quality in broiler chickens. Poultry Science 2013;92:1670-5. Johnston IA, Alderson R, Sandham C, Dingwall A, Mitchell D, Selkirk C, et al. REFERENCES Aberle ED, Forrest JC, Gerrard DE, Mills EW. Principles of meat science. 4th ed. Iowa: Kendall/Hunt Publishing Company; 2001. Alnahhas N, Berri C, Chabault M, Chartrin P, Boulay M, Bourin MC, et al. Genetic parameters of white striping in relation to body weight, carcass composition, and meat quality traits in two broiler lines divergently selected for the ultimate pH of the pectoralis major muscle. BMC Genetics 2016;17:61. Alves MFR, Abe FR, Boleli IC. Influence of enclosure size on growth of breast and leg muscle fibers in domestic fowl. International Journal of Poultry Science 2012;11:361-367. An JY, Zheng JX, Li JY, Zeng D, Qu LJ, Xu GY, et al. Effect of myofiber characteristics and thickness of perimysium and endomysium on meat tenderness of chickens. Poultry Science 2010;89:1750–1754. AOAC - Association of Official Analytical Chemists. Official methods of analysis of association of official analytical chemists. Gaithersburg: AOAC International; 2000. Baldi G, Soglia F, Mazzoni M, Sirri F, Canonico L, Babini E, et al. Implications of white striping and spaghetti meat abnormalities on meat quality and histological features in broilers. Animal 2018;12:164-173. Berri C, Le Bihan-Duval E, Debut M, Santé-Lhoutellier V, Baéza E, Gigaud V, Jégo Y, Duclos MJ. Consequence of muscle hypertrophy on characteristics of Pectoralis major muscle and breast meat quality of broiler chickens. Journal of Animal Science 2007;85:2005–2011. Buzala M, Janicki B. Review: effects of different growth rates in broiler breeder and layer hens on some productive traits. Poultry Science 2016;95:2151–2159. 9 eRBCA-2018-0941 Limpisophon K, E-tun S, Koeipudsa C, Charoensuk D, Malila Y Limpisophon K, E-tun S, Koeipudsa C, Charoensuk D, Malila Y Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Muscle fibre density in relation to the colour and texture of smoked Atlantic salmon (Salmo salar L.). Aquaculture 2000;189:335–349. Purslow PP. Intramuscular connective tissue and its role in meat quality. Meat Science 2005;70:435-447. Kang GH, Kim SH, Kim JH, Kang HK, Kim DW, Seong PN, et al. Effect of Flammulinavelutipes on spent-hen breast meat tenderization. Poultry Science 2012;91:232–236. Purslow PP. Contribution of collagen and connective tissue to cooked meat toughness;some paradigms reviewed. Meat Science 2018;144:127- 134. Kemp CM, Sensky PL, Bardsley RG, Buttery PJ, Parr T. Tenderness–an enzymatic view. Meat Science 2010;84:248-256. Rizzi C, Marangon A, Chiericato GM. Effect of genotype on slaughtering performance and meat physical and sensory characteristics of organic laying hens. Poultry Science 2007;86:128-135. Kijowski JM, Mast MG. Thermal properties of proteins in chicken broiler tissues. Journal of Food Science 1988;53:363-366. Sams AR. Lathyrogen effects of the collagen heat stability and tenderness of spent fowl muscle. Poultry Science 1990;69:477-481. Kittiphattanabawon P, Benjakul S, Visessanguan W. Isolation and characterization of collagen from the cartilages of brownbanded bamboo shark (Chiloscyllium punctatum) and blacktip shark (Carcharhinus limbatus). LWT - Food Science and Technology 2010;43:792-800. Schreurs FJG, Van Der Heide D, Leenstra FR, De Wit W. Endogenous proteolytic enzymes in chicken muscles. Difference among strains with different growth rate and protein efficiencies. Poultry Science 1995;74:523–537. 10 eRBCA-2018-0941 Limpisophon K, E-tun S, Koeipudsa C, Charoensuk D, Malila Y Limpisophon K, E-tun S, Koeipudsa C, Charoensuk D, Malila Y Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Characterization of Breast Meat Collected from Spent Lohmann Brown Layers in Comparison to Commercial Ross Broilers Taylor RG, Geesink GH, Thompson VF, Koohmaraie M, Goll DE. Is Z-disk degradation responsible for postmortem tenderization?. Journal of Animal Science 1995;73:1351-1367. Sirri F, Castellini C, Bianchi M, Petracci M, Meluzzi A, Franchini A. Effect of fast-, medium- and slow-growing strains on meat quality of chickens reared under the organic farming method. Animal 2011;5:312-319. Smith-Mungo LI, Kagan HM. Lysyl oxidase: properties, regulation and multiple functions in biology. Matrix Biology 1998;16:387-398. Tyszkiewicz I, Kłossowska BM, Wieczorek U, Jakubiec‐Puka A. Mechanical tenderisation of pork meat: protein and water release due to tissue damage. Journal of the Science of Food and Agriculture 1997;73:179- 185. Snedeker JG, Gautieri A. The role of collagen crosslinks in ageing and diabetes – the good, the bad, and the ugly. Muscles, Ligaments and Tendons Journal 2014;4:303-308. U-chupaj J, Malila Y, Gamonpilas C, Kijroongrojana K, Petracci M, Benjakul S, et al. Differences in textural properties of cooked caponized and broiler chicken breast meat. Poultry Science 2017;96:2491-2500. Sorapukdee S, Uesakulrungrueng C, Pilasombut K. Effects of humectant and roasting on physicochemical and sensory properties of jerky made from spent hen meat. Korean Journal for Food Science of Animal Resources 2016;36:326-334. Vaithiyanathan S, Naveena BM, Muthukumar M, Girish PS, Ramakrishna C, Sen AR, et al. Biochemical and physicochemical changes in spent-hen meat during postmortem aging. Poultry Science 2008;87:180–186. Suriani NW, Purnomo H, Estiasih T, Suwetja IK. Physicochemical properties, fatty acids profile and cholesterol content of indigenous manado chicken, broiler and spent hen meat. International Journal of ChemTech Research 2014;6:3896-3902. Visessanguan W, Benjakul S, Riebroyb S, Thepkasikul P. Changes in composition and functional properties of proteins and their contributions to Nham characteristics. Meat Science 2004;66:579–588. Tang H, Gong YZ, Wu CX, Jiang J, Wang Y, Li K. Variation of meat quality traits among five genotypes of chicken. Poultry Science 2009;88:2212- 2218. Visessanguan W, Ogawa M, Nakai S, An H. physicochemical changes and mechanism of heat-induced gelation of arrow tooth flounder myosin. Journal of Agricultural and Food Chemistry 2000;48:1016−1023. 11 eRBCA-2018-0941
https://openalex.org/W3120288095	https://zenodo.org/records/4456289/files/EvolSyst_article_60626.pdf	English	null	A new vine snake (Reptilia, Colubridae, Oxybelis) from Peru and redescription of O. acuminatus	Evolutionary Systematics	2,021	cc-by	9,338	Robert C. Jadin1, Michael J. Jowers2, Sarah A. Orlofske1, William E. Duellman3, Christopher Blair4,5, John C. Murphy6,7 1 Department of Biology and Museum of Natural History, University of Wisconsin Stevens Point, Stevens Point, WI 54481, USA 2 CIBIO/InBIO (Centro de Investigação em Biodiversidade e Recursos Genéticos), Universidade do Porto, Campus Agrario De Va 661, Vairão, Portugal 3 Biodiversity Institute, University of Kansas, 1345 Jayhawk Blvd., Lawrence, Kansas 66045-7593, USA 3 Biodiversity Institute, University of Kansas, 1345 Jayhawk Blvd., Lawrence, Kansas 66045-7593, USA 4 Department of Biological Sciences, New York City College of Technology, The City University of New York, 285 Jay Street, Brooklyn, NY 112015, USA 5 Biology PhD Program, CUNY Graduate Center, 365 5th Ave., New York, NY 10016, USA 7 Present address: 2564 E. Murdoch Ct., Green Valley, AZ 85614, USA http://zoobank.org/0370721B-4F60-4177-BE3B-823242A8B820 http://zoobank.org/0370721B-4F60-4177-BE3B-823242A8B820 Corresponding author: Robert C. Jadin (rcjadin@gmail.com) Corresponding author: Robert C. Jadin (rcjadin@gmail.com) Academic editor: A. Haas ♦ Received 11 November 2020 ♦ Accepted 30 December 2020 ♦ Published 14 Janua Key Words Amazon, conservation, Inkaterra, morphology, new species, Serpentes, Squamata, South America, systematics, taxono Abstract The Brown Vine Snake, Oxybelis aeneus, was until recently considered a single species, distributed from southern Arizona through the Neotropics into southeastern Brazil. However, newly conducted research restructured the species with a substantial taxonomic re- vision, recognizing five additional taxa (i.e. O. koehleri, O. microphthalmus, O. potosiensis, O. rutherfordi, O. vittatus) in this species complex. This revision focused on populations in North America, Central America, and northern South America while neglecting the southern portion of its distribution. Here, we examine the taxonomic history of the complex and use it along with specimen data to resurrect O. acuminatus from southeastern Brazil. Finally, we describe a new species from the Peruvian Amazon based on morpho- logical characters. This work increases the species diversity of the O. aeneus complex to eight, and we expect further increases in biodiversity discoveries with continued exploration of the New World vine snakes. Key Words Copyright Robert C. Jadin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. A new vine snake (Reptilia, Colubridae, Oxybelis) from Peru and redescription of O. acuminatus Robert C. Jadin1, Michael J. Jowers2, Sarah A. Orlofske1, William E. Duellman3, Christopher Blair4,5, John C. Murphy6,7 Evolutionary Systematics. 5 2021, 1–12 \| DOI 10.3897/evolsyst.5.60626 Evolutionary Systematics. 5 2021, 1–12 \| DOI 10.3897/evolsyst.5.60626 Introduction The ventral and subcaudal counts fall within the range of those of O. microphthalmus, but those individuals do not have a truncated snout. Therefore, giv- en the missing holotype, the lack of a detailed original de- scription, and a questionable type locality, we are unable to allocate specimens to this name and consequently, we consider this name a nomen nudum. The Brown Vine Snake, Dryinus aeneus Wagler, 1824, was described from a specimen collected at Ega, Brazil, (now Tefé, Brazil) on the south bank of the Amazon River at its junction with the Rio Tefé (Holotype ZSM 2645/0). Wagler was unaware that the generic name was preoc- cupied by Dryinus Latreille (1804), a Hymenopteran. Fitzinger (1826) used the combination Dryophis aeneus. Still, the generic name had been proposed previously by Dalman (1823) for the arboreal Asian snakes now in the genus Ahaetulla, but later rejected as invalid by ICZN Opinion 524. Subsequently, Wagler (1830) proposed the generic name Oxybelis but it did not gain common usage until the early 20th century. Bell’s (1825) description of Dryinus auratus (Fig. 1) on the basis of a specimen said to be from Mexico is like- ly in error. Günther (1858) reported 14 specimens of Dry- iophis acuminata in the British Museum. Specimen b in Günther’s (1858:156) list is described as “Adult. Brazil? Presented by T. Bell Esq.” Keiser (1974) considered this specimen as the holotype of Bell’s D. auratus and com- ments that A.G.C. Grandison and L.C. Stuart concurred with him. However, Grandison reported the specimen was no longer in the BMNH collection (Keiser 1974), and the Figure 1. Illustration reproduced from Bell 1825 of Dryinus au- ratus from “Mexico”. Wied (1824) described Coluber acuminatus (Holo- type, AMNH 3886, Fig. 2) without reporting a type lo- cality in the original description, though a second paper, Wied (1825:326), reported the specimen collected along the Río Espirito Santo in southeastern Brazil. He also remarks (rough translation) “Some differences notwith- standing it seems to me this snake is identical with Spix’s (1824) Dryinus aeneus…” Confusion over the publication date of Wied’s (1824) paper extended though most of the 19th century (see Keiser, 1974 for a discussion). Schlegel (1837) recognized D. auratus and placed Wagler’s D. ae- neus and Wied’s D. acuminatus as synonyms in error. Duméril et al. (1854) gave Wagler’s D. aeneus priority over D. acuminatus and D. auratus. Introduction Brazil, southern Brazil, southeastern Amazonia, Middle America, the Mexican Transition Zone, the Antilles, and the Pacific Coast. These distributions have populations on both sides of many extant biogeographic barriers that impede gene flow in the present day but may not have been isolating populations in the past (e.g. Daza et al. 2009, 2010; Jadin et al. 2012; Bagley and Johnson 2014). Additionally, some of these widespread taxa have com- plex nomenclatural histories, further challenging any at- tempts at revision. Widespread Neotropical snakes with distributions ex- tending from North America to South America, occu- py a variety of habitats and often contain unrecognized species diversity. Species such as the Boa constrictor (Reynolds and Henderson 2018), Chironius exoletus (Hamdan et al. 2017), and the Oxybelis aeneus complex (Jadin et al. 2019, 2020) occur in many important bio- geographical areas such as the Chacoan, Paraná, Boreal Copyright Robert C. Jadin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Robert C. Jadin et al.: New Peruvian vine snake and redescription of O. acuminatus 2 lost holotype is supported by Boulenger (1896) who list- ed all of the BMNH specimens with ventral and subcau- dal counts. None of the counts come close to those in the specimen described by Bell. Keiser (1974) raised the is- sue of collectors not being active in Mexico until later in the 19th century. Smith and Smith (1973) and Flores-Vil- lela et al. (2004) discussed the history of herpetological collections in Mexico. The timing of Bell’s publication suggests that if the specimen was from Mexico it most likely would have been collected by the Sessé and Mo- ciňo expedition (1788–1803). If the type specimen were indeed from “Mexico” it would share traits with popu- lations described as being either from Western Mexico (O. microphthalmus) or Eastern Mexico (O. potosiensis). Bell’s original description suggests the snout was trun- cated, ventrals numbered 196, and subcaudals were 160. Jadin et al. (2020) found that populations from Eastern Mexico have a truncated snout but fewer than 190 ven- trals and more than 160 subcaudals, though the tail tips of Bell’s specimen may have been broken as is often the case in vine snakes. Introduction That same year, Gi- rard, 1854, described Dryophis vittatus based on USNM 7315 (Fig. 3) with a type locality of Taboga Island, Bay of Panama, Panama. By 1858 Günther had placed O. aene- us (Wagler, 1824), D. auratus Bell, 1825, and O. vittatus (Girard, 1854) in the synonymy of Dryiophis acuminata. And, Boulenger (1896), following Cope (1862) used the combination Oxybelis acuminatus because of continuing confusion over the publication date of Wied’s (1824) pa- per. Given that the type localities of O. acuminatus and O. aeneus are separated by 3200 km, it would seem likely that they are separate species. Barbour and Amaral (1926) described Oxybelis mi- crophthalmus based on S. H. Beattie’s specimen (MCZ 22417) from Calabasas Canyon, in Santa Cruz County’s Pajaritos Mountains of Arizona; writing, “A large Oxybe- lis, similar in habit and coloration to O. acuminatus but differing from that species in having a much smaller eye Figure 1. Illustration reproduced from Bell 1825 of Dryinus au- ratus from “Mexico”. evolsyst.pensoft.net 3 Evolutionary Systematics 5 2021, 1–12 3 and a much longer and differently shaped snout.” More recently, Oxybelis potosiensis was described by Taylor (1941), which has a type locality near Ciudad Maíz, San Luis Potosí, México (Holotype UIMNH 25069). Bogert and Oliver (1945) examined several characters found in the O. aeneus complex. They concluded recognizing two populations of O aeneus: O a aeneus with a range ex phthalmus Barbour & Amaral, 1926 and O. potosiensis Taylor, 1941 into O. a. auratus. Recently, Jadin et al. (2019) conducted the first signif- icant phylogenetic study on Oxybelis and found strong support that O. aeneus sensu lato was a complex of spe- cies in drastic need of revision. Their work identified four novel taxa even as their dataset was restricted to Figure 2. A, Illustration of Coluber acuminatus reproduced from Wied 1824. B, Holotype of O. acuminatus AMNH 3886. Figure 3. A, Illustration of Dryophis vittatus Girard 1854. B and C, in life photographs of O. vittatus from Panama (S. Lotzkat). Figure 2. A, Illustration of Coluber acuminatus reproduced from Wied 1824. B, Holotype of O. acuminatus AMNH 3886. Figure 2. A, Illustration of Coluber acuminatus reproduced from Wied 1824. B, Holotype of O. acuminatus AMNH 3886. Figure 2. A, Illustration of Coluber acuminatus reproduced from Wied 1824. B, Holotype of O. acuminatus AMNH 3886. Figure 3. A, Illustration of Dryophis vittatus Girard 1854. evolsyst.pensoft.net Morphological data p g Alcohol-preserved specimens of Oxybelis aeneus sen- su lato from throughout its range were examined at the Field Museum of Natural History and the University of Wisconsin – Stevens Point Museum of Natural History (Appendix 1). Scale counts generally follow Peters (1964) with minor exceptions. Dorsal scales were counted on the diagonal, approximately ten ventral scales from the head, at mid-body, and approximately ten ventral scales anterior to the vent. Scale counts and scale measurements were conducted using a a Leica S8 APO dissection microscope. Larger body measurements were taken with a meter stick, metric tape, and/or dial calipers. Scale counts represent- ing a range taken from different individuals are separated by a dash (–). Scale counts separated by a slash (/) are taken from a single individual, with the number on the left representing scale numbers on the snake’s left and the number on the right representing scale numbers on the snake’s right. Ventral counts follow Dowling (1951). Pho- tographs of scale arrangements were taken with a Canon EOS cameras and macro lenses. Sex was determined by probing, tail shape, and/or visual inspection of the hemi- penes, testes, and/or ovaries. Coloration in life of the ho- lotype is based on field notes and photos taken by WED. To determine the distinctiveness of our Peruvian spec- imens and O. acuminatus within the Oxybelis aeneus complex we conducted a principal component analysis (PCA). We lumped our examined specimens into groups representing these two groups and the distinct species identified in Jadin et al. (2020). Our principal components analysis was conducted using DataLab Version 3.911 (Epina GmbH, Pressbaum, Austria) software and the following twelve morphological characters: (1) second upper labial at preocular, (2) underside of head black pig- mented, (3) orange pigment on labials, (3) eye diameter greater that preocular, (4) second pair of chin shields sep- arated (5) supraocular longer than prefrontals (6) number of upper labials post orbit, (7) number of upper labials on one side, (8) head width/head length, (9) number of upper labials in orbit, (10) eye diameter/ prefrontal (11) eye diameter divided by internasal length, (12) eye-nos- tril distance/ head length. Alcohol-preserved specimens of Oxybelis aeneus sen- su lato from throughout its range were examined at the Field Museum of Natural History and the University of Wisconsin – Stevens Point Museum of Natural History (Appendix 1). Scale counts generally follow Peters (1964) with minor exceptions. Introduction B and C, in life photographs of O. vittatus from Panama (S. Lotzkat). ustration of Dryophis vittatus Girard 1854. B and C, in life photographs of O. vittatus from Panama (S. Lotzkat). Figure 3. A, Illustration of Dryophis vittatus Girard 1854. B and C, in life photographs of O. vittatus from Panama and a much longer and differently shaped snout.” More recently, Oxybelis potosiensis was described by Taylor (1941), which has a type locality near Ciudad Maíz, San Luis Potosí, México (Holotype UIMNH 25069). Bogert and Oliver (1945) examined several characters found in the O. aeneus complex. They concluded recognizing two populations of O. aeneus: O. a. aeneus with a range ex- tending from Guatemala to southeastern Brazil, and O. a. auratus with a range from southern Arizona, in the northwest of its distribution, and from San Luis Potosi at the northeast, southward to the Isthmus of Tehuantepec and the Yucatan Peninsula, thus synonymizing O. micro- phthalmus Barbour & Amaral, 1926 and O. potosiensis Taylor, 1941 into O. a. auratus.i Recently, Jadin et al. (2019) conducted the first signif- icant phylogenetic study on Oxybelis and found strong support that O. aeneus sensu lato was a complex of spe- cies in drastic need of revision. Their work identified four novel taxa even as their dataset was restricted to populations in the northern part of the species’ distri- bution (i.e. Arizona, USA to Venezuela). However, they refrained from recognizing any additional species until morphological data could be included. Subsequently, Jadin et al. (2020) examinationed these populations to evolsyst.pensoft.net Robert C. Jadin et al.: New Peruvian vine snake and redescription of O. acuminatus 4 Materials and methods Figs 5–9 Suggested English Name: Inkaterra Vine Snake Suggested Spanish Name: Inkaterra Serpiente de vid Suggested English Name: Inkaterra Vine Snake Suggested English Name: Inkaterra Vine Snake Suggested Spanish Name: Inkaterra Serpiente de vid Morphological data Dorsal scales were counted on the diagonal, approximately ten ventral scales from the head, at mid-body, and approximately ten ventral scales anterior to the vent. Scale counts and scale measurements were conducted using a a Leica S8 APO dissection microscope. Larger body measurements were taken with a meter stick, metric tape, and/or dial calipers. Scale counts represent- ing a range taken from different individuals are separated by a dash (–). Scale counts separated by a slash (/) are taken from a single individual, with the number on the left representing scale numbers on the snake’s left and the number on the right representing scale numbers on the snake’s right. Ventral counts follow Dowling (1951). Pho- tographs of scale arrangements were taken with a Canon EOS cameras and macro lenses. Sex was determined by probing, tail shape, and/or visual inspection of the hemi- penes, testes, and/or ovaries. Coloration in life of the ho- lotype is based on field notes and photos taken by WED. Oxybelis aeneus – Keiser, 1974:7; Duellman 2005: 363, pl 205 has a photograph of a live specimen Jadin et al. 2020: Fig 1. has a photograph of a live specimen. Oxybelis aeneus – Keiser, 1974:7; Holotype. KU 220196 (Figs 5, 6), from Peru, Madre de Dios: Cusco Amazónico (now Reserva Amazónica), Río Madre de Dios, c. 15 km E Puerto Maldonado, 200 m, 12°34'59"S, 69°4'59"W; collected by William E. Duell- man (WED 59561), 21 December 1991. Holotype. KU 220196 (Figs 5, 6), from Peru, Madre de Dios: Cusco Amazónico (now Reserva Amazónica), Río Madre de Dios, c. 15 km E Puerto Maldonado, 200 m, 12°34'59"S, 69°4'59"W; collected by William E. Duell- man (WED 59561), 21 December 1991. Paratypes. KU 214887, Peru, Madre de Dios: Cusco Amazónico, Río Madre de Dios, c. 15 km E Puerto Mal- donado, 200 m, 12°34'59.88"S, 69°4'59.879"W; collect- ed by Erik R. Wild (Field number WED 59004), 23 De- cember 1989; ZMH R01702, Peru, Huánuco: Pachitea, Panguana Biological Fieldstation, Rio Yuyapichis [= Rio Llullapichis], 260 m, approx. 9°41'S, 74°57'W, collected by János Regös July 1980. Other material examined. FMNH 56141, from Peru, Loreto, Río Ucayali: Yarinacocha (c. 13°51'S, 71°1'W), collected by J.M. Schunke, 05 Sep 1946. FMNH 40085 (female), from the Madre de Dios area of Peru (no spe- cific locality). ZMH R01611, Peru, Huánuco: Pachitea, Panguana Biological Fieldstation, Rio Yuyapichis [= Rio Llullapichis], 260 m, approx. Results include morphology and more molecular data and re- moved O. microphthalmus, O. potosiensis, and O. vitta- tus from the synonymy of O. aeneus. Furthermore, Jadin et al. (2020) described O. koehleri from populations in Central America and O. rutherfordi from northern South America. They suggested that many more species would likely result from further investigation. Here, we inspect the clade further and resurrect O. acuminatus as a valid taxon from the Atlantic Coastal Forest of southeastern Brazil and describe a new species of Oxybelis from the Peruvian Amazon. Our morphological analyses suggest distinctiveness among members of the Oxybelis aeneus complex, includ- ing O. acuminatus and specimens from Peru (Table 1). More specifically, our PCA produced five distinct groups: (1) O. rutherfordi, (2) O. vittatus and Peru, (3) O. aeneus, (4) O. potosiensis, and (5) O. acuminatus, O. koehleri, and O. microphthalmus (Fig. 4). Morphological data 9°35'S, 74°56'W, collected by Carlos Vasquez Modena 1980. Like other members of the Oxybelis aeneus complex O. inkaterra has an elongated head and body, 8–9 upper labials, four lower labials contacting the first pair of chin shields, 173–205 ventrals and 158–203 subcaudals; a divided anal plate, dorsal scales in 17–17–13 rows, and undivided hemipenes. Other material examined. FMNH 56141, from Peru, Loreto, Río Ucayali: Yarinacocha (c. 13°51'S, 71°1'W), collected by J.M. Schunke, 05 Sep 1946. FMNH 40085 (female), from the Madre de Dios area of Peru (no spe- cific locality). ZMH R01611, Peru, Huánuco: Pachitea, Panguana Biological Fieldstation, Rio Yuyapichis [= Rio Llullapichis], 260 m, approx. 9°35'S, 74°56'W, collected by Carlos Vasquez Modena 1980. ypi p y To determine the distinctiveness of our Peruvian spec- imens and O. acuminatus within the Oxybelis aeneus complex we conducted a principal component analysis (PCA). We lumped our examined specimens into groups representing these two groups and the distinct species identified in Jadin et al. (2020). Our principal components analysis was conducted using DataLab Version 3.911 (Epina GmbH, Pressbaum, Austria) software and the following twelve morphological characters: (1) second upper labial at preocular, (2) underside of head black pig- mented, (3) orange pigment on labials, (3) eye diameter greater that preocular, (4) second pair of chin shields sep- arated (5) supraocular longer than prefrontals (6) number of upper labials post orbit, (7) number of upper labials on one side, (8) head width/head length, (9) number of upper labials in orbit, (10) eye diameter/ prefrontal (11) eye diameter divided by internasal length, (12) eye-nos- tril distance/ head length. Diagnosis. A vine snake with (1) three upper labials (4–5–6) bordering the orbit; (2) numerous bold black bars and spots present on the body; (3) ventral surface mottled with dense black spots; (4) preocular shorter than eye diameter; (5) second pair of chin shields separated by smaller scales posteriorly; (6) nine upper labials, three located behind the orbit; (7) snout from above relative- ly broad, tapered, and flat rostrum; (8) supraocular and prefrontal are about the same length; (9) last upper labi- Diagnosis. evolsyst.pensoft.net Morphological data vittatus Upper labials in orbit 3 (4-5-6) 3 (4-5-6) 3 (4-5-6) 3 (4-5-6) 3 (4-5-6) 2 (4-5) or (5-6) 2 (4-5) 3 (4-5-6) Stripes on venter Indistinct No No Variable Variable Variable Yes Yes Preocular shorter than eye diameter Yes Yes Yes Yes no Yes Yes Yes Posterior border of internasals extends beyond posterior edge of first upper labial Yes Yes No Yes Yes Yes No No Chin heavily mottled No No Yes Yes, in females No No No No Supraocular longer than prefrontal Yes No, equal in length No, equal in length No, equal in length Yes Yes Yes Yes Second upper labial contacts preocular Yes No No No No No No No Second pair of chin shields contacting each other No No No Yes Yes Yes Yes Yes Number of lower labials contacting first pair of chin shields 5 4 4 4 4 4 4 4 Figure 4. Plot of PC-1 and PC-2 scores extracted from a Principle Components Analysis of twelve morphological characters, show- ing distinct clustering among geographically defined groups. Circular symbols represent Oxybelis acuminatus (red), O. aeneus (or- ange), O. koehleri (yellow), O. microphthalmus (light blue), O. potosiensis (green), O. rutherfordi (dark blue), O. vittatus (brown) and Peruvian specimens (gray). Figure 4. Plot of PC-1 and PC-2 scores extracted from a Principle Components Analysis of twelve morphological characters, show- ing distinct clustering among geographically defined groups. Circular symbols represent Oxybelis acuminatus (red), O. aeneus (or- ange), O. koehleri (yellow), O. microphthalmus (light blue), O. potosiensis (green), O. rutherfordi (dark blue), O. vittatus (brown), and Peruvian specimens (gray). Rostral broader than high, barely visible from above; upper labials 9/9; internasals paired, not extending past the posterior border of the first upper labial; prefrontals paired, in contact with upper labials 2 and 3; frontal, paired parietals, and supraoculars elongated and about 6 mm long, and in contact with supraoculars and upper pos- tocular; postoculars 2/2; upper labials in contact with the preocular; 4–5–6 enter the orbit; 7–8–9 contact the pri- mary temporal; 9 interrictals; one preocular less than the diameter of the eye; lower labials 10/10, first four in con- tact with the first pair of chin shields; second pair of chin shields longest; five paired gulars. Dorsal scales smooth in 17–17–13 rows. Ventrals 182; 165 divided subcaudals; anal plate divided. Morphological data A vine snake with (1) three upper labials (4–5–6) bordering the orbit; (2) numerous bold black bars and spots present on the body; (3) ventral surface mottled with dense black spots; (4) preocular shorter than eye diameter; (5) second pair of chin shields separated by smaller scales posteriorly; (6) nine upper labials, three located behind the orbit; (7) snout from above relative- ly broad, tapered, and flat rostrum; (8) supraocular and prefrontal are about the same length; (9) last upper labi- evolsyst.pensoft.net Evolutionary Systematics 5 2021, 1–12 5 Table 1. A morphological comparison of the eight species in the Oxybelis aeneus complex. Table 1. A morphological comparison of the eight species in the Oxybelis aeneus complex. Oxybelis acuminatus O. aeneus O. inkaterra sp. nov. O. koehleri O. microphthalmus O. potosiensis O. rutherfordi O. vittatus Upper labials in orbit 3 (4-5-6) 3 (4-5-6) 3 (4-5-6) 3 (4-5-6) 3 (4-5-6) 2 (4-5) or (5-6) 2 (4-5) 3 (4-5-6) Stripes on venter Indistinct No No Variable Variable Variable Yes Yes Preocular shorter than eye diameter Yes Yes Yes Yes no Yes Yes Yes Posterior border of internasals extends beyond posterior edge of first upper labial Yes Yes No Yes Yes Yes No No Chin heavily mottled No No Yes Yes, in females No No No No Supraocular longer than prefrontal Yes No, equal in length No, equal in length No, equal in length Yes Yes Yes Yes Second upper labial contacts preocular Yes No No No No No No No Second pair of chin shields contacting each other No No No Yes Yes Yes Yes Yes Number of lower labials contacting first pair of chin shields 5 4 4 4 4 4 4 4 Figure 4. Plot of PC-1 and PC-2 scores extracted from a Principle Components Analysis of twelve morphological characters, show- ing distinct clustering among geographically defined groups. Circular symbols represent Oxybelis acuminatus (red), O. aeneus (or- ange), O. koehleri (yellow), O. microphthalmus (light blue), O. potosiensis (green), O. rutherfordi (dark blue), O. vittatus (brown), and Peruvian specimens (gray). al about same length as primary temporal; (10) much of Rostral broader than high barely visible from above; Table 1. A morphological comparison of the eight species in the Oxybelis aeneus complex. Oxybelis acuminatus O. aeneus O. inkaterra sp. nov. O. koehleri O. microphthalmus O. potosiensis O. rutherfordi O. evolsyst.pensoft.net Morphological data al about same length as primary temporal; (10) much of the lower surface of the head infused with black pigment; (11) second upper labial not in contact with preocular. Comparison. Oxybelis inkaterra can be distinguished from the seven other members of the Oxybelis aeneus complex by the presence of, upper labials three and four are in contact the preocular; a head with an irregular, dark- ly pigmented ventral surface with pale spots; and eyespot markings on the posterior ventral surface of the body and tail; the snout of O. inkaterra is also relatively short and broad compared to other species in the Oxybelis aeneus complex (Fig. 7); the lack the brown-gray dorsal color- ation seen in the other members of the complex. The dor- sum is instead a dirty cream with black flecking (Figs 6, 8). Description of the holotype. A male with everted hemipenes (Fig. 6), SVL 732 mm, tail length 498 mm. In alcohol. Top of the head is brown with dark brown to black mottling (Figs 7, 8); black spot on posterior 6 Robert C. Jadin et al.: New Peruvian vine snake and redescription of O. acuminatus Figure 5. Holotype of Oxybelis inkaterra sp. nov., KU 220196 in life from Reserva Amazonica, formerly Cusco Amazonico, Peru (W.E. Duellman). Coloration of the holotype in life (Fig. 5). Field notes by W.E. Duellman on 21 December 1991: Dorsum and venter grayish tan with dark brown flecks and streaks. Top of head brown; lateral stripe on head dark brown, bordered below by white. Iris cream with horizontal dark brown stripe. Lining of mouth and throat black. Variation. Whereas surrounding the black spots was not as pronounced in smaller individuals, KU 220196 has the first 33 ventral scales almost completely black (in preservative), but the stripes are still visible (Fig. 6). The black pigment extends onto the chin shields in varying amounts. The largest female was 1075 mm in total length; the largest male was 1278 mm. Two females had SVLs of 484 and 660 mm (x– = 572 mm SD = 88.0) with tails that were 0.62 and 0.63 of the SVL (x– =358.5, SD = 56.50). Two females (FMNH 40085, 56141) (had 184 and 191 ventrals (x– = 187.5, SD = 1.5). Eight upper labials, with 4–5–6 bordering the orbit. Usually 8–9 (nine on one side) lower labials, with four (usually) at first chin shield. Distribution. evolsyst.pensoft.net Morphological data This species occurs in the Amazonian rainforest of Peru in the departments of Huánuco, Loreto, and Madre de Dios. It is likely the species also occurs in Ucayali between these departments and possibly adjacent Bolivia, Brazil, and Colombia. Ecology. At Reserva Amazónica, Oxybelis inkaterra is found in the dense vegetation on the bank of the Río Madre de Dios and in an adjacent clearing. The steep riverbank has vegetation unlike that of the adjacent rain- forest. There are shrubby plants and no canopy; adja- cent to the river are stands of the cane-like Gynerium saggitatum (Ponaceae). Oxybelis inkaterra is a diurnal arboreal snake, which, if like other members of the ge- nus, has a fondness for small lizards. In the scrub forest adjacent to the river two species, Gonatodes humeralis (Sphaerodactylidae) and Anolis fuscoauratus (Dactyloi- dae), inhabit the scrub and probably are primary prey of the vine snake. Field notes. KU 220196, weight 30.5 g, caught on the ground in camp during the day. Dorsum and venter gray- ish tan with dark brown flecks and streaks. Top of head brown; lateral stripe on head dark brown, bordered below by white. Iris cream with horizontal dark brown stripe. Lining of mouth and throat black. KU 214887, caught in bush 1.5 m above ground by day edge of river in camp. Mass 15 g, 895 mm TL.i Figure 5. Holotype of Oxybelis inkaterra sp. nov., KU 220196 in life from Reserva Amazonica, formerly Cusco Amazonico, Peru (W.E. Duellman). edge of nasal, and on preocular; black mottling on tem- porals forming an irregular postocular stripe that ex- tends to second or third ventral; upper labials with mot- tling on borders, lower labials heavily mottled; mental, first pair of lower labials, and chin shields black with white spots; dorsal scales mottled with black and brown pigment in all rows; on anterior third of the body, some scales have heavy black pigment on their borders and form about 48 irregular transverse bands; anterior ven- trals heavily mottled becoming fine stippling posteri- orly; some ventrals mottled with scattered black spots anteriorly; posteriorly, these spots encircled with white pigment to form eye spot-like markings near the vent; some of these markings also occur on the ventral and lateral portions of the tail. Morphological data edge of nasal, and on preocular; black mottling on tem- porals forming an irregular postocular stripe that ex- tends to second or third ventral; upper labials with mot- tling on borders, lower labials heavily mottled; mental, first pair of lower labials, and chin shields black with white spots; dorsal scales mottled with black and brown pigment in all rows; on anterior third of the body, some scales have heavy black pigment on their borders and form about 48 irregular transverse bands; anterior ven- trals heavily mottled becoming fine stippling posteri- orly; some ventrals mottled with scattered black spots anteriorly; posteriorly, these spots encircled with white pigment to form eye spot-like markings near the vent; some of these markings also occur on the ventral and lateral portions of the tail. Etymology. The specific epithet honors the ecotour- ism company Inkaterra (https://www.inkaterra.com/) and its non-profit NGO counterpart Inkaterra Asociación. These two institutions started in 1975 and 1978, respec- tively, were founded by José E. Koechlin von Stein to promote education and conservation of Peruvian culture and ecosystems. Inkaterra and Mr. Koechlin have been recognized numerous times with awards and accolades for providing sustainable ecotourism and research oppor- tunities for scientists. The type locality, Cusco Amazóni- co (now Reserva Amazónica), is owned and operated by Inkaterra and is the site of one of the most thoroughly studied areas in the Neotropics, particularly for amphib- 7 Evolutionary Systematics 5 2021, 1–12 Figure 6. Holotype of Oxybelis inkaterra sp. nov., KU 220196 preserved. A, Dorsal whole specimen; B, ventral whole specimen views; C, top of the head; D, profile. Scale bar: 1 cm. Figure 6. Holotype of Oxybelis inkaterra sp. nov., KU 220196 preserved. A, Dorsal whole specimen; B, ventral whole specimen views; C, top of the head; D, profile. Scale bar: 1 cm. Figure 7. A comparison between the snout shapes of Oxybelis aeneus (FMNH 64417) (top) and O. inkaterra (FMNH 56141) (bot- tom) (JCM). Figure 7. A comparison between the snout shapes of Oxybelis aeneus (FMNH 64417) (top) and O. inkaterra (FMNH 56141) (bot- tom) (JCM). Figure 7. A comparison between the snout shapes of Oxybelis aeneus (FMNH 64417) (top) and O. inkaterra (FMNH 56141) (bot- tom) (JCM). ed to use visual coloration and behaviors to deter preda- tors (Green, 1997). Eyespots are circular markings, often with concentric rings and conspicuous colors, that occur in many animals. evolsyst.pensoft.net Oxybelis acuminatus (Wied, 1824) Atlantic Forest Vine Snake Coluber acuminatus – Wied, in Anonymous, 1824: 667. Holotype AMNH 3886. The type locality Rio Espirito Santo, in southeastern Brazil (~19°2'S, 40°43'W). Note that the name Coluber acuminatus was published in June of 1824, and it was long given priority over Wagler’s Dryinus aeneus 1824, which was published in March of 1824, see Keiser (1974:4). Oxybelis aeneus aeneus – Bogert & Oliver, 1945: 391. Bogert and Oliver (1945) reported on the type specimen, a female that is 1255 mm in total length with a 444 mm incomplete tail; the dorsal scales are in 17–17–15 rows; it has 197 ventral scales and 144 subcaudal scales but the tail tip is missing; the upper labials are 8/9, the fourth and fifth border the orbit on the right side, and upper labials 4–5–6 border the orbit on the left side; lower labials are 8/8; the preocular is single on both sides and two postoculars occur on each side; head width is 9.4 mm and the length is 23.8 (hl/w ratio is 2.53); eye diameter is 4.4 mm and the internasal is 4.6 mm (0.95 eye diameter/internasal ratio). Molecular techniques combined with morphological analyses are increasing the number of recognized squa- mate species. Uetz et al. (2020) reported 3,149 species of snakes in 2008 and 3,848 species in 2020: a difference of 699 species (>22%) in a span of 12 years. With the ad- dition of these two South American species, we increase the known species diversity of the Oxybelis aeneus com- plex to eight. This is likely a continued underestimate of species diversity within Oxybelis. For example, we have seen members of the O. aeneus complex from the west side of the Andes with a pair of well-defined stripes on the venter that are lacking in specimens from the east side of the Andes. In addition, recent work on the phylogeog- raphy of Oxybelis (Jadin et al. 2020) recovered O. fulg- idus from French Guiana and Venezuela paraphyletic to the Honduras and Mexico populations. Novel sampling and examination of present museum material of Oxybe- lis populations, especially in South America, is needed and further work with this genus should yield additional improvements to our understanding of the diversity and evolutionary history of Oxybelis. Diagnosis. Oxybelis acuminatus (Wied, 1824) Atlantic Forest Vine Snake A vine snake with (1) three upper labials (4–5–6) bordering the orbit on the left; (2) black bars or spots present on the anterior body; (3) indistinct stripe on the outer edges of ventral scales, venter finely mottled; (4) eye diameter greater than preocular length; (5) sec- ond pair of chin shields separated by smaller scales for most of their length; (6) nine upper labials, three located behind the orbit; (7) snout from above relatively broad, slightly tapered, and flat at rostrum; (8) supraocular lon- ger than prefrontals; (9) last upper labial longer than pri- mary temporal; (10) lower surface of head uniform in color; (11) second upper labial in contact with preocular (this character state appears to occurs only in this taxa). Morphological data way to startle or intimidate predators or they may work by being highly salient stimuli that promote sensory overload, biases, or neophobic reactions (Stevens and Ruxron 2014). Few snakes have been reported to have eyespots but Oxy- belis inkaterra appears to be an exception and does exhibit ventral eyespots (Fig. 9). Although the markings are quite variable in size and definition, they are best developed in specimen FMNH 56141 from Yarinacocha, Peru. Giv- en the absence of information in terms of how the snake uses these markings it is entirely possible that they simply make the snake more cryptic in its arboreal environment. However, the placement of the eyespots on the posterior ventral side of the body and on the tail suggests that they may be displayed in response to a predator. Distribution. This species is likely restricted to the Atlantic Forest of southeastern Brazil. Biodiversity Although our PCA analysis did not distinguish O. acum- inatus or O. inkaterra from all other species of the O. ae- neus complex, this not surprising given the large number of species in the analysis and the depauperate morpholog- ically distinguishing characters available due to the cryp- tic nature of this species complex. Furthermore, the anal- ysis placed these two species near Middle American taxa not likely to be the most closely related species based on geography. Therefore, we consider this analysis valuable in distinguishing them from other South American taxa and utilize additional morphological features to clearly distinguish all taxa from each other (see taxonomic de- scriptions above and Table 1). Morphological data They have been hypothesized to work as a ed to use visual coloration and behaviors to deter preda- tors (Green, 1997). Eyespots are circular markings, often with concentric rings and conspicuous colors, that occur in many animals. They have been hypothesized to work as a ian and reptile natural history (e.g. Duellman, 2005; Or- lofske et al. 2012). Notes on potential eyespots. Anti-predator adaptations in snakes are numerous and diurnal species can be expect- evolsyst.pensoft.net Robert C. Jadin et al.: New Peruvian vine snake and redescription of O. acuminatus 8 8 Figure 8. Referred specimen of Oxybelis inkaterra sp. nov., FMNH 56141 from Peru, Loreto, Rio Ucayali, Yarinacocha. A, profile; B, top of the head; C, bottom of the head. Figure 8. Referred specimen of Oxybelis inkaterra sp. nov., FMNH 56141 from Peru, Loreto, Rio Ucayali, Yarinacocha. A, profile; B, top of the head; C, bottom of the head. Figure 9. Referred specimen of Oxybelis inkaterra sp. nov., FMNH 56141 displaying eyespots on posterior ventral scales (left) and on subcaudal scales (right). Figure 9. Referred specimen of Oxybelis inkaterra sp. nov., FMNH 56141 displaying eyespots on posterior ventral scales (left) and on subcaudal scales (right). evolsyst.pensoft.net Evolutionary Systematics 5 2021, 1–12 9 way to startle or intimidate predators or they may work by being highly salient stimuli that promote sensory overload, biases, or neophobic reactions (Stevens and Ruxron 2014). Few snakes have been reported to have eyespots but Oxy- belis inkaterra appears to be an exception and does exhibit ventral eyespots (Fig. 9). Although the markings are quite variable in size and definition, they are best developed in specimen FMNH 56141 from Yarinacocha, Peru. Giv- en the absence of information in terms of how the snake uses these markings it is entirely possible that they simply make the snake more cryptic in its arboreal environment. However, the placement of the eyespots on the posterior ventral side of the body and on the tail suggests that they may be displayed in response to a predator. lower dorsum and ventral surface of the body and the tail have scattered small black spots. Keiser (1974) reported 17–20 maxillary teeth in specimens from southeastern Brazil. These traits and its presence in Brazil’s Atlantic Forest, a center for endemism, revalidate this species. Acknowledgements the systematics of microteiid lizards found 19 unnamed lineages at the level of species in the Cercosaurinae, a reminder of how little is known about some reptile groups in the region. A total of 38 species of snakes representing 13 genera are endemic to Peru and the new description of Oxybelis inkaterra places it as a new Peruvian endemic, at least temporarily, raising the total number of endemic snake species to 39 and 14 genera in the country. We thank T. Dowling and C. Johnson (ASU); A. Resetar (FMNH); L.J. Welton and R.M. Brown (KU); G.A. Ri- vas (MBLUZ); J. Rosado, T. Takahashi, and J. Hanken (MCZ); G. Bradley and P. Rienthal (UAZ); C.M. Sheehy III, D.C. Blackburn, M.A. Nickerson (UF); G. Schnei- der (UMMZ); C.J. Franklin, G. Pandelis, E.N. Smith, and J.A. Campbell (UTA); and M.G. Rutherford (UWIMZ) for allowing us to examine specimens under their care. We thank D.A. Kiziran and L. Vonnahme (AMNH) for photographs of the type specimen of Coluber acuminatus and S. Lotzkat for an in-life photograph of O. vittatus. We thank J. Hallermann (ZMH) for providing us data on specimens under his care. This manuscript was improved by reviews from J. Hallermann and E. Lehr. RCJ, SAO, and WED greatly appreciate the kind generosity of José E. Koechlin von Stein and the staff at Inkaterra for their friendship and support of our research over the years. MJJ was supported by the Portuguese Foundation for Science and Technology (FCT, SFRH/BPD/109148/2015). The presence of an endemic Oxybelis in Peru is note- worthy and may help elucidate how diverse ecological factors may drive regional patterns of species divergence and speciation (Card et al. 2016). Jadin et al. (2019) found a Mid-Miocene (14.5 Ma) divergence between the green colored clade composed by O. fulgidus (from Mexico and Guatemala) and O. wilsoni from (Roatán Island, Hondu- ras) and the brown colored clade with all other remaining Oxybelis included in their analyses. Their divergence time and ancestral area estimates suggest a Central American origin of the O. aeneus clade and its invasion of South America when the Panamanian isthmus closed, approxi- mately 2.8 Ma. The presence of Oxybelis in cis-Andean regions suggests that the Central and Eastern Cordille- ra of Colombia already uplifted after the timing of the Panamanian isthmus (Gregory-Wodzicki, 2000; Javadi et al. 2011; Murphy et al. Biogeography Comparison. Oxybelis acuminatus can be distin- guished from all other members in the O. aeneus com- plex by having their second upper labial contacting their preocular (Fig. 2B); all other species have the third up- per labial contacting the preocular (Table 1). Five lower labials are contacting the chin shields, a character state occasionally seen in O. rutherfordi from northern South America and O. vittatus from Panama. Posteriorly the Comparison. Oxybelis acuminatus can be distin- guished from all other members in the O. aeneus com- plex by having their second upper labial contacting their preocular (Fig. 2B); all other species have the third up- per labial contacting the preocular (Table 1). Five lower labials are contacting the chin shields, a character state occasionally seen in O. rutherfordi from northern South America and O. vittatus from Panama. Posteriorly the Peru is a biodiversity hotspot (Myers et al. 2000) with a staggering 506 reptiles, of which 231 are snakes (Uetz et al. 2020). Its notable richness is further evidenced by ongoing discoveries of new reptile genera (Moravec et al. 2018; Lehr et al. 2019, 2020), which raises ques- tions about the number of still undescribed species in the country. For example, Moravec et al.´s (2018) work on evolsyst.pensoft.net 10 Robert C. Jadin et al.: New Peruvian vine snake and redescription of O. acuminatus References Bagley JC, Johnson JB (2014) Phylogeography and biogeography of the lower Central American Neotropics: diversification between two continents and between two seas. Biological Reviews 89: 767–790. https://doi.org/10.1111/brv.12076 Barbour T, Amaral A do (1926) A new North American snake. Proceed- ings of the New England Zoological Club 9: 79–81. Bell T (1825) On Leptophina, a group of serpents comprising the ge- nus Dryinus of Merrem, and a newly formed genus to be named Leptophis. Zoological Journal, Zoological Society of London 2: 322–329. Bogert CM, Oliver JA (1945) A preliminary analysis of the herpetofau- na of Sonora. Bulletin of the American Museum of Natural History 83: 297–426. Acknowledgements 2017), and were not a deterrent to dispersal from west to east. In congruence, Oxybelis species are widespread and found at high elevations in mountainous regions, suggesting that mountain topog- raphy should not impose geographical barriers. In addi- tion, the presence of trans-Andean Oxybelis is intriguing, which again indicates that Oxybelis species are efficient at crossing high altitude barriers. In favor of this scenario, Rojas-Morales (2012) has provided the example of a for- est-dwelling dipsadid snake in the genus Rhinobothryum that crossed the Andes from west to east and speciated in the Amazon basin. evolsyst.pensoft.net Conservation Böhm M, Collen B, Baillie JE, Bowles P, Chanson J, Cox N, Ham- merson G, Hoffmann M, Livingstone SR, Ram M, Rhodin AG. et al. (2013) The conservation status of the world’s reptiles. Bio- logical Conservation 157: 372–85. https://doi.org/10.1016/j.bio- con.2012.07.015 Approximately 12% of snakes are estimated to be threat- ened with extinction (Böhm et al. 2013). However, this is likely a considerable underestimate as it is well known that detecting snakes for scientific study is incredibly difficult due to their secretive habits and crypticity, re- sulting in many, if not most, as Data Deficient. When we initiated this project (see Jadin et al. 2019, 2020), the ac- cepted hypothesis was that Oxybelis aeneus was a single, widespread species that was “well known” in museum collections and also understood from a few scattered field studies (i.e. Henderson 1974; Van Devender et al. 1994; Mesquita et al. 2012). With our addition of molecular and morphological analyses we revealed that this “species” is at least eight distinct species and while we recognize their existence, they likely are all Data Deficient. Thus, the number of Data Deficient species grows faster than the number of species that can be classified as a species of Least Concern or Vulnerable. Boulenger GA (1896) Catalogue of the snakes in the British Muse- um (Natural History). British Museum (Natural History), Vol. 3. London. Card DC, Schield C, Shield DR, Richard AH, Corbin AB, Perry BW, Audra AL, Pasquesi GIM, Smith EN, Jezkova T, Scott BM, Warren B, Castoe TA (2016) Phylogeographic and population genetic anal- yses reveal multiple species of Boa and independent origins of insu- lar dwarfism. Molecular Phylogenetics and Evolution 102: 104–116. https://doi.org/10.1016/j.ympev.2016.05.034 Cope ED (1862) Catalogues of the reptiles obtained during the explo- rations of the Parana, Paraguay, Vermejo and Uraguay Rivers, by Capt. Thos. J., Page, U. S. N., and of those procured by Lieut. N. Michler, U. S. Top. Eng., Commander of the Expedition Conducting the Survey of the Atrato River. Proceedings of the Academy of Nat- ural Sciences of Philadelphia 14: 346–359. evolsyst.pensoft.net Evolutionary Systematics 5 2021, 1–12 11 isms, Diversity, and Evolution 20: 723–746. https://doi.org/10.1007/ s13127-020-00461-0 Dalman J (1823) Analecta entomologica. Stockholm. https://doi. org/10.5962/bhl.title.66069 Javadi HR, Foroutan M, Ashtiani ME, Urbina JA, Saidi A, Faridi M (2011) Tectonics changes in NW South American Plate and their ef- fect on the movement pattern of the Boconó Fault System during the Mérida Andes evolution. Conservation Murphy JC, Angarita Sierra T, Downie JR, Jowers MJ (2017) Toads, tall mountains and taxonomy: the Rhinella granulosa group (Am- phibia: Anura: Bufonidae) on both sides of the Andes. Salamandra 53: 267–278. Gregory-Wodzicki KM (2000) Uplift history of the Central and North- ern Andes: a review. Geological Society of America Bulletin 112: 1091–1105. https://doi.org/10.1130/0016-7606(2000)112%3C1091: UHOTCA%3E2.0.CO;2 Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 403: 853–858. https://doi.org/10.1038/35002501 Green HW (1997) Snakes, the evolution of mystery in nature. Universi- ty of California Press, Los Angles. Orlofske SA, Hedman HD, Koechlin JE, Jadin RC (2012) Herpetologi- cal ecotourism and conservation. IRCF Reptiles & Amphibians 19: 254–262. Günther A (1858) Catalogue of Colubrine Snakes of the British Muse- um. British Museum (Natural History), XVI, London. Peters JA (1964) Dictionary of herpetology: a brief and meaningful defi- nition of words and terms used in herpetology. Hafner, New York. Hamdan B, Pereira AG, Loss-Oliveira L, Rödder D, Schrago CG (2017) Evolutionary analysis of Chironius snakes unveils cryptic diversity and provides clues to diversification in the Neotropics. Molecular Phylogenetics and Evolution 116: 108–119. https://doi. org/10.1016/j.ympev.2017.08.004 Reynolds RG, Henderson RW (2018) Boas of the World (superfamily Booidae): A checklist with systematic, taxonomic, and conservation assessments. Bulletin of the Museum of Comparative Zoology 162: 1–58. https://doi.org/10.3099/MCZ48.1 Henderson RW (1974) Aspects of the ecology of the Neotropical vine snake, Oxybelis aeneus (Wagler). Herpetologica 1: 19–24. Rojas-Morales JA (2012) On the geographic distribution of the false coral snake, Rhinobothryum bovallii (Serpentes: Dipsadidae), in Co- lombia – a biogeographical perspective. Salamandra 48: 243–248. Jadin RC, Townsend JH, Castoe TA, Campbell JA (2012) Cryptic diversity in disjunct populations of Middle American Montane Pitvipers: a systematic reassessment of Cerrophidion godmani. Zoologica Scripta 41: 455–470. https://doi.org/10.1111/j.1463- 6409.2012.00547.x Sabaj MH (2019) Standard symbolic codes for institutional resource collections in herpetology and ichthyology: An Online Reference. Version 7.1 American Society of Ichthyologists and Herpetologists, Washington. http://www.asih.org [21 March 2019] Jadin RC, Blair C, Jowers MJ, Carmona A, Murphy JC (2019) Hiding in the lianas of the tree of life: Molecular phylogenetics and species de- limitation reveal considerable cryptic diversity of New World Vine Snakes. Molecular Phylogenetics and Evolution 134: 61–65. https:// doi.org/10.1016/j.ympev.2019.01.022 Washington. http://www.asih.org [21 March 2019] Schlegel H (1837) Essai sur la physionomie des serpents. La Haye: J. Kips, J. Hz. et W.P. Van Stockum (text). [Vol. 1] Partie generale, xx- viii, 251 pp. [Vol. Conservation Journal of South American Earth Sciences, 32: 14–29. https://doi.org/10.1016/j.jsames.2011.04.008 Daza JM, Smith EN, Páez VP, Parkinson CL (2009) Complex evolu- tion in the Neotropics: The origin and diversification of the wide- spread genus Leptodeira (Serpentes: Colubridae). Molecular Phy- logenetics and Evolution 53: 653–667. https://doi.org/10.1016/j. ympev.2009.07.022 32: 14–29. https://doi.org/10.1016/j.jsames.2011.04.008 Daza JM, Castoe TA, Parkinson CL (2010) Using regional compara- tive phylogeographic data from snake lineages to infer historical processes in Middle America. Ecography 33: 343–354. https://doi. org/10.1111/j.1600-0587.2010.06281.x Keiser Jr ED (1974) A systematic study of the Neotropical vine snake Oxybelis aeneus (Wagler). Bulletin of the Texas Memorial Museum 22: 1–51. Latreille PA (1804) Tableau méthodique des insectes. In: Société de Naturalistes et d’Agriculteurs (Ed.) Nouveau dictionnaire d’Histoire naturelle 24: 129–200. Dowling HG (1951) A proposed standard system of counting ventral in snakes. British Journal of Herpetology 1: 97–99. https://doi. org/10.2307/1437542 Lehr E, Moravec J, Lundberg M, Köhler G, Catenazzi A, Šmíd J (2019) A new genus and species of arboreal lizard (Gymnophthalmidae: Cer- cosaurinae) from the eastern Andes of Peru. Salamandra 55: 1–13. Duellman WE (2005) Cusco Amazónico: the lives of amphibians and reptiles in an Amazonian rainforest. Ithaca: Cornell University Press. Lehr E, Moravec J, von May R (2020) A new cryptic genus of terrestrial lizard (Gymnophthalmidae: Cercosaurinae) from the eastern Andes of central Peru. Salamandra 56: 1–15. Duméril AMC, Bibron G, Duméril AHA (1854) Erpétologie générale ou histoire naturelle complète des reptiles. Tome septième. Deuxième partie, comprenant l’histoire des serpents venimeux. Paris, Librairie Encyclopédique de Roret. https://doi.org/10.5962/bhl.title.118790 Encyclopédique de Roret. https://doi.org/10.5962/bhl.title.118790 Mesquita PC, Borges-Nojosa DM, Passos DC, Bezerra CH (2012) Ac- tivity patterns of the Brown Vine snake Oxybelis aeneus (Wagler, 1824) (Serpentes, Colubridae) in the Brazilian semiarid. Animal Bi- ology 62: 289–99. https://doi.org/10.1163/157075611X618228 Fitzinger L (1826) Critische Bemerkungen über J. Wagler’s Schlangen- werk. Isis von Oken 19: 881–909. Flores-Villela O, Smith HM, Chiszar D (2004) The history of herpe- tological exploration in Mexico. Bonner Zoologische Beiträge 52: 311–335. Moravec J, Šmíd J, Štundl J, Lehr E (2018) Systematics of Neotrop- ical microteiid lizards (Gymnophthalmidae, Cercosaurinae), with the description of a new genus and species from the Andean mon- tane forests. ZooKeys 774: 105–139. https://doi.org/10.3897/zook- eys.774.25332 Girard C (1854) Report to Lieut. James M. Gillis, U.S.N. upon the reptiles collected during the U.S. Naval astronomical expedition to Chile. Report US Naval. Astronomical Expedition Southern Hemi- sphere. House of Representatives Document 121, 33rd Congress 2: 207–220. Conservation 2] Partie descriptive, 606 pp. [Amsterdam: M.H. Schonekat] https://doi.org/10.5962/bhl.title.4273 Smith HM, Smith RB (1973) Synopsis of the Herpetofauna of Mexico (Vol. 2). An analysis of the literature exclusive of the Mexican axo- lotl. John Johnson, Natural History Books, Bo. Bennington. Jadin RC, Blair C, Orlofske SA, Jowers MJ, Rivas GA, Vitt LJ, Ray JM, Smith EN, Murphy JC (2020) Not withering on the evolution- Jadin RC, Blair C, Orlofske SA, Jowers MJ, Rivas GA, Vitt LJ, Ray JM, Smith EN, Murphy JC (2020) Not withering on the evolution- ary vine: Systematic revision of New World Vine Snakes. Organ- ary vine: Systematic revision of New World Vine Snakes. Organ- evolsyst.pensoft.net Robert C. Jadin et al.: New Peruvian vine snake and redescription of O. acuminatus 12 in Arizona and Sonora, Mexico. Herpetological Natural History 2: 25–42. in Arizona and Sonora, Mexico. Herpetological Natural History 2: 25–42. Spix JB von (1824) Serpentum brasiliensium species novae ou histoire na- turelle des espèces nouvelles de serpens, recueillies et observées pen- dant le voyage dans l’intérieur du Brésil dans les années 1817, 1818, 1819, 1820, exécuté par ordre de sa majesté le Roi de Bavi Typis Franc. Seraph. Hübschmanni, Monachii. https://doi.org/10.5962/bhl.title.4269 Wagler JG (1824) Anonymous. Serpentum brasiliensium species novae. Isis von Oken 10: 1097–1098. Wagler JG (1830) Naturliches System der Amphibien, mit vorangehender Classification der Säugethiere und Vögel. J. G. Cotta; München, Stuttgart, Tübingen. https://doi.org/10.5962/bhl.title.58730 Stevens M, Ruxron GD (2014) Do animal eyespots really mimic eyes? Current Zoology 60: 26–36. https://doi.org/10.1093/czoolo/60.1.26 Stuttgart, Tübingen. https://doi.org/10.5962/bhl.title.58730 Wied M zu (1824) In Anon. Verzeichnis der Amphibien, welche im zweyten Bande der Naturgeschichte Brasiliens von Prinz Max von Neuwied werden beschreiben werden. Isis von Oken 6: 661–673. Taylor EH (1941) Herpetology Miscellany, No. II. University of Kansas Science Bulletin 27: 105–132. Uetz P, Freed P, Hošek J [Eds] (2020) The Reptile Database. http:// www.reptile-database.org [October 1, 2020] Wied M zu (1825) Beitrage zur Naturgeschichte von Brasilien (Vol. 1). Van Devender TR, Lowe CH, Lawler HE (1994) Factors influencing the distribution of the neotropical vine snake (Oxybelis aeneus) Van Devender TR, Lowe CH, Lawler HE (1994) Factors influencing the distribution of the neotropical vine snake (Oxybelis aeneus) Weimar Gr. H. S. private. Landes-Industrie-Comptoirs (1825–1833). Volume 1, 614 pp. https://doi.org/10.5962/bhl.title.48512 Museum acronyms follow Sabaj (2019). Museum acronyms follow Sabaj (2019). Oxybelis aeneus – (n = 8) Brazil: FMNH 64417 Ama- zonas; FMNH 19203 Pará; KU R-124605, 124606, 140173, MCZ R-2582, 2778, and 53211 Pará. O. brevirostris – (n = 2) Ecuador: UTA R-55952-53 Can- ton San Lorenzo: Parroquia Santa Rita, Esmeraldas. O. inkaterra – (n = 6) Peru: FMNH 40085, Madre de Dios; FMNH 56141, Loreto, Rio Ucayali: Yarinacocha; KU R-214887 & R-220196 Madre de Dios, Cuzco Ama- zonico, 15 km E Puerto Maldanado; ZMH R01702 & R01611, Huánuco, Panguana Biological Station, Rio Yuyapichis [= Rio Llullapichis], Pachitea. O. potosiensis – (n = 6) Mexico: UIMNH 25069 San Luis Potosí; UTA R-6107–10, 8752, and 12,368 S of Zapo- titl, Puebla; UTA R-9014 6.0 mi E San Rafael, road to Rancho Nuevo, Tamaulipas. y p p O. koehleri – (n = 34) Costa Rica: FMNH 179061 Cartago, Turrialba; El Salvador: FMNH 10997 Chalatenango; San Jose del Sacare, 3600′; FMNH 10998 Morazán, Divisa- dero; FMNH 64955, La Libertad, Volcan San Salvador, 1917 Lava, 500 m; FMNH 64956 La Paz, Los Blancos; KU 289907 Usulutan: Isla San Sebastian; Guatemala: FMNH 20088 Izabal: Bobos Plantation, near Playitas; FMNH 20171 and 20418 Sololá: Olas de Moca; UTA R-46795 Chiguimula; UTA R-45880 Huehuetenango; UTA R-22182–83, 33,040, 33,042, 37,256, 39,236, 42,433 Izabal; UTA R-37258 Peten; UTA R-46846 Za- capa, El Arenal; Honduras: FMNH 22231 Tela; FMNH 27050 San Pedro Sula; FMNH 34565, 34571, 34574, 34576, Bay Islands: Roatan, near Coxen Hole; UTA R-55231 Bay Islands: Roatan; FMNH 34770 Yoro, Portillo Grande; FMNH 40872 Gracias; UTA R-46865 Comayagua, Playitos: Aldea “Lo de Reina,” 785 m; UTA R-53176–78 Honduras: Gracias a Dios, Mocorón, 30–50 m. Nicaragua: UTA R-44838 Jinotega, El Paraíso Km 152.5, carretera Jinotega-Matagalpa, 1490 m. O. microphthalmus – (n = 36) USA: Arizona: UAZ 47314 O. rutherfordi – (n = 20) Tobago: FMNH 251213 Bloody Bay Rd., between Roxborough and Bloody Bay; Trini- dad: FMNH 49973 no specific locality; FMNH 49974– 75 Brickfield; FMNH 49976 Mount Harris, FMNH 49977–85 San Rafael; FMNH 215838 circa 3 miles S Simla-Quarry Rd., on Arima-Blanchisseuse Rd., egg farm; FMNH 215839 circa 2 miles S Simla-Quarry Rd., on Arima-Blanchisseuse Rd.; UTA R-64851 Ari- ma Valley, William Beebe Tropical Research Centre, c. 6 km N Arima, 247 m; Venezuela: FMNH 17839–40 Puerto Viejo, Península de Paria, Sucre; MBLUZ 1268 between San Francisco de Macanao and Cerro Los Ce- dros, Isla de Margarita, Nueva Esparta. O. Specimens examined east Sycamore Canyon, Ruby Rd.; UAZ 39544 Patago- nia Mts.; Santa Cruz County: ASU 33314, ASU 33364, ASU 35069, ASU 35563, UAZ 16787, UAZ 39545; no specific locality: UMMZ 75779. Mexico: Colima: UTA R-57658; Guerrero UAZ 106056, 106058, 38448, 38451, 38455, 38461, 38467, 106051, 106057, 106059, 106054; Oaxaca: UAZ 106055, 117841–43, 178707, 178708; So- nora: UAZ 26972 0.5 miles West Alamos; UAZ 28279 8.8 miles east Alamos; Alamos UAZ 16797, UAZ 26973, ASU 06735, ASU 68990, ASU 88990; 35 miles east of Cannansa junction w/ Aqua Prieta Rd. UAZ 16796. O. microphthalmus – (n = 36) USA: Arizona: UAZ 47314 2.8 mi west of Sycamore Canyon; UAZ 519,225 miles Museum acronyms follow Sabaj (2019). 34576, Bay Islands: Roatan, near Coxen Hole; UTA R-55231 Bay Islands: Roatan; FMNH 34770 Yoro, Portillo Grande; FMNH 40872 Gracias; UTA R-46865 Comayagua, Playitos: Aldea “Lo de Reina,” 785 m; UTA R-53176–78 Honduras: Gracias a Dios, Mocorón, 30–50 m. Nicaragua: UTA R-44838 Jinotega, El Paraíso Km 152.5, carretera Jinotega-Matagalpa, 1490 m. O. vittatus – (n = 16) Panama: FMNH 152067 Almirante; FMNH 83552, 130674, 131314 Canal Zone: Summit; FMNH 161478 Canal Zone: Barro Colorado Island; FMNH 153665 Coiba Island; FMNH 170132 San Blas Territory: Soskantupu, 8°57'N, 77°44'W, 1 m; FMNH 154043 Bocas del Toro, 11 km NW Almirante 600 ft.; FMNH 154478, 154517 no locality data; MCZ R-22274, 22231, and 25118 Canal Zone; UF 65037, 65038, and 170469 Canal Zone. O. microphthalmus – (n = 36) USA: Arizona: UAZ 47314 2.8 mi west of Sycamore Canyon; UAZ 519,225 miles evolsyst.pensoft.net
https://openalex.org/W2321741189	https://dash.harvard.edu/bitstream/1/26860089/1/4816300.pdf	English	null	LpMab-12 Established by CasMab Technology Specifically Detects Sialylated O-Glycan on Thr52 of Platelet Aggregation-Stimulating Domain of Human Podoplanin	PloS one	2,016	public-domain	6,855	Permanent link http://nrs.harvard.edu/urn-3:HUL.InstRepos:26860089 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA Published Version doi:10.1371/journal.pone.0152912 Published Version doi:10.1371/journal.pone.0152912 Citation Kato, Yukinari, Satoshi Ogasawara, Hiroharu Oki, Polina Goichberg, Ryusuke Honma, Yuki Fujii, and Mika K. Kaneko. 2016. “LpMab-12 Established by CasMab Technology Specifically Detects Sialylated O-Glycan on Thr52 of Platelet Aggregation-Stimulating Domain of Human Podoplanin.” PLoS ONE 11 (3): e0152912. doi:10.1371/journal.pone.0152912. http:// dx.doi.org/10.1371/journal.pone.0152912. Share Your Story The Harvard community has made this article openly available. Please share how this access benefits you. Submit a story . The Harvard community has made this article openly available. Please share how this access benefits you. Submit a story . Accessibility RESEARCH ARTICLE OPEN ACCESS Citation: Kato Y, Ogasawara S, Oki H, Goichberg P, Honma R, Fujii Y, et al. (2016) LpMab-12 Established by CasMab Technology Specifically Detects Sialylated O-Glycan on Thr52 of Platelet Aggregation-Stimulating Domain of Human Podoplanin. PLoS ONE 11(3): e0152912. doi:10.1371/journal.pone.0152912 Editor: Yves St-Pierre, INRS, CANADA Received: January 7, 2016 Accepted: March 21, 2016 Published: March 31, 2016 Citation: Kato Y, Ogasawara S, Oki H, Goichberg P, Honma R, Fujii Y, et al. (2016) LpMab-12 Established by CasMab Technology Specifically Detects Sialylated O-Glycan on Thr52 of Platelet Aggregation-Stimulating Domain of Human Podoplanin. PLoS ONE 11(3): e0152912. doi:10.1371/journal.pone.0152912 Editor: Yves St-Pierre, INRS, CANADA Received: January 7, 2016 Accepted: March 21, 2016 Published: March 31, 2016 Podoplanin (PDPN), also known as Aggrus, possesses three tandem repeat of platelet aggregation-stimulating (PLAG) domains in its N-terminus. Among the PLAG domains, sia- lylated O-glycan on Thr52 of PLAG3 is essential for the binding to C-type lectin-like recep- tor-2 (CLEC-2) and the platelet-aggregating activity of human PDPN (hPDPN). Although various anti-hPDPN monoclonal antibodies (mAbs) have been generated, no specific mAb has been reported to target the epitope containing glycosylated Thr52. We recently estab- lished CasMab technology to develop mAbs against glycosylated membrane proteins. Herein, we report the development of a novel anti-glycopeptide mAb (GpMab), LpMab-12. LpMab-12 detected endogenous hPDPN by flow cytometry. Immunohistochemical analy- ses also showed that hPDPN-expressing lymphatic endothelial and cancer cells were clearly labeled by LpMab-12. The minimal epitope of LpMab-12 was identified as Asp49– Pro53 of hPDPN. Furthermore, LpMab-12 reacted with the synthetic glycopeptide of hPDPN, corresponding to 38–54 amino acids (hpp3854: 38-EGGVAMPGAEDDVVTPG-54), which carries α2–6 sialylated N-acetyl-D-galactosamine (GalNAc) on Thr52. LpMab-12 did not recognize non-sialylated GalNAc-attached glycopeptide, indicating that sialylated Gal- NAc on Thr52 is necessary for the binding of LpMab-12 to hPDPN. Thus, LpMab-12 could serve as a new diagnostic tool for determining whether hPDPN possesses the sialylation on Thr52, a site-specific post-translational modification critical for the hPDPN association with CLEC-2. Citation: Kato Y, Ogasawara S, Oki H, Goichberg P, Honma R, Fujii Y, et al. (2016) LpMab-12 Established by CasMab Technology Specifically Detects Sialylated O-Glycan on Thr52 of Platelet Aggregation-Stimulating Domain of Human Podoplanin. PLoS ONE 11(3): e0152912. Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Funding: This work was supported in part by the Regional Innovation Strategy Support Program from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan (Y.K.); by the Platform for Drug Discovery, Informatics, and Structural Life Science (PDIS) from Japan Agency for Medical Research and development, AMED (Y.K.); by the Basic Science and Platform Technology Program for Innovative Biological Medicine from AMED (Y.K.); by Japan Society for the Promotion of Science LpMab-12 Established by CasMab Technology Specifically Detects Sialylated O- Glycan on Thr52 of Platelet Aggregation- Stimulating Domain of Human Podoplanin Yukinari Kato1, Satoshi Ogasawara1, Hiroharu Oki1, Polina Goichberg2, Ryusuke Honma1, Yuki Fujii1, Mika K. Kaneko1 a1111 1 Department of Regional Innovation, Tohoku University Graduate School of Medicine, 2–1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980–8575, Japan, 2 Department of Anesthesia, Brigham and Women’s Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, United States of America yukinari-k@bea.hi-ho.ne.jp * yukinari-k@bea.hi-ho.ne.jp OPEN ACCESS doi:10.1371/journal.pone.0152912 Editor: Yves St-Pierre, INRS, CANADA Received: January 7, 2016 Accepted: March 21, 2016 Published: March 31, 2016 Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Monoclonal Antibody against Thr52 of Human Podoplanin cancer, malignant brain tumors, mesotheliomas, testicular tumors, and osteosarcoma [3–13], but also in normal cells such as lymphatic endothelial cells and podocytes [14,15]. PDPN is also abundant in lung type I alveolar cells where it is called "T1α" [16]. We previously named PDPN as "Aggrus" because PDPN possesses a platelet aggregation-inducing activity, which is associated with cancer metastasis [3]. Further, PDPN is known as a specific lymphatic endothe- lial marker [17], and PDPN-CLEC-2 signaling leads to platelet aggregation, which is critical for the embryonic blood-lymphatic vascular separation [18]. (JSPS) KAKENHI Grant Number Grant Number 25462242 (Y.K.) and 26440019 (M.K.K.); by Takeda Science Foundation (S.O.); and by the Grant-in-Aid from the American Heart Association (P.G.). Competing Interests: The authors have declared that no competing interests exist. Abbreviations: mAb, monoclonal antibody; PLAG, platelet aggregation-stimulating; GalNAc, N-acetyl-D- galactosamine; GpMab, anti-glycopeptide mAb; CLEC-2, C-type lectin-like receptor-2; LEC, lymphatic endothelial cell. Interaction of human PDPN (hPDPN) with CLEC-2 mainly involves Glu47 and Asp48 in the platelet aggregation-stimulating domain-3 (PLAG3) and the α2–6 linked sialic acid residue [19]. The sequence motif is conserved among PDPNs of various species [20]. CLEC-2 has a rec- ognition motif in the form ‘‘EDXXXT/S,” where X is any amino acid, and T (or S) contains dis- ialyl-core 1 [21]. In our previous studies, we established that the glycosylation on Thr52 is critical for the binding of hPDPN to CLEC-2, and the sialylated O-glycan on Thr52 is required for the platelet aggregating activity of hPDPN [3,21]. Therefore, the detection of site-specific glycosylation on Thr52 is important for determining whether in given pathophysiological con- ditions, hPDPN is prone to the CLEC-2 binding and has the potential to cause platelet aggregation. Here, we describe the development and characterization of a new anti-hPDPN mAb, LpMab-12, which specifically binds to glycosylated Thr52, and might serve as a novel modality to study hPDPN-CLEC-2 interaction. Introduction Podoplanin (PDPN), the endogenous ligand of C-type lectin-like receptor-2 (CLEC-2) [1,2], is highly expressed not only in various tumors including oral cancer, lung cancer, esophageal 1 / 13 PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 Abbreviations: mAb, monoclonal antibody; PLAG, platelet aggregation-stimulating; GalNAc, N-acetyl-D- galactosamine; GpMab, anti-glycopeptide mAb; CLEC-2, C-type lectin-like receptor-2; LEC, lymphatic endothelial cell. PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 Cell lines, animals, and tissues Chinese hamster ovary (CHO)-K1, LN229, HEK-293T, COS-7, and P3U1 were obtained from the American Type Culture Collection (ATCC, Manassas, VA). Human lymphatic endothelial cell (LEC) was purchased from Cambrex (Walkersville, MD). The human glioblastoma cell line, LN319, was donated by Dr. Kazuhiko Mishima (Saitama Medical University, Saitama, Japan). LN229 was transfected with human PDPN plasmids (LN229/hPDPN) using Lipofecta- mine 2000 (Thermo Fisher Scientific Inc., Waltham, MA) according to the manufacturer’s instructions [22]. LN319/hPDPN-knock out (KO) cells (PDIS-6), HEK-293T/hPDPN-KO cells (PDIS-2), and COS-7/hPDPN-KO cells (PDIS-4) were produced by transfecting CRISPR/Cas plasmids, which targets hPDPN (Sigma-Aldrich Corp., St. Louis, MO), using a Gene Pulser Xcell electroporation system (Bio-Rad Laboratories Inc., Philadelphia, PA). The amplified hPDPN cDNA was subcloned into a pcDNA3 vector (Thermo Fisher Scientific Inc.) and a FLAG epitope tag was added at the C-terminus. Substitution of amino acids to alanine in hPDPN was performed using a QuikChange Lightning site-directed mutagenesis kit (Agilent Technologies Inc., Santa Clara, CA). CHO-K1 cells were transfected with the plasmids using a Gene Pulser Xcell electroporation system (Bio-Rad Laboratories Inc.). P3U1 and CHO-K1 cell lines, and their counterparts transfected with hPDPN were cultured in L-glutamine-containing RPMI 1640 medium (Nacalai Tesque, Inc., Kyoto, Japan), and LN229, LN319, HEK-293T, COS-7 cell lines and their transfected counterparts were cultured in L-glutamine-containing Dulbecco’s Modified Eagle’s Medium (DMEM) medium (Nacalai Tesque, Inc.), supplemented with 10% heat-inactivated fetal bovine serum (FBS; Thermo Fisher Scientific Inc.) at 37°C in a humidified atmosphere of 5% CO2 and 95% air. LEC was cultured in endothelial cell medium EGM-2MV supplemented with 5% FBS (Cambrex Corp.). Antibiotics including 100 units/ml of penicillin, 100 μg/ml of streptomycin, and 25 μg/ml of amphotericin B (Nacalai Tesque, Inc.) were added to all media. COS-7 cell lines and their transfected counterparts were cultured in L-glutamine-containing Dulbecco’s Modified Eagle’s Medium (DMEM) medium (Nacalai Tesque, Inc.), supplemented with 10% heat-inactivated fetal bovine serum (FBS; Thermo Fisher Scientific Inc.) at 37°C in a humidified atmosphere of 5% CO2 and 95% air. LEC was cultured in endothelial cell medium EGM-2MV supplemented with 5% FBS (Cambrex Corp.). Antibiotics including 100 units/ml of penicillin, 100 μg/ml of streptomycin, and 25 μg/ml of amphotericin B (Nacalai Tesque, Inc.) were added to all media. 2 / 13 PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 Monoclonal Antibody against Thr52 of Human Podoplanin Three female BALB/c mice (four-weeks old) were purchased from CLEA Japan (Tokyo, Japan). Hybridoma production Three BALB/c mice were immunized by intraperitoneal (i.p.) injection of 1 × 108 LN229/ hPDPN cells together with Imject Alum (Thermo Fisher Scientific Inc.), as previously described [22]. After several additional immunizations, a booster injection was given i.p. two days before mice were euthanized by cervical dislocation and spleen cells were harvested. The spleen cells were fused with P3U1 cells using PEG1500 (Roche Diagnostics, Indianapolis, IN). The fused cells were grown in RPMI medium with hypoxanthine, aminopterin, and thymidine selection medium supplement (Thermo Fisher Scientific Inc.). The culture supernatants were screened using enzyme-linked immunosorbent assay (ELISA) for binding to recombinant hPDPN purified from LN229/hPDPN cells. Enzyme-linked immunosorbent assay (ELISA) Recombinant hPDPN or glycopeptides were immobilized on Nunc Maxisorp 96-well immuno- plates (Thermo Fisher Scientific Inc.) at a concentration of 1 μg/ml for 30 min. After blocking with 1% BSA in 0.05% Tween20/phosphate buffered saline (PBS, Nacalai Tesque, Inc.), the plates were incubated with culture supernatant followed by 1:1000 diluted peroxidase-conju- gated anti-mouse IgG or anti-rat IgG (Dako; Agilent Technologies, Inc., Glostrup, Denmark). The enzymatic reaction was conducted with a 1-Step Ultra TMB-ELISA (Thermo Fisher Scien- tific Inc.). The optical density was measured at 655 nm using an iMark microplate reader (Bio- Rad Laboratories Inc.). Cell lines, animals, and tissues Animals were housed under pathogen-free conditions. "The Animal Care and Use Committee of Tohoku University" approved the animal experiments described herein. The use of one oral cancer tissue was reviewed and approved by "Tokyo Medical and Dental Uni- versity Institutional Review Board" [23]. Written informed consent was obtained for the human cancer tissue samples used in this study. The use of human heart tissue sections for immunohistochemical analysis was reviewed and approved by the "Partners Institutional Review Board". Western blot analyses Cell lysates (10 μg) were boiled in sodium dodecyl sulfate (SDS) sample buffer (Nacalai Tes- que, Inc.). The proteins were electrophoresed on 5–20% polyacrylamide gels (Wako Pure Chemical Industries Ltd.) and were transferred onto a PVDF membrane (EMD Millipore Corp., Billerica, MA). After blocking with 4% skim milk (Nacalai Tesque, Inc.) in 0.05% Tween20/PBS, the membrane was incubated with 1 μg/ml of LpMab-12, LpMab-7, 1E6 (anti-FLAG; Wako Pure Chemical Industries Ltd.), RcMab-3 (anti-IDH1) [24], or AC-15 (anti-β-actin; Sigma-Aldrich Corp.) and then with peroxidase-conjugated anti-mouse IgG (1:1000 diluted; Dako), and developed with the ImmunoStar LD Chemiluminescence Reagent (Wako Pure Chemical Industries Ltd.) using a Sayaca-Imager (DRC Co. Ltd., Tokyo, Japan). Determination of the apparent binding affinity using flow cytometry LN319 (2 × 105 cells) and LEC (1 × 105 cells) were resuspended in 100 μl of serially diluted LpMab-12 (0.061–100 μg/ml) followed by Oregon Green 488 goat anti-mouse IgG (Thermo Fisher Scientific Inc.). Fluorescence data were collected using a cell analyzer (EC800; Sony Corp.). The apparent dissociation constants (KD) were obtained by fitting the binding iso- therms using the built-in one-site binding models in GraphPad PRISM 6 (GraphPad software, Inc., La Jolla, CA). Immunohistochemical analyses of oral cancer Four-μm-thick histologic sections were deparaffinized in xylene and rehydrated. Without anti- gen retrieval procedure, sections were incubated with 1 μg/ml of LpMab-12 or LpMab-7 for 1 h at room temperature followed by treatment with Envision+ kit (Dako) for 30 min. Color was developed using 3, 3-diaminobenzidine tetrahydrochloride (DAB; Dako), and then the sections were counterstained with hematoxylin (Wako Pure Chemical Industries Ltd.). Immunohistochemical analysis of human heart tissues Four-μm-thick histologic sections of the myocardium were deparaffinized in xylene, rehy- drated, and subjected to 10 min heat-induced antigen retrieval in citric buffer (pH 6.0). Sam- ples were blocked in 10% normal donkey serum (Jackson ImmunoResearch Inc., West Grove, PA) for 30 min at room temperature, incubated with 10 μg/ml of LpMab-12 overnight at 4°C, and then with Alexa Fluor 568-conjugated donkey anti-mouse IgG (Thermo Fisher Scientific Inc.) for 1 h at 37°C. Subsequently, the sections were incubated with goat anti-human LYVE-1 (10 μg/ml; R&D Systems, Inc., Minneapolis, MN) and mouse anti-α-sarcomeric actin (α-SA) (1:200 diluted; Sigma-Aldrich Corp.) for 2 h at 37°C, followed by fluorescein isothiocyanate (FITC)-conjugated donkey anti-goat IgG and Alexa Fluor 647-conjugated donkey anti-mouse IgM (15 μg/ml each; Jackson ImmunoResearch Inc.) and 4',6-diamidino-2-phenylindole dihy- drochloride (DAPI) (1 μg/ml; Sigma-Aldrich Corp.) for 1 h at 37°C. The sections were then treated with 1% solution of Sudan Black B (Sigma-Aldrich Corp.) for 30 min at room tempera- ture, and mounted in Vectashield medium (Vector Laboratories, Inc., Road Burlingame, CA). Images were acquired with Olympus FluoView FV100 laser scanning confocal microscope equipped with CCD camera (Bio-Rad Laboratories Inc.). Flow cytometry Cell lines were harvested by brief exposure to 0.25% Trypsin/1 mM EDTA (Nacalai Tesque, Inc.). After washing with PBS, the cells were incubated with LpMab-12 (1 μg/ml) for 30 min at 4°C, followed by the incubation with Oregon Green 488 goat anti-mouse IgG (Thermo Fisher 3 / 13 PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 Monoclonal Antibody against Thr52 of Human Podoplanin Scientific Inc.). Fluorescence data were collected using a Cell Analyzer EC800 (Sony Corp., Tokyo, Japan). Production of hPDPN glycopeptide The hPDPN glycopeptide (hpp3854) with a GalNAc residue was purchased from Peptide Insti- tute (Osaka, Japan), and used as an acceptor substrate. For synthesis of the sialylated GalNAc on hpp3854, 25 mM HEPES (pH 7.0) containing 30 μM of acceptor substrate, 10 mM MnCl2 (Nacalai Tesque, Inc.), and 250 μM CMP-Neu5Ac (Sigma-Aldrich Corp.) was used. A half vol- ume of purified ST6GalNAcT-I enzyme was added to the reaction mixture and incubated at 37°C for 24 h. The recombinant ST6GalNAcT-I enzyme was bound to anti-FLAG M2 affinity gel (Sigma-Aldrich Corp.). After enzymatic reaction, the resin was removed by filtration using an Ultrafree-MC column (EMD-Millipore). Then, the glycopeptides were purified using a reversed-phase SPE cartridge (ZipTip C18; EMD-Millipore). The other glycopeptides were produced sequentially as previously described [2]. 4 / 13 PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 Monoclonal Antibody against Thr52 of Human Podoplanin Establishment and characterization of a novel anti-hPDPN mAb LpMab- 12 We immunized mice with hPDPN-expressing LN229 glioma cells (LN229/hPDPN), which possess cancer-type glycan patterns including highly sulfated polylactosamine and aberrant sialylation [22]. Spleen cells were harvested and fused with P3U1 cells. Selection of hybridoma was performed using ELISA and flow cytometry, and a novel anti-hPDPN LpMab-12 mAb (mouse IgG1, kappa) was developed. Fig 1A shows that LpMab-12 reacted with LN229/hPDPN and endogenous PDPN (HEK-293T, LN319, COS-7), and did not react with LN229 and PDPN-KO cells (HEK-293T/hPDPN-KO, LN319/hPDPN-KO, COS-7/hPDPN-KO), indicat- ing that LpMab-12 reliably detects hPDPN by immunohistochemistry. As shown in Fig 1B and 1C, lymphatic endothelial cells, identified by a lymphatic marker lymphatic vessel endothelial hyaluronan receptor-1 (LYVE-1), were clearly stained by LpMab- 12 in myocardial samples from human hearts, indicating that LpMab-12 is applicable for reli- ably detecting hPDPN by immunohistochemistry. Using flow cytometry analysis, apparent dissociation constant of LpMab-12 was determined to be 1.2 × 10−8 M for LN319 and 1.8 × 10−8 M for LEC, suggesting that the binding affinity of LpMab-12 is comparable with previously established anti-hPDPN mAbs [22] for hPDPN- expressing cancer cells and normal cells (Fig 1D). To confirm the utility of LpMab-12 for immunolabeling of tissues, we compared the reactiv- ity of LpMab-12 with LpMab-7, the most sensitive anti-hPDPN mAb for this type of analysis [29]. Both LpMab-12 (Fig 2A and 2B) and LpMab-7 (Fig 2E and 2F) strongly stained tumor cells in a membranous/cytoplasmic-staining pattern. Lymphatic vessels were immunolabeled clearly without background by LpMab-12 (Fig 2C and 2D) and LpMab-7 (Fig 2G and 2H). Blood vessels were not stained by both mAbs (Fig 2C, 2D, 2G and 2H). Assessment of antibody-mediated inhibition of hPDPN binding to hCLEC-2 Inhibition assays were performed by ELISA. The recombinant proteins of hPDPN-Fc [2] and hCLEC-2-Fc [19] were produced in our previous studies. The hPDPN-Fc was immobilized on Nunc Maxisorp 96-well immunoplates (Thermo Fisher Scientific Inc.) at 1 μg/ml for 30 min. After blocking with SuperBlock T20 (PBS) Blocking Buffer, LpMab-2 [22], LpMab-3 [25], LpMab-9 [26], LpMab-12, LpMab-3 + LpMab-12, or isotype control (PMab-32) [27,28] were added at 10 μg/ml for 30 min. The plates were incubated with biotinylated hCLEC-2-Fc (1 μg/ ml) followed by 1/1000 diluted peroxidase-conjugated streptavidin (GE Healthcare, Piscat- away, NJ). The enzymatic reaction was conducted with a 1-Step Ultra TMB-ELISA (Thermo Fisher Scientific Inc.). The optical density was measured at 655 nm using an iMark microplate reader (Bio-Rad Laboratories Inc.). All data were shown as means ± SD. Statistical analysis by one-way ANOVA was performed using GraphPad Prism 6 (GraphPad Software Inc., La Jolla, CA). Epitope mapping To determine the critical epitope for the LpMab-12 interaction with hPDPN, we compared the mAb binding to the hPDPN carrying different point mutations. Using Western blot, we found that LpMab-12 did not detect protein sequences with the following amino acid substitutions: D49A, V51A, T52A, and P53A (Fig 3A). 5 / 13 PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 Monoclonal Antibody against Thr52 of Human Podoplanin Fig 1. Characterization of an anti-hPDPN mAb LpMab-12. (A) Flow cytometry assessment of LpMab-12 binding to LN229/hPDPN and LN229 cells, endogenous hPDPN-expressing (HEK-293T, LN319, COS-7), and hPDPN-KO cells (HEK-293T/hPDPN-KO, LN319/hPDPN-KO, COS-7/hPDPN-KO). (B, C) Human myocardial samples were indirectly immunolabeled with LpMab-12 (red), the lymphatic endothelial epitope, LYVE-1 (green), and the myocytes were stained with anti-α-sarcomeric actin (α-SA) (grey). Nuclei were counterstained with DAPI (blue). Arrows, lymphatic endothelial cells; arrowheads, vascular endothelial cells of an artery. Scale bars: 100 μm (B) and 20 μm (C). Note the preferential labeling of lymphatic endothelium by LpMab-12. (D) Determination of apparent binding affinity against LN319 and LEC by flow cytometry. The apparent dissociation constants (KD) were obtained by fitting the binding isotherms using the built-in one-site binding models. Fig 1. Characterization of an anti-hPDPN mAb LpMab-12. (A) Flow cytometry assessment of LpMab-12 binding to LN229/hPDPN and LN229 cells, endogenous hPDPN-expressing (HEK-293T, LN319, COS-7), and hPDPN-KO cells (HEK-293T/hPDPN-KO, LN319/hPDPN-KO, COS-7/hPDPN-KO). (B, C) Human myocardial samples were indirectly immunolabeled with LpMab-12 (red), the lymphatic endothelial epitope, LYVE-1 (green), and the myocytes were stained with anti-α-sarcomeric actin (α-SA) (grey). Nuclei were counterstained with DAPI (blue). Arrows, lymphatic endothelial cells; arrowheads, vascular endothelial cells of an artery. Scale bars: 100 μm (B) and 20 μm (C). Note the preferential labeling of lymphatic endothelium by LpMab-12. (D) Determination of apparent binding affinity against LN319 and LEC by flow cytometry. The apparent dissociation constants (KD) were obtained by fitting the binding isotherms using the built-in one-site binding models. Fig 1. Characterization of an anti-hPDPN mAb LpMab-12. (A) Flow cytometry assessment of LpMab-12 doi:10.1371/journal.pone.0152912.g001 doi:10.1371/journal.pone.0152912.g001 In agreement, flow cytometry analysis demonstrated that LpMab-12 did not react with D49A, T52A, and P53A mutant proteins (Fig 3B) Thus, our results indicate that the epitope of LpMab-12 is Asp49-Pro53. In our previous study we established that the sialylated O-glycan on Thr52 is critical for platelet aggregating activity of hPDPN [21]. PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 Epitope mapping Therefore, the data point that the epitope of LpMab-12 contains the sialylated O-glycan on Thr52 in the Asp49-Pro53 sequence of hPDPN. To further clarify the essential epitope of LpMab-12, especially the essential glycan structure detected by LpMab-12, we synthesized several glycopeptides of hPDPN, which include the PLAG2 and PLAG3 domains (Fig 4). Specifically, we generated SAα2-6GalNAc + hpp3854; Gal + GalNAc + hpp3854; SAα2-3Gal + GalNAc + hpp3854; Gal + SAα2-6GalNAc + hpp3854; and SAα2-3Gal + SAα2-6GalNAc + hpp3854. LpMab-12 detected SAα2-6GalNAc + hpp3854, Gal + SAα2-6GalNAc + hpp3854, and SAα2-3Gal + SAα2-6GalNAc + hpp3854 (Table 1). LpMab-9, the epitope of which was identified as residues 25–30 of hPDPN [26], did 6 / 13 PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 Monoclonal Antibody against Thr52 of Human Podoplanin Fig 2. Immunohistochemical analysis of the oral cancer and heart tissue samples using LpMab-12 and LpMab-7. Serial sections of the tissues with oral cancer were incubated with LpMab-12 (A-D) or LpMab- 7 (E-H), followed by the development with the EnVision+ kit and counterstaining with hematoxylin, or the HE staining (I-L). Arrows, lymphatic endothelial cells; arrowheads, vascular endothelial cells. Scale bars: 100 μm. LpMab-12 stains lymphatic vessels with high efficiency, similarly to LpMab-7. doi:10.1371/journal.pone.0152912.g002 Fig 2. Immunohistochemical analysis of the oral cancer and heart tissue samples using LpMab-12 and LpMab-7. Serial sections of the tissues with oral cancer were incubated with LpMab-12 (A-D) or LpMab- 7 (E-H), followed by the development with the EnVision+ kit and counterstaining with hematoxylin, or the HE staining (I-L). Arrows, lymphatic endothelial cells; arrowheads, vascular endothelial cells. Scale bars: 100 μm. LpMab-12 stains lymphatic vessels with high efficiency, similarly to LpMab-7. doi:10.1371/journal.pone.0152912.g002 doi:10.1371/journal.pone.0152912.g002 not react with any glycopeptides of hpp3854. In contrast, LpMab-13 and LpMab-20, which were recently established using CasMab technology [30], recognized all the glycopepties of hpp3854. Collectively, these data indicate that the essential epitope of LpMab-12 is 49-DVVT (SAα2-6GalNAc)P-53 (Fig 5). PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 Neutralization assays of hPDPN and CLEC-2 Finally, we determined whether LpMab-12 inhibits hPDPN-CLEC-2 interaction using ELISA. Additional anti-hPDPN mAbs such as LpMab-2, LpMab-3, and LpMab-9 were employed as controls. Similarly to LpMab-12, LpMab-2 [22], LpMab-3 [25] and LpMab-9 [26] include both peptide and glycan as their epitopes; accordingly, we collectively named these mAbs as anti- glycopeptide mAbs (GpMabs). Anti-rabbit PDPN antibody PMab-32 was used as an additional negative control, since it is of the same isotype (mouse IgG1, kappa) with LpMab-12 [27]. As shown in Fig 6, LpMab-12 impaired the binding of hCLEC-2-Fc to hPDPN-Fc (10.3% inhibi- tion), whereas LpMab-2 did not affect the hPDPN/hCLEC-2 interaction. Interestingly, LpMab-3, the epitope of which includes Thr76 of hPDPN [25] also moderately reduced the hPDPN/hCLEC-2 binding (7.1% inhibition); and LpMab-9, the epitope of which includes Thr25 of hPDPN, impaired the hPDPN/hCLEC-2 interaction to a lesser extent (3.6% inhibi- tion). Importantly, the combination of LpMab-12 and LpMab-3 reduced the hPDPN/hCLEC-2 interaction more effectively (14.7% inhibition) than either LpMab-12 or LpMab-3 alone, indi- cating that a combination of several sialic acids in the hPDPN protein might be important for its optimal interaction with hCLEC-2 in this in vitro assay. 7 / 13 Monoclonal Antibody against Thr52 of Human Podoplanin Fig 3. Epitope mapping of LpMab-12 by Western blot analysis and flow cytometry. (A) CHO-K1 cells were transfected with a plasmid expressing wild-type hPDPN with the FLAG-tag added to the C-terminus (WT), or the FLAG-tag hPDPN containing a point mutation in the sequence E47A-E57A, as indicated in the figure. Total cell lysates from the transfected cell lines were analyzed by Western blot with LpMab-12 or LpMab-7, as a positive control for hPDPN expression. Immunoblot with anti-FLAG antibody was also used as well to establish the expression of exogenous hPDPN. Anti-IDH1 and anti-β-actin mAbs were used as internal controls to show that total proteins are equal protein load. Red arrow, 40-kDa; blue arrow, 30-kDa. (B) CHO-K1 cells transfected as in (A) were analyzed by flow cytometry using indirect immunolabeling with LpMab-12. Cells exposed to the secondary anti-mouse IgG only were used as a negative control (Control). Fig 3. Epitope mapping of LpMab-12 by Western blot analysis and flow cytometry. (A) CHO-K1 cells were transfected with a plasmid expressing wild-type hPDPN with the FLAG-tag added to the C-terminus (WT), or the FLAG-tag hPDPN containing a point mutation in the sequence E47A-E57A, as indicated in the figure. Neutralization assays of hPDPN and CLEC-2 Total cell lysates from the transfected cell lines were analyzed by Western blot with LpMab-12 or LpMab-7, as a positive control for hPDPN expression. Immunoblot with anti-FLAG antibody was also used as well to establish the expression of exogenous hPDPN. Anti-IDH1 and anti-β-actin mAbs were used as internal controls to show that total proteins are equal protein load. Red arrow, 40-kDa; blue arrow, 30-kDa. (B) CHO-K1 cells transfected as in (A) were analyzed by flow cytometry using indirect immunolabeling with LpMab-12. Cells exposed to the secondary anti-mouse IgG only were used as a negative control (Control). doi:10.1371/journal.pone.0152912.g003 doi:10.1371/journal.pone.0152912.g003 Discussion As of today, almost all anti-hPDPN mAbs produced using conventional methods react with the non-glycosylated peptide spanning the PLAG1-3 domains [7,12,31] or PLAG4 domain [32]. Our group also produced numerous mAbs against mouse, rat and rabbit PDPN proteins [27,33,34]. Rabbit polyclonal antibodies, which were reported by Matsui et al., also recognize PLAG1-3 domains, which are shown to be immunodominant antigenic sites of PDPN [35]. Recently, we established the CasMab technology for the production of cancer-specific mAbs and anti-glycopeptide mAbs (GpMabs). Using CasMab platform, we generated multiple mAbs, including LpMab-2, LpMab-3, LpMab-7, LpMab-9, LpMab-10, and LpMab-17, which target different epitopes of hPDPN [22,23,25,26,29,36–38]. Furthermore, using CasMab approach, 8 / 13 PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 Monoclonal Antibody against Thr52 of Human Podoplanin Fig 4. Binding assay of LpMab-12 against sialylated glycopeptide of hPDPN using ELISA. Strategy for the sialylated glycopeptide synthesis. SA, sialic acid; Gal, galacose; GalNAc, N-acetyl-D-galactosamine. doi:10.1371/journal.pone.0152912.g004 Fig 4. Binding assay of LpMab-12 against sialylated glycopeptide of hPDPN using ELISA. Strategy for the sialylated glycopeptide synthesis. SA, sialic acid; Gal, galacose; GalNAc, N-acetyl-D-galactosamine. doi:10.1371/journal.pone.0152912.g004 doi:10.1371/journal.pone.0152912.g004 we produced mAbs that detect residue-specific O-glycosylation in hPDPN: LpMab-2 on Thr55/Ser56, LpMab-3 on Thr76, and LpMab-9 on Thr25. Although the glycosylation on Thr52 is the most critical for the binding of hPDPN to CLEC-2 and platelet aggregating-activ- ity of hPDPN [2,19], no GpMab against Thr52-containing epitope has been developed. The direct detection of glycosylation on Thr52 using specific mAb might be implemented for inves- tigating the function of hPDPN or clinical diagnosis. In this study, we successfully developed LpMab-12 (mouse IgG1, kappa), which specifically detects the glycosylation on Thr52 of hPDPN by flow cytometry (Figs 1 and 3), Western blot (Fig 3), and immunohistochemical analysis (Figs 1 and 2). Because this modification was previ- ously shown to be of critical importance for hPDPN-CLEC-2 interaction [2,19], we hypothe- sized that LpMab-12 might interfere with the hPDPN-binding to CLEC-2. We found that LpMab-12 only partially and weakly reduced the hPDPN binding to hCLEC-2, yet with a higher efficiency than the other anti-hPDPN glycopeptide mAbs (GpMabs), such as LpMab-3 and LpMab-9 (Fig 6). These results indicate that hCLEC-2 might interact with several sialic acids attached to Ser/Thr of hPDPN. Indeed, a novel platelet aggregation-stimulating domain- 4 (PLAG4) of hPDPN (Fig 5) was recently suggested [32], further supporting the notion that complex interactions might be required for an optimal association of hPDPN with hCLEC-2. Discussion Our data show that LpMab-12 is advantageous for the use for hPDPN detection in fixed paraffin-embedded tissue sections, since, unlike other anti-hPDPN antibodies, including Table 1. The reaction of LpMab-12 against glycopeptides of hPDPN. Anti-hPDPN mAbs Glycopeptides LpMab-9 LpMab-12 LpMab-13 LpMab-20 GalNAc + hpp3854 - - +++ +++ Gal + GalNAc + hpp3854 - - +++ +++ SAα2-6GalNAc + hpp3854 - +++ +++ +++ SAα2-3Gal + GalNAc + hpp3854 - - +++ +++ Gal + SAα2-6GalNAc + hpp3854 - +++ +++ +++ SAα2-3Gal + SAα2-6GalNAc + hpp3854 - +++ +++ +++ +++, 0.5≦OD655; -, negative doi:10.1371/journal.pone.0152912.t001 PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 9 / 13 Table 1. The reaction of LpMab-12 against glycopeptides of hPDPN. Table 1. The reaction of LpMab-12 against glycopeptides of hPDPN. PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 9 / 13 Monoclonal Antibody against Thr52 of Human Podoplanin Fig 5. Schematic summary of the epitopes for several anti-hPDPN mAbs. Glycosylation sites are shown (O-glycan). Numbers indicate amino acid position. GpMab, anti-glycopeptide mAb; PLAG, platelet aggregation- stimulating. Fig 5. Schematic summary of the epitopes for several anti-hPDPN mAbs. Glycosylation sites are shown (O-glycan). Numbers indicate amino acid position. GpMab, anti-glycopeptide mAb; PLAG, platelet aggregation- stimulating. Fig 5. Schematic summary of the epitopes for several anti-hPDPN mAbs. Glycosylation sites are shown (O-glycan). Numbers indicate amino acid position. GpMab, anti-glycopeptide mAb; PLAG, platelet aggregation- stimulating. doi:10.1371/journal.pone.0152912.g005 LpMab-2 and LpMab-3 [22,25], or D2-40 and 18H5 [31], LpMab-12 does not necessitate anti- gen retrieval (Fig 2). Further, in most PDPN immunolabeling protocols, the antibodies have to be used at a concentration of 1 μg/ml or higher [22,25,31], whereas relatively low concentra- tions of LpMab-12 (less than 0.1 μg/ml) are sufficient to detected the lymphatic endothelial cells in fixed samples (data not shown). Lec2 mutant of CHO cells lacks a CMP-sialic acid transporter, and is not able to add sialic acid to glycans. In contrast, Lec8 mutant of CHO cells lacks a UDP-Gal transporter and is not able to add Gal to glycans [39]. Our results show that LpMab-12 detects hPDPN with sialylated O-GalNAc (Fig 4 and Table 1); therefore, LpMab-12 did not react with Lec2/hPDPN (S1B Fig). Surprisingly, we observed that LpMab-12 did not react with Lec8/hPDPN cells even at Fig 6. The hPDPN-hCLEC-2 interaction was reduced by LpMab-12. Inhibition assay was performed using ELISA. Supporting Information S1 Fig. (TIFF) S1 File. (DOCX) Supporting Information S1 Fig. (TIFF) S1 File. (DOCX) Acknowledgments We thank Takuro Nakamura, Noriko Saidoh, Hazuki Kanno, and Kanae Yoshida for their excellent technical assistance. We also thank Prof. Hiroyuki Harada for providing us with the tissue samples. Author Contributions Conceived and designed the experiments: YK. Performed the experiments: SO HO PG RH YF. Analyzed the data: MKK. Contributed reagents/materials/analysis tools: SO HO PG RH YF. Wrote the paper: YK PG MKK. Discussion Recombinant immobilized hPDPN-Fc was incubated with PMab-32 (Control), LpMab-2, LpMab-3, LpMab-9, LpMab-12, or LpMab-3 + LpMab-12, followed by sequential exposure to biotinylated hCLEC-2-Fc and peroxidase-conjugated streptavidin. The enzymatic reaction was conducted with a 1-Step Ultra TMB-ELISA. The optical density was measured at 655 nm. Each data bar represents the average of five independent wells. Error bars show standard deviation (SD). N.S., not significant, * P < 0.05, P < 0.01, *P < 0.0001, as determined by one-way ANOVA. doi:10.1371/journal.pone.0152912.g006 Fig 6. The hPDPN-hCLEC-2 interaction was reduced by LpMab-12. Inhibition assay was performed using ELISA. Recombinant immobilized hPDPN-Fc was incubated with PMab-32 (Control), LpMab-2, LpMab-3, LpMab-9, LpMab-12, or LpMab-3 + LpMab-12, followed by sequential exposure to biotinylated hCLEC-2-Fc and peroxidase-conjugated streptavidin. The enzymatic reaction was conducted with a 1-Step Ultra TMB-ELISA. The optical density was measured at 655 nm. Each data bar represents the average of five independent wells. Error bars show standard deviation (SD). N.S., not significant, P < 0.05, P < 0.01, **P < 0.0001, as determined by one-way ANOVA. doi:10 1371/journal pone 0152912 g006 PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 10 / 13 Monoclonal Antibody against Thr52 of Human Podoplanin relatively high concentrations of 10 μg/ml or 100 μg/ml (S1C Fig). Future studies are warranted to determine the reason for the deficiency in O-GalNAc sialylation in Lec8/hPDPN. relatively high concentrations of 10 μg/ml or 100 μg/ml (S1C Fig). Future studies are warranted to determine the reason for the deficiency in O-GalNAc sialylation in Lec8/hPDPN. Conclusion Our study suggests that LpMab-12 is useful for determining whether hPDPN possesses the site-specific sialylation on Thr52, an important post-translational modification for the associa- tion of hPDPN with CLEC-2 and activation of platelet aggregation. Furthermore, the combina- tion of different epitope-specific mAbs, especially GpMabs, might be advantageous for the PDPN-targeting therapies or disease diagnosis. PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 References Mishima K, Kato Y, Kaneko MK, Nishikawa R, Hirose T, Matsutani M (2006) Increased expression of podoplanin in malignant astrocytic tumors as a novel molecular marker of malignant progression. Acta Neuropathol (Berl) 111: 483–488. 9. Mishima K, Kato Y, Kaneko MK, Nishikawa R, Hirose T, Matsutani M (2006) Increased expression of podoplanin in malignant astrocytic tumors as a novel molecular marker of malignant progression. Acta Neuropathol (Berl) 111: 483–488. 10. Abe S, Morita Y, Kaneko MK, Hanibuchi M, Tsujimoto Y, Goto H, et al. (2013) A novel targeting therapy of malignant mesothelioma using anti-podoplanin antibody. J Immunol 190: 6239–6249. doi: 10.4049/ jimmunol.1300448 PMID: 23690472 11. Kunita A, Kashima TG, Ohazama A, Grigoriadis AE, Fukayama M (2011) Podoplanin is regulated by AP-1 and promotes platelet aggregation and cell migration in osteosarcoma. Am J Pathol 179: 1041– 1049. doi: 10.1016/j.ajpath.2011.04.027 PMID: 21801875 12. Kato Y, Vaidyanathan G, Kaneko MK, Mishima K, Srivastava N, Chandramohan V, et al. (2010) Evalua- tion of anti-podoplanin rat monoclonal antibody NZ-1 for targeting malignant gliomas. Nucl Med Biol 37: 785–794. doi: 10.1016/j.nucmedbio.2010.03.010 PMID: 20870153 13. Kunita A, Kashima TG, Morishita Y, Fukayama M, Kato Y, Tsuruo T, et al. (2007) The platelet aggrega- tion-inducing factor aggrus/podoplanin promotes pulmonary metastasis. Am J Pathol 170: 1337–1347. PMID: 17392172 14. Breiteneder-Geleff S, Matsui K, Soleiman A, Meraner P, Poczewski H, Kalt R, et al. (1997) Podoplanin, novel 43-kd membrane protein of glomerular epithelial cells, is down-regulated in puromycin nephrosis. Am J Pathol 151: 1141–1152. PMID: 9327748 15. Schacht V, Dadras SS, Johnson LA, Jackson DG, Hong YK, Detmar M (2005) Up-regulation of the lym- phatic marker podoplanin, a mucin-type transmembrane glycoprotein, in human squamous cell carcino- mas and germ cell tumors. Am J Pathol 166: 913–921. PMID: 15743802 16. Rishi AK, Joyce-Brady M, Fisher J, Dobbs LG, Floros J, VanderSpek J, et al. (1995) Cloning, character- ization, and development expression of a rat lung alveolar type I cell gene in embryonic endodermal and neural derivatives. Dev Biol 167: 294–306. PMID: 7851650 17. Breiteneder-Geleff S, Soleiman A, Kowalski H, Horvat R, Amann G, Kriehuber E, et al. (1999) Angiosar- comas express mixed endothelial phenotypes of blood and lymphatic capillaries: podoplanin as a spe- cific marker for lymphatic endothelium. Am J Pathol 154: 385–394. PMID: 10027397 18. Bertozzi CC, Schmaier AA, Mericko P, Hess PR, Zou Z, Chen M, et al. (2010) Platelets regulate lym- phatic vascular development through CLEC-2-SLP-76 signaling. References 1. Suzuki-Inoue K, Kato Y, Inoue O, Kaneko MK, Mishima K, Yatomi Y, et al. (2007) Involvement of the snake toxin receptor CLEC-2, in podoplanin-mediated platelet activation, by cancer cells. J Biol Chem 282: 25993–26001. PMID: 17616532 1. Suzuki-Inoue K, Kato Y, Inoue O, Kaneko MK, Mishima K, Yatomi Y, et al. (2007) Involvement of the snake toxin receptor CLEC-2, in podoplanin-mediated platelet activation, by cancer cells. J Biol Chem 282: 25993–26001. PMID: 17616532 1. Suzuki-Inoue K, Kato Y, Inoue O, Kaneko MK, Mishima K, Yatomi Y, et al. (2007) Involvement of the snake toxin receptor CLEC-2, in podoplanin-mediated platelet activation, by cancer cells. J Biol Chem 282: 25993–26001. PMID: 17616532 2. Kato Y, Kaneko MK, Kunita A, Ito H, Kameyama A, Ogasawara S, et al. (2008) Molecular analysis of the pathophysiological binding of the platelet aggregation-inducing factor podoplanin to the C-type lec- tin-like receptor CLEC-2. Cancer Sci 99: 54–61. PMID: 17944973 3. Kato Y, Fujita N, Kunita A, Sato S, Kaneko M, Osawa M, et al. (2003) Molecular identification of Aggrus/ T1alpha as a platelet aggregation-inducing factor expressed in colorectal tumors. J Biol Chem 278: 51599–51605. PMID: 14522983 4. Kato Y, Sasagawa I, Kaneko M, Osawa M, Fujita N, Tsuruo T (2004) Aggrus: A diagnostic marker that distinguishes seminoma from embryonal carcinoma in testicular germ cell tumors. Oncogene 23: 8552–8556. PMID: 15361850 5. Martin-Villar E, Scholl FG, Gamallo C, Yurrita MM, Munoz-Guerra M, Cruces J, et al. (2005) Characteri- zation of human PA2.26 antigen (T1alpha-2, podoplanin), a small membrane mucin induced in oral squamous cell carcinomas. Int J Cancer 113: 899–910. PMID: 15515019 6. Kato Y, Kaneko M, Sata M, Fujita N, Tsuruo T, Osawa M (2005) Enhanced expression of Aggrus (T1alpha/podoplanin), a platelet-aggregation-inducing factor in lung squamous cell carcinoma. Tumor Biol 26: 195–200. 7. Kato Y, Kaneko MK, Kuno A, Uchiyama N, Amano K, Chiba Y, et al. (2006) Inhibition of tumor cell- induced platelet aggregation using a novel anti-podoplanin antibody reacting with its platelet-aggrega- tion-stimulating domain. Biochem Biophys Res Commun 349: 1301–1307. PMID: 16979138 8. Mishima K, Kato Y, Kaneko MK, Nakazawa Y, Kunita A, Fujita N, et al. (2006) Podoplanin expression in primary central nervous system germ cell tumors: a useful histological marker for the diagnosis of ger- minoma. Acta Neuropathol (Berl) 111: 563–568. PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 11 / 13 Monoclonal Antibody against Thr52 of Human Podoplanin 9. PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 References Blood 116: 661–670. doi: 10.1182/ blood-2010-02-270876 PMID: 20363774 19. Nagae M, Morita-Matsumoto K, Kato M, Kaneko MK, Kato Y, Yamaguchi Y (2014) A Platform of C- Type lectin-like receptor CLEC-2 for binding O-glycosylated podoplanin and nonglycosylated rhodocy- tin. Structure 22: 1711–1721. doi: 10.1016/j.str.2014.09.009 PMID: 25458834 20. Kaneko MK, Kato Y, Kitano T, Osawa M (2006) Conservation of a platelet activating domain of Aggrus/ podoplanin as a platelet aggregation-inducing factor. Gene 378: 52–57. PMID: 16766141 21. Kaneko MK, Kato Y, Kameyama A, Ito H, Kuno A, Hirabayashi J, et al. (2007) Functional glycosylation of human podoplanin: glycan structure of platelet aggregation-inducing factor. FEBS Lett 581: 331– 336. PMID: 17222411 22. Kato Y, Kaneko MK (2014) A cancer-specific monoclonal antibody recognizes the aberrantly glycosy- lated podoplanin. Sci Rep 4: 5924. doi: 10.1038/srep05924 PMID: 25080943 23. Kato Y, Ogasawara S, Oki H, Honma R, Takagi M, Fujii Y, et al. (2016) Novel monoclonal antibody LpMab-17 developed by CasMab technology distinguishes human podoplanin from monkey podopla- nin. Monoclon Antib Immunodiagn Immunother. 24. Kato Y (2014) Specific monoclonal antibodies against IDH1/2 mutations as diagnostic tools for gliomas. Brain Tumor Pathol 32: 3–11. doi: 10.1007/s10014-014-0202-4 PMID: 25324168 25. Oki H, Ogasawara S, Kaneko MK, Takagi M, Yamauchi M, Kato Y (2015) Characterization of monoclo- nal antibody LpMab-3 recognizing sialylated glycopeptide of podoplanin. Monoclon Antib Immunodiagn Immunother 34: 44–50. doi: 10.1089/mab.2014.0087 PMID: 25723283 26. Kaneko MK, Oki H, Hozumi Y, Liu X, Ogasawara S, Takagi M, et al. (2015) Monoclonal antibody LpMab-9 recognizes O-glycosylated N-terminus of human podoplanin. Monoclon Antib Immunodiagn Immunother 34: 310–317. doi: 10.1089/mab.2015.0022 PMID: 26492618 27. Honma R, Fujii Y, Ogasawara S, Oki H, Liu X, Nakamura T, et al. (2016) Establishment of a novel monoclonal antibody PMab-32 against rabbit podoplanin. Monoclon Antib Immunodiagn Immunother 35: 41–47. doi: 10.1089/mab.2015.0066 PMID: 26788987 28. Honma R, Fujii Y, Ogasawara S, Oki H, Konnai S, Kagawa Y, et al. (2016) Critical Epitope of Anti-Rab- bit Podoplanin Monoclonal Antibodies for Immunohistochemical Analysis Monoclon Antib Immuno- diagn Immunother. 12 / 13 PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 Monoclonal Antibody against Thr52 of Human Podoplanin 29. Kaneko MK, Oki H, Ogasawara S, Takagi M, Kato Y (2015) Anti-podoplanin monoclonal antibody LpMab-7 detects metastatic legions of osteosarcoma. Monoclon Antib Immunodiagn Immunother 34: 154–161. doi: 10.1089/mab.2014.0091 PMID: 26090592 30. Ogasawara S, Kaneko MK, Honma R, Oki H, Fujii Y, Takagi M, et al. PLOS ONE \| DOI:10.1371/journal.pone.0152912 March 31, 2016 References (2016) Establishment of Mouse Monoclonal Antibody LpMab-13 against Human Podoplanin Monoclon Antib Immunodiagn Immunother. 31. Ogasawara S, Kaneko MK, Price JE, Kato Y (2008) Characterization of anti-podoplanin monoclonal antibodies: critical epitopes for neutralizing the interaction between podoplanin and CLEC-2. Hybrid- oma 27: 259–267. doi: 10.1089/hyb.2008.0017 PMID: 18707544 32. Sekiguchi T, Takemoto A, Takagi S, Takatori K, Sato S, Takami M, et al. (2015) Targeting a novel domain in podoplanin for inhibiting plateletmediated tumor metastasis. Oncotarget. 33. Kaji C, Tsujimoto Y, Kato Kaneko M, Kato Y, Sawa Y (2012) Immunohistochemical Examination of Novel Rat Monoclonal Antibodies against Mouse and Human Podoplanin. Acta Histochem Cytochem 45: 227–237. PMID: 23012488 34. Oki H, Honma R, Ogasawara S, Fujii Y, Liu X, Kaneko MK, et al. (2015) Development of a sensitive monoclonal antibody PMab-2 against rat podoplanin. Monoclon Antib Immunodiagn Immunother 34: 396–403. doi: 10.1089/mab.2015.0041 PMID: 26683179 35. Matsui K, Breiteneder-Geleff S, Kerjaschki D (1998) Epitope-specific antibodies to the 43-kD glomeru- lar membrane protein podoplanin cause proteinuria and rapid flattening of podocytes. J Am Soc Nephrol 9: 2013–2026. PMID: 9808087 36. Oki H, Kaneko MK, Ogasawara S, Tsujimoto Y, Liu X, Sugawara M, et al. (2015) Characterization of a monoclonal antibody LpMab-7 recognizing non-PLAG domain of podoplanin. Monoclon Antib Immuno- diagn Immunother 34: 174–180. doi: 10.1089/mab.2014.0090 PMID: 26090595 37. Ogasawara S, Oki H, Kaneko MK, Hozumi Y, Liu X, Honma R, et al. (2015) Development of monoclonal antibody LpMab-10 recognizing non-glycosylated PLAG1/2 domain including Thr34 of human podopla- nin. Monoclon Antib Immunodiagn Immunother 34: 318–326. doi: 10.1089/mab.2015.0018 PMID: 26492619 38. Kato Y, Kunita A, Abe S, Ogasawara S, Fujii Y, Oki H, et al. (2015) The chimeric antibody chLpMab-7 targeting human podoplanin suppresses pulmonary metastasis via ADCC and CDC rather than via its neutralizing activity. Oncotarget 6: 36003–36018. doi: 10.18632/oncotarget.5339 PMID: 26416352 39. Kaneko M, Kato Y, Kunita A, Fujita N, Tsuruo T, Osawa M (2004) Functional sialylated O-glycan to platelet aggregation on Aggrus (T1alpha/podoplanin) molecules expressed in Chinese Hamster Ovary cells. J Biol Chem 279: 38838–38843. PMID: 15231832 13 / 13
https://openalex.org/W2738184804	https://europepmc.org/articles/pmc5522844?pdf=render	English	null	Transcription Factors in Eosinophil Development and As Therapeutic Targets	Frontiers in medicine	2,017	cc-by	5,448	Mini Review published: 24 July 2017 doi: 10.3389/fmed.2017.00115 Transcription Factors in eosinophil Development and As Therapeutic Targets Dynamic gene expression is a major regulatory mechanism that directs hematopoietic cell fate and differentiation, including eosinophil lineage commitment and eosinophil differentiation. Though GATA-1 is well established as a critical transcription factor (TF) for eosinophil development, delineating the transcriptional networks that regulate eosinophil development at homeostasis and in inflammatory states is not complete. Yet, recent advances in molecular experimental tools using purified eosinophil developmen- tal stages have led to identifying new regulators of gene expression during eosinophil development. Herein, recent studies that have provided new insight into the mechanisms of gene regulation during eosinophil lineage commitment and eosinophil differentiation are reviewed. A model is described wherein distinct classes of TFs work together via collaborative and hierarchical interactions to direct eosinophil development. In addition, the therapeutic potential for targeting TFs to regulate eosinophil production is discussed. Understanding how specific signals direct distinct patterns of gene expression required for the specialized functions of eosinophils will likely lead to new targets for therapeutic intervention. Edited by: Mats W. Johansson, University of Wisconsin-Madison, United States Reviewed by: Steven J. Ackerman, University of Illinois at Chicago, United States David Voehringer, University of Erlangen- Nuremberg, Germany Keywords: hematopoiesis, eosinophilopoiesis, transcriptional regulation, eosinophil development, eosinophil lineage commitment INTRODUCTION Correspondence: Patricia C. Fulkerson patricia.fulkerson@cchmc.org Correspondence: Patricia C. Fulkerson patricia.fulkerson@cchmc.org Eosinophils differentiate in the bone marrow from an eosinophil lineage-committed progenitor (EoP) that is derived from the granulocyte/macrophage progenitor (GMP) in mice and the com- mon myeloid progenitor or an upstream multipotent progenitor in humans (1, 2). Cell fate choices, including lineage commitment, are specified by the action of primary, or lineage-determining, transcription factors (TFs) and then reinforced by induction of secondary TFs that orchestrate gene expression and lineage commitment and differentiation. TF concentrations can be important, as lineage-determining TFs can antagonize each other’s activity (3, 4). We have recently shown that markedly more transcriptome changes (1,199 genes) are associated with eosinophil maturation from the EoP than with eosinophil lineage commitment (EoP from GMP, 490 genes), highlighting the greater transcriptional investment necessary for terminal differentiation (5). These dynamic changes in gene expression during eosinophil development included a repertoire of TFs, many of which had never previously been associated with eosinophil development (5). New informa- tion from genome-wide and single-cell RNA sequencing (scRNA-seq) studies have built upon well-established models of transcriptional regulation of eosinophilopoiesis. The molecular regula- tory network that yields functional, mature eosinophils from EoPs is slowly being delineated. Specialty section: This article was submitted to Hematology, a section of the journal Frontiers in Medicine Specialty section: This article was submitted to Hematology, a section of the journal Frontiers in Medicine Received: 16 May 2017 Accepted: 06 July 2017 Published: 24 July 2017 Received: 16 May 2017 Accepted: 06 July 2017 Published: 24 July 2017 Keywords: hematopoiesis, eosinophilopoiesis, transcriptional regulation, eosinophil development, eosinophil lineage commitment EOSINOPHIL LINEAGE COMMITMENT Two nuclear factors, friend of GATA-1 (FOG-1; Zfpm1) and interferon regulatory factor 8 (IRF8; Irf8 or Icsbp), have been shown to be important for regulating Gata1 expression and/ or function in myeloid progenitors and, consequently, to affect eosinophil production. FOG-1 is a transcriptional cofactor that facilitates binding of GATA factors to DNA and recruits chroma- tin remodeling complexes (12–14). FOG-1 is highly expressed by multipotent progenitors, antagonizes GATA-1 transcriptional activity, and must be downregulated to allow for eosinophil lineage commitment (15, 16). Loss of FOG-1 expression in mice is early embryonic lethal from severe anemia due to the requirement for FOG-1 for the formation of erythroid-lineage progenitors (17). FOG-1 deficiency in hematopoietic stem cells results in increased commitment along the myeloid lineages and aberrant expression of myeloid-related genes in megakaryocytic and erythroid cells (18), highlighting the role for FOG-1 in suppressing myeloid cell development. In contrast, loss of Irf8 expression in mice resulted in reduced EoP (and eosinophil) frequency in the bone marrow and lower Gata1 expression in the EoPs that were produced (19), suggesting that the TF IRF8 is critical for upregulating and/or maintaining GATA-1 expression in myeloid progenitors for eosinophil lineage commitment. Notably, murine GMPs with eosinophil lineage potential and that maintained Gata1 expression also expressed intermediate levels of Irf8 (11). The first stage in eosinophil development is commitment to the eosinophil lineage by a myeloid multipotent progenitor to generate an EoP (Figure 1). The EoP is identified via surface expression of CD34, interleukin 5 (IL-5) receptor alpha (IL-5Rα, a.k.a. CD125), and low levels of c-KIT (CD117) in murine bone marrow (1). In humans, EoPs are identified by surface expression of CD34, CD38, and CD125 (2). EoPs reside in small numbers primarily in the bone marrow (~0.05% of lineage-negative CD34+ cells), with even lower levels found in peripheral blood and in human umbilical cord blood (2). Targeting the EoP and the steps determining eosinophil lineage fate for treatment purposes is an attractive strategy, as it would prevent the production of mature eosinophils and all of their immune-activating contents; thus, delineating the factors that are essential for eosinophil lineage commitment will likely be clinically relevant. Eosinophil Lineage Instruction by GATA-1 and GATA-2 Expression of friend of GATA-1 (FOG-1) declines, allowing for increasing expression and activity of GATA TFs, which is necessary for EoP production. Following lineage commitment, eosinophil granule protein gene expression is markedly increased with the collaborative interaction between C/EBPε, PU.1, and GATA-1. To assist with the elevated granule protein synthesis in the EoP and eosinophil precursors, XBP1 expression is increased and promotes survival during the demanding maturation process. Expression of activator isoforms of C/EBPε peaks during eosinophil maturation and then declines during the final stages. Expression of ID2 increases during eosinophil maturation and enhances the rate of maturation. Citation: Citation: Fulkerson PC (2017) Transcription Factors in Eosinophil Development and As Therapeutic Targets. Front. Med. 4:115. doi: 10.3389/fmed.2017.00115 Fulkerson PC (2017) Transcription Factors in Eosinophil Development and As Therapeutic Targets. Front. Med. 4:115. doi: 10.3389/fmed.2017.00115 July 2017 \| Volume 4 \| Article 115 1 Frontiers in Medicine \| www.frontiersin.org Targeting TFs in Eosinophils Fulkerson Defining how eosinophil production is regulated is critical to understanding how dysfunction of the immune response results in eosinophil overproduction and will likely lead to new eosinophil-targeting therapeutics. global gene expression profiling of single murine multipotent progenitor cells revealing that the commitment to the eosinophil lineage segregated with Gata1 expression (10). In addition, scRNA-seq of murine GMPs (Lin−CD34+c-KIT+CD16/32hi) revealed a rare GMP subset with eosinophil lineage potential and that maintained expression of Gata1 (11). Eosinophil Lineage Instruction by GATA-1 and GATA-2 It is well established that myeloid progenitor expression of the TF GATA-1 is essential for eosinophil lineage commitment (6–9). The findings of these earlier studies were supported recently by p p f ) Murine EoPs express both GATA-1 and GATA-2, whereas GMPs express no GATA-1 and low to no level of GATA-2 (5, 20). Ectopic expression of GATA-2 in murine GMPs and human CD34+ hematopoietic progenitors was sufficient to instruct commitment to the eosinophil lineage (7, 20) and induce expression of GATA-1 (20). GATA-1 and GATA-2 have identical DNA sequence binding preferences, but their target genes and transcriptional responsibilities can be cell specific and/or over- lapping, likely via a multitude of coregulators (e.g., FOG-1) (21). Targeted deletion of GATA-1 or GATA-2 has revealed that they control distinct biological processes that affect multiple hemat- opoietic lineages (21). Taken together, these studies emphasize the essential and instructive role for GATA TFs in eosinophil development; yet, targeting GATA-1 or GATA-2 therapeutically is likely to have significant and unacceptable effects on other hematopoietic lineages. FIGURE 1 \| Transcription Factor (TF) expression during eosinophil development. Eosinophils differentiate in the bone marrow from an eosinophil lineage-committed progenitor (EoP) that is derived from the granulocyte/ macrophage progenitor (GMP) in mice and the common myeloid progenitor (CMP) in humans. For eosinophil lineage commitment to occur, the myeloid progenitor (GMP or CMP) must express C/EBPα, C/EBPε, interferon regulatory factor 8 (IRF8), and PU.1. Expression of friend of GATA-1 (FOG-1) declines, allowing for increasing expression and activity of GATA TFs, which is necessary for EoP production. Following lineage commitment, eosinophil granule protein gene expression is markedly increased with the collaborative interaction between C/EBPε, PU.1, and GATA-1. To assist with the elevated granule protein synthesis in the EoP and eosinophil precursors, XBP1 expression is increased and promotes survival during the demanding maturation process. Expression of activator isoforms of C/EBPε peaks during eosinophil maturation and then declines during the final stages. Expression of ID2 increases during eosinophil maturation and enhances the rate of maturation. FIGURE 1 \| Transcription Factor (TF) expression during eosinophil development. Eosinophils differentiate in the bone marrow from an eosinophil lineage-committed progenitor (EoP) that is derived from the granulocyte/ macrophage progenitor (GMP) in mice and the common myeloid progenitor (CMP) in humans. For eosinophil lineage commitment to occur, the myeloid progenitor (GMP or CMP) must express C/EBPα, C/EBPε, interferon regulatory factor 8 (IRF8), and PU.1. Unclear Roles for PU.1h The TF PU.1 is a member of the ETS family of DNA-binding proteins with an essential function in both myeloid and lym- phoid development (29, 30). Though the PU.1 expression level in myeloid progenitors has been shown to be important in regulating macrophage and neutrophil cell fates (3, 31), a defini- tive early role for PU.1 in eosinophil lineage commitment has not been defined. Gene expression analysis of PU.1-deficient fetal liver cells revealed expression of eosinophil peroxidase and major basic protein (Prg2), but little to no Il5ra (32), suggesting that PU.1 is not essential for eosinophil lineage commitment, but studies with a specific focus on the eosinophil lineage potential of hematopoietic cells deficient in PU.1 are needed. C/EBPα Co-Expression with GATA-1 or GATA-2 In addition to expressing GATA-1 and GATA-2, EoPs express relatively high levels of the TF CCAAT/enhancer-binding pro- tein alpha (C/EBPα) (20). C/EBPα is necessary for eosinophil development, as C/EBPα-deficient mice lack eosinophils (and neutrophils) (22). The level of C/EBPα expression is important for eosinophil- vs neutrophil-lineage commitment, as elevated expression of C/EBPα in GMPs due to an impaired protein deg- radation pathway results in increased neutrophil differentiation July 2017 \| Volume 4 \| Article 115 Frontiers in Medicine \| www.frontiersin.org 2 Fulkerson Targeting TFs in Eosinophils at the expense of eosinophils (23). In addition, the order of expression of GATA factors and C/EBPα is critical for eosinophil lineage commitment (8, 20, 24). Enforced expression of GATA-1 or GATA-2 in a C/EBPα-expressing progenitor results in eosino- phil lineage commitment (20). In contrast, ectopic expression of GATA-2 prior to C/EBPα expression leads to basophil-lineage commitment (20). It is believed that C/EBPα is at least partially responsible for the downregulation of FOG-1 expression in myeloid progenitors promoting eosinophil development (15). hierarchical combination of TFs has been shown to be necessary for eosinophil lineage commitment. C/EBPε Interaction with PU.1 One of the PU.1 collaborators in regulating gene expression during eosinophil maturation is the TF C/EBPε. The peripheral blood and bone marrow of adult mice deficient in C/EBPε have a pronounced increase in immature myeloid precursors, indicating a blockade in terminal granulocyte differentiation in the absence of C/EBPε (27). In addition, ectopic expression of C/EBPε in CD34+ hematopoietic progenitors increased the rate of eosinophil maturation (25). C/EBPε is important for the expres- sion of secondary granules in both neutrophils and eosinophils (36, 37), and C/EBPε deficiency results in impaired functional responses for neutrophils (27). Individuals with mutations that abolish C/EBPε expression produce abnormal neutrophils and eosinophils that lack specific granules; thus, these individuals suffer from early and frequent bacterial infections (26, 38, 39), providing clinically relevant support for a critical role for C/EBPε in terminal differentiation of granulocytes. Interestingly, peripheral blood eosinophils predominantly express one of the repressor isoforms of C/EBPε (36), suggesting that C/EBPε’s repressive activity is more important during late-stage eosinophil maturation. PU.1 Priming for Transcription g p Recent studies in macrophages have revealed a collaborative inter- action between PU.1 and other lineage-determining TFs, such as C/EBPα, to open chromatin and “prime” genes for transcription (33, 34). Consistent with this role as a “pioneer” TF, PU.1 has been shown to cooperatively regulate the expression of eosinophil granule protein genes (35–37), including PRG2 (major basic pro- tein) and RNS2 (eosinophil-derived neurotoxin), highlighting an important role for PU.1 in eosinophil maturation. Future studies are needed to determine how the distribution of PU.1 across the genome differs between granulocytes (eosinophils, neutrophils, basophils, and mast cells) and what partnerships are critical for terminal differentiation of the distinct cell types. EOSINOPHIL MATURATION Human eosinophils have characteristic morphologic features, including a bilobed nucleus and cytoplasmic granules filled with cationic proteins that are packaged in a specific manner (Figure 1). Eosinophils are terminally differentiated and do not proliferate once they leave the bone marrow. We noted that mature eosinophils share expression of 60 TFs with EoPs and express an additional 35 TFs that EoPs do not (5), suggesting that it requires a greater number of TFs to produce a more complex and differentiated cell. Identifying the critical TFs for specific eosinophil functional responses will provide potential new thera- peutic targets. C/EBPε Promotes Eosinophil Cell Fate p Multiple isoforms of the TF C/EBPε with distinct transcriptional functions (e.g., activators and repressors) are expressed during eosinophil maturation, and expression levels of the varying iso- forms change with developmental stage (25, 26), reinforcing that ratios of TFs with combinatorial and even antagonistic activities are highlights of the eosinophil developmental program. Low levels of the activator C/EBPε isoforms are expressed in CD34+ hematopoietic progenitors, and all isoforms increase in expres- sion during IL-5-mediated differentiation, with the repressor isoforms predominating during later stages of maturation (25). Mice deficient in C/EBPε fail to generate mature eosinophils or normal neutrophils (27), supporting a critical role for C/EBPε in a common upstream myeloid progenitor. Notably, ectopic expression of the activator isoforms of C/EBPε in umbilical cord blood CD34+ progenitors resulted in markedly increased commitment to the eosinophil lineage (25). In contrast, expres- sion of the repressor isoforms decreased eosinophil cell fate, but not other myeloid lineages (25), suggesting that inducing expression of repressor isoforms in early myeloid progenitors may specifically inhibit eosinophil production. Expression of the four isoforms of C/EBPε results from differential splicing and alternative use of promoters (26, 28), but the critical transcrip- tional regulators that orchestrate the expression of the different isoforms is not known. XBP1 Is Required for EoP Survival In summary, eosinophil lineage commitment occurs in a myeloid multipotent progenitor that expresses C/EBPα, C/EBPε, and IRF8 followed by concomitant declining FOG-1 expression and increasing GATA-1 and GATA-2 expression (Figure 1). This q Murine EoPs have been shown to contain nascent granules (1, 5) and express granule protein mRNAs at a higher level than mature eosinophils (5); thus, early EoP differentiation likely represents July 2017 \| Volume 4 \| Article 115 Frontiers in Medicine \| www.frontiersin.org 3 Targeting TFs in Eosinophils Fulkerson a developmentally restricted period during eosinophilopoiesis when protein production and endoplasmic reticulum (ER) demand peaks. XBP1 (Xbp1) is a TF that is involved in the unfolded protein response triggered by ER stress (40). In response to ER stress, Xbp1 mRNA is spliced by the endoribonuclease IRE1α followed by translation of the active TF XBP1. Accumulation of the spliced Xbp1 mRNA was higher in GMPs and EoPs than eosinophil precursors, and no spliced Xbp1 mRNA was noted in mature eosinophils, which is consistent with activation of the ER stress pathway during high protein synthetic demands through eosinophil maturation (41). Notably, loss of Xbp1 expression in hematopoietic cells resulted in a compete loss of mature eosino- phils (41). EoPs were present in the bone marrow but at a lower frequency in Xbp1-deficient than Xbp1-sufficient mice, likely due to poor survival (41); thus, Xbp1 is essential for eosinophil maturation but not lineage commitment. STAT6 was not required for eosinophil recruitment into tissues in response to parasitic infection (53), highlighting the need for further investigations to delineate the impact of environmental signals on gene regulatory programs. Together, these studies suggest that targeting TFs in specific clinical settings may impact eosinophil function and survival. ID2 Enhances Terminal Differentiation Inhibitor of DNA-binding (ID) proteins is a family of negative transcriptional regulators that heterodimerizes with basic helix- loop-helix TFs and prevents binding to the DNA (42). Expression of ID2 was upregulated during eosinophil maturation, and ectopic expression of ID2 in human CD34+ hematopoietic pro- genitors resulted in increased mature eosinophils, with no change in frequency of the earlier precursors (43), suggesting that ID2 enhances terminal differentiation. In contrast, expression of ID1 declines during eosinophil maturation and inhibits terminal differentiation (43). EOSINOPHIL FUNCTION In addition to orchestrating eosinophil production, TFs also participate in eosinophil functional responses and survival. Glucocorticoids are the first-line therapy for eosinophil-associated disorders, such as allergy, asthma, eosinophilic gastrointestinal disorders and hypereosinophilic syndrome (44, 45); yet, there are a subset of individuals with severe asthma with eosinophilia despite high doses of glucocorticoids (46–48) and patients with hypereosinophilic syndrome often become glucocorticoid refractory (49, 50). The TF NFIL3 has recently been shown to be induced by IL-5 stimulation in eosinophils and to protect against glucocorticoid-induced apoptosis (51), suggesting that targeting NFIL3 in patients may restore glucocorticoid sensitivity. STAT6 is another TF that has been shown to regulate eosinophil functional responses, specifically in experimental asthma. Sensitized mice with STAT6-deficient eosinophils were protected against mucus overproduction and airway hyperresponsiveness following aller- gen challenge (52), highlighting an important role for STAT6 sign- aling in eosinophils in allergic asthma. Yet, eosinophil-intrinsic FUNDING This work was supported by the NIH grant R01AI130033. This work was supported by the NIH grant R01AI130033. AUTHOR CONTRIBUTIONS The author confirms being the sole contributor of this work and approved it for publication. of phenotypic definition of the human common myeloid progenitor. J Exp Med (2009) 206(1):183–93. doi:10.1084/jem.20081756 3. Dahl R, Walsh JC, Lancki D, Laslo P, Iyer SR, Singh H, et al. Regulation of macrophage and neutrophil cell fates by the PU.1:C/EBPalpha ratio and granulocyte colony-stimulating factor. Nat Immunol (2003) 4(10):1029–36. doi:10.1038/ni973 CONCLUSION AND FUTURE DIRECTIONS As there have been no described TFs that are specific to the eosinophil lineage, targeting eosinophil production currently has been achieved primarily via indirect means. A wealth of evidence support a critical role for the cytokine IL-5 in mediating disease-associated eosinophilia, and neutralizing IL-5 indirectly suppresses eosinophil maturation (54). IL-5 is produced by type 2 helper T (Th2) cells and the TF GATA-3 has been shown to control expression of IL-5 in Th2 cells (55). In addition, group 2 innate lymphoid cells (ILC2s) produce large amounts of IL-5 upon activation by epithelial-derived cytokines (56, 57) and GATA-3 is essential for ILC2 development (58); thus, GATA-3 is an attractive therapeutic target to prevent IL-5 expression. Notably, treatment with a DNA enzyme that cleaved GATA3 mRNA resulted in reduced airway eosinophilia and plasma lev- els of IL-5 in individuals with asthma (59, 60), highlighting the feasibility of targeting TFs in patients with eosinophil disorders. With emerging technology and public databases of information available to investigators around the world, the future for research in eosinophil development is bright. Many new questions have arisen as our knowledge expands. Recently, a new regulatory eosinophil subset has been described in the murine lung and with a transcriptome that differed from that of inflammatory eosinophils (61). In addition, thymus-resident eosinophils have a distinct phenotype from other tissue-resident eosinophils (62). Together, these studies indicate that extrinsic signals from the local environment likely affect gene expression via changes in the regulatory program or that these eosinophil subsets are produced via a differential developmental program. Understanding how specific signals direct distinct patterns of gene expression required for the specialized functions of tissue-resident eosinophils will likely lead to new targets for therapeutic intervention. of phenotypic definition of the human common myeloid progenitor. J Exp Med (2009) 206(1):183–93. doi:10.1084/jem.20081756 2. Mori Y, Iwasaki H, Kohno K, Yoshimoto G, Kikushige Y, Okeda A, et al. Identification of the human eosinophil lineage-committed progenitor: revision Frontiers in Medicine \| www.frontiersin.org REFERENCES of phenotypic definition of the human common myeloid progenitor. J Exp Med (2009) 206(1):183–93. doi:10.1084/jem.20081756 1. Iwasaki H, Mizuno S, Mayfield R, Shigematsu H, Arinobu Y, Seed B, et al. Identification of eosinophil lineage-committed progenitors in the murine bone marrow. J Exp Med (2005) 201(12):1891–7. doi:10.1084/jem. 20050548 1. Iwasaki H, Mizuno S, Mayfield R, Shigematsu H, Arinobu Y, Seed B, et al. Identification of eosinophil lineage-committed progenitors in the murine bone marrow. J Exp Med (2005) 201(12):1891–7. doi:10.1084/jem. 20050548 3. Dahl R, Walsh JC, Lancki D, Laslo P, Iyer SR, Singh H, et al. Regulation of macrophage and neutrophil cell fates by the PU.1:C/EBPalpha ratio and granulocyte colony-stimulating factor. Nat Immunol (2003) 4(10):1029–36. doi:10.1038/ni973 2. Mori Y, Iwasaki H, Kohno K, Yoshimoto G, Kikushige Y, Okeda A, et al. Identification of the human eosinophil lineage-committed progenitor: revision 4. Walsh JC, DeKoter RP, Lee HJ, Smith ED, Lancki DW, Gurish MF, et al. Cooperative and antagonistic interplay between PU.1 and GATA-2 in the 4. Walsh JC, DeKoter RP, Lee HJ, Smith ED, Lancki DW, Gurish MF, et al. Cooperative and antagonistic interplay between PU.1 and GATA-2 in the July 2017 \| Volume 4 \| Article 115 Frontiers in Medicine \| www.frontiersin.org 4 Targeting TFs in Eosinophils Fulkerson specification of myeloid cell fates. Immunity (2002) 17(5):665–76. doi:10.1016/ S1074-7613(02)00452-1 24. Nerlov C, McNagny KM, Doderlein G, Kowenz-Leutz E, Graf T. Distinct C/EBP functions are required for eosinophil lineage commitment and matu ration. Genes Dev (1998) 12(15):2413–23. doi:10.1101/gad.12.15.2413 specification of myeloid cell fates. Immunity (2002) 17(5):665–76. doi:10.1016/ S1074-7613(02)00452-1 5. Bouffi C, Kartashov AV, Schollaert KL, Chen X, Bacon WC, Weirauch MT, et al. Transcription factor repertoire of homeostatic eosinophilopoiesis. J Immunol (2015) 195(6):2683–95. doi:10.4049/jimmunol.1500510 25. Bedi R, Du J, Sharma AK, Gomes I, Ackerman SJ. Human C/EBP-epsilon activator and repressor isoforms differentially reprogram myeloid lineage commitment and differentiation. Blood (2009) 113(2):317–27. doi:10.1182/ blood-2008-02-139741 6. Kulessa H, Frampton J, Graf T. GATA-1 reprograms avian myelomonocytic cell lines into eosinophils, thromboblasts, and erythroblasts. Genes Dev (1995) 9(10):1250–62. doi:10.1101/gad.9.10.1250 26. Lekstrom-Himes JA. The role of C/EBP(epsilon) in the terminal stages of granulocyte differentiation. Stem Cells (2001) 19(2):125–33. doi:10.1634/ stemcells.19-2-125 7. Hirasawa R, Shimizu R, Takahashi S, Osawa M, Takayanagi S, Kato Y, et al. Essential and instructive roles of GATA factors in eosinophil develop- ment. J Exp Med (2002) 195(11):1379–86. doi:10.1084/jem.20020170 t 27. Yamanaka R, Barlow C, Lekstrom-Himes J, Castilla LH, Liu PP, Eckhaus M, et al. REFERENCES doi:10.1007/82_2011_142 h 14. Pal S, Cantor AB, Johnson KD, Moran TB, Boyer ME, Orkin SH, et al. Coregulator-dependent facilitation of chromatin occupancy by GATA-1. Proc Natl Acad Sci U S A (2004) 101(4):980–5. doi:10.1073/pnas.0307612100 34. Heinz S, Romanoski CE, Benner C, Glass CK. The selection and function of cell type-specific enhancers. Nat Rev Mol Cell Biol (2015) 16(3):144–54. doi:10.1038/nrm3949 15. Querfurth E, Schuster M, Kulessa H, Crispino JD, Doderlein G, Orkin SH, et al. Antagonism between C/EBPbeta and FOG in eosinophil lineage commitment of multipotent hematopoietic progenitors. Genes Dev (2000) 14(19):2515–25. doi:10.1101/gad.177200 35. van Dijk TB, Caldenhoven E, Raaijmakers JA, Lammers JW, Koenderman L, de Groot RP. The role of transcription factor PU.1 in the activity of the intronic enhancer of the eosinophil-derived neurotoxin (RNS2) gene. Blood (1998) 91(6):2126–32. 16. Du Roure C, Versavel A, Doll T, Cao C, Pillonel V, Matthias G, et al. Hematopoietic overexpression of FOG1 does not affect B-cells but reduces the number of circulating eosinophils. PLoS One (2014) 9(4):e92836. doi:10.1371/ journal.pone.0092836 36. Du J, Stankiewicz MJ, Liu Y, Xi Q, Schmitz JE, Lekstrom-Himes JA, et al. Novel combinatorial interactions of GATA-1, PU.1, and C/EBPepsilon isoforms regulate transcription of the gene encoding eosinophil granule major basic protein. J Biol Chem (2002) 277(45):43481–94. doi:10.1074/jbc. M204777200 17. Tsang AP, Fujiwara Y, Hom DB, Orkin SH. Failure of megakaryopoiesis and arrested erythropoiesis in mice lacking the GATA-1 transcriptional cofactor FOG. Genes Dev (1998) 12(8):1176–88. doi:10.1101/gad.12.8.1176 37. Gombart AF, Kwok SH, Anderson KL, Yamaguchi Y, Torbett BE, Koeffler HP. Regulation of neutrophil and eosinophil secondary granule gene expression by transcription factors C/EBP epsilon and PU.1. Blood (2003) 101(8):3265–73. doi:10.1182/blood-2002-04-1039 18. Mancini E, Sanjuan-Pla A, Luciani L, Moore S, Grover A, Zay A, et al. FOG-1 and GATA-1 act sequentially to specify definitive megakaryocytic and erythroid progenitors. EMBO J (2012) 31(2):351–65. doi:10.1038/emboj. 2011.390 38. Gombart AF, Shiohara M, Kwok SH, Agematsu K, Komiyama A, Koeffler HP. Neutrophil-specific granule deficiency: homozygous recessive inheritance of a frameshift mutation in the gene encoding transcription factor CCAAT/enhancer binding protein–epsilon. Blood (2001) 97(9):2561–7. doi:10.1182/blood.V97.9.2561 19. Milanovic M, Terszowski G, Struck D, Liesenfeld O, Carstanjen D. IFN consensus sequence binding protein (Icsbp) is critical for eosinophil devel- opment. J Immunol (2008) 181(7):5045–53. doi:10.4049/jimmunol.181. 7.5045 20. Iwasaki H, Mizuno S, Arinobu Y, Ozawa H, Mori Y, Shigematsu H, et al. The order of expression of transcription factors directs hierarchical specification of hematopoietic lineages. Genes Dev (2006) 20(21):3010–21. REFERENCES Impaired granulopoiesis, myelodysplasia, and early lethality in CCAAT/ enhancer binding protein epsilon-deficient mice. Proc Natl Acad Sci U S A (1997) 94(24):13187–92. doi:10.1073/pnas.94.24.13187 8. McNagny K, Graf T. Making eosinophils through subtle shifts in transcrip- tion factor expression. J Exp Med (2002) 195(11):f43–7. doi:10.1084/jem. 20020636 9. Yu C, Cantor AB, Yang H, Browne C, Wells RA, Fujiwara Y, et al. Targeted deletion of a high-affinity GATA-binding site in the GATA-1 promoter leads to selective loss of the eosinophil lineage in vivo. J Exp Med (2002) 195(11):1387–95. doi:10.1084/jem.20020656 h 28. Yamanaka R, Kim GD, Radomska HS, Lekstrom-Himes J, Smith LT, Antonson P, et al. CCAAT/enhancer binding protein epsilon is preferen- tially up-regulated during granulocytic differentiation and its functional versatility is determined by alternative use of promoters and differential splicing. Proc Natl Acad Sci U S A (1997) 94(12):6462–7. doi:10.1073/pnas.94. 12.6462 10. Drissen R, Buza-Vidas N, Woll P, Thongjuea S, Gambardella A, Giustacchini A, et al. Distinct myeloid progenitor-differentiation pathways identified through single-cell RNA sequencing. Nat Immunol (2016) 17(6):666–76. doi:10.1038/ ni.3412 29. McKercher SR, Torbett BE, Anderson KL, Henkel GW, Vestal DJ, Baribault H, et al. Targeted disruption of the PU.1 gene results in multiple hematopoietic abnormalities. EMBO J (1996) 15(20):5647–58. 11. Olsson A, Venkatasubramanian M, Chaudhri VK, Aronow BJ, Salomonis N, Singh H, et al. Single-cell analysis of mixed-lineage states leading to a binary cell fate choice. Nature (2016) 537(7622):698–702. doi:10.1038/nature19348 30. Scott EW, Simon MC, Anastasi J, Singh H. Requirement of transcription factor PU.1 in the development of multiple hematopoietic lineages. Science (1994) 265(5178):1573–7. doi:10.1126/science.8079170 h 12. Tsang AP, Visvader JE, Turner CA, Fujiwara Y, Yu C, Weiss MJ, et al. FOG, a multitype zinc finger protein, acts as a cofactor for transcription factor GATA-1 in erythroid and megakaryocytic differentiation. Cell (1997) 90(1):109–19. doi:10.1016/S0092-8674(00)80318-9 31. Dahl R, Simon MC. The importance of PU.1 concentration in hematopoietic lineage commitment and maturation. Blood Cells Mol Dis (2003) 31(2):229–33. doi:10.1016/S1079-9796(03)00152-9 13. Fox AH, Liew C, Holmes M, Kowalski K, Mackay J, Crossley M. Transcriptional cofactors of the FOG family interact with GATA proteins by means of mul- tiple zinc fingers. EMBO J (1999) 18(10):2812–22. doi:10.1093/emboj/18. 10.2812 32. Lee J, Rosenberg HF. Eosinophils in Health and Disease. 1st ed. London, Waltham, MA: Elsevier/Academic Press (2013). xxiii, 654 p. 33. Heinz S, Glass CK. Roles of lineage-determining transcription factors in establishing open chromatin: lessons from high-throughput studies. Curr Top Microbiol Immunol (2012) 356:1–15. REFERENCES doi:10.1101/ gad.1493506 39. Rosenberg HF, Gallin JI. Neutrophil-specific granule deficiency includes eosinophils. Blood (1993) 82(1):268–73. 40. Calfon M, Zeng H, Urano F, Till JH, Hubbard SR, Harding HP, et al. IRE1 couples endoplasmic reticulum load to secretory capacity by processing the XBP-1 mRNA. Nature (2002) 415(6867):92–6. doi:10.1038/415092a h 21. Katsumura KR, Bresnick EH, Group GFM. The GATA factor revo- lution in hematology. Blood (2017) 129(15):2092–102. doi:10.1182/ blood-2016-09-687871 41. Bettigole SE, Lis R, Adoro S, Lee AH, Spencer LA, Weller PF, et al. The tran- scription factor XBP1 is selectively required for eosinophil differentiation. Nat Immunol (2015) 16(8):829–37. doi:10.1038/ni.3225 22. Zhang DE, Zhang P, Wang ND, Hetherington CJ, Darlington GJ, Tenen DG. Absence of granulocyte colony-stimulating factor signaling and neutrophil development in CCAAT enhancer binding protein alpha-deficient mice. Proc Natl Acad Sci U S A (1997) 94(2):569–74. doi:10.1073/pnas.94.2.569 42. Kee BL. E and ID proteins branch out. Nat Rev Immunol (2009) 9(3):175–84. doi:10.1038/nri2507 43. Buitenhuis M, van Deutekom HW, Verhagen LP, Castor A, Jacobsen SE, Lammers JW, et al. Differential regulation of granulopoiesis by the basic helix-loop-helix transcriptional inhibitors Id1 and Id2. Blood (2005) 105 (11):4272–81. doi:10.1182/blood-2004-12-4883 23. Satoh T, Kidoya H, Naito H, Yamamoto M, Takemura N, Nakagawa K, et al. Critical role of Trib1 in differentiation of tissue-resident M2-like macro phages. Nature (2013) 495(7442):524–8. doi:10.1038/nature11930 July 2017 \| Volume 4 \| Article 115 Frontiers in Medicine \| www.frontiersin.org 5 Targeting TFs in Eosinophils Fulkerson 44. Klion AD. Eosinophilia: a pragmatic approach to diagnosis and treatment. Hematology Am Soc Hematol Educ Program (2015) 2015:92–7. doi:10.1182/ asheducation-2015.1.92 55. Ray A, Cohn L. Th2 cells and GATA-3 in asthma: new insights into the regulation of airway inflammation. J Clin Invest (1999) 104(8):985–93. doi:10.1172/JCI8204 56. Neill DR, Wong SH, Bellosi A, Flynn RJ, Daly M, Langford TK, et al. Nuocytes represent a new innate effector leukocyte that mediates type-2 immunity. Nature (2010) 464(7293):1367–70. doi:10.1038/nature08900 45. Uppal V, Kreiger P, Kutsch E. Eosinophilic gastroenteritis and colitis: a comprehensive review. Clin Rev Allergy Immunol (2016) 50(2):175–88. doi:10.1007/s12016-015-8489-4 46. Nair P, Pizzichini MM, Kjarsgaard M, Inman MD, Efthimiadis A, Pizzichini E, et al. Mepolizumab for prednisone-dependent asthma with sputum eosinophilia. N Engl J Med (2009) 360(10):985–93. doi:10.1056/ NEJMoa0805435 57. Saenz SA, Siracusa MC, Perrigoue JG, Spencer SP, Urban JF Jr, Tocker JE, et al. IL25 elicits a multipotent progenitor cell population that promotes T(H)2 cytokine responses. Nature (2010) 464(7293):1362–6. doi:10.1038/ nature08901 47. REFERENCES Pavord ID, Korn S, Howarth P, Bleecker ER, Buhl R, Keene ON, et al. Mepolizumab for severe eosinophilic asthma (DREAM): a multicentre, double-blind, placebo-controlled trial. Lancet (2012) 380(9842):651–9. doi:10.1016/S0140-6736(12)60988-X 58. Tindemans I, Serafini N, Di Santo JP, Hendriks RW. GATA-3 function in innate and adaptive immunity. Immunity (2014) 41(2):191–206. doi:10.1016/j. immuni.2014.06.006 59. Homburg U, Renz H, Timmer W, Hohlfeld JM, Seitz F, Luer K, et al. Safety and tolerability of a novel inhaled GATA3 mRNA targeting DNAzyme in patients with TH2-driven asthma. J Allergy Clin Immunol (2015) 136(3):797–800. doi:10.1016/j.jaci.2015.02.018 48. Pavord ID, Haldar P, Bradding P, Wardlaw AJ. Mepolizumab in refractory eosinophilic asthma. Thorax (2010) 65(4):370. doi:10.1136/thx.2009.122697 h 49. Debierre-Grockiego F, Leduc I, Prin L, Gouilleux-Gruart V. Dexamethasone inhibits apoptosis of eosinophils isolated from hypereosinophilic patients. Immunobiology (2001) 204(4):517–23. doi:10.1078/0171-2985-00060 i 60. Krug N, Hohlfeld JM, Kirsten AM, Kornmann O, Beeh KM, Kappeler D, et al. Allergen-induced asthmatic responses modified by a GATA3-specific DNAzyme. N Engl J Med (2015) 372(21):1987–95. doi:10.1056/NEJMoa1411776 50. Ogbogu PU, Bochner BS, Butterfield JH, Gleich GJ, Huss-Marp J, Kahn JE, et al. Hypereosinophilic syndrome: a multicenter, retrospective analysis of clinical characteristics and response to therapy. J Allergy Clin Immunol (2009) 124(6):1319–25.e3. doi:10.1016/j.jaci.2009.09.022 f 61. Mesnil C, Raulier S, Paulissen G, Xiao X, Birrell MA, Pirottin D, et al. Lung- resident eosinophils represent a distinct regulatory eosinophil subset. J Clin Invest (2016) 126(9):3279–95. doi:10.1172/JCI85664 51. Pazdrak K, Moon Y, Straub C, Stafford S, Kurosky A. Eosinophil resistance to glucocorticoid-induced apoptosis is mediated by the transcription factor NFIL3. Apoptosis (2016) 21(4):421–31. doi:10.1007/s10495-016-1226-5 62. Becher B, Schlitzer A, Chen J, Mair F, Sumatoh HR, Teng KW, et al. High- dimensional analysis of the murine myeloid cell system. Nat Immunol (2014) 15(12):1181–9. doi:10.1038/ni.3006 52. Stokes K, LaMarche NM, Islam N, Wood A, Huang W, August A. Cutting edge: STAT6 signaling in eosinophils is necessary for development of aller- gic airway inflammation. J Immunol (2015) 194(6):2477–81. doi:10.4049/ jimmunol.1402096 Conflict of Interest Statement: The author declares that the research was con- ducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Conflict of Interest Statement: The author declares that the research was con- ducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. 53. Voehringer D, van Rooijen N, Locksley RM. Frontiers in Medicine \| www.frontiersin.org July 2017 \| Volume 4 \| Article 115 REFERENCES Eosinophils develop in distinct stages and are recruited to peripheral sites by alternatively activated macro- phages. J Leukoc Biol (2007) 81(6):1434–44. doi:10.1189/jlb.1106686 i Copyright © 2017 Fulkerson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. 54. Molfino NA, Gossage D, Kolbeck R, Parker JM, Geba GP. Molecular and clinical rationale for therapeutic targeting of interleukin-5 and its recep- tor. Clin Exp Allergy (2012) 42(5):712–37. doi:10.1111/j.1365-2222.2011. 03854.x July 2017 \| Volume 4 \| Article 115 Frontiers in Medicine \| www.frontiersin.org 6
https://openalex.org/W4206517857	https://zenodo.org/records/5833168/files/Substantiation%20of%20the%20perspectivity%20of%20improving%20of%20the%20population%20informing%20about%20the%20criteria%20of%20the%20correct%20choice%20of%20modern%20multivitamin%20drugs.pdf	English	null	Substantiation of the perspectivity of improving of the population informing about the criteria of the correct choice of modern multivitamin drugs	ScienceRise. Biological science	2,021	cc-by	4,274	Tetiana Kutsenko, Dmitro Semeniv, Katherina Shchokina, Galina Belik, Yurii Stoletov, Olga Getalo Substantiation of the perspectivity of improving of the popula- tion informing about the criteria of the correct choice of modern multivitamin drugs. ScienceRise: Biological Science, 4 (29), 4–9. doi: http://doi.org/10.15587/2519-8025.2021.249494 №4(29)2021 №4(29)2021 Scientific Journal «ScienceRise: Biological Science» BIOLOGICAL RESEARCH UDC: 615.03.008.05 (470.324) DOI: 10.15587/2519-8025.2021.249494 UDC: 615.03.008.05 (470.324) DOI: 10.15587/2519-8025.2021.249494 How to cite: Kutsenko, T., Semeniv, D., Shchokina, K., Belik, G., Stoletov, Y., Getalo, O. (2021). Substantiation of the perspectivity of improving of the popula- tion informing about the criteria of the correct choice of modern multivitamin drugs. ScienceRise: Biological Science, 4 (29), 4–9. doi: http://doi.org/10.15587/2519-8025.2021.249494 Tetiana Kutsenko, Dmitro Semeniv, Katherina Shchokina, Galina Belik, Yurii Stoletov, Olga Getalo The aim. Determination of the need to raise awareness of the population about multivitamins and the criteria for their rational choice. Materials and research methods. To achieve the goal of the study, it was necessary to develop a questionnaire for visi- tors to pharmacies and carry out an anonymous survey of them. All adult visitors of the pharmacy were attracted to the survey. y The developed questionnaire consisted of 3 parts and contained 32 questions processed in the course of our own re- search. Research results. Among the pharmacy visitors we surveyed, the majority were between the ages of 35–55, approxi- mately equally divided were men and women who mainly lived in the Kiev region (87 %), were not students and did not have educational levels of bachelor or master, and had no relation in health care education. Summarizing the information obtained in the course of processing questionnaires with the answers of visitors to phar- macies, it can be noted that in the surveyed group of respondents there is a certain interest and indifference to the dis- cussed aspects, but quite often there is a lack of knowledge in this regard. Conclusions. In the course of analyzing the results of the questionnaire survey, the level of awareness of the population regarding general information about the pharmacology of multivitamin drugs and the criteria for their correct choice was determined. From the data obtained, it can be concluded that on many issues the respondents showed an insuffi- cient level of knowledge, which justifies the need for additional information about multivitamins, and indicates that bet- ter it should be done with participation of a specialist with a pharmaceutical education or physician. f Mostly the population lacks knowledge on the issues listed in the second part of the questionnaire, nam information about the biological and pharmacological properties of vitamins. t the information obtained from the Internet or other media, including advertising, has a significant im- reness and decision of the respondents It was found that the information obtained from the Internet or other media, including advertising, has a pact on the awareness and decision of the respondents Keywords: improvement of population informing, criteria of correct choice of drugs, awareness, multivitamin drugs How to cite: Kutsenko, T., Semeniv, D., Shchokina, K., Belik, G., Stoletov, Y., Getalo, O. (2021). © The Author(s) 2021 This is an open access article under the Creative Commons CC BY license hydrate 1. Introduction background of insufficient intake of vitamins from food; acute or chronic diseases, especially of the gastrointesti- nal tract, bad habits, adverse environmental conditions of the area of residence [3, 4]. Vitamins are nutrients that are vital to the hu- man body. Deficiency of vitamins in the body often develops under the complex influence of adverse fac- tors and is quite common among the inhabitants of Eastern Europe [1, 2]. In addition, there is a steady trend of year-round hypovitaminosis, in which the lack of vitamins is deter- mined not only in winter and spring, but also in the most favourable summer and autumn. Vitamin deficiency is usually combined, i.e., is polyvitaminosis, and in several This situation is complicated by irrational nutri- tion, in particular the excess energy value of the diet and the content of animal fat, added sugar and salt in the Biological research Biological research 4 Scientific Journal «ScienceRise: Biological Science» №4(29)2021 dence, level of education and availability of medical or pharmaceutical education). regions in parallel there is insufficient intake of calcium, iodine, selenium, fluorine and other macro – and micro- nutrients [3, 5]. The second part of the questionnaire asked ques- tions about general concepts of vitamins and vitamin therapy, namely the definition, classification and nomen- clature of vitamins, as well as other aspects of their pharmacological characteristics. There is also often a so-called subnormal or pre- clinical form of vitamin deficiency. In conditions of in- sufficient production of vitamin-enriched foods, the main way to eliminate vitamin deficiency is the use of vitamin- mineral complexes. The existence of inter-vitamin inter- actions, as well as the high frequency of cases among the population of polyvitaminosis, are the basis for the use of multivitamin-mineral complexes [6–8]. The third part of the questionnaire asked about the approaches to drug selection, which mostly concerned the priorities of choosing a source of information about a multivitamin and ways to determine the real need and feasibility of its use. In the pharmaceutical market of Ukraine there is a wide choice (about 50 names without biologically active additives (BAS) of similar composition, which also in- cludes more than 150 with BASes) of multivitamin prepa- rations developed by both domestic and foreign manufac- turers. These drugs differ in qualitative and quantitative composition, source of vitamins, dosage form, etc. [9]. 1. Introduction A total of 104 respondents from Kyiv, Chernihiv and Sumy oblasts took part in the survey, but 100 ques- tionnaires were selected. When processing the questionnaires, the absolute number and, accordingly, the percentage of respondents were counted for each item and question of the question- naire, except for questions where several answer options could be chosen, which made it impossible to determine the number of votes. Therefore, in such questions, the in- formation was indicated only in absolute numbers and in this way the rating of items was determined among them- selves. Many of these drugs can be used for prophylactic purposes by practically healthy people, which raises the question of the need for optimal individual choice of drug in each case [3, 6]. From the available and analyzed sources of litera- ture it is known that the appointment of multivitamins is not always done in consultation with a doctor or even a pharmacist – the choice is made independently [10–12]. Thus, in the works of foreign [13, 14] and domestic [15, 16] scientists note and discuss the facts of self- prescribing and self-medication of a number of drugs and BAS, including multivitamins, various segments of the population, even pregnant women [10, 17]. And in the work of Zeru N. and co-authors [18] it is noted that this phenomenon is observed and is quite common among students. Own research was conducted by processing the answers of respondents obtained during the anonymous survey on a previously developed questionnaire. 3. Research results Thus, the majority of pharmacy visitors we sur- veyed were aged 35–55, about the same number of men and women who mostly lived in Kyiv region (87 %), were not students and did not have a bachelor's or mas- ter's degree, and did not have attitude to education in the field of health care. At the same time, there are data [3, 19, 20] on dif- ferent approaches to drug choice by ordinary citizens, the feasibility of which in some cases is questionable, despite the existence of scientifically sound principles [4, 6, 16]. Summarizing the information obtained during the processing of questionnaires with the answers of phar- macy visitors, it can be noted that the surveyed group of respondents showed some interest and indifference to the discussed aspects, but often there is a noticeable lack of knowledge in this regard. Given the above, the study and analysis of ap- proaches to the choice of multivitamins by consumers is of interest. The aim of the research – determining the need to raise public awareness of multivitamins and criteria for their rational choice. This may be due to the low percentage of re- spondents with medical and / or pharmaceutical educa- tion, and, in particular, proves the feasibility of raising awareness of the general public on the subject of this work. Biological research 2. Materials and methods of the research For example, very low public awareness (Table 1) was recorded on the definition of “vitamins” (almost 80 % of respondents did not answer the question), the main functions of vitamins in the human body (47 % of respondents did not answer), the classification of vitamins (about 90 % did not answer). In addition, a very important and dangerous fact of the predominant lack of necessary knowledge on the side effects of multivitamins was revealed, namely, no meaningful answers were received to questions about the possibil- ity of side effects or their examples on average in al- most half of respondents (41–65 %). This indicates a lack of awareness of the risk of taking this group of drugs. To achieve the goal of the study, it was necessary to develop a questionnaire for pharmacy visitors and conduct an anonymous survey. All adult visitors to the pharmacy were included in the survey. An anonymous survey was conducted in October- November 2020. among visitors to pharmacies located in the city of Slavutych, Kyiv region. All participants re- ceived informational consent for the study. To conduct the survey, a questionnaire “Assess- ment of public awareness of the principles of rational choice of multivitamin drugs” was developed, which consisted of three parts and contained 32 questions. The first part of the questionnaire contained ques- tions with bibliographic data (age, gender, place of resi- Biological research 5 Scientific Journal «ScienceRise: Biological Science» №4(29)2021 Table 1 Low public awareness of the surveyed aspects Aspect of the survey Awareness of the population, % 1. Definition of “vitamins” ≈20 2. Classification of vitamins ≈10 3. Types of vitamin therapy 1 4. The main functions of vitamins ≈53 5. Information about the side effects of vitamins ≈50 6. Incompatibility of vitamins in the drug ≈10 7. The difference between BAS and drugs ≈15 8. Danger of vitamin overdose >80 the results obtained in the analysis of issues related to sources of information taken into account when choosing a multivitamin (Fig. 1), determine this choice and contain information about the daily human need for vitamins. A similar trend is observed with regard to the is- sue of overdose of fat- and water-soluble vitamins (only less than 20 % of respondents are focused on the issue). Awareness of the population about the incompati- bility of vitamins in one dosage form was very low. 2. Materials and methods of the research Of course, the answer to this question generally requires special knowledge, but now elements of such infor- mation are also contained in popular literature. However, 90 % of respondents are not informed about this issue. In addition to processing the survey results, it was found that the aspects listed mainly in Part III of the ques- tionnaire, in particular, on the nomenclature of vitamins, determining the need for their use, approaches to choosing multivitamins, the consequences of wrong choice, etc. consumers have shown considerable awareness. In the question about the dosage of vitamins, in particular in the case of substitution prophylaxis, really impressive data were obtained: only 1 respondent gave the correct answer. It is possible that this was a person with medical or pharmaceutical education, but according to the questionnaires, 4 people have specialized educa- tion, which proves once again the need for additional in- formation to the public on this issue. For example, in the question of determining the appropriateness of the appointment of multivitamins, re- spondents showed a fairly good level of knowledge and responsibility. Thus, depending on the question, 39 % – 92 % of respondents answered that the need for multi- vitamins is determined by a doctor and that the results of tests should be taken into account (52 %), and that self- medication is not correct (also 52 % of respondents). In addition, research has also shown that the vast majority (average 85 %) of respondents do not see the difference between BAS and a drug and this fact proba- bly does not affect the choice of multivitamin consumers. The survey found that when choosing a multi- vitamin for themselves (Fig. 2) about 80 % of respond- ents are still guided by the advice of specialists with rel- evant education, namely, doctors and pharmacy staff (the frequency of visits to a doctor or pharmacist was almost the same). However, it was found that the Internet and other mass media (television, radio, etc.), in particular, adver- tising information, have a great influence on the choice and awareness of the population. This is evidenced by Biological research 44 72 38 35 10 9 0 10 20 30 40 50 60 70 80 Information from the Internet Advertising on television or in other media Personal experience of using the drug with acquaintances or relatives General personal knowledge Data from medical and / or pharmaceutical literature Other Fig. 6. Conclusions Th l i f The analysis of the results of the questionnaire de- termined the level of public awareness of general infor- mation about the pharmacology of multivitamins and the criteria for their conscious choice. From the obtained da- ta it can be concluded that on many questions the re- spondents showed insufficient knowledge, which justi- fies the need for additional information about multivita- mins, and also indicates that specialist with a pharmaceu- tical education or a doctor will professionally help to de- cide on the choice of a multivitamin preparation.. However, despite the originality of this study, it should be noted that it was conducted by us in only one region of Ukraine and reflects the views of a relatively small number of respondents, mostly people without spe- cial (medical or pharmaceutical) education. In addition, it can be noted that the limitation of our study is the fact that it may be appropriate to conduct a similar survey among pharmacy staff, as well as to compare the situation in this regard in other regions of Ukraine. Mostly the population lacks knowledge on the is- sues listed in Part II of the questionnaire, namely, on general information about the biological and pharmaco- logical properties of vitamins. In addition, both the development of the question- naire and its analysis were carried out by us personally, which cannot exclude a somewhat one-sided approach to the evaluation of the obtained data. It is established that the information and decisions of the respondents are significantly influenced by data obtained from the Internet or other media, including ad- vertising information. These shortcomings and limitations of the study are a prerequisite for our further research and develop- ment, the relevance and feasibility of which is confirmed by the availability of similar studies in the world on as- pects of self-administration and choice of different groups of drugs and BAS, including herbal medicines, vitamins and mineral complexes, non-narcotic analge- sics, etc. [10, 14, 15, 18]. 2. Materials and methods of the research 1. The impact of the media and the Internet on respondents: sources of information that guide the choice of multivitamin Fig. 1. The impact of the media and the Internet on respondents: sources of information that guide the choice of multivitamin 6 №4(29)2021 Scientific Journal «ScienceRise: Biological Science» Drug selected at the pharmacy; 38 % Ask my doctor for advice; 41 % Advertising of the drug in the media ; 9 % Choose a drug on the Internet; 5 % On the advice of friends; 4 % Study the instructions for various drugs; 3 % Fig. 2. Distribution of respondents' views when choosing a multivitamin for themselves On the advice of friends; 4 % Study the instructions for various drugs; 3 % Choose a drug on the Internet; 5 % Drug selected at the pharmacy; 38 % Fig. 2. Distribution of respondents' views when choosing a multivitamin for themselves At the same time, a large number of people agree to be guided in choosing a multivitamin or studying their range of information from the media, in particular, adver- tising (45–72 %) and information from the Internet (19–44 %). own multivitamins and other remedies. In this and other works [19, 21–23], researchers also use person- ally designed questionnaires to interview the popula- tion. And the result of the data received by them is confirmation of the opinion on the need for additional information and explaining to the public the responsi- bility for self-medication, its possible negative conse- quences, as well as aspects of the correct choice of drugs [11, 13, 20, 24]. 4. Discussion of research results Thus, as a result of our study, we studied and as- sessed the level of public awareness of pharmacological properties and the choice of multivitamins. This was done for the first time among visitors to pharmacies lo- cated in the city of Slavutych, Kyiv region, according to a specially designed author's questionnaire. Thus, given the above, our study can also be con- sidered timely and promising. Financing The study was conducted without financial sup- port. port. port. port. References 1. Gromov, I. (2017). Sovremennaia kontseptsiia primeneniia poli 1. Gromov, I. (2017). Sovremennaia kontseptsiia primeneniia polivitaminov. Farmatsevticheskie vedomosti, 11 (47), 10–13. 1. Gromov, I. (2017). Sovremennaia kontseptsiia primeneniia polivitaminov. Farmatsevticheskie vedomosti, 11 (4 Sovremennaia kontseptsiia primeneniia polivitaminov. Farmatsevticheskie vedomosti, 11 (47), 10–13. 2. Yeltsova, L. B., Omelchuk, S. Т. (2019). Evaluation of daily fruit and vegetable consumption by students’ y and Nutrition Problems of Ukraine, 2 (49), 46–54. doi: http://doi.org/10.33273/2663-9726-2018-49-2-46-54 L. B., Omelchuk, S. Т. (2019). Evaluation of daily fruit and vegetable consumption by students’ youth. One Problems of Ukraine, 2 (49), 46–54. doi: http://doi.org/10.33273/2663-9726-2018-49-2-46-54 3. Afanaseva, T. G. (2008). Marketingovyi analiz farmatsevticheskogo rynka vitaminov. Voronezh, 60. g y g y 4. Spirichev, V. B. (2010). Nauchnoe obosnovanie primeneniia vitaminov v profilakticheskoi i lechebnoi tseliakh. Soobschenie 1. Nedostatok vitaminov v ratsione sovremennogo cheloveka: prichiny, posledstviia i puti korrektsii. Voprosy pitaniia, 5, 4–14. 4. Spirichev, V. B. (2010). Nauchnoe obosnovanie primeneniia vitaminov v profilakticheskoi i lechebnoi tseliakh. Soobschenie 1. Nedostatok vitaminov v ratsione sovremennogo cheloveka: prichiny, posledstviia i puti korrektsii. Voprosy pitaniia, 5, 4–14. 5. Slobodkin, V. I., Levytska, V. M., Senatova, A. O. (2014). Bioethical aspects of vitamins in medical practice. Yedyne zdorov`ya ta problemy kharchuvannia Ukrainy, 2 (41), 54–58. 5. Slobodkin, V. I., Levytska, V. M., Senatova, A. O. (2014). Bioethical aspects of vitamins in medical practice. Yedyne zdorov`ya ta problemy kharchuvannia Ukrainy, 2 (41), 54–58. 6. Dorokhova, L. P. (2017). Doslidzhennia stanu ukrainskoho rynku vitaminnykh preparativ. Promyslova farmatsiia. Kharkiv: NFaU, 42–45. 6. Dorokhova, L. P. (2017). Doslidzhennia stanu ukrainskoho rynku vitaminnykh preparativ. Promyslova farmatsiia. Kharkiv: NFaU, 42–45. 7. Puzak, N. O., Orlovetska, N. F. (2020). Neobkhidnist vitaminiv u nashomu zhytti ta marketynhovyi analiz ukrainskoho rynku vitaminnykh preparativ. Menedzhment i marketynh u skladi suchasnoi ekonomiky, nauky, osvity, praktyky. Kharkiv: NFaU, 294–296. 7. Puzak, N. O., Orlovetska, N. F. (2020). Neobkhidnist vitaminiv u nashomu zhytti ta marketynhovyi analiz ukrainskoho rynku vitaminnykh preparativ. Menedzhment i marketynh u skladi suchasnoi ekonomiky, nauky, osvity, praktyky. Kharkiv: NFaU, 294–296. 8. Shestopalov, A. E., Dmitriev, A. V., Zingerenko, V. B. (2011). Kliniko-farmakologicheskie aspekty primeneniia multivitaminnykh kompleksov dlia parenteralnogo vvedeniia (obzor literatury). Meditsina neotlozhnykh sostoianii, 5 (36), 35–45. 9. Spravochnik lekarstvennykh preparatov Kompendium. Available at: https://Compendium.com.ua 10. Alsous, M. M., Al-Azzam, S. I., Nusair, M. B. Alnahar, S. A., Obeidat, N. A. (2021). Self-medication among pregnant women attending outpatients` clinics in Northern Jordan: a cross-sectional study. Pharmacology Research & Perspectives, 9 (2). Acknowledgements The authors of the article express their gratitude to the 5th year student of the National University of Phar- macy Poltoratskaya S. S. for participating in data collec- tion for this study. Such measures, in our opinion, will improve pub- lic awareness of the research issues and help increase the effectiveness and safety of vitamin therapy. References doi: http://doi.org/10.1002/prp2.735 p g p p 11. Aziz, M. M., Masood, I., Yousaf, M., Saleem, H., Ye, D., Fang, Y. (2018). Pattern of medication selling and self- medication practices: A study from Punjab, Pakistan. PLOS ONE, 13 (3). doi: http://doi.org/10.1371/journal.pone.0194240 12. Ward, E. (2014). Addressing nutritional gaps with multivitamin and mineral supplements. Nutrition Journal, 13 (1). doi: http://doi.org/10.1186/1475-2891-13-72 13. Mathias, E. G., D’souza, A., Prabhu, S. (2020). Self-Medication Practices among the Adolescent Population of South Karnataka, India. Journal of Environmental and Public Health, 2020. doi: http://doi.org/10.1155/2020/9021819 14. Hashemzaei, M., Afshari, M., Koohkan, Z., Bazi, A., Rezaee, R., Tabrizian, K. (2021). Knowledge, attitude, and practice of pharmacy and medical students regarding self-medication, a study in Zabol University of Medical Sciences; Sistan and Baluchestan province in south-east of Iran. BMC Medical Education, 21 (1). doi: http://doi.org/10.1186/s12909-020-02374-0 15. Dorokhova, L. P. (2017). Doslidzhennia faktoriv, shcho vplyvaiut na vybir vitaminnykh preparativ. Suchasni dosiahnennia farmatsevtychnoi tekhnolohii ta biotekhnolohii, 3, 92–95. 16. Tkachova, O. V., Horkusha, N. O., Silaev, A. O. (2018). The assessment of professional competence of pharmaceutical employees on the issues of antiviral and immunostimulating drugs in the treatment of children with ARVI. Clinical pharmacy, 22 (2), 44–51. doi: http://doi.org/10.24959/cphj.18.1464 17. Pereira, G., Surita, F. G., Ferracini, A. C., Madeira, C. D. S., Oliveira, L. S., Gava Mazzola, P. (2021). Corrigendum: Self- Medication Among Pregnant Women: Prevalence and Associated Factors. Frontiers in Pharmacology, 12. doi: http://doi.org/10.3389/ fphar.2021.810762 18. Zeru, N., Fetene, D., Geberu, D. M., Melesse, A. W., Atnafu, A. (2020). Self-Medication Practice and Associated Factors Among University of Gondar College of Medicine and Health Sciences Students: A Cross-Sectional Study. Patient Preference and Adherence, 14, 1779–1790. doi: http://doi.org/10.2147/ppa.s274634 p g pp 19. Dickinson, A., MacKay, D., Wong, A. (2015). Consumer attitudes about the role of multivitamins and other dietary supplements: report of a survey. Nutrition Journal, 14 (1). doi: http://doi.org/10.1186/s12937-015-0053-9 20. Kotta, S., Gadhvi, D., Jakeways, N., Saeed, M., Sohanpal, R., Hull, S. et. al. (2015). “Test me and treat me” – attitudes to vitamin D deficiency and supplementation: a qualitative study. BMJ Open, 5 (7), e007401. doi: http://doi.org/10.1136/bmjopen- 2014-007401 21. Lutz, B. H., Miranda, V. I. A., Silveira, M. P. T., Dal Pizzol, T. da S., Mengue, S. S., da Silveira, M. F. et. al. (2020). Medication Use among Pregnant Women from the 2015 Pelotas (Brazil) Birth Cohort Study. International Journal of Environmental Research and Public Health, 17 (3), 989. Conflict of interests Conflict of interests The authors declare there is no conflict of interests. – offer pharmacy staff to create stands with in- formation about the properties of vitamins and the range of vitamin-containing products in the pharmaceutical market of Ukraine, as well as place information about sources of accurate information about daily human needs for vitamins (depending on age, sex, physiological condi- tion) and the need to pay attention to quantitative and qualitative composition of the multivitamin preparation before its use. 6. Conclusions Th l i f Given the above, the following recommendations were made: – during the educational process in medical and pharmaceutical institutions, as well as in advanced train- ing courses for specialists in medicine and pharmacy, it is advisable to emphasize the aspects of correct and safe choice and use of multivitamin drugs; – during the educational process in medical and pharmaceutical institutions, as well as in advanced train- ing courses for specialists in medicine and pharmacy, it is advisable to emphasize the aspects of correct and safe choice and use of multivitamin drugs; For example, Pereira G. and co-authors [17] found that about 36 % of pregnant women choose their Biological research 7 №4(29)2021 Scientific Journal «ScienceRise: Biological Science» 22. Liu, H., Zhang, S., Zou, H., Pan, Y., Yang, Q., Ouyang, Y. et. al. (2019). Dietary Supplement Use Among Chinese Primary School Students: A Cross-Sectional Study in Hunan Province. International Journal of Environmental Research and Public Health, 16 (3), 374. doi: http://doi.org/10.3390/ijerph16030374 Scientific Journal «ScienceRise: Biological Science» p g j p 23. Cybulski, M., Cybulski, L., Krajewska-Kulak, E., Orzechowska, M., Cwalina, U. (2018). Preferences and attitudes of older adults of Bialystok, Poland toward the use of over-the-counter drugs. Clinical Interventions in Aging, 13, 623–632. doi: http://doi.org/10.2147/cia.s158501 References doi: http://doi.org/10.3390/ijerph17030989 Biological research Biological research 8 Scientific Journal «ScienceRise: Biological Science» Scientific Journal «ScienceRise: Biological Science» №4(29)2021 22. Liu, H., Zhang, S., Zou, H., Pan, Y., Yang, Q., Ouyang, Y. et. al. (2019). Dietary Supplement Use Among Chinese Primary School Students: A Cross-Sectional Study in Hunan Province. International Journal of Environmental Research and Public Health, 16 (3), 374. doi: http://doi.org/10.3390/ijerph16030374 23. Cybulski, M., Cybulski, L., Krajewska-Kulak, E., Orzechowska, M., Cwalina, U. (2018). Preferences and attitudes of older adults of Bialystok, Poland toward the use of over-the-counter drugs. Clinical Interventions in Aging, 13, 623–632. doi: http://doi.org/10.2147/cia.s158501 24. Piekara, A., Krzywonos, M., Kaczmarczyk, M. (2020). What Do Polish Parents and Caregivers Think of Dietary Supplements for Children Aged 3–12? Nutrients, 12 (10), 3076. doi: http://doi.org/10.3390/nu12103076 Tetiana Kutsenko, PhD, Associate Professor, Department of Pharmacology and Pharmacotherapy, National University of Pharmacy, Pushkinska str., 53, Kharkiv, Ukraine, 61002 Dmitro Semeniv, Doctor of Pharmaceutical Sciences, Professor, Head of Department, Department of Pharmacy, Drug Technology and Pharmaceutical Management, Kyiv International University, Lvivska str., 49, Kyiv, Ukraine, 03179 Katherina Shchokina, Doctor of Pharmaceutical Sciences, Professor, Department of Pharmacology and Pharmacotherapy, National University of Pharmac, Pushkinska str., 53, Kharkiv, Ukraine, 61002 Galina Belik, PhD, Associate Professor, Department of Pharmacology and Pharmacotherapy, National University of Pharmacy, Pushkinska str., 53, Kharkiv, Ukraine, 61002 Yurii Stoletov, PhD, Associate Professor, Department of Pharmacology and Pharmacotherapy, National University of Pharmacy, Pushkinska str., 53, Kharkiv, Ukraine, 61002 Olga Getalo, PhD, Associate Professor, Department of Pharmacy, Drug Technology and Pharmaceutical Management, Kyiv International University, Lvivska str., 49, Kyiv, Ukraine, 03179 Corresponding author: Galina Belik, e-mail: belik-69@ukr.net Biological research 9
https://openalex.org/W2161654338	https://europepmc.org/articles/pmc3321941?pdf=render	English	null	Use of Norovirus Genotype Profiles to Differentiate Origins of Foodborne Outbreaks	Emerging infectious diseases	2,010	cc-by	7,349	Use of Norovirus Genotype Proﬁ les to Differentiate Origins of Foodborne Outbreaks Linda Verhoef, Harry Vennema, Wilfrid van Pelt, David Lees, Hendriek Boshuizen, Kathleen Henshilwood, and Marion Koopmans, on behalf of the Food-Borne Viruses in Europe Network1 Because secondary transmission masks the connec- tion between sources and outbreaks, estimating the pro- portion of foodborne norovirus infections is difﬁ cult. We studied whether norovirus genotype frequency distributions (genotype proﬁ les) can enhance detection of the sources of foodborne outbreaks. Control measures differ substan- tially; therefore, differentiating this transmission mode from person-borne or food handler–borne outbreaks is of public health interest. Comparison of bivalve mollusks collected during monitoring (n = 295) and outbreak surveillance strains (n = 2,858) showed 2 distinguishable genotype proﬁ les in 1) human feces and 2) source-contaminated food and bi- valve mollusks; genotypes I.2 and I.4 were more frequently detected in foodborne outbreaks. Overall, ≈21% of all out- breaks were foodborne; further analysis showed that 25% of the outbreaks reported as food handler–associated were probably caused by source contamination of the food. contaminated during processing, preparation or serving; sewage-contaminated water used for consumption, cultiva- tion or irrigation of food; contaminated aerosols resulting from vomiting; and environmental contamination (3,4). Five genogroups have been described (GI–V), subdivided into at least 40 genetic clusters (5,6). To implement effective measures for prevention, rec- ognition of the transmission routes is necessary. Conse- quently, the relative importance of different transmission routes in the total number of outbreaks is of interest for es- timation of cost-effectiveness of reducing the number and size of norovirus outbreaks, particularly for geographically disseminated foodborne outbreaks. Such outbreaks are dif- ﬁ cult to detect when the primary introduction of viruses through food occurs simultaneously in several countries or continents (7–9). Globalization of the food industry with consequential international distribution of products in- creases the risk for such outbreaks. For example, the ﬁ rst reported GII.b outbreak occurred in August 2000 during a large waterborne outbreak in southern France (10). After this outbreak, in December and January, 4 multipathogen and oyster-related outbreaks with this newly emerging genotype were reported from France. In the same period, Denmark, Finland, and the Netherlands reported norovi- rus cases resulting from oysters originating from a French batch that probably was sold in these countries, as well as in Sweden, Italy, and Belgium (6). All these outbreaks seemed to involve closely related and newly detected GII.b strains. 1Additional members of the Food-Borne Viruses in Europe Network are listed at the end of this article. Author afﬁ liations: National Institute for Public Health and the Envi- ronment, Bilthoven, the Netherlands (L. Verhoef, H. Vennema, W. van Pelt, H. Boshuizen, M. Koopmans); and Centre for Environ- ment, Fisheries and Aquaculture Science, Weymouth, UK (D. Lees, K. Henshilwood) DOI: 10.3201/eid1604.090723 Human Surveillance Data From January 1999 through December 2004, FBVE collected molecular information on 2,727 norovirus out- breaks and sporadic cases in Denmark, Finland, France, Germany, England and Wales, Hungary, Ireland, Italy, the Netherlands, Norway, Sweden, Slovenia, and Spain (20,21). Although the name FBVE suggested a foodborne focus, the network actually investigated outbreaks from all modes of transmission to obtain a comprehensive overview of viral activity in the community (strengths and limitations of the FBVE data collection were described by Kroneman et al. [20]; to compare newly detected strains with the FBVE da- tabase and ﬁ nd potential linked outbreaks, we used a com- parison tool [www.rivm.nl/bnwww]). Data were reported to FBVE at outbreak level; therefore, no informed consent was needed. Outbreaks were categorized as follows on the basis of the cause of infection as reported in the surveil- lance system: We studied whether the genotype frequency distribu- tions (genotype proﬁ les) of strains can be used to differen- tiate foodborne outbreaks related to contamination early in the food chain (i.e., during primary production) from those related to contamination later in the food chain (i.e., dur- ing preparation or serving). If so, detection of food origins likely to cause geographically disseminated outbreaks will be enhanced. We considered methods for attribution to multiple sources commonly applied to Salmonella infec- tions (13) because different transmission routes involved in norovirus infections can disguise the foodborne origin. However, such methods require strain collections represen- tative of noroviruses in the potential sources that are as yet unavailable because of difﬁ culties in the direct detection of viruses in food (14–16). Therefore, we compared 2 strain collections: noroviruses identiﬁ ed through ﬁ lter-feeding bi- valve mollusk monitoring representing source contamina- tion of food and noroviruses collected through systematic surveillance of illness in the population. The ﬁ rst was col- lected by the European Community Reference Laboratory for Monitoring Bacteriological and Viral Contamination of Bivalve Mollusks during 1995–2004 (17) and the second by the Food-Borne Viruses in Europe (FBVE) network, which has conducted surveillance for norovirus outbreaks in Europe since 1999. Prior investigation of the FBVE da- tabase of systematically collected epidemiologic and mi- crobiological norovirus surveillance data (6) showed that the epidemiology of norovirus outbreaks in Europe varies between genogroups. Methods were detected in Germany, the United Kingdom, Spain, Slovenia, and Sweden (11,12). Another example of a geo- graphically disseminated outbreak was several seemingly independent norovirus outbreaks in Denmark that were traced back to consumption of raspberries from Poland. Although raspberries from this contaminated batch were exported to other European countries, an alert in the Rapid Alert System for Food and Feed did not result in further linked outbreak reports (7). Thus, geographically dissemi- nated outbreaks are sometimes identiﬁ ed but only after the joint and exhaustive efforts of different organizations, such as laboratory networks, food safety authorities, and public health institutions. Knowledge of the proportion of geographically disseminated foodborne outbreaks to all norovirus outbreaks will therefore provide insight into the cost-effectiveness of such efforts. were detected in Germany, the United Kingdom, Spain, Slovenia, and Sweden (11,12). Another example of a geo- graphically disseminated outbreak was several seemingly independent norovirus outbreaks in Denmark that were traced back to consumption of raspberries from Poland. Although raspberries from this contaminated batch were exported to other European countries, an alert in the Rapid Alert System for Food and Feed did not result in further linked outbreak reports (7). Thus, geographically dissemi- nated outbreaks are sometimes identiﬁ ed but only after the joint and exhaustive efforts of different organizations, such as laboratory networks, food safety authorities, and public health institutions. Knowledge of the proportion of geographically disseminated foodborne outbreaks to all norovirus outbreaks will therefore provide insight into the cost-effectiveness of such efforts. Data Sources We used 2 broad databases reﬂ ecting norovirus preva- lence within the European countries under surveillance. These databases provided us the opportunity to compare genotype proportions as detected in outbreaks, i.e., human surveillance data, with those detected in source-contaminat- ed food products, i.e., bivalve mollusks monitoring data. Use of Norovirus Genotype Proﬁ les to Differentiate Origins of Foodborne Outbreaks After active case identiﬁ cation, further linked cases N N oroviruses are members of the family Caliciviridae and recognized as major pathogens in outbreaks of gastroenteritis worldwide. Because these viruses have en- vironmental stability (1), ability to use different transmis- sion routes, and low infective doses (2), their source may be difﬁ cult to determine during an outbreak. Transmission can occur through contact with shedding persons; food Author afﬁ liations: National Institute for Public Health and the Envi- ronment, Bilthoven, the Netherlands (L. Verhoef, H. Vennema, W. van Pelt, H. Boshuizen, M. Koopmans); and Centre for Environ- ment, Fisheries and Aquaculture Science, Weymouth, UK (D. Lees, K. Henshilwood) 617 Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 16, No. 4, April 2010 RESEARCH Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 16, No. 4, April 2010 Human Surveillance Data An analysis of the properties of re- ported outbreaks indicated a clear difference between GII.4 strains and other noroviruses; non-GII.4 strains were found more frequently in outbreaks with a foodborne mode of transmission, and GII.4 strains were found more frequently in healthcare settings with person-to-person transmission (18,19). Here we demonstrate that further speciﬁ cation into genotypes shows additional differences in the epidemiol- ogy of norovirus outbreaks. • Foodborne-food (FB-food) when an outbreak was reported to be caused by food and the outbreak strain was detected in food; • Foodborne-feces (FB-feces) when an outbreak was reported to be caused by food and the outbreak strain was detected in human feces only; • Foodborne (FB) when an outbreak was classiﬁ ed as FB-food or FB-feces; • Food handler–borne (FHB) when an outbreak was reported to be caused by an infected food handler contaminating the food and the outbreak strain was detected in human feces; • Person-borne (PB) when an outbreak was reported to be caused by person-to-person transmission and the outbreak strain was detected in human feces; • Unknown (UN) when the mode of transmission was not reported or was reported to be unknown and the outbreak strain was detected in human feces. 618 Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 16, No. 4, April 2010 Origins of Foodborne Outbreaks low to be ascribed a separate genotype and excluded. This was the situation for GII.18 and 6 clusters of nonassigned GII strains (n = 25, 1%). When the mode of transmission was not reported but information was given in text data ﬁ elds, this information was used to categorize the outbreak. Because we were interested in the origin of the virus, we categorized out- breaks involving PB transmission but starting with food as FB-food, FB-feces, or FHB, depending on available infor- mation. Strains detected in sporadic cases were clustered into outbreaks if information was available. The remaining strains detected in sporadic cases were considered of inter- est with respect to the genotypes causing human illness and representative of potential unreported outbreaks. When we detected multiple genotypes during an outbreak or in spo- radic cases, we recorded each genotype. Bivalve Mollusk Monitoring Data The European Community Reference Laboratory for Monitoring Bacteriological and Viral Contamination of Bi- valve Mollusks systematically collected sequence data on norovirus strains routinely detected in bivalve mollusks in Europe. During January 1999–December 2004, the labo- ratory systematically collected 295 strain sequences with region A sequence lengths varying from 76 to 78 nt. These strain sequences were detected as part of production area monitoring studies or outbreak investigations of gastroen- teritis in Denmark, England and Wales, Ireland, Scotland, and Spain. All samples were ﬁ rst routinely tested with GI and GII PCR methods; then all positive samples were cloned (22), resulting in a representative reﬂ ection of noro- virus presence in bivalve shellﬁ sh. If we detected multiple genotypes in 1 sample, we recorded each genotype. Second, to differentiate the remaining genotype pro- ﬁ les detected in outbreaks, we used the genotype proﬁ les of the 2 main transmission modes to be distinguished during an outbreak investigation. For each genotype in the human surveillance collection, the fraction of outbreaks of known origin being FB (i.e., FB-food and FB-feces) or PB was estimated on the basis of the proportion of FB outbreaks of all FB + PB outbreaks in each genotype. We used the esti- mated proportion of FB outbreaks of all FB + PB outbreaks in each genotype to estimate the probability that an FHB or UN outbreak was foodborne. We calculated 95% con- ﬁ dence intervals (CIs) using Monte Carlo simulation with 10,000 random draws from the β distributions, which are the posterior probabilities of the proportions (24). Assignment of Genotypes Strains were genotyped by using a previously de- scribed method for sequence analysis of a fragment of the RNA-dependent RNA polymerase gene regions B, C, and D (23) because these regions were used in the FBVE network. From the start, the network used sequence-based genotyping of the then most commonly used diagnostic PCR fragment, targeting the RNA-dependent RNA poly- merase gene. Since then, however, it has become clear that recombination is common and mainly occurs in the area be- tween the overlap between the polymerase and the capsid gene. Therefore, capsid-based and polymerase-based typ- ing may be discordant. Genotype assignment was therefore performed only after clustering of query strains against all relevant available sequences in the FBVE database (M. Koopmans et al., unpub. data). This process resulted in the genotyping of all but 68 (2%) strains. Genotypes were clas- siﬁ ed on the basis of their similarity to reference strains representing known genotypes by using the norovirus typing library (www.noronet.nl/nov_quicktyping). If the (clustered) genotypes occurred <5 times in our 5-year cov- ering data selection, the frequencies were considered too Data Analysis First, we compared the genotype frequency distribu- tions detected in outbreak categories reported as FB-food, FB-feces, FHB, PB, and UN and in routinely tested bivalve mollusks. To evaluate the correlation and measures of asso- ciation of these 6 proportional proﬁ les, Pearson correlation coefﬁ cient ρ was calculated on the basis of frequencies (ρ1) and logarithm (ρ2) of the frequencies of 22 genotypes, as well as Cramer V and simulated p values by using 20,000 replications with the exact variant of the χ2 test. The explor- atory technique correspondence analysis allows for exam- ining the structure of categorical variables in a multiway table and was used to visualize the measure of correspon- dence in the 6 genotype proﬁ les. p values <0.05 were con- sidered signiﬁ cant. Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 16, No. 4, April 2010 Results Of 3,022 detected noroviruses, 25 (1%) were excluded because of low frequencies; for 68 (2%), assignment of a genotype was not possible because of short sequences or in- ability of the method applied to type the detected norovirus beyond its genogroup. Of the remaining 2,929 strains, 71 (2%) could not be linked to epidemiologic data, and there- fore their origin remained unknown, leaving 2,858 (95%) strains for analysis: 922 originating from PB outbreaks, 24 from FB-food outbreaks, 151 FB-feces outbreaks, 20 FHB outbreaks, 1,446 UN outbreaks, and all 295 bivalve mol- lusk monitoring strains. Among the outbreaks of known origin, 175 (16%) of 1,117 were reported to be FB (i.e., FB-food and FB-feces). The proportion of genogroup I was signiﬁ cantly higher in bivalve mollusks (137/295, 46%) than in infected hu- mans (313/2,539, 12%) (Table 1). All genotypes detected in bivalve mollusks were also detected in humans; however, 9 genotypes causing human illness were not detected in bi- 619 Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 16, No. 4, April 2010 RESEARCH Table 1. Number of norovirus strains detected in samples from humans, bivalve mollusks, and food, 1999–2004* Genotypes Human surveillance, no. strains Bivalve monitoring, no. strains Total no. Results Pol, polymerase; Cap, capsid; FB-food, foodborne-food, i.e., an outbreak was reported to be caused by food and the outbreak strain was detected in food; FB-feces, foodborne-feces, i.e., an outbreak was reported to be caused by food and the outbreak strain was detected in human feces only; FHB, food handler–borne, i.e., an outbreak was reported to be caused by an infected food handler contaminating the food and the outbreak strain was detected in human feces; PB, person-borne, i.e., an outbreak was reported to be caused by person-to-person transmission and the outbreak strain was detected in human feces; UN, unknown, i.e., the mode of transmission was not reported or was reported to be unknown and the outbreak strain was detected in human feces. signiﬁ cant correlation coefﬁ cient (ρ = 0.81, p <0.001). The logarithm of the frequencies, ρ2 (Table 2), is less sensitive to peak frequencies of genotypes and therefore capable of differentiating proﬁ les with respect to the rare genotypes and approaching the Cramer V. Cramer V and ρ2 show less clear association of proﬁ les, with diverging results for the FHB and UN proﬁ les. valve mollusks. Overall, the II.4 genotype was responsible for most of the human outbreaks (1,326/2,539, 52%), fol- lowed by II.b (328/2,539, 13%) and II.7 (156/2,539, 6%). y ( , , ) ( , , ) We visualized genotype frequency distributions as proﬁ les for the observed categories of outbreaks and sorted them for their relevance in UN outbreaks, present- ed with different scales allowing for proportional com- parison (online Appendix Figure 1, www.cdc.gov/EID/ content/16/4/617-appF1.htm). The genotype proﬁ les vary between these groups. The correlation coefﬁ cients based on frequencies, ρ1, showed that 2 genotype proﬁ les were distinguishable (Table 2): 1 proﬁ le typically seen in human feces (FB-feces, FHB, or PB), and another proﬁ le typi- cally detected in sources other than human feces, i.e., in food (FB-food) or bivalve mollusks. The ρ1 reﬂ ects some genotypes frequently and others rarely seen in FB-food and bivalve mollusks. Because FB-food strains include oyster- related outbreaks as well, we assumed that the correlation between FB-food and bivalve mollusks can be explained partly by these oyster-related outbreaks. We therefore cal- culated an additional correlation coefﬁ cient using the 14 strains detected in food items other than bivalve mollusks. Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 16, No. 4, April 2010 Results strains Pol-based Cap-based FB-food FB-feces FHB PB UN Genogroups I.1 I.1 1 8 0 5 18 0 32 I.2 0 6 0 1 32 8 47 I.3 I.3 0 8 3 16 80 13 120 I.4 I.4 9 8 1 8 46 86 158 I.5 0 0 0 1 5 3 9 I.6 I.6 2 3 1 21 17 25 69 I.7 0 1 0 0 7 2 10 NA I.a NA I.a 0 1 0 0 4 0 5 II.1 0 5 2 12 94 7 120 II.2 II.2 0 13 1 27 66 0 107 II.3 0 1 0 1 38 11 51 II.3R II.3 0 1 0 1 41 2 45 II.4 II.4 5 47 9 681 584 63 1,389 II.5 0 3 0 6 12 0 21 II.8 1 0 1 1 13 0 16 NA II.a 0 0 0 2 7 0 9 NA II.c 0 2 0 8 31 1 42 NA II.d 0 1 0 3 8 0 12 IV.1 0 2 0 1 8 0 11 Recombinants NA II.b II.1, II.2, II.3 4 23 1 100 200 63 391 II.1 II.10 0 0 0 8 19 11 38 II.7 II.6, II.7 2 18 1 19 116 0 156 Total 24 151 20 922 1,446 295 2,858 Pol, polymerase; Cap, capsid; FB-food, foodborne-food, i.e., an outbreak was reported to be caused by food and the outbreak strain was detected in food; FB-feces, foodborne-feces, i.e., an outbreak was reported to be caused by food and the outbreak strain was detected in human feces only; FHB, food handler–borne, i.e., an outbreak was reported to be caused by an infected food handler contaminating the food and the outbreak strain was detected in human feces; PB, person-borne, i.e., an outbreak was reported to be caused by person-to-person transmission and the outbreak strain was detected in human feces; UN, unknown, i.e., the mode of transmission was not reported or was reported to be unknown and the outbreak strain was detected in human feces. Results Despite low numbers, this calculation resulted in a high, Table 2 shows the quantiﬁ cation of association; the associated genotype proﬁ les illustrated by correspondence analysis is shown in the Figure. The values of the 6 col- umns in Table 1 can be considered coordinates in a 6-di- mensional space, and the distances are computed. These distances summarize information about the similarity be- tween the rows in Table 1. Dimension 1 may be considered to differentiate transmission modes explaining 59.12% of the correspondence, conﬁ rming that the proﬁ les found in bivalve mollusks and FB-food are similar with regard to the pattern of relative frequencies in genotypes (rows in Table 1) and differ from those in PB. It also shows that the FHB, UN, and FB-feces proﬁ les are mutually similar, with their distance somewhere between the PB and FB-food/bivalve mollusk proﬁ les. Dimension 2 may represent dual origin, explaining an additional 31.40%, showing that FB-feces, Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 16, No. 4, April 2010 620 Origins of Foodborne Outbreaks FHB, and UN mutually correspond and differ from FB- food, bivalve mollusks, and PB that mutually correspond. ferentiate foodborne outbreaks caused by food contamina- tion early in the food chain from those caused by food han- dlers contaminating food. Our study is one step in deriving practical applicable information from the existing record and possible only through the availability of continuously updated databases containing detailed epidemiologic data and virus characterization. We conﬁ rmed a signiﬁ cant dif- ference in the GI:GII ratio; GI strains were more prevalent in bivalve mollusks. On the basis of the 5-year strain col- lections, some genotypes (I.2 and I.4) suggest FB instead of PB preference, and others (II.2 and II.6/II.7) are com- monly seen in outbreaks but not detected in bivalve mol- lusks (and FB-food). Strains detected in food that caused outbreaks (FB-food) showed a genotype proﬁ le similar to those in bivalve mollusk monitoring and dissimilar to the proﬁ le detected in human feces (i.e., FB-feces, FHB, PB, UN) with respect to the frequently seen genotypes. This ﬁ nding may reﬂ ect the ability of these genotypes to survive outside humans or their diminished ability to spread or rep- licate within the human population. Genotype proﬁ les of FHB and UN resulted in diverging association outcomes, which may reﬂ ect their potential dual origin. Results When we compared the proportions of genotypes de- tected in FB outbreaks with those in PB outbreaks, we de- tected genotypes I.2 and I.4 signiﬁ cantly more frequently in FB outbreaks (online Appendix Figure 2, www.cdc. gov/EID/content/16/4/617-appF2.htm). On the other hand, genotypes I.6, II.1W, II.2, II.4, II.b, II.c, and II.d were de- tected signiﬁ cantly more frequently in PB outbreaks. Us- ing these proportional FB and PB genotype proﬁ les and their conﬁ dence intervals to distinguish between FB and PB transmission among 20 FHB outbreaks, we could as- cribe 5 (95% CI 4–6) to FB and 15 (95% CI 14–16) to PB transmission. Ascribing 1,446 unexplained human norovi- rus outbreaks to either FB or PB transmission resulted in ≈367 (95% CI 327–417) FB outbreaks and ≈1,079 (95% CI 1,026–1,120) PB outbreaks. Overall, use of the genotype patterns increases the estimated number of FB proportion of outbreaks to 21% (547/2,563; range 20%–23%) com- pared with the 16% previously mentioned among the out- breaks of known origin. Discussion Although consumption of contaminated food causes both types of outbreaks, outbreaks resulting from infected food handlers clearly necessitate different measures than do outbreaks resulting from food contaminated early in the Our combined epidemiologic and virologic analysis demonstrated that norovirus genotype proﬁ les, derived from long-term norovirus strain collections, can be used to dif- Table 2. U1, U2, and Cramer V results with simulated p values (20,000 replications) of norovirus 6 genotype patterns as detected in routinely tested bivalve shellfish and during norovirus outbreaks, 1999–-2004* Source FB-food (p value) FB-feces (p value) FHB (p value) PB (p value) UN (p value) Bivalve mollusk (p value) FB-food ȡ1 1.00 0.48 (0.02) 0.40 (0.07) 0.43 (0.04) 0.48 (0.02) 0.91 (<0.01) ȡ2 0.46 (0.03) 0.15 (0.51) 0.34 (0.12) 0.24 (0.26) 0.47 (0.03) Cramer V 0.47 (0.01) 0.62 (0.04) 0.48 (<0.01) 0.26 (<0.01) 0.41 (0.02) FB-feces ȡ1 1.00 0.93 (<0.01) 0.92 (<0.01) 0.96 (<0.01) 0.53 (0.01) ȡ2 0.40 (0.06) 0.55 (<0.01) 0.66 (<0.01) 0.69 (<0.01) Cramer V 0.34 (0.41) 0.43 (<0.01) 0.19 (<0.01) 0.57 (<0.01) FHB ȡ1 1.00 0.97 (<0.01) 0.93 (<0.01) 0.43 (<0.05) ȡ2 0.22 (0.32) 0.39 (0.07) 0.47 (0.03) Cramer V 0.25 (<0.01) 0.09 (0.75) 0.46 (<0.01) PB ȡ1 1.00 0.96 (<0.01) 0.51 (0.01) ȡ2 0.61 (<0.01) 0.53 (0.01) Cramer V 0.42 (<0.01) 0.63 (0.01) UN ȡ1 1.00 0.59 (<0.01) ȡ2 0.65 (<0.01) Cramer V 0.48 (<0.01) Bivalve mollusk 1.00 ȡ1 = based on frequencies; ȡ2 = based on logarithm of frequencies; Cramer V, Ȥ2 test with simulated p values; FB-food, foodborne-food, i.e., an outbreak was reported to be caused by food and the outbreak strain was detected in food; FB-feces, foodborne-feces, i.e., an outbreak was reported to be caused by food and the outbreak strain was detected in human feces only; FHB, food handler–borne, i.e., an outbreak was reported to be caused by an infected food handler contaminating the food and the outbreak strain was detected in human feces; PB, person-borne, i.e., an outbreak was reported to be caused by person-to-person transmission and the outbreak; strain was detected in human feces; UN, unknown, i.e., the mode of transmission was not reported or was reported to be unknown and the outbreak strain was detected in human feces. Discussion Two-dimensional display of the correspondence analysis of 6 norovirus genotype proﬁ les based on nucleotide sequences in which points close to each other are similar with regard to the pattern of relative frequencies across genotypes. Dimension 1 explains 59.12% and dimension 2 an additional 31.40%. In dimension 1, foodborne-feces (FB-feces; i.e., outbreak reported to be caused by food with the outbreak strain detected in human feces only) and bivalve mollusk (BM) genotype proﬁ les are mutually similar and differ from other proﬁ les; the most distinct proﬁ le is person-borne (PB; i.e., an outbreak reported to be caused by person-to-person transmission with the outbreak strain detected in human feces). In dimension 2, food handler–borne (FHB; i.e., outbreak reported to be caused by an infected food handler contaminating the food with the outbreak strain detected in human feces), FB-feces, and unknown (UN; i.e., mode of transmission was not reported or was reported to be unknown with the outbreak strain detected in human feces) mutually correspond and differ from the mutually corresponding foodborne-food (FB-food; i.e., outbreak reported to be caused by food with the outbreak strain detected in food), BM, and PB. Our study has some limitations. First, our measures of association could not detect differences between genotype proﬁ les with respect to the rare genotypes. Even so, the rare outbreak or sporadic strains are of interest because they may represent potential emerging or zoonotic genotypes with consequences for public health. Types that were ini- tially rare may remain in human surveillance, as seen with the emergence of GII.b after a large waterborne outbreak (10) followed by, among others, foodborne distribution throughout Europe. Since then, GII.b strains have caused 13% of all outbreaks (Table 1), now mainly PB, suggesting good adaptation. On the other hand, if the rare types are unable to adapt for persistence in the human population, they may be repeatedly reintroduced, causing only sporad- ic cases but not outbreaks. This repeated introduction of sporadic cases would remain undetected at present because routine surveillance for sporadic cases is rare (32) and is not the current practice of FBVE. To identify the origin of newly emerging and rare strains, systematic monitoring of additional potential sources, such as cattle and swine (33) as well as sporadic human cases, is necessary. Second, in our analysis, the transmission route was reported as unknown for 57% of outbreak strains. Discussion ȡ1 = based on frequencies; ȡ2 = based on logarithm of frequencies; Cramer V, Ȥ2 test with simulated p values; FB-food, foodborne-food, i.e., an outbreak was reported to be caused by food and the outbreak strain was detected in food; FB-feces, foodborne-feces, i.e., an outbreak was reported to be caused by food and the outbreak strain was detected in human feces only; FHB, food handler–borne, i.e., an outbreak was reported to be caused by an infected food handler contaminating the food and the outbreak strain was detected in human feces; PB, person-borne, i.e., an outbreak was reported to be caused by person-to-person transmission and the outbreak; strain was detected in human feces; UN, unknown, i.e., the mode of transmission was not reported or was reported to be unknown and the outbreak strain was detected in human feces. Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 16, No. 4, April 2010 Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 16, No. 4, April 2010 621 RESEARCH ter recovery (25,27,29,30), education of food handlers (26), and standard testing of food handlers during outbreaks (28). A common source of contamination early in the food chain, however, may be more difﬁ cult to detect. Such con- tamination may result from sewage inﬂ ux containing mul- tiple viruses (8,9,31), making a link difﬁ cult to identify (31). Moreover, sewage most likely contains noroviruses from person-to-person outbreaks, which can contaminate the food and thereby dilute the genotype proﬁ ling effect. Use of genotype proﬁ les is a ﬁ rst step toward recognizing outbreaks resulting from contamination early in the food chain because it allows estimation of the incidence in sur- veillance data retrospectively and objectively minimizes misclassiﬁ cation of outbreaks. However, genotyping data need to be interpreted with care, and continuous updating of the database remains necessary. food chain. Consequently, differentiation of these modes of transmission is of interest to food safety authorities and public health institutions. Food handler–borne outbreaks are end-of-chain outbreaks easily recognized as such, as numerous outbreak reports illustrate (25–29). Such out- breaks can be prevented or limited by exclusion of infected or shedding food handlers from work until 48–72 hours af- are end-of-chain outbreaks easily recognized as such, as numerous outbreak reports illustrate (25–29). Such out- breaks can be prevented or limited by exclusion of infected or shedding food handlers from work until 48–72 hours af- Figure. Acknowledgments We thank Annelies Kroneman, Soizick Le Guyader, and Leena Maunula for critically reviewing the manuscript and Amal Chatterjee for editorial assistance. This work was supported by the Dutch Food and Consumer Product Safety Authority, the European Commission Director- ate General Research Quality of Life Program, 6th Framework (EVENT, SP22-CT-2004-502571) and Secretariat General SAN- CO (DIVINE-net, 2003213). Ms Verhoef is an epidemiologist in the Virology Division of the Diagnostic Laboratory for Infectious Diseases in the National Institute for Public Health and the Environment. Her work focus- es on the epidemiology and surveillance of infectious diseases, particularly noroviruses. Third, international comparison of norovirus strains is complicated because of their genetic diversity and the involvement of several laboratories in diagnosis; conse- quential different assays result in sequences with diverging lengths and from diverging genomic regions. However, this limitation is not likely to have inﬂ uenced our results because it affects mostly the comparison of sequence clusters and not genotypes. Moreover, within FBVE, standardization of di- agnostic methods occurs by having participating laboratories regularly test a representative panel of fecal samples (40). Discussion the prevalence of strains in the environment, foods, and humans is necessary for the interpretation of matching. Such knowledge requires monitoring, which is limited to shellﬁ sh and norovirus outbreaks (38). For monitoring of foods other than shellﬁ sh, methods sensitive enough to detect viruses in naturally contaminated (and not spiked) food are required. The technical advisory group (TAG 4) of the Viruses in Food workgroup (WG 6) in the Techni- cal Committee of Horizontal Methods for Food Analysis (TC 275) of the European Committee for Standardization (CEN) is validating standard methods for norovirus detec- tion in bivalve mollusks, soft fruit, leafy vegetables, and bottled water (39). Until such methods are available and provide knowledge about the prevalence of viral presence in foods, the use of genetic proﬁ les retrospectively derived from outbreak surveillance data is likely to improve food- borne viral surveillance. Because the norovirus strain pop- ulation is continuously evolving, our analysis needs to be repeated periodically to ensure that retrospective ﬁ ndings remain predictive. the prevalence of strains in the environment, foods, and humans is necessary for the interpretation of matching. Such knowledge requires monitoring, which is limited to shellﬁ sh and norovirus outbreaks (38). For monitoring of foods other than shellﬁ sh, methods sensitive enough to detect viruses in naturally contaminated (and not spiked) food are required. The technical advisory group (TAG 4) of the Viruses in Food workgroup (WG 6) in the Techni- cal Committee of Horizontal Methods for Food Analysis (TC 275) of the European Committee for Standardization (CEN) is validating standard methods for norovirus detec- tion in bivalve mollusks, soft fruit, leafy vegetables, and bottled water (39). Until such methods are available and provide knowledge about the prevalence of viral presence in foods, the use of genetic proﬁ les retrospectively derived from outbreak surveillance data is likely to improve food- borne viral surveillance. Because the norovirus strain pop- ulation is continuously evolving, our analysis needs to be repeated periodically to ensure that retrospective ﬁ ndings remain predictive. References 1. Cannon JL, Papafragkou E, Park GW, Osborne J, Jaykus LA, Vinje J. Surrogates for the study of norovirus stability and inactivation in the environment: a comparison of murine norovirus and feline cali- civirus. J Food Prot. 2006;69:2761–5. We showed that norovirus genotype proﬁ les can be used to estimate the foodborne proportion of norovirus outbreaks while excluding those of the food handler as a source. Distinction at genogroup level had already indicat- ed epidemiologic differences (19), and we have now dem- onstrated that genotype proﬁ les can be used to differentiate transmission modes. The proﬁ les and proportions are likely to be helpful for estimating the number of outbreaks with potential of causing geographically disseminated outbreaks. Because identiﬁ cation and investigation of such outbreaks provides insight into effective prevention measures during the production process, detection should enable contain- ment of viral foodborne infection and thus prevent further spread and the consequent potential for large numbers of human infections. 2. Dolin R, Blacklow NR, DuPont H, Formal S, Buscho RF, Kasel JA, et al. Transmission of acute infectious nonbacterial gastroenteritis to volunteers by oral administration of stool ﬁ ltrates. J Infect Dis. 1971;123:307–12. 3. Duizer E, Koopmans M. Tracking emerging pathogens: the case of noroviruses. In: Motarjemi Y, Adams M, editors. Emerging food- borne pathogens. Boca Raton (FL): Woodhead Publishing; 2006. p. 77–110. 4. Food and Agriculture Organization of the United Nations/World Health Organization. Viruses in food: scientiﬁ c advice to support risk management activities. Microbiological Risk Assessment series no. 13. Rome: The Organization; 2008. 5. Greening G. Human and animal viruses in food (including taxono- my of enteric viruses). In: Goyal SM, editor. Viruses in foods. New York (NY): Springer; 2006. p. 5–42. 6. Koopmans M, Vennema H, Heersma H, van Strien E, van Duynho- ven Y, Brown D, et al. Early identiﬁ cation of common-source food- borne virus outbreaks in Europe. Emerg Infect Dis. 2003;9:1136– 42. 7. Falkenhorst G, Krusell L, Lisby M, Madsen SB, Bottiger B, Mol- bak K. Imported frozen raspberries cause a series of norovirus outbreaks in Denmark, 2005. Euro Surveill. 2005;10:pii2795 [cit- ed 2005 Sep 22]. http://www.eurosurveillance.org/ViewArticle. aspx?ArticleId=2795 Members of the Food-Borne Viruses in Europe Network: B. Böttiger, K. Mølbak, C. Johnsen (Denmark); K.-H. von Bon- sdorff, L. Maunula, M. Kuusi (Finland); P. Pothier, K. Balay, J. Kaplon, G. Belliot, S. Le Guyader (France); E. Schreier, K. Stark, J. Koch, M. Höhne (Germany); G. Discussion Incom- pleteness of surveillance data is a common problem (34) and has been recognized in surveillance of foodborne viral infections (35), including in the FBVE database (19,20). Incomplete data may have resulted in underestimation of the number of foodborne outbreaks because they may be complicated to identify. Food safety authorities routinely conﬁ rm FB clusters by detecting pathogens in food, but such conﬁ rmation is difﬁ cult for viruses because viruses, unlike bacteria, do not replicate in food, resulting in a low viral load for extraction and concentration. In addition, the matrix involved may complicate these procedures, and successful detection methods are available primarily for fresh produce with surface contamination and virus- accumulating shellﬁ sh (36,37). However, knowledge of Figure. Two-dimensional display of the correspondence analysis of 6 norovirus genotype proﬁ les based on nucleotide sequences in which points close to each other are similar with regard to the pattern of relative frequencies across genotypes. Dimension 1 explains 59.12% and dimension 2 an additional 31.40%. In dimension 1, foodborne-feces (FB-feces; i.e., outbreak reported to be caused by food with the outbreak strain detected in human feces only) and bivalve mollusk (BM) genotype proﬁ les are mutually similar and differ from other proﬁ les; the most distinct proﬁ le is person-borne (PB; i.e., an outbreak reported to be caused by person-to-person transmission with the outbreak strain detected in human feces). In dimension 2, food handler–borne (FHB; i.e., outbreak reported to be caused by an infected food handler contaminating the food with the outbreak strain detected in human feces), FB-feces, and unknown (UN; i.e., mode of transmission was not reported or was reported to be unknown with the outbreak strain detected in human feces) mutually correspond and differ from the mutually corresponding foodborne-food (FB-food; i.e., outbreak reported to be caused by food with the outbreak strain detected in food), BM, and PB. Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 16, No. 4, April 2010 622 Origins of Foodborne Outbreaks S. Coughlan (Ireland); E. Duizer, A. Kroneman, Y. van Duyn- hoven (the Netherlands); K. Vainio, K. Nygard, G. Kapperud (Norway); M. Poljsak-Prijatelj, D. Barlic-Maganja, A. Hocevar Grom (Slovenia); F. Ruggeri, I. Di Bartolo (Italy); A Bosch, A. Dominguez, J. Buesa, A. Sanchez Fauquier, G. Hernández-Pezzi (Spain); K.-O. Hedlund, Y. Andersson, M. Thorhagen, M. Lysén, M. Hjertqvist (Sweden); D. Brown, B. Adak, J. Gray, J. Harris, M. Iturriza (United Kingdom). RESEARCH RESEARCH 25. Centers for Disease Control and Prevention. Multisite outbreak of no- rovirus associated with a franchise restaurant—Kent County, Michi- gan, May 2005. MMWR Morb Mortal Wkly Rep. 2006;55:395–7. 9. Webby RJ, Carville KS, Kirk MD, Greening G, Ratcliff RM, Crerar SK, et al. Internationally distributed frozen oyster meat causing mul- tiple outbreaks of norovirus infection in Australia. Clin Infect Dis. 2007;44:1026–31. DOI: 10.1086/512807 g y y p 26. Centers for Disease Control and Prevention. Norovirus outbreak as- sociated with ill food-service workers—Michigan, January–Febru- ary 2006. MMWR Morb Mortal Wkly Rep. 2007;56:1212–6. 10. Gallay A, De Valk H, Cournot M, Ladeuil B, Hemery C, Castor C, et al. A large multi-pathogen waterborne community outbreak linked to faecal contamination of a groundwater system, France, 2000. Clin Microbiol Infect. 2006;12:561–70. DOI: 10.1111/j.1469-0691 .2006.01441.x 27. Friedman DS, Heisey Grove D, Argyros F, Berl E, Nsubuga J, Stiles T, et al. An outbreak of norovirus gastroenteritis associated with wedding cakes. Epidemiol Infect. 2005;133:1057–63. DOI: 10.1017/S0950268805004760 11. Buesa J, Collado B, Lopez-Andujar P, Abu-Mallouh R, Rodriguez Diaz J, Garcia Diaz A, et al. Molecular epidemiology of calicivi- ruses causing outbreaks and sporadic cases of acute gastroenteri- tis in Spain. J Clin Microbiol. 2002;40:2854–9. DOI: 10.1128/ JCM.40.8.2854-2859.2002 28. Godoy P, Izcara J, Bartolome R, Bach P, Escobar A, Pal M, et al. Outbreak of food-borne norovirus associated with the consumption of sandwiches [in Spanish]. Med Clin (Barc). 2005;124:161–4. DOI: 10.1157/13071479 29. Schmid D, Stuger HP, Lederer I, Pichler AM, Kainz Arnfelser G, Schreier E, et al. A foodborne norovirus outbreak due to manu- ally prepared salad, Austria 2006. Infection. 2007;35:232–9. DOI: 10.1007/s15010-007-6327-1 12. Koopmans M, Lopman B, Vennema H, Reacher M, Carrique-Mas J, Van Duijnhoven Y, et al. Foodborne viruses in Europe: web- based technologies for investigation of transnational outbreaks of viral gastroenteritis. Proceedings of the International Conference on Emerging Infectious Diseases. 2002 Mar 24–27. Atlanta, GA, USA. 30. Rooney RM, Cramer EH, Mantha S, Nichols G, Bartram JK, Farber JM, et al. A review of outbreaks of foodborne disease associated with passenger ships: evidence for risk management. Public Health Rep. 2004;119:427–34. DOI: 10.1016/j.phr.2004.05.007 13. Hald T, Vose D, Wegener HC, Koupeev T. A Bayesian approach to quantify the contribution of animal-food sources to human salmo- nellosis. Risk Anal. 2004;24:255–69. DOI: 10.1111/j.0272-4332 .2004.00427.x 31. Gallimore CI, Pipkin C, Shrimpton H, Green AD, Pickford Y, Mc- Cartney C, et al. RESEARCH Detection of multiple enteric virus strains within a foodborne outbreak of gastroenteritis: an indication of the source of contamination. Epidemiol Infect. 2005;133:41–7. DOI: 10.1017/ S0950268804003218 14. Boxman IL, Tilburg JJ, te Loeke NA, Vennema H, de Boer E, Koop- mans M. An efﬁ cient and rapid method for recovery of norovirus from food associated with outbreaks of gastroenteritis. J Food Prot. 2007;70:504–8. 15. Le Guyader FS, Mittelholzer C, Haugarreau L, Hedlund KO, Alster- lund R, Pommepuy M, et al. Detection of noroviruses in raspber- ries associated with a gastroenteritis outbreak. Int J Food Microbiol. 2004;97:179–86. DOI: 10.1016/j.ijfoodmicro.2004.04.018 32. Zintz C, Bok K, Parada E, Barnes-Eley M, Berke T, Staat MA, et al. Prevalence and genetic characterization of caliciviruses among chil- dren hospitalized for acute gastroenteritis in the United States. Infect Genet Evol. 2005;5:281–90. DOI: 10.1016/j.meegid.2004.06.010 2004;97:179–86. DOI: 10.1016/j.ijfoodmicro.2004.04.018 Genet Evol. 2005;5:281–90. DOI: 10.1016/j.meegid.2004.06.01 33. Mattison K, Shukla A, Cook A, Pollari F, Friendship R, Kelton D, et al. Human noroviruses in swine and cattle. Emerg Infect Dis. 2007;13:1184–8. 16. Rutjes SA, Lodder Verschoor F, van der Poel WH, van Duijnhoven YT, de Roda Husman AM. Detection of noroviruses in foods: a study on virus extraction procedures in foods implicated in outbreaks of human gastroenteritis. J Food Prot. 2006;69:1949–56. 34. Doyle TJ, Glynn MK, Groseclose SL. Completeness of notiﬁ able infectious disease reporting in the United States: an analytical lit- erature review. Am J Epidemiol. 2002;155:866–74. DOI: 10.1093/ aje/155.9.866 17. Green J, Henshilwood K, Gallimore CI, Brown DW, Lees DN. A nested reverse transcriptase PCR assay for detection of small round- structured viruses in environmentally contaminated molluscan shell- ﬁ sh. Appl Environ Microbiol. 1998;64:858–63. 35. O’Brien S. The challenge of estimating the burden of an underre- ported disease. In: Koopmans M, Cliver DO, Bosch A, editors. Food- borne viruses. Washington (DC): ASM Press; 2008. p. 87–116. 18. Kroneman A, Verhoef L, Harris J, Vennema H, Duizer E, van Duyn- hoven Y, et al. Analysis of integrated virological and epidemiologi- cal reports of norovirus outbreaks collected within the foodborne viruses in Europe Network from 1 July 2001 to 30 June 2006. J Clin Microbiol. 2008;46:2959–65. DOI: 10.1128/JCM.00499-08 36. Atmar RL. Molecular methods of virus detection in food. In: Goyal SM, editor. Viruses in foods. New York: Springer 2006. p. 121–43. 37. Goyal SM. Conventional methods of virus detection in foods. In: Goyal SM, editor. Viruses in foods. New York: Springer; 2006. p. Address for correspondence: Linda Verhoef, National Institute for Public Health and the Environment (RIVM), Postbak 22, PO Box 1, 3720 BA Bilthoven, the Netherlands; email: linda.verhoef@rivm.nl References Szücs, G. Reuter, K. Krisz- talovics (Hungary); Ireland: M. Lynch, B. Foley, P. McKeown, 8. Le Guyader FS, Bon F, DeMedici D, Parnaudeau S, Bertone A, Crudeli S, et al. Detection of multiple noroviruses associated with an international gastroenteritis outbreak linked to oyster consumption. J Clin Microbiol. 2006;44:3878–82. DOI: 10.1128/JCM.01327-06 Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 16, No. 4, April 2010 623 RESEARCH 101–20. 19. Verhoef LP, Kroneman A, Van Duijnhoven Y, Boshuizen H, van Pelt W, Koopmans M. Selection tool for foodborne norovirus outbreaks. Emerg Infect Dis. 2009;15:31–8. DOI: 10.3201/eid1501.080673 38. Verhoef L, Boxman I, Koopmans M. Viruses transmitted through the food-chain: a review of the latest developments. CAB Reviews. 2008;3:1–15 . 20. Kroneman A, Harris J, Vennema H, Duizer E, van Duynhoven Y, Gray J, et al. Data quality of 5 years of central norovirus outbreak reporting in the European Network for food-borne viruses. J Public Health (Oxf). 2008;30:82–90. DOI: 10.1093/pubmed/fdm080 39. Costafreda MI, Bosch A, Pinto RM. Development, evaluation, and standardization of a real-time TaqMan reverse transcription–PCR assay for quantiﬁ cation of hepatitis A virus in clinical and shellﬁ sh samples. Appl Environ Microbiol. 2006;72:3846–55. DOI: 10.1128/ AEM.02660-05 21. Lopman BA, Reacher MH, Van Duijnhoven Y, Hanon FX, Brown D, Koopmans M. Viral gastroenteritis outbreaks in Europe, 1995–2000. Emerg Infect Dis. 2003;9:90–6. 22. Henshilwood K, Green J, Lees DN. Monitoring the marine environ- ment for small round structured viruses (SRSVs): a new approach to combating the transmission of these viruses by mulluscan shellﬁ sh. Water Sci Technol. 1998;38(12):51–6. DOI: 10.1016/S0273-1223 (98)00799-9 40. Vinje J, Vennema H, Maunula L, von Bonsdorff CH, Hoehne M, Schreier E, et al. International collaborative study to compare re- verse transcriptase PCR assays for detection and genotyping of noroviruses. J Clin Microbiol. 2003;41:1423–33. DOI: 10.1128/ JCM.41.4.1423-1433.2003 23. Vinje J, Koopmans MP. Molecular detection and epidemiology of small round-structured viruses in outbreaks of gastroenteritis in the Netherlands. J Infect Dis. 1996;174:610–5. 24. Brown LD, Cai TT, DasGupta A. Interval estimation for a binomial proportion. Stat Sci. 2001;16:101–33. 624 Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 16, No. 4, April 2010
https://openalex.org/W4210666708	https://www.ssoar.info/ssoar/bitstream/document/79981/1/ssoar-socialinclusion-2022-2-platero_et_al-Spanish_LGBTQ_Youth_and_the.pdf	English	null	Spanish LGBTQ+ Youth and the Role of Online Networks During the First Wave of Covid‐19	Social inclusion	2,022	cc-by	8,146	www.ssoar.info Issue Issue This article is part of the issue “Educational Inclusion of Vulnerable Children and Young People after Covid‐19” edited by Spyros Themelis (University of East Anglia) and Angela Tuck (Pakefield High School). © 2022 by the author(s); licensee Cogitatio (Lisbon, Portugal). This article is licensed under a Creative Commons Attribu‐ tion 4.0 International License (CC BY). under what conditions (Ozamiz‐Etxebarria et al., 2021). The requirements of young people were often overshad‐ owed by the urgent need to address the pandemic cri‐ sis, and by the common view that sexuality and bullying are not only minor issues but also politically controver‐ sial. Additionally, many families faced economic uncer‐ tainty and job losses, with unemployment rising to 16% (INE, 2021). Abstract During the lockdown measures put in place at the time of the first wave of the Covid‐19 pandemic in Spain (March through June 2020), LGBTQ+ youth lived through a particularly stressful situation that has so far received little attention. Confined in homes that are often hostile to their sexuality, struggling with the transition to online classes, they reached out to Internet social networks to obtain the support most of them lack in person. This article explores the role of technology for LGBTQ+ youth during a period when the educational environment was not supportive of students’ sexuality and iden‐ tity needs. The research assesses correlations between the use of online social networks and the perceptions of support received from others (using the concepts of social support, thwarted belongingness and burdensomeness, and cohabita‐ tion in their homes). The study involves a sample of 445 Spanish participants aged 13 to 21. A descriptive multivariate analysis of variance and bivariate correlations was performed. We found that social networks were very important for LGBTQ+ youth during the pandemic, helping them to explore their identities, but could also be a source of violence. In this regard, while trans and nonbinary youth’s use of social networks to contact acquaintances show important differences when compared to that of gays, lesbians, and bisexuals, the former group also experiences more violence coming from these networks, finds less social support through them, and feels a stronger sense of burdensomeness in relation to them. Additionally, they were often living with people other than family members during the lockdown. This data suggests the need to offer specific support and online services for LGBTQ+ youth, particularly for trans and nonbinary youth. Keywords burdensomeness; Covid‐19; gender identity; LGBTQ+; social networking; thwarted belongingness; vulnerable youth; youth support Spanish LGBTQ+ Youth and the Role of Online Networks During the First Wave of Covid‐19 Platero, R. Lucas; López‐Sáez, Miguel Ángel Veröffentlichungsversion / Published Version Zeitschriftenartikel / journal article Empfohlene Zitierung / Suggested Citation: Platero, R. L., & López‐Sáez, M. Á. (2022). Spanish LGBTQ+ Youth and the Role of Online Networks During the First Wave of Covid‐19. Social Inclusion, 10(2), 185-194. https://doi.org/10.17645/si.v10i2.4950 Empfohlene Zitierung / Suggested Citation: Empfohlene Zitierung / Suggested Citation: Platero, R. L., & López‐Sáez, M. Á. (2022). Spanish LGBTQ+ Youth and the Role of Online Networks During the First Wave of Covid‐19. Social Inclusion, 10(2), 185-194. https://doi.org/10.17645/si.v10i2.4950 Terms of use: This document is made available under a CC BY Licence (Attribution). For more Information see: https://creativecommons.org/licenses/by/4.0 Nutzungsbedingungen: Dieser Text wird unter einer CC BY Lizenz (Namensnennung) zur Verfügung gestellt. Nähere Auskünfte zu den CC-Lizenzen finden Sie hier: https://creativecommons.org/licenses/by/4.0/deed.de Social Inclusion (ISSN: 2183–2803) 2022, Volume 10, Issue 2, Pages 185–194 https://doi.org/10.17645/si.v10i2.4950 Spanish LGBTQ+ Youth and the Role of Online Networks During the First Wave of Covid‐19 R. Lucas Platero * and Miguel Ángel López‐Sáez Submitted: 15 October 2021 \| Accepted: 30 November 2021 \| Published: 19 May 2022 1. Introduction In Spain, unlike other European countries, childhood and youth were strongly stigmatized during the first wave of Covid‐19 (Chmielewska, 2020), which required harsh confinement and social distancing measures between 15 March and 21 June 2020. High schools and univer‐ sities moved their classes online until the end of the semester. Faculty felt overwhelmed and unsupported in this technological transition, not knowing whether their students had the means to keep up with their classes or Having access to a device (computer, phone, tablet, etc.) and the Internet was very important for these young people to attend online classes and maintain ties with Social Inclusion, 2022, Volume 10, Issue 2, Pages 185–194 185 change their names or receive hormonal or retroviral treatments, among others (Green et al., 2020; Platero & López‐Sáez, 2020). their peers. Probably due to the widespread use of cell phones (Pérez Díaz et al., 2021; Powell et al., 2010; Qustodio, 2019), young people spent a significant amount of time online during the pandemic and, depending on theiruseoftheseresources,wereabletoaccessacademic resources and maintain communication with one another. However, at the same time, they exposed themselves to potential mental health risks (Hamilton et al., 2020). Acknowledging the fact that LGBTQ+ youth in Spain often sought support online during the pandemic (Platero & López‐Sáez, 2020), we want to understand to what effect this technology was used at a time when the institutional educational environment was not able to provide a comprehensive response for youth develop‐ ment. With an awareness of the contradictory idiosyn‐ crasies of the Internet, which both provides LGBTQ+ youth with an opportunity to explore their sexuality but also exposes them to significant risks, we explore the role of online networks for the vulnerable group of LGBTQ+ youth during the first wave of the pandemic. In partic‐ ular, we pose questions related to the interrelationship between using online networks, social support, LGBTQ+ youth housemates, and the self‐perception of burden‐ someness. Finally, we analyze their experiences from the viewpoint of their age, sexual identity, and identifica‐ tion as cis or trans to offer information about a social group that is insufficiently studied in Spain (CIMOP, 2010; Coll‐Planas et al., 2009). Before Covid‐19, the literature indicated specific Internet usage by LGBTQ+ youth particularly related to their need to explore their sexuality (González‐Ortega et al., 2015). 2.1. Participants A total of 445 people aged 13–21 (M = 1.8, SD = 0.40) living in Spain completed the questionnaire, as part of a larger study that included the participation of 2,833 peo‐ ple of different ages. Overall, it is important to consider how having the social support of their families, schools, friends, and neighbors is essential for LGBTQ+ youth to cope with the stigma of being outside cisgender and heterocen‐ tric norms (Frost et al., 2016; Moody & Grant Smith, 2013; Platero, 2014; Warner, 2002), avoiding what is known as “minority stress” (Meyer, 2003). Having this support helps them avoid feelings of loneliness and isola‐ tion, but also the sensation of burdensomeness (Green et al., 2020). This is even more true in a situation of a pandemic. Alarming data exist on the lack of sup‐ port for LGBTQ+ youth and, in particular, trans or nonbi‐ nary youth (Buspavanich et al., 2021; Jones et al., 2021; Mirabella et al., 2021). Of the sample of 445 young people, 51.5% were cis women, 17.1% cis men, 13.9% trans men, 12.6% non‐binary, and 4.9% trans women. The vast majority were students, with 17.1% in elementary or compul‐ sory junior high education, 55.1% in high school or voca‐ tional training, and 27.9% enrolled in college. Politically, 66.5% described themselves as left‐wing, 26.1% center‐ left, 5.6% center, 1.6% center‐right, and 0.2% right‐wing. With specific regard to Covid‐19, 3.6% stated that they had had symptoms related to the illness. Concerning their place of residence during the lockdown, 26.5% were in large cities, 44% were in small cities, and 29.5% were in towns; 29.4% stated that they had to change their residence due to lockdown measures. Of the sample of 445 young people, 51.5% were cis women, 17.1% cis men, 13.9% trans men, 12.6% non‐binary, and 4.9% trans women. The vast majority were students, with 17.1% in elementary or compul‐ sory junior high education, 55.1% in high school or voca‐ tional training, and 27.9% enrolled in college. Politically, 66.5% described themselves as left‐wing, 26.1% center‐ left, 5.6% center, 1.6% center‐right, and 0.2% right‐wing. With specific regard to Covid‐19, 3.6% stated that they had had symptoms related to the illness. Concerning their place of residence during the lockdown, 26.5% were in large cities, 44% were in small cities, and 29.5% were in towns; 29.4% stated that they had to change their residence due to lockdown measures. 2. Method This is an exploratory ex post facto prospective and cross‐sectional study (Montero & León, 2002), with the independent study variables being age (adoles‐ cents and young adults) and gender identity (cis and trans/non‐binary). 1. Introduction Most notably, LGBTQ+ youth can make sense of their identities using this form of communica‐ tion (Austin et al., 2020). On social networks, LGBTQ+ youth explore their desires and make friends, practice their social skills, and seek resources to cope with a world that tells them they are too young to know about sexual‐ ity (Tortajada et al., 2020; Zheng et al., 2017). They find a “public intimacy” on these networks, having intense online experiences with their devices to which their families and other people around them are oblivious (Jenzen, 2017). LGBTQ+ youth can see how their identity is received online and “come out” to a small group before talking to their families. In particular, during the first wave of the Covid‐19 pandemic in Spain, access to these social networks was vital for LGBTQ+ youth to make sense of who they were: to stay in touch with other people, being able to express an identity that they themselves have chosen and which is not always known to all around them (Fish et al., 2020). For those who lack family sup‐ port, these online connections can alleviate stressful sit‐ uations linked to their non‐normative sexuality and gen‐ der identity (Green et al., 2020). However, online social networks are also a space where many LGBTQ+ youth are subjected to harassment (Tortajada et al., 2020). Social Inclusion, 2022, Volume 10, Issue 2, Pages 185–194 2.1. Participants During the pandemic, support networks helped these young people cope with the associated challenges and imposed restrictions (Mirabella et al., 2021). This occurred in a context in which not only were their social relationships reduced, but they faced potentially hos‐ tile situations around their sexuality and greater discom‐ fort linked to their uncertainty regarding the immediate future. They also encountered a standstill in the public administration that affected individuals who wanted to 2.2. Procedure 2.2. Procedure 2.2. Procedure 2.2. Procedure In May 2020, a group of researchers in gender psychol‐ ogy from the Rey Juan Carlos University, the Autonomous University of Barcelona, and the University of Barcelona Social Inclusion, 2022, Volume 10, Issue 2, Pages 185–194 186 LGTBQphobic aggression on virtual social networks”) and four on how they used networks (“I use online media like social networks/calls/video calls for sexual practices”) and whether they made voice or video calls for different purposes (flirting, sexual interactions, talking to friends, talking to family members). These items referred back to two moments: currently (the period of the state of alarm in Spain, between 15 March and 21 June) and before the Covid‐19 pandemic. These items were selected because of the usual importance of social networks for young people and adolescents, especially for those with non‐ normative sexualities and gender identities (Craig et al., 2015), at a particular time that usually required coping with living in very close quarters with family members and being isolated from peers and other people who help them have a sense of self that is more in line with their self‐perceived identities. designed a study to assess the psychosocial impact of Covid‐19 on the LGBTQ+ population. Participants were recruited through advertisements in different social net‐ works and by reaching out to feminist and LGBTQ+ non‐governmental organizations, between 4 April and 10 May 2020. Different scales with the appropriate psychometric properties were used to design the instrument bat‐ tery based on substantive relevance and consistency for our study. In addition, two experts in gender psychol‐ ogy reviewed the final battery to assess whether each item adequately represented the dimensions of inter‐ est. The items were also given to a pilot group con‐ sisting of two Black lesbians, two Caucasian gay men, two Caucasian trans persons, and one Caucasian inter‐ sex woman, who judged each item in terms of compre‐ hensibility. Four people in this pilot group were under 22 years of age (respectively 15, 17, 19, and 21). Lastly, the items were reviewed by an expert in inclusive lan‐ guage and an expert in psychometric analysis. These revisions improved the clarity, simplicity, and compre‐ hensibility of the questionnaire. 2.3.3. Social Support Frequency and Satisfaction Questionnaire This survey comprises 12 items that measure per‐ ceived social support on an emotional, informational, and instrumental plane. The tool has a factorial struc‐ ture composed of four dimensions: (a) social support received from a partner (Social Support Frequency and Satisfaction Questionnaire [SFSQ]‐P), (b) social support received from the family (SSFSQ‐F); (c) social support received from friends (SSFSQ‐FR), and (d) social support received from the community (SSFSQ‐C). Higher scores reflect a greater perception of social support. García‐ Martín et al. (2016) indicated a high reliability with internally‐consistent alpha coefficients of .95, .91, .92, and .92, respectively. All the participants received the same instructions and were informed of the voluntary nature, confiden‐ tiality, and anonymity of their responses. Before partic‐ ipating, they had to read and accept an informed con‐ sent form. 2.3.1. Socio‐Demographic Questionnaire This questionnaire gathered information about gender identity, sexual orientation, age, education, Covid‐19 sta‐ tus, access to treatment, and changes in place of resi‐ dence. The change in residence variable asked whether a change in residence had occurred and about the partic‐ ipants’ housemates before and after the lockdown mea‐ sures were enacted. 2.2. Procedure Likewise, control items were incorporated to avoid acquiescence bias and loss of veracity, and the non‐inclusion of intermediate response options was considered adequate to avoid central ten‐ dency bias and social desirability bias when responding to questions related to intimacy. 2.3.4. Interpersonal Needs Questionnaire This questionnaire is composed of nine items, six related to the dimension of self‐perception as a burden to others, i.e., burdensomeness (Interpersonal Needs Questionnaire [INQ]‐PB) and three related to the sensa‐ tion of loneliness and a lack of reciprocal support, i.e., thwarted belongingness (INQ‐TB). Feelings of burden‐ someness and thwarted belongingness are two risk fac‐ tors strongly linked to suicidal ideation (Van Orden et al., 2010). Higher scores reflect a greater self‐perception of burdensomeness. Silva et al. (2018) reported a good overall reliability with an omega coefficient that ranged between .85 and .95. 2.3. Instruments Except for the socio‐demographic questionnaire, the scales used a response format from 1 (strongly dis‐ agree) to 6 (strongly agree). The different instru‐ ments used, along with their corresponding consistency indexes according to the authors of each scale, are dis‐ cussed below. 3.2. Multivariate Analysis of Variance Regardless of whether there was a change of res‐ idence, most participants chose to live with family members: 39.3% lived with family members before 15 March, a figure that increased to 89.2% after that date. Adolescents and young people living with friends decreased from 26.1% to 4.3%, those living with their partner(s) increased from 1.3% to 3.1%, and those liv‐ ing alone decreased from 4.7% to 3.1%. During confine‐ ment, 28.1% felt little or no support from their part‐ ner(s), 27.2% from their family, and 18.2% from friends. During the same period, 31.6% had a feeling of burden‐ someness or thwarted belongingness either moderately, The results of the MANOVA indicate significance in the interaction (age group × gender identity), F(14,427) = 1.78, p = .05, 𝜂2 p = .05. This occurred with the items concerning SSFSQ‐FR, F(1,440) = 5.70, p < .05, 𝜂2 p = .01. This kind of interaction requires an analysis of the simple effects in order to be interpreted without error (see León & Montero, 2015). The analyses of the simple effects of the age groups showed that there were significant differences between cis‐ and trans/nonbinary adolescents (F(1,87) = 8.53, p = .005, 𝜂2 p = .09), but not Table 1. Means and standard deviations, divided by age group and gender identity. Table 1. Means and standard deviations, divided by age group and gender identity. 2.3.2. Items on Social Network Usage Descriptive statistics were obtained for each item and instrument, along with visual histograms and normality tests. The scores were calculated for each dimension by averaging the items. Five specific items were included in the questionnaire on the use of social networks, with one question focused on the perception of anti‐LGBTQ+ aggression on vir‐ tual social networks (“I have received/observed more Differences in age (adolescents aged 13–17 or young adults aged 18–21) and gender identity (woman, man, Social Inclusion, 2022, Volume 10, Issue 2, Pages 185–194 187 frequently, or very frequently. Social networks before the lockdown were used to talk to friends (94.6%), talk to family (79.6%), flirt (51.9%), or engage in cybersex (29.7%). The percentages during confinement were as follows: (a) talking to friends, 98.7%, (b) talking to family, 84.7%, (c) flirting, 40.4%, and (d) cybersex, 30.3%. Some 80% perceived anti‐LGBTQ+ aggression before the lock‐ down, while 71.5% perceived it during confinement. or gender non‐binary) were analyzed using a multivari‐ ate analysis of variance (MANOVA). The different kinds of cohabitation, changes in residence, scales, and the items related to social network usage were considered depen‐ dent variables, while age group and gender identity were independent variables. Lastly, correlations between the different variables were estimated using Pearson’s coefficient. Table 1 shows means and standard deviations, divided by age group (adolescents 13–17 years old × young adults 18–21 years old) and gender identity (cis × trans × nonbinary gender). 3.2. Multivariate Analysis of Variance On the negative self‐perception of burdensomeness to others and thwarted belongingness, INQ‐PB (F(1,440) = 14.90, p < .001, 𝜂2 p = .03) and INQ‐TB (F(1,440) = 11.23, p < .05, 𝜂2 p = .02), the main effects analyses of gender identity showed the existence of significant differences between cis‐ and trans/nonbinary people, with adoles‐ cents and trans/nonbinary young adults scoring higher. That is, both trans and nonbinary adolescents and young adults have more self‐perceptions of burdensomeness and more thwarted belongingness. Differences also appeared in the perception of aggression on social networks, F(1,440) = 7.01, p < .05, 𝜂2 p = .01. The analyses of the simple effects of the age groups showed that there were significant differ‐ ences between cis‐ and trans/nonbinary young adults (F(1,354) = 7.23, p = .05, 𝜂2 p = .02), but not between ado‐ lescents. That is, trans/nonbinary young adults scored higher on perceived aggression than cis young adults. Analyses of the simple effects of gender identity showed that there were significant differences between adoles‐ cents and trans/nonbinary young adults (F(1,138) = 6.07, p < .05, 𝜂2 p = .04), where young adults scored higher. No such differences appeared between cis young adults and adolescents. Finally, for the use of social networks and other apps to talk to family, the analyses of the main effects of gen‐ der identity (F(1,440) = 7.91, p < .05, 𝜂2 p = .02) showed the existence of significant differences between cis and trans/nonbinary people, with cis adolescents and young adults scoring higher. Homologously, although border‐ ing on significance (F(1,440) = 2.92, p = .08, 𝜂2 p = .01), this relationship was also found in the use of social net‐ works and other applications to talk to friends. Thus, cis people of all ages use networks more to talk to family and friends. Lastly, regarding the use of networks for flirting, the analyses found (F(1,440) = 5.62, p < .05, 𝜂2 p = .01). The analyses of the simple effects of the age groups showed that there were significant differences between cis—and trans/nonbinary adolescents (F(1,87) = 4.74, p < .05, 𝜂2 p = .05), but not between young adults. Thus, cis adolescents scored higher on the use of social net‐ works and dating apps than trans/nonbinary adolescents. 3.2. Multivariate Analysis of Variance Adolescents: 13–17 years old Young adults: 18–21 years old Cis Trans/non binary Cis Trans/nonbinary (N = 41) (N = 48) (N = 263) (N = 92) M SD M SD M SD M SD Change of residence 1.02 .16 1.08 .28 1.38 .49 1.27 .44 Live with family 1.98 .16 1.94 .24 1.90 .30 1.83 .38 Live with friends 1.00 .00 1.00 .00 1.05 .22 1.07 .25 Live with a partner 1.00 .00 1.04 .20 1.03 .16 1.05 .23 Live alone 1.02 .16 1.02 .14 1.03 .16 1.05 .23 Support from family (SSFSQ‐F) 4.17 1.20 3.56 1.42 4.01 1.35 3.39 1.52 Support from friends (SSFSQ‐FR) 4.24 1.36 3.34 1.51 4.24 1.22 4.10 1.30 Support from partner(s) (SSFSQ‐P) 3.87 1.60 3.79 1.44 3.96 1.50 3.86 1.64 Perceived burdensomeness (INQ‐PB) 2.39 1.54 3.30 1.75 2.29 1.46 2.83 1.60 Thwarted belongingness (INQ‐TB) 2.40 1.19 2.97 1.33 2.40 1.26 2.64 1.33 Current perception of aggression 3.39 1.92 2.79 1.70 3.00 1.83 3.60 1.91 Pre‐confinement perception of aggression 3.80 1.83 3.25 1.70 3.20 1.75 3.77 1.59 Current use for flirting 2.41 1.80 1.67 1.43 2.21 1.75 2.50 2.00 Pre‐confinement use for flirting 2.51 1.79 1.58 1.15 2.56 1.79 2.59 1.86 Current use for cybersex 1.78 1.44 1.60 1.27 1.90 1.60 2.15 1.80 Pre‐confinement use for cybersex 1.54 1.19 1.35 .79 1.79 1.46 1.90 1.48 Current use for talking to the family 5.51 1.17 4.96 1.54 5.22 1.34 5.21 1.40 Pre‐confinement use for talking to the family 5.27 1.32 4.46 1.79 4.53 1.65 4.52 1.67 Current use for talking to friends 4.56 1.92 3.79 1.83 4.05 1.85 3.54 1.92 Pre‐confinement use for talking to friends 4.05 1.95 3.31 1.93 3.58 1.88 3.08 1.82 Social Inclusion, 2022, Volume 10, Issue 2, Pages 185–194 188 that cis people perceive that they have more support from their families than trans and nonbinary people. among young adults. Thus, cis adolescents scored higher in perceived support from friends than trans and non‐ binary adolescents. Analyses of the simple effects of gender identity showed that there were significant differ‐ ences between trans/nonbinary adolescents and young adults (F(1,138) = 9.50, p < .005, 𝜂2 p = .06), with young adults scoring higher on perceived support from friends. No such differences appeared between cis young adults and adolescents. 3.2. Multivariate Analysis of Variance Analyses of the simple effects of gender identity showed that there were significant differences between adoles‐ cents and trans/nonbinary young adults (F(1,138) = 6.58, p < .05, 𝜂2 p = .04), and trans/nonbinary young adults, with young adults scoring higher. No such group differences appeared between cis young adults and adolescents. 3.3. Correlations Table 2 shows the correlations for the whole sample according to the following variables: gender identity, age, SSFSQ, INQ, housemates, change of residence, use of networks, and perception of aggression. The correlations were calculated using Spearman’s 𝜌coefficient due to the breakdown of the assumptions of continuity or nor‐ mality in all the pairs of variables. Social Inclusion, 2022, Volume 10, Issue 2, Pages 185–194 4. Discussion and Conclusions Correlations of the whole sample with current network use. Table 2. Correlations of the whole sample with current network use. Table 2. Correlations of the whole sample with current network use. Perceived Talking to aggression Flirting Cybersex family members Talking to friends Gender identity .075 −.033 .013 −.036 −.125 Age .016 .072 .058 −.012 −.053 Change of residence .055 .018 .012 .041 .015 Live with family −.014 −.009 −.041 .071 −.062 Live with friends −.071 −.011 .024 .001 .049 Live with partner(s) .129 −.018 .017 −.094* .065 Live alone −.022 .046 .027 −.032 −.013 Support of family (SSFSQ‐F) −.009 .088 −.006 .248 .385 Support of friends (SSFSQ‐FR) .094* .189** .102* .407 .269 Support of partner(s) (SSFSQ‐P) .115* .086 .160 .255 .212** Perceived burdensomeness (INQ‐PB) .100* −.067 .095* −.149 −.154 Thwarted belongingness (INQ‐TB) .001 −.201 −.029 −.297 −.200** Notes: p < .05; p < .01. that are informative, accessible, educational, and involve their peers, both online and offline (Fish et al., 2020). This work can be done by the public authorities who work in youth intervention programs. Moreover, these adolescents and young people are already content pro‐ ducers and can thus be an active part of these institu‐ tional proposals (Jenzen & Karl, 2014), challenging the adult‐centric view of intervention with young people. vulnerable to violence from which they cannot escape (Borraz, 2020; Gorman‐Murray et al., 2018; Hawke et al., 2021; Momoitio, 2020). As some preliminary studies among young college students have shown, the peo‐ ple with whom one lives can influence anxiety levels (Iñiguez‐Berrozpe et al., 2020). Age also influences the use of social networks. In gen‐ eral, during adolescence, there is a need to explore sexu‐ ality, and for those who have non‐normative identities this often means facing potential rejection (Mustanski, Newcomb, & Clerkin, 2011). This encourages these teens to turn to social networks in search of support, places where they may find peers and potential partners that they do not have in their “offline life” (DeHaan et al., 2013). Our study found that adolescents are more inter‐ ested in using networks to flirt, while youth use social networks more frequently for cybersex. 4. Discussion and Conclusions These data must be compared with what has been found in other stud‐ ies amongst the Spanish adolescent population, which is starting to use the Internet for sexual purposes (flirting, searching for information, watching pornography, cyber‐ sex, etc.) at an increasingly young age (Ballester‐Arnal et al., 2016). Additionally, we also found a high preva‐ lence of online “sexual activities” among Spanish young adults (Gutiérrez‐Puertas et al., 2020), as well as the use of social networks for flirting, searching for sexual infor‐ mation, purchasing sexual materials, etc., which is also significant and coincides with the international literature (Shaughnessy et al., 2013; Zheng & Zheng, 2014). On the other hand, gender identity determines the perception of support from friends, since the cis people in the sample perceived that they have more support than trans and nonbinary people. There is a greater self‐perception of burdensomeness, having feel‐ ings of frustration and thwarted belongingness, which is more common among trans and nonbinary people as the results of other studies have also shown (Pullen Sansfaçon et al., 2019; Reisner et al., 2015). Finally, gen‐ der identity determines the type of use of social net‐ works and apps to chat with family members, where cis people in the sample used them more frequently, per‐ haps because they receive more support from and have more communication with their families than trans and nonbinary people. The correlations in the sample as a whole affirm some findings in the earlier literature, as well as infor‐ mation appearing in the press (Borraz, 2020; Momoitio, 2020). Gender identity correlated negatively and signif‐ icantly with using networks to talk to friends. In other words, trans/nonbinary individuals make less use of networks to communicate with friends and—although not significantly but negatively—to flirt and talk with family members. This data raises two questions: What freedom did trans and nonbinary individuals have to communicate and talk during confinement about their identities while under intense family monitoring? Are trans and nonbinary youth finding friendships and bonds with peers that they may not find in their usual places The interactions between online and offline behav‐ ior shape the emerging identities, romantic relationships, sexual behaviors, and health of young people (DeHaan et al., 2013). For that reason, more studies are needed on the use of networks in this age group in the intersec‐ tion with LGBTQ+ identities during times of crisis, such as the Covid‐19 pandemic. 4. Discussion and Conclusions The intersection of age (adolescence and young adults) and gender identity (cis and trans/nonbinary) seems to influence the perception of support received from friends (especially for cis adolescents), as well as the use of net‐ works and applications (with communicating with fam‐ ily and friends and flirting being more frequent among cis people). Age and being trans or nonbinary are key when it comes to perceiving more aggression on social networks during confinement. This perception is linked to the fact that they are, indeed, subjected to greater violence than their cis peers and that such violence is increasingly frequent on social networks, although it is not always reported (FELGTB, 2020a, 2020b). With cohabitation with family members, the analy‐ ses of the main effects of age showed the existence of significant differences between adolescents and young adults (F(1,440) = 6.41, p < .05, 𝜂2 p = .01), with adoles‐ cents of all groups scoring higher in family cohabitation. Similarly, the analyses of the main effects of living with friends showed significant differences between adoles‐ cents and young adults (F(1,440) = 5.37, p < .05, 𝜂2 p = .01), with young adults of all groups scoring higher on living with friends. Regarding the use of social networks and applications for cybersex, the analyses of the main effects found dif‐ ferences close to significance between adolescents and young adults (F(1,440) = 2.92, p = .08, 𝜂2 p = .01), indicat‐ ing that young adults in all groups scored higher in the use of networks for cybersex. Likewise, age itself seems to influence the choice to live with some people or others during the lock‐ down. As might be expected, the lower the age, the greater the likelihood of cohabitation with family mem‐ bers and the less likely cohabitation with friends or partners. This intensive cohabitation with relatives at a time of crisis, like the Covid‐19 pandemic, forces ado‐ lescents to assess whether to reveal their identity in homes where they do not always receive support and are In the social support received from family, SSFSQ‐F, the analyses of gender identity F(1, 440) = 13.22, p < .001, 𝜂2 p = .03) showed the existence of significant differences between cis and trans/nonbinary people, with cis adoles‐ cents and young adults scoring higher. These data reveal Social Inclusion, 2022, Volume 10, Issue 2, Pages 185–194 189 Table 2. Social Inclusion, 2022, Volume 10, Issue 2, Pages 185–194 4. Discussion and Conclusions This suggests that those who live with a partner may not need as much family support. Furthermore, interacting and communicating with a part‐ ner could contribute to making this violence on social networks more visible. Feeling that one has family support positively cor‐ related with using social networks to talk to both fam‐ ily members and friends. This data is consistent with the literature that has observed that, for adolescents, Internet use is a way to stay in touch with the world and explore opportunities (Ofcom, 2014; Procentese et al., 2019; Subrahmanyam & Greenfield, 2008). For youth, the Internet extends how they connect and communi‐ cate with other important people in their lives, such as family members (Neustaedter et al., 2013). As some studies have indicated (Espinosa, 2020), access to health protection related to Covid‐19 must be better articulated as part of the basic human rights of adolescents and young adults. In Spain, this age group has been discriminated against because of their alleged “potential to spread the coronavirus” while, at the same time, they have not been sufficiently protected and their needs have been ignored. In particular, the lack of protec‐ tion for LGBTQ+ young adults and adolescents during the pandemic has entailed significant health risks for a pop‐ ulation that already has notable health disadvantages, intensifying the gap with their peers. It is significant that perceived support from friends correlated positively with all uses of social networks and with perceived aggression. For these adolescents and young adults, social networks may expand social circles, and separate circles may mix, allowing users to explore different uses because of this support (Jenzen & Karl, 2014). The same happens with perceiving partner sup‐ port, which correlates with all network uses (except flirt‐ ing) and perceived aggression. If flirting and looking for a partner are two frequent activities on social networks for this age group (Pascoe, 2011), and their online and offline life is interconnected, it is not surprising that partners in monogamous couples are not encouraged to use social networks in this way. In addition, the visibility of a partner or one’s very identity as an LGBTQ+ person with friends can be linked to greater exposure to online violence and, consequently, a greater perception of violence. One lesson learned from the effects of the pan‐ demic is that education and youth‐related policies must address existing social inequalities, including sexual and gender diversity. 4. Discussion and Conclusions In this regard, our data sug‐ gest the need to create spaces and resources for youth Social Inclusion, 2022, Volume 10, Issue 2, Pages 185–194 190 of socialization (school, neighborhood, leisure spaces, etc.) elsewhere? (DeHaan et al., 2013). Contacts made through social networks can compensate for the absence of support “in real life,” allow these youths to under‐ stand themselves and their processes, find peers with whom to share important experiences in the develop‐ ment of their identity, and potentially forge offline friend‐ ships (DeHaan et al., 2013; FELGTB, 2020b; Jenzen, 2017; Mustanski, Newcomb, & Garofalo, 2011; Subrahmanyam & Greenfield, 2008). (Shaughnessy et al., 2013), it also carries some poten‐ tial risks (Ballester‐Arnal et al., 2016), such as exposure to misinformation, reinforcing sexual stereotypes (Longo et al., 2002), and receiving unwanted sexual content (Castro et al., 2015). Furthermore, if it becomes an addic‐ tion, it can interfere with daily life (Döring, 2009). Lastly, the perception of thwarted belongingness cor‐ relates negatively with all uses of social networks that involve contact with other people, which is consistent with the feelings of thwarted belongingness and lack of reciprocal care that characterize them. This data is con‐ sistent with the existing literature, which indicates that a perceived lack of belonging is related to the perception of loneliness and isolation, which together with a feeling of burdensomeness are risk factors for an active desire to commit suicide (Joiner et al., 2012; Silva et al., 2015; Van Orden et al., 2010). These data, in particular on the perception of support received, suggest that there is a specific need for support (both online and offline), not only for adolescents and young adults with non‐normative sexualities but espe‐ cially for those who are trans and nonbinary, who often do not find answers in the existing resources for young people, especially during times of crisis. These data need to be contrasted with more specific studies (that is, based on more representative samples) and comparative studies between countries. However, our data show the need to recognize a population with intersectional characteristics who experiences a particu‐ lar type of violence and often lacks the necessary support from their environment and the institutions that serve young people. Living with a partner correlated positively and sig‐ nificantly with perceiving the existence of aggression on social networks, and negatively with using the net‐ works to talk to family. 4. Discussion and Conclusions Specifically, policies and youth pro‐ grams should pay more attention to the use of social networks and apps by LGBTQ+ adolescents and young adults, offering more support services, both inside and outside these networks, particularly considering that young adults and adolescents are already content pro‐ ducers of online materials, in addition to being con‐ sumers (Jenzen & Karl, 2014). LGBTQ+ inclusive programs and policies could be extraordinarily helpful in providing much‐needed support during these young people iden‐ tity processes, especially for vulnerable adolescents who are trans and non‐binary. Self‐perceived burdensomeness correlates positively with perceived aggression, but negatively with any use involving contact with others, except cybersex. This could indicate that cybersex is a poor protective factor, unlike other social network uses. Although cybersex can help young people to explore their sexual preferences Social Inclusion, 2022, Volume 10, Issue 2, Pages 185–194 References Austin, A., Craig, S., Navega, N., & McInroy, L. (2020). It’s my safe space: The life‐saving role of the internet in the lives of transgender and gender diverse youth. International Journal of Transgender Health, 21(1), 33–44. https://doi.org/10.1080/15532739. 2019.1700202 Döring, N. (2009). The Internet’s impact on sexuality: A critical review of 15 years of research. Computers in Human Behavior, 25(5), 1089–1101. Espinosa, M. A. (2020). Covid‐19, educación y dere‐ chos de la infancia en España [Covid‐19, education, and children’s rights in Spain]. Revista Internacional de Educación para la Justicia Social, 9(3), 245–258. https://doi.org/10.15366/riejs2020.9.3.013 Ballester‐Arnal, R., Giménez‐García, C., Gil‐Llario, M. D., & Castro‐Calvo, J. (2016). Cybersex in the “Net generation”: Online sexual activities among Span‐ ish adolescents. Computers in Human Behavior, 57, 261–266. https://doi.org/10.1016/j.chb.2015.12. 036 FELGTB. (Eds.). (2020a). Informe 2019: Delitos de odio [2019 report: Hate crimes]. https://bit.ly/2HkwynE Borraz, M. (2020, May 1). El doble encierro de vivir con una familia que rechaza al colectivo LGTBI: “Es triste que solo pueda ser yo misma a través de la pantalla” [The double confinement of living with a family that rejects the LGTBI community: “It’s sad that I can only be myself through the screen”]. El Diario. https://www.eldiario.es/sociedad/doble‐ encierro‐salido‐armario‐familia_1_1466142.html FELGTB. (Eds.). (2020b). Realidad del alumnado trans en el sistema educativo [The situation faced by transgen‐ der students in the education system]. https://bit.ly/ 302XIpR Fish, J. N., McInroy, L. B., Paceley, M. S., Williams, N. D., Henderson, S., Levine, D. S., & Edsall, R. N. (2020). “I’m kinda stuck at home with unsupportive parents right now”: LGBTQyouths’experienceswith Covid‐19 and the importance of online support. Journal of Adolescent Health, 67(3), 450–452. https://doi.org/ 10.1016/j.jadohealth.2020.06.002 Buspavanich, P., Lech, S., Lermer, E., Fischer, M., Berger, M., Vilsmaier, T., Kaltofen, T., Keckstein, S., Mahner, S., Behr, J., Thaler, C. J., & Batz, F. (2021). Well‐being during Covid‐19 pandemic: A comparison of individ‐ uals with minoritized sexual and gender identities and cis‐heterosexual individuals. PLoS ONE, 16(6). https://doi.org/10.1371/journal.pone.0252356 Frost, D. M., Meyer, I. H., & Schwartz, S. (2016). Social support networks among diverse sexual minority populations. American Journal of Orthopsychiatry, 86(1), 91–102. https://doi.org10.1037/ort0000117 Castro, J., Gómez, S., Gil, B., & Giménez, C. (2015). Jóvenes y sexo en la red: Reacciones ante la exposi‐ ción involuntaria a material sexual [Young people and online sex: Reactions to involuntary exposure to sex‐ ual material]. Agora de Salut, 1, 187–198. https:// doi.org/10.6035/AgoraSalut.2015.1.14 García‐Martín, M. Á., Hombrados‐Mendieta, I., & Gómez‐ Jacinto, L. (2016). The authors declare no conflict of interests. DeHaan, S., Kuper, L. E., Magee, J. C., Bigelow, L., & Mus‐ tanski, B. (2013). The interplay between online and offline explorations of identity, relationships, and sex: A mixed‐methods study with LGBT youth. Jour‐ nal of Sex Research, 50(5), 421–434. https://doi.org/ 10.1080/00224499.2012.661489 gay youth]. Secretaria de Joventut, Generalitat de Catalunya. We would also like to acknowledge the support provided by the AFIN research group, the Flax Foundation, and the y g p Rey Juan Carlos University. Craig, S. L., McInroy, L., McCready, L. T., & Alaggia, R. (2015). Media: A catalyst for resilience in lesbian, gay, bisexual, transgender, and queer youth. Jour‐ nal of LGBT Youth, 12(3), 254–275. https://doi.org/ 10.1080/19361653.2015.1040193 Rey Juan Carlos University. Acknowledgments We would like to thank all the anonymous LGBTQ+ youth who participated in our study, along with all the families, LGBTQ+ services, and professionals that support them. Social Inclusion, 2022, Volume 10, Issue 2, Pages 185–194 191 References A multidimensional approach to social support: The Questionnaire on the Frequency of and Satisfaction With Social Support (QFSSS). Anales de Psicología, 32(2), 501–515. Chmielewska, E. (2020, April 21). El confinamiento infantil no tiene base científica [Child confinement has no scientific basis]. CTXT. https://ctxt.es/es/ 20200401/Firmas/31983/coronavirus‐infancia‐ vectores‐contagio‐epidemia‐confinamiento‐ciencia‐ ewa‐chmielewska.htm González‐Ortega, E., Vicario‐Molina, I., Martínez, J. L., & Orgaz, B. (2015). The internet as a source of sex‐ ual information in a sample of Spanish adolescents: Associations with sexual behavior. Sexuality Research and Social Policy, 12(4), 290–300. https://doi.org/ 10.1007/s13178‐015‐0196‐7 Gorman‐Murray, A., McKinnon, S., Dominey‐Howes, D., Nash, C. J., & Bolton, R. (2018). Listening and learning: Giving voice to trans experiences of disasters. Gen‐ der, Place & Culture, 25(2), 166–187. https://doi.org/ 10.1080/0966369X.2017.1334632 CIMOP. (2010). El respeto a la diversidad sexual entre jóvenes y adolescentes. Una aproximación cualitativa [Respect for sexual diversity among youth and ado‐ lescents: A qualitative approach]. INJUVE. Coll‐Planas, G., Bustamante, G., & Missé, M. (2009). Tran‐ sitant per les fronteres del gènere: Estratègies, tra‐ jectòries i aportacions de joves trans, lesbianes i gais [Transiting gender boundaries: Strategies, tra‐ jectories and contributions of trans, lesbian and Green, A., Dorison, S., & Price‐Feeny, M. (2020). Implica‐ tions of Covid‐19 for LGBTQ youth mental health and suicide prevention. Trevor Project. p j Gutiérrez‐Puertas, L., Márquez‐Hernández, V. V., Social Inclusion, 2022, Volume 10, Issue 2, Pages 185–194 192 ceptual issues and research evidence. Psychological Bulletin, 129(5), 674–697. https://doi.org/10.1037/ 0033‐2909.129.5.674 Gutiérrez‐Puertas, V., Granados‐Gámez, G., Rodríguez‐García, M. C., & Aguilera‐Manrique, G. (2020). Online sexual activities among univer‐ sity students: Relationship with sexual satisfaction. Anales de Psicología, 36(1),166–172. https://doi.org/ 10.6018/analesps.353761 Mirabella, M., Senofonte, G., Giovanardi, G., Lingiardi, V., Fortunato, A., Lombardo, F., & Speranza, A. M. (2021). Psychological well‐being of trans people in Italy during the Covid‐19 pandemic: Critical issues and personal experiences. Sexuality Research and Social Policy. Advance online publication. https://doi.org/ 10.1007/s13178‐021‐00633‐3 Hamilton, J. L., Nesi, J., & Choukas‐Bradley, S. (2020). Teens and social media during the Covid‐19 pan‐ demic: Staying socially connected while physical distant. PsyArXiv. https://doi.org/10.31234/osf.io/ 5stx4 Momoitio, A. (2020, April 29). Armarios y miedos que sel‐ lan el encierro [Closets and fears that seal the lock‐ down]. Pikara Magazine. https://bit.ly/33Ulzcr Hawke, L. D., Hayes, E., Darnay, K., & Henderson, J. (2021). Mental health among transgender and gen‐ der diverse youth: An exploration of effects during the Covid‐19 pandemic. Psychology of Sexual Orien‐ tation and Gender Diversity. Advance online publica‐ tion. References https://doi.org/doi:10.1037/sgd0000467 Montero, I., & León, O. G. (2002). Clasificación y descrip‐ ción de las metodologías de investigación en psi‐ cología [The classification and description of research methodologies in psychology.]. International Journal of Clinical and Health Psychology, 2(3), 503–508. INE. (2021). Encuesta de población activa [Economically active population survey (EAPS)]. https://www.ine. es/prensa/epa_tabla.htm Moody, C., & Grant Smith, N. (2013). Suicide protective factors among trans adults. Archives of Sexual Behav‐ ior, 42(5), 739–752. https://doi.org/10.1007/s10508‐ 013‐0099‐8 Iñiguez‐Berrozpe, T., Lozano‐Blasco, R., Quílez‐Robres, A., & Cortés Pascual, A. (2020). Universitarios y confi‐ namiento: Factores Socio‐personales que influyen en sus niveles de ansiedad y empatía [College students and confinement: Socio‐personal factors that influ‐ ence their levels of anxiety and empathy]. Revista Internacional de Educación para la Justicia Social, 9(3), 301–316. https://doi.org/10.15366/riejs2020.9. 3.016 Mustanski, B., Newcomb, M. E., & Clerkin, E. M. (2011). Relationship characteristics and sexual risk‐taking in young men who have sex with men. Health Psy‐ chology, 30(5), 597–605. https://doi.org/10.1037= a0023858 Mustanski, B., Newcomb, M. E., & Garofalo, R. (2011). Mental health of lesbian, gay, and bisexual youth: A developmental resiliency perspective. Journal of Gay and Lesbian Social Services, 23(2), 204–225. https:// doi.org/10.1080=10538720.2011.561474 Jenzen, O. (2017). Trans youth and social media: Moving between counterpublics and the wider web. Gender, Place & Culture, 24(11), 1626–1641. https://doi.org/ 10.1080/0966369X.2017.1396204 Neustaedter, C., Harrison, C., & Sellen, A. (Eds.). (2013). Connecting families: The impact of new communica‐ tion technologies on domestic life. Springer. Jenzen, O., & Karl, I. (2014). Make, share, care: Social media and LGBTQ youth engagement. Ada: A Journal of Gender, New Media, and Technology, 5. https:// doi.org/10.7264/N39P2ZX3 Ofcom. (2014). Children’s online behaviour: Issues of risk and trust—Qualitative research findings. https://bit. ly/363osub Joiner, T. E., Ribeiro, J. D., & Silva, C. (2012). Nonsuicidal self‐injury, suicidal behavior, and their co‐occurrence as viewed through the lens of the interpersonal theory of suicide. Current Directions in Psychologi‐ cal Science, 21(5), 342–347. https://doi.org/10.1177/ 0963721412454873 Ozamiz‐Etxebarria, N., Berasategi Santxo, N., Idoiaga Mondragon, N., & Dosil Santamaría, M. (2021). The psychological state of teachers during the Covid‐19 crisis: The challenge of returning to face‐ to‐face teaching. Frontiers in Psychology. Advance online publication. https://doi.org/10.3389/fpsyg. 2020.620718 Jones, B. A., Bowe, M., McNamara, N., Guerin, E., & Carter, T. (2021). Exploring the mental health expe‐ riences of young trans and gender diverse people during the Covid‐19 pandemic. International Journal of Transgender Health. Advance online publication. https://doi.org/10.1080/26895269.2021.1890301 Pascoe, C. J. (2011). References Resource and risk: youth sexuality and new media use. Sexuality Research and Social Policy, 8(1), 5–17. Pérez Díaz, M. T., Simón, P., Clavería, S., García‐Albacete, S., López Ortega, A., & Torre, M. (2021). Informe: Juventud en España 2020 [Report: Youth in Spain 2020]. Instituto de la Juventud; Observatorio de la Juventud en España. León, O. G., & Montero, I. (2015). Métodos de investi‐ gación en psicología y educación [Research methods in psychology and education]. McGraw‐Hill. Longo, R., Brown, S., & Price, D. (2002). Effects of internet sexuality on children and adolescents. In A. Cooper (Ed.), Sex and the internet. A guidebook for clinicians (pp. 87–109). Routledge. Platero, R. L. (2014). Transexualidades. Acompañamien‐ tos, factores de salud y recursos educativos [Transgenderisms: Interventions, health factors and educational resources]. Bellaterra. Meyer, I. H. (2003). Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: Con‐ ] Platero, R. L., & López‐Sáez, M. A. (2020). “Perder la 193 Social Inclusion, 2022, Volume 10, Issue 2, Pages 185–194 and community samples. Archives of Sexual Behavior, 43(6), 1187–1197. https://doi.org/10.1007/s10508‐ 013‐0115‐z propia identidad”: La adolescencia LGTBQA+ frente a la pandemia por Covid‐19 y las medidas del estado de alarma en España [“Losing one’s identity”: LGTBQA+ adolescence in the face of the Covid‐19 pandemic and the state of alarm measures in Spain]. Sociedad e Infancias, 4, 95–98. https://doi.org/10.5209/soci. 69358 Silva, C., Chu, C., Monahan, K., & Joiner, T. E. (2015). Suicide risk among sexual minority college students: A mediated moderation model of sex and perceived burdensomeness. Psychology of Sexual Orientation and Gender Diversity, 2(1), 22–33. https://doi.org/ 10.1037/sgd0000086 Powell, J., Martin, S., Sutcliffe, P., Todkill, D., Gilbert, E., Paul, M., & Sturt, J. (2010). Young people and mental health: The role of information and communication technology. Warwick Medical School. Silva, C., Hurtado, G., Hartley, C., Rangel, J. N., Hovey, J. D., Pettit, J. W., Chorot, P., Valiente, R. M., Sandín, B., & Joiner, T. E. (2018). Spanish translation and valida‐ tion of the Interpersonal Needs Questionnaire. Psy‐ chological Assessment, 30(10), e21–e37. https://doi. org/10.1037/pas0000643 Procentese, F., Gatti, F., & Di Napoli, I. (2019). Families and social media use: The role of parents’ percep‐ tions about social media impact on family systems in the relationship between family collective efficacy and open communication. International Journal of Environmental Research and Public Health, 16(24). https://doi.org/10.3390/ijerph16245006 Subrahmanyam, K., & Greenfield, P. (2008). Online communication and adolescent relationships. The Future of Children, 18(1), 119–146. References https://doi.org/ 10.1353/foc.0.0006 Pullen Sansfaçon, A., Temple‐Newhook, J., Suerich‐ Gulick, F., Feder, S., Lawson, M. L., Ducharme, J., Ghosh, S., Holmes, C., & On behalf of the Stories of Gender‐Affirming Care Team. (2019). The experi‐ ences of gender diverse and trans children and youth considering and initiating medical interventions in Canadian gender‐affirming speciality clinics. Interna‐ tional Journal of Transgenderism, 20(4), 371–387. https://doi.org/10.1080/15532739.2019.1652129 Tortajada, I., Willem, C., Platero, R. L., & Araüna, N. (2020). Lost in transition? Digital trans activism on Youtube. Information, Communication & Soci‐ ety. Advance online publication. https://doi.org/ 10.1080/1369118X.2020.1797850 Van Orden, K. A., Witte, T. K., Cukrowicz, K. C., Braith‐ waite, S. R., Selby, E. A., & Joiner, T. E. (2010). The interpersonal theory of suicide. Psychological Review, 117(2). https://doi.org/10.1037/a0018697 Qustodio. (2019). Familias hiperconectadas: El nuevo panorama de aprendices y nativos digitales [Hyper‐ connected families: The new landscape of digital natives and learners]. shorturl.at/syzIX Warner, M. (2002). Publics and counterpublics (abbre‐ viated version). Quarterly Journal of Speech, 88(4), 413–425. https://doi.org/10.1080/0033563020938 4388 Reisner, S. L., Vetters, R., Leclerc, M., Zaslow, S., Wol‐ frum, S., Shumer, D., & Mimiaga, M. J. (2015). Men‐ tal health of transgender youth in care at an ado‐ lescent urban community health center: A matched retrospective cohort study. Journal of Adolescent Health, 56(3), 274–279. https://doi.org/10.1016/ j.jadohealth.2014.10.264 Zheng, L., Zhang, X., & Feng, Y. (2017). The new avenue of online sexual activity in China: The smartphone. Computers in Human Behavior, 67, 190–195. https:// doi.org/10.1016/j.chb.2016.10.024 Zheng, L., & Zheng, Y. (2014). Online sexual activity in mainland China: Relationship to sexual sensation seeking and sociosexuality. Computers in Human Behavior, 36, 323–329. https://doi.org/10.1016/ j.chb.2014.03.062 Shaughnessy, K., Byers, E. S., Clowater, S. L., & Kali‐ nowski, A. (2013). Outcomes of arousal‐oriented online sexual activities: Perspectives from university About the Authors R. Lucas Platero is an assistant professor at Rey Juan Carlos University, Psychology Department, and director of publications for trans* studies at Bellaterra Publishing House. His academic journey is strongly linked to his activist life, gradually shifting his social activism to activism based on academic research, to which he has made multiple contributions. In 2020, Platero received the Emma Goldman Award, supporting innovative research and knowledge on feminist and inequality issues in Europe. Miguel A. López‐Sáez holds a PhD in psychology from the Autonomous University of Madrid. Currently, he is a lecturer in the Department of Psychology at Rey Juan Carlos University. His work focuses on social psychology in the areas of children and youth, gender, sexual diversity, and sexual and gender‐ based violence. He recently coordinated projects on feminist research, trans* childhood, and masculin‐ ities. He is a member of activist networks reporting on sexual violence, as well as several public health policies and feminist epistemology research groups. 194 Social Inclusion, 2022, Volume 10, Issue 2, Pages 185–194
https://openalex.org/W2041300138	https://revije.ff.uni-lj.si/Dela/article/download/dela.21.7.97-107/1232	English	null	Canadian cities in transition: new sources of urban difference	Dela - Oddelek za geografijo Filozofske fakultete v Ljubljani	2,004	cc-by-sa	5,223	Dela 21 • 2004 • 97-107 Dela 21 • 2004 • 97-107 Abstract Cities, increasingly, are the principal arenas in which global, national and local forces inter- sect. Canadian cities are no exception. Those cities are currently undergoing a series of profound and irreversible transitions as a result of external forces originating from different sources and operating at different spatial scales. Specifically, this paper argues that Cana- dian cities are being transformed in a markedly uneven fashion through the intersection of changes in national and regional economies, the continued demographic transition, and shifts in government policy on the one hand, and through increased levels and new sources of immigration, and the globalization of capital and trade flows, on the other hand. These shifts, in turn, are producing new patterns of external dependence, a more fragmented urban system, and continued metropolitan concentration. They are also leading to increased socio- cultural differences, with intense cultural diversity in some cities juxtaposed with homoge- neity in other cities, and to new sets of urban winners and losers. In effect, these transitions are creating new sources of difference - new divides - among and within the country=s urban centres, augmenting or replacing the traditional divides based on city-size, location in the heartland or periphery, and local economic base. Key words: urban differences, diversity, globalization, Canadian cities CANADIAN CITIES IN TRANSITION: NEW SOURCES OF URBAN DIFFERENCE Larry S. Bourne Department of Geography, University of Toronto, Toronto ON M5S 3G3, Canada e-mail: Bourne@geog.utoronto.ca Key words: urban differences, diversity, globalization, Canadian cities SETTING THE STAGE Cities are widely viewed as the principal arenas in which global, national and local forces intersect. They are the settings where the synergies, opportunities and tensions generated by these forces operating in combination are mediated, and the resulting conflicts are resolved, accommodated or magnified. They are also where the outcomes become more visible poli- tically. As a consequence, cities are now said to matter politically, even in Canada (Brad- ford, 2002). 97 Larry S. Bourne / Dela 21 • 2004 • 97-107 Of course, cities have always served this pivotal role. Yet, there is general agreement that with continued urban growth and metropolitan concentration, fuelled by the forces of globalization, the intensity of the impacts of external forces has increased accordingly. Ci- ties are being transformed in multiple and seemingly irreversible ways through the effects of external forces, including globalization, but more emphatically through the intersection of these external forces with national conditions and local factors. This paper argues that Canadian cities are not immune to this mix of forces. Indeed, they offer an exceptionally rich example of the speed, scale and complexity of change and the importance of external forces. Specifically, the paper examines the proposition that Canadian cities are being transformed but in a markedly uneven fashion through the inter- section of changes in the economy, both national and regional, in the country’s demograp- hic structure, and through shifts in government policies and practices. At the same time, changes attributable to global forces such as economic competition, trade liberalization and capital flows, and immigration, have been superimposed on the national landscape and on Canadian cities. The hypothesis is that the combination – the intersection - of these trends has reorganized the urban system and created new divides and sources of “difference” among and within Canadian cities. The first part of the paper examines changes in both national and global forces as the context of urban growth and change. The second section documents the uneven impacts of these forces on the urban system and then on individual cities. The third section argues that these impacts, in turn, are creating new sources and new kinds of differences among cities that have augmented, and in some instances replaced, traditional sources of differences. The concluding section explores some of the implications of these emerging differences for the future of cities and the quality of life they provide. CONTEXT: EXTERNAL SOURCES OF CHANGE What are the underlying factors that have driven these changes? How have they affected cities and city-regions? This section examines four sets of trends that have reshaped the urban system and the context in which it has evolved: 1) the restructuring of the economy; 2) shifts in trade flows; 3) the demographic transition and immigration; and 4) the changing role of governments. All of these are closely related but each has its own dynamic, and its own distinctive geography. The following analysis is a brief summary that builds on a seri- es of recent papers that explore the empirical dimensions of the Canadian urban system in considerable detail (Simmons and McCann, 2000; Bourne, 2002; Bourne and Simmons, 2003; Simmons and Bourne, 2003). The Economy: The first set of trends involves the ongoing restructuring of the natio- nal economy, set within a changing global context of transnational integration and intense economic competition. These trends are similar to those prevailing in most western countri- es and are generally well documented in the international literature (Geyer, 2002; Champi- on and Hugo, 2003). But in Canada they also have a peculiar, if not unique, historical and 98 Canadian cities in transition: New sources of urban difference geographical base. The national economy has continued to shift in its sectoral composition from natural resources and basic manufacturing to services, both public and private. From 1981 to 2001 the country added 3.6 million jobs, of which over 80% have been created within the services sector. In a country spread over a vast continent, with a high degree of regional economic specialization, this sectoral transformation has also shifted the spatial distribution of economic growth, and thus the geography of urbanization. The fastest rates of growth, until recently, have been in high-order services in business and high-tech infor- mation sectors, as well as in the health and educational fields, all of which are over- whelmingly concentrated in the larger metropolitan areas or their immediate surroundings. It seems that there is a new premium attached to agglomeration economies and loca- tion, and specifically to a location in or near a large metropolitan area. Despite the rhetoric that the IT and communications revolution would lead to the elimination of distance as a constraint on location decisions, the opposite seems to have happened. The effect of distan- ce has been redefined but not eliminated. CONTEXT: EXTERNAL SOURCES OF CHANGE That social contract incorporates, among other inherited norms, a trade-off between the east-west flow of goods and services between the core and the periphery in exchange for equalization payments and the transfer of fiscal 99 Larry S. Bourne / Dela 21 • 2004 • 97-107 resources from richer to poorer regions. Why would richer regions continue to support such transfers if the markets provided by the peripheral regions are of diminishing importance to the national economy relative to the size of international markets. resources from richer to poorer regions. Why would richer regions continue to support such transfers if the markets provided by the peripheral regions are of diminishing importance to the national economy relative to the size of international markets. Equally problematic, there are no exchange mechanisms within the emerging North American economic zone to compensate for differences in economic performance and standard of living. Unlike the European Community, there are no effective institutions or policies for equalization, or for the trans-national transfer of fiscal resources, and certainly not the cross-border interregional transfer of resources, from richer to poorer regions. Inde- ed, the reverse is likely to be the case. The Demographic Transition and Immigration: Equally dramatic transformations have taken place in the country’s demography. This, in turn, is reflected in shifts in the relative importance of the different components of national and urban population growth, especially the increasing prominence of immigration. First, the demographic transition in Canada has, by any standard, been extremely sharp. The initial post-war baby-boom (1947- 1965) produced the highest fertility levels and the largest single population age cohort in the country’s history. This was followed by an equally sharp decline in fertility, and thus in rates of natural increase (the baby-bust), from the 1970s onward. Fertility levels are now at historically low levels, and are more-or-less uniform across the country (except for aborigi- nal communities). One obvious result of this decline is a rapidly aging population. Second, the increasing scale of immigration flows since the 1980s, both in absolute terms and relative to rates of natural increase, has altered the mix and the geography of growth. Immigration now averages around 225,000 persons per annum, and accounts for over 50% of national population growth and over 70% of labour force growth. The ethno- cultural composition of those flows has also shifted. CONTEXT: EXTERNAL SOURCES OF CHANGE Space and place have become more not less im- portant. Even high-tech and communication firms, which in theory are both wireless and footloose, as well as those activities most commonly associated with the new cultural sec- tors of the economy, are heavily concentrated in metropolitan regions, especially the larger places - the so-called global cities (Beaverstock et al, 2000; Marcuse and van Kempen, 2000). These are also places with strong international linkages, thick labour markets and high levels of employment in social and producer services. The periphery has not as yet benefited from the borderless world assumed in the knowledge economy (Polese and Shearmur 2002). Trade Flows: The rate of sectoral economic change in Canada has been accelerated by a series of trade agreements, with the Free Trade Agreement (1989) and NAFTA (1994) as the benchmarks. International trade flows have increased dramatically during the 1990s and now exceed the flows of commodities among the country’s major regions. Trade libera- lization has not only opened the border wider to imported goods (and to some services) it has changed the geography of the destinations of imports and the origins of exports. This, in turn, has augmented an already uneven pattern of urban growth. That pattern is depen- dent not only on the goods produced but on the emerging networks of linkages between urban places and export markets. In the Canadian case this openness reflects a broadening of the country’s traditional economic dependency on external markets, and thus the increa- sing degree of vulnerability to the actions of foreign governments, multi-national firms and organizations, and international regulatory agencies. Since most of this increased trade has been with the US, the trend can be seen not as a result of globalization per se, but rather the outcome of the continental integration of the Canadian economy within an expanding North American market that is also overwhelmingly dominated by the United States. One of the longer-term consequences of this shift in trade flows, and the increasing importance of international links compared to interregional links, may be political. It may, for example, undermine the implicit social contract that binds regions in Canada together as a nation state (Courchene and Telmer, 1998). CONTEXT: EXTERNAL SOURCES OF CHANGE In the 1960s almost 80% of immi- grants came from Europe and the US; now over 80% come from non-traditional sources, largely in Asia, Africa and the Caribbean. Moreover, those flows are geographically uneven, and are largely focused on a few metropolitan areas. Between 70% and 80% of immigrants are destined for the three largest metropolitan areas, with nearly 50% going to the Toronto region alone. This has changed the face and feel of these cities almost beyond recognition. For most of the rest of the country, in contrast, the level of immigration is relatively low, or non-existent. Third, interregional population flows have been relatively constant. The absolute size of flows of domestic migrants among regions within the country has remained more or less stable over the last two decades, and thus has declined in proportional terms as the country’s population has expanded. In other words, domestic migration has declined as a factor accounting for differences in regional and urban population growth rates, and as a means of adjusting the supply of labour to the market demand for workers and skills. Net domestic (e.g. inter-provincial) migration currently averages roughly 50,000 persons per year; while immigration adds over 175,000 people (net of emigration). The Role of Government: The actions of governments, even in those countries – such as Canada - without explicit national urban policies, have a significant impact on how the urban system evolves and on the character of individual cities. They can also be the prin- 100 Canadian cities in transition: New sources of urban difference cipal architects of urban convergence or increasing difference. Although national govern- ments may have lost considerable autonomy in macro-economic affairs, they still control, or at least influence, trans-national movements of goods, labour and people, and to a lesser extent, capital. The intersections between public policies can be substantial. For example, two recent policy decisions by the federal government in Canada – with respect to furthering trade liberalization and accelerated levels of immigration – have had dramatic and largely unanti- cipated effects on the structure and organization of the national economy and on the social character of cities. These effects have been intensified by the unevenness of the geography of the processes involved, especially among regions and within cities. It can be argued that the country’s principal population policy, albeit an implicit po- licy, mirrors decisions and practices on immigration (Ley and Hiebert, 2001). CONTEXT: EXTERNAL SOURCES OF CHANGE The stated objectives of the latter policy are to enhance labour force skills, to increase the size of the domestic market, and to avoid population decline in the future. But it is also transforming the country’s social fabric, most dramatically in the cities receiving the majority of the immigrants. It can also be argued that immigration policy, because of the localized geo- graphy of its outcomes, is the country’s implicit urban policy (Bourne and Simmons 2003). That policy implies, given the highly concentrated destinations of the immigrants, that Canada’s larger urban regions – notably Toronto and Vancouver - are not large enough. Summary: The above trends, for the most part, are not entirely new; nor are they specific to Canada or to Canadian cities. What is new is the emergence of new intersections in space and time between external and domestic forces, measured in terms of both the origins and the outcomes of the trends. Two examples of these intersections will suffice here. One described above relates to population growth and change. In Canada, as in most other countries, there have been periods of low fertility levels in the past (e.g. 1930s), and periods of high immigration levels (e.g. 1900-1920; 1950s). But these two conditions – low fertility and high immigration - have never prevailed at the same time, as they do now, and not in the same spatial configuration. As the geographies of natural increase (fertility) and immigration differ markedly, with rates of natural increase low and relatively even, in con- trast with immigration which is relatively high and spatially concentrated, their imprints on urban growth and population characteristics are therefore substantially different. The second example of the intersection premise is the coincidence in time of the inc- reasing liberalization of trade, and thus a larger role for foreign markets and agents in the geography of economic development, and the extensive decentralization (or downloading) of fiscal responsibilities from national to lower (provincial and local) levels of government. This downloading has not, however, been accompanied by a corresponding redistribution of revenues. To the extent that increased trade and immigration introduce greater uncer- tainty into national equations for urban growth, recent federal and provincial government actions, especially with respect to downloading, have at the same time reduced the ability of urban governments to adapt to that uncertainty. 101 Larry S. Bourne / Dela 21 • 2004 • 97-107 URBAN OUTCOMES The combined outcomes of the above factors, and especially their intersections, have reor- ganized the urban system in Canada and transformed the social and economic characteris- tics of individual cities and city regions in that system. The urban system is defined here as including 139 urban places with over 10,000 population – 27 census metropolitan areas (CMAs) and 122 census agglomerations (CAs). Because of low fertility levels, overall population growth rates have slowed, although they are still relatively high by western European standards. As a result, a much higher proportion of urban areas – both census metropolitan areas (CMAs) and census agglomera- tions (CAs) - actually declined in population over the last census period. Among smaller urban centers some 44% declined in population between 1996 and 2001, including several of the smaller metropolitan areas. For that part of the country outside of the urban system – that is, outside of the 139 CMAs and CAs - population declined by 0.4% during the last census period (Table 1). Table 1: The variability of urban growth in Cnada, by city size and relative location, 1996- 2001. Location/Region Number of Places Growth Rate N= 1996-2001 By City Size: All urban areas (CMAs and CAs) 139 5.2% (over 10,000 population) Metropolitan Areas (CMAs) 27 6.2% (over 100,000 population) Small urban areas only 112 1.5% (10,000 to 100,000) Non-urban areas (non-CMA/CA) 3800 -0.4% National growth rate 4.0% Table 1: The variability of urban growth in Cnada, by city size and relative location, 1996- 2001. Location/Region Number of Places Growth Rate N= 1996-2001 By City Size: All urban areas (CMAs and CAs) 139 5.2% (over 10,000 population) Metropolitan Areas (CMAs) 27 6.2% (over 100,000 population) Small urban areas only 112 1.5% (10,000 to 100,000) Non-urban areas (non-CMA/CA) 3800 -0.4% National growth rate 4.0% By degree of metropolitan linkages and influence for all non-CMA/CA places: location and accessibility with respect to CMAs/CAs: Strong CMA/CA influence/linkage (commuting over 30%) 3.7% Moderate CMA/CA influence/linkage (commuting 5% - 30%) -0.9% Weak CMA/CA influence/linkage (commuting 0% - 5%) -2.9% No CMA/CA influence/linkage (zero commuting) 1.0% Source: Statistics Canada, MIZ files, and author’s calculations. Table 1: The variability of urban growth in Cnada, by city size and relative location, 1996- 2001. ource: Statistics Canada, MIZ files, and author’s calculations. URBAN OUTCOMES By degree of metropolitan linkages and influence for all non-CMA/CA places: location and accessibility with respect to CMAs/CAs: and accessibility with respect to CMAs/CAs: Strong CMA/CA influence/linkage (commuting over 30%) 3.7% Moderate CMA/CA influence/linkage (commuting 5% - 30%) -0.9% Weak CMA/CA influence/linkage (commuting 0% - 5%) -2.9% No CMA/CA influence/linkage (zero commuting) 1.0% Source: Statistics Canada, MIZ files, and author’s calculations. Within the non-CMA/CA part of the country, proximity to a metropolitan area, or a large urban region, also seems to matter more under these conditions. A recent study of all com- munities located outside of the country’s urban system showed that growth rates declined systematically the further away those communities were (Bourne and Simmons 2003). Using 102 Canadian cities in transition: New sources of urban difference commuting to work as a composite index, places that were close enough to send a signifi- cant number of commuters to a larger urban area grew most rapidly. Those communities, in contrast, that are so isolated that commuting to a larger place was impossible actually decli- ned in population. In this case, proximity means not only access to employment alternatives in a different but nearby labour market, but also access to specialized services, such as health and educational facilities, that are generally not available in smaller communities. Ironically, the demand for those services is increasing most rapidly precisely in those areas least able to afford or sustain them. At the same time, urban growth has become more uneven across the country. Places that are growing rapidly, which tend to be those attracting immigrants, are juxtaposed with those undergoing serious decline, often within the same region. The coefficient of variation, which measures the variability of growth over the urban system, was the highest ever re- corded during the last census period. Population decline was most common in the eastern regions - in Atlantic Canada and Quebec - and among the more isolated resource-base communities in the north. But urban decline is also now a prominent feature in parts of the traditional core region of southern Ontario. It appears that the settlement frontier in Canada has been retreating, with people and economic activity migrating southward. In contrast, the larger metropolitan regions have continued to grow, driven primarily by immigration. As a result, the level of metropolitan concentration has increased. URBAN OUTCOMES Almost 85 percent of all growth has taken place within five of the larger metropolitan regions – Toronto, Montreal, Vancouver, Ottawa-Gatineau, and the Calgary-Edmonton corridor (Table 2). Table 2: Emerging urban regions in Canada, 2001 Rank Region Population Growth % of 2001 Rate 1996-01 Canada 1 Golden Horseshoe 6,700,000 7.4% 22.3 2 Montreal Region 3,500,000 2.9% 11.7 3 Vancouver – Victoria 2,700,000 7.3% 9.0 4 Edmonton – Calgary 2,150,000 12.3% 7.2 5 Ottawa – Gatineau 1,100,000 5.9% 3.6 Totals 16,150,000 6.9% 53.9 Canada 30,100,000 4.0% - Table 2: Emerging urban regions in Canada, 2001 Table 2: Emerging urban regions in Canada, 2001 Within those regions, on the other hand, growth in both population and employment has continued to decentralize outward from the older urban cores. The net effect is the emer- gence of geographically extensive urban regions, at least around those metropolitan areas that are growing. In the larger urban regions development now spreads over thousands of square kilometers. With the continued suburbanization of firms, and the appearance of new exurban concentrations of industrial employment, labour market catchment areas now extend over 100 kilometers from the urbanized core. Yet, suburban growth is not locally dispersed or haphazard. In most regions the new employment agglomerations that are deve- 103 Larry S. Bourne / Dela 21 • 2004 • 97-107 loping in newer suburban and exurban regions have simply accelerated the trend toward a poly-nucleated urban form. Nationally, as a direct consequence of the reorientation of trade flows to internatio- nal (i.e. US) markets, and the dominance of immigration as a determinant of population growth, the national urban system can be seen as fragmenting into a series of regional subsystems. Some of those subsystems, notably those focused on the larger metropolitan areas, are being drawn into the orbits of much larger, continental or global urban systems, and away from their traditional partners of exchange within the country. Those places not plugged into the continental or global economies, either through trade or immigration, or both, are becoming more detached from the metropolitan areas that dominate the national system. If this divergence of growth trajectories, and the weakening of the ties that underli- es it, continue, the consequences for national economic and political integration and identity could be substantial. NEW URBAN DIFFERENCES Returning to the initial proposition, the question is whether the trends outlined briefly abo- ve have, on balance, tended to increase the differences among individual urban places with respect to their structural attributes, living conditions, economic vitality and future prospects. Have they replaced, supplanted or added to the traditional sources of differences among cities within the Canadian urban system – for example, those based on contrasts between urban places located in the industrial core and northern periphery, between east and west, between French and English communities, and between types of urban economic base. Although it is not possible to evaluate the relative importance of all of these sources here with the data and analyses available to date, it is possible to provide examples of both new and extended sources of differences among the country’s urban places. These differen- ces are reflected in the following trends: 1. slower population growth overall has produced new sets of winners and losers within the urban system, and widespread urban decline. 2. an increase in the overall variability of growth rates among urban areas. 3. the continued concentration of growth in the largest metropolitan regions while small cities and even small metropolitan areas now show persistent decline. 4. sharper differences among cities in terms of economic viability and economic depen- dence, and thus enhanced vulnerability to external economic shocks. 5. wider contrasts in the demographic potential of urban places, as mirrored in the rapidly aging populations and older age structures of small and declining communiti- es, that also have future population decline built-in. 6. increased differences in levels of social and cultural diversity, primarily attributable to immigration, with increasing ethno-cultural heterogeneity prevailing in some places (in immigrant reception areas) and persistent homogeneity in most other places. 104 Canadian cities in transition: New sources of urban difference 7. wider variation in levels of social dependency between those places with aging popu- lations and smaller working age populations, and those with younger and growing po- pulations. 7. wider variation in levels of social dependency between those places with aging popu- lations and smaller working age populations, and those with younger and growing po- pulations. 7. wider variation in levels of social dependency between those places with aging popu- lations and smaller working age populations, and those with younger and growing po- pulations. p 8. diverging levels of personal investment assets (e.g. NEW URBAN DIFFERENCES housing) and in wealth accumula- tion are evident, due largely to appreciating assets in growing regions and depreciating assets in declining regions. 9. Government policy, in combination with economic and social trends, has produced even wider variations in the fiscal capacity of local and regional governments and in their ability to deliver high-quality goods and services to their residents. 10. in sum, increasing differences in the quality of urban life. n sum, increasing differences in the quality of urban It is evident from our analyses to date that most of the inherited sources of difference among cities have persisted. This is especially the case in the contrasting fortunes of places located in the east of the country and those in Ontario and the west; between resource-based northern communities and those in the settled ecumene; and between French and English communities. Yet new and augmented sources of difference, based on the factors identified above, have been superimposed on, and often replaced, the traditional urban divides. Of these new sources, demographic change, increased trade liberalization and higher levels of immigration, have been the most prominent factors. These factors, in turn, translate into wider differences in employment opportunities, wealth accumulation, social dependency and municipal fiscal capacity. Differences between places, of course, can be positive or negative, or sometimes both. And, identifying differences is not the same as explaining their existence or assessing their consequences (Fincher and Jacobs, 1998). Nevertheless, lower rates of population and em- ployment growth, and certainly rapid decline, sets in motion a series of negative multipliers that lower both expectations and opportunities. CONCLUSIONS Cities everywhere are increasingly subject to the effects of external factors over which they have little or not control. But in all instances these forces intersect in complex ways with national and local forces to shape the growth trajectories and attributes of individual cities and entire urban systems. This paper has attempted to illustrate that combinations of global, national and local factors have created new orders of differences among Canadian cities. Often these differences have magnified traditional contrasts among cities in other cases new dimensions of difference have arisen. Among those factors the discussion in this paper has emphasized four sets of factors: first, the impact of economic restructuring and trade liberalization on urban economies and networks of linkages; second, the increased importance of foreign trade relative to interre- gional flows; third, demographic change and lower fertility; and fourth, declining domestic migration in combination with higher levels of immigration. Two of these factors – immi- gration and trade - represent the forces of globalization, but both are also regulated directly 105 Larry S. Bourne / Dela 21 • 2004 • 97-107 by policies of the national government. National borders and policies still matter. Cities, on the other hand, have little or no say in either of these policy spheres. by policies of the national government. National borders and policies still matter. Cities, on the other hand, have little or no say in either of these policy spheres. What are the implications of increased levels of difference between urban places? The differences that matter are those that increase or decrease the potential for growth, in employment and income, that increase differentials in level of access to services, and those that augment inequalities in living standards and quality of life. Communities that are small, with declining and aging populations, and with weak and vulnerable economic bases, are likely to be the losers. The winners, in contrast, are likely to be the larger metropolitan regions, with high levels of services, links to the international economy and a population growing through immigration. These contrasts, if they continue to expand, will ultimately have implications for the viability of the nation state. In particular, wider urban differences will make achieving political consensus more difficult, and will likely further undermine the tacit acceptance of regional transfer payments (equalization), and the broader social contract, that bind the country together. Ley, D. and Hiebert, D. 2001: Immigration Policy as Population Policy”, The Canadian Geographer, 45, 1, 120-126. Harris, R. ed. 2003: North American Linkages. Calgary: University of Calgary Press. References Beaverstock, J. et al., 2002: Globalization and World Cities. GaWC Research Program, Loughborough University, UK. Bourne, L.S., 2002: “The Canadian Urban System: Old Structures, Recent Trends and New Challenges”, in W.K.D. Davies and I. Townshend (eds.). Monitoring Cities: Internati- onal Perspectives. Berlin and Calgary: IGU and University of Calgary, pp 15-31. Bourne, L.S. and Rose, D., 2001: “The Changing Face of Canada: The Uneven Geographi- es of Population and Social Change”, The Canadian Geographer, 45, 1, 105-119. Bourne, L.S. and Simmons, J. 2002: “The Dynamics of the Canadian Urban System”, in M. Geyer (ed.). International Handbook of Urban Systems: Studies of Urbanization and Migration in Advanced and Developing Countries. Cheltenham, UK: E. Elgar, pp. 391-418. Bourne, L.S. and Simmons, J., 2003: “New Fault Lines?: Recent Trends in the Canadian Urban System and Their Implications for Planning and Public Policy”. Canadian Jo- urnal of Urban Research, 12, 1, Summer, pp. 1-27. Bradford, N., 2002: Why Cities Matter. Policy Research Perspectives for Canada. Ottawa: Canadian policy Research Network. Champion, A. and Hugo, G. eds. 2003: New Forms of Urbanization: Beyond the Rural- Urban Dichotomy. Aldershot, UK: Ashgate (forthcoming). Courchene, T. and Telmer, C., 1998: Ontario: From Heartland to North American Region State. Toronto: University of Toronto Press. Fincher R and Jacobs J eds 1998: Cities of Difference New York: Guilford Press Fincher, R. and Jacobs, J. eds., 1998: Cities of Difference. New York: Guilford Press. Geyer, H.S. ed. 2002: International Handbook of Urban Systems: Studies of Urbanization and Migration in Advanced and Developing Countries. Northampton MA: E. Elgar Publishing. 106 Canadian cities in transition: New sources of urban difference Ley, D. and Hiebert, D. 2001: Immigration Policy as Population Policy”, The Canadian Geographer, 45, 1, 120-126. Marcuse, P. and van Kempen, R. eds. 2000: Globalizing Cities: A New Spatial Order? Oxford: Blackwell. Oxford: Blackwell. Polese, M. and Shearmur, R. 2002: The Periphery in the Knowledge Economy. Montreal: INRS. Simmons, J. and McCann, L. 2000: Growth and Transition in the Canadian Urban System, in P. Filion and T. Bunting, eds. Canadian Cities in Transition. Toronto: Oxford Uni- versity press, pp. 97-120. Simmons, J. and Bourne, L.S., 2003: The Canadian Urban System: Responses to a Chan- ging World. Research Paper No. 200, Centre for Urban and Community Studies, Uni- versity of Toronto, Toronto, Canada. 107
https://openalex.org/W2109872444	https://ris.utwente.nl/ws/files/20643154/sengupta_constructing.pdf	English	null	Constructing a seamless digital cadastral database using colonial cadastral maps and VHR imagery – an Indian perspective	Survey review/Survey review - Directorate of Overseas Surveys	2,016	cc-by	7,327	Survey Review ISSN: 0039-6265 (Print) 1752-2706 (Online) Journal homepage: http://www.tandfonline.com/loi/ysre20 Date: 21 December 2017, At: 05:51 Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=ysre20 Download by: [Universiteit Twente.] A. Sengupta, C. Lemmen, W. Devos, D. Bandyopadhyay & A. van der Veen To cite this article: A. Sengupta, C. Lemmen, W. Devos, D. Bandyopadhyay & A. van der Veen (2016) Constructing a seamless digital cadastral database using colonial cadastral maps and VHR imagery – an Indian perspective, Survey Review, 48:349, 258-268, DOI: 10.1179/1752270615Y.0000000003 To link to this article: https://doi.org/10.1179/1752270615Y.0000000003 © 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published online: 11 Apr 2016. Submit your article to this journal Article views: 318 View related articles View Crossmark data © 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published online: 11 Apr 2016. Submit your article to this journal Article views: 318 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=ysre20 Date: 21 December 2017, At: 05:51 Download by: [Universiteit Twente.] Received 12 August 2014; accepted 7 January 2015 DOI 10.1179/1752270615Y.0000000003 Survey Review 2016 VOL 48 NO 349 © 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A. Sengupta1,2, C. Lemmen1,3, W. Devos2, D. Bandyopadhyay1 and A. van der Veen1 pta1,2, C. Lemmen1,3, W. Devos2, D. Bandyopadhyay1 and A. van der A Land Administration System (LAS) with its cadastral component is the infrastructure that facilitates the implementation of land policies to attain sustainable development. Therefore, the availability of a digital, up-to-date and easily accessible cadastral database has become a primary requirement for undertaking efficient land administration and/or spatial planning decisions for any country. In this paper, the authors demonstrate a method for constructing a seamless digital cadastral database (DCDB) based on colonial cadastral maps using Geographic Information System (GIS) and image interpretation techniques for an area of about 326 km2. Geo- Eye1 (pan-sharpened) data were used for this purpose in combination with limited on-site survey. The proposed approach could be considered as an alternative to a complete cadastral resurvey. It is important to mention here that the quality of these colonial maps is quite high and can be proven as a basis for spatial planning. A cadastral resurvey may be required in the future where there is an urgent need for higher accuracy, but the approach would be time consuming and potentially bring unrest in villages and urban neighbourhoods. Hence, an alternative is, therefore, to respect the contents of the existing maps and records combined with a quality upgrade: make the existing records and maps up-to-date as a basis for a spatial planning. istration (clause 4.1.10) as the process of determining, recording and disseminating information about the relationship between people and land. 1University of Twente, Faculty of Geo-information Science and Earth Observation (ITC), PO Box 217, 7500 AE Enschede, The Netherlands 2Joint Research Centre, European Commission, Via E. Fermi, Ispra 21027 (VA), Italy 3 3Kadaster International, PO Box 9046, 7300 GH Apeldoorn, The Netherlands Corresponding author, email a.sengupta@utwente.nl Keywords: Land Administration System, Cadastral maps, Digital cadastral database, GIS, India Constructing a seamless digital cadastral database using colonial cadastral maps and VHR imagery – an Indian perspective A. Sengupta1,2, C. Lemmen1,3, W. Devos2, D. Bandyopadhyay1 and A. van der Veen1 1University of Twente, Faculty of Geo-information Science and Earth Observation (ITC), PO Box 217, 7500 AE Enschede, The Netherlands 2Joint Research Centre, European Commission, Via E. Fermi, Ispra 21027 (VA), Italy 3Kadaster International, PO Box 9046, 7300 GH Apeldoorn, The Netherlands C di th il t @ t t l Introduction A cadastre is one of the basic building blocks for any Land Administration System (LAS). Williamson et al. (2010) describe ‘land administration as the process run by the government using public or private sector agencies related to land tenure, land value, land use and land development’. In their view, LAS is an infras- tructure for the implementation of land policies and land management strategies in support of sustainable development. The infrastructure includes institutional arrangements, legal framework, processes, standards, land information, management and dissemination of systems, and technologies required to support allocation, land markets, valuation, control of use and developments of interests in land. Williamson et al. (2010) further explain the range of systems and processes related to land tenure, land value, land use and development. It should be noted that LADM (ISO 19152) deﬁned land admin- p p p The concept of cadastre is difﬁcult to identify, as it is designed in many different ways, depending on the origin, history and the cultural development of the country. Conventionally, cadastre (i.e. cadastral map) together with registers (i.e. land records) containing the details of the parcels, like ownership, type of land use, its value and size, etc. are used either for taxation (as was the original reason for establishing many European cadastres) or to ensure security of the property to its owner (as was the case in Australia). Today most cadastral registers around the world are linked with both land valuation/taxation and the recording of legal rights in land. As a result, the paradigm has shifted to the concept of a ‘cadastral system’ rather than a ‘cadastre’. Such a system includes the interaction between the identiﬁcation of land parcels, the registration of land rights, the valuation and taxation of land and property, and the present and future uses of land as well (Enemark 2006). However, because of the rapid growth of the world’s population and economic globalisation, the value of land is changing fast, thereby the security of land property rights can no longer be guaranteed by the traditional, paper-based, cadastral systems. Corresponding author, email a.sengupta@utwente.nl Survey Review 2016 VOL 48 NO 349 258 Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective Cadastral maps and related land records must reﬂect the changes in the framework arising from development and its effect on land use. Introduction This means that the land administration is of a dynamic nature as it depicts the people–land relationship. In such a way, mapping of the land parcels is a continuous job as it must be constantly updated to keep pace with the subdivision, consolidation or mutation of land boundaries. Hence, updating is considered as one of the essential activities in the LAS (Jing et al. 2013). In this regard, many developed and developing countries put effort to create so-called Digital Cadastral Databases (DCDBs). During mid- 70s, such effort was ﬁrst made in USA closely followed by UK and other western European countries. Later, Australia, New Zealand, Malaysia, and Singapore have also made effort to create such DCDBs (Habibullah and Ahuja 2005). The European Union Member States have developed DCDBs in accordance to the spatial data infrastructure (SDI) of the country. At the moment, about 50 countries have such LAS (Van der Molen 2003). In this regard, a number of examples representing different countries can be found in the literature showing where the existing maps were used to upgrade or to build initial DCDBs (Lemmen et al. 2009; Chris- todoulou 2003; Kansu and Sezgin 2006; Ondulo and Kalande 2006; Palm 2006; Paudyal and Subedi 2005; Tuladhar 2005). Government of India has taken an initiative called the ‘National Land Records Modernization Programme (NLRMP)’ for the modernisation of land records system across the country (NLRMP Guidelines 2008–2009). Major components of this programme comprise the computerisation of all land records including mutations, digitisation of maps and integration of textual and spatial data, survey/resurvey and updating the records, generation of original cadastral records wherever nece- ssary, computerisation of registration and its integration with the land records maintenance system, with the aim to develop a comprehensive and transparent GIS (Geographic Information System) based land-title sys- tem. However, so far, application of this guideline using VHR imagery has not been carried out over a large area. In addition, certain discrepancies pertaining to the digitisation of scanned maps were also observed. Different methods can be used to update the quality of attributes and spatial data. Public inspections or ﬁeld checks with the participation of the community may be used to ﬁnd the existing owners after inheritance, marriage, transactions, prescription, expropriations, re- cognised claims by courts or other ways of acquiring lands. Introduction The accuracy of the maps can be improved by renovation methods, see Salzmann (1996), Salzmann et al (1997), Song (2008) and Kumar (2006). Lemmen and Zevenbergen (2010) provide reference experiences and references on the use of satellite images for ﬁrst cadastral data acquisition. Resurvey is another method, but this is expensive and time consuming. In this paper, the authors present ‘an improved concept of map represen- tation’, or ‘an innovative concept of map improvement’ based on satellite images. India has remained away from such developments and is yet to reach a position of competence (Habibullah and Ahuja 2005). The existing LAS of the country is a British legacy considering the village as an adminis- trative unit. Since independence, a few exceptions apart, no signiﬁcant efforts have been made to revise or to update these colonial cadastral maps and registers. As a result, the colonial cadastral maps and land records available today are mostly outdated and do not always reﬂect the realities on the ground either in relation to ownership or plot boundaries. Nevertheless, updating of those maps on paper and related registers is anticipated to be very cumbersome for several reasons. First, in the conventional set-up that prevails in India, cadastral maps and land records are maintained separately in different organisations. In this case, updating of plot boundaries changed by mutation and modiﬁcation of other title information, takes a long time. Second, the cadastral maps used to be plotted on low-quality paper or cloth thus are subject to various kinds of degrading factors. Hence, in most cases, maps are in poor physical condition and torn because of lack of timely substitu- tion. Finally, the maintenance of an infrastructure to continue with this earlier practice also involves an extremely high cost. All these factors together reinforce the case for a digital (seamless) cadastral database with up-to-date information for India. Subsequently, the objective of this research is to demonstrate a methodology to construct a DCDB for an extended area using GIS tools and limited GPS survey. The work presented here represents a part of the broad research framework where the usability of these colonial cadastral maps as an acceptable basis for spatial planning is investigated (Sengupta et al. 2012, 2013). In particular, the present research focuses only on the ‘spatial’ aspects of the conversion of colonial cadastral maps to create a seamless DCDB based on the satellite imagery. Introduction In the following sections, the case study area is introduced in Study area section; description of the data and method used mentioned in Methodology section; results and level of accuracy achieved revealed in Results and accuracy assessment section; and ﬁnally, the conclusion and recommendations in Conclusion and recommendation section. Study area The present research work was carried out in the state of West Bengal, located in the eastern part of India (Fig. 1). The state has a fairly long history of cadastral mapping, which was initiated in 1888 and then steered through different phases. In West Bengal, the unit of survey for cadastral mapping and land records is a mouza (i.e. revenue village). Following the survey principle of ‘from whole to part’, the boundary of the mouza under survey was ﬁrst subjected to theodolite traverse, and then, ground details were surveyed and plotted by using plane table or chain survey. To achieve homogeneous accuracy in cadastral mapping, a uniform During the late 1990s, a pilot project was carried out in the states of Andhra Pradesh, Bihar, Kerala, Orissa and West Bengal for the digitisation of paper-based cadastral maps. However, the project experienced several problems because of the varying size and the quality of maps available, the absence of standards on accuracy to be maintained in digitisation, quality of equipment to be used and the amount of cost involved. More recently, the Department of Land Records (DoLR) under the Ministry of Rural Development, Survey Review 2016 VOL 48 NO 349 259 Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective 1 Location of Haldia, West Bengal, with example of colonial cadastral map available 1 Location of Haldia, West Bengal, with example of colonial cadastral map available 1 detailed history of the survey conducted for the area and mapping accordingly is presented in Table 1. Each of such maps at a scale of 1 : 3960 graphically depicts the individual plots (locally known as ‘dag’) with respective plot number. An example of the cadastral map available for the area is shown in Fig. 1. method of survey and scale of mapping was followed for the entire state. Owing to the high population density (1028 persons/ km2 as per 2011 Census), the average land holdings size of the state is among the lowest in the world, about 1 acre* per person. Moreover, the state has witnessed several land reforms in the postindependence era, hence rapid fragmentation of the land parcels. Keeping all this in mind, the authors tested the proposed approach in one of the medium-sized towns of West Bengal. Methodology The proposed methodology to construct a seamless digital cadastral map (database) DCDB using VHR{ imagery was formulated by adapting the technical manual of the NLRMP mission in accordance with the geodetic framework of India. Therefore, the dataset could easily be integrated with the other spatial datasets. For this purpose, Geo-Eye1 (pan-sharpened) imagery with 0.45 m pixel size, and 310 colonial paper-based cadastral sheets were used with limited on-site survey carried out in early 2012. In addition, other maps including topographic maps (sheet nos. 79B/4 and 78N/16) and a planning area map provided by the Development Authority were used for ground veriﬁcation. The methodology is summarised in the following sections. Haldia, located at the southern tip of the state, with a population density of 620 persons/km2 as per 2011 Census, was selected as the study area for this research. During the last few decades, the town has emerged as one of the major petrochemical industrial hubs of India, and as a consequence experiencing radical change in land use pattern. Moreover, being located in the lower deltaic region, the area is also subject to river dynamics, changes in the courses of natural canals, etc. and which eventually result in changing the plot boundary (locally known as ‘aal’). The planning area as demarcated by the Development Authority{ including 258 mouzas (i.e. rural area) and 26 municipal wards (i.e. urban area) covering an area of 327 km2 is represented in a total of 310 analogue cadastral maps or sheets. It is important to mention here that many of these maps were prepared in mid-1950s and were later updated in different time periods. A { Very high resolution. * 1 acre 5 4046.86 m2 5 0.404686 hectare. Results and accuracy assessment Following the methodology mentioned in the previous section, a seamless DCDB was prepared for the entire Haldia planning area. Figure 3 shows the different steps involved in the preparation of the DCDB. Image processing For the entire area, the Geo-Eye1 image was received in 18 scenes with different spectral and spatial bands. Using image processing software, resolutions of the Panchromatic (PAN) and Multi-spectral (MS) bands for each scene were merged to combine spectral and spatial Table 1 History of cadastral maps of Haldia planning area Surveyed in Mapped in Revised in 1913–14 1915–16 1933–34 1954–57 1979–91 1980–95 1996–2000 No. of sheets 70 18 158 258 2 4 2 { Very high resolution. Development Authority is a statutory authority constituted under the West Bengal Town and Country (Planning and Development) Act, 1979. Table 1 History of cadastral maps of Haldia planning area Surveyed in Mapped in Revised in 1913–14 1915–16 1933–34 1954–57 1979–91 1980–95 1996–2000 No. of sheets 70 18 158 258 2 4 2 260 Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective 2 Selection of ground control points (GCPs) from image features (L) and by edge matching (R) Downloaded by [Universiteit Twente.] at 05:51 21 December 2017 2 Selection of ground control points (GCPs) from image features (L) and by edge matching (R) 2 However, these geocoded raster maps do not have any spatial component in them, and hence are incapable of supporting further spatial analysis. It was therefore required to convert these raster maps into vector format. The process of transforming the raster map into vector map is called vectorisation. Here, georectiﬁed scanned cadastral maps were vectorised or digitised on-screen in a GIS platform. In doing so, ﬁrst the boundary of each mouza map was digitised in a polygon layer with respect to its neighbouring mouza map. Taking the adjusted boundary layer as the base, individual parcels or plots within each mouza map were then digitised as separate polygon layer. Subsequently, all the individual parcel layers were merged to make a seamless parcel layer covering the entire area. Then, topology was built for the layer to check for any gaps in between the parcels or overlaps between parcels. quality into a pan-sharpened image. Later, these 18 different pan-sharpened scenes were mosaicked using an UTM Projection with WGS-84 ellipsoid as per the NUIS (i.e. National Urban Information System) stan- dards provided by the Town and Country Planning Organization (TCPO), Government of India1. Collection and preprocessing of paper-based cadastral maps Paper-based cadastral maps (also known as mouza maps) of the area were collected from the local District Land and Land Reforms (DLRS) ofﬁce. In order to make use of these maps to create a DCDB, it was the ﬁrst requirement to convert those analogue maps into a digital format (i.e. raster format). Accordingly, paper- based mouza maps were scanned at 300 dpi resolution and saved in TIFF format, which were then converted to vector format. However, a few mouza maps were readily obtained in scanned format from the DLRS ofﬁce. Georeferencing and vectorisation of scanned cadastral maps Georeferencing or geocoding is the process of assigning geographical coordinates (e.g. latitude and longitude) of known locations to the corresponding positions on the raster map. In the process of georeferencing, the raster datasets convert from one coordinate system to another using a transformation function. In this research, the scanned cadastral maps were georeferenced with respect to the Geo-Eye1 pan-sharpened imagery. An afﬁne or polynomial ﬁrst-order transformation parameter was used for this purpose as the area is mostly ﬂat land with little undulation. For each map, 10–15 points identiﬁed both on satellite imagery and scanned cadastral maps were used as ‘ground control points (GCPs)’ to deﬁne the coordinate location. In addition, few GCPs were also taken along the map boundary by matching the edge of the individual mouza, thus to set the adjacent mouza accurately (Fig. 2). For any spatial dataset, accuracy deﬁned as ‘ﬁt for purpose’, is one of the prime requirements from a user- perspective (Enemark 2012). Accordingly, the accuracy of the DCDB prepared was evaluated from certain aspects as described in the following section. 1 Refer to: http://tcp.cg.gov.in/nuis/Design_Standards.pdf Positional accuracy assessment Positional accuracy is one of the important parameters to determine the geometric quality of a digital dataset (Positional Accuracy Handbook 1999). It is the coordi- nate difference between true and represented position of a particular point with respect to a particular reference system (Shi 1994; Caspray and Scheuring 1993). Thus, the accuracy in the position of a set of features can be expressed in terms of RMSE (i.e. root mean square error). In principle, an RMSE of a digital dataset close to 0 is considered as a perfect transformation. Nevertheless, Survey Review 2016 VOL 48 NO 349 26 261 Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective 3 Digitisation of individual parcel from georectiﬁed cadastral map (above); overlaying digitised parcel layer on VHR satel- lite image to update same (below) Note: A signiﬁcant change in parcel boundary as well as land use pattern can be observed in the area under the red circle as highlighted in the ﬁgure Downloaded by [Universiteit Twente.] at 05:51 21 December 2017 3 Digitisation of individual parcel from georectiﬁed cadastral map (above); overlaying digitised parcel layer on VHR satel- lite image to update same (below) Note: A signiﬁcant change in parcel boundary as well as land use pattern can be observed in the area under the red circle as highlighted in the ﬁgure obtained from the use of a ﬁrst-order transformation. A comparison of the level of RMSEs achieved in both orders is presented in Table 3. sometimes that is not the case, as the positional accuracy of any digital datasets depends on the quality of the original image (in this case analogue cadastral maps used), in combination with any errors accumulated from the survey, the mapping and also through the scanning process (Caspray and Scheuring 1993). Ghosh and Dubey (2009) has reported that the acceptable limit of RMSE for a digital dataset at a scale of 1 : 10 000 should be 4.38 m as a combination of the square root of plotting accuracy (0.25 mm), the accuracy while georeferencing (0.25 mm) and the digitising accuracy (0.3 mm). Survey Review 2016 VOL 48 NO 349 Validation of georeferencing In order to validate the georeferencing process, it requires further investigation. For this purpose, the coordinates of the identical points on the georectiﬁed cadastral maps must be compared with the original coordinates of those points. However, because of the security and conﬁdentiality issues associated with the sharing of the original coordinates of those GCPs, it was not possible to perform the validation exercise, and therefore to access the quality of the original cadastral maps. Apart from this, often a canal is used to delineate the adjacent mouza boundaries. In such cases, this canal, is usually represented on both mouza sheets (Fig. 6), increasing the possibility for adding the same area twice for individual mouza area calculations. Another impor- tant issue to mention, in a few cases, a discontinuation of this bordering canal has also been observed. Downloaded by [Universiteit Twente.] at 05:51 21 December 2017 The paper-based cadastral maps used in this research, are mostly from pre-1920s surveys and 1950s mapping (Table 1). Customarily, these maps were prepared manually as individual maps following a systematic mapping system. In many cases, it has been found that the boundaries of adjacent mouzas do not ﬁt each other precisely, either they overlap each other or leave a gap in between them (Fig. 4). In addition, depending on the size and shape, one single mouza is sometimes sub- divided in a number of separate sheets. In such cases, the division among these individual sheets is often not clear (Fig. 5). Ground control point selection for georeferencing Scanned analogue mouza maps were georeferenced with respect to the Geo-Eye1 imagery using 10–15 GCPs. Nevertheless, poor choice of GCPs may also contribute Table 2 Number of sheets with level of root mean square error (RMSE) achieved Range of RMSE/m No. of sheets Less than 2.00 7 2.01–3.00 64 3.01–4.00 185 4.01–5.00 47 More than 5.01 7 Table 2 Number of sheets with level of root mean square error (RMSE) achieved Table 2 Number of sheets with level of root mean square error (RMSE) achieved Range of RMSE/m No. of sheets Less than 2.00 7 2.01–3.00 64 3.01–4.00 185 4.01–5.00 47 More than 5.01 7 In this research, the RMSEs of georectiﬁed mouza maps were calculated using a polynomial ﬁrst-order transformation parameter. In more than 80% cases, the level of RMSE achieved was within the acceptable limit (Table 2). Nonetheless, to justify the level of RMSEs achieved for individual maps through this exercise, the authors also applied the second-order transformation function to those sheets with a higher level of RMSE Survey Review 2016 VOL 48 NO 349 262 Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective 4 Gaps and overlaps in adjoining mouza boundaries (mapping or plotting error) 4 Gaps and overlaps in adjoining mouza boundaries (mapping or plotting error) 4 ensure the precision of the area attribute in the GIS database. error to the georeferencing process. Sometimes it turned out to be difﬁcult to ascertain the location of the identical points from the paper-based cadastral maps and that from the image, for example, if there is a horizontal shift in the plot boundaries. These distur- bances could have been created either by natural events like ﬂood, cloud cover**, ground vegetation or man- made reasons. Area calculation and error analysis Error analysis of a spatial dataset is one of the key issues in GIS research. In land administration, the cadastral parcel is the basic object. According to the feature classiﬁcations in GIS, a cadastral parcel belongs to one kind of closed polygon objects. However, in cadastral parcel digitisation for capturing data, it is unavoidable to have some errors (including surveying, mapping and digitising error), and as a result, with the propagation of errors, the digitised parcel area is not equal to the authorised area (i.e. true area). Therefore, it is one of the major problems to minimise the effects of such errors to Such errors in the geometry of the analogue maps leads to a subsequent lack of accuracy while using these as the base for the preparation of a seamless digital cadastral map; hence, it was required to resolve these errors before area calculations. For example, gaps and overlaps between the original paper-maps were elimi- nated by matching the edge of the two, or in exceptional cases three or four, neighbour maps. It is important to mention here that special care was taken for small parcels along the boundary while doing the edge matching. On the other hand, in the case of a common canal, the boundary was digitised by following the middle of the canal. However, these cartographic adjustments in the boundary resulted in altering the area of the individual mouza. In order to assess how much of the area of an individual mouza was distorted because of this adjustment, areas compiled from ofﬁcial records (DLRS) were compared with the digitised area. A few examples are shown in Table 4. Table 3 Comparison of root mean square error (RMSE) using ﬁrst- and second-order transformations Sample No. Level of RMSE/m First order Second order 1 3.668 3.177 2 3.171 2.510 3 3.962 1.339 4 4.089 3.096 5 5.010 2.889 Table 3 Comparison of root mean square error (RMSE) using ﬁrst- and second-order transformations Table 4 shows that the differences (positive or negative) between the legal area and digitised area were negligible. As mentioned earlier, these differences mostly occurred either because of canal as a common bound- ary, or of the overlaps and/or gaps existing between the adjacent map boundaries. Exceptionally, in a few Survey Review 2016 VOL 48 NO 349 2 263 Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective Sengupta et al. Area calculation and error analysis Constructing a seamless digital cadastral database-Indian perspective 5 Unclear division between two adjoining sheets Downloaded by [Universiteit Twente.] at 05:51 21 December 2017 Downloaded by [Universiteit Twente.] at 05:51 21 December 2017 5 Unclear division between two adjoining sheets 5 to mention that these traditional analogue maps do not represent the area of individual parcel as measured with a planimetric survey. Conventionally, the area of these individual parcels used to be calculated from the map itself, hence depending on the accuracy achieved in the process of surveying and plotting or mapping (Habibullah and Ahuja 2005). On the contrary, in case of a digital cadastral map, the area precision of an individual parcel depends on the positional accuracy of the map. In order to instances, where original areas either slipped into the river or a new area was added to the original mouza area because of rapid change in river dynamics (Fig. 7), a signiﬁcant difference has been observed. The above mentioned cartographic adjustment or harmonisation at mouza boundaries also changed the area of the parcels within the mouza. Accordingly, the area of each individual parcel was compared with the ofﬁcial record (as shown in Table 5). It is important 6 Actual mouza boundary including canal (L): part of canal common for both mouzas (R) 6 Actual mouza boundary including canal (L): part of canal common for both mouzas (R) Survey Review 2016 VOL 48 NO 349 264 Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective 7 Area of original mouza slipped into river (L): new area added to the original area (R) of original mouza slipped into river (L): new area added to the original area (R) 7 Area of original mouza slipped into river (L): new area added to the original area (R) analogue cadastre are themselves crude and the scanned version of the line is often more than 4–5 pixels wide clarify the issue about how the area of a particular mouza and thereby its parcel may change with respect to the ﬁrst- and second-order transformation functions used were also compared with ofﬁcial records. A few examples from one mouza (i.e. sample no. 5 in Table 3) are shown in Table 6. Fig. Area calculation and error analysis 8 is graphically showing the distribution of number of plots with corresponding area difference. Table 5 Example of parcel area calculation (in acre) J.L. no. Parcel no. DLRS record Calculated area Difference 165 43 5.42 5.50 20.08 165 44 0.16 0.18 20.02 165 45 0.27 0.28 20.01 165 46 0.07 0.07 0.00 165 47 0.04 0.04 0.00 165 49 0.12 0.11 0.01 165 51 0.1 0.10 0.00 165 52 0.01 0.02 20.01 165 53 0.02 0.03 20.01 165 54 0.02 0.03 20.01 165 55 0.07 0.06 0.01 165 56 0.12 0.12 0.00 District Land and Land Reforms. Table 5 Example of parcel area calculation (in acre) Table 5 Example of parcel area calculation (in acre) J.L. no. Parcel no. DLRS record Calculated area Difference Another important issue for parcel area calculation is the inconsistency with the land records or registry and the paper-based maps. llage identification number as per DLRS record. Errors transferred from input (mouza maps) used In addition, other types of errors also result from the paper-based cadastral map itself. These cadastral maps used to be plotted on a low-quality paper or cloth, which are subject to various degrading factors like paper shrinkage, wrinkling or folding and tear, etc. over time. The scanning of such maps therefore can also contribute to error. Examples of scanning and archiving errors are shown in Fig. 9. Furthermore, the ‘map lines’ in the Table 4 A few examples of individual mouza area calculation (in hectares1) J.L. No.2 DLRS record Adjusted boundary Accurate boundary3 Difference4 % Difference5 % 9 92.31 93.71 93.99 21.68 21.82 21.40 21.52 10 55.36 55.43 56.12 20.76 21.37 20.07 20.12 13 189.70 191.54 191.58 21.88 20.99 21.84 20.97 14 161.67 160.39 161.13 0.54 0.33 1.28 0.79 15 13.96 13.98 14.03 20.07 20.50 20.02 20.18 16 49.55 49.97 50.37 20.82 21.66 20.42 20.85 17 25.68 25.09 25.49 0.19 0.73 0.59 2.28 18 131.11 132.58 133.13 22.02 21.54 21.47 21.12 19 43.53 43.67 43.76 20.23 20.52 20.14 20.32 20 48.09 49.16 49.16 21.07 22.23 21.07 22.23 21 32.06 32.36 32.42 20.36 21.11 20.30 20.94 22 93.54 94.70 95.31 21.77 21.89 21.16 21.24 23 28.93 29.17 29.32 20.39 21.36 20.24 20.82 24 86.97 87.64 87.47 20.50 20.57 20.67 20.77 11 Hectare 5 2.47105 Acre 5 10 000 m2. 2Village identification number as per DLRS record. 3Digitised as shown on the scanned maps without doing any cartographic adjustment. 4Difference between official record and digitised accurate mouza boundary. 5Difference between digitised adjusted mouza boundary and official record. DLRS: District Land and Land Reforms. Table 4 A few examples of individual mouza area calculation (in hectares1) Survey Review 2016 VOL 48 NO 349 265 Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective 8 Distribution of number of parcels in range of area difference work, UTM projection with the WGS-1984 ellipsoid was used. Therefore, it is anticipated that such a change in the projection system would also contribute errors in area calculations. Conclusion and recommendation To the best of our knowledge, this approach to construct a digital (seamless) cadastral database (DCDB) with an acceptable level of accuracy for a sufﬁciently large area is ﬁrst of its kind in India. As a result of this research, the authors are optimistic about the reuse of existing cadastral maps. They are also of the opinion that those existing maps can be completed in alignment to land registry data and will be of sufﬁcient quality for many purposes including tenure capacity, valuation and taxation, access to credit, support to land markets, management of land disputes and resource management. This ‘ﬁt for purpose’ approach even allows that the ﬁrst steps in spatial planning combined with land re- adjustment and/or development of infrastructure can be supported. A cadastral resurvey may be required in the future, but this will be time consuming. The authors think it is better to build on the existing (legal) data. For this purpose, the data should be available and ready to use, then upgrading of the accuracy is always possible and different approaches are known from practices in many countries. Another important aspect needed to be 8 Distribution of number of parcels in range of area difference (Fig. 10) because of which uncertainties are bound to arise in the process of digitising those lines on-screen. (Fig. 10) because of which uncertainties are bound to arise in the process of digitising those lines on-screen. Survey Review 2016 VOL 48 NO 349 266 Errors because of changes in coordinate reference system Errors because of changes in coordinate reference system Many of the cadastral maps available today in India do not conform to any conventional known map projec- tion. Conventionally, the casini-soldner projection with the Everest-1830 ellipsoid was used for cadastral mapping in the eastern states of India, including the state of West Bengal. However, this projection neither represents correct shapes nor the correct areas because of scale distortion (Nagarajan 2001). Following the Indian National Mapping Policy (2005) in this research Downloaded by [Universiteit Twente.] at 05:51 21 December 2017 9 Distorted and missing parcel (archiving error) 9 Distorted and missing parcel (archiving error) Table 6 Comparison of parcel area (acre) after ﬁrst- and second-order transformations Parcel no. DLRS record Calculated area Difference First order Second order First order Second order 2 0.16 0.30 0.15 20.14 0.01 3 0.18 0.10 0.17 0.08 0.01 4 0.39 0.11 0.39 0.28 0.00 6 0.19 0.09 0.19 0.1 0.00 9 0.18 0.41 0.19 20.23 20.01 10 1.16 1.23 1.13 20.07 0.03 12 0.09 0.48 0.39 20.39 20.30 14 0.14 0.65 0.11 20.51 0.03 16 1.90 1.39 2.00 0.51 20.10 17 0.44 0.17 0.41 0.27 0.03 19 1.55 1.48 1.64 0.07 20.09 20 1.53 1.05 1.56 0.48 20.03 DLRS: District Land and Land Reforms. Table 6 Comparison of parcel area (acre) after ﬁrst- and second-order transformations Survey Review 2016 VOL 48 NO 349 266 266 Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective 10 Example of crude map line of analogue cadastral maps 10 Example of crude map line of analogue cadastral maps 10 2 the assessment if the total approach is ‘fit for purpose’ where the basis for spatial planning is concerned (with participatory approaches, fair compensation in case of expropriation, speed and costs of availability compared to resurvey as criteria for assessment). 2 the assessment if the total approach is ‘fit for purpose’ where the basis for spatial planning is concerned (with participatory approaches, fair compensation in case of expropriation, speed and costs of availability compared to resurvey as criteria for assessment). 2 the assessment if the total approach is ‘fit for purpose’ where the basis for spatial planning is concerned (with participatory approaches, fair compensation in case of expropriation, speed and costs of availability compared to resurvey as criteria for assessment). Errors because of changes in coordinate reference system mentioned here is that the present method would be much more cost and time effective than resurvey; however, no investigation was done in this regard. Therefore, the authors strongly recommend that further assessment needs to be carried out to estimate the time and cost involved in this proposed method, and thereby its comparison with the method of resurvey. Acknowledgement With the advent of GIS techniques, the map can be overlaid on high-resolution satellite imagery to update the details of the parcel within a short time. Thus, it would also be helpful in monitoring the changes in land use across parcels, fragmentation or consolidation of parcels, areas, which have gone either into the river or have been added, thereby highlighting the changes that need to be carried out in the DLRS records. Then, the proposed methodology could be adopted to prepare a seamless and updated digital cadastral database for a large area with limited ﬁeld survey where require. The authors would like to acknowledge Dr. R.M. Bennett, Assistant Professor, University of Twente (ITC) for reviewing this article and providing necessary feedback. References Caspray, W. and Scheuring, R. 1993. Positional accuracy in spatial databases. Journal of Computer Environment and Urban Systems, 17, pp. 103–110. Christodoulou, K. 2003 ‘Combination of satellite image Pan IKONOS- 2 with GPS in cadastral applications’, UN/ECE WPLA Workshop on Spatial Information Management for Sustainable Real Estate Market Best Practice Guidelines on Nation-wide Land Administration (Athens, Greece, 28–31 May 2003). The proposed methodology is formulated in accor- dance with national mapping standards, so it can be used with any other spatial datasets at any scale. However, so far, no standardised framework for projec- tion, scale, contents, accuracy in surveying and mapping is available in India, which has led to a serious barrier to the creation of national geospatial data infrastructure (Kumar 2006). Therefore, the authors strongly recom- mend that following this method, a standard can be formulated about the level of accuracy and other parameters to be achieved for digital cadastral map. Moreover, a digital cadastral map with updated land- related information is one of the prime requisites for any Land Information System (LIS), a component of a LAS. Consequently, this can be used as a basis for a cadastre- based LIS preparation. Land Administration (Athens, Greece, 28–31 May 2003). Enemark, S. 2006. The land management perspective: building the capacity. In: Land administration: the path towards tenure security, poverty alleviation and sustainable development. ITC, Enschede, The Netherlands. Enemark, S. 2012. Sustainable land governance: spatial enabled, fit for purpose and supporting the global agenda. World Bank Conference on Land and Poverty, Washington, US, April 2012. Ghosh, J. K. and Dubey, A. 2009. Impact of India’s new map policy on accuracy of GIS theme. Journal of the Indian Society of Remote Sensing, 37, pp. 215–221. Habibullah, W. and Ahuja, M. eds. 2005. Land reforms in India – computerization of land records. Vol. 10. New Delhi, India: SAGE Publications Pvt. Ltd. Indian Mapping Policy, 2005. Survey of India. Available at: http:// www.surveyofindia.gov.in/files/nmp/National%20Map%20Policy.pdf. ISO. 2012. ISO 19152:2012. Geographic information – Land Administration Domain Model (LADM). Geneva, Switzerland: International Organization for Standardization (ISO). It is recommended to continue this research with developing a methodology for: Jing, Y., Bennett, R. M. and Zevenbergen, J. A. 2013 Up-to-dateness in land administration: setting the record straight. In: Proceedings of FIG working week 2013, Abuja, Nigeria, 6–10 May 2013 – Environment for Sustainability. Copenhagen: FIG, 2013. ISBN: 978-87-92853-05-9. 16 p. References 2 updating the colonial cadastral maps; 2 updating the land registers; 2 linking the maps and registers; 2 linking the maps and registers; 2 the inclusion of a mechanism for historical data retrieval; and p Kansu, O. and Sezgin G. 2006. The availability of the satellite image data in digital cadastral map production. In: XXIII International Survey Review 2016 VOL 48 NO 349 267 Sengupta et al. Constructing a seamless digital cadastral database-Indian perspective FIG Congress: Shaping the change, 8–13 October 2006, Munich, Germany. FIG Congress: Shaping the change, 8–13 October 2006, Munich, Germany. Salzmann, M. A. 1996. A unified approach to geometric quality assurance of cadastral mapping in the Netherlands. Geographical Information: from research to application through cooperation. In: M. Rumor, R. McMillan and H. F. L. Ottens, eds. V Congreso de la Asociaci¢n Espanola de Sistemas de Informacion Geogr fica. Vol. 2. Amsterdam: IOS Press. pp. 954–963. Kumar, N. 2006. Renovating cadastral map – an Indian perspective. Enschede: ITC Publication. Lemmen, C. H. J. and Zevenbergen, J. A. 2010. First experiences with a high-resolution imagery-based adjudication approach in Ethiopia. In: K. Deininger, C. Augustinus, S. Enemark and P. Munro-Faure, eds. Innovations in land rights recognition, administration, and governance. Washington D.C: The World Bank. pp. 96–104. Salzmann, M. A. Hoekstra, A. and Schut, T. 1997. Quality issues in cadastral map renovation. Paper presented at JEC-GI’97 (workshop on quality assurance in large-scale mapping), Vienna, 16–18 April 1997. Lemmen, C. H. J., Zevenbergen, J. A., Lengoiboni, M., Deininger, K. and Burns, T. R. 2009. First experiences with high resolution imagery based adjudication approach for social tenure domain models in Ethiopia. In: Proceedings FIG – World Bank Conference: Land governance in support of the Millennium development goals, responding to new challenges, 9–10 March, 2009, Washington, D.C. 22 p. Sengupta, A., Bandyopadhyay, D., Lemmen, C. H. J. and van der Veen, A. 2012. Constructing a cadastral database using colonial cadastral maps and satellite imagery: An Indian perspective: e- book. International Federation of Surveyors (FIG), International Office of Cadastre and Land Records (OICRF), 2012. ISBN: 978- 87-92853-00-4. Nagarajan, B. 2001. Need for introduction of a regular projection & grid system for cadastral Mapping. Dehradun, India: INCA. Sengupta, A., Bandyopadhyay, D., Lemmen, C. H. J. and van der Veen, A. 2013. Potential use of LADM in cadastral data management in India. Survey Review 2016 VOL 48 NO 349 268 References In: Proceedings of the 5th Land Administration Domain Model (LADM) workshop, 24–25 September 2013, Kuala Lumpur, Malaysia. pp. 311–328. ISBN: 978-87-92853-06-6. NLRMP Guidelines. 2008–2009. Technical manuals and MIS. Department of Land Records, Government of India. Ondulo, J. and Kalande, W. 2006. High spatial resolution satellite imagery for PID improvement in Kenya, shaping the change. In: XXIII International FIG Congress, October 8–13, 2006, Munich, Germany. Shi, W. Z. 1994. Modeling positional and thematic error in integration of GIS and remote sensing. Enschede: ITC Publication. Palm, L. 2006. Comparison of total station/advanced GPS survey and high resolution satellite imagers. The National Conference on Standardization of Rural Land Registration and Cadastral Survey Methodologies, United Nations Conference Centre, Addis Ababa Ethiopia, March 20–24, 2006. Song, W. H. 2008. Cadastral map renovation – an analysis of the South Korean perspective. Enschede: Netherlands. Downloaded by [Universiteit Twente.] at 05:51 21 December 2017 Tuladhar, A. M. 2005. Innovative use of remote sensing images for pro- poor land management. FIG Expert Group Meeting on Secure Land Tenure: New Legal Frameworks and Tools, Bangkok, Thailand, December 2005. Paudyal, D. R. and Subedi, N. R. 2005. Identification of informal settlement by integration of cadastral information and remote sensing satellite imagery. A Seminar on Space Technology Application and recent development in geo-spatial products in Kathmandu, Nepal, August 19, 2005. Van der Molen, P. 2003. The future cadastres after 2014. FIG Working Week 2003. Paris, France. Williamson, I. P., Enemark, S., Wallace, J. and Rajabifard, A. 2010. Land administration for sustainable development. Redlands, CA, USA: ESRI Press. Positional Accuracy Handbook. 1999. Minnesota Planning Land Management Information Center. Available at ,http://www.mnplan. state.mn.us/pdf/1999/lmic/nssda_o.pdf..
https://openalex.org/W4387908005	https://ijpds.org/article/download/2156/4960	English	null	Establishment of a birth-to-education cohort of 1 million Palestinian refugees using electronic medical records and electronic education records	International journal of population data science	2,023	cc-by	11,255	International Journal of Population Data Science (2023) 8:1:23 International Journal of Population Data Science (2023) 8:1:23 Results We established a birth cohort of Palestinian refugees using electronic records of 972,743 live births. We found high levels of linkage to health records overall (83%), which improved over time (from 73% to 86%), and variations in linkage rates by setting: these averaged 93% in Gaza, 89% in Lebanon, 75% in Jordan, 73% in West Bank and 68% in Syria. Of the 423,580 children age-eligible to go to school, 47% went to UNRWA schools and comprised of 197,479 children with both health and education records, and 2,447 children with only education records. In addition to year and setting, other factors associated with non-linkage included mortality and having a non-refugee mother. Misclassification errors were minimal. https://doi.org/10.23889/ijpds.v8i1.2156 October 24, 2023 © The Authors. Open Access under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/deed.en) Introduction By linking datasets, electronic records can be used to build large birth-cohorts, enabling researchers to cost-effectively answer questions relevant to populations over the life-course. Currently, around 5.8 million Palestinian refugees live in five settings: Jordan, Lebanon, Syria, West Bank, and Gaza Strip. The United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA) provides them with free primary health and elementary-school services. It maintains electronic records to do so. 1Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom 2School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan 3United Nations Relief and Works Agency for Palestinian Refugees in the Near East, UNRWA headquarters, Amman, Jordan 4Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, South Carolina, USA 5Center for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut Lebanon 1Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom 2School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan 3United Nations Relief and Works Agency for Palestinian Refugees in the Near East, UNRWA headquarters, Amman, Jordan 4Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, South Carolina, USA 5Center for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut Lebanon We aimed to establish a birth cohort of Palestinian refugees born between 1st January 2010 and 31st December 2020 living in five settings by linking mother obstetric records with child health and education records and to describe some of the cohort characteristics. In future, we plan to assess effects of size-at-birth on growth, health and educational attainment, among other questions. Methods We extracted all available data from 140 health centres and 702 schools across five settings, i.e. all UNRWA service users. Creating the cohort involved examining IDs and other data, preparing data, de-duplicating records, and identifying live-births, linking the mothers’ and children’s data using different deterministic linking algorithms, and understanding reasons for non-linkage. Establishment of a birth-to-education cohort of 1 million Palestinian refugees using electronic medical records and electronic education records Zeina Jamaluddine1,2, Akihiro Seita3, Ghada Ballout3, Hussam Al-Fudoli3, Gloria Paolucci3, Shatha Albaik3, Rami Ibrahim3, Miho Sato2, Hala Ghattas4,5, and Oona M. R. Campbell1,∗ ∗Corresponding Author: Email Address: oona.campbell@lshtm.ac.uk (Oona M. R. Campbell) ∗Corresponding Author: Conclusion This linked open birth-cohort is unique for refugees and the Arab region and forms the basis for many future studies, including to elucidate pathways for improved health and education in this vulnerable, understudied population. Our characterization of the cohort leads us to recommend using different sub-sets of the cohort depending on the research question and analytic purposes. International Journal of Population Data Science Journal Website: www.ijpds.org Establishment of a birth-to-education cohort of 1 million Palestinian refugees using electronic medical records and electronic education records Abstract Submission History Submitted: 14/04/2023 Accepted: 04/09/2023 Published: 24/10/2023 Aim We aimed to build a live birth-cohort to enable us to explore the effects of risk factors and exposures in pregnancy (e.g., previous obstetric history, complications in pregnancy, and pollution, temperature, and conflict), and of factors recorded via the obstetric record, (e.g., pregnancy outcome, gestation, birthweight, multiples, and mode of delivery) on adverse health and educational outcomes among children. Electronic data present challenges in terms of data- capture and linkage [6]; it is important to detect the extent of errors including misclassification, temporal data changes, missing data, and duplicated records and to identify the population included and excluded. Linking electronic data adds further challenges depending on the methods used for linkage (deterministic or probabilistic methods), the presence of duplicated records (causing additional linkage error), estimation of error rates (with challenges in obtaining a gold standard), and identification of the population (understanding who does and does not link) [6–8]. We identified a group of women eligible to access UNRWA services with a pregnancy that ended from 2010-2020. For the subset with live births, we aimed to link information from mothers’ obstetric records to UNRWA child health records and education records to create a live-birth cohort, and to describe some of its characteristics. Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Methods Palestinian refugees include all descendants of Palestine refugee males, who are “persons whose normal place of residence was Palestine during the period 1 June 1946 to 15 May 1948, and who lost both home and means of livelihood as a result of the 1948 conflict”. Palestinian refugees comprise 20% of the global refugee population and have experienced displacement and marginalisation since 1948 [9]. Currently, around 5.8 million Palestinian refugees live in 58 camps and multiple informal gatherings in five settings: Jordan, Lebanon, Syria, West Bank, and Gaza Strip (representing an estimated 45% of all Palestinians) [9, 10]. The United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA) is responsible for providing free primary health and elementary-school services to the refugees [10], and runs 140 health centres and 702 schools to do so [11]. UNRWA also supports Palestinian refugees’ access to secondary and tertiary health-care services via a partial reimbursement scheme. To create the cohort, we 1) examined IDs and other data, 2) prepared the data, de-duplicated records, and identified live- births 3) linked the mothers’ and children’s data using different deterministic linking algorithms, and 4) clarified reasons for non-linkage. Introduction UNRWA schools, and some use host-country public or private schools. Refugees and urban-poor populations remain under-studied globally because their unstable living circumstances make them difficult to research, especially longitudinally. The Arab region has few longitudinal cohorts [1], little research on refugees or the urban-poor, and limited research using individual-level electronic records at a large scale. UNRWA has consistently invested in record- keeping, and now maintains electronic administrative databases to provide its health and education services, namely an electronic health records system (E-health) and an Education Management Information System (EMIS). E-health was developed in 2010 as a web-based, patient- centred digital system to manage UNRWA’s increasing workload and to improve the quality of its health care provision [14]. E-health started gradually in clinics and was updated in 2013 and 2017. EMIS was launched in the 2016/2017 school year to manage education data in UNRWA schools and improve overall educational quality. Both systems include identification numbers (IDs) which allow for deterministic linkage. Large longitudinal studies are enormously beneficial in elucidating factors shaping human capital, including health and educational outcomes [2, 3]. The use of existing electronic records to build large birth-cohorts offers a cost-effective alternative to traditional birth cohorts, enabling researchers to answer questions relevant to populations over the life- course. Linked data make more information available, allowing analyses in different domains, for instance, understanding the effects of ill-health on educational attainment. Recently for example, linked administrative data have been used to model disease patterns and to examine factors associated with COVID-19 infection and related deaths to inform timely policy changes [4, 5]. Keywords Keywords electronic records; data linkage; mother child; Palestinian refugees; health records; education records; refugee birth cohort y electronic records; data linkage; mother child; Palestinian refugees; health records; education records; refugee birth cohort https://doi.org/10.23889/ijpds.v8i1.2156 October 24, 2023 © The Authors. Open Access under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/deed.en) A cohort of refugees from E-health and EMIS All records of pregnancies that ended between 1 January 2010 and 31 December 2020 (whether they resulted in live birth, early foetal death, stillbirth, miscarriage) were extracted from E-health, as were health and education records of children born in the same period in Jordan, Lebanon, Syria, West Bank and Gaza. All the health information was stored in the E-health system while all the education data was stored in the EMIS system. Access to UNRWA services differs by setting (Box 1). In 2021, UNRWA recorded 3,090,084 refugees accessed their health services, indicating not all 5.8 million Palestinian refugees are UNRWA service recipients [12]. Some, particularly the better-off, may use alternative services in the host communities [12, 13], yet others may use a mix of UNRWA and other service providers. In 2021, UNRWA recorded that 526,646 students attended their schools; as with healthcare [11], not all Palestinian children enrol in Figure 1 shows the key variables extracted from each of the three dataset: (1) mother E-health dataset including mother information, mother antenatal care (ANC) visit, mother obstetric records, (2) child E-health dataset including child information, child health data (including immunisation, growth monitoring, motor development, physical examination, outpatient visits, and laboratory results), (3) child EMIS 2 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Box 1: Political, social, health and education system context of Palestinian refugees Country (setting) where Palestinian refugees are located Jordan Lebanon Syria West Bank Gaza Number of registered refugees reported by UNRWA in 2021 [11, 12] 2,334,789 482,676 575,234 883,950 1,516,258 Estimated percentage of total national population that are refugees (World Bank population data in 2021 [12, 15]) 21% 9% 3% 30% 78% Political/Social context Most Palestinians have Jordanian nationality since 2009. Use of Jordanian government services permitted. Palestinians’ right to work & access to government services is severely constrained. Not eligible to use Lebanese public primary healthcare or schools. Massive internal displacement since 2011. 137,234 Palestinians in Syria fled to Lebanon & Jordan; an estimated 438,000 remain. Dual systems for Israeli settlers & Palestinians, restricting Palestinian rights and travel. Eligible to use public Palestinian Authority services. Blockade & travel restrictions. Eligible to use public Palestinian Authority services. Health and education context UNRWA co-finances hospitalisation services. UNRWA provides secondary school education. UNRWA co-finances hospitalisation. Starting in 2011, UNRWA services affected by conflict. UNRWA co-finances hospitalisation. Multiple checkpoints restricting access. UNRWA co-finances hospitalisation. A cohort of refugees from E-health and EMIS UNRWA co-finances hospitalisation services. Number of UNRWA health centres in 2021 [11] 25 27 23 43 22 Number of UNRWA schools in 2021 [11] 161 65 102 96 278 Estimated pregnant Palestinian refugees using UNRWA antenatal care services in 2022 [16] 35% 63% 42% 54% 73% Pregnant women using UNRWA antenatal care at least once with 4 or more antenatal visits in 2022 [16] 81% 75% 55% 90% 98% Deliveries by trained personnel in 2022 [16] 100% 100% 100% 100% 100% Children aged 12 months old receiving all vaccine immunisation (BCG, IPV, Poliomyelitis, DPT, Hepatitis B, Measles, Hib) in 2022 [16] 99% 97% 98% 100% 99% Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Box 1: Political, social, health and education system context of Palestinian refugees UNRWA’s primary care model provides for children to routinely undergo specific preventive measures, and it collects child health data on these accordingly, including immunisation as per host country schedules, growth monitoring (ages 0 to 59 months), motor development (ages 0 to 23 months), and periodic physical examinations (for new-borns and at 12 and 36 months). In 2017, they introduced mandatory screening for anaemia at 12 months. When care is sought for children who are ill, there may be additional outpatient records or laboratory-test results. This is an open cohort, for the children E-health records we extracted data from 01 January 2010 until 14 September 2021 (the day of the extraction) for the linkage. Elementary school enrolment is mandatory (and free) from 6 years of age in all settings. Children born in 2010 would have reached age 6 and entered Grade 1 beginning in the 2016/17 academic year, with subsequent birth years entering school in the following years. Extraction of the education data was done in a yearly basis with total of 5 academic years extracted. Data dataset including child education information, and child education. UNRWA’s primary care model provides for children to routinely undergo specific preventive measures, and it collects child health data on these accordingly, including immunisation as per host country schedules, growth monitoring (ages 0 to 59 months), motor development (ages 0 to 23 months), and periodic physical examinations (for new-borns and at 12 and 36 months). In 2017, they introduced mandatory screening for anaemia at 12 months. When care is sought for children who are ill, there may be additional outpatient records or laboratory-test results. A cohort of refugees from E-health and EMIS This is an open cohort, for the children E-health records we extracted data from 01 January 2010 until 14 September 2021 (the day of the extraction) for the linkage. Data from the mother’s information included sociodemographic information and IDs with which to link mothers to their children. Mother’s ANC records included women’s medical history, reproductive health, and ANC received. Data from the mother’s obstetric records included date of delivery, delivery outcome (live birth, stillbirth, early foetal death, miscarriage), multiple foetuses (twins/triplets/quadruplets), birthweight, gestational age, place of delivery, sex of live births, and mode of delivery. UNRWA partially covers childbirth costs, so neonatal information is gathered from the hospital records at billing and entered into the system after delivery as part of the women’s obstetric records. Active surveillance of pregnancy outcomes for women who sought ANC takes place, with a call-back mechanism in case no pregnancy outcome is recorded. Elementary school enrolment is mandatory (and free) from 6 years of age in all settings. Children born in 2010 would have reached age 6 and entered Grade 1 beginning in the 2016/17 academic year, with subsequent birth years entering school in the following years. Extraction of the education data was done in a yearly basis with total of 5 academic years extracted. Data 3 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Figure 1: Variables extracted from maternal, child health records and child education records (grey mother E-health dataset, blue child E-health dataset, purple child EMIS dataset) Identifying IDs in different records International Journal of Population Data Science (2023) 8:1:23 Figure 2: Lexis diagram containing age of the child and source of the variables collected We cleaned open-text fields using text-mining tools to check different phrasings and spellings of “twins,” “triplets,” “quadruplets," and “multiples” (e.g., “tribblets”) and of “death” (e.g., “died at 3 min”) in English and Arabic. We then standardised the coding of these terms. data on neonatal outcomes without child-specific IDs. Child- specific IDs, the CMFN, are listed for each woman in the mother information records (column 1) showing all her children who have used UNRWA services; this is unlinked with neonatal outcomes. To link live births to children’s health and education records, we excluded records of pregnancies that ended in miscarriage, early foetal death, or stillbirth, and records that were marked as training data or erroneous data (system- recorded errors). We then marked mothers’ obstetric records with the same mother and the same delivery date as being either potential multiple pregnancies or duplicated records. Identifying IDs in different records from EMIS captures information on students as they enter Grade 1 and progress in school from one year to the next. Extracted data included student characteristics, absenteeism, school performance, special education, class repetition and school drop-out. Six different IDs could potentially be used for linkage. The E- health system generates a unique Mother Medical File Number (MMFN) for each mother and a unique Child Medical File Number (CMFN) for each child. UNRWA also generates a unique refugee registration ID (RRIS) for each refugee and a family registration ID: MRRIS for mothers; CRRIS for their children; and FRRIS for families. As with birth registration, the CRRIS is generated when parents register their child in the system, so the first ID a child usually gets is the CMFN which is generated automatically by the E-health system when the child uses UNRWA services. In some cases, if the child was never taken to UNRWA services, the obstetric record might not have a CMFN. The CRRIS and FRRIS are also recorded in EMIS. p The Lexis diagram (Figure 2) indicates the different component datasets, and the time points when specific records could be accessed from E-health and EMIS to contribute to the birth cohort. The cohort (year of birth) is depicted as a blue diamond along the x-axis and the age of the child is on the y-axis. The shaded areas indicate the availability of data based on the cohort, age of the child, and the different types of records. For example, all children are expected to have records of routine preventive child health care (immunisation, growth, and motor monitoring records) up to 5 years of age, and education records starting at 6 years old. Haemoglobin level measurement for children at 1 year old (indicated using a red droplet) started in 2017. Outpatient and laboratory records are available at all ages (and into adulthood) for those needing these services. The different IDs available in the various mother, child health, and education records are shown in Figure 3, with pink and blue lines highlighting the IDs used to link across the various datasets. The obstetric records (column 3) include 4 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Figure 2: Lexis diagram containing age of the child and source of the variables collected Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Jamaluddine Z et al. Data linkage using multi-step deterministic methods Duplicated records were those with no mention of being a multiple, and where the records did not link to two or more different child IDs. We removed these duplicates leaving only one record, and then re-ran the linkage stages 1-4 with all the records (multiples and de-duplicated records, and all non- duplicate records). We removed the duplicated records that had missing data in one record entered in the birthweight measure as compared to the other records. Where duplicate records had contradicting information, we kept the last record of the duplicated records. The data linkage was conducted in four stages, linking: Stage 1) the mothers’ information to the mother’s ANC and the mother’s obstetric outcomes; Stage 2) the mother’s data from Stage 1 to the child information dataset; Stage 3) the dataset from Stage 2 to the child health datasets; and Stage 4) the information from Stage 2 to the child education dataset. The overall ID linkage stages are presented in Figure 3. When doing the linkage, we blocked on setting because each setting generates its own data (which are concatenated in UNRWA headquarters) and refugees rarely move across settings, and to help with managing a very large data set. We calculated the percentage linking after adding synthetic records for missing multiples and removing duplicated records. We also assessed percentages after removing children with missing CMFNs (i.e., only keeping children that used UNRWA services). We ran the linkage process twice. The first time included only multiple pregnancies and duplicated records and aimed to distinguish duplicated records from multiple pregnancies based on the stages 1-4 described above. In some cases, data for multiples were entered as a single birth, with open text indicating the delivery resulted in twins, triplets, or quadruplets. We generated (and flagged) synthetic records for these missing multiples (additional twins, triplets, etc.,) based on the original obstetric record. This involved creating a record for each child we knew about to: (1) redress a limitation in the data structure as designed in E-health (2) allow us to have a more comprehensive dataset with proper denominator of live births, (3) retain information on maternal variables such as age and education, as well as ANC variables. These maternal and ANC attributes apply equally to all foetuses in a given pregnancy. It was only birthweight that is potentially incorrect. Stage 1- linking mother’s data sets We first used the MMFN to link the mother’s information with her ANC records and her obstetric outcomes. The mother’s information includes a CMFN of all her children, without information on their birth order, date of birth, and sex. The mother’s obstetric record lists the child’s sex, delivery date, and multiple pregnancies, but does not have a child ID, for example, a CMFN. Data linkage using multi-step deterministic methods This information is clearly flagged in the dataset, and we record clear information to data users on how these variables can be used effectively. Data preparation, de-duplication of records and identification of multiple pregnancies Data preparation involved cleaning specific open-text variables, selecting live births, distinguishing between multiples (twins, triplets, etc.,) and duplicated records, and removing the latter. 5 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Figure 3: Steps in linkage of the different datasets (indicating the IDs used for linking in the different steps) Figure 3: Steps in linkage of the different datasets (indicating the IDs used for linking in the different steps) Figure 3: Steps in linkage of the different datasets (indicating the IDs used for linking in the different steps) Stage 2- linking mother information- obstetric with child information (from E-health) In Stage 2, we merged the Stage 1 mother datasets (1–3) with the child information dataset (4) via 11 steps. In all steps, we blocked on setting to ensure this was identical in both mother records and child records. In steps 1 to 9, we linked 6 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 the singleton births, then in steps 10 and 11, we linked multiple births. Since the MRRIS is the most accurate ID (most used in UNRWA to refer to individual refugees), we used this first as the “best linkage,” followed by linkage based on the CMFN. recorded mortality, and a composite of low birthweight, preterm, or multiples without recorded mortality (as a measure of being a high risk of mortality that may not be recorded). Children of non-refugee mothers, but where the male parent is a refugee, are included in these datasets because they are eligible for UNRWA services. Because the child’s information had the date of birth and the CMFN, we could then match the date of delivery/birth upon linking to the CMFN from the mother’s information, ensuring the obstetric record was given to the correct child. This approach worked for singleton or twins of discordant sex, but not for multiples of concordant sex. We also ran a multivariable regression analysis looking at determinants of failure to link (Appendix). The data cleaning, linkage and multivariable analyses were conducted using Stata software (StataCorp. Stata Statistical Software: Release 17. College Station, TX: StataCorp LL). The CART analysis was conducted using R software and rpart package (R Core Team, 2022, version 4.2.1 R Foundation for Statistical Computing, Vienna, Austria). In steps 1 to 3, we linked based on records having an identical month and year of delivery/birth, the same sex of the child, and the same MRRIS (step 1), same CMFN (step 2), and same FRRIS (step 3). In steps 4 to 5, we linked based on records having a delivery/birth date within plus or minus 90 days of each other and the same MRRIS (step 4), or the same CMFN (step 5). Then we allowed the delivery/birth date to be plus or minus 180 days and the same mother MRRIS (step 6), or the same CMFN (step 7). This was done to take into account the data entry errors in the delivery date or the date of birth. Data linkage Deterministic linkage mother with child health records (Steps 1 to 11) Stage 3- linking mother-child information with child health 3,851 birth records were synthetically added when pregnancy outcomes were marked as multiples (twins, triplets, or quadruplets), but only one birth record was available. In some cases, we had one record indicating both death and multiple (for example “1 twin died while the other survived”), another record indicating this was synthetically added. A total of 45,095 records had at least one other record with the same Mother IDs and the same delivery date. We were able to distinguish 18,378 as multiple pregnancies (as noted in the open text variable), 9,981 as singleton records, and 16,736 as duplicated records. We dropped the latter. We used the CMFN to link the dataset from Stage 2 (which linked datasets 1-4) to the child’s health records (dataset 5) including immunisation, growth monitoring, motor development, haemoglobin testing, outpatient visits, and laboratory results records. Examining IDs and other data From 1 January 2010 until 31 December 2020, a total of 1,158,354 pregnancy outcomes were extracted (Figure 4). For the linkage, we excluded 181 system-recorded errors as indicated in the open text and a total of 172,545 miscarriages, early foetal death, and stillbirth records and 181 system- recorded errors as indicated in the open text (Figure 4). ( ) ( ) For twins, triplets, and quadruplets (multiples) we linked based on identical dates of delivery/birth and same mother MRRIS ID (step 10) and same CMFN (step 11). Stage 2- linking mother information- obstetric with child information (from E-health) In steps 8 and 9, we removed the requirement for identical sex in steps 1 and 2, and linked based on MRRIS ID (step 8), and the same CMFN (step 9). Stage 4- linking mother-child health data with child education Children from Stage2 who reached age 6 years or above were linked to EMIS datasets 6 and 7 based on the CRRIS, identical setting, sex, and month and year of birth. This resulted in a total of 972,743 live birth records, born to women with an obstetric record, recorded in all five settings, of which 424,616 became eligible for school enrolment in the study time-period. From the child health records, in E-health, a total of 1,089,568 were extracted for the linkage. A total of 279,758 child education records were extracted from EMIS for the linkage. A total of 12,245 records mentioned death in an open text variable. Reasons for failure to link We developed hypotheses about structural (legitimate) and other reasons for data to not link and tested these using a classification and regression (CART) decision tree approach [17] to identify groups at substantial risk of not linking. CART repeatedly separates data into two groups, one with high levels of non-linkage and one with low by testing different cut-off points (for example the different year of delivery/birth), and splits the data based on the best within-group homogeneity. Deterministic linkage mother with child health records (Steps 1 to 11) Linkage increased from 69% in step 1 to 83% in step 11 (Table 1). The percentage linkage between mother and child records improved from 73% in 2010 to 86% in 2020 (Figure 5). Gaza had the highest linkage, followed by Lebanon, Jordan, Syria, and the West Bank (Figure 5). Information on mortality, mother’s refugee status, year of delivery/birth, sex of the child, birthweight, and gestational age were available and were used to predict non-linkage. Mortality of the child (whether neonatal or infant or other) was included in the mother’s obstetric records (thus this information is available in both linked and unlinked data). We also generated a low risk of mortality group (normal birthweight, term and singleton and not recorded as dead), In 79,942 cases, there was no CMFN in the mother’s records, most likely because their children did not use UNRWA services. By removing records with missing CMFN (in the 7 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Figure 4: Data preparation and de-duplication of records Figure 4: Data preparation and de-duplication of records ataset) to make a birth cohort of UNRWA health ers (mother used UNRWA ANC or obstetric services had at least one record within the E-health) linkage improved to 91% overall, from We refer to these as the “Stag dataset with children that used unlinked dataset) to make a birth cohort of UNRWA health service users (mother used UNRWA ANC or obstetric services and child had at least one record within the E-health) linkage improved to 91% overall, from 81% in 2010 to 94% in 2020. We refer to these as the “Stage 2 dataset” and the “Stage 2 dataset with children that used UNRWA health services”. 8 Jamaluddine Z et al. Reasons for failure to link Early mortality (as recorded in the obstetric records), and migration soon after birth were hypothesized as the main structural reasons why the obstetric and child health datasets might not link. Unlinked data had a higher percentage of early mortality and an increased presence of children vulnerable to mortality risks such as low birthweight or preterm infants even if their deaths weren’t explicitly recorded (Appendix Table 1). Unlinked data also contained a larger proportion of non-refugee mothers as compared to refugee mother. Unfortunately, we couldn’t assess migration-related non-linkage. Deterministic linkage mother with child health records (Steps 1 to 11) using UNRWA schools (education service users as denominator instead of among UNRWA health access users), coverage increased overall to 90%, and in Gaza (94%), Lebanon (94%), West Bank (87%), Jordan (83%), and Syria (72%). Figure 6 shows the percentage contributed by each linkage step per year. The percentage linking in steps 1 and 2 increased over time. Errors in the identical recording of the delivery/birth date were allowed for steps 4/5 (± 90 days) and step 6/7 (± 180 days); they decreased over time. Errors in recording sex (steps 8/9) were small and consistent over time. The percentage of multiples linking (steps 10/11) was the same across all years. Deterministic linkage mother with child health records (Steps 1 to 11) International Journal of Population Data Science (2023) 8:1:23 Table 1: Mother-child linkage steps: matching requirements Mother-child link Steps Field/ Setting Sex Multiple/ Duplicated records ID used Date of birth/ Delivery date match Numbers Linkage (%) N = 972,743 Linkage (%) children using UNRWA health services N = 892,801 1 Exact Exact No M RRIS Month and Year 674,968 69% 76% 2 Exact Exact No C MFN Month and Year 708,586 73% 79% 3 Exact Exact No F RRIS Month and Year 732,802 75% 82% 4 Exact Exact No M RRIS ±90 days 751,110 77% 84% 5 Exact Exact No C MFN ±90days 752,916 77% 84% 6 Exact Exact No M RRIS ±180 days 773,816 80% 87% 7 Exact Exact No C MFN ±180 days 774,556 80% 87% 8 Exact No M RRIS Month and Year 787,608 81% 88% 9 Exact No C MFN Month and Year 788,239 81% 88% 10 Exact Exact Multiple M RRIS Month and Year 811,221 83% 91% 11 Exact Exact Multiple C MFN Month and Year 811,871 83% 91% M RRIS Mother refugee registration ID. C MFN Child medical file number. F RRIS Family refugee registration ID. Figure 5: Percentage of mother-child linkage over time (a) overall (b) Stage 2 by setting and (c) Stage 2 children that use UNRWA services Figure 5: Percentage of mother-child linkage over time (a) overall (b) Stage 2 by setting and (c) Stage 2 children that use UNRWA ser ices Figure 5: Percentage of mother-child linkage over time (a) overall (b) Stage 2 by setting and (c) Stage 2 children that use UNRWA services Figure 5: Percentage of mother-child linkage over time (a) overall (b) Stage 2 by setting and (c) Stage 2 children that use UNRWA services Figure 6 shows the percentage contributed by each linkage step per year. The percentage linking in steps 1 and 2 increased over time. Errors in the identical recording of the delivery/birth date were allowed for steps 4/5 (± 90 days) and step 6/7 (± 180 days); they decreased over time Errors in recording using UNRWA schools (education service users as denominator instead of among UNRWA health access users), coverage increased overall to 90%, and in Gaza (94%), Lebanon (94%), West Bank (87%), Jordan (83%), and Syria (72%). Deterministic linkage of mother-child health records with education records The dataset from Stage 2 was linked to child health records (Stage 3) and education records (Stage 4). Linkage of the Stage 2 dataset of children that use UNRWA services to the child health records was extremely high at 98% (Figure 7). The live birth dataset had 424,616 records of children at an eligible age for school enrolment. These were linked to the EMIS data using CRRIS (available in the child health information records and the child education records). Around half of the children were linked (47%), but linkage differed by setting, with the highest linkage in Gaza (77%), Syria (72%), and Lebanon (64%), and the lowest in West Bank (33%) and Jordan (31%). When we looked at linkage among those Over time, unlinked data decreased, likely due to improved reporting, recording, and data entry (Figure 5 and Figure 6). Minimal data errors were identified in sex (1% error), location (0.05% error) or for recording live births as stillbirths (0.006% 9 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Figure 6: Percentage linked by each of the 11 steps, over time (different year of birth cohorts) Figure 6: Percentage linked by each of the 11 steps, over time (different year of birth cohorts) error) (Appendix Table 1). We found 69% of multiple pregnancies were of the same sex. not recorded as dead), recorded mortality, and a composite of low birthweight, preterm, or multiples without recorded mortality (as a measure of being a high risk of mortality that may not be recorded) had higher odds of not linking. Non- refugee mothers compared to refugee mother also had higher odds of not linking. The odds of not linking decreased over time. Figure 8 illustrates a decision tree segregating UNRWA- serviced Stage 2 children into various groups based on linkage levels. Three variables mortality, mother’s refugee status, and year of birth divided the data into four risk groups. The graph displays (1) group size (percentage of births the group represents out of all births), the percentage unlinked data in each group, the percentage of unlinked data out of all unlinked data. Discussion Mortality (group1) was the smallest group (1% of births) but had the highest prevalence of unlinked data (78%), followed by group2 without mortality recorded but with non- refugee mothers (4% of births with 44% of unlinked data), followed by group 3 (without morality, with a refugee mother, and with year of birth 2010-2012), which had 25% of births and 21% of unlinked data. No mention of mortality and having a refugee mother and a year of birth from 2013 onwards (group4) was the largest group (70% of births) and had the lowest prevalence of unlinked data (12%). We established a birth cohort of Palestinian refugees living in five settings from 2010-2020, using electronic medical records of 972,743 live births, and by linking mother and child health and education records. We found (1) high levels of linkage overall, which improved over time, (2) variations in linkage rates in the five different settings, and (3) factors associated with failure to link including the birth year, setting, mortality record (or risk factors for early mortality) and having a non-refugee mother. We also quantified the association between a failure to link and variables linked with structural lack of linkage (setting, mother’s non-refugee status, recorded mortality, risk factors for early mortality) and to reporting errors (setting, year) using logistic regression models (Appendix Table 2). Syria had the highest odds of data not linking followed by Jordan, West Bank and Lebanon as compared to Gaza. As compared to low risk of mortality group (normal birthweight, term and singleton and Establishment of a palestinian refugee cohort when defining the cohort as children who use UNRWA health services (91%). We note that linkage improved over time as experience with E-health increased and mis-recording in date of birth decreased (contributions of steps 4/5 and 6/7 to overall linkage decreased). Mis-classification data- entry errors were low (1% error for sex, 0.006% error for the delivery outcome, and 0.05% error for setting). Among children eligible for school, 47% linked, as not all children who used UNRWA health services also went to UNRWA schools. Among children attending UNRWA schools, 90% linked with E-health, indicating that children attending UNRWA schools were more likely to use UNRWA health services. It is possible to explore ways to increase the linkage with education data by loosening the criteria used for linkage (as was done for the mother-child linkage), for example if the date of birth criteria was loosened, as was done for health records in Stage 4. Linkage improvements over time are most likely to be because the E-Health system improved but may also be due to increased use of free UNRWA services as economic hardship foreclosed other options. Setting thus becomes a complex construct that encompasses both structural conditions, mortality, out-migration and data errors as reasons for non-linkage and for exclusion from the cohort. Characteristics of the population linking It is essential to recognise that the linked cohort is mainly of those children who used UNRWA services at least once. Access to, and use of, non-UNRWA services differs by setting and is reflected in the percentage of data linking to health and education. More children from Jordan and the West Bank are unlinked (probably because there are alternative choices available for refugee children) while those in Lebanon, Gaza and Syria have fewer options to use non-UNRWA services. In 2019, the Multiple Indicator Cluster Survey in Palestine found that 72% of children aged 5–17 in Gaza accessed UNRWA services, compared to only 22% in the West Bank [22], though this partly reflects the proportions of these populations that are refugees (67% and 30% respectively, see Table 1). Establishment of a palestinian refugee cohort Future analysis and recommendations The established, high-quality birth cohort presents a unique opportunity to explore key research questions concerning Palestinian refugees and urban-poor populations. For future analyses, we point out some considerations to enhance validity. Fi t d t lit d li k i d ti Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Figure 8: CART decision tree to determine the unlinked data Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Figure 8: CART decision tree to determine the unlinked data Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 The setting also reflects the timing of the introduction of E-health and the overall quality of record keeping and data entry which can in turn affect linkage. There are several indications from previous work [23] that records from Syria have the poorest recording of birth dates, and that data quality (assessed via digit preference and heaping) are weakest in Syria and Jordan. The conflict situation in Syria has almost certainly impacted the accuracy of the data collected and the linkage process. Migration might prevent the use of children’s health services. No studies of numbers of Palestinian-refugee specific migration were found in the literature, but news reports document that the adverse impacts of the conflict in Syria and the economic collapse in Lebanon on Palestinian refugees, have led to drownings during attempted illegal migrations [22, 23]. when defining the cohort as children who use UNRWA health services (91%). We note that linkage improved over time as experience with E-health increased and mis-recording in date of birth decreased (contributions of steps 4/5 and 6/7 to overall linkage decreased). Mis-classification data- entry errors were low (1% error for sex, 0.006% error for the delivery outcome, and 0.05% error for setting). Among children eligible for school, 47% linked, as not all children who used UNRWA health services also went to UNRWA schools. Among children attending UNRWA schools, 90% linked with E-health, indicating that children attending UNRWA schools were more likely to use UNRWA health services. It is possible to explore ways to increase the linkage with education data by loosening the criteria used for linkage (as was done for the mother-child linkage), for example if the date of birth criteria was loosened, as was done for health records in Stage 4. Establishment of a palestinian refugee cohort Endresen and Øversen (1994) [18] and Zureik and Tamari (2001) [19] have previously noted the research potential of UNRWA’s administrative data. Our study is the first use of these data to build a birth-cohort of Palestinian refugees. It provides a significant resource 10 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Figure 7: Linkage of (a) maternal records to child outpatient records, (b) maternal records of school-aged eligible children to child outpatient and education records Figure 7: Linkage of (a) maternal records to child outpatient records, (b) maternal records of school-aged eligible children to child outpatient and education records countries [20] or have not considered size for gestational age; such analyses are possible in our birth cohort. Another unusual feature of our cohort is that it includes five settings and services clustered in 140 health facilities and 702 schools, allowing for context-specific and comparative questions. for future understanding of associations, mechanisms, and problems for protracted refugees and urban poor, filling important gaps in the literature. Victora and Barros note that except for Brazil and India, the top 20 countries publishing on cohorts are all high-income [1]. Since exposures, disease patterns, policies, and health systems differ by setting, our longitudinal dataset will provide new possibilities to study a wide spectrum of policy-relevant questions that apply to urban-poor populations. For example, a 2023 review found that most studies examining the effect of size at birth on subsequent child wellbeing outcomes have been in high-income i Using multi-step deterministic algorithms, we reached a linkage rate of 83% overall for health records, with rates improving from 71% in 2010 to 86% in 2020. This is comparable to other studies linking mothers and children using deterministic methods, for example a linkage rate of 82% in Brazil [21]. The linkage percentage is even higher 11 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Figure 8: CART decision tree to determine the unlinked data when defining the cohort as children who use UNRWA health services (91%). We note that linkage improved over time as experience with E-health increased and mis-recording in date of birth decreased (contributions of steps 4/5 and 6/7 to overall linkage decreased). Mis-classification data- entry errors were low (1% error for sex, 0.006% error for the delivery outcome, and 0.05% error for setting). Establishment of a palestinian refugee cohort Among children eligible for school, 47% linked, as not all children who used UNRWA health services also went to UNRWA schools. Among children attending UNRWA schools, 90% linked with E-health, indicating that children attending UNRWA schools were more likely to use UNRWA health services. It is possible to explore ways to increase the linkage with education data by loosening the criteria used for linkage (as was done for the mother-child linkage), for example if the date of birth criteria was loosened, as was done for health records in Stage 4. Characteristics of the population linking It is essential to recognise that the linked cohort is mainly of those children who used UNRWA services at least once. Access to, and use of, non-UNRWA services differs by setting and is reflected in the percentage of data linking to health and education. More children from Jordan and the West Bank are unlinked (probably because there are alternative choices available for refugee children) while those in Lebanon, Gaza and Syria have fewer options to use non-UNRWA services. In 2019, the Multiple Indicator Cluster Survey in Palestine found th t 72% f hild d 5 17 i G d UNRWA The setting also reflects the timing of the introduction of E-health and the overall quality of record keeping and data entry which can in turn affect linkage. There are several indications from previous work [23] that records from Syria have the poorest recording of birth dates, and that data quality (assessed via digit preference and heaping) are weakest in Syria and Jordan. The conflict situation in Syria has almost certainly impacted the accuracy of the data collected and the linkage process. Migration might prevent the use of children’s health services. No studies of numbers of Palestinian-refugee specific migration were found in the literature, but news reports document that the adverse impacts of the conflict in Syria and the economic collapse in Lebanon on Palestinian refugees, have led to drownings during attempted illegal migrations [22, 23]. Linkage improvements over time are most likely to be because the E-Health system improved but may also be due to increased use of free UNRWA services as economic hardship foreclosed other options. Setting thus becomes a complex construct that encompasses both structural conditions, mortality, out-migration and data errors as reasons for non-linkage and for exclusion from the cohort. Future analysis and recommendations The established, high-quality birth cohort presents a unique opportunity to explore key research questions concerning Palestinian refugees and urban-poor populations. For future analyses, we point out some considerations to enhance validity. First, data quality and linkage improved over time, especially from 2013 on, and again from 2017 on, (these years were identified by the CART analyses and were also when UNRWA updated its E-health system). Researchers may wish The established, high-quality birth cohort presents a unique opportunity to explore key research questions concerning Palestinian refugees and urban-poor populations. For future analyses, we point out some considerations to enhance validity. First, data quality and linkage improved over time, especially from 2013 on, and again from 2017 on, (these years were identified by the CART analyses and were also when UNRWA updated its E-health system). Researchers may wish 12 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 to restrict their analyses to data from these years or consider running sensitivity analyses to ensure data quality in early years is not affecting results. for services. Deaths are recorded on the obstetric record, but in a free text format that needs cleaning, UNRWA also has a death registration system, but this is voluntary, and families may have little reason to report deaths, leading to under-reporting. This analysis pinpointed to UNRWA the need for a more accurate system to capture mortality data. The multivariable analysis characterising the failure to link found that neonates at higher risk of morality (low birthweight, preterm, or multiple pregnancy) had higher odds of not linking even though they were not reported as dead. This suggests deaths were missed and that researchers interested in mortality will need to examine the full birth cohort (including unlinked data) and include other sources (RRIS) or verification of the survival or migration status of children lost to follow-up. f Second, the characteristics of the data that linked need to be understood to avoid selection bias, and properly translate research to policy changes for specific populations. The service-use context suggests that our cohort (of UNRWA service users) is most likely to be generalisable to the entire population of Palestinian refugees in in Gaza, Lebanon and Syria. By contrast, refugees from Jordan and West Bank appeared to use a greater variety of non-UNRWA services or a mix of UNRWA and non-UNRWA services, potentially leading to only the most vulnerable refugees accessing UNRWA services. Future analysis and recommendations Our CART analysis also showed children with refugee fathers, but non-refugee mothers, were also less likely to link, possibly because non-refugee mothers could provide their children with access to alternative services. The CART analysis proved to be a useful method for identifying distinct groups within non-linkage data by utilising a combination of different variables and could be used for other linkage studies. This dataset offers a tremendous resource for answering important research questions on human capital development of urban-poor and of refugees. Some examples of planned research include exploring the effect of being post-term on size- at-birth and mortality outcomes, the effects of size-at-birth on child obesity, the association between recurrent infection and school performance, or the effects of exposure to conflict or high temperature on birth outcomes and child health and education attainment. However, this study has some limitations. We limited our evaluations of internal data quality to the characteristics of individuals that did or did not link, and to data recording and data-entry error rates based on date of birth/delivery, sex, setting and pregnancy outcome. There was no gold standard to evaluate the true or false matches, or the sensitivity and specificity of the linkage...[24]. UNRWA is consistently seeking to improve its system and this analysis allowed us to pinpoint points of changes to improve the data captured by E-health system. Third, most cohorts in the literature are based in a single country, whereas ours is in five settings (4 countries). This allows for the possibility to examine variations across populations and clusters from five settings, 140 health clinics, and 702 schools. Setting may well be an effect-modifier though, so analyses combining more than one setting need to consider this. Fourth, multiples (twins, triplets, etc.,) are a challenge in datasets, and many researchers exclude them, even though they are at high risk of adverse outcomes. We retained this important subgroup in our cohort. However, researchers may need to exclude multiples from analyses when using birthweight as an exposure, or alternatively to use imputation methods or sensitivity analyses. This is because some multiples did not have a record for each child, so we created (and flagged) a synthetic record for the second or third neonate (twin or triplet, etc.,) based on the original obstetric record, affecting mainly the birthweight variable where using the same weight for each birth could lead to misclassification. Future analysis and recommendations In case of duplicated records with contradicting birthweight results, we propose that future studies using this cohort to conduct a sensitivity analysis on the effect of choosing a different record. Moreover, even when birthweights of all multiples were recorded, we could not be certain which child they belonged to unless the sex was discordant, since the obstetric records had no child ID. Other variables affected by the lack of a child ID (i.e., gestational age, mode of delivery, date of birth, place of delivery) are not problematic because they can be assumed to be identical or very similar for all babies within multiple pregnancies. Moreover, even the potential discordance of birthweight in multiples can be quantified; the literature reports only 16% of multiples have birthweights that are more than 20% different. In future, we hope it will be possible to identify funds to allow data to be shared based on specific requests, subject to review by an independent research review board. Due to the vulnerable position of refugees, and the sensitive nature of their information, utmost care is needed to protect their privacy and to ensure research does not stigmatise them. UNRWA, being the primary collector of personal data of Palestinian refugees, has established a robust data protection system. We would seek to ensure specific components, such as de-identified participant data, linkage procedures, and the statistical analysis plan may be shared for designated analyses to be permitted under a formal access agreement. Role of funder/sponsor statement The funder had no role in study design, data collection, data analysis, data interpretation, or writing. 6. Christen P, Schnell R. Common Misconceptions about Population Data. arXiv preprint arXiv:211210912. 2021. https://doi.org/10.48550/arXiv.2112.10912 Statement on conflicts of interests AS, GB, HA, SA, GP, and RI are employed by UNRWA. The other authors (ZJ, MS, HG, OC) declare no competing interests. 7. Harron K, Dibben C, Boyd J, Hjern A, Azimaee M, Barreto ML, et al. Challenges in administrative data linkage for research. Big data & society. 2017;4(2):2053951717745678. https://doi.org/10.1177/2053951717745678 Funding statement This research was supported by the Nagasaki University “Doctoral Program for World-leading Innovative and Smart Education” for Global Health, KYOIKU KENKYU SHIEN KEIHI, Ministry of Education, Culture, Sports, Science and Technology (MEXT). 5. Victora CG, Castro MC, Gurzenda S, Medeiros AC, França GV, Barros AJ. Estimating the early impact of vaccination against COVID-19 on deaths among elderly people in Brazil: Analyses of routinely-collected data on vaccine coverage and mortality. EClinicalMedicine. 2021;38:101036. https://doi.org/10.1016/j.eclinm.2021.101036 Contributors statement OC conceived the use of UNRWA electronic records for linkage; ZJ, HG, AS, and OC designed the study approach; AS, GB, HA, SA, GP and RI guided the understanding of the dataset structure, GB, HA, SA and RI supported in the extraction of the data; GP encrypted the data; MS, HG, and OC supervised the data analysis; ZJ and OC analysed the data. ZJ wrote the first draft. All authors contributed to the writing of the paper. All authors read and approved the final version. 8. Harron K, Doidge JC, Goldstein H. Assessing data linkage quality in cohort studies. Annals of Human Biology. 2020;47(2):218–26. https://doi.org/10.1080/03014460.2020.1742379 9. United Nations High Commissioner for Refugee (UNHCR). United Nations High Commissioner for Refugee: Figures at a Glance 2022 [Available from: https://www.unhcr.org/figures-at-a-glance.html ZJ wrote the first draft. All authors contributed to the writing of the paper. All authors read and approved the final version. Conclusion We established a Palestinian refugee birth cohort from 2010- 2020 using electronic medical records of 972,786 live births, linking mother and child health from 140 primary clinic and education records from 702 schools. We also established criteria for selecting different sub-sets of the cohort depending on the research question and the analytic purposes. Since exposures, disease patterns, policies, and health systems differ by setting, this creates an invaluable resource for future research aiming to elucidate pathways for improved health and education in this vulnerable and understudied population. f Fifth, and finally, this analysis provides opportunities to improve the E-health system. As we showed, examining mortality using our data would require further work to identify deaths and to assess the survival status of children lost- to-follow-up. Child health records do contain a variable to record the date of death, but most deaths occur early, before most neonates are brought into the primary care facilities 13 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Acknowledgement movies. Journal of Adolescent Health. 2012;51(6):S3-S4. https://doi.org/10.1016/j.jadohealth.2012.09.003 We acknowledge the UNRWA clinic doctors, midwives, nurses, staff clerks, UNRWA school directors, teachers, and staff who entered the data used to build the cohort. UNRWA Information Technology staff and nurses in Jordan and Lebanon explained the system and the Lebanon field office shared the E-health support booklet used to make the data dictionary. We acknowledge UNRWA staff who supported in the data extraction Mohammad Shraim, Mohammad Habeeb, Anas Alhroub, Nema El-Faleet and Fuad Jadallah. We also acknowledge the SILA research group Sawsan Abdul Rahim, Bassam Abou Hamad, Chaza Akik, Imad El Hajj, Weeam Hammoudeh, Stephen McCall, Nisreen Salti, Aline Semaan, Sam Rose. We also thank Nagasaki University staff who helped administer the WISE grant. 2. Victora CG, Adair L, Fall C, Hallal PC, Martorell R, Richter L, et al. Maternal and child undernutrition: consequences for adult health and human capital. The lancet. 2008;371(9609):340-57. https://doi.org/10.1016/S0140-6736(07)61692-4 3. Victora CG, Christian P, Vidaletti LP, Gatica-Domínguez G, Menon P, Black RE. Revisiting maternal and child undernutrition in low-income and middle-income countries: variable progress towards an unfinished agenda. The Lancet. 2021;397(10282):1388-99. https://doi.org/10.1016/S0140-6736(21)00394-9 4. Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature. 2020;584(7821):430-6. https://doi.org/10.1038/s41586- 020-2521-4 Ethics statement 10. United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA). Annual operational report 2021. 2021. Approval to use de-identified encrypted data was obtained from ethics committees of the London School of Hygiene and Tropical Medicine, Nagasaki University, and UNRWA’s research review board. No identifiers (apart from encrypted IDs) were shared with researchers outside UNRWA. 11. United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA). UNRWA- Where we work [Available from: https://www.unrwa.org/where- we-work References 12. United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA). UNRWA- Departement of health annual report 2021. 2021. 1. Victora CG, Barros FC. Cohorts in low-and middle- income countries: from still photographs to full-length 1. Victora CG, Barros FC. Cohorts in low-and middle- income countries: from still photographs to full-length 14 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 ief and Works Agency for Palestine ar East. UNRWA Annual Operational aji N Abu Kishk N Turki Y Zeidan linkage process using nationwide Brazilian administrative databases to build a large birth cohort. BMC medical informatics and decision making. 2020;20(1):1-9. https://doi.org/10.1186/s12911-020-01192-0 linkage process using nationwide Brazilian administrative databases to build a large birth cohort. BMC medical informatics and decision making. 2020;20(1):1-9. https://doi.org/10.1186/s12911-020-01192-0 13. United Nations Relief and Works Agency for Palestine Refugees in the Near East. UNRWA Annual Operational Report 2018. 2018. 14. Ballout G, Al-Shorbaji N, Abu-Kishk N, Turki Y, Zeidan W, Seita A. UNRWA’s innovative E-Health for 5 million Palestine refugees in the Near East. BMJ Innovations. 2018:bmjinnov-2017-000262. 22. Statistics PCBo. Palestinian Multiple Indicator Cluster Survey 2019-2020, Survey Findings Report, Ramallah, Palestine.; 2021. 15. World Bank. Population total 2021 [Available from: https://data.worldbank.org/indicator/SP.POP.TOTL 23. Jamaluddine Z, Paolucci G, Ballout G, Al-Fudoli H, Day LT, Seita A, et al. Classifying caesarean section to understand rising rates among Palestinian refugees: results from 290,047 electronic medical records across five settings. BMC Pregnancy and Childbirth. 2022;22(1):1- 13. https://doi.org/10.1186/s12884-022-05264-z 16. United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA). UNRWA- Departement of health annual report 2022. 2022. 17. Wolfson J, Venkatasubramaniam A. Branching out: use of decision trees in epidemiology. Current Epidemiology Reports. 2018;5(3):221–9. https://doi.org/10.1007/s40471-018-0163-y 24. Harron KL, Doidge JC, Knight HE, Gilbert RE, Goldstein H, Cromwell DA, et al. A guide to evaluating linkage quality for the analysis of linked data. International journal of epidemiology. 2017;46(5):1699- 710. https://doi.org/10.1093/ije/dyx177 24. Harron KL, Doidge JC, Knight HE, Gilbert RE, Goldstein H, Cromwell DA, et al. A guide to evaluating linkage quality for the analysis of linked data. International journal of epidemiology. 2017;46(5):1699- 710. https://doi.org/10.1093/ije/dyx177 18. Endresen LC, Øvensen G. The Potential of UNRWA Data for Research on Palestinian Refugees: A Study of UNRWA Administrative Data.; 1994. 21. Almeida D, Gorender D, Ichihara MY, Sena S, Menezes L, Barbosa GC, et al. Examining the quality of record Abbreviations 19. Zureik E, Tamari S. Reinterpreting the Historical Records : The Uses of Palestinian Refugee Archives for Social Science Research and Policy Analysis2001. ANC: Antenatal care C: Child E-health: Electronic Health records system EMIS: Education Management Information system F: Family M: Mother MFN: Medical file number RRIS: Refugee registration number UNRWA: United Nations Relief and Works Agency for Palestine Refugees in the Near East ANC: Antenatal care C: Child E-health: Electronic Health records system EMIS: Education Management Information system F: Family M: Mother MFN: Medical file number RRIS: Refugee registration number UNRWA: United Nations Relief and Works Agency for Palestine Refugees in the Near East 20. Jamaluddine Z, Sharara E, Helou V, El Rashidi N, Safadi G, El-Helou N, et al. An umbrella review on the effects of size at birth on health, growth and developmental outcomes. Archieves of Disease in Childhood 2022. http://dx.doi.org/10.1136/archdischild-2022-324884 21. Almeida D, Gorender D, Ichihara MY, Sena S, Menezes L, Barbosa GC, et al. Examining the quality of record 15 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Appendix Table 1: Hypotheses Appendix Table 1: Hypotheses Hypotheses Link Unlinked Structural (legitimate) reasons for data not to link Early mortality (before the child used UNRWA services or got an MFN) 1 More deaths among the unlinked Mortality 0.3% 6.0% 2 More multiples among the unlinked because they have higher early mortality (even if one or both are not registered as a death) Multiple 1.4% 4.4% 3 More LBW/PT among the unlinked because LBW/PT have higher early mortality (even if not registered as a death) Preterm (Gestational age <37 weeks) 7.7% 10.9% Low Birthweight <2500) 5.6% 9.3% Child used other services (and never used UNRWA services) 4 More mothers who are not Palestinian among the unlinked because non-refugee mothers have alternative options for child health and education Mother RRIS missing in health 2.5% 10.3% 5 More children with a missing MFN (in the mother dataset) are unlinked because children did not use UNRWA services, so a C MFN was not generated Missing C MFN 0.0% 49.7% 6.a More families from Jordan and West Bank are unlinked mother and child (because they have more choices). Abbreviations Lebanon, Gaza, and Syria have fewer choices for other services 6ca and (6a or 6b) for in opposite directions % Linkage health Jordan 74.8% 25.2% Lebanon 89.1% 10.9% Syria 67.8% 32.2% West Bank 72.8% 27.2% Gaza 93.9% 6.1% 6b More children in Jordan, West Bank do not link to education services because they have more alternative options. Lebanon, Gaza and Syria have fewer choices for other education services % Link education Jordan 31.9% 68.1% Lebanon 63.5% 36.5% Syria 72.2% 27.8% West Bank 32.6% 67.4% Gaza 77.1% 22.9% Migration (before the child used UNRWA services or got an MFN) 6.c. More families from Lebanon and Syria are unlinked (because they have higher migration). Cannot test but might contribute to a higher proportion of unlinked. Cannot be distinguished from other causes in 4.a. Continued Hypotheses 6b 16 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Appendix Table 1: Continued Lack of linkage due to reporting, recording or data entry errors Data entry errors in any of the IDs (namely Mother/ C MFN, FRRIS.......) 7 Linkage will improve over time as experience with electronic medical records improved Figure 5 and Figure 6-Improvement of linkage 8 Very recent data has more zero in CRRIS as it takes more time to register them %Missing C RRIS 2010 2012 2014 2016 2018 2020 2.0% 3.8% 5.7% 8.8% 12.0% 38.9% Ages mis-recorded/ recorded approximately (heaped on 1 or 15th or in January) 9 Linkage based on steps +/- 90 and +/- 180 will decrease Figure 5- decrease in linkage errors 7 Linkage will improve over time as expertise in electronic medical records improved Figure 5 and Figure 6- Improvement of linkage Sex mis-recorded 10 Attempt to link unlinked kids to any sex. A total of 13,683. Error 1.4 % Location mis-recorded 11 Attempt to link unlinked kids to any location A total of 477 links. Error 0.05% Live birth miscoded as stillbirth (so was excluded from the start) 12 Attempt to link unlinked children to stillbirths A total of 56 links. Error 0.006% Stillbirth miscoded as a live birth Cannot test Might be like step 12 Distinguishing of duplicated records from multiples 13 The percentage of same-sex multiples. The sex ratio observed in the data is 1.03 male (50.7%) to 1 female (49.3%). In our dataset same sex multiples (69%); discordant multiples are 31%. Abbreviations This 69% is plausible if we assume that ∼30% of multiples are monozygotic (so same sex as per published reports) and around half of dizygotic multiples are same sex (0.3+(0.7(0.50682+0.49322)) = 0.30+0.35 = 65.0% of multiples expected to be same sex. Lack of linkage due to reporting, recording or data entry errors Data entry errors in any of the IDs (namely Mother/ C MFN, FRR Lack of linkage due to reporting, recording or data entry errors Data entry errors in any of the IDs (namely Mother/ C MFN, FRRIS.......) Lack of linkage due to reporting, recording or data entry errors Data entry errors in any of the IDs (namely Mother/ C MFN, FRRIS.......) 7 Linkage will improve over time as experience with electronic medical records improved Figure 5 and Figure 6-Improvement of linkage 8 Very recent data has more zero in CRRIS as it takes more time to register them %Missing C RRIS 2010 2012 2014 2016 2018 2020 2.0% 3.8% 5.7% 8.8% 12.0% 38.9% Ages mis-recorded/ recorded approximately (heaped on 1 or 15th or in January) 9 Linkage based on steps +/- 90 and +/- 180 will decrease Figure 5- decrease in linkage errors 7 Linkage will improve over time as expertise in electronic medical records improved Figure 5 and Figure 6- Improvement of linkage Sex mis-recorded 10 Attempt to link unlinked kids to any sex. A total of 13,683. Error 1.4 % Location mis-recorded 11 Attempt to link unlinked kids to any location A total of 477 links. Error 0.05% Live birth miscoded as stillbirth (so was excluded from the start) 12 Attempt to link unlinked children to stillbirths A total of 56 links. Error 0.006% Stillbirth miscoded as a live birth Cannot test Might be like step 12 Distinguishing of duplicated records from multiples Ages mis-recorded/ recorded approximately (heaped on 1 or 15th or in January) Ages mis-recorded/ recorded approximately (heaped on 1 or 15th or in January) 9 Linkage based on steps +/- 90 and +/- 180 will decrease Figure 5- decrease in linkage errors 7 Linkage will improve over time as expertise in electronic medical records improved Figure 5 and Figure 6- Improvement of linkage Sex mis-recorded 10 Attempt to link unlinked kids to any sex. A total of 13,683. Error 1.4 % Location mis-recorded 11 Attempt to link unlinked kids to any location A total of 477 links. Abbreviations Error 0.05% Live birth miscoded as stillbirth (so was excluded from the start) 12 Attempt to link unlinked children to stillbirths A total of 56 links. Error 0.006% Stillbirth miscoded as a live birth Cannot test Might be like step 12 Distinguishing of duplicated records from multiples Distinguishing of duplicated records from multiples The sex ratio observed in the data is 1.03 male (50.7%) to 1 female (49.3%). In our dataset same sex multiples (69%); discordant multiples are 31%. This 69% is plausible if we assume that ∼30% of multiples are monozygotic (so same sex as per published reports) and around half of dizygotic multiples are same sex (0.3+(0.7(0.50682+0.49322)) = 0.30+0.35 = 65.0% of multiples expected to be same sex. 13 The percentage of same-sex multiples. 13 The percentage of same-sex multiples. 17 17 Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Appendix Table 2: Multivariable logistic regression model of the association of different population characteristics of children using UNRWA services and odds of linkage (N = 892,801) Adjusted OR (95%CI) Setting Gaza (ref) 1.0 Jordan 3.2 (3.1-3.2) Lebanon 1.4 (1.3-1.4) Syria 4.3 (4.2-4.4) West Bank 2.4 (2.3-2.4) Mother ID Refugee (ref) 1.0 Not a refugee 2.7 (2.6-2.8) Dead or at risk of early mortality Normal birth weight, term and singleton and not recorded as dead (ref) 1.0 Low birthweight, or preterm or multiple, and not recorded as dead (at risk of early mortality) 1.6 (1.6-1.6) Recorded as dead 47.0 (44.8-49.3) Year of birth 2010 1.0 2011 0.8 (0.8-0.8) 2012 0.6 (0.5-0.6) 2013 0.4 (0.4-0.4) 2014 0.4 (0.4-0.4) 2015 0.3 (0.3-0.3) 2016 0.3 (0.3-0.3) 2017 0.2 (0.2-0.2) 2018 0.2 (0.2-0.2) 2o19 0.2 (0.2-0.2) 2020 0.2 (0.2-0.2) Jamaluddine Z et al. International Journal of Population Data Science (2023) 8:1:23 Appendix Table 2: Multivariable logistic regression model of the association of different population characteristics of children using UNRWA services and odds of linkage (N = 892,801) ble logistic regression model of the association of different population characteristics of children using linkage (N = 892,801) Adjusted OR (95%CI) 18
https://openalex.org/W4385666840	https://www.repository.cam.ac.uk/bitstreams/4dd1c672-d5ef-4560-a2e0-80858c22f144/download	English	null	Defining the spatial distribution of extracellular adenosine revealed a myeloid-dependent immunosuppressive microenvironment in pancreatic ductal adenocarcinoma	Journal for immunotherapy of cancer	2,023	cc-by	23,952	Defining the spatial distribution of extracellular adenosine revealed a myeloid-dependent 1 immunosuppressive microenvironment in pancreatic ductal adenocarcinoma 2 Kaistha current address: Oncology R&D, Research and Early Development, 22 AstraZeneca Cambridge, UK 23 # Brajesh P. Kaistha current address: Oncology R&D, Research and Early Development, 22 AstraZeneca Cambridge, UK 23 ° Frances M. Richards current address: Oncology R&D, Translational Medicine, AstraZeneca, 24 Cambridge, UK 25 ° Frances M. Richards current address: Oncology R&D, Translational Medicine, AstraZeneca, 24 Cambridge, UK 25 Defining the spatial distribution of extracellular adenosine revealed a myeloid-dependent 1 immunosuppressive microenvironment in pancreatic ductal adenocarcinoma 2 2Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, UK 9 3Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences (CPSS), 10 AstraZeneca, Cambridge, UK 11 3Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences (CPSS), 10 AstraZeneca, Cambridge, UK 11 4Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, CB2 12 1QW, UK 13 5CRUK Beatson Institute, Switchback Rd, Glasgow G61 1BD, UK 14 6Oncology R&D, Research and Early Development, AstraZeneca, Cambridge, UK 5 7Department of Oncology, University of Cambridge, Cambridge UK 16 7Department of Oncology, University of Cambridge, Cambridge UK 16 8Department of Pathology, Cambridge University Hospitals NHS Foundation Trust, 17 Cambridge, UK 18 9School of Cancer Sciences, University of Glasgow, Glasgow, UK 19 1 1 # Brajesh P. Kaistha current address: Oncology R&D, Research and Early Development, 22 AstraZeneca Cambridge, UK 23 ° Frances M. Richards current address: Oncology R&D, Translational Medicine, AstraZeneca, 24 Cambridge, UK 25 26 Running title 27 Extracellular adenosine shapes PDAC immune microenvironment 28 Keywords 29 Pancreatic cancer, adenosine pathway, immunotherapy, pro-tumorigenic macrophages, tumour 30 microenvironment 31 Financial support: 32 All CRUK CI authors received research funding from Cancer Research UK (Nos. 33 C14303/A17197 and C9545/A29580). The Li Ka Shing Centre where this work was performed 34 was generously funded by CK Hutchison Holdings Limited, the University of Cambridge, 35 CRUK, The Atlantic Philanthropies and others. This work was supported by Cancer Research 36 UK (C9685/A27444) funding for VG. This study was also funded by Cancer Research UK 37 Precision Panc grant C96/A25238. HB is funded by the University of Cambridge Experimental 38 Medicine Training Initiative programme in partnership with AstraZeneca (EMI-AZ) and SYL 39 is funded by the Cambridge Trust (Cambridge International Scholarship). Work by JT and KW 40 is funded by a core grant award from the MRC (MC_UU_00025/12). S.A.K. and. J.P.M. were 41 supported by Cancer Research UK core funding to the Beatson Institute (A17196 and A31287) 42 and to J.P.M. Lab (A29996). 43 44 # Brajesh P. Kaistha current address: Oncology R&D, Research and Early Development, 22 AstraZeneca Cambridge, UK 23 ° Frances M. Richards current address: Oncology R&D, Translational Medicine, AstraZeneca, 24 Cambridge, UK 25 26 Running title 27 Extracellular adenosine shapes PDAC immune microenvironment 28 Keywords 29 Pancreatic cancer, adenosine pathway, immunotherapy, pro-tumorigenic macrophages, tumour 30 microenvironment 31 Financial support: 32 # Brajesh P. Financial support: 32 All CRUK CI authors received research funding from Cancer Research UK (Nos. 33 C14303/A17197 and C9545/A29580). The Li Ka Shing Centre where this work was performed 34 was generously funded by CK Hutchison Holdings Limited, the University of Cambridge, 35 CRUK, The Atlantic Philanthropies and others. This work was supported by Cancer Research 36 UK (C9685/A27444) funding for VG. This study was also funded by Cancer Research UK 37 Precision Panc grant C96/A25238. HB is funded by the University of Cambridge Experimental 38 Medicine Training Initiative programme in partnership with AstraZeneca (EMI-AZ) and SYL 39 is funded by the Cambridge Trust (Cambridge International Scholarship). Work by JT and KW 40 is funded by a core grant award from the MRC (MC_UU_00025/12). S.A.K. and. J.P.M. were 41 supported by Cancer Research UK core funding to the Beatson Institute (A17196 and A31287) 42 and to J.P.M. Lab (A29996). 43 All CRUK CI authors received research funding from Cancer Research UK (Nos. 33 C14303/A17197 and C9545/A29580). The Li Ka Shing Centre where this work was performed 34 was generously funded by CK Hutchison Holdings Limited, the University of Cambridge, 35 CRUK, The Atlantic Philanthropies and others. This work was supported by Cancer Research 36 UK (C9685/A27444) funding for VG. This study was also funded by Cancer Research UK 37 Precision Panc grant C96/A25238. HB is funded by the University of Cambridge Experimental 38 Medicine Training Initiative programme in partnership with AstraZeneca (EMI-AZ) and SYL 39 is funded by the Cambridge Trust (Cambridge International Scholarship). Work by JT and KW 40 is funded by a core grant award from the MRC (MC_UU_00025/12). S.A.K. and. J.P.M. were 41 supported by Cancer Research UK core funding to the Beatson Institute (A17196 and A31287) 42 and to J.P.M. Lab (A29996). 43 44 2 2 Corresponding authors: 45 3 Corresponding authors: 45 Vincenzo Graziano: Cancer Research UK Cambridge Institute, University of Cambridge, Li 46 Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, United Kingdom. Email: 47 vincenzo.graziano@cruk.cam.ac.uk. Current email address: 48 vincenzo.graziano@astrazeneca.com 49 Duncan Jodrell: Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka 50 Shing Centre, Robinson Way, Cambridge, CB2 0RE, United Kingdom. Email: 51 dij21@cam.ac.uk 52 53 Authors’ disclosures: 54 AD, HH, BPK, MW, FMR, RG, SJD, AGS and JE are AstraZeneca employees and own 55 company stocks and shares. VG is AstraZeneca employee since May 2023. HB holds a 56 studentship partially funded by AstraZeneca. DJ is consultant for Ellipses Pharma. 57 58 Synopsis: The clinical development of anti-CD73 antibodies has demonstrated their utility, but 59 the mechanism for this effect has not been fully elucidated. We now show that targeting the 60 adenosine pathway reduces extracellular adenosine in myeloid rich, hypoxic areas of pancreatic 61 ductal adenocarcinoma, abrogating the pro-tumorigenic, immunosuppressive 62 microenvironment and improving the efficacy of anti-tumour interventions. 63 64 Abstract 65 Background: The prognosis for patients with pancreatic ductal adenocarcinoma (PDAC) 66 remains extremely poor. It has been suggested that the adenosine pathway contributes to the 67 Duncan Jodrell: Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka 50 Shing Centre, Robinson Way, Cambridge, CB2 0RE, United Kingdom. Email: 51 dij21@cam.ac.uk 52 Duncan Jodrell: Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka 50 Shing Centre, Robinson Way, Cambridge, CB2 0RE, United Kingdom. Email: 51 dij21@cam.ac.uk 52 3 ability of PDAC to evade the immune system and hence, its resistance to Immuno-Oncology 68 therapies (IOT), by generating extracellular adenosine (eAdo). 69 ability of PDAC to evade the immune system and hence, its resistance to Immuno-Oncology 68 therapies (IOT), by generating extracellular adenosine (eAdo). 69 Methods: Using genetically engineered allograft models of PDAC in syngeneic mice with 70 defined and different immune infiltration and response to IOT and autochthonous tumours in 71 KPC mice we investigated the impact of the adenosine pathway on the PDAC tumour 72 microenvironment (TME). Flow cytometry and Imaging Mass Cytometry (IMC) were used to 73 characterise the subpopulation frequency and spatial distribution of tumour-infiltrating 74 immune cells. Mass Spectrometry Imaging (MSI) was used to visualise adenosine 75 compartmentalisation in the PDAC tumours. Conclusions: The formation of eAdo promotes the development of the immunosuppressive 92 TME in PDAC, contributing to its resistance to conventional and novel therapies. Therefore, 93 inhibition of the adenosine pathway may represent a strategy to modulate the PDAC immune 94 milieu and improve therapy response in patients with PDAC. 95 Corresponding authors: 45 RNA sequencing was used to evaluate the 76 influence of the adenosine pathway on the shaping of the immune milieu and correlate our 77 findings to published datasets in human PDAC. 78 Results: We demonstrated high expression of adenosine pathway components in tumour- 79 infiltrating immune cells (particularly myeloid populations) in the murine models. MSI 80 demonstrated that extracellular adenosine distribution is heterogeneous in tumours, with high 81 concentrations in peri-necrotic, hypoxic regions, associated with rich myeloid infiltration, 82 demonstrated using IMC. Pro-tumorigenic M2 macrophages express high levels of the 83 Adora2a receptor; particularly in the IOT resistant model. Blocking the in vivo formation and 84 function of eAdo (Adoi), using a combination of anti-CD73 antibody and an Adora2a inhibitor 85 slowed tumour growth and reduced metastatic burden. Additionally, blocking the adenosine 86 pathway improved the efficacy of combinations of cytotoxic agents or immunotherapy. Adoi 87 remodelled the TME, by reducing the infiltration of M2 macrophages and Tregs. RNAseq 88 analysis showed that genes related to immune modulation, hypoxia and tumour stroma were 89 downregulated following Adoi and a specific adenosine signature derived from this is 90 associated with a poorer prognosis in patients with PDAC. 91 4 4 Conclusions: The formation of eAdo promotes the development of the immunosuppressive 92 TME in PDAC, contributing to its resistance to conventional and novel therapies. Therefore, 93 inhibition of the adenosine pathway may represent a strategy to modulate the PDAC immune 94 milieu and improve therapy response in patients with PDAC. 95 Conclusions: The formation of eAdo promotes the development of the immunosuppressive 92 TME in PDAC, contributing to its resistance to conventional and novel therapies. Therefore, 93 inhibition of the adenosine pathway may represent a strategy to modulate the PDAC immune 94 milieu and improve therapy response in patients with PDAC. 95 96 97 5 5 What is already known on this topic – The adenosine pathway generates extracellular 98 adenosine and its components are known to be overexpressed in tumours. Extracellular 99 adenosine is recognised as an immune suppressive molecule. CD73, the member of the 100 pathway that enables the final step of conversion of AMP to adenosine, is highly expressed on 101 the cancer cell surface in many tumours, including pancreatic adenocarcinoma. 102 What is already known on this topic – The adenosine pathway generates extracellular 98 adenosine and its components are known to be overexpressed in tumours. Introduction 123 Survival for patients with pancreatic ductal adenocarcinoma (PDAC) has not changed 124 significantly in the last 50 years and remains poor (https://www.cancerresearchuk.org/health- 125 professional/cancer-statistics-for-the-uk). There is a need for new treatments, given that 126 current standard of care for patients with metastatic disease is associated with poor outcomes, 127 with less than 10% of patients living for more than 2 years 1. In addition to relative resistance 128 to conventional therapies, cancer immunotherapy (Immuno-Oncology Therapy, IOT) is also 129 ineffective in this disease, except in a small group of patients (1-2%) with microsatellite 130 instability/mismatch repair deficient (MSI-H/dMMR) tumours 2. Several authors consider that 131 the reason for this resistance can be ascribed to the low mutational burden of this neoplasm, 132 which leads to lymphocyte exclusion and anergy 3 4. However, the tumour microenvironment 133 in PDAC has also been shown to be populated by a rich variety of immune cells, most of which 134 demonstrate immune suppressive features, which contribute to the resistance to 135 immunotherapy 5. 136 Survival for patients with pancreatic ductal adenocarcinoma (PDAC) has not changed 124 significantly in the last 50 years and remains poor (https://www.cancerresearchuk.org/health- 125 professional/cancer-statistics-for-the-uk). There is a need for new treatments, given that 126 current standard of care for patients with metastatic disease is associated with poor outcomes, 127 with less than 10% of patients living for more than 2 years 1. In addition to relative resistance 128 to conventional therapies, cancer immunotherapy (Immuno-Oncology Therapy, IOT) is also 129 ineffective in this disease, except in a small group of patients (1-2%) with microsatellite 130 instability/mismatch repair deficient (MSI-H/dMMR) tumours 2. Several authors consider that 131 the reason for this resistance can be ascribed to the low mutational burden of this neoplasm, 132 which leads to lymphocyte exclusion and anergy 3 4. However, the tumour microenvironment 133 in PDAC has also been shown to be populated by a rich variety of immune cells, most of which 134 demonstrate immune suppressive features, which contribute to the resistance to 135 immunotherapy 5. 136 The adenosine pathway is an immunosuppressive axis which has gained much attention 137 in cancer immunology for its role in suppressing the immune activation associated with 138 cytotoxic treatments (chemotherapy, targeted therapy and radiotherapy) 6 7 8. This has led to 139 the clinical evaluation of inhibitors of the pathway in combination with more conventional 140 approaches 9. Corresponding authors: 45 However, the tumour microenvironment 133 in PDAC has also been shown to be populated by a rich variety of immune cells, most of which 134 demonstrate immune suppressive features, which contribute to the resistance to 135 immunotherapy 5. 136 The adenosine pathway is an immunosuppressive axis which has gained much attention 137 in cancer immunology for its role in suppressing the immune activation associated with 138 cytotoxic treatments (chemotherapy, targeted therapy and radiotherapy) 6 7 8. This has led to 139 the clinical evaluation of inhibitors of the pathway in combination with more conventional 140 approaches 9. The adenosine pathway involves conversion of extracellular ATP (eATP), a 141 powerful immune activator, to extracellular adenosine (eAdo) by the ectonucleotidases CD39 142 and CD73 10. eAdo has been linked to cancer in several studies that have demonstrated that its 143 concentration in different tumour tissues is several folds higher than in normal tissues 6 11. 144 CD39 is overexpressed in a subpopulation of exhausted tumour-infiltrating T-cells 12 13 and its 145 expression correlates with another marker of immunosuppression (PD1 expression) 13. CD39 146 and CD73 have roles in the aggressiveness of adult glioblastoma 14, where they are expressed 147 Corresponding authors: 45 Extracellular 99 adenosine is recognised as an immune suppressive molecule. CD73, the member of the 100 pathway that enables the final step of conversion of AMP to adenosine, is highly expressed on 101 the cancer cell surface in many tumours, including pancreatic adenocarcinoma. 102 What this study adds – Here, we show that in murine models of pancreatic adenocarcinoma 103 (PDAC), the adenosine pathway is overexpressed by a population of myeloid immune cells. 104 We visualised adenosine spatially in the tumour microenvironment of a relevant, preclinical 105 model of PDAC, identifying that its distribution is mostly confined to myeloid-rich, hypoxic 106 areas. We discovered that pro-tumorigenic myeloid populations (in particular, M2 107 macrophages) represent the target of adenosine stimulation (Adora2a expressing) and therefore 108 it is responsible for the formation and maintenance of an immune suppressive 109 microenvironment. We were able to generate a specific, transcriptomic signature from our pre- 110 clinical experiments that predicts survival in patients with PDAC. Finally, we demonstrated 111 that inhibiting the adenosine pathway improved response to cytotoxic and immunotherapy 112 drugs in murine PDAC models. 113 How this study might affect research, practice or policy – This study unveils a previously 114 unknown myeloid-dependent axis of immunosuppression in PDAC and could inform future 115 clinical trials that will evaluate inhibitors of the adenosine pathway. Such studies might 116 improve outcomes for patients with PDAC, a major unmet clinical need. 117 118 119 120 121 122 6 6 Introduction 123 Survival for patients with pancreatic ductal adenocarcinoma (PDAC) has not changed 124 significantly in the last 50 years and remains poor (https://www.cancerresearchuk.org/health- 125 professional/cancer-statistics-for-the-uk). There is a need for new treatments, given that 126 current standard of care for patients with metastatic disease is associated with poor outcomes, 127 with less than 10% of patients living for more than 2 years 1. In addition to relative resistance 128 to conventional therapies, cancer immunotherapy (Immuno-Oncology Therapy, IOT) is also 129 ineffective in this disease, except in a small group of patients (1-2%) with microsatellite 130 instability/mismatch repair deficient (MSI-H/dMMR) tumours 2. Several authors consider that 131 the reason for this resistance can be ascribed to the low mutational burden of this neoplasm, 132 which leads to lymphocyte exclusion and anergy 3 4. Introduction 123 The adenosine pathway involves conversion of extracellular ATP (eATP), a 141 powerful immune activator, to extracellular adenosine (eAdo) by the ectonucleotidases CD39 142 and CD73 10. eAdo has been linked to cancer in several studies that have demonstrated that its 143 concentration in different tumour tissues is several folds higher than in normal tissues 6 11. 144 CD39 is overexpressed in a subpopulation of exhausted tumour-infiltrating T-cells 12 13 and its 145 expression correlates with another marker of immunosuppression (PD1 expression) 13. CD39 146 and CD73 have roles in the aggressiveness of adult glioblastoma 14, where they are expressed 147 7 7 on infiltrating macrophages 15 16. The adenosine signature recently published by Sidders and 148 colleagues 17 shows that this pathway correlates with resistance to immunotherapies and is 149 associated with other genetic features of tumour aggressiveness, such as p53 mutations. The 150 abundant presence of eAdo in the microenvironment can dampen immune activation through 151 the stimulation of a pro-tumorigenic stroma. This is mostly orchestrated by macrophages and 152 myeloid derived suppressive cells (MDSCs) 18 19, favouring a tolerogenic function of dendritic 153 cells (DCs) 20-22 which results in inhibition of T-cells/NK cell activation 23 24. 154 on infiltrating macrophages 15 16. The adenosine signature recently published by Sidders and 148 colleagues 17 shows that this pathway correlates with resistance to immunotherapies and is 149 associated with other genetic features of tumour aggressiveness, such as p53 mutations. The 150 abundant presence of eAdo in the microenvironment can dampen immune activation through 151 the stimulation of a pro-tumorigenic stroma. This is mostly orchestrated by macrophages and 152 myeloid derived suppressive cells (MDSCs) 18 19, favouring a tolerogenic function of dendritic 153 cells (DCs) 20-22 which results in inhibition of T-cells/NK cell activation 23 24. 154 The myeloid populations play a pivotal role in the aggressiveness of many cancer types 155 and in particular, PDAC. For instance, the presence of pro-tumorigenic populations of 156 macrophages 25 26 and myeloid-derived suppressive cells (MDSCs) 27 infiltrating the 157 microenvironment, is associated with poor survival and correlates with immune exclusion of 158 PDAC. Macrophages can elicit the secretion of cytokines which can on the one hand, favour 159 the proliferation and invasiveness of cancer cells while interacting with cancer-associated 160 fibroblasts 28-30, and on the other hand induce anergy and physical exclusion of adaptive 161 immune cells 31-33. Introduction 123 Using genetic manipulation of CD73 173 in cancer cells and mice, Jacoberger-Foissac and colleagues demonstrated that CD73 can be 174 overexpressed in a percentage of tumour-infiltrating myeloid cells other than cancer cells, 175 contributing to infiltration of M2 macrophages in KPC mice35. King and colleagues highlighted 176 that genetic alteration of CD73 impaired the secretion of GM-CSF, reducing myeloid-derived 177 suppressive cell infiltration in PDAC mouse models36. Also, it has been suggested that genetic 178 alteration of CD73 in cancer cells induces a modest sensitivity to gemcitabine treatment in 179 vitro. However, little is known about the complex mechanism generated by the adenosine 180 pathway resulting in the immunosuppressive characteristics of pancreatic cancer 181 microenvironment and stroma, in particular the role that the adenosine pathway and its 182 therapeutic inhibition have in shaping the immune infiltration of this disease. 183 Here, we propose a model where the tumour-infiltrating immune cell populations of 184 PDAC generate an axis of immunosuppression, where extracellular adenosine produced mostly 185 in hypoxic regions of the tumour (identified using Mass Spectrometry Imaging), enriched for 186 the myeloid cell infiltration, stimulates pro-tumorigenic M2 macrophages. The axis described 187 is expressed preferentially by the IOT-resistant model when compared to the IOT-responsive 188 one. Therefore, blocking the adenosine pathway in the IOT-resistant PDAC model, strongly 189 suppresses the formation of extracellular adenosine and reshapes the immune 190 microenvironment, favouring disease control when combined with cytotoxic treatments and 191 immunotherapies. Bulk RNAseq gene analysis confirms the role of the myeloid-dependent 192 adenosine pathway in PDAC survival, underpinning the importance of our results for 193 understanding the biological complexity and the clinical utility of the adenosine pathway 194 inhibition. 195 Introduction 123 Targeting macrophages in a pre-clinical pancreatic cancer model has been 162 demonstrated to be effective to obtain tumour regression and reduce metastatic formation 34. 163 Unfortunately, this approach has not translated into clinical benefit, which in part can be 164 explained by the fact that the global reduction of the tumour-infiltrating macrophages can be 165 biologically different from reprogramming distinct tumour associated macrophage (TAM) 166 subtypes 30. 167 Some recent publications link the adenosine pathway to the biology and aggressiveness 168 of PDAC. PDAC has been shown to have an increased adenosine pathway RNA signature 169 associated with a worse prognosis 17, and genes encoding for the receptors for eAdo as well as 170 CD73 have been found to be overexpressed in bulk-RNA sequencing (RNAseq) when 171 comparing tumours to normal pancreatic tissue 7. A role for extracellular adenosine in shaping 172 Some recent publications link the adenosine pathway to the biology and aggressiveness 168 of PDAC. PDAC has been shown to have an increased adenosine pathway RNA signature 169 associated with a worse prognosis 17, and genes encoding for the receptors for eAdo as well as 170 CD73 have been found to be overexpressed in bulk-RNA sequencing (RNAseq) when 171 comparing tumours to normal pancreatic tissue 7. A role for extracellular adenosine in shaping 172 8 myeloid response to PDAC has recently been suggested. Using genetic manipulation of CD73 173 in cancer cells and mice, Jacoberger-Foissac and colleagues demonstrated that CD73 can be 174 overexpressed in a percentage of tumour-infiltrating myeloid cells other than cancer cells, 175 contributing to infiltration of M2 macrophages in KPC mice35. King and colleagues highlighted 176 that genetic alteration of CD73 impaired the secretion of GM-CSF, reducing myeloid-derived 177 suppressive cell infiltration in PDAC mouse models36. Also, it has been suggested that genetic 178 alteration of CD73 in cancer cells induces a modest sensitivity to gemcitabine treatment in 179 vitro. However, little is known about the complex mechanism generated by the adenosine 180 pathway resulting in the immunosuppressive characteristics of pancreatic cancer 181 microenvironment and stroma, in particular the role that the adenosine pathway and its 182 therapeutic inhibition have in shaping the immune infiltration of this disease. 183 myeloid response to PDAC has recently been suggested. Cell lines and chemicals 197 KrasLSL-G12D/+; Trp53LSL-R172H/+; Pdx1-Cre; Rosa26YFP/YFP (KPCY)-derived cell lines 198 2838c3, 6499c4, 6620c1 (IOT-responsive), 6419c5, 6694c2 and 6422c1 (IOT-resistant) were 199 a kind gift from Ben Stanger (University of Pennsylvania). The cell lines were obtained from 200 single cell cloning strategy, as described previously, and were generated from tumours 201 developed in KPCY mice on a C57BL/6 background 37. PANC-1 was used for in vitro 202 experiments as a representative human PDAC cell line. Cells were grown up to 20 passages in 203 DMEM (with pyruvate, L-glutamine and D-glucose; Gibco, #41966029) supplemented with 204 5% FBS (Gibco, #10270106). All the cell lines were analysed for STR fingerprinting and 205 tested for mycoplasma routinely. 206 Methods and materials 196 9 9 Mice and in vivo experiments 207 Tumour allograft experiments were performed in the animal facility (Biological 208 Resource Unit, BRU) of the CRUK Cambridge Institute, in accordance with the UK Animals 209 Scientific Procedures Act 1986, with approval from the CRUK Cambridge Institute Animal 210 Ethical Review and Welfare Body. 8-12 week old female C57BL/6 mice were used for in vivo 211 experiments and were purchased from Charles River (UK). 212 Tumour allograft studies were performed with technical assistance from CRUK-CI BRU staff. 213 Mice were subcutaneously injected in the right flank with 1x106 KPCY-derived cells in 50% 214 PBS and 50% Matrigel basement membrane matrix (#354234, Corning). In the interventional 215 experiments, mice were treated as indicated, starting 12-14 days from tumour cell implantation, 216 to allow the microenvironment to establish. Tumour volume was calculated using the formula; 217 (π/6)(width)2length. Tumour response was defined based on the % of change of the longest 218 diameter from start of therapy (stable disease < 20% increase and < 30% decrease of target 219 lesion RECIST v. 1.1). Mice were then killed at specific endpoints (e.g. 14 days from start of 220 Tumour allograft studies were performed with technical assistance from CRUK-CI BRU staff. 213 Mice were subcutaneously injected in the right flank with 1x106 KPCY-derived cells in 50% 214 PBS and 50% Matrigel basement membrane matrix (#354234, Corning). In the interventional 215 experiments, mice were treated as indicated, starting 12-14 days from tumour cell implantation, 216 to allow the microenvironment to establish. Tumour volume was calculated using the formula; 217 (π/6)(width)2length. Tumour response was defined based on the % of change of the longest 218 diameter from start of therapy (stable disease < 20% increase and < 30% decrease of target 219 lesion RECIST v. 1.1). Mice were then killed at specific endpoints (e.g. 14 days from start of 220 10 10 treatment) or when the tumour reached 2000 mm3 (or before in case of appearance of clinical 221 signs). 222 KrasLSL-G12D/+; Trp53LSL-R172H/+; Pdx1-Cre (KPC) mice for tumour phenotyping, were obtained 223 from a breeding colony maintained by the CRUK-CI Genome Editing Core team. Tumours 224 were detected by palpation followed by ultrasound imaging by the Genome Editing Core. 225 Tumour tissues, spleens and mesenteric and inguinal lymph nodes from KPC mice were 226 provided once tumour dimensions or health status rendered them unsuitable for therapeutic 227 studies. Mice and in vivo experiments 207 After 24 hours, 258 cells were treated with different concentrations of anti-CD73 (2c5mIgG1) antibody (1, 10, 100 259 µg/ml) or isotype (NIP228 mouse IgG1 control kappa) for 8 days. Antibodies were added every 260 3 days. On day 8, colonies were stained with SRB protocol previously described (36). Images 261 were taken and analysed using GelCount (Oxford Optronix). Colony forming efficiency was 262 calculated as a ratio between the number of colonies and number of plated cells. Surviving 263 fractions were calculated as the ratio between wells treated with anti-CD73 antibody and the 264 ones treated with isotype. At least 3 wells per condition were plated for each of the 3 replicates 265 per experiment. 266 IncuCyte time lapse imaging 267 KPCY-derived cells were plated at 2500 cells/well density in a 96-well black-wall plate 268 (at least 3 wells per condition). Cells were grown in cell culture medium supplemented with 269 When indicated the following drugs were used: AZD6738 (ATRi; 25 mg/kg daily for 4 days), 246 AZD4635 (Adora2ai; 50 mg/kg bid), 2c5mIgG1 (anti-CD73; 10 mg/kg twice weekly), 247 AB740080 D265A (anti-PD-L1: 10 mg/kg twice weekly), NIP228 mouse IgG1 control kappa 248 (isotype; 10 mg/kg twice weekly) and NIP228 muIgG1 D265A (isotype; 10 mg/kg twice 249 weekly) were provided by AstraZeneca. The antibody anti-CD73 2c5mIgG1 is a murine IgG1 250 with minimal Fc mediated activity38; gemcitabine hydrochloride (Tocris, 3259) was used at 251 100 mg/kg twice weekly; inVivoPlus anti-CD40 (clone FGK4.5/FGK45; bioxcell BE0016-2) 252 and InVivoPlus rat IgG2a isotype control, anti-trinitrophenol (clone 2A3; bioxcell BE0089) 253 were used as a single injection of 100 µg. InVivoPlus anti-CTLA-4 (clone 9H10; bioxcell 254 BP0131) or InVivoPlus isotype control polyclonal Syrian hamster IgG (bioxcell BP0087): 200 255 µg/dose x 3 times. 256 KPCY-derived cells were seeded at 200 cells/well in a 6-well plate. After 24 hours, 258 cells were treated with different concentrations of anti-CD73 (2c5mIgG1) antibody (1, 10, 100 259 µg/ml) or isotype (NIP228 mouse IgG1 control kappa) for 8 days. Antibodies were added every 260 3 days. On day 8, colonies were stained with SRB protocol previously described (36). Images 261 were taken and analysed using GelCount (Oxford Optronix). Colony forming efficiency was 262 calculated as a ratio between the number of colonies and number of plated cells. Surviving 263 fractions were calculated as the ratio between wells treated with anti-CD73 antibody and the 264 ones treated with isotype. Mice and in vivo experiments 207 At least 3 wells per condition were plated for each of the 3 replicates 265 per experiment. 266 KPCY-derived cells were seeded at 200 cells/well in a 6-well plate. After 24 hours, 258 cells were treated with different concentrations of anti-CD73 (2c5mIgG1) antibody (1, 10, 100 259 µg/ml) or isotype (NIP228 mouse IgG1 control kappa) for 8 days. Antibodies were added every 260 3 days. On day 8, colonies were stained with SRB protocol previously described (36). Images 261 were taken and analysed using GelCount (Oxford Optronix). Colony forming efficiency was 262 calculated as a ratio between the number of colonies and number of plated cells. Surviving 263 fractions were calculated as the ratio between wells treated with anti-CD73 antibody and the 264 ones treated with isotype. At least 3 wells per condition were plated for each of the 3 replicates 265 per experiment. 266 Mice and in vivo experiments 207 KPC mice were killed when showing clinical signs of the disease (swollen abdomen, 228 loss of body conditioning resembling cachexia, reduced mobility). 229 KPC mice used for the interventional study were bred at the CRUK Beatson Institute and 230 maintained on a mixed background. All work was performed under UK Home Office license 231 and approved by the University of Glasgow Animal Welfare and Ethical Review Board. Mice 232 of both sexes, in similar proportions, were used in all cohorts. Mice suspected to have PDAC 233 following palpation were anesthetised in 0.2L/min medical air and isoflurane and then 234 underwent 3D ultrasound imaging using the VisualSonics Vevo 3100 ultrasound system with 235 MX550D 40μm resolution transducer (FujiFilm). Mice were randomly assigned to 1 of the 4 236 treatment groups (A: vehicles + isotype; B: AZD6738 + gemcitabine; C: AZD4635 + 237 2c5mIgG1; D: AZD6738 + gemcitabine + AZD4635 + 2c5mIgG1) once tumours were 238 confirmed by imaging, and follow-up scans were performed weekly until endpoint was 239 reached. Schedule of the treatments are specified in the results and figures sections. Mice were 240 culled when exhibiting moderate symptoms of pancreatic cancer (see above). Statistical 241 assessment of survival was carried out by Kaplan-Meier and Log-Rank analysis. Analysis of 242 ultrasound images was performed using VevoLab software (version 3.1.1) from VisualSonics. 243 In 3D mode, stacked images of the tumour were imported and the tumour border annotated, 244 allowing a 3D construct to be formed. 245 11 11 When indicated the following drugs were used: AZD6738 (ATRi; 25 mg/kg daily for 4 days), 246 AZD4635 (Adora2ai; 50 mg/kg bid), 2c5mIgG1 (anti-CD73; 10 mg/kg twice weekly), 247 AB740080 D265A (anti-PD-L1: 10 mg/kg twice weekly), NIP228 mouse IgG1 control kappa 248 (isotype; 10 mg/kg twice weekly) and NIP228 muIgG1 D265A (isotype; 10 mg/kg twice 249 weekly) were provided by AstraZeneca. The antibody anti-CD73 2c5mIgG1 is a murine IgG1 250 with minimal Fc mediated activity38; gemcitabine hydrochloride (Tocris, 3259) was used at 251 100 mg/kg twice weekly; inVivoPlus anti-CD40 (clone FGK4.5/FGK45; bioxcell BE0016-2) 252 and InVivoPlus rat IgG2a isotype control, anti-trinitrophenol (clone 2A3; bioxcell BE0089) 253 were used as a single injection of 100 µg. InVivoPlus anti-CTLA-4 (clone 9H10; bioxcell 254 BP0131) or InVivoPlus isotype control polyclonal Syrian hamster IgG (bioxcell BP0087): 200 255 µg/dose x 3 times. 256 Clonogenic assay 257 KPCY-derived cells were seeded at 200 cells/well in a 6-well plate. IncuCyte time lapse imaging 267 KPCY-derived cells were plated at 2500 cells/well density in a 96-well black-wall plate 268 (at least 3 wells per condition). Cells were grown in cell culture medium supplemented with 269 KPCY-derived cells were plated at 2500 cells/well density in a 96-well black-wall plate 268 (at least 3 wells per condition). Cells were grown in cell culture medium supplemented with 269 12 the indicated concentration of anti-CD73 (2c5mIgG1) or isotype (NIP228 mouse IgG1 control 270 kappa) antibody in triplicate. Images were acquired with 10x objective, every 3 hours from 3 271 different fields per well using Incucyte Live cells imaging microscope (Essen Bioscience). 272 Confluence was calculated as the average of the 3 fields using the Incucyte algorithm. 273 Experiments were repeated at least 3 times. 274 Human cell line viability assay 275 For viability experiments, 3000 PANC-1 cells/well were plated into a 96 well plate 276 overnight and then dosed with IC50 for each compound (gemcitabine 0.5 µM; oxaliplatin 30 277 µM; docetaxel 0.5 nM; 5-FU 52 µM; cisplatin 20 µM) either alone or in combination with 278 oleclumab at 1 nM. For combination and pre-treatment experiments, cells were either pre- 279 treated with oleclumab at 1 nM for indicated time (2hrs or 24hrs) before addition of 280 chemotherapies at IC50s. Viability was assessed using Cell Titre Glo as per manufacturer’s 281 instructions at either 3 or 7 days and expressed as percentage of cells in the treated wells over 282 control. Oleclumab (MEDI9447) was kindly provided by AstraZeneca. 283 Single cell suspension preparation 285 For experiments in subcutaneous allografts, tumours were weighed and placed in RPMI 286 and finely minced with scissors in a 2 ml tube, which was then washed with up to 2.5 ml of 287 digestion buffer (Tumour dissociation kit, Miltenyi, 130-096-730) plus Deoxyribonuclease I 288 (300 µg/ml, Sigma, DN25-1G). Dissociation was performed using the protocol suggested by 289 Miltenyi. For KPC tumours, a trypsin inhibitor (250 µg/ml, Sigma, T6522) was added to the 290 digestion buffer. Following the digestion, the samples were passed through a 70 µM strainer 291 filter (Greiner Bio-one, 542-070), washing with MACS buffer (PBS + 0.1% FBS and 2nM 292 EDTA). 293 13 13 Mouse spleens, inguinal and mesenteric lymph nodes were mashed on a 100 µM filter 294 (Greiner Bio-one, 542-000) over a 50 ml tube, using a syringe plug and the filter was washed 295 with MACS buffer and centrifuged (at 4° C as for all the following centrifugation). Red cell 296 lysis buffer (1 ml; 0.15M Ammonium Chloride; 10mM Potassium hydrogen carbonate; 0.1mM 297 EDTA; pH 7.4 (adjusted with KOH) was then used to resuspend splenocytes, 3 minutes at room 298 temperature and then washed with MACS buffer and centrifuged at 300g for 5 minutes. 299 Samples were eventually resuspended in 200-400 µl of MACS buffer. 300 Single cell suspensions were aliquoted in a round-bottom 96 well/plate (Costar, 3879) 302 and stained with live/dead fixable stain (Invitrogen, L34962; 1:100 in PBS) for 10 minutes at 303 room temperature. After washing in MACS buffer, cells were FC-blocked with anti-CD16/32 304 antibody (BioLegend Cat# 101320, RRID:AB_1574975; 1:100) for 5 minutes. Then, 305 antibodies for surface staining were added and incubated at 4° C degrees for 30 minutes. After 306 washing, cells were fixed with FACS fix buffer [PBS + 1% Formaldehyde + 0.02 g/ml Glucose 307 + 0.02% Sodium Azide] for 10 minutes and then washed and resuspended in MACS buffer for 308 FACS analysis. For intracellular staining, cells were fixed with fixation/permeabilization 309 buffer (Invitrogen 00-5123-43 and 00-5223-56) for 15 minutes, then washed in perm buffer 310 and stained with the relevant antibody in perm buffer for 60 minutes. Cells were then washed 311 and resuspended in MACS buffer for FACS analysis. Samples were acquired using BD- 312 Symphony flow cytometer and the generated FCS files were analysed using FlowJo V10 313 software (RRID:SCR_008520). Single cell suspension preparation 285 The following antibodies were used and gating strategies are 314 shown in the supplementary figures(myeloid populations and lymphoid population; suppl. fig. 315 1A and 1B respectively): BV786-CD45 (BD Biosciences Cat# 564225, RRID:AB_2716861; 316 1:200), APC/Fire750-CD3 (BioLegend Cat# 100248, RRID:AB_2572118; 1:50), BV650-CD8 317 (BioLegend Cat# 100741, RRID:AB_11124344; 1:100), BV711-CD4 (BioLegend Cat# 318 14 14 100549, RRID:AB_11219396; 1:200), APC-Foxp3 (Invitrogen Cat# 17-5773-82, 319 RRID:AB_469457; 1:100) , FITC-CD19 (BioLegend Cat# 115505, RRID:AB_313640; 1:200) 320 , BV510-CD11b (BioLegend Cat# 101245, RRID:AB_2561390; 1:200), PerCP/Cy5.5-CD44 321 (BioLegend Cat# 103031, RRID:AB_2076206; 1:200), BV421-PD1 (BioLegend Cat# 135218, 322 RRID:AB_2561447; 1:100), BV421-PD-L1 (BioLegend Cat# 124315, RRID:AB_10897097; 323 1:100), PE/Cy7-CD39 (BioLegend Cat# 143805, RRID:AB_2563393; 1:100), PE-CD73 324 (BioLegend Cat# 127206, RRID:AB_2154094; 1:100), FITC-F4/80 (BioLegend Cat# 123108, 325 RRID:AB_893502; 1:200), PE/Cy7-CD206 (BioLegend Cat# 141719, RRID:AB_2562247; 326 1:100), PerCP/Cy5.5-Ly6C (BioLegend Cat# 128012, RRID:AB_1659241; 1:100), APC/Cy7- 327 Ly6G (BioLegend Cat# 127624, RRID:AB_10640819; 1:100), AF700-MHCII (BioLegend 328 Cat# 107629, RRID:AB_2290801; 1:200), PE-CD11c (eBioscience Cat# 12-0114-83, 329 RRID:AB_465553; 1:200) , BV605-NKp46 (BioLegend Cat# 137619, RRID:AB_2562452; 330 1:25), APC-Adora2a (Novus Biotech Cat# NBP1-39474APC; 1:150) , APC-CD86 (BioLegend 331 Cat# 105012, RRID:AB_493342; 1:100). Gating strategy for immune subpopulations is shown 332 in supplementary figure 1A-B. For CD73 in vitro staining of KPCY-derived cell lines, cells 333 were stained as described above with live/dead fixable stain and PE-CD73 antibody and 334 analysed with BD-Symphony flow cytometer. For in vitro treatment, cells were treated with 335 anti-CD73 (2c5mIgG1) or isotype (NIP228) antibody at a concentration of 10 µg/ml for 24 336 hours. Competitive staining was performed before this experiment to confirm there was no 337 competition between 2c5mIgG1 and TY11.8 (PE-CD73) clones (data not shown). 338 Tissue preparation for Mass Spectrometry Imaging (MSI) and Imaging Mass Cytometry 339 PDAC mouse tumours were snap frozen in liquid nitrogen immediately after resection 341 and the tissues were embedded in a HPMC/PVP hydrogel as previously described 39. 342 Sectioning was performed on a CM3050 S cryostat (Leica Biosystems, Nussloch, Germany) at 343 PDAC mouse tumours were snap frozen in liquid nitrogen immediately after resection 341 and the tissues were embedded in a HPMC/PVP hydrogel as previously described 39. 342 Sectioning was performed on a CM3050 S cryostat (Leica Biosystems, Nussloch, Germany) at 343 15 a section thickness of 10 µm and the tissue sections were immediately thaw mounted and dried 344 under a stream of nitrogen and sealed in vacuum pouches to preserve the metabolic integrity 345 of the sections. Tissue sections for DESI-MSI and IMC were thaw-mounted onto Superfrost 346 microscope slides (Thermo Scientific Waltham, MA, USA), whilst sections prepared for 347 MALDI-MSI were thaw mounted onto conductive ITO coated slides (Bruker Daltonik, 348 Bremen, Germany). Polyvinylpyrrolidone (PVP) (MW 360 kDa) and (Hydroxypropyl)- 349 methylcellulose (HPMC) (viscosity 40-60 cP, 2 % in H2O (20 C) were purchased from Merck 350 (Darmstadt, Germany). Methanol, water, iso-pentane and isopropyl alcohol were obtained from 351 Fisher Scientific (Waltham, MA, USA). 352 Mass Spectrometry Imaging (MSI) 353 DESI-MSI analysis was performed on a Q-Exactive mass spectrometer (Thermo 354 Scientific, Bremen, Germany) equipped with an automated 2D-DESI ion source (Prosolia Inc., 355 Indianapolis, IN, USA) operated in negative ion mode, covering the applicable mass range up 356 to a m/z of 1000, with a nominal mass resolution of 70,000. The injection time was fixed to 357 150 ms resulting in a scan rate of 3.8 pixel/s. The spatial resolution was adapted between 358 experiments to allow acquisition of the data for all directly compared samples within a single 359 experiment of 48 h, with pixel sizes ranging from 35-75 µm. A home-built Swagelok DESI 360 sprayer was operated with a mixture of 95% methanol, 5% water delivered with a flow rate of 361 1.5 µL/min and nebulized with nitrogen at a backpressure of 6 bar. The resulting .raw files 362 were converted into .mzML files using ProteoWizard msConvert 40 (version 3.0.4043) and 363 subsequently compiled to an .imzML file (imzML converter 41 version 1.3). All subsequent 364 data processing was performed in SCiLS Lab (version 2021b, Bruker Daltonik, Bremen, 365 Germany). 366 16 MALDI-MSI analysis was performed on a RapifleX Tissuetyper instrument (Bruker Daltonik, 367 Bremen, Germany) operated in negative detection mode. 9-Aminoacridine (9-AA) prepared in 368 80:20 methanol:water was used as a MALDI matrix and spray deposited using an automated 369 spray system (M3-Sprayer, HTX technologies, Chapel Hill, NC, USA). MALDI experiments 370 were performed with a spatial resolution of 50 µm. A total of 400 laser shots were summed up 371 per pixel to give the final spectra. For all experiments the laser was operated with a repetition 372 rate of 10 kHz. All raw data were directly uploaded and processed in SCiLS lab (Version 373 2021b) software packages. All DESI and MALDI data and images were normalised to the total 374 ion current (TIC) to compensate for signal variation across the course of the experiments. Data 375 segmentation pipeline is shown in supplementary materials and methods. 376 Imaging Mass Cytometry (IMC) 377 Imaging mass cytometry was performed on a slide which had already been analysed by DESI- 378 MSI. Antibodies used for IMC staining are shown in supplementary table 1. Untagged 379 antibodies were tagged in house, using Fluidigm Maxpar Antibody Labelling Kit, according to 380 manufacturer’s instructions. Following DESI-MSI analysis, the slide was fixed with 4% 381 paraformaldehyde in phosphate-buffered saline (PBS) for 10 minutes. The slide was washed 3 382 x 5 minutes in PBS, permeabilized for 5 minutes with 1:1000 dilution of Triton X-100 in Casein 383 Solution, washed 3 x 5 minutes in PBS, and blocked for 30 minutes with Casein Solution. 384 Antibodies were diluted to an appropriate concentration in Casein Solution and the slide 385 incubated overnight with the antibody solution at 4 ˚C. The slide was washed 3 x 5 minutes in 386 PBS and nuclei were stained with DNA Intercalator-iridium at a dilution of 1:400 in PBS for 387 30 minutes. The slide was washed 3 x 5 minutes in PBS, 30 seconds in deionized water, then 388 dried for storage at room temperature until analysis. A region for IMC analysis was selected 389 using consecutive H and E stained sections and the DESI-MSI results. A box with 390 approximately 2 x 1.8 mm area was selected for analysis to include necrotic, necrotic margin 391 17 17 and viable tumour regions. IMC analysis was performed using a Hyperion instrument 392 (Fluidigm Corporation, San Francisco, CA, USA) with an ablation energy of 6 db an ablation 393 frequency of 200 Hz. IMC images were produced using MCD viewer (Version 1.0, Fluidigm) 394 and analysis was performed using HALO (Indica labs). Tissue regions were classified using 395 random forest with all markers included. Cells positive for each marker were manually 396 optimised by setting a cell intensity threshold. Values for the numbers of positive cells for 397 markers of interest were exported for analysis in Graphpad Prism v.8 (RRID:SCR_002798) 398 RNA sequencing 422 RNA was extracted from twelve subcutaneous allograft tumour tissues (6 mice of the 423 vehicle + isotype group or control and 6 mice of the AZD4635 + 2c5mIgG1 group or Adoi) 424 weighing up to 30 mg. Tissues were firstly disrupted and homogenised using TissueLyser II 425 and then RNA was extracted using a Qiagen RNAeasy kit, according to the manufacturer’s 426 instructions. RNA was then quantified using a Qubit 3.0 (life technologies) and purity and 427 quality were assessed using an Agilent 4150 (G2992AA) TapeStation system (Agilent). 428 Library construction was followed by paired-end 50 bp sequencing on a Novaseq 6000 429 sequencer. 430 Immunohistochemistry (IHC) 399 Immunohistochemistry was performed as previously described42 in the histopathology 400 core at the CRUK CI. Briefly, tissues were removed from the mouse at the endpoint and 401 immediately formalin-fixed for 24 hours. Fixed tissues were then processed, embedded in 402 paraffin and sectioned (3 µm sections). Following dewaxing and rehydration, as standard, 403 antigen retrieval was performed using Leica’s Epitope Retrieval Solution 2 (Tris EDTA) at 404 100° C for 20 minutes. Additional protein block from Dako (X090930-2) was applied. The 405 staining using anti-mouse CD8 (Cell signalling, #98941), anti-mouse Foxp3 (Affymetrix. #14- 406 5773) and anti-mouse p53 (Novocastra; #NCL-L-p53-CM5p) antibodies, was performed on 407 Leica’s automated Bond-III platform in conjunction with their Polymer Refine Detection 408 System (DS9800) and a modified version of their standard template. Slides were dehydrated 409 and cleared in xylene on Leica’s automated ST5020 before sections were mounted on Leica’s 410 coverslipper, CV5030 (mounting media: DPX Mountant for Histology; Sigma Aldrich, 06522- 411 500ML) and scanned using a ScanScopeAT2 (Aperio Leica Biosystems). Quantification of 412 viable tumour tissue was performed after exclusion of necrotic area using the Halo software v. 413 3.3.2541.405 (Indica Labs). Cell density was calculated as the number of positive cells x mm2 414 of tumour tissue analysed. Sections of mouse spleen were used on each slide as internal control. 415 18 18 For the analysis of the lung metastatic burden of any individual mouse, the 4 right lobes and 416 the left lobe were cut into multiple pieces and together fixed and then embedded, then treated 417 as above. p53 staining was used for helping the detection of smaller lesions (min. of 5 cells). 418 Analysis was performed using Halo software and expressed as % of metastatic areas/total lung 419 area analysed. Mice with intra-abdominal/thoracic organs direct infiltration were excluded 420 from the analysis. 421 Bioinformatics analysis 431 Sequencing files in FASTQ format were aligned against the GRCh38 mouse genome 432 using HISAT2 (RRID:SCR_015530) with default parameters. Samtools (RRID:SCR_002105) 433 was used to create, index and merge BAM files of reads from different lanes belonging to 434 individual samples. FeatureCounts (RRID:SCR_012919) was utilized to quantify gene-level 435 expression of transcripts. All downstream analyses were completed in R version 4.1.2. Prior to 436 analysis, MSI data for sequenced samples were examined. From the vehicle/isotype-treated 437 arm (control group), sample 23729 showed minimal necrosis, low peri-necrotic adenosine and 438 a high ATP/AMP ratio suggesting a very high energetic state. This identified the sample as a 439 19 19 potential outlier which was confirmed upon visual inspection of a PCA plot (Supplementary 440 fig. 1C). It was excluded prior to downstream analysis. 441 potential outlier which was confirmed upon visual inspection of a PCA plot (Supplementary 440 fig. 1C). It was excluded prior to downstream analysis. 441 For the remaining 11 samples, initially genes were filtered to maintain only genes that were 442 expressed at a reasonable level in >5 treatment conditions using the filterByExpr() command 443 from the edgeR package (ver 3.36.0) . 444 For the remaining 11 samples, initially genes were filtered to maintain only genes that were 442 expressed at a reasonable level in >5 treatment conditions using the filterByExpr() command 443 from the edgeR package (ver 3.36.0) . 444 Differential gene expression analyses were performed on raw read counts of the combined data 445 object of all 11 samples. To identify significantly expressed genes between Adoi and control 446 groups, we utilised a Wald test within the DESeq2 package (RRID:SCR_000154, ver 1.34.0). 447 Genes were considered differentially expressed when the analysis resulted in an adjusted P- 448 value (corrected for multiple testing using the Benjamini and Hochberg method) below 0.05. 449 The volcano plot was generated using the EnhancedVolcano package (ver 1.12.0) with the 450 addition of custom code. 451 Differential gene expression analyses were performed on raw read counts of the combined data 445 object of all 11 samples. To identify significantly expressed genes between Adoi and control 446 groups, we utilised a Wald test within the DESeq2 package (RRID:SCR_000154, ver 1.34.0). 447 Genes were considered differentially expressed when the analysis resulted in an adjusted P- 448 value (corrected for multiple testing using the Benjamini and Hochberg method) below 0.05. Bioinformatics analysis 431 449 The volcano plot was generated using the EnhancedVolcano package (ver 1.12.0) with the 450 addition of custom code. 451 Gene set enrichment analysis (GSEA) of 712 genes identified as differentially expressed with 452 padj≤0.05 and log2(fold change)≤-0.58 was performed via the Enrichr (RRID:SCR_001575) 453 (suppl. table 2) server database for Kyoto Encyclopedia of Genes and Genomes (KEGG) 454 (https://www.genome.jp/kegg/) pathways and Gene Ontology (GO): Biological Processes 455 (http://geneontology.org/). Subsequently, enriched terms ranked for significance for each 456 database were downloaded and are reported in Supplementary Table 4-5. Terms of interest 457 were selected from the top 15 ranks in each table. Genes from this study which were shown to 458 be enriched in these terms of interest were then selected to be displayed in a heatmap. Raw 459 counts were normalised with DESeq2 (RRID:SCR_000154) prior to visualisation of gene 460 expression levels with pheatmap (ver 1.0.12). Please refer to the supplementary methods and 461 materials references section for all of the above. 462 is of human PDAC available datasets and generation of PDAC-specific adenosine 20 20 In order to the evaluate the correlation of the adenosine-related gene expression profile 465 to human PDAC we analysed 712 genes which had at least a 50% decreased expression 466 (Log2FC <-0.58) following adenosine inhibition treatment, of which 561 had a human ortholog 467 (suppl. table 2-3). 468 In order to the evaluate the correlation of the adenosine-related gene expression profile 465 to human PDAC we analysed 712 genes which had at least a 50% decreased expression 466 (Log2FC <-0.58) following adenosine inhibition treatment, of which 561 had a human ortholog 467 (suppl. table 2-3). 468 In order to the evaluate the correlation of the adenosine-related gene expression profile 465 to human PDAC we analysed 712 genes which had at least a 50% decreased expression 466 (Log2FC <-0.58) following adenosine inhibition treatment, of which 561 had a human ortholog 467 (suppl. table 2-3). 468 465 For the analysis of the adenosine-related gene expression in Bailey 43 PDAC subtypes (ADEX, 469 Immunogenic, Squamous and Pancreatic progenitor) we derived z-scores for the 517 genes 470 analysed in the dataset (out of the 561 genes) for the 97 patients with RNAseq data and subtype 471 information (https://www.cbioportal.org/, RRID:SCR_014555). The z-score of all genes were 472 summed per patient and the total number represented as the adenosine pathway gene score as 473 previously shown 17 and in supplementary materials and methods. 474 For the analysis of the adenosine-related gene expression in Bailey 43 PDAC subtypes (ADEX, 469 Immunogenic, Squamous and Pancreatic progenitor) we derived z-scores for the 517 genes 470 analysed in the dataset (out of the 561 genes) for the 97 patients with RNAseq data and subtype 471 information (https://www.cbioportal.org/, RRID:SCR_014555). The z-score of all genes were 472 summed per patient and the total number represented as the adenosine pathway gene score as 473 previously shown 17 and in supplementary materials and methods. 474 For the generation of a PDAC-specific adenosine signature and application of this to PDAC 475 survival, from the list of 561 human ortholog genes, we manually curated the ones related 476 without ambiguity to the major biological processes implicated in PDAC pathogenesis and 477 indicated by pathway analysis (hypoxia, immunity and extracellular matrix organisation). Of 478 these genes, only those that correlated positively or negatively to survival in PDAC 479 (https://kmplot.com)44 and were significantly co-expressed with CD73 and/or Adora2a in 480 public datasets (Bailey et al. is of human PDAC available datasets and generation of PDAC-specific adenosine or TCGA) were selected. A final list of 52 genes was analysed 481 (suppl. table 6). 482 Using PDAC specific data from TCGA 45 available in https://www.cbioportal.org/, we derived 483 the z-score of these 52 genes for each patient with known disease-specific-survival (DSS), 484 Progression free survival (PFS) and disease-free-survival (DFS). The z-scores for all genes 485 were summed up for each patient and was deemed high adenosine score if >0 or low adenosine 486 score if <0, as previously shown 17. 487 21 Graphpad Prism v.8 (RRID:SCR_002798) was used for statistical analyses. Analysis 489 and comparisons of two groups was performed with two-tailed unpaired Student’s T-test when 490 assuming Gaussian distribution or Mann Whitney test. Analysis of three or more groups was 491 performed with one-way ANOVA with Tukey’s multiple comparisons post-test analysis unless 492 otherwise specified. Kaplan-Meier analysis with log-rank Mantel-Cox test was used to evaluate 493 difference in survivals. Differences were considered significant when p<0.05. 494 489 Data Availability Statement 495 The data generated in this study are available within the article and its supplementary data files 496 or from the corresponding authors upon reasonable request. Code for differential expression 497 analysis and visualisation of RNAseq data is available via Github https://github.com/ka- 498 lw/AdenoPDAC . 499 The data generated in this study are available within the article and its supplementary data files 496 or from the corresponding authors upon reasonable request. Code for differential expression 497 analysis and visualisation of RNAseq data is available via Github https://github.com/ka- 498 lw/AdenoPDAC . 499 509 22 Adenosine pathway expression on KPCY-derived cell lines 511 Human PDAC tumour cells express CD73 and demonstrate weak sensitivity to the targeting 512 of CD73 in vitro 35 46. For this reason, we sought to investigate whether murine KPCY-derived 513 cell lines (which are associated with contrasting ability to generate IOT- resistant or responsive 514 tumours when re-implanted in syngeneic mice) express the proteins of the canonical adenosine 515 pathway (CD39, CD73 and Adora2a). We found that, as in human cells, mouse PDAC cell 516 lines express CD73 (from 72% to 99% of cells; fig. 1A and suppl. fig. 2A) but demonstrate 517 negligible or no expression of CD39 and Adora2a (suppl. fig. 2B-C). Exposing cells to an anti- 518 CD73 antibody (2c5mIgG1) reduced significantly the detection of CD73 in all the cells after 519 only 24-hour treatment (p<0.05 in all cell lines, fig. 1B), but this did not translate into inhibition 520 of cell growth after short or long exposure at high concentrations. In addition, confluency 521 experiments showed that the treatment did not affect the proliferation of any of the cell lines 522 over a period of 72 hours (fig. 1C and suppl. fig. 2D-E), and colony-forming experiments 523 performed on 2838c3 (IOT-responsive) and 6419c5 (IOT-resistant) demonstrated no 524 differences in terms of number or size of the colonies formed after 8 days of continuous 525 treatment (fig. 1D-E and suppl. fig. 2F). Accordingly, in vitro inhibition of CD73 was 526 performed on human PDAC cell line PANC-1 using anti-human CD73 oleclumab (suppl. fig. 527 2G-I). Oleclumab did not reduce tumour cell growth when used alone or in combination with 528 multiple cytotoxic agents, either as a concomitant treatment (suppl. fig. 2G) or when used as a 529 pre-treatment (suppl. fig. 2H-I). In order to evaluate whether a direct effect of anti-CD73 530 exposure affects cell proliferation, reducing adenosine formation, we cultured KPCY-derived 531 cell lines with increasing concentrations of AMP and 5’-N-(Ethylcarboxamido)adenosine 532 (NECA, a stable form of adenosine). We were able to demonstrate that adenosine and AMP 533 23 23 have no effect on the proliferation capacity of these cell lines (suppl. fig. 2G-H), corroborating 534 the hypothesis of a non-cancer cell direct effect of anti-CD73 therapeutic approaches. 535 mparison between KPCY-derived cell lines allograft and KPC autochthonous tumour 563 In particular, the majority (65-91% in tumour vs 36-56% in spleen) of tumour-infiltrating 564 CD11b+ myeloid cells express the two receptors, due to an increase in expression of CD73, 565 given that those cells are normally CD39+ (fig. 2A-B). Similar results were shown for Tregs 566 and CD8+ T-cells, which are normally CD73+ and displayed an increase in expression of CD39 567 in tumour, compared to the secondary lymphoid organs counterparts (suppl. fig. 4A; p<0.05). 568 There was no significant difference in these findings when comparing the two models, despite 569 their differential response to IOT. We then confirmed these findings in KPC autochthonous 570 tumours and found similar results, with a significant increase of CD39/CD73 double expressing 571 CD11b+ myeloid cells infiltrating the tumours compared to spleens (mean 77% vs 36% 572 p<0.0001, fig. 2C-D), harvested from the same mice. Of note, 4 KPC mice had synchronous 573 metastases (3 liver and 1 spleen), and in 3 of these, myeloid cells infiltrating the metastases 574 were also enriched for CD73+CD39+ double expression (suppl. fig. 4 C) when compared to 575 secondary lymphoid organs. Significant increased co-expression was also observed for Tregs 576 and CD8+ T-cells in KPC tumours when compared to mesenteric or inguinal lymph nodes 577 (suppl. fig. 4B). An increased percentage of CD39/CD73 double expressing CD8 T-cells and 578 Tregs was noted in the spleens (suppl. fig. 4B) if compared to what was found in non-tumour 579 bearing mice (not shown) or subcutaneous tumour bearing mice, suggesting trafficking of 580 immune lymphoid populations between primary lesions and closer lymphoid organs. 581 Adenosine distributes primarily in the hypoxic areas surrounding necrosis 582 We hypothesized that the adenosine pathway might have a more impactful role in the 558 TME, as opposed to a cell autonomous effect. For this reason, we investigated the expression 559 of the adenosine pathway components on tumour-infiltrating immune cells which represent a 560 significant proportion of cells seen in PDAC lesions. We showed a highly significant 561 enrichment in both the IOT-resistant and IOT-responsive models for CD39+CD73+ double- 562 expressing immune cells, when compared to secondary lymphoid organs (spleen and nodes). 563 In particular, the majority (65-91% in tumour vs 36-56% in spleen) of tumour-infiltrating 564 CD11b+ myeloid cells express the two receptors, due to an increase in expression of CD73, 565 given that those cells are normally CD39+ (fig. 2A-B). mparison between KPCY-derived cell lines allograft and KPC autochthonous tumour Despite the lack of activity in our cell line experiments, preliminary responses have been 537 reported in early phase clinical trials when quemliclustat (a CD73 small molecule inhibitor) or 538 oleclumab were combined with PD(L)1 inhibition and standard-of-care therapy 47 48. As we 539 hypothesised that this might be the result of impact on the tumour microenvironment (TME), 540 we investigated the expression of this pathway on the tumour-infiltrating immune cells for 541 different murine PDAC models, including KPCY-derived cell line allografts (with differential 542 response to IOT) and autochthonous KPC tumours. In order to understand the complexity and 543 similarities of the immune system in these models we first compared the immune infiltration 544 of the cell line allografts to the KPC model. 545 The immunosuppressive characteristics identified in autochthonous KPC tumours, appear 546 to be more aligned with those of the IOT-resistant model. In particular regarding lymphocyte 547 populations, KPC tumours are usually infiltrated by a low number of CD8+ T cells (mean 548 number of CD45+ cells for 2838c3 is 6.9%, 0.9% for 6419c5 and 1.9% for KPC tumours), 549 which express lower levels of PD1, a known marker of activation/exhaustion (mean 70% vs 550 13% vs 10%) as shown in suppl. figure 3A and have a similar total CD4+ T-cells (suppl. fig. 551 3C) and regulatory T-cell (Tregs) infiltration (mean 3,2% vs 1% vs 0.7%, suppl. fig 3B) to 552 IOT-resistant tumours. Moreover, KPC tumours showed greater heterogeneity regarding 553 myeloid infiltrating populations (suppl. fig 3D-H). These results suggest that our IOT- resistant 554 and responsive models stand out as the extreme clonotypes which can arise from the complex 555 and heterogeneous biology found in KPC autochthonous tumours. 556 The adenosine pathway is enriched in immune cells infiltrating PDAC models 557 The adenosine pathway is enriched in immune cells infiltrating PDAC models 557 24 24 We hypothesized that the adenosine pathway might have a more impactful role in the 558 TME, as opposed to a cell autonomous effect. For this reason, we investigated the expression 559 of the adenosine pathway components on tumour-infiltrating immune cells which represent a 560 significant proportion of cells seen in PDAC lesions. We showed a highly significant 561 enrichment in both the IOT-resistant and IOT-responsive models for CD39+CD73+ double- 562 expressing immune cells, when compared to secondary lymphoid organs (spleen and nodes). mparison between KPCY-derived cell lines allograft and KPC autochthonous tumour We found that adenosine is present in high concentrations in the 593 microenvironment of PDAC murine models, although showing a heterogenous distribution, 594 with high abundance in the hypoxic necrotic margin areas (fig. 3C and suppl. fig. 4D). The 595 IOT-resistant model 6419c5 shows a higher abundance of adenosine, mostly due to the paucity 596 of necrotic areas in this 2838c3 IOT-responsive model (fig. 3A-C). This trend of adenosine 597 expression was then evaluated in other KPCY-derived allografts, confirming the lower 598 abundance of adenosine in the IOT-responsive models and higher expression in one other IOT- 599 resistant tumour (6694c2), particularly in the necrotic margins. A third IOT-resistant model 600 (6422c1) showed levels of adenosine similar to the IOT-responsive tumours, suggesting that 601 the expression of the adenosine pathway might not be a unique feature in the generation of 602 immunosuppression in murine PDAC (suppl. fig. 4E-F). The autochthonous KPC tumour 603 model showed a higher degree of complexity in their histological composition (suppl. fig. 4G). 604 MSI analysis demonstrated a primarily hypoxia-driven metabolic phenotype in which 605 adenosine and other metabolites such as succinate, lactate and metabolites associated with 606 purine metabolism were elevated. The hypoxic phenotype, and therefore adenosine, was not 607 Given the enrichment of the adenosine pathway in the TME of PDAC models, we 583 anticipated that extracellular adenosine might have been abundant in the tumour 584 microenvironment. Using Mass Spectrometry Imaging (MSI) we evaluated the presence and 585 the distribution of the purinergic system in the TME of IOT-resistant tumours. The tissue 586 classification and segmentation approaches were driven by tissue-defining metabolic pattern. 587 Areas characterised by a high energetic state defined by a high abundance of ATP and ADP 588 and a low abundance of depleted high energy phosphates such as AMP, were called viable 589 tumour. In contrast, areas of tumour adjacent to necrosis (termed necrotic margin) were 590 characterised by high abundance of lactate, products of ribonucleotide catabolism (i.e. xanthine 591 and hypoxanthine) and other metabolites associated with tissue hypoxia and an overall energy- 592 deprived state (fig. 3A-B). We found that adenosine is present in high concentrations in the 593 microenvironment of PDAC murine models, although showing a heterogenous distribution, 594 with high abundance in the hypoxic necrotic margin areas (fig. 3C and suppl. fig. 4D). mparison between KPCY-derived cell lines allograft and KPC autochthonous tumour Similar results were shown for Tregs 566 and CD8+ T-cells, which are normally CD73+ and displayed an increase in expression of CD39 567 in tumour, compared to the secondary lymphoid organs counterparts (suppl. fig. 4A; p<0.05). 568 There was no significant difference in these findings when comparing the two models, despite 569 their differential response to IOT. We then confirmed these findings in KPC autochthonous 570 tumours and found similar results, with a significant increase of CD39/CD73 double expressing 571 CD11b+ myeloid cells infiltrating the tumours compared to spleens (mean 77% vs 36% 572 p<0.0001, fig. 2C-D), harvested from the same mice. Of note, 4 KPC mice had synchronous 573 metastases (3 liver and 1 spleen), and in 3 of these, myeloid cells infiltrating the metastases 574 were also enriched for CD73+CD39+ double expression (suppl. fig. 4 C) when compared to 575 secondary lymphoid organs. Significant increased co-expression was also observed for Tregs 576 and CD8+ T-cells in KPC tumours when compared to mesenteric or inguinal lymph nodes 577 (suppl. fig. 4B). An increased percentage of CD39/CD73 double expressing CD8 T-cells and 578 Tregs was noted in the spleens (suppl. fig. 4B) if compared to what was found in non-tumour 579 bearing mice (not shown) or subcutaneous tumour bearing mice, suggesting trafficking of 580 immune lymphoid populations between primary lesions and closer lymphoid organs. 581 558 Adenosine distributes primarily in the hypoxic areas surrounding necrosis 582 25 25 Given the enrichment of the adenosine pathway in the TME of PDAC models, we 583 anticipated that extracellular adenosine might have been abundant in the tumour 584 microenvironment. Using Mass Spectrometry Imaging (MSI) we evaluated the presence and 585 the distribution of the purinergic system in the TME of IOT-resistant tumours. The tissue 586 classification and segmentation approaches were driven by tissue-defining metabolic pattern. 587 Areas characterised by a high energetic state defined by a high abundance of ATP and ADP 588 and a low abundance of depleted high energy phosphates such as AMP, were called viable 589 tumour. In contrast, areas of tumour adjacent to necrosis (termed necrotic margin) were 590 characterised by high abundance of lactate, products of ribonucleotide catabolism (i.e. xanthine 591 and hypoxanthine) and other metabolites associated with tissue hypoxia and an overall energy- 592 deprived state (fig. 3A-B). mparison between KPCY-derived cell lines allograft and KPC autochthonous tumour The 595 IOT-resistant model 6419c5 shows a higher abundance of adenosine, mostly due to the paucity 596 of necrotic areas in this 2838c3 IOT-responsive model (fig. 3A-C). This trend of adenosine 597 expression was then evaluated in other KPCY-derived allografts, confirming the lower 598 abundance of adenosine in the IOT-responsive models and higher expression in one other IOT- 599 resistant tumour (6694c2), particularly in the necrotic margins. A third IOT-resistant model 600 (6422c1) showed levels of adenosine similar to the IOT-responsive tumours, suggesting that 601 the expression of the adenosine pathway might not be a unique feature in the generation of 602 immunosuppression in murine PDAC (suppl. fig. 4E-F). The autochthonous KPC tumour 603 model showed a higher degree of complexity in their histological composition (suppl. fig. 4G). 604 MSI analysis demonstrated a primarily hypoxia-driven metabolic phenotype in which 605 adenosine and other metabolites such as succinate, lactate and metabolites associated with 606 purine metabolism were elevated. The hypoxic phenotype, and therefore adenosine, was not 607 583 26 26 limited to the margin around established necrosis, but found throughout the samples 608 independent of established necrosis. This limited the ability to delineate the necrotic margin as 609 it was possible in the KPCY-derived s.c. tumours, but confirmed the importance of hypoxia in 610 the generation of adenosine. When we investigated the cell population distribution in the 611 different areas using Imaging Mass Cytometry (IMC) in IOT-resistant tumours, we noted in 612 the necrotic margin areas a 2.7-fold increase in the number of infiltrating CD11b+ myeloid cells 613 (mean 1970 in the necrotic margin vs 730 in viable tumour CD11b+ cells/mm2), that led to a 614 significant decrease of the ratio between cancer cells/myeloid cells (suppl. fig. 5A). This again 615 suggests that myeloid cells have an instrumental role in the generation of adenosine in this 616 aggressive model of PDAC. 617 Expression of Adora2a receptor on myeloid subpopulations of pancreatic ca 618 Lymphoid cells were negative for 639 Adora2a both in tumours and in metastases (suppl. fig. 5D, bottom panel). 640 In addition to pro-tumorigenic macrophages, Adora2a expression was found enriched in 641 other myeloid immune populations infiltrating the tumours. In particular CD11b- dendritic 642 cells, CD11b+ dendritic cells (suppl. fig. 5E), M1 macrophages (suppl. fig. 5F), and mo- 643 MDSCs (suppl. fig. 5G) for both models and gMDSCs for IOT-resistant tumours (suppl. fig. 644 5H) express significantly higher Adora2a amount when compared to matched spleens. This 645 expression differs significantly between IOT- responsive and resistant models in CD11b+ 646 dendritic cells (mean MFI 2080 ± 174 vs 3190 ± 636 respectively; p=0.007), M1 macrophages 647 (4520 ± 983 vs 6940 ± 1690; p=0.02) and mo-MDSCs (1890 ± 479 vs 6110 ± 1870; p=0.001) 648 (suppl. fig. 5E-H). 649 Expression of Adora2a receptor on myeloid subpopulations of pancreatic ca 618 Having shown in these models that in the PDAC microenvironment, immunosuppressive 619 adenosine is present abundantly, we then investigated which cells within the microenvironment 620 might be responsive to this. We investigated the expression of the adenosine A2a receptor 621 (Adora2a, the receptor with the highest affinity for adenosine) that has been found to be 622 frequently overexpressed in human tumours, by flow cytometry We found that Adora2a was 623 highly expressed by tumour-infiltrating myeloid population when compared to the spleen 624 (suppl. fig. 5B-C) and this expression was significantly higher in the IOT-resistant model in 625 terms of MFI (10000 vs 6700, p<0.0001) and % of Adora2a+ myeloid cells (15% vs 11%, 626 p=0.009). In contrast, lymphoid populations infiltrating the tumours were negative for Adora2a 627 expression (suppl. fig. 5B, bottom). When comparing different subpopulations, pro- 628 tumorigenic M2 macrophages, infiltrating both IOT-resistant and IOT-responsive PDAC 629 showed high positivity for the receptor. The IOT-resistant model had higher expression of 630 Adora2a compared to the IOT-responsive model (fig. 3D-E; p<0.0001) and percentage of 631 Adora2a+ M2 positivity [72% vs 43%; p<0.0001) (fig. 3H)]. Once more, these findings were 632 27 confirmed in KPC tumours where Adora2a was found to be increased in M2 macrophages 633 infiltrating the lesions when compared to matched spleens (fig. 3F-G). The KPC model 634 demonstrated once again the heterogeneity of pancreatic lesions, which in terms of M2 635 macrophages, positive for the Adora2a receptor, covers the entire range of expression seen in 636 the two subcutaneous models used (fig. 3H). Notably, of three KPC mice where metastatic 637 nodules were found, Adora2a expression was found retained in the M2 macrophages 638 infiltrating the secondary lesions (suppl. fig. 5D, top panel). Lymphoid cells were negative for 639 Adora2a both in tumours and in metastases (suppl. fig. 5D, bottom panel). 640 confirmed in KPC tumours where Adora2a was found to be increased in M2 macrophages 633 infiltrating the lesions when compared to matched spleens (fig. 3F-G). The KPC model 634 demonstrated once again the heterogeneity of pancreatic lesions, which in terms of M2 635 macrophages, positive for the Adora2a receptor, covers the entire range of expression seen in 636 the two subcutaneous models used (fig. 3H). Notably, of three KPC mice where metastatic 637 nodules were found, Adora2a expression was found retained in the M2 macrophages 638 infiltrating the secondary lesions (suppl. fig. 5D, top panel). Targeting adenosine pathway delays tumour growth of murine pancreatic cancer 650 representing a combinational therapeutic opportunity 651 Our data suggest a mechanism by which the myeloid population contributes to the pro- 652 tumorigenic functionality of the pancreatic cancer microenvironment, where eAdo generated 653 by the myeloid cell populations and cancer cells would target and stimulate further the myeloid 654 cell subpopulations, in particular the pro-tumorigenic M2 macrophages. Therefore, we 655 inhibited in vivo eAdo formation and function, using an antibody against CD73 (2c5mIgG1) 656 28 and a small molecule inhibitor of Adora2a (AZD4635), a combination (Adoi) which would 657 maximise the inhibition of the axis. The 14-day treatment was started after the 658 microenvironment was allowed to establish (12-14 days after implantation) in the IOT-resistant 659 allografts (fig 4A). The anti-CD73 was extremely effective in reducing the expression of CD73 660 on the surface of all live cells (suppl. fig. 6A). MSI data confirmed marked reduction in 661 adenosine formation in the TME (Fig. 4 B-C). In particular, adenosine was completely 662 abolished in the viable tumour areas, while a small amount remained in the necrotic margins, 663 accounting for a 95% decrease (fig. 4C), highlighting the importance to block residual 664 adenosinergic signalling downstream CD73 inhibition, co-targeting adenosine receptors. The 665 effectiveness of the treatment on the extracellular purinergic pathway was also supported by 666 the decrease of molecules downstream of adenosine (adenine and inosine in viable tumour and 667 necrotic margin areas) (suppl. fig 6B-C), and the increase of upstream and alternative pathway 668 molecules as AMP (in the necrotic margin, suppl. fig 6D) and xanthine (in both viable tumour 669 and necrotic margin, suppl. fig 6E) respectively. There was no change in the distribution of 670 ATP, ADP and hypoxanthine (suppl. fig 6F-H). 671 The Adoi approach led to a 30% reduction of tumour growth ratio (mean of 8 vs 5.5 -folds 672 increase from the baseline, p=0.003, fig. 4D and suppl. fig. 7A) and tumour weight (median 673 1.24 vs 0.78 grams, 0.039 fig. 4A). Single agent AZD4635 induced a similar tumour control to 674 the full combination. However, the therapeutic effect was delayed (suppl. fig. 7B), with a 30% 675 growth reduction in the combination arm when compared to Adora2ai inhibition alone with 676 single agent AZD4635, over the first 4 days of treatment (p=0.01). Targeting adenosine pathway delays tumour growth of murine pancreatic cancer 650 representing a combinational therapeutic opportunity 651 For biological reasons, 677 given also that AZD4635 is a competitive inhibitor and its efficacy is dependent on the amount 678 of extracellular adenosine, we chose to use it in combination with anti-CD73 antibody to 679 maximise the blocking on extracellular adenosine effects. These data support previous findings 680 showing the same combination had greater anti-tumour immune effect 38. In contrast, targeting 681 29 29 the adenosine pathway with Adoi in 2838c3 allografts where necrosis and consequently peri- 682 necrotic adenosine are low, and M2 macrophages express lower level of Adora2a, did not 683 translate into tumour growth reduction (suppl. fig. 7C). The adenosine pathway has been shown 684 to control the metastatic process and several authors have shown that inhibiting this axis can 685 reduce the metastatic burden in mouse models 49 50. However, we were able to show for the 686 first time that blocking adenosine generation and function can significantly reduce the 687 occurrence of spontaneous metastasis in an IOT-resistant pre-clinical model of PDAC. The 688 6419c5 s.c. model spontaneously develops lung metastases in 100% of the mice and blocking 689 adenosine strongly reduced the metastatic burden (median of % mets/lung area 0.77% vs 2.6%; 690 p=0.016; fig. 4E). 691 the adenosine pathway with Adoi in 2838c3 allografts where necrosis and consequently peri- 682 necrotic adenosine are low, and M2 macrophages express lower level of Adora2a, did not 683 translate into tumour growth reduction (suppl. fig. 7C). The adenosine pathway has been shown 684 to control the metastatic process and several authors have shown that inhibiting this axis can 685 reduce the metastatic burden in mouse models 49 50. However, we were able to show for the 686 first time that blocking adenosine generation and function can significantly reduce the 687 occurrence of spontaneous metastasis in an IOT-resistant pre-clinical model of PDAC. The 688 6419c5 s.c. model spontaneously develops lung metastases in 100% of the mice and blocking 689 adenosine strongly reduced the metastatic burden (median of % mets/lung area 0.77% vs 2.6%; 690 p=0.016; fig. 4E). 691 the adenosine pathway with Adoi in 2838c3 allografts where necrosis and consequently peri- 682 necrotic adenosine are low, and M2 macrophages express lower level of Adora2a, did not 683 translate into tumour growth reduction (suppl. fig. 7C). Targeting adenosine pathway delays tumour growth of murine pancreatic cancer 650 representing a combinational therapeutic opportunity 651 A weekly ultrasound revealed a tendency for tumour 708 stabilisation in mice treated with cytotoxic therapeutics plus adenosine inhibition, when 709 compared to the control arm during the first 2 weeks of treatment (fig. 4K). 710 Combining adenosine blockade (Adoi) and immunotherapy (FCP) reduced significantly 711 tumour growth of the IOT-resistant allograft model when compared to control treatment (65% 712 tumour growth reduction; p=0.002) and FCP (35% tumour growth reduction; p=0.021) arms 713 (suppl. fig. 7 D-F). Data from two separate experiments with the same controls showed that 714 adding Adoi to FCP remains the best combination in controlling tumour growth (suppl. fig. 7 715 G-I). These data suggest again that targeting the adenosine pathway in PDAC offers a new 716 strategy to modulate the anti-tumour immune response. 717 Combining adenosine blockade (Adoi) and immunotherapy (FCP) reduced significantly 711 tumour growth of the IOT-resistant allograft model when compared to control treatment (65% 712 tumour growth reduction; p=0.002) and FCP (35% tumour growth reduction; p=0.021) arms 713 (suppl. fig. 7 D-F). Data from two separate experiments with the same controls showed that 714 adding Adoi to FCP remains the best combination in controlling tumour growth (suppl. fig. 7 715 G-I). These data suggest again that targeting the adenosine pathway in PDAC offers a new 716 strategy to modulate the anti-tumour immune response. 717 Targeting the adenosine pathway results in reprogramming of the TME in the IOT- 719 resistant pancreatic cancer mouse model. 720 Targeting the adenosine pathway results in reprogramming of the TME in the IOT- 719 resistant pancreatic cancer mouse model. 720 To understand the role of adenosine modulation in reprogramming the TME, given the effect 721 on tumour growth alone or in combination we analysed the changes in immune infiltration 722 following anti-CD73 and AZD4635 treatment. 723 The TME of PDAC is an intricate structure that relies on the presence of multiple non- 724 malignant cells. This TME is recapitulated in pre-clinical models of PDAC 37. In order to 725 investigate the broader effect of Adoi in the 6419c5 PDAC model, given the effect we have 726 seen on tumour growth when used alone or in combination, we performed a bulk RNAseq 727 analysis of the 6419c5 model treated with Adoi or control (5 vs 6 mice, see methods). Targeting adenosine pathway delays tumour growth of murine pancreatic cancer 650 representing a combinational therapeutic opportunity 651 The adenosine pathway has been shown 684 to control the metastatic process and several authors have shown that inhibiting this axis can 685 reduce the metastatic burden in mouse models 49 50. However, we were able to show for the 686 first time that blocking adenosine generation and function can significantly reduce the 687 occurrence of spontaneous metastasis in an IOT-resistant pre-clinical model of PDAC. The 688 6419c5 s.c. model spontaneously develops lung metastases in 100% of the mice and blocking 689 adenosine strongly reduced the metastatic burden (median of % mets/lung area 0.77% vs 2.6%; 690 p=0.016; fig. 4E). 691 These data suggest that targeting myeloid related, extracellular adenosine formation and 692 effect would have an effect on tumour growth, making this approach a candidate for 693 combinatorial therapeutic studies. Indeed, when combined with cytotoxic treatment 694 (AZD6738, an ATR inhibitor and gemcitabine; fig. 4F-G) or IOT (anti-CD40 agonist, anti-PD- 695 L1 and anti-CTLA4 (FCP); suppl. fig. 7D), the adenosine modulation reduced further the 696 tumour growth rate of the aggressive IOT-resistant 6419c5 tumour model. 697 AZD6738/gemcitabine alone was able to significantly slow the growth of the IOT-resistant 698 model (2/7 stable disease, SD [28.5%]), but the addition of the adenosine blocking (AZD4635 699 + 2c5mIgG1) led to further stabilization of the tumour growth in a 2-week regimen (p=0.003 700 vs AZD6738/gem alone; 4/7 SD [57.1%]; fig. 4G-H). These data supported the investigation 701 of the same combination in autochthonous tumours in KPC mice (fig. 4I) to assess whether the 702 addition of Adoi to cytotoxic treatment (AZD6738+gemcitabine) prolonged survival in this 703 model, considered a gold standard in this disease. As figure 4J shows, the combination of Adoi 704 and ATRi/gem induced a 3-fold increase in median overall survival (mOS) in KPC mice 705 compared to control groups (vehicles + isotype 12.5 days vs combo 41 days, p=0.0006). The 706 30 30 4-drug regimen is significantly better than single schedule arms (mOS: Adoi 19 days and 707 AZD6738 + gemcitabine 13 days). A weekly ultrasound revealed a tendency for tumour 708 stabilisation in mice treated with cytotoxic therapeutics plus adenosine inhibition, when 709 compared to the control arm during the first 2 weeks of treatment (fig. 4K). 710 4-drug regimen is significantly better than single schedule arms (mOS: Adoi 19 days and 707 AZD6738 + gemcitabine 13 days). Targeting adenosine pathway delays tumour growth of murine pancreatic cancer 650 representing a combinational therapeutic opportunity 651 728 Following the 14-day treatment with AZD4635 and anti-CD73 the relative expression of 712 729 genes decreased by ≥50% (logfold <-0.58; fig. 5A). KEGG and GO Biological process pathway 730 31 analysis revealed that extracellular adenosine has a broad impact on TME of the IOT-resistant 731 model of PDAC (fig. 5B and suppl. fig. 8A). Genes associated with hypoxia response and 732 vasculogenesis (e.g. Hif1a, Slc2a1, Hilpda, Adm, Vegfa, Vegfd), immunity and immune 733 suppression (e.g. Cd274, Cd209, Mrc1, Cd200, Il1a, Il6, Ptgs2) and tumour stroma/ECM 734 organisation (e.g. Col5a3, Col6a3, Itga2, Mmp13, Mmp3, Mmp9, Ereg, Pthlh) were 735 significantly downregulated by the treatment (fig. 5B-C). 736 Of note, several functional and structural downregulated genes were associated with 737 the innate immune system (fig. 5D left), particularly with M2 polarised macrophages (e.g. 738 Cd209, Mrc1, Mrc2, CD163). RNAseq analysis also showed a significant decrease of the 739 expression of Cd274 (PD-L1) gene, suggesting a strong rationale for the use of adenosine 740 inhibition as combination for immunotherapy studies involving immune checkpoint inhibitors. 741 The downregulation of Mrc1 (CD206) and Cd274 (PD-L1) was validated analysing their 742 protein expression on tumour-infiltrating live cells following Adoi treatment. As shown in fig 743 5D (right), the proteins of these genes were strongly downregulated in the adenosine inhibition 744 arm (38% and 41% reduction of CD206 and PD-L1 on live cells respectively). 745 Furthermore, the adenosine signalling has previously been associated with the presence 746 of hypoxia 51 52; here we show for the first time that the presence of a functional extracellular 747 adenosine pathway is responsible for the expression of several genes related to hypoxia 748 (including Hif1a) suggesting the presence of a positive feedback loop. 749 Considering that the RNAseq analysis indicated that the innate immune system was 750 affected by adenosine inhibition, we analysed the changes in immune infiltration following 751 anti-CD73 and AZD4635 treatment. Flow cytometry analysis confirmed the findings 752 highlighted by the RNAseq analysis. Following treatment, tumours were less likely to be 753 infiltrated by M2 macrophages (median approximately 35000 vs 23000 cells/100mg; p=0.004; 754 32 fig. 6 A-B), in particular PD-L1+ ones (median 79% vs 65%; p=0.004; fig. 6B, right). IMC 755 analysis also revealed a trend towards reduction of M2 macrophages following treatment 756 [F4/80+ CD206+ (fig. 6C, E) or CD68+ CD206+ (fig. Targeting adenosine pathway delays tumour growth of murine pancreatic cancer 650 representing a combinational therapeutic opportunity 651 The 4-drug combination 782 produced an enhanced increase of the CD8+ cell infiltration (median 4.5 cells/mm2 vs 2.7 in 783 the control group, 3.9 in the AZD6738/gem group and 2.8 in the AZD4635/αCD73 group) and 784 reduction of Foxp3+ cell infiltration (median 6.5 cells/mm2 vs 8.1 in the control group, 9.3 in 785 the AZD6738/gem group and 7.2 in the AZD4635/αCD73 group) (suppl. fig. 8K). Similarly, 786 combination with IOT (Adoi + FCP) determined a further increase of the intra-tumoral 787 CD8/Tregs ratio induced by FCP treatment (ratio means control 0.28 vs FCP/Adoi 6.10 788 p=0.008; suppl. fig. 8L) mostly due to the repression of the Treg recruitment induced by IOT 789 alone. 790 TME of IOT-resistant model (6419c5 allografts), we performed IHC staining for CD8 and 780 Foxp3 and showed that the quadruple combination almost tripled the ratio CD8/Tregs (median 781 0.70 vs 0.25 of vehicles + isotype group; p=0.04; fig. 6G-H). The 4-drug combination 782 produced an enhanced increase of the CD8+ cell infiltration (median 4.5 cells/mm2 vs 2.7 in 783 the control group, 3.9 in the AZD6738/gem group and 2.8 in the AZD4635/αCD73 group) and 784 reduction of Foxp3+ cell infiltration (median 6.5 cells/mm2 vs 8.1 in the control group, 9.3 in 785 the AZD6738/gem group and 7.2 in the AZD4635/αCD73 group) (suppl. fig. 8K). Similarly, 786 combination with IOT (Adoi + FCP) determined a further increase of the intra-tumoral 787 CD8/Tregs ratio induced by FCP treatment (ratio means control 0.28 vs FCP/Adoi 6.10 788 p=0.008; suppl. fig. 8L) mostly due to the repression of the Treg recruitment induced by IOT 789 alone. 790 Targeting adenosine pathway delays tumour growth of murine pancreatic cancer 650 representing a combinational therapeutic opportunity 651 6D, F)] and the trend was more 757 pronounced in viable tumour compared to necrotic margin, but the difference was not 758 significant. Notably this reduced trend in infiltration is present in areas other than those where 759 adenosine is abundant, suggesting that adenosine could be stimulating the production of factors 760 affecting recruitment of macrophages in the viable tumour areas. Blocking the axis, also led 761 to a reduced frequency of infiltrating Tregs (mean 42% vs 27%; p=0.03, suppl. fig. 8B-C) and 762 a reduction of PD-L1 expression for all live cells within the tumour, more prominently CD45+ 763 cells (p=0.008) as shown in suppl. fig. 8D. However, the expression of PD-L1 declined in 764 F4/80+ macrophages (p=0.02) but not in dendritic cells following treatment (suppl. fig. 8E). Of 765 note, the combination of 2c5mIgG1 and AZD4635 is required to reduce the M2 macrophage 766 infiltration (p=0.03, suppl. fig. 8F) and the ratio of M2/M1 macrophages (p=0.04; suppl. fig. 767 8G) in the tumour, while single agents fail to do so. Finally, IMC data also showed a trend 768 towards a reduction (ns) of total macrophages in the treated tumours as shown by flow 769 cytometry, again more evident in the viable tumour regions (fig. 6C-D, F4/80 and CD68 panels 770 and suppl. fig 8H). IMC also showed a trend towards global reduction (ns) of M1 macrophages 771 (F4/80+ CD206- MHCII+) (suppl. fig. 8I-J) which was not apparent in the flow analysis. Further 772 studies would shed light on the relevance of these results, analysing the contribution of 773 adenosine abundance and spatial distribution to modelling of tumour infiltration by distinct 774 macrophage subpopulations beyond M1-M2 dichotomy. 775 Considering the reduction of the immune suppression in the TME following Adoi, we 776 Considering the reduction of the immune suppression in the TME following Adoi, we 776 explored changes associated with the adaptive immune system following combination of 777 adenosine inhibition and cytotoxic or immunotherapy therapeutics. To assess whether the 778 combination of Adoi plus ATRi/gemcitabine had an effect on the immune infiltration of the 779 33 TME of IOT-resistant model (6419c5 allografts), we performed IHC staining for CD8 and 780 Foxp3 and showed that the quadruple combination almost tripled the ratio CD8/Tregs (median 781 0.70 vs 0.25 of vehicles + isotype group; p=0.04; fig. 6G-H). Adenosine-related gene expression is associated with phenotype and survival in human 792 pancreatic cancer 793 Adenosine-related gene expression is associated with phenotype and survival in human 792 pancreatic cancer 793 To evaluate the importance of this pathway in the context of human PDAC and 794 highlight the role in the formation of TME we scored our adenosine-related gene expression 795 set against the PDAC subtypes published by Bailey 43. Of our 712 genes with a 50% decrease, 796 561 had a human ortholog and of these the z-scores of 517 genes were summed in each of the 797 97 patients with RNAseq data in Bailey et al. to obtain a score. We were able to show that the 798 adenosine-related gene expression is mostly expressed in the aggressive squamous subtype 799 (fig. 7A), that has been associated with a poorer prognosis. The score remained significantly 800 higher even when comparing the squamous subtypes with the grouped non-squamous (fig. 7B). 801 In order to create a PDAC-specific adenosine signature and to evaluate its performance 802 in PDAC-specific outcomes, we created a signature using the 561 human orthologous genes 803 In order to create a PDAC-specific adenosine signature and to evaluate its performance 802 in PDAC-specific outcomes, we created a signature using the 561 human orthologous genes 803 34 34 with a ≥ 50% decrease in expression following Adoi treatment. Of these, 52 genes were 804 selected for the signature (fig. 7C), that according to our RNAseq dataset were clearly 805 associated with the pathway areas dependent on adenosine (hypoxia response, immunity, 806 tumour stroma), were associated positively or negatively with PDAC prognosis, and were 807 significantly co-expressed with CD73 and/or Adora2a in the PDAC genome datasets (TCGA 808 or Bailey). Of the 176 and 170 patients with available progression free survival (PFS) and 809 disease-specific survival (DSS) outcome respectively, we found that the presence of a high 810 adenosine signature is associated with higher probability of PDAC progression (mPFS high 811 Ado 13.05 vs low Ado 18.25, p=0.02; fig. 7D) and a poorer PDAC-specific survival (mDSS 812 high Ado 19.66 vs low Ado NR, p=0.01; fig. 7E), suggesting again that the presence of a 813 functional adenosine pathway has a detrimental role in human PDAC. The signature was 814 validated using the PDAC QCMG Bailey’s dataset (49 genes were assessed, see figure legend) 815 confirming a shorter overall survival in patients with high adenosine signature tumours (fig. 7F 816 p=0.003). Adenosine-related gene expression is associated with phenotype and survival in human 792 pancreatic cancer 793 It’s worthy to consider that patients in the TCGA dataset are predominantly non- 817 metastatic, and the presence of the adenosine signature seems to become relevant for PDAC 818 associated death 20 months after diagnosis. The presence of a high adenosine signature appears 819 to be associated with shorter disease-free-survival, (mDFS high Ado 23.5 months vs low Ado 820 49.7 months, p=0.12; suppl. fig. 8M). 821 Discussion 822 Overall our data highlight that the generation of the extracellular adenosine is 823 instrumental for the innate immune system in shaping a pro-tumorigenic, immune suppressive 824 microenvironment in PDAC, in the context of a hypoxic milieu. We can speculate that this 825 unfavourable environment may create the condition for a more aggressive PDAC phenotype 826 which would then translate into the ability to escape the immune system, be resistant to 827 cytotoxic treatment and metastasize readily. 828 Overall our data highlight that the generation of the extracellular adenosine is 823 instrumental for the innate immune system in shaping a pro-tumorigenic, immune suppressive 824 microenvironment in PDAC, in the context of a hypoxic milieu. We can speculate that this 825 unfavourable environment may create the condition for a more aggressive PDAC phenotype 826 which would then translate into the ability to escape the immune system, be resistant to 827 cytotoxic treatment and metastasize readily. 828 35 35 Pancreatic ductal adenocarcinoma (PDAC) is projected to become the second highest 829 cause of cancer-related death in the US within 10 years 53, and represents one of the major 830 unmet needs of cancer treatment. Despite extensive efforts by laboratory and clinical scientists 831 in the last 50 years, only 1% of patients diagnosed with PDAC today will survive for 10 years 832 (https://www.cancerresearchuk.org/health-professional/cancer-statistics-for-the-uk). The 833 Pancreatic ductal adenocarcinoma (PDAC) is projected to become the second highest 829 cause of cancer-related death in the US within 10 years 53, and represents one of the major 830 unmet needs of cancer treatment. Despite extensive efforts by laboratory and clinical scientists 831 in the last 50 years, only 1% of patients diagnosed with PDAC today will survive for 10 years 832 (https://www.cancerresearchuk.org/health-professional/cancer-statistics-for-the-uk). The 833 response rate following standard treatments is poor, usually short-lasting, and associated with 834 significant treatment related toxicity 1. In the past few years, immunotherapy has provided new 835 hope in the treatment of several types of cancer, and has dramatically changed the life 836 expectancy of many patients with metastatic disease 54. However, this has not been true for 837 patients with PDAC which is associated with a very low response rate to immunotherapy, 838 usually confined to MSI-H/dMMR tumours, found only rarely in this disease 2. 839 829 The role of the innate immune system in the generation of an immune suppressive/pro- 840 tumorigenic microenvironment in PDAC is well known. Discussion 822 The presence of marked infiltration 841 of macrophages has been identified as an independent predictive factor of the aggressiveness 842 and prognosis of PDAC, in patients 25 26. Only recently, three phase I clinical trials in patients 843 with PDAC have shown that targeting the innate immune system can have impact in patients 844 with PDAC. A phase I trial published on Lancet Oncology, showed that a combination of anti 845 PD-1 and CD40 agonist, added to gemcitabine and nab-paclitaxel, led to 60% of response rate, 846 with some durable responses 55. In addition, the inhibition of the CXCL12/CXCR4 axis has 847 been demonstrated to modify the immunosuppressive TME of PDAC and CRC patients 56 57. 848 The extracellular adenosine pathway has also been shown to influence the TME 849 fostering the immune suppression provided by some innate immune subpopulations (as 850 myeloid and NKs) and inhibiting the function of the adaptive immune system, in particular, T- 851 cells 6 7 49. By activating its receptors, eAdo is able to increase the intracellular concentration 852 of cAMP which leads to the induction of a M2 phenotype of macrophages and block the 853 36 secretion of IL1β increasing the release of CXCL1, IL-6, IL-10 and IL-8 among others from 854 myeloid population which are known to orchestrate immune exclusion 10 58. eAdo also favours 855 the formation and maintenance of Treg cells 10, which are known to favour cancer progression 856 and IOT resistance . 857 secretion of IL1β increasing the release of CXCL1, IL-6, IL-10 and IL-8 among others from 854 myeloid population which are known to orchestrate immune exclusion 10 58. eAdo also favours 855 the formation and maintenance of Treg cells 10, which are known to favour cancer progression 856 and IOT resistance . 857 A recent publication, shows that genomic targeting on mouse PDAC cells of CD73 858 leads to a reduced in vivo tumour formation and change in the circulating and infiltrating 859 immune system36. 860 However, to date, little was known about the expression of the adenosine pathway in 861 the context of the innate and adaptive immune system in PDAC, how the extracellular 862 adenosine is generated and what are the targets of adenosine also in regard to its spatial 863 distribution and formation of adenosine. Discussion 822 890 Further, the downregulation of genes associated with hypoxia (Hif1a, Hilpda, Nos2, Hk1, Hk2, 891 Egln3) following treatment shows not only that the adenosine pathway is induced during 892 hypoxia (e.g. CD73 and Adora2b), but that the hypoxia response is also dependent on the 893 presence of the adenosine pathway in what we can speculate is a positive feedback loop. The 894 inhibition of adenosine led to a reduced infiltration of M2 macrophages further from the 895 hypoxic regions where adenosine is most abundant, suggesting that the effect of adenosine is 896 stimulating the secretion of factors that are recruiting monocytes into the tumour 897 microenvironment, replenishing macrophage infiltration (fig. 6 and suppl. fig. 8). Notably, 898 targeting the pathway can reduce tumour growth in an IOT-resistant model, improving the 899 response to cytotoxic and immunotherapy combinations (fig. 4 and suppl. fig. 7) even in 900 historically therapy-resistant models such as the KPC mice. 901 not seem to correlate with IOT- resistant or responsive tumour models, but there is a difference 878 when the target of adenosine (Adora2a receptor), is considered. Adora2a on myeloid 879 populations, in particular in pro-tumorigenic M2 macrophages but also in antigen presenting 880 cells, is differentially expressed in regard of IOT response phenotype, with the resistant 881 tumours abundantly overexpressing the receptor in these populations (fig.3 and suppl. fig. 882 4&5). Future analysis of human PDAC fresh specimens are needed to confirm the mechanism 883 we propose in the context of human disease. The bulk RNAseq analysis of tumour treated with 884 adenosine inhibition revealed indeed a broader role for adenosine in PDAC TME (fig. 5). 885 Genes related to immunosuppression and innate immunity recruitment (Cd274, Csf2, Cxcl2, 886 Ccl3, Ccl4, Ccl12, Il1a, Osm, Il6), angiogenesis (Vegfa, Vegfd, Adm2, Flt1, Pgf, Egln1) and 887 cell-ECM interaction (Adam19, Adamts14, Adamts4, Adamts5, Col5a3, Col6a, Itga2, Itga7, 888 Mmp3, Mmp9, Mmp12) indicated the targeting of population of cells responsible for the 889 acquisition of a pro-tumorigenic, pro-metastatic, pro-fibrotic and immune resistant phenotype. 890 Further, the downregulation of genes associated with hypoxia (Hif1a, Hilpda, Nos2, Hk1, Hk2, 891 Egln3) following treatment shows not only that the adenosine pathway is induced during 892 hypoxia (e.g. CD73 and Adora2b), but that the hypoxia response is also dependent on the 893 presence of the adenosine pathway in what we can speculate is a positive feedback loop. Discussion 822 864 Our results show that the mechanism of generation of extracellular adenosine in 865 pancreatic cancer TME is finely orchestrated by tumour infiltrating myeloid cells and tumour 866 cells, due to the expression of high level of CD39 in infiltrating myeloid cells and CD73 on 867 both cell types. A recent paper demonstrated the presence of CD73 on MDSCs and 868 macrophages35. We identify that more broadly, ~90% of tumour-infiltrating myeloid cells in 869 s.c. KPCY-derived tumours express CD73. We also validated this finding using autochthonous 870 tumour model as the KPC mouse. We have also showed that the pathway can be overexpressed 871 in T-cells infiltrating the tumours, regardless of their activation status (fig. 1,2 and suppl. fig. 872 2,4). The distribution of extracellular adenosine is spatially heterogeneous and a high level of 873 extracellular adenosine correlates with the presence of a hypoxic environment and is favoured 874 by the presence of necrosis, where the myeloid population is enriched (fig.3). Necrosis is 875 common in human PDAC and related to poor prognosis for all stages 59. The enrichment of a 876 CD39+ CD73+ double population, potentially able to independently produce adenosine, does 877 37 37 not seem to correlate with IOT- resistant or responsive tumour models, but there is a difference 878 when the target of adenosine (Adora2a receptor), is considered. Adora2a on myeloid 879 populations, in particular in pro-tumorigenic M2 macrophages but also in antigen presenting 880 cells, is differentially expressed in regard of IOT response phenotype, with the resistant 881 tumours abundantly overexpressing the receptor in these populations (fig.3 and suppl. fig. 882 4&5). Future analysis of human PDAC fresh specimens are needed to confirm the mechanism 883 we propose in the context of human disease. The bulk RNAseq analysis of tumour treated with 884 adenosine inhibition revealed indeed a broader role for adenosine in PDAC TME (fig. 5). 885 Genes related to immunosuppression and innate immunity recruitment (Cd274, Csf2, Cxcl2, 886 Ccl3, Ccl4, Ccl12, Il1a, Osm, Il6), angiogenesis (Vegfa, Vegfd, Adm2, Flt1, Pgf, Egln1) and 887 cell-ECM interaction (Adam19, Adamts14, Adamts4, Adamts5, Col5a3, Col6a, Itga2, Itga7, 888 Mmp3, Mmp9, Mmp12) indicated the targeting of population of cells responsible for the 889 acquisition of a pro-tumorigenic, pro-metastatic, pro-fibrotic and immune resistant phenotype. Discussion 822 The 894 inhibition of adenosine led to a reduced infiltration of M2 macrophages further from the 895 hypoxic regions where adenosine is most abundant, suggesting that the effect of adenosine is 896 stimulating the secretion of factors that are recruiting monocytes into the tumour 897 microenvironment, replenishing macrophage infiltration (fig. 6 and suppl. fig. 8). Notably, 898 targeting the pathway can reduce tumour growth in an IOT-resistant model, improving the 899 response to cytotoxic and immunotherapy combinations (fig. 4 and suppl. fig. 7) even in 900 historically therapy-resistant models such as the KPC mice. 901 38 Targeting adenosine would represent an alternative strategy to reduce the infiltration of 902 pro-tumorigenic macrophages in PDAC lesions. One approach has been the administration of 903 a CSF1R inhibitor 34, which has shown promising pre-clinical data, that have not been 904 translated in human so far. A recent publication shows that in CRC mouse models, the use of 905 anti CSF1R treatment spares a subpopulation of macrophages characterised by the expression 906 of Cd274 (PD-L1), Vegfa, Hilpda, Bhlhe40, Mmp12, Cebpb, Hmox1 among others 30. Given 907 that all of these genes are among the immune suppressive and vasculogenic molecules that 908 seem to be strongly downregulated by adenosine inhibition and our data show a reduction of 909 some subpopulation of PD-L1+ macrophages, we can speculate that adenosine inhibition could 910 potentially target these populations of pro-angiogenic, immune suppressive macrophages. 911 Information provided by the PDAC specific adenosine signature, indicate that the 912 adenosine pathway appears to play a role in progression and survival of human PDAC, due to 913 the ability of the adenosine inhibition to profoundly reprogram the tumour microenvironment 914 in PDAC models (fig. 5-6 and suppl. fig. 8). Gathering more information on the role of this 915 pathway in human cancers should be a priority, retrospectively evaluating and then 916 prospectively stratifying the patients on the basis of histopathological/radiological features and 917 the spatial distribution of adenosine. 918 Targeting adenosine would represent an alternative strategy to reduce the infiltration of 902 pro-tumorigenic macrophages in PDAC lesions. One approach has been the administration of 903 a CSF1R inhibitor 34, which has shown promising pre-clinical data, that have not been 904 translated in human so far. Discussion 822 Finally, targeting extracellular adenosine should be considered 927 as an alternative to improve the efficacy of cytotoxic and IOT in future PDAC-specific clinical 928 trials. 929 delay of PDAC tumour growth. Finally, targeting extracellular adenosine should be considered 927 as an alternative to improve the efficacy of cytotoxic and IOT in future PDAC-specific clinical 928 trials. 929 delay of PDAC tumour growth. Finally, targeting extracellular adenosine should be considered 927 as an alternative to improve the efficacy of cytotoxic and IOT in future PDAC-specific clinical 928 trials. 929 Author contributions 930 V.G. and D.I.J conceptualised the project. V.G., A.D., H.H., K.W., J.P.M., J.E. and DIJ 931 designed the experiments. V.G., A.D., H.H., K.W., H.B., S.A.K., M.W., S.Y.L., B.P.K. 932 conducted the experiments. V.G., A.D., H.H., K.W., S.I., F.M.R., R.B., J.P.M, S.J.D. J.E. and 933 D.I.J analysed the data. J.E.D.T. R.G., J.P.M., S.J.D., A.G.S, J.E., D.I.J. provided supervision 934 and V.G., A.D., H.H., K.W., S.I., J.P.M., S.J.D., A.G.S, J.E., D.I.J. discussed the results. V.G. 935 and D.I.J. wrote the manuscript. All authors read, review, edited and approved the final 936 manuscript. 937 V.G. and D.I.J conceptualised the project. V.G., A.D., H.H., K.W., J.P.M., J.E. and DIJ 931 designed the experiments. V.G., A.D., H.H., K.W., H.B., S.A.K., M.W., S.Y.L., B.P.K. 932 conducted the experiments. V.G., A.D., H.H., K.W., S.I., F.M.R., R.B., J.P.M, S.J.D. J.E. and 933 D.I.J analysed the data. J.E.D.T. R.G., J.P.M., S.J.D., A.G.S, J.E., D.I.J. provided supervision 934 and V.G., A.D., H.H., K.W., S.I., J.P.M., S.J.D., A.G.S, J.E., D.I.J. discussed the results. V.G. 935 and D.I.J. wrote the manuscript. All authors read, review, edited and approved the final 936 manuscript. 937 Discussion 822 A recent publication shows that in CRC mouse models, the use of 905 anti CSF1R treatment spares a subpopulation of macrophages characterised by the expression 906 of Cd274 (PD-L1), Vegfa, Hilpda, Bhlhe40, Mmp12, Cebpb, Hmox1 among others 30. Given 907 that all of these genes are among the immune suppressive and vasculogenic molecules that 908 seem to be strongly downregulated by adenosine inhibition and our data show a reduction of 909 some subpopulation of PD-L1+ macrophages, we can speculate that adenosine inhibition could 910 potentially target these populations of pro-angiogenic, immune suppressive macrophages. 911 902 Information provided by the PDAC specific adenosine signature, indicate that the 912 adenosine pathway appears to play a role in progression and survival of human PDAC, due to 913 the ability of the adenosine inhibition to profoundly reprogram the tumour microenvironment 914 in PDAC models (fig. 5-6 and suppl. fig. 8). Gathering more information on the role of this 915 pathway in human cancers should be a priority, retrospectively evaluating and then 916 prospectively stratifying the patients on the basis of histopathological/radiological features and 917 the spatial distribution of adenosine. 918 Information provided by the PDAC specific adenosine signature, indicate that the 912 adenosine pathway appears to play a role in progression and survival of human PDAC, due to 913 the ability of the adenosine inhibition to profoundly reprogram the tumour microenvironment 914 in PDAC models (fig. 5-6 and suppl. fig. 8). Gathering more information on the role of this 915 pathway in human cancers should be a priority, retrospectively evaluating and then 916 prospectively stratifying the patients on the basis of histopathological/radiological features and 917 the spatial distribution of adenosine. 918 In summary, we have shown for the first time that tumour-infiltrating myeloid immune 919 cells contribute to the generation of extracellular adenosine in the context of PDAC, in 920 correlation with the presence of hypoxia. Macrophages in particular, express high levels of 921 Adora2a receptor in PDAC models and targeting the adenosine/myeloid axis remodels the 922 TME. Data from IMC, flow cytometry and RNAseq suggest that the adenosine pathway is 923 fundamental to the formation of a pro-tumorigenic, immunosuppressive TME, and its 924 expression is associated with an aggressive phenotype and poor survival in human PDAC. The 925 re-modelling of the TME caused by the inhibition of the adenosine pathway, translate into a 926 39 delay of PDAC tumour growth. Acknowledgments 938 All CRUK CI authors received research funding from Cancer Research UK (Nos. 939 C14303/A17197 and C9545/A29580). The Li Ka Shing Centre where this work was performed 940 was generously funded by CK Hutchison Holdings Limited, the University of Cambridge, 941 CRUK, The Atlantic Philanthropies and others. This work was supported by Cancer Research 942 UK (C9685/A27444) funding to VG. The authors wish to thank all the CRUK Cambridge 943 Institute core facilities, in particular Research Instrumentation & Cell Services (RICS), Flow 944 Cytometry, Histopathology, Biological Resource Unit (BRU), Genomics and Genome editing 945 cores. VG would like to thank Maike de la Roche (CRUK Cambridge Institute - University of 946 Cambridge) and Klaus Okkenhaug (Department of Pathology - University of Cambridge) for 947 helpful suggestions and advices. This study was also supported by Cancer Research UK 948 Precision Panc grant C96/A25238. HB holds a PhD studentship at the University of Cambridge 949 which is supported jointly by the University of Cambridge Experimental Medicine Training 950 40 40 Initiative (EMI) programme in partnership with AstraZeneca (EMI-AZ) and the NIHR 951 Biomedical Research Centre and SYL is founded by the Cambridge Trust (Cambridge 952 International Scholarship). Work by JT / KW is funded by a core grant award from the MRC 953 (MC_UU_00025/12). S.A.K. and. J.P.M. were supported by Cancer Research UK core 954 funding to the Beatson Institute (A17196 and A31287) and to J.P.M. Lab (A29996). The 955 KPCY-derived cell lines were a kind gift of Ben Stanger (University of Pennsylvania). 956 AZD4635, AZD6738 and the antibodies anti-CD73 (2C5, murine IgG1-Fc), anti-PD-L1 957 (AB740080 D265A), NIP228 muIgG1 isotype, NIP228 muIgG1 D265A isotype, were kindly 958 provided by AstraZeneca. The results shown here are in part based upon data generated by the 959 TCGA Research Network: https://www.cancer.gov/tcga. 960 Figure 1. Expression of CD73 on KPCY-derived cell lines and response to anti-CD73 in 962 vitro inhibition. 963 Figure 1. Expression of CD73 on KPCY-derived cell lines and response to anti-CD73 in 962 vitro inhibition. 963 Figure 1. Expression of CD73 on KPCY-derived cell lines and response t 962 989 Statistical analysis was performed using one-way ANOVA with post-hoc test analysis for 990 multiple comparisons (B) and two-tailed unpaired Student’s t-test (D); p values are shown in 991 the graphs when considered significant (p<0.05). 992 993 Figure 3. Adenosine distribution is spatially heterogeneous and targets myeloid 994 subpopulations. 995 (A) Mass spectrometry Imaging (MSI) representative images showing adenosine expression 996 and distribution in PDAC s c allografts (4 mice per group) at day 21 post-implantation 997 All data are presented as mean ± SEM from experiments repeated 3 times. Statistical analysis 974 was performed with two-tailed unpaired Student’s t-test (B), mixed-effect model (C) and one- 975 way ANOVA with post-test analysis for multiple comparisons; p values are shown in the 976 graphs when considered significant (p<0.05). 977 All data are presented as mean ± SEM from experiments repeated 3 times. Statistical analysis 974 was performed with two-tailed unpaired Student’s t-test (B), mixed-effect model (C) and one- 975 way ANOVA with post-test analysis for multiple comparisons; p values are shown in the 976 graphs when considered significant (p<0.05). 977 Figure 2. The adenosine pathway members are expressed on PDAC-infiltrating immune 979 cells. 980 (A) Representative flow cytometry plots showing expression of CD39 and CD73 on myeloid 981 population (left), Tregs (middle) and CD8+ T-cells (right) from KPCY-cell line derived tumour 982 (upper) and matched spleen (lower) (N= 5 mice per group). 983 (A) Representative flow cytometry plots showing expression of CD39 and CD73 on myeloid 981 population (left), Tregs (middle) and CD8+ T-cells (right) from KPCY-cell line derived tumour 982 (upper) and matched spleen (lower) (N= 5 mice per group). 983 (B) Box and whisker graph showing CD39+CD73+ double expression on CD11b+ cells for 984 2838c3 (N=5) and 6419c5 (N=5) in tumours, matched spleens and tumour draining lymph 985 nodes. 986 (B) Box and whisker graph showing CD39+CD73+ double expression on CD11b+ cells for 984 2838c3 (N=5) and 6419c5 (N=5) in tumours, matched spleens and tumour draining lymph 985 nodes. 986 (C-D) Representative flow cytometry plots (C) and box and whisker graph (D) showing 987 CD39+CD73+ double expression on CD11b+ cells infiltrating autochthonous KPC tumours 988 (N=13). All data are presented as interleaved box and whiskers. 989 (C-D) Representative flow cytometry plots (C) and box and whisker graph (D) showing 987 CD39+CD73+ double expression on CD11b+ cells infiltrating autochthonous KPC tumours 988 (N=13). All data are presented as interleaved box and whiskers. 989 CD39+CD73+ double expression on CD11b+ cells infiltrating autochthonous KPC tumours 988 (N=13). All data are presented as interleaved box and whiskers. 989 Statistical analysis was performed using one-way ANOVA with post-hoc test analysis for 990 multiple comparisons (B) and two-tailed unpaired Student’s t-test (D); p values are shown in 991 the graphs when considered significant (p<0.05). 992 993 Figure 3. Adenosine distribution is spatially heterogeneous and targets myeloid 994 subpopulations. 995 (A) Mass spectrometry Imaging (MSI) representative images showing adenosine expression 996 and distribution in PDAC s.c. allografts (4 mice per group) at day 21 post-implantation. 997 Statistical analysis was performed using one-way ANOVA with post-hoc test analysis for 990 multiple comparisons (B) and two-tailed unpaired Student’s t-test (D); p values are shown in 991 the graphs when considered significant (p<0.05). 992 Statistical analysis was performed using one-way ANOVA with post-hoc test analysis for 990 multiple comparisons (B) and two-tailed unpaired Student’s t-test (D); p values are shown in 991 the graphs when considered significant (p<0.05). 992 Figure 3. Adenosine distribution is spatially heterogeneous and targets myeloid 994 subpopulations. Figure 1. Expression of CD73 on KPCY-derived cell lines and response t 962 (A) Representative histogram of CD73 expression on KPCY-derived cell line (2838c3) in flow 964 cytometry. (B) CD73 expression was evaluated on KPCY-derived cell lines treated with 10 965 µg/ml of NIP228 (IgG isotype) or 2c5mIgG1 (anti-CD73 neutralising antibody) for 24 hours. 966 (A) Representative histogram of CD73 expression on KPCY-derived cell line (2838c3) in flow 964 cytometry. (B) CD73 expression was evaluated on KPCY-derived cell lines treated with 10 965 µg/ml of NIP228 (IgG isotype) or 2c5mIgG1 (anti-CD73 neutralising antibody) for 24 hours. 966 (C) 2838c3 (left) and 6419c5 (right) cell lines were grown with increasing concentration of 967 anti-CD73 or isotype (100 µg/ml) and confluency was evaluated using IncuCyte time lapse 968 imaging for up to 72 hours. For each experiment, 3 different wells per condition were used per 969 experiment. 970 (D-E) Representative images (D) and graphs (E) showing survival fraction of cells (2838c3 971 left, 6419c5 right) from the colony-forming experiment following 8-day treatment with anti- 972 CD73 or isotype. For each experiment, 3 different wells per condition were used. 973 (D-E) Representative images (D) and graphs (E) showing survival fraction of cells (2838c3 971 left, 6419c5 right) from the colony-forming experiment following 8-day treatment with anti- 972 CD73 or isotype. For each experiment, 3 different wells per condition were used. 973 41 41 All data are presented as mean ± SEM from experiments repeated 3 times. Statistical analysis 974 was performed with two-tailed unpaired Student’s t-test (B), mixed-effect model (C) and one- 975 way ANOVA with post-test analysis for multiple comparisons; p values are shown in the 976 graphs when considered significant (p<0.05). 977 978 Figure 2. The adenosine pathway members are expressed on PDAC-infiltrating immune 979 cells. 980 (A) Representative flow cytometry plots showing expression of CD39 and CD73 on myeloid 981 population (left), Tregs (middle) and CD8+ T-cells (right) from KPCY-cell line derived tumour 982 (upper) and matched spleen (lower) (N= 5 mice per group). 983 (B) Box and whisker graph showing CD39+CD73+ double expression on CD11b+ cells for 984 2838c3 (N=5) and 6419c5 (N=5) in tumours, matched spleens and tumour draining lymph 985 nodes. 986 (C-D) Representative flow cytometry plots (C) and box and whisker graph (D) showing 987 CD39+CD73+ double expression on CD11b+ cells infiltrating autochthonous KPC tumours 988 (N=13). All data are presented as interleaved box and whiskers. Figure 2. The adenosine pathway members are expressed on PDAC-infiltrating immune 979 cells. 980 1013 (H) Box and whisker plot of the percentage of M2 macrophages positive for Adora2a 1012 comparing two allografts (6419c5 and 2838c3) and KPC tumours. 1013 Statistical analysis was performed using one-way ANOVA with post-hoc test analysis for 1014 multiple comparisons (E,H) and two-tailed unpaired Student’s t-test (G); p values are shown 1015 in the graphs when considered significant (p<0.05). 1016 Statistical analysis was performed using one-way ANOVA with post-hoc test analysis for 1014 multiple comparisons (E,H) and two-tailed unpaired Student’s t-test (G); p values are shown 1015 in the graphs when considered significant (p<0.05). 1016 Statistical analysis was performed using one-way ANOVA with post-hoc test analysis for 1014 multiple comparisons (E,H) and two-tailed unpaired Student’s t-test (G); p values are shown 1015 in the graphs when considered significant (p<0.05). 1016 Figure 2. The adenosine pathway members are expressed on PDAC-infiltrating immune 979 cells. 980 995 (A) Mass spectrometry Imaging (MSI) representative images showing adenosine expression 996 and distribution in PDAC s.c. allografts (4 mice per group) at day 21 post-implantation. 997 (A) Mass spectrometry Imaging (MSI) representative images showing adenosine expression 996 and distribution in PDAC s.c. allografts (4 mice per group) at day 21 post-implantation. 997 42 42 Classification was obtained based on metabolites expression and is represented as follows: 998 viable tumour (red), necrotic margins (green). 999 Classification was obtained based on metabolites expression and is represented as follows: 998 viable tumour (red), necrotic margins (green). 999 (B) Relative tissue composition differences of viable tumour, necrotic margin and necrotic 1000 areas for 6419c5 (N=4) and 2838c3 (N=4) allografts at day 21 post-implantation. As shown, 1001 necrosis was present in only one 2838c3 sample at 21 days post-implantation. Error bars 1002 represent Standard Deviation. 1003 (C) MSI analysis showing relative abundance (a.u.) of adenosine in the different areas in 1004 6419c5 and 2838c3 allografts at day 21 post-implantation. Bars represent means. 1005 (C) MSI analysis showing relative abundance (a.u.) of adenosine in the different areas in 1004 6419c5 and 2838c3 allografts at day 21 post-implantation. Bars represent means. 1005 (D-E) Representative plots (E) and summary graph (F) from flow cytometry analysis showing 1006 Adora2a expression on pro-tumorigenic M2 macrophages in allografts (upper) derived from 1007 6419c5 (left) and 2838c3 (right) implantation. Same expression is shown in M2 macrophages 1008 in matched spleens (lower) (8-9 mice per group were used). 1009 (D-E) Representative plots (E) and summary graph (F) from flow cytometry analysis showing 1006 Adora2a expression on pro-tumorigenic M2 macrophages in allografts (upper) derived from 1007 6419c5 (left) and 2838c3 (right) implantation. Same expression is shown in M2 macrophages 1008 in matched spleens (lower) (8-9 mice per group were used). 1009 (F-G) Flow cytometry plots (G) and graph (H) showing expression of Adora2a in M2 1010 macrophages comparing KPC (n=8) autochthonous tumours and matched spleens. 1011 (F-G) Flow cytometry plots (G) and graph (H) showing expression of Adora2a in M2 1010 macrophages comparing KPC (n=8) autochthonous tumours and matched spleens. 1011 (H) Box and whisker plot of the percentage of M2 macrophages positive for Adora2a 1012 comparing two allografts (6419c5 and 2838c3) and KPC tumours. 1013 (H) Box and whisker plot of the percentage of M2 macrophages positive for Adora2a 1012 comparing two allografts (6419c5 and 2838c3) and KPC tumours. Figure 4. In vivo modulation of the adenosine pathway reduces tumour growth and 1018 metastasis and improves the efficacy of cytotoxic treatment. 1019 Figure 4. In vivo modulation of the adenosine pathway reduces tumour growth and 1018 metastasis and improves the efficacy of cytotoxic treatment. 1019 Figure 4. In vivo modulation of the adenosine pathway reduces tumour growth and 1018 metastasis and improves the efficacy of cytotoxic treatment. 1019 (A) Schedule of adenosine inhibition (Adoi) treatment. Treatment was started following 12-14 1020 days from implantation and continued for 2 weeks. Antibody anti-CD73 (2c5mIgG1, murine 1021 43 IgG1) was dosed twice per week intraperitoneally at 10 mg/kg. Adora2a inhibitor (AZD4635) 1022 was given by oral gavage twice daily at 50 mg/kg. 1023 (B-C) Mass spectrometry Imaging (MSI) representative images (B) and MSI analysis graph 1024 with relative abundance (a.u.) (C) showing adenosine expression and distribution in PDAC 1025 allografts treated with vehicle + isotype or Adoi, at day 14 from treatment start (6 mice per 1026 treatment group). Classification was obtained based on metabolites expression and is 1027 represented as follows: viable tumour (green line), necrotic margins (yellow line). 1028 (D) Tumour growth ratio (left) and weight (right) of 6419c5 allografts in C57Bl/6 mice treated 1029 with anti-CD73 + AZD4635 (N=16) or vehicle + isotype (N=15). 1030 (D) Tumour growth ratio (left) and weight (right) of 6419c5 allografts in C57Bl/6 mice treated 1029 with anti-CD73 + AZD4635 (N=16) or vehicle + isotype (N=15). 1030 (E) Representative image (left) and graph (right) showing % of area of the lung analysed 1031 occupied by metastasis (met/lung areas x 100) in vehicle + isotype (N=12) and anti- 1032 CD73+AZD4635 (N=13), evaluated for the presence of spontaneous occurrence of lung 1033 metastases. Every dot represents a single mouse. Tissues were stained with an anti-p53 1034 antibody to highlight the presence of cancer cells. A group of more than 5 p53-positive cells 1035 was counted as metastasis. 1036 (F) Schedule of 6419c5 tumour allografts 14-day treatment as following (N=7 mice per group): 1037 vehicles + isotype, AZD6738 + gemcitabine, anti-CD73 + AZD4635, AZD6738 + gemcitabine 1038 + anti-CD73 + AZD4635. 1039 (F) Schedule of 6419c5 tumour allografts 14-day treatment as following (N=7 mice per group): 1037 vehicles + isotype, AZD6738 + gemcitabine, anti-CD73 + AZD4635, AZD6738 + gemcitabine 1038 + anti-CD73 + AZD4635. Figure 4. In vivo modulation of the adenosine pathway reduces tumour growth and 1018 metastasis and improves the efficacy of cytotoxic treatment. 1019 1039 (G) Tumour growth ratio (14 days) of 6419c5 tumour allografts treated as above 1040 (G) Tumour growth ratio (14 days) of 6419c5 tumour allografts treated as above 040 (H) Percentage change in the long diameter length following 14 days of treatment per group. 1041 Number of mice with stable disease (SD, <20% increase and <30% decrease) are shown at the 1042 bottom. 1043 (H) Percentage change in the long diameter length following 14 days of treatment per group. 1041 Number of mice with stable disease (SD, <20% increase and <30% decrease) are shown at the 1042 bottom. 1043 (I) Schedule of KPC mice treatment as following: vehicles + isotype (12 mice), AZD6738 + 1044 gemcitabine (11 mice), anti-CD73 + AZD4635 (7 mice), AZD6738 + gemcitabine + anti-CD73 1045 (I) Schedule of KPC mice treatment as following: vehicles + isotype (12 mice), AZD6738 + 1044 gemcitabine (11 mice), anti-CD73 + AZD4635 (7 mice), AZD6738 + gemcitabine + anti-CD73 1045 44 44 + AZD4635 (combo, 12 mice). Adenosine inhibition was administered until endpoint, while 1046 AZD6738 + gemcitabine was allowed up to 3 weeks. 1047 (J) Survival analysis of KPC mice treated as above, including median overall survival (mOS). 1048 (K) Percentage of tumour volume increased in vehicles vs combo group at day 7 and 14 of 1049 treatment. 1050 (J) Survival analysis of KPC mice treated as above, including median overall survival (mOS). 1048 (K) Percentage of tumour volume increased in vehicles vs combo group at day 7 and 14 of 1049 treatment. 1050 All data are presented as mean ± SEM. Statistical analysis was performed using Mann- 1051 Whitney test (D-E,K), mixed-effect model (F) and one-way ANOVA with post-hoc test 1052 analysis for multiple comparisons (C). Log-rank Mantel-Cox test to evaluate difference in 1053 survivals (J); p values are shown in the graphs and considered significant when p<0.05. 1054 All data are presented as mean ± SEM. Statistical analysis was performed using Mann- 1051 Whitney test (D-E,K), mixed-effect model (F) and one-way ANOVA with post-hoc test 1052 analysis for multiple comparisons (C). Log-rank Mantel-Cox test to evaluate difference in 1053 survivals (J); p values are shown in the graphs and considered significant when p<0.05. 1054 1055 Figure 5. Adenosine inhibition remodels the PDAC tumour microenvironment 1056 (A) Volcano plot related to 6419c5 allografts. Genes overexpressed in vehicle + isotype arm 1057 are on the left side (blue dots), and genes overexpressed in the anti-CD73 + AZD4635 arm are 1058 on the right side (Adoi, orange dots). 1059 (A) Volcano plot related to 6419c5 allografts. Genes overexpressed in vehicle + isotype arm 1057 are on the left side (blue dots), and genes overexpressed in the anti-CD73 + AZD4635 arm are 1058 on the right side (Adoi, orange dots). 1059 (B) Enrichment bar plot of significantly overexpressed pathways in the vehicle + isotype group 1060 (adenosine high), according to KEGG and GO Biological processes. 1061 (B) Enrichment bar plot of significantly overexpressed pathways in the vehicle + isotype group 1060 (adenosine high), according to KEGG and GO Biological processes. 1061 (C) Heatmap showing genes regulated during treatment (light grey for controls, dark grey for 1062 Adoi) which are part of the significantly different pathways according to KEGG. 1063 (C) Heatmap showing genes regulated during treatment (light grey for controls, dark grey for 1062 Adoi) which are part of the significantly different pathways according to KEGG. 1063 (D) Table (left) showing genes associated with innate immunity that are downregulated by 1064 Adoi treatment. Validation of RNAseq data (right graphs) through flow analysis of PD-L1 and 1065 CD206 expression (MFI ratio) on intra-tumoral live cells (8 mice in the control and 10 in the 1066 Adoi arms). The samples analysed for validation were from different mice from the ones used 1067 for RNAseq. 1068 (D) Table (left) showing genes associated with innate immunity that are downregulated by 1064 Adoi treatment. Validation of RNAseq data (right graphs) through flow analysis of PD-L1 and 1065 CD206 expression (MFI ratio) on intra-tumoral live cells (8 mice in the control and 10 in the 1066 Adoi arms). The samples analysed for validation were from different mice from the ones used 1067 for RNAseq. 1068 Figure 6. Immunosuppressive immune subpopulations are modulated following 1069 adenosine pathway blockade. 1070 45 45 (A) Representative flow cytometry plots showing tumour associated macrophages (TAM) 1071 infiltrating 6419c5 allografts following 14 day of treatment with vehicle + isotype (left panel) 1072 or anti-CD73 + AZD4635 (right panel). 1073 (A) Representative flow cytometry plots showing tumour associated macrophages (TAM) 1071 infiltrating 6419c5 allografts following 14 day of treatment with vehicle + isotype (left panel) 1072 or anti-CD73 + AZD4635 (right panel). Figure 5. Adenosine inhibition remodels the PDAC tumour microenvironment 1056 Statistical analysis was performed using 1088 Mann-Whitney test (B-H) and one-way ANOVA with post-hoc test analysis for multiple 1089 comparisons (E-H); p values are shown in the graphs when considered significant (p<0.05). 1090 1091 Figure 5. Adenosine inhibition remodels the PDAC tumour microenvironment 1056 1073 (A) Representative flow cytometry plots showing tumour associated macrophages (TAM) 1071 infiltrating 6419c5 allografts following 14 day of treatment with vehicle + isotype (left panel) 1072 or anti-CD73 + AZD4635 (right panel). 1073 (B) M2 macrophage allograft infiltration (left, number of cells/100 mg of tumour) and (right) 1074 percentage of M2 macrophages positive for PD-L1 (8 and 10 mice per group analysed). 1075 (B) M2 macrophage allograft infiltration (left, number of cells/100 mg of tumour) and (right) 1074 percentage of M2 macrophages positive for PD-L1 (8 and 10 mice per group analysed). 1075 (C-D) Representative IMC image of F4/80 and CD206 (C) and CD68 and CD206 (D) positive 1076 cells infiltrating a 6419c5 allograft merged (1st panel of C and D) or not with segmentation 1077 following Adoi (lower panels) or control (upper). The tissue segmentation of the IMC image 1078 was performed by Random Forest Classification using all markers analysed. The scale bar on 1079 the IMC image is 200 µm. Segmentation shows viable tumour (green), necrosis (yellow), 1080 necrotic margin (blue) and off-tissue (red). 1081 (E-F) The bar plots show cell density (number of cells per mm2) of F480+CD206+ cells (E) and 1082 CD68+CD206+ (F) per segment area (6 mice per treatment group). 1083 (E-F) The bar plots show cell density (number of cells per mm2) of F480+CD206+ cells (E) and 1082 CD68+CD206+ (F) per segment area (6 mice per treatment group). 1083 (G-H) Immunohistochemistry analysis showing 6419c5 tumour-infiltrating CD8+/Foxp3+ ratio 1084 (G) at day 14 of the following treatments: Vehicles + isotype (N=7), AZD6738 + gemcitabine 1085 (N=7), aCD73 + AZD4635 (N=6) and AZD6738 + gemcitabine + aCD73 + AZD4635 (N=7). 1086 (H) Representative IHC images of the latter. 1087 (G-H) Immunohistochemistry analysis showing 6419c5 tumour-infiltrating CD8+/Foxp3+ ratio 1084 (G) at day 14 of the following treatments: Vehicles + isotype (N=7), AZD6738 + gemcitabine 1085 (N=7), aCD73 + AZD4635 (N=6) and AZD6738 + gemcitabine + aCD73 + AZD4635 (N=7). 1086 (H) Representative IHC images of the latter. 1087 All data are represented as box and whisker plots. Statistical analysis was performed using 1088 Mann-Whitney test (B-H) and one-way ANOVA with post-hoc test analysis for multiple 1089 comparisons (E-H); p values are shown in the graphs when considered significant (p<0.05). 1090 1091 All data are represented as box and whisker plots. Figure 7. RNA gene expression demonstrates a crucial role for the adenosine pathway in 1092 Statistical analysis was performed using one-way 1107 ANOVA with post-hoc test analysis for multiple comparisons (A), two-tailed unpaired 1108 Student’s t-test (B) and log-rank Mantel-Cox test to evaluate difference in survivals (D-F); p 1109 values are shown in the graphs when considered significant (p<0.05). 1110 References 1112 Cancer Research UK, https://www.cancerresearchuk.org/health-professional/cancer- 1113 statistics/statistics-by-cancer-type/pancreatic-cancer, Accessed March 2022 1114 1115 1. Conroy T, Desseigne F, Ychou M, et al. "FOLFIRINOX versus gemcitabine for 1116 metastatic pancreatic cancer." N Engl J Med 2011 364(19): 1817-25. 1117 2. Le DT, Durham JN, Smith KN, et al. "Mismatch repair deficiency predicts response 1118 of solid tumors to PD-1 blockade." Science 2017 357(6349): 409-13. 1119 3. Hu ZI, Shia J, Stadler ZK, et al. "Evaluating Mismatch Repair Deficiency in 1120 Pancreatic Adenocarcinoma: Challenges and Recommendations." Clin Cancer 1121 Res 2018 24(6): 1326-36. 1122 4. Balachandran VP, Luksza M, Zhao JN, et al. "Identification of unique neoantigen 1123 qualities in long-term survivors of pancreatic cancer." Nature 2017 551(7681): 1124 512-16. 1125 Figure 7. RNA gene expression demonstrates a crucial role for the adenosine pathway in 1092 (A-B) Human ortholog genes with a 50% downregulation following 14 days of Adoi, were 1094 scored using z-score derived from Bailey’s43 subtypes dataset. Genes scores comparing Adex, 1095 (A-B) Human ortholog genes with a 50% downregulation following 14 days of Adoi, were 1094 scored using z-score derived from Bailey’s43 subtypes dataset. Genes scores comparing Adex, 1095 (A-B) Human ortholog genes with a 50% downregulation following 14 days of Adoi, were 1094 scored using z-score derived from Bailey’s43 subtypes dataset. Genes scores comparing Adex, 1095 46 immunogenic, squamous and pancreatic progenitor (A) or squamous vs non-squamous (B) are 1096 shown. Each dot represents a single patient. 1097 immunogenic, squamous and pancreatic progenitor (A) or squamous vs non-squamous (B) are 1096 shown. Each dot represents a single patient. 1097 (C) PDAC-specific gene signature of 52 genes used for analysis of the TCGA human PDAC 1098 dataset, related to the main pathways implied (immunity, hypoxia response and tumour 1099 stroma). 1100 (C) PDAC-specific gene signature of 52 genes used for analysis of the TCGA human PDAC 1098 dataset, related to the main pathways implied (immunity, hypoxia response and tumour 1099 stroma). 1100 (D-E) Gene signature applied to PDAC TCGA dataset (D). Kaplan-Meier curves show 1101 progression free survival (PFS, 176 patients) and (E) disease specific survival (DSS, 170 1102 patients). 1103 (D-E) Gene signature applied to PDAC TCGA dataset (D). Kaplan-Meier curves show 1101 progression free survival (PFS, 176 patients) and (E) disease specific survival (DSS, 170 1102 patients). 1103 (F) Gene signature validation applied to PDAC QCMG Bailey’s dataset. Kaplan-Meier curve 1104 shows overall survival (OS, 95 patients). Three genes (Pecam1, Trarg1 and Vegfd) were not 1105 assessed in the Bailey’s dataset, thus the signature is composed of 49 genes. 1106 (F) Gene signature validation applied to PDAC QCMG Bailey’s dataset. Kaplan-Meier curve 1104 shows overall survival (OS, 95 patients). Three genes (Pecam1, Trarg1 and Vegfd) were not 1105 assessed in the Bailey’s dataset, thus the signature is composed of 49 genes. 1106 Data in A-B are presented as mean ± SEM. Statistical analysis was performed using one-way 1107 ANOVA with post-hoc test analysis for multiple comparisons (A), two-tailed unpaired 1108 Student’s t-test (B) and log-rank Mantel-Cox test to evaluate difference in survivals (D-F); p 1109 values are shown in the graphs when considered significant (p<0.05). 1110 Data in A-B are presented as mean ± SEM. Cancer Research UK, https://www.cancerresearchuk.org/health-professional/cancer- 1113 statistics/statistics-by-cancer-type/pancreatic-cancer, Accessed March 2022 1114 Allard D 1132 ther 1133 9. Augustin 1134 ade 1135 2022 1136 10. Cekic C 1137 2016 1138 11. Goodw 1139 for a 1140 Bioc 1141 12. Duhen 1142 tumo 1143 2724 1144 13. Simoni 1145 phe 1146 575 1147 14. Ott M, 1148 reve 1149 resto 1150 15. Takena 1151 mac 1152 2019 1153 16. Goswa 1154 iden 1155 39-4 1156 17. Sidder 1157 Can 1158 Clin 1159 18. Cekic C 1160 supp 1161 Can 1162 19. Sorrent 1163 to A 1164 mou 1165 20. Li L, Hu 1166 atte 1167 21. Borodo 1168 A2A 1169 enha 1170 22. Wilson 1171 Th1 1172 186 1173 6. Antonioli L, Blandizzi C, Pacher P, et al. "Immunity, inflammation and cancer: a 1128 leading role for adenosine." Nat Rev Cancer 2013 13(12): 842-57. 1129 7. Allard B, Allard D, Buisseret L, et al. "The adenosine pathway in immuno-oncology." 1130 Nat Rev Clin Oncol 2020 17(10): 611-29. 1131 8. Allard D, Allard B, Stagg J. "On the mechanism of anti-CD39 immune checkpoint 1132 therapy." J Immunother Cancer 2020 8(1). 1133 9. Augustin RC, Leone RD, Naing A, et al. "Next steps for clinical translation of 134 adenosine pathway inhibition in cancer immunotherapy." J Immunother Cancer 135 2022 10(2). 136 10. Cekic C, Linden J. "Purinergic regulation of the immune system." Nat Rev Immunol 2016 16(3): 177-92. 11. Goodwin KJ, Gangl E, Sarkar U, et al. "Development of a quantification method for adenosine in tumors by LC-MS/MS with dansyl chloride derivatization." Anal Biochem 2019 568: 78-88. 12. Duhen T, Duhen R, Montler R, et al. "Co-expression of CD39 and CD103 identifies tumor-reactive CD8 T cells in human solid tumors." Nat Commun 2018 9(1): 2724. 13. Simoni Y, Becht E, Fehlings M, et al. "Bystander CD8(+) T cells are abundant and phenotypically distinct in human tumour infiltrates." Nature 2018 557(7706): 575-79. 14. Ott M, Tomaszowski KH, Marisetty A, et al. "Profiling of patients with glioma reveals the dominant immunosuppressive axis is refractory to immune function restoration." JCI Insight 2020 5(17). g ( ) 15. Takenaka MC, Gabriely G, Rothhammer V, et al. "Control of tumor-associated macrophages and T cells in glioblastoma via AHR and CD39." Nat Neurosci 2019 22(5): 729-40. 16. Goswami S, Walle T, Cornish AE, et al. "Immune profiling of human tumors identifies CD73 as a combinatorial target in glioblastoma." Nat Med 2020 26(1): 39-46. 17. Cancer Research UK, https://www.cancerresearchuk.org/health-professional/cancer- 1113 statistics/statistics-by-cancer-type/pancreatic-cancer, Accessed March 2022 1114 1. Conroy T, Desseigne F, Ychou M, et al. "FOLFIRINOX versus gemcitabine for 1116 metastatic pancreatic cancer." N Engl J Med 2011 364(19): 1817-25. 1117 1. Conroy T, Desseigne F, Ychou M, et al. "FOLFIRINOX versus gemcitabine for 1116 metastatic pancreatic cancer." N Engl J Med 2011 364(19): 1817-25. 1117 2. Le DT, Durham JN, Smith KN, et al. "Mismatch repair deficiency predicts response 1118 of solid tumors to PD-1 blockade." Science 2017 357(6349): 409-13. 1119 2. Le DT, Durham JN, Smith KN, et al. "Mismatch repair deficiency predicts response 1118 of solid tumors to PD-1 blockade." Science 2017 357(6349): 409-13. 1119 ( ) 3. Hu ZI, Shia J, Stadler ZK, et al. "Evaluating Mismatch Repair Deficiency in 1120 Pancreatic Adenocarcinoma: Challenges and Recommendations." Clin Cancer 1121 Res 2018 24(6): 1326-36. 1122 3. Hu ZI, Shia J, Stadler ZK, et al. "Evaluating Mismatch Repair Deficiency in 1120 Pancreatic Adenocarcinoma: Challenges and Recommendations." Clin Cancer 1121 Res 2018 24(6): 1326-36. 1122 ( ) 4. Balachandran VP, Luksza M, Zhao JN, et al. "Identification of unique neoantigen 1123 qualities in long-term survivors of pancreatic cancer." Nature 2017 551(7681): 1124 512-16. 1125 4. Balachandran VP, Luksza M, Zhao JN, et al. "Identification of unique neoantigen 1123 qualities in long-term survivors of pancreatic cancer." Nature 2017 551(7681): 1124 512-16. 1125 47 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 5. Ho 1126 1127 6. An 1128 1129 7. Al 1130 1131 8. Al 1132 1133 9. A 1134 1135 1136 10. C 1137 1138 11. G 1139 1140 1141 12. D 1142 1143 1144 13. S 1145 1146 1147 14. O 1148 1149 1150 15. T 1151 1152 1153 16. G 1154 1155 1156 17. S 1157 1158 1159 18. C 1160 1161 1162 19. S 1163 1164 1165 20. L 1166 1167 21. B 1168 1169 1170 22. W 1171 1172 1173 5. Ho WJ, Jaffee EM, Zheng L. "The tumour microenvironment in pancreatic cancer - 1126 clinical challenges and opportunities." Nat Rev Clin Oncol 2020 17(9): 527-40. 1127 5. Ho WJ, J 1126 clini 1127 6. Antoniol 1128 lead 1129 7. Allard B, 1130 Nat 1131 8. Cancer Research UK, https://www.cancerresearchuk.org/health-professional/cancer- 1113 statistics/statistics-by-cancer-type/pancreatic-cancer, Accessed March 2022 1114 1174 1175 1176 24. C 1177 1178 25. I 1179 1180 1181 26. S 1182 1183 1184 27. Z 1185 1186 1187 28. 1188 1189 1190 29. Z 1191 1192 1193 30. Z 1194 1195 31. 1196 1197 1198 32. 1199 1200 1201 33. D 1202 1203 1204 34. 1205 1206 1207 1208 35. J 1209 1210 1211 36. 1212 1213 1214 37. L 1215 1216 1217 38. 1218 1219 1220 39. 1221 1222 y y ( ) 24. Cekic C, Linden J. "Adenosine A2A receptors intrinsically regulate CD8+ T cells in the tumor microenvironment." Cancer Res 2014 74(24): 7239-49. 25. Ino Y, Yamazaki-Itoh R, Shimada K, et al. "Immune cell infiltration as an indicator of the immune microenvironment of pancreatic cancer." Br J Cancer 2013 108(4): 914-23. 26. Steele NG, Carpenter ES, Kemp SB, et al. "Multimodal Mapping of the Tumor and Peripheral Blood Immune Landscape in Human Pancreatic Cancer." Nat Cancer 2020 1(11): 1097-112. ( ) 27. Zhang Y, Velez-Delgado A, Mathew E, et al. "Myeloid cells are required for PD- 1/PD-L1 checkpoint activation and the establishment of an immunosuppressive environment in pancreatic cancer." Gut 2017 66(1): 124-36. 28. Raghavan S, Winter PS, Navia AW, et al. "Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer." Cell 2021 184(25): 6119- 37 e26. 29. Zhu Y, Herndon JM, Sojka DK, et al. "Tissue-Resident Macrophages in Pancreatic Ductal Adenocarcinoma Originate from Embryonic Hematopoiesis and Promote Tumor Progression." Immunity 2017 47(3): 597. g y ( ) 30. Zhang L, Li Z, Skrzypczynska KM, et al. "Single-Cell Analyses Inform Mechanisms of Myeloid-Targeted Therapies in Colon Cancer." Cell 2020 181(2): 442-59 e29. 31. Beatty GL, Winograd R, Evans RA, et al. "Exclusion of T Cells From Pancreatic Carcinomas in Mice Is Regulated by Ly6C(low) F4/80(+) Extratumoral Macrophages." Gastroenterology 2015 149(1): 201-10. p g gy ( ) 32. Ruffell B, Chang-Strachan D, Chan V, et al. "Macrophage IL-10 blocks CD8+ T cell-dependent responses to chemotherapy by suppressing IL-12 expression in intratumoral dendritic cells." Cancer Cell 2014 26(5): 623-37. 33. Daley D, Mani VR, Mohan N, et al. "NLRP3 signaling drives macrophage-induced adaptive immune suppression in pancreatic carcinoma." J Exp Med 2017 214(6): 1711-24. ( ) 34. Candido JB, Morton JP, Bailey P, et al. "CSF1R(+) Macrophages Sustain Pancreatic Tumor Growth through T Cell Suppression and Maintenance of Key Gene Programs that Define the Squamous Subtype." Cell Rep 2018 23(5): 1448-60. 35. Cancer Research UK, https://www.cancerresearchuk.org/health-professional/cancer- 1113 statistics/statistics-by-cancer-type/pancreatic-cancer, Accessed March 2022 1114 Sidders B, Zhang P, Goodwin K, et al. "Adenosine Signaling Is Prognostic for Cancer Outcome and Has Predictive Utility for Immunotherapeutic Response." Clin Cancer Res 2020 26(9): 2176-87. 18. Cekic C, Day YJ, Sag D, et al. "Myeloid expression of adenosine A2A receptor suppresses T and NK cell responses in the solid tumor microenvironment." Cancer Res 2014 74(24): 7250-9. 19. Sorrentino C, Miele L, Porta A, et al. "Myeloid-derived suppressor cells contribute to A2B adenosine receptor-induced VEGF production and angiogenesis in a mouse melanoma model." Oncotarget 2015 6(29): 27478-89. 20. Li L, Huang L, Ye H, et al. "Dendritic cells tolerized with adenosine A(2)AR agonist attenuate acute kidney injury." J Clin Invest 2012 122(11): 3931-42. 21. Borodovsky A, Barbon CM, Wang Y, et al. "Small molecule AZD4635 inhibitor of A2AR signaling rescues immune cell function including CD103(+) dendritic cells enhancing anti-tumor immunity." J Immunother Cancer 2020 8(2). 22. Wilson JM, Kurtz CC, Black SG, et al. "The A2B adenosine receptor promotes 1171 Th17 differentiation via stimulation of dendritic cell IL-6." J Immunol 2011 1172 186(12): 6746-52. 1173 48 1174 1175 1176 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222 23. Romio M, Reinbeck B, Bongardt S, et al. "Extracellular purine metabolism and signaling of CD73-derived adenosine in murine Treg and Teff cells." Am J Physiol Cell Physiol 2011 301(2): C530-9. 23. Romio M 1174 signal 1175 Physi 1176 24. Cekic C, 1177 the tu 1178 25. Ino Y, Ya 1179 of the 1180 108(4 1181 26. Steele N 1182 Periph 1183 Cance 1184 27. Zhang Y 1185 1/PD- 1186 enviro 1187 28. Raghava 1188 plastic 1189 37 e2 1190 29. Zhu Y, H 1191 Ducta 1192 Promo 1193 30. Zhang L, 1194 of Mye 1195 31. Beatty G 1196 Carcin 1197 Macro 1198 32. Ruffell B 1199 cell-de 1200 intratu 1201 33. Daley D, 1202 adapt 1203 214(6 1204 34. Candido 1205 Pancr 1206 Gene 1207 1448- 1208 35. Jacoberg 1209 and C 1210 Res 2 1211 36. King RJ 1212 suppr 1213 Oncog 1214 37. Li J, Byrn 1215 of Imm 1216 49(1): 1217 38. Young A 1218 Adeno 1219 2016 1220 39. Dannhor 1221 Multim 1222 23. Cancer Research UK, https://www.cancerresearchuk.org/health-professional/cancer- 1113 statistics/statistics-by-cancer-type/pancreatic-cancer, Accessed March 2022 1114 Jacoberger-Foissac C, Cousineau I, Bareche Y, et al. "CD73 Inhibits cGAS-STING and Cooperates with CD39 to Promote Pancreatic Cancer." Cancer Immunol Res 2023 11(1): 56-71. 36. King RJ, Shukla SK, He C, et al. "CD73 induces GM-CSF/MDSC-mediated suppression of T cells to accelerate pancreatic cancer pathogenesis." Oncogene 2022 41(7): 971-82. g ( ) 37. Li J, Byrne KT, Yan F, et al. "Tumor Cell-Intrinsic Factors Underlie Heterogeneity of Immune Cell Infiltration and Response to Immunotherapy." Immunity 2018 49(1): 178-93 e7. 38. Young A, Ngiow SF, Barkauskas DS, et al. "Co-inhibition of CD73 and A2AR Adenosine Signaling Improves Anti-tumor Immune Responses." Cancer Cell 2016 30(3): 391-403. 39. Dannhorn A, Kazanc E, Ling S, et al. "Universal Sample Preparation Unlocking Multimodal Molecular Tissue Imaging." Anal Chem 2020 92(16): 11080-88. 49 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232 1233 1234 1235 1236 1237 1238 1239 1240 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 1251 1252 1253 1254 1255 1256 1257 1258 1259 1260 1261 1262 1263 1264 1265 1266 1267 1268 1269 1270 1271 1272 40. Adusumilli R, Mallick P. "Data Conversion with ProteoWizard msConvert." Methods Mol Biol 2017 1550: 339-68. 40. 1223 1224 41. R 1225 1226 42. D 1227 1228 1229 43. 1230 1231 44. N 1232 1233 45. L 1234 1235 1236 46. Z 1237 1238 47. 1239 1240 1241 1242 48. M 1243 1244 1245 1246 49. Y 1247 1248 50. 1249 1250 1251 51. S 1252 1253 1254 52. P 1255 1256 1257 53. R 1258 1259 1260 54. M 1261 1262 55. O 1263 1264 1265 1266 56. 1267 1268 1269 57. B 1270 41. Race AM, Styles IB, Bunch J. "Inclusive sharing of mass spectrometry imaging data requires a converter for all." J Proteomics 2012 75(16): 5111-12. 42. Dunlop CR, Wallez Y, Johnson TI, et al. "Complete loss of ATM function augments replication catastrophe induced by ATR inhibition and gemcitabine in pancreatic cancer models." Br J Cancer 2020 123(9): 1424-36. p ( ) 43. Bailey P, Chang DK, Nones K, et al. "Genomic analyses identify molecular subtypes of pancreatic cancer." Nature 2016 531(7592): 47-52. 44. Nagy A, Munkacsy G, Gyorffy B. "Pancancer survival analysis of cancer hallmark genes." Sci Rep 2021 11(1): 6047. g p ( ) 45. Liu J, Lichtenberg T, Hoadley KA, et al. Cancer Research UK, https://www.cancerresearchuk.org/health-professional/cancer- 1113 statistics/statistics-by-cancer-type/pancreatic-cancer, Accessed March 2022 1114 "An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics." Cell 2018 173(2): 400-16 e11. ( ) 46. Zhou L, Jia S, Chen Y, et al. "The distinct role of CD73 in the progression of pancreatic cancer." J Mol Med (Berl) 2019 97(6): 803-15. p 47. Overman MJ, LoRusso P, Strickler JH, et al. "Safety, efficacy and pharmacodynamics (PD) of MEDI9447 (oleclumab) alone or in combination with durvalumab in advanced colorectal cancer (CRC) or pancreatic cancer (panc)." Journal of Clinical Oncology 2018 36(15_suppl): 4123-23. (p ) gy ( pp ) 48. Manji GA, Wainberg ZA, Krishnan K, et al. "ARC-8: Phase I/Ib study to evaluate safety and tolerability of AB680 + chemotherapy + zimberelimab (AB122) in patients with treatment-naive metastatic pancreatic adenocarcinoma (mPDAC)." Journal of Clinical Oncology 2021 39(3_suppl): 404-04. 49. Yan J, Li XY, Roman Aguilera A, et al. "Control of Metastases via Myeloid CD39 and NK Cell Effector Function." Cancer Immunol Res 2020 8(3): 356-67. 50. Sun X, Wu Y, Gao W, et al. "CD39/ENTPD1 expression by CD4+Foxp3+ regulatory T cells promotes hepatic metastatic tumor growth in mice." Gastroenterology 2010 139(3): 1030-40. gy ( ) 51. Synnestvedt K, Furuta GT, Comerford KM, et al. "Ecto-5'-nucleotidase (CD73) regulation by hypoxia-inducible factor-1 mediates permeability changes in intestinal epithelia." J Clin Invest 2002 110(7): 993-1002. p ( ) 52. Philip K, Mills TW, Davies J, et al. "HIF1A up-regulates the ADORA2B receptor on alternatively activated macrophages and contributes to pulmonary fibrosis." FASEB J 2017 31(11): 4745-58. 53. Rahib L, Smith BD, Aizenberg R, et al. "Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States." Cancer Res 2014 74(11): 2913-21. ( ) 54. Mellman I, Coukos G, Dranoff G. "Cancer immunotherapy comes of age." Nature 2011 480(7378): 480-9. 55. O'Hara MH, O'Reilly EM, Varadhachary G, et al. "CD40 agonistic monoclonal antibody APX005M (sotigalimab) and chemotherapy, with or without nivolumab, for the treatment of metastatic pancreatic adenocarcinoma: an open-label, multicentre, phase 1b study." Lancet Oncol 2021 22(1): 118-31. 56. Biasci D, Smoragiewicz M, Connell CM, et al. "CXCR4 inhibition in human pancreatic and colorectal cancers induces an integrated immune response." Proc Natl Acad Sci U S A 2020 117(46): 28960-70. 57. Bockorny B, Semenisty V, Macarulla T, et al. 1227 58. Fong L, Hotson A, Powderly JD, et al. "Adenosine 2A Receptor Blockade as an 1273 Immunotherapy for Treatment-Refractory Renal Cell Cancer." Cancer Discov 1274 2020 10(1): 40-53. 1275 ( ) 59. Hiraoka N, Ino Y, Sekine S, et al. "Tumour necrosis is a postoperative prognostic 1276 marker for pancreatic cancer patients with a high interobserver reproducibility 1277 in histological evaluation." Br J Cancer 2010 103(7): 1057-65. 1278 Cancer Research UK, https://www.cancerresearchuk.org/health-professional/cancer- 1113 statistics/statistics-by-cancer-type/pancreatic-cancer, Accessed March 2022 1114 "BL-8040, a CXCR4 antagonist, in 1270 combination with pembrolizumab and chemotherapy for pancreatic cancer: the 1271 COMBAT trial." Nat Med 2020 26(6): 878-85. 1272 50 58. Fong L, Hotson A, Powderly JD, et al. "Adenosine 2A Receptor Blockade as an 1273 Immunotherapy for Treatment-Refractory Renal Cell Cancer." Cancer Discov 1274 2020 10(1): 40-53. 1275 59. Hiraoka N, Ino Y, Sekine S, et al. "Tumour necrosis is a postoperative prognostic 1276 marker for pancreatic cancer patients with a high interobserver reproducibility 1277 in histological evaluation." Br J Cancer 2010 103(7): 1057-65. 1278 1279 58. Fong L, Hotson A, Powderly JD, et al. "Adenosine 2A Receptor Blockade as an 1273 Immunotherapy for Treatment-Refractory Renal Cell Cancer." Cancer Discov 1274 2020 10(1): 40-53. 1275 59. Hiraoka N, Ino Y, Sekine S, et al. "Tumour necrosis is a postoperative prognostic 1276 marker for pancreatic cancer patients with a high interobserver reproducibility 1277 in histological evaluation." Br J Cancer 2010 103(7): 1057-65. 1278 51
https://openalex.org/W3184021924	https://www.frontiersin.org/articles/10.3389/fpls.2021.722596/pdf	English	null	EgmiR5179 Regulates Lipid Metabolism by Targeting EgMADS16 in the Mesocarp of Oil Palm (Elaeis guineensis)	Frontiers in plant science	2,021	cc-by	8,295	EgmiR5179 Regulates Lipid Metabolism by Targeting EgMADS16 in the Mesocarp of Oil Palm (Elaeis guineensis) Yifei Wang1†, Jixin Zou1,2†, Jin Zhao1, Yusheng Zheng1* and Dongdong Li1* 1College of Tropical Crops, Hainan University, Haikou, China, 2Rubber Research Institute of Chinese Academy of Tropical Agricultural Sciences (CATAS), Haikou, China 1College of Tropical Crops, Hainan University, Haikou, China, 2Rubber Research Institute of Chinese Academy of Tropical Agricultural Sciences (CATAS), Haikou, China EgMADS16, one of the MADS-box transcription factors in oil palm, has a high expression level in the late fruit development of the oil palm fruit mesocarp. At the same time, it is also predicted to be the target gene of EgmiR5179, which has been identified in previous research. In this paper, we focused on the function and regulatory mechanism of the EgMADS16 gene in oil palm lipid metabolism. The results indicated that the transcription level of EgMADS16 was highest in the fourth stage, and a dual-luciferase reporter assay proved that the EgMADS16 expression level was downregulated by EgmiR5179. In both the OXEgMADS16 Arabidopsis seeds and oil palm embryonic calli, the total lipid contents were significantly decreased, but the contents of C18:0 and C18:3 in OXEgMADS16 lines were significantly increased. As expected, EgmiR5179 weakened the inhibitory effect of EgMADS16 on the oil contents in transgenic Arabidopsis plants that coexpressed EgmiR5179 and EgMADS16 (OXEgmiR5179-EgMADS16). Moreover, yeast two-hybrid and BiFC analyses suggested that there was an interaction between the EgMADS16 protein and EgGLO1 protein, which had been proven to be capable of regulating fatty acid synthesis in our previous research work. In summary, a model of the molecular mechanism by which miRNA5179 targets EgMADS16 to regulate oil biosynthesis was hypothesized, and the research results provide new insight into lipid accumulation and molecular regulation in oil palm. Edited by: María Serrano, Miguel Hernández University of Elche, Spain Reviewed by: Hadi Pirasteh-Anosheh, Agricultural Research Education and Extention Organization, Iran Benjamin Lau, Malaysian Palm Oil Board, Malaysia Correspondence: Yusheng Zheng yusheng.zheng@hainanu.edu.cn Dongdong Li lidd@hainanu.edu.cn †These authors have contributed equally to this work Reviewed by: Hadi Pirasteh-Anosheh, Agricultural Research Education and Extention Organization, Iran Benjamin Lau, Malaysian Palm Oil Board, Malaysia Reviewed by: Hadi Pirasteh-Anosheh, Agricultural Research Education and Extention Organization, Iran Benjamin Lau, Malaysian Palm Oil Board, Malaysia Correspondence: Yusheng Zheng yusheng.zheng@hainanu.edu.cn Dongdong Li lidd@hainanu.edu.cn †These authors have contributed equally to this work Correspondence: Yusheng Zheng yusheng.zheng@hainanu.edu.cn Dongdong Li lidd@hainanu.edu.cn †These authors have contributed equally to this work Specialty section: This article was submitted to Crop and Product Physiology, a section of the journal Frontiers in Plant Science Specialty section: This article was submitted to Crop and Product Physiology, a section of the journal Frontiers in Plant Science INTRODUCTION Received: 09 June 2021 Accepted: 07 July 2021 Published: 26 July 2021 Oil palm (Elaeis guineensis Jacq.), which belongs to the Arecaceae family, is the most productive oil crop in the world and can accumulate up to 90% oil in the mesocarp (Bhagya et al., 2020). At present, the main oil crops that produce vegetable oils are oil palm, soybean, rape, and sunflower. They produce 79% of the total oil yields (Dyer et al., 2008). The palm oil produced by oil palm accounts for 36% of the total oil yields (Osorio-Guarin et al., 2019). Although much progress has been made on plant lipid metabolism and regulatory mechanisms via plant molecular biology research, it is still very difficult to obtain the ideal palm oil with the highest nutritional value or the largest yield. Presently, there are also few reports about Oil palm (Elaeis guineensis Jacq.), which belongs to the Arecaceae family, is the most productive oil crop in the world and can accumulate up to 90% oil in the mesocarp (Bhagya et al., 2020). At present, the main oil crops that produce vegetable oils are oil palm, soybean, rape, and sunflower. They produce 79% of the total oil yields (Dyer et al., 2008). The palm oil produced by oil palm accounts for 36% of the total oil yields (Osorio-Guarin et al., 2019). Although much progress has been made on plant lipid metabolism and regulatory mechanisms via plant molecular biology research, it is still very difficult to obtain the ideal palm oil with the highest nutritional value or the largest yield. Presently, there are also few reports about Keywords: oil palm, MADS-box gene, micorRNA5179, lipid content, fatty acid ORIGINAL RESEARCH published: 26 July 2021 doi: 10.3389/fpls.2021.722596 RNA Extraction and Real-Time PCR Analysis y Total RNA of oil palm fruit mesocarps (0.5 g), Arabidopsis leaves (0.1 g), and oil palm embryoids (0.2 g) was extracted by an RNAprep Pure Plant Kit (Polysaccharides and Polyphenolics-rich; Tiangen, Beijing, China). Protoplastic RNA was isolated using TRIzol Reagent (Invitrogen, United States). cDNA was synthesized using the FastQuant RT kit (with gDNase; Tiangen, Beijing, China), and quantitative real-time PCR (qPCR) was performed with TB GreenTM Premix Ex TaqTM II (Tli RNaseH Plus; TaKaRa, Japan) on a CFX96 Touch System (Bio-Rad, United States). Each sample was set to three replicates, and the internal control for the oil palm sample was β-Actine, while that for the Arabidopsis sample was Actin7. In addition, all experimental steps were provided by the manufacturer, and the related primers designed by Primer Premier 5 are shown in Supplementary Table 1. In our previous research, overexpressing EgmiR5179 significantly increased the oil yield in Arabidopsis seeds, and one MADS-box transcription factor (EgMADS16) was predicted to be the target gene of EgmiR5179 (Gao et al., 2019). In this study, we cloned full-length EgMADS16 from the mesocarp of oil palm. Transgenic Arabidopsis plants and oil palm embryoids overexpressing EgMADS16 were obtained, and the contents of oil and fatty acids were tested. Finally, transgenic Arabidopsis overexpressing EgmiR5179 and EgMADS16 was obtained, and lipid and fatty acid contents were detected to confirm the relationship between EgMADS16, EgmiR5179, and oil biosynthesis. The results depicted one pathway by which miRNAs target transcription factors and ultimately regulate lipid metabolism, providing a new strategy for lipid metabolism research in oil palm. Gene Cloning and Vector Construction The vector pCAMBIA3301 was used for plant transformation. pGreen II 62-SK (SK) was used for protoplast transfection and the dual-luciferase reporter assay. pCAMBIA1300S containing the green fluorescent protein (GFP) gene was used for subcellular localization. The pHiS2.1, pGADT7, and pGBKT7 vectors were used for the yeast hybrid assay, and the pSPYNE and pSPYCE vectors were used for BiFC analysis. The CDS of EgMADS16 was cloned using different primers and ligated into pGreen II 0800-miRNA (LUC), pGADT7, and pGBKT7 using a One Step Cloning Kit (Vazyme) according to the principle of homologous recombination. The CDS of EgMADS16 without the final TGA was cloned into pCAMBIA1300S and pSPYNE. Likewise, the CDS of EgGLO1 without the final TGA was cloned into pSPYCE vectors. Citation: Wang Y, Zou J, Zhao J, Zheng Y and Li D (2021) EgmiR5179 Regulates Lipid Metabolism by Targeting EgMADS16 in the Mesocarp of Oil Palm (Elaeis guineensis). Front. Plant Sci. 12:722596. doi: 10.3389/fpls.2021.722596 July 2021 \| Volume 12 \| Article 722596 Frontiers in Plant Science \| www.frontiersin.org EgMADS16 Regulates Lipid Metabolism Wang et al. the genes involved in the regulation of oil metabolism and related transcription factor regulation networks in oil palm (Li et al., 2020). PR China. These fruits were divided into phase 1 [30–60 days after pollination (DAP)], phase 2 (60–100 DAP), phase 3 (100–120 DAP), phase 4 (120–140 DAP), and phase 5 (140–160 DAP) according to the developmental stage (Tranbarger et al., 2011) and stored at −80°C until the next experiment. Three independent bunches were collected from three distinct individuals which at the similar stage. Arabidopsis thaliana plants were grown in a 23°C incubator with 16 h light/8 h dark cycles. In addition, oil palm embryoids were induced and cultured using the method in previous research (Zou et al., 2019). All strains, including DH5α (E. coli), Y187 and Y2HGold (yeast), and GV3101 (Agrobacterium), were maintained by our laboratory. In plant seeds, lipids are the main form of carbon storage, constituting up to 60% of the dry seed weight (Ohlroggeav and Browse, 1995). The biosynthesis of vegetable oil is affected by many factors, including transcription factors, microRNAs (miRNAs), plant hormones, signaling molecules, and environmental factors. Several transcription factors have been found to participate in the regulation of oil biosynthesis. For example, ZmWRI1, which belongs to the AP2/EREBP family, could regulate FA biosynthesis and increase seed oil by up to 46% in maize seeds overexpressing ZmWRI1 without affecting the germination, seedling growth, and grain yield (Shen et al., 2010). GmMYB73, which belongs to the MYB family, and GmbZIP123, which belongs to the bZIP family, could enhance lipid contents in both the seeds and leaves of transgenic Arabidopsis plants (Song et al., 2013; Liu et al., 2014). In oil palm, EgMADS21 regulates EgDGAT2 expression and ultimately affects fatty acid accumulation in the mesocarp (Li et al., 2020). In addition, EgWRI1-1 participated in the regulation of oil biosynthesis by interacting directly with the EgNF-YA3 protein. EgWRKY40 interacted with EgWRKY2 to inhibit the transcription of oil biosynthesis-related genes (Yeap et al., 2017). However, little is known about the molecular mechanism of lipid accumulation in the mesocarp of oil palm. RNA Extraction and Real-Time PCR Analysis For the EgMADS16-p3301 vector, we ligated the CDS of EgMADS16 into the pCAMBIA1300S vector, cut the 35S::EgMADS16::NOS terminator, and inserted the terminator into the multiple cloning site of the pCAMBIA3301 vector using a restriction enzyme. The plasmids about EgmiR5179 were constructed and conserved in our laboratory (Gao et al., 2019). All the primers used for the vector construction are shown in Supplementary Table 2. Abbreviations: AP2, APETALA2; AS, acetosyringone; BiFC, bimolecular fluorescence complementation; BR, biological reagent; CDSs, coding region sequences; CoA, coenzyme A; DAP, days after pollination; DAPI, 4', 6-diamidino-2-phenylindole; DGAT, diacylglycerol acyltransferase; FA, fatty acid; FAD, fatty acid dehydrogenase; FAME, fatty acid methyl ester; GC, gas chromatography; GFP, green fluorescent protein; LACS, long-chain acyl-CoA synthetase; MS medium, Murashige and Skoog medium; OD, optical density; OX, over-expressed; PEG, polyethylene glycol; qPCR, quantitative real-time PCR; SAD, stearoyl-ACP desaturase; YFP, yellow fluorescent protein. Abbreviations: AP2, APETALA2; AS, acetosyringone; BiFC, bimolecular fluorescence complementation; BR, biological reagent; CDSs, coding region sequences; CoA, coenzyme A; DAP, days after pollination; DAPI, 4', 6-diamidino-2-phenylindole; DGAT, diacylglycerol acyltransferase; FA, fatty acid; FAD, fatty acid dehydrogenase; FAME, fatty acid methyl ester; GC, gas chromatography; GFP, green fluorescent protein; LACS, long-chain acyl-CoA synthetase; MS medium, Murashige and Skoog medium; OD, optical density; OX, over-expressed; PEG, polyethylene glycol; qPCR, quantitative real-time PCR; SAD, stearoyl-ACP desaturase; YFP, yellow fluorescent protein. Subcellular Localization in Nicotiana benthamianah oil palm embryoids for 15 min with an OD600 of 0.5. Then, these embryoids were cultured on cocultivation medium (woody plant medium supplemented with 100 mg/L cysteine and 100 μm AS) at 19°C for 2 days and on screening medium (woody plant medium supplemented with 400 mg/L timentin and 60 mg/L glufosinate ammonium) at 28°C for 4 months, and the medium was regenerated every 20 days. The subcellular localization of EgMADS16 protein was performed in Nicotiana benthamiana leaves according to previous research (Jessen et al., 2015). Agrobacterium tumefaciens GV3101 strains harboring EgMADS16-p1300SGFP plasmids, which encode the MADS16-EGFP fusion protein, were incubated to an OD 600 of 0.6; after centrifugation (4,000 rpm, 10 min), they were resuspended in the equal volume buffer (0.01 M MgCl2, 0.01 M MES, PH5.5, and 150 μm AS) and infiltrated into the leaves of Nicotiana benthamiana. After incubation for 36–72 h, the GFP signals in the lower epidermis of these leaves were observed using a fluorescence inverted microscope (Nikon, TS2-LS) with an excitation wavelength of 430–510 nm. At the same time, nuclei were stained with 4', 6-diamidino-2-phenylindole (Sigma- Aldrich, United States) and observed using excitation wavelengths of 330–380 nm. Bimolecular Fluorescence Complementation Analysis p y EgMADS16-pSPYNE and EgGLO1-pSPYCE were transformed into Agrobacterium strains GV3101, respectively. And then these strains were coinfiltrated into the leaves of N. benthamiana using the same method as subcellular localization. Moreover, after incubation for 36–72 h, the yellow fluorescent protein (YFP) signal was observed using the excitation wavelength of 430–510 nm. Plant Materials and Strains Oil palm (Elaeis guineensis Jacq.) fruits were collected at the Chinese Academy of Tropical Agricultural Sciences in Hainan, July 2021 \| Volume 12 \| Article 722596 Frontiers in Plant Science \| www.frontiersin.org 2 EgMADS16 Regulates Lipid Metabolism Wang et al. Total Lipid Extraction and Fatty Acid Analysis of the Arabidopsis Plants and Oil Palm Embryoids y Both the lipid and fatty acid analyses of Arabidopsis plants and oil palm embryoids were conducted according to previous studies (Yuan et al., 2017). In brief, 5 ml chloroform-methanol (volume ratio 2:1) was used to extract lipids, and then, lipids were dried by a Termovap sample concentrator. In addition, 10 μg C17:0 was added to the lipid samples as an internal standard. All samples were methylated by 3 ml concentrated sulfuric acid-methanol (volume ratio 1:40) at 80°C for 2 h. Then, 3 ml N-hexane and 2 ml 0.9% (W/V) sodium chloride solution were added. After centrifuging at 4,000 rpm for 5 min, the supernatant was transferred to a new tube and dried by a Termovap sample concentrator. The fatty acid methyl ester was finally dissolved in 1 ml n-hexane for GC analysis. The GC analysis was performed by the Analytical and Testing Center of Hainan University. Detailed operation parameters: the oven temperature was initially maintained at 150°C for 1 min, then increased at 8°C/min to 250°C, and then increased to 250°C and maintained for 5 min. The split ratio was 1:30, and the carrier gas was helium at a flow rate of 1.0 ml/min in constant flow mode. The injector was at 250°C, and the detector, at 230°C. And the lipid mass was calculated using the internal standard method. Arabidopsis thaliana Transformation A. thaliana was cultured in 16 h light/8 h dark at 23°C. EgMADS16-p3301 plasmids were transformed into GV3101 Agrobacterium and then introduced into A. thaliana using the floral dip method (Jin et al., 2017). Moreover, transformants were selected by 1/2 Murashige and Skoog medium containing 60 mg/L glufosinate ammonium. Dual-Luciferase Reporter Assayh The 10 μg EgMADS16-LUC plasmids were transformed into 200 μl oil palm protoplasts (5 × 105/ml) with 10 μg EgmiR5179-SK or SK plasmids; each sample was set to three replicates. After incubating for 14–18 h, the firefly and Renilla luciferase activities were tested using a dual-luciferase reporter gene assay kit (Promega, United States). At the same time, EgMADS16-LUC was transformed into wild-type or OXEgmiR5179 Arabidopsis protoplasts, and the dual-luciferase activities were analyzed using the same method. Protoplast Isolation and Transformationh The protoplast isolation and transfection of Arabidopsis leaves were performed as described in a previous study (Yoo et al., 2007). In addition, protoplasts of oil palm leaves were isolated according to the preparation of Arabidopsis leaf protoplasts, but the contents of Cellulase R10 (BR) and Macerozyme R10 (BR) were doubled. The plasmids were transferred into oil palm protoplasts using an equal volume 40% (w/v) polyethylene glycol/50 mm MgCl2 solution, and heat shock treatment was performed as described in previous research (Masani et al., 2014). Yeast Two-Hybrid Assays Yeast two-hybrid assays were performed using Matchmaker™ Gold Yeast Two-Hybrid System (Clontech, United States). According to the user manual, EgMADS16-pGBKT7 plasmids were transfected into Y2H Gold yeast strains, and the autoactivation of EgMADS16 transcription factor was tested. Then, the EgMADS16-pGBKT7 Y2H Gold yeast strains and oil palm library strains which kept by our laboratory were combined. After incubation at 30°C for 20–24 h at 45 rpm, these strains were plated on SD/Try/Leu/-His/Ade/+X-α- Gal/+Aba mediums. RESULTS Effect of EgMADS16 on Lipid Biosynthesis To characterize the role of EgMADS16 in lipid biosynthesis, we obtained EgMADS16-overexpressing Arabidopsis lines (OXEgMADS16 Line A and Line B; Figure 4A) and oil palm embryonic callus lines (OXEgMADS16 Line 1 and Line 2; Figure 5A). Compared with the wild type, all OXEgMADS16 lines had higher EgMADS16 expression. Meanwhile, the relative fatty acid contents of OXEgMADS16 Arabidopsis seeds and oil palm embryonic calli were tested by GC. The results showed that the C18:0 and C18:3 contents of the OXEgMADS16 lines significantly increased, while the C18:1 content decreased compared with that of the wild type (Figures 4D, 5D). In addition, there were significant decreases in the lipid contents of both OXEgMADS16 Arabidopsis seeds and oil palm embryonic calli (Figures 4C, 5C). Cloning and Subcellular Localization of EgMADS16h g The mRNA of EgMADS16 (NM_001303583) is 951 bp in length and encodes a protein of 225 amino acids (NP_001290512.1). The CDS of EgMADS16, which is 678 bp, from oil palm mesocarp using primers is shown in Supplementary Table 2. qPCR indicated that the expression of EgMADS16 fluctuated from phase 1 to phase 3 and then sharply increased and reached a peak in phase 4; however, there was a gradual decline from phase 4 to phase 5 (Figure 1A). Conserved domain analysis (see footnote 1) showed that there are MADS_MEF2_like and K-box domains in the EgMADS16 amino acid sequence (Figure 1B). In addition, we constructed a phylogenetic tree of EgMADS16 and other MADS proteins from different species using the neighbor-joining method in MEGA6, including EgGLO1 (XP_010911271.1), EgGLO2 (AAQ03229.1), OsMADS2 (XP_015623988.1), OsMADS4 (XP_015640709.1), OsMADS6 (XP_015623947.1), OsMADS8 (XP_015610824.1), OsMADS16 (XP_015641661.1), AcMADS16 (XP_020082339.1), BnAGL11 (XP_013719732.1), BnTT16 (NP_001303188.1), CenDEF (ALB26780.1), CenDEF3 (AFH66787.1), OitaDEF1 (BAO00916.1), OitaDEF2 (BAO00917.1), OitaDEF3 (BAO00918.1), MaMADS16 (XP_009418316.1), and PdMADS16 (XP_008781489.1). As shown in Figure 1C, EgMADS16 was closest to PdMADS16 (91.56% identity), AcMADS16 (87.56% identity), and MaMADS16 (84.89% identity). Moreover, to identify whether EgMADS16 localized to the nucleus, similar to other transcription factors, we conducted a subcellular localization test in tobacco leaf epidermal cells, and the results indicated that the EgMADS16-GFP fusion protein was localized in the nucleus (Figure 2). Oil Palm Embryoids Culture and Transformation Oil palm embryoids were cultured using woody plant medium in a 28°C incubator with 12 h light/12 h dark cycles according to previous research (Zou et al., 2019). A. tumefaciens GV3101, which contained EgMADS16-p3301 plasmids, was used to infect July 2021 \| Volume 12 \| Article 722596 Frontiers in Plant Science \| www.frontiersin.org 3 EgMADS16 Regulates Lipid Metabolism Wang et al. Likewise, CenDEF3 is the target of CenmiR5179 in Cymbidium ensifolium (Li et al., 2015). Therefore, small RNA target analysis (see footnote 3) suggested that EgMADS16 is targeted by EgmiR5179. To verify this target relationship, we performed a dual-luciferase reporter assay in Arabidopsis and oil palm protoplasts. The results indicated that the relative luciferase activity of EgMADS16-LUC-transfected protoplasts was decreased with the expression of EgmiR5179 (Figures 3A,B). At the same time, we transformed either or both EgmiR5179-SK and EgMADS16-LUC into oil palm protoplasts, and then, the relative expression level of EgMADS16 was detected by qPCR. The results were consistent with the results of the dual-luciferase reporter assay in which the EgMADS16 expression level was downregulated by EgmiR5179 (Figure 3C). Likewise, CenDEF3 is the target of CenmiR5179 in Cymbidium ensifolium (Li et al., 2015). Therefore, small RNA target analysis (see footnote 3) suggested that EgMADS16 is targeted by EgmiR5179. To verify this target relationship, we performed a dual-luciferase reporter assay in Arabidopsis and oil palm protoplasts. The results indicated that the relative luciferase activity of EgMADS16-LUC-transfected protoplasts was decreased with the expression of EgmiR5179 (Figures 3A,B). At the same time, we transformed either or both EgmiR5179-SK and EgMADS16-LUC into oil palm protoplasts, and then, the relative expression level of EgMADS16 was detected by qPCR. The results were consistent with the results of the dual-luciferase reporter assay in which the EgMADS16 expression level was downregulated by EgmiR5179 (Figure 3C). Bioinformational Analysis Conserved domain was analyzed in the web site.1 Multiple sequence alignment was carried out by Clustal Omega.2 Small RNA target analysis was performed using the web site.3 The phylogenetic tree of EgMADS16 and other MADS proteins from different species was constructed using the neighbor- joining method in MEGA6. Statistical Analysish The values are the means ± SD (n ≧ 3). Significant differences between groups were analyzed by SPSS software using Student’s t-test. “” represents a significant difference (p < 0.05), and “*” represents a highly significant difference (p < 0.01). Regulation of EgMADS16 in Lipid Biosynthesis by EgmiR5179 y y g Based on the predicted targeting regulatory relationship, EgmiR5179 should regulate the expression of EgMADS16 and thus play a role in lipid biosynthesis. To verify this hypothesis, we generated transgenic Arabidopsis plants that coexpressed EgmiR5179 and EgMADS16 (OXEgmiR5179-EgMADS16; Figure 6A) and analyzed the FA and oil contents. As expected, EgmiR5179 weakened the inhibitory effect of EgMADS16 on oil contents (Figure 6B). Additionally, the relative contents of C18:0 and C18:3 in OXEgmiR5179-EgMADS16 seeds decreased compared with those of the OXEgMADS16 seeds, while those in OXEgMADS16 seeds rose compared with WT seeds. The C18:1 content of OXEgmiR5179-EgMADS16 seeds increased compared with that of OXEgMADS16 seeds, while that of OXEgMADS16 seeds decreased compared with that of WT seeds (Figure 6C). Moreover, to identify whether EgMADS16 localized to the nucleus, similar to other transcription factors, we conducted a subcellular localization test in tobacco leaf epidermal cells, and the results indicated that the EgMADS16-GFP fusion protein was localized in the nucleus (Figure 2). F ti i Pl t S i \| f ti i Verification of the Target Relationship Between EgmiR5179 and EgMADS16 According to previous research, OitaDEF2 is the target of OitamiR5179 in Orchid orchis italics (Aceto et al., 2014). 1https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi 2http://www.ebi.ac.uk/Tools/msa/clustalo/ 3http://plantgrn.noble.org/psRNATarget/analysis?function=3 Identification of the Downstream Genes of EgMADS16h Between EgmiR5179 and EgMADS16 According to previous research, OitaDEF2 is the target of OitamiR5179 in Orchid orchis italics (Aceto et al., 2014). g EgMADS16 belongs to MADS-box family. This means that it is likely to function as a transcription factor to regulate lipid biosynthesis by regulating lipid biosynthesis-related genes. Therefore, we selected seven related genes according to the 1https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi 2http://www.ebi.ac.uk/Tools/msa/clustalo/ 3http://plantgrn.noble.org/psRNATarget/analysis?function=3 July 2021 \| Volume 12 \| Article 722596 Frontiers in Plant Science \| www.frontiersin.org 4 EgMADS16 Regulates Lipid Metabolism Wang et al. A C B FIGURE 1 \| The expression patterns and sequence analysis of EgMADS16. (A) The relative expression level of EgMADS16 in different developmental stages of oil palm fruit mesocarp. Phase 1–5: fruits 30–60 days, 60–100 days, 100–120 days, 120–140 days, and 140–160 days after pollination. The values are the means±SD (n = 3). (B) Conserved domains analysis of EgMADS16 protein. (C) The phylogenetic tree of EgMADS16 and other MADS proteins, including EgGLO1 (XP_010911271.1), EgGLO2 (AAQ03229.1), OsMADS2 (XP_015623988.1), OsMADS4 (XP_015640709.1), OsMADS6 (XP_015623947.1), OsMADS8 (XP_015610824.1), OsMADS16 (XP_015641661.1), AcMADS16 (XP_020082339.1), BnAGL11 (XP_013719732.1), BnTT16 (NP_001303188.1), CenDEF (ALB26780.1), CenDEF3 (AFH66787.1), OitaDEF1 (BAO00916.1), OitaDEF2 (BAO00917.1), OitaDEF3 (BAO00918.1), MaMADS16 (XP_009418316.1), and PdMADS16 (XP_008781489.1). B (A) The relative expression level of EgMADS16 in different developmental stages of oil ays, 120–140 days, and 140–160 days after pollination. The values are the means±SD genetic tree of EgMADS16 and other MADS proteins, including EgGLO1 OsMADS4 (XP_015640709.1), OsMADS6 (XP_015623947.1), OsMADS8 339.1), BnAGL11 (XP_013719732.1), BnTT16 (NP_001303188.1), CenDEF BAO00917.1), OitaDEF3 (BAO00918.1), MaMADS16 (XP_009418316.1), and A B B C C FIGURE 1 \| The expression patterns and sequence analysis of EgMADS16. (A) The relative expression level of EgMADS16 in different developmental stages of oil palm fruit mesocarp. Phase 1–5: fruits 30–60 days, 60–100 days, 100–120 days, 120–140 days, and 140–160 days after pollination. The values are the means±SD (n = 3). (B) Conserved domains analysis of EgMADS16 protein. (C) The phylogenetic tree of EgMADS16 and other MADS proteins, including EgGLO1 (XP_010911271.1), EgGLO2 (AAQ03229.1), OsMADS2 (XP_015623988.1), OsMADS4 (XP_015640709.1), OsMADS6 (XP_015623947.1), OsMADS8 (XP_015610824.1), OsMADS16 (XP_015641661.1), AcMADS16 (XP_020082339.1), BnAGL11 (XP_013719732.1), BnTT16 (NP_001303188.1), CenDEF (ALB26780.1), CenDEF3 (AFH66787.1), OitaDEF1 (BAO00916.1), OitaDEF2 (BAO00917.1), OitaDEF3 (BAO00918.1), MaMADS16 (XP_009418316.1), and PdMADS16 (XP_008781489.1). EgMADS16 Binds to EgGLO1 Proteins Next, we used yeast two-hybrid assays to identify the transcription factors that interact with EgMADS16 proteins. Considering the activation domains of transcription factors, we tested the autoactivation of EgMADS16 on yeast reporters. Frontiers in Plant Science \| www.frontiersin.org DISCUSSION and EgDGAT2 were selected as candidate genes, and qRT-PCR was used to detect the expression levels of these seven oil biosynthesis-related genes in OXEgMADS16 oil palm embryonic calli. As a result, the transcription levels of EgSAD, EgFAD2, and EgDGAT2 were significantly suppressed (Figures 7A–C). This result indicates that EgMADS16 regulates the contents of fatty acids and oil by inhibiting the expression of EgSAD, EgFAD2, and EgDGAT2. To determine whether the EgMADS16 protein directly regulates the expression of these three genes by binding to their promoters, a yeast one-hybrid assay was conducted. However, the results showed that the EgMADS16 protein cannot directly bind to the promoters of EgSAD, EgFAD2, and EgDGAT2. This means that EgMADS16 protein likely inhibits the expression level of these three genes by interacting with an intermediate protein, which can directly bind to the promoters of EgSAD, EgFAD2, and EgDGAT2. In this paper, the role of the EgMADS16 gene in oil biosynthesis was studied. Among the oil palm fruits at five different developmental stages, the EgMADS16 gene had the highest transcription level in the fourth stage and decreased in the fifth stage. The phylogenetic tree analysis showed that PdMADS16 had the closest relationship with EgMADS16, followed by AcMADS16 and MaMADS16, but their functions have not been reported. The subcellular localization results showed that EgMADS16 protein was located in the nucleus, which is consistent with the localization of other transcription factors. Previous studies found that MADS-box genes were closely related to plant growth and development. In oil palm, it has been proven that the MADS-box gene EgSQUA1 is related to the height of the plant and the length of pedicels and siliques; EgGLO2 promotes a partial conversion of sepals to petals in whorl 1; and EgAGL2-1 is involved in stamens and gynoecium development (Adam et al., 2007). However, the overexpression of EgMADS16 (EgDEF1) did not change the phenotype of flowers (Adam et al., 2007) but participated in the biosynthesis of oil and fatty acids, which was demonstrated by the significant increases in C18:0 and C18:3 contents and the decreases in C18:1 content and total oil yield (Figures 4, 5). p g g g In addition, small RNA target analysis showed that EgMADS16 is targeted by EgmiR5179 (Supplementary Figure 3). Moreover, the dual-luciferase reporter assay and qRT-PCR in protoplasts further suggested this target relationship: EgmiR5179 can inhibit the expression of EgMADS16 (EgDEF1; Figure 3). Identification of the Downstream Genes of EgMADS16h The results showed that EgMADS16 proteins have an activation domain, but Aba can inhibit its autoactivation (Supplementary Figure 2). Therefore, we performed yeast two-hybrid assays and found that there was an interaction between EgMADS16 and EgGLO1 (XP_010911271.1) proteins (Figure 8A). To further verify this interaction, BiFC was used. YFP protein fluorescence was observed only when EgMADS16- pSPYNE and EgGLO1-pSPYCE were coinfiltrated into the leaves of N. benthamiana (Figure 8B), suggesting that EgMADS16 binds to the EgGLO1 proteins. EgMADS16 Binds to EgGLO1 Proteins results of fatty acid compositions and contents of OXEgMADS lines, and we examined the expression level of these genes in OXEgMADS oil palm embryonic callus by qPCR. As a result, the expression levels of EgFAD2, EgDGAT2, and EgSAD significantly declined, while those of EgFAD7, EgFAD6, EgLACS9, and EgDGAT1 did not significantly change (Figures 7A–G). i To further investigate whether EgMADS16 protein regulates the expression of EgFAD2, EgDGAT2, and EgSAD by binding to their promoters, we conducted yeast one-hybrid assays. However, interactions between EgMADS16 and the promoters of EgFAD2, EgDGAT2, or EgSAD were not detected (Supplementary Figure 1), suggesting that EgMADS16 downregulated these genes by interacting with other DNA-binding transcription factors rather than directly binding to their promoters. July 2021 \| Volume 12 \| Article 722596 Frontiers in Plant Science \| www.frontiersin.org 5 Wang et al. EgMADS16 Regulates Lipid Metabolism FIGURE 2 \| Subcellular localization of EgMADS16 protein in onion epidermal cells. (A) Bright light. (B) DAPI. (C) EgMADS-GFP fluorescence. (D) Merged image. Scale bar, 50 μm. tion of EgMADS16 protein in onion epidermal cells. (A) Bright light. (B) DAPI. (C) EgMADS-GFP fluorescence. (D) Merged image. FIGURE 2 \| Subcellular localization of EgMADS16 protein in onion epidermal cells. (A) Bright light. (B) DAPI. (C) EgMADS-GFP fluorescence. (D) Merged image. Scale bar 50 μm GURE 2 \| Subcellular localization of EgMADS16 protein in onion epidermal cells. (A) Bright light. (B) DAPI. (C) EgMADS-GFP fluo cale bar, 50 μm. Frontiers in Plant Science \| www.frontiersin.org DISCUSSION The overexpression of EgmiR5179 significantly increased the total oil content in seeds (Gao et al., 2019). In this study, the overexpression of EgMADS16 significantly reduced the total oil content of Arabidopsis seeds and oil palm embryonic calli (Figures 4, 5), which is consistent with the role of EgMADS16 as the target gene of EgmiR5179. In addition, compared with OXMADS16 transgenic Arabidopsis seeds, the total oil content As a transcription factor, EgMADS16 likely participates in the regulation of oil biosynthesis in the same way. According to the fatty acid compositions and contents of OXEgMADS lines, EgSAD, EgFAD2, EgFAD6, EgFAD7, EgLACS9, EgDGAT1, July 2021 \| Volume 12 \| Article 722596 Frontiers in Plant Science \| www.frontiersin.org 6 Wang et al. EgMADS16 Regulates Lipid Metabolism A C B FIGURE 3 \| EgMADS16 is the target gene of EgmiR5179. (A) Dual-luciferase reporter assay in Arabidopsis protoplasts. EgMADS16-LUC was transformed into wild-type and OXEgmiR5179 Arabidopsis protoplasts, respectively. (B) Dual-luciferase reporter assay in oil palm protoplasts. EgMADS16-LUC and SK or EgmiR5179-SK were transformed into oil palm protoplasts, respectively. (C) The relative expression level of EgMADS16 in oil palm protoplasts that transformed either or both of EgmiR5179 and EgMADS16. The values are the means ± SD (n = 3), “” represents a significant difference (p < 0.05), and “*” represents a highly significant difference (p < 0.01) using Student’s t-test. A B A B B C C FIGURE 3 \| EgMADS16 is the target gene of EgmiR5179. (A) Dual-luciferase reporter assay in Arabidopsis protoplasts. EgMADS16-LUC was transformed into wild-type and OXEgmiR5179 Arabidopsis protoplasts, respectively. (B) Dual-luciferase reporter assay in oil palm protoplasts. EgMADS16-LUC and SK or EgmiR5179-SK were transformed into oil palm protoplasts, respectively. (C) The relative expression level of EgMADS16 in oil palm protoplasts that transformed either or both of EgmiR5179 and EgMADS16. The values are the means ± SD (n = 3), “” represents a significant difference (p < 0.05), and “*” represents a highly significant difference (p < 0.01) using Student’s t-test. of OXEgmiR5179-EgMADS16 seeds increased significantly, C18:0 and C18:3 decreased, and C18:1 increased. More interestingly, this trend of change was opposite to the trend of oil and fatty acid contents in the seeds of OXMADS16 plants relative to the wild type (Figures 6B,C). This implies that EgmiR5179 can inhibit the regulation of EgMADS16 in the biosynthesis of oil and FAs and promote the accumulation of oil. Frontiers in Plant Science \| www.frontiersin.org DISCUSSION (C) The oil content of WT and OXEgMADS16 oil palm embryonic callus. (D) The relative FA content of WT and OXEgMADS16 oil palm embryonic callus. The values are the means ± SD (n = 3), “” represents a significant difference (p < 0.05), and “*” represents a highly significant difference (p < 0.01) using Student’s t-test. A B C D FIGURE 4 \| Effect of EgMADS16 on lipid biosynthesis in oil palm embryonic callus. (A) Wild-type oil palm (WT-OP) embryonic callus and EgMADS16 overexpression oil palm embryonic callus (OXEgMADS16 OP) on screening medium containing glufosinate ammonium. Scale bar, 3 mm. (B) The relative expression level of EgMADS16 in WT-OP and OXEgMADS16 OP. (C) The oil content of WT and OXEgMADS16 oil palm embryonic callus. (D) The relative FA content of WT and OXEgMADS16 oil palm embryonic callus. The values are the means ± SD (n = 3), “” represents a significant difference (p < 0.05), and “*” represents a highly significant difference (p < 0.01) using Student’s t-test. A B B A C D D D C FIGURE 4 \| Effect of EgMADS16 on lipid biosynthesis in oil palm embryonic callus. (A) Wild-type oil palm (WT-OP) embryonic callus and EgMADS16 overexpression oil palm embryonic callus (OXEgMADS16 OP) on screening medium containing glufosinate ammonium. Scale bar, 3 mm. (B) The relative expression level of EgMADS16 in WT-OP and OXEgMADS16 OP. (C) The oil content of WT and OXEgMADS16 oil palm embryonic callus. (D) The relative FA content of WT and OXEgMADS16 oil palm embryonic callus. The values are the means ± SD (n = 3), “” represents a significant difference (p < 0.05), and “*” represents a highly significant difference (p < 0.01) using Student’s t-test. A B C D FIGURE 5 \| Effect of EgMADS16 on lipid biosynthesis in Arabidopsis. (A) Wild-type Arabidopsis (WT-At) and EgMADS16 overexpression Arabidopsis (OXEgMADS16 At). (B) The relative expression level of EgMADS16 in WT-At and OXEgMADS16 At. (C) The oil content of WT and OXEgMADS16 Arabidopsis seeds. (D) The relative FA content of WT and OXEgMADS16 Arabidopsis seeds. The values are the means ± SD (n = 3), “” represents a significant difference (p < 0.05), and “*” represents a highly significant difference (p < 0.01) using Student’s t-test. B A B A C D D D C C FIGURE 5 \| Effect of EgMADS16 on lipid biosynthesis in Arabidopsis. DISCUSSION an interaction between the EgMADS16 protein and EgGLO1 protein (Figure 8). EgMADS16 proteins regulate oil biosynthesis by interacting with the EgGLO1 proteins, which directly bind to the promoters of oil biosynthesis-related genes. However, there is no interaction between the OsMADS16 protein and OsMADS2 (Lee et al., 2003), which are homologs of EgMADS16 and EgGLO1. In addition, this may be due to species differences. In previous studies, it has been proven that homologous complexes formed between MADS-box proteins to facilitate the binding of MADS-box proteins to DNA. For example, OsMADS16 protein interacts with OsMADS4, OsMADS6, and OsMADS8 proteins to regulate stamen development (Lee et al., 2003); GmMADS28 protein interacts with SOC1, AP1, and AGL8/FUL proteins to modulate floral organ number, petal identity, and sterility (Huang et al., 2014). Similarly, the results of yeast two-hybrid assays and BiFC suggested that there was f In summary, we are hypothesizing a model of the molecular mechanism by which EgMADS16 regulates oil biosynthesis (Figure 9). After EgMADS16 is translated, the EgMADS16 protein forms a complex with EgGLO1 or other proteins and binds to the promoter of EgFAD2, EgSAD, EgDGAT2, or other oil biosynthesis-related genes, inhibiting the transcription of these genes and affecting fatty acid components and oil accumulation. However, when EgmiR5179 is overexpressed, the EgmiR5179 mature sequence binds to EgMADS16 mRNA and July 2021 \| Volume 12 \| Article 722596 7 EgMADS16 Regulates Lipid Metabolism Wang et al. Frontiers in Plant Science \| www.frontiersin.org 8 July 2021 \| Volume 12 \| Article 722596 A B C D FIGURE 5 \| Effect of EgMADS16 on lipid biosynthesis in Arabidopsis. (A) Wild-type Arabidopsis (WT-At) and EgMADS16 overexpression Arabidopsis (OXEgMADS16 At). (B) The relative expression level of EgMADS16 in WT-At and OXEgMADS16 At. (C) The oil content of WT and OXEgMADS16 Arabidopsis seeds. (D) The relative FA content of WT and OXEgMADS16 Arabidopsis seeds. The values are the means ± SD (n = 3), “” represents a significant difference (p < 0.05), and “*” represents a highly significant difference (p < 0.01) using Student’s t-test. A B C D FIGURE 4 \| Effect of EgMADS16 on lipid biosynthesis in oil palm embryonic callus. (A) Wild-type oil palm (WT-OP) embryonic callus and EgMADS16 overexpression oil palm embryonic callus (OXEgMADS16 OP) on screening medium containing glufosinate ammonium. Scale bar, 3 mm. (B) The relative expression level of EgMADS16 in WT-OP and OXEgMADS16 OP. DISCUSSION (A) Wild-type Arabidopsis (WT-At) and EgMADS16 overexpression Arabidopsis (OXEgMADS16 At). (B) The relative expression level of EgMADS16 in WT-At and OXEgMADS16 At. (C) The oil content of WT and OXEgMADS16 Arabidopsis seeds. (D) The relative FA content of WT and OXEgMADS16 Arabidopsis seeds. The values are the means ± SD (n = 3), “” represents a significant difference (p < 0.05), and “*” represents a highly significant difference (p < 0.01) using Student’s t-test. July 2021 \| Volume 12 \| Article 722596 8 Frontiers in Plant Science \| www.frontiersin.org Wang et al. EgMADS16 Regulates Lipid Metabolism Frontiers in Plant Science \| www.frontiersin.org 9 July 2021 \| Volume 12 \| Article 722596 A C B FIGURE 6 \| The effect of EgMADS16 on lipid biosynthesis is inhibited by EgmiR5179 in Arabidopsis. (A) The relative expression level of EgMADS16 in wild-type and transgenic Arabidopsis. (B) The oil content of wild-type and transgenic Arabidopsis seeds. (C) The relative FA content of wild-type and transgenic Arabidopsis seeds. The values are the means ± SD (n = 3), “” represents a significant difference (p < 0.05), and “” represents a highly significant difference (p < 0.01) using Student’s t-test. OXEgmiR5179-EgMADS16 At: Arabidopsis coexpressed EgmiR5179 and EgMADS16. A B C D E F G FIGURE 7 \| Identification of downstream genes of EgMADS16 protein. (A–G) The relative expression level of EgFAD2 (A), EgDGAT2 (B), EgSAD (C), EgFAD7 (D), EgFAD6 (E), EgLACS9 (F), and EgDGAT1 (G) in WT and OXEgMADS16 oil palm embryonic callus. The values are the means ± SD (n = 3). “” represents a highly significant difference (p < 0.01) using Student’s t-test. A C B FIGURE 6 \| The effect of EgMADS16 on lipid biosynthesis is inhibited by EgmiR5179 in Arabidopsis. (A) The relative expression level of EgMADS16 in wild-type and transgenic Arabidopsis. (B) The oil content of wild-type and transgenic Arabidopsis seeds. (C) The relative FA content of wild-type and transgenic Arabidopsis seeds. The values are the means ± SD (n = 3), “” represents a significant difference (p < 0.05), and “” represents a highly significant difference (p < 0.01) using Student’s t-test. OXEgmiR5179-EgMADS16 At: Arabidopsis coexpressed EgmiR5179 and EgMADS16. A B C C FIGURE 6 \| The effect of EgMADS16 on lipid biosynthesis is inhibited by EgmiR5179 in Arabidopsis. (A) The relative expression level of EgMADS16 in wild-type and transgenic Arabidopsis. FUNDING This research was supported by the Hainan Provincial Natural Science Foundation of China (No. 2019CXTD397), the National Natural Science Foundation of China (NSFC; No. 31660222), and the National Key R&D Program of China (2018YFD1000500). DISCUSSION (B) The oil content of wild-type and transgenic Arabidopsis seeds. (C) The relative FA content of wild-type and transgenic Arabidopsis seeds. The values are the means ± SD (n = 3), “” represents a significant difference (p < 0.05), and “” represents a highly significant difference (p < 0.01) using Student’s t-test. OXEgmiR5179-EgMADS16 At: Arabidopsis coexpressed EgmiR5179 and EgMADS16. A B C D E F G FIGURE 7 \| Identification of downstream genes of EgMADS16 protein. (A–G) The relative expression level of EgFAD2 (A), EgDGAT2 (B), EgSAD (C), EgFAD7 (D), EgFAD6 (E), EgLACS9 (F), and EgDGAT1 (G) in WT and OXEgMADS16 oil palm embryonic callus. The values are the means ± SD (n = 3). “” represents a highly significant difference (p < 0.01) using Student’s t-test. A B C G F D E D E FIGURE 7 \| Identification of downstream genes of EgMADS16 protein. (A–G) The relative expression level of EgFAD2 (A), EgDGAT2 (B), EgSAD (C), EgFAD7 (D), EgFAD6 (E), EgLACS9 (F), and EgDGAT1 (G) in WT and OXEgMADS16 oil palm embryonic callus. The values are the means ± SD (n = 3). “**” represents a highly significant difference (p < 0.01) using Student’s t-test. July 2021 \| Volume 12 \| Article 722596 9 Frontiers in Plant Science \| www.frontiersin.org EgMADS16 Regulates Lipid Metabolism Wang et al. A B FIGURE 8 \| EgMADS16 protein binds to EgGLO1 protein. (A) Yeast two-hybrid assay of EgMADS16 protein and EgGLO1 protein. (B) BiFC of EgMADS16 protein and EgGLO1 protein. Scale bar, 20 μm. A A B FIGURE 8 \| EgMADS16 protein binds to EgGLO1 protein. (A) Yeast two-hybrid assay of EgMADS16 protein and EgGLO1 protein. (B) BiFC of EgMADS16 protein and EgGLO1 protein. Scale bar, 20 μm. B FIGURE 8 \| EgMADS16 protein binds to EgGLO1 protein. (A) Yeast two-hybrid assay of EgMADS16 protein and EgGLO1 protein. (B) BiFC of EgMADS16 protein d E GLO1 t i S l b 20 FIGURE 8 \| EgMADS16 protein binds to EgGLO1 protein. (A) Yeast two-hybrid assay of EgMADS16 protein and EgGLO1 protein. (B) BiFC of EgMADS16 protein and EgGLO1 protein. Scale bar, 20 μm. binds to EgGLO1 protein. (A) Yeast two-hybrid assay of EgMADS16 protein and EgGLO1 protein. (B) BiFC of EgMADS16 protein FIGURE 8 \| EgMADS16 protein binds to EgGLO1 protein. (A) Yeast two-hybrid assay of EgMADS16 protein and EgGLO1 prote and EgGLO1 protein. Scale bar, 20 μm. AUTHOR CONTRIBUTIONS inhibits its expression so that the transcription of downstream oil biosynthesis-related genes cannot be inhibited by EgMADS16 protein. DL and YZ designed the research. YW, JZo, and JZh performed the research. YZ and DL wrote the paper. All authors read and approved the final manuscript. Nevertheless, the intermediate proteins regulated by EgMADS16 proteins for the transcription of EgSAD, EgFAD2, and EgDGAT2 have yet to be studied. It is unclear which oil biosynthesis-related genes, the EgMADS16/EgGLO1 complex, regulate. Nevertheless, the molecular mechanism presented in this paper provides a preliminary understanding of the regulation of oil biosynthesis by transcription factors in oil palm, which lays the foundation for further research and provides a strategy for obtaining a higher yield of oil palm in the future. SUPPLEMENTARY MATERIAL The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material. The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpls.2021.722596/ full#supplementary-material July 2021 \| Volume 12 \| Article 722596 Frontiers in Plant Science \| www.frontiersin.org 10 Wang et al. EgMADS16 Regulates Lipid Metabolism FIGURE 9 \| A model about the molecular mechanism of EgMADS16 regulating oil biosynthesis. EgMADS16 protein forms a complex with EgGLO1 or other proteins and binds to the promoter of EgFAD2 or EgSAD or EgDGAT2 or other oil biosynthesis-related genes, inhibiting the transcription of these genes and affecting fatty acid components and oil accumulation. However, EgmiR5179 targets to EgMADS16 mRNA and inhibits its expression, so that the oil accumulation is promoted. REFERENCES Aceto S Sica M De Paolo S D’argenio V Cantiello P Salvatore F et al Adam, H., Jouannic, S., Orieux, Y., Morcillo, F., Richaud, F., Duval, Y., et al. (2007). Functional characterization of MADS box genes involved in the determination of oil palm flower structure. J. Exp. Bot. 58, 1245–1259. doi: FIGURE 9 \| A model about the molecular mechanism of EgMADS16 regulating oil biosynthesis. EgMADS16 protein forms a complex with EgGLO1 or other proteins and binds to the promoter of EgFAD2 or EgSAD or EgDGAT2 or other oil biosynthesis-related genes, inhibiting the transcription of these genes and affecting fatty acid components and oil accumulation. However, EgmiR5179 targets to EgMADS16 mRNA and inhibits its expression, so that the oil accumulation is promoted. REFERENCES Aceto, S., Sica, M., De Paolo, S., D’argenio, V., Cantiello, P., Salvatore, F., et al. (2014). The analysis of the inflorescence miRNome of the orchid orchis italica reveals a DEF-like MADS-box gene as a new miRNA target. PLoS One 9:e97839. doi: 10.1371/journal.pone.0097839 Adam, H., Jouannic, S., Orieux, Y., Morcillo, F., Richaud, F., Duval, Y., et al. (2007). Functional characterization of MADS box genes involved in the determination of oil palm flower structure. J. Exp. Bot. 58, 1245–1259. doi: 10.1093/jxb/erl263 Bhagya, H. P., Kalyana Babu, B., Gangadharappa, P. M., Naika, M. B. N., Satish, D., and Mathur, R. K. (2020). Identification of QTLs in oil palm Adam, H., Jouannic, S., Orieux, Y., Morcillo, F., Richaud, F., Duval, Y., et al. (2007). Functional characterization of MADS box genes involved in the determination of oil palm flower structure. J. Exp. Bot. 58, 1245–1259. doi: 10.1093/jxb/erl263 Bhagya, H. P., Kalyana Babu, B., Gangadharappa, P. M., Naika, M. B. N., Satish, D., and Mathur, R. K. (2020). Identification of QTLs in oil palm REFERENCES Adam, H., Jouannic, S., Orieux, Y., Morcillo, F., Richaud, F., Duval, Y., et al. (2007). Functional characterization of MADS box genes involved in the determination of oil palm flower structure. J. Exp. Bot. 58, 1245–1259. doi: 10.1093/jxb/erl263 Aceto, S., Sica, M., De Paolo, S., D’argenio, V., Cantiello, P., Salvatore, F., et al. (2014). The analysis of the inflorescence miRNome of the orchid orchis italica reveals a DEF-like MADS-box gene as a new miRNA target. PLoS One 9:e97839. doi: 10.1371/journal.pone.0097839 July 2021 \| Volume 12 \| Article 722596 Frontiers in Plant Science \| www.frontiersin.org 11 EgMADS16 Regulates Lipid Metabolism Wang et al. (Elaeis guineensis Jacq.) using SSR markers through association mapping. J. Genet. 99:19. doi: 10.1007/s12041-020-1180-4 (Elaeis guineensis Jacq.) using SSR markers through association mapping. J. Genet. 99:19. doi: 10.1007/s12041-020-1180-4 Shen, B., Allen, W. B., Zheng, P., Li, C., Glassman, K., Ranch, J., et al. (2010). Expression of ZmLEC1 and ZmWRI1 increases seed oil production in maize. Plant Physiol. 153, 980–987. doi: 10.1104/pp.110.157537 Dyer, J. M., Stymne, S., Green, A. G., and Carlsson, A. S. (2008). High-value oils from plants. Plant J. 54, 640–655. doi: 10.1111/j.1365-313X.2008.03430.x Song, Q.-X., Li, Q.-T., Liu, Y.-F., Zhang, F.-X., Ma, B., Zhang, W.-K., et al. (2013). Soybean GmbZIP123 gene enhances lipid content in the seeds of transgenic Arabidopsis plants. J. Exp. Bot. 64, 4329–4341. doi: 10.1093/jxb/ ert238 Gao, L.-C., Wang, Y.-F., Zhu, Z., Chen, H., Sun, R.-H., Zheng, Y.-S., et al. (2019). EgmiR5179 from the mesocarp of oil palm (Elaeis guineensis Jacq.) regulates oil accumulation by targeting NAD transporter 1. Ind. Crop. Prod. 137, 126–136. doi: 10.1016/j.indcrop.2019.05.013 Tranbarger, T. J., Dussert, S., Joet, T., Argout, X., Summo, M., Champion, A., et al. (2011). Regulatory mechanisms underlying oil palm fruit mesocarp maturation, ripening, and functional specialization in lipid and carotenoid metabolism. Plant Physiol. 156, 564–584. doi: 10.1104/pp.111.175141 Huang, F., Xu, G., Chi, Y., Liu, H., Xue, Q., Zhao, T., et al. (2014). A soybean MADS-box protein modulates floral. BMC Plant Biol. 14, 1–4. doi: 10.1186/1471-2229-14-89 Jessen, D., Roth, C., Wiermer, M., and Fulda, M. (2015). Two activities of long-chain acyl-coenzyme a synthetase are involved in lipid trafficking between the endoplasmic reticulum and the plastid in Arabidopsis. Plant Physiol. 167, 351–366. doi: 10.1104/pp.114.250365 Yeap, W. C., Lee, F. C., Shabari Shan, D. K., Musa, H., Appleton, D. R., and Kulaveerasingam, H. (2017). REFERENCES WRI1-1, ABI5, NF-YA3 and NF-YC2 increase oil biosynthesis in coordination with hormonal signaling during fruit development in oil palm. Plant J. 91, 97–113. Yoo, S. D., Cho, Y. H., and Sheen, J. (2007). Arabidopsis mesophyll protoplasts: a versatile cell system for transient gene expression analysis. Nat. Protoc. 2, 1565–1572. doi: 10.1038/nprot.2007.199 Jin, Y., Yuan, Y., Gao, L., Sun, R., Chen, L., Li, D., et al. (2017). Characterization and functional analysis of a type 2 diacylglycerol acyltransferase (DGAT2) gene from oil palm (Elaeis guineensis jacq.) mesocarp in saccharomyces cerevisiae and transgenic Arabidopsis thaliana. Front. Plant Sci. 8:1791. doi: 10.3389/fpls.2017.01791 Yuan, Y. J., Gao, L. C., Sun, R. H., Yu, T., Liang, Y. X., Li, D. D., et al. (2017). Seed-specific expression of an acyl-acyl carrier protein thioesterase CnFatB3 from coconut (Cocos nucifera L.) increases the accumulation of medium- chain fatty acids in transgenic Arabidopsis seeds. Sci. Hortic. 223, 5–9. doi: 10.1016/j.scienta.2017.05.029 Lee, S., Jeon, J.-S., An, K., Moon, Y.-H., Lee, S., Chung, Y.-Y., et al. (2003). Alteration of floral organ identity in rice through ectopic expression of OsMADS16. Planta 217, 904–911. doi: 10.1007/s00425-003-1066-8 Li, X., Jin, F., Jin, L., Jackson, A., Ma, X., Shu, X., et al. (2015). Characterization and comparative profiling of the small RNA transcriptomes in two phases of flowering in Cymbidium ensifolium. BMC Genomics 16:622. doi: 10.1186/ s12864-015-1764-1 Zou, J., Zhang, Q., Zhu, Z., Gao, L., Zheng, Y., and Li, D. (2019). Embryogenic callus induction and fatty acid composition analysis of oil palm (Elaeis guineensis cv. Tenera). Sci. Hortic. 245, 125–130. doi: 10.1016/j. scienta.2018.10.014 Li, S. Y., Zhang, Q., Jin, Y. H., Zou, J. X., Zheng, Y. S., and Li, D. D. (2020). A MADS-box gene, EgMADS21, negatively regulates EgDGAT2 expression and decreases polyunsaturated fatty acid accumulation in oil palm (Elaeis guineensis Jacq.). Plant Cell Rep. 39, 1505–1516. doi: 10.1007/s00299-020-02579-z Liu, Y.-F., Li, Q.-T., Lu, X., Song, Q.-X., Lam, S.-M., Zhang, W.-K., et al. (2014). Soybean GmMYB73 promotes lipid accumulation in transgenic plants. BMC Plant Biol. 14:73. doi: 10.1186/1471-2229-14-73 Li, S. Y., Zhang, Q., Jin, Y. H., Zou, J. X., Zheng, Y. S., and Li, D. D. (2020). A MADS-box gene, EgMADS21, negatively regulates EgDGAT2 expression and decreases polyunsaturated fatty acid accumulation in oil palm (Elaeis guineensis Jacq.). Plant Cell Rep. 39, 1505–1516. Frontiers in Plant Science \| www.frontiersin.org July 2021 \| Volume 12 \| Article 722596 REFERENCES doi: 10.1007/s00299-020-02579-z Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Liu, Y.-F., Li, Q.-T., Lu, X., Song, Q.-X., Lam, S.-M., Zhang, W.-K., et al. (2014). Soybean GmMYB73 promotes lipid accumulation in transgenic plants. BMC Plant Biol. 14:73. doi: 10.1186/1471-2229-14-73 Publisher’s Note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. Masani, M. Y., Noll, G. A., Parveez, G. K., Sambanthamurthi, R., and Prufer, D. (2014). Efficient transformation of oil palm protoplasts by PEG-mediated transfection and DNA microinjection. PLoS One 9:e96831. doi: 10.1371/ journal.pone.0096831 Ohlroggeav, J., and Browse, J. (1995). Lipid biosynthesis. Plant Cell 7, 957–970. doi: 10.1105/2Ftpc.7.7.957 Copyright © 2021 Wang, Zou, Zhao, Zheng and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Osorio-Guarin, J. A., Garzon-Martinez, G. A., Delgadillo-Duran, P., Bastidas, S., Moreno, L. P., Enciso-Rodriguez, F. E., et al. (2019). Genome-wide association study (GWAS) for morphological and yield-related traits in an oil palm hybrid (Elaeis oleifera × Elaeis guineensis) population. BMC Plant Biol. 19:533. doi: 10.1186/s12870-019-2153-8 July 2021 \| Volume 12 \| Article 722596 Frontiers in Plant Science \| www.frontiersin.org 12
https://openalex.org/W3171319256	https://digital.obvsg.at/ulbtirolfodok/content/titleinfo/7802593/full.pdf	English	null	Monetary policy announcements and bank lending: Do banks’ refinancing markets matter?	Economic modelling	2,021	cc-by	8,911	Max Breitenlechner ∗, Johann Scharler Max Breitenlechner ∗, Johann Scharler University of Innsbruck, Department of Economics, Universitaetsstrasse 15, A-6020, Innsbruck, Austria 1. Introduction We contribute to the literature, which has analyzed the eﬀects of proxies for banks’ funding costs, by isolating changes in funding costs that are associated with supply eﬀects on the market for banks’ funding, as emphasized by the bank lending channel, rather than demand side eﬀects. To identify supply side eﬀects on the market for banks’ fund- ing in the aftermath of monetary policy shocks, we propose a novel approach that combines macroeconomic data and data from the market for large certiﬁcates of deposits (jumbo CDs). The jumbo CD market rep- resents a common source for banks’ wholesale funding in the U.S. (see e.g. Acharya and Mora, 2015).3 Concretely, we interpret supply shifts as situations when interest rates and volumes on the jumbo CD market respond with opposite signs. Demand shifts, in contrast, are character- ized by responses in the same direction. How does monetary policy inﬂuence bank lending? The standard view of the monetary transmission mechanism suggests that bank loans, along with credit in the economy more generally, decline in response to a contractionary monetary policy shock. According to the bank lending channel, a monetary contraction reduces the supply of loans since banks are unable to perfectly oﬀset policy-induced ﬂuctuations in loanable funds (see e.g. Kashyap and Stein, 1994, 1995; 2000; Kis- han and Opiela, 2000; Gambacorta, 2005, 2008; Gambacorta and Mar- ques-Ibanez, 2011), which is partly due to higher funding costs of banks (Ellis and Flannery, 1992; Acharya and Mora, 2015; Breiten- lechner et al., 2016).1 Essentially, a contractionary monetary policy, for instance, increases banks’ funding costs as investors demand higher returns, which ultimately induces banks to reduce loans. In other words, We estimate a VAR with quarterly U.S. data ranging from 1990Q2 to 2016Q4 and identify monetary policy shocks using a high frequency ☆We thank Refet Gürkaynak for providing us with data on interest rate surprises, as well as two anonymous referees and the editor, Professor Sushanta Mallick, for their constructive comments and suggestions. This research did not receive any speciﬁc grant from funding agencies in the public, commercial, or not-for-proﬁt sectors. ∗Corresponding author. E-mail addresses: max.breitenlechner@uibk.ac.at (M. Breitenlechner), johann.scharler@uibk.ac.at (J. Scharler). 1 Kishan and Opiela (2012) ﬁnd that banks’ risk premiums respond to monetary policy shocks. Heryán and Tzeremes (2017) and Apergis and Christou (2015) study the bank lending channel during the global ﬁnancial crisis and the zero lower bound period. A R T I C L E I N F O How do bank loans respond to monetary policy shocks? The bank lending channel holds that banks’ reﬁnancing costs are crucial. This paper shows that what ultimately matters are shifts in the supply of funds available to banks. We use a structural VAR and a novel approach that combines data from the market for large certiﬁcates of deposits (jumbo CDs) and U.S. macroeconomic data from 1990Q2 to 2016Q4. We identify supply shifts on the jumbo CD market as situations when the volume and price of jumbo CDs respond with opposite signs to policy shocks. Demand shifts are characterized by responses in the same direction. We ﬁnd that only if policy shocks are associated with a lower supply of funds available to banks, then loan volumes fall immediately and persistently, in line with the bank lending channel. In contrast, loan volumes remain unresponsive if policy shocks shift banks’ demand for funds. Keywords: Bank lending External ﬁnance premium Structural vector autoregression High frequency identiﬁcation the supply curve on the market for banks’ funding shifts inward.2 the supply curve on the market for banks’ funding shifts inward.2 Economic Modelling 102 (2021) 105559 Economic Modelling 102 (2021) 105559 Contents lists available at ScienceDirect 1. Introduction See D’Avino (2018) for a global perspective. 2 In addition to a reduction in loan supply, loan volumes may also decline as ﬁrms and consumers demand fewer bank loans following a monetary contraction due to a worsened economic outlook, and hence banks reduce their demand for funding. g umbo CDs account on average for 14.06% of total deposits (the average is calculated for our sample across banks and time). 2.2. Identiﬁcation instruments as in Gertler and Karadi (2015), Nakamura and Steinsson (2018), and Caldara and Herbst (2019), among others. Speciﬁcally, we use the change in the three month ahead federal funds future rate from 10 min prior to 20 min after the policy announcement (see also Gürkay- nak et al., 2005). The policy announcement should dominate market movements within this tight window and thus the resulting surprises should be correlated with a monetary policy shock but uncorrelated with other macroeconomic shocks. Furthermore, as we use future rates and measure the surprises around scheduled meetings, any expecta- tions about the policy meeting should already be priced in prior to the announcement (Caldara and Herbst, 2019). As in Plagborg-Møller and Wolf (2021) we implement a recursive identiﬁcation scheme with the instrument ordered ﬁrst. instruments as in Gertler and Karadi (2015), Nakamura and Steinsson (2018), and Caldara and Herbst (2019), among others. Speciﬁcally, we use the change in the three month ahead federal funds future rate from 10 min prior to 20 min after the policy announcement (see also Gürkay- nak et al., 2005). The policy announcement should dominate market movements within this tight window and thus the resulting surprises should be correlated with a monetary policy shock but uncorrelated with other macroeconomic shocks. Furthermore, as we use future rates and measure the surprises around scheduled meetings, any expecta- tions about the policy meeting should already be priced in prior to the announcement (Caldara and Herbst, 2019). As in Plagborg-Møller and Wolf (2021) we implement a recursive identiﬁcation scheme with the instrument ordered ﬁrst. We identify monetary policy shocks using an instrument that is con- structed based on high frequency interest changes around monetary policy announcements (Gertler and Karadi, 2015; Nakamura and Steins- son, 2018; Caldara and Herbst, 2019). Speciﬁcally, we use the change in the three month ahead federal funds future rate from 10 min prior to 20 min after the policy announcement (see also Gürkaynak et al., 2005), since the policy announcement should dominate market move- ments within this tight window. Thus, the resulting surprises should be correlated with a monetary policy shock but uncorrelated with other macroeconomic shocks. 2.2. Identiﬁcation Furthermore, as we use future rates and mea- sure the surprises around scheduled meetings, any expectations about the policy meeting should already be priced in prior to the announce- ment (Caldara and Herbst, 2019).7 As a ﬁrst analysis, we consider the responses to a monetary policy shock without accounting for the dynamics on the market for jumbo CDs. We ﬁnd that although a contractionary monetary policy shock reduces real GDP, as expected, it has essentially no eﬀect on prices. And although the excess bond premium, which we interpret as a proxy for ﬁnancial market distress, increases slightly, the volume of bank loans initially increases and starts to decline with a substantial delay.4 In addition, we classify quarters as being characterized by either supply or demand eﬀects on the market for jumbo CDs and deﬁne the policy instrument accordingly. Consistent with an upward-sloping sup- ply curve we assume that a quarter is characterized by supply eﬀects if the interest rate and volume on the jumbo CD market move in opposite direction. In contrast, shifts in the demand for jumbo CDs are associated with interest rates and volumes moving in the same direction. Speciﬁ- cally, we deﬁne three separate policy instruments: Once we explicitly disentangle supply and demand eﬀects on the market for jumbo CDs that accompany the policy shock, output and prices both decline if the shock is associated with supply eﬀects on the market for jumbo CDs. The excess bond premium still increases but the loan volume starts to fall immediately following the shock. This contrasts with the responses to a policy shock accompanied by demand eﬀects on the market for jumbo CDs, where the excess bond premium remains essentially unresponsive and the volume of loans increases over the medium run. 5 In the robustness analysis (Section 4), we re-estimate the VAR without a linear trend and in ﬁrst log diﬀerences. Moreover, Table A1 in Appendix A presents the Akaike and Schwarz (Bayesian) information criteria for the three baseline estimations. As the information criteria favor a lag length of either 1 or 4 we select 2 in our baseline estimations. However, our results are also robust with respect to alternative lag lengths (see Figs. A1 and A2 in Appendix A). 6 We also estimate the model with an augmented Normal-Wishart prior to incorporate a standard Minnesota prior (see e.g. Litterman, 1986). Appendix B provides additional information about the estimation and the prior speciﬁca- tion. https://doi.org/10.1016/j.econmod.2021.105559 p g j Received 23 December 2020; Received in revised form 21 May 2021; Accepted 24 May 2021 Available online 4 June 2021 Received 23 December 2020; Received in revised form 21 May 2021; Accepted 24 May 2021 Available online 4 June 2021 0264-9993/© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). 0264-9993/© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http:/ M. Breitenlechner and J. Scharler Economic Modelling 102 (2021) 105559 2.2. Identiﬁcation (2) IVTotal,t = IVt, (2) IVCD Supply,t = ⎧ ⎪ ⎪ ⎪ ⎨ ⎪ ⎪ ⎪⎩ IVt, if IVt > 0 & ΔCD Ratet > 0 & ΔCD Volumet < 0 IVt, if IVt < 0 & ΔCD Ratet < 0 & ΔCD Volumet > 0 0, otherwise, (3) IVCD Demand,t = ⎧ ⎪ ⎪ ⎪ ⎨ ⎪ ⎪ ⎪⎩ IVt, if IVt > 0 & ΔCD Ratet > 0 & ΔCD Volumet > 0 IVt, if IVt < 0 & ΔCD Ratet < 0 & ΔCD Volumet < 0 0, otherwise, (4) (3) The remainder of the paper is structured as follows: In Section 2 we describe the empirical model, our identiﬁcation strategy, as well as the data. Section 3 presents our results and in Section 4 we perform various robustness checks. Finally, Section 5 concludes our analysis. 2. Empirical approach (4) 2.1. The model and estimation To evaluate the dynamic eﬀects of monetary policy shocks, we esti- mate a vector autoregressive (VAR) model speciﬁed in reduced form as follows: where IVt is the quarterly aggregated high frequency policy surprise measure, and ΔCD Rate and ΔCD Volume are the ﬁrst diﬀerence of the interest rates and volumes charged on jumbo CDs, respectively.8 Yt = c + p ∑ j=1 AjYt−j + dTt + et, (1) Yt = c + p ∑ j=1 AjYt−j + dTt + et, (1) We include the instruments sequentially in the VAR and due to the exogeneity of the instruments, as discussed above, we order the instru- ment ﬁrst and identify the structural parameters recursively using a Cholesky decomposition of the variance-covariance matrix Σe (see also Plagborg-Møller and Wolf, 2021; Noh, 2020).9 Nevertheless, we also consider alternative orderings in Section 4. where Yt is a vector of endogenous variables, Aj are matrices containing the reduced-form coeﬃcients, c is the constant term, and et is a vector of white noise reduced-form residuals with E(et) = 0 and Σe = E(ete′ t). In the baseline we include a linear time trend and set the lag length p = 2.5 We estimate the VAR using Bayesian methods but refrain from any speciﬁc prior assumptions. Following Uhlig (2005) we use the Normal-Wishart distribution as prior density and analytically derive the posterior distribution, which is also a Normal-Wishart density, using the estimated Aj and Σe as location parameters (see e.g. Uhlig, 1994).6 7 Unscheduled meetings may take place in response to unexpected economic developments and thus unscheduled policy announcements potentially capture the response to some other macroeconomic developments, at least to some extent (Nakamura and Steinsson, 2018). 7 Unscheduled meetings may take place in response to unexpected economic developments and thus unscheduled policy announcements potentially capture the response to some other macroeconomic developments, at least to some extent (Nakamura and Steinsson, 2018). 8 Jarocinski and Karadi (2020) and Jarocinski (2020) apply a similar approach to decompose monetary policy announcements into pure policy shocks and information shocks. 9 Alternatively, Paul (2020) includes the instrument as an exogenous regres- sor in the VAR framework and Jarocinski and Karadi (2020) impose a block- exogeneity between the high frequency instrument and other endogenous vari- ables in the VAR system. 4 Carpenter and Demiralp (2012) also ﬁnd that loans do not decline in response to an adverse policy shock. 8 Jarocinski and Karadi (2020) and Jarocinski (2020) apply a similar approach to decompose monetary policy announcements into pure policy shocks and information shocks. 9 Alternatively, Paul (2020) includes the instrument as an exogenous regres- sor in the VAR framework and Jarocinski and Karadi (2020) impose a block- exogeneity between the high frequency instrument and other endogenous vari- ables in the VAR system. 10 Until the end of 2016, large certiﬁcates of deposits are reported as deposits in denominations of 100,000 Dollar or more. In 2017, this threshold was set to 250,000 Dollar. 11 For simplicity, we refer to an impulse response as being signiﬁcant if the zero line lies outside the credibility bound. 12 Due to the availability of the CD market variables we aggregate the sur- prises on a quarterly frequency, although Gertler and Karadi (2015) aggregate the surprises on a monthly frequency. To see if our estimations are compara- ble to Gertler and Karadi (2015), we estimate the model with monthly data and without the CD market variables. The corresponding impulse response functions are displayed in Fig. A3 in Appendix A. As in Fig. 1, we see that loan volumes only decline after roughly two years, the excess bond premium increases, con- sumer prices do not respond systematically, and output declines, although the decline in industrial production is less persistent than the decrease in real GDP. 2.3. Data The interest expenses on jumbo CDs (RIAD4174 and RIADA517) cumulate yearly and therefore we take ﬁrst diﬀerences within each year to obtain quarterly interest expenses. No interest rate expenses are reported in 1997Q1 and 1997Q2 (missing values are interpolated using X12-ARIMA). The CD rate is multiplied by four to annualize the CD rate. rate, we use data only from banks that report volumes as well as interest expenses. (RGDP), the consumer price index (CPI), the one year Treasury rate (1YTR), the excess bond premium (EBP) provided by Gilchrist and Zakrajsek (2012), CD volumes (CDVOL), the CD rate (CDRATE), and total loans (TOLN). We use quarterly U.S. data over the period from 1990Q2 to 2016Q4. The start of the sample is determined by the avail- ability of the instrument and the end is restricted by the CD market data.10 We follow Gertler and Karadi (2015) and aggregate the high fre- quency policy instrument to match the data frequency of the other variables in the VAR. Speciﬁcally, to account for the timing of the pol- icy announcements we ﬁrst calculate a cumulative sum of the daily surprise series, then calculate quarterly averages, and ﬁnally take ﬁrst diﬀerences of this series to obtain quarterly surprises. Data for real GDP, the consumer price index, and the one year Treasury rate are obtained from the Federal Reserve Bank of St. Louis database, Federal Reserve Economic Data (FRED). For total loans we use the data reported in the H.8 statistical release issued by the Board of Governors of the Federal Reserve System. Data for the jumbo CD market are obtained from the Consolidated Reports of Condition and Income (Call Reports), which contain income and balance sheet state- ments of all U.S. insured banks. We calculate the aggregate volume of jumbo CDs (CDVOLt) from the data reported for individual banks as: The variables enter the VAR in log levels and are seasonally adjusted, except the interest rates and the policy instrument. Further- more, we deﬂate total loans and CD volumes by the consumer price index. Table 1 provides a detailed description of the data. 2.3. Data The vector of endogenous variables Yt includes the high frequency instrument (either IVTotal,t, IVCD Supply,t, or IVCD Demand,t), real GDP 4 Carpenter and Demiralp (2012) also ﬁnd that loans do not decline in response to an adverse policy shock. 7 Unscheduled meetings may take place in response to unexpected economic developments and thus unscheduled policy announcements potentially capture the response to some other macroeconomic developments, at least to some extent (Nakamura and Steinsson, 2018). 2 Economic Modelling 102 (2021) 105559 M. Breitenlechner and J. Scharler Variable description. Variables Name Source Code Period RGDPt Real gross domestic product (quarterly, seasonally adjusted, chained 2009) FRED GDPC1 1990Q2-2016Q4 CPIt Consumer price index: Total all items for the United States (quarterly, end of period, seasonally adjusted) FRED CPALTT01US Q661S 1990Q2-2016Q4 1YTRt One year Treasury constant maturity rate (quarterly, average, not seasonally adjusted) FRED GS1 1990Q2-2016Q4 TOLNt Loans and leases in bank credit (monthly, domestically chartered commercial banks, seasonally adjusted) H8 B1020NDMAM 1990Q2-2016Q4 CDVOLit Quarterly average of time certiﬁcates of deposit in denominations of $100,000 or more in domestic oﬃces CALL RCON3345 1990Q2-1996Q4 Quarterly averages of time deposits of $100,000 or more CALL RCONA514 1997Q1-2016Q4 CDVOLt Quarterly sum of CDVOLit across banks 1990Q2-2016Q4 INTEXit Interest on time certiﬁcates of deposit of $100,000 or more issued by domestic oﬃces CALL RIAD4174 1990Q2-1996Q4 Interest on time deposits of $100,000 or more CALL RIADA517 1997Q1-2016Q4 INTEXt Quarterly sum of INTEXit across banks 1990Q2-2016Q4 CDRATEt (INTEXt∕CDVOLt) · 4 1990Q2-2016Q4 EBPt Updated EBP series Favara et al. (2016) ebp 1990Q2-2016Q4 IVt Quarterly aggregated high frequency interest rate changes (three month ahead federal funds future rate) around monetary policy announcements Gürkaynak et al. (2005, updated) FF4 19990Q2-2016Q4 Notes: Federal Reserve Economic Data (FRED); Reports of Condition and Income (CALL reports); H.8 Assets and Liabilities of Commercial Banks in the United State (H8). The interest expenses on jumbo CDs (RIAD4174 and RIADA517) cumulate yearly and therefore we take ﬁrst diﬀerences within each year to obtain quarterly interest expenses. No interest rate expenses are reported in 1997Q1 and 1997Q2 (missing values are interpolated using X12-ARIMA). The CD rate is multiplied by four to annualize the CD rate. Notes: Federal Reserve Economic Data (FRED); Reports of Condition and Income (CALL reports); H.8 Assets and Liabilities of Commercial Banks in the United State (H8). 11 For simplicity, we refer to an impulse response as being signiﬁcant if the zero line lies outside the credibility bound. 3. Results Impulse response functions to the decomposed monetary policy shocks (using IVCD Supply,t or IVCD Demand,t as policy in response functions to the decomposed monetary policy shocks (using IVCD Supply,t or IVCD Demand,t as policy instrument). eﬀects on the jumbo CD market.13 run higher CD demand may counteract a decline in the supply of funds, leaving the CD volume rather unaﬀected. In other words, for a contractionary policy shock to induce stan- dard macroeconomic eﬀects, it appears to be necessary that the shock induces a tightening of funding conditions on banks’ wholesale funding markets. Moreover, our results suggest that the classical interest rate channel is rather weak in the sense that as long as funding conditions are favorable, macroeconomic eﬀects are rather muted. Fig. 2 shows the impulse responses to a monetary policy shock when we distinguish between supply (Panel A) and demand (Panel B) dynam- ics on the jumbo CD market. In contrast to what we ﬁnd for monetary policy shocks in general, loans decline immediately and persistently and ﬁnancial frictions tighten if the policy shock is associated with sup- ply eﬀects on the CD market, according to Panel A. The simultaneous decline of loan volumes and the worsening of funding conditions is con- sistent with the bank lending channel of monetary policy (Kashyap and Stein, 1994; Bernanke, 2007; Disyatat, 2011; Kishan and Opiela, 2012). In other words, when investors on CD markets reduce the availability of banks’ wholesale funding possibilities, banks reduce the availability of bank loans, consistent with the bank lending channel. If CD demand dynamics are dominant, loans initially increase and decline only with a time lag of roughly 8 to 9 quarters. Furthermore, we do not see a systematic response of the EBP, and hence, of funding conditions in general, in this case. The responses of the CD market variables in Fig. 2 show that the identiﬁed supply and demand dynamics capture relatively persistent patterns, with the CD volume and CD rate moving in opposite direc- tions for roughly 8 quarters in Panel A and in the same directions for roughly 12 quarters in Panel B. Moreover, if we compare the responses to the decomposed shocks with the responses to the unconstrained mon- etary policy shock (presented in Fig. 1) we see that CD demand related policy shocks are relatively more important for the overall eﬀects in the economy. 13 Fig. A4 in Appendix A shows the corresponding impulse response functions obtained with a standard Minnesota prior (see e.g. Litterman, 1986), as dis- cussed in Appendix B. The responses obtained with the Minnesota prior closely resemble those displayed in Figs. 1 and 2. 14 For instance, the overall monetary policy shock captures the large policy shocks related to demand dynamics at the very start of the sample, as well as, the large positive policy shocks linked to supply dynamics in late 1995 and early 1996. 13 Fig. A4 in Appendix A shows the corresponding impulse response functions obtained with a standard Minnesota prior (see e.g. Litterman, 1986), as dis- cussed in Appendix B. The responses obtained with the Minnesota prior closely resemble those displayed in Figs. 1 and 2. 3. Results Fig. 1 shows the impulse responses to a monetary policy shock when we do not distinguish between supply and demand dynamics on the jumbo CD market. The solid lines are the point-wise median impulse responses, and the light gray and dark gray areas represent 90% and 68% of the distribution of identiﬁed models in each period. CDVOLt = Nt ∑ i=1 CDVOLit, where Nt is the number of banks in each quarter t. where Nt is the number of banks in each quarter t. A one standard deviation monetary tightening increases the 1 year T-Bill rate by roughly 9 basis points. Real GDP declines per- sistently, although not signiﬁcantly,11 consumer prices do not respond systematically, and the excess bond premium increases, in line with ﬁndings in Gertler and Karadi (2015). Total loans increase slightly in the short run, before they start to decline after roughly two years (see e.g. Bernanke and Gertler, 1995; Carpenter and Demiralp, 2012).12 Although the CD rate is not directly available in the Call reports, it can be calculated as the quarterly interest expenses associated with jumbo CDs (INTEXit) over the volume of jumbo CDs (see also Acharya and Mora, 2015; Kishan and Opiela, 2012): CDRATEt = 4 ∑Nt i=1 INTEXit CDVOLt . Turning to the CD market we see that the CD rate increases, while CD volumes only decline after roughly two years. Thus, in the short We multiply the CD rate by four to obtain an annualized rate. We multiply the CD rate by four to obtain an annualized rate. For the calculation of CDVOL and CDRATE, we follow Den Haan et al. (2002) and use only insured banks that are located in the US (902,735 bank quarters). Interest expenses of jumbo CDs are reported for 875,672 bank quarters. Furthermore, we drop observations associ- ated with negative interest expenses (3038 observations). Volumes of jumbo CDs are available for each of the 872,634 bank quarters that we use in the analysis. To calculate the aggregate CD volume and the CD 3 M. Breitenlechner and J. Scharler Economic Modelling 102 (2021) 105559 M. Breitenlechner and J. Scharler Economic Modelling 102 (2021) 105559 Economic Modelling 102 (2021) 105559 Fig. 1. Impulse response functions to a monetary policy shock (using IVTotal,t as policy instrument). Fig. 2. Impulse response functions to the decomposed monetary policy shocks (using IVCD Supply t or IVCD Demand t as policy instrument). Fig. 2. 14 For instance, the overall monetary policy shock captures the large policy shocks related to demand dynamics at the very start of the sample, as well as, the large positive policy shocks linked to supply dynamics in late 1995 and early 1996. 15 In contrast, as can also be seen in Fig. 3, the two decomposed shocks bear with only −6% essentially no correlation. 3. Results This ﬁnding is also visible if we look at the time series of the three diﬀerent monetary policy shocks in Fig. 3. Although we see that the overall monetary policy shock in Panel A captures charac- teristics from both decomposed underlying shocks,14 we generally ﬁnd Concerning the macroeconomic variables, we also see diﬀerences across the two decomposed shocks. Real GDP and prices only decline with the increase of the policy rate in Panel A, i.e. when monetary policy shocks are accompanied by supply dynamics on the CD market. In contrast to Panel B, the GDP and price level responses in Panel A are at least marginally signiﬁcant. Although interest rates also increase in case of demand dynamics, the output response is only muted and we ﬁnd no systematic response of consumer prices. Thus, we conclude that monetary policy shocks give rise to responses that are in line with the predictions of standard models only if they are accompanied by supply 4 er and J. Scharler Economic Modelling 102 (2021) 1 Fig. 3. Identiﬁed monetary policy shocks (using the three diﬀerent policy instruments). rities with the policy shocks in Panel C that are linked to CD amics. More formally, we ﬁnd that the overall policy shock cy shocks in Panel B are correlated by roughly 40%, while on with the policy shocks in Panel C is about 70%.15 Finally, Fig. 4 shows the forecast error variance decomposi (FEVDs) of real GDP and total loans. We see that monetary p shocks that are accompanied by supply dynamics on the jumbo CD ket (Panel A) account for a higher share of the forecast error vari Economic Modelling 102 (2021) 105559 er and J. Scharler Economic M. Breitenlechner and J. Scharler Fig. 3. Identiﬁed monetary policy shocks (using the three diﬀerent policy instruments). Finally, Fig. 4 shows the forecast error variance decompositions (FEVDs) of real GDP and total loans. We see that monetary policy shocks that are accompanied by supply dynamics on the jumbo CD mar- ket (Panel A) account for a higher share of the forecast error variance of real GDP than shocks linked to demand dynamics (Panel B). For total loans, this is only true at longer horizons. Overall, we ﬁnd that monetary policy shocks account only for a limited amount of macroe- conomic ﬂuctuations, which is not unexpected and in line with, e.g. Ramey (2016). 16 To facilitate the comparison across the diﬀerent estimations, we show only the impulse response functions for real GDP, consumer prices, and total loans in this section. The remaining impulse responses, which generally support the robustness of our main results, are available upon request. 4. Robustness analysis (see e.g. Faust, 1998; Uhlig, 2005). The idea is that we identify two orthogonal shocks that are as highly correlated with the high fre- quency policy instrument (IVt) as possible and additionally impose sign restrictions on the responses of CD volumes and prices. Speciﬁcally, we require that negative policy shock, which are related to supply dynam- ics on the CD market, induce CD volumes to decline while the CD rate increases. In case of negative policy shocks, which are related to demand dynamics on the CD market, we impose that both CD volumes and prices increase.17 To assess the robustness of our ﬁndings we perform several sensitiv- ity checks. First, we consider an alternative identiﬁcation approach, which allows us to decompose policy induced CD market dynamics within one structural model. Second, we consider alternative orderings of the decomposed policy instruments. Finally, we assess alternative assumptions regarding the underlying data generating process and the number of autoregressive lags.16 To combine correlation restrictions with sign restrictions we rely on the algorithm suggested by Rubio-Ramírez et al. (2010) and Arias et al. (2018) for the implementation of sign restrictions and, in addition, check the correlation between a candidate monetary policy shock draw and the high frequency measure, as in Piﬀer and Podstawski (2017). In more detail, we draw 5000 models, where each model is a set of coef- ﬁcient matrices and a variance-covariance matrix, from the posterior distribution and sequentially we work through the following steps: 3. Results more similarities with the policy shocks in Panel C that are linked to CD demand dynamics. More formally, we ﬁnd that the overall policy shock and the policy shocks in Panel B are correlated by roughly 40%, while the correlation with the policy shocks in Panel C is about 70%.15 5 Economic Modelling 102 (2021) 105559 Fig 4 Forecast error variance decompositions of real GDP and total loans (using IV or IV as policy instrument) 17 The sign restrictions hold on impact plus three consecutive periods. 4.1. Alternative identiﬁcation To obtain decomposed policy shocks that are orthogonal by con- struction we consider an alternative identiﬁcation approach, which allows us to separate the dynamics on the CD market within one struc- tural model. For this approach we combine correlation restrictions, as put for- ward in Piﬀer and Podstawski (2017), with standard sign restrictions (i) We apply a Cholesky decomposition to the variance-covariance matrix to obtain orthogonal shocks, ut, that are related to the reduced form residuals through the linear mapping ut = P−1et, (i) We apply a Cholesky decomposition to the variance-covariance matrix to obtain orthogonal shocks, ut, that are related to the reduced form residuals through the linear mapping ut = P−1et, 6 Economic Modelling 102 (2021) 105559 M. Breitenlechner and J. Scharler chner and J. Scharler Economic Modelling 102 (20 Fig. 5. Impulse response functions to monetary policy shocks (alternative identiﬁcation). Fig. 5. Impulse response functions to monetary policy shocks (alternative identiﬁcation). Fig. 6. Impulse response functions to monetary policy shocks (alternative ordering). Fig. 6. Impulse response functions to monetary policy shocks (alternative ordering). 7 7 Economic Modelling 102 (2021) 105559 M. Breitenlechner and J. Scharler Fig. 7. Impulse response functions to monetary policy shocks (without a linear trend). Fig. 7. Impulse response functions to monetary policy shocks (without a linear trend). If the sign restrictions are not fulﬁlled we draw a new random matrix Q, obtain a new set of transformed, orthogonal shocks and check the sign restrictions. (ii) We obtain the impulse responses generated by the transformed model and check whether the imposed sign restrictions are ful- ﬁlled. We impose sign restrictions on impact and in the ﬁrst three periods. If the sign restrictions are not fulﬁlled we draw a new random matrix Q, obtain a new set of transformed, orthogonal shocks and check the sign restrictions. (iii) If the restrictions are fulﬁlled, we further check the correlation between the potential policy shock and the high frequency policy instrument. Speciﬁcally, we require that the two policy shocks (which are orthogonal to each other and all other not identi- ﬁed shocks by construction) reveal a signiﬁcant (at a 5 percent level) as well as the two highest absolute and squared correla- tions across all shocks in the model.18 If the correlation restric- tions are not fulﬁlled we draw a new random matrix Q, obtain a new set of transformed, orthogonal shocks and check the sign and correlation restrictions again. (iii) If the restrictions are fulﬁlled, we further check the correlation between the potential policy shock and the high frequency policy instrument. Speciﬁcally, we require that the two policy shocks (which are orthogonal to each other and all other not identi- ﬁed shocks by construction) reveal a signiﬁcant (at a 5 percent level) as well as the two highest absolute and squared correla- tions across all shocks in the model.18 If the correlation restric- tions are not fulﬁlled we draw a new random matrix Q, obtain a new set of transformed, orthogonal shocks and check the sign and correlation restrictions again. (iii) If the restrictions are fulﬁlled, we further check the correlation between the potential policy shock and the high frequency policy instrument. Speciﬁcally, we require that the two policy shocks (which are orthogonal to each other and all other not identi- ﬁed shocks by construction) reveal a signiﬁcant (at a 5 percent level) as well as the two highest absolute and squared correla- tions across all shocks in the model.18 If the correlation restric- tions are not fulﬁlled we draw a new random matrix Q, obtain a new set of transformed, orthogonal shocks and check the sign and correlation restrictions again. In Panel B and C of Fig. 18 Additionally as a minimum threshold we require that the policy shocks and the instrument are correlated by at least 25%. Fig. 7. Impulse response functions to monetary policy shocks (without a linear trend). 5, we see the impulse responses to the decomposed monetary policy shocks where the sign restrictions dis- entangle supply and demand dynamics on the CD market. Again we ﬁnd impulse responses that quantitatively follow the same pattern as in our baseline approach (see Fig. 2). Loan volumes decline in case of CD supply eﬀects, while they increase in case of loan demand eﬀects, consistent with our baseline ﬁndings. (iv) If the correlation restrictions are satisﬁed in addition to the sign restrictions ̃ut bears a structural interpretation and the trans- formed model is saved as part of the restricted posterior distri- bution, which we ﬁnally use for inference. Fig. 7. Impulse response functions to monetary policy shocks (without a linear trend). Fig. 8. Impulse response functions to monetary policy shocks (using ﬁrst log diﬀerences). Fig. 8. Impulse response functions to monetary policy shocks (using ﬁrst log diﬀerences). 8 Economic Modelling 102 (2021) 105559 M. Breitenlechner and J. Scharler Fig. 9. Impulse response functions to monetary policy shocks (using ﬁrst log diﬀerences and no linear trend). Fig. 9. Impulse response functions to monetary policy shocks (using ﬁrst log diﬀerences and no linear trend). through steps (i) and (ii). We repeat steps (i) to (v) until we ﬁnd 1000 model satisfying our set of restrictions. where PP′ = Σe. Using a random orthogonal matrix Q, with Q′Q = I, Σe can also be decomposed as PQQ′P′. Hence, by pre- multiplying the reduced-form system (1) by (PQ)−1, we obtain a transformed set of orthogonal shocks, ̃ut = (PQ)−1et. where PP′ = Σe. Using a random orthogonal matrix Q, with Q′Q = I, Σe can also be decomposed as PQQ′P′. Hence, by pre- multiplying the reduced-form system (1) by (PQ)−1, we obtain a transformed set of orthogonal shocks, ̃ut = (PQ)−1et. In Panel A of Fig. 5 we see the impulse responses to a monetary pol- icy shock identiﬁed using only correlation restrictions and no additional sign restrictions. While the median responses quantitatively follow the pattern of the baseline impulse responses (presented in Fig. 1), we see a substantially higher dispersion of our estimates. In contrast to our base- line identiﬁcation approach, in which we exactly identify the diﬀerent monetary policy shocks, we now are only able to set-identify the policy shocks and thus face model uncertainty in addition to sampling uncer- tainty (see e.g. Fry and Pagan, 2011). Put diﬀerently, we face higher uncertainty in this alternative identiﬁcation approach, as we impose a weaker set of restrictions. (ii) We obtain the impulse responses generated by the transformed model and check whether the imposed sign restrictions are ful- ﬁlled. We impose sign restrictions on impact and in the ﬁrst three periods. If the sign restrictions are not fulﬁlled we draw a new random matrix Q, obtain a new set of transformed, orthogonal shocks and check the sign restrictions. (ii) We obtain the impulse responses generated by the transformed model and check whether the imposed sign restrictions are ful- ﬁlled. We impose sign restrictions on impact and in the ﬁrst three periods. 19 The instruments are still ordered before the policy interest rate and the CD market variables as otherwise the instruments would no longer be exogenous to their endogenous counterparts. 4.3. Alternative speciﬁcations As a ﬁnal set of robustness checks, we re-estimate our baseline model without a linear time trend and include the level variables in ﬁrst log diﬀerences, again with and without a linear time trend. Figs. 7–9 show the impulse responses for these estimations for the overall mone- tary policy shock in Panel A and for the decomposed shocks in Panel B and C. In line with our baseline results, we ﬁnd that loan volumes only decline if supply dynamics dominate the CD market after a monetary policy contraction, while they increase if demand dynamics dominate the CD market. In contrast, credit conditions in general remain loose if a policy shock is associated with demand dynamics on the market for jumbo CDs and the loan volume even increases over the medium run. Thus, although we ﬁnd that the rate at which banks can obtain funding on the jumbo CD market increases unambiguously, the implications for loans and credit conditions more broadly depend on the dynamics on the jumbo CD market. 4.2. Alternative ordering While the policy instrument is constructed based on high frequency interest rate changes, and therefore is generally considered to be exoge- nous, Miranda-Agrippino and Ricco (2021) ﬁnd that high frequency measures are still potentially predictable by other macroeconomic vari- ables. Therefore, we consider an alternative ordering in which the pol- icy instruments are ordered after real GDP, consumer prices, total loan (v) We proceed to the next model if we ﬁnd a transformation that satisﬁes the imposed sign and correlation restrictions, or if a maximum of 2000 transformations are checked, and work 9 Economic Modelling 102 (2021) 105559 M. Breitenlechner and J. Scharler estimate the response of bank loans to monetary policy shocks and take into account that policy shocks give rise to supply as well as demand eﬀects on the market for jumbo CDs. volumes and the excess bond premium.19 Fig. 6 shows very similar impulse responses as compared to our baseline ﬁndings, and thus we conclude that our baseline ﬁndings do not depend on a speciﬁc order- ing of the policy instruments. We ﬁnd that the volume of bank loans declines in response to a con- tractionary policy shock only if the shock generates dynamics on the market for jumbo CDs that are consistent with a reduction of supply on this market. This ﬁnding is consistent with the predictions of the bank lending channel, which emphasizes that banks face funding constraints. 5. Summary Scharler Economic Modelling Economic Modelling 102 (2021) 105559 M. Breitenlechner and J. Scharler Fig. A3 Impulse response functions to a monetary policy shock (using monthly data but without CD market variables for which no data on a monthly frequency is available). Fig. A4 Impulse response functions to monetary policy shocks (Minnesota prior). Fig. A4 Impulse response functions to monetary policy shocks (Minnesota prior). Fig. A4 Impulse response functions to monetary policy shocks (Minnesota prior). 5. Summary The authors (Max Breitenlechner and Johann Scharler) certify that they have no relevant or material ﬁnancial interests that relate to the research described in the paper entitled “Monetary Policy Announce- ments and Bank Lending: Why the Dynamics on Banks’ Reﬁnancing Markets Matter.” The bank lending channel holds that monetary policy shocks deter- mine banks’ funding possibilities and thereby inﬂuence bank lending (see e.g. Kashyap and Stein, 1994, 1995; Bernanke, 2007). In this paper, we contribute to the literature by providing a novel perspective. We Appendix A. Additional Tables and Figures Appendix A. Additional Tables and Figures Table A1 Information criteria Lag (A) IVTotal,t (B) IVCD Supply,t (C) IVCD Demand,t AIC SBIC AIC SBIC AIC SBIC 0 −13.6722 −13.2579 −14.6601 −14.2458 −14.1251 −13.7109 1 −30.7375∗ −28.6661∗ −31.8987 −29.8273∗ −31.3259∗ −29.2545∗ 2 −30.6817 −26.9532 −31.9909 −28.2624 −31.1890 −27.4605 3 −30.5824 −25.1968 −32.0929 −26.7073 −30.9964 −25.6108 4 −30.4773 −23.4346 −32.1629∗ −25.1202 −30.8384 −23.7957 5 −30.1665 −21.4667 −31.9004 −23.2006 −30.6167 −21.9169 6 −30.2689 −19.9120 −31.7992 −21.4422 −30.7614 −20.4045 Notes: The table shows the Akaike information criterion (AIC) and the Schwarz (Bayesian) information criterion (SBIC) for the three baseline estimations using either IVTotal,t, IVCD Supply,t or IVCD Demand,t as the policy instrument. The asterisks indicate the preferred lag length according to the information criteria. Table A1 Information criteria Notes: The table shows the Akaike information criterion (AIC) and the Schwarz (Bayesian) information criterion (SBIC) for the three baseline estimations using either IVTotal,t, IVCD Supply,t or IVCD Demand,t as the policy instrument. The asterisks indicate the preferred lag length according to the information criteria. 10 Economic Modelling 102 (2021) 105559 M. Breitenlechner and J. Scharler Fig. A1 Impulse response functions to monetary policy shocks (p = 1). Fig. A1 Impulse response functions to monetary policy shocks (p = 1). Fig. A1 Impulse response functions to monetary policy shocks (p = 1). Fig. A2 Impulse response functions to monetary policy shocks (p = 4). Fig. A2 Impulse response functions to monetary policy shocks (p = 4). Fig. A2 Impulse response functions to monetary policy shocks (p = 4). Fig. A2 Impulse response functions to monetary policy shocks (p = 4). 11 Breitenlechner and J. Scharler Economic Modelling 102 (2021) 105 Fig. A3 Impulse response functions to a monetary policy shock (using monthly data but without CD market variables for which no data on a monthly frequency is available). hner and J. (10) (10) where Y = [Y1, … , YT]′ and X = [X1, … , XT]′ with Xt = [Yt−1, Yt−2, … , Yt−j]′ (Uhlig, 1994). To refrain from speciﬁc prior assumptions we set N = 0, 𝜈= 0, and thus A = ̂A and S = ̂Σe. As in Uhlig (2005) we use the MLE estimates of Aj and Σe as location parameters of the posterior distribution. where Y = [Y1, … , YT]′ and X = [X1, … , XT]′ with Xt = [Yt−1, Yt−2, … , Yt−j]′ (Uhlig, 1994). To refrain from speciﬁc prior assumptions we set N = 0, 𝜈= 0, and thus A = ̂A and S = ̂Σe. As in Uhlig (2005) we use the MLE estimates of Aj and Σe as location parameters of the posterior distribution. To incorporate a standard Minnesota prior (see e.g. Litterman, 1986) we use an augmented Normal-Wishart prior. Speciﬁcally, we set 𝜈= k + 2 and S to a diagonal matrix with the standard error of an autoregression with p lags of variable i on the main diagonal, where i = 1, … , k. To impose the prior assumption that the ﬁrst own lag of real GDP, CPI, total loans, and CD volumes follow a random walk, we set the corresponding entries in the coeﬃcient matrix A to 1 and all other entries to zero. Furthermore, to render higher lags less informative than more recent lags, we specify Ω as a diagonal matrix, such that the standard deviation of the parameter on lag p of variable i in equation l is 𝜆1𝜎l∕𝜎ip−𝜆2. For the hyperparameters, we set 𝜆 0 2 and 𝜆 2 (see e g Jarocinski and Karadi 2020 for a recent application) The results are based on 8000 Gibbs Sampler iterations To incorporate a standard Minnesota prior (see e.g. Litterman, 1986) we use an augmented Normal-Wishart prior. Speciﬁcally, we set 𝜈= k + 2 and S to a diagonal matrix with the standard error of an autoregression with p lags of variable i on the main diagonal, where i = 1, … , k. To impose the prior assumption that the ﬁrst own lag of real GDP, CPI, total loans, and CD volumes follow a random walk, we set the corresponding entries in the coeﬃcient matrix A to 1 and all other entries to zero. References Am. Econ. J. Macroecon. 11 (1), 157–192. Carpenter, S., Demiralp, S., 2012. Money, reserves, and the transmission of monetary policy: does the money multiplier exist? J. Macroecon. 34 (1), 59–75. Litterman, R.B., 1986. Forecasting with Bayesian vector autoregressions, ﬁve years of experience. J. Bus. Econ. Stat. 4 (1), 25–38. Carpenter, S., Demiralp, S., 2012. Money, reserves, and the transmission of monetary policy: does the money multiplier exist? J. Macroecon. 34 (1), 59–75. Miranda-Agrippino, S., Ricco, G., 2021. The transmission of monetary policy shocks. American Economic Journal (Macroeconomics, forthcoming). Miranda-Agrippino, S., Ricco, G., 2021. The transmission of mon D’Avino, C., 2018. Quantitative easing, global banks and the international bank lending channel. Econ. Modell. 71, 234–246. Nakamura, E., Steinsson, J., 2018. High-frequency identiﬁcation of monetary non-neutrality: the information eﬀect. Q. J. Econ. 133 (3), 1283–1330. Nakamura, E., Steinsson, J., 2018. High-frequency identiﬁcation of monetary non-neutrality: the information eﬀect. Q. J. Econ. 133 (3), 1283–1330. Noh, E., 2020. Impulse-response Analysis with Proxy Variables. Unpublished manuscript. Department of Economics, University of California, San Diego. Paul, P., 2020. The time-varying eﬀect of monetary policy on asset prices. Rev. Econ. Stat. 102 (4), 690–704. Den Haan, W.J., Sumner, S.W., Yamashiro, G.M., 2002. Construction of Aggregate and Regional Bank Data Using the Call Reports: Data Manual. Unpublished manuscript. University of Amsterdam. non-neutrality: the information eﬀect. Q. J. Econ. 133 (3), 1283–1330. Noh, E., 2020. Impulse-response Analysis with Proxy Variables. Unpublished manuscript. Department of Economics, University of California, San Diego. Paul P 2020 The time varying eﬀect of monetary policy on asset prices Rev Econ Noh, E., 2020. Impulse-response Analysis with Proxy Variables. Unpublished manuscript. Department of Economics, University of California, San Diego. Disyatat, P., 2011. The bank lending channel revisited. J. Money Credit Bank. 43 (4), 711–734. Paul, P., 2020. The time-varying eﬀect of monetary policy on asset prices. Rev. Econ. Stat. 102 (4), 690–704. Ellis, D.M., Flannery, M.J., 1992. Does the debt market assess large banks, risk?: time series evidence from money center CDs. J. Monetary Econ. 30 (3), 481–502. 12 Piﬀer, M., Podstawski, M., 2017. Identifying uncertainty shocks using the price of gold. Econ. J. 128 (616), 3266–3284. Faust, J., 1998. The robustness of identiﬁed VAR conclusions about money. Carnegie-Rochester Conf. Ser. Public Policy 49, 207–244. Plagborg-Møller, M., Wolf, C.K., 2021. Local projections and VARs estimate the same impulse responses. Econometrica 89 (2), 955–980. Favara, G., Gilchrist, S., Lewis, K.F., Zakrajsek, E., 2016. (10) Furthermore, to render higher lags less informative than more recent lags, we specify Ω as a diagonal matrix, such that the standard deviation of the parameter on lag p of variable i in equation l is 𝜆1𝜎l∕𝜎ip−𝜆2. For the hyperparameters, we set 𝜆1 = 0.2 and 𝜆2 = 2 (see e.g. Jarocinski and Karadi, 2020, for a recent application). The results are based on 8000 Gibbs Sampler iterations of which the ﬁrst 4000 are dropped as burn-in and every fourth iteration is saved afterwards. Appendix B. Estimation and Inference In our baseline estimations we use the Normal-Wishart distribution as prior density and analytically derive the posterior distribution, which also belongs to the Normal-Wishart family (see e.g. Uhlig, 2005). A Normal-Wishart prior speciﬁes p(Σ−1 e \|S, v) = (S−1, v), (5) p(A\|A, Ω) = (A, Ω), (6) 12 M. Breitenlechner and J. Scharler Economic Modelling 102 (2021) 105559 where is the Wishart distribution, the normal distribution, A the columnwise vectorized form of A = [A1, … , Aj]′ and Ω = Σe ⊗N−1, where N is a positive deﬁnite matrix of size kj × kj and k denotes the number of variables in Yt. Then, the posterior is described by 𝜈= T + 𝜈, (7) N = N + X′X, (8) A = N−1(NA + X′X̂A), (9) S = 𝜈 𝜈S + T 𝜈 ̂Σe + 1 𝜈(̂A −A)′NN−1X′X(̂A −A), (10) where Y = [Y1, … , YT]′ and X = [X1, … , XT]′ with Xt = [Yt−1, Yt−2, … , Yt−j]′ (Uhlig, 1994). To refrain from speciﬁc prior assumptions we set N = 0, 𝜈= 0, and thus A = ̂A and S = ̂Σe. As in Uhlig (2005) we use the MLE estimates of Aj and Σe as location parameters of the posterior distribution. To incorporate a standard Minnesota prior (see e.g. Litterman, 1986) we use an augmented Normal-Wishart prior. Speciﬁcally, we set 𝜈= k + 2 and S to a diagonal matrix with the standard error of an autoregression with p lags of variable i on the main diagonal, where i = 1, … , k. To impose the prior assumption that the ﬁrst own lag of real GDP, CPI, total loans, and CD volumes follow a random walk, we set the corresponding entries in the coeﬃcient matrix A to 1 and all other entries to zero. Furthermore, to render higher lags less informative than more recent lags, we specify Ω as a diagonal matrix, such that the standard deviation of the parameter on lag p of variable i in equation l is 𝜆1𝜎l∕𝜎ip−𝜆2. For the hyperparameters, we set 𝜆1 = 0.2 and 𝜆2 = 2 (see e.g. Jarocinski and Karadi, 2020, for a recent application). The results are based on 8000 Gibbs Sampler iterations of which the ﬁrst 4000 are dropped as burn-in and every fourth iteration is saved afterwards. M. Breitenlechner and J. References Gürkaynak, R.S., Sack, B., Swanson, E.T., 2005. Do actions speak louder than words? The response of asset prices to monetary policy actions and statements. International Journal of Central Banking. Acharya, V.V., Mora, N., 2015. A crisis of banks as liquidity providers. J. Finance 70 (1), 1–43. Heryán, T., Tzeremes, P.G., 2017. The bank lending channel of monetary policy in EU countries during the global ﬁnancial crisis. Econ. Modell. 67, 10–22. Apergis, N., Christou, C., 2015. The behaviour of the bank lending channel when interest rates approach the zero lower bound: evidence from quantile regressions. Econ. Modell. 49, 296–307. Jarocinski, M., 2020. Central Bank Information Eﬀects and Transatlantic Spillovers. Working Paper Series 2482, European Central Bank. Jarocinski, M., Karadi, P., 2020. Deconstructing monetary policy surprises—the role of information shocks. Am. Econ. J. Macroecon. 12 (2), 1–43. h l d k l d k Arias, J.E., Rubio-Ramírez, J.F., Waggoner, D.F., 2018. Inference based on structural vector autoregressions identiﬁed with sign and zero restrictions: theory and applications. Econometrica 86 (2), 685–720. Kashyap, A.K., Stein, J.C., 1994. Monetary policy and Bank lending. In: Mankiw, N.G. (Ed.), Monetary Policy. NBER Chapters. The University of Chicago Press, pp. 221–261. Bernanke, B.S., 2007. The ﬁnancial accelerator and the credit channel. In: Speech Given at the Credit Channel of Monetary Policy in the Twenty-First Century Conference. Federal Reserve Bank of Atlanta. Kashyap, A.K., Stein, J.C., 1995. The impact of monetary policy on bank balance sheets. Carnegie-Rochester Conf. Ser. Public Policy 42, 151–195 0. Bernanke, B.S., Gertler, M., 1995. Inside the black box: the credit channel of monetary policy transmission. J. Econ. Perspect. 9 (4), 27–48. Kashyap, A.K., Stein, J.C., 2000. What do a million observations on banks say about the transmission of monetary policy? Am. Econ. Rev. 90 (3), 407–428. Breitenlechner, M., Scharler, J., Sindermann, F., 2016. Banks’ external ﬁnancing costs and the bank lending channel: results from a SVAR analysis. J. Financ. Stabil. 26, 228–246. Kishan, R.P., Opiela, T.P., 2000. Bank size, bank capital, and the bank lending channel. J. Money Credit Bank. 32 (1), 121–141. Kishan, R.P., Opiela, T.P., 2012. Monetary policy, bank lending, and the risk-pricing channel. J. Money Credit Bank. 44 (4), 573–602. Caldara, D., Herbst, E., 2019. Monetary policy, real activity, and credit spreads: evidence from Bayesian proxy SVARs. Am. Econ. J. Macroecon. 11 (1), 157–192. Caldara, D., Herbst, E., 2019. Monetary policy, real activity, and credit spreads: evidence from Bayesian proxy SVARs. Appendix B. Estimation and Inference Scharler where is the Wishart distribution, the normal distribution, A the columnwise vectorized form of A = [A1, … , Aj]′ and Ω = Σe ⊗N−1, where N is a positive deﬁnite matrix of size kj × kj and k denotes the number of variables in Yt. Then, the posterior is described by 𝜈= T + 𝜈, (7) N = N + X′X, N = N + X′X, A = N−1(NA + X′X̂A), A = N−1(NA + X′X̂A), S = 𝜈 𝜈S + T 𝜈 ̂Σe + 1 𝜈(̂A −A)′NN−1X′X(̂A −A), References Updating the recession risk and the excess bond premium. FEDS Notes Board of Governors of the Federal Reserve System). Ramey, V., 2016. Macroeconomic shocks and their propagation. In: Taylor, J.B., Uhlig, H. (Eds.), Handbook of Macroeconomics. Vol. 2 of Handbook of Macroeconomics, Elsevier, pp. 71–162. Ch. 2. Fry, R., Pagan, A., 2011. Sign restrictions in structural vector autoregressions: a critical review. J. Econ. Lit. 49 (4), 938–960. Rubio-Ramírez, J.F., Waggoner, D.F., Zha, T., 2010. Structural vector autoregressions: theory of identiﬁcation and algorithms for inference. Rev. Econ. Stud. 77 (2), 665–696. Gambacorta, L., 2005. Inside the bank lending channel. Eur. Econ. Rev. 49 (7), 1737–1759. Uhlig, H., 1994. What macroeconomists should know about unit roots: a bayesian perspective. Econom. Theor. 10 (3–4), 645–671. Gambacorta, L., 2008. How do banks set interest rates? Eur. Econ. Rev. 52 (5), 792–819 G b L M Ib D 2011 Th b k l di h l l f h Gambacorta, L., Marques-Ibanez, D., 2011. The bank lending channel: lessons from the crisis. Econ. Pol. 26 (66), 135–182. Uhlig, H., 2005. What are the eﬀects of monetary policy on output? Results from an agnostic identiﬁcation procedure. J. Monetary Econ. 52 (2), 381–419. Gertler, M., Karadi, P., 2015. Monetary policy surprises, credit costs, and economic activity. Am. Econ. J. Macroecon. 7 (1), 44–76. Gilchrist, S., Zakrajsek, E., 2012. Credit spreads and business cycle ﬂuctuations. Am. Econ. Rev. 102 (4), 1692–1720. 13
https://openalex.org/W3198480686	https://zenodo.org/records/5508449/files/RRP_article_68001.pdf	English	null	Antiamnestic effect of new nicotinic acid derivatives	Research results in pharmacology	2,021	cc-by	6,629	Antiamnestic effect of new nicotinic acid derivatives Victor V. Yasnetsov1,3, Diana E. Kaurova2, Sofia Ya. Skachilova1, Evgeniy Yu. Bersenev3 1 All-Union Research Center for Safety of Biologically Active Substances, 23 Kirova St., Staraya Kupavna, Moscow Region 142450, Russia 2 State University of Humanities and Technology, 22 Zelenaya St., Orekhovo-Zuevo, Moscow Region 142611, Russia 3 State Scientific Center of Russian Federation – Institute of Biomedical Problems of the Russian Academy of Sciences, 76A Khoroshevskoe Rd., Moscow 123007, Russia 1 All-Union Research Center for Safety of Biologically Active Substances, 23 Kirova St., Staraya Kupavna, Moscow Region 142450, Russia 2 State University of Humanities and Technology, 22 Zelenaya St., Orekhovo-Zuevo, Moscow Region 142611, Russia 3 State Scientific Center of Russian Federation – Institute of Biomedical Problems of the Russian Academy of Sciences, 76A Khoroshevskoe Rd., Moscow 123007, Russia Corresponding author: Victor V. Yasnetsov (vicyas@yandex.ru) Academic editor: Oleg Gudyrev ♦ Received 28 April 2021 ♦ Accepted 15 June 2021 ♦ Published 7 September 2021 Citation: Yasnetsov VV, Kaurova DE, Skachilova SYa, Bersenev EYu (2021) Antiamnestic effect of new nicotinic acid derivatives. Research Results in Pharmacology 7(3): 15–22. https://doi.org/10.3897/rrpharmacology.7.68001 Citation: Yasnetsov VV, Kaurova DE, Skachilova SYa, Bersenev EYu (2021) Antiamnestic effect of new nicotinic acid derivatives. Research Results in Pharmacology 7(3): 15–22. https://doi.org/10.3897/rrpharmacology.7.68001 Research Results in Pharmacology 7(3): 15–22 UDC: 611.08:615.21:599.3/.8 DOI 10.3897/rrpharmacology.7.68001 Research Results in Pharmacology 7(3): 15–22 UDC: 611.08:615.21:599.3/.8 DOI 10.3897/rrpharmacology.7.68001 Abstract Introduction: The search for new drugs for the prevention and treatment of vascular cognitive disorders continues to be a relevant task of pharmacology. In this regard, the aim of this work is to study the antiamnestic effect of five new nicotin ic acid derivatives in comparison with the well-known drug mexidol (ethylmethylhydroxypyridine succinate) in animals. Materials and methods: The experiments were carried out on white male mice using conditioned passive avoidance reflex (CPAR). Electroconvulsive shock (ECS), scopolamine administration, and acute hypoxia in a hermetic chamber were used as amnesic effects. Testing for the safety of CPAR was performed 24 h after amnesic exposure. The new substances, reference drug mexidol, and a 0.9% sodium chloride solution (control group) were administered once intra peritoneally 60 min before mice training. Results and discussion: Three of the five new nicotinic acid derivatives, LKhT 4-19 (100 mg/kg), LKhT 6-19 (25, 50, and 100 mg/kg), and LKhT 7-19 (100 mg/kg), have antiamnestic properties on models of amnesia in mice induced by ESC, scopolamine, and acute hypoxia in a hermetic chamber. At the same time, the most efficient substance – LKhT 6-19 – exceeds the reference drug mexidol on all three models used. In addition, this compound is also more efficient than two other new compounds, LKhT 4-19 and LKhT 7-19, on the model of ESC-induced amnesia and LKhT 7-19 on the scopolamine-induced amnesia model. Conclusion: Compound LKhT 6-19 is promising for further advanced preclinical studies as a potential drug with antiamnestic activity. Graphical abstract: Keywords amnesia, conditioned passive avoidance reflex, mice, new nicotinic acid derivatives. Introduction Therefore, the aim of this work was to study the an tiamnestic effect of five new nicotinic acid derivatives in comparison with mexidol in animals. The number of patients with ischemic cerebrovascular di seases at present continues to increase in most countries in the world (Skvortsova et al. 2018, Stakhovskaya and Kotov 2018, Mendelson and Prabhakaran 2021). On the one hand, this is due to an increase in life expectancy and the number of elderly people and, on the other hand, to the fact that cerebrovascular disorders occur in employable and socially active middle-aged people more and more frequently, being among the leading causes of partial or complete disability (Tabeeva 2019a, Putaala 2020).i Animals The experiments were carried out on 1033 white male BALB/c mice weighing 20–24 g (Andreevka Nursery, Branch of the Scientific Center of Biomedical Tech nologies of the Federal Medical-Biological Agency of Russia, Moscow Region, Russia). The care for animals and conducting experiments were in compliance with Order No. 199n of the Ministry of Health of the Rus sian Federation of April 1, 2016 ”On Approval of the Rules of Good Laboratory Practice”. The experiments were approved by the Bioethics Commission of the All-Union Research Center for Safety of Biologically Active Substances (Minutes No. 20/2020 of September 21, 2020). A significant contribution to the disablement of pa tients with this pathology is made by cognitive disor ders that are diverse in severity and clinical manifesta tions (Belskaya et al. 2016, Parfenov 2019, Kotov et al. 2020, Frantellizzi et al. 2021), ranging from mild forms to dementia. In addition, patients with moderate post- stroke cognitive impairment may suffer a wide range of disorders, including memory loss (Kulesh and Shestak ov 2016). This leads to the deterioration in life quality, a violation of a person’s domestic, social and professional activity, and sometimes to complete dependence on oth ers (Bogolepova and Levin 2020). Graphical abstract: Copyright Yasnetsov VV et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Graphical abstract: Copyright Yasnetsov VV et al. This is an open access article distributed under the terms of the Creative Commons Attribution Lice unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. etsov VV et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permi e, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright Yasnetsov VV et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Yasnetsov VV et al.: Antiamnestic effect of new nicotinic acid derivatives 16 Keywords The effect of new nicotinic acid derivatives on the mo del of electroconvulsive shock-induced amnesia in mice It was found that the majority (87%; p < 0.001) of the mice had retrograde amnesia of conditioned passive avoi dance reflex 24 h after exposure to ECS (Table 2). The new nicotinic acid derivative LKhT 4-19 at a dose of 25 mg/kg did not significantly affect amnesia of CPAR, and at doses of 50 and 100 mg/kg significantly weak ened the amnesic effect by 1.5 (p < 0.05) and 2.7 times (p < 0.001), respectively.fi Another new substance, LKhT 6-19, was efficient in all three doses tested. Thus, it significantly (p < 0.001) reduced the severity of amnesia at a dose of 25 mg/kg by 3.1 times and at doses of 50 and 100 mg/kg completely prevented amnesia development. Substances and reference drug It should also be noted that cognitive impairment de velops as a result of ischemic brain damage in the severe course of the new coronavirus infection COVID-19 (Min ers et al. 2020). Five new nicotinic acid derivatives synthesized at the Department of Chemistry and Technology of Synthetic Drugs and Analytical Control of the All-Union Research Center for Safety of Biologically Active Substances (Rus sia) were studied. The chemical names of the compounds are given in Table 1. Despite the improvement of pharmacotherapy of vas cular cognitive impairments, the majority of the drugs used today are either insufficiently efficient or cause a number of side effects that limit their long-term and wide spread use (Sun 2018, Van der Flier et al. 2018, Tabee va 2019b). Therefore, the search for new drugs for the prevention and treatment of vascular cognitive disorders continues to be relevant. Table 1. New Nicotinic Acid Derivatives Table 1. New Nicotinic Acid Derivatives Laboratory code Chemical name LKhT 4-19 Bis (-2-aminium ethanesulfonate magnesium)-3- pyridinecarbonoate LKhT 6-19 Magnesium-bis(-3-pyridinecarbonoate) LKhT 7-19 3-pyridinecarboxamide-2-aminoethanesulfonic acid LKhT 9-19 5-bromo-3-pyridinecarboxamide-2-amino-5-ethyl-1,3,4- thiadiazole LKhT 13-19 3-pyridinecarboxamide-2-amino-5-methylpyridine Therefore, our focus was on new nicotinic acid de rivatives. As is known, nicotinic acid has been widely used since the middle of the XX century as a drug that has anti-inflammatory, hypolipidemic, anti-atherogenic, neuroprotective, and vasodilating effects, including those on brain vessels, as well as other valuable pharmacolog ical properties (Gasperi et al. 2019, Sharma and Madan 2019). However, presently nicotinic acid is not used for pharmacotherapy of cerebrovascular diseases and their consequences due to severe side effects.i All the substances are white microcrystalline pow ders with a slight odor. The compounds were dissolved in a 0.9% sodium chloride (NaCl) solution. In the case of insufficient solubility of substances, 1–2 droplets of Tween-80 were added to the solutions. We have previously shown that one of the five new nicotinic acid derivatives, LKhT 6-19, was the most effi cient on a model of acute hypoxia in a hermetic chamber in mice. This derivative provided an action depending on the dose, surpassing the severity of the effect of the well- known domestic drug mexidol (Yasnetsov et al. 2020). We used mexidol (ethylmethylhydroxypyridine succi nate, in the form of substance; “Pharmasoft”, Russia) as a reference drug. Statistical analysis ) The CPAR production in mice was carried out on the basis of electrocutaneous reinforcement according to the method by Cumin et al. (1982) taking into account the recommendations by Mondadori et al. (1990). The tests were conducted in an experimental black chamber 30×40×30 cm in size, with an electrode floor and a white plastic platform (7.5×7.5×0.5 cm), which was placed on the floor in the center of the chamber. The mice were placed onto the plastic platform, one at a time. Usually, the animals descended or jumped from the platform onto the electrode floor, where they were subjected to an elec tric shock as a “punishment” (at that time, direct electric current of 0.5 mA was applied to the floor of the cham ber). The electric current was switched on only when the mouse touched the floor with all four limbs. The usual reaction of the animals was to return to the safe platform. After 5 min of training, the mice developed CPAR: they remained on the platform. Testing for the retention of CPAR was performed 24 h after the amnesic exposure. But if the animal left the platform within 1 min, it was registered as having retrograde amnesia of CPAR. Statistic processing of the obtained data was performed using BioStat 2009 Professional software by the nonpara metric method, Fisher’s exact test. The differences were considered statistically significant at p < 0.05. Experimental methods The choice of doses of the studied compounds was dic tated by the results of previous experiments, in particular, to study their antihypoxic activity (Yasnetsov et al. 2020). The antiamnestic effect of new nicotinic acid derivatives was studied in mice using the conditioned passive avoi dance reflex (CPAR) of electrocutaneous irritation (Voro nina et al. 2012). Substances and reference drug This is a derivative of 3-hydroxypyridine, which, like the studied substances, contains the pyridine 17 Research Results in Pharmacology 7(3): 15–22 heterocycle in its structure and is also widely used today in neurology in the treatment of vascular cognitive disor ders (Voronina 2016). 15-min stay of mice in a hermetic 200-cm3 chamber) were used as amnesic effects. 15-min stay of mice in a hermetic 200-cm3 chamber) were used as amnesic effects. New nicotinic acid derivatives, reference drug mexidol, and a 0.9% NaCl solution (control group) were adminis tered once intraperitoneally 60 min before mice training. Note: differences are significant compared to control 1 and control 2 groups of animals, respectively: ° or * – р < 0.05, °° or – р < 0.01, °°° or * – р < 0.001. Differences between LKhT 6-19 and: mexidol in similar doses: # – p < 0.05; LKhT 4-19 at a dose of 50 mg/kg: && – р < 0.01; LKhT 7-19 at a dose of 100 mg/kg: §§ – р < 0.01 (Fisher’s exact test). es are significant compared to control 1 and control 2 groups of animals, respectively: ° or * – р < 0.05, °° or – р < 0.01, °°° or * – р < 0.00 ween LKhT 6-19 and: mexidol in similar doses: # – p < 0.05; LKhT 4-19 at a dose of 50 mg/kg: && – р < 0.01; LKhT 7-19 at a dose of 100 mg/k isher’s exact test). Note: differences are significant compared to control 1 and control 2 groups of animals, respectively: ° or * – р < 0.05, °° or – р < 0.01, °°° or * – р < 0.001. Differences between LKhT 6-19 and: mexidol in similar doses: # – p < 0.05; LKhT 4-19 at a dose of 50 mg/kg: && – р < 0.01; LKhT 7-19 at a dose of 100 mg/kg: Results and discussion The effect of new nicotinic acid derivatives on the mo del of electroconvulsive shock-induced amnesia in mice The effect of new nicotinic acid derivatives on the mo del of electroconvulsive shock-induced amnesia in mice The compound LKhT 6-19 as in the previous model of amnesia was efficient in all three tested doses: it signifi cantly (p < 0.001) weakened the amnesic effect at a dose of 25 mg/kg by 3.0 times and at doses of 50 and 100 mg/ kg completely prevented its development. The reference drug mexidol had antiamnestic properties in all three tested doses: at doses of 25 and 50 mg/kg it sig nificantly reduced the severity of amnesia by 1.4 (p < 0.05) and 2.2 times (p < 0.001), respectively, and at a dose of 100 mg/kg almost completely prevented its development.f LKhT 7-19 at doses of 25 and 50 mg/kg did not sig nificantly affect the severity of amnesia and at a dose of 100 mg/kg significantly (p < 0.05) reduced it by 1.8 times. In terms of the severity of the antiamnestic effect, LKhT 6-19 at doses of 25 and 50 mg/kg significantly (p < 0.05) exceeded mexidol at similar doses by 2.1 and 2.7 times, respectively, and at a dose of 50 mg/kg acted in the same way as mexidol at a dose of 100 mg/kg. In addition, LKhT 6-19 at doses of 50 and 100 mg/kg significantly (p < 0.01) exceeded LKhT 7-19 at a dose of 100 mg/kg by 3.8 and 4.8 times, respectively, and at a dose of 50 mg/kg exceed ed LKhT 4-19 at a similar dose by 3.8 times.i The substances LKhT 9-19 and LKhT 13-19 (25, 50, and 100 mg/kg) were inefficient. The reference drug mexidol had an antiamnestic ef fect at doses of 50 and 100 mg/kg, at the first dose sig nificantly reducing the severity of amnesia by 1.9 times (p < 0.001) and at the second dose completely prevent ing its development. At a dose of 25 mg/kg this drug was inefficient.f Therefore, three of the five new nicotinic acid deriv atives, LKhT 4-19 (50 and 100 mg/kg), LKhT 6-19 (25, 50, and 100 mg/kg), and LKhT 7-19 (100 mg/kg), have antiamnestic properties on the model of ECS-induced amnesia in mice. At the same time, the most efficient sub stance LKhT 6-19 is superior in the intensity of the action to both the well-known drug mexidol and two other new compounds, LKhT 4-19 and LKhT 7-19. The effect of new nicotinic acid derivatives on the mo del of electroconvulsive shock-induced amnesia in mice The electroconvulsive shock (ECS; electric current parameters: 50 Hz, 50 mA, 0.3 s), administration of sco polamine (Sigma-Aldrich) at a dose of 1 mg/kg intraperi toneally, and acute hypoxia in a hermetic chamber (13– ffect of New Nicotinic Acid Derivatives and the Reference Drug Mexidol on Amnesia in Mice Induced by Electro ck (ECS) convulsive Shock (ECS) Experimental conditions and substance (dose, mg/kg) Total number of mice Number of mice trained of conditioned passive avoidance reflex (%) Number of mice with amnesia in passive avoidance test 24 h after exposure to ECS (%) 0.9% NaCl solution + false ECS (control 1) 25 24 (96) 4 (17) 0.9% NaCl solution + ECS (control 2) 25 24 (96) 21 (87)°°° LKhT 4-19 (25) + ECS 15 14 (93) 9 (64)°° LKhT 4-19 (50) + ECS 15 14 (93) 8 (57)* LKhT 4-19 (100) + ECS 20 19 (95) 6 (32)* LKhT 6-19 (25) + ECS 19 18 (95) 5 (28)# LKhT 6-19 (50) + ECS 27 26 (96) 4 (15)#&&§§ LKhT 6-19 (100) + ECS 27 26 (96) 3 (12)§§ LKhT 7-19 (25) + ECS 12 11 (92) 8 (73)°° LKhT 7-19 (50) + ECS 12 11 (92) 7 (64)°° LKhT 7-19 (100) + ECS 15 14 (93) 8 (57) LKhT 9-19 (25) + ECS 10 9 (90) 7 (78)°° LKhT 9-19 (50) + ECS 10 9 (90) 6 (67)° LKhT 9-19 (100) + ECS 15 14 (93) 9 (64)°° LKhT 13-19 (25) + ECS 10 9 (90) 6 (67)° LKhT 13-19 (50) + ECS 10 9 (90) 6 (67)° LKhT 13-19 (100) + ECS 15 14 (93) 9 (64)° Mexidol (25) + ECS 21 20 (95) 12 (60)* Mexidol (50) + ECS 26 25 (96) 10 (40)* Mexidol (100) + ECS 20 19 (95) 4 (21)* 18 Yasnetsov VV et al.: Antiamnestic effect of new nicotinic acid derivatives The new nicotinic acid derivative LKhT 4-19 at doses of 25 and 50 mg/kg did not significantly affect the sever ity of amnesia and at a dose of 100 mg/kg significantly (p < 0.001) reduced it by 3.0 times. The compound LKhT 7-19 at doses of 25 and 50 mg/ kg did not significantly affect amnesia of CPAR and at a dose of 100 mg/kg significantly (p < 0.05) weakened the amnesic effect by 1.5 times. Two other new substances, LKhT 9-19 and LKhT 13- 19 (25, 50, and 100 mg/kg), were inefficient. The effect of new nicotinic acid derivatives on the mo del of electroconvulsive shock-induced amnesia in mice In terms of the intensity of the antiamnestic effect, LKhT 6-19 at doses of 25 and 50 mg/kg significantly (p < 0.05) exceeded mexidol at similar doses by 2.2 and 2.6 times, respectively, and at a dose of 50 mg/kg acted as mexidol at a dose of 100 mg/kg. In addition, LKhT 6-19 at a dose of 100 mg/kg significantly (p ≤ 0.05) exceeded LKhT 7-19 at a similar dose.i Therefore, three of the five new nicotinic acid deriva tives, LKhT 4-19 (100 mg/kg), LKhT 6-19 (25, 50, and 100 mg/kg), and LKhT 7-19 (100 mg/kg), have the an tiamnestic properties on the model of scopolamine-in duced amnesia in mice. At the same time, the most effi cient substance LKhT 6-19 is superior in the intensity of the action to both mexidol and LKhT 7-19. Note: differences are significant compared to control 1 and control 2 groups of animals, respectively: ° or * – р < 0.05, °° or – р < 0.01, °°° or * – р < 0.001. Differences between LKhT 6-19 and: mexidol in similar doses: # – p < 0.05; LKhT 7-19 at a dose of 100 mg/kg: § – р ≤ 0.05 (Fisher’s exact test). The effect of new nicotinic acid derivatives on the mo del of scopolamine-induced amnesia in mice The effect of new nicotinic acid derivatives on the mo del of scopolamine-induced amnesia in mice It was shown that the majority (79%; p < 0.001) of mice had retrograde amnesia of CPAR 24 h after scopolamine administration (Table 3). Effect of New Nicotinic Acid Derivatives and the Reference Drug Mexidol on Scopolamine-induced Amnesia in Mice Table 3. The Effect of New Nicotinic Acid Derivatives and the Reference Drug Mexidol on Scopolamine induced Amnesia in Mice Experimental conditions and substance (dose, mg/kg) Total number of mice Number of mice trained of conditioned passive avoidance reflex (%) Number of mice with amnesia in passive avoidance test 24 h after scopolamine administration (%) 0.9% NaCl solution + 0.9% NaCl solution (control 1) 26 25 (96) 4 (16) 0.9% NaCl solution + scopolamine (control 2) 25 24 (96) 19 (79)°°° LKhT 4-19 (25) + scopolamine 12 11 (92) 6 (55)° LKhT 4-19 (50) + scopolamine 15 14 (93) 7 (50)° LKhT 4-19 (100) + scopolamine 20 19 (95) 5 (26)* LKhT 6-19 (25) + scopolamine 20 19 (95) 5 (26)# LKhT 6-19 (50) + scopolamine 26 25 (96) 4 (16)# LKhT 6-19 (100) + scopolamine 24 23 (96) 3 (13)§ LKhT 7-19 (25) + scopolamine 12 11 (92) 7 (64)°° LKhT 7-19 (50) + scopolamine 15 14 (93) 7 (50)° LKhT 7-19 (100) + scopolamine 15 14 (93) 6 (43) LKhT 9-19 (25) + scopolamine 10 9 (90) 6 (67)°° LKhT 9-19 (50) + scopolamine 10 9 (90) 5 (56)° LKhT 9-19 (100) + scopolamine 15 14 (93) 7 (50)° LKhT 13-19 (25) + scopolamine 10 9 (90) 5 (56)° LKhT 13-19 (50) + scopolamine 12 11 (92) 6 (55)° LKhT 13-19 (100) + scopolamine 15 14 (93) 7 (50)° Mexidol (25) + scopolamine 20 19 (95) 11 (58)°° Mexidol (50) + scopolamine 25 24 (96) 10 (42) Mexidol (100) + scopolamine 20 19 (95) 3 (16)* Research Results in Pharmacology 7(3): 15–22 19 Table 4. The Effect of New Nicotinic Acid Derivatives and the Reference Drug Mexidol on Amnesia in Mice Induced by Acute Hypoxia in the Hermetic Chamber ffect of New Nicotinic Acid Derivatives and the Reference Drug Mexidol on Amnesia in Mice Induced by Acute Hermetic Chamber Table 4. The effect of new nicotinic acid derivatives on the mo del of scopolamine-induced amnesia in mice The effect of new nicotinic acid derivatives on the mo del of amnesia in mice induced by acute hypoxia in the hermetic chamber acute hypoxia in a hermetic chamber. At the same time, the most efficient substance LKhT 6-19 exceeds mexidol by the intensity of the action. Our results obtained on the antiamnestic activity in new nicotinic acid derivatives are indirectly confirmed by the literature data. For example, it was shown that the new Russian drug ampasse (calcium salt of N-(5-hydroxy-nic otinoyl)-L-glutamic acid) at a dose of 5–20 mg/kg had the antiamnestic properties on models of amnesia induced by ECS or scopolamine in rats (Kiselev et al. 2011). It was found that on the model of amnesia in mice induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine, the early nicotinamide administration (2–12 h after amnesic expo sure) was able to reduce the severity of memory disorders. However, the delayed administration of nicotinamide re sulted in decreased effects (Yang et al. 2004). It was demonstrated that the majority (71%, p < 0.001) of mice had retrograde amnesia of CPAR 24 h after the 13–15- min stay of the animals in the hermetic chamber (Table 4). It was demonstrated that the majority (71%, p < 0.001) of mice had retrograde amnesia of CPAR 24 h after the 13–15- min stay of the animals in the hermetic chamber (Table 4). LKhT 4-19 at doses of 25 and 50 mg/kg did not signif icantly affect amnesia of CPAR and at a dose of 100 mg/ kg significantly weakened the amnesic effect by 2.7 times (p < 0.01). LKhT 4-19 at doses of 25 and 50 mg/kg did not signif icantly affect amnesia of CPAR and at a dose of 100 mg/ kg significantly weakened the amnesic effect by 2.7 times (p < 0.01). LKhT 6-19 as in the two previous models of amnesia was efficient in all three tested doses. Thus, it significantly (p < 0.01) reduced the severity of amnesia at a dose of 25 mg/kg by 3.4 times and at doses of 50 and 100 mg/kg completely prevented its development. LKhT 7-19 at doses of 25 and 50 mg/kg did not signif icantly affect amnesia of CPAR and at a dose of 100 mg/ kg significantly (p < 0.05) weakened the amnesic effect by 2.0 times. The effect of new nicotinic acid derivatives on the mo del of scopolamine-induced amnesia in mice The Effect of New Nicotinic Acid Derivatives and the Reference Drug Mexidol on Amnesia in Mice Induced by Acute Hypoxia in the Hermetic Chamber Experimental conditions and substance (dose, mg/kg) Total number of mice Number of mice trained of conditioned passive avoidance reflex (%) Number of mice with amnesia in passive avoidance test 24 h after hypoxia (%) 0.9% NaCl solution + false hypoxia (control 1) 25 24 (96) 4 (17) 0.9% NaCl solution + hypoxia (control 2) 25 24 (96) 17 (71)°°° LKhT 4-19 (25) + hypoxia 15 14 (93) 7 (50)° LKhT 4-19 (50) + hypoxia 15 14 (93) 6 (43) LKhT 4-19 (100) + hypoxia 20 19 (95) 5 (26) LKhT 6-19 (25) + hypoxia 20 19 (95) 4 (21)# LKhT 6-19 (50) + hypoxia 24 23 (96) 4 (17)* LKhT 6-19 (100) + hypoxia 24 23 (96) 3 (13)* LKhT 7-19 (25) + hypoxia 12 11 (92) 6 (54)° LKhT 7-19 (50) + hypoxia 12 11 (92) 5 (45) LKhT 7-19 (100) + hypoxia 15 14 (93) 5 (36)* LKhT 9-19 (25) + hypoxia 10 9 (90) 6 (67)° LKhT 9-19 (50) + hypoxia 10 9 (90) 6 (67)° LKhT 9-19 (100) + hypoxia 15 14 (93) 8 (57)° LKhT 13-19 (25) + hypoxia 10 9 (90) 6 (67)° LKhT 13-19 (50) + hypoxia 10 10 (90) 5 (50) LKhT 13-19 (100) + hypoxia 15 14 (93) 6 (43) Mexidol (25) + hypoxia 20 19 (95) 10 (53)° Mexidol (50) + hypoxia 20 19 (95) 4 (21) Mexidol (100) + hypoxia 20 19 (95) 3 (16)* Note: differences are significant compared to control 1 and control 2 groups of animals, respectively: ° or * – р < 0.05, °° or – р < 0.01, °°° or * – р < 0.001; # – p < 0.05 - differences between LKhT 6-19 and mexidol at similar doses are significant (Fisher’s exact test). Note: differences are significant compared to control 1 and control 2 groups of animals, respectively: ° or * – р < 0.05, °° or – р < 0.01, °°° or * – р < 0.001; # – p < 0.05 - differences between LKhT 6-19 and mexidol at similar doses are significant (Fisher’s exact test). References Akhundov RA, Zagorevskiĭ VA, Voronina TA (1990) Nootropic activity of nicotinamide and its structural analogs. Bulletin of Ex perimental Biology and Medicine [Biulleten’ Eksperimental’noĭ Biologii i Meditsiny] 110(10): 384–386. https://doi.org/10.1007/ BF00842287 [PubMed] [in Russian] Fu L, Liu C, Chen L, Lv Y, Meng G, Hu M, Long Y, Hong H, Tang S (2019) Protective effects of 1-methylnicotinamide on Aβ 1-42-in duced cognitive deficits, neuroinflammation and apoptosis in mice. Journal of Neuroimmune Pharmacology: the official journal of the Society on NeuroImmune Pharmacology 14(3): 401–412. https:// doi.org/10.1007/s11481-018-09830-1 [PubMed] Belskaya GN, Chuprina SE, Vorobyev AA, Gorozha EN, Butorak ina TL, Sokolov MA, Izmaylov IA (2016) Cognitive disorders in stroke patients: the possibilities of pharmacological correction. S.S. Korsakov Journal of Neurology and Psychiatry [Zhurnal Nev rologii i Psikhiatrii im. S.S. Korsakova] 116(5): 33–37. https://doi. org/10.17116/jnevro20161165133-37 [in Russian] Gasperi V, Sibilano M, Savini I, Catani MV (2019) Niacin in the central nervous system: an update of biological aspects and clinical applications. International Journal of Molecular Sciences 20(4): 974. https://doi.org/10.3390/ijms20040974 [PubMed] [PMC] Hosseini L, Farokhi-Sisakht F, Badalzadeh R, Khabbaz A, Mah moudi J, Sadigh-Eteghad S (2019) Nicotinamide mononucleotide and melatonin alleviate aging-induced cognitive impairment via modulation of mitochondrial function and apoptosis in the prefron tal cortex and hippocampus. Neuroscience 423: 29–37. https://doi. org/10.1016/j.neuroscience.2019.09.037 [PubMed] Bogolepova AN, Levin OS (2020) Cognitive rehabilitation of pa tients with focal brain damage. S.S. Korsakov Journal of Neurology and Psychiatry [Zhurnal Nevrologii i Psikhiatrii im. S.S. Korsakova] 120(4): 115–122. https://doi.org/10.17116/jnevro2020120041115 [PubMed] [in Russian] Kiselev AV, Stovbun SV, Sergienko VI (2011) Study of the nootropic effects of D- and L-isomers of N-(5-hydroxynicotinoyl)-glutamic acid. Bulletin of the Moscow State Regional University. Series: Nat ural Sciences [Vestnik Moskovskogo Gosudarstvennogo Oblastnogo Universiteta. Seriya: Estestvennye Nauki] 2: 47–49. [in Russian] Chandrasekaran K, Choi J, Arvas MI, Salimian M, Singh S, Xu S, Gullapalli RP, Kristian T, Russell JW (2020) Nicotinamide mononu cleotide administration prevents experimental diabetes-induced cog nitive impairment and loss of hippocampal neurons. International Journal of Molecular Sciences 21(11): 3756. https://doi.org/10.3390/ ijms21113756 [PubMed] [PMC] Kotov SV, Isakova EV, Zaitseva EV, Egorova YuV (2020) Multi modal stimulation in the neurorehabilitation of patients with post stroke cognitive impairment. S.S. Korsakov Journal of Neurology and Psychiatry [Zhurnal Nevrologii i Psikhiatrii im. S.S. Korsakova] 120(5): 125–130. Conclusion Nicotinamide mononucleotide (100 mg/kg for 28 every other day) alleviates aging-induced memory impairment in rats of 24 months old (Hosseini et al. 2019). Nicotinamide mononucleotide (100 mg/kg for 28 every other day) alleviates aging-induced memory impairment in rats of 24 months old (Hosseini et al. 2019). To conclude, three of the five new nicotinic acid deri vatives, LKhT 4-19 (100 mg/kg), LKhT 6-19 (25, 50, and 100 mg/kg), and LKhT 7-19 (100 mg/kg), have the antiamnestic properties on the models of amnesia in mice induced by ESC, scopolamine, and acute hypoxia in a hermetic chamber. At the same time, the most ef ficient substance – LKhT 6-19 – exceeds the reference drug mexidol in terms of the intensity of its action on all the models used. In addition, the latter is also more efficient than the two other new compounds, LKhT 4-19 and LKhT 7-19, on the model of ESC-induced amnesia and LKhT 7-19 on the scopolamine-induced amnesia model. The results from animal and human interventional studies and epidemiological research suggest that nico tinamide may be beneficial in preserving and enhancing the neurocognitive functions (Rennie et al. 2015). The presence of nootropic activity not only in nicotinamide, but also in its structural analogues was previously report ed (Akhundov et al. 1990). As for drugs created on the basis of nicotinic acid, as far back as a few decades ago picamilon (nicotinoyl gam ma-aminobutyric acid) was found to have the antiamnes tic properties on various models of amnesia in animals (Voronina et al. 1987). Moreover, it was found in clinical studies involving patients with hypertensive dyscirculato ry encephalopathy that the inclusion of picamilon in com plex therapy contributed to the improvement of cognitive activity (Povetkin et al. 2009). Therefore, LKhT 6-19 is promising for further ad vanced preclinical studies as a potential drug with antiam nestic activity. Under the similar experimental conditions, it was shown that the calcium channel blocker nimodipine, a derivative of pyridindicarboxylic acid close to nicotin ic acid, had the antiamnestic properties on the model of ESC-induced amnesia in rats (Zupan et al. 1996). Authors declare no conflict of interest. Authors declare no conflict of interest. The effect of new nicotinic acid derivatives on the mo del of scopolamine-induced amnesia in mice It was also shown that 1-methylnicotinamide known as the main metabolite of nicotinamide, with intragastric ad ministration at 100 or 200 mg/kg for 3 weeks significantly reversed the bilateral intrahippocampal injection of be ta-amyloid Aβ1-42-induced or lipopolysaccharide-induced cognitive impairments in mice in the Morris water maze, Y-maze, and Novel object recognition tests. In addition, 1-methylnicotinamide suppressed neuroinflammation, decreased the expression of IL-6, TNF-α and protein of nuclear factor-kappa B p65 (NF-κB p65), and the activa tion of microglia and astrocytes in the hippocampus and frontal cortex, as well as attenuated neuronal apoptosis (Fu et al. 2019, Mu et al. 2019). Two other new compounds, LKhT 9-19 and LKhT 13- 19 (25, 50, and 100 mg/kg), were inefficient. The reference drug mexidol had the antiamnestic activity at doses of 50 and 100 mg/kg, almost completely or com pletely preventing the development of amnesia, and at a dose of 25 mg/kg it did not significantly affect amnesia severity.f In terms of the intensity of the antiamnestic effect, LKhT 6-19 at a dose of 25 mg/kg significantly (p < 0.05) exceeded mexidol at a similar dose by 2.5 times, acting as mexidol at a dose of 50 mg/kg, whereas at a dose of 50 mg/kg it acted as mexidol at a dose of 100 mg/kg.i More recently, it was found that nicotinamide mono nucleotide (intraperitoneally 100 mg/kg on alternate days for 3 months) can prevent diabetes-induced memory defi cits and the loss of CA1 neurons, although it had no sig nificant effect on hyperglycemic control in rats with strep tozotocin-induced diabetes (Chandrasekaran et al. 2020). Therefore, three of the five new nicotinic acid deriva tives, LKhT 4-19 (100 mg/kg), LKhT 6-19 (25, 50, and 100 mg/kg), and LKhT 7-19 (100 mg/kg), exhibit the an tiamnestic properties on the model of amnesia induced by Yasnetsov VV et al.: Antiamnestic effect of new nicotinic acid derivatives 20 References org/10.21687/0233-528X-2020-54-5-73-76 [in Russian] Skvortsova VI, Shetova IM, Kakorina EP, Kamkin EG, Boiko EL, Alekyan BG, Ivanova GE, Shamalov NA, Dashyan VG, Krylov VV (2018) Results of implementation of a “Complex of measures to im prove medical care for patients with stroke in the Russian Federa tion. S.S. Korsakov Journal of Neurology and Psychiatry [Zhurnal Zupan G, Vitezić D, Mrsić J, Matesić D, Simonić A (1996) Effects of nimodipine, felodipine and amlodipine on electroconvulsive shock-induced amnesia in the rat. European Journal of Pharmacology 310(2–3): 103–106. https://doi.org/10.1016/0014-2999(96)00534-1 [PubMed] Stakhovskaya LV, Kotov SV (2018) Stroke: a Guide for Doctors [Insul’t: Rukovodstvo dlya Vrachei]. Medical Information Agency, Moscow, 487 pp. [in Russian] References https://doi.org/10.17116/jnevro2020120051125 [PubMed] [in Russian] Cumin R, Bandle EF, Gamzu E, Haefely WE (1982) Effects of the novel compound aniracetam (Ro 13-5057) upon impaired learn ing and memory in rodents. Psychopharmacology 78(2): 104–111. https://doi.org/10.1007/BF00432244 [PubMed] Frantellizzi V, Conte M, De Vincentis G (2021) Hybrid imaging of vas cular cognitive impairment. Seminars in Nuclear Medicine 51(3): 286– 295. https://doi.org/10.1053/j.semnuclmed.2020.12.006 [PubMed] Kulesh AA, Shestakov VV (2016) Post-stroke cognitive impairment and the possibility of treatment with cellex. S.S. Korsakov Jour Kulesh AA, Shestakov VV (2016) Post-stroke cognitive impairment and the possibility of treatment with cellex. S.S. Korsakov Jour Research Results in Pharmacology 7(3): 15–22 21 nal of Neurology and Psychiatry [Zhurnal Nevrologii i Psikhiatrii im. S.S. Korsakova] 116(5): 38–42. https://doi.org/10.17116/jnev ro20161165138-42 [PubMed] [in Russian] nal of Neurology and Psychiatry [Zhurnal Nevrologii i Psikhiatrii im. S.S. Korsakova] 116(5): 38–42. https://doi.org/10.17116/jnev ro20161165138-42 [PubMed] [in Russian] Sun MK (2018) Potential therapeutics for vascular cognitive impair ment and dementia. Current Neuropharmacology 16(7): 1036–1044. https://doi.org/10.2174/1570159X15666171016164734 [PubMed] Sun MK (2018) Potential therapeutics for vascular cognitive impair ment and dementia. Current Neuropharmacology 16(7): 1036–1044. https://doi.org/10.2174/1570159X15666171016164734 [PubMed] Mendelson SJ, Prabhakaran S (2021) Diagnosis and management of transient ischemic attack and acute ischemic stroke: a review. JAMA 325(11): 1088–1098. https://doi.org/10.1001/jama.2020.26867 [PubMed] Tabeeva GR (2019a) Neurocognitive aging and cognitive disorders. S.S. Korsakov Journal of Neurology and Psychiatry [Zhurnal Nev rologii i Psikhiatrii im. S.S. Korsakova] 119(6): 160–167. https://doi. org/10.17116/jnevro2019119061160 [PubMed] [in Russian] Tabeeva GR (2019b) Mild cognitive impairment: what’s next? S.S. Korsakov Journal of Neurology and Psychiatry [Zhurnal Nevrologii i Psikhiatrii im. S.S. Korsakova] 119(10): 103–110. https://doi. org/10.17116/jnevro2019119101103 [PubMed] [in Russian] Miners S, Kehoe PG, Love S (2020) Cognitive impact of COVID-19: looking beyond the short term. Alzheimer’s Research & Therapy 12(1): 170. https://doi.org/10.1186/s13195-020-00744-w [PubMed] [PMC] Miners S, Kehoe PG, Love S (2020) Cognitive impact of COVID-19: looking beyond the short term. Alzheimer’s Research & Therapy 12(1): 170. https://doi.org/10.1186/s13195-020-00744-w [PubMed] [PMC] Van der Flier WM, Skoog I, Schneider JA, Pantoni L, Mok V, Chen CLH, Scheltens P (2018) Vascular cognitive impairment. Na ture Reviews. Disease Primers 4: 18003. https://doi.org/10.1038/ nrdp.2018.3 [PubMed] Mondadori C, Bhatnagar A, Borkovski J, Häusler A (1990) Involve ment of a steroidal component in the mechanism of action of pirac etam-like nootropics. Brain Research 506(1): 101–108. https://doi. References org/10.1016/0006-8993(90)91204-T [PubMed] Mondadori C, Bhatnagar A, Borkovski J, Häusler A (1990) Involve ment of a steroidal component in the mechanism of action of pirac etam-like nootropics. Brain Research 506(1): 101–108. https://doi. org/10.1016/0006-8993(90)91204-T [PubMed] Mu RH, Tan YZ, Fu LL, Nazmul Islam M, Hu M, Hong H, Tang SS (2019) 1-Methylnicotinamide attenuates lipopolysaccharide-in duced cognitive deficits via targeting neuroinflammation and neu ronal apoptosis. International Immunopharmacology 77: 105918. https://doi.org/10.1016/j.intimp.2019.105918 [PubMed] Voronina TA, Garibova TL, Khromova IV, Tilekeeva UM (1987) Dissociation of the anti-amnesic and antihypoxic effects of nootropic and antihypoxic preparations. Pharmacology and Toxicology [Far makologiia i Toksikologiia] 50(3): 21–24. [PubMed] [in Russian] Voronina TA, Ostrovskaya RU, Garibova TL (2012) Methodolog ical recommendations for the preclinical study of drugs with a nootropic type of action [Metodicheskie Rekomendatsii po Dok linicheskomu Izucheniyu Lekarstvennyh Sredstv s Nootropnym Tipom Dejstviya.]. In: Mironov AN, Bunyatyan ND, Vasiliev AN, Verstakova OL, Zhuravleva MV, Lepakhin VK, Uteshev DB, Ko robov NV, Merkulov VA, Orekhov SN, Sakaeva IV, Uteshev DB, Yavorskij AN (Eds) Guidelines for Preclinical Studies of Drugs [Rukovodstvo po Provedeniyu Doklinicheskikh Issledovaniy Lekarstvennykh Sredstv] Part 1. Grif and K, Moscow, 276–296. [in Russian] Parfenov VA (2019) Poststroke cognitive impairment. Neurology, Neuropsychiatry, Psychosomatics [Nevrologia, Nejropsikhiatria, Psikhosomatika] 11(4): 22–27. https://doi.org/10.14412/2074-2711- 2019-4-22-27 [in Russian] Povetkin SV, Laskov VB, Chernyshkov EV (2009) The influence of cavinton forte and picamilone on cognitive disorders in patients with dyscirculatory encephalopathy. Clinical Gerontology [Klinicheska ya Gerontologiya] 10–11: 17–21. [in Russian] Putaala J (2020) Ischemic stroke in young adults. Continuum (Minneapolis Minnesota) 26(2): 386–414. https://doi.org/10.1212/ CON.0000000000000833 [PubMed] Voronina TA (2016) The pioneer of antioxidant neuroprotection. 20 years in clinical practice. Russian Medical Journal [Russkiy Med itsinskiy Zhurnal] 24(7): 434–438. [in Russian] Rennie G, Chen AC, Dhillon H, Vardy J, Damian DL (2015) Nic otinamide and neurocognitive function. Nutritional Neuroscience 18(5): 193–200. https://doi.org/10.1179/1476830514Y.0000000112 [PubMed] Yang J, He L, Wang J, Adams Jr JD (2004) Early administration of nicotinamide prevents learning and memory impairment in mice induced by 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine. Phar macology, Biochemistry, and Behavior 78(1): 179–183. https://doi. org/10.1016/j.pbb.2004.03.007 [PubMed] Sharma A, Madan N (2019) Role of niacin in current clinical prac tice. Minerva Medica 110(1): 79–83. https://doi.org/10.23736/ S0026-4806.18.05826-3 [PubMed] Yasnetsov VikV, Kaurova DE, Bersenev EYu, Skachilova SYa (2020) Investigation of the antihypoxic properties of new nicotinic acid derivatives. Aerospace and Environmental Medicine [Aviakos micheskaya i Ekologicheskaya Meditsina] 54(5): 73–76. https://doi. Diana E. Kaurova, postgraduate student, specialist in educational and methodological work, Resource Center for Teacher Education of Moscow Region, e-mail: berseneva_diana@mail.ru, ORCID ID https://orcid.org/0000- 0002-6261-9832. The author developed the idea, concept and design of the study, conducted the experiments and statistic processing of the obtained data and prepared the final version of the article. Evgeniy Yu. Bersenev, PhD in Biology, Leading Researcher, Laboratory of Vegetative Regulation of the Cardio vascular System; Deputy Head, Department of Physiology and Biomechanics of the Cardiorespiratory System in Extreme Condition, e-mail: bersenev_evgenii@mail.ru, ORCID ID https://orcid.org/0000-0002-6974-5196. The author took part in experimental work and conducted the statistic processing of the obtained data. Author contributions Victor V. Yasnetsov, Doctor Habil. of Medical Sciences, Chief Researcher, Laboratory of Pharmacology, All-Union Research Center for Safety of Biologically Active Substances; Leading Researcher, Laboratory of Experimental and Clinical Pharmacology, State Scientific Center of Russian Federation – Institute of Biomedical Problems of the Rus sian Academy of Sciences, e-mail: vicyas@yandex.ru, ORCID ID https://orcid.org/0000-0002-6399-3703. The au thor developed the idea, concept and design of the study, took part in experimental work and wrote the initial draft. Yasnetsov VV et al.: Antiamnestic effect of new nicotinic acid derivatives 22 Diana E. Kaurova, postgraduate student, specialist in educational and methodological work, Resource Center for Teacher Education of Moscow Region, e-mail: berseneva_diana@mail.ru, ORCID ID https://orcid.org/0000- 0002-6261-9832. The author developed the idea, concept and design of the study, conducted the experiments and statistic processing of the obtained data and prepared the final version of the article. Sofia Ya. Skachilova, Doctor Habil. of Chemical Sciences, Professor, Head of Department, Department of Chem istry and Technology of Synthetic Drugs and Analytical Control, e-mail: skachilova@mail.ru, ORCID ID https:// orcid.org/0000-0003-4486-8883. The author carried out the synthesis of the studied compounds and provided con sulting support. Evgeniy Yu. Bersenev, PhD in Biology, Leading Researcher, Laboratory of Vegetative Regulation of the Cardio vascular System; Deputy Head, Department of Physiology and Biomechanics of the Cardiorespiratory System in Extreme Condition, e-mail: bersenev_evgenii@mail.ru, ORCID ID https://orcid.org/0000-0002-6974-5196. The author took part in experimental work and conducted the statistic processing of the obtained data.
https://openalex.org/W4313432905	https://e-jurnal.lppmunsera.org/index.php/KA/article/download/4448/2313	Indonesian	null	DOMPET DIGITAL SEBAGAI ALAT ALTERNATIF PEMBAYARAN NON-TUNAI PADA UMKM DI DESA PADANGSAMBIAN	Kaibon Abhinaya	2,023	cc-by	3,361	KAIBON ABHINAYA: JURNAL PENGABDIAN MASYARAKAT http://dx.doi.org/10.30656/ka.v5i1.4448 KAIBON ABHINAYA: JURNAL PENGABDIAN MASYARAKAT http://dx.doi.org/10.30656/ka.v5i1.4448 e-ISSN 2657-1110 DOMPET DIGITAL SEBAGAI ALAT ALTERNATIF PEMBAYARAN NON-TUNAI PADA UMKM DI DESA PADANGSAMBIAN Ida Nyoman Basmantra 1, Claudya Trihanura Pranurti2 1 Jurusan Manajemen, Universitas Pendidikan Nasional 2Jurusan Akuntansi, Universitas Pendidikan Nasional ail: 1 basmantra@undiknas.ac.id, 2 claudyatrihanura12@gmail. Abstract The Covid-19 pandemic that is currently ravaging Indonesia, especially in Bali, has caused Micro, Small, and Medium Enterprises who had not previously used digital platforms as an alternate method of payment to do so. The existing lack of understanding among MSMEs players in Padangsambian village regarding the usage of digital payment systems would almost surely reduce customer interest in transacting with the items on sale. As a result of the issues, there will be educational outreach on the benefits of digital payment platforms for MSMEs through the usage of an e-wallet. The purpose of this socialization is to increase the knowledge of MSMEs owners so that they can take advantage of the e-wallet platform as an alternative digital payment tool in the midst of a pandemic, so as to increase the effectiveness and attractiveness of consumers in making transactions. The method used is to implement a communication strategy to the owners of Micro,Small and Medium Enterprises (MSMEs). The results of this socialization will help MSMEs in Padangsambian village to increase sales and become more competitive in the digital era. Keywords: E-Wallet, Payment Method, cashless, MSMEs. N ahun 2019, dunia sedang ngan munculnya virus berbahaya yang menyerang saluran pernapasan manusia. Virus ini adalah Coronavirus disease 19 atau disingkat dengan Covid-19 (Dennison Himmelfarb, 2020). Wabah pandemi Covid-19 berbahaya yang menyerang saluran pernapasan manusia. Virus ini adalah Coronavirus disease 19 atau disingkat dengan Covid-19 (Dennison Himmelfarb, 2020). Wabah pandemi Covid-19 berbahaya yang menyerang saluran pernapasan manusia. Virus ini adalah Coronavirus disease 19 atau disingkat dengan Covid-19 (Dennison Himmelfarb, 2020). Wabah pandemi Covid-19 Kata Kunci: Dompet Digital, Alat Pembayaran, Non-tunai, UMKM Kata Kunci: Dompet Digital, Alat Pembayaran, Non-tunai, UMKM @ Ida Nyoman Basmantra; Claudya Trihanura Pranurti Abstrak Pandemi Covid-19 yang dihadapi Indonesia khususnya di Bali saat ini, memaksa usaha mikro kecil dan menengah yang sebelumnya tidak menggunakan platform digital sebagai alternatif alat untuk pembayaran kini harus menerapkan dalam usaha mereka. Minimnya pengetahuan para pelaku UMKM di desa Padangsambian Bali saat ini akan manfaat dari platform pembayaran digital tentu akan berakibat pada menurunnya tingkat ketertarikan konsumen untuk melakukan transaksi terhadap produk yang ditawarkan. Melihat permasalahan yang terjadi, maka akan dilakukan sosialisasi edukasi mengenai manfaat dari platform pembayaran digital melalui pemanfaatan e-wallet bagi UMKM. Tujuan dari program sosialisasi edukasi untuk meningkatkan pengetahuan pemilik UMKM agar dapat memanfaatkan platform e-wallet sebagai alternatif alat pembayaran digital ditengah pandemi sehingga dapat meningkatkan efektifitas serta daya tarik konsumen untuk melakukan transaksi. Metode yang digunakan adalah dengan menerapkan strategi komunikasi kepada pemilik usaha mikro kecil dan menengah (UMKM). Hasil dari sosialisasi ini akan membantu UMKM di desa Padangsambian untuk meningkatkan penjualan dan menjadi lebih kompetitif di era digital. KAIBON ABHINAYA: JURNAL PENGABDIAN MASYARAKAT http://dx.doi.org/10.30656/ka.v5i1.4448 e-ISSN 2657-1110 sudah berpengaruh kepada pola hidup masyarakat dalam menjalankan aktivitas keseharian mereka dengan beralih ke pemakaian digital technology. Hal ini disebabkan karena adanya himbauan untuk melakukan physical distancing atau pembatasan melakukan kontak fisik secara langsung dengan orang lain. Tentu hal ini yang menyebabkan pemanfaatan dan pemakaian digital technology semakin meningkat khususnya pemanfaatan media untuk melakukan transaksi secara digital. Selama pandemi Covid-19 pemakaian sejumlah layanan pembayaran digital di Indonesia mengalami peningkatan (Rangkuty, 2021). pemakaian e-wallet berada di posisi kedua dengan 65% persentase kenaikan (Santia, 2020). Kenaikan jumlah persentase pemakaian e-wallet ini membuktikan bahwa dompet digital kini telah menjadi pilihan bagi masyarakat untuk melakukan transaksi jual beli di masa Covid-19. Dalam pembayaran non-tunai, transaksi pembayaran dapat dilakukan tanpa melakukan kontak fisik antara penjual dan pembeli. Tentu hal ini akan membantu pemerintah dalam menerapkan physical distancing. Selain itu faktor lain yang mempengaruhi orang untuk bertransaksi dengan menggunakan e-wallet adalah mudah, cepat, dan aman dalam melakukan transaksi (Budiarti, 2021). sudah berpengaruh kepada pola hidup masyarakat dalam menjalankan aktivitas keseharian mereka dengan beralih ke pemakaian digital technology. Hal ini disebabkan karena adanya himbauan untuk melakukan physical distancing atau pembatasan melakukan kontak fisik secara langsung dengan orang lain. Tentu hal ini yang menyebabkan pemanfaatan dan pemakaian digital technology semakin meningkat khususnya pemanfaatan media untuk melakukan transaksi secara digital. Selama pandemi Covid-19 pemakaian sejumlah layanan pembayaran digital di Indonesia mengalami peningkatan (Rangkuty, 2021). pemakaian e-wallet berada di posisi kedua dengan 65% persentase kenaikan (Santia, 2020). Kenaikan jumlah persentase pemakaian e-wallet ini membuktikan bahwa dompet digital kini telah menjadi pilihan bagi masyarakat untuk melakukan transaksi jual beli di masa Covid-19. Dalam pembayaran non-tunai, transaksi pembayaran dapat dilakukan tanpa melakukan kontak fisik antara penjual dan pembeli. Tentu hal ini akan membantu pemerintah dalam menerapkan physical distancing. Selain itu faktor lain yang mempengaruhi orang untuk bertransaksi dengan menggunakan e-wallet adalah mudah, cepat, dan aman dalam melakukan transaksi (Budiarti, 2021). Meningkatnya pelaku usaha mikro kecil dan menengah (UMKM) di kota Denpasar Barat khususnya di desa Padangsambian di masa pandemi, membuat persaingan usaha untuk mengembangkan serta bersaing secara sehat semakin ketat. Hal ini yang menjadikan tantangan tersendiri bagi para pemilik UMKM agar dapat mempertahankan usaha bisnis mereka untuk memperoleh keuntungan. untuk menghadapi tantangan yang dihadapi oleh pemilik UMKM ini maka diperlukan pemahaman akan suatu strategi pemasaran dengan memanfaatkan digital technology. PENDAHULUAN Pada akhir tahun 2019, dunia sedang digencarkan dengan munculnya virus 27 \| K a i b o n A b h i n a y a @ Ida Nyoman Basmantra; Claudya Trihanura Pranurti KAIBON ABHINAYA: JURNAL PENGABDIAN MASYARAKAT http://dx.doi.org/10.30656/ka.v5i1.4448 KAIBON ABHINAYA: JURNAL PENGABDIAN MASYARAKAT http://dx.doi.org/10.30656/ka.v5i1.4448 e-ISSN 2657-1110 wawancara secara langsung kepada pemilik usaha mikro kecil menengah (UMKM) di desa Padangsambian yang mengalami kendala dalam mengembangkan strategi pemasaran yang tepat. Hasil wawancara diperoleh hasil yakni 80% dari 100% dengan total jumlah responden 20 pemilik UMKM belum memanfaatkan platform digital seperti e-wallet sebagai strategi pemasaran mereka karena mereka lebih memilih dan lebih tertarik untuk melakukan pembayaran secara tunai yang dinilai sudah praktis dan mudah. Selain itu juga ada yang beranggapan bahwa pembayaran dengan platform e-wallet adalah ribet karena diperlukan jaringan internet. Hal ini yang melatarbelakangi penulis untuk melakukan pengabdian kepada masyarakat di desa Padangsambian kepada pemilik UMKM yang belum memanfaatkan dan mengaplikasikan digital technology untuk mengembangkan usaha dan bisnis mereka agar konsumen tertarik untuk melakukan transaksi jual beli. menengah (UMKM) mengenai manfaat dompet digital (e-wallet) sebagai metode transaksi berbasis digital dan sebagai alternatif pembayaran non-tunai yang dapat meningkatkan daya tarik konsumen serta meningkatkan efektifitas akan hasil usaha di tengah pandemi Covid-19. METODE PELAKSANAAN Metode pelaksanaan program kerja yang diterapkan dalam kegiatan pengabdian masyarakat ini adalah dengan menerapkan strategi komunikasi. Strategi komunikasi yang dilakukan adalah dengan cara melakukan sosialisasi secara langsung kepada 20 UMKM yang bergerak dalam bidang kuliner, toko sembako, dan fashion yang terdapat di desa Padangsambian. Sosialisasi edukasi ini dengan tema untuk mengajak serta menambah wawasan kepada para pemilik UMKM mengenai manfaat serta dampak yang baik untuk kedepan jika menerapkan dan mengaplikasikan e-wallet ke dalam aktivitas usaha mereka. Kegiatan edukasi ini didukung dengan pemberian flyer tenang manfaat dari memfasilitasi e-wallet dalam mengembangkan usaha dan menarik konsumen di tengah pandemic. Kegiatan sosialisasi edukasi ini bertujuan untuk membantu UMKM di desa padangsambian agar mampu mempertahankan bisnis mereka di tengah pandemi dengan mengembangkan strategi pemasaran yang lebih luas dengan memanfaatkan perkembangan dompet digital atau dalam Bahasa inggrisnya adalah e-wallet seperti Go-pay, OVO, dan aplikasi e-wallet yang sejenis. selain itu sosialisasi ini juga diharapkan agar para pemilik usaha mikro kecil dan menengah memiliki informasi akan manfaat yang diperoleh dari pemakaian e-wallet sehingga menjadikan e- wallet sebagai alternatif alat pembayaran non- tunai. Adapun tahap penyuluhan yang dijalankan meliputi beberapa tahap yaitu: 1. Wawancara secara langsung Kegiatan wawancara secara langsung dengan mendatangi 20 UMKM yang berada di desa Padangsambian. hasil wawancara ini adalah untuk mengetahui tingkat persentase pemakaian platform e- wallet dalam aktivitas bisnis dan mengetahui alasan para pemilik UKM yang belum memanfaatkan platform e-wallet sebagai alternatif pembayaran non-digital yang efektif dan efisien. @ Ida Nyoman Basmantra; Claudya Trihanura Pranurti KAIBON ABHINAYA: JURNAL PENGABDIAN MASYARAKAT http://dx.doi.org/10.30656/ka.v5i1.4448 pemanfaatan digital technology bagi UMKM di tengah pandemi merupakan suatu hal yang diperlukan untuk meningkatkan jangkauan daya tarik konsumen untuk akan suatu produk agar tetap bertahan dan mampu bersaing antara produk atau usaha sejenis (Erlina, 2021). Pemanfaatan digital technology sebagai media promosi seperti melakukan promosi pada layanan e-commerce, merupakan salah satu contoh dari pengaplikasian strategi pemasaran terhadap suatu bisnis yang dijalankan untuk menarik daya tarik konsumen terhadap suatu produk. Namun, penerapan strategi pemasaran juga dapat meliputi pengadopsian platform e- wallet sebagai alternatif melakukan transaksi jual beli, karena pemakaian e-wallet saat ini telah menjadi trend untuk melakukan pembayaran di masa pandemi. Sehingga dapat dikatakan bahwa e-wallet dapat meningkatkan efektifitas dan ketertarikan konsumen untuk tertarik untuk melakukan transaksi pembelian akan produk yang ditawarkan. Hal ini disebabkan karena pada aplikasi e-wallet terdapat beberapa fitur penawaran yang menarik seperti cashback, promo, diskon atau potongan harga yang diperoleh oleh konsumen sebagai pengguna e- wallet sehingga konsumen memiliki ketertarikan untuk melakukan transaksi jual beli. E-wallet merupakan salah satu dari jenis perkembangan financial technology yang bermanfaat untuk membantu aktivitas keuangan dan juga sebagai fasilitas atau penunjang kehidupan masyarakat dalam bertransaksi. Fitur-fitur yang terdapat dalam platform e-wallet dibuat dengan tujuan untuk memudahkan pemakai platform e-wallet dalam bertransaksi secara aman, efektif dan efisien dan sebagai alat pembayaran yang resmi dan sudah diakui oleh Bank Indonesia. Terdapat 5 Platform e-wallet yang sering digunakan di Indonesia yang meliputi OVO, Gopay, ShoopeePay, Dana dan LinkAja (Rahardyan, 2021). Berdasarkan survei di lapangan yang dilakukan penulis yakni dengan melakukan 28 \| K a i b o n A b h i n a y a @ Ida Nyoman Basmantra; Claudya Trihanura Pranurti RUMUSAN MASALAH Permasalahan yang ditemukan pada pelaksanaan pengabdian masyarakat yang dilakukan di Desa Padangsambian adalah kurangnya pemahaman dan edukasi yang dibutuhkan oleh pemilik usaha mikro kecil dan 2. Mencari dan menentukan solusi 2. Mencari dan menentukan solusi Menentukan solusi dari permasalahan yang sedang terjadi. Penentuan solusi ini Menentukan solusi dari permasalahan yang sedang terjadi. Penentuan solusi ini 29 \| K a i b o n A b h i n a y a @ Ida Nyoman Basmantra; Claudya Trihanura Pranurti KAIBON ABHINAYA: JURNAL PENGABDIAN MASYARAKAT http://dx.doi.org/10.30656/ka.v5i1.4448 e-ISSN 2657-1110 akan melibatkan pemilik usaha mikro kecil dan menengah (UMKM) dan 1 orang pengabdi. Setelah penyuluhan dan pendampingan selesai dilaksanakan, target yang akan dicapai yaitu 20 pemilik UMKM diharapkan dapat memahami serta menambah pengetahuan informasi mengenai manfaat dari penggunaan e-wallet sebagai alternatif pembayaran di masa pandemi Covid-19 untuk meningkatkan daya tarik pembeli melakukan transaksi terhadap suatu produk usaha yang dijalankan oleh pemilik UMKM. merupakan bentuk dari rencana program kerja yang akan dijalankan oleh penulis sebagai bentuk dari pengabdian kepada masyarakat. Solusi dari permasalahan yang terjadi pada UMKM di desa padangsambian adalah dengan melakukan sosialisasi edukasi agar dapat menambah pengetahuan dan memberi motivasi bagi para pemilik UMKM dalam memanfaatkan platform e-wallet. 3. Kegiatan sosialisasi Akibat saat ini masih berada di situasi pandemi Covid-19 yang dimana melakukan pembatasan untuk mengumpulkan orang dalam jumlah besar pada satu lingkup. sosialisasi yang akan penulis jalankan adalah dengan melakukan sosialisasi secara langsung dengan mendatangkan satu persatu kepada 20 UMKM di Desa Padangsambian yang terdampak covid-19 dan belum mengadopsi dompet digital sebagai alat pembayaran non-tunai. Selain itu juga penulis membuat sebuah flyer yang akan dibagikan ketika proses penyuluhan. 3. Kegiatan sosialisasi Akibat saat ini masih berada di situasi pandemi Covid-19 yang dimana melakukan pembatasan untuk mengumpulkan orang dalam jumlah besar pada satu lingkup. sosialisasi yang akan penulis jalankan adalah dengan melakukan sosialisasi secara langsung dengan mendatangkan satu persatu kepada 20 UMKM di Desa Padangsambian yang terdampak covid-19 dan belum mengadopsi dompet digital sebagai alat pembayaran non-tunai. Selain itu juga penulis membuat sebuah flyer yang akan dibagikan ketika proses penyuluhan. @ Ida Nyoman Basmantra; Claudya Trihanura Pranurti 30 \| K a i b o n A b h i n a y a KAIBON ABHINAYA: JURNAL PENGABDIAN MASYARAKAT http://dx.doi.org/10.30656/ka.v5i1.4448 KAIBON ABHINAYA: JURNAL PENGABDIAN MASYARAKAT http://dx.doi.org/10.30656/ka.v5i1.4448 e-ISSN 2657-1110 membuka usaha bisnis di tengah pandemi Covid-19 agar dapat mencukupi kebutuhan hidup mereka. Akan tetapi, para pemilik UMKM yang terdampak Covid-19 belum mengetahui akan pemilihan strategi pemasaran dengan memanfaatkan digital technology yang tepat agar dapat meningkatkan daya tarik konsumen. Hal ini disebabkan karena minimnya pengetahuan untuk menentukan strategi pemasaran mereka dengan memanfaatkan jaringan digital yang sedang berkembang yakni dengan memanfaatkan e- wallet sebagai trend alat pembayaran digital di tengah pandemi Covid-19 dan sebagai media promosi yang mendukung proses kelancaran usaha agar dapat bertahan dan memperoleh keuntungan. dapat mempercepat penyebaran dan penyampaian informasi mengenai manfaat e- wallet. Gambar 1. Flyer yang di design untuk meningkatkan pengetahuan akan manfaat e- wallet @ Ida Nyoman Basmantra; Claudya Trihanura Pranurti HASIL DAN PEMBAHASAN Transaksi jual beli merupakan kegiatan keseharian masyarakat yang tidak mungkin dihindari. Manfaat menerapkan dan menggunakan e-wallet di tengah pandemi Covid-19 dapat membantu program pemerintah untuk meminimalisir penularan virus Covid-19 melalui uang tunai. Pemakaian dan pemanfaatan e-wallet akan memberikan dampak positif terhadap kedua belah pihak antara konsumen dan pemilik UMKM jika keduanya memanfaatkan dompet digital sebagai alternatif alat pembayaran. Dilihat dari sisi konsumen jika memakai e-wallet maka akan mendapatkan potongan harga yang beragam sesuai dengan promo yang berlaku dalam melakukan suatu transaksi pembelian, serta jika dilihat dari pemilik UMKM, manfaat e-wallet akan dapat meningkatkan daya tarik konsumen untuk melakukan transaksi akibat dari fitur penawaran yang tersedia pada platform e- wallet. 4. Pendampingan dan Observasi Pendampingan dan observasi dilakukan secara langsung dan melalui group chatting Whatsapp. Selama 14 hari dilakukan pengamatan dan pendampingan untuk melihat, bagaimana perkembangan dari metode yang telah dilaksanakan dalam upaya meningkatkan kesadaran dan minat para pemilik UKM dalam mengadopsi dompet digital sebagai alternatif alat pembayaran digital bagi UMKM di masa pandemi Covid-19, dan observasi ini akan menentukan hasil akhir dari keberhasilan program kerja pengabdian kepada masyarakat. 4. Pendampingan dan Observasi Pendampingan dan observasi dilakukan secara langsung dan melalui group chatting Whatsapp. Selama 14 hari dilakukan pengamatan dan pendampingan untuk melihat, bagaimana perkembangan dari metode yang telah dilaksanakan dalam upaya meningkatkan kesadaran dan minat para pemilik UKM dalam mengadopsi dompet digital sebagai alternatif alat pembayaran digital bagi UMKM di masa pandemi Covid-19, dan observasi ini akan menentukan hasil akhir dari keberhasilan program kerja pengabdian kepada masyarakat. Hasil dari pengabdian kepada masyarakat ini berfokus kepada kesadaran akan manfaat e- wallet bagi pemilik UMKM di desa Padangsambian. Pada tahap survei pertama, terdapat permasalahan yang terjadi di desa Padangsambian yakni meningkatnya jumlah masyarakat yang beralih profesi untuk Kegiatan pengabdian kepada masyarakat ini dilakukan selama 45 hari yaitu dari tanggal 10 Januari 2022 hingga 23 Februari 2022. program kerja yang dilakukan 30 \| K a i b o n A b h i n a y a @ Ida Nyoman Basmantra; Claudya Trihanura Pranurti Program kerja pengabdian kepada masyarakat adalah melakukan sosialisasi edukasi dengan tujuan untuk meningkatkan pemahaman dan motivasi kepada para pemilik UMKM akan alternatif pembayaran dengan memanfaatkan platform e-wallet. Sosialisasi edukasi manfaat pemakaian e-wallet ini dilaksanakan dengan memberikan edukasi secara langsung. Pemaparan materi secara singkat dan akan didukung dengan pembagian flyer kepada 20 UMKM di desa Padangsambian akan manfaat e-wallet sebagai alternatif pembayaran di tengah pandemi dan juga dapat berpartisipasi dalam menerapkan anjuran pemerintah mengenai physical distancing. Tidak hanya manfaat e-wallet, juga memaparkan tentang cara mengembangkan strategi pemasaran dengan memanfaatkan e-commerce. Gambar 1. Flyer yang di design untuk meningkatkan pengetahuan akan manfaat e- wallet Gambar 1. Flyer yang di design untuk meningkatkan pengetahuan akan manfaat e- wallet Gambar 1. Flyer yang di design untuk meningkatkan pengetahuan akan manfaat e- wallet Adapun materi edukasi yang disampaikan kepada 20 para pemilik UMKM meliputi 3 garis besar pemaparan materi edukasi diantaranya adalah sebagai berikut: 1. Pengertian e-wallet, pentingnya pengaplikasian serta manfaat dari e-wallet sebagai alat alternatif pembayaran non-tunai di masa pandemi. 2. Dampak yang diperoleh jika pemilik UMKM mengaplikasikan e-wallet ke dalam kegiatan mengembangkan bisnis mereka. 3. Manfaat dari digital technology sebagai media promosi untuk menarik daya tarik konsumen akan suatu produk yang ditawarkan, seperti menggunakan aplikasi e- commerce. Pembagian flyer bertujuan untuk memperluas pengetahuan akan manfaat e-wallet antara konsumen dan pemilik UMKM karena dalam flyer ini terdapat informasi pengetahuan yang dapat dibaca oleh pemilik UMKM dan kepada para konsumen, sehingga dapat memperluas target sosialisasi yang tidak hanya kepada pemilik UMKM akan tetapi juga kepada masyarakat umum serta penyebaran flayer juga 31 \| K a i b o n A b h i n a y a @ Ida Nyoman Basmantra; Claudya Trihanura Pranurti KAIBON ABHINAYA: JURNAL PENGABDIAN MASYARAKAT http://dx.doi.org/10.30656/ka.v5i1.4448 e-ISSN 2657-1110 Gambar 2. Kegiatan sosialisasi edukasi manfaat dompet digital Tabel 1. Hasil Pengabdian Kepada Masyarakat Kriteria Analisa Sebelum Sesudah Pengetahua n Para pemilik UMKM belum mengetahui manfaat dompet digital (E-Wallet) di tengah pandemi covid-19 sebagai alternatif pembayaran digital dan efektivitas dalam pengembanga n usaha agar konsumen memiliki daya tarik untuk melakukan suatu transaksi pembelian terhadap suatu produk. Pemilik UMKM sudah mengetahui manfaat manfaat dompet digital (E-Wallet) di tengah pandemi covid- 19 sebagai alternatif pembayaran digital dan efektivitas dalam pengembangan usaha agar konsumen memiliki daya tarik untuk melakukan suatu transaksi pembelian terhadap suatu produk.. Sikap dan k d Melakukan k i Melakukan k i Tabel 1. Hasil Pengabdian Kepada Gambar 2. Kegiatan sosialisasi edukasi manfaat dompet digital Setelah dilaksanakannya tahap sosialisasi edukasi secara langsung tahap pengamatan melalui media group chatting kepada 20 para pemilik UMKM di desa padangsambian, dengan ini penulis dapat mengambil keputusan, yang dimana hasil keputusan dan kesepakatan antara para pemilik UMKM ini merupakan hasil dari kelancaran program kerja pengabdian masyarakat yang telah dijalankan. Dapat dilihat dari setelah dilakukan sosialisasi, pengetahuan para pemilik usaha UMKM akan manfaat dari e-wallet sebagai media promosi dan meningkatkan daya beli konsumen di tengah pandemi Covid-19 akan bertambah dan memiliki rasa ketertarikan untuk mendaftarkan usaha mereka ke platform e-wallet yang mendung seperti, Gopay, OVO, Shopee pay, dan sebagainya. Gambar 1. Flyer yang di design untuk meningkatkan pengetahuan akan manfaat e- wallet Berikut adalah tabel hasil dari penyuluhan dan observasi setelah dilaksanakan proses sosialisasi edukasi akan manfaat dompet digital (e-wallet) sebagai alternatif pembayaran secara non-tunai di tengah pandemi dan meningkatkan strategi pemasaran dalam pengembangan bisnis di UMKM di desa Padangsambian yang ditinjau dari 3 jenis kriteria yakni pengetahuan, sikap dan kesadaran, dan keterampilan. 32 \| K a i b o n A b h i n a y a @ Ida Nyoman Basmantra; Claudya Trihanura Pranurti KAIBON ABHINAYA: JURNAL PENGABDIAN MASYARAKAT http://dx.doi.org/10.30656/ka.v5i1.4448 KAIBON ABHINAYA: JURNAL PENGABDIAN MASYARAKAT http://dx.doi.org/10.30656/ka.v5i1.4448 e-ISSN 2657-1110 e-ISSN 2657-1110 dengan secara tunai. mendaftarkan usaha mereka kedalam platform e- wallet sebagai alternatif alat pembayaran digital. keterampila n Para pemilik UMKM belum terampil untuk pemanfaatan platform digital salah satunya dompet digital untuk meningkatkan strategi pemasaran produk yang efektif dan efisien Para pemilik UMKM sudah terampil untuk memanfaatkan dompet digital untuk meningkatkan strategi pemasaran akan produk yang efektif dan efisien tertarik untuk melakukan pembayaran atau transaksi secara non- tunai. tertarik untuk melakukan pembayaran atau transaksi secara non- tunai. DAFTAR REFERENSI Budiarti, F. (2021). Financial Technology as Payment Methods in the Digital era. International journal of research and applied technology. Universitas Komputer Indonesia, 9-16. Dennison Himmelfarb, C. R. (2020). Coronavirus Disease (COVID-19). Journal of Cardiovascular Nursing, 318- 321. Erlina, E. (2021). Analisis Strategi Pemasaran Dalam Meningkatkan Daya Tarik Konsumen. Digital Repository. Diambil kembali dari http://repository.iainpurwokerto.ac.id/id/epr int/10364 Rahardyan, A. (2021). Survei 5 Dompet Digital Terpopuler di Indonesia, Siapa Juaranya? Diambil kembali dari https://finansial.bisnis.com/read/20210830/ 563/1435905/survei-5-dompet-digital- terpopuler-di-indonesia-siapa-jawaranya Rangkuty, D. M. (2021). Apakah E-wallet Masa Pandemi Covid-19 Semakin Meningkat di Indonesia? . Prosiding Konferensi Universitas Nahdlatul Ulama Indonesia, 251-260. 33 \| K a i b o n A b h i n a y a @ Ida Nyoman Basmantra; Claudya Trihanura Pranurti KESIMPULAN Berdasarkan uraian hasil dari kegiatan dari pengabdian kepada masyarakat yang sudah dijalankan dan juga sesuai dengan program kerja yang telah direncanakan diperoleh kesimpulan sebagai berikut: Santia, T. (2020). Diambil kembali dari Aktivitas Belanja Online Naik 28,9 Persen saat Pandemi Corona: https://www.liputan6.com Santia, T. (2020). Diambil kembali dari Aktivitas Belanja Online Naik 28,9 Persen saat Pandemi Corona: https://www.liputan6.com 1. Para pemilik UMKM di desa Padangsambian sudah mengetahui akan manfaat e-wallet atau dompet digital sebagai alternatif alat pembayaran non- tunai di tengah pandemi Covid-19. Hal ini dilihat dari tabel perbandingan hasil yang ditinjau dari pengetahuan, keterampilan, sikap dan kesadaran. 2. Dompet digital dapat meningkatkan efektifitas akan ketertarikan pelanggan untuk melakukan kegiatan bertransaksi. Hal ini dilihat dari gaya hidup masyarakat sejak pandemi Covid-19 yang mana lebih 33 \| K a i b o n A b h i n a y a @ Ida Nyoman Basmantra; Claudya Trihanura Pranurti
https://openalex.org/W2016295133	https://www.scielo.br/j/rbef/a/G4DgqpxC4DJ4mjSfhZDNRfh/?lang=pt&format=pdf	Portuguese	null	Software MUFCosm como ferramenta de estudo dos modelos da cosmologia padrão	Revista Brasileira de Ensino de Física	2,014	cc-by	5,076	R.R. Cuzinatto1, E.M. de Morais Instituto de Ciˆencia e Tecnologia, Universidade Federal de Alfenas, Po¸cos de Caldas, MG, Brasil Recebido em 12/6/2013; Aceito em 1/7/2013; Publicado em 6/2/2014 Instituto de Ciˆencia e Tecnologia, Universidade Federal de Alfenas, Po¸cos de Caldas, MG, Brasil Recebido em 12/6/2013; Aceito em 1/7/2013; Publicado em 6/2/2014 Instituto de Ciˆencia e Tecnologia, Universidade Federal de Alfenas, Po¸cos de Caldas, MG, Brasil Recebido em 12/6/2013; Aceito em 1/7/2013; Publicado em 6/2/2014 Apresentamos o software MUFCosm, constru´ıdo em Python, destinado ao estudo das diferentes etapas de evolu¸c˜ao do universo atrav´es do modelo uniﬁcado para o ﬂuido cosmol´ogico. Este modelo simpliﬁca a descri¸c˜ao das grandes eras evolutivas do cosmos, mas demanda a utiliza¸c˜ao de m´etodos num´ericos de grande precis˜ao. O software ´e uma ferramenta para efetuar interativamente os processamentos num´ericos e avaliar as propriedades cosmol´ogicas do modelo uniﬁcado para o ﬂuido cosmol´ogico. O mesmo software pode ser usado para estudar o comportamento do fator de escala do universo para cada um dos modelos cl´assicos de Friedmann, em que temos apenas uma componente de ﬂuido dominante (mat´eria, radia¸c˜ao, inﬂaton ou constante cosmol´ogica), o que d´a um car´ater pedag´ogico para esse trabalho. Palavras-chave: software, cosmologia, ﬂuido cosmol´ogico. This work presents the software MUFCosm that is built in Phyton for the study of the diﬀerent evolution eras of the Cosmos through the uniﬁed model for the cosmic ﬂuid. This model simpliﬁes the description of the main phases of the universe, but at the same time introduces the need of numerical integration of the dynamical equations. The software is a useful tool for carrying out the numerical processing and assess the physical pro- perties of the uniﬁed model for the cosmic ﬂuid. Software MUFCosm can also be used for studying the behavior of the scale factor related to each one of the classic Friedmann models, which deal with a single-component ﬂuid at a particular era – matter, radiation, inﬂation or dark energy (cosmological constant). This latter feature of the software makes this paper a pedagogical piece of work. Keywords: software, cosmology, cosmic ﬂuid. 1E-mail: cuzinatto@gmail.com. Copyright by the Sociedade Brasileira de F´ısica. Printed in Brazil. Revista Brasileira de Ensino de F´ısica, v. 36, n. 1, 1312 (2014) www.sbﬁsica.org.br Revista Brasileira de Ensino de F´ısica, v. 36, n. 1, 1312 (2014) www.sbﬁsica.org.br tware MUFCosm como ferramenta de estudo dos modelos da cosmologia padr˜ao (Software MUFCosm as a tool for studying the standard cosmological models) R.R. Cuzinatto1, E.M. de Morais R.R. Cuzinatto1, E.M. de Morais Instituto de Ciˆencia e Tecnologia, Universidade Federal de Alfenas, Po¸cos de Caldas, MG, Brasil Recebido em 12/6/2013; Aceito em 1/7/2013; Publicado em 6/2/2014 R.R. Cuzinatto1, E.M. de Morais R.R. Cuzinatto1, E.M. de Morais Instituto de Ciˆencia e Tecnologia, Universidade Federal de Alfenas, Po¸cos de Caldas, MG, Brasil Recebido em 12/6/2013; Aceito em 1/7/2013; Publicado em 6/2/2014 1. Introdu¸c˜ao O principal colaborador com a cosmologia dessa ´epoca foi o cientista russo Alexander Friedmann [5]. Ele abandonou a premissa de um universo mon´otono e estudou a sua dinˆamica pela aplica¸c˜ao das equa¸c˜oes de Einstein. Com elas, ele formulou em 1922 a rela¸c˜ao A cosmologia ´e a ciˆencia que o estuda do universo como um todo. Ela tem como um de seus objetivos mais b´asicos a determina¸c˜ao do comportamento e as dimens˜oes deste ao longo do tempo [1]. ( ˙a a )2 = 8πG 3c2 ε −kc2 R2a2 , (1) Com a descoberta das leis da f´ısica, surgiram as primeiras tentativas de aplica¸c˜ao destas ao universo. Por´em, a ausˆencia de dados experimentais era um pro- blema, pois n˜ao se podia comprovar por observa¸c˜oes o que as equa¸c˜oes propunham. (1) que ´e uma equa¸c˜ao diferencial que relaciona a es- cala do universo (a), densidade de energia (ε), curva- tura (k), as constantes fundamentais velocidade da luz (c) e constante gravitacional (G) al´em de (R) que ´e uma grandeza com dimens˜oes de comprimento e representa o raio atual do universo. A descri¸c˜ao mais completa do universo veio com a teoria da relatividade geral, formulada por Albert Eins- tein [2,3]. Com ela, era poss´ıvel determinar o universo como tendo um comportamento dinˆamico. Na vis˜ao de Einstein, o universo era eterno e est´atico, fato este que fez com que ele alterasse suas equa¸c˜oes com a adi¸c˜ao de uma chamada constante cosmol´ogica que estabilizaria o universo [4]. A equa¸c˜ao de Friedmann propunha apenas mais um modelo de universo, at´e que em 1929 o astrˆonomo norte americano Edwin Hubble observou o afastamento das gal´axias, provando a dinˆamica do universo [6]. Com isso, a equa¸c˜ao de Friedmann se tornou a principal fer- 1312-2 Cuzinatto e Morais uma das componentes s˜ao associadas a um valor dife- rente deste parˆametro. Para a radia¸c˜ao, este parˆametro vale 1/3, para mat´eria vale 0 e −1 para constante cos- mol´ogica. ramenta de estudo dos cosm´ologos. Mais recentemente, a medi¸c˜ao da radia¸c˜ao c´osmica de fundo comprovou a teoria do big bang para origem do universo e sua evolu¸c˜ao dinˆamica . Para solucionar problemas de conex˜ao causal entre diferentes regi˜oes afastadas no c´eu, e eliminar diﬁculda- des em se justiﬁcar a geometria plana do espa¸co, os cien- tistas te´oricos propuseram um crescimento exponencial vertiginoso logo no in´ıcio do universo. Essa dinˆamica acelerada primordial foi denominada inﬂa¸c˜ao [16, 17]. 1. Introdu¸c˜ao A descri¸c˜ao completa desse per´ıodo ´e extremamente custosa em termos matem´aticos e f´ısicos, por´em, pode- se aproximar um comportamento semelhante deﬁnindo que o crescimento exponencial foi resultado do dom´ınio de uma componente com parˆametro da equa¸c˜ao de es- tado igual a −1 (tal como a constante cosmol´ogica). Quando se aponta o telesc´opio ao c´eu, podemos ver nitidamente duas importantes componentes do uni- verso: a radia¸c˜ao e a mat´eria bariˆonica (formada por ´atomos). Ao estudar a dinˆamica de gal´axias, os f´ısicos encontraram evidˆencias de uma outra componente: a mat´eria escura [7–9], que tem propriedades semelhantes a mat´eria bariˆonica, por´em, ´e muito mais densa. De- vido `a semelhan¸ca, mat´eria escura e mat´eria bariˆonica s˜ao consideradas a mesma componente do universo: mat´eria. Com aplica¸c˜ao das propriedades termodinˆamicas de cada uma dessas componentes na equa¸c˜ao de Fried- mann, foi poss´ıvel prever que quando o universo era muito jovem, sua densidade de energia era composta basicamente por radia¸c˜ao, ou seja, a radia¸c˜ao era do- minante. Ao passar do tempo, a densidade de energia da mat´eria superou a da radia¸c˜ao deixando a densidade de energia do universo dominada pela mat´eria. Ambos os comportamentos previam um crescimento desacele- rado do raio do universo [1]. 2. Modelo uniﬁcado Baseados nos dados observacionais, os cosm´ologos ela- boraram um modelo de universo, chamado modelo de mercado ou modelo padr˜ao. Nele, foi considerado que no per´ıodo em que determinada componente era domi- nante, apenas o parˆametro da equa¸c˜ao de estado re- ferente `aquela componente era relevante (no modelo de mercado n˜ao ´e considerado o per´ıodo inﬂacion´ario). Desse modo, o parˆametro da equa¸c˜ao de estado per- manece valendo 1/3 durante o per´ıodo em que a ra- dia¸c˜ao domina, passando para 0 no per´ıodo de dom´ınio da mat´eria chegando ao valor de −1 juntamente com per´ıodo de dom´ınio da constante cosmol´ogica [1]. O problema do modelo de mercado ´e que as transi¸c˜oes entre os per´ıodos de dom´ınio ocorrem de forma des- cont´ınua, impossibilitando assim resolu¸c˜oes de equa¸c˜oes diferenciais nos intervalos de transi¸c˜ao. Recentemente, foi comprovado que o universo atu- almente est´a crescendo aceleradamente [10–12]. Como nenhuma das componentes descritas acima pode culmi- nar em um comportamento desse tipo, os cosm´ologos consideraram a possibilidade de uma terceira compo- nente atuante. Nenhuma experiˆencia ou observa¸c˜ao foi capaz de determinar qual seria esta componente, que ﬁcou conhecida apenas como energia escura. O modelo mais difundido para energia escura ´e o da constante cosmol´ogica de Einstein. Essa constante tem a propriedade de se antepor a gravidade, gerando uma repuls˜ao. ´E descrita por um campo escalar de densidade de energia constante, diferentemente da densidade de energia da radia¸c˜ao e da mat´eria, que diminuem hiper- bolicamente com o tempo [13]. Desse modo, em algum tempo recente (relativamente), a densidade de energia da mat´eria e radia¸c˜ao se tornaram menor que a densi- dade de energia da constante cosmol´ogica, que fez com que o universo se expandisse aceleradamente devido a repuls˜ao por ela gerada. O modelo uniﬁcado para o ﬂuido cosmol´ogico [18] tem como objetivo contornar essa diﬁculdade propondo uma ´unica equa¸c˜ao de estado que seja uma fun¸c˜ao cont´ınua do tempo referente a toda a hist´oria do uni- verso. Este modelo toma o universo como dotado de geometria plana (k = 0) e composto apenas por uma componente que tem o parˆametro da equa¸c˜ao de es- tado vari´avel com o tempo (ω (t)). O per´ıodo inﬂa- cion´ario, que ocorre no per´ıodo de domina¸c˜ao da ra- dia¸c˜ao, tamb´em ´e considerado. Essa equa¸c˜ao de estado tem a forma Al´em da equa¸c˜ao de Friedmann, duas outras equa¸c˜oes descrevem o comportamento do universo. 3. Software MUFCosm [24] (5) O software MUFCosm2 foi desenvolvido com o in- tuito de facilitar o ´arduo trabalho alg´ebrico e ter um maior controle da qualidade dos m´etodos de integra¸c˜ao num´erica. Sua tela inicial ´e basicamente divida em trˆes partes, conforme Fig. 3. onde ω1 = 1/3 , ω2 = −1 , ω3 = 1/3 , ω4 = 0 e ω5 = −1. Os tempo ti s˜ao os valores absolutos de tempo em que as mudan¸cas de comportamento de ω (t) ocorrem. A constante α ´e um parˆametro livre denominado cons- tante de suaviza¸c˜ao, que faz com que a fun¸c˜ao dada na Eq. (5) se aproxime da fun¸c˜ao cont´ınua por peda¸cos (ver Fig. 1) a medida que α cres¸ca. A Fig. 2 ilustra uma compara¸c˜ao entre esses dois comportamentos. Na parte superior esquerda, logo abaixo do t´ıtulo, est˜ao as caixas de entrada dos dados das propriedades de cada per´ıodo de dom´ınio das v´arias componentes c´osmicas (inﬂaton, radia¸c˜ao, materia e energia escura) mimetizadas pelo ﬂuido uniﬁcado. Essas propriedades s˜ao os tempos iniciais e ﬁnais do per´ıodo e o valor que o parˆametro da equa¸c˜ao de estado deve assumir. A aba R1 diz respeito ao per´ıodo de dom´ınio da radia¸c˜ao logo ap´os o big bang (explos˜ao que deu origem ao espa¸co- tempo) e antes do in´ıcio de Inﬂa¸c˜ao. Nessa aba deve- mos ﬁxar ω = 1/3; os tempos inicial e ﬁnal s˜ao ﬁxa- dos em valores arbitr´arios.3 A aba I ´e o espa¸co onde se deve entrar os dados do per´ıodo inﬂacion´ario, onde, por exemplo, ω = −1. A aba R2 ´e aquela do segundo dom´ınio da radia¸c˜ao, correspondente ao per´ıodo p´os- inﬂa¸c˜ao e pr´e-mat´eria. A aba M refere-se ao per´ıodo de dom´ınio da mat´eria, e, ﬁnalmente, a aba Λ da conta do per´ıodo em que o ﬂuido uniﬁcado comporta-se como a constante cosmol´ogica (ω = −1). Figura 2 - Comportamento da fun¸c˜ao exibida na Eq. (5) sobre- posto ao gr´aﬁco da Fig.1. Figura 2 - Comportamento da fun¸c˜ao exibida na Eq. (5) sobre- posto ao gr´aﬁco da Fig.1. Ao lado da caixa de entrada dos parˆametros, est´a a caixa de entrada dos dados referentes ao processo de integra¸c˜ao num´erica. Abaixo dela, uma caixa de mensa- gens, onde o software mostra ao usu´ario a sequˆencia de a¸c˜oes executadas. `A direita da tela do programa, uma grande caixa onde os gr´aﬁcos podem ser visualizados. Com as Eqs. 2. Modelo uniﬁcado A equa¸c˜ao do ﬂuido (derivada da primeira lei da Termo- dinˆamica) P (t) = ω (t) ε (t) , (4) (4) ˙ε + 3 ˙a a (P + ε) = 0, (2) (2) em que a fun¸c˜ao ω (t) deve ter o comportamento tal como o ilustrado na Fig. 1. O problema apresentado pelo modelo de mercado ´e que esse comportamento ´e descont´ınuo e a fun¸c˜ao ω (t) n˜ao pode ser utilizada nas Eqs. (2) e (3) se o que se deseja ´e integrar a Eq. (2) para todos os per´ıodos de evolu¸c˜ao do universo conti- nuamente. e a equa¸c˜ao de estado P = ωε, (3) (3) onde ε ´e a densidade de energia, P ´e a press˜ao e ω ´e conhecido como parˆametro da equa¸c˜ao de estado. Cada Software MUFCosm como ferramenta de estudo dos modelos da cosmologia padr˜ao 1312-3 1312-3 Figura 1 - Comportamento de ω(t) para as diversas fases sequen- ciais de dom´ınio das componentes do ﬂuido cosmol´ogico. em que ω (t) ´e dado pela Eq. (5). Essa equa¸c˜ao dife- rencial n˜ao tem solu¸c˜ao anal´ıtica e depende de m´etodos num´ericos para ser integrada. Para essa integra¸c˜ao foi escolhido o m´etodo de Runge-Kutta de quarta or- dem [22]. Usualmente, o per´ıodo inﬂacion´ario ´e descrito como sendo uma consequˆencia da transi¸c˜ao de fase de um campo escalar ϕ, em que o potencial V associado `a esse campo passa de um estado de maior energia para outro de menor energia [5,23]. Com o modelo uniﬁcado para o ﬂuido cosmol´ogico, torna-se poss´ıvel a obten¸c˜ao de um campo escalar ϕ uniﬁcado que satisfaz as condi¸c˜oes Figura 1 - Comportamento de ω(t) para as diversas fases sequen- ciais de dom´ınio das componentes do ﬂuido cosmol´ogico. { ε = 1 2 ˙ϕ2 + V (ϕ) , P = 1 2 ˙ϕ2 −V (ϕ) , (7) (7) Utilizando as propriedades da fun¸c˜ao Theta de He- aviside [19, 20] em sua parametriza¸c˜ao em termos da fun¸c˜ao arctan, encontramos a seguinte fun¸c˜ao com o comportamento semelhante ao da requerida (ver Fig. 1) em que ε ´e a densidade de energia e P ´e a press˜ao. Este campo ϕ est´a associado ao potencial V (ϕ) v´alido por toda a hist´oria do universo. ω(t) = 5 ∑ i=1 ωi π {arctan [10α (t −ti−1)] −arctan [10α (t −ti)]} , (5) 2O software MUFCosm est´a dispon´ıvel no s´ıtio http://mufcosm.webnode.com/downloads/. No mesmo s´ıtio encontram-se os links de onde se pode obter o interpretador Python, bem como os m´odulos necess´arios para rodar o arquivo execut´avel do programa MUFCosm. 3Os tempos inicial ti e ﬁnal tf (com tf > ti) s˜ao escolhidos arbitrariamente porque estamos interessados mais no comportamento funcional do modelo – que deve ser nitidamente observado nas curvas a (t), ω (t) e V (ϕ) – e menos interessados na descri¸c˜ao real´ıstica da evolu¸c˜ao c´osmica – a qual, embora poss´ıvel, torna as curvas a (t), ω (t) e V (ϕ) dif´ıceis de serem visualizadas. 3.2. An´alise de dados e constru¸c˜ao dos gr´aﬁcos Na aba An´alise Num´erica, ilustrada na Fig. 5, o usu´ario fornece os dados necess´arios para integrar numerica- mente a Eq. (6) para a derivada temporal do fator de escala (da/dt). O m´etodo de Runge-Kutta necessita de um ponto inicial conhecido, que chamamos de (tvi, avi). O usu´ario fornece os valores de tvi e avi nos dois pri- meiros campos da aba An´alise Num´erica. O campo H0, referente a constante de Hubble, ´e o valor que o parˆametro de Hubble5 assume no tempo atual. Os cam- pos α e Grau referem-se respectivamente `a constante de suaviza¸c˜ao e o grau de precis˜ao do m´etodo num´erico. 3. Software MUFCosm [24] Os cam- pos α e Grau referem-se respectivamente `a constante de suaviza¸c˜ao e o grau de precis˜ao do m´etodo num´erico. Com os campos QTDE. de Pontos ´e poss´ıvel ter um Figura 3 - Tela de trabalho o MUFCosm. Figura 3 - Tela de trabalho o MUFCosm. Figura 4 - Entrada de dados referentes a caracteriza¸c˜ao dos per´ıodos de universo. O MUFCosm foi implementado em linguagem de programa¸c˜ao Python, devido `a maior legibilidade do c´odigo fonte em compara¸c˜ao `as linguagens tradicio- nais [25]. Al´em disso, a linguagem Python ´e ´otima para implementa¸c˜ao de GUI (interface gr´aﬁca com o usu´ario, ou seja, s˜ao os recursos que permitem a intera¸c˜ao en- tre o usu´ario e o computador atrav´es do mouse e te- clado) pois vem com uma interface orientada a objetos padr˜ao para a API (Interface de Programa¸c˜ao de Apli- cativos) de GUI, chamada Tkinter. Juntamente com um pacote gratuito de extens˜oes conhecido como PMW (Python Megawidgets), essa linguagem de programa¸c˜ao ´e uma poderosa ferramenta de intera¸c˜ao entre m´aquina e usu´ario [26]. Figura 4 - Entrada de dados referentes a caracteriza¸c˜ao dos per´ıodos de universo. A maior vantagem quanto ao uso de Python se d´a pela facilidade de trabalhar com recursos de com- puta¸c˜ao cient´ıﬁca, tais como gerar os gr´aﬁcos e proces- samentos num´ericos [27]. Com a utiliza¸c˜ao do m´odulo matplotlib, ´e poss´ıvel obter gr´aﬁcos de alta qualidade e ainda salv´a-los em uma ampla gama de formatos, tudo de maneira interativa [28,29]. 5O parˆametro de Hubble ´e deﬁnido em termos do fator de escala a (t) e de sua derivada temporal ( ˙a = da dt ) com 4Enfatizamos que esses valores escolhidos n˜ao priorizam a correspondˆencia com as previs˜oes; os valores de tempo cosmol´ogico real´ısticos geram gr´aﬁcos com escala que diﬁculta a identiﬁca¸c˜ao dos pontos de inﬂex˜ao, inviabilizando a identiﬁca¸c˜ao dos diferentes regimes evolutivos (que ´e justamente o que queremos estudar com o nosso toy-model). ( ) 3. Software MUFCosm [24] (1), (2) e (4), foi poss´ıvel encontrar uma equa¸c˜ao diferencial que rege o comportamento do fator de escala do universo em rela¸c˜ao ao tempo [18,21]. da dt = 2 3 a (t) ( t + ∫ ω (t) dt ), (6) (6) 1312-4 Cuzinatto e Morais Figura 3 - Tela de trabalho o MUFCosm. ⌈ O MUFCosm foi implementado em linguagem de programa¸c˜ao Python, devido `a maior legibilidade do c´odigo fonte em compara¸c˜ao `as linguagens tradicio- nais [25]. Al´em disso, a linguagem Python ´e ´otima para implementa¸c˜ao de GUI (interface gr´aﬁca com o usu´ario, ou seja, s˜ao os recursos que permitem a intera¸c˜ao en- tre o usu´ario e o computador atrav´es do mouse e te- clado) pois vem com uma interface orientada a objetos padr˜ao para a API (Interface de Programa¸c˜ao de Apli- cativos) de GUI, chamada Tkinter. Juntamente com um pacote gratuito de extens˜oes conhecido como PMW (Python Megawidgets), essa linguagem de programa¸c˜ao ´e uma poderosa ferramenta de intera¸c˜ao entre m´aquina e usu´ario [26]. A maior vantagem quanto ao uso de Python se d´a pela facilidade de trabalhar com recursos de com- puta¸c˜ao cient´ıﬁca, tais como gerar os gr´aﬁcos e proces- samentos num´ericos [27]. Com a utiliza¸c˜ao do m´odulo matplotlib, ´e poss´ıvel obter gr´aﬁcos de alta qualidade e ainda salv´a-los em uma ampla gama de formatos, tudo de maneira interativa [28,29]. 3.1. Entrada de dados Nessa ´area (ver Fig. 4), o usu´ario informa as carac- ter´ısticas de cada per´ıodo. Os valores mostrados na ﬁgura foram escolhidos de forma a gerar gr´aﬁcos com mudan¸ca de comportamento vis´ıvel.4 Nessa ´area, o usu´ario poder´a entrar com um valor de ω e os tempos absolutos em que este ´e vigente. A imagem na Fig. 4 mostra o gr´aﬁco do comportamento do fator de escala f Figura 4 - Entrada de dados referentes a caracteriza¸c˜ao dos per´ıodos de universo. 3.2. An´alise de dados e constru¸c˜ao dos gr´aﬁcos Na aba An´alise Num´erica, ilustrada na Fig. 5, o usu´ario fornece os dados necess´arios para integrar numerica- mente a Eq. (6) para a derivada temporal do fator de escala (da/dt). O m´etodo de Runge-Kutta necessita de um ponto inicial conhecido, que chamamos de (tvi, avi). O usu´ario fornece os valores de tvi e avi nos dois pri- meiros campos da aba An´alise Num´erica. O campo H0, referente a constante de Hubble, ´e o valor que o parˆametro de Hubble5 assume no tempo atual. 3.1. Entrada de dados Nessa ´area (ver Fig. 4), o usu´ario informa as carac- ter´ısticas de cada per´ıodo. Os valores mostrados na ﬁgura foram escolhidos de forma a gerar gr´aﬁcos com mudan¸ca de comportamento vis´ıvel.4 Nessa ´area, o usu´ario poder´a entrar com um valor de ω e os tempos absolutos em que este ´e vigente. A imagem na Fig. 4 mostra o gr´aﬁco do comportamento do fator de escala do universo para aquele valor de ω fornecido. Com os campos QTDE. de Pontos ´e poss´ıvel ter um controle independente do passo de an´alise num´erica em 4Enfatizamos que esses valores escolhidos n˜ao priorizam a correspondˆencia com as previs˜oes; os valores de tempo cosmol´ogic real´ısticos geram gr´aﬁcos com escala que diﬁculta a identiﬁca¸c˜ao dos pontos de inﬂex˜ao, inviabilizando a identiﬁca¸c˜ao dos diferente regimes evolutivos (que ´e justamente o que queremos estudar com o nosso toy-model). ( ) Software MUFCosm como ferramenta de estudo dos modelos da cosmologia padr˜ao 1312-5 1312-5 Figura 6 - Nessa aba, os dados necess´arios para a gera¸c˜ao dos gr´aﬁcos s˜ao fornecidos. cada per´ıodo. Dessa forma, os per´ıodos mais cr´ıticos (tal como o in´ıcio da expans˜ao `a partir do big bang) po- dem ser integrados com um precis˜ao bastante grande e ao mesmo tempo, os per´ıodos de comportamento mais estabilizados (como o dom´ınio da materia) podem ser integrados com um passo de analise maior, ganhando em tempo de processamento de dados. Os trˆes bot˜oes na parte inferior dessa widget s˜ao res- pectivamente para Ajuda (s´ımbolo com o sinal de inter- roga¸c˜ao), Plotagem de Relat´orios (feita ap´os a an´alise conclu´ıda; representado pelo conjunto de trˆes folhas) e, por ´ultimo, a execu¸c˜ao da An´alise Num´erica (cujo ´ıcone ´e uma calculadora). Figura 5 - Aba An´alise Num´erica, onde o usu´ario entra com os dados necess´arios para integra¸c˜ao num´erica. Figura 6 - Nessa aba, os dados necess´arios para a gera¸c˜ao dos gr´aﬁcos s˜ao fornecidos. Figura 7 - Gr´aﬁco do comportamento do parˆametro da equa¸c˜ao de estado no tempo. Figura 5 - Aba An´alise Num´erica, onde o usu´ario entra com os dados necess´arios para integra¸c˜ao num´erica. Na aba “a × t” (vide Fig. 6), s˜ao encontrados os dados referentes a constru¸c˜ao do gr´aﬁco de a (t). Nessa aba, o usu´ario pode escolher o t´ıtulo do gr´aﬁco assim como os t´ıtulos dos eixos coordenados. ´E poss´ıvel tamb´em selecionar estilo e cor da linha. 3.1. Entrada de dados Se for de in- teresse, o usu´ario pode determinar, no campo Especi- ﬁcar Intervalo, regi˜oes espec´ıﬁcas para serem visuali- zadas ajustando adequadamente os valores m´ınimo e m´aximo da abscissa e da ordenda. Os ´ıcones no canto inferior direito d˜ao as op¸c˜oes de salvar a ﬁgura (s´ımbolo com o disquete), abri-la com o visualizador do m´odulo matplotlib (´ıcone com as curvas de um gr´aﬁco) ou pr´e- visualiz´a-la na pr´opria tela de trabalho do MUFCosm (bot˜ao com a lupa). As abas “ω × t” e “V × ϕ” s˜ao compostas pelos mesmos elementos, por´em, os gr´aﬁcos exibidos s˜ao outros: o do parˆametro da equa¸c˜ao de es- tado ω que caracteriza o per´ıodo cosmol´ogico em fun¸c˜ao do tempo universal t e o do potencial V em fun¸c˜ao do campo escalar uniﬁcado ϕ. Figura 7 - Gr´aﬁco do comportamento do parˆametro da equa¸c˜ao de estado no tempo. Fator de escala em fun¸c˜ao de tempo Como ω ´e uma fun¸c˜ao cont´ınua do tempo, a Eq. (6) para o fa- tor de escala a (t) pode ser integrada numericamente. O MUFCosm faz essa integra¸c˜ao de forma r´apida e intera- tiva, sendo que o usu´ario n˜ao necessita ter nenhum co- nhecimento em linguagens de programa¸c˜ao e nenhuma habilidade com softwares matem´aticos. Um exemplo de gr´aﬁco do fator de escala gerado pode ser visualizado na Fig. 8. 3.3. Gr´aﬁcos gerados Parˆametro ω em fun¸c˜ao do tempo A fun¸c˜ao para ω (t) dada na Eq. (5) ´e cont´ınua e descreve o comportamento do parˆametro da equa¸c˜ao de estado no tempo. Atrav´es da aba “ω × t”, o MUFCosm gera o gr´aﬁco desse comportamento que pode ser observado na Fig. 7. Potencial em fun¸c˜ao do campo escalar ϕ O MUFCosm gera tamb´em o gr´aﬁco do potencial em fun¸c˜ao de um campo escalar uniﬁcado referente a hist´oria do universo (ver Fig. 9), satisfazendo as condi¸c˜oes preditas na Eq. (7). 1312-6 Cuzinatto e Morais Figura 8 - Gr´aﬁco do fator de escala do universo em fun¸c˜ao do tempo, obtido numericamente. para a (t) dif´ıceis de resolver. Escrevemos o software MUFCosm para resolver essa conta numericamente. O software MUFCosm apresenta uma interface gr´aﬁca do tipo janelas, que o torna de f´acil utiliza¸c˜ao pelo usu´ario n˜ao familiarizado com programa¸c˜ao. Con- forme descrito detalhadamente ao longo do texto desse artigo, ´e poss´ıvel digitar os parˆametros do modelo cos- mol´ogico que se quer estudar, quer seja a solu¸c˜ao a (t) para o universo dominado pela radia¸c˜ao, quer seja para o modelo completo com quatro componentes. Os resultados num´ericos conseguidos `a partir do MUFCOsm s˜ao consistentes com os resultados num´ericos que se obt´em de um software de c´alculo anal´ıtico e num´erico muito conhecido e conﬁ´avel, o Mathematica R⃝. De fato, escrevemos um c´odigo de comandos no Mathematica [24] incluindo as equa¸c˜oes do modelo uniﬁcado, em particular as Eqs. (5) e (6). Esse c´odigo integra numericamente a equa¸c˜ao para o fator de escala fornecendo o gr´aﬁco de a (t) . Antes disso, escreve-se a fun¸c˜ao ω (t) usando o Mathematica para calcular explicitamente a combina¸c˜ao de termos da Eq. (5). Com a (t) e ω (t) obtemos ε (t) usando as Eqs. (2) e (3). Munidos com as formas funcionais de ε (t) e P (t) – Eq. (3) – ´e poss´ıvel resolver o sistema (7) para obter o campo escalar ϕ associado ao ﬂuido uniﬁcado e o potencial V (ϕ). As fun¸c˜oes ω (t) e a (t) obtidas com este processo, realizado com o software Mathematica, aparecem na Fig. 10. Figura 8 - Gr´aﬁco do fator de escala do universo em fun¸c˜ao do tempo, obtido numericamente. Figura 9 - Gr´aﬁco do potencial em fun¸c˜ao do campo escalar. As curvas da Fig. 3.3. Gr´aﬁcos gerados 10 apresentam o mesmo com- portamento funcional das curvas correspondentes ω (t), a (t) e V (ϕ) obtidas a partir do nosso software MUF- Cosm, cf. as Figs. (7), (8) e (9). Isso ´e um teste de consistˆencia importante para o nosso c´odigo computa- cional e confere conﬁabilidade ao software MUFCosm que produzimos. Figura 9 - Gr´aﬁco do potencial em fun¸c˜ao do campo escalar. 4. Coment´arios ﬁnais O fato de podermos controlar os parˆametros do mo- delo d´a ao software um car´ater educacional importante. O fato de podermos controlar os parˆametros do mo- delo d´a ao software um car´ater educacional importante. Em verdade, o estudante que come¸ca a aprender cos- mologia pode usar o software para aprender as carac- ter´ısticas dinˆamicas dos per´ıodos distintos da evolu¸c˜ao c´osmica. Esse estudante pode focar sua aten¸c˜ao nas eras de inﬂa¸c˜ao, de dom´ınio da radia¸c˜ao, de predo- minˆancia da mat´eria ou de prevalecimento da Cons- tante Cosmol´ogica, de maneira isolada ou combinando duas ou mais componentes. A resposta ´e imediata ap´os a entrada dos dados e o comportamento funcional do fator de escala ´e exibido na forma de um gr´aﬁco no pr´oprio corpo do programa. Al´em disso, o modelo uni- ﬁcado apresenta uma solu¸c˜ao para a (t) que inclui se- quencialmente e continuamente as quatro componentes principais do universo e isso n˜ao ´e assunto coberto por livros introdut´orios de cosmologia, o que s´o enfatiza a caracter´ıstica pedag´ogica desse trabalho. Na introdu¸c˜ao desse artigo apresentamos as equa¸c˜oes fundamentais da cosmologia, as quais, quando resol- vidas, d˜ao a forma da fun¸c˜ao a (t) para o parˆametro de distˆancias do universo. Essa fun¸c˜ao ter´a formas diferentes para cada componente que se sup˜oe domi- nante em um dado momento da evolu¸c˜ao c´osmica. Por exemplo, para uma era dominada pela radia¸c˜ao, tem-se a ∝ √ t, cf. se lˆe nas Refs. [1, 13] Os outros compo- nentes poss´ıveis considerados aqui s˜ao a mat´eria sem press˜ao (ordin´aria e escura), o campo de inﬂa¸c˜ao e a constante cosmol´ogica. O modelo cosmol´ogico para o ﬂuido uniﬁcado pretende considerar todas essas com- ponentes de forma sequˆencial e com uma equa¸c˜ao de estado P = ωρ cont´ınua. Essa equa¸c˜ao de estado ´e um tanto complicada, dada em termos de uma somat´oria com fun¸c˜oes arctan. Isso torna as equa¸c˜oes diferencias Software MUFCosm como ferramenta de estudo dos modelos da cosmologia padr˜ao 1312-7 1312-7 Figura 10 - Curvas de ω (t) e a (t) para o modelo uniﬁcado a partir do c´odigo em Mathematica [9] A. Liddle, An Introduction to Modern Cosmology (Wi- ley, San Francisco, 2003), 2a ed. [10] S. Perlmutter et al., Nature 392, 51 (1998). [11] A.G. Riess, A.V. Filippenko, P. Challis, A. Clocchiatti, A. Diercks, P.M. Garnavich, R.L. Gilliland, C.J. Ho- gan, S. Jha, R.P. Kirshner, B. Leiundgut, M.M. Phil- lips, D. Reiss, B.P. Schmidt, R.A. Schommer, R.C. 4. Coment´arios ﬁnais Smith, J. Spyromilio, C. Stubbs, N.B. Suntzeﬀ, J. Tonry, The Astronomical Journal 116, 1009 (1998). [12] D.N. Spergel, L. Verde, H. V. Peiris, E. Komatsu, M. R. Nolta, C. L. Bennett, M. Halpern, G. Hinshaw, N. Jarosik, A. Kogut, M. Limon, S. S. Meyer, L. Page, G. S. Tucker, J. L. Weiland, E. Wollack, E. L. Wright, Astrophys. J. Suppl. 148, 175 (2003). [13] V. Mukhanov, Physical Foundations of Cosmology (Cambridge University Press, New York, 2005). [14] R. K. Pathria, Statistical Mechanics (Butterworth- Heinemann, Oxford, 1996), 2a ed. [15] S. Weinberg, Cosmology (Oxford University Press, New York, 2008). [16] A.H. Guth, Phys. Rev. D 23, 357 (1981). [17] A.H. Guth, O Universo Inﬂacion´ario (Campus, Rio de Janeiro, 1997). [18] R.R. Cuzinatto and E.M. Morais, Uniﬁed Equation of State for the Cosmological Fluid, to be published (in preparation). Figura 10 - Curvas de ω (t) e a (t) para o modelo uniﬁcado a partir do c´odigo em Mathematica [19] S. Nair, Advanced Topics in Applied Mathematics: For Engineering and Physical Sciences (Cambridge Univer- sity Press, New York, 2011). Agradecimentos [20] K.B. Oldhan, J. Myland, J. Spanier, An Atlas of Functions: with Equator, the atlas functions calcula- tor (Springer, New York, 2008), 2a ed. Os autores agradecem a FAPEMIG (processo CEX APQ 04440-10) pelo apoio ﬁnanceiro. [21] E.M. Morais, Modelo Uniﬁcado para o Fluido Cos- mol´ogico. Monograﬁa de inicia¸c˜ao cient´ıﬁca. Publica¸c˜ao interna do ICT/UNIFAL-MG. Dispon´ıvel em http: //mufcosm.webnode.com/downloads/. Referˆencias [1] B. Ryden, Introduction to Cosmology (Addison Wesley, San Francisco, 2003). [22] J.D. Santos e C.S. Zanoni, M´etodos Num´ericos (Ed. Universit´aria da UFPE, Recife, 2006). [2] S. Weinberg, Gravitation and Cosmology (John Wiley & Sons, New York, 1972). [23] S. Bonometto, V. Gorini, U. Moschella, Modern Cos- mology (IOP Publishing, Bristol, 2002). [3] T. P. Cheng, Relativity, Gravitation and Cosmology: A Basic Introdution (Oxford University Press, New York, 2005). [24] http://mufcosm.webnode.com/downloads/. [25] L.E. Borges, Python para Desenvolvedores. 2ed. Dis- pon´ıvel em http://ark4n.wordpress.com/python/. [4] R. C. Tolman, Relativity, Thermodynamics and Cos- mology (Oxford University Press, Oxford, 1934). [26] M. Lutz, Programming Python (O’Reilly Media, Sebas- topol, 2011), 4aed. [5] J.A. Peacock, Cosmological Physics (Cambride Univer- sity Press, Cambridge, 1999). [27] H.P. Langtangen, A Primer on Scientiﬁc Programming with Python (Springer, Heidelberg, 2012), 3a ed. [6] E. Hubble, Procedings of the National Academy of Sci- ence 15, (1929). [28] S. Tosi, Matplotlib for Python Developers (Packt Pu- blishing, Birmingham, 2009). [7] R.E. Souza, Introdu¸c˜ao `a Cosmologia (Editora da Uni- versidade de S˜ao Paulo, S˜ao Paulo, 2004). [29] J. Hunter, D. Dale, E. Firing, M. Droettboom, Mat- plotlib User’s Guide, 2013. Dispon´ıvel em http:// matplotlib.org/Matplotlib.pdf. [8] D.W. Sciama, Modern Cosmology and the Dark Mat- ter Problem (Cambridge University Press, New York, 2003).
https://openalex.org/W4395027703	https://www.researchsquare.com/article/rs-4284571/latest.pdf	English	null	TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory	Research Square (Research Square)	2,024	cc-by	14,261	TOP2DFVT: An E¨cient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory Marcelo Vitor Oliveira Araujo Federal University of Alagoas Arnaldo dos Santos Júnior Federal University of Alagoas Romildo dos Santos Escarpini Filho Federal University of Alagoas Eduardo Nobre Lages Federal University of Alagoas Márcio André Araújo Cavalcante Research Article License:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Additional Declarations: The authors declare no competing interests. Optimization based on the Finite-Volume Theory Marcelo Vitor Oliveira Araujo(a) 0000-0002-4759-4374, Arnaldo dos Santos Júnior(a) 0009- 0001-1653-2285, Romildo dos Santos Escarpini Filho(b) 0000-0002-3530-6996, Eduardo Nobre Lages(a) 0000-0001-6704-4057 and Márcio André Araújo Cavalcante(c) 0000- 0002-8317-8714 (a) Center of Technology, Federal University of Alagoas, Maceió, 57072-900, Alagoas, Brazil. E- mail: marcelo.vitor.o.a@gmail.com; arnaldo@ctec.ufal.br; enl@ctec.ufal.br (b) Campus Arapiraca, Federal University of Alagoas, Penedo, 57200-000, Alagoas, Brazil. E- mail: romildo.escarpini@penedo.ufal.br Additional Declarations: The authors declare no competing interests. Version of Record: A version of this preprint was published at F1000Research on July 16th, 2024. See the published version at https://doi.org/10.12688/f1000research.150945.1. Corresponding Author Abstract. The finite-volume theory has shown to be numerically efficient and stable for topology optimization of continuum elastic structures. The significant features of this numerical technique are the local satisfaction of equilibrium equations and the employment of compatibility conditions along edges in a surface-averaged sense. These are essential properties to adequately mitigate some numerical instabilities in the gradient version of topology optimization algorithms, such as checkerboard, mesh dependence, and local minima issues. Several computational tools have been proposed for topology optimization employing analysis domains discretized with essential features for finite-element approaches. However, this is the first contribution to offer a platform to generate optimized topologies by employing a Matlab code based on the finite-volume theory for compliance minimization problems. The Top2DFVT provides a platform to perform 2D topology optimization of structures in Matlab, from domain initialization for structured meshes to TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory data post-processing. This contribution represents a significant advancement over earlier publications on topology optimization based on the finite-volume theory, which needed more efficient computational tools. Moreover, the Top2DFVT algorithm incorporates SIMP and RAMP material interpolation schemes alongside sensitivity and density filtering techniques, culminating in a notably enhanced optimization tool. The application of this algorithm to various illustrative cases confirms its efficacy and underscores its potential for advancing the field of structural optimization. Keywords: topology optimization; compliance minimization problem; finite-volume theory; Matlab. 1 INTRODUCTION In structural engineering, topology optimization is a technique that searches for the best material distribution inside an analysis domain based on an objective function and one or more constraints (Bendsøe and Sigmund, 2003). Therefore, topology optimization allows for the discovery of innovative and high-performance structural designs, which attracted the interest of mathematicians and engineers (Liu and Tovar, 2014). With the progressive development of computer technology and computational mechanics over the last decades, the structural topology optimization tools have gradually experienced improvements that allow the solution of medium and large-scale problems. In addition, topology optimization has become an effective strategy for generating innovative forms for additive manufacturing, architectural design, and engineering (Zhuang et al., 2023). In general, compliance evaluation has played an important role in topology optimization algorithms Since the pioneer work of Michell (1904), who derived the optimality criteria (OC) method, and the reconstruction proposed by Bendsøe and Kikuchi (1988), a great part of the advances in topology optimization has been achieved by employing methodologies based on structural compliance minimization problems. Some studies on this field can still be found in Liu et al. (2023), Yi et al. (2023), Lee et al. (2023), Arruda et al. (2022), Bouajila et al. (2021), and Ferrari and Sigmund (2020). In topology optimization algorithms, the interest is in determining whether we should put material or not, which generates a “black and white” design. Therefore, the structural 2 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante material distribution is obtained by a binary “0-1”, where 0 indicates void and 1 indicates the presence of material. However, this kind of topology optimization algorithms lead to an integer programming problem, which has revealed to be an unfeasible approach for large scale topology optimization problems. An alternative approach is the SIMP (Solid Isotropic Material with Penalization) method, which has been extensively used due to its versatility, convergence, and ease implementation (Rozvany, 2009). In this approach, the material properties can be evaluated inside each element of the discretized domain, and the design variables are the elements' relative densities. Therefore, the mechanical properties are modeled by the material relative density raised to a penalty factor that penalizes their intermediate values. 1 INTRODUCTION Another interpolation scheme to penalize intermediate values of relative density is the RAMP (Rotational Approximation of Material Properties) method proposed by Stolpe and Svanberg (2001), which employs a concave penalty function to suppress these intermediate values in the objective function. Unlike the SIMP method, the RAMP model presents non-zero sensitivity at zero density, so this model is especially efficient to remedy some numerical difficulties presented in problems with very low densities (Deaton and Grandhi, 2014). Different authors have developed educational algorithms to design optimized topologies in the last two decades. The trailblazer top99 educational code written in Matlab proposed by Sigmund (2001) had promoted important impacts in the topology optimization field, such as teaching of topology optimization tools in undergraduate courses, building simple code for new researchers, and pioneering a new popular category of publications in the structural optimization field: educational articles self-containing compact codes for teaching and research (Zhou and Sigmund, 2021). Beyond the well-known top99 Matlab code, several computer tools for Matlab and other platforms are available, such as PETSc by Smit et al. (2021) and Aage et al. (2015) for Python; TopOpt app by Aage et al. (2013) for language C; Stutz et al. (2022), Aage and Lazarov (2013), and Borrvall and Petersson (2001) for C++ language; Liu et al (2005) for Femlab; and Sokól (2011) for Mathematica. However, a significant part of the proposed educational algorithms for topology optimization is written in Matlab language, as top99neo by Ferrari and Sigmund (2020), an 88-line code for parametrized level-set method by Wei et al. (2018), top88 by Andreassen et al. (2011), Different authors have developed educational algorithms to design optimized topologies in the last two decades. The trailblazer top99 educational code written in Matlab proposed by Sigmund (2001) had promoted important impacts in the topology optimization field, such as teaching of topology optimization tools in undergraduate courses, building simple code for new researchers, and pioneering a new popular category of publications in the structural 3 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory top3d by Liu and Tovar (2014), PolyTop by Talischi et al. (2012), HoneyTop90 by Kumar (2023), a 115-line code for multi-material topology optimization by Tavakoli and Mohseni (2014), and GRAND by Zegard and Paulino (2014). 1 INTRODUCTION In the top99 topology optimization code, the performance of several operations can be increased by exploiting the strengths of Matlab, such as loop vectorization and memory preallocation, and by restructuring the program, as moving portions of code out of the optimization loop so they would be executed once (Andreassen et al., 2011). Therefore, Andreassen et al. (2011) have proposed an 88-line code in Matlab for compliance minimization by allocating these computational features (top88), which has substantially improved the computational performance of the optimization algorithm. Later, Liu and Tovar (2014) have extended this algorithm to three-dimensional problems by also placing other strategies for topology optimization of compliant mechanisms and heat conduction problems. With the evolution of topology optimization research field and Matlab, the top88 code has become outdated, which has motivated the publication of the new generation of the top99 code (top99neo) by Ferrari and Sigmund (2020), making some improvements in the assembly operations, accelerating the Optimality Criteria (OC) method, filters implementation, and extending to three-dimensional structures. Araujo et al. (2020a,b) propose applying the finite-volume theory for topology optimization considering compliance minimization. This theory has been shown to be numerically stable for optimization problems, especially its checkerboard-free property, even when a non- filtering technique is employed. Numerical stability is an essential feature of the finite- volume theory applied in topology optimization tools to obtain more reliable optimized topologies. Also, this technique has shown to be well suitable method for elastic stress analysis in solid mechanics, investigations of its numerical efficiency can be found in Araujo et al. (2021), Cavalcante et al. (2007a,b, 2008) and Cavalcante and Pindera (2012a,b). The satisfaction of equilibrium equations at the subvolume level, concomitant to kinematic and static continuities established in a surface-averaged sense between common faces of adjacent subvolumes, are features that distinguish the finite-volume theory from the finite-element method. Thus, in the finite-volume theory, the connections between 4 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante adjacent subvolumes occur through subvolumes' faces, which is more likely from the continuum mechanics point of view. This contribution provides a new topology optimization tool for the analysis of 2D structures using the Matlab language, which starts from domain discretization and continues until data is post-processed. 1 INTRODUCTION In addition, this is the first time a platform for optimizing structures using the finite-volume theory can be applied to medium and large- scale problems, besides obtaining checkerboard-free and mesh-independent designs. The topology optimization tool also incorporates the SIMP and RAMP methods and the sensitivity and density filters. Employing a symmetric modified stiffness matrix also represents an advance since it accelerates the algorithm and establishes a relation between resultant forces and displacements instead of tractions and displacements, which are energetically conjugated static and kinematic quantities. These improvements have dramatically reduced the computational cost and solved the oscillatory phenomenon issue through the RAMP approaches, especially compared with the results in Araujo et al. (2020a). More details about the implementation can be found in the GitHub link (https://github.com/fvt7782/Top2DFVT). 2. FINITE-VOLUME THEORY In general, the finite-volume theory employs the stress and displacement fields and imposes boundary and continuity conditions between adjacent subvolumes in an average-sense, which has guaranteed the checkerboard-free property discussed in Araujo et al. (2020a). Additionally, the differential equilibrium equations are locally satisfied in an average-sense (Araujo et al., 2021), and the displacement field in the subvolume is modeled by second- order polynomials defined in local coordinates (Cavalcante et al., 2007a). The presented formulation has its roots in the standard version of the finite-volume theory presented in Cavalcante and Pindera (2012a) for structured meshes formed by rectangular subvolumes. Fundamentally, the structural analysis problem involves mechanical quantities evaluation, as applied loads, internal forces, displacements, and strains. The main objective is determining the stress and displacements when structural discretized domains are employed, where stress-strain relation can be easily expressed. 5 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory Figure 1. Discretized reference domain and global coordinate system (left) and subvolume and local coordinate system (right) Figure 1. Discretized reference domain and global coordinate system (left) and subvolume and local coordinate system (right) Figure 1 presents the analysis domain in 𝑥1 −𝑥2 plane, which is discretized in 𝑁𝑞 subvolumes. The subvolume dimensions are 𝑙(𝑞) and ℎ(𝑞) for 𝑞= 1, … , 𝑁𝑞, where 𝑥1 (𝑞) and 𝑥2 (𝑞) represent the local coordinate system. Following Cavalcante and Pindera (2012a), the displacement of a subvolume 𝑞 can be approximated by an incomplete quadratic version of Legendre polynomial expansion in the local coordinate system as follows: 𝑢𝑖 (𝑞) = 𝑊𝑖(00) (𝑞) + 𝑥1 (𝑞)𝑊𝑖(10) (𝑞) + 𝑥2 (𝑞)𝑊𝑖(01) (𝑞) + 1 2 (3𝑥1 (𝑞)2 − 𝑙(𝑞)2 4 )𝑊𝑖(20) (𝑞) + 1 2 (3𝑥2 (𝑞)2 − ℎ(𝑞)2 4 ) 𝑊𝑖(02) (𝑞) , (1) (1) where 𝑖= 1,2 and 𝑊𝑖(𝑚𝑛) (𝑞) are unknown coefficients of the displacement field. Therefore, the surface-averaged displacement components of a generic subvolume are represented in Figure 2(a) and can be defined as where 𝑖= 1,2 and 𝑊𝑖(𝑚𝑛) (𝑞) are unknown coefficients of the displacement field. Therefore, the surface-averaged displacement components of a generic subvolume are represented in Figure 2(a) and can be defined as where 𝑖= 1,2 and 𝑊𝑖(𝑚𝑛) (𝑞) are unknown coefficients of the displacement field. 2. FINITE-VOLUME THEORY Therefore, the surface-averaged displacement components of a generic subvolume are represented in Figure 2(a) and can be defined as 𝑢̅𝑖 (𝑞,𝑝) = 1 𝑙(𝑞) ∫ 𝑢𝑖(𝑥1 (𝑞), ∓ ℎ(𝑞) 2 )𝑑𝑥1 (𝑞) 𝑙(𝑞) 2 −𝑙(𝑞) 2 , for 𝑝= 1, 3 𝑢̅𝑖 (𝑞,𝑝) = 1 ℎ(𝑞) ∫ 𝑢𝑖(± 𝑙(𝑞) 2 , 𝑥2 (𝑞)) 𝑑𝑥2 (𝑞) ℎ(𝑞) 2 −ℎ(𝑞) 2 , for 𝑝= 2, 4 . (2) (2) 6 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante Figure 2. Degrees of freedom in a generic subvolume q: (a) surface-averaged displacements, (b) surface-averaged tractions, and (c) resultant forces along edges Figure 2. Degrees of freedom in a generic subvolume q: (a) surface-averaged Figure 2. Degrees of freedom in a generic subvolume q: (a) surface-averaged displacements, (b) surface-averaged tractions, and (c) resultant forces along edges Similarly, considering the application of Cauchy’s law and the plane stress state, the surface-averaged traction components at the subvolume faces can be evaluated as 𝑡̅𝑖 (𝑞,𝑝) = ∓ 1 𝑙(𝑞) ∫ 𝜎2𝑖(𝑥1 (𝑞), ∓ ℎ(𝑞) 2 )𝑑𝑥1 (𝑞) 𝑙(𝑞) 2 −𝑙(𝑞) 2 , for 𝑝= 1, 3 𝑡̅𝑖 (𝑞,𝑝) = ± 1 ℎ(𝑞) ∫ 𝜎1𝑖(± 𝑙(𝑞) 2 , 𝑥2 (𝑞)) 𝑑𝑥2 (𝑞) ℎ(𝑞) 2 −ℎ(𝑞) 2 , for 𝑝= 2, 4 , (3) (3) where 𝑡̅𝑖 (𝑞,𝑝) are adequately represented in Figure 2(b). where 𝑡̅𝑖 (𝑞,𝑝) are adequately represented in Figure 2(b). where 𝑡̅𝑖 (𝑞,𝑝) are adequately represented in Figure 2(b). where 𝑡̅𝑖 (𝑞,𝑝) are adequately represented in Figure 2(b). Following Araujo et al. (2020a), the local system of equations for a generic subvolume can be established as Following Araujo et al. (2020a), the local system of equations for a generic subvolume can be established as 𝒕̅(𝑞) = 𝑲(𝑞)𝒖̅(𝑞), (4) 𝒕̅(𝑞) = 𝑲(𝑞)𝒖̅(𝑞), (4) 7 7 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory where 𝒖̅(𝑞) = [𝑢̅1 (𝑞,1), 𝑢̅2 (𝑞,1), 𝑢̅1 (𝑞,2), 𝑢̅2 (𝑞,2), 𝑢̅1 (𝑞,3), 𝑢̅2 (𝑞,3), 𝑢̅1 (𝑞,4), 𝑢̅2 (𝑞,4)] 𝑇 is the local surface- averaged displacement vector, 𝒕̅(𝑞) = [𝑡̅1 (𝑞,1), 𝑡̅2 (𝑞,1), 𝑡̅1 (𝑞,2), 𝑡̅2 (𝑞,2),𝑡̅1 (𝑞,3),𝑡̅2 (𝑞,3), 𝑡̅1 (𝑞,4), 𝑡̅2 (𝑞,4)] 𝑇 is the local surface-averaged traction vector, and 𝑲(𝑞) is the local stiffness matrix for a generic subvolume 𝑞. However, 𝑲(𝑞) is a non-symmetric matrix, which increases the computational cost of topology optimization problems based on the finite-volume theory when compared to the same approaches based on the finite-element method. 2. FINITE-VOLUME THEORY Additionally, the surface-averaged tractions are not energetically conjugated with the surface-averaged displacements along the subvolume faces, which leads the 𝑲(𝑞) matrix to be more a pseudo stiffness matrix. Following Araujo et al. (2021), it can be defined a modified local system of equations in terms of resultant forces acting in the edges of a subvolume 𝑞, which are energetically conjugated with the surface-averaged displacements, as follows 𝑹(𝑞) = 𝑳̅(𝑞)𝒕̅(𝑞) = 𝑳̅(𝑞)𝑲(𝑞)𝒖̅(𝑞) = 𝑲̅(𝑞)𝒖̅(𝑞), (5) 𝑹(𝑞) = 𝑳̅(𝑞)𝒕̅(𝑞) = 𝑳̅(𝑞)𝑲(𝑞)𝒖̅(𝑞) = 𝑲̅(𝑞)𝒖̅(𝑞), (5) (5) (𝑞) = 𝑳̅(𝑞)𝑲(𝑞) is the modified local stiffness matrix, which is found to be a the local resultant force vector, whose components are illustrated in Figure 2(c), and 𝑳̅(𝑞) can be defined as 𝑳̅(𝑞) = [ 𝑳(𝑞,1) 𝟎 𝟎 𝟎 𝟎 𝑳(𝑞,2) 𝟎 𝟎 𝟎 𝟎 𝑳(𝑞,3) 𝟎 𝟎 𝟎 𝟎 𝑳(𝑞,4) ] for 𝑳(𝑞,𝑝) = [ 𝐿𝑝 (𝑞) 0 0 𝐿𝑝 (𝑞)], (6) (6) where 𝐿1 (𝑞) = 𝑙(𝑞), 𝐿2 (𝑞) = ℎ(𝑞), 𝐿3 (𝑞) = 𝑙(𝑞) and 𝐿4 (𝑞) = ℎ(𝑞) as illustrated in Figure 1. where 𝐿1 (𝑞) = 𝑙(𝑞), 𝐿2 (𝑞) = ℎ(𝑞), 𝐿3 (𝑞) = 𝑙(𝑞) and 𝐿4 (𝑞) = ℎ(𝑞) as illustrated in Figure 1. Therefore, the modified global system of equations can be written as 𝑹= 𝑲̅𝒖̅, (7) (7) 𝑹= 𝑲̅𝒖̅, where 𝑲̅ = ∑ 𝑸(𝑞)𝑇𝑲̅(𝑞)𝑸(𝑞) 𝑁𝑞 𝑞=1 is the modified global stiffness matrix, obtained by summing the individual contribution of each subvolume of the discretized domain, with summing the individual contribution of each subvolume of the discretized domain, with 8 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante 𝑸(𝑞) and 𝑸(𝑞)𝑇 being the kinematic and static incidence matrices, respectively, 𝑹 is the global resultant force vector, and 𝒖̅ is the global surface-averaged displacement vector. 3. TOPOLOGY OPTIMIZATION PROBLEMS FOR COMPLIANCE MINIMIZATION 3. TOPOLOGY OPTIMIZATION PROBLEMS FOR COMPLIANCE MINIMIZATION A significant portion of the progress in topology optimization has been made through the consideration of compliance minimization problems, whose concepts are well-established in the context of finite-element strategies. In this study, we implement the compliance minimization problem using linear elastic stress analysis based on the finite-volume theory. According to Araujo et al. (2021), the total work done by external loadings and the total strain energy of a deformed structure are equal for quasi-static analysis in the context of the standard finite-volume theory. As a result, the nested topology optimization problem for compliance minimization can be written as { Find 𝝆 which minimizes 𝐶(𝝆) = ∑ 𝒖̅(𝑞)𝑇𝑲̅(𝑞)𝑇𝒖̅(𝑞) 𝑁𝑞 𝑞=1 = ∑ 𝐸𝑞(𝜌𝑞)𝒖̅(𝑞)𝑇𝑲̅0 (𝑞)𝑇𝒖̅(𝑞) 𝑁𝑞 𝑞=1 subject to: 𝑉(𝝆) 𝑉̅ = 𝑓 0 ≤𝜌𝑞≤1 , (8) nd 𝝆 which minimizes 𝐶(𝝆) = ∑ 𝒖̅(𝑞)𝑇𝑲̅(𝑞)𝑇𝒖̅(𝑞) 𝑁𝑞 𝑞=1 = ∑ 𝐸𝑞(𝜌𝑞)𝒖̅(𝑞)𝑇𝑲̅0 (𝑞)𝑇𝒖̅(𝑞) 𝑁𝑞 𝑞=1 subject to: { subject to: 𝑉(𝝆) 𝑉̅ = 𝑓 0 ≤𝜌𝑞≤1 , (8) (8) 𝑉(𝝆) 𝑉̅ = 𝑓 0 ≤𝜌𝑞≤1 , (8) where 𝐶(𝝆) is the compliance function, defined as twice the work done by external loadings, 𝝆 is the relative density vector, 𝜌𝑞 is the relative density associated with the subvolume 𝑞, 𝑲̅0 (𝑞) is the subvolume modified stiffness matrix for a subvolume with unit Young's modulus, 𝑓 is the volume fraction, and 𝑉(𝝆) and 𝑉̅ are the material and reference domain volumes, respectively. where 𝐶(𝝆) is the compliance function, defined as twice the work done by external loadings, 𝝆 is the relative density vector, 𝜌𝑞 is the relative density associated with the subvolume 𝑞, 𝑲̅0 (𝑞) is the subvolume modified stiffness matrix for a subvolume with unit Young's modulus, 𝑓 is the volume fraction, and 𝑉(𝝆) and 𝑉̅ are the material and reference domain volumes, respectively. The problem presented in Eq. (8) is solved with a nested iterative loop, where at each iteration, the displacement 𝒖̅ is computed by solving the modified global system of equations presented in Eq. (7). The two major material interpolation functions are implemented in the algorithm: SIMP (Sigmund, 2007) and RAMP (Stolpe and Svanberg, 2001). 3. TOPOLOGY OPTIMIZATION PROBLEMS FOR COMPLIANCE MINIMIZATION The Young's modulus 𝐸𝑞(𝜌𝑞) of each subvolume can be evaluated by the following expressions: 9 9 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory 𝐸𝑞(𝜌𝑞) = 𝐸𝑚𝑖𝑛+ 𝜌𝑞 𝑝(𝐸0 −𝐸𝑚𝑖𝑛) for SIMP 𝐸𝑞(𝜌𝑞) = 𝐸𝑚𝑖𝑛+ 𝜌𝑞 1+𝑎(1−𝜌𝑞)(𝐸0 −𝐸𝑚𝑖𝑛) for RAMP , (9) (9) where 𝑝 and 𝑎 are the penalization factors for SIMP and RAMP methods, respectively, 𝐸0 is the material stiffness, and 𝐸𝑚𝑖𝑛 is the soft (void) material stiffness, which is a non-zero positive low value to avoid the singularity in the stiffness matrix. Figure 3 shows the concavity of the penalization functions performed by the SIMP and RAMP methods as presented by Eq. (9), where the ratio 𝐸𝑚𝑖𝑛𝐸0 ⁄ is adopted as 10−9. The RAMP method presents a more gradual increase in its concavity when compared to the SIMP method, which softens the numerical response of this method. The function concavity observed in the RAMP method is smoother and presents a slower convergence to the limit relative density values (0 or 1), as observed in the green (RAMP for 𝑎= 1) and blue (RAMP for 𝑎= 2) lines, which incurs in a more gradual convergence for this method. On the other hand, the SIMP method concentrates the relative density values in 0 or 1, as observed in concavity of the orange (SIMP for 𝑝= 2) and yellow (SIMP for 𝑝= 3) lines, promoting a faster convergence to the black and white design. where 𝑝 and 𝑎 are the penalization factors for SIMP and RAMP methods, respectively, 𝐸0 is the material stiffness, and 𝐸𝑚𝑖𝑛 is the soft (void) material stiffness, which is a non-zero positive low value to avoid the singularity in the stiffness matrix. Figure 3 shows the concavity of the penalization functions performed by the SIMP and RAMP methods as presented by Eq. (9), where the ratio 𝐸𝑚𝑖𝑛𝐸0 ⁄ is adopted as 10−9. The RAMP method presents a more gradual increase in its concavity when compared to the SIMP method, which softens the numerical response of this method. The function concavity observed in the RAMP method is smoother and presents a slower convergence to the limit relative density values (0 or 1), as observed in the green (RAMP for 𝑎= 1) and blue (RAMP for 𝑎= 2) lines, which incurs in a more gradual convergence for this method. 3.1 OBJECTIVE FUNCTION GRADIENT The gradient of the compliance with respect to the subvolume density 𝜌𝑟 can be determined by by by 𝜕𝐶(𝝆) 𝜕𝜌𝑟= ∑ [ 𝜕𝒖̅(𝑞)𝑇 𝜕𝜌𝑟𝑲̅(𝑞)𝑇 𝒖̅(𝑞) + 𝒖̅(𝑞)𝑇𝜕𝑲̅(𝑞)𝑇 𝜕𝜌𝑟𝒖̅(𝑞) + 𝒖̅(𝑞)𝑇𝑲̅(𝑞)𝑇𝜕𝒖̅(𝑞) 𝜕𝜌𝑟] 𝑁𝑞 𝑞=1 . (10) (10) Employing 𝑲̅(𝑞)𝑇 = 𝑲̅(𝑞), the Eq. (10) can be simplified to Employing 𝑲̅(𝑞)𝑇 = 𝑲̅(𝑞), the Eq. (10) can be simplified to 𝜕𝐶(𝝆) 𝜕𝜌𝑟= 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) + 2 ∑ [𝒖̅(𝑞)𝑇𝑲̅(𝑞) 𝜕𝒖̅(𝑞) 𝜕𝜌𝑟] 𝑁𝑞 𝑞=1 . (11) (11) 𝜕𝐶(𝝆) 𝜕𝜌𝑟= 𝒖̅(𝑟)𝑇𝜕𝑲 𝜕𝜌𝑟𝒖̅(𝑟) + 2 ∑ [𝒖̅(𝑞)𝑇𝑲 (𝑞) 𝜕𝒖(𝑞) 𝜕𝜌𝑟] 𝑁𝑞 𝑞=1 . (11) The Eq. (11) can be rewritten as The Eq. (11) can be rewritten as The Eq. (11) can be rewritten as The Eq. (11) can be rewritten as 𝜕𝐶(𝝆) 𝜕𝜌𝑟= 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) + 2𝒖̅𝑇𝑲̅ 𝜕𝒖̅ 𝜕𝜌𝑟= 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) + 2𝑹𝑝𝑇𝜕𝒖̅𝑢 𝜕𝜌𝑟+ 2𝑹𝑢𝑇𝜕𝒖̅𝑝 𝜕𝜌𝑟, (12) (12) where 𝑹𝑝 and 𝒖̅𝑝 are the prescribed force and displacement vectors, respectively, where 𝑹𝑝 and 𝒖̅𝑝 are the prescribed force and displacement vectors, respectively, and 𝑹𝑢 and where 𝑹𝑝 and 𝒖̅𝑝 are the prescribed force and displacement vectors, respectively, and 𝑹𝑢 and 𝒖̅𝑢 are the unknown force and displacement vectors, respectively. In terms of these vectors, th l b l t f ti b d d f ll where 𝑹𝑝 and 𝒖𝑝 are the prescribed force and displacement vectors, respectively, and 𝑹𝑢 and 𝒖̅𝑢 are the unknown force and displacement vectors, respectively. In terms of these vectors, the global system of equations can be decomposed as follows 𝒖̅𝑢 are the unknown force and displacement vectors, respectively. In terms of these vectors, the global system of equations can be decomposed as follows [𝑹𝑝 𝑹𝑢 ] = [ 𝑲̅𝑝𝑢 𝑲̅𝑝𝑝 𝑲̅𝑢𝑢 𝑲̅𝑢𝑝 ][𝒖̅𝑢 𝒖̅𝑝]. (13) Once 𝜕𝒖̅𝑝𝜕𝜌𝑟 ⁄ = 𝟎, the Eq. (12) can be simplified to 𝜕𝐶(𝝆) 𝜕𝜌𝑟= 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) + 2𝑹𝑝𝑇𝜕𝒖̅𝑢 𝜕𝜌𝑟. (14) [𝑹𝑝 𝑹𝑢 ] = [ 𝑲̅𝑝𝑢 𝑲̅𝑝𝑝 𝑲̅𝑢𝑢 𝑲̅𝑢𝑝 ][𝒖̅𝑢 𝒖̅𝑝]. (13) (13) Once 𝜕𝒖̅𝑝𝜕𝜌𝑟 ⁄ = 𝟎, the Eq. (12) can be simplified to 𝜕𝐶(𝝆) 𝜕𝜌𝑟= 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) + 2𝑹𝑝𝑇𝜕𝒖̅𝑢 𝜕𝜌𝑟. (14) )𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) + 2𝑹𝑝𝑇𝜕𝒖̅𝑢 𝜕𝜌𝑟. (14) (14) Thus, there are two cases, as described below. Thus, there are two cases, as described below. Case 1: prescribed displacement (𝑹𝑝= 𝟎 and 𝒖̅𝑝≠𝟎), which implies in the maximization of 𝐶(𝝆). Case 1: prescribed displacement (𝑹𝑝= 𝟎 and 𝒖̅𝑝≠𝟎), which implies in the maximization of 𝐶(𝝆). Case 1: prescribed displacement (𝑹𝑝= 𝟎 and 𝒖̅𝑝≠𝟎), which implies in the maximization of 𝐶(𝝆). 3.1 OBJECTIVE FUNCTION GRADIENT 3.1 OBJECTIVE FUNCTION GRADIENT 3. TOPOLOGY OPTIMIZATION PROBLEMS FOR COMPLIANCE MINIMIZATION On the other hand, the SIMP method concentrates the relative density values in 0 or 1, as observed in concavity of the orange (SIMP for 𝑝= 2) and yellow (SIMP for 𝑝= 3) lines, promoting a faster convergence to the black and white design. Figure 3. SIMP and RAMP methods’ penalization functions. Figure 3. SIMP and RAMP methods’ penalization functions. 10 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante 3.1 OBJECTIVE FUNCTION GRADIENT 𝜕𝐶(𝝆) 𝜕𝜌𝑟= 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) 𝜕𝐶(𝝆) 𝜕𝜌𝑟= 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) (15) (15) Case 2: prescribed force (𝑹𝑝≠𝟎 and 𝒖̅𝑝= 𝟎), which implies in the minimiza Case 2: prescribed force (𝑹𝑝≠𝟎 and 𝒖̅𝑝= 𝟎), which implies in the minimization of 𝐶(𝝆). 𝜕𝐶(𝝆) 𝜕𝜌𝑟= 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) + 2𝒖̅𝑢𝑇𝑲̅𝑝𝑢 𝜕𝒖̅𝑢 𝜕𝜌𝑟 𝝆) 𝑟= 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) + 2𝒖̅𝑢𝑇𝑲̅𝑝𝑢 𝜕𝒖̅𝑢 𝜕𝜌𝑟 (16) Differentiating 𝑹𝑝= 𝑲̅𝑝𝑢𝒖̅𝑢 in relation to 𝜌𝑟, follows Differentiating 𝑹𝑝= 𝑲̅𝑝𝑢𝒖̅𝑢 in relation to 𝜌𝑟, follows Differentiating 𝑹𝑝= 𝑲̅𝑝𝑢𝒖̅𝑢 in relation to 𝜌𝑟, follows 11 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory 𝟎= 𝜕𝑲̅𝑝𝑢 𝜕𝜌𝑟𝒖̅𝑢+ 𝑲̅𝑝𝑢 𝜕𝒖̅𝑢 𝜕𝜌𝑟 ∴ 𝑲̅𝑝𝑢 𝜕𝒖̅𝑢 𝜕𝜌𝑟= − 𝜕𝑲̅𝑝𝑢 𝜕𝜌𝑟𝒖̅𝑢. (17) Thus 𝜕𝐶(𝝆) 𝜕𝜌𝑟= 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) −2𝒖̅𝑢𝑇𝜕𝑲̅𝑝𝑢 𝜕𝜌𝑟𝒖̅𝑢. (18) Considering 𝒖̅𝑝= 𝟎, follows (17) Thus 𝜕𝐶(𝝆) 𝜕𝜌𝑟= 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) −2𝒖̅𝑢𝑇𝜕𝑲̅𝑝𝑢 𝜕𝜌𝑟𝒖̅𝑢. (18) Considering 𝒖̅𝑝= 𝟎, follows 𝒖̅𝑢𝑇𝜕𝑲̅𝑝𝑢 𝜕𝜌𝑟𝒖̅𝑢= 𝒖̅𝑇𝜕𝑲̅ 𝜕𝜌𝑟𝒖̅ = 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟). (19) This implies 𝒖̅𝑢𝑇𝜕𝑲̅𝑝𝑢 𝜕𝜌𝑟𝒖̅𝑢= 𝒖̅𝑇𝜕𝑲̅ 𝜕𝜌𝑟𝒖̅ = 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟). (19) hi i li 𝒖̅𝑢𝑇𝜕𝑲̅𝑝𝑢 𝜕𝜌𝑟𝒖̅𝑢= 𝒖̅𝑇𝜕𝑲̅ 𝜕𝜌𝑟𝒖̅ = 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟). (19) This implies 𝜕𝐶(𝝆) 𝜕𝜌𝑟= 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) −2𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) = −𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟), (20) 𝜕𝐶(𝝆) 𝜕𝜌𝑟= 𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) −2𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟) = −𝒖̅(𝑟)𝑇𝜕𝑲̅(𝑟) 𝜕𝜌𝑟𝒖̅(𝑟), (20) which results in 𝜕𝐶(𝝆) 𝜕𝜌𝑟= − 𝑑𝐸𝑟(𝜌𝑟) 𝑑𝜌𝑟 𝒖̅(𝑟)𝑇𝑲̅0 (𝑟)𝒖̅(𝑟), (21) where where 𝑑𝐸𝑟(𝜌𝑟) 𝑑𝜌𝑟 = 𝑝𝜌𝑟 𝑝−1(𝐸0 −𝐸𝑚𝑖𝑛) for SIMP 𝑑𝐸𝑟(𝜌𝑟) 𝑑𝜌𝑟 = 1+𝑎 [1+𝑎(1−𝜌𝑟)]2 (𝐸0 −𝐸𝑚𝑖𝑛) for RAMP . (22) 𝑑𝐸𝑟(𝜌𝑟) 𝑑𝜌𝑟 = 𝑝𝜌𝑟 𝑝−1(𝐸0 −𝐸𝑚𝑖𝑛) for SIMP 𝑑𝐸𝑟(𝜌𝑟) 𝑑𝜌𝑟 = 1+𝑎 [1+𝑎(1−𝜌𝑟)]2 (𝐸0 −𝐸𝑚𝑖𝑛) for RAMP . (22) 3.2 OPTIMALITY CRITERIA METHOD 3.2 OPTIMALITY CRITERIA METHOD A high value for 𝜂 can accelerate the optimization convergence process, which may cause oscillations in the displacement field for the low-density regions (Ma et al., 1993). Also, the adoption of minor values of 𝜂 can prevent divergence in the topology optimization algorithm; however, this results in small changes in the design variables, which leads to a slower convergence process (Ma et al., 1993). The value of 𝜂 that provides the faster convergence for the overall process is 1/2, so it is recommended to maintain the damping factor as close as possible of this value. 3.2 OPTIMALITY CRITERIA METHOD The proposed optimization problem is solved employing the OC method. Following Si d (2001) d A d t l (2011) h i ti d ti h id ti l t th The proposed optimization problem is solved employing the OC method. Following Sigmund (2001) and Andreassen et al. (2011), a heuristic updating scheme identical to the scheme proposed in Bendsøe (1995) can be employed as The proposed optimization problem is solved employing the OC method. Following The proposed optimization problem is solved employing the OC method. Following Sigmund (2001) and Andreassen et al. (2011), a heuristic updating scheme identical to the scheme proposed in Bendsøe (1995) can be employed as 𝜌𝑞𝑛𝑒𝑤= { max(0, 𝜌𝑞−𝑚) , if 𝜌𝑞𝐵𝑞 𝜂≤max(0, 𝜌𝑞−𝑚) , min(1, 𝜌𝑞+ 𝑚) , if 𝜌𝑞𝐵𝑞 𝜂≥min(1, 𝜌𝑞+ 𝑚) , 𝜌𝑞𝐵𝑞 𝜂, otherwise , (23) (23) where 𝑚 is a positive move-limit, 𝜂 is a numerical damping factor, and 𝐵𝑞 is the optimality condition defined as where 𝑚 is a positive move-limit, 𝜂 is a numerical damping factor, and 𝐵𝑞 is the optimality condition defined as 12 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante (24) where the Lagrange multiplier 𝜆 can be found by means of a bisection algorithm. where the Lagrange multiplier 𝜆 can be found by means of a bisection algorithm. The damping factor can be employed to regularize possible oscillations during the optimization, mainly when no filtering techniques are employed. The parameter 𝜂 is directly related to the method performance, once this affects the speed variation of 𝐵𝑞 𝜂 (Montes, 2016). A high value for 𝜂 can accelerate the optimization convergence process, which may cause oscillations in the displacement field for the low-density regions (Ma et al., 1993). Also, the adoption of minor values of 𝜂 can prevent divergence in the topology optimization algorithm; however, this results in small changes in the design variables, which leads to a slower convergence process (Ma et al., 1993). The value of 𝜂 that provides the faster convergence for the overall process is 1/2, so it is recommended to maintain the damping factor as close as possible of this value. The damping factor can be employed to regularize possible oscillations during the optimization, mainly when no filtering techniques are employed. The parameter 𝜂 is directly related to the method performance, once this affects the speed variation of 𝐵𝑞 𝜂 (Montes, 2016). 3.2 MESH-INDEPENDENT FILTERS For the sensitivity-based strategy, the employed filtering technique modifies the subvolumes' sensitivities as follows 13 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory 𝜕𝐶 𝜕𝜌𝑞= 1 max(𝛾,𝜌𝑞)∑ 𝐻̂𝑞𝑖 𝑖𝜖𝑁 ∑ 𝐻̂𝑞𝑖𝜌𝑖 𝜕𝐶 𝜕𝜌𝑖 𝑖𝜖𝑁 , (25) 𝜕𝐶 𝜕𝜌𝑞= 1 max(𝛾,𝜌𝑞)∑ 𝐻̂𝑞𝑖 𝑖𝜖𝑁 ∑ 𝐻̂𝑞𝑖𝜌𝑖 𝜕𝐶 𝜕𝜌𝑖 𝑖𝜖𝑁 , (25) where 𝛾= 10−3 is a small positive real value introduced to avoid division by zero, 𝑁 is the set of subvolumes 𝑖 for which the center-to-center distance Δ(𝑞, 𝑖) to subvolume 𝑞 is smaller than the filter radius 𝑟𝑚𝑖𝑛, and 𝐻̂𝑞𝑖 is a weight factor evaluated as (Andreassen et al., 2011) where 𝛾= 10−3 is a small positive real value introduced to avoid division by zero, 𝑁 is the set of subvolumes 𝑖 for which the center-to-center distance Δ(𝑞, 𝑖) to subvolume 𝑞 is smaller than the filter radius 𝑟𝑚𝑖𝑛, and 𝐻̂𝑞𝑖 is a weight factor evaluated as (Andreassen et al., 2011) 𝐻̂𝑞𝑖= max(0, 𝑟𝑚𝑖𝑛−Δ(𝑞, 𝑖)), (26) 𝐻̂𝑞𝑖= max(0, 𝑟𝑚𝑖𝑛−Δ(𝑞, 𝑖)), (26) The density filter modifies, besides the sensitivities, the original densities 𝜌𝑞 as follows ̂ 1 ∑ ̂ The density filter modifies, besides the sensitivities, the original densities 𝜌𝑞 as follows 𝜌̂𝑞= 1 ∑ 𝐻̂𝑞𝑖 𝑖𝜖𝑁 ∑ 𝐻̂𝑞𝑖𝜌𝑖 𝑖𝜖𝑁 , (27) (27) 𝜌̂𝑞= 1 ∑ 𝐻̂𝑞𝑖 𝑖𝜖𝑁 ∑ 𝐻̂𝑞𝑖𝜌𝑖 𝑖𝜖𝑁 , where 𝜌̂𝑞 are referred to as the physical densities, as the application of a density filter causes the original densities 𝜌𝑞 to lose their physical meaning (Sigmund, 2007). When the density filter is employed, the objective function sensitivities with respect to the physical densities 𝜌̂𝑞 are given by Eq. (21) once the design variables 𝜌𝑞 are replaced by 𝜌̂𝑞. where 𝜌̂𝑞 are referred to as the physical densities, as the application of a density filter causes the original densities 𝜌𝑞 to lose their physical meaning (Sigmund, 2007). When the density filter is employed, the objective function sensitivities with respect to the physical densities 𝜌̂𝑞 are given by Eq. (21) once the design variables 𝜌𝑞 are replaced by 𝜌̂𝑞. 3.2 MESH-INDEPENDENT FILTERS As discussed by Araujo et al. (2020b), the topology optimization problem based on the finite-volume theory is a checkerboard-free approach; however, it is observed the occurrence of the mesh-dependency numerical issue. As a result, for topology problems employing the finite-volume theory, filtering techniques are employed to circumvent the mesh dependence issue. Filtering techniques intend to regularize topology optimization numerical issues by using density or sensitivity-based methods. For the density-based methods, each subvolume is redefined by a weighted average of the densities in the subvolume neighborhood, which modifies the sensitivities after the finite-volume analysis. For the strategy based on sensitivity methods, the finite-volume theory analysis is performed, and the sensitivities are consistently calculated; subsequently, they are heuristically recalculated by weighted averaged functions of the sensitivities in the neighboring subvolumes (Sigmund, 2007). As discussed by Araujo et al. (2020b), the topology optimization problem based on the finite-volume theory is a checkerboard-free approach; however, it is observed the occurrence of the mesh-dependency numerical issue. As a result, for topology problems employing the finite-volume theory, filtering techniques are employed to circumvent the mesh dependence issue. Filtering techniques intend to regularize topology optimization numerical issues by using density or sensitivity-based methods. For the density-based methods, each subvolume is redefined by a weighted average of the densities in the subvolume neighborhood, which modifies the sensitivities after the finite-volume analysis. For the strategy based on sensitivity methods, the finite-volume theory analysis is performed, and the sensitivities are consistently calculated; subsequently, they are heuristically recalculated by weighted averaged functions of the sensitivities in the neighboring subvolumes (Sigmund, 2007). 4. SOFTWARE DESCRIPTION Top2DFVT is an algorithm developed to obtain optimized topologies using the finite- volume theory for linear elastic continuum structures. The first use of this algorithm performed by Araujo et al. (2020a) was based on the implementation suggested by the top99 code (Sigmund, 2001), where some operations, such as the filtering procedure and matrices assembly, dramatically increase the computational cost. Therefore, the main features of the top88 code are now explored in this version, such as loop vectorization and memory preallocation, which are strengths of Matlab explored in this program. Additionally, some parts of the code are moved out of the optimization loop, guaranteeing they are only performed once. From the top99neo code, the fsparse function is implemented for finite-volume theory matrices assembly, which guarantees a gain of computational efficiency by accelerating the preallocation of these large matrices. The program also explores two new advances in the OC method promoted by the top99neo code. The first advancement incorporates a better approximation for the initial guess of the Top2DFVT is an algorithm developed to obtain optimized topologies using the finite- volume theory for linear elastic continuum structures. The first use of this algorithm performed by Araujo et al. (2020a) was based on the implementation suggested by the top99 code (Sigmund, 2001), where some operations, such as the filtering procedure and matrices assembly, dramatically increase the computational cost. Therefore, the main features of the top88 code are now explored in this version, such as loop vectorization and memory preallocation, which are strengths of Matlab explored in this program. Additionally, some parts of the code are moved out of the optimization loop, guaranteeing they are only performed once. From the top99neo code, the fsparse function is implemented for finite-volume theory matrices assembly, which guarantees a gain of computational efficiency by accelerating the preallocation of these large matrices. The program also explores two new advances in the OC method promoted by the top99neo code. The first advancement incorporates a better approximation for the initial guess of the 14 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante interval of the Lagrange multiplier 𝜆 in the bisection method. This improvement reduces the number of iterations operated by the OC method by suggesting initial values closer to the final solution in the iterative process of the bisection method. 4. SOFTWARE DESCRIPTION The second advancement involves avoiding the application of a filter at each bisection step when checking the volume constraint with the physical field. This alternative reduces the processing time of each bisection iteration and represents another improvement inspired by the top99neo code. The proposed algorithm is a collection of Matlab functions written in 175 lines, The proposed algorithm is a collection of Matlab functions written in 175 lines, disregarding the commented lines, that implement the design domain, material properties, finite-volume theory analysis, topology optimization, mesh-independency filters, and post- processing. In the data initialization step, the design domain and material properties are defined as inputs to the topology optimization problem, and homogeneous rectangular subvolumes are adopted in the discretized domain. The relative density of each subvolume in the discretized domain is taken as constant. The finite-volume theory analysis is performed for structured meshes considering linear elastic materials for plane stress state. The gradient-based topology optimization problem for compliance minimization is solved employing the OC method, considering a move limit of 0.2. The stopping criterium is set up as follows: 1% of tolerance for the maximum change in the design variables between successive steps. Two mesh-independent filters are implemented: a sensitivity filter and a density filter based on the filtering approaches presented by Andreassen et al. (2011). Finally, the algorithm prints the obtained optimized topology and the investigated numerical aspects, such as the number of iterations, processing time, compliance estimations, etcetera. 4.1 SOFTWARE ARCHITECTURE The algorithm is initialized by entering the following line in the Matlab command prompt: Top2DFVT(L,H,nx,ny,volfrac,penal,frad,ft,varargin) where L and H indicate the horizontal and vertical analysis domain length, respectively, nx and ny are the number of subvolumes in the horizontal and vertical directions, respectively, volfrac is the prescribed volume fraction constraint, penal is the penalty factor, frad is the 15 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory filter radius, ft specifies whether sensitivity filter (ft = 1), or density filter (ft = 2), or no filter (ft = 0), and varargin activates the use of the fsparse routine when set up as ‘fast’. In Top2DFVT.m file, the major sections are default parameters' declaration, initialization of design variables, domain initialization, local stiffness matrix calculation, material interpolation, filtering initialization, topology optimization iterative process, and post- processing. The default parameters indicate the value of the applied concentrated load, the material Young's modulus, the soft material stiffness, the Poisson ratio, the type of penalization method, the damping factor, and the maximum number of iterations. Fundamentally, the soft material stiffness must be a minimal value larger than zero, and the type of penalization method can be chosen between ‘SIMP’ or ‘RAMP’ for the material interpolation scheme. While the initialization of the design variables step establishes the discretization of the analysis domain by indexing each subvolume, allocating the relative density, and the volume-constrained gradient matrix. Therefore, the design domain is assumed to be rectangular and discretized in rectangular subvolumes. An example of a coarse mesh composed of 12 subvolumes with four edges per subvolume and two degrees of freedom (DOFs) per face is shown in Figure 4. Figure 4. Analysis domain with 12 subvolumes and face indexing. Figure 4. Analysis domain with 12 subvolumes and face indexing. The subvolume is indexed row-wise from left to right and down to up, as represented by the bold number shown in Figure 4. Similarly, the subvolume faces are numbered from left to right and down to up, however, the horizontal faces are first indexed, followed by the indexing of the vertical faces, as illustrated in Figure 4. As a result, two DOFs are defined 16 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante in each subvolume face, where the DOFs 2𝑗−1 and 2𝑗 correspond to the horizontal and vertical displacement of face j, respectively. 4.1 SOFTWARE ARCHITECTURE The DOFs assemblage is operated by the subroutine: [dof,ndof,ijK] = DOFassembly(nx,ny) for sK = K0(:)E(:)', where K0 is the local stiffness matrix for a unitary elastic modulus obtained with the function and E is the chosen material interpolation scheme. While the local stiffness matrix is symmetric, rounding errors during the assembly of the global stiffness matrix using the sparse or fsparse commands can cause asymmetry. To correct this, symmetry is enforced at the global level, improving the efficiency of the Matlab backslash (\) command, as recommended by Adreassen et al (2011). After solving the global system of equations, the subvolume compliance and its sensitivities are calculated. The objective function value is obtained by adding the individual contribution of each subvolume in the discretized domain, while the subvolume sensitivities are modified considering the aspects of the chosen filtering technique. Subsequently, the design variables are updated by the OC method. The convergence criterium is adopted as 1% of tolerance for the maximum change in design variables. As post-processing step, the investigated numerical aspects are printed, followed by the plotting of the optimized topology. Finally, the processing time is computed for the performed analysis. [dof,ndof,ijK] = DOFassembly(nx,ny) where dof is the matrix containing the subvolume DOFs, ndof is the total number of DOFs, and ijK is the indexing matrix employed for the global stiffness matrix assemblage. The row iK and column jK index vectors are generated by a Kronecker matrix product with a unit vector of 8 lines. The resulting vectors iK and jK are structured so that the iK(i) and jK(j) indices correspond to the assemblage of the stiffness matrix for the subvolume q. The assembly of the global system of equations is performed by employing the sparse function in Matlab, which takes three vectors as input arguments: the first and second contain the row and column indices of the non-zero entries, while the third vector contains the entry values of the sparse vectors and matrices. It can be also suggested the use of the fsparse routine, developed by Engblom and Lukarski (2016), which enhances the sparse assembly by providing a better ordering of the performed operations. Although Ferrari and Sigmund (2020) have achieved a speedup of 170-250% in the algorithm compared to sparse function on a single-core processor, the performance achieved in our computational environment is similar for both routines. The fsparse routine is performed by setting the variable varargin as ‘fast’, while the absence of values for this variable indicates the use of the ‘sparse’ routine. The structure supporting conditions are prescribed in supp vector by specifying which DOFs of the discretized domain are fixed, while the natural boundary conditions are specified directly in the global force vector F by addressing the DOFs with prescribed loads and their respective magnitude force values. The assemblage of the global stiffness matrix is operated by the function K = StiffnessAssemblage(sK) K = StiffnessAssemblage(sK) 17 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory for sK = K0(:)E(:)', where K0 is the local stiffness matrix for a unitary elastic modulus obtained with the function K0 LocalStiffMatrix(nu l h) 5. ILLUSTRATIVE EXAMPLES The performed example is a cantilever deep beam subject to a concentrated load, as shown in Figure 5. In this case, the vertical and horizontal averaged displacements at the edges of the left border of the structure are fixed, so the supp vector is set up as supp = unique(dof(1:nx:end-nx+1,7:8)) and the concentrated load is positioned in the middle of the right border in the structure, therefore, the global force vector F is given by and the concentrated load is positioned in the middle of the right border in the structure, therefore, the global force vector F is given by F = sparse(dof(nx*(ny+1)/2,4)',1,P,ndof,1) The data initialization is set up as 𝑃= −1, for the applied concentrated load, 𝐸0 = 1, for the Young's modulus, 𝐸𝑚𝑖𝑛= 10−9, for the soft material stiffness, 𝜈= 0.3, for the Poisson's ratio, 𝜂= 1/2, for the damping factor, 𝑚𝑜𝑣𝑒= 0.2, for the move-limit, and 18 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante 𝑚𝑎𝑥𝑖𝑡= 100, for the maximum number of iterations. For the approaches using the SIMP model, the damping factor is adjusted to 1/2.6 to avoid the oscillatory phenomenon, as discussed by Araujo et al. (2020a,b). The computational environment in terms of programming language and machine can be defined as Matlab R2023a (64-bits) for Windows 11, accompanied by the Optimization and Parallel Computing toolboxes, and processor of 12th Gen Intel(R) Core(TM) i7-1260P 2.10 GHz, RAM 16.0 GB DDR5. Figure 5. Cantilever deep beam. Figure 5. Cantilever deep beam. Considering the same parameters employed by Araujo et al. (2020a) in the filtering scenario, the algorithm can be started by the following command: Top2DFVT(100,50,202,101,0.4,1:0.5:4,0.71,1) Top2DFVT(100,50,202,101,0.4,1:0.5:4,0.71,1) which consists in the application of the sensitivity filter considering the adjacent subvolumes with a filter radius of 0.71, given by approximately 1.01√𝑙𝑞2 + ℎ𝑞2, where 𝑙𝑞 and ℎ𝑞 represent the subvolume dimensions, and a volume fraction of 40% of the total volume. The fsparse routine can be performed by including varargin = ‘fast’ in the Top2DFVT command. The obtained optimized topologies for the SIMP model are shown in Figure 6, where Figures 6a, 6b, and 6c show the optimized topologies obtained by employing the sensitivity, density, and no filtering techniques, respectively. The investigated numerical aspects are presented in Table 1. In general, the obtained optimized topologies have shown to be checkerboard-free and the employed filtering techniques have qualitatively reduced the mesh dependency issue. Table 1. Investigated numerical aspects of the cantilever deep beam with a discretization of 20,402 subvolumes. 5. ILLUSTRATIVE EXAMPLES Araujo et al. (2020a,b) have already verified these features; however, the current algorithm has obtained similar results by reducing the computational cost by 99.8%. For instance, the same analysis performed for a cantilever deep beam using the sensitivity filter with a mesh of 20,402 subvolumes took 10 19 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory hours, 28 minutes, and 37 seconds in Araujo et al. (2020a), while the same analysis employing the Top2DFVT algorithm took only 1 minute and 6 seconds, as shown in Table 1. (a) Sensitivity filter (b) Density filter (c) No filter Figure 6. Optimized topologies for the cantilever deep beam employing the SIMP material interpolation. hours, 28 minutes, and 37 seconds in Araujo et al. (2020a), while the same analysis employing the Top2DFVT algorithm took only 1 minute and 6 seconds, as shown in Table hours, 28 minutes, and 37 seconds in Araujo et al. (2020a), while the same analysis employing the Top2DFVT algorithm took only 1 minute and 6 seconds, as shown in Table hours, 28 minutes, and 37 seconds in Araujo et al. (2020a), while the same analysis employing the Top2DFVT algorithm took only 1 minute and 6 seconds, as shown in Table 1. (b) Density filter (a) Sensitivity filter (b) Density filter (c) No filter (c) No filter (c) No filter Figure 6. Optimized topologies for the cantilever deep beam employing the SIMP material interpolation. SIMP method Analysis Sensitivity filter Density filter No filter Compliance (J) 88.12 91.02 87.90 Filter radius 0.71 0.71 0 Number of iterations 368 577 391 Processing time (sparse) 1min 6s 1min 58s 1min 3s Processing time (fsparse) 1min 5s 1min 38s 1min 10s RAMP method Analysis Sensitivity filter Density filter No filter Compliance (J) 85.86 87.69 84.49 Filter radius 0.71 0.71 0 Number of iterations 397 614 451 Processing time (sparse) 1min 1s 1min 38s 1min 16s Processing time (fsparse) 1min 3s 1min 41s 1min 13s Table 1. Investigated numerical aspects of the cantilever deep beam with a discretization of 20,402 subvolumes. 20 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante For the RAMP approach, the penalty factor variable is adjusted to penal = 0:0.5:3, and the variable model is modified to ‘RAMP’. 5. ILLUSTRATIVE EXAMPLES The optimized topologies obtained for the RAMP model are shown in Figure 7, considering the application of the sensitivity filter, Figure 7a, density filter, Figure 7b, and no filtering, Figure 7c. In general, they are checkerboard-free optimized topologies with a reduction in the obtained structural compliance values compared to the optimized topologies generated by the SIMP model, as presented in Table 1. The no-filter approach generated an optimized structure like the optimized topologies obtained by employing the SIMP model and mesh-independent filters. Thus, the RAMP model coupled with the finite-volume theory has shown to be checkerboard-free and mesh- independent for the cantilever deep beam example, which are desired features for manufacturing purposes. In addition, the sensitivity filter for RAMP model has obtained better results by reducing the optimized structural perimeter even more. Table 1 also presents the investigated numerical aspects for the cantilever deep beam example considering the RAMP model. The approach based on the sensitivity filter has presented the lowest number of iterations and computational cost, while the density filter has shown the highest processing time. The minimum value for structural compliance is observed when the no-filtering technique is employed. (b) Density filter (a) Sensitivity filter (b) Density filter (c) No filter Figure 7. Optimized topologies for the cantilever deep beam employing the RAMP material interpolation. (a) Sensitivity filter (b) Density filter a) Sensitivity filter (a) (c) No filter (c) No filter Figure 7. Optimized topologies for the cantilever deep beam employing the RAMP material interpolation. 21 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory For computational efficiency, the fsparse routine is also implemented; however, for the performed analyses, such a difference in computational cost does not justify using the fsparse routine. However, a gain in computational performance is observed by around 30% when meshes with size between 105 and 106 subvolumes are employed. From Table 1, the non-filtering approach has obtained the optimized topologies with the minimum compliance. In contrast, the density filter approach has obtained the optimized topologies with the maximum values for compliance. In general, Top2DFVT provides a platform to perform 2D topology optimization of structures in Matlab, starting from a domain initialization for structured meshes to data post-processing. Several computational tools have been proposed for topology optimization employing analysis domains discretized with essential features for finite-element approaches. 5. ILLUSTRATIVE EXAMPLES As previously discussed, the finite-volume theory is an alternative technique to the finite-element method in the context of topology optimization algorithms. In addition, this is the first contribution to offer an algorithm that shows the implementation of standard finite-volume theory for structured meshes problems in Matlab. This investigation employs the finite-volume theory in topology optimization for compliance minimization problems. Top2DFVT offers some advantages, such as: Top2DFVT offers some advantages, such as: Top2DFVT offers some advantages, such as: a) It generates checkerboard-free optimized topologies even when a non-filtering approach is employed. b) It can be applied to medium and large-scale problems, as the implementation and computational performance are suited to these approaches. c) It employs different material interpolation methods for topology optimization, such as RAMP and SIMP models. When the non-filtering technique is employed, the optimized topologies generated by the RAMP model usually reduce the perimeter compared to those optimized topologies obtained by the SIMP approach. The Top2DFVT algorithm is currently being employed for educational and research purposes to promote the advantages of the finite-volume theory in the numerical analysis of structures. 22 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante 6. NUMERICAL RESULTS In this contribution, three examples are analyzed employing the compliance minimization problem based on the finite-volume theory for linear elastic materials under plane stress state, where the RAMP and SIMP approaches are employed to interpolate the material stiffness. The investigated examples are a cantilever beam subjected to a concentrated load, a Messerschmitt-Bölkow-Blom (MBB) beam, and an L-bracket beam subject to a concentrated load. Some numerical aspects are also investigated during the analyses, such as the number of iterations, processing time, and compliance estimation. The continued penalization scheme is adopted for the compliance minimization problem, where the penalty factor increases gradually (∆𝑝= 0.25) from 1 to 4 for SIMP and from 0 to 3 for RAMP. A maximum of 200 iterations is assumed for each performed penalty factor along the optimization process. 6.1 CANTILEVER DEEP BEAM A classical problem in topology optimization is the cantilever deep beam, whose analysis domain and boundary conditions are illustrated in Figure 8. In this example, it is observed a region of stress concentration where the concentrated load is applied. The adopted geometrical and physical parameters can be described as 𝐻= 450 mm, 𝐿= 900 mm, 𝑑= 10 mm, 𝑃= 1000 N, 𝐸= 200 GPa (Young Modulus), and 𝜈= 0.3 (Poisson’s ratio). The proposed optimization problem consists of minimizing the structural compliance, with a volume constraint of 40% of the total volume. Figure 8. Cantilever deep beam. Figure 8. Cantilever deep beam. Figure 8. Cantilever deep beam. 23 23 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory Figure 9 shows the obtained optimized topologies for the approach based on the finite- volume theory considering the SIMP material interpolation method, while Table 2 presents the investigated numerical parameters for each performed analysis. Although the non- filtering approach has obtained the lowest value for the objective function, the sensitivity filter results have presented the lowest computational cost and optimized topologies that better controls the length scale issue, by reducing the formation of thin bars. The density filtering results have shown more thin bars in the optimized topologies when compared to the sensitivity filter, and higher values for the compliance function in the overall investigation. For the SIMP method and considering the non-filtering strategies, the damping factor is adjusted to 1/2.6 to avoid divergence during the optimization process. Filter Mesh 90x45 Mesh 180x90 Mesh 360x180 None Sensitivity Density Figure 9. Optimized topologies for the cantilever deep beam obtained by the SIMP approach. Filter None Sensitivity Density Figure 9. Optimized topologies for the cantilever deep beam obtained by the SIMP approach. Figure 10 shows the obtained optimized topologies for the approach based on the RAMP method. In general, the RAMP method has obtained checkerboard-free optimized topologies by reducing the structural perimeter when the non-filtering strategy is employed in comparison to the same approach employing the SIMP approach, which is a desired feature for manufacturing purposes. On the other hand, the optimized topologies obtained by the SIMP method usually present a higher structural perimeter by producing more thin 24 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante bars. Additionally, the RAMP method has obtained a well-defined black-and-white design with lower values for the compliance function, as presented in Table 2. bars. Additionally, the RAMP method has obtained a well-defined black-and-white design with lower values for the compliance function, as presented in Table 2. Filter Mesh 90x45 Mesh 180x90 Mesh 360x180 None Sensitivity Density Figure 10. Optimized topologies for the cantilever deep beam obtained by the RAMP approach. Filter Mesh 90x45 Mesh 180x90 Mesh 360x180 None Sensitivity Density Figure 10. Optimized topologies for the cantilever deep beam obtained by the RAMP approach None Sensitivity Figure 10. Optimized topologies for the cantilever deep beam obtained by the RAMP approach. ure 10. Optimized topologies for the cantilever deep beam obtained by the RAMP h Table 2 presents the numerical aspects of the performed investigations for the cantilever deep beam example. In general, the RAMP method has presented a higher number of iterations and processing time, although the obtained optimized topologies have presented the lowest values for the objective function. The filter radius is calculated to be slightly higher than 1.01√𝑙𝑞2 + ℎ𝑞2 for the coarse mesh. Therefore, the optimized topology obtained for the finest mesh employing the sensitivity filter is very similar to that obtained for the coarse mesh without filtering techniques. This is only possible because the finite-volume theory is a checkerboard-free numerical technique in topology optimization algorithms. Filter 25 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory SIMP method Analysis Mesh Number of iterations Processing Time Compliance (J) Filter radius (mm) No filter 90x45 371 10s 448.87 0 180x90 813 4min 11s 391.94 0 360x180 1183 25min 53s 375.57 0 Sensitivity filter 90x45 213 6s 471.97 15 180x90 323 1min 25s 406.38 15 360x180 334 4min 18s 402.01 15 Density filter 90x45 525 15s 491.85 15 180x90 1450 7min 33s 450.89 15 360x180 2497 29min 35s 472.49 15 RAMP method Analysis Mesh Number of iterations Processing Time Compliance (J) Filter radius (mm) No filter 90x45 545 15s 435.65 0 180x90 900 3min 12s 382.82 0 360x180 1164 24min 26s 369.74 0 Sensitivity filter 90x45 350 9s 453.54 15 180x90 408 54s 394.17 15 360x180 465 5min 4s 391.36 15 Density filter 90x45 1010 30s 464.51 15 180x90 2040 4min 44s 420.37 15 360x180 2309 47min 10s 419.01 15 Table 2. Convergence analysis for the cantilever deep beam problem. Table 2. Convergence analysis for the cantilever deep beam problem. 6.2 HALF MBB BEAM Other classical problem for topology optimization of continuum structures is the Messerschmitt-Bölkow-Blom (MBB) beam. In this case, only half of the structure is analyzed as shown on Figure 11, where the geometric and physical parameters are taken as 𝐻= 300 mm, 𝐿= 900 mm, 𝑑= 10 mm, 𝑃= 1000 N, 𝐸= 78 GPa (Young Modulus), and 𝜈= 0.25 (Poisson’s ratio). The volume fraction for the minimum compliance optimization problem is assumed as 40% of the total structure volume. 26 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante Figure 11. Half-MBB beam. Figure 11. Half-MBB beam. Figure 12 shows the optimized topologies obtained considering the application of the SIMP method, while Table 3 presents the investigated numerical aspects for each performed analysis. The topology optimization technique considers the non-filtering, sensitivity, and density filtering scenarios. The adopted filter radius is slightly higher than half of the subvolume's diagonal length for the coarsest mesh, which can be written as 1.01√𝑙𝑞2 + ℎ𝑞2 and approximated by 15 mm. The no-filter analysis generally generates topologies with more thin bars, while the sensitivity filter obtains cleaner topologies with a reduced structural perimeter. Besides, the density filter has not presented the same efficiency as the sensitivity filter in reducing the structural perimeter in the final optimized topology, and the obtained compliance is higher when compared to the other approaches. Regarding computational cost, the sensitivity filter approach obtained the lowest processing time and number of iterations, while the density filter approach presented the highest processing time and number of iterations. Figure 13 shows the optimized topologies for the analyses employing the RAMP method, where the adopted filter radius is the same as those employing the SIMP method. The RAMP method has generally obtained optimized topologies with better control of the structural perimeter, even when the non-filtering technique is employed. Additionally, the optimized topology obtained for the coarse mesh without filtering techniques is geometrically close to the optimized topologies for the finest mesh employing filtering strategies. Therefore, the results obtained for the coarse mesh in the no-filter strategy 27 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory employing the RAMP method could be adopted as the solution for the optimization problem. Table 3 presents the investigated numerical aspects, where the number of iterations and processing time are usually higher for this method when compared to the SIMP approach. 6.2 HALF MBB BEAM Filter Mesh 90x30 Mesh 180x60 Mesh 360x120 None Sensitivity Density Figure 12. Optimized topologies for the MBB beam obtained by the SIMP approach. Filter Mesh 90x30 Mesh 180x60 Mesh 360x120 None Sensitivity Density Figure 13. Optimized topologies for the MBB beam obtained by the RAMP approach. Filter Mesh 90x30 Mesh 180x60 Mesh 360x120 None Sensitivity Density Figure 12. Optimized topologies for the MBB beam obtained by the SIMP approach. Filter Mesh 90x30 Mesh 180x60 Mesh 360x120 None Sensitivity Density Figure 12. Optimized topologies for the MBB beam obtained by the SIMP approach. Filter Mesh 90x30 Mesh 180x60 Mesh 360x120 None Sensitivity Density Figure 13. Optimized topologies for the MBB beam obtained by the RAMP approach. Filter Sensitivity ure 12. Optimized topologies for the MBB beam obtained by the SIMP approach. mized topologies for the MBB beam obtained by the SIMP approach. Figure 12. Optimized topologies for the MBB beam obtained by the SIMP Filter Mesh 90x30 Mesh 180x60 Mesh 360x120 None Sensitivity Density Figure 13. Optimized topologies for the MBB beam obtained by the RAMP approach. Sensitivity timized topologies for the MBB beam obtained by the RAMP approach. ure 13. Optimized topologies for the MBB beam obtained by the RAMP approach 28 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante SIMP method Analysis Mesh Number of iterations Processing Time Compliance (J) Filter radius (mm) No filter 90x30 538 10s 3160.01 0 180x60 804 1min 19s 2873.54 0 360x120 1352 11min 4s 2759.59 0 Sensitivity filter 90x30 410 8s 3174.88 15 180x60 533 48s 3050.52 15 360x120 921 7min 26s 2989.76 15 Density filter 90x30 843 15s 3586.61 15 180x60 1819 4min 59s 3524.15 15 360x120 2490 20min 51s 3560.40 15 RAMP method Analysis Mesh Number of iterations Processing Time Compliance (J) Filter radius (mm) No filter 90x30 811 15s 2921.81 0 180x60 1315 2min 50s 2731.09 0 360x120 1617 17min 14s 2654.87 0 Sensitivity filter 90x30 538 10s 3049.43 15 180x60 747 1min 51s 2935.32 15 360x180 1040 8min 27s 2923.79 15 Density filter 90x30 1191 21s 3174.77 15 180x60 2289 4min 11s 3084.24 15 360x120 2450 21min 16s 3087.59 15 Table 3. Convergence analysis for the half MBB beam problem. Table 3. Convergence analysis for the half MBB beam problem. 6.3 L-BRACKET BEAM Another analyzed topology optimization problem for stress concentration in two- dimensional structures is the L-bracket beam, whose analysis domain and boundary conditions are illustrated in Figure 14. In the L-bracket beam problem, it is observed a high level of stress concentration in the corner, which is important to check how the new Top2DFVT code leads to these kinds of topology optimization problems. The employed geometric parameters for this beam are assumed as 𝑑= 5 cm, 𝐿= 100 cm, and 𝑃= 200 kN, while the adopted material properties are 𝐸= 70 GPa (elastic moduli) and 𝜈= 0.25 29 29 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory (Poisson’s ratio). The proposed optimization problem consists of minimizing the structural compliance function under a volume constraint of 40% of the total volume. Figure 14. L-bracket beam domain, with d = 5 cm, P = 200 kN, and L = 1 m. Figure 14. L-bracket beam domain, with d = 5 cm, P = 200 kN, and L = 1 m. Figure 15 shows the optimized topologies obtained by the SIMP approach for the L-bracket beam problem, considering the absence of filtering techniques and the implementation of the sensitivity and density filters, respectively. The sensitivity filter has reduced the formation of thin bars along the optimized topologies, while the density filter has obtained irregular optimized topologies with the appearance of substantial gray regions. On the other hand, the no-filter strategy has generated well-defined optimized topologies with more thin bars, especially when compared to the sensitivity filter strategy. As Araujo et al. (2020a) suggested, the damping factor is adjusted to 1/2.6 for all performed approaches employing the SIMP to guarantee the absence of the oscillatory phenomenon to any employed filter radius. Table 4 presents the investigated numerical aspects for the performed analyses employing the SIMP method. Figure 16 presents the obtained optimized topologies by the RAMP method for the L- bracket beam problem. The RAMP method has generally reduced the formation of thin bars, demonstrating less sensitivity with the adopted meshes. As in the SIMP method, the sensitivity filter has shown to be more efficient by reducing the formation of thin bars in the optimized topologies, and the density filter has obtained more irregular topologies with the presence of gray regions. The RAMP method is more stable numerically, and the adopted 30 M.V.O. Araujo, A. Santos Júnior, R. S. 6.3 L-BRACKET BEAM Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante damping factor is 1/2, which guarantees a faster convergence for the analyses. However, the number of iterations is usually higher for the RAMP method. Filter Mesh 40x40 Mesh 80x80 Mesh 160x160 None Sensitivity Density Figure 15. Optimized topologies for the L-bracket beam obtained by the SIMP approach. Filter Mesh 40x40 Mesh 80x80 Mesh 160x160 None Sensitivity Density Figure 16. Optimized topologies for the L-bracket beam obtained by the RAMP approach. M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante damping factor is 1/2, which guarantees a faster convergence for the analyses. However, the number of iterations is usually higher for the RAMP method. the number of iterations is usually higher for the RAMP method. Filter Mesh 40x40 Mesh 80x80 Mesh 160x160 None Sensitivity Density Figure 15. Optimized topologies for the L-bracket beam obtained by the SIMP approach. Sensitivity Filter Mesh 40x40 Mesh 80x80 Mesh 160x160 None Sensitivity Density Figure 16. Optimized topologies for the L-bracket beam obtained by the RAMP approach. 31 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory SIMP method Analysis Mesh Number of iterations Processing Time Compliance (J) Filter radius (cm) No filter 40x40 404 4s 4469.64 0 80x80 698 35s 17388.97 0 160x160 946 4min 11s 68743.32 0 Sensitivity filter 40x40 274 2s 4794.02 3.6 80x80 226 10s 19461.58 3.6 160x160 155 39s 81058.11 3.6 Density filter 40x40 653 6s 6149.43 3.6 80x80 1140 1min 51s 25552.58 3.6 160x160 2585 11min 19s 115640.37 3.6 RAMP method SIMP method Analysis Mesh Number of iterations Processing Time Compliance (J) Filter radius (cm) No filter 40x40 404 4s 4469.64 0 80x80 698 35s 17388.97 0 160x160 946 4min 11s 68743.32 0 Sensitivity filter 40x40 274 2s 4794.02 3.6 80x80 226 10s 19461.58 3.6 160x160 155 39s 81058.11 3.6 Density filter 40x40 653 6s 6149.43 3.6 80x80 1140 1min 51s 25552.58 3.6 160x160 2585 11min 19s 115640.37 3.6 RAMP method Analysis Mesh Number of iterations Processing Time Compliance (J) Filter radius (cm) No filter 40x40 272 2s 4434.37 0 80x80 692 35s 17241.14 0 160x160 894 6min 38s 67478.81 0 Sensitivity filter 40x40 278 2s 4714.58 3.6 80x80 202 10s 19325.52 3.6 160x160 226 51s 77303.15 3.6 Density filter 40x40 590 5s 5848.89 3.6 80x80 1640 1min 41s 24364.83 3.6 160x160 2546 20min 6s 98444.69 3.6 Table 4. 6.3 L-BRACKET BEAM Convergence analysis for the L-bracket beam problem. SIMP method Analysis Mesh Number of iterations Processing Time Compliance (J) Filter radius (cm) No filter 40x40 272 2s 4434.37 0 80x80 692 35s 17241.14 0 160x160 894 6min 38s 67478.81 0 Sensitivity filter 40x40 278 2s 4714.58 3.6 80x80 202 10s 19325.52 3.6 160x160 226 51s 77303.15 3.6 Density filter 40x40 590 5s 5848.89 3.6 80x80 1640 1min 41s 24364.83 3.6 160x160 2546 20min 6s 98444.69 3.6 Table 4. Convergence analysis for the L-bracket beam problem. Table 4. Convergence analysis for the L-bracket beam problem. Table 4 presents the investigated numerical aspects of the optimized structures, such as the total number of iterations, processing time, and compliance estimation. When the sensitivity filter is employed, there is a remarkable decrease in the number of iterations and computational costs. However, the obtained values for structural compliance are lower when the non-filtering strategy is performed. In general, the RAMP method has been shown to efficiently produce checkerboard-free optimized topologies with lower values for structural compliance. Thus, these results demonstrate the proposed approach's efficiency and justify its use in topology optimization problems of continuum elastic structures since it better controls numerical issues associated with checkerboard and length scale. The filter 32 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante radius is slightly higher than 1.01√𝑙𝑞2 + ℎ𝑞2 for the coarse mesh. As a result, the filter guarantees the absence of mesh dependency, especially when the RAMP method or the sensitivity filter are employed. 7. CONCLUSIONS This study introduces the Top2DFVT, an innovative Matlab algorithm tailored for the topology optimization of two-dimensional elastic structures via the finite-volume theory. This contribution addresses compliance minimization problems, presenting a checkerboard- free methodology that mitigates numerical instabilities like mesh dependence and local minima, commonly encountered in gradient-based optimization techniques. The algorithm showcases improved computational efficiency and the ability to generate optimized topologies for medium to large-scale problems by employing two material interpolation schemes, SIMP and RAMP, alongside sensitivity and density filters. Such advancements facilitate the design of high-performance structures with potential applications in various engineering domains. This algorithm can provide checkerboard-free optimized topologies and reduce mesh dependence or length scale issues, mainly when the RAMP method is employed. The optimized topologies obtained without filtering techniques for the coarse meshes and employing the RAMP method are similar to those obtained with filtering strategies for the finer meshes. Usually, filtering techniques are based on image processing that geometrically changes the sensitivity or the relative density values. Therefore, obtaining optimized structures without filtering techniques provides more reliable and efficient designs. Besides, the optimized topologies without filtering strategies are well-defined “black and white” designs, where intermediate values of relative densities are reduced. The approach based on the finite-volume theory is also performed by employing a sensitivity filter to solve problems related to mesh dependence and length scale issues. The adopted strategy to define the filter radius consists of using approximately the subvolume's or element's diagonal of the coarse mesh. The continued penalization scheme is adopted for the compliance minimization problem, which guarantees a gradual convergence for the overall process. When the SIMP method is employed, the OC method's damping factor can be 33 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory adjusted to 1/2.6 to avoid divergence during the optimization process, especially when non- filtering strategies are employed. In conclusion, this study presents a novel approach to topology optimization using the finite- volume theory and significantly contributes to the field by addressing and overcoming inherent numerical challenges. The Top2DFVT algorithm represents a pivotal advancement in optimizing elastic structures, promising more reliable and efficient design solutions. The authors' efforts in developing and sharing this tool underscore the collaborative spirit of the research community, aiming to broaden the understanding and application of topology optimization in engineering. 7. CONCLUSIONS This work sets a new benchmark for future research, encouraging further exploration and development of optimization techniques. By providing a robust and efficient tool in Top2DFVT, the authors offer valuable resources for educators, researchers, and practitioners alike, fostering innovation and excellence in engineering design. Funding: scholarships for ENL and MAAC from CNPq (National Council for Scientific and Technological Development); scholarship for MVOA from CAPES (Coordination for the Improvement of Higher Education Personnel); high-performance notebooks for MVOA, ASJ and MAAC from FAPEAL (Alagoas State Research Support Foundation); Matlab and Maple licenses for MVOA, ASJ, RSEF, ENL and MAAC from CAPES (Coordination for the Improvement of Higher Education Personnel). Software Availability: the algorithm described in this study can be found in the GitHub link: https://github.com/fvt7782/Top2DFVT. Competing interests: the authors declare that they have no competing interests. Competing interests: the authors declare that they have no competing interests. Competing interests: the authors declare that they have no competing interests. Acknowledgements: the authors acknowledge the financial support provided by the National Council for Scientific and Technological Development (CNPq), Coordination for the Improvement of Higher Education Personnel (CAPES), and Alagoas State Research Support Foundation (FAPEAL). 34 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante References References Bendsøe M.P., Sigmund O. (2003). Topology optimization: Theory, methods, and applications. 2nd ed. Springer Berlin, Heidelberg. https://doi.org/10.1007/978-3-662- 05086-6 Bendsøe M.P., Sigmund O. (2003). Topology optimization: Theory, methods, and applications. 2nd ed. Springer Berlin, Heidelberg. https://doi.org/10.1007/978-3-662- 05086-6 Liu K., Tovar A. (2014) An efficient 3D topology optimization code written in Matlab. Structural and Multidisciplinary Optimization 50:1175-1196. https://doi.org/10.1007/s00158-014-1107-x Liu K., Tovar A. (2014) An efficient 3D topology optimization code written in Matlab. Structural and Multidisciplinary Optimization 50:1175-1196. https://doi.org/10.1007/s00158-014-1107-x Zhuang Z., Xie Y.M., Li Q., Zhou S. (2023). A 172-line Matlab code for structural topology optimization in the body-fitted mesh. Structural and Multidisciplinary Optimization 66:11. https://doi.org/10.1007/s00158-022-03464-x Zhuang Z., Xie Y.M., Li Q., Zhou S. (2023). A 172-line Matlab code for structural topology optimization in the body-fitted mesh. Structural and Multidisciplinary Optimization 66:11. https://doi.org/10.1007/s00158-022-03464-x Michell A.G.M. (1904). The limits of economy of material in frame structures. The London, Edinburg, and Dublin Philosophical Magazine and Journal of Science 8(47):589- 597. https://doi.org/10.1080/14786440409463229 Michell A.G.M. (1904). The limits of economy of material in frame structures. The London, Edinburg, and Dublin Philosophical Magazine and Journal of Science 8(47):589- 597. https://doi.org/10.1080/14786440409463229 Bendsøe M.P., Kikuchi N. (1988). Generating optimal topologies in structural design using a homogenization method. Computer Methods in Applied Mechanics and Engineering 71(2):197-224. https://doi.org/10.1016/0045-7825(88)90086-2 Bendsøe M.P., Kikuchi N. (1988). Generating optimal topologies in structural design using a homogenization method. Computer Methods in Applied Mechanics and Engineering 71(2):197-224. https://doi.org/10.1016/0045-7825(88)90086-2 Bendsøe M.P., Kikuchi N. (1988). Generating optimal topologies in structural design using a homogenization method. Computer Methods in Applied Mechanics and Engineering 71(2):197-224. https://doi.org/10.1016/0045-7825(88)90086-2 Liu Y., Lai Z., Lu Y., Zhou M., Lin Z. (2023). Topology optimization of shell-infill structures considering buckling constraint. Computers & Structures 283:107055. https://doi.org/10.1016/j.compstruc.2023.107055. Liu Y., Lai Z., Lu Y., Zhou M., Lin Z. (2023). Topology optimization of shell-infill structures considering buckling constraint. Computers & Structures 283:107055. https://doi.org/10.1016/j.compstruc.2023.107055. Yi B., Yoon G.H., Zheng R., Liu L., Li D., Peng X. (2023). A unified material interpolation for topology optimization of multi-materials. Computers & Structures 282:107041. https://doi.org/10.1016/j.compstruc.2023.107041. Yi B., Yoon G.H., Zheng R., Liu L., Li D., Peng X. (2023). A unified material interpolation for topology optimization of multi-materials. Computers & Structures 282:107041. https://doi.org/10.1016/j.compstruc.2023.107041. Yi B., Yoon G.H., Zheng R., Liu L., Li D., Peng X. (2023). A unified material interpolation for topology optimization of multi-materials. Computers & Structures 282:107041. https://doi.org/10.1016/j.compstruc.2023.107041. Lee S., Lieu Q.X., Vo T.P., Kang J., Lee J. (2023). References Topology optimization using super- resolution image reconstruction methods. Advances in Engineering Software 177:103413. https://doi.org/10.1016/j.advengsoft.2023.103413 Lee S., Lieu Q.X., Vo T.P., Kang J., Lee J. (2023). Topology optimization using super- resolution image reconstruction methods. Advances in Engineering Software 177:103413. https://doi.org/10.1016/j.advengsoft.2023.103413 Arruda L.S., Martim M.B., Góis W., de Lima C.R. (2022). Topology optimization – unconventional approaches using the generalized finite element method and the stable 35 35 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory generalized finite element method. Latin American Journal of Solids and Structures 19(3):1-17. generalized finite element method. Latin American Journal of Solids and Structures 19(3):1-17. Bouajila W., Furusawa D., Shimoda M. (2021). Multidisciplinary free-form optimization of solid structures for mean compliance minimization and time-dependent temperature control. Structural and Multidisciplinary Optimization 63(5):2305-2324. https://doi.org/10.1007/s00158-020-02810-1 Ferrari F., Sigmund O. (2020). A new generation 99 line Matlab code for compliance topology optimization and its extension to 3D. Structural and Multidisciplinary Optimization 62(4):2211-2228. https://doi.org/10.1007/s00158-020-02629-w Rozvany G.I.N. (2009). A critical review of established methods of structural topology optimization. Structural and Multidisciplinary Optimization 37(3):217-237. https://doi.org/10.1007/s00158-007-0217-0 Rozvany G.I.N. (2009). A critical review of established methods of structural topology optimization. Structural and Multidisciplinary Optimization 37(3):217-237. https://doi.org/10.1007/s00158-007-0217-0 Stolpe M., Svanberg K. (2001). An alternative interpolation scheme for minimum compliance topology optimization. Structural and Multidisciplinary Optimization 22(2):116-124. https://doi.org/10.1007/s001580100129. Deaton J.D., Grandhi R.V. (2014). A survey of structural and multidisciplinary continuum topology optimization: post 2000. Structural and Multidisciplinary Optimization 49:1-38. https://doi.org/10.1007/s00158-013-0956-z Sigmund O. (2001). A 99 line topology optimization code written in Matlab. Structural and Multidisciplinary Optimization 21(2):120-127. https://doi.org/10.1007/s001580050176. Zhou M., Sigmund O. (2021). Complementary lecture notes for teaching the 99/88-line topology optimization codes. Structural and Multidisciplinary Optimization 64:3227-3231. https://doi.org/10.1007/s00158-021-03004-z. g ( ) 99 p gy p Multidisciplinary Optimization 21(2):120-127. https://doi.org/10.1007/s001580050176. Zhou M., Sigmund O. (2021). Complementary lecture notes for teaching the 99/88-line topology optimization codes. Structural and Multidisciplinary Optimization 64:3227-3231. https://doi.org/10.1007/s00158-021-03004-z. Smit T., Aage N., Ferguson S.J., Helgason B. (2021). Topology optimization using PETSc: a Python wrapper and extended functionality. Structural and Multidisciplinary Optimization 64:4343-4353. https://doi.org/10.1007/s00158-021-03018-7. 36 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante Aage N., Andreassen E., Lazarov B.S. (2015) Topology optimization using PETSc: An easy-to-use, fully parallel, open-source topology optimization framework. Structural and Multidisciplinary Optimization 51:565-572. https://doi.org/10.1007/s00158-014-1157-0 Aage N., Jørgensen M.N., Andreasen C.S., Sigmund O. (2013) Interactive topology optimization on hand-held devices. Structural and Multidisciplinary Optimization 47:1-6. https://doi.org/10.1007/s00158-012-0827-z. Stutz F.C., Olsen T.F., Groen J.P., Trung T.N., Aage N., Sigmund O., Solomon J., Bærentzen J.A. (2022) Synthesis of frame field-aligned multi-laminar structures. ACM Transactions on Graphics 41(5):1-20. https://doi.org/10.1145/3516522. Stutz F.C., Olsen T.F., Groen J.P., Trung T.N., Aage N., Sigmund O., Solomon J., Bærentzen J.A. (2022) Synthesis of frame field-aligned multi-laminar structures. ACM Transactions on Graphics 41(5):1-20. https://doi.org/10.1145/3516522. Aage N., Lazarov B.S. (2013). Parallel framework for topology optimization using the method of moving asymptotes. Structural and Multidisciplinary Optimization 47:493-505. https://doi.org/10.1007/s00158-012-0869-2. Aage N., Lazarov B.S. (2013). Parallel framework for topology optimization using the method of moving asymptotes. Structural and Multidisciplinary Optimization 47:493-505. https://doi.org/10.1007/s00158-012-0869-2. Borrvall T., Petersson J. (2001). generalized finite element method. Latin American Journal of Solids and Structures 19(3):1-17. Large-scale topology optimization in 3D using parallel computing. Computer Methods in Applied Mechanics and Engineering 190(46-47):6201- 6229. https://doi.org/10.1016/S0045-7825(01)00216-X. Borrvall T., Petersson J. (2001). Large-scale topology optimization in 3D using parallel computing. Computer Methods in Applied Mechanics and Engineering 190(46-47):6201- 6229. https://doi.org/10.1016/S0045-7825(01)00216-X. Liu Z., Korvink J.G., Huang I. (2005). Structure topology optimization: fully coupled level set method via FEMLAB. Structural and Multidisciplinary Optimization 6(29):407-417. https://doi.org/10.1007/s00158-004-0503-z. Liu Z., Korvink J.G., Huang I. (2005). Structure topology optimization: fully coupled level set method via FEMLAB. Structural and Multidisciplinary Optimization 6(29):407-417. https://doi.org/10.1007/s00158-004-0503-z. Sokół T. (2011). A 99 line code for discretized Michell truss optimization written in Mathematica. Structural and Multidisciplinary Optimization 43(2):181-190. https://doi.org/10.1007/s00158-010-0557-z. Sokół T. (2011). A 99 line code for discretized Michell truss optimization written in Mathematica. Structural and Multidisciplinary Optimization 43(2):181-190. https://doi.org/10.1007/s00158-010-0557-z. Wei P., Li Z., Li X., Wang M.Y. (2018) An 88-line Matlab code for the parameterized level set method based topology optimization using radial basis functions. Structural and Multidisciplinary Optimization 58:831-849. https://doi.org/10.1007/s00158-018-1904-8 Andreassen E., Clausen A., Schevenels M., Lazarov B.S., Sigmund O. (2011). Efficient topology optimization in Matlab using 88 lines of code. Structural and Multidisciplinary Optimization 43(1):1-16. https://doi.org/10.1007/s00158-010-0594-7. 37 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory Talischi C., Paulino G.H., Pereira A., Menezes I.F.M. (2012). PolyTop: a Matlab implementation of a general topology optimization framework using unstructured polygonal finite-element meshes. Structural and Multidisciplinary Optimization 45:329- 357. https://doi.org/10.1007/s00158-011-0696-x. Talischi C., Paulino G.H., Pereira A., Menezes I.F.M. (2012). PolyTop: a Matlab implementation of a general topology optimization framework using unstructured polygonal finite-element meshes. Structural and Multidisciplinary Optimization 45:329- 357. https://doi.org/10.1007/s00158-011-0696-x. Talischi C., Paulino G.H., Pereira A., Menezes I.F.M. (2012). PolyTop: a Matlab implementation of a general topology optimization framework using unstructured polygonal finite-element meshes. Structural and Multidisciplinary Optimization 45:329- 357. https://doi.org/10.1007/s00158-011-0696-x. Kumar P. (2023). HoneyTop90: A 90-line Matlab code for topology optimization using honeycomb tessellation. Optimization and Engineering 24:1433-1460. https://doi.org/10.1007/s11081-022-09715-6. Kumar P. (2023). HoneyTop90: A 90-line Matlab code for topology optimization using honeycomb tessellation. Optimization and Engineering 24:1433-1460. https://doi.org/10.1007/s11081-022-09715-6. Tavakoli R., Mohseni S.M. (2014) Alternating active-phase algorithm for multimaterial topology optimization problems: a 115-line Matlab implementation. Structural and Multidisciplinary Optimization 49:621-642. https://doi.org/10.1007/s00158-013-0999-1. Zegard T., Paulino G.H. (2014). GRAND — Ground structure-based topology optimization for arbitrary 2D domains using Matlab. Structural and Multidisciplinary Optimization 50:861-882. https://doi.org/10.1007/s00158-014-1085-z. Díaz A., Sigmund O. (1995) Checkerboard patterns in layout optimization. Structural Optimization 10:40-45. https://doi.org/10.1007/BF01743693. Díaz A., Sigmund O. generalized finite element method. Latin American Journal of Solids and Structures 19(3):1-17. (1995) Checkerboard patterns in layout optimization. Structural Optimization 10:40-45. https://doi.org/10.1007/BF01743693. Jog C.S., Haber R.B. (1996). Stability of finite-element models for distributed-parameter optimization and topology design. Computer Methods in Applied Mechanics and Engineering 130(3-4):203-226. https://doi.org/10.1016/0045-7825(95)00928-0. Jog C.S., Haber R.B. (1996). Stability of finite-element models for distributed-parameter optimization and topology design. Computer Methods in Applied Mechanics and Engineering 130(3-4):203-226. https://doi.org/10.1016/0045-7825(95)00928-0. Jog C.S., Haber R.B., Bendsøe MP. (1994). Topology design with optimized, self-adaptive materials. International Journal for Numerical Methods in Engineering 37(8):1323-1350. https://doi.org/10.1002/nme.1620370805 Jog C.S., Haber R.B., Bendsøe MP. (1994). Topology design with optimized, self-adaptive materials. International Journal for Numerical Methods in Engineering 37(8):1323-1350. https://doi.org/10.1002/nme.1620370805 Sigmund O., Petersson J. (1998). Numerical instabilities in topology optimization: A survey on procedures dealing with checkerboards, mesh-dependencies and local minima. Structural and Multidisciplinary Optimization 16(1): 68-75. https://doi.org/10.1007/BF01214002. Sigmund O., Petersson J. (1998). Numerical instabilities in topology optimization: A survey on procedures dealing with checkerboards, mesh-dependencies and local minima. Structural and Multidisciplinary Optimization 16(1): 68-75. https://doi.org/10.1007/BF01214002. Swan C.C., Kosaka I. (1997). Voigt-Reuss topology optimization for structures with nonlinear material behaviors. International Journal for Numerical Methods in Engineering 38 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante 40(20):3785-3814. https://doi.org/10.1002/(SICI)1097-0207(19971030)40:20<3785::AID- NME240>3.0.CO;2-V 40(20):3785-3814. https://doi.org/10.1002/(SICI)1097-0207(19971030)40:20<3785::AID- NME240>3.0.CO;2-V Sigmund O. (2007) Morphology-based black and white filters for topology optimization. Structural and Multidisciplinary Optimization 33(4-5):401-424. https://doi.org/10.1007/s00158-006-0087-x. Haber R.B., Jog C.S., Bendsøe M.P. (1996). A new approach to variable-topology shape design using a constraint on perimeter. Structural Optimization 11(1):1-12. https://doi.org/10.1007/BF01279647. Haber R.B., Jog C.S., Bendsøe M.P. (1996). A new approach to variable-topology shape design using a constraint on perimeter. Structural Optimization 11(1):1-12. https://doi.org/10.1007/BF01279647. Fujii D., Kikuchi N. (2000) Improvement of numerical instabilities in topology optimization using SLP method. Structural and Multidisciplinary Optimization 19(2):113- 121. https://doi.org/10.1007/s001580050091. Rahmatalla S.F., Swan C.C. (2004). A Q4/Q4 continuum structural topology optimization implementation. Structural and Multidisciplinary Optimization 27(1-2):130-135. https://doi.org/10.1007/s00158-003-0365-9. Rahmatalla S.F., Swan C.C. (2004). A Q4/Q4 continuum structural topology optimization implementation. Structural and Multidisciplinary Optimization 27(1-2):130-135. https://doi.org/10.1007/s00158-003-0365-9. Balogh B., Lógó J. (2017). The application of drilling degree of freedom to checkerboards in structural optimization. Advances in Engineering Software 107:7-12. https://doi.org/10.1016/j.advengsoft.2017.02.005 Talischi C., Paulino G.H., Pereira A., Menezes I.F.M. (2010). Polygonal finite elements for topology optimization: A unifying paradigm. International Journal for Numerical Methods in Engineering 82(6):671-698. https://doi.org/10.1002/nme.2763 Talischi C., Paulino G.H., Pereira A., Menezes I.F.M. (2010). Polygonal finite elements for topology optimization: A unifying paradigm. International Journal for Numerical Methods in Engineering 82(6):671-698. generalized finite element method. Latin American Journal of Solids and Structures 19(3):1-17. https://doi.org/10.1002/nme.2763 Rozvany G.I.N., Querin O.M., Gaspar Z., Pomezanski V. (2003). Weight-increasing effect of topology simplification. Structural and Multidisciplinary Optimization 25(5-6):459-465. https://doi.org/10.1007/s00158-003-0334-3. Rozvany G.I.N., Querin O.M., Gaspar Z., Pomezanski V. (2003). Weight-increasing effect of topology simplification. Structural and Multidisciplinary Optimization 25(5-6):459-465. https://doi.org/10.1007/s00158-003-0334-3. Pomezanski V., Querin O.M., Rozvany G.I.N. (2005) CO-SIMP: extended SIMP algorithm with direct corner contact control. Structural and Multidisciplinary Optimization 30(2):164- 168. https://doi.org/10.1007/s00158-005-0514-4. Pomezanski V., Querin O.M., Rozvany G.I.N. (2005) CO-SIMP: extended SIMP algorithm with direct corner contact control. Structural and Multidisciplinary Optimization 30(2):164- 168. https://doi.org/10.1007/s00158-005-0514-4. 39 TOP2DFVT: An Efficient Matlab Implementation for Topology Optimization based on the Finite-Volume Theory Svanberg K., Werme M. (2005) A hierarchical neighbourhood search method for topology optimization. Structural and Multidisciplinary Optimization 29(5):325-340. https://doi.org/10.1007/s00158-004-0493-x. Svanberg K., Werme M. (2005) A hierarchical neighbourhood search method for topology optimization. Structural and Multidisciplinary Optimization 29(5):325-340. https://doi.org/10.1007/s00158-004-0493-x. Svanberg K., Werme M. (2005) A hierarchical neighbourhood search method for topology optimization. Structural and Multidisciplinary Optimization 29(5):325-340. https://doi.org/10.1007/s00158-004-0493-x. Poulsen T.A. (2002) A simple scheme to prevent checkerboard patterns and one-node connected hinges in topology optimization. Structural and Multidisciplinary Optimization 24(5):396-399. https://doi.org/10.1007/s00158-002-0251-x. Poulsen T.A. (2002) A simple scheme to prevent checkerboard patterns and one-node connected hinges in topology optimization. Structural and Multidisciplinary Optimization 24(5):396-399. https://doi.org/10.1007/s00158-002-0251-x. Ruiter M.J., Keulen F.V. (2004). Topology optimization using a topology description function. Structural and Multidisciplinary Optimization 26(6):406-416. https://doi.org/10.1007/s00158-003-0375-7. Abe K., Koro K. (2006) A topology optimization approach using VOF method. Structural and Multidisciplinary Optimization 31(6):470-479. https://doi.org/10.1007/s00158-005- 0582-5. Guest J.K., Prevost J.H., Belytschko T. (2004). Achieving minimum length scale in topology optimization using nodal design variables and projection functions. International Journal for Numerical Methods in Engineering 61(2):238-254. https://doi.org/10.1002/nme.1064 Wang M.Y., Zhou S., Ding H. (2004) Nonlinear diffusions in topology optimization. Structural and Multidisciplinary Optimization 28(4):262-276. https://doi.org/10.1007/s00158-004-0436-6. Araujo M.V.O., Lages E.N., Cavalcante M.A.A. (2020a). Checkerboard free topology optimization for compliance minimization applying the finite-volume theory. Mechanics Research Communications 108:103581. https://doi.org/10.1016/j.mechrescom.2020.103581 Araujo M.V.O., Lages E.N., Cavalcante M.A.A. (2020b). Checkerboard-free topology optimization for compliance minimization of continuum elastic structures based on the Araujo M.V.O., Lages E.N., Cavalcante M.A.A. (2020a). Checkerboard free topology optimization for compliance minimization applying the finite-volume theory. Mechanics Research Communications 108:103581. https://doi.org/10.1016/j.mechrescom.2020.103581 Araujo M.V.O., Lages E.N., Cavalcante M.A.A. (2020b). Checkerboard-free topology optimization for compliance minimization of continuum elastic structures based on the generalized finite-volume theory. Latin American Journal of Solids and Structures 17(8):1- 21. https://doi.org/10.1590/1679-78256053. Araujo M.V.O., Lages E.N., Cavalcante M.A.A. (2020a). generalized finite element method. Latin American Journal of Solids and Structures 19(3):1-17. Checkerboard free topology optimization for compliance minimization applying the finite-volume theory. Mechanics Research Communications 108:103581. https://doi.org/10.1016/j.mechrescom.2020.103581 Araujo M.V.O., Lages E.N., Cavalcante M.A.A. (2020b). Checkerboard-free topology optimization for compliance minimization of continuum elastic structures based on the Araujo M.V.O., Lages E.N., Cavalcante M.A.A. (2020a). Checkerboard free topology optimization for compliance minimization applying the finite-volume theory. Mechanics Research Communications 108:103581. https://doi.org/10.1016/j.mechrescom.2020.103581 Araujo M.V.O., Lages E.N., Cavalcante M.A.A. (2020b). Checkerboard-free topology optimization for compliance minimization of continuum elastic structures based on the generalized finite-volume theory. Latin American Journal of Solids and Structures 17(8):1- 21. https://doi.org/10.1590/1679-78256053. 40 M.V.O. Araujo, A. Santos Júnior, R. S. Escarpini Filho, E.N. Lages, and M.A.A. Cavalcante Araujo M.V.O., Lages E.N., Cavalcante M.A.A. (2021). Energy analysis of continuum elastic structures by the generalized finite-volume theory. Acta Mechanica 232:4625-4643. https://doi.org/10.1007/s00707-021-03031-3. Araujo M.V.O., Lages E.N., Cavalcante M.A.A. (2021). Energy analysis of continuum elastic structures by the generalized finite-volume theory. Acta Mechanica 232:4625-4643. https://doi.org/10.1007/s00707-021-03031-3. Cavalcante M.A.A., Marques S.P.C., Pindera M.-J. (2007a) Parametric formulation of the finite-volume theory for functionally graded materials – Part I: analysis. Journal of Applied Mechanics 74(5):935-945. https://doi.org/10.1115/1.2722312 Cavalcante M.A.A., Marques S.P.C., Pindera M.-J. (2007b) Parametric formulation of the finite-volume theory for functionally graded materials – Part II: numerical results. Journal of Applied Mechanics 74(5):946-957. https://doi.org/10.1115/1.2722313 Cavalcante M.A.A., Marques S.P.C., Pindera M.-J. (2007b) Parametric formulation of the finite-volume theory for functionally graded materials – Part II: numerical results. Journal of Applied Mechanics 74(5):946-957. https://doi.org/10.1115/1.2722313 Cavalcante M.A.A., Marques S.P.C., Pindera M.-J. (2008) Computational aspects of the parametric finite-volume theory for functionally graded materials. Computational Material Science 44(2):422-438. https://doi.org/10.1016/j.commatsci.2008.04.006 Cavalcante M.A.A., Marques S.P.C., Pindera M.-J. (2008) Computational aspects of the parametric finite-volume theory for functionally graded materials. Computational Material Science 44(2):422-438. https://doi.org/10.1016/j.commatsci.2008.04.006 Cavalcante M.A.A., Pindera M.-J. (2012a) Generalized finite-volume theory for elastic analysis in solid mechanics – part I: framework. Journal of Applied Mechanics 2012;79(5):051006. https://doi.org/10.1115/1.4006805 Cavalcante M.A.A., Pindera M.-J. (2012a) Generalized finite-volume theory for elastic analysis in solid mechanics – part I: framework. Journal of Applied Mechanics 2012;79(5):051006. https://doi.org/10.1115/1.4006805 Cavalcante M.A.A., Pindera M.-J. (2012b) Generalized finite-volume theory for elastic analysis in solid mechanics – part II: results. Journal of Applied Mechanics 79(5):051007. https://doi.org/10.1115/1.4006806 Cavalcante M.A.A., Pindera M.-J. (2012b) Generalized finite-volume theory for elastic analysis in solid mechanics – part II: results. Journal of Applied Mechanics 79(5):051007. https://doi.org/10.1115/1.4006806 Bendsøe M.P. (1995) Optimization of structural topology shape and material. Springer, New York. Bendsøe M.P. (1995) Optimization of structural topology shape and material. generalized finite element method. Latin American Journal of Solids and Structures 19(3):1-17. Springer, New York. Montes M.A. (2016). Topology optimization algorithms for the solution of compliance and volume problems in 2D. Master Thesis, Mexico: Investigation Center in Mathematics. Montes M.A. (2016). Topology optimization algorithms for the solution of compliance and volume problems in 2D. Master Thesis, Mexico: Investigation Center in Mathematics. Ma Z.-D., Kikuchi N., Hagiwara I. (1993). Structural topology and shape optimization for a frequency response problem. Computational Mechanics 13(3):157-174. https://doi.org/10.1007/BF00370133 Ma Z.-D., Kikuchi N., Hagiwara I. (1993). Structural topology and shape optimization for a frequency response problem. Computational Mechanics 13(3):157-174. https://doi.org/10.1007/BF00370133 Engblom S., Lukarski D. (2016). Fast Matlab compatible sparse assembly on multicore computers. Parallel Computing 56:1-17. https://doi.org/10.1016/j.parco.2016.04.001 41
https://openalex.org/W1488584052	https://retrovirology.biomedcentral.com/counter/pdf/10.1186/1742-4690-2-S1-S8	English	null	Mechanisms of HIV Suppression by Various Microbes in Human Lymphoid Tissue	Retrovirology	2,005	cc-by	391	BioMed Central BioMed Central Retrovirology Open Access Page 1 of 1 (page number not for citation purposes) Open Oral presentation Mechanisms of HIV Suppression by Various Microbes in Human Lymphoid Tissue Leonid Margolis‡ Address: Section of Intercellular Interactions, National Institute of Child Health and Human Development, Bethesda, MD 20892 Email: Leonid Margolis - margolis@helix.nih.gov * Corresponding author ‡Presenting author from 2005 International Meeting of The Institute of Human Virology Baltimore, USA, 29 August – 2 September 2005 from 2005 International Meeting of The Institute of Human Virology Baltimore, USA, 29 August – 2 September 2005 Published: 8 December 2005 Retrovirology 2005, 2(Suppl 1):S8 doi:10.1186/1742-4690-2-S1-S8 Published: 8 December 2005 Retrovirology 2005, 2(Suppl 1):S8 doi:10.1186/1742-4690-2-S1-S8 contribute to the development of efficient anti-HIV thera- pies. Various pathogens enhance HIV replication and disease progression in coinfected individuals. However, we, and others, have provided examples of microbial interactions that suppress HIV-1 infection both in vivo and ex vivo. Here, we report on the mechanisms of interactions of HIV-1 with several such microbes in the context of ex vivo infected human lymphoid tissue. Blocks of human tonsils maintained ex vivo were coinfected with R5 or X4 HIV-1 and with another microbe, measles virus (MV), vaccinia, herpesvirus 6 (HHV-6), herpesvirus 7 (HHV-7), cytomeg- alovirus (CMV), or a parasite, Toxoplasma gondii (TG). In ex vivo tissues, all the above-listed microbes, except CMV, inhibited replication of R5 HIV-1 whereas replica- tion of X4 HIV-1 was affected mildly. In spite of similarity of the effects, the mechanisms of R5 inhibition by coin- fecting microbes are strikingly diverse. HHV-6 and MV upregulate CC-chemokines, in particular RANTES to the levels sufficient to inhibit replication of R5 HIV-1; Toxo- plasma gondii seems to secret its own soluble factor, cyclo- phyline, that also binds to CCR5 coreceptor, HHV-7 downregulates the expression of CD4 on T cells. In conclusion, soluble factors encoded by microbes, including their components, or secreted by infected and bystander cells in response to microbial invasion (in par- ticular cytokines/chemokines) constitute a universal net- work through which microbes interact with human body creating a microenvironment that is beneficial for them. However, what is beneficial for one microbe can be detri- mental for another. Deciphering the molecular mecha- nisms by which pathogens alter tissue microenvironment so that it becomes detrimental to HIV, may significantly Page 1 of 1 (page number not for citation purposes)
https://openalex.org/W2125424147	https://ogma.newcastle.edu.au:443/vital/access/services/Download/uon:17078/ATTACHMENT01	English	null	Validity of the Australian Recommended Food Score as a diet quality index for Pre-schoolers	Nutrition journal	2,014	cc-by	7,339	Abstract Background: Diet quality tools provide researchers with brief methods to assess the nutrient adequacy of usual dietary intake. This study describes the development and validation of a pediatric diet quality index, the Australian Recommended Food Scores for Pre-schoolers (ARFS-P), for use with children aged two to five years. Background: Diet quality tools provide researchers with brief methods to assess the nutrient adequacy of usual dietary intake. This study describes the development and validation of a pediatric diet quality index, the Australian Recommended Food Scores for Pre-schoolers (ARFS-P), for use with children aged two to five years. Methods: The ARFS-P was derived from a 120-item food frequency questionnaire, with eight sub-scales, and was scored from zero to 73. Linear regressions were used to estimate the relationship between diet quality score and nutrient intakes, in 142 children (mean age 4 years) in rural localities in New South Wales, Australia. Results: Total ARFS-P and component scores were highly related to dietary intake of the majority of macronutrients and micronutrients including protein, β-carotene, vitamin C, vitamin A. Total ARFS-P was also positively related to total consumption of nutrient dense foods, such as fruits and vegetables, and negatively related to total consumption of discretionary choices such as sugar sweetened drinks and packaged snacks Methods: The ARFS-P was derived from a 120-item food frequency questionnaire, with eight sub-scales, and was scored from zero to 73. Linear regressions were used to estimate the relationship between diet quality score and nutrient intakes, in 142 children (mean age 4 years) in rural localities in New South Wales, Australia. Results: Total ARFS-P and component scores were highly related to dietary intake of the majority of macronutrients and micronutrients including protein, β-carotene, vitamin C, vitamin A. Total ARFS-P was also positively related to total consumption of nutrient dense foods, such as fruits and vegetables, and negatively related to total consumption of discretionary choices, such as sugar sweetened drinks and packaged snacks. Conclusion: ARFS-P is a valid measure that can be used to characterise nutrient intakes for children aged two to five years. Further research could assess the utility of the ARFS-P for monitoring of usual dietary intake over time or as part of clinical management. © 2014 Burrows et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Abstract Keywords: Diet quality index, Food frequency questionnaire, Pre-schoolers, Nutritional adequacy Keywords: Diet quality index, Food frequency questionnaire, Pre-schoolers, Nutritional adequacy and both total and disease specific morbidity and mortality, are greater in those with poorer diet quality [2,3]. Burrows et al. Nutrition Journal 2014, 13:87 http://www.nutritionj.com/content/13/1/87 Validity of the Australian Recommended Food Score as a diet quality index for Pre-schoolers Tracy L Burrows1,2, Kate Collins1, Jane Watson1,2, Maya Guest1,3, May M Boggess3,4, Melinda Neve1,2, Megan Rollo1,2, Kerith Duncanson1,2,5 and Clare E Collins1,2 Tracy L Burrows1,2, Kate Collins1, Jane Watson1,2, Maya Guest1,3, May M Boggess3,4, Melinda Neve1,2, Megan Rollo1,2, Kerith Duncanson1,2,5 and Clare E Collins1,2 * Correspondence: mboggess@asu.edu 3Environmental and Occupational Health and Safety, School of Health Sciences, Faculty of Health and Medicine, The University of Newcastle, Callaghan 2308, NSW, Australia 4School of Mathematical and Statistical Sciences, Arizona State University, Tempe 85281, AZ, USA Full list of author information is available at the end of the article Background Diet quality refers to both nutrient adequacy and food variety within healthful food groups, as well as align- ment of overall eating patterns with National Dietary Guidelines. Diet quality scores or indices are used to summarize dietary intake into a single numeric variable, which addresses some of the limitations in evaluations of diet-disease relationships based only on single nutrients [1]. However, given the major concerns related to these limitations, it is advisable to keep in mind that findings from food frequency questionnaire based epidemiological studies of diet-disease relationships could have their own limitations. In adults, chronic disease risk factors, including elevated systolic blood pressure, obesity, hyperglycemia, The validation and reproducibility of diet quality indi- ces in relation to health outcomes in pediatric popula- tions is more challenging to assess for two reasons: first, the time lag to disease development [4], and second, there are fewer indices that have been validated in pediatric populations [5]. Intermediate clinical markers that have been examined previously include BMI [6,7], percentage body fat and waist circumference [6,8], blood pressure [6], micronutrient intakes [9], plasma lipids, in- flammation markers, serum iron, vitamin B12 and homo- cysteine [10,11]. Reviews that examine the relationship between diet quality and health outcomes in children have demonstrated modest associations with asthma and dental caries [6]. * Correspondence: mboggess@asu.edu 3Environmental and Occupational Health and Safety, School of Health Sciences, Faculty of Health and Medicine, The University of Newcastle, Callaghan 2308, NSW, Australia 4School of Mathematical and Statistical Sciences, Arizona State University, Tempe 85281, AZ, USA Full list of author information is available at the end of the article To date, only a limited number of studies have sought to validate diet quality indices against nutrient intakes in pediatric populations [12,13]. Huybrechts et al. [12] developed a Diet Quality Index (DQI) for pre-school Burrows et al. Nutrition Journal 2014, 13:87 http://www.nutritionj.com/content/13/1/87 Page 2 of 10 children and evaluated it for validity (n = 510) and repro- ducibility (n = 58). The DQI was shown to positively cor- relate with a range of macronutrients and micronutrients, and additionally, food frequency questionnaire (FFQ)- based DQI calculations showed moderate agreement with the DQI calculated from a 3 day food record [12]. published elsewhere [4,14], demonstrating acceptable accuracy for ranking nutrient intakes in children and adolescents 9–16 years of age [14]. Background The AES-P was pre- viously shown to be a valid estimate of total energy expenditure in children 3 years of age [4], and children 8–11 years of age using doubly labeled water [17]. Caregivers recorded their child’s frequency of con- sumption of a comprehensive, defined list of foods over the previous 6 months. The frequency options ranged from ‘never’ to ‘4 or more times per day’, to ‘7 or more glasses per day’ for beverages. Questions from the FFQ were grouped categorically into food groups and sub- groups including those energy dense nutrient poor foods now referred to as ‘ discretionary choices’ [18]. Due to the seasonal availability of some fruits, a separate section was included in the FFQ for seasonal fruit. The fre- quency categories were listed as for other food items, with the question, “when the following fruit is in season, how often do you usually eat it?” to capture the usual consumption of the fruit when it is in season. Seasonal availability was determined by contacting the food mar- kets, Sydney, NSW and obtaining information about the wider availability in other markets and supermarkets during the year, in addition to referring to supermarket literature that indicated the months of the year different seasonal fruit was available. The authors previously evaluated the performance of the Australian Child and Adolescent Recommended Food Score (ACARFS) compared to nutrient intakes de- rived from an FFQ in a population (n = 691) of children aged 9–12 years [13]. Agreement between ACARFS and nutrient intakes was demonstrated through positive cor- relations between ACARFS and all vitamins, minerals and total energy intake. However, that evaluation did not include younger children. Therefore, the aims of this study were to develop a pediatric DQI, the Australian Recommended Food Score for Pre-schoolers (ARFS-P), and evaluate its perform- ance as a measure of diet quality by assessing agreement in pre-schoolers with nutrient intakes derived from a previously validated FFQ [4,14]. The Australian Recommended Food Score for Pre-Scoolers ARFS-P The Australian Recommended Food Score for Pre-Scoolers ARFS-P The ARFS-P was designed as a brief, culture specific, food based diet quality tool for young children, focusing on dietary variety within recommended food groups. It was modeled on the Recommended Food Score [23] and the Australian Recommended Food Score (ARFS) [24], and utilizes a subsample of questions from the AES-P FFQ consistent with the 2013 Australian Dietary Guide- lines [18]. The ARFS-P includes seventy questions relating Methods Th The current study was a cross-sectional evaluation of dietary intake in young children aged 2–5 years (n = 146). The data was baseline measures of a randomized control trial, Feeding Healthy Food to Kids (FHFK), conducted in five rural low socioeconomic localities in New South Wales (NSW), Australia, in August 2009 [15,16]. Briefly, parents of young children were recruited from childcare facilities by early childhood health professionals. Inclu- sion criteria were parents were aged 18 years or older and the child was aged 2–5 years. If more than one child in the family met this criterion, the eldest child within the eligible age range was selected as the study child for consistency and simplicity. Demographic variables col- lected included child age, gender, Aboriginal or Torres Strait Islander status, child health status, and parental education level. Four children had missing age, leaving a final sample size of n = 142. Written informed consent was obtained from all participants’ parents prior to their enrolment in the FHFK study. Approval was obtained from Hunter New England (HNE) Human Research Ethics Committee (reference number HREC/08/HNE/403) and the University of Newcastle Human Research Ethics Committee (approval number H-2009-0106). Pre-school age portion sizes in grams for individual foods items, was derived from the 2007 National Children’s Nutrition and Physical Activity Survey, purchased from the Australian Social Science Data Archive at the Australian National University [19]. Nutrient intakes from the AES-P FFQ were computed from the most current food compos- ition database of Australian foods available, the Australian AusNut 2007 database (All Foods) Revision 17 and AusFoods (Brands) Revision 5 [20] to generate individual mean daily macro-and micronutrient intakes. The esti- mated daily intakes for 20 macro- and micronutrients were calculated using FoodWorks [21] and compared to age-specific nutrient targets. Adequacy of nutrient intake was assessed using Recommended Daily Intake (RDI) and Adequate Intake (AI) targets [22], while intakes exceeding recommendations were defined by Upper Limits (UL) [22] and the 2013 Australian Dietary Guidelines [18]. Statistical analysis d Table 3 reports the ARFS-P score, component scores, and macronutrient intake and micronutrient intake de- scriptive statistics, by age group. The median ARFS-P score was 36 with a minimum of 12 and a maximum of 55, with no significant difference by age. There were no significant differences by age in any component ARFS-P, or macro or micronutrients. Marginal significance (p < 0.1) was reached with saturated fat and cholesterol. Scores were described by medians and interquartile range (IQR) and Fisher’s exact test and Wilcoxon rank- sum test were used to compare two age groups in uni- variate analyses. Groups were younger children (<4 years of age) and older children (≥4 years of age), so that the same RDI, AI and UL values would apply to all partici- pants in a group. Linear regressions were used to esti- mate the beta-coefficients (which can be thought of as correlations) of ARFS-P scores with FFQ components, whilst controlling for demographic factors. More pre- cisely, agreement was assessed using linear regression models with AES-P FFQ food group, macro and micro- nutrient intakes as response variables and ARFS-P com- ponents as explanatory variables. Demographic variables, age, gender and parent education, were controlled for by being kept in the model if significant (too few partici- pants were Aboriginal or Torres Strait Islander to be able to estimate the effect of race). The total energy intake was included as an explanatory variable if signifi- cant. By this we mean that backwards stepwise with p = 0.05 for removal was employed to remove variables that added no predictive value to the model. This was followed by adding any variable back in that was signifi- cant at the 0.05 level, so that that smallest model with the best predictive ability was identified. Both ARFS-P and FFQ were standardized (subtract mean and divide by standard deviation) so the model coefficient was the beta-coefficient. A square root transform was applied to some variables to improve the normality of the residuals. Kolmogorov-Smirnov tests and normal probability plots were used to assess normality of residuals. Square root transform of response variables was used if necessary to improve residual normality. Statistical significance was at the 5% level. All data manipulation and statistical analysis was undertaken using Stata MP v12 [25]. Results to eight food group components; vegetables (n = 20), fruit (n = 12), meat (n = 7), meat alternatives (i.e. non- meat protein) (n = 6), breads/cereals (n = 12), dairy (n = 10), water (n = 1) and condiments (n = 2). The procedure used to calculate ARFS has been published elsewhere [13]. Briefly, points were awarded for foods consumed according to frequency of consumption, with healthy foods receiving more points (i.e. vegetables, low-fat dairy, whole grains), and point caps on foods that should not be consumed overly often (e.g. meat, whole milk). An ARFS component was only calculated for those responses with not more than one question missing; one child was ex- cluded for this reason. The ARFS total possible score ranges from zero to 73, and the component scores from zero to the number of questions in that component, plus one more possible for vegetables, low-fat dairy, whole grains. Table 1 lists demographic characteristics of participants (n = 142) by age group. No significant difference across age groups was found for gender, chronic health condi- tions or race. Table 2 reports the percentage of participants that met age specific nutrient RDIs and AIs, and the percentage that exceeded UL for sodium and the percentage energy (%E) from saturated fat, according to their AES-P FFQ reported food intake. Over 75% of participants met rec- ommendations for the majority of macronutrients and micronutrients with the exception of fibre, iron and po- tassium. In fact, less than 20% met the daily requirement for iron. Only five percent of participants met recom- mendations in the Dietary Guidelines in Australia of less than 10% of total energy derived from saturated fat, while 81% of younger children and 61% of older children exceeded the recommended upper limit for sodium intake. Assessment of dietary intake AES-P FFQ Dietary intake was assessed using the Australian Eating Survey Pre-schooler Version (AES-P). Given the age of the pre-schoolers, a caregiver (i.e. parent or guardian) recorded the child’s frequency of consumption of a com- prehensive 120-item semi-quantitative FFQ. Further de- tails of the development of the AES FFQ have been Burrows et al. Nutrition Journal 2014, 13:87 http://www.nutritionj.com/content/13/1/87 Burrows et al. Nutrition Journal 2014, 13:87 http://www.nutritionj.com/content/13/1/87 Burrows et al. Nutrition Journal 2014, 13:87 http://www.nutritionj.com/content/13/1/87 Page 3 of 10 Statistical analysis d Table 2 Comparison of nutrient intakes, as assessed by the Australian Eating Survey Pre-schooler Version (AES-P) Food Frequency Questionnaire, to Australian Recommended Dietary Intakes (RDI), Adequate Intake (AI) and upper limit (UL), b 2Australian Dietary Guidelines [18]. Also in Table 3 is the %E from nutrient dense and discre- tionary choice components, as assessed by the AES-P FFQ, by age group. The median %E from nutrient dense food was 70.5%, and 29.5% from discretionary choices, with no significant difference by age. However, older children did obtain significantly higher %E from grains and sweetened cereals than their younger counterparts, and marginally so for packaged snacks. related to total consumption of nutrient-dense foods, as well as food sub-groups including vegetables, fruit, meat and meat alternatives. In contrast, total ARFS-P was negatively related to total consumption of discretionary choices, and subgroups such as confectionary, sugar sweetened drinks, packaged snacks and take-away foods. Figure 1 displays these beta-coefficients between total ARFS-P and AES-P FFQ reported intake, together with their 95% confidence intervals. Statistical analysis d Table 1 Demographic characteristics of study population of pre-schoolers, by age group All Younger < 4 yrs Older ≥4 yrs P n = 142 n = 76 n = 66 Gender Female 66 (46%) 40 (53%) 26 (39%) Male 76 (54%) 36 (47%) 40 (61%) 0.13 Chronic Health Condition Yes 4 (3%) 3 (4%) 1 (2%) No 138 (97%) 73 (96%) 65 (98%) 0.62 Aboriginal/ Torres Strait Islander Yes 5 (4%) 3 (4%) 2 (3%) No 137 (96%) 73 (96%) 64 (97%) 1.00 Parent Education Did not complete Year 10 3 (2%) 1 (1%) 2 (3%) Completed year 10 37 (26%) 16 (21%) 21 (32%) Completed Year 12 25 (18%) 19 (25%) 6 (9%) Commenced Higher Education Degree 14 (10%) 6 (8%) 8 (12%) Completed Higher Education Degree 42 (30%) 20 (26%) 22 (33%) Completed Post Graduate Course 21 (15%) 14 (18%) 7 (11%) 0.07 Table 1 Demographic characteristics of study population of pre-schoolers, by age group Burrows et al. Nutrition Journal 2014, 13:87 http://www.nutritionj.com/content/13/1/87 Page 4 of 10 Page 4 of 10 Table 2 Comparison of nutrient intakes, as assessed by the Australian Eating Survey Pre-schooler Version (AES-P) Food Frequency Questionnaire, to Australian Recommended Dietary Intakes (RDI), Adequate Intake (AI) and upper limit (UL), by age group Intake per day Younger < 4 yrs (n = 76) Older ≥4 yrs (n = 66) Meeting1 RDI/AI Mean Meeting RDI/AI Mean Meeting Protein (g) 14 57.23 100% 20 53.13 100% Fibre (g) 14 16.13 62% 18 15.9 44% Vitamin A (μg) 300 784.39 99% 400 735.54 97% Thiamine (mg) 0.5 1.4 99% 0.6 1.37 99% Riboflavin (mg) 0.5 2.27 100% 0.6 2.16 100% Niacine equiv (mg) 6 25.52 100% 8 24.26 100% Folate (μg) 150 223.91 89% 200 222.95 77% Vitamin C (mg) 35 84.14 97% 35 79.92 96% Calcium (mg) 500 1014.41 96% 700 945.23 87% Iron (mg) 9 7.84 22% 10 7.97 18% Magnesium (mg) 80 246.59 100% 130 239.72 100% Phosphorus(mg) 460 1151.03 100% 500 1073.8 100% Potassium(mg) 2000 2379.39 68% 2300 2188.1 54% Zinc (mg) 3 7.72 100% 4 7.3 99% Exceeding UL Mean Exceeding UL Mean Exceeding Sodium(mg)1 1000 1329.39 82% 1400 1342.27 61% %E Saturated fat2 10 16.83 95% 10 15.95 95% 1Nutrient Reference Values for Australia and New Zealand [22]. 2Australian Dietary Guidelines [18]. Discussion Table 4 demonstrates that total ARFS-P and the ARFS-P components were significantly related to AES-P FFQ in- take of the majority of macro and micronutrients. Total ARFS-P was positively related to protein (ρ = 22% CI95% 14-30), cholesterol (ρ = 27% CI95% 15-40), fibre (ρ = 12% CI95% 3-22), vitamin A (ρ = 40% CI95% 26-54), β-carotine (ρ = 58% CI95% 44-71), niacine equivalents (ρ = 20% CI95% 10-30), folate (ρ = 14% CI95% 2-26), vitamin C (ρ = 44% CI95% 31-58), calcium (ρ = 16% CI95% 4-29), magnesium (ρ = 16% CI95% 9-24), phosphorus (ρ = 13% CI95% 6-21), potassium (ρ = 27% CI95% 19-35) and zinc intake (ρ = 17% CI95% 10-25), while negatively related to carbohydrate (ρ = −10% CI95% -16- -5). The importance of consuming a large variety of nutri- tious foods is recognized within national food guide- lines [18]. The ARFS-P was developed to reflect the food behaviors and eating habits recommended in such guidelines. The use of brief tools is convenient for clinicians and allows for rapid individualized feed- back and early interventions targeting improvements in diet quality. This is important given recent reviews of diet quality indices in children suggesting healthier diet patterns are associated with cognition, behavior, and anthropometric factors [6,7]. Associations between diet quality indices and short and long term health out- comes, such as blood pressure, asthma, blood lipids, inflammation factors and dental caries, has also been recognized [6]. Table 4 also demonstrates that total ARFS-P was sig- nificantly related to eating patterns. It was positively Burrows et al. Discussion Nutrition Journal 2014, 13:87 http://www.nutritionj.com/content/13/1/87 Page 6 of 10 Table 3 The Australian Recommended Food Scores for Pre-schoolers (ARFS-P) and Australian Eating Survey Pre-schooler Version (AES-P) Food Frequency Questionnaire (FFQ) nutrients, and % energy from nutrient-dense and discretionary choices, by age (includes one for adequate water intake) (Continued) Discretionary choices 29 (21–37) 28 (19–36) 29.5 (21–37.5) 0.29 Sweetened drinks 2 (1–4) 2 (0–4) 2.5 (1–5) 0.19 Packaged snacks 4 (1–7) 3 (1–6) 4 (2–7) 0.09 Confectionary 3 (2–5) 4 (2–5) 3 (2–5) 0.81 Baked sweet products 5 (3–8) 5 (3–7) 4.5 (3–8) 0.92 Take-away 5 (3–6) 5 (3–7) 4 (3–6) 0.59 Condiments 2 (1–4) 2 (1–3) 3 (1–4) 0.14 Processed Meats 1 (1–2) 1 (1–2) 1 (1–2.5) 0.51 Sweet breakfast cereal 8 (5–11) 7 (5–10) 9 (7–11.5) 0.01 Table 3 The Australian Recommended Food Scores for Pre-schoolers (ARFS-P) and Australian Eating Survey Pre-schooler Version (AES-P) Food Frequency Questionnaire (FFQ) nutrients, and % energy from nutrient-dense and discretionary choices, by age (includes one for adequate water intake) (Continued) maximum point available, particularly for sub-scales of fruit and vegetables. This suggests that increasing the variety of fruit and vegetables consumed regularly could be important areas to target improvements in diet qual- ity. Other areas, in descending order, could include lean meat and vegetarian protein alternatives. This suggests that public health messages targeting increases in the variety amongst healthful foods that are consumed each week, could offer a new approach to nutrition promotion. This study is novel in applying this approach to assess diet quality in a pre-school population. We have previ- ously validated this diet quality scoring method, which uses a food-based approach in an older pediatric popula- tion aged 9–16 years [13]. While diet quality scores have been constructed for use in children, recent reviews have highlighted the need for additional studies in more di- verse population samples with analyses adjusted more fully for potential confounders [6,7] and a specific need for further studies in children under the age of five years [6,7,26]. The ARFS-P was calculated from intakes of whole foods rather than nutrient intakes, making this method of interest when information about usual food intake, as op- posed to nutrients, is sought or when feedback to individ- uals about their food patterns would be useful. This study found that ARFS-P scores were highly re- lated to both nutrient intakes and consumption patterns of children aged two to five years. Discussion Nutrition Journal 2014, 13:87 http://www.nutritionj.com/content/13/1/87 Page 5 of 10 Page 5 of 10 Table 3 The Australian Recommended Food Scores for Pre-schoolers (ARFS-P) and Australian Eating Survey Pre-schooler Version (AES-P) Food Frequency Questionnaire (FFQ) nutrients, and % energy from nutrient-dense and discretionary choices, by age (includes one for adequate water intake) Table 3 The Australian Recommended Food Scores for Pre-schoolers (ARFS-P) and Australian Eating Survey Pre-schooler Version (AES-P) Food Frequency Questionnaire (FFQ) nutrients, and % energy from nutrient-dense and discretionary choices, by age (includes one for adequate water intake) Table 3 The Australian Recommended Food Scores for Pre-schoolers (ARFS-P) and Australian Eating Survey Pre-schooler Version (AES-P) Food Frequency Questionnaire (FFQ) nutrients, and % energy from nutrient-dense and discretionary choices, by age (includes one for adequate water intake) Table 3 The Australian Recommended Food Scores for Pre-schoolers (ARFS-P) and Australian Eating Survey Pre-schooler Version (AES-P) Food Frequency Questionnaire (FFQ) nutrients, and % energy from nutrient-dense and discretionary choices, by age (includes one for adequate water intake) All (n = 142) Younger < 4 yrs (n = 76) Older ≥4 yrs (n = 66) ARFS-P (total possible score) Median IQR Median IQR Median IQR P Total (73)* 36 (29–42) 35 (29–42) 36 (29.5–41.5) 0.97 Vegetables (21) 11 (8–15) 11 (8–16) 11.5 (9–14) 0.91 Fruit (12) 8 (6–10) 8 (6–10) 8 (5.5–9.5) 0.67 Meat (7) 2 (2–3) 2 (2–3) 2 (2–3) 0.84 Meat alternatives (6) 2 (1–2) 1 (1–2) 2 (1–3) 0.78 Grains (13) 6 (4–7) 6 (4–7) 6 (4–7) 0.62 Dairy (11) 5 (4–6) 5 (4–6) 5 (4–6) 0.84 Condiments (2) 1 (1–2) 1 (1–2) 2 (1–2) 0.31 AES-P FFQ macronutrients Energy (kJ) 5216 (4647–6242) 5226 (4656–6379) 5182 (4577–5944) 0.43 Protein (g) 53.79 (47–63) 54.6 (48.0–63.9) 52.58 (44.7–60.1) 0.14 Saturated fat (g) 23.25 (17–28) 24.44 (19.6–28.7) 21.18 (16.5–26.9) 0.06 Cholesterol (mg) 161.7 (126–206) 167.3 (137–209) 155.9 (121–200) 0.09 Carbohydrate (g) 150.0 (130–177) 148.7 (129–181) 152.0 (133–175) 0.93 Sugars (g) 88.09 (72.9–109) 87.79 (73.7–110) 88.2 (69.9–106) 0.73 Fibre (g) 15.33 (12.4–18.0) 15.27 (11.7–18.6) 15.37 (12.9–17.8) 0.91 AES-P FFQ micronutrients Vitamin A (μg) 745.0 (604–891) 768.5 (620–914) 715.8 (594–878) 0.25 Retinol (μg) 339.5 (225–439) 359.2 (238–482) 314.1 (210–415) 0.08 β-carotine (μg) 2497 (1773–3049) 2580 (1676–3145) 2353 (184–2818) 0.65 Thiamine (mg) 1.28 (1.0–1.6) 1.28 (1.0–1.7) 1.28 (1.0–1.5) 0.96 Riboflavin (mg) 2.12 (1.7–2.6) 2.29 (1.7–2.6) 2.11 (1.6–2.5) 0.38 Niacine equivalent (mg) 23.75 (20.9–27.4) 24.01 (20.9–28.5) 23.71 (20.8–27.1) 0.60 Folate (μg) 211.2 (182–255) 211.2 (176–261) 210.2 (184–241) 0.95 Vitamin C (mg) 78.12 (59.9–100) 78.12 (63.2–102) 78.69 (59.6–98.3) 0.73 Calcium (mg) 963.2 (746–1167) 988.9 (828–1179) 889.9 (711–1093) 0.10 Iron (mg) 7.72 (6.1–8.9) 7.51 (6.1–8.9) 7.91 (6.2–8.7) 0.62 Magnesium (mg) 227.5 (202–277) 227.5 (202–278) 227.5 (202–275) 0.69 Potassium (mg) 2208 (1897–2618) 2311 (1931–2700) 2132 (1869–2494) 0.14 Phosphorus (mg) 1109 (900–1292) 1121 (956–1304) 1073 (869–1220) 0.15 Sodium (mg) 1279 (1052–1594) 1279 (1029–1603) 1287 (1097–1559) 0.69 Zinc (mg) 7.36 (6.3–8.5) 7.67 (6.4–8.7) 7.14 (6.2–8.1) 0.16 % Energy from Saturated Fat 17 (14.0–19.0) 17 (14.0–19.0) 16 (13.5–18.0) 0.12 Nutrient dense 71 (63–79) 72 (64–81) 70.5 (62.5–79) 0.29 Vegetables 5 (3–7) 5 (3–7) 5 (4–7) 0.78 Fruit 10 (7–15) 12 (8–16) 10 (7–13.5) 0.30 Meat 7 (5–9) 7 (5–9) 7 (5–9.5) 0.77 Meat alternatives 1 (1–3) 1 (1–3) 1 (1–3) 0.74 Grains 18 (14–21) 16 (13–20) 19 (15–22) 0.03 Dairy 28 (22–35) 29 (22–36) 26.5 (21.5–32.5) 0.10 Burrows et al. Discussion The sensitivity of this DQS is demonstrated by its ability to detect significant changes in macronutrient and micronutrient intake per unit change in ARFS-P. By way of example, the positive beta-coefficient of β-carotene with total ARFS-P means that an increase in total ARFS-P corresponds to an in- crease in pre-schooler β-carotene intake, on average. A similar trend was evident when considering intake of food groups and ARFS-P. Consequently the use of the ARFS-P was valid in assessing the eating patterns and nutrient intakes of the study population. Marginal sig- nificance was reached with saturated fat and cholesterol, providing some evidence that younger children may have been consuming more saturated fat and cholesterol than their older counterparts. While few DQIs have been developed specifically for use with toddler populations [27], findings from this study are similar to other diet quality validation studies in toddlers, including the FFQ DQI developed for pre- schoolers in which significant correlations were found between their DQI and nutrients such as protein, fibre, calcium and zinc [12], as we did in this study (r = 0.220, p < 0.001; r = 0.125, p = 0.008; r = 0.164, p = 0.011; r = 0.173, p < 0.001; respectively). However, we found a strong rela- tionship between ARFS-P and β-carotine where they did not; differences such as these are not surprising since they used Pearson's correlations that do not allow for control- ling for influences of, for instance total energy and age. Other validation studies of diet quality scores, such as the Healthy Eating index [28], found strong relationships with dietary intake, including fibre, folate and vitamin C, as did we (r = 0.125, p = 0.008; r = 0.141, p = 0.018; r = 0.441, p < 0.001; respectively). Strengths and limitations Anthropometric data, such as weight, were not obtained from this population, since the primary outcome measure of the FHFK randomized controlled trial was changes to dietary intake. As a consequence, the relationship be- tween weight status and ARFS-P could not be explored. However, unpublished data collected in 2008 as part of the Before School Screening program for 4–5 year olds (n = 571) in the same study locations suggested that rates of overweight and obesity were higher than the NSW average [29], with 26.8% of children overweight or obese Strategies to enhance diet quality need to focus on in- creasing the variety of nutrient-dense foods in a child’s diet, and reducing consumption of discretionary choices. Results of the current study indicate that each of the ARFS component scores were low compared to the total Burrows et al. Nutrition Journal 2014, 13:87 http://www.nutritionj.com/content/13/1/87 Page 7 of 10 Page 7 of 10 Table 4 Beta-coefficients relating intakes as assessed by the Australian Eating Survey Pre-schooler Version (AES-P) Food Frequency Questionnaire (FFQ), and the Australian Recommended Food Score for Pre-schoolers (ARFS-P) components of standardized ARFS component in linear regression model of standardized FFQ nutrient, adjusted for total FFQ energy and demographics age gender and education (n = 142) Table 4 Beta-coefficients relating intakes as assessed by the Australian Eating Survey Pre-schooler Version (AES-P) Food Frequency Questionnaire (FFQ), and the Australian Recommended Food Score for Pre-schoolers (ARFS-P) components of standardized ARFS component in linear regression model of standardized FFQ nutrient, adjusted for total FFQ energy and demographics age, gender and education (n = 142) Frequency Questionnaire (FFQ), and the Australian Recommended Food Score for Pre-schoolers (ARFS-P) components of standardized ARFS component in linear regression model of standardized FFQ nutrient, adjusted for total FFQ energy and demographics age, gender and education (n = 142) ARFS-P Total ARFS-P Veg ARFS-P Fruit ARFS-P Meat ARFS-P Altern. Strengths and limitations ARFS-P Grains ARFS-P Dairy ARFS-P Condmt AES-P FFQ Macronutrients Protein (g) 0.220 0.176 0.132 0.263 0.191 Saturated fat (g) Cholesterol (mg) 0.271 0.195 0.185 0.382 0.195 0.127 −0.156* Carbohydrate (g) −0.104 −0.100 −0.128** −0.052 −0.057 Sugars (g) −0.073 −0.093* Fibre (g) 0.125** 0.121* 0.173 0.091 −0.082 AES-P FFQ Micronutrients Vitamin A (μg) 0.399 0.442T 0.326 0.287** Retinol (μg) 0.187T β-carotine (μg) 0.578X 0.622X 0.469X 0.246X 0.235X Thiamine (mg) 0.246T Riboflavin (mg) 0.133 0.199* Niacine equivalent (mg) 0.171*T 0.123 0.138 0.152 0.158 0.147 Folate (μg) 0.141* 0.138* 0.165 0.105 Vitamin C (mg) 0.441 0.444 0.517 0.251** Calcium (mg) 0.164* 0.145* 0.111 0.125E 0.156* Iron (mg) Magnesium (mg) 0.164 0.126 0.133** 0.083* Potassium (mg) 0.273M 0.271M 0.281M 0.163E Phosphorus (mg) 0.132 0.110 0.068E 0.130E 0.149 Sodium (mg) −0.103* −0.083 0.194 0.176 Zinc (mg) 0.173 0.174 0.137 0.154 0.092* % Energy from Saturated Fat −0.149X Nutrient dense Foods 0.485 0.476 0.511 0.355 0.178* 0.231** −0.170* Vegetables 0.518 0.637 0.348 0.232 0.170* 0.208 Fruit 0.306X 0.277X 0.537 −0.207X Meat 0.276X 0.244X 0.214X 0.535 Meat alternatives 0.316T 0.198T 0.170T 0.673 0.279T Grains −0.171X Dairy Discretionary Choices −0.484* −0.476 −0.509 −0.355** −0.177* −0.231** 0.171* Sugar sweetened drinks −0.333T −0.272 −0.302*T −0.192T Packaged snacks −0.379 −0.284 −0.409** −0.187T −0.249T −0.271T Confectionary −0.199X −0.223*X −0.209X −0.152X Baked sweet products −0.149X −0.162X Take-away −0.354X −0.328X −0.290X −0.260X −0.199X −0.188X Burrows et al. Nutrition Journal 2014, 13:87 http://www.nutritionj.com/content/13/1/87 Page 8 of 10 Table 4 Beta-coefficients relating intakes as assessed by the Australian Eating Survey Pre-schooler Version (AES-P) Food Frequency Questionnaire (FFQ), and the Australian Recommended Food Score for Pre-schoolers (ARFS-P) components of standardized ARFS component in linear regression model of standardized FFQ nutrient, adjusted for total FFQ energy and demographics age, gender and education (n = 142) (Continued) Condiments −0.256X 0.258X Processed Meats −0.195X −0.199X −0.159X −0.178X −0.203X Sweet breakfast cereal −0.143X −0.172X −0.147X Only beta-coefficients with P < 0.10 are shown; 5% significance, **1% significance. (T) square root transform was applied, (M) gender significant in model, (E) parent education significant in model, (X) energy not significant in model. Shaded values indicate a negative relationship. Table 4 Beta-coefficients relating intakes as assessed by the Australian Eating Survey Pre-schooler Frequency Questionnaire (FFQ), and the Australian Recommended Food Score for Pre-schoolers (A standardized ARFS component in linear regression model of standardized FFQ nutrient, adjusted f and demographics age, gender and education (n = 142) (Continued) (27.3% male, 26.3% female). Strengths and limitations Despite a previous study sug- gesting that the FFQ was relatively accurate when asses- sing total energy intake at the group level [4], over –and under-reporting of dietary intake and physical activity level were not assessed in the current study. The rela- tively small sample from rural locations reduces the generalizability and hence results should be interpreted with caution. reports from both parents, or where appropriate, with the child present to try to reduce reporting biases [32,33]. Some limitations of calculating and using ARFS to de- termine usual diet quality have been previously published [13], including that the national nutrient databases used in this study does not accurately reflect population consump- tion of folate as fortification of breads, cereals and cereal products is not accounted for within the database, hence results obtained for FFQ folate intake are likely to be lower than true intake. The effect of parental bias must also be considered when interpreting results as a caregiver completed the AES-P on their child’s behalf. This may exacerbate the over reporting bias already associated with the use of an FFQ [30] and may increase the chance that the data is incomplete or that intake has been underestimated [31]. Future studies should consider obtaining dietary intake Abbreviations DQI Di Q li DQI: Diet Quality Index; FFQ: Food Frequency Questionnaire; ACARFS: Australian Child and Adolescent Recommended Food Score; ARFS: Australian Adolescent Recommended Food Score; ARFS-P: Australian Adolescent Recommended Food Score for Pre-schoolers; HNE: Hunter New England; FHFK: Feed Healthy Food to Kids; NSW: New South Wales; AES: Australian Healthy Eating Survey; AES-P: Australian Healthy Eating Survey Pre-schooler version; RDI: Recommended Daily Intake; AI: Adequate Intake; UL: Upper Limits; %E: Percent energy. 12. Huybrechts I, Vereecken C, De Bacquer D, Vandevijvere S, Van Oyen H, Maes L, Vanhauwaert E, Temme L, De Backer G, De Henauw S: Reproducibility and validity of a diet quality index for children assessed using a FFQ. Br J Nutr 2010, 104:135–144. 13. Marshall S, Watson J, Burrows T, Guest M, Collins C: The development and evaluation of the Australian child and adolescent recommended food score: a cross-sectional study. Nutr J 2012, 11:96. Received: 3 December 2013 Accepted: 29 August 2014 Published: 2 September 2014 Received: 3 December 2013 Accepted: 29 August 2014 Published: 2 September 2014 children, and provides researchers the opportunity to use an independent measure of intake, or calculated sec- ondarily, from the AES-P FFQ. Its calculation is less oner- ous than methods that require derivation of nutrient based sub-scales. This means that the provision of feedback based on overall score can potentially be in real-time. References kl 1. Nicklas T: Assessing diet quality in children and adolescents. J Am Diet Assoc 2004, 104:1383–1384. 2. Kant A: Indexes of overall diet quality: A review. J Am Diet Assoc 1996, 96:785–791. Based on the finding in the current study, the ARFS-P method for scoring diet quality could be applied to other FFQs, in other populations, age groups, and in other settings. This could include testing its use as a self- monitoring tool or within clinical practice. If validated in these settings it would be a convenient tool that could be used by a variety of health professionals to assess and monitor dietary patterns. 3. Wirt A, Collins C: Diet quality - what is it and does it matter? Public Health Nutr 2009, 12:2473–2492. 4. Collins C, Burrows T, Truby H, Morgan P, Wright I, Davies P, Callister R: Comparison of energy intake in toddlers assessed by food frequency questionnaire and total energy expenditure measured by the doubly labeled water method. J Acad Nutr Diet 2013, 113:459–463. 5. Burrows T, Martin R, Collins C: A systematic review of the validity of the dietary assessment methods in children when compared with the method of doubly labeled water. J Am Diet Assoc 2010, 110:1501–1510. y 6. Lazarou C, Newby P: Use of dietary indexes among children in developed countries. Adv Nutr 2011, 2:295–303. y 6. Lazarou C, Newby P: Use of dietary indexes among children in developed countries. Adv Nutr 2011, 2:295–303. 7. Smithers L, Golley R, Brazionis L, Lynch J: Characterizing whole diets of young children from developed countries and the association between diet and health: a systematic review. Nutr Rev 2011, 69:449–467. 7. Smithers L, Golley R, Brazionis L, Lynch J: Characterizing whole diets of young children from developed countries and the association between diet and health: a systematic review. Nutr Rev 2011, 69:449–467. Authors’ contributions KC JW TB MN MR KD KC, JW, TB, MN, MR, KD and CEC conceived of the study, and participated in its design and data collection and entry. MG and MMB participated in the design of the study, data collection and performed the statistical analysis. All authors contributed to the preparation of the manuscript. All authors read and approved the final manuscript. an accurate reporter? Clin Nutr 2012, 32:613–618. 18. Australian Government Publishing Service: Eat for Health: Australian Dietary Guidelines; 2013. 19. Commonwealth Scientific Industrial Research Organisation (CSIRO): 2007 Australian National Children’s Nutrition and Physical Activity Survey - Main Findings; 2008. ISBN ISBN: 1-74186-756-8. Conclusions In conclusion, the ARFS-P is a brief dietary index that as- sesses usual diet quality, food variety and the nutritional adequacy of dietary intakes of Australian pre-schoolers. It was a valid tool that can be used to characterize nutrient intake as well as eating patterns. Future research should examine whether the ARFS-P can be used to target im- provements in diet quality within interventions and/or population health approaches aimed at optimizing the diet- ary patterns of young children. 8. Lazarou C, Panagiotakos DB, Spanoudis G, Matalas A-L: E-KINDEX: a dietary screening tool to assess children’s obesogenic dietary habits. J Am Coll Nutr 2011, 30:100–112. 9. Hurley K, Oberlander S, Merry B, Wrobleski M, Klassen A, Black M: The healthy eating index and youth healthy eating index are unique, nonredundant measures of diet quality among low-income African American adolescents. J Nutr 2009, 139:359–364. 10. Kleiser C, Mensink G, Scheidt-Nave C, Kurth B: HuSKY: a healthy nutrition score based on food intake of children and adolescents in Germany. Br J Nutr 2009, 102:610–618. 11. Royo-Bordonada M, Gorgojo L, Ortega H, Martín-Moreno J, Lasuncíon M, Garcés C, Gil A, Rodríguez-Artalejo F, de Oya M: Greater dietary variety is associated with better biochemical nutritional status in Spanish children: The Four Provinces Study. Nutr Metab Cardiovasc Dis 2003, 13:357–364. Competing interests 14. Watson J, Collins C, Sibbritt D, Dibley M, Garg M: Reproducibility and comparative validity of a food frequency questionnaire for Australian children and adolescents. Int J Behav Nutr Phys Act 2009, 6:62. This study was conducted at the University of Newcastle, Callaghan NSW, Australia. All authors declare that they have no conflicts of interest or financial interests or affiliations with institutions, organizations or companies mentioned in the manuscript. CEC was supported by an Australian National Health and Medical Research Council Career Development Research Fellowship. MMB was supported by a Faculty of Health and Medicine, University of Newcastle Visiting Scholar Grant. KC was supported by a Summer Scholarship from the Australasian Child and Adolescent Obesity Research Network (ACAORN). 15. Duncanson K, Burrows T, Collins C: Study protocol of a parent-focused child feeding and dietary intake intervention: the feeding healthy food to kids randomised controlled trial. BMC Public Health 2012, 12:564–575. 16. Duncanson K, Burrows T, Collins C: Effect of a Low-Intensity Parent- Focused Nutrition Intervention on Dietary Intake of 2-to 5-Year Olds. J Pediatr Gastroenterol Nutr 2013, 57:728–734. 17. Burrows T, Truby H, Morgan P, Callister R, Davies P, Collins C: A comparison and validation of child versus parent reporting of children’s energy intake using food frequency questionnaires versus food records: Who’s an accurate reporter? Clin Nutr 2012, 32:613–618. Implications for research and practice The ARFS-P allows for the rapid measurement of diet quality of children aged 2–5 years in a single continuous variable. It was derived from a validated FFQ for young β−carotine (mg) %E vegetables %E nutrient dense Vitamin C (mg) %E meat alternatives Vitamin A (μg) %E fruit Potassium (mg) %E meat Cholesterol (mg) Protein (mg) Niacine Equiv. (mg) Zinc (mg) Magnesium (mg) Calcium (mg) Folate (μg) Fibre (g) Phosphorus (mg) Carbohydrate (g) %E processed meats %E confectionary %E sugar sweetened drinks %E take−away %E packaged snacks %E energy dense, nutrient poor −.6 −.4 −.2 0 .2 .4 .6 ARFS−P Beta−Coefficients p<0.05 p<0.01 p<0.001 p<0.0001 Figure 1 Significant beta-coefficients of ARFS-P component of AES-P nutrients and%E from food groups, controlling for total energy consumption, age, gender and parent education, as estimated by linear regression modelling, with 95% confidence intervals. .4 .2 0 .2 .4 ARFS−P Beta−Coefficients Figure 1 Significant beta-coefficients of ARFS-P component of AES-P nutrients and%E from food groups, controlling for total energy consumption, age, gender and parent education, as estimated by linear regression modelling, with 95% confidence intervals. Burrows et al. Nutrition Journal 2014, 13:87 http://www.nutritionj.com/content/13/1/87 Page 9 of 10 Page 9 of 10 Author details 1 20. Food Standards Australia New Zealand: AUSNUT 2007 Australian Food, Supplement & Nutrient Database 2007; 2008. 1Nutrition and Dietetics, School of Health Sciences, Faculty of Health and Medicine, The University of Newcastle, Callaghan 2308, NSW, Australia. 2Priority Research Centre in Physical Activity and Nutrition, Faculty of Health, The University of Newcastle, Callaghan 2308, NSW, Australia. 3Environmental and Occupational Health and Safety, School of Health Sciences, Faculty of Health and Medicine, The University of Newcastle, Callaghan 2308, NSW, Australia. 4School of Mathematical and Statistical Sciences, Arizona State University, Tempe 85281, AZ, USA. 5Hunter New England Local Health District, Forster 2428, NSW, Australia. 21. Xyris Software (Australia) Pty Ltd: FoodWorks Professional Version 3.02.581. 2004. 22. Australian Government Publishing Service: Nutrient Reference Values for Australian and New Zealand including Recommended Dietary Intakes. ; 2006. 22. Australian Government Publishing Service: Nutrient Reference Values for Australian and New Zealand including Recommended Dietary Intakes. ; 2006. 23. Kant A, Schatzkin A, Graubard B, Schairer C: A prospective study of diet quality and mortality in women. JAMA 2000, 283:2109–2115. 24. Collins C, Young A, Hodge A: Diet quality is associated with higher nutrient intake and self-related health in mid-aged women. J Am Coll Nutr 2008, 27:146–157. Page 10 of 10 Page 10 of 10 Burrows et al. Nutrition Journal 2014, 13:87 http://www.nutritionj.com/content/13/1/87 Burrows et al. Nutrition Journal 2014, 13:87 http://www.nutritionj.com/content/13/1/87 Burrows et al. Nutrition Journal 2014, 13:87 http://www.nutritionj.com/content/13/1/87 25. StataCorp LP: Stata MP, version 12; 2012. 26. Magarey A, Watson J, Golley R, Burrows T, Sutherland R, McNaughton S, Denney-Wilson E, Campbell K, Collins C: Assessing dietary intake in children and adolescents: Considerations and recommendations for obesity research Int J Pediatr Obes 2011, 6:2–11. 27. Collins C, Duncanson K, Burrows T: A systematic review investigating associations between parenting style and child feeding behaviours. J Hum Nutr Diet 2013, doi:10.1111/jhn.12192. 28. Manios Y, Kourlaba G, Kondaki K, Grammatikaki E, Birbilis M, Oikonomou E, Roma-Giannikou E: Diet quality of preschoolers in Greece based on the Healthy Eating Index: the GENESIS study. J Am Diet Assoc 2009, 109:616–623. 29. Hardy L, King L, Bauman A, Espinel P: NSW Schools Physical Activity and Nutrition Survey (SPANS) 2010 Full Report; 2010. y 30. Kourlaba G, Kondaki K, Grammatikaki E, Roma-Giannikou E, Manois Y: Diet quality of preschool children and maternal perceptions/misperceptions: the GENESIS study. Public Health 2009, 123:738–742. 30. Author details 1 Kourlaba G, Kondaki K, Grammatikaki E, Roma-Giannikou E, Manois Y: Diet quality of preschool children and maternal perceptions/misperceptions: the GENESIS study. Public Health 2009, 123:738–742. 31. Baranowski T, Sprague D, Baranowski J, Harrison J: Accuracy of maternal dietary recall for preschool children. J Am Diet Assoc 1991, 91:669–674. 32. Eck L, Klesges R, Hanson C: Recall of a child’s intake from one meal: are parents accurate? J Am Diet Assoc 1989, 89:784–789. 33. Sobo E, Rock C: “You Ate All That!?”: Caretaker‐Child Interaction during Children’s Assisted Dietary Recall Interviews. Med Anthropol Q 2001, 15:222–244. doi:10.1186/1475-2891-13-87 Cite this article as: Burrows et al.: Validity of the Australian Recommended Food Score as a diet quality index for Pre-schoolers. Nutrition Journal 2014 13:87. Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color ﬁgure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color ﬁgure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit
https://openalex.org/W3014191315	https://europepmc.org/articles/pmc7140574?pdf=render	English	null	Morpho-physiological integrators, transcriptome and coexpression network analyses signify the novel molecular signatures associated with axillary bud in chrysanthemum	BMC plant biology	2,020	cc-by	11,818	Abstract Background: Axillary bud is an important agronomic and economic trait in cut chrysanthemum. Bud outgrowth is an intricate process controlled by complex molecular regulatory networks, physio-chemical integrators and environmental stimuli. Temperature is one of the key regulators of bud’s fate. However, little is known about the temperature-mediated control of axillary bud at molecular levels in chrysanthemum. A comprehensive study was designed to study the bud outgrowth at normal and elevated temperature in cut chrysanthemum. Leaf morphology, histology, physiological parameters were studied to correlate the leaf activity with bud morphology, sucrose and hormonal regulation and the molecular controllers. Results: Temperature caused differential bud outgrowth along bud positions. Photosynthetic leaf area, physiological indicators and sucrose utilization were changed considerable due to high temperature. Comparative transcriptome analysis identified a significant proportion of bud position-specific genes.Weighted Gene Co- expression Network Analysis (WGCNA) showed that axillary bud control can be delineated by modules of coexpressed genes; especially, MEtan3, MEgreen2 and MEantiquewhite presented group of genes specific to bud length. A comparative analysis between different bud positions in two temperatures revealed the morpho- physiological traits associated with specific modules. Moreover, the transcriptional regulatory networks were configured to identify key determinants of bud outgrowth. Cell division, organogenesis, accumulation of storage compounds and metabolic changes were prominent during the bud emergence. Ahmad et al. BMC Plant Biology (2020) 20:145 https://doi.org/10.1186/s12870-020-02336-0 Ahmad et al. BMC Plant Biology (2020) 20:145 https://doi.org/10.1186/s12870-020-02336-0 Open Access Morpho-physiological integrators, transcriptome and coexpression network analyses signify the novel molecular signatures associated with axillary bud in chrysanthemum Sagheer Ahmad1, Cunquan Yuan1, Qingqing Yang1, Yujie Yang1, Tangren Cheng1, Jia Wang1, Huitang Pan1 and Qixiang Zhang1,2* * Correspondence: zqx@bjfu.edu.cn 1 Correspondence: zqx@bjfu.edu.cn 1Beijing Key Laboratory of Ornamental Plants Germplasm Innovation & Molecular Breeding, National Engineering Research Center for Floriculture, Beijing Laboratory of Urban and Rural Ecological Environment, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants of Ministry of Education, School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China 2Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing 100083, China 2Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing 100083, China Background on ROS (reactive oxygen species) along with transcrip- tome implied the importance of ROS balance in panicle growth [24]. According to a report on rice genome, one half of the genes (50.4%) expressed at 25 °C and another half (50.2%) expressed at 30 °C; moreover, temperature stimulated many transcription factor families, including WRKY, bZIP, and MYB [25]. Thus far, nothing is docu- mented on the transcriptional mechanism of axillary bud outgrowth in response to high temperature in cut chrysanthemum. Branches, besides being the architectural determinants, provide plants with plenty of shapes and ornamental values. Axillary bud is one of the most important agro- nomic traits related to cut floral beauty; especially in chrysanthemum where excessive outgrowth of axillary branches is a major drawback in market success of cut flowers. Since antiquity, strides have been directed to- wards the temperature control, manual disbudding and the molecular regulation of axillary growth. However, due to limited access to the complex genomic structure of this crop, the bud control remained a mystery for the researchers. Recently, the whole genome sequencing [1] have facilitated the tracing of axillary bud regulation at molecular levels. With this breakthrough, a comprehen- sive assessment of molecular regulatory mechanism of bud outgrowth controlled by temperature can point out important thermal inhibitors of axillary bud. Temperature extremes can cause water stress, thereby triggering the reactive oxygen species (ROS) [26–28]. Excessive accumulation of ROS can cause oxidative harm to lipids leading to the production of MDA (mal- ondialdehyde), an indicator of oxidative stress level in plants [29]. Plants use antioxidant defense system to cope with the accumulation of ROS. This system uses water-soluble reducing agents (e.g., glutathione and as- corbate), lipid-soluble antioxidants (e.g., carotene and α- tocopherol) and enzymes like SOD (superoxide dismut- ase) [27, 30]. Thus, deciphering the accumulation of SOD and MDA can expose the damages caused by water stress and/or temperature stress. SOD triggers the ca- talysis of superoxide radical to H2O2 and O2 through a spontaneous and extremely fast reaction in order to de- fend the plant cells from the products of superoxide rad- ical reaction. The potentially toxic compound is reduced to water through the action of enzymes, such as catalase (CAT) and peroxidase (POD) [31, 32]. CAT converts hydrogen per oxide (H2O2) to H2O and O2. (Continued from previous page) (Continued from previous page) Conclusions: RNA-seq data coupled with morpho-physiological integrators from three bud positions at two temperature regimes brings a robust source to understand bud outgrowth status influenced by high temperature in cut chrysanthemum. Our results provide helpful information for elucidating the regulatory mechanism of temperature on axillary bud growth in chrysanthemum. Keywords: High temperature, Axillary bud, WGCNA, Chrysanthemum, Keywords: High temperature, Axillary bud, WGCNA, Chrysanthemum, © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Page 2 of 15 Ahmad et al. BMC Plant Biology (2020) 20:145 Ahmad et al. BMC Plant Biology Background High-definition transcriptomic investigations in different plants have provided valuable insights into the molecular pathways and networks, and their interactions with differ- ent aspects of bud outgrowth [2–7]. The molecular mech- anism behind bud outgrowth has been demonstrated to some depth in some plants [2, 8]. Carbohydrate distribu- tion, photoassimilate supply and the accumulation rate of storage compounds during bud initiation are important regulators of bud outgrowth [9–11]. Moreover, epigenetic imprinting and hormonal signal transduction have also been considered as pivotal regulators of bud kinetics [12– 17]. Along with these regulators, temperature is also con- sidered pivotal when studying bud opening and outgrowth. Chrysanthemum is the second most important flori- culture crop in worldwide floriculture trade [33, 34], sharing 30% of the total cut flower production in the world. Axillary branching is a vital end-user quality attri- bute of cut chrysanthemum. Diminished axillary bud growth is highly desirable to provide high market price for cut flowers. The accessibility to its genomic se- quences and the transcriptome [1] along with RNA- Sequencing can do a great deal to reveal genetic regula- tion of bud initiation and outgrowth in cut chrysanthe- mum. A few efforts have been made to understand the transcriptomic basis of bud development [2, 3, 6]. How- ever, no such strides have been made to find the temperature-mediated molecular mechanism behind bud initiation and outgrowth in chrysanthemum. However, after the report of Faust and Heins [18], stat- ing that chrysanthemum (Powerhouse) produces little axillary shoots at 35 °C; no further progress could be made in chrysanthemum. Temperature elevation beyond a certain level can cause sterile spikelet [19]; as sug- gested to be due to high temperature [20–23]. The re- cent researches have shown many spikelet-related DEGs sensitive to heat stress [19] and a high temperature ex- posure of 39 °C suppressed the spikelet fertility [23]. Gene expression profiling of rice panicles growing at 40 °C identified DEGs involving mainly in transport, transcriptional regulation, stress response and cellular homeostasis [24]. Moreover, the pattern of gene expres- sion due to heat stress and the regulation model based Page 3 of 15 Page 3 of 15 Ahmad et al. BMC Plant Biology (2020) 20:145 Ahmad et al. BMC Plant Biology (2020) 20:145 To the best of our knowledge, a comparative transcrip- tome analysis of bud outgrowth, at different positions, at different temperatures has not yet been performed in cut chrysanthemum. Results High temperature causes morpho-physiological changes in plants [35] and removing leaves retards bud outgrowth, showing the importance of leaf-derived physio-metabolic factors in axillary bud control [36]. Therefore, connecting leaf dynamics with bud outgrowth can be an effective tool to understand the leaf-mediated influence of temperature. Background Here, we applied RNA-Seq technology to analyze axillary bud transcriptome at two different temper- atures (i.e., 25 °C and 35 °C). The data were dissected to as- certain transcriptome dynamics and the transcriptional regulatory networks linked with bud outgrowth. The coex- pressed gene modules were identified for each bud position under contrasting temperatures. Moreover, spacial control of photoassimilates and the chemical homeostasis by leaves were also studied as indirect controlling mechanism for bud regulation. Thus, this study gives valuable insights into the molecular regulatory mechanism and the pivotal factors governing axillary bud outgrowth. (Supplementary Fig. 1). At this stage, high density of ax- illary growth was seen in normal temperature regime as compared to high temperature. Top buds retained the growth potential at both the temperatures. However, high temperature almost completely checked the out- growth of top axillary buds (TAB). More axillary growth was seen at lower axillary positions at 25 °C, whereas it was restricted in high temperature regime, suggesting that different bud positions respond differently against temperature changes. Temperature indirectly affects bud kinetics via leaf Temperature indirectly affects bud kinetics via leaf Among the leaf morphological indices, leaf area (Fig. 1o), wet to dry mass ratio (Fig. 1q) and stomatal density (Fig. 1p) were observed in 11 days post-transplantation in contrasting temperature regimes. Leaf area was mar- ginally high in normal temperature plants as compared to high temperature. High wet to dry mass ratio was seen in high temperature plants, suggesting more accu- mulation of photoassimilates in the leaf. However, the stomatal density was significantly high in top bud leaves (50.33 mm−2, p < 0.01) in 35 °C leaves as compared to 24 °C where only 10.33 stomata were found in 1 mm−2 surface area. Bud positions express differently for high and normal temperature More photosynthesis was observed in 25 °C plants as compared to 35 °C (Fig. 1a). Same was the case with transpiration (Fig. 1d) where normal temperature caused more gas exchange. In the case of water conductance At an extended plant height (35–40 cm) the plant shows maximum bearing of axillary buds at all positions Fig. 1 Bud length, sucrose concentration and internodal distance (extreme left). Sampling plan for axillary buds and leaves of Chrysanthemum morifolium ‘Jinba’ under contrasting temperatures (left) and three leaf positions used for analysis (middle) and the leaf parameters (right). The leaf characteristics include, (a) photosynthesis, (b) water conductance, (c) intercellular CO2 concentration, (d) transpiration, (e) chlorophyll a, (f) chlorophyll b, (g) total chlorophyll, (h) carotenoids, (i) crude protein, (j) MDA, (k) SOD, (l) CAT, (m) POD, (n) leaf area, (o) stomatal density and (p) W/D ratio. Data are shown as mean ± SE of three biological replicates. Asterisks on specific terms show significant differences between the treatment conditions 25 °C and 35 °C for each bud position at p < 0.05() and p < 0.01() level Fig. 1 Bud length, sucrose concentration and internodal distance (extreme left). Sampling plan for axillary buds and leaves of Chrysanthemum morifolium ‘Jinba’ under contrasting temperatures (left) and three leaf positions used for analysis (middle) and the leaf parameters (right). The leaf characteristics include, (a) photosynthesis, (b) water conductance, (c) intercellular CO2 concentration, (d) transpiration, (e) chlorophyll a, (f) chlorophyll b, (g) total chlorophyll, (h) carotenoids, (i) crude protein, (j) MDA, (k) SOD, (l) CAT, (m) POD, (n) leaf area, (o) stomatal density and (p) W/D ratio. Data are shown as mean ± SE of three biological replicates. Asterisks on specific terms show significant differences between the treatment conditions 25 °C and 35 °C for each bud position at p < 0.05() and p < 0.01(*) level Fig. 1 Bud length, sucrose concentration and internodal distance (extreme left). Sampling plan for axillary buds and leaves of Chrysanthemum morifolium ‘Jinba’ under contrasting temperatures (left) and three leaf positions used for analysis (middle) and the leaf parameters (right). The leaf characteristics include, (a) photosynthesis, (b) water conductance, (c) intercellular CO2 concentration, (d) transpiration, (e) chlorophyll a, (f) chlorophyll b, (g) total chlorophyll, (h) carotenoids, (i) crude protein, (j) MDA, (k) SOD, (l) CAT, (m) POD, (n) leaf area, (o) stomatal density and (p) W/D ratio. Transcriptome analysis of buds at different positions a sc pto e a a ys s o buds at d e e t pos t o s The transcriptome analysis of buds from different positions can give important system-level insights into the molecular regulatory mechanism behind bud initiation and outgrowth. A total of 13 billion high-quality reads (average ~ 65 million reads from each sample) were generated for all bud samples and mapped to chrysanthemum genome (v2.0) using TopHat. The mapped reads were processed via cuffdiff to generate normalized expression as FPKM for each tran- script. The number of expressed genes varied from 60 to 70% in different tissues. About 10–15% of genes showed high expression (FPKM ≥10) (Supplementary Table 1). Overall, these analyses exhibited enough coverage of tran- scriptome during bud outgrowth in chrysanthemum. Ultra-structural leaf and bud attributes as influenced by temperature variation Paraffin sectioning buds showed that high temperature pro- hibited the bud outgrowth to some extent in all bud posi- tions (Fig. 2a, b). Top buds showed a little restricted growth in high temperature as compared to normal temperature (Fig. 2; A1, B1). However, the marked difference was noted at top axillary buds where bud outgrowth was completely checked by high temperature at the 11th day of growth in contrasting temperatures (Fig. 2, B2). In lower axillary buds, the outgrowth was more at normal temperature (Fig. 2, A3) as compared to high temperature (Fig. 2, B3). Bud positions express differently for high and normal temperature Data are shown as mean ± SE of three biological replicates. Asterisks on specific terms show significant differences between the treatment conditions 25 °C and 35 °C for each bud position at p < 0.05() and p < 0.01(*) level Page 4 of 15 Ahmad et al. BMC Plant Biology (2020) 20:145 Ahmad et al. BMC Plant Biology (2020) 20:145 F1-F3) temperature for TBL (E1, F1), MBL (E2-F2) and LBL (E3-F3). Figure 3(g-h) shows the transmission elec- tron micrographs of top axillary leaves for understanding the chloroplast distribution within the cell as influenced by temperature variations. (Fig. 1b), considerable difference was observed at differ- ent temperatures as compared to intercellular CO2 con- centration (Fig. 1c). Significant changes occurred in chlorophyll contents (Fig. 1e-g) at different tempera- tures, suggesting positive correlation between photosyn- thetic pigments and normal temperature. Carotenoids were also observed to be more fluctuating at upper bud leaves due to temperature change (Fig. 1h). Physiological responses of leaf against temperature Physiological responses of leaf against temperature A significant difference (p < 0.01) was observed in the top bud leaves (TBL) in crude protein concentration (Fig. 1i). 25 °C leaves showed significant high MDA con- tent in top bud leaves (Fig. 1j) whereas negligible differ- ences were seen at other bud positions. In case of SOD concentration (Fig. 1k), top leaves showed high concen- tration in normal temperature and lower bud leaves (LBL) showed high concentration in high temperature. However, the difference was more significant in TBL as compared to LBL. For POD (Fig. 1m), the maximum concentration was shown by TBL in normal temperature than high temperature. However, the TBL and LBL did not show significant differences, except that the POD concentration was little high in normal temperature leaves at both leaf positions. The catalase activity was significant at LBL and CAT concentration was the max- imum at 25 °C than 35 °C. However, at other leaf posi- tions, there was no considerable difference between the leaves at contrasting temperatures (Fig. 1l). Temperature causes differential bud outgrowth and sugar distribution along bud positions Significant difference (p < 0.01) of sucrose accumulation was noted at lower axillary buds in normal temperature as compared to high temperature (Fig. 1). However, the difference was not significant at top buds and top axil- lary buds at both the temperatures except that the su- crose levels were slightly high in high temperature. Significant effect of temperature can be seen in bud length at both temperature regimes, whereby high temperature suppressed the bud outgrowth (Fig. 1). In- ternodal distance was higher in normal temperature plants as compared to high temperature. Transcriptomic comparison revealed dynamic relationships among bud stages Leaf outer surface pictures at 25 °C (TBL:E1, MBL:E2; LBL:E3) and 35 °C (TBL:F1, MBL:F2; LBL:F3). Transmission electron micrographs at 25 oC (TBL: G1, G2) and 35 °C (TBL: H1, H2) Preferential gene expression during bud outgrowth Stage specificity (SS) algorithm was applied, with SS score greater than or equal to 0.05, to point out the genes expressed commonly and specifically at a particular bud position in both the temperatures. Due to huge number of data, only those genes were selected with FPKM ≥5. A total of 15,144, 15,127 and 14,791 genes were found to be common in TB, TAB and LAB, respectively, at both the temperatures (Fig. 3a). However, 339 genes were express- ing specifically in TB at 25 °C and 581 at 35 °C; 391 and 559 were specific to TAB at 25 °C and 35 °C, respectively; 1043 and 336 were defined as specific to LAB at 25 °C and 35 °C, respectively (Fig. 3b). The analysis of gene ontology (GO) enrichment of all the specifically expressed genes at two different temperatures exhibited the genes mainly related to metabolic processes, response to stress, growth regulation, transport, organo- genesis, cell cycle, cell division and hormonal regulation (Fig. 3d). These processes are well established as integral regulators of bud growth and development. The analysis of gene ontology (GO) enrichment of all the specifically expressed genes at two different temperatures exhibited the genes mainly related to metabolic processes, response to stress, growth regulation, transport, organo- genesis, cell cycle, cell division and hormonal regulation (Fig. 3d). These processes are well established as integral regulators of bud growth and development. Transcriptomic comparison revealed dynamic relationships among bud stages To know the transcriptomic differences in bud outgrowth at two different temperatures, we performed principal component analysis (PCA) and hierarchical clustering based on spearman correlation coefficient analysis of aver- age FPKM values of all the genes expressed in at least one of the 3 tissue samples (Supplementary Fig. 2). Considering the microscopic examination of leaves (Fig. 2c, d), the leaf mesophyll cells were more arranged and shaped in normal temperature leaves (Fig. 2; C1-C3) as compared to high temperature (Fig. 2; D1-D3), where a mild disruption was seen in the cortex. However, the influence was more prominent in top axillary leaves (Fig. 2; C1, D1), whereby high temperature caused more dis- rupted growth (Fig. 2, D1) than that of normal temperature (Fig. 2, C1). While observing the stomatal density, the outer surface was also seen via nail polish (Fig. 2e, f). Cell surfaces were presenting some sort of variations against normal (Fig. 2; E1-E3) and high (Fig. 2; The tissues exhibiting high correlation are supposed to have similarity in transcriptomes and activities. These analyses pointed out higher correlation among similar bud developmental stages between two temperature re- gimes. It can be seen that bud transcriptomes in 35 °C were clustering differently as compared to 25 °C (Supple- mentary Fig. 2a). 35 °C TB and LAB were clustering more close than any of the other tissues and these two were closely placed with 25 °C TB, suggesting some point of coordination between the two temperature regimes (Supplementary Fig. 2b). Ahmad et al. BMC Plant Biology (2020) 20:145 Page 5 of 15 Fig. 2 Microscopic examinations of bud (A,B) and leaf (C-H) characteristics under two different temperatures. Paraffin sectioning pictures of bud at 25 °C (TB:A1, TAB:A2; LAB:A3) and 35 °C (TB:B1, TAB:B2; LAB:B3). Paraffin sectioning pictures of leaf cross section at 25 °C (TBL:C1, MBL:C2; LBL:C3) and 35 °C (TBL:D1, MBL:D2; LBL:D3). Leaf outer surface pictures at 25 °C (TBL:E1, MBL:E2; LBL:E3) and 35 °C (TBL:F1, MBL:F2; LBL:F3). Transmission electron micrographs at 25 oC (TBL: G1, G2) and 35 °C (TBL: H1, H2) Fig. 2 Microscopic examinations of bud (A,B) and leaf (C-H) characteristics under two different temperatures. Paraffin sectioning pictures of bud at 25 °C (TB:A1, TAB:A2; LAB:A3) and 35 °C (TB:B1, TAB:B2; LAB:B3). Paraffin sectioning pictures of leaf cross section at 25 °C (TBL:C1, MBL:C2; LBL:C3) and 35 °C (TBL:D1, MBL:D2; LBL:D3). Differentially expressed gene sets between 25 °C and 35 °C at different bud positions A total of 3366, 3280 and 3291 genes were up-regulated in TB, TAB and LAB, respectively; while, 4653, 3714 and 6061 genes were down-regulated in TB, TAB and LAB, respectively. A significant number of transcription fac- tors were also detected as differentially expressing, A heatmap showing the stage-specific expression of genes in chrysanthemum axillary buds is shown in Fig. 3c. Ahmad et al. BMC Plant Biology (2020) 20:145 Page 6 of 15 Fig. 3 Preferential expression of genes during bud outgrowth at 25 °C and 35 °C. a Bar graph depicting the number of commonly expressed genes. b Bar graph showing the preferentially expressed genes at 25 °C and 35 °C. c Heatmap showing the preferentially expressed gene expression at 25 °C and 35 °C for each bud position. d Gene ontology (GO) enrichment (biological process) at 25 °C and 35 °C for each bud position Fig. 3 Preferential expression of genes during bud outgrowth at 25 °C and 35 °C. a Bar graph depicting the number of commonly expressed genes. b Bar graph showing the preferentially expressed genes at 25 °C and 35 °C. c Heatmap showing the preferentially expressed gene expression at 25 °C and 35 °C for each bud position. d Gene ontology (GO) enrichment (biological process) at 25 °C and 35 °C for each bud position Fig. 3 Preferential expression of genes during bud outgrowth at 25 °C and 35 °C. a Bar graph depicting the number of commonly expressed genes. b Bar graph showing the preferentially expressed genes at 25 °C and 35 °C. c Heatmap showing the preferentially expressed gene expression at 25 °C and 35 °C for each bud position. d Gene ontology (GO) enrichment (biological process) at 25 °C and 35 °C for each bud position including 2244, 2191 and 2140 up-regulated TFs in TB, TAB and LAB, respectively; and 2857, 2427 and 3949 down-regulated TFs in TB, TAB and LAB, respectively (Fig. 4a). Top axillary position offers the nascent buds appearing under different temperatures; therefore, focus- ing on the TABs can give a better idea about the effect of high temperature. TFs were specifically analyzed for this stage (Fig. 4b). Plenty of TF families exhibited differ- ential expression in TAB, suggesting diverse functions during bud outgrowth (Fig. 4b). Major TF families in- clude, ARF, B3, ERF, GRAS, MIKC_MADS, MYB, NAC, WRK and TCP. Differentially expressed gene sets between 25 °C and 35 °C at different bud positions a The number of up-regulated and down-regulated DEGs at each bud position, including genes and transcriptional factors. b The number of genes representing different transcriptional families in TAB. c Gene ontology enrichment (biological process), showing up- and down-regulated genes at different temperatures for TB, TAB and LAB. d Metabolic pathways in association with differential expression in TAB at different temperatures. Blue color represents higher expression and the red color shows lower expression Fig. 4 DEGs at 25 °C and 35 °C. a The number of up-regulated and down-regulated DEGs at each bud position, including genes and transcriptional factors. b The number of genes representing different transcriptional families in TAB. c Gene ontology enrichment (biological process), showing up- and down-regulated genes at different temperatures for TB, TAB and LAB. d Metabolic pathways in association with differential expression in TAB at different temperatures. Blue color represents higher expression and the red color shows lower expression normal temperature regime as compared to high temperature (Fig. 5c). activity of the genes responsible for starch biosynthesis, especially the sucrose metabolism. Moreover, hormonal pathways were also evident in the temperature responses in TAB, including the signalling for auxin, cytokinins and abscisic acid. The genes governing the starch metab- olism and photosynthesis were also active in TAB at high temperature (Fig. 4d). A significant proportion of cell wall related genes expressed at higher levels in nor- mal temperature top axillary buds, suggesting higher cell activity at suitable ambient environment than that of higher temperature, where temperature fluctuations be- yond a normal range can hinder a range of cell activities. The transcriptome analysis also depicted a role played by these hormones in axillary buds at two dif- ferent temperature regimes (Fig. 5a). However, the role of strigolactone and ABA related genes was dif- ferent from those of auxin and cytokinins related genes (Fig. 5d). ABA related genes exhibited quite high expression (a measure of FPKM value) in high temperature samples as compared to normal temperature. Fluctuations at TAB for IAA and CK at high temperature are obvious as compared to normal temperature (Fig. 5; IAA, CK). However, the expres- sion intensity and difference was prominent in top axillary buds which are the most probable sites for receiving high temperature influence. Differentially expressed gene sets between 25 °C and 35 °C at different bud positions Presence of these families point out the involvement of divers activities including, cell differenti- ation (ARF), hormonal signalling pathways (ARF), cyto- kinin signalling (ARR-B). These families showed up- regulation in 35 °C as compared to 25 °C. WRK, the im- portant transcriptional factor family for stress responses, showed significant up-regulation in response to high temperature in TAB. The GO enrichment analysis of DEGs in different bud positions pointed out a number of biological processes uniquely overrepresented at TB, TAB and LAB. Differ- ent terms related to cell division, cell cycle and cell growth were significantly enriched in the genes with ele- vated expressions at TAB. Similarly, GO terms associ- ated with cellular components were also showing high expression at Tab. A wide range of GO terms were evi- dent at all stages of bud outgrowth, including organo- genesis, DNA replication, phosphorylation, hormonal responses, sucrose metabolism, transport, regulation of shoot development, photosynthesis etc. (Fig. 4c). including 2244, 2191 and 2140 up-regulated TFs in TB, TAB and LAB, respectively; and 2857, 2427 and 3949 down-regulated TFs in TB, TAB and LAB, respectively (Fig. 4a). Top axillary position offers the nascent buds appearing under different temperatures; therefore, focus- ing on the TABs can give a better idea about the effect of high temperature. TFs were specifically analyzed for this stage (Fig. 4b). Plenty of TF families exhibited differ- ential expression in TAB, suggesting diverse functions during bud outgrowth (Fig. 4b). Major TF families in- clude, ARF, B3, ERF, GRAS, MIKC_MADS, MYB, NAC, WRK and TCP. Presence of these families point out the involvement of divers activities including, cell differenti- ation (ARF), hormonal signalling pathways (ARF), cyto- kinin signalling (ARR-B). These families showed up- regulation in 35 °C as compared to 25 °C. WRK, the im- portant transcriptional factor family for stress responses, showed significant up-regulation in response to high temperature in TAB. To ascertain the metabolic pathways responsible for bud outgrowth at TAB, the expression profiles of DEGs were overlaid onto the already known metabolic path- ways using MapMan tool (Fig. 4d). Differential activity was observed about certain metabolic pathways at TAB under contrasting temperatures. Considerable differ- ences were seen, under both the temperatures, in the Ahmad et al. BMC Plant Biology (2020) 20:145 Page 7 of 15 Fig. 4 DEGs at 25 °C and 35 °C. Differentially expressed gene sets between 25 °C and 35 °C at different bud positions Significantly high expression intensities of ABA related genes are obvious at top axillary buds, showing that high temperature reception was negatively expressed at top axillary sites to restrict bud outgrowth. However, the differences are considerable at other bud positions, including top buds and lower axillary buds. High ABA concentration at TB and TAB at high temperature suggests thermal regulation of bud through ABA (Fig. 5ABA). Hormonal networks are also involved in temperature sensing for bud kinetics A number of genes were identified involving in auxin biosynthesis and signalling with significant dif- ferent set of expressions at 25 °C and 35 °C (Fig. 5b). Some of the candidate genes already known for auxin control have also been mined through sequen- cing data, including PIN, IAA, YUCCA, SKP2A and CUL1. Most of the genes are showing high expres- sion in 25 °C as compared to 35 °C. Similar results can be seen in the case of cytokinins wherein most of the genes exhibited high expression values in Ahmad et al. BMC Plant Biology (2020) 20:145 Page 8 of 15 Fig. 5 Hormonal concentrations [IAA (indole acetic acid), ABA (abscisic acid), CK (cytokinins), GA (gibberellic acid), JA (jasmonic acid) and Sa (salicylic acid)], and DEGs related to hormonal control of buds, including top buds, top axillary buds and lower axillary buds. a Mapman based identification of DEG groups involving different hormones, including auxins, cytokinins, abscisic acid (ABA). b Gene expression values (FPKM based) for auxin related genes at 25 °C and 35 °C. c Gene expression values (FPKM based) for cytokinins related genes at 25 °C and 35 °C. d Gene expression values (FPKM based) for ABA related genes at 25 °C and 35 °C. e Gene expression values (FPKM based) for strigolactone related genes at 25 °C and 35 °C. Data are shown as mean ± SE of three biological replicates. Asterisks on specific terms show significant differences between the treatment conditions 25 °C and 35 °C for each bud position at p < 0.05() and p < 0.01(*) level Fig. 5 Hormonal concentrations [IAA (indole acetic acid), ABA (abscisic acid), CK (cytokinins), GA (gibberellic acid), JA (jasmonic acid) and Sa (salicylic acid)], and DEGs related to hormonal control of buds, including top buds, top axillary buds and lower axillary buds. a Mapman based identification of DEG groups involving different hormones, including auxins, cytokinins, abscisic acid (ABA). b Gene expression values (FPKM based) for auxin related genes at 25 °C and 35 °C. c Gene expression values (FPKM based) for cytokinins related genes at 25 °C and 35 °C. d Gene expression values (FPKM based) for ABA related genes at 25 °C and 35 °C. e Gene expression values (FPKM based) for strigolactone related genes at 25 °C and 35 °C. Data are shown as mean ± SE of three biological replicates. Hormonal networks are also involved in temperature sensing for bud kinetics Asterisks on specific terms show significant differences between the treatment conditions 25 °C and 35 °C for each bud position at p < 0.05() and p < 0.01(*) level Fig. 5 Hormonal concentrations [IAA (indole acetic acid), ABA (abscisic acid), CK (cytokinins), GA (gibberellic acid), JA (jasmonic acid) and Sa (salicylic acid)], and DEGs related to hormonal control of buds, including top buds, top axillary buds and lower axillary buds. a Mapman based identification of DEG groups involving different hormones, including auxins, cytokinins, abscisic acid (ABA). b Gene expression values (FPKM based) for auxin related genes at 25 °C and 35 °C. c Gene expression values (FPKM based) for cytokinins related genes at 25 °C and 35 °C. d Gene expression values (FPKM based) for ABA related genes at 25 °C and 35 °C. e Gene expression values (FPKM based) for strigolactone related genes at 25 °C and 35 °C. Data are shown as mean ± SE of three biological replicates. Asterisks on specific terms show significant differences between the treatment conditions 25 °C and 35 °C for each bud position at p < 0.05() and p < 0.01(**) level Page 9 of 15 Page 9 of 15 Ahmad et al. BMC Plant Biology (2020) 20:145 Ahmad et al. BMC Plant Biology (2020) 20:145 exhibited strong responses for bud length, including MEdarkorchid3, MEantiquewhite1, MEgreen2, MEr- oyalblue 1, MEtan3 and MEdarkgoldenrod (Fig. 6). However, the rate of photosynthesis and the leaf area were only prominent in MEroyalblue 1 and MEdar- korchid3, respectively. In the case of sucrose, high expression modules included MEdarkorchid3, MEan- tiquewhite1, MErosybrown3 and MEgreen2, suggest- ing the involvement of sugar homeostasis in bud kinetics. Some genes were found related to strigolactone (Fig. 5e). The difference was not very significant between two temperatures. However, relatively high gene expression was seen in two candidate genes (D27 and MAX2) at 35 °C as compared to 25 °C. Discussion Temperature elevation beyond a certain limit nega- tively affects plant growth by delaying growth and sev- eral gene units can be involved [42]. For example, temperature stress can disturb the nutrient balance, hor- monal and metabolic homeostasis in plants [50, 51], thereby impacting the regulatory machinery behind bud outgrowth. Temperature change modifies the hormonal levels inside the plant body [52]. ARFs are the transcrip- tional factors that control the expression of genes in- duced by auxin through their binding to ARPs (auxin- responsive promoters) [53]. The molecular regulation for the axillary bud outgrowth is poorly defined in chrysanthemum while the success of cut chrysanthemum solely depends on the vigor of single stalk devoid of axillary branches. However, so far, the ef- forts to nullify branching have not yet been successful due to unavailability of a profound regulatory network to knock out. We used leaf morpho-physiological indica- tors and RNA-seq approach from axillary buds to ascer- tain the transcriptome dynamics at three bud positions influenced by contrasting temperature regimes. A con- siderable proportion of chrysanthemum genes were shown to be expressed in at least one of the bud posi- tions. High throughput RNA-Seq facilitated the mining of new genes with differential expression profiles. The expression information around the three bud positions exhibited significant reproducibility at two temperatures and each bud position was distinguished from the other in the principal component analysis, suggesting promin- ent gene expression changes among bud stages. The comprehensive analysis of transcriptome data along with coexpression networks pointed out a number of specific and coregulated transcriptional plans associated with dif- ferent bud outgrowth stages. Moreover, sucrose, hormo- nal contents and the morpho-physiological indicators from leaf also strengthened the deep impact of temperature on the axillary bud sites. p p Researchers have shown that bud outgrowth status is controlled by numerous factors, including mainly the growth promoters such as sugars, cytokinins and inhibi- tors like auxin, ABA and strigolactone [11, 12, 54–58]. Relatively high amounts of ABA at top buds and top ax- illary buds suggest high temperature control of axillary buds by ABA (Fig. 5). However, higher IAA concentra- tions at TAB and LAB at 35 °C point more movement of auxin from top buds towards lower bud positions as compared to normal temperature (Fig. 5). Discussion Through de- cades of research, a group of genes expressing in sor- ghum buds (i.e., GT1/BRC1/TB1/MAX2) has been identified to repress bud outgrowth until environmental cues, cytokinins and sugar signaling are permissible for axillary bud outgrowth [2]. Strigolactones are the key controllers of axillary shoots that unite to DAD2/MAX2: D14 complex and work through GT1/BRCI/TB1 path- way [12]. MAX2 inhibits bud outgrowth through encod- ing an F-box protein [13, 14]. RwMAX, from rose, was downregulated by sucrose supplies [11]. In stem, the level of cytokinins is degraded by auxin-induced down- regulation of cytokinins biosynthesis gene, whereas abscisic acid (ABA) expresses an auxin-independent in- hibition of bud outgrowth [17, 54, 59]. In our study, high expression of MAX2 at TAB at 35 °C shows strigolactone-mediated inhibition of axillary sites by high temperature (Fig. 5e). In the temperate zone, the bud burst is caused mainly by temperature [37, 38]. The tillering extent can affect leaf area, plant density and the light interception [2]. In our study, leaf area was narrowed down by high temperature (Fig. 1). Bud development starts with the initiation of meristem [12] and then at a certain transi- tion stage, the outgrowth fate is driven by intrinsic and extrinsic factors [39, 40]. A plant may be unable to de- velop an axillary growth due to malformation of meri- stem or outgrowth inhibition of axillary buds [41]. Environmental fluctuations may trigger differential expression of certain miRNAs to compete with stress conditions [42]. Some of miRNAs have been identified in plants related to stress, including drought [43], nu- trient deficiency [44], heat [45] and cold [46]. Most of the plants can adjust their biochemical and physio- logical processes by fluctuating proline contents, MDA, hydrogen peroxide and sucrose contents to manage temperature variations [47, 48]. Interesting fluctuations were observed in ROS and antioxidant species in leaves at 35 °C as compared to 25 °C. How- ever, most of them showed high values in lower bud leaves as compared to top bud leaves in normal temperature. The chloroplast is a potent sensor for stress responses and environmental changes [49]. Slight movement of chloroplast can be seen in leaves under 35 °C (Fig. 2g, h). The differential increase in bud length at different po- sitions suggested the differential role of two tempera- tures in cell division. Identification of coexpressed gene modules for selected morphological leaf and bud traits To understand the gene regulatory networks during bud outgrowth, we performed weighted gene co- expression network analysis (WGCNA) in association with leaf characteristics (leaf area and photosynthetic rate) and bud characteristics (bud length and sucrose concentration) (Fig. 6). The genes showing a FPKM ≥1 were considered for this analysis due to large amount of data. A total of 24 modules were ob- served for bud outgrowth at contrasting tempera- tures (Fig. 6). Among these modules, MEdarkorchid3 was the most prominent in representing highly up- regulated genes involved in leaf area and bud- sucrose and length manipulations. Some modules Hub genes were identified using Cytoscape for MEantiquewhite1 (trpC and GRR1) (supplementary Fig. 3) and MEGreen2 (UBC12 and CYP17) (supple- mentary Fig. 4). All bud positions showed difference for these hub genes at different temperatures. How- ever, the significant differences can be seen at lower axillary buds (supplementary Fig. 5). The trpC plays role in cell wall synthesis and the GRR1 works in auxin biosynthetic pathway. UBC12 acts as an en- zyme in auxin biosynthetic pathways and the CYP17 plays a role in steroid hormone biosynthesis. Fig. 6 Coexpression network analysis during axillary bud outgrowth in association with leaf (leaf area, photosynthesis) and bud (sucrose, bud length) attributes Fig. 6 Coexpression network analysis during axillary bud outgrowth in association with leaf (leaf area, photosynthesis) and bud (sucrose, bud length) attributes Page 10 of 15 Ahmad et al. BMC Plant Biology (2020) 20:145 Ahmad et al. BMC Plant Biology (2020) 20:145 Sampling procedure After 11 days of growth in contrasting temperatures, the sampling was performed from top buds (TB), top axillary buds (TAB) and lower axillary buds (LAB). The sam- pling portion was the rectangular stem portion including the axillary bud (Fig. 1). The leaves around the top bud were regarded as the top bud leaves (TBL) and those around top and lower axillary buds as middle bud leaves (MBL) and lower bud leaves (LBL), respectively. Leaf samples were also collected along with bud samples for physiological indices. Single repeat included sampling from 15 plants, containing 15 TBs, 45 TABs and 45 LABs. Thus, three repeats were collected from 45 plants in each temperature regime. Sampling was done in three biological repeats. Samples were collected in liquid Discussion The gene ontology enrichment analysis shows high rate (higher FPKM) of cell cycle and cell division in normal temperature especially at TAB. The extended mitosis can be seen at normal temperature. High mitotic activity causes higher gluco- neogenesis, resulting in increased seed size [60]. We noted considerable transcriptional activity of genes for cell growth, cell cycle, heat stress and GO enrichment, showing significant differences at both the temperatures (Fig. 4). Moreover, several genes related to cell expan- sion, storage compounds and fatty acid biosynthesis shown higher transcriptional activity for normal temperature (Fig. 4c). A number of TF families are stud- ied to be involved in organ development [61–63]; Page 11 of 15 Page 11 of 15 Ahmad et al. BMC Plant Biology (2020) 20:145 however, a few of them are considered to be involved in temperature-induced bud outgrowth. Our study found plenty of TFs to be involved in differential bud out- growth at contrasting temperatures, especially at TABs. Some known TF families were shown among the differ- entially expressing TFs; however, the exact function is still unclear for most of these genes. Some known TF families, for example NAC, ARF and WRKY, which expressed differently at two temperature regimes, are well established in their role in organ development [7, 61–64]. Differential expression intensities of same family members at different bud positions and different tem- peratures may involve different regulatory pathways, thereby determining position-specific bud development. To get better understanding of this, we used coexpres- sion network analysis to mine unique and common gene groups associated with bud outgrowth at contrasting temperatures. provided the evidence that different bud positions exhib- ited relative susceptibility towards temperature changes, especially the top axillary buds showed distinguished re- sponse for high temperature in chrysanthemum. Our re- sults showed that photosynthetic leaf area, physiological indicators, hormonal fluctuations and sucrose utilization are significantly changed, indicating that they were in- volved in inhibiting the axillary bud outgrowth by high temperature. Transcriptomic comparison revealed amount of bud position-specific expression gene sets. Using WGCNA, we identified important modules highly associated with morphological leaf and bud traits. Our results provide helpful information for elucidating the regulatory mechanism of temperature on axillary bud growth in chrysanthemum. Plant material and growth conditions Ascertaining the transcription modules can disclose gene regulatory networks governing biological processes linked with bud and seed development [2, 7, 42, 65]. Therefore, we created transcription modules (by con- necting transcriptional factors with their respective bind- ing motifs and coexpressed target genes) for top axillary buds which are considered to be the crucial bud out- growth stage to study temperature influence. Although an extensive overlap was observed for TAB at 25 °C and 35 °C, there were several components pertinent to a spe- cific transcriptional accumulation, suggesting uniqueness of the transcription modules for each temperature re- gime. The modules with opposite expression genes were mainly concerned with cell cycle, growth, cell size, his- tone modification and energy. Several components of these modules have previously been implicated in differ- ent aspects of bud and seed development [2, 65–70]. Thus, our study demonstrated that transcriptional mod- ule construction along with coexpression networks can do a great deal to comprehend the inherent mechanism governing agronomic traits of bud outgrowth. However, further studies about each network member are needed to elucidate the whole diagram of GRNs. Plant material and growth conditions Cuttings of the Chrysanthemum morifolium variety ‘Jinba’ were obtained from the Chrysanthemum Germ- plasm Resource Preserving Nursery (Beijing Forestry University, Beijing, China). Cuttings of uniform length, containing at least two buds were obtained from mother plant and were grown in 50H-Cutting tray Drip trays in the greenhouse of Beijing Forestry University. After 20 days, the seedlings were grown into pots. Two month old seedlings at 15 axillary bud stage were transferred to controlled temperature chambers fitted with uniform light (Philips T8 TLD36/33 cold white tube, 120 μmol m−2 s−1 optical density). One of the chambers was set to day and night temperature of 35/25 °C, respectively, and was regarded as high temperature regime. The other chamber was set to 25/15 °C and was regarded as normal temperature regime. Both the chambers were provided with equal light intensities with a day to night duration of 16/8 h. A total of 45 plants were kept in each of the high and normal temperature chambers. Conclusion The regulation of axillary bud by environmental and hormonal signals is well established; however, their in- herent mechanisms are largely unknown in chrysanthe- mum. Studying high temperature as a vital factor inhibiting but outgrowth provides a much better under- standing of how stooling is controlled during plant growth. In the present study, RNA-Seq data coupled with morpho-physiological integrators from three bud positions at two temperature regimes brings a robust source to understand bud outgrowth status influenced by high temperature in cut chrysanthemum. Our results Page 12 of 15 Page 12 of 15 Ahmad et al. BMC Plant Biology (2020) 20:145 nitrogen and stored at −80 °C until RNA extraction or physiological analyses. Physiological indices Protein, Malondialdehyde contents and the antioxidant enzyme activities were measured following the protocol by Chen and Zhang [74]. Leaf area (cm2) After 11 days of growth under contrasting temperatures, top leaf, top axillary leaf and lower axillary leaf were scanned along with proper scale. Scanned pictures were used to measure leaf area by ImageJ software [71]. Morphological parameters Bud length Bud length (mm) was measured every week using digital Vernier calipers. Wet to dry mass ratio Top bud leaf (TL), middle bud leaf (MBL) and the lower bud leaf (LBL) were selected from 11 days old plants and weighted initially to note the wet weights. The leaves were packed in paper and kept overnight in an incubator set to 65 °C. Crack-dried leaves were weighted again to take the dry weights. Wet to dry ratios were calculated by dividing the wet weight of each leaf to its dry weight. Measurement of sucrose concentration The concentration of sucrose was estimated following the methodology of Yuan et al. [78] with slight modifica- tion. In short, buds were finely ground in liquid nitrogen and extracted three times (at 80 °C) in 80% ethyl alcohol. The pooled supernatants were filtered using carbon black, making a final volume of 25 ml by adding distilled water into filtrate. The reaction mixture contained 100 μl of 2 N NaOH and 900 μl of extract. This solution was boiled at 99 °C in a water bath for 10 min, followed by cooling for 5 min. After that, 1 ml of 0.1% resorcinol and 3 ml of 10 N HCl were added to this reaction mix- ture and heated at 80 °C for 1 h. Absorbance was ob- served at 480 nm using a UV-1700 PharmaSpec spectrophotometer (Shimadzu Corporation, Kyoto, Japan). Sucrose solution of 20 μg/ml was used to obtain a standard curve at a proper correlation coefficient (R2 = 0.998). Paraffin sectioning Stem cuttings containing single axillary buds were ex- cised to see bud activities at micro level. After every 24 h the buds were fixed in FAA (formalin-acetic acid- alcohol) containing 70% ethanol, 37% formaldehyde acetic acid at a ratio of 18:1:1. Buds were then dehy- drated using butyl alcohol series and embedded in paraf- fin. Embedded samples were cut into 10 μm thick strips using rotary microtone and then placed on microscopic slides. Slides were kept overnight at 40 °C and stained in Safranin-O and fast-green staining series (Kebrom and Mullet, 2015) and were mounted using few drops of Per- mount medium (Fisher Scientific, Waltham, MA, USA). The slides were covered with cover glass and observed using a bright-field microscope. Transmission electron microscopy Top axillary leaf mesophyll cells were anatomically ana- lyzed using transmission electron microscopy [76, 77]. 2 mm2 leaf sections were cut parallel to the midrib and immersed in 2.5% (v/v) glutaraldehyde solution. The so- lution was then replaced with fresh fixative. After proper washing, the samples were fixed in 1% OsO4 (w/v) with K3Fe(CN)6 in 0.1 M Sodium carbohydrate buffer. Succes- sive ethanol series were run to dry the samples (includ- ing staining with 2% uranyl acetate at 50% ethanol step), followed by embedding in Spurr’s resin. Extremely thin sections were cut using an ultramicrotome (Leica EM UC6). These sections were further stained with uranyl acetate and lead citrate. Sections were finally viewed with a high definition transmission electron microscope (Tecnai 12, Philips, The Netherlands). Gas exchange and photosynthetic pigments Net rate of photosynthesis (Pn), water conductance (Cw), intercellular CO2 concentration (Ci) and transpir- ation rate (E) were measured using a portable measuring system (Ecotek, China). The environmental parameters were: leaf temperature 25 °C, relative air humidity 80%, 1200 μmol m−2 s−1 photosynthetic photon flux density (PPFD) and 400 ± 5 μmol mol−1 of ambient CO2 concentration. Chlorophyll pigments were measured using the method of Zhang [72] with little modification. Briefly, 1 g of leaf sample was homogenized in 80% (v/v) acetone solution, followed by centrifugation at 10,000 g for 10 min at 4 °C. The supernatant was collected to measure absorbance at 663, 645 and 470 nm to measure chloro- phyll a (Chl a), chlorophyll b (Chl b), carotenoids (Caro), and total chlorophyll (Chl) considering the calculations by Lichtenthaler [73]. Analysis of hormones between all gene pairs was produced, followed by trans- formation into an adjacency matrix using the following formula: adjacency value = \|(1 + correlation)/2\|β. β shows soft threshold value for the correlation matrix, giving el- evated weight to the strongest correlations while reserv- ing inter-gene connectivity. A β magnitude of 12 was chosen on the basis of scale-free criterion for topology described previously [7, 82]. Adjacency matrix, thus ob- tained, was changed to a TO (topology overlap) matrix through TOM similarity algorithm, followed by hier- archical clustering of genes on the basis of TO similarity. Hierarchical clustering dendrogram was cut via dynamic tree-cutting algorithm and the modules were defined by combining the branches to a stable number of clusters [83]. A summary profile called module eigengene (ME) was calculated for each module using PCA. Those mod- ules were retained with higher TO value as compared to the TO values of randomly selected gene modules. GO enrichment analysis was performed for each module. Major hormones related to bud outgrowth were analysed with HPLC-MS/MS (Aglient) as described by Pan et al. [79]. RNA-seq library preparation and sequencing Total RNA was extracted from frozen buds using Mini- BESTplant RNA extraction kit (TaKaRa) including DNA removal as well, finally obtaining DNA-free RNA. All the 18 libraries (6 samples in three biological replicates) were sequenced on Illumina platform (HiSeq 2000) to produce paired-end sequence reads of 150-nucleotide long. The raw data were analyzed to understand various parameters and the high-quality reads were sorted with NGS QC Toolkit (v2.3). The quality reads were mapped on the Chrysanthemum nankingense genome [1] using TopHat (v2.0.0) with default parameters. FPKM (frag- ments per kilobase of transcript length per million mapped reads) values were obtained for all the genes in each sample by processing the mapped data through Cufflinks (v2.0.2). Spearman correlation coefficient (SCC) was applied to determine the correlation between the biological repeats. Principal component analysis (PCA) and hierarchical clustering were executed using prcomp and corrplot utilities of R package [7]. Differen- tial expression was ascertained between the samples using Cuffdiff and the genes showing at least twofold difference in expression with a corrected P-value (q- value) of < 0.05 after the adjustment of false discovery rate. Stage specificity (SS) scoring algorithm was used to identify preferentially expressed/stage-specific genes. SS scoring algorithm identifies stage-specific gene by com- paring the expression of that genes in a specific stage with its maximum expression value in other stages as ex- plained in previous researches [7, 80]. Higher the SS score of gene in a given stage more significant is the ex- pression of that gene at that stage. A selected set of genes was used to generate heatmap using pheatmap and ggplot2 utilities of R. Statistical analysis The data was analysed using One-way ANOVA in SPSS software (SPSS Inc., Chicago, IL, USA; ver. 16.0). Signifi- cant variations are indicated at p < 0.05 or p < 0.01 level. Acknowledgments We are thankful to Nadia Sucha (Kingston University London) for suggesting professional native English speaker for our manuscript. We are also thankful to Xie Jianbo (Beijing Forestry University) for providing help in analyzing RNA-seq data for our manuscript. Weighted gene coexpression network analysis For the construction of coexpression modules, the WGCAN packages were used [82, 83]. Using log2 (1 + FPKM) values, a matrix containing pairwise SCCs Weighted gene coexpression network analysis Stomatal density Stomatal density was measured following the proced- ure described by Hopper et al. [71]. Stomatal density was ascertained using ImajeJ (National Institutes of Health, Bethesda, MD, USA) applying the plug-in of cell counter [75]. Page 13 of 15 Ahmad et al. BMC Plant Biology (2020) 20:145 Ahmad et al. BMC Plant Biology (2020) 20:145 Supplementary information pp y Supplementary information 1186/s12870-020-02336-0. y Supplementary information accompanies this paper at https://doi.org/10. 1186/s12870-020-02336-0. Additional file 1: Figure S1. Bud length and bud morphology at different plant heights. Figure S2. Correlation between the transcriptomes of different bud positions. Figure S3. Candidate gene selection for Antiquewhite1. Figure S4. Candidate gene selection for Green2. Figure S5. FPKM values of selective candidate genes from ‘Antiquewhite1’ (tprC, GRR1) and ‘Green2’ (UBC12, CYP17) modules of bud length. Table S1. FPKM based grouping of mapped reads. Additional file 1: Figure S1. Bud length and bud morphology at different plant heights. Figure S2. Correlation between the transcriptomes of different bud positions. Figure S3. Candidate gene selection for Antiquewhite1. Figure S4. Candidate gene selection for Green2. Figure S5. FPKM values of selective candidate genes from ‘Antiquewhite1’ (tprC, GRR1) and ‘Green2’ (UBC12, CYP17) modules of bud length. Table S1. FPKM based grouping of mapped reads. Abbreviations ABA: Abscisic acid; Caro: Carotenoids; CAT: Catalase; Chl: Total chlorophyll; Chl a: Chlorophyll a; Chl b: Chlorophyll b; Ci: Intercellular CO2 concentration; CK: Cytokinins; Cw: Water conductance; DEGs: Differentially expressed genes; FAA: Formalin-acetic acid-alcohol; FPKM: Fragments Per Kilobase of transcript per Million mapped reads; GO: Gene ontology; IAA: Indole-3-acetic acid; MDA: Malondialdehyde; PCA: Principal component analysis; PIN: Pin-formed; Pn: Net rate of photosynthesis; POD: Peroxidase; PPFD: Photosynthetic photon flux density; ROS: Reactive oxygen species; SOD: Superoxide dismutase; TB: Top buds; TAB: Top axillary buds; LAB: Lower axillary buds; TFs: Transcription factors; TBL: Top bud leaf; MBL: Middle bud leaf; LBL: Lower bud leaf; WGCNA: Weighted Gene Co-expression Network Analysis Gene ontology and pathway enrichment analysis GO enrichment analysis was performed for DEGs using BINGO plug-in of Cytoscape [7, 81]. For each GO term, the P-value was calculate and corrected using the error correction method by Benjamini Hoschberg [7]. The GO terms with q-value of ≤0.05 were regarded as signifi- cantly enriched. MapMan (v3.6.0RC1) was used to gen- erate pathway enrichment analysis of different gene sets with the best Arabidopsis (TAIR10) homolog. References 1. Song C, Liu Y, Song A, Dong G, Zhao H, Sun W, Ramakrishnan S, Wang Y, Wang S, Li T. The Chrysanthemum nankingense genome provides insights into the evolution and diversification of chrysanthemum flowers and medicinal traits. Mol Plant. 2018. 25. Kelliher T, Egger RL, Zhang H, Walbot V. Unresolved issues in pre-meiotic anther development. Front Plant Sci. 2014;5:347. 26. Asada K. The water-water cycle in chloroplasts: scavenging of active oxygens and dissipation of excess photons. Annu Rev Plant Biol. 1999;50(1):601–39. 2. Kebrom TH, Mullet JE. Transcriptome profiling of tiller buds provides new insights into phyB regulation of tillering and indeterminate growth in Sorghum. Plant Physiol. 2016;170(4):2232–50. 27. Ahmad P, Jaleel CA, Salem MA, Nabi G, Sharma S. Roles of enzymatic and nonenzymatic antioxidants in plants during abiotic stress. Crit Rev Biotechnol. 2010;30(3):161–75. 3. Leeggangers H, Nijveen H, Bigas JN, Hilhorst HW, Immink RG: Molecular regulation of temperature-dependent floral induction in Tulipa gesneriana. Plant Physiol 2017:pp. 01758.02016. 28. Ahmad P, Nabi G, Jeleel C, Umar S: Free radical production, oxidative damage and antioxidant defense mechanisms in plants under abiotic stress. Oxidative stress: role of antioxidants in plants Studium Press, New Delhi 2011:19–53. 4. Bhandawat A, Singh G, Seth R, Singh P, Sharma RK. Genome-wide transcriptional profiling to elucidate key candidates involved in bud burst and rattling growth in a subtropical bamboo (Dendrocalamus hamiltonii). Front Plant Sci. 2017;7:2038. 29. Hodges DM, DeLong JM, Forney CF, Prange RK. Improving the thiobarbituric acid-reactive-substances assay for estimating lipid peroxidation in plant tissues containing anthocyanin and other interfering compounds. Planta. 1999;207(4):604–11. 5. Fan Z, Li J, Li X, Wu B, Wang J, Liu Z, Yin H. Genome-wide transcriptome profiling provides insights into floral bud development of summer- flowering Camellia azalea. Sci Rep. 2015;5:9729. 30. Koyro H-W, Ahmad P, Geissler N: Abiotic stress responses in plants: an overview. In: Environmental adaptations and stress tolerance of plants in the era of climate change. Springer; 2012: 1–28. 6. Ni J, Zhao M-L, Chen M-S, Pan B-Z, Tao Y-B, Xu Z-F. Comparative transcriptome analysis of axillary buds in response to the shoot branching regulators gibberellin A3 and 6-benzyladenine in Jatropha curcas. Sci Rep. 2017;7(1):11417. 6. Ni J, Zhao M-L, Chen M-S, Pan B-Z, Tao Y-B, Xu Z-F. Comparative transcriptome analysis of axillary buds in response to the shoot branching regulators gibberellin A3 and 6-benzyladenine in Jatropha curcas. Sci Rep. 2017;7(1):11417. 31. Funding 15. Crawford S, Shinohara N, Sieberer T, Williamson L, George G, Hepworth J, Müller D, Domagalska MA, Leyser O: Strigolactones enhance competition between shoot branches by dampening auxin transport. Development 2010:dev. 051987. g This work was supported by the Fundamental Research Funds for the National Natural Science Foundation of China (No. 31700621) and Special Fund for Beijing Common Construction Project. Funding bodies were not involved in the design of the study and data collection, analysis, and interpretation of data and in writing the manuscript. 16. Domagalska MA, Leyser O. Signal integration in the control of shoot branching. Nat Rev Mol Cell Biol. 2011;12(4):211. 17. Chatfield SP, Stirnberg P, Forde BG, Leyser O. The hormonal regulation of axillary bud growth in Arabidopsis. Plant J. 2000;24(2):159–69. References Liu W, Yu K, He T, Li F, Zhang D, Liu J. The low temperature induced physiological responses of Avena nuda L., a cold-tolerant plant species. Sci World J. 2013;2013:7. 7. Garg R, Singh VK, Rajkumar MS, Kumar V, Jain M. Global transcriptome and coexpression network analyses reveal cultivar-specific molecular signatures associated with seed development and seed size/weight determination in chickpea. Plant J. 2017;91(6):1088–107. 32. Kochhar S, Watkins CB, Conklin PL, Brown SK. A quantitative and qualitative analysis of antioxidant enzymes in relation to susceptibility of apples to superficial scald. J Am Soc Hortic Sci. 2003;128(6):910–6. 33. Hall CR, Dickson MW. Economic, environmental, and health/well-being benefits associated with green industry products and services: a review. J Environ Hortic. 2011;29(2):96–103. 8. Porto DD, Bruneau M, Perini P, Anzanello R, Renou J-P, HPd S, Fialho FB. revers LF: transcription profiling of the chilling requirement for bud break in apples: a putative role for FLC-like genes. J Exp Bot. 2015;66(9):2659–72. 34. Teixeira da Silva J. Tissue culture and cryopreservation of chrysanthemum: a review. Biotechnol Adv. 2003;21:715–66. 9. Rabot A, Henry C, Ben Baaziz K, Mortreau E, Azri W, Lothier J, Hamama L, Boummaza R, Leduc N, Pelleschi-Travier S. Insight into the role of sugars in bud burst under light in the rose. Plant Cell Physiol. 2012;53(6):1068–82. 35. Savicka M, Škute N. Effects of high temperature on malondialdehyde content, superoxide production and growth changes in wheat seedlings (Triticum aestivum L.). Ekologija. 2010;56(1):26–33. 10. Mason MG, Ross JJ, Babst BA, Wienclaw BN, Beveridge CA. Sugar demand, not auxin, is the initial regulator of apical dominance. Proc Natl Acad Sci. 2014;111(16):6092–7. 36. Kebrom TH, Mullet JE. Photosynthetic leaf area modulates tiller bud outgrowth in sorghum. Plant Cell Environ. 2015;38(8):1471–8. 11. Barbier FF, Lunn JE, Beveridge CA. Ready, steady, go! A sugar hit starts the race to shoot branching. Curr Opin Plant Biol. 2015;25:39–45. 37. Chuine I. A unified model for budburst of trees. J Theor Biol. 2000;207(3): 337–47. 12. Janssen BJ, Drummond RS, Snowden KC. Regulation of axillary shoot development. Curr Opin Plant Biol. 2014;17:28–35. 38. Kramer K, Leinonen I, Loustau D. The importance of phenology for the evaluation of impact of climate change on growth of boreal, temperate and Mediterranean forests ecosystems: an overview. Int J Biometeorol. 2000; 44(2):67–75. 13. Stirnberg P, Furner IJ, Ottoline Leyser H. MAX2 participates in an SCF complex which acts locally at the node to suppress shoot branching. Plant J. Competing interests 23. Endo M, Tsuchiya T, Hamada K, Kawamura S, Yano K, Ohshima M, Higashitani A, Watanabe M, Kawagishi-Kobayashi M. High temperatures cause male sterility in rice plants with transcriptional alterations during pollen development. Plant Cell Physiol. 2009;50(11):1911–22. The authors declare that they have no competing interest. The authors declare that they have no competing interest. Received: 13 November 2019 Accepted: 9 March 2020 Received: 13 November 2019 Accepted: 9 March 2020 Received: 13 November 2019 Accepted: 9 March 2020 24. Zhang X, Li J, Liu A, Zou J, Zhou X, Xiang J, Rerksiri W, Peng Y, Xiong X, Chen X. Expression profile in rice panicle: insights into heat response mechanism at reproductive stage. PLoS One. 2012;7(11):e49652. Consent for publication Consent for publication Not applicable. PQ. Physiological and proteomic approaches to address heat tolerance during anthesis in rice (Oryza sativa L.). J Exp Bot. 2009;61(1):143–56. 22. Matsui T, Omasa K. Rice (Oryza sativa L.) cultivars tolerant to high temperature at flowering: anther characteristics. Ann Bot. 2002;89(6):683–7. 22. Matsui T, Omasa K. Rice (Oryza sativa L.) cultivars tolerant to high temperature at flowering: anther characteristics. Ann Bot. 2002;89(6):683–7. Authors’ contributions SA, CY and QZ designed the experiments; SA, CY, YY and QY performed the experiments. SA wrote the manuscript; CY revised the manuscript. SA, CY, TC, JW and HP analyzed the data. All authors read and approved the final manuscript. Page 14 of 15 Page 14 of 15 Page 14 of 15 Ahmad et al. BMC Plant Biology (2020) 20:145 Ahmad et al. BMC Plant Biology (2020) 20:145 Ahmad et al. BMC Plant Biology Availability of data and materials 18. Faust JE, Heins RD. High night temperatures do not cause poor lateral branching of chrysanthemum. Hort Science. 1992;27(9):981–2. The data sets are included within the article and its Additional files. The raw sequence data reported in this paper have been deposited in the NCBI under the BioProgect ID PRJNA608820. The raw sequence data are also available in the Genome Sequence Archive in BIG Data Center, Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, under accession numbers CRA002314. 19. Yang J, Chen X, Zhu C, Peng X, He X, Fu J, Ouyang L, Bian J, Hu L, Sun X. RNA-seq reveals differentially expressed genes of rice (Oryza sativa) spikelet in response to temperature interacting with nitrogen at meiosis stage. BMC Genomics. 2015;16(1):959. 20. Prasad P, Boote K, Allen L Jr, Sheehy J, Thomas J. Species, ecotype and cultivar differences in spikelet fertility and harvest index of rice in response to high temperature stress. Field Crop Res. 2006;95(2–3):398–411. Ethics approval and consent to participate Not applicable. 21. Jagadish S, Muthurajan R, Oane R, Wheeler TR, Heuer S, Bennett J, Craufurd PQ. Physiological and proteomic approaches to address heat tolerance during anthesis in rice (Oryza sativa L.). J Exp Bot. 2009;61(1):143–56. References Van Dingenen J, De Milde L, Vermeersch M, Maleux K, De Rycke RM, De Bruyne M, Storme V, Gonzalez N, Dhondt S, Inzé D: Chloroplasts are central players in sugar-induced leaf growth. Plant Physiol 2016:pp. 01669.02015. 54. Beveridge CA, Dun EA, Rameau C. Pea has its tendrils in branching discoveries spanning a century from auxin to strigolactones. Plant Physiol. 2009;151(3):985–90. 78. Yuan C, Ahmad S, Cheng T, Wang J, Pan H, Zhao L, Zhang Q. Red to far-red light ratio modulates hormonal and genetic control of axillary bud outgrowth in Chrysanthemum (Dendranthema grandiflorum ‘Jinba’). Int J Mol Sci. 2018;19(6):1590. 55. Müller D, Leyser O. Auxin, cytokinin and the control of shoot branching. Ann Bot. 2011;107(7):1203–12. 56. Kebrom TH, Spielmeyer W, Finnegan EJ. Grasses provide new insights into regulation of shoot branching. Trends Plant Sci. 2013;18(1):41–8. 79. Pan X, Welti R, Wang X. Quantitative analysis of major plant hormones in crude plant extracts by high-performance liquid chromatography–mass spectrometry. Nat Protoc. 2010;5(6):986. 57. Wang H, Wang H. Phytochrome signaling: time to tighten up the loose ends. Mol Plant. 2015;8(4):540–51. 80. Zhan J, Thakare D, Ma C, Lloyd A, Nixon NM, Arakaki AM, Burnett WJ, Logan KO, Wang D, Wang X: RNA sequencing of laser-capture microdissected compartments of the maize kernel identifies regulatory modules associated with endosperm cell differentiation. The Plant Cell 2015:tpc. 114.135657. 58. Yuan C, Xi L, Kou Y, Zhao Y, Zhao L. Current perspectives on shoot branching regulation. Front Agric Sci Eng. 2015;2(1):38–52. 59. Tanaka M, Takei K, Kojima M, Sakakibara H, Mori H. Auxin controls local cytokinin biosynthesis in the nodal stem in apical dominance. Plant J. 2006; 45(6):1028–36. 81. Maere S, Heymans K, Kuiper M. BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics. 2005;21(16):3448–9. 81. Maere S, Heymans K, Kuiper M. BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics. 2005;21(16):3448–9. 60. Sekhon RS, Hirsch CN, Childs KL, Breitzman MW, Kell P, Duvick S, Spalding EP, Buell CR, de Leon N, Kaeppler SM. Phenotypic and transcriptional analysis of divergently selected maize populations reveals the role of developmental timing in seed size determination. Plant Physiol. 2014;165(2): 658. 82. Zhang B, Horvath S: A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol 2005, 4(1). 83. Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC bioinformatics. 2008;9(1):559. 61. References 2007;50(1):80–94. 14. Stirnberg P, van De Sande K, Leyser HO. MAX1 and MAX2 control shoot lateral branching in Arabidopsis. Development. 2002;129(5):1131–41. 39. Shimizu-Sato S, Mori H. Control of outgrowth and dormancy in axillary buds. Plant Physiol. 2001;127(4):1405–13. Page 15 of 15 Page 15 of 15 Ahmad et al. BMC Plant Biology (2020) 20:145 Ahmad et al. BMC Plant Biology (2020) 20:145 40. Dun EA, Ferguson BJ, Beveridge CA. Apical dominance and shoot branching. Divergent opinions or divergent mechanisms? Plant Physiology. 2006;142(3):812–9. 65. Becker MG, Hsu S-W, Harada JJ, Belmonte MF: Genomic dissection of the seed. Front Plant Sci 2014, 5(464). 66. Belmonte MF, Kirkbride RC, Stone SL, Pelletier JM, Bui AQ, Yeung EC, Hashimoto M, Fei J, Harada CM, Munoz MD, et al. Comprehensive developmental profiles of gene activity in regions and subregions of the Arabidopsis seed. Proc Natl Acad Sci. 2013;110(5):E435–44. 41. Ward SP, Leyser O. Shoot branching. Curr Opin Plant Biol. 2004;7(1):73–8. 42. Wang Q, Liu N, Yang X, Tu L, Zhang X. Small RNA-mediated responses to low- and high-temperature stresses in cotton. Sci Rep. 2016;6:35558. 67. Sreenivasulu N, Wobus U. Seed-development programs: a systems biology– based comparison between dicots and monocots. Annu Rev Plant Biol. 2013;64(1):189–217. 43. Zhou L, Liu Y, Liu Z, Kong D, Duan M, Luo L. Genome-wide identification and analysis of drought-responsive microRNAs in Oryza sativa. J Exp Bot. 2010;61(15):4157–68. 68. Tecza A, Bugner V, Kühl M, Kühl SJ. Pescadillo homologue 1 and Peter Pan function during Xenopus laevis pronephros development. Biol Cell. 2011; 103(10):483–98. 44. Fujii H, Chiou T-J, Lin S-I, Aung K, Zhu J-K. A miRNA involved in phosphate- starvation response in Arabidopsis. Curr Biol. 2005;15(22):2038–43. 45. Xin M, Wang Y, Yao Y, Xie C, Peng H, Ni Z, Sun Q. Diverse set of microRNAs are responsive to powdery mildew infection and heat stress in wheat (Triticum aestivum L.). BMC Plant Biol. 2010;10(1):123. 69. Casaretto JA, El-kereamy A, Zeng B, Stiegelmeyer SM, Chen X, Bi Y-M, Rothstein SJ. Expression of OsMYB55 in maize activates stress-responsive genes and enhances heat and drought tolerance. BMC Genomics. 2016; 17(1):312. 46. Lv D-K, Bai X, Li Y, Ding X-D, Ge Y, Cai H, Ji W, Wu N, Zhu Y-M. Profiling of cold-stress-responsive miRNAs in rice by microarrays. Gene. 2010;459(1–2): 39–47. 70. Williams L, Grigg SP, Xie M, Christensen S, Fletcher JC. References Regulation of Arabidopsis shoot apical meristem and lateral organ formation by microRNA miR166g and its AtHD-ZIP target genes. Development. 2005; 132(16):3657–68. 47. Nahar K, Hasanuzzaman M, Alam M, Fujita M. Exogenous spermidine alleviates low temperature injury in mung bean (Vigna radiata L.) seedlings by modulating ascorbate-glutathione and glyoxalase pathway. Int J Mol Sci. 2015;16(12):30117–32. 71. Hopper DW, Ghan R, Cramer GR. A rapid dehydration leaf assay reveals stomatal response differences in grapevine genotypes. Horticulture Res. 2014;1:2. 48. Peng T, Zhu X, Duan N, LIU JH. P tr BAM 1, a β-amylase-coding gene of P oncirus trifoliata, is a CBF regulon member with function in cold tolerance by modulating soluble sugar levels. Plant Cell Environ. 2014;37(12):2754–67. 72. Zhang S, Jiang H, Peng S, Korpelainen H, Li C. Sex-related differences in morphological, physiological, and ultrastructural responses of Populus cathayana to chilling. J Exp Bot. 2010;62(2):675–86. 49. Fernández AP, Strand Å. Retrograde signaling and plant stress: plastid signals initiate cellular stress responses. Curr Opin Plant Biol. 2008;11(5): 509–13. 73. Lichtenthaler HK: [34] Chlorophylls and carotenoids: pigments of photosynthetic biomembranes. In: Methods in enzymology. vol. 148: Elsevier; 1987: 350–382. 73. Lichtenthaler HK: [34] Chlorophylls and carotenoids: pigments of photosynthetic biomembranes. In: Methods in enzymology. vol. 148: Elsevier; 1987: 350–382. 50. Guy C, Kaplan F, Kopka J, Selbig J, Hincha DK. Metabolomics of temperature stress. Physiol Plant. 2008;132(2):220–35. 74. Chen T, Zhang B: Measurements of proline and malondialdehyde content and antioxidant enzyme activities in leaves of drought stressed cotton. Plant & Cell Physiology 2015. 51. Yamasaki H, Abdel-Ghany SE, Cohu CM, Kobayashi Y, Shikanai T, Pilon M. Regulation of copper homeostasis by micro-RNA in Arabidopsis. J Biol Chem. 2007;282(22):16369–78. 75. Abràmoff MD, Magalhães PJ, Ram SJ. Image processing with ImageJ. Biophoton Int. 2004;11(7):36–42. 52. Achard P, Gong F, Cheminant S, Alioua M, Hedden P, Genschik P. The cold- inducible CBF1 factor–dependent signaling pathway modulates the accumulation of the growth-repressing DELLA proteins via its effect on gibberellin metabolism. Plant Cell. 2008;20(8):2117–29. 76. Ouyang W, Struik PC, Yin X, Yang J. Stomatal conductance, mesophyll conductance, and transpiration efficiency in relation to leaf anatomy in rice and wheat genotypes under drought. J Exp Bot. 2017;68(18):5191–205. 53. Chapman EJ, Estelle M. Mechanism of auxin-regulated gene expression in plants. Annu Rev Genet. 2009;43:265–85. 77. References Le BH, Cheng C, Bui AQ, Wagmaister JA, Henry KF, Pelletier J, Kwong L, Belmonte M, Kirkbride R, Horvath S. Global analysis of gene activity during Arabidopsis seed development and identification of seed-specific transcription factors. Proc Natl Acad Sci. 2010;107(18):8063–70. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. 62. Agarwal P, Kapoor S, Tyagi AK. Transcription factors regulating the progression of monocot and dicot seed development. Bioessays. 2011;33(3): 189–202. 63. Verdier J, Lalanne D, Pelletier S, Torres-Jerez I, Righetti K, Bandyopadhyay K, Leprince O, Chatelain E, Vu BL, Gouzy J. A regulatory network-based approach dissects late maturation processes related to the acquisition of desiccation tolerance and longevity of Medicago truncatula seeds. Plant Physiol. 2013;163(2):757–74. 64. Li N, Li Y. Signaling pathways of seed size control in plants. Curr Opin Plant Biol. 2016;33:23–32.
W4386961136.txt	https://ace.ewapublishing.org/media/c1d2d67cb08045d58856963c4cece8a8.marked_lj4yhsL.pdf	en		HCCI technology using hydrogen energy and artificial intelligence	Applied and computational engineering	2,023	cc-by	4,254	Proceedings of the 2023 International Conference on Mechatronics and Smart Systems DOI: 10.54254/2755-2721/11/20230226 HCCI technology using hydrogen energy and artificial intelligence Yinlong Fu1, †, Erhan Hu2, † and Zongxian Xia3, †, 4 1 Kunming No.8 High School, Kunming, 650000, China Chongqing Nankai Secondary School, Chongqing, 400000, China 3 Nanjing University of Aeronautics and Astronautics, 210016, China † These authors contributed equally. 2 4 182110118@nuaa.edu.cn Abstract. The principle of a HCCI engine is to inject a mixture of fuel and air into the cylinder and allow it to self-ignite under a high compression ratio. Unlike traditional gasoline and diesel engines, the mixture in the HCCI engine is homogeneous and does not require an ignition system to ignite it. The air-fuel mixture in the cylinder is burned completely by compressing. It makes effective use of fuel. The structure is simpler than a conventional internal combustion engine. HCCI engine has a huge application prospect in many fields. Among them, the automobile is one of the biggest parts. However, some applications have not been widely used. Although the HCCI engine has so many advantages, as this study has discussed, many of its drawbacks are still serious, such as the difficulty in controlling the parameters in the combustion and work process, resulting in the theoretical process being difficult to realize fully. The stringent environmental constraints of HCCI engines, the scarcity of suitable fuels and the significantly lower lifetime of HCCI engines than conventional engines pose significant obstacles to their practical use. This study presents the idea of using artificial intelligence system-assisted control system to accurately control HCCI engines in real time, which has shown great potential in HCCI engine misfire detection and HCCI engine initial burn time prediction. Keywords: HCCI technology, hydrogen energy, artificial intelligence, sustainability. 1. Introduction A spray field is a traditional diesel engine composed of liquid fuel, oil droplets, liquid column, oil vapor and air mixed field. The spray field is a very heterogeneous and sensitive thermodynamic system. Conventional diesel engines spontaneously combust through piston compression of the abovementioned spray field, causing its temperature to rise. Incomplete and uneven diesel combustion produces NOx and PM emissions, and this is the problem with conventional diesel engines, where fuel and air in the spray field mix neither quickly nor evenly [1]. NOx is produced in the high-temperature flame zone, and PM is produced in the high-temperature overconcentration zone. Traditional gasoline engines ignite gas through a spark plug, and it is premixed quasi-homogeneous combustion; there is no combustion to produce a lot of harmful gas problems [1]. But at the same time, gasoline engines can only use a small compression ratio to do work, which makes them inefficient. And this efficiency limit is difficult for conventional engines to overcome. Homogeneous charge © 2023 The Authors. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/). 167 Proceedings of the 2023 International Conference on Mechatronics and Smart Systems DOI: 10.54254/2755-2721/11/20230226 compression ignition (HCCI) combines the advantages of both spontaneous and homogeneous combustion compression [1]. HCCI engines avoid locally uneven combustion by igniting a thin, uniform mixture and then distributing the combustion [1]. This method greatly reduces the production and emission of pollutants, such as NOx and PM, while maintaining the engine's efficiency. Therefore, the HCCI engine has great research potential and a broad market. From the fuel point of view, HCCI internal combustion engine can choose more kinds of fuel, and the engine flexibility and adaptability are better; From the perspective of pollutant emission, the emission of HCCI is low, resulting in less environmental pollution and lower environmental governance costs, which is in line with the overall background of the development of green economy in the world [2]. At the same time, HCCI internal combustion engine requires far less precious metal than gasoline and diesel engines, which can greatly reduce costs and has a strong economy [2]. The HCCI internal combustion engine is superior to the traditional internal combustion engine in technology and more in line with sustainable development and ecological protection in the new era, which is worthy of our exploration [2]. In this study, the advantages of the HCCI engine compared with traditional engines are introduced, and the problems encountered in its development are explained, as well as the feasible solutions. 2. The working principle of HCCI engines The principle of an HCCI engine is to inject a mixture of fuel and air into it to self-ignite under a high compression ratio. Unlike traditional gasoline and diesel engines, the mixture in the HCCI engine is homogeneous and does not require an ignition system to ignite it. Instead, the self-ignition of the mixture is achieved by generating enough temperature and pressure through a high compression ratio. Specifically, during the working process of the HCCI engine, both the intake and exhaust valves are closed, and the mixture is compressed, increasing its temperature and pressure until it reaches the selfignition point. Then, the mixture begins to self-ignite, producing high-temperature and high-pressure combustion gas, which pushes the piston down to generate power. Since the combustion is self-ignited, there is no need for spark plugs or injectors to ignite or spray fuel, reducing engine components and costs and improving fuel efficiency. To ensure that the mixture self-ignites appropriately, it is necessary to control parameters such as intake temperature and pressure to control the self-ignition point precisely. At the same time, to avoid premature or delayed self-ignition, the mixture ratio, compression ratio, and intake temperature need to be adjusted. The control and adjustment of these parameters require advanced electronic control systems to ensure engine stability and reliability. In summary, the principle of the HCCI engine is to achieve the combustion process through self-ignition, without the need for an ignition system or fuel injection system, which can achieve higher fuel efficiency and lower exhaust emissions. 3. Unique advantages of HCCI engines in automobile 3.1. Complete burning of the air-fuel mixture by compression Recent research reveals that the combustion method of the HCCI engine has a significant characteristic: the homogenization of mixed gases in the turbine and their exhaustion in low temperatures. Its combusting procedure relies on chemical reactions’ highlights in the mixed gases. Based on the graph, there are two distinguished subdivisions. One is called low-temperature heat release, another is called high-temperature heat release, and the latter subdivision occupies most of the total heat consumed. But one thing to notice: for the critical point lies on the boundary of both subdivisions, its vertical coordinate could directly influence the heat-releasing disciplinarian. On the other hand, the matching turning corner on the curved axis of 50% of total heat released during the high-temperature heat release process is an essential factor in controlling the HCCI combustion process. To be more specific, “explosive combustion” is a typical signal of incomplete combustion, as to prevent it from happening, a stabilized HCCI engine must situate its combustion control’s crank angle in a range of (0,6) [3]. Thus, the reason why HCCI engines possess a higher thermal efficiency is figured out in the following two aspects: Through a low-temperature negative-entropy-induced reaction, the pressure and 168 Proceedings of the 2023 International Conference on Mechatronics and Smart Systems DOI: 10.54254/2755-2721/11/20230226 temperature of gases increase, it not only optimizes the combustion conditions of mixture gases but also decreases the fraction of dissipation of work conducting ability. Burning tenuously pushes to complete combustion and shifts up the multilateral index. By the way, to harness the engine properly, engineers suggest users regulate the peak combustion temperature beneath 1800 K to minimize the production of NOx. This culprit resists high efficiency and contaminates the environment but exceeds 1500 K to unlock the automatic igniting point. 3.2. Different types of fuels Mazda is the pioneer in applying the HCCI engine on an automobile. In 2007, the CEO of Mazda published a creative technology called SPCCI (spark-controlled compression ignition), which could thoroughly realize super-subtle combustions in its ordinary loading range and lower oil consumption rate. Since the HCCI engine would spark simultaneously in different locations, the throttling loss is eliminated, and the subtle mixing gases can adopt a relatively high compression ratio. When the ideal isochoric combustion gets access, the engine will provide a high thermal efficiency; meanwhile, another course for achieving higher thermal efficiency is due to a low climax of combustion temperature, minimizing the amount of heat transferred from the sparking locations to air cylinder wall surface even in the case that the thermal conductivity is unchangeable. With more heat transfer, HCCI can fit many fuels, including gasoline, diesel oil, natural gas, alcohol, and dimethyl ether (DME). The principle is that as the fuel could vaporize and effectively react to air before the spark appears, it is classified as qualified. 3.3. Simpler structure and easier manipulation for HCCI Distinguished from traditional car engines, the HCCI engine does not require an air damper because it can automatically control the amount of fuel injection. For traditional engines, its burning process is called sparking ignition. Combustion of SI requires the local flame (the burning gas) to be mixed with the unburned gas, allowing the local unburned gas temperature to rise above the spontaneous ignition temperature before combustion. Therefore, the rate of combustion depends on the rate of local gas mixing, which is relatively slow. But the situation is not so in HCCI. In the HCCI engine, the gas temperature in the cylinder is around 1100 K; some gas temperature is higher, and some gas temperature is lower. The hottest gas burns first and gives off some heat, and at this point, the colder gas is above 1,100 K, so it starts burning. The process is very fast: for example, if the gas temperature in the tank is exactly 1,100 K, then suddenly, all of the gas will spontaneously ignite and burn. And then it would look exactly like an ideal Otto cycle. But in reality, since the cylinder wall is cold, the gas will have different temperatures. Thus, the ignition time is slightly later because the cold gas only needs to be hotter to burn. In certainty, the HCCI will still burn much faster than the SI. Here is a picture of the temperature distribution of the gas in an optical engine cylinder, where hot and cold are randomly distributed. When the hot spot burns up, the little bit around it burns up quickly rather than spreading outward from the center, like SI. In this case, its strong control of temperature in each part reflects the fact that valves are not necessary to be installed, resulting in an easier manipulation restriction for the staff, who only needs to notice the variation of the multilateral index, gas exhaustion rate, compression ratio and degree of NOx emission. 4. Practical application of HCCI engine HCCI engine has a huge application prospect in many fields. Among them, the automobile is one of the biggest parts. However, some applications have not been widely used. 4.1. GM OPEL vectra and GM saturn aura They both used 2.2L L4 gasoline engines with HCCI technology. Due to the HCCI technology, their oil consumption is only 4.3 L/100 km, more than 15% lower than that of conventional vehicles. Unfortunately, due to the temporary unsophistication of combustion moment control technology, the HCCI engines cannot always work properly. On the other hand, the cold start of these engines is 169 Proceedings of the 2023 International Conference on Mechatronics and Smart Systems DOI: 10.54254/2755-2721/11/20230226 extremely hard because the air-fuel mixture`s initial temperature is too low to burn by compressing, and it becomes even worse in a frozen environment. These two factors determined the effect of these vehicles have not carried out volume production, which had made their names rarely known by people. 4.2. 2007 mercedes F700 Its Diesel Otto 1.8T straight 4 CGI direct injection engine adopts HCCI technology, the output power reaches 238 horsepower, and the maximum torque reaches 400N.m, which can be compared to a 3.5 L V6 engine's performance. The rare thing is that its fuel consumption is only 6 L/100 km, and the carbon dioxide emission is only 127 g/100 km. Due to the market and manufacturing costs, Mercedes-Benz has a very mature traditional internal combustion engine manufacturing technology, making this car a dazzling concept car. 4.3. Mazda oncella 3 Theoretically, the HCCI engine does not need a spark plug, but HCCI engines cannot perform well and reach high thermal efficiency in low-temperature environments. This also led to another problem: more pollution in this process was produced. HCCI is prevalent with diesel-powered engines, but gasoline has been a tough cookie to crack since the initial temperature is the one factor that must be present for the air-fuel mix to combust. If the engine is too hot, engine knock and unpredictable timing is present; if it is too cold, ignition problems ensue. So, Mazda looked to the past and found a solution: use a spark plug. Like a traditional gas engine, Mazda's HCCI engine uses a spark plug to ignite the air and fuel mixture should ambient temperatures be too low, if the engine is subject to a cold start and during high-rpm driving situations. For example, when the car constantly cruises on the highway or during low-load situations around town. According to Mazda's official data, Mazda has said its HCCI engine, known as Skyactiv-X, will be 20 to 30 percent more efficient than its current crop of powertrains. 5. Challenges and development prospects of HCCI diesel engine commercialization 5.1. Strict environmental conditional restrictions 5.1.1. Threshold of temperature. The ignition threshold temperature for a cold starting state, referring to a relatively hard sparking induction, is approximately 1000 K. Being ignited in an unprepared situation, the temperature of combustor walls is low, which does not enable heat absorption from the gas intake turbine and does not have accessible hot, exhausted gases. Such a condition is hard to provide additional heat from the last circulation. Likewise, without temperature compensation, igniting the HCCI engine to reach the threshold temperature during the cold starting stage is nearly a miracle. 5.1.2. Picky for loading degree. If encountering underloads, the working condition for the engine belongs to subtle combustion. Since the number of components and their molecular concentrations of the mixing gaseous fuel are few, it is easier to be on fire when igniting. On the other hand, if encountering overloads, the engine would burn rapidly; under such a situation, the mixture of gases is excessively dense, resulting in a horrible explosion. In fact, according to a claim made by the CEO of Mazda, the most comfortable degree of loading for the engine’s combustion is the mid-low one. 5.1.3. Pollution. There is an engineering chain: the pollution index, a standard statistic to measure the degree of contamination, depends on nitrogen oxidization emission. At the same time, the level emission of nitrogen oxidations is largely decided by the air-fuel ratio, and the ternary catalytic converting technology aimed to improve this ratio effectively constrains the pollution index. For the strata of airfuel ratio, when promising its value to surpass 16, which signals the upper bound of NOx emission, with a marginal increase of air-fuel ratio, there is no supplement of NOx gases, and they have been substituted by pure inhaling air. Although the absolute value of noxious exhaustion gases remains constant, more units of kinetic energy could present for a steady amount of NOx, which implicitly controls their 170 Proceedings of the 2023 International Conference on Mechatronics and Smart Systems DOI: 10.54254/2755-2721/11/20230226 emission. By the way, the essence of tackling key problems of the scanty air-fuel ratio is important: it is equivalent to controlling the ejection of combusting oils. The ECU system is based on real working conditions to ensure the correction factor and nominal fuel ejection rate. There are three ways to control: a. Feedback-proved air-fuel ratio control; b. Physical model-based air-fuel ratio control with the selfcorrecting regulator; c. Combusting pressure control. However, none of the above technologies have been studied thoroughly. 5.2. Rarity of ideal kinds of fuel Since the ternary catalyst requires the reduction reaction for NOx with assistance from HC or CO from the exhausted gases, with incremental air-fuel ratio, the decreased temperature after the combustion of mixed gases causes depression on the production of HC and CO, impeding the reduction reaction trend of NOx. In this way, the engine usually needs an additional NOx -absorbing catalytic converter in subtle combustion. But a new difficulty emerges. This converter reveals intensive repulsion of manganese and sulfur, implying that it cannot be applied to stick their venomous compounds when filtering. If these venomous elements sediment in the converter, they could damage the original functions of catalyzing. Take sulfur as an example; to obliterate it, engineers can either adopt low-sulfur oils or increase the combustion temperature to 650 degrees [4]. Objectively scrutinizing, the low sulfur oil mentioned in the former solution cannot be found in common stores, and economically, no authorized brands are formed, reflecting the hardship of its manipulation. 5.3. Shorter lifespan The working pattern of an advanced HCCI engine still experiences 4 stages when being observed, and the discoverer would conclude that all of them contain difficulties of the small piston. Besides, a spring was installed and tangled on the moving piston to alleviate the explosive vibrating effect when homogeneous combustion occurred to prolong the engine's lifespan. The consequence is inconceivable without the installment. Otherwise, compared to traditional engines, the HCCI engine possesses a higher pressure if gasoline explodes because of a larger displacement of the dragged piston. A long-run overload accelerates its despoiling process [5]. 6. Artificial intelligence for HCCI 6.1. Emission and operation characteristics of HCCI engines The factors in HCCI engine operation, such as intake temperature, intake pressure, fuel type, EGR rate, load, speed and so on, strongly correlate with the engine's output parameters [6]. However, this correlation is not a simple linear but sensitive nonlinear relationship [6]. Over the years, several researchers have explored ways to solve this problem. Javad et al. used fuel mixing ratio and excess air coefficient as input parameters to construct a radial basis neural network and feed-forward neural network, respectively, to predict the output parameters of the HCCI engine [6]. Finally, experimental data verification found that the average error of parameter prediction of the two models was lower than 4% [6]. Harisankar et al. also designed a hybrid model of generalized regression neural network and particle swarm optimization and used an optimization algorithm to optimize the intake temperature, EGR rate and load of HCCI engines [6]. Artificial neural networks are also nonlinear systems, so it is possible to design AI suitable for the operation and control of HCCIs. The previous example is a good example of this. 6.2. Artificial intelligence and HCCI engine real-time control Exhaust gas recirculation, variable valve timing, intake heating and controllable oil supply system are necessary auxiliary control systems to ensure the stable operation of the HCCI engine in the actual working process. HCCI engines must carry many of the above auxiliary control systems, which greatly increases the complexity of the HCCI engine and the cost of HCCI engine control. Previous studies mainly focused on using experimental data to train the neural network to predict the running parameters 171 Proceedings of the 2023 International Conference on Mechatronics and Smart Systems DOI: 10.54254/2755-2721/11/20230226 of the HCCI engine in an off-line state. However, this requires a large amount of experimental data, requiring high computer processing power and calculation cost. On the other hand, different engines have different optimum operating conditions, which makes it difficult for some neural networks with good training effects to be applied to other engines [6]. At the same time, the HCCI engine will generate much data that needs attention, but the subtle changes in the engine will significantly impact the control process. This puts forward the requirement of fast operation and fast update iteration for the prediction model of artificial intelligence. To solve the above problems, Vijay et al. developed a stable online learning algorithm (SG-ELM) based on a stochastic gradient extreme learning machine combined with the characteristics of online real-time control of the HCCI engine, which can carry out online regression learning of an HCCI engine and detect the dynamic operating boundary of the engine [6]. Although there are still many problems that cannot be solved for the time being, the SG-ELM algorithm guarantees the stability of learning and reduces the amount of computation, which is likely to be applied to the realtime control of the HCCI engine in the future. 6.3. HCCI engine misfire detection Misfire is an important factor restricting the expansion of the HCCI engine to low load. SI/HCCI composite engines need to switch combustion modes, and the accuracy of misfire detection will directly affect the safety and speed of this process. HCCI engine fire is mainly caused by unstable combustion. Once the engine fire causes unburned fuel into the tail gas post-treatment system to cool the catalyst, when the activity of the catalyst is reduced, it will significantly increase the emissions of HC and CO, the addition of these combustible gas components, and aggravate the instability of combustion. Therefore, misfire detection of HCCI engines is very important, which is an important link to ensure the safety and availability of HCCI engines [6]. Experiments have verified that the accuracy of predicting engine misfires can reach 100% using neural network input. Bahram B et al. found the in-cylinder pressure at 5, 10, 15 and 20 °C. A top dead center was the key factor determining engine misfires [7]. 6.4. Initial combustion time prediction of HCCI engine HCCI engine belongs to homogeneous compression combustion, and chemical reaction dynamics control the initial combustion moment. Intake temperature, pressure and fuel characteristics will affect the initial combustion moment. The initial combustion time plays a leading role in the combustion process of the internal combustion engine [6]. The spark plug ignition controls the initial combustion time of the ignition engine, while the pressure combustion engine indirectly controls the initial combustion time by the injection time [8]. Taghavi et al. compared engine speed, intake temperature, pressure, equivalent ratio, octane number and EGR Rate as the input, the neural network was constructed to predict the initial combustion time, and the genetic algorithm was used to optimize the structural parameters of the neural network, which not only improved the prediction accuracy but also reduced the calculation cost [9]. Choi et al. established a new prediction model of the initial combustion time by coupling the semi-empirical model of the initial combustion time with the artificial neural network, and the average CPU calculation time of this prediction model is 20-30 ms [10]. Therefore, it has the potential to be applied to the real-time dynamic control of HCCI engine combustion. 7. Conclusions According to the study, adding a spark plug into HCCI engines lets its cold start easier and brings in fuel economy. The stable operation of the HCCI engine is affected by many factors, so it is more difficult to predict the output parameters of the HCCI engine. The trained artificial neural network can achieve higher prediction accuracy than other prediction models. At the same time, the artificial intelligence prediction model does not need to monitor the complex in-cylinder combustion process in real time and can complete the prediction through the initial parameters, and the prediction speed is extremely fast. In the future, this technology will be applied to the HCCI engine on a large scale. With the needs of national and social development, there will certainly be more research on the HCCI engine in the future, and the difficulties the HCCI engine is facing will be solved, and it will shine brightly in the practical field. 172 Proceedings of the 2023 International Conference on Mechatronics and Smart Systems DOI: 10.54254/2755-2721/11/20230226 References [1] Antunes, J.G., Mikalsen, R. and Roskilly, A.P., 2008. An investigation of hydrogen-fuelled HCCI engine performance and operation. International journal of hydrogen energy, 33(20), pp.58235828 [2] Hairuddin, A.A., Yusaf, T. and Wandel, A.P., 2014. A review of hydrogen and natural gas addition in diesel HCCI engines. Renewable and Sustainable Energy Reviews, 32, pp.739-761 [3] Koo, T., Kim, Y.S., Lee, Y.D., Yu, S., Lee, D.K. and Ahn, K.Y., 2021. Exergetic evaluation of operation results of 5-kW-class SOFC-HCCI engine hybrid power generation system. Applied Energy, 295, p.117037 [4] Wang, F., Harindintwali, J.D., Yuan, Z., Wang, M., Wang, F., Li, S., Yin, Z., Huang, L., Fu, Y., Li, L. and Chang, S.X., 2021. Technologies and perspectives for achieving carbon neutrality. The Innovation, 2(4), p.100180 [5] Ezoji, H. and Ajarostaghi, S.S.M., 2020. Thermodynamic-CFD analysis of waste heat recovery from homogeneous charge compression ignition (HCCI) engine by Recuperative organic Rankine Cycle (RORC): Effect of operational parameters. Energy, 205, p.117989 [6] Solmaz, H., 2020. A comparative study on the usage of fusel oil and reference fuels in an HCCI engine at different compression ratios. Fuel, 273, p.117775 [7] Wu, Y.Y. and Jang, C.T., 2019. Combustion analysis of homogeneous charge compression ignition in a motorcycle engine using a dual-fuel with exhaust gas recirculation. Energies, 12(5), p.847 [8] Bahri, B., Aziz, A.A., Shahbakhti, M. and Said, M.F.M., 2013. Understanding and detecting misfire in an HCCI engine fuelled with ethanol. Applied Energy, 108, pp.24-33 [9] Taghavi, M., Gharehghani, A., Nejad, F.B. and Mirsalim, M., 2019. Developing a model to predict the start of combustion in HCCI engine using ANN-GA approach. Energy Conversion and Management, 195, pp.57-69 [10] Choi, Y. and Chen, J.Y., 2005. Fast prediction of start-of-combustion in HCCI with combined artificial neural networks and ignition delay model. Proceedings of the Combustion Institute, 30(2), pp.2711-2718 173
https://openalex.org/W4300926875	https://revistas.ucm.es/index.php/INFE/article/download/53804/50019	Spanish; Castilian	null	Politics and scholarship: feminist academic journals and the production of knowledge	Choice/Choice reviews	1,995	cc-by	10,322	RESUMEN El objetivo de este artículo es explorar los procesos de publicación de seis revistas académicas feministas anglófonas. Se presenta la génesis de las revistas, así como el nivel de participación de hombres y mujeres, la colaboración y la productividad. En esta perspectiva se analizan y comparan dos grupos de revistas (el primero compuesto por tres revistas feministas generalistas y el segundo de tres revistas feministas especializadas en filosofía, sociología y psicología). Los resultados muestran que el contexto histórico y el compromiso político de las revistas explican las diferencias y similitudes entre ellas y entre los dos grupos de revistas. Si bien la participación de los hombres es minoritaria en todas las revistas, es mucho mayor en las generalistas. La colaboración entre autoras y autores es mayor en las revistas especializadas debido a su fuerte componente empírico. Palabras clave: Sexo, género, producción de conocimiento, colaboración científica, revistas académicas feministas. Academia y política: revistas feministas y producción de conocimiento Artemisa FLORES ESPÍNOLA Universidad París-Sorbona artemisa.flores@gmail.com Recibido: Octubre 2014 Aceptado: Diciembre 2014 Recibido: Octubre 2014 Aceptado: Diciembre 2014 Academia y política: revistas feministas Academia y política: revistas feministas Academia y política: revistas feministas Academia y política: revistas feministas INTRODUCCIÓN La década de los setenta fue particularmente importante para el movimiento feminista con la consolidación de la teoría feminista del género, ya que el contexto histórico y político ocasionó que este movimiento político, se volviera también académico (Flores Espínola, 2005). Las universidades, en particular a través de los women’s studies, fueron un lugar privilegiado de discusión y de debates entre el activismo político y la academia. Sin embargo, la institucionalización académica del pensamiento político feminista no fue recibida con entusiasmo por todas las militantes, particularmente en las asociaciones, que veían estas transformaciones como una forma de desactivación de la vertiente de denuncia social. Las académicas que, en tanto que feministas, se encontraban participando en un movimiento social y político sin precedentes, vieron la oportunidad de crear un tipo de conocimiento comprometido con el cambio social. La aparición de las publicaciones feministas tiene lugar en un contexto histórico y político determinado que influye necesariamente en sus políticas editoriales. Este artículo examina el proceso de producción de conocimiento feminista y busca contestar cuestiones como: ¿existen diferencias en la participación de los hombres de acuerdo al tipo de revista feminista?, ¿por qué algunas revistas cuentan con un mayor o menor nivel de impacto?, ¿el nivel de colaboración entre autores y autoras es igual en las revistas feministas generalistas que en las especializadas? Y ¿las políticas editoriales influyen en el tipo de metodología utilizada? Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 ABSTRACT The aim of this article is to explore the process of publication of six feminist academic journals. The genesis of journals as well as the level of participation of men and women, collaboration and productivity is presented. In this perspective, they are analyzed and compared two groups of academics journals (the first composed of three general feminist journals and the second of three feminist academics journals specialized in philosophy, sociology and psychology). The results show that the historical context and the political commitment of journals explain the differences and similarities between them and between the two groups of magazines. While the participation of men is a minority in every magazine, it is much higher in general. The collaboration between authors and authors is higher in magazines due to its strong empirical component s: Sex, gender, production of knowledge, scientific collaboration, feminist academi Keywords: Sex, gender, production of knowledge, scientific collaboration, feminist academic journals. ISSN: 2171-6080 http://dx.doi.org/10.5209/INFE.53804 179 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Artemisa Flores Espínola 1. GÉNESIS Y CARACTERÍSTICAS GENERALES DE LAS REVISTAS ACADÉMICAS FEMINISTAS Entre 1965 y 1968 hubo una explosión de publicaciones feministas, principalmente bajo la forma de boletines informativos que formaban parte de la estrategia política feminista. Una gran proporción de mujeres de izquierda comenzó incorporando sus reivindicaciones dentro de los órganos de prensa de sus respectivas organizaciones. Fue el inicio de un proceso que dio como resultado artículos cada vez de mayor calidad y reflexión y que necesitaban un lugar propio de expresión, ya que no existía un espacio para las feministas en las revistas de la corriente dominante. La columna Ms, que apareció a partir de 1972 en el New York Times, fue considerada una de las más importantes publicaciones de derechos de las mujeres del momento. Según McDermott (1994) todas las publicaciones feministas, antes de esta columna, fueron realizadas por colectivos radicales y grupos de autoconciencia de mujeres que pertenecían a movimientos de izquierda. En este mismo año se crean las dos primeras revistas feministas en Estados Unidos: Feminist Studies y Women’s Studies. La institucionalización y profesionalización de las universidades y las academias de ciencia produjeron una especialización de la investigación, y de ahí una demanda de revistas científicas especializadas. De 1960 a 1975, las revistas científicas y técnicas publicadas en Estados Unidos duplicaron su número, pasando de 2.800 a 4.200. Este hecho, combinado con el movimiento de mujeres, fue el contexto en el que aparecen 180 Academia y política: revistas feministas Artemisa Flores Espínola las primeras revistas feministas. Las académicas feministas se dieron cuenta de la “importancia política de construir un tipo de conocimiento opuesto legitimado y disponible” (Mc Dermott, 1994:1) y con este fin se entregaron a la tarea de fundar revistas multidisciplinarias dentro de instituciones académicas. Las seis revistas académicas se reconocen como feministas, como queda de manifiesto en sus editoriales. 1. GÉNESIS Y CARACTERÍSTICAS GENERALES DE LAS REVISTAS ACADÉMICAS FEMINISTAS En este trabajo utilizamos el término de revistas académicas feministas definido por McDermott (1994), para referirse a aquéllas que cumplen con ciertos criterios: tienen su sede en una universidad, que al mismo tiempo las sustenta financieramente; exponen una perspectiva feminista en su prefacio, en la editorial o en el contenido; usan personal académico como editores/as y consultores/as; se adhieren a las normas y estilos de las publicaciones académicas convencionales como se definen en los manuales oficiales; son escritas y formateadas de acuerdo con la apariencia de reconocidas revistas; sus resúmenes e índices van de acuerdo con los principales servicios de referencias académicas (Modern Language Association International Bibliography, Psychological Abstracts, etc) y, finalmente, las revistas son publicadas en intervalos regulares. 1.1. MÉTODOS Y CARACTERÍSTICAS GENERALES DE LAS REVISTAS Los resultados de la investigación que aquí se presentan forman parte de una investigación más amplia realizada en el marco de la tesis doctoral de la autora (Flores Espínola, 2013). Para la realización de este artículo se consideran los artículos publicados en seis revistas académicas feministas anglófonas desde su creación y hasta el año 2005. Para elegir las revistas que forman parte de la muestra se consideraron tres criterios: primero, que fueran revistas con arbitraje internacional; segundo, que la universidad y/o sociedad que las acoge y sustenta gozara de gran prestigio; tercero, como forma de corroborar su importancia en la especialidad, consideramos también el nivel de impacto de la revista según el Journal Impact Factor. El primer grupo de tres revistas feministas generalistas lo conforman: Feminist Studies (1972), Signs: Journal of Women in Culture and Society (1975), Women’s Studies International Forum (1977) y el segundo grupo de tres revistas académicas feministas en psicología, filosofía y sociología son: Psychology of Women Quarterly (1976) Hypatia (1986), Gender & Society (1987). En la siguiente tabla (1) se observan las fechas de creación de las revistas, la frecuencia de publicaciones por revista, el número total de artículos y también el total de contribuciones, ya que cada artículo puede ser firmado por varias personas. Para elaborar este estudio se contabilizaron todos los artículos publicados desde la creación de cada revista y hasta el año 2005, lo que representa un total de N=5.866 artículos en las seis revistas. Los artículos de la muestra representaron un total de 7.840 contribuciones, de las cuales 7.172 fueron contribuciones de mujeres y 794 de hombres. Para procesar la información se utilizó el programa Excel. Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 181 Academia y política: revistas feministas Artemisa Flores Espínola Tabla 1. Número de artículos publicados en las revistas desde su fundación y hasta 2005 Revista Año de fundación Nº. total de volúmenes (números) Nº. de publicaciones anuales Nº. de Artículos N°. total de contribuciones Contribuc. de H Contribuc. de M Feminist Studies 1972 31 (90) 3 816 905 35 870 Signs 1975 31 (123) 4 1.257 1344 126 1344 Women’s Studies Int. Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 1.1. MÉTODOS Y CARACTERÍSTICAS GENERALES DE LAS REVISTAS Forum 1977 28 (146) 6* 1.354 1.658 52 1606 Psychology of Women Quarterly 1976 29 (117) 4 1.035 2.193 367 1826 Hypatia 1986 20 (73) 4 794 852 87 765 Gender & Society 1987 19 (98) 6* 610 888 127 761 N=5.866 7.840 794 7.172 * Del Vol. 1 al 4 (1978-1981) fue trimestral y cambia a bimestral en el Vol. 5 (1982). El Vol. 1 fue semestral, Vol. 2 al 6 (1986-1991) cuatrimestral y trimestral a partir del Vol. 7 (1992). * Del Vol. 1 al 8 (1987-1994) fue trimestral y a partir del Vol. 9 (1995) es bimestral. mero de artículos publicados en las revistas desde su fundación y hasta 2005 En general, las revistas feministas generalistas (FS, Signs y WSIF) cuentan con los más bajos factores de impacto, respecto a las especializadas, como se muestra en la gráfica (1). Se observa que G&S, a pesar de su reciente creación cuenta cada vez con un mayor reconocimiento ubicándose en el primer lugar de las 40 revistas que aparecen en la categoría de estudios de las mujeres, PWQ se ubica en el segundo lugar, Signs se ubica en el octavo lugar, WSIF en el 26, FS en el 27 y en el lugar 28 se encuentra la revista Hypatia. Gender & Society y Psychology of Women Quarterly cuentan con los mayores factores de impacto. Algunas revistas, como FS, fueron creadas con el objetivo de combinar academia y militantismo, lo que puede influir en el factor de impacto, en cambio Signs que surge en el mundo universitario y con un claro perfil académico cuenta con un nivel de impacto mayor. En general, se observa un mayor factor de impacto en las revistas especializadas que en las generalistas. Esto puede explicarse porque en las primeras se presentan resultados de investigaciones mientras que en las otras tres revistas se concentran más en los debates teóricos del feminismo, que puede 182 Artemisa Flores Espínola Academia y política: revi Academia y política: revistas feministas Artemisa Flores Espínola Artemisa Flores Espínola menos a un público más amplio. Gráfica 1. Factores de impacto de las revistas en estudios de las mujeres según JCR Fuente: Elaboración propia con los datos del Journal Citation Report 2015. 0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6 1,8 2 2,2 2,4 FS G &S Hypatia PWQ Signs WSIF Fuente: Elaboración propia con los datos del Journal Citation Report 2015. 1.1. MÉTODOS Y CARACTERÍSTICAS GENERALES DE LAS REVISTAS Las seis revistas que se analizan en este artículo son bastantes diferentes, pero las une un compromiso político feminista de cambio social. Tanto FS como WSIF son revistas que combinan academia y militantismo, es decir, que acogen también panfletos militantes, ensayos y poemas. Una diferencia evidente con respecto a la revista Signs que cuenta con un formato más académico. En cambio, las otras revistas especializadas pueden considerarse menos accesibles a la gente fuera de la filosofía (Hypatia), la psicología (PWQ) o la sociología (G&S), lo que ocasiona que cuenten con estilos y políticas editoriales diferentes. 1.2. PARTICIPACIÓN Y COLABORACIÓN EN LAS REVISTAS Como puede observarse en la siguiente gráfica (2), en las tres revistas generalistas la participación de los hombres es más baja que en las revistas especializadas. PWQ cuenta con la más alta participación de hombres con un 17%, lo que duplica el porcentaje de las tres revistas generalistas, que cuentan con 3,9% para FS, 8,6% para Signs y 3,1% para WSIF. En las otras dos revistas especializadas la participación de autores también fue importante ubicándose en 14% y 10% en G&S e Hypatia respectivamente. 183 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Artemisa Flores Espínola Academia y política: revistas Academia y política: revistas feministas Artemisa Flores Espínola Artemisa Flores Espínola Gráfica 2. Porcentaje de contribuciones por sexo en las seis revistas feministas Gráfica 2. Porcentaje de contribuciones por sexo en las seis revistas feministas Fuente: Creación propia tomando en cuenta la media de contribuciones por revista. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% FS Signs WSIF PWQ Hypatia G&S 96,1% 91,4% 96,9% 83,3% 89,8% 85,7% 3,9% 8,6% 3,1% 16,7% 10,2% 14,3% Mujeres Hombres Fuente: Creación propia tomando en cuenta la media de contribuciones por revista. La poca participación de los autores en las revistas feministas puede deberse a que se sienten más alejados que las mujeres con las preocupaciones feministas. Lo que llama la atención son las grandes diferencias entre los niveles de participación de los hombres en estas seis revistas. Por ejemplo, vemos que su participación es bastante baja en Feminist Studies (3,9%) y Women’s Studies International Forum (3,1%) pero que puede representar hasta casi el 17% en PWQ. Diferentes factores pueden explicar estas disparidades. Un factor puede ser el de las diferencias en las trayectorias de publicación de hombres y mujeres. De acuerdo con Rier (2003) los hombres comienzan sus carreras profesionales publicando artículos potencialmente controvertidos en revistas visibles, para tener una mayor visibilidad pública y de los medios, pero aumentan sus preocupaciones con la edad, el rango y la experiencia. En cambio, señala que las trayectorias de las mujeres son menos homogéneas. Mientras, con frecuencia, la élite reportó patrones similares a los hombres, la mayoría dijo seguir el patrón opuesto. Es decir, los hombres eligen publicar artículos en revistas con un mayor prestigio y visibilidad, como es el caso de G&S o PWQ. Estas revistas son bastante especializadas y académicas y no buscan necesariamente difundir sus resultados entre la población no académica como es el caso de FS et WSIF. El nombre de la revista puede tener también un impacto en la participación, una revista llamada Feminist Studies puede atraer menos hombres e incluso a algunas mujeres, debido a la carga política radical con la que cuenta feminismo desde sus inicios. Finalmente, unas políticas editoriales más estrictas con los artículos propuestos por hombres que por mujeres podría también constituir otro factor que explicativo de esta menor participación. De forma general, los estudios sobre los procesos de publicación y patrones de productividad han mostrado que existe una diferencia significativa entre la 184 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Investigaciones Feministas Vol. Gráfica 2. Porcentaje de contribuciones por sexo en las seis revistas feministas 7 Núm 2 (2016) 179-202 Academia y política: revistas feministas Artemisa Flores Espínola productividad de los hombres y la de las mujeres (Cole y Zuckerman 1984; Kyvik 1990; Zuckerman, Cole y Bruer 1991; Long y Fox, 1995; Kyvik y Teigen, 1996; Ward y Grant, 1996; Xie y Shauman 1998; Long, 2001; Fox, 2005 y 2007; Larivière et al, 2013). Un elemento importante para explicar la menor productividad de las científicas es la colaboración. Scott Long (1990) examinó el proceso de menor productividad de las científicas al finalizar su formación de doctorado y encontró que el factor más importante que afecta la productividad es la colaboración con el mentor. Señala además que, para las mujeres, las posibilidades de colaboración disminuyen cuando se tienen hijos/as pequeños/as, lo que tiene un efecto negativo en su productividad. Este mismo efecto no se observa en los hombres. El autor identifica también algunas otras diferencias que producen ventajas para los hombres y desventajas para las mujeres, especificando que es precisamente la concentración de pequeñas desventajas lo que explica las diferencias de productividad al inicio de la carrera. La mayoría de los autores y autoras que trabajan sobre el tema coinciden en que la explicación de las diferencias de publicación por sexos es compleja. Se tiene que considerar el impacto o la influencia de las investigaciones, por ejemplo, a través de la frecuencia con que los trabajos son citados en ciencia. Marianne Ferber (1986) encontró que las mujeres citan más mujeres y los hombres citan con frecuencia hombres, por lo que las citas no pueden seguir viéndose como un indicador imparcial del mérito. Para Zuckerman (1991), la menor proporción de mujeres como autoras explicaría el menor índice de citas que tienen las mujeres. Utilizando los resultados de su análisis sobre las citas en trabajos de hombres y mujeres del mismo nivel en seis ciencias, muestra en efecto que el índice de citas de un investigador o investigadora se encuentra relacionado con el índice de publicación. Observando que los trabajos de las mujeres son citados en promedio tanto como los de los hombres, la autora concluye entonces que es el menor índice de publicación de las mujeres lo que explica su menor índice de citas. Todos los datos coinciden en que los hombres publican más que las mujeres, sin que haya por tanto una explicación satisfactoria sobre esta diferencia de productividad en función del sexo. Investigaciones Feministas 186 Vol. 7 Núm 2 (2016) 179-202 p g g 2 Las antiguas editoras fueron Kathryn Pyne Addelson, Eileen C. Boris, Lynn Bolles, Paola Bacchetta, Ann Calderwood, Barbara Christian, Lisa Crooms, Rachel Du Plessis, Nan Enstad, Sara Evans, Evelyn Nakano Glenn, Sharon Groves, Sandra Gunning, Heidi Hartman, Arlene Keizer, Susan S. Lanser, Tessie Liu, Marilyn Sanders Mobley, Nancy Hewitt, Irma McClaurin, Véase la historia en la página de la revista: www.feministstudies.org. 2 Las antiguas editoras fueron Kathryn Pyne Addelson, Eileen C. Boris, Lynn Bolles, Paola Bacchetta, Ann Calderwood, Barbara Christian, Lisa Crooms, Rachel Du Plessis, Nan Enstad, Sara Evans, Evelyn Nakano Glenn, Sharon Groves, Sandra Gunning, Heidi Hartman, Arlene Keizer, Susan S. Lanser, Tessie Liu, Marilyn Sanders Mobley, Nancy Hewitt, Irma McClaurin, 1 Véase la historia en la página de la revista: www.feministstudies.org. 2 2.1. FEMINIST STUDIES En este artículo se analizan los patrones de colaboración y de productividad por sexo, sin embargo, debido al bajo porcentaje de participación de hombres en las revistas, lo que sobresale son sobre todo los patrones de colaboración y productividad de las autoras en las revistas. Feminist Studies es la revista académica más antigua en el campo de los estudios de las mujeres en los Estados Unidos. Esta revista tuvo su origen en los grupos de autoconciencia que se organizaban alrededor del movimiento de liberación de las mujeres de la Universidad de Columbia, las estudiantes de los cursos de estudios de las 185 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Artemisa Flores Espínola Academia y política: revistas feministas mujeres del Sarah Lawrance College y la comunidad de activistas de Nueva York. Toda esta red de feministas tenía la idea de crear una revista académica de calidad, una revista que reflejara los valores, intereses y experiencias no reconocidas de las mujeres. Sobre todo, el objetivo era crear un foro de análisis que abordara los asuntos que surgían del movimiento y que reuniera las contribuciones de las activistas feministas y las académicas. Fueron tres años de discusión y de planes para que por fin la revista apareciera publicada por vez primera en 1972. El título de la revista fue elegido “para indicar que el contenido de la revista sería académico y político y que pondría en primer plano a las mujeres como grupo social y el género como una categoría de análisis”1. FS ha buscado combinar la academia con el movimiento de mujeres y los múltiples problemas para continuar su publicación dan cuenta de lo difícil que es mantener una revista que no es considerada completamente académica y tampoco completamente militante. Tabla 2. Distribución de artículos según el número de personas y sexo en FS (1972 y 2005) Nº de personas por artículo Total de artículos Nº de artículos realizados por hombres % Nº de artículos realizados por mujeres % Nº de artículos Mixtos % % Total 1 753 29 3,55 724 88,73 92,28 2 48 - - 42 5,15 6 0,74 5,89 3 9 - - 9 1,10 - - 1,10 4 3 - - 3 0,37 - - 0,37 5 1 - - 1 0,12 - - 0,12 6 2 - - 2 0,24 - - 0,24 Total 816 29 3,55 781 95,71 6 0,74 100 Fuente: Creación propia. 2.1. FEMINIST STUDIES Tabla 2. Distribución de artículos según el número de personas y sexo en FS (1972 y 2005) Nº de personas por artículo Total de artículos Nº de artículos realizados por hombres % Nº de artículos realizados por mujeres % Nº de artículos Mixtos % % Total 1 753 29 3,55 724 88,73 92,28 2 48 - - 42 5,15 6 0,74 5,89 3 9 - - 9 1,10 - - 1,10 4 3 - - 3 0,37 - - 0,37 5 1 - - 1 0,12 - - 0,12 6 2 - - 2 0,24 - - 0,24 Total 816 29 3,55 781 95,71 6 0,74 100 Fuente: Creación propia. . Distribución de artículos según el número de personas y sexo en FS (1972 y 2005) Gracias al entusiasmo de Ann Calderwood, la revista pudo publicarse entre 1972 y 1976, ya que al principio se publicaba desde el apartamento de la misma. Calderwood se encargaba de las tareas de edición, pero también de las suscripciones y envíos de la revista. En 1977 se reestructura la revista y pasa a ser editada por un colectivo de académicas2 y en este mismo año se nombra como directora editorial a 186 Artemisa Flores Espínola Academia y política: revistas feministas Artemisa Flores Espínola Claire G. Moses quien permanece como editora hasta el 2011. La actual editora de la revista es Ashwini Tambe. La revista cuenta con un total de artículos de N=816 que corresponden a un total de 905 contribuciones (35 de hombres y 870 de mujeres). La contribución de los hombres en la revista es baja (3,9%) y también se observa la más baja colaboración de las tres revistas generalistas (tanto entre personas del mismo sexo como en los artículos mixtos). Una mayoría de personas presentó sus trabajos de forma individual: los artículos escritos por una mujer representan así 88,73% de todos los artículos; los escritos por un hombre 3,55% de los artículos. Es decir, que de las 35 contribuciones de hombres 29 (82,86%) corresponden a artículos individuales y los seis restantes corresponden a artículos mixtos con una mujer. Ruth Milkman, Donna Murdock, Debra Newman, Alicia Ostriker, Rosalind Petchesky, Layli Phillips, Rayna Rapp, Raka Ray, Deborah S. Rosenfelt, Ellen Ross, Mary Ryan, Gay Seidman, Judith Stacey, Christine Stansell, Rosalyn Terborg-Penn, France Winddance Twine, Marian Urquilla, Mariana Valverde, Martha Vicinus, Judith R. Walkowitz, Rhonda Williams. 3 En 1981 toma el puesto Barbara Charlesworth Gelpi, en 1986 se nombra editora a Jane F. O’Barr y en 1991 la edición es compartida por Ruth-Ellen Boetcher Joeres y Barbara Laslett. En 1996 las editoras fueron Carolyn Allen y Judith A. Howard, de 2001 a 2005 Sandra Harding y Kathryn Norberg y Mary Hawkesworth 2005-2014. 2.1. FEMINIST STUDIES Las contribuciones que las autoras hicieron en colaboración, exceptuando las seis en que colaboraron con un hombre, todas (140 contribuciones) corresponden a trabajos entre mujeres: 84 en el marco de artículos de dos autoras (5,15% de los artículos), 27 en los artículos de tres autoras (1,10%) y por último 29 en el marco de artículos escritos por cuatro, cinco o seis mujeres (0,73% de los artículos). 2.2. SIGNS: JOURNAL OF WOMEN IN CULTURE AND SOCIETY La revista Signs, fundada en 1975, fue una de las primeras publicaciones académicas feministas en los Estados Unidos y puede considerarse como una de las más prestigiosas en su campo. La creación de la revista fue consecuencia del éxito experimentado por uno de los números especiales de la revista American Journal of Sociology (AJS) publicado en 1973 llamado ‘Changing Women in a Changing Society’. Los editores de la revista se sorprendieron por el interés que suscitó dicha publicación, así que decidieron apoyar la creación de una revista específica sobre el tema de las mujeres en la cultura y la sociedad. Con este antecedente, la Universidad de Chicago, no tuvo inconveniente en apoyar financieramente una revista específica sobre mujeres (McDermott, 1994). Signs es una revista internacional de frecuencia trimestral. Su primera editora fue Catherine R. Stimpson3 y desde el 2015 las editoras son Suzanna Danuta Walters y Carla Kaplan. El puesto de editora en la revista cambia aproximadamente cada cinco años. La historia de la creación de Signs explica que tenga un estilo y una política editorial diferente de las otras revistas feministas como FS y WSIF. La revista presenta 187 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Artemisa Flores Espínola Academia y política: revistas feministas un formato académico riguroso, que acoge una gran parte de artículos teóricos e interdisciplinarios, bastante extensos y con poco o nulo espacio para manifestaciones feministas no científicas. El número de artículos que componen la muestra de la revista es de N=1.257. Esos artículos fueron escritos por 1.277 personas (1.158 mujeres y 119 hombres) que produjeron 1.470 contribuciones (1.344 de mujeres y 126 de hombres). La colaboración en Signs es ligeramente mejor que en FS tanto para las autoras como para los autores (tabla 3). La colaboración de las mujeres en la revista indica que el 81,14% fueron escritos por una mujer y el resto en colaboración. La colaboración de los hombres en la revista es incluso mayor que las mujeres, ya que de los 126 autores que publicaron en la revista, el 68,3% (86/126) lo hicieron de forma individual, el 20,6% (26/126) con una mujer y el restante 11,1% (14 contribuciones) fueron realizadas con hombres y mujeres. Tabla 3. Distribución de artículos según número de personas y sexo en Signs (1975- 2005) Nº. de personas por artículo Total de artículos Nº. Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 2.3. WOMEN’S STUDIES INTERNATIONAL FORUM Esta revista se funda en el Reino Unido en 1977, bajo el nombre de Women’s Studies International Quarterly y se publica con un intervalo de publicación trimestral. La revista nace por la voluntad de algunas feministas que buscaban un espacio de comunicación y divulgación. Las editoras señalan las dificultades y riesgos asociados a la estrategia de formar parte de una institución académica, de un lado se asume que los estudios sobre mujeres deben continuar preservando su libertad, pero al mismo tiempo se tienen que seguir los lineamientos que las instituciones demandan. Esta revista es una de las primeras revistas feministas en Inglaterra y surge, como FS, con la voluntad de combinar escritos militantes y académicos. En 1982 la revista toma el nombre de Women’s Studies International Forum y su frecuencia pasa de ser trimestral a bimestral. Desde sus inicios hasta hoy se han publicado 28 volúmenes. En esta revista como en las otras, para conocer la información sobre los números que se han publicado, hay que analizarlos en detalle, ya que en gran parte de los volúmenes existe un mismo número que incluye dos. De esta forma, en total no hay 160 números, sino 139 números. La primera editora de la revista, en 1977, fue Dale Spender que permaneció durante diez años con tres coordinadoras asociadas por regiones que estaban junto a ella. Sin embargo, a partir de 1987, el trabajo de edición se realiza de forma colectiva. Liz Stanley deja la revista en 1988 y su puesto es tomado por Ailbhe Smyth. En 1990, Sue V. Rosser es nombrada editora y comienzan una serie de cambios sucesivos en las editoras regionales. En 2003 se convierte en editora en jefe Christine Zmrockek y actualmente la editora es Kalwant Bhopal. El número de artículos publicados en la revista es de N=1.354. Estos artículos fueron escritos a partir de 1.658 contribuciones (1.606 de mujeres y 52 de hombres). Es decir, las contribuciones masculinas representaron el 3,1% del total de contribuciones y las de las mujeres 96,9%. Se observa que, de las 52 contribuciones de hombres, solamente 13 artículos (25%) corresponden a artículos individuales, que corresponde al 0,96% del total, lo que significa que los hombres que publican en esta revista lo hacen más en el marco de una colaboración que en las otras (tabla 4). Los artículos mixtos representan el 2,30% del total. 2.2. SIGNS: JOURNAL OF WOMEN IN CULTURE AND SOCIETY de artículos realizados por hombres % Nº. de artículos realizados por mujeres % Nº. de artículos Mixtos % % Total 1 1.106 86 6,84 1.020 81,14 87,98 2 120 5 0,40 94 7,48 21 1,67 9,55 3 18 - - 14 1,11 4 0,32 1,43 4 7 1 0,08 5 0,40 1 0,08 0,56 5 1 - - 1 0,08 - - 0,08 6 1 - - 1 0,08 - - 0,08 7 1 - - 1 0,08 - - 0,08 8 3 - - 3 0,24 - - 0,24 Total 1.257 92 7,32 1.139 90,61 26 2,07 100 Fuente: Creación propia. . Distribución de artículos según número de personas y sexo en Signs (1975- 2005) Tabla 3. Distribución de artículos según número de personas y sexo en Signs (1975- 2005) En cuanto a ellas, las mujeres realizaron 324 contribuciones en colaboración mixta (1.344 contribuciones menos 1.020 hechas en el marco de un artículo individual). Se observa una colaboración mixta importante con 209 contribuciones en artículos de dos personas (94 en artículos de dos mujeres y 21 en los artículos de un hombre y una mujer). Se observaron 50 contribuciones en los artículos de tres personas 188 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Artemisa Flores Espínola Academia y política: revistas feministas (42 artículos de mujeres y 4 artículos escritos por dos mujeres y un hombre). Las mujeres en la revista publicaron artículos en colaboración de 5, 6, 7 y 8 autoras, con casi el 25% de sus contribuciones hechas en colaboración (324/1344), las autoras de Signs cuentan con la mayor colaboración de las tres revistas generalistas. 2.3. WOMEN’S STUDIES INTERNATIONAL FORUM Pero si se toma en cuenta con respecto a las publicaciones de los hombres, 36,5% (19/52) de sus contribuciones corresponden a artículos escritos con una mujer y 26,9% (14/52) a artículos mixtos de 189 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Artemisa Flores Espínola Academia y política: revistas feministas tres y cuatro personas. En total, 63,4% de las contribuciones de los hombres fueron hechas en el marco de una colaboración mixta y el resto fueron los tres artículos escritos entre dos hombres. De esta forma, se puede decir que la mayor parte de los hombres que publican artículos en WSIF lo hacen con otras mujeres y en menor medida de forma individual o con otros hombres. Tabla 4. Distribución de artículos según número de personas y sexo en WSIF (1977 y 2005) Nº de personas por artículo Total de artículos Nº de artículos realizados por hombres % Nº de artículos realizados por mujeres % Nº de artículos Mixtos % % Total 1 1.128 13 0,96 1.115 82,35 - - 83,31 2 171 3 0,22 149 11,0 19 1,40 12,62 3 39 - - 29 2,14 10 0,75 2,89 4 13 - - 11 0,81 2 0,15 0,96 5 1 - - 1 0,07 - - 0,07 6 - - - - - - 7 2 - - 2 0,15 - - 0,15 Total 1.354 16 1,18 1.307 96,52 31 2,30 100 Fuente: Creación propia istribución de artículos según número de personas y sexo en WSIF (1977 y 2005) Fuente: Creación propia. En general, WSIF y Signs cuentan con una mayor colaboración, a pesar de presentar altos porcentajes de artículos escritos individualmente, 82,35% y 81,14% respectivamente. 3. GÉNERO Y COLABORACIÓN CIENTÍFICA EN LAS REVISTAS ESPECIALIZADAS: NEUTRALIDAD Y CIENTIFICIDAD 3. GÉNERO Y COLABORACIÓN CIENTÍFICA EN LAS REVISTAS ESPECIALIZADAS: NEUTRALIDAD Y CIENTIFICIDAD Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 3.1. PSYCHOLOGY OF WOMEN QUARTERLY En 1976 aparece el primer número de la revista de Psychology of Women Quarterly, revista oficial de la División 35 de la American Psychological Association (APA). Su origen podría ubicarse en 1973, cuando la APA crea un área específica sobre psicología de las mujeres. Como su nombre lo indica, la revista tiene una publicación trimestral. Conforme pasan los años, PWQ ha ampliado constantemente su campo de análisis hasta llegar a la diversidad actual. Esta revista tiene una gran 190 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Artemisa Flores Espínola Academia y política: revistas feministas tradición dentro de las revistas de psicología de orientación crítica. Georgia Babladelis fue editora de la revista los primeros cinco años4 y la editora actual es Mary M. Brabeckes. PWQ es la revista de la corriente dominante en psicología, es decir, que gran parte de sus publicaciones presentan resultados de encuestas psicométricas, lo que le otorga un estatuto de cientificidad y rigurosidad. Quizás por ello un mayor número de personas eligen publicar en ella y que se constata también por su alto nivel de impacto. Los artículos en la revista son bastante desencarnados y hacen muy poco recurso de la experiencia personal. Esto la diferencia de otras revistas de la especialidad, como es el caso de Feminism & Psychology, en donde la reflexividad y los artículos cualitativos constituyen la norma, pero que cuentan con un bajo nivel de impacto y menor reconocimiento. Tabla 5. Distribución de artículos según número de personas y sexo en PWQ (1976- 2005). Nº de personas por artículo Total de artículos Nº de artículos realizados por hombres % Nº de artículos realizados por mujeres % Nº. de artículos Mixtos % % Total 1 348 32 3,09 316 30,53 33,62 2 386 5 0,48 288 27,83 93 8,98 37,29 3 193 6 0,58 104 10,05 83 8,02 18,65 4 67 1 0,096 31 3,00 35 3,38 6,476 5 28 1 0,096 10 0,97 17 1,64 2,706 6 10 - - 3 0,28 7 0,68 0,97 7 2 - - 1 0,096 1 0,096 0,192 8 1 - - - - 1 0,096 0,096 Total 1,035 45 4,342 753 72,75 237 22,892 100 Fuente: Creación propia. 5. Distribución de artículos según número de personas y sexo en PWQ (1976- 2005). En PWQ los autores y autoras publican mayoritariamente de forma colectiva (tabla 5). 4 Luego toma el puesto de editora Nancy M. Henley, la sucede Janet Shibley Hyde en 1987, Judith Worell en 1990 y luego Nancy Felipe Ruso (1995-1999), Jacquelyn W. White (2000- 2004), Jayne E. Sake (2005 al 2009) y Yanice D. Yoder (2010-2014). 5 Entre 1990 y 1995 la editora es Linda Lopéz McAlister. En 1995 la revista tiene tres coeditoras, la misma McAlister, Joanne Waugh y Cheryl Hall, que permanecen hasta 1998, año en que toman el puesto de editoras Laurie Shrage et Nancy Tuana. En 2003 se convierte en editora Hilde Lindeman, quién pasa la mano en 2008 a Alison Wylie y de 2010 a 2013 el puesto de editora es propuesto a Linda Martin Alcoff. 3.1. PSYCHOLOGY OF WOMEN QUARTERLY Del total de las contribuciones masculinas (367), una cuarta parte (93) corresponden a artículos escritos en colaboración con una mujer, lo que representa 191 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Artemisa Flores Espínola Academia y política: revistas feministas 8,98% de los artículos. 4,34% de los artículos son de hombres y de estos la mayor parte corresponde a trabajos individuales. Las autoras escriben sus artículos en colaboración (65,1% de los artículos), sobre todo con otra mujer (72,8-30,5=42,3% de los artículos) pero también con hombres (22,80% de los artículos). Así, las mujeres trabajan menos de forma individual en esta revista que en las otras de la muestra. Cabe observar, que 3,38% de los artículos fueron escritos por cuatro personas en el marco de una colaboración mixta y el 1,64% corresponde a los artículos mixtos de cinco personas. El resto de los artículos mixtos (0,86%) corresponde a los de seis, siete y ocho personas. PWQ es una de las revistas feministas más importantes en psicología y aunque la revista señala su compromiso con la pluralidad metodológica, una gran parte de los artículos publicados utilizan una metodología cuantitativa. Los estudios experimentales y la utilización de escalas psicométricas son bastantes valorados en la disciplina, lo que puede explicar el prestigio de la revista y también el mayor número de hombres que publican en ella. Academia y política: revistas feministas Academia y política: revistas feministas Academia y política: revistas feministas corresponde a artículos mixtos. 3.2. HYPATIA La revista se llama Hypatia en honor de la famosa filósofa, matemática y astrónoma Hypatia de Alejandría. En las páginas de la revista se señala que Hypatia fue publicada en 1983, 1984 y 1985 como números especiales de la revista Women’s Studies International Forum. Hypatia tiene sus raíces en la Society for Women in Philosophy y fue una de las primeras revistas feministas de filosofía en Estados Unidos. La revista se encuentra comprometida con promover la pluralidad dentro de la filosofía feminista y en la filosofía general como era uno de los objetivos de la filósofa Hypatia. Esta revista se funda formalmente en 1986 y su edición ha estado siempre a cargo de mujeres. La primera editora de la revista fue Margaret A. Simons (1986- 1990)5 y la editora actual es Sally J. Scholz. El número de artículos publicados en la revista es de N=794, los cuales fueron realizados a partir de 852 contribuciones (765 contribuciones de mujeres y 87 de hombres). En la siguiente tabla (6) se muestra el nivel de colaboración de hombres y mujeres en la revista. La proporción de artículos individuales de hombres es de 8,56% (68 artículos del total de 794 artículos). Esos 68 artículos representan también 68 contribuciones, lo que significa el 78,2% de todas las contribuciones de hombres (68 de las 87 contribuciones de hombres en total), un elevado porcentaje que refleja una menor colaboración entre autores en esta revista. La mayor colaboración de hombres 192 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Artemisa Flores Espínola Academia y política: revistas feministas 6 Judith Lorber fue remplazada en 1990 por Margaret L. Andersen, la tercera editora fue Beth E. Schneider (1996-1999), la cuarta Christine Bose (2000-2003), en 2004 toma el puesto Christine L. Williams y en 2008 la edición estuvo a cargo de Dana M. Britton. Investigaciones Feministas 194 V l 7 Nú 2 (2016) 179 202 6 Judith Lorber fue remplazada en 1990 por Margaret L. Andersen, la tercera editora fue Beth E. Schneider (1996-1999), la cuarta Christine Bose (2000-2003), en 2004 toma el puesto Christine L. Williams y en 2008 la edición estuvo a cargo de Dana M. Britton. Investigaciones Feministas 194 Vol. 7 Núm 2 (2016) 179-202 corresponde a artículos mixtos. De acuerdo con la distribución de artículos en la revista Hypatia no existe mucha colaboración entre sus autoras, ya que 85,14% de los artículos fueron escritos individualmente. En el caso de la colaboración entre dos personas hay 34 artículos escritos por mujeres (4,28% de los artículos) y tres artículos de dos hombres (0,38% de los artículos). Los artículos mixtos de un hombre y una mujer no son tampoco frecuentes, con un 1,38%. En cuanto a la cooperación de tres personas, solo se encuentra un artículo que fue realizado por tres mujeres. Como puede observarse, hay un artículo de nueve personas (siete mujeres y dos hombres) lo que es una excepción en la revista, ya que no hay trabajos en colaboración de más de tres personas. La colaboración de los hombres y de las mujeres en la revista parece cambiar rápidamente, lo que parece ir de la mano de su mayor prestigio y visibilidad. Al inicio de la investigación Hypatia no formaba parte de las revistas del Journal Citation Report, y desde su inclusión en 2011, sus niveles de impacto la sitúan inmediatamente arriba de FS y a la par de revistas como Signs. 193 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Tabla 6. Distribución de artículos según número de personas y sexo en Hypatia (1971-2005) Fuente: Elaboración propia. 3.3.GENDER AND SOCIETY Nº. de personas por artículo Total de artículos Nº. de artículos realizados por hombres % Nº. de artículos realizados por mujeres % Nº. de artículos Mixtos % % Total 1 744 68 8,56 676 85,14 93,7 2 48 3 0,38 34 4,28 11 1,38 6,04 3 1 - - 1 0,13 - - 0,13 4 - - - - - - - - 5 - - - - - - - - 6 - - - - - - - - 7 - - - - - - - - 8 - - - - - - - - 9 1 - - - 1 0,13 0,13 Total 794 71 8,94 711 89,55 12 1,51 100 . Distribución de artículos según número de personas y sexo en Hypatia (1971-2005) Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 193 Artemisa Flores Espínola ( ), ( ), p L. Williams y en 2008 la edición estuvo a cargo de Dana M. Britton. g Vol. 7 Núm 2 (2016) 179-202 Artemisa Flores Espínola Academia y política: revistas feministas La revista Gender & Society fue la primera publicación internacional de sociología dedicada al estudio del género fundada en 1987. La revista es interdisciplinaria y acepta trabajos de otras disciplinas afines como la antropología, economía, historia, ciencia política y psicología social. La revista es la publicación oficial de Sociologists for Women in Society y se define como una revista centrada en el estudio social y estructural del género como categoría principal de análisis. Desde la creación de la revista, siempre han sido mujeres las editoras. La primera editora y creadora fue Judith Lorber6 y en la actualidad este puesto lo tiene Jo Rogers. El número de artículos en la revista es de N=610. Estos artículos fueron escritos a partir de 888 contribuciones (761 de mujeres y 127 de hombres). En términos generales, en esta revista 81,64% de los trabajos son firmados por mujeres, 7,06% por hombres y 11,23% de los artículos son escritos en colaboración mixta (tabla 7). Un 60% de los artículos son firmados por una mujer y el 25,58% corresponden a la colaboración de dos mujeres (17,88%) o de una mujer con un hombre (7,70%). La revista comprende un 2,29% de artículos de tres mujeres y varios artículos realizados por cinco y siete mujeres. Tabla 7. Distribución de artículos según el número de personas y sexo en G&S (1987-2005) No. de personas por artículo Total de artículos No. de artículos realizados por hombres % No. de artículos realizados por mujeres % No. de artículos Mixtos % % Total 1 404 38 6,23 366 60,00 - 66,23 2 161 5 0,83 109 17,88 47 7,70 26,41 3 30 - 14 2,29 16 2,62 4,91 4 9 - 6 0,98 3 0,49 1,47 5 3 - 1 0,16 2 0,33 0,49 6 - - - - 7 3 - 2 0,33 1 0,16 0,49 Total 610 43 7,06 498 81,64 69 11,3 100 Fuente: Creación propia. abla 7. Distribución de artículos según el número de personas y sexo en G&S (1987-2005) En lo que se refiere a los hombres, 33,9% de sus contribuciones (43/127) 194 Artemisa Flores Espínola Academia y política: revistas feministas corresponden a artículos realizados individualmente o en colaboración con otro hombre y esas 43 contribuciones representan 7,06 % de los artículos. Artemisa Flores Espínola Entonces, en esta revista, los hombres contribuyen mayoritariamente en el marco de una colaboración mixta (66,1% de sus contribuciones) pero esas contribuciones representan solamente 11,3 % de todos los artículos. Los artículos mixtos de tres personas fueron realizados por 27 contribuciones de mujeres y 21 de hombres y representan el 2,62% de todos los artículos. Los datos señalan que existe una fuerte colaboración entre autores y autoras en la revista y que se observa en el porcentaje relativamente elevado de artículos de tres (4,91%) y cuatro personas (1,47%). Si bien los datos anteriores permiten conocer la forma más frecuente de publicación entre autores y autoras y su colaboración; parece también importante analizar el número de artículos publicados por persona con el fin de saber si se trata de un número grande de autores y autoras ocasionales con un solo artículo, o de personas con un alto grado de productividad en las revistas. 4. GÉNERO Y PRODUCTIVIDAD CIENTÍFICA EN LAS REVISTAS ACADÉMICAS FEMINISTAS El interés por examinar la productividad científica en las revistas no es solamente para conocer quiénes publican con más frecuencia en cada revista, sino analizar también las líneas editoriales de las revistas. Una revista en la que la mayoría de las autoras u autores son ocasionales puede indicar por ejemplo una mayor apertura, en cambio, una revista en la que una misma persona puede publicar con frecuencia puede considerarse como endogámica. En la siguiente tabla (8) se observa la distribución de artículos según el número de autoras en las tres revistas generalistas. De las 751 mujeres que publicaron en Feminist Studies, la mayoría son autoras ocasionales (87,88%) con un solo artículo. Se observa que 9,32% de las autoras publicaron dos artículos y pocas pudieron contar con tres o cuatro artículos. Las siete autoras (0,93% de todas ellas) que escribieron cuatro artículos en la revista son Alicia Ostriker, Judith Kegan Gardiner, Judith R. Walkowitz, Judith Stacey, Mariana Valverde, Rachel Blau DuPlessis y Susan Stanford Friedman. De forma similar, en Signs de las 1.158 autoras el 87,65% publicó también un solo artículo en la revista y el 9,67% dos artículos. El porcentaje de las autoras que publicaron tres trabajos es de 1,98% y el de las autoras con 4 artículos en la revista es de 0,35% y que corresponde a cuatro autoras (Janice Haaken, Josephine Donovan, Marysa Navarro y Myra H. Strober). Las autoras con mayor productividad en Signs fueron Hanna Papanek, Judith Kegan Gardiner, Leila J. Rupp y Sandra Harding (con cinco artículos cada una). Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 195 Academia y política: revistas feministas Artemisa Flores Espínola Tabla 8. Distribución de artículos según el número de autoras en las revistas generalistas No. de artículos por persona Total de artículos FS % Total de artículos Signs % Total de artículos WSIF % 1 660 87,88 1.015 87,65 1.181 87,48 2 70 9,32 112 9,67 125 9,26 3 14 1,87 23 1,98 25 1,86 4 7 0,93 4 0,35 7 0,52 5 - - 4 0,35 6 0,45 6 - - - - 3 0,22 7 - - - - 1 0,07 8 - - - - 1 0,07 9 - - - - 1 0,07 751 (870) 100 1.158 (1344) 100 1.350 (1.606) 100 Fuente: Creación propia. la 8. Distribución de artículos según el número de autoras en las revistas generalistas Fuente: Creación propia. Fuente: Creación propia. 4. GÉNERO Y PRODUCTIVIDAD CIENTÍFICA EN LAS REVISTAS ACADÉMICAS FEMINISTAS La mayoría de las autoras en WSIF publicaron un solo artículo (87,48%) y un 9,26% lo hizo dos veces. No se observan muchas mujeres con tres artículos (1,86%), sin embargo, cuenta con tres autoras con siete, ocho y nueve artículos en la revista (Renate D. Klein, Liz Stanley y Lynda I. Birke). Los datos (tabla 9) muestran que ningún autor publicó dos veces en FS, en cambio, tres autores publicaron dos veces en WSIF (Brian Burkitt, Craig M. Gurney y Orland W. Wooley). La situación es diferente en Signs donde si bien se observa que una gran mayoría de autores (94,96%) publica un artículo de forma ocasional, cinco autores publicaron dos veces y Richard W. McCormick publicó tres artículos en esta revista. De la misma forma que en las revistas generalistas, en las revistas especializadas una mayoría de autoras y autores son ocasionales, sin embargo, ciertas autoras lograron publicar hasta 12 y 14 artículos, como en el caso de Hypatia y PWQ (tabla 10). 196 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Academia y política: revistas feministas Artemisa Flores Espínola Artemisa Flores Espínola Tabla 9. Distribución de artículos según el número de autores en las revistas generalistas No. de artículos por persona Total de artículos FS % Total de artículos Signs % Total de artículos WSIF % 1 35 100 113 94,96 46 93,9 2 - - 5 4,20 3 6,1 3 - - 1 0,84 - - 35 (35) 100 119 (126) 100 49 (52) 100 Fuente: Creación propia. abla 9. Distribución de artículos según el número de autores en las revistas generalistas Tabla 10. Distribución de artículos según el número de mujeres en las tres revistas especializadas No. Academia y política: revistas feministas Academia y política: revistas feministas Artemisa Flores Espínola Academia y política: revistas feministas 12 13 14 - 2 2 - 0,15 0,15 1 - - 0,18 - - - - - - - - 1.345 100 552 100 639 100 Fuente: Creación propia. Fuente: Creación propia. En PWQ se observa una mayoría de autoras ocasionales con un solo artículo (84,03%) o dos (9,66%). Una minoría logró publicar más de tres o cuatro artículos, sin embargo, se encontraron algunas grandes productoras (es decir, autoras con 10 o más artículos): Abigail J. Stewart con 10 artículos; Gloria Cowan, Janice D. Yoder y Leticia Anne Peplau que cuentan con 11; Jayne E. Stake y Mary P. Koss con 13; y Janet Shibley Hyde y Nancy Felipe Russo con el récord de 14 artículos publicados. En Hypatia las autoras pueden publicar con mayor frecuencia que en todas las otras revistas de la muestra. Se observa que el 14,3% de las autoras han publicado dos veces y el 5% logró hacerlo hasta tres veces. Un 1,27% de mujeres tienen cuatro artículos publicados y el récord con 10 y 12 artículos lo tienen Penelope Deutscher y Claudia Card. En G&S una gran mayoría de autoras (86,22%) cuenta con una sola publicación, mientras 10,33% de ellas han publicado dos veces y el 2,66% cuenta con tres publicaciones. Se puede apreciar que hay dos autoras (Irene Padovic y Janeen Baxter) que tienen cuatro artículos publicados. En la revista hay tres autoras que publican con más frecuencia que las otras, como Patricia Yancey Martin que ha publicado cinco veces, Christine L. Williams que fue editora de la revista y aparece con seis publicaciones o Myra Marx Ferree que cuenta con el mayor número de artículos publicados (ocho artículos). En el caso de la distribución de artículos según el número de autores en las revistas especializadas se observan menos diferencias que en el caso de las autoras (tabla 11). Una diferencia importante en la revista PWQ, ya que a pesar de que la mayoría publicó una sola vez (88,14%), hay un 9,62% que cuenta con dos artículos, un autor publicó tres veces (0,32%) y otros cuatro artículos (lo cual es poco usual). Sin embargo, lo que más resalta de los datos (tabla 11) es un autor en la revista que publica regularmente, ya que cuenta con nueve publicaciones (Arnold S. Kahn). 4. GÉNERO Y PRODUCTIVIDAD CIENTÍFICA EN LAS REVISTAS ACADÉMICAS FEMINISTAS de artículos por persona N° de autoras PWQ % N° de autoras Hypatia % Nº de autoras G&S % 1 1.130 84,03 428 77,54 551 86,22 2 130 9,66 79 14,31 66 10,33 3 34 2,53 28 5,07 17 2,66 4 17 1,26 7 1,27 2 0,31 5 10 0,74 4 0,73 1 0,16 6 6 0,45 3 0,54 1 0,16 7 4 0,30 1 0,18 - - 8 1 0,07 - - 1 0,16 9 5 0,37 - - - - 10 1 0,07 1 0,18 - - 11 3 0,22 - - - - istribución de artículos según el número de mujeres en las tres revistas especializadas Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 197 Academia y política: revistas feministas En Hypatia, se observa también que la mayoría de los autores son ocasionales (88,31%), pero un 10% publicó dos veces y sólo uno pudo hacerlo tres veces (Larry May). Este autor realizó sus trabajos en colaboración con otro hombre y los tres artículos tratan sobre masculinidad. 198 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Academia y política: revistas feministas Artemisa Flores Espínola Tabla 11. Distribución de artículos según el número de hombres en las tres revistas especializadas No. de artículos por persona Total de artículos PWQ % Total de artículos Hypatia % Total de artículos G&S % 1 275 88,14 68 88,31 98 88,29 2 30 9,62 8 10,39 11 9,91 3 4 5 6 7 8 9 1 5 - - - - 1 0,32 1,60 - - - - 0,32 1 - - - - - - 1,30 - - - - - - 1 1 - - - - 0,90 0,90 - - - - 312 100 77 100 111 100 Fuente: Creación propia. 11. Distribución de artículos según el número de hombres en las tres revistas especializadas Fuente: Creación propia. Fuente: Creación propia. Finalmente, se puede observar que una mayoría de los autores en Gender & Society son ocasionales (88,29%) con un solo artículo publicado, el 9,91% cuenta con dos artículos y dos autores aparecen con tres y cuatro artículos: Erick Olin Wright y Michael A. Messner. participación de hombres y de nivel de impacto. participación de hombres y de nivel de impacto. participación de hombres y de nivel de impacto. Las tres revistas especializadas nacieron como consecuencia del feminismo académico y dentro de ciertas disciplinas marcando claras diferencias entre ellas y con las generalistas. En comparación con las revistas generalistas las tres revistas especializadas cuentan con una mayor participación de hombres. G&S y PWQ cuentan también con elevados niveles de impacto, no sólo comparadas con las revistas feministas sino también en otras disciplinas (Flores Espínola, 2011). Algunos autores y autoras sugieren que la producción científica se encuentra vinculada con el nivel de colaboración (Kyvik y Taigen, 1996; Scott Long, 1990) y este es un estilo de trabajo mucho más común en sociología y psicología que en filosofía o en las revistas feministas generalistas. La colaboración se encuentra a su vez ligada al tipo de metodologías utilizadas en cada una de las revistas, que son producto también del contexto histórico, así como de los dictados de las diferentes disciplinas. La colaboración en las revistas feministas generalistas es baja en comparación con las revistas especializadas, salvo para el caso de Hypatia, que cuenta también con una muy baja colaboración como suele ser el caso de las revistas de filosofía. De las revistas feministas WSIF es la que cuenta con la mayor proporción de artículos en colaboración entre autoras y autores, mientras que Signs cuenta con la más alta colaboración entre mujeres. En cambio, en las revistas Hypatia y FS se observó poca colaboración en general. La menor colaboración en las revistas generalistas tiene que ver en gran medida con el componente teórico de los artículos. Desde un punto de vista metodológico podemos decir que PWQ (1977) es una revista con un estilo de escritura científica habitual en el que el autor o autora desaparece y en donde la experiencia personal no es usada como recurso. Los artículos en PWQ utilizan con frecuencia escalas psicométricas, son breves y descriptivos. Parlee (1991) cuestiona que los estudios realizados sobre la revista hayan pasado por alto aspectos metodológicos importantes como por ejemplo que una mayoría de artículos utilizan cuestionarios cerrados como el único método de obtener los datos. Las personas que escriben en G&S hacen más recurso de la experiencia personal en sus publicaciones, pero sigue apareciendo un número importante de trabajos empíricos descriptivos basados en cuestionarios. Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 5. CONCLUSIONES Las primeras publicaciones feministas surgen como consecuencia de los movimientos sociales y políticos que tuvieron lugar en la década de los setenta en diferentes países. Estas primeras revistas en fundarse son las que cuentan con la participación de hombres más baja y con los niveles de impacto más bajos, con excepción de PWQ que cuenta con unas características diferentes ligadas en gran parte a su disciplina. A diferencia de FS y WSIF que buscaron desde sus inicios poder combinar el activismo con la academia, Signs nace en el mundo académico, no del movimiento de mujeres, lo que le da de entrada una legitimidad y prestigio académico que las otras no tienen. Las otras dos revistas han tenido que esforzarse para continuar, sobre todo con las importantes críticas realizadas por el movimiento de mujeres ante la institucionalización y es por esta razón que Signs cuenta con niveles más elevados de 199 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Artemisa Flores Espínola Academia y política: revistas feministas mujeres con 14 artículos en PWQ. Como hemos podido observar las revistas son distintas entre sí y esto explica en parte que sea difícil encontrar un patrón claro de participación de autores o autoras o sobre la colaboración. La participación de los hombres en las revistas feministas es minoritaria y no parece cambiar mucho con el paso del tiempo. El presente estudio puede ser completado con un estudio futuro sobre la producción científica en revistas feministas en otros países y en diferentes áreas. También sería interesante analizar las temáticas tratadas en las revistas académicas feministas y el tipo de métodos utilizados por los hombres y las mujeres en las revistas ya que ciertos estudios afirman un vínculo o conexión entre el sexo y el método. No es de sorprender las diferencias en los niveles de impacto de las revistas feministas con respecto a las revistas especializadas, ya que no cuentan todavía con el prestigio alcanzado por otras y su problema para abrirse espacios se encuentra relacionado con la renuencia de la corriente dominante (en su mayoría hombres) a incluir las contribuciones feministas. El menor factor de impacto también puede explicarse por el hecho de que los estudios feministas son de reciente creación y como otras especialidades se enfrentan con la dificultad de ser considerados como relevantes. Academia y política: revistas feministas Academia y política: revistas feministas Academia y política: revistas feministas participación de hombres y de nivel de impacto. Las políticas editoriales han cambiado con el tiempo y actualmente los artículos son presentados bajo un formato claro: una presentación de la problemática, los métodos y el diseño de investigación, los resultados y conclusiones. Como se observó, la colaboración en la revista es importante pero no mayoritaria, ya que los trabajos individuales representaron 66,2% de los artículos. En general, la mayor parte de las publicaciones en todas las revistas feministas son realizadas por autoras y autores ocasionales. Sin embargo, se observan ciertas diferencias entre las revistas feministas generalistas y las especializadas. Si bien WSIF cuenta con el mayor número de autoras frecuentes de las tres revistas generalistas con una autora que publicó nueve artículos, en las revistas especializadas, se observó una mujer con ocho artículos en G&S, una mujer con doce artículos en Hypatia y dos 200 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Artemisa Flores Espínola Academia y política: revistas feministas REFERENCIAS BIBLIOGRÁFICAS COLE, JONATHAN R. Y HARRIET ZUCKERMAN (1984): The Productivity Puzzle: Persistence and Change in Patterns of Publication among Men and Women Scientists, En, Steimkamp M.W. y Maehr, eds., Advances in Motivation and Achievement, vol. 2, pp. 217-256, Greenwich, CT: JAI Press. FERBER, MARIANNE A. (1986): Citations: Are They an Objective Measure of Scholarly Merit?, Signs, Vol. 11, nº 2, 381-389. FLORES ESPINOLA, ARTEMISA (2013): Metodología feminista: ¿una transformación de prácticas científicas?, Madrid, Tesis doctoral, Universidad Complutense de Madrid. __ (2011): Mujeres y feminismo en ciencia y tecnología: un análisis de revistas científicas, En: Navarro, María, Estévez, Betty y Sánchez, Antolín, Claves actuales de pensamiento, coord., Madrid: Ed. Plaza y Valdés. __ (2005): Reflexiones Feministas en ciencia, Cuadernos del Centro Universitario de Estudios de Género (CUEG), Monterrey: Universidad Autónoma de Nuevo León. FOX, MARY FRANK (2005): Gender, Family Characteristics, and Publication Productivity among Scientists, Social Studies of Science, Vol. 35, nº 1, 131-150. GRANT, LINDA Y KATHRYN B. WARD (1991): Gender and Publishing in Sociology, Gender and Society, Vol. 5, nº 2, 207-223. 201 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202 Academia y política: revistas feministas Artemisa Flores Espínola KYVIK, SVEIN (1990): Motherhood and Scientific Productivity, Social Studies of Science, Vol. 20, nº 1, 149-60. KYVIK, SVEIN (1990): Motherhood and Scientific Productivity, Social Studies of Science, Vol. 20, nº 1, 149-60. KYVIK, SVEIN Y MARI TEIGEN (1996): Child Care, Research Collaboration, and Gender Differences in Scientific Productivity, Science, Technology & Human Values, Vol. 21, nº 1, 54-71. LARIVIERE, VINCENT, NI, CHAOQUN, GINGRAS, YVES, CRONIN, BLAISE Y SUGIMOTO, CASSIDY R. (2013) : Bibliometrics: Global gender disparities in science, Nature News, 11 de diciembre. LONG, J. SCOTT (2001): From Scarcity to visibility: Gender differences in the careers of doctoral scientists and engineers, Washington, D.C: National Academy Press. __ (1990) : The Origins of Sex Differences in Science, Social Forces, Vol. 68, nº 4, 1297-1316. LONG, J. SCOTT Y FOX, MARY FRANK (1995): Scientific Careers: Universalism and Particularism, Annual Review of Sociology, Vol. 21, pp. 45-71. MCDERMOTT, PATRICE (1994): Politics and Scholarship: Feminist Academic Journals and the Production of Knowledge, University of Illinois Press. PARLEE, MARY BROWN (1991): Happy birth-day to Feminism & Psychology, Feminism & Psychology, Vol. 1, nº 1, pp. 39-48. RIER, DAVID A. (2003): Gender, Lifecourse and Publication Decisions in Toxic- Exposure Epidemiology: ‘Now!’ versus ‘wait a minute!’, Social Studies of Science, Vol. 33, nº 2, pp. 269-300. REFERENCIAS BIBLIOGRÁFICAS SONNERT, GERHARD Y HOLTON, GERALD (1995): Gender Differences in Science Careers, New Brunswick, NJ: Rutdgers University Press. WARD, KATHRYN B. y GRANT, LINDA (1996): Gender and academic publishing. In J. Smart (Ed.), Higher education: Handbook of theory and research, Vol. 11, pp. 171–222, New York: Agathon. XIE, XU Y SHAUMAN, KIMBERLEE A. (2003): Women in Science: Career Processes and Outcomes, Cambridge: Harvard University Press. ZUCKERMAN, HARRIET, COLE, JONATHAN R. Y BRUER, JOHN. T. (cords.) (1991): The outer circle. Women in the scientific community, New York: W.W. Norton and Co. 202 Investigaciones Feministas Vol. 7 Núm 2 (2016) 179-202
https://openalex.org/W4280514563	https://www.aanda.org/articles/aa/pdf/2022/07/aa43418-22.pdf	English	null	The dynamical state of RXCJ1230.7+3439: A multi-substructured merging galaxy cluster	Astronomy & astrophysics	2,022	cc-by	13,600	ABSTRACT We analyse the kinematical and dynamical state of the galaxy cluster RXCJ1230.7+3439 (RXCJ1230), at z = 0.332 using 93 new spectroscopic redshifts of galaxies acquired at the Telescopio Nazionale Galileo and from SDSS DR16 public data. We study the density galaxy distribution retrieved from photometric SDSS multiband data and ﬁnd that RXCJ1230 appears as a clearly isolated peak in the redshift space, with a global line-of-sight (LOS) velocity dispersion of σv = 1004+147 −122 km s−1. Several tests applied to the spatial and velocity distributions reveal that RXCJ1230 is a complex system with the presence of three subclusters, located to the southwest, east, and south with respect to the main body of the cluster, containing several bright galaxies (BGs) in their respective cores. Our analyses conﬁrm that the three substructures are in a pre-merger phase, where the main interaction takes place with the southwest subclump, almost in the plane of the sky. We compute a velocity dispersion of σv ∼1000 and σv ∼800 km s−1 for the main cluster and the southwest substructure, respectively. The central main body and southwest substructure diﬀer by ∼870 km s−1 in the LOS velocity. From these data, we estimate a dynamical mass of M200 = 9.0±1.5×1014 M⊙and 4.4±3.3×1014 M⊙for the RXCJ1230 main body and southwest clump, respectively, which reveals that the cluster will undergo a merger characterised by a 2:1 mass ratio impact. We solve a two-body problem for this interaction and ﬁnd that the most likely solution suggests that the merging axis lies ∼17◦from the plane of the sky and the subcluster will fully interact in ∼0.3 Gyr. However, a slight excess in the X-ray temperature observed in the southwest clump conﬁrms a certain degree of interaction already. The comparison between the dynamical masses and those derived from X-ray data reveals good agreement within errors (diﬀerences ∼15%), which suggests that the innermost regions (< r500) of the galaxy clumps are almost in hydrostatical equilibrium. In summary, RXCJ1230 is a young but also massive cluster in a pre-merging phase accreting other galaxy systems from its environment. Key words. galaxies: clusters: individual: RXCJ1230.7+3439 – X-rays: galaxies: clusters R. Barrena1,2 , H. Böhringer3,4, and G. Chon4 R. Barrena1,2 , H. Böhringer3,4, and G. Chon4 1 Instituto de Astrofísica de Canarias, C/Vía Láctea s/n, 38205 La Laguna, Tenerife, Spain e-mail: rbarrena@iac.es Instituto de Astrofísica de Canarias, C/Vía Láctea s/n, 38205 La Laguna, Tenerife, Spain e-mail: rbarrena@iac.es 2 Universidad de La Laguna, Departamento de Astrofísica, 38206 La Laguna, Tenerife, Spain 3 Max-Planck-Institut für extraterrestrische Physik 85748 Garching Germany 2 Universidad de La Laguna, Departamento de Astrofísica, 38206 La Laguna, Tenerife, Spain 3 Universidad de La Laguna, Departamento de Astrofísica, 38206 La Laguna, Tenerife, Spain Max-Planck-Institut für extraterrestrische Physik, 85748 Garching, Germany 2 Universidad de La Laguna, Departamento de Astrofísica, 38206 La Laguna, Tenerife, Spai 3 Max-Planck-Institut für extraterrestrische Physik, 85748 Garching, Germany 3 Max-Planck-Institut für extraterrestrische Physik, 85748 Garching, Germany 4 Universitäts-Sternwarte München, Fakultät für Physik, Ludwig-Maximilian-Universität München, Scheinerstr. 1, 81679 München, Germany 4 Universitäts-Sternwarte München, Fakultät für Physik, Ludwig-Maximilian-Universität München, Scheinerstr. 1, 81679 München, Germany Received 24 February 2022 / Accepted 11 May 2022 Received 24 February 2022 / Accepted 11 May 2022 Astronomy & Astrophysics Astronomy & Astrophysics Astronomy & Astrophysics A&A 663, A78 (2022) https://doi.org/10.1051/0004-6361/202243418 c⃝R. Barrena et al. 2022 A&A 663, A78 (2022) https://doi.org/10.1051/0004-6361/202243418 c⃝R. Barrena et al. 2022 Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This article is published in open access under the Subscribe-to-Open model. Subscribe to A&A to support open access publication. A78, page 1 of 11 pen Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This article is published in open access under the Subscribe-to-Open model. Subscribe to A&A to support open access publication. A 1. Introduction (2009) and Hao et al. (2010). RXCJ1230 contains a strong X-ray point source in the north of the cluster associated with the NVSS 123050+344257 radio galaxy, at the redshift of the cluster. procedure yields radial velocity estimates and the corresponding errors due to the correlation technique applied. After rejecting the spectra with lower signal-to-noise ratio (S/N), we obtained 81 spectroscopic redshifts. In addition, we also consider 12 red- shifts retrieved from the SDSS DR16 spectroscopic database present in the region sampled by the two-mask ﬁeld of view around RXCJ1230. To date, there is little spectroscopic information on RXCJ1230 available in the literature and databases. For instance, only 15 spectroscopic redshifts are reported by SDSS-DR16 within a region of 15′ radius with respect to the centre of the cluster, which is insuﬃcient to perform any detailed dynami- cal study. We therefore recently carried out multiobject spectro- scopic observations at the TNG 3.5m telescope, obtaining new redshift data for 81 galaxies in the ﬁeld of RXCJ1230. In addi- tion, we also include photometric information retrieved from SDSS-DR16 and Pan-STARRS1 imaging archives. These data, together with X-ray information, will allow us to investigate the kinematics and dynamics of RXCJ1230, obtaining satisfactory answers for questions such as whether or not this is a merging cluster, whether it is in a pre- or a post-merger phase, and how well X-ray and dynamic mass estimates match. Here, we clarify the dynamical stage of RXCJ1230. A detailed comparison between redshifts derived from mul- tiple measures of the same target (obtained from two diﬀerent estimations in the two masks, or even between SDSS redshift and our estimate), we see that the nominal velocity errors provided by the cross-correlation technique are too small. Therefore, in order to convert this error into a realistic value, considering sys- tematic errors, we need to multiply it by a factor of 2 (see e.g. Boschin et al. 2013). Table 1 lists the full spectroscopic sample considered in this work (see also Fig. 1). Col. 1 lists an ID number (clus- ter members are indicated), Cols. 2 and 3 report the equatorial coordinates of galaxies in the J2000 system, Col. 4 the helio- centric radial velocity (v = cz) with errors (∆v), and Cols 5 and 6, the complementary photometric information (r′ and i′ dered magnitudes) retrieved from SDSS DR16. The last column includes some comments regarding particular features of some galaxies. 2 dered magnitudes are the extinction-corrected values following Schlegel et al. (1998) reddening maps. 3 See https://www.sdss.org/dr12/imaging/other_info/ 4 See https://ps1images.stsci.edu/cgi-bin/ps1cutouts 1. Introduction multi-wavelength observations provide a more complete view of the reality of GCs. According to the hierarchical structure formation scenario, galaxy clusters (GCs) are the youngest bound systems in our Universe. The cold dark matter model together with the the- ory of cosmic inﬂation predicts the initial conditions for the structure formation (see e.g. Springel 2005), where clusters form in the deepest potential wells generated by the dark matter (DM) overdensities. GCs contain multiple components. In addition to DM, haloes include baryonic matter in diﬀer- ent forms (see e.g. Allen et al. 2011). Cold and hot gas and non-thermal plasma constitute the intra-cluster medium (ICM), which highly reacts in collision processes, while the galac- tic component is less aﬀected in merger events. This multi- component nature allows us to analyse GCs through diﬀerent wavelengths, given that diﬀerent physical processes take place in each case. For example, we use X-rays and radio observa- tions to probe the ICM (Loewenstein 2003; Böhringer & Werner 2010; van Weeren et al. 2019), while visible and infrared (IR) data are used to analyse the galactic behaviour (see Biviano 2000, for a review). On the other hand, DM is better studied through weak-lensing techniques (Umetsu 2000), therefore the X-ray observations are often used to investigate the dynam- ical state of GCs. However, optical information is essential for studying the dynamics of cluster mergers (Golovich et al. 2019). The spatial distribution (obtained from photometric observa- tions) and kinematics (retrieved using spectroscopic redshifts) of galaxy members allow us to identify substructures and to analyse possible pre- and post-merging scenarios. Moreover, optical data complement the X-ray information because ICM and galaxies react on diﬀerent timescales during a collision (Roettiger et al. 1997), hence the importance of combining X-ray and optical data. In this context, we analyse in this work the dynamical state of the RXCJ1230.7+3439 (hereafter RXCJ1230) cluster of galaxies using X-ray and optical data. RXCJ1230 was discovered using X-ray data by Appenzeller et al. (1998) under the designation ATZ98- D219 and by Böhringer et al. (2000) as part of the NORAS survey, with a redshift of z = 0.333. This cluster was also detected through its Sunyaev-Zeldovich (SZ) signal in the second Planck cluster catalogue (Planck Collaboration XXVII 2016). It was also detected in the Northern Sky Cluster Survey A&A 663, A78 (2022) (Gal et al. 2003) and in the Sloan Digital Sky Survey (SDSS) by Wen et al. 1. Introduction This paper is organised as follows. We describe the new spec- troscopic observations and data samples in Sect. 2. In Sect. 3 we present our results about the selection of galaxy members, velocity and spatial distributions, and substructures. In Sect. 4, we present global properties, dynamical masses of the diﬀerent structures, and a comparison with X-ray properties. In Sect. 5, we analyse the 3D dynamics of the complex and propose a plau- sible pre-merging scenario for RXCJ1230. At the end of this paper, in Sect. 6, we summarise our results and present our con- clusions. Our spectroscopic catalogue includes a total of 93 galaxy redshifts in a region of 9′ × 10′ arcmin (see Fig. 1, left panel). The MOS mask design was initially planned to cover the dens- est galaxy regions more eﬃciently. The majority of the spectro- scopic redshifts therefore follow an elongated region in the NE– SW direction. Our full redshift sample presents a median S/N and cz error of 8 and 82 km s−1, respectively. We detect 12 star forming galaxies characterised by the presence of the [OII] emission line. In this paper, we assume a ﬂat cosmology with Ωm = 0.3, ΩΛ = 0.7 and H0 = 70 h70 km s−1 Kpc−1. Under this cosmol- ogy, 1 arcmin corresponds to 287 h−1 70 Mpc at the redshift of the cluster. 2.2. Optical photometry We complement our redshift sample with photometric informa- tion retrieved from the SDSS DR16 database. We consider dered r′ and i′ magnitudes2. Galaxy counts in this region reveal the photometric SDSS sample is ∼90% complete for galaxies down to a magnitude of r′ = 21.5, which is in agreement with the mean SDSS DR12 depth estimations3. Comparing the spectro- scopic and photometric samples in the area covered by MOS masks, we ﬁnd that the completeness of the spectroscopic sam- ple is ∼55% for galaxies down to magnitude r′ = 21. However, we are able to obtain redshifts even for galaxies with r′ > 21.5. On the other hand, Pan-STARRS1 data archive4 was only used in order to retrieve RGB images and overplot density contours and galaxies with spectroscopic redshifts (see Fig. 1). 2.1. Optical spectroscopy We performed multi-object spectroscopic (MOS) observations of RXCJ1230 at the 3.5m TNG telescope in 2020 March, map- ping a region of about 10′ × 10′ with two MOS masks and including a total of 92 slits. We used the DOLORES spectro- graph and the LR-B grism1, which oﬀers a wavelength cover- age of between 370 and 800 nm with a spectral resolution of 2.75 Å per pixel. The total integration time was 3600 s per mask, divided into two exposures of 1800 s each. The combination of these two acquisitions allowed us to correct the spectra for cosmic rays. The spectra were extracted using standard IRAF packages. The radial velocity computation was performed using the cross- correlation technique developed by Tonry & Davis (1979) and implemented as the task RVSAO.XCSAO in IRAF environment. This procedure correlates the features detected in the observed spectra (mainly Ca H and K doublet, Hδ, G band, MgI, in absorp- tion and the most relevant emission lines such as OII, OIII dou- blet, Hα, Hβ and Hδ) with that present in the templates spectra. We used ﬁve diﬀerent reference spectra of the Kennicutt Spec- trophotometric Atlas of Galaxies (Kennicutt 1992), for ﬁve dif- ferent morphologies (Elliptical, Sa, Sb, Sc and Irr types). This 1 See http://www.tng.iac.es/instruments/lrs 2.3. Complementary X-ray data The XMM-Newton observations (ID 0841900101) and their data analysis, which complete our multi-wavelength study, are described in detail in Böhringer et al. (2022). Here, we only use X-ray data for a qualitative and morphological analysis. We use the 0.5 to 2.0 keV band, which provides the highest S/N above the background. In the present work we perform two minor mod- iﬁcations to the raw X-ray image. Firstly, we remove the point 1 See http://www.tng.iac.es/instruments/lrs A78, page 2 of 11 R. Barrena et al.: The dynamical status of RXCJ1230 cluster of galaxies Table 1. Velocity catalogue of 93 galaxies measured spectroscopically in the RXJ1230 ﬁeld. Table 1. continued. ab e . Ve oc ty cata ogue o 93 ga a es easu ed spect oscop ca y in the RXJ1230 ﬁeld. 2.3. Complementary X-ray data ID RA & Dec (J2000) v ± ∆v r′ i′ Notes RA = 12:mm:ss.ss (km s−1) Dec = +34:mm:ss.s 1⋆ 30:17.02 34:22.3 98 389 ± 102 19.69 19.25 2 30:19.11 40:59.0 90 506 ± 77 19.78 19.22 3⋆ 30:22.18 36:37.2 99 651 ± 62 18.86 18.22 4⋆ 30:22.86 36:44.4 100 135 ± 79 20.66 20.14 5⋆ 30:23.72 39:40.5 97 351 ± 94 19.21 18.77 ELG 6 30:23.17 40:41.3 118 366 ± 76 19.55 19.12 ELG 7⋆ 30:24.45 40:01.7 97 405 ± 82 20.63 20.07 8 30:25.53 40:28.5 90 865 ± 85 19.04 18.43 ELG 9⋆ 30:26.53 36:01.1 100 299 ± 68 20.39 19.89 10⋆ 30:26.00 37:23.0 100 012 ± 103 21.04 20.47 11⋆ 30:27.68 40:49.8 98 300 ± 100 20.75 20.33 12⋆ 30:27.16 37:30.3 98 085 ± 31 20.22 19.68 13⋆ 30:28.11 34:51.2 98 441 ± 142 20.57 20.16 14⋆ 30:28.03 35:42.0 99 284 ± 78 21.07 20.75 15⋆ 30:28.63 37:35.5 99 494 ± 60 19.73 19.16 16⋆ 30:28.61 37:41.4 100 177 ± 85 19.53 18.97 17⋆ 30:28.36 37:52.8 97 806 ± 98 20.80 20.37 18⋆ 30:28.78 40:12.7 98 013 ± 76 20.46 19.87 19 30:28.96 41:20.4 118 244 ± 55 20.15 19.52 ELG 20⋆ 30:29.28 38:01.3 98 445 ± 70 20.46 19.83 21⋆ 30:29.54 38:06.9 97 959 ± 16 18.07 17.50 BG-W (2) 22⋆ 30:30.55 38:01.4 98 007 ± 18 17.90 17.33 BG-W (1) 23 30:31.78 41:28.7 90 405 ± 145 20.24 19.61 24⋆ 30:32.80 38:11.5 98 538 ± 92 20.59 20.10 25⋆ 30:33.48 38:19.5 100 904 ± 116 19.95 19.51 26⋆ 30:33.73 38:32.7 98 418 ± 54 19.53 19.03 27⋆ 30:35.37 38:27.4 98 488 ± 86 20.60 20.17 28 30:36.83 38:41.1 139 900 ± 100 21.98 21.71 ELG 29⋆ 30:37.75 36:16.5 101 460 ± 85 19.92 19.37 30⋆ 30:38.15 34:58.3 99 530 ± 100 20.70 20.21 31⋆ 30:38.52 35:48.8 100 702 ± 118 20.72 20.14 32⋆ 30:38.80 39:55.4 102 345 ± 100 19.86 19.20 33⋆ 30:38.19 36:18.8 98 484 ± 34 20.67 20.09 34⋆ 30:38.21 38:06.3 100 291 ± 25 19.92 19.38 35 30:39.41 34:36.2 86 666 ± 111 21.04 20.55 36⋆ 30:39.73 39:22.6 99 681 ± 51 20.28 19.68 37 30:39.18 35:55.6 156 900 ± 100 21.89 21.63 ELG 38⋆ 30:39.97 39:32.3 101 073 ± 115 19.72 19.14 39⋆ 30:40.75 35:29.6 99 991 ± 93 20.25 19.63 40⋆ 30:41.59 34:12.3 98 373 ± 81 19.33 18.94 41⋆ 30:41.64 39:51.4 99 151 ± 67 20.61 20.13 42 30:41.18 41:48.5 112 903 ± 63 20.32 20.12 ELG 43⋆ 30:42.20 41:40.3 101 134 ± 182 19.91 19.33 44⋆ 30:42.48 36:13.5 98 196 ± 89 20.39 19.85 45 30:42.48 36:30.5 157 618 ± 100 20.92 20.19 ELG 46⋆ 30:42.57 37:31.2 99 913 ± 157 20.53 20.01 47⋆ 30:42.12 38:01.7 99 099 ± 61 20.21 19.67 48⋆ 30:42.47 40:24.3 100 238 ± 98 19.70 19.22 49 30:43.81 35:12.0 103 864 ± 68 18.19 17.72 50⋆ 30:43.73 36:27.2 100 334 ± 105 20.35 19.76 51⋆ 30:43.56 36:06.1 100 379 ± 107 20.55 20.12 52⋆ 30:43.93 39:21.2 100 007 ± 35 20.47 19.94 53⋆ 30:44.95 38:46.7 99 914 ± 107 20.58 20.07 Notes. 2.3. Complementary X-ray data Asterisk in Col. 1 (ID) indicates the galaxies selected as cluster members. ab e . co t ued. 2.3. Complementary X-ray data ID RA & Dec (J2000) v ± ∆v r′ i′ Notes RA = 12:mm:ss.ss (km s−1) Dec = +34:mm:ss.s 54 30:44.83 37:50.8 112 918 ± 101 20.07 19.80 ELG 55⋆ 30:44.47 39:38.7 100 638 ± 87 19.49 18.87 56⋆ 30:44.82 40:58.1 99 794 ± 62 20.17 19.52 57⋆ 30:45.65 40:18.0 99 754 ± 88 20.80 20.28 58⋆ 30:45.57 35:41.8 102 128 ± 68 20.45 19.90 59⋆ 30:45.92 38:19.0 100 622 ± 70 19.60 19.06 60⋆ 30:45.78 39:26.3 100 064 ± 28 18.49 17.89 BCG 61⋆ 30:47.98 36:56.7 99 109 ± 78 18.69 18.10 BG-S 62⋆ 30:47.93 37:03.7 96 570 ± 100 20.80 20.74 ELG 63⋆ 30:47.78 43:26.5 100 517 ± 86 19.54 18.98 64⋆ 30:48.41 37:11.3 99 457 ± 77 20.32 19.75 65⋆ 30:48.35 36:48.7 99 042 ± 108 21.82 21.26 66⋆ 30:48.52 36:58.9 99 102 ± 145 21.27 20.93 67⋆ 30:48.83 37:07.7 99 103 ± 55 20.68 20.17 68⋆ 30:48.50 38:11.8 99 959 ± 83 19.55 19.06 69⋆ 30:48.41 38:47.2 102 209 ± 60 21.19 20.52 70⋆ 30:48.66 39:08.4 99 497 ± 63 21.17 20.57 71⋆ 30:48.60 42:27.7 99 761 ± 63 19.60 19.08 72 30:48.06 42:37.2 63 400 ± 100 18.78 18.44 73⋆ 30:49.14 37:17.7 98 558 ± 88 20.36 19.98 74⋆ 30:49.72 40:33.5 99 387 ± 52 19.72 19.07 75⋆ 30:49.81 42:10.1 101 085 ± 77 21.03 20.39 76⋆ 30:49.43 41:25.4 99 249 ± 37 20.57 20.03 77⋆ 30:50.36 42:01.2 101 520 ± 100 20.58 20.11 78⋆ 30:50.67 42:53.5 100 907 ± 98 18.51 17.93 NVSS RG 79 30:51.83 36:20.4 90 272 ± 145 21.20 20.68 80⋆ 30:51.66 38:59.0 101 592 ± 49 19.63 18.94 ELG 81⋆ 30:51.07 40:48.1 100 908 ± 71 20.73 20.18 82⋆ 30:51.03 38:27.4 96 834 ± 39 20.35 19.83 83⋆ 30:52.32 43:18.4 100 868 ± 97 20.12 19.64 84⋆ 30:53.33 41:54.3 102 042 ± 90 19.23 18.81 ELG 85⋆ 30:54.56 37:42.9 101 422 ± 92 20.90 20.52 86 30:54.99 41:23.5 40 650 ± 100 21.49 21.04 87⋆ 30:55.30 41:31.8 99 746 ± 48 18.68 18.10 88 30:56.48 41:46.3 92 621 ± 165 20.46 19.77 89⋆ 30:57.96 39:23.5 101 676 ± 54 18.56 17.92 90⋆ 30:59.34 39:13.9 100 226 ± 19 19.51 18.92 91⋆ 31:01.05 38:09.1 97 834 ± 17 18.54 17.93 92⋆ 31:03.70 39:08.1 99 064 ± 20 18.64 18.05 93⋆ 31:04.67 40:08.7 99 113 ± 45 18.13 17.54 BG-E in the right panel of Fig. 2.3. Complementary X-ray data 1, overlaid to an optical colour com- posite image from the PanSTARSS survey (similarly as shown in Fig. 2 by Böhringer et al. 2022). Analysis of the X-ray spectra in the diﬀerent substructures of the cluster yields an intracluster plasma temperature of 4.7 ± 0.4 keV for the central main component, 4.4±0.6 keV for the south- western subcluster, and 3.3 +0.7 −0.6 keV for the eastern structure (Böhringer et al. 2022). These authors also ﬁnd that the tem- perature proﬁle for the main component is not very steep, with a polytropic index of between isothermal and 1.2, and none of the components have a cool core. From the temperature and the shape of the intracluster gas distribution, Böhringer et al. (2022) obtained a hydrostatic mass estimate of the cluster components. They combined this result with mass estimates based on scaling in the right panel of Fig. 1, overlaid to an optical colour com- posite image from the PanSTARSS survey (similarly as shown in Fig. 2 by Böhringer et al. 2022). g y g ) Analysis of the X-ray spectra in the diﬀerent substructures of the cluster yields an intracluster plasma temperature of 4.7 ± 0.4 keV for the central main component, 4.4±0.6 keV for the south- western subcluster, and 3.3 +0.7 −0.6 keV for the eastern structure (Böhringer et al. 2022). These authors also ﬁnd that the tem- perature proﬁle for the main component is not very steep, with a polytropic index of between isothermal and 1.2, and none of the components have a cool core. From the temperature and the shape of the intracluster gas distribution, Böhringer et al. (2022) obtained a hydrostatic mass estimate of the cluster components. They combined this result with mass estimates based on scaling relations of cluster mass with X-ray temperature, X-ray luminos- ity, total gas mass, and YX (the product of temperature and gas mass) to arrive at a consistent picture for the mass estimation; see Sect. 4.1 for a summary of X-ray mass and a comparison with the dynamical one. Notes. Asterisk in Col. 1 (ID) indicates the galaxies selected as cluster members. sources and emission from the NVSS 123050+344257 radio galaxy (ID 78) by masking them with circular apertures of 10–20 pixels radius. Secondly, we smooth the original image using a Gaussian ﬁlter with a FWHM = 12 arcsec. 3.1. Member selection and global properties To minimise the presence of interlopers, we applied a 2.7σv clip- ping in the cz coordinate, taking into account the radial pro- ﬁle of the expected velocity dispersion (Mamon et al. 2010). To this end, we applied an iterative method whereby, in a ﬁrst step, we ﬁnd the mean signiﬁcant peak in the velocity distribu- tion (v0 = ⟨cz0⟩) and estimate ﬁrst velocity dispersion (σ0 = σv,0) using the rms estimator. Considering these two values, in a second step, we select cluster members as galaxies with v < v0 ± 2.7σ0. In the ﬁnal step, we reﬁne the estimation of the mean cz of the cluster and re-evaluate the velocity dispersion σv of the cluster. This simple three-step procedure yields stable and converging values of ¯v and σv in a fourth and subsequent step. Figure 2 shows the redshift distribution of the galaxies listed in Table 1. Fig. 2. Galaxy redshift distribution. Dashed vertical lines delimit the redshift range including 77 galaxy members assigned to RXCJ1230 according to 2.7σv clipping. The velocity distribution in the cluster rest frame of the 77 cluster members selected is superimposed. The black curve represents the reconstruction of the velocity distribution as a Gaussian proﬁle, considering the σv computed using the biweight estimator and assuming all the galaxies belong to a single system. The velocity corresponding to the BCG is also marked. To select cluster members out of the 93 galaxies in our spec- troscopic sample, we followed a method based on the galaxy position in the 2D projected phase space (r, cz), where r is the projected distance from the cluster centre, and cz is the galaxy line-of-sight velocity (see Fig. 3, top panel). In this way, we select 77 galaxy members with a ¯v = 99658± 161 km s−1 (z = 0.3324) with an rms of 969 ± 130 km s−1 (errors at 95% conﬁdence leve [c.l.]) in the cluster rest frame. In order to verify these values, we also apply the bi-weight scale esti- mator (Beers et al. 1990) considering the 77 redshifts. We ﬁnd σv = 1004+147 −122 km s−1. Thus, both rms and bi-weight estimators produce results in perfect agreement within errors. However, in order to check how robust this estimate is, we study the varia- tion of σv with the distance to the centre of the cluster, which is taken to be the brightest cluster galaxy BCG) position. 2.3. Complementary X-ray data After this process, we obtain the X-ray surface brightness maps plotted as contours A78, page 3 of 11 A78, page 3 of 11 A&A 663, A78 (2022) Fig. 1. Left panel: RGB colour composite image obtained by combining g′-, r′-, and i′-band images of 13′ × 10′ ﬁeld of view from Pan-Starrs1 public archive. Circles and squares correspond to galaxy members and non-members, respectively, obtained from our spectroscopic observations and SDSS-DR16 spectroscopic database. Superimposed, we also show the contour levels of isodensity galaxy distribution of likely members (see Sect. 3.3). Right panel: same RGB image but overplotting the contour levels of the XMM-Newton image corresponding to the observation ID 0841900101. The X-ray contours were obtained after smoothing the original image using a Gaussian ﬁlter with σ = 6 arcsec. Point sources and emission from NVSS 123050+344257 radio galaxy (ID 78) have been removed, masking them with circular apertures of 10–20 pixels radius. In both panels, the BCG and BGs are also marked. North is up and east is left. Fig. 1. Left panel: RGB colour composite image obtained by combining g′-, r′-, and i′-band images of 13′ × 10′ ﬁeld of view from Pan-Starrs1 public archive. Circles and squares correspond to galaxy members and non-members, respectively, obtained from our spectroscopic observations and SDSS-DR16 spectroscopic database. Superimposed, we also show the contour levels of isodensity galaxy distribution of likely members (see Sect. 3.3). Right panel: same RGB image but overplotting the contour levels of the XMM-Newton image corresponding to the observation ID 0841900101. The X-ray contours were obtained after smoothing the original image using a Gaussian ﬁlter with σ = 6 arcsec. Point sources and emission from NVSS 123050+344257 radio galaxy (ID 78) have been removed, masking them with circular apertures of 10–20 pixels radius. In both panels, the BCG and BGs are also marked. North is up and east is left. Fig. 2. Galaxy redshift distribution. Dashed vertical lines delimit the redshift range including 77 galaxy members assigned to RXCJ1230 according to 2.7σv clipping. The velocity distribution in the cluster rest frame of the 77 cluster members selected is superimposed. The black curve represents the reconstruction of the velocity distribution as a Gaussian proﬁle, considering the σv computed using the biweight estimator and assuming all the galaxies belong to a single system. The velocity corresponding to the BCG is also marked. A78, page 4 of 11 3.2. Velocity ﬁeld Deviation from Gaussianity in the radial velocity distributions is a clear indicator that clusters present substructures (see e.g. Ribeiro et al. 2011). In order to check whether the velocity dis- tribution of RXCJ1230 follows a Gaussian shape, we use two proﬁle estimators, the skewness and kurtosis indexes. Positive skewness indicates the distribution is skewed to the right, with a longer tail to the right of the distribution maximum, while nega- tive skewness indicates that the distribution is shifted and tailed to the left. On the other hand, positive values of the kurtosis indicate distributions presenting thinner tails (leptokurtic) than the normal distribution, while negative values indicate distribu- tions with fatter tails (platykurtic). In our case, we obtain −0.038 and −0.532 for the skewness and kurtosis, respectively. These values suggest that the velocity distribution follows a slightly ﬂatter shape than a normal one, and is quite symmetric. This implies that most of the substructures are probably placed close to the plane of the sky and no signiﬁcant velocity deviations are expected in the radial component (along the line of sight). middle panel). We notice that the inner region shows higher mean velocity, while regions surrounding the main body exhibit velocities of up to 500 km s−1 lower. p The BCG of RXCJ1230 (the ID 60) presents a velocity of 100 064 ± 28 km s−1, which is about 310 km s−1 higher than the mean velocity of the cluster. In addition to the BCG, with mag- nitude r′ = 18.49, we also detect two even brighter galaxies (IDs 22 and 21, with r′ = 17.90 and 18.07) located to the southwest. In addition to these bright galaxies (BGs), we identify two very bright galaxies showing BCG features. One of them is located to the south (the ID 61, with r′ = 18.69), and the other to the east (the ID 93, with r′ = 18.13). As Fig. 1 shows, the BCG and all BGs are very close to the X-ray peaks as recovered from XMM- Newton data. The BCG is coincident with the main (and central) body of the cluster, while the BG-W(1) and BG-W(2) are very close to the southwest X-ray peak. R. Barrena et al.: The dynamical status of RXCJ1230 cluster of galaxies Fig. 3. Top panel: rest frame velocity versus projected distance to the cluster centre for the 77 galaxy members selected. The cluster centre is assumed to be the position of the BCG. Middle and bottom panels: integral proﬁles and LOS velocity dispersion, respectively. These values are computed by considering all galaxies within that radius. The ﬁrst value computed is estimated from the ﬁrst ﬁve galaxies closest to the centre. The error bars are at the 68% c.l. Fig. 4. Colour–magnitude diagram (r′ −i′,r′) of galaxies in a region of 12.4′ × 9.6′. Red symbols correspond to galaxy members conﬁrmed spectroscopically (red dot corresponds to the BCG of the cluster). The solid line represents the red sequence deﬁned as the densest locus in this diagram, which follows the linear ﬁt r′ −i′ = −0.028 ∗r′ + 1.118. Dashed lines delimit the region that encloses the RS and the blue cloud in this diagram. Galaxies included in this region are considered likely members, which are used to obtain the isodensity galaxy distribution shown in Fig. 1. Fig. 4. Colour–magnitude diagram (r′ −i′,r′) of galaxies in a region of 12.4′ × 9.6′. Red symbols correspond to galaxy members conﬁrmed spectroscopically (red dot corresponds to the BCG of the cluster). The solid line represents the red sequence deﬁned as the densest locus in this diagram, which follows the linear ﬁt r′ −i′ = −0.028 ∗r′ + 1.118. Dashed lines delimit the region that encloses the RS and the blue cloud in this diagram. Galaxies included in this region are considered likely members, which are used to obtain the isodensity galaxy distribution shown in Fig. 1. linked to a corresponding substructure, conﬁguring a complex multi-substructure cluster. In addition to this set of BGs, we detect 12 galaxies show- ing [OII] emission lines, but only 4 of these galaxies are clus- ter members. The S/N and the spectral resolution of our data allow us to detect [OII] lines with equivalent widths >8 Å. These emission line galaxies (ELGs; star-forming galaxies) are the IDs 5, 62, 80, and 84, and show [OII] equivalent widths of 15, 95, 12, and 18 Å, respectively. The ELG members represent 5.2% of the cluster members in our sample. This fraction indicates that the star-forming processes have been quenched in RXCJ1230, which is in agreement with the presence of high-galaxy-density environments with ICM showing high TX (Laganá et al. 2008). Fig. 3. R. Barrena et al.: The dynamical status of RXCJ1230 cluster of galaxies Top panel: rest frame velocity versus projected distance to the cluster centre for the 77 galaxy members selected. The cluster centre is assumed to be the position of the BCG. Middle and bottom panels: integral proﬁles and LOS velocity dispersion, respectively. These values are computed by considering all galaxies within that radius. The ﬁrst value computed is estimated from the ﬁrst ﬁve galaxies closest to the centre. The error bars are at the 68% c.l. 3.2. Velocity ﬁeld In a similar way, the BG-S is almost coincident with a small elongation of the X-ray surface brightness towards the south, and the BG-E is placed in the max- imum of a weak X-ray emission located to the east of the cluster. As we discuss in following sections, each one of these BGs is 3.1. Member selection and global properties The bottom panel of Fig. 3 shows that the integral σv proﬁle is ﬂat beyond 0.7 Mpc, suggesting that the estimation of the σv is robust for the whole cluster. In the following analyses, we use the bi-weight estimator given its robustness in cases where the statistics clearly departs from the Gaussian distribution. In addi- tion to the 77 members, we detect 6 galaxies in the foreground and 10 in the background of RXCJ1230. We note that the BCG is not strictly the brightest galaxy of this complex cluster. The BCG is the brightest galaxy in the main body and the most massive clump of galaxies, and lies very close to the X-ray peak emission and the maximum of galaxy isoden- sity distribution (see Fig. 1). There are another four galaxy mem- bers even brighter than the BCG in RXCJ1230 (see Table 1 and Figs. 1 and 4) lying in the surrounding subclusters. These four bright galaxies are labelled as BGs in order to diﬀerentiate them from the actual BCG. These four galaxies can also probably be considered as BCGs of their respective subclusters, but we label them as BGs to keep the notation clear. Another remarkable eﬀect that we ﬁnd is a clear dependence of the mean velocity on the clustercentric distance (see Fig. 3, A78, page 4 of 11 R. Barrena et al.: The dynamical status of RXCJ1230 cluster of galaxies 3.3. Two-dimensional galaxy distribution This map was obtained by evaluating the cumulative contribution of 618 Gaus- sian proﬁles (with σ = 1 arcsec width) centred on each individ- ual member in a grid of 245 × 200 points. From this study we can assess that the cluster presents a central high-density clump (the main body) and the BCG (ID 60) coincident with the highest density peak. A secondary and very dense clump is seen towards the southwest and two very bright galaxies (IDs 22 and 21) are positioned very close to the corresponding peak of that clump. The isodensity contours show a clear elongation from the main body of the cluster to the south. This concentration of galaxies shapes a third small substructure towards the south also contain- ing a BG (ID 61). Finally, a fourth galaxy clump that is not as clear in the isodensity contours but also contains a BG (ID 93) is located eastward. Thus, we detect three galaxy clumps (towards the southwest, south, and east, respectively, and following the order of a decreasing density) surrounding a very dense main cluster. Table 2 lists the precise positions and global properties for these four signiﬁcant galaxy clumps. In a second approach, we again divide the galaxy velocity sample into two sets: one containing low velocities with v < ¯v, and a second subset with high velocities (v > ¯v). In other words, the low- and high-velocity subsamples correspond to galaxies with negative and positive velocities with respect to the mean velocity in the cluster velocity rest frame (see inner panel of Fig. 2). We check the diﬀerence between the two distributions of galaxy positions. Figure 5 shows that low- and high-velocity galaxies are segregated, as we advance in Sect. 3.1. While high- velocity galaxies (red contours) shape the main body of the sys- tem, the low-velocity galaxies (blue contours) are placed in the three surrounding substructures. This can also be seen in Fig. 3 (middle panel), where ⟨v⟩takes values of about 100 200 km s−1 for distances ∼0.3−0.4 Mpc and 99 700 km s−1 at >1.2 Mpc. p p We carry out a second test for checking this spatial–velocity segregation. 3.3. Two-dimensional galaxy distribution In addition, we select galaxies down to r′ = 22.2. This locus in the CMD selects 618 likely galaxy members (dashed lines in Fig. 4) in the region considered. also adopt the photometric SDSS DR16 catalogues. Using the r′ and i′ SDSS DR16 photometry in a region of 12.4′ × 9.6′, we construct a (r′ −i′ vs. r′) colour–magnitude diagram (CMD; see Fig. 4) and select likely members from there. First, we ﬁt a red sequence (RS) to the spectroscopicaly conﬁrmed mem- bers by ﬁxing the slope to −0.028 following the prescription detailed in Barrena et al. (2012). We obtain r′ −i′ = −0.028 × r′ + 1.118(±0.05). Then, in order to select both likely early-type members (placed in the RS) and galaxy members residing in the green valley and blue cloud (below the RS) in the CMD of the cluster (Eales et al. 2018), we select the locus deﬁned by the RS ± 3 × rms as upper limit and −0.1615 × r′ + 3.37 as lower limit in r′ −i′, respectively. In addition, we select galaxies down to r′ = 22.2. This locus in the CMD selects 618 likely galaxy members (dashed lines in Fig. 4) in the region considered. The presence of internal structures clearly inﬂuences the cluster velocity ﬁeld. Therefore, in a ﬁrst step, in order to inves- tigate the RXCJ1230 complex, we divide galaxies into two sam- ples. We search for possible bimodality through the presence of gaps in the velocity distribution, which could cause drops in the galaxy counts for some particular bins of the velocity histogram (see e.g. Fig. 4 in Barrena et al. 2007 for a clear bimodal con- ﬁguration of Abell 773). In our case, the most important drop is that detected around −500 km s−1 (see Fig. 2, inner panel). Con- sidering this drop of galaxy counts around −500 km s−1 as a pos- sible frontier between two separate galaxy subsamples, we study the spatial distribution of galaxies with v < −500 km s−1 and v ≥−500 km s−1, respectively. We detect no diﬀerences between these two galaxy subsets and both populations are homoge- neously distributed in space, which suggests that this drop in the velocity histogram is not representative of individual galaxy clumps. ( g ) g The left panel of Fig. 1 shows the contour levels of the iso- density galaxy distribution of likely members. 3.3. Two-dimensional galaxy distribution We combine galaxy velocities and positions by computing the δ-statistics using the Dressler & Schectman (DS) test (Dressler & Shectman 1988), which looks for groups of galaxies showing deviations from the local velocity mean, or with velocity dispersion that diﬀers from the global one. If one assumes a random distribution of velocities, one would expect such deviations to be proportional to the number of galaxy mem- bers, ∆∼N, for clusters without substructure or clusters with substructures with similar velocity dispersion and relative move- ment in the line of sight with respect to their main body. On the other hand, one would expect ∆> N for clusters with sub- structures showing relative movements in the line of sight well diﬀerentiated from the main body, and/or even subclusters with lower velocity dispersion with respect to the main cluster. We g g y p We note that the external regions of RXCJ1230 are par- ticularly rich in substructures. The substructure conﬁguration reported here using optical data, which is characterised by a cen- tral main body with three substructures around it, completely agrees with that observed and reported by Böhringer et al. (2022) using X-ray data retrieved by XMM-Newton. As Fig. 1 shows, the galaxy density contours (left panel) and X-ray sur- face brightness proﬁle (right panel) are almost coincident and follow the same shape. 3.3. Two-dimensional galaxy distribution Given that our spectroscopic sample suﬀers from magnitude incompleteness and does not map the whole cluster ﬁeld, we A78, page 5 of 11 A78, page 5 of 11 A&A 663, A78 (2022) Table 2. Positions and global properties of the whole cluster and the four galaxy clumps detected in RXCJ1230. Table 2. Positions and global properties of the whole cluster and the four galaxy clumps detected in RXCJ1230. Structure RA & Dec (J2000) Ngal ¯v σv r200 M200 M500 RA = 12:mm:ss.ss (km s−1) (km s−1) (h−1 70Mpc) (×1014 M⊙) (×1014 M⊙) Dec = +34: ′ : ′′ Global 30:45.78 39:26.3 77 99 658±161 1004+147 −122 – 14.1 ± 3.8 9.0 ± 2.3 Centre 30:45.78 39:26.3 58 99 967±161 999 ± 160 ∼1.8 9.0 ± 1.5 5.6 ± 1.0 Southwest 30:30.55 38:01.4 9 98 810±126 792 ± 230 ∼1.5 4.4 ± 3.3 2.7 ± 2.0 East 31:04.67 40:08.7 3 ∼99 468 ∼500 ∼0.8 ∼1 ∼0.7 South 30:47.98 36:56.7 7 99 090±192 <300 <0.5 – – Notes. σv of the eastern and southern substructures have to be taken as guide values, as well as the masses and radii derived from them. and southern substructures have to be taken as guide values, as well as the masses and radii derived from them. Notes. σv of the eastern and southern substructures have to be taken as guide values, as well as the masses and rad work, we use diﬀerent techniques to analyse the structure of RXCJ1230 combining positions and velocities of galaxy mem- bers. also adopt the photometric SDSS DR16 catalogues. Using the r′ and i′ SDSS DR16 photometry in a region of 12.4′ × 9.6′, we construct a (r′ −i′ vs. r′) colour–magnitude diagram (CMD; see Fig. 4) and select likely members from there. First, we ﬁt a red sequence (RS) to the spectroscopicaly conﬁrmed mem- bers by ﬁxing the slope to −0.028 following the prescription detailed in Barrena et al. (2012). We obtain r′ −i′ = −0.028 × r′ + 1.118(±0.05). Then, in order to select both likely early-type members (placed in the RS) and galaxy members residing in the green valley and blue cloud (below the RS) in the CMD of the cluster (Eales et al. 2018), we select the locus deﬁned by the RS ± 3 × rms as upper limit and −0.1615 × r′ + 3.37 as lower limit in r′ −i′, respectively. A78, page 6 of 11 3.4. Spatial–velocity correlations BGC and BG positions are marked with dots. Fig. 5. Isodensity contours of spectroscopically conﬁrmed galaxy mem- bers. Blue contours corresponds to the 2D distribution of galaxies with negative velocity with respect to the mean velocity in the cluster rest frame (see Fig. 2, inner panel). Similarly, red contours show isodensity levels for galaxies with positive velocity with respect to the mean cluster velocity. This plot is centred on the BCG marked with a large big dot. Blue dots correspond to BGs belonging to the corresponding clumps. Red and blue contours are plotted at the same density level. With the aim of identifying individual galaxies belonging to each substructure, we use a new 3D diagnostic test. We apply a 3D version of the Key Mixture Model (KMM; Ashman et al. 1994) algorithm in order to separate diﬀerent components in velocity space. The KMM algorithm estimates the probability that a given galaxy belongs to a given component in an iterative procedure. The output from the algorithm is a list of galaxies associated with the cluster main body and with each additional substructure. However, it needs to start from an initial input conﬁguration. In order to minimise the dependence of the ﬁnal results of probabilities on the initial guess input, we run KMM with several (more than ten) initial random allocations to three galaxy populations composed of 25, 25, and 24 galaxies (the three easternmost galaxies have been excluded from this test given the redshift undersampling in this region5). The ﬁnal result was always the same, converging into a very stable solution. The output set of probabilities always ﬁts a three-group parti- tion, assigning 9 and 7 galaxies to the southwestern and southern substructures, respectively, with >95% probabilities according to the likelihood ratios obtained from KMM test. The remain- ing galaxies are assigned to the main cluster body. This galaxy allocation, for the main body and the two (southwestern and southern) substructures is shown in Fig. 7. On the other hand, the analysis of the p-value probability of obtaining this KMM result by chance is lower than 0.001 (<0.1% probability). The substructure to the east was not identiﬁed through this technique mainly due to the lack of redshift information in this zone. How- ever, the DS test shows high δi deviations in the surroundings of this region, around the (−3′, 1′) position in Fig. 6. 5 Including a fourth galaxy clump with the three easternmost galaxies does not produce a reliable KMM test result. 3.4. Spatial–velocity correlations One of the most useful tools for verifying the existence of sub- structures is the study of spatial–velocity correlations. In this R. Barrena et al.: The dynamical status of RXCJ1230 cluster of galaxies Fig. 5. Isodensity contours of spectroscopically conﬁrmed galaxy mem- bers. Blue contours corresponds to the 2D distribution of galaxies with negative velocity with respect to the mean velocity in the cluster rest frame (see Fig. 2, inner panel). Similarly, red contours show isodensity levels for galaxies with positive velocity with respect to the mean cluster velocity. This plot is centred on the BCG marked with a large big dot. Blue dots correspond to BGs belonging to the corresponding clumps. Red and blue contours are plotted at the same density level. Fig. 6. Spatial distribution of the 77 cluster members, each marked by a square. The sizes of the squares are proportional to exp(δi), which is computed using the δi deviations obtained in the DS test. Red and blue squares separate populations showing deviations lower and higher than ¯δi, respectively. BGC and BG positions are marked with dots. With the aim of identifying individual galaxies belonging to each substructure, we use a new 3D diagnostic test. We apply Fig. 5. Isodensity contours of spectroscopically conﬁrmed galaxy mem- bers. Blue contours corresponds to the 2D distribution of galaxies with negative velocity with respect to the mean velocity in the cluster rest frame (see Fig. 2, inner panel). Similarly, red contours show isodensity levels for galaxies with positive velocity with respect to the mean cluster velocity. This plot is centred on the BCG marked with a large big dot. Blue dots correspond to BGs belonging to the corresponding clumps. Red and blue contours are plotted at the same density level. Fig. 6. Spatial distribution of the 77 cluster members, each marked by a square. The sizes of the squares are proportional to exp(δi), which is computed using the δi deviations obtained in the DS test. Red and blue squares separate populations showing deviations lower and higher than ¯δi, respectively. BGC and BG positions are marked with dots. Fig. 6. Spatial distribution of the 77 cluster members, each marked by a square. The sizes of the squares are proportional to exp(δi), which is computed using the δi deviations obtained in the DS test. Red and blue squares separate populations showing deviations lower and higher than ¯δi, respectively. 3.4. Spatial–velocity correlations ﬁnd a cumulative deviation of ∆= 65 (at the 95% c.l., as esti- mated by computing 1000 Monte Carlo simulations), which is a value comparable to the number of members (77). This suggests that all of the substructures of RXCJ1230 move with no signiﬁ- cant deviation in the line of sight component with respect to the main cluster body, which is in agreement with the ﬁnding we present in Sect. 3.2. In addition, the ∆value shows that no group has been detected that has a velocity dispersion that is very dif- ferent from that of the whole cluster. However, the cumulative ∆is unable to provide information on the presence of possible individual galaxy clumps. This issue is explored in the following using the individual δ associated to each galaxy position and also obtained through the DS test. Figure 6 illustrates the δ-statistics combined with the spa- tial distribution of the 77 cluster members. A square is plotted around each point of size proportional to exp(δi). Therefore, the larger the square, the larger the deviation (δ) of the local mean velocity from the global mean. Red squares correspond to galax- ies with δi < ¯δi (where ¯δi is the mean δi deviation of the 77 clus- ter members), while blue represents members with deviations δi > ¯δi. This plot shows that the most important substructures are mainly located east and southwest of the main body of the cluster. The galaxies of these groups present higher deviations than galaxies in the main body (centre). The main advantage of this method is that no a priori selections or assumptions about the positions of subclumps have to be imposed. Therefore, this ﬁnding is more parameter-independent and thus more robust. 4. Dynamical mass of RXCJ1230 Moreover, no shock fronts are detected in the X-ray surface brightness map, which are very commonly formed after collisions. It is there- fore reasonable to assume that each substructure has not yet col- lided and is roughly in dynamical equilibrium, which allows us to compute virial quantities and estimate the mass of the whole cluster as the sum of the individual subclump masses. In addition to the mass, we can also estimate the virial radius, r200, which provides information about the quasi-virialised region, as the radius of a sphere of mass M200 and 200 times the critical density of the Universe at the redshift of the system, 200ρc(z). Therefore, M200 = 100r3 200 H(z)2/G. Following this expression, we obtain r200 ∼1.8 and ∼1.5 h−1 70 Mpc for the main body and the southwestern substructure, respectively. We com- pile the radius and mass estimates in Table 2. p Table 2 lists the kinematical properties of this complex, which is composed of a main central cluster surrounded by three substructures. Following the KMM test, we unequivocally asso- ciate 9 and 7 galaxies to the southwestern and southern substruc- tures (see Fig. 7). This allows us to estimate a mean velocity and a rough velocity dispersion for these substructures: we obtain ¯vSW = 98 810 ± 126 and ¯vS = 99 090 ± 192 km s−1 for the mean velocity of the substructures to the SW and S, respec- tively. In the same way, we estimate a velocity dispersion of σmain = 999±160, σSW = 792±230 for the main body (assumed to be composed of 58 galaxies) and the southwestern clump, respectively. The 7 galaxies identiﬁed in the southern substruc- ture seem to conﬁgure a small compact group of galaxies with very low σv. In this case, we were only able to estimate an upper limit of σS < 300 km s−1. Regarding the eastern substructure, we assume that the mean velocity should be similar to its cor- responding BG (99 100 km s−1); and in agreement with the low galaxy density and the low X-ray emission observed, the veloc- ity dispersion (in this case computed as the rms) of these three galaxies is σE ∼500 km s−1. 6 r200 is deﬁned as the radius inside which the average mass density in the cluster is 200 times the critical density of the Universe at the clus- ter redshift. Similarly to r500 for its corresponding mass density. There- fore, M200 and M500 are the virial mass contained within r200 and r500, respectively. 4. Dynamical mass of RXCJ1230 (1) therein), given that the relation they obtain is constructed using very complete simulations, which take into account not only dark matter particles but also subhaloes, galaxies, and AGN feed- back. Therefore, following the σv−M200 relation of Munari et al. (2013), we ﬁnd dynamical masses of M200 = 9.0±1.5×1014 M⊙ and 4.4±3.3×1014 M⊙for the main cluster and the southwestern substructure, respectively. Regarding the eastern substructure, the velocity dispersion estimate is very inaccurate. This makes very diﬃcult to determine its mass with a minimum of preci- sion. However, applying the again the σv −M200 scaling rela- tion, we obtain a rough estimate of ∼1 × 1014 M⊙for the eastern clump. In order to compare these values with others in the litera- ture (which mainly refer to M500), M200 can also be converted into M500 following the relation given by Duﬀy et al. (2008). M500 has been rescaled from M200 assuming a concentration parameter c = 3.5 (an appropriate value for clusters at z = 0.3 and M200 = 1014−1015 M⊙), integrating a Navarro-Frenk-White (NFW) proﬁle (Navarro et al. 1997) and interpolating to obtain M500. In this way, we obtain M500 = 5.6 ± 1.0 × 1014 M⊙and 2.7 ± 2.0 × 1014 M⊙for the main cluster and the southwestern substructure, respectively, and a rough (and qualitative) value of M500 ∼0.7 × 1014 M⊙for the eastern clump. Fig. 7. Spatial distribution on the sky of the 77 cluster members. The 9 blue and 7 green dots correspond to the galaxies belonging to the south- western and southern substructures identiﬁed with >95% probability using the KMM procedure. Red dots correspond to galaxy members that are part of the cluster main body with diﬀerent probabilities fol- lowing the same algorithm. Black dots correspond to galaxies selected manually as part of the eastern clump according to their space–velocity segregation (see Fig. 5). Large dots mark the BCG and BGs. galaxies and the X-ray surface brightness map suggest the pres- ence of a third clump located to the east and containing a BG. Although RXCJ1230 is in a phase of interaction, the main system and the three surrounding substructures are still well separated and the 2D galaxy density distribution and BGs closely match their corresponding X-ray peaks. We can therefore assume that RXCJ1230 is in a pre-merging phase. 4. Dynamical mass of RXCJ1230 In summary, the study of the individual δ of the DS test provides us with valuable proof of the presence of substruc- tures in the periphery of the cluster conﬁrmed by high devia- tions from the mean velocity of the cluster in the external zones. This ﬁnding is in agreement with what we ﬁnd in the 2D spatial distribution (see Sect. 3.3). In addition, the cumulative ∆is com- parable to the number of cluster members, which suggests that no large relative movement of these substructures is expected in the radial component. Therefore, in agreement with what we ﬁnd in Sect. 3.2, relative movements of subclusters with respect to the main body should be (almost) contained in the plane of the sky. On the basis of the results presented in the previous section, we can conclude that RXCJ1230 is composed of three substructures, which are spatially well separated in the sky. The main substruc- ture is placed to the southwest with respect to the main body of the cluster, and contains two very bright galaxies, the BGs-W (1 and 2). A second substructure is located toward the south, which resembles a very compact group of galaxies dominated by a very bright galaxy, the BG-S. In addition, the spatial distribution of A78, page 7 of 11 A78, page 7 of 11 A&A 663, A78 (2022) Fig. 7. Spatial distribution on the sky of the 77 cluster members. The 9 blue and 7 green dots correspond to the galaxies belonging to the south- western and southern substructures identiﬁed with >95% probability using the KMM procedure. Red dots correspond to galaxy members that are part of the cluster main body with diﬀerent probabilities fol- lowing the same algorithm. Black dots correspond to galaxies selected manually as part of the eastern clump according to their space–velocity segregation (see Fig. 5). Large dots mark the BCG and BGs. and its relation with M2006 to determine the dynamical mass of RXCJ1230 and its substructures. In the literature, there are many scaling relations that can be used to obtain dynamical masses of clusters from their velocity dispersion. Some examples are those obtained by Evrard et al. (2008), Saro et al. (2013), Munari et al. (2013) and Ferragamo et al. (2020). All of these produce very similar values for the dynamical mass. However, in this work, we follow the prescription of Munari et al. (2013; see Eq. 4.1. Comparison with X-ray observations Assuming that the two components are to cause a head-on collision and that their kinetic energies are com- pletely converted to thermal energy, the colliding velocity is v2 coll = 3k∆T/µmp km s−1, following prescriptions detailed in Shibata et al. (1999), where µ and mp are the mean molecular weight (0.6) in amu, and the proton mass, respectively. There- fore, assuming an excess temperature of k∆T ∼1.5 keV, we ﬁnd vcoll ≃850 km s−1, which is in very good agreement with the observed relative LOS velocity in the cluster rest frame, as computed from (¯vC −¯vSW)/(1 + z) = 869 km s−1. Comparing the mass of individual clumps, Böhringer et al. (2022) ﬁnd M500,X = 3.7 ± 0.5 × 1014 M⊙within r500 in the main cluster, while we obtain M500,dyn = 5.6±1.0×1014 M⊙. This dis- crepancy of about 30% may come from the fact that M500,dyn has been derived by converting M200 into M500. In fact, when con- sidering only the 47 galaxy members with redshift within r500 (=3.45 arcmin =1 Mpc; see Table 3 in Böhringer et al. 2022), σv = 913 ± 133 km s−1 is obtained, which points to a mass of about M500,dyn ∼4.3 × 1014 M⊙, which is almost coinci- dent with that derived from X-ray data. For the southwestern component, we ﬁnd good agreement of the mass determina- tion with M500,X = 2.5 ± 0.64 × 1014 M⊙from X-rays and M500,dyn = 2.7 ± 2 × 1014 M⊙from the galaxy dynamics. For the eastern component, a mass estimate is more diﬃcult. How- ever, even considering rough estimations, M500,dyn ∼1×1014 M⊙ and M500,X = 1.35 ± 0.3 × 1014 M⊙roughly agree within errors. Two-body merging model. We investigate the relative dynamics of the main body (C) of RXCJ1230 and its main substructure, the southwestern (SW) one, which dominates the dynamics of the whole cluster with a mass ratio about 2:1. The remaining interactions, involving the southern and east- ern substructures, are minor merger events with mass ratios of about 10:1. We analyse this C–SW interaction using diﬀerent approaches based on an energy integral formalism in the frame- work of locally ﬂat spacetime and Newtonian gravity (see e.g. Beers et al. 1982). 4.1. Comparison with X-ray observations By analysing X-ray data, Böhringer et al. (2022) also ﬁnd a com- plex conﬁguration of substructures around the main body of the cluster, which is elongated toward the south. The main substruc- ture is placed to the southwest, while another minor clump is detected toward the east. The detailed X-ray analysis of the RXCJ1230 complex is presented in Böhringer et al. (2022). In summary, these authors ﬁnd that the X-ray temperature of the main body is 4.7±0.4 keV, while the southwestern and eastern components show a TX = 4.4 ± 0.6 and 3.3 ± 0.6 keV, respectively. On the other hand, Böhringer et al. (2022) calculate the mass of gas inside r500, which is 3.45, 2.98, and 2.39 arcmin for the central, south- western, and eastern cluster components, respectively, and use a β-model for the plasma density distribution. They assume a ﬁx β-value of 2/3, which is typical for massive relaxed clus- ters. Finally, these authors adopted several scaling relations with LX, TX, YX, and Mgas and of M500(βﬁx) and ﬁnd a total mass of M500,X = 7.7(±0.7) × 1014 M⊙. Fig. 8. Two-body model applied to the main cluster and southwestern galaxy substructure (C–SW system). The black curve separates bound and unbound regions according to the Newtonian criterion. Solid curves represent the bound incoming (BI) and bound outgoing (BO) solutions. Blue and red curves denote the models for 706 and 1022 km s−1, which represent the marginal relative velocity between main cluster and sub- structure, considering the corresponding uncertainties. The horizontal lines represent the observational values of the total mass of the C–SW system, with it uncertainty (dashed lines). , The sum of dynamical masses corresponding to the main body and the southwestern clump, that is, the two main systems of RXCJ1230, is M500,dyn ≃9.0 ± 2.3 × 1014 M⊙. Comparing this value with that derived from X-ray, we see that M500,dyn and M500,X are in agreement within errors and they diﬀer by about 15%. erences therein), the southwestern substructure could be starting to show an enhancement of its intra-cluster medium (ICM) tem- perature. This enhancement supports the fact that the main body and southwestern substructure are starting to collide. When the merging scenario is assumed to explain an enhancement of the ICM temperature, a relative colliding veloc- ity is needed to heat up the ICM (Gutierrez & Krawczynski 2005). 4. Dynamical mass of RXCJ1230 We obtain velocity dispersions for the eastern and southern substructures as guide values, and only consider these in order to extract information about the magni- tude and the importance of such galaxy clumps in the context of the whole RXCJ1230 cluster. As for the whole mass of the system, the contribution of the eastern and southern groups is of minor importance because they likely have low velocity dispersion and M200 scales with σ3 v. Thus, we can estimate a reliable total mass for the cluster as the sum of the main body and the other substructures; we obtain a total mass of M200 ≃1.4 ± 0.4 × 1015 M⊙. In summary, RXCJ1230 is composed of a central main body accreting three substructures from its environment. The main substructure is the one to the southwest, which keeps a mass ratio of about 2:1 with respect to the main cluster. The substruc- ture to the east is very small, because the velocity dispersion and mass estimate show a mass ratio of about 10:1 with respect to the main body. Something similar may occur with the south- ern substructure, which seems to be a very compact group with very low velocity dispersion. As we are not able to compute an accurate velocity dispersion for the E and S clumps, the values reported in Table 2 for these overdensities should be taken as qualitative results; however, they are important in order to char- acterise these minor subclumps. Our results agree with those of Given that galaxies are tracers of the gravitational potential of a halo, it is possible to estimate the dynamical mass of a system from its velocity dispersion. We use the calculated σv A78, page 8 of 11 R. Barrena et al.: The dynamical status of RXCJ1230 cluster of galaxies Fig. 8. Two-body model applied to the main cluster and southwestern galaxy substructure (C–SW system). The black curve separates bound and unbound regions according to the Newtonian criterion. Solid curves represent the bound incoming (BI) and bound outgoing (BO) solutions. Blue and red curves denote the models for 706 and 1022 km s−1, which represent the marginal relative velocity between main cluster and sub- structure, considering the corresponding uncertainties. The horizontal lines represent the observational values of the total mass of the C–SW system, with it uncertainty (dashed lines). Böhringer et al. (2022) from X-ray data, supporting the validity of our ﬁndings. 4.1. Comparison with X-ray observations The three relevant observable quantities for the two system interactions are: the relative line-of-sight veloc- ity, Vr = 869 ± 153 km s−1; the projected physical distance, D = 0.97 h−1 70 Mpc (3.38 arcmin); and the total mass of the two systems by adding the masses of the two clumps within r200, Msys ∼13.4 ± 3.6 × 1014 M⊙(see Sect. 4). 4. Dynamical mass of RXCJ1230 Böhringer et al. (2022) from X-ray data, supporting the validity of our ﬁndings. 5. Dynamics and merging As pointed out above, both the main cluster and the three sub- structures are well detectable and optical and X-ray data indicate very similar locations. We are therefore seeing RXCJ1230 in a pre-merger phase. However, the velocity distribution and the not particularly well-resolved galaxy populations suggest that the substructures are starting to interact with the main cluster. With this scenario, the main collision will be produced between the substructure to the southwest involving a mass ratio of 2:1. We note that the X-ray temperatures of the main body and the sub- structure are very similar, namely TX,C = 4.7 ± 0.4 and TX,SW = 4.4 ± 0.6 keV (Böhringer et al. 2022) for the central main clump and the southwestern substructure, respectively, even though they show very diﬀerent dynamical masses. Whereas typical X- ray temperatures of relaxed clusters with M500 ∼2.7 × 1014 M⊙ are about 3 keV (see e.g. Fig. 9 in Kettula et al. 2013, and ref- y First, we consider the Newtonian criterion for the grav- itational binding, which follows the expression V2 r D ≤ 2GMsys sin2 α cos α, where α is the projection angle between the line connecting the centres of the two clumps and the plane of the sky. Figure 8 represents the two-body model obtained. Considering the value of Msys, the C–SW system is bound A78, page 9 of 11 A78, page 9 of 11 A78, page 9 of 11 A&A 663, A78 (2022) between 6◦and 86◦with a probability of R 86◦ 6◦ cos αdα = 0.89 (i.e. 89%). ture shows σE ∼500 km s−1. The dynamical masses estimated from these velocity dispersions are M200 = 9.0 ± 1.5 × 1014 M⊙, 4.4 ± 3.3 × 1014 M⊙, and ∼1 × 1014 M⊙for the main cluster and the southwestern and eastern substructures, respectively. Con- sidering the complex structure of RXCJ1230, we estimate that the whole cluster contains a total mass in the range of M200 ≃ 1.4 ± 0.4 × 1015. ( ) We then apply the analytical two-body model introduced by Beers et al. (1982) and Thompson et al. (1982), (see also Lubin et al. 1998). This model assumes radial orbits and no rota- tion of the system. 5. Dynamics and merging Department of Energy, the Japanese Monbukagakusho, and the Max Planck Society. The Pan-STARRS1 Surveys (PS1) and the PS1 public sci- ence archive have been made possible through contributions by the Institute for Astronomy, the University of Hawaii, the Pan-STARRS Project Oﬃce, the Max-Planck Society and its participating institutes, the Max Planck Institute for Astronomy, Heidelberg and the Max Planck Institute for Extraterrestrial Physics, Garching, The Johns Hopkins University, Durham University, the University of Edinburgh, the Queen’s University Belfast, the Harvard-Smithsonian Cen- ter for Astrophysics, the Las Cumbres Observatory Global Telescope Network Incorporated, the National Central University of Taiwan, the Space Telescope Science Institute, the National Aeronautics and Space Administration under Grant No. NNX08AR22G issued through the Planetary Science Division of the NASA Science Mission Directorate, the National Science Foundation Grant No. AST-1238877, the University of Maryland, Eotvos Lorand University (ELTE), the Los Alamos National Laboratory, and the Gordon and Betty Moore Foundation. Between the two possible incoming solutions, α = 17◦and α = 76◦, the second one is quite unlikely. The solution of α = 76◦(associated to the BIb solution) would imply a distance between clumps of ∼4.0 h−1 70 Mpc, which is more than twice r200. On the other hand, α = 17◦(BIa) is the most likely solution, and for this case, the distance between the centres of C and SW would be ∼1.0 h−1 70 Mpc, which would explain a certain degree of interaction. Thus, when assuming α = 17◦, the colliding velocity would be ∼3000 km s−1 and the cluster clumps would cross after ∼0.3 Gyr. We acknowledge that the characterisation of the dynamics of RXCJ1230 through these models is aﬀected by several limita- tions. First, the two-body model does not consider the possibility of an oﬀ-axis merger, or a mass distribution in the subclusters. Secondly, this study does not take into account the presence of minor subclusters (the southern and eastern clumps). Therefore, the model presented here remains one of the many possible col- lision scenarios for RXCJ1230. 6. Summary and Conclusions We present ﬁndings for the kinematical and dynamical state of the complex galaxy cluster RXCJ1230.7+3439. Our study is based on new spectroscopic redshifts acquired at the 3.5m TNG telescope covering a region of ∼8′ × 8′. We also consider some SDSS DR16 spectroscopic redshifts in order to comple- ment our sample. In addition, we use the SDSS photometry in a ﬁeld of ∼13′ × 10′ to analyse the spatial distribution of likely cluster members. We select 77 galaxy cluster members around z = 0.332 and compute a LOS global velocity dispersion of σv = 1004+147 −122 km s−1. 5. Dynamics and merging In addition, the clumps are assumed to start their evolution at t0 = 0 with a separation of d0 = 0 and are moving apart or coming together for the ﬁrst time in the history. That is, with this model, we are assuming that we are seeing the cluster prior to collision (at t = 9.98 Gyr at the redshift of RXCJ1230). The solutions for this model are shown in Fig. 8, where we compare the total mass of the system, Msys, with the projection angle, α. The possible solutions span several cases: two bound incoming solutions (BIa and BIb) around 14◦–20◦and 74◦–77◦, respectively, and one bound outgoing (BO) at ∼85◦. The incoming case is degenerated because of the ambiguity in the projection angle α. Therefore, for simplicity, we assume that the mean value in the incoming cases (BIa ∼17◦and BIb ∼76◦), and Msys values are equally probable for individual solutions. Under these assumptions, we estimate the following probabili- ties: PBIa ∼87%, PBIb ∼13%, and PBO ≪0.1%. We discard the BO solution because it is very unlikely and we analyse the BI ones below. Given that the galaxy density peaks coincide with those observed in X-ray surface brightness, we infer that the system is taking part in a pre-merger event, where the main collision is that involving the main body and the southwestern clump. This interaction occurs with a mass ratio of 2:1 and an impact velocity of ∆vr f ∼3000 km s−1. The most likely solution obtained from a two-body problem for these two systems suggests that the merg- ing axis lies at ∼17◦(±3◦) with respect to the plane of the sky and the systems will be completely joined in about 0.3 Gyr. However, a slight increase in the X-ray temperature (k∆T ∼1.5 keV) to the southwest may indicate that we are already observing a certain degree of interaction. Acknowledgements. We thank to the referee for his useful comments, which have really helped the authors to improve this work. R. Barrena acknowledges support by the Severo Ochoa 2020 research programme of the Instituto de Astrofísica de Canarias. H. Böhringer acknowledges support from the Deutsche Forschungsgemeinschaft through the Excellence cluster “Origins”. G. Chon acknowledges support by the DLR under the grant n◦50 OR 1905. 5. Dynamics and merging This arti- cle is based on observations made with the Italian Telescopio Nazionale Galileo operated by the Fundación Galileo Galilei of the INAF (Istituto Nazionale di Astroﬁsica). This facility is located at the Spanish del Roque de los Mucha- chos Observatory of the Instituto de Astrofísica de Canarias on the island of La Palma. Funding for the Sloan Digital Sky Survey (SDSS) has been pro- vided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Aeronautics and Space Administration, the National Science Founda- tion, the U.S. Department of Energy, the Japanese Monbukagakusho, and the Max Planck Society. The Pan-STARRS1 Surveys (PS1) and the PS1 public sci- ence archive have been made possible through contributions by the Institute for Astronomy, the University of Hawaii, the Pan-STARRS Project Oﬃce, the Max-Planck Society and its participating institutes, the Max Planck Institute for Astronomy, Heidelberg and the Max Planck Institute for Extraterrestrial Physics, Garching, The Johns Hopkins University, Durham University, the University of Edinburgh, the Queen’s University Belfast, the Harvard-Smithsonian Cen- ter for Astrophysics, the Las Cumbres Observatory Global Telescope Network Incorporated, the National Central University of Taiwan, the Space Telescope Science Institute, the National Aeronautics and Space Administration under Grant No. NNX08AR22G issued through the Planetary Science Division of the NASA Science Mission Directorate, the National Science Foundation Grant No. AST-1238877, the University of Maryland, Eotvos Lorand University (ELTE), the Los Alamos National Laboratory, and the Gordon and Betty Moore Foundation. Acknowledgements. We thank to the referee for his useful comments, which have really helped the authors to improve this work. R. Barrena acknowledges support by the Severo Ochoa 2020 research programme of the Instituto de Astrofísica de Canarias. H. Böhringer acknowledges support from the Deutsche Forschungsgemeinschaft through the Excellence cluster “Origins”. G. Chon acknowledges support by the DLR under the grant n◦50 OR 1905. This arti- cle is based on observations made with the Italian Telescopio Nazionale Galileo operated by the Fundación Galileo Galilei of the INAF (Istituto Nazionale di Astroﬁsica). This facility is located at the Spanish del Roque de los Mucha- chos Observatory of the Instituto de Astrofísica de Canarias on the island of La Palma. Funding for the Sloan Digital Sky Survey (SDSS) has been pro- vided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Aeronautics and Space Administration, the National Science Founda- tion, the U.S. Acknowledgements. We thank to the referee for his useful comments, which have really helped the authors to improve this work. R. Barrena acknowledges support by the Severo Ochoa 2020 research programme of the Instituto de Astrofísica de Canarias. H. Böhringer acknowledges support from the Deutsche Forschungsgemeinschaft through the Excellence cluster “Origins”. G. Chon acknowledges support by the DLR under the grant n◦50 OR 1905. This arti- cle is based on observations made with the Italian Telescopio Nazionale Galileo operated by the Fundación Galileo Galilei of the INAF (Istituto Nazionale di Astroﬁsica). This facility is located at the Spanish del Roque de los Mucha- chos Observatory of the Instituto de Astrofísica de Canarias on the island of La Palma. Funding for the Sloan Digital Sky Survey (SDSS) has been pro- vided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Aeronautics and Space Administration, the National Science Founda- tion, the U.S. Department of Energy, the Japanese Monbukagakusho, and the Max Planck Society. The Pan-STARRS1 Surveys (PS1) and the PS1 public sci- ence archive have been made possible through contributions by the Institute for Astronomy, the University of Hawaii, the Pan-STARRS Project Oﬃce, the Max-Planck Society and its participating institutes, the Max Planck Institute for Astronomy, Heidelberg and the Max Planck Institute for Extraterrestrial Physics, Garching, The Johns Hopkins University, Durham University, the University of Edinburgh, the Queen’s University Belfast, the Harvard-Smithsonian Cen- ter for Astrophysics, the Las Cumbres Observatory Global Telescope Network Incorporated, the National Central University of Taiwan, the Space Telescope Science Institute, the National Aeronautics and Space Administration under Grant No. NNX08AR22G issued through the Planetary Science Division of the NASA Science Mission Directorate, the National Science Foundation Grant No. AST-1238877, the University of Maryland, Eotvos Lorand University (ELTE), the Los Alamos National Laboratory, and the Gordon and Betty Moore Foundation. Allen, S. W., Evrard, A. E., & Mantz, A. B. 2011, ARA&A, 49, 409 Appenzeller, I., Thiering, I., & Zickgraf, F. J. 1998, ApJS, 117, 319 Ashman, K. M., Bird, C. M., & Zepf, S. E. 1994, AJ, 108, 2348 Barrena, R., Boschin, W., Girardi, M., et al. 2007, A&A, 467, 37 Barrena, R., Girardi, M., Boschin, W., et al. 2012, A&A, 540, A90 Beers, T. C., Geller, M. J., & Huchra, J. P. 1982, ApJ, 257, 23 Beers, T. C., Flynn, K., & Gebhardt, K. 1990, AJ, 100, 32 Biviano, A. 2000, in IAP 2000 meeting, eds. F. Durret, & D. Gerbal Böhringer, H., & Werner, N. 2010, A&A Rv., 18, 127 Böhringer, H., Voges, W., & Huchra, J. P. 2000, ApJS, 129, 435 Böhringer, H., Chon, G., Ellis, R. S., et al. 2022, A&A in press, https://doi. org/10.1051/0004-6361/202243424 Boschin, W., Girardi, M., & Barrena, R. 2013, MNRAS, 434, 772 Dressler, A., & Shectman, S. A. 1988, AJ, 95, 985 Duﬀy, A. R., Schaye, J., Kay, S. T., et al. 2008, MNRAS, 390, L64 Eales, S. A., Baes, M., Bourne, N., et al. 2018, MNRAS, 481, 1183 Evrard, A. E., Blalek, J., Busha, M., et al. 2008, ApJ, 672, 122 Ferragamo, A., Rubiño-Martín, J. A., Betancort-Rijo, J., et al. 2020, A&A, 641, A41 Gal, R. R., del Carvalho, R. R., & Lopes, P. A. A. 2003, AJ, 125, 2064 References Allen, S. W., Evrard, A. E., & Mantz, A. B. 2011, ARA&A, 49, 409 Appenzeller, I., Thiering, I., & Zickgraf, F. J. 1998, ApJS, 117, 319 Ashman, K. M., Bird, C. M., & Zepf, S. E. 1994, AJ, 108, 2348 Barrena, R., Boschin, W., Girardi, M., et al. 2007, A&A, 467, 37 Barrena, R., Girardi, M., Boschin, W., et al. 2012, A&A, 540, A90 Beers, T. C., Geller, M. J., & Huchra, J. P. 1982, ApJ, 257, 23 Beers, T. C., Flynn, K., & Gebhardt, K. 1990, AJ, 100, 32 Biviano, A. 2000, in IAP 2000 meeting, eds. F. Durret, & D. Gerbal Böhringer, H., & Werner, N. 2010, A&A Rv., 18, 127 Böhringer, H., Voges, W., & Huchra, J. P. 2000, ApJS, 129, 435 Böhringer, H., Chon, G., Ellis, R. S., et al. 2022, A&A in press, https://doi. org/10.1051/0004-6361/202243424 Boschin, W., Girardi, M., & Barrena, R. 2013, MNRAS, 434, 772 Dressler, A., & Shectman, S. A. 1988, AJ, 95, 985 Duﬀy, A. R., Schaye, J., Kay, S. T., et al. 2008, MNRAS, 390, L64 Eales, S. A., Baes, M., Bourne, N., et al. 2018, MNRAS, 481, 1183 Evrard, A. E., Blalek, J., Busha, M., et al. 2008, ApJ, 672, 122 Ferragamo, A., Rubiño-Martín, J. A., Betancort-Rijo, J., et al. 2020, A&A, 641, A41 Gal, R. R., del Carvalho, R. R., & Lopes, P. A. A. 2003, AJ, 125, 2064 Our analysis conﬁrms the presence of three substructures surrounding the main body of the cluster, which are clearly recognisable in the plane of the sky in the 2D spatial distribu- tion of galaxies. Moreover, we identify several bright galaxies dominating the core of each substructure. The most massive sub- structure is that located to the southwest, which shows σv ∼ 800 km s−1 and diﬀers by ∼870 km s−1 from the main body in the LOS velocity. The southern substructure resembles a compact group of galaxies with very low velocity dispersion (σS < 300 km s−1), while we ﬁnd that the eastern substruc- g j A41 Gal, R. R., del Carvalho, R. R., & Lopes, P. A. A. 2003, AJ, 125, 2064 A78, page 10 of 11 A78, page 10 of 11 R. Barrena et al.: The dynamical status of RXCJ1230 cluster of galaxies Ribeiro, A. L. B., Lopes, P. A. A., & Trevisan, M. 2011, MNRAS, 413, L81 Roettiger, K., Loken, C., & Burns, J. O. 1997, ApJS, 109, 307 Saro, A., Mohr, J. J., Bazin, G., et al. 2013, ApJ, 772, 47 Schlegel, D. J., Finkbeiner, D. P., & Davis, M. 1998, ApJ, 500, 525 Shibata, R., Honda, H., Ishida, M., et al. 1999, ApJ, 524, 603 Springel, V. 2005, MNRAS, 364, 1105 Thompson, L. A. 1982, in Early Evolution of the Universe and the Present Structure, eds. G. O. Abell, & G. Chincarini (Dordrecht: Reidel), IAU Symp., 104 Tonry, J., & Davis, M. 1979, ApJ, 84, 1511 Umetsu, K. 2000, A&A Rv., 28, 7 van Weeren, R. J., de Gasperin, F., Akamatsu, H., et al. 2019, Space Sci. Rev., 215, 16 Wen, Z. L., Han, J. L., & Liu, F. S. 2009, ApJS, 183, 197 Golovich, N., Dawson, W. A., Wittman, D. M., et al. 2019, ApJS, 240, 39 Gutierrez, K., & Krawczynski, H. 2005, ApJ, 619, 161 Hao, J., McKay, T. A., Koester, B. P., et al. 2010, ApJS, 191, 254 Kennicutt, R. C. 1992, ApJS, 79, 255 Kettula, K., Finoguenov, A., Massey, R., et al. 2013, ApJ, 778, 74 Laganá, T. F., Lima Neto, G. B., Andrade-Santos, F., et al. 2008, A&A, 485, 633 Loewenstein, M. 2003, Origin and Evolution of the Elements (Cambridge University Press), 4, 422 Lubin, L. M., Postman, M., & Oke, J. B. 1998, AJ, 116, 643 Mamon, G., Biviano, A., & Murante, G. 2010, A&A, 520, A30 Munari, E., Biviano, A., Borgani, S., et al. 2013, MNRAS, 430, 2638 Navarro, J. F., Frenk, C. S., & White, S. D. M. 1997, ApJ, 490, 493 Planck Collaboration XXVII. 2016, A&A, 594, A27 y p Hao, J., McKay, T. A., Koester, B. P., et al. 2010, ApJS, 191, 254 y p Hao, J., McKay, T. A., Koester, B. P., et al. 2010, ApJS, 191, 254 p Schlegel, D. J., Finkbeiner, D. P., & Davis, M. 1998, ApJ, 500, 52 y Kennicutt, R. C. 1992, ApJS, 79, 255 y Kennicutt, R. C. 1992, ApJS, 79, 255 p Kettula, K., Finoguenov, A., Massey, R., et al. 2013, ApJ, 778, 74 p Kettula, K., Finoguenov, A., Massey, R., et al. 2013, ApJ, 778, 74 Shibata, R., Honda, H., Ishida, M., et al. 1999, ApJ, 52 Springel, V. 2005, MNRAS, 364, 1105 Laganá, T. F., Lima Neto, G. R. Barrena et al.: The dynamical status of RXCJ1230 cluster of galaxies B., Andrade-Santos, F., et al. 2008, A&A, 485, 633 Laganá, T. F., Lima Neto, G. B., Andrade-Santos, F., et al. 2008, A&A, 485, 633 Thompson, L. A. 1982, in Early Evolution of the Universe and the Present Structure, eds. G. O. Abell, & G. Chincarini (Dordrecht: Reidel), IAU Symp., 104 Loewenstein, M. 2003, Origin and Evolution of the Elements (Cambridge University Press), 4, 422 Loewenstein, M. 2003, Origin and Evolution of the Elements (Cambridge University Press), 4, 422 Tonry, J., & Davis, M. 1979, ApJ, 84, 1511 y Lubin, L. M., Postman, M., & Oke, J. B. 1998, AJ, 116, 643 y ubin, L. M., Postman, M., & Oke, J. B. 1998, AJ, 116, 643 Umetsu, K. 2000, A&A Rv., 28, 7 Mamon, G., Biviano, A., & Murante, G. 2010, A&A, 520, A30 Mamon, G., Biviano, A., & Murante, G. 2010, A&A, 520, A30 van Weeren, R. J., de Gasperin, F., Akamatsu, H., et al. 2019, Space Sci. Rev., 215, 16 Munari, E., Biviano, A., Borgani, S., et al. 2013, MNRAS, 430, 2638 Navarro, J. F., Frenk, C. S., & White, S. D. M. 1997, ApJ, 490, 493 Planck Collaboration XXVII. 2016, A&A, 594, A27 , , , , , , p , , Planck Collaboration XXVII. 2016, A&A, 594, A27 Wen, Z. L., Han, J. L., & Liu, F. S. 2009, ApJS, 183, 197 Wen, Z. L., Han, J. L., & Liu, F. S. 2009, ApJS, 183, 197 A78, page 11 of 11
W2900591407.txt	https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0006748&type=printable	en		Dengue seroprevalence in a cohort of schoolchildren and their siblings in Yucatan, Mexico (2015-2016)	PLoS neglected tropical diseases	2,018	cc-by	8,971	RESEARCH ARTICLE Dengue seroprevalence in a cohort of schoolchildren and their siblings in Yucatan, Mexico (2015-2016) Norma Pavı́a-Ruz1, Gloria Abigail Barrera-Fuentes ID1, Salha Villanueva-Jorge2, Azael Che-Mendoza1, Julio César Campuzano-Rincón3, Pablo Manrique-Saide ID4, Diana Patricia Rojas ID5,6, Gonzalo M. Vazquez-Prokopec ID7, M. Elizabeth Halloran ID6,8,9¤, Ira M. Longini5,6, Héctor Gómez-Dantés ID10* a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS 1 Centro de Investigaciones Regionales “Dr. Hideyo Noguchi”, Universidad Autónoma de Yucatán, Merida, Yucatan, Mexico, 2 Laboratorio Estatal de Salud Pública y Referencia Epidemiológica, Servicios de Salud de Yucatán, Merida, Yucatan, Mexico, 3 Centro de Investigación en Salud Poblacional, Instituto Nacional de Salud Pública, Cuernavaca, Morelos, Mexico, 4 Campus de Ciencias Biológicas y Agropecuarias, Universidad Autónoma de Yucatán, Merida, Yucatan, Mexico, 5 Department of Biostatistics, University of Florida, Gainesville, Florida, United States of America, 6 Center for Inference and Dynamics of Infectious Diseases, Seattle, Washington, United States of America, 7 Department of Environmental Sciences, Emory University, Atlanta, Georgia, United States of America, 8 Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America, 9 Department of Biostatistics, University of Washington, Seattle, Washington, United States of America, 10 Center for Health Systems Research, National Institute of Public Health, Mexico City, Mexico Citation: Pavı́a-Ruz N, Barrera-Fuentes GA, Villanueva-Jorge S, Che-Mendoza A, CampuzanoRincón JC, Manrique-Saide P, et al. (2018) Dengue seroprevalence in a cohort of schoolchildren and their siblings in Yucatan, Mexico (2015-2016). PLoS Negl Trop Dis 12(11): e0006748. https://doi. org/10.1371/journal.pntd.0006748 ¤ Current address: Department of Biostatistics, University of Washington, Seattle, Washington, United States of America * hector.gomez@insp.mx Editor: Robert C Reiner, University of Washington, UNITED STATES Background Received: April 2, 2018 Accepted: August 12, 2018 Published: November 21, 2018 Copyright: © 2018 Pavı́a-Ruz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: Data cannot be shared publicly to keep the confidentiality of the families. Data from the cohort study is available on request to the Institutional Review Board at the Hospital General “Dr. Agustin O’Horan” of Yucatan, Mexico for researchers who meet the criteria for access to confidential data. Please contact Dr. Adolfo Palma Chan. Mailing address: Avenida Itzaes s/n, Centro, Jacinto Canek, 97000, Merida Yucatan, Mexico. email: adolfopalma@prodigy.net. mx. Phone number: 0-199-9303320 ext 45480. Abstract The implementation of vector control interventions and potential introduction new tools requires baseline data to evaluate their direct and indirect effects. The objective of the study is to present the seroprevalence of dengue infection in a cohort of children 0 to 15 years old followed during 2015 to 2016, the risk factors and the role of enhanced surveillance strategies in three urban sites (Merida, Ticul and Progreso) in Yucatan, Mexico. Methods A cohort of school children and their family members was randomly selected in three urban areas with different demographic, social conditions and levels of transmission. We included results from 1,844 children aged 0 to 15 years. Serum samples were tested for IgG, NS1 and IgM. Enhanced surveillance strategies were established in schools (absenteeism) and cohort families (toll-free number). Results Seroprevalence in children 0 to 15 years old was 46.8 (CI 95% 44.1–49.6) with no difference by sex except in Ticul. Prevalence increased with age and was significantly lower in 0 to 5 years old (26.9%, 95% CI:18.4–35.4) compared with 6 to 8 years old (43.9%, 95% CI:40.1–47.7) and 9 to 15 years old (61.4%, 95% CI:58.0–64.8). Sharing the domestic PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 1 / 17 Dengue seroprevalence in schoolchildren in Mexico Funding: Sanofi-Pasteur Laboratories (DNG25); National Institute of Allergy and Infectious Diseases (R37 AI032042) and National Institute of General Medical Sciences (U54 GM111274) from NIH financed this Project. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. space with other families increased the risk 1.7 times over the individual families that own or rented their house, while risk was significantly higher when kitchen and bathroom were outside. Complete protection with screens in doors and windows decreased risk of infection. Seroprevalence was significantly higher in the medium and high risk areas. Conclusions The prevalence of antibodies in children 0 to 15 years in three urban settings in the state of Yucatan describe the high exposure and the heterogenous transmission of dengue virus by risk areas and between schools in the study sites. The enhanced surveillance strategy was useful to improve detection of dengue cases with the coincident transmission of chikungunya and Zika viruses. Author summary Dengue is a major public health problem in Latin America. Its transmission is highly heterogeneous, and its burden varies by geographic region, age group affected, serotype and other factors. While surveillance of dengue in the region has improved, several limitations remain, including under detection, misdiagnosis and the complexity of controlling a vector that has adapted to human dwellings in tropical and subtropical urban contexts. Prospective studies have become crucial to understand the transmission of dengue in urban environments and assess the impact of control strategies, such as the introduction of a dengue vaccine or additional vector control interventions. Our findings provide epidemiological data regarding the serological profile and risk factors for dengue infections in a cohort of children 0 to 15 years old in an endemic state in Mexico and confirmed the high exposure in these age groups. Likewise, enhanced and passive surveillance of cases gave us the opportunity to measure the behavior of dengue activity during chikungunya and Zika viruses’ arrival, which we believe will contribute to improve the design of surveillance and control strategies. Introduction Dengue is a major public health problem in Latin America due to the increasing trend of cases, the vast urban areas affected, and the complexity of controlling a vector that has adapted to human dwellings in tropical and subtropical urban contexts [1]. Accurate estimates of the burden of dengue [2] are difficult because of the high proportion of asymptomatic infections, the syndromic nature of the clinical spectrum that allows for misdiagnosis with other viral infections [3], the limited capacities of the surveillance systems, and the low demand for health services by affected populations [4–6]. Transmission of the four dengue serotypes in endemic countries is heterogeneous with respect to the age groups affected, the seasonality, and the intensity and severity of epidemics[7]. An improved understanding of the complex dynamic of factors involved in dengue transmission requires the characterization of different parameters related to the incidence of asymptomatic, sub-clinical and symptomatic infections [8,9]; the prevalence and seroconversion rates by age group and sex; the herd immunity to specific serotypes [10]; the profile of primary and secondary infections and risk factors associated with severe dengue; as well as their PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 2 / 17 Dengue seroprevalence in schoolchildren in Mexico relationship with the entomological variables at the individual, household, neighborhood, locality and regional levels [11–14]. Prospective studies have become crucial for understanding dengue transmission in urban settings and are invaluable in providing the data required to effectively evaluate the impact of traditional and innovative control strategies [15,16]. In endemic areas, transmission dynamics can be better understood with the longitudinal study of young and naïve populations [17]. Selecting school children as the basis for a cohort has several advantages. They are generally susceptible to dengue infection; can be involved and followed-up for longer periods through their attendance to nearby schools; their families are responsive and supportive to health initiatives arising from the educational institutions, and their households are near the school facilitating logistics for follow-up and allowing for a febrile and absentee school-based surveillance system [18] to monitor under reporting of febrile and dengue cases. In addition, there are concerns about the specific risks that school grounds may have in triggering transmission in certain environments [19]. The availability of a licensed vaccine poses different challenges to current dengue control programs since its gradual introduction is not expected to cover all susceptible and at-risk populations or even provide complete immunity in target groups. In each of these populations there are several questions that need to be addressed regarding the clinical spectrum and transmission risks where the vaccine or any other control innovation may provide a potential benefit [20]. The objective was to describe the seroprevalence of dengue infection in a cohort of children from elementary and middle schools in three urban sites with different socio-demographiceconomic profiles and transmission patterns in the state of Yucatan, Mexico. This study presents the seroprevalence status, the socio-demographic risk factors associated with dengue infection, and the results of enhanced surveillance strategies established to support detection of dengue cases from 2015 through 2016. Methods This cohort study was designed to generate baseline epidemiological information of dengue transmission during 2015 and 2016 in three urban areas in the southern state of Yucatan, Mexico. Study sites Merida is the capital and major human settlement of Yucatan State, with 892,363 inhabitants (42.5% of the state population) and 257,826 (46.4%) houses. It is the most important economic city, concentrating 50% of the industrial activity. Approximately 1 million national and 250,000 international tourists visit Merida every year [21]. Climate in Yucatan is warm and humid, and the rainy season falls between June and October; the mean annual temperature is 25.9◦C (19.5 to 33.6) and annual precipitation is 1050 (mm). Merida concentrates ~60% of all dengue cases reported in the state. Ticul is an urban locality, located 96 kilometers south of Merida with 40,161 people and about 9,808 houses, concentrates around 3% of all dengue cases in the state. Progreso is the major seaport located 27 km north of Merida. It has 59,122 people and about 16,020 houses. Progreso is the most popular beach resort and tourist destination for many local citizens as well as national and international visitors (291,709 tourists and 136 cruises ship every year). Consequently, most inhabitants of Progreso (60.4%) are involved in commercial and tourist services. Progreso represents around 1% of all dengue cases reported in Yucatan. PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 3 / 17 Dengue seroprevalence in schoolchildren in Mexico The cohort study was initially defined by a random selection of five extensive geographical areas within those cities. These included: two low risk areas (one urban area in the north of Merida and the town of Progreso); two medium risk areas (one urban area in central Merida and the town of Ticul); and one high-risk urban area in the south of Merida. The definition of risk was determined by the historical reports of the number of dengue cases, the percent of cases reported every year and the continuous transmission during 6 to 8 or more weeks every year provided by the state surveillance system [22]. The entire study population was composed of a cohort of children (index children) in elementary and middle schools together with their family members sharing the same home with the index children (family equals number of index children). This report describes the results from the cohort of index school children and their siblings up to 15 years of age. Enrolment of school children and their families The State Ministry of Education of Yucatan provided a list of elementary public schools located in the selected areas, and a cohort of children from 1st to 3rd grade (6 to 8 years old) was randomly selected from eight schools in Merida, four in Progreso and two from Ticul. A convenience sample of 50 children per grade was defined to gather 150 school children (index children) in each of the five risk areas (450 for Merida (150 in each low, middle high risk areas), 150 for Ticul (middle risk) and 150 for Progreso (low risk)). Because children from different grades could come from the same family, we restricted the selection to one child per family to have 50 different and independent families per grade. Recruitment of school-aged children (between 6 to 12 years) included invitation to all other members of the household of the children enrolled. Consent and assent forms were obtained individually from each adult and from parents in the case of children and participants younger than 18 years old and were signed before blood samples were taken. Exclusion criteria included refusal to participate or plans to move outside of the study area during the months following enrolment. The enrolment of new school children in the 2nd year (2016) was designed to incorporate 50 new 1st grade children per risk area from the same elementary schools or additional ones when required. Based on the results of the dengue vaccine trials [23] the target groups for the vaccine were children over 9 years old instead of under-five years old. Therefore, the recruitment scheme changed to include more children aged 9 to 12 years old from new middle schools. From the additional 150 new children required from middle schools in Merida, only 134 were recruited along with 37 from elementary schools (171 new index children). Ticul and Progreso recruited 50 middle school children each plus 19 and 16 new index children from elementary schools, respectively. Baseline and follow-up evaluations of the cohort population were obtained during the period December 2014 through August 2016 with baseline demographic information, clinical history of dengue and blood samples taken for serological evidence of dengue virus (DENV) infection after the annual transmission season (August to December). Baseline and first follow up evaluation are presented here. Individual, family and household questionnaires The data collected included individual, family and household questionnaires and was obtained by a multidisciplinary field team called “Familias sin Dengue” (FSD = Families without dengue) integrated by physicians, nurses, social scientists and technical personnel. Basic data regarding house characteristics included construction material, number of rooms, sanitation services (potable water, sewage, garbage collection), water use patterns, and physical protection of windows such as screens in doors and windows. The individual and family questionnaires PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 4 / 17 Dengue seroprevalence in schoolchildren in Mexico included basic demographic data (age, sex, education level, occupation, among others) together with a clinical history of dengue including signs and symptoms, dates of occurrence, access or utilization of health services and hospitalization. The febrile questionnaire included data regarding febrile episodes, symptoms, dates, duration, severity, movements outside the area, utilization of health services, contacts and blood sample results (serology). Symptomatic dengue was detected through passive surveillance for dengue-associated symptoms and absenteeism from schools. The clinical team of FSD visited schools every week, checked attendance, and visited the homes of absentees. If absentees had a febrile illness in the previous week, they were evaluated with a physical exam and an acute blood sample to confirm infection. In addition, this population was monitored for febrile symptoms and suspected dengue illness through a toll-free number where parents could call for medical assistance when febrile disease appeared in any member of the family. This free of charge telephone line was directed only to the members of the cohort so as to voluntarily report febrile cases to the team (FSD) where a physician in charge would respond to their request. Participants were defined as lost to follow up after a full year had passed since their previous blood sample, despite repeated attempts to locate the participant, or if there was a verifiable reason for dropping from the study (voluntary request from the participant, movement from the study area). Laboratory procedures Baseline serum samples were taken to test for IgG antibodies by capture enzyme-linked immunosorbent assay (ELISA-Panbio). A 5ml of peripheral venous blood was obtained with BD Vacutainer and centrifuged at 3000 rpm (Bio-Lion XC-L4). The serum was stored at 4±2˚C and aliquots obtained with Scilogex micropette plus autoclavable pipettor of 500μl at -70˚C (Eppendorf CryoCube F570-86 Upright). Following the reference values, negative, equivocal and positive results were determined as <9, 9–11 and >11 Panbio units, respectively. Febrile episodes in enhanced surveillance were classified as DENV infections based on NS1 and IgM serology. Statistical analysis Descriptive analysis of the cohort included school children and their siblings aged 0 to 15 years. Participants were stratified in three age groups (0 to 5, 6 to 8 and 9 to 15 years old). Dengue IgM and IgG results above >11 Panbio units were considered positive for dengue and were included as the dependent variable in the analysis. The logistic regression analysis was adjusted by age and sex and was used to identify risk factors for dengue infection. Odds ratios (ORs) and their 95% confidence intervals were calculated and statistically significant differences (p<0.05) were included in the final model. The analysis was done with STATA 14.2. The protocol was approved by the Ethics and Research Committee from the O´Horan General Hospital from the state Ministry of Health, Register No. CEI-0-34-1-14 and the review board at the Fred Hutchinson Cancer Research Center. Results A total of 767 index children and 3,401 family members were recruited in year 1. In Merida, 463 families and index school children and 448 siblings aged 0 to 15 years old were enrolled at baseline from eight elementary schools: 151 from low risk area, 153 from middle risk and 159 from high risk area. In Ticul, a total of 151 families and index school children were recruited from two elementary schools along with 170 siblings aged 0 to 15 years old. In Progreso, 153 families and index school children from four elementary schools together with 136 siblings PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 5 / 17 Dengue seroprevalence in schoolchildren in Mexico Table 1. Cohort of school children by city, Yucatan, 2015 to 2016. 2015ʹs Cohort (Y1) Merida N Recruitment Lost to follow up Progreso (%) N Ticul (%) N Total (%) N (%) Index children 463 51 153 53 151 47 767 50 Siblings 448 49 136 48 170 53 754 50 Total 911 100 289 100 321 100 1521 100 Index children 149 32 21 14 19 13 189 25 Siblings 155 35 23 17 44 26 222 29 Subtotal 304 33 44 15 63 20 411 27 Index children 314 68 132 86 132 87 578 75 Siblings� 347 65 147 83 134 74 628 71 Baseline cohort (Y1) Total 661 100 279 100 266 100 1206 100 New participants (2016) Index children 171 48 66 47 69 48 306 48 Follow up Cohort 2016 (Y2) Siblings 185 52 73 53 74 52 332 52 Subtotal 356 100 139 100 143 100 638 100 Index children 485 48 198 47 201 49 884 48 Siblings 532 52 220 53 208 51 960 52 1017 100 418 100 409 100 1844 100 Total cohort � Total includes siblings not participating in Y1 but decided to participate in Y2. https://doi.org/10.1371/journal.pntd.0006748.t001 were selected (Table 1). The total number of children aged 0 to 15 years old in the 2015 cohort was 1,521 of whom 1301 (85%) had blood sampled. During the period we lost 189 families that add up to 1,096 individuals, 37% of which (411) were under 15 years old. The baseline cohort (year 1) ended with 578 families and 2,305 individuals of whom 1,110 (48.2%) were children aged 0 to 15 years old. Baseline samples for this first year accounted for 972 (87%) of school children in the cohort. The enrolment of new index children (middle plus elementary schools) incorporated 306 new families and index students along with 1,688 new participants, including 734 new children aged 0 to 15 years old (Fig 1). The baseline cohort experienced losses to follow-up and drop out in different proportions in the five areas studied. Of the total 2,255 school children recruited in both years we included in this report 1,844 children aged 0 to 15 years (884 index children) with a total of 1,571 blood samples taken (85%) (S1 Table). The results of paired samples taken in the same individuals in baseline and follow up are presented elsewhere. Voluntary dropouts were more frequent in Merida (21.8%) than in Progreso (9.8%) or Ticul (9.9%). Dropout due to the family moving from the area of study or not found in subsequent visits was much higher in Merida (10.4%) than Progreso (3.9%) or Ticul (2.6%). We had a 76% success of follow up in Merida but higher in Progreso (90%) and Ticul (91%) (Table 1). The family patterns are basically nuclear with similar composition between cities, nevertheless, families lost to follow-up had a higher average number of individuals per family (5.9, range 2–9) than families that were followed up (4.8, range 2–10). Progreso and Ticul showed more stable patterns of mobility within the neighborhoods where they lived, which was not the case in Merida. Demographic characteristics of the cohort Sex distribution in the cohort of school children was very similar (48.7% women and 51.3% men) in all risk areas although low risk Merida had 59.1% male children. The age distribution of all children was 14.3% for children under five years old, 39.9% for 6 to 8 years old and 45.9% PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 6 / 17 Dengue seroprevalence in schoolchildren in Mexico Fig 1. Cohort of families and school children aged 0 to 15 years old, 2015–2016. Percent represents blood samples coverage of 0 to 15 years old. https://doi.org/10.1371/journal.pntd.0006748.g001 for children aged 9 to 15 years old. Ticul had the lowest proportion of children under five years (8.6%) (Table 2). Socioeconomic conditions of households House property patterns in Yucatan showed that most of the houses were privately owned (70.5%), few were rented (4.5%) and 25% shared with other families (usually kin). Construction materials of walls, floor and roof were cement (>95%) although palm roofs in Progreso (7.7%) and Ticul (7.9%) described particular socioeconomic conditions of some families participating in the study. Most of the houses (72%) had 2 to 3 rooms while 18.8% of houses in Ticul, low risk Merida (18.2%) and high risk Merida (15.9%) had 4 to 5 rooms. Protection with screens in doors and windows was a common practice in this region with almost 95% of houses with at least one door or window protected. The presence of kitchen and bathroom outside the house was much more common in Ticul (25.7% and 24.1% respectively) than in Progreso (3.3% and 12.6%) and the high risk area in Merida (7.7% and 12.6%). Access to potable water was also a common feature (>90%) in the three cities but the need to store water for several domestic activities was also very common (45.9%) in all sites, particularly in Ticul that reported a higher need to store potable water (78%). Garbage collection was a widespread public service in the areas, although in Ticul, 19.4% of households reported the need to burn or throw away the garbage (Table 3). Serology results The percentage of blood sampling in 1,521 children in the 2015 cohort and 1,844 children in 2016 was 85% (Fig 1). Ticul had the highest coverage (90.5%) of blood samples, Merida had similar coverages by risk areas (87%), while Progreso presented the lowest coverage (75.6%). PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 7 / 17 Dengue seroprevalence in schoolchildren in Mexico Table 2. Demographic characteristics of school children in Yucatán, 2016. Variables Merida LR n (%) Progreso n (%) MR n (%) Ticul n (%) Total n (%) HR n (%) Sex Women 124 (40.9) 180 (47.9) 169 (50.0) 207 (49.5) 218 (53.3) 898 (48.7) Men 179 (59.1) 196 (52.1) 169 (50.0) 211 (50.5) 191 (46.7) 946 (51.3) Total 303 (100) 376 (100) 338 (100) 418 (100) 409 (100) 1844 (100) Age 0–5 46 (15.2) 62 (16.5) 50 (14.8) 70 (16.7) 35 (8.6) 263 (14.3) 6–8 120 (39.6) 141 (37.5) 125 (37.0) 169 (40.4) 180 (44.0) 735 (39.9) 9–15 137 (45.2) 173 (46.0) 163 (48.2) 179 (42.8) 194 (47.4) 846 (45.9) Total 303 (100) 376 (100) 338 (100) 418 (100) 409 (100) 1844 (100) LR: Low risk, MR: Medium risk, HR: high risk. https://doi.org/10.1371/journal.pntd.0006748.t002 There were 888 (68.3%) paired samples in children. Again, Ticul led the blood sampling with 79.3%, followed by Progreso (70%) and Mérida (63.7%). (S1 Table). Seroprevalence of 0 to 15 years old was 46.8 (CI 95% 44.1–49.6). Overall seroprevalence to dengue showed no difference in females (53.9%, 95% CI: 50.4–57.4) compared to males (49.4%, 95% CI: 45.8–52.9) and differences by age group or city were not significant except in Ticul (61%, 95% CI: 53.9–67.9) for female vs male (49.4% 95% CI: 45.82–52.87). Seroprevalence increased with age and was significantly lower in 0 to 5 years old (26.9%, 95% CI:18.4– 35.4) compared with children 6 to 8 years old (43.9%, 95% CI:40.1–47.7) and 9 to 15 years old (61.4%, 95% CI:58.0–64.8). Seroprevalence by age group and risk area showed significant differences between the 0 to 5 years old compared to the 9 to 15 years old in low risk Merida (15.8%, 95% CI: -0.61–32.2 vs 61.5%, 95% CI:53.2–69.9), medium risk Merida (13.3%, 95% CI:1.2–25.5 vs 66.2%, 95% CI:58.9–73.6) and Ticul (30%, 95% CI:1.6–58.4 vs 69.0%, 95% CI:62.3–75.6) but not in Progreso or high risk Merida. Differences between 6 to 8 years old and the 9 to 15 age groups were significant in all risk areas except Progreso (Fig 2). Seroprevalence by schools Seroprevalence by school showed variations in dengue exposure within areas of risks. The lowest rate in low risk areas like Progreso or low risk area in Merida are not different from the lowest rate in Ticul or high risk Merida. Similar patterns appeared in the schools with the highest seroprevalence in each risk area (Fig 3). Risk factors and dengue infection The multivariate analysis of children with blood results showed no difference by sex but dengue risk increased with age, being four times higher for those 9 to 15 years old compared to children under five years old. While parents reported very few cases of dengue in the previous year, the history of dengue was significant as well as the report of dengue confirmation by health personnel. Regarding the risks derived from household conditions obtained by the questionnaires: sharing the domestic space with other families increased the risk 1.7 times over the individual families that own or rented their house, and the risk of dengue was significantly higher when kitchen and bathroom were located outside the house. Protection with screens of windows showed a good level of protection only when screens cover all the windows. While bivariate analysis of the prevalence of dengue by urban areas showed discrete differences, the analysis combining areas of risk (Progreso and low risk Merida vs. medium risk Merida and PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 8 / 17 Dengue seroprevalence in schoolchildren in Mexico Table 3. Households characteristics in Merida, Ticul and Progreso, 2016. Variables Merida LR n (%) Progreso n (%) MR n (%) Ticul n (%) Total n (%) HR n (%) House Own Rent Shared Total 124 (75.2) 130 (79.3) 127 (69.8) 143 (78.6) 99 (51.8) 623 (70.5) 40 (4.5) 8 (4.8) 8 (4.9) 11 (6) 13 (7.1) 33 (20) 26 (15.9) 44 (24.2) 26 (14.3) 92 (48.2) 221 (25) 165 (100) 164 (100) 182 (100) 182 (100) 191 (100) 884 (100) 165 (100) 164 (100) 180 (98.9) 168 (92.3) 176 (92.1) 853 (96.5) 2 (1.1) 14 (7.7) 15 (7.9) 31 (3.5) Roof Cement Palm Total 165 (100) 164 (100) 182 (100) 182 (100) 191 (100) 884 (100) Cement 165 (100) 164 (100) 182 (100) 181 (99.5) 188 (98.4) 880 (99.5) Total 165 (100) 164 (100) 182 (100) 182 (100) 191 (100) 884 (100) 165 (100) 164 (100) 181 (99.5) 179 (98.4) 186 (97.4) 875 (99) 1 (0.5) 3 (1.6) 5 (2.6) 9 (1) Floor Walls Cement Wood Total 165 (100) 164 (100) 182 (100) 182 (100) 191 (100) 884 (100) 7 (4.2) 2 (1.2) 20 (11) 39 (21.4) 24 (12.6) 92 (10.4) Rooms 1 2 to 3 124 (75.2) 136 (82.9) 125 (68.7) 129 (70.9) 123 (64.4) 637 (72.1) 4 to 5 30 (18.2) 22 (13.4) 29 (15.9) 13 (7.1) 36 (18.8) 130 (14.7) 4 (2.4) 4 (2.4) 8 (4.4) 1 (0.5) 8 (4.2) 25 (2.8) 165 (100) 164 (100) 182 (100) 182 (100) 191 (100) 884 (100) >5 Total Screened windows 0 10 (6.1) 2 (1.2) 10 (5.5) 9 (4.9) 9 (4.7) 40 (4.5) 1 47 (28.5) 59 (36) 51 (28) 99 (54.4) 28 (14.7) 284 (32.1) 2 62 (37.6) 73 (44.5) 77 (42.3) 58 (31.9) 124 (64.9) 394 (44.6) 46 (27.9) 30 (18.3) 44 (24.2) 16 (8.8) 30 (15.7) 166 (18.8) 165 (100) 164 (100) 182 (100) 182 (100) 191 (100) 884 (100) 3 or more Total Screened doors 0 3 (1.9) 1 (0.6) 3 (1.7) 4 (2.2) 11 (1.3) 1 22 (13.9) 32 (19.9) 29 (16.4) 42 (23.1) 10 (5.2) 135 (15.5) 2 93 (58.9) 105 (65.2) 127 (71.8) 119 (65.4) 166 (86.9) 610 (70.2) 3 or more 40 (25.3) 23 (14.3) 18 (10.2) 17 (9.3) 15 (7.9) 113 (13) 158 (100) 161 (100) 177 (100) 182 (100) 191 (100) 869 (100) 160 (97) 162 (98.8) 167 (92.3) 176 (96.7) 142 (74.3) 807 (91.4) 5 (3) 2 (1.2) 14 (7.7) 6 (3.3) 49 (25.7) 76 (8.6) 165 (100) 164 (100) 181 (100) 182 (100) 191 (100) 883 (100) 165 (100) 164 (100) 177 (97.3) 171 (94) 183 (95.8) 860 (97.3) 5 (2.7) 11 (6) 8 (4.2) 24 (2.7) (100) 182 (100) 191 (100) 884 (100) Total Kitchen Inside Outdoors Total Bathroom WC Letrine/outdoors Total 165 (100) 164 (100) 182 160 (97) 161 (98.2) 159 (87.4) 159 (87.4) 145 (75.9) 784 (88.7) 5 (3) 3 (1.8) 23 (12.6) 23 (12.6) 46 (24.1) 100 (11.3) 165 (100) 164 (100) 182 (100) 182 (100) 191 (100) 884 (100) Bathroom Inside Outdoors Total (Continued ) PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 9 / 17 Dengue seroprevalence in schoolchildren in Mexico Table 3. (Continued) Variables Merida LR n (%) Progreso n (%) MR n (%) Ticul n (%) Total n (%) HR n (%) Potable water Yes 146 (88.5) 159 (97) 173 (95.1) 171 (94.0) 189 (99) 838 (94.8) Total 165 (100) 164 (100) 182 (100) 182 (100) 191 (100) 884 (100) Yes 60 (36.4) 75 (45.7) 86 (47.3) 36 (19.8) 149 (78) 406 (45.9) No 105 (63.6) 89 (54.3) 96 (52.7) 146 (80.2) 42 (22) 478 (54.1) Total 165 (100) 164 (100) 182 (100) 182 (100) 191 (100) 884 (100) 164 (99.4) 163 (99.4) 178 (97.8) 166 (91.2) 154 (80.6) 825 (93.3) 1 (0.6) 1 (0.6) 4 (2.1) 16 (8.7) 37 (19.4) 59 (7.7) 165 (100) 164 (100) 182 (100) 182 (100) 191 (100) 884 (100) Storing water Garbage Municipal service Burns/throw Total LR: Low risk, MR: Medium risk, HR: high risk. https://doi.org/10.1371/journal.pntd.0006748.t003 Ticul, and high risk Merida alone) pointed out that risk of infection was significantly higher in the medium and high risk areas compared to those in the low level risk (Table 4). School absenteeism Surveillance of absenteeism in the schools showed 98 cases of absentees due to fever (January to June 2015). An outbreak of 57 cases of chickenpox was detected along with three likely cases of dengue that had negative test results. During the second semester, an outbreak of chikungunya emerged in the State of Yucatan, four schools closed for four days and 20 probable cases of dengue and 34 of chikungunya were detected. In Ticul, 44 children were detected as absentees and only three probable cases of dengue were detected with negative results. A total of seven cases of chikungunya were reported. In Progreso, 11 children were absent, six cases were respiratory infections, two diarrheas, two cases of conjunctivitis and one with chickenpox. From Fig 2. Seroprevalence of school children by age group and risk areas, Yucatan, 2016. Seroprevalence is represented by percentage and 95% CI. https://doi.org/10.1371/journal.pntd.0006748.g002 PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 10 / 17 Dengue seroprevalence in schoolchildren in Mexico Fig 3. Seroprevalence by schools and risk areas, Yucatan, 2016. Seroprevalence is represented by percentage and 95% CI. https://doi.org/10.1371/journal.pntd.0006748.g003 September to November, three fever cases were reported, two suspected cases of dengue that were negative. During 2016, absenteeism surveillance reported 434 total cases of absenteeism, 219 cases (50%) due to fever. Four cases were surgical pathologies and only two clinical dengue cases; 107 cases of respiratory diseases and 78 chickenpox cases (46% and 51% were in Merida and Ticul schools), 28 cases were not located. A total of 53 cases of absenteeism were reported in cohort students: 23% (12/53) were non-febrile cases; 77% due to febrile pathologies such as allergy symptoms (1), abdominal pain (1), respiratory tract infections (27), urinary infection (1), chickenpox (10) and one family was not located. Toll-free number During 2015, 373 telephone calls were received by the FSD group, 32.5% (n = 121) were not related to a febrile episode and patients were referred to their family physician or clinic. Around 59.1% (n = 149/252) of febrile patients that contact the dengue line had previously consulted a physician who gave the diagnosis of probable dengue and people requested the blood sample for confirmation of clinical diagnosis. The febrile patients (n = 103/252) who did not consult a physician, 59.2% (n = 61/103) mentioned previous contact with a dengue case in their neighborhood. Of all febrile patients that contact the dengue line, 78.82% (n = 294) had 2 or more days with fever (>38 ˚C). The age group that more frequently contact the FSD line was the 20–49 years group (41.5%), followed by the 5–9 years old (25%), >50 years (13.3%), 10–14 years (10.2%), 15–19 years (5.5%) and 0–4 years old (4.5%). The average number of days between the beginning of the fever and the blood sample was 3.9±3.7 days, with significant variations between cities: Merida 4.4 days, Progreso 3.2 days and Ticul 2.8 days. Through the enhanced surveillance strategies (absenteeism and toll-free number) 244 serological tests for dengue (IgM or NS1) were performed, 59% (n = 144) from Merida, 17% (n = 42) from Progreso and 24% (n = 58) from Ticul. Only 8% of these samples were positive for dengue. Discussion The results provided by the cohort of school children in three urban settings in the state of Yucatan, Mexico, described the high exposure to dengue infection in scholar groups that increased with age, without differences by sex but with significant differences between low, medium and high risk areas. The prevalence of antibodies in children 9 to 15 years above 60% PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 11 / 17 Dengue seroprevalence in schoolchildren in Mexico Table 4. Risk factors and dengue infection school children 0 to 15 years old, Yucatan, 2016. Factors OR CI 95% p value (<0.05)� Sex Woman 1.0 Man 0.9 0.8–1.1 0.370 � Age 0 to 5 1.0 6 to 8 1.9 1.3–3.0 0.002� 9 to 15 4.1 2.7–6.3 0.000� 1.8–10.1 0.001� 2.1–24.5 0.002� History of dengue No 1.0 Yes 4.3 Confirmed by health personnel No 1.0 Yes 7.1 House property Rent 1.0 Own 0.7 0.3–1.3 0.334 Shared 1.7 1.2–2.3 0.001� Windows with screens 0 1.0 1–2 0.6 0.3–1.2 0.15 3 or more 0.4 0.2–0.9 0.034� 1.2–2.7 0.001� 1.2–3.1 0.005� 1.2–2.8 0.004� Doors with screens 0–1 1.0 2–3 1.8 Kitchen Inside 1.0 Outside 1.9 Bathroom Inside 1.0 Outside 1.8 Transmission risk � Low/Progreso 1.0 Medium/Ticul 1.6 1.3–2.1 0.000� High 1.4 1.1–1.9 0.005� Age is adjusted by sex, all other variables adjusted by age and sex. https://doi.org/10.1371/journal.pntd.0006748.t004 in all areas except Progreso (low risk) confirmed the high transmission of dengue virus in this endemic state of the country. Prevalence found in this study were as expected and comparable to those from other endemic countries inside and outside the Americas, as reported in urban Nicaragua (2003) [24,25] or in urban settings in Central Brazil (2001) and northeast Brazil (2013) [26] with similar exposure and prevalence rates. Studies in India also showed increasing dengue infection with age and differences by region [27] were comparable to those reported in other endemic countries like Indonesia (1996) [28]; Sri Lanka (2014) [29] and Vietnam [30]. In the case of Yucatan, a state level prevalence of 72.5% was reported since 1985 [31]; seroprevalences in school children 8 to 14 years old (1987–1988) in urban (56.8%) and rural Merida (63.7%) [32] PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 12 / 17 Dengue seroprevalence in schoolchildren in Mexico demonstrated the high exposure to dengue in the past, while another serological surveys done in Yucatan in 1996 and 2006 demonstrated seroprevalences of 22% and 20% in under five years old and 30% to 51% in 5 to 14 years old, respectively [33]. In other states of the country similar prevalence have been also reported: 35.7% in 5 to 9 years old and 52.2% for 10 to 14 years old (2011) [34]. Dengue transmission is highly heterogeneous and the burden varies by geographic region [35], countries [36], age groups affected and serotype [37]. Significant heterogeneity in transmission intensity has been identified within districts, sub-districts and even finer spatial scales like schools [38–41]. The differences between risk areas was expected since social, economic and environmental conditions have all proven to have certain influence in infection risks of populations [42,43]. These conditions could also influence transmission within the different schools in the selected areas. The low risk areas selected in our study comprise one urban area in the capital city and a town (Progreso) with historical low and occasional reports of dengue cases. Overall seroprevalence in these sites was significantly lower than the reported for medium and high risk areas. The higher prevalence of dengue infection in all age groups in Ticul (medium risk) demonstrated that conditions for transmission were wider than expected. The under report of cases by local health services as well as less demand for care from the sick population could be some distinctive traits within this community. Population movements between Ticul and high risk areas of Merida due to economic dynamics could also be a contributing factor. On the other hand, we did identify certain household risk conditions (storage of water [44], bathroom and kitchen outdoors) in Ticul that could help explain this particular situation. Window screening has been suggested as an important feature to prevent Aedes from entering houses in Merida and potentially affect dengue transmission risk as well [45]. In this study, having ample coverage of screens in windows and doors was protective and urban programs should promote the inclusion of this preventive measure in houses in high risk areas [46,47]. Under reported cases is also a very common trait in school children in several settings [48,49]. The long history of dengue in Yucatan has created conditions where dengue is no longer identified as a health threat; fever is confused with other diseases and appears as a nonspecific febrile syndrome. The enhanced strategies introduced (school absenteeism and toll-free number) helped identify new cases within the school cohort although coverage and use of the telephone line needs to be promoted within the community to become a reliable and useful surveillance tool. Regular community home-to-home visits have proven to be an additional and useful strategy to support the traditional surveillance established by the health sector [50]. Circulation of DEN-1, DEN2 and DEN-4 serotypes in the Yucatan region has not changed although the recent introduction of DEN-3 virus in 2016 could increase transmission due to low herd immunity towards this serotype. The introduction of chikungunya virus in 2015 and Zika virus in 2016 competed with all dengue serotypes and diminished the capacity to identify dengue cases by health providers and family members in the cohort as well. The enhance surveillance strategies implemented help improve detection of dengue cases under this circumstance. Limitations in our cohort are linked to the problems arising from the difficulties to engage family members and individuals in this kind of study. Losses to follow-up were higher in Merida and drop-out families were larger than those who stayed participating and it could generate under estimations of the risk of dengue in this city. The coincidence of chikungunya and Zika epidemics virus produced competing conditions for diagnosis and promoted intensive control interventions that eventually diminished our capacity to identify dengue cases or lower the transmission of dengue infection in the community. Nevertheless, the enhanced surveillance strategies allowed us to identify the three infections in our cohort. We did not PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 13 / 17 Dengue seroprevalence in schoolchildren in Mexico perform entomological surveys to establish potential differences in vector densities by risk areas and these data could provide additional to support our findings. Screening of doors and windows may behave as a proxy of entomological risk since areas with this kind of protection are prone to have higher mosquito densities. With the potential introduction of innovative preventive or vector control interventions at sight, it is imperative that countries improve their surveillance system and produce baseline data that describe the epidemiological profile of the target population in order to improve the estimates of the direct and indirect effects of these individual or combined interventions. Our results confirmed the high exposure in these age groups and provide evidence that preventive and control interventions directed to children could decrease the burden of disease in high transmission areas [51]. Supporting information S1 Table. Blood sampling in schoolchildren (baseline, follow-up and new members, 2015– 2016). (DOCX) S2 Table. STROBE Statement-checklist of items that should be included in reports of observational studies. (DOC) Acknowledgments We are indebted to the extensive support from state health and educational authorities, school teachers and particularly appreciative of the support from the “Familias sin dengue” field team. We would like to extend special regards to Elsa Sarti and Esteban Puentes who were key supporters and advisors all along the development of this Project. Author Contributions Conceptualization: Pablo Manrique-Saide, Gonzalo M. Vazquez-Prokopec, M. Elizabeth Halloran, Ira M. Longini, Héctor Gómez-Dantés. Data curation: Norma Pavı́a-Ruz, Gloria Abigail Barrera-Fuentes, Salha Villanueva-Jorge, Azael Che-Mendoza, Julio César Campuzano-Rincón, Diana Patricia Rojas, Héctor Gómez-Dantés. Formal analysis: Norma Pavı́a-Ruz, Gloria Abigail Barrera-Fuentes, Julio César CampuzanoRincón, Diana Patricia Rojas, M. Elizabeth Halloran, Ira M. Longini, Héctor GómezDantés. Funding acquisition: Norma Pavı́a-Ruz, M. Elizabeth Halloran, Ira M. Longini, Héctor Gómez-Dantés. Investigation: Norma Pavı́a-Ruz, Gloria Abigail Barrera-Fuentes, Salha Villanueva-Jorge, Azael Che-Mendoza, Pablo Manrique-Saide, Diana Patricia Rojas, Gonzalo M. VazquezProkopec, M. Elizabeth Halloran, Ira M. Longini, Héctor Gómez-Dantés. Methodology: Pablo Manrique-Saide, Gonzalo M. Vazquez-Prokopec, M. Elizabeth Halloran, Ira M. Longini, Héctor Gómez-Dantés. Project administration: Norma Pavı́a-Ruz. Resources: Norma Pavı́a-Ruz, Salha Villanueva-Jorge. PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 14 / 17 Dengue seroprevalence in schoolchildren in Mexico Software: Gloria Abigail Barrera-Fuentes, Julio César Campuzano-Rincón, Ira M. Longini. Supervision: Norma Pavı́a-Ruz, Gloria Abigail Barrera-Fuentes. Validation: Gloria Abigail Barrera-Fuentes, Salha Villanueva-Jorge, Julio César CampuzanoRincón, Diana Patricia Rojas. Writing – original draft: Norma Pavı́a-Ruz, Gloria Abigail Barrera-Fuentes, Héctor GómezDantés. Writing – review & editing: Norma Pavı́a-Ruz, Gloria Abigail Barrera-Fuentes, Azael CheMendoza, Pablo Manrique-Saide, Diana Patricia Rojas, Gonzalo M. Vazquez-Prokopec, M. Elizabeth Halloran, Ira M. Longini, Héctor Gómez-Dantés. References 1. Gubler DJ. Dengue, Urbanization and Globalization: The Unholy Trinity of the 21st Century. Trop Med Health. 2011; 39(4SUPPLEMENT):S3–11. 2. Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, et al. The global distribution and burden of dengue. Nature. 2013; 496:504–7. https://doi.org/10.1038/nature12060 PMID: 23563266 3. Capeding MR, Chua MN, Hadinegoro SR, Hussain IIHM, Nallusamy R, Pitisuttithum P, et al. Dengue and other common causes of acute febrile illness in Asia: an active surveillance study in children. PLoS Negl Trop Dis. 2013; 7(7):e2331. https://doi.org/10.1371/journal.pntd.0002331 PMID: 23936565 4. Perkins TA, Paz-Soldan VA, Stoddard ST, Morrison AC, Forshey BM, Long KC, et al. Calling in sick: impacts of fever on intra-urban human mobility. Proc R Soc B Biol Sci. 2016; 283(1834):20160390. 5. Chávez-Arias NP, Villegas-Chim JE, Wejebe-Shanahan M, Barrera-Buenfil DJ, Rafful-Ceballos MJ, Ramos-Valencia JE, et al. Studying sociocultural factors associated with dengue fever in elementary school children in Yucatan, Mexico. SAGE Research Methods Cases. 2017. 6. Sarti E, Cox H, Besada-Lombana S, Tapia-Maruri L. Dengue Awareness in Latin American Populations: A Questionnaire Study. Infect Dis Ther. 2015; 4(2):199–211. https://doi.org/10.1007/s40121-015-00688 PMID: 26021614 7. Balmaseda A, Standish K, Mercado JC, Matute JC, Tellez Y, Saborı́o S, et al. Trends in patterns of dengue transmission over 4 years in a pediatric cohort study in Nicaragua. J Infec Dis. 2010; 201(1):5–14. 8. Yoon I-K, Rothman AL, Tannitisupawong Darunee, Anon S, Jarman RG, Aldstadt J, Nisalak A, et al. Underrecognized mildly symptomatic viremic dengue virus infections in rural thai schools and villages. J Infect Dis. 2012; 206(3):389–98. https://doi.org/10.1093/infdis/jis357 PMID: 22615312 9. Endy TP, Chunsuttiwat S, Nisalak A, Libraty DH, Green S, Rothman AL, et al. Epidemiology of inapparent and symptomatic acute dengue virus infection: a prospective study of primary school children in Kamphaeng Phet, Thailand. Am J Epidemiol. 2002; 156(1):40–51. PMID: 12076887 10. Kikuti M, Cunha GM, Paploski IA, Kasper AM, Silva MM, Tavares AS, et al. Spatial distribution of dengue in a brazilian urban slum setting: role of socioeconomic gradient in disease risk. PLoS Negl Trop Dis. 2015; 9(7):e0003937. https://doi.org/10.1371/journal.pntd.0003937 PMID: 26196686 11. Cromwell EA, Stoddard ST, Barker CM, Van-Rie A, Messer WB, Meshnick SR, et al. The relationship between entomological indicators of Aedes aegypti abundance and dengue virus infection. PLoS Negl Trop Dis. 2017; 11(3):e0005429. https://doi.org/10.1371/journal.pntd.0005429 PMID: 28333938 12. Salje H, Lessler J, Berry IM, Melendrez MC, Endy T, Kalayanarooj S, et al. Dengue diversity across spatial and temporal scales: local structure and the effect of host population size. Science (80-). 2017; 355:1302–6. 13. Souza LS, Barradas-Barata R de C. Intra-urbandiferentials in dengue distribution, Cuiabá, 2007–2008. Rev Bras Epidemiol. 2012; 15(4):761–70. PMID: 23515772 14. Morrison AC, Minnick SL, Rocha C, Forshey BM, Stoddard ST, Getis A, et al. Epidemiology of dengue virus in Iquitos, Peru 1999 to 2005: interepidemic and epidemic patterns of transmission. PLoS Negl Trop Dis. 2010; 4(5):e670. https://doi.org/10.1371/journal.pntd.0000670 PMID: 20454609 15. Luz PM, Codeço CT, Massad E, Struchiner CJ. Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil. Mem Inst Oswaldo Cruz. 2003; 98(7):871–8. PMID: 14765541 16. Yoksan S, Tubthong K, Kanitwithayanun W, Jirakanjanakit N. Laboratory assays and field dengue vaccine evaluation at Ratchaburi province, Thailand: a preliminary result. J Clin Virol. 2009; 46:S13–5. PMID: 19800560 PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 15 / 17 Dengue seroprevalence in schoolchildren in Mexico 17. Endy TP, Yoon I, Mammen MP. Prospective cohort studies of dengue viral transmission and severity of disease. En: Rothman AL, editor. Dengue virus, current topics in microbiology and immunology. Springer-Verlag Berlin Heildelberg; 2010. p. 1–13. https://doi.org/10.1007/978-3-642-02215-9_1 PMID: 19802574 18. Mammen MP, Pimgate C, Koenraadt CJM, Rothman AL, Aldstadt J, Nisalak A, et al. Spatial and temporal clustering of dengue virus transmission in thai villages. Plos Med. 2008; 5(11):e205. https://doi.org/ 10.1371/journal.pmed.0050205 PMID: 18986209 19. Ratanawong P, Kittayapong P, Olanratmanee P, Wilder-smith A, Byass P, Tozan Y, et al. Spatial variations in denguetransmission in schools in Thailand. PLoS One. 2016; 11(9):e0161895. https://doi.org/ 10.1371/journal.pone.0161895 PMID: 27669170 20. Lee J, Mogasale V, Lim JK, Carabali M, Sirivichayakul K, Tho LH, et al. A multi-country study of the household willingness-to-pay for dengue vaccines: household surveys in Vietnam, Thailand, and Colombia. PLoS Negl Trop Dis. 2015; 9(6):e0003810. https://doi.org/10.1371/journal.pntd.0003810 PMID: 26030922 21. Instituto Nacional de Estadı́stica y Geogragı́a (INEGI). Anuario de estadı́sticas por entidad federativa 2010. México; 2010. 22. Escobar-Mesa J, Gómez-Dantés H. Determinantes de la transmisión de dengue en Veracruz: un abordaje ecológico para su control. Salud Publica Mex. 2003; 45(1):43–53. 23. CYD-TDV Dengue Vaccine Working Group. Efficacy and long-term safety of a dengue vaccine in regions of endemic disease. N Engl J Med. 2015; 373:1195–206. https://doi.org/10.1056/ NEJMoa1506223 PMID: 26214039 24. Balmaseda A, Hammond SN, Tellez Y, Imhoff L, Rodriguez Y, Saira I, et al. High seroprevalence of antibodies against dengue virus in a prospective study of schoolchildren in Managua, Nicaragua. Trop Med Int Heal. 2006; 11(6):935–42. 25. Balmaseda A, Standish K, Mercado JC, Matute JC, Tellez Y, Saborı́o S, et al. Trends in patterns of dengue transmission over 4 years in a pediatric cohort study in Nicaragua. J Infect Dis. 2010; 201(1):5–14. https://doi.org/10.1086/648592 PMID: 19929380 26. Castanha PMS, Cordeiro MT, Martelli CMT, Souza WV, Marques ETA, Braga C. Force of infection of dengue serotypes in a population-based study in the northeast of Brazil. Epidemiol Infect. 2013; 141:1080–8. https://doi.org/10.1017/S0950268812001367 PMID: 22800513 27. Garg S, Chakravarti A, Singh R, Masthi NRR, Chandra R, Rajesh G, et al. International Journal of Infectious Diseases Dengue serotype-specific seroprevalence among 5- to 10-year-old children in India: a community-based cross-sectional study. Int J Infect Dis. 2017; 54:25–30. https://doi.org/10.1016/j.ijid. 2016.10.030 28. Graham RR, Juffrie M, Tan R, Hayes CG, Laksono I, Roef CMA, et al. A prospective seroepidemiologic study on dengue in children four to nine years of age in Yogyakarta, Indonesia I. Studies in 1995–1996. Am J Trop Med Hyg. 1999; 61(3):412–9. PMID: 10497982 29. Jeewandara C, Gomes L, Paranavitane SA, Tantirimudalige M, Panapitiya SS, Jayewardene A, et al. Change in dengue and japanese encephalitis seroprevalence rates in Sri Lanka. PLoS One. 2015; 10 (12):e0144799. https://doi.org/10.1371/journal.pone.0144799 PMID: 26696417 30. Thai KTD, Binh TQ, Giao PT, Phuong HL, Hung LQ, Nam VN, et al. Seroprevalence of dengue antibodies, annual incidence and risk factors among children in southern Vietnam. Trop Med Int Heal. 2005; 10 (4):379–86. 31. Loroño-Pino MA, Farfán-Ale JA, Rosado-Paredes E del P, Arjona-Torres AI, Flores-Flores L-F, Cabrera-Manzano LA, et al. Prevalencia de anticuerpos contra virus dengue en Yucatán, México, 1985. Rev Lat-amer Microbiol. 1985; 31:259–62. 32. Farfán-Ale JA, Loroño-Pinto MA. The incidence of dengue virus infection in children 8 to 14 years old residing in the urban and rural areas of the city of Mérida, Yucatán. Bol Med Hosp Infant Mex. 1991; 48 (11):780–4. PMID: 1768354 33. Gómez-Caro S, Méndez-Domı́nguez N, Méndez-Galván JF. Dengue seropositivity in a randomly selected sample from Yucatan analyzed in the context of dengue cases reported between 1996 and 2006. J Epidemiol Res. 2017; 3(1):23–7. 34. Amaya-Larios IY, Martı́nez-Vega RA, Mayer S V, Galeana-Hernández M, Comas-Garcı́a A, Sepúlveda-Salinas KJ, et al. Seroprevalence of neutralizing antibodies against dengue virus in two localities in the state of Morelos, Mexico. Am J Trop Med Hyg. 2014; 91(5):1057–65. https://doi.org/10.4269/ ajtmh.14-0145 PMID: 25294613 35. Halstead SB. Dengue in the Americas and Southeast Asia: do they differ? Rev Panam Salud Pública. 2006; 20(6):407–15. PMID: 17341332 PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 16 / 17 Dengue seroprevalence in schoolchildren in Mexico 36. San-Martı́n JL, Brathwaite O, Zambrano B, Solórzano JO, Bouckenooghe A, Dayan GH, et al. The epidemiology of dengue in the Americas over the last three decades: a worrisome reality. Am J Trop Med Hyg. 2010; 82(1):128–35. https://doi.org/10.4269/ajtmh.2010.09-0346 PMID: 20065008 37. Shen S, Wei H, Fu Y, Zhang H, Mo Q, Wang X. Multiple Sources of Infection and Potential Endemic Characteristics of the Large Outbreak of Dengue in Guangdong in 2014. Nat Publ Gr. 2015;(May):1–10. 38. Rodrı́guez-Barraquer I, Buathong R, Iamsirithaworn S, Nisalak A, Lessler J, Jarman RG, et al. Revisiting rayong: shifting seroprofiles of dengue in Thailand and their implications for transmission and control. Am J Epidemiol. 2014; 179(3):353–60. https://doi.org/10.1093/aje/kwt256 PMID: 24197388 39. Braga C, Feitosa-Luna C, Turchi-Martelli CM, Vieira de Souza W, Tenório-Cordeiro M, Alezander N, et al. Seroprevalence and risk factors for dengue infection in socioeconomically distinct areas of Recife, Brazil. Acta Trop. 2013; 113(3):16. 40. Mattos-Almeida MC, Teixeira-Caiaffa W, Martins-Assuncao R, Proietti FA. Spatial vulnerability to dengue in a brazilian urban area during a 7-year surveillance. J urban Heal. 2007; 84(3):334–45. 41. Barrera R, Delgado N, Jiménez M, Villalobos I, Romero I. Estratificación de una ciudad hiperendémica en dengue hemorrxgico. Rev Panam Salud Pública. 2000; 8(4):225–33. 42. Teixeira M da G, Barreto ML, Costa M da CN, Ferreira LDA, Vasconcelos PFC, Cairncross S. Dynamics of dengue virus circulation: a silent epidemic in a complex urban area. Trop Med Int Heal. 2002; 7 (9):757–62. 43. Siqueira JB, Maciel IJ, Barcellos C, Souza W V, Carvalho MS, Nascimento NE, et al. Spatial point analysis based on dengue surveys at household level in central Brazil. BMC Public Health. 2008; 8:361. https://doi.org/10.1186/1471-2458-8-361 PMID: 18937868 44. Schmidt W, Suzuki M, Thiem VD, White RG, Tsuzuki A, Yoshida L-M, et al. Population density, water supply, and the risk of dengue fever in vietnam: cohort study and spatial analysis. Plos Med. 2011; 8(8): e1001082. https://doi.org/10.1371/journal.pmed.1001082 PMID: 21918642 45. Manrique-Saide P, Coleman P, McCall PJ, Lenhart A, Vázquez-Prokopec GM, Davies CR. Multi-scale analysis of the associations among egg, larval and pupal surveys and the presence and abundance of adult female Aedes aegypti (Stegomyia aegypti) in the city of Merida, Mexico. Med Vet Entomol. 2014; 28(3):264–72. https://doi.org/10.1111/mve.12046 PMID: 24797405 46. Vazquez-Prokopec GM, Lenhart A, Manrique-Saide P. Housing improvement: A novel paradigm for urban vector-borne disease control? Trans R Soc Trop Med Hyg. 2016; 110(10):567–9. https://doi.org/ 10.1093/trstmh/trw070 PMID: 27864518 47. Lindsay SW, Wilson A, Golding N, Scott TW, Takken W. Improving the built environment in urban areas to control Aedes aegypti-borne diseases. Bull World Health Organ. 2017; 95(8):607–8. https://doi.org/ 10.2471/BLT.16.189688 PMID: 28804174 48. Wichmann O, Yoon I, Vong S, Limkittikul K, Gibbons RV, Mammen PM, et al. Dengue in Thailand and Cambodia: an assessment of the degree of underrecognized disease burden based on reported cases. PLoS Negl Trop Dis. 2011; 5(3):e996. https://doi.org/10.1371/journal.pntd.0000996 PMID: 21468308 49. Endy TP, Chunsuttiwat S, Nisalak A, Libraty DH, Green S, Rothman AL, et al. Determinants of inapparent and symptomatic dengue infection in a prospective study of primary school children in Kamphaeng Phet, Thailand. PLoS Negl Trop Dis. 2d. C.; 5(3):e975. 50. Rocha C, Morrison AC, Forshey BM, Blair PJ, Olson JG, Stancil JD, et al. Comparison of two active surveillance programs for the detection of clinical dengue cases in Iquitos, Peru. Am J Trop Med Hyg. 2009; 80(4):656–60. PMID: 19346395 51. Ferguson NM, Rodrı́guez-Barraquer I, Dorigatti I, Mier-y-Teran-Romero L, Laydon DJ, Cummings DAT. Benefits and risks of the Sanofi-Pasteur dengue vaccine: modeling optimal deployment. Science (80-). 2016; 353(6303):1033–6. PLOS Neglected Tropical Diseases \| https://doi.org/10.1371/journal.pntd.0006748 November 21, 2018 17 / 17
https://openalex.org/W2786503273	https://arpi.unipi.it/bitstream/11568/1027350/2/JHEP_01_2018_045.pdf	English	null	Pseudorapidity distributions of charged hadrons in proton-lead collisions at s N N = 5.02 $$ \sqrt{s_{\mathrm{NN}}}=5.02 $$ and 8.16 TeV	The Journal of high energy physics/The journal of high energy physics	2,018	cc-by	16,335	Pseudorapidity distributions of charged hadrons in proton-lead collisions at √sNN = 5.02 and 8.16 TeV JHEP01(2018)045 The CMS collaboration Received: October 25, 2017 Revised: December 12, 2017 Accepted: December 27, 2017 Published: January 11, 2018 Received: October 25, 2017 Revised: December 12, 2017 Accepted: December 27, 2017 Published: January 11, 2018 Received: October 25, 2017 Revised: December 12, 2017 Accepted: December 27, 2017 Published: January 11, 2018 Open Access, Copyright CERN, for the beneﬁt of the CMS Collaboration. The CMS collaboration E-mail: cms-publication-committee-chair@cern.ch E-mail: cms-publication-committee-chair@cern.ch Abstract: The pseudorapidity distributions of charged hadrons in proton-lead colli- sions at nucleon-nucleon center-of-mass energies √sNN = 5.02 and 8.16 TeV are presented. The measurements are based on data samples collected by the CMS experiment at the LHC. The number of primary charged hadrons produced in non-single-diﬀractive proton- lead collisions is determined in the pseudorapidity range \|ηlab\| < 2.4. The charged- hadron multiplicity distributions are compared to the predictions from theoretical cal- culations and Monte Carlo event generators. In the center-of-mass pseudorapidity range \|ηcm\| < 0.5, the average charged-hadron multiplicity densities ⟨dNch/dηcm⟩ \|ηcm\| < 0.5 are 17.31 ± 0.01 (stat) ± 0.59 (syst) and 20.10 ± 0.01 (stat) ± 0.85(syst) at √sNN = 5.02 and 8.16 TeV, respectively. The particle densities per participant nucleon are compared to similar measurements in proton-proton, proton-nucleus, and nucleus-nucleus collisions. Keywords: Hadron-Hadron scattering (experiments), Heavy-ion collision ArXiv ePrint: 1710.09355 https://doi.org/10.1007/JHEP01(2018)045 Contents 1 Introduction 1 2 The CMS detector 2 3 Event selection 2 4 Data analysis 3 4.1 Systematic uncertainties 5 5 Results 6 6 Summary 9 The CMS collaboration 15 Contents 1 Introduction 2 The CMS detector 3 Event selection 4 Data analysis 4.1 Systematic uncertainties 5 Results 6 Summary The CMS collaboration Contents 1 Introduction 2 The CMS detector 3 Event selection 4 Data analysis 4.1 Systematic uncertainties 5 Results 6 Summary The CMS collaboration Contents 1 Introduction 1 2 The CMS detector 2 3 Event selection 2 4 Data analysis 3 4.1 Systematic uncertainties 5 5 Results 6 6 Summary 9 The CMS collaboration 15 1 2 2 3 5 6 9 15 JHEP01(2018)045 15 1 Introduction Studies of charged-hadron yields have long been a key tool for exploring perturbative and nonperturbative quantum chromodynamics (QCD) phenomena in high-energy particle and nuclear collisions [1]. Measurements in proton-lead (pPb) collisions can shed light on initial- state nuclear eﬀects in these interactions [2]. An example is the nuclear modiﬁcation of parton distribution functions (PDFs) that can be observed in measurements of hadron [3–7] and jet [8–10] production. Such measurements also provide reference data for understand- ing the hot, dense medium produced in nucleus-nucleus (AA) collisions. At the CERN LHC energies, measurements of proton-nucleus (pA) collisions allow studies of the nuclear gluon distributions and parton shadowing eﬀects at very small values (10−4–10−6) of the Bjorken x variable [2, 11]. This provides a crucial test of current theoretical approaches for high-energy QCD [11–13], and yields important constraints on phenomenological models and event generators [14–17]. The number of primary charged hadrons, Nch, is commonly characterized by its pseu- dorapidity density, dNch/dη. The pseudorapidity, η, is deﬁned as −ln[tan θ/2], where θ is the polar angle of the particle with respect to the beam axis. The center-of-mass energy dependence of dNch/dη constrains the theoretical modeling of particle production arising from hard and soft QCD processes in high-energy hadronic interactions. In the presence of the quark-gluon plasma (QGP), the hot medium produced in AA collisions, modiﬁcations of hadron production have been observed. Studying the energy dependence of the pseudo- rapidity density in diﬀerent colliding systems (proton-proton (pp), pA, AA), for both total inelastic and non-single-diﬀractive (NSD) [18–20] collision processes, improves our under- standing of these modiﬁcations in the AA case by identifying nuclear eﬀects present in the initial state. Monte Carlo (MC) event generators, which reproduce the main characteristics – 1 – of experimental results from hadronic collisions at lower energies, can provide predictions for the energy dependence of hadron production using diﬀerent implementations of QCD eﬀects [21]. In this paper, measurements of dNch/dηlab (where the pseudorapidity is measured in the laboratory frame) in the range \|ηlab\| < 2.4 are reported for NSD events in pPb collisions delivered by the LHC in 2016 at √sNN = 5.02 and 8.16 TeV. 1 Introduction Following earlier analyses in pp collisions at √s = 0.9–13 TeV [22–25] and in lead-lead collisions at √sNN = 2.76 TeV [26], Nch is restricted to “primary” charged hadrons, deﬁned to include prompt hadrons as well as decay products of all particles with proper decay length cτ < 1 cm, where τ is the proper lifetime of the particle and c is the velocity of light in vacuum. Contributions from prompt leptons and decay products of longer-lived particles and secondary interactions are excluded. For √sNN = 5.02 (8.16) TeV, the beam energies per nucleon were 4 (6.5) TeV and 1.58 (2.56) TeV for the proton and lead nucleus, respectively. Because the beam energies were asymmetric and the proton was going in the positive ηlab direction, massless particles emitted at midrapidity in the nucleon-nucleon center-of-mass, ηcm = 0, will be detected at ηlab = 0.465. Results are compared to predictions from the KLN model [11], as well as the Epos LHC (v3400) [17, 27], Hijing [14] (versions 1.3 [15] and 2.1 [12]), and Dpmjet- III [16] MC event generators. The √sNN dependence of dNch/dηcm in the region ηcm ≈0 is also presented. JHEP01(2018)045 2 The CMS detector The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter. Within the solenoid volume are a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter, and a brass and scintillator hadron calorimeter, each composed of a barrel and two endcap sections. The silicon tracker measures charged par- ticles within the range \|ηlab\| < 2.5. It consists of 1440 silicon pixel detector modules. The barrel region of the pixel detector consists of three layers, which are very close to the beam line. They are located at average radii of 4.3, 7.2, and 11.0 cm, and provide excellent posi- tion resolution with their 150×100 µm pixels. The forward hadron (HF) calorimeter uses steel as an absorber and quartz ﬁbers as the sensitive material. It consists of two halves, each located 11.2 m from the interaction region, and together they provide coverage in the range 3.0 < \|ηlab\| < 5.2. The beam pickup for timing (BPTX) devices were used to trigger the detector readout. They are located around the beam pipe at a distance of 175 m on either side of the interaction point (IP) and are designed to provide precise information on the LHC bunch structure and the timing of the incoming beams. Muons are detected in gas-ionization chambers embedded in the steel ﬂux-return yoke outside the solenoid. A more detailed description of the CMS detector, together with a deﬁnition of the coordinate system used and the relevant kinematic variables, can be found in ref. [28]. 3 Event selection The data used in this analysis were taken with the beam conﬁguration in which the proton beam traveled in the negative pseudorapidity direction, and selected to contain collision – 2 – events recorded during low-intensity beam conﬁgurations, with 0.3–0.6% proton-lead inter- action probability per bunch crossing. The collision events are selected online by requiring a coincidence of signals from both BPTX devices, indicating the presence of both proton and lead ion bunches crossing the IP, and at least one energy deposit above the readout threshold of 3 GeV on either side of the HF. The oﬄine selection of NSD events is accom- plished by requiring that at least one energy deposit greater than 3 GeV is found on each of the two sides of the HF and at least one reconstructed interaction vertex is found. A study of noncolliding bunches shows that these requirements are also suﬃcient to reject all backgrounds not originating from pPb collisions. The probability to select events in the presence of a single (noncolliding) beam is found to be around 2 × 10−5 per bunch cross- ing, to be compared to the average number of collisions per bunch crossing of 4.5 × 10−3. Consequently, the contribution of background events from beam, beam halo, and cosmic ray sources to the observed yields is negligible. The total number of pPb collision events passing the selection criteria is approximately 420 thousand and 3 million at √sNN = 5.02 and 8.16 TeV, respectively. JHEP01(2018)045 The corrections from the detector-level oﬄine event selection to the hadron-level event deﬁnition are derived from MC simulations with the Epos generator. The MC simulations are produced with the same vertex distribution along the interaction region as observed in data. The detector response is simulated with Geant4 [29] and processed through the same event reconstruction chain as the collision data. 4 Data analysis In the presence of a magnetic ﬁeld, charged particles follow curved trajectories, perturbed mostly by multiple Coulomb scattering. The reconstructed pixel clusters (or “hits”) alone are suﬃcient to reconstruct vertices and tracks with high precision and purity. The analysis technique is based on tracklets, pairs of hits from two diﬀerent layers, and relies on the fact that for a primary charged hadron, the diﬀerences in pseudorapidity (∆η) and azimuthal angle (∆φ) between the two hits are small. This method is sensitive to charged hadrons with transverse momenta pT as low as 40 MeV/c. The primary vertex reconstruction is based on pixel hits in the ﬁrst two layers of the detector, as in ref. [26]. In the ﬁrst step, a hit from the ﬁrst layer is selected and a matching hit from the second layer is sought. If the \|∆φ\| of the hits is smaller than 0.05 (optimized to maximize the vertex reconstruction eﬃciency), the z positions of the hits (with the z axis deﬁned to be parallel to the beam axis) are extrapolated linearly and projected onto the beam axis. This procedure is repeated for every hit in the ﬁrst layer, and the projected z positions are saved as vertex candidates. The primary vertex is determined in a second step. If the magnitude of the diﬀerence between the z positions of any two vertex candidates is smaller than 0.12 cm, they are combined into a vertex cluster. The vertex cluster with the highest number of associated vertex candidates is selected as the primary vertex, and the ﬁnal vertex z position, zv, is given by the average z position of the associated vertex candidates. The typical resolution of zv is 0.02–0.04 cm, depending on the number of pixel hits. 4 Data analysis The vertex reconstruction eﬃciency is found to be high even – 3 – 0.1 − 0.05 − 0 0.05 0.1 η ∆ 3 − 10 2 − 10 1 − 10 1 Fraction of tracklets Data LHC POS E 1.3 IJING H = 8.16 TeV NN s pPb CMS a) 0.1 − 0.05 − 0 0.05 0.1 φ ∆ Fraction of tracklets 0.01 0.02 0.03 Data LHC POS E 1.3 IJING H = 8.16 TeV NN s pPb CMS b) 2 − 1 − 0 1 2 φ ∆ 2 − 10 1 − 10 Fraction of tracklets Data LHC POS E 1.3 IJING H = 8.16 TeV NN s pPb CMS c) Figure 1. The ∆η (a) and ∆φ (b, c) distributions of hit pairs for tracklets in pPb collisions at 8.16 TeV (squares) and from MC simulations with the Epos and Hijing 1.3 generators (solid lines). The statistical uncertainties are smaller than the marker sizes for all distributions shown. 0.1 − 0.05 − 0 0.05 0.1 φ ∆ Fraction of tracklets 0.01 0.02 0.03 Data LHC POS E 1.3 IJING H = 8.16 TeV NN s pPb CMS b) 2 − 1 − 0 1 2 φ ∆ 2 − 10 1 − 10 Fraction of tracklets Data LHC POS E 1.3 IJING H = 8.16 TeV NN s pPb CMS c) 0.1 − 0.05 − 0 0.05 0.1 η ∆ 3 − 10 2 − 10 1 − 10 1 Fraction of tracklets Data LHC POS E 1.3 IJING H = 8.16 TeV NN s pPb CMS a) JHEP01(2018)045 Figure 1. The ∆η (a) and ∆φ (b, c) distributions of hit pairs for tracklets in pPb collisions at 8.16 TeV (squares) and from MC simulations with the Epos and Hijing 1.3 generators (solid lines). The statistical uncertainties are smaller than the marker sizes for all distributions shown. for low-multiplicity events with few pixel hits, with around 90 (100)% eﬃciency for events with 4 (10) hits in the ﬁrst layer. The tracklet reconstruction follows a separate algorithm from the vertex reconstruc- tion. There is no requirement on the ∆φ of the hits. Instead, a hit on a given layer is paired with the hit on another layer which is closest in η (where η is measured with respect to the primary vertex) and these two hits form a tracklet. No hit can be used more than once. 4 Data analysis No selection is applied on the hit quality or charge, such that the analysis is rather insensitive to the accuracy of the simulation of pixel cluster charge. Three diﬀerent types of tracklets can be reconstructed, corresponding to diﬀerent combinations of the three pixel detector layers: 1+2, 1+3, and 2+3. The reconstruction eﬃciency, acceptance, fraction of back- ground hits, and sensitivity to particle pT is diﬀerent for each type of tracklet. This serves as a consistency check for the analysis, and reduces systematic biases in the measurement. Figures 1(a) and (b) show the ∆η and ∆φ distributions of reconstructed hit pairs for tracklets in data and simulation. To suppress the combinatorial background, while still including most particles in the analysis, only tracklets with \|∆η\| < 0.1 are considered “signal”. In this kinematic region, there is good agreement between data and simulations with the Epos generator, indicating that the pT distributions of both hard and soft particles in data are described well by this MC generator. The Hijing generator, used in this analysis for systematic studies, gives a poorer description of the distributions, especially for ∆φ . Tracklets corresponding to charged hadrons that originate from the primary vertex have small but nonzero ∆φ due to the magnetic ﬁeld in the detector, while background tracklets from uncorrelated pixel hits form a roughly ﬂat ∆φ spectrum over the entire ∆φ range, as shown in ﬁgure 1(c), where the abscissa is extended to \|∆φ\| < 2. Hence, a sideband region deﬁned by 1 < \|∆φ\| < 2 is used to estimate the background fraction, which is then subtracted from the signal region (\|∆φ\| < 1) to obtain the uncorrected dNch/dηlab [26]. The background estimation and subtraction is performed as a function of ηlab, zv, and tracklet multiplicity. Typical values of the estimated background fraction in the signal region in data increase with \|ηlab\| from 10–25%. The ηlab range is restricted to \|ηlab\| < 2.4 to avoid a large acceptance correction. – 4 – The ﬁnal results need to be corrected for contributions from decaying particles with cτ > 1 cm, particles created in secondary interactions, and prompt leptons. The contribu- tion of these particles to dNch/dηlab is removed using a correction factor found using MC simulations. In addition, corrections are needed to account for the selection, eﬃciency, and acceptance of reconstructed tracklets, as well as trigger and vertexing eﬃciencies. 4 Data analysis The ac- ceptance factor includes the extrapolation down to pT = 0 GeV/c. Correction factors (with a typical total of <15%) are derived using the Epos event generator as a reference and are calculated as a function of ηlab, zv, and tracklet multiplicity, as was done in ref. [26]. To account for the diﬀerences between data and MC in the pixel detector geometry and its alignment conditions, an additional correction is applied as a function of ηlab and zv. This correction is obtained by taking the ratio between data and simulation of the geometrical distribution of tracklets in (ηlab, zv) intervals. The size of this correction ranges from 0 to 5%, where the largest correction factors are associated with the presence of inactive tracker modules. JHEP01(2018)045 4.1 Systematic uncertainties The systematic uncertainties in the ﬁnal results arise from several sources: detector mis- alignment, pixel hit reconstruction ineﬃciency, pixel cluster splitting, background model- ing, selection of signal and sideband regions, parametrization of the correction factors, and the NSD event selection. For each source of uncertainty, that part of the analysis procedure is varied independently and the change is propagated to the ﬁnal results. The individual contributions are then summed in quadrature to give the total systematic uncertainty. To estimate the uncertainty from detector misalignment, each pixel hit is oﬀset by a small distance corresponding to the uncertainty in the alignment of the pixel detectors. The eﬀects of pixel hit reconstruction ineﬃciency are studied by randomly excluding 0.5% of the pixel hits from the analysis. The 0.5% ineﬃciency value is determined by studying tracklets reconstructed from pixel hits in layers 1 and 3, and taking the double ratio in data and simulation of the fraction of tracklets that have no corresponding hit in layer 2. Pixel cluster splitting refers to the situation where the charge deposit in the pixel detector from a single charged particle is reconstructed as two separate pixel clusters. Its eﬀect on the measurement is estimated by randomly splitting pixel clusters with a probability of 1.2%, as determined by previous studies [22]. The contributions from the above three sources are all below 1%. The remaining uncertainties are associated with the MC correction factors. Additional pixel hits, randomly sampled from the hit distributions in data, are added such that the ∆φ sidebands match between data and MC. The percentage of additional pixel hits needed is less than 5%. The variations observed compared to the nominal results are around 1.5– 2.5%. The signal and sideband regions are also varied to \|∆φ\| < 1.5 and 1.5 < \|∆φ\| < 3.0, respectively. A variation of 0.6–1.5% is found as compared to the nominal setting, which is propagated as a systematic uncertainty. 4.1 Systematic uncertainties Diﬀerent multiplicity variables are used to parametrize the correction factors, in addition to the background-subtracted tracklets variable used for the nominal results: number of tracklets (before background subtraction), number of pixel hits in the ﬁrst pixel layer used (layer 1 for tracklet type 1+2 and 1+3, and – 5 – Source Uncertainty [%] 5.02 TeV 8.16 TeV Data and simulation Detector misalignment 0.2 – 1.0 0.2 – 1.0 Pixel hit reconstruction ineﬃciency 1.0 1.0 Pixel cluster splitting 0.3 – 0.8 0.3 – 0.6 MC corrections Background modeling 1.3 – 3.2 1.5 – 2.5 Signal and sideband region selection 0.5 – 1.5 0.6 – 1.5 Choice of parametrization variable 1.6 – 2.5 1.5 – 3.5 NSD selection 1.2 1.2 Total uncertainty 3.0 – 4.3 3.7 – 4.6 JHEP01(2018)045 Table 1. Summary of the systematic uncertainties from various sources, for pPb collisions at 5.02 and 8.16 TeV. The range of values indicates the minimum and maximum uncertainties across the ηlab range. layer 2 for tracklet type 2+3). The maximum deviation in each ηlab interval, 1.5–2.5%, is quoted as an uncertainty. An uncertainty is assigned for the selection of NSD events. The fraction of the single-diﬀractive events removed by the event selection, as determined from the Epos generator, is 16% when the tracklet multiplicity in the event is less than 10, and falls quickly to 0% with increasing tracklet multiplicity. This fraction is varied from 0% to twice the nominal value, and the maximum deviation from the ﬁnal results, 1.2%, is quoted as the uncertainty. A summary of the systematic uncertainties for the measurements at 5.02 and 8.16 TeV is shown in table 1. layer 2 for tracklet type 2+3). The maximum deviation in each ηlab interval, 1.5–2.5%, is quoted as an uncertainty. An uncertainty is assigned for the selection of NSD events. The fraction of the single-diﬀractive events removed by the event selection, as determined from the Epos generator, is 16% when the tracklet multiplicity in the event is less than 10, and falls quickly to 0% with increasing tracklet multiplicity. This fraction is varied from 0% to twice the nominal value, and the maximum deviation from the ﬁnal results, 1.2%, is quoted as the uncertainty. A summary of the systematic uncertainties for the measurements at 5.02 and 8.16 TeV is shown in table 1. 5 Results Pseudorapidity density distributions of charged hadrons in the region \|ηlab\| < 2.4 for NSD pPb collisions are shown in ﬁgure 2. The distributions shown are the average of the measured distributions from the three types of tracklets (1+2, 1+3, and 2+3), which are consistent with each other within 3%. A clear diﬀerence in the particle densities between the lead ion (ηlab < 0) and the proton (ηlab > 0) beam directions is observed. The measured dNch/dηlab distribution at 5.02 TeV agrees with the measurement by the ALICE Collaboration [30]. The multiplicities at 8.16 TeV are signiﬁcantly higher than those at 5.02 TeV. Figure 3 shows a comparison between the measurement at 8.16 TeV and theoretical calculations from the Hijing (versions 1.3 and 2.1), Epos LHC (v3400), and Dpmjet-III MC generators, and the KLN model. The Hijing and Epos generators were tuned to data from RHIC and the LHC, respectively. Calculations from Hijing 2.1, a two-component model that combines perturbative QCD descriptions of hard parton scatterings with a string excitation model for soft interactions, agree with the experimental data in the re- gion −0.5 < ηlab < 1.5 when the nuclear modiﬁcation of the initial parton distributions (shadowing) is included in the calculation. The Hijing 1.3 calculation overpredicts the par- ticle density because it has an older implementation of the gluon shadowing eﬀects. The – 6 – Figure 2. Distributions of the pseudorapidity density of charged hadrons in the region \|ηlab\| < 2.4 in NSD pPb collisions at √sNN = 5.02 (open squares) and 8.16 TeV (full squares). The measurement at 5.02 TeV by the ALICE Collaboration [30] is shown as ﬁlled circles. The shaded boxes indicate the systematic uncertainties which, in the case of the CMS data, are correlated between the two beam energies. The proton beam goes in the positive ηlab direction. JHEP01(2018)045 Figure 2. Distributions of the pseudorapidity density of charged hadrons in the region \|ηlab\| < 2.4 in NSD pPb collisions at √sNN = 5.02 (open squares) and 8.16 TeV (full squares). The measurement at 5.02 TeV by the ALICE Collaboration [30] is shown as ﬁlled circles. The shaded boxes indicate the systematic uncertainties which, in the case of the CMS data, are correlated between the two beam energies. The proton beam goes in the positive ηlab direction. 5 Results importance of shadowing can be assessed using the comparison of Hijing 2.1 simulations generated with and without this physics process included. The results are signiﬁcantly higher than the data when shadowing is disabled. The KLN parton saturation model combines Glauber modeling of the collision geometry with a simple model for the unin- tegrated parton distributions that accounts for the existence of a saturation momentum scale [31, 32]. It describes the particle density accurately for \|ηlab\| < 1 but overall shows a steeper increase of density versus ηlab than observed in the data, similar to what was observed in the comparisons to the PHOBOS deuteron-gold (dAu) data at 200 GeV [33] and ALICE data at 5.02 TeV [30]. The Dpmjet-III generator, commonly used in the de- scription of cosmic ray, nucleon-nucleon, and nucleon-nucleus interactions, is based on the dual parton model [34], which generates soft hadronic interactions by considering the ex- pansion of nonperturbative QCD in the limit where the number of color and ﬂavor states are large [35]. This generator is found to predict both a steeper increase versus ηlab and a higher particle density over the measured ηlab interval. The Epos generator, which is based on the Gribov-Regge theory and includes the eﬀect of collective hadronization in hadron-hadron scattering, was found to describe pp data up to 13 TeV [25], but underpre- dicts the observed dNch/dηlab by a roughly constant factor over the entire measured range for pPb at 8.16 TeV. One of the main goals of the heavy ion studies is to understand hadron production in the extremely dense medium formed in AA collisions. One way to approach this goal is to consider a direct comparison between the charged-hadron multiplicity density in minimum – 7 – Figure 3. Distributions of the pseudorapidity density of charged hadrons in the region \|ηlab\| < 2.4 for NSD pPb collisions at 8.16 TeV (squares) compared to predictions from the MC event generators Epos LHC [17, 27] (v3400), Hijing [14] (versions 1.3 [15] and 2.1 [12]), and Dpmjet-III [16], as well as from the KLN model [11]. The shaded boxes around the data points indicate their systematic uncertainties. The proton beam goes in the positive ηlab direction. JHEP01(2018)045 Figure 3. 5 Results Distributions of the pseudorapidity density of charged hadrons in the region \|ηlab\| < 2.4 for NSD pPb collisions at 8.16 TeV (squares) compared to predictions from the MC event generators Epos LHC [17, 27] (v3400), Hijing [14] (versions 1.3 [15] and 2.1 [12]), and Dpmjet-III [16], as well as from the KLN model [11]. The shaded boxes around the data points indicate their systematic uncertainties. The proton beam goes in the positive ηlab direction. bias pp and pA collisions, reference systems for particle production in the absence of a QGP, and central AA collisions (the most extreme type of collisions with the highest particle multiplicities). The comparison is made by dividing dNch/dηcm by the number of participating nucleons, Npart, determined by a Glauber model calculation [4, 36]. This normalization is the one assumed in two-component models (e.g. Hijing) for the bulk of the particle production. In order to compare particle production in pPb collisions to that in symmetric collision systems such as pp or AA, the rapidity shift due to the asymmetric beam energies must be taken into account. The average charged-hadron multiplicity density at midrapidity in the center-of-mass frame, ⟨dNch/dηcm⟩\|\|ηcm\|<0.5, in pPb collisions is calculated by inte- grating the data in the interval −0.035 < ηlab < 0.965, corresponding to \|ηcm\| < 0.5 for massless particles. A correction is applied to account for the massless assumption entering the calculation of the pseudorapidity shift: 0.1 and 0.2% for the 5.02 TeV and 8.16 TeV analyses, respectively, as obtained from the Epos generator. The 1% variation in the results, obtained when this correction is evaluated from Hijing, is quoted as an addi- tional uncertainty for the ⟨dNch/dηcm⟩\|\|ηcm\|<0.5 results. In the range \|ηcm\| < 0.5, values of 17.31 ± 0.01 (stat) ± 0.59 (syst) and 20.10 ± 0.01 (stat) ± 0.85 (syst) are obtained for pPb collisions at √sNN = 5.02 and 8.16 TeV, respectively. Figure 4 shows the dependence of normalized dNch/dηcm on the collision energy for various collision systems and event selections. 5 Results The NSD pA results are found to be lower than those from central AA collisions [26, 37–50] (s0.158 NN dependence) and NSD pp collisions – 8 – 10 2 10 3 10 4 10 (GeV) NN s 0 1 2 3 4 5 6 7 〉 part N 〈 / 0 ≈ cm η 〉 cm η d / h c N d〈 CMS ) NSD p pp (p CMS ALICE CDF UA5 UA1 STAR 0.110 NN s ∝ ) Inel. p pp (p CMS ALICE UA5 PHOBOS ISR 0.103 NN s ∝ Central AA CMS ALICE ATLAS BRAHMS PHENIX STAR PHOBOS NA50 0.158 NN s ∝ pA NSD pPb CMS pPb ALICE dAu PHOBOS dAu PHENIX (Central) pA Inel. pPb E178 pAu NA35 Figure 4. Comparison of the measured dNch/dηcm at midrapidity, scaled by the number of par- ticipating nucleons (Npart) in pPb [30, 51], pAu [52], dAu [33, 48, 53] and central heavy ion colli- sions [26, 37–50], as well as NSD [22, 23, 50, 54–57] and inelastic [25, 37, 56, 58, 59] pp collisions. The AA data points at √sNN = 2.76 TeV have been shifted horizontally for visibility. The dashed curves, included to guide the eye, correspond to a ﬁt to the data points using the same functional form as in refs. [46, 59]. 10 2 10 3 10 4 10 (GeV) NN s 0 1 2 3 4 5 6 7 〉 part N 〈 / 0 ≈ cm η 〉 cm η d / h c N d〈 CMS ) NSD p pp (p CMS ALICE CDF UA5 UA1 STAR 0.110 NN s ∝ ) Inel. p pp (p CMS ALICE UA5 PHOBOS ISR 0.103 NN s ∝ Central AA CMS ALICE ATLAS BRAHMS PHENIX STAR PHOBOS NA50 0.158 NN s ∝ pA NSD pPb CMS pPb ALICE dAu PHOBOS dAu PHENIX (Central) pA Inel. pPb E178 pAu NA35 JHEP01(2018)045 Figure 4. Comparison of the measured dNch/dηcm at midrapidity, scaled by the number of par- ticipating nucleons (Npart) in pPb [30, 51], pAu [52], dAu [33, 48, 53] and central heavy ion colli- sions [26, 37–50], as well as NSD [22, 23, 50, 54–57] and inelastic [25, 37, 56, 58, 59] pp collisions. The AA data points at √sNN = 2.76 TeV have been shifted horizontally for visibility. 5 Results The dashed curves, included to guide the eye, correspond to a ﬁt to the data points using the same functional form as in refs. [46, 59]. (s0.110 NN dependence) at similar center-of-mass energies, but coincide with the trend observed in inelastic pp collisions (s0.103 NN dependence). While the diﬀerence between the NSD pp and pA results could be attributed to non-QGP nuclear eﬀects, the similarity between the NSD pA and total inelastic pp is yet to be understood. Acknowledgments We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staﬀs at CERN and at other CMS institutes for their contributions to the success of the CMS eﬀort. In ad- dition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid for delivering so eﬀectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: BMWFW and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COL- CIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR and RAEP (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI and FEDER (Spain); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (U.S.A.). JHEP01(2018)045 ( ) ( ) ( ) Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract No. 675440 (European Union); the Leventis Foundation; the A. P. 6 Summary The pseudorapidity distributions of primary charged hadrons have been measured by the CMS experiment at the LHC in proton-lead collisions at √sNN = 5.02 and 8.16 TeV. Based on pairs of pixel clusters from two diﬀerent layers of the barrel region of the CMS pixel de- tector, the distributions have been obtained for NSD pPb events at both collision energies. The measured dNch/dηlab distribution at 5.02 TeV is consistent with published results by the ALICE Collaboration. At 8.16 TeV, the measured dNch/dηlab distribution is higher than the predictions of Epos LHC, but signiﬁcantly lower than the predictions from the Hijing 1.3 and Dpmjet-III event generators. At ηlab ≈0, the measured distributions are in good agreement with calculations from the KLN gluon saturation model and predic- tions from the Hijing 2.1 event generator with the eﬀects of gluon shadowing included. The charged-hadron multiplicity densities in the nucleon-nucleon center-of-mass frame, ⟨dNch/dηcm⟩\|\|ηcm\|<0.5, are 17.31±0.01 (stat)±0.59 (syst) and 20.10±0.01 (stat)±0.85 (syst) at √sNN = 5.02 and 8.16 TeV, respectively. When comparing the average charged-particle – 9 – density per participant nucleon for pp, pA, and AA collisions as a function of collision energy, the pA results are found to be below those in central AA collisions and NSD pp collisions, but coincide with the trend seen in inelastic pp collisions. These results represent the ﬁrst measurement of hadron production at this new center-of-mass energy frontier in nuclear collisions, and provide constraints for the understanding of nonperturbative QCD eﬀects in high-energy nuclear collisions. Acknowledgments Sloan Foundation; the Alexander von Humboldt Founda- tion; the Belgian Federal Science Policy Oﬃce; the Fonds pour la Formation `a la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Council of Science and Industrial Research, India; the HOMING PLUS program of the Foundation for Polish Science, coﬁnanced from European Union, Regional Development Fund, the Mobility Plus program of the Min- istry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities Re- search Program by Qatar National Research Fund; the Programa Severo Ochoa del Prin- cipado de Asturias; the Thalis and Aristeia programs coﬁnanced by EU-ESF and the – 10 – Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); the Welch Foundation, contract C-1845; and the Weston Havens Foun- dation (U.S.A.). Open Access. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits any use, distribution and reproduction in any medium, provided the original author(s) and source are credited. References JHEP01(2018)045 [1] W. Busza, Review of experimental data on hadron-nucleus collisions at high-energies, Acta Phys. Polon. B 8 (1977) 333 [INSPIRE]. [2] C.A. Salgado et al., Proton-nucleus collisions at the LHC: scientiﬁc opportunities and requirements, J. Phys. G 39 (2012) 015010 [arXiv:1105.3919] [INSPIRE]. [3] CMS collaboration, Nuclear eﬀects on the transverse momentum spectra of charged particles in pPb collisions at √sNN = 5.02 TeV, Eur. Phys. J. C 75 (2015) 237 [arXiv:1502.05387] [INSPIRE]. [4] CMS collaboration, Charged-particle nuclear modiﬁcation factors in PbPb and pPb collisions at √sNN = 5.02 TeV, JHEP 04 (2017) 039 [arXiv:1611.01664] [INSPIRE]. [5] CMS collaboration, Study of B meson production in p+Pb collisions at √sNN = 5.02 TeV using exclusive hadronic decays, Phys. Rev. Lett. 116 (2016) 032301 [arXiv:1508.06678] [INSPIRE]. [6] ALICE collaboration, D-meson production in p-Pb collisions at √sNN = 5.02 TeV and in pp collisions at √s = 7 TeV, Phys. Rev. C 94 (2016) 054908 [arXiv:1605.07569] [INSPIRE]. [7] CMS collaboration, Measurement of prompt and nonprompt J/ψ production in pp and pPb collisions at √sNN = 5.02 TeV, Eur. Phys. J. C 77 (2017) 269 [arXiv:1702.01462] [INSPIRE]. [8] CMS collaboration, Transverse momentum spectra of inclusive b jets in pPb collisions at √sNN = 5.02 TeV, Phys. Lett. B 754 (2016) 59 [arXiv:1510.03373] [INSPIRE]. [9] CMS collaboration, Measurement of inclusive jet production and nuclear modiﬁcations in pPb collisions at √sNN = 5.02 TeV, Eur. Phys. J. C 76 (2016) 372 [arXiv:1601.02001] [INSPIRE]. [10] CMS collaboration, Studies of dijet transverse momentum balance and pseudorapidity distributions in pPb collisions at √sNN = 5.02 TeV, Eur. Phys. J. C 74 (2014) 2951 [arXiv:1401.4433] [INSPIRE]. [11] A. Dumitru, D.E. Kharzeev, E.M. Levin and Y. Nara, Gluon saturation in pA collisions at the LHC: KLN model predictions for hadron multiplicities, Phys. Rev. C 85 (2012) 044920 [arXiv:1111.3031] [INSPIRE]. [12] R. Xu, W.-T. Deng and X.-N. Wang, Nuclear modiﬁcation of high-pT hadron spectra in p+A collisions at LHC, Phys. Rev. C 86 (2012) 051901 [arXiv:1204.1998] [INSPIRE]. [13] J.L. Albacete, A. Dumitru, H. Fujii and Y. Nara, CGC predictions for p + Pb collisions at the LHC, Nucl. Phys. A 897 (2013) 1 [arXiv:1209.2001] [INSPIRE]. – 11 – [14] X.-N. Wang and M. Gyulassy, HIJING: a Monte Carlo model for multiple jet production in pp, pA and AA collisions, Phys. Rev. D 44 (1991) 3501 [INSPIRE]. [15] M. Gyulassy and X.-N. References Wang, HIJING 1.0: A Monte Carlo program for parton and particle production in high-energy hadronic and nuclear collisions, Comput. Phys. Commun. 83 (1994) 307 [nucl-th/9502021] [INSPIRE]. [16] S. Roesler, R. Engel and J. Ranft, The Monte Carlo event generator DPMJET-III, in the proceedings of the Advanced Monte Carlo for radiation physics, particle transport simulation and applications conference (MC2000), October 23–26, Lisbon, Portugal (2000). [17] T. Pierog, I. Karpenko, J.M. Katzy, E. Yatsenko and K. Werner, EPOS LHC: test of collective hadronization with data measured at the CERN Large Hadron Collider, Phys. Rev. C 92 (2015) 034906 [arXiv:1306.0121] [INSPIRE]. JHEP01(2018)045 [18] C. Halliwell et al., Energy dependence of the pseudorapidity distributions in proton-nucleus collisions between 50 GeV/c and 200 GeV/c., Phys. Rev. Lett. 39 (1977) 1499 [INSPIRE]. [19] W. Kittel and E.A. De Wolf, Soft multihadron dynamics, World Scientiﬁc, Singapore (2005 [20] CMS collaboration, Charged particle multiplicities in pp interactions at √s = 0.9, 2.36 and 7 TeV, JHEP 01 (2011) 079 [arXiv:1011.5531] [INSPIRE]. [21] D. d’Enterria, R. Engel, T. Pierog, S. Ostapchenko and K. Werner, Constraints from the ﬁrst LHC data on hadronic event generators for ultra-high energy cosmic-ray physics, Astropart. Phys. 35 (2011) 98 [arXiv:1101.5596] [INSPIRE]. [22] CMS collaboration, Transverse momentum and pseudorapidity distributions of charged hadrons in pp collisions at √s = 0.9 and 2.36 TeV, JHEP 02 (2010) 041 [arXiv:1002.0621] [INSPIRE]. [23] CMS collaboration, Transverse-momentum and pseudorapidity distributions of charged hadrons in pp collisions at √s = 7 TeV, Phys. Rev. Lett. 105 (2010) 022002 [arXiv:1005.3299] [INSPIRE]. [24] CMS and TOTEM collaborations, Measurement of pseudorapidity distributions of charged particles in proton-proton collisions at √s = 8 TeV by the CMS and TOTEM experiments, Eur. Phys. J. C 74 (2014) 3053 [arXiv:1405.0722] [INSPIRE]. [25] CMS collaboration, Pseudorapidity distribution of charged hadrons in proton-proton collisions at √s = 13 TeV, Phys. Lett. B 751 (2015) 143 [arXiv:1507.05915] [INSPIRE]. [26] CMS collaboration, Dependence on pseudorapidity and centrality of charged hadron production in PbPb collisions at a nucleon-nucleon centre-of-mass energy of 2.76 TeV, JHEP 08 (2011) 141 [arXiv:1107.4800] [INSPIRE]. [27] K. Werner, F.-M. Liu and T. Pierog, Parton ladder splitting and the rapidity dependence of transverse momentum spectra in deuteron-gold collisions at RHIC, Phys. Rev. C 74 (2006) 044902 [hep-ph/0506232] [INSPIRE]. [28] CMS collaboration, The CMS experiment at the CERN LHC, 2008 JINST 3 S08004 [INSPIRE]. [29] GEANT4 collaboration, S. Agostinelli et al., GEANT4 — a simulation toolkit, Nucl. Instrum. Meth. References A 506 (2003) 250 [INSPIRE]. [30] ALICE collaboration, Pseudorapidity density of charged particles in p + Pb collisions at √sNN = 5.02 TeV, Phys. Rev. Lett. 110 (2013) 032301 [arXiv:1210.3615] [INSPIRE]. – 12 – [31] D. Kharzeev and E. Levin, Manifestations of high density QCD in the ﬁrst RHIC data, Phys. Lett. B 523 (2001) 79 [nucl-th/0108006] [INSPIRE]. [32] D. Kharzeev, E. Levin and M. Nardi, The onset of classical QCD dynamics in relativistic heavy ion collisions, Phys. Rev. C 71 (2005) 054903 [hep-ph/0111315] [INSPIRE]. [33] PHOBOS collaboration, B.B. Back et al., Pseudorapidity distribution of charged particles in d + Au collisions at √sNN = 200 GeV, Phys. Rev. Lett. 93 (2004) 082301 [nucl-ex/0311009] [INSPIRE]. [34] A. Capella, U. Sukhatme, C.-I. Tan and J. Tran Thanh Van, Dual parton model, Phys. Rept. 236 (1994) 225 [INSPIRE]. [35] G. Veneziano, Regge intercepts and unitarity in planar dual models, Nucl. Phys. B 74 (1974) 365 [INSPIRE]. JHEP01(2018)045 [36] M.L. Miller, K. Reygers, S.J. Sanders and P. Steinberg, Glauber modeling in high energy nuclear collisions, Ann. Rev. Nucl. Part. Sci. 57 (2007) 205 [nucl-ex/0701025] [INSPIRE]. [37] PHOBOS collaboration, B. Alver et al., Phobos results on charged particle multiplicity and pseudorapidity distributions in Au+Au, Cu+Cu, d+Au and p+p collisions at ultra-relativistic energies, Phys. Rev. C 83 (2011) 024913 [arXiv:1011.1940] [INSPIRE]. [38] NA50 collaboration, M.C. Abreu et al., Scaling of charged particle multiplicity in Pb Pb collisions at SPS energies, Phys. Lett. B 530 (2002) 43 [INSPIRE]. [39] STAR collaboration, C. Adler et al., Multiplicity distribution and spectra of negatively charged hadrons in Au+Au collisions at √sNN = 130 GeV, Phys. Rev. Lett. 87 (2001) 112303 [nucl-ex/0106004] [INSPIRE]. [40] BRAHMS collaboration, I.G. Bearden et al., Charged particle densities from Au+Au collisions at √sNN = 130 GeV, Phys. Lett. B 523 (2001) 227 [nucl-ex/0108016] [INSPIRE]. [41] BRAHMS collaboration, I.G. Bearden et al., Pseudorapidity distributions of charged particles from Au+Au collisions at the maximum RHIC energy, Phys. Rev. Lett. 88 (2002) 202301 [nucl-ex/0112001] [INSPIRE]. [42] PHENIX collaboration, K. Adcox et al., Centrality dependence of charged particle multiplicity in Au-Au collisions at √sNN = 130 GeV, Phys. Rev. Lett. 86 (2001) 3500 [nucl-ex/0012008] [INSPIRE]. [43] PHOBOS collaboration, B.B. Back et al., Charged particle multiplicity near mid-rapidity in central Au+Au collisions at √s = 56 A/GeV and 130 A/GeV, Phys. Rev. Lett. 85 (2000) 3100 [hep-ex/0007036] [INSPIRE]. [44] PHOBOS collaboration, B.B. References Back et al., Charged particle pseudorapidity density distributions from Au+Au collisions at √sNN = 130 GeV, Phys. Rev. Lett. 87 (2001) 102303 [nucl-ex/0106006] [INSPIRE]. [45] B.B. Back et al., The Signiﬁcance of the fragmentation region in ultrarelativistic heavy ion collisions, Phys. Rev. Lett. 91 (2003) 052303 [nucl-ex/0210015] [INSPIRE]. [46] ALICE collaboration, Charged-particle multiplicity density at mid-rapidity in central PbPb collisions at √sNN = 2.76 TeV, Phys. Rev. Lett. 105 (2010) 252301 [arXiv:1011.3916] [INSPIRE]. [47] ATLAS collaboration, Measurement of the centrality dependence of the charged particle pseudorapidity distribution in lead-lead collisions at √sNN = 2.76 TeV with the ATLAS detector, Phys. Lett. B 710 (2012) 363 [arXiv:1108.6027] [INSPIRE]. – 13 – [48] PHENIX collaboration, A. Adare et al., Transverse energy production and charged-particle multiplicity at midrapidity in various systems from √sNN = 7.7 to 200 GeV, Phys. Rev. C 93 (2016) 024901 [arXiv:1509.06727] [INSPIRE]. [49] STAR collaboration, B.I. Abelev et al., Identiﬁed particle production, azimuthal anisotropy and interferometry measurements in Au+Au collisions at √sNN = 9.2 GeV, Phys. Rev. C 81 (2010) 024911 [arXiv:0909.4131] [INSPIRE]. [50] STAR collaboration, B.I. Abelev et al., Systematic measurements of identiﬁed particle spectra in pp, d+Au and Au+Au collisions from STAR, Phys. Rev. C 79 (2009) 034909 [arXiv:0808.2041] [INSPIRE]. [51] J.E. Elias et al., An experimental study of multiparticle production in hadron-nucleus interactions at high-energy, Phys. Rev. D 22 (1980) 13 [INSPIRE]. JHEP01(2018)045 JHEP01(2018)045 [52] NA35 collaboration, T. Alber et al., Charged particle production in proton, deuteron, oxygen and sulphur nucleus collisions at 200 GeV per nucleon, Eur. Phys. J. C 2 (1998) 643 [hep-ex/9711001] [INSPIRE]. [53] PHENIX collaboration, C. Aidala et al., Measurements of azimuthal anisotropy and charged-particle multiplicity in d+Au collisions at √sNN = 200, 62.4, 39 and 19.6 GeV, Phys. Rev. C 96 (2017) 064905 [arXiv:1708.06983] [INSPIRE]. [54] UA1 collaboration, C. Albajar et al., A study of the general characteristics of p¯p collisions at √s = 0.2 TeV to 0.9 TeV, Nucl. Phys. B 335 (1990) 261 [INSPIRE]. [55] UA5 collaboration, K. Alpgard et al., Particle multiplicities in ¯pp interactions at √s = 540 GeV, Phys. Lett. 121B (1983) 209 [INSPIRE]. [56] UA5 collaboration, G.J. Alner et al., Scaling of pseudorapidity distributions at c.m. energies up to 0.9 TeV, Z. Phys. C 33 (1986) 1 [INSPIRE]. [57] CDF collaboration, F. Abe et al., Pseudorapidity distributions of charged particles produced in ¯pp interactions at √s = 630 GeV and 1800 GeV, Phys. Rev. References D 41 (1990) 2330 [INSPIRE]. [58] Aachen-CERN-Heidelberg-Munich collaboration, W. Thome et al., Charged particle multiplicity distributions in pp collisions at ISR energies, Nucl. Phys. B 129 (1977) 365 [INSPIRE]. [59] ALICE collaboration, Charged-particle multiplicity measurement in proton-proton collisions at √s = 0.9 and 2.36 TeV with ALICE at LHC, Eur. Phys. J. C 68 (2010) 89 [arXiv:1004.3034] [INSPIRE]. – 14 – The CMS collaboration Vrije Universiteit Brussel, Brussel, Belgium S. Abu Zeid, F. Blekman, J. D’Hondt, I. De Bruyn, J. De Clercq, K. Deroover, G. Flouris, D. Lontkovskyi, S. Lowette, S. Moortgat, L. Moreels, Q. Python, K. Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders, I. Van Parijs D. Beghin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B. Dorney, G. Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, G. Karapostoli, T. Lenzi, J. Luetic, T. Maer- schalk, A. Marinov, T. Seva, E. Starling, C. Vander Velde, P. Vanlaer, D. Vannerom, R. Yonamine, F. Zenoni, F. Zhang2 Ghent University, Ghent, Belgium Ghent University, Ghent, Belgium A. Cimmino, T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov3, D. Poyraz, C. Roskas, S. Salva, M. Tytgat, W. Verbeke, N. Zaganidis Universit´e Catholique de Louvain, Louvain-la-Neuve, Belgium H. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, C. Caputo, A. Caudron, P. David, S. De Visscher, C. Delaere, M. Delcourt, B. Francois, A. Giammanco, M. Komm, G. Krintiras, V. Lemaitre, A. Magitteri, A. Mertens, M. Musich, K. Piotrzkowski, L. Quertenmont, A. Saggio, M. Vidal Marono, S. Wertz, J. Zobec Yerevan Physics Institute, Yerevan, Armenia A.M. Sirunyan, A. Tumasyan Institut f¨ur Hochenergiephysik, Wien, Austria W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, E. Brondolin, M. Drag- icevic, J. Er¨o, M. Flechl, M. Friedl, R. Fr¨uhwirth1, V.M. Ghete, J. Grossmann, J. Hrubec, M. Jeitler1, A. K¨onig, N. Krammer, I. Kr¨atschmer, D. Liko, T. Madlener, I. Mikulec, E. Pree, N. Rad, H. Rohringer, J. Schieck1, R. Sch¨ofbeck, M. Spanring, D. Spitzbart, W. Waltenberger, J. Wittmann, C.-E. Wulz1, M. Zarucki JHEP01(2018)045 Institute for Nuclear Problems, Minsk, Belarus V. Chekhovsky, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen, Antwerpen, Belgium E.A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, M. Van De Klundert, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel E.A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, M. Van De Klundert, H. Va Haevermaet, P. Van Mechelen, N. Van Remortel Vrije Universiteit Brussel, Brussel, Belgium The CMS collaboration Yerevan Physics Institute, Yerevan, Armenia A.M. Sirunyan, A. Tumasyan Universit´e de Mons, Mons, Belgium N. Beliy Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil W.L. Ald´a J´unior, F.L. Alves, G.A. Alves, L. Brito, M. Correa Martins Junior, C. Hensel, A. Moraes, M.E. Pol, P. Rebello Teles – 15 – Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato4, E. Coelho, E.M. Da Costa, G.G. Da Silveira5, D. De Jesus Damiao, S. Fonseca De Souza, L.M. Huertas Guativa, H. Malbouisson, M. Melo De Almeida, C. Mora Herrera, L. Mundim, H. Nogima, L.J. Sanchez Rosas, A. Santoro, A. Sznajder, M. Thiel, E.J. Tonelli Manganote4, F. Torres Da Silva De Araujo, A. Vilela Pereira Universidade Estadual Paulista a, Universidade Federal do ABC b, S˜ao Paulo, Brazil S. Ahujaa, C.A. Bernardesa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb, P.G. Mercadanteb, S.F. Novaesa, Sandra S. Padulaa, D. Romero Abadb, J.C. Ruiz Vargasa JHEP01(2018)045 Institute for Nuclear Research and Nuclear Energy of Bulgaria Academy of Sciences A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov, M. Shopova, G. Sul- tanov University of Soﬁa, Soﬁa, Bulgaria University of Soﬁa, Soﬁa, Bulgaria A Dimitrov I Glushkov L Litov B Pavlov P Petkov University of Soﬁa, Soﬁa, Bulgaria University of Soﬁa, Soﬁa, Bulgaria A. Dimitrov, I. Glushkov, L. Litov, B. Pavlov, P. Petkov A. Dimitrov, I. Glushkov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China W. Fang6, X. Gao6, L. Yuan Beihang University, Beijing, China W. Fang6, X. Gao6, L. Yuan Institute of High Energy Physics, Beijing, China Institute of High Energy Physics, Beijing, China Institute of High Energy Physics, Beijing, China M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D. Leggat, M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D. Leggat, H. Liao, Z. Liu, F. Romeo, S.M. Shaheen, A. Spiezia, J. Tao, C. Wang, Z. Wang, E. Yazgan, H. Zhang, S. Zhang, J. Zhao State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China Y. Ban, G. Chen, Q. Li, S. Liu, Y. Mao, S.J. Qian, D. Wang, Z. Xu Universidad de Los Andes, Bogota, Colombia C. Avila, A. Cabrera, L.F. Chaparro Sierra, C. Florez, C.F. Gonz´alez Hern´andez, J.D. Ruiz Alvarez, M.A. Segura Delgado University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia B. Courbon, N. Godinovic, D. Lelas, I. Puljak, P.M. Ribeiro Cipriano, T. Sculac University of Split, Faculty of Science, Split, Croatia Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, A. Starodumov7, T. Susa University of Cyprus, Nicosia, Cyprus M.W. Ather, A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H. Rykaczewski – 16 – Charles University, Prague, Czech Republic M. Finger8, M. Finger Jr.8 Universidad San Francisco de Quito, Quito, Ecuador E. Carrera Jarrin Academy of Scientiﬁc Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt A.A. Abdelalim9,10, Y. Mohammed11, E. Salama12,13 National Institute of Chemical Physics and Biophysics, Tallinn, Estonia R.K. Dewanjee, M. Kadastik, L. Perrini, M. Raidal, A. Tiko, C. Veelken JHEP01(2018)045 Department of Physics, University of Helsinki, Helsinki, Finland P. Eerola, H. Kirschenmann, J. Pekkanen, M. Voutilainen Helsinki Institute of Physics, Helsinki, Finland Helsinki Institute of Physics, Helsinki, Finland J. Havukainen, J.K. Heikkil¨a, T. J¨arvinen, V. Karim¨aki, R. Kinnunen, T. Lamp´e J. Havukainen, J.K. Heikkila, T. Jarvinen, V. Karimaki, R. Kinnunen, T. Lampen, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lind´en, P. Luukka, H. Siikonen, E. Tuominen, J. Tuominiemi Lappeenranta University of Technology, Lappeenranta, Finland J. Talvitie, T. Tuuva Lappeenranta University of Technology, Lappeenranta, Finland J. Talvitie, T. Tuuva IRFU, CEA, Universit´e Paris-Saclay, Gif-sur-Yvette, France M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J.L. Faure, F. Ferri, S. Ganjour, S. Ghosh, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, I. Kucher, C. Leloup, E. Locci, M. Machet, J. Malcles, G. Negro, J. Rander, A. Rosowsky, M. ¨O. Sahin, M. Titov Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Univer- sit´e Paris-Saclay, Palaiseau, France Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Unive sit´e Paris-Saclay, Palaiseau, France A. Abdulsalam, C. Amendola, I. Antropov, S. Baﬃoni, F. Beaudette, P. Busson, L. Cadamuro, C. Charlot, R. Granier de Cassagnac, M. Jo, S. Lisniak, A. Lobanov, J. Martin Blanco, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, R. Salerno, J.B. Sauvan, Y. Sirois, A.G. Stahl Leiton, T. Strebler, Y. Yilmaz, A. Zabi, A. Zghiche Universit´e de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France J.-L. Agram14, J. Andrea, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert, N. Chanon, C. Collard, E. Conte14, X. Coubez, J.-C. Fontaine14, D. Gel´e, U. Goerlach, M. Jansov´a, A.-C. Le Bihan, N. Tonon, P. Van Hove Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France S. Gadrat – 17 – Universit´e de Lyon, Universit´e Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucl´eaire de Lyon, Villeurbanne, France S. Beauceron, C. Bernet, G. Boudoul, R. Chierici, D. Contardo, P. Depasse, H. El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G. Grenier, B. Ille, F. Lagarde, I.B. Laktineh, M. Lethuillier, L. Mirabito, A.L. Pequegnot, S. Perries, A. Popov15, V. Sordini, M. Vander Donckt, S. Viret Georgian Technical University, Tbilisi, Georgia T. Toriashvili16 Tbilisi State University, Tbilisi, Georgia Tbilisi State University, Tbilisi, Georgia Z. Tsamalaidze8 JHEP01(2018)045 Z. Tsamalaidze8 RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, C. Schomakers, J. Schulz, V. Zhukov15 RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany A. Albert, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, A. G¨uth, M. Hamer, T. Hebbeker, C. Heidemann, K. Hoepfner, S. Knutzen, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, T. Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, D. Teyssier, S. Th¨uer RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany G. Fl¨ugge, B. Kargoll, T. Kress, A. K¨unsken, T. M¨uller, A. Nehrkorn, A. Nowack, C. Pistone, O. Pooth, A. Stahl17 Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, K. Beernaert, O. Behnke, U. Behrens, A. Berm´udez Mart´ınez, A.A. Bin Anuar, K. Borras18, V. Botta, A. Camp- bell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G. Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo19, J. Garay Garcia, A. Geiser, A. Gizhko, J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, M. Guthoﬀ, A. Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Unive sit´e Paris-Saclay, Palaiseau, France Harb, J. Hauk, M. Hempel20, H. Jung, A. Kalogeropoulos, M. Kasemann, J. Keaveney, C. Kleinwort, I. Korol, D. Kr¨ucker, W. Lange, A. Lelek, T. Lenz, J. Leonard, K. Lipka, W. Lohmann20, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, G. Mittag, J. Mnich, A. Mussgiller, E. Ntomari, D. Pitzl, A. Raspereza, M. Savitskyi, P. Saxena, R. Shevchenko, S. Spannagel, N. Stefaniuk, G.P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O. Zenaiev University of Hamburg, Hamburg, Germany R. Aggleton, S. Bein, V. Blobel, M. Centis Vignali, T. Dreyer, E. Garutti, D. Gonzalez, J. Haller, A. Hinzmann, M. Hoﬀmann, A. Karavdina, R. Klanner, R. Kogler, N. Kovalchuk, S. Kurz, T. Lapsien, I. Marchesini, D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, F. Pantaleo17, T. Peiﬀer, A. Perieanu, C. Scharf, P. Schleper, A. Schmidt, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbr¨uck, F.M. Stober, M. St¨over, H. Tholen, D. Troendle, E. Usai, A. Vanhoefer, B. Vormwald R. Aggleton, S. Bein, V. Blobel, M. Centis Vignali, T. Dreyer, E. Garutti, D. Gonzalez, J. Haller, A. Hinzmann, M. Hoﬀmann, A. Karavdina, R. Klanner, R. Kogler, N. Kovalchuk, S. Kurz, T. Lapsien, I. Marchesini, D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, F. Pantaleo17, T. Peiﬀer, A. Perieanu, C. Scharf, P. Schleper, A. Schmidt, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbr¨uck, F.M. Stober, M. St¨over, H. Tholen, D. Troendle, E. Usai, A. Vanhoefer, B. Vormwald – 18 – Institut f¨ur Experimentelle Kernphysik, Karlsruhe, Germany M. Akbiyik, C. Barth, M. Baselga, S. Baur, E. Butz, R. Caspart, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, N. Faltermann, B. Freund, R. Friese, M. Giﬀels, M.A. Har- rendorf, F. Hartmann17, S.M. Heindl, U. Husemann, F. Kassel17, S. Kudella, H. Mildner, M.U. Mozer, Th. M¨uller, M. Plagge, G. Quast, K. Rabbertz, M. Schr¨oder, I. Shvetsov, G. Sieber, H.J. Simonis, R. Ulrich, S. Wayand, M. Weber, T. Weiler, S. Williamson, C. W¨ohrmann, R. Wolf Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece JHEP01(2018)045 JHEP01(2018)045 G. Anagnostou, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas, I. Topsis-Giotis National and Kapodistrian University of Athens, Athens, Greece G. Karathanasis, S. Kesisoglou, A. Panagiotou, N. Saoulidou National Technical University of Athens, Athens, Greece K. Kousouris University of Io´annina, Io´annina, Greece y , , I. Evangelou, C. Foudas, P. Kokkas, S. Mallios, N. Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F.A. Triantis MTA-ELTE Lend¨ulet CMS Particle and Nuclear Physics Group, E¨otv¨os Lor´and University, Budapest, Hungary M. Csanad, N. Filipovic, G. Pasztor, O. Sur´anyi, G.I. Veres21 Wigner Research Centre for Physics, Budapest, Hungary G. Bencze, C. Hajdu, D. Horvath22, ´A. Hunyadi, F. Sikler, V. Veszpremi Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi23, A. Makovec, J. Molnar, Z. Szillasi Institute of Physics, University of Debrecen, Debrecen, Hungary M. Bart´ok21, P. Raics, Z.L. Trocsanyi, B. University of Hamburg, Hamburg, Germany Ujvari Indian Institute of Science (IISc), Bangalore, India S. Choudhury, J.R. Komaragiri National Institute of Science Education and Research, Bhubaneswar, India S. Bahinipati24, S. Bhowmik, P. Mal, K. Mandal, A. Nayak25, D.K. Sahoo24, N. Sahoo, S.K. Swain Panjab University, Chandigarh, India Indian Institute of Technology Madras, Madras, India P.K. Behera Indian Institute of Technology Madras, Madras, India P.K. Behera Bhabha Atomic Research Centre, Mumbai, India Bhabha Atomic Research Centre, Mumbai, India R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty17, P.K. Netrakanti, L.M. Pant, P. Shukla, A. Topkar JHEP01(2018)045 Tata Institute of Fundamental Research-A, Mumbai, India T. Aziz, S. Dugad, B. Mahakud, S. Mitra, G.B. Mohanty, N. Sur, B. Sutar T. Aziz, S. Dugad, B. Mahakud, S. Mitra, G.B. Mohanty, N. Sur, B. Sutar Tata Institute of Fundamental Research-B, Mumbai, India S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S. Kumar, M. Maity26, G. Majumder, K. Mazumdar, T. Sarkar26, N. Wickramage27 Indian Institute of Science Education and Research (IISER), Pune, India S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran S. Chenarani28, E. Eskandari Tadavani, S.M. Etesami28, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi29, F. Rezaei Hosseinabadi, B. Safarzadeh30, M. Zeinali University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald Panjab University, Chandigarh, India S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, N. Dhingra, A.K. Kalsi, A. Kaur, M. Kau S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, N. Dhingra, A.K. Kalsi, A. Kaur, M. Kaur, S. Kaur, R. Kumar, P. Kumari, A. Mehta, J.B. Singh, G. Walia S. Kaur, R. Kumar, P. Kumari, A. Mehta, J.B. Singh, G. Walia University of Delhi, Delhi, India Ashok Kumar, Aashaq Shah, A. Bhardwaj, S. Chauhan, B.C. Choudhary, R.B. Garg, S. Keshri, A. Kumar, S. Malhotra, M. Naimuddin, K. Ranjan, R. Sharma – 19 – Saha Institute of Nuclear Physics, HBNI, Kolkata, India Saha Institute of Nuclear Physics, HBNI, Kolkata, India R. Bhardwaj, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep, S. Dey, S. Dutt, S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S. Nandan, A. Purohit, A. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur R. Bhardwaj, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep, S. Dey, S. Dutt, S. Dutt R. Bhardwaj, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep, S. Dey, S. Dutt, S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S. Nandan, A. Purohit, A. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald M. Felcini, M. Grunewald INFN Sezione di Bari a, Universit`a di Bari b, Politecnico di Bari c, Bari, Italy M. Abbresciaa,b, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b, N. De Filippisa,c, M. De Palmaa,b, F. Erricoa,b, L. Fiorea, G. Iasellia,c, S. Lezkia,b, G. Maggia,c, M. Maggia, G. Minielloa,b, S. Mya,b, S. Nuzzoa,b, A. Pompilia,b, G. Pugliesea,c, R. Radognaa, A. Ranieria, G. Selvaggia,b, A. Sharmaa, L. Silvestrisa,17, R. Vendittia, P. Verwilligena P. Verwilligena INFN Sezione di Bologna a, Universit`a di Bologna b, Bologna, Italy G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, L. Borgonovia,b, S. Braibant-Giacomellia,b, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa, S.S. Chhibraa, G. Codispotia,b, M. Cuﬃania,b, G.M. Dallavallea, F. Fabbria, A. Fanfania,b, D. Fasanellaa,b, P. Giacomellia, C. Grandia, L. Guiduccia,b, S. Marcellinia, G. Masettia, A. Montanaria, F.L. Navarriaa,b, A. Perrottaa, A.M. Rossia,b, T. Rovellia,b, G.P. Sirolia,b, N. Tosia INFN Sezione di Catania a, Universit`a di Catania b, Catania, Italy S. Albergoa,b, S. Costaa,b, A. Di Mattiaa, F. Giordanoa,b, R. Potenzaa,b, A. Tricomia,b, C. Tuvea,b INFN Sezione di Catania a, Universit`a di Catania b, Catania, Italy S. Albergoa,b, S. Costaa,b, A. Di Mattiaa, F. Giordanoa,b, R. Potenzaa,b, A. Tricomia C. Tuvea,b – 20 – INFN Sezione di Firenze a, Universit`a di Firenze b, Firenze, Italy G. Barbaglia, K. Chatterjeea,b, V. Ciullia,b, C. Civininia, R. D’Alessandroa,b, E. Focardia,b, P. Lenzia,b, M. Meschinia, S. Paolettia, L. Russoa,31, G. Sguazzonia, D. Stroma, b 17 INFN Sezione di Firenze a, Universit`a di Firenze b, Firenze, Italy G. Barbaglia, K. Chatterjeea,b, V. Ciullia,b, C. Civininia, R. D’Alessandroa,b, E. Focardia INFN Sezione di Firenze a, Universit`a di Firenze b, Firenze, Italy G. Barbaglia, K. Chatterjeea,b, V. Ciullia,b, C. Civininia, R. D’Alessandroa,b, E. Focardia,b, P. Lenzia,b, M. Meschinia, S. Paolettia, L. Russoa,31, G. Sguazzonia, D. Stroma, L. Viliania,b,17 P. Lenzia,b, M. Meschinia, S. Paolettia, L. Russoa,31, G. Sguazzonia, D. Stroma, L. Viliania,b,17 INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera17 INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera17 INFN Sezione di Genova a, Universit`a di Genova b, Genova, Italy V. Calvellia,b, F. Ferroa, E. Robuttia, S. Tosia,b JHEP01(2018)045 INFN Sezione di Milano-Bicocca a, Universit`a di Milano-Bicocca b, Milano, Italy A. Benagliaa, A. Beschi, L. Brianzaa,b, F. Brivioa,b, V. Cirioloa,b, M.E. Dinardoa,b, A. Benagliaa, A. Beschi, L. Brianzaa,b, F. Brivioa,b, V. Cirioloa,b, M.E. University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald Dinardoa,b, S Fiorendia,b S Gennaia A Ghezzia,b P Govonia,b M Malbertia,b S Malvezzia g , , , , , , Fiorendia,b, S. Gennaia, A. Ghezzia,b, P. Govonia,b, M. Malbertia,b, S. Malvezzia, R.A. Manzonia,b, D. Menascea, L. Moronia, M. Paganonia,b, K. Pauwelsa,b, D. Pedrinia, S Pi i ia b 32 S R ia b N R d llia T T b lli d F ti a b R.A. Manzonia,b, D. Menascea, L. Moronia, M. Paganonia,b, K. Pauwelsa,b, D. Pedrinia, S. Pigazzinia,b,32, S. Ragazzia,b, N. Redaellia, T. Tabarelli de Fatisa,b INFN Sezione di Napoli a, Universit`a di Napoli ’Federico II’ b, Napoli, Italy, Universit`a della Basilicata c, Potenza, Italy, Universit`a G. Marconi d, Roma, Italy S. Buontempoa, N. Cavalloa,c, S. Di Guidaa,d,17, F. Fabozzia,c, F. Fiengaa S. Buontempoa, N. Cavalloa,c, S. Di Guidaa,d,17, F. Fabozzia,c, F. Fiengaa,b, A.O.M. Iorioa,b, W.A. Khana, L. Listaa, S. Meolaa,d,17, P. Paoluccia,17, C. Sciaccaa,b, F Thyssena S. Buontempoa, N. Cavalloa,c, S. Di Guidaa,d,17, F. Fabozzia,c, F. Fiengaa,b, A.O.M. Iorioa,b, W.A. Khana, L. Listaa, S. Meolaa,d,17, P. Paoluccia,17, C. Sciaccaa,b, S. Buontempoa, N. Cavalloa,c, S. Di Guidaa,d,17, F. Fabozzia,c, F. Fiengaa,b, A.O.M. Iorioa,b, W.A. Khana, L. Listaa, S. Meolaa,d,17, P. Paoluccia,17, C. Sciaccaa,b, F. Thyssena INFN Sezione di Padova a, Universit`a di Padova b, Padova, Italy, Universit`a di Trento c, Trento, Italy P. Azzia, N. Bacchettaa, L. Benatoa,b, D. Biselloa,b, A. Bolettia,b, R. Carlina,b, A. Car- valho Antunes De Oliveiraa,b, P. Checchiaa, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, F. Gasparinia,b, U. Gasparinia,b, A. Gozzelinoa, S. Lacapraraa, M. Margonia,b, A.T. Meneguzzoa,b, N. Pozzobona,b, P. Ronchesea,b, R. Rossina,b, F. Simonettoa,b, E. Torassaa, M. Zanettia,b, P. Zottoa,b, G. Zumerlea,b INFN Sezione di Pavia a, Universit`a di Pavia b, Pavia, Italy INFN Sezione di Pavia a, Universit`a di Pavia b, Pavia, Italy A. Braghieria, A. Magnania, P. Montagnaa,b, S.P. Rattia,b, V. Rea, M. Ressegottia,b, C. Riccardia,b, P. Salvinia, I. Vaia,b, P. Vituloa,b A. Braghieria, A. Magnania, P. Montagnaa,b, S.P. Rattia,b, V. Rea, M. Ressegottia C. Riccardia,b, P. Salvinia, I. Vaia,b, P. Vituloa,b INFN Sezione di Perugia a, Universit`a di Perugia b, Perugia, Italy L. Alunni Solestizia,b, M. Biasinia,b, G.M. Bileia, C. Cecchia,b, D. Ciangottinia,b, L. Fan`oa,b, P. Laricciaa,b, R. Leonardia,b, E. Manonia, G. Mantovania,b, V. Mariania,b, M. Menichellia, A. Rossia,b, A. Santocchiaa,b, D. Spigaa INFN Sezione di Pisa a, Universit`a di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy K. Androsova, P. Azzurria,17, G. Bagliesia, T. Boccalia, L. Borrello, R. Castaldia, K. Androsova, P. Azzurria,17, G. Bagliesia, T. Boccalia, L. Borrello, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, L. Gianninia,c, A. Giassia, M.T. Grippoa,31, F. Ligabuea,c, T. Lomtadzea, E. Mancaa,c, G. Mandorlia,c, A. Messineoa,b, F. Pallaa, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, L. Gianninia,c, A. Giassia, M.T. Grippoa,3 M.A. Ciocci , , R. Dell Orso , G. Fedi , L. Giannini , , A. Giassi , M.T. Grippo , , F. Ligabuea,c, T. Lomtadzea, E. Mancaa,c, G. Mandorlia,c, A. Messineoa,b, F. Pallaa, F. Ligabuea,c, T. Lomtadzea, E. Mancaa,c, G. Mandorlia,c, A. Messineoa,b, F. Pallaa, – 21 – A. Rizzia,b, A. Savoy-Navarroa,33, P. Spagnoloa, R. Tenchinia, G. Tonellia,b, A. Venturia, P.G. Verdinia INFN Sezione di Roma a, Sapienza Universit`a di Roma b, Rome, Italy L. Baronea,b, F. Cavallaria, M. Cipriania,b, N. Dacia, D. Del Rea,b,17, E. Di Marcoa,b, M. Diemoza, S. Gellia,b, E. Longoa,b, F. Margarolia,b, B. Marzocchia,b, P. Meridiania, G. Organtinia,b, R. Paramattia,b, F. Preiatoa,b, S. Rahatloua,b, C. Rovellia, F. Santanastasioa,b INFN Sezione di Torino a, Universit`a di Torino b, Torino, Italy, Universit`a del Piemonte Orientale c, Novara, Italy JHEP01(2018)045 JHEP01(2018)045 , , y N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika, R. Bellana,b, C. Biinoa, N. Cartigliaa, F. Cennaa,b, M. Costaa,b, R. Covarellia,b, A. Deganoa,b, N. Demariaa, B. Kiania,b, C. Mariottia, S. Masellia, E. Migliorea,b, V. Monacoa,b, E. Monteila,b, M. Montenoa, M.M. Obertinoa,b, L. Pachera,b, N. Pastronea, M. Pelliccionia, G.L. Pinna Angionia,b, F. Raveraa,b, A. Romeroa,b, M. Ruspaa,c, R. Sacchia,b, K. Shchelinaa,b, V. Solaa, A. Solanoa,b, A. Staianoa, P. Traczyka,b G.L. Pinna Angionia,b, F. Raveraa,b, A. Romeroa,b, M. Ruspaa,c, R. Sacchia,b, K. Shchelinaa,b, V. Solaa, A. Solanoa,b, A. Staianoa, P. Korea University, Seoul, Korea S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, K. Lee, K.S. Lee, S. Lee, J. Lim, S.K. Park, Y. Roh INFN Sezione di Pavia a, Universit`a di Pavia b, Pavia, Italy Traczyka,b INFN Sezione di Trieste a, Universit`a di Trieste b, Trieste, Italy S. Belfortea, M. Casarsaa, F. Cossuttia, G. Della Riccaa,b, A. Zanettia Kyungpook National University, Daegu, Korea D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S. Sekmen, D.C. Son, Y.C. Yang Chonbuk National University, Jeonju, Korea A. Lee Chonbuk National University, Jeonju, Korea A. Lee Chonnam National University, Institute for Universe and Elementary Particles, Kwangju, Korea Chonnam National University, Institute for Universe and Elementary Particles, K j K Kwangju, Korea Kwangju, Korea H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea J.A. Brochero Cifuentes, J. Goh, T.J. Kim Korea University, Seoul, Korea Seoul National University, Seoul, Korea Seoul National University, Seoul, Korea J. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, K. Nam, S.B. Oh, B.C. Radburn-Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu J. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, K. Nam, S.B. Oh, B.C. Radburn-Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul, Korea M. Choi, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park University of Seoul, Seoul, Korea M. Choi, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park M. Choi, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park M. Choi, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park Sungkyunkwan University, Suwon, Korea Y. Choi, C. Hwang, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania V. Dudenas, A. Juodagalvis, J. Vaitkus V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia I. Ahmed, Z.A. Ibrahim, M.A.B. Md Ali34, F. Mohamad Idris35, W.A.T. Wan Abdullah, M.N. Yusli, Z. Zolkapli Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico Reyes-Almanza, R, Ramirez-Sanchez, G., Duran-Osuna, M. C., H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz36, Rabadan-Trejo, R. I., R. Lopez-Fernandez, J. Mejia Guisao, A. Sanchez-Hernandez JHEP01(2018)045 Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia U ve s dad be oa e ca a, e co C ty, e co S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad Aut´onoma de San Luis Potos´ı, San Luis Potos´ı, Mexico A. Morelos Pineda University of Auckland, Auckland, New Zealand D. Krofcheck University of Canterbury, Christchurch, New Zealand P.H. Butler National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, A. Saddique, M.A. Shah, M. Shoaib, M. Waqas Sungkyunkwan University, Suwon, Korea Y. Choi, C. Hwang, J. Lee, I. Yu Y. Choi, C. Hwang, J. Lee, I. Yu – 22 – Vilnius University, Vilnius, Lithuania Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia Y. Ivanov, V. Kim40, E. Kuznetsova41, P. Levchenko, V. Murzin, V. Oreshkin, I. Smirnov, V. Sulimov, L. Uvarov, S. Vavilov, A. Vorobyev National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. G´orski, M. Kazana, K. Nawrocki, M. Szleper, P. Zalewski Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland K. Bunkowski, A. Byszuk37, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, A. Pyskir, M. Walczak Laborat´orio de Instrumenta¸c˜ao e F´ısica Experimental de Part´ıculas, Lisboa, Portugal P. Bargassa, C. Beir˜ao Da Cruz E Silva, A. Di Francesco, P. Faccioli, B. Galinhas, M G lli J H ll N L d L Ll t I l i M V N ll di J S i P. Bargassa, C. Beir˜ao Da Cruz E Silva, A. Di Francesco, P. Faccioli, B. Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M.V. Nemallapudi, J. Seixas, G St O T ld i D V d i J V l P. Bargassa, C. Beir˜ao Da Cruz E Silva, A. Di Francesco, P. Faccioli, B. Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M.V. Nemallapudi, J. Seixas, G. Strong, O. Toldaiev, D. Vadruccio, J. Varela M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M.V. Nemallapudi, J. Seixas, G. Strong, O. Toldaiev, D. Vadruccio, J. Varela , , , g , p , , G. Strong, O. Toldaiev, D. Vadruccio, J. Varela – 23 – Joint Institute for Nuclear Research, Dubna, Russia S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev, V. Karjavi S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbuno S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev, V. Karjavin, A. Lanev, A. Malakhov, V. Matveev38,39, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin, A. Zarubin , , , , , , j , A. Lanev, A. Malakhov, V. Matveev38,39, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia Centro de Investigaciones Energ´eticas Medioambientales y Tec- nol´ogicas (CIEMAT), Madrid, Spain Centro de Investigaciones Energ´eticas Medioambientales y Tec- nol´ogicas (CIEMAT), Madrid, Spain J. Alcaraz Maestre, M. Barrio Luna, M. Cerrada, N. Colino, B. De La Cruz, A. Delgado Peris, A. Escalante Del Valle, C. Fernandez Bedoya, J.P. Fern´andez Ramos, J. Flix, M.C. Fouz, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, D. Moran, A. P´erez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, M.S. Soares, A. ´Alvarez Fern´andez Universidad Aut´onoma de Madrid, Madrid, Spain C. Albajar, J.F. de Troc´oniz, M. Missiroli JHEP01(2018)045 Universidad de Oviedo, Oviedo, Spain J. Cuevas, C. Erice, J. Fernandez Menendez, I. Gonzalez Caballero, J.R. Gonz´alez Fern´andez, E. Palencia Cortezon, S. Sanchez Cruz, P. Vischia, J.M. Vizan Garcia Instituto de F´ısica de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain I.J. Cabrillo, A. Calderon, B. Chazin Quero, E. Curras, J. Duarte Campderros, M. Fer- nandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, P. Martinez Ruiz del Arbol, F. Matorras, J. Piedra Gomez, T. Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar Cortabitarte CERN, European Organization for Nuclear Research, Geneva, Switzerland D. Abbaneo, B. Akgun, E. Auﬀray, P. Baillon, A.H. Ball, D. Barney, J. Bendavid, M. Bianco, P. Bloch, A. Bocci, C. Botta, T. Camporesi, R. Castello, M. Cepeda, G. Cerminara, E. Chapon, Y. Chen, D. d’Enterria, A. Dabrowski, V. Daponte, A. David, M. De Gruttola, A. De Roeck, N. Deelen, M. Dobson, T. du Pree, M. D¨unser, N. Dupont, A. Elliott-Peisert, P. Everaerts, F. Fallavollita, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, A. Gilbert, K. Gill, F. Glege, D. Gulhan, P. Harris, J. Hegeman, V. Innocente, A. Jafari, P. Janot, O. Karacheban20, J. Kieseler, V. Kn¨unz, A. Kornmayer, M.J. Kortelainen, M. Krammer1, C. Lange, P. Lecoq, C. Louren¸co, M.T. Lucchini, L. Malgeri, M. Mannelli, A. Martelli, F. Meijers, J.A. Merlin, S. Mersi, E. Meschi, P. Milenovic45, F. Moortgat, M. Mulders, H. Neugebauer, J. Ngadiuba, S. Orfanelli, L. Orsini, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A. Pfeiﬀer, M. Pierini, D. Rabady, A. Racz, T. Reis, G. Rolandi46, M. Rovere, H. Sakulin, C. Sch¨afer, C. Schwick, M. Seidel, M. Selvaggi, A. Sharma, P. Silva, P. Sphicas47, A. Stakia, J. Steggemann, M. Stoye, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns48, M. Verweij, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland W. Bertl†, L. Caminada49, K. Deiters, W. Erdmann, R. Horisberger, Q. Institute for Nuclear Research, Moscow, Russia Institute for Nuclear Research, Moscow, Russia JHEP01(2018)045 JHEP01(2018)045 Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical and Experimental Physics, Moscow, Russia V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, A. Stepennov, M. Toms, E. Vlasov, A. Zhokin Moscow Institute of Physics and Technology, Moscow, Russia T. Aushev, A. Bylinkin39 National Research Nuclear University ’Moscow Engineering Physics Insti- tute’ (MEPhI), Moscow, Russia M. Chadeeva42, P. Parygin, D. Philippov, S. Polikarpov, E. Popova, V. Rusinov P.N. Lebedev Physical Institute, Moscow, Russia P.N. Lebedev Physical Institute, Moscow, Russia V Andreev M Azarkin39 I Dremin39 M Kirakosyan39 A Terkulov V. Andreev, M. Azarkin39, I. Dremin39, M. Kirakosyan39, A. Terkulov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia A. Baskakov, A. Belyaev, E. Boos, A. Demiyanov, A. Ershov, A. Gribushin, O. Kodolova, V. Korotkikh, I. Lokhtin, I. Miagkov, S. Obraztsov, S. Petrushanko, V. Savrin, A. Snigirev, I. Vardanyan Novosibirsk State University (NSU), Novosibirsk, Russia V. Blinov43, Y.Skovpen43, D. Shtol43 State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin, D. Kon- stantinov, P. Mandrik, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin, D. Kon- stantinov, P. Mandrik, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia P. Adzic44, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia Sciences, Belgrade, Serbia P. Adzic44, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic P. Adzic44, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic – 24 – Centro de Investigaciones Energ´eticas Medioambientales y Tec- nol´ogicas (CIEMAT), Madrid, Spain Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe, S.A. Wiederkehr ETH Zurich - Institute for Particle Physics and Astrophysics (IPA), Zurich, Switzerland M. Backhaus, L. B¨ani, P. Berger, L. Bianchini, B. Casal, G. Dissertori, M. Dittma M. Backhaus, L. B¨ani, P. Berger, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Doneg`a, C. Dorfer, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, T. Klijnsma, , , g , , , , , M. Doneg`a, C. Dorfer, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, T. Klijnsma, – 25 – W. Lustermann, B. Mangano, M. Marionneau, M.T. Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandolﬁ, J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quit- tnat, M. Reichmann, D.A. Sanz Becerra, M. Sch¨onenberger, L. Shchutska, V.R. Tavolaro, K. Theoﬁlatos, M.L. Vesterbacka Olsson, R. Wallny, D.H. Zhu Universit¨at Z¨urich, Zurich, Switzerland T.K. Aarrestad, C. Amsler50, M.F. Canelli, A. De Cosa, R. Del Burgo, S. Donato, C. Galloni, T. Hreus, B. Kilminster, D. Pinna, G. Rauco, P. Robmann, D. Salerno, K. Schweiger, C. Seitz, Y. Takahashi, A. Zucchetta National Central University, Chung-Li, Taiwan V. Candelise, T.H. Doan, Sh. Jain, R. Khurana, C.M. Kuo, W. Lin, A. Pozdnyakov, S.S. Yu JHEP01(2018)045 National Taiwan University (NTU), Taipei, Taiwan Arun Kumar, P. Chang, Y. Chao, K.F. Chen, P.H. Chen, F. Fiori, W.-S. Hou, Y. Hsiung, Y.F. Liu, R.-S. Lu, E. Paganis, A. Psallidas, A. Steen, J.f. Tsai Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, Thailand Baylor University, Waco, U.S.A. Baylor University, Waco, U.S.A. A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika, C. Smith Catholic University of America, Washington DC, U.S.A. R. Bartek, A. Dominguez The University of Alabama, Tuscaloosa, U.S.A. A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West The University of Alabama, Tuscaloosa, U.S.A. A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University, Boston, U.S.A. D. Arcaro, A. Avetisyan, T. Bose, D. Gastler, D. Rankin, C. Richardson, J. Rohlf, L. Sulak, D. Zou Imperial College, London, United Kingdom G. Auzinger, R. Bainbridge, J. Borg, S. Breeze, O. Buchmuller, A. Bundock, S. Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M. Della Negra, R. Di Maria, A. Elwood, Y. Haddad, G. Hall, G. Iles, T. James, R. Lane, C. Laner, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, T. Matsushita, J. Nash, A. Nikitenko7, V. Palladino, M. Pesaresi, D.M. Raymond, A. Richards, A. Rose, E. Scott, C. Seez, A. Shtipliyski, S. Summers, A. Tapper, K. Uchida, M. Vazquez Acosta64, T. Virdee17, N. Wardle, D. Winterbottom, J. Wright, S.C. Zenz JHEP01(2018)045 Thailand B. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas B. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas C¸ ukurova University, Physics Department, Science and Art Faculty, Adana, Turkey M.N. Bakirci51, A. Bat, F. Boran, S. Damarseckin, Z.S. Demiroglu, C. Dozen, S. Girgi M.N. Bakirci , A. Bat, F. Boran, S. Damarseckin, Z.S. Demiroglu, C. Dozen, S. Girgis, G. Gokbulut, Y. Guler, I. Hos52, E.E. Kangal53, O. Kara, U. Kiminsu, M. Oglakci, G. Onengut54, K. Ozdemir55, S. Ozturk51, A. Polatoz, B. Tali56, U.G. Tok, H. Topakli51, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez G. Gokbulut, Y. Guler, I. Hos52, E.E. Kangal53, O. Kara, U. Kiminsu, M. Oglakci, G Onengut54 K O demir55 S O turk51 A Polato B Tali56 U G Tok H Topakli51 G. Onengut54, K. Ozdemir55, S. Ozturk51, A. Polatoz, B. Tali56, U.G. Tok, H. Topakli51, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey B. Bilin, G. Karapinar57, K. Ocalan58, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. G¨ulmez, M. Kaya59, O. Kaya60, S. Tekten, E.A. Yetkin61 Bogazici University, Istanbul, Turkey Istanbul Technical University, Istanbul, Turkey M.N. Agaras, S. Atay, A. Cakir, K. Cankocak Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, Ukraine B. Grynyov National Scientiﬁc Center, Kharkov Institute of Physics and Technology, Kharkov, Ukraine L. Levchuk National Scientiﬁc Center, Kharkov Institute of Physics and Technology, Kharkov, Ukraine L. Levchuk University of Bristol, Bristol, United Kingdom F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans, O. Davignon, H. Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, D.M. Newbold62, S. Paramesvaran, T. Sakuma, S. Seif El Nasr-storey, D. Smith, V.J. Smith University of Bristol, Bristol, United Kingdom F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans, O. Davignon, H. Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, D.M. Newbold62, S. Paramesvaran, T. Sakuma, S. Seif El Nasr-storey, D. Smith, V.J. Smith – 26 – Rutherford Appleton Laboratory, Didcot, United Kingdom A. Belyaev63, C. Brew, R.M. Brown, L. Calligaris, D. Cieri, D.J.A. Cockerill, J.A. Cough- lan, K. Harder, S. Harper, E. Olaiya, D. Petyt, C.H. Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams Imperial College, London, United Kingdom Brown University, Providence, U.S.A. G. Benelli, D. Cutts, A. Garabedian, M. Hadley, J. Hakala, U. Heintz, J.M. Hogan, K.H.M. Kwok, E. Laird, G. Landsberg, J. Lee, Z. Mao, M. Narain, J. Pazzini, S. Piperov, S. Sagir, R. Syarif, D. Yu University of California, Davis, Davis, U.S.A. University of California, Davis, Davis, U.S.A. R. Band, C. Brainerd, D. Burns, M. Calderon De La Barca Sanchez, M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, M. Gardner, W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout, M. Shi, J. Smith, D. Stolp, K. Tos, M. Tripathi, Z. Wang University of California, Los Angeles, U.S.A. Brunel University, Uxbridge, United Kingdom J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, I.D. Reid, P. Symonds, L. Teodorescu, M. Turner, S. Zahid University of California, San Diego, La Jolla, U.S.A. University of California, San Diego, La Jolla, U.S.A. J.G. Branson, S. Cittolin, M. Derdzinski, R. Gerosa, D. Gilbert, B. Hashemi, A. Holzner, D. Klein, G. Kole, V. Krutelyov, J. Letts, I. Macneill, M. Masciovecchio, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A. Vartak, S. Wasserbaech65, J. Wood, F. W¨urthwein, A. Yagil, G. Zevi Della Porta JHEP01(2018)045 University of California, Santa Barbara - Department of Physics, Santa Bar- bara, U.S.A. N. Amin, R. Bhandari, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta, M. Franco Sevilla, C. George, F. Golf, L. Gouskos, J. Gran, R. Heller, J. Incandela, A. Ovcharova, H. Qu, J. Richman, D. Stuart, I. Suarez, J. Yoo California Institute of Technology, Pasadena, U.S.A. D. Anderson, A. Bornheim, J.M. Lawhorn, H.B. Newman, T. Nguyen, C. Pena, M. Spirop- ulu, J.R. Vlimant, S. Xie, Z. Zhang, R.Y. Zhu Carnegie Mellon University, Pittsburgh, U.S.A. M.B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, J. Russ, M. Sun, H. Vogel, I. Vorobiev, M. Weinberg Carnegie Mellon University, Pittsburgh, U.S.A. University of Colorado Boulder, Boulder, U.S.A. J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, M. Krohn, S. Leontsinis, T. Mulholland, K. Stenson, S.R. Wagner Cornell University, Ithaca, U.S.A. J. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, J.R. Patterso J. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, J.R. Patterson, D. Quach, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soﬃ, S.M. Tan, Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Fermi National Accelerator Laboratory, Batavia, U.S.A. S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S. Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, G. Bolla†, K. Burkett, J.N. But- ler, A. Canepa, G.B. Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi, J. Duarte, V.D. Elvira, J. Freeman, Z. Gecse, E. Gottschalk, L. Gray, D. Green, S. Gr¨unendahl, O. Gutsche, R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B. Klima, B. Kreis, S. Lammel, D. Lincoln, R. Lipton, M. Liu, T. Liu, R. Lopes De S´a, J. Lykken, K. Maeshima, N. Magini, J.M. Marraﬃno, D. Ma- son, P. McBride, P. Merkel, S. Mrenna, S. Nahn, V. O’Dell, K. Pedro, O. Prokofyev, G. Rakness, L. Ristori, B. Schneider, E. Sexton-Kennedy, A. Soha, W.J. Spalding, L. Spiegel, S. Stoynev, J. Strait, N. Strobbe, L. Taylor, S. Tkaczyk, N.V. Tran, L. University of California, Los Angeles, U.S.A. M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M. Ignatenko, N. Mccoll, S. Regnard, D. Saltzberg, C. Schnaible, V. Valuev – 27 – University of California, Riverside, Riverside, U.S.A. E. Bouvier, K. Burt, R. Clare, J. Ellison, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanso E. Bouvier, K. Burt, R. Clare, J. Ellison, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, J. Heilman, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete, M.I. Paneva, W. Si, L. Wang, H. Wei, S. Wimpenny, B. R. Yates J. Heilman, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete, M.I. Paneva, W. Si, L. Wang, H. Wei, S. Wimpenny, B. R. Yates The University of Iowa, Iowa City, U.S.A. y , y, B. Bilki66, W. Clarida, K. Dilsiz67, S. Durgut, R.P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya68, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul69, Y. Onel, F. Ozok70, A. Penzo, C. Snyder, E. Tiras, J. Wetzel, K. Yi Johns Hopkins University, Baltimore, U.S.A. University of California, San Diego, La Jolla, U.S.A. Uplegger, E.W. Vaandering, C. Vernieri, M. Verzocchi, R. Vidal, M. Wang, H.A. Weber, A. Whitbeck – 28 – University of Florida, Gainesville, U.S.A. D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerhoﬀ, A. Carnes, M. Carve D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerhoﬀ, A. Carnes, M. Carver, D. Curry, R.D. Field, I.K. Furic, S.V. Gleyzer, B.M. Joshi, J. Konigsberg, A. Korytov, K. Kotov, P. Ma, K. Matchev, H. Mei, G. Mitselmakher, D. Rank, K. Shi, D. Sperka, N. Terentyev, L. Thomas, J. Wang, S. Wang, J. Yelton Florida International University, Miami, U.S.A. Y.R. Joshi, S. Linn, P. Markowitz, J.L. Rodriguez Florida State University, Tallahassee, U.S.A. A. Ackert, T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, T. Kolberg, G. Martinez, T. Perry, H. Prosper, A. Saha, A. Santra, V. Sharma, R. Yohay JHEP01(2018)045 Johns Hopkins University, Baltimore, U.S.A. B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan, P. Maksimovic, J. Roskes, U. Sarica, M. Swartz, M. Xiao, C. You The University of Kansas, Lawrence, U.S.A. A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, J. Castle, S. Khalil, A. Kropivnit- skaya, D. Majumder, W. Mcbrayer, M. Murray, C. Royon, S. Sanders, E. Schmitz, J.D. Tapia Takaki, Q. Wang Kansas State University, Manhattan, U.S.A. A. Ivanov, K. Kaadze, Y. Maravin, A. Mohammadi, L.K. Saini, N. Skhirtladze, S. Toda Lawrence Livermore National Laboratory, Livermore, U.S.A. F. Rebassoo, D. Wright Florida Institute of Technology, Melbourne, U.S.A. Florida Institute of Technology, Melbourne, U.S.A. M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, T. Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, U.S.A. M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, R. Cavanaugh, X. Chen, O. Evdoki- mov, C.E. Gerber, D.A. Hangal, D.J. Hofman, K. Jung, J. Kamin, I.D. Sandoval Gonzalez, M.B. Tonjes, H. Trauger, N. Varelas, H. Wang, Z. Wu, J. Zhang Massachusetts Institute of Technology, Cambridge, U.S.A. Massachusetts Institute of Technology, Cambridge, U.S.A. D. Abercrombie, B. Allen, V. Azzolini, R. Barbieri, A. Baty, R. Bi, S. Brandt, W. B D. Abercrombie, B. Allen, V. Azzolini, R. Barbieri, A. Baty, R. Bi, S. Brandt, W. Busza, I.A. Cali, M. D’Alfonso, Z. Demiragli, G. Gomez Ceballos, M. Goncharov, D. Hsu, M. Hu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi, Y.S. Lai, Y.-J. Lee, A. Levin, P.D. Luckey, B. Maier, A.C. Marini, C. Mcginn, C. Mironov, S. Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, J. Salfeld-Nebgen, G.S.F. Stephans, K. Tatar, D. Velicanu, J. Wang, T.W. Wang, B. Wyslouch University of Minnesota, Minneapolis, U.S.A. University of Minnesota, Minneapolis, U.S.A. A.C. Benvenuti, R.M. Chatterjee, A. Evans, P. Hansen, J. Hiltbrand, S. Kalafut, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, J. Turkewitz, M.A. Wadud JHEP01(2018)045 University of Mississippi, Oxford, U.S.A. J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, U.S.A. University of Nebraska-Lincoln, Lincoln, U.S.A. E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, R. Gonzalez Suarez, R. Kamalieddin, I. Kravchenko, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, R. Gonzalez Suarez, R. Kamalieddin, I. Kravchenko, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger State University of New York at Buﬀalo, Buﬀalo, U.S.A. State University of New York at Buﬀalo, Buﬀalo, U.S.A. J. Dolen, A. Godshalk, C. Harrington, I. Iashvili, D. Nguyen, A. Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, U.S.A. Northeastern University, Boston, U.S.A. G. Alverson, E. Barberis, A. Hortiangtham, A. Massironi, D.M. Morse, T. Orimoto, R. Teixeira De Lima, D. Trocino, D. Wood Northwestern University, Evanston, U.S.A. Northwestern University, Evanston, U.S.A. S. Bhattacharya, O. Charaf, K.A. Hahn, N. Mucia, N. Odell, B. Pollack, M.H. Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, U.S.A. N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N. Kellams, K. Lannon, N. Loukas, N. Marinelli, F. Meng, C. Mueller, Y. Musienko38, M. Planer, A. Reinsvold, R. Ruchti, G. Smith, S. Taroni, M. Wayne, M. Wolf, A. Woodard The Ohio State University, Columbus, U.S.A. J. Alimena, L. Antonelli, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, A. Hart, C. Hill, W. Ji, B. Liu, W. Luo, B.L. Winer, H.W. Wulsin Princeton University, Princeton, U.S.A. University of Maryland, College Park, U.S.A. University of Maryland, College Park, U.S.A. C. Anelli, A. Baden, O. Baron, A. Belloni, B. Calvert, S.C. Eno, Y. Feng, C. Ferraioli, N.J. Hadley, S. Jabeen, G.Y. Jeng, R.G. Kellogg, J. Kunkle, A.C. Mignerey, F. Ricci-Tam, Y.H. Shin, A. Skuja, S.C. Tonwar y, , g, gg, , g y, , Y.H. Shin, A. Skuja, S.C. Tonwar Y.H. Shin, A. Skuja, S.C. Tonwar – 29 – Princeton University, Princeton, U.S.A. S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, S. Higginbotham, D. Lange, J. Luo, D. Marlow, K. Mei, I. Ojalvo, J. Olsen, C. Palmer, P. Pirou´e, D. Stickland, C. Tully University of Puerto Rico, Mayaguez, U.S.A. S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, S. Higginbotham, D. Lange, J. Luo, D. Marlow, K. Mei, I. Ojalvo, J. Olsen, C. Palmer, P. Pirou´e, D. Stickland, C. Tully University of Puerto Rico, Mayaguez, U.S.A. S. Malik, S. Norberg University of Puerto Rico, Mayaguez, U.S.A. S. Malik, S. Norberg – 30 – Purdue University, West Lafayette, U.S.A. A. Barker, V.E. Barnes, S. Das, S. Folgueras, L. Gutay, M.K. Jha, M. Jones, A.W. J A. Khatiwada, D.H. Miller, N. Neumeister, C.C. Peng, H. Qiu, J.F. Schulte, J. Sun, F. Wang, W. Xie Purdue University Northwest, Hammond, U.S.A. T. Cheng, N. Parashar, J. Stupak Rice University, Houston, U.S.A. Rice University, Houston, U.S.A. A. Adair, Z. Chen, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Guilbaud, M. Kilpatrick, W. Li, B. Michlin, M. Northup, B.P. Padley, J. Roberts, J. Rorie, W. Shi, Z. Tu, J. Zabel, A. Zhang JHEP01(2018)045 University of Rochester, Rochester, U.S.A. A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, T. Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A. Khukhunaishvili, K.H. Lo, P. Tan, M. Verzetti The Rockefeller University, New York, U.S.A. R. Ciesielski, K. Goulianos, C. Mesropian Rutgers, The State University of New Jersey, Piscataway, U.S.A. A. Agapitos, J.P. Chou, Y. Gershtein, T.A. G´omez Espinosa, E. Halkiadakis, M. Heindl, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath, R. Montalvo, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, D. Sheﬃeld, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker S. Thomas, P. Thomassen, M. Walker University of Tennessee, Knoxville, U.S.A. A.G. Delannoy, M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa University of Tennessee, Knoxville, U.S.A. A.G. Delannoy, M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas A&M University, College Station, U.S.A. O. Bouhali71, A. Castaneda Hernandez71, A. Celik, M. Dalchenko, M. De Mattia, A. Del- gado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, T. Kamon72, R. Mueller, Y. Pakhotin, R. Patel, A. Perloﬀ, L. Perni`e, D. Rathjens, A. Safonov, A. Tatarinov, K.A. Ulmer Texas Tech University, Lubbock, U.S.A. Texas Tech University, Lubbock, U.S.A. N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, J. Faulkner, E. Gurpinar, S. Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, T. Mengke, S. Muthumuni, T. Peltola, S. Undleeb, N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, J. Faulkner, E. Gurpinar, S. Kunori, N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, J. Faulkner, E. Gurpinar, S. Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, T. Mengke, S. Muthumuni, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang I. Volobouev, Z. Wang Vanderbilt University, Nashville, U.S.A. Vanderbilt University, Nashville, U.S.A. S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K. Padeken, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu y, , S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K. Padeken, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia, Charlottesville, U.S.A. M.W. Arenton, P. Barria, B. Cox, R. Hirosky, M. Joyce, A. Ledovskoy, H. Li, C. Neu, T. Sinthuprasith, Y. Wang, E. Wolfe, F. Xia Wayne State University, Detroit, U.S.A. Wayne State University, Detroit, U.S.A. R. Harr, P.E. Karchin, N. Poudyal, J. Sturdy, P. Thapa, S. Zaleski R. Harr, P.E. Karchin, N. Poudyal, J. Sturdy, P. Thapa, S. University of Rochester, Rochester, U.S.A. Zaleski – 31 – University of Wisconsin — Madison, Madison, WI, U.S.A. University of Wisconsin — Madison, Madison, WI, U.S.A. M. Brodski, J. Buchanan, C. Caillol, S. Dasu, L. Dodd, S. Duric, B. Gomber, M. Groth , , , , , , , , M. Herndon, A. Herv´e, U. Hussain, P. Klabbers, A. Lanaro, A. Levine, K. Long, R. Loveless, G. Polese, T. Ruggles, A. Savin, N. Smith, W.H. Smith, D. Taylor, N. Woods M. Herndon, A. Herv´e, U. Hussain, P. Klabbers, A. Lanaro, A. Levine, K. Long, †: Deceased 1: Also at Vienna University of Technology, Vienna, Austria 2: Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijin China JHEP01(2018)045 3: Also at IRFU, CEA, Universit´e Paris-Saclay, Gif-sur-Yvette, France 4: Also at Universidade Estadual de Campinas, Campinas, Brazil 5: Also at Universidade Federal de Pelotas, Pelotas, Brazil 6: Also at Universit´e Libre de Bruxelles, Bruxelles, Belgium 7: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 8: Also at Joint Institute for Nuclear Research, Dubna, Russia 9: Also at Helwan University, Cairo, Egypt 10: Now at Zewail City of Science and Technology, Zewail, Egypt 10: Now at Zewail City of Science and Technology, Zewail, Egypt Now at Fayoum University, El-Fayoum, Egypt 12: Also at British University in Egypt, Cairo, Egypt 13: Now at Ain Shams University, Cairo, Egypt 14: Also at Universit´e de Haute Alsace, Mulhouse, France 14: Also at Universit´e de Haute Alsace, Mulhouse, France 15: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia 16: Also at Tbilisi State University, Tbilisi, Georgia 17: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 18: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany Also at RWTH Aachen University, III. Physika 19: Also at University of Hamburg, Hamburg, Germany 20: Also at Brandenburg University of Technology, Cottbus, Germany 20: Also at Brandenburg University of Technology, Cottbus, Germany 21: Also at MTA-ELTE Lend¨ulet CMS Particle and Nuclear Physics Group, E¨otv¨os Lor´and University, Budapest, Hungary 21: Also at MTA-ELTE Lend¨ulet CMS Particle and Nuclear Physics Group, E¨otv¨os Lor´and 21: Also at MTA-ELTE Lend¨ulet CMS Particle and Nuclear Physics Group, E¨otv¨os Lor´an 21: Also at MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand University, Budapest, Hungary University, Budapest, Hungary 22: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 22: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 23: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary 23: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary 24: Also at Indian Institute of Technology Bhubaneswar, Bhub 25: Also at Institute of Physics, Bhubaneswar, India 26: Also at University of Visva-Bharati, Santiniketan, India 26: Also at University of Visva-Bharati, Santiniketan, India 27: Also at University of Ruhuna, Matara, Sri Lanka 27: Also at University of Ruhuna, Matara, Sri Lanka 28: Also at Isfahan University of Technology, Isfahan, Iran 28: Also at Isfahan University of Technology, Isfahan, Iran 29: Also at Yazd University, Yazd, Iran 30: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Aza University, Tehran, Iran 30: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran University, Tehran, Iran 31: Also at Universit`a degli Studi di Siena, Siena, Italy 31: Also at Universit`a degli Studi di Siena, Siena, Italy 32: Also at INFN Sezione di Milano-Bicocca; Universit`a di Milano-Bicocca, Milano, Italy 32: Also at INFN Sezione di Milano-Bicocca; Universit`a di Milano-Bicocca, Mila 33: Also at Purdue University, West Lafayette, U.S.A. 34: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 34: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 35: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 35: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 36: Also at Consejo Nacional de Ciencia y Tecnolog´ıa, Mexico city, Mexico 36: Also at Consejo Nacional de Ciencia y Tecnolog´ıa, Mexico city, Mexico 37: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland – 32 – 38: Also at Institute for Nuclear Research, Moscow, Russia 39: Now at National Research Nuclear University ’Moscow Engineering Physics Insti- tute’ (MEPhI), Moscow, Russia 40: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 41: Also at University of Florida, Gainesville, U.S.A. 42: Also at P.N. University, Tehran, Iran Lebedev Physical Institute, Moscow, Russia 43: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia 44: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 45: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia 46: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy JHEP01(2018)045 47: Also at National and Kapodistrian University of Athens, Athens, Greece 47: Also at National and Kapodistrian University of Athens, Athens, Greece 48: Also at Riga Technical University, Riga, Latvia 49: Also at Universit¨at Z¨urich, Zurich, Switzerland 50: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna, Austria 50: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna, Austria 51: Also at Gaziosmanpasa University, Tokat, Turkey 52: Also at Istanbul Aydin University, Istanbul, Turkey 53: Also at Mersin University, Mersin, Turkey 54: Also at Cag University, Mersin, Turkey 55: Also at Piri Reis University, Istanbul, Turkey 56: Also at Adiyaman University, Adiyaman, Turkey 57: Also at Izmir Institute of Technology, Izmir, Turkey 58: Also at Necmettin Erbakan University, Konya, Turkey 59: Also at Marmara University, Istanbul, Turkey 60: Also at Kafkas University, Kars, Turkey 61: Also at Istanbul Bilgi University, Istanbul 62: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 62: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 63: Also at School of Physics and Astronomy, University of Southampton, Southampton, United Kingdom 64: Also at Instituto de Astrof´ısica de Canarias, La Laguna, Spain 64: Also at Instituto de Astrof´ısica de Canarias, La Laguna, Spain 65: Also at Utah Valley University, Orem, U.S.A. 66: Also at Beykent University, Istanbul, Turkey 67: Also at Bingol University, Bingol, Turkey 68: Also at Erzincan University, Erzincan, Turkey 69: Also at Sinop University, Sinop, Turkey 70: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 70: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 71: Also at Texas A&M University at Qatar, Doha, Qatar 71: Also at Texas A&M University at Qatar, Doha, Qatar 72: Also at Kyungpook National University, Daegu, Korea 72: Also at Kyungpook National University, Daegu, Korea – 33 –
https://openalex.org/W3156238992	https://rua.ua.es/dspace/bitstream/10045/115067/1/Guardiola_etal_2021_Mathematics.pdf	English	null	Unitary Owen Points in Cooperative Lot-Sizing Models with Backlogging	Mathematics	2,021	cc-by	13,353	Keywords: unitary Owen points; cooperation; cost allocation; coalitional stability mathematics mathematics mathematics mathematics Article Unitary Owen Points in Cooperative Lot-Sizing Models with Backlogging Luis A. Guardiola 1,,† , Ana Meca 2,† and Justo Puerto 3,† Luis A. Guardiola 1,,† 1 Departamento de Fundamentos del Análisis Económico, Universidad de Alicante, 03690 Alicante, Spain 2 1 Departamento de Fundamentos del Análisis Económico, Universidad de Alicante, 03690 Alicante, Spain 2 I.U. Centro de Investigación Operativa, Universidad Miguel Hernández, Ediﬁcio Torretamarit, 2 I.U. Centro de Investigación Operativa, Universidad Miguel Hernández, Ediﬁcio Torretama Avda. de la Universidad s.n., 03202 Elche , Spain; ana.meca@umh.es Avda. de la Universidad s.n., 03202 Elche , Spain; ana.meca@umh.es 3 Facultad de Matemáticas, Universidad de Sevilla, 41012 Sevilla, Spain; puerto@us.es * Correspondence: luis.guardiola@ua.es † All the authors contributed equally to this work. Abstract: This paper analyzes cost sharing in uncapacitated lot-sizing models with backlogging and heterogeneous costs. It is assumed that several ﬁrms participate in a consortium aiming at satisfying their demand over the planning horizon with minimal operating cost. Each individual ﬁrm has its own ordering channel and holding technology, but cooperation with other ﬁrms consists in sharing that information. Therefore, the ﬁrms that cooperate can use the best ordering channels and holding technology among members of the consortium. This mode of cooperation is stable. in that allocations of the overall operating cost exist, so that no group of agents beneﬁt from leaving the consortium. Our contribution in the current paper is to present a new family of cost sharing allocations with good properties for enforcing cooperation: the unitary Owen points. Necessary and sufﬁcient conditions are provided for the unitary Owen points to belong to the core of the cooperative game. In addition, we provide empirical evidence, through simulation, showing that, in randomly-generated situations, the above condition is fulﬁlled in 99% of the cases. Additionally, a relationship between lot-sizing games and a certain family of production-inventory games, through Owen’s points of the latter, is described. This interesting relationship enables easily constructing a variety of coalitionally stable allocations for cooperative lot-sizing models. 1. Introduction Received: 25 February 2021 Accepted: 11 April 2021 Published: 15 April 2021 The economic lot-sizing problem (henceforth ELSP) is a production problem in op- erations management and inventory theory that has been studied by many researchers for more than 50 years. The ELSP is an extension of the economic order quantity model to the case where there are some goods to be produced over a planning horizon, so that the production lots must be decided, in order to meet certain demand over the given ﬁnite horizon. Demand is usually generated from forecasts or by customer orders, or often by a combination of both. This production planning model is a common point for most companies or industries: planning what, when, and how much to produce. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional afﬁl- iations. To deﬁne the feasible production plans, several parameters of the production system are usually taken into account: the resource capacity (with or without restrictions) and all of the inventory costs involved. The simpler production planning model is known as the single-item uncapacitated lot-sizing model. It corresponds to the production planning of a single item to meet some demand over a discretized planning horizon. Despite its simplicity, it already contains most of the modeling elements that are cited above, with the exception of the capacity constraints. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). There are also some other modeling elements that can be found in some situations. Those elements usually complicate the models and make them more difﬁcult to solve. For instance, a competitive model for the allocation of capacity from some shared resources. https://www.mdpi.com/journal/mathematics Mathematics 2021, 9, 869. https://doi.org/10.3390/math9080869 Mathematics 2021, 9, 869 2 of 19 In other cases, the products interact through multi-level product structures. Finally, there may be other elements that are needed to reﬁne the model. For instance, the production process may allow demand for ﬁnished products to be backlogged. In this case, it is possible to deliver to a customer later than required, but that delay is pennalized because it has a negative impact on customer satisfaction. 1. Introduction The latter is currently happening, for example, with the main producers of vaccines for COVID-19 (BioNTech, Moderna, Oxford), which do not have enough capacity to deliver all of the vaccines requested (Pﬁzer, Moderna, and Astrazeneca) to all countries on time. The reader is referred to the surveys by [1,2] for a complete and well-organized description of lot- sizing problems. Over the last 40 years, single-item uncapacitated lot-sizing problems have been stud- ied, trying out different formulations that have enabled more efﬁcient solutions to the problem to be found. Among them, Pochet and Wolsey [3] present a mixed integer pro- gramming reformulation of the uncapacitated lot-sizing problem with backlogging, which in an extended space of variables, give strong reformulations using linear programming. Nevertheless, most of the traditional research on lot-sizing-models focuses on tactical decision-making by single agents using optimization methods. This approach relies on the assumption that the outcome of a particular decision is independent of the decisions of other agents. However, as a result of global interaction, it has also reached supply chain management, an alternative perspective is becoming more common. Speciﬁcally, many recent research papers recognize the strategic interaction of multiple agents within supply chains. These agents are often independently owned and motivated companies. The fact that the outcomes from the agents’ decisions partly depend on the decisions of other independent agents makes game theory a natural approach to modeling those decisions. In practice, the agents may behave either cooperatively or noncooperatively, and the recent literature contains two comprehensive general reviews, by [4] for both cooperative and noncooperative planning and scheduling games, and by [5,6] for non cooperative lot- sizing games, with and without capacity restrictions, respectively. However, our focus is speciﬁcally on cooperative lot-sizing models with backlogging, but without capacity restrictions. Each ﬁrm faces demand for a single product in each period and coalitions can pool orders. Firms cooperate by using the best ordering channel and holding technology provided by the participants in the consortium, e.g., they produce, hold inventory, pay backlogged demand, and make orders at the minimum cost among the members of the coalition. Thus, ﬁrms aim at satisfying their demand over the planning horizon with minimal operating cost. In principle, sharing private information can be seem as a limitation of this model. However, the reader may notice that this can be easily overcome. 1. Introduction A possible answer may be to consider the Owen point that applies for PI-problems. The Owen point works very-well as long as there is a strong formulation for the underlying optimization problem, such as PI-problems, because the dual variables (shadow prices) are used to construct the core allocations. However, this does not work for SI-problems, since the corresponding optimization problem has integer variables, and strong duality does not apply in the original space of variables. In this paper, we further extend the idea of dual prices and construct an “ad hoc” price type as the sum of the production, inventory and backlogging costs plus a proportion of the ﬁxed order cost, which depends on the total demand satisﬁed in that period. They are called unitary prices. These unit prices enable replicating the construction of the Owen point by multiplying such unit prices by the demands and adding in all of the periods. These allocations “a la Owen” are called unitary Owen points. Unfortunately, one cannot always guarantee that unitary Owen points are core allocations. Nevertheless, we provide necessary and sufﬁcient conditions for this situation to hold, i.e., for unitary Owen points to be core allocations and also show, by simulation empirical evidence, that this condition is satisﬁed in most cases. Furthermore, we consider whether it is possible to relate general SI-situations to simpler situations, where the core is well-known and characterized as in PI-games. In this regard, we prove that the answer to this question is yes: one can use the Owen point of the surplus game, a PI-game that measures the excess in costs that occurs with respect to the minimum unit price. p p As compared with the existing literature on lot-sizing games, the contributions of this paper can be summarized, as follows. First of all, when compared with previous papers on the topic, our model extends the results in [7,8] to deal with backlogging and heterogeneous costs, whereas the models in those papers only consider homogeneous costs, and backlogging is not allowed. In addition, we also extend the models in [9,10], since those models do not allow set-up costs, whereas our new model does. Moreover, with respect to the cost sharing literature of production-inventory models, this paper introduces a new family of cost sharing allocations: the unitary Owen points. This family is an extension of the Owen set that enjoys very-good properties in production-inventory problems. 1. Introduction To prevent disclosing private information, one can assume that companies communicate through a mediator who helps them to make their optimal decisions without having to share their private information. The mediator implements the cooperation mechanism without disclosing information, reaching a win–win situation for all entities involved and giving rise to acceptable costs allocations. p To illustrate this form of cooperation today, let us consider four automotive companies, Peugeot (P), Citroen (C), Fiat (F), and Iveco (I). They all use the same chassis for their cars and buy it from a Chinese supplier twice a year (two periods). Peugeot is interested in buying a larger quantity of chassis to avoid supply problems from China and a possible increase in transportation costs. In addition, P is able to negotiate with the Chinese supplier and obtain very competitive unit and period purchasing costs for large-scale order sizes. P then proposes to the other companies to place a joint order for chassis. Citroen thinks that this is a good idea, because it has a large warehouse in Vigo where the entire order can always be stored. Iveco proposes to take advantage of its good contacts with transport companies and to ﬂeet a ship to transport the joint orders from China to Vigo. The ﬁxed order and transport costs are included in the set-up costs. Fiat analyzes the proposal and, although it does not have a long delay per period in the delivery of its cars, and its penalty costs are the lowest, it concludes that it turns out proﬁtable. The four companies then Mathematics 2021, 9, 869 3 of 19 3 of 19 reach an agreement and taking the unit purchasing costs of P, the holding costs of C, the set-up costs of I and the backlogging costs of F, they place a joint order with the lowest total cost c(N). We should note that the cooperation of the four companies generates a reduction in the backlogging costs of P, C, and I (to those of F), because they can now reduce delivery times to their customers and leave fewer cars undelivered. We wonder whether there are any kind of unitary prices for the demands, related to inventory costs, which enable coalitional stable allocations of the overall operating costs to be built among the automotive companies, so that no group of ﬁrms proﬁts from leaving the consortium. 2. Literature Review Several papers have tackled problems that are associated with lot-sizing models and the interested reader is referred to [1] for an excellent survey. However, in addition to the references that can be found therein, some interesting recent papers deserve to be cited, since they consider aspects of coordination and cooperation that are directly related with our model. Related with the concept of coordination, Gharaei et al. [11] develop an integrated lot-sizing policy in a multi-level multi-product supply chain under stochastic conditions with limitations. They use generalised Benders decomposition to obtain a satisfactory performance in optimal solution, the number of iterations, dual infeasibility, constraint violation, and complementarity. In addition, Zissis, Ioannou, and Burnetas [12] study the important aspect of coordination in lot-sizing models. They develop a model for coordinating lot-sizing decisions under bilateral information asymmetry while using a mediator. This mediator makes coordination achievable, without enforcing centralized policies. Therefore, individual objectives can be aligned with channel objectives, reducing costs and eliminating inefﬁciencies. g Concerning the analysis of cooperation in lot-sizing models, several papers have con- sidered the cost sharing aspects of these models. Speciﬁcally, Van den Heuvel, Borm, and Hammers [8] focus on the cooperation in economic lot-sizing situations with homogeneous costs, but without backlogging (henceforth, ELS-games). Subsequently, Guadiola, Meca, and Puerto [9,10] present the class of production-inventory games (henceforth, PI-games). PI-games study the cooperation among heterogeneous companies coming from production- inventory situations with discrete demand and backlogging, but without set-up costs. PI-games may be considered to be ELS games without set-up costs, but with backlogging and heterogeneous costs. They prove that the Owen set, i.e., the set of cost allocations that are achievable through shadow prices (the dual solutions to the primal linear optimization problem) (see [13]), is reduced to a unique cost allocation in the class of PI-games. These authors coined the term Owen point to refer to them and prove that the Owen point is always a coalitional stable and consistent cost allocation, in the sense that there is no group of ﬁrms that can improve upon or block this point by reducing the aggregated cost for the group (recall that the core of a cooperative cost game consists of all coalitional stable cost allocations, usually called core allocations). 1. Introduction We also contribute by providing the necessary and sufﬁcient conditions for unitary Owen points to be core allocations. Furthermore, we empirically show that these conditions are satisﬁed for almost any SI-situation, which results in an explicit quasi-solution for this class of games. Finally, this paper also proves a new result that establishes a relationship between lot-sizing games and a certain family of PI-games, through the Owen’s points of the latter. This relationship enables us to analyze cooperative lot-sizing models using properties of the much simpler and well-known class of PI-games. The rest of this paper is organized, as follows: the next section reviews the literature of lot-sizing models. Section 3 formulates SI-problems and it shows that SI-games are totally balanced, resorting to a result of [3]. Section 4 describes the unitary Owen points, provides a necessary and sufﬁcient condition for those points to be core allocations, and gives empirical evidence to consider the unitary Owen point as a quasi-solution for SI- games. Section 5 presents a relationship between SI-games and a certain family of PI-games through the Owen’s points of the latter. This interesting relationship simpliﬁes the analysis and construction of core allocations for SI-games. Finally, Section 6 presents a research summary and some conclusions. Mathematics 2021, 9, 869 4 of 19 2. Literature Review More recently, Chen and Zhang [7] consider the ELS-game with general concave ordering costs and they found out that a core allocation can be computed in polynomial time when all retailers have the same cost parameters (again homogeneous costs). Their approach is based on linear programming (LP) duality. Speciﬁcally, they prove that there is an optimal dual solution that deﬁnes an allocation in the core and point out that it is not necessarily true that every core allocation can be obtained by means of dual solutions. y On the other hand, Dreschel [14] focuses on cooperative lot-sizing games in supply chains. That paper considers several models of cooperation in lot-sizing problems of different complexity that are analyzed regarding theoretical properties, like monotonicity or concavity, and solved with a row generation algorithm to ﬁnd stable cost allocations. Zeng, Li, and Cai [15] study the ELS-game with perishable inventory. They consider a single supplier and several retailers that collaborate to place joint orders of known and perishable demand in a determinate number of periods. They demonstrate that the associate ELS- game is subadditive and totally balanced. Moreover, they present a core-solution that allocates, in an equal form, the unit cost to each period. q p In another paper, Gopaladesikan and Uhan [16] consider cooperative cost-sharing games that arise from ELS-problems with remanufacturing options. While studying the relative strength and integrality gaps of several mathematical optimization formulations of this problem, they show that the core associated to the cost-sharing game is, in general, empty. However, they show that, for two speciﬁc cases: large initial quantity of low cost returns and zero setup costs, the cost sharing game has a non-empty core. Finally, they demonstrate that a cost allocation in the core can be computed in polynomial time. Xu and Yang [17] present a competitive cost-sharing method with approximate cost recovering and Mathematics 2021, 9, 869 5 of 19 cross-monotonic for an ELS-game under a weak triangle inequality assumption. They show the effectiveness of the proposed method with numerical results. In addition, Tsao, Chan, and Wu [18] investigate the combined effects of an imperfect production process, learning effect, and lot-sizing integration on a manufacturer-retailer channel for the Nash game and the cooperation game in an imperfect production system. 2. Literature Review They also solved the problem by a search procedure, and studied the relationship between downstream entities of the supply chain and the upstream to obtain structural and quantitative results. By numerical experiments, they reach the conclusion that the cooperative policy enables further cost reduction under a wide range of parameter settings. We conclude this literature review, recalling that the class of set-up-inventory games (henceforth, SI-games), considered in this paper, is introduced in [19] as a new class of combinatorial optimization games that arise from cooperation in lot-sizing problems with backlogging and heterogeneous costs. That paper proves that the game is balanced, proposes an “ad hoc” parametric family of cost allocations, and provides sufﬁcient conditions for this family to be stable against the coalitional defection of ﬁrms. 3. SI-Games: Reformulation and Balancedness . , T}, zt ∈{0, 1}, ∀t ∈{1, . . . , T}. The above objective function minimizes the sum of all the considered costs over the planning horizon. The ﬁrst constraint imposes that the model must start and ﬁnish with an empty inventory. The second group of constraints are ﬂow conservation constraints that ensure the correct transition of inventory and backlogged demand among periods. The third group of constraints model that set-up cost is only charged whenever an order is placed. Zangwill [21] proved that there is an optimal solution to C(d, k, h, b, p), such that, for each t = 1, . . . , T, Et > 0 and It > 0, simultaneously; that is, there is always an optimal solution that fulﬁlls the constraints in the formulation of the problem. Therefore, that formulation provides optimal plans to the problem. Actually, this property and formulations were already proposed by [3]. Obviously, it does not mean that other optimal plans dividing the production may not exist, but restriction to these plans is sufﬁcient for achieving an optimal solution. g p In order to simplify the notation, we deﬁne Z as a matrix in which all costs are included, which is, Z := (K, H, B, P) being K, H, B and P the matrices containing the set-up, inventory carrying, backlogging and unit production costs for all periods t = 1, . . . , T. A cooperative cost TU-game is an ordered pair (N, c), where N is a ﬁnite set, the set of players, and the characteristic function c is a function from P(N) to R with c(∅) = 0, where P(N) is the power set of N (i.e., the set of coalitions in N). We use x(S) to denote ∑i∈S xi with x(∅) = 0 for any cost allocation x ∈Rn and for every coalition S ⊆N. 3. SI-Games: Reformulation and Balancedness We begin by formulating the set-up-inventory problems with backlogging (SI-problems). Consider T periods, numbered from 1 to T, where the demand for a single product occurs in each of them. This demand is satisﬁed by own production, and it can be done during the production periods, in previous periods (inventory), or later periods (back- logging). A ﬁxed cost must be paid in each production period. Therefore, the model includes production, inventory holding, backlogging, and set-up costs. The aim is to ﬁnd an optimal ordering plan, which is, a feasible ordering plan that minimizes the sum of set-up, production, inventory holding and backlogging costs. Although the model assumes that companies produce their demand, we can interchangeably consider the case where demand is satisﬁed either by producing or purchasing. One has simply to interpret that the purchasing costs can be ordering costs (set-up costs) and unit purchasing costs (variable costs). The goal is to establish an operational plan in order to satisfy demand at a minimum total cost. The notation of the parameters and decision variables of the model are described in Table 1. Table 1. Notation table. T number of periods in the planning horizon dt demand during period t pt unit production costs in period t ht unit inventory carrying costs in period t bt unit backlogging carrying costs in period t kt set-up cost in period t M = ∑T t=1 dt upper bound on the production Decision variables qt production during period t It inventory at the end of the period t Et backlogged demand at the end of period t zt a binary variable that assumes value 1 if an order is placed at the beginning of period t and 0, otherwise In the following, we recall the mathematical programming formulation for the set-up- inventory problem (SI-problem). The reader is referred to [3,20] for a detailed discussion of this model. We denote, by C(d, k, h, b, p), the minimum overall operating cost during the planning horizon, then Mathematics 2021, 9, 869 6 of 19 C(d, k, h, b, p) := min T ∑ t=1 (ptqt + htIt + btEt + ktzt) s.t. I0 = IT = E0 = ET = 0, It −Et = It−1 −Et−1 + qt −dt, ∀t ∈{1, . . . , T}, qt ≤M · zt, ∀t ∈{1, . . . , T}, qt, It, Et, non-negative, integer, ∀t ∈{1, . . 3. SI-Games: Reformulation and Balancedness ∑i∈S i ( ) y y For each SI-situation represented by its cost matrices (N, D, Z), we associate a cost TU-game (N, c), where, for any nonempty coalition S ⊆N, c(S) := C(dS, kS, hS, bS, pS) with dS = ∑i∈S di, where di = di 1, ..., di T , and the rest of the costs will be the minimum value among all the costs of the players in the coalition S at each one of the periods, serve as an example pS = [pS 1, . . . , pS T]′, where pS t = mini∈S{pi t} for t = 1, . . . , T. Subsequently, for each S ⊆N : c(S) := min T ∑ t=1 pS t qt + hS t It + bS t Et + kS t zt s.t. I0 = IT = E0 = ET = 0, It −Et = It−1 −Et−1 + qt −dS t , ∀t ∈{1, . . . , T}, qt ≤M · zt, ∀t ∈{1, . . . , T}, qt, It, Et, non-negative, integer, ∀t ∈{1, . . . , T}, zt ∈{0, 1}, ∀t ∈{1, . . . , T}. Every cost TU-game that is deﬁned in this way is what we call a set-up-inventory game (SI-game). The reader may notice that every PI-game (as introduced by [9]) is a SI-game with kt = 0, for all t ∈T. Moreover, as mentioned above, although the model assumes that companies produce their demand, we can interchangeably consider the case where demand is satisﬁed by either producing or purchasing. One has simply to interpret that the purchasing costs can be ordering costs (set-up costs) and unit purchasing costs (variable costs). Recall that the core of a game (N, c) consists of those cost allocations that Mathematics 2021, 9, 869 7 of 19 divide the cost of the grand coalition, c(N), in a efﬁcient way, so that no coalition has an incentive to break the consortium because its costs increase. Formally, divide the cost of the grand coalition, c(N), in a efﬁcient way, so that no coalition has an incentive to break the consortium because its costs increase. Formally, Core(N, c) = x ∈Rn x(N) = c(N) and x(S) ≤c(S) for all S ⊂N . 3. SI-Games: Reformulation and Balancedness In the following, as is common in cooperative game theory, we call stable allocations the elements of the core. Bondareva [22] and Shapley [23] independently provide a general characterization of games with a nonempty core by means of balancedness. They prove that (N, c) has a nonempty core if and only if it is balanced. In addition, it is a totally balanced game (totally balanced games were introduced by Shapley and Shubik in the study of market games (see [24])) if the core of every subgame is nonempty. Our goal is to show that SI-games are totally balanced. To do so, we use an easy proof that is based on duality resorting to a result by [3]. Observe that the characteristic function c(S) of these games can be written as the optimal value of the following LSI(S) problem: c(S) = max ∑ 1≤t≤T ∑ 1≤τ≤T dS τ pS tτλtτ + ∑ 1≤t≤T kS t zt (LSI(S)) s.t. dS τ ∑ 1≤t≤T λtτ = dS τ, ∀τ ∈{1, . . . , T}, λtτ ≤zt, ∀t, τ ∈{1, . . . , T}, λtτ, zt ∈{0, 1}, ∀t, τ ∈{1, . . . , T}. (LSI(S)) The variables λtτ are equal to 1, if and only if demand in period τ is produced in period t and zero otherwise. Likewise, the variables zt are equal to 1 if and only if there is some production at period t. The cost of covering the demand in period τ if the production is done in period t is given by pS tτ =    pS t if t = τ, pS t + ∑τ−1 i=t hS i if t < τ, pS t + ∑t−1 i=τ bS i if t > τ. (1) (1) This is the facility location reformulation by [3] of the SI problem. This formulation has a strong dual if the underlying graph of the location problem is a tree ([25]). In this case, the graph is a line and, thus, the mentioned result applies. Let yτ be the dual variable that is associated with the ﬁrst constraints and βtτ those that are associated with the second family of constraints, then the dual is: c(S) = max ∑ 1≤τ≤T dS τyτ (DSI(S)) s.t. ∑ 1≤τ≤T βtτ ≤kS t , ∀t ∈{1, . . . , T}, dS τyτ −βtτ ≤dS τ pS tτ, ∀t, τ ∈{1, . . Theorem 1. Every SI-game is totally balanced. 4. Unitary Owen Points In this section, we introduce a new family of cost allocations on the class of SI-games. This family is inspired by the ﬂavour of the Owen point and its relationship with the shadow prices of the dual problems that are associated with SI-problems. To deﬁne those cost allocations, it is necessary to describe the set of optimal plans and the unitary prices. y p p y p Consider a SI-situation (N, D, Z). A feasible ordering plan for such a situation is deﬁned by σ ∈RT, where σt ∈T ∪{0} denotes the period where the demand of period t is ordered. We assume the convention that σt = 0 if and only if dt = 0. It means that no order can be placed to satisfy demand at period t, since demand is null there. Moreover, PS(σ) ∈RT is deﬁned as the operating cost vector that is associated to the ordering plan σ (henceforth: cost-plan vector) for any coalition S ⊆N, where PS t (σ) = 0 if σt = 0, pS σtt if σt ∈{1, ..., T}. Given an optimal ordering plan, σS, for the SI-problem C(dS, kS, hS, bS, pS), the char- acteristic function is rewritten, as follows: for any non-empty coalition S ⊆N, Given an optimal ordering plan, σS, for the SI-problem C(dS, kS, hS, bS, pS), the char- acteristic function is rewritten, as follows: for any non-empty coalition S ⊆N, c(S) = PS(σS)′dS + δ(σS)′kS = T ∑ t=1 PS t (σS)dS t + δt(σS)kS t , where, δ(σS) = δt(σS) t∈T and where, δ(σS) = δt(σS) t∈T and δt(σS) = 1 if ∃r ∈T/σS r = t , 0 otherwise. The set of optimal plans is denoted by Λ(N, D, Z) := nσS S∈P(N) o where σS is an optimal ordering plan that is associated to LSI(S). Note that the set of optimal plans may be large, since there are often multiple optimal solutions for the program LSI(S). Core allocations that are built from optimal dual variables are known to exhibit some questionable properties, as pointed out, for instance, by [26] or [27]. For this reason, whenever the core is larger than the set of allocations coming from dual variables, it is interesting to provide some alternative core allocations. In the following, we derive alternatives that, under mild conditions, are stable, i.e., core allocations for these situations. 3. SI-Games: Reformulation and Balancedness . , T}, βtτ ≥0, ∀t, τ ∈{1, . . . , T}, yt free, ∀t ∈{1, . . . , T}. (DSI(S)) Reference [3] proved that the linear relaxation of a SI-problem, LSI(S), has an integral optimal solution. Hence, the optimal value of its dual problem matches that of the primal one, which is, v(DSI(S)) = C(dS, kS, hS, bS, pS) = c(S) for all S ⊆N. Theorem 1. Every SI-game is totally balanced. Mathematics 2021, 9, 869 8 of 19 Proof. Take a SI-situation (N, D, Z) and the associated SI-game (N, c). Consider (y∗, β∗) to be an optimal solution to dual DSI(N), where y∗= (y∗ 1, ..., y∗ T) and β∗= (β∗ 11, ..., β∗ TT). It is known from optimality that T ∑ t=1 y∗ t dN t = v(DSI(N)) = c(N) Note that the solution (y∗, β∗) is also feasible for any dual problem with S ⊆N, since pN ≤pS, hN ≤hS, bN t ≤bS t and kN t ≤kS t . Therefore, T ∑ t=1 y∗ t dS t ≤v(DSI(S)) = c(S) Thus, the allocation (∑T t=1 y∗ t di t)i∈N ∈Core(N, c). Thus, the allocation (∑T t=1 y∗ t di t)i∈N ∈Core(N, c). Note that every subgame of a SI-game is also a SI-game. Hence, we can also conclude that every SI-game is totally balanced. 4. Unitary Owen Points We deﬁne the unitary prices as the sum of the production, inventory, and backlogging costs plus a proportion of the ﬁxed order cost which depends on the total demand satisﬁed in each period. Mathematics 2021, 9, 869 9 of 19 9 of 19 Deﬁnition 1. Let (N, D, Z) be a SI-situation and σS S∈P(N) ∈Λ(N, D, Z). For each period t ∈T and each coalition S ⊆N, the unitary price is deﬁned, as follows: yt σS, dS, zS :=      0 if σS t = 0, PS t (σS) + kS σS t ∑m∈QS(σS t ) dSm if σS t ̸= 0, where QS(t) := k ∈T : σS k = t and zS represent the cost matrix (kS, hS, bS, pS). The reader should observe that QS(t) is the set of periods that satisfy the demand in period t, for the optimal plan σS. Note that, for any coalition S ⊆N, ∑T t=1 yt σS, dS, zS · dS t = c(S). t ( ) The next proposition shows that we may construct core allocations from the unitary prices of the grand coalition, as long as they are the cheapest in each period with positive demand. We shall call them unitary Owen points. Deﬁnition 2. Let (N, D, Z) be a SI-situation and σS S∈P(N) ∈Λ(N, D, Z). The unitary Owen point is given by ! θ σN, dN, zN := T ∑ t=1 yt σN, dN, zN · di t ! i∈N . Note that every optimal plan generates a unit price for each period of time and, hence a unitary Owen point. y p Observe that, from y(σN, dN, zN), we can build a solution (y(σN, dN, zN), β(σN)) with kN Observe that, from y(σ , d , z ), we can build a solution (y(σ , d , z ), β(σ )) with βσN(τ),τ = 0 if σN(τ) = 0 and βσN(τ),τ = kN σN(τ) ∑m∈QN(σN(τ)) dN m if σN(τ) ̸= 0 satisfying c(N) = ∑T τ=1 dN τ yt(σN, dN, zN). However, it may not be a feasible solution of the dual for the grand coalition whenever PN τ (σN(τ)) > pN tτ for some t. Still, the unitary Owen point that is associated with this dual solution can be a core allocation. Example 1. Consider the following SI-situation with two periods and three players and the associ- ated SI-game, as shown in Table 2: Example 1. Consider the following SI-situation with two periods and three players and the associ- ated SI-game, as shown in Table 2: Table 2. SI-situation with two periods and three players and the associated SI-game. Table 2. SI-situation with two periods and three players and the associated SI-game. dS 1 dS 2 pS 1 pS 2 hS 1 bS 1 kS 1 kS 2 c {1} 2 1 9 9 6 4 6 8 39 {2} 8 2 9 6 9 7 7 9 100 {3} 6 1 5 6 3 5 6 10 44 {1, 2} 10 3 9 6 6 4 6 8 122 {1, 3} 8 2 5 6 3 4 6 8 62 {2, 3} 14 3 5 6 3 5 6 9 100 {1, 2, 3} 16 4 5 6 3 4 6 8 118 The optimal plan for coalition N is σN = (1, 1) with pN(σN) = (5, 8) and y σN, dN, zN = 5 + 3 10, 8 + 3 10 . The unitary Owen point θ σN, dN, zN = 18 + 9 10, 59, 40 + 1 10 ∈Core(N, c). Note that (y(σN, dN, zN), β(σN)) with β21(σN) = 3 10, β22(σN) = 3 10 and βtτ(σN) = 0 for all the remaining t and τ, is not feasible for the dual problem DSI(N). Indeed, it violates the constraint dN 2 y2(σN, dN, zN) −β22(σN) ≤dN 2 pN 22, since this is equivalent to 32 + 9 10 ≤24. Table 2. SI-situation with two periods and three players and the associated SI-game. dS 1 dS 2 pS 1 pS 2 hS 1 bS 1 kS 1 kS 2 c {1} 2 1 9 9 6 4 6 8 39 {2} 8 2 9 6 9 7 7 9 100 {3} 6 1 5 6 3 5 6 10 44 {1, 2} 10 3 9 6 6 4 6 8 122 {1, 3} 8 2 5 6 3 4 6 8 62 {2, 3} 14 3 5 6 3 5 6 9 100 {1, 2, 3} 16 4 5 6 3 4 6 8 118 The optimal plan for coalition N is σN = (1, 1) with pN(σN) = (5, 8) and y σN, dN, zN = 5 + 3 10, 8 + 3 10 . ∈Core(N, c). 4. Unitary Owen Points βσN(τ),τ = 0 if σN(τ) = 0 and βσN(τ),τ = kN σN(τ) ∑m∈QN(σN(τ)) dN m if σN(τ) ̸= 0 satisfying c(N) = ∑T τ=1 dN τ yt(σN, dN, zN). However, it may not be a feasible solution of the dual for the grand coalition whenever PN τ (σN(τ)) > pN tτ for some t. Still, the unitary Owen point that is associated with this dual solution can be a core allocation. βσN(τ),τ = 0 if σN(τ) = 0 and βσN(τ),τ = kσN(τ) ∑m∈QN(σN(τ)) dN m if σN(τ) ̸= 0 satisfying c(N) = ∑T τ=1 dN τ yt(σN, dN, zN). However, it may not be a feasible solution of the dual for the grand coalition whenever PN τ (σN(τ)) > pN tτ for some t. Still, the unitary Owen point that is associated with this dual solution can be a core allocation. The following example elaborates on a SI-situation with three players and two peri- ods. The unitary Owen point for the corresponding SI-game is a core allocation, but this allocation does not come from optimal dual prices. Example 1. Consider the following SI-situation with two periods and three players and the associ- ated SI-game, as shown in Table 2: Example 1. Consider the following SI-situation with two periods and three players and the associ- ated SI-game, as shown in Table 2: The unitary Owen point θ σN, dN, zN = 18 + 9 10, 59, 40 + 1 10 ∈Core(N, c). Note that (y(σN, dN, zN), β(σN)) with β21(σN) = 3 10, β22(σN) = 3 10 and βtτ(σN) = 0 for all the remaining t and τ, is not feasible for the dual problem DSI(N). Indeed, it violates the constraint dN 2 y2(σN, dN, zN) −β22(σN) ≤dN 2 pN 22, since this is equivalent to 32 + 9 10 ≤24. Mathematics 2021, 9, 869 10 of 19 10 of 19 Therefore, it is clear that the unitary Owen point can provide core allocation, which does not come from optimal dual prices, although it is not clear under which conditions this unitary price fulﬁlls this property. The following result provides an easy sufﬁcient condition for this to happen. Proposition 1. Let (N, D, Z) be a SI-situation, σS S∈P(N) ∈Λ(N, D, Z), and (N, c) the associated SI-game. If yt σN, dN, zN ≤yt σS, dS, zS for all t ∈T and for all S ⊂N with dS t ̸= 0, then θ σN, dN, zN ∈Core(N, c). Proof. It is straightforward from the deﬁnition of the unitary Owen point. It would be reasonable that, the larger a coalition, the lower its unit prices, since its members operate with the best technology available in the group. Unfortunately, this condition is not always satisﬁed as Example 3 shows. Therefore, we are interested in ﬁnding stronger conditions than the one that is given in Proposition 1. This question is addressed below. In order to simplify the notation, for each t ∈T, we deﬁne: • Cost difference per demand unit between coalition S and R in a period t: aSR t := PS t (σS) −PR t (σR). aSR t := PS t (σS) −PR t (σR). Note that aSR t + aRS t = 0. Note that aSR t + aRS t = 0. t t • Aggregate demand of coalition S ⊆N in all of those periods that satisfy its demand in period t: ∑ S t t • Aggregate demand of coalition S ⊆N in all of those periods that satisfy its demand in period t: t t • Aggregate demand of coalition S ⊆N in all of those periods that satisfy its demand in period t: αt(S) := ∑ m∈QN(t) dS m. • Aggregate order cost of coalition S ⊆N : k(S) := ∑ t∈TS kS t , where TS := t ∈T δt(σS) = 1 is the set of ordering periods. where TS := t ∈T δt(σS) = 1 is the set of ordering periods. where TS := t ∈T δt(σS) = 1 is the set of ordering periods. The next theorem provides the necessary and sufﬁcient conditions for the unitary Owen point to be a core allocation. These conditions state an upper bound for the average cost savings per unit demand in the grand coalition, for those periods where an order is placed. Such an upper bound is related to the savings in ﬁxed order costs. Theorem 2. Let (N, D, Z) be a SI-situation, σS S∈P(N) ∈Λ(N, D, Z), and (N, c) the associ- ated SI-game. θ σN, dN, zN ∈Core(N, c) if and only if there are real weights βS t , for any S ⊊N and any t ∈TN with αt(S) > 0, satisfying that ∑ j∈QN(t) aNS j · dS j αt(S) ≤βS t · k(S) αt(S) − kN t αt(N) with ∑t∈TN:αt(S)>0 βS t ≤1. Proof. (if) Take σS S∈P(N) ∈Λ(N, D, Z) and consider a coalition S ⊊N. Proof. It is straightforward from the deﬁnition of the unitary Owen point. We must prove that θ σN, dN, zN ∈Core(N, c), e.g., ∑i∈S θi σN, dN, zN −c(S) ≤0. Indeed, Proof. (if) Take σS S∈P(N) ∈Λ(N, D, Z) and consider a coalition S ⊊N. We must prove that θ σN, dN, zN ∈Core(N, c), e.g., ∑i∈S θi σN, dN, zN −c(S) ≤0. Indeed, ∑ i∈S θi σN, dN, zN −c(S) ∑ i∈S θi σN, dN, zN −c(S) 11 of 19 Mathematics 2021, 9, 869 = T ∑ t=1 yt σN, dN, zN · dS t − T ∑ t=1 yt σS, dS, zS · dS t = T ∑ t=1  aNS t · dS t + kN σN t · dS j ∑m∈QN(σN t ) dN m − kS σS t · dS j ∑m∈QS(σS t ) dSm   = ∑ t∈TN  ∑ j∈QN(t) aNS j · dS j + kN t · dS j αt(N) ! −k(S) = ∑ t∈TN:αt(S)>0  αt(S) · ∑ j∈QN(t) aNS j · dS j αt(S) ! + kN t · αt(S) αt(N)  −k(S) ≤ ∑ t∈TN:αt(S)>0 βS t · αt(S) · k(S) αt(S) −αt(S) · kN t αt(N) + kN t · αt(S) αt(N) −k(S) = k(S) · ∑ t∈TN:αt(S)>0 βS t −k(S) ≤0 (only if) Consider now that θ σN, dN, zN ∈ Core(N, c). Then, for all S ⊂N, ∑i∈S θi σN, dN, zN −c(S) ≤0 which is equivalent to ∑ t∈TN  ∑ j∈QN(t) aNS j · dS j + kN t · dS j αt(N) ! ≤k(S). For all t ∈TN and every coalition S ⊊N with αt(S) > 0, there are always real weights βS t with ∑t∈TN βS t ≤1, satisfying ∑ j∈QN(t) aNS j · dS j + kN t · dS j αt(N) ! ≤βS t · k(S), ∑ j∈QN(t) aNS j · dS j αt(S) ! + kN t · αt(S) αt(N) · αt(S) ≤βS t · k(S) αt(S) , ∑ j∈QN(t) aNS j · dS j αt(S) ≤βS t · k(S) αt(S) − kN t αt(N). Example 3. Now, consider the following SI-situation with three periods, two players, and the associated 2-player SI-game, given by Table 7: The next example illustrates Proposition 1 and Theorem 2. It shows how unitary Owen points are calculated by using unitary prices. Example 2. Consider the following SI-situation with three periods and three players with the associated SI-game, as shown in Table 3: Table 3. SI-situation with three periods and three players with the associated SI-game. dS 1 dS 2 dS 3 pS 1 pS 2 pS 3 hS 1 hS 2 bS 1 bS 2 kS 1 kS 2 kS 3 c {1} 1 3 1 1 1 1 1 1 1 1 3 1 5 8 {2} 2 1 1 2 3 4 1 1 1 1 1 4 8 12 {3} 2 1 3 2 3 5 1 1 1 1 1 1 7 20 {1, 2} 3 4 2 1 1 1 1 1 1 1 1 1 5 13 {1, 3} 3 4 4 1 1 1 1 1 1 1 1 1 5 17 {2, 3} 4 2 4 2 3 4 1 1 1 1 1 1 7 31 {1, 2, 3} 5 5 5 1 1 1 1 1 1 1 1 1 5 22 Table 3. SI-situation with three periods and three players with the associated SI-game. Mathematics 2021, 9, 869 12 of 19 An optimal plan is given by Table 4: Table 4. An optimal plan for the SI-situation. Table 4. An optimal plan for the SI-situation. σS 1 σS 2 σS 3 PS 1 (σS) PS 2 (σS) PS 3 (σS) k(S) {1} 2 2 2 2 1 2 1 {2} 1 1 1 2 3 4 1 {3} 1 1 1 2 3 4 1 {1, 2} 1 2 2 1 1 2 2 {1, 3} 1 2 2 1 1 2 2 {2, 3} 1 1 1 2 3 4 1 {1, 2, 3} 1 2 2 1 1 2 2 Thus, the unitary prices for the optimal plan above are described in Table 5: Thus, the unitary prices for the optimal plan above are described in Table 5: Thus, the unitary prices for the optimal plan above are described in Table 5: Table 5. The unitary prices associated to the optimal plan above. Table 5. The unitary prices associated to the optimal plan above. Table 5. The unitary prices associated to the optimal plan above. y1 σS, dS, zS y2 σS, dS, zS y3 σS, dS, zS {1} 2 + 1 5 1 + 1 5 2 + 1 5 {2} 2 + 1 4 3 + 1 4 4 + 1 4 {3} 2 + 1 6 3 + 1 6 4 + 1 6 {1, 2} 1 + 1 3 1 + 1 6 2 + 1 6 {1, 3} 1 + 1 3 1 + 1 8 2 + 1 8 {2, 3} 2 + 1 10 3 + 1 10 4 + 1 10 {1, 2, 3} 1 + 1 5 1 + 1 10 2 + 1 10 One can observe that yt σN, dN, zN ≤yt σS, dS, zS for all t ∈T and, so, by Proposition 1, θ σN, dN, zN = (6.6, 5.6, 9.8) ∈Core(N, c). ( ) On the other hand, the ordering plan for the grand coalition eσN = (1, 2, 3) belongs to an optimal plan and the associated unit prices are y1 eσN, dN, zN = 1 + 1 5, y2 eσN, dN, zN = 1 + 1 5 and y3 eσN, dN, zN = 1 + 5 5. Note that for this plan TN = {1, 2, 3}. Theorem 2 is applied here for the weights that are given in Table 6. The unitary prices for the optimal plan above are described in Table 9: The unitary prices for the optimal plan above are described in Table 9: Table 9. The unitary prices associated to the optimal plan above. Table 9. The unitary prices associated to the optimal plan above. Table 9. The unitary prices associated to the optimal plan above. y1 σS, dS y2 σS, dS y3 σS, dS {1} 0 2 + 1 10 1 + 15 10 {2} 0 2 + 1 35 0 {1, 2} 0 1 + 50 55 2 + 50 55 Note that θ σN, dN, zN = 30 + 200 11 , 35 + 350 11 = (48′ b18, 66′ b81) is not a core allocation. Theorem 2 fails here, because TN = {2} and β{1} 2 ≥5 4. Note that θ σN, dN, zN = 30 + 200 11 , 35 + 350 11 = (48′ b18, 66′ b81) is not a core allocation. Theorem 2 fails here, because TN = {2} and β{1} 2 ≥5 4. Note that θ σN, dN, zN = 30 + 200 11 , 35 + 350 11 = (48′ b18, 66′ b81) is not a core allocation. Theorem 2 fails here, because TN = {2} and β{1} 2 ≥5 4. Numerical Experiments ﬁ l h d h h k h h d f h It can be seen that the the larger the number of players and periods, the higher the percentage that some unitary Owen point belongs to the core. In case that we impose that the demand and the costs are greater than zero: di t ∈[1, 30], pi t, hi t, bi t ∈[1, 10], and ki t ∈[1, 50], the results even improve signiﬁcantly, as Table 11 shows. Table 6. Weights associated to the optimal plan. Table 6. Weights associated to the optimal plan. βS 1 ≥ βS 2 ≥ βS 3 ≥ ∑t∈TN βS t {1} −4 5 3 5 0 −1 5 {2} −8 5 −9 5 −2 −27 5 {3} −8 5 −9 5 −6 −47 5 {1, 2} 3 10 4 10 0 7 10 {1, 3} 3 10 4 10 0 7 10 {2, 3} −16 5 −18 5 −8 −27 5 Hence, it follows that θ eσN, dN, zN = (6′8, 5′6, 9′6) ∈Core(N, c). Hence, it follows that θ eσN, dN, zN = (6′8, 5′6, 9′6) ∈Core(N, c). This section is completed with a third example showing that, if any of the conditions either of the Proposition 1 or Theorem 2 fail, the unitary Owen points are no longer core allocations. Example 3. Now, consider the following SI-situation with three periods, two players, and the associated 2-player SI-game, given by Table 7: Mathematics 2021, 9, 869 13 of 19 13 of 19 Table 7. SI-situation with three periods and two players with the associated SI-game. dS 1 dS 2 dS 3 pS 1 pS 2 pS 3 hS 1 hS 2 bS 1 bS 2 kS 1 kS 2 kS 3 c {1} 0 10 10 1 1 1 1 1 1 1 1 50 15 46 {2} 0 35 0 1 1 1 1 1 1 1 1 50 15 71 {1, 2} 0 45 10 1 1 1 1 1 1 1 1 50 15 115 There is a single optimal ordering plan that is shown in Table 8: Table 7. SI-situation with three periods and two players with the associated SI-game. There is a single optimal ordering plan that is shown in Table 8: Table 8. An optimal plan for SI-situation. σS 1 σS 2 σS 3 PS 1 (σS) PS 2 (σS) PS 3 (σS) k(S) {1} 0 1 3 0 2 1 16 {2} 0 1 0 0 2 0 1 {1, 2} 0 2 2 0 1 2 50 Table 8. An optimal plan for SI-situation. Numerical Experiments At ﬁrst glance, the reader might think that the conditions of Theorem 2 are too restrictive, i.e., they are only satisﬁed by a small family of SI-situations. However, an empirical analysis simulating SI-situations shows that most of the instances satisfy those conditions. Indeed, we start by randomly generating (using the uniform probability distribution) a ﬁrst set of 100,000 instances of SI-situations, so that, for every player and for each period, the data range in di t ∈[0, 30], pi t, hi t, bi t ∈[0, 10], and ki t ∈[0, 50]. Table 10 shows the percentage of SI-situations for which the Unitary Owen point belongs to the core of the corresponding SI-game. Table 10. Percentage of instances fulﬁlling the condition of Theorem 2 for the ﬁrst set of instances. Players T = 2 T = 3 T = 4 T = 5 2 99.934% 99.979% 99.993% 100% 3 99.942% 99.983% 99.989% 99.995% 4 99.950% 99.991% 99.996% 99.999% 5 99.974% 99.982% 99.992% 99.998% 6 99.974% 99.993% 99.998% 99.999% 7 99.985% 99.996% 99.999% 100% It can be seen that the the larger the number of players and periods, the higher the percentage that some unitary Owen point belongs to the core. In case that we impose that the demand and the costs are greater than zero: di t ∈[1, 30], pi t, hi t, bi t ∈[1, 10], and ki t ∈[1, 50], the results even improve signiﬁcantly, as Table 11 shows. Table 10. Percentage of instances fulﬁlling the condition of Theorem 2 for the ﬁrst set of instances. Players T = 2 T = 3 T = 4 T = 5 2 99.934% 99.979% 99.993% 100% 3 99.942% 99.983% 99.989% 99.995% 4 99.950% 99.991% 99.996% 99.999% 5 99.974% 99.982% 99.992% 99.998% 6 99.974% 99.993% 99.998% 99.999% 7 99.985% 99.996% 99.999% 100% Table 10. Percentage of instances fulﬁlling the condition of Theorem 2 for the ﬁrst set of instances. It can be seen that the the larger the number of players and periods, the higher the percentage that some unitary Owen point belongs to the core. In case that we impose that the demand and the costs are greater than zero: di t ∈[1, 30], pi t, hi t, bi t ∈[1, 10], and ki t ∈[1, 50], the results even improve signiﬁcantly, as Table 11 shows. Numerical Experiments Mathematics 2021, 9, 869 14 of 19 14 of 19 In the previous simulation, the range of variation for the costs have been chosen, so that those costs are actually relevant in determining the optimal plans for each coalition. In addition, if the the set-up costs are large when compared to the other costs, as, for instance, for di t ∈[0, 10], pi t, hi t, bi t ∈[0, 10] and ki t ∈[50, 500] the percentage of instances where the unitary Owen point is a core allocation is close to 99.995%, even for the case of two players and two periods. Moreover, if the demand is larger, as happens in the following situation di t ∈[10, 50], pi t, hi t, bi t ∈[0, 10] and ki t ∈[0, 50], percentages of “success” also increase close to 1 (99.999%). Table 11. Percentage of instances fulfilling the condition of Theorem 2 for instances with positive costs. Table 11. Percentage of instances fulfilling the condition of Theorem 2 for instances with positive costs. Players T = 2 T = 3 T = 4 T = 5 2 99.984% 99.996% 99.999% 100% 3 99.997% 99.995% 99.999% 99.999% 4 99.998% 99.996% 99.999% 99.998% 5 100% 99.999% 100% 100% 6 100% 100% 100% 100% 5. SI-Games and PI-Games 5. SI-Games and PI-Games To complete the paper, we provide a relationship between a generic SI-game and a speciﬁc family of PI-games through Owen’s points of the latter. We use Owen points from an ad hoc family of PI-situations constructed from core allocations of the so-called surplus game, which measures the excess in costs that occurs with respect to the minimum unit price. This interesting relationship simpliﬁes the analysis and construction of core allocations for SI-games. g First, we introduce the minimum unitary prices for every optimal plan. Denote, by ∆:= σS S∈P(N), an optimal plan in Λ(N, D, Z). Deﬁnition 3. Let (N, D, Z) be a SI-situation. The minimum unitary price for ∆, in each period t ∈T, is y∗ t (∆) = min S⊆N dS t ̸=0 {yt σS, dS, zS }. Deﬁnition 3. Let (N, D, Z) be a SI-situation. The minimum unitary price for ∆, in each period t ∈T, is y∗(∆) min{y σS dS zS } Deﬁnition 3. Let (N, D, Z) be a SI-situation. The minimum unitary price for ∆, in each period t ∈T is y∗ t (∆) = min S⊆N dS t ̸=0 {yt σS, dS, zS }. y∗ t (∆) = min S⊆N dS t ̸=0 {yt σS, dS, zS }. Second, for each coalition, we measure the excess in costs that occurs with respect to the minimum unit prices. The resulting cost game is what we have called surplus game. Deﬁnition 4. Let (N, D, Z) be a SI-situation and (N, c) the associated SI-game. For any ∆∈ Λ(N, D, Z), the surplus game (N, c∆) is deﬁned for all S ⊆N, as c∆(S) := c(S) − T ∑ t=1 y∗ t (∆) · dS t . Note that the surplus game is a non-negative cost game that measures the increase in costs by the inﬂuence of set-up costs. The ﬁrst result of this section shows that surplus games are always balanced. Proposition 2. Every surplus game (N, c∆) is balanced. Proposition 2. Every surplus game (N, c∆) is balanced. Mathematics 2021, 9, 869 15 of 19 15 of 19 Proof. It follows from Theorem 1 that every SI-game (N, c) is balanced. Take a core allocation x ∈RN for it. Proposition 3. Let (N, c) be a SI-game. For any ∆∈Λ(N, D, Z), c∆(N) = 0 if and only if T ∑ t=1 y∗ t (∆) · di t ! i∈N ∈Core(N, c). Proof. (If) If c∆(N) = 0 then ∑T t=1 y∗ t (∆) · dN t = c(N). For each S ⊂N, ∑i∈S ∑T t=1 y∗ t (∆) · di t = ∑T t=1 y∗ t (∆) · dS t ≤∑T t=1 yt σS, dS · dS t = c(S). Thus, ∑T t=1 y∗ t (∆) · di t i∈N ∈Core(N, c). (Only if) If ∑T t=1 y∗ t (∆) · di t i∈N ∈Core(N, c), it is satisfied that ∑T t=1 y∗ t (∆) · dN t = c(N), and, so, c∆(N) = 0. The main theorem in this section shows that the core of any SI-game consists of the Owen points of certain PI-games that were obtained from core allocations of surplus games. To state this theorem, it is necessary to describe a procedure for constructing a PI-situation from core allocations of surplus games. Consider a SI-situation (N, D, Z), the associated SI-game (N, c), and the surplus game (N, c∆), for ∆∈Λ(N, D, Z). For any α ∈Core(N, c∆), N, D(α), Z is a PI-situation with Z = (K, H, B, P) and D(α) = [d 1, . . . , d n]′, K = 0, H = [M, . . . , M]′, B = [M, . . . , M]′, P = [p, . . . , p]′, with p = (y∗ 1(∆), ..., y∗ T(∆), 1), d i = (di 1, ..., di T, αi) for all i ∈N and M ∈RN large enough. This procedure shows that any SI-situation can be transformed into multiple PI-situations just by using the core of the surplus games. Theorem 3. Let (N, c) be a SI-game and (N, c∆) the associated surplus game for ∆∈Λ(N, D, Z). Thus, Core(N, c) = n Owen N, D(α), Z : α ∈Core(N, c∆) o . Proof. As (N, c∆) is balanced, there is at least one α ∈RN, such that α(S) ≤c∆(S) = c(S) −∑T t=1 y∗ t (∆) · dS t for all S ⊂N and α(N) = c(N) −∑T t=1 y∗ t (∆) · dN t . Consider a PI-situation (N, D(α), Z) with T + 1 periods, where D(α) = [d 1, . . . 5. SI-Games and PI-Games For each S ⊂N, it holds that x(S) ≤ c(S) ⇐⇒x(S) − T ∑ t=1 y∗ t (∆) · dS t ≤c(S) − T ∑ t=1 y∗ t (∆) · dS t ⇐⇒ x(S) − T ∑ t=1 y∗ t (∆) · dS t ≤c∆(S) ⇐⇒∑ i∈S xi − T ∑ t=1 y∗ t (∆) · di t ! ≤c∆(S). Moreover x(N) = c(N), which easily implies that ∑i∈N xi −∑T t=1 y∗ t (∆) · di t = c∆(N). Hence, we conclude that xi −∑T t=1 y∗ t (∆) · di t i∈N ∈Core(N, c∆). Moreover x(N) = c(N), which easily implies that ∑i∈N xi −∑T t=1 y∗ t (∆) · di t = c∆(N). Hence, we conclude that xi −∑T t=1 y∗ t (∆) · di t i∈N ∈Core(N, c∆). In the following, we use this game to construct core allocations for SI-games by means of the Owen points of the surplus game, which is an easy PI-game. The next result provides a necessary and sufﬁcient condition for this purpose: the set-up costs cannot contribute to any increase in costs for the grand coalition. In other words, there are no costs exceeding the unit prices of the grand coalition. Proposition 3. Let (N, c) be a SI-game. For any ∆∈Λ(N, D, Z), Proposition 3. Let (N, c) be a SI-game. For any ∆∈Λ(N, D, Z), Proposition 3. Let (N, c) be a SI-game. For any ∆∈Λ(N, D, Z), i∈N ( ) t 1 yt ( ) t ( ) t 1 ∑T t=1 y∗ t (∆)dN t = c(N). Thus Owen N, D(α), Z ∈Core(N, c). On the other hand, if x ∈Core(N, c), for each S ⊂N, it holds that On the other hand, if x ∈Core(N, c), for each S ⊂N, it holds that x(S) ≤ c(S); x(S) − T ∑ t=1 y∗ t (∆) · dS t ≤ c(S) − T ∑ t=1 y∗ t (∆) · dS t ; ∑ i∈S xi −∑ i∈S T ∑ t=1 y∗ t (∆) · d{i} t ! ≤ c∆(S); ∑ i∈S xi − T ∑ t=1 y∗ t (∆) · d{i} t ! ≤ c∆(S); Moreover, x(N) = c(N) ⇔∑ i∈N xi −∑T t=1 y∗ t (∆) · di t = c∆(N). Thus, for each x ∈ Core(N, c), we can take αi := xi −∑T t=1 y∗ t (∆) · di t for all i ∈N, such that α ∈Core(N, c∆). From there, it easily follows that Owen N, D(α), Z = ∑T t=1 y∗ t (∆) · di t + αi i∈N = x. Moreover, x(N) = c(N) ⇔∑ i∈N xi −∑T t=1 y∗ t (∆) · di t = c∆(N). Thus, for each x ∈ Core(N, c), we can take αi := xi −∑T t=1 y∗ t (∆) · di t for all i ∈N, such that α ∈Core(N, c∆). From there, it easily follows that Owen N, D(α), Z = ∑T t=1 y∗ t (∆) · di t + αi i∈N = x. We illustrate the procedure above with the Example 3 that is shown above. Example 4. Consider the two-player SI-game that is given in Example 3. We have shown that the unitary Owen point is not a core allocation for this example. It can be easily checked that the minimal unit prices are those shown in Table 12. Table 12. Minimal unit prices. y∗ 1 (∆) y∗ 2 (∆) y∗ 3 (∆) 0 1 + 50 55 1 + 15 10 Table 12. Minimal unit prices. Consider a core allocation from the surplus game, for instance, the nucleolus η(N, c∆) = ( 10 11, 3 2 11). We obtain a core allocation for the SI-game just by calculating the Owen point of the Proposition 3. Let (N, c) be a SI-game. For any ∆∈Λ(N, D, Z), , d n]′, K = 0, H = [M, . . . , M]′, B = [M, . . . , M]′, P = [p, . . . , p]′ Mathematics 2021, 9, 869 16 of 19 with p = (y∗ 1(∆), ..., y∗ T(∆), 1), d i = (di 1, ..., di T, αi) for all i ∈N and M ∈RN large enough. For each i ∈N, Oweni N, D(α), Z = ∑T+1 t=1 y∗ t (N)di t = ∑T t=1 y∗ t (∆)di t + αi. Subsequently, for all S ⊂N: with p = (y∗ 1(∆), ..., y∗ T(∆), 1), d i = (di 1, ..., di T, αi) for all i ∈N and M ∈RN large enough. For each i ∈N, Oweni N, D(α), Z = ∑T+1 t=1 y∗ t (N)di t = ∑T t=1 y∗ t (∆)di t + αi. Subsequently, for all S ⊂N: ∑ i∈S Oweni N, D(α), Z = T ∑ t=1 y∗ t (∆) · dS t + α(S) ≤ T ∑ t=1 y∗ t (∆) · dS t + c(S) − T ∑ t=1 y∗ t (∆) · dS t = c(S). Moreover, ∑ i∈N Oweni N, D(α), Z = ∑T t=1 y∗ t (∆)dN t + α(N) = ∑T t=1 y∗ t (∆)dN t + c(N) − ∑T t=1 y∗ t (∆)dN t = c(N). Thus Owen N, D(α), Z ∈Core(N, c). On the other hand, if x ∈Core(N, c), for each S ⊂N, it holds that Moreover, ∑ i∈N Oweni N, D(α), Z = ∑T t=1 y∗ t (∆)dN t + α(N) = ∑T t=1 y∗ t (∆)dN t + c(N) − T Moreover, ∑ i∈N Oweni N, D(α), Z = ∑T t=1 y∗ t (∆)dN t + α(N) = ∑T t=1 y∗ t (∆)dN t + c(N) − ∑T t=1 y∗ t (∆)dN t = c(N). Thus Owen N, D(α), Z ∈Core(N, c). On the other hand if x ∈Core(N c) for each S ⊂N it holds that Moreover, ∑ i∈N Oweni N, D(α), Z = ∑T t=1 y∗ t (∆)dN t + α(N) = ∑T t=1 y∗ t (∆)dN t + c(N) − ∑T t=1 y∗ t (∆)dN t = c(N). Thus Owen N, D(α), Z ∈Core(N, c). Proposition 3. Let (N, c) be a SI-game. For any ∆∈Λ(N, D, Z), y∗ 1 (∆) y∗ 2 (∆) y∗ 3 (∆) 0 1 + 50 55 1 + 15 10 Thus, the surplus game is given by in Table 13 Thus, the surplus game is given by in Table 13 Table 13. The surplus game. c c∆ {1} 46 1 + 10 11 {2} 71 4 + 2 11 {1, 2} 115 4 + 1 11 Consider a core allocation from the surplus game, for instance, the nucleolus η(N, c∆) = ( 10 11, 3 2 11). We obtain a core allocation for the SI-game just by calculating the Owen point of the Mathematics 2021, 9, 869 17 of 19 17 of 19 associated PI-situation N, D(η(N, c∆)), Z . Thus, Owen N, D(η(N, c∆)), Z = (45, 70). It can be concluded that η(N, c) = Owen N, D(η(N, c∆)), Z . associated PI-situation N, D(η(N, c∆)), Z . Thus, Owen N, D(η(N, c∆)), Z = (45, 70). It can be concluded that η(N, c) = Owen N, D(η(N, c∆)), Z . associated PI-situation N, D(η(N, c∆)), Z . Thus, Owen N, D(η(N, c∆)), Z = (45, 70). It can be concluded that η(N, c) = Owen N, D(η(N, c∆)), Z . η(N, c) = Owen N, D(η(N, c∆)), Z . In the above example, the nucleolus of the surplus game leads to the nucleolus of the SI-game through the Owen point. The last result in the paper shows that this close relationship between both nucleoli always holds, e.g., the nucleolus of any SI-game matches the Owen point for the PI-situation that is obtained from the nucleolus of the surplus game. Proposition 4. Let (N, D, Z) be a SI-situation, (N, c) the associated SI-game, and (N, c∆) the surplus game for ∆∈Λ(N, D, Z). Thus, Owen N, D(η(N, c∆)), Z = η(N, c). Proof. It is known that x ∈Core(N, c) if and only if x∆:= xi −∑T t=1 y∗ t (∆) · di t i∈N ∈ Core(N, c∆). Thus, the excess vectors, e(S, x), and e∆(S, x∆) coincide. Proposition 3. Let (N, c) be a SI-game. For any ∆∈Λ(N, D, Z), For each coalition S ⊆N, it holds that: e(S, η(N, c)) = c(S) −∑ i∈S ηi(N, c) = c∆(S) + T ∑ t=1 y∗ t (∆) · dS t −∑ i∈S ηi(N, c) = c∆(S) −∑ i∈S ηi(N, c) − T ∑ t=1 y∗ t (∆) · di t ! . Therefore, ηi(N, c∆) = ηi(N, c) −∑T t=1 y∗ t (∆) · di t for all i ∈N, because otherwise η(N, c) would not be the nucleolus. Moreover, Therefore, ηi(N, c∆) = ηi(N, c) −∑T t=1 y∗ t (∆) · di t for all i ∈N, because otherwise η(N, c) would not be the nucleolus. Moreover, c∆(S) −ηi(N, c∆) = c(S) − T ∑ t=1 y∗ t (∆) · dS t + ∑ i∈S ηi(N, c∆) ! = c(S) −∑ i∈S Oweni N, D(η(N, c∆)), Z = e(S, Owen N, D(η(N, c∆)), Z ). c∆(S) −ηi(N, c∆) = c(S) − T ∑ t=1 y∗ t (∆) · dS t + ∑ i∈S ηi(N, c∆) ! = c(S) −∑ i∈S Oweni N, D(η(N, c∆)), Z = e(S, Owen N, D(η(N, c∆)), Z ). This implies that Owen N, D(η(N, c∆)), Z = η(N, c). This implies that Owen N, D(η(N, c∆)), Z = η(N, c). This implies that Owen N, D(η(N, c∆)), Z = η(N, c). 6. Discussion The study of cooperation in lot-sizing problems with backlogging and heterogeneous costs has been previously considered by [19]. The authors prove that there are always stable allocations of the overall operating cost among the ﬁrms, so that no group of agents beneﬁt from leaving the consortium. They propose a parametric family of cost allocations and provide sufﬁcient conditions for this to be a stable family against coalitional defections of ﬁrms and focus on those periods of the time horizon that are consolidated, analyzing their effect on the stability of cost allocations. This paper completes the study of those cooperative lot-sizing models by presenting unitary Owen points. As mentioned, the Owen point works very well for constructing core-allocations in the class of PI-games. Unfortunately, no longer works for SI-problems. In spite of that, here we have managed to construct a particular kind of prices, which we call unitary prices, based on the production, inventory, and backlogging costs, and a proportion of the ﬁxed order cost, which depends on the total demand satisﬁed in each period. These unit prices resemble the Owen point and allow to replicate its construction, Mathematics 2021, 9, 869 18 of 19 18 of 19 so that these allocations “a la Owen” are called unitary Owen points. These quantities can be understood as approximate dual prices that allow pricing each ﬁrm resources, in order to distribute, in a stable manner, the overall operating costs. Necessary and sufﬁcient conditions are provided for the unitary Owen points to belong to the core of the cooperative game. In addition, we provide empirical evidence, through simulation, showing that, in randomly generated situations, the above condition is fulﬁlled in 99% of cases. Finally, a relationship between lot-sizing games and a certain family of production-inventory games, through Owen’s points of the latter, is described. This interesting relationship enables us to easily derive and interpret a variety of coalitionally stable allocations for cooperative lot-sizing models. The growing literature that is devoted to the study of cooperation in lot- sizing models shows that there are always ways to allocate the minimum cost that results from cooperation that are coalitionally stable. In addition, a few algorithms have been proposed to determine some of these allocations. 6. Discussion The main contribution of this paper is that it presents an explicit cost allocation for cooperative lot-sizing models with backlogging and heterogeneous costs that is coalitional stable and consistent in 99% of cases. Moreover, the analysis of cooperation in general lot-sizing models offers a vast ﬁeld for future research. We propose the following directions for future research. The ﬁrst direction is to ﬁnd a set of properties the determine the unitary Owen point by means of an axiomatic characterization. The second direction is to consider lot-sizing models with capacity constraints, which is, to study capacitated lot-sizing models with backlogging. We believe that adding restrictions on the companies’ production capacity could create incentives for them to compete with each other, in a ﬁrst stage, and to cooperate later, once the production capacity has been decided. Finally, it would also be interesting to study the cooperation in lot-sizing models with limited information sharing. Full information sharing us a typical assumption in cooperative models. However, in supply chains settings, companies may not release all of their relevant information. Furthermore, it should be possible to design mechanisms to encourage the ﬁrms to release full and true information. Author Contributions: The authors of this manuscript have evenly contributed to all aspects of the research. Conceptualization, L.A.G., A.M. and J.P. ; methodology, L.A.G., A.M. and J.P.; software, L.A.G., A.M. and J.P.; validation, L.A.G., A.M. and J.P.; formal analysis, L.A.G., A.M. and J.P.; investigation, L.A.G., A.M. and J.P.; writing—original draft preparation, L.A.G., A.M. and J.P.; writing—review and editing, L.A.G., A.M. and J.P.; funding acquisition, A.M. and J.P. All authors have read and agreed to the published version of the manuscript. Funding: The research authors is supported from Spain’s Ministerio de Ciencia, Innovación y Universidades (MCIU), from the Agencia Estatal de Investigación (AEI) and from the Fondo Europeo de Desarrollo Regional (FEDER) under the projects MTM2016-74983-C02-01 and PGC2018-097965-B- I00. The research of the third author is also partially supported from projects FEDER-US-1256951, CEI-3-FQM331 and NetmeetData: Ayudas Fundación BBVA a equipos de investigación cientíﬁca 2019. Institutional Review Board Statement: Not applicable. Institutional Review Board Statement: Not applicable. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Data Availability Statement: Not applicable. Conﬂicts of Interest: The authors declare no conﬂict of interest. Conﬂicts of Interest: The authors declare no conﬂict of interest. 1. Brahimi, N.; Absi, N.; Dauzère-Pérès, S.; Nordli, Single-item dynamic lot-sizing problems: An updated survey. Eur. J. Oper. Res. 2017, 263, 838–863. [CrossRef] f g f g 5. Li, H.; Meissner, J. Competition under capacitated dynamic lot-sizing with capacity acquisition. 131, 535–544. [CrossRef] 4. Hall, N.G.; Liu, Z. Cooperative and Noncooperative Games for Capacity Planning and Scheduling. I Research: State-of-the-Art Decision-Making Tools in the Information-Intensive Age; INFORMS: Hanover, MD , [ ] 4. Hall, N.G.; Liu, Z. Cooperative and Noncooperative Games for Capacity Planning and Scheduling. In TutORials in Operations Research: State-of-the-Art Decision-Making Tools in the Information-Intensive Age; INFORMS: Hanover, MD, USA; 2008; pp. 108–129. 5. Li, H.; Meissner, J. Competition under capacitated dynamic lot-sizing with capacity acquisition. Int. J. Prod. Econ. 2011, 131 535 544 [CrossRef] 2. Ullah, H.; Parveen, S. A Literature Review on Inventory lot-sizing Problems. Glob. J. Res. Eng. 2010 2. Ullah, H.; Parveen, S. A Literature Review on Inventory lot-sizing Problems. Glob. J. Res. Eng. 2010, 10, 21–36. 3. Pochet, Y.; Wolsey, A.L. Lot-size models with backlogging: Strong reformulations and cutting planes. Math. Program. 1988, 40, 317–335. [CrossRef] 4. Hall, N.G.; Liu, Z. Cooperative and Noncooperative Games for Capacity Planning and Scheduling. In TutORials in Operations Research: State-of-the-Art Decision-Making Tools in the Information-Intensive Age; INFORMS: Hanover, MD, USA; 2008; pp. 108–129. 5. Li, H.; Meissner, J. Competition under capacitated dynamic lot-sizing with capacity acquisition. Int. J. Prod. Econ. 2011, 131, 535–544. [CrossRef] References 1. Brahimi, N.; Absi, N.; Dauzère-Pérès, S.; Nordli, Single-item dynamic lot-sizing problems: An updated survey. Eur. J. Oper. Res. 2017, 263, 838–863. [CrossRef] 2. Ullah, H.; Parveen, S. A Literature Review on Inventory lot-sizing Problems. Glob. J. Res. Eng. 2010, 10, 21–36. 3. Pochet, Y.; Wolsey, A.L. Lot-size models with backlogging: Strong reformulations and cutting planes. Math. Program. 1988, 40, 317–335. [CrossRef] 4. Hall, N.G.; Liu, Z. Cooperative and Noncooperative Games for Capacity Planning and Scheduling. In TutORials in Operations Research: State-of-the-Art Decision-Making Tools in the Information-Intensive Age; INFORMS: Hanover, MD, USA; 2008; pp. 108–129. 5. Li, H.; Meissner, J. Competition under capacitated dynamic lot-sizing with capacity acquisition. Int. J. Prod. Econ. 2011, 131, 535–544. [CrossRef] y g g 3. Pochet, Y.; Wolsey, A.L. Lot-size models with backlogging: Strong reformulations and cutting planes. Math. Program. 1988, 40, 317–335. [CrossRef] References 3. Pochet, Y.; Wolsey, A.L. Lot-size models with backlogging: Strong reformulations and cutting planes. Math. Program. 1988, 40, 317–335. [CrossRef] 5. Li, H.; Meissner, J. Competition under capacitated dynamic lot-sizing with capacity acquisition. Int. J. Prod. Econ. 2011, 131, 535–544. [CrossRef] 19 of 19 19 of 19 Mathematics 2021, 9, 869 6. Carvalho, M.; Pedroso, J.P.; Telha, C.; Van Vyve, M. Competitive uncapacitated lot-sizing game. Int. J. Prod. Econ. 2018, 204, 148–159. [CrossRef] , [ ] 7. Chen, X.; Zhang, J. Duality approaches to economic lot-sizing games. Prod. Oper. Manag. 2016, 25, 1203–1215. [CrossRef] , ; g, J y pp g g p g , , 8. Van den Heuvel, W.; Borm, P.; Hamers, H. Economic lot-sizing games. Eur. J. Oper. Res. 2007, 176, 1117 , ; , ; , g g J p , , [ ] 9. Guardiola, L.A.; Meca, A.; Puerto, J. Production-Inventory games: a new class of totally balanced combinatorial optimization games. Games Econ. Behav. 2009, 65, 205–219. [CrossRef] 10. Guardiola, L.A.; Meca, A.; Puerto, J. PI-games and pmas games: characterizations of Owen point. Math. Soc. Sci. 2008, 56, 96–108. [CrossRef] 11. Gharaei, A.; Karimi, M.; Hoseini Shekarabi, S.A. Joint Economic Lot-sizing in Multi-product Multi-level Integrated Supply Chains: Generalized Benders Decomposition. Int. J. Syst. Sci. Oper. Logist. 2020, 7, 309–325. [CrossRef] G.; Burnetas, A. Coordinating Lot Sizing Decisions Under Bilateral Information Asymmetry. Prod. Oper –387. [CrossRef] 12. Zissis, D.; Ioannou, G.; Burnetas, A. Coordinating Lot Sizing Decisions Under Bilateral Information Manag. 2020, 29, 371–387. [CrossRef] 13. Owen, G. On the core of linear production games. Math. Program. 1975, 9, 358–370. [CrossRef] 15. Zeng, Y.; Li, J.; Cai, X. Economic lot-sizing games with perishable inventory. In Proceedings of the ICSSSM11, Tianjin, China, 25–27 June 2011; pp. 1–5. [CrossRef] 16. Gopaladesikan, M.; Uhan, N.A. Cost Sharing for the Economic Lot-Sizing Problem with Remanufacturing Options. 2011. Available online: http://www.optimization-online.org/DB_FILE/2010/09/2733.pdf (accessed on 15 January 2021). 17. Xu, D.; Yang, R. A cost-sharing method for an economic lot-sizing game. Oper. Res. Lett. 2009, 37, 107–110. [CrossRef] 18. Tsao, Y.C.; Chen, T.H.; Wu, P.Y. Effects of Lot-Sizing Integration and Learning Effect on Managing Imperfect Items in a Manufacturer-Retailer Chain. J. Appl. Math. 2013, 9, 1–11. [CrossRef] , ; g, g g g p , , [ ] 18. Tsao, Y.C.; Chen, T.H.; Wu, P.Y. Effects of Lot-Sizing Integration and Learning Effect on Managing Imperfect Items in a Manufacturer-Retailer Chain. J. Appl. Math. References 2013, 9, 1–11. [CrossRef] J pp 19. Guardiola, L.A.; Meca, A.; Puerto, J. Cooperation in lot-sizing problems with heterogeneous costs: the effect of consolidated periods. arXiv 2021, arXiv:2103.09086 pp 19. Guardiola, L.A.; Meca, A.; Puerto, J. Cooperation in lot-sizing problems with heterogeneous costs: the effect of consolidated periods. arXiv 2021, arXiv:2103.09086 p 20. Zangwill, W.I. A deterministic multi-period production scheduling model with backlogging. Manag. Sci. 1966, 13, 105–119. [CrossRef] 20. Zangwill, W.I. A deterministic multi-period production scheduling model with backlogging. Manag. Sci. 1966, 13, 105–119. [CrossRef] 21. Zangwill, W.I. A backlogging model and multi-echelon model of a dynamic economic lot size produc approach. Manag. Sci. 1969, 15, 506–527. [CrossRef] 21. Zangwill, W.I. A backlogging model and multi-echelon model of a dynamic economic lot size production system—A network approach. Manag. Sci. 1969, 15, 506–527. [CrossRef] 21. Zangwill, W.I. A backlogging model and multi-echelon model of a dynamic economic lot size production system—A network approach. Manag. Sci. 1969, 15, 506–527. [CrossRef] 22. Bondareva, O.N. Some applications of linear programming methods to the theory of cooperative games. Probl. Kibernety 1963, 10, 22. Bondareva, O.N. Some applications of linear programming methods to the theory of cooperative gam 119–139. (In Russian) ( ) 23. Shapley, L.S. On Balanced Sets and Cores. Naval. Res. Logist. 1967, 14, 453–460. [CrossRef] 23. Shapley, L.S. On Balanced Sets and Cores. Naval. Res. Logist. 1967, 14, 453–460. [CrossRef] p y g y 25. Tamir, A. On the complexity of some classes of location problems. Transp. Sci. 1992, 26, 352–354. [CrossRef] p y g y 25. Tamir, A. On the complexity of some classes of location problems. Transp. Sci. 1992, 26, 352–354. [Cros 25. Tamir, A. On the complexity of some classes of location problems. Transp. Sci. 1992, 26, 352–354. [CrossRef] 26. Perea, F.; Puerto, J.; Fernández, F.R. Avoiding unfairness of Owen allocations in linear production pr 2012, 220, 125–131. [CrossRef] 27. Fernández, F.R.; Hinojosa, M.A.; Puerto J. Core solutions in vector-valued games. J. Optim. Theory Appl. 2002, 112, 331–360. [CrossRef] 27. Fernández, F.R.; Hinojosa, M.A.; Puerto J. Core solutions in vector-valued games. J. Optim. Theory Appl. 2002, 112, 331–360. [CrossRef]
https://openalex.org/W2032519102	https://hal.science/hal-00172232/document	English	null	Super-transmission of light through subwavelength annular aperture arrays in metallic films: Spectral analysis and near-field optical images in the visible range	Photonics and nanostructures	2,006	cc-by	4,906	Super-transmission of light through subwavelength annular aperture arrays in metallic films: Spectral analysis and near-field optical images in the visible range Y. Poujet, M. Roussey, J. Salvi, F.I. Baida, D. van Labeke, A. Perentes, C. Santschi, P. Hoffmann Super-transmission of light through subwavelength annular aperture arrays in metallic films: Spectral analysis and near-field optical images in the visible range Y. Poujet, M. Roussey, J. Salvi, F.I. Baida, D. van Labeke, A. Perentes, C. Santschi, P. Hoffmann Santschi, P. Hoffmann To cite this version: Y. Poujet, M. Roussey, J. Salvi, F.I. Baida, D. van Labeke, et al.. Super-transmission of light through subwavelength annular aperture arrays in metallic films: Spectral analysis and near-field optical images in the visible range. Photonics and Nanostructures - Fundamentals and Applications, 2006, 4 (1), pp.47-53. 10.1016/j.photonics.2005.12.002. hal-00172232 Distributed under a Creative Commons Attribution 4.0 International License * Corresponding author. Tel.: +33 38 1666410; fax: +33 38 1666423. E-mail address: jerome.salvi@univ-fcomte.fr (J. Salvi). Super-transmission of light through subwavelength annular aperture arrays in metallic ﬁlms: Spectral analysis and near-ﬁeld optical images in the visible range Y. Poujet a, M. Roussey a, J. Salvi a,, F.I. Baida a, D. Van Labeke a, A. Perentes b, C. Santschi b, P. Hoffmann b a FEMTO-ST UMR 6174, De´partement d’Optique P.M. Dufﬁeux, Universite´ de Franche-Comte´, 16 route de Gray, 25030 Besanc¸on Cedex, France b IOA, E´cole Polytechnique Fe´de´rale de Lausanne, CH-1015 Lausanne, Switzerland This paper presents experimental studies of the enhanced light transmission through metallic ﬁlms pierced by subwavelength annular apertures. Two different methods (e-beam lithography and focused ion beam) have been used to build the nano-structures. We have experimentally recorded their far-ﬁeld spectral response in the visible range and the optical near-ﬁeld above the nano- structures when they are excited at 633 nm. The spectral response exhibits a transmission peak at 700 nm with maximum efﬁciency around 16%. The near-ﬁeld exhibits a characteristic two-lobe structure just above the aperture. Finite difference time domain (FDTD) simulations reproduce quite well the experimental results. Keywords: Enhanced transmission; Nanostructures; Coaxes; Near-ﬁeld optics instance) [12–14]. These annular nano-structures have been named annular aperture array (AAA). HAL Id: hal-00172232 https://hal.science/hal-00172232v1 Submitted on 26 Apr 2021 L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci- entific research documents, whether they are pub- lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. Distributed under a Creative Commons Attribution 4.0 International License Super-transmission of light through subwavelength annular aperture arrays in metallic ﬁlms: Spectral analysis and near-ﬁeld optical images in the visible range Y. Poujet a, M. Roussey a, J. Salvi a,, F.I. Baida a, D. Van Labeke a, A. Perentes b, C. Santschi b, P. Hoffmann b a FEMTO-ST UMR 6174, De´partement d’Optique P.M. Dufﬁeux, Universite´ de Franche-Comte´, 16 route de Gray, 25030 Besanc¸on Cedex, France b IOA, E´cole Polytechnique Fe´de´rale de Lausanne, CH-1015 Lausanne, Switzerland 1. Introduction It has already been shown that enhanced light transmission could be achieved through a subwavelength array of cylindrical holes in metallic ﬁlms [1–4]. This type of nanostructure offers many interesting applica- tions: nanophotonics [5,6], nanophotolithography [7,8], ﬂuorescence [9,10] and chemical sensors [11]. In order to increase the transmission,BaidaandVanLabekerecently proposed a structure which consists of an array of nanometric coaxial cavities in a real metal (gold for Unlike a simple cylindrical wave guide, a coaxial cavity in the same metal with the same external radius accepts a guided mode with a cut-off wavelength shifted toward the red region of the spectrum [15]. This mode has a very small imaginary part of the effective index, so it can mediate light transmission through the structure with a high efﬁciency. Finite difference time domain (FDTD) simulations have established that a 2D metallic grating pierced with this kind of nano-structure could reach a 90% transmission in the visible region of the spectrum [13]. However, the designed structure presents several difﬁcult technical constraints: ﬁrst, the metal is silver, which is not well adapted to nano-fabrication. Second, the period and the coaxial radii must be very small (period ¼ 300 nm, inner radius ¼ 50 nm and outer radius = 75 nm). Recently, Fan et al. experimen- tally established 80% transmission through an AAA structure in the near infrared part of the spectrum (l ¼ 1:97 mm) [16,17]. After developing in the surfactant containing the developer MF 319 (Shipley), oxygen plasma treatment and adhesion promoting Ti evaporation coating (5 nm thick), 150 nm gold is deposited by e-beam evapora- tion. Finally, gold lift-off is achieved in an ultrasonic acetone bath. More details are given in reference [19]. In this paper, we present an AAA structure that we have designed and built in order to achieve a large transmission in the visible region. Our ﬁrst experimental results are presented here. So far, the AAA structure has been fabricated in gold by electron lithography and gold lift-off or with a focused ion beam (FIB). We have experimentally recorded its far-ﬁeld spectral response by using a very bright ﬁbered light source that presents a continuum spectrum in the whole visible range. We also present near-ﬁeld optical images of the fabricated structure. In the fabrication process, the gold coaxial holes are arranged in a total of 12 matrices of AAA with different geometrical parameters. 1. Introduction The width of each matrix is 30 mm 30 mm and they are separated by hundreds of microns. Consequently, a conventional spectrometer cannot be used to obtain a far-ﬁeld spectroscopic response and, therefore, a local illumination or detection is necessary. A SEM image of one of the arrays is presented in Fig. 1 a. The parameters of the coaxes are period p ¼ 600 nm, inner diameter r1 ¼ 250 nm and outer diameter r2 ¼ 330 nm. We also present an AFM image of an AAA structure with a different period (Fig. 1 b). Both images clearly show the quality of the fabricated the structures: regularity and shape aspect. 2. Fabrication of the periodic subwavelength nano-structures The ﬁrst two-dimensional arrays of co are generated by electron beam lithogr lift-off. The gold structures are made on sol–gel coated transparent conductive deposited on a microscope slide. Th Micro Resist Technology1ma-N 2410 resist was chosen, since it allows a 5 patterning with 150 nm resolution [18]. spin coated to 700 nm thickness in orde necessary high aspect-ratio resist st electron lithography equipment is base 6400 JSM scanning electron microscop a LaB6 thermionic emitter. The elec controlled with a Nabity Systems Patte (NPGS). The exposure dose varied and 250 mC/cm2. With 250 mC/cm2 structures correspond best to the calcul (see Fig. 1 a). Fig. 1. Scanning electronic microscope (SEM) a diameters are 250/330 nm. (a) SEM image: 2D arr structure milled with a FIB (period: 500 nm). The ﬁrst two-dimensional arrays of coaxial apertures are generated by electron beam lithography and gold lift-off. The gold structures are made on a 20 nm thick sol–gel coated transparent conductive oxyde layer deposited on a microscope slide. The commercial Micro Resist Technology1ma-N 2410 negative tone resist was chosen, since it allows a 5.2-aspect-ratio- patterning with 150 nm resolution [18]. The resist was spin coated to 700 nm thickness in order to obtain the necessary high aspect-ratio resist structures. The electron lithography equipment is based on a JEOL 6400 JSM scanning electron microscope (SEM) with a LaB6 thermionic emitter. The electron beam is controlled with a Nabity Systems Patterning Software (NPGS). The exposure dose varied between 200 and 250 mC/cm2. With 250 mC/cm2 the obtained structures correspond best to the calculated geometry (see Fig. 1 a). 3. Numerical simulations of the transmission The numerical simulations are performed by using the FDTD method. Our homemade code, already described elsewhere [12–14], includes the Berenger’s perfectly matched layers (PMLs) boundary conditions to avoid the parasitical reﬂections, due to the edges of the calculation window. The latter technique only treats the homogeneous waves [20]. Therefore, to cancel unwanted reﬂections of evanescent waves, the object is placed at a distance from the edges much larger than half of the highest value of the illuminating wavelength. In addition, to obtain accurate results, the spatial meshing of the object must be very small, which implies a great number of spatial nodes if a uniform mesh is used. In order to decrease the number of nodes, we use a Fig. 1. Scanning electronic microscope (SEM) and atomic force microscope (AFM) images of the two different built structures. The coaxes diameters are 250/330 nm. (a) SEM image: 2D array of coaxial cavities built by e-beam lithography (period: 600 nm). (b) AFM image of an other structure milled with a FIB (period: 500 nm). Fig. 1. Scanning electronic microscope (SEM) and atomic force microscope (AFM) images of the two different built structures. The coaxes diameters are 250/330 nm. (a) SEM image: 2D array of coaxial cavities built by e-beam lithography (period: 600 nm). (b) AFM image of an other structure milled with a FIB (period: 500 nm). Fig. 2. (a) Schematic of the structure and (b) experimental setup. Fig. 2. (a) Schematic of the structure and (b) experimental setup. non-uniform spatial discretization of the metallic structure as described before [21]. wavelengths between l ¼ 532 nm (beginning of our continuum) and l ¼ 600 nm, other diffracted orders appear (1), but they are not experimentally recorded because they propagate far from the ﬁber axis (see below). The incident ﬁeld is an x-polarized pulsed wave-plane propagating alongthe z-axis(seeFig. 2a).Itiscentered at a wavelength of 650 nm and covers the spectral range from 530 to 900 nm. Because we studied a very broad spectral range with real metal (gold, silver or aluminum), the dispersion of the permittivity must be taken into account. Therefore, the spectral range is subdivided into small spectral intervals of width dl ¼ 10 nm. In every spectraldomain,thetabulatedexperimentalpermittivities [22] are ﬁt with an appropriate Drude’s analytical model and a simple computing scheme connecting the dis- placement vector to the electric ﬁeld is obtained. 4. Spectroscopic setup and experimental results The experimental setup is shown in Fig. 2 b. A local illumination, under normal incidence, is obtained by using a powerful white light ﬁbered source [25]. This stable supercontinuum of light is generated thanks to a subnanosecond microship laser at 532 nm: its mean output power is around 30 mW and the full width at half-maximum pulse duration is 0.4 ns. The laser output beam is focused into a 100 m dispersion-shifted ﬁbre (DSF), generating a broadband single-mode super- continuum by stimulated Raman scattering and para- metric four-wave mixing. The object is a bi-periodic (in the x- and y- directions) array of coaxial apertures in a gold ﬁlm. The metallic layer is deposited on a glass substrate also incorporated into simulations. The calculation window consists of one array period (see Fig. 2 a, where four periods are presented). Consequently, the absorbing PML layers are only necessary in the z- direction. Periodic conditions are applied in the x- and y-directions. The spatial increment step is set to Dx ¼ Dy ¼ 10 nm. The non-uniform meshing is in the z-direction. A spatial step of dz ¼ 10 nm is chosen to mesh the metallic ﬁlm; whereas, the spatial step is Dz ¼ 25 nm for the rest of the window. These mesh variations are carried out gradually in order to avoid artiﬁcial reﬂections [24]. To collect the transmitted light through the AAA, a cleaved end multimode ﬁber (62.5 mm core diameter) is brought around 20 mm close to the sample. Thus, the angular acceptance of the cleaved ﬁber is equal to 57; whereas, the homogeneous ﬁrst diffracted order for l ¼ 532 nm is located at 62 from the ﬁber axis. Therefore, only the diffracted zero order is collected. The spectrum is then recorded by means of an optical spectrum analyser (S2000 Miniature Fiber Optic Spectrometer from Ocean Optics). In order to normalize the spectral response of one AAA, we recorded the source spectrum through a large metal-free zone. Fig. 3 shows the experimental spectral response of the AAA zone presented in Fig. 1 a compared to the theoretical spectral response obtained by the FDTD calculation. We would like to point out that, apart from a background subtraction, no image treatment has been performed on the curve. 3. Numerical simulations of the transmission It can be easily incorporated into the usual leap-frog FDTD scheme [23]. The transmission is obtained by evaluating the far-ﬁeld intensity of the diffracted zero order normalized by the incident one. 4. Spectroscopic setup and experimental results First, one can see from Fig. 3 there is very good agreement between experience and theory: for both curves a transmission peak at 700 nm (theoretically around 17%) is observed. The coaxial apertures array exhibits a super-transmission in the visible range: the transmitted fraction of the incident light exceeds by more than a factor1.5theopen area fractionof the ﬁlm whichis 10%. By comparison, FDTD calculations show that the maximum transmission of the corresponding cylindrical hole array (hole diameter 330 nm and period 600 nm) is around 30% at l ¼ 640 nm. However, in this case, the open area is 30% as well. Moreover, in the near-infrared region the transmission of the coaxes gets up to 60% at 1330 nm (see inset in Fig. 3), while there is no transmission beyond 1000 nm for the circular apertures. Second, the experimental curve is slightly translated towards higher wavelengths. This shift is probably linked to the polarization direction of the incident beam: the polarisation slightly affects the peak position [12]. As noticed in Fig. 4, the peak occurs at 700 nm, if the polarization is set along one axis x or y of the matrix and around 695 nm if the polarization is oriented at 45 from x or y. In the theoretical simulation in Fig. 3, the polarization was set along the x- or y-direction. The experimental setup could not allow us to control this parameter. Moreover, the fabrication parameters slightly differ from one coax with respect to the other and from the theoretical ones. Finally, the calculation does not take into account the very thin Ti layer (5 nm thick) used to improve the adhesion of gold onto the substrate. First, one can see from Fig. 3 there is very good agreement between experience and theory: for both curves a transmission peak at 700 nm (theoretically around 17%) is observed. The coaxial apertures array exhibits a super-transmission in the visible range: the transmitted fraction of the incident light exceeds by more than a factor1.5theopen area fractionof the ﬁlm whichis 10%. By comparison, FDTD calculations show that the maximum transmission of the corresponding cylindrical hole array (hole diameter 330 nm and period 600 nm) is around 30% at l ¼ 640 nm. However, in this case, the open area is 30% as well. 4. Spectroscopic setup and experimental results Moreover, in the near-infrared region the transmission of the coaxes gets up to 60% at 1330 nm (see inset in Fig. 3), while there is no transmission beyond 1000 nm for the circular apertures. 4. Spectroscopic setup and experimental results The noise appearing in the experimental spectrum is probably induced by temporal The transmission corresponds to the zero-order diffracted intensity normalized by the incident one. Note because of the periodicity of the structure ( p ¼ 600 nm), only one diffracted order (zero order) exists for the wavelengths larger than p. For the Fig. 3. Theoretical (dotted line) and experimental (solid line) spectral responses of the studied AAA structure (the coaxes diameters are 250/ 330 nm and the period is 600 nm). Inset: theoretical transmission in the near-infrared region showing a maximum of transmission at l ¼ 1330 nm. Fig. 4. Theoretical spectral response of the AAA structure with the polarization of the incident beam oriented at 45 from the coaxes matrix axes (dotted line) and with the polarization along one of the matrix axes (solid line). The coaxes diameters are 250/330 nm and the period is 600 nm. Fig. 4. Theoretical spectral response of the AAA structure with the polarization of the incident beam oriented at 45 from the coaxes matrix axes (dotted line) and with the polarization along one of the matrix axes (solid line). The coaxes diameters are 250/330 nm and the period is 600 nm. Fig. 3. Theoretical (dotted line) and experimental (solid line) spectral responses of the studied AAA structure (the coaxes diameters are 250/ 330 nm and the period is 600 nm). Inset: theoretical transmission in the near-infrared region showing a maximum of transmission at l ¼ 1330 nm. Fig. 4. Theoretical spectral response of the AAA structure with the polarization of the incident beam oriented at 45 from the coaxes matrix axes (dotted line) and with the polarization along one of the matrix axes (solid line). The coaxes diameters are 250/330 nm and the period is 600 nm. Fig. 3. Theoretical (dotted line) and experimental (solid line) spectral responses of the studied AAA structure (the coaxes diameters are 250/ 330 nm and the period is 600 nm). Inset: theoretical transmission in the near-infrared region showing a maximum of transmission at l ¼ 1330 nm. instability of the laser and mechanical instabilities in the injection and/or detection processes. Let us add that the extraordinary transmission corresponds to a resonance of the TE11 guided mode of the coaxial apertures: the peak position only slightly depends on the period value (compare Figs. 4 and 5 and see Ref. [15]). injection and/or detection processes. 5. Near-ﬁeld optical images A second sample has been used to perform near-ﬁeld optical images of an AAA structure. It has simply been fabricated by milling a 150 nm thick gold layer with a FIB. The metallic ﬁlm was deposited on a microscope slide with 5 nm thick adhesion titanium layer. The period is 500 nm, the inner-ring diameter 250 nm and Fig. 5. Theoretical spectral response of the AAA structure studied in near-ﬁeld optical microscopy (the coaxes diameters are 250/330 nm and the period is 500 nm). Second, the experimental curve is slightly translated towards higher wavelengths. This shift is probably linked to the polarization direction of the incident beam: the polarisation slightly affects the peak position [12]. As noticed in Fig. 4, the peak occurs at 700 nm, if the polarization is set along one axis x or y of the matrix and around 695 nm if the polarization is oriented at 45 from x or y. In the theoretical simulation in Fig. 3, the polarization was set along the x- or y-direction. The experimental setup could not allow us to control this parameter. Moreover, the fabrication parameters slightly differ from one coax with respect to the other and from the theoretical ones. Finally, the calculation does not take into account the very thin Ti layer (5 nm thick) used to improve the adhesion of gold onto the substrate. Fig. 5. Theoretical spectral response of the AAA structure studied in near-ﬁeld optical microscopy (the coaxes diameters are 250/330 nm and the period is 500 nm). Fig. 6. Reﬂectionscanning near-ﬁeld optical microscope (RSTOM) principle and images: (a) shear-force image; (b) corresponding optical image (both imagesare15 mm 15 mm);(c) opticalimage(b)ﬁlteredbyFourierTransform;(d)numericalzoominofimage (c)(6 mm 6 mm).Thewhitesquarein picture (c) shows the location of picture (d); (e) RSTOM experiment scheme; (f) theoretical image obtained by FDTD calculation(4:5 mm 4:5 mm). reﬂection. For this purpose we used our 3D-FDTD code, the incident ﬁeld is a plane wave and we plot the squared modulus of the diffracted ﬁeld calculated in a plane located 30 nm above the metal interface. The FDTD calculation also produces a ‘‘coffee-beans’’ array. The two-lobe structure corresponds to the mode excited inside the coaxial cavity [15]. The orientation of the two-lobe is determined by the polarization of the incident wave. It is oriented at 45 in the theoretical image. 6. Conclusions In conclusion, we demonstrated high transmission through an annular aperture array in the visible range and we present a ﬁrst optical near-ﬁeld image above this structure at 633 nm. These results are a ﬁrst attempt in the fabrication and experimental study of the AAA structure in the visible region. New structures with different parameters (period, metal thickness, and smaller coaxial radii) must be built in order to achieve a higher far-ﬁeld transmission. In prospect, FDTD simulations show a high transmission peak in an infrared wavelength: 60% transmission at 1330 nm (see inset in Fig. 3). Moreover, if silver is used instead of A shear-force image of the AAA structure is plotted in Fig. 6 a and the simultaneously obtained near-ﬁeld optical image is presented in Fig. 6 b. At ﬁrst look, the optical image in Fig. 6 b does not seem to correspond to the structure, the image is blurred by fringes. They are aligned along the array diagonal, not exactly superposed on the AAA structure, and their period is around 300 nm, which does not correspond to the structure period. The origin of these fringes is not clearly understood, but they often occur in many near-ﬁeld experiments. It can correspond to interference between the incident ﬁeld and diffracted ﬁelds along the sample surface or to feedback defects. However, we can note a slight modulation of the fringes, due to the presence of coaxial structure. By a simple Fourier ﬁltering of the optical image the parasitical fringes can be suppressed and the result is presented in Fig. 6 c and d (image d is a numerical enlargement of the zone marked by a white square in image c). On these ﬁltered images, the near- ﬁeld structure is now resolved. It shows a periodic array of ‘‘coffee-beans’’. The measured period in the ﬁltered optical image exactly corresponds to the period measured by AFM. The characteristic two-lobes structure (‘‘coffee-bean’’) of the near-ﬁeld above the apertures can be completely theoretically explained. For comparison we calculated the optical near-ﬁeld above the AAA structure (Fig. 6 f), when it is illuminated by Fig. 7. Theoretical transmission through an AAA on a 150 nm thick silver layer vs. wavelength (the coaxes diameters are 100/200 nm and the period is 500 nm). Fig. 7. Theoretical transmission through an AAA on a 150 nm thick silver layer vs. 5. Near-ﬁeld optical images The experimental polarization is not well controlled because of the propagation through the tapered optical ﬁber. The annular structure of the ﬁeld does not appear in the theoretical image because the high frequencies of the near-ﬁeld are strongly attenu- ated by the propagation from the sample surface to the tip apex. In the experiments, the images are degraded by the same effect and by a convolution effect created by the tip geometry, which is not an exact point detector. the outer-ring diameter 330 nm (see AFM picture in Fig. 1 b). The theoretical transmission of these coaxes is shown in Fig. 5: we worked around 630 nm because the transmission at this wavelength is close to zero and we recorded near-ﬁeld optical images in reﬂection mode. Fig. 6 shows indeed the used set-up (Fig. 6 e) and different near-ﬁeld images of the studied structure (Fig. 6 b–d). The images were recorded with a commercial scanning tunneling optical microscope used in a reﬂection mode (RSTOM) [26]. The sample is illumi- nated with a He–Ne laser at 632.8 nm thanks to a dielectric tip (around 100 nm diameter) and the back- ward signal is also recorded by the way of the tip. A coupler allows us to separate both signals and the reﬂected intensity is recorded by a photomultiplier (PM) and a computer. The computer controls the scanning and the feedback of the RSTOM as well. The microscope head contains piezo actuators which move the tip in the three directions with a nanometric spatial step. This head also includes a stand alone ‘‘shear-force’’set-up [27]: the tip, glued on a tuning fork, is dithered at 32 kHz and the amplitude of its oscillations is directly connected to the tip-sample distance, which leads to a feedback signal, i.e., to the sample topography. The microscope head works in constant distance mode. References [19] A. Perentes, I. Utke, B. Dwir, M. Leutenegger, T. Lasser, P. Hoffmann, F. Baida, M.-P. Bernal, M. Roussey, J. Salvi, D. Van Labeke, Fabrication of arrays of sub-wavelength nano-apertures in an optically thick gold layer on glass slides for optical studies, Nanotechnology 16 (2005) S273–S277. [1] T. Ebbesen, H. Lezec, H. Ghaemi, T. Thio, P. Wolff, Extra- ordinary optical transmission through sub-wavelength hole arrays, Nature 391 (1998) 667–669. [2] H. Ghaemi, T. Thio, D. Grupp, T. Ebessen, H. Lezec, Surface plasmons enhance optical transmission through sub-wavelength holes, Phys. Rev. B 58 (1998) 6779–6782. [20] J.-P. Berenger, A perfectly matched layer for the absorption of electromagnetic waves, J. Comput. Phys. 114 (1994) 185–200. [3] T. Thio, H. Lezec, T. Ebbesen, Strongly enhanced optical transmission through subwavelength holes in metal ﬁlms, Phy- sica B 279 (2000) 90–93. [21] J. Seidel, F.I. Baida, L. Bischoff, B. Guizal, S. Grafstrom, D. Van Labeke, L.M. Eng, Coupling between surface plasmon modes on metal ﬁlms, Phys. Rev. B 69 (2004) 121405. [22] P.B. Johnson, R.W. Christy, Optical constants of the noble metals, Phys. Rev. B 12 (1972) 4370–4379. [4] L. Martin-Moreno, F.J. Garcı´a-Vidal, H.J. Lezec, K.M. Pellerin, T. Thio, J.B. Pendry, T.W. Ebbesen, Theory of extraordinary optical transmission through subwavelength hole arrays, Phys. Rev. Lett. 86 (6) (2001) 1114–1117. [23] F.I. Baida, D. Van Labeke, Y. Pagani, Body-of-revolution FDTD simulations of improved tip performance for scanning near-ﬁeld optical microscopes, Opt. Commun. 255 (2003) 241– 252. [5] D. Gifford, D. Hall, Emission through one of two metal electro- des of an organic light-emitting diode via surface-plasmon cross coupling, Appl. Phys. Lett. 81 (23) (2002) 4315–4317. [24] A. Taﬂove, S.C. Hagness, Computational Electrodynamics, the Finite-Difference Time-Domain Method, second ed., Artech House, Norwood, MA, USA, 2000. [6] S. Shinada, J. Hashizume, F. Koyama, Surface plasmon reso- nance on microaperture vertical-cavity surface-emitting laser with metal grating, Appl. Phys. Lett. 83 (5) (2003) 836–838. [25] A. Mussot, T. Sylvestre, L. Provino, H. Maillotte, Generation of a broadband single-mode supercontinuum in a conventional dispersion shifted ﬁber by use of a subnanosecond microchip laser, Opt. Lett. 28 (19) (2003) 1820–1822. [7] M. Alkaisi, R.J. Blaikie, S.J. McNab, R. Cheung, D.R.S. Cum- ming, Sub-diffraction-limited patterning using evanescent near- ﬁeld optical lithography, Appl. Phys. Lett. 75 (1999) 3560–3562. [26] D. Courjon, J.-M. Vigoureux, M. Spajer, K. Sarayeddine, S. Leblanc, External and internal reﬂection near ﬁeld microscopy: Experiment and results, Appl. Opt. 29 (1990) 3734–3740. 6. Conclusions wavelength (the coaxes diameters are 100/200 nm and the period is 500 nm). [10] S. Garrett, L. Smith, W. Barnes, Fluorescence in the presence of metallic hole arrays, J. Mod. Opt. 52 (8) (2005) 1105–1122. gold, a super-transmission (80%) for visible wave- lengths is reached as shown on Fig. 7. The near-ﬁeld structure is also important for some applications (lithography, ﬂuorescence, second harmonic genera- tion). For a better comparison between theory and experiment, a better knowledge of the experimental parameters will be necessary. In following experiments, we must improve the shear-force control in order to stabilize the tip apex at a closer distance from the sample surface. Moreover, a metal coated tip with a smaller aperture must be used to increase the resolution of near-ﬁeld images. In our FDTD calculation, we must introduce a realistic tip model in order to try to describe the effects induced by the tip on the near-ﬁeld images (polarization, tip shape, coupling between the tip and the sample). [11] A. Brolo, R. Gordon, B. Leathem, K. Kavanagh, Surface plas- mon sensor based on the enhanced light transmission through arrays of nanoholes in gold ﬁlms, Langmuir 20 (2004) 4813– 4815. [12] F. Baida, D. Van Labeke, Light transmission by subwavelength annular aperture arrays in metallic ﬁlms, Opt. Commun. 209 (2002) 17–22. [13] F. Baida, D. Van Labeke, Three-dimensional structures for enhanced transmission trough a mettalic ﬁlm: Annular aperture arrays, Phys. Rev. B 67 (155314) (2003) 1–7. [14] D. Van Labeke, F. Baida, J.-M. Vigoureux, A new structure for enhanced transmission through a two-dimensional metallic grat- ing, J. Microscopy 213 (2) (2004) 140–143. [15] F. Baida, D. Van Labeke, G. Granet, A. Moreau, A. Belkhir, Origin of the super-enhanced light transmission through a 2-D metallic annular aperture array: a study of photonic bands, Appl. Phys. B 79 (2004) 1–8. [16] W. Fan, S. Zhang, B. Minhas, K. Malloy, S. Brueck, Over 80 % subwavelength transmission in annular coaxial metallic arrays, The Moscone Center West, San Francisco, California, USA, Optical Society of America, CLEO/EQEC-PhAST, 2004. Acknowledgement This research has been supported by the ‘‘Labor- atoire Europe´en Associe´ en Microtechnique Franco- Suisse’’. [17] W. Fan, S. Zhang, B. Minhas, K. Malloy, S. Brueck, Enhanced infrared transmission through subwavelength coaxial metallic arrays, Phys. Rev. Lett. 94 (33902) (2005) 1–4. [18] H. Elsner, H.-G. Meyer, Nanometer and high aspect ratio patterning by electron beam lithography using a simple DUV negative tone resist, Microelectron. Eng. 57–58 (2001) 291–296. References [8] X. Luo, T. Ishihara, Subwavelength photolithography based on surface-plasmon polariton resonance, Opt. Express 12 (14) (2004) 3055–3065. [9] Y. Liu, S. Blair, Fluorescence enhancement from an array of subwavelength metal apertures, Opt. Lett. 28 (7) (2003) 507– 509. [27] K. Karraı¨, R.D. Grober, Piezoelectric tip-sample distance control for near ﬁeld optical microscopes, Appl. Phys. Lett. 66 (14) (1995) 1842–1844.
https://openalex.org/W4246290152	https://malariajournal.biomedcentral.com/track/pdf/10.1186/s12936-021-03638-w	English	null	Hematological Profile of Children With Malaria in Sorong, West Papua, Indonesia	Research Square (Research Square)	2,021	cc-by	9,532	Abstract Background: Malaria remains a major public health problem in Indonesian Papua, with children under five years of age being the most affected group. Haematological changes, such as cytopenia that occur during malaria infec- tion have been suggested as potential predictors and can aid in the diagnosis of malaria. This study aimed to assess the haematological alterations associated with malaria infection in children presenting with signs and symptoms of malaria. Methods: A retrospective study was performed by collecting data from the medical records of malaria patients at Sorong Regional General Hospital, Sorong, West Papua, Indonesia, both from outpatient and inpatient clinics, from January 2014 until December 2017. The laboratory profile of children suffering from malaria was evaluated. Results: One hundred and eighty-two children aged 1 month to 18 years old were enrolled. The subjects were mostly male (112, 61.5%) with a mean age of 6.45 years (SD = 4.3 years). Children below 5 years of age suffered the most from malaria in this study (77, 42.3%). One hundred two subjects (56%) were infected with Plasmodium falcipa- rum. Half of the enrolled subjects (50%) had haemoglobin level (Hb) between 5.1 and 10 gr/dL. A total of 41 children (53.2%) less than 5 years old suffered from P. falciparum infection. In the age group of 5–10 years, there were 34 children (57.6%) who suffered from P. falciparum, and in the age group > 10 years, 27 children (58.7%) suffered from P. falciparum infection. Only 4 subjects (5.2%) in the less than 5 years old age group had mixed malaria infection. Among eight predictors of the haematological profile, there were five predictors that were significantly associated with the diagnostic criteria, namely haemoglobin, haematocrit, leukocytes, platelets and monocytes (p < 0.05). Generally, clini- cal symptoms are not significantly associated with a malaria diagnosis, and only one variable showed a significant relationship, pale, with a P value of 0.001. Conclusions: Children with malaria had changes in some haematological markers, with anaemia, low platelet count, white blood count, and lymphocyte count being the most important predictors of malaria infection in the study area. These markers could be used to raise suspicion of malaria in children living in high endemic areas, such as West Papua. Keywords: Haematological profile, Plasmodium falciparum, Plasmodium vivax, Malaria, West Papua Jiero and Pasaribu Malar J (2021) 20:126 https://doi.org/10.1186/s12936-021-03638-w Jiero and Pasaribu Malar J (2021) 20:126 https://doi.org/10.1186/s12936-021-03638-w Malaria Journal Open Access Syilvia Jiero1 and Ayodhia Pitaloka Pasaribu2* Syilvia Jiero1 and Ayodhia Pitaloka Pasaribu2* Background Malaria is a life-threatening protozoan disease caused by parasites that are transmitted to humans through the bite of infected female Anopheles mosquitoes [1]. The World Health Organization (WHO) estimates that there were 229 million cases of malaria in worldwide 2019, with 409,000 deaths, most of which occurred in Africa, fol- lowed by SouthEast Asia. 67% of all malaria deaths were Correspondence: ayodhia@usu.ac.id 2 Department of Child Health, Medical Faculty, Universitas Sumatera Utara, Dr. Mansur Street No. 5, 20156 Medan, Indonesia Full list of author information is available at the end of the article Correspondence: ayodhia@usu.ac.id 2 Department of Child Health, Medical Faculty, Universitas Sumatera Utara, Dr. Mansur Street No. 5, 20156 Medan, Indonesia Full list of author information is available at the end of the article Correspondence: ayodhia@usu.ac.id 2 Department of Child Health, Medical Faculty, Universitas Sumatera Utara, Dr. Mansur Street No. 5, 20156 Medan, Indonesia Full list of author information is available at the end of the article © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativeco mmons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/ zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Jiero and Pasaribu Malar J (2021) 20:126 Page 2 of 12 Page 2 of 12 in children under 5 year of age. Thus, malaria continues to be viewed as a highly significant disease of global pub- lic health importance [2]. There are six major Plasmo- dium species infecting humans: Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae Plasmodium ovale curtisi, Plasmodium ovale wallikeri and Plasmo- dium knowlesi [3]. Plasmodium falciparum and P. vivax are the two main causes of human malaria infections. Falciparum malaria poses a risk of severe complications and contributes to the majority of deaths [4]. features, climate conditions and extreme poverty pro- vides a suitable environment for malaria transmission, both biologically and socially [9]. in children under 5 year of age. Thus, malaria continues to be viewed as a highly significant disease of global pub- lic health importance [2]. There are six major Plasmo- dium species infecting humans: Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae Plasmodium ovale curtisi, Plasmodium ovale wallikeri and Plasmo- dium knowlesi [3]. Plasmodium falciparum and P. vivax are the two main causes of human malaria infections. Falciparum malaria poses a risk of severe complications and contributes to the majority of deaths [4]. Based on the Ministry of Health of the Republic of Indonesia, Annual Parasite Index (API) for West Papua in 2017 was 15‰ and classified by WHO as hyper-endemic area. Specifically API for Sorong city was 1.5‰ and clas- sified by WHO as meso-endemic area. 1 Location of study area in Sorong, West Papua, Indonesia Jiero and Pasaribu Malar J (2021) 20:126 Jiero and Pasaribu Malar J (2021) 20:126 Page 3 of 12 Page 3 of 12 Study design Inclusion criteria the underlying pathology determines the potential pre- dictors and can aid in the diagnosis, management and prognosis of malaria [25, 26]. It plays a major role in fatality [27, 28]. When compared across different malarial species, haematological parameters count also vary sig- nificantly [29, 30].h • Children in age group 1 month to 18 years. • Children in age group 1 month to 18 years. • Any acute febrile illness lasting for 2–7 days. • Peripheral blood smear or rapid malaria anti- gen test positive for P. vivax and/or P. falciparum malaria. i The prediction of haematologic changes in malaria allows clinicians to establish early and effective therapeu- tic interventions to prevent major complications, espe- cially in nonendemic countries with declining malaria transmission and nonendemic countries [31]. Haema- tologic parameters can help provide a presumption of treatment, especially if the results of parasitological examinations are not immediately available or are uncer- tain to decide malaria treatment [13, 31, 32], and help intensively treat the patient and prevent possible death occurs as a result of these complications [33].h • Complete medical record data. • Complete medical record data. Sample collection Two to three millilitres of venous blood were col- lected from each participant using a 5 ml sterile dispos- able syringe and dispensed into an EDTA anticoagulated test tube, followed by preparation of the thick and thin smears and automated for determination of the complete blood count (CBC). The EDTA test tubes containing the blood samples were gently inverted approximately 8 times to ensure the complete mixture of blood cells. The blood samples were collected by a trained medical labo- ratory scientist. Blood counts were performed using Sys- mex XP 100 Haematology Analyzer. Peripheral blood smear examination Peripheral blood smears were prepared using venous blood samples. Separate slides were used for thick and thin smears. Examination of thin and thick blood films were based on WHO 2010 guidelines [35]. Thick and thin films of peripheral smear (PS) examination blood slides were prepared and stained with Giemsa. Peripheral blood smear examination for the type of malaria parasite was performed systematically under low power, high power and oil immersion using an Olympus CX21 Microscope. • Definition of anaemia was based on WHO guide- lines with different cut off for different agegroup and categorized by different severity [36] . Methods A retrospective study of data from medical records of malaria patients at Sorong Regional General Hospital, Sorong, West Papua, Indonesia Outpatient and Inpa- tient Clinic from January 2014 until December 2017 was performed. It included 182 children from 1 month to 18 years old with signs and symptoms of malaria at Sorong Regional General Hospital, Sorong, West Papua, Indone- sia. Blood samples were collected from children into eth- ylenediaminetetraacetic acid (EDTA) tubes and used to prepare thin and thick blood films, which were then used for Giemsa microscopy to detect malaria parasites and malaria species. Patients’ haematological predictors were determined using an automated haematology analyzer. Study population Th d l The study involved children aged 1 month to 18 years, who were malaria-confirmed by microscopy. Individ- ual data was obtained from medical records. The study included children who were treated as inpatients or out- patients at Sorong Regional General Hospital, Sorong, West Papua, Indonesia from January 2014 until Decem- ber 2017. The study was approved by the Research Ethics Committee of the Medical School of the Universitas of Sumatera Utara. f • Lymphocytopenia in chidren is defined as a total lymphocyte count less than 3.0 × 109/L [37]. The number of confirmed malaria cases microscopically in 2017 was 13,690 cases and for the city of Sorong was 127 cases [10]. In Southeast Asia, Indonesia contributes 9 % of all malaria cases and has the second highest burden of dis- ease after India [5]. The WHO estimated that 27% of the 257,563,815 people in the Indonesian population lives in malaria endemic areas. One of the endemic areas of malaria in Indonesia is Papua [6]. Haematological alterations that are thought to char- acterize malaria are related to the overt biochemical changes that occur during the asexual stage of the life cycle of the malaria parasite [11]. Patients infected with malaria tend to have significantly lower platelet, leuko- cyte, lymphocyte, eosinophil, red blood cell, and hae- moglobin (Hb) counts, while the number of monocytes and neutrophils was significantly higher than that in nonmalaria-infected patients [12–15]. Anaemia [16], leukopenia [17, 18] and thrombocytopenia [19, 20] are commonly seen in P. falciparum infection, probably as a result of the higher levels of parasitaemia found in these patients [21, 22]. Thrombocytopenia is most com- monly seen in malaria infection [14, 23, 24]. People with platelet counts < 150,000/µL are 12–15 times more likely to develop malaria infection than people with a platelet count > 150,000/µL [14]. Pancytopenia and bicytopenia are common haematological problems encountered in clinical practice [12, 13] that have multiple causes, and West Papua is an Indonesian province located on the western tip of Papua Island, which capital city is Manok- wari. The area of the province is about 99671,63 km2 covering the bird’s head area of Papua island and the sur- rounding islands [7]. Geographically, Sorong city (Fig. 1) is located at the coordinates 131° 51′ East Longitude and 0° 54′ South Latitude with an area of 1105 km2 with pop- ulation density about 365 persons per square kilometre consisting of 30 districts and 26 sub-districts. The popu- lation in Sorong city is about 239,815 people in 2017 with the number of villages in about 226 villages and 11 com- munity health centres [8]. As many as 70–75% of Papu- ans live in rural areas. The combination of geographic Fig. 1 Location of study area in Sorong, West Papua, Indonesia Fig. 1 Location of study area in Sorong, West Papua, Indonesia Fig. Exclusion criteria • No malaria found from either rapid diagnostic test (RDT) or microscopic examination. • No malaria found from either rapid diagnostic test (RDT) or microscopic examination. The gold standard for malaria examination is micro- scopic slide examination [34]. Knowledge of changes in various haematological parameters in children suffer- ing from malaria can increase the diagnosis of malaria by increasing suspicion of malaria and encouraging a careful search for parasitaemia using a microscope [25]. There has been no research to investigate the effects of malaria on the haematological profile of Indonesian Pap- uan children. • Definition of anaemia was based on WHO guide- lines with different cut off for different agegroup and categorized by different severity [36] . • Lymphocytopenia in chidren is defined as a total lymphocyte count less than 3.0 × 109/L [37]. Definitions • Definition of anaemia was based on WHO guide- lines with different cut off for different agegroup and categorized by different severity [36] . f • Lymphocytopenia in chidren is defined as a total lymphocyte count less than 3.0 × 109/L [37]. Jiero and Pasaribu Malar J (2021) 20:126 Page 4 of 12 Table 1 Characteristics and hematological profile of subjects with malaria Characteristics n = 182 Sex, n (%) Male 112 (61.5) Female 70 (38.5) Age, mean (SD), years 6.45 (4.30) Age group > 10 years 46 (25.3) 5–10 years 59 (32.4) < 5 years 77 (42.3) Weight, mean (SD), kg 18.95 (11.27) Type of malaria Plasmodium vivax 76 (41.8) Plasmodium falciparum 102 (56) Mixed malaria 4 (2.2) Hemoglobin, n (%) > 10 gr/dL 77 (42.3) 5.1–10 gr/dL 91 (50) ≤ 5 gr/dL 14 (7.7) Leukocytes, n (%) > 11,000 35 (19.2) 6000–11,000 73 (40.1) < 6000 74 (40.7) Platelets, n (%) > 100.000 126 (69.2) ≤ 100.000 56 (30.8) Anemia, n (%) Yes 140 (76.9) No 42 (23.1) Anemia grade, n (%) No anemia 42 (23.1) Mild 27 (14.8) Moderate 68 (37.4) Severe 45 (24.7) Leucopenia, n (%) Yes 31 (17) No 151 (83) Monocytosis, n (%) Yes 53 (29.1) No 129 (70.9) Lymphocytopenia, n (%) Yes 120 (65.9) No 62 (34.1) Thrombocytopenia, n (%) Yes 97 (53.3) No 85 (46.7) Hepatomegaly, n (%) Yes 41 (22.5) No 141 (77.5) Splenomegaly, n (%) Yes 34 (18.7) Table 1 Characteristics and hematological profile of subjects with malaria • Leukopenia was defined as white blood cells (WBCs) < 4 × 103/µl [29].i • Monocytosis was defined as an absolute monocyte count > 3 × 103/µl [37].hi • Thrombocytopenia was defined as platelet count < 150 × 103/µl [29]. • Categorization of malaria into uncomplicated and severe forms [38].i • Severe malaria (SM) was defined by the presence of asexual parasitaemia in addition to at least one or more of the following WHO [39, 40]. The criterias for severe malaria follows the 2010 WHO guidelines [41].i • Uncomplicated malaria (UM) was defined as the presence of symptoms and/or signs of malaria and a positive parasitologic test in the absence of evidence of end organ damage [40]. Statistical analysish The data are presented as the means, percentages, stand- ard deviations, medians, and ranges. Statistical analysis was performed using ANOVA, the Kruskal-Wallis test, contingency coefficient correlation, the Mann-Whitney U test, and the independent t-test. The data were ana- lysed using SPSS version 21 statistical software with appropriate statistical methods. Differences with P-val- ues of less than 0.05 were considered significant. Characteristics and haematological profile of research subjectsh falciparum Mixed malaria p-value < 5 years 32 (41.6) 41 (53.2) 4 (5.2) 0.226 5–10 years 25 (42.4) 34 (57.6) 0 (0) > 10 years 19 (41.3) 27 (58.7) 0 (0) elimination efforts since 2000, resulting in a global reduction of 40% in morbidity and 60% in mortality [42]. Many efforts have been made to minimize malaria transmission worldwide; however, this infection remains high among humans [43]. All species of Plas- modium have been documented in Indonesia. Plasmo- dium vivax is the predominant species except in Papua where P. falciparum slightly predominates [5, 44, 45]. Table 1 (continued) Characteristics n = 182 No 148 (81.3) Table 2 Results of malaria diagnosis by age group Contingency coefficient correlation Age group, n (%) P. vivax P. falciparum Mixed malaria p-value < 5 years 32 (41.6) 41 (53.2) 4 (5.2) 0.226 5–10 years 25 (42.4) 34 (57.6) 0 (0) > 10 years 19 (41.3) 27 (58.7) 0 (0) Table 2 Results of malaria diagnosis by age group Table 2 Results of malaria diagnosis by age group Age group, n (%) P. vivax P. falciparum Mixed malaria p-value* Plasmodium falciparum is the most prevalent malaria parasite in the WHO African region, accounting for 99.7% of estimated malaria cases in 2017, as well as in the WHO regions of South-East Asia Region (62.8%), the Eastern Mediterranean (69%) and the Western Pacific (71.9%). Plasmodium vivax is the predominant parasite in the WHO region of the Americas (74.1%) [42]. Plasmodium vivax contributed 4% of the total global cases in 2015, but outside Africa the proportion was 41% among all malaria infections. Its high burden of disease is maintained in part due to dormant liver stage parasite forms known as hypnozoites which can induce clinical relapse episodes [46]. were significantly more common in P. falciparum as comparedto P. vivax infection in uncomplicated malaria (Table 5). Discussion Malaria is a preventable and treatable condition and remains the most important parasitic disease globally [6]. In 2017, it was still endemic in 80 countries, plac- ing 3.7 billion people at risk. Considerable progress has been made due to aggressive malaria control and In the present study, there were more male patients infected with malaria than female patients, which is similar to the results of a study in South Sorong [47]. One hundred two subjects (56%) were infected with P. Table 3 Hematology profile based on age group Hematology profile < 5 years 5–10 years > 10 years Hemoglobin (g/dL), mean (SD) 8.71 (2.92) 9.51 (2.62) 9.73 (2.09) Hematocrit (%), mean (SD) 27.81 (9.10) 30.38 (8.42) 30.99 (6.99) Erythrocytes (x 106/µL), median (range) 4.17 (1.33–8.05) 4.27 (1.75–7.11) 4.16 (2.55–5.69) Leukocytes (x 103/µL), median (range) 8.1 (1.9-29.17) 5.89 (2-20.4) 5.50 (2-17.9) Platelets (x 103/µL), median (range) 168 (29–718) 154 (13–391) 105 (41–470) Neutrophil (x 103/µL), median (range) 51.1 (23.2–89.9) 48.7 (26–84,5) 54.15 (25.9–88) Lymphocytes (x 103/µL), median (range) 38.8 (4.7–77.9) 41.2 (12.3–88.5) 35.7 (9.8–82.4) Monocytes (x 103/µL), median (range) 7.5 (2-64.3) 7.8 (2.8–27.2) 8.35 (2.9–28.5) Table 3 Hematology profile based on age group Hematology profile < 5 years 5–10 years > 10 years Hemoglobin (g/dL), mean (SD) 8.71 (2.92) 9.51 (2.62) 9.73 (2.09) Hematocrit (%), mean (SD) 27.81 (9.10) 30.38 (8.42) 30.99 (6.99) Erythrocytes (x 106/µL), median (range) 4.17 (1.33–8.05) 4.27 (1.75–7.11) 4.16 (2.55–5.69) Leukocytes (x 103/µL), median (range) 8.1 (1.9-29.17) 5.89 (2-20.4) 5.50 (2-17.9) Platelets (x 103/µL), median (range) 168 (29–718) 154 (13–391) 105 (41–470) Neutrophil (x 103/µL), median (range) 51.1 (23.2–89.9) 48.7 (26–84,5) 54.15 (25.9–88) Lymphocytes (x 103/µL), median (range) 38.8 (4.7–77.9) 41.2 (12.3–88.5) 35.7 (9.8–82.4) Monocytes (x 103/µL), median (range) 7.5 (2-64.3) 7.8 (2.8–27.2) 8.35 (2.9–28.5) Table 4 Comparison of hematology profiles with different malaria species a Kruskal-Wallis, bANOVA Hematology profile P. vivax P. Characteristics and haematological profile of research subjectsh This study included 182 subjects who met the inclusion and exclusion criteria. The subjects were mostly male (112, 61.5%) with a mean age of 6.45 years (SD = 4.3 years). Chil- dren < 5 years accounted for the majority of the cases, (77, 42.3%). A total of 102 subjects (56%) were infected with P. falciparum. Some subjects (50%) had a Hb level between 5.1 and 10 gr/dL. The results of the haematological profile examination of the subjects are presented in Table 1 below. Forty-one subjects who were less than five years old suffered from P. falciparum infection (53.2%). Only four subjects (5.2%) less than five years old had mixed infec- tions (Table 2). Table 3 shows the haematological pro- files based on the age group of the study subjects. Of the eight predictors in the haematological profile, there are five predictors that were significantly associated with the diagnostic criteria, namely haemoglobin, haematocrit, leukocytes, platelets and monocytes (p < 0.05) (Tables 4). Anemia (p < 0.001) andthrombocytopenia (p = 0.011) This study included 182 subjects who met the inclusion and exclusion criteria. The subjects were mostly male (112, 61.5%) with a mean age of 6.45 years (SD = 4.3 years). Chil- dren < 5 years accounted for the majority of the cases, (77, 42.3%). A total of 102 subjects (56%) were infected with P. falciparum. Some subjects (50%) had a Hb level between 5.1 and 10 gr/dL. The results of the haematological profile examination of the subjects are presented in Table 1 below.i Forty-one subjects who were less than five years old suffered from P. falciparum infection (53.2%). Only four subjects (5.2%) less than five years old had mixed infec- tions (Table 2). Table 3 shows the haematological pro- files based on the age group of the study subjects. Of the eight predictors in the haematological profile, there are five predictors that were significantly associated with the diagnostic criteria, namely haemoglobin, haematocrit, leukocytes, platelets and monocytes (p < 0.05) (Tables 4). Anemia (p < 0.001) andthrombocytopenia (p = 0.011) Page 5 of 12 Jiero and Pasaribu Malar J (2021) 20:126 were significantly more common in P. falciparum as comparedto P. vivax infection in uncomplicated malaria (Table 5). Table 1 (continued) Characteristics n = 182 No 148 (81.3) Table 2 Results of malaria diagnosis by age group Contingency coefficient correlation Age group, n (%) P. vivax P. Discussion falciparum Mixed malaria p-value Hemoglobin (g/dL), median (IQR) 10.25 (8.73–11.48) 8.70 (6.80–11.05) 6.05 (3.25–12.15) 0.018a Hematocrit (%), median (IQR) 31.31 (8.066) 28.33 (8.27) 22.45 (13.99) 0.016b Erythrocytes (x 106/µL), median (IQR) 4.34 (3.99–4.76) 3.89 (3.19–4.76) 3.42 (1.81–5.49) 0.059a Leukocytes (x 103/µL), median (IQR) 7.2 (5.1–10.150) 5.55 (3.953–8.43) 11.4 (6.28–14.95) 0.006a Platelets (x 103/µL), median (IQR) 189 (106–236.5) 118.5 (817.5–175.75) 186.5 (74.75–226.25) 0.01a Neutrophil (x 103/µL), median (IQR) 53.15 (39.53–66.70) 49.65 (38.35–67.43) 50.95 (44.00–61.88) 0.942a Lymphocytes (x 103/µL), median (IQR) 38.35 (27.05–52.00) 40.40 (24.28–50.80) 41.25 (30.45–46.28) 0.910a Monocytes (x 103/µL), median (IQR) 6.60 (4.55–11.83) 8.60 (6.15–12.65) 7.80 (3.18–9.73) 0.031a Table 3 Hematology profile based on age group Table 4 Comparison of hematology profiles with different malaria species a Kruskal-Wallis, bANOVA Hematology profile P. vivax P. falciparum Mixed malaria p-value Hemoglobin (g/dL), median (IQR) 10.25 (8.73–11.48) 8.70 (6.80–11.05) 6.05 (3.25–12.15) 0.018a Hematocrit (%), median (IQR) 31.31 (8.066) 28.33 (8.27) 22.45 (13.99) 0.016b Erythrocytes (x 106/µL), median (IQR) 4.34 (3.99–4.76) 3.89 (3.19–4.76) 3.42 (1.81–5.49) 0.059a Leukocytes (x 103/µL), median (IQR) 7.2 (5.1–10.150) 5.55 (3.953–8.43) 11.4 (6.28–14.95) 0.006a Platelets (x 103/µL), median (IQR) 189 (106–236.5) 118.5 (817.5–175.75) 186.5 (74.75–226.25) 0.01a Neutrophil (x 103/µL), median (IQR) 53.15 (39.53–66.70) 49.65 (38.35–67.43) 50.95 (44.00–61.88) 0.942a Lymphocytes (x 103/µL), median (IQR) 38.35 (27.05–52.00) 40.40 (24.28–50.80) 41.25 (30.45–46.28) 0.910a Monocytes (x 103/µL), median (IQR) 6.60 (4.55–11.83) 8.60 (6.15–12.65) 7.80 (3.18–9.73) 0.031a Table 4 Comparison of hematology profiles with different malaria species Jiero and Pasaribu Malar J (2021) 20:126 Page 6 of 12 Table 5 Comparison of characteristics with different species of malaria a Contingency coefficient correlation b Characteristics of subjects P. vivax P. About 42.3% of malaria cases in our study was among children < 5 year old. According to WHO data in 2017, they are the most vulnerable group affected by malaria. They accounted for 61% (266,000) of all malaria deaths worldwide [42]. Discussion Jiero and Pasaribu Malar J (2021) 20:126 Page 7 of 12 Jiero and Pasaribu Malar J (2021) 20:126 Page 7 of 12 There are various hypotheses about thrombocytope- nia that occurs in malaria infections. Thrombocytopenia seems to occur through peripheral damage [65], excessive removal of platelets by spleen pooling [66, 67] and plate- let consumption by the process of disseminated intravas- cular coagulopathy (DIC) [68]. Sufficient or increased numbers of megakaryocytes in the bone marrow affect the decrease in thrombopoiesis, which is a possible cause of thrombocytopenia in malaria [66]. The destruc- tion of circulating platelets mediated by immunity has been postulated as the cause of thrombocytopenia seen in malaria infections. Platelets have also been shown to mediate clumping of erythrocytes infected with P. falci- parum [69]. This can cause apparent thrombocytopenia. Patients infected with malaria experience increased lev- els of specific immunoglobulin G (IgG) in the blood that binds to malaria antigens bound to platelets, which may lead to acceleration of platelet destruction [23]. Previ- ous studies revealed that platelet aggregation, which is the clumping of platelets, was incorrectly calculated as a single platelet by the analyzer, causing pseudothrom- bocytopenia [13]. In addition, during malaria infection, endothelial activation is activated and can contribute to the loss of endothelium barrier function and organ dys- function. This process can use released platelets and pro- teins as important regulators of endothelial permeability, resulting in thrombocytopenia [70]. However, thrombo- cytopenia in malaria infection has also been associated with sequestration and pooling of platelets in the spleen, immune-mediated destruction of circulating platelets, and platelets mediating the clumping of P. falciparum- infected erythrocytes, leading to pseudothrombocytope- nia [13, 63, 69].h Cytopenia is a disorder in which the production of one or more blood cell types ceases or is greatly reduced. The types of cytopenia are anaemia, which is a reduction in red blood cells (RBCs); leukopenia, which is a reduc- tion in WBCs; neutropenia (neutrophils make up over half of all WBCs), which is a deficiency in neutrophils; and thrombocytopenia, which is deficiency in platelets. Bicytopenia is defined as a condition in which two out of three cell lines (RBCs, WBCs, and platelets) are reduced. The simultaneous reduction in all three formed cell lines is termed pancytopenia [49]. Discussion These kinds of cytopenias are not uncommon in malaria; bone marrow diagnosis of adults with bicytopenia and pancytopenia has shown that 3% of bicytopenia and 6% of pancytopenia were caused by malaria [50, 51]. Anaemia is also a common manifestation, particularly in infants with P. vivax and in children with P. knowlesi infection [52–54]. Anaemia is one of the most common complications in malaria infection, especially in younger children and pregnant women in high transmission areas [55, 56].h The pathogenesis of anaemia during malaria infection is not clearly understood. However, it is estimated that the main targets of parasites are RBCs, which results in damage to RBCs, acceleration of parasite growth and nonparasitic removal [57], bone marrow dysfunc- tion [58], and the level of parasitaemia [59]. Anaemia in malaria, however, is associated with a combination of haemolysis of parasitized RBCs, accelerated removal of both parasitized and unparasitized RBCs, depressed and ineffective erythropoiesis due to tumor necrosis factor alpha, anaemia of chronic disease, and splenic phagocy- tosis or pooling [60–62].h This study showed that haematological abnormalities in children with malaria infection are common. Some sub- jects (50%) had a Hb level between 5.1 and 10 gr/dL. The prevalence of anaemia in This study was 77.4%; 14.8% of subjects had mild anaemia, 35.7% had moderate anae- mia, and 26.9% had severe anaemia. The rate of anaemia in children < 5 years old was higher than that in children 5–10 years old and > 10 years old, with a mean Hb of 8.71 gr/dL. Data from household surveys conducted in 25 high-burden African countries between 2015 and 2019 show that, among children < 5 years who tested positive for malaria, the prevalence of moderate to severe anae- mia was between 9–76.3% [2]. A laboratory trial study of 30 patients in Iran observed significantly lower values of Hb/dL, haematocrit (Ht)%, mean corpuscular volume (MCV)/ fl. and mean corpuscular haemoglobin (MCH)/ µl, WBC/ µl, and platelet/ µl among malaria-infected children compared to healthy children [13, 15, 63, 64]. Our findings were consistent with these previous reports. Thrombocytopenia was seen in 97 children (53.3%) and was highly significant in the age group > 10 years, with a median 105 × 103/µL in this study. It is found mostly in P. falciparum infection, as many as 65 (35.7%). Thrombocytopenia was observed in malaria-infected children in this study, which is consist- ent with earlier reports [13, 63]. Discussion falciparum Mixed malaria p-value Sex, n (%) Male 49 (26.9) 60 (33) 3 (1.6) 0.637a Female 27 (14.8) 42 (23.1) 1 (0.5) Age (years), median (range) 6.67 (0.33-14) 6 (0.08–15.67) 1.88 (1.42–3) 0.059b Age group, n (%) < 5 years 32 (17.6) 41 (22.5) 4 (2.2) 0.226a 5–10 years 25 (13.7) 34 (18.7) 0 (0.0) > 10 years 19 (10.4) 27 (14.8) 0 (0.0) Weight (kg), mean (SD) 18.71 (11.77) 19.49 (10.99) 9.7 (0.36) 0.069b Hemoglobin, n (%) ≤ 5 g/dL 3 (1.6) 9 (4.9) 2 (1.1) 0.005a 5.1–10 g/dL 34 (18.7) 56 (30.8) 1 (0.5) > 10 g/dL 39 (21.4) 37 (20.3) 1 (0.5) Leukocytes, n (%) < 6000 g/dL 23 (12.6) 50 (27.5) 1 (0.5) 0.065a 6000–11.000 g/dL 36 (19.8) 36 (19.8) 1 (0.5) > 11.000 g/dL 17 (9.3) 16 (8.8) 2 (1.1) Platelets, n (%) ≤ 100.000 g/dL 18 (9.9) 37 (20.3) 1 (0.5) 0.192a > 100.000 g/dL 58 (31.9) 65 (35.7) 3 (1.6) Anemia, n (%) Yes 54 (29.7) 83 (45.6) 3 (1.6) 0.270a No 22 (12.1) 19 (10.4) 1 (0.5) Thrombocytopenia, n (%) Yes 31 (17) 65 (35.7) 1 (0.5) 0.005a No 45 (24.7) 37 (20.3) 3 (1.6) Grading anemia, n (%) No anemia 22 (12.1) 19 (10.4) 1 (0.5) 0.256a Mild 12 (6.6) 15 (8.2) 0 (0) Moderate 30 (16.5) 37 (20.3) 1 (0.5) Severe 12 (6.6) 31 (17.0) 2 (1.1) Severe malaria, n (%) Yes 9 (4.9) 13 (7.1) 2 (1.1) 0.087a No 67 (36.8) 89 (48.9) 2 (1.1) Hepatomegaly, n (%) Yes 9 (4.9) 31 (17.0) 1 (0.5) 0.021a No 67 (36.8) 71 (39.0) 3 (1.6) Splenomegaly, n (%) Yes 7 (3.8) 26 (14.3) 1 (0.5) 0.014a No 69 (37.9) 76 (41.8) 3 (1.6) Table 5 Comparison of characteristics with different species of malaria Mixed malaria About 42.3% of malaria cases in our study was among children < 5 year old. According to WHO data in 2017, they are the most vulnerable group affected by malaria. They accounted for 61% (266,000) of all malaria deaths worldwide [42]. falciparum. This study also shows that the most com- mon type of Plasmodium infection in Sorong, West Papua, is P. falciparum. This is similar with other prov- inces in Indonesia and in Manokwari, West Papua, P. falciparum is the predominant malaria species [45, 48]. Discussion There were both quali- tative and quantitative changes in platelet abnormalities in malaria. Platelet counts were significantly reduced in children infected with malaria. A study conducted in Thailand–Myanmar border showed that thrombocytope- nia occured. This observation may imply that thrombo- cytopenia can be a marker of Plasmodium infection [13, 71–73]. In the present study overall, when compared between malaria species in uncomplicated cases, Hb and plate- let value in the P. falciparum infection was lower than P. vivax infection as well as the platelet value (Table 6) with p value 0.001. These figures were in good agree- ment with studies done by Latif et al. showing P. Jiero and Pasaribu Malar J (2021) 20:126 Page 8 of 12 Table 6 Comparison of hematological profile between different malaria species Kruskal-Wallis Hematology profile Uncomplicated Malaria p-value* Complicated Malaria p-value* P. vivax P. falciparum Mixed malaria P. vivax P. falciparum Mixed malaria Hemoglobin (g/dL), median (IQR) 10.30 (8.80– 11.40) 8.90 (6.85–11.15) 3.30 (3.20) 0.001 8.70 (4.15–12.10) 8.20 (6.20–9.95) 11.0 (8.70) 0.340 Hematocrit (%), median (IQR) 32.0 (28.0–38.0) 28.40 (22.05– 35.0) 11.30 (11.0) 0.001 25.0 (12.55– 33.90) 26.50 (21.80– 33.20) 33.60 (26.90) 0.322 Erythrocytes (x 106/µL), median (IQR) 4.38 (4.06–4.77) 3.89 (3.18–4.74) 1.88 (1.75) 0.001 3.77 (1.87–4.51) 3.90 (3.14–4.89) 5.27 (4.84) 0.124 Leukocytes (x 103/µL), median (IQR) 7.30 (4.90–10.20) 5.50 (4.05–8.15) 11.40 (8.0) 0.007 7.10 (5.95–11.0) 6.70 (3.30–16.95) 10.35 (5.70) 0.904 Platelets (x 103/ µL), median (IQR) 189.0 (106.0– 233.0) 120.0 (89.50– 175.50) 204.0 (173.0) 0.011 218.0 (78.0– 354.0) 109.0 (68.50– 197.0) 121.0 (42.0) 0.352 Neutrophil (x 103/µL), median (IQR) 51.60 (39.60– 64.90) 50.40 (38.70– 67.25) 44.80 (43.20) 0.810 58.90 (34.60– 68.50) 48.90 (28.80– 69.70) 59.75 (55.50) 0.555 Lymphocytes (x 103/µL), median (IQR) 38.70 (28.70– 52.0) 40.50 (24.40– 48.95) 45.70 (44.70) 0.568 34.10 (25.65– 52.10) 37.80 (23.15– 67.80) 32.90 (28.0) 0.785 Monocytes (x 103/µL), median (IQR) 6.60 (4.50–12.30) 8.50 (6.25–11.90) 9.45 (8.90) 0.092 7.20 (4.90–8.20) 11.60 (5.25– 20.60) 4.35 (2.0) 0.108 Table 6 Comparison of hematological profile between different malaria species parison of hematological profile between different malaria species the P. vivax parasite resistant to chloroquine in recent years is one of the main triggers of the new severe vivax malaria [82]. All these variables make the risk and spec- trum of malaria complications different around the world [83–85]. falciparum-associated anaemia and thrombocytopenia compared to P. vivax infection, (8.1 ± 2.2 vs. 11 ± 3.2 g/ dL and 60.338 ± 50.6 × 103/µL vs. Discussion that an increase in Jiero and Pasaribu Malar J (2021) 20:126 Page 9 of 12 Table 7 Comparison of malaria symptoms and species of parasites Contingency coefficient correlation Symptoms P. vivax P. falciparum Mixed malaria p-value Fever, n (%) 75 (98.7) 102 (100.0) 4 (100.0) 0.469 Anorexia, n (%) 51 (67.1) 73 (71.6) 3 (75.0) 0.793 Asthenia, n (%) 48 (63.2) 72 (70.6) 3 (75.0) 0.549 Myalgia/ arthralgia, n (%) 47 (61.8) 72 (70.6) 3 (75) 0.444 Nausea, n (%) 50 (65.8) 60 (58.8) 1 (25.0) 0.211 Pale, n (%) 24 (31.6) 59 (57.8) 3 (75.0) 0.001 Abdominal pain, n (%) 25 (32.9) 42 (41.2) 1 (25) 0.462 Headache, n (%) 28 (36.8) 39 (38.2) 0 (0.0) 0.298 Chills, n (%) 15 (19.7) 20 (19.6) 0 (0.0) 0.614 Sweating, n (%) 8 (10.5) 11 (10.8) 0 (0.0) 0.787 Jaundice, n (%) 0 (0.0) 1 (1.0) 0 (0.0) 0.674 Table 7 Comparison of malaria symptoms and species of parasites transmission areas, high and repeated exposure to par- asites has an impact on the acquisition of immunity, resulting in a high proportion of asymptomatic infec- tions, particularly in older children and adults [93]. Leukocyte value in P. falciparum (5.55 × 103/µL) was lower than in P. vivax infection (7.2 × 103/µL). Simi- lar outcome was also reported in a study conducted by Latif et al. showing leukocyte in P. falciparum (8,906 ± 1.06 × 103/µL) compared to P. vivax infection (11,868 ± 2.34 × 103/µL) was lower [21]. This was in contrast to the findings reported by Ullah et al.., which showed that leukocyte in P. vivax (8.7 ± 4.5 × 103/ µL) was lower than in P. falciparum infection (10.4 ± 11.4 × 103/µL) [29].h There are several limitations in this study. First, this was a retrospective study. Some data of the haemato- logical and microscopic results retrieved from medical records were not provided. Second, there was no control group in this study, therefore association between hae- matological markers in malaria and non-malaria infected groups could not be stated. This study showed lymphocytopenia in 97 children (53.3%). The study has further revealed that there were no statistically significant differences in granulocyte and lymphocyte counts between malaria-infected and noninfected children, and these findings are in agree- ment with many earlier reports [13–15, 57, 72, 86–88] but disagree with the findings of George and Ewelike- Ezeani [63]. Discussion 77.907 ± 78.4 × 103/µL, respectively) [21]. A study by Hyder et al. also found the same thing with the following results 10.1921 ± 0.33157 g/ dL vs. 11.3306 ± 0.29730 g/dL and 88.0239 ± 1.17476/µL x 103/µL vs. 98.1763 ± 0.99502 × 103/µL [30]. Price et al. found that P. vivax infection associated with severe and fatal malaria particularly in young children in Timika, Papua [82]. Otherwise, severe malaria was found more in falciparum malaria cases (7.1%) than in vivax malaria (4.9%) and mixed malaria (1.1%). This study still has shortcomings where there are no data on the number of parasites and chloroquine resistance.h On the contrary, studies, such as Goyal et al. [74], Nad- wani et al. [75], Sajjanar et al. [76], George and Alexander [77], Rodriguez-Monrale et al. [78] have shown P. vivax- associated anaemia and thrombocytopenia. Ullah et al. showed something different where P. falciparum-associ- ated anaemia (9.9 ± 4.48 g/dL vs. 10.7 ± 2.36 g/dL) and P. vivax-associated thrombocytopenia (135.8 ± 89.4 × 103/ µL vs. 222 ± 118.7 × 103/µL) [29]. This study has shown, however, that there was no significant difference in total white blood cell count in malaria-infected children. Leukopenia was seen in only 17% of children. A study by Maina et al. also showed that there was no significant difference in the total white blood cell count in malaria-infected chil- dren compared to control subjects [13]. The differ- ence in values can be related to environmental factors, socioeconomic status, or malaria immunity, among other factors [14, 57, 86]. Different views have been expressed on the total WBCs in subjects infected with malaria because leukopenia has been reported by sev- eral authors [14, 63, 73], and leukocytosis has also been documented by other authors [13, 15, 65]. In the recent years, there have been reported many severe vivax malaria cases [75, 76, 79]. The current dogma has been that P. falciparum can be severe and life-threatening, whereas P. vivax tends to be mild [80]. However, there is currently growing evidence that P. vivax can cause significant morbidity and even mortality in endemic areas [81]. Malaria severity is a function of parasite virulence, degree of parasitaemia, sequestration and host immune competence which in turn depends on factors, namely. age, regional transmission intensity, nutritional status and genetic susceptibility [82–86]. Another hypothesis of Price et al. Abbreviations Hb: Haemoglobin; WHO: World Health Organization; API: Annual parasite index; EDTA: Ethylenediaminetetraacetic acid; CBC: Complete blood count; PS: Peripheral smear; WBCs: White blood cells; UM: Uncomplicated malaria; Ht: Haematocrit; MCV: Mean corpuscular volume; MCH: Mean corpuscular haemoglobin; RBCs: Red blood cells; DIC: Disseminated intravascular coagu- lopathy; SM: Severe malaria; RDT: Rapid diagnostic test. Discussion In some cases of acute malaria, however, lymphocytopenia has been reported, but this has been associated with redistribution of lymphocytes with sequestration in the spleen [89, 90].i Conclusions Ch ld f Children infected with malaria revealed changes in some haematological markers, with anaemia, low platelet counts, white blood counts, and lymphocyte counts being the most important predictors of malaria infection in our study area. Children living in malaria high endemic areas such as West Papua who appear with acute febrile illness and either thrombocytopenia alone or in combination with anaemia should be suspected for malaria, therefore, RDT or microscopic examination must be performed. These haematological markers could raise the suspicion of malaria in this area. Generally, clinical symptoms are not significantly associated with a malaria diagnosis, and only one vari- able shows a significant relationship, pale, with a p value of 0.001 (Table 7). The first symptoms of malaria are nonspecific and characterized by headache, fatigue, abdominal discomfort, and muscle and joint aches, fol- lowed by fever, chills, perspiration, anorexia, vomiting and worsening malaise. These features often lead to overdiagnosis of malaria in developing countries, where diagnosis is frequently based only on clinical judgment with limited resources for parasitological testing [91]. Hb: Haemoglobin; WHO: World Health Organization; API: Annual parasite index; EDTA: Ethylenediaminetetraacetic acid; CBC: Complete blood count; PS: Peripheral smear; WBCs: White blood cells; UM: Uncomplicated malaria; Ht: Haematocrit; MCV: Mean corpuscular volume; MCH: Mean corpuscular haemoglobin; RBCs: Red blood cells; DIC: Disseminated intravascular coagu- lopathy; SM: Severe malaria; RDT: Rapid diagnostic test. References 23. Moulin F, Lesage F, Legros AH, Maroga C, Moussavou A, Guyon P, et al. Thrombocytopenia and Plasmodium falciparum malaria in children with different exposures. Arch Dis Child. 2003;88:540–1. 1. WHO. World malaria report 2015. Geneva: World Health Organization; 2015. https://apps.who.int/iris/bitstream/handle/10665/200018/97892 41565158_eng.pdf;jsessionid=A63034A5EF79C858F9DE80D3349C82 AD?sequence=1. Accessed 15 July 2020. 1. WHO. World malaria report 2015. Geneva: World Health Organization; 2015. https://apps.who.int/iris/bitstream/handle/10665/200018/97892 41565158_eng.pdf;jsessionid=A63034A5EF79C858F9DE80D3349C82 AD?sequence=1. Accessed 15 July 2020. 24. Mahmood A, Yasir M. Thrombocytopenia: a predictor of malaria among febrile patient in Liberia. Infect Dis J Pakistan. 2008;14:41–4. febrile patient in Liberia. Infect Dis J Pakistan. 2008;14:41–4 2. WHO. World malaria report 2020. Geneva: World Health Organization; 2020. https://www.who.int/docs/default-source/malaria/world-malar ia-reports/9789240015791-double-page-view.pdf?sfvrsn=2c24349d_5. Accessed 6 January 2021. 25. Njunda AL, Ngouadjeu DTE, Nsagha DS, Nyanjoh EM, Kwenti TD, Assob NJC. Haematological profile of children with malaria in Kumba Health District, South West Region Cameroon. Afr J Integ Health. 2016;6:23–9. 26. Kumar R, Kalra SP, Kumar H, Anand AC, Madan H. Pancytopenia–a six year study. J Assoc Phys India. 2001;49:1078–81. 3. Sutherland CJ, Tanomsing N, Nolder D, Oguike M, Jennison C, Pukrit- tayakamee S, et al. Two nonrecombining sympatric forms of the human malaria parasite Plasmodium ovale occur globally. J Infect Dis. 2010;201:1544–50. 3. Sutherland CJ, Tanomsing N, Nolder D, Oguike M, Jennison C, Pukrit- tayakamee S, et al. Two nonrecombining sympatric forms of the human malaria parasite Plasmodium ovale occur globally. J Infect Dis. 2010;201:1544–50. 27. Zaki SA, Shanbag P. Atypical manifestations of malaria. Res Rep Trop Med. 2011;2:9–22. 28. Kaewpitoon S, Rujiragul R, Namwichaisirikul N, Churproong S, Ueng- arporn N, Matrakool L, et al. Malaria in Thailand 2007–2011. Srinagarind Med J. 2012;27:118–20. 4. White NJ, Pukrittayakarnee S, Hien TT, Faiz MA, Makuolu OA, Dondorp AM. Malaria Lancet. 2013;383:723–35. 4. White NJ, Pukrittayakarnee S, Hien TT, Faiz MA, Makuolu OA, Dondorp AM. Malaria Lancet. 2013;383:723–35. 5. WHO. National malaria control programme review: Republic of Indonesia. Indonesia. WHO Country Office for Indonesia; 2011. https://apps.who.int/ iris/bitstream/handle/10665/253960/9789791947749-eng.pdf;jsessionid =DABF97E279DB585057E086467F1EAB5A?sequence=1. Accessed 20 July 2020. 29. Ullah I, Ali MU, Ali S, Rafiq A, Sattar Z, Hussain S. Hematological profile of patients having malaria-positive peripheral blood smears: a cross- sectional study at a diagnostic research center in Khyber Pakhtunkhwa, Pakistan. Cureus. 2018;10:e3376. 30. Hyder A, Mahmood A, Mahmood R, Iqbal MI. Evaluation of haematologi- cal parameters in malaria infection and its association with different species of malarial parasite. Pak Armed Forces Med J. 2020;70:1576–80. 6. WHO. World malaria report 2016. Availability of data and materials 14. Erhart LM, Yingyuen K, Chuanak N, Buathong N, Laoboonchai A, Miller RS, et al. Hematologic and clinical indices of malaria in a semi-immune population of western Thailand. Am J Trop Med Hyg. 2004;70:8–14. The datasets analysed in this study are available from the corresponding author on request. The datasets analysed in this study are available from the corresponding author on request. 15. Adedapo AD, Falade CO, Kotila RT, Ademowo GO. Age as a risk factor for thrombocytopenia and anaemia in children treated for acute uncompli- cated falciparum malaria. J Vector Borne Dis. 2007;44:266–71. Funding 13. Maina RN, Walsh D, Gaddy C, Hongo G, Waitumbi J, Otieno L, et al. Impact of Plasmodium falciparum infection on haematological parameters in children living in Western Kenya. Malar J. 2010;9:4. g The authors did not receive any financial support for the research. Acknowledgements Conversely, in children, these manifestations of uncomplicated malaria can be misinterpreted and attributed to other prevalent infections, such as pneumonia, gastroenteritis, and sepsis[92]. In high The authors thank the medical records staff at Sorong Regional General Hospi- tal for their help in providing data. Page 10 of 12 Page 10 of 12 Jiero and Pasaribu Malar J (2021) 20:126 Consent for publication Not applicable. 17. McKenzie FE, Prudhomme WA, Magill AJ, Forney JR, Permpanich B, Lucas C, et al. White blood cell counts and malaria. J Infect Dis. 2005;192:323–30. 17. McKenzie FE, Prudhomme WA, Magill AJ, Forney JR, Permpanich B, Lucas C, et al. White blood cell counts and malaria. J Infect Dis. 2005;192:323–30. Authors’ contribution Plasmodium falciparum malaria in an endemic region? ISRN Trop Med. 2013;2013:1–9. Plasmodium falciparum malaria in an endemic region? ISRN Trop Med. 2013;2013:1–9. SJ conceived the study, undertook a literature review, fieldwork, analysed and drafted the manuscript. APP was involved in the critical revision of the manu- script. All authors read and approved the final manuscript. 12. Bakhubaira S. Hematological parameters in severe complicated Plas- modium falciparum malaria among adults in Aden. Turk J Haematol. 2013;30:394–9. Received: 23 October 2020 Accepted: 9 February 2021 Received: 23 October 2020 Accepted: 9 February 2021 21. Latif I, Jamal A. Hematological changes in complete blood picture in pae- driatric patients of malaria caused by Plasmodium vivax and falciparum. J Ayub Med Coll Abbottabad. 2015;27:351–5. y 22. Chianura L, Errante IC, Travi G, Rossotti R, Puoti M. Hyperglycemia in severe falciparum malaria: a case report. Case Rep Crit Care. 2012;2012:312458. Competing interests 18. Alves-Junior ER, Gomes LT, Ribatski-Silva D, Mendes CRJ, Leal-Santos FA, Simões LR, et al. Assumed white blood cell count of 8,000 cells/µL overestimates malaria parasite density in the Brazilian Amazon. PLoS ONE. 2014;9:e94193. The authors have no conflict of interest to declare regarding the publication of this manuscript. Ethics approval and consent to participate Ethical approval for this study was obtained from the Research Ethics Commit- tee of the Medical School of the Universitas of Sumatera Utara. Ethical approval for this study was obtained from the Research Ethics Commit- tee of the Medical School of the Universitas of Sumatera Utara. 16. Helegbe GK, Goka BQ, Kurthals JA, Addae MM, Ollaga E, Tetthe JK, et al. Complement activation in Ghanaian children with severe Plasmodium falciparum malaria. Malar J. 2007;6:165. 16. Helegbe GK, Goka BQ, Kurthals JA, Addae MM, Ollaga E, Tetthe JK, et al. Complement activation in Ghanaian children with severe Plasmodium falciparum malaria. Malar J. 2007;6:165. Author details 1 Department of Child Health, Sorong Regional General Hospital, Sorong, West Papua, Indonesia. 2 Department of Child Health, Medical Faculty, Universitas Sumatera Utara, Dr. Mansur Street No. 5, 20156 Medan, Indonesia. 19. Lacerda MV, Mourᾶo MP, Coelho HC, Santos JB. Thrombocytopenia in malaria: who cares? Mem Inst Oswaldo Cruz. 2011;106:52–63. 20. Horstmann RD, Dietrich M, Bienzle U, Rasche H. Malaria-induced throm- bocytopenia. Ann Hematol. 1981;42:157–64. Received: 23 October 2020 Accepted: 9 February 2021 handle/10665/163782/9789241549219_eng.pdf;jsessionid=070C9A2E74 C3C475EEFC56E301155262?sequence=1. Accessed 6 January 2021. 60. Perrin LH, Mackey LJ, Miescher PA. The hematology of malaria in man. Semin Hematol. 1982;19:70–82. handle/10665/163782/9789241549219_eng.pdf;jsessionid=070C9A2E74 C3C475EEFC56E301155262?sequence=1. Accessed 6 January 2021. 61. Clark IA, Chaudhri G. Tumour necrosis factor may contribute to the anae- mia of malaria by causing dyserythropoiesis and erythrophagocytosis. Br J Haematol. 1988;70:99–103. 36. WHO. Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity. Geneva, World Health Organization; 2011. https:// apps.who.int/iris/handle/10665/85839. Accessed 6 January 2021. 62. Dondorp AM, Angus BJ, Chotivanich K, Silamut K, Ruangveerayuth R, Hardeman MR, et al. Red blood cell deformability as a predictor of anemia in severe falciparum malaria. Am J Trop Med Hyg. 1999;60:733–7. 37. Tobón-Castaño A, Mesa-Echeverry E, Miranda-Arboleda AF. Leukogram profile and clinical status in vivax and falciparum malaria patients from Colombia. J Trop Med. 2015;2015:1–11. 63. George LO, Ewelike-Ezeani CS. Haematological changes in children with malaria infection in Nigeria. Journal of Medicine and Medical Science. 2011;2:768–71. 38. Kwenti TE, Kwenti TDB, Latz A, Njunda LA, Nkuo-Akenji T. Epidemiologi- cal and clinical profile of paediatric malaria: a cross sectional study performed on febrile children in five epidemiological strata of malaria in Cameroon. BMC Infect Dis. 2017;17:499. 64. Fattahi BA, Hashemi A, Abolhasanizadeh S. Comparison of hematologi- cal aspects among children with malaria and healthy children. Iran J Ped Hematol Oncol. 2015;5:89–92. 39. WHO. Severe falciparum malaria. World Health Organization, Communi- cable diseases cluster. Trans R Soc Trop Med Hyg. 2000;94(Suppl 1):1–90. 65. Ladhani S, Lowe B, Cole AO, Kowuondo K, Newton CR. Changes in white blood cells and platelets in children with falciparum malaria: relationship to disease outcome. Br J Haematol. 2002;119:839–47. 40. Cohee LM, Laufer MK. Malaria in children. Pediatr Clin North Am. 2017;64:851–66. 41. WHO. Management of severe malaria—a practical handbook, 3rd edn. Geneva: World Health Organization; 2012. https://www.who.int/malaria/ publications/atoz/9789241548526/en/. Accessed 6 January 2021. 66. Beale PJ, Cormack JD, Oldrey TB. Thrombocytopenia in malaria with immunoglobulin (IgM) changes. Br Med J. 1972;1:345–9. 67. Skudowitz RB, Katz J, Lurie A, Levin J, Metz J. Mechanisms of thrombocy- topenia in malignant tertian malaria. BMJ. 1973;2:515–8. 42. WHO. World malaria report 2018. Geneva: World Health Organization; 2018. https://apps.who.int/iris/bitstream/handle/10665/275867/97892 41565653-eng.pdf. Accessed 15 July 2020. g 68. Essien EM. The circulating platelet in acute malaria infection. Br J Haema- tol. 1989;72:589–90. 43. Bawah AT, Nyakpo KT, Ussher FA, Alidu H, Dzogbo JJ, Agbemenya S, Kwasie DA, Seini MM. handle/10665/163782/9789241549219_eng.pdf;jsessionid=070C9A2E74 C3C475EEFC56E301155262?sequence=1. Accessed 6 January 2021. Sajjanar AB, Dinesh US, Kanbur D, Mane V, Athanikar V. Hematological parameters in Plasmodium Vivax and Falciparum Malaria-a study at tertiary care centre in North Karnataka. NJLM. 2013;8047:1997. 51. Sweta Barik S, Chandoke RK, Verma AK. A prospective clinico-hemato- logical study in 100 cases of pancytopenia in capital city of India. J Appl Hematol. 2014;5:45–50. y 77. George P, Alexander L. A study on the clinical profile of complicated Plasmodium vivax mono–infections. Asian Pac J Trop Med. 2010;3:560–2. 52. Kenangalem E, Karyana M, Burdarm L, Yeung S, Simpson JA, Tjitra E, et al. Plasmodium vivax infection: a major determinant of severe anaemia in infancy. Malar J. 2016;15:321. 78. Rodríguez-Morales AJ, Sánchez E, Vargas M, Piccolo C, Colina R, Arria M. Anemia and thrombocytopenia in children with Plasmodium vivax malaria. J Trop Pediatr. 2006;52:49–51. y 53. Barber BE, William T, Jikal M, Jilip J, Dhararaj P, Menon J, et al. Plasmodium knowlesi malaria in Children. Emerg Infect Dis. 2011;17:814–20. p 79. Srivastava S, Ahmad S, Shirazi N, Verma SK, Puri P. Retrospective analysis of vivax malaria patients presenting to tertiary referral centre of Uttara- khand. Acta Trop. 2011;117(2):82–5. 54. Price RN, Tjitra E, Guerra CA, Yeung S, White NJ, Anstey NM. Vivax malaria: neglected and not benign. Am J Trop Med Hyg. 2007;77:79–87. 55. Menendez C, Fleming AF, Alonso PL. Malaria-related anaemia. Parasitol Today. 2000;16:469–76. 80. Rogerson SJ, Carter R. Severe vivax malaria: newly recognised or rediscov- ered. PLoS Med. 2008;5(6):e136. 56. Ugwu EO, Dim CC, Uzochukwu BS, Iloghalu EI, Ugwu AO. Malaria and anaemia in pregnancy: a cross-sectional study of pregnant women in rural communities of Southeastern Nigeria. Int Health. 2014;6:130–7. 81. Genton B, Mueller I. Vivax malaria: more severe and more resistant. Therapy. 2010;7(1):39–48. 82. Price RN, Douglas NM, Anstey NM. New developments in Plasmodium vivax malaria: severe disease and the rise of chloroquine resistance. Curr Opin Infect Dis. 2009;22(5):430–5. 82. Price RN, Douglas NM, Anstey NM. New developments in Plasmodium vivax malaria: severe disease and the rise of chloroquine resistance. Curr Opin Infect Dis. 2009;22(5):430–5. 57. Price RN, Simpson JA, Nosten F, Luxemburger C, Hkirjaroen L, ter Kuile F, et al. Factors contributing to anemia after uncomplicated falciparum malaria. Am J Trop Med Hyg. 2001;65(5):614–22. 83. World Health Organisation. Severe malaria. Trop Med Int Health. 2014;19(1):7–131. 58. Quintero JP, Siqueira AM, Tobón A, Blair S, Moreno A, Arévalo-Herrera M, et al. Malaria-related anaemia: a Latin American perspective. handle/10665/163782/9789241549219_eng.pdf;jsessionid=070C9A2E74 C3C475EEFC56E301155262?sequence=1. Accessed 6 January 2021. Hematological profile of children under five years with malaria at the Ho Municipality of Ghana. Edorium. J Pediatr. 2018;2:100004P05AB2018. 69. Pain A, Ferguson DJ, Kai O, Urban BC, Lowe B, Marsh K, et al. Platelet- mediated clumping of Plasmodium falciparum-infected erythrocytes is a common adhesive phenotype and is associated with severe malaria. Proc Natl Acad Sci U S A. 2001;98(4):1805–10. 44. Sulistyaningsih E, Loeki EA, Loscher T, Berens-Riha N. Diagnostic difficul- ties with Plasmodium knowlesi infection in humans. Emerg Infect Dis. 2010;16:1033–4. 70. Brouwers J, Noviyanti R, Fijnheer R, de Groot PG, Trianty L, Mudali- ana S, et al. Platelet activation determines angiopoietin-1 and VEGF levels in malaria: implications for their use as biomarkers. PLoS ONE. 2013;8(6):e64850. 45. Elyazar IR, Hay SI, Baird JK. Malaria distribution, prevalence, drug resist- ance and control in Indonesia. Adv Parasitol. 2011;74:41–175. 71. Gérardin P, Rogier C, Ka AS, Jouvencel P, Brousse V, Imbert P. Prognostic value of thrombocytopenia in African children with falciparum malaria. Am J Trop Med Hyg. 2002;66:686–91. 46. Baird JK. Resistance to therapies for infection by Plasmodium vivax. Clin Microbiol Rev. 2009;22:508–34. 47. Abdussalam R, Krimadi RNI, Siregar R, Lestari ED, Salimo H. Profil infeksi plasmodium, anemia dan status nutrisi pada malaria anak di RSUD Scholoo Keyen. Kabupaten Sorong Selatan. Sari Pediatri. 2016;17:446–9. 72. Lathia TB, Joshi R. Can hematological parameters discriminate malaria from nonmalarious acute febrile illness in the tropics? Indian J Med Sci. 2004;58:239–44. 48. Subekti N, Kawulur Paiticen M, EIJJ, Sirait SHK, Mohammed S. Types of plasmodium and the effect of environmental factor against malaria in Manokwari, West Papua. JPII. 2018;7(3):322–32. 73. Kotepui M, Phunphuech B, Phiwklam N, Chupeerach C, Duangmano S. Effect of malarial infection on haematological parameters in population near Thailand-Myanmar border. Malar J. 2014;13:218. Manokwari, West Papua. JPII. 2018;7(3):322–32. 49. Anabire NG, Aryee PA, Helegbe GK. Hematological abnormalities in patients with malaria and typhoid in Tamale Metropolis of Ghana. BMC Res Notes. 2018;11:353. 74. Goyal JP, Makwana AM. Comparison of clinical profile between P. vivax and P. falciparum malaria in children: a tertiary care centre perspective from India. Malar Res Treat. 2014;2014:132672. 50. Durrani SH, Sayyar M, Lal A, Aslam R. Incidentally diagnosed bicytopenia showing a wide spectrum of pathologies on bone marrow morphology. KJMS. 2015;8:247–50. 75. Nandwani S, Pande A, Saluja M. Clinical profile of severe malaria: study from a tertiary care center in north India. J Parasit Dis. 2014;38(1):11–5. 76. References Geneva: World Health Organization; 2016. https://apps.who.int/iris/bitstream/handle/10665/252038/97892 41511711-eng.pdf?sequence=1. Accessed 15 July 2020. 31. D’acremont V, Landry P, Mueller I, Pécoud A, Genton B. Clinical and labo- ratory predictors of imported malaria in an outpatient setting: an aid to medical decision making in returning travelers with fever. Am J Trop Med Hyg. 2002;66:481–4. 7. Supriyanto D, Bachtia A. Achievement of malaria control program in West Papua 2012–2016. Indonesia: The 5th International Conference on Public Health; 2019. https://doi.org/10.26911/theicph.2019.01.25. Accessed 6 January 2021. 32. Murphy GS, Oldfield EC. Falciparum malaria. Infect Dis Clin North Am. 1996;10:747–75. 8. BPS. Badan Pusat Statistik Kota Sorong. 2020. https://sorongkota.bps. go.id/. Accessed 6 January 2021. 33. Bidaki Z, Dalimi A. Biochemical and hematological alteration in vivax malaria in Kahnouj city. J Rafsanjan Univ Med Sci. 2003;3:17–24. 9. Hanandita W, Tampubolon G. Geography and social distribution of malaria in Indonesia Papua: a cross-sectional study. Int J Health Geogr. 2016;15:13. 34. WHO. World malaria report 2010. Geneva: World Health Organization; 2010. https://www.who.int/malaria/world_malaria_report_2010/world malariareport2010.pdf. Accessed 15 July 2020. 10. Ministry of Health of the Republic of Indonesia. West Papua provincial government health profile health office 2018. Indonesia; 2018 (govern- ment document, unpublished). 35. WHO. Methods manual microscopy for the detection, identification and quantification of malaria parasites on stained thick and thin blood films in research settings procedure. Geneva: Research Malaria Microscopy Standards Working Group; 2015. https://apps.who.int/iris/bitstream/ 11. Muwonge H, Kikomeko S, Sembajjwe LF, Seguya A, Namugwanya C. How reliable are hematological parameters in predicting uncomplicated Jiero and Pasaribu Malar J (2021) 20:126 Page 11 of 12 Page 11 of 12 Page 11 of 12 handle/10665/163782/9789241549219_eng.pdf;jsessionid=070C9A2E74 C3C475EEFC56E301155262?sequence=1. Accessed 6 January 2021. Jiero and Pasaribu Malar J (2021) 20:126 Page 12 of 12 Page 12 of 12 92. Crawley J, Chu C, Mtove G, Nosten F. Malaria in children. Lancet. 2010;375(9724):1468–81. 86. Wickramasinghe SN, Abdalla SH. Blood and bone marrow changes in malaria. Best Pract Res Clin Haematol. 2000;13:277–99. 93. Baird JK, Krisin Barcus MJ, Elyazar IRF, Bangs MJ, Maguire JD, et al. Onset of clinical immunity to Plasmodium falciparum among Javanese migrants to Indonesian Papua. Ann Trop Med Parasitol. 2003;97(6):557–64. 87. Greenwood BM, Armstrong JR. Comparison of two simple methods for determining malaria parasite density. Trans R Soc Trop Med Hyg. 1991;85:186–8. 88. Nwanjo HU, Opara AU. Effects of falciparum malaria infection on some haematological indices and renal functions. J Med Lab Sci. 2005;14:6–10 handle/10665/163782/9789241549219_eng.pdf;jsessionid=070C9A2E74 C3C475EEFC56E301155262?sequence=1. Accessed 6 January 2021. Mem Inst Oswaldo Cruz. 2011;106(Suppl 1):91–104. 84. Saravu K, Rishikesh K, Kamath A, Shastry AB. Severity in Plasmodium vivax malaria claiming global vigilance and exploration-a tertiary care centre- based cohort study. Malar J. 2014;13(1):304. 59. Kitua AY, Smith TA, Alonso PL, Urassa H, Masanja H, Kimario J, et al. The role of low level Plasmodium falciparum parasitaemia in anaemia among infants living in an area of intense and perennial transmission. Trop Med Int Health. 1997;2:325–33. 85. Gupta P, Sharma R, Chandra J, Kumar V, Singh R, Pande V, et al. Clinical manifestations and molecular mechanisms in the changing paradigm of vivax malaria in India. Infect Genet Evol. 2016;39:317–24. Jiero and Pasaribu Malar J (2021) 20:126 Publisher’s note g 89. Kueh YK, Yeo KL. Haematological alterations in acute malaria. Scand J Haematol. 1982;29:147–52. Springer Nature remains neutral with regard to jurisdictional claims in pub- lished maps and institutional affiliations. 90. Lisse IM, Aaby P, Whittle H, Knudsen K. A community study of T lym- phocyte subsets and malaria parasitaemia. Trans R Soc Trop Med Hyg. 1994;88:709–10. 91. Reyburn H, Mbatia R, Drakeley C, Carneiro I, Mwakasungula E, Mwerinde O, et al. Overdiagnosis of malaria in patients with severe febrile illness in Tanzania: a prospective study. BMJ. 2004;329:1212. • fast, convenient online submission • thorough peer review by experienced researchers in your ﬁeld • rapid publication on acceptance • support for research data, including large and complex data types • gold Open Access which fosters wider collaboration and increased citations maximum visibility for your research: over 100M website views per year • At BMC, research is always in progress. Learn more biomedcentral.com/submissions Ready to submit your research Ready to submit your research ? Choose BMC and benefit from: ? Choose BMC and benefit from: • fast, convenient online submission • thorough peer review by experienced researchers in your ﬁeld • rapid publication on acceptance • support for research data, including large and complex data types • gold Open Access which fosters wider collaboration and increased citations maximum visibility for your research: over 100M website views per year • At BMC, research is always in progress. Learn more biomedcentral.com/submissions Ready to submit your research Ready to submit your research ? Choose BMC and benefit from: ? Choose BMC and benefit from:
https://openalex.org/W4323030089	https://zenodo.org/records/7695757/files/ZDIFT%200809.pdf	Quechua	null	AKKUZATIV KELISHIGINING NEMIS VA QORAQALPOQ TILIDA BERILISHI	Zenodo (CERN European Organization for Nuclear Research)	2,023	cc-by	1,105	` Abishova Gulxan Matjanovna Berdaq nomidagi Qoraqalpoq davlat universiteti Nemis tili va adabiyoti kafedrasi stajor o’qituvchisi https://doi.org/10.5281/zenodo.7695757 Xorijiy tillarni o‘zbek, keyinchalik qoraqalpoq tillari bilan qiyosiy o‘rganishga o‘tgan asrning ikkinchi yarmidan boshlab ko‘proq e’tibor berildi, aytarliktay ilmiy va ilmiy-metodik tadqiqotlar yuzaga keldi. Bu esa yuqorida ta’kidlaganidek, O‘zbekistonimizning o‘rta va oliy o‘quv yurtlarida chet tillarni o‘qitishni takomillashtirishga bo‘lgan talabning ortib borishi, shuningdek milliy, ilmiy-pedagogik kadrlarning paydo bo‘lishi, etishib chiqishi bilan isbotlanadi. Akademik V.V.Vinogradov tillarni qiyosiy o‘rganishning ahamiyatli ekanligini alohida ta’kidlab: “Qardosh, bir-biriga yaqin tillarni qiyosiy-tarixiy tarzda o‘rganish bilan birga turli sistemadagi tillarni qiyosiy yoki solishtirmali turda o‘rganishga bo‘ladi hamda ularni shu tarzda o‘rganish kerak” – degan edi.1 Nemis tilida ataw ma’nosini anglatadigan fe’llardan keyin ham vositasiz akkuzativ gapda qator kelgan holda qullaniladi: bunday f’ellarga nennen, heiβen, lehren, kiradi. Qoraqalpoq tiliga akkuzativdagi birinchi ot tabıs, ayrim hollarda barıs, ikkinchisi esa ataw kelishiklari orqali u‘giriladi: Er nannte den ersten Mann einen Lügner (B. Kellerman. Reisen in Asien) – Ol birinshi adamdı ótirikshi deytug‘ın edi. Sie nannten ihn einen Künstler - Olar onı artist dep aytadı. Akkuzativ lang, hoch, breit, weit, schwer, wert u.a. (sein) sifatlari bilan qo‘llanilganda, ular predikativ yoki attributiv sifatida qullanilib, o‘lchov ma’nosini ifoda etadi. Bunday hodisa qoraqalpoq tilida yo‘q. Shu sababli akkuzativning bu ma’nosi turli kelishiklarda o‘z ifodasini topishi mumkin: Das Kind ist Akkuzativ lang, hoch, breit, weit, schwer, wert u.a. (sein) sifatlari bilan qo‘llanilganda, ular predikativ yoki attributiv sifatida qullanilib, o‘lchov ma’nosini ifoda etadi. Bunday hodisa qoraqalpoq tilida yo‘q. Shu sababli akkuzativning bu ma’nosi turli kelishiklarda o‘z ifodasini topishi mumkin: Das Kind ist 6 Monate alt- Bala altı aylıq. Unsere Straβe ist einen Kilometer lang - Kóshemizdiń uzınlıǵı bir kilometr. Der Baum ist 15 Meter hoch – Terektiń biyikligi 15 metr. topishi mumkin: Das Kind ist 6 Monate alt- Bala altı aylıq. Unsere Straβe ist einen Kilometer lang - Kóshemizdiń uzınlıǵı bir kilometr. Der Baum ist 15 Meter hoch – Terektiń biyikligi 15 metr. Nemis tilida akkuzativning fe’llarining infinitiv formasi bilan qo‘shilib kela olishiga akkuzativning maxsus oboroti deb yuritiladi. Akkuzativning bu turi qoraqalpoq tilida iyelik kelishigi va undan keyin hozirgi zamon sifatdoshining tabıs kelishigi formasi yordaminda qoraqalpoq tilida: Oiy.k + St.k Bunday oborot hőren, sehen, fühlen fe’llari bilan yasaladi: Ich sah das Kind spielen - Men balanıń oynap atırǵanın kórdim. Wir hőren ihn kommen. Biz onıń kiyatırǵanın esitip atırmız. Nemis tilida haben fe’li, shuningdek, es gibt fe’lidan keyin ot hamisha akkuzativ kelishigida turib qullanadi. 1 Виноградов В.В. Русский язык (грамматическое учение о слове). – Москва, 1947. – C. 81. Qoraqalpoq tilida tabıs kelishigiga bunday xususiyat xos emas. Gaplarda so‘zlarining sintaktik funktsiyalari o‘zgarib ketadi. Nemis tilida ataw kelishikda kelgan olmosh (shuningdek ot ham bo‘lishi mumkin), iyelik kelishigida, akkuzativda kelgan so‘z ham ataw kelishigida keladi. Gaplarda ma’no to‘laligicha saqlangan, biroq gaplarning tuzilishi, ulardagi har bir so‘zning gapdagi ma’nosi qiyoslanayotgan tillar orasidagi farqlanishga sabab bo‘ladi. Ayrim birikmalar tavtologik xarakterga ega bo‘lib, tavtologiya esa ularda sifat attributi (aniqlovchisi)ning ishlatilishida nazarga tushadi: bittere Tränen weinen (=bitter weinen), einen tiefen Schlaf schlafen (=tief schlafen). Qoraqalpoq tilida bunday birikmalar deyarli ishlatilmaydi. Shu sababdan tavtologik holati emas, balki ularning keyingi sinonimlari o‘z ifodasini topadi: qattı (óksip - óksip) jılaw (eńrew), qattı uyıqlaw va boshqalar. Qoraqalpoq tilida bunday birikmalar deyarli ishlatilmaydi. Shu sababdan tavtologik holati emas, balki ularning keyingi sinonimlari o‘z ifodasini topadi: qattı (óksip - óksip) jılaw (eńrew), qattı uyıqlaw va boshqalar. Nemis tilida sport, o‘yin turlarini ifodalaydigan turg‘un birikmalar mavjud. Ular asosan artiklsiz S+V (ot+fe’l) shaklida ishlatiladi. Qoraqalpoq tilida ham xuddi shunday iboralar bo‘lib, ularning nemis tilidagiga juda o‘xshash. Iboralarda ham ma’no, ham shakl birdek: Schach spielen – shaxmat oynaw, Fuβball spielen - futbol oynaw, Tennis spielen – tennis oynaw, Kannst du Schach spielen – Shaxmat oynay alasań ba? Qiyoslanayotgan tillarning birinchisida shunday turg‘un frazeologik birikmalar bo‘lib ularning akkuzativdagi ot va fe’ldan tuzilgan. Xuddi boshqa frazeologik birikmalarga xos bo‘lganidek ular ham o‘zlarining ma’nosiga ega ular qoraqalpoq tilida ma’nolari bo‘yicha o‘z aksini topadi, chunki maqol, matollar hamisha ham tillarda strukturasi va ma’nosi jihatdan o‘xshash bo‘lavermaydi: Schwein haben – isi ońınan keliw, sátine túsiw, sátli bolıw; Pech haben – isi júrispew, sátsizlikke duwshar bolıw, isi ońınan kelmewi; Glück haben – baxıtlı bolıw. Er hatte Schwein, er hat die Flugkarte besorgt. Isi ońınan kelip, samolyotqa bilet aldı. Der Freund hatte Glück (Schwein), er bezog die Universität. Dostımnıń baxıtı bar eken, universitetke kirdi. Xuddi yuqorida keltirganlaridek, ular akkuzativdagi ot+fe’l birikmasida tuziladi va yaxlit bir manogo ega buladi. Fuβ fassen, ein Auge auf jemanden werfen, seinen Mann stehen, Rede stehen Abschied nehmen, einen guten, (schlechten) angenechen Eindruck machen, verzicht lesten, Notiz nehmen, Unterricht halten, Rede halten, Anerkennung finden u.a. Ularning ayrimlari ajiralmas leksik birikmalarga aylanib ketgan bo‘lsa, ayrimlarini ma’nosidan, kelib chiqib o‘timli fe’llar bilan olmashtirib qo‘llash mumkin bo‘ladi: Einen Eindruck machen – beeindrucken, Unterricht halten – (Dat) – unterrichten (Akk), Abschied nehmen – sich verabschieden. 2 Erben I. Abriß der deutschen Grammatik. – Берлин, 1965. – P. 101. ` Qoraqalpoq tilida esa tabıs kelishigining bunday tu‘ri yo‘qligidan boshqa kelishiklar bilan ifodolanadi. Bunday noo‘xshashliklar tillarning o‘ziga xos xususiyatlaridan kelib chiqadi: Ich habe einen Freund Meniń bir dostım bar. Er hat keinen Bleistift - Onıń qálemi joq. Im 2. Stock gibt es einen Lesesaal – Ekinshi qabatta oqıw zalı bar. Nemis tilida akkuzativ o‘timsiz fe’llardan keyin turib ham qo‘llanilish hususiyatiga ega. Ular ko‘pincha turg‘un birikmalarga o‘xshash bo‘lib, asosiy ma’noni (tushunchani) fe’l ifodolaydi: einen Walzer tanzen - valsqa túsiw (oynaw), Ski laufen - lıja menen (lıjada) júriw, Boot fahren – qayıqta júriw, qayıqta súziw. 1 Виноградов В.В. Русский язык (грамматическое учение о слове). – Москва, 1947. – C. 81. 41 ` ` References: 1. Erben I. Abriß der deutschen Grammatik. – Берлин, 1965. – P. 101. 2. Виноградов В.В. Русский язык (грамматическое учение о слове). – Москва, 1947. – C. 81. Tilshunos I.Erben “Akkuzativ tu‘ldiruvshili gaplarni aktivdan passivga aylantirish haqqida to‘xtalib, haqiqiy akkuzativ obyekt passivga aylantirilganda ega vazifasida kelishini, idioma va frazeologik birikmalarda esa bu holat umuman sodir bo‘lmasligini ko‘rsatadi”.2 Karl schreibt einen Brief. Ein Brief wird geschrieben. arl schreibt einen Brief. Ein Brief wird geschrieben. baut hier ein Haus. Ein Haus wird hier gebaut. Man baut hier ein Haus. Ein Haus wird hier gebaut. Lekin: Sei fassen hier immer mehr Fuβ→ Er wird Fuβ getaβt aber nicht: Der Fuβ wird getaβt. Wer nehmen Abschied von unserem Freund. Es wird Abschied genommen. Jetzt wird Abschied genommen, aber nicht. Der Abschied wird genommen. Wir stehen Schlange → Es wird Schlange 42 ` ` ; Heute wird Schlange gestanden: aber nicht. Die Schlange wird gestanden. gestanden; Heute wird Schlange gestanden: aber nicht. Die Schlange wird gestanden. Xulosa qilib aytganda, shu usul bilan haqiqiy akkuzativ obyektlari turg‘un birikmaga aylangan, ammo shaklan vositasiz to‘ldiruvchiga o‘xshash idioma va frazeologik birikmalardan farqlab olishga bo‘lar ekan. Ularning qoraqalpoqcha ekvivalentlari esa ma’nolarga qarab o‘z izohlarini topadi. 43 43
https://openalex.org/W2984978087	https://www.scielo.br/j/cadbto/a/KB84TVtSmHWc5CkSVbfgpqJ/?lang=pt&format=pdf	Portuguese	null	Aspectos do cuidado integral para pessoas em situação de rua acompanhadas por serviço de saúde e de assistência social: um olhar para e pela terapia ocupacional	Cadernos Brasileiros de Terapia Ocupacional	2,019	cc-by	9,225	ISSN 2526-8910 Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 https://doi.org/10.4322/2526-8910.ctoAO1809 ISSN 2526-8910 Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 https://doi.org/10.4322/2526-8910.ctoAO1809 Aspectos do cuidado integral para pessoas em situação de rua acompanhadas por serviço de saúde e de assistência social: um olhar para e pela terapia ocupacional Fernanda Oliveira Motaa , Rafaela Maria Alves Martins Fonsecab , Josenaide Engracia dos Santosb , Andrea Donatti Gallassib  aUniversidade Luterana de Palmas, Palmas, TO, Brasil. bUniversidade de Brasília – UnB, Brasília, DF, Brasil. aUniversidade Luterana de Palmas, Palmas, TO, Brasil. bUniversidade de Brasília – UnB, Brasília, DF, Brasil. Resumo: Introdução: A população que (sobre)vive nas ruas se caracteriza, muitas vezes, pela ruptura dos vínculos sociais e pelo uso de drogas, necessitando de cuidados de saúde e de assistência social. Objetivo: Identificar e analisar as percepções dos profissionais terapeutas ocupacionais e dos usuários sobre a atuação e especificidade da terapia ocupacional junto às pessoas em situação de rua atendidas pelo Centro de Atenção Psicossocial álcool e drogas (CAPS-ad III) e pela Unidade de Acolhimento (UA). Método: Trata-se de um estudo exploratório, de abordagem qualitativa, realizada a partir de entrevistas semiestruturadas com três terapeutas ocupacionais e cinco usuários de um CAPS-ad III do Distrito Federal e da UA referenciada por este CAPS-ad III; os dados foram analisados a partir do método de Análise de Conteúdo. Resultados: Os dados foram organizados em três categorias temáticas: (1) uso de drogas, a situação de morador de rua e o tratamento no CAPS-ad III; (2) o cotidiano de atuação da terapia ocupacional; e (3) terapia ocupacional e reinserção social. Conclusão: A terapia ocupacional atua com população em situação de rua com olhar para o cotidiano e desempenho de Atividades de Vida Diária (AVD), trabalhando na perspectiva da Redução de Danos como forma de buscar uma maior qualidade de vida dos usuários. Torna-se necessário levar espaços de saúde e de assistência social para o contexto do usuário, realizar ações extrapolando o espaço físico do CAPS-ad e colocando o usuário como participante ativo desse processo. Palavras-chave: População em Situação de Rua, Drogas de Abuso, Terapia Ocupacional. licença Creative Commons Attribution Este é um artigo publicado em acesso aberto (Open Access) sob a licença Creative Commons Attribution, que permite uso, distribuiçã e reprodução em qualquer meio, sem restrições desde que o trabalho original seja corretamente citado. Autor para correspondência: Andrea Donatti Gallassi, Universidade de Brasília, Campus Ceilândia, Centro Metropolitano 1, Conjunto A, Ceilândia Sul, CEP 72220-140, Brasília, DF, Brasil, e-mail: andrea.gallassi@gmail.com Recebido em Out. 17, 2018; 1ª Revisão em: Fev. 18, 2019; 2ª Revisão em: Abr. 10, 2019; Aceito em: Maio 12, 2019. 1 Introdução A população que (sobre)vive nas ruas vem aumentando por diversos motivos, tais como: situação de pobreza, desemprego, rupturas dos vínculos familiares e das redes sociais de suporte, migrações face a violência urbana, e/ou uso problemático de álcool e outras drogas (SILVA et al., 2018). A compreensão do processo saúde-doença se constitui ferramenta indispensável para a definição das ações do setor saúde junto à PSR. As práticas, no entanto, acabam por ocorrer somente em situações de emergência e realizadas, muitas vezes, por profissionais sem o devido preparo técnico; esta abordagem, porém, deve, necessariamente, ocorrer a partir da compreensão de fatores que extrapolam o universo da saúde e dialoguem com os aspectos sociais e da cultura de rua, a história de vida dessas pessoas e suas estratégias de sobrevivência. O Consultório na Rua, dispositivo de cuidado que compõe a atenção básica em saúde, foi criado com o objetivo de prestar atendimento in loco à PSR numa perspectiva menos emergencial, mas de acompanhamento contínuo e prevenção realizado por profissionais capacitados. O estar vivo, muitas vezes, é o necessário para se considerar com saúde, e a doença passa a ser compreendida somente quando se encontram em uma situação debilitante que os impeça de trabalhar para ganhar dinheiro e garantir sua sobrevivência (PAIVA et al., 2016; SILVA; FRAZÃO; LINHARES, 2014). Em países da Europa e no Brasil, as respostas institucionais frente a esta questão, historicamente compuseram o rol de ações da assistência social a partir de uma abordagem assistencialista e pouco problematizada sobre os elementos constituintes do fenômeno. Especialmente no Brasil, a partir da década de 1960, o debate passa, então, a ser compreendido de uma perspectiva sanitária, “medicalizante”, que mantém o estreitamento da compreensão de sua complexidade passando a considerá-la partir de um diagnóstico médico, recrudescendo a perspectiva higienista de remoção de populações indesejadas dos centros urbanos. Tal compreensão acaba por ser reproduzida pelos próprios serviços de saúde (FOUCAULT; ALVAREZ-URÍA; VARELA, 1992; VARANDA; ADORNO, 2004; AMARANTE, 2007). A visibilidade que a população em situação de rua (PSR) adquiriu, exigiu do Estado políticas públicas que pudessem responder às suas necessidades, que eram, até então, ignoradas. Aspects of the whole care for people in street followed by health and social assistance services: a look at and for occupational therapy Abstract: Introduction: The population that lives (survive) on the streets is often characterized by the rupture of social ties and the use of drugs, necessitating health care and social assistance. Objective: To identify and analyze the perceptions of the occupational therapist professionals and the users about the performance and specificity of the occupational therapy with the street people assisted by the community-based drug treatment service (CAPS-ad III) and the Embracement Unit (EU). Method: This is an exploratory and qualitative study based on semi-structured interviews with 3 occupational therapists and 5 users of a CAPS-ad III from the Federal District and the Embracement Unit (EU) referenced by this CAPS-ad III; the data were analyzed using analysis content. Results: The data were organized into three thematic categories: (1) drug use, homelessness and treatment in CAPS-ad III; (2) the daily routine of Occupational Therapy; (3) Occupational Therapy and Mota, F. O. et al. 8078 Social Integration. Conclusion: The Occupational Therapy acts with the population in a street situation with a look at the daily life and performance of Activity of Daily Living (ADL), working in the perspective of Harm Reduction as a way to seek a higher quality of life of users. It is necessary to take care spaces and social assistance to the user context, to take actions extrapolating the physical space of CAPS-ad and placing the user as an active participant in this process. Keywords: Homeless Persons, Street Drugs, Occupational Therapy. Keywords: Homeless Persons, Street Drugs, Occupational Therapy. direito à saúde, ao atendimento pelos diversos serviços e categorias profissionais e de forma humanizada, visando também a concretização dos princípios de equidade, universalidade, integralidade e igualdade do Sistema Único de Saúde (SUS) (BRASIL, 2009a). Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 1 Introdução Neste serviço, a terapia ocupacional atua no cotidiano destas pessoas, buscando ampliar e retomar seu repertório de atividades com vistas à maior participação social e consequente diminuição ou interrupção do uso de álcool ou outras drogas (GALLASSI et al., 2016). No caso das pessoas em situação de rua e que são atendidas no CAPS-ad, há uma série de questões específicas relacionadas aos cuidados de saúde e às rupturas sociais, o que torna ainda mais desafiadora a intervenção (ANDRADE et al., 2011). UA funciona como uma espécie de “república” e em uma estrutura física independente, porém próxima, do CAPS-ad III que a referencia; os afazeres domésticos são compartilhados e as regras estabelecidas pelos próprios residentes, cabendo à equipe do CAPS-ad III atuar como mediadora das relações interpessoais e apoio para o cumprimento do PTS. Em ambos os serviços – CAPS-ad III e UA – o desafio das profissões é buscar a sua especificidade e identidade, dada a complexidade e intersecção das demandas sociais e de saúde (BOCCARDO et al., 2011). Coloca-se, portanto, a necessidade e o desafio dos profissionais, dentre eles o terapeuta ocupacional, que atuam neste campo de relação entre a saúde e o social, de elaborar, discutir e implementar ações de acordo com as necessidades locais e dos usuários, tendo claro o objetivo de efetivar políticas públicas pautadas pelos direitos sociais e de saúde (MALFITANO; BIANCHI, 2013). Outro ponto de atenção que integra a RAPS, segundo objeto de estudo, é a Unidade de Acolhimento (UA). Trata-se de um serviço de caráter residencial transitório, cujo objetivo é oferecer acolhimento voluntário e cuidados contínuos para pessoas com necessidades decorrentes do uso de crack, álcool e outras drogas, em situação de extrema vulnerabilidade social e familiar e que demandem acompanhamento terapêutico e protetivo. Os critérios para acessar a UA são: ter um Plano Terapêutico Singular (PTS) preestabelecido junto à equipe do serviço de referência que o encaminhou (que inclui, quando for o caso, além da permanência na UA o tratamento no CAPS-ad ou em outro serviço da RAPS), estar em busca de trabalho, estudo, ou como meio temporário para reorganização de vida (BRASIL, 2011). 1 Introdução O parágrafo único da Política Nacional para a População em Situação de Rua (PNPSR) a define: Dentre as políticas públicas de saúde voltadas para a PSR, destaca-se a Portaria 3.088 (BRASIL, 2011) que instituiu a Rede de Atenção Psicossocial (RAPS), composta por serviços articulados que buscam uma atenção integral para pessoas com transtorno mental e/ou com necessidades decorrentes do uso de crack, álcool e outras drogas no âmbito do SUS. Dentre os serviços especializados que compõem a RAPS, o Centro de Atenção Psicossocial (CAPS) se configura como um articulador desta rede, classificados como I, II, III (24 horas), i (infantil) ou ad (álcool e drogas), variando de acordo com número de habitantes do município e o público alvo. [...] grupo populacional heterogêneo que possui em comum a pobreza extrema, os vínculos familiares interrompidos e/ou a inexistência de moradia convencional regular, e que utiliza os logradouros públicos e as áreas degradadas como espaço de moradia e de sustento, de forma temporária ou permanente, bem como as unidades de acolhimento para pernoite temporário ou como moradia provisória (BRASIL, 2009a). O CAPS-ad III, um dos objetos deste estudo, é um serviço portas abertas, de funcionamento 24 horas que oferece atendimento aos que dele necessitam e sua família. Possui equipe multidisciplinar A PNPSR versa sobre os direitos desta população, incluindo o respeito à pessoa humana, direito à convivência familiar e comunitária, valorização e respeito à vida e cidadania. Além destes, é destacado o Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 Aspectos do cuidado integral para pessoas em situação de rua acompanhadas por serviço de saúde e de assistência social: um olhar para e pela terapia ocupacional Aspectos do cuidado integral para pessoas em situação de rua acompanhadas por serviço de saúde e de assistência social: um olhar para e pela terapia ocupacional 808 6 formada, majoritariamente, por enfermeiros, assistentes sociais, médicos, psicólogos e terapeutas ocupacionais. Conta com leitos de retaguarda para desintoxicação – denominados de acolhimento integral – onde o usuário pode permanecer por até 14 dias, de acordo com sua necessidade clínica e social, participando das atividades do CAPS-ad III durante o dia (acolhimento diurno) e permanecendo no serviço também durante a noite. 1 Introdução Ou seja, residir na UA é parte do PTS do usuário, tanto no que se refere ao tratamento pelo uso de álcool ou outras drogas, quando for o caso, quanto às estratégias de reinserção social, elementos que se articulam e são imprescindíveis para o processo de reabilitação psicossocial dessas pessoas, diferenciando-se do simples abrigamento noturno realizado pelos dispositivos de assistência social. O objetivo deste estudo é identificar e analisar as percepções dos profissionais terapeutas ocupacionais e dos usuários sobre a atuação e especificidade da terapia ocupacional junto às pessoas em situação de rua atendidas pelo Centro de Atenção Psicossocial álcool e drogas (CAPS-ad III) e pela Unidade de Acolhimento (UA). Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 3 Resultados De acordo com a ordem de entrevista, os usuários foram nominados como Usuário 1, Usuário 2, Usuário 3, Usuário 4 e Usuário 5 e tinham idade de 29, 47, 52, 26 e 57 anos, respectivamente; todos eram do sexo masculino, estavam em situação de rua há mais ou menos 6 meses, 5 anos, 15 anos, 1 ano e 21 anos, respectivamente; estavam residindo na UA há mais ou menos 3 meses, e eram assistidos pelo CAPS-ad III há pelo menos 6 meses frequentando o serviço ao menos 3 vezes por semana. Estes usuários relataram que o principal motivo que os levaram a viver nas ruas foi o uso de álcool e outras drogas e a consequente desavença familiar; referem que tiveram tentativas anteriores de retornarem às casas de suas famílias, mas, novamente, por conta do uso, os conflitos se intensificaram e a saída de casa acabou sendo inevitável. A coleta de dados ocorreu entre o período de outubro a novembro de 2017. Com os profissionais, foi realizada no espaço do CAPS-ad III de forma individual de acordo com a disponibilidade de cada participante; com os usuários, a coleta ocorreu no espaço da UA, também individualmente. A definição dos espaços para a coleta de dados foi determinada levando em consideração o que seria mais conveniente para os participantes segundo eles próprios. Todas as entrevistas foram gravadas em áudio para posterior transcrição. As entrevistas com os usuários ocorreram após as entrevistas com os profissionais e todas as perguntas norteadoras do roteiro de entrevistas aos profissionais foram correlacionadas às perguntas feitas aos usuários, para possibilitar uma maior compreensão acerca do tratamento, como também para realizar possíveis relações comas informações obtidas. Os profissionais de terapia ocupacional eram do sexo feminino e também foram nominados de acordo com a ordem das entrevistas, sendo Profissional 1, Profissional 2 e Profissional 3, com idades de 26, 35 e 21 anos, respectivamente. O tempo de formação de cada uma foi de 4, 13 e 1 ano(s), respectivamente, e a área de formação complementar foi saúde mental (residência), hospitalar (aprimoramento) e a última estava cursando a residência em saúde mental. As duas primeiras eram servidoras da Secretaria de Estado da Saúde do DF (SES/DF) e atuavam no CAPS-ad III há 5 anos, e a última há 6 meses. Mota, F. O. et al. 8098 Mota, F. O. et al. Os critérios de inclusão para os profissionais participarem do estudo foram: terem formação em terapia ocupacional, estarem atuando no CAPS-ad III que referencia a UA, desenvolverem ações de cuidado com usuários que se encontram em situação de rua e aceitarem participar do estudo mediante a assinatura do Termo de Consentimento Livre e Esclarecido (TCLE). Os critérios de inclusão para os usuários foram: estarem em tratamento no CAPS-ad III, estarem em situação de rua quando acolhidos no serviço, residir temporariamente na UA referenciada por este CAPS-ad III, serem acompanhados por terapeuta ocupacional, e aceitarem participar do estudo mediante a assinatura do TCLE. à luz dos referenciais teóricos que fundamentaram essa pesquisa – a abordagem psicossocial de pessoas em situação de rua e que fazem uso problemático de drogas, e o cotidiano de atuação do terapeuta ocupacional junto a esta população. Os dados foram organizados em planilha categorial. Este estudo foi aprovado pelo Comitê de Ética em Pesquisa (CEP) com parecer número 1.081.907/2015. Foi entregue no momento da entrevista o TCLE para assinatura dos participantes, bem como, o termo de autorização de uso de som de voz para fins de pesquisa. Os nomes dos participantes foram mantidos em sigilo, utilizando somente referência à fala de acordo com a ordem de entrevista. Para a coleta de dados, foi elaborado um roteiro de entrevista semiestruturada (MINAYO; SANCHES, 1993), composto por 24 questões que abordavam com os profissionais terapeutas ocupacionais sobre a rotina do serviço, a atuação da equipe multidisciplinar, as demandas dos usuários em situação de rua, a relação interprofissional, bem como os desafios e as experiências positivas na relação terapêutica com estes usuários. O roteiro de entrevista com os usuários foi distinto do utilizado com os profissionais, e contou também com 24 questões que abordavam sobre a vida anterior ao início do tratamento no CAPS-ad III, o contexto de situação de rua em que estavam inseridos, as demandas prioritárias, a visão sobre a equipe multidisciplinar, a visão específica sobre a terapia ocupacional e a experiência na UA. 2 Método Trata-se de um estudo exploratório de abordagem qualitativa. Foram entrevistados três profissionais terapeutas ocupacionais que atuam em um CAPS-ad III do Distrito Federal (DF) e cinco usuários que estavam residindo temporariamente na UA e faziam tratamento neste CAPS-ad III. O DF conta com 07 CAPS-ad, sendo três com funcionamento 24h e que contam com leitos de retaguarda para desintoxicação (acolhimento integral), e atendem adultos e adolescentes a partir de 16 anos em uso problemático de álcool e outras drogas; 05 CAPS “transtorno”, para adultos com outros transtornos mentais que não relacionados ao uso problemático de álcool e outras drogas; 03 equipes de Consultório na Rua, que atuam, especialmente, em cenas urbanas de uso de álcool e outras drogas; 02 CAPS i, para crianças e adolescentes com transtornos mentais; 02 enfermarias psiquiátricas em hospitais gerais; 01 hospital psiquiátrico e 01 UA adulto. Os CAPS funcionam com portas abertas e são os principais articuladores da rede psicossocial do DF, encaminhando os usuários quando necessário para os demais serviços que compõem a RAPS. As atividades de tratamento que os usuários residentes da UA realizam, são estabelecidas pela equipe do serviço de referência, e podem não incluir sua frequência diária ao tratamento, considerando que parte de suas necessidades de saúde e social requer articulações comunitárias para a busca de emprego, retomada dos laços familiares, na maioria das vezes rompidos, e moradia. Ao final do dia, os usuários devem retornar à UA em um horário pré-determinado (de acordo com o PTS) e não devem estar sob efeito de álcool ou de outras drogas. Em outras palavras, a Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 3 Resultados A análise dos dados foi feita pelo método de Análise de Conteúdo de Bardin (2009), que compreende um conjunto de técnicas, e foi realizada em duas etapas: na primeira, a partir da marcação de palavras chaves a fim de identificar possíveis categorias de análise; na segunda, as categorias que emergiram foram discutidas Os dados foram organizados em três categorias temáticas, sendo que a primeira e a terceira emergiram das entrevistas com os usuários, e a segunda e a terceira das entrevistas com os profissionais: (1) uso de drogas, a situação de morador de rua e o tratamento no CAPS-ad III; (2) o cotidiano de Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 Aspectos do cuidado integral para pessoas em situação de rua acompanhadas por serviço de saúde e de assistência social: um olhar para e pela terapia ocupacional 810 6 atuação da terapia ocupacional; (3)terapia ocupacional e reinserção social. terceiros, de familiar, ou por demanda espontânea, e ouviram comentários ruins sobre esse tipo de serviço, relacionando-o à prisão e ao tratamento para “gente doida”, não entendendo, de início, o seu objetivo; quando passaram a frequentá-lo, ficaram surpresos com a abordagem: Porém, relatam que há algumas exceções: O Usuário 1 relata que tinha uma vida “normal”, trabalhava, mas não possuía mais vínculos com a família, porque saiu de casa muito novo e não tinha bom relacionamento com os irmãos, que eram usuários de drogas. Refere ter estudado e construído uma carreira: fez curso técnico na área da saúde e trabalhou em laboratórios como Exame e Pasteur. Começou a usar drogas por influência de amigos e com o tempo passou a fazer uso pesado, principalmente de cocaína, o que o levou aos “corres” no centro de Taguatinga (Região Administrativa do DF), segundo ele, para roubar, traficar e se prostituir, sendo a partir desta experiência que passou a viver realmente na rua. Eu vejo um trabalho muito bom, pessoas acolhedoras, profissionais de excelência. Tem seus profissionais que estão somente pelo dinheiro, mas tem também aqueles que estão aqui por amor à profissão, sempre poderá contar com eles, estão sempre abertos ao diálogo, a um conselho. Resumindo eu os vejo muito humanos e muito profissionais (Usuário 1). 3.1 Uso de droga, a situação de morador de rua e o tratamento no CAPS-ad III Pra mim, é meu porto seguro, pode ser exagerado, mas assim… Em toda a minha vida eu nunca tive amor, apesar que eu também não sei se tenho amor no CAPS, mas aparenta ser. Me acolhem, me escutam, me medicam, cuidam de mim, e isso me ajuda muito pro meu EGO, até para o meu próprio vício, porque eu acho que quando temos um vício é a perda de alguma coisa, é a perda de algo que você não consegue saber o que é. Você fica naquela busca infinita (Usuário 2). A vida na rua se configurou como um marco para esses usuários. Relataram que não tinham a percepção real sobre o que era estar em situação de rua e da exposição às situações de violência e ao uso de drogas. Relacionaram um aumento no padrão de consumo com as perdas sofridas, como no trabalho e, especialmente, na família, buscando a substância muitas vezes para tapar um vazio existente. Alguns referiram a sensação de medo por não saberem o que aconteceria no dia seguinte, se iam ter o que comer ou se iam estar vivos, por passarem cotidianamente por diversas situações de violência: Sobre a atuação da equipe multidisciplinar, de uma maneira geral, os usuários relataram que a assistência é adequada e os profissionais estão sempre disponíveis para ouvi-los. Eu tenho filhos né, me afastei para não prejudicar a eles, nem a mim nem a eles né, principalmente a eles. Eles sabem que eu estou em Brasília, mas, não tenho contato, face, whatsapp. Não tenho contato de nada sabe, pra não atrapalhar a vida deles eu larguei de mão, já fiquei em situação de rua, mas nunca procurei eles não (Usuário 5). Aqui no CAPS eu tenho achado isso, eu me emociono porque vejo a vontade das pessoas, e já fui muito maltratado. Quando vejo o ato de gentileza comigo, dá vontade de pegar no colo sabe, e caminhar (Usuário 2). Aqui no CAPS eu tenho achado isso, eu me emociono porque vejo a vontade das pessoas, e já fui muito maltratado. Quando vejo o ato de gentileza comigo, dá vontade de pegar no colo sabe, e caminhar (Usuário 2). 3.2 O cotidiano de atuação da terapia ocupacional De acordo com a fala das profissionais, o serviço possui uma grande demanda diária, principalmente por funcionar 24 horas, e todos os usuários que chegam são acolhidos (serviço porta aberta). Neste momento do acolhimento é que acontece a escuta qualificada, o levantamento dos objetivos terapêuticos e a elaboração do PTS, de acordo com as demandas e interesses do usuário: Atualmente fez um exame e descobriu uma doença sexualmente transmissível (sífilis) e isso o deixou bastante assustado: “graças ao tratamento do CAPS eu descobri e estou tratando essa doença”. A descoberta do serviço para esse usuário foi aleatória: Fui na agência do trabalhador e me deparei com o CAPS, e busquei ajuda; vim no CAPS e fiz acolhimento com a Maria1 e contei a minha história; também contei que tentei suicídio (Usuário 1). Fui na agência do trabalhador e me deparei com o CAPS, e busquei ajuda; vim no CAPS e fiz acolhimento com a Maria1 e contei a minha história; também contei que tentei suicídio (Usuário 1). A partir do momento que ele entra no acolhimento inicial, a gente faz avaliação, escuta e verifica quais são as demandas e prioridades dele, e damos os devidos encaminhamentos (Profissional 1). A partir dos relatos, observa-se que os usuários não tinham a compreensão exata sobre o funcionamento do CAPS-ad III. Chegaram por indicação de Na elaboração do PTS, o usuário poderá ser encaminhado para o acolhimento diurno ou para Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 Mota, F. O. et al. 8118 o acolhimento integral. No acolhimento diurno, ele passa o dia em tratamento no serviço, participando dos grupos, oficinas e sendo assistido pela equipe de acordo com suas necessidades, e a noite ele volta para casa; nesta modalidade, ele terá acesso às refeições oferecidas pelo serviço. pois, muitas vezes, mesmo estes usuários estando em situação de rua, não há a demanda de permanência no serviço durante o dia todos os dias, e pela perspectiva da Redução de Danos, os usuários poderão acessar o serviço para demandas simples, como banho e alimentação, bem como para o uso de medicação. O acolhimento diurno é indicado para os dias em que as pessoas que fazem tratamento no CAPS-ad III tem atividades/atendimentos programados. O usuário será encaminhado ao acolhimento integral (leitos de retaguarda para desintoxicação) de acordo com sua necessidade clínica e situação de vulnerabilidade social. 3.2 O cotidiano de atuação da terapia ocupacional Nesta modalidade, além de participar do acolhimento diurno, ele passará a noite no serviço e poderá ficar até 14 dias “internado”, podendo ser prorrogado se houver necessidade: Quanto ao encaminhamento de usuários para UA e a própria compreensão sobre os objetivos deste serviço, os relatos são divergentes. Uma(s) profissionai(s) refere(m) o local como uma unidade apenas para abrigamento temporário; outra(s) o categoriza(m) como dispositivo de reinserção social: A gente sugere o acolhimento integral quando tem demanda, que geralmente são mais físicas, conflitos psicológicos e também pessoas que estão em situação de rua, a gente considera muito a vulnerabilidade, né (Profissional 3). Se fosse para destacar quais os serviços da rede intersetorial que mais nos acessam, temos a Casa Santo André, com serviço de abordagem na rua, que faz parte da SEDESTMIDH [Secretaria de Estado do Trabalho, Desenvolvimento Social, Mulheres, Igualdade Racial e Direitos Humanos], que é da rede mesmo de assistência social. Tem encaminhamentos da UNAF que é um dos abrigos do DF, e também temos encaminhamentos de comunidades terapêuticas que possuem equipes atuando no território, aí trazem os pacientes com o intuito de conseguirem encaminhamentos para o abrigamento (Profissional 1). Quanto à elaboração PTS, instrumento norteador de todo o tratamento do usuário no serviço, há profissional que acredita que quando se trata de usuários em situação de rua, esta elaboração seria mais complexa pelo fato de, muitas vezes, estarem com os vínculos familiares fragilizados ou rompidos, e por não terem objetivos tão claros quando chegam à unidade. No entanto, outras profissionais acreditam que por ser singular e elaborado de acordo com cada caso, não se difere muito dos demais. A terapia ocupacional atua em ambos os serviços – CAPS-ad III e UA – estando com os usuários desde o primeiro contato. De acordo com as entrevistadas, há um olhar social e integral para os usuários, e quando se trata de uma pessoa em situação de rua, já no acolhimento se busca ter o conhecimento sobre o desempenho nas AVDs, visando sua autonomia e independência. De acordo com as profissionais entrevistadas, a demanda prioritária dos usuários em situação de rua que chegam ao serviço é de abrigamento. 3.2 O cotidiano de atuação da terapia ocupacional É bastante marcante a fala de que o usuário que busca um espaço protegido vê o CAPS-ad III e a UA como sendo estes espaços: A demanda principal muitas vezes é de abrigo né, nem sempre ele quer tratar a droga, mas às vezes ele quer um abrigo. Ou às vezes ele tá fugindo de situação de violência (Profissional 2). Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 3.3 Terapia ocupacional e reinserção social2 Quando há demanda de abrigamento, são feitas as articulações necessárias para que esse usuário tenha um espaço de moradia e condições mínimas para continuar o tratamento. A dificuldade encontrada neste momento é a de conseguir um espaço que seja realmente protegido, pois os próprios usuários relatam que não se sentem seguros em determinados serviços da rede. Ao realizarem a busca pelos locais disponíveis, as profissionais dão preferência pelos abrigos, seguidos das comunidades terapêuticas, posteriormente a própria UA e, caso o usuário tenha demanda, o acolhimento diurno do CAPS-ad III. O acolhimento diurno (passar o dia no serviço) é colocado como última estratégia para esse público, A TO nesse público a depender do indivíduo, a gente trabalha a questão da reinserção social, pois muitas vezes é um público que realmente não tem esse manejo de estar desempenhando essas atividades básicas e aí a gente tenta junto com o paciente fazer esse contato, junto com a rede, ou familiares e amigos e até mesmo dentro do nosso serviço para facilitar realmente o desempenho ocupacional (Profissional 1). A busca pela reinserção social é bem marcante no serviço de uma maneira geral, e quando se trata de usuário em situação de rua, essa preocupação é Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 Aspectos do cuidado integral para pessoas em situação de rua acompanhadas por serviço de saúde e de assistência social: um olhar para e pela terapia ocupacional Aspectos do cuidado integral para pessoas em situação de rua acompanhadas por serviço de saúde e de assistência social: um olhar para e pela terapia ocupacional 812 6 ainda maior, visto que ele está, muitas vezes, em condição de extrema vulnerabilidade: e objetivos” e “ocupar a mente”. Somente dois dos cinco usuários entrevistados conseguiram explicar de uma forma mais ampla o que seria o trabalho da terapeuta ocupacional no serviço. Às vezes a questão não é nem tirar ele da rua, porque muitas vezes ele não quer sair da rua, mas também de tornar a vida dele mais digna e melhor possível, explorando os potenciais que ele tem. Eu acho a TO muito importante nesse campo aí (Profissional 2). 3.3 Terapia ocupacional e reinserção social2 Pra mim a terapia ocupacional é aquela pessoa que se depara com uma pessoa numa situação de risco, por exemplo, álcool ou drogas, e ela tenta deixá-la à vontade para expor o problema dela pra ela conseguir entrar com uma solução, com uma luz no final do túnel, com uma esperança para aquela pessoa, porque muitas vezes quem está dentro da situação não tem esperança nenhuma em conseguir se tratar, conseguir se reintegrar na sociedade. Então eu vejo a terapia ocupacional como isso, como a reintegração na sociedade, um trabalho mental mesmo (Usuário 1). Expectativa que a gente tem, enquanto pessoa que tem que ter uma casa, um teto, um trabalho. Isso causa algumas frustrações, aí a gente percebe o quanto é importante trabalhar dentro da lógica de redução de dados. Dificilmente a gente percebe no dia a dia, que pacientes que moram na rua conseguem a abstinência. Aí temos que lidar com toda a nossa construção cultural do que seria o ideal para quem está na rua, ou para quem é usuário de substância, acho que isso é o que mais impacta com relação ao plano terapêutico (Profissional 1). Não sei. Conheço a terapeuta ocupacional Nara3, muito gente boa, que me assiste, me vigia, a que toma conta. A Nara tá sempre visando meus objetivos, traçando meus objetivos, procurando saber como eu tô fazendo, como devo fazer como devo proceder. Isso que eu acho que é uma terapeuta ocupacional, ocupar-se e procurar melhoras para o outro (Usuário 2). As principais dificuldades relatadas pelas profissionais quanto à atuação com esse público, foram acerca da adesão do usuário ao serviço, a rede pouco fortalecida para atendê-lo, poucos profissionais de terapia ocupacional atuantes na área, o próprio manejo com a equipe e, principalmente, quanto à rotina do serviço: Por fim, foi destacado que a UA funciona como um importante dispositivo da RAPS para acolher essas pessoas que estão em situação de rua: Um projeto específico, acho que seria até interessante, por exemplo, uma equipe que esteja familiarizada com isso pra dar atenção a eles, porque assim, o CAPS é de base territorial, então uma equipe pra ir mesmo até esse território, conhecer essas pessoas, tentar trazer para os serviços, ou então tentar levar espaços de saúde para lá (Profissional 2). Bom, eu considero uma preparação pra você voltar a sociedade né. 3.3 Terapia ocupacional e reinserção social2 Ter uma visão diferente né, de permanecer sóbrio, e ter autonomia pra tudo. Graças a Deus tenho metas para serem cumpridas, mas nós temos autonomia, porque pra gente aqui é importante porque aprende a viver em comunidade, aprende a viver, cada um tem sua função, seu quarto, então aqui você aprende para quando você morar sozinho, você aprende né (Usuário 5). Mas é, não só isso, eu acho que também assim, a demanda da rotina do serviço, eu por ser residente, é uma carga horária muito grande, mas não dá pra ser revertida em um maior estudo de um local onde essas pessoas estão, e, de conhecer. A gente acaba sendo atropelada pela demanda institucional do serviço e aí não dá tempo de a gente ir ao território conhecer essas pessoas, ver as principais demandas, fazer uma abordagem com eles mesmos, onde as relações acontecem, a gente fica muito restrito aqui, ao espaço, e a demanda do serviço (Profissional 3). Ao final das entrevistas, os usuários ressaltaram a necessidade de continuidade do tratamento no CAPS-ad III, mesmo após a saída da UA, pois entendem que o uso problemático de álcool e outras drogas é uma questão de saúde a ser cuidada a médio e longo prazo. Ainda que consigam um emprego e uma moradia, pretendem seguir frequentando o serviço. Para avaliar a percepção dos usuários quanto à atuação do terapeuta ocupacional no serviço, foram abordadas duas questões específicas: “O que é a terapia ocupacional para você? Você consegue identificar quais são as atuações específicas da terapia ocupacional no serviço?” Mesmo os usuários que não compreendiam sobre a profissão, definiram como “trabalhar metas 4 Discussão Para os usuários participantes, a condição de exclusão para a vida nas ruas ocorreu como uma das consequências do uso problemático de álcool e outras drogas. Essa associação e o perfil dos usuários Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 Mota, F. O. et al. 8138 ampliada (VASCONCELOS et al., 2016). Este novo modelo de cuidado se encontra ainda em processo de implantação, revelando fragilidades persistentes da rede socioassistencial e das políticas públicas voltadas para populações vulneráveis, como as PSR, e que fazem uso problemático de álcool e outras drogas; a articulação intersetorial nestes casos, se torna ainda mais necessária para a garantia de direitos, seja de saúde, moradia, assistência social, trabalho, entre outros. do estudo se assemelham aos dados de outro estudo (ALVAREZ; ALVARENGA; RINA, 2009) e da Pesquisa Nacional sobre População de Rua, que estima que 31.922 adultos vivem nesta situação, sendo 82% do sexo masculino, e tendo como principais motivos problemas relacionados ao uso de álcool ou outras drogas (35,5%) e as desavenças familiares (29%) (BRASIL, 2009b). A ruptura dos vínculos familiares é outro fator que se destaca como determinante para essas pessoas viverem nas ruas. Em um estudo de revisão de literatura, foi demonstrado que as relações familiares tem forte associação na relação com o uso de álcool e outras drogas, podendo ser fator de risco ou de proteção; quando a relação familiar é conflituosa, com brigas constantes, torna-se um fator de risco, gerando o afastamento de seus membros (VASCONCELOS et al., 2015). O acolhimento integral (leitos de retaguarda para desintoxicação existentes nos CAPS-ad III – 24h) foi um recurso utilizado por todos os participantes antes de serem encaminhados para a UA ou mesmo durante sua permanência. Torna-se indispensável sua utilização nestes casos de maior complexidade clínica e social, uma vez que o cuidado oferecido é contínuo e, desde sua entrada, se inicia o processo de participação dos usuários das atividades do CAPS-ad III (VAINER, 2016). A frustração diante da realidade vivenciada e as dificuldades para planejar projetos futuros, resultam, muitas vezes, em disparadores para o uso de álcool e outras drogas; compreende-se que o uso passa a ser uma forma de fuga, de prazer temporário e de preenchimento de um vazio existente (MATOS, 2018). 4 Discussão Nos casos em que o usuário “não quer sair da situação de rua” – compreendido como um processo de desfiliação, segundo Castel (1995), em que há uma situação de perda de direitos sociais e de progressivas rupturas de redes sociais, onde a rua passa a ser o local de moradia e de trabalho, permitindo uma articulação do cotidiano deste usuário em torno desta nova realidade – as profissionais de terapia ocupacional referiram utilizar como estratégia terapêutica de redução de danos o encaminhamento para o acolhimento diurno, onde o usuário permanece apenas o dia no serviço e a noite pode retornar para a rua. Neste caso, o ganho terapêutico não está na redução ou interrupção total do uso de drogas, mas no auxílio à reorganização do cotidiano e das atividades de vida diária do usuário (GALHEIGO, 2003), considerando, inclusive como ganho, o tempo em que ele passa no serviço e que não está fazendo uso de álcool ou de outras drogas (CONTE et al., 2004). Nesse sentido, o trabalho articulado dos profissionais do CAPS-ad III com as equipes de Consultório na Rua torna-se fundamental para o processo de aproximação da rede de cuidado a estes usuários, sensibilizando-os para o tratamento e viabilizando possíveis mudanças em seu cotidiano com vistas à melhora de sua qualidade de vida por meio do acesso à saúde e à assistência social, conforme sugerido pela Profissional 2 em uma de suas falas. A nova forma de pensar e lidar com o processo de sofrimento psíquico no Brasil, orienta a implantação de serviços substitutivos ao modelo asilar e que sejam portas abertas às demandas de saúde mental e de álcool e outras drogas do território, como também para identificar populações específicas e mais vulneráveis, as quais devem ser objeto de estratégias diferenciadas de cuidado. Foi possível verificar que o CAPS-ad III, de maneira geral, atua com “porta aberta” e é a entrada da rede de saúde mental da região referenciada, promovendo ações que são sustentadas pelas evidências científicas, no que se refere ao acolhimento, ao acesso, à escuta qualificada, ao planejamento do PTS, à técnica e à reorientação de serviços (BALLARIN et al., 2011; SALLES; SILVA, 2017; SILVA; CID; MATSUKURA, 2018). Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 4 Discussão Quanto à elaboração do PTS dos usuários em situação de rua, os resultados demonstraram não haver um consenso sobre esta questão; algumas profissionais referiram não encontrar dificuldades adicionais na elaboração do PTS quando se tratam de PSR; outras já referiram ter dificuldades. Tais dificuldades podem estar relacionadas às mudanças que ocorreram nos serviços diante do novo modelo de cuidado, exigindo uma revisão de saberes e práticas, ampliando o foco da intervenção para além do sintoma relatado, trazendo para a clínica os aspectos sociais e de história de vida das pessoas, com a missão de cumprir com os pressupostos da reabilitação psicossocial fundamentados pela clínica Os usuários destacaram a importância dos profissionais do serviço, considerando-os como pessoas fundamentais para o seu tratamento e demonstrando relação de confiança e vínculo, porém não conseguiram explicar a especificidade do terapeuta ocupacional, pontuando apenas como “ocupar a mente” e “trabalhar Aspectos do cuidado integral para pessoas em situação de rua acompanhadas por serviço de saúde e de assistência social: um olhar para e pela terapia ocupacional 814 6 metas e objetivos” O conceito de ocupação é central para os terapeutas ocupacionais e decorre de como desenvolvem sua intervenção; o termo ocupação pode ser utilizado como atividade, ou como papéis ocupacionais produtivos; no entanto, ambos devem dar sentido à vida humana cumprindo com o seu papel terapêutico para a recuperação e central para a saúde e o bem-estar (SALLES; MATSUKURA, 2016). É, ainda, um desafio para os terapeutas ocupacionais atuarem com pessoas que apresentam necessidades de saúde interrelacionadas sobremaneira com carências sociais, reveladas pela falta de acesso a direitos fundamentais, como moradia e emprego, tornando o planejamento e a execução das ações de cuidado um processo complexo e que depende do acúmulo de diferentes saberes (SOUZA; PEREIRA; GONTIJO, 2014). terapêutico, estratégias de cuidado interdisciplinar e intersetorial, projetos de geração de renda e outros, criando espaços de experimentação e aprendizagem, explorando reflexões e subjetividades que os aproximam de seus territórios e das relações de conflitos e afeto nele presentes (SABINO et al., 2017; ASSAD; PEDRÃO; CIRINEU, 2016). Além disso, o terapeuta ocupacional deve oferecer reais possibilidades para os usuários exercitarem sua participação social com autonomia, por meio da oferta do acesso a bens e direitos sociais rompendo com a lógica excludente e alienante dos processos terapêuticos circunscritos ao espaço institucional (CASTRO et al., 2001). 4 Discussão As atividades realizadas pelo terapeuta ocupacional com PSR e em uso problemático de álcool e outras drogas devem enriquecer, reestruturar, integrar e fortalecer os sentimentos da vida dos usuários, lançando mão de diferentes linguagens, sejam elas artísticas, corporal ou literária, com vistas ao favorecimento da reconstrução da cidadania e da reinserção social, da melhora/retorno das relações familiares e sociais, e que devem ir além de uma abordagem exclusivamente individual, mas considere pontos coletivos e territoriais ao longo do processo de cuidado (SILVA et al., 2015). Ao identificar a necessidade de se criar estratégias para a inclusão de novos e diversos saberes em seu contexto de atuação, a terapia ocupacional passa, então, a ser “credenciada” como partícipe neste cenário de práticas interdisciplinares; sua contribuição se revela a partir do momento em que, ao longo de sua história, o processo terapêutico ocupacional rompe com uma prática diretiva com foco na doença e incorpora novas tecnologias oriundas de outros campos do conhecimento, para além da saúde, empodera os usuários nas tomadas de decisões sobre seu PTS, democratiza a assistência atuando extramuros, e desloca seu foco da doença para a promoção de saúde mental e reinserção social (ALMEIDA; TREVISAN, 2011). Além disso, a própria Prática Centrada no Cliente dialoga com outros campos do conhecimento, uma vez que prioriza no processo terapêutico áreas do desempenho ocupacional referentes ao lazer, produtividade e autocuidado, que fazem sentido para o usuário naquele momento e contexto de vida (MÂNGIA, 2002). Nesse sentido, a percepção dos próprios terapeutas ocupacionais acerca do trabalho interdisciplinar e a visão de sua especificidade neste novo contexto de atuação, passa a ser, ao mesmo tempo, um desafio e um alento, uma vez que mesmo que as dificuldades se manifestem, encontram respaldo teórico e prático para subsidiar suas práticas. Sabe-se, contudo, que é um desafio para os serviços e para os terapeutas ocupacionais contemplarem as singularidades de cuidado desta população, que vão desde a essencial disponibilidade de materiais, recursos e equipamentos adequados à prática do profissional, até a própria capacitação destes terapeutas ocupacionais para atenderem à complexidade de demandas que estes usuários apresentam como necessidades de saúde. Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 Referências ALMEIDA, D. T.; TREVISAN, E. R. Estratégias de intervenção da terapia ocupacional em consonância com as transformações da assistência em saúde mental no Brasil. Interface – Comunicação, Saúde, Educação, Botucatu, v. 15, n. 36, p. 299-308, 2011. FOUCAULT, M.; ALVAREZ-URÍA, F.; VARELA, J. Microfísica del poder. Barcelona: La Piqueta, 1992. GALHEIGO, S. M. O cotidiano na terapia ocupacional: cultura, subjetividade e contexto histórico-social. Revista de Terapia Ocupacional da Universidade de São Paulo, São Paulo, v. 14, n. 3, p. 104-109, 2003. ALVAREZ, A. M. S.; ALVARENGA, A. T.; RINA, S. C. S. A. D. Histórias de vida de moradores de rua, situações de exclusão social e encontros transformadores. Saúde e Sociedade, São Paulo, v. 18, n. 2, p. 259-272, 2009. GALLASSI, A. D. et al. Characteristics of clients using a community-based drug treatment service (‘CAPS-AD’) in Brazil: an exploratory study. International Journal of Drug Policy, London, v. 31, p. 99-103, 2016. GALLASSI, A. D. et al. Characteristics of clients using a community-based drug treatment service (‘CAPS-AD’) in AMARANTE, P. Saúde mental e atenção psicossocial. Rio de Janeiro: Editora Fiocruz, 2007. Brazil: an exploratory study. International Journal of Drug Policy, London, v. 31, p. 99-103, 2016. ANDRADE, T. et al. ‘What a pity!’–Exploring the use of ‘pitilho’as harm reduction among crack users in Salvador, Brazil. Drugs: Education Prevention and Policy, Abingdon, v. 18, n. 5, p. 382-386, 2011. LOPES, R. E. et al. Juventude pobre, violência e cidadania. Saúde e Sociedade, São Paulo, v. 17, n. 3, p. 63-76, 2008. MALFITANO, A. P. S. et al. Social occupational therapy: conversations about a Brazilian experience. Canadian Journal of Occupational Therapy, Canada, v. 81, n. 5, p. 298-307, 2014. ASSAD, F. B.; PEDRÃO, L. J.; CIRINEU, C. T. Estratégia de cuidado utilizada por terapeutas ocupacionais em Centros de Atenção Psicossocial. Cadernos de Terapia Ocupacional da UFSCar, São Carlos, v. 24, n. 4, p. 743-753, 2016. ASSAD, F. B.; PEDRÃO, L. J.; CIRINEU, C. T. Estratégia de cuidado utilizada por terapeutas ocupacionais em Centros de Atenção Psicossocial. Cadernos de Terapia Ocupacional da UFSCar, São Carlos, v. 24, n. 4, p. 743-753, 2016. MALFITANO, A. P.; BIANCHI, P. C. Terapia Ocupacional e atuação em contextos de vulnerabilidade social: distinções e proximidades entre a área social e o campo de atenção básica em saúde. Cadernos de Terapia Ocupacional da UFSCar, São Carlos, v. 21, n. 3, p. 563-574, 2013. BALLARIN, M. L. G. S. et al. 5 Conclusão BRASIL. Ministério do Desenvolvimento Social e Combate à Fome. Pesquisa Nacional sobre a População Nacional em Situação de Rua. Brasília: MDS, 2009b. A reinserção social de pessoas em situação de rua e em uso problemático de álcool e outras drogas é um desafio presente para terapeutas ocupacionais e demais profissionais que atuam neste campo. BRASIL. Portaria GM/MS nº 3088, de 23 de dezembro de 2011. Institui a Rede de Atenção Psicossocial para pessoas com sofrimento ou transtorno mental e com necessidades decorrentes do uso de crack, álcool e outras drogas, no âmbito do Sistema Único de Saúde. Diário Oficial [da] República Federativa do Brasil, Poder Executivo, Brasília, DF, 23 dez. 2011. As práticas cotidianas enquanto lugar de ação do terapeuta ocupacional junto a essa população, devem ser pensadas a partir de seu contexto histórico, cultural e social, favorecendo o cuidado integral e em consonância com a complexidade da demanda. O avanço da intersecção entre os saberes da saúde e do social possibilitarão a expansão do fazer terapia ocupacional, no sentido de lhe atribuir a devida magnitude revelada no processo de produção de vida que se dá a partir de sua relação com pessoas que se beneficiam de seu conhecimento. CASTEL, R. Les métamorphoses de la question sociale: une chronique du salariat. Paris: Gallimard, 1995. CASTRO, E. D.; LIMA, E. M. F. A.; BRUNELLO, M. I. B. Atividades humanas e Terapia Ocupacional. In: DE CARLO, M. M. R. P.; BARTALOTTI, C. C. Terapia Ocupacional no Brasil: fundamentos e perspectivas. São Paulo: Plexus, 2001. p. 41-59. CASTRO, E. D.; LIMA, E. M. F. A.; BRUNELLO, M. I. B. Atividades humanas e Terapia Ocupacional. In: DE CARLO, M. M. R. P.; BARTALOTTI, C. C. Terapia Ocupacional no Brasil: fundamentos e perspectivas. São Paulo: Plexus, 2001. p. 41-59. CONTE, M. et al. Redução de Danos e Saúde mental na Perspectiva da atenção básica. Boletim da Saúde, Porto Alegre, v. 18, n. 1, p. 59-77, 2004. 4 Discussão A articulação com as redes sociais de suporte, assim como a mediação de conflitos entre usuários e seus familiares, exigem uma multiplicidade de saberes e práticas: [...] os objetivos terapêuticos ocupacionais estão pautados em dimensões humanas impossíveis de serem segmentadas, visando redimensionamento dos projetos de vida, promoção e produção de vida. O que revela também desafios de ordem macrossocial que devem ser considerados (SILVA et al., 2015, p. 332). Um dos principais objetivos dos serviços de saúde mental se refere à reinserção social dos usuários. A terapia ocupacional no cuidado das PSR e em uso problemático de álcool e outras drogas deve lançar mão de estratégias que busquem reconstruir processos de ressocialização e vínculos dentro e fora do espaço institucional (MALFITANO et al., 2014), por meio de atividades grupais, oficinas, rodas de conversa, visitas domiciliares, acompanhamento O que se pode destacar a partir deste e de outros estudos, é que as estratégias utilizadas pelas terapeutas ocupacionais na relação com as pessoas em situação de rua e em uso problemático de álcool e outras drogas, perpassam os campos da saúde e do social, e se sustentam nos conhecimentos sobre a atividade humana para a construção do cuidado à luz dos pressupostos da reabilitação psicossocial. Ainda, Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 Mota, F. O. et al. 8158 da Universidade de São Paulo, São Paulo, v. 22, n. 1, p. 85-92, 2011. da Universidade de São Paulo, São Paulo, v. 22, n. 1, p. 85-92, 2011. cabem a estas terapeutas ocupacionais a atuação em defesa das políticas sociais e de saúde para o fortalecimento de ações e pesquisas que busquem diminuir desigualdades e promover acesso a direitos de uma forma mais justa e digna (MUÑOZ, 2014; LOPES et al., 2008). BRASIL. Decreto nº 7.053 de 23 de dezembro de 2009. Institui a Política Nacional para a População em Situação de Rua e seu Comitê Intersetorial de Acompanhamento e Monitoramento, e dá outras providências. Diário Oficial [da] República Federativa do Brasil, Poder Executivo, Brasília, DF, 23 dez. 2009a. Aspectos do cuidado integral para pessoas em situação de rua acompanhadas por serviço de saúde e de assistência social: um olhar para e pela terapia ocupacional Aspectos do cuidado integral para pessoas em situação de rua acompanhadas por serviço de saúde e de assistência social: um olhar para e pela terapia ocupacional 816 6 Ocupacional da Universidade de São Paulo, São Paulo, v. 13, n. 3, p. 15-21, 2002. e Drogas (CAPS ad) do interior do estado de São Paulo. Cadernos de Terapia Ocupacional da UFSCar, São Carlos, v. 23, n. 2, p. 321-324, 2015. e Drogas (CAPS ad) do interior do estado de São Paulo. Cadernos de Terapia Ocupacional da UFSCar, São Carlos, v. 23, n. 2, p. 321-324, 2015. MÂNGIA, E. F.; MURAMOTO, M. Integralidade e construção de novas profissionalidades nos contexto dos serviços substitutivos de saúde mental. Revista de Terapia Ocupacional da Universidade de São Paulo, São Paulo, v. 17, n. 3, p. 115-122, 2006. SILVA, F. P. D.; FRAZÃO, I. D. S.; LINHARES, F. M. P. Práticas de saúde das equipes dos Consultórios de Rua. Cadernos de Saúde Pública, Rio de Janeiro, v. 30, n. 4, p. 805-814, 2014. MATOS, A. C. N. População em situação de rua: a drogadição como escape para fuga da realidade. Psicologia. pt, Porto, v. 1, n. 1, p. 1-11, 2018. SILVA, I. C. N. et al. Representações sociais do cuidado em saúde de pessoas em situação de rua. Revista da Escola de Enfermagem da USP, São Paulo, v. 52, n. e03314, p. 1-7, 2018. MINAYO, M. C. S.; SANCHES, O. Quantitative and qualitative methods: opposition or complementarity? Cadernos de Saúde Pública, Rio de Janeiro, v. 9, n. 3, p. 237-248, 1993. SILVA, J. F.; CID, M. F. B.; MATSUKURA, T. S. Atenção psicossocial de adolescentes: a percepção de profissionais de um CAPSi. Cadernos Brasileiros de Terapia Ocupacional, São Carlos, v. 26, n. 2, p. 329-343, 2018. MUÑOZ, C. G. M. La labor de la terapia ocupacional en el marco de los determinantes sociales de la salud en Chile. Revista Chilena de Terapia Ocupacional, Chile, v. 14, n. 1, p. 73-80, 2014. SOUZA, V. C. A.; PEREIRA, A. R.; GONTIJO, D. T. A experiência no serviço de Consultório de Rua na perspectiva dos profissionais: contribuições para a atenção ao usuário de álcool e outras drogas. Cadernos de Terapia Ocupacional da UFSCar, São Carlos, v. 22, p. 37-47, 2014. Suplemento Especial. PAIVA, I. K. S. et al. Direito à saúde da população em situação de rua: reflexões sobre a problemática. Ciência & Saúde Coletiva, Rio de Janeiro, v. Aspectos do cuidado integral para pessoas em situação de rua acompanhadas por serviço de saúde e de assistência social: um olhar para e pela terapia ocupacional 21, n. 8, p. 2595- 2606, 2016. VAINER, A. A. Demanda e Utilização do Acolhimento Noturno em Centro de Atenção Psicossocial III na Cidade do Rio de Janeiro. 2016. 92 f. Tese (Doutorado em Saúde Pública) – Fundação Oswaldo Cruz, Rio de Janeiro, 2016. SABINO, J. S. et al. As ações da terapia ocupacional com adolescentes em situação de vulnerabilidade social: uma revisão de literatura. Cadernos Brasileiros de Terapia Ocupacional, São Carlos, v. 25, n. 3, p. 627-640, 2017. VARANDA, W.; ADORNO, R. C. F. Descartáveis urbanos: discutindo a complexidade da população de rua e o desafio para políticas de saúde. Saúde e Sociedade, São Paulo, v. 13, n. 1, p. 56-69, 2004. SALLES, D. B.; SILVA, M. L. Percepção de profissionais da área de saúde mental sobre o acolhimento ao usuário de substância psicoativa em CAPS-ad. Cadernos Brasileiros de Terapia Ocupacional, São Carlos, v. 25, n. 2, p. 341- 349, 2017. VASCONCELOS, A. C. M. et al. Relações familiares e dependência química: uma revisão de literatura. Revista Brasileira de Ciências da Saúde, João Pessoa, v. 19, n. 4, p. 321-326, 2015. SALLES, M. M.; MATSUKURA, T. S. O uso dos conceitos de ocupação e atividade na Terapia Ocupacional: uma revisão sistemática da literatura. Cadernos de Terapia Ocupacional da UFSCar, São Carlos, v. 24, n. 4, p. 801-810, 2016. VASCONCELOS, M. G. F. et al. Projeto terapêutico em Saúde Mental: práticas e processos nas dimensões constituintes da atenção psicossocial. Interface – Comunicação, Saúde, Educação, Botucatu, v. 20, n. 57, p. 313-323, 2016. SILVA, C. R. et al. Mapeamento da atuação do terapeuta ocupacional nos Centros de Atenção Psicossocial Álcool Contribuição dos Autores Fernanda Oliveira Mota: concepção do trabalho, coleta, organização e análise dos dados e redação do texto. Rafaela Maria Alves Martins Fonseca: análise dos dados, redação e revisão do texto. Josenaide Engracia dos Santos: análise dos dados e revisão do texto. Andrea Donatti Gallassi: concepção do trabalho, orientação, análise dos dados, redação e revisão do texto. Todas as autoras aprovaram a versão final do artigo. Referências Percepção de profissionais de um CAPS sobre as práticas de acolhimento no serviço. O Mundo da Saúde, São Paulo, v. 35, n. 2, p. 162-168, 2011. BARDIN, L. Análise de conteúdo. Lisboa: Edições 70, 2009. MÂNGIA, E. F. Contribuições da abordagem canadense “Prática de Terapia Ocupacional Centrada no Cliente” e dos autores da desinstitucionalização italiana para a Terapia Ocupacional em Saúde Mental. Revista de Terapia BOCCARDO, A. C. S. et al. O projeto terapêutico singular como estratégia de organização do cuidado nos serviços de saúde mental. Revista de Terapia Ocupacional Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 Notas 1 O nome real foi substituído por este fictício para preservar o sigilo. 2 O conceito de reinserção social aqui utilizado tem como referência o apontado por Mângia e Muramoto (2006, p. 116): “Para a reabilitação psicossocial e mais especificamente para a terapia ocupacional, o desafio da inserção social de pessoas vulneráveis e o desenvolvimento de formas de convívio com a diferença exigem transformações profundas nos modos de conceber o cuidado e organizar os serviços em confronto com as concepções e estratégias tradicionais o que implica na definição de novos perfis profissionais”. 3 O nome real foi substituído por este fictício para preservar o sigilo. Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019 Cad. Bras. Ter. Ocup., São Carlos, v. 27, n. 4, p. 806-816, 2019
https://openalex.org/W4361236510	https://aacr.figshare.com/ndownloader/files/39861761	English	null	Supplementary Tables and Figures from Combined CDK4/6 and PI3Kα Inhibition Is Synergistic and Immunogenic in Triple-Negative Breast Cancer	null	2,023	cc-by	1,075	Combined CDK4/6 and PI3Kα inhibition is synergistic and immunogenic in 1 triple negative breast cancer 2 3 Combined CDK4/6 and PI3Kα inhibition in TNBC 4 Zhi Ling Teo1,2, Stephanie Versaci1, Sathana Dushyanthen1, Franco Caramia1, Peter 5 Savas1, Chris P. Mintoff1, Magnus Zethoven1, Balaji Virassamy1, Stephen J. Luen1, 6 Grant A. McArthur1,2, Wayne A. Phillips1,2,4,5, Phillip K. Darcy1,2,3, and Sherene Loi,1,2 7 Supplementary Table and Figures 8 Combined CDK4/6 and PI3Kα inhibition is synergistic and immunogenic in 1 triple negative breast cancer 2 3 Combined CDK4/6 and PI3Kα inhibition in TNBC 4 Zhi Ling Teo1,2, Stephanie Versaci1, Sathana Dushyanthen1, Franco Caramia1, Peter 5 Savas1, Chris P. Mintoff1, Magnus Zethoven1, Balaji Virassamy1, Stephen J. Luen1, 6 Grant A. McArthur1,2, Wayne A. Phillips1,2,4,5, Phillip K. Darcy1,2,3, and Sherene Loi,1,2 7 Supplementary Table and Figures 8 Combined CDK4/6 and PI3Kα inhibition is synergistic and immunogenic in 1 triple negative breast cancer 2 Combined CDK4/6 and PI3Kα inhibition in TNBC 4 Zhi Ling Teo1,2, Stephanie Versaci1, Sathana Dushyanthen1, Franco Caramia1, Peter 5 Savas1, Chris P. Mintoff1, Magnus Zethoven1, Balaji Virassamy1, Stephen J. Luen1, 6 Grant A. McArthur1,2, Wayne A. Phillips1,2,4,5, Phillip K. Darcy1,2,3, and Sherene Loi,1,2 7 1 1 9 9 Supplementary Table S1: Characteristics of TNBC human cell lines TNBC subtypeA Cell line HistologyB ERB PRB HER2B MutationsC BL1 HCC1143 IDC - - - TP53 MDAMB468 DC - - - PTEN; RB1; SMAD4; TP53 BL2 HCC70 DC - - - PTEN; TP53 HCC1806 ASCC - - - CDKN2A; TP53; UTX MSL MDAMB231 IDC - - - BRAF; CDKN2A; KRAS; NF2; TP53; PDGFRA HS578T CS - - - CDKN2A; HRAS; TP53 LAR MDAMB453 AC - - - PIK3CA; CDH1; PTEN ALehman et al (1).BNeve et al (2). CCOSMIC: Forbes et al (3). BL1: basal-like 1; BL2: basal-like 2; MSL: mesenchymal-like; LAR: luminal androgen receptor AC: adenocarcinoma; ASCC: acantholytic squamous cell carcinoma; CS: carcinosarcoma; DC: ductal carcinoma; IDC: invasive ductal carcinoma. ER: estrogen receptor; PR: progesterone receptor; HER2: human epidermal growth factor receptor 2. Supplementary Table S1: Characteristics of TNBC human cell lines : estrogen receptor; PR: progesterone receptor; HER2: human epidermal growth factor receptor 2. 10 10 2 2 Supplementary Figure S3. Immune checkpoint blockade in combination with 28 BYL719 and LEE011 results in durable tumor regression in vivo. Tumor growth of 29 AT3OVA in each treatment group. Tumor-bearing mice were treated with indicated 30 drug combinations with the following doses: BYL719 (10mg/kg), LEE011 (40 mg/kg), 31 anti-PD-1 (200 µg) and anti-CTLA-4 (150 µg). n = number of mice in each treatment 32 group. All treatments ceased by day 50. 33 12 3 3 Supplementary Figure S1. Quantitation of protein expression in HCC1806 and 13 MDAMB2321 cells following 72 hour treatment with vehicle, 1 µM of BYL719, 1 µM 14 of LEE011, or the combination. Lysates were made and probed with indicated 15 antibodies. Signal intensities were quantitated using Image J. Data represents signal 16 intensity of indicated protein expression relative to vehicle treatment group. 17 18 4 4 19 19 5 5 Supplementary Figure S2. Combined BYL719 and LEE011 induces anti-tumor 20 immunity in AT3OVA mouse model of TNBC in vivo. Tumor-bearing mice were 21 treated with vehicle, BYL719 (10 mg/kg), LEE011 (40 mg/kg) or the combination for 22 7 days in vivo. N=5-11 mice per treatment group. Tumors were then harvested and 23 tumor-infiltrating (A) CD8+ T cells, (B) CD4+ T cells and (C) innate immune cells were 24 analysed using flow cytometry. Data in this figure represent mean ± SEM. p<0.05, 25 p<0.01, p<0.001, ***p<0.0001 by one-way ANOVA. 26 6 6 27 7 Supplementary Figure S3. Immune checkpoint blockade in combination with 28 BYL719 and LEE011 results in durable tumor regression in vivo. Tumor growth of 29 AT3OVA in each treatment group. Tumor-bearing mice were treated with indicated 30 drug combinations with the following doses: BYL719 (10mg/kg), LEE011 (40 mg/kg), 31 anti-PD-1 (200 µg) and anti-CTLA-4 (150 µg). n = number of mice in each treatment 32 group. All treatments ceased by day 50. 33 Supplementary Figure S3. Immune checkpoint blockade in combination with 28 BYL719 and LEE011 results in durable tumor regression in vivo. Tumor growth of 29 AT3OVA in each treatment group. Tumor-bearing mice were treated with indicated 30 drug combinations with the following doses: BYL719 (10mg/kg), LEE011 (40 mg/kg), 31 anti-PD-1 (200 µg) and anti-CTLA-4 (150 µg). n = number of mice in each treatment 32 group. All treatments ceased by day 50. 33 34 8 8 References 35 1. Lehmann BD, Bauer JA, Chen X, Sanders ME, Chakravarthy AB, Shyr Y, et al. 36 Identification of human triple-negative breast cancer subtypes and preclinical models 37 for selection of targeted therapies. J Clin Invest 2011;121(7):2750-67 doi 38 10.1172/jci45014. 39 2. Neve RM, Chin K, Fridlyand J, Yeh J, Baehner FL, Fevr T, et al. A collection of 40 breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer 41 Cell 2006;10(6):515-27 doi 10.1016/j.ccr.2006.10.008. 42 3. Forbes SA, Beare D, Boutselakis H, Bamford S, Bindal N, Tate J, et al. COSMIC: 43 somatic cancer genetics at high-resolution. Nucleic Acids Research 44 2017;45(D1):D777-D83 doi 10.1093/nar/gkw1121. 45 46 1. Lehmann BD, Bauer JA, Chen X, Sanders ME, Chakravarthy AB, Shyr Y, et al. 36 Identification of human triple-negative breast cancer subtypes and preclinical models 37 for selection of targeted therapies. J Clin Invest 2011;121(7):2750-67 doi 38 10.1172/jci45014. 39 1. Lehmann BD, Bauer JA, Chen X, Sanders ME, Chakravarthy AB, Shyr Y, et al. 36 Identification of human triple-negative breast cancer subtypes and preclinical models 37 for selection of targeted therapies. J Clin Invest 2011;121(7):2750-67 doi 38 10.1172/jci45014. 39 1. Lehmann BD, Bauer JA, Chen X, Sanders ME, Chakravarthy AB, Shyr Y, et al. 36 Identification of human triple-negative breast cancer subtypes and preclinical models 37 for selection of targeted therapies. J Clin Invest 2011;121(7):2750-67 doi 38 10.1172/jci45014. 39 2. Neve RM, Chin K, Fridlyand J, Yeh J, Baehner FL, Fevr T, et al. A collection of 40 b t ll li f th t d f f ti ll di ti t bt C 41 ( ) j 3. Forbes SA, Beare D, Boutselakis H, Bamford S, Bindal N, Tate J, et al. COSMIC: 43 somatic cancer genetics at high-resolution. Nucleic Acids Research 44 2017;45(D1):D777-D83 doi 10.1093/nar/gkw1121. 45 ( ) j 3. Forbes SA, Beare D, Boutselakis H, Bamford S, Bindal N, Tate J, et al. COSMIC: 43 somatic cancer genetics at high-resolution. Nucleic Acids Research 44 2017;45(D1):D777-D83 doi 10.1093/nar/gkw1121. 45 46 9 9
https://openalex.org/W3086403437	https://www.biorxiv.org/content/biorxiv/early/2021/02/05/2020.09.10.291658.full.pdf	English	null	The temporal and spectral characteristics of expectations and prediction errors in pain and thermoception	bioRxiv (Cold Spring Harbor Laboratory)	2,020	cc-by	20,411	. CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint The temporal and spectral characteristics of expectations and 1 prediction errors in pain and thermoception 2 Andreas Strube1, Michael Rose1, Sepideh Fazeli1 & Christian Büchel1 3 1Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany 4 5 Corresponding Author: Christian Büchel 6 Department of Systems Neuroscience 7 University Medical Center Hamburg-Eppendorf 8 20246 Hamburg, Germany 9 Phone: +49 40 7410 57 10 email: buechel@uke.de 11 12 Keywords: pain, thermoception, expectation, prediction error 13 14 The temporal and spectral characteristics of expectations and 1 prediction errors in pain and thermoception 2 1 1 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint Abstract 15 In the context of a generative model, such as predictive coding, pain and heat perception 16 can be construed as the integration of expectation and input with their difference 17 denoted as a prediction error. In a previous neuroimaging study (Geuter et al., 2017) we 18 observed an important role of the insula in such a model, but could not establish its 19 temporal aspects. Here we employed electroencephalography to investigate neural 20 representations of predictions and prediction errors in heat and pain processing. Our 21 data show that alpha-to-beta activity was associated with stimulus intensity expectation, 22 followed by a negative modulation of gamma band activity by absolute prediction errors. 23 This is in contrast to prediction errors in visual and auditory perception, which are 24 associated with increased gamma band activity, but is in agreement with observations in 25 working memory and word matching, which show gamma band activity for correct, 26 rather than violated predictions. 27 Introduction 28 It has been shown that physically identical nociceptive input, can lead to variable 29 sensations of pain, depending on contextual factors (Tracey and Mantyh, 2007). In 30 particular, attention, reappraisal and expectation are core mechanisms that influence 31 how nociception leads to pain (Wiech et al., 2008). A clinically important example of 32 how expectations can shape pain processing is placebo hypoalgesia: pain relief mediated 33 by expectation and experience - in the absence of active treatment (Petrovic et al., 2002; 34 Wager et al., 2004; Colloca and Benedetti, 2005; Bingel et al., 2006; Atlas and Wager, 35 2012; Anchisi and Zanon, 2015). 36 In the context of a generative model of pain, it has been proposed that pain perception 37 can be seen as the consequence of an integration of expectations with nociception 38 (Büchel et al., 2014; Wiech, 2016; Ongaro and Kaptchuk, 2019). In this framework, 39 expectations are integrated with incoming nociceptive information and both are 40 weighted by their relative precision (Grahl et al., 2018) to form a pain percept. This can 41 be seen in analogy to ideas in multisensory integration (Ernst and Banks, 2002). 42 Expectations or predictions and resulting prediction errors also play a key role in 43 generative models such as predictive coding (Huang and Rao, 2011). In essence, this 44 framework assumes that neuronal assemblies implement perception and learning by 45 2 . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint constantly matching incoming sensory data with the top-down predictions of an internal 46 or generative model (Knill and Pouget, 2004; Huang and Rao, 2011; Clark, 2013). 47 Basically, minimizing prediction errors allows systems to resist their tendency to 48 disorder by the creation of models with better predictions regarding the sensory 49 environment, leading to a more efficient encoding of information (Friston, 2010). Introduction 28 CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint both terms as required for predictive coding (Büchel et al., 2014; Ongaro and Kaptchuk, 78 2019). However, in fMRI studies predictions and prediction errors cannot be temporally 79 dissociated due to the low temporal resolution of the method. To investigate this further, 80 we conducted a cue based pain experiment using EEG to achieve high temporal and 81 spectral resolution of predictions and prediction error processes in the context of pain. 82 both terms as required for predictive coding (Büchel et al., 2014; Ongaro and Kaptchuk, 78 2019). However, in fMRI studies predictions and prediction errors cannot be temporally 79 dissociated due to the low temporal resolution of the method. To investigate this further, 80 we conducted a cue based pain experiment using EEG to achieve high temporal and 81 spectral resolution of predictions and prediction error processes in the context of pain. 82 In this experiment (N=29) we employed contact heat stimuli with three different 83 intensities (low heat, medium heat and high heat), preceded by a visual cue indicating 84 the upcoming intensity (Figure 1). To generate prediction errors, the modality (picture 85 or heat) was correctly cued only in 70% of all trials and stimulus intensities were 86 correctly cued only in 60% of all trials. We then investigated oscillatory activity related 87 to stimulus intensity, expectation and prediction errors (Figure 2). 88 89 Figure 1. Left: Graphical representation of the trial structure. Each trial started with the 90 presentation of a cue, indicating the stimulus intensity and modality of the following stimulus. 91 After a jittered phase where only the fixation cross was shown, the stimulus (visual or thermal) 92 was presented. A rating phase (1-4) of the stimulus aversiveness followed. Right: Contingency 93 table for all conditions for each cue-stimulus combination. Introduction 28 50 EEG correlates of nociceptive skin stimulation have been widely investigated. Generally, 51 phasic gamma activity has been associated with stimulus intensity over the sensory 52 cortex where the amplitudes of pain-induced gamma oscillations increase with objective 53 stimulus intensity and subjective pain intensity (Gross et al., 2007; Hauck et al., 2007; 54 Zhang et al., 2012; Rossiter et al., 2013; Tiemann et al., 2015). Additionally, pain-related 55 gamma band oscillations have been linked to the insular cortex as well as temporal and 56 frontal regions using depth electrodes in epilepsy patients (Liberati et al., 2018). In tonic 57 painful heat stimulation, medial prefrontal gamma activity has been observed (Schulz et 58 al., 2015). In addition, gamma activity is enhanced by attention in human EEG 59 experiments in visual (Gruber et al., 1999), auditory (Tiitinen et al., 1993; Debener et al., 60 2003) and sensorimotor processing (i.e. tactile stimuli) (Bauer et al., 2006) as well as in 61 nociception (Hauck et al., 2007, 2015; Tiemann et al., 2010). 62 Pain-related alpha-to-beta band oscillations are typically found to be suppressed with 63 higher stimulus intensity (Mouraux et al., 2003; Ploner et al., 2006; May et al., 2012; Hu 64 et al., 2013), which is enhanced by attention (May et al., 2012) and (placebo) expectation 65 (Huneke et al., 2013; Tiemann et al., 2015; Albu and Meagher, 2016). Interestingly, pre- 66 stimulus theta (Taesler and Rose, 2016) as well as pre-stimulus alpha and gamma 67 activity (Tu et al., 2016) can affect subsequent pain processing. Specifically, trials with 68 smaller pre-stimulus alpha and gamma oscillations were perceived as more painful, 69 suggesting a negative modulation of subsequent pain perception (Tu et al., 2016). 70 Cued pain paradigms (Atlas et al., 2010) have been used to generate expectations and 71 prediction errors. Previous fMRI studies have suggested an important role of the 72 anterior insular cortex for mediating expectation effects and the integration of prior 73 expectation and prediction errors in the context of pain (Ploghaus et al., 1999; Koyama 74 et al., 2005; Atlas et al., 2010; Geuter et al., 2017; Fazeli and Büchel, 2018). These studies 75 have revealed that neuronal signals in the anterior insula represent predictions and 76 prediction errors with respect to pain, which in theory would allow the combination of 77 3 3 . Introduction 28 (ii) Based on the functional neuroanatomy of cortical 104 microcircuits (Bastos et al., 2012), with feedforward connections predominately 105 originating from superficial layers and feedback connections from deep layers, we 106 expect that prediction error signals should be related to higher frequencies (e.g. gamma 107 band) than prediction signals (Todorovic et al., 2011; Arnal and Giraud, 2012). 108 Based on previous data, we (i) hypothesized that expectation signals should temporally 103 precede prediction error signals. (ii) Based on the functional neuroanatomy of cortical 104 microcircuits (Bastos et al., 2012), with feedforward connections predominately 105 originating from superficial layers and feedback connections from deep layers, we 106 expect that prediction error signals should be related to higher frequencies (e.g. gamma 107 band) than prediction signals (Todorovic et al., 2011; Arnal and Giraud, 2012). 108 Introduction 28 Note that percentages are for all 94 trials, therefore each row adds up to 1/6 (6 different cues). 95 89 89 Figure 1. Left: Graphical representation of the trial structure. Each trial started with the 90 presentation of a cue, indicating the stimulus intensity and modality of the following stimulus. 91 After a jittered phase where only the fixation cross was shown, the stimulus (visual or thermal) 92 was presented. A rating phase (1-4) of the stimulus aversiveness followed. Right: Contingency 93 table for all conditions for each cue-stimulus combination. Note that percentages are for all 94 trials, therefore each row adds up to 1/6 (6 different cues). 95 . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint 96 Figure 2. Hypothetical response patterns based on Stimulus Intensity (left), Expectation 97 (middle) and Absolute Prediction Error (right). The y-axis represents a hypothetical response 98 variable (e.g. EEG power). Each dot represents a different condition for each stimulus-cue 99 combination. Blue colors represent low heat conditions, green colors represent medium heat 100 conditions and red colors represent high heat conditions. Color intensities depict expectation 101 level. 102 96 96 Figure 2. Hypothetical response patterns based on Stimulus Intensity (left), Expectation 97 (middle) and Absolute Prediction Error (right). The y-axis represents a hypothetical response 98 variable (e.g. EEG power). Each dot represents a different condition for each stimulus-cue 99 combination. Blue colors represent low heat conditions, green colors represent medium heat 100 conditions and red colors represent high heat conditions. Color intensities depict expectation 101 level. 102 Based on previous data, we (i) hypothesized that expectation signals should temporally 103 precede prediction error signals. Participants 110 We investigated 35 healthy male participants (mean 26, range: 18–37 years), who were 111 paid as compensation for their participation. Applicants were excluded if one of the 112 following exclusion criteria applied: neurological, psychiatric, dermatological diseases, 113 pain conditions, current medication, or substance abuse. All volunteers gave their 114 informed consent. The study was approved by the Ethics board of the Hamburg Medical 115 Association. Of 35 participants, data from six participants had to be excluded from the 116 final EEG data analysis due to technical issues during the EEG recording (i.e.: the data of 117 We investigated 35 healthy male participants (mean 26, range: 18–37 years), who were 111 paid as compensation for their participation. Applicants were excluded if one of the 112 following exclusion criteria applied: neurological, psychiatric, dermatological diseases, 113 pain conditions, current medication, or substance abuse. All volunteers gave their 114 informed consent. The study was approved by the Ethics board of the Hamburg Medical 115 Association. Of 35 participants, data from six participants had to be excluded from the 116 final EEG data analysis due to technical issues during the EEG recording (i.e.: the data of 117 . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint the excluded participants were contaminated with excessive muscle and/or technical 118 artifacts) leaving a final sample of 29 participants. The sample size was determined 119 according a power calculation (G*Power V 3.1.9.4) based on Geuter et al., 2017. For the 120 left anterior insula (fMRI; Table 1 in Geuter et al., 2017) we observed an effect size of 121 partial eta squared of 0.17 and an effect size of 0.22 for the right anterior insula (Cue x 122 stimulus interaction). Participants 110 Using a power of (1-beta) of 0.95 and an alpha level of 0.05 and 123 assuming a low correlation (0.1) between repeated measures, this leads to a sample size 124 of 25 assuming the weaker effect in the left insula. 125 Stimuli and Task 126 ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint Each trial began with the presentation of the cue for 500ms as an indicator for the 149 modality and intensity of the subsequently presented stimulus. The modality was 150 correctly cued in 70% of all trials by the color of the triangle. In 60% of all trials, the 151 stimulus intensity was correctly indicated by the digit within the triangle (see Figure 1 152 for an overview of all cue contingencies). 153 Before the presentation of the stimulus, there was a blank period with a variable time 154 frame between 1000ms and 1400ms. Then, the visual or thermal stimulus was 155 presented for a duration of two seconds. The visual stimulus was centered on the screen 156 and allowed the participant to perceive the stimulus without eye movements. Right after 157 the termination of the stimulus, subjects were asked to rate the aversiveness of the 158 stimulus on a four point rating scale, where 1 was labeled as “neutral” and 4 was labeled 159 as “very strong”. Ratings were performed using a response box operated with the right 160 hand (see Figure 1 for a visualization of the trial structure). 161 In addition, four catch trials were included in each block. Subjects were asked to report 162 the preceding cue in terms of their information content of the modality and intensity 163 within 8s and no stimulation was given in these trials. 164 In addition, four catch trials were included in each block. Subjects were asked to report 162 the preceding cue in terms of their information content of the modality and intensity 163 within 8s and no stimulation was given in these trials. 164 Trials were presented in four blocks. Each block consisted of 126 trials and four catch 165 trials and lasted about 15 minutes. The trial order within each block was 166 pseudorandomized. The order of blocks was randomized across subjects. The whole EEG 167 experiment including preparation and instructions lasted for about three hours. 168 Prior to the actual EEG experiment, subjects participated in a behavioral training 169 session. During this session, participants were informed about the procedure and gave 170 their written informed consent. The behavioral training session was implemented to 171 avoid learning effects associated with the contingencies between the cues and the 172 stimuli during the EEG session. Stimuli and Task 126 Stimulus properties were chosen to be identical to a previous fMRI study of predictive 127 coding in pain where both expectation and absolute prediction error effects were 128 observed (Fazeli and Büchel, 2018). Thermal stimulation was performed using a 30 × 30 129 mm2 Peltier thermode (CHEPS Pathway, Medoc) at three different intensities: low heat 130 (42°C), medium heat (46°C), and high heat (48°C) at the left radial forearm. These three 131 temperatures cover a large range of temperatures associated with nociception. The 132 lowest temperature was set at 42°C to ensure a temperature above the median 133 threshold of heat sensitive C-fiber nociceptors which have a median heat threshold of 134 41°C (Treede et al., 1995). The baseline temperature was set at 33°C and the rise rate to 135 40°C/s. After two blocks, the stimulated skin patch was changed to avoid sensitization. 136 Aversive pictures were chosen from the International Affective Picture System (IAPS) 137 (Lang et al., 2008) database at three different levels of aversiveness. The images 138 presented during the EEG experiment had three levels of valence of which the low 139 valence category had valence values of 2.02±0.05 (mean ± standard error), the medium 140 valence category had valence values of 4.06±0.02 (mean ± standard error) and the high 141 valence category had valence values of 5.23±0.01 (mean ± standard error). 142 Prior to each picture or heat stimulus, a visual cue was presented. The color of the cue 143 (triangle) indicated (probabilistically) the modality of the stimulus (orange for picture 144 and blue for heat). A white digit written inside of each triangle indicated 145 (probabilistically) the intensity of the subsequent stimulus (1, 2 and 3 for low, medium 146 and high intensity). During the whole trial, a centered fixation cross was presented on 147 the screen. 148 6 . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. Stimuli and Task 126 Between two and three blocks were presented during 173 the training session (without electrophysiological recordings). The experimenter 174 assessed the performance after each block based on the percentage of successful catch 175 trials and the ability to distinguish the three levels of aversiveness of each modality. The 176 training session was terminated after the second block if participants were able to 177 successfully label cues in 75% of the catch trials within the second block. 178 7 7 7 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint EEG Data Acquisition 179 EEG data were acquired using a 64-channel Ag/AgCl active electrode system (ActiCap64; 180 BrainProducts) placed according to the extended 10–20 system (Klem et al., 1999). Sixty 181 electrodes were used of the most central scalp positions. The EEG was sampled at 182 500Hz, referenced at FCz and grounded at Iz. For artifact removal, a horizontal, bipolar 183 electrooculogram (EOG) was recorded using two of the remaining electrodes and 184 placing them on the skin approximately 1cm left from the left eye and right from the 185 right eye at the height of the pupils. One vertical electrooculogram was recorded using 186 one of the remaining electrodes centrally approx. 1cm beneath the left eye lid and 187 another electrode was fixated on the neck at the upper part of the left trapezius muscle 188 (Musculus trapezius) to record an electromyogram (EMG). 189 EEG Preprocessing 190 Using this procedure, up 212 to 30 components were removed before remaining non-artifactual components were 213 back-projected and resulted in corrected data. Subsequently, the data was re-referenced 214 to a common average of all EEG channels and the previous reference channel FCz was 215 re-used as a data channel (see Figure 1, figure supplement 1 for a summary of rejected 216 components per participant). 217 compared with the raw ICA components. Specifically, single and separate muscle spikes 211 were identified as columns or “clouds” in time-frequency plots. Using this procedure, up 212 to 30 components were removed before remaining non-artifactual components were 213 back-projected and resulted in corrected data. Subsequently, the data was re-referenced 214 to a common average of all EEG channels and the previous reference channel FCz was 215 re-used as a data channel (see Figure 1, figure supplement 1 for a summary of rejected 216 components per participant). 217 Before time-frequency transformations for data analysis were performed on the cleaned 218 data set, the time axis of single trials were shifted to create cue-locked and stimulus- 219 locked data. Cue-locked data uses the onset of the cue as t = 0. Stimulus-locked data 220 takes the ramp up period of the thermode into account and sets t = 0 to the time point 221 when the thermode reached the target temperature (225ms, 325ms and 375 after 222 trigger onset for low, medium and high heat conditions, respectively). Frequencies up to 223 30 Hz (1 to 30Hz in 1Hz steps) were analyzed using a sliding Hanning-window Fourier 224 transformation with a window length of 300ms and a step-size of 50ms. For the analysis 225 of frequencies higher than 30Hz (31 to 100Hz in 1Hz steps) spectral analyses of the EEG 226 data were performed using a sliding window multi-taper analysis. A window of 200ms 227 length was shifted over the data with a step size of 50ms with a spectral smoothing of 15 228 Hz. Spectral estimates were averaged for each subject over trials. Afterwards, a z- 229 baseline normalization was performed based on a 500ms baseline before cue onset. For 230 cue-locked data, a time frame ranging from -650ms to -150ms was chosen as a baseline. 231 A distance from the cue onset to the baseline period of 150ms was set because of the 232 half-taper window length of 150ms, i.e. EEG Preprocessing 190 The data analysis was performed using the Fieldtrip toolbox for EEG/MEG-analysis 191 (Oostenveld et al., 2011, Donders Institute for Brain, Cognition and Behaviour, Radboud 192 University Nijmegen, the Netherlands. See http://www.ru.nl/neuroimaging/fieldtrip). 193 EEG data were epoched and time-locked to the stimulus onset using the electrical trigger 194 signaling the thermode to start the temperature rise of a given heat trial. Each epoch 195 was centered (subtraction of the temporal mean) and detrended and included a time 196 range of 3410ms before and 2505ms after trigger onset. 197 The data was band-pass filtered at 1-100Hz, Butterworth, 4th order. EEG epochs were 198 then visually inspected and trials contaminated by artifacts due to gross movements or 199 technical artifacts were removed. Subsequently, trials contaminated by eye-blinks and 200 movements were corrected using an independent component analysis (ICA) algorithm 201 (Makeig et al., 1996; Jung et al., 2000). In all datasets, individual eye movements, 202 showing a large EOG channel contribution and a frontal scalp distribution, were clearly 203 seen in the removed independent components. Additionally, time-frequency 204 decomposed ICA data were inspected at a single trial level, after z-transformation (only 205 for artifact detection purposes) based on the mean and the standard deviation across all 206 components separately for each frequency from 31 to 100Hz. Time-Frequency 207 representations were calculated using a sliding window multi-taper analysis with a 208 window of 200ms length, which was shifted over the data with a step size of 20ms with 209 a spectral smoothing of 15 Hz. Artifact components or trials were easily visible and were 210 8 . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint compared with the raw ICA components. Specifically, single and separate muscle spikes 211 were identified as columns or “clouds” in time-frequency plots. EEG Preprocessing 190 data points between -150ms and 0ms are 233 contaminated by the onset of the cue. For stimulus-locked trials, a variable cue duration 234 (1500-1900ms) and a variable stimulus offset based on the ramp-up time (225-375ms) 235 were additionally taken into account, resulting in an according baseline from -2950ms to 236 -2450ms from stimulus onset. For the baseline correction of time-frequency data, the 237 mean and standard deviation were estimated for the baseline period (for each subject- 238 channel-frequency combination, separately). The mean spectral estimate of the baseline 239 was then subtracted from each data point, and the resulting baseline-centered values 240 were divided by the baseline standard deviation (classical baseline normalization – 241 additive model; see Grandchamp and Delorme, 2011). 242 9 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint Predictive Coding Model 243 Similar to a previous fMRI study (Fazeli and Büchel, 2018), our full model included three 244 experimental within-subject factors (see Figure 2). The stimulus intensity factor (INT) 245 models the measured response with a simple linear function of the stimulus intensity (- 246 1, 0 and 1 for low, medium and high intensities, respectively). The expectation (EXP) 247 factor was defined (see Figure 2; center column) linearly from the intensity predicted by 248 the cue. Again, conditions with a low intensity cue were coded with a -1, conditions with 249 a medium intensity cue with a 0 and conditions with a high intensity cue with a 1. The 250 absolute prediction error factor (PE) resulted from the absolute difference of the 251 expectation and actual stimulus intensity (see Figure 2; right column). 252 We also investigated a signed PE. However, it should be noted that such a term is not 253 orthogonal to the expectation factor. However, assuming that an expectation can only be 254 observed after the cue and a PE after the nociceptive stimulus, we were able to test for a 255 signed PE during the heat phase. Also, we considered a one-sided prediction error 256 factor, where a prediction error is only signaled when the stimulus is more intense as 257 expected, which is motivated by previous work (Egner et al., 2010; Summerfield and de 258 Lange, 2014; Geuter et al., 2017). 259 As the lowest stimulus intensity was often perceived as non-painful, we additionally 260 performed an analysis only with medium and high stimulus intensities. Accordingly, the 261 lowest stimulus intensity (42°C) were excluded in an additional repeated measures 262 ANOVA analysis for this purpose (which will be referred to as the reduced pain model). 263 Behavioral aversiveness ratings were averaged for all 3x3 cue-stimulus combinations 265 over each participant, resulting in a 29x9 matrix (subject x condition) for the full model 266 and a 29x6 matrix for the reduced pain model. We tested for main effects across 267 stimulus intensity, expectation, as well as prediction error using a repeated measures 268 ANOVA as implemented in MATLAB (see fitrm and ranova; version 2020a, The 269 MathWorks). 270 Behavioral aversiveness ratings were averaged for all 3x3 cue-stimulus combinations 265 over each participant, resulting in a 29x9 matrix (subject x condition) for the full model 266 and a 29x6 matrix for the reduced pain model. Predictive Coding Model 243 We tested for main effects across 267 stimulus intensity, expectation, as well as prediction error using a repeated measures 268 ANOVA as implemented in MATLAB (see fitrm and ranova; version 2020a, The 269 MathWorks). 270 10 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint EEG data analysis 271 All statistical tests in electrode space were corrected for multiple comparisons using 272 non-parametrical permutation tests of clusters (Maris & Oostenveld, 2007). Cluster 273 permutation tests take into account that biological processes are not strictly locked to a 274 single frequency or time point and that activity could be picked up by multiple 275 electrodes. Cluster permutation tests are specifically useful for explorative testing, as 276 explained by Maris & Oostenveld (2007). While prior hypotheses could have been 277 formulated regarding the spatial, temporal and spectral characteristics of brain 278 responses associated with the intensity of thermal stimulation and regions-of-interest 279 could have been described, variations in the present design could be related to temporal 280 and spectral differences compared to other studies which would be taken into account 281 using non-parametric cluster permutation testing. 282 We wanted to explore positive and negative time-frequency patterns associated with 283 our variations of stimulus intensity, expectation and absolute prediction errors using a 284 repeated measures ANOVA. A statistical value corresponding to a p-value of .05 (F(1,28) 285 = 4.196) obtained from the repeated measures ANOVA F-statistics of the respective 286 main effect was used for clustering. Samples (exceeding the threshold of F(1,28) = 287 4.196) were clustered in connected sets on the basis of temporal (i.e. adjacent time 288 points), spatial (i.e. neighboring electrodes) and spectral (i.e. +/- 1Hz) adjacency. 289 Further, clustering was restricted in a way that only samples were included in a cluster 290 which had at least one significant neighbor in electrode space, i.e. at least one 291 neighboring channel also had to exceed the threshold for a sample to be included in the 292 cluster. Neighbors were defined by a template provided by the Fieldtrip toolbox 293 corresponding to the used EEG montage. 294 Subsequently, a cluster value was defined as the sum of all statistical values of included 295 samples. Monte Carlo sampling was used to generate 1000 random permutations of the 296 design matrix and statistical tests were repeated in time-frequency space with the 297 random design matrix. The probability of a cluster from the original design matrix (p- 298 value) was calculated by the proportion of random design matrices producing a cluster 299 with a cluster value exceeding the original cluster. This test was applied two-sided for 300 negative and positive clusters, which were differentiated by the average slope of the 301 estimated factors. EEG data analysis 271 302 Subsequently, a cluster value was defined as the sum of all statistical values of included 295 samples. Monte Carlo sampling was used to generate 1000 random permutations of the 296 design matrix and statistical tests were repeated in time-frequency space with the 297 random design matrix. The probability of a cluster from the original design matrix (p- 298 value) was calculated by the proportion of random design matrices producing a cluster 299 with a cluster value exceeding the original cluster. This test was applied two-sided for 300 negative and positive clusters, which were differentiated by the average slope of the 301 estimated factors. 302 11 . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint Monte Carlo cluster tests were performed with 1000 permutations using the test 303 statistics of a repeated measures ANOVA model as the value for clustering (at p < .05 / 304 F(1,28) = 4.196). All tests were performed for low frequencies (1-30Hz) and high 305 frequencies (31-100Hz), separately. Muscular and ocular electrodes were excluded from 306 the cluster analysis. 307 Monte Carlo cluster tests were performed with 1000 permutations using the test 303 statistics of a repeated measures ANOVA model as the value for clustering (at p < .05 / 304 F(1,28) = 4.196). All tests were performed for low frequencies (1-30Hz) and high 305 frequencies (31-100Hz), separately. Muscular and ocular electrodes were excluded from 306 the cluster analysis. 307 The within-subject stimulus intensity factor (which was coded as increasing linearly 308 with stimulus intensity) was tested stimulus-locked from 0 to 1.6s. The within-subject 309 expectation factor, which was coded as increasing linearly with the cued stimulus 310 intensity was tested cue-locked from 0 to 3.6s. The signed prediction error factor was 311 coded as the difference between stimulus intensity and expectation. EEG data analysis 271 The absolute 312 prediction error was coded as the absolute difference between stimulus intensity and 313 expectation (see Figure 2 for details). Additionally, we tested a one-sided prediction 314 error, occurring only when the actual stimulus is of a higher intensity than expected. The 315 signed, absolute and one-sided prediction error factors were tested stimulus-locked 316 from 0 to 1.6s. 317 Behavioral data - aversiveness ratings 319 Behavioral data - aversiveness ratings 319 Participants experienced aversive heat or saw picture stimuli which were 320 probabilistically cued in terms of modality and intensity, evoking an expectation of 321 modality and intensity. The subsequently applied stimuli were then rated on a visual 322 analog scale (VAS) from 1-4. Our primary behavioral question was whether ratings are 323 influenced by the experimental manipulation of stimulus intensity, expectation and 324 absolute prediction errors. 325 To validate our intensity manipulation for thermal stimuli and to verify the 326 discriminability between different levels of heat, we first tested for the main effect of 327 stimulus intensity (Figure 3a). Our data show a clear rating difference between the three 328 levels of heat. Results regarding the aversive pictures are not the focus of this report but 329 are depicted in Figure 3b for the sake of comparison. 330 331 12 12 . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint 332 Figure 3. Bars indicate pooled aversiveness ratings for a) heat and b) aversive pictures for low, 333 medium and high intensity conditions. Dots indicate average single subject ratings. 334 332 Figure 3. Bars indicate pooled aversiveness ratings for a) heat and b) aversive pictures for low, 333 medium and high intensity conditions. Dots indicate average single subject ratings. 334 To evaluate the main effects of stimulus intensity, expectation and absolute prediction 335 errors, we employed a repeated measures ANOVA of the behavioral data, which revealed 336 significant effects for the main effect of stimulus intensity, i.e. the three levels of heat 337 (F(1,28) = 743.97, p < .001). Also, the main effect for expectation on aversiveness ratings 338 was significant (F(1,28) = 38.53, p = < .001) (Table 1), indicating an influence of the cued 339 intensity on behavioral aversiveness ratings (Figure 4). Behavioral data - aversiveness ratings 319 The absolute difference between 340 the cued intensity and the actual stimulus intensity (i.e. absolute prediction error), only 341 showed a trend effect on aversiveness ratings (F(1,28) = 2.87, p = .10). The results 342 regarding the aversive pictures are summarized in Table 1. 343 To evaluate the main effects of stimulus intensity, expectation and absolute prediction 335 errors, we employed a repeated measures ANOVA of the behavioral data, which revealed 336 significant effects for the main effect of stimulus intensity, i.e. the three levels of heat 337 (F(1,28) = 743.97, p < .001). Also, the main effect for expectation on aversiveness ratings 338 was significant (F(1,28) = 38.53, p = < .001) (Table 1), indicating an influence of the cued 339 intensity on behavioral aversiveness ratings (Figure 4). The absolute difference between 340 the cued intensity and the actual stimulus intensity (i.e. absolute prediction error), only 341 showed a trend effect on aversiveness ratings (F(1,28) = 2.87, p = .10). The results 342 regarding the aversive pictures are summarized in Table 1. 343 To evaluate the main effects of stimulus intensity, expectation and absolute prediction 335 errors, we employed a repeated measures ANOVA of the behavioral data, which revealed 336 significant effects for the main effect of stimulus intensity, i.e. the three levels of heat 337 (F(1,28) = 743.97, p < .001). Also, the main effect for expectation on aversiveness ratings 338 was significant (F(1,28) = 38.53, p = < .001) (Table 1), indicating an influence of the cued 339 intensity on behavioral aversiveness ratings (Figure 4). The absolute difference between 340 the cued intensity and the actual stimulus intensity (i.e. absolute prediction error), only 341 showed a trend effect on aversiveness ratings (F(1,28) = 2.87, p = .10). The results 342 regarding the aversive pictures are summarized in Table 1. 343 344 Table 1. Main effects of stimulus intensity, expectation and absolute prediction errors on 345 subjective ratings in both heat and picture conditions. 346 344 Table 1. Main effects of stimulus intensity, expectation and absolute prediction errors on 345 subjective ratings in both heat and picture conditions. 346 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. Behavioral data - aversiveness ratings 319 ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint 347 Figure 4. Ratings for heat stimuli (left) and “expectation factor” weights (right). Bars indicate 348 average aversiveness ratings. Ratings were given on a scale from 1 to 4. Error bars depict SEM. 349 The data shows both an effect of stimulus intensity (increase from blue to green to red), but also 350 an effect of expectation (low to medium to high expectation). The right figure represents 351 hypothetical response patterns based on the expectation factor. The y-axis represents the 352 hypothetical response variable (e.g. VAS rating). Each dot represents a different condition for 353 each stimulus-cue combination. Blue colors represent low heat conditions, green colors 354 represent medium heat conditions and red colors represent high heat conditions. Color 355 intensities depict expectation level. 356 47 347 Figure 4. Ratings for heat stimuli (left) and “expectation factor” weights (right). Bars indicate 348 average aversiveness ratings. Ratings were given on a scale from 1 to 4. Error bars depict SEM. 349 The data shows both an effect of stimulus intensity (increase from blue to green to red), but also 350 an effect of expectation (low to medium to high expectation). The right figure represents 351 hypothetical response patterns based on the expectation factor. The y-axis represents the 352 hypothetical response variable (e.g. VAS rating). Each dot represents a different condition for 353 each stimulus-cue combination. Blue colors represent low heat conditions, green colors 354 represent medium heat conditions and red colors represent high heat conditions. Color 355 intensities depict expectation level. 356 In a first EEG analysis, we tested for a main effect of the intensity of the heat input in the 358 context of a correctly cued modality (i.e. heat was expected and received). In order to do 359 so, we performed a repeated measures ANOVA on the time-frequency representation of 360 the EEG data on low frequencies (1-30Hz) and high frequencies (31-100Hz) separately 361 after stimulus onset using a cluster correction criterion to address the multiple 362 comparisons problem (see Methods for details). Any significant cluster – composed of 363 neighboring data points in time, frequency and space – would indicate a neuronal 364 oscillatory representation of variations in stimulus intensity in a given frequency band. 365 In the low frequency range (1-30Hz), one positive cluster (i.e. a positive average slope of 366 the factor) and one negative cluster (i.e. Behavioral data - aversiveness ratings 319 This sample was observed at 1250ms and 22Hz and had a maximum at 373 channel CP2. All channels included samples of the negative low frequency stimulus 374 intensity cluster. 375 F-value within this cluster obtained from the repeated measures ANOVA was F(1,28) = 372 36.40, (p < .001). This sample was observed at 1250ms and 22Hz and had a maximum at 373 channel CP2. All channels included samples of the negative low frequency stimulus 374 intensity cluster. 375 F-value within this cluster obtained from the repeated measures ANOVA was F(1,28) = 372 36.40, (p < .001). This sample was observed at 1250ms and 22Hz and had a maximum at 373 channel CP2. All channels included samples of the negative low frequency stimulus 374 intensity cluster. 375 Also in the low frequency range (1-30Hz), a positive significant cluster included samples 376 in a time range from 150 to 1050ms after stimulus onset in the theta frequency range 377 from 1 to 7Hz predominately at midline electrode sites (p = .048). The highest 378 parametric F-Value from the repeated measures ANOVA was F(1,28) = 27.93, (p < .001). 379 This sample was found at 550ms and 3Hz and had a maximum at channel O2. All 380 channels except FC5, CP4, C6 and FT7 were part of the positive low frequency stimulus 381 intensity cluster. 382 In the high frequency range (31-100Hz) representing gamma activity one positive 383 cluster was significant (p < .001). This cluster included samples in a time range from 550 384 to 1600ms after stimulus onset and frequencies from 46 to 100Hz, predominately at 385 contra-lateral centroparietal electrode sites (Figure 5). The highest parametric F-value 386 within this cluster obtained from the repeated measures ANOVA was F(1,28) = 33.35, (p 387 < .001). This sample was observed at 1600ms and 100Hz and had a maximum at channel 388 Cz. All channels included samples of the positive high frequency stimulus intensity 389 cluster. Behavioral data - aversiveness ratings 319 a negative average slope of the factor) were 367 significant (Figure 5), indicating a linear association of stimulus intensity and power in 368 this frequency range. Specifically, the negative cluster included samples in a time range 369 from 250 to 1600ms after stimulus onset in a frequency range from 1 to 30Hz, 370 predominately at contralateral central electrode sites (p = .002). The highest parametric 371 In a first EEG analysis, we tested for a main effect of the intensity of the heat input in the 358 context of a correctly cued modality (i.e. heat was expected and received). In order to do 359 so, we performed a repeated measures ANOVA on the time-frequency representation of 360 the EEG data on low frequencies (1-30Hz) and high frequencies (31-100Hz) separately 361 after stimulus onset using a cluster correction criterion to address the multiple 362 comparisons problem (see Methods for details). Any significant cluster – composed of 363 neighboring data points in time, frequency and space – would indicate a neuronal 364 oscillatory representation of variations in stimulus intensity in a given frequency band. 365 In the low frequency range (1-30Hz), one positive cluster (i.e. a positive average slope of 366 the factor) and one negative cluster (i.e. a negative average slope of the factor) were 367 significant (Figure 5), indicating a linear association of stimulus intensity and power in 368 this frequency range. Specifically, the negative cluster included samples in a time range 369 from 250 to 1600ms after stimulus onset in a frequency range from 1 to 30Hz, 370 predominately at contralateral central electrode sites (p = .002). The highest parametric 371 . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint F-value within this cluster obtained from the repeated measures ANOVA was F(1,28) = 372 36.40, (p < .001). Behavioral data - aversiveness ratings 319 390 In conclusion, these results indicate that a higher intensity of the thermal input is 391 associated with increased theta and gamma band power and a negative relationship of 392 alpha-to-beta band power and the intensity of the thermal input (see Figure 5 for a 393 summary of the results of the main effect of stimulus intensity; see Figure 5, figure 394 supplement 1 for single subject differences in the gamma band between low stimulus 395 intensity and high stimulus intensity trials). 396 In the high frequency range (31-100Hz) representing gamma activity one positive 383 cluster was significant (p < .001). This cluster included samples in a time range from 550 384 to 1600ms after stimulus onset and frequencies from 46 to 100Hz, predominately at 385 contra-lateral centroparietal electrode sites (Figure 5). The highest parametric F-value 386 within this cluster obtained from the repeated measures ANOVA was F(1,28) = 33.35, (p 387 < .001). This sample was observed at 1600ms and 100Hz and had a maximum at channel 388 Cz. All channels included samples of the positive high frequency stimulus intensity 389 cluster. 390 In the high frequency range (31-100Hz) representing gamma activity one positive 383 cluster was significant (p < .001). This cluster included samples in a time range from 550 384 to 1600ms after stimulus onset and frequencies from 46 to 100Hz, predominately at 385 contra-lateral centroparietal electrode sites (Figure 5). The highest parametric F-value 386 within this cluster obtained from the repeated measures ANOVA was F(1,28) = 33.35, (p 387 < .001). This sample was observed at 1600ms and 100Hz and had a maximum at channel 388 Cz. All channels included samples of the positive high frequency stimulus intensity 389 cluster. 390 In conclusion, these results indicate that a higher intensity of the thermal input is 391 associated with increased theta and gamma band power and a negative relationship of 392 alpha-to-beta band power and the intensity of the thermal input (see Figure 5 for a 393 summary of the results of the main effect of stimulus intensity; see Figure 5, figure 394 supplement 1 for single subject differences in the gamma band between low stimulus 395 intensity and high stimulus intensity trials). Behavioral data - aversiveness ratings 319 396 In conclusion, these results indicate that a higher intensity of the thermal input is 391 associated with increased theta and gamma band power and a negative relationship of 392 alpha-to-beta band power and the intensity of the thermal input (see Figure 5 for a 393 summary of the results of the main effect of stimulus intensity; see Figure 5, figure 394 supplement 1 for single subject differences in the gamma band between low stimulus 395 intensity and high stimulus intensity trials). 396 In conclusion, these results indicate that a higher intensity of the thermal input is 391 associated with increased theta and gamma band power and a negative relationship of 392 alpha-to-beta band power and the intensity of the thermal input (see Figure 5 for a 393 summary of the results of the main effect of stimulus intensity; see Figure 5, figure 394 supplement 1 for single subject differences in the gamma band between low stimulus 395 intensity and high stimulus intensity trials). 396 15 . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint 397 Figure 5. Parametric effects of stimulus intensity. Time-frequency representation averaged 398 over all channels including a significant time-frequency sample of any cluster (a) and 399 topographies over the whole cluster extents (i.e. full time and frequency range), respectively (b) 400 of the stimulus intensity main effect of the repeated measures ANOVA depicting increases 401 (warm) and decreases (cold) in power in relation to heat stimulus intensity. Significant clusters 402 are highlighted. Colors represent F-values from the repeated measures ANOVA statistics for the 403 main effect of stimulus intensity. 404 97 397 Figure 5. Parametric effects of stimulus intensity. Time-frequency representation averaged 398 over all channels including a significant time-frequency sample of any cluster (a) and 399 topographies over the whole cluster extents (i.e. Behavioral data - aversiveness ratings 319 full time and frequency range), respectively (b) 400 of the stimulus intensity main effect of the repeated measures ANOVA depicting increases 401 (warm) and decreases (cold) in power in relation to heat stimulus intensity. Significant clusters 402 are highlighted. Colors represent F-values from the repeated measures ANOVA statistics for the 403 main effect of stimulus intensity. 404 In a next step, we investigated the representation of the expectation factor in our 406 repeated measures model, again for low frequencies (1-30Hz) and high frequencies (31- 407 100Hz) separately in the cue-locked time-frequency representation of the EEG data. 408 This analysis revealed one significant positive cluster in the low frequency range (1- 409 30Hz), indicating a linear association of cue intensity (EXP) and power in this frequency 410 range (p < .05). The expectation cluster (p = .022) included samples from time points 411 ranging from 100ms to 2000ms after cue onset and included frequencies from 1 to 412 20Hz. The highest parametric statistical test value (F(1,28) = 26.96, p < .001) was 413 observed at channel P1 700ms after cue onset at a frequency of 9Hz. All channels except 414 TP8 included samples of the late expectation cluster (see Figure 6 for a summary of the 415 results of the expectation cluster; see Figure 6, figure supplement 1 for single subject 416 values). 417 In a next step, we investigated the representation of the expectation factor in our 406 repeated measures model, again for low frequencies (1-30Hz) and high frequencies (31- 407 100Hz) separately in the cue-locked time-frequency representation of the EEG data. 408 This analysis revealed one significant positive cluster in the low frequency range (1- 409 30Hz), indicating a linear association of cue intensity (EXP) and power in this frequency 410 range (p < .05). The expectation cluster (p = .022) included samples from time points 411 ranging from 100ms to 2000ms after cue onset and included frequencies from 1 to 412 20Hz. The highest parametric statistical test value (F(1,28) = 26.96, p < .001) was 413 observed at channel P1 700ms after cue onset at a frequency of 9Hz. All channels except 414 TP8 included samples of the late expectation cluster (see Figure 6 for a summary of the 415 results of the expectation cluster; see Figure 6, figure supplement 1 for single subject 416 values). 417 . Behavioral data - aversiveness ratings 319 CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint represent SEM. d) Predicted responses based on the positive expectation factor are shown: The 430 y-axis represents an imaginary response variable (e.g. EEG power). Each dot represents a 431 different condition (in the order of the bar plot representation of average EEG power) for each 432 stimulus-cue combination. Blue colors represent low heat conditions, green colors represent 433 medium heat conditions and red colors represent high heat conditions. Color intensities depict 434 expectation level. 435 represent SEM. d) Predicted responses based on the positive expectation factor are shown: The 430 y-axis represents an imaginary response variable (e.g. EEG power). Each dot represents a 431 different condition (in the order of the bar plot representation of average EEG power) for each 432 stimulus-cue combination. Blue colors represent low heat conditions, green colors represent 433 medium heat conditions and red colors represent high heat conditions. Color intensities depict 434 expectation level. 435 Likewise, clustering was performed for the prediction error term after stimulus onset in 437 low (1-30Hz) and high frequencies (31-100Hz). Any significant cluster would associate 438 oscillatory activity with the difference of the expectation regarding the intensity of the 439 thermal stimulation and the actual stimulation, representing a violation of this 440 expectation (prediction error). 441 This analysis revealed a significant negative cluster in the high frequency range (31- 442 100Hz), indicating a (negative) linear association of absolute prediction errors (PE) and 443 power in this frequency range (p = .002). This (negative) absolute prediction error 444 cluster included samples from frequencies ranging from 51 to 100Hz and time points 445 ranging from 50ms to 1600ms after stimulus onset. The highest parametric statistical 446 test value (F(1,28) = 28.52, p < .001) was found at channel O1 1300ms after stimulus 447 onset at a frequency of 98Hz. Behavioral data - aversiveness ratings 319 CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint In summary, these results suggest an increase in alpha-to-beta band power to be 418 associated with our experimental manipulation of expectations regarding the intensity 419 of the thermal input. 420 In summary, these results suggest an increase in alpha-to-beta band power to be 418 associated with our experimental manipulation of expectations regarding the intensity 419 of the thermal input. 420 21 Figure 6. The main effect of expectation. a) Time-frequency representation of the statistical F- 22 values averaged over all channels. The significant cluster is highlighted. The black box between 23 1500 and 1900ms marks the jittered onset of the trigger signal to start the ramp up of the heat 24 stimulus. b) Topography of the averaged power over time and frequency of the whole cluster 25 extent (i.e. over the whole time and frequency range) at each channel. Brighter colors indicate 26 higher F-values. c) Power values for all conditions with a valid modality cue (expect heat receive 27 heat) averaged over all significant time-frequency-electrode samples of the EXP cluster show 28 421 Figure 6. The main effect of expectation. a) Time-frequency representation of the statistical F- 422 values averaged over all channels. The significant cluster is highlighted. The black box between 423 1500 and 1900ms marks the jittered onset of the trigger signal to start the ramp up of the heat 424 stimulus. b) Topography of the averaged power over time and frequency of the whole cluster 425 extent (i.e. over the whole time and frequency range) at each channel. Brighter colors indicate 426 higher F-values. c) Power values for all conditions with a valid modality cue (expect heat receive 427 heat) averaged over all significant time-frequency-electrode samples of the EXP cluster show 428 alpha-to-beta enhancement (i.e. positive representation) associated with expectation. Error bars 429 . Behavioral data - aversiveness ratings 319 All channels included samples of the absolute prediction 448 error cluster (see Figure 7 for a summary of the results; see Figure 7, figure supplement 449 1 for single subject values). 450 A cluster analysis of the signed prediction error, stimulus-locked after stimulus onset 451 (from 1-30Hz for low frequencies and 31-100Hz for gamma frequencies; from 0 to 452 1600ms, stimulus-locked) did not reveal any significant cluster of activity associated 453 with a linear increase or decrease of the EXP factor (all p > .05). Ignoring all stimulus- 454 cue combinations of the prediction error factor where the stimulus intensity was less 455 intense than expected, leads to a one-sided prediction error factor. A cluster analysis of 456 this effect did not reveal any significant cluster of activity (all p > .05). 457 In summary, these results suggest a decrease in gamma band power to be associated 458 with our experimental manipulation of expectation violations, resulting from a 459 mismatch of the cued intensity and the actual heat input. 460 In summary, these results suggest a decrease in gamma band power to be associated 458 with our experimental manipulation of expectation violations, resulting from a 459 mismatch of the cued intensity and the actual heat input. 460 18 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint 1 Figure 7. The main effect of absolute prediction errors. a) Time-frequency representation of 2 the statistical F-values averaged over all channels. The significant cluster is highlighted. b) 3 Topography of the averaged power over time and frequency of the whole cluster extent (i.e. over 4 the whole time and frequency range) at each channel. Brighter colors indicate higher F-values. c) 5 Power values for all conditions with a valid modality cue (expect heat receive heat) averaged 6 over all significant time-frequency-electrode samples of the PE cluster show gamma decreases 7 (i.e. Behavioral data - aversiveness ratings 319 negative representation) associated with prediction errors. Error bars represent SEM. d) 8 461 Figure 7. The main effect of absolute prediction errors. a) Time-frequency representation of 462 the statistical F-values averaged over all channels. The significant cluster is highlighted. b) 463 Topography of the averaged power over time and frequency of the whole cluster extent (i.e. over 464 the whole time and frequency range) at each channel. Brighter colors indicate higher F-values. c) 465 Power values for all conditions with a valid modality cue (expect heat receive heat) averaged 466 over all significant time-frequency-electrode samples of the PE cluster show gamma decreases 467 (i.e. negative representation) associated with prediction errors. Error bars represent SEM. d) 468 Predicted responses based on the negative prediction error factor are shown: The y-axis 469 represents an imaginary response variable (e.g. EEG power). Each dot represents a different 470 condition (in the order of the bar plot representation of average EEG power) for each stimulus- 471 cue combination. Blue colors represent low heat conditions, green colors represent medium heat 472 conditions and red colors represent high heat conditions. Color intensities depict expectation 473 level. 474 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint Reduced Pain Model 475 In an additional analysis, we tested all effects in a reduced pain model, which only 476 included painful stimuli (i.e. three expectation levels and two intensity levels). 477 In an additional analysis, we tested all effects in a reduced pain model, which only 476 included painful stimuli (i.e. three expectation levels and two intensity levels). 477 To evaluate the main effects of stimulus intensity, expectation and absolute prediction 478 errors in the behavioral data, we employed again a repeated measures ANOVA which 479 revealed significant effects for the main effect of stimulus intensity, i.e. the two 480 remaining levels of pain (F(1,28) = 1109.9, p < .001). Also, the main effect for 481 expectation on pain ratings was significant (F(1,28) = 17.07, p = < .001), indicating again 482 an influence of the cued intensity on behavioral pain ratings. The absolute difference 483 between the cued intensity and the actual stimulus intensity (i.e. absolute prediction 484 error) when only painful stimuli were included revealed a positive significant effect on 485 pain ratings (F(1,28) = 80.75, p < .001). This indicates prediction errors and prior 486 expectations to modulate behavioral aversiveness ratings in painful stimulation. 487 For the analysis of time-frequency EEG data, we performed a repeated measures ANOVA 488 on the time-frequency representation of the EEG data on low frequencies (1-30Hz) and 489 high frequencies (31-100Hz) separately and again using the same cluster correction 490 criterion to address the multiple comparisons problem as in the initial analysis of the 491 full model. 492 The cluster test of stimulus intensity revealed one negative cluster (p = .014) in the low 493 frequency range (1-30Hz) including time points from 850 to 1600ms and frequencies 494 from 8 to 30Hz (Figure 8a; see Figure 8, figure supplement 1 for single subject values). 495 The maximum statistical F-value (F(1,28 = 31.82; p < .001) was found at channel AF3 at 496 a frequency of 30Hz at 1600ms and revealed a similar but more broad topography as 497 compared to the original alpha-to-beta negative main effect of stimulus intensity of the 498 analysis of the full model. All channels included samples of the negative stimulus 499 intensity cluster. Reduced Pain Model 475 500 In the high frequency range (31-100Hz), a negative cluster of activity (p = .038) was 501 associated with absolute prediction errors and included samples in a time range from 502 850 to 1600ms after stimulus onset in the gamma frequency range from 54 to 90Hz 503 predominately at occipital and parietal electrode sites. The highest parametric F-Value 504 from the repeated measures ANOVA was F(1,28) = 24.10, (p < .001). This sample was 505 In the high frequency range (31-100Hz), a negative cluster of activity (p = .038) was 501 associated with absolute prediction errors and included samples in a time range from 502 850 to 1600ms after stimulus onset in the gamma frequency range from 54 to 90Hz 503 predominately at occipital and parietal electrode sites. The highest parametric F-Value 504 from the repeated measures ANOVA was F(1,28) = 24.10, (p < .001). This sample was 505 20 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint found at 1150ms and 77Hz and had a maximum at channel F8 (Figure 8b; see Figure 8, 506 figure supplement 2 for single subject values). All channels except FC5, CP4, C6 and FT7 507 were part of the gamma frequency negative absolute prediction error cluster. 508 In the low (1-30Hz) and high frequency (31-100Hz) ranges no significant cluster was 509 observed representing a significant relationship between expectations and EEG activity. 510 However, one cluster in the low frequency range (1-30Hz) showed a trend level (p = 511 0.14; based on cluster mass, i.e. the sum of all clustered F-values) and included samples 512 in a time range from 550 to 1600ms after stimulus onset and frequencies from 6 to 24Hz 513 and is displayed in dotted lines in Figure 8c (see Figure 8, figure supplement 3 for single 514 subject values). Reduced Pain Model 475 515 found at 1150ms and 77Hz and had a maximum at channel F8 (Figure 8b; see Figure 8, 506 figure supplement 2 for single subject values). All channels except FC5, CP4, C6 and FT7 507 were part of the gamma frequency negative absolute prediction error cluster. 508 found at 1150ms and 77Hz and had a maximum at channel F8 (Figure 8b; see Figure 8, 506 figure supplement 2 for single subject values). All channels except FC5, CP4, C6 and FT7 507 were part of the gamma frequency negative absolute prediction error cluster. 508 21 . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint 516 Figure 8. EEG data analysis of the reduced pain model. The top three rows show (a) the main 517 effect of stimulus intensity, (b) the main effect of negative absolute prediction errors and (c) the 518 main effect of expectation. Left column: Time-frequency representation of the statistical F-values 519 averaged over all channels. Significant clusters are highlighted by a solid line. The non- 520 significant expectation cluster is highlighted by a thin dotted line. Right column: Power values 521 for all conditions included in the reduced model with a valid modality cue (expect heat receive 522 516 Figure 8. EEG data analysis of the reduced pain model. The top three rows show (a) the main 517 effect of stimulus intensity, (b) the main effect of negative absolute prediction errors and (c) the 518 main effect of expectation. Left column: Time-frequency representation of the statistical F-values 519 averaged over all channels. Significant clusters are highlighted by a solid line. The non- 520 significant expectation cluster is highlighted by a thin dotted line. Right column: Power values 521 for all conditions included in the reduced model with a valid modality cue (expect heat receive 522 16 Figure 8. EEG data analysis of the reduced pain model. Stimulus intensity and oscillatory activity 541 y y y Note that our definition of stimulus onset is based on the moment the thermode reached 542 the target temperature. Using a thermode heating gradient of 40°C/s and neglecting any 543 small internal delays, the target temperatures of 42, 46 and 48°C are reached after 225, 544 325 and 375ms respectively. Therefore our observed increase in theta power agrees 545 with previous studies (Ploner et al., 2017) and most likely correspond to pain-related 546 evoked potentials (Lorenz and Garcia-Larrea, 2003; Tiemann et al., 2015), such as the P2 547 with a similar topography. In addition we observed a significant suppression of alpha-to- 548 beta activity which, given the above mentioned delays of our painful stimuli, is in line 549 with the reported beta suppression in previous EEG studies on pain (Mouraux et al., 550 2003; Ploner et al., 2006; May et al., 2012; Hu et al., 2013). Finally, power in the gamma 551 band was also correlated with heat intensity, which is in line with previous studies 552 (Gross et al., 2007; Hauck et al., 2007; Zhang et al., 2012; Rossiter et al., 2013; Tiemann 553 et al., 2015). Interestingly, only the alpha-to-beta band desynchronization differentiated 554 between medium and high pain conditions, whereas differences in the theta and gamma 555 Note that our definition of stimulus onset is based on the moment the thermode reached 542 the target temperature. Using a thermode heating gradient of 40°C/s and neglecting any 543 small internal delays, the target temperatures of 42, 46 and 48°C are reached after 225, 544 325 and 375ms respectively. Therefore our observed increase in theta power agrees 545 with previous studies (Ploner et al., 2017) and most likely correspond to pain-related 546 evoked potentials (Lorenz and Garcia-Larrea, 2003; Tiemann et al., 2015), such as the P2 547 with a similar topography. In addition we observed a significant suppression of alpha-to- 548 beta activity which, given the above mentioned delays of our painful stimuli, is in line 549 with the reported beta suppression in previous EEG studies on pain (Mouraux et al., 550 2003; Ploner et al., 2006; May et al., 2012; Hu et al., 2013). Reduced Pain Model 475 The top three rows show (a) the main 517 effect of stimulus intensity, (b) the main effect of negative absolute prediction errors and (c) the 518 main effect of expectation. Left column: Time-frequency representation of the statistical F-values 519 averaged over all channels. Significant clusters are highlighted by a solid line. The non- 520 significant expectation cluster is highlighted by a thin dotted line. Right column: Power values 521 for all conditions included in the reduced model with a valid modality cue (expect heat receive 522 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint heat) averaged over all significant time-frequency-electrode samples of the respective cluster. d) 523 Topographies of the averaged power over time and frequency of the whole cluster extent (i.e. 524 over the whole time and frequency range) at each channel for stimulus intensity (left), negative 525 absolute prediction errors (center) and expectation (right), brighter colors indicate higher F- 526 values. 527 heat) averaged over all significant time-frequency-electrode samples of the respective cluster. d) 523 Topographies of the averaged power over time and frequency of the whole cluster extent (i.e. 524 over the whole time and frequency range) at each channel for stimulus intensity (left), negative 525 absolute prediction errors (center) and expectation (right), brighter colors indicate higher F- 526 values. 527 heat) averaged over all significant time-frequency-electrode samples of the respective cluster. d) 523 Topographies of the averaged power over time and frequency of the whole cluster extent (i.e. 524 over the whole time and frequency range) at each channel for stimulus intensity (left), negative 525 absolute prediction errors (center) and expectation (right), brighter colors indicate higher F- 526 values. 527 Discussion 528 Using a cued heat paradigm with three different stimulus intensities, our data showed a 529 clear discriminability of different levels of aversiveness based on behavioral ratings and 530 EEG time-frequency patterns. Specifically, we observed several clusters of activity to be 531 associated with the intensity of thermal stimulation in the theta, beta and gamma band. 532 Furthermore, behavioral data clearly indicated a positive influence of cued intensity on 533 pain perception. In addition, our results provide evidence for temporally and spectrally 534 separable clusters of oscillatory activity associated with expectation and a negative 535 modulation of gamma activity by prediction errors for thermoception and pain. 536 Specifically, one early low frequency (1-30Hz) cluster was related to expectation in 537 thermoception i.e. cued intensity. In contrast, a later occurring cluster at higher 538 frequencies (31-100Hz) was related to negative prediction errors in thermoception and 539 pain. 540 Using a cued heat paradigm with three different stimulus intensities, our data showed a 529 clear discriminability of different levels of aversiveness based on behavioral ratings and 530 EEG time-frequency patterns. Specifically, we observed several clusters of activity to be 531 associated with the intensity of thermal stimulation in the theta, beta and gamma band. 532 Furthermore, behavioral data clearly indicated a positive influence of cued intensity on 533 pain perception. In addition, our results provide evidence for temporally and spectrally 534 separable clusters of oscillatory activity associated with expectation and a negative 535 modulation of gamma activity by prediction errors for thermoception and pain. 536 Specifically, one early low frequency (1-30Hz) cluster was related to expectation in 537 thermoception i.e. cued intensity. In contrast, a later occurring cluster at higher 538 frequencies (31-100Hz) was related to negative prediction errors in thermoception and 539 pain. 540 band activity were only evident when the lowest stimulus intensity was included which 556 was perceived as neutral. 557 band activity were only evident when the lowest stimulus intensity was included which 556 was perceived as neutral. 557 On a more conceptual level, the investigation of neurophysiological effects even in the 566 absence of a behavioral effect has been considered meaningful (Wilkinson and Halligan, 567 2004). In particular, the authors argue that because it is commonly unknown which 568 parts of a cognitive process (and in which way) produce a specific behavioral response 569 the relationship between neurophysiological data and behavioral responses should not 570 be overemphasized, and therefore it can be misleading to declare behavioral effects a 571 reference or “gold standard”. Studies aiming to understand neurophysiological 572 mechanisms of cognition, usually relate a neurophysiological readout to a known 573 perturbation (i.e. experimental design), which is meaningful in its own right. 574 On a more conceptual level, the investigation of neurophysiological effects even in the 566 absence of a behavioral effect has been considered meaningful (Wilkinson and Halligan, 567 2004). In particular, the authors argue that because it is commonly unknown which 568 parts of a cognitive process (and in which way) produce a specific behavioral response 569 the relationship between neurophysiological data and behavioral responses should not 570 be overemphasized, and therefore it can be misleading to declare behavioral effects a 571 reference or “gold standard”. Studies aiming to understand neurophysiological 572 mechanisms of cognition, usually relate a neurophysiological readout to a known 573 perturbation (i.e. experimental design), which is meaningful in its own right. 574 Stimulus intensity and oscillatory activity 541 Finally, power in the gamma 551 band was also correlated with heat intensity, which is in line with previous studies 552 (Gross et al., 2007; Hauck et al., 2007; Zhang et al., 2012; Rossiter et al., 2013; Tiemann 553 et al., 2015). Interestingly, only the alpha-to-beta band desynchronization differentiated 554 between medium and high pain conditions, whereas differences in the theta and gamma 555 23 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint band activity were only evident when the lowest stimulus intensity was included which 556 was perceived as neutral. 557 We observed a behavioral effect of prediction errors on perceived stimulus intensity in 558 the reduced pain model, but this effect was only a trend in the full model. The latter 559 finding replicates a previous study (Fazeli and Büchel, 2018) indicating a robust effect. 560 Interestingly, the effect of prediction errors on perception increased, and became 561 significant, when we constrained our analysis to the clearly painful stimuli (reduced 562 pain model). This suggests that a prediction error seems to more strongly affect pain 563 perception whereas the effect is weaker in the context of thermoception. However, this 564 speculation should be corroborated in a future study. 565 Hypotheses based on microcircuits 575 Theoretical accounts (Arnal and Giraud, 2012; Bastos et al., 2012) have suggested that 576 predictive coding mechanisms could be related to the functional architecture of 577 neuronal microcircuits. As feedforward connections are predominately originating from 578 superficial layers and feedback connections from deep layers, it has been suggested that 579 prediction errors should be expressed by higher frequencies than the predictions that 580 accumulate them. 581 In the auditory modality, these ideas are supported by empirical data (Todorovic et al., 582 2011) showing that prediction errors in the context of repetition suppression were 583 associated with higher gamma band activity. Likewise, in the visual domain, an MEG 584 study has shown that temporo-parietal beta power was correlated with the 585 In the auditory modality, these ideas are supported by empirical data (Todorovic et al., 582 2011) showing that prediction errors in the context of repetition suppression were 583 associated with higher gamma band activity. Likewise, in the visual domain, an MEG 584 study has shown that temporo-parietal beta power was correlated with the 585 24 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint predictability of an action kinematics-outcome sequence, while gamma power was 586 correlated with the prediction error (van Pelt et al., 2016). 587 predictability of an action kinematics-outcome sequence, while gamma power was 586 correlated with the prediction error (van Pelt et al., 2016). 587 Frequency Patterns in Predictive Coding of Pain 588 Frequency Patterns in Predictive Coding of Pain 588 CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint 2016). Our findings are in line with these results indicating an important role of low 617 frequency activity in mediating expectation effects in a pain network underlying a 618 generative model for pain perception. 619 2016). Our findings are in line with these results indicating an important role of low 617 frequency activity in mediating expectation effects in a pain network underlying a 618 generative model for pain perception. 619 In contrast to prediction error effects in the visual (Bauer et al., 2014; van Pelt et al., 620 2016) and auditory (Edwards et al., 2005; Parras et al., 2017) domains, we observed a 621 negative modulation of gamma activity by absolute prediction errors. However it should 622 be noted that opposite effects have been observed in other cognitive domains. For 623 instance, increased gamma power has been associated with successful matching (i.e. the 624 absence of a prediction error) between external input and internal representation 625 (Herrmann et al., 2004a; Osipova et al., 2006; Wang et al., 2018). In particular, gamma- 626 band responses have been explained in terms of the match between bottom-up and top- 627 down information (Herrmann et al., 2004b). One example is the observation of 628 increased gamma activity with a higher so called cloze probability in sentence-level 629 language comprehension (Hald et al., 2006; Obleser and Kotz, 2011; Wang et al., 2012, 630 2018; Molinaro et al., 2013). It has been shown that a critical word that is semantically 631 predictable by the preceding sentence (so-called high cloze probability) induces a larger 632 gamma response than words which are semantically incongruent (i.e. unpredicted; low 633 cloze probability) (Wang et al., 2018). 634 In the present study, the lowest stimulus intensity was often not perceived as painful but 636 as hot. Frequency Patterns in Predictive Coding of Pain 588 Only a few studies have investigated the spectral and temporal properties of 589 expectations and prediction errors in the context of pain (summarized by Ploner et al., 590 2017). A recent study in rodents has suggested an information flow between S1 gamma 591 and ACC beta activity during spontaneous pain (Xiao et al., 2019). Based on these data, 592 the authors have proposed a predictive coding model including a bottom-up (gamma) 593 and top-down (beta) component (Song et al., 2019). Finally, in humans a recent EEG 594 study showed that the sensorimotor cortex is more strongly connected to the medial 595 prefrontal cortex at alpha frequencies during tonic pain, suggesting alpha band activity 596 in tonic pain to be associated with bottom-up instead of top-down signaling (Nickel et 597 al., 2020). Nevertheless, the focus of these studies was on generic interactions (i.e. top 598 down versus bottom up) processes without directly inducing prediction errors as in a 599 cued pain paradigm employed in our study. 600 In the flexible routing model proposed by Ploner et al. (2017), pain is seen as driven by 601 contextual processes, such as expectations, which is associated with alpha/beta 602 oscillations and alpha/beta synchrony across brain areas. Previous studies have started 603 to examine the spectral properties of mechanisms related to generative models of pain 604 perception. In particular, a previous MEG study reported that alpha suppression in the 605 anterior insula is related mainly to pain expectation in a paradigm in which painful 606 stimuli were interleaved with non-painful stimuli (Franciotti et al., 2009). This was 607 interpreted as a preparatory mechanism for an upcoming painful stimulus. In a related 608 study, alpha desynchronization in the context of predictable painful stimuli, has been 609 discussed as a possible neural correlate of attentional preparatory processes (Babiloni 610 et al., 2003). 611 Expectation is also a crucial ingredient of placebo analgesia and nocebo hyperalgesia. A 612 previous study reported that resting state alpha band activity was also linked to the 613 expectation of pain modulation (analgesia) in a placebo paradigm (Huneke et al., 2013). 614 With respect to negative expectations, it has been shown that pain modulation due to 615 nocebo expectation is associated with enhanced alpha activity (Albu and Meagher, 616 25 . Frequency Patterns in Predictive Coding of Pain 588 In general, stimulus properties were chosen to be comparable to a previous fMRI 637 study which showed fMRI signals related to prediction errors (Fazeli and Büchel, 2018). 638 However, even though the lowest stimulus intensity (42°C) was above the threshold of 639 nociceptors (Treede et al., 1998), the subjective experience of the lowest pain stimuli 640 was often rated as neutral. Therefore, we performed an additional analysis (reduced 641 pain model) only comprising clearly painful stimuli (46°C and 48°C) to more specifically 642 address expectations and predictions errors in pain. The analyses of the behavioral data 643 revealed similar results. Both models showed a highly significant effect of stimulus 644 intensity and expectation on perceived stimulus intensity. In addition, the reduced pain 645 model showed a significant prediction error effect, which was formally not observed in 646 the full model. However, it is important to note that this difference should not be over 647 interpreted as the p-value for the prediction error effect of the full model was at a trend 648 26 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint level (p = 0.1). Importantly, the negative representation of prediction errors in the 649 gamma band was evident in both, the reduced and the full model. 650 Limitations 651 It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint Summary 678 Our data show that key variables required for pain perception and thermoception in the 679 context of a generative model are correlated with distinct oscillatory profiles in the 680 brain. Furthermore, each oscillatory frequency band was correlated with a distinct 681 variable such as expectation and prediction errors. These mechanistic insights could be 682 very helpful in patients with acute and more importantly in patients with chronic pain, 683 where expectations have been shown to play a critical role in pain persistence. 684 Our data show that key variables required for pain perception and thermoception in the 679 context of a generative model are correlated with distinct oscillatory profiles in the 680 brain. Furthermore, each oscillatory frequency band was correlated with a distinct 681 variable such as expectation and prediction errors. These mechanistic insights could be 682 very helpful in patients with acute and more importantly in patients with chronic pain, 683 where expectations have been shown to play a critical role in pain persistence. 684 Our data show that key variables required for pain perception and thermoception in the 679 context of a generative model are correlated with distinct oscillatory profiles in the 680 brain. Furthermore, each oscillatory frequency band was correlated with a distinct 681 variable such as expectation and prediction errors. These mechanistic insights could be 682 very helpful in patients with acute and more importantly in patients with chronic pain, 683 where expectations have been shown to play a critical role in pain persistence. 684 Limitations 651 To unravel, the temporal aspects of expectations and prediction errors, this study has 652 been designed in close analogy to a previous fMRI study and we decided to use the same 653 experimental paradigm (Fazeli and Büchel, 2018). We therefore decided to also keep the 654 sample characteristics similar and restricted the sample to male participants, which 655 means that we cannot generalize our results to the population. However, our study 656 agrees with findings of a previous study using a similar design (Geuter et al., 2017) 657 which tested male and female participants. Future studies should investigate samples 658 including female participants. This would also allow to investigate sex effects with 659 respect to expectation and prediction error effects in pain. 660 To minimize motor responses and speed-up the rating procedure, we used a 4-button 661 device to directly assess stimulus intensity (in contrast to using two buttons to move a 662 slider on a VAS), thus being limited to a coarse rating scale of 4 levels, where 1 was 663 labeled as “neutral” and 4 was labeled as “very strong”. This allows to accommodate 664 more trials, but is not ideal to assess fine-grained differences, specifically to differentiate 665 between non-painful and painful stimulation, as level 1 would represent 0-25 on a 0-100 666 VAS. Future research could use conventional 0-100 VAS to assess stimulus intensity on a 667 finer scale. 668 For reasons of comparability to a previous fMRI study, we employed three different 669 temperatures for all volunteers. Alternatively, we could have defined three levels of pain 670 based on individual calibration of heat stimuli (Taesler and Rose, 2017; Grahl et al., 671 2018; Horing et al., 2019; Zhang et al., 2020; Feldhaus et al., 2021). Such a procedure 672 could have avoided trials where no pain was subjectively perceived. On the other hand, 673 such an approach also carries the risk that subjective ratings during the calibration 674 process do not truly reflect pain and can lead to errors (especially if ratings are too low) 675 which then affect the entire experiment. However, to address this shortcomming, we 676 performed an additional analysis, which only included painful stimulus intensities. 677 27 27 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. Acknowledgements 685 We would like to thank Markus Ploner for comments on an earlier version of this 686 manuscript. We would also like to thank Matthias Kerkemeyer for his help during data 687 collection. C.B is supported by the DFG, SFB 289, M.R. is supported by the DFG SFB TR 688 169 project B3. 689 690 28 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint References 691 CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint Edwards E, Soltani M, Deouell LY, Berger MS, Knight RT (2005) High Gamma Activity in 725 Response to Deviant Auditory Stimuli Recorded Directly From Human Cortex. 726 Journal of Neurophysiology 94:4269–4280. 727 Egner T, Monti JM, Summerfield C (2010) Expectation and Surprise Determine Neural 728 Population Responses in the Ventral Visual Stream. J Neurosci 30:16601–16608. 729 Ernst MO, Banks MS (2002) Humans integrate visual and haptic information in a 730 statistically optimal fashion. Nature 415:429–433. 731 Fazeli S, Büchel C (2018) Pain-Related Expectation and Prediction Error Signals in the 732 Anterior Insula Are Not Related to Aversiveness. J Neurosci 38:6461–6474. 733 Feldhaus MH, Horing B, Sprenger C, Büchel C (2021) Association of nocebo hyperalgesia 734 and basic somatosensory characteristics in a large cohort. Scientific Reports 735 11:762. 736 Franciotti R, Ciancetta L, Della Penna S, Belardinelli P, Pizzella V, Romani GL (2009) 737 Modulation of alpha oscillations in insular cortex reflects the threat of painful 738 stimuli. Neuroimage 46:1082–1090. 739 Friston K (2010) The free-energy principle: a unified brain theory? Nat Rev Neurosci 740 11:127–138. 741 Geuter S, Boll S, Eippert F, Büchel C (2017) Functional dissociation of stimulus intensity 742 encoding and predictive coding of pain in the insula. Elife 6. 743 Grahl A, Onat S, Büchel C (2018) The periaqueductal gray and Bayesian integration in 744 placebo analgesia. Elife 7. 745 Grandchamp R, Delorme A (2011) Single-Trial Normalization for Event-Related Spectral 746 912 Decomposition Reduces Sensitivity to Noisy Trials. Front Psychol 2. 747 Gross J, Schnitzler A, Timmermann L, Ploner M (2007) Gamma Oscillations in Human 748 Primary Somatosensory Cortex Reflect Pain Perception Fries P, ed. PLoS Biol 749 5:e133. 750 Gruber T, Müller MM, Keil A, Elbert T (1999) Selective visual-spatial attention alters 751 induced gamma band responses in the human EEG. Clin Neurophysiol 110:2074– 752 2085. 753 Hald LA, Bastiaansen MCM, Hagoort P (2006) EEG theta and gamma responses to 754 semantic violations in online sentence processing. Brain and Language 96:90– 755 105. 756 Hauck M, Lorenz J, Domnick C, Gerloff C, Engel AK (2015) Top-Down and Bottom-Up 757 Modulation of Pain-Induced Oscillations. References 691 Albu S, Meagher MW (2016) Expectation of nocebo hyperalgesia affects EEG alpha- 692 activity. Int J Psychophysiol 109:147–152. 693 Anchisi D, Zanon M (2015) A Bayesian perspective on sensory and cognitive integration 694 in pain perception and placebo analgesia. PLoS ONE 10:e0117270. 695 Arnal LH, Giraud A-L (2012) Cortical oscillations and sensory predictions. Trends Cogn 696 Sci (Regul Ed) 16:390–398. 697 Atlas LY, Bolger N, Lindquist MA, Wager TD (2010) Brain Mediators of Predictive Cue 698 Effects on Perceived Pain. Journal of Neuroscience 30:12964–12977. 699 Atlas LY, Wager TD (2012) How expectations shape pain. Neurosci Lett 520:140–148. 700 Babiloni C, Brancucci A, Babiloni F, Capotosto P, Carducci F, Cincotti F, Arendt-Nielsen L, 701 Chen ACN, Rossini PM (2003) Anticipatory cortical responses during the 702 expectancy of a predictable painful stimulation. A high-resolution 703 electroencephalography study. Eur J Neurosci 18:1692–1700. 704 Bastos AM, Usrey WM, Adams RA, Mangun GR, Fries P, Friston KJ (2012) Canonical 705 microcircuits for predictive coding. Neuron 76:695–711. 706 Bauer M, Oostenveld R, Peeters M, Fries P (2006) Tactile spatial attention enhances 707 gamma-band activity in somatosensory cortex and reduces low-frequency 708 activity in parieto-occipital areas. J Neurosci 26:490–501. 709 Bauer M, Stenner M-P, Friston KJ, Dolan RJ (2014) Attentional Modulation of Alpha/Beta 710 and Gamma Oscillations Reflect Functionally Distinct Processes. Journal of 711 Neuroscience 34:16117–16125. 712 Bingel U, Lorenz J, Schoell E, Weiller C, Büchel C (2006) Mechanisms of placebo 713 analgesia: rACC recruitment of a subcortical antinociceptive network. Pain 714 120:8–15. 715 Büchel C, Geuter S, Sprenger C, Eippert F (2014) Placebo Analgesia: A Predictive Coding 716 Perspective. Neuron 81:1223–1239. 717 Clark A (2013) Whatever next? Predictive brains, situated agents, and the future of 718 cognitive science. Behav Brain Sci 36:181–204. 719 Colloca L, Benedetti F (2005) Placebos and painkillers: is mind as real as matter? Nat 720 Rev Neurosci 6:545–552. 721 Debener S, Herrmann CS, Kranczioch C, Gembris D, Engel AK (2003) Top-down 722 attentional processing enhances auditory evoked gamma band activity. 723 Neuroreport 14:683–686. 724 29 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . References 691 Front Hum Neurosci 9 758 Hauck M, Lorenz J, Engel AK (2007) Attention to Painful Stimulation Enhances γ-Band 759 Activity and Synchronization in Human Sensorimotor Cortex. The Journal of 760 Neuroscience 27:9270. 761 30 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint Herrmann C, Lenz D, Junge S, Busch N, Maess B (2004a) Memory-matches evoke human 762 gamma-responses. BMC neuroscience 5:13. 763 Herrmann CS, Munk MHJ, Engel AK (2004b) Cognitive functions of gamma-band activity: 764 memory match and utilization. Trends in Cognitive Sciences 8:347–355. 765 Horing B, Sprenger C, Büchel C (2019) The parietal operculum preferentially encodes 766 heat pain and not salience. PLOS Biology 17:e3000205. 767 Hu L, Peng W, Valentini E, Zhang Z, Hu Y (2013) Functional features of nociceptive- 768 induced suppression of alpha band electroencephalographic oscillations. J Pain 769 14:89–99. 770 Huang Y, Rao RPN (2011) Predictive coding. Wiley Interdisciplinary Reviews-Cognitive 771 Science 2:580–593. 772 Huneke NTM, Brown CA, Burford E, Watson A, Trujillo-Barreto NJ, El-Deredy W, Jones 773 AKP (2013) Experimental placebo analgesia changes resting-state alpha 774 oscillations. PLoS ONE 8:e78278. 775 Jung TP, Makeig S, Humphries C, Lee TW, McKeown MJ, Iragui V, Sejnowski TJ (2000) 776 Removing electroencephalographic artifacts by blind source separation. 777 Psychophysiology 37:163–178. 778 Klem GH, Lüders HO, Jasper HH, Elger C (1999) The ten-twenty electrode system of the 779 International Federation. The International Federation of Clinical 780 Neurophysiology. Electroencephalogr Clin Neurophysiol Suppl 52:3–6. 781 Knill DC, Pouget A (2004) The Bayesian brain: the role of uncertainty in neural coding 782 and computation. Trends Neurosci 27:712–719. 783 Koyama T, McHaffie JG, Laurienti PJ, Coghill RC (2005) The subjective experience of 784 pain: where expectations become reality. Proc Natl Acad Sci USA 102:12950– 785 12955. 786 Lang, P.J., Bradley, M.M., & Cuthbert, B.N. (2008). International affective picture system 787 (IAPS): Affective ratings of pictures and instruction manual. References 691 Technical Report A- 788 8. University of Florida, Gainesville, FL. 789 Liberati G, Klöcker A, Algoet M, Mulders D, Maia Safronova M, Ferrao Santos S, Ribeiro 790 Vaz J-G, Raftopoulos C, Mouraux A (2018) Gamma-Band Oscillations Preferential 791 for Nociception can be Recorded in the Human Insula. Cereb Cortex 28:3650– 792 3664. 793 Lorenz J, Garcia-Larrea L (2003) Contribution of attentional and cognitive factors to 794 laser evoked brain potentials. Neurophysiol Clin 33:293–301. 795 Makeig S, Bell A, Jung T-P, Sejnowski T (1996) Independent Component Analysis of 796 Electroencephalographic Data. 8. 797 31 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint May ES, Butz M, Kahlbrock N, Hoogenboom N, Brenner M, Schnitzler A (2012) Pre- and 798 post-stimulus alpha activity shows differential modulation with spatial attention 799 during the processing of pain. Neuroimage 62:1965–1974. 800 Molinaro N, Barraza P, Carreiras M (2013) Long-range neural synchronization supports 801 fast and efficient reading: EEG correlates of processing expected words in 802 sentences. NeuroImage 72:120–132. 803 Mouraux A, Guérit JM, Plaghki L (2003) Non-phase locked electroencephalogram (EEG) 804 responses to CO2 laser skin stimulations may reflect central interactions between 805 A partial partial differential- and C-fibre afferent volleys. Clin Neurophysiol 806 114:710–722. 807 Nickel MM, Dinh ST, May ES, Tiemann L, Hohn VD, Gross J, Ploner M (2020) Neural 808 oscillations and connectivity characterizing the state of tonic experimental pain 809 in humans. Human Brain Mapping 41:17–29. 810 Obleser J, Kotz SA (2011) Multiple brain signatures of integration in the comprehension 811 of degraded speech. NeuroImage 55:713–723. 812 Ongaro G, Kaptchuk TJ (2019) Symptom perception, placebo effects, and the Bayesian 813 brain. Pain 160:1–4. 814 Oostenveld R, Fries P, Maris E, Schoffelen J-M (2011) FieldTrip: Open Source Software 815 for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data. 816 Computational intelligence and neuroscience 2011:156869. References 691 817 Osipova D, Takashima A, Oostenveld R, Fernández G, Maris E, Jensen O (2006) Theta and 818 Gamma Oscillations Predict Encoding and Retrieval of Declarative Memory. J 819 Neurosci 26:7523–7531. 820 Parras GG, Nieto-Diego J, Carbajal GV, Valdés-Baizabal C, Escera C, Malmierca MS (2017) 821 Neurons along the auditory pathway exhibit a hierarchical organization of 822 prediction error. Nature Communications 8:2148. 823 Petrovic P, Kalso E, Petersson KM, Ingvar M (2002) Placebo and opioid analgesia-- 824 imaging a shared neuronal network. Science 295:1737–1740. 825 Ploghaus A, Tracey I, Gati JS, Clare S, Menon RS, Matthews PM, Rawlins JN (1999) 826 Dissociating pain from its anticipation in the human brain. Science 284:1979– 827 1981. 828 Ploner M, Gross J, Timmermann L, Pollok B, Schnitzler A (2006) Pain suppresses 829 spontaneous brain rhythms. Cereb Cortex 16:537–540. 830 Ploner M, Sorg C, Gross J (2017) Brain Rhythms of Pain. Trends Cogn Sci (Regul Ed) 831 21:100–110. 832 Rossiter HE, Worthen SF, Witton C, Hall SD, Furlong PL (2013) Gamma oscillatory 833 amplitude encodes stimulus intensity in primary somatosensory cortex. Front 834 Hum Neurosci 7 Available at: 835 32 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint https://www.frontiersin.org/articles/10.3389/fnhum.2013.00362/full 836 [Accessed December 2, 2020]. 837 Schulz E, May ES, Postorino M, Tiemann L, Nickel MM, Witkovsky V, Schmidt P, Gross J, 838 Ploner M (2015) Prefrontal Gamma Oscillations Encode Tonic Pain in Humans. 839 Cereb Cortex 25:4407–4414. 840 Song Y, Yao M, Kemprecos H, Byrne Á, Xiao Z, Zhang Q, Singh A, Wang J, Chen ZS (2019) 841 Predictive Coding Models for Pain Perception. Neuroscience. Available at: 842 http://biorxiv.org/lookup/doi/10.1101/843284 [Accessed March 31, 2020]. 843 Summerfield C, de Lange FP (2014) Expectation in perceptual decision making: neural 844 and computational mechanisms. Nature Reviews Neuroscience 15:745–756. 845 Taesler P, Rose M (2016) Prestimulus Theta Oscillations and Connectivity Modulate Pain 846 Perception. J Neurosci 36:5026–5033. References 691 875 Wager TD, Rilling JK, Smith EE, Sokolik A, Casey KL, Davidson RJ, Kosslyn SM, Rose RM, 876 Cohen JD (2004) Placebo-induced changes in FMRI in the anticipation and 877 experience of pain. Science 303:1162–1167. 878 Wang L, Hagoort P, Jensen O (2018) Gamma Oscillatory Activity Related to Language 879 Prediction. Journal of Cognitive Neuroscience 30:1075–1085. 880 Wang L, Zhu Z, Bastiaansen M (2012) Integration or Predictability? A Further 881 Specification of the Functional Role of Gamma Oscillations in Language 882 Comprehension. Front Psychol 3 Available at: 883 https://www.frontiersin.org/articles/10.3389/fpsyg.2012.00187/full [Accessed 884 February 2, 2021]. 885 Wiech K (2016) Deconstructing the sensation of pain: The influence of cognitive 886 processes on pain perception. Science 354:584–587. 887 Wiech K, Ploner M, Tracey I (2008) Neurocognitive aspects of pain perception. Trends 888 Cogn Sci (Regul Ed) 12:306–313. 889 Wilkinson D, Halligan P (2004) The relevance of behavioural measures for functional- 890 imaging studies of cognition. Nature Reviews Neuroscience 5:67–73. 891 Xiao Z, Martinez E, Kulkarni PM, Zhang Q, Hou Q, Rosenberg D, Talay R, Shalot L, Zhou H, 892 Wang J, Chen ZS (2019) Cortical Pain Processing in the Rat Anterior Cingulate 893 Cortex and Primary Somatosensory Cortex. Front Cell Neurosci 13:165. 894 Zhang S, Yoshida W, Mano H, Yanagisawa T, Mancini F, Shibata K, Kawato M, Seymour B 895 (2020) Pain Control by Co-adaptive Learning in a Brain-Machine Interface. 896 Current Biology 30:3935-3944.e7. 897 Zhang ZG, Hu L, Hung YS, Mouraux A, Iannetti GD (2012) Gamma-band oscillations in the 898 primary somatosensory cortex--a direct and obligatory correlate of subjective 899 pain intensity. J Neurosci 32:7429–7438. 900 van Pelt S, Heil L, Kwisthout J, Ondobaka S, van Rooij I, Bekkering H (2016) Beta- and 873 gamma-band activity reflect predictive coding in the processing of causal events. 874 Soc Cogn Affect Neurosci 11:973–980. 875 Wager TD, Rilling JK, Smith EE, Sokolik A, Casey KL, Davidson RJ, Kosslyn SM, Rose RM, 876 Cohen JD (2004) Placebo-induced changes in FMRI in the anticipation and 877 experience of pain. Science 303:1162–1167. 878 Wang L, Hagoort P, Jensen O (2018) Gamma Oscillatory Activity Related to Language 879 Prediction. Journal of Cognitive Neuroscience 30:1075–1085. 880 Wang L, Zhu Z, Bastiaansen M (2012) Integration or Predictability? A Further 881 Specification of the Functional Role of Gamma Oscillations in Language 882 Comprehension. Front Psychol 3 Available at: 883 https://www.frontiersin.org/articles/10.3389/fpsyg.2012.00187/full [Accessed 884 February 2, 2021]. References 691 847 Taesler P, Rose M (2017) Psychophysically-anchored, Robust Thresholding in Studying 848 Pain-related Lateralization of Oscillatory Prestimulus Activity. Journal of 849 Visualized Experiments 2017. 850 Tallon-Baudry C, Kreiter A, Bertrand O (1999) Sustained and transient oscillatory 851 responses in the gamma and beta bands in a visual short-term memory task in 852 humans. Vis Neurosci 16:449–459. 853 Tiemann L, May ES, Postorino M, Schulz E, Nickel MM, Bingel U, Ploner M (2015) 854 Differential neurophysiological correlates of bottom-up and top-down 855 modulations of pain. Pain 156:289–296. 856 Tiemann L, Schulz E, Gross J, Ploner M (2010) Gamma oscillations as a neuronal 857 correlate of the attentional effects of pain. Pain 150:302–308. 858 Tiitinen H, Sinkkonen J, Reinikainen K, Alho K, Lavikainen J, Näätänen R (1993) Selective 859 attention enhances the auditory 40-Hz transient response in humans. Nature 860 364:59–60. 861 Todorovic A, van Ede F, Maris E, de lange FP (2011) Prior Expectation Mediates Neural 862 Adaptation to Repeated Sounds in the Auditory Cortex: An MEG Study. Journal of 863 Neuroscience 31:9118–9123. 864 Tracey I, Mantyh PW (2007) The cerebral signature for pain perception and its 865 modulation. Neuron 55:377–391. 866 Treede RD, Meyer RA, Campbell JN (1998) Myelinated mechanically insensitive afferents 867 from monkey hairy skin: heat-response properties. J Neurophysiol 80:1082– 868 1093. 869 Tu Y, Zhang Z, Tan A, Peng W, Hung YS, Moayedi M, Iannetti GD, Hu L (2016) Alpha and 870 gamma oscillation amplitudes synergistically predict the perception of 871 forthcoming nociceptive stimuli. Human Brain Mapping 37:501–514. 872 33 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint van Pelt S, Heil L, Kwisthout J, Ondobaka S, van Rooij I, Bekkering H (2016) Beta- and 873 gamma-band activity reflect predictive coding in the processing of causal events. 874 Soc Cogn Affect Neurosci 11:973–980. References 691 885 Wiech K (2016) Deconstructing the sensation of pain: The influence of cognitive 886 processes on pain perception. Science 354:584–587. 887 Wiech K, Ploner M, Tracey I (2008) Neurocognitive aspects of pain perception. Trends 888 Cogn Sci (Regul Ed) 12:306–313. 889 Wilkinson D, Halligan P (2004) The relevance of behavioural measures for functional- 890 imaging studies of cognition. Nature Reviews Neuroscience 5:67–73. 891 Xiao Z, Martinez E, Kulkarni PM, Zhang Q, Hou Q, Rosenberg D, Talay R, Shalot L, Zhou H, 892 Wang J, Chen ZS (2019) Cortical Pain Processing in the Rat Anterior Cingulate 893 Cortex and Primary Somatosensory Cortex. Front Cell Neurosci 13:165. 894 Zhang S, Yoshida W, Mano H, Yanagisawa T, Mancini F, Shibata K, Kawato M, Seymour B 895 (2020) Pain Control by Co-adaptive Learning in a Brain-Machine Interface. 896 Current Biology 30:3935-3944.e7. 897 Zhang ZG, Hu L, Hung YS, Mouraux A, Iannetti GD (2012) Gamma-band oscillations in the 898 primary somatosensory cortex--a direct and obligatory correlate of subjective 899 pain intensity. J Neurosci 32:7429–7438. 900 901 34 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint 902 Supplementary Materials 903 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint Supplementary Materials 903 Supplementary Materials 903 904 Figure 1-figure supplement 1. Histogram showing the distribution of the total number of 905 rejected components based on detected muscle artifacts. 906 904 Figure 1-figure supplement 1. Histogram showing the distribution of the total number of 905 rejected components based on detected muscle artifacts. 906 909 35 35 . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint 910 911 Figure 5-figure supplement 1. Difference for the main effect of stimulus intensity in the 912 gamma band (averaged over 60-100Hz, 1250 to 1600ms) in power values for all high heat vs. 913 low heat conditions with a valid modality cue (expect heat receive heat) for each subject, 914 respectively. 915 916 911 Figure 5-figure supplement 1. Difference for the main effect of stimulus intensity in the 912 gamma band (averaged over 60-100Hz, 1250 to 1600ms) in power values for all high heat vs. 913 low heat conditions with a valid modality cue (expect heat receive heat) for each subject, 914 respectively. 915 916 916 . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint 7 Figure 6-figure supplement 1. Power values for all conditions with a valid modality cue 8 (expect heat receive heat) averaged over all significant time-frequency-electrode samples period 9 for each subject (ID) of the EXP cluster. Supplementary Materials 903 Blue colors represent low heat conditions, green colors 0 represent medium heat conditions and red colors represent high heat conditions. Color 1 intensities depict expectation level. 2 Figure 6-figure supplement 1. Power values for all conditions with a valid modality cue 918 (expect heat receive heat) averaged over all significant time-frequency-electrode samples period 919 for each subject (ID) of the EXP cluster. Blue colors represent low heat conditions, green colors 920 represent medium heat conditions and red colors represent high heat conditions. Color 921 intensities depict expectation level. 922 . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint Figure 7-figure supplement 1. Power values for all conditions with a valid modality cue (expect heat receive heat) averaged over all significant time-frequency-electrode samples period for each subject (ID) of the negative absolute prediction error cluster. Blue colors represent low heat conditions, green colors represent medium heat conditions and red colors represent high heat conditions. Color intensities depict expectation level. Figure 7-figure supplement 1. Power values for all conditions with a valid modality cue 924 (expect heat receive heat) averaged over all significant time-frequency-electrode samples period 925 for each subject (ID) of the negative absolute prediction error cluster. Blue colors represent low 926 heat conditions, green colors represent medium heat conditions and red colors represent high 927 heat conditions. Color intensities depict expectation level. 928 929 . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. Supplementary Materials 903 It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint Figure 8-figure supplement 1. Power values for all medium and high intensity conditions with a valid modality cue (expect heat receive heat) averaged over all significant time-frequency- electrode samples period for each subject (ID) of the negative stimulus intensity cluster of the analysis of the reduced model. Green colors represent medium heat conditions and red colors represent high heat conditions. Color intensities depict expectation level. 0 930 Figure 8-figure supplement 1. Power values for all medium and high intensity conditions with 931 a valid modality cue (expect heat receive heat) averaged over all significant time-frequency- 932 electrode samples period for each subject (ID) of the negative stimulus intensity cluster of the 933 analysis of the reduced model. Green colors represent medium heat conditions and red colors 934 represent high heat conditions. Color intensities depict expectation level. 935 . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint 6 Figure 8-figure supplement 2. Power values for all medium and high intensity conditions with 7 a valid modality cue (expect heat receive heat) averaged over all significant time-frequency- 8 electrode samples period for each subject (ID) of the negative absolute prediction error cluster 9 of the analysis of the reduced model. Green colors represent medium heat conditions and red 0 colors represent high heat conditions. Color intensities depict expectation level. 1 Figure 8-figure supplement 2. Power values for all medium and high intensity conditions with 937 a valid modality cue (expect heat receive heat) averaged over all significant time-frequency- 938 electrode samples period for each subject (ID) of the negative absolute prediction error cluster 939 of the analysis of the reduced model. Green colors represent medium heat conditions and red 940 colors represent high heat conditions. Color intensities depict expectation level. Supplementary Materials 903 941 . CC-BY 4.0 International license available under a which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint . CC-BY 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted February 5, 2021. ; https://doi.org/10.1101/2020.09.10.291658 doi: bioRxiv preprint Figure 8-figure supplement 3. Power values for all medium and high intensity conditions with a valid modality cue (expect heat receive heat) averaged over all (non-significant) time- frequency-electrode samples of the respective cluster period for each subject (ID) of the non- significant expectation cluster of the analysis of the reduced model. Green colors represent medium heat conditions and red colors represent high heat conditions. Color intensities depict expectation level. 942 Figure 8-figure supplement 3. Power values for all medium and high intensity conditions with 943 Figure 8-figure supplement 3. Power values for all medium and high intensity conditions with 943 a valid modality cue (expect heat receive heat) averaged over all (non-significant) time- 944 frequency-electrode samples of the respective cluster period for each subject (ID) of the non- 945 significant expectation cluster of the analysis of the reduced model. Green colors represent 946 medium heat conditions and red colors represent high heat conditions. Color intensities depict 947 expectation level. 948 949
https://openalex.org/W4211194924	https://www.researchsquare.com/article/rs-1172380/latest.pdf	English	null	Identification of TARDBP Gly298Ser as a Founder Mutation for Amyotrophic Lateral Sclerosis in Southern China	Research Square (Research Square)	2,022	cc-by	8,435	Identification of TARDBP Gly298Ser as a Founder Mutation for Amyotrophic Lateral Sclerosis in Southern China Identification of TARDBP Gly298Ser as a Founder Mutation for Amyotrophic Lateral Sclerosis in Southern China Fanxi Xu Xuanwu Hospital of Capital Medical University Sen Huang First Affiliated Hospital of Sun Yat-sen University Xu-Ying Li Xuanwu Hospital of Capital Medical University Jianing Lin First Affiliated Hospital of Sun Yat-sen University Xiuli Feng National Human Genome Center in Beijing Shu Xie National Human Genome Center in Beijing Zhanjun Wang Xuanwu Hospital of Capital Medical University Xian Li Xuanwu Hospital of Capital Medical University Junge Zhu Xuanwu Hospital of Capital Medical University Hong Lai Xuanwu Hospital of Capital Medical University Yanming Xu West China Hospital of Sichuan University Xusheng Huang Chinese PLA General Hospital Xiaoli Yao First Affiliated Hospital of Sun Yat-sen University Chaodong Wang (  cdongwang01@126.com ) Xuanwu Hospital of Capital Medical University Identification of TARDBP Gly298Ser as a Founder Mutation for Amyotrophic Lateral Sclerosis in Southern China Fanxi Xu Xuanwu Hospital of Capital Medical University Identification of TARDBP Gly298Ser as a Founder Mutation for Amyotrophic Lateral Sclerosis in Southern China Fanxi Xu Introduction Amyotrophic lateral sclerosis (ALS) is a progressive, fatal neurodegenerative disease characterized by predominant impairment of upper and lower motor neurons, with an incidence of approximately 1-2 per 100,000 people. Patients usually suffer from progressive muscle weakness and atrophy and die of respiratory failure 3-5 years after the onset [1,2]. The etiology of ALS is not fully understood. Appropriately 90% of patients appear sporadically (sporadic ALS, SALS), while ~10% of patients have a family history positive for ALS (familial ALS, FALS) or frontotemporal dementia (FTD). With the advancement of sequencing technologies, rapid increasing number of genes and mutations have been identified in ALS, suggesting that genetic factors play important roles in its pathogenesis. To date, variants in 25 genes that fulfill adequate criteria for causation for ALS have been reported [3,4]. Mutations in these genes have been identified in approximately two-thirds of FALS and 10% of SALS cases [5]. Recent studies have identified SOD1, FUS, TARDBP and C9orf72 as the major ALS-related genes in both European and Asian populations [6]. Mutations in SOD1 are the most common cause for ALS in the world, and are detected in ~20% of FALS and 3% of sporadic ALS (SALS) [7]. C9orf72 mutation is a prevalent cause for ALS in Caucasians, but was rarely reported in Eastern Asians [8,9]. FUS mutations seem to be the most frequent genetic cause in early-onset sporadic ALS patients [10,11]. A characteristic feature of degenerating neurons in ALS patients is the presence of cytoplasmic insoluble and ubiquitinated inclusions containing abnormal aggregates of TAR DNA-binding protein (TDP-43), encoded by the TARDBP gene [12]. However, it is worthwhile to explore that since the first report of TDP-43 positive aggregates in ALS and FTD, they were also reported in other neurodegenerative diseases as a secondary feature [13]. TDP-43 is involved in RNA processing, splicing and transport. It consists of an N-terminal nuclear localization signal followed by two RNA recognition motifs and a C-terminal glycine rich domain. To date, more than 50 TARDBP mutations have been reported which explain approximately 4% of FALS cases and a smaller proportion of FTD cases [14]. Of course, this does not mean that all mutations are actually pathogenic mutations. But, all TARDBP pathogenic mutations exhibit an autosomal dominant pattern of inheritance [15]. The disease-associated mutations in TARDBP are distributed in the C-terminal glycine-rich domain, indicating critical involvement of this region in the pathogenesis of TDP-43 proteinopathy [16,17]. Introduction Indeed, emerging evidence supports that TDP-43 may act like a prion to initiate cascades of protein misfolding [18]. Some mutations are in high frequency in certain geographic regions and genetic founder effects have been examined for their associations with ALS. The distribution of ALS causing genes varies widely across populations and may differ widely between two seemingly similar countries. Founder mutations for ALS have been established in Italians (SOD1: D124G and G41S) [19-21], North American (SOD1: A4V) [22], Polish (SOD1: L144S) [23], Brazil (VAPB: P56S) [24] and Germany (SOD1: R115G) [25]. Hexanucleotide (G4C2) repeat expansion (HRE) in C9orf72 has a single founder and is the most common mutation in familial and sporadic ALS in Europe [26]. While several founder mutations have been reported, by far the most common is the SOD1 D90A (highly prevalent in Sweden and Finland but are rare in neighboring countries) [27]. In TARDBP, the most commonly reported missense mutations are A382T and M337V, and some of the most well-studied mutations are A315T, Q331K, M337V, D169G, G294A/V, Q343R, etc. Moreover, ALS cases carrying the A382T and G295S mutation of TARDBP and the C9orf72 repeat expansion shared distinct haplotypes across these loci in Sardinia [28]. In Chinese ALS cases, H47R, R521 and M337V are the most frequent mutations in SOD1, FUS and TARDBP, respectively [29]. However, there is still no haplotype analysis to support the founder effect of these mutations. Here, we identified a prevalent heterozygous Gly298Ser mutation (G298S, as follows) in TARDBP in both FALS and SALS in Guangdong and Guangxi, two neighboring Southern Chinese provinces. Haplotype analysis with the microsatellites surrounding the gene further confirmed a founder effect of this mutation in Southern, but not Northern Chinese. We also reviewed the global distribution of the mutations in TARDBP and revealed geographic distribution patterns and clinical relevance of some prevalent mutations. Abstract Background: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease characterized by predominant impairment of upper and lower motor neurons. Over 50 TARDBP mutations have been reported in both familial (FALS) and sporadic ALS (SALS). Some mutations in TARDBP, e.g. A382T and G294V, have genetic founder effects in certain geographic regions. However, such prevalence and founder effect have not been reported in Chinese. Methods: Whole-exome sequencing (WES) was performed in 16 Chinese FALS patients, followed by Sanger sequencing for the TARDBP p.Gly298Ser mutation (G298S) in 798 SALS patients and 1,325 controls. Haplotype analysis using microsatellites flanking TARDBP was conducted in the G298S-carrying patients and noncarriers. The geographic distribution and phenotypic correlation of the TARDBP mutations reported worldwide were reviewed. Results: WES detected the TARDBP G298S mutation in 8 FALS patients, and Sanger sequencing found additional 8 SALS cases, but no controls, carrying this mutation. All the 16 cases came from Southern China, and 7 of these patients shared the 117-286-257-145-246-270 allele for the D1S2736-D1S1151- D1S2667-D1S489-D1S434-D1S2697 markers, which was not found in the 92 non-carrier patients (0/92) (p <0.0001). The A382T and G298S mutations were prevalent in Caucasians and Eastern Asians, respectively. Additionally, carriers for the M337V mutation are dominated by bulbar onset with a long survival, whereas those for G298S are dominated by limb onset with a short survival. Conclusions: Some prevalent TARDBP mutations are distributed in a geographic pattern and related to clinical profiles. TARDBP G298S mutation is a founder mutation in the Southern Chinese ALS population. Research Article Keywords: Amyotrophic lateral sclerosis, TARDBP, G298S mutation, founder effect, China Posted Date: February 10th, 2022 DOI: https://doi.org/10.21203/rs.3.rs-1172380/v1 License:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Keywords: Amyotrophic lateral sclerosis, TARDBP, G298S mutation, founder effect, China DOI: https://doi.org/10.21203/rs.3.rs-1172380/v1 cense:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full Lic Page 1/12 Page 1/12 Page 1/12 Materials And Methods Subjects Demographics and clinical phenotype of the patients A total of 798 ALS patients were included in this study, including 16 FALS (from 15 pedigrees) and 782 SALS. All patients were of Chinese Han origin. Among the 798 cases diagnosed, 482 were males and 316 were females. The mean age of ALS onset was 52.77 ± 10.40 years. For initial symptoms, 615 patients (77.07%) first involved the spinal cord, while 183 (22.93%) presented with a bulbar-onset. The survival time ranged from 6-122 months. In the controls, 749 were males and 576 were females, and the mean age were 69.23 ± 14.62 years. Sanger sequencing for the TARDBP G298S mutation in the SALS patients and controls In order to confirm whether the TARDBP c.892G>A (p.Gly298Ser) mutation was also present in SALS patients and controls, validation of the mutation was performed in 782 sporadic cases (including 511 Southern and 271 Northern) and 1,325 controls. The specific methods can be found in the Supplementary Material. Haplotype analysis using the microsatellite markers To test whether the TARDBP G298S mutation carriers share the common ancestry, we performed haplotype analysis for the ALS patients with the mutation using the eight microsatellite markers in 1p36.22 spanning a region of about 7Mb (D1S450, D1S244, D1S2736, D1S1151, D1S2667, D1S434, D1S489, D1S2697) surrounding the TARDBP gene, according to Orrù et al [35].They were genotyped in the 16 ALS individuals carrying the G298S mutation and 92 cases not carrying the mutation, using the fluorescent-labeled primers designed and listed in Supplemental Table 1. The alleles were typed by electrophoresis on an ABI 3730 (Applied Biosystems, Foster City, CA, USA) and analyzed using GeneMarker Demo software V2.6.3 (SoftGenetics, State College, PA, USA). Haplotype frequencies and association statistics for the markers were constructed using PHASE version 2 software [36]. Ethnics approvals and patient consents Written informed consent was obtained from all participants, as approved by the Ethics Committee and the Expert Committee of Xuanwu Hospital of Capital Medical University (Clinical Research Audit: [2021] 034) and The China Human Genetic Resource Administration Office (China Ministry of Science and Technology Genetics Audit: [2021] CJ1167). Statistical analysis The results of all continuous data are presented in this report as mean ± standard deviation. The difference in h carriers and noncarriers was evaluated by χ2 and Fisher’s exact tests. The results of all continuous data are presented in this report as mean ± standard deviation. The difference in haplotype distribution between mutation carriers and noncarriers was evaluated by χ2 and Fisher’s exact tests. Subjects Page 2/12 Page 2/12 A total of 798 ALS cases were recruited between 2016 to 2021, including 462 from The First Affiliated Hospital of Sun Yet-Sen University, 232 from Xuanwu Hospital of Capital Medical University and the Chinese PLA General Hospital, and 104 from West China Hospital of Sichuan University. Among these, 16 had a family history. All the patients were diagnosed as definite, probable or possible ALS by at least 2 neuromuscular specialists, based on the revised EI Escorial criteria (2000) [30]. During the same period, 1,325 ethnicity-matched controls without any neurological diseases were enrolled. To avoid recruiting presymptomatic patients, we tended to recruit older people as healthy controls. Therefore, all healthy controls were older than 55 years. Screening of C9orf72 (GGGGCC)n repeat Two-step polymerase chain reaction (PCR) was performed to detect C9orf72 GGGGCC hexanucleotide repeat expansion (HRE) as previously described [31].Briefly, fluorescent fragment-length analysis was performed with genotyping primers. The samples with a homozygous peak pattern were analyzed by fluorescent repeat-primed PCR to identify HREs. The HRE was defined as repeat number >30 indicated by the typical “saw-tooth” pattern seen by repeat-primed PCR [32]. Whole-exome sequencing for FALS As it is easier to find causative mutations in FALS, whole-exome sequencing (WES) was performed in all the 16 FALS cases whose DNA samples were available. The WES was performed as the methods described previously (see details in Supplementary Methods) [33]. We only selected the pathogenic, likely pathogenic or uncertain significance variants according to the 2015 American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) criteria [34].For all the variants, mutations in 25 known ALS causative genes, including SOD1, ALS2, SETX, FUS, VAPB, ANG, TARDBP, FIG4, OPTN, VCP, UBQLN2, KIF5A, TIA1, ANXA11, SIGMAR1, CHMP2B, PFN1, AR, DCTN1, NEFH, PRPH, DAO, TFG, TAF15 and GRN, were analyzed. Further Sanger sequencing was used to confirmed the mutation. Sanger sequencing for the TARDBP G298S mutation in the SALS patients and controls Mutations identified in the FALS patients by whole-exome sequencing In total, we detected 134 variants of all types in the 25 selected genes. After sequential screening and filtering by population frequency (max frequency <0.01) and selection of variant types (missense, stop gained, frameshift, in-frame and splicing) and functional /conservation prediction (SIFT, CADD, Polyphen2, GERP++), 7 rare damaging variants were identified in the 16 FALS patients. Among all the rare damaging variants, 5 were pathogenic and 2 were likely pathogenic, according to the ACMG/AMP guidelines. Among the 16 patients, 10 carried mutations in TARDBP (G298S, N378D and N345K), 3 carried mutations in SOD1 (C112Y and G142A), 1 carried a FUS mutation (R521C) and 1 carried a VCP mutation (R155C), and no mutation was identified in one patient (No.12) (Table 1). The GGGGCC hexanucleotide repeats in C9orf72 were 2 to 11 copies and not pathogenic in the cases. Strikingly, among all the mutations, G298S Page 3/12 Page 3/12 was the most frequently (8/16, 50%) identified, and all of these 8 patients were from 7 pedigrees in Guangdong Province, a region in Southern China (Fig. 1). This is a high frequency mutation that has not been widely reported. was the most frequently (8/16, 50%) identified, and all of these 8 patients were from 7 pedigrees in Guangdong Province, a region in Southern China (Fig. 1). This is a high frequency mutation that has not been widely reported. Table 1 Clinical data and mutations identified in the 16 FALS probands Table 1 Clinical data and mutations identified in the 16 FALS probands Patienta Gender Birthplace (provinces) AAO (y) Onset site Duration (months) Genetic variant ACMG 1(F1) M Guangdong 50 Upper limb 48 (alive) TARDBP, c.892G>A, p. Gly298Ser P 2(F2) F Guangdong 50 Lower limb 15 TARDBP, c.892G>A, p. Gly298Ser P 3 F Guangdong 38 Lower limb NA SOD1, c.425G>C, p. Gly142Ala P 4(F3-1) F Guangdong 62 Upper limb 13 TARDBP, c.892G>A, p. Gly298Ser P 5 F Sichuan 43 Bulbar NA FUS, c.1561C>T, p. Arg521Cys P 6 F Guangxi 60 Bulbar NA TARDBP, c.1035C>A, p. Asn345Lys LP 7 M Guangdong 33 Lower limb NA VCP, c.463C>T, p. Arg155Cys P 8 F Hunan 50 Upper limb NA SOD1, c.335G>A, p. Cys112Tyr P 9(F6) F Guangdong 53 Upper limb 20 TARDBP, c.892G>A, p. Gly298Ser P 10 M Guangdong 40 Upper limb 12 (alive) TARDBP, c.1132A>G, p. Asn378Asp LP 11(F3-2) M Guangdong 54 Bulbar 20 TARDBP, c.892G>A, p. Carriers for TARDBP G298S mutation in the SALS patients To further identify the carriers for G298S mutation in TARDBP, we screened it by Sanger sequencing in 782 SALS patients (including 511 Southern and 271 Northern Chinese) and 1,325 ethnically matched healthy controls. In all the cases, 8 were found to carry the TARDBP G298S mutation. Ultimately, we found 16 patients carried the same G298S mutation, in which 13 were from Guangdong Province and 3 were from its neighboring province—Guangxi. However, the mutation was not detected in the 232 Northern or 104 Western Chinese ALS patients, neither in the 1,325controls. And no mutation was found in these 16 patients in other ALS-causing gene, such as SOD1, FUS, NEK1, VAPB, ALS2, OPTN, VCP, etc. Given the strong geographic preference of the mutation, we hypothesize that G298S might be a founder mutation in the Guangdong-Guangxi region. Mutations identified in the FALS patients by whole-exome sequencing Gly298Ser P 12 F Guangdong 66 Upper limb NA Not identified - 13(F4) F Guangdong 73 Upper limb 10 TARDBP, c.892G>A, p. Gly298Ser P 14(F5) F Guangdong 49 Bulbar 11 TARDBP, c.892G>A, p. Gly298Ser P 15(F7) M Guangdong 46 Bulbar 14 TARDBP, c.892G>A, p. Gly298Ser P 16 F Hunan 32 Upper limb NA SOD1, c.335G>A, p. Cys112Tyr P A stands for “not available.” LP, Likely Pathogenic. VUS, Uncertain significance. AAO, Age at onset. Patienta, Numbers with F in brackets represent the FALS ur G298S carriers. NA stands for “not available.” LP, Likely Pathogenic. VUS, Uncertain significance. AAO, Age at onset. Patienta, Numbers with F in brackets represent the FALS in our G298S carriers. NA stands for “not available.” LP, Likely Pathogenic. VUS, Uncertain significance. AAO, Age at onset. Patienta, Numbers with F in brackets represent the FALS in our G298S carriers. The TARDBP G298S mutation was associated with an ancestral haplotype To test whether all the 16 cases carrying the TARDBP G298S mutations were inherited from the same ancestor, we genotyped the cases and 92 sporadic ALS cases (Southern 40, Northern 52) not carrying the mutation, using eight microsatellite markers (D1S450, D1S244, D1S2736, D1S1151, D1S2667, D1S489, D1S434, D1S2697) flanking the TARDBP gene (Table 2). The 7 of 16 patients shared the 117-286-257-145-246-270 (bps) allele at markers D1S2736-D1S1151- D1S2667-D1S489-D1S434-D1S2697, which was not detected in the 92 non-carrier cases (0/92) (p <0.0001). The large haplotype spans a 5.8 Mb fragment that includes the TARDBP gene. For each marker, the number of alleles observed in the control group and the frequency of the shared alleles were shown in Table 2. In particular, the 286 and 257 bp alleles for the D1S1151 and D1S2667, which were very close (0.3Mb) to the TARDBP gene, were shared by 9 mutation-carriers but were not frequent in the non-carriers (10% and 18%). These data suggest that the G298S mutation may come from a common ancestral chromosome. Page 4/12 Table 2 Genotypes of microsatellites flanking TARDBP in the ALS patients carrying the G298S mutation Marker D1S450 D1S244 D1S2736 TARDBP D1S1151 D1S2667 D1S489 D1S434 D1S2697 (Mb) a (9.585) (10.574) (10.615) (11.083) (11.464) (11.487) (12.048) (12.332) (16.419) F1 250/252 286/290 118/124 278/290 262/268 136/144 238/246 270/270 F2 251/257 288/290 115/117 286/310 257/265 139/145 246/248 270/270 F3-1 248/250 298/300 117/119 260/286 257/259 139/145 244/246 270/274 F3-2 248/250 288/290 117/119 260/286 257/259 139/145 244/246 270/274 F4 250/254 286/290 117/125 282/290 258/266 136/144 244/246 268/270 F5 248/254 288/290 119/121 268/290 261/277 141/147 246/254 270/270 F6 248/256 290/294 119/125 275/293 257/269 139/145 246/256 270/270 F7 250/256 288/290 117/119 278/286 257/259 136/138 246/248 270/270 S1 254/256 284/290 117/123 268/286 257/259 143/145 246/248 268/270 S2 244/250 286/288 117/119 274/286 257/265 143/145 246/248 270/270 S3 250/256 288/290 117/119 286/292 257/265 143/145 242/246 270/274 S4 248/250 286/290 117/119 290/310 257/271 137/145 242/246 270/270 S5 248/250 282/290 115/117 252/286 257/259 139/145 246/248 270/270 S6 248/250 286/290 117/119 290/306 257/265 138/146 242/246 270/270 S7 244/250 286/290 118/122 286/302 257/269 139/143 246/256 270/270 S8 250/258 298/300 117/119 282/290 257/271 137/145 238/246 268/270 Shared allele b 250 290 117 286 257 145 246 270 Frequencyc(n=92) 0.28 0.58 0.61 0.10 0.18 0.33 0.77 0.95 equencies in the control group for each marker. Shared alleles are indicated in bold. frequencies in the control group for each marker. Shared alleles are indicated in bold. Geographical distribution and clinical features of TARDBP mutations reported worldwide To date, over 50 mutations of TARDBP have been described in both familial and sporadic ALS cases (Supplemental Table 2). A geographical map of the mutations highlights the qualitative distribution patterns (Fig. 2A). Most reported mutations were detected in countries of North America (US, Canada), Europe (France, Italy, Norway, Germany, Denmark) and Asia (India, Japan, Korea and China). Moreover, mutations were mostly detected in the exon 6 of TARDBP and dominantly reported in different geographic regions, such as I383V and S375G in the US, G348C and A382T in France, A382T and G295S in Italy, N352S, G357S and N378D in Japan, and M337V and G298S in China. According to the reported cases, most of the mutations, such as M337V, G348C, N352S and I383V, showed a distribution in multiple ethnicities, while some mutations were detected in specific geographic regions. For example, the A382T mutation was the most frequent mutation in Europe and America but not in Eastern Asians, while G298S was only detected in Eastern Asians. Among the 11 mutations reported in Chinese cases, M337V was most frequently reported in Fujian and Taiwan. In contrast, the G298S mutation was common in Guangdong and Guangxi (Fig. 2B, Table 3). In demographic and clinical characteristics, except for G287S, most of the mutations were detected in both familial and sporadic cases, and most of the cases displayed onset of limb weakness. However, carriers for M337V mainly developed the disease with a bulbar-onset (bulbar/limb: 37/22) and had the longest survival (75.9 months), while the G298S carriers displayed a limb onset and the shortest survival (19.3 months). At onset age, carriers for three mutations had a later onset (>60 years): G287S, G294V and G295S (Table 3). Geographical distribution and clinical features of TARDBP mutations reported worldwide Page 5/12 Page 5/12 Table 3 Clinical characteristics of the hotspot mutations in TARDBP Characteristics G298S M337V A382T G287S G294V G295S G348C I383V N352S Birth place a East Asia Admixed Europe and America Europe and America Italy Italy Admixed Admixed Admixed Family History b (F/S) 10/10 1/15 78/95 0/9 8/8 4/10 5/4 6/2 11/4 Gender (M/F) 13/9 28/30 122/60 2/0 9/6 2/1 9/6 1/2 1/8 Age at onset 51.3 (8.3) 51.7 52.7 67.5 61.1 60.0 49.9 58.3 57.1 (mean years, SD) (7.1) (12.9) (3.5) (11.2) (5.3) (11.3) (11.4) (12.7) Onset site L:15; B:6 L:22; B:37 L:141; B:36 L:1; B:1 L:7; B:8 L:3; B:0 L:13; B:2 L:1; L+B:2 L:7; B:0 Disease duration (mean months) 19.3 75.9 57.3 57.5 19.1 32.0 49.1 36.0 63.1 Cognitive impairment No Yes Yes No Yes Yes No Yes No Birthplace a: admixed: the mutation can be detected in both Asian and European patients Family History b: F, familial ALS; S, sporadic ALS Onset site: L, limb; B, bulbar Table 3 Clinical characteristics of the hotspot mutations in TARDBP Birthplace a: admixed: the mutation can be detected in both Asian and European patients Onset site: L, limb; B, bulbar Clinical characteristics of ALS patients with the TARDBP G298S mutation The 16 FALS and SALS patients carrying the G298S mutation had similar clinical features (Table 4). The onset age varied considerably, cases S3 and S4 showed early onset at 38 and 39 years old, while F4 had onset at 73 years old. Of all the patients, 11 showed limb-onset, while 5 showed bulbar-onset. Most of the patients displayed fasciculation and signs of dysfunction in both upper motor neuron (UMN) and lower motor neuron (LMN). No signs of dementia were reported in these patients. The severity of neurological functions varies: the scores for ALS functional rating scale-revised (ALSFRS-R) ranged 20-48. Electromyography (EMG) examination was performed in 12 patients, all showed fibrillations, fasciculations and positive sharp waves. Except F-1, all the patients had survived no longer than 24 months. In particular, the survival time of S4 and S7 was 7-8 months since onset. Most of the cases did not have histories of drinking, smoking or pesticide exposure. Five patients (F6, F7, S5, S6 and S7) carried another rare variant in the ALS-causing genes (ALS2, SPG11, FIG4, NEK1), but all these variants were classified as variant of unknown significance (VUS), according to the ACMG guidelines. Discussion In this study, we identified G298S as a frequent mutation that were merely detected in patients from the Southern Chinese provinces, and haplotype analysis revealed that inheritance of the G298S mutation was attributable to a founder effect. We also reviewed the TARDBP mutations reported worldwide and found that some prevalent mutations were apparently distributed in geographical prevalence and associated with specific clinical features. Increasing studies have reported the correlation of mutations in ALS genes with specific haplotypes. For TARDBP variants, haplotype analyses for the A382T [19,37], N352S [38] and G294V [39] mutations have been documented. However, these mutations had been mostly reported in Westerners but scarcely reported in Easterners. Before this report, the G298S mutation has only been described in Chinese and Japanese FALS families [40-42]. Our study adds the most cases carrying this mutation and demonstrates that the high prevalence of the G298S mutation in Southern Chinese patients is due to a founder effect. The analysis of microsatellite markers surrounding the TARDBP gene in cases carrying the mutation showed that they were inherited from a common ancestor with the D1S2736-D1S1151-D1S2667-D1S489-D1S434-D1S2697 haplotype. Clinically, no patient with the G298S mutation exhibited overt cognitive impairment in our study, although the TDP-43 protein inclusions being originally identified in FTD cases [43]. However, a limitation of our study is that we were unable to perform postmortem studies to investigate this. Interestingly, as reported here and in the Chinese and Japanese FALS cases, most of the patients carrying this mutation displayed a relatively short survival (<25 months). These data suggest that G298S is a mutation with unique genetic basis and clinical relevance. However, due to the rarity of the mutation carriers, it remains unclear where was this founder effect originated and transmitted. Population-based studies that would be taken into account biologic and sociocultural factors would help in the understanding of these questions. The consequences of TARDBP mutations on TDP-43 function and neuro-degeneration remain unclear. Studies have suggested that TDP-43 alters RNA metabolism in the cytoplasm through a toxic gain of function whereas the nuclear depletion of TDP-43 could lead to aberrant RNA metabolism through a loss of function [17]. More than 15 mouse models have been reported in which WT and ALS mutant of human TDP-43 are expressed, but its roles in disease mechanisms is uncertain [44, 45]. Clinical characteristics of ALS patients with the TARDBP G298S mutation a: F, familial case, S=sporadic case, F3-1 and F3-2 are two cases in the third family; Birthplace b: GD, Guangdong; GX, Guangxi; Site of onset c: U, upper Lower limb; B, Bulbar; EMG d: Fib, Fibrillations, Fas, fasciculations, PSW, positive sharp waves; Diagnosis level: Def, definite; Prob, probable; Poss, l bl Patient a: F, familial case, S=sporadic case, F3-1 and F3-2 are two cases in the third family; Birthplace b: GD, Guangdong; GX, Guangxi; Site of onset c: U, upper limb; L, Lower limb; B, Bulbar; EMG d: Fib, Fibrillations, Fas, fasciculations, PSW, positive sharp waves; Diagnosis level: Def, definite; Prob, probable; Poss, possible. NA, not available. Clinical characteristics of ALS patients with the TARDBP G298S mutation Page 6/12 Page 6/12 Table 4 The demographic and clinical features of the ALS patients carrying the TARDBP G298S mutation Patient a F1 F2 F3-1 F3-2 F4 F5 F6 F7 S1 S2 S3 S4 S5 S6 S7 S8 Gender F F F M F F F M F M F F M M M M Birthplaceb GD GD GD GD GD GD GD GD GX GD GD GD GX GD GX GD Diagnosis level e Def Def Def Def Def Prob Poss Def Def Def Prob Def Poss Def Poss De AAO (years) 50 50 62 54 73 49 53 46 43 53 38 39 59 49 52 59 Site of onsetc U L U B U B U B U U U B U U B U+ UMN signs Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Ye LMN signs No Yes Yes Yes Yes Yes No No Yes Yes Yes Yes No Yes Yes Ye Fasciculation Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Ye ALSFRS-R 48 46 44 NA 40 37 37 45 42 42 NA NA NA 46 40 20 Survival (months) ＞48 15 13 20 10 11 20 14 NA 14 NA ＜7 NA 24 8 NA EMGd NA Fib Fas PSW Fib Fas PSW Fib Fas PSW Fib Fas PSW Fib Fas PSW Fib Fas PSW Fib Fas PSW Fib Fas PSW Fib Fas PSW NA Fib Fas PSW NA Fib Fas PSW Fib Fas PSW NA Other variants No No No No No No ALS2 A1550T SPG11 L1982S No No No No FIG4 I220V NEK1 D1208N No No Smoking No No No No No No No No No Yes NA No NA Yes No No Drinking No No No No No No No No No No NA No NA No No No Pesticide No No No No No No No Yes No No NA No NA Yes No No Patient a: F, familial case, S=sporadic case, F3-1 and F3-2 are two cases in the third family; Birthplace b: GD, Guangdong; GX, Guangxi; Site of onset c: U, upper limb; L, Lower limb; B, Bulbar; EMG d: Fib, Fibrillations, Fas, fasciculations, PSW, positive sharp waves; Diagnosis level: Def, definite; Prob, probable; Poss, possible. NA, not available. Conclusion In conclusion, our study identified G298S as a unique mutation showing founder effect in cases from Southern China. However, the number of cases carrying the mutation were relatively small, and more G298S carriers are needed in the future in order to gain a clearer genotype-phenotype picture of this rare mutation. In addition, we reviewed the correlation of geographic and clinical features with TARDBP mutations reported worldwide, highlighting the mutation hotspots in Western and Eastern countries. Discussion These data suggest the distinct geographic distribution and clinical features of different mutations, and the differences in the site of onset in patients with different mutations does not seem to explain the differences in survival. Abbreviations ALS: Amyotrophic lateral sclerosis; FTD: frontotemporal dementia; PCR: polymerase chain reaction; HRE: hexanucleotide repeat expansion; WES: whole-exome sequencing; ACMG/AMP: American College of Medical Genetics and Genomics and the Association for Molecular Pathology; SIFT: Sorting intolerant from tolerant; CADD: Combined annotation-dependent depletion; GERP: Genomic evolutionary rate profiling; UMN: upper motor neuron; LMN: lower motor neuron; ALSFRS-R: ALS functional rating scale-revised; EMG: Electromyography; VUS: variant of unknown significance. Discussion In addition, although the mutations have been involved in alteration of the aggregation propensity and cytoplasmic mislocalization in neurons, their pathological effects remain to be established [15]. A recent study using the knock-in mice expressing the M337V and G298S mutations showed that the hemizygous mutations did not influence TDP-43 levels or changed its nuclear localization by 2 years of age, while most homozygous knock-in animals display asymmetric denervation of tibialis anterior muscle at 2.5 years, demonstrating the dose dependent MN toxicity of the TDP-43 mutant protein. Moreover, the TDP-43 knock-in mice displayed varying degrees of denervation, consistent with the incomplete penetrance of TARDBP Page 7/12 Page 7/12 mutations in ALS patients. These observations suggest that other factors, such as environmental or genetic, may contribute to TDP-43 pathology [46]. However, such factors have not been documented and could be identified via studies using larger cohorts and more advanced sequencing technologies. mutations in ALS patients. These observations suggest that other factors, such as environmental or genetic, may contribute to TDP-43 pathology [46]. However, such factors have not been documented and could be identified via studies using larger cohorts and more advanced sequencing technologies. Although the genotype-phenotype correlations of TARDBP mutations have been reported, the inter-mutational differences in distribution and clinical features remain elusive. We reviewed the literature-reported mutations and revealed a geographic pattern of the recurrent mutations. Interestingly, the M337V, G348C, N352S and I383V mutations were detected in cases all over the world, whereas the A382T was predominantly detected in European (especially Sardinian) [28 and American, but not in Asians. The clinical phenotype encompasses patients with bulbar and limb onset and with short and long disease durations. Although most of the cases with mutations displayed limb onset, a bulbar symptoms-dominant onset and the longest disease duration was reported in the carriers for M337V mutation [47]. In contrast, a limb onset and the shortest survival was observed in our carriers for G298S mutation. These data suggest the distinct geographic distribution and clinical features of different mutations, and the differences in the site of onset in patients with different mutations does not seem to explain the differences in survival. Although the genotype-phenotype correlations of TARDBP mutations have been reported, the inter-mutational differences in distribution and clinical features remain elusive. We reviewed the literature-reported mutations and revealed a geographic pattern of the recurrent mutations. Availability of data and materials Detailed mutational and clinical data of all patients are submitted as Table 1 and Table 4. Genotypes of microsatellites flanking TARDBP in the ALS patients carrying the G298S mutation are submitted as Table 2. The primer sequences are shown in Additional file: Supplementary Materials. Geography-mutation analyses were based on published reports or databases. The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive [48] in National Genomics Data Center [49], China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences (GSA- Human: HRA001905) that are publicly accessible at https://ngdc.cncb.ac.cn/gsa-human. Consent for publication Not applicable. Discussion Interestingly, the M337V, G348C, N352S and I383V mutations were detected in cases all over the world, whereas the A382T was predominantly detected in European (especially Sardinian) [28] and American, but not in Asians. The clinical phenotype encompasses patients with bulbar and limb onset and with short and long disease durations. Although the genotype-phenotype correlations of TARDBP mutations have been reported, the inter-mutational differences in distribution and clinical features remain elusive. We reviewed the literature-reported mutations and revealed a geographic pattern of the recurrent mutations. Interestingly, the M337V, G348C, N352S and I383V mutations were detected in cases all over the world, whereas the A382T was predominantly detected in European (especially Sardinian) [28] and American, but not in Asians. The clinical phenotype encompasses patients with bulbar and limb onset and with short and long disease durations. Although most of the cases with mutations displayed limb onset, a bulbar symptoms-dominant onset and the longest disease duration was reported in the carriers for M337V mutation [47]. In contrast, a limb onset and the shortest survival was observed in our carriers for G298S mutation. These data suggest the distinct geographic distribution and clinical features of different mutations, and the differences in the site of onset in patients with different mutations does t t l i th diff i i l N352S and I383V mutations were detected in cases all over the world, whereas the A382T was predominantly detected in European (especially Sardinian) [28] and American, but not in Asians. The clinical phenotype encompasses patients with bulbar and limb onset and with short and long disease durations. Although most of the cases with mutations displayed limb onset, a bulbar symptoms-dominant onset and the longest disease duration was reported in the carriers for M337V mutation [47]. In contrast, a limb onset and the shortest survival was observed in our carriers for G298S mutation. These data suggest the distinct geographic distribution and clinical features of different mutations, and the differences in the site of onset in patients with different mutations does not seem to explain the differences in survival. Although most of the cases with mutations displayed limb onset, a bulbar symptoms-dominant onset and the longest disease duration was reported in the carriers for M337V mutation [47]. In contrast, a limb onset and the shortest survival was observed in our carriers for G298S mutation. Ethics approval and consent to participate All research participants or their legal representatives signed informed consent forms for participation in clinical and genetic research. This study was approved by the institutional ethics board of Xuanwu Hospital of the Capital Medical University (Clinical Research Audit: [2021]034) and The China Human Genetic Resource Administration Office (China Ministry of Science and Technology Genetics Audit: [2021] CJ1167). In this study, all methods were performed in accordance with the relevant guidelines and regulations in accordance with the Declaration of Helsinki. Funding CW was supported by grants from the National Natural Science Foundation [82171412], Ministry of Science and Technology [2016YFC1306000], Special Fund from Key laboratory of Neurodegenerative Diseases, Ministry of Education of China [PXM2019_026283_000002]. XY was supported by was supported by grants from National Key Research and Development Program of China [2017YFC0907703], Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases [2020B1212060017], Guangdong Provincial Clinical Research Center for Neurological Diseases [2020B1111170002], the Southern China International Cooperation Base for Early Intervention and Functional Rehabilitation of Neurological Diseases [2015B050501003, 2020A0505020004]. Competing interests The authors declare no conflicts of interest. All authors are grateful for the participation and contribution of all patients and their families. All authors are grateful for the participation and contribution of all patients and their families References Clinical and genetic analysis of MAPT, GRN, and C9orf72 genes in Korean patients with frontotemporal dementia. Neurobiol Aging. 2014;35:1213.e13-1213.e17. 9. Kim EJ, Kwon JC, Park KH, et al. Clinical and genetic analysis of MAPT, GRN, and C9orf72 genes in Korean patients with frontotemporal dementia. Neurobiol Aging. 2014;35:1213.e13-1213.e17. 10. Zou ZY, Liu MS, Li XG, et al. Mutations in FUS are the most frequent genetic cause in juvenile sporadic ALS patients of Chinese origin. Amyotroph Lateral Scler Frontotemporal Degener. 2016;17:249-252. 10. Zou ZY, Liu MS, Li XG, et al. Mutations in FUS are the most frequent genetic cause in juvenile sporadic ALS patients of Chinese origin. Amyotroph Lateral Scler Frontotemporal Degener. 2016;17:249-252. 11. Liu ZJ, Lin HX, Liu GL, et al. The investigation of genetic and clinical features in Chinese patients with juvenile amyotrophic lateral sclerosis. Clin Genet. 2017;92:267-273. 12. Arai T, Hasegawa M, Akiyama H, et al. TDP-43 is a component of ubiquitin-positive tau-negative inclusions in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Biochem Biophys Res Commun. 2006;351:602–611. 13. Liachko N F, Saxton A D, McMillan P J, et al. The phosphatase calcineurin regulates pathological TDP-43 phosphorylation. Acta Neuropathol 2016;132:545-561. ran J, Blair IP, Tripathi VB, et al. TDP-43 mutations in familial and sporadic amyotrophic lateral sclerosis. Science. 14. Sreedharan J, Blair IP, Tripathi VB, et al. TDP-43 mutations in familial and sporadic amyotrophic lateral sclerosis. Science. 2008;319:1668-1672. 14. Sreedharan J, Blair IP, Tripathi VB, et al. TDP-43 mutations in familial and sporadic amyotrophic lateral sclerosis. Science. 2008;319:1668-1672. 15. Rutherford NJ, Zhang YJ, Baker M, et al. Novel mutations in TARDBP (TDP-43) in patients with familial amyotrophic lateral sclerosis. PLoS Genet. 2008;4:e1000193. 15. Rutherford NJ, Zhang YJ, Baker M, et al. Novel mutations in TARDBP (TDP-43) in patients with familial amyotrophic lateral sclerosis. PLoS Genet. 2008;4:e1000193. 16. Pesiridis GS, Lee VM, Trojanowski JQ. Mutations in TDP-43 link glycine-rich domain functions to amyotrophic lateral sclerosis. Hum Mol Genet. 2009;18:R156–162; 7. Lee EB, Lee VM, Trojanowski JQ. Gains or losses: molecular mechanisms of TDP43-mediated neurodegenerati 17. Lee EB, Lee VM, Trojanowski JQ. Gains or losses: molecular mechanisms of TDP43-mediated neurodegeneration. Nat Rev Neurosci. 2011;13:38–50. 18. McAlary L, Plotkin S S, Yerbury J J, et al. Prion-like propagation of protein misfolding and aggregation in amyotrophic lateral sclerosis. Front Mol Neurosci. 2019;12:262. 18. McAlary L, Plotkin S S, Yerbury J J, et al. Prion-like propagation of protein misfolding and aggregation in amyotrophic lateral sclerosis. References 1. Brown RH, Al-Chalabi A. Amyotrophic Lateral Sclerosis. N Engl J Med. 2017;377:162-172. 2. van Es MA, Hardiman O, Chio A, et al. Amyotrophic lateral sclerosis. Lancet. 2017;390:2084-2098. 2. van Es MA, Hardiman O, Chio A, et al. Amyotrophic lateral sclerosis. Lancet. 2017;390:2084-2098. 2. van Es MA, Hardiman O, Chio A, et al. Amyotrophic lateral sclerosis. Lancet. 2017;390:2084-2098. 3. Morgan S, Shoai M, Fratta P, et al. Investigation of next-generation sequencing technologies as a diagnostic tool for amyotrophic lateral sclerosis. Neurobiol Aging. 2015;36:1600.e5-1600.e8. 3. Morgan S, Shoai M, Fratta P, et al. Investigation of next-generation sequencing technologies as a diagnostic tool for amyotrophic lateral sclerosis. Neurobiol Aging. 2015;36:1600.e5-1600.e8. 3. Morgan S, Shoai M, Fratta P, et al. Investigation of next-generation sequencing technologies as a diagnostic tool for amyotrophic lateral sclerosis. Neurobiol Aging. 2015;36:1600.e5-1600.e8. 4. Nguyen HP, Van Broeckhoven C, van der Zee J. ALS Genes in the Genomic Era and their Implications for FTD. T 5. Zou ZY, Zhou ZR, Che CH, et al. Genetic epidemiology of amyotrophic lateral sclerosis: a systematic review and meta-analysis. J Neurol Neurosurg Psychiatry. 2017;88:540-549. 5. Zou ZY, Zhou ZR, Che CH, et al. Genetic epidemiology of amyotrophic lateral sclerosis: a systematic review and meta-analysis. J Neurol Neurosurg Psychiatry. 2017;88:540-549. 5. Zou ZY, Zhou ZR, Che CH, et al. Genetic epidemiology of amyotrophic lateral sclerosis: a systematic review and meta-analysis. J Neurol Neurosurg Psychiatry. 2017;88:540-549. 6. Renton AE, Chiò A, Traynor BJ. State of play in amyotrophic lateral sclerosis genetics. Nat Neurosci. 2014;17:17 6. Renton AE, Chiò A, Traynor BJ. State of play in amyotrophic lateral sclerosis genetics. Nat Neurosci. 2014;17:17–23. 6. Renton AE, Chiò A, Traynor BJ. State of play in amyotrophic lateral sclerosis genetics. Nat Neurosci. 2014;17:17–23. 7. Deng HX, Hentati A, Tainer JA, et al. Amyotrophic lateral sclerosis and structural defects in Cu, Zn superoxide d 7. Deng HX, Hentati A, Tainer JA, et al. Amyotrophic lateral sclerosis and structural defects in Cu, Zn superoxide dismutase. Science. 1993;261:1047-1051. 8. Jiao B, Guo JF, Wang YQ, et al. C9orf72 mutation is rare in Alzheimer’s disease, Parkinson's disease, and essential tremor in China. Front Cell Neurosci. 2013;7, 164. 8. Jiao B, Guo JF, Wang YQ, et al. C9orf72 mutation is rare in Alzheimer’s disease, Parkinson's disease, and essential tremor in China. Front Cell Neurosci. 2013;7, 164. 9. Kim EJ, Kwon JC, Park KH, et al. Authors' contributions FX, XY and CW conceived the project and designed the study. FX wrote the original draft. FX, SH, XYL, XF, ZW, XY and CW analysed and annotated the data. FX, SH, XYL, XF, SX, ZW and XL performed methodology. XY and CW acquired funding and supervised the whole project. All authors read and approved the final manuscript. Page 8/12 Page 8/12 Acknowledgments References Front Mol Neurosci. 2019;12:262. 19. Chiò A, Borghero G, Pugliatti M, et al. Large proportion of amyotrophic lateral sclerosis cases in Sardinia due to a single founder mutation of the TARDBP gene. Arch Neurol. 2011;68:594-598. 20. Ricci C, Giannini F, Intini E, et al. Genotype-phenotype correlation and evidence for a common ancestor in two Italian ALS patients with the D124G SOD1 mutation. Amyotroph Lateral Scler Frontotemporal Degener. 2019;20:611-614. 20. Ricci C, Giannini F, Intini E, et al. Genotype-phenotype correlation and evidence for a common ancestor in two Italian ALS patients with the D124G SOD1 mutation. Amyotroph Lateral Scler Frontotemporal Degener. 2019;20:611-614. 21. Battistini S, Ricci C, Giannini F, et al. G41S SOD1 mutation: A common ancestor for six ALS Italian families with an aggressive phenotype. Amyotroph Lateral Scler. 2010;11:210-215. 21. Battistini S, Ricci C, Giannini F, et al. G41S SOD1 mutation: A common ancestor for six ALS Italian families with an aggressive phenotype. Amyotroph Lateral Scler. 2010;11:210-215. 22. Saeed M, Yang Y, Deng HX, et al. Age and founder effect of SOD1 A4V mutation causing ALS. Neurology. 2 22. Saeed M, Yang Y, Deng HX, et al. Age and founder effect of SOD1 A4V mutation causing ALS. Neurology. 2009;72:1634-1639. 22. Saeed M, Yang Y, Deng HX, et al. Age and founder effect of SOD1 A4V mutation causing ALS. Neurology. 2009;72:1634-1639. 23. Kuźma-Kozakiewicz M, Andersen PM, Elahi E, et al. Putative founder effect in the Polish, Iranian and United States populations for the L144S SOD1 mutation associated with slowly uniform phenotype of amyotrophic lateral sclerosis. Amyotroph Lateral Scler Frontotemporal Degener. 2021;22:80-85. 24. Nishimura AL, Al-Chalabi A, Zatz M. A common founder for amyotrophic lateral sclerosis type 8 (ALS8) in the Brazilian population. Hum Genet. 2005;118:499-500. 23. Kuźma-Kozakiewicz M, Andersen PM, Elahi E, et al. Putative founder effect in the Polish, Iranian and United States populations for the L144S SOD1 mutation associated with slowly uniform phenotype of amyotrophic lateral sclerosis. Amyotroph Lateral Scler Frontotemporal Degener. 2021;22:80-85. 24. Nishimura AL, Al-Chalabi A, Zatz M. A common founder for amyotrophic lateral sclerosis type 8 (ALS8) in the Brazilian population. Hum Genet. 2005;118:499-500. 23. Kuźma-Kozakiewicz M, Andersen PM, Elahi E, et al. Putative founder effect in the Polish, Iranian and United States populations for the L144S SOD1 mutation associated with slowly uniform phenotype of amyotrophic lateral sclerosis. Amyotroph Lateral Scler Frontotemporal Degener. 2021;22:80-85. 24. Nishimura AL, Al-Chalabi A, Zatz M. References A common founder for amyotrophic lateral sclerosis type 8 (ALS8) in the Brazilian population. Hum Genet. 2005;118:499-500. 25. Niemann S, Joos H, Meyer T, et al. Familial ALS in Germany: origin of the R115G SOD1 mutation by a founder effect. Journal of neurology, neurosurgery, and psychiatry. 2004;75:1186-1188. 25. Niemann S, Joos H, Meyer T, et al. Familial ALS in Germany: origin of the R115G SOD1 mutation by a founder effect. Journal of neurology, neurosurgery, and psychiatry. 2004;75:1186-1188. 26. Smith BN, Newhouse S, Shatunov A, et al. The C9ORF72 expansion mutation is a common cause of ALS+/-FTD in Europe and has a single founder. Eur J Hum Genet. 2013;21:102-108. 26. Smith BN, Newhouse S, Shatunov A, et al. The C9ORF72 expansion mutation is a common cause of ALS+/-FTD in Europe and has a single founder. Eur J Hum Genet. 2013;21:102-108. 27. Andersen P M. Amyotrophic lateral sclerosis associated with mutations in the CuZn superoxide dismutase 27. Andersen P M. Amyotrophic lateral sclerosis associated with mutations in the CuZn superoxide dismutase gene. Curr Neurol Neurosci Rep. 2006;6:37-46. 28. Borghero G, Pugliatti M, Marrosu F, et al. Genetic architecture of ALS in Sardinia. Neurobiol Aging. 2014;35:2882.e7-2882.e12. y p p g p 28. Borghero G, Pugliatti M, Marrosu F, et al. Genetic architecture of ALS in Sardinia. Neurobiol Aging. 2014;35:2882.e7-2882.e12. 28. Borghero G, Pugliatti M, Marrosu F, et al. Genetic architecture of ALS in Sardinia. Neurobiol Aging. 2014;35: 28. Borghero G, Pugliatti M, Marrosu F, et al. Genetic architecture of ALS in Sardinia. Neurobiol Aging. 2014;35:2882.e7-2882.e12. 29. Liu ZJ, Lin HX, Wei Q, et al. Genetic Spectrum and Variability in Chinese Patients with Amyotrophic Lateral 29. Liu ZJ, Lin HX, Wei Q, et al. Genetic Spectrum and Variability in Chinese Patients with Amyotrophic Lateral Sclerosis. Aging Dis. 2019;10:1199-1206. 30. Deng J, Wu W, Xie Z, et al. Novel and Recurrent Mutations in a Cohort of Chinese Patients with Young-Onset Amyotrophic Lateral Sclerosis. Front Neurosci. 2019;13:1289. 30. Deng J, Wu W, Xie Z, et al. Novel and Recurrent Mutations in a Cohort of Chinese Patients with Young-Onset Amyotrophic Lateral Sclerosis. Front Neurosci. 2019;13:1289. Page 9/12 Page 9/12 31. DeJesus-Hernandez M, Mackenzie IR, Boeve BF, et al. Expanded GGGGCC hexanucleotide repeat in noncoding region of C9ORF72 causes chromosome 9p-linked FTD and ALS. Neuron. 2011;72:245-256. 31. DeJesus-Hernandez M, Mackenzie IR, Boeve BF, et al. References Rodent models of amyotrophic lateral sclerosis. Biochim Biophys Acta. 2013;1832:1421–1436. 45. Xu YF, Gendron TF, Zhang YJ, et al. Wild-type human TDP-43 expression causes TDP-43 phosphorylation, mitochondrial aggregation, motor deficits, and early mortality in transgenic mice. J Neurosci. 2010;30:10851–10859. 46. Ebstein SY, Yagudayeva I, Shneider NA. Mutant TDP-43 Causes Early-Stage Dose- Dependent Motor Neuron Degeneration in a TARDBP Knockin Mouse Model of ALS. Cell Rep. 2019;26:364-373.e4. 7. Liu W, Li X, Sun Y, et al. Genotype-phenotype correlations in a chinese population with familial amyotrophic late 47. Liu W, Li X, Sun Y, et al. Genotype-phenotype correlations in a chinese population with familial amyotrophic lateral sclerosis. Neurol Res. 2021;1-11. 47. Liu W, Li X, Sun Y, et al. Genotype-phenotype correlations in a chinese population with familial amyotrophic lateral sclerosis. Neurol Res. 2021;1-11. 48. Chen T, Chen X, Zhang S, et al.The Genome Sequence Archive Family: Toward Explosive Data Growth and Diverse Data Types. Genomics Proteomics Bioinformatics. 2021; S1672-0229: 00163-00167. 48. Chen T, Chen X, Zhang S, et al.The Genome Sequence Archive Family: Toward Explosive Data Growth and Diverse Data Types. Genomics Proteomics Bioinformatics. 2021; S1672-0229: 00163-00167. 49. CNCB-NGDC Members and Partners: Xue Y, Bao Y, Zhang Z, et al. Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2022. Nucleic Acids Res 2022,50: D27-D38. 49. CNCB-NGDC Members and Partners: Xue Y, Bao Y, Zhang Z, et al. Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2022. Nucleic Acids Res 2022,50: D27-D38. References Expanded GGGGCC hexanucleotide repeat in noncoding region of C9ORF72 causes chromosome 9p-linked FTD and ALS. Neuron. 2011;72:245-256. 32. Renton AE, Majounie E, Waite A, et al. A hexanucleotide repeat expansion in C9ORF72 is the cause of chromosome 9p21-linked ALS-FTD. Neuron. 2011;72: 257-268. 33. Li XY, Cui Y, Jing D, et al. Novel PSEN1 and PSEN2 Mutations Identified in Sporadic Early-onset Alzheimer Disease and Posterior Cortical Atrophy. Alzheimer Dis Assoc Disord. 2021;35:208-213. 34. Richards S, Aziz N, Bale S, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17:405-424. 35. Orrù S, Manolakos E, Orrù N, et al. High frequency of the TARDBP p.Ala382Thr mutation in Sardinian patients with amyotrophic lateral sclerosis. Clin Genet. 2012;81:172-178. 36. Stephens M and Donnelly P. A comparison of bayesian methods for haplotype reconstruction from population genotype data. Am J Hum Genet. 2003;73:1162-1169. 37. Orrù S, Manolakos E, Orrù N, et al. High frequency of the TARDBP p.Ala382Thr mutation in Sardinian patients with amyotrophic lateral sclerosis. Clin Genet. 2012;81:172-178. 8. van Blitterswijk M, van Es MA, Hennekam EA, et al. Evidence for an oligogenic basis of amyotrophic lateral scle 38. van Blitterswijk M, van Es MA, Hennekam EA, et al. Evidence for an oligogenic basis of amyotrophic lateral sclerosis. Hum Mol Genet. 2012;21:3776-3784. 39. Corrado L, Pensato V, Croce R, et al. The first case of the TARDBP p.G294V mutation in a homozygous state: is a single pathogenic allele sufficient to cause ALS? Amyotroph Lateral Scler Frontotemporal Degener. 2020;21:273-279. 40. Lin J, Chen W, Huang P, et al. The distinct manifestation of young-onset amyotrophic lateral sclerosis in China. Amyotroph Lateral Scler Frontotemporal Degener. 2021;22:30-37. 41. Van Deerlin VM, Leverenz JB, Bekris LM, et al. TARDBP mutations in amyotrophic lateral sclerosis with TDP-43 neuropathology: a genetic and histopathological analysis. Lancet Neurol. 2008;7:409-416. 42. Nozaki I, Arai M, Takahashi K, et al. Familial ALS with G298S mutation in TARDBP: a comparison of CSF tau protein levels with those in sporadic ALS. Intern Med. 2010;49:1209-1212. 43. Synofzik M, Born C, Rominger A, et al. Targeted high-throughput sequencing identifies a TARDBP mutation as a cause of early-onset FTD without motor neuron disease. Neurobiol Aging. 2014;35:1212.e1-1212.e5. 44. McGoldrick P, Joyce PI, Fisher EM, et al. Rodent models of amyotrophic lateral sclerosis. Biochim Biophys A Fisher EM, et al. Figure 2 Distribution of TARDBP mutations reported in the world and China. (A) Mutations reported in the world. Each mutation was represented for one number. The three prevalent mutations were denoted in dots with different colors: M337V (orange), A382T (yellow) and G298S (purple), and other mutations were denoted in blue dots. The amplified gray square regions represent West Europe which was enlarged on upper right. Five pie charts show the countries in which mutations were more frequently detected. Maps were obtained through My Maps (https://www. google. com /mymaps, Accessed in 05.30.2021). (B) Map of China with reported TARDBP mutations. Different mutations were denoted with different colors. The number on the dot represents the number of reported cases. SupplementaryMaterials.docx Figures Page 10/12 gure 1 edigree map of the TARDBP G298S families. Pedigrees showing 7 families detected to carry the TARDBP G298S mutations. Black symbols represent atients affected with ALS, white symbols represent unaffected individuals. Arrowheads indicate the probands. Figure 1 Pedigree map of the TARDBP G298S families. Pedigrees showing 7 families detected to carry the TARDBP G298S mutations. Black symbols represent patients affected with ALS, white symbols represent unaffected individuals. Arrowheads indicate the probands. Page 11/12 Figure 2 Supplementary Files This is a list of supplementary files associated with this preprint. Click to download. SupplementaryMaterials.docx Page 12/12 Page 12/12
https://openalex.org/W2130476329	https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1155/ASP.2005.1110	English	null	Speech Enhancement by MAP Spectral Amplitude Estimation Using a Super-Gaussian Speech Model	EURASIP Journal on Advances in Signal Processing	2,005	cc-by	14,257	This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. EURASIP Journal on Applied Signal Processing 2005:7, 1110–1126 c⃝2005 T. Lotter and P. Vary EURASIP Journal on Applied Signal Processing 2005:7, 1110–1126 c⃝2005 T. Lotter and P. Vary Peter Vary Institute of Communication Systems and Data Processing, RWTH Aachen University of Technology, RWTH Aachen, 52056 Aachen, Germany Email: vary@ind.rwth-aachen.de stitute of Communication Systems and Data Processing, RWTH Aachen University of Technology, RWTH Aachen, 2056 Aachen, Germany il @i d th h d Received 7 June 2004; Revised 17 September 2004; Recommended for Publication by Jacob Benesty This contribution presents two spectral amplitude estimators for acoustical background noise suppression based on maximum a posteriori estimation and super-Gaussian statistical modelling of the speech DFT amplitudes. The probability density function of the speech spectral amplitude is modelled with a simple parametric function, which allows a high approximation accuracy for Laplace- or Gamma-distributed real and imaginary parts of the speech DFT coeﬃcients. Also, the statistical model can be adapted to optimally ﬁt the distribution of the speech spectral amplitudes for a speciﬁc noise reduction system. Based on the super- Gaussian statistical model, computationally eﬃcient maximum a posteriori speech estimators are derived, which outperform the commonly applied Ephraim-Malah algorithm. Keywords and phrases: speech enhancement, MAP estimation, speech model. Speech Enhancement by MAP Spectral Amplitude Estimation Using a Super-Gaussian Speech Model Thomas Lotter Institute of Communication Systems and Data Processing, RWTH Aachen University of Technology, RWTH Aachen, 52056 Aachen, Germany Institute of Communication Systems and Data Processing, RWTH Aachen University of Technology, RWTH Aach 52056 Aachen, Germany Siemens Audiological Engineering Group, Gebbertstrasse 125, 91058 Erlangen, Germany Email: thomas.tl.lotter@siemens.com 1. INTRODUCTION property can be exploited by separating speech and noise in the spectral domain. The concept of spectral domain noise attenuation has been introduced more than twenty years ago by Boll [1] as the subtraction of an estimated noise spectral magnitude from the noisy spectral magnitude. The reduction of acoustical background noise using a single microphone is an important subject to improve the quality of speech communication systems in the context of digital hear- ing aids, speech recognition, hands-free telephony, or tele- conferencing. Although single-microphone speech enhance- ment has been a research topic for decades, the estimation of a clean speech signal from its noisy observation remains a challenging task, especially due to the wide variety of envi- ronmental noises. To estimate the noise power spectral density, the sec- ond property, nonstationarity, is exploited by averaging DFT squared magnitudes in noise-only phases or by tracking spectral minima over time [2]. Noise reduction by spectral domain weighting has frequently been plagued by musical tones, that is, annoying ﬂuctuations in the residual noise sig- nal. This is especially due to the subtraction of an expecta- tion in terms of the noise power spectral density from an in- stantaneous value. To overcome this problem, improved al- gorithms have been proposed by Ephraim and Malah [3, 4]. The clean speech spectral amplitude is estimated with respect to the minimization of a statistical error criterion. Together with a recursive estimation of the underlying speech vari- ance, the approach results in a good speech quality without audible musical noise. If the disturbing noise is assumed to be truly environ- mental, that is, its origin is, for example, machines, cars, or several persons talking at the same time, the speciﬁc proper- ties of speech such as nonwhiteness, nonstationarity and non- Gaussianity compared to unwanted noise allow a diﬀerentia- tion between speech and noise. Nonwhiteness means that the short-time spectrum of speech is generally less ﬂat than that of acoustic noise. This Recently, the third property, non-Gaussianity, has been included in the spectral domain noise reduction framework by Martin [5, 6]. The statistical estimation of the speech Speech Estimation Using a Super-Gaussian Speech Model 1111 y(l) Segmentation windowing FFT Y(k) Speech estimation ˆξ(k), ˆγ(k) SNR estimation G(k) ˆS(k) IFFT Overlap-add ˆs(l) Figure 1: Overview of the single-channel speech enhancement system (l: time index, k: frequency index). 1. INTRODUCTION Speech estimation Figure 1: Overview of the single-channel speech enhancement system (l: time index, k: frequency index). a MAP estimator for the speech spectral amplitude and a joint MAP estimator for the speech spectral amplitude and phase. Finally, in Section 5, experimental results are pre- sented. spectrum requires a statistical model of the undisturbed speech and noise spectral coeﬃcients. It is well known that speech samples have a super-Gaussian distribution, which causes the speech spectral coeﬃcients to be super-Gaussian distributed as well. By including a super-Gaussian model of speech, the mean squared error of a statistical estimator can be decreased compared to an estimation with an underlying Gaussian model. Whereas the proposed estimators by Martin with underlying Gamma or Laplace PDFs for real and imagi- nary parts of speech and noise DFT coeﬃcients [5, 6] are op- timal with respect to the mean squared estimation error of the estimated complex speech DFT coeﬃcient, they are sub- optimal for the estimation of the speech spectral amplitude. 2. OVERVIEW Figure 1 shows an overview of the single-channel speech en- hancement system examined in this work [9]. The noisy time signal y(l) sampled at regular time intervals l·T is composed of clean speech s(l) and additive noise n(l): y(l) = s(l) + n(l). (1) (1) Spectral amplitude estimation can be considered more advantageous due to the perceptual unimportance of the phase [7]. Ephraim and Malah have proposed two estimators that minimize the squared or logarithmic error of the speech spectral amplitude under a Gaussian model of the complex speech and noise DFT coeﬃcients [3, 4]. After segmentation and windowing with a function h(l), for example, Hann window, the DFT coeﬃcient of frame λ and frequency bin k is calculated with Y(λ, k) = L−1 l=0 y(λQ + l)h(l)e−j2πlk/L, (2) (2) In this contribution spectral amplitude estimators with super-Gaussian speech modelling are introduced. The prob- ability density function of the speech spectral amplitude is approximated by a function with two parameters. With a proper choice of the parameters, for example, the proba- bility density of the amplitude of a complex random vari- able (RV) with both independent Laplace and Gamma com- ponents can be approximated with high accuracy. Also, the parameters of the underlying PDF can be optimally ﬁt- ted to the real distribution of the speech spectral ampli- tude for a speciﬁc noise reduction algorithm. Using this statistical model, computationally eﬃcient speech estima- tors can be found by applying the maximum a posteriori (MAP) estimation rule. The resulting estimators, which are super-Gaussian extensions of the MAP estimators derived by Wolfe and Godsill [8], outperform the commonly applied Ephraim-Malah estimators by the more accurate statistical model. L denotes the DFT frame size. For the noise reduction system applied in this work, L = 256 is used at a sampling frequency of 20kHz. For the computation of the next DFT, the window is shifted by Q samples. To decrease the disturbing eﬀects of cyclic convolution, we apply half overlapping Hann windows with 16 zeros at the beginning and end. The eﬀective frame size is thus only 224 samples, which corresponds to a frame size of 11.2 milliseconds and a frame shift of 5.6 milliseconds, respectively. L denotes the DFT frame size. For the noise reduction system applied in this work, L = 256 is used at a sampling frequency of 20kHz. 3. STATISTICAL MODEL We introduce the statistical model for the speech and noise spectral amplitudes. For the sake of brevity the frame index λ and frequency index k are omitted, however the following considerations hold independently for every frequency bin k and frame λ. Motivated by the central limit theorem, real and imag- inary parts of both speech and noise DFT coeﬃcients are very often modelled as zero-mean independent Gaussian [3, 14, 15] with equal variance. This is due to the properties of the DFT: Y(λ, k) = L−1 l=0 y(λQ + l) cos 2πkl L −j L−1 l=0 y(λQ + l) sin 2πkl L , (9) Based on the noise estimates ˆσ2 N and the observed Fourier amplitudes R the a priori and the a posteriori SNRs are esti- mated by (9) ˆξ(λ, k) = ˆσ2 S(λ, k) ˆσ2 N(λ, k), ˆγ(λ, k) = R2(λ, k) ˆσ2 N(λ, k). (5) (5) where L samples are added after multiplication with modula- tion terms. The central limit theorem states that the distribu- tion of the DFT coeﬃcients will converge towards a Gaussian PDF regardless of the PDF of the time samples y(l), if suc- cessive samples are statistically independent. This also holds if the correlation in y(l) is short compared to the analysis frame size [14]. Here, σ2 S denotes the instantaneous power spectral density of the speech. Whereas the a posteriori SNRs γ can directly be computed, the a priori SNRs ξ have to be estimated. This is performed using a recursive approach proposed by Ephraim and Malah [3]: For many relevant acoustic noises this assumption holds. Moreover, multiple noise sources or reverberation often re- duce the noise correlation in between the analysis frame size, so that the Gaussian assumption is fulﬁlled. The variance of the noise DFT coeﬃcient σ2 N is assumed to split equally into real and imaginary parts. Thus, the probability density func- tion of real and imaginary parts of noise Fourier coeﬃcients can be modelled as ˆξ(λ, k) = αsnr ˆA2(λ −1, k) ˆσ2 N(λ, k) + 1 −αsnr F γ ˆλ, k −1 , F[x] =    x, x > 0, 0, else. (6) ˆξ(λ, k) = αsnr ˆA2(λ −1, k) ˆσ2 N(λ, k) + 1 −αsnr F γ ˆλ, k −1 , (6) F[x] =    x, x > 0, 0, else. 2. OVERVIEW For the computation of the next DFT, the window is shifted by Q samples. To decrease the disturbing eﬀects of cyclic convolution, we apply half overlapping Hann windows with 16 zeros at the beginning and end. The eﬀective frame size is thus only 224 samples, which corresponds to a frame size of 11.2 milliseconds and a frame shift of 5.6 milliseconds, respectively. The noisy DFT coeﬃcient Y consists of speech part S and noise N: Y(λ, k) = S(λ, k) + N(λ, k), (3) (3) with S = SRe + jSIm and N = NRe + jNIm, where SRe = Re{S} and SIm = Im{S}. In polar coordinates the noisy DFT coeﬃ- cient of amplitude R and phase ϑ is written as The remainder of the paper is organized as follows. Section 2 gives an overview of the single-channel noise re- duction by spectral weighting. Section 3 introduces the un- derlying statistical model for the speech and noise spec- tral amplitudes along with comparisons to experimental data. In Section 4 the statistical model is applied to derive R(λ, k)ejϑ(λ,k) = A(λ,k)ejα(λ,k) + B(λ, k)ejβ(λ,k). (4) (4) The speech DFT amplitude is termed as A, the noise DFT amplitude as B, and the respective phases as α, β. The speech DFT amplitude is termed as A, the noise DFT amplitude as B, and the respective phases as α, β. 1112 EURASIP Journal on Applied Signal Processing The SNR estimation block calculates a priori SNR ξ and a posteriori SNR γ for each DFT bin k. The SNR calcula- tion requires an estimate of the noise power spectral density σ2 N(λ, k). It can be estimated by averaging DFT squared mag- nitudes in periods of speech pauses. Assuming that noise is stationary, the measured PSD can be saved and applied as an estimate during following speech activity. This method re- quires a reliable voice activity detector (e.g., [10]). However, a VAD is diﬃcult to tune and its application at low SNRs of- ten results in clipped speech. Therefore, we apply minimum statistics, which tracks minima of the smoothed periodogram over a time period that greatly exceeds the speech short-time stationarity [2]. 3. STATISTICAL MODEL An alternative estimation approach which incorporates fre- quency correlation is presented in [11]. It is frequently ar- gued [12, 13] that the recursive approach is essential for a high quality of the enhanced signal. A high smoothing factor αsnr greatly reduces the dynamics of the instantaneous SNR in speech pauses and thus reduces musical tones. However the a priori SNR will then comprise a delayed version of the speech. Since the a priori SNR has a high impact on the noise reduction amount, it is useful to lower limit the a priori SNR according to p NRe = 1 √πσN exp −N2 Re σ2 N . (10) (10) Based on (10) and the assumption of statistically indepen- dent real and imaginary parts, the PDF of the noisy spectrum Y conditioned on the speech amplitude A and phase α can be written as joint Gaussian: p(Y\|A,α) = 1 πσ2 N exp − Y −Aejα2 σ2 N . (11) (11) ˜ξ(λ, k) =    ˆξ(λ, k), ˆξ(λ, k) > ξthr, ξthr, else. (7) (7) A Rice PDF is obtained for the density of the noisy amplitude given the speech amplitude A after polar integration of (11) [15]: The task of the speech estimation block is the calculation of spectral weights G for the noisy spectral components Y, such that the estimated speech DFT coeﬃcient ˆS is calculated by p(R\|A) = 2R σ2 N exp −R2 + A2 σ2 N I0 2AR σ2 N , (12) (12) where I0 denotes the modiﬁed Bessel function of the ﬁrst kind and zeroth order. ˆS(λ, k) = G ˆξ(λ, k), ˆγ(λ, k) · Y(λ, k). (8) (8) Considering speech, the span of correlation with typical frame sizes from 10 milliseconds to 30 milliseconds cannot be neglected. The smaller the frame size, the less Gaussian After IFFT and overlap-add, the enhanced time signal ˆs(l) is obtained. After IFFT and overlap-add, the enhanced time signal ˆs(l) is obtained. 3. STATISTICAL MODEL 1113 Speech Estimation Using a Super-Gaussian Speech Model 3 2 1 0 −1 −2 −3 SIm −3 −2 −1 0 1 2 3 SRe 0.005 0.01 0.025 0.05 0.1 (a) 3 2 1 0 −1 −2 −3 SIm −3 −2 −1 0 1 2 3 SRe 0.005 0.01 0.025 0.05 0.1 0.25 (b) Figure 2: Contour lines of complex Gaussian model with independent Cartesian coordinates and of complex Laplace model with indepen- dent Cartesian coordinates (σ2 S = 1). 3 2 1 0 −1 −2 −3 SIm −3 −2 −1 0 1 2 3 SRe 0.005 0.01 0.025 0.05 0.1 0.25 (b) 3 2 1 0 −1 −2 −3 SIm −3 −2 −1 0 1 2 3 SRe 0.005 0.01 0.025 0.05 0.1 (a) (b) (a) Figure 2: Contour lines of complex Gaussian model with independent Cartesian coordinates and of complex Laplace model with indepen- dent Cartesian coordinates (σ2 S = 1). will the distribution of the speech real and imaginary parts of the Fourier coeﬃcients will be. It is well known, that the PDFs of speech samples in the time domain are much better modelled by a Laplace or Gamma density [16]. In the fre- quency domain similar distributions can be observed. Mar- tin [5, 6] has abandoned the Gaussian speech model accord- ing to will the distribution of the speech real and imaginary parts of the Fourier coeﬃcients will be. It is well known, that the PDFs of speech samples in the time domain are much better modelled by a Laplace or Gamma density [16]. In the fre- quency domain similar distributions can be observed. Mar- tin [5, 6] has abandoned the Gaussian speech model accord- ing to Considering noise, the Gaussian assumptions hold due to comparably low correlation in the analysis frame. Assum- ing statistical independence of real and imaginary parts the PDF of the noise amplitude B can easily be found as Rayleigh distributed by polar integration p(B) = 2π 0 B · p NRe,NIm dβ = 2B σ2 N exp −B2 σ2 N . (16) (16) p SRe = 1 √πσS exp −S2 Re σ2 S . (13) (13) For the calculation of an appropriate PDF for A, the Gauss, Laplace, and Gamma PDFs for real and imaginary parts are taken into account. The real and imaginary parts of the Fourier coeﬃcients can be considered statistically indepen- dent with high accuracy. 3. STATISTICAL MODEL Then, p(A) can in general be calcu- lated by Instead, the Laplace probability density function p SRe = 1 σS exp −2 SRe σS (14) (14) p(A) = 2π 0 A · p(Acosα) · p(Asinα)dα, (17) and Gamma PDFs for statistical independent real and imag- inary parts have been proposed: (17) with the PDFs according to (13), (14), or (15) for p(SRe = A cosα), p(SIm = Asin α). p SRe = 4√3 SRe −1/2 2 4√2√πσS exp − √3 SRe √2σS . (15) (15) (15) Figure 2 shows contour lines of a complex Gaussian or Laplace PDF with independent Cartesian components. Com- pared to the Gaussian PDF, the Laplace PDF has a higher peak, a low amplitude and decreases slower towards higher amplitudes visible by the greater distances of the contour lines compared to the complex Gaussian PDF. While the complex Gaussian PDF is rotational invariant, the Laplace amplitude depends on the phase. The same equations hold for the imaginary parts. The same equations hold for the imaginary parts. 3.1. Modelling the spectral amplitudes In the following a simple statistical model for the speech and noise spectral amplitudes will be presented [17], which is sig- niﬁcantly closer to the real distribution than the commonly applied Gaussian model. Considering Gaussian components, the rotational invari- ance greatly facilitates the polar integration. Similar to (16) the amplitude is Rayleigh distributed: The spectral amplitudes are of special importance, be- cause the phase of the Fourier coeﬃcients can be considered unimportant from a perceptual point of view [7, 18]. Hence, spectral amplitude estimators are more advantageous and a statistical model for the amplitude alone is needed. p(A) = 2A σ2 S exp −A2 σ2 S . (18) (18) 1114 EURASIP Journal on Applied Signal Processing 1 0.5 0 p(A) 0 1 2 3 A 1 0.5 0 p(A) 0 1 2 3 A Histogram amplitude of complex Laplace random values Histogram amplitude of complex Gamma random values Rayleigh PDF rameter µ is introduced, which enables to approximate both. After normalizing A by the standard deviation σS we thus as- sume p(A) ∼exp −µ A σS . (19) (19) At low values of A the PDF of the Laplace and Gamma am- plitudes is much higher than the Rayleigh PDF as shown in Figure 3. Considering the Rayleigh PDF according to (18), the behavior at low values is mainly due to the linear term of A, whereas the exponential term plays a minor role at small values. Both the PDF of the Laplace amplitude and the PDF of the Gamma amplitude can be approximated by abandoning a linear term in A. Instead, A is taken to the power of a pa- rameter ν after normalization to the standard deviation of speech, that is, p(A) ∼(A/σS)ν in order to be able to approx- imate a large variety of PDFs. The smaller the parameter ν, the larger the proposed PDF at low values. The term hardly inﬂuences the behavior of the function at a high value due to the dominance of the exponential decay Histogram amplitude of complex Laplace random values Histogram amplitude of complex Gamma random values Rayleigh PDF Figure 3: Measured histograms of amplitudes of complex 1.000.000 random variables with independent Cartesian Laplace (solid) or Gamma (dashed) components along with Rayleigh PDF (dotted) (σ2 S = 1). p(A) ∼Aν σν S exp −µ A σS . 3.1. Modelling the spectral amplitudes (20) (20) The PDF of the amplitude of a complex Laplace or Gamma random variable with independent Cartesian components varies with the angle α. This makes an analytic calculation of the distribution A = S2 Re + S2 Im for (14) or (15) diﬃcult, if not impossible. After taking ∞ 0 p(A)dA = 1 into account, the approximating function with parameters ν, µ is ﬁnally obtained using [21, equation 3.381.4]: p(A) = µν+1 Γ(ν + 1) Aν σν+1 S exp −µ A σS . (21) (21) Instead of an analytic solution to (17) we are looking for a function that approximates the real PDF of the spec- tral amplitudes with high accuracy regardless of the under- lying joint distribution of real and imaginary parts of the Fourier coeﬃcients. However, as indication about how the function should look like the amplitude of a complex Laplace or Gamma PDF with independent components is taken into account. Here, Γ denotes the Gamma function. , Figure 4 shows the approximation of the measured his- togram of the amplitude of 1.000.000 complex Laplace or Gamma random values with independent components with σ2 S = 1 by (21) using diﬀerent sets of parameters ν, µ. Apparently, (21) allows a very accurate approximation for both Laplace and Gamma components. To approximate the Laplace amplitude, we applied the parameter set (ν = 1, µ = 2.5). To approximate the Gamma amplitude we used (ν = 0.01, µ = 1.5). PDFs in between both or closer to the Rayleigh PDF can be approximated with diﬀerent sets of pa- rameters ν, µ. Figure 3 plots histograms of the amplitude A = S2 Re + S2 Im of 1.000.000 Laplace and Gamma, respectively, distributed independent random values SRe, SIm of variance σ2 S/2. Whereas the Laplace-distributed random variables can easily be generated using the inverse distribution function method [19], the Gamma-distributed random values were generated according to [20]. Compared to the Rayleigh- distributed amplitude of a complex Gaussian random vari- able, low values are more likely, but the PDF decreases more slowly towards high values. 3.1.1. Matching with experimental data Figure 6a a plots the histogram of the speech ampli- tude, which is obtained by integration over the phase of the two-dimensional histogram along with the analytic Rayleigh PDF and the approximation according to (21) with the pa- rameter set for Laplace and Gamma amplitude approxima- tions, respectively. Figure 6b shows a zoom into the higher regions. Apparently, (21) provides a much better ﬁt for the speech amplitude than the Rayleigh PDF for both Laplace and Gamma amplitude approximations. For low arguments, the Rayleigh PDF rises too slowly, while for large arguments, the density function decays too fast. The real PDF of the speech amplitude lies between the Laplace and Gamma am- plitude approximations for the data measured with our sys- tem the Gamma amplitude approximation. (a) 1.5 1 0.5 0 p(A) 0 0.5 1 1.5 2 2.5 3 A To ﬁnd a set (ν, µ) that approximates the real PDF best, a distance measure between the analytic function and the his- togram with N bins is numerically minimized. The Kullback divergence [22] can be considered optimal from an informa- tion theoretical point of view. Given two random variables of probability density p1(x) and p2(x), then I(2 : 1) describes the mean information per observation of process 2 for dis- crimination in favor of process 2 and I(1 : 2) for discrimina- tion in favor of process 1: Figure 4: Approximation of amplitudes of complex random val- ues with Laplace and Gamma components using (21). (a) Laplace components: (ν = 1, µ = 2.5). (b) Gamma components: (ν = 0.01, µ = 1.5). I(1 : 2) = p1(x) log p1(x) p2(x)dx, I(2 : 1) = p2(x) log p2(x) p1(x)dx. (22) To measure the probability density function of the speech complex DFT coeﬃcients S or speech DFT amplitudes A, a histogram is built using 1-hour speech from diﬀerent speak- ers. Ideally, DFT bins, which solely contain speech of equal variance, should be taken into account. (22) In practice, the speech variance in a frequency bin is strongly time variant and can only be estimated in a time frame and frequency bin with a certain estimation error. Thus, we apply (6), which is commonly considered as the best performing method to estimate the speech variance in the form of the a priori SNR. 3.1.1. Matching with experimental data The real PDF of the speech amplitude will not be exactly like the Laplace or Gamma amplitude approximation but somewhere in between. Also, it will depend on parameters of the noise reduction system such as the analysis frame size. At a larger frame size the correlation decreases relative to the analysis frame size and thus the distribution will be less super-Gaussian. The task is therefore to ﬁnd a set of param- eters (ν, µ) which outperforms the above sets for Laplace or Gamma amplitude approximation for a given system. The fast decay of the Rayleigh PDF results from the second-order term of A in the argument of the exponential function in (18) similar to the decay of the Gauss function in (13). Similarly, the measured PDFs of the complex Laplace and Gamma amplitudes can be assumed to decay like (14) and (15) with a linear argument in the exponential function. Apparently, the slope of the Gamma amplitude PDF dif- fers from that of the Laplace amplitude PDF. Hence, a pa- Speech Estimation Using a Super-Gaussian Speech Model 1115 1 0.8 0.6 0.4 0.2 0 p(A) 0 0.5 1 1.5 2 2.5 3 A Approximation Histogram of amplitude of complex Laplace random values (a) 1.5 1 0.5 0 p(A) 0 0.5 1 1.5 2 2.5 3 A Approximation Histogram of amplitude of complex Gamma random values (b) Figure 4: Approximation of amplitudes of complex random val- ues with Laplace and Gamma components using (21). (a) Laplace components: (ν = 1, µ = 2.5). (b) Gamma components: (ν = 0.01, µ = 1.5). 1 0.8 0.6 0.4 0.2 0 p(A) 0 0.5 1 1.5 2 2.5 3 A plitudes and faster increase towards low amplitudes is vis- ible. Also, the observed data hardly shows any dependency on the phase as in the Laplace contour lines in Figure 2 as shown for the complex Laplace PDF in Figures 5b, 5c, 5d, 5e, 5e, 5f, and 5g which depict the histogram of phases for the six speciﬁc contour lines. Approximately, the phases can be considered as uniformly distributed. The variation visible for A = 0.005 is probably due to the low amount of data available here. 3.1.1. Matching with experimental data Hereby, the histogram measure- ment process also incorporates the same method of estimat- ing the time-varying speech variance as the noise reduction system. Data is collected for the histogram at time instances, when the frequency bin is dominated by speech. For that pur- pose a high and narrow a priori SNR interval is predeﬁned, for example, 19–21 dB. The width of the interval is a trade- oﬀbetween the amount of data obtained and the demand to pick samples of same variance. The sum J(1 : 2) = I(1 : 2) + I(2 : 1) is a measure of diver- gence between the two processes. To diﬀerentiate between the analytical pA(n) and the histogram PDF ph(n) with N bins, the divergence can be calculated by J(A : h) = N n=1 ph(n) −pA(n) log ph(n) pA(n) . (23) (23) Figure 7 shows the best p(A) according to (21) determined by minimizing the Kullback divergence. The analytical PDF now ﬁts even better to the observed data than the Laplace or Gamma amplitude approximation. To illustrate the improve- ment provided by the new model, Table 1 shows the Kullback divergences between measured data and model functions. The divergences have been normalized to that of the Rayleigh PDF, that is, the Gaussian model. When using the Laplace or Gamma amplitude approximation, the Kullback divergence is signiﬁcantly lower than that for the Gaussian model. By determining an optimal parameter set, the divergence fur- ther decreases. Figure 7 shows the best p(A) according to (21) determined by minimizing the Kullback divergence. The analytical PDF now ﬁts even better to the observed data than the Laplace or Gamma amplitude approximation. To illustrate the improve- ment provided by the new model, Table 1 shows the Kullback divergences between measured data and model functions. The divergences have been normalized to that of the Rayleigh PDF, that is, the Gaussian model. When using the Laplace or Gamma amplitude approximation, the Kullback divergence is signiﬁcantly lower than that for the Gaussian model. By determining an optimal parameter set, the divergence fur- ther decreases. Figure 5a shows the contour lines of the measured speech DFT coeﬃcients. The data shown has been obtained by building separate histograms for each frequency and nor- malizing each histogram to σ2 S = 1 for an averaged his- togram over the frequency. 3.1.1. Matching with experimental data Compared to the Gaussian con- tour lines in Figure 2, a slower decrease towards high am- EURASIP Journal on Applied Signal Processing 1116 3 2 1 0 −1 −2 −3 SIm −3 −2 −1 0 1 2 3 SRe 0.005 0.01 0.025 0.05 0.1 0.25 A = 0.005 0.2 0.1 0 p(α) −2 0 2 α 1 0 −1 −2 −3 SIm −3 −2 −1 0 1 2 3 SRe 0.025 0.05 0.1 0.25 (a) A = 0.005 0.2 0.1 0 p(α) −2 0 2 α (b) A = 0.01 0.2 0.1 0 p(α) −2 0 2 α (c) A = 0.025 0.2 0.1 0 p(α) −2 0 2 α (d) A = 0.05 0.2 0.1 0 p(α) −2 0 2 α (e) A = 0.1 0.2 0.1 0 p(α) −2 0 2 α (f) A = 0.25 0.2 0.1 0 p(α) −2 0 2 α (g) ontour lines of measured speech DFT coeﬃcients. ((b), (c), (d), (e), (f), (g)) Histogram of speech DFT phases fo A = 0.005 0.2 0.1 0 p(α) −2 0 2 α (b) A = 0.01 0.2 0.1 0 p(α) −2 0 2 α A = 0.025 0.2 0.1 0 p(α) −2 0 2 α 0.1 0 −2 0 2 α (c) 0.1 0 −2 0 2 α (d) A = 0.05 0.2 0.1 0 p(α) −2 0 2 α A = 0.1 0.2 0.1 0 p(α) −2 0 2 α (d) A = 0.05 0.2 0.1 0 p(α) −2 0 2 α A = 0.05 0.2 0.1 0 p(α) −2 0 2 α A = 0.1 0.2 0.1 0 p(α) −2 0 2 α A = 0.1 0.2 0.1 0 p(α) −2 0 2 α (e) (f) (e) (f) A = 0.25 0.2 0.1 0 p(α) −2 0 2 α (g) of measured speech DFT coeﬃcients. ((b), (c), (d), (e), (f), (g)) Histogram of speech DFT phases for six diﬀeren Figure 5: (a) Contour lines of measured speech DFT coeﬃcients. ((b), (c), (d), (e), (f), (g)) Histogram of speech DFT phases for six diﬀerent amplitudes. Speech Estimation Using a Super-Gaussian Speech Model 1117 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 p(A) 0 0.5 1 1.5 2 2.5 3 A Gamma ampl. approx. (ν = 0.01, µ = 1.5) Laplace ampl. approx. 3.1.1. Matching with experimental data (ν = 1, µ = 2.5) Rayleigh PDF Histogram of speech spectral amplitudes (a) 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 p(A) 1.5 2 2.5 3 A Gamma ampl. approx. (ν = 0.01, µ = 1.5) Laplace ampl. approx. (ν = 1, µ = 2.5) Rayleigh PDF Histogram of speech spectral amplitudes (b) Figure 6: (a) Histogram of speech DFT amplitudes A (σ2 S = 1) ﬁtted with Rayleigh PDF and Laplace/Gamma amplitude approximation (21). (b) Zoom into the area 1.5 ≤A ≤3. 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 p(A) 0 0.5 1 1.5 2 2.5 3 A 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 p(A) 1.5 2 2.5 3 A Gamma ampl. approx. (ν = 0.01, µ = 1.5) Laplace ampl. approx. (ν = 1, µ = 2.5) Rayleigh PDF Histogram of speech spectral amplitudes (a) (b) (a) Figure 6: (a) Histogram of speech DFT amplitudes A (σ2 S = 1) ﬁtted with Rayleigh PDF and Laplace/Gamma amplitude approximation (21). (b) Zoom into the area 1.5 ≤A ≤3. 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 p(A) 0 0.5 1 1.5 2 2.5 3 A Kullback divergence ﬁt (ν = 0.126, µ = 1.74) Histogram of speech spectral amplitudes (a) 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 p(A) 1.5 2 2.5 3 A Kullback divergence ﬁt (ν = 0.126, µ = 1.74) Histogram of speech spectral amplitudes (b) Figure 7: (a) Histogram of speech DFT amplitudes and ﬁtted approximation by (21) according to Kullback divergence (σ2 S = 1). (b) Zoom into the area 1.5 ≤A ≤3. 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 p(A) 1.5 2 2.5 3 A 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 p(A) 0 0.5 1 1.5 2 2.5 3 A Kullback divergence ﬁt (ν = 0.126, µ = 1.74) Histogram of speech spectral amplitudes Kullback divergence ﬁt (ν = 0.126, µ = 1.74) Histogram of speech spectral amplitudes (a) Kullback divergence ﬁt (ν = 0.126, µ = 1.74) g µ Histogram of speech spectral amplitudes Histogram of speech spectral amplitudes (a) (b) Figure 7: (a) Histogram of speech DFT amplitudes and ﬁtted approximation by (21) according to Kullback divergence (σ2 S = 1). (b) Zoom into the area 1.5 ≤A ≤3. 3.1.2. Reverberant signal time: T0 = 0.2 s Position source: (5 m, 2 m, 1.5 m) Position microphone: (5 m, 5 m, 1.5 m) 2 m 2 m Microphone Speech source 2 m 2 m Ly Lx Figure 8: Simulation of impulse response between speech source and microphone in a reverberant room using the image method. The intensity of the sound from an image source at the mi- crophone array is determined by a frequency-independent reﬂection coeﬃcient ζ and by the distance to the micro- phone. In our experiment, the reverberation time was set to T = 0 2 seconds which corresponds to a reﬂection 1.4 1.2 1 0.8 0.6 0.4 0.2 0 p(A) 0 0.5 1 1.5 2 2.5 3 A Kullback divergence ﬁt (ν = 0.264, µ = 1.82) Histogram of speech spectral amplitudes (a) 0.16 0.14 0.12 0.1 Table 1: Normalized Kullback divergence between measured speech PDF and diﬀerent model functions. p(A) ν, µ J(A : h)/J(A : h)Rayleigh Rayleigh (18) — 1 Laplace amplitude approximation (21) 1, 2.5 0.35 Gamma amplitude approximation (21) 0.01, 1.5 0.05 Kullback ﬁt (21) 0.126, 1.74 0.045 1: Normalized Kullback divergence between measured speech PDF and diﬀerent model functions. Table 1: Normalized Kullback divergence between p(A) Rayleigh (18) Laplace amplitude approximation (21) Gamma amplitude approximation (21) Kullback ﬁt (21) Room dimensions: Lx = Ly = 7 m Lz = 3 m Reﬂection coeﬀ.: ζ = 0.72 Reverb. time: T0 = 0.2 s Position source: (5 m, 2 m, 1.5 m) Position microphone: (5 m, 5 m, 1.5 m) 2 m 2 m Microphone Speech source 2 m 2 m Ly Lx Figure 8: Simulation of impulse response between speech source and microphone in a reverberant room using the image method. Room dimensions: Lx = Ly = 7 m Lz = 3 m Reﬂection coeﬀ.: ζ = 0.72 Reverb. 3.1.2. Reverberant signal time: T0 = 0.2 s Position source: (5 m, 2 m, 1.5 m) Position microphone: (5 m, 5 m, 1.5 m) 2 m 2 m Microphone Speech source 2 m 2 m Ly Lx 1.4 1.2 1 0.8 0.6 0.4 0.2 0 p(A) 0 0.5 1 1.5 2 2.5 3 A Kullback divergence ﬁt (ν = 0.264, µ = 1.82) Histogram of speech spectral amplitudes Kullback divergence ﬁt (ν = 0.264, µ = 1.82) Histogram of speech spectral amplitudes Kullback divergence ﬁt (ν = 0.264, µ = 1.82) Histogram of speech spectral amplitudes Figure 8: Simulation of impulse response between speech source and microphone in a reverberant room using the image method. (a) 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 p(A) 1.5 2 2.5 3 A The intensity of the sound from an image source at the mi- crophone array is determined by a frequency-independent reﬂection coeﬃcient ζ and by the distance to the micro- phone. In our experiment, the reverberation time was set to T0 = 0.2 seconds, which corresponds to a reﬂection coeﬃcient of ζ = 0.72 according to Eyring’s formula ζ = exp −13.82/ c 1 Lx + 1 Ly + 1 Lz T0 . (24) (24) The histogram of the speech amplitude was then taken as be- fore after convolving the database of speech with the impulse response delivered by the image method. Figure 9 plots the histogram along with the approxi- mation with parameters ﬁtted according to the Kullback divergence. As expected, the speech spectral amplitude is now less super-Gaussian distributed. However the opti- mal parameters with respect to the Kullback divergence (i.e., ν = 0.264, µ = 1.82) are still much closer to the val- ues originally obtained from the Kullback ﬁt than to those of the Laplace amplitude approximation or even from the Rayleigh PDF. It can be concluded that accuracy of the statis- tical model is only slightly aﬀected by reverberation. Whereas a slight performance gain can be expected when adapting the parameters of the statistical model during run-time, the gain Kullback divergence ﬁt (ν = 0.264, µ = 1.82) Histogram of speech spectral amplitudes (b) Kullback divergence ﬁt (ν = 0.264, µ = 1.82) Histogram of speech spectral amplitudes (b) Figure 9: (a) Histogram of speech amplitudes in reverberant room and ﬁtted approximation (21) according to Kullback divergence (σ2 S = 1). 3.1.2. Reverberant signal frame and thus will lead to a less super-Gaussian distribu- tion. The acoustic environment will inﬂuence the distribution of the speech spectral amplitude. Especially if the desired acous- tic source is located at larger distances from the microphone, for example, in a hearing aid application, reverberation will degrade the amount of correlation in between an analysis To examine the amount of inﬂuence of reverberation, the scenario depicted in Figure 8 is considered. The acoustical impulse response in a reverberant room from a source to a microphone was simulated with the image method [23], which models the reﬂecting walls by several image sources. EURASIP Journal on Applied Signal Processing asured speech PDF and diﬀerent model functions. ν, µ J(A : h)/J(A : h)Rayleigh — 1 1, 2.5 0.35 0.01, 1.5 0.05 0.126, 1.74 0.045 1.4 1.2 1 0.8 0.6 0.4 0.2 0 p(A) 0 0.5 1 1.5 2 2.5 3 A Kullback divergence ﬁt (ν = 0.264, µ = 1.82) Histogram of speech spectral amplitudes (a) 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 p(A) 1.5 2 2.5 3 A Kullback divergence ﬁt (ν = 0.264, µ = 1.82) Histogram of speech spectral amplitudes (b) Figure 9: (a) Histogram of speech amplitudes in reverberant room and ﬁtted approximation (21) according to Kullback divergence (σ2 S = 1). (b) Zoom into the area 1.5 ≤A ≤3. might not justify the additional computational complexity of 1118 EURASIP Journal on Applied Signal Processing 1118 EURASIP Journal on Applied Signal Processing Table 1: Normalized Kullback divergence between measured speech PDF and diﬀerent model functions. p(A) ν, µ J(A : h)/J(A : h)Rayleigh Rayleigh (18) — 1 Laplace amplitude approximation (21) 1, 2.5 0.35 Gamma amplitude approximation (21) 0.01, 1.5 0.05 Kullback ﬁt (21) 0.126, 1.74 0.045 Room dimensions: Lx = Ly = 7 m Lz = 3 m Reﬂection coeﬀ.: ζ = 0.72 Reverb. time: T0 = 0.2 s Position source: (5 m, 2 m, 1.5 m) Position microphone: (5 m, 5 m, 1.5 m) 2 m 2 m Microphone Speech source 2 m 2 m Ly Lx Figure 8: Simulation of impulse response between speech source and microphone in a reverberant room using the image method. The intensity of the sound from an image source at the mi- crophone array is determined by a frequency-independent reﬂection coeﬃcient ζ and by the distance to the micro- phone. 3.1.2. Reverberant signal In our experiment, the reverberation time was set to T0 = 0.2 seconds, which corresponds to a reﬂection coeﬃcient of ζ = 0.72 according to Eyring’s formula ζ = exp −13.82/ c 1 Lx + 1 Ly + 1 Lz T0 . (24) The histogram of the speech amplitude was then taken as be- fore after convolving the database of speech with the impulse response delivered by the image method. Figure 9 plots the histogram along with the approxi- mation with parameters ﬁtted according to the Kullback divergence. As expected, the speech spectral amplitude is now less super-Gaussian distributed. However the opti- mal parameters with respect to the Kullback divergence (i.e., ν = 0.264, µ = 1.82) are still much closer to the val- ues originally obtained from the Kullback ﬁt than to those of the Laplace amplitude approximation or even from the Rayleigh PDF. It can be concluded that accuracy of the statis- tical model is only slightly aﬀected by reverberation. Whereas li ht f i b t d h d ti th 1.4 1.2 1 0.8 0.6 0.4 0.2 0 p(A) 0 0.5 1 1.5 2 2.5 3 A Kullback divergence ﬁt (ν = 0.264, µ = 1.82) Histogram of speech spectral amplitudes (a) 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 p(A) 1.5 2 2.5 3 A Kullback divergence ﬁt (ν = 0.264, µ = 1.82) Histogram of speech spectral amplitudes (b) Figure 9: (a) Histogram of speech amplitudes in reverberant room and ﬁtted approximation (21) according to Kullback divergence (σ2 S = 1). (b) Zoom into the area 1.5 ≤A ≤3. might not justify the additional computational complexity of ti l iﬁ Th i th f ll i th ﬁ d Table 1: Normalized Kullback divergence between measured speech PDF and diﬀerent model functions. p(A) ν, µ J(A : h)/J(A : h)Rayleigh Rayleigh (18) — 1 Laplace amplitude approximation (21) 1, 2.5 0.35 Gamma amplitude approximation (21) 0.01, 1.5 0.05 Kullback ﬁt (21) 0.126, 1.74 0.045 Room dimensions: Lx = Ly = 7 m Lz = 3 m Reﬂection coeﬀ.: ζ = 0.72 Reverb. 3.1.2. Reverberant signal (b) Zoom into the area 1.5 ≤A ≤3. might not justify the additional computational complexity of an acoustic classiﬁer. Thus, in the following the ﬁxed param- eter set (ν = 0.126, µ = 1.74) is considered as optimal. Speech Estimation Using a Super-Gaussian Speech Model 1119 1 0.5 0 p(B) 0 0.5 1 1.5 2 2.5 3 B Rayleigh PDF Laplace amp. aprox. Histogram (a) 1 0.5 0 p(B) 0 0.5 1 1.5 2 2.5 3 B Rayleigh PDF Laplace amp. aprox. Histogram (b) 1 0.5 0 p(B) 0 0.5 1 1.5 2 2.5 3 B Rayleigh PDF Laplace amp. aprox. Histogram (c) Figure 10: Histogram of noise DFT amplitudes B for (a) white uniform distributed noise, (b) fan noise, and (c) cafeteria noise (σ2 N = 1) ﬁtted with Rayleigh PDF and Laplace amplitude approximation. 1 0.5 0 p(B) 0 0.5 1 1.5 2 2.5 3 B Rayleigh PDF Laplace amp. aprox. Histogram (a) 1 0.5 0 p(B) 0 0.5 1 1.5 2 2.5 3 B Rayleigh PDF Laplace amp. aprox. Histogram (b) 1 0.5 0 p(B) 0 0.5 1 1.5 2 2.5 3 B 1 0.5 0 p(B) 0 0.5 1 1.5 2 2.5 3 B 1 0.5 0 p(B) 0 0.5 1 1.5 2 2.5 3 B Rayleigh PDF Laplace amp. aprox. Histogram (a) (b) 1 0.5 0 p(B) 0 0.5 1 1.5 2 2.5 3 B (c) Figure 10: Histogram of noise DFT amplitudes B for (a) white uniform distributed noise, (b) fan noise, and (c) cafeteria noise (σ2 N = 1) ﬁtted with Rayleigh PDF and Laplace amplitude approximation. 3.1.3. Spectral amplitude of noise The deviation for the measured histogram from the Rayleigh model is low compared to that of speech. In the follow- ing, the Gaussian assumption for the noise will therefore be kept. Compared to speech, the span of noise correlation in an anal- ysis frame is much lower. Thus, the PDF of the real and imaginary parts of the noise spectral coeﬃcients will ac- cording to the central limit theorem be closer to a Gaus- sian function. Martin [5, 6] has proposed spectral estima- tors with Laplace or Gaussian noise model (and Laplace and Gamma models for the speech coeﬃcients). A Laplace model for noise is motivated by the observation that environmental noises are also super-Gaussian distributed to a certain degree. Figure 10 plots histograms of DFT amplitudes measured for three diﬀerent noise classes. For building the histograms, the frequency- and time-dependent noise variances σ2 N were es- timated using the same system as applied in the noise re- duction algorithm, that is, minimum statistics [2]. Spectral amplitudes with corresponding estimated noise variances in- side a narrow predeﬁned interval were then collected for the histogram database. To plot the histogram together with the Rayleigh function (18) and the super-Gaussian model func- tion (21) in Figure 10 the collected database was normalized to σ2 N = 1. 4.1. MAP spectral amplitude estimator After multiplication with A, one reasonable solution ˆA = GR to the quadratic equation is found, because the second solu- tion delivers spectral amplitudes A < 0 at least for ν > 0.5. The second derivative at ˆA is negative, thus a local maximum is guaranteed: After multiplication with A, one reasonable solution ˆA = GR to the quadratic equation is found, because the second solu- tion delivers spectral amplitudes A < 0 at least for ν > 0.5. The second derivative at ˆA is negative, thus a local maximum is guaranteed: A computationally eﬃcient MAP solution following ˆA = argmax A p(A\|R) = argmax A p(R\|A)p(A) p(R) (29) (29) G = u + u2 + ν −1/2 2γ , u = 1 2 − µ 4 γξ . (33) similar to [26], where Gaussian-distributed SRe, SIm are as- sumed, can be found. Now, the super-Gaussian function (21) is used to model the PDF of the speech spectral amplitude p(A). The Gaussian assumption of noise allows to apply (12) for p(R\|A). We need to maximize only p(R\|A) · p(A), since p(R) is independent of A. A closed form solution can be found if the modiﬁed Bessel function I0 is considered asymp- totically with (33) Whereas the MAP spectral amplitude estimator is very useful for an estimation with an underlying Laplace model of the DFT coeﬃcients, it cannot be applied using a Gamma model or the optimal parameter set. This is due to the inac- curacy introduced by the approximation of the Bessel func- tion (30). For ν < 0.5, the approximated a posteriori density p(A\|R) has a pole at A = 0, which will misplace the maxi- mum found by (33). I0(x) ≈ 1 √2πxex. (30) (30) Figure 12 shows the dependency of the weights on the a posteriori SNR γ for two a priori SNRs ξ for the param- eter set (ν, µ), that approximates the amplitude of a com- plex Laplace PDF. Most of the time, the weights of the super- Gaussian estimator are smaller than those of the Ephraim- Malah algorithm due to the larger value of p(A) at low am- plitudes compared to the Rayleigh PDF. At high a posteri- ori SNRs the Ephraim-Malah weights converge towards the Wiener weights, that is, ξ/(1 + ξ). 4. SPEECH ESTIMATORS The task of the speech estimator lies in calculating an esti- mate for the speech spectral amplitude ˆA = G · R given the observed noisy coeﬃcient Y or the noisy amplitude R and the variances of speech σ2 S and noise σ2 N. With probability one, the estimate will not be identical to the real value, there- fore a cost function C(A, ˆA) is introduced [24], which assigns a value to each combination of undisturbed and estimated speech spectral amplitudes. The Bayesian estimators aim at minimizing the expectation of the cost according to E C A, ˆA = ∞ −∞ ∞ 0 C A, ˆA p(A, Y)dAdY. (25) (25) For C(A, ˆA) = (A −ˆA)2 the Ephraim-Malah or conditional expectation estimator [3] is obtained: For the white noise, which was uniformly distributed in the time domain, a Rayleigh function perfectly models the PDF of the noise spectral amplitude. This is because there is no correlation in a time frame, resulting in Gaussian- distributed real and imaginary parts of Fourier coeﬃcients according to the central limit theorem. For fan noise, the PDF slightly changes towards the Laplace amplitude approxima- tion, while the eﬀect is more visible for the cafeteria noise, which contains speech components from many speakers. G = √v γ · Γ(1.5)F1(−0.5, 1, −v), v = γ ξ 1 + ξ , (26) (26) where the conﬂuent hypergeometric series F1 can be calcu- lated with F1(−0.5, 1, −v) = e−v/2 (1 + v)I0 v 2 + vI1 v 2 , (27) (27) EURASIP Journal on Applied Signal Processing 1120 102 101 100 0 1 2 3 4 5 6 X f (x) 102 101 100 0 1 2 3 4 5 6 X f (x) Bessel function Approximation Figure 11: Modiﬁed Bessel function of zeroth-order f (x) = I0(x) and approximation (30), f (x) = (1/ √2πx)ex. where I0, I1 denote the modiﬁed Bessel function of zeroth and ﬁrst order. The cost function C(A, ˆA) = log A −log ˆA leads to the logarithmic Ephraim-Malah estimator [4]. Al- ternatively the β-order MMSE estimator [25] allows an esti- mation in between both rules. By choosing a uniform cost function according to C =    0, S −ˆS < ϵ, 1, else. (28) (28) MAP estimators can be obtained, which are in general com- putationally more eﬃcient. 4. SPEECH ESTIMATORS Wolfe and Godsill [8, 26] introduced alternatives to the Ephraim-Malah spectral amplitude estimator based on the maximum a posteriori estimation rule. The spectral weights obtained by the MAP estimators are similar to those of the Ephraim and Malah estimator, thus a quality improvement cannot be expected. However, straightforward implementa- tions without the use of computational expensive Bessel or exponential function are possible. obtained by the MAP estimators are similar to those of the Ephraim and Malah estimator, thus a quality improvement cannot be expected. However, straightforward implementa- tions without the use of computational expensive Bessel or exponential function are possible. Figure 11: Modiﬁed Bessel function of zeroth-order f (x) = I0(x) and approximation (30), f (x) = (1/ √2πx)ex. In the following, we introduce two speech spectral am- plitude estimators, which keep the computational simplicity of the Wolfe and Godsill estimators but also achieve a quality gain by applying the super-Gaussian speech model according to (21) and a Gaussian model for noise. Instead of diﬀerentiating p(R\|A)p(A), the maximization can be performed better after applying the natural logarithm, because the product of the polynomial and exponential con- verts into a sum: First, a MAP estimator for the speech spectral amplitude is derived. Secondly, a joint MAP estimator for the amplitude and phase is introduced. Both estimators are extensions of the MAP estimators proposed by [8]. d log p(R\|A)p(A) dA = ν−1 2 1 A −2A σ2 N −µ σS + 2R σ2 N !=0. (32) (32) 4.1. MAP spectral amplitude estimator The weights of the super- Gaussian MAP estimator however increase due to the slower Figure 11 shows that the approximation is reasonable for larger arguments and becomes erroneous for low arguments. After insertion of (30) and (21) in (12) we get p(R\|A)p(A) ∼Aν−1/2 exp −A2 σ2 N −A µ σS −2R σ2 N . (31) Note that the approximation of the Bessel function has intro- duced a negative exponent for ν > 0.5. Speech Estimation Using a Super-Gaussian Speech Model 1121 phase p(A, α) is now required. For a rotational invariant PDF, 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 Weight G −15 −10 −5 0 5 10 15 γ = R2/σ2 N (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) ξ = 5 dB ξ = −5 dB Figure 12: Weights of the super-Gaussian MAP estimator with Laplace amplitude approximation (ν = 1, µ = 2.5) compared to the Ephraim-Malah weighting rule depending on the a posteriori SNR γ for two a priori SNRs ξ = −5dB and ξ = 5dB. p(A, α) = 1 2π p(A). (35) (35) Formulas (34) can be solved similar to the MAP estimator. Again, the natural logarithm greatly facilitates the optimiza- tion process. After insertion of (11) and (21) we get log p(Y\|A,α)p(A, α) = log µν+1 2π2σ2 Nσν+1 S Γ(ν + 1) − Y −Aejα2 σ2 N +ν logA−µ A σS . (36) (36) The partial derivatives of log(p(Y\|A,α)p(A, α)) with respect to the phase α and amplitude A need to be zero. Diﬀerentiat- ing with respect to α yields δ δα log p(Y\|A, α)p(A,α) =− Y ∗−Ae−jα −jAejα+ Y −AejαjAe−jα σ2 N . (37) Figure 12: Weights of the super-Gaussian MAP estimator with Laplace amplitude approximation (ν = 1, µ = 2.5) compared to the Ephraim-Malah weighting rule depending on the a posteriori SNR γ for two a priori SNRs ξ = −5dB and ξ = 5dB. (37) Setting to zero and substituting Y = Rejϑ yields Setting to zero and substituting Y = Rejϑ yields ˆα = ϑ. (38) decay of the model function towards larger values. Higher observed spectral amplitudes R will result in a higher spec- tral output compared to the Wiener ﬁlter or Ephraim-Malah estimator. 4.1. MAP spectral amplitude estimator This eﬀect is due to the underlying more accu- rate statistical model of the spectral amplitude of speech, in which high amplitudes are considered more likely than in the Rayleigh model. Consequently, high observed noisy ampli- tude will be judged to contain more speech components by the super-Gaussian MAP estimator. (38) The candidate for the joint MAP phase estimate is simply the noisy phase. Diﬀerentiating with respect to the speech am- plitude gives The candidate for the joint MAP phase estimate is simply the noisy phase. Diﬀerentiating with respect to the speech am- plitude gives δ δA log p(Y\|A, α)p(A, α) = Y ∗−Ae−jαejα + Y −Aejαe−jα σ2 N + ν A −µ σS . (39) (39) 4.2. Joint MAP amplitude and phase estimator To overcome the inability of the proposed MAP estimator with approximation of the Bessel function to cope with an underlying Gamma model or the model that minimizes the Kullback divergence towards the measured data, we intro- duce a joint MAP estimator of the amplitude and phase. Instead of maximizing the a posteriori probability p(A\|R), we now jointly maximize the probability of amplitude and phase conditioned on the observed complex coeﬃcient, that is, p(A, α\|Y): Setting to zero and replacing α = ϑ, the following quadratic equation is obtained: A2 + A µσ2 N 2σS −R −ν 2σ2 N != 0. (40) (40) Instead of maximizing the a posteriori probability p(A\|R), we now jointly maximize the probability of amplitude and phase conditioned on the observed complex coeﬃcient, that is, p(A, α\|Y): Solving the equation leads to an estimation rule similar to that of the super-Gaussian MAP estimator: G = u + u2 + ν 2γ, u = 1 2 − µ 4 γξ . (41) ˆA = argmax A p(A, α\|Y) = argmax A p(Y\|A, α)p(A, α) p(Y) , ˆα = arg max α p(A, α\|Y) = arg max α p(Y\|A, α)p(A, α) p(Y) . (34) (41) (34) Again, checking the second derivatives guarantees that the extremum found by (41) is a local maximum. Figures 13 and 14 plot the weights of the joint MAP estimator in de- pendence on the a posteriori SNR for two diﬀerent a priori SNRs and diﬀerent set of parameters (ν, µ), that is, Laplace and Gamma amplitude approximations as well as Kullback divergence matching. If the problem is formulated this way, the Bessel function and its erroneous approximation are avoided. p(Y\|A, α) is given by (11) using the Gaussian assumption of noise. Up to now we have only dealt with the probability of the speech ampli- tude, that is, p(A), while the joint PDF of the amplitude and If the problem is formulated this way, the Bessel function and its erroneous approximation are avoided. p(Y\|A, α) is given by (11) using the Gaussian assumption of noise. 4.2. Joint MAP amplitude and phase estimator (ν = 0.01, µ = 1.5) Figure 14: Weights of the joint MAP estimator as a function of the a posteriori SNR γ with diﬀerent parameter sets, that is, Laplace and Gamma amplitude approximations as well as Kullback divergence matching, compared to the MAP estimator with Laplace approxi- mation model for ξ = 5dB. Figure 14: Weights of the joint MAP estimator as a function of the a posteriori SNR γ with diﬀerent parameter sets, that is, Laplace and Gamma amplitude approximations as well as Kullback divergence matching, compared to the MAP estimator with Laplace approxi- mation model for ξ = 5dB. Figure 13: Weights of the joint MAP estimator as a function of the a posteriori SNR γ with diﬀerent parameter sets, that is, Laplace and Gamma amplitude approximations as well as Kullback divergence matching, compared to the MAP estimator with Laplace approxi- mation model for ξ = −5dB. Figure 13: Weights of the joint MAP estimator as a function of the a posteriori SNR γ with diﬀerent parameter sets, that is, Laplace and Gamma amplitude approximations as well as Kullback divergence matching, compared to the MAP estimator with Laplace approxi- mation model for ξ = −5dB. For comparison the weights of the MAP estimator with Laplace amplitude approximation are also plotted. The weights of the joint MAP estimator with Laplace approxi- mation model are always higher than that of the MAP am- plitude estimator. Using the Gamma amplitude approxima- tion or the Kullback ﬁt, the weighting rule delivers signif- icantly lower values at low observed SNRs. Moreover, the weights rise faster towards higher a posteriori SNRs com- pared to the Laplace estimation. This behavior is directly due to the diﬀerent underlying statistical models of the speech amplitude by using diﬀerent parameters (ν, µ) in (21). Low observed a posteriori SNRs compared to the ratio of vari- ances in the form of the a priori SNR will highlight the ef- fect of the statistical model at low values of A, while the be- havior at high a posteriori SNRs will be inﬂuenced by the values of the PDF towards high speech spectral amplitudes. Since the Gamma amplitude approximation model assumes the highest values of the speech spectral amplitude PDF at low amplitudes and also shows the slowest decay towards high amplitude, its resulting weight rule deviates most from the Ephraim-Malah rule both at low and high a posteriori SNRs. 4.2. Joint MAP amplitude and phase estimator sors OFTEN realized by dedicated memory tables and other more exotic functions, which are hardly considered for real- time implementations. Among the estimators that apply a Gaussian model of speech and noise, the Wiener ﬁlter requires by far the fewest computations. The Ephraim-Malah spectral amplitude esti- mator needs to evaluate a square root, an exponential func- tion, and also two Bessel functions. The MAP estimators de- rived by Wolfe can be realized at signiﬁcantly less computa- tions. Considering the spectral estimators with super-Gaussian speech model, Martin’s Laplace-Gauss estimator requires some divisions and a special function to be evaluated four times, especially because the estimation rule has to be exe- cuted independently for both real and imaginary parts. The proposed super-Gaussian estimators consume one square root operation more than the eﬃcient Wolfe estimator. In a real-time implementation, the special functions for the Ephraim-Malah or Martin estimator will be realized as lookup tables. Such a table can be spared when using the pro- posed estimators. 4.2. Joint MAP amplitude and phase estimator Up to now we have only dealt with the probability of the speech ampli- tude, that is, p(A), while the joint PDF of the amplitude and EURASIP Journal on Applied Signal Processing 1122 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Weight G −15 −10 −5 0 5 10 15 γ = R2/σ2 N (dB) MAP, Laplace approx. (ν = 1, µ = 2.5) Joint MAP, Laplace approx. (ν = 1, µ = 2.5) Joint MAP, Kullback ﬁt (ν = 0.126, µ = 1.74) Joint MAP, Gamma approx. (ν = 0.01, µ = 1.5) Figure 13: Weights of the joint MAP estimator as a function of the a posteriori SNR γ with diﬀerent parameter sets, that is, Laplace and Gamma amplitude approximations as well as Kullback divergence matching, compared to the MAP estimator with Laplace approxi- mation model for ξ = −5dB. 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 Weight G −15 −10 −5 0 5 10 15 γ = R2/σ2 N (dB) MAP, Laplace approx. (ν = 1, µ = 2.5) Joint MAP, Laplace approx. (ν = 1,µ = 2.5) Joint MAP, Kullback ﬁt (ν = 0.126, µ = 1.74) Joint MAP, Gamma approx. (ν = 0.01, µ = 1.5) Figure 14: Weights of the joint MAP estimator as a function of the a posteriori SNR γ with diﬀerent parameter sets, that is, Laplace and Gamma amplitude approximations as well as Kullback divergence matching, compared to the MAP estimator with Laplace approxi- mation model for ξ = 5dB. 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 Weight G −15 −10 −5 0 5 10 15 2 2 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Weight G −15 −10 −5 0 5 10 15 R2/ 2 (dB) MAP, Laplace approx. (ν = 1, µ = 2.5) Joint MAP, Laplace approx. (ν = 1,µ = 2.5) Joint MAP, Kullback ﬁt (ν = 0.126, µ = 1.74) Joint MAP, Gamma approx. (ν = 0.01, µ = 1.5) MAP, Laplace approx. (ν = 1, µ = 2.5) Joint MAP, Laplace approx. (ν = 1,µ = 2.5) Joint MAP, Kullback ﬁt (ν = 0.126, µ = 1.74) Joint MAP, Gamma approx. Speech Estimation Using a Super-Gaussian Speech Model Using the master-slave system depicted in Figure 15 the speech quality is tracked using the segmental signal-to-noise ratio, that is, Fixed ﬁlter segmental speech SNR/dB Noise reduction = 1 P P p=1  10·log10   I i=1 s2(i+pI) I i=1 s(i+pI)−˜s(i + pI) 2    . (42) (42) Filter coeﬃcients Here M is the length of the signal, I denotes the length of the segment and P the number of segments, such that P ·I = M. On the other hand, the noise reduction amount is measured in terms of segmental noise power attenuation as Fixed ﬁlter Figure 15: Instrumental performance evaluation of the noise re- duction system. segmental noise reduction/dB = 1 P P p=1  10 · log10   I i=1 n2(i + pI) I i=1 ˜n2(i + pI)    . (43) (43) The Ephraim-Malah MMSE estimator was taken as a reference, because it is considered as the best-performing speech spectral amplitude estimator. The MAP estimator de- rived by Wolfe results in approximately the same spectral weight, which can be calculated with much less computa- tions. A detailed discussion about the diﬀerence in spectral weights and performance between the MAP estimators and the Ephraim-Malah rule can be found in [8]. The behav- ior of the proposed super-Gaussian MAP estimators with respect to the Ephraim-Malah reference is similar to the performance gain obtained by Martin’s complex spectrum estimators [5, 6] with Laplace and Gamma speech model with respect to the Wiener reference. Some additional per- formance gain can be expected when the parameters of the super-Gaussian model function are optimally adjusted to the real distribution. Also , the resulting estimation rule is much more simple for the proposed super-Gaussian spectral am- plitude estimators. Compared to approaches that model the DFT coeﬃcient vector with Gaussian mixture models [27], the proposed estimators require less training in advance. To highlight the noise reduction during speech we only take segments p with global speech activity into account. The global activity is detected in advance by applying a VAD on the clean speech signal. The parameters (ν, µ) determine the underlying statistical model of the speech amplitude. For the super-Gaussian MAP estimator we favor (ν = 1, µ = 2.5), which approximate the amplitude of a complex RV with independent Laplace components. Comparison of computational burden While in informal listening tests, the super-Gaussian estima- tors seem to deliver a higher noise reduction at a similar speech quality compared to the Ephraim-Malah estimator, we also evaluate the performance by instrumental measure- ments. Table 2 lists the computational burden of the proposed esti- mators compared to other existing rules in the form of basic operations, and the evaluation of functions. A diﬀerentiation has been made between common functions like square root or exponential function, which are in digital signal proces- Speech Estimation Using a Super-Gaussian Speech Model Speech Estimation Using a Super-Gaussian Speech Model 1123 Table 2: Computations required for diﬀeren Estimation rule Add Multiply Divid Wiener rule 1 — 1 Ephraim-Malah MMSE 3 8 2 Martin Laplace-Gauss 10 4 7 Wolfe MAP 4 3 2 Super-Gaussian MAP 3–4 3 2 Speech quality s(l) Fixed ﬁlter ˜s(l) Filter coeﬃcients y(l) Noise reduction ˆs(l) Filter coeﬃcients Noise reduction n(l) Fixed ﬁlter ˜n(l) Figure 15: Instrumental performance evaluation of the noise re- duction system. Table 2: Computations required for diﬀerent estimation rules (for each frequency bin). Estimation rule Add Multiply Divide Function Specia Wiener rule 1 — 1 — Ephraim-Malah MMSE 3 8 2 Sqrt. (1x), exp (1x) Besse Martin Laplace-Gauss 10 4 7 Sqrt. (2x) Scaled com Wolfe MAP 4 3 2 Sqrt. (1x) Super-Gaussian MAP 3–4 3 2 Sqrt. (2x) Speech quality s(l) Fixed ﬁlter ˜s(l) Filter coeﬃcients y(l) Noise reduction ˆs(l) Filter coeﬃcients Noise reduction n(l) Fixed ﬁlter ˜n(l) Figure 15: Instrumental performance evaluation of the noise re- duction system. Hence, the system enables separate tracking o and noise reduction amount by comparing o of the ﬁxed ﬁlters. Using the master-slave sys Figure 15 the speech quality is tracked usin signal-to-noise ratio, that is, segmental speech SNR/dB = 1 P P p=1  10·log10   I i=1 s2(i+pI) I i=1 s(i+pI)−˜s(i + Here M is the length of the signal, I denotes t segment and P the number of segments, such On the other hand, the noise reduction amo in terms of segmental noise power attenuatio segmental noise reduction/dB   Table 2: Computations required for diﬀerent estimation rules (for each frequency bin). Estimation rule Add Multiply Divide Function Special functions Wiener rule 1 — 1 — — Ephraim-Malah MMSE 3 8 2 Sqrt. (1x), exp (1x) Bessel-fct. (2x) Martin Laplace-Gauss 10 4 7 Sqrt. (2x) Scaled compl. error-fct. (4x) Wolfe MAP 4 3 2 Sqrt. (1x) — Super-Gaussian MAP 3–4 3 2 Sqrt. (2x) — Table 2: Computations required for diﬀerent estimation rules (for each frequency bin). Speech quality s(l) Fixed ﬁlter ˜s(l) Filter coeﬃcients y(l) Noise reduction ˆs(l) Filter coeﬃcients Noise reduction n(l) Fixed ﬁlter ˜n(l) Figure 15: Instrumental performance evaluation of the noise re- duction system. Hence, the system enables separate tracking of speech quality and noise reduction amount by comparing outputs to inputs of the ﬁxed ﬁlters. Speech Estimation Using a Super-Gaussian Speech Model If the parame- ters are adjusted for Gamma-distributed components or in order to minimize the Kullback divergence, the enhanced sig- nal is greatly disturbed. This is due to the approximation of the Bessel function, which generates an uncompensated pole at A = 0 for ν < 0.5. In general, the proposed super-Gaussian MAP estimator cannot be applied for ν < 0.5. The super-Gaussian joint MAP estimator however can be applied to every reasonable set of parameters (ν, µ). Here, we favor the parameters that were determined by minimizing the Kullback divergence towards the measured data, that is, (ν = 0.126, µ = 1.74). The noise reduction ﬁlter was applied to a speech signal with additive noise at diﬀerent SNRs. To measure the qual- ity of the ﬁlter, the system described in [28, 29] depicted in Figure 15 was applied to judge the performance of a noise reduction algorithm. The desired signal s and the interfer- ing undesired signal n are superposed with a given SNR. The noisy signal y(l) is processed with the noise reduction al- gorithm. Afterwards the desired and the interfering signal are separately processed with the resulting ﬁlter coeﬃcients. The amount of noise reduction using (33) with (ν = 1, µ = 2.5) or (41) with (ν = 0.126, µ = 1.74) is signiﬁ- cantly higher than that for the Ephraim-Malah algorithm. The more super-Gaussian the statistical model for the speech spectral amplitude, the higher the noise reduction. Conse- quently, a lower speech quality will be reached. Comparing speech quality and noise reduction of the super-Gaussian EURASIP Journal on Applied Signal Processing 1124 20 15 10 Segmental speech SNR/dB 0 5 10 15 SNR (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) Super-Gaussian joint MAP (ν = 0.126, µ = 1.74) (a) 12 10 8 6 4 Segmental noise reduction/dB 0 5 10 15 SNR (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) Super-Gaussian joint MAP (ν = 0.126, µ = 1.74) (b) Figure 16: Speech quality and noise reduction amount of statistical ﬁlter with Ephraim-Malah estimator (solid), super-Gaussian MAP estimator (dashed), and super-Gaussian joint MAP estimator (dot- ted) for speech corrupted with white noise. Speech Estimation Using a Super-Gaussian Speech Model 20 15 10 Segmental speech SNR/dB 0 5 10 15 SNR (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) Super-Gaussian joint MAP (ν = 0.126, µ = 1.74) (a) 12 10 8 6 4 Segmental noise reduction/dB 0 5 10 15 SNR (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) Super-Gaussian joint MAP (ν = 0.126, µ = 1.74) (b) Figure 17: Speech quality and noise reduction amount of statistical ﬁlter with Ephraim-Malah estimator (solid), super-Gaussian MAP estimator (dashed), and super-Gaussian joint MAP estimator (dot- ted) for reverberant speech corrupted with white noise. 20 15 10 Segmental speech SNR/dB 0 5 10 15 SNR (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) Super-Gaussian joint MAP (ν = 0.126, µ = 1.74) (a) 20 15 10 Segmental speech SNR/dB 0 5 10 15 SNR (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) Super-Gaussian joint MAP (ν = 0.126, µ = 1.74) (a) 12 10 8 6 4 Segmental noise reduction/dB 0 5 10 15 SNR (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) Super-Gaussian joint MAP (ν = 0.126, µ = 1.74) (b) Figure 17: Speech quality and noise reduction amount of statistical ﬁlter with Ephraim-Malah estimator (solid), super-Gaussian MAP estimator (dashed), and super-Gaussian joint MAP estimator (dot- ted) for reverberant speech corrupted with white noise. 12 10 8 6 4 Segmental noise reduction/dB 0 5 10 15 SNR (dB) 10 (b) (b) Figure 16: Speech quality and noise reduction amount of statistical ﬁlter with Ephraim-Malah estimator (solid), super-Gaussian MAP estimator (dashed), and super-Gaussian joint MAP estimator (dot- ted) for speech corrupted with white noise. Figure 17: Speech quality and noise reduction amount of statistical ﬁlter with Ephraim-Malah estimator (solid), super-Gaussian MAP estimator (dashed), and super-Gaussian joint MAP estimator (dot- ted) for reverberant speech corrupted with white noise. estimators to the Ephraim-Malah estimator would thus be of limited value. For comparability the weights of the super- Gaussian estimators are scaled by a constant factor greater than one so that approximately the same speech quality is reached for all estimators. The amount of noise reduction achieved then allows a comparison between the estimators. In all versions we include the soft weight given by Ephraim and Malah [3] with tracking speech absence probabilities [30]. Figure 16. The super-Gaussian MAP estimator achieves a sig- niﬁcantly higher noise attenuation than the Ephraim-Malah estimator. Speech Estimation Using a Super-Gaussian Speech Model By applying the super-Gaussian joint MAP esti- mator with parameters optimally adjusted to the measured data, the noise reduction amount can be increased further without decreasing the speech quality. Generally, the single-microphone noise reduction system is comparably robust against reverberation. However, rever- beration will degrade its performance, especially because it is harder for the noise estimation algorithm to diﬀerentiate between noise and weak reverberating parts of the speech. While this will degrade the performance of all estimators, the proposed super-Gaussian estimators are also aﬀected by the change of distribution of the speech DFT coeﬃcients as shown in Figure 9. To examine the performance of the pro- posed estimators, the acoustic scenario depicted in Figure 8 was simulated using the image method. The clean speech was ﬁltered with the impulse response delivered by the image method and was processed by the noise reduction algorithm after adding white noise at diﬀerent SNRs. In the following, diﬀerent experiments are documented. First, the system is applied to the speech disturbed by white noise at diﬀerent SNRs and the performance when using the Ephraim-Malah estimator, the super-Gaussian MAP estima- tor with Laplace amplitude approximation, and the super- Gaussian joint MAP estimator with optimal parameters is compared. The experiment is then extended to reverberant speech with additive white noise. Thirdly, the experiments are conducted with fan noise and ﬁnally, the performance of the estimators is compared with the speech disturbed by cafeteria noise. Figure 17 plots the performance in terms of instrumen- tal speech quality and noise reduction. The reverberation hardly aﬀects the performance gain provided by the super- Gaussian estimators. Still a signiﬁcant advantage compared to the Ephraim-Malah estimator can be expected. Also, the 5.1. Performance in white noise ( ) 12 10 8 6 4 Segmental noise reduction/dB 0 5 10 15 SNR (dB) Segmental noise 10 10 SNR (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) Super-Gaussian joint MAP (ν = 0.126, µ = 1.74) (b) (b) (b) Figure 19: Speech quality and noise reduction amount of statistical ﬁlter with Ephraim-Malah estimator (solid), super-Gaussian MAP estimator (dashed), and super-Gaussian joint MAP estimator (dot- ted) for speech corrupted with cafeteria noise. Figure 18: Speech quality and noise reduction amount of statistical ﬁlter with Ephraim-Malah estimator (solid), super-Gaussian MAP estimator (dashed), and super-Gaussian joint MAP estimator (dot- ted) for speech corrupted with fan noise. The underlying super-Gaussian model can be adjusted to the demands of the speciﬁc noise reduction system. While the MAP estimator allows an estimation with respect to a Laplace amplitude model for the speech DFT magnitude, the joint MAP estimator also allows an optimal adjustment of the un- derlying statistical model to the real PDF of the speech spec- tral amplitude for a speciﬁc noise reduction system. The underlying super-Gaussian model can be adjusted to the demands of the speciﬁc noise reduction system. While the MAP estimator allows an estimation with respect to a Laplace amplitude model for the speech DFT magnitude, the joint MAP estimator also allows an optimal adjustment of the un- derlying statistical model to the real PDF of the speech spec- tral amplitude for a speciﬁc noise reduction system. joint MAP estimator with optimal parameters for anechoic conditions outperforms the MAP estimator with Laplace ap- proximation. This is because the anechoic approximation is still closer to the real PDF than the Laplace amplitude ap- proximation as depicted in Figure 9. 5.2. Performance in realistic noise Figure 18 plots the performance of the estimators for speech with fan noise and Figure 19 shows the performance for speech disturbed by cafeteria noise. The proposed super-Gaussian spectral amplitude estima- tors signiﬁcantly improve the quality of the enhanced signal. The performance gain comes for free, it is obtained by ap- plying a more accurate statistical model. Also, the weight- ing rules do not require the use of tables for special com- plicated functions compared to the state-of-the art speech spectral amplitude estimator derived by Ephraim-Malah or the super-Gaussian speech spectral estimators derived by Martin. The noise reduction amount is lower for white noise, be- cause the nonstationary cafeteria and fan noise are harder to track by the noise estimation algorithm. The proposed super-Gaussian estimators still outper- form the Ephraim-Malah algorithm although the perfor- mance gain is lower for the white noise. Again, the joint MAP estimator with optimal parameters performs best. [2] R. Martin, “Noise power spectral density estimation based on optimal smoothing and minimum statistics,” IEEE Trans. Speech Audio Processing, vol. 9, no. 5, pp. 504–512, 2001. 5.1. Performance in white noise The results for white noise and the three diﬀerent estima- tors, that is, Ephraim-Malah, MAP with (ν = 1, µ = 2.5), and joint MAP with (ν = 0.126, µ = 1.74) are shown in Speech Estimation Using a Super-Gaussian Speech Model 1125 20 15 10 5 Segmental speech SNR/dB 0 5 10 15 SNR (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) Super-Gaussian joint MAP (ν = 0.126, µ = 1.74) (a) 12 10 8 6 4 Segmental noise reduction/dB 0 5 10 15 SNR (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) Super-Gaussian joint MAP (ν = 0.126, µ = 1.74) (b) Figure 18: Speech quality and noise reduction amount of statistical ﬁlter with Ephraim-Malah estimator (solid), super-Gaussian MAP estimator (dashed), and super-Gaussian joint MAP estimator (dot- ted) for speech corrupted with fan noise. 25 20 15 10 5 Segmental speech SNR/dB 0 5 10 15 SNR (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) Super-Gaussian joint MAP (ν = 0.126, µ = 1.74) (a) 9 8 7 6 5 4 3 Segmental noise reduction/dB 0 5 10 15 SNR (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) Super-Gaussian joint MAP (ν = 0.126, µ = 1.74) (b) Figure 19: Speech quality and noise reduction amount of statistical ﬁlter with Ephraim-Malah estimator (solid), super-Gaussian MAP estimator (dashed), and super-Gaussian joint MAP estimator (dot- ted) for speech corrupted with cafeteria noise. 25 20 15 10 5 Segmental speech SNR/dB 0 5 10 15 SNR (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) Super-Gaussian joint MAP (ν = 0.126, µ = 1.74) (a) 25 20 15 10 5 Segmental speech SNR/dB 0 5 10 15 SNR (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) Super-Gaussian joint MAP (ν = 0.126, µ = 1.74) (a) 9 8 7 6 5 4 3 Segmental noise reduction/dB 0 5 10 15 SNR (dB) Ephraim-Malah Super-Gaussian MAP (ν = 1, µ = 2.5) Super-Gaussian joint MAP (ν = 0.126, µ = 1.74) (b) Figure 19: Speech quality and noise reduction amount of statistical ﬁlter with Ephraim-Malah estimator (solid), super-Gaussian MAP estimator (dashed), and super-Gaussian joint MAP estimator (dot- ted) for speech corrupted with cafeteria noise. 6. CONCLUSION Gannot, “Speech enhancement using a mixture-maximum model,” IEEE Trans. Speech Audio Pro- cessing, vol. 10, no. 6, pp. 341–351, 2002. [7] P. Vary, “Noise suppression by spectral magnitude estima- tion—mechanisms and theoretical limits,” Signal Processing, vol. 8, no. 4, pp. 387–400, 1985. [28] S. Gustafsson, R. Martin, and P. Vary, “On the optimiza- tion of speech enhancement systems using instrumental mea- sures,” in Proc. Workshop on Quality Assessment in Speech, Au- dio, and Image Communication, pp. 36–40, Darmstadt, Ger- many, March 1996. [8] P. J. Wolfe and S. J. Godsill, “Eﬃcient alternatives to the Ephraim and Malah suppression rule for audio signal en- hancement,” EURASIP Journal on Applied Signal Processing, vol. 2003, no. 10, pp. 1043–1051, 2003, special issue: Digital Audio for Multimedia Communications. [29] K. U. Simmer, J. Bitzer, and C. Marro, “Post-ﬁltering tech- niques,” in Microphone Arrays, M. Brandstein and D. Ward, Eds., pp. 39–60, Springer-Verlag, New York, NY, USA, 2001. [9] T. Lotter, Single and multimicrophone speech enhancement for hearing aids, Ph.D. thesis, Aachen University (RWTH), Aachen, Germany, 2004. [30] D. Malah, R. V. Cox, and A. J. Accardi, “Tracking speech-presence uncertainty to improve speech enhance- ment in non-stationary noise environments,” in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing (ICASSP ’99), vol. 2, pp. 789–792, Phoenix, Ariz, USA, March 1999. [10] J. Sohn, N. S. Kim, and W. Sung, “A statistical model-based voice activity detection,” IEEE Signal Processing Lett., vol. 6, no. 1, pp. 1–3, 1999. [11] I. Cohen and B. Berdugo, “Speech enhancement for non- stationary noise environments,” Signal Processing, vol. 81, no. 11, pp. 2403–2418, 2001, Elsevier. [12] O. Cappe, “Elimination of the musical noise phenomenon with the Ephraim and Malah noise suppressor,” IEEE Trans. Speech Audio Processing, vol. 2, no. 2, pp. 345–349, 1994. Thomas Lotter received the Dipl.-Ing. de- gree in electrical engineering in 2000 from the Aachen University of Technology, RWTH Aachen. He received the Ph.D. de- gree from the RWTH Aachen in 2004 af- ter working at the Institute of Communi- cation Systems and Data Processing in the area of single- and multimicrophone speech enhancement. In 2004, he joined Siemens Audiological Engineering Group, Erlangen, Germany with focus on wireless hearing aid applications. His main research interests include speech enhancement, signal processing for wireless systems, wireless standards, and audio coding. [13] P. Scalart and J. V. Filho, “Speech enhancement based on a pri- ori signal to noise estimation,” in Proc. 6. CONCLUSION [1] S. F. Boll, “Suppression of acoustic noise in speech using spec- tral subtraction,” IEEE Trans. Acoustics, Speech, and Signal Processing, vol. 27, no. 2, pp. 113–120, 1979. We have derived a computationally eﬃcient MAP estimator for the speech spectral amplitude and a joint MAP estima- tor for the speech spectral amplitude and phase. Both es- timators apply a Gaussian model for the noise coeﬃcients, and a super-Gaussian model for the speech DFT coeﬃcients. [2] R. Martin, “Noise power spectral density estimation based on optimal smoothing and minimum statistics,” IEEE Trans. Speech Audio Processing, vol. 9, no. 5, pp. 504–512, 2001. EURASIP Journal on Applied Signal Processing 1126 [22] S. Kullback, Information Theory and Statistics, Dover Publi- cation, New York, NY, USA, 1968. [3] Y. Ephraim and D. Malah, “Speech enhancement using a min- imum mean-square error short-time spectral amplitude esti- mator,” IEEE Trans. Acoustics, Speech, and Signal Processing, vol. 32, no. 6, pp. 1109–1121, 1984. [22] S. Kullback, Information Theory and Statistics, Dover Publi- cation, New York, NY, USA, 1968. [23] J. B. Allen and D. A. Berkley, “Image method for eﬃciently simulating small-room acoustics,” Journal Acoustical Society of America, vol. 65, no. 4, pp. 943–950, 1979. [4] Y. Ephraim and D. Malah, “Speech enhancement using a min- imum mean-square error log-spectral amplitude estimator,” IEEE Trans. Acoustics, Speech, and Signal Processing, vol. 33, no. 2, pp. 443–445, 1985. [24] J. L. Melsa and D. L. Cohn, Decision and Estimation Theory, McGraw-Hill, New York, NY, USA, 1978. [25] C. You, S. Koo, and S. Rahardja, “Adaptive β-order MMSE estimation for speech enhancement,” in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing (ICASSP ’03), vol. 1, pp. 900–903, Hong Kong, China, April 2003. [5] R. Martin, “Speech enhancement using MMSE short time spectral estimation with gamma distributed speech priors,” in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing (ICASSP ’02), vol. 1, pp. 253–256, Orlando, Fla, USA, May 2002. [26] P. J. Wolfe and S. J. Godsill, “Simple alternatives to the Ephraim and Malah suppression rule for speech enhance- ment,” in Proc. 11th IEEE Signal Processing Workshop on Statis- tical Signal Processing, pp. 496–499, Singapore, August 2001. [6] R. Martin and C. Breithaupt, “Speech enhancement in the DFT domain using Laplacian speech priors,” in Proc. Interna- tional Workshop on Acoustic Echo and Noise Control (IWAENC ’03), pp. 87–90, Kyoto, Japan, September 2003. [27] D. Burshtein and S. 6. CONCLUSION IEEE Int. Conf. Acous- tics, Speech, Signal Processing (ICASSP ’96), vol. 2, pp. 629– 632, Atlanta, Ga, USA, May 1996. [14] D. R. Brillinger, Time Series: Data Analysis and Theory, McGraw-Hill, New York, NY, USA, 1981. [15] R. J. McAulay and M. L. Malpass, “Speech enhancement using a soft-decision noise suppression ﬁlter,” IEEE Trans. Acoustics, Speech, and Signal Processing, vol. 28, no. 2, pp. 137–145, 1980. [16] H. Brehm and W. Stammler, “Description and generation of spherically invariant speech-model signals,” Signal Processing, vol. 12, no. 2, pp. 119–141, 1987, Elsevier. Peter Vary received the Dipl.-Ing. degree in electrical engineering in 1972 from the University of Darmstadt, Darmstadt, Ger- many. In 1978, he received the Ph.D. degree from the University of Erlangen-Nurem- berg, Germany. In 1980, he joined Philips Communication Industries (PKI), Nurem- berg, where he became Head of the Digi- tal Signal Processing Group. Since 1988, he has been a Professor at Aachen University of Technology, Aachen, Germany, and Head of the Institute of Com- munication Systems and Data Processing. His main research inter- ests are in speech coding, channel coding, error concealment, adap- tive ﬁltering for acoustic echo cancellation and noise reduction, and concepts of mobile radio transmission. [17] T. Lotter and P. Vary, “Noise reduction by maximum a poste- riori spectral amplitude estimation with supergaussian speech modeling,” in Proc. International Workshop on Acoustic Echo and Noise Control (IWAENC ’03), pp. 83–86, Kyoto, Japan, September 2003. [18] D. L. Wang and J. S. Lim, “The unimportance of phase in speech enhancement,” IEEE Trans. Acoustics, Speech, and Sig- nal Processing, vol. 30, no. 4, pp. 679–681, 1982. [19] A. Papoulis, Probability, Random Variables and Stochastic Pro- cesses, McGraw-Hill, New York, NY, USA, 1991. [20] N. D. Wallace, “Computer generation of gamma random vari- ates with non-integral shape parameters,” Communications of the ACM, vol. 17, no. 12, pp. 691–695, 1974. [21] I. S. Gradshteyn and I. M. Ryzhik, Table of Integrals, Series, and Products, Academic Press, San Diego, Calif, USA, 1994.
https://openalex.org/W2964645428	https://tore.tuhh.de/bitstreams/d4209393-147e-4181-a07a-ba7ca9d90b8a/download	English	null	Predicting industrial‐scale cell culture seed trains–A Bayesian framework for model fitting and parameter estimation, dealing with uncertainty in measurements and model parameters, applied to a nonlinear kinetic cell culture model, using an MCMC method	Biotechnology and bioengineering	2,019	cc-by	13,353	Received: 4 April 2019 \| Revised: 20 June 2019 \| Accepted: 19 July 2019 DOI: 10.1002/bit.27125 ved: 4 April 2019 \| Revised: 20 June 2019 \| Accepted: 19 July 2019 Revised: 20 June 2019 \| Accepted: 19 July 2019 DOI: 10.1002/bit.27125 Tanja Hernández Rodríguez1 \| Christoph Posch2 \| Julia Schmutzhard2 \| Josef Stettner2 \| Claus Weihs3 \| Ralf Pörtner4 \| Björn Frahm1 Tanja Hernández Rodríguez1 \| Christoph Posch2 \| Julia Schmutzhard2 \| Josef Stettner2 \| Claus Weihs3 \| Ralf Pörtner4 \| Björn Frahm1 1Biotechnology & Bioprocess Engineering, Ostwestfalen‐Lippe University of Applied Sciences and Arts, Lemgo, Germany 2Novartis Technical Research & Development, Sandoz GmbH, Langkampfen, Austria 3Faculty of Statistics, TU Dortmund University, Dortmund, Germany 4Institute for Bioprocess‐ and Biosystems Engineering, Hamburg University of Technology, Germany Abstract For production of biopharmaceuticals in suspension cell culture, seed trains are required to increase cell number from cell thawing up to production scale. Because cultivation conditions during the seed train have a significant impact on cell performance in production scale, seed train design, monitoring, and development of optimization strategies is important. This can be facilitated by model‐assisted prediction methods, whereby the performance depends on the prediction accuracy, which can be improved by inclusion of prior process knowledge, especially when only few high‐quality data is available, and description of inference uncertainty, providing, apart from a “best fit”‐prediction, information about the probable deviation in form of a prediction interval. This contribution illustrates the application of Bayesian parameter estimation and Bayesian updating for seed train prediction to an industrial Chinese hamster ovarian cell culture process, coppled with a mechanistic model. It is shown in which way prior knowledge as well as input uncertainty (e.g., concerning measurements) can be included and be propagated to predictive uncertainty. The impact of available information on prediction accuracy was investigated. It has been shown that through integration of new data by the Bayesian updating method, process variability (i.e., batch‐to‐batch) could be considered. The implementation was realized using a Markov chain Monte Carlo method. Correspondence Björn Frahm, Biotechnology & Bioprocess Engineering, Department of Life Science Technologies, Ostwestfalen-Lippe University of Applied Sciences and Arts, Campusallee 12, 32657 Lemgo, Germany. Email: bjoern.frahm@th-owl.de 1 \| INTRODUCTION Within a Bayesian context, this kind of knowledge is expressed by probability statements and it is combined with the available data, leading to a whole set of probable model parameter values for each model parameter. This procedure is also called Bayesian parameter estimation and the numerical implementation can be performed through a Markov chain Monte Carlo (MCMC) procedure. There are many ways of numerically implementing this method and some examples in the field of biochemical engineering can be found in Galagali and Marzouk (2015); Liu and Gunawan (2017); Vrugt (2016); and Xing, Bishop, Leister, and Li (2010). Another similar technique to simulate process dynamics under uncertainty are Gaussian processes, but they were not subject to investigation in this work. To maintain cell growth and product formation attributes within the seed train, monitoring and optimization strategies are required (Frahm, 2014). Temporal or longer lasting changes in cell behavior can occur, so that the seed train protocol has to be adapted. Also, for new cell lines or new products or the transfer of the process to another production plant, seed train protocols also have to be developed or adapted, keeping in mind the reduction of time and costs during development of those protocols. Another application is to support the selection of the optimal clone for a new process and the development of a suitable seed train protocol. Model building of dynamic bioprocesses such as cell culture seed trains faces a lot of challenges due to different factors, like limited amount of high‐quality experimental data (measurement uncertainty, offline data and large time steps between measurements, etc.), process nonlinearity and the necessity of various model parameters characteriz- ing the bioprocess. As already described in Liu and Gunawan (2017), these factors lead to significant uncertainty in the process model. Furthermore, prediction performance depends on the accuracy of the model, the variability of the biological process, and identifiability of model parameters. Nonidentifiability arises if many different combinations of model parameters can explain the experimental data equally well. The reasons could be that the model contains too many parameters (overparameterization) leading to the problem that noise or random variations in the training data is interpreted and learned as concepts. Consequently, these concepts do not apply to new data, which impede the models' ability to generalize to new data. 1 \| INTRODUCTION optimization algorithm is a “best fit” estimator, a point estimator, meaning that only one value for each model parameter is identified, leading to one predicted value of the quantity of interest at each time step. No information about the output uncertainty is given this way, and most of these types of optimization algorithms could get stuck in a local minimum. Nevertheless, these methods have turned out to be useful tools, sometimes resulting in fast solutions and they are already implemented in functions (e.g., in Matlab or R), which are easy to apply. They can be combined with statistical methods like Monte Carlo (MC) simulation, sensitivity, uncertainty, and/or identifiability analysis, in order simulate output uncertainty and to gain more information of the process (Hines, 2015; Price, Nordblad, Woodley, & Huusom, 2013; Raue et al., 2009; Sin et al., 2009). In bioprocessing, mathematical modeling, statistical data analysis, and IT‐supported tools have become important instruments within the framework of process design, optimization, and control. They are also part of the process analytical technology (PAT) regulatory initiative for building in quality to pharmaceutical manufacturing, defined by the United States Food and Drug Administration. PAT methods are playing an important role, for example, in cell culture upstream processes for the production of biopharmaceuticals (Glassey et al., 2011). While optimization of the production scale has been in the focus for a long time, it turned out, that the cost‐ and time‐intensive cell proliferation process (the so‐called seed train) also has an impact on the success rate in production (Brunner, Fricke, Kroll, & Herwig, 2017). There are various factors that influence the seed train (Le et al., 2012). Examples are selection of vessel and filling volumes of the seed train scales, differences in bioprocess engineer- ing parameters between scales, inoculation cell densities, ratio of fresh medium to passaged medium, substrate and metabolite concentrations, point in time for cell passaging and corresponding viable cell density, apparent growth rate, and viability. However, in many cases, there are only few data available for model building and parameter estimation (e.g., when planing a new production), but frequently there is some knowledge about the organism or process from literature or expert knowledge. It is desirable to quantify this information and include it in the model building process. K E Y W O R D S K E Y W O R D S Bayes, CHO cell culture, Markov chain Monte Carlo (MCMC), seed train prediction, uncertainty © 2019 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc. Biotechnology and Bioengineering. 2019;116:2944–2959. 2944 \| wileyonlinelibrary.com/journal/bit - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2019 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc. Biotechnology and Bioengineering. 2019;116:2944–2959. Biotechnology and Bioengineering. 2019;116:2944–2959. HERNÁNDEZ RODRÍGUEZ ET AL. 2945 2.3 \| Data cleansing/preparation Data cleansing and preparation was performed by handling missing data. Within the parameter estimation process initial concentration values are required for solving the ordinary differential equation system (the model), but in some cultivation datasets, there are one or two missing initial concentrations. Concerning datasets of 20 seed trains, with three bioreactor scales and six state variables each, 16% of the initial concentrations are missing in total (viable cell concentration 0%, viability 0%, glucose 0%, glutamine 23%, lactate 72%, and ammonia 0%). If initial concentrations are missing at the beginning of bioreactor scale 1, the relevant quantity is replaced by the mean of initial concentra- tion values of training datasets. This decision is based on the fact that the same cultivation conditions are intended for each cultivation. If initial concentrations of bioreactor scale 2 or 3 are missing, then they are calculated based on the concentrations at the end of the previous scales and the volumes of the previous and the current scale. TABLE 1 List of available data, some used for training, and other for testing, containing the following abbreviations: Systems (SF, shake flask; BR, bioreactor; ST, seed train), initial filling volumes (Volume) and cultivation labels (Label). 2.1 \| Investigated suspension cell culture process In this contribution, the subject of investigation is an industrial CHO cell culture process containing a seed train comprising five shake flask scales and three bioreactor scales as well as the production scale, whereby the focus lies on the the bioreactor part of the seed train, which is composed of bioreactor 1 (N‐3, 40 L), bioreactor 2 (N‐2, 320 L) and bioreactor 3 (N‐1, 2,160 L). From experimental data (offline measurements), taken once a day, time profiles for viable cell density Xv, viability Via, concentrations of glucose cGlc, glutamine cGln, lactate cLac, and ammonia cAmm have been used. In this work, data from 20 cultivations from six campaigns with cultivation times between 72 and 96 hours per scale (meaning 4–5 measurement time points per scale) were divided into 10 seed trains for training and 10 seed trains for testing, choosing randomly one or two cultivations for training and one or two for testing per campaign. Additional datasets have been generated for modeling purposes. Therefore, 12 cultivations in four flask scales (three cultivations each) having filling volumes of 40, 70, 300, and 1,500 ml were provided. They cover cultivation time spans of 264 hr (11 days) each, meaning that the stationary and death phases were also included. All datasets are labeled and listed in Table 1 to assign them correctly in this work. 2.2 \| Cultivation conditions and analytics The industrial CHO cell culture process is used to illustrate in which way inference uncertainty can be derived and with which accuracy individual seed train scales and the whole seed train can be predicted, depending on the available information. Cell cultivation was carried out using a CHO cell line for the production of a therapeutic recombinant protein (cell line and product are not further specified due to confidential reasons). Process conditions, which were the same for all investigated seed train cultivations, are listed in Table 1. Samples were taken once a day. Viable cell concentration and viability were measured using the Vi‐CELL cell viability analyzer from Beckman Coulter. Glucose, glutamine, lactate, and ammonia were determined by a Nova Bioprofile 100+ Analyzer. 1 \| INTRODUCTION Different approaches addressing this problem can be found in literature (Ashyraliyev, Fomekong‐Nanfack, Kaandorp, & Blom, 2009; Liu & Gunawan, 2017; Sin, Gernaey, & Lantz, 2009). In this work, a Bayesian approach, facing the above‐mentioned challenges in model building and parameter estimation dealing with uncertainties and eventually lack of data, is applied to seed train prediction of an industrial Chinese hamster ovarian (CHO) cell culture process. It is shown in which way sources of uncertainty as well as prior knowledge (from experts or literature) can be considered leading to predictions including inference uncertainty. Bayesian parameter estimation also provides a framework for detection of nonidentifiabi- lites but as this is not the focus of this work, we refer to Raue, Kreutz, Theis, and Timmer (2013). Numerical implementation of the Bayesian approach was carried out via an MCMC procedure using an adaptive single component metropolis algorithm. A mechanistic model, similar to Frahm (2014) and Kern, Platas‐ Barradas, Pörtner, and Frahm (2016) is applied for this approach. These types of models have gained renewed attention because they can be considered as a structured representation of the available process knowledge (Glassey et al., 2011; Kroll, Hofer, Stelzer, & Herwig, 2017; Möller & Pörtner, 2017; Sanderson, Phillips, & Barford, 1996). They have been used for development of predictive control strategies, for example, to ensure high batch‐to‐batch reproducibility in animal suspension cell cultures (Aehle et al., 2012) and for the design of cell culture fed‐batch control (Frahm et al., 2002). Often, estimation methods identifying only one set of model parameters based on the available dataset, like the Nelder–Mead simplex algorithm (Press, 1996), are applied. This type of HERNÁNDEZ RODRÍGUEZ ET AL. 2946 2.4 \| Cell culture model y g ( y , , p ) Variable/ parameter Unit Description Xt cell/L Total cell density Xv cell/L Viable cell density cGlc mmol/L Glucose concentration cGln mmol/L Glutamine concentration cLac mmol/L Lactate concentration cAmm mmol/L Ammonia concentration V L Volume max μ hr−1 Maximum cell‐specific growth rate KS,Glc mmol/L Monod kinetic constant for glucose KS,Gln mmol/L Monod kinetic constant for glutamine aLag – Correction factor for lag phase tLag hr Duration of la phase d,min μ hr−1 Minimum cell‐specific death rate d,max μ hr−1 Maximum cell‐specific death rate KLys hr−1 Cell lysis constant qGlc,max mmol·cell−1·hr−1 Maximum cell‐specific glucose uptake rate kGlc mmol/L Monod kinetic constant for glucose uptake qGln,max mmol·cell−1·hr−1 Maximum cell‐specific glutamine uptake rate kGln mmol/L Monod kinetic constant for glutamine uptake YLac Glc ∕ mmol/mmol Kinetic production constant for lactate qLac,uptake,max mmol·cell−1·hr−1 Cell‐specific maximum lactate uptake rate YAmm Gln ∕ mmol/mmol Kinetic production constant for ammonia qAmm uptake max , , mmol·cell−1·hr−1 Cell‐specific maximum ammonia uptake rate kAmm – Correction factor for ammonia uptake dX dt Xv dX dt Xv K X X dc dt X q dc dt X q dc dt X q dc dt X q v d t t v v v v v Lys Glc Glc Gln Gln Lac Lac Amm Amm μ μ μ = ⋅( − ) = ⋅ − ⋅( − ) = − ⋅ = − ⋅ = ⋅ = ⋅ dX dt Xv dX dt Xv K X X dc dt X q dc dt X q dc dt X q dc dt X q dV dt F c c K c c K t t a K K c K K c q q c c k q q c c k q Y q c c q q Y q c c K q 1 v d t t v v v v v Glc S S d d d S S S S Lys Glc Glc Gln Gln Lac Lac Amm Amm Sample max Glc ,Glc Gln Gln ,Gln Lag Lag max ,min ,max ,Glc ,Glc Glc ,Gln ,Gln Gln Glc Glc,max Glc Glc Glc Gln Gln,max Gln Gln Gln Lac Lac Glc Glc Glc Lac Lac,uptake max max Amm Amm Gln Gln Gln Amm Amm Amm,uptake,max max max μ μ μ μ μ μ μ μ μ μ μ μ μ μ μ ⎜ ⎟ = ⋅( − ) = ⋅ − ⋅( − ) = − ⋅ = − ⋅ = ⋅ = ⋅ = = ⋅( + ) ⋅( + ) ‐⎛ ⎝ − ⎞ ⎠ ⋅ ⋅ = + ⋅( + ) ⋅( + ) = ⋅( + ) = ⋅( + ) = ⋅ ⋅ − ⋅( − ) = ⋅ ⋅ − ⋅ ⋅( − ) ∕ ∕ (1) (1) The specific growth rate includes a term for lag phase description where tLag stands for the duration of the lag phase. 2.4 \| Cell culture model TABLE 2 Modeled variables and model parameters included in the underlying model (symbols, units, and descriptions) TABLE 2 Modeled variables and model parameters included in the underlying model (symbols, units, and descriptions) The applied kinetic model is based on modifications of previous model variations published in Frahm et al. (2002) and Kern et al., 2016. Differential algebraic equations (Equation 1), containing six mostly Monod‐type algebraic equations (description of growth rate, death rate, substrate uptake, and metabolite production kinetics) and 17 model parameters are describing cell culture dynamics of total and viable cell density, Xt and Xv, as well as concentrations of glucose cGlc, glutamine cGln, lactate cLac, and ammonia cAmm. All these variables and model parameters are listed in Table 2 including unit and description. Volume changes because of sampling were considered by the sampling flow rate FSample (describing the sample volume expressed as an effluent flow rate [with negative values] during the sampling period of time). The titer dynamics are not considered in this example as it was measured only in production scale, but not during the seed train. 2.3 \| Data cleansing/preparation Since process data from 6 campaigns were considered, they were labeled by C1 (campaign 1) to C6 (campaign 6) considered, they were labeled by C1 (campaign 1) to C6 (campaign 6) System Volume (L) Cultivation labels Controlled process parameters Usage Training data from development SF 0.04 SF1.1, SF1.2, SF1.3 Temperature, CO2, humidity, seeding VCD Training SF 0.07 SF2.1, SF2.2, SF2.3 Training SF 0.3 SF3.1, SF3.2, SF3.3 Training SF 1.5 SF4.1, SF4.2, SF4.3 Training Training and test data from the process (from 6 campaigns) BR 40 R1.1, … , R1.10 (10 sets) Temperature, pH, DO (disolved oxygen) total gas flow stirrer speed, seeding/ transfer VCD, pressure Training BR 40 R1.11, … , R1.20 (10 sets) Testing BR 320 R2.1, … , R2.10 (10 sets) Training BR 320 R2.11, … , R2.20 (10 sets) Testing BR 2160 R3.1, … , R3.10 (10 sets) Training BR 2160 R3.11, … , R3.20 (10 sets) Testing Cultivations ending on … belong to campaign (C.): .1, 0.2, 0.11, 0.12 (C1), 0.3, 0.4, 0.13, 0.14 (C2), 0.5, 0.6, 0.15, 0.16 (C3), 0.7, 0.8, 0.17, 0.18 (C4), 0.9, 0.19 (C5), 0.10, 0.20 (C6) Seed trains (comprising BR1 [40 L], BR2 [320 L], and BR3 [2,160 L]): ST1, ST2 (C1), ST3, ST4 (C2), ST5, ST6 (C3), ST7, ST8 (C4), ST9 (C5), ST10 (C6) Training ST11, ST12 (C1), ST13, ST14 (C2), ST15, ST16 (C3), ST17, ST18 (C4), ST19 (C5), ST20 (C6) Testing (In brackets the campaigns the seed trains belong to) HERNÁNDEZ RODRÍGUEZ ET AL. 2947 2.5 \| Bayesian parameter estimation and inference The goal of Bayesian parameter estimation is to compute a maximum a posteriori point (MAP) estimate of each unknown model parameter (e.g., maximum growth rate max μ ) as well as the corresponding probability distribution (posterior distribution), describing how probable it is that certain parameter values are adopted, based on the measured data and prior knowledge. These estimates and distributions can then be used for prediction of new observations (e.g., viable cell density Xv; Gelman et al., 2013, chap. 1). Bayesian parameter estimation and prediction can be divided into the following main tasks, which will be explained afterward: E Y Y Y E Y Var and Var . 2 α λ = ( ) ( ) = ( ) ( ) (2) (2) • Step 1: Quantification of prior knowledge including uncertainties • Step 1: Quantification of prior knowledge including uncertainties • Step 2: Bayesian parameter estimation/determination of posterior distributions More details on different types of prior distributions are given in the Supporting Information Material. • Step 3: Prediction including credible intervals • Step 4: Bayesian updating (if desired and additional data is available) 2948 2.5 \| Bayesian parameter estimation and inference measurement deviations (see Figure 1). A gamma distribution was chosen to describe the existing prior knowledge including the above‐ mentioned uncertainties. This assumption is based on the fact that the considered random variables can only adopt positive values, and, furthermore, the gamma distribution is well suited for representing the realistic range based on the available priori knowledge. It is defined by the parameters α (shape) and λ (rate). The expected value and variance are calculated by E Y Y , Var 2 α λ α λ ( ) = ( ) = . For estimat- ing expected value and variance, the two equations can be solved for α and λ (method of moments) and consequently, measures of location and variation of the distribution can be computed by 2.4 \| Cell culture model a 0, 1 Lag ∈[ ] describes by which percentage growth rate is decreased in the beginning of the lag phase and for t tLag > . The specific death rate contains constant minimum and maximum death rates as well as dependencies on glucose and glutamine concentration (similar to Frahm, 2014). Substrate uptake rates are expressed similar to substrate uptake rates presented in Frahm (2014) and Kern et al. (2016), describing a high glucose uptake at high glucose concentrations and low glucose uptake at low glucose concentrations and analogously for glutamine. Also metabolic produc- tion rates are expressed similar to substrate uptake rates presented in Frahm (2014) but with additional terms for metabolite uptake, followed by renewed production (in case of ammonia) at the end of the death phase, with by renewed production (in case of ammonia) at the end of the death phase, with c c q q q c c K c c K K k if : 0 else: constant if : 0 else if and 0.001 : 1 else: constant d Glc Lac Lac,uptake Lac,uptake Lac,uptake,max Gln Amm Amm Gln Amm Amm Amm Amm μ μ > = = ( ) ( > ) = ( ≤ ) (( − ) > ) = = − ( ) The ode23 function of MATLAB version 2017b (Matlab, 2017) was used for numerical computation. HERNÁNDEZ RODRÍGUEZ ET AL. 2.5.1 \| Quantification of prior knowledge In a second step, Bayesian parameter estimation using prior probabilities and experimental data has to be performed, obtaining posterior parameter distributions. The key element is the Bayes theorem, which is a theorem for the computation of conditional probabilities. Since in practice the applied mathematical models are complex and high dimensional, the calculation of the posteriori parameter distributions turns out to be a nontrivial tasks. But numerical solutions can be computed by application of MCMC methods. The concept of MCMC In a first step, quantification of prior knowledge including uncertain- ties through probability distributions is required. These probability distributions are called prior distributions. There are different types of prior distributions which can be chosen, according to the available prior information. In the present work, there are mainly two sources of uncertainties considered, the uncertainty in model parameters and the uncertainty in initial concentration values, resulting from FIGURE 1 Propagation of uncertainty. Uncertainty in model parameters and uncertainty resulting from measurement deviations are considered and a Bayesian approach, having the Bayes theorem as a key element, was applied to propagate these uncertainties, to estimate model parameters, and to include the information of uncertainty in the prediction of the interesting quantities in form of prediction intervals forming a prediction band [Color figure can be viewed at wileyonlinelibrary.com] 2.5.3 \| Prediction including credible intervals In a third step, predictions based on the obtained posterior parameter distributions can be performed, using MC simulations. As a result the posterior predictive distributions of the variables included in the model (or even of functions built with these variables) are obtained. In the case of a dynamic process model over time, a posterior prediction distribution is obtained for each variable at each point in time within the defined time span. Credible intervals (also called prediction intervals or prognostic intervals) of nonobserved values can be computed using the posterior predictive distributions. A credible interval can be described as a coverage interval that contains the set of true values of a quantity with a given probability, based on available information. For example, they can be computed using quantiles of the posterior predictive distributions at different points in time, leading to prediction bands over the considered time span (see Figure 1). Accuracy score 1, within band score: Percentage of subsequently added test data falling within prediction band in relation to the total number k of test data. Values between 0 and 100 can be adopted, where a high value stands for a high prediction accuracy. Within band score 1 No. of predicted values out of band k 100. = ⎛ ⎝ − ⎞ ⎠ · (4) (4) Accuracy score 2, the relative error: The relative deviation between predicted values (values with maximum posterior probability for model parameters (MAP estimate)) and subsequently added test data is described by the relative error in % with values between 0 and 100, where a low value stands for a high accuracy. 2.5.4 \| Bayesian updating k y y y Rel. error 1 100, i k i i i 1 ,exp ,pred ,exp ∑ = · ( − ) · = (5) (5) As a fourth step, (if additional data is provided), Bayesian updating can be executed, which is an important characteristic of Bayesian statistics. It is the ability to learn from new data through adding information to the present knowledge and thus, to update the current state of information. with k number of measurements. All criteria can be computed for one or more quantities. Furthermore, the coefficient of variation is used for the quantifica- tion of uncertainty. The coefficient of variation of a sample y is calculated by This is realized by repetition of Steps 2 and 3 using the current posterior distributions as new prior distributions and executing MCMC simulation to obtain new posterior parameter distributions. Simply spoken Bayesian updating is performed by “taking the posterior from today as prior from tomorrow.” This is described in literature by terms like Bayesian updating, Bayesian learning, or the sequential nature of Bayes (Luce, Anthony, & Dennis, 2003; O’Hagan, 2008). This is realized by repetition of Steps 2 and 3 using the current posterior distributions as new prior distributions and executing MCMC simulation to obtain new posterior parameter distributions. cv y y var mean 100. = ( ) ( ) · (6) (6) (6) Simply spoken Bayesian updating is performed by “taking the posterior from today as prior from tomorrow.” This is described in literature by terms like Bayesian updating, Bayesian learning, or the sequential nature of Bayes (Luce, Anthony, & Dennis, 2003; O’Hagan, 2008). FIGURE 1 Propagation of uncertainty. Uncertainty in model parameters and uncertainty resulting from measurement deviations are considered and a Bayesian approach, having the Bayes theorem as a key element, was applied to propagate these uncertainties, to estimate model parameters, and to include the information of uncertainty in the prediction of the interesting quantities in form of prediction intervals forming a prediction band [Color figure can be viewed at wileyonlinelibrary.com] HERNÁNDEZ RODRÍGUEZ ET AL. 2949 simulation is to create a random process whose stationary distribution is the specified target distribution and to run the simulation long enough that the distribution of the current draws is close enough to this stationary distribution (Gelman et al., 2013, chap. 11). Different types of algorithms realizing this principle exist, whereby the single component Metropolis‐Hastings algorithm was applied in this work (Gilks et al., 1998), which has the posterior samples of the model parameters as its output, which represent the posterior distributions of the model parameters to be estimated. The sample size should be chosen large enough so that the Markov Chain (MC) standard error is less than 5% (more details on convergence diagnostics are given in the Supporting Information Material). quantifies the amount of predictive uncertainty, based on the available information and is expressed in this work by the relative half bandwidth of the prediction interval at a specified point in time. Supposing that ypred is the posterior predictive sample and q0.975 its 97.5% quantile and q0.025 its 0.25% quantile, then: q q y Half bandwidth 1 2 100. 0.975 0.025 pred = − ¯ · (3) (3) Simply spoken, this measure describes how well the prediction can be bounded (precision) or how much deviation from the predicted value is expected, based on the available information. This score is computed before test data are used for evaluation and can adopt values between 0 and 100, where a low value is desired because it stands for a high prediction precision. The other two criteria, within band score and relative error describe how good the prediction performed, thus describing the prediction accuracy. They are measures for evaluation of the prediction after adding the test data. 3 \| RESULTS AND DISCUSSION More detailed information, such as formulas and implementation of the adaptive single based Metropolis‐Hastings algorithm, is provided as Supporting Information Material. This section shows how an industrial cell culture seed train, that is described by a mechanistic model, is predicted (simulated) using Bayesian parameter estimation. The prediction is complemented by corresponding prediction intervals describing the expected deviation from the predicted values based on the available information. Furthermore, the performance of the predictions will be analyzed concerning prediction precision and accuracy. Moreover, it is investi- gated, how taking additional data into account improves the prediction. 3.1.1 To characterize the prior distributions of model parameters, means and coefficients of variation, representing the uncertainty, were defined using information from literature (Kern et al. 2016), information from analysis of training data and information from expert knowledge (from industry concerning the investigated process and from academia relying on experiences with cultivation of similar cell lines). Training data of four flask scale cultivations, one from 40 (SF 1.1), 70 (SF 2.1), 300 (SF 3.1), and 1,500 ml (SF 4.1) (labels according to Table 1), respectively were analyzed using offline measurements of viable cell density Xv and viability as well as concentrations of glucose cGlc, glutamine cGln, lactate cLac, and ammonia cAmm. Measurements were taken once a day (except on weekends) at cultivation days 0, 1, 2, 3, 6, 7, 8, 9, 10, 11. This time period covered lag phase, exponential phase, stationary phase, and death phase. In case of viable cell density Xv, the coefficient of variation (cv) from Table 3B was composed of a cv due to uncertainty caused by practical reasons and by a Poisson distributed cv because of uncertainty in cell count data (under the assumption of independent Poisson random variables). Thus, cv cv cv total pract pois = + , where cv N pois 1 = depends on the number of cells in the sample volume (here 0.001 ml) and cvpract is computed from cv cv cv 0.047 100 1.5 pract total pois 1 1000 = − = ( − ) ⋅ = . Furthermore, the 17 model parameters were divided into model parameters with fixed values and model parameters to be estimated (“free” parameters) according to the identifiability of model para- meters based on the available data. This was carried out because in some cases the available data is not sufficient for identifying every model parameter unambiguously concerning the applied discrepancy function (which is optimized during parameter estimation). Never- theless, some parameters can be estimated combining training data and expert knowledge. Thus, considering the equation for growth rate μ both parameters describing lag phase, the correction factor aLag and the duration of lag phase tLag, were kept as fixed parameter 3.1.2 \| Prior knowledge of starting concentrations The starting concentration values (of the modeled time courses, e.g., initial viable cell density Xv,0, glucose concentration c , Glc,0 …) are also set as random variables because it is assumed that the measurement errors have a significant impact on prediction performance. The prior distributions of the measurement error were derived from trend chart data of Vi‐Cell in case of viable cell density (sample size N = 236, gathered from two instruments) and Nova BioProfile 100+ analyzers for glucose, glutamine, lactate, and ammonia concentrations (sample size N = 1,065, gathered from three instruments) using resampling techniques (bootstrapping). The corresponding means and standard deviations of coefficients of variation are listed in Table 3B. 3.1 For all quantities, which are assumed as random variables (meaning that they were considered including uncertainties), a prior probability distribution, expressing the prior knowledge about the possible model parameter values, had to be defined. In which way prior knowledge (based on literature/expert knowledge/historical or training data analysis; before parameter estimation) of model parameters as well as prior information about starting concentration values were quantified is described below. values, while max μ , KS,Glc, and KS,Gln were set as “free” parameters. Concerning death rate, the minimum death rate d,min μ were kept fix, while the maximum death rate d,max μ were kept “free”. Moreover the cell lysis constant KLys were kept fix, based on Kern et al. (2016). Concerning production and uptake of lactate and ammonia the parameters qLac uptake , and qAmm uptake , were kept fix because they describe lactate and ammonia uptake at the end of the death rate, which is not relevant during the process. Because they would increase the complexity of parameter estimation, we decided to estimate them once from training data and keep them fix later on whereas kAmm was set “free” as well as kinetic production constants YLac Glc ∕ and YAmm Gln ∕ . First, it is demonstrated in Section 3.1 how prior knowledge was quantified in form of probability distributions. Afterwards, Bayesian parameter estimation by determination of posterior distributions for the model parameters as well as a Bayesian updating step is explained and illustrated (see Section 3.2). Thereafter, the model parameter distributions were used for prediction and the prediction performance based on available information/knowledge was evaluated using test data. First, these investigation were realized for single bioreactor scales (see Section 3.3). Afterwards the whole seed train comprising the mentioned three consecutive bioreactor scales (before production) was pre- dicted based on available information. The corresponding results are presented and discussed in Section 3.4. In a next step these quantities were used to adopt a gamma distribution for each free model parameter following the methods explained in Section 2.5, meaning that the distribution were calculated according to Equation (2). This form of probability distribution was chosen because of the range of the model parameters (only positive values) and the flexibility of the gamma distribution (more information on gamma distributions can be found in the Supporting Information Material). The assumed means and coefficients of variation, expressing the amount of uncertainty, are listed in Table 3A. 2.6 \| Evaluation To evaluate the prediction performance regarding accuracy and precision, three criteria are presented in this work. The first criterion HERNÁNDEZ RODRÍGUEZ ET AL. 2950 This is not surprisingly, since a lot of information (prior knowledge from literature and experiences regarding similar cell lines as well as training data from the four shake flask cultivation scales) were already available. B) Measurement error of initial concentrations In each MCMC run, convergence diagnostic was applied using visual methods such as history plots and autocorrelation plots. Furthermore, the MC error was controlled and an MC error less than 5% was satisfied in each run, which indicates convergence. This procedure was applied during every parameter estimation (update step) via MCMC. cultivations (SF1.2, SF1.3, SF2.2, SF2.3, SF3.2, SF3.3, SF4.2, and SF4.3; labels according to Table 1), for each dataset individually. The starting parameter values were also sampled randomly from these prior distributions. TABLE 3 A) Prior knowledge of model parameters expressed by prior means and coefficients of variation (cv) in % as well as posterior knowledge expressed by posterior means (based on eight specific experiments performed for modeling; after parameter estimation) and posterior coefficients of variation (cv) in %. Prior distributions were also used for sampling starting values of model parameters. B, Prior knowledge concerning measurement errors of initial concentrations expressed by mean and standard deviation (sd) of coefficient of variation The corresponding distributions are illustrated in Figure 2, where the prior distributions “prior 1” are shown in light gray dashed lines and the posterior distributions “posterior 1” from shake flask data are shown in gray dotted lines. (The values on the y‐axis depend on the parameter values on the x‐axis and have to fulfill that the integral of a density function integrates to one.) As soon as new cultivation data are collected, a Bayesian update can be performed using the old posterior “posterior 1” as new prior “prior 2,” running a new MCMC run using the new dataset. As an example, cultivation data R1.3 from the smallest bioreactor seed train scale (40 L) was used for this update step, getting a new posterior “posterior 2” (see dark gray solid lines in Figure 2). All three mentioned distributions are shown exemplarily for nine model parameters in Figure 2. cultivations (SF1.2, SF1.3, SF2.2, SF2.3, SF3.2, SF3.3, SF4.2, and SF4.3; labels according to Table 1), for each dataset individually. The starting parameter values were also sampled randomly from these prior distributions. Every MCMC run results in posterior samples representing the posterior parameter distributions of each free model parameter and then the quantities mean, variance and coefficient of variation (cv) were computed for each posterior sample. For each of these quantities the mean was computed to derive one distribution representing all shake flask datasets. The resulting mean and cv for every free parameter are listed in Table 3A. A) Model parameters Prior Posterior Parameter Unit Mean cv (%) Mean cv (%) max μ hr−1 .028 20 .029 9 KS,Glc mmol/L .03 30 .025 32.2 KS,Gln mmol/L .03 30 .025 32.8 aLag – .01 30 – 0 tLag hr 24 30 – 0 d,min μ hr−1 .0005 – 0 d,max μ hr−1 .005 50 .003 63.9 KLys hr−1 .001 – 0 qGlc max , mmol·cell−1·hr−1 1.8 × 10−10 30 1.5 × 10−10 30.4 kGlc mmol/L 10 30 8.2 32 qGln,max mmol·cell−1·hr−1 .8 × 10−10 30 .6 × 10−10 20.7 kGln mmol/L 2.5 30 2.4 27 YLac Glc ∕ mmol/mmol .3 30 .2 28.6 qLac,uptake mmol·cell−1·hr−1 1.2 × 10−11 30 – 0 YAmm Gln ∕ mmol/mmol .7 30 .5 29.4 qAmm,uptake mmol·cell−1·hr−1 4 × 10−12 30 – 0 kAmm – .5 30 .4 32.2 B) Measurement error of initial concentrations Prior Variable Unit Mean of cv Mean of cv (%) SD of cv Xv cells/L .047 4.7 .002 cGlc mmol/L .097 9.7 .004 cGln mmol/L .084 8.4 .003 cLac mmol/L .079 7.9 .005 cAmm mmol/L .068 6.8 .004 It can be seen that the steps from prior 1 to posterior 1 and from prior 2 (= posterior 1) to posterior 2 lead to more narrow distributions →less uncertainty, more precision) in case of the maximum growth rate max μ . In case of the other parameters K K k k q q Y , , , , , , S S ,Glc ,Gln Glc Gln Glc,max Gln,max Lac , and the mean moved slightly to the left (smaller values) without significant changes in the variance. This can also be conducted from Table 3 by comparing prior and posterior coefficients of variation. For most parameters, the coefficient of variation changed only slightly except for the parameter concerning maximum cell growth, max μ , and the parameter describing the maximum uptake rate of glutamine qGln max , . It should be mentioned that stronger deviations between prior and posterior means could have been obtained if the data used for Bayesian parameter estimation would have clearly indicated this deviation. But it turned out that the information contained in the prior distributions mostly coincided with the information coming along with the additional data. 3.2 \| Bayesian parameter estimation/ determination of posterior distributions and Bayesian updating After quantification of prior knowledge, Bayesian parameter estima- tion using the MCMC method described in Section 2.5 was performed, based on the remaining eight datasets from shake flask HERNÁNDEZ RODRÍGUEZ ET AL. 2951 3.3 \| Prediction of a single seed train bioreactor scale based on available information Following the above presented procedure, a comprehensive study concerning prediction accuracy and prediction precision based on available information from cultivation training data is presented. Every MCMC run results in posterior samples representing the posterior parameter distributions of each free model parameter and then the quantities mean, variance and coefficient of variation (cv) were computed for each posterior sample. For each of these quantities the mean was computed to derive one distribution representing all shake flask datasets. The resulting mean and cv for every free parameter are listed in Table 3A. For the prediction of one cultivation scale at a time (reactor scale 1 (N‐3) = 40 L, 2 (N‐2) = 320 L, or 3 (N‐1) = 2,160 L), the initial concentrations of a scale are known and the following two sources of HERNÁNDEZ RODRÍGUEZ ET AL. 2952 952 \| HERNÁN certainty and their propagation on the predictions are considered: certainty of model parameters and uncertainty of measurements. another reactor scale training dataset from the sam considered. GURE 2 Probability distributions describing knowledge about possible values of nine selected model parameters (17 mod al, 6 fixed and 11 to be identified) before and after two updating steps. Prior 1: Based on literature, expert knowledge and p alysis, before parameter estimation. Posterior 1 (=Prior 2): Knowledge based on additional specific experiments performed for m sks, after (posterior to) parameter estimation. Posterior 2: Knowledge based on additional data from smallest bioreactor seed t 52 \| HERNÁNDEZ FIGURE 2 Probability distributions describing knowledge about possible values of nine selected model parameters (17 model parameters in total, 6 fixed and 11 to be identified) before and after two updating steps. Prior 1: Based on literature, expert knowledge and previous data analysis, before parameter estimation. Posterior 1 (=Prior 2): Knowledge based on additional specific experiments performed for modeling in shake flasks, after (posterior to) parameter estimation. Posterior 2: Knowledge based on additional data from smallest bioreactor seed train scale (40 L) uncertainty and their propagation on the predictions are considered: uncertainty of model parameters and uncertainty of measurements. another reactor scale training dataset from the same campaign was considered. presented. The labels of the cultivation data used for training and testing correspond to the labels listed in Table 1. 3.3.1 \| Example: Prediction based on shake flask data versus prediction based on shake flask data and one bioreactor scale 3.3.1 \| Example: Prediction based on shake flask data versus prediction based on shake flask data and one bioreactor scale It should be mentioned that evaluation scores, half bandwidth, within band score and rel. error, were first calculated comparing one test dataset at a time (e.g., concerning viable cell density often only four measurements were compared with the predictions at the same points in time, meaning if one measurement falls outside the prediction band, the within band score is reduced to 75%). Afterwards, the average over 10 cultivations was calculated. As an example, Figure 3 shows the predicted temporal courses (solid lines) as well as the corresponding 90% prediction bands (dashed lines) for all six observed state variables (viable and total cell concentration, Xv and Xt, concentration of glucose cGlc, glutamine cGln, lactate cLac, and ammonia cAmm,) for the smallest seed train bioreactor scale (R1.13, 40 L). The six diagrams of Figure 3 (above) show the prediction, only based on shake flask FIGURE 3 Predicted time courses of six state variables, viable and total cell concentration Xv and Xt, concentration of glucose cGlc, glutamine cGln, lactate cLac, and ammonia cAmm as well as performance measures of prediction, for the smallest seed train bioreactor scale (40 L filling volume). As measures of accuracy the within band score (percentage of test data falling within prediction band) and the rel. error (the relative deviation between predicted values and subsequently added test data) are presented. The amount of uncertainty (only presented by numbers on the right) is expressed by the relative half bandwidth, that is, half width of prediction interval of viable cell density at the last time point of each scale, describing how many deviation from the predicted value is expected. The prediction was performed given data from shake flask scales (six diagrams above) and from data of another cultivation from the same campaign in the same bioreactor scale (six diagrams below) FIGURE 3 Predicted time courses of six state variables, viable and total cell concentration Xv and Xt, concentration of glucose cGlc, glutamine cGln, lactate cLac, and ammonia cAmm as well as performance measures of prediction, for the smallest seed train bioreactor scale (40 L filling volume). As measures of accuracy the within band score (percentage of test data falling within prediction band) and the rel. error (the relative deviation between predicted values and subsequently added test data) are presented. 3.3 \| Prediction of a single seed train bioreactor scale based on available information At first, an example is presented in Subsection 3.3.1, where prediction results based on the information from shake flask data are compared with the prediction results, where also information from Thereafter, the investigation results of prediction perfor- mance for a single seed train bioreactor, depending on the available information, evaluated for 10 seed train cultivations are HERNÁNDEZ RODRÍGUEZ ET AL. HERNÁNDEZ RODRÍGUEZ ET AL. 2953 3.3.2 \| Prediction performance of a single bioreactor scale It should be noted that only one additional dataset containing five measurements per quantity were considered here. In terms of prediction accuracy both predictions are showing high scores, in both scenarios at least 90% of the test data are falling within the 90%‐prediction band and the relative deviation between predicted and experimental data is 6%. To investigate the impact of information from bioreactor scales of other seed trains, 10 seed trains ST1,…, ST10 were used as training data and seed trains ST11, … , ST20 as test data, whereby only one out of 10 seed train bioreactor scales was considered at a time (e.g., information from bioreactor R1.1 [40 L] of ST1 was used for prediction of bioreactor scale R1.11 [40 L] of ST11, then information from R2.1 [320 L] of ST1 was used for prediction of R1.11 [40 L] of ST11 etc.). This way, every combination of training and test data concerning scales was performed and investigated 10 times. The corresponding averaged results concerning precision and accuracy of prediction are shown in the columns 2–4 (BR1, BR2, and BR3) of Table 4. TABLE 4 Results of predictions of single bioreactor scales concerning precision and accuracy Training scale used for updating Predicted scale SF BR 1 BR 2 BR 3 Previous scale Half bandwidth (%) BR 1 44 26 29 29 – BR 2 35 22 23 23 21 BR 3 34 21 23 22 23 Within band score for Xv (in total; %) BR 1 92 (94) 94 (92) 78 (87) 87 (89) – BR 2 100 (92) 95 (88) 91 (90) 95 (89) 100 (90) BR 3 88 (91) 66 (79) 78 (83) 83 (85) 88 (93) Rel. error for Xv (in total; %) BR 1 15 (10) 7 (8) 14 (10) 13 (10) – BR 2 7 (9) 5 (8) 7 (8) 6 (8) 5 (8) BR 3 8 (9) 11 (10) 9 (9) 8 (9) 9 (8) Note: As a measure for precision the relative half bandwidth for viable cell density before transfer was computed (low percentage, less uncertainty and therefore high precision) and as measures of accuracy the within band score and the rel. error were computed and presented in %, both for Xv and in total, meaning averaged over all six variables (viable and total cell concentration Xv and Xt, concentration of glucose cGlc, glutamine cGln, lactate cLac, and ammonia cAmm). 3.3.2 \| Prediction performance of a single bioreactor scale scale data (SF1.1‐SF4.3). This means that the posterior 1 distributions of the model parameters (compare with Figure 2) were used for prediction. The six diagrams in Figure 3 (below) show the prediction based on the updated information, based on shake flask data and another cultivation from the same campaign in the same bioreactor scale (here R1.3, 40 L). This means that the posterior 2 distributions (compare with Figure 2) were used for prediction. In both cases the starting concentration values were varied according to the coefficients of variation, presented in Table 3. scale data (SF1.1‐SF4.3). This means that the posterior 1 distributions of the model parameters (compare with Figure 2) were used for prediction. The six diagrams in Figure 3 (below) show the prediction based on the updated information, based on shake flask data and another cultivation from the same campaign in the same bioreactor scale (here R1.3, 40 L). This means that the posterior 2 distributions (compare with Figure 2) were used for prediction. In both cases the starting concentration values were varied according to the coefficients of variation, presented in Table 3. The impact of available information on prediction performance of three single bioreactor scales (N‐3 : 40 L, N‐2 : 320 L, and N‐1 : 2,160 L) was investigated for 10 seed trains comprising these bioreactor scales. The labels used in this section are listed in Table 1. Prediction of a single bioreactor based on information from shake flask data, which was expressed by the corresponding model parameter distributions (compare with posterior 1 in Figure 2), lead to the results presented in the first column (SF) of Table 4, whereby the entries correspond to the averaged values, determined from investigation of datasets R1.11, … , R1.20 (reactor scale 1, 40 L), R2.11, … , R2.20 (reactor scale 2, 320 L) and R3.11, … , R3.20 (reactor scale 3, 2,160 L). It can be seen comparing the six diagrams above and below in Figure 3, that especially for viable cell density Xv as well as for total cell density Xt the amount of uncertainty, represented by the width of the prediction band, is reduced significantly meaning that the precision is increased. At the last point in time (hour 92 on the x‐axis) the relative half bandwidth (compare with Section 2.6) was reduced from 45% to 28% for Xv. 3.3.1 \| Example: Prediction based on shake flask data versus prediction based on shake flask data and one bioreactor scale The amount of uncertainty (only presented by numbers on the right) is expressed by the relative half bandwidth, that is, half width of prediction interval of viable cell density at the last time point of each scale, describing how many deviation from the predicted value is expected. The prediction was performed given data from shake flask scales (six diagrams above) and from data of another cultivation from the same campaign in the same bioreactor scale (six diagrams below) HERNÁNDEZ RODRÍGUEZ ET AL. 2954 3.3.2 \| Prediction performance of a single bioreactor scale The following scales were used for training: Shake flasks (SF), shake flasks and another bioreactor scale (BR 1, BR 2 or BR 3), the previous bioreactor scale of the same cultivation (Previous scale). TABLE 4 Results of predictions of single bioreactor scales concerning precision and accuracy It should be noted that no scale up parameters were considered within the underlying model, although differences in cell growth at different bioreactor scales were not excluded. In addition, process variability due to biological variability (“batch‐to‐batch variability”) was expected. But such differences or variabilities would be expressed by corresponding changes in model parameter distribu- tions (e.g., by the increase or decrease of the average maximum growth rate), as soon as respective data would be included for updating parameter distributions. These aspects will be discussed later on based on the presented findings. Several aspects concerning propagation of uncertainty as well as prediction accuracy become apparent from the results presented in Table 4. Prediction of single bioreactor scales, only based on shake flask scale data was possible showing relative errors not exceeding 15% (for Xv) and 10% (in total), concerning predictions based on the Bayes estimator (MAP estimator, see Section 2.5). At least 88% (in case of Xv) and 91% (in total) of the test data are falling within the 90% prediction band. Nevertheless, predictions include between 34% and 44% of uncertainty (represented by the relative half bandwidth). Note: As a measure for precision the relative half bandwidth for viable cell density before transfer was computed (low percentage, less uncertainty and therefore high precision) and as measures of accuracy the within band score and the rel. error were computed and presented in %, both for Xv and in total, meaning averaged over all six variables (viable and total cell concentration Xv and Xt, concentration of glucose cGlc, glutamine cGln, lactate cLac, and ammonia cAmm). The following scales were used for training: Shake flasks (SF), shake flasks and another bioreactor scale (BR 1, BR 2 or BR 3), the previous bioreactor scale of the same cultivation (Previous scale). Note: As a measure for precision the relative half bandwidth for viable cell density before transfer was computed (low percentage, less uncertainty and therefore high precision) and as measures of accuracy the within band score and the rel. 3.4.1 \| Seed train prediction based on shake flask data—Example and performance A seed train prediction, only based on small scale shake flask data and considering the above‐mentioned sources of uncertainty is illustrated as an example in Figure 4 (top left). Predictive time profiles, based on initial concentrations at reactor scale 1 and parameter distributions derived from small scale data, are illustrated as solid lines and 90% prediction bands composed of 90% prediction intervals at each considered point in time are illustrated by dashed lines. After seed train prediction (of ST13) the corresponding experimental data (test data) were considered for evaluation of the prediction concerning accuracy. It has to be mentioned that as points in time for cell passaging the experimentally realized points in time for passaging were applied, due to the comparability. In practice the point in time for cell passaging is often performed according to a specified strategy, for example, based on a minimum transfer cell density. This predictive performance has been further improved by using the information from the previous scale of the running cultivation to update the posterior distributions of model parameters one more time (see Table 4, last column). Predicting bioreactor scale 2, 100% (in case of Xv) and 90% (in total) of the test data are falling within the 90% prediction band which was reduced to 21% relative half bandwidth and the relative error states 5% (for Xv) and 8% in total. Predicting bioreactor scale 3, 88% (in case of Xv) and 93% (in total) of the test data are falling within the 90% prediction band which was reduced to 23% relative half bandwidth and the relative error states 9% (for Xv) and 8% in total. These results reveal that batch‐to‐batch variability can be considered by adaption of model parameter distributions through Bayesian updating. It hast to be mentioned that for each Bayesian update, only 4–5 measurements per quantity of a training dataset were used as additional information. It is expected that by adding more process data describing similar cell growth, the amount of predictive uncertainty decreases further. On the other hand, less measurement uncertainty would also lead to less uncertainty in the models outcome, because input uncertainty is propagated to uncertainty in the outcomes. This seed train prediction leads to high accuracy (100% of the test data fall within the prediction band and the relative deviation between experimental data and predicted values yields 11%), but a low precision (the relative half bandwidth yields 65%). 3.3.2 \| Prediction performance of a single bioreactor scale error were computed and presented in %, both for Xv and in total, meaning averaged over all six variables (viable and total cell concentration Xv and Xt, concentration of glucose cGlc, glutamine cGln, lactate cLac, and ammonia cAmm). The following scales were used for training: Shake flasks (SF), shake flasks and another bioreactor scale (BR 1, BR 2 or BR 3), the previous bioreactor scale of the same cultivation (Previous scale). The inclusion of information from one bioreactor scale of another seed train bioreactor of the same campaign led to a reduction of predictive uncertainty (=increased precision) to 22–29% relative half bandwidth. In terms of prediction accuracy, what stands out most is that predicting a bioreactor scale 1, a significantly higher accuracy was reached if another bioreactor scale 1 dataset was used for training HERNÁNDEZ RODRÍGUEZ ET AL. 2955 (see row 7 [BR 1] in Table 4). This indicates that there are sometimes small effects when cells are passaged from shaken conditions to stirred conditions (here this happens between shake flak scales and bioreactor scale 1). Prediction of a bioreactor scale 2 instead shows a high accuracy (rel. error: 5–8%, within band score 88–95%) independently of which bioreactor scale was used for training or even if information from shake flaks scales was used. Prediction of a bioreactors scale 3 turned out to perform best if another bioreactor scale 3 or even shake flask scales were used for training but also good results were reached if another bioreactor scale 2 was considered. A brief posterior analysis (after analyzing prediction performance) revealed a lower cell growth on average in reactor scale 1 compared with reactor scale 3, which was expressed by corresponding probability distributions. prediction performance is evaluated, taking further data from bioreactor scales into account. 3.4.1 \| Seed train prediction based on shake flask data—Example and performance Considering the results of the prediction of single bioreactor scales, this results for seed train prediction can be improved as described below, where information from another seed train cultivation and as soon as available information from the previous scale of the running cultivation is used for the future predictions (see Subsection 3.4.2). 3.4.2 \| Optimized seed train prediction through Bayesian updating While in the last subsection prediction performance of seed train prediction based on the information from shake flask data was presented, here it was investigated how prediction performance changes, when new data (of the current cultivation) are collected and used to update model parameter distributions. By this, prediction for seed trains composed of three large bioreactor scales was performed stepwise: 3.4 \| Prediction of seed trains 2956 IGURE 4 Prediction of an exemplary seed train, that is, three consecutive bioreactor scales of 40, 320, and 2,160 L for the six state ariables, viable and total cell concentration Xv and Xt, concentration of glucose cGlc, glutamine cGln, lactate cLac, and ammonia cAmm, for fo cenarios: Only based on initial concentrations at reactor scale 1 (40 L) and posterior parameter distributions from shake flask scales (top lef ased on initial concentrations at reactor scale 1 and posterior parameter distributions from another seed train (top right); based on initia oncentrations at reactor scale 2 or 3 and including parameter distributions from the previous reactor scale (bottom left, bottom right) \| FIGURE 4 Prediction of an exemplary seed train, that is, three consecutive bioreactor scales of 40, 320, and 2,160 L for the six state variables, viable and total cell concentration Xv and Xt, concentration of glucose cGlc, glutamine cGln, lactate cLac, and ammonia cAmm, for four scenarios: Only based on initial concentrations at reactor scale 1 (40 L) and posterior parameter distributions from shake flask scales (top left); based on initial concentrations at reactor scale 1 and posterior parameter distributions from another seed train (top right); based on initial concentrations at reactor scale 2 or 3 and including parameter distributions from the previous reactor scale (bottom left, bottom right) The optimized prediction of an exemplary seed train is also illustrated in Figure 4. Time profiles for all six state variables, viable and total cell concentration, Xv and Xt, concentration of glucose cGlc, glutamine cGln, lactate cLac, and ammonia cAmm, were predicted at the beginning of the seed train (top right), after collecting data from scale 1 (bottom left), and after collecting data from scale 2 (bottom right). Here again, predictive time profiles are shown by solid lines, and 90% prediction bands are illustrated by dashed lines. The corresponding precision and accuracy values are shown in Table 5, row 3 (ST13). bands (in the Figure, the “past” is shown in light gray, the “future” in the dark gray). Also notable is the fact that the high accuracy (within band score 96% in total [i.e., concerning all six variables] and 92% for Xv [i.e., concerning only viable cell density]) and rel. 3.4 \| Prediction of seed trains In the previous sections it has been shown how single bioreactors could be predicted and how these predictions could be updated integrating information from additional data via Bayesian updating. Now, the complete bioreactor part of the seed train, comprising three consecutive bioreactor scales (40, 320, and 2,160 L) before the production bioreactor, is predicted. It should be noted, that in addition to the already considered sources of uncertainty (in model parameters and initial concentrations) uncertainty in the passaging process, which can be caused by different reasons like unknown volume when flushing the sampling valve or deviation of actual substrate concentration in the medium from the intended value (e.g., in case of glutamine in media), must be considered for the prediction of more than one seed train scale. This uncertainty was estimated evaluating the passaging processes of four seed trains (used as training data). In a first step, an exemplary seed train prediction, only based on small shake flask scale data will be illustrated. Afterwards, I) Time profiles for reactor scale 1 (40 L), 2 (320 L), and 3 (2,160 L) were predicted based on the initial concentrations of reactor scale 1 and parameter distributions of a training dataset (data from reactor scales 1, 2, and 3 of another seed train of the same campaign). II) After running reactor scale 1, time profiles for reactor scale 2 and 3 were updated using the initial concentrations of reactor scale 2 and updated posterior parameter distributions using information from the previous (reactor) scale 1. III) After running reactor scale 2, time profiles for bioreactor scale 3 were updated, using the initial concentrations of reactor scale 3 and updated posterior distributions of the previous reactor scale 2. HERNÁNDEZ RODRÍGUEZ ET AL. 3.4 \| Prediction of seed trains I) Predictions based on initial concentrations at R1 and on posterior parameter distributions from another R1 cultivation of the same campaign. II) Prediction after running R1 and update using initial concentrations of R2 and posterior parameter distributions of R1 for prediction of R2. I) Predictions based on initial concentrations at R1 and on posterior parameter distributions from another R1 cultivation of the same campaign. II) Prediction after running R1 and update using initial concentrations of R2 and posterior parameter distributions of R1 for prediction of R2. III) Prediction after running R2 and update using initial concentrations of R3 and posterior parameter distributions from previous scales. from ST1 and so on) and updated as soon as data from one scale of the current cultivation were available. The corresponding results concerning prediction performance are presented in Table 5. Application of Bayesian updating led to significant narrowing of the prediction, meaning a reduction of uncertainty, while reaching or maintaining a high prediction accuracy. The amount of uncertainty concerning relative half bandwidth was reduced from 41% to 31% on average after a Bayesian update step using process data of the previous scale 1 for prediction of scale 2 (see last row “Mean” of Table 5). This uncertainty was further reduced to 21% on average after a Bayesian update step using process data of the previous scale 2. This improvement of precision was achieved without a loss of accuracy, because at least 90% (for Xv) and 87% (in total) of the test data were falling within the prediction band, while the rel. error has been even decreased from 13% to 8% (for Xv) and from 15% to 9% (in total) on average over 10 seed trains. performance was achieved. Considering for example seed trains ST17 and ST18, the rel. error concerning all six variables was reduced from 22% to 12% and from 20% to 10% respectively, after two updating steps. It should be noticed that in this contribution only few datasets were used for the Bayesian updating steps, because it was intended to illustrate every step and to show the corresponding changes to visualize the impact of the available information. Often, there are more datasets available in practice, which could be used for further updating steps, leading possibly to less predictive uncertainty in case of consistent cultivations. 3.4 \| Prediction of seed trains error of 10% in total and 7% for Xv, achieved for the prediction of bioreactor scale 1, 2, and 3 has been further improved by updating after cultivation of each scale. After two updating steps the within band score yielded 100% for Xv and 96% in total and the rel. error yielded 1% for Xv and 5% in total (see also Table 5, ST 3). It can be seen that the prediction uncertainty for the remaining “future” time span is reduced (from 42% to 24% half bandwidth, see Table 5, row 3) after each update step indicated by narrow prediction Following the same procedure, 10 seed trains (from six different campaigns) were predicted, each based on one seed train used as training data (e.g., ST11 was predicted based on information HERNÁNDEZ RODRÍGUEZ ET AL. 2957 TABLE 5 Prediction performance of 10 optimized seed train predictions, (three consecutive bioreactor scales of 40 [R1], 320 [R2], and 2,160 L [R3]), based on one seed train for training each TABLE 5 Prediction performance of 10 optimized seed train predictions, (three consecutive bioreactor scales of 40 [R1], 320 [R2], and 2,160 L [R3]), based on one seed train for training each Seed train Within band score (%) for Xv (in total) (high values desired) Rel. 3.4 \| Prediction of seed trains Apart from that, the knowledge about predictive uncertainty (which reflects the propagated uncertainty due to input uncertainties) is highly relevant, even though it is not as small as desired. It can help to find out where the process could fail or be improved (e.g., uncertainty would decrease if less uncertainty in measurements or variability in the passaging process could be assured). Using Bayesian parameter estimation and Bayesian updating as presented in this work it could furthermore be investigated, to which amount predictive uncer- tainty would decrease if input uncertainty would be decreased to a certain amount. Nevertheless, the results show that not all seed trains could be predicted well only based on the information (updated parameter distribution) from another randomly sampled seed train as this is the case for seed train 17 (ST17) which was predicted based on information of ST7 (see row 4, ST17, first column of within band score and first column of relative error in Table 5). This can occur due to batch‐to‐batch variability. A brief posterior analysis (after investigation of prediction performance) revealed that variabilities between the cultivations (batches [here between ST7 and ST17]) are sometimes bigger than the already mentioned variability between reactor scale 1 and the other scales (compare with Section 3.3.2). When this occurred this was taken into account by a Bayesian updating step using data from the ongoing seed train. The presented results show that this way, an improvement of prediction Note: Within band score and rel. error only for Xv and in total (viable and total cell concentration Xv, Xt, concentrati lactate cLac, and ammonia cAmm); relative half bandwidth of prediction interval at last point in time for Xv. 3.4 \| Prediction of seed trains error (%) for Xv (in total) (low values desired) Half bandwidth (%) for Xv (low values desired) I) R1‐R3 II) R2‐R3 III) R3 I) R1‐R3 II) R2‐R3 III) R3 I) R1‐R3 II) R2‐R3 III) R3 ST 11 85 (91) 100 (92) 75 (75) 15 (14) 4 (10) 10 (9) 42 31 21 ST 12 100 (87) 100 (88) 100 (83) 5 (13) 11 (15) 8 (12) 41 31 20 ST 13 92 (96) 100 (98) 100 (96) 7 (10) 8 (9) 1 (5) 42 32 24 ST 14 77 (82) 63 (79) 75 (79) 17 (18) 13 (14) 13 (10) 39 29 23 ST 15 100 (90) 100 (94) 100 (100) 8 (15) 2 (11) 3 (5) 42 31 24 ST 16 100 (94) 100 (92) 100 (95.8) 6 (10) 9 (11) 4 (7) 39 32 25 ST 17 69 (86) 75 (79) 75 (83) 33 (22) 17 (17) 17 (12) 44 31 23 ST 18 85 (78) 100 (90) 100 (83) 14 (20) 10 (14) 10 (10) 43 31 23 ST 19 100 (96) 100 (87) 100 (87) 19 (16) 9 (14) 3 (11) 40 30 20 ST 20 100 (100) 100 (94) 75 (83) 7 (10) 6 (9) 8 (8) 38 28 21 Mean 91 (90) 94 (89) 90 (87) 13 (15) 9 (12) 8 (9) 41 31 21 Note: Within band score and rel. error only for Xv and in total (viable and total cell concentration Xv, Xt, concentration of glucose cGlc, glutamine cGln, lactate cLac, and ammonia cAmm); relative half bandwidth of prediction interval at last point in time for Xv. I) Predictions based on initial concentrations at R1 and on posterior parameter distributions from another R1 cultivation of the same campaign. II) Prediction after running R1 and update using initial concentrations of R2 and posterior parameter distributions of R1 for prediction of R2. III) Prediction after running R2 and update using initial concentrations of R3 and posterior parameter distributions from previous scales. Rel. error (%) for Xv (in total) (low values desired) Half bandwidth (%) for Xv (low values desired) Note: Within band score and rel. error only for Xv and in total (viable and total cell concentration Xv, Xt, concentration of glucose cGlc, glutamine cGln, lactate cLac, and ammonia cAmm); relative half bandwidth of prediction interval at last point in time for Xv. REFERENCES α shape parameter of gamma distribution λ rate parameter of gamma distribution μ cell‐specific growth rate [hr−1] d μ cell‐specific death rate [hr−1] d,min μ minimum cell‐specific growth rate [hr−1] d,max μ maximum cell‐specific growth rate [hr−1] σ standard deviation aLag correction factor for lag phase cAmm ammonia concentration [mmol/L] cGlc glucose concentration [mmol/L] cGln glutamine concentration [mmol/L] cLac lactate concentration [mmol/L] cv coefficient of variation FGlc glucose feeding rate [L/hr] FGln glutamine feeding rate [L/hr] FSample sampling rate [L/hr] kAmm correction factor for ammonia uptake [–] kGlc monod kinetic constant for glucose uptake [mmol/L] kGln monod kinetic constant for glutamine uptake [mmol/L] KLys cell lysis constant [hr−1] KS,Glc monod kinetic constant for glucose [mmol/L] α shape parameter of gamma distribution λ rate parameter of gamma distribution μ cell‐specific growth rate [hr−1] d μ cell‐specific death rate [hr−1] d,min μ minimum cell‐specific growth rate [hr−1] d,max μ maximum cell‐specific growth rate [hr−1] σ standard deviation aLag correction factor for lag phase cAmm ammonia concentration [mmol/L] cGlc glucose concentration [mmol/L] cGln glutamine concentration [mmol/L] cLac lactate concentration [mmol/L] cv coefficient of variation FGlc glucose feeding rate [L/hr] FGln glutamine feeding rate [L/hr] FSample sampling rate [L/hr] kAmm correction factor for ammonia uptake [–] kGlc monod kinetic constant for glucose uptake [mmol/L] kGln monod kinetic constant for glutamine uptake [mmol/L] KLys cell lysis constant [hr−1] KS,Glc monod kinetic constant for glucose [mmol/L] α shape parameter of gamma distribution λ rate parameter of gamma distribution μ cell‐specific growth rate [hr−1] d μ cell‐specific death rate [hr−1] d,min μ minimum cell‐specific growth rate [hr−1] d,max μ maximum cell‐specific growth rate [hr−1] σ standard deviation aLag correction factor for lag phase cAmm ammonia concentration [mmol/L] cGlc glucose concentration [mmol/L] cGln glutamine concentration [mmol/L] cLac lactate concentration [mmol/L] cv coefficient of variation FGlc glucose feeding rate [L/hr] FGln glutamine feeding rate [L/hr] FSample sampling rate [L/hr] kAmm correction factor for ammonia uptake [–] kGlc monod kinetic constant for glucose uptake [mmol/L] kGln monod kinetic constant for glutamine uptake [mmol/L] KLys cell lysis constant [hr−1] KS,Glc monod kinetic constant for glucose [mmol/L] Aehle, M., Bork, K., Schaepe, S., Kuprijanov, A., Horstkorte, R., Simutis, R., & Lübbert, A. (2012). Increasing batch‐to‐batch reproducibility of cho‐ cell cultures usinga model predictive control approach. Cytotechnol- ogy, 64(6), 623–634. Ashyraliyev, M., Fomekong‐Nanfack, Y., Kaandorp, J. A., & Blom, J. G. (2009). Systems biology: Parameter estimation for biochemical models. KS,Gln monod kinetic constant for glutamine [mmol/L] PAT process analytical technology qAmm cell‐specific ammonia production rate [mmol·L−1·hr−1] qAmm,uptake cell‐specific ammonia uptake rate [mmol·L−1·hr−1] qLac cell‐specific lactate production rate [mmol·L−1·hr−1] qGlc cell‐specific glucose uptake rate [mmol·L−1·hr−1] qGlc,max maximum cell‐specific glucose uptake rate [mmol·L−1·hr−1] qGln cell‐specific glutamine uptake rate [mmol·L−1·hr−1] qGln,max maximum cell‐specific glutamine uptake rate [mmol·L−1·hr−1] qLac,max cell‐specific lactate production rate [mmol·L−1·hr−1] qLac,uptake cell‐specific lactate uptake rate [mmol·L−1·hr−1] t time [hr] tLag duration of lag phase [hr] Xt total cell density [cells/L] Xv viable cell density [cells/L] y concentration values in general (data) y0 initial concentration values YAmm Gln ∕ kinetic production constant (stoichiometric ratio of ammonia production and glutamine uptake) [–] YLac Glc ∕ kinetic production constant (stoichiometric ratio of lactate production and glucose uptake) [–] comprising three consecutive bioreactor scales (40, 320, and 2,160 L filling volume) under consideration of shake flask experiments under equal cultivation conditions. It has been shown that Bayesian parameter estimation, performed using MCMC simulations, in combination with a mechan- istic model, describing the time profiles of viable and total cell density as well as concentrations of glucose, glutamine, lactate, and ammonia, is a suitable statistical method for seed train prediction. It provides the capability of propagating information content (including input uncertainty) provided by prior knowledge and experimental data to prediction uncertainty, expressed by predictions intervals. This way, process relevant decisions can be made based on probabilities of certain events. It should be noted that the same mechanistic model was applied for all scales, from shake flask scales to large bioreactor scales (up to 2,160 L filling volume). It became apparent that despite batch‐to‐batch variability (e.g., due to biological variability) a high predictive accuracy can be reached, by taking data of the running seed train cultivation into account performing Bayesian updating. This approach provides various practical advantages concerning applications within the field of bioprocessing. One potential advantage is the capability of the design of robust and optimal seed train protocols, saving experimental work by using prior knowledge (which is currently subject of investigation). Besides, the transfer from one plant to a similar plant can be supported. Furthermore, prediction of running processes can be used for feed‐forward control strategies (e.g., prediction of points in time for cell passaging that can be based on viable cell density) or for the development of soft sensors (predicting variables which are difficult to measure). Tanja Hernández Rodríguez http://orcid.org/0000-0002-7667- 8390 4 \| CONCLUSION In this contribution, the application of a Bayesian approach for parameter estimation and prediction of an industrial cell culture seed train, enabling the integration of prior knowledge and the consideration of uncertainty, is presented. Subject of investigations is the bioreactor part of an industrial CHO cell culture seed train HERNÁNDEZ RODRÍGUEZ ET AL. 2958 Gilks, W. R., Richardson, S., & Spiegelhalter, D. J. (Eds.). (1998). Markov chain Monte Carlo in practice. Boca Raton, FL: Chapman & Hall/CRC. partiallyobserved dynamical models by exploiting the profile likelihood. Bioinformatics, 25(15), 1923–1929. Glassey, J., Gernaey, K. V., Clemens, C., Schulz, T. W., Oliveira, R., Striedner, G., & Mandenius, C.‐F. (2011). Process analytical technol- ogy (PAT) for biopharmaceuticals. Biotechnology Journal, 6(4), 369–377. Raue, A., Kreutz, C., Theis, F. J., & Timmer, J. (2013). Joining forces of Bayesian and frequentist methodology: A study for inference in the presence of non‐identifiability. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences, 371, 1984. Hines, K. E. (2015). A primer on Bayesian inference for biophysical systems. Biophysical Journal, 108(9), 2103–2113. Sanderson, C. S., Phillips, P. J., & Barford, J. P. (1996). Structured modelling of animal cells. Cytotechnology, 21(2), 149–153. Kern, S., Platas‐Barradas, O., Pörtner, R., & Frahm, B. (2016). Model‐based strategy for cell culture seed train layout verified atlab scale. Cytotechnology, 68(4), 1019–1032. Sin, G., Gernaey, K. V., & Lantz, A. E. (2009). Good modeling practice for pat applications: Propagation of inputuncertainty and sensitivity analysis. Biotechnology Progress, 25(4), 1043–1053. Kroll, P., Hofer, A., Stelzer, I. V., & Herwig, C. (2017). Workflow to set up substantial target‐oriented mechanistic processmodels in bioprocess engineering. Process Biochemistry, 62, 24–36. Vrugt, J. A. (2016). Markov chain Monte Carlo simulation using the DREAM software package: Theory, concepts, and MATLAB imple- mentation. Environmental Modelling & Software, 75, 273–316. Le, H., Kabbur, S., Pollastrini, L., Sun, Z., Mills, K., Johnson, K., & Hu, W.‐S. (2012). Multivariate analysis of cell culture bioprocess data‐lactate- consumption as process indicator. Journal of Biotechnology, 162(2‐3), 210–223. Xing, Z., Bishop, N., Leister, K., & Li, Z. J. (2010). Modeling kinetics of a large‐scale fed‐batch CHO cell culture by Markov chain Monte Carlo method. Biotechnology Progress, 26(1), 208–219. Liu, Y., & Gunawan, R. (2017). Bioprocess optimization under uncertainty using ensemble modeling. Journal of Biotechnology, 244, 34–44. SUPPORTING INFORMATION REFERENCES The FEBS Journal, 276(4), 886–902. Brunner, M., Fricke, J., Kroll, P., & Herwig, C. (2017). Investigation of the interactions of critical scale‐up parameters (pH, pO2 and pCO2) on CHO batch performance and critical quality attributes. Bioprocess and Biosystems Engineering, 40(2), 251–263. Frahm, B. (2014). Seed train optimization for cell culture. In Pörtner, R. (Ed.), Animal cell biotechnology (pp. 355–367). New York, NY: Humana Press. Frahm, B., Lane, P., Atzert, H., Munack, A., Hoffmann, M., Hass, V. C., & Pörtner, R. (2002). Adaptive, model‐based control by the open‐loop‐ feedback‐optimal (OLFO) controller for the effective fed‐batch cultiva- tion of hybridoma cells. Biotechnology Progress, 18(5), 1095–1103. Galagali, N., & Marzouk, Y. M. (2015). Bayesian inference of chemical kinetic models from proposed reactions. Chemical Engineering Science, 123, 170–190. Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian data analysis (3rd.). Hoboken, NJ: Chapman & Hall/CRC. HERNÁNDEZ RODRÍGUEZ ET AL. 2959 SUPPORTING INFORMATION Luce, B., Anthony, O. H., & Dennis, F. (2003). A primer on Bayesian statistics in health economics and outcomes research. Bethesda, MD: MEDTAP International, Incorporated. Additional supporting information may be found online in the Supporting Information section. Additional supporting information may be found online in the Matlab (2017). Version 9.3.0.713579 (R2017b). Natick, MA: The Math- Works, Inc. Möller, J., & Pörtner, R. (2017). Model‐based design of process strategies for cell culture bioprocesses: State of the art and new perspectives. In Gowder, S. J. T. (Ed.), New insights into cell culture technology (pp. 157–172). Rijeka, Croatia: InTech. How to cite this article: Hernández Rodríguez T, Posch C, Schmutzhard J, et al. Predicting industrial-scale cell culture seed trains–A Bayesian framework for model fitting and parameter estimation, dealing with uncertainty in measurements and model parameters, applied to a nonlinear kinetic cell culture model, using an MCMC method. Biotechnology and Bioengineering. 2019;116: 2944–2959. https://doi.org/10.1002/bit.27125 O’Hagan, A. (2008). The bayesian approach to statistics. In Rudas, T. (Ed.), Handbook of probability (pp. 85–100). Los Angeles, CA: SAGE. Press, W. H. (1996). Numerical recipes in C: The art of scientific computing (2nd.). Cambridge, UK: Cambridge University Press. Price, J., Nordblad, M., Woodley, J. M., & Huusom, J. K. (2013). Application of uncertainty and sensitivity analysis to a kineticmodel for enzymatic biodiesel production. IFAC Proceedings Volumes, 46(31), 149–156. Raue, A., Kreutz, C., Maiwald, T., Bachmann, J., Schilling, M., Klingmüller, U., & Timmer, J. (2009). Structural and practical identifiability analysis of
W4388941358.txt	https://www.frontiersin.org/articles/10.3389/fmicb.2023.1252127/pdf?isPublishedV2=False	en		Distribution, characterization, and evolution of heavy metal resistance genes and Tn7-like associated heavy metal resistance Gene Island of Burkholderia	Frontiers in microbiology	2,023	cc-by	8,381	TYPE Original Research 23 November 2023 10.3389/fmicb.2023.1252127 PUBLISHED DOI OPEN ACCESS EDITED BY Ravindra Soni, Indira Gandhi Krishi Vishva Vidyalaya, India REVIEWED BY Hiren Patel, Anand Agricultural University, India Olesya Sazonova, Institute of Biochemistry and Physiology of Microorganisms (RAS), Russia CORRESPONDENCE Dening Luo loening@foxmail.com Dairong Qiao scuqiaodr@163.com RECEIVED 04 July 2023 October 2023 PUBLISHED 23 November 2023 Distribution, characterization, and evolution of heavy metal resistance genes and Tn7-like associated heavy metal resistance Gene Island of Burkholderia Yanhong Lan 1, Meijia Liu 1, Yao Song 1, Yu Cao 1, Fosheng Li 1, Dening Luo 2 and Dairong Qiao 1* Microbiology and Metabolic Engineering Key Laboratory of Sichuan Province, Key Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, Sichuan, China, 2 Chengdu University of Information Technology, Chengdu, China 1 ACCEPTED 31 CITATION Lan Y, Liu M, Song Y, Cao Y, Li F, Luo D and Qiao D (2023) Distribution, characterization, and evolution of heavy metal resistance genes and Tn7-like associated heavy metal resistance Gene Island of Burkholderia. Front. Microbiol. 14:1252127. doi: 10.3389/fmicb.2023.1252127 COPYRIGHT © 2023 Lan, Liu, Song, Cao, Li, Luo and Qiao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Introduction: Burkholderia is a rod-shaped aerobic Gram-negative bacteria with considerable genetic and metabolic diversity, which can beused for bioremediation and production applications, and has great biotechnology potential. However, there are few studies on the heavy metal resistance of the Burkholderia genus. Methods: In this paper, the distribution, characteristics and evolution of heavy metal resistance genes in Burkholderia and the gene island of Tn7-like transposable element associated with heavy metal resistance genes in Burkholderia were studied by comparative genomic method based on the characteristics of heavy metal resistance. Results and discussion: The classification status of some species of the Burkholderia genus was improved, and it was found that Burkholderia dabaoshanensis and Burkholderia novacaledonica do not belong to the Burkholderia genus.Secondly, comparative genomics studies and pan-genome analysis found that the core genome of Burkholderia has alarger proportion of heavy metal resistance genes and a greater variety of heavy metalresistance genes than the subsidiary genome and strain specific genes. Heavy metal resistance genes are mostly distributed in the genome in the form of various gene clusters (for example, mer clusters, ars clusters, czc/cusABC clusters). At the same time, transposase, recombinase, integrase and other genes were foundupstream and downstream of heavy metal gene clusters, indicating that heavy metal resistance genes may beobtained through horizontal transfer. The analysis of natural selection pressure of heavy metal resistance genes showed that heavy metal resistance genes experienced strong purification selection under purification selection pressure in the genome. The Tn7 like transposable element of Burkholderia was associated with the heavy metal resistance gene island, and there were a large number of Tn7 transposable element insertion events in genomes. At the same time, BGI metal gene islands related to heavy metal resistance genes of Tn7 like transposable element were found, and these gene islands were only distributed in Burkholderia cepacia, Burkholderia polyvora, and Burkholderia contaminant. KEYWORDS Burkholderia, comparative genome, pan-genome, heavy metal resistance gene, Tn7-like transposon, horizontal transfer Frontiers in Microbiology 01 frontiersin.org Lan et al. 10.3389/fmicb.2023.1252127 Introduction system (resistant to divalent cadmium and zinc ions) and multiple drug resistance (β-lactam, kanamycin, erythromycin, neomycin, ofloxacin and sodium dodecyl sulfate) (Hayashi et al., 2000). DsbA, the disulfide bond catalyst of Escherichia coli, is a periplasmic protein having a thioredoxin-like Cys-30-Xaa-Xaa-Cys-33 motif. DsbB, an integral membrane protein having two pairs of essential cysteines, reoxidizes DsbA that has been reduced upon functioning. The Burkholderia genus had received widespread attention due to its pathogenicity and drug resistance, resulting in the accumulation of a large number of gene/proteome and various biochemical and physiological research results. At present, research on this genus is still focused on pathogenicity and drug resistance, while its environmental value, such as the adsorption of heavy metals (zinc, lead, manganese, chromium, etc.) in soil, is rarely studied. Moreover, the studies of this genus focused on the pathogenic gene island, and the heavy metal resistance still was not reported. Therefore, understanding the resistance of the Burkholderia genus to heavy metals and the structure and characteristics of heavy metal islands in the genome is crucial for subsequent theoretical research and environmental adaptation of the genus. With the development of industrialization and the interference of natural biogeochemical cycle, heavy metal (such as cadmium, lead, arsenic, mercury) pollution poses a serious threat to natural ecosystems and human health (Ali et al., 2013; Vignaroli et al., 2018). Unlike organic pollutants, heavy metals cannot be degraded and difficult to remove, leading to persistent environmental hazards, which can lead to microbial and plant poisoning in the environment, affecting growth and development or death, and even affecting the normal operation of ecosystems in some areas, thereby exacerbating the harm to the environment. Heavy metal tolerant bacteria can survive in the environment polluted by heavy metals, and can be isolated and selected for bioremediation of contaminated sites. Multiple microorganisms have been reported to have resistance to heavy metals. For example, the impact of plant growth promoting (PGP) bacteria on plant growth had received much attention in phytoremediation (Das et al., 2014; Hao et al., 2015; Chen et al., 2016). PGP bacteria can ingest the genus Phyllostachys and promote plant growth through various mechanisms (Yuan et al., 2018). Many PGP bacteria that are resistant to specific heavy metals such as cadmium, nickel, and arsenic promote metal absorption and transport, or improve plant growth and heavy metal tolerance (Das et al., 2014; Wang et al., 2022). Burkholderia is a ubiquitous microorganism with high resistance to heavy metals. In recent years, many new species of Burkholderia have been tested and analyzed, and it is found that some Burkholderia have high efficiency in biological pest control and bioremediation (Coenye and Vandamme, 2003; Pal et al., 2022). Burkholderia sp. J62 polluted soil absorbs lead and cadmium, while also promoting plant growth (Jiang et al., 2008). The Burkholderia sp. Z-90 fermentation broth was used for bioleaching remediation of heavy metal contaminated soil. The removal rate of zinc was 44.0%, lead 32.5%, manganese 52.2%, cadmium 37.7%, copper 24.1%, and arsenic 31.6% (Yang et al., 2016). Burkholderia sp. LD-11 can accumulate copper and lead in contaminated soil, and produce indole-3-acetic acid, 1-aminonenenebb cyclopropane 1-carboxylate deaminase and iron carrier, which can increase the dry weight of plants growing in copper or lead contaminated soil, and increase the diversity of active soil urease and rhizosphere bacteria (Huang et al., 2013). Burkholderia dabaoshanensis GIMN1.004 was a new strain isolated from Dabaoshan, China, with strong cadmium tolerance (22 mmol/L) and adsorption capacity (144.94 mg/g) (Zhu et al., 2012). Ion gallium (III) had antibacterial activity against both Gram-negative and Gram positive bacteria as well as mycobacteria (Peeters et al., 2008; Choi et al., 2014, 2019; Tyrrell et al., 2015). Some studies had shown that resistance genes in microbial bacteria can repair pollution points in urban rivers, thereby achieving a sustainable green strategy for the environment (Lechuga-Ballesteros et al., 2009; Fu et al., 2023; Li et al., 2023; Tripathi et al., 2023). The IrlR-IrlS two-component system of B. pseudoallei AJ1D8 was involved in the regulation of heavy metal resistance (Jones et al., 1997). IrlR and IrlS were homologous to two-component sensor responder proteins involved in regulating resistance to heavymetals. IrlR and IrlS may be involved in theregulation of two distinct phenotypes, invasion and heavymetal (Cd21 and Zn21) resistance. The dsbA-dsbB system of B. cepacia was involved in the production of protease and alkaline phosphatase, mobility, formation of metal efflux Frontiers in Microbiology Materials and methods Source of genome data, genome filtering, and evaluation 220 plasmid sequences and 1841 complete or draft genomes of the Burkholderia genus were obtained from the national center for biotechnology information database (NCBI),1 involving a total of 32 bacterial species (Supplementary Table S1). 162,516 protein sequences were identified by CD hit (with a cutoff value of 0.8 and a sequence identity value of 0.9) (Li and Godzik, 2006). The ORFs, protein coding genes, and non-coding RNAs of the genome were predicted using prokka (Seemann, 2014). To select representative genomes and ensure accurate subsequent analysis, genomes or proteomic integrity below 85% integrity were filtered and evaluated using BUSCO (Simao et al., 2015), The average nucleotide similarity among strains with genome numbers greater than 3 was calculated by pyani (v0.2.7) software. Phylogenetic analysis To understand the distribution of heavy metal resistance genes in Burkholderia, multiple sequence alignments of all selected 16S rDNA sequences were performed using the ClustalW method with default parameters. The neighbor-joining (NJ) method was used to construct phylogenetic trees of 16S rDNA sequences using the MEGA software (v7.0.26, with the following parameters: Poisson correction, pairwise deletion and a bootstrap test of 1,000 replicates) (Kumar et al., 2018). Some genomes do not contained 16S rDNA sequences, the Neighbor Joining method of CVTree3 (Zuo and Hao, 2015) was used to construct a phylogenetic tree based on the entire genome (Set the K value to 5, 6, and 7). After 1 https://www.ncbi.nlm.nih.gov/ 02 frontiersin.org Lan et al. 10.3389/fmicb.2023.1252127 Prediction of selection pressure analyzing pan-genome, the MLST method (Multi Locus Sequence Typing) of BPGA was used to obtain a phylogenetic tree based on the core genome, and the final results were visualized using iTOL online tools (Letunic and Bork, 2016). The ratio of nucleotide non synonymous substitution (dN) and synonymous substitution (dS) of each heavy metal lineal homeotic gene was estimated to evaluate the strength of natural selection of heavy metal resistance genes in the evolution of Burkholderia. Muscle (v3.8.1551) (Edgar, 2004) was used for various heavy metal resistant protein alignments, converting the aligned protein sequences into corresponding nucleotide alignments using pal2nal (v14) (Suyama et al., 2006), with an output format of paml. Finally, the codeml program of the paml (v4.9) (Yang, 2007) software toolkit was use to calculate the dN and dS values, and select the branch model (with the main parameters set to CodonFreq = 2, model = 2, NSsites = 0) to calculate the Ka, Ks, and ω value. The non synonymous substitution rate (dN)/ synonymous substitution rate (dS) ratios were counted using DnaSP.2 It was generally believed that positive selection results in dN/dS > 1, while negative (purified) selection results in dN/dS < 1. Genomic identification of toxic heavy metal resistance The filtered 1831 genomes were compared using BLASTP to the BacMet database, and genes related to heavy metal resistance in the genome of Burkholderia were identified. The BacMet dataset used for analysis was the experimentally confirmed gene set for metal resistance function (BacMet Experimental Database) (e < 1e-6, sequence similarity ≥40%, sequence coverage ≥55%, alignment amino acid length ≥ 80). Multiple sequence alignments of the nucleic acid sequence of heavy metal resistance genes were performed using the ClustalW method with default parameters. The phylogenetic trees were constructed using the MEGA software (Kumar et al., 2018). Identification and insertion location of Tn7 like transposable element Pan-genome analysis and speculation of Burkholderia model The structural domains of various proteomes in the Burkholderia genus were annotated by interprescan (Jones et al., 2014). Candidate proteins were obtained (TnsA (PF08722, PF08721), TnsB (PF00665, PF09299), TnsC (PF13401), TnsD (PF15978), TniQ (PF06527)). The nucleic acid sequences containing TnsA, TnsB, TnsC, and TnsD (TniQ) were directly identified as 5 – bp target site repeats based on the left and right terminal characteristics of Tn7, the 8 – bp terminal sequence ended of 5 ‘- TGT-3’/3 ‘- ACA-5’, and a 22 bp TnsB binding sequence (Gary et al., 1996; Choi et al., 2014; Kaczmarska et al., 2022). There were three TnsB binding sequences spaced at the left end, with a length of ~150 bp, and four overlapping TnsB binding sequences at the right end, with a length of ~90 bp. To determine the location of Tn7 like transposable element structure inserted into the genome and the source of the inserted sequence, the complete Tn7-like and its upstream and downstream 5 kb sequences were online compared to NCBI blastn to find the location of the structure on other genomes or plasmids. Localize blastn alignment after localization to generate alignment file (output format outfmt 6), the GenBank file of Tn7-like transposable element was visualized using BacAnt (Hua et al., 2021). The bacterial pan-genome analysis (BPGA) process was used to identify the orthologous genome of the genome of Burkholderia experimental data and to infer the pan-genome model of Burkholderia. In this study, the pan-genome and core genome size of Burkholderia were inferred by the intrinsic function of BPGA. The calculation formula of BPGA’s intrinsic function is as follows: N pan = ∑ n f i =1 pan (Gi ) N core = ∑ n f i =1 core (Gi ) Gi represents the ith gene family, n was the total number of different gene family obtained from the entire dataset and the pan/ core genome size, and (Npan/Core) represents the size of the pan/core genome after the n th genome was added from the dataset. The power law regression model of pan-genome data and the exponential curve fitting model of core genome data were as follows: Ypan = A pan .x Bpan Identification of gene islands and functional annotation analysis of heavy metal resistance gene islands associated with Tn7 like transposable element + C pan The gene islands of the genome were predicted by IslandViewer (Bertelli et al., 2017). The analysis of codon preference using R3.8 package took the following steps: using a self-made Perl script to slide window scan (5 Kb size, 2.5 Kb step size), and calculate codon usage frequencies of genes in each window. Subsequently, principal component analysis was performed on this matrix in R and plotted Ycore = Acore .x Bcore + Ccore Apan, Bpan, Cpan, and Acore, Bcore, Ccore were fitting parameters. Ypan and Ycore were used to calculate the size of pan-genome and core genome size, respectively. If Bpan < 0, it means that pan-genome was closed. With the increase of additional genomes, the size of pan-genome reached a constant value. Frontiers in Microbiology 2 www.ub.edu/dnasp 03 frontiersin.org Lan et al. 10.3389/fmicb.2023.1252127 using the scores of the first two components. The KEGG pathway analysis of Tn7-like transposable element associated heavy metal resistance of gene-island was conducted with BlastKOALA, and the protein was KO annotated. GO functional enrichment analysis was visualized using WEGO 2.0 (Ye et al., 2018). 12.6, 11.4, and 4.3% of the genes in the core genome, accessory genome, and endemic genome were involved in heavy metal resistance and transformation, respectively (Figure 3A). The heavy metal annotation results of the core genome, accessory genome, and endemic genome showed that the heavy metal resistance genes in the core genome, accessory genome, and endemic genome account for 5.2, 1.3, and 0.8% of the BacMet database, respectively (Figures 3B,C). The surface core genome had more genes involved in heavy metal resistance than the affiliated and endemic genomes, and had more types of heavy metal resistance genes. A phylogenetic tree was constructed using the core genome of 60 genomes. Compared to the previous whole genome phylogenetic tree results, the phylogenetic tree constructed based on core genes of 60 genomes was highly reliable (Figure 4). According to the core genome evolution results, Burkholderia first appeared 0.1162 million years ago (MYA, Million Years Ago) and differentiated into several species at nearly 0 ~ 0.05 MYA, indicating that the genus has been actively evolving in recent years. The power regression equation deduced by BPGA shows that Bpan = 0.503865, which belongs to the range of 0 < Bpan < 1, indicating that pan-genome is open. As the number of genomes increases, the extrapolation curve of the core genome followed a steep slope. As the number of genomes gradually was 60, the number of core genes tends to be relatively constant (Figure 3A). Results Distribution and characteristics of heavy metal resistance genes in Burkholderia genus A total of 220 plasmid sequences and 1841 complete or draft genomes of the Burkholderia genus were obtained from the NCBI database, containing a total of 32 bacterial species (Supplementary Table S2). After evaluating the integrity of the genome and proteome by BUSCO, 1831 genomes were obtained by filtering out incomplete genomes (integrity <85%). The genomic characteristics (GC-content, Genome size, genome integrity and protein integrity) of 1831 genomes were analyzed (Supplementary Figure S1). After average nucleotide similarity identification, 62 genomes of 32 species were used for pan-genome analysis (Supplementary Table S3). Previous reports have indicated that the percentage threshold for species boundaries is 95% ANI, and the similarity in ANI between 62 strains ranges from 84 to 99%. The average nucleotide similarity of B. dabaoshanensis and B. novacaledonica was lowest compared to other strains (approximately 84%, Figures 1A,B). The average nucleotide similarity between Paraburkholderia and Burkholderia is about 85%. Meanwhile, using the whole genome to construct a phylogenetic tree (Figure 1C), the results showed that B. dabaoshanensis, B. novacaledonica, and P. phenoliruptrix converged into one branch, and the 16 s rDNA phylogenetic tree results showed that B. dabaoshanensis and B. novacaledonica is individually aggregated into one branch (Supplementary Figure S2). Those results indicated that B. dabaoshanensis and B. novacaledonica do not belong to the Burkholderia genus, and these two strains were excluded in subsequent analysis. Distribution and evolution of heavy metal resistance genes in Burkholderia genus Heavy metal genes are distributed in most strains, and they are clustered and divided into multiple subgroups. The mercury genes were divided into merA, merR, merG, merRTP, merRTPCAB, merDAFPTR, etc. subgroups, with some strains including two or more mer cluster subgroups (Figure 5; Supplementary Table S4). The arsA and arsD of arsenic and arsenate resistance genes were only identified in some genomes of vietnamiensis (B. cenocepacia, B. cepacian, B. contaminans, B. gladioli, B. glumae, B. ubonensis, B. vietnamiensis) (Figure 6; Supplementary Table S5). Aio (A/B) and arr (A/B) were involved in arsenous acid oxidation and arsenate respiration reduction, and aio (A/B) was only identified in B. centocepacia, B. cepacian, B. multivorans, B. pseudomallei, B. ubonensis, B. vietnamiensis, while arr (A/B) was not identified in the Burkholderia genus. The distribution of cadmium, zinc, cobalt, and copper resistance genes in the Burkholderia genus was shown in Figure 7 and Supplementary Table S6. The czc/cusABC gene cluster was involved in the detoxification of divalent cations (cadmium, zinc and cobalt) and monovalent cations (copper and silver). The genes encoding CzcD and copper translocated P-type ATPase (Cop) had been identified in some Berkholderia genomes, most of which were located next to the czc/cusABC gene cluster, while the genes encoding copper oxidase (mco) had not been detected in the Berkholderia genome. The different distributions and combinations of heavy-metal genes indicate differences of origin and evolution. The GC-content analysis of the strains showed that the GC-content of the strains containing large heavy-metal clusters was lower than the genome GC-content of the strains. To further elucidate the evolution of heavy-metal, it was found Evolutionary tree analysis and pan-genome analysis of Burkholderia genus To analyze the genomic characteristics of each strain, the homologous groups of 62 strains were identified. It was found that the number of unique genes in B. dabaoshanensis and B. novacaledonica is greater than 1,000, with 1,609 and 1875, respectively. Combining the calculation results of average nucleotide similarity, the construction results of the whole genome phylogenetic tree, and the 16 s rDNA phylogenetic tree, it is once again confirmed that B. dabaoshanensis and B. novacaledonica does not belong to the Burkholderia genus. B. dabaoshanensis and B. novacaledonica were removed, and Pan-genome analysis was performed again for the remaining 60 genomes. The results showed that the number of protein coding genes of Burkholderia was 367,029. The unique genes of each strain range from 46 to 797 (Figure 2). The BacMet annotation results showed that Frontiers in Microbiology 04 frontiersin.org Lan et al. 10.3389/fmicb.2023.1252127 FIGURE 1 (A) Average nucleotide identity heat map of 62 Burkholderia genomes. (B) Average nucleotide error heat map of 62 Burkholderia genomes. (C) Genome-wide phylogenetic tree. The red * represents the model species. that upstream and downstream of these large gene clusters contain multiple sequences of transposase, integrase, site-specific recombination enzyme and phage origin, which indicates that the origin of these clusters may be transferred to the genome through horizontal transfer. The analysis of the upstream and downstream clusters of the strain showed that different clusters have different insertion positions in different strains, indicating that the cluster may have been obtained more than once in this genus of species. Frontiers in Microbiology The dN/dS ratios of almost all heavy metal resistance genes were less than 1, indicating that these genes are subject to purification selection (Figure 8). The dN/dS ratios of arsB, czcB, and merR genes were greater than 1, indicating that of them may be in positive selection. The ArsB (average dN/dS ≤ 0.03) and czcA (average dN/dS ≤ 0.02) were observed to exhibit the lowest dN/dS ratio, indicating strong purification selection (Figure 8). 05 frontiersin.org Lan et al. 10.3389/fmicb.2023.1252127 FIGURE 2 Petal diagram of the pangenome. The center is the number of orthologous coding sequences shared by all strains (i.e., the core genome). Numbers in nonoverlapping portions of each oval show the numbers of CDSs unique to each strain. Tn7 Like transposable element associated heavy metal resistance genes in Burkholderia pathways: “signaling and cellular processes” and “environmental information processing” (Figures 11A,B). 1831 genomes were annotated by prokka, domain, and blast, and the results showed that the Tn7 like element is commonly present in the Burkholderia genus (Supplementary Figure S3; Supplementary Table S7). The Tn7 like element structures of the three strains (B. cenocepacia，B. multivorans，B. contaminans) contained a special gene island (Figures 9, 10; Supplementary Table S8). The gene island is named ‘BGImetal’. The Open reading frame of BGImetal was annotated using prokka software, the results showed that most ORFs on BGImetal were related to heavy metal resistance. The GO function of the Tn7 like element region was enriched in localization, response to stimuli, detoxification, and biological regulation. KEGG analysis showed that the proteins of this region mainly involve in two Gene island BGImetal was obtained through horizontal transfer Frontiers in Microbiology The annotation results of the gene island showed that the 574,969– 618,208 bp segment of chromosome 3 (CP008728.1) in B. multiorans DDS 15A-1 was a Tn7 like element. The GC-content of this region (61.72%) was significantly different from the average GC-content of the whole genome (66.60%). The 23,162–56,803 bp segment of a contig (NZ_MUQU01000095.1) of genome sequence in B. cenocepacia VC10178 was a Tn7 like element. The GC-content of this region (62.78%) was significantly different from the average GC-content of the whole genome (67.04%). The GC-content of Tn7 like element 06 frontiersin.org Lan et al. 10.3389/fmicb.2023.1252127 FIGURE 3 Pangenome analysis of Burkholderia. (A) Mathematical modeling of the pangenome and core genome. (B) Proportions of heavy metal resistance genes in pangenome, accessory genome, and unique genes. (C) Proportions of resistance genes to the BacMet database in the pangenome, accessory genome, and unique genes. region of B. contaminans LMG 23361 (62.72%) was different from the average GC-content of the whole genome (65.89%). Sliding window (5 kb size; 2.5 kb step size) was used to statistics the frequency of codon usage in various regions of the B. multivorans DDS 15A-1, B. Centocepacia VC10178, B. contraminans LMG 23361 genome (Figure 12). The principal component analysis indicated that the codon preferences of these two regions are different from the majority of genes. The annotation analysis of gene island indicated that approximately 14.28% of the entire genome of B. multivorans DDS 15A-1 is a gene island region, with approximately 25.67% of the region on chromosome 3 (CP008728.1) being a gene island. These results demonstrated that this region is a horizontal gene transfer insertion event into the genome based on Tn7 like elements. poor only based on 16S rRNA. It was not reliable to identify strains only through 16S rRNA phylogenetic tree. It was necessary to supplement identification through phylogenetic research of other Housekeeping gene. As a result, some strains in online databases (such as NCBI) were misclassified as species. However, many subsequent studies were based on previous classifications, which may result in bias in the results of studies based on previous classifications. Previous studies had found that the classification of some Burkholderia genera was incorrect (Meza-Radilla et al., 2019). The method of constructing phylogenetic trees through the whole genome and core genome to determine the taxonomic status of strains was more reliable than the 16S rDNA method. Therefore, it is recommended that subsequent studies can use the method of constructing phylogenetic trees using whole genome and core genome when identifying the classification of Burkholderia species. In this study, Pararaburkholderia was selected as a reference and exogenous species, and compared to other possible options such as the Ralstonia genus, Pararaburkholderia has a closer genetic relationship with Burkholderia (Kaur et al., 2017). Previous studies had shown that using Pararaburkholderia as an exogenous species can effectively analyze the main evolutionary branches and phylogenetic relationships of Burkholderia (Sawana et al., 2014; Mullins and Mahenthiralingam, 2021). The use of Pararaburkholderia will not have a negative impact on phylogenetic of Burkholderia. has been added in discussion section. It was found that two bacterial species (B. dabaoshanensis and B. novacaledonica) were misclassified Discussion Classification of Burkholderia genus Once long ago some researchers have only used the method of constructing 16S rRNA (or 16S rDNA) phylogenetic trees to identify the taxonomic status of Burkholderia strains (Bazhanov et al., 2010; Schönmann et al., 2010; Sawana et al., 2014). However, there was a high similarity of 16S rRNA among Burkholderia strains, and the resolution of 16S rRNA in taxonomy analysis is Frontiers in Microbiology 07 frontiersin.org Lan et al. 10.3389/fmicb.2023.1252127 FIGURE 4 Divergence time trees of 60 Burkholderia genomes. Genome evolution of Burkholderia into the genus Burkholderia. The average nucleotide similarity results indicate that B. dabaoshanensis and B. novacaledonica has a lower average nucleotide similarity (~84%) compared to other strains in the Burkholderia genus, while the average nucleotide similarity between strains in the Burkholderia genus and Paraburkholderia phenolitrix strains in the same family (Burkholderia ceae) is 85%, indicating B. dabaoshanensis and B. novacaledonica may not belong to the Burkholderia genus, meaning that these two species belong to Burkholderia and are mistakenly defined as genera; The phylogenetic tree results of whole genome construction will also be B. dabaoshanensis, B. novacaledonica and P. phenoliruptrix converge into one branch; Through pan-genome analysis, only B. dabaoshanensis and B. novacaledonica had a large number of unique genes (1,609 and 1875, respectively), while other strains had fewer than 1,000 unique genes; Based on the above results, it is believed that B. dabaoshanensis and B. novacaledonica was misclassified into the genus Burkholderia. Frontiers in Microbiology The Burkholderia genus includes some plant and animal pathogens as well as important environmental microorganisms (Nisr et al., 2012; Shen et al., 2014; Artemeva et al., 2021). Due to some Burkholderia are clinical pathogenic bacteria and have relatively high antibiotic resistance (Arora et al., 2021; Peng et al., 2021; Schaumburg et al., 2022), they can be used for biodegradation, prevention of various plant diseases, production of enzymes, and remediation of heavy metals in soil (Park, 2012; Vu and Moreau, 2017; Liu et al., 2021), which has attracted widespread attention from researchers, and new strains continue to be discovered. It was found that Burkholderia species have rapidly differentiated (Shion et al., 2016). The divergent time tree constructed by pan-genome analysis showed that Burkholderia has differentiated into several species at 0 ~ 0.05 MYA, and differentiated strains such as B. humptydooensis, which was classified and identified in 2017, 08 frontiersin.org Lan et al. 10.3389/fmicb.2023.1252127 FIGURE 5 Distribution of mercury resistance genes on 60 Burkholderia genomes. belongs to the Burkholderia pseudomallei complex. Other recently differentiated species include B. pseudomallei, B. mallei, and B. thailandiensis et al. Pan-genome analysis showed that the number of core genomes is 1,368 (28.6% of the genes in each strain were core genes on average), and the specific genes of each strain ranged from 46 to 797 (the average number of specific genes of each strain was 242). The unique genes of bacterial strains were usually considered as newly generated genes during the evolutionary process of bacteria, and horizontal gene transfer is the main driving force for bacteria to obtain new genes, which indicating that the Burkholderia genus has a strong ability to obtain genes from the outside world. There were numerous transposable events on the genome (Bishop and Rachwal, 2014). The analysis of codon usage frequency showed that a significant portion of the genome of Burkholderia has different codon preferences compared to most regions on the genome. The analysis results of gene islands show that there is a certain proportion of gene island regions in the genome of the Burkholderia, such as, approximately 14.28% of the genome of B. multivoran DDS 15A-1 is a gene island region, indicating that the Burkholderia genus obtains genes from the outside world through horizontal transfer and other methods to enrich its own Frontiers in Microbiology genome. Based on the above results, it was believed that the Burkholderia genus has a faster evolutionary rate. Due to the widespread impact of the Burkholderia genus on humans, animals, and plants, as well as the rapid evolution rate of the Burkholderia genus, it was possible to isolate and identify more members of the genus in more habitats in the future, and to discover more life and production applications of Burkholderia bacteria in the future. Acquisition of heavy metal resistance genes in Burkholderia In recent years, many new strains of Burkholderia had been tested and analyzed, and it was found that some Burkholderia have high efficiency in biological pest control and bioremediation, including resistance to heavy metals (Nguyen et al., 2021; Simonetti et al., 2021). Experimental studies had shown that the Burkholderia genus is resistant to various heavy metals such as mercury, lead, cadmium, manganese, etc. (Min et al., 2013; Si et al., 2017; Wang et al., 2020). This study explored the resistance of Burkholderia to some heavy metals at the genomic level. It was found that heavy metal resistance 09 frontiersin.org Lan et al. 10.3389/fmicb.2023.1252127 FIGURE 6 Distribution of arsenic resistance genes on 60 Burkholderia genomes. genes appeared in clusters in Burkholderia, and there were differences in heavy metal resistance genes in different strains. The observation of the upstream and downstream of heavy metal clusters found that there were transposase, recombinant enzyme, integrase and other genes, indicating that these genes may be obtained through horizontal transfer. B. centocepacia, B. multivorans, B. genes related to resistance to heavy metals such as mercury and manganese were found on the gene island BGImetal in the three strains of contaminans. The gene island BGImetal was horizontally transferred through Tn7 Transposable element in these three strains (Figures 9, 10). The gene island BGImetal associated with Tn7 like was a form of heavy metal resistance gene transfer in the genus Burkholderia. The horizontal transfer of other heavy metal resistance genes (or clusters) in Burkholderia may take the form of other transposable element. With the increasing severity of heavy metal pollution, pollution control has become a focus of attention. At present, heavy metal resistance genes have been identified in other bacterial genus. Yang et al. studies results found that two kinds of copper-tolerant bacteria and copper-tolerant yeast can with stand Cu2+. The cadmium-tolerant Cellulosimicrobium Frontiers in Microbiology sp. strain and Enterococcus sp.stain can with stand of Cd2+. Leadresistant bacteria of the Lysinibacillus sp. stain and the cadmiumresistant Microbacterium sp. strain can with stand Pb2+ (Yang, 2020). Pesudomonas aeruginosa M1 has the ability to resist cadmium The cadmium resistant fungal strain janthinellum Penicillium ZZ-2 has the potential to improve the growth, cadmium accumulation, and cadmium tolerance of dog tooth root plants (Xie et al., 2021). Whether the metal resistance genes of these bacterial genus are located on the genome island has not been reported yet. Conclusion 1841 genomes of the Burkholderia genus were obtained from the NCBI database and filtered by BUSCO to obtain 1831 genomes and 32 bacterial species. The Pan-genome analysis of 62 genomes showed that B. dabaoshanensis and B. novacaledonica has an abnormal number of unique genes compared to other genomes. The whole genome phylogenetic tree would be B. dabaoshanensis, 10 frontiersin.org Lan et al. 10.3389/fmicb.2023.1252127 FIGURE 7 Distribution of cadmium, zinc, cobalt, copper resistance genes on 60 Burkholderia genomes. B. novacaledonica and P. phenolitrix converge to form a branch, indicating B. dabaoshanensis and B. novacaledonica did not belong to the Burkholderia genus. Removing B. dabaoshanensis and B. novacaledonica genome, pan-genome analysis showed that many core genes were involved in heavy metal resistance. By analyzing the distribution and characteristics of heavy metals such as mercury, arsenic, cadmium, zinc, cobalt and copper in the genus Burkholderia, it was found that heavy metal resistance genes appeared in clusters in the genus Burkholderia. At the same time, the GC-content of the heavy metal cluster was different from that of the genome, and there were transposase, recombinase, integrase and other genes in the upstream and downstream of the heavy metal cluster, which might be obtained through horizontal transfer. The dN/dS ratio of heavy metal resistance genes in Burkholderia was less than 1, indicating that the heavy metal resistance gene undergoes purification selection in the Burkholderia genus, and also showing that the heavy metal resistance gene is crucial for the growth of the Burkholderia genus. Tn7 like transposable element was identified in Burkholderia. It was found that Tn7 like transposable element are ubiquitous in Frontiers in Microbiology Burkholderia, and they were inserted in various positions in the genome. Due to the evolution of the genome, some Tn7-like transposable element were no longer complete (some Tn7 proteins are lost, and the protein structure is incomplete). It was found that there is a special Tn7 like transposable element that has formed a gene island form (BGI metal) in the genus Burkholderia, and this transposable element was only found in B. Centocepacia, B. multivorans, Burkholderia contaminans. The difference of GC-content and codon usage frequency between BGImetal region and other regions of the genome showed that the gene island is horizontally transferred through Tn7 transposable element. Observing the Tn7 element in the structure of BGImetal, it was found that the structure and sequence of Tn7 proteins (TnsA, TnsB, TnsC, TnsD/TniQ) have not undergone a certain degree of change, indicating that the gene island has recently been horizontally transferred into the genome, and the Tn7 protein, L, and R end sequences of the Tn7 element in all BGImetal structures are completely consistent. It was speculated that all discovered BGImetal are from the same source. 11 frontiersin.org Lan et al. 10.3389/fmicb.2023.1252127 FIGURE 8 Selection pressures on metal resistance genes of Burkholderia. FIGURE 9 Gene island BGImetal was associated with a Tn7-like structure. (A) Tn7-like structure, four genes (tnsA, tnsB, tnsC, tniQ) were arranged in sequence on the genome. (B) Burkholderia multivorans DDS 15A-1 Tn7-like structure right end sequence (90bp). (C) Burkholderia multivorans. The left-end sequence (158bp) of the Tn7-like structure of DDS 15A-1. Frontiers in Microbiology 12 frontiersin.org Lan et al. 10.3389/fmicb.2023.1252127 FIGURE 10 (A) B. cenocepacia VC10178 genomic fragment has a longer 33,652 bp region than the B. cenoc epacia MSMB384WGS chromosome 2, there is also a highly similar fragment in the some B. cenoc taminans genome; (B) B. multivoran DDS 15A-1 chromosome 3 interval compared to B. multivoran ATCC 17616 Chromosome 3 has a 43,240 bp region. FIGURE 11 GO, KEGG function annotation gene island BGImetal. (A) GO annotation B. multivoran DDS 15A-1, B. cenocepacia VC10178 gene island BGImetal; (B) KEGG annotation B. multivoran DDS 15A-1 gene island BGImetal. Frontiers in Microbiology 13 frontiersin.org Lan et al. 10.3389/fmicb.2023.1252127 FIGURE 12 PCA plot of codon usage frequency (A) was represented as B. multivoran DDS15A-1; (B) was represented as B. cenocepacia VC10178; (C) was represented as B. cenocepacia LMG 23361. The blue dots represent the codon usage bias of the gene island BGI metal, and the red dots represent the codon usage bias of other regions on the genome. Meanwhile, the discovery of this structure in all three bacterial species indicates that the gene island has already spread horizontally within the genus. The heavy metal resistance gene carried by Tn7 transposable element in Burkholderia was beneficial to the host, making the host become a dominant strain of heavy metal resistance, thus the host has the ability to survive in the environment polluted by heavy metals. Tn7 structure was retained because it is beneficial to the host. Acknowledgments We thank Carlos Flores for his critical review. Conflict of interest Data availability statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding authors. Publisher’s note All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. Author contributions YL, ML, and YC: conceptualization. YL, YS, and FL: investigation. YL, YS, and DL: visualization. YL: writing – original draft. YL, DQ, and DL: writing – review editing. All authors contributed to the article and approved the submitted version. Funding Supplementary material This work was supported by the National Natural Science Foundation of China (32071479 and 32271535), the Sichuan Provincial S&T Projects, China (Nos. 2022NSFSC0934 and 2023YFG0122). The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb.2023.1252127/ full#supplementary-material Frontiers in Microbiology 14 frontiersin.org Lan et al. 10.3389/fmicb.2023.1252127 References Ali, H., Khan, E., and Sajad, M. A. (2013). Phytoremediation of heavy metals—concepts and applications. Chemosphere 91, 869–881. doi: 10.1016/j.chemosphere.2013.01.075 heavy-metal resistance in Burkholderia Pseudomallei. Infect. Immun. 65, 4972–4977. doi: 10.1128/iai.65.12.4972-4977.1997 Arora, T., Kanad, R. B., and Syed, M. (2021). A model-driven in-silico metabolic pathway analysis (MPA) for the identification of potential drug targets for Burkholderia Sps. The international society for computational biology (Iscb): 17th international student council symposium (Scs). Lyon, France: 33. Kaczmarska, Z., Czarnocki-Cieciura, M., Karolina, M., Górecka-Minakowska, K. M., Wingo, R. J., Jackiewicz, J., et al. (2022). Structural basis of transposon end recognition explains central features of Tn7 transposition systems. Molecular Cell 82, 2618–2632.E7. doi: 10.1016/j.molcel.2022.05.005 Artemeva, E. A., Melnikova, L. A., and Rodionov, A. P. (2021). Preparation and transfer of Burkholderia Mallei production strain 5584 in accordance with the biosafety requirements. Vet. Sci. Today 3, 243–247. doi: 10.29326/2304-196X-2021-3-38-243-247 Kaur, C., Selvakumar, G., and Ganeshamurthy, A. N. (2017). Burkholderia to Paraburkholderia: the journey of a plant-beneficial-environmental bacterium. Recent Adv. Appl. Microbiol. 10:1724. doi: 10.1007/978-981-10-5275-0_10 Bazhanov, D. P., Yatsevich, K. K., and Bazhanova, A. A. (2010). Phylogenetic identification of three strains of rhizosphere Bacteria based on the results of 16s rRNA gene analysis and genetic typing. Microbiology 79, 374–384. doi: 10.1134/ S0026261710030148 Kumar, S., Stecher, G., Li, M., Knyaz, C., and Tamura, K. (2018). Mega X: molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35, 1547–1549. doi: 10.1093/molbev/msy096 Bertelli, C., Laird, M. R., Williams, K. P., Lau, B. Y., Hoad, G., Winsor, G. L., et al. (2017). Islandviewer 4: expanded prediction of Genomic Islands for larger-scale datasets. Nucleic Acids Res. 45, W30–W35. doi: 10.1093/nar/gkx343 Lechuga-Ballesteros, D., Truong-Le, V., and Patzer, E. J. (2009). Comment on: resistance of planktonic And biofilm-grown Burkholderia Cepacia complex isolates to the transition metal gallium. J. Antimicrob. Chemother. 63, 1078–1079. doi: 10.1093/jac/ dkp086 Bishop, A. H., and Rachwal, P. A. (2014). Identification of genes required for soil survival in Burkholderia Thailandensis by transposon-directed insertion site sequencing. Curr. Microbiol. 68, 693–701. doi: 10.1007/s00284-014-0526-7 Letunic, I., and Bork, P. (2016). Interactive tree of life (Itol) V3: An online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Res. 44, W242– W245. doi: 10.1093/nar/gkw290 Chen, L., He, L. Y., Wang, Q., and Sheng, X.-F. (2016). Synergistic effects of plant growth-promoting Neorhizobium Huautlense T1-17 And immobilizers on the growth and heavy metal accumulation of edible tissues of hot pepper. J. Hazard. Mater 312, 123–131. doi: 10.1016/j.jhazmat.2016.03.042 Li, W., and Godzik, A. (2006). Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658–1659. doi: 10.1093/ bioinformatics/btl158 Li, L., Meng, D., Yin, H., Zhang, T., and Liu, Y. (2023). Genome-resolved metagenomics provides insights into the ecological roles of the keystone taxa in heavymetal-contaminated soils. Front. Microbiol. 14:1203164. doi: 10.3389/ fmicb.2023.1203164 Choi, S. R., Britigan, B. E., and Narayanasamy, P. (2019). Iron/Heme metabolismtargeted gallium(iii) nanoparticles are active against extracellular and intracellular pseudomonas aeruginosa and Acinetobacter Baumannii. Antimicrob. Agents Chemother. 63:18. doi: 10.1128/AAC.02643-18 Liu, Y., Chen, H., Zhao, L., Li, Z., Yi, X., Guo, T., et al. (2021). Enhanced trichloroethylene biodegradation: roles of biochar-microbial collaboration beyond adsorption. Sci. Total Environ. 792:148451. doi: 10.1016/j.scitotenv.2021.148451 Choi, K. Y., Spencer, J. M., and Craig, N. L. (2014). The Tn7 transposition regulator TnsC interacts with the transposase subunit TnsB and target selector TnsD. Proc. Natl. Acad. Sci. U. S. A. 111:9111. doi: 10.1073/pnas.1409869111 Coenye, T., and Vandamme, P. (2003). Diversity and significance of Burkholderia species occupying diverse ecological niches. Environ. Microbiol. 5, 719–729. doi: 10.1046/j.1462-2920.2003.00471.x Meza-Radilla, G., Mendez-Canarios, A., Xicohtencatl-Cortes, J., Escobedo-Guerra, M. R., Torres, A. G., Ibarra, J. A., et al. (2019). Misidentification of Burkholderia pseudomallei and other Burkholderia species from pediatric infections in Mexico. Open Forum Infect. Dis. 6:Ofz008. doi: 10.1093/ofid/ofz008 Das, S., Jean, J. S., Kar, S., Chou, M.-L., and Chen, C.-Y. (2014). Screening of plant growth-promoting traits in arsenic-resistant bacteria isolated from agricultural soil and their potential implication for arsenic bioremediation. J. Hazard Mater 272, 112–120. doi: 10.1016/j.jhazmat.2014.03.012 Min, J. Z., Sha, W., Fu, Z. Y., Zhao, J., and Ji, H. (2013). Isolation of Burkholderia cepacia JB12 from lead- and cadmium-contaminated soil and its potential in promoting phytoremediation with tall fescue and red clover. Canadian J. Microbiol. 59, 449–455. doi: 10.1139/cjm-2012-0650 Edgar, R. C. (2004). Muscle: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32, 1792–1797. doi: 10.1093/nar/gkh340 Mullins, A. J., and Mahenthiralingam, E. (2021). The hidden genomic diversity, specialized metabolite capacity, and revised taxonomy of Burkholderia Sensu Lato. Front. Microbiol. 12:726847. doi: 10.3389/fmicb.2021.726847 Fu, L., Yu, Y., Yu, F., Xiao, J., Fang, H., Li, W., et al. (2023). Profiles and spatial distributions of heavy metals, microbial communities, and metal resistance genes in sediments from an Urban River. Front. Microbiol. 14:1188681. doi: 10.3389/ fmicb.2023.1188681 Nguyen, B.-A. T., Hsieh, J.-L., Lo, S.-C., Wang, S.-Y., Hung, C.-H., and Huang, E. (2021). Biodegradation of dioxins by Burkholderia Cenocepacia strain 869t2: role of 2-Haloacid dehalogenase. J. Hazardous Mat. 401:123347. doi: 10.1016/j. jhazmat.2020.123347 Gary, P. A., Biery, M. C., Bainton, R. J., and Craig, N. L. (1996). Multiple DNA processing reactions underlie Tn7 transposition. J. Mol. Biol. 257, 301–316. doi: 10.1006/ jmbi.1996.0164 Nisr, R. B., Moody, A. J., and Gilpin, M. L. (2012). Screening microorganisms for insulin binding reveals binding by Burkholderia multivorans and Burkholderia cenocepacia and novel attachment of insulin to Aeromonas salmonicida via the A-layer. Fems. Microbiol. Lett. 328, 93–99. doi: 10.1111/j.1574-6968.2011.02484.x Hao, X., Xie, P., Zhu, Y.-G., Taghavi, S., Wei, G., and Rensing, C. (2015). Copper tolerance mechanisms of Mesorhizobium Amorphae and its role in aiding Phytostabilization by Robinia Pseudoacacia in copper contaminated soil. Environ. Sci. Technol. 49, 2328–2340. doi: 10.1021/es504956a Pal, G., Saxena, S., Kumar, K., Verma, A., Sahu, P. K., Pandey, A., et al. (2022). Endophytic Burkholderia: multifunctional roles in plant growth promotion and stress tolerance. Microbiol. Res. 265:127201. doi: 10.1016/j.micres.2022.127201 Hayashi, S., Abe, M., Kimoto, M., Furukawa, S., and Nakazawa, T. (2000). The dsbADsbB disulfide bond formation system of Burkholderia Cepacia is involved in the production of protease and alkaline phosphatase, motility, metal resistance, and multidrug resistance. Microbiol. Immunol. 44, 41–50. doi: 10.1111/j.1348-0421.2000.tb01244.x Park, D. S. (2012). Rapid and specific detection of Burkholderia Glumae in rice seed by real-time bio-PCR using species-specific primers based on an RHS family gene. Plant Dis. 96, 577–580. doi: 10.1094/PDIS-03-11-0235 Peeters, E., Nelis, H. J., and Coenye, T. (2008). Resistance of planktonic and biofilmgrown Burkholderia Cepacia complex isolates to the transition metal gallium. J. Antimicrob. Chemother. 61, 1062–1065. doi: 10.1093/jac/dkn072 Hua, X., Liang, Q., Deng, M., He, J., Wang, M., Hong, W., et al. (2021). Bacant: a combination annotation server for bacterial DNA sequences to identify antibiotic resistance genes, integrons, and transposable elements. Front. Microbiol. 12:649969. doi: 10.3389/fmicb.2021.649969 Peng, D., Xiaoqiang, W., Baird, S. M., Showmaker, K. C., Leif, S., and Peterson, D. G. (2021). Comparative genome-wide analysis reveals that Burkholderia Contaminans Ms14 possesses multiple antimicrobial biosynthesis genes but not major genetic loci required for pathogenesis. Microbiologyopen [J] 5, 353–369. doi: 10.1002/mbo3.333 Huang, G. H., Tian, H. H., Liu, H.-Y., Fan, X.-W., Liang, Y., and Li, Y.-Z. (2013). Characterization of plant-growth-promoting effects and concurrent promotion of heavy metal accumulation in the tissues of the plants grown in the polluted soil by Burkholderia strain LD-11. Int. J. Phytoremediation 15, 991–1009. doi: 10.1080/15226514.2012.751354 Sawana, A., Adeolu, M., and Gupta, R. S. (2014). Molecular signatures and phylogenomic analysis of the genus Burkholderia: proposal for division of this genus into the emended genus Burkholderia containing pathogenic organisms And a new genus Paraburkholderia gen Nov. Harboring Environmental Species. Front. Genet. 5:429. doi: 10.3389/fgene.2014.00429 Jiang, C. Y., Sheng, X.-F., Qian, M., and Wang, Q.-y. (2008). Isolation and characterization of a heavy metal-resistant Burkholderia Sp. from heavy metalcontaminated Paddy field soil and its potential in promoting plant growth and heavy metal accumulation in metal-polluted soil. Chemosphere 72, 157–164. doi: 10.1016/j. chemosphere.2008.02.006 Jones, P., Binns, D., Chang, H. Y., Fraser, M., Li, W., McAnulla, C., et al. (2014). Interproscan 5: genome-scale protein function classification. Bioinformatics 30, 1236–1240. doi: 10.1093/bioinformatics/btu031 Schaumburg, F., Idelevich, E. A., Mellmann, A., and Kahl, B. C. (2022). Susceptibility of Burkholderia Cepacia complex to ceftazidime/avibactam and standard drugs of treatment for cystic fibrosis patients. Microb. Drug Resist. 28, 545–550. doi: 10.1089/ mdr.2021.0353 Jones, A. L., Deshazer, D., and Woods, D. E. (1997). Identification and characterization of a two-component regulatory system involved in invasion of eukaryotic cells and Schönmann, S., Loy, A., Wimmersberger, C., Sobek, J., and Eberl, L. (2010). 16s rRNA gene-based phylogenetic microarray for simultaneous identification of members of the Frontiers in Microbiology 15 frontiersin.org Lan et al. 10.3389/fmicb.2023.1252127 genus Burkholderia. Environ. Microbiol. 11, 779–800. doi: 10.1111/j.14622920.2008.01800.x Vu, H. P., and Moreau, J. W. (2017). Effects of environmental parameters on thiocyanate biodegradation by Burkholderia Phytofirmans candidate strain St01hv. Environ. Eng. Sci. 35, –351. doi: 10.1089/ees.2016.0351 Seemann, T. (2014). Prokka: rapid prokaryotic genome annotation. Bioinformatics 30, 2068–2069. doi: 10.1093/bioinformatics/btu153 Wang, L., Wang, L. A., and Zhan, X. (2020). Response mechanism of microbial community to the environmental stress caused by the different mercury concentration in soils. Ecotoxicol. Environ. Safety 188, 109906.1–109906.7. doi: 10.1016/j.ecoenv.2019.109906 Shen, P., Song, Z., Zhang, Z., Zeng, H., Tang, X., Jiang, C., et al. (2014). Screening of Burkholderia Sp. Wgb31 producing Anisic acid from Anethole and optimization of fermentation conditions. J. Basic Microbiol. 54, 1251–1257. doi: 10.1002/jobm.201400049 Wang, Q., Zhou, Q., Huang, L., Xu, S., Fu, Y., Hou, D., et al. (2022). Cadmium Phytoextraction through Brassica Juncea L under different consortia of plant growthpromoting Bacteria from different ecological niches. Ecotoxicol. Environ. Safety 237:113541. doi: 10.1016/j.ecoenv.2022.113541 Shion, O. K., Kit, A. Y., and Han, L. L. (2016). Burkholderia paludis Sp. Nov. An antibiotic-Siderophore producing novel Burkholderia Cepacia complex species, isolated from Malaysian tropical peat swamp soil. Front. Microbiol. 7:2046. doi: 10.3389/ fmicb.2016.02046 Xie, Y., Bu, H., Feng, Q., Wassie, M., Amee, M., Jiang, Y., et al. (2021). Identification of Cd-resistant microorganisms from heavy metal-contaminated soil and its potential in promoting the growth and Cd accumulation of bermudagrass. Environ Res. 2021, 200:111730. doi: 10.1016/j.envres.2021.111730 Si, M., Zhao, C., Burkinshaw, B., Zhang, B., Wei, D., Wang, Y., et al. (2017). Manganese scavenging and oxidative stress response mediated by type VI secretion system in Burkholderia Thailandensis. Proc. Natl. Acad. Ences 114:201614902. doi: 10.1073/ pnas.1614902114 Yang, Y. (2020). Screening and identification of heavy metal copper,cadmium and lead resistant bacteria in tailings. doi: 10.13140/RG.2.2.17931.67363 Simao, F. A., Waterhouse, R. M., and Ioannidis, P. (2015). Busco: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210–3212. doi: 10.1093/bioinformatics/btv351 Yang, Z. (2007). PAML 4: phylogenetic analysis by maximum likelihood. Mol. Biol. Evol. 24, 1586–1591. doi: 10.1093/molbev/msm088 Simonetti, E., Alvarez, F., and Feldman, N. (2021). Genomic insights into the potent antifungal activity of B. ambifaria T16. Biol. Control 155:104530. doi: 10.1016/j. biocontrol.2020.104530 Yang, Z., Zhang, Z., Chai, L., Wang, Y., Liu, Y., and Xiao, R. (2016). Bioleaching remediation of heavy metal-contaminated soils using Burkholderia Sp. Z-90. J. Hazard Mater 301, 145–152. doi: 10.1016/j.jhazmat.2015.08.047 Suyama, M., Torrents, D., and Bork, P. (2006). Pal2nal: robust conversion of protein sequence alignments into the corresponding codon alignments. Nucleic Acids Res. 34, W609–W612. doi: 10.1093/nar/gkl315 Ye, J., Zhang, Y., Cui, H. H., Liu, J., Wu, Y., Cheng, Y., et al. (2018). WEGO 2.0: a web tool for analyzing and plotting GO annotations, 2018 update. Nucleic Acids Res. 46, W71–W75. doi: 10.1093/nar/gky400 Vignaroli, C., Pasquaroli, S., Citterio, B., Di Cesare, A., Mangiaterra, G., Fattorini, D., et al. (2018). Antibiotic and heavymetal resistance in enterococci fromcoastal marine sediment. Environ Pollut. 237:406–413. doi: 10.1016/j.envpol.2018.02.073 Yuan, Z. S., Liu, F., Xie, B. G., and Zhang, G. F. (2018). The growth-promoting effects of endophytic Bacteria on Phyllostachys Edulis. Arch. Microbiol. 200, 921–927. doi: 10.1007/s00203-018-1500-8 Tripathi, M., Singh, P., Singh, R., Bala, S., Pathak, N., Singh, S., et al. (2023). Microbial biosorbent for remediation of dyes and heavy metals pollution: a green strategy for sustainable environment. Front. Microbiol. 14:1168954. doi: 10.3389/ fmicb.2023.1168954 Zhu, H., Guo, J., Chen, M., Feng, G., and Yao, Q. (2012). Burkholderia dabaoshanensis Sp. Nov., a heavy-metal-tolerant Bacteria isolated from Dabaoshan mining area soil in China. PLoS One 7:E50225. doi: 10.1371/journal.pone.0050225 Tyrrell, J., Whelan, N., Wright, C., Sá-Correia, I., Mcclean, S., Thomas, M., et al. (2015). Investigation of the multifaceted Iron acquisition strategies of Burkholderia Cenocepacia. Biom. J. 28, 367–380. doi: 10.1007/s10534-015-9840-1 Frontiers in Microbiology Zuo, G., and Hao, B. (2015). Cvtree3 web server for whole-genome-based and alignment-free prokaryotic phylogeny and taxonomy. Genom. Proteom. Bioinformatics 13, 321–331. doi: 10.1016/j.gpb.2015.08.004 16 frontiersin.org
https://openalex.org/W4386186074	https://ijsra.net/sites/default/files/IJSRA-2023-0664.pdf	English	null	Career aspirations as a predictor of academic achievement of learners with hearing impairment in special secondary schools in north eastern Nigeria	International Journal of Science and Research Archive	2,023	cc-by	5,287	Career aspirations as a predictor of academic achievement of learne impairment in special secondary schools in north eastern Nigeria Career aspirations as a predictor of academic achievement of learners with hearing impairment in special secondary schools in north eastern Nigeria Yahya Umar Magaji , Beatrice Bunyasi Awori and Muthee J. M. ublication history: Received on 08 July 2023; revised on 19 August 2023; accepted on 22 August 202 Article DOI: https://doi.org/10.30574/ijsra.2023.9.2.0664 Article DOI: https://doi.org/10.30574/ijsra.2023.9.2.0664 Article DOI: https://doi.org/10.30574/ijsra.2023.9.2.0664 Abstract This study focused on career aspirations as predictor of academic achievement among learners with hearing impairment in special schools in North eastern Nigeria. Correlation research design was adopted for the study. Total 351 learners with hearing impairment in Senior Secondary Two (SS II) was selected based on multistage sampling technique across five special schools in North Eastern Nigeria. The instruments for data collection are Learners’ Career Aspiration Questionnaire (LCAQ), and English Language Pro forma (ELP). Data gathered from the respondents were analyzed using Pearson product moment correlation and Analysis of Covariance (ANCOVA) at a 0.05 alpha level. The study found a strong relationship between career aspiration and academic achievement of learners with hearing impairment in English language in North Eastern, Nigeria. However, gender did not correlate with career aspiration of students with hearing impairment toward their academic achievement. The study concludes that career aspiration can independently enhance students’ academic performance. The study recommends among others that teachers should work toward boosting career aspiration of their students through constructive teaching approach that will make education look achievable and admirable to them. Keywords: Career Aspiration; Gender, Academic Achievement; Leaners with Hearing Impairment Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Corresponding author: Yahya Umar Magaji; Email: or(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0. Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0. International Journal of Science and Research Archive, 2023, 09(02), 760–767 Career aspiration is one of the positive outcome variables considered in vocational psychology (Rishaelly, 2019). Aspiration is expressed by Eccles (2017) as a strong desire, longing, or aim to attain particular level of achievement. Carlson, Brooklyn and Adsworth (2018) argued that aspiration require a good ambition, wisdom and intellectual to follow up someone set goal. Hassan (2019) expressed aspiration as a goal or objective that is strongly desired. The author hinted that aspiration is used to attain a goal. Aspiration is a hope or ambition of achieving something while the goal is the object of a person's ambition or effort; an aim or desired result. Craig et al. (2018) expressed those goals are objective, measurable, a tangible target to shoot for, whereas, aspiration is motivators toward achieving the set goal. In short, unlike goal, aspirations are typically subjective, immeasurable, and intangible. Therefore, having career aspiration could be a factor for learners to show dedication toward learning. However, this assumption requires substantial proves, especially when considering learning with hearing impairment. Hearing is very important for the overall development of any human being. Apart from vision, hearing accounts for the ability of the learner to perform well in school-related tasks. Learners who are hearing-impaired may find it impossible to have stable social and emotional relationships for sustainable development. Learners who fall into this category are known as Learners with Hearing Impairment (LHI). Learners with hearing impairment are those who lost their hearing either due to disease or accident (Ugwuanyi, 2018). This loss of hearing has a devastating effect on the ability of these students to think, communicate and learn like others. LHI seem to exhibit flexible patterns of adjustment, sometimes acting out when upset and withdrawing at other times, all point to communication difficulty. Any learner with a disorder in one or more of these basic psychological processes involved in understanding spoken or written language tend to have maladjustment due to communication gap (Ugwuanyi, 2018). It has been hypothesized that learners with hearing impairment are difficult to be thrilled with particular future career, which lead to their low participation in various academic activities, but such contention is yet to be substantiated with enough data. Though. International Journal of Science and Research Archive, 2023, 09(02), 760–767 Punch, Hyde and Creed (2021) argued that anxiety and embarrassment may occur as a result of fear of misunderstanding and callous comments from others which may jeopardize the personal safety or self-esteem, which in turn may make them become frustrated, drop out of school, resort to be begging and become permissive about future career. The functional effects of hearing loss and other people’s negative attitudes have created career barriers for many people who are deaf or hard of hearing (Punch et al., 2021). Further, the effects of their hearing loss may be perceived by young people and by important others such as parents, teachers, and potential employers as a limitation to the accessibility of many occupations (Weisel & Cinamon, 2019). Although job accommodations may resolve some difﬁculties in the workplace for people with disabilities (Szymanski, Hershenson, Enright, & Ettinger, 2018), ignorance of the possibility of job accommodations and the rights of workers to access them may lead students to be adversely affected by a perception of barriers associated with their disability. To this end this study investigates whether the career aspiration of learners with hearing impairment and gender correlate with their academic achievement. 1. Introduction In Africa, for certain reasons, the education of children with disabilities has always been of inferior importance (Iweka, 2018). Stereotypically, children with disabilities have been deemed to be indifferent to education and unable to perform as perfectly as others. This misconception led to exclusion of children with disabilities in education which left them out of focus not only in education but also in almost all areas of social life (Craig, Richard, & du-Plessis, 2018). Therefore, this sphere always demanded special, harder and affectionate consideration throughout all stages of history as disabilities vary in terms of mental and physical aspects and both require deep consideration and professional approach in every corner of the world (Bleidorn, Jaap, Peter, & Samuel, 2016). Nigeria and North East region (Adamawa, Bauchi, Gombe, Yobe, Borno & Taraba States) in particular like other countries in Africa and the world at large considers inclusive education as a very essential process of increasing access and quality of education for all. Many African states including Nigeria, are signatories of various international education documents that includes the International Declarations of Human Rights which states that education is a right for all; World Declaration on Education For All (EFA) which focused on universalizing access and promoting equity in education by considering disability; and Salamanca Statements and Frameworks of Action on Special Needs Education which emphasized on attention of education to children with special needs (UNESCO in Rishaelly, 2019). However, the right to education of leaners with disabilities in North East Nigeria, is still been trampled by the Federal Government of Nigeria, as not all students with disabilities can access quality education (Iweka, 2018). International Journal of Science and Research Archive, 2023, 09(02), 760–767 2. Theoretical and Conceptual Frameworks This study is supported by Michelle and Krumboltz’s Social Learning Theory of Career Development (Michelle & Krumboltz, 1996). The Social Learning Theory of Career Development (SLTCD) Michelle and Krumbolz developed attempts to explain why people make the career decisions they make. People make their career decisions through an indefinite number of learning opportunities in their social environment which influence their views and ideas. These planned and unplanned learning moments, through the views and perceptions they influence and create, have an impact on which route an individual takes through the myriad of career and educational opportunities available to them. Michelle and Krumboltz social learning theory consist of two parts: The Social Learning Theory of Career Decision Making (SLTCDM) and The Learning Theory of Career Counselling (LTCC). This study adopts the Social Learning Theory of Career Decision Making (SLTCDM) to explain students’ career aspiration and their academic achievement. SLTCDM attempts to explain the origin of career choice. The theory presented by Michelle and Krumboltz, known as social learning theory of career decision making, explains how educational and occupational skills are required for selection of career (Michelle and Krumboltz, 1996 cited in Pattanayak & Naik, 2020). The theory is said to explain the development of career aspirations and clarifies the role of decision making. According to SLTCDM, there are four major factors that influence how people make career decisions. These four factors are environmental conditions and events, genetic endowment and special abilities, task approach skills and educational experiences. Krumboltz believes that genetic endowment and special abilities—qualities one inherited from birth, can make one more apt to pursue certain careers and limit one from chasing others. Everyone is born with specific qualities that make him/her better and most productive in one career and least effective in another. These differences effect on the person’s occupational preference and educational exposure. These differences can be of race, gender, physical appearance and characteristics, and birth defects. Just as the mind and body one is born with have an effect on the person, so, also does the world into which one is born. Ideally, career development is the method in which an individual develops accurate perceptions of the available opportunities and the relationship between that individual and those opportunities. In this process the individual collects the information obtained in career development and construct their own reality using his cognitive theory and receiving input from the environment. 1.2. Research Hypotheses  Ha1: There is a relationship between career aspirations and academic achievement of learners with hearing impairment in special secondary schools  Ha2: There is no significant interaction between career aspiration and gender toward prediction of academic achievement of learners with hearing impairment in special secondary schools Objective of the Study Specifically, the study seeks to:  Establish the relationship between career aspiration and academic achievement of learners with hearing impairment in special secondary schools.  Establish the relationship between career aspiration and academic achievement of learners with hearing impairment in special secondary schools.  Determine whether career aspiration interact with gender to predict the academic achievement of learners with hearing impairment in special secondary schools. 1.1. Statement of the Problem Evidences from earlier study in Nigeria, has shown that education of learners with hearing impairment has always been below average (Agu, 2017). Also, Oyesiku (2019) argued that children with disabilities have been deemed to be indifferent to education and unable to perform as perfectly as others. Some parents as well as education planners are seemed not totally convinced that children with disabilities especially learners with hearing impairment can cope with others in the labour markets. Therefore, the inputs from both parents and other stakeholders to motivate children with hearing impairment regarding choosing promising career were low. Though, poor performance in academic is worrisome and has attracted different research that led to series of findings and conclusions. The need to seek the causes of such under performance among children with hearing impairment, especially in north-eastern part of Nigeria is high. Considering the fact that academic achievement of students in special schools is of paramount to their future and national development. The persistent poor performance as reported by Omollo and Yambo (2017); Udonsa (2020) across secondary schools in Northern part of Nigeria, with larger proportion of such poor result recorded among children with disabilities called for through examination. Specifically, initial assessment of the external examination results conducted by West African Examination Council (WAEC) in English Language, revealed that only 22% of candidates that sat for the examination passed at credit or distinction level (Udonsa, 2020), while more than 78% were all below average. One of the factors earlier pointed as motivator for learners’ commitment and high performance is career aspiration (Oyesiku, 2019). Incidentally, having huge proportion of failure among hearing impairment students raise the curiosity to determine whether level of career aspiration among them could be responsible for the underachievement of students with hearing impairment. It was against the backdrop 761 International Journal of Science and Research Archive, 2023, 09(02), 760–767 that this study investigates the contribution of career aspiration on academic achievement of learners with hearing impairment in special schools, North Eastern Nigeria. 2.1. Conceptual Framework The study enhances conceptual framework demonstrates the relationship and interactions among predictor variables and outcome variables as illustrated in figure 1. It also envisions how career aspirations impact on students’ academic achievement. Source: Researcher, 2021 Figure 1 Conceptual Framework of Variables in the Study Figure 1 Conceptual Framework of Variables in the Study Figure 1.1 provides a graphical illustration of how career aspirations may influence learners’ academic achievement. The framework shows that learners’ career aspirations may determine their academic achievement. For instance, a learner’s confidence to excel academically in certain subject areas may lead the learner towards the choice of careers related to that subject matter. Likewise, learners in secondary school, who hope to graduate someday, may develop different forms of career aspirations that they want to pursue in the future. These aspirations, be it occupational, achievement, leadership and educational may determine the efforts they put academically to achieve their dreams. However, the yardstick commonly used by learning institutions to determine this is the students’ academic achievement. Therefore, this study will find out whether career aspirations singly predict academic achievement of learners with hearing impairment. 2. Theoretical and Conceptual Frameworks This is called environmental conditions and events. Michelle and Krumboltz describe these environmental conditions and list twelve environmental categories as below: Job opportunities, social policies, benefits and salaries for certain jobs, labor laws, physical events, natural resources, technology development (technology), changes in social organizations, family education, educational resources, neighbors and social impact. These events are often beyond our control and may or may not be scheduled. Krumboltz and his colleague emphasize that the uniqueness of each individual experiences in life brings about some factors which determine the job choices. According to the theory, these factors become the reasons for people to aspire for different careers opportunities. These factors interact with each other in complex and unpredictable ways in each individual and influence the beliefs we have of ourselves and the world. According to Mitchell and Krumbolz, the combination of these factors results in correct or incorrect beliefs, stereotypes and generalizations about the self, careers, the world of work, society, among others. The combined effect of these factors encourages the person to look for a new career that best suits him/her. The options available to every individual are influenced by both internal and 762 International Journal of Science and Research Archive, 2023, 09(02), 760–767 external factors, which either facilitate or discourage the person, and changes the shape and number of available opportunities and how the individual response to them. external factors, which either facilitate or discourage the person, and changes the shape and number of available opportunities and how the individual response to them. The school is an environment where teaching and learning takes place and where learners’ abilities in different subjects are tested. Environmental conditions and events, genetic endowment and special abilities, task approach skills and most importantly, educational experiences of learners with hearing impairment may interact to affect their career choices and consequently academic achievement based on those career choices. For example, a learner who obtained good grades in science-related subjects is likely to develop greater career aspirations in science-related careers than a learner who had bad grades in science-related subjects. Moreover, the environment in which a learner is born and raised provides only certain types of learning opportunities. The more learners actively engage in activities that give them joy and produces tangible results, the more likely they are to encounter valuable learning experiences that may shape their career aspirations. 4. Results and discussion Table 1 Outcome of Pearson Product Moment Correlation (PPMC) on Relationship between Career Aspiration and Academic Achievement of Learners with Hearing Impairment in Special Secondary Schools, North Eastern, Nigeria Stat Value Asymp. Std. Errora Sig. Pearson's R 0.512 0.035 0.000c Eta 0.624 N of Valid Cases 351 Source: Field Work (2022) of Pearson Product Moment Correlation (PPMC) on Relationship between Career Aspiration an ment of Learners with Hearing Impairment in Special Secondary Schools, North Eastern, Nigeria Table 1 Outcome of Pearson Product Moment Correlation (PPMC) on Relationship between Career Aspiration and Academic Achievement of Learners with Hearing Impairment in Special Secondary Schools, North Eastern, Nigeria Stat Value Asymp. Std. Errora Sig. Pearson's R 0.512 0.035 0.000c Eta 0.624 N of Valid Cases 351 Source: Field Work (2022) The results on Table 1 established strong and positive relationship between career aspiration and students’ academic achievement in English could be as results of motivation that can be attributed to career wishes among respective students. It is obvious and expected that those students seeking higher post and well-paid job are much likely to understand the need to sit tight for their studies in order to come out in flying colour. This concurs with the finding earlier made by Mahoney, Taylor and Kanarek (2018) which established significant relationship between students’ career choice and students’ academic performance. Also, Bleidorn et al. (2016) attributed the significant relationship between career aspiration and academic performance to the level of students’ awareness of the requirements for particular chosen career. This agrees with the finding earlier made by O’Brien (2019) who established that the degree to which individual hope to attain certain positions is related with the degree of efforts such individual could put-in toward achieving his/her goal. Though, Hassan (2019), and Narimani and Mousazadeh (2018) show that irrespective of career aspiration by learners there is other aspect of cognitive capability, readiness and self-discipline that can impact on the learners’ academic achievement. Students with higher career aspiration but with gross academic indiscipline are likely to seek ill-ways of passing their examination. In the scope of this study, it is expected that learners with hearing impairment are much likely to be more ready to learn, working towards achieving their aim of career choice as well as attaining fairer academic achievement. 3. Material and methods The study adopted survey research design. The locale for this study is north-eastern region of Nigeria, which located between latitude 70N and 13.50N, and longitude 8.50E and 14.250E, and has a land area of 402,159 square kilometres. The north-eastern region of Nigeria is made up of six states: Adamawa, Bauchi, Gombe, Maiduguri, Yobe, and Taraba. The target population of this study includes all the 1,402 students with HI in Senior Secondary Two (SS II) across the five public special schools in north eastern Nigeria. These five public special schools are the only schools in North Eastern Nigeria that accommodate learners with disabilities. The sample size for this study is 351 which was randomly sampled across four school across north eastern region of Adamawa State. The instruments for this study include “Learners’ Career Aspiration Questionnaire (LCAQ) and English Language Pro forma”. Data collected was analyzed using Person Product Moment Correlation (PPMC) and Analysis of Covariance (ANCOVA) at 0.05 significance level. 763 International Journal of Science and Research Archive, 2023, 09(02), 760–767 4. Results and discussion The table reveals F (1, 351) = 0.050 at p =0.757. Thus, F(0.050) is not significant, since P (0.757) > P (0.05). Therefore, the null hypothesis is not rejected. This shows that there is no significant interaction effect of career aspiration and gender on academic achievement of learners with hearing impairment in north eastern, Nigeria. In this case, gender is not a determinant of performance, it is basically the individual aspiration of learners toward future career. Table 2 presents summary of one-way ANCOVA results on interaction effects of career aspiration and gender on academic achievement of learners with hearing impairment in English language. The table reveals F (1, 351) = 0.050 at p =0.757. Thus, F(0.050) is not significant, since P (0.757) > P (0.05). Therefore, the null hypothesis is not rejected. This shows that there is no significant interaction effect of career aspiration and gender on academic achievement of learners with hearing impairment in north eastern, Nigeria. In this case, gender is not a determinant of performance, it is basically the individual aspiration of learners toward future career. Table 2 presents summary of one-way ANCOVA results on interaction effects of career aspiration and gender on academic achievement of learners with hearing impairment in English language. The table reveals F (1, 351) = 0.050 at p =0.757. Thus, F(0.050) is not significant, since P (0.757) > P (0.05). Therefore, the null hypothesis is not rejected. This shows that there is no significant interaction effect of career aspiration and gender on academic achievement of learners with hearing impairment in north eastern, Nigeria. In this case, gender is not a determinant of performance, it is basically the individual aspiration of learners toward future career. The findings from this study did not establish a significant interaction effect between career aspiration and gender to affect different performance of students. This shows that interactive stimulation is capable of enhancing students’ performance irrespective of their career aspiration. Thus, irrespective of gender, learners with hearing impairment that has higher career aspiration are expected to perform better in academic, while those with low aspiration may have weak performance in academic. This concurs with the finding in the earlier studies by Pattanayak and Naik (2020) and Iweka (2018) that encouraging learners on better career pursue could enhanced their input in education irrespective of gender. Carlson et al. 4. Results and discussion (2018) expressed that both male and female learners with higher desired for good job doing well in their academic activities. Though, the current finding differed to that made by Rishaelly (2019), the study concluded that societal gender stereotypes such as job differentiation among gender within the society could responsible for having students of particular gender performed better than others. The findings from this study that show moderate relationship between career aspiration and students’ academic achievement that other variable such as when gender interacted with career aspiration against academic achievement, only career aspiration contributed meaningfully towards students’ achievement while gender was not significant. The results further showed that most male students’ choses white collar job while female dominated blue- and pink-collar jobs. However, the study showed that the higher the career aspiration, the higher the mean academic achievement score. This agrees with the finding made Agu (2017) that career aspiration interacted significantly with gender to enhance students’ academic performance. Similar finding was also made by Bleidorn et al. (2016), which established gender as a weaker factor for predicting academic performance but was a moderating factor along with career aspiration to promote better learner academic performance. 4. Results and discussion The current finding shows consistency with the earlier conclusion by Pattanayak and Naik (2020) that the aspiration to secure good job after schooling promote good self-esteem among students as well as promoted positive participation and their overall academic achievement. Likewise, Narimani and Mousazadeh (2018) maintained that the students’ career aspiration makes significant effect on their academic performance. Also, in the study by Agu (2017) it was recoded that career inspiration pattern of students related strongly with students’ academic achievement. Thus, the current study has shown that career aspiration can serve as motivation for students to perform better in their respective academic activities. This agrees with the submission made by Hassan (2019) that aspiration is a goal or objective that is strongly desired. Therefore, aspiration needs to be used to attain a goal. Pattanayak and Naik (2020) found that career aspiration, career development, self-esteem related strongly with learners’ performance. Likewise, Agu (2017) maintained that students’ career aspiration propelled their achievement academically. According to Carlson et al. (2018) most of the students in urban centred schools do aspire to pursue higher qualification such as university degrees. This show that students’ interaction with immediate society could impact on their aspiration for specific career or position, which could push them to learn more and perform better. The similar view was shared by Booth and Gerard (2019) and Mahoney et al. (2018) that career aspiration related strongly with learning performance or learners’ environment. Ha2: There is no significant interaction between career aspiration and gender toward prediction of academic achievement of learners with hearing impairment in special secondary schools 764 International Journal of Science and Research Archive, 2023, 09(02), 760–767 Table 2 Summary of ANCOVA of Interaction Effects of Career Aspiration and Gender on Academic Achievement of learners with hearing impairment Source Type III Sum of Squares df Mean Square F Partial Eta Squared Sig. Corrected Model 10406.27 3 3468.76 19.02 0.02 .000 Intercept 118040.67 1 118040.67 647.25 0.04 .000 Career Aspiration 8919.17 1 8919.17 48.91 0.13 .000 Gender 16.147 1 16.15 0.09 0.11 .701 Career Aspiration * Gender 8.223 1 8.22 0.05 0.02 .757 Error 63830.16 350 182.37 Total 212388.52 351 Corrected Total 74236.41 350 Dependent Variable: Performance; R Squared = .281 (Adjusted R Squared = .272) Table 2 presents summary of one-way ANCOVA results on interaction effects of career aspiration and gender on academic achievement of learners with hearing impairment in English language. References [1] Agu, K. (2017). Relationship among career inspiration patterns and students’ academic achievement in Enugu state of Nigeria. Unpublished MSc. Thesis University of Nigeria Nsukka. [1] Agu, K. (2017). Relationship among career inspiration patterns and students’ academic achievement in Enugu state of Nigeria. Unpublished MSc. Thesis University of Nigeria Nsukka. [2] Bleidorn, W., Jaap, J. A., Peter, J. R. & Samuel, D. G. (2016). Age and gender differences in self-esteem—a cross- cultural window. Journal of Personality and Social Psychology, 111(3), 396 – 410. [2] Bleidorn, W., Jaap, J. A., Peter, J. R. & Samuel, D. G. (2016). Age and gender differences in self-esteem—a cross- cultural window. Journal of Personality and Social Psychology, 111(3), 396 – 410. [3] Booth, M. Z., & Nolan, R. S. (2020). Effect of self-esteem, career aspirations on academic achievement of adolescent students United States. International Journal of Institute of Health, 2(3), 14 – 27. [3] Booth, M. Z., & Nolan, R. S. (2020). Effect of self-esteem, career aspirations on academic achievement of adolescent students United States. International Journal of Institute of Health, 2(3), 14 – 27. [4] Carlson, D. S., Brooklyn, D. C., & Adsworth, L. L. (2018). The effects of internal career orientation on multiple dimensions of work-family conflict. Journal of Family and Economic Issues, 24, 99 – 116. [5] Craig, C. J., Richard, J. K. & du-Plessis, J. (2018). Teacher and teaching development: Making an impact. Innovative Education & Research, 2(1),7 – 15. [6] Eccles, J. (2017). Gendered educational and occupational choices: Applying the Eccles model of achievement- related choices. International Journal of Behavioral Development, 35, 195-201. [7] Hassan, B. (2019). Career maturity of Indian adolescents as a function of self-concept, vocational aspiration and gender, Journal of the Indian Academy of Applied Psychology, 32, 2, 127-133. [8] Iweka, F. (2018). School-type, self-esteem, career aspiration and gender as correlate of students’ academic achievement in junior secondary school integrated science. International Journal of Education, Learning and Development, 5(4), 48 – 54. [9] Mahoney, C. R., Taylor, H. A., & Kanarek, R. B. (2018). Relationship between self-esteem, social support and students’ educational achievement among high school students in United States. Physiology & Behaviour, 85 (5), 635–645. [10] Mitchell, L. K., & Krumboltz, J. D. (1996). Krumboltz learning theory of career choice development. In D. Brown, L. Brooks (Ed), Career choice development (3rd Eds.). San Francisco, CA. Jossey-Bass. [11] Narimani, M., & Mousazadeh, T. (2018). 5. Conclusion This study has shown through its findings that career aspiration has significant relationship with academic achievement of learners with hearing impairment in special secondary schools in North Eastern, Nigeria. Thus, the study has justified the influence of mindset by individual students toward brighter future after graduation in term securing well paid job that can make them self-dependence. More so, this study has shown that gender is not a barrier toward learners’ academic achievement, but their level of aspiration toward future career. In this case, students that aspired better job or a well-paid job after graduation will aware of the need to put more efforts toward study in order to attain require grade that can make them achieved their aspired career. In short, as career aspiration for individual students high their 765 International Journal of Science and Research Archive, 2023, 09(02), 760–767 chances to make good academic performance is also high, simply due to zeal to excel in academic activities in order to achieve the targeted career. chances to make good academic performance is also high, simply due to zeal to excel in academic activities in order to achieve the targeted career. Recommendations  There is need for teachers in the special school in north eastern Nigeria to make effort in giving students more supports in terms of guidance and orientation on various career that can encourage their readiness to learn and perform better in academic.  There should be concerted efforts through management in special schools in north eastern Nigeria to form partnership with parents in encouraging the learners with hearing impairment on various career opportunities waiting for them after graduation, such inputs will increase their commitment toward academic as well as their performance in education. Disclosure of conflict of interest No conflict of interest to be disclosed. No conflict of interest to be disclosed. Statement of informed consent Informed consent was obtained from all individual participants included in the study. Informed consent was obtained from all individual participants included in the study. Compliance with ethical standards Disclosure of conflict of interest References Comparing self-esteem and self-concept of handicapped and normal students. Procedia-Social and Behavioral Sciences, 2(2), 1554-1557. [12] O’Brien, K. M. (2019). The influence of psychological separation and parental attachment on the career development of adolescent. Journal of Vocational Behavior, 48, 257-274. [13] Omollo, A. E., & Yambo, O. J. M. (2017). Influence of peer pressure on secondary school students drop out in Rongo sub-county, Migori county, Kenya. Journal of Education and Practice, 8(9), 20 – 27. 766 International Journal of Science and Research Archive, 2023, 09(02), 760–767 [14] Oyesiku, K. (2019). Relationship between self-esteem and academic achievement amongst pre-university students in the South Western, Nigeria. International Journal of Educational Management, 20(6), 466-479. [15] Pattanayak, M. B., & Naik, P. K (2020). Career aspirations and career development barriers of tribal students in the Salboni block of Jangal Mahal. Journal of International Academic Research for Multidisciplinary, 2(3), 655 – 678. [16] Punch, R., Hyde, M., & Creed, P. A. (2021). Issues in the school-to-work transition of hard of hearing adolescents. American Annals of the Deaf, 149(1), 28–38. [17] Rishaelly, C. E. (2019). Factors influencing academic performance of hearing-impaired students in inclusive education: a case of Moshi technical secondary school. An Unpublished M.Ed. Thesis, Open University of Tanzania. [18] Szymanski, E. M., Hershenson, D. B., Enright, M. S., & Ettinger, J. M. (2018). Career development theories, constructs, and research: Implications for people with disabilities. In E. M. Szymanski & R. M. Parker (Eds.), Work and disability: Issues and strategies in career development and job placement. Austin, TX: Pro-ed. [19] Udonsa, A. E. (2020). Salient issues in students’ poor performance in mathematics at public examinations in Nigeria: A case study of selected secondary schools in Adamawa State. Journal of Research in Education and Society, 6(1), 23 – 35. [20] Ugwuanyi, L. T. (2018). Effect of three sign language modes on reading comprehension of pupils with hearing impairment. Unpublished Ph.D Thesis, University of Nigeria, Nsukka. [21] Weisel, A., & Cinamon, R. G. (2019). Hearing, deaf, and hard-of-hearing Israeli adolescents’ evaluations of deaf men and deaf women’s occupational competence. Journal of Deaf Studies and Deaf Education, 10, 376–389. 767
https://openalex.org/W2515333699	https://europepmc.org/articles/pmc5021837?pdf=render	English	null	Studies on clinical signs and biochemical alteration in pregnancy toxemic goats	Veterinary world/Veterinary World	2,016	cc-by	4,877	RESEARCH ARTICLE Open Access RESEARCH ARTICLE Open Access Veterinary World, EISSN: 2231-0916 Veterinary World, EISSN: 2231-0916 Available at www.veterinaryworld.org/ Veterinary World, EISSN: 2231-0916 Available at www.veterinaryworld.org/Vol.9/August-2016/12.pdf Copyright: Vasava, et al. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/ by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http:// creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Ethical approval Samples were collected from clinical cases coming to Veterinary Hospital at Veterinary College, Anand Agricultural University, Anand. Hence, this particular study did not require ethical approval. Copyright: Vasava, et al. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/ by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http:// creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Studies on clinical signs and biochemical alteration in pregnancy toxemic goats Prasannkumar R. Vasava1, R. G. Jani1, H. V. Goswami2, S. D. Rathwa3 and F. B. Tandel1 1. Department of Veterinary Medicine, College of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand - 388 001, Gujarat, India; 2. Department of Veterinary Anatomy, College of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand - 388 001, Gujarat, India; 3. Department of Veterinary Physiology & Biochemistry, College of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand - 388 001, Gujarat, India. j Corresponding author: Prasannkumar R. Vasava, e-mail: prvasava6@gmail.com, RGJ: vetjani@gmail.com, HVG: harshgoswami2001@gmail.com, SDR: sawanrathwa@gmail.com, FBT: tandelfalguni1890@gmail com Corresponding author: Prasannkumar R. Vasava, e-mail: prvasava6@gmail.com, RGJ: vetjani@gmail.com, HVG: harshgoswami2001@gmail.com, SDR: sawanrathwa@gmail. Corresponding author: Prasannkumar R. Vasava, e mail: prvasava RGJ: vetjani@gmail.com, HVG: harshgoswami2001@gmail.com, SDR: sawa FBT: tandelfalguni1890@gmail.com g g , FBT: tandelfalguni1890@gmail.com j g , g g , FBT: tandelfalguni1890@gmail.com g g Received: 15-03-2016, Accepted: 14-07-2016, Published online: 18-08-2016 doi: 10.14202/vetworld.2016.869-874 How to cite this article: Vasava PR, Jani RG, Goswami HV, Rathwa SD, Tandel FB (2016) Studies on clinical signs and biochemical alteration in pregnancy toxemic goats, Veterinary World, 9(8): 869-874. Introduction bodies in blood circulation, and thus increasing the susceptibility to pregnancy toxemia [3]. Pregnancy toxemia, also known as “twin-lamb” disease, is a metabolic disorder of pregnant small ruminants, caused by an abnormal metabolism of car- bohydrates and fats, which occurs at the final stage of pregnancy [1]. Obese ewes or does carrying mul- tiple fetuses are at higher risk to develop the disease because of the limited space for adequate intake of feed [2]. Rapid fetal development at the late gestation causes rapid mobilization of the fat stores to assure adequate energy. The liver also increases gluconeo- genesis to facilitate glucose availability to the fetus. However, in the negative energy balance (NEB), this increased mobilization may overwhelm the capacity of the liver resulting in hepatic lipidosis. At the same time, ketone bodies are being produced and accu- mulated, which eventually leads to excessive ketone The early detection of pregnancy toxemia in sus- ceptible animals is essential for successful treatment. In clinical pregnancy toxemia, the diagnosis is based on history, clinical signs of hepatic encephalopathy, and the results of serum biochemical analyses [4]. While clinical pregnancy toxemia in sheep was relatively well studied, there is a paucity of informa- tion regarding metabolic changes in the clinical form of the disease, especially in goats. So, this study was planned. Abstract Aim: This study was planned to reveal the clinical signs and biochemical alterations in pregnancy toxemi Materials and Methods: Blood samples were collected from 20 healthy pregnant and 45 pregnancy toxemic goats and analyzed biochemically. Results: The most significant clinical findings were observed in naturally affected goats with pregnancy toxemia included anorexia, recumbency, lethargy, opisthotonos, dropped head, periodic convulsion, sweetish fruity odor from breath, apparent blindness, bloat, grinding of teeth, and frothy salivation. In this study, the level of serum glutamic-oxaloacetic transaminase (SGOT) (84.23±1.44 IU/L), serum glutamic pyruvic transaminase (SGPT) (216.01±4.07 IU/L), blood urea nitrogen (BUN) (22.24±0.31 mg/dl), creatinine (2.13±0.09 mg/dl), β-hydroxybutyric acid (BHBA) (0.46±0.83 mmol/L), and non-esterified fatty acid (NEFA) (1.67±0.71 mmol/L) was significantly higher whereas glucose (30.89±0.38 mg/dl) and calcium (8.10±0.20 mg/dl) levels were significantly decreased in pregnancy toxemic goats as compared to healthy goats. Conclusion: The goats with pregnancy toxemia exhibited clinical signs include anorexia, recumbency, sweetish fruity odor from breath, apparent blindness, bloat, grinding of teeth, and frothy salivation. Biochemically, there were significantly decreased the level of glucose and calcium, and increased level of SGPT, SGOT, BUN, creatinine, BHBA, and NEFA in the pregnancy toxemic goats. Keywords: alteration, biochemistry, clinical signs, goat, pregnancy toxemia. Study area Anand district is situated at latitude 22° N and longitude 72° E with 2939.9 km2 areas in Gujarat, India, and witnessed a temperature range of 35-38°C with a maximum of 42°C, relative humidity of 57-55% and rainfall about 1-4 inch. The season in this area can Veterinary World, EISSN: 2231-0916 869 d.org/Vol.9/August-2016/12.pdf Table-1: Vital signs observed in pregnancy toxemic and healthy goats. Parameter (Units) Pregnancy toxemia infected (N=45) Healthy pregnant (N=20) Rectal temperature (°F) 102.9±0.18 102.6±0.17 Heart rate (per minute) 81.16±0.75* 76.25±3.67 Respiration rate (per minute) 28.3±0.31 27±0.47 p<0.05 (significant), N=Number of goats Table-2: Clinical variant recorded from pregnancy toxemic goats. Clinical signs Total number of affected goats shown clinical symptoms (N=45) Percentage Anorexia 45 100.00 Recumbency 45 100.00 Lethargy 39 86.67 Opisthotonos 33 73.33 Dropped head 28 62.22 Periodic convulsion 26 57.78 Sweetish fruity odor from breath 23 51.11 Apparent blindness 19 42.22 Bloat 18 40.00 Grinding of teeth 17 37.78 Frothy salivation 11 24.44 Star gazing 07 15.56 N=Number of goats Figure-1: Mean±standard error values of vital signs of healthy pregnant and pregnancy toxemic goats. Available at www.veterinaryworld.org/Vol.9/August-2016/12.pdf Table-1: Vital signs observed in pregnancy toxemic and healthy goats. Parameter (Units) Pregnancy toxemia infected (N=45) Healthy pregnant (N=20) Rectal temperature (°F) 102.9±0.18 102.6±0.17 Heart rate (per minute) 81.16±0.75 76.25±3.67 Respiration rate (per minute) 28.3±0.31 27±0.47 p<0.05 (significant), N=Number of goats Table-2: Clinical variant recorded from pregnancy toxemic goats. Clinical signs Total number of affected goats shown clinical symptoms (N=45) Percentage Anorexia 45 100.00 Recumbency 45 100.00 Lethargy 39 86.67 Opisthotonos 33 73.33 Dropped head 28 62.22 Periodic convulsion 26 57.78 Sweetish fruity odor from breath 23 51.11 Apparent blindness 19 42.22 Bloat 18 40.00 Grinding of teeth 17 37.78 Frothy salivation 11 24.44 Star gazing 07 15.56 N=Number of goats Table-1: Vital signs observed in pregnancy toxemic and healthy goats. be broadly classified into hot and dry summer from March to June, rainy (monsoon) season from July to October, and the winter (mild) season from November to February. be broadly classified into hot and dry summer from March to June, rainy (monsoon) season from July to October, and the winter (mild) season from November to February. Study period The data, recorded from the case records of Department of Teaching Veterinary Clinical Complex, Veterinary College, Anand, were compiled and ana- lyzed for a period of 6-month from June 1, 2015, to December 31, 2015. Sample collection All the cases of pregnancy toxemia were diag- nosed using Rothera’s qualitative test from urine samples [5]. The blood samples were collected from jugular vein in 20 healthy pregnant as control and 45 pregnancy toxemic goats to carry out different laboratory and biochemical tests by standard kits. Serum glutamic pyruvic transaminase (SGPT) and serum glutamic-oxaloacetic transaminase (SGOT) were estimated by modified IFCC method (Coral Pvt. Ltd). Glucose, blood urea nitrogen (BUN), cal- cium, magnesium, phosphorus, and creatinine were estimated by glucose oxidase-peroxidase, diacetylm- onoxime, o-cresolphthalein complexone, calmagite, Molybdate U.V., and Mod. Zaffe’s Kinetic method. β-hydroxyl butyric acid (BHBA) was estimated by D-3-hydroxybutyrate kit and non-esterified fatty acid (NEFA) were estimated by NEFA Kit (Randox Laboratories Ltd). Figure-1: Mean±standard error values of vital signs of healthy pregnant and pregnancy toxemic goats. Statistical analysis Data, obtained from biochemical parameters, were statistically analyzed by Student’s t-test as per the method described by Snedecor and Cochran [6]. T-test: Two samples assuming unequal variance were used for comparing of pregnancy toxemic and healthy goats biochemical parameters. Variables with p<0.05 were considered as statistically “sig- nificant,” variables with p<0.01 were considered as statistically “highly significant,” and vari- ables with p>0.05 were considered as statistically “non-significant.” Figure-1: Mean±standard error values of vital signs of healthy pregnant and pregnancy toxemic goats. Results Due to lack of energy and hypocalcemia, there was recumbency in the pregnancy toxemic goat which was in agreement with Scott and Woodman [11], El-Sebaie [12], Andrews [13], Balikci et al. [9], Barakat et al. [14], Hefnawy et al. [19], Al-Qudah [15], Abdelaal et al. [16], and Reddy et al. [10]. 23 (51.11%) goats presented with sweetish fruity odor from breath. Similar clinical findings in goat with pregnancy toxemia were recorded by Balikci et al. [9], Hefnawy et al. [20], Abdelaal et al. [16], and Rani et al. [18]. The sweetish odor which was a typical characteristic of ketone bodies which was increased in pregnancy toxemia. 11 (24.44%) goats presented with frothy salivation were in agreement with Balikci et al. [9] and Barakat et al. [14]. Chew movement and salivation were seen in the nervous form of preg- nancy toxemia in does. The teeth grinding behavior in 17 (37.78%) goats suffered from pregnancy toxemia was in agreement with Balikci et al. [9], Abdelaal at al. [16], Reddy et al. [10], and Rani et al. [18]. It was due to the cerebral hypoglycemia which results teeth gnashing behavior. 39 (86.67%) goats presented with lethargy in agreement with Andrews [13] and Reddy et al. [10]. It was due to lack of adequate glucose in body for the production of energy. 19 (42.22%) goats presented with apparent blindness were in agreement with El-Sebaie [12], Andrews [13], Barakat et al. [14], and Al-Qudah [15]. Nervous degeneration was due to cerebral hypoglycemia resulted into apparent blind- ness. 22 (57.58%) goats present with convulsion due to nervous manifestation because of hypoglycemia and ketonemia were in agreement with Hefnawy et al. [20]. 18 (40.00%) goats presented with bloat were in agreement with Souto et al. [17], Rodolfo et al. [7], and Rani et al. [18] and the bloat was due to longer time recumbency, anorexia, stasis of rumen motil- ity, and ketoacidosis. 28 (62.22%) goats presented with dropped head were in agreement with Abdelaal et al. [16] and Reddy et al. [10]. Dropped head condi- tion was nervous manifestation due to lack of energy in the nervous form of pregnancy toxemia. 34 (75.56%) goats, presented with the extension of head, were in agreement with Abdelaal et al. [16]. 7 (15.56%) goats, Results Figure-2: Clinical findings in pregnancy toxemic goats. The vital signs like rectal temperature and res- piration rate were normal, but heart rate was sig- nificantly increased than normal goats. The most significant clinical findings were observed in natu- rally affected goat with pregnancy toxemia included anorexia (100.00%), recumbency (100.00%), leth- argy (86.67%), opisthotonos (73.33%), dropped head (62.22%), periodic convulsion (57.78%), sweetish fruity odor from breath (51.11%), apparent blindness (42.22%), bloat (40.00%), grinding of teeth (37.78%), and frothy salivation (24.44%) (Tables-1 and 2; Figures-1 and 2). Figure-2: Clinical findings in pregnancy toxemic goats. Figure-2: Clinical findings in pregnancy toxemic goats. The study was aimed to evaluate the bio- chemical indicators in goats positive for naturally occurring pregnancy toxemia in comparison with normal healthy goats (Table-1). The mean values of SGPT (IU/L), SGOT (IU/L), glucose (mg/dl), normal healthy goats (Table-1). The mean values of SGPT (IU/L), SGOT (IU/L), glucose (mg/dl), 870 Veterinary World, EISSN: 2231-0916 Available at www.veterinaryworld.org/Vol.9/August-2016/12.pdf BUN (mg/dl), creatinine (mg/dl), calcium (mg/dl), magnesium (mg/dl), phosphorus (mg/dl), BHBA (mmol/L) and NEFA (mmol/L) in 20 healthy preg- nant goats were 50.02±0.68 (IU/L), 132.80±2.62 (IU/L), 64.62±1.19 (mg/dl), 18.57±0.59 (mg/dl), 0.99±0.11 (mg/dl), 9.55±0.34 (mg/dl), 3.04±0.14 (mg/dl), 6.91±0.52 (mg/dl), 0.46±0.83 (mmol/L) and 0.29±0.91 (mmol/L), respectively. Among var- ious biochemical parameters evaluated from 45 pregnancy toxemic goats, the mean values of SGPT (84.23±1.44 IU/L), SGOT (216.01±4.07 IU/L), BUN (22.24±0.31 mg/dl), creatinine (2.13±0.09 mg/dl), BHBA 4.82±0.27 (mmol/L), and NEFA 1.67±0.71 (mmol/L) increased significantly in goats with pregnancy toxemia. Whereas, the level of glucose (30.89±0.38 mg/dl) and calcium (8.10±0.20 mg/dl) decreased significantly in goats with pregnancy tox- emia (Table-3 and Figure-3). heart rate (81.16±0.75/min) substantiated the find- ings of Manokaran et al. [8], Balikci et al. [9], and Reddy et al. [10]. Anorexia was observed in all cases which were in agreement with Scott and Woodman [11], El-Sebaie [12], Andrews [13], Balikci et al. [9], Barakat et al. [14], Al-Qudah [15], Manokaran et al. [8], Abdelaal et al. [16], Souto et al. [17], Reddy et al. [10], Rodolfo et al. [7], and Rani et al. [18]. Depression of feed intake before kid- ding has been considered a major factor in the devel- opment of the pregnancy toxemia. Accumulation of fat in the liver occurred during periods of elevated fat mobilization, especially in goats with excessive fat body reserves at kidding. During this period, incom- plete breakdown of NEFA was responsible for the pro- duction of ketone bodies. Discussion [8], Souto et al. [17], Albay et al. [22], Rodolfo et al. [7], Reddy et al. [10], and Rani et al. [18]. Decreased calcium level might be due to high need of calcium for fetal skeleton development. When doe carry twin or triplet in last trimester, there was a greater risk of the development of pregnancy toxemia. Magnesium and phosphorus level were found in the normal range which substan- tiated the findings of Hefnawy et al. [19] and Ismail et al. [34]. In contrast to the present study, Souto et al. [17] and Rodolfo et al. [7] reported decreased phosphorus level in pregnancy toxemia. Increased SGPT and SGOT level of the pres- ent study were in agreement with report of Barakat et al. [14], Gupta et al. [21], Balikci et al. [9], Hefnawy et al. [19], Abdelaal et al. [16], Albay et al. [22], Anoushepour et al. [23], Reddy et al. [10], Marutsova [24], and Abba et al. [25]. In contrast with the present study, Gupta et al. [21] reported decreased values of SGPT and SGOT. In this study, SGPT and SGOT were increased due to fat mobilization because of NEB and hepatic damage or hepatic lipidosis. Due to energy deficiency, the body used its fatty tissue which reserves as a source of energy and increased response of free circulating free fatty acids that reach to the liver so, subsequent induce fatty infiltration. Increased BHBA level was in agreement with report of Scott and Woodman [11], Ismail et al. [34], Balikci et al. [9], Al-Qudah [15], Hefnawy et al. [19], Gonzalez et al. [39], Abdelaal et al. [16], Olfati et al. [40], Anoushepour et al. [23], Gurdogan et al. [37], Sharma et al. [14], and Marutsova [24]. Increased NEFA level was in agreement with the report of Marteniuk and Herdt [33], Olfati et al. [40], Anoushepour et al. [23], and Sharma et al. [14]. The increases in the serum BHBA and NEFA level could be attributed to the lipolysis of tissue and the release of long-chain fatty acids, which were converted by the liver into ketones in goats. Moreover, these increased could be attributed to disturbance in carbohydrate and fat metabolism leading to hypoglycemia and mobili- zation of fat stores which lead to hepatic ketogenesis according to Rook [41] and Hefnawy et al. [19]. Discussion In this study, rectal temperature and respira- tory rate were found within normal range, which were contrast to Rodolfo et al. [7], who reported increased body temperature. In this study, increased increased body temperature. In this study, increased Figure-3: Mean±standard error values of biochemical parameters of healthy pregnant and pregnancy toxemic goats. Table-3: Biochemical parameters of healthy pregnant and pregnancy toxemia affected goats. Parameters Mean±SE Healthy pregnant (N=20) Pregnancy toxemia (N=45) SGPT (IU/L) 50.02±0.68 84.23±1.44* SGOT (IU/L) 132.80±2.62 216.01±4.07 Glucose (mg/dl) 64.62±1.19 30.89±0.38 BUN (mg/dl) 18.57±0.59 22.24±0.31 Creatinine (mg/dl) 0.99±0.11 2.13±0.09 Calcium (mg/dl) 9.55±0.34 8.10±0.20 Magnesium (mg/dl) 3.04±0.14 2.74±0.09 Phosphorus (mg/dl) 6.91±0.52 6.72±0.15 BHBA (mmol/L) 0.46±0.83 4.82±0.27 NEFA (mmol/L) 0.29±0.91 1.67±0.71 p<0.01 (highly significant). N=Number of goats, SGOT=Serum glutamic-oxaloacetic transaminase, SGPT=Serum glutamic pyruvic transaminase, BUN=Blood urea nitrogen, BHBA=β-hydroxybutyric acid Table-3: Biochemical parameters of healthy pregnant and pregnancy toxemia affected goats. Table-3: Biochemical parameters of healthy pregnant and pregnancy toxemia affected goats. Figure-3: Mean±standard error values of biochemical parameters of healthy pregnant and pregnancy toxemic goats. Table-3: Biochemical parameters of healthy pregnant and pregnancy toxemia affected goats. Parameters Mean±SE Healthy pregnant (N=20) Pregnancy toxemia (N=45) SGPT (IU/L) 50.02±0.68 84.23±1.44 SGOT (IU/L) 132.80±2.62 216.01±4.07 Glucose (mg/dl) 64.62±1.19 30.89±0.38 BUN (mg/dl) 18.57±0.59 22.24±0.31 Creatinine (mg/dl) 0.99±0.11 2.13±0.09 Calcium (mg/dl) 9.55±0.34 8.10±0.20 Magnesium (mg/dl) 3.04±0.14 2.74±0.09 Phosphorus (mg/dl) 6.91±0.52 6.72±0.15 BHBA (mmol/L) 0.46±0.83 4.82±0.27 NEFA (mmol/L) 0.29±0.91 1.67±0.71 p<0.01 (highly significant). N=Number of goats, SGOT=Serum glutamic-oxaloacetic transaminase, SGPT=Serum glutamic pyruvic transaminase, BUN=Blood urea nitrogen, BHBA=β-hydroxybutyric acid Parameters Mean±SE Healthy pregnant (N=20) Pregnancy toxemia (N=45) SGPT (IU/L) 50.02±0.68 84.23±1.44 SGOT (IU/L) 132.80±2.62 216.01±4.07 Glucose (mg/dl) 64.62±1.19 30.89±0.38 BUN (mg/dl) 18.57±0.59 22.24±0.31 Creatinine (mg/dl) 0.99±0.11 2.13±0.09 Calcium (mg/dl) 9.55±0.34 8.10±0.20 Magnesium (mg/dl) 3.04±0.14 2.74±0.09 Phosphorus (mg/dl) 6.91±0.52 6.72±0.15 BHBA (mmol/L) 0.46±0.83 4.82±0.27 NEFA (mmol/L) 0.29±0.91 1.67±0.71 p<0.01 (highly significant). N=Number of goats, SGOT=Serum glutamic-oxaloacetic transaminase, SGPT=Serum glutamic pyruvic transaminase, BUN=Blood urea nitrogen, BHBA=β-hydroxybutyric acid Figure-3: Mean±standard error values of biochemical parameters of healthy pregnant and pregnancy toxemic goats. Figure-3: Mean±standard error values of biochemical parameters of healthy pregnant and pregnancy toxemic goats. Veterinary World, EISSN: 2231-0916 871 Available at www.veterinaryworld.org/Vol.9/August-2016/12.pdf presented with stargazing posture due to the nervous degeneration, were in agreement with Andrews [13], Barakat et al. [14], and Rani et al. [18]. 33 (73.33%) goats presented with opisthotonos were in agreement with Reddy et al. [10] and the opisthotonos was due to hypoglycemia, ketonemia, and neurodegeneration. et al. [19], Manokaran et al. Discussion Increased BUN and creatinine level were in agreement with report of Kolb and Kaskom [26], Barakat et al. [14], Hefnawy et al. [19], Lima et al. [4], Abdelaal et al. [16], Souto et al. [17], Anoushepour et al. [23], Rodolfo et al. [7], and Reddy et al. [10]. In this study, BUN and creatinine were increased sug- gested that involvement of kidney due to catabolism. Increased BUN and creatinine attributed to severe kidney dysfunction accompanied with acidosis which is the result of increased ketone body in general cir- culation. There was fatty infiltration in tubular epi- thelium of kidney in pregnancy toxemic goat leads to elevation of both parameters. Conclusion The goats with naturally occurring pregnancy toxemia exhibited clinical signs includes anorexia, recumbency, sweetish fruity odor from breath, appar- ent blindness, bloat, grinding of teeth, and frothy sal- ivation. Characteristic biochemical pattern associated with pregnancy toxemia in goats showed that there were decreased the level of glucose and calcium, and increased levels of SGPT, SGOT, BUN, creatinine, BHBA and NEFA. p Decreased glucose level of the present study was in agreement with result of many researcher such as McClymont and Setchell [27], Robert [28], Lindsay and Pethick [29], Buswell et al. [30], Cantley et al. [31], El-Sebaie [12], Scott and Woodman [11], Andrews [13], Henze et al. [32], Marteniuk and Herdt [33], Gupta et al. [21], Barakat et al. [14], Ismail et al. [34], Schlumbohm and Harmeyer [35], Balikci et al. [9], Hefnawy et al. [20], Al-Qudah [15], Hefnawy et al. [19], Manokaran et al. [8], Abdelaal et al. [16], Anoushepour et al. [23], Albay et al. [22], Sharma et al. [36], Reddy et al. [10], Gurdogan et al. [37] and Rani et al. [18]. However, in contrast to the present study, report of Souto et al. [17] and Lima et al. [4] showed hyperglycemia in the later stages of pregnancy toxemia when the fetuses were dead. Hypoglycemia was due to dietary deficiency of net energy along with the increased demand for energy in the later part of pregnancy due to twin or triplet. Due to increased BHBA, there was NEB, which causes hypoglycemic effect, reduced food intake and glucose turnover leads to pregnancy toxemia. In the present surveillance, from June to December, the most of animals which shown the clini- cal sign of recumbency, were suffered from pregnancy toxemia which was confirmed by biochemical tests and urine analysis. Authors’ Contributions This study was a part of PRV’s original research work during M.V.Sc. thesis program. RGJ had designed the plan of work. HVG and FBT helped during sampling, statistical analysis, and manuscript preparation. SDR helped in the laboratory work. All the authors read and approved the final manuscript. References Manokaran, S.K., Kumar, R., Palanisamy, M., Raguvaran, R., Mohanasundaram, N., Napolean, R.E. and Selvaraju, M. (2011) Pregnancy toxaemia and hypocalcae- mia in a Jamnapari doe. Indian J. Small Anim. Res., 17(2): 250-251. 28. Robert, J.S. (1971) Veterinary Obstetrics and Genital Diseases. 2nd ed. CBS Publisher and Distributors, New Delhi, India. p313-316. 29. Lindsay, D.B. and Pethick, D.W. (1983) In: Riis, P.M., edi- tor. Dynamic Biochemistry of Animal Production. Elsevier, Amsterdam. p431. 9. Balikci, E., Yildiz, A. and Gurdogan, F. (2009) Investigation on some biochemical and clinical parameters for pregnancy toxemia in Akkaraman ewes. J. Anim. Vet. Adv., 8(7): 1268-1273. p 30. Buswell, J.S., Haddy, J.P. and Bywater, R.J. (1986) Treatment of pregnancy toxaemia in sheep using a concen- trated oral rehydration solution. Vet. Rec., 118: 208-209. 10. Reddy, B.S., Jythi, K., Reddy, Y.V.P., Rao, K.P., Sivajothi, S. and Ganesan, A. (2014) Pregnancy toxaemia associated with dystocia in a Nellore brown ewe. Adv. Appl. Sci. Res., 5(3): 325-327. y 31. Cantley, C.E.I., Ford, C.M. and Health, M.F. (1991) Serum fructosamine in ovine pregnancy toxaemia: A possible prognostic index. Vet. Rec., 128: 525-526. 11. Scott, P.R. and Woodman, M.P. (1993) An outbreak of preg- nancy toxaemia in a flock of Scottish Blackface sheep. Vet. Rec., 133(24): 597-598. p g 32. Henze, P., Bickhardt, K., Fuhrmann, H. and Sallmann, H.P. (1998) Spontaneous pregnancy toxaemia (ketosis) in sheep and the role of insulin. J. Vet. Med., A45: 255-266. 12. El-Sebaie, A.H. (1995) Caprine Ketosis in Does 3rd Science Congress Egyptian Society, Cattle Diseases. p368-371. 33. Marteniuk, J.V. and Herdt, T.H. (1998) Pregnancy toxaemia and ketosis of ewes and does. Vet. Clin. North Am. Food Anim. Pract., 4(2): 307-315. 13. Andrews, A. (1997) Pregnancy toxaemia in the ewe. Practice, 19: 306-312. doi:10.1136/inpract.19.6.306. ( ) 34. Ismail, B.Z.A., AI-Majali, A.M., Amireh, F. and Al-Rawashdeh, O. (2008) Metabolic profiles in goat in late pregnancy with and without subclinical pregnancy toxae- mia. Vet. Clin. Pathol., 37(4): 434-437. 14. Barakat, S.E.M., Al-Bhanasawi, G.E., Elazhari, N.M. and Bakhiet, A.O. (2007) Clinical and sero-biochemical studies on naturally occurring pregnancy toxaemia in Shamia goats. J. Anim. Vet. Adv., 6(6): 768-772. ( ) 35. Schlumbohm, C. and Harmeyer, J. (2008) Twin-pregnancy increases susceptibility of ewe to hypoglycaemic stress and pregnancy toxaemia. Res. Vet. Sci., 84: 286-299. 15. Al-Qudah, K.M. (2011) Oxidant and antioxidant profile of hyperketonemic ewes affected by pregnancy toxemia. Vet. Clin. Pathol., 40(1): 60-65. 16. Abdelaal, A., Zaher, H., Elgaml, S.A. References 1. Brozos, C., Mavrogianni, V.S. and Fthenakis, G.C. (2011) Treatment and control of peri-parturient metabolic diseases: Pregnancy toxemia, hypocalcemia, hypomagnesemia. Vet. Clin. North Am. Food Anim. Pract., 27: 106-107. 22. Albay, M.K., Karakurum, M.C., Sahinduran, S., Sezer, K. and Yildiz, R. (2014) Selected serum biochemical parame- ters and acute phase protein levels in a herd of Saanen goats showing signs of pregnancy toxaemia. Vet. Med., 59(7): 336-342. 2. Ermilio, E.M. and Smith, M.C. (2011) Treatment of emer- gency conditions in sheep and goats. Vet. Clin. North Am. Food Anim. Pract., 27: 105-106. 2. Ermilio, E.M. and Smith, M.C. (2011) Treatment of emer- gency conditions in sheep and goats. Vet. Clin. North Am. Food Anim. Pract., 27: 105-106. 23. Anoushepour, A., Mottaghian, P. and Mehdi, S. (2014) The comparison of some biochemical parameters in hyperke- tonemic and normal ewes. Eur. ‎J. Exp. Biol., 4(3): 83-87. 3. Menzies, P.I. (2011) Pregnancy Toxemia in Ewes: Hepatic Lipidosis: Merck Veterinary Manual. Merial, USA. 3. Menzies, P.I. (2011) Pregnancy Toxemia in Ewes: Hepatic Lipidosis: Merck Veterinary Manual. Merial, USA. 24. Marutsova, V. (2015) Changes in blood enzyme activities in ewes with ketosis. Int. J. Adv. Res., 3(6): 462-473. 4. Lima, M.S., Pascoal, R.A. and Stilwell, S.T. (2012) Glycaemia as a sign of the viability of the foetuses in the last days of gestation in dairy goats with pregnancy toxae- mia. Ir. Vet. J., 65(1): 1. 25. Abba, Y., Abdullah, F.F.J., Chung, E.L.T., Sadiq, M.A., Mohammed, K., Osman, A.Y., Rahmat, N.B.R., Razak, I.A., Lila, M.A.M., Haron, A.W. and Saharee, A.A. (2015) Biochemical and pathological findings of pregnancy toxaemia in Saanen doe: A case report. J. Adv. Vet. Anim. Res., 2(2): 236-239. 5. Fox, F.H. (1971) Clinical diagnosis and treatment of keto- sis. J. Dairy Sci., 54: 974-985. 6. Snedecor, G.W. and Cochran, W.G. (1994) Statistical Methods. 6th ed. Oxford and JBH Publishing, New York. 26. Kolb, E. and Kaskom, S. (2004) Patho-biochemical aspects of pregnancy ketosis in sheep and goats. Tierarztl. Umsch., 59: 374-380. 7. Rodolfo, S.J.C., Augusto, A.J.B., Mendonça, C.L., Cleyton, C.C.D., Alonso, S.F.P., Jobson, C.F.P., Elizabeth, L.H.F. and Pierre, S.C. (2014) Biochemical, electrolytic and hormonal findings in goats affected with pregnancy toxemia. Pesqui. Vet. Bras., 33(10): 1174-1182. 27. McClymont, G.L. and Setchell, B.P. (1956b) Ovine preg- nancy toxaemia IV. Insulin induced hypoglycaemic enceph- alopathy in sheep and its implications as regards pathogen- esis of the disease. Aust. Vet. J., 32: 97-109. 8. Acknowledgments This study was funded by College of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand, Gujarat. Authors are thank- ful to the staff of Teaching Veterinary Clinical Decreased calcium level of the present find- ings was in agreement with results of Jopp and Quinlivan [38], Anoushepour et al. [23], Hefnawy Veterinary World, EISSN: 2231-0916 872 Available at www.veterinaryworld.org/Vol.9/August-2016/12.pdf pregnancy toxaemia. Pesqui. Vet. Bras., 33(10): 1174-1182. Complex and Department of Veterinary Physiology and Biochemistry at College of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand, Gujarat, as well as goat-owners of different areas of Anand town for their valuable cooperation. pregnancy toxaemia. Pesqui. Vet. Bras., 33(10): 1174-1182. 18. Rani, R.U., Palanichamy, V. and Muruganandan, B. (2015) Clinical and serobiochemical studies on pregnancy toxae- mia in does. Int. J. Curr. Innov. Res., 1(4): 102-104. 19. Hefnawy, A.E., Shousha, S. and Youssef, S. (2011) Haematobiochemical profile of pregnant and experimen- tally pregnancy toxaemic goats. J. Basic Appl. Chem., 1(8): 65-69. Competing Interests ( ) 20. Hefnawy, A.E., Youssef, S. and Shousha, S. (2010) Some immunohormonal changes in experimentally pregnant tox- aemic goats. Vet. Med. Int., DOI: 10.4061/2010/768438. The authors declare that there is no conflict of interests. 21. Gupta, V.K., Sharma, S.D., Vihan, V.S. and Kumar, A. (2008) Serum enzymes and thyroid hormone in sub-clinical ketosis in goats and sheep reared under organized farming system. Indian. J. Anim. Sci., 78(11): 1199-1201. References and Abdallah, H. (2013) Prognostic value of serum cardiac troponin T and nitric oxide as cardiac biomarkers in pregnancy toxaemic goats. Glob. Vet., 11(6): 817-823. 36. Sharma, N., Kumar, A., Kumar, R., Pawaiya, R.V.S. and Chaturvedi, V. (2014) Metabolic profiling for diagnosis and control of metabolic diseases in goats. CIRG Annu. Rep., (2013-14) 4: 64-65. 37. Gurdogan, F., Balıkci, E. and Yildiz, A. (2014) Some acute phase proteins, oxidative stress biomarkers and antioxidant enzyme activities in ewes with pregnancy toxaemia. IJVR., 48(15): 297-299. 17. Souto, R.J.C., Afonso, J.A.B., Mendonça, C.L., Carvalho, C.C.D., Alonso, P., Filho, S., Cajueiro, F.P., Lima, E.H.F. and Soares P.C. (2013) Biochemical, elec- trolytic and hormonal findings in goats affected with Veterinary World, EISSN: 2231-0916 873 Available at www.veterinaryworld.org/Vol.9/August-2016/12.pdf 38. Jopp, A.J. and Quinlivan, T.D. (1981) Ovine post-parturient hypomagnesaemia ketosis. NZ. Vet. J., 29(3): 37-38. 39. Gonzalez, F.H.D., Hernandez, F., Madrid, J., Martinez- Subiela, S., Tvarijonaviciute, A., Ceron, J.J. and Tecles, F. (2011) Acute phase proteins in experimentally induced preg- nancy toxemia in goats. J. Vet. Diagn. Invest., 23: 57-62. Veterinary World, EISSN: 2231-0916 ( ) 41. Rook, J.S. (2000) Pregnancy toxaemia of ewes, does, and beef cows. Vet. Clin. North Am. Food Anim. Pract., 16: 293-317. 38. Jopp, A.J. and Quinlivan, T.D. (1981) Ovine post-parturient hypomagnesaemia ketosis. NZ. Vet. J., 29(3): 37-38. 39. Gonzalez, F.H.D., Hernandez, F., Madrid, J., Martinez- Subiela, S., Tvarijonaviciute, A., Ceron, J.J. and Tecles, F. (2011) Acute phase proteins in experimentally induced preg- nancy toxemia in goats. J. Vet. Diagn. Invest., 23: 57-62. 40. Olfati, A., Moghaddam, G. and Bakhtiari, M. (2013) Diagnosis, treatment and prevention of pregnancy toxaemia in ewes. Int. J. Adv. Biol. Biomed. Res., 1(11): 1452-1456. 41. Rook, J.S. (2000) Pregnancy toxaemia of ewes, does, and beef cows. Vet. Clin. North Am. Food Anim. Pract., 16: 293-317. ****** Available at www.veterinaryworld.org/Vol.9/August-2016/12.pdf 40. Olfati, A., Moghaddam, G. and Bakhtiari, M. (2013) Diagnosis, treatment and prevention of pregnancy toxaemia in ewes. Int. J. Adv. Biol. Biomed. Res., 1(11): 1452-1456. 40. Olfati, A., Moghaddam, G. and Bakhtiari, M. (2013) Diagnosis, treatment and prevention of pregnancy toxaemia in ewes. Int. J. Adv. Biol. Biomed. Res., 1(11): 1452-1456. 41. Rook, J.S. (2000) Pregnancy toxaemia of ewes, does, and beef cows. Vet. Clin. North Am. Food Anim. Pract., 16: 293-317. 41. Rook, J.S. (2000) Pregnancy toxaemia of ewes, does, and beef cows. Vet. Clin. North Am. Food Anim. Pract., 16: 293-317. ****** Veterinary World, EISSN: 2231-0916 874
https://openalex.org/W3135855299	https://www.frontiersin.org/articles/10.3389/fphys.2021.639857/pdf	English	null	Cyclopiazonic Acid-Induced Ca2+ Store Depletion Initiates Endothelium-Dependent Hyperpolarization-Mediated Vasorelaxation of Mesenteric Arteries in Healthy and Colitis Mice	Frontiers in physiology	2,021	cc-by	10,539	ORIGINAL RESEARCH published: 09 March 2021 doi: 10.3389/fphys.2021.639857 Cyclopiazonic Acid-Induced Ca2+ Store Depletion Initiates Endothelium-Dependent Hyperpolarization-Mediated Vasorelaxation of Mesenteric Arteries in Healthy and Colitis Mice Lu Yun Zhang 1, Xiong Ying Chen 1, Hui Dong 1,2* and Feng Xu 1* 1 Department of Pediatric Intensive Care Unit, Children’s Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing, China, 2 Department of Gastroenterology, Xinqiao Hospital, Army Medical University, Chongqing, China Keywords: store-operated calcium entry, endothelium-dependent hyperpolarization, cyclopiazonic acid, colitis, mesenteric arteries Purposes: Since the role of store-operated calcium entry (SOCE) in endothelium- dependent hyperpolarization (EDH)-mediated vasorelaxation of mesenteric arteries in health and colitis is not fully understood, cyclopiazonic acid (CPA), a specific inhibitor of the sarco(endo) plasmic reticulum calcium-ATPases (SERCA), was used as a SOCE activator to investigate its role in normal mice and its alteration in colitis mice. Edited by: Andrew P. Braun, University of Calgary, Canada Edited by: Andrew P. Braun, University of Calgary, Canada Reviewed by: William F. Jackson, Michigan State University, United States Cor de Wit, University of Lübeck, Germany Correspondence: Hui Dong dhxq@tmmu.edu.cn Feng Xu xufeng9899@163.com Reviewed by: William F. Jackson, Michigan State University, United States Cor de Wit, University of Lübeck, Germany Methods: The changes in Ca2+ signaling in vascular endothelial cells (VEC) were examined by single cell Ca2+ imaging and tension of mesenteric arteries in response to CPA were examined using Danish DMT520A microvascular measuring system. Results: CPA activated the SOCE through depletion of the endoplasmic reticulum (ER) Ca2+ in endothelial cells. CPA had a concentration-dependent vasorelaxing effect in endothelium-intact mesenteric arteries, which was lost after endothelial removal. Both nitric oxide (NO) and prostacyclin (PGI2) inhibitors did not affect CPA-induced vasorelaxation; however, after both NO and PGI2 were inhibited, KCa channel blocker [10 mM tetraethylammonium chloride (TEA)] inhibited CPA-induced vasorelaxation while KCa channel activator (0.3 μM SKA-31) promoted it. Two SOCE blockers [30 μM SKF96365 and 100 μM flufenamic acid (FFA)], and an Orai channel blocker (30 μM GSK-7975A) inhibited this vasorelaxation. The inhibition of both Na+/K+-ATPase (NKA) and Na+/Ca2+-exchange (NCX) also inhibited CPA-induced vasorelaxation. Finally, the CPA involved in EDH-induced vasorelaxation by the depletion of ER Ca2+ of mesenteric arteries was impaired in colitis mice. Specialty section: This article was submitted to Vascular Physiology, a section of the journal Frontiers in Physiology Specialty section: This article was submitted to Vascular Physiology, a section of the journal Frontiers in Physiology Received: 10 December 2020 Accepted: 09 February 2021 Published: 09 March 2021 Received: 10 December 2020 Accepted: 09 February 2021 Published: 09 March 2021 INTRODUCTION CPA/SOCE/EDH of mesenteric endothelial cells is altered in the progression of IBD. Therefore, in this study, we aimed to explore the regulatory mechanisms of CPA/SOCE/EDH action on mesenteric arteries in healthy and colitis mice to provide new potential targets for the prevention/treatment of colitis. Ca2+ as an important second messenger plays a critical role in the regulation of cell function and participates in various human physiological processes. In the normal resting state, there is a fine regulation of the cellular Ca2+ levels, such that the free intracellular Ca2+ ([Ca2+]i) is much lower than the extracellular Ca2+. When cells are stimulated, the rapid influx of extracellular Ca2+ increases the concentration of [Ca2+]i, which is an important signal that triggers many physiological activities in the cells (Garland et al., 2017). Putney first proposed the concept of the store-operated calcium entry (SOCE), a physiological phenomenon that the depletion of Ca2+ store in the endoplasmic reticulum (ER) activates the influx of extracellular Ca2+ (Putney, 1990). The molecular mechanism of the SOCE is comprised of the STIM protein of the endoplasmic reticulum membrane and the Orai protein family of the cell membrane. The STIM protein senses a decrease in the ER Ca2+, and activates the Orai protein located on the cell membrane through protein-protein interactions, thereby causing the influx of extracellular Ca2+ (Liou et al., 2005; Zhang et al., 2006). Under physiological conditions, the SOCE can be activated by GPCR/PLC/IP3-mediated ER Ca2+ release (Taylor, 2006). Cell Culture Human umbilical vein endothelial cells (HUVECs; American Type Culture Collection, Manassas, VA, United States) were cultured in RPMI-1640 (Hyclone, Waltham, MA, United States) containing 10% fetal bovine serum (FBS; Gibco, Gaithersburg, MD, United States) and 1% Penicillin–Streptomycin (Beyotime Biotechnology, China) at 37°C under 5% CO2 and saturated humidity. Cells were plated on glass coverslips about 24 h before experiments. Inflammatory bowel disease (IBD) is a group of chronic inflammatory diseases, including Crohn’s disease (CD) and ulcerative colitis (UC), and there is no effective treatment for them currently. Numerous studies on IBD focused on intestinal mucosal barrier damage and immune dysfunction, while only a few investigated the involvement of mesenteric circulation in the pathogenesis of IBD. Mesenteric arteries in IBD patients have weakened vasorelaxation in response to ACh, resulting in reduced blood flow in the inflamed area (Hatoum et al., 2003a; Hatoum and Binion, 2005). This dysfunction in the mesenteric vasorelaxation affects the blood supply in the intestinal mucosa, thereby promoting the progression of IBD. Understanding the role of intestinal blood circulation in IBD may have theoretical significance and clinical implication; however, it has not been explored at present whether the Citation: Zhang LY, Chen XY, Dong H and Xu F (2021) Cyclopiazonic Acid-Induced Ca2+ Store Depletion Initiates Endothelium-Dependent Hyperpolarization-Mediated Vasorelaxation of Mesenteric Arteries in Healthy and Colitis Mice. Front. Physiol. 12:639857. doi: 10.3389/fphys.2021.639857 Conclusion: Depletion of ER Ca2+ by CPA induces a vasorelaxation of mesenteric arteries that is mediated through EDH mechanism and invokes the activation of SOCE. The CPA-induced endothelium-dependent dilation is impaired in colitis which may limit blood perfusion to the intestinal mucosa. March 2021 \| Volume 12 \| Article 639857 1 Frontiers in Physiology \| www.frontiersin.org SOCE/EDH in Mesenteric Arteries Function Zhang et al. Animalsh The animal studies were approved by the Ethics Committee of Chongqing Medical University, Chongqing, China. Experiments were conducted on male C57BL/6 mice (6–12 weeks-old; 20–25 g), which were purchased from Chongqing Tengxin Biotechnology Co. Ltd., Chongqing, China. The mice were housed in polypropylene plastic cages with unlimited access to tap water, with up to a maximum of five animals per cage, in a temperature-controlled room with a 12/12-h light/dark cycle. The mice were anesthetized using 100% CO2 and euthanized through cervical dislocation. Before each experiment, the mice were deprived of food and water for at least 1 h. For all animal experiments, only male mice were used to minimize possible variations owing to the sex of the animal. y y Vascular endothelial cells (VEC) play an important role in regulating vascular function by producing three relaxing signals: nitric oxide (NO; Kruse et al., 1994; Zuccolo et al., 2016), prostacyclin (PGI2; Asai et al., 2009), and endothelium-dependent hyperpolarization (EDH; Félétou and Vanhoutte, 2007, 2009). EDH plays a major role in regulating the relaxation of fine resistance blood vessels (Garland et al., 1995; Crane et al., 2003), while NO and PGI2 in that of large blood vessels (Guo et al., 2018). Although the nature of EDH has not been fully identified, the endothelial Ca2+-activated KCa channels are generally accepted as irreplaceable components of EDH signal (Cocks et al., 1988; Garland and Dora, 2017). In VEC, the SOCE has an important effect on the fine regulation of [Ca2+]i. Physiologically, the SOCE was shown to mainly involve in the acetylcholine (ACh)/NO-induced vasorelaxation (Lin et al., 2000; Dedkova and Blatter, 2002). Edwards stated that CPA contributes to EDH-induced vasorelaxation by the depletion of ER Ca2+ (Edwards et al., 2008), however, the role of SOCE in this phenomenon is not well established.l Animal studies were conducted in accordance to the ARRIVE guidelines (Kilkenny et al., 2010; McGrath and Lilley, 2015). The protocols were in compliance with the Army Military Medical University Committee on Investigations Involving Animal Subjects. All animal care and experimental studies were conducted in accordance with the guidelines of the Animal Ethical Committee of Chongqing Medical University and the Guide for the Care and Use of Laboratory Animals published by the United States National Institutes of Health (NIH Publication No. 85–23, revised 1996). Frontiers in Physiology \| www.frontiersin.org Measurement of [Ca2+]i by Digital Ca2+ Imaging with different drugs for 20 min, and then the cumulative CRC to CPA (4, 6, 8, 10, and 12 μM) were performed in NE (5 μM)‐ or KCl (80 mM)-preconstricted arteries. ( μ ) ( ) p To understand the mechanism underlying CPA-induced vasorelaxation, arterial rings were treated for 20 min with the following activators and inhibitors: indomethacin (INDO, 10 μM, inhibitor of cyclooxygenase, COX), Nω-nitro-L-arginine (L-NNA, 100 μM, inhibitor of nitric oxide synthase, NOS), ouabain (100 μM, inhibitor of Na+/K+-ATPase, NKA), SN-6 (10 μM, inhibitor of Na+/Ca2+ exchanger, NCX), GSK-7975A (30 μM, blocker of SOCE), flufenamic acid (FFA; 100 μM, blocker of SOCE, FFA), SKF96365 (30 μM, blocker of SOCE), tetraethylammonium chloride (TEA, 10 mM, blocker of Ca2+- activated K+ channels, KCa), and SKA-31 (0.3 μM, activator of Ca2+-activated K+ channels, KCa). Myograph Experimentsh y g p p The mesenteric artery is a recognized microvascular model, which is often used to study the physiological and pathological mechanism of resistance vessels; therefore, we used mesenteric arteries as the representative model in this study. The C57BL/6 mice were sacrificed, abdomen was fully exposed, and the mesangial intestinal tube was quickly removed and placed in pre-cooled Krebs–Henseleit solution. Krebs–Henseleit solution contained 118 mM NaCl, 4.7 mM KCl, 1.18 mM MgSO4, 25 mM NaHCO3, 1.2 mM KH2PO4, 1.6 mM CaCl2, and 11.1 mM D-glucose. The fat and connective tissues around the blood vessels were carefully removed under a microscope. The mesenteric arteries (100–150 μm of diameter, 2-mm segments in length) were obtained from the second-order branch of the superior mesenteric artery and placed in Krebs solution. Two tungsten wires (each 40 μm in diameter) were passed through the mesenteric arteries, which were fixed to jaws of the Mulvany-style wire myograph (Model 520A, DMT, Aarhus, Denmark) for functional assessment. Isometric tension changes were recorded using a Powerlab analytical system (AD Instruments, Colorado Springs, CO, United States). The chamber bath contained 5 ml K-H solution, the bath temperature was maintained at 37°C, and a mixture of 95% O2 + 5% CO2 was injected and maintained at a pH of ~7.4. One side of the tungsten wire was connected to the tension transducer, and the other side was connected to the blood vessel fine-tuning device.h Data and Statistics Analysis y All results are expressed as mean ± SE, with n representing the number of animals, and no data points were excluded from the analysis in any of the results. Furthermore, the sample sizes of animal experiments have taken the 3Rs principles into consideration (Kilkenny et al., 2010). All results are means ± SE with n represents the number of animals and n ≥ 6 in each group of experiments. In cell experiments (Ca2+ imaging), n represented the number of cells. For all studies, animals were randomly assigned to different experimental groups. GraphPad Software 6.0 (San Diego, CA) was used to determine the cumulative CRC, maximal relaxation (Rmax), and the concentration for 50% maximal effect (EC50). The statistical significance of differences in the means of experimental groups was determined using unpaired, two-tailed Student’s t-test for two groups or one-way ANOVA. Dunnett’s post or post hoc tests were performed Dextran Sulfate Sodium-Induced Colitis Mouse Model Dextran sulfate sodium (DSS)-induced colitis mouse is a commonly used animal model for studying colitis (Okayasu et al., 1990; Meir et al., 2019). Twelve healthy male C57 mice (6–8 weeks, 17–23 g) were randomly divided into two groups. The control group was fed drinking water, and the test group was fed water with 2.5% DSS, for 7 days (labeled as days 1–7). Mice were monitored daily for body weight, rectal bleeding, and water consumption. After 4 days, the mice in the test group developed bloody stools and started losing weight. On day 7, the mice were anesthetized using 100% CO2 and sacrificed through cervical dislocation. The lengths of the colons of the mice in the two groups were measured. Materials Cyclopiazonic acid, L-NNA, carbachol (CCH), TEA, ACh, and INDO were purchased from Sigma. Ouabain was purchased from ApexBio. SKA-31, SKF96365, and GSK-7975A were purchased from MedChemExpress. SN-6 was purchased from Tocris. The most of the reagents were dissolved in DMSO at final concentration of less than 0.1%, which did not alter vascular activities in the experiments. Cyclopiazonic acid, L-NNA, carbachol (CCH), TEA, ACh, and INDO were purchased from Sigma. Ouabain was purchased from ApexBio. SKA-31, SKF96365, and GSK-7975A were purchased from MedChemExpress. SN-6 was purchased from Tocris. The most of the reagents were dissolved in DMSO at final concentration of less than 0.1%, which did not alter vascular activities in the experiments. The vascular endothelium was removed by rubbing the luminal surface of the mesenteric arteries for several times using human hair. Successful endothelial denudation was verified by a lack (≤10%) of vasorelaxation response to CCh (100 μM). The experiments were performed after the successful removal of the vascular endothelium. Measurement of [Ca2+]i by Digital Ca2+ Imaging g g Ca2+ imaging experiments were performed as previously described (Wan et al., 2017). Cells grown on coverslips were loaded with 5 μM Fura-2/AM in physiological salt solution (PSS), described below, at 37°C for 60 min and then washed for 20 min. Thereafter, the coverslips with HUVEC were mounted in a perfusion chamber on a Nikon microscope stage (Nikon Corp, Tokyo, Japan). The ratio of Fura-2/AM fluorescence with excitation at 340 or 380 nm (F340/380) was followed over time and captured using an intensified charge-coupled device camera (ICCD200) and a MetaFluor imaging system (Universal Imaging March 2021 \| Volume 12 \| Article 639857 2 SOCE/EDH in Mesenteric Arteries Function Zhang et al. with different drugs for 20 min, and then the cumulative CRC to CPA (4, 6, 8, 10, and 12 μM) were performed in NE (5 μM)‐ or KCl (80 mM)-preconstricted arteries. To understand the mechanism underlying CPA-induced vasorelaxation, arterial rings were treated for 20 min with the following activators and inhibitors: indomethacin (INDO, 10 μM, inhibitor of cyclooxygenase, COX), Nω-nitro-L-arginine (L-NNA, 100 μM, inhibitor of nitric oxide synthase, NOS), ouabain (100 μM, inhibitor of Na+/K+-ATPase, NKA), SN-6 (10 μM, inhibitor of Na+/Ca2+ exchanger, NCX), GSK-7975A (30 μM, blocker of SOCE), flufenamic acid (FFA; 100 μM, blocker of SOCE, FFA), SKF96365 (30 μM, blocker of SOCE), tetraethylammonium chloride (TEA, 10 mM, blocker of Ca2+- activated K+ channels, KCa), and SKA-31 (0.3 μM, activator of Ca2+-activated K+ channels, KCa). with different drugs for 20 min, and then the cumulative CRC to CPA (4, 6, 8, 10, and 12 μM) were performed in NE (5 μM)‐ or KCl (80 mM)-preconstricted arteries. Corp, Downingtown, PA). In our study, fluorescence ratios from single cells were recorded at 3 s intervals, so the sampling rate used in our study was 1/3 fs (Hz). The Ca2+ imaging system was calibrated using Titration Calibration in situ according to MetaFluor Online Help. F340/380 ratio measurements were performed and imaged every 3 s. The PSS used in digital Ca2+ measurement contained the following: 140 mM Na+, 5 mM K+, 2 mM Ca2+, 147 mM Cl−, 10 mM Hepes, and 10 mM glucose (pH 7.4). For the Ca2+-free PSS, Ca2+ was omitted, but 0.5 mM EGTA was added. The osmolality for all solutions was ~300 mosmol/kg of H2O. Frontiers in Physiology \| www.frontiersin.org CPA Activated the SOCE in Vascular Endothelial Cellsi Next, we used CPA as a selective SOCE activator to examine whether CPA induced vasorelaxation. CPA at 4–12 μM induced marked vasorelaxation of the arteries pre-constricted using NE (5 μM) in a concentration-dependent manner (NE-vasoconstriction value 9.51 ± 1.26 mN, Rmax 91.46 ± 5.09%, and EC50 6.18 ± 0.07 μM; Figures 2A,B). To test if CPA-induced vasorelaxation was endothelium-dependent, we compared CPA-induced vasorelaxation between endothelium-intact and endothelium-denuded mesenteric arteries. In endothelium- denuded mesenteric arteries, which was confirmed using CCh (100 μM, Rmax 6.32 ± 1.49%, and n = 6), CPA induced only 20% vasorelaxation (Rmax 18.29 ± 2.33%, n = 6; Figures 2A,B). Therefore, CPA predominantly induced endothelium-dependent and concentration-dependent vasorelaxation. Cyclopiazonic acid is a well-known specific inhibitor of the sarco(endo) plasmic reticulum calcium-ATPases (SERCA). The SERCA inhibition can deplete the ER Ca2+ to presumably activate the SOCE. We examined the CPA-induced SOCE in HUVEC. First, after basal [Ca2+]i was stable in normal PSS containing 2 mM extracellular Ca2+, application of CPA (10 μM) induced a marked increase in [Ca2+]i in HUVEC (Figure 1A). Second, in the absence of extracellular Ca2+ (0Ca PSS), CPA induced a transient increase in [Ca2+]i due to Ca2+ release from the ER to the cytosol. When the store was depleted (i.e., when the [Ca2+]cyt transients declined back to the basal level), restoration of extracellular Ca2+ to 2 mM (2Ca) induced a further increase in [Ca2+]i due to Ca2+ entry through the SOCE (Figure 1B). Third, GSK-7975A (30 μM), a selective Orai blocker, did not affect the CPA-induced transient increase in [Ca2+]i due to Ca2+ release from the ER, but significantly attenuated the further increase in [Ca2+]i due to Ca2+ entry through the SOCE (Figure 1C). Figure 1D summarizes the CPA-induced [Ca2+]i in HUVEC in 2Ca PSS, and Figures 1E,F CPA-Induced Mesenteric Arterial Relaxation Through EDH Vasorelaxation of mesenteric arteries plays a critical role in controlling blood flow perfusion in mesenteric circulation, which maintains normal mucosal barrier function in the A D E F B C FIGURE 1 \| The cyclopiazonic acid (CPA)-induced store-operated calcium entry (SOCE) in single vascular endothelial cells. (A) Summary data showing the time courses of CPA (10 μM)-induced Ca2+ signaling in Ca2+-containing solution (2Ca, n = 17 cells). (B) Summary data showing the time courses of CPA-induced Ca2+ signaling in Ca2+-free solution (0Ca) and after restoration of extracellular Ca2+ (2Ca, n = 16 cells). (C) Summary data showing the time courses of CPA-induced Ca2+ signaling in 0Ca and after restoration of 2Ca in the presence of GSK-7975A (30 μM, n = 16 cells). (D) Summary data showing CPA-induced Ca2+ signaling in Ca2+-containing solution (2Ca, n = 17 cells). (E) Summary data showing the delta Ca2+ signaling induced by CPA in Ca2+-free solution (0Ca, n = 16 cells) in the absence or the presence of GSK-7975A (30 μM). (F) Summary data showing the delta Ca2+ signaling induced by CPA after restoration of 2Ca in the absence or the presence of GSK-7975A (30 μM, n = 16 cells). Data were shown as means ± SEM. p < 0.01, *p < 0.0001, and ns, no significance. C A B A B D E F D E F FIGURE 1 \| The cyclopiazonic acid (CPA)-induced store-operated calcium entry (SOCE) in single vascular endothelial cells. (A) Summary data showing the time courses of CPA (10 μM)-induced Ca2+ signaling in Ca2+-containing solution (2Ca, n = 17 cells). (B) Summary data showing the time courses of CPA-induced Ca2+ signaling in Ca2+-free solution (0Ca) and after restoration of extracellular Ca2+ (2Ca, n = 16 cells). (C) Summary data showing the time courses of CPA-induced Ca2+ signaling in 0Ca and after restoration of 2Ca in the presence of GSK-7975A (30 μM, n = 16 cells). (D) Summary data showing CPA-induced Ca2+ signaling in Ca2+-containing solution (2Ca, n = 17 cells). (E) Summary data showing the delta Ca2+ signaling induced by CPA in Ca2+-free solution (0Ca, n = 16 cells) in the absence or the presence of GSK-7975A (30 μM). (F) Summary data showing the delta Ca2+ signaling induced by CPA after restoration of 2Ca in the absence or the presence of GSK-7975A (30 μM, n = 16 cells). Data were shown as means ± SEM. Concentration-Response Curve Cumulative concentration-response curve (CRC) to cyclopiazonic acid (CPA, 4–12 μM) was performed in norepinephrine (NE, 10 μM)‐ or KCl (80 mM)-pre-constricted arteries. Since the in situ blood vessels are under a transmural pressure by neurohumoral regulation, the isolated blood vessels must be standardized to meet physiological tension in Krebs–Henseleit solution for at least 20 min. After standardization, the tension was equivalent to 0.9 times the blood vessel diameter under 100 mmHg pressure. The blood vessels were first incubated March 2021 \| Volume 12 \| Article 639857 Frontiers in Physiology \| www.frontiersin.org 3 SOCE/EDH in Mesenteric Arteries Function Zhang et al. summarize effect of GSK-7975A on the CPA-induced [Ca2+]i in 0Ca PSS and after restoring 2Ca. These results indicate that CPA indeed activates the SOCE, and thus it can be reasonably used as a selective SOCE activator in VEC. only if F achieved p < 0.05 (GraphPad Prism 7.0, GraphPad Software, Inc., RRID: SCR_002798) for multiple groups. p < 0.05 was considered statistically significant. CPA-Induced Mesenteric Arterial Relaxation Through EDH p < 0.01, **p < 0.0001, and ns, no significance. March 2021 \| Volume 12 \| Article 639857 4 SOCE/EDH in Mesenteric Arteries Function Zhang et al. A B C D FIGURE 2 \| Cyclopiazonic acid-induced endothelium-dependent and extracellular K+-sensitive vasorelaxation of mesenteric arteries. (A) Representative tracings showing CPA or carbachol (CCh, 100 μM) induced endothelium-dependent vasorelaxation with intact endothelium (EC+, the left panel; the right panel) and the loss of vasorelaxation in response to CCh (100 μM) or CPA in endothelium-denuded arteries (EC−, the middle panel). (B) Summary data showing concentration- response curve (CRC), Rmax, and EC50 of CPA-induced vasorelaxation with intact endothelium (EC+, n = 6) or denuded endothelium (EC−, n = 6). (C) Representative tracings of CPA-induced concentration-dependent vasorelaxation in mesenteric arteries preconstricted with noradrenalin (5 μM NE, the left panel), and CPA or SNP concentration-dependent vasorelaxation in mesenteric arteries preconstricted with high extracellular K+ (80 mM KCl, the middle and the right panels). (D) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in mesenteric arteries preconstricted with norepinephrine (NE; n = 6) or KCl (n = 6). Data were expressed as percentage of NE‐ or KCl-induced vasoconstriction and shown as means ± SEM. p < 0.01, *p < 0.001, p < 0.0001. A B C D FIGURE 2 \| Cyclopiazonic acid-induced endothelium-dependent and extracellular K+-sensitive vasorelaxation of mesenteric arteries. (A) Representative tracings showing CPA or carbachol (CCh, 100 μM) induced endothelium-dependent vasorelaxation with intact endothelium (EC+, the left panel; the right panel) and the loss of vasorelaxation in response to CCh (100 μM) or CPA in endothelium-denuded arteries (EC−, the middle panel). (B) Summary data showing concentration- response curve (CRC), Rmax, and EC50 of CPA-induced vasorelaxation with intact endothelium (EC+, n = 6) or denuded endothelium (EC−, n = 6). (C) Representative tracings of CPA-induced concentration-dependent vasorelaxation in mesenteric arteries preconstricted with noradrenalin (5 μM NE, the left panel), and CPA or SNP concentration-dependent vasorelaxation in mesenteric arteries preconstricted with high extracellular K+ (80 mM KCl, the middle and the right panels). (D) Summary A A B C B B C D D FIGURE 2 \| Cyclopiazonic acid-induced endothelium-dependent and extracellular K+-sensitive vasorelaxation of mesenteric arteries. CPA-Induced Mesenteric Arterial Relaxation Through EDH (A) Representative tracings showing CPA or carbachol (CCh, 100 μM) induced endothelium-dependent vasorelaxation with intact endothelium (EC+, the left panel; the right panel) and the loss of vasorelaxation in response to CCh (100 μM) or CPA in endothelium-denuded arteries (EC−, the middle panel). (B) Summary data showing concentration- response curve (CRC), Rmax, and EC50 of CPA-induced vasorelaxation with intact endothelium (EC+, n = 6) or denuded endothelium (EC−, n = 6). (C) Representative tracings of CPA-induced concentration-dependent vasorelaxation in mesenteric arteries preconstricted with noradrenalin (5 μM NE, the left panel), and CPA or SNP concentration-dependent vasorelaxation in mesenteric arteries preconstricted with high extracellular K+ (80 mM KCl, the middle and the right panels). (D) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in mesenteric arteries preconstricted with norepinephrine (NE; n = 6) or KCl (n = 6). Data were expressed as percentage of NE‐ or KCl-induced vasoconstriction and shown as means ± SEM. p < 0.01, *p < 0.001, *p < 0.0001. intestine of healthy subjects (Aneman et al., 1997; Hatoum et al., 2003a). CPA induced marked vasorelaxation of the arteries pre-constricted using NE (5 μM) in a concentration- dependent manner, but induced only a marginal vasorelaxation of the arteries pre-constricted using high K+ (80 mM; Figures 2C,D). The CPA-induced CRC and Rmax were much greater in the arteries pre-constricted using NE (Rmax 91.46 ± 5.09%, n = 6) compared to those pre-constricted using high K+ (Rmax 17.51 ± 4.17%, n = 6, p < 0.05; Figure 2D). Therefore, CPA induced much greater vasorelaxation of the arteries pre-constricted using NE than those pre-constricted using high K+, in a concentration-dependent manner, suggesting that K+ channels possibly participate in the CPA-induced vasorelaxation (Li et al., 2015). We explored the underlying mechanisms of CPA-induced vasorelaxation. VEC are known to generate three different endothelium-derived relaxing factors: NO, PGI2, and EDH (Félétou and Vanhoutte, 2007, 2009). Neither NO inhibitor L-NNA (100 μM, n = 6, NE-vasoconstriction value 6.40 ± 0.62 mN) nor PGI2 inhibitor INDO (10 μM, n = 6, March 2021 \| Volume 12 \| Article 639857 Frontiers in Physiology \| www.frontiersin.org 5 SOCE/EDH in Mesenteric Arteries Function Zhang et al. (30 μM), respectively, in the presence of L-NNA + INDO (Figures 4A–C). As shown in Figures 4A–C, they significantly reduced CPA-induced Rmax. CPA-Induced Mesenteric Arterial Relaxation Through EDH Compared with L-NNA + INDO (Rmax 92.55 ± 2.79%), the CPA-induced Rmax were significantly reduced by SKF963659 (Rmax 41.65 ± 4.64%, NE-vasoconstriction value 6.88 ± 0.70 mN, p < 0.0001), FFA (Rmax 45.13 ± 6.65%, NE-vasoconstriction value 8.62 ± 0.70 mN, p < 0.0001), and GSK-7975A (Rmax 52.84 ± 6.62%, NE-vasoconstriction value 7.20 ± 0.99 mN, p < 0.0001). In summary, CPA induces an endothelium-dependent vasorelaxation through the SOCE/ EDH mechanism. NE-vasoconstriction value 6.67 ± 0.55 mN) affected CPA-induced vasorelaxation (Figure 3A). Similarly, the combination of L-NNA and INDO did not affect the CPA-induced vasorelaxation (Figure 3B; Rmax 92.55 ± 2.79%, EC50 5.92 ± 0.10 μM, NE-vasoconstriction value 9.74 ± 0.86 mN), further supporting that both NO and PGI2 play minor roles in the vasorelaxation, while EDH may play a major role.h NE-vasoconstriction value 6.67 ± 0.55 mN) affected CPA-induced vasorelaxation (Figure 3A). Similarly, the combination of L-NNA and INDO did not affect the CPA-induced vasorelaxation (Figure 3B; Rmax 92.55 ± 2.79%, EC50 5.92 ± 0.10 μM, NE-vasoconstriction value 9.74 ± 0.86 mN), further supporting that both NO and PGI2 play minor roles in the vasorelaxation, while EDH may play a major role.h y y j The CPA-induced vasorelaxation through EDH was selected for further analysis after L-NNA and INDO were applied to inhibit the endothelium-dependent vasorelaxation through NO and PGI2. A large portion of CPA-induced vasorelaxation was further attenuated by TEA (10 mM, Rmax 55.31 ± 0.93%, EC50 5.83 ± 0.40 μM, NE-vasoconstriction value 6.47 ± 1.12 mN), a blocker of KCa channels; but potentiated by SKA-31 (0.3 μM, NE-vasoconstriction value 6.92 ± 0.74 mN), a selective IKCa and SKCa channel activator that can in turn potentiate EDH-type arterial dilation (Sankaranarayanan et al., 2009). The inhibitory effect of TEA and the potentiation effect of SKA-31 on CPA-induced CRC, Rmax, and EC50 in the presence of L-NNA and INDO are summarized in Figure 3B. Taken together, CPA-induced vasorelaxation is mainly dependent on EDH. Na+-K+ ATPase in the SOCE/EDH-Mediated Vasorelaxation Since SKCa‐ and IKCa-mediated EDH hyperpolarizes VEC, K+ efflux could stimulate NKA in vascular smooth muscle cells (VSMCs; Garland and Dora, 2017). To test if NKA is involved in CPA-induced vasorelaxation, we applied ouabain (100 μM, NE-vasoconstriction value 7.84 ± 1.55 mN) to inhibit NKA in the presence of L-NNA and INDO. CPA-induced CRC and Rmax (51.45 ± 6.90%), were significantly attenuated by ouabain (p < 0.0001, Figure 5A). Furthermore, when extracellular K+ was omitted (0 K+, NE-vasoconstriction value 8.36 ± 1.95 mN) to silence NKA, CPA-induced CRC and Rmax (41.56 ± 8.15%) were also significantly attenuated (p < 0.0001, Figure 5B). Since both ouabain and 0 K+ significantly reduced CPA-induced Rmax (Figures 5A,B), we concluded that CPA-induced EDH activated NKA, leading to the vasorelaxation of mesenteric arteries. The EDH-Mediated Vasorelaxation Depended on the SOCE Mechanism We further investigated if CPA-induced vasorelaxation through EDH depends on the SOCE mechanism. Indeed, CPA-induced CRC was significantly attenuated by selective SOCE blockers SKF96365 (30 μM), FFA (100 μM), and Orai blocker GSK-7975A A B FIGURE 3 \| Cyclopiazonic acid induction of mesenteric arterial relaxation through endothelium-dependent hyperpolarization. (A) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in mesenteric arteries in the absence (control, n = 6) or the presence of either 100 μM Nω-nitro-L-arginine (L-NNA; n = 6) or 10 μM indomethacin (INDO; n = 6). (B) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in the presence of L-NNA + INDO (n = 6), L-NNA + INDO (&) + 0.3 μM SKA-31 (n = 6), or L-NNA + INDO (&) + 10 mM tetraethylammonium chloride (TEA; n = 6). Data were expressed as percentage of NE (5 μM)-induced vasoconstriction and shown as means ± SEM. p < 0.05, ***p < 0.0001, and ns, no significance. A A B B FIGURE 3 \| Cyclopiazonic acid induction of mesenteric arterial relaxation through endothelium-dependent hyperpolarization. (A) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in mesenteric arteries in the absence (control, n = 6) or the presence of either 100 μM Nω-nitro-L-arginine (L-NNA; n = 6) or 10 μM indomethacin (INDO; n = 6). (B) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in the presence of L-NNA + INDO (n = 6), L-NNA + INDO (&) + 0.3 μM SKA-31 (n = 6), or L-NNA + INDO (&) + 10 mM tetraethylammonium chloride (TEA; n = 6). Data were expressed as percentage of NE (5 μM)-induced vasoconstriction and shown as means ± SEM. p < 0.05, **p < 0.0001, and ns, no significance. March 2021 \| Volume 12 \| Article 639857 Frontiers in Physiology \| www.frontiersin.org 6 SOCE/EDH in Mesenteric Arteries Function Zhang et al. A B C FIGURE 4 \| Cyclopiazonic acid induced vasorelaxation through the SOCE/endothelium-dependent hyperpolarization (EDH) mechanism. (A) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in the presence of either L-NNA + INDO (n = 6) or L-NNA + INDO (&) + 30 μM SFK96365 (n = 6). Successfully Created a Mouse Colitis Modelll Na+/Ca2+ Exchanger in the SOCE/EDH-Mediated Vasorelaxation The EDH-Mediated Vasorelaxation Depended on the SOCE Mechanism (B) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in the presence of either L-NNA + INDO (n = 6) or L-NNA + INDO (&) + 100 μM flufenamic (FFA, n = 6). (C) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in the presence of either L-NNA + INDO (n = 6) or L-NNA + INDO (&) + 30 μM GSK-7975A (n = 6). Data were expressed as percentage of NE (5 μM)-induced vasoconstriction and shown as means ± SEM. p < 0.01, *p < 0.001, p < 0.0001, and ns, no significance. A C FIGURE 4 \| Cyclopiazonic acid induced vasorelaxation through the SOCE/endothelium-dependent hyperpolarization (EDH) mechanism. (A) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in the presence of either L-NNA + INDO (n = 6) or L-NNA + INDO (&) + 30 μM SFK96365 (n = 6). (B) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in the presence of either L-NNA + INDO (n = 6) or L-NNA + INDO (&) + 100 μM flufenamic (FFA, n = 6). (C) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in the presence of either L-NNA + INDO (n = 6) or L-NNA + INDO (&) + 30 μM GSK-7975A (n = 6). Data were expressed as percentage of NE (5 μM)-induced vasoconstriction and shown as means ± SEM. p < 0.01, *p < 0.001, p < 0.0001, and ns, no significance. Na+/Ca2+ Exchanger in the SOCE/EDH-Mediated Vasorelaxation Although in IBD patients, blood flow to chronically inflamed regions of gut was reduced (Hatoum et al., 2003a; Hatoum and Binion, 2005), it is not known if SOCE/EDH signals in the mesenteric circulation are involved in the pathogenesis. We first created DSS-induced colitis in a mouse model and found that the body weight and colon length of colitis mice were significantly reduced (Figures 7A,C). After 4 days of ingestion of water containing 2.5% DSS, the mice had bloody stools and their body weight was significantly lower than that of the control group after a week. On day 7, the mice were sacrificed through cervical dislocation, and the intestinal segment from the anus to the ileocecal area was removed. There was Endothelium-dependent hyperpolarization signal is mediated not only by Ca2+-activated IKCa and SKCa channels in VEC, but also by NKA and Na+/Ca2+ exchanger (NCX) in VSMCs (Cocks et al., 1988), in which they play a critical role in regulating vascular tone (Matchkov et al., 2007). Therefore, we applied SN-6 (10 μM, a selective inhibitor of Na+/Ca2+ exchanger, NE-vasoconstriction value 8.44 ± 1.65 mN) in the presence of L-NNA and INDO, to test whether NCX is also involved in CPA-induced vasorelaxation. CPA-induced CRC and Rmax (51.45 ± 6.90%) were significantly inhibited (Figures 6A,B), indicating that NCX plays a critical role in CPA-induced EDH-mediated vasorelaxation. March 2021 \| Volume 12 \| Article 639857 Frontiers in Physiology \| www.frontiersin.org 7 SOCE/EDH in Mesenteric Arteries Function Zhang et al. A B FIGURE 5 \| The involvement of Na+-K+-ATPase (NKA) in the EDH-mediated vasorelaxation of mesenteric arteries. (A) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in the presence of either L-NNA + INDO (n = 6) or L-NNA + INDO (&) + 100 μM ouabain (n = 6). (B) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in the presence of either L-NNA + INDO (n = 6) or L-NNA + INDO (&) + 0 K+ (n = 6). Data were expressed as percentage of NE (5 μM)-induced vasoconstrictions and shown as means ± SEM. p < 0.001, and ns, no significance. A B B FIGURE 5 \| The involvement of Na+-K+-ATPase (NKA) in the EDH-mediated vasorelaxation of mesenteric arteries. Na+/Ca2+ Exchanger in the SOCE/EDH-Mediated Vasorelaxation (A) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in the presence of either L-NNA + INDO (n = 6) or L-NNA + INDO (&) + 100 μM ouabain (n = 6). (B) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in the presence of either L-NNA + INDO (n = 6) or L-NNA + INDO (&) + 0 K+ (n = 6). Data were expressed as percentage of NE (5 μM)-induced vasoconstrictions and shown as means ± SEM. p < 0.001, and ns, no significance. vasorelaxation was higher in colitis mice (EC50 8.54 ± 0.44 μM) compared to that in control mice (EC50 5.92 ± 0.10 μM, p < 0.05). Therefore, CPA/SOCE/EDH-mediated vasorelaxation is largely impaired in the pathogenesis of colitis. considerable bleeding in the intestinal segment as well as a significant reduction in the colon length of colitis mice (Figures 7B,C). To verify the dysfunctions of vascular endothelial cells in colitis, we compared the ACh-induced (10 nM–1 mM) relaxation between normal mice and DSS-induced colitis mice (Rmax: 95.65% vs. 74.18%, p < 0.05, Figure 7D). In summary, the DSS-induced colitis in a mouse model was successful. Frontiers in Physiology \| www.frontiersin.org The Vasorelaxation Through SOCE/EDH Was Impaired in Colitis (B) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in the presence of either L-NNA + INDO (n = 6) or L-NNA + INDO (&) + 10 μM SN-6 (n = 6). Data were expressed as percentage of NE (5 μM)-induced vasoconstriction and shown as means ± SEM. p < 0.001 and ns, no significance. A B C D FIGURE 7 \| Comparison of body weight and colon length between control mice and dextran sulfate sodium (DSS)-induced colitis of mouse model. (A) Summary data showing the time courses of body weight in control mice (n = 6) or colitis mice treated with 2.5% DSS (po) for 7 days (n = 6). (B) Representative photos of colon length in control and colitis mice. (C) Summary data showing colon length in control mice (n = 6) and colitis mice (n = 6). (D) Summary data showing the acetylcholine (ACh)-induced (10 nM–1 mM) maximal vasorelaxation from normal mice and colitis mice (n = 4). Data were shown as means ± SEM. p < 0.01, *p < 0.0001. C D C B A B A FIGURE 7 \| Comparison of body weight and colon length between control mice and dextran sulfate sodium (DSS)-induced colitis of mouse model. (A) Summary data showing the time courses of body weight in control mice (n = 6) or colitis mice treated with 2.5% DSS (po) for 7 days (n = 6). (B) Representative photos of colon length in control and colitis mice. (C) Summary data showing colon length in control mice (n = 6) and colitis mice (n = 6). (D) Summary data showing the acetylcholine (ACh)-induced (10 nM–1 mM) maximal vasorelaxation from normal mice and colitis mice (n = 4). Data were shown as means ± SEM. p < 0.01, **p < 0.0001. balance (Várnai et al., 2009). Under physiological conditions, IP3 is the usual stimulus for the ER/Ca2+ release via IP3 receptors which results in the loss of Ca2+ from the ER, leading to SOCE activation; and thereby the degree of SOCE activation is related to the ER/Ca2+ depletion degree (Taylor, 2006). to inhibit the SOCE/Orai channels, and revealed that CPA-induced vasorelaxation was significantly inhibited, proving that CPA exerts endothelium-dependent vasorelaxation likely through the SOCE/Orai channels.h The mesenteric artery is a recognized resistance vessel model and plays an important role in regulating blood flow to the intestine and in maintaining blood pressure. The Vasorelaxation Through SOCE/EDH Was Impaired in Colitis SOCE/EDH in Mesenteric Arteries Function A B 6 \| The involvement of sodium-calcium exchanger in the EDH-mediated vasorelaxation of mesenteric arteries.(A) Representative tracings of CPA-induced pendent vasorelaxation in the presence of either L-NNA + INDO (the left panel) or L-NNA + INDO + 10 μM SN-6 (the right panel). (B) Summary data the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in the presence of either L-NNA + INDO (n = 6) or L-NNA + INDO (&) + 10 μM SN-6 (n = 6). Data ressed as percentage of NE (5 μM)-induced vasoconstriction and shown as means ± SEM. p < 0.001 and ns, no significance. A B C D 7 \| Comparison of body weight and colon length between control mice and dextran sulfate sodium (DSS)-induced colitis of mouse model. (A) Summary wing the time courses of body weight in control mice (n = 6) or colitis mice treated with 2.5% DSS (po) for 7 days (n = 6). (B) Representative photos of gth in control and colitis mice. (C) Summary data showing colon length in control mice (n = 6) and colitis mice (n = 6). (D) Summary data showing the line (ACh)-induced (10 nM–1 mM) maximal vasorelaxation from normal mice and colitis mice (n = 4). Data were shown as means ± SEM. p < 0.01, 0001. A B FIGURE 6 \| The involvement of sodium-calcium exchanger in the EDH-mediated vasorelaxation of mesenteric arteries.(A) Representative tracings of CPA-induced dose-dependent vasorelaxation in the presence of either L-NNA + INDO (the left panel) or L-NNA + INDO + 10 μM SN-6 (the right panel). (B) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in the presence of either L-NNA + INDO (n = 6) or L-NNA + INDO (&) + 10 μM SN-6 (n = 6). Data were expressed as percentage of NE (5 μM)-induced vasoconstriction and shown as means ± SEM. *p < 0.001 and ns, no significance. A A A B B FIGURE 6 \| The involvement of sodium-calcium exchanger in the EDH-mediated vasorelaxation of mesenteric arteries.(A) Representative tracings of CPA-induced dose-dependent vasorelaxation in the presence of either L-NNA + INDO (the left panel) or L-NNA + INDO + 10 μM SN-6 (the right panel). Frontiers in Physiology \| www.frontiersin.org The Vasorelaxation Through SOCE/EDH Was Impaired in Colitis The main findings of this study are as follows: (1) CPA-induced depletion of ER Ca2+ induces an endothelium-dependent dilation that requires activation of SOCE; (2) this vasorelaxation upon CPA-induced depletion of ER Ca2+ mainly relies on EDH; (3) both NKA and NCX are involved in the vasorelaxation through the CPA/SOCE/EDH mechanism; and (4) the CPA/SOCE/ EDH-mediated vasorelaxation is defective in colitis. We compared the CPA-induced vasorelaxation between the control and colitis mice. The CRC in response to CPA treatment was markedly impaired in colitis mice (Figure 8A). The Rmax (36.71 ± 1.40%) in colitis mice were significantly reduced compared to that in control mice (Rmax 91.46 ± 5.09%, p < 0.0001). The EC50 of CPA-induced vasorelaxation was higher in colitis mice (EC50 8.43 ± 0.78 μM) compared to that in control mice (EC50 6.16 ± 0.07 μM, p < 0.05). Therefore, the CPA/SOCE-mediated endothelium-dependent vasorelaxation is impaired in the pathogenesis of colitis. [Ca2+]i plays a critical role in regulating vasoconstriction and vasorelaxation (Rocha and Bendhack, 2009), as an important second cell messenger. In the resting state, the intracellular and extracellular Ca2+ levels remain relatively stable, and the extracellular Ca2+ is much higher than the intracellular Ca2+. The fine regulation of [Ca2+]i is of great significance for maintaining the normal function of endothelial cells and VSMCs (Garland et al., 2017). In molecular pathway of the SOCE, STIM protein senses the depletion of Ca2+ in the endoplasmic reticulum, and induces Ca2+ influx through coupling with protein Orai (Liou et al., 2005; Zhang et al., 2006). In non-excitable cells, such as vascular endothelial cells, the SOCE plays an important role in regulating cellular Ca2+ To further understand the contribution of EDH, we compared the CPA-induced vasorelaxation between control and colitis mice in the presence of a combination of L-NNA and INDO. After inhibition of NO plus PGI2 using L-NNA and INDO, CPA-induced EDH-mediated vasorelaxation was largely impaired in colitis mice (Figure 8B). Similarly, the Rmax (40.44 ± 5.91%) in colitis mice were significantly reduced compared to that in control mice (Rmax 92.55 ± 2.79%, p < 0.0001). The EC50 of CPA-induced March 2021 \| Volume 12 \| Article 639857 Frontiers in Physiology \| www.frontiersin.org 8 SOCE/EDH in Mesenteric Arteries Function Zhang et al. The Vasorelaxation Through SOCE/EDH Was Impaired in Colitis Importantly, endothelial dysfunction leads to reduced generation of NO, which in turn stimulates EDH, as a compensatory mechanism to maintain the endothelium-dependent vasorelaxation of resistance vessels (Ueda et al., 2005; Yada et al., 2018), highlighting the critical role of EDH in resistance vessels. was confirmed by single cell Ca2+ imaging. Although all inhibitors applied in the present study will affect both vascular endothelial and smooth muscle cells, the SOCE function is opposite: it induces endothelium-dependent vasorelaxation as shown in our study, but it enhances intracellular calcium level in smooth muscle cells to induce vasoconstriction. Our findings are consistent with the reports in different animal arteries from other laboratories (Dora et al., 2003; Crane and Garland, 2004; Edwards et al., 2008), and electrophysiological experiments confirmed CPA-induced hyperpolarization in rat mesenteric arteries (Fukao et al., 1995), further supporting our notion of CPA-induced endothelial SOCE/EDH mechanism. Although both NKA and NCX are known to jointly participate in the vasorelaxation mechanism of EDH signals (Cocks et al., 1988; Garland and Dora, 2017), if they are involved in the SOCE/EDH mechanism is still elusive. After applying either ouabain or 0 K+ solutions to inhibit NKA and SN-6 to inhibit NCX, we observed that CPA-induced vasorelaxation was significantly inhibited by each of them, suggesting their involvement. Therefore, our results indicated that CPA activates endothelial SOCE to raise [Ca2+]i that stimulates the IKCa and SKCa. The efflux of K+ results in accumulation between endothelial and smooth muscle cells, which leads to NKA activation and hyperpolarization to inactivate the voltage-dependent calcium channels, eventually resulting in vasorelaxation. Concurrently, NKA activation decreases [Na+]i in smooth muscle cells, which in turn stimulates NCX activity to decrease [Ca+]i (Guo et al., 2020), further enhancing vasorelaxation (Figure 9). Although the nature of EDH is still elusive so far (Félétou and Vanhoutte, 2007), it has been generally accepted that it is the Ca2+ increase in endothelial cells that activates IKCa and SKCa channels to induce membrane hyperpolarization (Gluais et al., 2005). The Vasorelaxation Through SOCE/EDH Was Impaired in Colitis When the resistance vessels relax, blood flow to the organ increases and vice versa. NO and EDH derived from endothelial cells have been recognized as the main factors regulating vasorelaxation (Félétou and Vanhoutte, 2007). NO activates guanylate cyclase on VSMC As a selective SERCA inhibitor, CPA inhibits Ca2+ uptake into the ER to finally activate SOCE so that it is often used as an SOCE activator. In the present study, we found that CPA indeed activated endothelial SOCE through depletion of the ER Ca2+, indicating it is a reliable SOCE activator. Afterwards, we applied two selective SOCE blockers and an Orai blocker March 2021 \| Volume 12 \| Article 639857 Frontiers in Physiology \| www.frontiersin.org 9 SOCE/EDH in Mesenteric Arteries Function Zhang et al. A B FIGURE 8 \| Impairments of the SOCE/EDH-mediated vasorelaxation in colitis. (A) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in control mice (n = 6) or colitis mice treated with 2.5% DSS (po) for 7 days (n = 6). (B) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation as described in (A) but in the presence of L-NNA + INDO (n = 6). Data were expressed as percentage of NE (5 μM)-induced vasoconstriction and shown as means ± SEM. p < 0.05, ***p < 0.0001. A A B B FIGURE 8 \| Impairments of the SOCE/EDH-mediated vasorelaxation in colitis. (A) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation in control mice (n = 6) or colitis mice treated with 2.5% DSS (po) for 7 days (n = 6). (B) Summary data showing the CRC, Rmax, and EC50 of CPA-induced vasorelaxation as described in (A) but in the presence of L-NNA + INDO (n = 6). Data were expressed as percentage of NE (5 μM)-induced vasoconstriction and shown as means ± SEM. p < 0.05, ****p < 0.0001. to increase intracellular cGMP, which exerts a vasorelaxation effect (Vanhoutte et al., 2017). PGI2 activates receptors on VSMC, causing vasorelaxation (Parkington et al., 2004), and EDH is known as a non-NO and non-PGI2 endothelium- dependent hyperpolarization (Busse et al., 2002; Matoba and Shimokawa, 2003). Under physiological conditions, both NO and EDH are the major vasodilators: the former is dominant in conduit arteries, but the latter is critical in resistance vessels (Shimokawa et al., 1996). Frontiers in Physiology \| www.frontiersin.org DATA AVAILABILITY STATEMENT This study was supported by research grants from the National Key Research and Development Program of China (No. 2016YFC1302200 to HD) and the National Natural Science Foundation of China (No. 81873544 to HD). The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher. AUTHOR CONTRIBUTIONS HD conceived the study, designed most experiments, and wrote and finalized the manuscript. LZ performed most experiments and data analysis. FX designed and XC performed some experiments. All authors contributed to the article and approved the submitted version. ETHICS STATEMENT The intestinal blood circulation plays an important role to maintain normal GI function (Gasbarrini et al., 2008), and mesenteric artery is critically involved in blood perfusion in the intestinal mucosa. It was previously reported that dysfunction of intestinal microvasculature impaired mucosal wound healing, which may lead to refractory mucosal ulceration (Papa et al., 2008). Although loss of NO generation and change in PGI2-dependent vasorelaxation (Hatoum et al., 2003b) resulted in dysfunction of the microvascular relaxation in colitis (Mori et al., 2005), it has not been addressed if the CPA-mediated vasorelaxation is impaired in colitis. By systematically compared the vasorelaxation of the mesenteric arteries in healthy and colitis mice in terms of the CPA/EDH mechanism, we revealed that this pathway was severely impaired in colitis. This may lead to the reduced blood perfusion to the intestinal mucosa, which will affect mucosal repair after injury to finally promote the progression of colitis. The animal study was reviewed and approved by the Animal Ethical Committee of Chongqing Medical University and the Guide for the Care and Use of Laboratory Animals published by the US National Institutes of Health. The animal study was reviewed and approved by the Animal Ethical Committee of Chongqing Medical University and the Guide for the Care and Use of Laboratory Animals published by the US National Institutes of Health. The Vasorelaxation Through SOCE/EDH Was Impaired in Colitis SOCE, store operated Ca2+ entry; VEC, vascular endothelial cells; VSMC, vascular smooth muscle cells; SERCA, sarcoendoplasmic reticulum calcium transport ATPase, IKCa and SKCa: intermediate and small conductance of Ca2+-activated K+ channels; NKA, Na+/K+-ATPase; and NCX, Na+/Ca2+-exchanger. FIGURE 9 \| The underlying mechanisms of the SOCE/EDH-mediated vasorelaxation of mesenteric arteries in health and its impairments in the pathogenesis of colitis. The SOCE/EDH-mediated vasorelaxation in health (left panel) and its impairments in colitis (right panel). CPA inhibits the SERCA to activate the SOCE and induce Ca2+ signaling that stimulates IKCa and SKCa on vascular endothelial cells (VEC), leading to K+ efflux. An increase in extracellular K+ between VEC and VSMC activates NKA to eventually cause vasorelaxation through hyperpolarization. Moreover, NKA activation reduces [Na+]i in VSMC, which stimulates Na+/Ca2+-exchange (NCX) activity to decreases [Ca2+]i, resulting in further vasorelaxation. However, the SOCE/EDH-mediated vasorelaxation is likely impaired by inflammatory factors-induced endothelial dysfunction in the pathogenesis of colitis. SOCE, store operated Ca2+ entry; VEC, vascular endothelial cells; VSMC, vascular smooth muscle cells; SERCA, sarcoendoplasmic reticulum calcium transport ATPase, IKCa and SKCa: intermediate and small conductance of Ca2+-activated K+ channels; NKA, Na+/K+-ATPase; and NCX, Na+/Ca2+-exchanger. Busse, R., Edwards, G., Félétou, M., Fleming, I., Vanhoutte, P. M., and Weston, A. H. (2002). EDHF: bringing the concepts together. Trends Pharmacol. Sci. 23, 374–380. doi: 10.1016/S0165-6147(02)02050-3 Asai, M., Takeuchi, K., Saotome, M., Urushida, T., Katoh, H., Satoh, H., et al. (2009). Extracellular acidosis suppresses endothelial function by inhibiting store-operated Ca2+ entry via non-selective cation channels. Cardiovasc. Res. 83, 97–105. doi: 10.1093/cvr/cvp105 The Vasorelaxation Through SOCE/EDH Was Impaired in Colitis In this study, we revealed that SOCE activation upon the ER/Ca2+ store depletion by CPA initiates relaxation of mesenteric artery that is mediated by EDH, which is supported by the following evidence: (1) mechanical removal of endothelium resulted in nearly complete inhibition of CPA-induced vasorelaxation; (2) high potassium to pre-contract the vessels significantly inhibited CPA-induced vasorelaxation; (3) while both NO and PGI2 inhibitors did not alter the CPA-induced vasorelaxation, KCa inhibitor significantly inhibited it but KCa activator promoted it; and (4) the CPA-induced vasorelaxation was attenuated by SOCE blockers, and the endothelial SOCE March 2021 \| Volume 12 \| Article 639857 10 SOCE/EDH in Mesenteric Arteries Function Zhang et al. FIGURE 9 \| The underlying mechanisms of the SOCE/EDH-mediated vasorelaxation of mesenteric arteries in health and its impairments in the pathogenesis of colitis. The SOCE/EDH-mediated vasorelaxation in health (left panel) and its impairments in colitis (right panel). CPA inhibits the SERCA to activate the SOCE and induce Ca2+ signaling that stimulates IKCa and SKCa on vascular endothelial cells (VEC), leading to K+ efflux. An increase in extracellular K+ between VEC and VSMC activates NKA to eventually cause vasorelaxation through hyperpolarization. Moreover, NKA activation reduces [Na+]i in VSMC, which stimulates Na+/Ca2+-exchange (NCX) activity to decreases [Ca2+]i, resulting in further vasorelaxation. However, the SOCE/EDH-mediated vasorelaxation is likely impaired by inflammatory factors-induced endothelial dysfunction in the pathogenesis of colitis. SOCE, store operated Ca2+ entry; VEC, vascular endothelial cells; VSMC, vascular smooth muscle cells; SERCA, sarcoendoplasmic reticulum calcium transport ATPase, IKCa and SKCa: intermediate and small conductance of Ca2+-activated K+ channels; NKA, Na+/K+-ATPase; and NCX, Na+/Ca2+-exchanger. FIGURE 9 \| The underlying mechanisms of the SOCE/EDH-mediated vasorelaxation of mesenteric arteries in health and its impairments in the pathogenesis of colitis. The SOCE/EDH-mediated vasorelaxation in health (left panel) and its impairments in colitis (right panel). CPA inhibits the SERCA to activate the SOCE and induce Ca2+ signaling that stimulates IKCa and SKCa on vascular endothelial cells (VEC), leading to K+ efflux. An increase in extracellular K+ between VEC and VSMC activates NKA to eventually cause vasorelaxation through hyperpolarization. Moreover, NKA activation reduces [Na+]i in VSMC, which stimulates Na+/Ca2+-exchange (NCX) activity to decreases [Ca2+]i, resulting in further vasorelaxation. However, the SOCE/EDH-mediated vasorelaxation is likely impaired by inflammatory factors-induced endothelial dysfunction in the pathogenesis of colitis. Asai, M., Takeuchi, K., Saotome, M., Urushida, T., Katoh, H., Satoh, H., et al. (2009). Extracellular acidosis suppresses endothelial function by inhibiting store-operated Ca2+ entry via non-selective cation channels. Cardiovasc. Res. 83, 97–105. doi: 10.1093/cvr/cvp105 Frontiers in Physiology \| www.frontiersin.org Asai, M., Takeuchi, K., Saotome, M., Urushida, T., Katoh, H., Satoh, H., et al. (2009). Extracellular acidosis suppresses endothelial function by inhibiting store-operated Ca2+ entry via non-selective cation channels. Cardiovasc. Res. 83, 97–105. doi: 10.1093/cvr/cvp105 Busse, R., Edwards, G., Félétou, M., Fleming, I., Vanhoutte, P. M., and Weston, A. H. (2002). EDHF: bringing the concepts together. Trends Pharmacol. Sci. 23, 374–380. doi: 10.1016/S0165-6147(02)02050-3 REFERENCES Endothelium- dependent hyperpolarization: a role in the control of vascular tone. Trends Pharmacol. Sci. 16, 23–30. doi: 10.1016/S0165-6147(00)88969-5 Gasbarrini, G., Montalto, M., Santoro, L., Curigliano, V., D’Onofrio, F., Gallo, A., et al. (2008). Intestine: organ or apparatus? Dig. Dis. 26, 92–95. doi: 10.1159/000116765 Parkington, H. C., Coleman, H. A., and Tare, M. (2004). Prostacyclin and endothelium-dependent hyperpolarization. Pharmacol. Res. 49, 509–514. doi: 10.1016/j.phrs.2003.11.012 Gluais, P., Edwards, G., Weston, A. H., Falck, J. R., Vanhoutte, P. M., and Félétou, M. (2005). Role of SKCa and IKCa in endothelium-dependent hyperpolarizations of the Guinea-pig isolated carotid artery. Br. J. Pharmacol. 144, 477–485. doi: 10.1038/sj.bjp.0706003 j Putney, J. W. Jr. (1990). Capacitative calcium entry revisited. Cell Calcium 11, 611–624. doi: 10.1016/0143-4160(90)90016-N Rocha, M. L., and Bendhack, L. M. (2009). Relaxation evoked by extracellular Ca2+ in rat aorta is nerve-independent and involves sarcoplasmic reticulum and L-type Ca2+ channel. Vasc. Pharmacol. 50, 98–103. doi: 10.1016/j. vph.2008.11.004 Guo, Y., Lu, C., Zhang, L., Wan, H., Jiang, E., Chen, Y., et al. (2021). Nutrient- induced hyperosmosis evokes vasorelaxation via TRPV1-mediated endothelium- dependent hyperpolarization in healthy and colitis mice. Br. J. Pharmacol. 178, 689–708. doi: 10.1111/bph.15322 Sankaranarayanan, A., Raman, G., Busch, C., Schultz, T., Zimin, P. I., Hoyer, J., et al. (2009). Naphtho[1,2-d]thiazol-2-ylamine (SKA-31), a new activator of KCa2 and KCa3.1 potassium channels, potentiates the endothelium-derived hyperpolarizing factor response and lowers blood pressure. Mol. Pharmacol. 75, 281–295. doi: 10.1124/mol.108.051425 Guo, Y., Yang, X., He, J., Liu, J., Yang, S., and Dong, H. (2018). Important roles of the Ca2+-sensing receptor in vascular health and disease. Life Sci. 209, 217–227. doi: 10.1016/j.lfs.2018.08.016hl Hatoum, O. A., and Binion, D. G. (2005). The vasculature and inflammatory bowel disease: contribution to pathogenesis and clinical pathology. Inflamm. Bowel Dis. 11, 304–313. doi: 10.1097/01.MIB.0000160772.78951.61 Shimokawa, H., Yasutake, H., Fujii, K., Owada, M. K., Nakaike, R., Fukumoto, Y., et al. (1996). The importance of the hyperpolarizing mechanism increases as the vessel size decreases in endothelium-dependent relaxations in rat mesenteric circulation. J. Cardiovasc. Pharmacol. 28, 703–711. doi: 10.1097/000 05344-199611000-00014 Hatoum, O. A., Binion, D. G., Otterson, M. F., and Gutterman, D. D. (2003a). Acquired microvascular dysfunction in inflammatory bowel disease: loss of nitric oxide-mediated vasodilation. Gastroenterology 125, 58–69. doi: 10.1016/ S0016-5085(03)00699-1 Taylor, C. W. (2006). Store-operated Ca2+ entry: a STIMulating stOrai. Trends Biochem. Sci. 31, 597–601. doi: 10.1016/j.tibs.2006.09.007 Hatoum, O. A., Miura, H., and Binion, D. G. (2003b). The vascular contribution in the pathogenesis of inflammatory bowel disease. REFERENCES Aneman, A., Pettersson, A., Eisenhofer, G., Friberg, P., Holm, M., von Bothmer, C., et al. (1997). Sympathetic and renin-angiotensin activation during graded hypovolemia in pigs: impact on mesenteric perfusion and duodenal mucosal function. Shock 8, 378–384. doi: 10.1097/00024382- 199711000-00011 Frontiers in Physiology \| www.frontiersin.org March 2021 \| Volume 12 \| Article 639857 11 SOCE/EDH in Mesenteric Arteries Function Zhang et al. Kruse, H. J., Grünberg, B., Siess, W., and Weber, P. C. (1994). Formation of biologically active autacoids is regulated by calcium influx in endothelial cells. Arterioscler. Thromb. 14, 1821–1828. doi: 10.1161/01. ATV.14.11.1821 Cocks, T. M., Little, P. J., Angus, J. A., and Cragoe, E. J. Jr. (1988). Amiloride analogues cause endothelium-dependent relaxation in the canine coronary artery in vitro: possible role of Na+/Ca2+ exchange. Br. J. Pharmacol. 95, 67–76. doi: 10.1111/j.1476-5381.1988.tb16549.x Crane, G. J., Gallagher, N., Dora, K. A., and Garland, C. J. (2003). Small‐ and intermediate-conductance calcium-activated K+ channels provide different facets of endothelium-dependent hyperpolarization in rat mesenteric artery. J. Physiol. 553, 183–189. doi: 10.1113/jphysiol.2003.051896 Li, H., Hong, D. H., Son, Y. K., Na, S. H., Jung, W. K., Bae, Y. M., et al. (2015). Cilostazol induces vasodilation through the activation of Ca2+-activated K+ channels in aortic smooth muscle. Vasc. Pharmacol. 70, 15–22. doi: 10.1016/j.vph.2015.01.002 J. Physiol. 553, 183–189. doi: 10.1113/jphysiol.2003.051896 Crane, G. J., and Garland, C. J. (2004). Thromboxane receptor stimulation associated with loss of SKCa activity and reduced EDHF responses in the rat isolated mesenteric artery. Br. J. Pharmacol. 142, 43–50. doi: 10.1038/sj.bjp.0705756 Lin, S., Fagan, K. A., Li, K. X., Shaul, P. W., Cooper, D. M., and Rodman, D. M. (2000). Sustained endothelial nitric-oxide synthase activation requires capacitative Ca2+ entry. J. Biol. Chem. 275, 17979–17985. doi: 10.1074/ jbc.275.24.17979 Dedkova, E. N., and Blatter, L. A. (2002). Nitric oxide inhibits capacitative Ca2+ entry and enhances endoplasmic reticulum Ca2+ uptake in bovine vascular endothelial cells. J. Physiol. 539, 77–91. doi: 10.1113/jphysiol.2001.013258 Liou, J., Kim, M. L., Heo, W. D., Jones, J. T., Myers, J. W., Ferrell, J. E. Jr., et al. (2005). STIM is a Ca2+ sensor essential for Ca2+-store-depletion- triggered Ca2+ influx. Curr. Biol. 15, 1235–1241. doi: 10.1016/j. cub.2005.05.055 Dora, K. A., Sandow, S. L., Gallagher, N. T., Takano, H., Rummery, N. M., Hill, C. E., et al. (2003). Myoendothelial gap junctions may provide the pathway for EDHF in mouse mesenteric artery. J. Vasc. Res. 40, 480–490. doi: 10.1159/000074549 Matchkov, V. REFERENCES V., Gustafsson, H., Rahman, A., Briggs Boedtkjer, D. M., Gorintin, S., Hansen, A. K., et al. (2007). Interaction between Na+/K+-pump and Na+/ Ca2+-exchanger modulates intercellular communication. Circ. Res. 100, 1026–1035. doi: 10.1161/01.RES.0000262659.09293.56 Edwards, D. H., Li, Y., and Griffith, T. M. (2008). Hydrogen peroxide potentiates the EDHF phenomenon by promoting endothelial Ca2+ mobilization. Arterioscler. Thromb. Vasc. Biol. 28, 1774–1781. doi: 10.1161/ATVBAHA. 108.172692 Matoba, T., and Shimokawa, H. (2003). Hydrogen peroxide is an endothelium- derived hyperpolarizing factor in animals and humans. J. Pharmacol. Sci. 92, 1–6. doi: 10.1254/jphs.92.1 Félétou, M., and Vanhoutte, P. M. (2007). Endothelium-dependent hyperpolarizations: past beliefs and present facts. Ann. Med. 39, 495–516. doi: 10.1080/07853890701491000 McGrath, J. C., and Lilley, E. (2015). Implementing guidelines on reporting research using animals (ARRIVE etc.): new requirements for publication in BJP. Br. J. Pharmacol. 172, 3189–3193. doi: 10.1111/bph.12955 Félétou, M., and Vanhoutte, P. M. (2009). EDHF: an update. Clin. Sci. 117, 139–155. doi: 10.1042/CS20090096 Meir, M., Burkard, N., Ungewiß, H., Diefenbacher, M., Flemming, S., Kannapin, F., et al. (2019). Neurotrophic factor GDNF regulates intestinal barrier function in inflammatory bowel disease. J. Clin. Invest. 129, 2824–2840. doi: 10.1172/ JCI120261 Fukao, M., Hattori, Y., Kanno, M., Sakuma, I., and Kitabatake, A. (1995). Thapsigargin‐ and cyclopiazonic acid-induced endothelium-dependent hyperpolarization in rat mesenteric artery. Br. J. Pharmacol. 115, 987–992. doi: 10.1111/j.1476-5381.1995.tb15908.x Mori, M., Stokes, K. Y., Vowinkel, T., Watanabe, N., Elrod, J. W., Harris, N. R., et al. (2005). Colonic blood flow responses in experimental colitis: time course and underlying mechanisms. Am. J. Physiol. Gastrointest. Liver Physiol. 289, G1024–G1029. doi: 10.1152/ajpgi.00247.2005 Garland, C. J., Bagher, P., Powell, C., Ye, X., Lemmey, H. A. L., Borysova, L., et al. (2017). Voltage-dependent Ca2+ entry into smooth muscle during contraction promotes endothelium-mediated feedback vasodilation in arterioles. Sci. Signal. 10:eaal3806. doi: 10.1126/scisignal.aal3806 Okayasu, I., Hatakeyama, S., Yamada, M., Ohkusa, T., Inagaki, Y., and Nakaya, R. (1990). A novel method in the induction of reliable experimental acute and chronic ulcerative colitis in mice. Gastroenterology 98, 694–702. doi: 10.1016/0016-5085(90)90290-H Garland, C. J., and Dora, K. A. (2017). EDH: endothelium-dependent hyperpolarization and microvascular signalling. Acta Physiol. 219, 152–161. doi: 10.1111/apha.12649 Papa, A., Scaldaferri, F., Danese, S., Guglielmo, S., Roberto, I., Bonizzi, M., et al. (2008). Vascular involvement in inflammatory bowel disease: pathogenesis and clinical aspects. Dig. Dis. 26, 149–155. doi: 10.1159/000116773 Garland, C. J., Plane, F., Kemp, B. K., and Cocks, T. M. (1995). Zhang, S. L., Yeromin, A. V., Zhang, X. H., Yu, Y., Safrina, O., Penna, A., et al. (2006). Genome-wide RNAi screen of Ca2+ influx identifies genes that regulate Ca2+ release-activated Ca2+ channel activity. Proc. Natl. Acad. Sci. U. S. A. 103, 9357–9362. doi: 10.1073/pnas.0603161103 REFERENCES Am. J. Physiol. Heart Circ. Physiol. 285, H1791–H1796. doi: 10.1152/ajpheart.00552.2003 Ueda, A., Ohyanagi, M., Koida, S., and Iwasaki, T. (2005). Enhanced release of endothelium-derived hyperpolarizing factor in small coronary arteries from rats with congestive heart failure. Clin. Exp. Pharmacol. Physiol. 32, 615–621. doi: 10.1111/j.0305-1870.2005.04240.x Kilkenny, C., Browne, W. J., Cuthill, I. C., Emerson, M., and Altman, D. G. (2010). Improving bioscience research reporting: the ARRIVE guidelines for reporting animal research. PLoS Biol. 8:e1000412. doi: 10.1371/journal. pbio.1000412 Vanhoutte, P. M., Shimokawa, H., Feletou, M., and Tang, E. H. (2017). Endothelial dysfunction and vascular disease—a 30th anniversary update. Acta Physiol. 219, 22–96. doi: 10.1111/apha.12646 March 2021 \| Volume 12 \| Article 639857 Frontiers in Physiology \| www.frontiersin.org 12 SOCE/EDH in Mesenteric Arteries Function Zhang et al. Várnai, P., Hunyady, L., and Balla, T. (2009). STIM and Orai: the long-awaited constituents of store-operated calcium entry. Trends Pharmacol. Sci. 30, 118–128. doi: 10.1016/j.tips.2008.11.005 Zuccolo, E., Bottino, C., Diofano, F., Poletto, V., Codazzi, A. C., Mannarino, S., et al. (2016). Constitutive store-operated Ca2+ entry leads to enhanced nitric oxide production and proliferation in infantile hemangioma-derived endothelial colony-forming cells. Stem Cells Dev. 25, 301–319. doi: 10.1089/scd.2015.0240 j Wan, H., Xie, R., Xu, J., He, J., Tang, B., Liu, Q., et al. (2017). Anti-proliferative effects of nucleotides on gastric cancer via a novel P2Y6/SOCE/Ca2+/β- catenin pathway. Sci. Rep. 7:2459. doi: 10.1038/s41598-017-02562-x Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Yada, T., Shimokawa, H., and Tachibana, H. (2018). Endothelium-dependent hyperpolarization-mediated vasodilatation compensates nitric oxide-mediated endothelial dysfunction during ischemia in diabetes-induced canine coronary collateral microcirculation in vivo. Microcirculation 25:e12456. doi: 10.1111/ micc.12456 Copyright © 2021 Zhang, Chen, Dong and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Zhang, S. L., Yeromin, A. V., Zhang, X. H., Yu, Y., Safrina, O., Penna, A., et al. (2006). Genome-wide RNAi screen of Ca2+ influx identifies genes that regulate Ca2+ release-activated Ca2+ channel activity. Proc. Natl. Acad. Sci. U. S. A. Frontiers in Physiology \| www.frontiersin.org Várnai, P., Hunyady, L., and Balla, T. (2009). STIM and Orai: the long-awaited constituents of store-operated calcium entry. Trends Pharmacol. Sci. 30, 118–128. doi: 10.1016/j.tips.2008.11.005 March 2021 \| Volume 12 \| Article 639857 REFERENCES 103, 9357–9362. doi: 10.1073/pnas.0603161103 March 2021 \| Volume 12 \| Article 639857 Frontiers in Physiology \| www.frontiersin.org 13
https://openalex.org/W3198260234	https://jurnal.harapan.ac.id/index.php/JPH/article/download/404/268	Indonesian	null	Analisis Yuridis Terhadap Kewajiban Magang dan Relevansi dengan Pengangkatan Pejabat Pembuat Akta Tanah (Ppat)	Jurnal Perspektif Hukum	2,021	cc-by	6,660	ANALISIS YURIDIS TERHADAP KEWAJIBAN MAGANG DAN RELEVANSI DENGAN PENGANGKATAN PEJABAT PEMBUAT AKTA TANAH (PPAT) Eka Cristy Sembiring1) Magister Kenotariatan Universitas Sumatera Utara, ekacristy2@gmail.com Eka Cristy Sembiring1) tariatan Universitas Sumatera Utara, ekacristy2@g 24 Tahun 1997 disebutkan bahwa Pejabat Pembuat Akta Tanah, selanjutnya disebut ABSTRACT The Official for this research is to discover the obligation of candidates of PPAT (Officials Empowered to Draw up Land Deeds), to take an internship: in which they are obliged to understand and help the process of land activity and service, recruitment and verification process of registered deeds as well as verification of juridical data op application for land title. The primary task of PPAT is carry out partland registration activities by drawing up deeds as evidence for having taken particular legal actions regarding land title or ownership right over apartment units, that is made the ground for registration of changes in land registration resulted from the legal actions. This research employs normative juridical method in form of document study, which studies the obligations of candidates of PPAT (Officials Empowered to Draw up Land Deeds) to take an internship and its relevance with appointment of PPAT. This research is descriptive; it describes the obligation of PPAT to take an internship. The legal materials used in this research are sourced from results of library research such as primary, secondary and tertiary legal materials. In addition, this research is supported by interviews with relevant parties to complete this thesis. These legal materials that have been collected are firstly described by legal and non-legal proportion, then interpreted to be further estimated and evaluated; argumentation is provided to draw conclusion for the research problem. The research result demonstrate that internship of PPAT is the obligationsof every candidate of PPAT before they are appointed PPAT. Internship is taken to provide the candidate theoretical and practicalacademic knowledge, to provide the candidate skills and expertise in technique of Drawing up Deeds as fuel for practice as PPAT. The internship term of PPAT candidates consists of 6 (six months) in the land office and 6 (six) months in PPAT offices. The enactment of PPAT internship encourages better performance for PPAT candidates who will put the knowledge into practice in the future; thus, the knowledge gained during internship can be directly applied. Keywords: Candidates of PPAT,Internships of PPAT, Obligation of PPAT ABSTRAK Jabatan Pejabat Pembuat Akta Tanah (PPAT) diatur dalam Peraturan Pemerintah Republik Indonesia Nomor 24 Tahun 2016 tentang perubahan atas Peraturan Pemerintah Nomor 37 Tahun 1998 tentang Peraturan Jabatan Pejabat Pembuat Akta Tanah, Pasal 1 angka (1) Peraturan Pemerintah Nomor 24 Tahun 1997 disebutkan bahwa Pejabat Pembuat Akta Tanah, selanjutnya disebut 192 PPAT adalah pejabat umum yang diberi kewenangan untuk membuat akta-akta otentik mengenai perbuatan hukum tertentu mengenai hak atas tanah atau Hak Milik Atas Satuan Rumah Susun. PPAT adalah pejabat umum yang diberi kewenangan untuk membuat akta-akta otentik mengenai perbuatan hukum tertentu mengenai hak atas tanah atau Hak Milik Atas Satuan Rumah Susun. Didalam Pasal 1 Peraturan Kepala Badan Pertanahan Nasional Nomor 1 Tahun 2006, tentang ketentuan Pelaksanaan Peraturan Pemerintah Nomor 37 Tahun 1998 Tentang Peraturan Jabatan Pejabat Pembuat Akta Tanah, menyebutkan bahwa Pejabat Pembuat Akta Tanah, selanjutnya disebut PPAT adalah pejabat umum yang diberi kewenangan untuk membuat akta- akta otentik mengenai perbuatan hukum tertentu mengenai hak atas tanah atau Hak Milik Atas Satuan Rumah Susun. Dalam Ketentuan Peraturan Pemerintah Nomor 37 Tahun 1998 tentang Peraturan Jabatan Pejabat Pembuat Akta Tanah, dapat dilihat Pejabat Pembuat Akta Tanah terdiri dari 3 (tiga) jenis, yakni :  Pejabat Pembuat Akta Tanah, selanjutnya disebut PPAT adalah pejabat umum yang diberi kewenangan untuk membuat akta-akta otentik mengenai perbuatan hukum tertentu mengenai hak atas tanah atau Hak Milik Atas Satuan Rumah Susun. Kedudukan PPAT ini dikenal dengan pejabat umum.  PPAT Sementara adalah pejabat Pemerintah yang ditunjuk karena jabatannya untuk melaksanakan tugas PPAT dengan membuat akta PPAT di daerah yang belum cukup terdapat PPAT.  PPAT Sementara adalah pejabat Pemerintah yang ditunjuk karena jabatannya untuk melaksanakan tugas PPAT dengan membuat akta PPAT di daerah yang belum cukup terdapat PPAT. Keberadaan dari Pejabat Pembuat Akta Tanah, selanjutnya disebut PPAT adalah pejabat umum yang diberi kewenangan untuk membuat akta-akta otentik mengenai perbuatan hukum tertentu mengenai hak atas tanah atau Hak Milik Atas Satuan Rumah Susun. Kedudukan PPAT ini dikenal dengan pejabat umum yang merangkap jabatan sebagai Notaris. Tugas pokok PPAT adalah melaksanakan sebagian kegiatan pendaftaran tanah dengan membuat akta sebagai bukti telah dilakukannya perbuatan hukum tertentu mengenai hak atas tanah atau Hak Milik Atas Satuan Rumah Susun, yang akan dijadikan dasar bagi pendaftaran perubahan data pendaftaran tanah yang diakibatkan oleh perbuatan hukum itu. Kata-kata kunci : Calon PPAT, Magang PPAT, Kewajiban PPAT. ABSTRAK Penelitian ini penulis menggunakan metode penelitian hukum normatif dalam bentuk studi dokumen (studi kasus), yaitu suatu jenis penelitian yang akan mengkaji kewajiban magang dan relevansi dengan pengangkatan PPAT, sedangkan jika dilihat dari sifatnya, maka penelitian ini bersifat deskriptif yaitu suatu penelitian dengan menggambarkan tentang kewajiban magang PPAT. Bahan hukum yang dipergunakan dalam penelitian ini berasal dari hasil penelitian kepustakaan berupa bahan hukum primer, bahan hukum sekunder, dan bahan hukum tertier, selain itu penelitian ini didukung dengan wawancara kepada pihak-pihak yang terkait dalam pembuatan tesis ini.Bahan hukum yang telah terkumpulkan tersebut terlebih dahulu dilakukan deskripsi dengan penguraian proporsi-proporsi hukum dan non hukum yang dijumpai, diinterpretasikan untuk selanjutnya disistematisasi, dievaluasi serta diberikan argumentasi untuk mendapat kesimpulan atas permasalahan yang dibahas. Hasil penelitian menunjukan bahwa magang PPAT merupakan kewajiban yang harus dijalani setiap calon PPAT sebelum diangkat sebagai PPAT.Magang dilakukan untuk memberikan ilmu dalam bidang akademis yang secara teori dan praktek untuk calon PPAT, memberikan keahlian dan kemahiran calon PPAT dalam membuat Teknik Pembuatan Akta sebagai bekal dalam praktek sebagai Pejabat Pembuat Akta Tanah (PPAT). Lama magang PPAT dilakukan selama 1 tahun dengan pembagian 6 bulan di kantor pertanahan dan 6 bulan di kantor PPAT. Dampak dari diberlakukannya magang PPAT tersebut dapat memberikan kinerja yang lebih baik bagi calon PPAT, dimana ketika nantinya berpraktek maka ilmu yang didapat ketika magang bisa diaplikasikan secara langsung. Kata-kata kunci : Calon PPAT, Magang PPAT, Kewajiban PPAT. I. PENDAHULUAN Latar Belakang 193 Profesi di bidang hukum merupakan profesi leluhur dan terhormat atau pun profesi mulia dan sangatlah berpengaruh pada tatanan kenegaraan. Profesi di bidang hukum, antaranya: Polisi, Advokat, Jaksa, Hakim, serta Notaris dan juga Pejabat Pembuat Akta Tanah (PPAT) merupakan pilar-pilar utama dalam penegakan supremasi hukum dan memberikan pelayananbagi masyarakat dalam bidang hukum untuk menjalankan strategi pembangunan hukum nasional. Profesionalitas dan integritas yang tinggi dari masing-masing individu yang menjalankan profesi dibidang hukum mutlak dibutuhkan sesuai dengan tugas pokok, fungsi dan kewenangannya masing-masing. g g p g g y g g Apabila Profesi itu berkenaan dengan bidang hukum, maka kelompok profesi itu disebut kelompok profesi hukum.Pengemban profesi hukum bekerja secara profesional dan fungsional. kelompok profesi memiliki tingkat ketelitian, kehati-hatian, ketekunan, kritis dan pengabdian yang tinggi karena mereka bertanggung jawab kepada diri sendiri dan kepada semua anggota masyarakat, bahkan kepada Tuhan Yang Maha Esa. ABSTRAK Profesi hukum sebagai profesi terhormat, terdapat nilai-nilai moral dan profesi yang harus ditaati oleh aparatur hukum yang menjalankan profesi tersebut, yaitu sebagai berikut: kejujuran, otentik, bertanggung jawab, kemandirian moral dan keberanian moral (Muhammad, 1997:62). PPAT sebagai salah satu profesi di bidang hukum yang mendapatkan delegasi kewenangan dari pemerintah untuk membuat akta outentik bagi kepastian hukum masyarakat, dalam menjalankan profesinya selain harus berdasarkan pada peraturaan pemerintah, juga harus memegang teguh nilai-nilai moral profesi tersebut. Dalam menjalankan tugasnya PPAT harus professional, yaitu menjalankan tugas selalu mengutamakan keahlihan berlandasan kode etik dan ketentuan peraturan yang berlaku, kinerjanya dapat dipercaya dan amanah, bekerja sesuai Standar Operasional Prosedural (SOP) dari memulai pekerjaan, menjalankan dan menghasilkan hasil yang akurat. selain professional, PPAT juga harus mampu memberikan penyuluhan hukum yang tepat dan baik untuk para penghadap. p g p Menurut E. Utrecht, seperti dikutip di dalam Pengantar Hukum Administrasi Indonesia, ”Jabatan” (ambht) adalah suatu lingkungan pekerjaan tetap (kring van vaste werkzaamheden) yang diadakan dan dilakukan guna kepentingan negara (kepentingan umum). Selanjutnya dijelaskan bahwa yang dimaksud dengan “lingkungan pekerjaan tetap” ialah suatu lingkugan pekerjaan yang sebanyak- sebanyaknya dapat dinyatakan dengan tepat-teliti/seakurat mungkin (zoveel mogeljk nauwkeurig omschhreven) dan yang bersifat duurzam (tidak dapat diubah begitu saja) (Utrecht, 2010:159). Oleh karena itu, maka jabatan merupakan subjek hukum (person), sehingga kekuasaan tidak diberikan kepada orang pejabat, tetapi diberikan kepada jabatan (lingkungan pekerjaan).Sebagai pendukung suatu hak dan kewajiban, walaupun pejabatnya berganti-ganti. Pembentukan hukum secara spesifisik yang mengatur tentang Camat sebagai PPAT Sementara khususnya pada daerah-daerah pedesaan dan terpencil yang belum ada PPAT memang masih sangat dibutuhkan. Dalam Peraturan Pemerintah Nomor 10 Tahun 1961 tentang Pendaftaran Tanah yang telah diganti dengan Peraturan Pemerintah Nomor 24 Tahun 1997 tentang Pendaftaran tanah, diatur bahwa selama dalam suatu wilayah kecamatan belum diangkat Pejabat Pembuat Akta Tanah (PPAT) maka Camat demi jabatannya masih bertindak sebagaiPejabat Pembuat Akta Tanah (PPAT) Sementara. (Benny, 2004:10-11). PPAT Khusus adalah pejabat Badan Pertanahan Nasional yang ditunjuk karena jabatannya untuk melaksanakan tugas PPAT dengan membuat akta PPAT tertentu khusus dalam rangka pelaksanaan program atau tugas Pemerintah tertentu. PPAT Khusus biasanya dikenal sebagai Badan Pertanahan Nasional (BPN). ABSTRAK Tugas pokok PPAT yang terdapat dalam Pasal 2 angka (1) Peraturan Pemerintah Nomor 37 Tahun 1998 menyebutkan bahwa PPAT memiliki tugas pokok melaksanakan sebagian kegiatan pendaftaran tanah dengan membuat akta sebagai bukti telah dilakukannya perbuatan hukum tertentu mengenai hak atas tanah atau Hak Milik Atas Satuan Rumah Susun, yang akan Tugas pokok PPAT yang terdapat dalam Pasal 2 angka (1) Peraturan Pemerintah Nomor 37 Tahun 1998 menyebutkan bahwa PPAT memiliki tugas pokok melaksanakan sebagian kegiatan pendaftaran tanah dengan membuat akta sebagai bukti telah dilakukannya perbuatan hukum tertentu mengenai hak atas tanah atau Hak Milik Atas Satuan Rumah Susun, yang akan 194 dijadikan dasar bagi pendaftaran perubahan data pendaftaran tanah yang diakibatkan oleh perbuatan hukum itu. Kemudian di tegaskan didalam Pasal 2 angka dijadikan dasar bagi pendaftaran perubahan data pendaftaran tanah yang diakibatkan oleh perbuatan hukum itu. Kemudian di tegaskan didalam Pasal 2 angka (2) Peratuan Pemerintah Nomor 37 Tahun 1998 tentang Peraturan Jabatan Pejabat Pembuat Akta Tanah, Perbuatan hukum sebagaimana dimaksud pada angka (1) adalah sebagai berikut : jual beli; tukar menukar; hibah; pemasukan ke dalam perusahaan (inbreng); pembagian hak b b i H k G B /H k P k i T h H k Milik b i H k perbuatan hukum itu. Kemudian di tegaskan didalam Pasal 2 angka (2) Peratuan Pemerintah Nomor 37 Tahun 1998 tentang Peraturan Jabatan Pejabat Pembuat Akta Tanah, Perbuatan hukum sebagaimana dimaksud pada angka (1) adalah sebagai berikut : jual beli; tukar menukar; hibah; pemasukan ke dalam perusahaan (inbreng); pembagian hak bersama; pemberian Hak Guna Bangunan/Hak Pakai atas Tanah Hak Milik; pemberian Hak Tanggungan; pemberian Kuasa membebankan Hak Tanggungan. (2) Peratuan Pemerintah Nomor 37 Tahun 1998 tentang Peraturan Jabatan Pejabat Pembuat Akta Tanah, Perbuatan hukum sebagaimana dimaksud pada angka (1) adalah sebagai berikut : jual beli; tukar menukar; hibah; pemasukan ke dalam perusahaan (inbreng); pembagian hak bersama; pemberian Hak Guna Bangunan/Hak Pakai atas Tanah Hak Milik; pemberian Hak Tanggungan; pemberian Kuasa membebankan Hak Tanggungan. Untuk dapat melaksanakan tugas pokok tersebut diatas, seseorang Pejabat Pembuat Akta Tanah atau PPAT mempunyai kewenangan membuat akta otentik mengenai semua perbuatan hukum sebagaimana yang dimaksud dalam Pasal 2 angka (2) mengenai hak atas tanah dan Hak Milik Atas Satuan Rumah Susun. Seseorang yang mempunyai keinginan untuk menjadi PPAT wajib menyelesaikan Studi dengan Program Prodi Khusus PPAT maupun dengan Strata Dua Magister Kenotariatan. ABSTRAK Dewasa ini dengan semakin banyak peminat dari Pejabat Pembuat Akta Tanah didukung dengan banyak Universitas lainnya yang membuka Program Studi Kenotariatan, maka hal ini memicu pemerintah untuk lebih menyeleksi calon PPAT yang nantinya akan mengemban tugas dan tanggungjawab yang diberikan oleh pemerintah melalui proses magang yang dilakukan di Kantor Pertanahan dan di Kantor Pejabat Pembuat Akta Tanah (PPAT). Perkembangan PPAT saat ini sangat banyak peminatnya, dan permasalahan hukum tentang pertanahan juga semakin marak di Indonesia, hal tersebut salah satunya dikarenakan potensi ilmu dari sumber daya manusia tersebut yang masih kurang, untuk itu pemerintah membuat program magang di Kantor Pertanahan dan di Kantor PPAT. Apabilaseseorang berkeinginan untuk menjadi PPAT maka harus melalui tahapan-tahapan dan memenuhi sejumlah persyaratan apabila ingin mengajukan diri menjadi calon PPAT, calon PPATbisa memilih sendiri dimana akanmelaksanakan magang ataupun bekerja dengan tetap mendapatkan rekomendasi dari organisasi PPAT. Proses magang yang seharusnya dijalani oleh setiap calon PPAT wajib dilaksanakan sebelum pengangkatan PPAT. Syarat untuk menjadi seorang Pejabat Pembuat Akta Tanah (PPAT) salah satunya ialah telah menjalani magang selama 1 (satu) tahun. Pelaksanaan magang dilakukan sebelum mengikuti ujian, atau setelah lulus ujian dan sebelum diangkat sebagai Pejabat Pembuat Akta Tanah (PPAT). Menurut Peraturan Menteri Agraria dan Tata Ruang/Kepala Badan Pertanahan Nasional Republik Indonesia Nomor 20 Tahun 2018 Tentang Tata Cara Ujian, Magang, Pengangkatan, Pengangkatan Kembali, dan Perpanjangan Masa Jabatan Pejabat Pembuat Akta Tanah, Pasal 17 angka(1) dan (2) menyatakan bahwa, Magang dilaksanakan selama 1 (satu) tahun pada Kantor Pertanahan dan Kantor Pejabat Pembuat Akta Tanah (PPAT), dengan pembagian waktu 6 (enam) bulan di Kantor Pertanahan dan 6 (enam) bulan di Kantor Pejabat Pembuat Akta Tanah (PPAT). Profesi Pejabat Pembuat Akta Tanah (PPAT), jabatan ini melaksanakan pembuatan akta yang berhubungan dengan perbuatan hukum khusus tentang tanah dan bangunan. Dalam melaksanakan tugas dan tanggung jawab sebagai pejabat umum, masih ada terdapat pelanggaran-pelanggaran yang dilakukan, masih ada penyalahgunaan kewenangan jabatan, kurang memahami dalam pembuatan akta, sebagai akibat kurangnya kesadaran dan pemahaman tentang jabatan yang diemban sebagai PPAT. Hakikat sebenarnya dari pemerintah membuat peraturan tentang magang PPAT agar setiap calon PPAT, yang akan diangkat dapat menjalani profesinya dengan professional dan terampil. Rumusan Masalah Berdasarkan uraian dalam latar belakang masalah tersebut di atas, permasalahan dalam penelitian ini adalah Analisis Yuridis Terhadap Kewajiban Magang dan Relevansi dengan Pengangkatan Pejabat Pembuat Akta Tanah (PPAT) II. METODE PENELITIAN II. METODE PENELITIAN 195 Metode adalah “proses, prinsip-prinsip dan tata cara memecahkan suatu masalah”. Penelitian adalah “usaha atau pekerjaan untuk mencari kembali yang dilakukan dengan suatu metode tertentu dengan cara hati-hati, sistematis serta sempurna terhadap permasalahan, sehingga dapat digunakan untuk menyelesaikan atau menjawab permasalahannya. Penelitian hukum merupakan penemuan kembali secara teliti dan cermat bahan hukum atau data hukum untuk memecahkan permasalahan hukum” (Koentjaraningrat, 1997:16). Jenis dan Sifat Penelitian Penelitian ini bersifat deskriptif analisis, maksudnya dari penelitian ini diharapkan diperoleh gambaran secara rinci dan sistematis tentang permasalahan yang akan diteliti. Analisis dimaksudkan berdasarkan gambaran, fakta yang diperoleh akan dilakukan analisis secara cermat untuk menjawab permasalahan.” (Hartono, 1994:101) Penelitian yuridis normatif atau penelitian yang menganalisis hukum, baik yang tertulis dalam buku maupun hukum yang diputuskan oleh hakim melalui proses pengadilan (litigation). Penelitian hukum normatif meneliti hukum dari perspektif internal dengan objek penelitiannya adalah norma hukum. Penelitian hukum normatif berfungsi untuk memberi argumentasi yuridis ketika terjadi kekosongan, kekaburan dan konflik norma. Sifat penelitian ini adalah deskriptif analitis, maksudnya adalah: penelitian ini diharapkan diperoleh gambaran secara rinci dan sistematis tentang permasalahan yang akan diteliti. Analisis dilakukan berdasarkan gambaran, fakta yang diperoleh dan akan dilakukan secara cermat bagaimana menjawab permasalahan dalam menyimpulkan suatu solusi sebagai jawaban dari permasalahan tersebut”. (Hartono, 1994:101). Penelitian ini sering disebut juga penelitian dokumenter untuk memperoleh data sekunder di bidang hukum.Penelitian lebih meliputi penelitian yang mengkaji asas-asas hukum positif yang berasal dari data kepustakaan dan sumber-sumber hukum, peraturan perundang- undangan yang berlaku, sertaunsur- unsurataufaktor-faktoryang berhubungan dengan penelitian ini. Teknik dan Alat Pengumpulan Data Pengumpulan data dalam penelitian ini menggunakan teknik pengumpulan data melalui penelitian kepustakaan (Library Research), yaitu penelitian yang dilakukan dengan cara meneliti bahan pustaka untuk memperoleh data sekunder berupa buku-buku baik koleksi pribadi maupun perpustakaan, artikel baik yang diambil dari media cetak maupun media elektronik, dokumen pemerintah termasuk peraturan pemerintah, peraturan kepala badan pertanahan nasional, peraturan menteri agraria dan tata ruang/kepala badan pertanahan nasional, hasil dari kegiatan pengkajian tersebut kemudian dibuat ringkasan secara sistematis sebagai inti sari hasil pengkajian studi dokumen. Tujuannya adalah untuk mencari konsepsi- konsepsi, teori- teori, pendapat-pendapat atau penemuan yang berkaitan dengan permasalahan penelitian yang dilakukan dengan cara menginventarisis, mempelajari dan mendalami bahan hukum berupa peraturan perundang- undangan, buku-buku, tulisan ilmiah, dokumen-dokumen hukum dan karya-karya ilmiah yang terkait dengan penelitian ini. (Ikhsan dan Siregar, 2009:24) Selain itu penelitian ini juga menggunakan teknik pengumpulan data melalui penelitian lapangan (field research) dengan wawancara informan. Dalam penelitian ini yang menjadi informan adalah 4(empat) orang Pejabat Pembuat Akta Tanah (PPAT), 2 (dua) orang staff pegawai Kantor Pertanahan Kota Medan, 1 (satu) orang staff pegawai Kantor Pertanahan Kabupaten Karo, dan 1 (satu) orang calon Pejabat Pembuat Akta Tanah (PPAT) yang sedang melaksanakan magang di Kantor Pertanahan Kabupaten Karo. Alat pengumpulan data dalam penelitian ini adalah dengan menggunakan studi dokumen dan pedoman wawancara.Studi dokumen atau studi kepustakaan merupakan penelitian untuk mendapatkan konsepsi teori atau doktrin, pemikiran konseptual dan penelitian yang dilakukan secara relevan dengan menginventarisasi pendapat juga latar belakang pemikiran.Pemikiran dan gagasan serta konsepsi tersebut dapat diperoleh melalui peraturan perundang-undangan yang berlaku, literatur dari para pakar yang relevan dengan objek penelitian, yang termuat dalam data ataupun doukumen yang berkaitan dengan permasalahan penelitian. (Yamin, 2007:4) Wawancara adalah situasi peran antar pribadi bertatap muka, ketika seseorang yakni pewawancara mengajukan pertanyaan-pertanyaan yang dirancang untuk memperoleh jawaban-jawaban yang relevan dengan masalah penelitian.( Amirudin dan Asikin , 2006:82) Jenis wawancara ada 3 (tiga), yaitu: Wawancara bebas yaitu pewawancara bebas menanyakan apa saja, tetapi juga mengingat akan data yang dikumpulkan; Wawancara terpimpin yaitu wawancara yang dilakukan oleh pewawancara dengan membawa sederet pertanyaan dan terperinci; Wawancara bebas terpimpin yaitu wawancara yang dikombinasi antara wawancara bebas dan terpimpin (Yamin, 2007:4) Jenis wawancara yang akan digunakan dalam tesis ini adalah wawancara bebas terpimpin, dengan menyiapkan terlebih dahulu pertanyaan-pertanyaan sebagai pedoman wawancara, tetapi tidak menutup kemungkinan juga adanya pertanyaan lain yang sesuai dengan kebutuhan tesis ini. Hasil wawancara yang diperoleh akan digunakan sebagai data pendukung dalam penelitian ini. Sumber Data Penelitian ini menggunakan data sekunder. Data sekunder, yaitu data yang diperoleh dari studi kepustakaan yaitu: arsip-arsip, bahan pustaka, data resmi pada instansi pemerintah, peraturan pemerintah, peraturan kepala badan pertanahan nasional, peraturan menteri agraria dan tata ruang/kepala badan pertanahan nasional, tesis dan makalah yang ada kaitannya dengan masalah yang sedang diteliti, yang terdiri dari: Bahan hukum primer, yaitu bahan hukum yang mengikat. Bahan hukum primer ini sendiri adalah bahan-bahan utama yang akan menjadi dasar untuk membuat penelitian ini. Melalui bahan hukum primer inilah nantinya akan diolah data- data yang akan dimasukkan menjadi substansi-substansi penelitian. Adapun bahan-bahan hukum primer yang akan digunakan adalah segenap peraturan perundang-undangan yang ada. Bahan hukum sekunder, yaitu bahan hukum yang menjelaskan dan pendukung bahan hukum primer yang diperoleh dari berbagai sumber yang berupa beberapa bahan diantaranya hasil penelitian baik dilakukan langsung maupun secara tidak langsung, antara lain seminar, jurnal hukum, majalah, koran, media online, karya tulis ilmiah serta pendapat dari pakar-pakar hukum tentang hibah. Bahan hukum tersier, yaitu bahan-bahan hukum yang sifatnya penunjang untuk dapat memberikan petunjuk dan penjelasan terhadap bahan hukum primer dan sekunder. Bahan hukum tersier ini merupakan bahan tambahan yang juga merupakan pelengkap terhadap data- data yang akan dirangkum dalam mengisi penelitian ini sehingga menjadi karya ilmiah yang nantinya tersusun secara terangkai dan berurutan (Soekanto dan Mamudji, 1995:14). 196 (PPAT) Peningkatan Kualitas Bagi Calon Pejabat Pembuat Akta Tanah (PPAT). Pelaksanaan Peningkatan Kualitas berkaitan dengan kewajiban magang pada calon PPAT. Selaku calon PPAT wajib mengikuti kegiatan Peningkatan Kualitas, sebagai syarat untuk mengajukan pengangkatan PPAT. Pemerintah, dalam hal ini Kementerian Agraria Tata Ruang/Kepala Badan Pertanahan Nasional, mempunyai perhatian yang sangat besar terhadap peningkatan kualitas Pejabat Pembuat Akta Tanah (PPAT). Dengan kualitas yang bagus dan menguasai ilmu pengetahuan, khusunya yang berkaitan dengan bidang pertanahan maupun dalam pembuatan akta-akta yang berkaitan dengan bidang pertanahan, PPAT tersebut akan mampu memberikan pelayanan yang baik kepada masyarakat yang memerlukan jasanya. p y y g p y y g j y Peningkatan Kualitas, yang dalam bahasa inggris, disebut dengan quality improvement,sedangkan dalam bahasa belanda, disebut dengan kwaliteitsverbetering merupakan proses, cara atau perbuatan untuk meningkatkan kualitas. Meningkatkan (derajat atau taraf), mempertinggi atau mengangkat dirinya. Kualitas dikonsepkan sebagai derajat atau taraf, baik kepandaian maupun kecakapan atau mutu. Secara umum peningkatan kualitas dikonsepkan sebagai upaya dari seseorang atau lembaga atau instansi untuk menaikkan tingkat kepandaian atau kecakapan atau mutuPPAT dari kualitas yang rendah menjadi kualitas yang lebih tinggi. “Pengertian peningkatan kualitas ditemukan dalam Pasal 1 angka (5) Peraturan Menteri Agraria dan Tata Ruang/Kepala Badan Pertanahan Nasional Nomor 10 Tahun 2017 tentang Tata Cara Ujian, Magang, Pengangkatan dan Perpanjangan Masa Jabatan Pejabat Pembuat Akta Tanah. Peningkatan Kualitas adalah upaya meningkatkan kemampuan bagi seorang Warga Negara Indonesia sebelum diangkat menjadi PPAT, upaya meningkatkan pengetahuan dibidang pertanahan bagi seorang yang telah menjabat sebagai PPAT dalam waktu tertentu; dan upaya meningkatkan kemampuan bagi Camat yang akan ditunjuk sebagai PPAT sementara. Ada 3 unsur yang tercantum dalam defenisi diatas, yang meliputi : Adanya upaya; Subjeknya; dan Objek. Upaya dikonsepkan sebagai usaha atau ikhtiar untuk menaikkan kepandaian atau mutu dari seorang. Subjek yang ditingkatkan kualitas, yaitu : Warga Negara Indonesia sebelum menjadi PPAT; PPAT; dan Camat. Bidang Ilmu yang akan ditingkatkan kualitasnya, yaitu bidang pertanahan. Landasan Filosofis dilakukan peningktan kualitas calon PPAT adalah dalam rangka meningkatkan kemampuan teoritis dan praktis dari calon PPAT. Dengan adanya kegiatan itu, calon PPAT akan menjadi PPAT yang berkualitas dan Profesional. Landasan Yuridis peningkatan kualitas calon PPAT telah ditentukan dalam Peraturan Menteri Agraria dan Tata Ruang/Kepala Badan Pertanahan Nasional Nomor 10 Tahun 2017 tentang Tata Cara Ujian Magang, Pengangkatan dan Perpanjangan Masa Jabatan Pejabat Pembuat Akta Tanah. Analisis Data Analisis data yang dipergunakan adalah kualitatif terhadap data primer dan data sekunder.Bentuk penelitian yang kualitatif merupakan bentuk penelitian yang sesuai dengan peraturan perundang-undangan sehingga dapat tercapai tujuan dari 197 penelitian ini (Nazir,1986:159). penelitian ini (Nazir,1986:159). III. HASIL DAN PEMBAHASAN Proses Magang PPAT Sesuai Peraturan Menteri Agraria dan Tata Ruang Kepala Badan Pertanahan Nasional Republik Indonesia Nomor 20 Tahun 2018 III. HASIL DAN PEMBAHASAN (PPAT) Ada 4 pasal yang mengatur tentang peningkatan kualitas dalam Peraturan Menteri Agraria dan Tata Ruang/Kepala Badan Pertanahan Nasional, yang meliputi sebagai berikut : Pasal 1 angka (5) mengatur tentang pengertian peningkatan kualitas; Pasal 3 mengatur tentang ruang lingkup pengaturan peraturan menteri ini, yang salah satunya peningkatan kualitas; Pasal 4 mengatur tentang syarat mengikuti ujian PPAT, salah satu syaratnya, yaitu mengikuti peningkatan kualitas; Pasal 5 mengatur tentang penyelenggaraan peningkatan kualitas. Landasan Sosiologis dilakukan peningkatan kualitas adalah karena masih banyaknya calon PPAT yang kualitasnya masih rendah, masih rendahnya kemampuan calon PPAT dalam memahami Peraturan Perundang-undangan yang berkaitan dengan bidang pertanahan, masih rendahnya kemampuan dalam membuat akta PPAT.” (HS, 2019:33-35) 198 Pelaksanaan Peningkatan Kualitas bagi Calon PPAT, yaitu : Pasal 15, menyebutkan bahwa: Peningkatan Kualitas diselenggarakan oleh Kementerian untuk: menghasilkan PPAT yang berkualitas dan profesional; mengingkatkan kemampuan dan pengetahuan seseorang di bidang pertanahan; meningkatkan kualitas pembuatan akta dalam melayani masyarakat; meningkatkan pemahaman dasar hukum sesuai dengan ketentuan peraturan perundang- undangan, pembinaan dan pengawasan administrasi keagrariaan/pertanahan, dan pelaksanaan jabatan PPAT. Peningkatan Kualitas diperuntukkan: bagi calon PPAT telah lulus Ujian PPAT dan belum diangkat sebagai PPAT; bagi yang telah menjabat sebagai PPAT dalam waktu tertentu; dan bagi camat sebelum dilantik/menjalankan tugas sebagai PPAT sementara. Penyelenggaraan Peningkatan Kualitas sebagaimana dimaksud pada angka (2) huruf a dan huruf b dilaksanakan oleh Direktur Jenderal. Penyelenggaraan Peningkatan Kualitas sebagaimana dimaksud pada angka (2) huruf c dilaksanakan oleh Kantor Wilayah Badan Pertanahan Nasional atau Kantor Pertanahan. Peserta Peningkatan Kualitas dikenakan biaya layanan sesuai dengan ketentuan peraturan perundangundangan. Peserta Peningkatan Kualitas diberikan Sertifikat Peningkatan Kualitas. g Pelaksanaan Magang Bagi Calon Pejabat Pembuat Akta Tanah (PPAT). Pelaksanan magang bagi calon Pejabat Pembuat Akta Tanah (PPAT) Pasal 16, menyebutkan bahwa: Pelaksanaan Magang Bagi Calon Pejabat Pembuat Akta Tanah (PPAT). Pelaksanan magang bagi calon Pejabat Pembuat Akta Tanah (PPAT) Pasal 16, menyebutkan bahwa:  Magang atau nyata-nyata telah bekerja sebagai karyawan pada kantor PPAT dan Kantor Pertanahan merupakan syarat untuk diangkat menjadi PPAT.  Magang sebagaimana dimaksud pada angka (1) hanya dapat diikuti oleh orang yang telah lulus program pendidikan spesialis notariat atau S-2 (strata-dua) hukum bidang kenotariatan.  Magang sebagaimana dimaksud pada angka (1) hanya dapat diikuti oleh orang yang telah lulus program pendidikan spesialis notariat atau S-2 (strata-dua) hukum bidang kenotariatan. (PPAT)  Ketentuan Magang sebagaimana dimaksud pada angka (1) dikecualikan bagi:  peserta yang lulus Ujian dan telah menjabat sebagai Notaris;  lulusan Program Pendidikan Khusus yang diselenggarakan oleh Kementerian; atau  pernah menduduki jabatan struktural di bidang hubungan hukum keagrariaan atau yang setara dengan itu, paling rendah pejabat pengawas di lingkungan Kementerian. Pasal 17, menyebutkan bahwa: Pelaksanaan magang dilakukan: sebelum mengikuti Ujian; atau setelah lulus Ujian dan sebelum diangkat sebagai PPAT.  Ketentuan Magang sebagaimana dimaksud pada angka (1) dikecualikan bagi:  peserta yang lulus Ujian dan telah menjabat sebagai Notaris;  lulusan Program Pendidikan Khusus yang diselenggarakan oleh Kementerian; atau Kementerian; atau  pernah menduduki jabatan struktural di bidang hubungan hukum keagrariaan atau yang setara dengan itu, paling rendah pejabat pengawas di lingkungan Kementerian. Pasal 17, menyebutkan bahwa: Pelaksanaan magang dilakukan: sebelum mengikuti Ujian; atau setelah lulus Ujian dan sebelum diangkat sebagai PPAT.  pernah menduduki jabatan struktural di bidang hubungan hukum keagrariaan atau yang setara dengan itu, paling rendah pejabat pengawas di lingkungan Kementerian. Pasal 17, menyebutkan bahwa: Pelaksanaan magang dilakukan: sebelum mengikuti Ujian; atau setelah lulus Ujian dan sebelum diangkat sebagai PPAT.  Magang dilaksanakan selama 1 (satu) tahun pada Kantor Pertanahan dan Kantor PPAT, dengan pembagian waktu:  6 (enam) bulan di Kantor Pertanahan; dan   6 (enam) bulan di Kantor PPAT.  Peserta magang sebagaimana dimaksud pada angka (1) tidak diberikan honorarium.  Peserta magang sebagaimana dimaksud pada angka (1) tidak  Permohonan magang diajukan secara tertulis kepada:  Kepala Kantor Pertanahan, apabila magang dilaksanakan di Kantor Pertanahan; atau  PPAT dengan tembusan Ketua Pengurus Daerah IPPAT sesuai dengan lokasi permohonan Magang, apabila magang dilaksanakan di Kantor PPAT. g g g  fotokopi KTP pemohon;  fotokopi KTP pemohon;  fotokopi ijazah Program Pendidikan Spesialis Notariat atau Strata Dua Hukum Bidang Kenotariatan;  Surat Keterangan Lulus Ujian, apabila telah lulus Ujian; dan  Surat Pernyataan bermeterai cukup dari pemohon yang menerangkan bahwa bersedia Magang di Kantor Pertanahan atau Kantor PPAT dengan sukarela tanpa meminta imbalan jasa serta menaati tata tertib magang sesuai dengan ketentuan. 199  Permohonan magang dan pernyataan bersedia menjalani magang dibuat sesuai dengan format tercantum dalam lampiran I A dan lampiran I B yang merupakan bagian tidak terpisahkan dari Peraturan Menteri ini. Pasal 18, menyebutkan bahwa:  Kantor Pertanahan menerima permohonan magang yang diajukan sebagaimana dimaksud dalam Pasal 17 angka (4) huruf a dan mengatur jadwal pelaksanaan magang. (PPAT)  Kantor PPAT sebagaimana dimaksud dalam Pasal 17 angka (4) huruf b yang menjadi tempat magang mempunyai kriteria meliputi:  Kantor PPAT sebagaimana dimaksud dalam Pasal 17 angka (4) huruf b yang menjadi tempat magang mempunyai kriteria meliputi:  PPAT dengan masa kerja paling sedikit 5 (lima) tahun; atau j p g g p y p  PPAT dengan masa kerja paling sedikit 5 (lima) tahun; atau  telah menerbitkan paling sedikit 60 (enam puluh) akta. Pasal 19, menyebutkan bahwa:  Dalam hal magang dilaksanakan pada Kantor Pertanahan, peserta magang wajib memahami dan membantu:  proses kegiatan dan pelayanan pertanahan;   proses penerimaan dan pemeriksaan akta yang didaftar; dan   proses pemeriksaan data yuridis permohonan hak atas tanah  Dalam hal magang dilaksanakan pada Kantor PPAT, peserta magang wajib membantu dalam pelaksanaan kegiatan:  pembuatan akta perbuatan hukum hak atas tanah atau Hak Milik Atas Satuan Rumah Susun paling sedikit 7 (tujuh) akta; dan  proses penatausahaan dan pengelolaan Protokol PPAT.  Dalam hal magang dilaksanakan pada Kantor PPAT, peserta magang wajib membantu dalam pelaksanaan kegiatan:  proses penatausahaan dan pengelolaan Protokol PPAT.  Peserta magang wajib merahasiakan dan dilarang menggandakan dokumen pelaksanaan kegiatan dan pelayanan Kantor Pertanahan dan pelaksanaan jabatan PPAT. Pasal 20, menyebutkan bahwa: Pasal 20, menyebutkan bahwa:  Kantor Pertanahan dan Kantor PPAT menerbitkan Surat Keterangan Magang bagi peserta magang yang telah melaksanakan magang sesuai dengan ketentuan sebagaimana dimaksud dalam Pasal 19.  Kantor Pertanahan menyampaikan laporan secara berkala setiap 6 (enam) bulan sekali pada awal bulan berikutnya kepada Direktur Jenderal melalui Kepala Kantor Wilayah Badan Pertanahan Nasional. Surat Keterangan Magang sebagaimana dimaksud pada angka (1) tercantum dalam lampiran I C yang merupakan bagian tidak terpisahkan dari Peraturan Menteri ini. Surat Keterangan Magang sebagaimana dimaksud pada angka (1) tercantum dalam lampiran I C yang merupakan bagian tidak terpisahkan dari Peraturan Menteri ini. Pelaksanaan Magang Di Lingkungan Wilayah Kantor Pertanahan Sumatera Utara Pelaksanaan Magang Pada Kantor Pertanahan Kota Medan Pelaksanaan Magang Pada Kantor Pertanahan Kota Medan Kesiapan Kantor Pertanahan Kota Medan dalam menerima peraturan diberlakukannya magang untuk Calon PPAT.Kantor Pertanahan tersebut menanggapi dengan baik dan siap untuk mengajari dan mengarahkan setiap calon PPAT yang melaksanakan magang. (Khaliq, Wawancara, 03 Agustus 2020) Pada saat magang berlangsung dilingkungan Kantor Pertanahan Kota Medan, yang mana kegiatan magang tersebut berlangsung selama 6 (enam) bulan, maka hal-hal yang dikerjakan oleh calon PPAT pada saat magang yaitu tentang Surat Keterangan Pendaftaran Tanah dan memeriksa kelengkapan berkas (memeriksa identitas, Pajak Bumi dan Bangunan (PBB), Bea Perolehan Hak Atas Tanah dan Bangunan (BPHTB) dan Pajak Penghasilan (PPH). (Khaliq, Wawancara, 03 Agustus 2020) Kewajiban magang untuk calon PPATmerupakan suatu kewajiban yang harus 200 dilaksanakan calon PPAT, magang yang diberlakukan dapat menambah kemampuan dan kemahiran saat sudah diangkat menjadi PPAT. Atau hanya menjadi sebuah formalitas untuk memenuhi syarat dalam Peraturan Menteri Agraria dan Tata Ruang/Kepala Badan Pertanahan Nasional Republik Indonesia Nomor20 Tahun 2018 tentangTata Cara Ujian, Magang, Pengangkatan, Pengangkatan Kembali, Dan Perpanjangan Masa Jabatan Pejabat Pembuat Akta Tanah. Dalamhal inidapat dilihat langsung pada calon PPAT yang sedang melaksanakan magang, belum semua dari calon PPAT yang benar-benar melaksanakan magang dengan baik, tergantung pada calon PPAT itu sendiri, ada calon PPAT yang memiliki kemauan untuk belajar, rasa ingin tahu dalam tugas-tugas yang berkaitan dengan pertanahan. Dalam melaksanakan magang calon PPAT tidak boleh canggung untuk bertanya, rajin melaksanakan magang,harus proaktif dan tidak menunggu untuk diberikan pekerjaan oleh pembina magang. (Khaliq, Wawancara, 03 Agustus 2020) Kantor Pertanahan tersebut memiliki harapan kedepannya bagi calon PPAT dalam melaksanakan kewajiban magang, peserta magang harus belajar untuk disiplin dalam waktu kehadiran, karena masih ada beberapa peserta magangyang seringtidak hadir melaksanakan kewajiban magangnya. (Khaliq, Wawancara, 03 Agustus 2020) j g g y ( q g ) Sesuai dengan peraturan yang berlaku bagi calon PPAT, calon PPAT harus melaksanakan magang di Kantor Pertanahan dan Kantor PPAT, dilaksanakan magang PPAT, memiliki hubungan keterkaitan dengan tugas pada Kantor Pertanahandengan Kantor PPAT, yaitu Kantor Pertanahanbertugas dalam mencatat isi akta sedangkan PPAT atau Pejabat Pembuat Akta Tanah bertugas dalam membuat akta, sehingga calon PPAT tersebut wajib mengetahui kedua tugas tersebut. (Khaliq, Wawancara, 03 Agustus 2020) Pelaksanaan Magang Pada Kantor Pertanahan Kabupaten Karo Pelaksanaan Magang Pada Kantor Pertanahan Kabupaten Karo Diberlakukannya pelaksanaan magang pada calon PPAT, sangat perlu dilakukan penerapan dalam prakteknya, karena sangat membantu peningkatan kualitas setelah pengangkatan PPATdengan ikut serta dalam pelayanan membantu masyarakat.Kantor Pertanahan Kabupaten Karo siap menerima dengan baik dan siap dalam mengajari serta mengarahkan setiap calon PPAT yang melaksanakan magang. Merespon dan menerima dengan baik calon PPAT yang memiliki kemauan serta kesadaran terhadap kewajibannya dan memiliki nilai plus terhadap calon PPAT yang melaksanakan magang disetiap hari kerja. (Sutrisno ginting, Wawancara, 03 Agustus 2020) Pelaksanaan magang diberlakukan tanpa ada paksaan,diberi kebebasan dalam 1(satu) mingguberapa kalimelaksanakan magang, tergantung keinganan calon PPAT itu sendiri, waktu pelaksanaan magang mengikuti jam kerja Kantor Pertanahan mulai dari jam 08.00 wib sampai dengan jam 17.00 wib.Terbatasnya ruangan kerja di Kantor Pertanahan tersebut, membuat calon PPAT harus menerima keterbatasan ruangan, dan bergabung serta berbaur dengan staff pegawai lainnya dalam melaksanakan kegiatan pelayanan di setiap ruangan. (Sutrisno ginting, Wawancara, 03 Agustus 2020) Magang berlangsung secara efektif, karena calon PPAT yang melaksanakan magang di Kantor Pertanahan Kabupaten Karo, harus memiliki kedisplinan waktu, begitu juga dengan adanya keinginan dan kemauan pada setiap calon PPAT atau individu untuk memiliki rasa ingin tahu dalam menambah wawasannya di bidang pertanahan, aktif dalam bertanya kepada pembina magang dan tidak malu untuk berbaur dengan staff pegawai lainnya melaksanakan tugas dalam memberikan pelayanan kepada masyarakat setempat. (Sutrisno ginting, Wawancara, 03 Agustus 2020) Kantor Pertanahan Kabupaten Karo tidak akanbersedia untuk mengeluarkan Surat Keterangan Magang bagi peserta magang, jika tidak menyelesaikan magang dengan waktu yang sudah ditentukan karena melanggar suatu ketentuan yang berlaku. Jangka waktu yang sudah ditetapkan merupakan waktu yang sangat singkat dan cukup dalam melaksanakan kewajiban magang, calon PPAT harus benar-benar mempergunakan dan memamfaatkan waktu yang ada, karena kualitas selaku PPAT akan diuji pada saat membuka kantor, diberlakukannya magang 201 akan menghasilkan PPAT yang berkualitas dan professional serta akan memberikan kemahiran dan pemahaman dalam pembuatan akta yang berkaitan dengan pertanahan dan prosuder- prosedur kerja Kantor Pertanahan. (Sutrisno ginting, Wawancara, 03 Agustus 2020) p j ( g g g ) Tugas yang diberikan pada calon PPAT, sudah pasti berkaitan dengan pertanahandengan menyesuaikannya pada ilmu yang didapat dalam perkuliahan tentang tugas PPAT yang memiliki kaitan dalam bidang pelayanan pertanahan, yaitu, membantu dan memeriksa setiap kelengkapan berkas Permohonan Peralihan Hak (Jual Beli, Waris, Hibah, Pembagian Hak Bersama dan lain-lainnya) Kantor Pertanahan tersebut hanya memberikan tugas didalam Kantor dan calon PPAT tidak diikutsertakan pelayanan diluar kantor. Pelaksanaan Magang Pada Kantor Pertanahan Kabupaten Karo (Sutrisno ginting, Wawancara, 03 Agustus 2020) Penulis melihat bahwa diberlakukannya kewajiban magang memberikan mamfaat dan nilai yang positif bagi calon PPAT,menambah pengetahuan dalam praktek. Begitu juga dengan peranturan-peraturan yang memberlakukan magang, magang benar-benar terlaksana dengan baik, walaupun calon PPAT tersebut memiliki kegiatan lain selain magang, peserta magang harus mengorbankan tenaga, waktu danpikirannya. Calon PPAT harus mampu memilih, apakah tetap menjalankan magang, atau tetap dengan kesibukan kegiatan lainnya. Karena menjadi seorang PPAT tidaklah mudah, harus benar-benar memahami serta dapat menguasai tata cara pembuatan akta, dasar hukumnya dan prosedur-prosedur kerjaberkaitan dengan wewenang PPAT dan mengetahui proses alur kegiatandalam pelayanan Kantor Pertanahan, maka calon PPAT harus benar-benar belajar lebih banyak lagi tentang pemahamannya dalam tugas PPAT. Kendala Yang Dihadapi Oleh Calon Pejabat Pembuat Akta Tanah (PPAT)Pada Saat Melaksanakan Magang di Kantor Pertanahan Seorang calon PPAT yang mengikuti magang PPAT di Kantor Pertanahan haruslah seseorang yang telah menyelesaikan jenjang pendidikan Strata Dua Magister Kenotariatan. Sesuai dengan prosedur yang telah ditetapkan oleh Badan Pertanahan Nasional, yakni sebelum melakukan magang, calon PPAT wajib mengantarkan berkas-berkas(fotokopi KTP, fotokopi Ijazah Strata Satu danStrata Dua yang telah dilegalisir, Surat Permohonan Magang, Surat Pernyataan Magang yang ditandatangani diatas materai). Proses magang PPAT dilakukan dengan waktu 1 (satu) tahun, dimana magang tersebut dibagi 2 (dua) yaitu 6 (enam) bulan magang di Kantor Pertanahan, dan 6 (enam) bulan magang di Kantor Pejabat Pembuat Akta Tanah (PPAT). Kendala atau sering disebut dengan faktor atau keadaan yang membatasi. (Kamus Besar Bahasa Indonesia) Ada 2 (dua) kendala yang sering dihadapi calon PPAT dalam melaksanakan tugasnya pada saat melaksanakan magang, antara lain: Kendala Internal Selain itu dalam proses magang di Kantor Pertanahan kendala yang kerap sekali ditemui oleh peserta magang ketika melaksanakan magang, mengenai pribadi atau individu yang tidak mau tahu tentang bagaimana pekerjaan di Kantor Pertanahan yang berhubungan dengan PPAT. (Sutrisno, Wawancara, 03 Agustus 2020). Kendala terhadap peserta magangpada saat melayani masyarakat setempat, peserta magang langsung diarahkan untuk menawarkan produk-produk atau program Pelayanan Pendaftaran Tanah kepada masyarakat setempat didaerah Kantor Pertanahan Kota Binjai, wilayah tempat yang akan dikunjungi satu persatu ditentukan oleh Kantor Pertanahan tersebut, setiap calon PPAT langsung ikut melayani masyarakat terkait dengan Program Pelayanan Pendaftaran Tanah yaitu, PRONA (Program Nasional Agraria) yang merupakan Program dari Badan Pertanahan Nasional dan PTSL (Pendaftaran Tanah Sistematis Lengkap) yang merupakan Program secara gratis dari Pemerintah Pusat yaitu Program dari Presiden Joko Widodo. Pada saat melakukan Pelayanan Pendaftaran Tanah terhadap masyarakat setempat, masyarakat belum semua dapat menerima dan mengetahui program tersebut, beberapa masyarakat ada yang mau menerima pelayanan yang kami lakukan dan ada juga masyarakat yang berpikir program ini hanya membuang-buang waktu saja dan mereka takut ada penipuan terhadap program ini, tanpa mendengarkanterlebih dahulu penjelasan produk-produk atau program pelayanan Pendaftaran Tanah dari staff pegawai Kantor Pertanahan terseebut. (Renita, Wawancara, 15 Oktober 2020) Kendala Eksternal Kendala yang kerap sekali ditemui oleh calon PPAT ketika magang yakni, apabila calon PPAT yang melaksanakan magang tersebut berstatus sebagai karyawan/pekerja pada perusahaan atau instansi, yang menyebabkan tenaga, waktu dan pikiran terbagi di karenakan memiliki kegiatan lain, ketika mengikuti magang di Kantor Pertanahan peserta magang harus mengikuti prosedur kerja, yaitu dalam hal mulai dari waktu masuk hingga pulang yang harus mengikuti jam kantor pertanahan dimulai dari jam masuk pukul 09.00 WIB sampai dengan jam pulang pukul 17.00 WIB, calon PPAT memiliki absensi kehadiran,dalam hal tersebut membuat setiap orang berstatus sebagai pekerja ditempat lain merasakan dilema untuk melakukan pembagian waktu. (Berni, Wawancara, 03 Agustus 2020). Begitu juga dengan peserta magang yang bertempat tinggal di luar kota atau bertempat tinggal diluar dari wilayah Kantor Pertanahan tersebut, sehingga peserta magang sering sekali ijin untuk tidak masuk dengan berbagai alasan. (Sutrisno, Wawancara, 03 Agustus 2020). 202 Kantor Pertanahan Kota Binjai juga disiplin terhadap peraturan yang berlaku bagi peserta magang, mengenai Surat Keterangan Magang yang dikeluarkan oleh Kantor Pertanahan tersebut, jika peserta magang tidak displin dengan waktu kehadiran, maka peserta magang akan dikeluarkan dan tidak boleh melaksanakan magang di Kantor Pertanahan tersebut.Kantor Pertanahan tersebut memberikan keringanan waktu, hanya boleh melakukan absensi kehadiran maksimal 3 (tiga) kali pertemuan, jika peserta magang tetap melanggar peraturan maka Kantor Pertanahan tersebut tidak akan memberikan keringanan karena sudah melanggar peraturan dan prosedur kerja dan tidak akan mengeluarkan Surat Keterangan Magang. (Renita, Wawancara, 15 Oktober 2020). Begitu juga dengan Kantor Pertanahan Kabupaten Karo dalam 1 (satu) minggu calon PPAT diberi kebebasan berapa kali melaksanakan magang, tidak ada paksaan berapa kali harus datang, tergantung pribadi atau individunya yang memiliki kemauan melaksanakan magang di setiap hari kerja, adanya keinginan pada peserta magang untuk memiliki rasa ingin tahu dalam menambah wawasannya pada saat melaksanakan magang di Kantor Pertanahan tersebut. Jika tidak menjalankan kewajibannya Kantor Pertanahan tersebut tidak akan bersedia untuk mengeluarkan Surat Keterangan Magang bagi peserta magang yang sering tidak disiplin dengan waktu dalam kewajiban menyelesaikan magang sesuai dengan waktu yang sudah ditentukan, Kantor Pertanahan tersebut tidak bersedia mengeluarkan Surat Keterangan Magang karena melanggar suatu ketentuan yang berlaku. (Sutrisno, Wawancara, 03 Agustus 2020) V. UCAPAN TERIMA KASIH Terima kasih penulis ucapkan kepada Ketua Program Pasca Sarjana Ilmu Hukum, Dekan Fakultas Hukum Universitas Sumatera Utara, Para Dosen Pembimbing, Dosen Penguji dan rekan-rekan penulis yang telah memberikan kontribusi terhadap penelitian penulis ini. IV. KESIMPULAN Pelaksaanan peningkatan kualitas berkaitan dengan kewajiban magang yang dilaksanakan Kementerian Agraria Dan Tata Ruang/Badan Pertanahan.Proses magang yang berlangsung bagi calon PPAT merupakan suatu kewajiban yang harus dilaksanakan, menjadi seorang PPAT tidaklah mudah, harus 203 memiliki kemauan untuk belajar dan melatih kemahiran membuat akta. Akta yang dibuat seorang PPAT, bukan hanya sekedar membuat akta, tetapi akta yang sudah dibuat akan menjadi tanggung jawab sepenuhnya dikemudian hari. Perlu diberlakukan magang agar calon PPAT memiliki kemampuan dan kemahiran dalam menjalankan setiap tugas yang diberikan dan meningkat kualitas seorang calon PPAT pada saat sudah membuka kantor, PPAT teserbut menjadi professional dan berkualitas dalam menjalankan tugasnya. VI. REFERENSI Abdulkadir Muhammad, 1997, Etika Profesi Hukum, PT. Citra Aditya Bakti, Bandung. Abdulkadir Muhammad, 1997, Etika Profesi Hukum, PT. Citra Aditya Bakti, Bandung. E.Utrecht, Pengantar Hukum Administrasi Indonesia, Penerbit Ikhtiar, Jakarta, 2010. Muhammad Benny, Kewenangan Camat Sebagai PPAT Sementara Dalam Membuat Akta Peralihan Hak Atas Tanah Dengan Ganti Rugi, Tesis Magister Kenotariatan USU, Medan, 2004. Koentjaraningrat, Metode-Metode Penelitian Masyarakat, Gramedia, Jakarta, 1997. Sunaryati Hartono, Penelitian Hukum Indonesia Pada Akhir Abad ke-20, Bandung, Alumni, 1994. Bismar Nasution, Penelitian HukumNormatif dan Perbandingan Hukum, Makalah FH USU, 18 Februari 2003. Soerjono Soekanto dan Sri Mamudi, 1995, Penelitiant Hukum Normatif suatu Tinjauan Singkat, Jakarta, PT. Raja Grafindo Persada. Edy Ikhsan, Mahmul Siregar, Metode Penelitian dan Penulisan Hukum Sebagai Bahan Ajar , Fakultas Hukum Universitas Sumatera Utara, Medan, 2009 Moh. Yamin, Pelatihan Peningkatan Kualitas Penelitian Hukum : Metode Penelitian Hukum Normatif dan Empirik serta Aplikasinya, Fakultas Hukum UNS, Surakarta, 2007 Amirudin dan M. Zainal Asikin, Pengantar Metode Penelitian Hukum, Raja Grafindo Persada, Jakarta, 2006 Muhammad Nazir, Metode Penelitian, Remaja Rosdakarya,Bandung, 1986. Salim, HS., Peraturan Jabatan & Kode Etik Pejabat Pembuat Akta Tanah (PPAT), PT. Rajagrafindo Persada, Depok, 2019. Pertanahan Kota Binjai tahun 2019, pada tanggal 15 Oktober 2020, pukul 10.15 WIB. 204 Peraturan Kepala Badan Pertanahan Nasional Nomor 1 Tahun 2006, tentang Ketentuan Pelaksanaan Peraturan Pemerintah Nomor 37 Tahun 1998 tentang Peraturan Jabatan Pejabat. Pembuat Akta Tanah Peraturan Pemerintah Republik Indonesia Nomor 37 Tahun 1998 tentang Peraturan Jabatan Pejabat Pembuat Akta Tanah. Peraturan Menteri Agraria dan Tata Ruang/Kepala Badan Pertanahan Nasional Republik Indonesia Nomor 20 Tahun 2018 Tentang Tata Cara Ujian, Magang, Pengangkatan, Pengangkatan Kembali, dan Perpanjangan Masa Jabatan Pejabat Pembuat Akta Tanah. Peraturan Menteri Agraria Dan Tata Ruang/Kepala Badan Pertanahan Nasional Republik Indonesia Nomor 20 Tahun 2018 Tentang Tata Cara Ujian, Magang, Pengangkatan Dan Perpanjangan Masa Jabatan Pejabat Pembuat Akta Tanah. 205
https://openalex.org/W1976657365	https://europepmc.org/articles/pmc3562608?pdf=render	English	null	Bilateral Adrenal Incidentalomas: A Case Report and Review of Diagnostic Challenges	Case reports in endocrinology	2,013	cc-by	2,352	1. Introduction approximately 6 months. He denied other associated symp- toms including Ęushing, diaphoresis, and palpitations. ere was no family history of endocrine neoplasms or early cere- bral or cardiovascular disease. e incidentally found adrenal mass presents several complex management issues. Deĕned as a mass 1 cm or more in diameter found during a radiologic study done for reasons other than evaluation for adrenal disease, the adrenal “inci- dentaloma” is present in approximately 6% of the population [1]. e prevalence increases with age, with patients greater than 70 years old having a prevalence of 7%, compared to 0.2% for those age 20–29 [2]. Most are nonfunctional benign adenomas, and recently published guidelines address the optimal approach to these lesions [3]. However, the discovery of incidental bilateral adrenal masses requires special attention and an expanded diagnostic approach. We obtained a renal artery duplex to evaluate for ren- ovascular disease due to patient’s young age and hyperten- sion. e duplex demonstrated bilateral enlargement of the adrenal glands, and MRI of the abdomen showed high T2 intensity of bilateral adrenal masses with the right-sided mass measuring 4.3 cm and the le-sided mass measuring 2.8 cm (Figure 1). A 24-hour urine collection demonstrated a normetanephrine level of 9250 ug/24 hours (normal range 50–650 ug/24 hours). Plasma norepinephrine was also ele- vated at 3127 pg/mL (normal supine range 70–750 pg/mL) with a plasma normetanephrine of 23.1 nmol/L (normal < 0.90 nmol/L). Early morning ACTH and cortisol levels were normal. A plasma aldosterone concentration (PAC) to plasma renin activity (PRA) ratio was 2.8 (normal < 25.0). Hindawi Publishing Corporation Case Reports in Endocrinology Volume 2013, Article ID 953052, 4 pages http://dx.doi.org/10.1155/2013/953052 Hindawi Publishing Corporation Case Reports in Endocrinology Volume 2013, Article ID 953052, 4 pages http://dx.doi.org/10.1155/2013/953052 Hindawi Publishing Corporation Case Reports in Endocrinology Volume 2013, Article ID 953052, 4 pages http://dx.doi.org/10.1155/2013/953052 Anders L. Carlson,1 Annis M. Marney,2 Scott R. Anderson,3 and Matthew P. Gilbert2 1 Division of Endocrinology, Regions Hospital, University of Minnesota Medical School, 401 Phalen Boulevard, Saint Paul, MN 55130 USA 2 Division of Endocrinology, Diabetes and Metabolism, e University of Vermont College of Medicine, Burlington, VT 05401, USA 3 Department of Pathology and Laboratory Science, e University of Vermont College of Medicine, Burlington, VT 05401, USA Correspondence should be addressed to Anders L. Carlson; anders.l.carlson@healthpartners.com Received 6 December 2012; Accepted 30 December 2012 Received 6 December 2012; Accepted 30 December 2012 Academic Editors: M. T. Garcia-Buitrago, T. Kita, and T. Usui Academic Editors: M. T. Garcia-Buitrago, T. Kita, and T. Usui Copyright © 2013 Anders L. Carlson et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Incidentally discovered adrenal masses (incidentalomas) are common and present challenges both in diagnosis and management. When incidentally discovered adrenal masses are bilateral, a reĕned diagnostic approach is warranted since bilateral disease is more likely to be pathologic. We review a case of a 34-year-old man with incidentally discovered bilateral adrenal nodules. A comprehensive diagnostic strategy led to the diagnosis of bilateral pheochromocytoma caused by von Hippel-Lindau syndrome. He was successfully treated with bilateral laparoscopic adrenalectomy and has recovered well. While the initial diagnostic approach is similar to the unilateral incidentaloma, additional testing and/or genetic testing should be considered in the case of the bilateral adrenal mass. 2. Case Presentation e patient is a 34-year-old, Caucasian male who was referred to our endocrinology clinic for evaluation of resis- tant hypertension. e patient had been experiencing chronic headaches and intermittent episodes of chest pressure for y He was diagnosed with bilateral pheochromocytoma. e patient was started on phenoxybenzamine 10 mg twice daily which was titrated up to 60 mg twice daily; propranolol 40 mg Case Reports in Endocrinology Case Reports in Endocrinology 2 T1: Recommended screening tests in adrenal incidentalomas. Additional analyses in bilateral incidentalomas listed below will depend on the clinical presentation and family history. Recommended screening for all incidentalomas Test Cushing’s syndrome 1 mg overnight dexamethasone suppression test Pheochromocytoma 24-hour urine collection for fractionated metanephrines and catecholamines Primary aldosteronism (screen only in hypertensive patients) Plasma aldosterone to plasma renin activity ratio Additional screening recommended for bilateral incidentalomas Test Adrenal insuﬃciency Morning cortisol and ACTH (or corticotrophin stimulation test) MEN2 RET gene mutation analysis, evaluation for hyperparathyroidism, medullary thyroid cancer, or mucosal neuromas Von Hippel-Lindau syndrome VHL gene mutation analysis and evaluation for additional tumors (such as renal, retinal, or nervous system) Neuroĕbromatosis type 1 NF1 gene mutation analysis Pheochromocytoma-paraganglioma syndrome SDHB/SDHD gene mutation analysis F1: T2-weighted MRI of the abdomen showing bilateral adrenal masses. e lemass measures 4.3 cm and the right mass measures 2.8 cm in greatest dimension. hyperplasia, macronodular Cushing’s syndrome, or bilateral cortical adenomas [5]. Bilateral pheochromocytomas are also possible, especially as part of a familial syndrome. e most likely primary cancers to metastasize to the adrenal glands are breast, lung, colon, kidney, and esophagus, though case reports exist for many other primary sites [6]. It is rare for metastatic disease to the adrenal glands to be the ĕrst manifestation of the primary cancer. Inĕltration diseases, such as tuberculosis, histoplasmosis, and sarcoidosis, are also possible causes of bilateral disease. In evaluating the hormone function of any adrenal incidentaloma, testing for subclinical Cushing’s, pheochro- mocytoma, and hyperaldosteronism (in patients with hyper- tension) should be performed [1, 2]. A 1 mg overnight dexamethasone suppression test to screen for Cushing’s syndrome and a 24-hour urine collection for fractionated metanephrines and catecholamines to screen for pheochro- mocytoma are recommended ĕrst-line tests [1]. Plasma aldosterone concentration (PAC) and renin activity levels (PRA) should be obtained and a PAC/PRA ratio calculated in patients with hypertension to screen for primary hyperaldos- teronism. 2. Case Presentation In the case of the bilateral adrenal incidentaloma, patients who present with symptoms such as hypotension, dizziness, weight loss, or abdominal pain in the setting of bilateral adrenal masses should be evaluated for adrenal insuﬃciency using an ACTH stimulation test (Table 1). Con- genital adrenal hyperplasia (CAH) infrequently manifests as bilateral adrenal disease [7]. CAH is unlikely to present as an adult, since most patients are diagnosed in childhood or have symptoms of adrenal insuﬃciency, virilization, or salt-wasting [8]. If CAH is suspected, screening for adrenal insuﬃciency as well as mutation analysis for CYP21B is recommended. F1: T2-weighted MRI of the abdomen showing bilateral adrenal masses. e lemass measures 4.3 cm and the right mass measures 2.8 cm in greatest dimension. twice daily was added once appropriate alpha blockade was achieved. Metyrosine was added prior to surgery. He under- went successful laparoscopic bilateral adrenalectomy, and the histopathologic features were consistent with pheochromo- cytoma (Figure 2). Staining for synaptophysin, chromogranin A, and S-100 protein were all positive. Subsequent referral for genetic testing and sequencing of the von Hippel-Lindau gene showed a deleterious mutation (R167Q). Additional genetic testing was not performed. No hemangioblastomas were seen on imaging, and he had no signiĕcant neurologic or ophthalmic ĕndings. Following surgery, he recovered well and his hypertension has resolved. patients who present with symptoms such as hypotension, dizziness, weight loss, or abdominal pain in the setting of bilateral adrenal masses should be evaluated for adrenal insuﬃciency using an ACTH stimulation test (Table 1). Con- genital adrenal hyperplasia (CAH) infrequently manifests as bilateral adrenal disease [7]. CAH is unlikely to present as an adult, since most patients are diagnosed in childhood or have symptoms of adrenal insuﬃciency, virilization, or salt-wasting [8]. If CAH is suspected, screening for adrenal insuﬃciency as well as mutation analysis for CYP21B is recommended. Speciĕc attention should be paid to the unique clinical sit- uation of the bilateral pheochromocytoma, which account for approximately 10% of pheochromocytomas [4, 5]. As in our case, where testing identiĕed a familial etiology, most cases of bilateral pheochromocytoma are hereditary. Genetic syn- dromes of pheochromocytoma include multiple endocrine neoplasia type 2 (MEN2A and 2B), neuroĕbromatosis 3. Discussion Approximately 15% of adrenal incidentalomas occur bilater- ally [4]. Whereas most unilateral masses are benign or non- functional, the bilateral adrenal mass is more likely metastatic disease, hemorrhage, inĕltrative disease, congenital adrenal Case Reports in Endocrinology 3 (a) (b) F2: Histologic sections from the right (a) and le(b) show an alveolar (zellballen) architecture with tumor cells surrounded by a delicate ĕbrous framework. e tumor cells show variable nuclear pleomorphism and contain granular and basophilic to amphophilic cytoplasm. Hemorrhage (a) and hemosiderin (b) are common in these tumors. Both images are at 200x magniĕcation and are stained with hematoxylin and eosin. 3 Case Reports in Endocrinology 3 (b) (a) (a) (b) (a) F2: Histologic sections from the right (a) and le(b) show an alveolar (zellballen) architecture with tumor cells surrounded by a delicate ĕbrous framework. e tumor cells show variable nuclear pleomorphism and contain granular and basophilic to amphophilic cytoplasm. Hemorrhage (a) and hemosiderin (b) are common in these tumors. Both images are at 200x magniĕcation and are stained with hematoxylin and eosin. type 1 (NF1), the pheochromocytoma-paraganglioma syn- drome (mutation of the SDHB or SDHD genes), and von Hippel-Lindau syndrome (VHL). MEN2A is a syn- drome that includes hyperparathyroidism, medullary thy- roid carcinoma, and pheochromocytoma, whereas MEN2B includes medullary thyroid carcinoma, pheochromocytoma, and mucosal neuromas. Neuroĕbromatosis type 1 is charac- terized by cafÏ-au-lait spots and neuroĕbromas. Mutations in the SDHB or SDHD genes predispose patients to glo- mus tumors and occasionally pheochromocytomas. Patients with bilateral pheochromocytoma should be screened for mutations in the genes associated with the above syndromes depending on the clinical presentation and family history (Table 1). If MEN2 is suspected, further testing with a calcitonin, intact PTH, and calcium level is warranted to eval- uate for medullary thyroid cancer and hyperparathyroidism. Referral to a genetic counselor may be appropriate. given the added morbidity of adrenal insuﬃciency aer bilat- eral adrenalectomy. No speciĕc guidelines exist addressing the optimal surgical approach to the bilateral pheochromo- cytoma; alpha-blockade followed by beta-blockade (with or without metyrosine) along with intravenous volume expan- sion remains the mainstay of preoperative management. Fol- lowing bilateral adrenalectomy, care must be taken to ensure proper glucocorticoid and mineralocorticoid replacement. 4. Conclusion e bilateral adrenal incidentaloma presents a unique diag- nostic challenge. In addition to the risk of hormone hyper- secretion, the bilateral adrenal mass carries additional risk of being metastatic from another primary carcinoma or part of a genetic syndrome. While the initial diagnostic approach is similar to the unilateral incidentaloma, additional testing and/or genetic testing should be considered in the case of the bilateral adrenal mass. Surgery remains the mainstay of treatment in most cases. g y pp p Von Hippel-Lindau syndrome is an autosomal-dominant syndrome characterized by cerebellar hemangioblastoma, renal cell carcinoma, retinal angiomatosis, and pheochromo- cytoma. Type 1 VHL uncommonly has pheochromocytoma. Type 2 VHL is either 2A (low risk for renal cell tumor), 2B (high risk for renal cell tumor), or 2C (pheochromocytoma alone). 0ur patient would ĕt most with VHL type 2C. e gene involved, VHL, is a tumor suppressor gene [9]. Pheochromocytoma is uncommon in VHL patients, with a prevalence of 14% in VHL kindreds [10]. ey can be particularly challenging cases to manage because adrenal nodules may be present without symptoms of pheochromo- cytoma [11]. is likely occurs when the diagnosis of VHL is made before the clinical manifestations of the underly- ing pheochromocytoma are apparent. e discovery of an adrenal nodule in a VHL patient who has had a previous contralateral pheochromocytoma should be considered a pheochromocytoma until proven otherwise. ConëicU of *nUeresUs All authors had access to the data and a role in writing the paper and report no conĘict of interests. References [1] W. F. Young Jr., “e incidentally discovered adrenal mass,” e New England Journal of Medicine, vol. 356, no. 6, pp. 601–610, 2007. [2] R. T. Kloos, M. D. Gross, I. R. Francis, M. Korobkin, and B. Shapiro, “Incidentally discovered adrenal masses,” Endocrine Reviews, vol. 16, no. 4, pp. 460–484, 1995. Deĕnitive treatment for bilateral adrenal masses is sur- gical resection of both adrenal glands in most cases, except in the case of aldosterone secreting tumors, in which case medical options may be the preferred approach. Special care is needed in the case of the bilateral pheochromocytoma [3] M. A. Zeiger, G. B. ompson, Q. Y. Duh et al., “e Amer- ican Association of Clinical Endocrinologists and American Association of Endocrine Surgeons medical guidelines for the management of adrenal incidentalomas,” Endocrine Practice, vol. 15, supplement 1, pp. 1–20, 2009. Case Reports in Endocrinology 4 [4] L. Barzon, C. Scaroni, N. Sonino et al., “Incidentally discovered adrenal tumors: endocrine and scintigraphic correlates,” e Journal of Clinical Endocrinology and Metabolism, vol. 83, no. 1, pp. 55–62, 1998. [5] A. Angeli, G. Osella, A. Ali, and M. Terzolo, “Adrenal inciden- taloma: an overview of clinical and epidemiological data from the National Italian Study Group,” Hormone Research, vol. 47, no. 4–6, pp. 279–283, 1997. [6] J. E. Lee, D. B. Evans, R. C. Hickey et al., “Unknown primary cancer presenting as an adrenal mass: frequency and impli- cations for diagnostic evaluation of adrenal incidentalomas,” Surgery, vol. 124, no. 6, pp. 1115–1122, 1998. [7] M. Kjellman, M. Holst, M. Bäckdahl, C. Larsson, L. O. Farnebo, and A. Wedell, “No overrepresentation of congenital adrenal hyperplasia in patients with adrenocortical tumours,” Clinical Endocrinology, vol. 50, no. 3, pp. 343–346, 1999. [8] S. Jaresch, E. Kornely, H. K. Kley, and R. Schlaghecke, “Adrenal incidentaloma and patients with homozygous or heterozy- gous congenital adrenal hyperplasia,” e Journal of Clinical Endocrinology and Metabolism, vol. 74, no. 3, pp. 685–689, 1992. [9] F. Latif, K. Tory, J. Gnarra et al., “Identiĕcation of the von Hippel-Lindau disease tumor suppressor gene,” Science, vol. 260, no. 5112, pp. 1317–1320, 1993. [10] “Case records of the Massachusetts General Hospital. Weekly clinicopathological exercises. Case 16-1991. A 36-year-old man with von Hippel-Lindau disease and an adrenal mass,” e New England Journal of Medicine, vol. 324, no. 16, pp. 1119–1127, 1991. [11] B. S. Aprill, A. J. Drake III, D. H. Lasseter, and K. M. M. References Shakir, “Silent adrenal nodules in von Hippel-Lindau disease suggest pheochromocytoma,” Annals of Internal Medicine, vol. 120, no. 6, pp. 485–487, 1994.
https://openalex.org/W3009739186	https://www.biorxiv.org/content/biorxiv/early/2020/03/09/2020.03.09.983361.full.pdf	English	null	Episodic evolution of coadapted sets of amino acid sites in mitochondrial proteins	bioRxiv (Cold Spring Harbor Laboratory)	2,020	cc-by	25,878	. CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 1 Episodic evolution of coadapted sets of amino acid sites in mitochondrial 2 proteins 3 Neverov A.D.1, Fedonin G.G.1,2,3, Cheremukhin E.A.4, Klink G.V. 2, Popova A.V.1 and Bazykin 4 G.A.2,5. 5 6 1 Department of Molecular Diagnostics, Central Research Institute for Epidemiology, Moscow, 7 Russia. 8 2 Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of 9 Sciences, Moscow, Russia. 10 3 Moscow Institute of Physics and Technology, Dolgoprudny, Moscow region, Russia. 11 4 Department of Chemistry, M. V. Lomonosov Moscow State University, Moscow, Russia. 12 5 Skolkovo Institute of Science and Technology, Skolkovo, Russia. 13 14 The corresponding author: Neverov A.D., mailto: neva_2000@mail.ru 15 16 17 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 42 Introduction 43 Correlated occurrence of amino acids at different sites 43 Correlated occurrence of amino acids at different sites 44 The rate at which individual protein sites accumulate substitutions changes in the course of evolution, 45 which violates the assumptions of evolutionary models and may cause problems for phylogenetic 46 reconstruction. This variability can uniformly affect all substitution types (“heterotachy” [1,2]) or 47 differentiate between them (“heteropecilly” [2]). The substitution rate is the product of the rate at which 48 mutations arise and the rate at which they are fixed [3], and can be affected by changes in either of these 49 processes. The main factor affecting the fixation probability is selection favoring some variants over 50 others. The direction or magnitude of selection at a site can change due to multiple forces including 51 changes in environmentally induced constraints or substitutions at other epistatically interacting genomic 52 sites. 47 differentiate between them (“heteropecilly” [2]). The substitution rate is the product of the rate at which 48 mutations arise and the rate at which they are fixed [3], and can be affected by changes in either of these 49 processes. The main factor affecting the fixation probability is selection favoring some variants over 50 others. The direction or magnitude of selection at a site can change due to multiple forces including 51 changes in environmentally induced constraints or substitutions at other epistatically interacting genomic 52 sites. 53 54 The latter process appears to play a major role [4,5]. One type of evidence for this is the correlations 55 between the occurrence of different amino acids at pairs of sites in multiple alignments (MSAs) of 56 homologous sequences. Such correlations, inferred using direct coupling analysis (DCA) or related 57 methods, are associated with physical proximity, and are sufficiently strong that they can be used to infer 58 protein structures and interprotein contacts [6–10] and to predict fitness effects of substitutions [11–13]. 59 60 Given the success of these approaches, it is tempting to aggregate cooccurrence data across many sites to 61 get a bird’s eye view of the constraints on the evolution of the entire protein. Granata et. al. [14] have 62 processed a DCA-derived cooccurrence matrix by graph vertex clustering. They thus partitioned protein 63 sites into dense domains spatially separated on the structure, and showed that these domains correspond 64 to rigid dynamics domains of the protein. 18 Abstract 19 The rate of evolution differs between protein sites and changes with time. However, the link between 20 these two phenomena remains poorly understood. Here, we design a phylogenetic approach for 21 distinguishing pairs of amino acid sites that undergo coordinated evolution, i.e., such that substitutions at 22 one site trigger subsequent substitutions at the other; and also pairs of sites that undergo discordant 23 evolution, so that substitutions at one site impede subsequent substitutions at the other. We distinguish 24 groups of amino acid sites that undergo coordinated evolution and evolve discordantly from other such 25 groups. In mitochondrially encoded proteins of metazoans and fungi, we show that concordantly evolving 26 sites are clustered in protein structures. Moreover, the substitution rates within individual concordant 27 groups themselves change in the course of evolution, and phylogenetic positions of these changes are 28 consistent between proteins, suggesting common selective forces underlying them. 30 Evolution in most protein sites is constrained by alleles in other sites, this phenomena is called epistasis. 31 Generally, newly arisen allele, if it would not be lost, increases its fitness with time due to adaptive 32 mutations occurred in other sites in the process called the entrenchment. Thus, we expect that the 33 evolution of sites would be coordinated, such that mutations in sites rapidly follow each other on 34 phylogenetic lineages. Indeed, we have observed such coordinated evolution of sites in five proteins 35 encoded in the mitochondria genomes of metazoan and fungi. Unexpectedly, coordinated evolution is 36 observed only for nearby sites on protein structures, such that each protein could be partitioned into 37 several groups of concordantly evolving sites. Evolution of sites from different groups is discordant, i.e. 38 their mutations repel each other into different phylogenetic lineages or clades. Thus, the proteins encoded 39 in mitochondrial genome consist of the sort of structural blocks like elements of the LEGO kit. Some of 40 them have functional specialization, e.g. some blocks are associated with interfaces between proteins 41 composing respiratory complexes. . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 42 Introduction It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 70 71 Such approaches can reveal groups of sites that are associated with each other, which may help unravel 72 evolutionary constraints linked with some biological functions. However, how these associations manifest 73 themselves in the course of evolution is not understood well. 74 Complexity of mitochondrial evolution 75 Mitochondrial-encoded proteins are a good model system for coevolution between sites. On the one hand, 76 sequencing data is abundant across all eukaryotes, and structures and functions of proteins and protein 77 complexes are well understood. On the other hand, mitochondrial evolution is a complex process. This 78 complexity has been mainly studied from the viewpoint of phylogenetic reconstruction. Mitochondrial 79 proteins violate the basic assumptions of phylogenetic methods, namely, homogeneity of the processes of 80 amino acid substitutions along lineages, between sites in alignment and between character states within 81 sites [18]. This variation can arise due to differences in mutation [19,20] and/or selection [21,22]. As a 82 result, mitochondrial evolution has motivated development of approaches that relax one or several of 83 these assumptions. Heterogeneity between sites has been addressed by using Gamma [23] or general 84 discrete distributions of substitution rates [24] and CAT-models that use Dirichlet processes to classify 85 sites into categories with different equilibrium frequencies of characters [25]. Heterogeneity between 86 lineages has been modeled by using more complicated models [1,2,19]. 87 70 71 Such approaches can reveal groups of sites that are associated with each other, which may help unravel 72 evolutionary constraints linked with some biological functions. However, how these associations manifest 73 themselves in the course of evolution is not understood well. 74 Complexity of mitochondrial evolution 75 Mitochondrial-encoded proteins are a good model system for coevolution between sites. On the one hand, 76 sequencing data is abundant across all eukaryotes, and structures and functions of proteins and protein 77 complexes are well understood. On the other hand, mitochondrial evolution is a complex process. This 78 complexity has been mainly studied from the viewpoint of phylogenetic reconstruction. Mitochondrial 79 proteins violate the basic assumptions of phylogenetic methods, namely, homogeneity of the processes of 80 amino acid substitutions along lineages, between sites in alignment and between character states within 81 sites [18]. 42 Introduction In a different approach, Neuwald [15] partitioned sequences 65 into hierarchically organized subsets, each characterized by a group of sites (domain) conserved within 66 this subset but distinguishing it from adjacent subsets. Comparison of such domains with the protein 67 structure allows to associate them with biological functions [16]. Domains obtained by this approach are 68 only weakly similar to those inferred by factorization of DCA cooccurrence matrices [17], suggesting that 69 these methods can provide complementary perspectives. 53 54 The latter process appears to play a major role [4,5]. One type of evidence for this is the correlations 55 between the occurrence of different amino acids at pairs of sites in multiple alignments (MSAs) of 56 homologous sequences. Such correlations, inferred using direct coupling analysis (DCA) or related 57 methods, are associated with physical proximity, and are sufficiently strong that they can be used to infer 58 protein structures and interprotein contacts [6–10] and to predict fitness effects of substitutions [11–13]. 59 60 Given the success of these approaches, it is tempting to aggregate cooccurrence data across many sites to 61 get a bird’s eye view of the constraints on the evolution of the entire protein. Granata et. al. [14] have 62 processed a DCA-derived cooccurrence matrix by graph vertex clustering. They thus partitioned protein 63 sites into dense domains spatially separated on the structure, and showed that these domains correspond 64 to rigid dynamics domains of the protein. In a different approach, Neuwald [15] partitioned sequences 65 into hierarchically organized subsets, each characterized by a group of sites (domain) conserved within 66 this subset but distinguishing it from adjacent subsets. Comparison of such domains with the protein 67 structure allows to associate them with biological functions [16]. Domains obtained by this approach are 68 only weakly similar to those inferred by factorization of DCA cooccurrence matrices [17], suggesting that 69 these methods can provide complementary perspectives. . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. 42 Introduction 102 Evolution is decelerated, indicating stronger purifying selection, at contact interface sites of COX2 and 103 COX3, compared to exposed noncontact noninterface sites. By contrast, in COX1, selective constraint is 104 stronger at non-interface sites, possibly due to their involvement in formation of heme environment. In all 105 three proteins, sites in contact with other mitochondrial-encoded proteins evolve slower than those in 106 contact with nuclear-encoded proteins [29]. These data suggest that the effect of epistasis on the rate of 107 evolution strongly depends on the identity of the interacting partners. 108 109 Second, epistasis has been inferred from compensated pathogenic deviations [30], i.e., cases when a 110 human pathogenic variant has been observed in wildtype in some species. Several such cases have been 111 described for the mitochondrial-encoded proteins of oxidative phosphorylation (OXPHOS). Detailed 112 studies have shown that such variants can be neutralized by substitutions at other sites proximal in the 3D 113 structure or in the same interaction interface [31]. 114 115 Finally, sites in close proximity in protein structures tend to coevolve. This has been observed in COX1 116 protein [32] as well as in mitochondria-nuclear interfaces [33–35]. 117 118 Still, our understanding of interactions between sites and the role of such interactions in the evolution of 119 OXPHOS proteins remains limited. Here, extending our previous work [36,37], we develop a 120 phylogenetic method for inference of protein sites involved either in positive or negative epistatic 121 interactions. Roughly, for each pair of sites, we count the number of cases when a substitution at one of 122 these sites rapidly follows a substitution in the other within the same evolutionary lineage. An excess of 123 96 Epistasis in mitochondrial proteins 97 Several lines of evidence suggest that amino acid sites are involved in tight epistatic interactions both 98 within and between mitochondrial proteins [28]. First, sites of mitochondrial proteins COX1, COX2 and 99 COX3 of the cytochrome oxidase complex (COX) that are involved in contact interfaces with other 100 proteins encoded by mitochondrial or nuclear genomes evolve at systematically different rates, compared 101 to sites not involved in such interfaces [29]. The direction of this difference varies among proteins. 102 Evolution is decelerated, indicating stronger purifying selection, at contact interface sites of COX2 and 103 COX3, compared to exposed noncontact noninterface sites. 42 Introduction This variation can arise due to differences in mutation [19,20] and/or selection [21,22]. As a 82 result, mitochondrial evolution has motivated development of approaches that relax one or several of 83 these assumptions. Heterogeneity between sites has been addressed by using Gamma [23] or general 84 discrete distributions of substitution rates [24] and CAT-models that use Dirichlet processes to classify 85 sites into categories with different equilibrium frequencies of characters [25]. Heterogeneity between 86 lineages has been modeled by using more complicated models [1,2,19]. 8 88 Another dimension of the complexity of mitochondrial evolution is the high degree of convergence 89 between unrelated lineages. This convergence can be caused by mutational biases [19,26] or natural 90 selection favoring the same amino acid in different lineages at a site (homoplasy) [22,27]. Selection- 91 induced convergence at a small subset of sites may produce erroneous phylogenetic signal overwhelming 92 that from unaffected sites, especially when this convergence at different sites affects the same lineages, 93 which has been observed in all 13 protein-coding mitochondrial genes between the lineages of snakes and 94 agamid lizards [27]. The strong signal of convergent evolution cannot be fully addressed in the phylogeny 95 reconstruction even with modern methods [18]. . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 96 Epistasis in mitochondrial proteins 97 Several lines of evidence suggest that amino acid sites are involved in tight epistatic interactions both 98 within and between mitochondrial proteins [28]. First, sites of mitochondrial proteins COX1, COX2 and 99 COX3 of the cytochrome oxidase complex (COX) that are involved in contact interfaces with other 100 proteins encoded by mitochondrial or nuclear genomes evolve at systematically different rates, compared 101 to sites not involved in such interfaces [29]. The direction of this difference varies among proteins. 42 Introduction By contrast, in COX1, selective constraint is 104 stronger at non-interface sites, possibly due to their involvement in formation of heme environment. In all 105 three proteins, sites in contact with other mitochondrial-encoded proteins evolve slower than those in 106 contact with nuclear-encoded proteins [29]. These data suggest that the effect of epistasis on the rate of 107 evolution strongly depends on the identity of the interacting partners. 109 Second, epistasis has been inferred from compensated pathogenic deviations [30], i.e., cases when a 110 human pathogenic variant has been observed in wildtype in some species. Several such cases have been 111 described for the mitochondrial-encoded proteins of oxidative phosphorylation (OXPHOS). Detailed 112 studies have shown that such variants can be neutralized by substitutions at other sites proximal in the 3D 113 structure or in the same interaction interface [31]. . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 125 first substitution decreases the selective advantage, or increases the deleterious effect, of the second one. 126 To address this formally, we compare this number to that expected if substitutions at each site proceed 127 independently of each other. This is done by calculating the association statistic, which is positive if the 128 number of pairs of consecutive substitutions at these sites is unexpectedly high, and negative, if it is 129 unexpectedly low. We apply this method to evolution of OXPHOS proteins encoded in mitochondrial 130 genomes of metazoans and fungi. 131 132 In all proteins, we observe many site pairs with positive and negative phylogenetic associations, with the 133 signal of negative associations being much stronger. Using modularity, a community detection method in 134 networks with negative and positive links, we partition sites in each protein into coevolving groups with a 135 high density of positive links within and negative links between groups. 42 Introduction Sites within a group tend to be 136 located densely on the protein structure. We show that groups distinguished on the basis of cooccurrence 137 of individual substitutions also demonstrate concordance of substitution rates; and that changes in these 138 rates occur in concert between all five OXPHOS proteins encoded in mitochondrial genomes, suggesting 139 that these changes have a common cause. 140 141 Results 142 Concordantly and discordantly evolving pairs of sites 143 First, we modified the previously developed phylogenetic approach [36] to detect pairs of concordantly 142 Concordantly and discordantly evolving pairs of sites 143 First, we modified the previously developed phylogenetic approach [36] to detect pairs of concordantly 144 evolving amino acid sites in mitochondrial-encoded proteins (fig. 1). In brief, we reconstructed the 145 phylogenetic positions of all substitutions, and identified pairs of sites such that a substitution at one of 146 them frequently triggered a rapid subsequent substitution in the other, as evidenced by higher than 147 expected values of the epistatic statistic [36]. Such pairs were assumed to be concordantly evolving, under 148 the logic that the first substitution increased the selective benefit of the second one, implying positive 149 epistatic interactions. In each of the five studied proteins, we observed strong positive associations of 150 substitutions for a number of site pairs that was significantly above that expected randomly (tab. 1). 151 Surprisingly, at a number of other site pairs, the observed epistatic statistics were significantly lower than 152 expected, indicating that a substitution at one of these sites was followed by a substitution at the other 151 Surprisingly, at a number of other site pairs, the observed epistatic statistics were significantly lower than 152 expected, indicating that a substitution at one of these sites was followed by a substitution at the other . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. 42 Introduction ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 153 more rarely than expected randomly, and suggesting negative associations whereby the first substitution 154 makes the second one more deleterious. The negative signal was much stronger than the signal of positive 155 associations, both in terms of lower FDR and larger number of significant site pairs (tab. 2). At most of 156 the negatively associated site pairs, the substitutions at the two considered sites tended to occur in 157 lineages that were not only distinct, but also remote from each other on the phylogeny (fig. 2). 158 159 Table 1. Numbers of concordantly evolving site pairs under different significance thresholds p ≤1e-4 p ≤0.001 p ≤0.01 p ≤0.05 gene #PP FDR #PP FDR #PP FDR #PP FDR ATP6 123 0.036 250 0.104 683 ** 0.357 1727 * 0.704 CYTB 221 0.068 446 0.183 1313 * 0.571 3212 1.02 COX1 762 0.03 1730 0.073 5199 0.227 13121 0.45 COX2 142 0.032 238 0.103 576 0.408 1378 0.87 COX3 306 0.019 640 0.053 1680 0.183 3949 ** 0.393 160 For each gene, the number of predicted site pairs (#PP) and the false discovery rate (FDR) for 160 161 the corresponding nominal p-values are shown. Asterisks indicate the false Exceedance Rate 162 (FER), i.e., the probability that the number of chance-alone findings corresponding to a 163 particular nominal p-value threshold (#FP) is equal or exceeds the number of findings in real 164 data (#PP) (, FER≤0.05; , FER≤0.01). 165 166 Table 2. Numbers of discordantly evolving site pairs under different significance thresholds p ≤1e-4 p ≤0.001 p ≤0.01 p ≤0.05 gene #PP FDR #PP FDR #PP FDR #PP FDR ATP6 1650 0.004 2453 0.01 4206 0.052 6641 0.171 CYTB 2487 0.004 4061 0.013 8132 0.066 14716 0.199 COX1 1504 0.006 2635 0.02 6283 0.093 13273 0.26 COX2 764 0.004 1202 0.015 2446 0.074 4522 0.218 COX3 715 0.005 1159 0.018 2385 0.091 4451 0.267 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . 42 Introduction CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 167 For each gene, the number of predicted site pairs (#PP) and the false discovery rate (FDR) for 168 the corresponding nominal p-values are shown. For all genes and nominal p-values, the FER is 169 below 0.01. 170 171 Conceivably, apparent biases in phylogenetic distribution of substitutions, and specifically hemiplasies 172 (spurious convergent or parallel events), could arise from errors in phylogenetic reconstruction. To 173 control for this, we devised a procedure for accounting for uncertainty of phylogenetic reconstruction. 174 Under this procedure, we weight all potentially hemiplasic substitutions corresponding to a single actual 175 substitution by the reciprocal of the number of such hemiplasic substitutions, so that their contribution to 176 the statistic is not inflated (see Methods). Applying this procedure slightly decreased the power of the 177 test: for each nominal p-value threshold, the number of inferred site pairs decreased and the 178 corresponding FDRs slightly increased (tab. S1, tab. S2). 179 However, this correction changed the list of positively and negatively interacting pairs only slightly; e.g., 180 for COX2, 87 and 72 of the top 100 positive and negative site pairs coincided between the two lists. 179 However, this correction changed the list of positively and negatively interacting pairs only slightly; e.g., 180 for COX2, 87 and 72 of the top 100 positive and negative site pairs coincided between the two lists. 181 Concordant evolution is associated with proximity in protein structures 181 Concordant evolution is associated with proximity in protein structures p y p 182 While the epistatic statistic provides a useful measure of positive or negative association between 183 substitutions at a pair of sites, its values are not comparable between site pairs. To better understand the 184 patterns of associations between multiple site pairs, for each pair of sites, we converted the epistatic 185 statistic into a normalized form. For this, the statistic for each site pair was z-score transformed, and the 186 resulting z-scores across all site pairs were divided by their maximum value. 42 Introduction The resulting values are 187 referred to below as pseudo-correlations; they fall into the range between -1 and 1, with positive values 188 corresponding to coordinated evolution, negative values, to discordant evolution, and 0, to independent 189 evolution of sites. 190 191 We asked how the interacting site pairs are positioned relative to each other in 3D protein structures. For 192 significantly positively interacting site pairs (those with positive pseudo-correlations and significant 193 epistatic statistics, see Methods), we found that stronger pseudo-correlations are associated with smaller 194 distances between sites. By contrast, in all genes except COX1, stronger significant negative pseudo- 182 While the epistatic statistic provides a useful measure of positive or negative association between 182 While the epistatic statistic provides a useful measure of positive or negative association . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 195 correlations are characteristic of sites remote in the 3D structure; while in COX1, they were characteristic 196 of sites nearby in the 3D structure, similar to positive pseudo-correlations (tab. 3). 197 Table 3. Numbers of concordantly and discordantly evolving site pairs mappable to the protein 198 structures, and correlation between concordance (discordance) and protein structure distance. 42 Introduction gene sign of association statistics #pairs nominal p- value threshold for FER<0.05 rho (Spearman’s) p-value ATP6 + 1726 0.05 -0.196 2.81E-13 - 6637 0.05 -0.016 0.2344 CYTB + 1511 0.0129 -0.306 < 2.2e-16 - 14699 0.05 0.006 0.474 COX1 + 13105 0.05 -0.197 < 2.2e-16 - 13265 0.05 0.060 2.41E-10 COX2 + 1009 0.0293 -0.222 6.41E-10 - 4513 0.05 -0.053 0.002 COX3 + 3945 0.05 -0.170 < 2.2e-16 - 4449 0.05 -0.083 6.51E-08 199 For each protein, the numbers of significantly concordantly ('+') and discordantly ('-') evolving 195 correlations are characteristic of sites remote in the 3D structure; while in COX1, they were characteristic 196 of sites nearby in the 3D structure, similar to positive pseudo-correlations (tab. 3). 195 correlations are characteristic of sites remote in the 3D structure; while in COX1, they were characteristic 196 of sites nearby in the 3D structure, similar to positive pseudo-correlations (tab. 3). 195 correlations are characteristic of sites remote in the 3D structure; while in COX1, they were characteristic 196 of sites nearby in the 3D structure, similar to positive pseudo-correlations (tab. 3). Numbers of concordantly and discordantly evolving site pairs mappable to the protein es, and correlation between concordance (discordance) and protein structure distance. 199 200 site pairs with known distances between sites in protein structures (#pairs) are shown, along with 201 the Spearman's correlations (rho) and the corresponding p-value between the association statistic 202 and the structure distance for significant site pairs. For concordantly evolving pairs of sites, a 203 significantly negative value of rho means that strongly associated sites tend to be closer on the 204 structure; for discordantly evolving pairs of sites, a significantly negative rho means that strongly 205 associated sites tend to be apart from each other. 200 site pairs with known distances between sites in protein structures (#pairs) are shown, along with 201 the Spearman's correlations (rho) and the corresponding p-value between the association statistic 202 and the structure distance for significant site pairs. For concordantly evolving pairs of sites, a 203 significantly negative value of rho means that strongly associated sites tend to be closer on the 204 structure; for discordantly evolving pairs of sites, a significantly negative rho means that strongly 205 associated sites tend to be apart from each other. 42 Introduction 206 Detecting groups of coevolving sites 207 Based on the observed pseudo-correlations, we aimed to construct a coevolution graph in which vertices 208 correspond to individual sites, and edges correspond to either positive or negative associations between 209 them. For this, we transformed the matrix of pseudo-correlations by singling out only significant 210 associations, and, among the positively associated site pairs, only those responsible for direct, rather than . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 211 spurious, correlations (see Methods). The resulting association statistics were then used to construct the 212 coevolution graphs (tab 4). 213 Table 4. Basic characteristics of coevolution graphs. protein #sites #vertices #positive edges #negative edges ATP6 226 210 1726 5456 CYTB 379 327 1511 10093 COX1 514 484 13101 13087 COX2 227 202 1009 3475 COX3 260 246 3944 4106 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint Table 5. Sites within a coevolving group are colocated on protein structures. 226 sites. Contact graph of a protein represents the physical contacts between sites on protein 225 For each protein, we partitioned the vertices in the coevolution graph into groups of coevolving 227 structures. For each protein, for each group of coevolving sites as well as for entire graph the 42 Introduction gene group #sites Observed, in- group contact density Expected, in- group contact density p-value atp6 1 80 0.3 0.26 0.0471 2 71 0.29 0.23 0.0023 3 39 0.29 0.11 <1e-4 4 1 0 0 1 total 191 0.45 0.35 <1e-4 cytb 1 92 0.22 0.17 0.0009 2 62 0.14 0.11 0.0121 3 60 0.3 0.1 <1e-4 4 32 0.08 0.05 0.0378 5 29 0.16 0.05 <1e-4 6 23 0.3 0.04 <1e-4 7 12 0.14 0.02 <1e-4 8 6 0.04 0.01 0.0311 total 316 0.33 0.18 <1e-4 cox1 1 121 0.2 0.15 <1e-4 2 112 0.23 0.13 <1e-4 3 89 0.4 0.1 <1e-4 4 66 0.24 0.07 <1e-4 5 39 0.08 0.04 0.0046 6 43 0.25 0.05 <1e-4 total 470 0.39 0.19 <1e-4 cox2 1 49 0.18 0.15 0.0733 2 51 0.2 0.16 0.0202 3 36 0.18 0.1 0.0009 4 36 0.24 0.1 <1e-4 5 14 0.09 0.04 0.0122 total 186 0.32 0.22 <1e-4 cox3 1 67 0.2 0.16 0.012 2 63 0.21 0.15 0.0021 3 44 0.11 0.1 0.2566 4 38 0.22 0.09 <1e-4 5 25 0.1 0.05 0.0075 total 237 0.3 0.22 <1e-4 For each protein, we partitioned the vertices in the coevolution graph into groups of it C t t h f t i t th h i l t t b t it 224 227 structures. For each protein, for each group of coevolving sites as well as for entire graph the . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 228 mean fraction of edges connecting a site with other sites in the same group, the corresponding 229 expected contact density on random partitions of sites, and the corresponding p-values are 230 shown. 231 232 Next, we asked whether groups of coevolving positions correspond to clusters in the 3D structure of the 233 protein. 42 Introduction For this, for each protein, we constructed a second graph, referred to as contact graph. In this 234 graph, vertices again correspond to sites, but there is just one type of edges: two sites are connected if the 235 minimal distance between heavy atoms of their correspondent residues is under 4Å. Considering each 236 group of sites in the coevolution graph of each protein, we then asked whether the corresponding 237 subgraph is tightly connected in the contact graph. 238 239 Indeed, coevolving sites were frequently in contact (tab. 5, fig. 3): for each protein, the density of contacts 240 between sites in coevolving groups was higher than expected (P<1e-4). A significantly elevated number 241 of contacts with sites of the same group was also observed for the majority of individual groups of 242 coevolving sites (Table 5), and these groups include the majority of sites 243 (for the p<0.05 threshold, 100% for COX1 and CYTB, 99% for ATP6, 74% for COX2 and 81% for 244 COX3). 243 (for the p<0.05 threshold, 100% for COX1 and CYTB, 99% for ATP6, 74% for COX2 and 81% for 244 COX3). 245 Coevolving groups of sites and interfaces of protein-protein interactions 246 Next, we tested whether the grouping of sites into coevolving sets tends to be non-random with respect to 247 their involvement in inter-protein interactions with other proteins in the respiratory complexes (either 248 mitochondrial- or nuclear-encoded). In doing so, we controlled for the previously established fact that the 249 coevolving sites tend to be colocalized within a protein. For COX1, COX2,COX3 and ATP6, although 250 not for CYTB, we found that the groups of coevolving sites were non-random with respect to protein- 251 protein interfaces (Fig. 4, 5, Tables S3–S7). 252 253 To better understand the link between coevolution and involvement in protein-protein interfaces, we 254 considered each group of concordantly evolving sites in each protein individually. In three of the 255 analyzed proteins, COX1, COX2 and COX3, we found that some groups favored such interfaces, while 245 Coevolving groups of sites and interfaces of protein-protein interactions 246 Next, we tested whether the grouping of sites into coevolving sets tends to be non-random with respect to 247 their involvement in inter-protein interactions with other proteins in the respiratory complexes (either 248 mitochondrial- or nuclear-encoded). 42 Introduction In doing so, we controlled for the previously established fact that the 249 coevolving sites tend to be colocalized within a protein. For COX1, COX2,COX3 and ATP6, although 250 not for CYTB, we found that the groups of coevolving sites were non-random with respect to protein- 251 protein interfaces (Fig. 4, 5, Tables S3–S7). 246 Next, we tested whether the grouping of sites into coevolving sets tends to be non-random with respect to 247 their involvement in inter-protein interactions with other proteins in the respiratory complexes (either 248 mitochondrial- or nuclear-encoded). In doing so, we controlled for the previously established fact that the 249 coevolving sites tend to be colocalized within a protein. For COX1, COX2,COX3 and ATP6, although 250 not for CYTB, we found that the groups of coevolving sites were non-random with respect to protein- 251 protein interfaces (Fig. 4, 5, Tables S3–S7). 253 To better understand the link between coevolution and involvement in protein-protein interfaces, we 254 considered each group of concordantly evolving sites in each protein individually. In three of the 255 analyzed proteins, COX1, COX2 and COX3, we found that some groups favored such interfaces, while 253 To better understand the link between coevolution and involvement in protein-protein interfaces, we 254 considered each group of concordantly evolving sites in each protein individually. In three of the 255 analyzed proteins, COX1, COX2 and COX3, we found that some groups favored such interfaces, while . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 256 other groups avoided them (fig. 4, Tables S3–S7). In APT6, most of the sites belonging to the group 3 257 were located in the helices H5 and H6 and faced the c-ring of the ATP-synthase complex, forming 258 hydrophilic cavities essential for proton transport through the membrane [39]. 42 Introduction The conserved arginine 259 159 crucial for proton translocation [40] also belongs to group 3 (fig. 5). 260 Concordant evolution of groups of sites in different OXPHOS proteins 261 Groups of sites involved in coevolutionary interactions may undergo coordinated acceleration and 262 deceleration of the overall rate of evolution. We aimed to understand when such acceleration or 263 deceleration had taken place. For this, for each protein, we identified a number (between 31 and 94) of 264 branches of the phylogenetic tree out of the total of 4349 internal branches where the relative frequencies 265 of substitutions had changed between groups of coevolving sites, so that the clade of the descendants of 266 this branch has a substitution frequency significantly different from that in the rest of the tree (tab. S8). 267 268 We asked whether the identity of such branches was concordant between proteins. To test this, we 269 considered the 2275 branches with enough mutations in coevolving groups to test for a change in 270 mutation frequencies in all five proteins. Since it was impossible to unambiguously position such changes 271 when they had occurred in the two consecutive branches (see Methods), for this test, we shifted the 272 inferred position of each change by one branch towards the root of the tree (i.e., to the parental branch). 273 This resulted in 1611 parental branches that could correspond to frequency shifts at one or both of the 274 daughter branches (tab. 6). Depending on the protein, at between 31 and 90 of these branches, such 275 frequency shifts were actually observed (tab. S8). 276 Table 6. Substitutions rates in groups of coevolving sites have changed concordantly in the 277 evolution of Metazoa and Fungi. No. of proteins that have changed their substitution rates concordantly 5 4 or more 3 or more 2 or more 1 or more 0 or more Observed no. of branches with this no. of changes 5 10 17 45 130 1611 Expected no. of branches with this no 256 other groups avoided them (fig. 4, Tables S3–S7). In APT6, most of the sites belonging to the group 3 257 were located in the helices H5 and H6 and faced the c-ring of the ATP-synthase complex, forming 258 hydrophilic cavities essential for proton transport through the membrane [39]. The conserved arginine 259 159 crucial for proton translocation [40] also belongs to group 3 (fig. 5). 42 Introduction 256 other groups avoided them (fig. 4, Tables S3–S7). In APT6, most of the sites belonging to the group 3 257 were located in the helices H5 and H6 and faced the c-ring of the ATP-synthase complex, forming 258 hydrophilic cavities essential for proton transport through the membrane [39]. The conserved arginine 259 159 crucial for proton translocation [40] also belongs to group 3 (fig. 5). 260 Concordant evolution of groups of sites in different OXPHOS proteins 268 We asked whether the identity of such branches was concordant between proteins. To test this, we 269 considered the 2275 branches with enough mutations in coevolving groups to test for a change in 270 mutation frequencies in all five proteins. Since it was impossible to unambiguously position such changes 271 when they had occurred in the two consecutive branches (see Methods), for this test, we shifted the 272 inferred position of each change by one branch towards the root of the tree (i.e., to the parental branch). 273 This resulted in 1611 parental branches that could correspond to frequency shifts at one or both of the 274 daughter branches (tab. 6). Depending on the protein, at between 31 and 90 of these branches, such 275 frequency shifts were actually observed (tab. S8). 276 Table 6. Substitutions rates in groups of coevolving sites have changed concordantly in the 277 evolution of Metazoa and Fungi. No. of proteins that have changed their substitution rates concordantly 5 4 or more 3 or more 2 or more 1 or more 0 or more Observed no. of branches with this no. of changes 5 10 17 45 130 1611 Expected no. of branches with this no. of changes 0.1 0.8 4.2 25.1 176.8 1611 p-value <1e-4 <1e-4 <1e-4 <1e-4 1 1 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. 42 Introduction ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 278 We compared the numbers of branches such that the specified number of different proteins 279 (between 0 and 5) changed substitution rates concordantly on this branch. The expected values 280 where obtained from a null-model assuming the same number of rate changes occurring in each 281 protein (tab. S8) independently of the other proteins, with the probability of a change in 282 substitution rates on a particular branch to be proportional to its length. 283 284 The identity of the branches corresponding to frequency shifts was unexpectedly similar between proteins 285 (tab. 6). Five branches were concordantly represented for all five proteins; they corresponded to the last 286 common ancestors (LCA) of Fungi and Metazoa, Protostomia and Deuterostomia, 287 Echinodermata+Hemichordata and Chordata, Actinopterigia and Sarcopterigia+Tetrapoda, and 288 Lophotrochozoa and Ecdysozoa. Five branches were each represented for four proteins; these were the 289 LCAs of Cnidaria and Bilateria, Amphibia and Amniota, Otomorpha and Euteleosteomorpha, 290 Neocoleoidea and other taxa within Mollusca, and Neolepidoptera and other taxa within the 291 Holometabola group. 7 branches, including the LCA of Mammalia and Diapsida, were each observed in 292 three proteins; and 28 branches were observed in two proteins. 293 294 Discussion 295 Epistatic interactions leave a footprint in the evolutionary history of a protein. Explicit reconstruction of 296 past evolution of individual sites allows inferring pairs of sites such that substitutions at them are 297 correlated in time, a pattern which may arise due to positive epistasis. This idea has been used in an 298 approach designed to infer as interacting site pairs those where substitutions occur unexpectedly rapidly 299 after one another [36,37,41,42]. This, however, has only allowed detecting positive epistasis, i.e., the 278 We compared the numbers of branches such that the specified number of different proteins 279 (between 0 and 5) changed substitution rates concordantly on this branch. The expected values 280 where obtained from a null-model assuming the same number of rate changes occurring in each 281 protein (tab. S8) independently of the other proteins, with the probability of a change in 282 substitution rates on a particular branch to be proportional to its length. 280 where obtained from a null-model assuming the same number of rate changes occurring in each 281 protein (tab. 42 Introduction S8) independently of the other proteins, with the probability of a change in 282 substitution rates on a particular branch to be proportional to its length. 283 284 The identity of the branches corresponding to frequency shifts was unexpectedly similar between proteins 285 (tab. 6). Five branches were concordantly represented for all five proteins; they corresponded to the last 286 common ancestors (LCA) of Fungi and Metazoa, Protostomia and Deuterostomia, 287 Echinodermata+Hemichordata and Chordata, Actinopterigia and Sarcopterigia+Tetrapoda, and 288 Lophotrochozoa and Ecdysozoa. Five branches were each represented for four proteins; these were the 289 LCAs of Cnidaria and Bilateria, Amphibia and Amniota, Otomorpha and Euteleosteomorpha, 290 Neocoleoidea and other taxa within Mollusca, and Neolepidoptera and other taxa within the 291 Holometabola group. 7 branches, including the LCA of Mammalia and Diapsida, were each observed in 292 three proteins; and 28 branches were observed in two proteins. 293 294 Discussion 295 Epistatic interactions leave a footprint in the evolutionary history of a protein. Explicit reconstruction of 296 past evolution of individual sites allows inferring pairs of sites such that substitutions at them are 297 correlated in time, a pattern which may arise due to positive epistasis. This idea has been used in an 298 approach designed to infer as interacting site pairs those where substitutions occur unexpectedly rapidly 299 after one another [36,37,41,42]. This, however, has only allowed detecting positive epistasis, i.e., the 300 situation in which the first of the two substitutions in a pair increases the selective advantage of the 301 second substitution. 302 303 Most existing methods for detection of interactions between sites, such as DCA-based methods, use 304 multiple sequence alignments without explicitly accounting for evolutionary relationships between 305 considered species. Accounting for the phylogeny provides several advantages. First, the MSA-based 284 The identity of the branches corresponding to frequency shifts was unexpectedly similar between proteins 285 (tab. 6). Five branches were concordantly represented for all five proteins; they corresponded to the last 286 common ancestors (LCA) of Fungi and Metazoa, Protostomia and Deuterostomia, . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . 42 Introduction CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 306 methods implicitly assume independence of lineages, considering differences in evolutionary distances 307 between lineages as a nuisance factor. By contrast, phylogeny-based methods provide a formal way to 308 account for non-independence between evolving lineages. Second, rooted phylogenies provide explicit 309 polarization of trait states, allowing to distinguish between ancestral and descendant states. In turn, this 310 allows to detect not only positive, but also negative associations between allele pairs. 311 312 Here, we make use of this latter advantage. We extend our phylogenetic approach to detect the second 313 possible type of epistatic interactions: negative epistasis. In a pair of negatively epistatically interacting 314 sites, the first substitution reduced the fitness benefit conferred by the second substitution, making the 315 second substitution less probable. As a result, substitutions at negatively epistatically interacting pairs of 316 sites will be “repelled” from one another, leading to a deficit of substitutions occurring one after another 317 at the same lineage. 318 319 Any approach based on detection of interactions will have an important caveat which has been discussed 320 previously in the context of positive associations [36,37]. While positively associated substitutions may 321 arise due to interactions, they may also arise due to correlated changes in substitution rates, i.e. due to 322 temporally accelerated mutation or episodes of selection, coinciding between these two sites. Similarly, 323 while a tendency of substitutions to occur at different branches may arise due to negative epistatic 324 interactions, it may also be a result of differences in selection pressure between segments of the 325 phylogeny that differently affect individual sites. Our null model accounts for the differences in selection 326 pressure between branches common to all protein sites, and between protein sites common to all 327 branches. Still, a spurious signal of negative epistasis could arise due to non-epistatically induced changes 328 in selection pressure at a site that are limited to some branches. 329 330 We apply our method to the mitochondrial-encoded subunits of the OXPHOS protein complexes. 42 Introduction Sites of 331 OXPHOS proteins are known to have undergone changes both in their substitution rates (‘heterotachy’) 306 methods implicitly assume independence of lineages, considering differences in evolutionary distances 307 between lineages as a nuisance factor. By contrast, phylogeny-based methods provide a formal way to 308 account for non-independence between evolving lineages. Second, rooted phylogenies provide explicit 309 polarization of trait states, allowing to distinguish between ancestral and descendant states. In turn, this 310 allows to detect not only positive, but also negative associations between allele pairs. 311 306 methods implicitly assume independence of lineages, considering differences in evolutionary distances 307 between lineages as a nuisance factor. By contrast, phylogeny-based methods provide a formal way to 308 account for non-independence between evolving lineages. Second, rooted phylogenies provide explicit 309 polarization of trait states, allowing to distinguish between ancestral and descendant states. In turn, this 310 allows to detect not only positive, but also negative associations between allele pairs. 330 We apply our method to the mitochondrial-encoded subunits of the OXPHOS protein complexes. Sites of 331 OXPHOS proteins are known to have undergone changes both in their substitution rates (‘heterotachy’) 332 and spectra (‘heteropecilly’) between lineages. Here, we show that much of this change is correlated 333 between sites, either positively or negatively. Positively interacting sites are positioned close to each other 334 in the protein structure, providing an independent validation for our approach. . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 335 336 Furthermore, by applying community detection methods, we show that the positively interacting sites are 337 grouped into domains of coevolving sites, with negative epistatic interactions distinguishing these groups 338 from each other. Substitutions at sites within the same domain tend to occur in rapid “bursts” on the 339 phylogeny (fig. 42 Introduction 1); by contrast, substitutions at sites belonging to different domains tend to occur in 340 distinct clades (fig. 2). 341 342 The substitution rate is affected by mutation rate and selection. While the mitochondrial substitution rates 343 have changed due to changes in the mutation rates [19,26], it is unlikely that such changes are site- 344 specific. By contrast, changes in substitution rate may occur naturally at individual sites due to changes in 345 site-specific amino acid propensities. The observed within-site heterogeneity may be most simply 346 explained by such changes in selection with time. 347 348 We find that the sites that have changed concordantly are those that are functionally and structurally 349 linked. This is consistent with previous findings obtained by analyzing sequence alignments [9,13,43]. 350 Such concordance may be caused by direct pairwise interactions between sites. Even in the absence of 351 direct interactions, groups of coevolving sites may arise [44] due to protein-level selection forces 352 mediated by one-dimensional, or global, epistasis [45,46]. 353 354 One possible evolutionary constraint shaping the evolution of COX is the maintenance of interactions 355 between proteins within this complex [47]. Indeed, some of the inferred coevolving groups of sites in 356 COX1, COX2 and COX3 are associated with interactions with other COX proteins, either mitochondrial- 357 or nuclear-encoded or both. Earlier, an excess of biochemically radical substitutions has been observed at 358 interfaces between nuclear and mitochondrial-encoded subunits of COX, suggestive of adaptation [48]. 359 Incompatibilities between nuclear and mitochondrial genomes may play a role in speciation, affecting 360 substitution patterns [47 49 50]; in particular selection for reproductive isolation may cause bursts of 335 336 Furthermore, by applying community detection methods, we show that the positively interacting sites are 337 grouped into domains of coevolving sites, with negative epistatic interactions distinguishing these groups 338 from each other. Substitutions at sites within the same domain tend to occur in rapid “bursts” on the 339 phylogeny (fig. 1); by contrast, substitutions at sites belonging to different domains tend to occur in 340 distinct clades (fig. 2). 341 342 The substitution rate is affected by mutation rate and selection. While the mitochondrial substitution rates 343 have changed due to changes in the mutation rates [19,26], it is unlikely that such changes are site- 344 specific. 42 Introduction 388 As the respiratory function is carried out by several protein complexes, each consisting of multiple 389 subunits encoded in two genomes with significantly different mutation rates, the negative epistasis 390 between sites or domains of one protein may be driven by the need to support the integrity of this 391 complex system. Our findings that negative epistasis appears to be more prevalent than positive epistasis 364 To understand what causes changes in substitution rates in groups of concordantly evolving sites, we 365 hypothesized that the evolution of different mitochondrial proteins was also concordant in that 366 evolutionary rate changes were coordinated between different proteins, in addition to their coordination 367 within proteins. Consistently with this hypothesis, we find that different proteins that are subunits of the 368 same as well as different complexes of OXPHOS change substitution rates in groups of sites on 369 coincident branches of the phylogeny. This concordance may reflect changes in the selection pressure on 370 the respiratory function in the process of adaptation to certain ecological niches affecting multiple 371 OXPHOS proteins simultaneously [53]. The branches that had experienced such concordant changes 372 tended to be deeply rooted in the phylogeny, likely indicative of adaptation at the origin of large 373 taxonomic groups. For example, the LCA of mammals indicated concordant changes in substitution 374 spectra for three genes: CYTB, COX3 and ATP6. 364 To understand what causes changes in substitution rates in groups of concordantly evolving sites, we 365 hypothesized that the evolution of different mitochondrial proteins was also concordant in that 366 evolutionary rate changes were coordinated between different proteins, in addition to their coordination 367 within proteins. Consistently with this hypothesis, we find that different proteins that are subunits of the 368 same as well as different complexes of OXPHOS change substitution rates in groups of sites on 369 coincident branches of the phylogeny. This concordance may reflect changes in the selection pressure on 370 the respiratory function in the process of adaptation to certain ecological niches affecting multiple 371 OXPHOS proteins simultaneously [53]. The branches that had experienced such concordant changes 372 tended to be deeply rooted in the phylogeny, likely indicative of adaptation at the origin of large 373 taxonomic groups. For example, the LCA of mammals indicated concordant changes in substitution 374 spectra for three genes: CYTB, COX3 and ATP6. 42 Introduction By contrast, changes in substitution rate may occur naturally at individual sites due to changes in 345 site-specific amino acid propensities. The observed within-site heterogeneity may be most simply 346 explained by such changes in selection with time. 347 348 We find that the sites that have changed concordantly are those that are functionally and structurally 349 linked. This is consistent with previous findings obtained by analyzing sequence alignments [9,13,43]. 350 Such concordance may be caused by direct pairwise interactions between sites. Even in the absence of 351 direct interactions, groups of coevolving sites may arise [44] due to protein-level selection forces 335 348 We find that the sites that have changed concordantly are those that are functionally and structurally 349 linked. This is consistent with previous findings obtained by analyzing sequence alignments [9,13,43]. 350 Such concordance may be caused by direct pairwise interactions between sites. Even in the absence of 351 direct interactions, groups of coevolving sites may arise [44] due to protein-level selection forces 352 mediated by one-dimensional, or global, epistasis [45,46]. 354 One possible evolutionary constraint shaping the evolution of COX is the maintenance of interactions 355 between proteins within this complex [47]. Indeed, some of the inferred coevolving groups of sites in 356 COX1, COX2 and COX3 are associated with interactions with other COX proteins, either mitochondrial- 357 or nuclear-encoded or both. Earlier, an excess of biochemically radical substitutions has been observed at 358 interfaces between nuclear and mitochondrial-encoded subunits of COX, suggestive of adaptation [48]. 359 Incompatibilities between nuclear and mitochondrial genomes may play a role in speciation, affecting 360 substitution patterns [47,49,50]; in particular, selection for reproductive isolation may cause bursts of 361 substitutions in interfaces between subunits encoded in nuclear and mitochondrial genomes [33,51,52]. 362 The observed coevolution within interface sites may be partially explained by such selective pressures. 363 363 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. 42 Introduction It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 364 To understand what causes changes in substitution rates in groups of concordantly evolving sites, we 365 hypothesized that the evolution of different mitochondrial proteins was also concordant in that 366 evolutionary rate changes were coordinated between different proteins, in addition to their coordination 367 within proteins. Consistently with this hypothesis, we find that different proteins that are subunits of the 368 same as well as different complexes of OXPHOS change substitution rates in groups of sites on 369 coincident branches of the phylogeny. This concordance may reflect changes in the selection pressure on 370 the respiratory function in the process of adaptation to certain ecological niches affecting multiple 371 OXPHOS proteins simultaneously [53]. The branches that had experienced such concordant changes 372 tended to be deeply rooted in the phylogeny, likely indicative of adaptation at the origin of large 373 taxonomic groups. For example, the LCA of mammals indicated concordant changes in substitution 374 spectra for three genes: CYTB, COX3 and ATP6. 375 376 Synergistic negative epistasis between deleterious mutations has been described from population 377 genomics data [54] and has been postulated to play a major role in maintenance of sexual reproduction 378 [55]. Furthermore, negative epistasis has been observed in experimental evolution. One characteristic 379 pattern is the presence of distinct “seeding” mutations early in the adaptation process that each trigger its 380 own cascade of subsequent adaptive mutations, directing subsequent evolution. The seeding mutations 381 themselves are in negative epistasis, making them effectively mutually exclusive, and leading to 382 substantial randomness in the choice of the particular adaptive path taken by the population [56]. This 383 pattern is indeed theoretically expected both within and between proteins on fitness landscapes with high 384 local ruggedness [57–59] and has been observed in multiple evolutionary experiments [56,58]. 385 High prevalence of negative epistasis in mitochondrial proteins may have to do with their strong 386 modularity. Conceivably, changes in one domain may trigger subsequent changes in the same domain 387 while increasing the cost of changes in other domains, in line with the “seeding mutations” model [56]. 42 Introduction 376 Synergistic negative epistasis between deleterious mutations has been described from population 377 genomics data [54] and has been postulated to play a major role in maintenance of sexual reproduction 378 [55]. Furthermore, negative epistasis has been observed in experimental evolution. One characteristic 379 pattern is the presence of distinct “seeding” mutations early in the adaptation process that each trigger its 380 own cascade of subsequent adaptive mutations, directing subsequent evolution. The seeding mutations 381 themselves are in negative epistasis, making them effectively mutually exclusive, and leading to 382 substantial randomness in the choice of the particular adaptive path taken by the population [56]. This 383 pattern is indeed theoretically expected both within and between proteins on fitness landscapes with high 384 local ruggedness [57–59] and has been observed in multiple evolutionary experiments [56,58]. 385 High prevalence of negative epistasis in mitochondrial proteins may have to do with their strong 386 modularity. Conceivably, changes in one domain may trigger subsequent changes in the same domain 387 while increasing the cost of changes in other domains, in line with the “seeding mutations” model [56]. 388 As the respiratory function is carried out by several protein complexes, each consisting of multiple 389 subunits encoded in two genomes with significantly different mutation rates, the negative epistasis 390 between sites or domains of one protein may be driven by the need to support the integrity of this 391 complex system. Our findings that negative epistasis appears to be more prevalent than positive epistasis 392 (Tables 1 and 2), and that positive epistatic interactions tend to be short-range, and negative, long-range . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 393 in protein structures (Table 3), are also broadly consistent with the results obtained in a high throughput 394 mutagenesis experiment in GB1 protein [60]. 42 Introduction Families of 398 mitochondrial proteins are an excellent model for the study of negative epistasis between sites because of 399 a high number of substitutions in each site and multiple constraints on their evolution. 400 Methods 395 Whereas bursts of substitutions in correlated sites caused by positive epistasis have been reported 396 previously [36,37,61,62], negative epistasis has, to our knowledge, not been reported from similar data, 397 probably because detection of a deficit of events is harder than detection of an excess. Families of 398 mitochondrial proteins are an excellent model for the study of negative epistasis between sites because of 399 a high number of substitutions in each site and multiple constraints on their evolution. 400 Methods 401 Data 402 Amino acid sequences of five OXPHOS proteins (COX1, COX2, COX3, ATP6 and CYTB) encoded in 403 mitochondrial genomes of 4350 species of metazoans and fungi were obtained from [22]. Each protein 404 was aligned with MAFFT v6.864b [63] using einsi option. For phylogenetic reconstruction, alignment 405 columns with more than 1% of gaps were excluded, and sequences of the five genes were concatenated. 406 The phylogenetic tree was reconstructed with RAxML 8.0.0 using ITOL taxonomy-constrained topology 407 as described in [22]. Bootstrap support for each branch was obtained using rapid bootstrap option of 408 RAxML8.0.0 [64]. For ancestral state reconstruction, we excluded columns with ≥10% of internal gaps. 409 Ancestral states were reconstructed with MEGA-CC using “mtREV with Freqs. (+F)” model and Gamma 410 distributed evolutionary rates between sites with 4 discrete Gamma categories. As the length of COX1 411 exceeds the limit of MEGA, ancestral states were reconstructed separately for two halves of its alignment. 412 413 3D structures were obtained from PDB (1occ for COX, 5ara for ATP6 and 1bgy for CYTB) [65–67]. To 414 map the sites from the MSA to the 3D structure, we performed a pairwise alignment of the Bos taurus 413 3D structures were obtained from PDB (1occ for COX, 5ara for ATP6 and 1bgy for CYTB) [65–67]. To 414 map the sites from the MSA to the 3D structure, we performed a pairwise alignment of the Bos taurus 415 (TaxID=9913) protein sequence from our MSA to that of the corresponding protein chain in the PDB 416 using BlastP [68,69]. 42 Introduction 395 Whereas bursts of substitutions in correlated sites caused by positive epistasis have been reported 396 previously [36,37,61,62], negative epistasis has, to our knowledge, not been reported from similar data, 397 probably because detection of a deficit of events is harder than detection of an excess. Families of 398 mitochondrial proteins are an excellent model for the study of negative epistasis between sites because of 399 a high number of substitutions in each site and multiple constraints on their evolution. 400 Methods 401 Data 402 Amino acid sequences of five OXPHOS proteins (COX1, COX2, COX3, ATP6 and CYTB) encoded in 403 mitochondrial genomes of 4350 species of metazoans and fungi were obtained from [22]. Each protein 404 was aligned with MAFFT v6.864b [63] using einsi option. For phylogenetic reconstruction, alignment 405 columns with more than 1% of gaps were excluded, and sequences of the five genes were concatenated. 406 The phylogenetic tree was reconstructed with RAxML 8.0.0 using ITOL taxonomy-constrained topology 407 as described in [22]. Bootstrap support for each branch was obtained using rapid bootstrap option of 408 RAxML8.0.0 [64]. For ancestral state reconstruction, we excluded columns with ≥10% of internal gaps. 409 Ancestral states were reconstructed with MEGA-CC using “mtREV with Freqs. (+F)” model and Gamma 410 distributed evolutionary rates between sites with 4 discrete Gamma categories. As the length of COX1 411 exceeds the limit of MEGA, ancestral states were reconstructed separately for two halves of its alignment 412 413 3D structures were obtained from PDB (1occ for COX, 5ara for ATP6 and 1bgy for CYTB) [65–67]. To 414 map the sites from the MSA to the 3D structure, we performed a pairwise alignment of the Bos taurus 393 in protein structures (Table 3), are also broadly consistent with the results obtained in a high throughput 394 mutagenesis experiment in GB1 protein [60]. 393 in protein structures (Table 3), are also broadly consistent with the results obtained in a high throughput 394 mutagenesis experiment in GB1 protein [60]. 395 Whereas bursts of substitutions in correlated sites caused by positive epistasis have been reported 396 previously [36,37,61,62], negative epistasis has, to our knowledge, not been reported from similar data, 397 probably because detection of a deficit of events is harder than detection of an excess. 42 Introduction 417 Inference of epistatic site pairs 418 To detect epistasis between protein sites, we reimplemented the phylogenetic method from [36], with 419 some modifications, using BioPhylo package for Perl [70]. As in [36], for each pair of sites, we calculated 417 Inference of epistatic site pairs 418 To detect epistasis between protein sites, we reimplemented the phylogenetic method from [36], with 419 some modifications, using BioPhylo package for Perl [70]. As in [36], for each pair of sites, we calculated . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 420 the epistatic statistic as the number of pairs of single amino acid substitutions that were consecutive, i.e., 421 fell onto the same phylogenetic lineage. Mutations that followed one another rapidly had higher weight, 422 with exponential penalties for the waiting time of a second mutation in a pair [36]. Unlike [36], we did 423 not distinguish between “leading” and “trailing” sites; instead, the epistatic statistic was defined for an 424 unordered pair of sites as the sum of the statistics for the two corresponding ordered pairs. As in [36], we 425 compared the observed values of the epistatic statistics with those expected if mutations at different sites 426 were distributed independently of each other, preserving the numbers of mutations for each site and for 427 each branch. To generate these null distributions, we used BiRewire package for R [71]. A total of 10000 428 sets of mutations were generated in parallel using the GNU Parallel [72] utility. The upper and lower p- 429 values for the epistatic statistic were defined as the percentiles of the null distribution corresponding to 430 the observed values of this statistic. 431 432 For each p-value, we estimated the false discovery (FDR) and exceedance (FER) [73,74] rates following 433 the procedure from [36]. 42 Introduction Briefly, for 400 random sets of mutations on the phylogeny, we inferred 434 positively and negatively coevolving site pairs. We estimated the FDR as the ratio of the average number 435 of findings (coevolving site pairs with the same or better p-value) in a random dataset to the number of 436 findings in the real data. We estimated the FER as the probability that the number of true positive findings 437 in the data was greater than zero, namely, , where is the number of false positive 𝑃(#𝐹𝑃≥#𝑃𝑃) < 𝛼 #𝐹𝑃 438 findings estimated from a random set, #PP is the number of positive findings in the data and is 𝛼= 0.05 439 the significance level. For each gene, we determined the largest sets of significant site pairs as those with 440 positive pseudo-correlations and the nominal p-values of epistatic statistics below the threshold t, were t 441 is the lesser of the two values: 0.05 and the highest p-value for which FER was <0.05. 442 443 To make sure that the observed associations between evolutionary processes at different sites were not 444 artifacts of clustering of spurious substitutions in clades with incorrectly reconstructed topologies [75], 445 we performed a separate analysis accounting for the uncertainty in phylogenetic reconstruction as 446 follows. We defined a subset of well resolved branches of the phylogeny as those with rapid bootstrap 447 [64] support exceeding 95%. These branches split the tree into subtrees with poorly resolved branches. 420 the epistatic statistic as the number of pairs of single amino acid substitutions that were consecutive, i.e., 421 fell onto the same phylogenetic lineage. Mutations that followed one another rapidly had higher weight, 422 with exponential penalties for the waiting time of a second mutation in a pair [36]. Unlike [36], we did 423 not distinguish between “leading” and “trailing” sites; instead, the epistatic statistic was defined for an 424 unordered pair of sites as the sum of the statistics for the two corresponding ordered pairs. As in [36], we 425 compared the observed values of the epistatic statistics with those expected if mutations at different sites 426 were distributed independently of each other, preserving the numbers of mutations for each site and for 427 each branch. To generate these null distributions, we used BiRewire package for R [71]. 42 Introduction A total of 10000 428 sets of mutations were generated in parallel using the GNU Parallel [72] utility. The upper and lower p- 429 values for the epistatic statistic were defined as the percentiles of the null distribution corresponding to 430 the observed values of this statistic. 420 the epistatic statistic as the number of pairs of single amino acid substitutions that were consecutive, i.e., 421 fell onto the same phylogenetic lineage. Mutations that followed one another rapidly had higher weight, 422 with exponential penalties for the waiting time of a second mutation in a pair [36]. Unlike [36], we did 423 not distinguish between “leading” and “trailing” sites; instead, the epistatic statistic was defined for an 424 unordered pair of sites as the sum of the statistics for the two corresponding ordered pairs. As in [36], we 425 compared the observed values of the epistatic statistics with those expected if mutations at different sites 426 were distributed independently of each other, preserving the numbers of mutations for each site and for 427 each branch. To generate these null distributions, we used BiRewire package for R [71]. A total of 10000 428 sets of mutations were generated in parallel using the GNU Parallel [72] utility. The upper and lower p- 429 values for the epistatic statistic were defined as the percentiles of the null distribution corresponding to 430 the observed values of this statistic. 432 For each p-value, we estimated the false discovery (FDR) and exceedance (FER) [73,74] rates following 433 the procedure from [36]. Briefly, for 400 random sets of mutations on the phylogeny, we inferred 434 positively and negatively coevolving site pairs. We estimated the FDR as the ratio of the average number 435 of findings (coevolving site pairs with the same or better p-value) in a random dataset to the number of 436 findings in the real data. We estimated the FER as the probability that the number of true positive findings 437 in the data was greater than zero, namely, , where is the number of false positive 𝑃(#𝐹𝑃≥#𝑃𝑃) < 𝛼 #𝐹𝑃 438 findings estimated from a random set, #PP is the number of positive findings in the data and is 𝛼= 0.05 439 the significance level. 42 Introduction 456 Construction of coevolution graphs 457 For each unordered pair of sites, we defined the pseudo-correlation as the sum of the epistatic statistics 458 for the two corresponding ordered pairs, normalized so that the highest value was 1 if positive, or lowest - 459 1 if negative. Next, we aimed to single out the site pairs driving the observed positive pseudo- 460 correlations, and to get rid of spurious positive pseudo-correlations resulting from indirect interactions 461 between sites. For this, following previous studies [7,76,77], for each site pair, we defined the association 462 statistic as follows. If the pseudo-correlation was positive, the association statistic was assumed to equal 463 the corresponding partial correlation calculated by cor2pcor R package 464 (http://www.strimmerlab.org/software/corpcor/) with the correlation shrinkage intensity lambda set to 0.9 465 [78]; if the pseudo-correlation was negative, the association statistic was assumed to equal the pseudo- 466 correlation itself. 467 468 For each protein, we then used the values of the association statistic to construct the coevolution graph as 469 f ll All i bl it t d h d W t d i f d ith 456 Construction of coevolution graphs 457 For each unordered pair of sites, we defined the pseudo-correlation as the sum of the epistatic statistics 458 for the two corresponding ordered pairs, normalized so that the highest value was 1 if positive, or lowest - 459 1 if negative. Next, we aimed to single out the site pairs driving the observed positive pseudo- 460 correlations, and to get rid of spurious positive pseudo-correlations resulting from indirect interactions 461 between sites. For this, following previous studies [7,76,77], for each site pair, we defined the association 462 statistic as follows. If the pseudo-correlation was positive, the association statistic was assumed to equal 463 the corresponding partial correlation calculated by cor2pcor R package 464 (http://www.strimmerlab.org/software/corpcor/) with the correlation shrinkage intensity lambda set to 0.9 465 [78]; if the pseudo-correlation was negative, the association statistic was assumed to equal the pseudo- 466 correlation itself. 467 468 For each protein, we then used the values of the association statistic to construct the coevolution graph as 469 follows. All variable sites were represented as graph nodes. We connected a pair of nodes with a 470 “positive” edge if the corresponding site pair had the upper p-value and the corresponding FER both 471 below 0.05 and a positive association statistic. 42 Introduction For each gene, we determined the largest sets of significant site pairs as those with 440 positive pseudo-correlations and the nominal p-values of epistatic statistics below the threshold t, were t 441 is the lesser of the two values: 0.05 and the highest p-value for which FER was <0.05. . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 449 unambiguous. By contrast, the precise number and phylogenetic position of substitutions falling onto a 450 poorly resolved subtree was unknown. We conservatively assumed that each poorly resolved subtree had 451 experienced no more than one substitution at a site. If multiple substitutions within a poorly resolved 452 subtree were reconstructed, we therefore assumed that all but one of these substitutions were spurious. 453 Under this assumption, the phylogenetic position of the only real substitution was not known exactly. We 454 therefore calculated the epistatic statistic as the weighted sum over all of the n potential (reconstructed) 455 positions of this substitution within the subtree, each with the weight of 1/n. 449 unambiguous. By contrast, the precise number and phylogenetic position of substitutions falling onto a 450 poorly resolved subtree was unknown. We conservatively assumed that each poorly resolved subtree had 451 experienced no more than one substitution at a site. If multiple substitutions within a poorly resolved 452 subtree were reconstructed, we therefore assumed that all but one of these substitutions were spurious. 453 Under this assumption, the phylogenetic position of the only real substitution was not known exactly. We 454 therefore calculated the epistatic statistic as the weighted sum over all of the n potential (reconstructed) 455 positions of this substitution within the subtree, each with the weight of 1/n. 42 Introduction 485 486 For each group of coevolving sites, we identified the subgraph of the contact graph corresponding to these 487 sites, and defined the contact density statistic as follows. For each group, we calculated the ratio of the 488 number of edges connecting vertices within group to the total number of edges which had at least one 489 vertex in this group. For the entire protein, we calculated the ratio of the number of edges having both 490 vertices in the same group to the total number of edges in the contact graph. 491 Associations between groups of coevolving sites and protein-protein interface sites 492 We estimated the associations between coevolving groups and protein-protein interaction interfaces, 493 defined as follows. Following Aledo et. al. [29,79], we classified the amino acid residues with solvent 494 accessibilities in isolated subunit below 5% as buried; those sites were excluded from the contact graph 495 and not considered further in this analysis. The remaining exposed residues were partitioned into contact 496 residues that had contacts with other subunits in the complex; exposed noncontact interface 497 (ENC_interface) residues that had solvent accessibility within the complex lower than that as an isolated 498 subunit; and the remaining exposed noncontact noninterface residues that were on the protein surface but 499 not involved in interactions with other subunits. Sites in MSA were classified as the corresponding 500 residues of the Bos taurus protein. We separately estimated associations of coevolving groups of sites 501 with contact sites and with interface sites, a larger set defined as the union of contact and ENC_interface 502 sites. . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). 479 Overlaying coevolution and contact graphs 480 If the inferred coevolution graphs reflect the structural constraints on proteins evolution, the amino acids 481 adjacent in that graph can be expected to be in spatial contact. To test this, we constructed a contact graph 482 with vertices representing sites, and edges corresponding to contacts in the protein structure. Following 483 earlier studies, we defined a site pair to be in contact if the minimal distance between the heavy atoms of 484 their residues was <4 angstroms [29]. 485 486 For each group of coevolving sites, we identified the subgraph of the contact graph corresponding to these 487 sites, and defined the contact density statistic as follows. For each group, we calculated the ratio of the 488 number of edges connecting vertices within group to the total number of edges which had at least one 489 vertex in this group. For the entire protein, we calculated the ratio of the number of edges having both 490 vertices in the same group to the total number of edges in the contact graph. 491 Associations between groups of coevolving sites and protein-protein interface sites 492 We estimated the associations between coevolving groups and protein-protein interaction interfaces, 493 defined as follows. Following Aledo et. al. [29,79], we classified the amino acid residues with solvent 494 accessibilities in isolated subunit below 5% as buried; those sites were excluded from the contact graph 495 and not considered further in this analysis. The remaining exposed residues were partitioned into contact 486 For each group of coevolving sites, we identified the subgraph of the contact graph corresponding to these 487 sites, and defined the contact density statistic as follows. For each group, we calculated the ratio of the 488 number of edges connecting vertices within group to the total number of edges which had at least one 489 vertex in this group. For the entire protein, we calculated the ratio of the number of edges having both 490 vertices in the same group to the total number of edges in the contact graph. 491 Associations between groups of coevolving sites and protein-protein interface sites 492 We estimated the associations between coevolving groups and protein-protein interaction interfaces, 493 defined as follows. Following Aledo et. al. 42 Introduction Alternatively, we connected them with a “negative” edge if 472 they had the lower p-value below 0.05 and a negative association statistic. For all five genes, the 473 estimates of FER corresponding to the threshold 0.05 on the nominal lower p-value were below the 474 significance level . The values of the association statistic were assigned to each edge as its 𝛼= 0.05 475 weight. 456 Construction of coevolution graphs 457 For each unordered pair of sites, we defined the pseudo-correlation as the sum of the epistatic statistics 458 for the two corresponding ordered pairs, normalized so that the highest value was 1 if positive, or lowest - 459 1 if negative. Next, we aimed to single out the site pairs driving the observed positive pseudo- 460 correlations, and to get rid of spurious positive pseudo-correlations resulting from indirect interactions 461 between sites. For this, following previous studies [7,76,77], for each site pair, we defined the association 462 statistic as follows. If the pseudo-correlation was positive, the association statistic was assumed to equal 463 the corresponding partial correlation calculated by cor2pcor R package 476 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). 479 Overlaying coevolution and contact graphs 480 If the inferred coevolution graphs reflect the structural constraints on proteins evolution, the amino acids 481 adjacent in that graph can be expected to be in spatial contact. To test this, we constructed a contact graph 482 with vertices representing sites, and edges corresponding to contacts in the protein structure. Following 483 earlier studies, we defined a site pair to be in contact if the minimal distance between the heavy atoms of 484 their residues was <4 angstroms [29]. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). [29,79], we classified the amino acid residues with solvent 494 accessibilities in isolated subunit below 5% as buried; those sites were excluded from the contact graph 495 and not considered further in this analysis. The remaining exposed residues were partitioned into contact 496 residues that had contacts with other subunits in the complex; exposed noncontact interface 497 (ENC_interface) residues that had solvent accessibility within the complex lower than that as an isolated 498 subunit; and the remaining exposed noncontact noninterface residues that were on the protein surface but 499 not involved in interactions with other subunits. Sites in MSA were classified as the corresponding 500 residues of the Bos taurus protein. We separately estimated associations of coevolving groups of sites 501 with contact sites and with interface sites, a larger set defined as the union of contact and ENC_interface 502 sites. 503 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 504 The vertex clustering algorithm partitioned protein sites into groups of coevolving sites. We asked 505 whether these groups were enriched or depleted in contact or interface sites, referred to as the testing 506 subsets. To test the null hypothesis of independence, we constructed the contingency table and calculated 507 the chi^2 statistic. Additionally, for each group of coevolving sites, we estimated the Jaccard index, i.e., 508 the number of vertices common to the testing subset and the considered group of coevolving sites, divided 509 by the number of vertices in either of these sets. 510 511 Groups of coevolving sites as well as many of the testing subsets formed dense clusters in the protein 512 structure. We were concerned that significant associations between these characteristics could spuriously 513 arise due to such spatial clustering rather than due to interactions between sites. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). To control for this, we 514 compared the observed values of the statistics with those expected from random groups of sites with the 515 same extent of clustering in the spatial structure as the testing subset. For this, we sampled random 516 subgraphs of the contact graph that had the same number of vertices and equal or greater number of edges 517 connecting them as the testing subset, and used these samples to estimate the expected counts for the 518 contingency tables and to obtain the p-values. To perform this sampling, we implemented an algorithm 519 similar to the algorithm of uniform sampling of connected subgraphs with predefined numbers of vertices 520 [80], with two differences. First, our method rejected subgraphs having fewer edges than the subgraph of 521 the testing subset. Second, we allowed disconnected subgraphs as follows. If the testing subset 522 corresponded to a disconnected subgraph, we performed sampling for each connected component 523 separately, but prohibited the sampled subgraphs corresponding to different components from containing 524 overlapping sets of vertices. For this, we randomly ordered the connected components; sampled a 525 random connected subgraph corresponding to the first component; removed its vertices from the graph; 526 and repeated the procedure for all subsequent components. Sometimes it was impossible to sample a 527 connected subgraph with the given number of edges from the remainder of the graph. To address this, we 528 limited the number of sampling trials to 10000; if no trial succeeded in finding a suitable subgraph, we 504 The vertex clustering algorithm partitioned protein sites into groups of coevolving sites. We asked 505 whether these groups were enriched or depleted in contact or interface sites, referred to as the testing 506 subsets. To test the null hypothesis of independence, we constructed the contingency table and calculated 507 the chi^2 statistic. Additionally, for each group of coevolving sites, we estimated the Jaccard index, i.e., 508 the number of vertices common to the testing subset and the considered group of coevolving sites, divided 509 by the number of vertices in either of these sets. 510 511 Groups of coevolving sites as well as many of the testing subsets formed dense clusters in the protein 512 structure. We were concerned that significant associations between these characteristics could spuriously 513 arise due to such spatial clustering rather than due to interactions between sites. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). To control for this, we 514 compared the observed values of the statistics with those expected from random groups of sites with the 515 same extent of clustering in the spatial structure as the testing subset. For this, we sampled random 516 subgraphs of the contact graph that had the same number of vertices and equal or greater number of edges 517 connecting them as the testing subset, and used these samples to estimate the expected counts for the 518 contingency tables and to obtain the p-values. To perform this sampling, we implemented an algorithm 519 similar to the algorithm of uniform sampling of connected subgraphs with predefined numbers of vertices 520 [80], with two differences. First, our method rejected subgraphs having fewer edges than the subgraph of 521 the testing subset. Second, we allowed disconnected subgraphs as follows. If the testing subset 522 corresponded to a disconnected subgraph, we performed sampling for each connected component 523 separately, but prohibited the sampled subgraphs corresponding to different components from containing 524 overlapping sets of vertices. For this, we randomly ordered the connected components; sampled a 525 random connected subgraph corresponding to the first component; removed its vertices from the graph; 526 and repeated the procedure for all subsequent components. Sometimes it was impossible to sample a 527 connected subgraph with the given number of edges from the remainder of the graph. To address this, we 528 limited the number of sampling trials to 10000; if no trial succeeded in finding a suitable subgraph, we 529 rolled the algorithm one step back, sampling a different random subgraph for the previous component. 530 Each subgraph thus sampled defined a binary partition of sites. . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 559 560 We tested the significance of the overlap between the branches corresponding to changes in relative 561 substitution frequencies between different genes using a permutation test, assuming that a longer branch 562 was more likely to experience a significant change than a short branch. For this, we calculated the 563 numbers of branches corresponding to changes in zero, one, two, etc., five genes. To calculate the 564 expectation for this value, we generated 10000 permutations, randomly picking for each gene the same 565 number of branches as in the data, each with the probability proportional to the sum of the lengths of its 566 two daughter branches. Finally, we calculated the probabilities to observe the specified number of 567 concordant events for k or more genes, where k=0, 1, 2, ..., 5. 568 Supplementary Information 569 Table S1. Numbers of concordantly evolving site pairs, inferred with correction for phylogenetic 570 uncertainty, under different significance thresholds. 571 572 Table S2. Numbers of discordantly evolving site pairs, inferred with correction for phylogenetic 573 uncertainty, under different significance thresholds. 574 575 Table S3. Coevolution of surface sites of COX1 and interactions with other proteins of the 576 respiratory complex IV. 577 578 Table S4. Coevolution of surface sites of COX2 and interactions with other proteins of the 579 respiratory complex IV. 580 581 Table S5. Coevolution of surface sites of COX3 and interactions with other proteins of the 582 respiratory complex IV. 583 584 Table S6. Coevolution of surface sites of CYTB and interactions with other proteins of the 585 respiratory complex III. 586 587 Table S7. Coevolution of surface sites of ATP6 and interactions with other proteins of the 588 respiratory complex V. 589 590 Table S8. Substitutions rates in groups of coevolving sites have changed during evolution of 591 Metazoa and Fungi. 592 559 560 We tested the significance of the overlap between the branches corresponding to changes in relative 561 substitution frequencies between different genes using a permutation test, assuming that a longer branch 562 was more likely to experience a significant change than a short branch. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 531 Inference of episodic evolution 532 We analyzed the distribution of substitutions over the phylogeny, identifying the phylogenetic branches 533 corresponding to changes in substitution accumulation rates in some groups of coevolving sites. For this, 534 we used the following procedure. For each branch of the tree i, we calculated the vector ni of the numbers 535 of substitutions that occurred at each group of coevolving sites on this branch, and mi as the sum of nk 536 across all branches k descendant to i. We then traversed the tree, looking for branches corresponding to 537 significant changes in this vector. First, we defined the root branch as the “current ancestor”. Next, 538 starting from it, we traversed the tree towards the terminal branches. For each branch i encountered in this 539 process, we compared the vector of substitutions that occurred on this and all subsequent branches 540 vi=ni+mi to the vector of substitutions that occurred in all the remaining branches descendant to the 541 current ancestor ci=ma(i)-vi, where a(i) is the current ancestor to i. The two vectors were compared using 542 the Fisher's exact or chi^2 tests as implemented in the fisher.test package of R, with the Bonferroni 543 correction for the number of internal nodes tested. In each comparison, the groups that had no 544 substitutions in the subtree of the current ancestor were excluded. If vi and ci were significantly different, 545 we assumed that the branch i corresponded to a significant change in the relative substitution frequencies 546 between groups. In this case, we redefined the current ancestor as i, and repeated the procedure for 547 descendant branches. If the total number of substitutions in a subtree of a branch was very low (equal to 548 the number of groups or less), the test was not further applied to descendant branches. 549 Estimation of concordance of episodic evolution between OXPHOS proteins . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 593 The tree, alignments, predicted pairs of epistatically interacting sites and all other data required for 594 analyses mentioned in the Methods section with the detailed description of file contents are provided in 595 the "08_SupplData.7z" file. 596 References 597 1. Lopez P, Casane D, Philippe H. Heterotachy, an important process of protein evolution. 598 Mol Biol Evol. 2002;19: 1–7. doi:10.1093/oxfordjournals.molbev.a003973 599 2. Roure B, Philippe H. Site-specific time heterogeneity of the substitution process and its 600 impact on phylogenetic inference. BMC Evolutionary Biology. 2011;11. doi:10.1186/1471- 601 2148-11-17 602 3. Halpern AL, Bruno WJ. Evolutionary distances for protein-coding sequences: modeling 603 site-specific residue frequencies. Mol Biol Evol. 1998;15: 910–917. 604 doi:10.1093/oxfordjournals.molbev.a025995 605 4. Bazykin GA. Changing preferences: deformation of single position amino acid fitness 606 landscapes and evolution of proteins. Biology Letters. 2015;11: 20150315. 607 doi:10.1098/rsbl.2015.0315 608 5. Storz JF. Compensatory mutations and epistasis for protein function. Current Opinion in 609 Structural Biology. 2018;50: 18–25. doi:10.1016/j.sbi.2017.10.009 610 6. Morcos F, Pagnani A, Lunt B, Bertolino A, Marks DS, Sander C, et al. Direct-coupling 611 analysis of residue coevolution captures native contacts across many protein families. Proc 612 Natl Acad Sci USA. 2011;108: E1293-1301. doi:10.1073/pnas.1111471108 613 7. Jones DT, Buchan DWA, Cozzetto D, Pontil M. PSICOV: precise structural contact 614 prediction using sparse inverse covariance estimation on large multiple sequence 615 li t Bi i f ti 2012 28 184 190 d i 10 1093/bi i f ti /bt 638 593 The tree, alignments, predicted pairs of epistatically interacting sites and all other data required for 594 analyses mentioned in the Methods section with the detailed description of file contents are provided in 595 the "08_SupplData.7z" file. 599 2. Roure B, Philippe H. Site-specific time heterogeneity of the substitution process and its 600 impact on phylogenetic inference. BMC Evolutionary Biology. 2011;11. doi:10.1186/1471- 601 2148-11-17 599 2. Roure B, Philippe H. Site-specific time heterogeneity of the substitution process and its 600 impact on phylogenetic inference. BMC Evolutionary Biology. 2011;11. doi:10.1186/1471- 601 2148-11-17 602 3. Halpern AL, Bruno WJ. Evolutionary distances for protein-coding sequences: modeling 603 site-specific residue frequencies. Mol Biol Evol. 1998;15: 910–917. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). For this, we calculated the 563 numbers of branches corresponding to changes in zero, one, two, etc., five genes. To calculate the 564 expectation for this value, we generated 10000 permutations, randomly picking for each gene the same 565 number of branches as in the data, each with the probability proportional to the sum of the lengths of its 566 two daughter branches. Finally, we calculated the probabilities to observe the specified number of 567 concordant events for k or more genes, where k=0, 1, 2, ..., 5. 559 567 concordant events for k or more genes, where k=0, 1, 2, ..., 5. 568 Supplementary Information 569 Table S1. Numbers of concordantly evolving site pairs, inferred with correction for phylogenetic 570 uncertainty, under different significance thresholds. 571 572 Table S2. Numbers of discordantly evolving site pairs, inferred with correction for phylogenetic 573 uncertainty, under different significance thresholds. 574 575 Table S3. Coevolution of surface sites of COX1 and interactions with other proteins of the 576 respiratory complex IV. 577 578 Table S4. Coevolution of surface sites of COX2 and interactions with other proteins of the 579 respiratory complex IV. 580 581 Table S5. Coevolution of surface sites of COX3 and interactions with other proteins of the 582 respiratory complex IV. 583 584 Table S6. Coevolution of surface sites of CYTB and interactions with other proteins of the 585 respiratory complex III. 586 587 Table S7. Coevolution of surface sites of ATP6 and interactions with other proteins of the 588 respiratory complex V. 589 590 Table S8. Substitutions rates in groups of coevolving sites have changed during evolution of 591 Metazoa and Fungi. 592 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). 605 4. Bazykin GA. Changing preferences: deformation of single position amino acid fitness 606 landscapes and evolution of proteins. Biology Letters. 2015;11: 20150315. 607 doi:10.1098/rsbl.2015.0315 608 5. Storz JF. Compensatory mutations and epistasis for protein function. Current Opinion in 609 Structural Biology. 2018;50: 18–25. doi:10.1016/j.sbi.2017.10.009 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 616 8. Kaján L, Hopf TA, Kalaš M, Marks DS, Rost B. FreeContact: fast and free software for 617 protein contact prediction from residue co-evolution. BMC Bioinformatics. 2014;15: 85. 618 doi:10.1186/1471-2105-15-85 619 9. Hopf TA, Ingraham JB, Poelwijk FJ. Quantification of the effect of mutations using a 620 global probability model of natural sequence variation. arXiv. 2015;arXiv:1510.04612. 621 Available: http://arxiv.org/ftp/arxiv/papers/1510/1510.04612.pdf 622 10. Flynn WF, Haldane A, Torbett BE, Levy RM. Inference of Epistatic Effects Leading to 623 Entrenchment and Drug Resistance in HIV-1 Protease. Molecular Biology and Evolution. 624 2017;34: 1291–1306. doi:10.1093/molbev/msx095 625 11. Barton JP, Kardar M, Chakraborty AK. Scaling laws describe memories of host–pathogen 626 riposte in the HIV population. Proceedings of the National Academy of Sciences. 627 2015;112: 1965–1970. doi:10.1073/pnas.1415386112 628 12. Barton JP, Goonetilleke N, Butler TC, Walker BD, McMichael AJ, Chakraborty AK. 629 Relative rate and location of intra-host HIV evolution to evade cellular immunity are 630 predictable. Nature Communications. 2016;7: 11660. doi:10.1038/ncomms11660 631 13. Hopf TA, Ingraham JB, Poelwijk FJ, Schärfe CPI, Springer M, Sander C, et al. Mutation 632 effects predicted from sequence co-variation. Nat Biotechnol. 2017;35: 128–135. 633 doi:10.1038/nbt.3769 634 14. Granata D, Ponzoni L, Micheletti C, Carnevale V. Patterns of coevolving amino acids 635 unveil structural and dynamical domains. Proceedings of the National Academy of 636 Sciences. 2017;114: E10612–E10621. doi:10.1073/pnas.1712021114 637 15. Neuwald AF. Protein domain hierarchy Gibbs sampling strategies. Statistical Applications 616 8. Kaján L, Hopf TA, Kalaš M, Marks DS, Rost B. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). FreeContact: fast and free software for 617 protein contact prediction from residue co-evolution. BMC Bioinformatics. 2014;15: 85. 618 doi:10.1186/1471-2105-15-85 619 9. Hopf TA, Ingraham JB, Poelwijk FJ. Quantification of the effect of mutations using a 620 global probability model of natural sequence variation. arXiv. 2015;arXiv:1510.04612. 621 Available: http://arxiv.org/ftp/arxiv/papers/1510/1510.04612.pdf 622 10. Flynn WF, Haldane A, Torbett BE, Levy RM. Inference of Epistatic Effects Leading to 623 Entrenchment and Drug Resistance in HIV-1 Protease. Molecular Biology and Evolution. 624 2017;34: 1291–1306. doi:10.1093/molbev/msx095 622 10. Flynn WF, Haldane A, Torbett BE, Levy RM. Inference of Epistatic Effects Leading to 623 Entrenchment and Drug Resistance in HIV-1 Protease. Molecular Biology and Evolution. 624 2017;34: 1291–1306. doi:10.1093/molbev/msx095 625 11. Barton JP, Kardar M, Chakraborty AK. Scaling laws describe memories of host–pathogen 626 riposte in the HIV population. Proceedings of the National Academy of Sciences. 627 2015;112: 1965–1970. doi:10.1073/pnas.1415386112 628 12. Barton JP, Goonetilleke N, Butler TC, Walker BD, McMichael AJ, Chakraborty AK. 629 Relative rate and location of intra-host HIV evolution to evade cellular immunity are 630 predictable. Nature Communications. 2016;7: 11660. doi:10.1038/ncomms11660 634 14. Granata D, Ponzoni L, Micheletti C, Carnevale V. Patterns of coevolving amino acids 635 unveil structural and dynamical domains. Proceedings of the National Academy of 636 Sciences. 2017;114: E10612–E10621. doi:10.1073/pnas.1712021114 637 15. Neuwald AF. Protein domain hierarchy Gibbs sampling strategies. Statistical Applications 638 in Genetics and Molecular Biology. 2014;13. doi:10.1515/sagmb-2014-0008 637 15. Neuwald AF. Protein domain hierarchy Gibbs sampling strategies. Statistical Applications 638 in Genetics and Molecular Biology. 2014;13. doi:10.1515/sagmb-2014-0008 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 639 16. Neuwald AF, Aravind L, Altschul SF. Inferring joint sequence-structural determinants of 640 protein functional specificity. eLife. 2018;7. doi:10.7554/eLife.29880 641 17. Neuwald AF, Altschul SF. Statistical investigations of protein residue direct couplings. 642 Punta M, editor. PLOS Computational Biology. 2018;14: e1006237. 643 doi:10.1371/journal.pcbi.1006237 644 18. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). Castoe TA, de Koning APJ, Kim H-M, Gu W, Noonan BP, Naylor G, et al. Evidence for an 668 ancient adaptive episode of convergent molecular evolution. Proceedings of the National 669 Academy of Sciences. 2009;106: 8986–8991. doi:10.1073/pnas.0900233106 670 28. Wolters JF, Charron G, Gaspary A, Landry CR, Fiumera AC, Fiumera HL. Mitochondrial 671 Recombination Reveals Mito-Mito Epistasis in Yeast. Genetics. 2018;209: 307–319. 672 doi:10.1534/genetics.117.300660 673 29. Aledo JC, Valverde H, Ruíz-Camacho M, Morilla I, López FD. Protein–Protein Interfaces 674 from Cytochrome c Oxidase I Evolve Faster than Nonbinding Surfaces, yet Negative 675 Selection Is the Driving Force. Genome Biology and Evolution. 2014;6: 3064–3076. 676 doi:10.1093/gbe/evu240 677 30. Kondrashov AS, Sunyaev S, Kondrashov FA. Dobzhansky-Muller incompatibilities in 678 protein evolution. Proc Natl Acad Sci USA. 2002;99: 14878–14883. 679 doi:10.1073/pnas.232565499 680 31. Azevedo L, Carneiro J, van Asch B, Moleirinho A, Pereira F, Amorim A. Epistatic 681 interactions modulate the evolution of mammalian mitochondrial respiratory complex 682 components. BMC Genomics. 2009;10: 266. doi:10.1186/1471-2164-10-266 . CC-BY 4.0 International license made available under a 661 25. Lartillot N, Philippe H. A Bayesian Mixture Model for Across-Site Heterogeneities in the 662 Amino-Acid Replacement Process. Molecular Biology and Evolution. 2004;21: 1095–1109. 663 doi:10.1093/molbev/msh112 664 26. Nabholz B, Glemin S, Galtier N. Strong Variations of Mitochondrial Mutation Rate across 665 Mammals--the Longevity Hypothesis. Molecular Biology and Evolution. 2007;25: 120– 666 130. doi:10.1093/molbev/msm248 667 27. Castoe TA, de Koning APJ, Kim H-M, Gu W, Noonan BP, Naylor G, et al. Evidence for an 668 ancient adaptive episode of convergent molecular evolution. Proceedings of the National 669 Academy of Sciences. 2009;106: 8986–8991. doi:10.1073/pnas.0900233106 667 27. Castoe TA, de Koning APJ, Kim H-M, Gu W, Noonan BP, Naylor G, et al. Evidence for an 668 ancient adaptive episode of convergent molecular evolution. Proceedings of the National 669 Academy of Sciences. 2009;106: 8986–8991. doi:10.1073/pnas.0900233106 670 28. Wolters JF, Charron G, Gaspary A, Landry CR, Fiumera AC, Fiumera HL. Mitochondrial 671 Recombination Reveals Mito-Mito Epistasis in Yeast. Genetics. 2018;209: 307–319. 672 doi:10.1534/genetics.117.300660 673 29. Aledo JC, Valverde H, Ruíz-Camacho M, Morilla I, López FD. Protein–Protein Interfaces 674 from Cytochrome c Oxidase I Evolve Faster than Nonbinding Surfaces, yet Negative 675 Selection Is the Driving Force. Genome Biology and Evolution. 2014;6: 3064–3076. 676 doi:10.1093/gbe/evu240 677 30. Kondrashov AS, Sunyaev S, Kondrashov FA. Dobzhansky-Muller incompatibilities in 678 protein evolution. Proc Natl Acad Sci USA. 2002;99: 14878–14883. 680 31. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). Gouy R, Baurain D, Philippe H. Rooting the tree of life: the phylogenetic jury is still out. 645 Philos Trans R Soc Lond, B, Biol Sci. 2015;370: 20140329. doi:10.1098/rstb.2014.0329 644 18. Gouy R, Baurain D, Philippe H. Rooting the tree of life: the phylogenetic jury is still out. 645 Philos Trans R Soc Lond, B, Biol Sci. 2015;370: 20140329. doi:10.1098/rstb.2014.0329 646 19. Blanquart S, Lartillot N. A site- and time-heterogeneous model of amino acid replacement. 647 Mol Biol Evol. 2008;25: 842–858. doi:10.1093/molbev/msn018 646 19. Blanquart S, Lartillot N. A site- and time-heterogeneous model of amino acid replacement. 647 Mol Biol Evol. 2008;25: 842–858. doi:10.1093/molbev/msn018 648 20. Montooth KL, Rand DM. The Spectrum of Mitochondrial Mutation Differs across Species. 649 PLoS Biology. 2008;6: e213. doi:10.1371/journal.pbio.0060213 648 20. Montooth KL, Rand DM. The Spectrum of Mitochondrial Mutation Differs across Species. 649 PLoS Biology. 2008;6: e213. doi:10.1371/journal.pbio.0060213 650 21. Popadin K, Polishchuk LV, Mamirova L, Knorre D, Gunbin K. Accumulation of slightly 651 deleterious mutations in mitochondrial protein-coding genes of large versus small 652 mammals. Proc Natl Acad Sci USA. 2007;104: 13390–13395. 654 22. Klink GV, Bazykin GA. Parallel Evolution of Metazoan Mitochondrial Proteins. Genome 655 Biol Evol. 2017;9: 1341–1350. doi:10.1093/gbe/evx025 656 23. Uzzell T, Corbin KW. Fitting Discrete Probability Distributions to Evolutionary Events. 657 Science. 1971;172: 1089–1096. doi:10.1126/science.172.3988.1089 658 24. Kosakovsky Pond SL, Frost SDW. A Simple Hierarchical Approach to Modeling 659 Distributions of Substitution Rates. Molecular Biology and Evolution. 2005;22: 223–234. 660 doi:10.1093/molbev/msi009 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 661 25. Lartillot N, Philippe H. A Bayesian Mixture Model for Across-Site Heterogeneities in the 662 Amino-Acid Replacement Process. Molecular Biology and Evolution. 2004;21: 1095–1109 663 doi:10.1093/molbev/msh112 664 26. Nabholz B, Glemin S, Galtier N. Strong Variations of Mitochondrial Mutation Rate across 665 Mammals--the Longevity Hypothesis. Molecular Biology and Evolution. 2007;25: 120– 666 130. doi:10.1093/molbev/msm248 667 27. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). Azevedo L, Carneiro J, van Asch B, Moleirinho A, Pereira F, Amorim A. Epistatic 681 interactions modulate the evolution of mammalian mitochondrial respiratory complex 682 components. BMC Genomics. 2009;10: 266. doi:10.1186/1471-2164-10-266 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 683 32. Wang ZO, Pollock DD. Coevolutionary patterns in cytochrome c oxidase subunit I depend 684 on structural and functional context. J Mol Evol. 2007;65: 485–495. doi:10.1007/s00239- 685 007-9018-8 686 33. Osada N, Akashi H. Mitochondrial–Nuclear Interactions and Accelerated Compensatory 687 Evolution: Evidence from the Primate Cytochrome c Oxidase Complex. Molecular Biology 688 and Evolution. 2012;29: 337–346. doi:10.1093/molbev/msr211 689 34. Havird JC, Whitehill NS, Snow CD, Sloan DB. Conservative and compensatory evolution 690 in oxidative phosphorylation complexes of angiosperms with highly divergent rates of 691 mitochondrial genome evolution: MITONUCLEAR COEVOLUTION IN SILENE 692 OXPHOS COMPLEXES. Evolution. 2015;69: 3069–3081. doi:10.1111/evo.12808 693 35. Sunnucks P, Morales HE, Lamb AM, Pavlova A, Greening C. Integrative Approaches for 694 Studying Mitochondrial and Nuclear Genome Co-evolution in Oxidative Phosphorylation. 695 Frontiers in Genetics. 2017;8. doi:10.3389/fgene.2017.00025 696 36. Kryazhimskiy S, Dushoff J, Bazykin GA, Plotkin JB. Prevalence of epistasis in the 697 evolution of influenza A surface proteins. PLoS Genet. 2011;7: e1001301. 698 doi:10.1371/journal.pgen.1001301 699 37. Neverov AD, Kryazhimskiy S, Plotkin JB, Bazykin GA. Coordinated Evolution of 700 Influenza A Surface Proteins. Malik HS, editor. PLOS Genetics. 2015;11: e1005404. 701 doi:10.1371/journal.pgen.1005404 702 38. Traag VA, Bruggeman J. Community detection in networks with positive and negative 703 links. Physical Review E. 2009;80. doi:10.1103/PhysRevE.80.036115 683 32. Wang ZO, Pollock DD. Coevolutionary patterns in cytochrome c oxidase subunit I depend 684 on structural and functional context. J Mol Evol. 2007;65: 485–495. doi:10.1007/s00239- 685 007-9018-8 686 33. Osada N, Akashi H. Mitochondrial–Nuclear Interactions and Accelerated Compensatory 687 Evolution: Evidence from the Primate Cytochrome c Oxidase Complex. Molecular Biology 688 and Evolution. 2012;29: 337–346. doi:10.1093/molbev/msr211 689 34. Havird JC, Whitehill NS, Snow CD, Sloan DB. Conservative and compensatory evolution 690 in oxidative phosphorylation complexes of angiosperms with highly divergent rates of 691 mitochondrial genome evolution: MITONUCLEAR COEVOLUTION IN SILENE 692 OXPHOS COMPLEXES. Evolution. 2015;69: 3069–3081. doi:10.1111/evo.12808 689 34. Havird JC, Whitehill NS, Snow CD, Sloan DB. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). Conservative and compensatory evolution 690 in oxidative phosphorylation complexes of angiosperms with highly divergent rates of 691 mitochondrial genome evolution: MITONUCLEAR COEVOLUTION IN SILENE 692 OXPHOS COMPLEXES. Evolution. 2015;69: 3069–3081. doi:10.1111/evo.12808 693 35. Sunnucks P, Morales HE, Lamb AM, Pavlova A, Greening C. Integrative Approaches for 694 Studying Mitochondrial and Nuclear Genome Co-evolution in Oxidative Phosphorylation. 695 Frontiers in Genetics. 2017;8. doi:10.3389/fgene.2017.00025 696 36. Kryazhimskiy S, Dushoff J, Bazykin GA, Plotkin JB. Prevalence of epistasis in the 697 evolution of influenza A surface proteins. PLoS Genet. 2011;7: e1001301. 699 37. Neverov AD, Kryazhimskiy S, Plotkin JB, Bazykin GA. Coordinated Evolution of 700 Influenza A Surface Proteins. Malik HS, editor. PLOS Genetics. 2015;11: e1005404. 701 doi:10.1371/journal.pgen.1005404 702 38. Traag VA, Bruggeman J. Community detection in networks with positive and negative 703 links. Physical Review E. 2009;80. doi:10.1103/PhysRevE.80.036115 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 704 39. Allegretti M, Klusch N, Mills DJ, Vonck J, Kühlbrandt W, Davies KM. Horizontal 705 membrane-intrinsic α-helices in the stator a-subunit of an F-type ATP synthase. Nature. 706 2015;521: 237–240. doi:10.1038/nature14185 707 40. Mitome N, Ono S, Sato H, Suzuki T, Sone N, Yoshida M. Essential arginine residue of the 708 Fo-a subunit in FoF1-ATP synthase has a role to prevent the proton shortcut without c-ring 709 rotation in the Fo proton channel. Biochemical Journal. 2010;430: 171–177. 710 doi:10.1042/BJ20100621 711 41. Bazykin GA, Dushoff J, Levin SA, Kondrashov AS. Bursts of nonsynonymous 712 substitutions in HIV-1 evolution reveal instances of positive selection at conservative 713 protein sites. Proceedings of the National Academy of Sciences. 2006;103: 19396–19401. 714 doi:10.1073/pnas.0609484103 715 42. Callahan B, Neher RA, Bachtrog D, Andolfatto P, Shraiman BI. Correlated Evolution of 716 Nearby Residues in Drosophilid Proteins. McVean G, editor. PLoS Genetics. 2011;7: 717 e1001315. doi:10.1371/journal.pgen.1001315 718 43. Levy RM, Haldane A, Flynn WF. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). Potts Hamiltonian models of protein co-variation, free 719 energy landscapes, and evolutionary fitness. Current Opinion in Structural Biology. 720 2017;43: 55–62. doi:10.1016/j.sbi.2016.11.004 721 44. Wang S-W, Bitbol A-F, Wingreen NS. Revealing evolutionary constraints on proteins 722 through sequence analysis. Morcos F, editor. PLOS Computational Biology. 2019;15: 723 e1007010. doi:10.1371/journal.pcbi.1007010 724 45. Kondrashov FA, Kondrashov AS. Multidimensional epistasis and the disadvantage of sex. 725 Proc Natl Acad Sci USA. 2001;98: 12089–12092. doi:10.1073/pnas.211214298 . CC-BY 4.0 International license made available under a 704 39. Allegretti M, Klusch N, Mills DJ, Vonck J, Kühlbrandt W, Davies KM. Horizontal 705 membrane-intrinsic α-helices in the stator a-subunit of an F-type ATP synthase. Nature. 706 2015;521: 237–240. doi:10.1038/nature14185 707 40. Mitome N, Ono S, Sato H, Suzuki T, Sone N, Yoshida M. Essential arginine residue of the 708 Fo-a subunit in FoF1-ATP synthase has a role to prevent the proton shortcut without c-ring 709 rotation in the Fo proton channel. Biochemical Journal. 2010;430: 171–177. 707 40. Mitome N, Ono S, Sato H, Suzuki T, Sone N, Yoshida M. Essential arginine residue of the 708 Fo-a subunit in FoF1-ATP synthase has a role to prevent the proton shortcut without c-ring 709 rotation in the Fo proton channel. Biochemical Journal. 2010;430: 171–177. 715 42. Callahan B, Neher RA, Bachtrog D, Andolfatto P, Shraiman BI. Correlated Evolution of 716 Nearby Residues in Drosophilid Proteins. McVean G, editor. PLoS Genetics. 2011;7: 717 e1001315. doi:10.1371/journal.pgen.1001315 715 42. Callahan B, Neher RA, Bachtrog D, Andolfatto P, Shraiman BI. Correlated Evolution of 716 Nearby Residues in Drosophilid Proteins. McVean G, editor. PLoS Genetics. 2011;7: 717 e1001315. doi:10.1371/journal.pgen.1001315 718 43. Levy RM, Haldane A, Flynn WF. Potts Hamiltonian models of protein co-variation, free 719 energy landscapes, and evolutionary fitness. Current Opinion in Structural Biology. 720 2017;43: 55–62. doi:10.1016/j.sbi.2016.11.004 721 44. Wang S-W, Bitbol A-F, Wingreen NS. Revealing evolutionary constraints on proteins 722 through sequence analysis. Morcos F, editor. PLOS Computational Biology. 2019;15: 723 e1007010. doi:10.1371/journal.pcbi.1007010 724 45. Kondrashov FA, Kondrashov AS. Multidimensional epistasis and the disadvantage of sex. 725 Proc Natl Acad Sci USA. 2001;98: 12089–12092. doi:10.1073/pnas.211214298 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 726 46. Otwinowski J, McCandlish DM, Plotkin JB. Inferring the shape of global epistasis. 727 Proceedings of the National Academy of Sciences. 2018;115: E7550–E7558. 728 doi:10.1073/pnas.1804015115 729 47. Hill GE. Mitonuclear coevolution as the genesis of speciation and the mitochondrial DNA 730 barcode gap. Ecology and Evolution. 2016;6: 5831–5842. doi:10.1002/ece3.2338 731 48. da Fonseca RR, Johnson WE, O’Brien SJ, Ramos M, Antunes A. The adaptive evolution of 732 the mammalian mitochondrial genome. BMC Genomics. 2008;9: 119. doi:10.1186/1471- 733 2164-9-119 734 49. Gershoni M, Templeton AR, Mishmar D. Mitochondrial bioenergetics as a major motive 735 force of speciation. Bioessays. 2009;31: 642–650. doi:10.1002/bies.200800139 736 50. Lane N. Biodiversity: On the origin of bar codes. Nature. 2009;462: 272–274. 737 doi:10.1038/462272a 738 51. Barreto FS, Watson ET, Lima TG, Willett CS, Edmands S, Li W, et al. Genomic signatures 739 of mitonuclear coevolution across populations of Tigriopus californicus. Nature Ecology & 740 Evolution. 2018;2: 1250–1257. doi:10.1038/s41559-018-0588-1 741 52. Yan Z, Ye G, Werren JH. Evolutionary Rate Correlation between Mitochondrial-Encoded 742 and Mitochondria-Associated Nuclear-Encoded Proteins in Insects. Tamura K, editor. 743 Molecular Biology and Evolution. 2019;36: 1022–1036. doi:10.1093/molbev/msz036 744 53. Edwards SV. Natural selection and phylogenetic analysis. Proceedings of the National 745 Academy of Sciences. 2009;106: 8799–8800. doi:10.1073/pnas.0904103106 726 46. Otwinowski J, McCandlish DM, Plotkin JB. Inferring the shape of global epistasis. 727 Proceedings of the National Academy of Sciences. 2018;115: E7550–E7558. 728 doi:10.1073/pnas.1804015115 729 47. Hill GE. Mitonuclear coevolution as the genesis of speciation and the mitochondrial DNA 730 barcode gap. Ecology and Evolution. 2016;6: 5831–5842. doi:10.1002/ece3.2338 731 48. da Fonseca RR, Johnson WE, O’Brien SJ, Ramos M, Antunes A. The adaptive evolution of 732 the mammalian mitochondrial genome. BMC Genomics. 2008;9: 119. doi:10.1186/1471- 733 2164-9-119 731 48. da Fonseca RR, Johnson WE, O’Brien SJ, Ramos M, Antunes A. The adaptive evolution of 732 the mammalian mitochondrial genome. BMC Genomics. 2008;9: 119. doi:10.1186/1471- 733 2164-9-119 734 49. Gershoni M, Templeton AR, Mishmar D. Mitochondrial bioenergetics as a major motive 735 force of speciation. Bioessays. 2009;31: 642–650. doi:10.1002/bies.200800139 736 50. Lane N. Biodiversity: On the origin of bar codes. Nature. 2009;462: 272–274. 738 51. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). Barreto FS, Watson ET, Lima TG, Willett CS, Edmands S, Li W, et al. Genomic signatures 739 of mitonuclear coevolution across populations of Tigriopus californicus. Nature Ecology & 740 Evolution. 2018;2: 1250–1257. doi:10.1038/s41559-018-0588-1 738 51. Barreto FS, Watson ET, Lima TG, Willett CS, Edmands S, Li W, et al. Genomic signatures 739 of mitonuclear coevolution across populations of Tigriopus californicus. Nature Ecology & 740 Evolution. 2018;2: 1250–1257. doi:10.1038/s41559-018-0588-1 741 52. Yan Z, Ye G, Werren JH. Evolutionary Rate Correlation between Mitochondrial-Encoded 742 and Mitochondria-Associated Nuclear-Encoded Proteins in Insects. Tamura K, editor. 743 Molecular Biology and Evolution. 2019;36: 1022–1036. doi:10.1093/molbev/msz036 744 53. Edwards SV. Natural selection and phylogenetic analysis. Proceedings of the National 745 Academy of Sciences. 2009;106: 8799–8800. doi:10.1073/pnas.0904103106 744 53. Edwards SV. Natural selection and phylogenetic analysis. Proceedings of the National 745 Academy of Sciences. 2009;106: 8799–8800. doi:10.1073/pnas.0904103106 746 54. Sohail M, Vakhrusheva OA, Sul JH, Pulit SL, Francioli LC, Genome of the Netherlands 747 Consortium, et al. Negative selection in humans and fruit flies involves synergistic 748 epistasis. Science. 2017;356: 539–542. doi:10.1126/science.aah5238 746 54. Sohail M, Vakhrusheva OA, Sul JH, Pulit SL, Francioli LC, Genome of the Netherlands 747 Consortium, et al. Negative selection in humans and fruit flies involves synergistic 748 epistasis. Science. 2017;356: 539–542. doi:10.1126/science.aah5238 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 749 55. Kondrashov AS. Deleterious mutations and the evolution of sexual reproduction. Nature. 750 1988;336: 435–440. doi:10.1038/336435a0 751 56. Salverda MLM, Dellus E, Gorter FA, Debets AJM, van der Oost J, Hoekstra RF, et al. 752 Initial Mutations Direct Alternative Pathways of Protein Evolution. Zhang J, editor. PLoS 753 Genet. 2011;7: e1001321. doi:10.1371/journal.pgen.1001321 754 57. Szendro IG, Schenk MF, Franke J, Krug J, de Visser JAGM. Quantitative analyses of 755 empirical fitness landscapes. J Stat Mech. 2013;2013: P01005. doi:10.1088/1742- 756 5468/2013/01/P01005 757 58. de Visser JAGM, Krug J. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 771 63. Katoh K, Toh H. Recent developments in the MAFFT multiple sequence alignment 772 program. Briefings in Bioinformatics. 2008;9: 286–298. doi:10.1093/bib/bbn013 772 program. Briefings in Bioinformatics. 2008;9: 286–298. doi:10.1093/bib/bbn013 773 64. Stamatakis A, Hoover P, Rougemont J. A rapid bootstrap algorithm for the RAxML Web 774 servers. Syst Biol. 2008;57: 758–771. doi:10.1080/10635150802429642 775 65. Tsukihara T, Aoyama H, Yamashita E, Tomizaki T, Yamaguchi H, Shinzawa-Itoh K, et al. 776 The whole structure of the 13-subunit oxidized cytochrome c oxidase at 2.8 A. Science. 777 1996;272: 1136–1144. doi:10.1126/science.272.5265.1136 778 66. Iwata S, Lee JW, Okada K, Lee JK, Iwata M, Rasmussen B, et al. Complete structure of the 779 11-subunit bovine mitochondrial cytochrome bc1 complex. Science. 1998;281: 64–71. 780 doi:10.1126/science.281.5373.64 781 67. Zhou A, Rohou A, Schep DG, Bason JV, Montgomery MG, Walker JE, et al. Structure and 782 conformational states of the bovine mitochondrial ATP synthase by cryo-EM. Elife. 783 2015;4: e10180. doi:10.7554/eLife.10180 784 68. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. 785 J Mol Biol. 1990;215: 403–410. doi:10.1016/S0022-2836(05)80360-2 786 69. Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, et al. Gapped BLAST 787 and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 788 1997;25: 3389–3402. 789 70. Vos RA, Caravas J, Hartmann K, Jensen MA, Miller C. BIO::Phylo-phyloinformatic 790 analysis using perl. BMC Bioinformatics. 2011;12: 63. doi:10.1186/1471-2105-12-63 791 71. Iorio F, Bernardo-Faura M, Gobbi A, Cokelaer T, Jurman G, Saez-Rodriguez J. Efficient 792 randomization of biological networks while preserving functional characterization of 773 64. Stamatakis A, Hoover P, Rougemont J. A rapid bootstrap algorithm for the RAxML Web 774 servers. Syst Biol. 2008;57: 758–771. doi:10.1080/10635150802429642 775 65. Tsukihara T, Aoyama H, Yamashita E, Tomizaki T, Yamaguchi H, Shinzawa-Itoh K, et al. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). Empirical fitness landscapes and the predictability of evolution. 758 Nat Rev Genet. 2014;15: 480–490. doi:10.1038/nrg3744 759 59. Palmer AC, Kishony R. Understanding, predicting and manipulating the genotypic 760 evolution of antibiotic resistance. Nat Rev Genet. 2013;14: 243–248. doi:10.1038/nrg3351 761 60. Olson CA, Wu NC, Sun R. A Comprehensive Biophysical Description of Pairwise Epistasis 762 throughout an Entire Protein Domain. Current Biology. 2014;24: 2643–2651. 763 doi:10.1016/j.cub.2014.09.072 764 61. Shapiro B, Rambaut A, Pybus OG, Holmes EC. A phylogenetic method for detecting 765 positive epistasis in gene sequences and its application to RNA virus evolution. Mol Biol 766 Evol. 2006;23: 1724–1730. doi:10.1093/molbev/msl037 767 62. Akand EH, Downard KevinM. Identification of epistatic mutations and insights into the 768 evolution of the influenza virus using a mass-based protein phylogenetic approach. 769 Molecular Phylogenetics and Evolution 2018;121: 132–138 749 55. Kondrashov AS. Deleterious mutations and the evolution of sexual reproduction. Nature. 750 1988;336: 435–440. doi:10.1038/336435a0 751 56. Salverda MLM, Dellus E, Gorter FA, Debets AJM, van der Oost J, Hoekstra RF, et al. 752 Initial Mutations Direct Alternative Pathways of Protein Evolution. Zhang J, editor. PLoS 753 Genet. 2011;7: e1001321. doi:10.1371/journal.pgen.1001321 754 57. Szendro IG, Schenk MF, Franke J, Krug J, de Visser JAGM. Quantitative analyses of 755 empirical fitness landscapes. J Stat Mech. 2013;2013: P01005. doi:10.1088/1742- 756 5468/2013/01/P01005 757 58. de Visser JAGM, Krug J. Empirical fitness landscapes and the predictability of evolution. 758 Nat Rev Genet. 2014;15: 480–490. doi:10.1038/nrg3744 759 59. Palmer AC, Kishony R. Understanding, predicting and manipulating the genotypic 760 evolution of antibiotic resistance. Nat Rev Genet. 2013;14: 243–248. doi:10.1038/nrg3351 761 60. Olson CA, Wu NC, Sun R. A Comprehensive Biophysical Description of Pairwise Epistasis 762 throughout an Entire Protein Domain. Current Biology. 2014;24: 2643–2651. 764 61. Shapiro B, Rambaut A, Pybus OG, Holmes EC. A phylogenetic method for detecting 765 positive epistasis in gene sequences and its application to RNA virus evolution. Mol Biol 766 Evol. 2006;23: 1724–1730. doi:10.1093/molbev/msl037 767 62. Akand EH, Downard KevinM. Identification of epistatic mutations and insights into the 768 evolution of the influenza virus using a mass-based protein phylogenetic approach. 767 62. Akand EH, Downard KevinM. Identification of epistatic mutations and insights into the 768 evolution of the influenza virus using a mass-based protein phylogenetic approach. 769 Molecular Phylogenetics and Evolution. 2018;121: 132–138. 770 doi:10.1016/j.ympev.2018.01.009 . 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). 776 The whole structure of the 13-subunit oxidized cytochrome c oxidase at 2.8 A. Science. 777 1996;272: 1136–1144. doi:10.1126/science.272.5265.1136 778 66. Iwata S, Lee JW, Okada K, Lee JK, Iwata M, Rasmussen B, et al. Complete structure of the 779 11-subunit bovine mitochondrial cytochrome bc1 complex. Science. 1998;281: 64–71. 780 doi:10.1126/science.281.5373.64 781 67. Zhou A, Rohou A, Schep DG, Bason JV, Montgomery MG, Walker JE, et al. Structure and 782 conformational states of the bovine mitochondrial ATP synthase by cryo-EM. Elife. 783 2015;4: e10180. doi:10.7554/eLife.10180 , , p , , g y , , 782 conformational states of the bovine mitochondrial ATP synthase by cryo-EM. Elife. 783 2015;4: e10180. doi:10.7554/eLife.10180 784 68. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. 785 J Mol Biol. 1990;215: 403–410. doi:10.1016/S0022-2836(05)80360-2 786 69. Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, et al. Gapped BLAST 787 and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 788 1997;25: 3389–3402. 789 70. Vos RA, Caravas J, Hartmann K, Jensen MA, Miller C. BIO::Phylo-phyloinformatic 790 analysis using perl. BMC Bioinformatics. 2011;12: 63. doi:10.1186/1471-2105-12-63 791 71. Iorio F, Bernardo-Faura M, Gobbi A, Cokelaer T, Jurman G, Saez-Rodriguez J. Efficient 792 randomization of biological networks while preserving functional characterization of 793 individual nodes. BMC Bioinformatics. 2016;17. doi:10.1186/s12859-016-1402-1 789 70. Vos RA, Caravas J, Hartmann K, Jensen MA, Miller C. BIO::Phylo-phyloinformatic 790 analysis using perl. BMC Bioinformatics. 2011;12: 63. doi:10.1186/1471-2105-12-63 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 794 72. Tange O. GNU Parallel 20150322 ('Hellwig’). Zenodo; 2015. doi:10.5281/zenodo.16303 794 72. Tange O. GNU Parallel 20150322 ('Hellwig’). Zenodo; 2015. doi:10.5281/zenodo.16303 795 73. Genovese C, Wasserman L. A stochastic process approach to false discovery control. Ann 796 Statist. 2004;32: 1035–1061. doi:10.1214/009053604000000283 797 74. Benjamini Y. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). Simultaneous and selective inference: Current successes and future 798 challenges. Biom J. 2010;52: 708–721. doi:10.1002/bimj.200900299 799 75. Mendes FK, Hahn Y, Hahn MW. Gene Tree Discordance Can Generate Patterns of 800 Diminishing Convergence over Time. Mol Biol Evol. 2016;33: 3299–3307. 801 doi:10 1093/molbev/msw197 802 76. Burger L, van Nimwegen E. Disentangling direct from indirect co-evolution of residues in 803 protein alignments. PLoS Comput Biol. 2010;6: e1000633. 802 76. Burger L, van Nimwegen E. Disentangling direct from indirect co-evolution of residues in 803 protein alignments. PLoS Comput Biol. 2010;6: e1000633. 804 doi:10.1371/journal.pcbi.1000633 805 77. Stein RR, Marks DS, Sander C. Inferring Pairwise Interactions from Biological Data Using 806 Maximum-Entropy Probability Models. Chen S-J, editor. PLOS Computational Biology. 807 2015;11: e1004182. doi:10.1371/journal.pcbi.1004182 808 78. Schäfer J, Strimmer K. A shrinkage approach to large-scale covariance matrix estimation 809 and implications for functional genomics. Stat Appl Genet Mol Biol. 2005;4: Article32. 810 doi:10.2202/1544-6115.1175 811 79. Aledo JC, Valverde H, Ruíz-Camacho M. Thermodynamic Stability Explains the 812 Differential Evolutionary Dynamics of Cytochrome b and COX I in Mammals. Journal of 813 Molecular Evolution. 2012;74: 69–80. doi:10.1007/s00239-012-9489-0 814 80. Lu X, Bressan S. Sampling Connected Induced Subgraphs Uniformly at Random. In: 815 Ailamaki A, Bowers S, editors. Scientific and Statistical Database Management. Berlin, . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 816 Heidelberg: Springer Berlin Heidelberg; 2012. pp. 195–212. doi:10.1007/978-3-642-31235 817 9_13 818 819 Figures 820 Figure 1. Concordant evolution of protein sites. 821 An example of phylogenetic distribution of substitution densities for a positively coevolving site pair 822 (COX1 protein, sites 684 and 776, both belonging to group 2). For each internal node of the tree, we 823 calculate the number of substitutions in its subtree, and show the differences between the observed and 824 expected numbers of substitutions by colors of branches, with blue indicating a deficit, and red, an exces 825 of substitutions. The expected number of substitutions for a subtree at each site has been estimated as the 826 total subtree length (sum of its branch lengths) multiplied by the corresponding site- or group-specific 827 rate. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). The 838 expected number of substitutions for a subtree at each group (a) or site (b) has been estimated as the total 839 branch length multiplied by the corresponding group- or site-specific rate. (a) Groups 5 and 2 (b). In (b), 840 individual substitutions are shown with dots: open green dots mark leading substitutions (occurred fist), 841 closed green dots mark trailing substitutions (occurred second), closed sand dots mark substitutions in a 842 site co-occurred with substitutions in another site in the site pair (654,994) and closed gray dots are other 843 substitutions in each site. 820 Figure 1. Concordant evolution of protein sites. 821 An example of phylogenetic distribution of substitution densities for a positively coevolving site pair 822 (COX1 protein, sites 684 and 776, both belonging to group 2). For each internal node of the tree, we 823 calculate the number of substitutions in its subtree, and show the differences between the observed and 824 expected numbers of substitutions by colors of branches, with blue indicating a deficit, and red, an excess 825 of substitutions. The expected number of substitutions for a subtree at each site has been estimated as the 826 total subtree length (sum of its branch lengths) multiplied by the corresponding site- or group-specific 827 rate. Individual substitutions are shown with dots: open green dots mark leading substitutions (occurred 828 fist), closed green dots mark trailing substitutions (occurred second), closed sand dots are substitutions at 829 a site that co-occurred with substitutions in another site in the site pair (684,776), and closed gray dots are 830 other substitutions. 832 Figure 2. Discordant evolution of protein sites. 833 Examples of distribution of substitution densities for two groups of coevolving sites (a, groups 5 and 2 of 834 the COX1 protein) and for a pair of negatively coevolving sites belonging to these groups (b, site 654 of 835 group 5 and site 994 of group 2). For each internal node of the tree, we calculate the number of 836 substitutions in its subtree, and show the differences between the observed and expected numbers of 837 substitutions by colors of branches, with blue indicating a deficit, and red, an excess of substitutions. The 838 expected number of substitutions for a subtree at each group (a) or site (b) has been estimated as the total 839 branch length multiplied by the corresponding group- or site-specific rate. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). Individual substitutions are shown with dots: open green dots mark leading substitutions (occurred 828 fist), closed green dots mark trailing substitutions (occurred second), closed sand dots are substitutions at 829 a site that co-occurred with substitutions in another site in the site pair (684,776), and closed gray dots ar 830 other substitutions. 831 832 Figure 2. Discordant evolution of protein sites. 833 Examples of distribution of substitution densities for two groups of coevolving sites (a, groups 5 and 2 of 834 the COX1 protein) and for a pair of negatively coevolving sites belonging to these groups (b, site 654 of 816 Heidelberg: Springer Berlin Heidelberg; 2012. pp. 195–212. doi:10.1007/978-3-642-31235- eidelberg: Springer Berlin Heidelberg; 2012. pp. 195–212. doi:10.1007/978-3-642-31235 819 Figures 820 Figure 1. Concordant evolution of protein sites. 821 An example of phylogenetic distribution of substitution densities for a positively coevolving site pair 822 (COX1 protein, sites 684 and 776, both belonging to group 2). For each internal node of the tree, we 823 calculate the number of substitutions in its subtree, and show the differences between the observed and 824 expected numbers of substitutions by colors of branches, with blue indicating a deficit, and red, an excess 825 of substitutions. The expected number of substitutions for a subtree at each site has been estimated as the 826 total subtree length (sum of its branch lengths) multiplied by the corresponding site- or group-specific 827 rate. Individual substitutions are shown with dots: open green dots mark leading substitutions (occurred 828 fist), closed green dots mark trailing substitutions (occurred second), closed sand dots are substitutions at 829 a site that co-occurred with substitutions in another site in the site pair (684,776), and closed gray dots are 830 other substitutions. 831 832 Figure 2. Discordant evolution of protein sites. 833 Examples of distribution of substitution densities for two groups of coevolving sites (a, groups 5 and 2 of 834 the COX1 protein) and for a pair of negatively coevolving sites belonging to these groups (b, site 654 of 835 group 5 and site 994 of group 2). For each internal node of the tree, we calculate the number of 836 substitutions in its subtree, and show the differences between the observed and expected numbers of 837 substitutions by colors of branches, with blue indicating a deficit, and red, an excess of substitutions. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). (a) Groups 5 and 2 (b). In (b), 840 individual substitutions are shown with dots: open green dots mark leading substitutions (occurred fist), 841 closed green dots mark trailing substitutions (occurred second), closed sand dots mark substitutions in a 842 site co-occurred with substitutions in another site in the site pair (654,994) and closed gray dots are other 843 substitutions in each site. 844 845 Figure 3. Schematic representation of coevolution and contact graphs for COX1 (a-c), COX2 (d-f), COX3 846 (g-i), ATP6 (j-l) and CYTB (m-o) proteins. 847 Left column (a, d, g, j and m), contact graphs; middle column (b, e, h, k and n), positive edges in 848 coevolution graphs; right column (c, f, i, l and o), negative edges in coevolution graphs. Each group of 849 coevolving sites is represented by a circle. Links connecting circles represent between-group edges, and 850 links connecting a circle to itself represent within-group edges. The color represent the number of edges 851 (left column) or sum of the weights of edges of the corresponding type (center and left columns) 852 normalized by their expected values obtained from random model used by the vertex clustering 853 algorithm[38]. For contact graphs, groups of coevolving sites are enriched in contacts on the protein 854 structure: the normalized number of edges connecting sites within a group is greater than that between 855 groups. For coevolution graphs, the groups of coevolving sites have larger normalized total weights of 856 positive edges within groups than between groups; by contrast, negative edges tend to have greater 857 normalized total weights between groups. 858 859 Figure 4. Groups of coevolving sites and interactions between subunits of COX. 860 For each mitochondrial-encoded COX protein: COX1 (a-b), COX2 (c-d) and COX3 (e-f), the groups of 861 coevolving sites are color-coded. (a, c, e) protein structure of COX. Residues at sites involved in 862 interactions with other COX proteins are shown as spheres; residues at sites on protein surfaces not 863 involved in interprotein interactions, as ribbons; the remaining sites of COX were colored in gray. (b, d, f) 864 the numbers of sites which are in contact and numbers of sites which are not in contact with other COX 865 proteins in the protein structure, compared to the expected values. Significant differences are marked with 866 asterisks (, p<0.025; , p<0.005; , p<0.0005). 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). For COX1 (a-b), interactions with nuclearly encoded 867 COX proteins are considered; for COX2 and COX3 (c-f), interactions with other mitochondrial-encoded 868 COX proteins are considered. 869 870 Figure 5. Groups of coevolving sites and function of ATP synthase. . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 844 845 Figure 3. Schematic representation of coevolution and contact graphs for COX1 (a-c), COX2 (d-f), COX3 846 (g-i), ATP6 (j-l) and CYTB (m-o) proteins. 847 Left column (a, d, g, j and m), contact graphs; middle column (b, e, h, k and n), positive edges in 848 coevolution graphs; right column (c, f, i, l and o), negative edges in coevolution graphs. Each group of 849 coevolving sites is represented by a circle. Links connecting circles represent between-group edges, and 850 links connecting a circle to itself represent within-group edges. The color represent the number of edges 851 (left column) or sum of the weights of edges of the corresponding type (center and left columns) 852 normalized by their expected values obtained from random model used by the vertex clustering 853 algorithm[38]. For contact graphs, groups of coevolving sites are enriched in contacts on the protein 854 structure: the normalized number of edges connecting sites within a group is greater than that between 855 groups. For coevolution graphs, the groups of coevolving sites have larger normalized total weights of 856 positive edges within groups than between groups; by contrast, negative edges tend to have greater 857 normalized total weights between groups. 845 Figure 3. 873 face the rotor part of the ATP synthase and may contribute to proton transport across the membrane. 874 Yellow, Arg159 which also belongs to group 3. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). Schematic representation of coevolution and contact graphs for COX1 (a-c), COX2 (d-f), COX3 846 (g-i), ATP6 (j-l) and CYTB (m-o) proteins. 845 Figure 3. Schematic representation of coevolution and contact graphs for COX1 (a-c), COX2 (d-f), COX3 846 (g-i), ATP6 (j-l) and CYTB (m-o) proteins. 859 Figure 4. Groups of coevolving sites and interactions between subunits of COX. 859 Figure 4. Groups of coevolving sites and interactions between subunits of COX. 860 For each mitochondrial-encoded COX protein: COX1 (a-b), COX2 (c-d) and COX3 (e-f), the groups of 861 coevolving sites are color-coded. (a, c, e) protein structure of COX. Residues at sites involved in 862 interactions with other COX proteins are shown as spheres; residues at sites on protein surfaces not 863 involved in interprotein interactions, as ribbons; the remaining sites of COX were colored in gray. (b, d, f) 864 the numbers of sites which are in contact and numbers of sites which are not in contact with other COX 865 proteins in the protein structure, compared to the expected values. Significant differences are marked with 866 asterisks (, p<0.025; , p<0.005; *, p<0.0005). For COX1 (a-b), interactions with nuclearly encoded 867 COX proteins are considered; for COX2 and COX3 (c-f), interactions with other mitochondrial-encoded 868 COX proteins are considered. 870 Figure 5. Groups of coevolving sites and function of ATP synthase. 870 Figure 5. Groups of coevolving sites and function of ATP synthase. 870 Figure 5. Groups of coevolving sites and function of ATP synthase. 871 For the mitochondrial-encoded ATP6 protein, the groups of coevolving sites are color-coded. Residues at 872 sites of group 3 are shown as spheres; residues at other sites, as ribbons. Most residues at group 3 sites . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. 874 Yellow, Arg159 which also belongs to group 3. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 873 face the rotor part of the ATP synthase and may contribute to proton transport across the membrane. 874 Yellow, Arg159 which also belongs to group 3. 873 face the rotor part of the ATP synthase and may contribute to proton transport across the membrane. 874 Yellow, Arg159 which also belongs to group 3. 874 Yellow, Arg159 which also belongs to group 3. . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 875 Figure 1. Concordant evolution of protein sites. 876 877 Figure 1. Concordant evolution of protein sites. 875 876 877 Figure 2. Discordant evolution of protein sites. . CC-BY 4.0 International license made available under a ch was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: Rxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 8 Figure 2. Discordant evolution of protein sites. 878 Figure 2. Discordant evolution of protein sites. Figure 2. Discordant evolution of protein sites. 878 879 880 . 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 881 Figure 3. Schematic representation of coevolution and contact graphs for CO 882 f), COX3 (g-i), ATP6 (j-l) and CYTB (m-o) proteins. 883 884 885 886 887 888 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the p 881 Figure 3. Schematic representation of coevolution and contact graphs for COX1 (a-c), COX2 (d- 882 f), COX3 (g-i), ATP6 (j-l) and CYTB (m-o) proteins. 882 f), COX3 (g-i), ATP6 (j 883 884 884 885 885 886 886 887 888 888 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint Figure 4. Groups of coevolving sites and interactions between subunits of COX. 889 Figure 4. Groups of coevolving sites and interactions between subunits of COX. 890 891 . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 9, 2020. ; https://doi.org/10.1101/2020.03.09.983361 doi: bioRxiv preprint 892 Figure 5. Groups of coevolving sites and function of ATP synthase. 893 894 892 Figure 5. Groups of coevolving sites and function of ATP synthase. 477 To identify groups of coevolving sites, we then applied a vertex clustering algorithm optimizing graph 478 modularity [38] implemented in the louvain package (https://pypi.org/project/louvain/). 892 893 894 893 894 893 894
https://openalex.org/W2045820106	https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0076526&type=printable	English	null	Amyloid Beta1-40-Induced Astrogliosis and the Effect of Genistein Treatment in Rat: A Three-Dimensional Confocal Morphometric and Proteomic Study	PloS one	2,013	cc-by	11,518	Maryam Bagheri1, Arjang Rezakhani2, Sofie Nyström3, Maria V. Turkina2, Mehrdad Roghani4, Per Hammarström3, Simin Mohseni2* 1 Department of Physiology, Faculty of Medicine, Ilam University of Medical Sciences, Ilam, Iran, 2 Department of Clinical and Experimental Medicine, Faculty of Health Sciences, Linköping University, Linköping, Sweden, 3 IFM-Department of Chemistry, Linköping University, Linköping, Sweden, 4 Department of Physiology, Neurophysiology Research Group, Shahed University, Tehran, Iran Abstract This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This project was supported by grants from the County Council of Östergötland (Sweden), Linköping University, and the Cellular and Molecular Research Center affiliated with Tehran University of Medical Sciences (Tehran, Iran). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. * E-mail: Simin.Mohseni@liu.se Competing interests: The authors have declared that no competing interests exist. * E-mail: Simin.Mohseni@liu.se damaged area, reconstructing the blood-brain barrier, and rearranging the tissue structure. On the other hand, Garwood and colleagues [11] recently observed that Aβ-induced neuronal death was accelerated by the presence of astrocytes in primary culture, and this neuronal loss was reduced when astrocyte activation was inhibited by treatment with an anti- inflammatory drug. Such drugs have been used in patients as a therapeutic approach to delay the progression of AD, but, unfortunately, they have not achieved the desired effects. For example, Jaturapatporn and coworkers in 2012 noted that a non-steroidal anti-inflammatory drug (NSAID) failed to influence the progression of cognitive deterioration [12]. Overall, knowledge regarding the role of astrogliosis in AD is limited. Abstract Astrocytes are highly involved in regulation and homeostasis of the extracellular environment in the healthy brain. In pathological conditions, these cells play a major role in the inflammatory response seen in CNS tissues, which is called reactive astrogliosis and includes hypertrophy and proliferation of astrocytes. Here, we performed 3D confocal microscopy to evaluate the morphological response of reactive astrocytes positive for glial fibrillary acidic protein (GFAP) in rats, to the presence of Aβ1–40 in the rat brain before and after treatment with genistein. In 50 astrocytes per animal, we measured the volume and surface area for the nucleus, cell body, the entire cell, the tissue covered by single astrocytes and quantified the number and length of branches, the density of the astrocytes and the intensity of GFAP immunoreactivity. Injecting Aβ1–40 into the brain of rats caused astrogliosis indicated by increased values for all measured parameters. Mass spectrometric analysis of hippocampal tissue in Aβ1–40-injected brain showed decreased amounts of tubulins, enolases and myelin basic protein, and increased amounts of dihydropyrimidinase- related protein 2. In Aβ1–40-injected rats pretreated with genistein, GFAP intensity was decreased to the sham- operated group level, and Aβ1–40-induced astrogliosis was significantly ameliorated. , Rezakhani A, Nyström S, Turkina MV, Roghani M, et al. (2013) Amyloid Beta1-40-Induced Astrogliosis and the Effect of Genistei Three-Dimensional Confocal Morphometric and Proteomic Study. PLoS ONE 8(10): e76526. doi:10.1371/journal.pone.0076526 Citation: Bagheri M, Rezakhani A, Nyström S, Turkina MV, Roghani M, et al. (2013) Amyloid Beta1-40-Induced Astrogliosis and the Effect of Genistein Treatment in Rat: A Three-Dimensional Confocal Morphometric and Proteomic Study. PLoS ONE 8(10): e76526. doi:10.1371/journal.pone.0076526 Editor: Ken Arai, Massachusetts General Hospital/Harvard Medical School, United States of America Received June 4, 2013; Accepted August 30, 2013; Published October 9, 2013 Copyright: © 2013 Bagheri et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This project was supported by grants from the County Council of Östergötland (Sweden), Linköping University, and the Cellular and Molecular Research Center affiliated with Tehran University of Medical Sciences (Tehran, Iran). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist Copyright: © 2013 Bagheri et al. Amyloid Beta1-40-Induced Astrogliosis and the Effect of Genistein Treatment in Rat: A Three-Dimensional Confocal Morphometric and Proteomic Study Maryam Bagheri1, Arjang Rezakhani2, Sofie Nyström3, Maria V. Turkina2, Mehrdad Roghani4, Per Hammarström3, Simin Mohseni2* October 2013 \| Volume 8 \| Issue 10 \| e76526 Immunohistochemistry For each animal, two separate hippocampal sections were deparaffinized and rehydrated, and then incubated with PBS containing normal serum (3.5%), triton X100 (0.25%), and bovine serum albumin (BSA, 0.25%) for 20 minutes. Thereafter, the sections were incubated for 5–10 min with serum-free protein block solution (Dako, Glostrup, Denmark) and subsequently overnight at 4° C with polyclonal rabbit antibodies against (GFAP; Dako, Glostrup, Denmark) diluted in PBS (1:1500) containing normal serum, triton X100, and BSA as described above. After washing in PBS, the sections were incubated with alkaline phosphatase-conjugated swine anti- rabbit IgG antibodies (1:100; Dako, Glostrup, Denmark) at room temperature for one hour. The sections were then washed in PBS and incubated for 15 min with Liquid Permanent Red Chromogen diluted in Liquid Permanent Red Substrate Buffer (Dako,Glostrup, Denmark). Finally, the nuclei were stained with 4'-6-diamidino-2-phenylindole (DAPI; diluted 1:500 in PBS) and mounted. Sections used as negative controls were run parallel with other sections but were omitted from primary antibodies i.e. GFAP antibodies. Ethics statement This study was carried out in accordance with the policies set forth in the Guide for the Care and Use of Laboratory Animals (NIH), approved by Ethics Committee of Tehran University of Medical Sciences (Tehran, Iran), and was according to stipulated guidelines available online at http://vcr.tums.ac.ir/ word_files/animal research.doc (In Persian). All surgery was performed under anesthesia (see below), and all efforts were made to minimize suffering. Animals Eighteen adult male Wistar rats (age 5 months ± 1 week; weight 250–300 g) were randomly assigned to four groups, which, respectively, were subjected to the following: sham operation (n = 4); injection of Aβ1–40 (n = 5); genistein pretreatment and subsequent Aβ1–40injection (n = 5); Cremophor EL pretreatment and subsequent Aβ1–40 injection (n = 4). Cremophor EL (0.5 ml) was used as a vehicle for genistein (10 mg/kg), and both agents were administered by gavage. In addition, three healthy and three Aβ1–40-injected rats were used for proteomic analysis by mass spectrometry. Specimen preparation for light microscopy nuclear factor-[kappa]B (NFKB) [13]. Recent studies of rats have demonstrated that genistein ameliorates both memory impairment [14] and Aβ1–40-induced neuronal death [15]. The effect of this compound on astrogliosis, however, is unknown. In the current investigation, we evaluated the morphological response of astrocytes to the presence of Aβ1–40 in the brain before and after treatment with genistein. In short, we used 3D confocal microscopy images to measure 12 different parameters, which revealed signs of hypertrophy in astrocytes exposed to Aβ1–40. In addition, the protein composition of the Aβ1–40 inoculated tissue was analyzed by mass spectrometry. Three weeks after the surgery, the animals were anesthetized with ketamine (150 mg/kg) and perfused with paraformaldehyde (4%) in 0.1 M PBS (pH 7.4). The brain of each rat was post-fixed and embedded in paraffin, and every third coronal sections (20 µm) of the right hippocampus were prepared to allow detection of GFAP by immunohistochemical staining. The sections used for morphometric analysis were taken between -3.3 and -4.5 posterior to bregma [16]. Introduction Astrocytes are highly involved in the regulation of extracellular ion and neurotransmitter homeostasis in the healthy brain [1-4] and failure of astrocyte-dependent homeostasis leads to imbalance in neurotransmission in a wide range of diseases [5]. Astrocytes also play a pivotal role in the modulation of synaptic plasticity that is important for mechanisms of cognition, learning, and memory [6,7]. These glia cells respond to harmful stimuli by changing their molecular, cellular, and functional properties. This response is known as reactive astrogliosis and is manifested as hypertrophy, proliferation, and functional remodeling [8]. In Alzheimer’s disease (AD), activation of astrocytes is initiated by pro-inflammatory factors and excessive nitrosative and oxidative stress [9]. Sofroniew et al. [10] postulate that reactive astrocytes protect the brain from insults by isolating the Genistein is an isoflavone that is found in a number of plants and has been shown to have anti-oxidant and anti- inflammatory properties. This compound can decrease the level of inflammatory cytokines and inhibit the activity of PLOS ONE \| www.plosone.org October 2013 \| Volume 8 \| Issue 10 \| e76526 1 Genistein Ameliorates the Aβ-Induced Astrogliosis Morphometric analysis of astrocytes A confocal microscope (Zeiss LSM 700) was used to acquire images for morphometric analysis. In this assessment, we used two sections from each animal and captured 3D images (z- stack) of fifty astrocytes/animal. The cells that were photographed had a clearly visible cell body, a DAPI-stained nucleus, and no overlapping branches; these cells were located in an area between the hippocampal fissure and stratum granulare in the medial blade of the dentate gyrus (DGmb) in hippocampal formation. For the morphometric analysis, 3D images of 900 astrocytes from all animals were created from 14,000 consecutive 2D images included in the study taken at a uniform interval of 1.01µm. The X, Y, and Z properties of the images were 0.132, 0.132, and 1 µm/pixel, respectively. To determine the conformational forms of the Aβ1–40 used in our study, a sample of the Aβ1–40 solution was analyzed using the Thioflavin T fluorescence assay. The results showed that the vast majority of the injected Aβ1–40 was in non-fibrillar form. The ThTassay showed relative fluorescence units at 480 nm (RFU) which was approximately 2% of the reference RFU for fully mature Aβ fibrils. October 2013 \| Volume 8 \| Issue 10 \| e76526 Surgery Rats were anesthetized by intraperitoneal injection of ketamine (100 mg/kg) and xylazine (10 mg/kg) and immobilized in a stereotaxic instrument (Stoelting, IL, USA). The animals were then given 4 µl of normal saline (sham-operated group) or Aβ1–40 (2 nM; three experimental groups) bilaterally in the hippocampus at -3.5 mm posterior to bregma, ± 2 mm lateral to midline, and -2.8 mm below dura, according to the atlas of the rat brain [16]. Injections were performed over 4 min (1 µl/min) in each hemisphere using a Hamilton syringe with a 26S gauge needle. The needle was left in place for an additional 5 min and thereafter slowly retracted. The length of branches was determined by using Easy Image Analysis® 2000 software (Tekno Optic, Stockholm, Sweden) to manually draw individual branches. Volocity 5.5 (Perkin Elmer Inc., Massachusetts, USA) was used to measure the following for each astrocyte: the surface area and volume of the DAPI-stained nucleus, the cell body, and the entire cell (i.e., the cell body and branches), and the area and volume of the tissue covered by the astrocyte (designated the astrocyte territory). We performed a pilot study for the measurements and observed that the software recognized two cells that were very close to each other as one cell. Therefore, the boarder of PLOS ONE \| www.plosone.org October 2013 \| Volume 8 \| Issue 10 \| e76526 2 Genistein Ameliorates the Aβ-Induced Astrogliosis the cells were manually determined on coded slides which was very time consuming but reliable. Delimitation of the astrocyte territory was achieved by drawing a line between the tips of the branches. The Perkin Elmer online support kindly assisted us and did a few measurements, and also calculated the surface area and volume of few cells by using the diameter of the cell to control if we had determined the measurements correctly. were stained with Biosafe coomassie (Biorad, CA, USA). For in-gel digestion, the selected protein bands that showed obvious differences in protein amount between samples from healthy and Aβ1–40-injected tissues were excised and digested by trypsin according to Shevchenko et al. [17]. Obtained peptide mixtures were analyzed by LC-MS/MS. In short, the proteins were digested with trypsin. The resulting peptides were extracted from the gel with trifluoroacetic acid, dried, and stored at -20 °C until needed. Fluorescence intensity In two separate hippocampal sections from each animal, we measured the intensity of GFAP+ immunoreactivity (arbitrary units) in an area of 0.7 mm2 located between stratum moleculare and the DGmb. Surgery The obtained peptide mixtures were analyzed by LC-MS/MS, using nano-flow HPLC system (EASY-nLC from Bruker Daltonics, Bremen, Germany) on a 20 mm x 100 μm (particle size 5 μm) C18 pre-column followed by a 100 mm x 75 μm C18 column (particle size 5 μm) at a flow rate 300 nL/min, using a linear gradient constructed from 0.1% formic acid (solvent A) to 0.1% formic acid in 100% acetonitrile (solvent B): 0–100% B for 60 min. Data were acquired by on- line electrospray ionization ion trap “HCT ultra PTM Discovery System” (Bruker Daltonics, Bremen, Germany) using collision- induced dissociation mode. Peak lists were created from the raw data using Bruker Daltonics Data Analysis 3.4 (Bruker Daltonics, Bremen, Germany) and the resulting MGF files were used to search for Rattus proteins in NCBI on the Mascot server (www.matrixscience.com). The search parameters allowed mass errors up to 0.8 Da for MS data, and up to 0.8 Da for MS/MS data. The charge states of the peptides were varied; one missed cleavage sites were permitted. Cysteine carbamidomethylation was selected as a fixed modification. N- terminal protein acetylation and methionine oxidation were selected as variable modifications. For identification of peptides we used the following criteria: the peptide MASCOT score was above 30, the significance threshold was set at 0.05 and redundant identifications were excluded using the bold red function. The above mentioned experiments were repeated 4 times for the capillary electrophoresis and 3 times with SDS- PAGE using in total 10 independent samples from both right and left hemispheres. The number of the primary- and the total number of branches was counted in 50 astrocytes/animal. Furthermore, the number of astrocyte cell body was counted in a well-defined area (117.000 µm2) including DGlb, DGmb and CA3 by using 2D pictures (x100). For this purpose, we counted the astrocytes exhibiting a clear cell body and a well-defined DAPI-stained nucleus and calculated the mean density of astrocyte cell body. The pattern of GFAP-positive astrocytes Sections of the cerebral cortex were found to contain a large number of GFAP-positive (GFAP+) astrocytes around the site where the syringe needle had been inserted. However, the slides that were incubated without primary antibodies and served as negative controls showed no sign of immunoreactivity. These observations were made in sections taken from rats in all four groups, and thus they are not discussed further below. Capillary electrophoresis Bioanalyzer 4200 (Agilent biotechnology) equipped with Protein 80 chip was used to analyze the homogenates of frozen tissue. The prepared soluble fractions of brain homogenates from right and left hippocampi were diluted 1:1 in the sucrose-PBS buffer. Electrophoresis samples were prepared and run according to manufacturer’s instructions. Preparation of brain homogenates for gel electrophoresis In order to evaluate the biochemical changes caused by injection of Aβ1–40 peptide in the hippocampus of the rat, three healthy and three Aβ1–40-injected rats were deeply anesthetized (ketamine, 150 mg/kg) and decapitated by guillotine apparatus three weeks after the surgery. The brains were removed in less than 5 minutes, frozen instantly in liquid nitrogen and stored at -70 °C until used. At the time for analysis, the hippocampi were isolated, weighed and homogenized. The brain material was pestled and two equivalents of 0.32 M sucrose in PBS were added. Soluble and insoluble material was separated by centrifugation 8000g, 4° C, 15 min in table top centrifuge. The supernatant (soluble fractions) was removed, and the pelleted material (insoluble fraction) was resuspended in 5 M guanidinium thiocyanate, GdnSCN, using a volume equivalent to the removed supernatant. The GdnSCN was removed by dialysis back to sucrose-PBS buffer. Statistical analysis All results were expressed as mean ± SEM, and GraphPad Prism 5 (GraphPad Software Inc., CA, USA) and SigmaStat® 3.5 were used to assess the statistical differences. Parametric one-way ANOVA followed by Tukey’s post hoc test were used to compare the data between groups. In all analyses, a difference at P < 0.05 was regarded as significant. Quantitative observations The immunoreactivity was extremely high in the DGlb and the polymorphic layer of the hippocampus in the animals that exhibited neuronal degeneration, whereas it was weak in those that had a normal DGlb. The DGmb was mostly GFAP negative in all five animals. In general, the branches of the astrocytes in the hippocampus of three of the rats had short, thin branches and a stellate form resembling that observed in the sham- operated rats. The corresponding branches in the other two In the Aβ1–40-injected group (n = 5), the DAPI-stained sections showed signs of neuronal loss in the DGlb of all the animals (Figure 1D). As observed in the serial sections, this cell loss affected the whole hippocampus. The cerebral cortex of these animals contained only a few small stellate-shaped GFAP+ astrocytes exhibiting short branches. The corpus callosum contained a dense network of GFAP+ cells in two of the rats but only few such cells were observed in the other three animals. The hippocampus from the CA1 subfield to the polymorph layer of the dentate gyrus displayed extensive signs of GFAP immunoreactivity, particularly in the area of the DGlb that exhibited severe loss of neurons (Figure 1E). The CA2 contained only a few GFAP+ astrocytes, and the DGmb showed negative GFAP immunoreactivity (Figure 1E). Overall, astrocytes in the hippocampus of the rats in this group had multiple long thin or thick branches. Also, most of the astrocytes were stellate in shape (Figure 1F left), and in some the nucleus was located laterally, and the branches were directed toward one side of the cell (Figure 1F right). In most astrocytes, the GFAP+ immunoreactivity had a punctuate appearance along the length of the branches. Astrocyte nucleus. The mean volume of the nucleus in the sham-operated rats was 663 µm3. Injection of Aβ1–40 led to a 37% increase in this parameter (P< 0.01; Table 1, Figure 2A) and a 27% increase in the surface area (P< 0.0001; Figure 2B). Genistein treatment prevented the Aβ1–40-induced increasein the volume of the nucleus and significantly decreased the increment of the surface area (P< 0.0001 vs. Aβ-injected rats; Table 1, Figure 2A,B). Astrocyte cell body. In the sham-operated rats, the mean volume of the cell body of astrocytes was 930 µm3. Astrocyte cell body. In the sham-operated rats, the mean volume of the cell body of astrocytes was 930 µm3. Quantitative observations Injection of Aβ1–40 increased the cell body volume by 23% (P = 0.003; Table 1, Figure 3A) and the surface area by 43% (P< 0.0001; Figure 3B). The Aβ1–40-induced enlargement was significantly blocked by treatment with genistein (volume P = 0.003 and surface area P< 0.0001 vs. Aβ-injected rats; Table 1, Figure 3A,B). Compared with the sham-operated animals, the genistein-treated rats had astrocytes with a 19% smaller mean cell body volume (P = 0.003) and a 6% smaller surface area (P< 0.0001; Table 1, Figure 3A,B). In The group treated with Aβ1–40 and genistein (n = 5), the DAPI-stained sections showed signs of neuronal loss in the DGlb in three of the animals and appeared normal in the other two. In the cortex, the occurrence of GFAP+ astrocytes increased from layer 1 towards layer 6 in three of the rats, whereas such immunoreactivity was absent in the other animals. Corpus callosum and the CA1 subfield of the hippocampus contained few GFAP+ astrocytes in this group. The immunoreactivity was extremely high in the DGlb and the polymorphic layer of the hippocampus in the animals that exhibited neuronal degeneration, whereas it was weak in those that had a normal DGlb. The DGmb was mostly GFAP negative in all five animals. In general, the branches of the astrocytes in the hippocampus of three of the rats had short, thin branches and a stellate form resembling that observed in the sham- operated rats. The corresponding branches in the other two animals were long and thin. Furthermore, many astrocytes in Astrocyte branches. A mean astrocyte in the sham- operation group exhibited 8.9 ± 0.3 GFAP+ branches; 68.5% were primary branches. In these respects, Aβ1–40 injection did not affect the astrocytes but genistein treatment significantly increased the number of branches compared to sham or Aβ1–40- injection group (Table 2). The mean length of the astrocyte branches in the sham-operated rats was 119.4 µm. This parameter was significantly increased (15%; P = 0.004) in the astrocytes of Aβ1–40 injected rats, and this elongation was inhibited by genistein (Table 1, Figure 4). Astrocyte size (cell body + branches). The astrocytes in the sham-operated rats had a mean volume of 5280 µm3. Genistein Ameliorates the Aβ-Induced Astrogliosis Genistein Ameliorates the Aβ-Induced Astrogliosis (Figure 1A). The GFAP+ astrocytes occurred throughout the cerebral cortex and hippocampus. In the cortex, they were small and sparsely distributed, and exhibited stellate morphology with multiple short branches. The occurrence of GFAP+ astrocytes increased from layer 1 towards layer 6 of the cortex and was most intense in corpus callosum and the polymorphic layer of the hippocampus (Figure 1B). In the hippocampus, the cornuammonis 1 (CA1) subfield contained few GFAP+ astrocytes with long branches, and the cornuammonis 2 (CA2) subfield displayed a dense network of small astrocytes with overlapping short branches. Both the DGmb and the lateral blade of the dentate gyrus (DGlb) showed weak GFAP immunoreactivity (Figure 1B). In the area that was in focus in our morphometric analysis, the branches of individual astrocytes appeared in either of two ways (Figure 1C): distributed symmetrically around the cell and thereby creating a stellate shape resembeling protoplasmic astrocytes, or asymmetrically arborized and pointed towards one side of the cell, with the nucleus located laterally in the cell body resembling fibrous astrocytes. these two animals had an atrophic appearance that included the lack of a distinct cell body and branches creating an irregular pattern (Figure 1G). In The Aβ1–40–vehicle (Cremophor EL) group (n = 4), the DAPI-stained sections revealed signs of neuronal loss in the DGlb of all of the rats. The brains of these animals showed a pattern of gliosis that was very similar to that observed in the brains of the rats given only Aβ injection and hence will not be discussed further. Overall, astrocytes in the hippocampus of the four animals in this group had long branches of varying thickness, and many of them displayed the atrophic pattern described for the genistein-treated rats. SDS-PAGE and proteomic analysis Based on the results from capillary electrophoresis, representative samples from control group and Aβ-injected group were selected for SDS-PAGE and subsequent proteomic analysis. The samples were fractionated in soluble and insoluble material. SDS-PAGE was run to perform in-gel tryptic digestion and mass finger printing. Criterion TQX 4-20% gel (Biorad, CA, USA) was used and electrophoretic separation was performed at 100 V for 1.5 h. After electrophoresis, gels In The sham-operated group (n = 4), the architecture of the hippocampus appeared normal in the DAPI-stained sections PLOS ONE \| www.plosone.org October 2013 \| Volume 8 \| Issue 10 \| e76526 3 Quantitative observations All values obtained for the Aβ1–40-injected–Cremophor-EL- treated rats (except measurements of the surface area of both the cell body and entire astrocytes) differed significantly from the corresponding values for the sham-operated rats but showed the same pattern as in the values for the Aβ1–40- injected rats. Therefore, data on the Aβ1–40-Cremophor-EL group are presented only in Table 1 and Figures 2–7 (i.e., are not given further consideration below). creating a stellate shape resembeling protoplasmic astrocytes, or asymmetrically arborized and pointed towards one side of the cell, with the nucleus located laterally in the cell body resembling fibrous astrocytes. In the Aβ1–40-injected group (n = 5), the DAPI-stained sections showed signs of neuronal loss in the DGlb of all the animals (Figure 1D). As observed in the serial sections, this cell loss affected the whole hippocampus. The cerebral cortex of these animals contained only a few small stellate-shaped GFAP+ astrocytes exhibiting short branches. The corpus callosum contained a dense network of GFAP+ cells in two of the rats but only few such cells were observed in the other three animals. The hippocampus from the CA1 subfield to the polymorph layer of the dentate gyrus displayed extensive signs of GFAP immunoreactivity, particularly in the area of the DGlb that exhibited severe loss of neurons (Figure 1E). The CA2 contained only a few GFAP+ astrocytes, and the DGmb showed negative GFAP immunoreactivity (Figure 1E). Overall, astrocytes in the hippocampus of the rats in this group had multiple long thin or thick branches. Also, most of the astrocytes were stellate in shape (Figure 1F left), and in some the nucleus was located laterally, and the branches were directed toward one side of the cell (Figure 1F right). In most astrocytes, the GFAP+ immunoreactivity had a punctuate appearance along the length of the branches. In The group treated with Aβ1–40 and genistein (n = 5), the DAPI-stained sections showed signs of neuronal loss in the DGlb in three of the animals and appeared normal in the other two. In the cortex, the occurrence of GFAP+ astrocytes increased from layer 1 towards layer 6 in three of the rats, whereas such immunoreactivity was absent in the other animals. Corpus callosum and the CA1 subfield of the hippocampus contained few GFAP+ astrocytes in this group. Quantitative observations An increase of 11% in both the volume (P = 0.03) and the surface area (P < 0.05) of the astrocytes were observed when measurements were performed on tissue from Aβ1–40 injected animals, and both these increases were inhibited by genistein October 2013 \| Volume 8 \| Issue 10 \| e76526 PLOS ONE \| www.plosone.org 4 Genistein Ameliorates the Aβ-Induced Astrogliosis Figure 1. Confocal images of hippocampal sections obtained from rats subjected to sham operation (A–C) or injection of Aβ1–40 (D–F) in the hippocampus. A: DAPI-stained section showing normal architecture of the hippocampus. B:Image illustrating the pattern of GFAP immunoreactivity. C: Astrocyte branches were distributed either symmetrically (arrowhead) or asymmetrically (arrow) around the cell. D: DAPI-stained section showing abnormal architecture of the hippocampus; note the absence of the DGlb. E: GFAP immunoreactivity. F: individual astrocytes were either stellate in shape (F-left) or asymmetric with branches directed towards one side of the cell (F-right). G: An astrocyte lacking a distinct cell body, as observed in Aβ–genistein- and Aβ–Cremophor- EL-treated rats. Aβ1–40 (2 nM) was injected into the hippocampus. Abbreviations: DGlb, lateral blade of the dentate gyrus; DGmb, medial blade of the dentate gyrus; CA1, cornuammonis area 1. (A, B, D, E: 100 µm), (C, F, G: 20 µm). doi: 10.1371/journal.pone.0076526.g001 Figure 1. Confocal images of hippocampal sections obtained from rats subjected to sham operation (A–C) or injection of Aβ1–40 (D–F) in the hippocampus. A: DAPI-stained section showing normal architecture of the hippocampus. B:Image illustrating the pattern of GFAP immunoreactivity. C: Astrocyte branches were distributed either symmetrically (arrowhead) or asymmetrically (arrow) around the cell. D: DAPI-stained section showing abnormal architecture of the hippocampus; note the absence of the DGlb. E: GFAP immunoreactivity. F: individual astrocytes were either stellate in shape (F-left) or asymmetric with branches directed towards one side of the cell (F-right). G: An astrocyte lacking a distinct cell body, as observed in Aβ–genistein- and Aβ–Cremophor- EL-treated rats. Aβ1–40 (2 nM) was injected into the hippocampus. Abbreviations: DGlb, lateral blade of the dentate gyrus; DGmb, medial blade of the dentate gyrus; CA1, cornuammonis area 1. (A, B, D, E: 100 µm), (C, F, G: 20 µm). doi: 10.1371/journal.pone.0076526.g001 Figure 1. Confocal images of hippocampal sections obtained from rats subjected to sham operation (A–C) or injection of Aβ1–40 (D–F) in the hippocampus. A: DAPI-stained section showing normal architecture of the hippocampus. B:Image illustrating the pattern of GFAP immunoreactivity. effect of Aβ1–40 on the volume and also lessened the impact of the amyloid on the surface area (Table 1, Figures 6A,B). Astrocyte density. The mean number of astrocytes/1000 µm2, was 5.6 ± 0.05 in the sham-operated rats, 11.7 ± 0.1 in the Aβ1–40-injected rats, and 6.7 ± 0.05 in the Aβ1–40-genistein- treated animals. The higher astrocyte density in Aβ1–40-injected rats was significant in comparison with data from other groups (P < 0.0001). Quantitative observations C: Astrocyte branches were distributed either symmetrically (arrowhead) or asymmetrically (arrow) around the cell. D: DAPI-stained section showing abnormal architecture of the hippocampus; note the absence of the DGlb. E: GFAP immunoreactivity. F: individual astrocytes were either stellate in shape (F-left) or asymmetric with branches directed towards one side of the cell (F-right). G: An astrocyte lacking a distinct cell body, as observed in Aβ–genistein- and Aβ–Cremophor- EL-treated rats. Aβ1–40 (2 nM) was injected into the hippocampus. Abbreviations: DGlb, lateral blade of the dentate gyrus; DGmb, medial blade of the dentate gyrus; CA1, cornuammonis area 1. (A, B, D, E: 100 µm), (C, F, G: 20 µm). doi: 10.1371/journal.pone.0076526.g001 (P < 0.0001 and P < 0.001, respectively; Table 1, Figures 5A,B). effect of Aβ1–40 on the volume and also lessened the impact of the amyloid on the surface area (Table 1, Figures 6A,B). effect of Aβ1–40 on the volume and also lessened the impact of the amyloid on the surface area (Table 1, Figures 6A,B). Astrocyte density. The mean number of astrocytes/1000 µm2, was 5.6 ± 0.05 in the sham-operated rats, 11.7 ± 0.1 in the Aβ1–40-injected rats, and 6.7 ± 0.05 in the Aβ1–40-genistein- treated animals. The higher astrocyte density in Aβ1–40-injected rats was significant in comparison with data from other groups (P < 0.0001). Astrocyte density. The mean number of astrocytes/1000 µm2, was 5.6 ± 0.05 in the sham-operated rats, 11.7 ± 0.1 in the Aβ1–40-injected rats, and 6.7 ± 0.05 in the Aβ1–40-genistein- treated animals. The higher astrocyte density in Aβ1–40-injected rats was significant in comparison with data from other groups (P < 0.0001). Astrocyte territory. To assess what we called the functional astrocyte territory, we measured the surface area and the volume of the tissue covered by individual astrocytes. Compared to astrocytes in the sham-operated rats, those in the animals that received an injection of Aβ1–40 showed a 22% increase in the mean territory volume (P< 0.0001) and a 17% increase in the surface area (P< 0.004); genistein inhibited the October 2013 \| Volume 8 \| Issue 10 \| e76526 PLOS ONE \| www.plosone.org 5 Genistein Ameliorates the Aβ-Induced Astrogliosis Table 1. Morphometric analysis of GFAP+ astrocytes in rat hippocampus. Quantitative observations Aβ-injected Cremophor EL treated group. Astrocyte surface area and volume = surface area and volume of cell body + branches. Territory surface area and volume = the surface area and volume of the tissue covered by individual astrocytes. n = number of astrocytes. doi: 10.1371/journal.pone.0076526.t001 GFAP Intensity. The mean intensity of the GFAP+ immunoreactivity was 43.7 ± 5.4 in the sham-operated group, 102.8 ± 7.7 in the Aβ1–40-injected rats, and 52.9 ± 8.3 in the Aβ1–40-genistein-treated animals. The results clearly showed that injection of Aβ increased the presence of GFAP+ astrocytes in the hippocampus by 135% (P = 0.0001), and this rise in immunoreactivity was significantly inhibited by genistein (Table 1, Figure 7). diabetes [18] and on various types of tissue, including retina [19], gut [20], respiratory organs [21], kidney [22], and arthritic joints [23,24]. Genistein exerts its anti-inflammatory effect by influencing transcription factors, enzymes, and inflammatory mediators that are involved in inducing inflammation. For example, genistein decreases production of reactive oxygen species (ROS) [25], and it inhibits NF-κB and the signal transducer and activator of transcription 1 (STAT-1), which are transcription factors for nitric oxide synthase (iNOS) [26,27]. In addition, genistein prevents the hemolysate- or Aβ-mediated induction of iNOS, as well as other inflammatory mediators such as cyclooxygenase-2 (COX-2), prostaglandin E synthases (enzymes that are involved in the synthesis of prostaglandin E2), interleukin 1 beta (IL-1 beta), and tumor necrosis factor alpha (TNF-alpha) in primary cultures of astrocytes or macrophages [26,28,29]. Furthermore, it has been observed that intravitreal injection of genistein in diabetic rodents reduced inflammation and microglial activation in the retina by involving extracellular signal-regulated kinase (ERK) and P38 mitogen-activated protein kinases (MAPKs) in activated microglia [19]. Activation of p38 MAPK by genistein increases the export of iron from astrocytes via the estrogen receptor [30]. Considering activation of apoptotic pathways, it has been suggested that genistein induces apoptosis in glioblastoma cells, but not in normal human astrocytes, by eliciting production of ROS [31]. Thus, genistein can ameliorate inflammation through activation of a cascade of intracellular molecules. Protein composition in the gliotic hippocampus of Aβ1– 40-injected rats SDS-PAGE with in gel digestion and mass spectrometric analysis revealed decrease of tublin, enolase and myelin basic proteins, and increase of dihydropyrimidinase-related protein 2 and pyruvate kinase M1/M2 in Aβ1–40-induced gliotic tissue in comparison to tissue taken from healthy animals (Figure 8; Table 3). Quantitative observations Sham–operated Aβ–injected Aβ–injected + genistein Aβ–injected + CremophorEL n = 50 n = 50 n = 50 n = 50 Nucleus volume (µm3) 663 ± 18 911 ± 16 698 ± 16 799 ±15 *P < 0.0001 P < 0.01 * P < 0.01 δP < 0.01 ** P < 0.01 Cell body volume (µm3) 930 ± 34 1148 ± 33 754 ± 26 1082 ± 36 * P = 0.003 * P = 0.003 * P < 0.05 *P = 0.003 δP = 0.003 Total length of branches (µm 119.4 ± 5.3 138.0 ± 4.0 128.1 ± 2.8 130.4 ± 2.9 P = 0.004 * P < 0.05 Astrocyte volume (µm3) 5280 ± 215 5875 ± 168 4629 ± 164 5645 ± 125 * P = 0.03 * P = 0.01 * P < 0.05 *P < 0.0001 δP < 0.05 Territory volume (µm3) 16994 ± 634 20672 ± 604 15887 ± 486 19869 ± 489 P < 0.0001 *P < 0.05 P < 0.05 δP < 0.0001 GFAP intensity 43.7 ± 5.4 102.8 ±7.7 52.9 ± 8.3 89.9 ± 6.5 * P = 0.0001 *P = 0.0001 P < 0.05 δP < 0.05 NaCl (sham-operated) or Aβ1-40 (2 nM) was injected in the hippocampus. Genistein (10 mg/ kg) and Cremophor EL (0.5 ml/ rat) were administered by gavage. * vs. sham operated group, ** vs. Aβ-injected group, δ vs. Aβ-injected Cremophor EL treated group. Astrocyte surface area and volume = surface area and volume of cell body + branches. Territory surface area and volume = the surface area and volume of the tissue covered by individual astrocytes. n = number of astrocytes. doi: 10.1371/journal.pone.0076526.t001 NaCl (sham-operated) or Aβ1-40 (2 nM) was injected in the hippocampus. Genistein (10 mg/ kg) and Cremophor EL (0.5 ml/ rat) were administered by gavage. * vs. sham operated group, ** vs. Aβ-injected group, δ vs. Aβ-injected Cremophor EL treated group. Astrocyte surface area and volume = surface area and volume of cell body + branches. Territory surface area and volume = the surface area and volume of the tissue covered by individual astrocytes. n = number of astrocytes. doi: 10.1371/journal.pone.0076526.t001 NaCl (sham-operated) or Aβ1-40 (2 nM) was injected in the hippocampus. Genistein (10 mg/ kg) and Cremophor EL (0.5 ml/ rat) were administered by gavage. * vs. sham operated group, ** vs. Aβ-injected group, δ vs. Discussion In the current study, we used antibodies against GFAP as a marker for identification of astrogliosis that is characterized by overexpression of GFAP, and pronounced hypertrophy of the cell body and their processes (9,10). We found that injection of Aβ1–40 into the rat brain was associated with astrocytic hypertrophy and this event was significantly inhibited by genistein. Previous studies have demonstrated that genistein has an anti-inflammatory impact on conditions such as October 2013 \| Volume 8 \| Issue 10 \| e76526 PLOS ONE \| www.plosone.org 6 Genistein Ameliorates the Aβ-Induced Astrogliosis Figure 2. Compared to sham-operated rats, the mean volume (A) and surface area (B) of the astrocyte nucleus were increased in animals that received an Aβ injection in the hippocampus (n = 5), an Aβ injection plus genistein treatment (area only; n = 5), or an Aβ injection plus Cremophor EL treatment (n = 4). Cremophor EL was used as a vehicle for genistein. Values are means ± SEM. The nucleus of fifty astrocytes per group were evaluated. n = number of rats. doi: 10.1371/journal.pone.0076526.g002 Figure 2. Compared to sham-operated rats, the mean volume (A) and surface area (B) of the astrocyte nucleus were increased in animals that received an Aβ injection in the hippocampus (n = 5), an Aβ injection plus genistein treatment (area only; n = 5), or an Aβ injection plus Cremophor EL treatment (n = 4). Cremophor EL was used as a vehicle for genistein. Values are means ± SEM. The nucleus of fifty astrocytes per group were evaluated. n = number of rats. doi: 10.1371/journal.pone.0076526.g002 Changes in GFAP intensity presence of a high level of Aβ peptide, astrocytic processes become convoluted and can exhibit swollen terminals [38]. In addition, both decreased and increased complexity and size of astrocytes have been observed in conditions such as hypoxia/ ischemia [35,39]. The current results suggest that when Aβ1–40 is present in brain tissue, astrocytes become reactive. This assumption agrees with data reported by Garwood and colleagues [11] demonstrating the presence of hypertrophic astrocytes in proximity to senile plaques. The occurrence of reactive astrogliosis in tissue early after injury is considered to be beneficial, because it can reestablish the chemical environment by removing harmful molecules. Reactive astrocytes can also improve the physical environment by creating scar tissue to prevent harmful molecules from spreading to healthy parts of the tissue [40]. On the other hand, the scar tissue contains a dense network of astrocytes that release inhibitory molecules, which in turn reduce the ability of the tissue to recover [8]. Astrocyte activation is accompanied by elevated production of neurotoxic factors, including cytokines, NO, and ROS, which can induce neuronal death and brain atrophy [40]. Here, we found that rats that were treated only with Aβ1–40 exhibited more extensive astrogliosis than those that were given both Aβ1–40 and genistein. In one of our earlier studies [15], we noted that neuronal degeneration in hippocampus was also more severe in rats given only Aβ1–40 than in those that received both Aβ1–40 and genistein. In addition, the results of the current study showed significantly higher density of GFAP+ astrocytes in the Aβ1–40 exposed Compared with the sham-operated group, the Aβ1–40-injected rats in our study showed increased intensity of GFAP immunoreactivity in the hippocampus, but this was not found in the Aβ1–40-injected–genistein-treated animals. This increase can be explained partly by hypertrophy and partly by upregulation of the GFAP transcription in reactive astrocytes, which is considered to play a role in the events involved in gliosis [8,32-34]. In fact, the density of the GFAP+ astrocytes in the hippocampus of Aβ1–40-injected rats in the current study was raised over 200% compared to other groups. In conclusion, our results suggest that genistein can alleviate those cellular reactions that led to Aβ1–40-induced raise of GFAP intensity. Changes in shape and size of astrocytes Protoplasmic astrocytes are normally stellate in shape and have fine branches, although, depending on their location in the CNS, these cells can modify their own morphology and size [35]. This morphological transformation is a rapid process that requires redistribution of the cytoskeletal proteins [36]. For example, in a study of the rostral preoptic area of the hypothalamus [37], it was noted that the surface area of astrocytes that were in close apposition to neurons that produced gonadotropin-releasing hormone (GnRH) exhibited a decrease in surface area between the hours of 0800 and 1200, before the onset of the luteinizing hormone surge. In a diseased condition in the brain, such as that induced by the 7 October 2013 \| Volume 8 \| Issue 10 \| e76526 PLOS ONE \| www.plosone.org Genistein Ameliorates the Aβ-Induced Astrogliosis Figure 3. The mean volume (A) and surface area (B) of the cell body of astrocytes measured in rats subjected to sham operation (n = 4), Aβ1–40 injection (n = 5), Aβ1–40 injection plus genistein treatment (n = 5), or Aβ1–40 injection plus vehicle (Cremophor EL; n = 4) treatment. Genistein treatment inhibited the Aβ1-40-induced cell body enlargement (vs. Aβ1-40 injection) and also significantly ameliorated the enlargement caused by the insertion of the needle (vs. sham operation). Astrocyte cell body size was increased in the Cremophor EL injection group compared to the sham-operated and the Aβ1–40-injected–genistein-treated rats. Cremophor EL was used as a vehicle for genistein. Values are means ± SEM. Fifty astrocytes per group were evaluated. n = number of rats. doi: 10 1371/journal pone 0076526 g003 Figure 3. The mean volume (A) and surface area (B) of the cell body of astrocytes measured in rats subjected to sham operation (n = 4), Aβ1–40 injection (n = 5), Aβ1–40 injection plus genistein treatment (n = 5), or Aβ1–40 injection plus vehicle (Cremophor EL; n = 4) treatment. Genistein treatment inhibited the Aβ1-40-induced cell body enlargement (vs. Aβ1-40 injection) and also significantly ameliorated the enlargement caused by the insertion of the needle (vs. sham operation). Astrocyte cell body size was increased in the Cremophor EL injection group compared to the sham-operated and the Aβ1–40-injected–genistein-treated rats. Cremophor EL was used as a vehicle for genistein. Values are means ± SEM. Fifty astrocytes per group were evaluated. n = number of rats. Figure 4. doi: 10.1371/journal.pone.0076526.g003 Changes in shape and size of astrocytes Chvatal and colleagues [49] performed confocal microscopy on slices of cortex from transgenic GFAP/EGFP mice to evaluate the 3D size of astrocytes, and the results showed that the cell body volume was 14.6% of the total cell volume. Similarly, we found that the average cell body volume of astrocytes in our study was 17.6% of the total cell volume detected by GFAP. It should be mentioned that our rats were perfused with 4% PFA, whereas the mice studied by Chvatal and colleagues [49] were decapitated and each brain was placed in artificial cerebrospinal fluid before analysis. Regarding the hypertrophy, Anderova and colleagues [39] observed that the total astrocyte volume (cell body and branches) increased by 250% in rats one month after hypoxia/ ischemia, and Girardi et al. [50] found that the astrocyte area increased by 300% in a rat model of epilepsy. By comparison, our data indicated an 11% increase in astrocyte area and volume three weeks after injection of Aβ1–40, a level that is quite low compared to the values reported in the cited investigations. However, it should be taken into consideration that astrocytes in our sham-operated group were already hippocampus.Together, these observations suggest that a positive correlation exists between the density of reactive astrogliosis and the severity of the damage in the tissue, which has also been proposed by other investigators [41-44]. p p y g [ ] As already mentioned, we found that injection of Aβ peptide into the hippocampus caused hypertrophy of the astrocytes in the damaged tissue. Hypertrophic astrocytes have been observed in patients with pathological conditions such as Alzheimer’s [45] and AIDS [46], and in depressed suicide subjects [47]. In studies thus far, morphometric analysis of astrogliosis has been performed on 2D photographs that only measure a fraction of a cell. Moreover, the investigations have varied considerably with regard to the choice of staining methods (i.e., histochemistry or immunohistochemistry) and techniques for creating micrographs, as well as the types of microscopes employed. For example, Hama and colleagues [48] measured the perimeter and area of the processes of the same astrocytes and obtained 2.06 times higher values when using high-voltage electron microscopy compared with light microscopy. The detection of GFAP is also limited, because this protein is not expressed in fine tertiary cell processes; according to Bushong and colleagues [1], this means that the method can only visualize 15% of an astrocyte. Changes in shape and size of astrocytes Compared to sham-operated rats (n = 4), the total length of astrocytic branches was increased in Aβ1–40-injected (n = 5) and Aβ1–40-Cremophor-EL-treated rats (n = 4), but not in Aβ1–40-genistein-treated rats (n = 5). Cremophor EL was used as a vehicle for genistein. Values are means ± SEM. Fifty astrocytes per group were included in the evaluation. n= number of rats. doi: 10.1371/journal.pone.0076526.g004 Figure 4. Compared to sham-operated rats (n = 4), the total length of astrocytic branches was increased in Aβ1–40-injected (n = 5) and Aβ1–40-Cremophor-EL-treated rats (n = 4), but not in Aβ1–40-genistein-treated rats (n = 5). Cremophor EL was used as a vehicle for genistein. Values are means ± SEM. Fifty astrocytes per group were included in the evaluation. n= number of rats. doi: 10.1371/journal.pone.0076526.g004 October 2013 \| Volume 8 \| Issue 10 \| e76526 PLOS ONE \| www.plosone.org 8 Genistein Ameliorates the Aβ-Induced Astrogliosis Figure 5. The mean volume (A) and surface area (B) of astrocytes (cell body + branches) was increased in Aβ1–40-injected rats (n = 5), and this enlargement was inhibited by genistein (n = 5) but not by Cremophor EL (n = 4). Cremophor EL was used as a vehicle for genistein. Values are means ± SEM. Fifty astrocytes per group were included in the evaluation. n = number of rats. doi: 10.1371/journal.pone.0076526.g005 Figure 5. The mean volume (A) and surface area (B) of astrocytes (cell body + branches) was increased in Aβ1–40-injected rats (n = 5), and this enlargement was inhibited by genistein (n = 5) but not by Cremophor EL (n = 4). Cremophor EL was used as a vehicle for genistein. Values are means ± SEM. Fifty astrocytes per group were included in the evaluation. n = number of rats. doi: 10.1371/journal.pone.0076526.g005 in the tissue, and hence the astrocytes in these animals were probably hypertrophic due to the mechanical damage of the brain. To our knowledge, there are no reports describing measurement of the size of astrocytes in an animal model of AD similar to the one we used in the current study, and therefore it is not possible to compare our measurements with values published by other researchers. However, some data on astrocytic hypertrophy have been obtained in other animal models. Changes in shape and size of astrocytes Consequently, it is not possible to compare measurements of astrocytes reported by different authors. Nonetheless, the question arises whether the sizes of astrocytes recorded in our investigation are reasonable. In our sham-operated rats, the brain was exposed to a needle that was inserted to inject NaCl PLOS ONE \| www.plosone.org October 2013 \| Volume 8 \| Issue 10 \| e76526 9 Genistein Ameliorates the Aβ-Induced Astrogliosis Figure 6. The mean volume (A) and surface area (B) of astrocyte tissue territory were increased in the Aβ1–40-injected (n = 5) and Aβ1–40-Cremophor-EL-treated groups (n = 4), but not in the Aβ1–40-genistein-treated rats (n = 5). Cremophor EL was used as a vehicle for genistein. Values are means ± SEM. Fifty astrocytes per group were included in the evaluation. n = number of rats. doi: 10.1371/journal.pone.0076526.g006 Figure 6. The mean volume (A) and surface area (B) of astrocyte tissue territory were increased in the Aβ1–40-injected (n = 5) and Aβ1–40-Cremophor-EL-treated groups (n = 4), but not in the Aβ1–40-genistein-treated rats (n = 5). Cremophor EL was used as a vehicle for genistein. Values are means ± SEM. Fifty astrocytes per group were included in the evaluation. n = number of rats. doi: 10.1371/journal.pone.0076526.g006 Figure 6. The mean volume (A) and surface area (B) of astrocyte tissue territory were increased in the Aβ1–40-injected (n = 5) and Aβ1–40-Cremophor-EL-treated groups (n = 4), but not in the Aβ1–40-genistein-treated rats (n = 5). Cremophor EL was used as a vehicle for genistein. Values are means ± SEM. Fifty astrocytes per group were included in the evaluation. n = number of rats. doi: 10.1371/journal.pone.0076526.g006 Figure 7. The intensity of GFAP+ immunoreactivity was increased in the Aβ1–40-injected (n = 5) and Aβ1–40-Cremophor-EL- treated rats (n = 4), but not in the Aβ1–40-genistein-treated animals (n = 5). Cremophor EL was used as a vehicle for genistein. Values are means ± SEM. For each animal two brain sections were evaluated. n = number of rats. doi: 10.1371/journal.pone.0076526.g007 Figure 7. The intensity of GFAP+ immunoreactivity was increased in the Aβ1–40-injected (n = 5) and Aβ1–40-Cremophor-EL- treated rats (n = 4), but not in the Aβ1–40-genistein-treated animals (n = 5). Cremophor EL was used as a vehicle for genistein. Values are means ± SEM. For each animal two brain sections were evaluated. n = number of rats. Protein composition in gliotic tissue We analyzed protein composition of Aβ1–40-injected hippocampal tissue to validate the occurrence of Aβ-induced neuronal cell damage in the brain. The results of mass spectrometric analysis in the current study showed a weak presence of tubulin, enolase and myelin basic proteins in Aβ1– 40-injected tissue compared with healthy tissue which signals the loss of neurons in the tissue as we have previously reported (15). In addition, there appeared to be an increased amount of the tubulin binding and axonal transport protein Changes in shape and size of astrocytes SDS-PAGE of hippocampal brain tissue homogenates for in-gel digestion and protein identification by mass spectrometry, comparing Aβ1–40 injected rats and healthy controls. Proteins identified as tublins and enolases (a) and myelin basic proteins (c) appear to decrease in Aβ1–40 injected rats indicative of neuronal loss. Proteins identified as dihydropyrimidinase- related protein 2 and pyruvate kinase M1/M2 (b), appear more abundant in Aβ1–40 injected rats compared to healthy control animals. Soluble and insoluble fractions of brain homogenate were isolated as described in Materials and Methods. The right and left hemispheres from three healthy and three Aβ1–40-injected rats were included. doi: 10.1371/journal.pone.0076526.g008 Figure 8. SDS-PAGE of hippocampal brain tissue homogenates for in-gel digestion and protein identification by mass spectrometry, comparing Aβ1–40 injected rats and healthy controls. Proteins identified as tublins and enolases (a) and myelin basic proteins (c) appear to decrease in Aβ1–40 injected rats indicative of neuronal loss. Proteins identified as dihydropyrimidinase- related protein 2 and pyruvate kinase M1/M2 (b), appear more abundant in Aβ1–40 injected rats compared to healthy control animals. Soluble and insoluble fractions of brain homogenate were isolated as described in Materials and Methods. The right and left hemispheres from three healthy and three Aβ1–40-injected rats were included. doi: 10 1371/journal pone 0076526 g008 hypertrophic as a result of mechanical injury caused by insertion of a needle, and thus the increase we recorded represents additional hypertrophy initiated by the presence of the amyloid. This mechanical injury can partly contributed to the high density of GFAP+ astrocytes in the tissue of rats in our study. dihydropyrimidinase-related protein 2. This is well in line with proteomic analyses in transgenic AβPP mice [51]. The results of the current study is in agreement with our previous studies showing that intrahippocampal injection of the Aβ1–40 in rats caused extensive neuronal degeneration in the tissue [15] leading to impaired memory [14]. Furthermore, the study presented here indicated the presence of a higher level of pyruvate kinase M1/M2 in Aβ1–40-injected tissue indicating a high metabolic activity in the gliotic tissue. Since the gliotic tissue was deprived of neurons as discussed above, this high metabolic activity is likely related to glial cells. Changes in shape and size of astrocytes doi: 10.1371/journal.pone.0076526.g007 October 2013 \| Volume 8 \| Issue 10 \| e76526 10 PLOS ONE \| www.plosone.org Genistein Ameliorates the Aβ-Induced Astrogliosis Table 2. Mean number of GFAP+ branches/astrocyte. Table 2. Mean number of GFAP+ branches/astrocyte. Branches Sham–operated Aβ–injected Aβ–injected + genistein n = 197 n = 247 n = 198 Total number 8.9 ± 0.3 8.4 ± 0.2 10.1 ± 0.2 P < 0.001 P < 0.0001 Primary branches 6.1 ± 0.2 5.9 ± 0.1 6.8 ± 0.2 (% of total number) (68.5) (70.2) (67.3) P = 0.001 *P = 0.0001 NaCl (sham-operated) or Aβ1-40 (2 nM) was injected into the hippocampus. Genistein (10 mg/ kg) was administered by gavage. n = number of astrocytes. vs. sham operated group, ** vs. Aβ-injected group. doi: 10.1371/journal.pone.0076526.t002 Table 2. Mean number of GFAP+ branches/astrocyte. Branches Sham–operated Aβ–injected Aβ–injected + genistein n = 197 n = 247 n = 198 Total number 8.9 ± 0.3 8.4 ± 0.2 10.1 ± 0.2 P < 0.001 P < 0.0001 Primary branches 6.1 ± 0.2 5.9 ± 0.1 6.8 ± 0.2 (% of total number) (68.5) (70.2) (67.3) P = 0.001 *P = 0.0001 NaCl (sham-operated) or Aβ1-40 (2 nM) was injected into the hippocampus. Genistein (10 mg/ kg) was administered by gavage. n = number of astrocytes. vs. sham operated group, ** vs. Aβ-injected group. doi: 10.1371/journal.pone.0076526.t002 Figure 8. SDS-PAGE of hippocampal brain tissue homogenates for in-gel digestion and protein identification by mass spectrometry, comparing Aβ1–40 injected rats and healthy controls. Proteins identified as tublins and enolases (a) and myelin basic proteins (c) appear to decrease in Aβ1–40 injected rats indicative of neuronal loss. Proteins identified as dihydropyrimidinase- related protein 2 and pyruvate kinase M1/M2 (b), appear more abundant in Aβ1–40 injected rats compared to healthy control animals. Soluble and insoluble fractions of brain homogenate were isolated as described in Materials and Methods. The right and left hemispheres from three healthy and three Aβ1–40-injected rats were included. doi: 10.1371/journal.pone.0076526.g008 NaCl (sham-operated) or Aβ1-40 (2 nM) was injected into the hippocampus. Genistein (10 mg/ kg) was administered by gavage. n = number of astrocytes. * vs. sham operated group, ** vs. Aβ-injected group. doi: 10.1371/journal.pone.0076526.t002 NaCl (sham-operated) or Aβ1-40 (2 nM) was injected into the hippocampus. Genistein (10 mg/ kg) was administered by gavage. n = number of astrocytes. * vs. sham operated group, ** vs. Aβ-injected group. doi: 10.1371/journal.pone.0076526.t002 Figure 8. Author Contributions Conceived and designed the experiments: MR PH SN MVT SM MB. Performed the experiments: MB AR MVT PH SM SN. Analyzed the data: MB AR SN MVT PH SM MR. Contributed reagents/materials/analysis tools: PH MR MVT SM. Wrote the manuscript: MB AR SN MVT PH SM. Acknowledgements Regarding the time window for our observation. in the current study, we performed our observation three weeks after hippocampal Aβ1–40 injection. We chose this time window since in our previous studies we did not observe any alteration in learning and memory in rats before day 14 after Aβ1–40 injection. At day 14 to 20 post-surgery, however, a significant behavioral, biochemical and morphological alteration was found in the rats (14,15). The aim of the current study was to evaluate the morphological response of astrocytes to the presence of Aβ1–40 in the rat brain before and after treatment with genistein, and for that reason, we studied astrocytes when the cell damage should be significant and the presence of astrogliosis would be expected in the tissue i.e. 3 weeks after We are grateful to Aida Vahdat for introducing us to confocal microscopy. Aβ1–40 injection. The limitation of our research design is that the long-term development of the astrogliosis remains unknown. Aβ1–40 injection. The limitation of our research design is that the long-term development of the astrogliosis remains unknown. dietary level of this compound, however, can have inhibitory effect on tyrosine kinase [52] and therefore, can impair long- term potentiation (LTP) in the hippocampus. Furthermore, Kim et al. [53] showed that high concentration of genistein can have toxic effects on the development of zebrafish embryos. In the current study, we used a single dose of 10 mg/kg genistein since the daily consumption of this amount was shown to improve the values of biomarkers in clinical studies of Sanfilippo syndrome Patients without significant side effects [54,55]. Furthermore, Morán and colleagues [56] did not find any beneficial effect of a higher concentration (40 mg/kg) on homeostasis in rat cerebral cortex in comparison to a dose of 10 mg/kg. Concluding Remarks In conclusion, we used 3D confocal microscopy to quantify morphological changes of reactive astrocytes and found that presence of Aβ1–40 in the tissue caused astrogliosis. Proteomic assessment indicated neuronal loss and enhanced metabolic activity of astrocytes responding to damage caused by Aβ1–40. Our findings also demonstrate that genistein can significantly ameliorate Aβ1–40-induced astrogliosis. Method considerations Regarding the genistein. genistein asserts its beneficial effect by its affinity to the estrogen receptor, stimulating the expression of antioxidants in normal condition, and inhibition of DNA synthesis in cancer cells as discussed above. A high PLOS ONE \| www.plosone.org 11 October 2013 \| Volume 8 \| Issue 10 \| e76526 Genistein Ameliorates the Aβ-Induced Astrogliosis le 3. Mass spectrometric analysis of brain hippocampus in Aβ1–40 injected rats and healthy animals. BandProtein Uniprot Accession number/Entry name Theoretical MW, kDa Number of peptides identified Mascot protein score A tubulin beta-2B Q3KRE8 (TBB2B_RAT) 50,361 16 636 beta-3 Q4QRB4 (TBB3_RAT) 50,419 14 582 beta-5 P69897 (TBB5_RAT) 49,671 14 571 alpha-1A P68370 (TBA1A_RAT) 50,894 15 559 enolase alpha P04764 (ENOA_RAT) 47,440 11 398 gamma P07323 (ENOG_RAT) 47,510 4 184 B dihydropyrimidinase-related protein 2 P47942 (DPYL2_RAT) 62,278 15 683 pyruvate kinase M1/M2 P11980 (KPYM_RAT) 58,294 17 534 C myelin basic protein P02688 (MBP_RAT) 21,546 6 149 Three protein groups (A; tubulin and enolase, B; dihydropyrimidinase-related protein 2 and pyruvate kinase M1/M2, and C; myelin basic protein) were identified in rat hippocampus homogenate using in-gel digestion and LC-MS/MS analysis. Aβ1-40 injected rats showed less amount of proteins in group A and C and higher amount of proteins in group B in comparison with the homogenate of the brain tissue taken from healthy animals. doi: 10.1371/journal.pone.0076526.t003 Three protein groups (A; tubulin and enolase, B; dihydropyrimidinase-related protein 2 and pyruvate kinase M1/M2, and C; myelin basic protein) were identified in rat hippocampus homogenate using in-gel digestion and LC-MS/MS analysis. Aβ1-40 injected rats showed less amount of proteins in group A and C and higher amount of proteins in group B in comparison with the homogenate of the brain tissue taken from healthy animals. doi: 10.1371/journal.pone.0076526.t003 7. Perea G, Navarrete M, Araque A (2009) Tripartite synapses: astrocytes process and control synaptic information. Trends Neurosci 32: 421-431. doi:10.1016/j.tins.2009.05.001. PubMed: 19615761. 5. Tsai G, Coyle JT (2002) Glutamatergic mechanisms in schizophrenia. Annu Rev Pharmacol Toxicol 42: 165-179. doi:10.1146/ annurev.pharmtox.42.082701.160735. PubMed: 11807169. 6. Verkhratsky A, Olabarria M, Noristani HN, Yeh CY, Rodriguez JJ (2010) Astrocytes in Alzheimer's disease. Neurotherapeutics 7: 399-412. doi:10.1016/j.nurt.2010.05.017. PubMed: 20880504. 7. Perea G, Navarrete M, Araque A (2009) Tripartite synapses: astrocytes process and control synaptic information. Trends Neurosci 32: 421-431. doi:10.1016/j.tins.2009.05.001. PubMed: 19615761. 8. Sofroniew MV (2009) Molecular dissection of reactive astrogliosis and glial scar formation. Trends Neurosci 32: 638-647. doi:10.1016/j.tins. 2009.08.002. PubMed: 19782411. References ( ) 33. Pekny M, Pekna M (2004) Astrocyte intermediate filaments in CNS pathologies and regeneration. J Pathol 204: 428-437. doi:10.1002/path. 1645. PubMed: 15495269. 12. Jaturapatporn D, Isaac MG, McCleery J, Tabet N (2012). spirin Steroidal Nonsteroidal Antinflamm Drugs Treat Alzheimers Dis 2:CD006378 34. Little AR, O'Callagha JP (2001) Astrogliosis in the adult and developing CNS: is there a role for proinflammatory cytokines? Neurotoxicology 22: 607-618. doi:10.1016/S0161-813X(01)00032-8. PubMed: 11770882. 13. Ji G, Yang Q, Hao J, Guo L, Chen X et al. (2011) Anti-inflammatory effect of genistein on non-alcoholic steatohepatitis rats induced by high fat diet and its potential mechanisms. Int Immunopharmacol 11: 762-768. doi:10.1016/j.intimp.2011.01.036. PubMed: 21320636. 35. Sullivan SM, Björkman ST, Miller SM, Colditz PB, Pow DV (2010) Structural remodeling of gray matter astrocytes in the neonatal pig brain after hypoxia/ischemia. Glia 58: 181-194. doi:10.1002/glia.20911. PubMed: 19606499. 14. Bagheri M, Joghataei MT, Mohseni S, Roghani M (2011) Genistein ameliorates learning and memory deficits in amyloid beta(1-40) rat model of Alzheimer's disease. Neurobiol Learn Mem 95: 270-276. doi: 10.1016/j.nlm.2010.12.001. PubMed: 21144907. 36. Safavi-Abbasi S, Wolff JR, Missler M (2001) Rapid morphological changes in astrocytes are accompanied by redistribution but not by quantitative changes of cytoskeletal proteins. Glia 36: 102-115. doi: 10.1002/glia.1099. PubMed: 11571788. 15. Bagheri M, Roghani M, Joghataei MT, Mohseni S (2012) Genistein inhibits aggregation of exogenous amyloid-beta(1-40) and alleviates astrogliosis in the hippocampus of rats. Brain Res 1429: 145-154. doi: 10.1016/j.brainres.2011.10.020. PubMed: 22079317. 37. Cashion AB, Smith MJ, Wise PM (2003) The morphometry of astrocytes in the rostral preoptic area exhibits a diurnal rhythm on proestrus: relationship to the luteinizing hormone surge and effects of age. Endocrinology 144: 274-280. doi:10.1210/en.2002-220711. PubMed: 12488355. j 16. Paxinos G, Watson C (1998)The rat brain in stereotaxic coordinates. New York: Academic. 17. Shevchenko A, Tomas H, Havlis J, Olsen JV, Mann M (2006). ngels Digest Mass Spectrometric Charact Proteins Proteomes1: 2856-2860. 18. Elmarakby AA, Ibrahim AS, Faulkner J, Mozaffari MS, Liou GI et al. (2011) Tyrosine kinase inhibitor, genistein, reduces renal inflammation and injury in streptozotocin-induced diabetic mice. Vasc Pharmacol 55: 149-156. doi:10.1016/j.vph.2011.07.007. PubMed: 21807121. 38. Hatten ME (1985) Neuronal regulation of astroglial morphology and proliferation in vitro. J Cell Biol 100: 384-396. doi:10.1083/jcb. 100.2.384. PubMed: 3881455. 39. Anderova M, Vorisek I, Pivonkova H, Benesova J, Vargova L et al. (2011) Cell death/proliferation and alterations in glial morphology contribute to changes in diffusivity in the rat hippocampus after hypoxia-ischemia. References 5. Tsai G, Coyle JT (2002) Glutamatergic mechanisms in schizophrenia. Annu Rev Pharmacol Toxicol 42: 165-179. doi:10.1146/ annurev.pharmtox.42.082701.160735. PubMed: 11807169. 5. Tsai G, Coyle JT (2002) Glutamatergic mechanisms in schizophrenia. Annu Rev Pharmacol Toxicol 42: 165-179. doi:10.1146/ annurev.pharmtox.42.082701.160735. PubMed: 11807169. 1. Bushong EA, Martone ME, Ellisman MH (2004) Maturation of astrocyte morphology and the establishment of astrocyte domains during postnatal hippocampal development. Int J Dev Neurosci 22: 73-86. doi: 10.1016/j.ijdevneu.2003.12.008. PubMed: 15036382. 6. Verkhratsky A, Olabarria M, Noristani HN, Yeh CY, Rodriguez JJ (2010) Astrocytes in Alzheimer's disease. Neurotherapeutics 7: 399-412. doi:10.1016/j.nurt.2010.05.017. PubMed: 20880504. 2. Bushong EA, Martone ME, Jones YZ, Ellisman MH (2002) Protoplasmic astrocytes in CA1 stratum radiatum occupy separate anatomical domains. J Neurosci 22: 183-192. PubMed: 11756501. 7. Perea G, Navarrete M, Araque A (2009) Tripartite synapses: astrocytes process and control synaptic information. Trends Neurosci 32: 421-431. doi:10.1016/j.tins.2009.05.001. PubMed: 19615761. 3. Kofuji P, Newman EA (2004) Potassium buffering in the central nervous system. Neuroscience 129: 1045-1056. PubMed: 15561419. j 8. Sofroniew MV (2009) Molecular dissection of reactive astrogliosis and glial scar formation. Trends Neurosci 32: 638-647. doi:10.1016/j.tins. 2009.08.002. PubMed: 19782411. y 4. Newman EA, Frambach DA, Odette LL (1984) Control of extracellular potassium levels by retinal glial cell K+ siphoning. Science 225: 1174-1175. doi:10.1126/science.6474173. PubMed: 6474173. y 4. Newman EA, Frambach DA, Odette LL (1984) Control of extracellular potassium levels by retinal glial cell K+ siphoning. Science 225: 1174-1175. doi:10.1126/science.6474173. PubMed: 6474173. PLOS ONE \| www.plosone.org October 2013 \| Volume 8 \| Issue 10 \| e76526 12 Genistein Ameliorates the Aβ-Induced Astrogliosis 9. Heneka MT, Rodriguez JJ, Verkhratsky A (2010) Neuroglia in neurodegeneration. Brain. Res Rev 63: 189-211. doi:10.1016/ j.brainresrev.2009.11.004. expression via MAP kinases and C/EBPbeta, AP-1, and NF-kappaB activation. Neurosci Lett 484: 133-138. doi:10.1016/j.neulet. 2010.08.034. PubMed: 20727382. j 10. Sofroniew MV, Vinters HV (2010) Astrocytes: biology and pathology. Acta Neuropathol 119: 7-135. doi:10.1007/s00401-009-0619-8. PubMed: 20012068. 31. Das A, Banik NL, Ray SK (2010) Flavonoids activated caspases for apoptosis in human glioblastoma T98G and U87MG cells but not in human normal astrocytes. Cancer 116: 164-176. PubMed: 19894226. 11. Garwood CJ, Pooler AM, Atherton J, Hanger DP, Noble W (2011) Astrocytes are important mediators of Abeta-induced neurotoxicity and tau phosphorylation in primary culture. Cell Death. Drosophila Inf Serv 2: e167. 32. Ridet JL, Malhotra SK, Privat A, Gage FH (1997) Reactive astrocytes: cellular and molecular cues to biological function. Trends Neurosci 20: 570-577. doi:10.1016/S0166-2236(97)01139-9. PubMed: 9416670. References J Cereb Blood Flow Metab 31: 894-907. doi: 10.1038/jcbfm.2010.168. PubMed: 20877389. 19. Ibrahim AS, El-Shishtawy MM, Peña A Jr, Liou GI (2010) Genistein attenuates retinal inflammation associated with diabetes by targeting of microglial activation. Mol Vis 16: 2033-2042. PubMed: 21042558. g 20. Sadowska-Krowicka H, Mannick EE, Oliver PD, Sandoval M, Zhang XJ, Eloby-Childess S et al. (1998) Genistein and gut inflammation: role of nitric oxide. Proc Soc Exp Biol Med 217: 351-357. doi: 10.3181/00379727-217-44244. PubMed: 9492347. 40. Buffo A, Rolando C, Ceruti S (2010) Astrocytes in the damaged brain: molecular and cellular insights into their reactive response and healing potential. Biochem Pharmacol 79: 77-89. doi:10.1016/j.bcp. 2009.09.014. PubMed: 19765548. 21. Duan W, Kuo IC, Selvarajan S, Chua KY, Bay BH et al. (2003) Antiinflammatory effects of genistein, a tyrosine kinase inhibitor, on a guinea pig model of asthma. Am J Respir Crit Care Med 167: 185-192. doi:10.1164/rccm.200205-420OC. PubMed: 12406820. 41. Muramori F, Kobayashi K, Nakamura I (1998) A quantitative study of neurofibrillary tangles, senile plaques and astrocytes in the hippocampal subdivisions and entorhinal cortex in Alzheimer's disease, normal controls and non-Alzheimer neuropsychiatric diseases. Psychiatry Clin Neurosci 52: 593-599. doi:10.1111/j. 1440-1819.1998.tb02706.x. PubMed: 9895207. 22. Kim JM, Uehara Y, Choi YJ, Ha YM, Ye BH et al. (2011) Mechanism of attenuation of pro-inflammatory Ang II-induced NF-kappaB activation by genistein in the kidneys of male rats during aging. Biogerontology 12: 537-550. doi:10.1007/s10522-011-9345-4. PubMed: 21713398. 42. Parachikova A, Vasilevko V, Cribbs DH, LaFerla FM, Green KN (2010) Reductions in amyloid-beta-derived neuroinflammation, with minocycline, restore cognition but do not significantly affect tau hyperphosphorylation. J Alzheimers Dis 21: 527-542. PubMed: 20555131. 23. Verdrengh M, Jonsson IM, Holmdahl R, Tarkowski A (2003) Genistein as an anti-inflammatory agent. Inflamm Res 52: 341-346. doi:10.1007/ s00011-003-1182-8. PubMed: 14504672. 24. Zhang Y, Dong J, He P, Li W, Zhang Q et al. (2012) Genistein Inhibit Cytokines or Growth Factor-Induced Proliferation and Transformation Phenotype in Fibroblast-Like Synoviocytes of Rheumatoid Arthritis. Inflammation 35: 377-387. PubMed: 21792602. 43. Nimmerjahn A (2009) Astrocytes going live: advances and challenges. J Physiol 587: 1639-1647. doi:10.1113/jphysiol.2008.167171. PubMed: 19204050. 25. Caccamo D, Campisi A, Currò M, Bramanti V, Tringali M et al. (2005) Antioxidant treatment inhibited glutamate-evoked NF-kappaB activation in primary astroglial cell cultures. Neurotoxicology 26: 915-921. doi: 10.1016/j.neuro.2005.01.010. PubMed: 15894376. 44. Garwood CJ, Cooper JD, Hanger DP, Noble W (2010) Anti- inflammatory impact of minocycline in a mouse model of tauopathy. Front Psychiatry 1: 136. PubMed: 21423446. Genistein Ameliorates the Aβ-Induced Astrogliosis References y y 45. Vanzani MC, Iacono RF, Caccuri RL, Berria MI (2005) Immunochemical and morphometric features of astrocyte reactivity vs. plaque location in Alzheimer's disease. Medicina (B Aires) 65:213-218. 26. Hämäläinen M, Nieminen R, Asmawi MZ, Vuorela P, Vapaatalo H et al. (2011) Effects of flavonoids on prostaglandin E2 production and on COX-2 and mPGES-1 expressions in activated macrophages. Planta Med 77: 1504-1511. doi:10.1055/s-0030-1270762. PubMed: 21341175. 46. Weis S, Haug H, Budka H (1993) Astroglial changes in the cerebral cortex of AIDS brains: a morphometric and immunohistochemical investigation. Neuropathol Appl Neurobiol 19: 329-335. doi:10.1111/j. 1365-2990.1993.tb00448.x. PubMed: 8232753. 27. Palanisamy N, Kannappan S, Anuradha CV (2011) Genistein modulates NF-kappaB-associated renal inflammation, fibrosis and podocyte abnormalities in fructose-fed rats. Eur J Pharmacol 667: 355-364. doi:10.1016/j.ejphar.2011.06.011. PubMed: 21704028. 47. Torres-Platas SG, Hercher C, Davoli MA, Maussion G, Labonté B et al. (2011) Astrocytic hypertrophy in anterior cingulate white matter of depressed suicides. Neuropsychopharmacology 36: 2650-2658. doi: 10.1038/npp.2011.154. PubMed: 21814185. 28. Valles SL, Dolz-Gaiton P, Gambini J, Borras C, Lloret A et al. (2010) Estradiol or genistein prevent Alzheimer's disease-associated inflammation correlating with an increase PPAR gamma expression in cultured astrocytes. Brain Res1312: 138-144. doi:10.1016/j.brainres. 2009.11.044. PubMed: 19948157. 48. Hama K, Arii T, Katayama E, Marton M, Ellisman MH (2004) Tri- dimensional morphometric analysis of astrocytic processes with high voltage electron microscopy of thick Golgi preparations. J Neurocytol 33: 277-285. doi:10.1023/B:NEUR.0000044189.08240.a2. PubMed: 15475683. 29. Lu H, Shi JX, Zhang DM, Wang HD, Hang CH et al. (2009) Inhibition of hemolysate-induced iNOS and COX-2 expression by genistein through suppression of NF-small ka, CyrillicB activation in primary astrocytes. J Neurol Sci 278: 91-95. doi:10.1016/j.jns.2008.12.007. PubMed: 19162281. 49. Chvátal A, Anderová M, Hock M, Prajerová I, Neprasová H et al. (2007) Three-dimensional confocal morphometry reveals structural changes in astrocyte morphology in situ. J Neurosci Res 85: 260-271. doi:10.1002/ jnr.21113. PubMed: 17086549. 30. Persichini T, Maio N, di Patti MC, Rizzo G, Toscano S et al. (2010) Interleukin-1beta induces ceruloplasmin and ferroportin-1 gene October 2013 \| Volume 8 \| Issue 10 \| e76526 13 PLOS ONE \| www.plosone.org concentrations in zebrafish embryos. Toxicol Mech Methods 19: 251-256. doi:10.1080/15376510802563330. PubMed: 19750021. concentrations in zebrafish embryos. Toxicol Mech Methods 19: 251-256. doi:10.1080/15376510802563330. PubMed: 19750021. Genistein Ameliorates the Aβ-Induced Astrogliosis concentrations in zebrafish embryos. Toxicol Mech Methods 19: 251-256. doi:10.1080/15376510802563330. PubMed: 19750021. concentrations in zebrafish embryos. Toxicol Mech Methods 19: 251-256. doi:10.1080/15376510802563330. PubMed: 19750021. 50. Girardi E, Ramos AJ, Vanore G, Brusco A (2004) Astrocytic response in hippocampus and cerebral cortex in an experimental epilepsy model. Neurochem Res 29: 371-377. doi:10.1023/B:NERE. 0000013739.15160.a8. PubMed: 15002732. 54. de Ruijter J, Valstar MJ, Narajczyk M, Wegrzyn G, Kulik W et al. (2012) Genistein in Sanfilippo disease: a randomized controlled crossover trial. Ann Neurol 71: 110–120. doi:10.1002/ana.22643. PubMed: 22275257. 51. Guerreiro N, Staufenbiel M, Gomez-Mancilla B (2008) Proteomic 2-D DIGE profiling of APP23 transgenic mice brain from pre-plaque and plaque phenotypes. J Alzheimers Dis13: 17-30. PubMed: 18334753. 55. Malinová V, Węgrzyn G, Narajczyk M (2012) The use of elevated dose of genistein-rich soy extract in the gene expression-targeted isoflavone therapy for Sanfilippo disease patients. JIMD Rep 5: 21-25. PubMed: 23430913. 52. Akiyama T, Ishida J, Nakagawa S, Ogawara H,Watanabe S et al. (1987) Genistein, a specific inhibitor of tyrosine-specific protein kinases. J Biol Chem 262: 5592–5595. PubMed: 3106339. 56. Morán J, Garrido P, Alonso A, Cabello E, González C (2013) 17 β- Estradiol and genistein acute treatments improve some cerebral cortex homeostasis aspects deteriorated by aging in female rats. Exp Gerontol 48: 414-421. doi:10.1016/j.exger.2013.02.010. PubMed: 23419687. 53. Kim DJ, Seok SH, Baek MW, Lee HY, Na YR et al. (2009) Developmental toxicity and brain aromatase induction by high genistein PLOS ONE \| www.plosone.org PLOS ONE \| www.plosone.org October 2013 \| Volume 8 \| Issue 10 \| e76526 14
https://openalex.org/W4311783054	https://drpress.org/ojs/index.php/fbem/article/download/3623/3471	English	null	Exploration and Research on Deepening the Full Coverage of Audit Supervision in Enterprise Internal Audit	Frontiers in business, economics and management	2,022	cc-by	4,216	1. Introduction As an important part of the national audit system, internal audit plays an important role in promoting enterprises to tap their internal potential, improve their management and economic benefits. At present, the supply-side structural reform and the reform of state-owned enterprises have entered a critical period, which puts forward higher requirements for the high-quality development of enterprises, and it is urgent to promote the full coverage of internal audit of enterprises. However, the full coverage of internal audit supervision is a systematic project, which needs to strengthen the top-level design and actively innovate the audit concept and audit methods. Therefore, based on the analysis of the new situation, new requirements and new challenges faced by the internal audit of enterprises, we need to deepen the full coverage of audit and fully promote the audit supervision service to open a new bureau. 3. The Necessity of Internal Audit to Promote Full Coverage of Audit Supervision Implementing full coverage of audit supervision is a clear requirement put forward by the state for audit work, which is of great significance for promoting the improvement of enterprise governance system and modernization of governance capacity. Jun Wu, Jincheng Zhao, Pengfei Yang, Xinyu Kan Anhui University of Finance and Economics, Bengbu, 233030, China Abstract: After nearly 40 years of exploration and development, China's auditing industry has made remarkable achievements. The Opinions on Strengthening Audit Work, Framework Opinions on Perfecting Some Major Issues of Audit System and related supporting documents issued successively by the state clearly state that public funds, state-owned assets, state-owned resources and leading cadres should be fully covered by audit. The development and changes of the social situation put forward new requirements for the development of audit work. Internal audit, an important part of the audit system, also needs to establish a working mechanism that is compatible with the full coverage of audit supervision, so as to ensure the orderly advancement of the full coverage of audit. It is of great significance to explore and study how to deepen the full coverage of internal audit supervision in enterprises. Keywords: Internal audit, Full supervision coverage, Exploratory research. new problems and situations of enterprise governance; It is necessary to continuously expand the breadth of audit coverage and the depth of audit supervision, strengthen the disclosure of hidden risks faced by enterprises, and strengthen the follow-up audit of the implementation of national policies and measures[3]; It is necessary to explore the implementation of big data audit and strengthen the intelligent construction of audit; Internal audit institutions should also do a good job in the normalization of "economic physical examination", not only to "check the disease", but also to "treat the disease and prevent it from happening". Frontiers in Business, Economics and Management ISSN: 2766-824X \| Vol. 6, No. 3, 2022 Frontiers in Business, Economics and Management ISSN: 2766-824X \| Vol. 6, No. 3, 2022 Exploration and Research on Deepening the Full Coverage of Audit Supervision in Enterprise Internal Audit Jun Wu, Jincheng Zhao, Pengfei Yang, Xinyu Kan 2. New Situation, New Requirements and New Challenges Faced by Internal Audit g p y The state advocates that audit supervision should strengthen overall planning and exert joint efforts, and proposes that internal audit should give full play to its role. Enterprise internal audit should actively strengthen coordination with national audit, establish and improve internal audit working mechanism, provide help for national audit to effectively use internal audit results, and improve the quality of full audit coverage[4]. The state has set up an audit committee, managed the national audit work as a whole, optimized the allocation of audit resources, ensured that all audits should be conducted with strict accountability, and strived to build a centralized, unified, comprehensive, authoritative and efficient audit supervision system, giving full play to the important role of audit in the state supervision system[1]. Enterprise internal audit should actively strengthen coordination with national audit, establish and improve internal audit working mechanism, provide help for national audit to effectively use internal audit results, and improve the quality of full audit coverage[4]. Internal audit has incomparable advantages over other audits in promoting the capacity building of enterprise governance system. First of all, internal audit takes internal service as its working purpose. 2. New Situation, New Requirements and New Challenges Faced by Internal Audit State audit and social audit are often used as supervision departments or entrusted by supervision to examine audited units, while internal audit is an internal supervision department of enterprises, whose existence value is to serve enterprise managers, strengthen control management and realize value-added for organizations, and it has a wide scope of examination: it can As an important part of the audit supervision system, the internal audit of enterprises also needs to adhere to the new development concept, closely follow the development and changes of the main contradictions in our society, fully perform the internal audit supervision duties of enterprises, promote the healthy and sustainable development of enterprises, and promote the standardized operation of power[2]; It is necessary to deepen the reform of the audit system, innovate the audit concept, and focus on reflecting the 217 evaluate the soundness of enterprise internal control system and the effectiveness of internal control implementation, find hidden defects of internal control, and put forward suggestions for improvement; Audit financial management to ensure that accounting information is true, reasonable and legal, which is helpful to provide useful information for decision makers[5]; Find the mistakes and omissions in the economic activities of business departments, reveal the root causes of problems, urge management departments to correct them in time, and improve operation and management; Reflect the loss and waste in the business investment of enterprises, and safeguard the investment benefit and asset security of enterprises; Supervise compliance with laws, regulations and company rules and regulations in business activities, and ensure the development of enterprises in accordance with relevant national policies and established goals of enterprises. Secondly, internal audit has the characteristics of simple procedure, easy to catch key points and high audit timeliness. As the management and supervision department of the internal audit enterprise, it is very familiar with various economic activities and business management of the enterprise. Knowing where is the focus and weak link of the enterprise management can accurately lock the audit object and save a lot of pre-trial investigation time[6]. It is also convenient to obtain information and exchange opinions during the audit process, and it can quickly carry out audit verification and solicit opinions. At the same time, internal audit has the characteristics of finding problems and being easily adopted, which can realize the transformation of audit supervision from backward to in- process and in advance. 2. New Situation, New Requirements and New Challenges Faced by Internal Audit Problems and potential risks found in the process of auditing matters are easy to be corrected by the management department in time, and can be audited, rectified, standardized and improved at the same time[7]. risks should be fully, accurately and deeply mastered, and risk assessment should be regarded as the necessary support for major business decision-making matters, and matters beyond the enterprise's risk tolerance or inadequate risk response measures should not be organized and implemented. g p The second is to focus on risk judgment and improve the management and control mechanism. Internal audit should adhere to the bottom-line thinking, give full play to subjective initiative, pay real-time attention to policies, funds, market dynamics, etc., timely reveal the main risks that affect the development of enterprises, issue risk warnings, promote the management departments to implement management and control responsibilities in time, deploy preventive measures ahead of time, and effectively improve the ability to prevent and control risks beforehand. Establish a risk management information collection and accumulation mechanism, so that the risks can be known, controllable and affordable[9]. The third is to build a risk monitoring index system and strengthen process monitoring. Internal audit should build and improve the monitoring system of risk early warning indicators, focus on management and control requirements such as strategic risk, market risk, financial risk, operational risk and legal risk, and do a good job in monitoring the risk process. Through the change of risk indicators, we can find the risk development law and provide the basis for decision- making. It can organize business departments to accurately fill in the indicator data on a monthly basis, set the normal, abnormal and alarm thresholds of indicators, strengthen the analysis of the same month-on-month, benchmark situation and critical state of indicators, thoroughly investigate the causes and change rules of risks, and put forward prevention and control suggestions, so as to do a good job in the closed- loop rectification of abnormal alarm indicators and give full play to the scientificity and effectiveness of prediction and monitoring[10]. 4. How to Deepen the Full Coverage of Enterprise Internal Audit Supervision? The fourth is to strengthen the prevention and control of major risks. The internal audit shall organize the relevant management departments of the enterprise to formulate the annual major risk prevention and resolution work plan, and clarify the responsibilities of each department in major risk prevention and control[11]. Especially for major investment decisions, large capital flows and other matters, it is necessary to carefully study and comprehensively consider, formulate strategies to deal with major risks before, during and after the event, strengthen supervision in the whole process, and timely adjust prevention and control strategies in combination with changes in policies and markets. The application of major risk monitoring results should be strengthened, major risk events should be notified in time, and major risks should be prevented, discovered and disposed of early, so as to effectively prevent the spread and superposition of major risks. Internal audit should adhere to the risk-oriented, problem- oriented and goal-oriented, take "strengthening internal control, preventing risks and promoting compliance" as the starting point, classify and determine the focus of audit objects, audit cycle and frequency, and promote risk management, internal control supervision, audit supervision and accountability for violations, so as to build a comprehensive supervision system. 4.2. Improve the supervision of internal control construction, and improve the efficiency of corporate governance system state-owned resources, and leading cadres' performance of economic responsibilities, natural resource asset management, and ecological environmental protection responsibilities within a certain cycle. The supervision of enterprise internal control construction should give full play to the important role of internal control system in strengthening the foundation and preventing and controlling risks, and effectively promote the high-quality development of enterprises. First, carry out the audit of the implementation of major policies and measures. Internal audit should focus on improving quality and increasing efficiency, promote the implementation of major decision-making arrangements with the power of audit, carry out audits of "three stresses and one major", managing deficits and getting out of difficulties, science and technology funds, poverty alleviation projects, etc. at appropriate frequency, pay attention to the legality and scientificity of decision-making, actively put forward opinions and suggestions to improve effectiveness, and give full play to the role of audit in strengthening management and promoting implementation. First, adhere to the rule of law and improve the standard operation level. Modern enterprise governance should speed up the establishment of rules and regulations, learn from each other, integrate advanced management into all aspects of decision-making and operation, better adapt to various changes in policies and situations, standardize and operate efficiently, promote the company's management to be more scientific, standardized and standardized, and highlight the good image of enterprise construction. The second is to carry out economic responsibility audit in a solid manner. Adhere to the principle of "must be audited before leaving office, and combine with middle office", establish a mechanism to inform leaders of their economic responsibilities, and promote the change of audit supervision from afterwards to beforehand. In view of the emerging and tendentious problems found in the audit, an internal reminding and talking mechanism should be established to enhance the leaders' ability to hold enterprises and their sense of compliance and responsibility. During the audit, weekly audit report mechanism, manuscript confirmation mechanism, centralized review mechanism and rectification supervision mechanism can be established and implemented according to the management ability. We should objectively and fairly evaluate leaders' performance of economic responsibilities; According to the "problems that have been rectified in the audit will no longer be reflected in the audit report" mentioned in Decree No.11 of the National Audit Office, the auditees are encouraged to set up their own banks and make changes. 4.2. Improve the supervision of internal control construction, and improve the efficiency of corporate governance system The second is to strengthen the supervision and evaluation of the internal control system and improve the efficiency of scientific management and control. Internal audit should constantly promote and strengthen the internal control concept of management institutionalization, system flow and process information. Regularly sort out the key points of internal control, risk status and control measures in key business areas. According to the requirements of separation of incompatible posts and control of authorization and approval, the rights and responsibilities of important posts and key personnel in authorization, approval, execution and reporting shall be standardized, and risk management and compliance management shall be embedded into business processes to form an internal control working mechanism with mutual connection, checks and balances and mutual supervision. Explore the full coverage of internal control supervision and evaluation, take "strong supervision and strict accountability" as the starting point, and comprehensively improve the scientificity, effectiveness and advancement of the internal control system. The third is to carry out follow-up audit of construction projects. Carry out the whole-process tracking audit of major investment projects and key special funds, strengthen the control of tracking nodes in the process of projects under construction, speed up the settlement progress of completed projects, and pay attention to the expenditure of project funds, the completion progress, and the transformation and application of results. Internal audit can make timely use of social audit forces to strengthen the risk supervision of project nodes, improve the investment benefit of construction projects, standardize the supervision of the use of state- allocated funds, scientific and technological funds, etc., and ensure earmarking. The third is to strengthen the rectification of defects in supervision and evaluation, and deepen the effect of supervision and evaluation. The internal audit of enterprises should carry out internal control evaluation, and should be fully evaluated. Especially for listed companies, internal control evaluation is mandatory. Enterprise internal auditors should carefully study and understand the evaluation contents and working procedures, strictly follow the schedule requirements, and carry out the annual internal control evaluation to ensure the evaluation quality. For the major defects found in the internal control evaluation, we should draw inferences from others to carry out special investigations, fill in the management loopholes in time, and for the general defects and hidden dangers found, we should set up a company to make changes, regularly track the rectification effect, and comprehensively improve the compliance management level. 4.2. Improve the supervision of internal control construction, and improve the efficiency of corporate governance system The fourth is to carry out the special audit of operation and management. Focus on special key work and give full play to the quality and efficiency of audit supervision. Intensify the audit of contract management, material management and various expenses in economic operation, formulate the audit implementation plan in light of the actual situation, pay attention to discovering and reflecting emerging and tendentious problems, thoroughly investigate the most prominent and critical issues, do a good job in reviewing audit problems and soliciting opinions, actively put forward suggestions to solve problems and mitigate risks, promote the establishment and improvement of institutional mechanisms, and standardize management behaviors. 4.1. Strengthen risk prevention and control, and highlight risk life cycle management Enterprise's internal audit should devote itself to the task of "three lines of defense" in risk management, promote the management department to establish the concept of "managing business must manage risks", and integrate risk prevention and control into various business management work. Fifth, strengthen enterprise special risk management. The internal audit can assess and determine the annual special risks of the enterprise according to the important and difficult areas that affect the development, quality improvement and efficiency increase of the enterprise, as well as the shortcomings and problems existing in the production, operation and management. Formulate a special risk management plan, organize and carry out special risk management, follow up the management progress on a monthly basis, and promote the improvement of management effectiveness[12]. First, adhere to the bottom line thinking and strengthen risk assessment. Internal audit should strengthen risk awareness, deeply understand and accurately grasp the new situation, new problems and new challenges faced by external environmental changes and enterprise reform, development and stability. Combined with the actual situation, major risks should be sorted out[8], re-analyzed, re-evaluated, hidden dangers should be comprehensively investigated, enterprise 218 4.4. Focus on maintaining and increasing the value of assets, and promote the implementation of accountability The second is to strengthen audit standardization management. We will revise all kinds of audit management methods and practical guidelines, unify internal audit standards, strengthen the disclosure of audit information, effectively improve the transparency of audit work, implement the internal audit project review and notification mechanism, and promote the improvement of internal audit supervision and service capabilities. The first is to establish an accountability organization system. The internal audit shall regularly report the work of accountability and major issues of accountability to the internal deliberative body of the enterprise. Overall planning, discipline inspection, inspection and organization of personnel and other supervisory forces' responsibilities in acceptance, investigation and handling, etc., forming a "trinity" supervision chain of business supervision, comprehensive supervision and accountability, and building an effective and well-connected accountability organization system. The third is to carry out research audit exploration. Focus on audit practice, serve audit needs, start with studying the deployment requirements of domestic and international economic situation and policies on audit work, grasp the direction and key points of audit work, and carry out research throughout the whole process and all aspects of audit. Through research, find out the situation, identify problems and make good suggestions, internal audit can truly become a reliable force of enterprises. The second is to improve the accountability system. Internal audit should formulate the accountability system according to the actual situation of the enterprise's business model, volume scale, etc., clarify the scope and procedures of accountability, and refine the standards of loss identification and responsibility identification. With the power of the system, the accountability requirements will be implemented, and the accountability system system of accountability according to laws and regulations, objective and fair accountability, and hierarchical accountability will be established. The fourth is to speed up the informatization construction of audit work. Set up the audit management information system, implement the online operation of the whole process of internal audit, real-time control of the whole process, and all-round report result management. Adhere to strong audit by science and technology, use digital technology, build smart audit analysis models such as contract audit and expense audit, promote the integration of industry audit, improve the working mechanism of "data analysis+on-site verification", and explore the development of big data audit. The third is to consolidate the accountability reporting mechanism. 4.5. Do a good job in infrastructure construction and comprehensively promote internal audit to improve quality and efficiency First, strengthen the leadership role of the board of directors. Further strengthen the management of important internal audit matters by the board of directors, fully mobilize internal audit resources, strengthen the guidance and supervision of internal audit work, and promote the audit committee of the board of directors to play a professional role. 4.3. Around the work center, deepen the full coverage of audit supervision The internal audit of an enterprise should define the cycle length of full coverage of audits in various fields, scientifically prepare annual audit project plans, make a good connection with medium-and long-term projects, and make scientific planning, overall arrangement, and classified implementation to ensure full coverage of state-owned assets, Fifth, focus on management improvement and strengthen the rectification and application of audit issues. Strictly implement the responsibility for rectification, further improve 219 the linkage mechanism of rectification, in which the main leaders take the lead, team members take the lead, business departments rectify and audit departments supervise, and put an end to formalism problems such as false rectification, digital rectification and paper rectification. To do detailed rectification tracking, the internal audit department of the enterprise should comprehensively check and analyze the problems found in the audit, intensify the rectification tracking and inspection of problems, refine the rectification objectives and measures, and implement the rectification and cancellation number management. According to the principle of "three-no-no-no-no-no-no-no-no-no-no-no-no-no-no-no- no-no-no-no-no-no-no-no-no-no-no-no-no-no-no-no-no-no- no-no-no-no-no-no-no-no-no To consolidate the rectification results, while rectifying the problems found in the audit, we should strengthen the transformation and application of the audit results, draw inferences from others, strengthen management, and strive to prevent problems before they happen. loopholes in enterprise management exposed in accountability, and improve the linkage mechanism of internal control and risk prevention. While being seriously accountable to those responsible for illegal business investment, the common problems can be summarized and notified within a certain range, and the warning education function of pursuing one responsibility, standardizing one and promoting the other can be played. 4.4. Focus on maintaining and increasing the value of assets, and promote the implementation of accountability Enterprises should routinely carry out self- examination and self-correction of management compliance, take the initiative to investigate and sort out the potential risks existing in compliance with the regulatory rules and regulations of state-owned assets and the internal management regulations of enterprise groups, and establish a real-time reporting and regular reporting mechanism for violation accountability. Regularly strengthen the tracking and monitoring of asset loss risk, and submit regular reports and real-time reports of accountability work on time and on demand, so as to ensure that effective measures are taken in time to solve the problem and promote the steady operation and sustainable development of enterprises. Fifth, strengthen the construction of audit team. Organize internal audit project comment guidance and experience exchange activities on schedule, put forward guidance opinions around the standardization, effectiveness and innovation of the project, and commend outstanding audit projects. In case of major special audits, excellent internal auditors can be selected and transferred to set up an audit team for implementation, so as to realize the practice of auditing instead of training. Encourage internal auditors to actively participate in the qualification examination, cultivate lifelong learning habits, and build a high-quality professional audit team. 5. Concluding Remarks The fourth is to strengthen the application of accountability results. Implement the requirements of "three distinctions" and ensure the performance of duties with precise accountability and incentives. Adhere to the combination of punishment education and system construction, study the Under the new situation, the internal audit of enterprises is facing more arduous tasks. It is necessary to follow the national audit game. Objectively, the internal audit 220 [5] Cao Yingzhao, Zheng Wei, Huang Keying, Ning Zixuan, Meng Zilu, Tian Zhuping, Song Jiamin. Study on the implementation ways of auditing to supervise the implementation of rural revitalization strategy--Xin'an County as an example [C]//.Proceedings department is required to strengthen the overall planning of audit work, scientifically plan, innovate ways, implement them by categories, and make overall arrangements for auditors in the system to audit major issues, so as to optimize the allocation of audit resources. Internal auditors should also improve their own quality, strive to establish themselves with the spirit of auditing, establish their careers with innovative norms, build their own trust, base themselves on the new development stage, implement the new development concept, effectively deepen the full coverage of internal audit supervision, realize the complementary advantages of internal audit and national audit, and push the internal audit supervision to a new level. [6] Fang Suju. Hebei audit supervision effectively promotes the implementation of active fiscal policy[N]. Hebei Daily,2022- 09-01(006).DOI:10.28326/n.cnki.nhbrb.2022.005872. [7] Chen Hongchun. The relationship between accounting supervision and audit supervision[J]. Wealth Today, 2022 (15): 124-126. [8] Zhang, H. Q.. Research on the path and mechanism for achieving full coverage of internal audit supervision in state- owned enterprises[J]. International Business Accounting, 2022(14):59-61. References [9] Bai Benming. Discussion on issues related to the construction of internal audit supervision system in the new era [J]. Modern auditing and accounting, 2022(07):25-27. [1] Li Hong. Exploration of problems related to audit supervision of state-owned enterprises [J]. Modern Auditing and Accounting, 2022(11):37-39. [10] Bian Lin-Li,Liu Ze-Hui,An J. High-quality audit supervision and high-quality economic development [J]. Journal of Yulin College,2022,32(04):53- 56.DOI:10.16752/j.cnki.jylu.2022.04.012. [2] Shi Yunyun. Exploring the democratic political logic of audit supervision in the national governance system[J]. International Business Accounting,2022(20):94-97. [3] Zhang Lili. Exploration of financial management and audit supervision of rural collective economy [J]. Agricultural development and equipment,2022(09):66-67. [11] Hu Anqin,Kong Qingjing. Research on the mechanism of enterprise financial audit supervision system under risk orientation[J]. Modern auditing and accounting,2 Chinese and foreign enterprise culture,2022(06):94-96. [4] Kong Qingjing, Hu Anqin. Prevention and governance of accounting fraud from the perspective of audit supervision[J]. Modern Business,2022(27):183- 185.DOI:10.14097/j.cnki.5392/2022.27.046. [12] Qi Runze, Hao Yugui, Hu Kewei. Research on the digital synergy platform of audit supervision, party supervision and other supervision [J/OL]. Finance and Accounting Newsletter:1-5[2022-12-05].DOI:10.16144/j.cnki.issn1002- 8072.20220609.001. 221
https://openalex.org/W2981822064	https://research.rug.nl/files/118428217/Leeman2020_Article_ASingle_CenterComparisonOfExte_1_.pdf	English	null	Maturation of Gut Microbiota and Circulating Regulatory T Cells and Development of IgE Sensitization in Early Life	Frontiers in immunology	2,019	cc-by	5,861	University of Groningen Maturation of Gut Microbiota and Circulating Regulatory T Cells and Development of IgE Sensitization in Early Life Ruohtula, Terhi; de Goffau, Marcus C.; Nieminen, Janne K.; Honkanen, Jarno; Siljander, Heli; Hamalainen, Anu-Maaria; Peet, Aleksandr; Tillmann, Vallo; Ilonen, Jorma; Niemela, Onni Published in: Frontiers in Immunology DOI: 10.3389/fimmu.2019.02494 IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record University of Groningen Maturation of Gut Microbiota and Circulating Regulatory T Cells and Development of IgE Sensitization in Early Life Ruohtula, Terhi; de Goffau, Marcus C.; Nieminen, Janne K.; Honkanen, Jarno; Siljander, Heli; Hamalainen, Anu-Maaria; Peet, Aleksandr; Tillmann, Vallo; Ilonen, Jorma; Niemela, Onni Published in: Frontiers in Immunology DOI: 10.3389/fimmu.2019.02494 IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record University of Groningen Maturation of Gut Microbiota and Circulating Regulatory T Cells and Development of IgE Sensitization in Early Life Ruohtula, Terhi; de Goffau, Marcus C.; Nieminen, Janne K.; Honkanen, Jarno; Siljander, Heli; Hamalainen, Anu-Maaria; Peet, Aleksandr; Tillmann, Vallo; Ilonen, Jorma; Niemela, Onni Published in: Frontiers in Immunology DOI: 10.3389/fimmu.2019.02494 IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record Publication date: 2019 Link to publication in University of Groningen/UMCG research database Citation for published version (APA): Ruohtula, T., de Goffau, M. C., Nieminen, J. K., Honkanen, J., Siljander, H., Hamalainen, A.-M., Peet, A., Tillmann, V., Ilonen, J., Niemela, O., Welling, G. W., Knip, M., Harmsen, H. J., & Vaarala, O. (2019). Maturation of Gut Microbiota and Circulating Regulatory T Cells and Development of IgE Sensitization in Early Life. Frontiers in Immunology, 10, Article 2494. https://doi.org/10.3389/fimmu.2019.02494 Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons). The publication may also be distributed here under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license. More information can be found on the University of Groningen website: https://www.rug.nl/library/open-access/self-archiving-pure/taverne- amendment. Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. Abstract Introduction Morbid obesity is an important risk factor for developing a venous thromboembolic events (VTE) after surgery. Fast-track protocols in metabolic surgery can lower the risk of VTE in the postoperative period by reducing the immobilization period. Administration of thromboprophylaxis can be a burden for patients. This study aims to compare extended to restricted thromboprophylaxis with low molecular weight heparin (LMWH) for patients undergoing metabolic surgery. Methods In this single center retrospective cohort study, data was collected from patients undergoing a primary Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG) between 2014 and 2018. Patients operated in 2014–2017 received thromboprophylaxis for two weeks. In 2018, patients only received thromboprophylaxis during hospital admission. Patients already using anticoagulants were analyzed as a separate subgroup. The primary outcome measure was the rate of clinically significant VTEs within three months. Secondary outcome measures were postoperative hemorrhage and reoperations for hemorrhage. Introduction Morbid obesity is an important risk factor for developing a venous thromboembolic events (VTE) after surgery. Fast-track protocols in metabolic surgery can lower the risk of VTE in the postoperative period by reducing the immobilization period. Administration of thromboprophylaxis can be a burden for patients. This study aims to compare extended to restricted thromboprophylaxis with low molecular weight heparin (LMWH) for patients undergoing metabolic surgery. Methods In this single center retrospective cohort study, data was collected from patients undergoing a primary Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG) between 2014 and 2018. Patients operated in 2014–2017 received thromboprophylaxis for two weeks. In 2018, patients only received thromboprophylaxis during hospital admission. Patients already using anticoagulants were analyzed as a separate subgroup. The primary outcome measure was the rate of clinically significant VTEs within three months. Secondary outcome measures were postoperative hemorrhage and reoperations for hemorrhage. Results 3666 Patients underwent a primary RYGB or SG following the fast-track protocol. In total, two patients in the 2014– 2017 cohort were diagnosed with VTE versus zero patients in the 2018 cohort. In the historic group, 34/2599 (1.3%) hemor- rhages occurred and in the recent cohort 8/720 (1.1%). Postoperative hemorrhage rates did not differ between the two cohorts (multivariable analysis, p = 0.475). In the subgroup of patients using anticoagulants, 21/347(6.1%) patients developed a postop- erative hemorrhage. Anticoagulant use was a significant predictor of postoperative hemorrhage (p < 0.001). Conclusion Despite the restricted use of thromboprophylaxis administration since 2018, the rate of VTEs did not increase. M. Leeman1 & L. U. Biter1 & J. A. Apers1 & E. Birnie2,3 & S. Verbrugge4 & C. Verhoef5 & M. Dunkelgrun1 M. Leeman1 & L. U. Biter1 & J. A. Apers1 & E. Birnie2,3 & S. Verbrugge4 & C. Verhoef5 & M. Dun # Springer Science+Business Media, LLC, part of Springer Nature 2019 Published online: 23 October 2019 # Springer Science+Business Media, LLC, part of Springer Nature 2019 Published online: 23 October 2019 * M. Leeman M.Leeman@Franciscus.nl University of Groningen Maturation of Gut Microbiota and Circulating Regulatory T Cells and Development of IgE Sensitization in Early Life Ruohtula, Terhi; de Goffau, Marcus C.; Nieminen, Janne K.; Honkanen, Jarno; Siljander, Heli; Hamalainen, Anu-Maaria; Peet, Aleksandr; Tillmann, Vallo; Ilonen, Jorma; Niemela, Onni Published in: Frontiers in Immunology DOI: 10.3389/fimmu.2019.02494 IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record For technical reasons the number of authors shown on this cover page is limited to 10 maximum. https://doi.org/10.1007/s11695-019-04188-6 Obesity Surgery (2020) 30:553–559 ORIGINAL CONTRIBUTIONS Abstract This may be explained by quick mobilization and hospital discharge, as encouraged by the fast-track protocol. There was no significant difference in postoperative hemorrhage rates by thromboprophylaxis protocol. Short term use of thromboprophylaxis in metabolic surgery is safe in patients at low risk of VTE. Keywords Roux-en-Y gastric bypass . Sleeve gastrectomy . Hemorrhage . Pulmonary embolism . Deep venous thrombosis . ERABS . Enhanced recovery Abbreviations ASMBS American Society for Metabolic and Bariatric Surgery BMI body mass index CI confidence interval DOAC direct oral anticoagulant DVT deep venous thrombosis ERABS enhanced recovery after bariatric surgery IRB institutional review board LMWH low molecular weight heparin OR odds ratio PE pulmonary embolism RYGB Roux-en-Y gastric bypass SG sleeve gastrectomy * M. Leeman M.Leeman@Franciscus.nl 1 Department of Surgery, Franciscus Gasthuis & Vlietland, Kleiweg 500, 3045, PM Rotterdam, The Netherlands 2 Department of Statistics and Education, Franciscus Academy, Franciscus Gasthuis & Vlietland, Rotterdam, the Netherlands 3 Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands 4 Department of Anesthesiology, Franciscus Gasthuis & Vlietland, Rotterdam, the Netherlands 5 Department of Surgery, Erasmus Medical Center, Rotterdam, the Netherlands * M. Leeman M.Leeman@Franciscus.nl * M. Leeman M.Leeman@Franciscus.nl 554 OBES SURG (2020) 30:553–559 TWOR toetsingscommissie wetenschappelijk onderzoek Rotterdam VKA vitamin K antagonist VTE venous thromboembolic events [10, 11]. Thus, not only preventive measures for VTE should be undertaken, but also for postoperative hemorrhage. This study aims to investigate if the VTE risk of restricted LMWH prophylaxis is sufficiently low in patients undergoing metabolic surgery with no or little risk factors besides their obesity. In addition, we assessed whether the risk of postop- erative hemorrhage decreased when the duration of thromboprophylaxis was shortened. Design and Data Collection We performed a retrospective cohort study using two cohorts (details mentioned below). Data was collected prospectively from all patients undergoing a primary Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG) between January 2014 and December 2018 in a single center teaching hospital. The mean (± SD) duration of surgery was 53 ± 19 min for RYGB and 36 ± 13 min for SG. The median (IQR) length of hospital stay for the complete cohort was 1.17 (0.18) days. The primary outcome measure was the clin- ically significant VTE within three months postoperatively. Secondary outcome measures were postoperative hemorrhage within one month and reoperation for postoperative hemor- rhage within one month. Rates of deep venous thrombosis (DVT) and pulmonary embolism (PE) after metabolic surgery are moderate: 0.3– 2.2% within one month after surgery for DVT and 1% for PE [4]. Nevertheless, PE plays an important role in the mor- tality of this patient category and guidelines advice to admin- ister prophylactic low molecular weight heparin (LMWH) perioperatively and after discharge to all patients undergoing metabolic surgery [6, 7]. There is no consensus on type, dos- age or duration of prophylaxis, but a recent publication from the American Society for Metabolic and Bariatric Surgery (ASMBS) Clinical Issues Committee suggested that extended pharmacological thromboprophylaxis can be restricted to only those patients who are deemed high risk of developing venous thromboembolic events (VTEs) [6]. Guidelines for periopera- tive care in metabolic surgery with respect to the Enhanced Recovery After Bariatric Surgery (ERABS) protocols recom- mend early mobilization and mechanical prophylaxis, such as intermittent pneumatic compression or graduated compres- sion stockings. However, there are also guidelines that addi- tionally encourage extended use of thromboprophylaxis for three to four weeks [7]. The effect of exclusive preoperative and/or extended pharmacological thromboprophylaxis on the incidence of postoperative bleeding is currently unknown. Introduction Severe obesity (body mass index (BMI) ≥40 kg/m2) is asso- ciated with increased mortality rates, with most deaths attrib- uted to heart disease, cancer and diabetes [1]. These increased risks can largely be reversed by significant weight loss, which is most permanently achieved by metabolic surgical proce- dures [2]. Whilst these procedures are safe, morbidly obese patients are at increased risk of developing short-term postop- erative complications [3, 4]. Reduction of BMI-related health risks are thought to outweigh the risks of metabolic surgery such as venous thromboembolic events (VTE) with high mor- tality rates [5]. Cohorts Studies suggest that the rate of VTE af- ter laparoscopic metabolic surgery nowadays is relatively low [8, 9], while the incidence of major bleeding seems to increase The protocol alteration to restricted thromboprophylaxis in 2018 was implemented because the risk of hemorrhage was thought to exceed the risk of VTE and based on gained expe- rience with pharmacological thromboprophylaxis, and sup- ported by the work of Blanchet et al., showing that extended 555 OBES SURG (2020) 30:553–559 Table 1 Caprini score and treatment per patient group Patient group Treatment Therapeutic anticoagulants • Vitamin K antagonists • Direct Oral Anticoagulant (DOAC) • Low Molecular Weight Heparin (LMWH) Pre- and postoperative bridging with Dalteparin 1 dd 5000 IE, continue until INR is adequate One or more risk factors: • Age ≥75 years • Medical history of VTE • Known hereditary thrombophilia* • Recent cerebrovascular accident (≤1 month) • Malignancy Dalteparin 5000 IE from 1 day pre-operatively until 14 days postoperatively In case of medical history of VTE: Patient wears own stockings No risk factors Dalteparin 1 dd 5000 IE during hospital admission For example protein C-, protein S-, or antithrombin-deficiencies, factor V Leiden, prothrombin 20210A mutation Treatment Pre- and postoperative bridging with Dalteparin 1 dd 5000 IE, continue until INR is adequate Dalteparin 5000 IE from 1 day pre-operatively until 14 days postoperatively In case of medical history of VTE: Patient wears own stockings Dalteparin 1 dd 5000 IE during hospital admission For example protein C-, protein S-, or antithrombin-deficiencies, factor V Leiden, prothrombin 20210A mutation pharmacological prophylaxis can increase the incidence of postoperative bleeding [11]. per dose, and repeated after a minimum of six hours if con- sidered necessary by the surgeon. If a hemorrhage was not confirmed by diagnostic imaging and the patient was hemo- dynamically stable, cases were classified as ‘no hemorrhage’. Statistical Analysis The surgical techniques did not change over the years for any of the procedures [14–16]. For SG, clips are applied on the staple line in case of visible bleeding in normotensive patients. In some cases of peroperative bleeding, a drain is placed, which is removed the next day in case of no or little produc- tion. The RYGB is checked at the entero-enterostomy and gastro-enterostomy for bleeding spots. During the operation and certainly towards the end, the aim is to keep the patient normotensive and to control the possible bleeding spots properly. All analyses were performed using SPSS (PASW) 25 software (SPSS Inc., Chicago, Illinois, USA). The risk of VTE in the two cohorts with different thromboprophylaxis regimens was compared using the binomial test, testing the hypothesis that not more than three VTE cases occur when restricted thromboprophylaxis regimen II is implemented. For patients without anticoagulants use, risks of hemorrhage in the two regimens were compared using Fisher’s Exact test. Moreover, the adjusted risk of hemorrhage was analyzed with multivariable binary logistic regression analysis, with pres- ence of hemorrhage as the dependent variable and the two thromboprophylaxis regimens (one dummy variable) as inde- pendent variables, adjusting for patient characteristics, type of surgery and presence of comorbidities. All characteristics listed in Table 2 were also included to avoid that differences between regimens I and II could be attributed to differences in casemix between regimens. A similar multivariable logistic regression analysis was performed to assess the difference in risk of postoperative hemorrhage between patients with and without anticoagulant use. Results were evaluated at a signif- icance threshold of p < 0.05 (two-sided). Postoperative Complications VTE was defined as clinically apparent VTE, as no routine venous duplex ultrasound of the calf veins was performed. On the first postoperative day, patients were asked about com- plaints of calf pain as part of the ERABS protocol postopera- tive checklist [17]. In case of a positive answer, physical ex- amination would be performed, followed by diagnostic imag- ing of the calf veins, if indicated, by venous duplex ultra- sound. This treatment pathway also applies to patients pre- senting themselves at the emergency ward or outpatient clinic with complaints of calf pain. Postoperative hemorrhage was confirmed when clinically apparent (e.g., hematemesis or melena) or when visualized on diagnostic imaging or during reoperation. In several cases, hemorrhage was suspected based on clinical and chemical parameters such as tachycardia, hypotension, severe abdomi- nal pain in combination with a decrease in hemoglobin. In these patients, no diagnostic imaging was performed and tranexamic acid was administered pragmatically, 1000 mg Cohorts All patients were treated in accordance with the ERABS pro- tocol in use in that period [12]. Two cohorts were formed according to the two regimens of thromboprophylaxis; I) 2014–2017: Extended thromboprophylaxis: Dalteparin 5000 IE from 12 h pre-operatively until two weeks postoper- atively for all patients; II) 2018: Restricted thromboprophylaxis: Dalteparin 5000 IE only during hospital admission, starting postoperatively. High risk patients were identified according to the Caprini score (Table 1) [13] and received pharmacological thromboprophylaxis according to the 2014–2017 protocol: Dalteparin 5000 IE starting the day before surgery and continuing until two weeks postoperative- ly. Patients who had had previous VTEs were advised to wear their own stockings. Patients using vitamin K antagonists (VKAs) or direct oral anticoagulants (DOACs) would bridge the perioperative period using a prophylactic dosage of Dalteparin instead of therapeutic, because of the non- negligible risk of postoperative hemorrhage. Over the years, multiple studies have been published on the advantages of following an ERABS protocol. One of the most important items in these fast-track protocols is to stimulate early mobilization after surgery, thereby allowing for early hospital discharge and reducing the number of VTEs. At the same time, the fast-track program aims to prevent overtreat- ment with potentially unnecessary pharmacological thromboprophylaxis. Results In regimen II (2018) the postoperative VTE rate was 0/720 (0%, exact 95%CI: 0.0%–0.51%), hereby not exceed- ing the pre-set threshold of three VTE cases (exact binomial test, p > 0.99). Both patients diagnosed with VTE had devel- oped early postoperative complications prior to the VTE oc- currence, and did therefore not follow the fast-track protocol. The absolute hemorrhage rates for patients without antico- agulants use were 34/2599 (1.3%, exact 95%CI 0.9–1.8%) for regimen I (2014–17) and 8/720 (1.1%, exact 95%CI 0.5– 2.2%) for regimen II (cohort 2018) (p = 0.675). The thromboprophylaxis regimen in the group not on anticoagu- lant therapy was not significantly associated with higher post- operative hemorrhage rates, adjusted for patient characteris- tics, type of surgery and comorbidities: OR 1.370, 95%CI 0.577–3.254, p = 0.475. Two patients were diagnosed with postoperative VTE in regimen I (2014–17): 2/2599 (0.01%, exact 95%CI: 0.0– 0.3%). In regimen II (2018) the postoperative VTE rate was 0/720 (0%, exact 95%CI: 0.0%–0.51%), hereby not exceed- ing the pre-set threshold of three VTE cases (exact binomial test, p > 0.99). Both patients diagnosed with VTE had devel- oped early postoperative complications prior to the VTE oc- currence, and did therefore not follow the fast-track protocol. The absolute hemorrhage rates for patients without antico- agulants use were 34/2599 (1.3%, exact 95%CI 0.9–1.8%) for regimen I (2014–17) and 8/720 (1.1%, exact 95%CI 0.5– 2.2%) for regimen II (cohort 2018) (p = 0.675). The thromboprophylaxis regimen in the group not on anticoagu- lant therapy was not significantly associated with higher post- operative hemorrhage rates, adjusted for patient characteris- tics, type of surgery and comorbidities: OR 1.370, 95%CI 0.577–3.254, p = 0.475. Table 3 Baseline characteristics based on anticoagulants use Results Between 2014 and 2018, 3666 patients underwent a primary RYGB (n = 1983) or SG (n = 1683). Over the years, popular- ity of the sleeve gastrectomy as opposed to the RYGB gradu- ally increased from 296/669 (44.2%) in 2014 to 437/777 OBES SURG (2020) 30:553–559 556 Table 2 Baseline characteristics based on thromboprophylaxis regimen No anticoagulants use; 2 weeks thromboprophylaxis (regimen I, n = 2599) No anticoagulants use; thromboprophylaxis during hospitalization (regimen II, n = 720) p value Female, n (%) 2145 (82.5%) 592 (82.2%) 0.847 Age (years), mean ± sd 40.5 ± 11.0 40.1 ± 11.4 0.759 Baseline BMI (kg/m2), mean ± sd 43.4 ± 4.8 42.8 ± 4.9 0.001 RYGB, n (%) 1460 (56.2%) 309 (42.9%) <0.001 Presence of hypertension, n (%) 655 (25.2%) 166 (24.1%) 0.552 Presence of T2D, n (%) 404 (15.6%) 74 (10.8%) 0.001 Presence of dyslipidemia, n (%) 300 (11.6%) 41 (6.0%) <0.001 Table 2 Baseline characteristics based on thromboprophylaxis regimen (56.2%) in 2018. Table 2 shows the baseline characteristics and comorbidities for the two thromboprophylaxis regimens. Significant differences were found between the two regimens for baseline BMI, type of surgery, type 2 diabetes (T2D) and hypercholesterolemia. Table 3 shows the baseline characteris- tics divided by anticoagulant usage. Patients who used antico- agulants were more often males of older age, and had higher rates of hypertension, diabetes and dyslipidemia compared to patients without anticoagulant use. The absolute hemorrhage rate for the group with preexisting anticoagulant use was 6.1% (95%CI: 3.9–8.9%) versus 1.3% (95%CI: 0.9–1.7%) without anticoagulant use (Fig. 1). Anticoagulant use was significantly associated with postoperative hemorrhage: OR 3.143, 95%CI 1.642–6.019, p = 0.001, adjusted for patient characteristics, type of surgery and comorbidities. In the period of 2014–2016, before the introduction of tranexamic acid, 33/2114 patients (1.6%, exact 95%CI 1.1– 2.2%) had a postoperative hemorrhage requiring a reintervention. Of the 1552 patients that underwent a metabol- ic procedure in 2017–2018 (after implementation of tranexamic acid), 24 (1.5%) patients received tranexamic acid and still underwent a reintervention due to hemorrhage. Six additional (0.4%) patients underwent a reintervention, but did not receive tranexamic prior to this. Another 35 (2.3%) pa- tients received tranexamic acid and did not undergo a reintervention. Two patients were diagnosed with postoperative VTE in regimen I (2014–17): 2/2599 (0.01%, exact 95%CI: 0.0– 0.3%). Discussion This study showed that a VTE was observed in none of the patients managed according to the restricted thromboprophylaxis protocol. A total of two of the patients with an intention-to-treat according to the fast-track protocol developed a VTE, both with extended use of thromboprophylaxis. Adequate thromboprophylaxis is con- sidered to be of great importance because of the high mortality rate associated with VTE [8]. Therefore, the ERABS guide- lines recommend both pharmacological prophylaxis and com- pression devices of the lower extremities [7]. Quick mobiliza- tion after surgery might be an even more important aspect in preventing VTE. In the fast-track setting, mobilization starts directly after surgery. On the first postoperative day, physical therapists practice mobilization and advise patients on how to mobilize after discharge. Our results, supported by the available literature, demon- strate that a short length of hospital stay (during which mobi- lization is encouraged) can be beneficial for patients. However, the window to detect complications during admis- sion is small. It is suggested that the incidence of major bleed- ing is increasing [10]. More specifically, postoperative hem- orrhage occurs in 2.0% of patients undergoing SG and in 1.5– 3.1% of patients undergoing a RYGB [22, 23]. While our results are in line with these rates (2.2% for SG and 1.3% for RYGB), our study does not corroborate the increasing trend. As expected, the rates of postoperative hemorrhage were higher in patients using anticoagulants. Also, this patient group had higher rates of hypertension, diabetes and dyslipid- emia, suggesting that these patients’ clinical condition was already worse preoperatively. The study by Coblijn et al. found that the use of anticoagulants is associated with postop- erative complications (OR 1.5, 95%CI 0.884–2.394, p = 0.142) [24]. Our results correspond to these findings. Before the introduction of fast-track programs, VTE was a feared complication of metabolic surgery and a significant contributor of the mortality associated with these procedures [18]. In 2007, Raftopoulos et al. concluded that extended thromboprophylaxis was safe and effective in reducing the incidence of VTE as compared to in-hospital thromboprophylaxis only [19]. The authors mention a mean duration of surgery of 220 min. The current study showed a mean duration of surgery of 53 min for RYGB and 36 min for SG in our cohort, supporting the earlier findings that duration of surgery independently influences the risk of VTE [20]. Discussion This study aimed to determine the safety of a restricted policy of pharmacological prophylaxis for VTE in patients undergo- ing metabolic surgery with no or few risk factors besides their obesity, and to determine the risk of postoperative bleeding Table 3 Baseline characteristics based on anticoagulants use Anticoagulants use (n = 347) No anticoagulants use (n = 3319) p value Female, n (%) 231 (66.6%) 2737 (82.5%) <0.001 Age (years), mean ± sd 50.6 ± 8.9 40.5 ± 11.0 <0.001 Baseline BMI (kg/m2), mean ± sd 42.2 ± 5.2 43.3 ± 4.8 <0.001 RYGB, n (%) 214 (61.7%) 1769 (53.3%) <0.001 Presence of hypertension, n (%) 196 (57.3%) 821 (24.7%) <0.001 Presence of T2D, n (%) 110 (32.2%) 478 (14.4%) <0.001 Presence of dyslipidemia, n (%) 143 (41.8%) 341 (10.3%) <0.001 Table 3 Baseline characteristics based on anticoagulants use 557 OBES SURG (2020) 30:553–559 Fig. 1 Crude postoperative hemorrhage rates per thromboprophylaxis regimen. There were no significant differences in hemorrhage rates by thromboprophylaxis regimen either including (p = 0.674, gray bars) or excluding (p = 0.675, black bars) patients with anticoagulant use poor clinical condition, the patient eventually developed a DVT while on thromboprophylaxis. In the second case, the pharmacological thromboprophylaxis was paused directly af- ter surgery, because of suspicion of postoperative hemorrhage that was later confirmed on diagnostic imaging. After several days of bedrest due to poor clinical condition and no safe possibility to administer thromboprophylaxis, pulmonary embolisms occurred. These two cases emphasize the impor- tance of close monitoring for the presence of VTE in patients that do not follow the fast-track protocol. The importance of close monitoring of patients with an extended length of hospital stay was also shown by Froehling et al. The authors state that the incidence of VTE rose from 0.3% to 1.9% between thromboprophylaxis for sev- en and 30 days postoperatively [21]. However, the patients that developed VTEs had a mean length of hospital stay of six days. In the current study, the median length of hospital stay was 1.16 days. Fig. 1 Crude postoperative hemorrhage rates per thromboprophylaxis regimen. There were no significant differences in hemorrhage rates by thromboprophylaxis regimen either including (p = 0.674, gray bars) or excluding (p = 0.675, black bars) patients with anticoagulant use under different pharmacological thromboprophylaxis proto- cols. Discussion Postoperative hemorrhage can have a very serious course and prevention of hemorrhage should therefore receive at least equal attention as prevention of VTE. In 2017–2018, patients that were suspected of postoperative hemorrhage were given tranexamic acid, a plasminogen inhibitor that can reduce blood loss by inhibiting fibrinolysis [25]. This decision was mainly influenced by the patient’s clinical condition, the direct availability of an operating room and the surgeon-on-call’s experience with tranexamic acid. Klaassen et al. performed a retrospective analysis on postoperative administration of tranexamic acid in case of suspected hemorrhage and sug- gested that tranexamic acid can reduce the reoperation rate for bleeding after metabolic surgery [26]. Our retrospective study has insufficient power to draw a conclusion on the pos- sible prevention of reoperations due to administration of tranexamic acid. Because of the increasing experience with Nowadays, the incidence of VTE after laparoscopic meta- bolic surgery is relatively low [8] which is also confirmed in our study: only two patient developed VTEs. Interestingly, these patients did not follow the fast-track protocol because of short-term postoperative complications. In one case, the patient was readmitted within one week postoperatively and underwent a reoperation because of staple line leakage. During a two month hospital admission because of persistent staple line leakage and the patient being bedridden and in a OBES SURG (2020) 30:553–559 558 protocol with no preexisting risk factors for VTE. Furthermore, our study underlines that patients using antico- agulants have an increased risk of postoperative hemorrhage as compared to patients not on anticoagulant therapy. From our data, we cannot conclude if administration of tranexamic acid for clinical suspicion of hemorrhage could prevent reintervention after metabolic surgery. Large national data- bases could play an important role in further research on the topic of short term thromboprophylaxis. Also, future studies should focus on prevention of postoperative hemorrhage in patients with a restricted thromboprophylaxis strategy follow- ing the fast-track protocol. tranexamic acid over the years and the negligible disadvan- tages, the threshold to prescribe tranexamic acid in case of suspicion of hemorrhage is currently low. A randomized con- trolled trial should further investigate the effects of tranexamic acid administration on the reoperations rates for hemorrhage. Many studies report on either the risk of VTE or the risk of postoperative hemorrhage. Discussion No articles were found on the op- timal balance between VTE risk and hemorrhage risk in pa- tients undergoing metabolic surgery and following a fast-track program. Altieri et al. do report on both the risk of VTE and the risk of hemorrhage and conclude that postoperative VTE chemoprophylaxis is associated with decreased VTE events compared to no prophylaxis, while minimizing hemorrhage compared to pre-operative prophylaxis [27]. However, their patients did not follow a fast-track protocol, which is known to accelerate mobilization and shorten hospital stay. To our knowledge, this article is the first to demonstrate that a restrict- ed thromboprophylaxis strategy for certain low-risk patients while following the fast-track protocol does not increase the risk of VTE. References 1. Kitahara CM, Flint AJ, Berrington de Gonzalez A, et al. Association between class III obesity (BMI of 40-59 kg/m2) and mortality: a pooled analysis of 20 prospective studies. PLoS Med. 2014;11(7):e1001673. 2. Colquitt JL, Pickett K, Loveman E, Frampton GK. Surgery for weight loss in adults. Cochrane Database Syst Rev 2014(8): Cd003641. https://doi.org/10.1002/14651858.CD003641.pub4 3. Nimeri AA, Bautista J, Ibrahim M, et al. Mandatory risk assessment reduces venous thromboembolism in bariatric surgery patients. Obes Surg. 2018;28(2):541–7. 4. Stein PD, Matta F. Pulmonary embolism and deep venous throm- bosis following bariatric surgery. Obes Surg. 2013;23(5):663–8. 5. Fried M, Yumuk V, Oppert JM, et al. Interdisciplinary European guidelines on metabolic and bariatric surgery. Obes Surg. 2014;24(1):42–55. 6. ASMBS updated position statement on prophylactic measures to reduce the risk of venous thromboembolism in bariatric surgery patients. Surg Obes Relat Dis: official journal of the American Society for Bariatric Surgery. 2013;9(4):493–7. 7. Thorell A, MacCormick AD, Awad S, et al. Guidelines for periop- erative Care in Bariatric Surgery: enhanced recovery after surgery (ERAS) society recommendations. World J Surg. 2016;40(9): 2065–83. Compliance with Ethical Standards Conflict of Interest The authors declare that they have no conflict of interest. Conflict of Interest The authors declare that they have no conflict of interest. Ethical Approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institu- tional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study protocol was approved by the institutional review board (IRB) and the regional Medical Research Ethics Committee TWOR, Rotterdam, the Netherlands (protocol number 2018–03). This study has several limitations. It was a single-center, ret- rospective study and cohorts were consecutive instead of parallel in time. However, these factors did not contribute to heterogene- ity of the cohorts, except for the type of surgery. The sample size of regimen II was limited, VTE is a rare event and observed VTE incidence rates were low. A formal comparison of regimens I and II in a randomized controlled trial would require at least 98,000 patients per treatment arm to demonstrate the superiority of reg- imen II, and a non-inferiority study probably would require even more patients. Such an unrealistically large study would clearly be unfeasible. As such, our study does not demonstrate in abso- lute terms that regimen II is superior (or non-inferior) to regimen I. However, what our study actually does show is that it is highly likely that the observed VTE rate of regimen II is below a rea- sonably chosen threshold of three VTE cases. Also, routine ve- nous duplex ultrasound was not performed. Therefore, only clin- ically significant VTEs could be registered, and there may have been some underreporting. However, it is unclear whether the not-clinically apparent VTEs are relevant to diagnose and should receive aggressive therapy when diagnosed. Unfortunately, due to the retrospective aspect of this study, it was not possible to perform a valid comparative analysis on the effects of tranexamic acid on postoperative hemorrhage. Therefore, the results were stated purely in descriptive terms and we refrained from any conclusions regarding tranexamic acid use. We aim to address this matter in future research projects. Informed Consent Informed consent was obtained from all individual participants included in the study. Conclusion 8. Bhattacharya S, Kumar SS, Swamy PDK, et al. Deep vein throm- bosis prophylaxis: are we overdoing? An Asian survey on trends in bariatric surgery with a systematic review of literature. Journal of minimal access surgery. 2018;14(4):285–90. This study demonstrates that a restricted thromboprophylaxis strategy did not adversely affect the rates of VTE and postop- erative hemorrhage for patients following the fast-track OBES SURG (2020) 30:553–559 559 9. Thereaux J, Lesuffleur T, Czernichow S, et al. To what extent does Posthospital discharge chemoprophylaxis prevent venous thrombo- embolism after bariatric surgery?: results from a Nationwide cohort of more than 110,000 patients. Ann Surg. 2018;267(4):727–33. 19. Raftopoulos I, Martindale C, Cronin A, et al. The effect of extended post-discharge chemical thromboprophylaxis on venous thrombo- embolism rates after bariatric surgery: a prospective comparison trial. Surg Endosc. 2008;22(11):2384–91. 10. Becattini C, Agnelli G, Manina G, et al. Venous thromboembolism after laparoscopic bariatric surgery for morbid obesity: clinical bur- den and prevention. Surg Obes Relat Dis: official journal of the American Society for Bariatric Surgery. 2012;8(1):108–15. 20. Chan MM, Hamza N, Ammori BJ. Duration of surgery indepen- dently influences risk of venous thromboembolism after laparo- scopic bariatric surgery. Surg Obes Relat Dis: official journal of the American Society for Bariatric Surgery. 2013;9(1):88–93. 21. Froehling DA, Daniels PR, Mauck KF, et al. Incidence of venous thromboembolism after bariatric surgery: a population-based cohort study. Obes Surg. 2013;23(11):1874–9. 11. Blanchet MC, Gignoux B, Matussiere Y, et al. Experience with an enhanced recovery after surgery (ERAS) program for bariatric sur- gery: comparison of MGB and LSG in 374 patients. Obes Surg. 2017;27(7):1896–900. 22. Zafar SN, Miller K, Felton J, et al. Postoperative bleeding after laparoscopic roux en Y gastric bypass: predictors and conse- quences. Surg Endosc. 2018;33(1):272–80. 12. Mannaerts GH, van Mil SR, Stepaniak PS, et al. Results of implementing an enhanced recovery after bariatric surgery (ERABS) protocol. Obes Surg. 2016;26(2):303–12. 23. Zellmer JD, Mathiason MA, Kallies KJ, et al. Is laparoscopic sleeve gastrectomy a lower risk bariatric procedure compared with laparo- scopic roux-en-Y gastric bypass? A meta-analysis. Am J Surg. 2014;208(6):903–10; discussion 9-10 13. Caprini JA. Thrombosis risk assessment as a guide to quality patient care. Disease-a-month : DM. 2005;51(2–3):70–8. 14. Apers J, Wijkmans R, Totte E, et al. Implementation of mini gastric bypass in the Netherlands: early and midterm results from a high- volume unit. Surg Endosc. 2018;32(9):3949–55. 24. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Conclusion Coblijn UK, Karres J, de Raaff CAL, et al. Predicting postoperative complications after bariatric surgery: the bariatric surgery index for complications, BASIC. Surg Endosc. 2017;31(11):4438–45. 15. Biter LU, Gadiot RP, Grotenhuis BA, et al. The sleeve bypass trial: a multicentre randomized controlled trial comparing the long term outcome of laparoscopic sleeve gastrectomy and gastric bypass for morbid obesity in terms of excess BMI loss percentage and quality of life. BMC Obesity. 2015;2:30. 25. Picetti R, Shakur-Still H, Medcalf RL, et al. What concentration of tranexamic acid is needed to inhibit fibrinolysis? A systematic re- view of pharmacodynamics studies. Blood Coagul Fibrinolysis : an international journal in haemostasis and thrombosis. 2019;30(1):1– 10. 16. Gadiot RP, Biter LU, Zengerink HJ, et al. Laparoscopic sleeve gastrectomy with an extensive posterior mobilization: technique and preliminary results. Obes Surg. 2012;22(2):320–9. 26. Klaassen RA, Selles CA, van den Berg JW, et al. Tranexamic acid therapy for postoperative bleeding after bariatric surgery. BMC Obes. 2018;5:36. 17. van Mil SR, Duinhouwer LE, Mannaerts GHH, et al. The standard- ized postoperative checklist for bariatric surgery; a tool for safe early discharge? Obes Surg. 2017;27(12):3102–9. 27. Altieri MS, Yang J, Hajagos J, et al. Evaluation of VTE prophylaxis and the impact of alternate regimens on post-operative bleeding and thrombotic complications following bariatric procedures. Surg Endosc. 2018;32:4805–12. 18. Raftopoulos I, Ercole J, Udekwu AO, et al. Outcomes of roux-en-Y gastric bypass stratified by a body mass index of 70 kg/m2: a com- parative analysis of 825 procedures. J Gastrointest Surg: official journal of the Society for Surgery of the Alimentary Tract. 2005;9(1):44–52. discussion -3 Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
https://openalex.org/W4287991006	https://zenodo.org/record/4012200/files/Balneo280.pdf	English	null	Possibilities of using natural mineral waters in the treatment of patients with non-alcoholic fatty liver disease	Zenodo (CERN European Organization for Nuclear Research)	2,019	cc-by	6,322	Possibilities of using natural mineral waters in the treatment of patients with non-alcoholic fatty liver disease GUSHCHA Sergey1, DRAGOMIRETSKA Natalia1, ZABOLOTNA Iryna1, NASIBULLIN Boris1, IZHA Anna1, ВADIUK Natalia2, KOIEVA Khrystyna1 Coresponding author: Sergey Gushcha E-mail address: gushchasergey@rambler.ru Balneo Research Journal DOI: http://dx.doi.org/10.12680/balneo.2019.280 Vol.10, No.4, December 2019 p: 450–456 Possibilities of using natural mineral waters in the treatment of patients with non-alcoholic fatty liver disease GUSHCHA Sergey1, DRAGOMIRETSKA Natalia1, ZABOLOTNA Iryna1, NASIBULLIN Boris1, IZHA Anna1, ВADIUK Natalia2, KOIEVA Khrystyna1 Coresponding author: Sergey Gushcha E-mail address: gushchasergey@rambler.ru Balneo Research Journal DOI: http://dx.doi.org/10.12680/balneo.2019.280 Vol.10, No.4, December 2019 p: 450–456 Abstract Possibilities of using natural mineral waters in the treatment of patients with non-alcoholic fatty liver disease GUSHCHA Sergey1, DRAGOMIRETSKA Natalia1, ZABOLOTNA Iryna1, NASIBULLIN Boris1, IZHA Anna1, ВADIUK Natalia2, KOIEVA Khrystyna1 Coresponding author: Sergey Gushcha E-mail address: gushchasergey@rambler.ru 1. State Institution «Ukrainian Scientific-Research Institute of Medical Rehabilitation and Balneology, the Ministry of Public Health of Ukraine», Odessa. 2. State Enterprise Ukrainian Research Institute for Medicine of Transport, the Ministry of Public Health of Ukraine», Odessa. Balneo Research Journal DOI: http://dx.doi.org/10.12680/balneo.2019.280 Vol.10, No.4, December 2019 p: 450–456 1. State Institution «Ukrainian Scientific-Research Institute of Medical Rehabilitation and Balneology, the Ministry of Public Health of Ukraine», Odessa. 2. State Enterprise Ukrainian Research Institute for Medicine of Transport, the Ministry of Public Health of Ukraine», Odessa. 1. State Institution «Ukrainian Scientific-Research Institute of Medical Rehabilitation and Balneology, the Ministry of Public Health of Ukraine», Odessa. 1. State Institution «Ukrainian Scientific Research Institute of Medical Rehabilitation and Balneology, the Ministry of Public Health of Ukraine», Odessa. 2 State Enterprise Ukrainian Research Instit te for Medicine of Transport the Ministr of P blic Health of Ukraine . State Enterprise Ukrainian Research Institute for Medicine of Transport, the Ministry of Public Odessa. Abstract Non-alcoholic fatty liver disease (NAFLD) is a chronic pathology that is increasingly diagnosed in different countries. The pathogenesis of NAFLD associated with insulin resistance, abdominal obesity, atherogenic dyslipidemia, arterial hypertension, endothelial dysfunction, impaired adipokine secretion, that is, components of metabolic syndrome. Treatment of NAFLD should be comprehensive and lengthy, although there are no standardized approaches to the treatment of NAFLD. Meanwhile, drug therapy carries certain risks: the development of serious adverse reactions with prolonged use. The work highlights modern views on the etiology, epidemiology, pathogenesis, drug and non-drug treatment of non-alcoholic fatty liver disease (NAFLD). Experimental and clinical studies on the mechanism of biological action, the effects of using different in composition and mineralization of mineral waters on the course of NAFLD had presented. Based on experimental and clinical studies, ideas about the specificity of the action of mineral waters of various balneological types and mineralization on the clinical course of NAFLD at different stages of the disease, the effect on the functional state of the liver, and the dynamics of lipid and carbohydrate metabolism had detailed. It is concluded that mineral waters could be successfully used in the complex treatment of NAFLD patients. K d l h li f li di i li i d li id i i l p Key words: non-alcoholic fatty liver disease, insulin resistance, dyslipidemia, mineral waters, Introduction y ( ) In general, at the beginning of the XXI century the concentration of “improper lifestyle” factors contributing to the development of NAFLD in the urban population (overeating and unbalanced diet, inadequate physical activity, chronic stress and arterial hypertension, environmental pollution, drug toxicity) was extremely high. This happened against the background of a simultaneous active restructuring of traditional food technologies - a process that accelerated at the beginning of the XXI century and had led to the fact that in the standard diet of the urban population of industrialized countries the content of foods containing vegetable fiber, irreplaceable polyunsaturated fats and antioxidants was sharply reduced and fast food was popularized. Indeed, for countries whose economies are only developing, the common is: NAFLD is partially associated with the pathology of the biliary tract, peptic ulcer, pancreatitis, gastroesophageal reflux disease, irritable bowel syndrome (6, 7). Today, despite the complexity of the etiopathogenesis of NAFLD, many of its mechanisms have already been studied. But the question of the treatment of this disease is still open (14). Treatment of NAFLD should be comprehensive and lengthy, although there are no standardized approaches to the treatment of NAFLD. First of all, therapeutic tactics provide for a modification of lifestyle and drug exposure. Lifestyle modification is aimed at correcting body weight using a hypocaloric diet and adequate physical activity (8, 9, 14). q p y y ( ) The success of drug therapy is associated with the appointment of insulin resistance and statins, ursodeoxycholic acid, essential phospholipids, drugs with antioxidant effects (vitamin E), etc. (7, 11, 14). Meanwhile, drug therapy carries certain risks: the development of serious adverse reactions with prolonged use (for example, aggressive statin therapy with concomitant dyslipidemia), allergic manifestations, polypharmacy, and some of them (for example, vitamin E) can increase mortality from various causes, in particular, from hemorrhagic stroke and prostate cancer. Also, the results of drug therapy are not always satisfactory. All this reduces compliance and adherence to treatment (4,11, 14, 15). - low incomes of the population; - low incomes of the population; - the process of active urbanization has recently begun and the need for more recently the rural population to adapt to the high nervousness of life in the metropolis during the life of 1-2 generations; - urban lithogenic and atherogenic diet; - high levels of toxic pollution of the environment and food. Introduction Non-alcoholic fatty liver disease (NAFLD) is a chronic pathology that is increasingly diagnosed in different countries (1). Depending on the diagnostic method, age, gender, and ethnicity of patients, the frequency of NAFLD in the adult population are from 17 to 46% (2, 3, 4, 5). Moreover, NAFLD is found not only in patients with obesity and metabolic syndrome, where its frequency reaches 60-80% (6) but also in 7% of individuals with normal body weight, mainly in young women with normal levels of liver enzymes (1, 7). According to the latest meta-analysis of 86 clinical studies in 22 countries, the frequency of NAFLD in the general population is 25%, reaching maximum values among the population of the Middle East and South America. It is assumed that by 2030, NAFLD will become the main cause of liver transplantation in developed countries (8). Studies in the Asia-Pacific region have identified a growing prevalence of the European diet, the popularization of fast food, a decrease in the diet of plant foods, an increase in the consumption of meat products and fats by 7 times, which, according to the authors, would leaded to an increase in the prevalence of NAFLD. It is noted that increasingly this pathology acts as a cause of mortality (9). As part of a study conducted by American scientists [8], a model was developed to assess the progression of NAFLD, when the predicted changes in the development of liver cirrhosis associated with NAFLD, progressive liver diseases, and associated mortality had estimated until 2030. According to the results of the analysis, we can expect that the prevalence of NAFLD cases will increase by 21% from 83,300,000 (30% among people over 15 years old and 25.8% among all age groups) in 2015 to 100,900,000 (33.5 and 28.4 %, respectively) in 2030. At the same time, the number of cases of non- alcoholic stenotic hepatitis (NASH) will increase by 63% - from 16.5 to 27 million people. The number of patients with advanced liver disease will increase by 160%, from about 3,300,000 to 7,900,000 by 2030. The incidence of decompensated cirrhosis will increase by 168%, while the incidence of 450 hepatobillary carcinoma - by 137%. It is noted that the growth in mortality from liver diseases in 2030 will be 178% compared to (8). Introduction The same authors came to the conclusion that in order to reduce the burden of the disease, strategies are needed to slow down the growth of cases of diseases, as well as to improve therapeutic options, because while maintaining high rates of prevalence of obesity and type II diabetes in adults, as well as taking into account the aging population, morbidity and mortality from NAFLD in the US will increase (8). In general, at the beginning of the XXI century the concentration of “improper lifestyle” factors contributing to the development of NAFLD in the urban population (overeating and unbalanced diet, inadequate physical activity, chronic stress and arterial hypertension, environmental pollution, drug toxicity) was extremely high. This happened against the background of a simultaneous active restructuring of traditional food technologies - a process that accelerated at the beginning of the XXI century and had led to the fact that in the standard diet of the urban population of industrialized countries the content of foods containing vegetable fiber, irreplaceable polyunsaturated fats and antioxidants was sharply reduced and fast food was popularized. Indeed, for countries whose economies are only developing, the common is: hepatobillary carcinoma - by 137%. It is noted that the growth in mortality from liver diseases in 2030 will be 178% compared to (8). The same authors came to the conclusion that in order to reduce the burden of the disease, strategies are needed to slow down the growth of cases of diseases, as well as to improve therapeutic options, because while maintaining high rates of prevalence of obesity and type II diabetes in adults, as well as taking into account the aging population, morbidity and mortality from NAFLD in the US will increase (8). distribution, type 2 diabetes mellitus, atherogenic dyslipidemia. There is growing evidence that NAFLD is a multi- systemic disease that increases the risk of developing not only type 2 diabetes mellitus (DM) and cardiovascular disease, but also osteoporosis, hypogonadism, hypothyroidism, polycystic ovary syndrome, kidney pathology, etc. (3 6, 8). The pathogenesis of NAFLD associated with insulin resistance, abdominal obesity, atherogenic dyslipidemia, arterial hypertension, endothelial dysfunction, impaired adipokine secretion, that is, components of metabolic syndrome . Introduction Of all the hormones in this regard, most researchers note the special role of serotonin. Analysis of the obtained experimental data showed that after a course of taking MW, along with other hormones, the basal level of serotonin rises by almost 75%. In this case, similarly to insulin, the early phase of serotonin secretion is stimulated. In general, an increase in the general nonspecific resistance of the organism as a result of the course of exposure to mineral water is achieved not only by activating hormones of the intestinal hormonal system, but also by adaptive restructuring of the activity of hormonal systems of higher levels of biological integration, where activation of the early phase of insulin and serotonin secretion is decisive (17, 21). Numerous experimental and clinical studies have proven the ability of MW of various composition and mineralization to stimulate the production of intestinal and pancreatic hormones (17, 18). These studies allow us to consider the role of gastrin as a pacemaker, which triggers all the sequential regulatory processes of the gastrointestinal tract, and glucagon - is a hormone that enhances the level of metabolic processes. Besides, together with other hormones, they perform adaptive functions. Already a single intake of MW causes a whole cascade of hormonal reactions due to a certain sequence and relationship. The beginning of the multi-chain reaction is the entero-insular axis: enteric signals to islet cells are ahead of signals from the internal environment of the body (19). ( ) In experimental studies of Reps V.F., dedicated to the justification of the therapeutic and prophylactic use of drinking mineral waters for impaired liver function, it was convincingly proved that the pathogenic effects of aggressive and toxic factors have a powerful effect on energy metabolism in the liver with subsequent systemic metabolic disorders, which are the disintegration of the insulin mechanism of regulation of carbohydrate metabolism due to changes in the activity of transport membrane enzymes in hepatocytes, enhancement of lipid peroxidation (LPO) and the further development of dyslipidemia and formation of fatty liver (22). Mineral waters act on the digestive organs and the body directly (contact, directly, quickly), mobilize homeostatic systems from molecular to a higher level of biological integration and affect the pathological process. MW act “indirectly” from the gastroenteropancreatic endocrine system, acting on the endocrine, paracrine and neuroendocrine channels of regulation. Introduction Analysis of the obtained experimental data showed that after a course of taking MW, along with other hormones, the basal level of serotonin rises by almost 75%. In this case, similarly to insulin, the early phase of serotonin secretion is stimulated. In general, an increase in the general nonspecific resistance of the organism as a result of the course of exposure to mineral water is achieved not only by activating hormones of the intestinal hormonal system, but also by adaptive restructuring of the activity of hormonal systems of higher levels of biological integration, where activation of the early phase of insulin and serotonin secretion is decisive (17, 21). In experimental studies of Reps V.F., dedicated to the justification of the therapeutic and prophylactic use of drinking mineral waters for impaired liver Recent years have proved the fundamental possibility of drinking mineral water (MW) to influence the course of metabolic processes in lipid and carbohydrate metabolism disorders in patients of different nosological groups, including those with metabolic syndrome, which is often associated with NAFLD (16]) Studies of the regulatory effects of MW on the activity of the gastrointestinal tract have established the presence of important phenomena: the first is an increase in the sensitivity of pancreatic beta cells to the stimulating effects of MW. The second - the maximum rise in insulin after a course of taking MW occurs not at the 15th minute, as in the initial state, but already on the 5th. The biological significance of this phenomenon can be figuratively compared with the “early warning device,” since it is the usefulness of the early phase of insulin secretion that creates the conditions for the optimal course of postprandial metabolic reactions. According to modern concepts, the name "mineral water" refers to groundwater that has a therapeutic effect on the human body, due to the increased content of useful biologically active components, their ionic and gas composition, and the general ion- salt composition of water. MW are not only complex multicomponent anionic cationic solutions, but they also have a diverse composition and different mineralization, which makes it possible to vary the drinking treatment depending on the phase of the disease, the severity of the pathological process and associated pathology. p p The third phenomenon is directly related to increasing the duration and quality of human life. Introduction All this, along with the high steatogenicity of the modern urban diet (typical for the USA, for example) leads to the rapid development of liver steatosis, as the base of NAFLD and its subsequent stages (10 -14). Further growth of NAFLD and non-alcoholic NASH is found in all racial and ethnic groups of the countries of the world, increasing hepatic and cardiovascular morbidity and mortality. Analysis of mortality of NAFLD patients identified three main causes: cardiovascular events (13–38%), malignant neoplasms (6–28%) and liver pathology (2.8–19.0%) (1, 2, 14,15). Summing up the cited material, we can conclude that, despite the current progress in the treatment of NAFLD patients, there are still many open questions. This stimulates the search for new non- drug treatment technologies for NAFLD aimed at developing differentiated methods of rehabilitation treatment of patients of this nosological form using natural and preformed physical factors because now The traditional risk factors for developing NAFLD include: eating high-calorie foods, a sedentary lifestyle, obesity with a visceral type of fat 451 there is no single conceptual approach to such treatment of NAFLD patients. The course intake of MW due to the general training effect causes a long-term restructuring of the pituitary-adrenal and other systems, as well as mineral metabolism, which leads to an increase and improvement of the regulatory abilities of the body (5). effect causes a long term restructuring of the pituitary-adrenal and other systems, as well as mineral metabolism, which leads to an increase and improvement of the regulatory abilities of the body (5). Studies of the regulatory effects of MW on the activity of the gastrointestinal tract have established the presence of important phenomena: the first is an increase in the sensitivity of pancreatic beta cells to the stimulating effects of MW. The second - the maximum rise in insulin after a course of taking MW occurs not at the 15th minute, as in the initial state, but already on the 5th. The biological significance of this phenomenon can be figuratively compared with the “early warning device,” since it is the usefulness of the early phase of insulin secretion that creates the conditions for the optimal course of postprandial metabolic reactions. The third phenomenon is directly related to increasing the duration and quality of human life. Of all the hormones in this regard, most researchers note the special role of serotonin. Introduction So, the mechanism of action of drinking mineral waters is associated not only with the accumulation of ions, but with their effect on the endocrinocytes of the intestinal hormonal system, which forms urgent and long-term adaptive reactions that mediate the functioning reserves of both regulatory units and various organs and the whole organism (20). In experimental modeling of pathological conditions, the course intake of drinking mineral 452 of dyslipidemia and related diseases of the cardiovascular system. of dyslipidemia and related diseases of the cardiovascular system. According to the data (23), the use of chloride- bicarbonate sodium low-mineralized mineral water with different humic acids for 21 days in animals with experimental hepatitis was accompanied by a significant improvement in the detoxification function of the liver, an increase in basal metabolism, a decrease in inflammatory changes, normalization of liver enzymes, and an increase in protein- synthesizing function, which occurred parallel to the positive dynamics of the morphological changes of the organ. Numerous experimental and clinical studies have proven the versatility of the therapeutic effect of MW (5, 20). MW can influence the regulation of the central brain structures, tissue respiration, stimulate the enteroinsular axis and release gastrointestinal hormones, enhance the function of the gastric glands, the regeneration of the gastric mucosa, normalize its motor and evacuation functions, restore the metabolism of hepatocytes, provide an immunoregulatory effect, stimulate processes bile formation, bile secretion and pancreatic secretion, harmonize relationships in the peroxidation system of lipids and antioxidant system. These general mechanisms underlie the therapeutic effects of a drinking cure. In recent years a small number of works have water has a stimulating effect on insulin secretion, inhibits lipid peroxidation processes, increasing AOS power, and normalizes the activity of transport ATPases in the liver cells. The dependence of the influence of mineral waters of various salinity on the course of the pathological process depending on its severity was demonstrated (22). According to the data (23), the use of chloride- bicarbonate sodium low-mineralized mineral water with different humic acids for 21 days in animals with experimental hepatitis was accompanied by a significant improvement in the detoxification function of the liver, an increase in basal metabolism, a decrease in inflammatory changes, normalization of liver enzymes, and an increase in protein- synthesizing function, which occurred parallel to the positive dynamics of the morphological changes of the organ. Introduction A concept has been formed on the mechanism of the optimizing effect of mineral waters on hormonal- enzymatic regulation of metabolism, which consists inactivating a certain sequence of reactions: in the first minutes, lipid peroxidation in hepatocyte membranes is enhanced with the simultaneous mobilization of glucose, then (up to the 30th minute) against the background of increase in peak In the early phase of insulin increment, processes of active glucose transport through the cell membrane and its utilization in the cell along the pentose phosphate pathway are enhanced. The cycle of these reactions ends with an increase in the level of free fatty acids, which indicates an increased use of lipids as energy substrates (17, 19). p g g g Numerous experimental and clinical studies have proven the versatility of the therapeutic effect of MW (5, 20). MW can influence the regulation of the central brain structures, tissue respiration, stimulate the enteroinsular axis and release gastrointestinal hormones, enhance the function of the gastric glands, the regeneration of the gastric mucosa, normalize its motor and evacuation functions, restore the metabolism of hepatocytes, provide an immunoregulatory effect, stimulate processes bile formation, bile secretion and pancreatic secretion, harmonize relationships in the peroxidation system of lipids and antioxidant system. These general mechanisms underlie the therapeutic effects of a drinking cure. It has been shown that an increase in the efficiency of metabolic processes during the intake of mineral waters occurs due to the activation of cortisol-insulin interaction, phase changes in the activity of the free radical oxidation system and transmembrane transfer of metabolites. g In recent years, a small number of works have appeared that prove the effectiveness of the course drinking intake of MW in patients with NAFLD and associated diseases and conditions. At the same time, mineral waters of different composition (mineral waters of the "Esentuki", "Morshin" type, with a high content of organic substances - such as "Naftusya") provide unidirectionality, a similar effect of varying degrees of expression. Stabilization of carbohydrate metabolism through normalization of the physiological profile of insulin secretion, a decrease in insulin resistance, a decrease in dyslipidemia, a significant improvement in the basic functions of the liver and its hemodynamics were noted (24, 25). Studies conducted by Yu. Gerasimenko et al. Confirm the positive effect of various MW on metabolic processes in patients with type 2 diabetes mellitus (26). Introduction At the same time, the long-term results of this study (after 1 year) are noteworthy, when in patients who additionally took MW in the treatment complex, the number of days of temporary disability decreased by 2.5 times, the number of exacerbations decreased by 1.7 times, and the longer (8-12 months) a stable period of remission was observed in 90% of patients (28). 0.4 kg when taking Essentuki No. 4 ). Conclusions. Therefore, it can be argued that the mineral waters in the complex treatment of NAFLD can have a significant effect on the metabolism of lipids and carbohydrates, the restoration of the functional state of the liver. Meanwhile, the above studies are scattered and do not form a general idea of the differentiated purpose of mineral waters, depending on the stage of the underlying disease, metabolic disorders, and concomitant diseases of the digestive system. Existing data also do not answer the question about the specificity of the influence of mineral water of different composition and mineralization on the course of NAFLD. All of the above proves the importance of studying the effect of mineral water of different chemical composition and mineralization on the course of NAFLD in the experiment and, further, in clinical studies, to prevent the progression of the underlying disease and reduce cardiometabolic risk. g g ) Conclusions. Therefore, it can be argued that the mineral waters in the complex treatment of NAFLD can have a significant effect on the metabolism of lipids and carbohydrates, the restoration of the functional state of the liver. Meanwhile, the above studies are scattered and do not form a general idea of the differentiated purpose of mineral waters, depending on the stage of the underlying disease, metabolic disorders, and concomitant diseases of the digestive system. Existing data also do not answer the question about the specificity of the influence of mineral water of different composition and mineralization on the course of NAFLD. The use of a low-mineralized hydro carbonate calcium-sodium MW “ Zapovedniy source” in combination with physical activity for 21-24 days in people with metabolic syndrome led to a significant, 42% decrease in insulin resistance according to the NOMA index, along with a possible decrease in the concentration of triglycerides and atherogenic coefficient (p <0.05) (29). Introduction All of the above proves the importance of studying the effect of mineral water of different chemical composition and mineralization on the course of NAFLD in the experiment and, further, in clinical studies, to prevent the progression of the underlying disease and reduce cardiometabolic risk. References 1. Younossi ZM, Marchesini G, Pinto-Cortez H, the concentration of total cholesterol, LDL and the atherogenic coefficient (p <0.05) (30). The effectiveness of the internal course application of mineral waters of the "Essentuki" type in the treatment of NAFLD, including with simultaneous type 2 diabetes mellitus, has been convincingly demonstrated (31, 32). The improvement of the functional state of the liver, indicators of hepatic hemodynamics, normalization of the lipid spectrum of the blood, peroxide homeostasis, weight loss was established. The normalization of the secretion of adiponectin, leptin and a decrease in insulin resistance under the influence of these mineral waters have been proven (19). At the same time, MW “Essentuki” No. 4 (medium-mineralized carbonic acid, hydro carbonate-chloride sodium MW) had a more pronounced insulinotropic effect, and “Essentuki New” (low-mineralized carbonic acid-hydro carbonate-sulphate-sodium chloride- calcium) contributed to greater weight loss (3.5 ± 0.4 kg) taking “Essentuki New” versus 2.3 ± 0.4 kg when taking “Essentuki No. 4”). g y A study of the effectiveness of the average mineralized sulfuric magnesium-sodium MW of the Morshin resort (source No. 6) in patients with type 2 diabetes mellitus while taking metformin and dietary support indicate a decrease in glycemia by 1.4 times (in the control - 1.2 times), possible a decrease in the level of glycosylated hemoglobin (after 3 months there was no decrease in the control), a decrease in insulin resistance (p <0.05). The above changes were accompanied by normalization of ALT and AST levels (p <0.05), which did not occur in the comparison group (27). A study of the effects of weakly carbonic, weakly mineralized hydro carbonate-magnesium-calcium MW of the Tibskoye field in the complex treatment of patients with NAFLD at the stationary stage showed an improvement in the clinical course of the disease, restoration of the functional state of the digestive system and, especially, a decrease in the levels of interleukin-6 and interleukin-8, peroxidation products lipids compared with the control. Introduction Existing dat the question about the specific mineral water of differen mineralization on the course of All of the above proves the im the effect of mineral water o composition and mineralizatio NAFLD in the experiment an studies, to prevent the progress disease and reduce cardiometab References . Younossi ZM, Marchesin Petta S. Epidemiology of n pronounced effect was exerted by MW, elimination of glucosuria and acetonuria. A similar trend was observed in lipid metabolism when there was a significant decrease in total cholesterol and triglycerides. However, in terms of lipid metabolism, “Timan” MW had a more pronounced therapeutic effect, and a more pronounced decrease in body weight occurred with the course application of “Zvenigorodskaya” MW. the concentration of total cholesterol, LDL and the atherogenic coefficient (p <0.05) (30). The effectiveness of the internal course application of mineral waters of the "Essentuki" type in the treatment of NAFLD, including with simultaneous type 2 diabetes mellitus, has been convincingly demonstrated (31, 32). The improvement of the functional state of the liver, indicators of hepatic hemodynamics, normalization of the lipid spectrum of the blood, peroxide homeostasis, weight loss was established. The normalization of the secretion of adiponectin, leptin and a decrease in insulin resistance under the influence of these mineral waters have been proven (19). At the same time, MW “Essentuki” No. 4 (medium-mineralized carbonic acid, hydro carbonate-chloride sodium MW) had a more pronounced insulinotropic effect, and “Essentuki New” (low-mineralized carbonic acid-hydro carbonate-sulphate-sodium chloride- calcium) contributed to greater weight loss (3.5 ± 0.4 kg) taking “Essentuki New” versus 2.3 ± 0.4 kg when taking “Essentuki No. 4”). Conclusions. Therefore, it can be argued that the mineral waters in the complex treatment of NAFLD can have a significant effect on the metabolism of lipids and carbohydrates, the restoration of the functional state of the liver. Meanwhile, the above studies are scattered and do not form a general idea of the differentiated purpose of mineral waters, depending on the stage of the underlying disease, metabolic disorders, and concomitant diseases of the digestive system. Existing data also do not answer the question about the specificity of the influence of mineral water of different composition and mineralization on the course of NAFLD. Introduction Low-mineralized MW with a high content of organic substances “Timan”, low-mineralized sulfate-calcium-magnesium MW “Zvenigorodskaya” and medium-mineralized sulfate-bicarbonate-magnesium MW “Donat Mg” had a unidirectional effect to reduce the level of glycemia, and the higher the glycemia, the more a In the mechanisms of therapeutic and prophylactic action of mineral waters, one of the central places belongs to an increase in the power of antioxidant protection due to the optimization of metabolic reactions. It has been established that the insulin stimulating effect of mineral waters is directly related to their ability to inhibit lipid peroxidation (5, 20). In studies conducted by N.D. Polushin and Topuria D.I. it was found that in experimental animals that received a course of mineral waters in the resort of Essentuki, the effect of various poisons on the liver is noticeably (2-3 times) (18). These primary preventive effects occur against the background of optimization of the insulin regulation of metabolic reactions and are directly related to them. The ability of the mineral waters of the Essentuki resort to optimize metabolic reactions by activating the early phase of insulin secretion during the early phase of the digestive cycle can and should be widely used to prevent the metabolic syndrome, in the pathogenesis of which the central place belongs to the disruption of the interaction of insulin with receptors on the cell membrane, which provokes the gradual development 453 the concentration of total cholesterol, LDL and the atherogenic coefficient (p <0.05) (30). the concentration of total chol atherogenic coefficient (p <0.05 The effectiveness of the intern of mineral waters of the "Es treatment of NAFLD, includin type 2 diabetes mellitus, ha demonstrated (31, 32). The functional state of the liver, hemodynamics, normalization of the blood, peroxide homeos established. The normalization adiponectin, leptin and a resistance under the influenc waters have been proven (19 MW “Essentuki” No. 4 carbonic acid, hydro carbon MW) had a more pronounced and “Essentuki New” (low-m acid-hydro carbonate-sulpha calcium) contributed to greate 0.4 kg) taking “Essentuki New 0.4 kg when taking “Essentuki Conclusions. Therefore, it ca mineral waters in the complex can have a significant effect o lipids and carbohydrates, th functional state of the liver. M studies are scattered and do no of the differentiated purpose depending on the stage of th metabolic disorders, and conco digestive system. References 1. 1. Younossi ZM, Marchesini G, Pinto-Cortez H, Petta S. Epidemiology of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis: implications for liver transplantation // Transplantation. 2019;103(1):22–27. doi: 10.1097/TP.0000000000002484. The study of the effect of low-mineralized sulfate- bicarbonate magnesium-calcium MW “Narzan” in the complex of treatment of patients with coronary heart disease (CHD) showed a clear effect on reducing dyslipidemia, in particular, a decrease in 2. Nseir W, Hellou Е, Assy N. Role of diet and lifestyle changes in nonalcoholic fatty liver disease. World J Gastroenterol. 2014 Jul 28; 454 9338–9344. 2005;142(1):37–46. doi: 10.7326/0003-4819-142- 1-200501040-00110. 10.1177/1535370215579161. 13. Pastori D, Polimeni I, Baratta F, Pani A, Del Ben M, Angelico F.The efficacy and safety of statins for the treatment of nonalcoholic fatty liver disease. Dig. Liver Dis. 2015;47(1):4–11. doi: 10.1016/j.dld.2014.07.170. 4. Lonardo А, Nascimbeni F, Maurantonio М, Marrazzo А, Rinaldi L, Adinolfi LE. Nonalcoholic fatty liver disease: Evolving paradigms. World J Gastroenterol. 2017 Sep 28; 23(36): 6571–6592. doi: 10.3748/wjg.v23.i36.657.1. 14. EASL-EASD-EASO Clinical Practice Guidelines for the management of non-alcoholic fatty liver disease. J. Hepatology. 2016;64(6):1388–1402. DOI: 10.1016/j.jhep.2015.11.004. Š 5. Iqbal U, Perumpail BJ., Akhtar D, Kim D, Ahmed A. The Epidemiology, Risk Profiling and Diagnostic Challenges of Nonalcoholic Fatty Liver Disease. Medicines (Basel). 2019 Mar; 6(1): 41. doi:10.3390/medicines6010041. 15. Milić S, Štimac D. Nonalcoholic fatty liver disease/steatohepatitis: epidemiology, pathogenesis, clinical presentation, treatment. Dig Dis 2012;30(2):158–162. doi: 10.1159/000336669. 6. Zvenigorodskaya LA, Mkrtumyan AM, Shinkin NV, Nilova TV, Petrakov AV. Misheni metabolicheskogo tandema: nealkogolnaya zhirovaya bolezn pecheni i saharnyj diabet 2 tipa. Medicinskij sovet Targets of the metabolic tandem: non-alcoholic fatty liver disease and type 2 diabetes mellitus. Medical advice. 2017;20:20– 25. https://doi.org/10.21518/2079-701X-2017-20- 20-25. 2005;142(1):37–46. doi: 10.7326/0003-4819-142- 1-200501040-00110. 12. Nouredding M, Mato JM, Lu SC. Nonalcoholic fatty liver disease: Update on pathogenesis, diagnosis, treatment and the role of S- adenosylmethionine // Exp. Biol.Med. 2015;240(6):809–820. doi: 10.1177/1535370215579161. 3. Pavlov ChS., Kuznetsova ЕA, Arslanyan MG, Semenistaya MCh, Glushenkov DV, Nikolenko VN. Non-alcoholic fatty liver disease: modern concepts of etiology, pathogenesis, diagnostics and treatment. Medical news of north caucasus 2017. Vоl. 12. Iss. 2. Р. 230 – 234. https://doi.org/10.14300/mnnc.2017.12066. 10.1159/000336669. 16. Mineralni vodi Ukrayini / Za red. EO. Kolesnika, KD. Babova. Mineral waters of Ukraine / Ed. EO. Kolesnik, KD. Babov. — К.: Kupriyanov, 2005. — 576 с. 17. Efimenko NV, Mehanizmy dejstviya pitevyh mineralnyh vod i ih rol v kurortnoj gastroenterologii. Kurortnaya medicina. The mechanisms of action of drinking mineral waters and their role in spa gastroenterology. Spa medicine. 2015;3:2–7. http://www.gniik.ru/files/kur_medicina3_2015.pd f. 7. Harchenko NV, Fadeenko GD, Skripnik IN, Kurinnaya EG. Proceedings of the International Liver Disease Congress of the European Association for the Study of the Liver. Modern gastroenterology. 2014;3:107–112. 8. Younossi CD, Koening AB, Abdelatif D, Fazel Y, Henry L, Wymer M. Global epidemiology of non-alcoholic fatty liver disease – Meta-analitic assessment of prevalence incidence and outcomes. Hepatology. 2016;64 (1):73–84. doi: 10.1002/hep.28431. 18. Zhernov VA, Frolkov VK, Zubarkina MM. [The mechanisms underlying the therapeutic effects of reflexotherapy and drinking mineral waters in the patients presenting with metabolic syndrome]. Vopr Kurortol Fizioter Lech Fiz Kult. 2017;94(2):36–41. doi: 10.17116/kurort201794236-41. 9. Byrne CD, Targher G. NAFLD: a multisystem disease. J. Hepatology. 2015;62(1):47–64. doi: 10.1016/j.jhep.2014.12.012. 19. Botvineva LA, Nikitin EN, Melnikova LN, Akaeva EA. [Drinking mineral water and a diet with a high content of dietary fiber in the treatment of patients with type 2 diabetes]. Vopr Kurortol Fizioter Lech Fiz Kult. 2010;2:13–16. 10. Guo Y, Xiong Y, Sheng Q, Zhao S, Wattacheril J, Flynn CR. A micro-RNA expression signature for human NAFLD progression. J. Gastroenterol. 2016;51(10):1022–1030. doi: 10.1007/s00535- 016-1178-0. 20 20. Mineralni vodi Poltavshini / Za red. K.D Babova, O.M. Nikipelovoyi, O.D. Gavlovskogo. Mineral waters of Poltava region / Ed. KD Babova, OM Nikipelova, OD Gavlovsky.— Kiev: KIM, 2010: 220 р. 11. Miller ER, Pastor-Barriuso R, Dalal D, Riemersmara RА, Appel LJ, Guallar E. Meta- analysis: high-dosage vitamin E supplementation may increase all-cause mortality. Ann Intern Med 455 21. Fizioterapiya i kurortologiya / pod red. V.M. Bogolyubova. Kniga I Physiotherapy and balneology / Ed. V.M. Bogolyubova. Book I.— М.: BIONOM Publisher, 2008. — 408 с. 27. Mishchuk VG, Mishchuk AV, Diba SG. Efektivnist reabilitacijnogo likuvannya hvorih na cukrovij diabet 2 tipu ta jogo vpliv na pokazniki lipidnogo spektru krovi i funkcionalnij stan pechinki // Medichna reabilitaciya, kurortologiya ta fizioterapiya. The effectiveness of rehabilitation treatment of patients with type 2 diabetes mellitus and its effect on the lipid spectrum of the blood and the functional state of the liver // Medical Rehabilitation, Balneology and Physiotherapy. 2014;1:23–27. 22. Reps V.F. 10.1159/000336669. Metabolicheskie mehanizmy lechebno- profilakticheskogo dejstviya pitevyh mineralnyh vod // Ministerstvo zdravoohraneniya Rossijskoj Federacii. Pyatigorskij gosudarstvennyj nauchno- issledovatelskij institut kurortologii. Metabolic mechanisms of therapeutic and prophylactic action of drinking mineral waters // Ministry of Health of the Russian Federation. Pyatigorsk State Scientific Research Institute of Balneology - Pyatigorsk: Publishing House of PGGLU, 2001: 176 р. 28. Efimenko NV, Kajsinova AS, Mercaeva ZV. i dr. Mineralnye vody v reabilitacii bolnyh s nealkogolnymi porazheniyami pecheni na stacionarnomu etape // Voprosy kurortologi, fizioterapii i lechebnojfizicheskojkultury. Mineral waters in the rehabilitation of patients with non- alcoholic liver lesions at the stationary stage // Problems of balneology, physiotherapy and physical therapy. 2012;1:17–20. 23. Verigo NS, Ulashik VS. Gepatotropnoe dejstvie soderzhashej guminovye kisloty hloridno- gidrokarbonatnoj natrievoj mineralnoj vody (ekperimentalnoe issledovanie). Voprosy kurortologii, fizioterapii i LFK. Hepatotropic action of humic acids containing chloride- hydrocarbonate sodium mineral water (experimental study). Problems of balneology, physiotherapy and physical therapy. 2015;1:37– 42. 29. Frolkov VK., Mihajlyuk OV. Prirodnye i fizicheskie faktory v korrekcii obmela veshestv u pacientov s metbolicheskim sindromom. // Fizioterapiya, balneologiya i reabilitaciya. Natural and physical factors in the correction of substances in patients with metabolic syndrome. // Physiotherapy, balneology and rehabilitation. 2014;4:11–14. (In Russ.). 24. Efimenko NV, Kaĭsinova AS, Fedorova TE, Botvineva LA. The effectiveness of the spa and health resort-based treatment with the application of Essentuki-type drinking mineral waters for the management of non-alcoholic fatty liver disease in the patients presenting with type 2 diabetes mellitus.Vopr Kurortol Fizioter Lech Fiz Kult. 2015 May-Jun; 92(3):14–17. doi: 10.17116/kurort2015314-17. 30. Leonchuk AL, Merkulova GA. Korrekciya dislipidemii u bolnyh IBS pri sanatorno- kurortnom lechenii // Voprosy kurortologii, fizioterapii i lechebnoj fizicheskoj kultury. Correction of dyslipidemia in patients with coronary artery disease during spa treatment // Problems of balneology, physiotherapy and physical therapy. 2012;4:8–9. (In Russ.). 25. Shestopalov VM, Moiseeva NP, Ishenko AP, Kondratyuk EI, Usov VYu. Lechebnye mineralnye vody tipa «Naftusya» Ukrainskih Karpat i Podolya:[monografiya. Medicinal mineral waters of the type "Naftusia" of the Ukrainian Carpathians and Podolia: [monograph]. - Kyiv: Buкrek, 2013 - Київ: Букрек, 2013: 508 р. 31. 31. Demchenko VP, Efimenko NV, Fedorova TE, Fedorov SL, Markus MN. Effektivnost kurortnoj terapii s primeneniem pitevyh mineralnyh vod essentukskogo tipa pri lechenii metabolicheskih porazhenij pecheni u bolnyh saharnym diabetom 2-go tipa. // Fizioterapiya, balneologiya i reabilitaciya. 10.1159/000336669. The effectiveness of spa therapy using drinking mineral waters of the Essentuki type in the treatment of metabolic lesions of the liver in patients with type 2 diabetes. // Physiotherapy, balneology and rehabilitation. 2013;6:50–51. (In Russ.). 26. Gerasimenko Yu.A., Britov AI, Chkheidze AP, Gerasimenko M.Yu. Sravnitelnaya effektivnost pitevyh mineralnyh vod u bolnyhsaharnym diabetom 2 tipa v sanatorno-kurortnom lechenii // Fizioterapiya, balneologiya,reabilitaciya. Comparative effectiveness of drinking mineral waters in patients with type 2 diabetes mellitus in spa treatment // Physiotherapy, balneology, rehabilitation. 2006;2:29–32. 32 32. Frolkov VK. New ideas about the mechanisms of therapeutic and prophylactic action of mineral waters. Klinicheskaja medicina i farmakologija. 2015;(4):34–38. (In Russ.). 456
https://openalex.org/W4323967099	http://journal.thamrin.ac.id/index.php/jkmp/article/download/1196/pdf	Indonesian	null	Pembuatan Dawet Daun Kelor (Moringa Oleifera L.), Daya Terima dan Peluangnya Sebagai Pangan Bernutrisi	Jurnal Kesehatan Masyarakat Perkotaan	2,021	cc-by	4,315	Abstrak Dawet mudah dibuat dan dapat dikreasikan dengan berbagai macam bahan serta modal yang tidak terlalu banyak, sehingga dawet dapat dimodifikasikan dengan bahan yang mempunyai nilai gizi yang akan membuat mutu dawet yang dihasilkan dapat menjadi lebih tinggi. Adapun Tujuan dari penelitian ini adalah untuk Mengetahui pengaruh penambahan daun kelor terhadap sifat organoleptik dan daya terima dawet. Penelitian ini merupakan jenis penelitian eksperimental yang bertujuan untuk mengetahui pengaruh penambahan daun kelor terhadap sifat organoleptik produk dawet daun kelor dilakukan di Laboratorium Gizi Universitas MH Thamrin. Rancangan yang digunakan dalam penelitian ini adalah Rancangan Acak Lengkap dengan 3 perlakuan dan 2 kali pengulangan. Ada pengaruh penambahan daun kelor terhadap aspek warna, rasa, aroma, dan tekstur pada dawet daun kelor. Penambahan daun kelor pada tingkat kesukaan aspek rasa lebih disukai pada produk dengan penambahan daun kelor sebanyak 35%. Pada tingkat kesukaan aspek warna, aspek aroma, dan aspek tekstur lebih disukai pada produk dengan penambahan daun kelor sebanyak 50%. Produk yang lebih disukai oleh panelis adalah produk dengan penambahan daun kelor sebanyak 50%. Kata kunci: Dawet, Daun Kelor, Nutrisi Kata kunci: Dawet, Daun Kelor, Nutrisi Abstract Dawet is easy to make and can be created with a variety of materials and not too much capital, so that dawet can be modified with ingredients that have nutritional value which will make the quality of the resulting dawet higher. The purpose of this study was to determine the effect of adding Moringa leaves to the organoleptic properties and acceptability of dawet. This research is an experimental research that aims to determine the effect of adding Moringa leaves to the organoleptic properties of Moringa leaf dawet products carried out at the Nutrition Laboratory of the University of MH Thamrin. The design used in this study was a completely randomized design with 3 treatments and 2 repetitions. There is an effect of the addition of Moringa leaves on aspects of color, taste, aroma, and texture in Moringa leaf dawet. The addition of Moringa leaves at the level of preference for the taste aspect is preferable to the product with the addition of Moringa leaves as much as 35%. At the level of preference, the color aspect, the aroma aspect, and the texture aspect were preferred to the product with the addition of 50% Moringa leaves. The product preferred by the panelists is the product with the addition of 50% Moringa leaves. Keywords: Dawet, Moringa Leaves, Nutrition Pembuatan Dawet Daun Kelor (Moringa Oleifera L.), Daya Terima dan Peluangnya Sebagai Pangan Bernutrisi Parlin Dwiyanaˡ) *), Fadhillah Miftahul2) 1)2)Program Studi Gizi, Fakultas Kesehatan, Universitas Mohammad Husni Thamrin Correspondence Author: pdwijana70@gmail.com DOI: https://doi.org/10.37012/jkmp.v1i2.1196 Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 PENDAHULUAN Dawet adalah minuman khas Indonesia yang berasal dari Banjarnegara, Jawa Tengah biasa dikonsumsi bersama dengan santan, larutan gula merah, dan es serut. Jajanan ini mempunyai rasa yang manis dan diminati banyak kalangan mulai dari anak-anak hingga orang dewasa. 56 Open Journal System (OJS): journal.thamrin.ac.id http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 Dawet dapat dibuat dari tepung kanji, tepung beras atau tepung hunkue. Dawet mudah dibuat dan dapat dikreasikan dengan berbagai macam bahan serta modal yang tidak terlalu banyak, sehingga dawet dapat dimodifikasikan dengan bahan yang mempunyai nilai gizi yang akan membuat mutu dawet yang dihasilkan dapat menjadi lebih tinggi. Penelitian yang dilakukan oleh Andriyani et al. pada tahun 2015, Ni Putu Ayu pada tahun 2018, serta Sholiha pada tahun 2019 sudah membuktikan bahwa dawet dapat dimodifikasi dengan penambahan beberapa bahan seperti ceker ayam, rumput laut, dan tepung daun torbangun. Dari penelitian tersebut dapat dilihat bahwa nilai gizi dawet dapat bertambah dengan penambahan bahan-bahan yang bernilai gizi. Dawet yang selama ini masyarakat kenal terbuat dari tepung beras yang diberi tambahan daun pandan atau daun suji sebagai bahan pewarna. Penggunaan warna hijau pada daun pandan dan daun suji dalam proses pembuatan dawet dapat digantikan dengan sayuran yang mempunyai warna hijau yang mempunyai nilai gizi lebih baik, salah satunya adalah daun kelor. Daun Kelor dikenal di seluruh dunia sebagai tanaman bergizi dan WHO telah memperkenalkan kelor sebagai salah satu pangan alternatif untuk mengatasi masalah gizi (malnutrisi) (Broin, 2010). Namun, di Indonesia pemanfaatan daun kelor masih belum banyak, umumnya hanya dikenal sebagai salah satu menu sayuran. Di negara Senegal dan Haiti, daun kelor diberikan untuk mengatasi masalah gizi buruk pada anak-anak dan wanita hamil serta menyusui. Daun kelor sebagai sumber vitamin dan mineral dapat dikonsumsi dengan cara dimasak, dimakan mentah, atau dikeringkan menjadi serbuk daun kelor. Selain itu, daun kelor memiliki kandungan protein yang tinggi (Krisnadi, 2015). Daun kelor mengandung vitamin A 6.8 mg, 4 kali lebih banyak dibandingkan dengan vitamin A yang terkandung dalam wortel. Vitamin C yang terkandung dalam daun kelor yaitu 220 mg, 7 kali lebih tinggi dibandingkan dengan vitamin C pada buah jeruk. Kalsium 4 kali lebih banyak dibandingkan dengan susu tinggi kalsium sekitar 440 mg per 100 gram. Kalium pada daun kelor 259 mg, 3 kali lebih banyak dibandingkan dengan buah pisang. Open Journal System (OJS): journal.thamrin.ac.id http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf METODE PELAKSANAAN Penelitian ini merupakan jenis penelitian eksperimental yang bertujuan untuk mengetahui pengaruh penambahan daun kelor terhadap sifat organoleptik produk dawet daun kelor dilakukan di Laboratorium Gizi Universitas MH Thamrin. Rancangan yang digunakan dalam penelitian ini adalah Rancangan Acak Lengkap dengan 3 perlakuan dan 2 kali pengulangan. Tujuan 3 perlakuan dalam penelitian ini untuk mengetahui sifat organoleptik serta daya terima dawet dengan penambahan daun kelor. Sampel yang akan diujikan diberikan kode masing-masing agar memudahkan panelis dalam mengisi form uji. Pengkodean dilakukan secara acak, sampel diletakkan mulai dari kode random terendah. PENDAHULUAN Protein dalam daun kelor 6.7 gram, 2 kali lebih banyak daripada protein dalam sebutir telur atau yoghurt, dan zat besi 25 kali jauh lebih tinggi dibandingkan dengan bayam, serta mengandung fosfor sebanyak 70 mg per 100 gram (Krisnadi, 2015). 57 Open Journal System (OJS): journal.thamrin.ac.id http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf Open Journal System (OJS): journal.thamrin.ac.id http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 Potensi daun kelor yang dapat digunakan sebagai bahan tambahan dalam pembuatan dawet baik sebagai pewarna hijau dan/atau sebagai tambahan gizi dapat meningkatkan mutu dari dawet sehingga menjadi jajanan yang bernilai gizi, maka penelitian mengenai pemanfaatan daun kelor sebagai bahan tambahan pembuatan dawet perlu dilakukan. Karena peneliti yakin dawet akan menjadi lebih bergizi dan aman jika komponen penyusunnya terdiri dari bahan alami. Adapun Tujuan dari penelitian ini adalah untuk Mengetahui pengaruh penambahan daun kelor terhadap sifat organoleptik dan daya terima dawet. HASIL DAN PEMBAHASAN Penelitian ini merupakan jenis penelitian eksperimental menggunakan bahan baku daun kelor yang bertujuan untuk mengetahui pengaruh penambahan daun kelor terhadap sifat organoleptik produk dawet daun kelor. Proses penelitian ini meliputi penambahan daun kelor terhadap dawet pada persentase 20%, 35%, dan 50% yang selanjutnya dilakukan uji organoleptik yaitu uji hedonik dan uji mutu hedonik dengan kriteria uji warna, rasa, aroma, dan tekstur. Prinsip uji mutu hedonik berdasarkan penilaian panelis terhadap sifat organoleptik dengan penganalisaan tingkat kesan (skala mutu hedonik). Pada uji mutu hedonik produk dawet daun kelor, ditentukan nilai 1 hingga 5 dimana nilai paling rendah yang berarti kualitas dawet paling jelek, menaik hingga nilai 5 pada skala hedonik dimana kualitas dawet semakin baik seiring menaiknya penilaian panelis. Uji mutu hedonik pada penelitian dawet daun kelor mencakup kriteria uji warna, rasa, aroma, dan tekstur. Pengujian dilakukan oleh panelis agak terlatih. 58 p y ( ) j http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 Penelitian ini menggunakan Rancangan Acak Lengkap (RAL) dengan 2 kali pengulangan. Uji organoleptik dianalisis dengan sidik ragam (ANOVA), menunjukkan beda nyata pada taraf 5%. Jika ANOVA menunjukkan pengaruh perlakuan nyata, maka dilanjutkan dengan Duncan’s Multiple Range Test untuk mencari keberadaan perbedaan dari perlakuan yang ada. Penentuan mutu bahan makanan umumnya bergantung pada warna yang dimilikinya, warna yang tidak menyimpang dari warna yang seharusnya akan memberi kesan penilaian tersendiri oleh panelis. Kategori penilaian warna meliputi hijau kecokelatan sampai hijau. Kategori penilaian tingkat kesukaan warna meliputi tidak suka sampai amat sangat suka. Warna daun kelor pada penelitian ini dipilih warna yang tidak terlalu muda (hijau muda) dan juga tidak terlalu tua (kuning kecokelatan atau kuning muda). Warna daun kelor yang dipilih yaitu daun kelor yang berwarna hijau tua. Warna hijau yang dimiliki daun kelor berasal dari zat hijau daun klorofil. Klorofil merupakan salah satu unsur penting yang dimiliki Kelor. Saat ini, ada tiga sumber makanan paling penting dan terbaik kandungan klorofilnya yaitu Kelor, rumput Gandum (Wheatgrass) dan rumput Barley (Krisnadi, 2015). Berdasarkan Tabel 1, hasil uji organoleptik menunjukkan bahwa nilai rata-rata uji mutu hedonik aspek warna pada P1 = 3.18 (hijau pucat), P2 = 3.40 (hijau pucat), dan P3 = 3.90 (cenderung agak hijau). HASIL DAN PEMBAHASAN Hasil uji hedonik aspek warna menunjukkan bahwa nilai rata- rata tingkat kesukaan panelis terhadap warna dawet daun kelor pada P1 = 1.96 (cenderung agak suka), P2 = 2.56 (cenderung suka), dan P3= 2.95 (cenderung suka). Hasil uji anova didapatkan bahwa terdapat pengaruh penambahan daun kelor terhadap sifat organoleptik warna produk dawet daun kelor karena p value < 0.05 yaitu sebesar 0.0005 yang artinya H0 ditolak. Secara deskriptif terlihat adanya kecenderungan makin bertambah konsentrasi daun kelor, produk dawet daun kelor cenderung sangat hijau. Hal ini didukung dengan analisis statistik memang ada perbedaan yang nyata pada penambahan daun kelor terhadap aspek warna dawet daun kelor. Nilai p value uji hedonik aspek warna yaitu sebesar 0.0005 yang artinya H0 ditolak atau terdapat pengaruh penambahan daun kelor terhadap tingkat kesukaan warna produk dawet daun kelor. Secara deskriptif terlihat bahwa penambahan daun kelor berpengaruh nyata terhadap tingkat kesukaan aspek warna dawet daun kelor. Hasil uji organoleptik terhadap mutu hedonik dan hedonik dawet daun kelor aspek warna dapat dilihat pada tabel di bawah ini. 59 Open Journal System (OJS): journal.thamrin.ac.id http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 Tabel 1. Data Hasil Uji Organoleptik Kriteria Warna Konsentrasi Kriteria Uji Warna Kriteria Uji Tingkat Kesukaan Warna 20% P1 3.27a 2.00a 20% P1` 3.10a 1.93a 35% P2 3.40a 2.90b 35% P2` 3.40a 2.23a 50% P3 4.47b 2.77b 50% P3` 3.33a 3.13b Tabel 1. Data Hasil Uji Organoleptik Kriteria Warna Kategori penilaian rasa meliputi rasa daun kelor amat sangat kuat sampai rasa daun kelor tidak nyata dan kategori penilaian tingkat kesukaan rasa meliputi tidak suka sampai amat sangat suka. Untuk rasanya, daun kelor memiliki rasa agak pahit, namun bila sudah dikukus dan dicampur dengan bahan lain seperti tepung dalam adonan dan gula serta santan pada produk jadi, rasa asli dari daun kelor sudah tertutupi. Hasil uji organoleptik terhadap mutu hedonik dan hedonik aspek rasa dapat dilihat pada tabel di bawah ini. Tabel 2. Data Hasil Uji Organoleptik Kriteria Rasa Tabel 2. Data Hasil Uji Organoleptik Kriteria Rasa Konsentrasi Kriteria Uji Rasa Kriteria Uji Tingkat Kesukaan Rasa 20% P1 3.97c 1.97b 20% P1` 4.33cd 2.13bc 35% P2 3.03b 1.77ab 35% P2` 4.43d 2.47c 50% P3 2.53a 1.43a 50% P3` 2.13a 1.50a Berdasarkan Tabel 2, hasil uji organoleptik menunjukkan bahwa nilai rata-rata uji mutu hedonik aspek rasa pada P1 = 4.15 (rasa daun kelor agak kuat), P2 = 3.73 (rasa daun kelor cenderung agak kuat), dan P3 = 2.33 (rasa daun kelor sangat kuat). Hasil uji hedonik aspek rasa menunjukkan bahwa nilai rata-rata tingkat kesukaan panelis terhadap rasa dawet daun kelor pada P1 = 2.05 (agak suka), P2 = 2.12 (agak suka), dan P3 = 1.46 (cenderung tidak suka). 60 Open Journal System (OJS): journal.thamrin.ac.id http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 Hasil uji anova didapatkan bahwa terdapat pengaruh penambahan daun kelor terhadap sifat organoleptik rasa produk dawet daun kelor karena p value < 0.05 yaitu sebesar 0.0005 yang artinya H0 ditolak. Secara deskriptif terlihat adanya kecenderungan makin bertambah konsentrasi daun kelor, maka rasa daun kelor akan semakin kuat. Hal ini didukung dengan analisis statistik memang ada perbedaan yang nyata pada penambahan daun kelor terhadap aspek rasa dawet daun kelor. Nilai p value uji hedonik aspek rasa yaitu sebesar 0.0005 yang artinya H0 ditolak atau terdapat pengaruh penambahan daun kelor terhadap tingkat kesukaan rasa produk dawet daun kelor. Open Journal System (OJS): journal.thamrin.ac.id http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf 61 Open Journal System (OJS): journal.thamrin.ac.id http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 Secara deskriptif terlihat bahwa penambahan daun kelor berpengaruh nyata terhadap tingkat kesukaan aspek rasa dawet daun kelor. Aroma yang terdapat pada dawet berasal dari aroma khas daun kelor. Penambahan daun kelor dengan konsentrasi berbeda pada penelitian ini dilakukan untuk mengetahui pengaruh konsentrasi daun kelor yang diberikan terhadap aroma dan tingkat kesukaan aroma pada produk dawet. Penambahan daun kelor yang berpengaruh terhadap aroma disebabkan daun kelor mengandung enzim lipoksidase yang menghidrolisis atau menguraikan lemak menjadi senyawa-senyawa penyebab bau langu, yang tergolong pada kelompok heksanal 7 dan heksanol (Santoso, 2005). Menurut Kurniasih (2013) daun kelor berbentuk bulat telur dengan ukuran kecil-kecil bersusun majemuk dalam satu tangkai berwarna hijau pucat menyirip ganda dengan anak daun menyirip ganjil dan helaian daunnya bulat telur. Aroma daun kelor agak langu, namun aroma akan berkurang ketika dipetik dan dicuci bersih lalu disimpan pada suhu ruang 30ºC sampai 32ºC. Hasil uji organoleptik terhadap mutu hedonik dan hedonik aspek aroma dapat dilihat pada tabel di bawah ini. Tabel 3. Data Hasil Uji Organoleptik Kriteria Aroma Konsentrasi Kriteria Uji Aroma Kriteria Uji Tingkat Kesukaan Aroma 20% P1 3.80c 2.63ab 20% P1` 4.03c 2.33a 35% P2 3.23b 2.30a 35% P2` 4.57d 2.60ab 50% P3 2.87b 2.20a 50% P3` 2.30a 2.93b Tabel 3. Data Hasil Uji Organoleptik Kriteria Aroma 61 Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 Berdasarkan Tabel 3, hasil uji organoleptik menunjukkan bahwa nilai rata-rata uji mutu hedonik aspek aroma pada P1 = 3.91 (aroma daun kelor cenderung agak kuat), P2 = 3.90 (aroma daun kelor cenderung agak kuat), dan P3 = 2.58 (aroma daun kelor cenderung kuat). Hasil uji hedonik aspek aroma menunjukkan bahwa nilai rata- rata tingkat kesukaan panelis terhadap aroma dawet daun kelor pada P1 = 2.48 (cenderung agak suka), P2 = 2.45 (cenderung agak suka), dan P3 = 2.56 (cenderung suka). Hasil uji anova didapatkan bahwa terdapat pengaruh penambahan daun kelor terhadap sifat organoleptik aroma produk dawet daun kelor karena p value < 0.05 yaitu sebesar 0.0005 yang artinya H0 ditolak. Secara deskriptif terlihat adanya kecenderungan makin bertambah konsentrasi daun kelor, maka aroma daun kelor akan semakin kuat. Hal ini didukung dengan analisis statistik memang ada perbedaan yang nyata pada penambahan daun kelor terhadap aspek aroma dawet daun kelor. Nilai p value uji hedonik aspek aroma yaitu sebesar 0.030 yang artinya H0 diterima atau tidak terdapat pengaruh penambahan daun kelor terhadap tingkat kesukaan aroma produk dawet daun kelor. Secara deskriptif terlihat bahwa penambahan daun kelor tidak berpengaruh nyata terhadap tingkat kesukaan aspek aroma dawet daun kelor. Tekstur berupa kekenyalan dari produk dawet dengan penambahan daun kelor. Penambahan daun kelor dengan konsentrasi berbeda pada penelitian ini dilakukan untuk mengetahui pengaruh konsentrasi daun kelor yang diberikan terhadap tekstur dan tingkat kesukaan tekstur dawet. Kategori penilaian tekstur dawet meliputi sangat lembek sampai kenyal dan kategori penilaian tingkat kesukaan tekstur meliputi tidak suka sampai amat sangat suka. Umumnya tekstur dawet yaitu kenyal. Semakin besar persen daun kelor yang ditambahkan ke dalam dawet, maka tekstur dawet semakin lembek. Hal itu disebabkan karena persen dari tepung yang ditambahkan akan semakin kecil bila persen daun kelor yang ditambahkan semakin besar. Hasil uji organoleptik terhadap mutu hedonik dan hedonik aspek tekstur dapat dilihat pada tabel 4. Berdasarkan Tabel 4, hasil uji organoleptik menunjukkan bahwa nilai rata-rata uji mutu hedonik aspek tekstur pada P1 = 2.85 (cenderung agak lembek), P2 = 3.48 (cenderung agak lembek), dan P3 = 3.76 (cenderung agak kenyal). Hasil uji hedonik aspek tekstur menunjukkan bahwa nilai rata-rata tingkat kesukaan panelis terhadap tekstur dawet daun kelor pada P1 = 2.28 (cenderung agak suka), P2 = 2.31 (cenderung agak suka), dan P3 = 2.53 (cenderung suka). Open Journal System (OJS): journal.thamrin.ac.id http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 62 Open Journal System (OJS): journal.thamrin.ac.id http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf Open Journal System (OJS): journal.thamrin.ac.id http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf Jurnal Kesehatan Masyarakat Perkotaan p-ISSN: 2776-0952 e-ISSN : 2776-0944 Volume 3, No. 1; Maret 2023 Hal 22-33 Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 Tabel 4. Data Hasil Uji Organoleptik Kriteria Tekstur Konsentrasi Kriteria Uji Tekstur Kriteria Uji Tingkat Kesukaan Tekstur 20% P1 2.93a 2.30a 20% P1` 2.77a 2.27a 35% P2 3.97b 2.30a 35% P2` 3.00a 2.33a 50% P3 3.60b 2.33a 50% P3` 3.93b 2.73a Hasil uji anova didapatkan bahwa terdapat pengaruh penambahan daun kelor terhadap sifat organoleptik tekstur produk dawet daun kelor karena p value < 0.05 yaitu sebesar 0.0005 yang artinya H0 ditolak. Secara deskriptif terlihat adanya kecenderungan makin bertambah konsentrasi daun kelor, maka tekstur daun kelor akan semakin kenyal. Hal ini didukung dengan analisis statistik memang ada perbedaan yang nyata pada penambahan daun kelor terhadap aspek tekstur dawet daun kelor. Nilai p value uji hedonik aspek aroma yaitu sebesar 0.527 yang artinya H0 diterima atau tidak terdapat pengaruh penambahan daun kelor terhadap tingkat kesukaan tekstur produk dawet daun kelor. Secara deskriptif terlihat bahwa penambahan daun kelor tidak berpengaruh nyata terhadap tingkat kesukaan aspek tekstur dawet daun kelor. Penentuan produk terpilih ditentukan berdasarkan hasil uji tingkat kesukaan (hedonik) dan seberapa banyak kandungan protein dan kalsium yang dapat disumbangkan oleh daun kelor ke dalam dawet. Uji hedonik dawet daun kelor meliputi warna, rasa, aroma, dan tekstur. Parameter uji hedonik yang digunakan adalah 1 (tidak suka) hingga 5 (amat sangat suka). Nilai rata-rata hasil uji tingkat kesukaan (hedonik) dawet daun kelor dapat dilihat pada tabel 5 di bawah ini. Berdasarkan Tabel 5, nilai tertinggi pada kategori penilaian aspek warna adalah P3` 50% yaitu 3.13 (suka). Nilai tertinggi pada kategori penilaian aspek rasa adalah P2` 35% yaitu 2.47 (cenderung agak suka). Nilai tertinggi pada kategori penilaian aspek aroma adalah P3` 50% yaitu 2.93 (suka). Nilai tertinggi pada kategori penilaian aspek tekstur adalah P3` 50% yaitu 2.73 (cenderung suka). 63 Open Journal System (OJS): journal.thamrin.ac.id http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf Open Journal System (OJS): journal.thamrin.ac.id http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 Tabel 5. Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 Hasil Uji Hedonik Dawet Daun Kelor Kategori Perlakuan Warna Rasa Aroma Tekstu r 20% P1 2.00a 1.97b 2.63ab 2.30a 20% P1` 1.93a 2.13bc 2.33a 2.27a 35% P2 2.90b 1.77ab 2.30a 2.30a 35% P2` 2.23a 2.47c 2.60ab 2.33a 50% P3 2.77b 1.43a 2.20a 2.33a 50% P3` 3.13b 1.50a 2.93b 2.73a Ket: Huruf yang berbeda pada baris yang sama menunjukkan perbedaan yang nyata (p<0.05) Tabel 5. Hasil Uji Hedonik Dawet Daun Kelor Dapat disimpulkan berdasarkan hasil uji tingkat kesukaan (hedonik), diketahui produk terpilih adalah P3` yaitu perlakuan dengan penambahan daun kelor sebanyak 50% yang memiliki nilai tertinggi dari tingkat kesukaan aspek warna, aroma, dan tekstur. Deskripsi sifat fisik produk dawet daun kelor terpilih dapat dilihat pada tabel di bawah ini. Tabel 6. Deskripsi Sifat Fisik Dawet Daun Kelor Produk Terpilih (P3`) Aspek Mutu Hedonik Hedonik Warna Cenderung Hijau Pucat Suka Rasa Rasa Daun Kelor Sangat Kuat Cenderung Agak Suka Aroma Aroma Daun Kelor Cenderung Sangat Kuat Suka Tekstur Agak Kenyal Cenderung Suka Tabel 6. Deskripsi Sifat Fisik Dawet Daun Kelor Produk Terpilih (P3`) KESIMPULAN Ada pengaruh penambahan daun kelor terhadap aspek warna, rasa, aroma, dan tekstur pada dawet daun kelor. Penambahan daun kelor akan menaikkan intensitas warna hijau, rasa dan aroma daun kelor yang semakin nyata, serta tekstur dawet yang semakin kenyal. Ada pengaruh penambahan daun kelor terhadap tingkat kesukaan pada aspek warna, aroma, dan tekstur. Penambahan daun kelor pada tingkat kesukaan aspek rasa lebih disukai pada produk dengan penambahan daun kelor sebanyak 35%. Pada tingkat kesukaan aspek warna, aspek aroma, dan aspek tekstur lebih disukai pada produk dengan penambahan daun kelor sebanyak 50%. Produk yang lebih disukai oleh panelis adalah produk dengan penambahan daun kelor sebanyak 50%. 64 http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 REFERENSI 1. Alkham, Fithri Fakhrunnisa. 2014. Uji Kadar Protein Dan Organoleptik Biskuit Tepung Terigu Dan Tepung Daun Kelor (Moringa Oleifera) Dengan Penambahan Jamur Tiram (Pleurotus Ostreatus). Surakarta. 2. Almatsier, Sunita. 2009. Prinsip Dasar Ilmu Gizi. Jakarta: Gramedia Pustaka Utama. Aminah, Syarifah., Ramdhan, Tezar., dan Yanis, Muflihani. 2015. Kandungan 3. Nutrisi dan Sifat Fungsional Tanaman Kelor (Moringa Oleifera). Buletin 4. Pertanian Perkotaan Volume 5 Nomor 2. 5. Andarwulan, N., Kusnandara, F, dan Herawati, D. 2011. Analisis Pangan. Kencana- Jakarta. 6. Andriyani, Ferry., Silvia, Figur Jaya., Kusminanto, Richi Yuliavian., dan Sholikhah, Yuni Khatus. 2015. Dawet Ceker Ayam “Dawet Kera” Kaya Gizi, Rendah Kolesterol Sebagai Upaya Meningkatkan Kesadaran Gizi Masyarakat. Surakarta. 7. Anonim. 2011. Petunjuk Praktikum Teknologi Pengolahan Pangan dan Hasil Pertanian. Jember: FTP UNEJ. 8. Anonim. 2019. Resep Dawet Jadul, Dawet Tepung Beras. Pemalang. 8. Anonim. 2019. Resep Dawet Jadul, Dawet Tepung Beras. Pemalang. 9. Arbi, Armein Syukri. 2009. Modul 1. Pengenalan Evaluasi Sensori. Kegiatan Praktikum 1. Ketentuan Panelis, Lab, dan Bahan dalam Evaluasi Sensori. Universitas Terbuka. Jakarta. 9. Arbi, Armein Syukri. 2009. Modul 1. Pengenalan Evaluasi Sensori. Kegiatan Praktikum 1. Ketentuan Panelis, Lab, dan Bahan dalam Evaluasi Sensori. Universitas Terbuka. Jakarta. 10. Ardhanareswari, Ni Putu. 2019. Daya Terima Dan Kandungan Gizi Dim Sum Yang Disubstitusi Ikan Patin (Pangasius Sp.) Dan Pure Kelor (Moringa Oleifera) Sebagai Snack Balita. Media Gizi Indonesia. 2019.14(2): 123–131. Surabaya. 10. Ardhanareswari, Ni Putu. 2019. Daya Terima Dan Kandungan Gizi Dim Sum Yang Disubstitusi Ikan Patin (Pangasius Sp.) Dan Pure Kelor (Moringa Oleifera) Sebagai Snack Balita. Media Gizi Indonesia. 2019.14(2): 123–131. Surabaya. 12. Cahyadi, Wisnu., 2012, Bahan Tambahan Pangan, Bumi Aksara, Jakarta. 12. Cahyadi, Wisnu., 2012, Bahan Tambahan Pangan, Bumi Aksara, Jakarta. 13. Estiasih, Teti., Harijono, Waziiroh, Elok., Fibrianto, Kiki., 2016, Kimia dan FisikPangan, Bumi Aksara, Jakarta. 13. Estiasih, Teti., Harijono, Waziiroh, Elok., Fibrianto, Kiki., 2016, Kimia dan FisikPangan, Bumi Aksara, Jakarta. 14. Fuglie, Lowell J., ed. 2001. The Miracle Tree: The multiple attributes of moringa. 14. Fuglie, Lowell J., ed. 2001. The Miracle Tree: The multiple attributes of moringa. 15. Dakar, Senegal: Church World Service. 14. Fuglie, Lowell J., ed. 2001. The Miracle Tree: The multiple attributes of moringa. 15. Dakar, Senegal: Church World Service. 16. Godam64. 2012. Isi Kandungan Gizi Tepung Sagu - Komposisi Nutrisi Bahan Makanan. [Online]. Available from: http://www.organisasi.org/1970/01/isi- kandungan-gizi- tepung-sagu-komposisi-nutrisi-bahan- makanan.html#.XefblegzbDc [Accessed: 04/12/19 11:14 PM]. 65 http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf Open Journal System (OJS): journal.thamrin.ac.id http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 17. Gopalakrishnan, L., Doriya, K. and Kumar, D.S. 2016. Moringa oleifera: A review on nutritive importance and its medicinal application. Journal Food Science and Human Wellness 5 (2016) 49-56. 18. Hasanah, Imroatul. 2018. Pengaruh Penambahan Sari Daun Kelor (Moringa Oleifera) Dan Sari Stoberi Terhadap Hasil Uji Organoleptik Pada Peremen Karamel Susu. Yogyakarta. 19. Hasbullah. 2001. Teknologi Tepat Guna Agroindustri Kecil Sumatera Barat, Dewan Ilmu Pengetahuan, Teknologi dan Industri Sumatera Barat. 20. Hastono, Sutanto Priyo. 2007. Analisis Data Kesehatan. Fakultas Kesehatan Masyarakat. Universitas Indonesia. Depok. 21. Indria. 2015. Makanan Sehat. Indonesia Publishing House. Bandung. 22. Isnan, Wahyudi. dan M., Nurhaedah. 2017. Ragam Manfaat Tanaman Kelor (Moringa Oleifea Lamk.) Bagi Masyarakat. Info Teknis EBONI. Vol. 14 No. 1, Juli 2017 : 63 – 75. 23. Krisnadi, A. Dudi. 2015. Kelor Super Nutrisi. Available From: kelorina.com. [Accessed: 08/09/2019]. 24. Kurniasih. 2013. Khasiat dan Manfaat Daun Kelor. Pustaka Baru Press. Yogyakarta. Mardiah. 2017. Analisa Kadar Kalsium (Ca) Pada Daun Kelor (Moringa oleifera). 25. Jurnal Ilmu Alam dan Lingkungan 8 (15) (2017) 49 – 52. Makassar. 26. Mardiana, L. (2013). Daun Ajaib Tumpas Penyakit. Jakarta: Penebar Swadaya. Meilgaard et al. 2006. Sensory Evaluation Techniques Fourth Edition. USA: CRC 27. Press. 28. Melo, N. V., Vargas, T. Quirino and C. M. C. Calvo. (2013). Moringa oleifera L. An underutilized tree with macronutrients for human health. Emir. J. Food Agric, 25 (10): 785-789. 29. Michael E.J.L. 2013. Ilmu Pangan, Gizi, dan Kesehatan, Ed. I, diterjemahkan oleh: Nata Nilamsari & Astri Fajriyah, Pustaka Belajar, Yogyakarta. 30. Mirayanti, Ni Putu Ayu Prisiana. 2018. Pengembangan Dawet Dengan Penambahan Tepung Torbangun (Coleus Amboinicus Lour). Bogor. 31. Musfiroh, Ida., Indriyati, Wiwiek., Muchtaridi., Setiya, Yudhi. 2009. Analisis Proksimat dan Penetapan Kadar - Karoten dalam Selai Lembaran Terung Belanda (Cyphomandra betacea Sendtn.) Dengan Metode Spektrofotometri Sinar Tampak. Bandung. 66 http://journal.thamrin.ac.id/index.php/jkmp/article/view/1196/pdf Jurnal Kesehatan Masyarakat Perkotaan p-ISSN: 2776-0952 e-ISSN : 2776-0944 Volume 3, No. 1; Maret 2023 Hal 22-33 Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 p-ISSN: 2776-0952 e-ISSN : 2776-0944 Hal 22-33 Jurnal Kesehatan Masyarakat Perkotaan Volume 3, No. 1; Maret 2023 32. Palupi, N.S., Zakaria, F.R. dan Prangdimurti, E. 2007. Pengaruh Pengolahan Terhadap Nilai Gizi Pangan. Modul e-Learning ENBP, Departemen Ilmu & Teknologi Pangan- Fateta-IPB. 33. Probosari, Enny. 2019. Pengaruh Protein Diet Terhadap Indeks Glikemik. JNH (Journal of Nutrition and Health) Vol.7 No.1. e ISSN: 2622-8483; p ISSN: 2338-3380. 34. Setyaningsih D., Aprianto A., Sari MP. 2010. Analisis Sensori Untuk Industri Pangan dan Agro. Bogor: IPB-Press. 35. Sholiha, Illiyatus. 2019. Pengolahan Rumput Laut (Eucheuma Cottoni) Menjadi Dawet Rumput Laut. Jurnal Biologi dan Pembelajarannya, Vol 6 No 1. Pp: 1-6. e-ISSN: 2406 – 8659. 36. Simbolan, J.M. dan Katharina, N. 2007. Cegah Malnutrisi dengan Kelor. Kanisius. 37. Yogyakarta. 38. SNI 01-2346-2006. 2006. Petunjuk Pengujian Organoleptik dan atau Sensori. Badan Standarisasi Nasional. Jakarta. 39. SNI 01-2891-1992. 1992. Cara Uji Makanan dan Minuman. Badan Standarisasi Nasional. Jakarta. 40. Surdijati, Siti. 2001. Identifikasi Dan Penetapan Kadar Zat Warna Merah Dalam Dawet Secara KLT-Densitometri. Jurnal Teknologi Pangan dan Gizi Volume 2 Nomor 1. 41. Winarno, F.G. 2008. Kimia Pangan dan Gizi. Penerbit PT. Gramedia Pustaka Utama. Jakarta. 67
https://openalex.org/W4387845674	https://nanoconvergencejournal.springeropen.com/counter/pdf/10.1186/s40580-023-00398-y	English	null	Nano-biomaterials and advanced fabrication techniques for engineering skeletal muscle tissue constructs in regenerative medicine	Nano convergence	2,023	cc-by	14,481	© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 1 Introduction Volumetric muscle loss (VML) refers to a significant loss of muscle tissue due to trauma or surgery, leading to the failure of intrinsic muscle regeneration and function and the healing of the defect area by fibrosis [1]. The current gold standard for treating VML is the transplantation of functional muscle tissues obtained from donors [2]. However, tissue transplantation still possesses multiple can decrease the outcomes of functional regeneration [3]. To find an alternative method, various regenerative therapies, such as stem cells delivery, scaffolds implan- tations, and engineered muscle tissue grafts, have been developed to address long-term functional defi- cits and various pathologic comorbidities caused by a large amount of tissue loss [4, 5]. These therapies aim to regenerate new muscle via implanted stem cells or by inducing the differentiation of host cells along with neuromuscular junctions and blood vessels, which are necessary to restore the muscle function [6, 7]. Cur- rently, these approaches have been combined with novel engineering strategies, such as bioprinting, which enables the precise control over the size, shape, and compartmentation of various cells, ultimately pro- viding personalized engineered tissues with complex 3D architectures to fit defect areas [8]. Furthermore, Correspondence: Sungsu Park nanopark@skku.edu Su Ryon Shin sshin4@bwh.harvard.edu 1 Division of Engineering in Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Cambridge, MA 02139, USA 2 School of Mechanical Engineering, Sungkyunkwan University (SKKU), Suwon 16419, Korea 3 Department of Biophysics, Institute of Quantum Biophysics (IQB), Sungkyunkwan University (SKKU), Suwon 16419, Korea Correspondence: Sungsu Park nanopark@skku.edu Su Ryon Shin sshin4@bwh.harvard.edu 1 Division of Engineering in Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Cambridge, MA 02139, USA 2 School of Mechanical Engineering, Sungkyunkwan University (SKKU), Suwon 16419, Korea 3 Department of Biophysics, Institute of Quantum Biophysics (IQB), Sungkyunkwan University (SKKU), Suwon 16419, Korea Abstract Engineered three-dimensional (3D) tissue constructs have emerged as a promising solution for regenerating dam- aged muscle tissue resulting from traumatic or surgical events. 3D architecture and function of the muscle tissue constructs can be customized by selecting types of biomaterials and cells that can be engineered with desired shapes and sizes through various nano- and micro-fabrication techniques. Despite significant progress in this field, further research is needed to improve, in terms of biomaterials properties and fabrication techniques, the resem- blance of function and complex architecture of engineered constructs to native muscle tissues, potentially enhancing muscle tissue regeneration and restoring muscle function. In this review, we discuss the latest trends in using nano- biomaterials and advanced nano-/micro-fabrication techniques for creating 3D muscle tissue constructs and their regeneration ability. Current challenges and potential solutions are highlighted, and we discuss the implications and opportunities of a future perspective in the field, including the possibility for creating personalized and biomanu- facturable platforms. Keywords Nanomaterials, Biomaterials, Stem cells, Skeletal muscle, Tissue engineering, Tissue regeneration clinical limitations, such as donor site morbidity, lack of donors, immune rejection, and low integration, which can decrease the outcomes of functional regeneration [3]. To find an alternative method, various regenerative therapies, such as stem cells delivery, scaffolds implan- tations, and engineered muscle tissue grafts, have been developed to address long-term functional defi- cits and various pathologic comorbidities caused by a large amount of tissue loss [4, 5]. These therapies aim to regenerate new muscle via implanted stem cells or by inducing the differentiation of host cells along with neuromuscular junctions and blood vessels, which are necessary to restore the muscle function [6, 7]. Cur- rently, these approaches have been combined with novel engineering strategies, such as bioprinting, which enables the precise control over the size, shape, and compartmentation of various cells, ultimately pro- viding personalized engineered tissues with complex 3D architectures to fit defect areas [8]. Furthermore, clinical limitations, such as donor site morbidity, lack of donors, immune rejection, and low integration, which can decrease the outcomes of functional regeneration [3]. Open Access Open Access Nano‑biomaterials and advanced fabrication techniques for engineering skeletal muscle tissue constructs in regenerative medicine Seokgyu Han1,2, Sebastián Herrera Cruz1, Sungsu Park2,3* and Su Ryon Shin1* Han et al. Nano Convergence (2023) 10:48 https://doi.org/10.1186/s40580-023-00398-y Han et al. Nano Convergence (2023) 10:48 https://doi.org/10.1186/s40580-023-00398-y Nano Convergence Nano Convergence Stem cells for skeletal muscle regeneration 2 Stem cells for skeletal muscle regeneration many studies have explored nanomaterials and nano- technologies to resemble the biophysical and biologi- cal properties of the nanofibrous native extracellular matrix (ECM) that allow us to create functional tissue constructs, like the native skeletal muscle tissue [9]. Incorporation of these unique nanomaterials or nano- structures into 3D engineered tissue constructs using advanced bioprinting technologies can improve the communication between cells and promote the integra- tion of the engineered tissue with the host tissue, ulti- mately leading to better outcomes for regeneration. 2 Stem cells for skeletal muscle regeneration Most of the cells in skeletal muscle are multinucleated, generating myofibers that are surrounded by ECM such as endomysium. ECM components, such as collagen (types I, III, and VI), proteoglycans, and fibronectins, exist between myofibers, regulating muscle development and facilitating the transmission of mechanical forces [14]. When the skeletal muscle undergoes some defects, the process of muscle regeneration starts with clearance of necrotic cells by phagocytosis of pro-inflammatory macrophages. The prompt clearance of debris is crucial for the timely initiation of muscle regeneration [15, 16]. Then, myofiber regeneration may be facilitated when implanted stem cells become active due to their regen- erative capacity [17]. Stem cells that are introduced into the injured area can release various factors, such as cytokines, extracellular vesicles, including exosomes, and growth factors, which can affect the behavior of host cells, including resident stem cells, immune cells, and endothelial cells, etc. Specifically, these secreted factors can promote the activation of anti-inflammatory mac- rophages, which can help reduce inflammation and sup- port the regeneration of muscle tissue [18]. Additionally, Previous reviews have primarily focused on mus- cle regeneration using stem cells and biomaterials as scaffolds [4, 10–13]. This review aims to address the existing limitations in the literature by providing an overview of recent advancements in the combined uti- lization of stem cells, nano-biomaterials, and nano/ micro fabrication technologies in bioengineering strategies for muscle regeneration. It also explores the diverse roles played by various nanomaterials in this field (Fig. 1). Finally, we will provide future perspectives on skeletal muscle regeneration. Fig. 1 Stem cells, nanomaterials, and advanced tissue engineering for engineering skeletal muscle tissue constructs in regenerative medicine. (AuNP Gold nanoparticle, CNT Carbon nanotube, iPSC Induced pluripotent stem cell, ADSC Adipose-derived stem cell, MSC Mesenchymal stem cell) Fig. Han et al. Nano Convergence (2023) 10:48 Page 2 of 19 Han et al. Nano Convergence (2023) 10:48 Stem cells for skeletal muscle regeneration Obtaining an adequate q lite cells from a small muscle sample can ficulties, and obtaining a larger sample is to potential harm to the biopsy site. More cells age, their ability to divide and contr growth diminishes over time. Therefore, f is necessary to comprehend the mecha ing immune rejection and to develop str gate the immune response to transplant remains a significant obstacle. Table 1 Characteristics of stem cells delivered Stem cell Characteristics SCs - Muscle-specific stem cells - Expression of Pax7 - Ability to differentiate into multiple type of muscle cells ADSCs - Paracrine effect for muscle regeneration - Capacity to differentiate into mesoderm lineage - Promotion of angiogenesis MSCs - Secretion of growth factor for promotion of the regeneration - Increase of myogenin expression hiPSCs - Unlimited proliferative potential - Ability to differentiate into any types of cells - Patient-specific Skeletal muscles have a strong regenerative ability com- pared to other adult tissue, partly due to the presence of satellite cells, which constitute less than 5% of the cells in muscle tissue [20]. These satellite cells rely on the tran- scription factor Pax7 for their proper functioning and maintenance, essential for self-regeneration [21]. Studies have shown that when Pax7 is absent, satellite cells and myoblasts experience cell cycle arrest and an imbalance in myogenic regulatory factors, underscoring the criti- cal role of Pax7 in skeletal muscle regeneration [22]. Due to their high rate of proliferation and capacity to differ- entiate into a variety of muscle cell types, satellite cells have been intensively researched for muscle regenera- tion [23–25]. However, there are still several challenges to address in order to fully harness the potential of sat- ellite cells in skeletal muscle regeneration. The limited number of satellite cells within muscle tissue may restrict their ability to completely repair significant or extensive muscle injuries. Obtaining an adequate quantity of satel- lite cells from a small muscle sample can also present dif- ficulties, and obtaining a larger sample is not feasible due to potential harm to the biopsy site. Moreover, as satellite cells age, their ability to divide and contribute to muscle growth diminishes over time. Therefore, further research is necessary to comprehend the mechanisms underly- ing immune rejection and to develop strategies to miti- gate the immune response to transplanted cells, which remains a significant obstacle. Stem cells for skeletal muscle regeneration 1 Stem cells, nanomaterials, and advanced tissue engineering for engineering skeletal muscle tissue constructs in regenerative medicine. (AuNP Gold nanoparticle, CNT Carbon nanotube, iPSC Induced pluripotent stem cell, ADSC Adipose-derived stem cell, MSC Mesenchymal stem cell) Fig. 1 Stem cells, nanomaterials, and advanced tissue engineering for engineering skeletal muscle tissue constructs in regenerative medicine. (AuNP Gold nanoparticle, CNT Carbon nanotube, iPSC Induced pluripotent stem cell, ADSC Adipose-derived stem cell, MSC Mesenchymal stem cell) Han et al. Nano Convergence (2023) 10:48 Han et al. Nano Convergence (2023) 10:48 Han et al. Nano Convergence (2023) 10:48 Page 3 of 19 Future directions for stem cell research in skeletal mus- cle regeneration include exploring novel delivery strate- gies for satellite cells, such as gene therapy and tissue engineering approaches, to enhance their survival and integration into host tissue. Researchers may also inves- tigate the use of combination therapies that include stem cells and other growth factors or biomaterials to further enhance muscle regeneration. Finally, the development of new technologies, such as organ-on-a-chip platforms, may provide new avenues for testing the efficacy of sat- ellite cell-based therapies in a more physiologically rel- evant setting. stem cells can also inhibit the activation of pro-inflam- matory cells, further reducing inflammation and promot- ing tissue healing. These immunomodulatory effects play a crucial role in promoting myofiber regeneration and restoring muscle function [19]. Table 1 presents a sum- mary of the advantages and limitations associated with these stem cell types. a crucial role in promoting myofiber re restoring muscle function [19]. Table 1 p mary of the advantages and limitations these stem cell types. Skeletal muscles have a strong regenera pared to other adult tissue, partly due to satellite cells, which constitute less than 5 muscle tissue [20]. These satellite cells r scription factor Pax7 for their proper f maintenance, essential for self-regenerati have shown that when Pax7 is absent, sa myoblasts experience cell cycle arrest an in myogenic regulatory factors, undersc cal role of Pax7 in skeletal muscle regene to their high rate of proliferation and ca entiate into a variety of muscle cell type have been intensively researched for m tion [23–25]. However, there are still se to address in order to fully harness the p ellite cells in skeletal muscle regenerati number of satellite cells within muscle tis their ability to completely repair signific muscle injuries. Stem cells for skeletal muscle regeneration Nano Convergence (2023) 10:48 Page 4 of 19 differentiate into the specific type of muscle cell needed for regeneration [39]. Furthermore, there are concerns regarding potential immune reactions and an elevated risk of cancer [40]. Further research is needed to fully understand the capabilities and limitations of MSCs in muscle regeneration. tissue that would natively occur, filling the voids of the defect spaces. This approach can improve the overall appearance of the muscle and prevent functional limita- tions resulting from the loss of muscle tissue. Therefore, biomaterials hold great promise in the field of skeletal muscle regeneration, as they can serve as a critical tool in repairing and restoring damaged muscle tissue. In this section, we will introduce the types of acellular and cel- lular biomaterials as scaffolds, delineated in Table 2, and discuss their regenerative characteristics when implanted into animal models. g Human pluripotent stem cells (hPSCs), includ- ing human embryonic stem cells (hESCs) and induced pluripotent stem cells (hiPSCs), possess two key char- acteristics that differentiate them from adult stem cells. Firstly, they have an unlimited capacity to divide and create more cells, referred to as "unlimited proliferative potential." Secondly, they have the ability to differentiate into any type of cell in the body, including skeletal mus- cle cells (SMCs) [11]. These cells can then be expanded in the laboratory settings, and, upon transplantation into native muscle, can populate the stem cell niche and contribute to muscle repair and regeneration [41]. Numerous studies have demonstrated that transplanting hPSC-derived myogenic cells may cause them to merge with host muscle fibers and thereby improve muscular function [41–45]. The mere engraftment of myofibers alone is insufficient for muscle restoration, highlight- ing the need for immune modulation and the release of biological factors from implanted stem cells to enhance the regenerative process [46, 47]. The use of iPSCs to cre- ate patient-specific in vitro skeletal models is another advantage. This allows for the study of the pathogenesis of muscle diseases and the screening of potential drugs in a personalized manner. IPSCs are a powerful tool for understanding the underlying mechanisms of disease and developing therapies tailored to specific patient popula- tions [48]. Various biomaterials such as alginate, gelatin, and col- lagens have been used to engineer 3D acellular scaffolds [49, 50]. These materials offer unique properties that make them suitable for tissue engineering applications. Stem cells for skeletal muscle regeneration In terms of collagens, they are vital components in many biological structures. Collagen type I stands out as the most abundant component in muscle connective tissue. Specifically, collagen type I α1 provides tensile strength and rigidity to tissue, while collagen type VI plays a cru- cial role in regulating satellite cell self-renewal [14, 51]. Although gelatin is a desaturated collagen; it does not provide similar biological properties to collagen and to collagen’s fibrous triplex helix structure. However, depending on the hydrolysis method, gelatin still pos- sesses peptides and proteins that might be broken down during hydrolysis, such as cell binding sites [52]. Also, growth factors such as vascular endothelial cell growth factor (VEGF) and insulin-like growth factor-2 (IGF- 2) have been combined with biomaterials that improve blood vessel perfusion, regenerate damaged axons and increase muscle strength. For instance, when an acellu- lar collagen sponge was inserted into the vastus lateralis of a rabbit leg with a muscle defect, the number, thick- ness, and length of myofibers increased compared to the untreated area, and the concavity decreased by filling of the void muscle area by the scaffold. However, conven- tional biomaterials are often insufficient to mimic tis- sue microenvironment due to lack of growth factors and cytokines for cell proliferation and regeneration [53]. Stem cells for skeletal muscle regeneration Adipose-derived stem cells (ADSCs) are a prevalent, multipotent, adult mesenchymal stem cell type that may develop into tissues of the mesodermal lineage, such as cartilage, bone, adipose tissue, and skeletal muscle. Transplantation of ADSCs has been shown to lead to improved muscle strength and endurance in dystrophin- deficient mice [26, 27], as well as to promote the rapid onset of angiogenesis. Interestingly, ADSCs’ exosomes have also been found to promote the proliferation and expression of myogenic genes [28, 29]. Previous stud- ies have suggested that ADSCs may have the ability to differentiate into muscle cells, but in the specific study being discussed, no direct evidence of implanted ADSCs becoming new muscle fibers was observed [30]. This sug- gests that ADSCs may instead exert their effects through a paracrine mechanism, releasing molecules that support muscle growth and repair, rather than becoming muscle cells themselves [31, 32]. Although mesenchymal stem cells (MSCs) have dem- onstrated potential in promoting skeletal muscle regen- eration by secreting growth factors and differentiating into skeletal muscle cells in various studies [33–38], one notable drawback is that they may not consistently Table 1 Characteristics of stem cells delivered for skeletal muscle regeneration Stem cell Characteristics Animal model Table 1 Characteristics of stem cells delivered for skeletal muscle regeneration Stem cell Characteristics Animal model Drawbacks Refs. SCs - Muscle-specific stem cells - Expression of Pax7 - Ability to differentiate into multiple types of muscle cells Mice cardiotoxin tibialis ante- rior (TA) - Limited numbers of cells - Difficulty to obtain from samples - Loss of regenerative ability over time [24, 25, 154] ADSCs - Paracrine effect for muscle regeneration - Capacity to differentiate into mesodermal lineage - Promotion of angiogenesis Rat VML TA - No direct evidence of myofibers differen- tiation after implantation [26, 28–32] MSCs - Secretion of growth factor for promotion of the regeneration - Increase of myogenin expression Mice ischemia hindlimb - Not always differentiate into the specific type of muscle cell - Possibility to cause immune reactions - Increase of risks of cancers [37–40] hiPSCs - Unlimited proliferative potential - Ability to differentiate into any types of cells - Patient-specific Mice cardiotoxin TA - Limited migrations from the site of injec- tions [11, 41–45] Table 1 Characteristics of stem cells delivered for skeletal muscle regeneration Han et al. Nano Convergence (2023) 10:48 Page 4 of 19 Han et al. 3 Advantages of acellular and cellular biomaterials and their limitations Biomaterials play a crucial role in skeletal muscle regen- eration by providing 3D scaffolds for muscle tissue growth at the defect area. The scaffold provides favora- ble microenvironments that physically support cell attachment, proliferation, and differentiation, serving as a substrate for muscle tissue growth. Biomaterials can be engineered to deliver diverse biological factors, such as cells, growth factors, drugs, miRNAs, and other mol- ecules, directly to the site of injury. This targeted delivery enhances the healing process and facilitates the forma- tion of new muscle tissue, promoting muscle regenera- tion. Moreover, biomaterials can be designed to mimic the structure and mechanical properties of native muscle tissue, guiding the growth and organization of new mus- cle fibers and the maturation of newly formed muscle fib- ers. In cases of large-sized muscle defects, biomaterials can fill the defects and prevent the formation of fibrotic Decellularized extracellular matrix (dECM) scaffolds provide an attractive way to overcome the hurdles of natural and synthetic biomaterials-based scaffolds. Com- pared to transplanted cell-laden tissue, dECM scaffolds have superior biological properties, with a lower risk of immune response due to the removal of almost all cel- lular DNA [54]. Therefore, dECM scaffolds provide a promising strategy for creating a natural cell environ- ment and maintaining various bioactive components that more closely resembles native ECM [55, 56]. Fur- thermore, dECM scaffolds have successfully regenerated damaged muscle tissue as they contain crucial growth factors and cytokines, such as transforming growth Page 5 of 19 Han et al. Nano Convergence (2023) 10:48 Han et al. Nano Convergence Table 2 Characteristics of biomaterials and their combination with stem cell Biomaterial Cell Animal model Growth factors Structure Characteristics Refs. 3 Advantages of acellular and cellular biomaterials and their limitations Acellular Alginate – Mouse ischemia hindlimb VEGF, IGF-2 Bulk hydrogel Reaching normal tissue perfu- sion levels in 3 weeks Regenerating damaged axons in rats with ischemic injury [49] Mouse ischemia hindlimb – Bulk hydrogel Minimizing s invasive surgeries shape-memory alginate [77] Collagen Rabbit acute soft tissue trauma TA VEGF Bulk hydrogel Increasing muscle strength [50] Skeletal muscle-ECM Rat VML latissimus dorsi – Bulk dECM Compatible with host tissue Induced myogenesis increas- ing mechanical stability between damaged areas [66] Musculofascial-ECM Rat VML quadricep – Bulk dECM 20 times higher than muscle ECM in Young’s modulus improving in myogenic properties [69] Cellular Alginate Myoblast Mouse myotoxin/ ischemia hindlimb VEGF, IGF-1 Bulk hydrogel Increasing muscle regenera- tion by sustained release of GF [75] Skeletal muscle-ECM MSCs Rat VML lateral gastrocnemius – Bulk dECM Regenerating blood ves- sels and skeletal myofibers than the ECM without cells [79] Table 2 Characteristics of biomaterials and their combination with stem cell Growth factors Structure Characteristics factor-beta (TGF-β), VEGF, fibroblast growth factor (FGF) and IGF-1 [57]. However, dECM scaffolds have several limitations, such as uncontrolled degradation and inadequate mechanical properties. Also, it is challeng- ing to select the type of cell, tissue, and donor to obtain dECM scaffolds for treating specific types of tissues defects or diseases. ECM components of dECM scaffolds are significantly affected by the source of material such as type of cells, tissue species of donor tissue, etc. For instance, fibroblast-derived dECM is primarily composed of fibronectin and collagen I, while adipose cell-derived dECM contains collagen enriched with VEGF [58, 59]. Lung dECM is characterized by the presence of colla- gen, glycosaminoglycans, and elastin [60]. In contrast, kidney dECM contains glycosaminoglycans along with VEGF and bFGF [61]. Selecting the right tissue or organ for decellularization is challenging because of the need to keep its natural properties, remove all cells without caus- ing immune reactions, and ensure its structure remains intact. Sterilization methods must also be chosen care- fully to maintain the tissue’s safety and function. Each tis- sue has its own unique requirements and challenges for regenerative applications [62]. Sometimes, dense dECM can hinder cell infiltration and impair tissue regenera- tion. Also, it is difficult to create complex 3D architec- tures to resemble the structure of native ECM due to inadequate rheological properties of dECM biomaterials using biofabrication methods. 3 Advantages of acellular and cellular biomaterials and their limitations So, to fabricate large-scale and free-standing 3D scaffolds by microfabrication tech- niques (i.e., bioprinting), naturally derived or synthetic biomaterials have been applied for tuning the physical and rheological properties of dECM biomaterials [63]. Finally, dECM-derived biomaterials obtained from vari- ous types of tissues, such as small intestinal submucosa, dermis, or skeletal muscle tissue, through a decellulariza- tion process, can be made into 3D scaffolds using various microfabrication techniques [64, 65]. Muscle dECM- based scaffolds are compatible with host tissue and play a role as physical bridges that help with force transmission and improve muscle function by increasing mechanical stability between damaged areas [66]. The muscle-dECM, which contains components like proteoglycans and laminin, has been shown to promote the differentiation of satellite cells and their fusion into mature myofiber [67, 68]. Additionally, there is a growing interest in fascial ECM scaffolds for skeletal muscle regeneration. Fascial tissue, as a connective tissue responsible for force trans- mission and physical support, can serve as a template for guiding muscle tissue regeneration. Fascial dECM scaffolds offer a promising approach in this regard [69]. Furthermore, dECM-derived biomaterials can be fabri- cated into hydrogels. Upon implantation at the defective site, these hydrogels facilitate the infiltration of host cells and promote increased myogenesis, or the formation of new muscle tissue [70, 71]. Despite recent advancements in acellular scaffolds that fill muscle defects and provide favorable microenvironments for neo-tissue formation, complete regeneration of volumetric muscle tissue and restoration of muscle function remain challenging. How- ever, the incorporation of myogenic precursor cells or Han et al. Nano Convergence (2023) 10:48 Page 6 of 19 Page 6 of 19 controlled release of growth factors, cytokines, and other bioactive molecules. This localized delivery enhances muscle regeneration by promoting angiogenesis, reduc- ing inflammation, and stimulating myogenesis. Further- more, the unique physical, mechanical, and electrical properties of nanomaterials can overcome limitations of conventional biomaterials, such as lack of mechanical strength, electrical conductivity, and nanofibrous mor- phology. These enhanced properties of hybrid materials improve cellular behaviors and control the differentia- tion of stem cells and their maturation. Moreover, nano- topography achieved through nanostructured surfaces can influence cell behavior, effectively guiding the align- ment and maturation of muscle cells [86]. Nanopatterned substrates facilitate myoblast alignment, myotube forma- tion, and the development of functional muscle tissue constructs. 3 Advantages of acellular and cellular biomaterials and their limitations Additionally, hybrid materials that combine different nanoscale components show promise in terms of mechanical reinforcement, controlled release capabili- ties, and improved cellular interactions for muscle tissue engineering [87]. The following sections provide recent advances in nanotechnology for each respective applica- tion area (Table 3). stem cells into biomaterials holds promise in overcoming these challenges, as they possess remarkable regenerative abilities. Cell-laden biomaterials have been shown to restore both morphology and function in the area where VML occurred [72, 73]. Moreover, combining growth fac- tors with the scaffold has been attempted to increase the regeneration of cells in the scaffold and host tissue [74, 75]. Research has also been conducted on muscle regeneration based on the types of stem cells and scaf- folds, as well as applied mechanical stimulation [76–78]. Even when a scaffold containing non-muscle-derived stem cells was implanted, the effects of muscle regenera- tion were observed [79]. For instance, when bone mar- row derived MSCs with skeletal muscle dECM hydrogels were implanted into the lateral gastrocnemius in a VML rat model, increased von Willebrand factor stained blood vessels and recovery in the tension forces of LGAS resulted, as compared to observations in the muscles implanted with dECM without cells. Pre-implantation of cells isolated from the tibialis anterior (TA) of rats in a bladder acellular matrix with uniaxial tension using a bioreactor has also induced enhanced functional recov- ery in a mouse latissimus dorsi (LD) VML model [80, 81]. Continued exploration of cellular biomaterials and their applications in skeletal muscle regeneration will undoubtedly yield exciting developments and insights in the coming years. One of the key limitations and biosafety concerns associated with the use of stem cells in the clinical field is the potential for tumorigenicity [82]. Stem cells are highly beneficial for tissue engineering and regenerative medicine because they can self-renew and differentiate into various kinds of cells. However, this same property can lead to the formation of tumors if the transplanted stem cells undergo uncontrolled growth. To prevent the tumorigenesis in stem cells transplantation, stem cells should be genetically screened to define cell fate and change the cancer-related genes through epi- genic modifications [83]. Carbon nanotubes (CNTs) are cylindrical carbon tubes with high aspect ratios and nanometer-diameters that can be significantly longer than 100 nm [88]. They pos- sess superior mechanical properties, large surface areas, and electrical conductivity properties. In a study by Ramón-Azcón et al. 3 Advantages of acellular and cellular biomaterials and their limitations [89], dielectrophoresis was used to align multi-walled CNTs within GelMA hydrogel. It was observed that the electrical conductivity of the GelMA hydrogel increased as a result, leading to elevated gene expression of myogenic differentiation markers (such as sarcomeric actin and myogenin) in C2C12 myoblasts. This effect was not observed with randomly dispersed CNTs within GelMA hydrogel, indicating the enhanced efficiency of electrical stimulation due to alignment. Incorporating polydopamine-coated CNTs into gelatin- based cryogels promoted muscle regeneration in a rat TA muscle defect model. This enhancement was attributed to the improved mechanical properties and conductiv- ity of the cryogels, which facilitated enhanced muscle cell communication and signal transduction (Fig. 2A) [90]. 4 Nanotechnology for muscle regeneration 4 Nanotechnology for muscle regeneration In recent research on developing advanced biomateri- als, the application of nanotechnology, including pro- viding precise control over surface characteristics, has become essential because it allows for creating scaffolds that closely resemble the structures and mechanical properties of the native ECM [84]. This engineering of ECM-mimicking structures promotes cellular adhesion, proliferation, and differentiation, enhancing muscle tis- sue regeneration. Preferentially, the term “nanomateri- als” or “nano-sized materials” refers to substances with at least one dimension less than 100 nm [85]. Nanoma- terials can be utilized as carriers for the targeted and Graphene is an allotrope of carbon that exists in a 2D monolayer with a honeycomb pattern and has π-π bonds between carbon layers. The distance between car- bon atoms in their hexagonal framework is around 140 nm, and the integral strong covalent bonding allows the structure of graphene to maintain a few hundred-folds higher tensile strength than steel [91]. Graphene oxide (GO) is an oxidized form of graphene having func- tional groups that include oxygen, such as hydroxyl, car- boxyl, and epoxy carbonyl, making the final substance Page 7 of 19 Han et al. Nano Convergence (2023) 10:48 Han et al. Nano Convergence Table 3 Nanomaterials for muscle regeneration Materials Cell Animal model 3D structure Feature Refs. CNT Polydopamine coated CNT/ Gelatin C2C12 Rat VML TA Tubular cryogel Inducing myogenic differen- tiation of C2C12 and muscle regeneration by polydopamine coated CNT [90] Graphene Polydopamine/rGO aerogel C2C12 Mouse denervated gastrocne- mius muscle Bulk aerogel Promoting the weight, fiber size, and contractile force of the den- ervated muscles [95] Polycitrate-based rGO C2C12 Rat VML TA Rectangle film Fabricating highly conductive and elastomeric and enhancing myogenic gene expression [97] Exosome Myostatin propeptide conjugated exosome – mdx mouse cardiotoxin TA – Increasing muscle mass and func- tional rescue without any detect- able toxicity in mdx mice [102] PLGA-PEG PTEN inhibitor C2C12 – – Promoting the selective uptake by muscle cells/tissue in vitro and in vivo [104] AuNP IL-4 or IL-10 – mdx mouse VML TA – Improving muscle function in murine DMD model [105] F-127-polydopamine NP C2C12 Rat VML TA Bulk hydrogel Regenerating structural and func- tional in the VML mouse model [107] Table 3 Nanomaterials for muscle regeneration water-dispersible [92]. C2C12 myoblasts cultured on GO substrate significantly increased their myogenic proteins, such as myosin heavy chain and myogenin [93]. (See figure on next page.) Fig. 2 Nanomaterials and nanostructures for engineering skeletal muscle tissues and improving muscle regeneration. A. 3D Anisotropic cryogels composed of conductive aligned polydopamine coated carbon nanotubes (PCNTs) for muscle regeneration. (i) Schematic of the fabrication of PCNT cryogel [90]. (ii) Compressive, conductive and highly aligned skeletal muscle PCNT cryogel mimicking mechanical properties of natural muscle and inducing cell alignment and differentiation. (iii) Evaluation of in vivo muscle regeneration in a rat TA muscle defect model after implantation of the PCNT cryogel for 4 weeks. Red arrows indicate the presence of freshly created blood vessels, while black arrows indicate the newly formed muscle fibers assessed by centronucleated myofibers. B. Anti-inflammatory cytokine immobilized AuNPs for improving muscle function in dystrophic mice. (i) Schematic showing PEGylation and interleukin-4 (IL-4) conjugations to AuNPs for T cell recruitment and muscle function improvement. (ii) Enhancement of muscle functions observed in mdx mice by IL 4-conjugated AuNPs. Scale bar: 300 μm [105]. C. Stretchable nanofibrous sheet using coaxial electrospinning for improving muscle regeneration. (i) Schematic showing co-axial electrospinning of PCL and gelatin solutions, followed by chemical crosslinking of the gelatin core using glutaraldehyde. The sacrificial PCL layers were removed to produce gelatin co-axial nanofibers (NF). (ii) NF5 + C2C12 (5% stretched nanofiber with cell) showed the largest muscle regeneration compared to NF0 + cell (unstretched nanofiber with cell) or NF0 (unstretched nanofiber) (n: interface between host tissue and implants. o: host muscle tissue) [111]. (iii) Stretchable nanofiber for enhancing myotube formation. D. Nanostructured fibers resembling the ordered and striated pattern of myofibrils via self-assembly of ABA triblock copolymers.. (i) Schematic showing the fiber fabrication process and structural characteristics of the fiber. (ii) Nanostructured fiber mimicking the patterns (A and I band) and the size of myofibril. (iii) Images showing elongation ratios ranging from one to five. As the elongation ratio increased, the diameters of the subsequently treated fibers rapidly decreased [112] 4 Nanotechnology for muscle regeneration Nano Convergence (2023) 10:48 patterns on GO-incorporated polyacrylamide hydro- gel. When C2C12 myoblasts were cultured on these macro-patterned substrates and subjected to electrical stimulation, they exhibited improved myogenesis and increased differentiation. Electrospinning, a technique capable of producing nanofibers ranging from 100 nm to several micrometers in diameter, was utilized in combi- nation with nanomaterials like GO to fabricate muscle constructs using C2C12 myoblasts [111] (Fig. 2C). Lang et al. [112] developed myofibril-resembling fibers with I and A band patterns using poly(styrene)-b-poly(ethylene oxide)-b-poly(styrene) through the solvent injection technique. These fibers demonstrated superior efficiency, actuation strain, and mechanical properties compared to existing actuators (Fig. 2D). messenger RNA, microRNA, or other proteins, and act as messengers to transfer these proteins to other cells [100]. MSC-derived exosomes have been found to pro- mote myogenesis in both in vitro and in vivo studies, potentially mediated by the presence of miRNA mol- ecules. For instance, miR-494, found in MSC-exosomes, has been shown to enhance regeneration processes [101]. Ran et al. [102] anchored myostatin propeptide, a nega- tive regulator of muscle growth [103], into the CD63 loop. This inhibited myostatin activity and was observed to have beneficial effects in mdx mice [102]. Huang et al. [104] used M12-conjugated poly(lactic-co-glycolic acid)- polyethylene glycol (PLGA-PEG) to selectively deliver phosphatase and tensin homolog inhibitors to mus- cle cells in vivo, leading to improved muscle growth. AuNPs were employed to conjugate anti-inflammatory cytokines, such as IL-4, for the purpose of enhancing muscle function in mdx mouse models, through immune cell recruitment [105] (Fig. 2B). Ge et al. [106, 107] dem- onstrated that AuNPs can stimulate myogenic differen- tiation via p38 mitogen-activated protein kinase (MAPK) signaling. Furthermore, they found that combining AuNPs with hydrogels and injecting them into rat muscle defect models facilitated muscle tissue formation. Overall, nanomaterials hold great potential as a tool for enhancing skeletal muscle regeneration due to their unique mechanical and electrical properties or delivery of biological factors. However, it is worth noting that most in vitro experiments have used C2C12 myoblasts, an immortalized cell line, rather than primary cells or stem cells [12]. Further research utilizing primary cells and stem cells is essential to gain a comprehensive under- standing of the effectiveness and safety of these materials, paving the way for their translation into clinical practice. 4 Nanotechnology for muscle regeneration The heightened myogenic behavior observed on GO surfaces can be attributed to the surface oxygen concentration and roughness, which have an impact on serum protein adsorption. Moreover, highly wrinkled GO substrates were found to promote greater cell adhesion regions and more efficient myogenic differentiation [94]. Wang et al. [95] fabricated ultralight, conductive, and elastic aero- gels using polydopamine and reduced GO (rGO), which enabled the promotion of fiber size and contractile forces of the denervated muscle. Annabi et al. [96] developed a conductive hydrogel by combining GO with the elastic natural material tropoelastin, which resulted in a hydro- gel with 250% ultimate strain and 9700° of reversible rotation. The added electric conductivity of GO allowed for muscle contraction with low voltage after implanta- tion of the hydrogel in rat abdominal muscle. Similarly, Du et al. [97] added rGO to poly(citric acid-octanediol- polyethylene glycol) (PCE) to provide conductivity, and they observed improved expression levels of MyoD, myo- genin, and Troponin T, as well as the development of new muscle tissue and an increase in the mass of centronucle- ated myofibers and capillaries within a week. i Other nanoparticles, such as exosomes and gold nan- oparticles (AuNPs), have been used in skeletal muscle regeneration. They can be used in combination with Han et al. Nano Convergence (2023) 10:48 Page 8 of 19 Han et al. Nano Convergence Page 8 of 1 Han et al. Nano Convergence (2023) 10:48 proteins for targeted delivery as they have unique prop- erties. For instance, AuNPs exhibit high surface activity, strong antioxidant properties, and good biocompatibility, while exosomes possess innate stability, low immuno genicity, and excellent cell penetration capacity [98, 99] Exosomes, a natural biological nanoparticle, contain Fig. 2 (See legend on previous page.) Fig. 2 (See legend on previous page.) Fig. 2 (See legend on previous page.) Fig. 2 (See legend on previous page.) Fig. 2 (See legend on previous page.) while exosomes possess innate stability, low immuno- genicity, and excellent cell penetration capacity [98, 99]. Exosomes, a natural biological nanoparticle, contain proteins for targeted delivery as they have unique prop- erties. For instance, AuNPs exhibit high surface activity, strong antioxidant properties, and good biocompatibility, while exosomes possess innate stability, low immuno- genicity, and excellent cell penetration capacity [98, 99]. Exosomes, a natural biological nanoparticle, contain Han et al. Nano Convergence (2023) 10:48 Page 9 of 19 Han et al. 4 Nanotechnology for muscle regeneration Additionally, it is crucial to address the long-term safety issues and limitations associated with non-biodegrada- ble nanomaterials, such as bioaccumulation, long-term exposure effects, and off-target effects [113]. Nanomaterials, including GO, have been employed in tissue engineering to fabricate skeletal muscle con- structs. A summary of these applications can be found in Table 4. Kim et al. [108] used graphene to create stretch- able and implantable electric devices using patterning. Graphene was capable of regulating the proliferation and differentiation of C2C12 myoblasts and reading electro- myographical signals when implanted. Patel et al. [109] used CNTs to create nano-functionalized foam scaf- folds via a pyrolysis technique, and the CNTs were then aligned to significantly increase the fusion of C2C12 myoblasts into multinucleated myotubes. Park et al. [110] used femtosecond laser ablation to create line 5 Engineering 3D muscle tissues for skeletal muscle regenerationh The fabrication of functional 3D muscle tissues by tis- sue engineering offers significant potential as an alter- native therapy since it may restore the structure and function of damaged muscle tissue. Accelerated mus- cle tissue formation and integration can be achieved by Table 4 Technique for fabricating nanostructure Technique Materials Cell Animal model 3D structure Feature (Add size in the feature) Refs. Electrospinning PCL/gelatin C2C12 Mouse VML quadriceps Fiber Enhancing myotube formation on the nanofiber scaffold [111] Patterning Graphene Mouse VML hind limb Mesh pattern Stimulating implanted sites electrically and/ or optically in vivo and recoding electromyo- graphical signals [108] Pyrolysis Nanostructured CNT – Foam, fiber Enhancing myocyte fusion into multinucleated mature myotubes [109] Laser ablation GO/polyacrylamide – Line pattern Micropatterned rGO/PAAm hydrogel enhancing myogenesis and increased differentiation [110] Solvent injection poly(styrene)-b- poly(ethylene oxide)-b- poly(styrene) – – Fiber Resembling myofibril (I, A band) and excelling in efficiency, actuation strain and mechanical properties over current actuators [112] Table 4 Technique for fabricating nanostructure Han et al. Nano Convergence (2023) 10:48 Han et al. Nano Convergence (2023) 10:48 Page 10 of 19 Page 10 of 19 but also introduce unique functionalities, like pH- responsiveness and electro-conductivity. Furthermore, nanomaterials enable targeted and controlled delivery of various biomolecules, including miRNA, proteins or drugs, resulted in improving biological properties of the bioinks. These hybrid bioinks closely mimic the anatomy and function of native extracellular matrix to improve tissue-engineered muscle performance and regeneration. Table 5 summarizes the investiga- tion and findings on the utilization of various printing techniques, along with nano-biomaterials and stem cells, for muscle regeneration in the context of tissue engineering. conferring constructs with biomimetic physical proper- ties and architectures and integrating skeletal muscle and other cells, such as endothelial cells and neurons. To mimic highly aligned muscle fibers and organ- ized vessel networks like native muscle tissue, various nano- and micro-fabrication techniques have been developed. Bioprinting, including in-situ and ex-situ, and electrospinning technologies have been used to integrate and implant different types of cells in a scal- able manner. Furthermore, hydrogel-based bioinks can be fortified with specific nanomaterials, such as GO, AuNPs, laponite and CNTs to enhance their printability and mechanical properties [114]. These diverse nano- materials not only provide mechanical reinforcement Table 5 Bioprinting for generation of functional skeletal muscle construct Table 5 Bioprinting for generation of functional skeletal muscle construct Printing methods Materials Cells Animal model Features Refs. 5.1 Bioprintingh The use of 3D printing technology in tissue engineering has shown promising results for skeletal muscle regen- eration. This approach involves using additive manufac- turing techniques to create complex muscle structures that mimic the native tissue’s design and function [115] (Fig. 3A). Bioprinting has been used to print muscle constructs using myoblast cell lines like C2C12, but more recently, stem cells have been used for muscle regenera- tion and repair [116, 117]. Bioprinting enables precise control of the spatial organization of cells, allowing for improved tissue engineering outcomes. In one study, inkjet bioprinting was used to engineer a spatially defined microenvironment for primary muscle-derived stem cells, promoting their differentiation into osteogenic or myogenic cells [118].h The bioprinting strategy for muscle regeneration involves developing new printing methods or printing cells that interact with muscle, such as neural cells or endothelial cells, in a spatially heterogeneous manner. For example, Kang et al. [119] developed the integrated tissue-organ printer (ITOP), which allows for the produc- tion of human-scale tissue. They used this technology with fibrinogen (fib), gelatin, hyaluronic acid (HA) and glycerol mixed bioink to construct a biomimetic implant- able human skeletal muscle construct made up of tightly packed, viable, and aligned human primary muscle pro- genitor cells (hMPCs) [119, 120]. In another study, ITOP was used to create neuro-muscular junctions between hMPCs and human neural stem cells (hNSCs) with the same bioink as above, promoting rapid innervation in a rodent model of muscle defect injury [121] (Fig. 3B). When applied to a rat TA muscle defect model, about 1 × 105 hNSCs were bioprinted with hMPCs in the mid- dle third of the TA, demonstrating successful innerva- tion over a span of 8 weeks. The addition of neurotrophic factors in a PLGA microsphere further accelerated nerve regeneration and innervation in hMPCs bioprinted mus- cle constructs [122]. Multi-material bioprinting was used to replicate muscle structural integrity by depositing per- fusable vasculatures and aligned hiPSC-MPC channels within an endomysium-like supporting gel [123]. Human The electroconductive nature of nanomaterials, such as graphene and its family, facilitates the upregulation of myogenic gene expression in myoblasts. For exam- ple, in a study by Jo et al. [128], GO-incorporated elec- troconductive polyacrylamide hydrogels could enhance myogenic gene expression in myoblasts through cellular interactions with the electrical and mechanical signals provided by the nanomaterials. 5 Engineering 3D muscle tissues for skeletal muscle regenerationh Inkjet printing Fib/BMP-2 hMPCs – Controlling cells fate of primary muscle derived stem cells toward osteogenic or myogenic cells by BMP-2 patterning [118] 3D ITOP Fib/gelatin/ HA/glycerol hMPCs Rat VML TA Fabricating biomimetic implant- able human skeletal muscle construct (mm3-cm3 size) made up of hundreds of long parallel myofiber bundles [120] Fib/gelatin/ HA/glycerol hMPCs/hNSCs Rat VML TA Forming neuro-muscular junction and facilitating rapid innervations in rodent model [121] Fib/NF loaded microsphere hMPCs – Accelerating peripheral nerve regeneration and innervation by release NF delivery [122] Extrusion Au nanowires/collagen C2C12 Rat VML temporalis muscle Increasing C2C12 differentiation by aligned in Au nanowires [130] Collagen hADSC/HUVEC Rat VML temporalis muscle Achieving in-situ direct bioprint- ing by combining bioprinting with bioreactor enabling [145] dECM – Canine VML biceps femoris Acellular 3D bioprinted dECM patches for implantation of bulk patient-specific scaffold (12 × 8 × 2 cm) based on com- puted tomography imaging [127] Collagen hMSCs Rat VML TA Fabricating collagen microfiber with 1,000 times higher tensile strengths than a normal col- lagen gel [124] SLA Oxidized methacrylic alginate/ PEGMA Primary neurons/C2C12 – Demonstrating spatial control of neurons and myoblasts for enhancing functionality of neurons [125] DLP Poly (glycerol sebacate) acrylate C2C12 Rat VML TA Tuning of mechanical and geo- metrical cues through 3D print- ing process [126] Embedded printing GelMA hiPSC-MPCs/HUVEC Mouse VML quadriceps Forming endothelialized perfus- able channels with increasing iPSC-MPC’s viability and func- tionality [123] Refs. Page 11 of 19 Page 11 of 19 Han et al. Nano Convergence (2023) 10:48 Han et al. Nano Convergence (2023) 10:48 umbilical vein endothelial cell (HUVEC) at a density of 4 × 107 cells were bioprinted within the gelatin to create a perfusable endothelialized microchannel. After implanta- tion subcutaneously for 4 weeks, the structure sustained the viability and function of the muscle cells in vivo This resulted in a high degree of alignment and effec- tive formation of myotubes in 1 cm3 hexahedral GelMA. Another technique called assembled cell-decorated colla- gen (AC-DC) bioprinting was invented to generate colla- gen microfibers with 100 μm diameter coated with MPCs or hMSCs resulting in a ring shaped structure around 10 mm in diameter, which had almost 1000 times higher tensile strength than normal collagen gels [124]. Digital light processing (DLP) and stereolithography (SLA) bio- printing were also used to precisely control (~ 5 μm) the location of heterogenous cells [125, 126]. Fig. 3 Recent bioprinting strategy for the generation of functional skeletal muscle construct. A. Pros and cons of bioprinting technique for fabricating skeletal muscle tissue. B. Neural cell integration with bioprinted skeletal muscle constructs. (i) The bioprinted construct’s design, where the multi-dispensing units are applied with the acellular sacrificial bioink, the cell-laden bioink carrying hMPCs and/or hNSCs, and the supporting PCL structure. (ii) Microchannels to preserve the viability of printed cells in the structures made after the sacrificial designs were removed. (iii) MPC + NPC group showed developed neuromuscular junctions and neuronal contact on the freshly created myofibers in the transplanted constructs. (Neurofilaments; NF (green)/Acetylcholine receptor; AChR (red)/Myosin heavy chain; MHC (white)) [121]. C. In-situ bioprinting of hASC-laden bioink for muscle regeneration. (i) Schematic of directly printed hASC-laden collagen structure on damaged human skeletal muscle using the bioprinter-actuator combined system. (ii) Images of in-situ bioprinting using a bioprinter-actuator combined system in rat temporalis muscle VML model [145]. D. Future direction for generating functional skeletal muscle tissue (See figure on next page.) 5 Engineering 3D muscle tissues for skeletal muscle regenerationh Finally, acellu- lar 3D bioprinted urinary bladder matrix dECM patches (≈ 12 × 8 × 2 cm) were used for implantation of a bulk patient-specific scaffold based on CT imaging, allowing for precise adaptation to complex wounds [127].h Fig. 3 (See legend on previous page.) 5.3 Other engineered 3D muscle tissues Various engineered 3D muscle tissues, through molding and microfluidics have been used, in addition to bioprint- ing, to produce muscle constructs. Molding is a popular method for creating 3D muscle tissue using stem cells and hydrogels. Collagen and fibrinogen are commonly used polymers, as they are easily crosslinked. The type of biomaterial used does not significantly affect the dif- ferentiation of stem cells [76]. For instance, a mixture of collagen and hMPCs was used to create a 3D structure for laryngeal reconstruction [146]. Molding is not only used for implantation but also for in vitro models, and can be used to study the effects of culture media on hPSC myogenesis and contractile force, or as an intramuscular injection model for drug testing [147, 148]. In addition, fiber-shaped molds can be used to create single fibers with a length of 10 mm and diameter of 120 μm. When ESC-derived myoblasts were placed in Matrigel inside a mold, muscle maturation could be observed within 7 days [149].l Microfluidic devices have been used as models to study the interactions between different tissues, including mus- cle tissue. Osaki et al. [150] used a microfluidic chip to culture muscle bundles and iPSC-derived motor neuron spheroids in different compartments to create an amyo- trophic lateral sclerosis (ALS) model. In the chip-based ALS motor unit, fewer muscle contractions and mus- cle apoptosis were observed. Microfluidic chips offer a promising platform for assessing the safety of nano- materials in muscle regeneration. Their inherent ability to produce laminar flow ensures a uniform exposure of nanomaterials to cells [151]. Additionally, by manipulat- ing the flow rate, there is precise control over the cellular uptake of these nanomaterials [152]. Given their suc- cessful applications in skin models, it is anticipated that microfluidic chips will find extensive utility in muscle models in forthcoming research [153]. In-situ bioprinting has been highlighted as a core methodology for muscle regeneration due to the feasible extensive processing times and post-bioprinting manip- ulations. Quint et al. [142] developed a VEGF-releasing nanomaterials-based bioink printed using a portable in- situ printer. The bioink incorporated laponite, an artifi- cially manufactured nano-structure, to control the release of VEGF, enhance its adhesion to the muscle surface, increase the rheological behavior of bioinks, and increase mechanical properties due to entanglement with GelMA. This approach synergistically modulated the wound environment, leading to improved functional mus- cle recovery after VML in a murine model. 5.1 Bioprintingh This unique GO sub- stance could be easily incorporated into bioinks due to its hydrophilic nature, excellent water solubility, and easy chemical modification. For examples, the incorporation of GO as a component for a myogenesis-inducing mate- rial, into phenol-rich gelatin hydrogels used for 3D print- ing has been shown to improve thermal stability, increase molecular interactions, and potentially influence the patterning process during bioprinting, making the print- ing process more efficient [129]. Later, 3D printed GO/ phenol-rich gelatin hydrogel patterns provided suitable microenvironments for improving myogenic differen- tiation of C2C12 cells, showing potential for muscle tis- sue engineering and regenerative medicine. C2C12 cells were also mixed with gold nanowires in collagen bioink, Han et al. Nano Convergence (2023) 10:48 Page 12 of 19 Han et al. Nano Convergence Fig. 3 (See legend on previous page.) Han et al. Nano Convergence (2023) 10:48 Page 13 of 19 Page 13 of 19 printed and then exposed to electric fields to align the nanowires [130]. This resulted in a high degree of align- ment and effective formation of myotubes. a partially-automated handheld bioprinter [143]. The results showed the formation of multinucleated myo- tubes 24 days post-printing, indicating the promising potential of in-situ bioprinting in muscle regeneration [144]. In-situ bioprinting of human ADSCs (hADSCs) with collagen in the VML area was achieved using a bioprinter combined with a bioreactor called Pri-Actor [145] (Fig. 3C). Myogenic differentiation of hADSCs was induced by the mechanical stimulation in the bioreactor, leading to the formation dense myofibers in VML model of rat in the temporalis muscle. In-situ bioprinting repre- sents a significant step forward in regenerative medicine, showing potential in muscle regeneration. 5.2 In‑situ bioprinting In-situ bioprinting technology has been extensively explored to create complex and heterogeneous archi- tectures of engineered constructs directly following their sophisticated deposition in custom designed pat- terns to fill cutaneous injured area [131–135]. Theses in-situ printing technologies have the potential to pro- vide improved tissue regeneration ability for individual patients compared to ex-situ printed implants due to benefits proffered by the natural cellular microenviron- ment of the body [136–139] and from the ability to fab- ricate customized acellular or cellular scaffolds that fit different injured area and shapes on individual patients [131–134]. In recent advancements of in-situ bioprint- ing, there is a clear inclination towards incorporating novel tools to enhance the precision and adaptability of the printing process. For examples, robotic and hand- held bioprinting devices are being increasingly utilized for targeted deposition of bioinks, especially, in areas requiring wound, skin, bone, muscle, and cartilage regen- eration [137, 138]. The integration of camera systems and scanners provides real-time feedback, ensuring accu- rate placement and alignment of printed tissues [140]. The emergence of multi-degree-of-freedom bioprint- ing robots, equipped with advanced sensing and imag- ing capabilities, highlighted the intersection of robotics, imaging, and bioprinting in addressing intricate chal- lenges, such as hair-follicle-inclusive skin repair [141]. This integration signifies the growing role of in-situ bio- printing within the broader context of regenerative medi- cine and tissue engineering. Author contributions h l d Looking towards the future, there are several avenues of research that are most relevant and productive. These include exploring the use of new materials and nanotech- nology for tissue engineering, developing new methods for in vitro muscle maturation and neural integration, and investigating the use of iPSCs and gene editing tech- niques for personalized therapies. Furthermore, advance- ments in artificial intelligence and machine learning can The review was planned by SH and SRS. SH and SHC wrote the manuscript. SH, SRS and SP contributed to the discussion and editing. SRS provided overall supervision. All authors read and approved the final manuscript. 5.3 Other engineered 3D muscle tissues In a related study by the same group, C2C12 myoblasts encapsulated in a GelMA bioink were directly printed onto a VML murine model (79 ± 7.5 mg resection) injury site using Han et al. Nano Convergence (2023) 10:48 Page 14 of 19 Han et al. Nano Convergence (2023) 10:48 Han et al. Nano Convergence help to optimize scaffold design and improve the efficacy of clinical treatments. Abbreviations Abbreviations 3D Three-dimentional VML Volumetric muscle loss ECM Extracellular matrix ADSCs Adipose-derived stem cells MSCs Mesenchymal stem cells hPSC Human pluripotent stem cells hESCs Human embryonic stem cells hiPSCs Human induced pluripotent stem cells SMCs Skeletal muscle cells hMPCs Human primary muscle progenitor cells IGF-1 Insulin-like growth factor-1 IGF-2 Insulin-like growth factor-2 TGF-β Transforming growth factor-beta VEGF Vascular endothelial growth factor HGF Hepatocyte growth factor FGF-2 Fibroblast growth factor-2 dECM Decellularized ECM PCE Poly(citric acid-octanediol-polyethylene glycol) MAPK Mitogen-activated protein kinase CNT Carbon nanotube ITOP Integrated tissue-organ printer GO Graphene oxide NPs Nanoparticles hNSCs Human neural stem cells HUVEC Human umbilical vein endothelial cell NF Neurotrophic factor PLGA Poly(lactic-co-glycolic acid) AuNPs Gold nanoparticles PCL Polycaprolactone PEG Poly(ethylene glycol) IL Interleukin TA Tibialis anterior Fib Fibrinogen BMP-2 Bone morphogenetic protein-2 SLA Stereolithography DLP Digital light processing CT Computed tomography AC-DC Assembled cell-decorated collagen LD Latissimus dorsi f One of the most promising fabrication techniques for producing muscle scaffolds is 3D bioprinting com- bined with nanomaterials and nanotechnologies. This technique enables the precise positioning of acellular or cellular structures, resulting in a biomimetic scaffold that mimics the natural tissue. Additionally, computed tomography (CT)-guided bioprinting can be used to rep- licate the tissue microarchitecture obtained from patient CT images following an injury, leading to the creation of custom scaffolds tailored to individual patients. Once proven effective in a mouse model, custom scaffolds will undergo Phase I testing before being considered for use in human patients (Fig. 3D). The biomanufacturing industry is another area that holds great promise in the production of functional tis- sues for direct implantation in patients. By using 3D bio- printing to digitally design the scaffold and establishing automated or semi-automated biomanufacturing pro- cesses, it can improve the quality of an acellular or cel- lular scaffold and ultimately lead to enhanced efficacy of implants and related clinical therapies. The ability to fabricate and culture tissues in a high throughput man- ner and in real-time can greatly improve the speed and efficiency of the biomanufacturing process, making treat- ments more accessible to patients in need. 6 Conclusion and future perspectives In conclusion, the development of skeletal muscle tis- sue engineering has led to promising advances in the field of regenerative medicine. As the understanding of the complex interplay among cells, materials, and mechanical forces continues to grow, new research areas will emerge, leading to the full realization of the potential of personalized, customized, and biomanu- facturable platforms for muscle regeneration. Nano- materials, indeed, offer great potential for muscle regeneration. However, the exact mechanism behind their effectiveness still requires deeper exploration for clinical translation. It is speculated that scaffolds built using nanomaterials like GO, CNT, and AuNP not only enhance mechanical and electrical properties but also influence the differentiation and proliferation of myo- genic stem cells. Furthermore, safety issues related to the application of non-biodegradable nanomateri- als, such as bio-accumulation or long-term exposure effects, need to be considered. In summary, the novel approaches discussed in this review have the potential to significantly enhance the patient’s quality of life. By continuing to invest in research and development in the field of skeletal mus- cle tissue engineering, we can accelerate the transla- tion of these promising therapies into clinical practice, ultimately improving the lives of millions of people worldwide. References 1. K. Garg, C.L. Ward, B.J. Hurtgen, J.M. Wilken, D.J. Stinner, J.C. Wenke, J.G. Owens, B.T. Corona, Volumetric muscle loss: persistent functional defi- cits beyond frank loss of tissue. J. Orthop. Res. 33, 40–46 (2015). https:// doi.org/10.1002/jor.22730 21. S. Günther, J. Kim, S. Kostin, C. Lepper, C.-M. Fan, T. Braun, Myf5-positive satellite cells contribute to Pax7-dependent long-term maintenance of adult muscle stem cells. Cell Stem Cell 13, 590–601 (2013). https://doi. org/10.1016/j.stem.2013.07.016 2. B.F. Grogan, J.R. Hsu, Volumetric muscle loss. J. Am. Acad. Orthop. Surg. 19, S35–S37 (2011). https://doi.org/10.5435/00124635-20110 2001-00007 22. P. Seale, L.A. Sabourin, A. Girgis-Gabardo, A. Mansouri, P. Gruss, M.A. Rudnicki, Pax7 is required for the specification of myogenic satellite cells. Cell 102, 777–786 (2000). https://doi.org/10.1016/s0092-8674(00) 00066-0 3. J. Gilbert-Honick, S.R. Iyer, S.M. Somers, R.M. Lovering, K. Wagner, H.-Q. Mao, W.L. Grayson, Engineering functional and histological regeneration of vascularized skeletal muscle. Biomaterials 164, 70–79 (2018). https://doi.org/10.1016/j.biomaterials.2018.02.006 23. A. Marg, H. Escobar, S. Gloy, M. Kufeld, J. Zacher, A. Spuler, C. Birchmeier, Z. Izsvák, S. Spuler, Human satellite cells have regenerative capacity and are genetically manipulable. J. Clin. Investig. 124, 4257–4265 (2020). https://doi.org/10.1172/JCI63992 4. A. Dunn, M. Talovic, K. Patel, A. Patel, M. Marcinczyk, K. Garg, Bioma- terial and stem cell-based strategies for skeletal muscle regenera- tion. J. Orthop. Res. 37, 1246–1262 (2019). https://doi.org/10.1038/ s41536-020-0094-3 24. H. Yin, F. Price, M.A. Rudnicki, Satellite cells and the muscle stem cell niche. Physiol. Rev. 93, 23–67 (2013). https://doi.org/10.1152/physrev. 00043.2011 5. R.N. Judson, F.M. Rossi, Towards stem cell therapies for skeletal muscle repair. NPJ Regen. Med. 5, 10 (2020). https://doi.org/10.1038/ s41536-020-0094-3 25. S.S. Rayagiri, D. Ranaldi, A. Raven, N.I.F.M. Azhar, O. Lefebvre, P.S. Zammit, A.-G. Borycki, Basal lamina remodeling at the skeletal muscle stem cell niche mediates stem cell self-renewal. Nat. Commun. 9, 1–12 (2018). https://doi.org/10.1038/s41467-018-03425-3 6. M. Juhas, G.C. Engelmayr Jr., A.N. Fontanella, G.M. Palmer, N. Bursac, Bio- mimetic engineered muscle with capacity for vascular integration and functional maturation in vivo. Proc. Natl. Acad. Sci. USA 111, 5508–5513 (2014). https://doi.org/10.1073/pnas.1402723111 p g 26. S.-V. Forcales, Potential of adipose-derived stem cells in muscular regenerative therapies. Front. Aging Neurosci. 7, 123 (2015). https://doi. org/10.3389/fnagi.2015.00123 7. T.H. Qazi, G.N. Duda, M.J. Ort, C. Perka, S. Geissler, T. Winkler, Cell therapy to improve regeneration of skeletal muscle injuries. J. Cachexia. Sarco- penia Muscle 10, 501–516 (2019). https://doi.org/10.1002/jcsm.12416 27. C.H. da Justa Pinheiro, J.C.F. de Queiroz, L. Guimarães-Ferreira, K.F. Vitzel, R.T. Nachbar, L.G.O. de Sousa, A.L. References de Souza-Jr, M.T. Nunes, R. Curi, Local injections of adipose-derived mesenchymal stem cells modulate inflammation and increase angiogenesis ameliorating the dystrophic phenotype in dystrophin-deficient skeletal muscle. Stem Cell Rev. Rep. 8, 363–374 (2012). https://doi.org/10.1007/s12015-011-9304-0 8. C.S. Ong, P. Yesantharao, C.Y. Huang, G. Mattson, J. Boktor, T. Fukunishi, H. Zhang, N. Hibino, 3D bioprinting using stem cells. Pediatr. Res. 83, 223–231 (2018). https://doi.org/10.1038/pr.2017.252 9. M. Mehrali, A. Thakur, C.P. Pennisi, S. Talebian, A. Arpanaei, M. Nikkhah, A. Dolatshahi-Pirouz, Nanoreinforced hydrogels for tissue engineering: biomaterials that are compatible with load-bearing and electroactive tissues. Adv. Mater. 29, 1603612 (2017). https://doi.org/10.1002/adma. 201603612 28. V. Kesireddy, Evaluation of adipose-derived stem cells for tissue- engineered muscle repair construct-mediated repair of a murine model of volumetric muscle loss injury. Int. J. Nanomedicine 11, 1461 (2016). https://doi.org/10.2147/IJN.S101955 10. J.M. Grasman, M.J. Zayas, R.L. Page, G.D. Pins, Biomimetic scaffolds for regeneration of volumetric muscle loss in skeletal muscle injuries. Acta Biomater. 25, 2–15 (2015). https://doi.org/10.1016/j.actbio.2015.07.038 29. S.-E. Byun, C. Sim, Y. Chung, H.K. Kim, S. Park, D.K. Kim, S. Cho, S. Lee, Skeletal muscle regeneration by the exosomes of adipose tissue- derived mesenchymal stem cells. Curr. Issues Mol. Biol. 43, 1473–1488 (2021). https://doi.org/10.3390/cimb43030104 11. R. Abujarour, B. Valamehr, Generation of skeletal muscle cells from pluripotent stem cells: advances and challenges. Front. Cell Dev. Biol. 3, 29 (2015). https://doi.org/10.3389/fcell.2015.00029 30. A. Gorecka, S. Salemi, D. Haralampieva, F. Moalli, D. Stroka, D. Candinas, D. Eberli, L. Brügger, Autologous transplantation of adipose-derived stem cells improves functional recovery of skeletal muscle without direct participation in new myofiber formation. Curr. Stem Cell Res. Ther. 9, 1–12 (2018). https://doi.org/10.1186/s13287-018-0922-1 12. K. Nogami, M. Blanc, F. Takemura, S. iTakeda, Y. Miyagoe-Suzuki, in Muscle Cell and Tissue: Current Status of Research Field, ed. by K. Sakuma. Making Skeletal Muscle from Human Pluripotent Stem Cells (Intecho- pen, London, 2018), p. 117 p g 31. A.J. Salgado, R.L. Reis, N. Sousa, J.M. Gimble, Adipose tissue derived stem cells secretome: soluble factors and their roles in regenerative medicine. Curr. Stem Cell Res. Ther. 5, 103–110 (2010). https://doi.org/ 10.2174/157488810791268564 13. D. Yu et al., Myogenic differentiation of stem cells for skeletal muscle regeneration. Stem Cells Int. 2021, 10 (2021). https://doi.org/10.1155/ 2021/8884283 14. R. Csapo, M. Gumpenberger, B. Wessner, Skeletal muscle extracellular matrix–what do we know about its composition, regulation, and physi- ological roles? A narrative review. Front. Physiol. 11, 253 (2020). https:// doi.org/10.3389/fphys.2020.00253 32. J. Received: 21 June 2023 Accepted: 10 October 2023 Received: 21 June 2023 Accepted: 10 October 2023 19. C. Bernard, A. Zavoriti, Q. Pucelle, B. Chazaud, J. Gondin, Role of macrophages during skeletal muscle regeneration and hypertrophy— Implications for immunomodulatory strategies. Physiol. Rep. 10, e15480 (2022). https://doi.org/10.14814/phy2.15480 20. L. Boldrin, J.E. Morgan, Human satellite cells: identification on human muscle fibres. PLoS Curr. 3, 7 (2012). https://doi.org/10.1371/currents. RRN1294 Availability of data and materials Not applicable Not applicable. 17. P. Scala, L. Rehak, V. Giudice, E. Ciaglia, A.A. Puca, C. Selleri, G. Della Porta, N. Maffulli, Stem cell and macrophage roles in skeletal muscle regenerative medicine. Int. J. Mol. Sci. 22, 10867 (2021). https://doi.org/ 10.3390/ijms221910867 Funding g This research was supported by the National Institutes of Health (R01AR077132) in USA and National Research Foundation (NRF) grant (RS- 2023-00218543) by the MSIT (Ministry of Science and ICT) in Korea. S. H. was supported by Korean Institute for Advancement of Technology (KIAT) grant (P0017305, Human Resource Development Program for Industrial Innovation Page 15 of 19 Han et al. Nano Convergence (2023) 10:48 Han et al. Nano Convergence (2023) 10:48 Han et al. Nano Convergence (2023) 10 (Global) funded by the MOTIE (Ministry of Trade, Industry, and Energy) in Korea. S. P. was supported by SKKU Global Research Platform Research Fund, Sungkyunkwan University, 2022. 15. A.B. Aurora, E.N. Olson, Immune modulation of stem cells and regenera- tion. Cell Stem Cell 15, 14–25 (2014). https://doi.org/10.1016/j.stem. 2014.06.009 16. V. Rybalko, P.-L. Hsieh, M. Merscham-Banda, L.J. Suggs, R.P. Farrar, The development of macrophage-mediated cell therapy to improve skeletal muscle function after injury. PLoS ONE 10, e0145550 (2015). https://doi.org/10.1371/journal.pone.0145550 Availability of data and materials Not applicable. Competing interests The authors declare that they have no competing interests. 18. J. Fang et al., Redressing the interactions between stem cells and immune system in tissue regeneration. Biol. Direct 16, 1–10 (2021). https://doi.org/10.1186/s13062-021-00306-6 References Circulation 109, 1543–1549 (2004). https://doi.org/10.1161/01.CIR.0000124062.31102.57 55. V.A. Solarte David, V.R. Guiza-Arguello, M.L. Arango-Rodriguez, C.L. Sossa, S.M. Becerra-Bayona, Decellularized tissues for wound healing: towards closing the gap between scaffold design and effective extra- cellular matrix remodeling. Front. Bioeng. Biotechnol. 10, 821852 (2022). https://doi.org/10.3389/fbioe.2022.821852 38. L. Santa María, C.V. Rojas, J.J. Minguell, Signals from damaged but not undamaged skeletal muscle induce myogenic differentiation of rat bone-marrow-derived mesenchymal stem cells. Exp. Cell Res. 300, 418–426 (2004). https://doi.org/10.1016/j.yexcr.2004.07.017 56. M. Brown, J. Li, C. Moraes, M. Tabrizian, N.Y.K. Li-Jessen, Decellularized extracellular matrix: new promising and challenging biomaterials for regenerative medicine. Biomaterials 289, 121786 (2022). https://doi. org/10.1016/j.biomaterials.2022.121786 39. J. Garcia-Castro, C. Trigueros, J. Madrenas, J. Perez-Simon, R. Rodriguez, P. Menendez, Mesenchymal stem cells and their use as cell replacement therapy and disease modelling tool. J. Cell. Mol. Med. 12, 2552–2565 (2008). https://doi.org/10.1111/j.1582-4934.2008.00516.x 57. D. Boso, E. Maghin, E. Carraro, M. Giagante, P. Pavan, M. Piccoli, Extra- cellular matrix-derived hydrogels as biomaterial for different skeletal muscle tissue replacements. Materials 13, 2483 (2020). https://doi. org/10.3390/ma13112483 40. U. Galderisi, A. Giordano, M.G. Paggi, The bad and the good of mesen- chymal stem cells in cancer: Boosters of tumor growth and vehicles for targeted delivery of anticancer agents. World J. Stem Cells 2, 5 (2010). https://doi.org/10.4252/wjsc.v2.i1.5 58. P. Du, M.P. Hwang, Y.K. Noh, R. Subbiah, I.G. Kim, S.E. Bae, K. Park, Fibro- blast-derived matrix (FDM) as a novel vascular endothelial growth factor delivery platform. J. Control. Release 194, 122–129 (2014). https://doi.org/10.1016/j.jconrel.2014.08.026 41. R. Darabi, R.W. Arpke, S. Irion, J.T. Dimos, M. Grskovic, M. Kyba, R.C. Per- lingeiro, Human ES-and iPS-derived myogenic progenitors restore DYS- TROPHIN and improve contractility upon transplantation in dystrophic mice. Cell Stem Cell 10, 610–619 (2012). https://doi.org/10.1016/j.stem. 2012.02.015 59. L. Wang, J.A. Johnson, Q. Zhang, E.K. Beahm, Combining decel- lularized human adipose tissue extracellular matrix and adipose- derived stem cells for adipose tissue engineering. Acta Biomater. 9, 8921–8931 (2013). https://doi.org/10.1016/j.actbio.2013.06.035 42. E. van der Wal et al., Large-scale expansion of human iPSC-derived skeletal muscle cells for disease modeling and cell-based therapeutic strategies. Stem Cell Rep. 10, 1975–1990 (2018). https://doi.org/10. 1016/j.stemcr.2018.04.002 60. S.E. Gilpin, J.P. Guyette, G. Gonzalez, X. Ren, J.M. Asara, D.J. Mathisen, J.P. Vacanti, H.C. Ott, Perfusion decellularization of human and porcine lungs: Bringing the matrix to clinical scale. J. Heart Lung Transplant. 33, 298–308 (2014). https://doi.org/10.1016/j.healun. 2013.10.030 43. S.S.-K. Chan, R.W. Arpke, A. Filareto, N. Xie, M.P. Pappas, J.S. Penaloza, R.C. Perlingeiro, M. References Rehman et al., Secretion of angiogenic and antiapoptotic factors by human adipose stromal cells. Circulation 109, 1292–1298 (2004). https://doi.org/10.1161/01.CIR.0000121425.42966.F1 33. C. Linard, M. Brachet, B. L’homme, C. Strup-Perrot, E. Busson, M. Bon- neau, J.-J. Lataillade, E. Bey, and M. Benderitter., Long-term effectiveness Page 16 of 19 Han et al. Nano Convergence (2023) 10:48 Han et al. Nano Convergence (2023) 10:48 50. S.P. Frey, H. Jansen, M.J. Raschke, R.H. Meffert, S. Ochman, VEGF improves skeletal muscle regeneration after acute trauma and recon- struction of the limb in a rabbit model. Clin. Orthop. Relat. Res. 470, 3607–3614 (2012). https://doi.org/10.1007/s11999-012-2456-7 of local BM-MSCs for skeletal muscle regeneration: a proof of concept obtained on a pig model of severe radiation burn. Curr. Stem. Cell. Res. Ther. 9, 1–14 (2018). https://doi.org/10.1186/s13287-018-1051-6 3607–3614 (2012). https://doi.org/10.1007/s11999-012-2456-7 34. N.T. Ninagawa, E. Isobe, Y. Hirayama, R. Murakami, K. Komatsu, M. Nagai, M. Kobayashi, Y. Kawabata, S. Torihashi, Transplantated mesenchymal stem cells derived from embryonic stem cells promote muscle regen- eration and accelerate functional recovery of injured skeletal muscle. Biores. Open Access 2, 295–306 (2013). https://doi.org/10.1089/biores. 2013.0012 51. A. Urciuolo et al., Collagen VI regulates satellite cell self-renewal and muscle regeneration. Nat. Commun. 4, 1964 (2013). https://doi.org/10. 1038/ncomms2964 52. J. Valcarcel, J. Fraguas, C. Hermida-Merino, D. Hermida-Merino, M.M. Piñeiro, J.A. Vázquez, Production and physicochemical characterization of gelatin and collagen hydrolysates from turbot skin waste generated by aquaculture activities. Mar. Drugs 19, 491 (2021). https://doi.org/10. 3390/md19090491 35. S. Oshima, N. Kamei, T. Nakasa, Y. Yasunaga, M. Ochi, Enhancement of muscle repair using human mesenchymal stem cells with a magnetic targeting system in a subchronic muscle injury model. J. Orthop. Sci. 19, 478–488 (2014). https://doi.org/10.1007/s00776-014-0548-9 53. Y.S. Kim, M. Majid, A.J. Melchiorri, A.G. Mikos, Applications of decellu- larized extracellular matrix in bone and cartilage tissue engineering. Bioeng. Transl. Med. 4, 83–95 (2019). https://doi.org/10.1002/btm2. 10110 36. T. Winkler, P. von Roth, G. Matziolis, M. Mehta, C. Perka, G.N. Duda, Dose– response relationship of mesenchymal stem cell transplantation and functional regeneration after severe skeletal muscle injury in rats. Tissue Eng. Part A 15, 487–492 (2009). https://doi.org/10.1089/ten.tea.2007. 0426 54. J.M. Fishman et al., Immunomodulatory effect of a decellularized skeletal muscle scaffold in a discordant xenotransplantation model. Proc. Natl. Acad. Sci. USA. 110, 14360–14365 (2013). https://doi.org/ 10.1073/pnas.1213228110 37. T. Kinnaird, E. Stabile, M. Burnett, M. Shou, C. Lee, S. Barr, S. Fuchs, S. Epstein, Local delivery of marrow-derived stromal cells augments collateral perfusion through paracrine mechanisms. References 428, 131017 (2022). https://doi.org/10.1016/j.cej.2021.131017 91. C. Lee, X. Wei, J.W. Kysar, J. Hone, Measurement of the elastic properties and intrinsic strength of monolayer graphene. Science 321, 385–388 (2008). https://doi.org/10.1126/science.1157996 74. D. Cornelison, M.S. Filla, H.M. Stanley, A.C. Rapraeger, B.B. Olwin, Synde- can-3 and syndecan-4 specifically mark skeletal muscle satellite cells and are implicated in satellite cell maintenance and muscle regenera- tion. Dev. Biol. 239, 79–94 (2001). https://doi.org/10.1006/dbio.2001. 0416 92. D.R. Dreyer, S. Park, C.W. Bielawski, R.S. Ruoff, The chemistry of graphene oxide. Chem. Soc. Rev. 39, 228–240 (2010). https://doi.org/10.1039/ B917103G 75. C. Borselli, C.A. Cezar, D. Shvartsman, H.H. Vandenburgh, D.J. Mooney, The role of multifunctional delivery scaffold in the ability of cul- tured myoblasts to promote muscle regeneration. Biomaterials 32, 8905–8914 (2011). https://doi.org/10.1016/j.biomaterials.2011.08.019 93. S.H. Ku, C.B. Park, Myoblast differentiation on graphene oxide. Biomate- rials 34, 2017–2023 (2013). https://doi.org/10.1016/j.biomaterials.2012. 11.052 94. E.A. Lee, S.-Y. Kwak, J.-K. Yang, Y.-S. Lee, J.-H. Kim, H.D. Kim, N.S. Hwang, Graphene oxide film guided skeletal muscle differentiation. Mater. Sci. Eng. C 126, 112174 (2021). https://doi.org/10.1016/j.msec.2021.112174 76. J. Prüller, I. Mannhardt, T. Eschenhagen, P.S. Zammit, N. Figeac, Satellite cells delivered in their niche efficiently generate functional myotubes in three-dimensional cell culture. PLoS ONE 13, e0202574 (2018). https:// doi.org/10.1371/journal.pone.0202574 95. L. Wang, X. Zhang, Y. He, Y. Wang, W. Zhong, K. Mequanint, X. Qiu, M. Xing, Ultralight conductive and elastic aerogel for skeletal muscle atrophy regeneration. Adv. Funct. Mat. 29, 1806200 (2019). https://doi. org/10.1002/adfm.201806200 77. L. Wang, L. Cao, J. Shansky, Z. Wang, D. Mooney, H. Vandenburgh, Mini- mally invasive approach to the repair of injured skeletal muscle with a shape-memory scaffold. Mol. Ther. 22, 1441–1449 (2014). https://doi. org/10.1038/mt.2014.78 96. N. Annabi et al., Highly elastic and conductive human-based protein hybrid hydrogels. Adv. Mater. 28, 40–49 (2016). https://doi.org/10.1002/ adma.201503255 78. L. Wang, J. Shansky, C. Borselli, D. Mooney, H. Vandenburgh, Design and fabrication of a biodegradable, covalently crosslinked shape-memory alginate scaffold for cell and growth factor delivery. Tissue Eng. Part A 18, 2000–2007 (2012). https://doi.org/10.1089/ten.TEA.2011.0663 97. Y. Du, J. Ge, Y. Li, P.X. Ma, B. Lei, Biomimetic elastomeric, conductive and biodegradable polycitrate-based nanocomposites for guiding myo- genic differentiation and skeletal muscle regeneration. Biomaterials 157, 40–50 (2018). https://doi.org/10.1016/j.biomaterials.2017.12.005 gf g y g 18, 2000–2007 (2012). https://doi.org/10.1089/ten.TEA.2011.0663 79. E.K. Merritt et al., Repair of traumatic skeletal muscle injury with bone- marrow-derived mesenchymal stem cells seeded on extracellular matrix. Tissue Eng. Part A 16, 2871–2881 (2010). https://doi.org/10. 1089/ten.TEA.2009.0826 98. H. References H. Olguin, E. Brandan, Expression and localization of proteoglycans during limb myogenic activation. Dev. Dyn. 221, 106–115 (2001). https://doi.org/10.1002/dvdy.1129 84. A.C. Farr, K.J. Hogan, A.G. Mikos, Nanomaterial additives for fabrication of stimuli-responsive skeletal muscle tissue engineering constructs. Adv. Healthc. Mater. 9, 2000730 (2020). https://doi.org/10.1002/adhm. 202000730 68. B.B. Olwin, Z.W. Hall, Developmental regulation of laminin accumula- tion in the extracellular matrix of a mouse muscle cell line. Dev. Biol. 112, 359–367 (1985). https://doi.org/10.1016/0012-1606(85)90407-5 85. L.A. Kolahalam, I.K. Viswanath, B.S. Diwakar, B. Govindh, V. Reddy, Y. Mur- thy, Review on nanomaterials: Synthesis and applications. Mater. Today: Proc. 18, 2182–2190 (2019). https://doi.org/10.1016/j.matpr.2019.07.371 69. L. Wang, J.A. Johnson, D.W. Chang, Q. Zhang, Decellularized muscu- lofascial extracellular matrix for tissue engineering. Biomaterials 34, 2641–2654 (2013). https://doi.org/10.1016/j.biomaterials.2012.12.048 86. B. Xu, A. Magli, Y. Anugrah, S.J. Koester, R.C. Perlingeiro, W. Shen, Nanotopography-responsive myotube alignment and orientation as a sensitive phenotypic biomarker for duchenne muscular dystrophy. Biomaterials 183, 54–66 (2018). https://doi.org/10.1016/j.biomaterials. 2018.08.047 70. M.T. Wolf, K.A. Daly, E.P. Brennan-Pierce, S.A. Johnson, C.A. Carruthers, A. D’Amore, S.P. Nagarkar, S.S. Velankar, S.F. Badylak, A hydrogel derived from decellularized dermal extracellular matrix. Biomaterials 33, 7028–7038 (2012). https://doi.org/10.1016/j.biomaterials.2012.06. 051f 87. W. Park, H. Shin, B. Choi, W.-K. Rhim, K. Na, D.K. Han, Advanced hybrid nanomaterials for biomedical applications. Prog. Mater. Sci. 114, 100686 (2020). https://doi.org/10.1016/j.pmatsci.2020.100686 71. B.M. Sicari et al., An acellular biologic scaffold promotes skeletal muscle formation in mice and humans with volumetric muscle loss. Sci. Transl. Med. (2014). https://doi.org/10.1126/scitranslmed.3008085 88. B.S. Harrison, A. Atala, Carbon nanotube applications for tissue engi- neering. Biomaterials 28, 344–353 (2007). https://doi.org/10.1016/j. biomaterials.2006.07.044 72. B.T. Corona, C.L. Ward, H.B. Baker, T.J. Walters, Implantation of in vitro tissue engineered muscle repair constructs and bladder acellular matrices partially restore in vivo skeletal muscle function in a rat model of volumetric muscle loss injury. Tissue Eng. Part A 20, 705–715 (2014). https://doi.org/10.1089/ten.TEA.2012.0761 89. J. Ramón-Azcón et al., Dielectrophoretically aligned carbon nanotubes to control electrical and mechanical properties of hydrogels to fabri- cate contractile muscle myofibers. Adv. Mater. 25, 4028–4034 (2013). https://doi.org/10.1002/adma.201301300 73. P.D. Coppi, S. Bellini, M.T. Conconi, M. Sabatti, E. Simonato, P.G. Gamba, G.G. Nussdorfer, P.P. Parnigotto, Myoblast–acellular skeletal muscle matrix constructs guarantee a long-term repair of experimental full- thickness abdominal wall defects. Tissue Eng. 12, 1929–1936 (2006). https://doi.org/10.1089/ten.2006.12.1929 90. T. Hu et al., Biomimetic 3D aligned conductive tubular cryogel scaffolds with mechanical anisotropy for 3D cell alignment, differentiation and in vivo skeletal muscle regeneration. Chem. Eng. J. References Kyba, Skeletal muscle stem cells from PSC-derived tera- tomas have functional regenerative capacity. Cell Stem Cell 23, 74–85 (2018). https://doi.org/10.1016/j.stem.2018.06.010 61. M. Figliuzzi, B. Bonandrini, A. Remuzzi, Decellularized kidney matrix as functional material for whole organ tissue engineering. J. Appl. Biomater. Funct. Mater. 15, e326–e333 (2017). https://doi.org/10. 5301/jabfm.5000393 44. F.S. Tedesco et al., Transplantation of genetically corrected human iPSC- derived progenitors in mice with limb-girdle muscular dystrophy. Sci. Transl. Med. 4, 140ra189 (2012). https://doi.org/10.1126/scitranslmed. 3003541 62. A. Neishabouri, A. Soltani Khaboushan, F. Daghigh, A.-M. Kajbafzadeh, M. Majidi Zolbin, Decellularization in tissue engineering and regen- erative medicine: Evaluation, modification, and application methods. Front. Bioeng. Biotechnol. 10, 805299 (2022). https://doi.org/10.3389/ fbioe.2022.805299 45. S. Goudenege, C. Lebel, N.B. Huot, C. Dufour, I. Fujii, J. Gekas, J. Rousseau, J.P. Tremblay, Myoblasts derived from normal hESCs and dystrophic hiPSCs efficiently fuse with existing muscle fibers following transplanta- tion. Mol. Ther. 20, 2153–2167 (2012). https://doi.org/10.1038/mt.2012. 188 63. S. Sart, R. Jeske, X. Chen, T. Ma, Y. Li, Engineering stem cell-derived extracellular matrices: decellularization, characterization, and biologi- cal function. Tissue Eng. Part B Rev. 26, 402–422 (2020). https://doi. org/10.1089/ten.TEB.2019.0349 46. Z. Julier, A.J. Park, P.S. Briquez, M.M. Martino, Promoting tissue regenera- tion by modulating the immune system. Acta Biomater. 53, 13–28 (2017). https://doi.org/10.1016/j.actbio.2017.01.056 p g j 47. Q. Lian et al., Functional mesenchymal stem cells derived from human induced pluripotent stem cells attenuate limb ischemia in mice. Circulation 121, 1113–1123 (2010). https://doi.org/10.1161/CIRCULATIO NAHA.109.898312 g 64. J.E. Valentin, N.J. Turner, T.W. Gilbert, S.F. Badylak, Functional skel- etal muscle formation with a biologic scaffold. Biomaterials 31, 7475–7484 (2010). https://doi.org/10.1016/j.biomaterials.2010.06.039 65. B.E. Uygun et al., Organ reengineering through development of a transplantable recellularized liver graft using decellularized liver matrix. Nat. Med. 16, 814–820 (2010). https://doi.org/10.1038/nm. 2170 48. Y. Miyagoe-Suzuki, Si. Takeda, Skeletal muscle generated from induced pluripotent stem cells-induction and application. Stem Cells World J. 9, 89–97 (2017). https://doi.org/10.4252/wjsc.v9.i6.89 66. X.K. Chen, T.J. Walters, Muscle-derived decellularised extracellular matrix improves functional recovery in a rat latissimus dorsi muscle defect model. J. Plast. Reconstr. Aesthet. Surg. 66, 1750–1758 (2013). https://doi.org/10.1016/j.bjps.2013.07.037 49. C. Borselli, H. Storrie, F. Benesch-Lee, D. Shvartsman, C. Cezar, J.W. Licht- man, H.H. Vandenburgh, D.J. Mooney, Functional muscle regeneration with combined delivery of angiogenesis and myogenesis factors. Proc. Natl. Acad. Sci. USA 107, 3287–3292 (2010). https://doi.org/10.1073/ pnas.0903875106 Page 17 of 19 Page 17 of 19 Han et al. Nano Convergence (2023) 10:48 Han et al. Nano Convergence (2023) 10:48 67. References Chen, L. Wang, X. Zeng, H. Schwarz, H.S. Nanda, X. Peng, Y. Zhou, Exosomes, a new star for targeted delivery. Front. Cell Dev. Biol. (2021). https://doi.org/10.3389/fcell.2021.751079 99. F.-Y. Kong, J.-W. Zhang, R.-F. Li, Z.-X. Wang, W.-J. Wang, W. Wang, Unique roles of gold nanoparticles in drug delivery, targeting and imaging applications. Molecules 22, 1445 (2017). https://doi.org/10.3390/molec ules22091445 80. M.A. Machingal, B.T. Corona, T.J. Walters, V. Kesireddy, C.N. Koval, A. Dannahower, W. Zhao, A tissue-engineered muscle repair construct for functional restoration of an irrecoverable muscle injury in a murine model. Tissue Eng. Part A 17, 2291–2303 (2011). https://doi.org/10. 1089/ten.TEA.2010.0682 100. H. Valadi, K. Ekström, A. Bossios, M. Sjöstrand, J.J. Lee, J.O. Lötvall, Exosome-mediated transfer of mRNAs and microRNAs is a novel mech- anism of genetic exchange between cells. Nat. Cell Biol. 9, 654–659 (2007). https://doi.org/10.1038/ncb1596 81. B.T. Corona, M.A. Machingal, T. Criswell, M. Vadhavkar, A.C. Dannahower, C. Bergman, W. Zhao, Further development of a tissue engineered mus- cle repair construct in vitro for enhanced functional recovery following implantation in vivo in a murine model of volumetric muscle loss injury. Tissue Eng. Part A 18, 1213–1228 (2012). https://doi.org/10.1089/ten. tea.2011.0614 101. Y. Nakamura, S. Miyaki, H. Ishitobi, S. Matsuyama, T. Nakasa, N. Kamei, T. Akimoto, Y. Higashi, M. Ochi, Mesenchymal-stem-cell-derived exosomes accelerate skeletal muscle regeneration. FEBS Lett. 589, 1257–1265 (2015). https://doi.org/10.1016/j.febslet.2015.03.031 (2015). https://doi.org/10.1016/j.febslet.2015.03.031 82. M. Mousavinejad, P.W. Andrews, E.K. Shoraki, Current biosafety consid- erations in stem cell therapy. Cell J. 18, 281 (2016). https://doi.org/10. 22074/cellj.2016.4324 102. N. Ran, X. Gao, X. Dong, J. Li, C. Lin, M. Geng, H. Yin, Effects of exosome- mediated delivery of myostatin propeptide on functional recovery of mdx mice. Biomaterials 236, 119826 (2020). https://doi.org/10.1016/j. biomaterials.2020.119826 83. K. Wuputra, C.-C. Ku, D.-C. Wu, Y.-C. Lin, S. Saito, K.K. Yokoyama, Preven- tion of tumor risk associated with the reprogramming of human pluripotent stem cells. J. Exp. Clin. Cancer Res. 39, 1–24 (2020). https:// doi.org/10.1186/s13046-020-01584-0 103. K. Patel, H. Amthor, The function of Myostatin and strategies of Myosta- tin blockade—new hope for therapies aimed at promoting growth of Page 18 of 19 Han et al. Nano Convergence (2023) 10:48 Han et al. Nano Convergence function restoration. Sci. Rep. 8, 1–15 (2018). https://doi.org/10.1038/ s41598-018-29968-5 skeletal muscle. Neuromuscul. Disord. 15, 117–126 (2005). https://doi. org/10.1002/adhm.202200866 skeletal muscle. Neuromuscul. Disord. 15, 117–126 (2005). https://doi. org/10.1002/adhm.202200866 121. J.H. Kim, I. Kim, Y.-J. Seol, I.K. Ko, J.J. Yoo, A. Atala, S.J. Lee, Neural cell integration into 3D bioprinted skeletal muscle constructs accelerates restoration of muscle function. Nat. Commun. 11, 1–12 (2020). https:// doi.org/10.1038/s41467-020-14930-9 104. D. Huang, F. Yue, J. Qiu, M. Deng, S. Kuang, Polymeric nanoparticles functionalized with muscle-homing peptides for targeted delivery of phosphatase and tensin homolog inhibitor to skeletal muscle. Acta Biomater. 118, 196–206 (2020). https://doi.org/10.1016/j.actbio.2020.10. 009 122. A. Poerio et al., Towards innervation of bioengineered muscle con- structs: development of a sustained neurotrophic factor delivery and release system. Bioprinting 27, e00220 (2022). https://doi.org/10.1016/j. bprint.2022.e00220 105. T.M. Raimondo, D.J. Mooney, Anti-inflammatory nanoparticles sig- nificantly improve muscle function in a murine model of advanced muscular dystrophy. Sci. Adv. 7, eabh3693 (2021). https://doi.org/10. 1126/sciadv.abh3693 123. Y.A. Jodat et al., hiPSC-derived 3D bioprinted skeletal muscle tissue implants regenerate skeletal muscle following volumetric muscle loss. Res. Sq. (2021). https://doi.org/10.21203/rs.3.rs-146091/v1 106. J. Ge, K. Liu, W. Niu, M. Chen, M. Wang, Y. Xue, C. Gao, P.X. Ma, B. Lei, Gold and gold-silver alloy nanoparticles enhance the myogenic differentia- tion of myoblasts through p38 MAPK signaling pathway and promote in vivo skeletal muscle regeneration. Biomaterials 175, 19–29 (2018). https://doi.org/10.1016/j.biomaterials.2018.05.027 124. K.W. Christensen et al., Assembled cell-decorated collagen (AC-DC) fiber bioprinted implants with musculoskeletal tissue properties promote functional recovery in volumetric muscle loss. Adv. Healthc. Mater. 11, 2101357 (2022). https://doi.org/10.1002/adhm.202101357 107. J. Ge, Y. Li, M. Wang, C. Gao, S. Yang, B. (2015). https://doi.org/10.1016/j.febslet.2015.03.031 Sci. Rep. 9, 1856 (2019). https://doi.org/10.1038/s41598-018-38366-w 113. M.I. Anik, N. Mahmud, A. Al Masud, M. Hasan, Gold nanoparticles (GNPs) in biomedical and clinical applications a review. Nano. Select. 3, 792–828 (2022). https://doi.org/10.1002/nano.202100255 132. F. Agostinacchio, X. Mu, S. Dire, A. Motta, D.L. Kaplan, In situ 3D printing: opportunities with silk inks. Trends Biotechnol. 39, 719–730 (2021). https://doi.org/10.1016/j.tibtech.2020.11.003 114. A. Chakraborty, A. Roy, S.P. Ravi, A. Paul, Exploiting the role of nano- particles for use in hydrogel-based bioprinting applications: concept, design, and recent advances. Biomater. Sci. 9, 6337–6354 (2021). https://doi.org/10.1039/D1BM00605C 133. Y. Chen et al., Noninvasive in vivo 3D bioprinting. Sci. Adv. 6, eaba7406 (2020). https://doi.org/10.1126/sciadv.aba7406 134. M. Samandari, A. Mostafavi, J. Quint, A. Memic, A. Tamayol, In situ bioprinting: intraoperative implementation of regenerative medicine. Trends Biotechnol. 40, 1229-1247 (2022). https://doi.org/10.1016/j.tibte ch.2022.03.009 115. L. Moroni, J.A. Burdick, C. Highley, S.J. Lee, Y. Morimoto, S. Takeuchi, J.J. Yoo, Biofabrication strategies for 3D in vitro models and regenerative medicine. Nat. Rev. Mater. 3, 21–37 (2018). https://doi.org/10.1038/ s41578-018-0006-y 135. N. Ashammakhi, S. Ahadian, C. Xu, H. Montazerian, H. Ko, R. Nasiri, N. Barros, A. Khademhosseini, Bioinks and bioprinting technologies to make heterogeneous and biomimetic tissue constructs. Mater Today Bio 1, 100008 (2019). https://doi.org/10.1016/j.mtbio.2019.100008 116. S. Yi, Y. Zhang, X. Gu, L. Huang, K. Zhang, T. Qian, X. Gu, Application of stem cells in peripheral nerve regeneration. Burns Trauma 8, tkaa02 (2020). https://doi.org/10.1093/burnst/tkaa002 136. S. Tasoglu, E. Diller, S. Guven, M. Sitti, U. Demirci, Untethered micro- robotic coding of three-dimensional material composition. Nat. Com- mun. 5, 3124 (2014). https://doi.org/10.1038/ncomms4124 117. C.H. Lee, B. Shah, E.K. Moioli, J.J. Mao, CTGF directs fibroblast differ- entiation from human mesenchymal stem/stromal cells and defines connective tissue healing in a rodent injury model. J. Clin. Investig. 120, 3340–3349 (2010). https://doi.org/10.1172/JCI43230 137. K. Ma et al., Application of robotic-assisted in situ 3D printing in carti- lage regeneration with HAMA hydrogel: an in vivo study. J. Adv. Res. 23, 123–132 (2020). https://doi.org/10.1016/j.jare.2020.01.010 118. J.A. Phillippi, E. Miller, L. Weiss, J. Huard, A. Waggoner, P. Campbell, Micro- environments engineered by inkjet bioprinting spatially direct adult stem cells toward muscle-and bone-like subpopulations. Stem Cells 26, 127–134 (2008). https://doi.org/10.1634/stemcells.2007-0520 138. L. Li, J. Shi, K. Ma, J. Jin, P. Wang, H. Liang, Y. Cao, X. Wang, Q. Jiang, Robotic in situ 3D bio-printing technology for repairing large segmen- tal bone defects. J. Adv. Res. 30, 75–84 (2021). https://doi.org/10.1016/j. jare.2020.11.011 119. H.-W. Kang, S.J. Lee, I.K. (2015). https://doi.org/10.1016/j.febslet.2015.03.031 Lei, Engineering conductive anti- oxidative antibacterial nanocomposite hydrogel scaffolds with oriented channels promotes structure-functional skeletal muscle regeneration. Chem. Eng. J. 425, 130333 (2021). https://doi.org/10.1016/j.cej.2021. 130333 125. P. Zorlutuna, J.H. Jeong, H. Kong, R. Bashir, Stereolithography-based hydrogel microenvironments to examine cellular interactions. Adv. Funct. Mater. 21, 3642–3651 (2011). https://doi.org/10.1002/adfm. 201101023 126. W. Kiratitanaporn, D.B. Berry, A. Mudla, T. Fried, A. Lao, C. Yu, N. Hao, S.R. Ward, S. Chen, 3D printing a biocompatible elastomer for modeling muscle regeneration after volumetric muscle loss. Biomater Adv. 142, 213171 (2022). https://doi.org/10.1016/j.bioadv.2022.213171 108. S.J. Kim et al., Stretchable and transparent biointerface using cell-sheet– graphene hybrid for electrophysiology and therapy of skeletal muscle. Adv. Func. Mat. 26, 3207–3217 (2016). https://doi.org/10.1002/adfm. 201504578 109. A. Patel, S. Mukundan, W. Wang, A. Karumuri, V. Sant, S.M. Mukhopad- hyay, S. Sant, Carbon-based hierarchical scaffolds for myoblast differen- tiation: synergy between nano-functionalization and alignment. Acta Biomater. 32, 77–88 (2016). https://doi.org/10.1016/j.actbio.2016.01.004 127. A. Behre et al., 3D bioprinted patient-specific extracellular matrix scaffolds for soft tissue defects. Adv. Healthc. Mat. 11, 2200866 (2022). https://doi.org/10.1002/adhm.202200866 128. H. Jo, M. Sim, S. Kim, S. Yang, Y. Yoo, J.-H. Park, T.H. Yoon, M.-G. Kim, J.Y. Lee, Electrically conductive graphene/polyacrylamide hydrogels produced by mild chemical reduction for enhanced myoblast growth and differentiation. Acta Biomater. 48, 100–109 (2017). https://doi.org/ 10.1016/j.actbio.2016.10.035 110. J. Park, J.H. Choi, S. Kim, I. Jang, S. Jeong, J.Y. Lee, Micropatterned con- ductive hydrogels as multifunctional muscle-mimicking biomaterials: graphene-incorporated hydrogels directly patterned with femtosecond laser ablation. Acta Biomater. 97, 141–153 (2019). https://doi.org/10. 1016/j.actbio.2019.07.044 129. M.S. Kang, J.I. Kang, P. Le Thi, K.M. Park, S.W. Hong, Y.S. Choi, D.-W. Han, K.D. Park, Three-dimensional printable gelatin hydrogels incorporating graphene oxide to enable spontaneous myogenic differentiation. ACS Macro Lett. 10, 426–432 (2021). https://doi.org/10.1021/acsmacrolett. 0c00845 111. O.V. Pham-Nguyen, Y.J. Son, T.W. Kwon, J. Kim, Y.C. Jung, J.B. Park, B.J. Kang, H.S. Yoo, Preparation of stretchable nanofibrous sheets with sac- rificial coaxial electrospinning for treatment of traumatic muscle injury. Adv. Healthc. Mat. 10, 2002228 (2021). https://doi.org/10.1002/adhm. 202002228 130. W. Kim, C.H. Jang, G.H. Kim, A myoblast-laden collagen bioink with fully aligned Au nanowires for muscle-tissue regeneration. Nano Lett. 19, 8612–8620 (2019). https://doi.org/10.1021/acs.nanolett.9b03182 112. C. Lang, E.C. Lloyd, K.E. Matuszewski, Y. Xu, V. Ganesan, R. Huang, M. Kumar, R.J. Hickey, Nanostructured block copolymer muscles. Nat. Nanotechnol. 17, 752–758 (2022). https://doi.org/10.1038/ s41565-022-01133-0 131. M. Albanna et al., In situ bioprinting of autologous skin cells accelerates wound healing of extensive excisional full-thickness wounds. (2015). https://doi.org/10.1016/j.febslet.2015.03.031 Ko, C. Kengla, J.J. Yoo, A. Atala, A 3D bioprint- ing system to produce human-scale tissue constructs with structural integrity. Nat. Biotechnol. 34, 312–319 (2016). https://doi.org/10.1038/ nbt.3413 139. X. Li, Q. Lian, D. Li, H. Xin, S. Jia, Development of a robotic arm based hydrogel additive manufacturing system for in-situ printing. Appl. Sci. 7, 10 (2017). https://doi.org/10.3390/app7010073 120. J.H. Kim, Y.-J. Seol, I.K. Ko, H.-W. Kang, Y.K. Lee, J.J. Yoo, A. Atala, S.J. Lee, 3D bioprinted human skeletal muscle constructs for muscle Page 19 of 19 Han et al. Nano Convergence (2023) 10:48 Han et al. Nano Convergence (2023) 10:48 140. Z. Zhu, S.Z. Guo, T. Hirdler, C. Eide, X. Fan, J. Tolar, M.C. McAlpine, 3D printed functional and biological materials on moving freeform surfaces. Adv. Mater. 30, 1707495 (2018). https://doi.org/10.1002/adma. 201707495 141. W. Zhao, H. Chen, Y. Zhang, D. Zhou, L. Liang, B. Liu, T. Xu, Adaptive multi-degree-of-freedom in situ bioprinting robot for hair-follicle-inclu- sive skin repair: a preliminary study conducted in mice. Bioeng. Transl. Med. 7, e10303 (2022). https://doi.org/10.1002/btm2.10303 142. J.P. Quint et al., In vivo printing of nanoenabled scaffolds for the treat- ment of skeletal muscle injuries. Adv. Healthc. Mater. 10, 2002152 (2021). https://doi.org/10.1002/adhm.202002152f 143. C.S. Russell et al., In situ printing of adhesive hydrogel scaffolds for the treatment of skeletal muscle injuries. ACS Appl. Bio Mater. 3, 1568–1579 (2020). https://doi.org/10.1021/acsabm.9b01176 144. Z. Mahmoudi, M. Sedighi, A. Jafari, S. Naghieh, E. Stefanek, M. Akbari, H. Savoji, In situ 3D bioprinting: a promising technique in advanced biofabrication strategies. 31, e00260 Bioprinting (2023). https://doi.org/ 10.1016/j.bprint.2023.e00260 145. W. Kim, C.H. Jang, G. Kim, Bioprinted hASC-laden structures with cell-differentiation niches for muscle regeneration. Chem. Eng. J. 419, 129570 (2021). https://doi.org/10.1016/j.cej.2021.129570 p g j j 146. S. Brookes, S. Voytik-Harbin, H. Zhang, S. Halum, Three-dimensional tissue-engineered skeletal muscle for laryngeal reconstruction. Laryn- goscope 128, 603–609 (2018). https://doi.org/10.1002/lary.26771 147. B. Xu, M. Zhang, R.C. Perlingeiro, W. Shen, Skeletal muscle constructs engineered from human embryonic stem cell derived myogenic progenitors exhibit enhanced contractile forces when differentiated in a medium containing EGM-2 supplements. Adv. Biosyst. 3, 1900005 (2019). https://doi.org/10.1002/adbi.201900005 148. D. Gholobova, M. Gérard, L. Decroix, L. Desender, N. Callewaert, P. Annaert, L. Thorrez, Human tissue-engineered skeletal muscle: a novel 3D in vitro model for drug disposition and toxicity after intramus- cular injection. Sci. Rep. 8, 1–14 (2018). https://doi.org/10.1038/ s41598-018-30123-3 149. A. (2015). https://doi.org/10.1016/j.febslet.2015.03.031 Urciuolo et al., Engineering a 3D in vitro model of human skeletal muscle at the single fiber scale. PLoS ONE 15, e0232081 (2020). https:// doi.org/10.1371/journal.pone.0232081 150. T. Osaki, S.G. Uzel, R.D. Kamm, Microphysiological 3D model of amyo- trophic lateral sclerosis (ALS) from human iPS-derived muscle cells and optogenetic motor neurons. Adv. Sci. 4, eaat5847 (2018). https://doi. org/10.1126/sciadv.aat5847 151. L. Richter, V. Charwat, C. Jungreuthmayer, F. Bellutti, H. Brueckl, P. Ertl, Monitoring cellular stress responses to nanoparticles using a lab-on- a-chip. Lab Chip 11, 2551–2560 (2011). https://doi.org/10.1039/C1LC2 0256A 151. L. Richter, V. Charwat, C. Jungreuthmayer, F. Bellutti, H. Brueckl, P. Ertl, Monitoring cellular stress responses to nanoparticles using a lab-on- a-chip. Lab Chip 11, 2551–2560 (2011). https://doi.org/10.1039/C1LC2 0256A 152. Y.Y. Chen, A.M. Syed, P. MacMillan, J.V. Rocheleau, W.C. Chan, Flow rate affects nanoparticle uptake into endothelial cells. Adv. Mater. 32, 1906274 (2020). https://doi.org/10.1002/adma.201906274 153. S. Costa, V. Vilas-Boas, F. Lebre, J. Granjeiro, C. Catarino, L.M. Teixeira, P. Loskill, E. Alfaro-Moreno, A. Ribeiro, Microfluidic-based skin-on-chip systems for safety assessment of nanomaterials. Trends Biotechnol. 41, 1282–1298 (2023). https://doi.org/10.1016/j.tibtech.2023.05.009 154. M. Tosic, A. Allen, D. Willmann, C. Lepper, J. Kim, D. Duteil, R. Schüle, Lsd1 regulates skeletal muscle regeneration and directs the fate of satellite cells. Nat. Commun. 9, 1–14 (2018). https://doi.org/10.1038/ s41467-017-02740-5 Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in pub- lished maps and institutional affiliations.
https://openalex.org/W4376983122	https://escholarship.org/content/qt4v6874kw/qt4v6874kw.pdf?t=rwi95s	English	null	Sub-internship Simulation Curriculum to Enhance Medical Student Preparedness for Practice	The western journal of emergency medicine/Western journal of emergency medicine	2,023	cc-by	1,057	UC Irvine Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health Title Sub-internship Simulation Curriculum to Enhance Medical Student Preparedness for Practice Permalink https://escholarship.org/uc/item/4v6874kw Journal Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health, 24(3.1) ISSN 1936-900X Authors Nolan, Robert Bustos, Eric Ponce, Joseph et al. Publication Date 2023 DOI 10.5811/westjem.61086 Copyright Information Copyright 2023 by the author(s).This work is made available under the terms of a Creative Commons Attribution License, available at https://creativecommons.org/licenses/by/4.0/ UC Irvine Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health Title Sub-internship Simulation Curriculum to Enhance Medical Student Preparedness for Practice Permalink https://escholarship.org/uc/item/4v6874kw Journal Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health, 24(3.1) ISSN 1936-900X Authors Nolan, Robert Bustos, Eric Ponce, Joseph et al. Publication Date 2023 DOI 10.5811/westjem.61086 Copyright Information Copyright 2023 by the author(s).This work is made available under the terms of a Creative Commons Attribution License, available at https://creativecommons.org/licenses/by/4.0/ UC Irvine Western Journal of Emergency Medicine: Integrating Emergen Care with Population Health Title Sub-internship Simulation Curriculum to Enhance Medical Student Preparedness for Pract Permalink https://escholarship.org/uc/item/4v6874kw Journal Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health, 24(3.1) ISSN 1936-900X Authors Nolan, Robert Bustos, Eric Ponce, Joseph et al. Publication Date 2023 DOI 10.5811/westjem.61086 Copyright Information Copyright 2023 by the author(s).This work is made available under the terms of a Creativ Commons Attribution License, available at https://creativecommons.org/licenses/by/4.0/ Title Copyright Information Copyright 2023 by the author(s).This work is made available under the terms of a Creative Commons Attribution License, available at https://creativecommons.org/licenses/by/4.0/ 71 What’s Wrong with Me, Doc? Applying A Curriculum for Communicating Diagnostic Uncertainty in The Emergency Medicine Clerkship Robert Nolan, Eric Bustos, Joseph Ponce, Cody McIlvain, Maria Moreira, Manuel Montano Robert Nolan, Eric Bustos, Joseph Ponce, Cody McIlvain, Maria Moreira, Manuel Montano Background: Simulation and procedure work-shops in Emergency Medicine (EM) training aid in the development of procedural competence, recognition of disease processes, and help address a lack of clinical experience to better prepare medical students for residency training. We developed a simulation curriculum for our senior medical student EM rotation incorporating procedural practice and exposure to high acuity clinical scenarios. Frances Rusnack, Chaiya Laoteppitaks, Xiao Chi Zhang, Alan Cherney, Kestrel Reopelle, Danielle McCarthy, Dimitrios Papanagnou, Kristin Rising Frances Rusnack, Chaiya Laoteppitaks, Xiao Chi Zhang, Alan Cherney, Kestrel Reopelle, Danielle McCarthy, Dimitrios Papanagnou, Kristin Rising Background: Diagnostic uncertainty is ubiquitous in emergency medicine (EM). Training to prepare students to communicate uncertainty with emergency department (ED) patients is limited in UME. Previous work has integrated the Uncertainty Communication Checklist (UCC) in EM resident education. Implementation in the EM clerkship has not yet been examined. We developed a curricular intervention that implements uncertainty training into the EM clerkship for third-year medical students. Objective: Develop an EM clerkship curriculum focused on teaching common procedures and exposure to high acuity clinical scenarios via simulated cases appropriate for fourth year medical students. Methods: All the residents at a three-year EM program were surveyed using an anonymous questionnaire in Google Forms. Resident wellness was assessed using the Depression, Anxiety and Stress Scale (DASS), a validated psychometric scale that is used across multiple industries. Using a 5-point Likert scale, residents were also asked how often they feel like they are the victim of microaggressions: 1: never or almost never to 5: very frequently. The term “microaggressions” was not defined, allowing residents to determine what they feel it to be. Pearson product moment correlation between the two variables was calculated and statistical significance to p<0.05 was determined. Objectives: Students will be able to describe diagnostic uncertainty and its impact on patients and provider, explain the UCC during patient conversations, practice using checklist during simulated encounters, and apply the checklist to patient conversations on shift. Curricular Design: At our institution, students complete a required 3-week EM clerkship. Students were first tasked with completing prework in the form of an Articulate Rise module on communicating diagnostic uncertainty. An additional didactic session was included in the clerkship orientation. Powered by the California Digital Library University of California eScholarship.org eScholarship.org CORD Abstracts Issue 2023 resources available to manage these issues, and ultimately the confidence to pass this education on to their patients. 72 Sub-internship Simulation Curriculum to Enhance Medical Student Preparedness for Practice 71 What’s Wrong with Me, Doc? Applying A Curriculum for Communicating Diagnostic Uncertainty in The Emergency Medicine Clerkship Frances Rusnack, Chaiya Laoteppitaks, Xiao Chi Zhang, Alan Cherney, Kestrel Reopelle, Danielle McCarthy, Dimitrios Papanagnou, Kristin Rising 71 What’s Wrong with Me, Doc? Applying A Curriculum for Communicating Diagnostic Uncertainty in The Emergency Medicine Clerkship Students then engaged in peer role play, as either patient or physician during a simulated case of discharging a patient with an uncertain diagnosis. The session ended with a debriefing. While in the department, we assessed students’ performance in applying each aspect of the checklist while communicating diagnostic uncertainty with patients through a standardized direct observation tool. Results: 20 out of 27 residents responded to the questionnaire. Seven residents scored for at least mild depression (three severe), nine residents scored for at least mild anxiety (five severe), and 11 residents scored for at least mild stress (one severe). The average rating on the frequency of being the victim of microaggressions was 2.2 (95%CI: 1.6, 2.7), suggesting residents infrequently felt victimized by microaggressions. The Pearson correlation between Depression and the frequency of microaggressions is r=0.56 (p=0.01), between Anxiety and microaggressions is r=0.41 (p=0.07, NS), and between Stress and microaggressions is r=0.63 (p=0.004) Impact: As students grapple with diagnostic uncertainty during their EM clerkship for the first time, the clerkship itself may serve as an ideal time to implement training on navigating these conversations. The breadth of patient encounters in the ED allows for deliberate practice of this skill. The UCC was successfully implemented into our clerkship. Initial data shows that students perform well and complete most elements of the checklist (83%). We plan to continue with implementation, data collection, and dissemination of this innovation. Conclusion: This study suggests there is a correlation between depression/stress and a residents’ perception of being victimized by microaggressions. It is unclear whether being the victim of microaggression leads to more depression/stress or if residents with more depression/stress view comments as being more insulting. Certainly, this subject merits further study. Volume 24, Supplement : May 2023 Western Journal of Emergency Medicine S79
https://openalex.org/W2129901073	https://biotechnologyforbiofuels.biomedcentral.com/counter/pdf/10.1186/s13068-015-0245-8	English	null	Uniconazole-induced starch accumulation in the bioenergy crop duckweed (Landoltia punctata) II: transcriptome alterations of pathways involved in carbohydrate metabolism and endogenous hormone crosstalk	Biotechnology for biofuels	2,015	cc-by	10,340	* Correspondence: zhaohai@cib.ac.cn †Equal contributors 1Chengdu Institute of Biology, Chinese Academy of Sciences, No.9 Section 4, Renmin Nan Road, 610041 Chengdu, China 3Key Laboratory of Environmental and Applied Microbiology, Chinese Academy of Sciences, No.9 Section 4, Renmin Nan Road, 610041 Chengdu, China Full list of author information is available at the end of the article Liu et al. Biotechnology for Biofuels (2015) 8:64 DOI 10.1186/s13068-015-0245-8 Liu et al. Biotechnology for Biofuels (2015) 8:64 DOI 10.1186/s13068-015-0245-8 Uniconazole-induced starch accumulation in the bioenergy crop duckweed (Landoltia punctata) II: transcriptome alterations of pathways involved in carbohydrate metabolism and endogenous hormone crosstalk Yang Liu1,2,3,4†, Yang Fang1,3,4†, Mengjun Huang1,2,3,4, Yanling Jin1,3,4, Jiaolong Sun1,3,4, Xiang Tao1,3,4, Guohua Zhang1,3,4, Kaize He1,3,4, Yun Zhao5 and Hai Zhao1,3,4* Yang Liu1,2,3,4†, Yang Fang1,3,4†, Mengjun Huang1,2,3,4, Yanling Jin1,3,4, Jiaolong Sun1,3,4, Xiang Tao1,3,4, Guohua Zhang1,3,4, Kaize He1,3,4, Yun Zhao5 and Hai Zhao1,3,4* RESEARCH ARTICLE Open Access Uniconazole-induced starch accumulation in the bioenergy crop duckweed (Landoltia punctata) II: transcriptome alterations of pathways involved in carbohydrate metabolism and endogenous hormone crosstalk Background hormone content [25]. However, there have been few in- depth studies into the responsive mechanism of plant growth regulators. There has thus far been little research linking uniconazole with expression changes in hormone biosynthesis enzymes and on the roles of certain hormone variations that cause high starch accumulation. Starch is the major storage form of sugar and energy in plants. The synthesis of starch in plant cells begins with the en- zyme ADP-glucose pyrophosphorylase (AGPase), which catalyzes the reaction of glucose-1-phosphate with ATP to form ADP-glucose. The ADP-glucose is then used a substrate by starch synthase (SS) enzymes to build up a starch molecule. Branches in the chain are introduced by starch-branching enzymes (SBEs), which hydrolyse 1, 4-glycosidic bonds, and in their place, create 1, 6 bonds with other glucose units. [26,27]. Environmental pollution, global warming, and energy shortages are urgent problems for sustainable develop- ment. To gradually decrease our excessive dependence on oil and reduce greenhouse gas emissions, many coun- tries are looking for alternative energy sources. Renewable and clean bioethanol is a promising alternative to oil. However, most feedstocks for bioethanol production are terrestrial crops, such as corn, cassava, and sweet potato, which may compete with food or feed crops for agricul- tural land and may lead to other environmental problems [1-3]. Therefore, it is necessary to explore novel feedstocks to make the development of the bioethanol industry more sustainable and environmentally friendly. y y Duckweed, the smallest and fastest-growing aquatic plant on earth [4], has become a novel potential alterna- tive for bioethanol production in recent years [5]. Duck- weed can double its biomass in 16 h to 2 days [6] and hence grows much faster than most other higher plants [7]. The growth rate of duckweed can reach 12.4 g/m2/ day dry weight in warm regions [8], and its yield has been documented up to 26.50 tons/ha/year dry weight [9]. The dry weight of starch content can reach 75% under ideal growth conditions [10]. Moreover, duckweed can grow on eutrophic wastewater to recover pollution nutrients, and it has been widely applied for wastewater treatment, including industrial wastewater and domestic sewage [11,12]. Importantly, duckweed biomass exhibits good characteristics for bioethanol production due to its relatively high starch and low lignin percentages [13], and it has been successfully converted to bioethanol in recent years [14,15]. Therefore, duckweed could be an ideal candidate for renewable bioenergy sources. Abstract Background: Landoltia punctata is a widely distributed duckweed species with great potential to accumulate enormous amounts of starch for bioethanol production. We found that L. punctata can accumulate starch rapidly accompanied by alterations in endogenous hormone levels after uniconazole application, but the relationship between endogenous hormones and starch accumulation is still unclear. Results: After spraying fronds with 800 mg/L uniconazole, L. punctata can accumulate starch quickly, with a dry weight starch content of up to 48% after 240 h of growth compared to 15.7% in the control group. Electron microscopy showed that the starch granule content was elevated after uniconazole application. The activities of key enzymes involved in starch synthesis were also significantly increased. Moreover, the expression of regulatory elements of the cytokinin (CK), abscisic acid (ABA) and gibberellin (GA) signaling pathways that are involved in chlorophyll and starch metabolism also changed correspondingly. Importantly, the expression levels of key enzymes involved in starch biosynthesis were up-regulated, while transcript-encoding enzymes involved in starch degradation and other carbohydrate metabolic branches were down-regulated. Conclusion: The increase of endogenous ABA and CK levels positively promoted the activity of ADP-glucose pyrophosphorylase (AGPase) and chlorophyll content, while the decrease in endogenous GA levels inactivated α-amylase. Thus, the alterations of endogenous hormone levels resulted in starch accumulation due to regulation of the expression of genes involved in the starch metabolism pathway. Keywords: Bioethanol, Starch accumulation, Endogenous hormones, Uniconazole, Crosstalk, Pathway Full list of author information is available at the end of the article © 2015 Liu et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Liu et al. Biotechnology for Biofuels (2015) 8:64 Page 2 of 12 Background Duck- weed has great potential to accumulate high starch, and a high starch percentage is the key to energy utilization for duckweed. The starch content of duckweed can be consid- erably increased by manipulating growing conditions, such as phosphate concentration, nutrient starvation [16], and plant growth regulators [17-19]. Plant growth regula- tors are common and efficient synthetic compounds that are widely used to regulate plant growth and development [20,21]. To obtain high quality and quantity duckweed for bioethanol utilization, we systematically screened more than 20 plant growth regulators, including auxin, cytoki- nins (CKs), abscisic acid (ABA), and gibberellins (GAs), to improve the starch and biomass yield of duckweed. Screening results showed that uniconazole can be used as an effective candidate for starch and biomass accumula- tion of duckweed in Hoagland nutrient solution. Unicona- zole (S3307) is a potent and active member of the triazole family that was developed as plant growth retardants [22]. It can enhance plant photosynthetic rates, increase soluble protein and total sugar content, elevate yield components in various crop plants [23,24], and change the endogenous g Next-generation sequencing (NGS) technology is a new development of sequencing technology, and it can provide a novel method to uncover transcriptomics data. It is difficult to research metabolic pathways using con- ventional biological techniques in non-model plants. However, NGS technologies are not limited to detect- ing transcripts that correspond to existing genomic sequences, it is particularly attractive for non-model plants with genomic sequences that are yet to be de- termined [28,29]. This technology has been applied to investigations in some non-model plants and was suc- cessfully used to study metabolic pathways in duck- weed last year [30]. In the accompanying report, we showed that uniconazole elevated chlorophyll content, enhanced the net photosynthetic rate, and altered the en- dogenous hormone levels of duckweed (data not shown). However, the relationship between the alteration of en- dogenous hormone levels and starch accumulation is still unclear. In this study, we constructed a comprehensive transcriptome using NGS technology in combination with physiological and biochemical analyses to investigate the process of starch accumulation mediated by endogenous hormones in Landoltia punctata. Impact of uniconazole on starch accumulation of L. punctata L. punctata 0202, originally collected from Sichuan, China, is a widely distributed duckweed species with great potential for starch accumulation. In this study, frond samples were collected at 13 time points after treatment with uniconazole for measurement of starch percentages and the activity of enzymes related to starch metabolism. As shown in Figure 1, the starch content was 3.16% (DW) at 0 h, but reached 10.31% at 3 h post-treatment. The starch content reached 19.46% (DW) at 12 h and finally reached 48.01% (DW) at 240 h following uniconazole Liu et al. Biotechnology for Biofuels (2015) 8:64 Page 3 of 12 Figure 1 Starch percentage of uniconazole-treated L. punctata. Fronds were collected at different time points and used for starch percentage analysis. The starch percentage was calculated basing on dry weight. Each data point represents the mean of triplicate values; error bars indicate the standard deviation. Figure 1 Starch percentage of uniconazole-treated L. punctata. Fronds were collected at different time points and used for starch percentage analysis. The starch percentage was calculated basing on dry weight. Each data point represents the mean of triplicate values; error bars indicate the standard deviation. treatment. The starch content in the control fronds over the same time course remained mostly steady, reaching 8.7% (DW) at 12 h and 15.68% (DW) at 240 h post- treatment. Next, frond samples were examined by electron microcopy (Figure 2). The control frond cell contained several chloroplasts with a few small starch granules. In the uniconazole treatment group, several huge starch granules were found in the chloroplasts. very little in both in the control and treatment samples. The activity of α-amylase was 0.0025 U/mg protein at 0 h and reached to 0.037 and 0.0051 U/mg protein in the treated and control samples at 240 h, respectively. How- ever, following treatment, beta-amylase (β-amylase) activ- ity increased gradually from 0.0319 to 0.0747 U/mg protein at 1 h, and finally increased to the 0.3446 U/mg protein at 240 h in the treated sample, with little change in the control sample. Sequencing, de novo assembly, and functional annotation of the L. punctata transcriptome Figure 2 Transmission electron micrographs (TEM) study of L. punctata. (A) TEM picture of frond cells under lower magnification without treatment, Bars = 2 μm; (B) TEM picture of a section of a frond cell under higher magnification without treatment, Bar = 1 μm; (C) TEM picture of frond cells under lower magnification treated by uniconazole, Bar = 2 μm; (D) TEM picture of a section of a frond cell under higher magnification treated with uniconazole, Bar = 1 μm; Abbreviations are chloroplast (C), starch granule (S), intercellular air space (A), nucleus (N). significantly differentially expressed at 2, 5, 72, and 240 h, respectively (Additional file 1: Table S1). Among these four differentially expressed transcripts (DETs: 2 vs 0 h, 5 vs 0 h, 72 vs 0 h, 240 vs 0 h), 2,929 transcripts were shared between these four DET sets. Compared with each other in these four DET sets, 5,503 transcripts were shared be- tween 2 vs 0 h and 5 vs 0 h, 6,281 were shared between 5 vs 0 h and 72 vs 0 h, 5,339 transcripts were shared be- tween 2 vs 0 h and 72 vs 0 h, 5,738 transcripts were shared between 2 vs 0 h and 240 vs 0 h, 6,641 transcripts were shared between 5 vs 0 h and 24 vs 0 h, and 10,621 were shared between 72 vs 0 h and 240 vs 0 h. oxidase/dehydrogenase (CKXs) which is thought to play a key role in controlling cytokinin levels in plants. The ex- pression of CKX was down-regulated from 11.97 frag- ments per kilobase of transcripts per million mapped fragments (FPKM) at 0 h to 4.22 FPKM at 240 h. In the signaling pathway of cytokinin, the cytokinin receptors histidine kinases (HKs) were up-regulated. For example, HK3 expression increased from 27.22 to 49.06 FPKM at 72 h (Additional file 2: Table S2). Their downstream ele- ments histidine phosphotransfer proteins (AHPs) carry conserved amino acids required for phosphotransfer via a conserved histidine residue. There was no significant change in expression of AHPs. Type-B Arabidopsis thali- ana response regulator (type-B ARR) interacts with the promoter of STAY-GREEN2 (SGR2) and interrupts tran- scription of the chlorophyll degradation pathway. SGR ex- pression was up-regulated significantly from an initial value of 8.46 to 130.77 FPKM. Sequencing, de novo assembly, and functional annotation of the L. punctata transcriptome To gain insight into the rapid accumulation of high starch following uniconazole application, the activity of enzymes involved in starch metabolism was analyzed. The activities of two of the most important key enzymes involved in starch synthesis (starch biosynthesis related enzymes AGPase and soluble starch synthase (SSS)) were measured (Figure 3). The activity of AGPase in- creased significantly from 8.20 to 27.59 U/mg protein at 5 h. After 24 h, the activity of AGPase increased slightly until 48 h when it reached a nearly stable level, while the activities of AGPase remained mostly constant in the control sample. SSS activity increased from the initial 8.03 to 25.69 U/mg protein at 2 h, and then decreased to 7.24 U/mg protein at 240 h. SSS activity did not change in the control sample. To investigate the genome-wide expression patterns of uniconazole treated L. punctata, samples collected at the 0, 2, 5, 72, and 240 h time points were used for RNA- Seq analysis. Results indicated that most of the contigs were protein-encoding transcripts. For more details on assembly statistics of the L. punctata transcriptome, please see the accompanying report (data not shown). To analyze temporal expression patterns of each tran- script following uniconazole treatment, all RNA-Seq reads from each L. punctata sample were used for mapping analysis. The expression value of each tran- script was calculated and normalized according to the RESM-based algorithm. We identified 70,090, 71,268, 71,170, 75,092, and 95,367 transcripts expressed at 0, 2, 5, 72, and 240 h, respectively (Figure 4). According to edgeR [31], compared with 0 h, there were 9,722, 11,139, 15,261, and 25,323 transcripts that were The activities of starch degradation related enzymes in L. punctata were also investigated (Figure 3). The activity of alpha-amylase (α-amylase) was very low and changed Page 4 of 12 Liu et al. Biotechnology for Biofuels (2015) 8:64 Figure 2 Transmission electron micrographs (TEM) study of L. punctata. (A) TEM picture of frond cells under lower magnification without treatment, Bars = 2 μm; (B) TEM picture of a section of a frond cell under higher magnification without treatment, Bar = 1 μm; (C) TEM picture of frond cells under lower magnification treated by uniconazole, Bar = 2 μm; (D) TEM picture of a section of a frond cell under higher magnification treated with uniconazole, Bar = 1 μm; Abbreviations are chloroplast (C), starch granule (S), intercellular air space (A), nucleus (N). Expression analysis of transcript-encoding regulatory proteins and transcription factors involved in the CK, ABA, and GA signaling pathways The transcripts of regulatory proteins and transcription factors involved in the CK, ABA, and GA signaling path- ways changed significantly in response to uniconazole treatment (Figure 5). Cytokinins are degraded by cytokinin The core ABA signaling components have been well described in recent years. The family of START proteins Page 5 of 12 Liu et al. Biotechnology for Biofuels (2015) 8:64 Figure 3 AGPase, SSS, α-amylase, and β-amylase activity. Fronds were collected at different time points and used for starch metabolism-related enzymatic activity assay after uniconazole treatment. (A) The activity of ADP-glucose pyrophosphorylase (AGPase); (B) The activity of soluble starch synthase (C) The activity of α-amylase; (D) The activity of β-amylase. All data are presented as the mean of triplicate measurements ± standard deviation. Figure 3 AGPase, SSS, α-amylase, and β-amylase activity. Fronds were collected at different time points and used for starch metabolism-related enzymatic activity assay after uniconazole treatment. (A) The activity of ADP-glucose pyrophosphorylase (AGPase); (B) The activity of soluble starch synthase (C) The activity of α-amylase; (D) The activity of β-amylase. All data are presented as the mean of triplicate measurements ± standard deviation. (PYLs) act as ABA receptors, and 13 of 14 members of the Arabidopsis PYL family have been identified. PYL1 and PYL8 were identified in duckweed, and the expres- sion levels of PYL1 increased from 36.88 FPKM at 0 h to 45.27 FPKM at 240 h. The expression of the PP2C negative regulator (comp31119_c0_seq1) decreased from 308.55 FPKM at 0 h to 122.48 FPKM at 240 h. There were no significant changes observed for the expression of transcript-encoding abscisic acid insensitive 4 (ABI4) (comp31717_c0_seq1). The expression was 0.14, 0.22, 0.05, 0.09 and 0.14 FPKM, respectively. The expression of two identical large subunits of AGPase (AGP-LS comp37255_c0_seq1) was up-regulated from the initial value of 122.13 to 192.48 FPKM at 240 h (Additional file 2: Table S2). Figure 4 Differential expression between each pair of samples. Venn diagram showing unique and shared genes between time points. Overlapping examinations were performed based on the resulting gene lists from four comparisons by VENNY [74]. Overlap among four groups, 2 vs 0 h (blue), 5 vs 0 h (yellow), 7 vs 0 h (green), and 240 vs 0 h (red) are shown. Expression analysis of transcript-encoding regulatory proteins and transcription factors involved in the CK, ABA, and GA signaling pathways In the GAs signal pathway, transcriptomics data showed that the expressions of GA receptor GA insensitive dwarf 1 (GID1 comp41567_c0_seq1) were down-regulated from 44.03 to 23.93, 28.28, and 33.5 FPKM at different time points. The expressions of transcript-encoding DELLA pro- teins (comp33138_c1_seq1) were down-regulated from 6.3 to 4.55, 3.05, 3.61, and 2.12 FPKM, respectively. Moreover, the expression levels of transcript-encoding α-amylase were down-regulated from the initial value of 8.03 to 6 FPKM. Expression analysis of transcript-encoding key enzymes involved in starch accumulation Figure 4 Differential expression between each pair of samples. Venn diagram showing unique and shared genes between time points. Overlapping examinations were performed based on the resulting gene lists from four comparisons by VENNY [74]. Overlap among four groups, 2 vs 0 h (blue), 5 vs 0 h (yellow), 7 vs 0 h (green), and 240 vs 0 h (red) are shown. Figure 4 Differential expression between each pair of samples. Venn diagram showing unique and shared genes between time points. Overlapping examinations were performed based on the resulting gene lists from four comparisons by VENNY [74]. Overlap among four groups, 2 vs 0 h (blue), 5 vs 0 h (yellow), 7 vs 0 h (green), and 240 vs 0 h (red) are shown. Starch is the major storage carbohydrate in plants. To investigate the mechanisms by which uniconazole treat- ment resulted in starch accumulation, the expression patterns of transcript-encoding key enzymes were analyzed Liu et al. Biotechnology for Biofuels (2015) 8:64 Page 6 of 12 Height CK increase GA decrease Chloroplast Light -D-Glucose-1P increase Cytoplasm AGPase (2.7.7.27) increase Dextrin decrease Frond -AMY (3.2.1.1) Starch increase ChL increase Starch accumulation Calvin cycle CO2 Glucose Starch granule GID1 HK2 DELLA ABA intensitivity 1b Uniconazole treatment AGPLs ABA increase PSII/PSI Amy32b bHLHs SGR2 Type-B ARRs AHPs Chl degradation HK3 HK4 PYL PYL ABA Nucleus Transcription Transcription Transcription ABI4 KO HKs CKX CK degradation ABA degradation ABA 8'-hydroxylase GA biosynthesis Up-regulation Down-regulation No change SnRK2 PP2C Figure 5 A hypothetical model of cytokinin, abscisic acid, and gibberellin signal pathways related to carbohydrate metabolism. Red indicates up-regulated expression, green down-regulated gene expression, gray means no significant difference was observed, and white means this enzyme was not found in this study. The major signaling pathways are indicated by black lines and arrows. Dotted arrowed lines indicate indirect or unconfirmed connections. Blue arrow indicates enlarged image. Cytokinin is perceived by the cytokinin receptor HKs. Cytokinin binding to HKs activates autophosphorylation (P) via AHPs (histidine phosphotransfer proteins) in the cytoplasm. Then type-B Arabidopsis thaliana response regulator (type-B ARR) interacts with the promoter of STAY-GREEN2 (SGR2). The family of START proteins (PYLs) act as ABA receptors. ABA combines with intracellular PYL and type 2C protein phosphatase (PP2C) to form an ABA-PYL-PP2C complex. This complex inhibits the activity of PP2C in an ABA-dependent manner and activates SNF1-related protein kinase 2 families (SnRK2s). Expression analysis of transcript-encoding key enzymes involved in starch accumulation Dotted arrowed lines indicate indirect or unconfirmed connections. Blue arrow indicates enlarged image. Cytokinin is perceived by the cytokinin receptor HKs. Cytokinin binding to HKs activates autophosphorylation (P) via AHPs (histidine phosphotransfer proteins) in the cytoplasm. Then type-B Arabidopsis thaliana response regulator (type-B ARR) interacts with the promoter of STAY-GREEN2 (SGR2). The family of START proteins (PYLs) act as ABA receptors. ABA combines with intracellular PYL and type 2C protein phosphatase (PP2C) to form an ABA-PYL-PP2C complex. This complex inhibits the activity of PP2C in an ABA-dependent manner and activates SNF1-related protein kinase 2 families (SnRK2s). Abscisic acid insensitive 4 (ABI4) induces ADP-glucose pyrophosphorylase subunit AGPLs (ApL3) gene expression. The main components of the GA signal pathway include GA receptor (GID1) and DELLA growth inhibitors. The GA-GID1-DELLA complex stimulates the degradation of DELLAs to regulate plant growth. GID1 regulated the transcription of amylase by a number of transcriptional regulatory. (Figure 6). Gene expression profiling results showed that the expression of transcript-encoding AGPase were up- regulated from 24 to 95 FPKM at 240 h (comp37852_c0_ seq1). Transcript-encoding granule-bound starch synthase (GBSS) exhibited an expression level of 106 FPKM at 0 h and increased to 311 FPKM at 240 h (comp31254_c0_ seq1). There were no significant changes observed for the expression of transcript-encoding SSS and SBE (Additional file 3: Table S3). (Figure 6). Gene expression profiling results showed that the expression of transcript-encoding AGPase were up- regulated from 24 to 95 FPKM at 240 h (comp37852_c0_ seq1). Transcript-encoding granule-bound starch synthase (GBSS) exhibited an expression level of 106 FPKM at 0 h and increased to 311 FPKM at 240 h (comp31254_c0_ seq1). There were no significant changes observed for the expression of transcript-encoding SSS and SBE (Additional file 3: Table S3). phosphate synthase (EC: 2.4.1.14), and sucrose synthase (SuSy EC: 2.4.1.13). Specifically, hexokinase (comp24929_ c1_seq2) was significantly down-regulated from 59 to 18 FPKM at 240 h. No significant increase was observed for the expression of transcript-encoding α-amylase. However, transcript-encoding β-amylase exhibited an expression level of 15 FPKM at 0 h and increased to 309 FPKM at 240 h (comp16912_c0_seq1). Expression analysis of transcript-encoding key enzymes involved in starch accumulation Abscisic acid insensitive 4 (ABI4) induces ADP-glucose pyrophosphorylase subunit AGPLs (ApL3) gene expression. The main components of the GA signal pathway include GA receptor (GID1) and DELLA growth inhibitors. The GA-GID1-DELLA complex stimulates the degradation of DELLAs to regulate plant growth. GID1 regulated the transcription of amylase by a number of transcriptional regulatory. Height CK increase GA decrease Chloroplast Light -D-Glucose-1P increase Cytoplasm AGPase (2.7.7.27) increase Dextrin decrease Frond -AMY (3.2.1.1) Starch increase ChL increase Starch accumulation Calvin cycle CO2 Glucose Starch granule GID1 HK2 DELLA ABA intensitivity 1b Uniconazole treatment AGPLs ABA increase PSII/PSI Amy32b bHLHs SGR2 Type-B ARRs AHPs Chl degradation HK3 HK4 PYL PYL ABA Nucleus Transcription Transcription Transcription ABI4 KO HKs CKX CK degradation ABA degradation ABA 8'-hydroxylase GA biosynthesis Up-regulation Down-regulation No change SnRK2 PP2C Amy32b on Starch accumulation Starch accumulation Figure 5 A hypothetical model of cytokinin, abscisic acid, and gibberellin signal pathways related to carbohydrate metabolism. Red indicates up-regulated expression, green down-regulated gene expression, gray means no significant difference was observed, and white means this enzyme was not found in this study. The major signaling pathways are indicated by black lines and arrows. Dotted arrowed lines indicate indirect or unconfirmed connections. Blue arrow indicates enlarged image. Cytokinin is perceived by the cytokinin receptor HKs. Cytokinin binding to HKs activates autophosphorylation (P) via AHPs (histidine phosphotransfer proteins) in the cytoplasm. Then type-B Arabidopsis thaliana response regulator (type-B ARR) interacts with the promoter of STAY-GREEN2 (SGR2). The family of START proteins (PYLs) act as ABA receptors. ABA combines with intracellular PYL and type 2C protein phosphatase (PP2C) to form an ABA-PYL-PP2C complex. This complex inhibits the activity of PP2C in an ABA-dependent manner and activates SNF1-related protein kinase 2 families (SnRK2s). Abscisic acid insensitive 4 (ABI4) induces ADP-glucose pyrophosphorylase subunit AGPLs (ApL3) gene expression. The main components of the GA signal pathway include GA receptor (GID1) and DELLA growth inhibitors. The GA-GID1-DELLA complex stimulates the degradation of DELLAs to regulate plant growth. GID1 regulated the transcription of amylase by a number of transcriptional regulatory. Figure 5 A hypothetical model of cytokinin, abscisic acid, and gibberellin signal pathways related to carbohydrate metabolism. Red indicates up-regulated expression, green down-regulated gene expression, gray means no significant difference was observed, and white means this enzyme was not found in this study. The major signaling pathways are indicated by black lines and arrows. Discussion Transcript-encoding enzymes involved in starch deg- radation and other carbohydrate metabolic branches were also analyzed. The expression level of transcript- encoding trehalose-6-phosphate synthase (EC: 2.4.1.15; TPS), which catalyze the biosynthesis of trehalose using UDPGlucose as substrate, was down-regulated from 78.1 to 18.7 FPKM (comp36386_c1_seq6) at 240 h after uni- conazole treatment. Carbohydrate metabolic branches that compete with the synthesis of starch were also mea- sured, including hexokinase (EC: 2.7.1.1), beta-glucosidase (EC: 3.2.1.21), phosphoglucomutase (EC: 5.4.2.2), sucrose- The relationship between endogenous hormones induced by uniconazole and starch accumulation in L. punctata Numerous studies have investigated different types of plant growth regulators that regulate growth and development in plants. Some articles focus their investigations on cer- tain stress responses mediated by one or two types of plant hormones [32-34]. These studies often analyze phenotypic, biochemical, and physiological data. Some studies research the function of regulatory elements on hormones of signaling pathways [35,36]. Other studies investigate the relationship Liu et al. Biotechnology for Biofuels (2015) 8:64 Page 7 of 12 Figure 6 Expression patterns of carbohydrate metabolism-related transcripts. Expression variations of some carbon metabolism-related transcripts are displayed in the simplified starch and sucrose metabolism pathway. Red boxes indicate the up-regulated enzymes involved in carbohydrate metabolism, green boxes indicate the down-regulated enzymes, gray boxes mean no significant difference was observed, and white boxes mean this enzyme was not found in this study. The numbers in the upper half of the boxes correspond to the EC numbers and the numbers in the lower half, separated by slashes, correspond to the expression levels of these enzymes shown in FPKM at 0, 2, 5, 72, and 240 h, respectively. 1.1.1.22: UDP-glucose 6-dehydrogenase; 2.4.1.1: glycogen phosphorylase; 2.4.1.13: sucrose synthase; 2.4.1.14: sucrose phosphate synthase; 2.4.1.21: soluble starch synthase; 2.4.1.15: trehalose-6-phosphate synthase; 2.4.1.18: starch-branching enzyme; 2.4.1.12: cellulose synthase; 2.4.1.242: granule bound starch synthase; 2.7.7.27: ADP-glucose pyrophosphorylase; 2.7.7.9: UDP-glucose pyrophosphorylase; 2.7.1.1: hexokinase; 3.2.1.1: alpha-amylase; 3.2.1.2: beta-amylase; 3.1.3.12: trehalose 6-phosphate phosphatase; 3.2.1.4: endoglucanase; 3.2.1.28: trehalase; 5.4.2.2: phosphoglucomutase. Figure 6 Expression patterns of carbohydrate metabolism-related transcripts. Expression variations of some carbon metabolism-related transcripts are displayed in the simplified starch and sucrose metabolism pathway. Red boxes indicate the up-regulated enzymes involved in carbohydrate metabolism, green boxes indicate the down-regulated enzymes, gray boxes mean no significant difference was observed, and white boxes mean this enzyme was not found in this study. Discussion The numbers in the upper half of the boxes correspond to the EC numbers and the numbers in the lower half, separated by slashes, correspond to the expression levels of these enzymes shown in FPKM at 0, 2, 5, 72, and 240 h, respectively. 1.1.1.22: UDP-glucose 6-dehydrogenase; 2.4.1.1: glycogen phosphorylase; 2.4.1.13: sucrose synthase; 2.4.1.14: sucrose phosphate synthase; 2.4.1.21: soluble starch synthase; 2.4.1.15: trehalose-6-phosphate synthase; 2.4.1.18: starch-branching enzyme; 2.4.1.12: cellulose synthase; 2.4.1.242: granule bound starch synthase; 2.7.7.27: ADP-glucose pyrophosphorylase; 2.7.7.9: UDP-glucose pyrophosphorylase; 2.7.1.1: hexokinase; 3.2.1.1: alpha-amylase; 3.2.1.2: beta-amylase; 3.1.3.12: trehalose 6-phosphate phosphatase; 3.2.1.4: endoglucanase; 3.2.1.28: trehalase; 5.4.2.2: phosphoglucomutase. 9.25 to 5.57 ng/g (FW) following treatment (accompany- ing report). CKs elevated the chlorophyll content by con- trolling regulatory proteins involved in the chlorophyll biosynthesis signaling pathway. CKs are a class of plant growth substances that promote cell division, chloroplast synthesis, and amyloplast formation [44,45]. Furthermore, the increase of CKs plays an important role in regulating grain filling pattern and consequently elevated starch ac- cumulation [46]. In the CK mediated chlorophyll synthesis signaling pathway [47,48], CKs are degraded by CKXs. The transcriptomics data suggested that HKs and SGR were up-regulated. The expression of SGR was up- regulated significantly from the initial value of 8.46 to 130.77 FPKM. The interaction of type-B ARR with SGR2 was assayed to determine whether the cytokinin signaling pathway interacted with a key step in chlorophyll degrad- ation within the chloroplast [49]. The increase in SGR can suppress the degradation of chlorophyll, thereby improv- ing chlorophyll content. Furthermore, the expression pat- tern of the regulatory proteins described above coincided with the increase in chlorophyll content. The chlorophyll a content increased from the initial value of 0.998 to 1.239 mg/g (FW), and chlorophyll b increased from the initial value of 0.426 to 0.488 mg/g (FW). The chlorophyll a and chlorophyll b content increased by 25.6% and 27%, respectively, compared to the control sample. Importantly, between different types of hormones [37-39]. Regulatory proteins are the main focus in these articles, which utilize molecular biology techniques with little to no focus on metabolic pathways. Additionally, some articles used tran- scriptome analyses to study the response of plants treated with hormones [40-42]; however, these articles empha- sized the up- or down-regulation of genes or discovery of new genes, but did not consider metabolic pathways. Starch accumulation of L. punctata under uniconazole treatment ABA up-regulated the expression of AGPase large sub- unit gene transcription by controlling the expression of regulatory elements of the ABA signal pathway. Studies have shown that ABA can up-regulate AGPase gene transcription in rice suspension cells [50] and suppress the expression of gene-encoding amylases and proteases [51]. Reports also indicated that the rates of starch accu- mulation are positively correlated with ABA levels in wheat grains. As shown in Figure 5, the expression of transcript-encoding ABA receptors of PYLs was up- regulated from 36.88 to 45.27 FPKM at 240 h. ABA com- bines with intracellular PYL and negative regulator PP2C (type 2C protein phosphatase) to form an ABA-PYL-PP2C complex. ABI4 induces ADP-glucose pyrophosphorylase subunit (ApL3) gene expression [52-55]. Moreover, the ex- pression of the AGPase large subunit gene (ApL3) also in- creased. Importantly, the up-regulated expression of the AGPase large subunit gene strongly supported the im- proved activity of AGPase, and the increased activity of AGPase promoted starch accumulation in duckweed. The rapid starch accumulation in fronds of L. punctata after uniconazole treatment displayed some similarities to grain filling which is a major process of starch biosynthesis and accumulation in seeds. For instance, both processes are rapid and show similar alteration of endogenous hor- mone levels such as a decrease in GAs and an increase in ABA. In addition, some key enzymes (AGPase and SSS) involved in starch biosynthesis are regulated in a similar way in both processes. In this study, the transcriptomics analyses, enzymatic assays, and starch percentages were integrated to un- cover the process of rapid accumulation of high starch after uniconazole application. The data from three lines of evidence were analyzed and compared. Investigation of starch composition showed that the starch content and biomass yield in L. punctata accumulated rapidly. After culturing for 240 h, the starch content reached 48% in the treated samples and 15.7% in the control samples from an initial yield of 3.2% (Figure 1). The bio- mass of treated samples (dry weight) improved 10% over the control samples (data not shown). As a result, the total starch that accumulated in the treated samples was 3.4 times higher than that in the control samples. Mean- while, the enzyme activities involved in starch synthesis, such as AGPase and SSS, were improved dramatically by uniconazole treatment (Figure 3). The activity of AGPase increased significantly from 8.20 to 27.59 U/mg protein, representing a 3.4-fold increase. Discussion Li [43] used RNA sequencing technology to understand the mechanisms of parthenocarpy and predicted 14 genes as putative parthenocarpic genes. The transcription ana- lyses of these candidate genes revealed that auxin, cytoki- nin, and gibberellin crosstalk at the transcriptional level during parthenocarpic fruit set, but the metabolic path- ways of these hormones were not mentioned. In this study, we analyzed metabolic pathways using NGS tech- nology; this data, combined with physiological and bio- chemical analyses and crosstalk of different plant hormones, allowed us to elucidate the process of starch accumulation in L. punctata. between different types of hormones [37-39]. Regulatory proteins are the main focus in these articles, which utilize molecular biology techniques with little to no focus on metabolic pathways. Additionally, some articles used tran- scriptome analyses to study the response of plants treated with hormones [40-42]; however, these articles empha- sized the up- or down-regulation of genes or discovery of new genes, but did not consider metabolic pathways. Li [43] used RNA sequencing technology to understand the mechanisms of parthenocarpy and predicted 14 genes as putative parthenocarpic genes. The transcription ana- lyses of these candidate genes revealed that auxin, cytoki- nin, and gibberellin crosstalk at the transcriptional level during parthenocarpic fruit set, but the metabolic path- ways of these hormones were not mentioned. In this study, we analyzed metabolic pathways using NGS tech- nology; this data, combined with physiological and bio- chemical analyses and crosstalk of different plant hormones, allowed us to elucidate the process of starch accumulation in L. punctata. The alteration of the endogenous CK, ABA, and GAs co-regulates starch metabolism in L. punctata. The en- dogenous hormone content changed dramatically fol- lowing uniconazole application. ABA content increased from 61.47 to 166.53 ng/g (FW), ZR increased from 7.73 to 11.87 ng/g (FW), and the level of GA1+3 decreased from Page 8 of 12 Liu et al. Biotechnology for Biofuels (2015) 8:64 net photosynthetic rate, the increased ABA content pro- moted the activity of AGPase, and the low levels of GAs inactivated amylase. Overall, the alterations in endogen- ous hormone levels following uniconazole treatment im- proved starch accumulation in duckweed by influencing the related enzymes involved in carbohydrate metabol- ism and processes. the improvement of the net photosynthetic rate was con- sistent with the increase of starch and biomass accumula- tion. Discussion The net photosynthetic rate increased from the initial value of 8.83 μmol CO2/m2/s to 22.05 and 25.6 μmol CO2/m2/s in the control and treatment groups, respect- ively (accompanying report). Thus, the improvement of chlorophyll content and net photosynthetic rate may lead to starch and biomass accumulation in L. punctata. Starch accumulation of L. punctata under uniconazole treatment Importantly, the ex- pression patterns of transcript-encoding key enzymes involved in starch biosynthesis and degradation fur- ther supported the physiological and biochemical re- sults described above. Transcriptome analysis showed that the expression of GBSS transcripts were up-regulated significantly. GAs suppressed the expression of the amylase gene by controlling expression of regulatory factors. A study of GA regulating the growth and carbohydrate metabolism of potatoes showed that GA3 could substantially reduce the activity of AGPase in the growing tubers of potatoes [56]; therefore, uniconazole treatment might eliminate the obstacle by blocking GA synthesis and enhancing starch accumulation. GAs can induce or activate α- amylase and other hydrolases, which is not conducive to the synthesis and accumulation of starch [57,58]. More- over, reports showed that during grain filling, the ratio of endogenous GAs and ABA changes greatly in rice. The ABA content was significantly increased and GA content dramatically decreased, which enhanced the remobiliza- tion of prestored carbon to the grains and accelerated the grain filling rate [59]. In this study, the expression of α-amylase was down-regulated from the initial 8.03 to 6 FPKM. The decrease of GA levels suppressed α-amylase expression, and the reduced activities of α-amylase pre- vented starch degradation in duckweed. These findings also support starch accumulation. Starch phosphorylation and glucan hydrolysis are two necessary steps in the degradation process. Glucan water dikinase (GWD) and phosphoglucan water dikinase (PWD) are responsible for starch phosphorylation. Β- amylases catalyze the hydrolysis of a-1, 4-glycosidic link- ages and release maltose from the exposed nonreducing ends of glucan chains. Α-amylases hydrolyze α-1, 4 link- ages within polymers exposed on the surface or in chan- nels within granules, releasing soluble glucans that are the substrate for further degradation [60,61]. In this study, The improvement of starch accumulation following uniconazole treatment was closely associated with the el- evated level of endogenous ABA and CK and reduced GA content in duckweed. In this study, high levels of CKs accelerated the biosynthesis of chlorophyll and the Page 9 of 12 Liu et al. Biotechnology for Biofuels (2015) 8:64 there no significant changes were observed for the expres- sion of transcript-encoding GWD. The expression level of GWD (comp38348_c1_seq1) was 40.24, 39.54, 63.45, 39.05, and 47.73 FPKM in different time points, respect- ively. The starch degradation enzyme activities of α- amylase changed little between the control and treated samples. Conclusions In this study, high starch accumulation in L. punctata 0202 was achieved after uniconazole application in a nutrient-rich environment. The process of starch accu- mulation was investigated at physiological, biochemical, and transcriptome levels. The increase in endogenous ABA and CK levels further enhanced the activity of AGPase and chlorophyll biosynthesis, while decreased en- dogenous GA levels significantly correlated with the in- activation of α-amylase. Moreover, uniconazole increased the levels of substrates of starch synthesis and regulated transcriptional expression of enzymes by changing the biosynthesis of endogenous hormones, resulting in starch accumulation in duckweed. Because of the complex interaction among different hormones, the alteration Material composition The starch content was described as glucose content in total sugar by HPLC (Thermo 2795, Thermo Corp, Wal- tham, USA)-ELSD (All-Tech ELSD 2000, All-tech, Corp, Nicholasville, USA) using the following method. The starch content was determined using the total sugar content (starch content = glucose content × 0.909). Dry duckweed powder was hydrolyzed with 1.2 M HCl in a boiling water bath. After adjusting the pH to 7 with 10 M NaOH, PbAc was added to precipitate protein. After the solution was measured, filtered, and treated with a C18 extraction column, the hydrolyzate was analyzed by HPLC (Thermo 2795, Thermo Corp.) with an Evaporative Lightscattering Detector (All-Tech ELSD 2000, All-tech., Corp.) [65]. Starch accumulation of L. punctata under uniconazole treatment Though the expression of β-amylase was in- creased in a manner contradictory with starch accu- mulation, physiological data showed that the activity of β-amylase was too low to compare with the improved enzyme activity of starch biosynthesis. The expression of enzymes involved in competitive starch metabolic branches, including hexokinase sucrose-phosphate syn- thase, phosphoglucomutase (EC: 5.4.2.2) and others were also down-regulated (Figure 6). Coupled with the up- regulation of starch biosynthesis related key enzyme- encoding transcripts, the down-regulation of transcripts finally redirected alpha-D-glucose-1P and UDP-glucose to the starch biosynthesis branch. of endogenous hormone levels can provide further insight into the relationship of endogenous hormones to starch accumulation. In this study, an operable process for high starch accumulation in duckweed was developed, paving the way for large-scale treatment of wastewater and the application of duckweed to bioenergy. Duckweed cultivation and uniconazole treatments Duckweed cultivation and uniconazole treatments L. punctata 0202 was originally collected from Sichuan province, China. It was cultivated in standard 1/6Hoagland E+ solution (Total N = 58.3 mg/L, P = 25.8 mg/L) [64] cul- ture for 3 days under a 16/8 h day/night photoperiod, with a light intensity of 130 μmol/m2/s and a temperature of 25°C/15°C at day/night. Then, 6 g of fronds were trans- ferred into 1,000 mL 1/6 Hoagland E+ culture plastic con- tainers (23 × 14 × 4.5 cm) for further cultivation over a period of 10 days. Uniconazole powder was produced in Japan and purchased from Aoke Biotech Corp (Beijing, China). The concentration of uniconazole used in this study was 800 mg · L−1. To investigate the effect of unico- nazole treatment on L. punctata, a 5-mL solution of 800 mg · L−1 uniconazole was sprayed evenly on the sur- face of fronds. Controls were sprayed with 5 mL water containing 10% methanol. The experiments were carried out with three replicates. Thirteen different time points, in- cluding 0, 1, 2, 3, 5, 7, 12, 24, 48, 72, 120, 168, and 240 h after fronds were cultured in solution and were chosen for composition and enzymatic activity assays. For each time point, fronds were collected from three culture plastic con- tainers. Samples collected at 0, 2, 5, 72, and 240 h were fro- zen in liquid nitrogen immediately for the RNA-Seq study. In this study, up-regulation of key enzymes in starch biosynthesis, in combination with down-regulation of transcripts of key enzymes related to starch degradation and other carbohydrate metabolic branches that com- pete with the synthesis of starch, eventually led to the accumulation of starch in L. punctata. Uniconazole has a similar chemical structure to paclo- butrazol. It reduces plant growth more than paclobutra- zol when applied as a soil drench in equal amounts. On average, the amount of paclobutrazol required is four to ten times that of uniconazole, to obtain a similar effect on plant size [62]. Early research indicated that unicona- zole can be very persistent in retarding plant growth without causing phytotoxicity [63]. Half-lives of paclobu- trazol and uniconazole in water were 24.4 and 5.2 days, respectively. Uniconazole-p is non-toxic to birds, bees, and earthworms, but slightly toxic to fish and aquatic in- vertebrates. Therefore, it can be applied to high starch accumulation of duckweed in large-scale cultivation. Calculations and statistics Each data point represents the results of three sample experiments; the results are provided as means ± stand- ard error in the figures. Expression pattern analysis To analyze the express levels of each transcript at differ- ent time points following uniconazole treatment, all PE reads for each sample were used for mapping analysis with Perl scripts in the Trinity package (v2012-06-08) [70] under default parameter choices. The expression value of each transcript was calculated and normalized according to the RESM-based algorithm using the Perl scripts in the Trinity (v2012-06-08) package to obtain FPKM values. P values and log2 fold change (log2FC) were calculated, and significantly DETs between each sample set were identified with P value ≤0.05 and log2FC ≥1. Hypergeometric tests based on the KEGG annotation were performed for each DET group identified between each sample set using R scripts (Additional file 4) to ex- tract the enriched KEGG pathway. Additionally, we depicted differences and commonalities in the number of DEGs using the VENNY under default parameter choices (http://bioinfogp.cnb.csic.es/tools/venny/index.html) [74]. RNA extraction and cDNA fragment library construction Five L. punctata samples were collected at the 0, 2, 5, 72, and 240 h time points after treatment with unicona- zole. For each sample, total RNA was extracted from 200 mg fronds using the OMEGATM Plant DNA/RNA kit (OMEGA, Norcross, USA) and genomic DNA was digested by DNase I (Fermentas, Waltham, USA) accord- ing to the manufacturer’s instructions. RNA concentra- tion, OD260/280, OD260/230, 28S/18S and RNA integrity number (RIN) were measured with the Agilent 2100 Bioanalyzer or NanoDrop (Agilent, Santa Clara, USA). Qualified total RNA extracted from each sample was sub- mitted to the Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China, (http://www.genomics.cn) for RNA se- quencing by Illumina HiSeq 2000 (Illumina, San Diego, USA). cDNA fragment libraries were constructed accord- ing to the manufacturer’s instructions using the TruSeq RNA Sample Prep kit. Library quality control analysis was performed using the Agilent 2100 Bio-analyzer. Carbohydrate metabolism enzyme activity assay To investigate enzyme activity, 1 g fresh weight duck- weed was homogenized with a ceramic pestle in an ice- cold mortar in 5 mL of 50 mmol/L HEPES-NaOH (pH = 7.6), 5 mmol/L DL-Dithiothreitol, 8 mmol/L MgCl2, 2 mmol/L EDTA, 2% (w/v) polyvinylpyrrolidone-40, and 12.5% (w/v) glycerol. The homogenate was centri- fuged at 10,000 × g for 5 min. The supernatant extract was used as a crude enzyme solution stored at −20°C. All pro- cedures were carried out at 0 to 4°C. The activities of α- amylase (1, 4, d-glucan glucanohydrolase) and β-amylase (1, 4, d-glucan maltohydrolase) were estimated following the method of Tarrago and Nicolas [68,69]. The enzymatic activities of SSS and AGPase were assayed according to Nakamura et al. [69]. Functional annotation and cluster All contigs assembled by Trinity (v2012-06-08) [70] were submitted to Blast2GO [72,73] for functional annotation. A BLASTX similarity search was performed against the NR database (http://www.ncbi.nlm.nih.gov/) by Blast2GO with a threshold of E value <103. Enzyme codes were ex- tracted, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were retrieved from the KEGG web ser- ver (http://www.genome.jp/kegg/). Microscopic analysis of fronds Fronds in the uniconazole treatment group and control group were fixed, embedded, and dehydrated as described [66,67]. Samples were fixed in 5% glutaraldehyde in 0.1 M PBS (pH 7.4) containing 2% Suc in a 2 mL tube at 4°C Page 10 of 12 Liu et al. Biotechnology for Biofuels (2015) 8:64 overnight followed by 3 h at room temperature. Samples were rinsed with 0.1 M PBS (pH 7.4) and postfixed in buffered 1% osmium tetroxide at 4°C overnight, followed by dehydration in a graded series of acetone washes. The dehydrated samples were then embedded in epon resin. The 1 mm-thick sections were picked up on a glass slide, stained with methylene blue, and scoped with a light microscope. Ultrathin sections were cut with an ultrami- crotome (Leica EM UC6, Wetzlar, Germany) and ob- served with transmission electron microscopy (TEM; Tecnai G2 F20S-Twin, FEI, Hillsboro, USA) at 200 kV after staining with uranyl acetate and lead citrate. ac.uk/projects/fastqc/) and then de novo assembled using Trinity (v2012-06-08) [70] under default parameter choices. All PE reads were used to align back to these assembled sequences using the Bowtie2 (v2.0.0-beta5) program [71]. Accordingly, the read align rate was calculated. Length distribution analysis was performed with Perl scripts (Additional file 4) to calculate the N50 number, average length, and max length. The best candidate open reading frame (ORF) was predicted using Perl scripts in the Trinity package (v2012-06-08) [70]. Additional file 1: Table S1. Sequence annotations of L. punctata transcripts and the gene expression profiling of five samples. Additional file 2: Table S2. Expression levels of some regulatory proteins and transcription factors involved in CK, ABA, and GA signaling pathways. Competing interests 14. Cui W, Xu J, Cheng J, Stomp A. Starch accumulation in duckweed for bioethanol production. Biol Eng. 2011;3:187–97. The authors declare that they have no competing interests. 15. Chen Q, Jin Y, Zhang G, Fang Y, Xiao Y, Zhao H. Improving production of bioethanol from Duckweed (Landoltia punctata) by pectinase pretreatment. Energies. 2012;5(8):3019–32. Received: 31 October 2014 Accepted: 24 March 2015 Received: 31 October 2014 Accepted: 24 March 2015 29. Wang X, Zhou G, Xu X, Geng R, Zhou J, Yang Y, et al. Transcriptome profile analysis of adipose tissues from fat and short-tailed sheep. Gene. 2014;549(2):252–7. Authors’ contributions YL carried out biochemical assays, the data analysis, drafted and revised the manuscript. YF participated in the design of the study, the data analysis, conceived the study and revised the manuscript. Y-lJ and YZ participated in the design of the study and revised the manuscript. M-jH and XT participated in the data analysis and revised the manuscript. J-lS participated in the data analysis. G-hZ participated in the part of data analysis and interpretation and revised the manuscript. K-zH participated in the design of the study. HZ conceived the study and revised the manuscript. All authors read and approved the final manuscript. YL carried out biochemical assays, the data analysis, drafted and revised the manuscript. YF participated in the design of the study, the data analysis, conceived the study and revised the manuscript. Y-lJ and YZ participated in the design of the study and revised the manuscript. M-jH and XT participated in the data analysis and revised the manuscript. J-lS participated in the data analysis. G-hZ participated in the part of data analysis and interpretation and 16. Xiao Y, Fang Y, Jin Y, Zhang G, Zhao H. Culturing duckweed in the field for starch accumulation. Ind Crop Prod. 2013;48:183–90. 17. McLAREN JS, Smith H. The effect of abscisic acid on growth, photosynthetic rate and carbohydrate metabolism in Lemna minor L. New Phytol. 1976;76(1):11–20. revised the manuscript. K-zH participated in the design of the study. HZ conceived the study and revised the manuscript. All authors read and approved the final manuscript. 18. McCombs P, Ralph R. Protein, nucleic acid and starch metabolism in the duckweed Spirodela oligorrhiza treated with cytokinins. Biochem J. 1972;129:403–17. 19. Wang W, Messing J. Analysis of ADP-glucose pyrophosphorylase expression during turion formation induced by abscisic acid in Spirodela polyrhiza (greater duckweed). BMC Plant Biol. 2012;12:5. Abbreviations ABA: abscisic acid; ABI4: abscisic acid insensitive 4; AHPs: histidine phosphotransfer proteins; CKs: cytokinins; DET: differentially expressed transcript; DW: dry weight; EC: enzyme codes; FPKM: fragments per kilobase of transcripts per million mapped fragments; FW: fresh weight; GAs: gibberellins; HKs: histidine kinases; KEGG: Kyoto Encyclopedia of Genes and Genomes; log2FC: log2 fold change; NGS: next-generation sequencing; PE: paired-end; PP2C: type 2C protein phosphatase; PYLs: family of START proteins; SGR2: STAY-GREEN2 protein; type-B ARR: type-B Arabidopsis thaliana response regulator. 10. Reid M, Bieleski R. Response of Spirodela oligor deficiency. Plant Physiol. 1970;46(4):609–13. 10. Reid M, Bieleski R. Response of Spirodela oligorrhiza to phosphorus deficiency. Plant Physiol. 1970;46(4):609–13. 11. Bayrakci AG, Kocar G. Second-generation bioethanol production from water hyacinth and duckweed in Izmir: a case study. Renew Sust Energ Rev. 2014;30:306–16. 12. El-Shafai SA, El-Gohary FA, Nasr FA, Peter Van Der Steen N, Gijzen HJ. Nutrient recovery from domestic wastewater using a UASB-duckweed ponds system. Bioresour Technol. 2007;98(4):798–807. y 13. Blazey EB, McClure JW. The distribution and taxonomic significance of lignin in the Lemnaceae. Amer J Bot. 1968;55:1240–5. in the Lemnaceae. Amer J Bot. 1968;55:1240–5. RNA sequencing and paired-end reads assembly The validated 200 bp fragment cDNA libraries were sub- mitted to the Illumina HiSeq 2000 platform for paired- end (PE) RNA sequencing. PE read sequencing quality was assessed by fastqc (http://www.bioinformatics.bbsrc. Page 11 of 12 Liu et al. Biotechnology for Biofuels (2015) 8:64 6. Leng R, Stambolie J, Bell R. Duckweed-a potential high-protein feed resource for domestic animals and fish. Livest Res Rural Dev. 1995;7(1):36. Additional file 3: Table S3. Expression levels of some carbon metabolism related genes. Additional file 3: Table S3. Expression levels of some carbon metabolism related genes. Additional file 3: Table S3. Expression levels of some carbon metabolism related genes. 7. Hillman WS, Culley Jr DD. The uses of duckweed. Am Sci. 1978;66:442–51. Additional file 4: Common scripts. The common scripts including Perl scripts and R scripts for assembly statistic and pathway enrich. Additional file 4: Common scripts. The common scripts including Perl scripts and R scripts for assembly statistic and pathway enrich. 8. Xu J, Cui W, Cheng JJ, Stomp A-M. Production of high-starch duckweed and its conversion to bioethanol. Biosyst Eng. 2011;110(2):67–72. 9. Zhao Y, Fang Y, Jin Y, Huang J, Bao S, Fu T, et al. Potential of duckweed in the conversion of wastewater nutrients to valuable biomass: a pilot-scale comparison with water hyacinth. Bioresour Technol. 2014;163:82–91. Acknowledgements Th h k l d The authors acknowledge financial support received from the National Key Technology R&D Program of China (No. 2015BAD15B01), the Projects of International Cooperation of Ministry of Science and Technology of China (2014DFA30680), Key Laboratory of Environmental and Applied Microbiology, Chengdu Institute of Biology, Chinese Academy of Sciences (No. KLCAS-2014-02), and West Light Foundation of The Chinese Academy of Sciences (Y2C5021100). We thank Dr. Wei-zao Huang, Prof Song-hu Wang, and Prof Wan Xiong for revising the manuscript. We thank Miss Wen Zheng, Dr. Zhen Liu, and Dr. Ying-hong Gu for writing some scripts. 20. Pavlista AD. Growth regulators increased yield of Atlantic potato. Am J Potato Res. 2011;88(6):479–84. 21. Fletcher RA, Hofstra G. Improvement of uniconazole-induced protection in wheat seedlings. J Plant Growth Regul. 1990;9(4):207–12. 22. Fletcher R, Hofstra G, Gao JG. Comparative fungitoxic and plant growth regulating properties of triazole derivatives. Plant Cell Physiol. 1986;27(2):367–71. 23. Zhou W, Ye Q. Physiological and yield effects of uniconazole on winter rape (Brassica napus L.). J Plant Growth Regul. 1996;2:69–73. Author details 1 h d 24. Wan-zhuo G, Zheng-yi Z, Weng-yu Y, Wen-zhu L. Effect of uniconazloe for dry seed treatment on morphological characteristics and yield of soybean. Soybean Science. 2007;26(3):369. 1Chengdu Institute of Biology, Chinese Academy of Sciences, No.9 Section 4, Renmin Nan Road, 610041 Chengdu, China. 2University of Chinese Academy of Sciences, No.19A Yuquan Road, 100049 Beijing, China. 3Key Laboratory of Environmental and Applied Microbiology, Chinese Academy of Sciences, No.9 Section 4, Renmin Nan Road, 610041 Chengdu, China. 4Environmental Microbiology Key Laboratory of Sichuan Province, No.9 Section 4, Renmin Nan Road, 610041 Chengdu, China. 5Key Laboratory of Bio-Resources and Eco-Environment, Ministry of Education, College of Life Sciences, Sichuan University, N0.24 South Section 1, Yihuan Road, 610064 Chengdu, China. 25. Zhang M, Duan L, Tian X, He Z, Li J, Wang B, et al. Uniconazole-induced tolerance of soybean to water deficit stress in relation to changes in photosynthesis, hormones and antioxidant system. J Plant Physiol. 2007;164(6):709–17. 26. Smith AM. The biosynthesis of starch granules. Biomacromolecules. 2001;2(2):335–41. 27. Martin C, Smith AM. Starch biosynthesis. Plant Cell. 1995;7(7):971–85. 28. Wu Y, Wei W, Pang X, Wang X, Zhang H, Dong B, et al. Comparative transcriptome profiling of a desert evergreen shrub, Ammopiptanthus mongolicus, in response to drought and cold stresses. BMC Genomics. 2014;15:671. References SCFKMD controls cytokinin signal- ing by regulating the degradation of type-B response regulators. Proc Natl Acad Sci U S A. 2013;110(24):10028–33. 59. Yang J, Zhang J, Wang Z, Zhu Q, Wang W. Hormonal changes in the grains of rice subjected to water stress during grain filling. Plant Physiol. 2001;127(1):315–23. 37. Yang D-L, Yao J, Mei C-S, Tong X-H, Zeng L-J, Li Q, et al. Plant hormone jasmonate prioritizes defense over growth by interfering with gibberellin signaling cascade. Proc Natl Acad Sci U S A. 2012;109(19):E1192–200. 60. Smith AM, Zeeman SC, Smith SM. Starch degradation. Annu Rev Plant Biol. 2005;56:73–98. 61. Ghiena C, Schulz M, Schnabl H. Starch degradation and distribution of the starch-degrading enzymes in Vicia faba leaves. Plant Physiol. 1993;101(1):73–9. 38. Giulia E, Alessandro B, Mariano D, Andrea B, Benedetto R, Angelo R. Early induction of apple fruitlet abscission is characterized by an increase of both isoprene emission and abscisic acid content. Plant Physiol. 2013;161(4):1952–69. 62. Barrett JE, Nell TA. Irrigation interval and growth retardants affect poinsettia development. Proceed Florida State Horticultural Soc. 1982;95:167–9. 39. Wang Y, Li L, Ye T, Zhao S, Liu Z, Feng Y-Q, et al. Cytokinin antagonizes ABA suppression to seed germination of Arabidopsis by downregulating ABI5 expression. Plant J. 2011;68(2):249–61. 63. Davis TD, Steffens GL, Sankhla N. Triazole plant growth regulators. Hortic Rev. 1988;63:105. 64. Hoagland DR, Arnon DI: The water-culture method for growing plants without soil. Circular California Agricultural Experiment Station,1950;347:2nd edit pp.32 pp. 40. Wang Y, Tao X, Tang X-M, Xiao L, Sun J-l, Yan X-F, et al. Comparative transcriptome analysis of tomato (Solanum lycopersicum) in response to exogenous abscisic acid. BMC Genomics. 2013;14:841. 65. Zhang L, Zhao H, Gan M, Jin Y, Gao X, Chen Q, et al. Application of simultaneous saccharification and fermentation (SSF) from viscosity reducing of raw sweet potato for bioethanol production at laboratory, pilot and industrial scales. Bioresour Technol. 2011;102(6):4573–9. 41. Chandrasekaran U, Xu W, Liu A: Transcriptome profiling identifies ABA mediated regulatory changes towards storage filling in developing seeds of castor bean (Ricinus communis L.). Cell Biosci 2014, 4:33. 66. Wu Y, Messing J. RNA interference-mediated change in protein body morphology and seed opacity through loss of different Zein Proteins1 C W OA. Plant Physiol. 2010;153(1):337–47. 42. Dugas DV, Monaco MK, Olsen A, Klein RR, Kumari S, Ware D, et al. References 1. Ge L, Wang P, Mou H. Study on saccharification techniques of seaweed wastes for the transformation of ethanol. Renew Energ. 2011;36(1):84–9. 1. Ge L, Wang P, Mou H. Study on saccharification techniques of seaweed wastes for the transformation of ethanol. Renew Energ. 2011;36(1):84–9. 30. Tao X, Fang Y, Xiao Y, Jin YL, Ma XR, Zhao Y, et al. Comparative transcriptome analysis to investigate the high starch accumulation of duckweed (Landoltia punctata) under nutrient starvation. Biotechnol Biofuels. 2013;6(1):72. 2. Crutzen PJ, Mosier AR, Smith KA, Winiwarter W. N2O release from agro-biofuel production negates global warming reduction by replacing fossil fuels. Atmos Chem Phys. 2008;8(2):389–95. 31. Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26(1):139–40. 32. Guan C, Wang X, Feng J, Hong S, Liang Y, Ren B, et al. Cytokinin antagonizes abscisic acid-mediated inhibition of cotyledon greening by promoting the degradation of abscisic acid insensitive5 protein in Arabidopsis. Plant Physiol. 2014;164(3):1515–26. 5. Ge X, Zhang N, Phillips GC, Xu J. Growing Lemna minor in agricultural wastewater and converting the duckweed biomass to ethanol. Bioresour Technol. 2012;124:485–8. Liu et al. Biotechnology for Biofuels (2015) 8:64 Page 12 of 12 33. Ramireddy E, Chang L, Schmulling T. Cytokinin as a mediator for regulating root system architecture in response to environmental cues. Plant Signal Behav. 2014;9:e27771–1. 56. Mares DJ, Marschner H, Krauss A. Effect of gibberellic-acid on growth and carbohydrate-metabolism of developing tubers of potato (solanum-tuberosum). Physiol Plant. 1981;52(2):267–74. 57. Kaur S, Gupta AK, Kaur N. Gibberellin A3 reverses the effect of salt stress in chickpea (Cicer arietinum L.) seedlings by enhancing amylase activity and mobilization of starch in cotyledons. Plant Growth Regul. 1998;26(2):85–90. 34. Reguera M, Peleg Z, Abdel-Tawab YM, Tumimbang EB, Delatorre CA, Blumwald E. Stress-induced Cytokinin synthesis increases drought tolerance through the coordinated regulation of carbon and nitrogen assimilation in rice. Plant Physiol. 2013;163(4):1609–22. 58. Rentzsch S, Podzimska D, Voegele A, Imbeck M, Mueller K, Linkies A, et al. Dose- and tissue-specific interaction of monoterpenes with the gibberellin-mediated release of potato tuber bud dormancy, sprout growth and induction of alpha-amylases and beta-amylases. Planta. 2012;235(1):137–51. 35. Bastias A, Yanez M, Osorio S, Arbona V, Gomez-Cadenas A, Fernie AR, et al. The transcription factor AREB1 regulates primary metabolic pathways in to- mato fruits. J Exp Bot. 2014;65(9):2351–63. 36. Kim HJ, Chiang Y-H, Kieber JJ, Schaller GE. References Functional annotation of the transcriptome of Sorghum bicolor in response to osmotic stress and abscisic acid. BMC Genomics. 2011;12:514. 67. Ji X, Gai Y, Zheng C, Mu Z. Comparative proteomic analysis provides new insights into mulberry dwarf responses in mulberry (Morus alba L.). Proteomics. 2009;23:5328–39. 43. Li J, Wu Z, Cui L, Zhang T, Guo Q, Xu J, et al. Transcriptome comparison of global distinctive features between pollination and parthenocarpic fruit set reveals transcriptional phytohormone cross-talk in cucumber (Cucumis sativus L.). Plant Cell Physiol. 2014;55(7):1325–42. 68. Tárrago JF, Nicolás G. Starch degradation in the cotyledons of germinating lentils. Plant Physiol. 1976;58(5):618–21. 44. Sakai A, Yashiro K, Kawano S, Kuroiwa T. Amyloplast formation in cultured tobacco cells; effects of plant hormones on multiplication, size, and starch content. Plant Cell Rep. 1996;15(8):601–5. 69. Nakamura Y, Yuki K, Park S-Y, Ohya T. Carbohydrate metabolism in the developing endosperm of rice grains. Plant Cell Physiol. 1989;30(6):833–9. 70. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol. 2011;29(7):644–52. 45. Fletcher RA, McCullag D. Cytokinin-induced chlorophyll formation in cucumber cotyledons. Planta. 1971;101(1):88. 46. Yang J, Peng S, Visperas RM, Sanico AL, Zhu Q, Gu S. Grain filling pattern and cytokinin content in the grains and roots of rice plants. Plant Growth Regul. 2000;30(3):261–70. 71. Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10(3):R25. 47. To JPC, Kieber JJ. Cytokinin signaling: two-components and more. Trends Plant Sci. 2008;13(2):85–92. 72. Conesa A, Götz S. Blast2GO: A comprehensive suite for functional analysis in plant genomics. Int J Plant Genomics. 2008;2008:1–13. 48. Werner T, Schmuelling T. Cytokinin action in plant development. Curr Opin Plant Biol. 2009;12(5):527–38. 73. Conesa A, Götz S, García-Gómez JM, Terol J, Talón M, Robles M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics. 2005;21(18):3674–6. 73. Conesa A, Götz S, García-Gómez JM, Terol J, Talón M, Robles M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics. 2005;21(18):3674–6. 49. Pilkington SM, Montefiori M, Galer AL, Emery RJN, Allan AC, Jameson PE. Endogenous cytokinin in developing kiwifruit is implicated in maintaining fruit flesh chlorophyll levels. Ann Bot. 2013;112(1):57–68. 74. Oliveros JC. VENNY: An interactive tool for comparing lists with Venn Diagrams. 2007. 50. References Akihiro T, Mizuno K, Fujimura T. Gene expression of ADP-glucose pyrophosphorylase and starch contents in rice cultured cells are cooperatively regulated by sucrose and ABA. Plant Cell Physiol. 2005;46(6):937–46. 51. Gomez-Cadenas A, Zentella R, Walker-Simmons MK, Ho THD. Gibberellin/ abscisic acid antagonism in barley aleurone cells: Site of action of the protein kinase PKABA1 in relation to gibberellin signaling molecules. Plant Cell. 2001;13(3):667–79. Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color ﬁgure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color ﬁgure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit Submit your next manuscript to BioMed Central and take full advantage of: Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color ﬁgure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit 52. Hubbard KE, Nishimura N, Hitomi K, Getzoff ED, Schroeder JI. Early abscisic acid signal transduction mechanisms: newly discovered components and newly emerging questions. Gene Dev. 2010;24(16):1695–708. • Convenient online submission 53. Park S-Y, Fung P, Nishimura N, Jensen DR, Fujii H, Zhao Y, et al. Abscisic acid inhibits type 2C protein phosphatases via the PYR/PYL family of START proteins. Science. 2009;324(5930):1068–71. • Thorough peer review 54. Umezawa T, Nakashima K, Miyakawa T, Kuromori T, Tanokura M, Shinozaki K, et al. Molecular basis of the core regulatory network in ABA responses: sensing. Signaling Trans Plant Cell Physiol. 2010;51(11):1821–39. 55. Rook F, Corke F, Card R, Munz G, Smith C, Bevan MW. Impaired sucrose-induction mutants reveal the modulation of sugar-induced starch biosynthetic gene expression by abscisic acid signalling. Plant J. 2001;26(4):421–33. Submit your manuscript at www.biomedcentral.com/submit
https://openalex.org/W2170643888	https://www.scielo.br/j/rbz/a/JtkYsVxh7TYLv7GTqSvCWFg/?lang=pt&format=pdf	Portuguese	null	Efeito da ausência de trato dos bezerros de rebanhos leiteiros aos domingos sobre seus desempenhos até os seis meses de idade	Revista Brasileira de Zootecnia	2,004	cc-by	3,196	1 Pesquisador da Embrapa Gado de Leite, Campo Experimental Santa Mônica, Barão de Juparanã, Valença, RJ. CEP: 27610-000. Bolsista do CNPq. E.mail: oriel@cnpgl.embrapa.br 2 Técnico de Nível Superior da Embrapa Gado de Leite, Campo Experimental Santa Mônica, Barão de Juparanã, Valença, RJ. CEP: 27610-000. Bolsista do CNPq. E.mail: marcomj@cnpgl.embrapa.br 3 Graduando em Zootecnia pela UFRRJ e Bolsista de Iniciação Científica do CNPq. 4 Pesquisadora da Pesagro-RJ, Estação Experimental de Itaguaí, Seropédica, RJ. CEP: 23850-000. Bolsista do CNPq. E.mail: eei@domain.com.br Efeito da Ausência de Trato dos Bezerros de Rebanhos Leiteiros aos Domingos sobre seus Desempenhos até os Seis Meses de Idade Oriel Fajardo de Campos1, Marcos Macedo Junqueira2, Daniel de Noronha Figueiredo Vieira da Cunha3, Rosane Scatamburlo Lizieire4 Efeito da Ausência de Trato dos Bezerros de Rebanhos Leiteiros aos D seus Desempenhos até os Seis Meses de Idade sência de Trato dos Bezerros de Rebanhos Leiteiros aos Domingos sobre seus Desempenhos até os Seis Meses de Idade RESUMO - Vinte quatro bezerros mestiços Holandês x Zebu foram usados para comparar os seguintes tratamentos experimentais: 1) presença do tratador todos os dias da semana; 2) ausência do tratador aos domingos, com compensação na quantidade de leite oferecida (seis litros de leite integral aos sábados e às segundas-feiras); e 3) ausência do tratador aos domingos, sem compensação na quantidade de leite oferecida. Os bezerros receberam quatro litros de leite integral/animal/dia até as oito semanas de idade, quando foram abruptamente desaleitados. A partir da segunda semana de vida, receberam concentrado limitado em 2 kg/animal/dia. Conclui-se que: a ausência do tratador aos domingos não afetou o peso vivo (72,3 vs 71,7 kg) e o ganho de peso médio diário (479 vs 451 g/animal/dia) aos seis meses de idade e o consumo médio de concentrado durante as dez primeiras semanas de vida (784 vs 732 g/animal/dia); a compensação na quantidade oferecida de leite resultou em animais mais pesados ao desaleitamento (63,0 vs 58,2 kg), mas não aos seis meses de idade (114,3 vs 113,8 kg). Palavras-chave: bezerros, gado de leite, manejo, quantidade de leite Effect of the Absence of Dairy Calves Management on Sundays on theirs Performance up to Six Months of Age ABSTRACT - Twenty-four Holstein x Zebu crossbred calves were used to compare the following experimental treatments: 1) calves management every day of the week, 2) absence of calves management on Sundays, with the compensation of the amount of milk fed (6 kg of whole milk given on Saturdays and on Mondays), and 3) absence of calves management on Sundays without the compensation of the amount of milk fed. Calves were fed 4 kg of whole milk/animal/day (except for treatment 2) up to 8 weeks of age when they were abruptly weaned. Starter was available to calves since the second week of age and limited to 2 kg/animal/day. It was concluded that: (a) the absence of calves management on Sundays did not affect body weight (72.3 vs 71.7 kg) and average daily weight gains (479 vs 451 g/animal/day) at six months of age, and average starter intake during the first ten weeks of age (784 vs 732 g/animal/day); (b) the compensation of the amount of milk fed resulted in heavier calves at weaning (63.0 vs 58.2 kg), but not at six month of age (114.3 vs 113.8 kg) Key Words: amount of milk, calves, dairy cattle, management R. Bras. Zootec., v.33, n.2, p.407-411, 2004 R. Bras. Zootec., v.33, n.2, p.407-411, 2004 Material e Métodos O presente experimento foi conduzido no Campo Experimental Santa Mônica, da Embrapa Gado de Leite, localizado em Valença, RJ, no período de 27/04/2001 a 04/02/2002. Os animais foram pesados ao nascer e aos dois primeiros dias de vida, considerando-se como peso inicial a média dessas três pesagens. Do mesmo modo, os pesos médios desses animais aos 56, 70 e 180 dias de idade foram obtidos de três pesagens consecutivas nessas datas. Além disso, os animais foram pesados a cada sete dias, sendo que todas as pesagens mencionadas iniciaram-se às 7h30, antes da alimentação matinal. Foram utilizados 24 bezerros desde o nascimento até os 180 dias de idade, oito por tratamento experi- mental, blocados por sexo e peso ao nascer. Os bezerros foram mantidos em abrigos individuais no campo até os 70 dias de idade, distanciados entre si o suficiente para evitar o contato entre eles. Dos 70 aos 180 dias de idade, os animais eram mantidos juntos em piquetes de capim-estrela dotados de cochos, bebedouros e sombra. Os consumos diários de leite e de concentrado inicial foram estabelecidos, para cada animal, me- diante diferença entre as quantidades de matéria natural oferecidas e as sobras. Os bezerros permaneceram com suas mães du- rante as primeiras 24 horas de vida, tendo os tratadores induzido os bezerros a mamarem o colostro mais cedo, quando possível nas primeiras duas horas após o nascimento. Colostro fresco e integral (sem dilui- ção), de preferência de vacas multíparas, foi forne- cido até o terceiro dia de idade, na quantidade de 4 litros/animal/dia, em duas refeições. Do quarto ao décimo dia de idade, os animais receberam o leite em duas refeições diárias. A partir daí, a dieta líquida de 4 litros/animal/dia foi fornecida em uma só refeição pela manhã. Após o fornecimento da dieta líquida, não foi disponibilizada água aos bezerros por 30 minutos. O desaleitamento se deu, de forma abrupta, aos 56 dias de idade dos animais. Diariamente, foram anotadas as consistências das fezes de cada bezerro, registrando-se 1 para fezes normais e 2 para diarréia. O controle de medi- cações foi realizado em um caderno, registrando-se o número do animal, a data da medicação, o diagnóstico e a medicação realizada. O delineamento estatístico adotado para ganho de peso e consumo de concentrado foi o de blocos casualizados, com três tratamentos e oito repetições por tratamento. Introdução passar os domingos sem a visita do tratador e, em conseqüência, sem a dieta líquida. O fornecimento de concentrado poderia ser compensado pela colocação de maior quantidade no sábado e na segunda-feira. Fica a questão sobre possíveis efeitos adversos deste manejo sobre o desempenho dos animais. As despesas com mão-de-obra representam parcela significativa no custo da criação de bezerros em propriedades leiteiras. Nas indicações atuais de manejo, recomenda-se que os bezerros sejam obser- vados e alimentados todos os dias da semana. Isto faz com que empregados sejam escalados para tratarem dos bezerros aos domingos, o que resulta em folgas ou em pagamentos de horas extras em dobro em relação àquelas pagas em dias normais da semana. Seria extremamente vantajoso se os bezerros pudessem Com base em revisão bibliográfica de artigos publicados entre as décadas de 50 e 70, Appleman et al. (1975) concluíram que esta prática, quando adotada a partir da segunda semana de idade, não traz des- vantagens. Há registros, no entanto, de que os ganhos de peso iniciais de animais da raça Holandesa se CAMPOS et al. 408 mostraram menores (Boucque et al., 1971), embora por volta da 12a à 16a semana os pesos dos bezerros passem a ser iguais. Wood et al. (1971), também utilizando animais da raça Holandesa, constataram maior deposição de carne, gordura e ossos em bezer- ros que não sofreram jejum, mas os ganhos não diferiram estatisticamente. Os autores autores tam- bém verificaram maior peso dos fígados dos animais que passaram por jejum de 24 horas, explicado pelo maior estoque de glicogênio nesse órgão. ausência de trato aos domingos, sem compensação na quantidade de leite. Os animais do segundo tratamento receberam, nos sábados e às segundas-feiras, seis litros de dieta líquida para compensar os quatro litros de leite não recebidos no domingo. Já os animais do terceiro tratamento não tiveram esta compensação, reduzindo a quantidade total de leite gasta em sua criação. Durante a fase nos abrigos individuais, os animais dos dois tratamentos que não recebiam trato aos domingos eram alocados em área distante e sem comunicação com aqueles do tratamento controle. O objetivo deste trabalho foi comparar o sistema tradicional em que se considerou a presença do tratador alimentando bezerros de rebanhos leiteiros, até os seis meses de idade todos os dias da semana, com a ausência de trato aos domingos, compensando-se ou não a quantidade de leite não fornecida nesse dia. Introdução Os bezerros receberam, a partir da segunda semana de idade, à vontade, concentrado comercial inicial para bezerros, com 87% de matéria seca (mínima), 16% de proteína bruta (mínima), 6,7% de matéria fibrosa (máximo), 1,5% de cálcio (máximo) e 0,4% de fósforo (mínimo), sendo estas informações do fabricante. Aos sábados, foi colocada, à disposi- ção, maior quantidade de concentrado para suprir a ausência de trato aos domingos. Material e Métodos A variável peso vivo foi analisada como parcelas subdivididas, tendo-se os tratamentos experimentais como parcelas e as semanas de idade como subparcelas. A ocorrência de diarréias foi analisada pelo método qui-quadrado, adotando-se, para todas as análises estatísticas, os procedimentos descritos por Gomes (1990). Os tratamentos experimentais foram: trato todos os dias da semana (controle); ausência de trato aos domingos, com compensação na quantidade de leite; R. Bras. Zootec., v.33, n.2, p.407-411, 2004 409 Efeito da Ausência de Trato dos Bezerros de Rebanhos Leiteiros aos Domingos sobre seus... Material e Métodos Efeito da Ausência de Trato dos Bezerros de Rebanhos Leiteiros aos Domingos sobre otec., v.33, n.2, p.407-411, 2004 Tratamentos experimentais Contraste 1 Experimental treatments Contrast Ausência de trato aos domingos, Ausência de trato aos domingos, sem Erro- A vs B B vs C Variáveis Trato todos os dias com compensação na quantidade compensação na quantidade de leite (C) padrão Variables da semana (A) de leite (B) No calves management on Sundays, Standard Calves management No calves management on without compensation of the amount of error every day (A) Sundays, with compensation of the milk fed (C) amount of milk fed (B) Ganho médio de peso (g/animal/dia) Daily weight gain (g/animal/day) 2 a 8 semanas 570 540 491 26 0,464 0,250 2 to 8 weeks of age 8 a 10 semanas 570 617 618 31 0,358 0,939 8 to 10 weeks of age 2 a 10 semanas 572 557 520 21 0,671 0,239 2 to 10 weeks of age 2 a 26 semanas 479 451 460 39 0,305 0,561 2 to 26 weeks of age Consumo médio de concentrado (g de matéria natural/animal/dia) Avarage starter intake (g, as fed/animal/day) 2 a 8 semanas 472 447 490 40 0,598 0,492 2 to 8 weeks of age 8 a 10 semanas 1.876 1730 1625 88 0,144 0,555 8 to 10 weeks of age 2 a 10 semanas 784 732 743 44 0,281 0,892 2 to 10 weeks of age Tabela 1 - Efeito do “trato” aos domingos e da compensação da quantidade de leite oferecida durante a fase de aleitamento sobre o ganho de peso (g/animal/dia) e o consumo de concentrado (g de matéria natural/animal/dia) por bezerros mestiços Holandês x Zebu Table 1 - Effect of calves management on Sundays and the amount of milk fed during the liquid feeding period on body weight gain (g/animal/day) and starter intake (g, as fed/animal/ day) of crossbred Holstein-Zebu calves 1 Teste de Scheffé (Scheffé interval). 410 CAMPOS et al. Resultados e Discussão cujos resultados são mostrados na Tabela 2, revelou que os animais alimentados com menor quantidade de leite apresentaram pesos significativamente menores que aqueles submetidos aos tratamentos controle ou com compensação no sábado e na segunda-feira, da terceira à décima semana; contudo, o peso vivo aos seis meses de idade foi semelhante para os três tratamentos. Este mesmo resultado foi verificado por Boucque et al. (1971). Do ponto de vista prático, tal resultado sugere que, para fazendas com bom manejo, alimentação e mão-de-obra, pode-se considerar a possibilidade de não compensar o leite que os bezer- ros deixaram de beber no domingo, uma vez que isto representaria redução de 10 a 15% na quantidade de leite gasta na alimentação desses animais. Em pro- priedades onde o manejo, a alimentação e a mão-de- obra apresentam problemas, melhor seria compensar o leite não oferecido no domingo, uma vez que os animais que não receberam esta compensação se mostraram mais leves, em princípio mais susceptíveis a doenças. Observa-se, na Tabela 1, que não houve diferença significativa (P>0,05) entre os tratamentos experi- mentais para ganho médio diário de peso e consumo médio diário de concentrado, nos períodos avaliados, à semelhança dos resultados obtidos por Appleman et al. (1975) e Wood et al. (1971). Desse modo, a adoção desta prática poderá resultar em redução sensível no gasto com mão-de-obra, prevendo-se impacto benéfico no custo de produção de leite. Por outro lado, a ausência de trato dos bezerros aos domingos exige algumas mudanças em paralelo, a saber: o local onde são criados os bezerros em aleitamento deve ser, preferencialmente, isolado de outros locais onde pessoas circulam aos domingos, uma vez que a presença delas pode estressar os animais, que estariam já acostumados àquela rotina, à espera da refeição líquida; maior atenção deve ser dada aos animais nos outros dias da semana, em especial na segunda-feira, para verificar se eles estão bem após o jejum imposto no dia anterior; as aplicações de remédios em animais doentes devem prever este novo manejo. A ocorrência de diarréias independeu do trata- mento experimental (Tabela 3), não sendo registrados problemas sérios mesmo naqueles animais que rece- biam mais leite aos sábados e às segundas-feiras. Semelhantemente, não foram observadas diferenças entre os dias sob medicação. Médias com sobrescritos diferentes, na coluna, diferem entre si (P<0,05) pelo teste Tukey. Means, within a column, with different superscripts are different (P<.05) by Tukey test. Conclusões WOOD, A.S.; BAYLEY, H.F.; MACLEOD, G. K. Evaluation of imposing weekly fast on calves receiving a milk replacer diet once and twice daily: protein and energy utilization. Journal of Dairy Science, v.54, n.3, p.405- 412, 1971. A ausência de trato dos bezerros de rebanhos leiteiros, um dia da semana, não influenciou negativa- mente no peso dos bezerros aos seis meses de idade, no consumo de concentrado e na ocorrência de diarréias dos animais até os 70 dias de idade. A compensação do leite não fornecido no dia de folga do tratador resultou em maiores pesos dos bezerros ao desaleitamento, mas não aos seis meses de idade. Resultados e Discussão 411 Efeito da Ausência de Trato dos Bezerros de Rebanhos Leiteiros aos Domingos sobre seus... Tabela 3 - Efeito do “trato” aos domingos e da compensação da quantidade de leite oferecida durante a fase de aleitamento sobre a ocorrência de diarréias em bezerros mestiços Holandês x Zebu Table 3 - Effect of calveskeeper presence on Sundays and the amount of milk fed during the liquid feeding period on crossbred Holstein x Zebu calves diarrhea occurrence Tabela 3 - Efeito do “trato” aos domingos e da compensação da quantidade de leite oferecida durante a fase de aleitamento sobre a ocorrência de diarréias em bezerros mestiços Holandês x Zebu Table 3 - Effect of calveskeeper presence on Sundays and the amount of milk fed during the liquid feeding period on crossbred Holstein x Zebu calves diarrhea occurrence Número de dias Totais Tratamentos experimentais Number of days Totals Experimental treatments Fezes normais Diarréia Normal feces Diarrhea Trato todos os dias da semana 542 26 568 Calves management every day Ausência de trato aos domingos 528 40 568 com compensação na quantidade de leite No calves management on Sundays, with compensation of the amount of milk fed Ausência de trato aos 539 29 568 domingos, sem compensação na quantidade de leite No calves management on Sundays, without compensation of the amount of milk fed Total 1.609 95 1.704 Total during the liquid feeding period on crossbred Holstein x Zebu calves diarrhea occurrence Qui-quadrado = 3,63, aceitando a hipótese de independência entre tratamentos experimen- tais e ocorrência de diarréias. Chi-square = 3.63, accepting the hypothesis of independence between experimental treatments and diarrhea occurrence. GOMES, F.P. Curso de estatística experimental. 13.ed. São Paulo: Nobel, 1990. 467p. WOOD, A.S.; BAYLEY, H.F.; MACLEOD, G. K. Evaluation of imposing weekly fast on calves receiving a milk replacer diet once and twice daily: protein and energy utilization. Journal of Dairy Science, v.54, n.3, p.405- 412, 1971. GOMES, F.P. Curso de estatística experimental. 13.ed. São Paulo: Nobel, 1990. 467p. GOMES, F.P. Curso de estatística experimental. 13.ed. São Paulo: Nobel, 1990. 467p. RR. Bras. Zootec., v.33, n.2, p.407-411, 2004 Resultados e Discussão A análise dos pesos vivos dos bezerros a cada semana, durante as primeiras dez semanas de vida, Tratamentos experimentais Semanas de idade Experimental treatments Weeks of age 0 1 2 3 4 5 6 7 8 9 10 Trato todos os dias da semana 34,0a 36,3a 39,2 a 42,1 a 45,0 a 49,4 a 54,2 a 59,7 a 64,3 a 70,6 a 72,3 a Calves management every day (A) Ausência de trato aos domingos, 34,6 a 36,6 a 38,5 a 41,2 a 44,6 a 48,7 a 53,0 a 58,6 a 63,0 a 68,9 a 71,7 a com compensação na quantidade de leite No calves management on Sundays, with compensation of the amount of milk fed (B) Ausência de trato aos domingos, sem 33,9 a 34,1 a 36,5 a 38,6 b 41,0 b 44,7 b 49,8 b 53,1 b 58,2 b 63,5 b 66,9 b compensação na quantidade de leite No calves management on Sundays, without compensation of the amount of milk fed (C) Tabela 2 - Efeito do “trato” aos domingos e da compensação da quantidade de leite oferecida durante a fase de aleitamento sobre o peso vivo (kg) de bezerros mestiços Holandês x Zebu Table 2 - Effect of calves management on Sundays and the amount of milk fed during the liquid feeding period on crossbred Holstein x Zebu calves body weight (kg) Médias com sobrescritos diferentes, na coluna, diferem entre si (P<0,05) pelo teste Tukey. Means, within a column, with different superscripts are different (P<.05) by Tukey test. Tabela 2 - Efeito do “trato” aos domingos e da compensação da quantidade de leite oferecida durante a fase de aleitamento sobre o peso vivo (kg) de bezerros mestiços Holandês x Zebu Table 2 - Effect of calves management on Sundays and the amount of milk fed during the liquid feeding period on crossbred Holstein x Zebu calves body weight (kg) Médias com sobrescritos diferentes, na coluna, diferem entre si (P<0,05) pelo teste Tukey. Means, within a column, with different superscripts are different (P<.05) by Tukey test. Médias com sobrescritos diferentes, na coluna, diferem entre si (P<0,05) pelo teste Tukey. Means, within a column, with different superscripts are different (P<.05) by Tukey test. R. Bras. Zootec., v.33, n.2, p.407-411, 2004 Efeito da Ausência de Trato dos Bezerros de Rebanhos Leiteiros aos Domingos sobre seus... Efeito da Ausência de Trato dos Bezerros de Rebanhos Leiteiros aos Domingos sobre seus... Literatura Citada APPLEMAN, R.D. Breeding, housing and feeding management. Journal of Dairy Science, v. 58, n.3, p.447-464, 1975. BOUCQUE, C.H.; BUYSSE, F.X.; COTTYN, B.G. The effect of giving 11 or 14 feeds of milk substitute per week to early-weaned calves. Animal Production, v.13, n.4, p.613- 618, 1971. BOUCQUE, C.H.; BUYSSE, F.X.; COTTYN, B.G. The effect of giving 11 or 14 feeds of milk substitute per week to early-weaned calves. Animal Production, v.13, n.4, p.613- 618, 1971. Recebido em: 15/01/03 Aceito em: 27/08/03 Recebido em: 15/01/03 Aceito em: 27/08/03 RR. Bras. Zootec., v.33, n.2, p.407-411, 2004
https://openalex.org/W4387399982	https://jelectrochem.xmu.edu.cn/cgi/viewcontent.cgi?article=3076&context=journal	Chinese	null	Application of Taguchi Method to Phosphate Coating	Deleted Journal	1,996	cc-by	3,004	Journal of Electrochemistry Journal of Electrochemistry Volume 2 Issue 2 Application of Taguchi Method to Phosphate Coating Application of Taguchi Method to Phosphate Coating Zidong Wei Zidong Wei Recommended Citation Recommended Citation Zidong Wei. Application of Taguchi Method to Phosphate Coating[J]. Journal of Electrochemistry, 1996 , 2(2): Article 16. DOI: 10.61558/2993-074X.3076 Available at: https://jelectrochem.xmu.edu.cn/journal/vol2/iss2/16 Recommended Citation Recommended Citation Zidong Wei. Application of Taguchi Method to Phosphate Coating[J]. Journal of Electrochemistry, 1996 , 2(2): Article 16. DOI: 10.61558/2993-074X.3076 Available at: https://jelectrochem.xmu.edu.cn/journal/vol2/iss2/16 This Article is brought to you for free and open access by Journal of Electrochemistry. It has been accepted for inclusion in Journal of Electrochemistry by an authorized editor of Journal of Electrochemistry. 电化学 EL ECTROCHEM ISTRY 第2 卷　第2 期 1996 年5 月 Vo l. 2　No. 2 M ay 1996 磷化过程的T aguch i 设计 ① 郭鹤桐　(天津大学应用化学系, 天津　300072) 魏子栋3 　　　　　　　　　郭鹤桐 (山东工业大学化学工程系, 济南　250061) 　　(天津大学应用化学系, 天津　300072) 摘要　通过对磷化液配方及磷化工艺的改进, 解决了磷化液沉淀多, 不稳定及磷化膜微观结构差的问题. 针对钢铁磷化过程中出现的磷化膜质量与磷化面积之间的非线性关系, 应用Taguchi 方法, 对磷化过程进行了优化, 实现了磷化膜质量与磷化件面积之间的线性关系, 磷化液连续循环使用的性能也得到根本的改进. 关键词　磷化, Taguchi 方法磷化处理是金属表面转化处理工艺的一种. 它可以改变金属表面原有的性质而提供新的物理特性或物理化学特性. 在许多化学表面处理中, 磷化处理占有重要的地位. 磷化膜的最大用途是作为油漆底层, 增强油漆与金属基体的结合能力以及提高漆膜的耐蚀能力. 此外, 还可以作为油脂或其它防腐材料的底层; 零件在有油或无油存在下接触面摩擦运动的润滑底层, 暂时或短期的防锈层; 塑料或橡胶与金属粘接的底层等. 磷化还在拔丝、拔管、冷挤压加工等工业中有着广泛的应用. 可以说, 正是由于磷化工艺在冷加工工业中的应用, 才使这一工业过程在商业上获得了经济效益 [11 ]. 磷化的工业应用已有80 年的历史. 但目前磷化工艺还存在着磷化液沉渣多, 性质不稳定及难维护的问题, 特别是对磷化后处理有着重要影响的磷化膜微观结构形态还没有引起国内同行的注意. 本研究工作表明, 从传统的磷化工艺中获得的磷化膜呈片状结构, 这对漆的吸附以及吸附强度都是不理想的. 同时, 在钢铁件上的磷化膜常呈不均匀性, 严重时肉眼就可以观察到. 基于这些问题, 本文首先对磷化液的组成进行了改进, 同时应用Taguchi 方法, 对磷化过程进行了优化设计, 最后获得了一个理想的磷化液组成和磷化工艺, 较好地解决了前面提到的问题. Sm = ∑ n i= 1 y i 2 n 　V e= ∑ n i= 1 y i- yθ 2 (n- 1) 1　Taguchi 方法方法是由 aguc 方法 Taguchi 方法是由Genichi Taguchi 博士于本世纪40 年代末建立的, 并在日本工业界得到广泛应用, 大约在15 年前, 这种方法传入美国 [2 ], 成功地应用在集成电路的优化产生, 波峰焊多参数过程的优化设计. 在我国, 尚未见到应用Taguchi 方法的报道. 1. 1　Taguch i 统计函数产品的质量总是呈正态分布, 在Taguchi 方法统计法中, 不仅关心质量的标准值, 还注意 ①本文收到, 收到修改稿偏差的大小. Taguchi 提出的信噪比S ö N (Signal to no ise ratio) 是一个把产品标准值与偏差合为一体的参数, 其定义为: 　S ö N = 20 log (yθöSD ) (1) 其中yθ 和SD 分别为平均值与标准偏差. 根据实验类型的不同, Taguchi 把S ö N 分成三种情况: 越大越好(L B ) , 正常最好(N B ) 和越小越好(SB ). 在SB 情况下, 由于理想输出的平均值趋近于零, 因而方程(1) 又可表示为　S ö N SB = - 20 log (SD ) (2) 其中SD = (1ön)∑ n i= 1 y 2 i 1ö2 (3) 根据质量特性的互反性, SB 问题可以转化为LB 问题, 其目标函数S ö N LB 可表达为　S ö N LB = - 10 log (1ön)∑ n i= 1 (1öy 2 i ) (4) 在正常最好问题中, 理想输出值等于某一目标值, 平均值期望的平方E (yθ) 2 等于(Sm - V e) ön 　S ö N N B = 10 log ( (1ön) (Sm - V e) ö V e) (5) 其中平均值变量Sm 和样品方差V e 分别为　Sm = ∑ n i= 1 y i 2 n (6) 　V e= ∑ n i= 1 y i- yθ 2 (n- 1) (7) 由于以上三种问题的目标值均为一个固定的数值, 通常称其为静态特性. 在动态情况下, 理想的输出(y ) 应为某显著因素(M ) 的函数. y = ΒM (8) Β为相关因数. 此时, Taguchi 建议的目标函数为　S ö N Β= 10 log ( (1ör) (S Β- V e) ö V e) (9) 其中(S Β- V e) ör 为期望值的平方[E (Β) ] 2, S Β 为Β平方和, 即　S Β= ∑ n i= 1 M iy i 2 ∑ n i= 1M 2 i (10) 　r = ∑ n i= 1M 2 i (11) 1. 2　Taguch i 方法实验设计把影响一个工艺过程的因素分为控制因素显著因素和干扰因素 · 3 0 2 · 第2 期　　　　　　　　　魏子栋等: 磷化过程的Taguchi 设计魏子栋等: 磷化过程的Taguchi 设计第2 期第2 期 · 3 0 2 · · 3 0 2 · (1) S ö N = 20 log (yθöSD ) (1) 其中yθ 和SD 分别为平均值与标准偏差. 根据实验类型的不同, Taguchi 把S ö N 分成三种情况: 越大越好(L B ) , 正常最好(N B ) 和越小越好(SB ). 其中SD = (1ön)∑ n i= 1 y 2 i 电　化　学 1996 年 ·4 0 2 它的输出特性之间呈线性关系. 磷化过程磷化时间对以磷化膜厚度为输出响应时即为一个显著因素. 在实验过程中难以控制的因素称为干扰因素. 将干扰因素并入参数设计是很关键的. 如图 2, 控制因素在高水平A 2 时对干扰因素N 变化的灵敏度大于低水平A 1, 说明控制因素在A 1 下具有更为稳定的输出特性. 1　Taguchi 方法方法是由在SB 情况下, 由于理想输出的平均值趋近于零, 因而方程(1) 又可表示为　S ö N SB = - 20 log (SD ) (2) 其中SD = (1ön)∑ n i= 1 y 2 i 1ö2 (3) 根据质量特性的互反性, SB 问题可以转化为LB 问题, 其目标函数S ö N LB 可表达为　S ö N LB = - 10 log (1ön)∑ n i= 1 (1öy 2 i ) (4) 在正常最好问题中, 理想输出值等于某一目标值, 平均值期望的平方E (yθ) 2 等于(Sm - V e) ön 　S ö N N B = 10 log ( (1ön) (Sm - V e) ö V e) (5) 其中平均值变量Sm 和样品方差V e 分别为　Sm = ∑ n i= 1 y i 2 n (6) 　V e= ∑ n i= 1 y i- yθ 2 (n- 1) (7) 由于以上三种问题的目标值均为一个固定的数值, 通常称其为静态特性. 在动态情况下, 理想的输出(y ) 应为某显著因素(M ) 的函数. y = ΒM (8) Β为相关因数. 此时, Taguchi 建议的目标函数为　S ö N Β= 10 log ( (1ör) (S Β- V e) ö V e) (9) 其中(S Β- V e) ör 为期望值的平方[E (Β) ] 2, S Β 为Β平方和, 即　S Β= ∑ n i= 1 M iy i 2 ∑ n i= 1M 2 i (10) 　r = ∑ n i= 1M 2 i (11) 1. 2　Taguch i 方法实验设计 Taguchi 把影响一个工艺过程的因素分为: 控制因素, 显著因素和干扰因素. 影响偏差的因素称为控制因素, 如图1. 控制因素与输出特性之间呈非线性关系. 当控制因素位于较高的水平(A 2) 时比位于较低水平(A 1) 有着更小的偏差. 因而, 控制因素的鉴别和水平确定就成为参数设计中最重要的任务之一. 不影响偏差的因素被称为显著因素. 它被用来将平均值调整到指定的目标值. 显著因素与 S ö N LB = - 10 log (1ön)∑ n i= 1 (1öy 2 i ) V e) ön S ö N N B = 10 log ( (1ön) (Sm - V e) ö V e) 其中平均值变量Sm 和样品方差V e 分别为 (7) (8) (9) (10) (11) 1. 2　Taguch i 方法实验设计 Taguchi 把影响一个工艺过程的因素分为: 控制因素, 显著因素和干扰因素. 影响偏差的因素称为控制因素, 如图1. 控制因素与输出特性之间呈非线性关系. 当控制因素位于较高的水平(A 2) 时比位于较低水平(A 1) 有着更小的偏差. 因而, 控制因素的鉴别和水平确定就成为参数设计中最重要的任务之一. 水平确定就成为参数设计中最重要的任务之一不影响偏差的因素被称为显著因素. 它被用来将平均值调整到指定的目标值. 显著因素与不影响偏差的因素被称为显著因素. 它被用来将平均值调整到指定的它的输出特性之间呈线性关系. 磷化过程磷化时间对以磷化膜厚度为输出响应时即为一个显著因素. 6　磷化过程的Taguchi 设计控制因素与信号因素的水平如表1 所示. 表1　实验L 18 (21× 37) 的控制因素与信号因素水平设置 Tab. 1　Facto rs and levels fo r A rray L 18 (21× 37) 　控制因素水平1 水平2 水平3 A 浸草酸时间 (s) 60 40 B 磷化时间 (m in) 30 20 15 C 磷化温度 (℃) 60 40 50 D W 21 (mo löL ) 0. 015 0. 010 0. 005 E W 22 (mo löL ) 0. 068 0. 047 0. 027 F M n 2+ (mo löL ) 0. 158 0. 140 0. 105 G Zn 2+ (mo löL ) 0. 423 0. 740 0. 265 H H 2PO 2- 4 (mo löL ) 0. 846 0. 740 0. 530 　信号因素水平1 水平2 水平3 M 试片面积 (cm 2) 7. 23 9. 31 11. 13 根据L 18 (2 1× 3 7) 正交表安排控制因素实验, 依公式(7, 8, 9, 10, 11) 计算S ö N Β, 膜重量和磷化试片的面积分别对应于式(8) 中的y 和M , 膜重量通过磷化膜在剥离前后的重量差求取. 计算所得的S ö N Β 和硫酸铜点滴后磷化膜出现粉红色斑点的时间列于表2. 2　Taguchi 方法在磷化过程的应用 2. 1　磷化过程　　除油→清水漂洗→除锈→清水漂洗→浸1% 草酸→清水漂洗→磷化→清水漂洗→热风吹干 2　Taguchi 方法在磷化过程的应用它的输出特性之间呈线性关系. 磷化过程磷化时间对以磷化膜厚度为输出响应时即为一个显著因素. 在实验过程中难以控制的因素称为干扰因素. 将干扰因素并入参数设计是很关键的. 如图 2, 控制因素在高水平A 2 时对干扰因素N 变化的灵敏度大于低水平A 1, 说明控制因素在A 1 下具有更为稳定的输出特性. 在实验过程中难以控制的因素称为干扰因素. 将干扰因素并入参数设计是很关键的. 如图 2, 控制因素在高水平A 2 时对干扰因素N 变化的灵敏度大于低水平A 1, 说明控制因素在A 1 下具有更为稳定的输出特性. 图1　控制因素与输出之间的非线性关系 F ig. 1　The nonlinear relationship betw een contro l facto r (A ) and its output charcteristic 图2　控制因素(A ) 与干扰因素(N ) 相互作用下的输出态性 F ig. 2　The output chacteristic in the p resence of the interaction betw een contro l facto r (A ) and no ise facto r (N ) 图1　控制因素与输出之间的非线性关系 F ig. 1　The nonlinear relationship betw een contro l facto r (A ) and its output charcteristic 图2　控制因素(A ) 与干扰因素(N ) 相互作用下的输出态性 F ig. 2　The output chacteristic in the p resence of the interaction betw een contro l facto r (A ) and no ise facto r (N ) 图2　控制因素(A ) 与干扰因素(N ) 相互作用下的输出态性 F ig. 1　The nonlinear relationship betw een contro l facto r (A ) and its output charcteristic F ig. 1　The nonlinear relationship betw een contro l facto r (A ) and its output charcteristic F ig. 2　The output chacteristic in the p resence of the interaction betw een contro l facto r (A ) and no ise facto r (N ) 根据各影响因素的性质, Taguchi 动态实验设计所规定的方案如图3 所示, 为达到减少实验次数和取得最好的S ö N Β 值, 对控制因素的正交设计, 其相应的Taguchi 正交表有: L 12 (2 11) ,L 18 (2 1× 3 7) 和L 36 (2 11× 3 12). 根据各影响因素的性质, Taguchi 动态实验设计所规定的方案如图3 所示, 为达到减少实验次数和取得最好的S ö N Β 值, 对控制因素的正交设计, 其相应的Taguchi 正交表有: L 12 (2 11) ,L 18 (2 1× 3 7) 和L 36 (2 11× 3 12). 魏子栋等: 磷化过程的Taguchi 设计第2 期第2 期 · 5 0 2 · 2　Taguchi 方法在磷化过程的应用 2. 1　磷化过程　　除油→清水漂洗→除锈→清水漂洗→浸1% 草酸→清水漂洗→磷化→清水漂洗→热风吹干 2. 2　评价磷化膜质量的点滴液 10% CuSO 4· 5H 2O 40 mL ; 10% N aC l 20 mL ; 0. 1N HC l 1 mL 2. 3　磷化膜剥离液 C rO 3 50 g; H 2O 1 000 mL ; 温度75 ℃ 2. 4　传统的磷化液配方[4 ] 马日夫盐30 göL; Zn (NO 3) 2　70 gö L ; N aF 3 göL; N aNO 3　1 göL 2. 5　新磷化液组成 M n 2+ 　0. 06～0. 20 mo löL; Zn 2+ 0. 20～0. 40 mo löL; PO 3- 4 0. 30～0. 75 mo löL ; 酸度调节剂W 21　0. 003～0. 01 mo löL; 加速剂W 22　0. 02～0. 05 mo löL 其中W 21 为对磷化过程要求的FA 和TA 有理想调节作用的酸度调节剂. W 22 为磷化加速剂和磷化膜微观结构调整剂. 2. 2　Taguchi 方法在磷化过程的应用 2. 1　磷化过程　　除油→清水漂洗→除锈→清水漂洗→浸1% 草酸→清水漂洗→磷化→清水漂洗→热风吹干 2. 2　评价磷化膜质量的点滴液 10% CuSO 4· 5H 2O 40 mL ; 10% N aC l 20 mL ; 0. 1N HC l 1 mL 2. 3　磷化膜剥离液 C rO 3 50 g; H 2O 1 000 mL ; 温度75 ℃ 2. 3　磷化膜剥离液 C rO 3 50 g; H 2O 1 000 mL ; 温度75 ℃ 2. 4　传统的磷化液配方[4 ] 2. 4　传统的磷化液配方[4 ] 马日夫盐30 göL; Zn (NO 3) 2　70 gö L ; N aF 3 göL; N aNO 3　1 göL 2. 5　新磷化液组成 M n 2+ 　0. 06～0. 20 mo löL; Zn 2+ 0. 20～0. 40 mo löL; PO 3- 4 0. 30～0. 75 mo löL ; 酸度调节剂W 21　0. 003～0. 01 mo löL; 加速剂W 22　0. 02～0. 05 mo löL 其中W 21 为对磷化过程要求的FA 和TA 有理想调节作用的酸度调节剂. W 22 为磷化加速剂和磷化膜微观结构调整剂. 2. 6　磷化过程的Taguchi 设计控制因素与信号因素的水平如表1 所示. 表1　实验L 18 (21× 37) 的控制因素与信号因素水平设置 Tab. 1　Facto rs and levels fo r A rray L 18 (21× 37) 　控制因素水平1 水平2 水平3 A 浸草酸时间 (s) 60 40 B 磷化时间 (m in) 30 20 15 C 磷化温度 (℃) 60 40 50 D W 21 (mo löL ) 0. 015 0. 010 0. 005 E W 22 (mo löL ) 0. 068 0. 047 0. 027 F M n 2+ (mo löL ) 0. 158 0. 140 0. 105 G Zn 2+ (mo löL ) 0. 423 0. 740 0. 265 H H 2PO 2- 4 (mo löL ) 0. 846 0. 740 0. 530 　信号因素水平1 水平2 水平3 M 试片面积 (cm 2) 7. 23 9. 31 11. 13 根据L 18 (2 1× 3 7) 正交表安排控制因素实验, 依公式(7, 8, 9, 10, 11) 计算S ö N Β, 膜重量和磷化试片的面积分别对应于式(8) 中的y 和M , 膜重量通过磷化膜在剥离前后的重量差求取. 计算所得的S ö N Β 和硫酸铜点滴后磷化膜出现粉红色斑点的时间列于表2 表1　实验L 18 (21× 37) 的控制因素与信号因素水平设置 Tab. 1　Facto rs and levels fo r A rray L 18 (21× 37) 根据L 18 (2 1× 3 7) 正交表安排控制因素实验, 依公式(7, 8, 9, 10, 11) 计算S ö N Β, 膜重量和磷化试片的面积分别对应于式(8) 中的y 和M , 膜重量通过磷化膜在剥离前后的重量差求取. 计算所得的S ö N Β 和硫酸铜点滴后磷化膜出现粉红色斑点的时间列于表2. 根据L 18 (2 1× 3 7) 正交表安排控制因素实验, 依公式(7, 8, 9, 10, 11) 计算S ö N Β, 膜重量和磷化试片的面积分别对应于式(8) 中的y 和M , 膜重量通过磷化膜在剥离前后的重量差求取. 计算所得的S ö N Β 和硫酸铜点滴后磷化膜出现粉红色斑点的时间列于表2. 电　化　学 1996 年 ·6 0 2 表2　正交表, S ö N Β 和硫酸铜点滴后磷化膜出现粉红色斑点的时间(t) Tab. 2　Taguchi 方法在磷化过程的应用 2　A rray, S ö N Β　and tim e of p ink speckle advent after dropp ing CuSO 4　test so lution No A B C D E F G H M 1 M 2 M 3 S ö N Β t (s) 1 1 1 1 3 2 1 2 2 1 2 3 - 10. 26 172 2 1 2 1 1 1 2 1 1 1 2 3 - 9. 49 130 3 1 3 1 2 3 3 3 3 1 2 3 - 10. 59 95 4 1 1 2 2 1 3 1 2 1 2 3 - 14. 17 152 5 1 2 2 3 3 1 3 1 1 2 3 - 10. 74 145 6 1 3 2 1 2 2 2 3 1 2 3 - 9. 47 92 7 1 1 3 1 3 3 2 1 1 2 3 - 9. 70 167 8 1 2 3 2 2 1 1 3 1 2 3 - 10. 42 151 9 1 3 3 3 1 2 3 2 1 2 3 - 10. 89 85 10 2 1 1 1 1 1 3 3 1 2 3 - 10. 17 135 11 2 2 1 2 3 2 2 2 1 2 3 - 10. 72 57 12 2 3 1 3 2 3 1 1 1 2 3 - 9. 83 110 13 2 1 2 3 3 2 1 3 1 2 3 - 9. 12 75 14 2 2 2 1 2 3 3 2 1 2 3 - 10. 92 105 15 2 3 2 2 1 1 2 1 1 2 3 - 12. 00 62 16 2 1 3 2 2 3 3 1 1 2 3 - 12. 50 200 17 2 2 3 3 1 2 2 3 1 2 3 - 13. 88 80 18 2 3 3 1 3 1 1 2 1 2 3 - 11. 99 120 　图4　磷化膜SEM 照片 (a) 和(b) 传统磷化液所形成的磷化膜 (c) 和(d) 新磷化液所形成的磷化膜 3　结果与讨论 3. 1　磷化膜防腐性能与微观结构从表2 可以看出, 从新磷化液中获得的磷化膜硫酸铜点滴出现粉红色斑点的时间在57～200 s 之间, 而传统磷化液在50 ℃ 下, 磷化30 m in, 其点滴时间仅有15 s. 这表明新的磷化液比传统磷化液所形成的磷化膜有着更好的耐腐蚀性能, 从两种磷化液所得的磷化膜SEM 照片(图4) 可以看出, 传统磷化液中获得的磷化膜结构稀疏, 呈不均匀片状树枝状晶体, 而新的磷化液中获得的磷化膜致密, 均匀且呈柱状或球状. 这种优良的磷化膜结构除了具有优良的防腐效果外, 还增加了基体的有效表面积, 有利于油漆的吸附, 增强油漆与基体之间的结合力. 3. 2　Taguchi 方法在磷化过程的应用 2　利用S ö N Β 优化磷化工艺依表2 的实验结果, 做出各因素水平与 ö 的关系如图根据产生最高 ö 表2　正交表, S ö N Β 和硫酸铜点滴后磷化膜出现粉红色斑点的时间(t) 图4　磷化膜SEM 照片 (a) 和(b) 传统磷化液所形成的磷化膜 (c) 和(d) 新磷化液所形成的磷化膜　F ig. 4　SEM of phophating film s 魏子栋等: 磷化过程的Taguchi 设计图5　各因素水平下磷化膜质量的S ö N Β F ig. 5 　Coating w eight S ö N Β　ratio s. The sub2 scrip ts rep resent levels 图6　磷化膜质量与磷化面积的关系 F ig. 6　Pho sphates coating w eight as a function of coating p late area 3. 4　本磷化液的维护性能本文提出的磷化液使用过后, 看不出任何沉淀, 静置48 h, 底部仅出现少许沉淀物, 连续添加使用14 个循环后, 亦能获得优良如初的磷化膜. 而传统磷化液使用一次即出现大量沉淀, 过滤后补加量大, FA 和TA 不易恢复到原始值, 其可操作性极差. 4　结　论应用Taguchi 方法, 可以在干扰因素存在情况下, 以最小的偏差获得最好的目标值. 利用 Taguchi 方法中S ö N Β 值获得了最佳磷化工艺, 实现了磷化膜与磷化试片面积之间的线性关系. 有机加速剂W 22 和酸度调节剂W 21 的联合使用, 不仅可减少磷化过程的沉淀物而且可获得微观结构优良的磷化膜. 本文提出的磷化液比传统磷化液可操作性好, 其应用前景将十分乐观. App lication of TaguchiM ethod to Pho sphate Coating W ei Zidong (D ep artm ent of Chem ical E ng ineering , S handong U niversity of T echnology , J inan　250061) Guo H etong (D ep artm ent of A pp lied Chem istry , T ianj in U niversity , T ianj in　300072) 图5　各因素水平下磷化膜质量的S ö N Β F ig. 5 　Coating w eight S ö N Β　ratio s. The sub2 scrip ts rep resent levels 图6　磷化膜质量与磷化面积的关系 F ig. 6　Pho sphates coating w eight as a function of coating p late area 3. 4　本磷化液的维护性能本文提出的磷化液使用过后, 看不出任何沉淀, 静置48 h, 底部仅出现少许沉淀物, 连续添加使用14 个循环后, 亦能获得优良如初的磷化膜. 而传统磷化液使用一次即出现大量沉淀, 过滤后补加量大, FA 和TA 不易恢复到原始值, 其可操作性极差. 结　论魏子栋等: 磷化过程的Taguchi 设计 · 7 0 2 · 第2 期第2 期得出最好的磷化工艺组合为A 1B 3C1D 1E 3F 2G1H 3. 3. 3　磷化膜质量与磷化面积成线性关系的实现在3. 2 得出的最佳磷化工艺条件下, 获得的磷化膜重量与磷化试片面积之间的关系如图 6, 表明获得均匀磷化膜的工艺已经实现了. 得出最好的磷化工艺组合为A 1B 3C1D 1E 3F 2G1H 3. 3. 3　磷化膜质量与磷化面积成线性关系的实现在3. 2 得出的最佳磷化工艺条件下, 获得的磷化膜重量与磷化试片面积之间的关系如图 6, 表明获得均匀磷化膜的工艺已经实现了. 电　化　学电　化　学 1996 年 1996 年 ·8 0 2 Abs tra c t　The p roblem s encountered in pho sphating such as unstability of pho s2 phating bath, too m uch sludge in pho sphating and the poo r m icroco sm ic fo rm ation of pho s2 phating film s have been so lved by imp roving the pho sphating bath compo sition and pho s2 phating p rocedures. A s far as the non2linear relationship betw een the coating w eight and ge2 om etric area of coating in the pho sphating of the steel is concerned, the TaguchiM ethod is used to op tim ize the pho sphating p rocess. The linear relationship betw een the coating w eight and geom etric area of coating is finally obtained. The operational p roperty of the p resent pho sphating bath is also dram atically imp roved by the adop tion of new pho sphating compo si2 tion. Key w o rds　Pho sphating, Taguchim ethod Key w o rds　Pho sphating, Taguchim ethod Key w o rds　Pho sphating, Taguchim ethod Refe rences 1　雷作钅咸, 胡梦珍. 金属的磷化处理, 北京: 机械工业出版社, 1992 2 　L eisener P, U lrich D , M o llo r P. App lying Taguchi statistics to op tim ize current efficiency in hard chrom ium pulse p lating. P lating and S urf ace F inishing , 1992, 7: 62 3　Taguchi G. Introduction to quality engineering. A sian P roductiv ity organiz ation, 1986: 76 4　曾华粱, 吴仲达等. 电镀工艺手册. 北京: 机械工业出版社, 1989 《电化学》第2 卷第3 期　　部分内容预告研究快讯庄　林, 陆君涛: T im e2R eso lved Electron Sp in R esonance Spectro scopy fo r in2 situ Studies of Electrochem ical System s 毛秉伟等: 微电极上金电沉积初始阶段的间接测量及研究研究论文陈　剑、查全性: 采用粉末电极技术改善葡萄糖氧化酶电极的抗干扰性能薛江云等: 电化学方法制备铜钴纳米层膜姚立广等: A Study of R uO 22Co 3O 42T iO 2 (60) Coating on T i2substrate fo r Chlo2 rine Gas Evo lution 技术论文汤皎宁、周绍民等: 添加剂Ce 4+ 对Co2P2PTFE 复合镀层的影响 Refe rences 1　雷作钅咸, 胡梦珍. 金属的磷化处理, 北京: 机械工业出版社, 1992 2 　L eisener P, U lrich D , M o llo r P. App lying Taguchi statistics to op tim ize current efficiency in hard chrom ium pulse p lating. P lating and S urf ace F inishing , 1992, 7: 62 3　Taguchi G. Introduction to quality engineering. A sian P roductiv ity organiz ation, 1986: 76 4　曾华粱, 吴仲达等. 电镀工艺手册. 北京: 机械工业出版社, 1989 App lication of TaguchiM ethod to Pho sphate Coating W ei Zidong (D ep artm ent of Chem ical E ng ineering , S handong U niversity of T echnology , J inan　250061) Guo H etong (D ep artm ent of A pp lied Chem istry , T ianj in U niversity , T ianj in　300072) W ei Zidong (D ep artm ent of Chem ical E ng ineering , S handong U niversity of T echnology , J inan　250061) Guo H etong (D ep artm ent of A pp lied Chem istry , T ianj in U niversity , T ianj in　300072)
https://openalex.org/W2906165687	https://www.research-collection.ethz.ch/bitstream/20.500.11850/315744/2/PhysRevD.98.112011.pdf	English	null	Angular analysis of the decay <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msup><mml:mi>B</mml:mi><mml:mo>+</mml:mo></mml:msup><mml:mo stretchy="false">→</mml:mo><mml:msup><mml:mi>K</mml:mi><mml:mo>+</mml:mo></mml:msup><mml:msup><mml:mi>μ</mml:mi><mml:mo>+</mml:mo></mml:msup><mml:msup><mml:mi>μ</mml:mi><mml:mo>−</mml:mo></mml:msup></mml:math> in proton-proton collisions at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msqrt><mml…	Physical review. D/Physical review. D.	2,018	cc-by	19,435	ETH Library ETH Library Author(s): Author(s): CMS Collaboration; Sirunyan, Albert M.; Backhaus, Malte; Bäni, Lukas; Berger, Pirmin; Chernyavskaya, Nadezda; Dissertori, Günther; Dittmar, Michael; Donegà, Mauro; Dorfer, Christian; Grab, Christophorus ; Heidegger, Constantin; Hits, Dmitry; Hoss, Jan; Klijnsma, Thomas; Lustermann, Werner; Manzoni, Riccardo A.; Marionneau, Matthieu; Meinhard, Maren T.; Micheli, Francesco; Musella, Pasquale; Nessi-Tedaldi, Francesca; Pata, Joosep; Pauss, Felicitas; Perrin, Gaël; Perrozzi, Luca; Pigazzini, Simone; Quittnat, Milena; Ruini, Daniele; Sanz Becerra, Diego A.; Schönenberger, Myriam; Shchutska, Lesya; Tavolaro, Vittorio R.; Theofilatos, Konstantinos ; Vesterbacka Olsson, Minna L.; Wallny, Rainer ; Zhu, De Hua; et al. Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Funded by SCOAP3. (Received 2 June 2018; published 20 December 2018) The angular distribution of the flavor-changing neutral current decay Bþ →Kþμþμ−is studied in proton-proton collisions at a center-of-mass energy of 8 TeV. The analysis is based on data collected with the CMS detector at the LHC, corresponding to an integrated luminosity of 20.5 fb−1. The forward- backward asymmetry AFB of the dimuon system and the contribution FH from the pseudoscalar, scalar, and tensor amplitudes to the decay width are measured as a function of the dimuon mass squared. The measurements are consistent with the standard model expectations. I. INTRODUCTION are implied throughout this paper. The data, corresponding to an integrated luminosity of 20.5 fb−1 [14], were collected by the CMS experiment at the LHC in 2012. The angular distribution of this decay has previously been studied by the BABAR [15], Belle [16], CDF [17], and LHCb [18,19] experiments, but no hints of BSM have been seen. The decay Bþ →Kþμþμ−is a manifestation of a flavor- changing neutral current process of the type b →slþl−, with l denoting a charged lepton. In the standard model (SM), this decay is forbidden at tree level and occurs through higher-order processes. This makes the measure- ment of this process more sensitive to possible physics phenomena beyond the SM (BSM). II. THE CMS DETECTOR The central feature of the CMS detector is a super- conducting solenoid of 6 m internal diameter, providing a magnetic field of 3.8 T. Within the solenoid volume are a silicon pixel and a strip tracker, a lead tungstate crystal electromagnetic calorimeter, and a brass and scintillator hadron calorimeter, each composed of a barrel and two end-cap sections. Forward calorimeters extend the pseu- dorapidity coverage provided by the barrel and end-cap detectors. Muons are detected in gas-ionization chambers embedded in the steel flux-return yoke outside the solenoid. A detailed description of the CMS detector, together with a definition of the coordinate system used and the relevant kinematic variables, can be found elsewhere [20]. In the SM, three amplitudes contribute to Bþ →Kþμþμ− via either electroweak Z=γ penguin diagrams or a WþW− box diagram, as shown in Fig. 1. Two independent param- eters describe the decay rate for the Bþ →Kþμþμ−process: the forward-backward asymmetry AFB of the dimuon system and the contribution FH from the pseudoscalar, scalar, and tensor amplitudes to the decay width. Theoretical predictions are available for both parameters [1–3]. In the SM, AFB is zero up to small corrections, and FH is also small. Because SM amplitudes may interfere with the contributions from BSM particles in loop diagrams, the decay can probe the presence of yet-unobserved particles and processes [4–9]. For example, a nonzero AFB or large FH would point to a BSM contribution [1,10], which can be probed [11,12] by comparing the experimental measurements with the theo- retical predictions [6,10,13]. The events are selected online using a two-stage trigger system [21]. The first level is composed of custom hardware processors and uses information from the calo- rimeters and muon detectors to select events at a rate of around 100 kHz within a time interval of less than 4 μs. The second level, known as the high-level trigger (HLT), consists of a farm of processors running a version of the full event reconstruction software optimized for fast processing, and reduces the event rate to around 1 kHz before data storage. In this paper, we report the measurement of AFB and FH as a function of the dimuon mass squared (q2) based on an angular fit of the decay Bþ →Kþμþμ−in proton-proton collisions at ﬃﬃﬃs p ¼ 8 TeV. Charge-conjugate decay modes *Full author list given at the end of the article. Publication date: 2018-12-01 Permanent link: https://doi.org/10.3929/ethz-b-000315744 Rights / license: Creative Commons Attribution 4.0 International Originally published in: Originally published in: Physical Review D 98(11), https://doi.org/10.1103/PhysRevD.98.112011 This page was generated automatically upon download from the ETH Zurich Research Collection. For more information, please consult the Terms of use. PHYSICAL REVIEW D 98, 112011 (2018) DOI: 10.1103/PhysRevD.98.112011 III. EVENT SELECTION Monte Carlo (MC) simulated event samples are widely used in the analysis. The number of simulated events for the signal sample Bþ →Kþμþμ−corresponds to more than 160 times that of the data. Other simulated samples used in this analysis are Bþ →KþJ=ψðμþμ−Þ, Bþ → Kþψð2SÞðμþμ−Þ, and Bþ →μþμ−X. In the last decay mode, the muon pairs come from J=ψ or ψð2SÞ decay, and X denotes all other final-state particles. The MC samples are produced using the PYTHIA generator [22] version 6.424. Decays of Bþ and J=ψ or ψð2SÞ mesons are processed by the EVTGEN [23] version 9.1 program (with the default matrix element for the signal), in which final- state radiation is generated using PHOTOS [24]. Particles are traced through a detailed model of the detector with GEANT4 [25], producing signals similar to the actual detector responses. Particles coming from other proton- proton collisions in the same or nearby beam crossings (pileup) are simulated according to the data-taking con- ditions, but their effects on this analysis are small. Events with a dimuon invariant mass (q) close to the J=ψ or ψð2SÞ resonance region are rejected to remove this contamination from the control channels, as in Ref. [28]. The J=ψ and ψð2SÞ resonance regions are defined as mPDG J=ψ −5σq < q < mJ=ψ þ 3σq and jq −mPDG ψð2SÞj < 5σq, respectively, where σq is the calculated uncertainty in q, and the PDG superscript indicates the world-average mass value [29] for each particle. We further suppress such events by requiring, jðm−mPDG Bþ Þ−ðq−mPDG J=ψ Þj>0.13 GeV and jðm −mPDG Bþ Þ −ðq −mPDG ψð2SÞÞj > 0.06 GeV in the Bþ meson invariant mass region of 5.1–5.6 GeV, where m is the Bþ candidate invariant mass. With these requirements, the maximum contribution of events containing a J=ψ or ψð2SÞ is less than 7% in any q2, and the kinematic distributions of these events can be described together with those of the combinatorial background. meson invariant mass region of 5.1–5.6 GeV, where m is the Bþ candidate invariant mass. With these requirements, the maximum contribution of events containing a J=ψ or ψð2SÞ is less than 7% in any q2, and the kinematic distributions of these events can be described together with those of the combinatorial background. The selected events are reconstructed through the decay into the fully charged final state of one charged hadron and a pair of oppositely charged muons. III. EVENT SELECTION The data for this analysis was recorded using a low-mass dimuon HLT with a displaced vertex. The trigger requires a 112011-1 2470-0010=2018=98(11)=112011(20) © 2018 CERN, for the CMS Collaboration PHYS. REV. D 98, 112011 (2018) A. M. SIRUNYAN et al. W b s + − t, c, u − b s W W − − + + t, c, u FIG. 1. The SM electroweak Z=γ penguin (left) and WþW−box (right) diagrams for the decay process Bþ →Kþμþμ−. two oppositely charged muons matching the HLT criteria that triggered the event readout. To discriminate signal events from background, additional selection criteria on kinematic variables are used. The following selection criteria are determined through a maximization of the expected signal significance using MC signal events and the surviving data events in the final Bþ meson invariant mass fitting region, 5.1–5.6 GeV. The charged hadron track must have pT > 1.3 GeV and the distance of closest approach in the transverse plane of the charged hadron trajectory to the interaction point, divided by its uncer- tainty, must be greater than 3.3. The Bþ meson candidate is formed by combining a dimuon candidate with the charged hadron track assumed to be a kaon. The event kinematic information is updated by fitting these three tracks to a common vertex. The chi-squared probability of the vertex fit for the Bþ candidate is required to be greater than 12%. To further reduce the background, the distance in the transverse plane between the Bþ vertex and the interaction point must be larger than 10.6 times its uncertainty. The cosine of the angle in the transverse plane between the Bþ momentum and a vector from the interaction point to the Bþ meson vertex must be greater than 0.9997. After applying the selection criteria, less than 1% of the selected events contain multiple Bþ candidates. In these events, only the candidate with the highest Bþ decay vertex fit prob- ability is retained. s FIG. 1. The SM electroweak Z=γ penguin (left) and WþW−box (right) diagrams for the decay process Bþ →Kþμþμ−. pair of opposite-sign muons with a dimuon vertex displaced from the interaction point by more than three times the calculated uncertainty. The trigger also requires the dimuon candidate to have invariant mass in the range 1.0–4.8 GeV and pT > 6.9 GeV, and for each muon to have pT > 3.5 GeV and jηj < 2.2. III. EVENT SELECTION Events from the control channels Bþ →KþJ=ψðμþμ−Þ and Bþ →Kþψð2SÞðμþμ−Þ have the same final state as the signal process Bþ → Kþμþμ−, and are extensively used to validate the analysis and to evaluate the systematic uncertainties. The muons are reconstructed using information from the silicon tracker and muon detector systems [26]. They must satisfy the off-line muon identification criteria that are optimized for low-pT muons [27]. Dimuon candidates are formed from IV. ANGULAR ANALYSIS The measurement of AFB and FH is performed through angular analysis in seven q2 ranges from 1 to 22 GeV2. The q2 ranges used in this analysis are the same as in previous measurements [16–18], facilitating the compari- son. The J=ψ and ψð2SÞ regions, corresponding to q2 ranges of 8.68–10.09 and 12.86–14.18 GeV2, respectively, are used as control regions [28,30]. Additionally, we define an inclusive low-q2 range of 1.00–6.00 GeV2 in order to 112011-2 ANGULAR ANALYSIS OF THE DECAY Bþ … PHYS. REV. D 98, 112011 (2018) candidates in each q2 range. The unnormalized probability density function (pdf) used in the two-dimensional fit is compare the results to SM calculations with the best- controlled theoretical uncertainty, and a full inclusive q2 range of 1.00–22.00 GeV2, excluding the control regions. The analysis for these two ranges is performed with the same procedure as for the other ranges. pdfðm; cos θlÞ ¼ YSSmðmÞSaðcos θlÞϵðcos θlÞ þ YBBmðmÞBaðcos θlÞ; ð2Þ ð2Þ þ YBBmðmÞBaðcos θlÞ; ð2Þ The decay rate for the process Bþ →Kþμþμ−depends on cos θl, where θl is the angle between the directions of the μ−and Kþ in the dilepton rest frame. The differential decay width Γl with respected to cos θl can be para- metrized [1,8,9] in terms of the observables of interest AFB and FH as: where the two contributions on the right-hand side corre- spond to the parametrization of the signal and background. The parameters YS and YB are the yields of signal and background events, respectively. The functions SmðmÞ and Saðcos θlÞ describe the signal invariant mass and angular distributions, while BmðmÞ and Baðcos θlÞ are similar functions describing the background. The function ϵðcos θlÞ is the signal efficiency as a function of cos θl. 1 Γl dΓl dcos θl ¼ 3 4ð1 −FHÞð1 −cos2θlÞ þ 1 2FH þ AFB cos θl: ð1Þ ð1Þ ð Þ The signal distribution SmðmÞ is modeled as the sum of two Gaussian functions with a common mean, and Saðcos θlÞ is given in Eq. (1). The background distribution BmðmÞ is modeled as a single exponential function, while Baðcos θlÞ is parametrized as the sum of a Gaussian function and a third- or fourth-degree polynomial, depend- ing on the particular q2 range. The requirement for the decay rate to remain positive over all possible lepton angles constrains the parameter space to the region 0 ≤FH ≤3 and jAFBj ≤minð1; FH=2Þ. A. M. SIRUNYAN et al. The ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 Data Total fit Signal Background 2 < 2 GeV 2 q 1 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 150 200 2 < 4.3 GeV 2 q 2 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 100 200 300 400 2 < 8.68 GeV 2 q 4.3 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 150 200 250 2 < 12.86 GeV 2 q 10.3 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 2 < 16 GeV 2 q 14.18 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 150 2 < 18 GeV 2 q 16 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 2 < 22 GeV 2 q 18 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 100 200 300 400 500 2 < 6 GeV 2 q 1 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 500 1000 2 < 22 GeV 2 q 1 < (8 TeV) -1 20.5 fb CMS FIG. 3. Projections of the Kþμþμ−invariant mass distributions for each q2 range from the two-dimensional fit of data. The solid lines show the total fit, the shaded area the signal contribution, and the dashed-dotted lines the background. The vertical bars on the points represent the statistical uncertainty in the data. A. M. SIRUNYAN et al. A. M. SIRUNYAN et al. Many of the parameters in the final fit are set to a given value with a Gaussian constraint that reflects the input uncertainty of the value. For the SmðmÞ function, the mean is constrained to the world-average Bþ mass [29] and the widths and relative fraction of the two Gaussians are constrained to the values found from fitting simulated events. The parameters of the Baðcos θlÞ function are obtained by fitting the events in the Bþ meson invariant mass sideband regions of 5.10–5.21 and 5.35–5.46 GeV. The free parameters of the fit are YS, YB, AFB, and FH, as well as the exponential decay parameter of BmðmÞ. reconstruction efficiency is obtained from the ratio of the number of reconstructed MC events passing the final event selection to the number of events passing the single-muon selection at the generator level. It varies from 4 to 7% depending on q2. The signal efficiency ϵðcos θlÞ is para- metrized and fit with a sixth-order polynomial, as shown in Fig. 2 for the nine different signal q2 ranges used in this analysis. The angular distributions of data and simulation from the two control channels are compared and the good agreement between them provides a validation of the efficiency description. We also check that the ratio of the branching fractions of the two control channels is consistent with the world-average value [29] within their uncertainties. The MC simulation samples are used to validate the fitting procedure in each q2 range. The results of fitting the signal MC sample at the generator level and the standard signal simulation are consistent with each other. The large MC signal sample is divided into 20 subsamples and fits of The signal efficiency ϵðcos θlÞ is factorized into an acceptance ϵacc times a reconstruction efficiency ϵreco, which are both functions of cos θl. The acceptance is obtained from generated events, before the particle propa- gation with GEANT4, and is calculated as the fraction of MC simulated signal events passing the muon requirement of pT > 3.5 GeV and jηj < 2.2 relative to all generated events. It varies from 2 to 4% depending on q2. A. M. SIRUNYAN et al. ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 Data Total fit Signal Background 2 < 2 GeV 2 q 1 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 150 200 2 < 4.3 GeV 2 q 2 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 100 200 300 400 2 < 8.68 GeV 2 q 4.3 < (8 TeV) -1 20.5 fb CMS Events / 0.025 GeV Events / 0.025 GeV ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 G 0 50 100 Data Total fit Signal Background ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 G 0 50 100 150 ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 G 0 100 200 300 ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 150 200 250 2 < 12.86 GeV 2 q 10.3 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 2 < 16 GeV 2 q 14.18 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 150 2 < 18 GeV 2 q 16 < (8 TeV) -1 20.5 fb CMS (8 TeV) -1 20 5 fb CMS (8 TeV) -1 20 5 fb CMS (8 TeV) -1 20 5 fb CMS ) (GeV) - μ + μ + m(K ) ( ) μ μ ( ) ( ) μ μ ( ) ( ) μ μ ( ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 150 200 250 2 < 12.86 GeV 2 q 10.3 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 2 < 16 GeV 2 q 14.18 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 150 2 < 18 GeV 2 q 16 < (8 TeV) -1 20.5 fb CMS 5.6 V) ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 2 < 16 GeV 2 q 14.18 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 150 2 < 18 GeV 2 q 16 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 150 200 250 2 < 12.86 GeV 2 q 10.3 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 150 2 < 18 GeV 2 q 16 < (8 TeV) -1 20.5 fb CMS Events / 0.025 GeV ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 100 200 300 400 500 2 < 6 GeV 2 q 1 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 500 1000 2 < 22 GeV 2 q 1 < (8 TeV) -1 20.5 fb CMS ) (GeV) - μ + μ + m(K 5.1 5.2 5.3 5.4 5.5 5.6 Events / 0.025 GeV 0 50 100 2 < 22 GeV 2 q 18 < (8 TeV) -1 20.5 fb CMS FIG. IV. ANGULAR ANALYSIS The angular observables AFB and FH are extracted from a two-dimensional extended unbinned maximum-likelihood fit to the angular distribution of the selected Bþ meson lθ cos 1 − 0.5 − 0 0.5 1 Efficiency (%) 0 0.1 0.2 0.3 CMS Simulation 2 < 2 GeV 2 q 1 < lθ cos 1 − 0.5 − 0 0.5 1 Efficiency (%) 0 0.1 0.2 0.3 CMS Simulation 2 < 4.3 GeV 2 q 2 < lθ cos 1 − 0.5 − 0 0.5 1 Efficiency (%) 0 0.1 0.2 0.3 CMS Simulation 2 < 8.68 GeV 2 q 4.3 < lθ cos 1 − 0.5 − 0 0.5 1 Efficiency (%) 0 0.1 0.2 0.3 CMS Simulation 2 < 12.86 GeV 2 q 10.3 < lθ cos 1 − 0.5 − 0 0.5 1 Efficiency (%) 0 0.1 0.2 0.3 CMS Simulation 2 < 16 GeV 2 q 14.18 < lθ cos 1 − 0.5 − 0 0.5 1 Efficiency (%) 0 0.1 0.2 0.3 CMS Simulation 2 < 18 GeV 2 q 16 < lθ cos 1 − 0.5 − 0 0.5 1 Efficiency (%) 0 0.1 0.2 0.3 CMS Simulation 2 < 22 GeV 2 q 18 < lθ cos 1 − 0.5 − 0 0.5 1 Efficiency (%) 0 0.1 0.2 0.3 CMS Simulation 2 < 6 GeV 2 q 1 < lθ cos 1 − 0.5 − 0 0.5 1 Efficiency (%) 0 0.1 0.2 0.3 CMS Simulation 2 < 22 GeV 2 q 1 < FIG. 2. The signal efficiency determined from simulated events as a function of cos θl for the different q2 ranges (points). The vertical bars indicate the statistical uncertainty. The curves show the sixth-order polynomial fits to the points. lθ cos 1 − 0.5 − 0 0.5 1 Efficiency (%) 0 0.1 0.2 0.3 CMS Simulation 2 < 4.3 GeV 2 q 2 < Efficiency (%) Efficiency (%) Efficiency (%) Efficiency (%) Efficiency (%) FIG. 2. The signal efficiency determined from simulated events as a function of cos θl for the different q2 ranges (points). The vertical bars indicate the statistical uncertainty. The curves show the sixth-order polynomial fits to the points. 112011-3 PHYS. REV. D 98, 112011 (2018) A. M. SIRUNYAN et al. lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 50 100 150 Data Total fit Signal Background 2 < 2 GeV 2 q 1 < (8 TeV) -1 20.5 fb CMS lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 100 200 300 400 500 2 < 8.68 GeV 2 q 4.3 < (8 TeV) -1 20.5 fb CMS lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 100 200 300 2 < 4.3 GeV 2 q 2 < (8 TeV) -1 20.5 fb CMS lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 20 40 60 80 2 < 16 GeV 2 q 14.18 < (8 TeV) -1 20.5 fb CMS lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 50 100 150 200 2 < 12.86 GeV 2 q 10.3 < (8 TeV) -1 20.5 fb CMS lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 20 40 60 80 2 < 18 GeV 2 q 16 < (8 TeV) -1 20.5 fb CMS Events / 0.1 Events / 0.1 lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 200 400 600 800 1000 2 < 22 GeV 2 q 1 < (8 TeV) -1 20.5 fb CMS lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 20 40 60 80 2 < 22 GeV 2 q 18 < (8 TeV) -1 20.5 fb CMS lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 200 400 600 2 < 6 GeV 2 q 1 < (8 TeV) -1 20.5 fb CMS Events / 0.1 Events / 0.1 FIG. 4. Projections of the cos θl distributions for each q2 range from the two-dimensional fit of data. The solid lines show the total fit, the shaded area the signal contribution, and the dashed-dotted lines the background. The vertical bars on the points represent the statistical uncertainty in the data. these subsamples reveal no additional bias. In addition, we generate 200 pseudoexperiments of 100 times the size of data, using the pdf in Eq. (2), with parameters from fitting the data. A. M. SIRUNYAN et al. 3. Projections of the Kþμþμ−invariant mass distributions for each q2 range from the two-dimensional fit of data. The solid lines show the total fit, the shaded area the signal contribution, and the dashed-dotted lines the background. The vertical bars on the points represent the statistical uncertainty in the data. 112011-4 ANGULAR ANALYSIS OF THE DECAY Bþ … PHYS. REV. D 98, 112011 (2018) lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 50 100 150 Data Total fit Signal Background 2 < 2 GeV 2 q 1 < (8 TeV) -1 20.5 fb CMS lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 100 200 300 2 < 4.3 GeV 2 q 2 < (8 TeV) -1 20.5 fb CMS lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 100 200 300 400 500 2 < 8.68 GeV 2 q 4.3 < (8 TeV) -1 20.5 fb CMS lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 50 100 150 200 2 < 12.86 GeV 2 q 10.3 < (8 TeV) -1 20.5 fb CMS lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 20 40 60 80 2 < 16 GeV 2 q 14.18 < (8 TeV) -1 20.5 fb CMS lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 20 40 60 80 2 < 18 GeV 2 q 16 < (8 TeV) -1 20.5 fb CMS lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 20 40 60 80 2 < 22 GeV 2 q 18 < (8 TeV) -1 20.5 fb CMS lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 200 400 600 2 < 6 GeV 2 q 1 < (8 TeV) -1 20.5 fb CMS lθ cos 1 − 0.5 − 0 0.5 1 Events / 0.1 0 200 400 600 800 1000 2 < 22 GeV 2 q 1 < (8 TeV) -1 20.5 fb CMS FIG. 4. Projections of the cos θl distributions for each q2 range from the two-dimensional fit of data. The solid lines show the total fit, the shaded area the signal contribution, and the dashed-dotted lines the background. The vertical bars on the points represent the statistical uncertainty in the data. A. M. SIRUNYAN et al. The differences between the fitted values from these samples and the input parameters from data follow Gaussian distributions with the means consistent with zero and the widths smaller than the variations among the signal MC subsample fits in the same q2 range. fit the signal invariant mass distribution within their uncertainties results in a negligible change in the measured values of AFB and FH. The finite size of the simulated event samples can affect the accuracy of the efficiency determination. To estimate the uncertainty, 200 alternative efficiency functions are created by varying the parameters of the signal efficiency function ϵðcos θlÞ within their uncertainties. These alternative effi- ciencies are independently used to fit the data. The standard deviations of the resulting AFB and FH fit values are taken as their systematic uncertainties from this source. The system- atic uncertainty due to the efficiency description is estimated by changing the modeling of ϵðcos θlÞ. The fit to ϵðcos θlÞ is modified from a sixth-order polynomial to the product of a Gaussian function and a sixth-order polynomial, where the Gaussian function parameters are the fit results from ϵacc, and the sixth-order polynomial parameters are the fit results from ϵreco. The differences in the results of AFB and FH are used as the systematic uncertainties. The final fit is performed over the full Bþ meson invariant mass range and results in 2286 73 signal events with q2 from 1 to 22 GeV2. Figures 3 and 4 show the Kþμþμ−invariant mass and the cos θl projections, respec- tively, for each q2 range from the two-dimensional fit to the data. V. SYSTEMATIC UNCERTAINTIES Several sources of systematic uncertainty in the mea- sured values of AFB and FH are considered, as summarized in Table I. Varying the parameter values of SmðmÞ used to 112011-5 PHYS. REV. D 98, 112011 (2018) A. M. SIRUNYAN et al. TABLE I. Absolute values of the uncertainty contributions in the measurements of AFB and FH. For each item, the range indicates the variation of the uncertainty in the signal q2 ranges. added in quadrature to obtain the overall systematic uncertainty from the fitting procedure. In some q2 ranges there are visible structures in the background cos θl distributions, as seen in Fig. 4. We have investigated many possible contributions to these struc- tures, and none of them has been identified. This uncer- tainty is estimated using the “second” method from the fitting procedure systematic uncertainty calculation, with the cos θl distribution for the background obtained sepa- rately from the lower- and higher-mass sideband regions, 5.10–5.21 and 5.35–5.60 GeV. The larger of the two differences between these alternative fits and the nominal fit is taken as the systematic uncertainty from fitting the background cos θl distribution. indicates the variation of the uncertainty in the signal q ranges. Systematic uncertainty AFBð×10−2Þ FHð×10−2Þ Finite size of MC samples 0.4–1.8 0.9–5.0 Efficiency description 0.1–1.5 0.1–7.8 Simulation mismodeling 0.1–2.8 0.1–1.4 Background parametrization model 0.1–1.0 0.1–5.1 Angular resolution 0.1–1.7 0.1–3.3 Dimuon mass resolution 0.1–1.0 0.1–1.5 Fitting procedure 0.1–3.2 0.4–25 Background distribution 0.1–7.2 0.1–29 Total systematic uncertainty 1.6–7.5 4.4–39 The simulated signal sample is used to evaluate the effects of any simulation mismodeling. The difference in the fitted values of AFB and FH between a simulated sample at the generator level without the detector simulation and reconstruction steps, and the standard signal simulation sample is assigned as the systematic uncertainty. The specific parametrization of the function used to fit the backgrounds can cause the results to change. To evaluate the effect of fitting the background cos θl distribution, the degrees of the polynomials used to describe the angular shapes of the combinatorial background are decreased by one. After fitting with the alternative background para- metrization, the differences in the AFB and FH results are taken as the systematic uncertainties from the background parametrization model. V. SYSTEMATIC UNCERTAINTIES The systematic uncertainties com- ing from the experimental resolution in cos θl and q2 are estimated by comparing the values of AFB and FH obtained from the reconstructed MC events with those found using the generated values of cos θl and q2 in the fit. ) 2 (GeV 2 q 0 5 10 15 20 FB A 0.4 − 0.2 − 0 0.2 0.4 (8 TeV) -1 20.5 fb CMS ) 2 (GeV 2 q 0 5 10 15 20 H F 0 0.5 1 1.5 (8 TeV) -1 20.5 fb CMS Data DHMV Data FIG. 5. Results of the AFB (left) and FH (right) measurements in ranges of q2. The statistical uncertainties are shown by the inner vertical bars, while the outer vertical bars give the total un- certainties. The horizontal bars show the q2 range widths. The vertical shaded regions are 8.68–10.09 and 12.86 −14.18 GeV2, corresponding to the J=ψ- and ψð2SÞ-dominated control regions, respectively. The horizontal lines in the right plot show the DHMV SM theoretical predictions [32,33], whose uncertainties are smaller than the line width. ) 2 (GeV 2 q 0 5 10 15 20 FB A 0.4 − 0.2 − 0 0.2 0.4 (8 TeV) -1 20.5 fb CMS Data ) ( q ) 2 (GeV 2 q 0 5 10 15 20 H F 0 0.5 1 1.5 (8 TeV) -1 20.5 fb CMS Data DHMV g l q An estimate of the systematic uncertainty from the fitting procedure is calculated using two different methods. In the first method, we divide the large simulated signal sample into multiple subsamples, each with a size similar to that of the data. The difference between the average of the fitted values of AFB and FH from the subsamples and the fitted value from the full sample is taken as an estimate of the systematic uncertainty from the modeling of the signal. In the second method, we generate many pseudoexperiments in which each of the mass and cos θl distributions are obtained from combining a signal and background distri- bution. The signal distribution is obtained by selecting signal events from the simulated sample, with the number of events determined by the fit to the data. The background distribution is obtained from sampling a parent distribution that comes from subtracting the fitted signal distributions from the data. V. SYSTEMATIC UNCERTAINTIES The mean value of the differences from these pseudoexperiments and the measurements from the reconstruction-level simulated signal sample is taken as an estimate of the fitting uncertainty due to the presence of background. The estimates from the two methods are then FIG. 5. Results of the AFB (left) and FH (right) measurements in ranges of q2. The statistical uncertainties are shown by the inner vertical bars, while the outer vertical bars give the total un- certainties. The horizontal bars show the q2 range widths. The vertical shaded regions are 8.68–10.09 and 12.86 −14.18 GeV2, corresponding to the J=ψ- and ψð2SÞ-dominated control regions, respectively. The horizontal lines in the right plot show the DHMV SM theoretical predictions [32,33], whose uncertainties are smaller than the line width. 112011-6 PHYS. REV. D 98, 112011 (2018) ANGULAR ANALYSIS OF THE DECAY Bþ … TABLE II. Results of the fit for each q2 range, together with several SM predictions. The inclusive q2 ¼ 1.00–22.00 GeV2 range in the bottom line does not include events from the J=ψ and ψð2SÞ resonance regions. The signal yield YS is given, along with its statistical uncertainty. The measured values of AFB and FH are presented, where the first uncertainties are statistical and the second are systematic. The fifth column is a theoretical prediction by C. Bobeth et al. [1,3] using the EOS package [34] with the form factors from Refs. [2,35,36]. The sixth column is the calculation from S. Descotes-Genon et al. (DHMV) based on Refs. [32,33]. The last column is the prediction using the FLAVIO package [37] with the form factors from Ref. [38]. Only the central values of the theoretical predictions are shown, since their uncertainties are insignificant compared to those in the measurements. V. SYSTEMATIC UNCERTAINTIES q2 (GeV2) YS AFB FH FH (EOS) FH (DHMV) FH (FLAVIO) 1.00–2.00 169 22 0.08 þ0.22 −0.19 0.05 0.21 þ0.29 −0.21 0.39 0.047 0.046 0.045 2.00–4.30 331 32 −0.04 þ0.12 −0.12 0.07 0.85 þ0.34 −0.31 0.14 0.024 0.023 0.022 4.30–8.68 785 42 0.00 þ0.04 −0.04 0.02 0.01 þ0.02 −0.01 0.04 0.012 0.011 10.09–12.86 365 29 0.00 þ0.05 −0.05 0.05 0.01 þ0.02 −0.01 0.06 14.18–16.00 215 19 0.01 þ0.06 −0.05 0.02 0.03 þ0.03 −0.03 0.07 0.007 0.007 0.006 16.00–18.00 262 21 0.04 þ0.05 −0.04 0.03 0.07 þ0.06 −0.07 0.07 0.007 0.007 0.006 18.00–22.00 226 20 0.05 þ0.05 −0.04 0.02 0.10 þ0.06 −0.10 0.09 0.008 0.009 0.008 1.00–6.00 778 47 −0.14 þ0.07 −0.06 0.03 0.38 þ0.17 −0.21 0.09 0.025 0.025 0.020 1.00–22.00 2286 73 0.00 þ0.02 −0.02 0.03 0.01 þ0.01 −0.01 0.06 The systematic uncertainties are estimated for each q2 range independently. As the systematic uncertainty sources are considered to be independent, they are added in quadrature to obtain the total systematic uncertainties, as shown in the last row of Table I. 20.5 fb−1 recorded with the CMS detector at ﬃﬃﬃs p ¼ 8 TeV. The forward-backward asymmetry AFB of the muon system and the contribution FH of the pseudoscalar, scalar, and tensor amplitudes to the decay width are measured as a function of the dimuon mass squared. The results are consistent with previous measurements, and are also compatible with three different standard model predictions. ACKNOWLEDGMENTS We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: BMWFW and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); NKFIA (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); The correlation between the two variables is ignored by setting the confidence interval after using this profiling method. The systematic and statistical uncertainties are added in quadrature to obtain the total uncertainty. The measured values of AFB and FH for each q2 range are shown in Fig. 5. The numerical results are summarized in Table II, including the two special q2 ranges. The measured values of AFB are consistent with the SM expectation of no asymmetry. Table II also includes three SM predictions for FH with different input parameters and different handling of higher-order corrections, one of which is also shown in Fig. 5. There is generally good agreement between the predictions and our results, as well as between our results and previous measurements [15–19]. VI. RESULTS To evaluate the statistical uncertainties, the 68.3% con- fidence level intervals on AFB and FH are estimated using the profiled Feldman-Cousins technique [31]. When esti- mating the uncertainty in AFB and FH, the other variable is treated as a nuisance parameter and profiled. A large number of pseudoexperiments are generated with the maximum-likelihood estimate of the nuisance parameter. The correlation between the two variables is ignored by setting the confidence interval after using this profiling method. The systematic and statistical uncertainties are added in quadrature to obtain the total uncertainty. To evaluate the statistical uncertainties, the 68.3% con- fidence level intervals on AFB and FH are estimated using the profiled Feldman-Cousins technique [31]. When esti- mating the uncertainty in AFB and FH, the other variable is treated as a nuisance parameter and profiled. A large number of pseudoexperiments are generated with the maximum-likelihood estimate of the nuisance parameter. VII. SUMMARY An angular analysis of the decay Bþ →Kþμþμ−has been performed using a data sample of proton-proton collisions corresponding to an integrated luminosity of 112011-7 PHYS. REV. D 98, 112011 (2018) A. M. SIRUNYAN et al. research Grants No. 123842, No. 123959, No. 124845, No. 124850 and No. 125105 (Hungary); the Council of Science and Industrial Research, India; the HOMING PLUS program of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund, the Mobility Plus program of the Ministry of Science and Higher Education, the National Science Center (Poland), Contracts Harmonia No. 2014/14/ M/ST2/00428, Opus No. 2014/13/B/ST2/02543, No. 2014/ 15/B/ST2/03998, and No. 2015/19/B/ST2/02861, Sonata- bis No. 2012/07/E/ST2/01406; the National Priorities Research Program by Qatar National Research Fund; the Programa Estatal de Fomento de la Investigación Científica y T´ecnica de Excelencia María de Maeztu, Grant No. MDM-2015-0509 and the Programa Severo Ochoa del Principado de Asturias; the Thalis and Aristeia pro- grams cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); the Welch Foundation, Contract No. C-1845; and the Weston Havens Foundation (USA). JINR (Dubna); MON, RosAtom, RAS and RFBR (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI and FEDER (Spain); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (USA). Individuals have received support from the Marie- Curie program and the European Research Council and Horizon 2020 Grant, Contract No. 675440 (European Union); the Leventis Foundation; the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation `a la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT- Belgium); the F.R.S.-FNRS and FWO (Belgium) under the “Excellence of Science—EOS”—be.h Project No. 30820817; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Lendület (“Momentum”) Program and the János Bolyai Research Scholarship of the Hungarian Academy of Sciences, the New National Excellence Program ÚNKP, the NKFIA [1] C. Bobeth, G. Hiller, and G. Piranishvili, Angular distri- butions of B →Klþl−decays, J. High Energy Phys. 12 (2007) 040. [10] A. K. Alok, A. Dighe, and S. Uma Sankar, Large forward- backward asymmetry in B →Kμþμ−from new physics tensor operators, Phys. Rev. D 78, 114025 (2008). VII. SUMMARY [2] A. Khodjamirian, Th. Mannel, A. A. Pivovarov, and Y. M. Wang, Charm-loop effect in B →KðÞlþl−and B →Kγ, J. High Energy Phys. 09 (2010) 089. [11] F. Sala and D. M. Straub, A new light particle in B decays?, Phys. Lett. B 774, 205 (2017). [12] W. Altmannshofer and D. M. Straub, New physics in b →s transitions after LHC run 1, Eur. Phys. J. C 75, 382 (2015). [3] C. Bobeth, G. Hiller, D. van Dyk, and C. Wacker, The decay B →Klþl−at low hadronic recoil and model-independent δB ¼ 1 constraints, J. High Energy Phys. 01 (2012) 107. [13] D. Ghosh, M. Nardecchia, and S. A. Renner, Hint of lepton flavour non-universality in B meson decays, J. High Energy Phys. 12 (2014) 131. [4] A. Ali, T. Mannel, and T. Morozumi, Forward-backward asymmetry of dilepton angular distribution in the decay b →slþl−, Phys. Lett. B 273, 505 (1991). [14] CMS Collaboration, CMS Luminosity Based on Pixel Cluster Counting—Summer 2013 Update, CMS Physics Analysis Summary Report No. CMS-PAS-LUM-13-001 (CERN, 2013). [5] F. Beaujean, C. Bobeth, and S. Jahn, Constraints on tensor and scalar couplings from B →K¯μμ and Bs →¯μμ, Eur. Phys. J. C 75, 456 (2015). [6] W. Altmannshofer, C. Niehoff, P. Stangl, and D. M. Straub, Status of the B →Kμþμ−anomaly after Moriond 2017, Eur. Phys. J. C 77, 377 (2017). [15] B. Aubert et al. (BABAR Collaboration), Measurements of branching fractions, rate asymmetries, and angular distri- butions in the rare decays B →Klþl−and B →Klþl−, Phys. Rev. D 73, 092001 (2006). [7] W. Altmannshofer, P. Paradisi, and D. M. Straub, Model- independent constraints on new physics in b →s transitions, J. High Energy Phys. 04 (2012) 008. [16] J.-T. Wei et al. (Belle Collaboration), Measurement of the Differential Branching Fraction and Forward-Backward Asymmetry for B →KðÞlþl−, Phys. Rev. Lett. 103, 171801 (2009). [8] A. Ali, P. Ball, L. T. Handoko, and G. Hiller, A comparative study of the decays B →KðÞlþl−in standard model and supersymmetric theories, Phys. Rev. D 61, 074024 (2000). [17] T. Aaltonen et al. (CDF Collaboration), Measurements of the Angular Distributions in the Decays B →KðÞμþμ−at CDF, Phys. Rev. Lett. 108, 081807 (2012). [9] C. Bobeth, T. Ewerth, F. Kruger, and J. Urban, Analysis of neutral Higgs-Boson contributions to the decays Bs →lþl−and B →Klþl−, Phys. Rev. D 64, 074014 (2001). VII. SUMMARY [18] LHCb Collaboration, Differential branching fraction and angular analysis of the Bþ →Kþμþμ−decay, J. High Energy Phys. 02 (2013) 105. 112011-8 PHYS. REV. D 98, 112011 (2018) ANGULAR ANALYSIS OF THE DECAY Bþ … [30] CMS Collaboration, Angular analysis of the decay B0 → K0μþμ−from pp collisions at ﬃﬃﬃs p ¼ 8 TeV, Phys. Lett. B 753, 424 (2016). [19] LHCb Collaboration, Angular analysis of charged and neutral B →Kμþμ−decays, J. High Energy Phys. 05 (2014) 082. [20] CMS Collaboration, The CMS experiment at the CERN LHC, J. Instrum. 3, S08004 (2008). [31] G. J. Feldman and R. D. Cousins, A unified approach to the classical statistical analysis of small signals, Phys. Rev. D 57, 3873 (1998). [21] CMS Collaboration, The CMS trigger system, J. Instrum. 12, P01020 (2017). [32] S. Descotes-Genon, L. Hofer, J. Matias, and J. Virto, On the impact of power corrections in the prediction of B →Kμþμ−observables, J. High Energy Phys. 12 (2014) 125. [22] T. Sjöstrand, S. Mrenna, and P. Skands, PYTHIA 6.4 physics and manual, J. High Energy Phys. 05 (2006) 026. [23] D. J. Lange, The EvtGen particle decay simulation package, Nucl. Instrum. Methods Sect. A 462, 152 (2001). [33] S. Descotes-Genon, L. Hofer, J. Matias, and J. Virto, Global analysis of b →sll anomalies, J. High Energy Phys. 06 (2016) 092. [24] P. Golonka and Z. Was, PHOTOS monte carlo: A precision tool for QED corrections in Z and W decays, Eur. Phys. J. C 45, 97 (2006). [34] D. van Dyk et al., EOS—A HEP program for flavor observables (2016), https: //eos.github.io. [25] S. Agostinelli et al. (GEANT4 Collaboration), GEANT4—A simulation toolkit, Nucl. Instrum. Methods Sect. A 506, 250 (2003). [35] C. Bouchard, G. P. Lepage, C. Monahan, H. Na, and J. Shigemitsu (HPQCD Collaboration), Rare decay B → Klþl−form factors from lattice QCD, Phys. Rev. D 88, 054509 (2013); 88, 079901(E) (2013). [26] CMS Collaboration, Performance of CMS muon reconstruction in pp collision events at ﬃﬃﬃs p ¼ 7 TeV, J. Instrum. 7, P10002 (2012). [36] P. Ball and R. Zwicky, New results on B →π, K, η decay form factors from light-cone sum rules, Phys. Rev. D 71, 014015 (2005). [27] CMS Collaboration, Muon ID performance: low-pT muon efficiencies, CMS Detector Performance Report No. CMS- DP-2014-020 (CERN, 2014). [37] D. M. Straub, flavio: a Python package for flavour and precision phenomenology in the Standard Model and beyond, arXiv:1810.08132. A. M. Sirunyan,1 A. Tumasyan,1 W. Adam,2 F. Ambrogi,2 E. Asilar,2 T. Bergauer,2 J. Brandstetter,2 E. Brondolin,2 M. Dragicevic,2 J. Erö,2 A. Escalante Del Valle,2 M. Flechl,2 R. Frühwirth,2,b V. M. Ghete,2 J. Hrubec,2 M. Jeitler,2,b N. Krammer,2 I. Krätschmer,2 D. Liko,2 T. Madlener,2 I. Mikulec,2 N. Rad,2 H. Rohringer,2 J. Schieck,2,b R. Schöfbeck,2 M. Spanring,2 D. Spitzbart,2 A. Taurok,2 W. Waltenberger,2 J. Wittmann,2 C.-E. Wulz,2,b M. Zarucki,2 V. Chekhovsky,3 V. Mossolov,3 J. Suarez Gonzalez,3 E. A. De Wolf,4 D. Di Croce,4 X. Janssen,4 J. Lauwers,4 M. Pieters,4 M. Van De Klundert,4 H. Van Haevermaet,4 P. Van Mechelen,4 N. Van Remortel,4 S. Abu Zeid,5 F. Blekman,5 J. D’Hondt,5 I. De Bruyn,5 J. De Clercq,5 K. Deroover,5 G. Flouris,5 D. Lontkovskyi,5 S. Lowette,5 I. Marchesini,5 S. Moortgat,5 L. Moreels,5 Q. Python,5 K. Skovpen,5 S. Tavernier,5 W. Van Doninck,5 P. Van Mulders,5 I. Van Parijs,5 D. Beghin,6 B. Bilin,6 H. Brun,6 B. Clerbaux,6 G. De Lentdecker,6 H. Delannoy,6 B. Dorney,6 G. Fasanella,6 L. Favart,6 R. Goldouzian,6 A. Grebenyuk,6 A. K. Kalsi,6 T. Lenzi,6 J. Luetic,6 N. Postiau,6 E. Starling,6 L. Thomas,6 C. Vander Velde,6 P. Vanlaer,6 D. Vannerom,6 Q. Wang,6 T. Cornelis,7 D. Dobur,7 A. Fagot,7 M. Gul,7 I. Khvastunov,7,c D. Poyraz,7 C. Roskas,7 D. Trocino,7 M. Tytgat,7 W. Verbeke,7 B. Vermassen,7 M. Vit,7 N. Zaganidis,7 H. Bakhshiansohi,8 O. Bondu,8 S. Brochet,8 G. Bruno,8 C. Caputo,8 P. David,8 C. Delaere,8 M. Delcourt,8 B. Francois,8 A. Giammanco,8 G. Krintiras,8 V. Lemaitre,8 A. Magitteri,8 A. Mertens,8 M. Musich,8 K. Piotrzkowski,8 A. Saggio,8 M. Vidal Marono,8 S. Wertz,8 J. Zobec,8 F. L. Alves,9 G. A. Alves,9 L. Brito,9 G. Correia Silva,9 C. Hensel,9 A. Moraes,9 M. E. Pol,9 P. Rebello Teles,9 E. Belchior Batista Das Chagas,10 W. Carvalho,10 J. Chinellato,10,d E. Coelho,10 E. M. Da Costa,10 G. G. Da Silveira,10,e D. De Jesus Damiao,10 C. De Oliveira Martins,10 S. Fonseca De Souza,10 H. Malbouisson,10 D. Matos Figueiredo,10 M. Melo De Almeida,10 C. Mora Herrera,10 L. Mundim,10 H. Nogima,10 W. L. Prado Da Silva,10 L. J. Sanchez Rosas,10 A. Santoro,10 A. Sznajder,10 M. Thiel,10 E. J. Tonelli Manganote,10,d F. Torres Da Silva De Araujo,10 A. Vilela Pereira,10 S. Ahuja,11a C. A. Bernardes,11a L. Calligaris,11a T. R. Fernandez Perez Tomei,11a E. M. Gregores,11a,11b P. G. Mercadante,11a,11b S. F. Novaes,11a Sandra S. Padula,11a D. Romero Abad,11a,11b A. Aleksandrov,12 R. Hadjiiska,12 P. Iaydjiev,12 A. Marinov,12 M. Misheva,12 M. Rodozov,12 M. Shopova,12 G. Sultanov,12 A. Dimitrov,13 L. Litov,13 B. Pavlov,13 P. Petkov,13 W. Fang,14,f X. Gao,14,f L. Yuan,14 M. Ahmad,15 J. G. Bian,15 G. M. Chen,15 H. S. Chen,15 M. Chen,15 Y. Chen,15 C. H. Jiang,15 D. Leggat,15 H. Liao,15 Z. Liu,15 F. Romeo,15 S. M. Shaheen,15 A. Spiezia,15 J. Tao,15 C. Wang,15 Z. Wang,15 E. Yazgan,15 H. Zhang,15 J. Zhao,15 Y. Ban,16 G. Chen,16 A. Levin,16 J. Li,16 L. Li,16 Q. Li,16 Y. Mao,16 S. J. Qian,16 D. Wang,16 Z. Xu,16 Y. Wang,17 C. Avila,18 A. Cabrera,18 C. A. Carrillo Montoya,18 L. F. Chaparro Sierra,18 C. Florez,18 C. F. González Hernández,18 M. A. Segura Delgado,18 B. Courbon,19 N. Godinovic,19 D. Lelas,19 I. Puljak,19 T. Sculac,19 Z. Antunovic,20 M. Kovac,20 V. Brigljevic,21 D. Ferencek,21 K. Kadija,21 B. Mesic,21 A. Starodumov,21,g T. Susa,21 M. W. Ather,22 A. Attikis,22 M. Kolosova,22 G. Mavromanolakis,22 J. Mousa,22 C. Nicolaou,22 F. Ptochos,22 P. A. Razis,22 H. Rykaczewski,22 M. Finger,23,h M. Finger Jr.,23,h E. Ayala,24 E. Carrera Jarrin,25 A. Mahrous,26,i Y. Mohammed,26,j E. Salama,26,k,l S. Bhowmik,27 A. Carvalho Antunes De Oliveira,27 R. K. Dewanjee,27 K. Ehataht,27 M. Kadastik,27 M. Raidal,27 C. Veelken,27 P. Eerola,28 H. Kirschenmann,28 J. Pekkanen,28 M. Voutilainen,28 J. Havukainen,29 J. K. Heikkilä,29 T. Järvinen,29 V. Karimäki,29 R. Kinnunen,29 T. Lamp´en,29 K. Lassila-Perini,29 S. Laurila,29 S. Lehti,29 T. Lind´en,29 P. Luukka,29 T. Mäenpää,29 H. Siikonen,29 E. Tuominen,29 J. Tuominiemi,29 T. Tuuva,30 M. Besancon,31 F. Couderc,31 M. Dejardin,31 D. Denegri,31 J. L. Faure,31 F. Ferri,31 S. Ganjour,31 A. Givernaud,31 P. Gras,31 G. Hamel de Monchenault,31 P. Jarry,31 C. Leloup,31 E. Locci,31 J. Malcles,31 G. Negro,31 J. Rander,31 A. Rosowsky,31 M. Ö. Sahin,31 M. Titov,31 A. Abdulsalam,32,m C. Amendola,32 I. Antropov,32 F. Beaudette,32 P. Busson,32 C. Charlot,32 R. Granier de Cassagnac,32 I. Kucher,32 S. Lisniak,32 A. Lobanov,32 J. Martin Blanco,32 M. Nguyen,32 C. Ochando,32 G. Ortona,32 P. Pigard,32 R. Salerno,32 J. B. Sauvan,32 Y. Sirois,32 A. G. Stahl Leiton,32 A. Zabi,32 A. Zghiche,32 J.-L. Agram,33,n J. Andrea,33 D. Bloch,33 J.-M. Brom,33 E. C. Chabert,33 V. Cherepanov,33 C. Collard,33 E. Conte,33,n J.-C. Fontaine,33,n D. Gel´e,33 U. Goerlach,33 M. Jansová,33 A.-C. Le Bihan,33 N. Tonon,33 P. Van Hove,33 S. Gadrat,34 S. Beauceron,35 C. Bernet,35 G. Boudoul,35 N. Chanon,35 R. Chierici,35 D. Contardo,35 P. Depasse,35 H. El Mamouni,35 J. Fay,35 L. Finco,35 S. Gascon,35 M. Gouzevitch,35 G. Grenier,35 B. Ille,35 F. Lagarde,35 I. B. Laktineh,35 H. Lattaud,35 M. Lethuillier,35 L. Mirabito,35 A. L. Pequegnot,35 S. Perries,35 A. Popov,35,o V. Sordini,35 M. Vander Donckt,35 S. Viret,35 S. Zhang,35 T. Toriashvili,36,p I. Bagaturia,37,q C. Autermann,38 L. Feld,38 M. K. Kiesel,38 K. Klein,38 M. Lipinski,38 M. Preuten,38 M. P. Rauch,38 C. Schomakers,38 J. Schulz,38 M. Teroerde,38 B. Wittmer,38 V. Zhukov,38,o A. Albert,39 D. Duchardt,39 M. Endres,39 M. Erdmann,39 T. Esch,39 R. Fischer,39 S. Ghosh,39 A. Güth,39 T. Hebbeker,39 C. Heidemann,39 K. Hoepfner,39 H. Keller,39 S. Knutzen,39 L. Mastrolorenzo,39 M. Merschmeyer,39 A. Meyer,39 P. Millet,39 S. Mukherjee,39 T. Pook,39 M. Radziej,39 H. Reithler,39 M. Rieger,39 F. Scheuch,39 A. Schmidt,39 D. Teyssier,39 G. Flügge,40 O. Hlushchenko,40 B. Kargoll,40 T. Kress,40 A. Künsken,40 T. Müller,40 A. Nehrkorn,40 A. Nowack,40 C. Pistone,40 O. Pooth,40 H. Sert,40 A. Stahl,40,r M. Aldaya Martin,41 T. Arndt,41 C. Asawatangtrakuldee,41 I. Babounikau,41 K. Beernaert,41 O. Behnke,41 U. Behrens,41 A. Bermúdez Martínez,41 D. Bertsche,41 A. A. Bin Anuar,41 K. Borras,41,s V. Botta,41 A. Campbell,41 P. Connor,41 C. Contreras-Campana,41 F. Costanza,41 V. Danilov,41 A. De Wit,41 M. M. Defranchis,41 C. Diez Pardos,41 D. Domínguez Damiani,41 G. Eckerlin,41 T. Eichhorn,41 A. Elwood,41 E. Eren,41 E. Gallo,41,t A. Geiser,41 J. M. Grados Luyando,41 A. Grohsjean,41 P. Gunnellini,41 M. Guthoff,41 M. Haranko,41 A. Harb,41 41 41 41 41 41 41 41 41 41 VII. SUMMARY Leloup,31 E. Locci,31 J. Malcles,31 G. Negro,31 J. M. Ö. Sahin,31 M. Titov,31 A. Abdulsalam,32,m C. Amendola,32 I. Antropov,32 F. Beaudette,32 32 32 32 32 32 R. Granier de Cassagnac,32 I. Kucher,32 S. Lisniak,32 A. Lobanov,32 J. Martin Blanco,32 M. Nguyen,32 C. Ochando,32 G. Ortona,32 P. Pigard,32 R. Salerno,32 J. B. Sauvan,32 Y. Sirois,32 A. G. Stahl Leiton,32 A. Zabi,32 A. Zghiche,32 J.-L. Agram,33,n J. Andrea,33 D. Bloch,33 J.-M. Brom,33 E. C. Chabert,33 V. Cherepanov,33 C 33 33 33 33 33 33 S. Beauceron,35 C. Bernet,35 G. Boudoul,35 N. Chanon,35 R. Chierici,35 D. Contardo,35 P. Depasse,35 H. El Mamouni,35 J. Fay,35 L. Finco,35 S. Gascon,35 M. Gouzevitch,35 G. Grenier,35 B. Ille,35 F. Lagarde,35 I. B S. Zhang,35 T. Toriashvili,36,p I. Bagaturia,37,q C. Autermann,38 L. Feld,38 M. K. Kiesel,38 K. Klein,38 M. Lipinski,38 M. Preuten,38 M. P. Rauch,38 C. Schomakers,38 J. Schulz,38 M. Teroerde,38 B. Wittmer,38 V. Zhukov,38,o A. Albert,39 D. Duchardt,39 M. Endres,39 M. Erdmann,39 T. Esch,39 R. Fischer,39 S. Ghosh,39 A. Güth, K. Hoepfner,39 H. Keller,39 S. Knutzen,39 L. Mastrolorenzo,39 M. Merschmeyer,39 A. Meyer,39 P. Millet,39 S. Mukherjee,39 T. Pook,39 M. Radziej,39 H. Reithler,39 M. Rieger,39 F. Scheuch,39 A. Schmidt,39 D. Teyssier,39 G. Flügge,40 O. Hlushchenko,40 B. Kargoll,40 T. Kress,40 A. Künsken,40 T. Müller,40 A. Nehrkorn,40 A. Nowack,40 C. Pistone,40 O. Pooth,40 H. Sert,40 A. Stahl,40,r M. Aldaya Martin,41 T. Arndt,41 C. Asawatangtrakuldee,41 I. Babounikau,41 K. Beernaert,41 O. Behnke,41 U. Behrens,41 A. Bermúdez Martínez,41 D. Bertsche,41 A. A. Bin Anuar,41 K. Borras,41,s V. Botta,41 A. Campbell,41 P. Connor,41 C. Contreras-Campana,41 F. Costanza,41 V. Danilov,41 A. De Wit,41 M. M. Defranchis,41 C. Diez Pardos,41 D. Domínguez Damiani,41 G. Eckerlin,41 T. Eichhorn,41 A. Elwood,41 E. Eren,41 E. Gallo,41,t A. Geiser,41 J. M. Grados Luyando,41 A. Grohsjean,41 P. Gunnellini,41 M. Guthoff,4 J. Hauk,41 H. Jung,41 M. Kasemann,41 J. Keaveney,41 C. Kleinwort,41 J. Knolle,41 D. Krücker,41 W. Lange,41 A. Lelek,41 T. Lenz,41 K. Lipka,41 W. Lohmann,41,u R. Mankel,41 I.-A. Melzer-Pellmann,41 A. B. Meyer,41 M. Meyer,41 M. Missiroli,41 G. Mittag,41 J. Mnich,41 V. Myronenko,41 S. K. Pflitsch,41 D. Pitzl,41 A. Raspereza,41 M. Savitskyi,41 P. Saxena,41 P. Schütze,41 C. Schwanenberger,41 R. Shevchenko,41 A. Singh,41 N. Stefaniuk,41 H. Tholen,41 O. Turkot,41 A. Vagnerini,41 G. P. Van Onsem,41 R. Walsh,41 Y. Wen,41 K. Wichmann,41 C. Wissing,41 O. Zenaiev,41 R. Aggleton,42 S. Bein,42 L. Benato,42 A. Benecke,42 V. Blobel,42 M. Centis Vignali,42 T. Dreyer,42 E. Garutti,42 D. Gonzalez,42 J. Haller,42 G. Mittag, J. Mnich, V. Myronenko, S. K. VII. SUMMARY Pflitsch, D. Pitzl, A. Raspereza, M. Savitskyi, P. Saxena, P. Schütze,41 C. Schwanenberger,41 R. Shevchenko,41 A. Singh,41 N. Stefaniuk,41 H. Tholen,41 O. Turkot,41 A. Vagnerini,41 G. P. Van Onsem,41 R. Walsh,41 Y. Wen,41 K. Wichmann,41 C. Wissing,41 O. Zenaiev,41 R. Aggleton,42 S. Bein,42 L. Benato,42 A. Benecke,42 V. Blobel,42 M. Centis Vignali,42 T. Dreyer,42 E. Garutti,42 D. Gonzalez,42 J. Haller,42 A. Hinzmann,42 A. Karavdina,42 G. Kasieczka,42 R. Klanner,42 R. Kogler,42 N. Kovalchuk,42 S. Kurz,42 V. Kutzner,42 J. Lange,42 D. Marconi,42 J. Multhaup,42 M. Niedziela,42 D. Nowatschin,42 A. Perieanu,42 A. Reimers,42 O. Rieger,42 M. Stöver,42 D. Troendle,42 A. Vanhoefer,42 B. Vormwald,42 M. Akbiyik,43 C. Barth,43 M. Baselga,43 S. Baur,43 E. Butz,43 R. Caspart,43 T. Chwalek,43 F. Colombo,43 W. De Boer,43 A. Dierlamm,43 N. Faltermann,43 M. A. Harrendorf,43 F. Hartmann,43,r S. M. Heindl,43 U. Husemann,43 F. Kassel,43,r I. Katkov,43,o S. Kudella,43 H. Mildner,43 M. A. Harrendorf,43 F. Hartmann,43 VII. SUMMARY [28] CMS Collaboration, Angular analysis and branching frac- tion measurement of the decay B0 →K0μþμ−, Phys. Lett. B 727, 77 (2013). [38] J. A. Bailey et al. (Fermilab Lattice and MILC Collabora- tions), B →Klþl−decay form factors from three-flavor lattice QCD, Phys. Rev. D 93, 025026 (2016). [29] C. Patrignani et al. (Particle Data Group), Review of particle physics, Chin. Phys. C 40, 100001 (2016). A. M. Sirunyan,1 A. Tumasyan,1 W. Adam,2 F. Ambrogi,2 E. Asilar,2 T. Bergauer,2 J. Brandstetter,2 E. Brondolin,2 M D i i 2 J E ö 2 A E l t D l V ll 2 M Fl hl 2 R F üh i th 2,b V M Gh t 2 J H b 2 M J itl 2,b N. Krammer,2 I. Krätschmer,2 D. Liko,2 T. Madlener,2 I. Mikulec,2 N. Rad,2 H. Rohringer,2 J 2 2 2 2 2 2 b M. Spanring,2 D. Spitzbart,2 A. Taurok,2 W. Waltenberger,2 J. Wittmann,2 C.-E. Wulz,2,b M. Zarucki,2 V. Chekhovsky,3 V. Mossolov,3 J. Suarez Gonzalez,3 E. A. De Wolf,4 D. Di Croce,4 X. Janssen,4 J. Lauwers,4 M. Pieters,4 . Van De Klundert,4 H. Van Haevermaet,4 P. Van Mechelen,4 N. Van Remortel,4 S. Abu Zeid,5 F. . De Bruyn,5 J. De Clercq,5 K. Deroover,5 G. Flouris,5 D. Lontkovskyi,5 S. Lowette,5 I. Mar L. Moreels,5 Q. Python,5 K. Skovpen,5 S. Tavernier,5 W. Van Doninck,5 P. Van Mulders,5 I. V Bilin,6 H. Brun,6 B. Clerbaux,6 G. De Lentdecker,6 H. Delannoy,6 B. Dorney,6 G. Fasanella,6 L. A. Grebenyuk,6 A. K. Kalsi,6 T. Lenzi,6 J. Luetic,6 N. Postiau,6 E. Starling,6 L. Thomas,6 C. Vander Velde,6 P. Vanlaer,6 D. Vannerom,6 Q. Wang,6 T. Cornelis,7 D. Dobur,7 A. Fagot,7 M. Gul,7 I. Khvastunov,7,c D. Poyraz,7 C. Roskas,7 M. Melo De Almeida,10 C. Mora Herrera,10 L. Mundim,10 H. Nogima,10 W. L. Prado Da Silva,10 L. J. Sanchez Rosas,10 A. Santoro,10 A. Sznajder,10 M. Thiel,10 E. J. Tonelli Manganote,10,d F. Torres Da Silva De Araujo,10 A. Vilela Pereira,10 S. Ahuja,11a C. A. Bernardes,11a L. Calligaris,11a T. R. Fernandez Perez Tomei,11a E. M. Gregores,11a,11b 112011-9 PHYS. REV. D 98, 112011 (2018) A. M. SIRUNYAN et al. Y. Mohammed,26,j E. Salama,26,k,l S. Bhowmik,27 A. Carvalho Antunes De Oliveira,27 R. K. Dewanjee,27 K. Ehataht,27 M. Kadastik,27 M. Raidal,27 C. Veelken,27 P. Eerola,28 H. Kirschenmann,28 J. Pekkanen,28 M. Voutilainen,28 J. Havukainen,29 J. K. Heikkilä,29 T. Järvinen,29 V. Karimäki,29 R. Kinnunen,29 T. Lamp´en,29 K. Lassila-Perini,29 G. Hamel de Monchenault,31 P. Jarry,31 C. 112011-10 Lenzi,67a,67b M. Meschini,67a S. Paoletti,67a L. Russo,67a,ee G. Sguazzoni,67a D. Strom,67a L. Viliani,67a G. Latino,67a P. Lenzi,67a,67b M. Meschini,67a S. Paoletti,67a L. Russo,67a,ee G. Sguazzoni,67a L. Benussi,68 S. Bianco,68 F. Fabbri,68 D. Piccolo,68 F. Ferro,69a F. Ravera,69a,69b E. Robutti,69a S. Tosi,69a,69b A. Benaglia,70a A. Beschi,70a,70b L. Brianza,70a,70b F. Brivio,70a,70b V. Ciriolo,70a,70b,r S. Di Guida,70a,70b,r M. E. Dinardo,70a,70b S. Fiorendi,70a,70b S. Gennai,70a A. Ghezzi,70a,70b P. Govoni,70a,70b M. Malberti,70a,70b S. Malvezzi,70a A. Massironi,70a,70b 70 70 70 70b 70 70 70b 70 70b L. Benussi,68 S. Bianco,68 F. Fabbri,68 D. Piccolo,68 F. Ferro,69a F. Ravera,69a,69b E. Robutti,69a S. Tosi,69a,69b A. Benaglia,70a A. Beschi,70a,70b L. Brianza,70a,70b F. Brivio,70a,70b V. Ciriolo,70a,70b,r S. Di Guida,70a,70b,r M. E. Dinardo,70a,70b 70 70b 70 70 70b 70 70b 70 70b 70 70 70b S. Fiorendi,70a,70b S. Gennai,70a A. Ghezzi,70a,70b P. Govoni,70a,70b M. Malberti,70a,70b S. Malvezzi,70a A. Massironi,70a,70b D. Menasce,70a L. Moroni,70a M. Paganoni,70a,70b D. Pedrini,70a S. Ragazzi,70a,70b T. Tabarelli de Fatis,70a,70b S. Fiorendi, S. Gennai, A. Ghezzi, P. Govoni, M. Malberti, S. Malvezzi, A. Massironi, D. Menasce,70a L. Moroni,70a M. Paganoni,70a,70b D. Pedrini,70a S. Ragazzi,70a,70b T. Tabarelli de Fatis,70a,70b D. Menasce,70a L. Moroni,70a M. Paganoni,70a,70b D. Pedrini,70a S. Ragazzi,70a,70b T. Tabarelli de Fatis,70a,70b S Buontempo 71a N Cavallo 71a,71c A Di Crescenzo 71a,71b F Fabozzi 71a,71c F Fienga 71a G Galati 71a A O M Iorio 71a,71b S. Buontempo,71a N. Cavallo,71a,71c A. Di Crescenzo,71a,71b F. Fabozzi,71a,71c F. Fienga,71a G. Ga W. A. Khan,71a L. Lista,71a S. Meola,71a,71d,r P. Paolucci,71a,r C. Sciacca,71a,71b E. Voevodina,71a,71b P. Azzi,72a N. Bacchetta,72a D Bisello 72a,72b A Boletti 72a,72b A Bragagnolo 72a R Carlin 72a,72b P Checchia 72a M Dall’Osso 72a,72b W. A. Khan, L. Lista, S. Meola, , , P. Paolucci, , C. Sciacca, , E. Voevodina, , P. Azzi, N. Bacchetta, D. Bisello,72a,72b A. Boletti,72a,72b A. Bragagnolo,72a R. Carlin,72a,72b P. Checchia,72a M. Dall’Osso,72a,72b P. De Castro Manzano,72a T. Dorigo,72a F. Gasparini,72a,72b U. Gasparini,72a,72b S. Lacaprara,72a P. Lujan,72a M. Margoni,72a,72b A. T. Meneguzzo,72a,72b N. Pozzobon,72a,72b P. Ronchese,72a,72b R. Rossin,72a,72b F. Simonetto,72a,72b A. Tiko,72a E. Torassa,72a S. Ventura,72a M. Zanetti,72a,72b P. Zotto,72a,72b G. Zumerle,72a,72b A. Braghieri,73a A. Magnani,73a P. De Castro Manzano,72a T. Dorigo,72a F. Gasparini,72a,72b U. Gasparini,72a,72b S. Lacaprara,72a P. Lujan,72a M. Margoni,72a,72b A. T. Meneguzzo,72a,72b N. Pozzobon,72a,72b P. Ronchese,72a,72b R. Rossin,72a,72b F. Simonetto,72a,72b A. Tiko,72a E. Torassa,72a S. Ventura,72a M. Zanetti,72a,72b P. Zotto,72a,72b G. Zumerle,72a,72b A. Braghieri,73a A. Magnani,73a g g P. Montagna,73a,73b S. P. Ratti,73a,73b V. Re,73a M. Ressegotti,73a,73b C. Riccardi,73a,73b P. 112011-10 Codispoti,65a,65b M. Cuffiani,65a,65b 61 V. Hegde,61 A. Kapoor,61 K. Kothekar,61 S. Pandey,61 A. Rane,61 S. Sharma,61 S. Chenaran S. Dube,61 V. Hegde,61 A. Kapoor,61 K. Kothekar,61 S. Pandey,61 A. Rane,61 S. Sharma,61 S. Chenarani,62,cc E. Eskandari Tadavani,62 S. M. Etesami,62,cc M. Khakzad,62 M. Mohammadi Najafabadi,62 M. Naseri,62 F. Rezaei Hosseinabadi,62 B. Safarzadeh,62,dd M. Zeinali,62 M. Felcini,63 M. Grunewald,63 M. Abbrescia,64a,64b C. Calabria,64a,64b A. Colaleo,64a D. Creanza,64a,64c L. Cristella,64a,64b N. De Filippis,64a,64c M. De Palma,64a,64b A Di Florio 64a,64b F Errico 64a,64b L Fiore 64a A Gelmi 64a,64b G Iaselli 64a,64c S Lezki 64a,64b G Maggi 64a,64c M Maggi 64a kandari Tadavani,62 S. M. Etesami,62,cc M. Khakzad,62 M. Mohammadi Najafabadi,62 M. Naser G. Selvaggi,64a,64b A. Sharma,64a L. Silvestris,64a,r R. Venditti,64a P. Verwilligen,64a G. Zito,64a G. Abbiendi,65a C. Battilana,65a,65b D. Bonacorsi,65a,65b L. Borgonovi,65a,65b S. Braibant-Giacomelli,65a,65b R. Campanini,65a,65b G. Se vagg , . S a a, . S vest s, . Ve d tt , . Ve w ge , G. to, G. bb e d , C. Battilana,65a,65b D. Bonacorsi,65a,65b L. Borgonovi,65a,65b S. Braibant-Giacomelli,65a,65b R. Campanini,65a,65b 65 65b 65 65b 65 65 65b 65 65 65b 65 65b C. Battilana,65a,65b D. Bonacorsi,65a,65b L. Borgonovi,65a,65b S. Braibant-Giacomelli,65a,65b R. Campanini,65a,65b P. Capiluppi,65a,65b A. Castro,65a,65b F. R. Cavallo,65a S. S. Chhibra,65a,65b C. Ciocca,65a G. Codispoti,65a,65b M. Cuffiani,65a,65b C. Battilana,65a,65b D. Bonacorsi,65a,65b L. Borgonovi,65a,65b S. Braibant-Giacomelli,65a,65b R. Campanini,65a,65b P. Capiluppi,65a,65b A. Castro,65a,65b F. R. Cavallo,65a S. S. Chhibra,65a,65b C. Ciocca,65a G. Codispoti,65a,65b M. Cuffiani,65a,65b p pp G. M. Dallavalle,65a F. Fabbri,65a A. Fanfani,65a,65b P. Giacomelli,65a C. Grandi,65a L. Gu G. M. Dallavalle,65a F. Fabbri,65a A. Fanfani,65a,65b P. Giacomelli,65a C. Grandi,65a L. Guiducci,65a,65b F. Iemmi,65a,65b G. Masetti,65a A. Montanari,65a F. L. Navarria,65a,65b A. Perrotta,65a F. Primavera,65a,65b,r A. M. Ro S. Marcellini, G. Masetti, A. Montanari, F. L. Navarria, , A. Perrotta, F. Primavera, , , A. M. Rossi, , T. Rovelli,65a,65b G. P. Siroli,65a,65b N. Tosi,65a S. Albergo,66a,66b A. Di Mattia,66a R. Potenza,66a,66b A. Tricomi,66a,66b C Tuve 66a,66b G Barbagli 67a K Chatterjee 67a,67b V Ciulli 67a,67b C Civinini 67a R D’Alessandro 67a,67b E Focardi 67a,67b , , , , , , , T. Rovelli,65a,65b G. P. Siroli,65a,65b N. Tosi,65a S. Albergo,66a,66b A. Di Mattia,66a R. Potenza,66a,66b A. Tricomi,66a,66b C T 66a 66b G B b li 67a K Ch j 67a 67b V Ci lli 67a 67b C Ci i i i 67a R D’Al d 67a 67b E F di 67a 67b G. Latino,67a P. 112011-10 Salvini,73a I. Vai,73a,73b P. Vitulo,73a,73b L. Alunni Solestizi,74a,74b M. Biasini,74a,74b G. M. Bilei,74a C. Cecchi,74a,74b D. Ciangottini,74a,74b L. Fanò,74a,74b P. Lariccia,74a,74b E. Manoni,74a G. Mantovani,74a,74b V. Mariani,74a,74b M. Menichelli,74a A. Rossi,74a,74b A. Santocchia,74a,74b 74 75 75 75 75 75 75 75 D. Spiga,74a K. Androsov,75a P. Azzurri,75a G. Bagliesi,75a L. Bianchini,75a T. Boccali,75a L. Borrello,75a R. Castaldi,75a M. A. Ciocci,75a,75b R. Dell’Orso,75a G. Fedi,75a F. Fiori,75a,75c L. Giannini,75a,75c A. Giassi,75a M. T. Grippo,75a F. Ligabue,75a,75c E. Manca,75a,75c G. Mandorli,75a,75c A. Messineo,75a,75b F. Palla,75a A. Rizzi,75a,75b P. Spagnolo,75a D. Spiga, K. Androsov, P. Azzurri, G. Bagliesi, L. Bianchini, T. Boccali, L. Borrello, R. Castaldi, M. A. Ciocci,75a,75b R. Dell’Orso,75a G. Fedi,75a F. Fiori,75a,75c L. Giannini,75a,75c A. Giassi,75a M. T. Grippo,75a 75a 75c 75a 75c 75a 75c 75a 75b 75a 75a 75b 75a R. Tenchini,75a G. Tonelli,75a,75b A. Venturi,75a P. G. Verdini,75a L. Barone,76a,76b F. Cavallari,76a M. Cipriani,76a,76b N. Daci,76a 76 76b 76 76b 76 76 76b 76 76b 76 76b 76 D. Del Re,76a,76b E. Di Marco,76a,76b M. Diemoz,76a S. Gelli,76a,76b E. Longo,76a,76b B. Marzo g G. Organtini,76a,76b F. Pandolfi,76a R. Paramatti,76a,76b F. Preiato,76a,76b S. Rahatlou,76a,76b C. Rovelli,76a F. Santanastasio,76a,76b N. Amapane,77a,77b R. Arcidiacono,77a,77c S. Argiro,77a,77b M. Arneodo,77a,77c N. Bartosik,77a R. Bellan,77a,77b C. Biino,77a G. Organtini,76a,76b F. Pandolfi,76a R. Paramatti,76a,76b F. Preiato,76a,76b S. Rahatlou,76a,76b C. Rovelli,76a F. Santanastasio,76a,76b N. Amapane,77a,77b R. Arcidiacono,77a,77c S. Argiro,77a,77b M. Arneodo,77a,77c N. Bartosik,77a R 112011-11 112011-10 112011-10 PHYS. REV. D 98, 112011 (2018) ANGULAR ANALYSIS OF THE DECAY Bþ … C. Hajdu,49 D. Horvath,49,w Á. Hunyadi,49 F. Sikler,49 T. Á. Vámi,49 V. Veszpremi,49 G. Vesztergombi,49,a,v N. Beni,50 S. Czellar,50 J. Karancsi,50,x A. Makovec,50 J. Molnar,50 Z. Szillasi,50 P. Raics,51 Z. L. Trocsanyi,51 B. Ujvari,51 52 52 52 53 y 53 53 53 53 z S. Sharma,54 J. B. Singh,54 G. Walia,54 A. Bhardwaj,55 B. C. Choudhary,55 R. B. Garg,55 M. Gola,55 S. Keshri,55 Ashok Kumar,55 S. Malhotra,55 M. Naimuddin,55 P. Priyanka,55 K. Ranjan,55 Aashaq Shah,55 R. Sharma,55 R. Bhardwaj,56,aa M. Bharti,56 R. Bhattacharya,56 S. Bhattacharya,56 U. Bhawandeep,56,aa D. Bhowmik,56 S. Dey,56 S. Dutt,56,aa S. Dutta,56 , g , , j, y, g, , , Ashok Kumar,55 S. Malhotra,55 M. Naimuddin,55 P. Priyanka,55 K. Ranjan,55 Aashaq Shah,55 R. Sharma,55 R. Bhardwaj,56,aa M. Bharti,56 R. Bhattacharya,56 S. Bhattacharya,56 U. Bhawandeep,56,aa D. Bhowmik,56 S. Dey,56 S. Dutt,56,aa S. Dutta,56 S. Ghosh,56 K. Mondal,56 S. Nandan,56 A. Purohit,56 P. K. Rout,56 A. Roy,56 S. Roy Chowdhury,56 S. Sarkar,56 M. Sharan,56 B. Singh,56 S. Thakur,56,aa P. K. Behera,57 R. Chudasama,58 D. Dutta,58 V. Jha,58 V. Kumar,58 P. K. Netrakanti,58 L. M. Pant,58 P. Shukla,58 T. Aziz,59 M. A. Bhat,59 S. Dugad,59 G. B. Mohanty,59 N. Sur,59 B. Sutar,59 Ravindra Kumar Verma 59 S Banerjee 60 S Bhattacharya 60 S Chatterjee 60 P Das 60 M Guchait 60 Sa Jain 60 Ravindra Kumar Verma, S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S. Karmakar,60 S. Kumar,60 M. Maity,60,bb G. Majumder,60 K. Mazumdar,60 N. Sahoo,60 T. Sarkar,60,bb S. Chauhan,61 S. Karmakar, S. Kumar, M. Maity, G. Majumder, K. Mazumdar, N. Sahoo, T. Sarkar, S. Chauhan, S. Dube,61 V. Hegde,61 A. Kapoor,61 K. Kothekar,61 S. Pandey,61 A. Rane,61 S. Sharma,61 S. Chenarani,62,cc E. Eskandari Tadavani,62 S. M. Etesami,62,cc M. Khakzad,62 M. Mohammadi Najafabadi,62 M. Naseri,62 F. Rezaei Hosseinabadi,62 B. Safarzadeh,62,dd M. Zeinali,62 M. Felcini,63 M. Grunewald,63 M. Abbrescia,64a,64b C. Calabria,64a,64b A. Colaleo,64a D. Creanza,64a,64c L. Cristella,64a,64b N. De Filippis,64a,64c M. De Palma,64a,64b A. Di Florio,64a,64b F. Errico,64a,64b L. Fiore,64a A. Gelmi,64a,64b G. Iaselli,64a,64c S. Lezki,64a,64b G. Maggi,64a,64c M. Maggi,64a G. Miniello,64a,64b S. My,64a,64b S. Nuzzo,64a,64b A. Pompili,64a,64b G. Pugliese,64a,64c R. Radogna,64a A. Ranieri,64a G. Selvaggi,64a,64b A. Sharma,64a L. Silvestris,64a,r R. Venditti,64a P. Verwilligen,64a G. Zito,64a G. Abbiendi,65a C. Battilana,65a,65b D. Bonacorsi,65a,65b L. Borgonovi,65a,65b S. Braibant-Giacomelli,65a,65b R. Campanini,65a,65b P. Capiluppi,65a,65b A. Castro,65a,65b F. R. Cavallo,65a S. S. Chhibra,65a,65b C. Ciocca,65a G. 112011-11 112011-11 PHYS. REV. D 98, 112011 (2018) A. M. SIRUNYAN et al. N. Cartiglia,77a F. Cenna,77a,77b S. Cometti,77a M. Costa,77a,77b R. Covarelli,77a,77b N. Demaria,77a B. Kiani,77a,77b C. Mariotti,77a S. Maselli,77a E. Migliore,77a,77b V. Monaco,77a,77b E. Monteil,77a,77b M. Monteno,77a M. M. Obertino,77a,77b , , , , , , y , , g, , , , S. Lee,82 J. Lim,82 S. K. Park,82 Y. Roh,82 H. S. Kim,83 J. Almond,84 J. Kim,84 J. S. Kim,84 H. Lee,84 K. Lee,84 K. Nam,84 y g S. Lee,82 J. Lim,82 S. K. Park,82 Y. Roh,82 H. S. Kim,83 J. Almond,84 J. Kim,84 J. S. Kim,84 H. Lee,84 K. Lee,84 K. Nam,84 S. B. Oh,84 B. C. Radburn-Smith,84 S. h. Seo,84 U. K. Yang,84 H. D. Yoo,84 G. B. Yu,84 D. Jeon,85 H. Kim,85 J. H. Kim,85 85 85 86 86 86 86 87 87 87 88 g g Z. A. Ibrahim,88 M. A. B. Md Ali,88,ff F. Mohamad Idris,88,gg W. A. T. Wan Abdullah,88 M. N. Yusli,88 Z. Zolkapli,88 A. Castaneda Hernandez,89 J. A. Murillo Quijada,89 H. Castilla-Valdez,90 E. De La Cruz-Bure Q j I. Heredia-De La Cruz,90,hh R. Lopez-Fernandez,90 J. Mejia Guisao,90 R. I. Rabadan-Trejo,90 G. Ramirez-Sanchez,90 I. Heredia-De La Cruz,90,hh R. Lopez-Fernandez,90 J. Mejia Guisao,90 R. I. Rabadan-Trejo,90 G R. Reyes-Almanza,90 A. Sanchez-Hernandez,90 S. Carrillo Moreno,91 C. Oropeza Barrera,91 F R. Reyes Almanza, A. Sanchez Hernandez, S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia, J. Eysermans,92 I. Pedraza,92 H. A. Salazar Ibarguen,92 C. Uribe Estrada,92 A. Morelos Pineda,93 D. Krofcheck,94 J. Eysermans,92 I. Pedraza,92 H. A. Salazar Ibarguen,92 C. Uribe Estrada,92 A. Morelos Pineda,93 D. Krofcheck,94 S Bh 95 P H B l 95 A Ah d 96 M Ah d 96 M I A h 96 Q H 96 H R H i 96 A S ddi 96 J. Eysermans,92 I. Pedraza,92 H. A. Salazar Ibarguen,92 C. Uribe Estrada,92 A. Morelos Pineda,93 D. Krofcheck,94 S. Bheesette,95 P. H. Butler,95 A. Ahmad,96 M. Ahmad,96 M. I. Asghar,96 Q. Hassan,96 H. R. Hoorani,96 A. Saddique,96 g q M. A. Shah,96 M. Shoaib,96 M. Waqas,96 H. Bialkowska,97 M. Bluj,97 B. Boimska,97 T. Frueboes,97 M. Górski,97 M. Kazana,97 K. Nawrocki,97 M. Szleper,97 P. Traczyk,97 P. Zalewski,97 K. Bunkowski,98 A A. Kalinowski,98 M. Konecki,98 J. Krolikowski,98 M. Misiura,98 M. Olszewski,98 A. Pyskir,98 M. Walczak,98 P. Bargassa,99 C. Beirão Da Cruz E Silva,99 A. Di Francesco,99 P. Faccioli,99 B. Galinhas,99 M. Gallinaro,99 J. Hollar,99 N. Leonardo,99 L. 112011-11 Gavrilov,103 N. Lychkovskaya,103 , , , p , p y , , y y , V. Popov,103 I. Pozdnyakov,103 G. Safronov,103 A. Spiridonov,103 A. Stepennov,103 V. Stolin,103 M. Toms,103 E. Vlasov,103 A. Zhokin,103 T. Aushev,104 R. Chistov,105,nn M. Danilov,105,nn P. Parygin,105 D. Philippov,105 S. Polikarpov,105,nn V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, A. Stepennov, V. Stolin, M. Toms, E. Vlasov, A. Zhokin,103 T. Aushev,104 R. Chistov,105,nn M. Danilov,105,nn P. Parygin,105 D. Philippov,105 S. Polikarpov,105,nn A. Zhokin,103 T. Aushev,104 R. Chistov,105,nn M. Danilov,105,nn P. Parygin,105 D. Philippov,105 S. Polikarpov,105,nn A. Baskakov,107 A. Belyaev,107 E. Boos,107 M. Dubinin,107,oo L. Dudko,107 A. Ershov,107 A. Gribushin,107 V. Klyukhin,107 107 107 107 107 107 107 107 108 O. Kodolova,107 I. Lokhtin,107 I. Miagkov,107 S. Obraztsov,107 S. Petrushanko,107 V. Savrin,107 A. Snigirev,107 V. Blinov,108,pp T. Dimova,108,pp L. Kardapoltsev,108,pp D. Shtol,108,pp Y. Skovpen,108,pp I. Azhgirey,109 I. Bayshev,109 S. Bitioukov,109 D. Elumakhov,109 A. Godizov,109 V. Kachanov,109 A. Kalinin,109 D. Konstantinov,109 P. Mandrik,109 V. Petrov,109 R. Ryutin,109 S. Slabospitskii,109 A. Sobol,109 S. Troshin,109 N. Tyurin,109 A. Uzunian,109 A. Volkov,109 A. Babaev,110 S Baidali 110 P Adzic 111,qq P Cirkovic 111 D Devetak 111 M Dordevic 111 J Milosevic 111 J Alcaraz Maestre 112 O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, S. Petrushanko, V. Savrin, A. Snigirev, V. Blinov, T. Dimova,108,pp L. Kardapoltsev,108,pp D. Shtol,108,pp Y. Skovpen,108,pp I. Azhgirey,109 I. Bayshev,109 S. Bitioukov,109 109 109 109 109 109 109 109 D. Elumakhov,109 A. Godizov,109 V. Kachanov,109 A. Kalinin,109 D. Konstantinov,109 P. Mandrik,109 V. Petrov,109 R. Ryutin,109 S. Slabospitskii,109 A. Sobol,109 S. Troshin,109 N. Tyurin,109 A. Uzunian,109 A. Volkov,109 A. Babaev,110 110 111 qq 111 111 111 111 112 S. Baidali, P. Adzic, qq P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, J. Alcaraz Maestre, A. Álvarez Fernández,112 I. Bachiller,112 M. Barrio Luna,112 J. A. Brochero Cifuentes,112 M. Cerrada,112 N. Colino,112 B. De La Cruz,112 A. Delgado Peris,112 C. Fernandez Bedoya,112 J. P. Fernández Ramos,112 J. Flix,112 M. C. Fouz,112 O. Gonzalez Lopez,112 S. Goy Lopez,112 J. M. Hernandez,112 M. I. Josa,112 D. Moran,112 A. P´erez-Calero Yzquierdo,112 J P P l 112 I R d d 112 L R 112 M S S 112 A T i i 112 C Alb j 113 J F d T ó i 113 B. De La Cruz, A. Delgado Peris, C. Fernandez Bedoya, J. P. Fernández Ramos, J. Flix, M. C. Fouz, O. Gonzalez Lopez,112 S. Goy Lopez,112 J. M. Hernandez,112 M. 112011-11 Lloret Iglesias,99 M. V. Nemallapudi,99 J. Seixas,99 G. Strong,99 O. Toldaiev,99 D. Vadruccio,99 J. Varela,99 A. Baginyan,100 I. Golutvin,100 V. Karjavin,100 I. Kashunin,100 V. Korenkov,100 G. Kozlov,100 A. Lanev,100 A. Malakhov,100 V. Matveev,100,jj,kk V. V. Mitsyn,100 P. Moisenz,100 V. Palichik,100 V. Perelygin,100 S. Shmatov,100 N. Skatchkov,100 V. Smirnov,100 V. Trofimov,100 A. Zarubin,100 V. Zhiltsov,100 V. Golovtsov,101 Y. Ivanov,101 V. Kim,101,ll E. Kuznetsova,101,mm C. Beirão Da Cruz E Silva, A. Di Francesco, P. Faccioli, B. Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias,99 M. V. Nemallapudi,99 J. Seixas,99 G. Strong,99 O. Toldaiev,99 D. Vadruccio,99 J. Varela,99 C. Beirão Da Cruz E Silva, A. Di Francesco, P. Faccioli, B. Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias,99 M. V. Nemallapudi,99 J. Seixas,99 G. Strong,99 O. Toldaiev,99 D. Vadruccio,99 J. Varela,99 A. Baginyan,100 I. Golutvin,100 V. Karjavin,100 I. Kashunin,100 V. Korenkov,100 G. Kozlov,100 A. Lanev,100 A. Malakhov,100 V. Matveev,100,jj,kk V. V. Mitsyn,100 P. Moisenz,100 V. Palichik,100 V. Perelygin,100 S. Shmatov,100 N. Skatchkov,100 L. Lloret Iglesias, M. V. Nemallapudi, J. Seixas, G. Strong, O. Toldaiev, D. Vadruccio, J. Varela, A. Baginyan,100 I. Golutvin,100 V. Karjavin,100 I. Kashunin,100 V. Korenkov,100 G. Kozlov,100 A. Lanev,100 A. Malakhov,100 V. Matveev,100,jj,kk V. V. Mitsyn,100 P. Moisenz,100 V. Palichik,100 V. Perelygin,100 S. Shmatov,100 N. Skatchkov,100 V. Smirnov,100 V. Trofimov,100 A. Zarubin,100 V. Zhiltsov,100 V. Golovtsov,101 Y. Ivanov,101 V. Kim,101,ll E. Kuznetsova,101,mm g y , , j , , , , , , V. Matveev,100,jj,kk V. V. Mitsyn,100 P. Moisenz,100 V. Palichik,100 V. Perelygin,100 S. Shmatov,100 N. Skatchkov,100 V Smirnov 100 V Trofimov 100 A Zarubin 100 V Zhiltsov 100 V Golovtsov 101 Y Ivanov 101 V Kim 101,ll E Kuznetsova 101,mm V. Matveev,100,jj,kk V. V. Mitsyn,100 P. Moisenz,100 V. Palichik,100 V. Perelygin,100 S. Shmatov,100 N. Skatchkov,100 P. Levchenko,101 V. Murzin,101 V. Oreshkin,101 I. Smirnov,101 D. Sosnov,101 V. Sulimov,101 L. Uvarov,101 S. Vavilov,101 A. Vorobyev,101 Yu. Andreev,102 A. Dermenev,102 S. Gninenko,102 N. Golubev,102 A. Karneyeu,102 M. Kirsanov,102 N. Krasnikov,102 A. Pashenkov,102 D. Tlisov,102 A. Toropin,102 V. Epshteyn,103 V. Gavrilov,103 N. Lychkovskaya,103 P. Levchenko,101 V. Murzin,101 V. Oreshkin,101 I. Smirnov,101 D. Sosnov,101 V. Sulimov,101 L. Uvarov,101 S. Vavilov,101 101 102 102 102 102 102 102 A. Vorobyev,101 Yu. Andreev,102 A. Dermenev,102 S. Gninenko,102 N. Golubev,102 A. Karneyeu,102 M. Kirsanov,102 N. Krasnikov,102 A. Pashenkov,102 D. Tlisov,102 A. Toropin,102 V. Epshteyn,103 V. Gavrilov,103 N. Lychkovskaya,103 y y N. Krasnikov,102 A. Pashenkov,102 D. Tlisov,102 A. Toropin,102 V. Epshteyn,103 V. J. Cuevas, C. Erice, J. Fernandez Menendez, S. Folgueras, I. Gonzalez Caballero, J. R. González Fernández, E. Palencia Cortezon,114 V. Rodríguez Bouza,114 S. Sanchez Cruz,114 P. Vischia,114 J. M. Vizan Garcia,114 I. J. Cabrillo,115 A. Calderon,115 B. Chazin Quero,115 J. Duarte Campderros,115 M. Fernandez,115 P. J. Fernández Manteca,115 A. García Alonso,115 J. Garcia-Ferrero,115 G. Gomez,115 A. Lopez Virto,115 J. Marco,115 C. Martinez Rivero,115 P. Martinez Ruiz del Arbol,115 F. Matorras,115 J. Piedra Gomez,115 C. Prieels,115 T. Rodrigo,115 A. Ruiz-Jimeno,115 L. Scodellaro,115 N. Trevisani,115 I. Vila,115 R. Vilar Cortabitarte,115 D. Abbaneo,116 B. Akgun,116 E. Auffray,116 P. Baillon,116 A. H. Ball,116 D. Barney,116 J. Bendavid,116 M. Bianco,116 A. Bocci,116 C. Botta,116 T. Camporesi,116 M. Cepeda,116 G. Cerminara,116 E. Chapon,116 Y. Chen,116 G. Cucciati,116 D. d’Enterria,116 A. Dabrowski,116 V. Daponte,116 A. David,116 A. De Roeck,116 N. Deelen,116 M. Dobson,116 T. du Pree,116 M. Dünser,116 N. Dupont,116 A. Elliott-Peisert,116 112011-11 Brzhechko,119 M F Canelli 119 A De Cosa 119 R Del B rgo 119 S Donato 119 C Galloni 119 T Hre s 119 B Kilminster 119 I Ne telings 119 D. Pinna,119 G. Rauco,119 P. Robmann,119 D. Salerno,119 K. Schweiger,119 C. Seitz,119 Y. Takahashi,119 A. Zucchetta,119 Y. H. Chang, K. y. Cheng, T. H. Doan, Sh. Jain, R. Khurana, C. M. Kuo, W. Lin, A. Pozdnyakov, S. S. Yu,120 P. Chang,121 Y. Chao,121 K. F. Chen,121 P. H. Chen,121 W.-S. Hou,121 Arun Kumar,121 Y. y. Li,121 R.-S. Lu,121 S. S. Yu,120 P. Chang,121 Y. Chao,121 K. F. Chen,121 P. H. Chen,121 W.-S. Hou,121 Arun Kumar,121 Y. y. Li,121 R.-S. Lu,121 S. S. Yu,120 P. Chang,121 Y. Chao,121 K. F. Chen,121 P. H. Chen,121 W.-S. Hou,121 Arun Kumar,121 Y. y. Li,121 R.-S. Lu,121 E. Paganis,121 A. Psallidas,121 A. Steen,121 J. f. Tsai,121 B. Asavapibhop,122 N. Srimanobhas,122 N. Suwonjandee,122 A. Bat,123 F. Boran,123 S. Cerci,123,yy S. Damarseckin,123 Z. S. Demiroglu,123 F. Dolek,123 C. Dozen,123 I. Dumanoglu,123 S. Girgis,123 G. Gokbulut,123 Y. Guler,123 E. Gurpinar,123 I. Hos,123,zz C. Isik,123 E. E. Kangal,123,aaa O. Kara,123 g p g A. Kayis Topaksu,123 U. Kiminsu,123 M. Oglakci,123 G. Onengut,123 K. Ozdemir,123,bbb S. Ozturk,123,ccc D. Sunar Cerci,123,yy B. Tali,123,yy U. G. Tok,123 S. Turkcapar,123 I. S. Zorbakir,123 C. Zorbilmez,123 B. Isildak,124,ddd G. Karapinar,124,eee p p M. Yalvac,124 M. Zeyrek,124 I. O. Atakisi,125 E. Gülmez,125 M. Kaya,125,fff O. Kaya,125,ggg S. Tekten,125 E. A. Yetkin,125,hhh M. N. Agaras,126 S. Atay,126 A. Cakir,126 K. Cankocak,126 Y. Komurcu,126 S. Sen,126,iii B. Grynyov,127 L. Levchuk,128 F. Ball,129 L. Beck,129 J. J. Brooke,129 D. Burns,129 E. Clement,129 D. Cussans,129 O. Davignon,129 H. Flacher,129 , , , , , , g , , J. Goldstein,129 G. P. Heath,129 H. F. Heath,129 L. Kreczko,129 D. M. Newbold,129,jjj S. Paramesvaran,129 B. Penning,129 T. Sakuma,129 D. Smith,129 V. J. Smith,129 J. Taylor,129 A. Titterton,129 K. W. Bell,130 A. Belyaev,130,kkk C. Brew,130 , , , , , , J. Goldstein,129 G. P. Heath,129 H. F. Heath,129 L. Kreczko,129 D. M. Newbold,129,jjj S. Param , , , , , , g, T. Sakuma,129 D. Smith,129 V. J. Smith,129 J. Taylor,129 A. Titterton,129 K. W. Bell,130 A. Belyaev,130,kkk C. Brew,130 T. Sakuma,129 D. Smith,129 V. J. Smith,129 J. Taylor,129 A. Titterton,129 K. W. Bell,130 A. B R. M. Brown,130 D. Cieri,130 D. J. A. Cockerill,130 J. A. Coughlan,130 K. Harder,130 S. Harper,130 J. Linacre,130 E. Olaiya,130 D. Petyt,130 C. 112011-11 I. Josa,112 D. Moran,112 A. P´erez-Calero Yzquierdo,112 J. Puerta Pelayo,112 I. Redondo,112 L. Romero,112 M. S. Soares,112 A. Triossi,112 C. Albajar,113 J. F. de Trocóniz,113 E. Palencia Cortezon,114 V. Rodríguez Bouza,114 S. Sanchez Cruz,114 P. Vischia,114 J. M. Vizan Garcia,114 I. J. Cabrillo,115 A. Calderon,115 B. Chazin Quero,115 J. Duarte Campderros,115 M. Fernandez,115 P. J. Fernández Manteca,115 A. García Alonso,115 J. Garcia-Ferrero,115 G. Gomez,115 A. Lopez Virto,115 J. Marco,115 C. Martinez Rivero,115 P. Martinez Ruiz del Arbol,115 F. Matorras,115 J. Piedra Gomez,115 C. Prieels,115 T. Rodrigo,115 A. Ruiz-Jimeno,115 L. Scodellaro,115 N. Trevisani,115 I. Vila,115 R. Vilar Cortabitarte,115 D. Abbaneo,116 B. Akgun,116 E. Auffray,116 P. Baillon,116 A. H. Ball,116 D. Barney,116 J. Bendavid,116 M. Bianco,116 A. Bocci,116 C. Botta,116 T. Camporesi,116 M. Cepeda,116 G. Cerminara,116 E. Chapon,116 Y. Chen,116 G. Cucciati,116 D. d’Enterria,116 A. Dabrowski,116 V. Daponte,116 A. David,116 A. De Roeck,116 N. Deelen,116 M. Dobson,116 T. du Pree,116 M. Dünser,116 N. Dupont,116 A. Elliott-Peisert,116 112011-12 112011-12 PHYS. REV. D 98, 112011 (2018) ANGULAR ANALYSIS OF THE DECAY Bþ … P. Everaerts,116 F. Fallavollita,116,rr D. Fasanella,116 G. Franzoni,116 J. Fulcher,116 W. Funk,116 D. Gigi,116 A. Gilbert,116 K. Gill,116 F. Glege,116 M. Guilbaud,116 D. Gulhan,116 J. Hegeman,116 V. Innocente,116 A. Jafari,116 P. Janot,116 O Karacheban 116,u J Kieseler 116 A Kornmayer 116 M Krammer 116,b C Lange 116 P Lecoq 116 C Lourenço 116 g j M. Mulders,116 J. Ngadiuba,116 S. Orfanelli,116 L. Orsini,116 F. Pantaleo,116,r L. Pape,116 E. G. Rolandi, M. Rovere, H. Sakulin, C. Schäfer, C. Schwick, M. Seidel, M. Selvaggi, A. Sharma, P. Silva,116 P. Sphicas,116,uu A. Stakia,116 J. Steggemann,116 M. Tosi,116 D. Treille,116 A. Tsirou,116 V. Veckalns,116,vv W. D. Zeuner,116 L. Caminada,117,ww K. Deiters,117 W. Erdmann,117 R. Horisberger,117 Q. Ingram,117 H. C. Kaestli,117 D. Kotlinski,117 U. Langenegger,117 T. Rohe,117 S. A. Wiederkehr,117 M. Backhaus,118 L. Bäni,118 P. Berger,118 N. Chernyavskaya,118 G. Dissertori,118 M. Dittmar,118 M. Doneg`a,118 C. Dorfer,118 C. Grab,118 C. Heidegger,118 D. Hits,118 118 118 118 118 118 118 118 g gg g N. Chernyavskaya,118 G. Dissertori,118 M. Dittmar,118 M. Doneg`a,118 C. Dorfer,118 C. Grab,118 C. Heidegger,118 D. Hits,118 118 118 118 118 118 118 118 P. Musella, F. Nessi-Tedaldi, J. Pata, F. Pauss, G. Perrin, L. Perrozzi, S. Pigazzini, M. Quittnat, D. Ruini,118 D. A. Sanz Becerra,118 M. Schönenberger,118 L. Shchutska,118 V. R. Tavolaro,118 K. Theofilatos,118 M. L. Vesterbacka Olsson,118 R. Wallny,118 D. H. Zhu,118 T. K. Aarrestad,119 C. Amsler,119,xx D. 112011-11 H. Shepherd-Themistocleous,130 A. Thea,130 I. R. Tomalin,130 T. Williams,130 W. J. Womersley,130 g p y D. Petyt,130 C. H. Shepherd-Themistocleous,130 A. Thea,130 I. R. Tomalin,130 T. Williams,130 W. J. Womersley,130 131 131 131 131 131 131 131 131 G. Auzinger,131 R. Bainbridge,131 P. Bloch,131 J. Borg,131 S. Breeze,131 O. Buchmuller,131 A. D. Colling,131 L. Corpe,131 P. Dauncey,131 G. Davies,131 M. Della Negra,131 R. Di Maria,131 D. Colling,131 L. Corpe,131 P. Dauncey,131 G. Davies,131 M. Della Negra,131 R. Di Maria,131 Y. Haddad,131 G. Hall,131 131 131 131 131 131 131 131 131 131 lll G. Iles,131 T. James,131 M. Komm,131 C. Laner,131 L. Lyons,131 A.-M. Magnan,131 S. Malik,131 A. Nikitenko,131,g V. Palladino,131 M. Pesaresi,131 A. Richards,131 A. Rose,131 E. Scott,131 C. Seez,131 A. Shtipliyski,131 G. Singh,131 M. Stoye,131 T. Strebler,131 S. Summers,131 A. Tapper,131 K. Uchida,131 T. Virdee,131,r N. Wardle,131 D. Winterbottom,131 J. Wright,131 S. C. Zenz,131 J. E. Cole,132 P. R. Hobson,132 A. Khan,132 P. Kyberd,132 C. K. Mackay,132 A. Morton,132 I. D. Reid,132 L. Teodorescu,132 S. Zahid,132 K. Call,133 J. Dittmann,133 K. Hatakeyama,133 H. Liu,133 C. Madrid,133 B. Mcmaster,133 N. Pastika,133 C. Smith,133 R. Bartek,134 A. Dominguez,134 A. Buccilli,135 S. I. Cooper,135 A. Morton, I. D. Reid, L. Teodorescu, S. Zahid, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, C. Madrid,133 B. Mcmaster,133 N. Pastika,133 C. Smith,133 R. Bartek,134 A. Dominguez,134 A. Buccilli,135 S. I. Cooper,135 C. Henderson,135 P. Rumerio,135 C. West,135 D. Arcaro,136 T. Bose,136 D. Gastler,136 D. Rankin,136 C. Richardson,136 136 136 136 137 137 137 137 137 137 C. Madrid, B. Mcmaster, N. Pastika, C. Smith, R. Bartek, A. Dominguez, A. Buccilli, S. I. Cooper, C. Henderson,135 P. Rumerio,135 C. West,135 D. Arcaro,136 T. Bose,136 D. Gastler,136 D. Rankin,136 C. Richardson,136 6 D. Zou,136 G. Benelli,137 X. Coubez,137 D. Cutts,137 M. Hadley,137 J. Hakala,137 U. Heintz,1 J. M. Hogan,137,mmm K. H. M. Kwok,137 E. Laird,137 G. Landsberg,137 J. Lee,137 Z. Mao,137 M. Narain,137 J. Pazzini,137 Sagir,137,nnn R. Syarif,137 E. Usai,137 D. Yu,137 R. Band,138 C. Brainerd,138 R. Breedon,138 D. B p g y M. Calderon De La Barca Sanchez,138 M. Chertok,138 J. Conway,138 R. Conway,138 P. T. Cox,138 R. Erbacher,138 C. Flores,138 n De La Barca Sanchez,138 M. Chertok,138 J. Conway,138 R. Conway,138 P. T. Cox,138 R. Erbacher, G. Funk,138 W. Ko,138 O. Kukral,138 R. Lander,138 C. Mclean,138 M. Mulhearn,138 D. Pellett,138 J. Pilot,138 S. Shalhout,138 M. Shi,138 D. Stolp,138 D. Taylor,138 K. Tos,138 M. 112011-11 Tripathi,138 Z. Wang,138 F. Zhang,138 M. Bachtis,139 C. Bravo,139 139 139 139 139 139 139 139 139 M. Shi,138 D. Stolp,138 D. Taylor,138 K. Tos,138 M. Tripathi,138 Z. Wang,138 F. Zhang,138 M. Bachtis,139 C. Bravo,139 C. Schnaible,139 V. Valuev,139 E. Bouvier,140 K. Burt,140 R. Clare,140 J. W. Gary,140 S. M. A. Ghiasi Shirazi,140 G. Hanson,140 G. Karapostoli,140 E. Kennedy,140 F. Lacroix,140 O. R. Long,140 M. Olmedo Negrete,140 M. I. Paneva,140 W. Si,140 112011-13 PHYS. REV. D 98, 112011 (2018) A. M. SIRUNYAN et al. D. Gilbert,141 B. Hashemi,141 A. Holzner,141 D. Klein,141 G. Kole,141 V. Krutelyov,141 J. Letts,141 M. Masciovecchio,141 D. Olivito,141 S. Padhi,141 M. Pieri,141 M. Sani,141 V. Sharma,141 S. Simon,141 M. Tadel,141 A. Vartak,141 S. Wasserbaech,141,ooo J. Wood,141 F. Würthwein,141 A. Yagil,141 G. Zevi Della Porta,141 N. Amin,142 R. Bhandari,142 142 142 142 142 142 142 142 g J. Bradmiller-Feld,142 C. Campagnari,142 M. Citron,142 A. Dishaw,142 V. Dutta,142 M. Franco p g R. Heller,142 J. Incandela,142 A. Ovcharova,142 H. Qu,142 J. Richman,142 D. Stuart,142 I. Suarez,142 S. Wang,142 J. Yoo,142 143 143 143 143 143 143 143 D. Anderson,143 A. Bornheim,143 J. M. Lawhorn,143 H. B. Newman,143 T. Q. Nguyen,143 M. Sp , , , , Q g y , p p , , R. Wilkinson,143 S. Xie,143 Z. Zhang,143 R. Y. Zhu,143 M. B. Andrews,144 T. Ferguson,144 T. Mudholkar,144 M. Paulini,144 144 144 144 145 145 145 145 145 R. Wilkinson,143 S. Xie,143 Z. Zhang,143 R. Y. Zhu,143 M. B. Andrews,144 T. Ferguson,144 T. Mudholkar,144 M. Paulini,144 M. Sun,144 I. Vorobiev,144 M. Weinberg,144 J. P. Cumalat,145 W. T. Ford,145 F. Jensen,145 A. Johnson,145 M. Krohn,145 M. Sun,144 I. Vorobiev,144 M. Weinberg,144 J. P. Cumalat,145 W. T. Ford,145 F. Jensen,145 A. Johnson,145 M. Krohn,145 145 145 145 145 145 145 146 E. MacDonald,145 T. Mulholland,145 K. Stenson,145 K. A. Ulmer,145 S. R. Wagner,145 J. Alexa S. Leontsinis,145 E. MacDonald,145 T. Mulholland,145 K. Stenson,145 K. A. Ulmer,145 S. R. Wagner,145 J. Alexander,146 J. Chaves,146 Y. Cheng,146 J. Chu,146 A. Datta,146 K. Mcdermott,146 N. Mirman,146 J. R. Patterson,146 D. Quach,146 , , , , , g , , J. Chaves,146 Y. Cheng,146 J. Chu,146 A. Datta,146 K. Mcdermott,146 N. Mirman,146 J. R. Patterson,146 D. Quach,146 A. Rinkevicius,146 A. Ryd,146 L. Skinnari,146 L. Soffi,146 S. M. Tan,146 Z. Tao,146 J. Thom,146 6 A. Ryd,146 L. Skinnari,146 L. Soffi,146 S. M. Tan,146 Z. Tao,146 J. Thom,146 J. Tucker,146 P. W M. 112011-11 Modak, A. Mohammadi, L. K. Saini, N. Skhirtladze, F. Rebassoo, D. Wright, A. Baden, O. Baron, A. Belloni,158 S. C. Eno,158 Y. Feng,158 C. Ferraioli,158 N. J. Hadley,158 S. Jabeen,158 G. Y. Jeng,158 R. G. Kellogg,158 158 158 158 158 158 158 158 unkle,158 A. C. Mignerey,158 F. Ricci-Tam,158 Y. H. Shin,158 A. Skuja,158 S. C. Tonwar,158 K. W D. Abercrombie,159 B. Allen,159 V. Azzolini,159 A. Baty,159 G. Bauer,159 R. Bi,159 S. Brandt,159 W. Busza,159 I. A. Cali,159 159 Z. Demiragli,159 G. Gomez Ceballos,159 M. Goncharov,159 P. Harris,159 D. Hsu,159 M. Hu,159 Y 159 159 159 159 159 159 159 G. M. Innocenti,159 M. Klute,159 D. Kovalskyi,159 Y.-J. Lee,159 P. D. Luckey,159 B. Maier,159 A. C. Marini,159 C. Mcginn,159 C. Mironov,159 S. Narayanan,159 X. Niu,159 C. Paus,159 C. Roland,159 G. Roland,159 G. S. F. Stephans,159 K. Sumorok,159 K. Tatar,159 D. Velicanu,159 J. Wang,159 T. W. Wang,159 B. Wyslouch,159 S. Zhaozhong,159 A. C. Benvenuti,160 j N. Ruckstuhl,160 R. Rusack,160 J. Turkewitz,160 M. A. Wadud,160 J. G. Acosta,161 S. Oliveros,161 E. Avdeeva,162 K. Bloom,162 162 162 162 162 162 162 162 N. Ruckstuhl,160 R. Rusack,160 J. Turkewitz,160 M. A. Wadud,160 J. G. Acosta,161 S. Oliveros,161 E. Avdeeva,162 K. Bloom,162 D R Claes 162 C Fangmeier 162 F Golf 162 R Gonzalez Suarez 162 R Kamalieddin 162 I Kravchenko 162 J Monroy 162 112011-14 112011-11 Zientek,146 S. Abdullin,147 M. Albrow,147 M. Alyari,147 G. Apollinari,147 A. Apresyan,147 A. Apyan,147 S. Banerjee,147 M. Zientek,146 S. Abdullin,147 M. Albrow,147 M. Alyari,147 G. Apollinari,147 A. Apresyan,14 uerdick,147 A. Beretvas,147 J. Berryhill,147 P. C. Bhat,147 G. Bolla,147,a K. Burkett,147 J. N. Butler,147 L. A. T. Bauerdick,147 A. Beretvas,147 J. Berryhill,147 P. C. Bhat,147 G. Bolla,147,a K. Burkett,147 J. N. Butler,147 A. Canepa,147 G. B. Cerati,147 H. W. K. Cheung,147 F. Chlebana,147 M. Cremonesi,147 J. Duarte,147 V. D. Elvira,147 J. Freeman,147 147 147 147 147 147 147 147 147 L. A. T. Bauerdick, A. Beretvas, J. Berryhill, P. C. Bhat, G. Bolla, K. Burkett, J. N. Butler, A. Canepa, G. B. Cerati,147 H. W. K. Cheung,147 F. Chlebana,147 M. Cremonesi,147 J. Duarte,147 V. D. Elvira,147 J. Freeman,147 Z. Gecse,147 E. Gottschalk,147 L. Gray,147 D. Green,147 S. Grünendahl,147 O. Gutsche,147 J. H S. Hasegawa,147 J. Hirschauer,147 Z. Hu,147 B. Jayatilaka,147 S. Jindariani,147 M. Johnson,147 U. Joshi,147 B. Klima,147 M. J. Kortelainen,147 B. Kreis,147 S. Lammel,147 D. Lincoln,147 R. Lipton,147 M. Liu,147 T. Liu,147 J. Lykken,147 K. Maeshima,147 J. M. Marraffino,147 D. Mason,147 P. McBride,147 P. Merkel,147 S. Mrenna,147 S. Nahn,147 V. O’Dell,147 K. Pedro,147 C. Pena,147 O. Prokofyev,147 G. Rakness,147 L. Ristori,147 A. Savoy-Navarro,147,ppp B. Schneider,147 K. Maeshima,147 J. M. Marraffino,147 D. Mason,147 P. McBride,147 P. Merkel,147 S. Mrenna,147 S. Nahn,147 V. O’Dell,147 K P d 147 C P 147 O P k f 147 G R k 147 L Ri t i 147 A S N 147,ppp B S h id 147 y y E. Sexton-Kennedy,147 A. Soha,147 W. J. Spalding,147 L. Spiegel,147 S. Stoynev,147 J. Strait,147 N. Strobbe,147 L. Taylor,147 S. Tkaczyk,147 N. V. Tran,147 L. Uplegger,147 E. W. Vaandering,147 C. Vernieri,147 M. Verzocchi,147 R. Vidal,147 M. Wang,147 H. A. Weber,147 A. Whitbeck,147 D. Acosta,148 P. Avery,148 P. Bortignon,148 D. Bourilkov,148 A. Brinkerhoff,148 y , , p gg , g, , , , g, H. A. Weber,147 A. Whitbeck,147 D. Acosta,148 P. Avery,148 P. Bortignon,148 D. Bourilkov,148 A. Brinkerhoff,148 L Cadamuro 148 A Carnes 148 M Carver 148 D Curry 148 R D Field 148 S V Gleyzer 148 B M Joshi 148 J Konigsberg 148 H. A. Weber,147 A. Whitbeck,147 D. Acosta,148 P. Avery,148 P. Bortignon,148 D. Bourilkov,148 A. Brinkerhoff,148 148 148 148 148 148 148 148 148 y y g g A. Korytov,148 P. Ma,148 K. Matchev,148 H. Mei,148 G. Mitselmakher,148 K. Shi,148 D. Sperka,148 J. Wang,148 S. 112011-11 Wang,148 y y g g A. Korytov,148 P. Ma,148 K. Matchev,148 H. Mei,148 G. Mitselmakher,148 K. Shi,148 D. Sperka,148 J. Wang,148 S. Wang,148 Y R Joshi 149 S Linn 149 A Ackert 150 T Adams 150 A Askew 150 S Hagopian 150 V Hagopian 150 K F Johnson 150 y y g g A. Korytov,148 P. Ma,148 K. Matchev,148 H. Mei,148 G. Mitselmakher,148 K. Shi,148 D. Sperka,148 J. Wang,148 S. Wang,148 Y. R. Joshi,149 S. Linn,149 A. Ackert,150 T. Adams,150 A. Askew,150 S. Hagopian,150 V. Hagopian,150 K. F. Johnson,150 T Kolberg 150 G Martinez 150 T Perry 150 H Prosper 150 A Saha 150 A Santra 150 V Sharma 150 R Yohay 150 Y. R. Joshi,149 S. Linn,149 A. Ackert,150 T. Adams,150 A. Askew,150 S. Hagopian,150 V. Hagopian,150 K. F. Johnson,150 T. Kolberg,150 G. Martinez,150 T. Perry,150 H. Prosper,150 A. Saha,150 A. Santra,150 V. Sharma,150 R. Yohay,150 F. Yumiceva,151 M. R. Adams,152 L. Apanasevich,152 D. Berry,152 R. R. Betts,152 R. Cavanaugh,152 X. Chen,152 S. Dittmer,152 O. Evdokimov,152 C. E. Gerber,152 D. A. Hangal,152 D. J. Hofman,152 K. Jung,152 J. Kamin,152 C. Mills,152 I. D. Sandoval Gonzalez,152 M. B. Tonjes,152 N. Varelas,152 H. Wang,152 X. Wang,152 Z. Wu,152 J. Zhang,152 M. Alhusseini,153 B. Bilki,153,qqq W. Clarida,153 K. Dilsiz,153,rrr S. Durgut,153 R. P. Gandrajula,153 M. Haytmyradov,153 I. D. Sandoval Gonzalez,152 M. B. Tonjes,152 N. Varelas,152 H. Wang,152 X. Wang,152 Z. Wu,152 J. Zhang,152 M. Alhusseini,153 B. Bilki,153,qqq W. Clarida,153 K. Dilsiz,153,rrr S. Durgut,153 R. P. Gandrajula,153 M. Haytmyradov,153 C. You,154 A. Al-bataineh,155 P. Baringer,155 A. Bean,155 S. Boren,155 J. Bowen,155 A. Bylinkin,155 J. Castle,155 S. Khalil,155 A. Kropivnitskaya,155 D. Majumder,155 W. Mcbrayer,155 M. Murray,155 C. Rogan,155 S. Sanders,155 E. Schmitz,155 C. You, A. Al bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, A. Bylinkin, J. Castle, S. Khalil, A. Kropivnitskaya,155 D. Majumder,155 W. Mcbrayer,155 M. Murray,155 C. Rogan,155 S. Sanders,155 E. Schmitz,155 p y j y y g J. D. Tapia Takaki,155 Q. Wang,155 A. Ivanov,156 K. Kaadze,156 D. Kim,156 Y. Maravin,156 D. R. Mendis,156 T. Mitchell,156 156 156 156 156 15 15 158 158 A. Modak, A. Mohammadi, L. K. Saini, N. Skhirtladze, F. Rebassoo, D. Wright, A. Baden, O. Baron, A. Belloni,158 S. C. Eno,158 Y. Feng,158 C. Ferraioli,158 N. J. Hadley,158 S. Jabeen,158 G. Y. Jeng,158 R. G. Kellogg,158 J. Kunkle,158 A. C. Mignerey,158 F. Ricci-Tam,158 Y. H. Shin,158 A. Skuja,158 S. C. Tonwar,158 K. Wong,158 A. L. Wang,140 H. Wei,140 S. Wimpenny,140 B. R. Yates,140 J. G. Branson,141 S. Cittolin,141 M. Derdzinski,141 R. Gerosa,141 D. Gilbert,141 B. Hashemi,141 A. Holzner,141 D. Klein,141 G. Kole,141 V. Krutelyov,141 J. Letts,141 M. Masciovecchio,141 D Oli it 141 S P dhi 141 M Pi i 141 M S i 141 V Sh 141 S Si 141 M T d l 141 A V t k 141 ANGULAR ANALYSIS OF THE DECAY Bþ … Neu,179 T. Sinthuprasith,179 Y. Wang,179 E. Wolfe,179 F. Xia,179 R. Harr,180 P. E. Karchin,180 N. Poudyal,180 J. Sturdy,180 P. Thapa,180 S. Zaleski,180 M. Brodski,181 J. Buchanan,181 C. Caillol,181 D. Carlsmith,181 S. Dasu,181 L. Dodd,181 S. Duric,181 B. Gomber,181 M. Grothe,181 M. Herndon,181 A. Herv´e,181 U. Hussain,181 P. Klabbers,181 A. Lanaro,181 A. Levine,181 K. Long,181 R. Loveless,181 T. Ruggles,181 A. Savin,181 N S i h 181 W H S i h 181 d N W d 181 J. D. Ruiz Alvarez,178 P. Sheldon,178 S. Tuo,178 J. Velkovska,178 M. Verweij,178 Q. Xu,178 M. W. Arenton,179 P. Barria,179 179 179 179 179 179 179 179 179 179 B. Cox, R. Hirosky, M. Joyce, A. Ledovskoy, H. Li, C. Neu, T. Sinthuprasith, Y. Wang, E. Wolfe, F. Xia,179 R. Harr,180 P. E. Karchin,180 N. Poudyal,180 J. Sturdy,180 P. Thapa,180 S. Zaleski,180 M. Brodski,181 J. Buchanan,181 C. Caillol,181 D. Carlsmith,181 S. Dasu,181 L. Dodd,181 S. Duric,181 B. Gomber,181 M. Grothe,181 M. Herndon,181 A. Herv´e,181 U. Hussain,181 P. Klabbers,181 A. Lanaro,181 A. Levine,181 K. Long,181 R. Loveless,181 T. Ruggles,181 A. Savin,181 N. Smith,181 W. H. Smith,181 and N. Woods181 , , , , , , , , , U. Hussain,181 P. Klabbers,181 A. Lanaro,181 A. Levine,181 K. Long,181 R. Loveless,181 T. Ruggles,181 A. Savin,181 N Smith 181 W H Smith 181 and N Woods181 N. Smith,181 W. H. Smith,181 and N. Woods181 112011-14 112011-14 PHYS. REV. D 98, 112011 (2018) (CMS Collaboration) 1Yerevan Physics Institute, Yerevan, Armenia 2Institut für Hochenergiephysik, Wien, Austria 3Institute for Nuclear Problems, Minsk, Belarus 4Universiteit Antwerpen, Antwerpen, Belgium 5Vrije Universiteit Brussel, Brussel, Belgium 6Universit´e Libre de Bruxelles, Bruxelles, Belgium 7Ghent University, Ghent, Belgium 8Universit´e Catholique de Louvain, Louvain-la-Neuve, Belgium 9Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil 10Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil 11aUniversidade Estadual Paulista, São Paulo, Brazil 11bUniversidade Federal do ABC, São Paulo, Brazil 12Institute for Nuclear Research and Nuclear Energy, Bulgarian Academy of Sciences, Sofia, Bulgaria 13University of Sofia, Sofia, Bulgaria 14Beihang University, Beijing, China 15Institute of High Energy Physics, Beijing, China 16State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China 1Yerevan Physics Institute, Yerevan, Armenia 2 2Institut für Hochenergiephysik, Wien, Austria 3 3Institute for Nuclear Problems, Minsk, Belarus 4 4Universiteit Antwerpen, Antwerpen, Belgium 5 5Vrije Universiteit Brussel, Brussel, Belgium ANGULAR ANALYSIS OF THE DECAY Bþ … Spanier,175 K Th 175 O B h li 176,uuu A C lik 176 M D l h k 176 M D M tti 176 A D l d 176 S Dildi k 176 R E bi 176 p g J. Gilmore,176 T. Huang,176 T. Kamon,176,vvv S. Luo,176 R. Mueller,176 Y. Pakhotin,176 R. Patel,176 A. Perloff,176 L. Perni`e,176 J. Gilmore,176 T. Huang,176 T. Kamon,176,vvv S. Luo,176 R. Mueller,176 Y. Pakhotin,176 R. Patel,176 A. Perloff,176 L. Perni`e,176 K. Lamichhane,177 S. W. Lee,177 T. Mengke,177 S. Muthumuni,177 T. Peltola,177 S. Undleeb,177 I. Volobouev,177 Z. Wang,177 S. Greene,178 A. Gurrola,178 R. Janjam,178 W. Johns,178 C. Maguire,178 A. Melo,178 H. Ni,178 K. Padeken,178 K. Lamichhane,177 S. W. Lee,177 T. Mengke,177 S. Muthumuni,177 T. Peltola,177 S. Undleeb,177 I. Volobouev,177 Z. Wang,177 S. Greene,178 A. Gurrola,178 R. Janjam,178 W. Johns,178 C. Maguire,178 A. Melo,178 H. Ni,178 K. Padeken,178 J. D. Ruiz Alvarez,178 P. Sheldon,178 S. Tuo,178 J. Velkovska,178 M. Verweij,178 Q. Xu,178 M. W. Arenton,179 P. Barria,179 B. Cox,179 R. Hirosky,179 M. Joyce,179 A. Ledovskoy,179 H. Li,179 C. Neu,179 T. Sinthuprasith,179 Y. Wang,179 E. Wolfe,179 F. Xia,179 R. Harr,180 P. E. Karchin,180 N. Poudyal,180 J. Sturdy,180 P. Thapa,180 S. Zaleski,180 M. Brodski,181 J. Buchanan,181 C. Caillol,181 D. Carlsmith,181 S. Dasu,181 L. Dodd,181 S. Duric,181 B. Gomber,181 M. Grothe,181 M. Herndon,181 A. Herv´e,181 U Hussain 181 P Klabbers 181 A Lanaro 181 A Levine 181 K Long 181 R Loveless 181 T Ruggles 181 A Savin 181 K. Lamichhane,177 S. W. Lee,177 T. Mengke,177 S. Muthumuni,177 T. Peltola,177 S. Undleeb,177 I. Volobouev,177 Z. Wang,177 S. Greene,178 A. Gurrola,178 R. Janjam,178 W. Johns,178 C. Maguire,178 A. Melo,178 H. Ni,178 K. Padeken,178 J. D. Ruiz Alvarez,178 P. Sheldon,178 S. Tuo,178 J. Velkovska,178 M. Verweij,178 Q. Xu,178 M. W. Arenton,179 P. Barria,179 B. Cox,179 R. Hirosky,179 M. Joyce,179 A. Ledovskoy,179 H. Li,179 C. Neu,179 T. Sinthuprasith,179 Y. Wang,179 E. Wolfe,179 S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K. Padeken, J. D. Ruiz Alvarez,178 P. Sheldon,178 S. Tuo,178 J. Velkovska,178 M. Verweij,178 Q. Xu,178 M. W. Arenton,179 P. Barria,179 179 179 179 179 179 179 179 179 179 S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K. Padeken, J. D. Ruiz Alvarez,178 P. Sheldon,178 S. Tuo,178 J. Velkovska,178 M. Verweij,178 Q. Xu,178 M. W. Arenton,179 P. Barria,179 B. Cox,179 R. Hirosky,179 M. Joyce,179 A. Ledovskoy,179 H. Li,179 C. ANGULAR ANALYSIS OF THE DECAY Bþ … ANGULAR ANALYSIS OF THE DECAY Bþ … J. E. Siado,162 G. R. Snow,162 B. Stieger,162 A. Godshalk,163 C. Harrington,163 I. Iashvili , , g , , g , , , D. Nguyen,163 A. Parker,163 S. Rappoccio,163 B. Roozbahani,163 G. Alverson,164 E. Barberis,164 C. Freer,164 164 164 164 164 164 164 164 D. Nguyen,163 A. Parker,163 S. Rappoccio,163 B. Roozbahani,163 G. Alverson,164 E. Ba g y pp A. Hortiangtham,164 D. M. Morse,164 T. Orimoto,164 R. Teixeira De Lima,164 T. Wamorkar,164 B. M. Trovato,165 M. Velasco,165 R. Bucci,166 N. Dev,166 M. Hildreth,166 K. Hurtado Anampa,166 C. Jessop,166 D. J. Karmgard,166 N. Kellams,166 K. Lannon,166 W. Li,166 N. Loukas,166 N. Marinelli,166 F. Meng,166 C. Mueller,166 166 jj 166 166 166 166 166 166 166 , , , , , p , p, D. J. Karmgard,166 N. Kellams,166 K. Lannon,166 W. Li,166 N. Loukas,166 N. Marinelli,166 F. Meng,166 C. Mueller,166 166 jj 166 166 166 166 166 166 166 gg g p g J. Luo,168 D. Marlow,168 K. Mei,168 I. Ojalvo,168 J. Olsen,168 C. Palmer,168 P. Pirou´e,168 J. Salfeld-Nebgen,168 D. Stickland,168 A. Khatiwada,170 B. Mahakud,170 D. H. Miller,170 N. Neumeister,170 C. C. Peng,170 H. Qiu,170 J. F. Schulte,170 J. Sun,170 F. Wang,170 R. Xiao,170 W. Xie,170 T. Cheng,171 J. Dolen,171 N. Parashar,171 Z. Chen,172 K. M F. J. M. Geurts,172 M. Kilpatrick,172 W. Li,172 B. Michlin,172 B. P. Padley,172 J. Roberts,172 J. Rorie,172 W. Shi,172 Z. Tu,172 172 172 173 173 173 173 173 173 F. J. M. Geurts,172 M. Kilpatrick,172 W. Li,172 B. Michlin,172 B. P. Padley,172 J. Roberts,172 J. Rorie,172 W. Shi,172 Z. Tu,172 J. Zabel,172 A. Zhang,172 A. Bodek,173 P. de Barbaro,173 R. Demina,173 Y. t. Duh,173 J. L. Dulemba,173 C. Fallon,173 T. Ferbel,173 M. Galanti,173 A. Garcia-Bellido,173 J. Han,173 O. Hindrichs,173 A. Khukhunaishvili,173 K. H. Lo,173 P. Tan,173 R. Taus,173 M. Verzetti,173 A. Agapitos,174 J. P. Chou,174 Y. Gershtein,174 T. A. Gómez Espin 1 4 1 4 1 4 1 4 1 4 ,173 A. Agapitos,174 J. P. Chou,174 Y. Gershtein,174 T. A. Gómez Espinosa,174 E. Halkiadakis,17 M. Heindl,174 E. Hughes,174 S. Kaplan,174 R. Kunnawalkam Elayavalli,174 S. Kyriacou,174 A. Lath,174 R. Montalvo,174 M. Heindl,174 E. Hughes,174 S. Kaplan,174 R. Kunnawalkam Elayavalli,174 S. Kyriacou,17 S. Thomas,174 P. Thomassen,174 M. Walker,174 A. G. Delannoy,175 J. Heideman,175 G. Riley,175 K. Rose,175 S. Spanier,175 S. Thomas,174 P. Thomassen,174 M. Walker,174 A. G. Delannoy,175 J. Heideman,175 G. Riley,175 K. Rose,175 S. Budapest, Hungary 49Wigner Research Centre for Physics, Budapest, Hungary 50 50Institute of Nuclear Research ATOMKI, Debrecen, Hungary 1 51Institute of Physics, University of Debrecen, Debrecen, Hungary 52 112011-15 A. M. SIRUNYAN et al. PHYS. REV. D 98, 112011 (2018) 17Tsinghua University, Beijing, China 18Universidad de Los Andes, Bogota, Colombia 19University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia 20University of Split, Faculty of Science, Split, Croatia 21Institute Rudjer Boskovic, Zagreb, Croatia 22University of Cyprus, Nicosia, Cyprus 23Charles University, Prague, Czech Republic 24Escuela Politecnica Nacional, Quito, Ecuador 25Universidad San Francisco de Quito, Quito, Ecuador 26Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt 27National Institute of Chemical Physics and Biophysics, Tallinn, Estonia 28Department of Physics, University of Helsinki, Helsinki, Finland 29Helsinki Institute of Physics, Helsinki, Finland 30Lappeenranta University of Technology, Lappeenranta, Finland 31IRFU, CEA, Universit´e Paris-Saclay, Gif-sur-Yvette, France 32Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Universit´e Paris-Saclay, Palaiseau, France 33Universit´e de Strasbourg, CNRS, IPHC UMR 7178, Strasbourg, France 34Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France 35Universit´e de Lyon, Universit´e Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucl´eaire de Lyon, Villeurbanne, France 36Georgian Technical University, Tbilisi, Georgia 37Tbilisi State University, Tbilisi, Georgia 38RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany 39RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany 40RWTH Aachen University, III. 112011-15 Physikalisches Institut B, Aachen, Germany 41Deutsches Elektronen-Synchrotron, Hamburg, Germany 42University of Hamburg, Hamburg, Germany 43Karlsruher Institut fuer Technology 44Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece 45National and Kapodistrian University of Athens, Athens, Greece 46National Technical University of Athens, Athens, Greece 47University of Ioánnina, Ioánnina, Greece 48MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary 49Wigner Research Centre for Physics, Budapest, Hungary 50Institute of Nuclear Research ATOMKI, Debrecen, Hungary 51Institute of Physics, University of Debrecen, Debrecen, Hungary 52Indian Institute of Science (IISc), Bangalore, India 53National Institute of Science Education and Research, HBNI, Bhubaneswar, India 54Panjab University, Chandigarh, India 55University of Delhi, Delhi, India 56Saha Institute of Nuclear Physics, HBNI, Kolkata,India 57Indian Institute of Technology Madras, Madras, India 58Bhabha Atomic Research Centre, Mumbai, India 59Tata Institute of Fundamental Research-A, Mumbai, India 60Tata Institute of Fundamental Research-B, Mumbai, India 61Indian Institute of Science Education and Research (IISER), Pune, India 62Institute for Research in Fundamental Sciences (IPM), Tehran, Iran 63University College Dublin, Dublin, Ireland 64aINFN Sezione di Bari, Bari, Italy 64bUniversit`a di Bari, Bari, Italy 64cPolitecnico di Bari, Bari, Italy 65aINFN Sezione di Bologna, Bologna, Italy 65bUniversit`a di Bologna, Bologna, Italy 66 5Universit´e de Lyon, Universit´e Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucl´eaire de Lyon, Villeurbanne, France 36 41Deutsches Elektronen-Synchrotron, Hamburg, Germany 42 46National Technical University of Athens, Athens, Greece 47 47University of Ioánnina, Ioánnina, Greece Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, 112011-16 PHYS. REV. D 98, 112011 (2018) ANGULAR ANALYSIS OF THE DECAY Bþ … ANGULAR ANALYSIS OF THE DECAY Bþ … Lebedev Physical Institute, Moscow, Russia 107Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia 108Novosibirsk State University (NSU), Novosibirsk, Russia 109State Research Center of Russian Federation, Institute for High Energy Physics of NRC “Kurchatov Institute”, Protvino, Russia , 81Hanyang University, Seoul, Korea 82 82Korea University, Seoul, Korea 83 83Sejong University, Seoul, Korea 84Seoul National University, Seoul, Korea 85 85University of Seoul, Seoul, Korea 6 86Sungkyunkwan University, Suwon, Korea 87 87Vilnius University, Vilnius, Lithuania nal Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia 89 90Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico 91 91Universidad Iberoamericana, Mexico City, Mexico 92 92Benemerita Universidad Autonoma de Puebla, Puebla, Mexico ANGULAR ANALYSIS OF THE DECAY Bþ … 67aINFN Sezione di Firenze, Firenze, Italy 67bUniversit`a di Firenze, Firenze, Italy 68INFN Laboratori Nazionali di Frascati, Frascati, Italy 69aINFN Sezione di Genova, Genova, Italy 69bUniversit`a di Genova, Genova, Italy 70aINFN Sezione di Milano-Bicocca, Milano, Italy 70bUniversit`a di Milano-Bicocca, Milano, Italy 71aINFN Sezione di Napoli, Napoli, Italy 71bUniversit`a di Napoli ’Federico II’, Napoli, Italy 71cUniversit`a della Basilicata, Potenza, Italy 71dUniversit`a G. Marconi, Roma, Italy 72aINFN Sezione di Padova, Padova, Italy 72bUniversit`a di Padova, Padova, Italy 73aINFN Sezione di Pavia 73bUniversit`a di Pavia 74aINFN Sezione di Perugia, Perugia, Italy 74bUniversit`a di Perugia, Perugia, Italy 75aINFN Sezione di Pisa, Pisa, Italy 75bUniversit`a di Pisa, Pisa, Italy 75cScuola Normale Superiore di Pisa, Pisa, Italy 76aINFN Sezione di Roma, Rome, Italy 76bSapienza Universit`a di Roma, Rome, Italy 77aINFN Sezione di Torino, Torino, Italy 77bUniversit`a di Torino, Torino, Italy 77cUniversit`a del Piemonte Orientale, Novara, Italy 78aINFN Sezione di Trieste, Trieste, Italy 78bUniversit`a di Trieste, Trieste, Italy 79Kyungpook National University 80Chonnam National University, Institute for Universe and Elementary Particles, Kwangju, Korea 81Hanyang University, Seoul, Korea 82Korea University, Seoul, Korea 83Sejong University, Seoul, Korea 84Seoul National University, Seoul, Korea 85University of Seoul, Seoul, Korea 86Sungkyunkwan University, Suwon, Korea 87Vilnius University, Vilnius, Lithuania 88National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia 89Universidad de Sonora (UNISON), Hermosillo, Mexico 90Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico 91Universidad Iberoamericana, Mexico City, Mexico 92Benemerita Universidad Autonoma de Puebla, Puebla, Mexico 93Universidad Autónoma de San Luis Potosí, San Luis Potosí, Mexico 94University of Auckland, Auckland, New Zealand 95University of Canterbury, Christchurch, New Zealand 96National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan 97National Centre for Nuclear Research, Swierk, Poland 98Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland 99Laboratório de Instrumentação e Física Experimental de Partículas, Lisboa, Portugal 100Joint Institute for Nuclear Research, Dubna, Russia 101Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia 102Institute for Nuclear Research, Moscow, Russia 103Institute for Theoretical and Experimental Physics, Moscow, Russia 104Moscow Institute of Physics and Technology, Moscow, Russia 105National Research Nuclear University ’Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia 106P.N. 133Baylor University, Waco, Texas, USA 33Baylor University, Waco, Texas, USA 134Catholic University of America, Washington, DC, USA 135 135The University of Alabama, Tuscaloosa, Alabama, USA 136 136Boston University, Boston, Massachusetts, USA 137 137Brown University, Providence, Rhode Island, USA 137Brown University, Providence, Rhode Island, USA 138University of California, Davis, Davis, California, USA 139 138University of California, Davis, Davis, California, USA 139 139University of California, Los Angeles, California, USA 139University of California, Los Angeles, California, USA 140University of California, Riverside, Riverside, California, USA 141 140University of California, Riverside, Riverside, California, USA 141 142University of California, Santa Barbara—Department of Physics, Santa Barbara, California, USA 143 143California Institute of Technology, Pasadena, California, USA 144 144Carnegie Mellon University, Pittsburgh, Pennsylvania, USA 145 145University of Colorado Boulder, Boulder, Colorado, USA 146 46Cornell University, Ithaca, New York, USA Cornell University, Ithaca, New York, USA 147Fermi National Accelerator Laboratory, Batavia, Illinois, USA 148 147Fermi National Accelerator Laboratory, Batavia, Illinois, USA 148 147Fermi National Accelerator Laboratory, Batavia, Illinois, USA 148University of Florida, Gainesville, Florida, USA 149 149Florida International University, Miami, Florida, USA 150 f gy 152University of Illinois at Chicago (UIC), Chicago, Illinois, USA 153The University of Iowa, Iowa City, Iowa, USA 154Johns Hopkins University, Baltimore, Maryland, USA 155The University of Kansas, Lawrence, Kansas, USA 156Kansas State University, Manhattan, Kansas, USA 157 156Kansas State University, Manhattan, Kansas, US 157Lawrence Livermore National Laboratory, Livermore, California, USA 158University of Maryland, College Park, Maryland, USA 159 159Massachusetts Institute of Technology, Cambridge, Massachusetts, USA 160University of Minnesota, Minneapolis, Minnesota, USA 161University of Mississippi, Oxford, Mississippi, USA 162University of Nebraska-Lincoln, Lincoln, Nebraska, USA 163State University of New York at Buffalo, Buffalo, New York, USA 164Northeastern University, Boston, Massachusetts, USA 165Northwestern University, Evanston, Illinois, USA 166University of Notre Dame, Notre Dame, Indiana, USA 167The Ohio State University, Columbus, Ohio, USA 168Princeton University, Princeton, New Jersey, USA 169University of Puerto Rico, Mayaguez, Puerto Rico 159Massachusetts Institute of Technology, Cambridge, Massachusetts, USA 160University of Minnesota, Minneapolis, Minnesota, USA 161University of Mississippi, Oxford, Mississippi, USA 162University of Nebraska-Lincoln, Lincoln, Nebraska, USA University of Nebraska Lincoln, Lincoln, Nebraska, USA 163State University of New York at Buffalo, Buffalo, New York, USA 164Northeastern University, Boston, Massachusetts, USA 165Northwestern University, Evanston, Illinois, USA 166University of Notre Dame, Notre Dame, Indiana, USA 167The Ohio State University, Columbus, Ohio, USA 168Princeton University, Princeton, New Jersey, USA 169University of Puerto Rico, Mayaguez, Puerto Rico 9University of Puerto Rico, Mayaguez, Puerto Rico Moscow, Russia 112011-17 A. M. SIRUNYAN et al. PHYS. REV. D 98, 112011 (2018) 27Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, Ukraine 128 8National Scientific Center, Kharkov Institute of Physics and Technology, Kharkov, Ukraine 129 129University of Bristol, Bristol, United Kingdom 130Rutherford Appleton Laboratory, Didcot, United Kingdom 131 131Imperial College, London, United Kingdom 132 132Brunel University, Uxbridge, United Kingdom 133 ANGULAR ANALYSIS OF THE DECAY Bþ … kk kkAlso at National Research Nuclear University ’Moscow Engi ll kkAlso at National Research Nuclear University ’Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia. llAl S b S l h i l i i S b i kkAlso at National Research Nuclear University ’Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia. ll llAlso at St. Petersburg State Polytechnical Univers State Polytechnical University, St. Petersburg, Russ mmAlso at University of Florida, Gainesville, USA. mmAlso at University of Florida, Gainesville, USA. nnAlso at P.N. Lebedev Physical Institute, Moscow, Russia. nnAlso at P.N. Lebedev Physical Institute, Moscow, Russia ooAlso at California Institute of Technology, Pasadena, USA. ooAlso at California Institute of Technology, Pasadena, USA. ppAlso at Budker Institute of Nuclear Physics, Novosibirsk, Russia. ppAlso at Budker Institute of Nuclear Physics, Novosibirsk, Russia. qqAlso at Faculty of Physics, University of Belgrade, Belgrade, Serbia. rrAlso at INFN Sezione di Pavia, Universit`a di Pavia, Pavia, Italy. rrAlso at INFN Sezione di Pavia, Universit`a di Pavia, Pavia, Italy. ss rrAlso at INFN Sezione di Pavia, Universit`a di Pavia, Pavia, Italy. ss ssAlso at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrad tt ssAlso at University of Belgrade, Faculty of Physics and Vinca Inst ttAlso at Scuola Normale e Sezione dell’INFN, Pisa, Italy. ttAlso at Scuola Normale e Sezione dell’INFN, Pisa, Italy. uuAlso at National and Kapodistrian University of Athens, Athens, Greece. uuAlso at National and Kapodistrian University of Athens, Athens, Greece. 112011-18 ANGULAR ANALYSIS OF THE DECAY Bþ … ANGULAR ANALYSIS OF THE DECAY Bþ … rAlso at CERN, European Organization for Nuclear Research, Geneva, Switz sAlso at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany. t sAlso at RWTH Aachen University, III. Physikalisches t y y y tAlso at University of Hamburg, Hamburg, Germany. tAlso at University of Hamburg, Hamburg, Germany. Also at University of Hamburg, Hamburg, Germany uAlso at Brandenburg University of Technology, Cottbus, Germany. uAlso at Brandenburg University of Technology, Cottbus, Germany. g y gy y vAlso at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary. wAl I i f N l R h ATOMKI D b H ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungar vAlso at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd Univ vAlso at MTA-ELTE Lendület CMS Particle and Nuclear Physics Gr wAlso at Institute of Nuclear Research ATOMKI, Debrecen, Hungary. wAlso at Institute of Nuclear Research ATOMKI, Debrecen, Hungary. xAlso at Institute of Physics, University of Debrecen, Debrecen, Hungary. xAlso at Institute of Physics, University of Debrecen, Debrecen, Hungary. yAlso at IIT Bhubaneswar, Bhubaneswar, India. zAlso at Institute of Physics, Bhubaneswar, India aaAlso at Shoolini University, Solan, India. aaAlso at Shoolini University, Solan, India. bb bbAlso at University of Visva-Bharati, Santiniketan, India. bbAlso at University of Visva-Bharati, Santiniketan, India. ccAlso at Isfahan University of Technology, Isfahan, Iran. dd ccAlso at Isfahan University of Technology, Isfahan, Iran. dd ddAlso at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran. ee ddAlso at Plasma Physics Research Center, Science and Research Branch, ddAlso at Plasma Physics Research Center, Science and Research Branch, Islamic Azad eAlso at Universit`a degli Studi di Siena, Siena, Ital ffAlso at International Islamic University of Malaysia, Kuala Lu ffAlso at International Islamic University of Malaysia, Kuala Lumpur, Malaysia. ggAlso at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia. hh ggAlso at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia. hh hhAlso at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico ii hhAlso at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico. ii iiAlso at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland. jj iiAlso at Warsaw University of Technology, Institute of Electronic Systems, jj jjAlso at Institute for Nuclear Research, Moscow, Russia. jjAlso at Institute for Nuclear Research, Moscow, Russia. ANGULAR ANALYSIS OF THE DECAY Bþ … PHYS. REV. D 98, 112011 (2018) 170Purdue University, West Lafayette, Indiana, USA 171Purdue University Northwest, Hammond, Indiana, USA 172Rice University, Houston, Texas, USA 173University of Rochester, Rochester, New York, USA 174Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA 175University of Tennessee, Knoxville, Tennessee, USA 176Texas A&M University, College Station, Texas, USA 177Texas Tech University, Lubbock, Texas, USA 178Vanderbilt University, Nashville, Tennessee, USA 179University of Virginia, Charlottesville, Virginia, USA 180Wayne State University, Detroit, Michigan, USA 181University of Wisconsin—Madison, Madison, Wisconsin, USA 170Purdue University, West Lafayette, Indiana, USA 171 172Rice University, Houston, Texas, USA 173University of Rochester, Rochester, New York, USA 174 rs, The State University of New Jersey, Piscataway, New Jersey, USA 175 175University of Tennessee, Knoxville, Tennessee, USA 176 176Texas A&M University, College Station, Texas, USA 177 177Texas Tech University, Lubbock, Texas, USA 178 178Vanderbilt University, Nashville, Tennessee, USA 179 179University of Virginia, Charlottesville, Virginia, USA 180 180Wayne State University, Detroit, Michigan, USA 181University of Wisconsin—Madison, Madison, Wisconsin, USA aDeceased. b bAlso at Vienna University of Technology, Vienna, Austria. c cAlso at IRFU, CEA, Universit´e Paris-Saclay, Gif-sur-Yvette, France. d dAlso at Universidade Estadual de Campinas, Campinas, Brazil. eAlso at Federal University of Rio Grande do Sul, Porto Alegre, Brazil. f fAlso at Universit´e Libre de Bruxelles, Bruxelles, Belgium. fAlso at Universit´e Libre de Bruxelles, Bruxelles, Belgium. gAlso at Institute for Theoretical and Experimental Physics, Moscow, Russia. h hAlso at Joint Institute for Nuclear Research, Dubna, Russia. i iAlso at Helwan University, Cairo, Egypt. j iAlso at Helwan University, Cairo, Egypt. j jAlso at Fayoum University, El-Fayoum, Egypt. k jAlso at Fayoum University, El-Fayoum, Egypt. k kAlso at Ain Shams University, Cairo, Egypt. l kAlso at Ain Shams University, Cairo, Egypt. l lAlso at British University in Egypt, Cairo, Egypt. lAlso at British University in Egypt, Cairo, Egypt. mAlso at Department of Physics, King Abdulaziz University, mAlso at Department of Physics, King Abdulaziz University, Jeddah, Saudi Arabia. at Universit´e de Haute Alsace, Mulhouse, France. oAlso at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia. p l bili i i i bili i i oAlso at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University pAlso at Tbilisi State University, Tbilisi, Georgia. pAlso at Tbilisi State University, Tbilisi, Georgia. qAlso at Ilia State University, Tbilisi, Georgia. qAlso at Ilia State University, Tbilisi, Georgia. rAlso at CERN, European Organization for Nuclear Research, Geneva, Switzerland. 112011-19 PHYS. REV. D 98, 112011 (2018) A. M. SIRUNYAN et al. A. M. SIRUNYAN et al. vvAlso at Riga Technical University. vvAlso at Riga Technical University. wwAlso at Universität Zürich, Zurich, Switzerland. xxAlso at Stefan Meyer Institute for Subatomic Physics. yyAlso at Adiyaman University, Adiyaman, Turkey. yyAlso at Adiyaman University, Adiyaman, Turkey. zzAlso at Istanbul Aydin University, Istanbul, Turkey. zzAlso at Istanbul Aydin University, Istanbul, Turkey. aaaAlso at Mersin University, Mersin, Turkey. aaaAlso at Mersin University, Mersin, Turkey. bbb y y bbbAlso at Piri Reis University, Istanbul, Turkey. bbbAlso at Piri Reis University, Istanbul, Turkey. cAlso at Gaziosmanpasa University, Tokat, Turkey. d p y dddAlso at Ozyegin University, Istanbul, Turkey. dddAlso at Ozyegin University, Istanbul, Turkey. eeeAlso at Izmir Institute of Technology, Izmir, Turkey. eeeAlso at Izmir Institute of Technology, Izmir, Turkey. fff fffAlso at Marmara University, Istanbul, Turkey. fffAlso at Marmara University, Istanbul, Turkey. gggAlso at Kafkas University, Kars, Turkey. gggAlso at Kafkas University, Kars, Turkey. hhh hhhAlso at Istanbul Bilgi University, Istanbul, Turkey. iii hhhAlso at Istanbul Bilgi University, Istanbul, Turkey. iii iiiAlso at Hacettepe University, Ankara, Turkey jjj iiiAlso at Hacettepe University, Ankara, Turkey. jjj jjjAlso at Rutherford Appleton Laboratory, Didcot, United Kingdom. kkk jjjAlso at Rutherford Appleton Laboratory, Didcot, United Kingdom. kkk kkkAlso at School of Physics and Astronomy, University of Southampton, Southampton, United Kingdom. lllAl M h U i i F l f S i Cl A li kkkAlso at School of Physics and Astronomy, University of Southampto lll kkkAlso at School of Physics and Astronomy, University of Southampton, So lll lllAlso at Monash University, Faculty of Science, Clayton, Australia. lllAlso at Monash University, Faculty of Science, Clayton, Australia. sh University, Faculty of Science, Clayton, Australia mmmAlso at Bethel University. mmmAlso at Bethel University. nnnAlso at Karamanoğlu Mehmetbey University, Karaman, Turkey. nnnAlso at Karamanoğlu Mehmetbey University, Karaman, Turkey. oooAlso at Utah Valley University, Orem, USA. pppAlso at Purdue University, West Lafayette, USA. pppAlso at Purdue University, West Lafayette, USA. qqqAlso at Beykent University. qqqAlso at Beykent University. rrrAlso at Bingol University, Bingol, Turkey. rrrAlso at Bingol University, Bingol, Turkey. sssAlso at Sinop University, Sinop, Turkey. sssAlso at Sinop University, Sinop, Turkey. tttAlso at Mimar Sinan University, Istanbul, Istanbul, Turkey. tttAlso at Mimar Sinan University, Istanbul, Istanbul, Turkey. uuuAlso at Texas A&M University at Qatar, Doha, Qatar uuuAlso at Texas A&M University at Qatar, Doha, vvvAlso at Kyungpook National University. vvvAlso at Kyungpook National University. 112011-20
https://openalex.org/W2129146733	https://curationis.org.za/index.php/curationis/article/download/1218/1203	English	null	The lived experience by psychiatric nurses of aggression and violence from patients in a Gauteng psychiatric institution	Curationis	2,009	cc-by	9,935	Research Article Research Article The lived experience by psychiatric nurses of aggression and violence from patients in a Gauteng psychiatric institution E Bimenyimana (MCur): Doctoral Candidate Department of Nursing Science, University of Johannesburg V van Niekerk (MCur): Lecturer Dept of Nursing, University of Johannesburg Keywords: Lived experience, aggression, nurses, patients, aggression and violence and psychiatric institution. Keywords: Lived experience, aggression, nurses, patients, aggression and violence and psychiatric institution. ( ) Caring fo r good people is difficult enough; to care fo r people who are either aggres sive or violent is even more difficult. This is what psychiatric nurses working in the psychiatric institution in which research was done are exposed to on a daily basis. The aim o f the research was to explore and describe the lived experience by psychi atric nurses o f aggression and violence from patients in a Gauteng psychiatric insti tution. A qualitative, explorative, descriptive, and contextual study design was uti lised. Data was collected by means o f semi-structured interviews and naïve sketches. Tesch s (Creswell, 2004: 256) method o f open coding and an independent coder were utilised fo r data analysis. This study shed some light on the lived experience by psychiatric nurses o f aggres sion and violence from patients in a Gauteng psychiatric institution. The findings show that the level o f violence and aggression to which psychiatric nurses are exposed is overwhelming and the consequences are alarming. The contributing fa c tors to this violence and aggression are: the mental status and the conditions in which patients are admitted; the staff shortage; the lack o f support among the mem bers o f the multidisciplinary team (MDT); and the lack ofstructured and comprehen sive orientation among newly appointed staff members. g y pp ff As a result, psychiatric nurses are emotionally, psychologically, and physically af fected. They then respond with the following emotions and behaviour: fear, anger, frustration, despair, hopelessness and helplessness, substance abuse, absenteeism, retaliation and the development o f an “I don ’t care ” attitude. Correspondence address P rof Marie Poggenpoel, Department o f Nursing Science, University o f Johannesburg, Box 524, Auckland Park, 2006 Tel no: 011-559-2860 Fax:011-559-2257 E-mail: mariep@uj.ac.za 4 Curationis September 2009 Problem statement The Mental Health Care Act 17 o f2002 (Government Gazette no. 24024) classi fies mental health care users (formerly known as patients) in different catego ries. Among these categories, the re search study focused on Sections 33, 34, and 42. These are: involuntary ad mitted mental health care users, as sisted involuntary adm itted mental health care users; and state patients committed pending the court's decision respectively. These mental health care users are admitted on the basis o f their being a danger to themselves, a dan ger to others, and/or a danger to the property o f others. In other words, they are admitted because o f their violent or aggressive behaviour. Any attempt by the psychiatric nurses to give the p a tient medication may be viewed as an act o f aggression. The patients will re spond aggressively in what patients believe to be self-defence. The re searcher wondered what happened during these or similar incidents to the psychiatric nurses regularly in their working environment in a psychiatric institution (Bimenyimana, 2008:3&4). Psychiatric institutions worldwide are known to be encountering a certain level o f violence and aggression. Re search conducted in countries such as England (Whittington, 2002:819-825), the United States o f America (Noble, 2003:389-393), and Australia (Forster, Petty, Schleiger, & Walters, 2005:357- 361) among others, bear witness. In South Africa, the research in the hos p ita l en viron m en t con du cted by Steinman (2003), Kennedy (2004), and Lucas and Stevenson (2006:195-203) shows that violence is present and ac tive in health workplace settings. Aggression: This is hostile or destruc tive behaviour (Thompson, 1996: 16). In this article aggression means any behaviour, gesture, verbal or non-ver- bal communication, with the intention to provoke a negative feeling or nega tive reaction in another person. This includes intimidation, threats, swear ing, undermining, humiliating, indecent exposure and so forth (Bimenyimana, 2008: 7 & 8). Psychiatric Patient/M ental Health Care User: Government Gazette no. 24024, November 2002 refers to a per son with mental illness as a person that is necessary to be detained, super vised, controlled and treated. It includes a person who is suspected o f being al leged to be mentally ill to such a de gree (Allwood, Gagiano, Gmeiner& Van Wvk (2002:268-270). Background and rationale Background and rationale Violence is everywhere and known to almost everyone, yet its impact on so ciety and its consequences to individu als need further studies. In the context o f South Africa, aggression and vio lence have become part and parcel o f everyday living. Thus, defining the concepts o f aggression, violence, and crime distinctively becomes difficult. It is almost impossible to open a news paper or watch news on television with out reading or seeing scenes o f vio lence and aggression. This state o f af fairs spares no one, as even babies on their mothers ’ backs are affected (Seale, Eliseev, & Rondgangerin “TheStar”, II October, 2006). Definition of concepts Violence: This is the unlawful use o f force (Thompson, 1996:16). In this arti cle, violence means any act, word, even attitudes, such as an intimidating fa cial expression, that creates fea r or negative feelings, leading to or result ing in physical or psycho-social un wanted results. This understanding is also extended to any actions, or inac tion, p rem editated and done con sciously or unconsciously, with the intention to harm, whether physically, emotionally, psychologically, or spiritu ally (Bimenyimana, 2008:7). Problem statement In this article, a Mental Health Care User (psychiatric patient) will mean any person (male or female), aged between 20 and 70years, admitted because o f a mental illness and who has spend at least six uninter rupted weeks in the mental healthcare institution (Bimenyimana, 2008:8). In her research on workplace violence in the health sector, Steinman (2003:27) shows that 61.9% o f all the health care workers interviewed had experienced violence o f one type or another during the period o f 12 months prior to the research study. Further on, she reveals that there are considerable differences in the violence experienced in public health sei-vices to that observed in pri vate health services. Steinman (2003: 29) states that the combined percent ages fo r health care workers who had been exposed as either direct or as wit nesses o f victims to physical workplace violence in both health care sectors were 30.9%. Within the public sector this figure was 42.5% and in the p ri vate sector 19.2%. She then concludes with the following statement: “These are alanning figures and more alarming, the huge discrepancy between the two sectors " (Steinman, 2033:29). In view o f the above background, ra tionale and problem statement the fol lowing questions were posed: What are the lived experiences by psy chiatric nurses o f aggression and vio lence from patients in a Gauteng psy chiatric institution where they care fo r these violent and aggressive users on a daily basis? What can be done to assist the psy chiatric nurses in order to prevent, or to deal effectively with violence and aggression from patients? Psychiatric Hospital/M ental Health Care Institution. This refers to a psy chiatric hospital, recognised by the National Health A uthoritv as such and known to care, treat, and rehabilitate people with mental disorders compre h en sively (G overnm ent G azette, 2002:10). The institution that will be referred to in this article is a psychiat ric hospital (Bimenyimana, 2008:8). Curationis September 2009 the psychiatric nurses to man age the aggression and vio lence from patients in the psy chiatric institution. ric institutions with regard to finding out what the psychiatric nurses ’ lived experiences o f aggression and violence from patients are, and the impact o f these experiences on the psychiatric nurses’ personal life and the service they render to the mental health care users (Bimenyimana, 2008:3). the psychiatric nurses to man age the aggression and vio lence from patients in the psy chiatric institution. Research objectives The research objectives were: • to explore and describe the lived experiences by psychiatric nurses o f aggression and vio lence from patients in a Gauteng psychiatric institution: and • to describe guidelines to assist • to explore and describe the lived experiences by psychiatric nurses o f aggression and vio lence from patients in a Gauteng psychiatric institution: and • to describe guidelines to assist Despite all these findings, little has been done in South African psychiat 5 Curationis September 2009 The findings Demographic Information All the participants were registered psychiatric nurses who had been work ing in the institution at leastfor the last two years. Out often participants, five were males and five were fem ales all aged between twenty and forty years old. They all participated voluntarily and willingly (Bimenyimana: 2008:33- 34). Transferability refers to the instance to which the findings can be applied in other contexts or with other participants (Babbie & Mouton, 2001:277). In this regard the researcher used purposive sa m p le; d en se d escrip tio n o f demographics o f participants; and a dense description o f results supported by direct quotations o f participants. Dependability refers to the evidence that, if the study were to be repeated with the same or similar participants in the same or similar context, its findings would be similar (Babbie & Mouton, 2001:278). The researcher utilised step w ise re p lica tio n o f th e resea rch method; code — recoding o f data; and Data Collection Interviews can reveal the discourses and language, verbal and non-verbal, which people use to construct their lived realities (Lee & Stanko, 2003:52). The researcher chose one-on-one in terviews because they can provide rich, meaningful insights into participants' experiences and the meanings they at tach to them, their feelings, attitudes and values. Interviews were audio taped; then transcribed. All participants were asked one question: "H owis vio lence an d aggression f o r you in this hospital? "Later on, in order to reach saturation (Shank, 2002:30), a chance was given, to those who preferred to tell their lived experiences o f aggres sion and violence in writing, to write a naive sketch. Research method The research was conducted in two phases: in phase one the lived experi ence by psychiatric nurses o f aggres sion and violence from patients in a Gauteng Psychiatric Institution is ex plored and described (Bimenyimana, 2008:18-24). In phase two guidelines are form ulated to assist psychiatric nurses to cope with aggression and violence fro m p a tie n ts in th eir w orkplace (Bimenyimana, 2008:24). Curationis September 2009 Curationis September 2009 dependability audit: Confirmability refers to the degree to which the findings are the product o f the focus o f the inquiry and not o f bi ases o f the researcher (Babbie & Mouton, 2001:278). The researcher used a dependability audit o f whole research process: -chain ofevidence- the researcher remainedfaithful to the academic and ethical requirements in conducting the research. The field- notes, observation and memos, were kept as guarantee that the findings, conclusions and recom m endations were supported by the data and that there was an internal agreement be tween the researcher’s interpretation and the actual evidence. Psychiatric Nurse: In this article psy chiatric nurse refers to a registeredpsy chiatric nurse. The psychiatric nurse is registered at the South African Nurs ing Council. appears to the people who are living it (Leedy, 1997:161). The researcher uti lised open coding (Creswell, 2004:256) to analyse the data. Themes and cat egories were identified. For the re searchers not to be overwhelmed by personal interest, and in order to keep objectivity and reduce bias (Burns & Grove, 2005:224), an independent coder with academic knowledge and compe tence in the field was used and a con sensus was reached between the re searcher and the independent coder. The researchers ’ task was to try to get to the heart o f the matter by looking for them es that lay con cealed in the unexamined events o f everyday life, to find meaningful, shared themes in dif ferent people ’s descriptions o f common experiences (Barritt in Leedy, 1997:162). appears to the people who are living it (Leedy, 1997:161). The researcher uti lised open coding (Creswell, 2004:256) to analyse the data. Themes and cat egories were identified. For the re searchers not to be overwhelmed by personal interest, and in order to keep objectivity and reduce bias (Burns & Grove, 2005:224), an independent coder with academic knowledge and compe tence in the field was used and a con sensus was reached between the re searcher and the independent coder. The researchers ’ task was to try to get to the heart o f the matter by looking for them es that lay con cealed in the unexamined events o f everyday life, to find meaningful, shared themes in dif ferent people ’s descriptions o f common experiences (Barritt in Leedy, 1997:162). Research design A research design is defined as a set o f guidelines and instructions to be fo l lowed in addressing the research prob lem (Mouton, 1996:107). In this re search study, a qualitative, descriptive and contextual research design was utilised (Bimenyimana, 2008:15-17). The central theme identified in the data is set out below. Psychiatric nurses working in this Mental Health Institution experience an overwhelming level o f violence and aggression from patients. This violence is real, active, and pervasive. It is ex pressed verbally, physically, and emo tionally, and it has contributing factors and negative consequences. The con- tributingfactors mentioned by the par Trustworthiness T ru stw orth in ess (B im enyim ana, 2008:24-27) refers to gaining knowledge and understanding o f the true nature, essence, meanings, attributes, and char acteristics ofa particular phenomenon understudy (Leininger, 1985:68). In or der to ensure trustworthiness, the re searcher paid attention to the follow ing criteria: credibility, transferability, dependability, and con firm ability (Marshall & Rossman, 1999:192-194). Credibility refers to the compatibility between the constructed realities that exist in the minds o f the participants, and those that are attributed to them (Babbie & Mouton 2001:277). The re searcher 's attention focuses on the fo l lowing aspects: p ro lo n g ed engage ment with the field; reflexivityjournal; triangulation; member checking; and structural coherence (Lincoln & Guba, 1985:302-305; Babbie & Mouton, 2001:277-278). Sample', a purposive sample o f psy chiatric nurses was utilised and one- on-one interviews were conducted with p a rtic ip a n ts u ntil sa tu ra tio n (LoBiondo-Wood& Haber, 1994:257) was reached. Ethical considerations Gorman et al„ (2005:43) point out that ethical considerations are very impor tant, given thefact that participants will provide in-depth highly personal infor mation, and that the information elic ited could potentially compromise ei ther the participants or the organisa tion. In this study, the principles o f ethi cal standards o f human dignity and human rights, benefit and harm, au tonomy and individual responsibility, consent, privacy and confidentiality, equity and justice, as stipulated by the United Nations Educational, Scientific and Cultural Organisation (UNESCO, 2006) were adhered to and applied (Bimenyimana,2008:27-29). 6 Curationis September 2009 Data Analysis The purpose o f data analysis is to at tempt to understand what a specific experience is like by describing it as it is found in concrete situation, and as it 6 Theme 1: Contributing factor to violance and agression from patients The researcher believes that there is more to the orientation o f newly em ployed psychiatric nurses than telling them what they should and should not do. In this institution, the first week o f employment is dedicated to the orien tation programme that focuses on the “do s ” and “don ’t ’ s ” with regard to legal matters. As fo r what to expect in the wards, this is left to the discretion o f the nursing staff in the ward, who themselves went through a similar ori entation. What seems to be the prob lem here is that there is no follow-up after this initial orientation, and despite the differences between wards, the same orientation is applied. The lack o f proper and structured orientation leads to frustration and renders newly employed psychiatric nurses more vul nerable to this violence and aggression. These are some o f their concerns: one said “/ was told by the sisters during orientation that there m ight be vio lence but yo u don ’t g et fu ll orienta tion ’’. Another one said: “The time that I was hit nobody helped me. They ju st said:you don ’/ have to worry, you are not bleeding, and it is nothing. In time you will see m ore”. Another one added: “Thefirst time I experienced violence in this hospital I was very, very scared. It was a fem ale and I didn ’t expect that a fem ale could be so violent... we were hiding and I was scared, confused... nobody sa id anything to me. ” In this theme the contributing factors to aggression and violence from pa tients in this hospital, as identified by participants, are grouped in four cat egories below: (Bimenyimana, 2008:42- 47). Staff shortages The shortage o f staff makes psychiat ric nurses overwork. This results in tiredness and jo b dissatisfaction. Psy chiatric nurses then become discour aged and even absent themselves from work as a sign o f protest against the situation in which they fin d them selves. This situation further decreases the already overstretched number o f staff causing more stress and anxiety to those on duty. This is what one o f the participants said: "There was a time when a patient was kicking win dows and then we had to p u t her in a side room and we were only two in the ward. So we còuldn ’t take her in a side room an d she was fighting us, yeah and our clothes were torn". Another partidipant mentioned: "Asyou can see today, I am working alone. I am one registered nurse to 35 patients. This shortage is demotivating. ” In Table 1 a summary an overview o f the themes and categories identified in the data is given (Bimenyimana, 2008: 37-38). Lack of support by management and the Multidisciplinary Team (MDT) The participants expressed their feel ings o f isolation and dissatisfaction concerning the support they expect from the management and the MDT. This lack o f support is experienced in many ways. Despite the shortage, it seem s th at the rest o f the multidisciplinary team expect the psy chiatric nurses do the work o f other members o f the team, but when psy chiatric nurses need a hand there is nobody to help. This participant said: “The nurses are expected to do every thing, like when the psych ologists com e here first o f all they a 'ill depend on you fo r assistance but at the end o f the day, they will not respect you. A doctor w ill expect you to do every thing: p a tie n ts 'file s a n d different forms, y e t when you are alone, nobody helps”. Another one added: “Usually the doctors w ill come and prescribe something, but they d o n ’t help. You are ju s t left alone there, yo u don ’t g e t help ”. • type o f the patients admitted and the hospital environment: • staff shortages; • lack o f support by management and multidisciplinary team (MDT); and • type o f the patients admitted and the hospital environment: • staff shortages; • lack o f support by management and multidisciplinary team (MDT); and • lack o f comprehensive orient- tion. Curationis September 2009 I think the management fa ils to see that we need supportjust to build us u p.” p olice to bring him here due to com mitting violence a t home after smok ing dagga. When he gets here, he then shifts that anger tow ard yo u fo r keep ing him here". Curationis September 2009 ticipants are, among others, the type o f patients admitted here, staff short age, lack ofsupport from the manage ment and from the members o f the multidisciplinary team (MDT), and the lack o f structured and comprehensive orientation. Psychiatric nurses faced with violence from patients experience negative feelings o f fear, anger, frus tration, despair, hopelessness, and helplessness. They then use ineffec tive coping mechanisms to deal with violence and aggression from patients. A m ong th ese in effective coping mechanisms are: substance abuse, ab senteeism, retaliation, a development o f an "I d o n ’t care attitude ",and apa thy tow ards the work and towards w h at is h appen in g arou nd them (Bimenyimana, 2008:36). ticipants are, among others, the type o f patients admitted here, staff short age, lack ofsupport from the manage ment and from the members o f the multidisciplinary team (MDT), and the lack o f structured and comprehensive orientation. Psychiatric nurses faced with violence from patients experience negative feelings o f fear, anger, frus tration, despair, hopelessness, and helplessness. They then use ineffec tive coping mechanisms to deal with violence and aggression from patients. A m ong th ese in effective coping mechanisms are: substance abuse, ab senteeism, retaliation, a development o f an "I d o n ’t care attitude ",and apa thy tow ards the work and towards w h at is h appen in g arou nd them (Bimenyimana, 2008:36). sise the mistakes made by the nurses. This participant said that “When the sta ff is assaulted, management is on the side o fth e p a tien t”. Another ech oed the first saying “When they come (meaning management), they talk to you, but it's like sort o f highlighting you r wrong doing m ost o f the time. I t ’s a ll abou t the patien t, the patien t, which is ok, but what about yo u as someone who is working and then who is going through a situation? ” This is also coupled with the fa ct that man agement is perceived as distant and does-not give credit to the nurses where this is due. This is what one partici pant had to say “Itg ets too frustrating when you work hard and you are not appreciated. The management should learn how to say thank you... The type of patients yp p Patients are admitted in this hospital on the basis o f their violent behaviour. In many cases, the fam ily requests as sistance from the police who use force to bring the patients to the hospital as if they were criminals making them think ofthe hospital as if it was a jail. Once in the hospital, the patients display their aggression towards nurses who are thought to be the cause o f their admis sion. This participant said: “Another cause o f violence is... our patients are involuntarily admitted. You will fin d that this patient is very angry and bit ter against his mother who called the As for management, participants com plained that in many instances manage ment is not there to help but to empha 7 Curationis September 2009 Curationis September 2009 1995:49). Table 1 Summary of the themes and categories identified during data analysis THEMES 1. Contributing factors to vio lence and aggression from patients CATEGORIES • Types o f patients admitted and the hospital environment: psychotic p a tients, patients who are violent by na ture, and criminals. The fact that all the wards are closed wards makes pa tients feel as if they are in prison. • Staff shortages: participants said that when there are enough staff on duty the violence from patients decreases as the staff can detect it before it erupts and control the situation. • Lack o f support by the management and the multidisciplinary team (MDT): each department seems to be doing its own thing without the coordina tion o f the whole. • Lack o f comprehensive orientation: newly employed stafffind it difficult to face violence from patients they had never been told o f and had not ex pected. They become fearful and this makes them vulnerable, as self-control and logical thinking are compromised. The experience o f aggression and violence from patients in cludes certain feelings, emo tions, and physical conse quences such as bodily injuries and damage to property (torn clothes and broken glasses) The psychiatric nurses exposed to this violence from patients experience negative feelings o f • Fear • Anger and frustration • Despair • Helplessness and Hopelessness • Apathy / Desensitisation • Resentment • Job dissatisfaction The experience o f aggression and violence from pa tients leads to ineffective coping mechanisms The psychiatric n urses’ ineffective coping mechanisms include: • Substance abuse • Absenteeism • Violence—in the form ofretaliation • Resentment • Apathy — "I don ’t care attitude " deve lops. It ld b f t l if th d i l Theme 2: The experiences of aggression and violence from patients include certain feelings and emotions (Bimenyimana, 2008: 47-53) Negative Emotions Related to Fear Participants verbalised fear in differ ent wavs. The main point is that for some participants this fea r tends to dictate their reactions and each time they think about going to work, they sense that the day is going to be another risk o f being harmed. Hence the work becomes a burden and the working environment is stressful. One said " / would walk on m y way to work, eish, ju s t feeling this heavy load on m y shoulders thinking I am going to that place, I ’m gonna fin d so and so and I know they are like this, they are gonna do this". An other one said "Ifyou go to the file and see that they have killed their parents, then they threaten you, you end up having fe a r ”. This partici pant added: “ There is one patient even who went to the poin t o f say ing that we will m eet outside. He knows he is gonna g et leave and he knows where I stay so we will meet outside and he will g et me. " Lack o f comprehensive orientation: newly employed stafffind it difficult to face violence from patients they had never been told o f and had not ex pected. They become fearful and this makes them vulnerable, as self-control and logical thinking are compromised. The psychiatric nurses exposed to this violence from patients experience negative feelings o f f p p g f g f • Fear • Anger and frustration • Despair • Helplessness and Hopelessness • Apathy / Desensitisation • Resentment • Job dissatisfaction U nm anageable fe a r m akes the caregivers feel small and helpless, unable to think clearly, while a feel- ing o f powerlessness overwhelms them (Carlsson, Dahlberg, Liitzen, <6 Nystrom, 2004:191-271). The experience o f aggression and violence from patients in cludes certain feelings, emo tions, and physical conse quences such as bodily injuries and damage to property (torn clothes and broken glasses) Theme 2: The experiences of aggression and violence from patients include certain feelings and emotions (Bimenyimana, 2008: 47-53) THEMES 1. Contributing factors to vio lence and aggression from patients Anger and Frustration Participants talked about experienc ing the above emotions basically becau se they fin d th em selves caught between their vocation fo r a caring career, and what they per ceive as the ingratitude o f some o f the patients who use their mental con dition as a shield and hurt psychiatric nurses, even when the patients are aware o f what they are doing. When the nurses become angry, depending on the target, the patients either with- It would be o f great value if, once the new nursing staff is employed, to be a llo c a te d to a se n io r nurse f o r mentoring purposes fo r at least fo r six months. This mentor should be cho sen based on his or her work ethics and commitment to serve as a role model. The main purpose o f this orien tation would be not to teach the newly employed psychiatric nurse, but to help him/her to adjust to the new working en vironm en t (Jooste á Troskie, 8 Apathy I Desensitisation volvement in the treatment and reha bilitation processes o f the patients. This makes psychiatric nurses experi ence that they are doing the same thing over and over admitting the same p a tients with no end to this vicious cir cle. Some participants even feel that they have lost direction that they no longer know why they are still working as psychiatric nurses, and they doubt their own caring capacity. This is what one o f them had to say: "I am some how dem otivated because there is no goal. / ask m yself what skills am I tak ingfrom here? "Another one echoed: "Everyday you com e to work, you are demotivated. You are ju s t working be cause you have no choice ”. draw and harbour resentment or they strike back in retaliation. Among the many factors that de-moti- vate psychiatric nurses, the main one is the multiple readmissions o f the same mental health care users over and over that make psychiatric nurses feel that they are labouring in vain. strike back in retaliation. Frieze (2005:83) argues that when some one is victimised, another type o f re sponse is to become angry and to fight back. This is exactly what one o f the participants did as she gives the ac count: "I was writing the report. He came into the office and said: who are you eh... like I was accusing him o f som ething an d before / cou ld even look, already he hit me. It was b ad and / was so angry. I nearly cried. But when I was on m y way to the toilet to cry, J decided no. I can give him a clap. / ju st went in and took him out then / d id figh t an d gave him a bit ofhis own medicine ". “Iam somehow de-motivatedbecause there is no goal; I ask m yself what skills am J taking from here? "Another said "Every day you come to work, you are de-motivated. You are ju s t working because yo u have no choice One said “I developed an 'ld o n 't care 'at titude because I felt that the manage ment d id little o r nothing to address the issues. Substance Abuse Resentment occurs when dealing with the situation becomes difficult and the end to the problem is not at sight. Some psychiatric nurses resort to keeping everything inside themselves and re senting the person who caused the pain, while waiting fo r an opportunity to strike back. Most specifically this happens when there is a conflict be tween a nurse and a member o f MDT or management. One nurse said “IVhen we had ward meetings I would be ex cluded, and m y suggestions o r opin ions would be brushed off. 1felt angry an d harboured deep resentment to wards the sister-in-charge. " Some ofthe participants mentioned that in order to cope with the amount o f aggression and violence from patients, they drink alcohol on a daily basis, whether they are on or off duty. One nurse said: "Maybe that's why in the nurses' home there are so many bot tles empty everywhere; they drink on an almost daily basis because I know people who drink every day. No mat ter in or out, o ff or on duty, every day they must drink. ” Helplessness and Hopelessness O f all the participants in this research stu dy, not one ex p ressed a hope that things would change fo r the better. In this battle that the psychiat ric nurses are faced with in caring fo r violent patients, it cannot be sufficiently emphasised how they feel. It would be an understatement to express the feel- ing o f hopelessness and helplessness that one reads on their faces as they talk about their experiences. “ The onl) • thing that helps is giving medication then we hope the patient will be fin e because there are patients who came here an d we g ive them medication. They becom e better yo u sen d them home, but they go an d do the same thing that they d id before. ” Frieze (2005:80) confirms that one o f the ways to avoid thinking about a highly stressful event is to get drunk, and he goes on to say that a large majority o f people o f all ages turn to others to share highly emotional experiences. Apathy I Desensitisation ” Lupton and Gillespie (1994:165) discov ered that the way many social services staff see their roles leads them to ac cept a certain level o f violence as nor mal because violence happens all the time. In an earlier study Cherniss (1980:5) had found that professionals who were working in extremely de manding, frustrating, or boring jobs, became less trusting and sympathetic toward clients. Absenteeism Although absenteeism first affects the psychiatric nurses who are in regular contact with the patients, some psy chiatric nurses absent themselves as a sign o f protest and to show dissatis faction at what is happening. This is how some expressed it: "Instead o f getting m oral support from their man agers and other members o f the team, nursing sta ff g et blam ed fo r each inci dent that happens. These things end Needham , A bderhalden, H alfens, Dassen, Haugand Fischer (2005:296— 300) found that adverse consequences such as avoiding the perpetrator or the perception o f an impaired relationship with the patient involved, can lead to psychiatric nurses doubting their pro fessional abilities or even provoke feel ings o f being a failure. Despair The participants ’ are ofthe opinion that they have done all they could and now that the result is not what they ex pected, they feel like ju st giving up. " / can think o f nothing g o o d since I came, here except maybe seeing them being well after seeing them coming to the hospital very sick and very p sy chotic, an d then seeing the change. You know it s almost like two different people but then they go home do the sam e things and come back! ” Substance Abuse Siann (1985:264) argues that it is when people feel at risk both psychologically and physically that the displacement o f their emotional insecurity on to oth ers becomes particularly rewarding. Resenting others mav.for a while, make the nurse forget the real source o f the problem. Job Dissatisfaction The things that de-motivate psychiat ric nurses include: the inaction o f man agement; the lack o f communication and coordination o f activities among the MDT; and the lack o f fam ily in 9 Burnout Some psychiatric nurses have come to the p o in t o f w on derin g why they should give their all to the work that is not rewarding. This participant said: “/ was n ot happy with the situation. I thought they d id not care, so started wondering why I should care about the h ospital a n d that attitude. Why sh ou ld / care i f p e o p le d o n ’t care about m e ’’? Guidelinel: Addressing factors contributing to violence and aggression Job dissatisfaction is often synony mous with burnout and can be associ ated, and even sometimes identified with, stress. According to Cherniss (1980:158) stress occurs when there is an imbalance between jo b demands and the w orkers’ resources fo r meeting them. This participant stated: “It is very challenging an d stressful waking up in the morning with the intention o f going to help patients, whereas these patients are going tofight you. We end up working f o r the sake o f our fa m i lies as there is nothing else we can do to survive. "Another one added: "... but the chair landed on m y fa c e and injured m y nose. I thought o f resign- ing from the institution an d seeking em ploym en t so m ew h ere e lse o r whether I should let patientsfight and not p u t m y life a t risk b y separating them. " In Table 2 an overview o f these guide lines and recommendations is given. Facilitation of Mental Health Approach to Mental Health Care Users There was a general concern among the participants thatfamily members o f the mental health care users seem to regard the hospital as a “dumping site". There fore, intensive health education to the community is needed because most o f the fam ily members do not understand what their relatives are going through, and the fam ily members become frus trated and powerless not knowing what to do to help them. Request fo r comprehensive orientation fo r newly appointed psychiatric nurses Newly em ployed psychiatric nurses need to know not only what the insti tution expects from them and how to be legally covered, but also the envi ronment in which they will be operat ing and what they can expect in the way ofchallenges and problems related to their work so that they will be able to use a variety o f skills (Seybolt in Booyens, 1998:375). The orientation o f an employee should be individualised in order to develop those specific skill and abilities required fo r the present placement (Booyens, 1998:375). Given Guidelines and recommendations (Bimenyimana, 2008:59- 71) Murphy et al., (1995:128) argue that too often the threat o f exposing anxiety about per formance or ill health, or fears o f in competence, or any sign that there is something wrong, forces managers to suppress or deny problems until it is too late. C urationis September 2009 Snyder (2001:290) argues that finding meaning plays a prominent role in the individual’s ad justment to negative events. In the af termath o f stressful situations, people want to understand what caused the events to happen, as well as determine the impact o f the event on their lives. C urationis September 2009 up causing emotional stress to nurs ing staff and this leads to alcohol abuses and a high rate o f absentee ism. ’’ up causing emotional stress to nurs ing staff and this leads to alcohol abuses and a high rate o f absentee ism. ’’ important points. Snyder (2001:290) argues that finding meaning plays a prominent role in the individual’s ad justment to negative events. In the af termath o f stressful situations, people want to understand what caused the events to happen, as well as determine the impact o f the event on their lives. However, one cannot fo ld on e’s arms and wait fo r miracles to happen. Em powering the limited number o f psy chiatric nurses available would be a large part o f the solution. To empower the psychiatric nurses, one must take into consideration the environment in which they are working, and their pro fessional and personal development. For example, the report from the exit interviews held by the human resource department o f the hospital, shows a pattern ofthe recurring problem o f “in adequate working conditions " as cited by the resigning psychiatric nurses. Improving these conditions may attract more psychiatric nurses, or at least re tain those already working there. N egotiation with m anagement and multidisciplinary team fo r support One is left wondering whether it makes sense to the psychiatric nurses that a psychologist can come to the w ardfor psychotherapy and expect the psychi atric nurses to be the ones to call the patient that he/she is going to be deal ing with fo r the next whole hour or so. Teamwork is also needed as, som e times, health care workers work against each other instead o f working together. What use is it if a doctor prescribes sedation fo r a violent patient when there are no psychiatric nurses to pin him/her down and administer the injec tion? Management must meet the psy chiatric nurses halfway and not wait fo r a crisis or pretend to ignore a prob lem when it is there. Murphy et al., (1995:128) argue that too often the threat o f exposing anxiety about per formance or ill health, or fears o f in competence, or any sign that there is something wrong, forces managers to suppress or deny problems until it is too late. important points. Facilitation of active recruitment of Psychiatric Nurses The problem o f the shortage o f psy chiatric nurses is not lim ited to this hospital; in fact it is a countrywide prob lem (http://www.sanc. co.za/stats.htm). In a situation like this one, when a per son starts asking him/herself whether he/she made a right choice, reassur ance and sense o f being valued are 10 Curationis September 2009 Guidelines and recommendations (Bimenyimana, 2008:59- 71) ) In formulating guidelines fo r psychi atric nurses, it would be a mistake to think that a lasting solution can be foun d without considering the p a tients, their family environment, and the community as a whole, since the vio lence is first lived and expressed there. The approach to managing violence and aggression must not only focus on short-term goals but also on long term goals and the starting point would be to know what violence really is. Gilligan (2000:92) argues that the only way to explain the causes o f violence, so that it can be prevented, is to ap proach it as a problem in public health and preventive medicine, and to think o f it as a symptom o f life-threatening pathology. Burnout is viewed as the exhaustion o f physical or emotional strength as a re sult ofprolonged stress or frustration (Felton, 1998:237-250). The situation in this institution calls fo r attention because the consequences o f burnout are not only detrimental to psychiatric nurses but also to the institution as a whole. Participants mentioned that at times they question why they ended up working in a psychiatric hospital. This study has shown some similari ties to Felton's (1998:237-250)findings: the situation reveals an increase in ab senteeism, behavioural changes, ex pressed by short-temperedness, and chemical abuse shown by daily alco hol drinking. N egotiation with m anagement and multidisciplinary team fo r support One is left wondering whether it makes sense to the psychiatric nurses that a psychologist can come to the w ardfor psychotherapy and expect the psychi atric nurses to be the ones to call the patient that he/she is going to be deal ing with fo r the next whole hour or so. Teamwork is also needed as, som e times, health care workers work against each other instead o f working together. What use is it if a doctor prescribes sedation fo r a violent patient when there are no psychiatric nurses to pin him/her down and administer the injec tion? Management must meet the psy chiatric nurses halfway and not wait fo r a crisis or pretend to ignore a prob lem when it is there. Management of aggression It appears that the best way o f manag ing aggression in this institution is find ing solutions to its leading causes. Staff development fo r example and a change o f approach by management may contribute considerably to man aging aggression. This may boost the morale o f the psychiatric nurses, who are already demotivated, and counter the absenteeism that seems to be a major factor contributing to violence. The negative feelings are a result o f a hostile environment and the psychiat ric nurses' inability’ to cope positively with the situation. One of the ways to manage these negative feelings would be a modification o f the environment in which these nurses are working. This can be done by hiring security person nel specifically in the forensic wards where state patients and observation patients are cared for. This also requires a structured environment. One o f the participants expressed the following concern: “ Two staff members on night The strategy to deal with the burnout, or at least to tolerate it, is associated with two occupational factors: length o f experience and level o f burnout (Whittington, 2002:819-825). Curationis September 2009 the fact that the institution has differ ent categories o f wards (acute wards, adolescent ward, and forensic wards), it is imperative that orientation be spe cific and diverse, otherwise, if the nec essary supervision o f the newly em ployed nurses is absent, even the best training system will not provide opti mum results (Booyens, 1998:27). duty were attacked by yen ■ dangerous observation patients and were both sent to hospital. After some discus sions, it was suggested that correc tional service personnel or police of ficers be allocated to that unit. A del egation from correctional services found that the structure o f the unit was not suitable fo r their personnel's safety. ” the fact that the institution has differ ent categories o f wards (acute wards, adolescent ward, and forensic wards), it is imperative that orientation be spe cific and diverse, otherwise, if the nec essary supervision o f the newly em ployed nurses is absent, even the best training system will not provide opti mum results (Booyens, 1998:27). Curationis September 2009 Table 2: challenges and possible corresponding solutions Themes and Categories Guidelines Theme 1: Contributing factors to violence and aggression • Type o f patients admitted into the hospital • Staff shortages • Lack o f support by management and multidisciplinary team • Lack o f comprehensive orientation Guideline 1: Addressing factors contributing to violence and aggression • Facilitation ofmental health approach to psychiatric patents • Facilitation o f active recruitment o f psychiatric nurses • Negotiation with management and multidisciplinary team fo r support • Request fo r comprehensive orientation fo r newly ap pointed psychiatric nurses Theme 2: Experiencing aggression and violence arouses the following feelings and emotions • Fear and despair • Anger and frustration • Helplessness and hopelessness • Job dissatisfaction Guideline2: facilitation o f the management o f aggression and violence by psychiatric nurses • Management o f negative feelings • Management o f aggression • Coping with stress Theme 3: The Physical consequences o f aggression and vio lence • Bodily injuries • Damage to property such as torn clothes and broken glasses Guideline 3: Addressing the concerns and trying to find solu tions to the problem • Debriefing o f psychiatric nurses after incidents o f aggression and violence • Speedy financial compensation Table 2: challenges and possible corresponding solutions • Debriefing o f psychiatric nurses after incidents o f aggression and violence • Speedy financial compensation actions can enable the nurses to live with this stressfu l environm ent. Murphy, Hurrell, Sauter and Keita (1995:221) argue that identifying and recognising the problem and taking steps to tackle it, perhaps by negotia tion, might arguably mitigate the whole stress process. In dealing with stress, the focus must be on the holistic ap proach, that is, not only taking into consideration the working environment o f the psychiatric nurse, but also his or her home environment. Murphy et al., (1996:228) state that workers do not leave their fam ily and personal prob lems behind when they go to work, nor do they forget jo b problems upon re turning home. Nearly all models o f jo b stress acknowledge the importance o f non-workfactors, and their interaction with work factors, in affecting health outcomes. Coping with Stress Given the situation in which the insti tution finds itself, it is not possible to eliminate the stress. However, some Curationis September 2009 versity Press. Guideline 3: Addressing the concerns of nurses and trying to find solutions to the problem Debriefing of nurses after incidences of aggression and violence pered by limits imposed on the expres sions o f feelings by having to use a foreign language. BABBIE, E & MOUTON, J 2001: The practice o f social research. Southern Africa: Oxford University Press. Suggestions for further research the long-term consequences o f aggression and violence from patients in psychiatric institu tions with regard to the quality o f care; BURNS, N & GROVE, SK 2005: The Practice o f Nursing Research: Conduct, Critique, and Utilisation.St Louis, Mis souri: Elsevier. the lived experience o f aggres sion and violence from patients in open and semi-open psychi atric hospitals; and the lived experience o f aggres sion and violence from patients in open and semi-open psychi atric hospitals; and CARLSSON, G; DAHLBERG, K & DREW , N 2004: Encountering Vio lence and Aggression in Mental Health Nursing: A Phenomenological Study o f Tacit Caring knowledge. Issues in Mental Health Nursing 21 (5): 533 — 545. Speedy Financial Compensation Participants voiced the concern that once their property has been damaged by the mental health care users, or once they have been injured, it takes too much time before they are compen sated. The nursing management could negotiate with the human resource de partment responsiblefor processing the documentation so that a time fram e could be agreed upon, as this would give the nurse victim o f this aggres sion an indication as to how to follow up, and to know how things are pro gressing. Suggestions for further research gg The institution does not have a proper program m e to deal with psychiatric nurses ’ stress-related problems. It re lies on the G auten g em p lo yees ’ wellness programme, called ICAS (In dependent Counselling and Advisory Services), that nurses can use fo r free. However, the participants in this re search study said that ICAS is a "face less " organisation because the initial contact is done on the phone in a con versation with someone one does not know. Again this reflects the lack o f teamwork in the institution because the psychological services are there fo r patients, so why not fo r the nurses in times o f crisis? BIMENYIMANA, E 2008: The Lived Experience o f Aggression and Violence in a Gauteng Psychiatric Institution. Unpublished MCur Psychiatric Nurs ing Mini-dissertation. Johannesburg: University o f Johannesburg The researcher would like to recom m end fu rth e r stu d ie s/re sea rch es (Bimenyimana, 2008: 72-73) in this field in order to cover the following issues: 1. the impact o f violence and ag gression from patients in psy chiatric hospital on the profes sional and personal lives o f the psychiatric nurses; 2. the long-term consequences o f aggression and violence from patients in psychiatric institu tions with regard to the quality o f care; 3. the lived experience o f aggres sion and violence from patients in open and semi-open psychi atric hospitals; and 4. the causes and reasons behind the psychiatric patients' attacks on the psychiatric nurses. The researcher would like to recom m end fu rth e r stu d ie s/re sea rch es (Bimenyimana, 2008: 72-73) in this field in order to cover the following issues: 1. the impact o f violence and ag gression from patients in psy chiatric hospital on the profes sional and personal lives o f the psychiatric nurses; The researcher would like to recom m end fu rth e r stu d ie s/re sea rch es (Bimenyimana, 2008: 72-73) in this field in order to cover the following issues: f g 1. the impact o f violence and ag gression from patients in psy chiatric hospital on the profes sional and personal lives o f the psychiatric nurses; BOOYSENS, SW 1998: Dimensions o f Nursing Management. Cape Town: Juta & Co, Ltd. 2. Conclusion CHERNISS, C 1980a: Professional Burnout: Job Stress in the Human Serv ices. Praeger: Sage. The purpose o f this study was to ex amine the lived experiences by psychi atric nurses o f aggression and violence from patients in a Gauteng psychiatric public institution, the essence o f this violence, and how psychiatric nurses experiencing this violence cope with the situation, so that guidelines could be drawn to help those nurses strug gling and prepare those contemplating working in a psychiatric institution. Various factors leading to this aggres sion and violence from patients have been discussed in detail. Guidelines and recommendations have been form u lated. It is therefore hoped that more research willfollow and that a solution will be developed to end this plight o f nurses who are exposed to violence from patients on a daily basis. The hope is that there will be a positive outcome which is the wholistic balanced men tal, physical, and psychosocial well being o f all those involved in this spe cial calling. CHERNISS, C 1980b: Staff Burnout. Job Stress in the Human Service. Praeger: Sage. CRESWELL, JW 2003: Research De- sign. Qualitative, Quantitative, and M ixed M ethods Approaches. Thou sand Oaks: Sage. References References A L L W O O D , C; G A G IA N O , C; GMEINER, A & VAN WYK, S 2002: Handbook o f Psychiatric Nursing for Primary Care. New York: Oxford Uni FRIEZE, IH 2005: Hurting the One You FRIEZE, IH 2005: Hurting the One You Limitations This research was done in a psychiat ric institution with closed wards, and it is unique as there has not been any research on the psychiatric nurses’ lived experiences by nurses o f violence and aggression from patients in psy chiatric institutions in South Africa. Hence this made it difficult as there were not enough theories or literature to analyse and compare the findings with. While the findings are contextualised within this institution, and given the fact that the researcher works in this hospital, an element o f bias cannot be totally excluded, though there was no intention on the side o f the researcher to be biased. The researcher and par ticipants com m unicated in English which is not their first language. The richness o f expression o f what psychi atric nurses feel may have been ham DAVIS, DA 1997: Threats Pending Fuses Burning. Managing Workplace Violence. California: Davies—Black. FELTON, JS 1998: Burnout as a clini cal entity—its importance in health care workers. Occupation Medicine 48 (4): 237-259. F O R ST E R , JA ; P E T T Y , M T; SCHLEIGER, C & W ALTERS HC 2005: Violence in Health Care—Policy and Strategy. Know workplace vio lence: Developing programs fo r man aging the risk o f aggression in the health care setting. Medical Journal o f Australia 183 (7):357-361. 2007). Love: Violence in Relationships. Cali fornia: Thompson Wadsworth. THE SOUTH AFRICAN NURSING COUNCIL 2007: Distribution o f the population o f South Africa versus Nurs ing Manpower. Available from http:// www.sanc.co.za/stats.htm. (accessed 24 June 2008). M ARSHALL, C & ROSSM AN, GB 1999: Designing Qualitative Research. California: Sage. GILLIGAN, J 2000: Violence: Reflec tions on Our Deadliest Epidemic. Lon don: Kingsley. MOUTON, J 1996: Understanding so cial Research. Pretoria: Van Schaik Pub lishers. GOVERNMENT GAZETTE, Republic o f South Africa, Mental Health Act I 7 o f2002, vol.449 Cape Town 6 Novem ber 2002 No. 24024. Available from internet: http://www.info.gov.za/ga- zette/acts/2002/a 17-02.pdf (accessed 05 March 2007). THOM PSON, D (Editor) 1996: The Pocket Oxford Dictionary o f Current English. Oxford: Oxford University Press. MURPHY, LA; HURREL, JJ^SAUTER, SL & KEITA, CP 1996: Job Stress In terventions. Washington, DC: Ameri can Psychological Association. UNITED NATIONS EDUCATIONAL, SCIENTIFIC AND CULTURAL OR GANISATION 2006: Division o f Sci ence and Technology Social and Hu man Science Sector. Universal Decla ration on Bioethics and Human Rights. Switzerland: UNESCO. GORMAN, GE & CLAYTON, P 2005: Qualitative Research fo r the Informa tion Professional. A Practical Hand book. London: Facet Publishing. NEEDHAMU; ABDERHALDEN, C; HALFENS, RJG; DASSEN, T; HAUG, H J & FISHER, JE 2005: The Impact o f Patient Aggression on Carers Scale: instrument derivation and psychomet ric testing. Scandinavian Journal o f Caring Sciences 19 (3):296-300. JOOSTE, K & TROSKIE, R 1995: Staff development fo r nurses. Halfway House, Midrand: Southern Book Pub lishers. W HITTINGTON, R 2002: Attitude tow ard patient aggression amongst mental health nurses in the ‘zero toler ance ’ era: associations with burnout and length o f experience. Journal o f Clinical Nursing. 11 (6), 819-825. NOBLE, P 2003: Violence in psychiat ric in-patients. Review and clinical im plications. Psychiatric Sen’ice 54:389- 393, March. American Psychiatric As sociation. KENNEDY, M A 2004: Workplace vio lence: an exploratory study into nurses' interpretations and responses to vio lence and abuse in trauma and emer gency departments. Masters Disserta tion. Western Cape: University o f West ern Cape. SE A L E , L; E L ISE E Y , A & RONDGANGER, L 2006: Baby shot dead on her mom's back: 15 — month- old infant becomes the youngest vic tim o f heist terror. Johannesburg: “The Star". October, 11 LEE, RM & STANKO, E 2003: Re search in g Violence. Curationis September 2009 2007). Love: Violence in Relationships. Cali fornia: Thompson Wadsworth. W orking with Violence. London: MacMillan Press. 2007). London: Routledge. SHANK, GD 2002: Qualitative Re search. A Personal Skills Approach. New Jersey: Merrill. LEEDY, P D 1997: Practical Research: Planning and Design. Upper Saddle River, New Jersey: Merrill. LEINIGER,MM 1985: Qualitative Re search Methods in Nursing. Orlando: Grune & Stratton. SIANN, G 1985: Accounting fo r ag gression: perspectives on aggression and violence. Boston: Allen & Unwin. LINCOLN, YS & GUBA, EG 1985: Naturalistic Inquiry. Newbury Park: Sage. SNY D ER , CR 2001: Coping with Stress: effective people and Processes. Oxford: Oxford University Press. STEINMAN, S 2003: International La bour Office ILO International Council o f Nurses ICN World Health Organiza tion WHO Public Services International PSI Joint Programme on Workplace V iolence in the H ealth S ector Workplace Violence in the Health Sec tor Country’ Case Study: South Africa. LOBIONDO-WOOD, G & HABER, J 1994: Nursing Research: methods, critical appraisal, and utilization. St. Louis: Mosby. LUCAS, M & STEVENSON, D 2006: Violence and abuse in psychiatric in patient institutions: A South African perspective. International Journal o f Law and Psvchiatrw M ay-Ju n e, 29 (3):l95-203. THE SOUTH AFRICAN NURSING COUNCIL 2005: Nurses Rights. Avail able from h ttp ://w w w .sa n c.co .za / policvrights.htm (accessed 05 March LUPTON, C & GILLESPIE, T 1994
https://openalex.org/W2562863359	https://jurnal.unimed.ac.id/2012/index.php/jpf/article/download/3698/3291	Indonesian	null	EFFECT OF INQUIRY LEARNING MODEL AND MOTIVATION ON PHYSICS OUTCOMES LEARNING STUDENTS	Jurnal Pendidikan Fisika	2,016	cc-by	3,861	Jurnal Pendidikan Fisika p-ISSN 2252-732X e-ISSN 2301-7651 Jurnal Pendidikan Fisika p-ISSN 2252-732X e-ISSN 2301-7651 D.M. Pardede dan S.R. Manurung: Pengaruh Model Pembelajaran Inquiry Training dan Motivasi terhadap Hasil Belajar Fisika Siswa PENGARUH MODEL PEMBELAJARAN INQUIRY TRAINING DAN MOTIVASI TERHADAP HASIL BELAJAR FISIKA SISWA Abstrak. Penelitian ini bertujuan: (a) untuk mengetahui perbedaan hasil belajar fisika siswa yang diajarkan dengan model pembelajaran menggunakan inquiry training dengan pembelajaran konvensional, (b) untuk mengetahui hasil belajar siswa yang diajarkan dengan model pembelajaran inquiry training dan konvensional (c) perbedaan hasil belajar siswa yang memiliki motivasi yang tinggi dan motivasi yang rendah, (d) interaksi antara model pembelajaran dengan motivasi dalam mempengaruhi hasil belajar siswa. Sampel dalam penelitian ini dilakukan secara cluster random sampling sebanyak dua kelas, dimana kelas pertama sebagai kelas eksperimen diterapkan model pembelajaran inquiry training dan kelas kedua sebagai kelas kontrol diterapkan pembelajaran konvensional. Hasil penelitian dapat disimpulkan bahwa: (a) terdapat perbedaan hasil belajar fisika siswa yang diajarkan dengan model pembelajaran inquiry training dan pembelajaran konvensional. (b) hasil belajar siswa yang diajarkan dengan model pembelajaran inquiry training lebih baik dari hasil belajar siswa yang diajarkan dengan pembelajaran konvensional. (c) hasil belajar siswa yang memiliki motivasi tinggi lebih baik dari hasil belajar siswa yang memiliki motivasi rendah. (d) terdapat interaksi antara model pembelajaran dan motivasi terhadap hasil belajar siswa. Hasil belajar siswa yang diajarkan dengan model inquiry training dipengaruhi juga oleh motivasi, hasil belajar siswa yang diajarkan dengan pembelajaran konvensional dipengaruhi oleh motivasi siswa. Katakunci: Motivasi, Inquiry Training, Hasil Belajar PENDAHULUAN Pendidikan merupakan salah satu usaha untuk mencerdaskan kehidupan bangsa dan merupakan suatu kunci pokok untuk mencapai cita-cita suatu bangsa. Pendidikan memegang peranan yang sangat penting bagi pengembangan siswa agar kelak menjadi sumber daya manusia berkualitas. Keberhasilan dalam bidang pendidikan membuat kualitas suatu bangsa mendapat pengakuan di seluruh dunia. Namun, pada kenyataannya kualitas pendidikan di Indonesia masih sangat memprihatinkan. Driana, (2013) menyatakan hasil Trends in International Mathematics and Science Studies (TIMSS) 2011, yang baru dipublikasikan, semakin menegaskan kondisi pendidikan di tanah air sangat memprihatinkan hasil sains tak kalah mengecewakan. Indonesia di urutan ke 40 dari 42 negara dengan nilai rata-rata 406 di bawah Indonesia ada Maroko dan Ghana. Yang paling mengherankan nilai matematika dan sains siswa kelas VIII Indonesia bahkan berada di bawah Palestina yang negaranya didera konflik berkepanjangan. g Fisika merupakan ilmu sains yang diajarkan di sekolah dan salah satu pelajaran yang dinilai dalam PISA. Berdasarkan hasil wawancara dengan salah satu guru di SMA Kalam Kudus Medan menyatakan pelajaran fisika sering kali dianggap siswa merupakan pelajaran yang sulit dan sangat membosankan, tidak mengherankan nilai pelajaran fisika lebih rendah dibandingkan pelajaran lain. Terlihat dari nilai rata-rata hasil ulangan harian fisika siswa di SMA Kalam Kudus Medan masih banyak di bawah Kriteria ketuntasan Minimal (KKM). Konsep fisika yang bersifat abstrak yang harus diserap siswa dalam waktu yang relatif terbatas menjadikan ilmu fisika menjadi salah satu mata pelajaran yang paling sulit bagi siswa sehingga banyak siswa yang gagal dalam belajar. Pada umumnya siswa cenderung dengan menghapal rumus dari pada secara aktif membangun pemahaman mereka sendiri terhadap konsep fisika. Proses pembelajaran yang masih tecaher centered tidak memberikan keleluasaan kepada siswa untuk berkembang secara mandiri, dimana guru hanya menekankan pada pemahaman konsep melalui hafalan-hafalan. Rendahnya kemampuan siswa-siswi Indonesia di matematika, sains, dan membaca juga tercermin dalam. Hasil Programme for International Student Assessment (PISA) 2012, Indonesia berada di peringkat ke 64 dari 65 negara yang berpartisipasi dalam tes. Indonesia telah ikut serta dalam siklus tiga tahunan penilaian tersebut yaitu 2003, 2006, dan 2009 hasilnya sangat memprihatinkan. Siswa-siswi Indonesia secara konsisten terpuruk di peringkat bawah. Berbagai upaya dilakukan pemerintah untuk meningkatkan mutu pendidikan antara lain dengan melengkapi sarana dan prasarana, meningkatkan kualitas pendidik, serta penyempurnaan kurikulum yang menekankan pada aspek-aspek yang bermuara pada peningkatkan dan pengembangan kecakapan hidup yang diwujudkan melalui pencapaian kompetisi peserta didik untuk dapat menyesuaikan diri dan berhasil dimasa yang akan datang. Motivasi merupakan salah satu faktor yang diduga besar pengaruhnya terhadap hasil belajar. Jurnal Pendidikan Fisika p-ISSN 2252-732X e-ISSN 2301-7651 Dahlia Megawati Pardede1 and Sondang R. Manurung2 1Student Alumni of Physics Education Study Programs Postgraduate School UNIMED 2Physics Education Study Programs Postgraduate School UNIMED email: dahliafisika@yahoo.co.id Abstract. The purposes of the research are: (a) to determine differences in learning outcomes of students with Inquiry Training models and Konvensional models, (b) to determine differences in physics learning outcomes of students who have high motivation and low motivation, (c) to determine the interaction between learning models with the level of motivation in improving student Vol.5 No.1 Juni 2016 http://jurnal.unimed.ac.id/2012/index.php/jpf 1 D.M. Pardede dan S.R. Manurung: Pengaruh Model Pembelajaran Inquiry Training dan Motivasi terhadap Hasil Belajar Fisika Siswa Physics learning outcomes. The results were found: (a) there are differences in physical students learning outcomes are taught by Inquiry Training models and konvensional models. (b) learning outcomes of students who are taught by Inquiry Learning Model Training better than student learning outcomes are taught with konvensional model. (c) there is a difference in student's learning outcomes that have high motivation and low motivation. (d) Student learning outcomes that have a high motivation better than student learning outcomes than have a low motivation. (e) there is interaction between learning and motivation to student learning outcomes. Learning outcomes of students who are taught by the model is influenced also by the motivation, while learning outcomes of students who are taught with konvensional models are not affected by motivation. Keywords: Motivation, Inquiry Training, Learning Outcomes yang seharusnya dilakukan dalam rangka perbaikan dan peningkatan mutu hasil belajar. Kualitas lulusan sekolah juga harus diperhatikan, karena banyak sekali faktor yang mempengaruhinya, ditinjau dari unsur siswa masih banyak faktor yang mempengaruhi baik faktor yang ada dalam diri siswa maupun dari luar diri siswa. Faktor yang ada dalam diri anak didik adalah faktor fisiologis dan psikologis. Misalnya: persepsi, minat, sikap, motivasi, bakat, IQ. Sedangkan faktor yang berada di luar diri anak didik misalnya lingkungan tempat tinggal, keadaan sosial ekonomi orang tua. METODE PENELITIAN Penelitian ini dilaksanakan di SMA Swasta Kalam Kudus Medan. Populasi dalam penelitian ini adalah seluruh siswa kelas X SMA Swasta Kalam Kudus Medan Tahun Pembelajaran 2014/2015. Jumlah populasi sebanyak 3 kelas paralel dengan jumlah siswa seluruhnya 116 orang siswa. Teknik pengambilan sampel dilakukan secara cluster random sampling sebanyak dua kelas, dimana kelas X-2 sebagai kelas eksperimen dengan jumlah siswa 35 orang diterapkan model pembelajaran inquiry training dan kelas X-4 sebagai kelas kontrol dengan jumlah siswa 35 orang diterapkan pembelajaran konvensional. Salah satu model pembelajaran yang tepat dan sesuai dalam penelitian ini adalah dengan menggunakan model inquiry training. Joyce, dkk, (2009) menyatakan model pembelajaran inquiry training dirancang untuk membawa siswa secara langsung ke dalam proses ilmiah melalui latihan-latihan yang dapat memadatkan proses ilmiah tersebut ke dalam periode waktu yang singkat, tujuannya adalah membantu siswa mengembangkan disiplin dan mengembangkan keterampilan intelektual yang diperlukan untuk mengajukan pertanyaan dan menemukan jawabannya berdasarkan rasa ingin tahu. Variabel penelitian ini terdiri dari 2 (dua) jenis, yaitu variabel bebas dan variabel terikat. Pada penelitian ini yang menjadi variabel bebas adalah model pembelajaran inquiry training, sedangkan variabel moderator pada penelitian ini adalah motivasi dan variabel terikat adalah hasil belajar. Melalui model pembelajaran inquiry training siswa diharapkan aktif mengajukan pertanyaan mengapa sesuatu terjadi kemudian mencari dan mengumpulkan serta memproses data secara logis untuk selanjutnya mengembangkan strategi intelektual yang dapat digunakan untuk dapat menemukan jawaban atas pertanyaan tersebut. Siddiqui (2013) menyatakan Model pelatihan inquiry training memberikan lebih menekankan pada pengembangan kesadaran dan menguasai proses penyelidikan. Jenis penelitian ini termasuk penelitian quasi eksperimen, yang bertujuan untuk mengetahui ada tidaknya akibat dari suatu yang dikenakan pada subjek didik yaitu siswa. Penelitian ini melibatkan dua kelas sampel yang diberi perlakuan yang berbeda. Pada kelas eksperimen diberi perlakuan yaitu model pembelajaran inquiry training. Sedangkan pada kelas kontrol diberi perlakuan yang biasa dilakukan sekolah dengan pembelajaran konvensional. Adapun desain penelitian yang digunakan adalah desain anava 2 x 2. Latihan inkuiri memberi kesempatan kepada peserta didik untuk mengembangkan keingintahuannya dan melakukan eksplorasi menyelidiki sebuah fenomena (Sani, 2013). Model Pembelajaran inquiry training terdapat tiga prinsip kunci, yaitu pengetahuan bersifat tentatif, manusia memiliki sifat ingin tahu yang alamiah, dan manusia mengembangkan individual secara mandiri. PENDAHULUAN Motivasi didefenisikan sebagai proses yang menstimulasi perilaku atau menggerakkan manusia untuk bertindak (Arends, 2007). Motivasi belajar adalah segala sesuatu yang dapat memotivasi peserta didik atau individu untuk belajar (Sani, 2013). Tella (2007) menyatakan siswa yang memiliki motivasi tinggi dan rendah memiliki prestasi belajar yang berbeda pula. Pengkajian tentang faktor-faktor yang mempengaruhi mutu hasil belajar merupakan usaha awal Vol.5 No.1 Juni 2016 http://jurnal.unimed.ac.id/2012/index.php/jpf 2 Jurnal Pendidikan Fisika p-ISSN 2252-732X e-ISSN 2301-7651 Jurnal Pendidikan Fisika p-ISSN 2252-732X e-ISSN 2301-7651 D.M. Pardede dan S.R. Manurung: Pengaruh Model Pembelajaran Inquiry Training dan Motivasi terhadap Hasil Belajar Fisika Siswa dari pengajar), dalam pendekatan inkuiri ini dapat memperoleh intrinsic reward, c). Peserta didik dapat mempelajari heuristik (mengolah pesan atau informasi) dari penemuan (discovery). Guru harus mampu memperbaiki hasil belajar fisika siswa yang rendah dengan memilih model pembelajaran yang sesuai, dan untuk mengatasi hal tersebut salah satu cara yang digunakan untuk meningkatkan prestasi belajar siswa adalah menggunakan model pembelajaran yang tepat sasaran ketika menyampaikan materi pembelajaran. Belajar harus sesuatu yang menyenangkan, simpel, menyenangkan dan efektif bagi diri siswa. Dengan begitu hasil belajar siswa akan meningkat, dan akan semakin memberikan kontribusi yang besar baik kegiatan proses belajar mengajar. METODE PENELITIAN Prinsip pertama menghendaki proses penelitian secara berkelanjutan, prinsip kedua mengindikasikan pentingkan siswa melakukan eksplorasi, dan yang ketiga kemandirian, akan bermuara pada pengenalan jati diri dan sikap ilmiah, tujuan umum dari model latihan inkuiri adalah membantu peserta didik mengembangkan keterampilan intelektual dan keterampilan lainnya, seperti mengajukan pertanyaan dan menemukan (mencari) jawaban yang berawal dari keingintahuan mereka. Untuk memperoleh data yang diperlukan pada penelitian ini, peneliti menggunakan dua instrumen pengumpulan data. Instrumen penelitian tes dalam penelitian ini adalah tes motivasi dalam bentuk angket yang telah diuji validitas, reliabilitas, taraf kesukaran dan daya pembedanya. Instrumen kedua adalah tes hasil belajar dalam bentuk soal butir soal (pilihan ganda) yang sesuai dengan taksonomi Bloom revisi. Tes ini juga telah diuji validitas, reliabilitas, taraf kesukaran dan daya pembedanya. http://jurnal.unimed.ac.id/2012/index.php/jpf Tabel 5. Pembagian Kelompok Motivasi Tinggi dan Rendah Tabel 3. Uji Homogenitas Pretes Uji Homogenitas Fhitung Ftabel Sig Ket. Berdasarkan rerata 0.009 3.99 0.924 Homogen Tabel 3. Uji Homogenitas Pretes Kelompok Interval Skor Jumlah PK IT Tinggi 76 – 86 17 19 Rendah 68 – 75 18 16 Hasil pengujian memperlihatkan nilai Fhitung untuk pretes hasil belajar 0,009 dengan signifikansi 0,924 (Ftabel= 3,99 , α= 0,05). Berdasarkan hasil tersebut Fhitung < F tabel dan signifikan hitung lebih besar dibandingkan α = 0,05 sehingga dapat disimpulkan data pretes hasil belajar kelas kontrol dan kelas eksperimen memiliki varians yang sama atau homogen. Uji normalitas dan uji homogenitas dari kedua kelas sampel dibutuhkan sebagai uji prasyarat untuk melakukan uji kesamaan kemampuan awal (uji t dua pihak). Karena data kedua kelas normal dan homogen maka dapat dilakukan uji kesamaan kemampuan awal dari kedua kelas sampel.Uji kesamaan varians dan rata-rata nilai pretes dilakukan dengan uji t sampel bebas menggunakan SPSS 16.0 dengan hasil pengujian pada Tabel 4. Setelah diberikan uji pretes kepada siswa maka selanjutnya diberikan perlakuan sesuai dengan model yang digunakan pada masing-masing kelas dimana pada kelas eksperimen diberikan model pembelajaran inquiry training dan pada kelas kontrol diberikan pembelajaran konvensional. Setelah perlakuan maka diberikan postes kepada siswa. Di mana hasil postes dapat dilihat pada Tabel 6. Tabel 1. Hasil Pretes Kelas Ekperimen dan Kelas Kontrol Tabel 1. Hasil Pretes Kelas Ekperimen dan Kelas Kontrol Tabel 2. Uji Normalitas Pretes Hasil Belajar Siswa Tabel 2. Uji Normalitas Pretes Hasil Belajar Siswa No Uji Normalitas Lhitung Ltabel Sig Ket. 1 Kontrol 0.136 0.154 0.099 Normal 2 Eksperimen 0.138 0.152 0.092 Normal Tabel 6. Hasil Postes pada Kelas Eksperimen dan Kelas Kontrol Tabel 6. Hasil Postes pada Kelas Eksperimen dan Kelas Kontrol Kelas Jumlah Rata-rata Eksperimen 35 11,28 Kontrol 35 9,88 Kelas Jumlah Rata-rata Eksperimen 35 11,28 Kontrol 35 9,88 Tabel 4. Uji Kesamaan Kemampuan Awal Pengujian thitung ttabel Sig Keterangan Uji t 0.314 1.67 0.754 Sama (tidak signifikan berbeda) HASIL PENELITIAN Deskripsi data yang disajikan dalam penelitian ini terdiri dari skor hasil belajar (HB) kelas kontrol dan kelas eksperimen. Pada tahapan penelitian ini kedua kelas sampel yaitu kelas eksperimen diajarkan dengan model Inquiry Training (IT) dan kelas kontrol akan diajarkan dengan Pembelajaran Konvensional (PK). Data hasil pretes dapat dilihat pada Tabel 1. Selanjutnya dilakukan uji normalitas untuk mengetahui kedua kelas berdistribusi secara normal dengan menggunakan SPSS 16.0. Uji normalitas belajar ditunjukkan pada Tabel 2. Model pembelajaran inquiry training memiliki lima fase sebagai sintaks pembelajarannya. 1) menghadapkan pada masalah dan merumuskannya. 2)merumuskan hipotesis. 3) mengumpulkan data eksperimen. 4) mengolah dan memformulasikan suatu data. 5) analisis proses dan hasil penyelidikan. Model pembelajaran inquiry training memiliki kelebihan a). Dapat membangkitkan potensi intelektual siswa, b). Peserta didik yang semula memperoleh extrinsic reward dalam keberhasilan belajar (seperti mendapat nilai baik Kelas kontrol diperoleh nilai Lhitung sebesar 0,136 dan signifikansi sebesar 0,099 (Ltabel = 0,154, α = 0,05). Vol.5 No.1 Juni 2016 3 http://jurnal.unimed.ac.id/2012/index.php/jpf Jurnal Pendidikan Fisika p-ISSN 2252-732X e-ISSN 2301-7651 Jurnal Pendidikan Fisika p-ISSN 2252-732X e-ISSN 2301-7651 D.M. Pardede dan S.R. Manurung: Pengaruh Model Pembelajaran Inquiry Training dan Motivasi terhadap Hasil Belajar Fisika Siswa Hasil menunjukkan bahwa Lhitung< Ltabel dan signifikansi lebih besar dari 0,05, maka data pada kelas kontrol adalah berdistribusi normal. Uji kesamaan varians dan rata-rata nilai pretes dilakukan dengan Test of Homogenety of Variance menggunakan SPSS 16.0 dengan hasil pengujian pada Tabel 3. Selain hasil penelitian berupa nilai hasil belajar, deskripsi hasil juga memuat data motivasi. Deskripsi data yang disajikan dalam penelitian ini terdiri dari skor motivasi dengan menggunakan model pembelajaran inquiry training dan pembelajaran konvensional. Pada tahapan penelitian kedua kelas sampel yaitu kelas inquiry training dan kelas pembelajaran konvensional diberikan angket motivasi yang bertujuan untuk melihat motivasi siswa pada kedua kelas tersebut. Kelas dengan pembelajaran konvensional memiliki rerata motivasi dengan nilai 76,17 dan kelas Inquiry Training memiliki rerata motivasi dengan nilai 75,77. Untuk pembagian kelompok tinggi dan rendah maka data di atas dibagi dalam 2 (dua) kelas. Data motivasi kedua kelas ini kemudian digabung menjadi satu dan dikelompokan menjadi 2 (dua) kelompok yaitu kelompok tinggi dan rendah berdasarkan median dengan interval yang dapat dilihat pada Tabel 5. Tabel 1. Hasil Pretes Kelas Ekperimen dan Kelas Kontrol Kelas Jumlah Rata-rata Eksperimen 35 3,85 Kontrol 35 3,97 Tabel 2. Uji Normalitas Pretes Hasil Belajar Siswa Tabel 4. Uji Kesamaan Kemampuan Awal Tabel 4. Uji Kesamaan Kemampuan Awal Berdasarkan hasil penelitian nilai postes hasil belajar pada kelas kontrol dengan model pembelajaran konvensional didapat rerata 9,88 dan kelas eksperimen dengan model pembelajaran inquiry training didapat rerata 11,28. Data postes hasil belajar siswa dikelompokan berdasarkan kelompok motivasinya yaitu kelompok tinggi dan rendah. Hasil belajar kelompok motivasi rendah dan tinggi dilihat pada Tabel 7. Berdasarkan pengujian kesamaan kemampuan awal dengan hasil thitung 0,314 dan signifikansi sebesar 0,754 (ttabel= 1,67, α = 0,05). Hasil ini menunjukkan bahwa -ttabel ≤thitung ≤ttabel dan nilai signifikansi lebih besar dibandingkan 0,05. Berdasarkan hasil tersebut disimpulkan bahwa tidak ada perbedaan kemampuan awal hasil belajar di kelas eksperimen dengan kelas kontrol atau dengan kata lain kedua kelas memiliki kemampuan awal yang sama. Hasil belajar yang diajarkan dengan model pembelajaran konvensional (PK) dan motivasi rendah (MR) diperoleh rerata 9,83 sedangkan pada motivasi tinggi (MT) dengan model pembelajaran konvensional (PK) diperoleh rerata 9,94. Vol.5 No.1 Juni 2016 http://jurnal.unimed.ac.id/2012/index.php/jpf 4 D.M. Pardede dan S.R. Manurung: Pengaruh Model Pembelajaran Inquiry Training dan Motivasi terhadap Hasil Belajar Fisika Siswa Jurnal Pendidikan Fisika p-ISSN 2252-732X e-ISSN 2301-7651 Jurnal Pendidikan Fisika p-ISSN 2252-732X e-ISSN 2301-7651 D.M. Pardede dan S.R. Manurung: Pengaruh Model Pembelajaran Inquiry Training dan Motivasi terhadap Hasil Belajar Fisika Siswa antara model pembelajaran dan motivasi terhadap hasil belajar siswa. Tabel 7. Data Disain Faktorial Rata-rata HB antar Model Pembelajaran dan Motivasi Kelompok Motivasi Rerata HB PK IT Tinggi 9,94 12,16 11,11 Rendah 9,83 10,25 10,03 Rerata 9,88 11,28 - Tabel 7. Data Disain Faktorial Rata-rata HB antar Model Pembelajaran dan Motivasi Gambar 1. Grafik Interaksi Uji Hipotesis Hasil belajar yang diajarkan dengan model pembelajaran inquiry training (IT) pada kelompok motivasi rendah diperoleh rerata 10,25 dan pada kelompok motivasi tinggi (MT) dengan model pembelajaran inquiry training (IT) diperoleh rerata 12,16. Setelah pengelompokan siswa dilakukan maka, dapat dilakukan uji hipotesis dengan menggunakan analisis varians (Anava) dua jalur. Tabel 8. Berikut ini menyajikan hasil analisis Anava dengan bantuan SPSS 16.0. Gambar 1. Grafik Interaksi Uji Hipotesis PEMBAHASAN Hasil uji statistik pada penelitian ini dengan menggunakan anava dua jalur untuk mengetahui apakah hasil belajar siswa dengan menggunakan model pembelajaran inquiry training lebih baik dari model pembelajaran konvensional. Untuk mengetahui apakah hasil belajar siswa yang memiliki motivasi tinggi lebih baik dari hasil belajar siswa yang memiliki motivasi rendah, dan untuk mengetahui interaksi model pembelajaran inquiry training dan motivasi terhadap hasil belajar siswa. Hasil yang diperoleh dalam penelitian ini menunjukkan terdapat perbedaan hasil belajar pada kelas ekspeimen yang menggunakan model pembelajaran inquiry training dan kelas kontrol dengan menggunakan model pembelajaran konvensional. Di mana hasil belajar dengan menggunakan model pembelajaran inquiry training lebih baik dari pada dengan menggunakan model pembelajaran konvensional. Dimana hasil belajar dengan menggunakan model pembelajaran inquiry training lebih baik dari pada dengan menggunakan model pembelajaran konvensional. Hal ini menunjukkan bahwa model pembelajaran inquiry training lebih efektif dalam meningkatkan hasil belajar temuan ini diperkuat dari rata- rata hasil belajar kelas eksperimen lebih tinggi dari pada nilai rata-rata kelas kontrol di mana rata-rata hasil belajar kelas eksperimen sebesar 11,28 sementara nilai rata-rata kelas kontrol sebesar 9,88. Dari nilai tersebut dapat dilihat bahwa hasil belajar dengan menggunakan model pembelajaran inquiry training lebih baik dari pada dengan menggunakan model pembelajaran konvensional. Hal ini karena model pembelajaran inquiry training melibatkan siswa secara aktif menemukan ilmu pengetahuan sendiri melalui proses penyelidikan. KESIMPULAN DAN SARAN Ada perbedaan hasil belajar siswa yang dibelajarkan dengan model pembelajaran inquiry training dan model pembelajaran konvensional. Hasil belajar siswa yang diajarkan dengan model pembelajaran inquiry training lebih baik dari hasil belajar siswa yang diajarkan dengan model pembelajaran konvensional. Begitu juga dengan motivasi Ada perbedaan hasil belajar siswa yang mempunyai motivasi tinggi dan motivasi rendah. Hasil belajar siswa yang mempunyai motivasi tinggi lebih baik dari hasil belajar siswa yang mempunyai motivasi rendah. Hal yang sama juga dalam interaksi Ada interaksi antara model pembelajaran dan motivasi terhadap hasil belajar siswa. Hasil belajar siswa yang diajarkan dengan model inquiry training dipengaruhi juga oleh motivasi, sedangkan hasil belajar siswa yang diajarkan dengan pembelajaran konvensional signifikan dipengaruhi motivasi. Pramukantoro, J & Wiratam, D. (2014). Perbedaan Model Pembelajaran Guided Inquiry dan MPL terhadap Prestasi Belajar Siswa yang Memiliki Motivasi Prestasi Berbeda Mada mata Pelajaran Teknik Listrik. Jurnal Pendidikan Teknik Elektro 3(1): 179-185. Diakses: November 2014 Sani, A. R. (2013). Inovasi Pembelajaran. Jakarta: Bumi Aksara Siddiqui, M., H. (2013). Inquiry Training Model of Teaching. IJSR-International Journal of Scientific Research vol 2.Tersedia: globaljournals.com, diakses: 25 nopember 2013 Tella, A. (2007). The impact of motivation on student’s Academic Achievement and learning Outcomes in School Students in Nigeria. Journal of innovation Research Education. Diakses: 28 Nopember 2014 Berdasarkan hasil dan kesimpulan penelitian ini, maka peneliti memiliki beberapa saran untuk menerapkan model pembelajaran inquiry training yaitu (1) Dalam penerapan model pembelajaran inquiry training guru harus memperhatikan motivasi siswa, karena model ini tepat untuk siswa yang motivasi tinggi. (2) Untuk siswa yang memiliki motivasi rendah disarankan untuk tidak diajarkan dengan model pembelajaran inquiry training karena siswa akan kesulitan dalam melakukan proses inquiry (penemuan) selama pembelajaran, siswa sulit menganalisis data dan fenomena alam yang mereka temukan selama pembelajaran. (3) Disarankan kepada peneliti lanjutan, kiranya dapat melanjutnya penelitian ini dengan menerapkan model pembelajaran inquiry training dengan bantuan metode ataupun media pembelajaran kreatif dalam proses pembelajaran untuk meningkatkan hasil belajar siswa. Vaishnav, R.S. (2013). Effectivness of Inquiry Training Model for Teaching Science. Scholarly Reseach Journal for Interdisciplinary Studies. 1(5):32-40. April 2013. Nagpur-India Zubaidah, S. (2008). Pembelajaran Kontekstual dengan metode inkuiri dan motivasi belajar IPA. Jurnal Pendidikan dan Pembelajaran. Vol 5(1): 19-25. Jurnal Pendidikan Fisika p-ISSN 2252-732X e-ISSN 2301-7651 Jurnal Pendidikan Fisika p-ISSN 2252-732X e-ISSN 2301-7651 D.M. Pardede dan S.R. Manurung: Pengaruh Model Pembelajaran Inquiry Training dan Motivasi terhadap Hasil Belajar Fisika Siswa D.M. Pardede dan S.R. Manurung: Pengaruh Model Pembelajaran Inquiry Training dan Motivasi terhadap Hasil Belajar Fisika Siswa akademik siswa dibanding metode konvensional. Mustachido (2013) yang menyimpulkan model inkuiri dapat meningkatkan prestasi belajar siswa SMA Driana. (2013). Gawat Darurat Pendidikan Nasional. Diakses: November 2013. Joyce, B., Weil, M., & Calhoun, E. (2009). models of teaching (edisi kedelapan). Model-Model Pengajaran (Terjemahan Achmad Fawai & Ateila Mirza). Yogyakarta: Pustaka Pelajar Hasil penelitian juga menunjukkan disimpulkan siswa yang memiliki motivasi belajar yang tinggi akan memperoleh hasil belajar yang lebih baik dibandingkan siswa yang memiliki motivasi belajar rendah. Zubaidah (2008) menyimpulkan siswa yang memiliki motivasi yang tinggi memperoleh hasil belajar IPA yang lebih baik dari pada siswa yang memiliki motivasi rendah. Terdapat interaksi antara model pembelajaran inquiry training dan motivasi terhadap hasil belajar siswa. Hal ini sesuai dengan hasil penelitian lain Pramunkantoro (2014) menyimpulkan ada interaksi antara model pembelajaran dan motivasi terhadap prestasi belajar siswa. Mustachfidoh. (2013). Pengaruh Model Pembelajaran Inkuiri Terhadap Prestasi Belajar Biologi Ditinjau Dari Inteligensi Siswa SMA Negeri 1 Srono. e-Journal Program Pascasarjana Universitas Pendidikan Ganesha Program Studi Pendidikan Sains 3(5): 20-23. Diakses: Agustus 2013 Pandey. (2011). Effectiveness of Inquiry Training Model Over Conventional Teaching Method on Academic Achivement of Student in India. Journal of Innovative Research in Education 1(1): 21-27. Maret, 2011. Dhanbad-India Tabel 8. Output Perhitungan ANAVA Dua Jalur Tabel 8. Output Perhitungan ANAVA Dua Jalur Source Type III Sum of Squares Df Mean Square F Sig. Model 30.215 1 30.215 10.023 0.002 Motivasi 17.704 1 17.704 5.873 0.018 model * motivasi 14.118 1 14.118 4.683 0.034 Berdasarkan Tabel 9 hasil perhitungan Anava dua jalur terdapat perbedaan hasil belajar antara siswa yang diajarkan menggunakan model pembelajaran inquiry training dengan siswa yang diajarkan menggunakan model pembelajaran konvensional, karena α = 0,05 > sig 0.002 dan Fhitung > Ftabel (10,023 > 4,01). Bagian motivasi diperoleh nilai signifikansi sebesar 0,018, artinya terdapat perbedaan hasil belajar siswa antara siswa yang memiliki motivasi rendah dengan siswa yang memiliki motivasi tinggi, karena α = 0,05 > sig 0,018 dan Fhitung > Ftabel (5,873 > 3,16). ) Bagian interaksi diperoleh nilai signifikansi sebesar 0,034, artinya ada interaksi antara pembelajaran konvensional dan inquiry training dengan motivasi dalam mempengaruhi hasil belajar, karena α = 0,05 > sig 0,034 dan Fhitung > Ftabel (4,683 > 3,16). Hasil interaksi antara model pembelajaran dan motivasi dapat dilihat pada Gambar 1. Berdasarkan Gambar 1 terlihat bahwa siswa yang diajarkan dengan pembelajaran konvensional memiliki rerata hasil kelompok motivasi tinggi sebesar 9,94 dan motivasi rendah sebesar 9,83. Sedangkan siswa yang diajarkan dengan model inquiry training memiliki rerata hasil kelompok motivasi tinggi sebesar 12,16 dan motivasi rendah sebesar 10,25. Grafik antara motivasi tinggi dan rendah pada model pembelajaran inquiry training dan pembelajaran konvensional berpotongan pada satu titik. Perpotongan ini menunjukan adanya interaksi Kesimpulan di atas sama dengan hasil penelitian sebelumnya. Mudjiono (2009) menyimpulkan terdapat pengaruh model pembelajaran inquiry training berbatuan portopolio dengan menggunakan media komputer terhadap hasil belajar. Vaishnav (2013) menyimpulkan bahwa model inquiry training efektif meningkatkan prestasi belajar siswa. Pandey (2011) menyimpulkan bahwa model inquiry training lebih efektif dalam meningkatkan prestasi Vol.5 No.1 Juni 2016 5 http://jurnal.unimed.ac.id/2012/index.php/jpf Arends. R. (2007). Learning to Teach (seven edition). New York: Mc Grawn Hill Companies. Inc http://jurnal.unimed.ac.id/2012/index.php/jpf REFERENSI Arends. R. (2007). Learning to Teach (seven edition). New York: Mc Grawn Hill Companies. Inc Arends. R. (2007). Learning to Teach (seven edition). New York: Mc Grawn Hill Companies. Inc http://jurnal.unimed.ac.id/2012/index.php/jpf http://jurnal.unimed.ac.id/2012/index.php/jpf Vol.5 No.1 Juni 2016 Vol.5 No.1 Juni 2016 6
https://openalex.org/W2976811937	https://www.fundamentaljournals.org/index.php/ijfps/article/download/21/30	English	null	The Energy-Mass relation indicates that in remote times there was a great explosion	International journal of fundamental physical sciences	2,019	cc-by	2,446	Fundamental Journals International Journal of Fundamental Physical Sciences (IJFPS) Fundamental Journals International Journal of Fundamental Physical Sciences (IJFPS) Fundamental Journals International Journal of Fundamental Physical Sciences (IJFPS) Original Research Papers Open Access Journals ISSN: 2231-8186 Original Research Papers Open Access Journals ISSN: 2231-8186 IJFPS, Vol 9 , No 3, pp 30-32, Sept, 2019 DOI: 10.14331/ijfps.2019.330127 IJFPS, Vol 9 , No 3, pp 30-32, Sept, 2019 DOI: 10.14331/ijfps.2019.330127 E.M Viladesau https://www.fundamentaljournals.org/index.php/ijfps E.M Viladesau https://www.fundamentaljournals.org/index.php/ijfps , , , pp , p , DOI: 10.14331/ijfps.2019.330127 ABSTRACT When we read about an author who pretends to deduce the expression 𝐸= 𝑚𝑐2 by mathematical procedures, we will see him rely on fallacies and lock himself into real labyrinths. What we mean is that he will intend to introduce the fallacy of time dilation and the inappropriate use of the Lorentz factor intervention. Moving away from these false paths, we do not treat the expression 𝐸= 𝑚𝑐2 as a mathematical formula, but instead, we investigate it as an expression on how to group these three physical magnitudes: Energy-Mass-Speed of light, in order to produce a work. With this approach, we will see that 𝐸= 𝑚𝑐2 is the expression of the history of an atom and the manifestation of the energy that it is capable of supplying. For this, we have created the Theory of the Meeting (TM) that allows us to go to the origin of when this energy was generated. We leave for consideration, analysis, and criticism, for experts in astrophysics and atomic physics. Keywords: Remote times, Energy-Mass-Speed, Theory of the Meeting (TM) Keywords: Remote times, Energy-Mass-Speed, Theory of the Meeting (TM) ©2019 The Authors. Published by Fundamental Journals. This is an open access article under the CC BY-NC https://creativecommons.org/licenses/by-nc/4.0/ ©2019 The Authors. Published by Fundamental Journals. This is an open access article under the CC BY-NC https://creativecommons.org/licenses/by-nc/4.0/ https://doi.org/10.14331/ijfps.2019.330127 https://doi.org/10.14331/ijfps.2019.330127 The Energy-Mass relation indicates that in remote times there was a great explosion Enrique Martinez Viladesau Escuela Técnica Superior de Ingenieros Industriales de Barcelona (ETSIUB), Spain E-mail addresses: emviladesau@gmail.com Received July 2019 Received in revised: Sept 2019 Published: Sept 2019 Received July 2019 Received in revised: Sept 2019 Published: Sept 2019 MANIFESTATIONS OF THE PHYSICAL MAGNITUDES To get to identify what the expression says that Eq (2) and continuing with the TM, we dealing with the information that a physical expression gives us, due to the relationships between the physical magnitudes that makes it up. We will accept that physical magnitudes, such as force, acceleration and …, can detect their existence through the manifestations that can be observed in the experimental field. For example, the acceleration 𝑎 that acquires a mass 𝑚, will betray the existence of a force that causes it. Another aspect will be the assessment of its intensity, in which case we will apply the formula 𝐹= 𝑚𝑎 but, according to what we said, we will now focus on considering the manifestations of the expressions of the physical quantities and avoid considering them as mathematical formulas that allow us to value them. 𝑣= ∫ 𝑒 𝑡 𝑓 𝑖 𝑑𝑡 (5) (5) where 𝑣 is the final speed that is to be reached after the time 𝑡 elapses between the initial and final points. However, we must bear in mind that the final point 𝑓 is located in the place where 𝑣 reaches the speed of light 𝑐, since this is the limit value of speed. Therefore, the acceleration between the starting point and the end point, that is, the increase in speed between zero and 𝑐, will be 𝛥𝑣 between 0 and 𝑐. So the referred force 𝐹 firstborn that acted on the particle must be expressed as, where 𝑣 is the final speed that is to be reached after the time 𝑡 elapses between the initial and final points. However, we must bear in mind that the final point 𝑓 is located in the place where 𝑣 reaches the speed of light 𝑐, since this is the limit value of speed. Therefore, the acceleration between the starting point and the end point, that is, the increase in speed between zero and 𝑐, will be 𝛥𝑣 between 0 and 𝑐. So the referred force 𝐹 firstborn that acted on the particle must be expressed as, 𝐹= 𝑈𝑚𝑐 (6) (6) The approach of considering only the aforementioned manifestations, allows us to encompass and connect within the same physical phenomenon different physical magnitudes. This will allow us to interpret the meaning of expression 𝐸= 𝑈𝑚𝑐2. It allows us to go back from current data to the origins that produced them. MANIFESTATIONS OF THE PHYSICAL MAGNITUDES Reasoning a way to the inverse of the one that we have used, we can say that the aforementioned expression tells us the story that there was a primogenital force due to that explosion, which ejected and pushed the atom we are analyzing. THEORY OF THE MEETING (TM) In the development of this study, we present our theory, which we have called the Theory of the Meeting (TM) as follow. In fact, the expression 𝐸= 𝑚𝑐2 not be seen as a mathematical formula but as a physical expression that encompasses different concepts. For this reason, we will never use the wrong words of formula or equation, but we will use the word of expression. With this, we want to avoid the interpretation that when writing 𝐸 = 𝑚𝑐2, we are interpreting it as a product of two variables, that is 𝐸 = 𝑚𝑐2. To avoid such an interpretation, we need to consider that 𝐸 is reunited to the physical magnitudes, mass 𝑚 and speed of light 𝑐. Consequently, in symbolic form, we write, 𝐹 = 𝑈𝑚𝑎 (3) (3) 𝐸= 𝑈𝑚𝑐2 (2) (2) and, the acceleration 𝑎 is expressed as, and, the acceleration 𝑎 is expressed as, Here we will define that, the expression of energy is equal to the reunion of mass and speed of light. To confirm our claim, we will inspect an atom containing this mass and identify it as the mass 𝑚 that we are testing. Here we will define that, the expression of energy is equal to the reunion of mass and speed of light. To confirm our claim, we will inspect an atom containing this mass and identify it as the mass 𝑚 that we are testing. 𝑎= 𝑈 𝜕𝑣 𝜕𝑡 (4) 𝑎= 𝑈 𝜕𝑣 𝜕𝑡 (4) (4) t e eu o o ass a d speed o g t. o co ou c a , we will inspect an atom containing this mass and identify it as the mass 𝑚 that we are testing. That 𝑣 here is being the speed that the atom was acquiring due to the thrust of the force 𝐹 and 𝑡 the time employed. On the other hand, we know that by using mathematical terms we can consider the variation of that velocity 𝑣 due to the aforementioned force, by means of the formula. (1) Here 𝐹 is the force that will have acted on the mass 𝑚 and 𝑒 is the space traveled by applying the aforementioned force. Therefore, the expression 𝐸= 𝑚𝑐2 shows that the above equation Eq (1) is the expression that manifests the origin and history of the atom. Here we present a theoretical approach that allows us to interpret our reasoning. We believe that this cause was an explosion that drove the atoms out of a common center. To justify that the said expression shows that the atom has incorporated the content of a force proceed as follows. We will use the TM and write as 𝐸 = ∪𝑚𝑐∪𝑐. With this expression, we want to indicate that the meeting of two events is joined. On one hand, there is the reunion of the mass 𝑚 with the speed of light. On the other hand, another meeting is added to this event, expressed as the speed 𝑐 of the light. Here we investigate the meaning of the expression 𝐸 = 𝑚𝑐2, which, as we shall see, leads us to reveal the existence of a force. In the previous issue, we have exposed the way in which the actions that perform the physical magnitudes are manifested. With the hypothesis that there was a big explosion, the first Physical magnitude that we will consider is force. The primogenital force acted on the atom at the origin of its existence. The physical magnitude that we are considering, by acting continuous on the particle, we know that it is manifested by the action of printing an acceleration 𝑎. Therefore, we can express this action as, IJFPS, Vol 9 , No 3, pp 30-32, Sept, 2019 IJFPS, Vol 9 , No 3, pp 30-32, Sept, 2019 E.M Viladesau 𝑇= 𝐹𝑒 us to admit there was a factor that caused the appearance of this force (Enrique Martinez Viladesau, 2018b). (1) INTRODUCTION the path from where this source of energy began (Enrique Martinez Viladesau, 2018a). We begin with considering the idea of the movement of atoms, in infinite directions, within the matter that contains them. By applying our reasoning about the mass 𝑚 of an atom and, we anticipate in this brief summary, what we will later justify with physical expositions. The start point is from the fact that the expression 𝐸= 𝑚𝑐2 contains two physical magnitudes whose joint action in a certain process can generate a large amount of energy. From this fact, we will go back in time to try to find In this return to the past and reinitiating the history of what happened, we hypothesized that a force 𝐹 of expansion intervened, perhaps due to an explosion, which in ancient times acted in all direction and on all atoms, between the atoms that we choose as a prototype in this paper. The force 𝐹 injected to the atom a potential to be able to develop a work. To identify this work 𝑇, we use the corresponding physical magnitudes that define as, https://doi.org/10.14331/ijfps.2019.330127 2231-8186/ ©2019 The Authors. Published by Fundamental Journals. This is an open access article under the CC BY-NC https://creativecommons.org/licenses/by-nc/4.0/ LOOKING FOR THE SYMPTOMS OF EXPLOSION As we have indicated 𝑊𝑈𝐹𝑐 and how we have obtained, 𝐹= 𝑈𝑚𝑐 is obtained 𝐸𝑝 ~ 𝑇 (6) (6) Applying the topic that we discussed on part three we will assimilate the content in potential energy with the quality of performing a work. Applying physical concepts, to identify the work (𝑇), we will use the following reunion of physical magnitudes as, 𝐸 ~ 𝑇= 𝑈(𝑚𝑐)𝑈𝑐= 𝑇𝑈𝑚𝑐2 (9) (9) which is the expression we were investigating. Here we can observe that 𝐸 is seen as the reunion of a quantity of movement that takes the mass and the space 𝑒 that was displaced, when measuring it in units of light speed 𝑢𝑣𝑙, it is expressed with c. In summary, the expression 𝐸= 𝑚𝑐2 placed in the test piece of analysis, and treated as the expression of a grouping of physical variables, informs us of what happened to the atom in ancient times and of what is able to perform. We leave the consideration, analysis and criticism, for the experts in astrophysics and atomic physics. 𝑇= 𝑈𝐹𝑒 (7) (7) That is, the work 𝑇 that the aforementioned expression states that the atom is capable of providing, has the atom saved and has it registered as the reunion of the first-born force 𝐹 of which we have spoken and 𝑒 the space that traveled the mass at the time when the events occurred. Recall that in the physical level, we measure the distances we move in light speed units 𝑈𝑣𝑒, so the referred particle, pushed by force 𝐹 Journal of Fundamental Physical Sciences (IJFPS), 8(3), 87-91. LOOKING FOR THE SYMPTOMS OF EXPLOSION By investigating through the expression, 𝐸 = 𝑚𝑐2 we show that the energy contained in the atom is manifested. Obtained the expression of the force 𝐹 that intervened, we must find out how the expression 𝐸 = 𝑈𝑚𝑐2 shows the capacity that the analyzed atom can perform a work 𝑇, that is, as the aforementioned expression states that the atom is in possession of supply a potential energy 𝐸. As previously mentioned, we started from the existence of an atom, which already existed in ancient times and we propose to relate the behavior of this atom in the current era, with what it expresses 𝐸 = 𝑚𝑐2. We will justify that the expression 𝐸= 𝑈𝑚𝑐2 shows that the atom has incorporated the content of a force and this will lead 31 IJFPS, Vol 9 , No 3, pp 30-32, Sept, 2019 E.M Viladesau This is another conclusion to come from the aforementioned expression. We justify the possession of this energy because the atom at a moment of its journey acquired a kinetic energy. By not consuming it, it was accumulated as potential energy 𝐸𝑝, and this potential energy can be expressed as having trapped the ability to perform a work 𝑇. We remember the idea of movement, in all directions, of the atoms contained in the material. We will propose the equivalence between this energy 𝐸𝑝 and its ability to perform a job 𝑇. This is to say that, This is another conclusion to come from the aforementioned expression. We justify the possession of this energy because came to move at the speed of light 𝑐. In addition, with this form, we measure the routes 𝑒 (Enrique Martínez Viladesau, 2008; Enrique Martinez Viladesau, 2018c, 2019). We value space 𝑒 in units of light speed 𝑢𝑣𝑙. If 𝑣 increases until reaching speed of light 𝑐, then is equivalent to having reached one unit 𝑐 so that 𝑒= 𝑐 and therefore, we have, 𝑇= 𝑈𝐹𝑐 (8) (8) To be able to show that the expression 𝐸𝑈𝑚𝑐2 in its content contains the idea of a potential energy, we propose the following reasoning. As we have indicated 𝑊𝑈𝐹𝑐 and how we have obtained, 𝐹= 𝑈𝑚𝑐 is obtained To be able to show that the expression 𝐸𝑈𝑚𝑐2 in its content contains the idea of a potential energy, we propose the following reasoning. Viladesau, E. M. (2019). Theory of Relativity: The Fallacy of the Principle of Equivalence. International Journal of Fundamental Physical Sciences (IJFPS), 9(1), 6-9. REFERENCES Viladesau, E. M. (2008). Theory of Relativity: LAP Lambert Academic Publishing Okt Viladesau, E. M. (2018c). Theory of special relativity: False premise that leads to obtain incorrect conclusions. International Journal of Fundamental Physical Sciences (IJFPS), 8(2), 83-86. Viladesau, E. M. (2018a). Theory of relativity-atomic watches and time dilation. International Journal of Fundamental Physical Sciences (IJFPS), 8(1), 1-4. Viladesau, E. M. (2019). Theory of Relativity: The Fallacy of the Principle of Equivalence. International Journal of Fundamental Physical Sciences (IJFPS), 9(1), 6-9. Viladesau, E. M. (2018b). Theory of relativity: Analysis of Lorentz transformation and Lorentz factor. International 32
https://openalex.org/W2101525769	https://europepmc.org/articles/pmc3741365?pdf=render	English	null	Genetic Variation in the Base Excision Repair Pathway, Environmental Risk Factors, and Colorectal Adenoma Risk	PloS one	2,013	cc-by	8,927	Abstract Cigarette smoking, high alcohol intake, and low dietary folate levels are risk factors for colorectal adenomas. Oxidative damage caused by these three factors can be repaired through the base excision repair pathway (BER). We hypothesized that genetic variation in BER might modify colorectal adenoma risk. In a sigmoidoscopy-based study, we examined associations between 182 haplotype tagging SNPs in 14 BER genes, and colorectal adenoma risk, and examined their potential role as modifiers of the effect cigarette smoking, alcohol intake, and dietary folate levels. Among all individuals, no statistically significant associations between BER SNPs and adenoma risk persisted after correction for multiple comparisons. However, among Asian-Pacific Islanders we observed two SNPs in FEN1 and one in NTHL1, and among African-Americans one SNP in APEX1 that were associated with colorectal adenoma risk. Significant associations were also observed between SNPs in the NEIL2 gene and rectal adenoma risk. Three SNPS modified the effect of smoking (MUTYH interaction p = 0.002; OGG1 interaction p = 0.013); FEN1 interaction p = 0.013)), one SNP in LIG3 modified the effect of alcohol consumption (interaction p = 0.024) and two SNPs in LIG3 modified the effect of dietary folate (interaction p = 0.001 and p = 0.08) on colorectal adenoma risk. These findings support a role for genetic variants in the BER pathway as potential modifiers of colorectal adenoma risk. Our findings strengthen the role of oxidative damage induced by key lifestyle and dietary risk factors in colorectal adenoma formation. Citation: Corral R, Lewinger JP, Joshi AD, Levine AJ, Vandenberg DJ, et al. (2013) Genetic Variation in the Base Excision Repair Pathway, Environmental Risk Factors, and Colorectal Adenoma Risk. PLoS ONE 8(8): e71211. doi:10.1371/journal.pone.0071211 Editor: Xiaoping Miao, MOE Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong Technology, China Editor: Xiaoping Miao, MOE Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China Received April 24, 2013; Accepted June 27, 2013; Published August 12, 2013 Copyright: 2013 Corral et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported by the National Cancer Institute, National Institutes of Health under 1R01 CA096830 and 5P01 CA42710. Dr. Abstract Stern received support from grant RSF-09-020-01-CNE from the American Cancer Society and from award number 5P30 ES07048 from the National Institute of Environmental Health Sciences and award number P30CA014089 from the National Cancer Institute. Roman Corral received support from NIH grant T32GM067587. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: marianas@usc.edu Genetic Variation in the Base Excision Repair Pathway, Environmental Risk Factors, and Colorectal Adenoma Risk Roman Corral1, Juan Pablo Lewinger1, Amit D. Joshi1,2, A. Joan Levine1,3, David J. Vandenberg1, Robert W. Haile1,3, Mariana C. Stern1* 1 Department of Preventive Medicine, Keck School of Medicine of USC, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, United States of America, 2 Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America, 3 Division of Oncology, Department of Medicine, Stanford School of Medicine, Stanford, California, United States of America SNP Selection and Genotyping yp g TagSNPs for each BER gene were selected using Haploview Tagger [30] based on the HapMap CEPH (CEU) population using the following criteria: minor allele frequency (MAF) $5%, pairwise r2$0.95, and a distance from the closest SNP greater than 60 base pairs on the Illumina platform. Linkage disequilib- rium (LD) blocks were defined using data from HapMap data release #16c.1, June 2005, on NCBI B34 assembly, dbSNP b124. For each gene, we included the 59- and 39-most SNP within the LD block within ,10 kb upstream and ,5 kb downstream. In regions of no or low LD, tagSNPs with a MAF $5% at a density of , 1 per kb were selected from either HapMap or dbSNP. In this analysis, we report our results for 182 tagSNPs across 14 genes that participate in the BER pathway (Table 1 and Table S1). TagSNPs were genotyped on the Illumina GoldenGate platform, as we previously described [31]. Among the BER genes in our study, we required that all 182 tagSNPs have call rates $0.90 and that we not observe evidence of statistically significant deviations of observed from expected values, when assuming Hardy- TagSNP 6 environmental risk factor interactions. We investigated whether BER genes tagSNPs modify the effect of alcohol use, dietary folate intake, or smoking in all individuals and in non-Hispanic Whites (NHW) only. We categorized smoking variables using median values among smoking controls to create the following variables: smoking status (never, quit, current), years of smoking (0, #26 years, .26 years), pack-years smoked (0, #21 pack years, .21 pack years). We also considered the following alcohol intake variables: number of drinks per day (never, #1 drink/day, .1 drink/day) and median daily alcohol intake (using median intake among drinking controls as a cut point: 0, #6 g/d, .6 g/d), with one alcoholic drink per day defined as approxi- TagSNP 6 environmental risk factor interactions. We investigated whether BER genes tagSNPs modify the effect of alcohol use, dietary folate intake, or smoking in all individuals and in non-Hispanic Whites (NHW) only. We categorized smoking variables using median values among smoking controls to create the following variables: smoking status (never, quit, current), years of smoking (0, #26 years, .26 years), pack-years smoked (0, #21 pack years, .21 pack years). Ethics Statement The research protocol was approved by the institutional review boards at both USC and Kaiser Permanente, and all subjects signed a written informed consent approved by both institutions. Introduction We included in final analyses genotype data from 1,368 (94%; 677 cases and 691 controls) of 1,457 total subjects in this study. Demographic and matching characteristics for individ- uals with and without genotype data were not statistically significantly different. ment. The base excision repair (BER) pathway, is the predominant mechanism for repair of oxidative DNA damage [24]. We hypothesized that genetic variation in BER genes may modify the risk of colorectal adenomas, in particular, in combination with smoking, alcohol, and low dietary folate. We examined potential associations between single nucleotide polymorphisms (SNPs) in genes involved in BER and distal adenoma risk, and considered their role as potential modifiers of the effect of cigarette smoking, alcohol consumption, and dietary folate intake. Using data and samples from a sigmoidoscopy-based study conducted in Los Angeles County we comprehensively investigated associations between genetic variation in 14 BER genes and colorectal adenoma risk. Statistical Analysis SNP main effect analyses. Deviations of observed genotype frequencies from those expected when assuming HWE were examined among controls by race/ethnicity using exact tests. We used unconditional logistic regression, assuming a log-additive model, to estimate per-allele odds ratios (ORs) and corresponding 95% confidence intervals (95% CIs) for the association between genotype and adenoma risk, adjusting for race (Non-Hispanic Whites, Latinos, African-American, Asian/Pacific Islander), study phase (phase I/phase II), age at sigmoidoscopy (continuous), gender, exam date, and clinic (Bellflower or Sunset). In this study, similar results are obtained when using unconditional logistic regression adjusting for the matching factors as using conditional logistic regression, with the benefit of using all genotype information in the study population [26]. Additional control for the following adenoma risk factors did not change ORs by more than 10%; therefore, they were not included in final analyses: alcohol intake (g/day), smoking status, dietary folate intake (mcg/ day), body mass index, multivitamin use (yes/no), total caloric intake, total dietary fiber (g/day). Study Subjects Study participants were enrolled in a University of Southern California/Kaiser Permanente study of risk factors for colorectal adenomas. All individuals were examined by flexible sigmoidos- copy from 1991 to 1993 (phase I) and from 1993 to 1995 (phase II) at one of two southern California Kaiser Permanente clinics (Bellflower or Sunset), and were recruited using identical criteria, as we have previously described [25,26]. Briefly, cases were individuals with a first-time diagnosis of a histologically confirmed adenoma. Controls were selected from the remaining eligible individuals who did not present with polyps at sigmoidoscopy examination and had no past history of histologically confirmed adenomas. Controls were individually matched to cases by gender, age (within 5 years), sigmoidoscopy date (within 3 months), and Kaiser Permanente clinic. All subjects signed a written informed consent approved by the Institutional Review Board, donated a blood sample, and completed two questionnaires. A risk factor questionnaire was administered during an in-person interview, and collected data on demographics, smoking history, family history of cancer, physical activity and other factors described previously [27,28]. A semi-quantitative food frequency questionnaire was administered in reference to diet during the year before sigmoidoscopy examination, as previously described [29]. When testing SNP main effects we corrected for multiple testing within each gene region as well as across all BER gene regions investigated. Specifically, for each tagSNP obtained under a log- additive model, p-values were corrected for multiple testing, taking into account multiple correlated tests due to LD between SNPs within each gene region, using the PACT (p-value adjusted for correlated tests) method implemented in the PACT R package [32]. Additionally, we corrected for multiple testing between gene regions by applying a Bonferroni correction multiplying each PACT p-value by the 14 investigated BER gene regions to determine overall pathway significance (ppathway) [33]. We assessed potential heterogeneity of SNP main effects by race/ethnicity (among tagSNPs with MAF .5% in controls for each race/ ethnicity), by performing 3df likelihood-ratio tests of interaction between genotypes and race/ethnicity. We used multinomial logistic regression to examine differences in SNP main effects by adenoma location (rectal versus left colon) and adenoma size (,1 cm) versus $1 cm) with respect to the control group. SNP main effect p-values for stratified analyses were corrected using PACT as described above. When considering linkage between different SNPs we used the square of the correlation coefficient (R2) to estimate pairwise LD using Haploview [30]. Introduction smoke contains reactive oxygen species (ROS) and chemical carcinogens [11] which can damage DNA [11,12]. Additionally, smoking has been associated with decreased folate levels [13], which may contribute to folate deficiency, which is associated with double strand breaks and abasic sites [14]. Colorectal cancer (CRC) is the third most common cancer diagnosed in men and women and is the third leading cause of cancer death in the United States [1]. In 2011, there were approximately 141,210 individuals diagnosed with CRC and 49,380 deaths from this disease in the United States [1]. More than 80% of CRC evolve from neoplastic adenomatous polyps or adenomas [2]. Prevalence of adenomas is estimated at 30% at age 50 and 40% by age 60 [3]. Compared to small (,1 cm) adenomas, larger ones ($ 1 cm) have a greater potential to grow and progress into CRC [4]. Use of endoscopy screening with polyp removal has significantly reduced CRC incidence and mortality [5,6], reinforcing the pathogenetic relationship between adenomas and CRC. Therefore, the identification of risk factors for adenoma development has significant public health implications. Alcohol consumption is currently considered a convincing CRC risk factor [15,16]. Increasing alcohol intake has previously been shown to reduce folate levels [17,18]. Alcohol metabolism generates acetaldehyde, a known mutagen which generate ROS in the colon lumen [19,20], directly inhibits O6 methylguanine- methyl-transferase, an enzyme involved in removal of alkylation- induced DNA damage, and leads to hyper regeneration of crypt cells which induces multiple forms of DNA damage [19,21]. In addition, alcohol metabolism can induce cytochrome P450 enzymes, which can increase activation of chemical pro-carcino- gens [19,22,23]. Cigarette smoking [7,8] and folate deficiency [9] are established adenoma risk factors, whereas folate supplementation may promote progression of established adenomas [10]. Cigarette Overall, smoking, alcohol consumption and decreased folate availability can lead to oxidative DNA damage and excess uracil misincorporation, which may all contribute to adenoma develop- 1 PLOS ONE \| www.plosone.org August 2013 \| Volume 8 \| Issue 8 \| e71211 BER Pathway and Colorectal Adenoma Risk BER Pathway and Colorectal Adenoma Risk Weinberg equilibrium $0.00027 using exact tests (Bonferroni- corrected p value; a = 0.05/182). All tagSNPs met these two requirements. Additionally, we required all individuals had overall call rates $90%, which led to exclusion from analyses of 89 individuals. BER Genes and Colorectal Adenoma Risk Among all individuals combined, out of the 182 tagSNPs only NEIL2 rs11785481 showed a statistically significant association with adenoma risk; however, it was not statistically significant after multiple comparisons adjustment within gene region (PACT) (OR = 0.70; 95%CI = 0.55–0.90; p = 0.006; PACT = 0.140) (Table 3). We corrected for multiple testing by applying two Bonferroni corrections to the crude interaction p-values which we report separately: first, we applied a within gene region Bonferroni correction (interaction pgene), by considering the number of tagSNPs in its respective gene region; second, we applied an overall pathway Bonferroni correction (interaction ppathway), by considering the 14 investigated BER gene regions. Statistical significance was declared if either corrected p-values were ,0.05. All tests conducted were two sided and all statistical analysis were conducted using Stata 11 SE (Stata Corporation, College Station, TX) and the R programming language (The R Project for Statistical Computing, http://www.r-project.org). When considering stratified analyses by racial/ethnic group, among African-Americans we observed an association with APEX1 rs17111750 (OR = 2.19; 95%CI = 1.36–3.55; PACT = 0.013; ppathway = 0.180; pheterogeneity = 0.004)(Table 3). Among Asian- Pacific Islanders we observed an association with two tagSNPs in the FEN1 gene, rs108499 (OR = 2.12; 95%CI = 1.30–3.45; PACT = 0.009; ppathway = 0.129; pheterogeneity = 0.024) and rs509360 (OR = 0.40; 95%CI = 0.30–0.79; PACT = 0.011; ppathway = 0.159; pheterogeneity = 0.052), and one tagSNP in NTHL1, rs2516781 (OR = 0.45; 95%CI = 0.25–0.80; PACT = 0.032; ppathway = 0.461; pheterogeneity = 0.062)(Table 3). All estimates of per-allele associa- tions for adenoma risk among all individuals combined and by race/ethnicity are shown in Table S2. SNP Selection and Genotyping We also considered the following alcohol intake variables: number of drinks per day (never, #1 drink/day, .1 drink/day) and median daily alcohol intake (using median intake among drinking controls as a cut point: 0, #6 g/d, .6 g/d), with one alcoholic drink per day defined as approxi- August 2013 \| Volume 8 \| Issue 8 \| e71211 PLOS ONE \| www.plosone.org 2 BER Pathway and Colorectal Adenoma Risk Table 1. Base excision repair pathway genes investigated. Gene Symbol # tagSNPs Chromosomal location Protein Function APEX1 13 14q11.2 Endonuclease FEN1 7 11q12 Endonuclease LIG1 23 19q13.2-q13.3 Ligase LIG3 7 17q11.2-q12 Ligase MUTYH 7 1p34.1 Glycosylase NEIL1 4 15q33.33 Glycosylase NEIL2 43 8p23.1 Glycosylase NTHL1 9 16p13.3 Endonuclease and Glycosylase OGG1 7 3p26 Glycosylase PARP1 18 1q41-q42 poly(ADP-ribosyl)ation POLb 6 8p12-p11 Polymerase POLD1 7 19q13.3 Polymerase SMUG1 10 12q13.11–13.3 Glycosylase XRCC1 21 19q13.2 Scaffolding protein Genes are listed according to HUGO gene nomenclature format (http://www.genenames.org), Abbreviations: APEX1, APEX nuclease 1; FEN1, flap structure-specific endonuclease 1; LIG1, ligase I, DNA, ATP-dependent; LIG3, ligase III, DNA, ATP-dependent; MUTYH, mutY homolog (E. coli); NEIL1, nei endonuclease VIII-like 1 (E. coli); NEIL2, nei endonuclease VIII-like 2 (E. coli); NTHL1, nth endonuclease III-like 1 (E. coli); OGG1, 8-oxoguanine DNA glycosylase; PARP, poly (ADP-ribose) polymerase 1; POLb, polymerase (DNA directed),beta; POLD1, polymerase (DNA directed), delta 1, catalytic subunit 125 kDa; SMUG1, single-strand-selective monofunctional uracil- DNA glycosylase 1; XRCC1, X-ray repair complementing defective repair in Chinese hamster cells 1. doi:10.1371/journal.pone.0071211.t001 Genes are listed according to HUGO gene nomenclature format (http://www.genenames.org), Abbreviations: APEX1, APEX nuclease 1; FEN1, flap structure-specific endonuclease 1; LIG1, ligase I, DNA, ATP-dependent; LIG3, ligase III, DNA, ATP-dependent; MUTYH, mutY homolog (E. coli); NEIL1, nei endonuclease VIII-like 1 (E. coli); NEIL2, nei endonuclease VIII-like 2 (E. coli); NTHL1, nth endonuclease III-like 1 (E. coli); OGG1, 8-oxoguanine DNA glycosylase; PARP, poly (ADP-ribose) polymerase 1; POLb, polymerase (DNA directed),beta; POLD1, polymerase (DNA directed), delta 1, catalytic subunit 125 kDa; SMUG1, single-strand-selective monofunctional uracil- DNA glycosylase 1; XRCC1, X-ray repair complementing defective repair in Chinese hamster cells 1. doi:10.1371/journal.pone.0071211.t001 Genes are listed according to HUGO gene nomenclature format (http://www.genenames.org), Abbreviations: APEX1, APEX nuclease 1; FEN1, flap structure-specific endonuclease 1; LIG1, ligase I, DNA, ATP-dependent; LIG3, ligase III, DNA, ATP-dependent; MUTYH, mutY homolog (E. coli); NEIL1, nei endonuclease VIII-like 1 (E. coli); NEIL2, nei endonuclease VIII-like 2 (E. coli); NTHL1, nth endonuclease III-like 1 (E. SNP Selection and Genotyping coli); OGG1, 8-oxoguanine DNA glycosylase; PARP, poly (ADP-ribose) polymerase 1; POLb, polymerase (DNA directed),beta; POLD1, polymerase (DNA directed), delta 1, catalytic subunit 125 kDa; SMUG1, single-strand-selective monofunctional uracil- DNA glycosylase 1; XRCC1, X-ray repair complementing defective repair in Chinese hamster cells 1. doi:10.1371/journal.pone.0071211.t001 mately 15 grams of ethanol. We considered a dietary folate intake variable (low/medium/high) defined using tertiles of dietary folate intake among controls as cut points: #267 mcg/day, .267– 387 mcg/day, $388 mcg/day). and Phase II participants. However, Phase II participants had higher dietary folate intake than those who participated in phase I (p = ,0.001). Fifty-two percent of enrolled subjects were NHW. The mean age of cases was 61.46 years (66.75) and the mean age of controls was 61.67 years (66.88). Cases smoked longer and more intensely than controls and were more likely to be current smokers (p,0.001). Cases were also found to have a lower mean dietary folate intake (mcg/d) and a lower mean dietary fiber intake (g/d) than controls (p = 0.013; p = 0.036). Approximately 81% of adenomas were colon adenomas and approximately 67% were small adenomas (,1 cm). Analyses of gene-environment interactions (GxE) were con- ducted by testing interaction terms between tagSNPs (assuming a log-additive model) and each environmental exposure using likelihood ratio tests based on unconditional logistic regression. To reduce the multiple testing burden and avoid possible failure of asymptotic tests, any tagSNPs for which a genotypic category count was less than 10 for any of the environmental factor strata considered was not included in analyses. Gene-exposure interac- tions were mutually adjusted for all three exposures considered. Further adjustment for body mass index, multivitamin use (yes/ no), total caloric intake, or total dietary fiber (g/day) produced almost identical estimates; therefore we did not keep these variables in the models. Results Demographic characteristics of all cases (N = 721) and controls (N = 736) in our study are summarized in Table 2. As we previously described [25], there were no differences in age, gender, ethnicity, alcohol intake and smoking patterns between Phase I August 2013 \| Volume 8 \| Issue 8 \| e71211 PLOS ONE \| www.plosone.org 3 BER Pathway and Colorectal Adenoma Risk Table 2. Demographics and descriptive characteristics of cases and controls. Table 2. Demographics and descriptive characteristics of cases and controls. Controls Cases Variable n = 736 % n = 721 % p Mean age at interview,y (6SD) 61.46 6.75 61.67 6.88 0.550 Mean Smoking years,y (6SD) 14.6 16.77 18.52 17.86 ,0.001 Mean smoking packyears, (6SD) 16.61 31.51 21.04 31.51 0.008 Mean alcohol intake, y (6SD) 8.03 14.76 9.44 18.54 0.108 Mean dietary folate, mcg/day (6SD) 366.63 210.28 340.08 194.28 0.013 Mean Calories (6SD) 2046.25 951.76 2081 924.43 0.473 Mean dietary fiber, g/day (6SD) 22.84 13.18 21.43 12.67 0.036 Mean saturated fat, g/day (6SD) 23.37 13.38 24.4 13.42 0.147 Mean BMI (6SD) 27.08 4.79 27.57 4.61 0.051 Median Age at interview,y #60 yrs 331 44.97 313 43.41 0.549 .60 yrs 405 55.03 408 56.59 Race/ethnicity non-Hispanic White 386 52.59 372 52.10 0.344 African-American 112 15.26 126 17.65 Hispanic 149 20.30 123 17.23 Asian-Pacific Islander 79 10.76 80 11.20 Other 8 1.09 13 1.82 Sex Male 479 65.17 465 64.49 0.787 Female 256 34.83 256 35.51 Clinic of diagnosis Bellflower 472 64.13 464 64.36 0.929 Sunset 264 35.87 257 35.64 Study Phase Phase I 460 62.50 438 60.75 0.492 Phase II 276 37.50 283 39.25 Number of Adenomas 1 638 88.73 $2 81 11.27 Missing 2 Adenoma site Rectum (,15 cm) 137 19.13 Colon ($15 cm) 579 80.87 Missing 5 Adenoma size Small (,1 cm) 476 66.85 Large ($1 cm) 236 33.15 Missing 9 Smoking Never 301 42.94 253 36.77 ,0.001 Former 326 46.50 312 45.35 Current 74 10.56 123 17.88 Missing 35 33 Smoking years Never 301 43.43 253 37.21 ,0.001 .0–26 yrs 198 28.57 168 24.71 .26 yrs 194 27.99 259 38.09 Missing 43 41 PLOS ONE \| www plosone org 4 August 2013 \| Volume 8 \| Issue 8 \| e71211 August 2013 \| Volume 8 \| Issue 8 \| e71211 4 BER Pathway and Colorectal Adenoma Risk Table 2. Cont. Results Controls Cases Variable n = 736 % n = 721 % p Smoking Pack-years Never 301 43.56 253 37.26 0.001 .0–21 196 28.36 171 25.18 .21 194 28.08 255 37.56 Alcohol intake Never 283 38.45 268 37.33 0.323 #6 g/day 227 30.84 204 27.41 .6 g/day 226 30.71 246 34.26 Missing 0 3 Alcohol intake Never 283 38.45 268 37.33 0.864 #15 g/day 333 45.24 327 45.54 .15 g/day230 g/day 50 6.79 46 6.41 .30 g/day 70 9.51 77 10.72 Missing 0 3 Alcohol intake Never 283 38.45 268 37.33 0.871 #15 g/day 333 45.24 327 45.54 .15 g/day 120 16.30 123 17.13 Missing 0 3 Dietary folate Low (#267 mcg/day) 248 33.70 283 40.60 0.024 Medium (.267–387 mcg/day) 241 32.74 210 30.13 High ($388 mcg/day) 247 33.56 204 29.27 Missing Multivitamin use No 303 41.28 293 42.40 0.668 Yes 431 58.72 398 57.60 Missing 2 30 doi:10.1371/journal.pone.0071211.t002 BER Genes and Adenoma Risk Taking into Account Adenoma Size and Location alcohol intake (never, 1 drink/day, .1 drink/day; interaction pgene = 0.029, interaction ppathway =0.345) (Table 5). Specifically, among carriers of two major (C) alleles, those who drank more than one drink per day had an 84% increased risk of adenoma compared with non-drinkers (OR = 1.84; 95%CI = 1.09–3.11; p = 0.022; p for trend = 0.024), and those who drank more than 6 grams per day had a 77% increased risk of adenoma compared with non-drinkers (OR = 1.77; 95%CI = 1.17–2.68; p = 0.006; p for trend = 0.003). There was no association between alcohol and adenoma risk for subjects with 1 minor (T) allele (Table 5). When restricting analyses to NHW we observed interactions for LIG3 rs1052536 that were of similar magnitude although not statistically significant (data not shown). We did not find evidence of any statistically significant per-allele associations within either the small polyp (,1 cm) or large polyp ($1 cm) group after multiple comparisons adjustment within gene region (PACT). When adenomas location (colon versus rectum), we observed two NEIL2 tagSNPs were associated with increased risk for rectal adenomas: NEIL2 rs7015453 (OR = 1.72; 95%CI = 1.24–2.39; PACT = 0.025; pheterogeneity = 0.003) and rs3757949 (OR = 1.58; 95%CI = 1.18–2.13; PACT = 0.044; pheterogeneity = 0.004) (Table 4). These two tagSNPs were not found to be in LD among NHW (r2 = 0.11), among whom we observed similar findings (data not shown). Complete data for analysis by adenoma location can be found in Table S3. Genetic Variation in BER Genes, Adenoma Risk and Dietary Folate Intake Genetic Variation in BER Genes, Adenoma Risk and Alcohol Genetic Variation in BER Genes, Adenoma Risk and Alcohol We observed that the association between folate and adenoma risk was modified by two LIG3 tagSNPs (rs1052536 interaction pgene =0.006, interaction ppathway =0.081; rs3744358 interaction pgene = 0.032, interaction ppathway =0.451) (Table 5). For each of Statistically significant interactions were observed for LIG3 rs1052536 and amount (0 g/day, #6 g/day, .6 g/day; interac- tion pgene = 0.019, interaction ppathway =0.241) and frequency of PLOS ONE \| www.plosone.org August 2013 \| Volume 8 \| Issue 8 \| e71211 PLOS ONE \| www.plosone.org 5 BER Pathway and Colorectal Adenoma Risk Table 3. Colorectal adenoma SNP associations among the entire population and stratified by race/ethnicity. Gene SNP All combined Non-Hispanic White African-American Hispanic Asian-Pacific Islander Phet e NEIL2 rs11785481 0.131 Ca/Coa 666/692 354/364 121/109 116/140 75/79 OR b 0.70 0.64 0.60 1.29 0.25 95%CI 0.55–0.90 0.48–0.87 0.24–1.53 0.72–2.31 0.05–1.37 pc 0.006 0.004 0.286 0.387 0.111 pACT d 0.139 0.089 1.000 1.000 0.806 FEN1 rs108499 0.024 Ca/Coa 691/663 353/365 122/109 113/140 75/77 OR b 1.06 0.95 0.67 1.09 2.12 95%CI 0.90–1.25 0.76–1.18 0.37–1.21 0.76–1.57 1.30–3.45 pc 0.516 0.635 0.185 0.641 0.002 pACT d 1.000 1.000 0.645 1.000 0.009 APEX1 rs17111750 0.004 Ca/Coa 695/664 354/367 121/110 114/140 75/78 OR b 1.00 0.88 2.19 0.78 1.04 95%CI 0.85–1.18 0.71–1.10 1.36–3.55 0.52–1.15 0.58–1.86 pc 0.981 0.271 0.001 0.208 0.897 pACT d 1.000 0.781 0.013 0.573 1.000 FEN1 rs509360 697/665 0.052 Ca/Coa 697/665 353/367 122/111 116/140 74/79 OR b 0.93 0.95 1.27 1.09 0.49 95%CI 0.78–1.09 0.76–1.19 0.81–2.01 0.71–1.68 0.30–0.79 pc 0.358 0.662 0.302 0.694 0.003 pACT d 0.888 1.000 0.746 1.000 0.011 NTHL1 rs2516781 0.062 Ca/Coa 688/664 353/363 122/108 115/140 74/77 OR b 0.91 1.01 0.83 1.06 0.45 95%CI 0.77–1.08 0.80–1.27 0.51–1.34 0.74–1.52 0.25–0.80 pc 0.271 0.960 0.445 0.747 0.006 pACT d 0.840 1.000 0.960 1.000 0.033 aExcludes 21 individuals who characterized their race/ethnic group as "other"; b dCrude p-value corrected for multiple comparisons using PACT; eRace/ethnicity specific per-allele ORs and 95% confidence intervals computed using logistic regression assuming a log-additive model and adjusting for the matching factors age, exam date, sex, clinic, study phase; e p-value for heterogeneity by race. doi 10 1371/jo rnal pone 0071211 t003 eRace/ethnicity specific per-allele ORs and 95% confidence intervals computed using logistic regression assuming a log-additive model and adjusting for the matching factors age, exam date, sex, clinic, study phase; e p-value for heterogeneity by race. doi:10.1371/journal.pone.0071211.t003 Table 4. Significant BER per-allele associations by polyp sub-site. Genetic Variation in BER Genes, Adenoma Risk and Alcohol doi:10.1371/journal.pone.0071211.t005 y Table 5. Cont. Table 5. Cont. (p for trend ,0.001). Analysis among non-Hispanic Whites was not performed due to sparse data. the two LIG3 tagSNPs, among individuals with one copy of the minor allele, those with the highest level of dietary folate intake had a 31% and 37% decreased adenoma risk compared to those with the lowest level of dietary folate intake for LIG3 rs1052536 (OR = 0.61; 95%CI = 0.51–0.93; p = 0.015; p for trend = 0.021) and LIG3 rs3744358 (OR = 0.63; 95%CI = 0.45–0.90; p = 0.010; p for trend =0.003), respectively. Among individuals with two copies of the minor allele, those with the highest level of dietary folate intake had a 72% and 73% decreased adenoma risk compared to those with the lowest level of dietary folate intake for LIG3 rs1052536 (OR = 0.37; 95%CI = 0.20–0.65; p = 0.0007) and LIG3 rs3744358 (OR = 0.38; 95%CI = 0.19–0.75; p = 0.006), respec- tively. Among individuals with 2 copies of the major alleles there was no statistically significant trend across increasing levels of dietary folate intake. When restricting analyses to NHW, similar statistically significant trends were observed for rs1052536 and rs3744358 (data not shown). There is no evidence of LD between LIG3 tagSNPs rs3744358 and rs1052536 among NHW. Second, the OGG1 rs159153 SNP modified the association between smoking pack-years and adenoma risk (interaction pgene =0.040, interaction ppathway =0.517). While among individuals with two copies of the major (A) allele there was no association between increasing pack-years and adenoma risk (p for trend = 0.610), among carriers of one copy of the minor (C) allele, having smoked over 21 pack-years was associated with a 75% increased adenoma risk when compared to never smokers (OR = 1.75; 95%CI = 1.26–2.44; p = 0.001; p for trend ,0.001). Among individuals carrying a second minor (C) allele, smoking over 21 pack-years was significantly associated with an almost 3- fold increased risk of adenoma (p for trend ,0.001) when compared to never smokers. Significant trends of increasing adenoma risk among carriers of 1 and 2 minor alleles were observed with increasing smoking years, but there was no statistically significant evidence of interaction between OGG1 rs159153 and smoking years and adenoma risk. y Finally, the FEN1 rs108499 SNP also modified the association between smoking pack-years and adenoma risk (interaction pgene =0.039, interaction ppathway =0.507). Genetic Variation in BER Genes, Adenoma Risk and Alcohol Rectal Polyp Colon Polyp Rectal/Colon Gene SNP CA/COa ORb 95%CI Pc PACT d P pathway e CA/COa ORb 95%CI Pc PACT d P pathway e phet f NEIL2 rs3757949 123/669 1.58 1.18–2.13 0.002 0.044 0.610 528/669 1.02 0.85–1.23 0.795 1.000 1.000 0.004 NEIL2 rs7015453 123/670 1.72 1.24–2.39 0.001 0.025 0.346 525/670 1.03 0.84–1.27 0.738 1.000 1.000 0.003 aExcludes 21 individuals who characterized their race/ethnic group as "other."; bPer-allele ORs and 95%confidence intervals computed using multinomial logistic regression assuming a log-additive model and adjusting for age, exam date, sex, clinic, study phase, and race among all study participants; cCrude p-value; dCrude p-value corrected for multiple comparisons using PACT; ePathway wide (ppathway) p-value based on Bonferroni correction of PACT for the number of BER gene regions investigated (N = 14); fp-value for heterogeneity by polyp subsite. doi:10.1371/journal.pone.0071211.t004 Table 4. Significant BER per-allele associations by polyp sub-site. August 2013 \| Volume 8 \| Issue 8 \| e71211 August 2013 \| Volume 8 \| Issue 8 \| e71211 PLOS ONE \| www.plosone.org 6 BER Pathway and Colorectal Adenoma Risk Table 5. Cont. Exposure variable CA/CO CA/CO CA/CO OR a,b,c 95%CI P OR a,b,c 95%CI P OR a,b,c 95%CI P FEN1 rs108499 Smoking Pack-yrs CC CT TT C/C C/T T/T Never 95/118 87/108 48/44 1ref 1ref 1ref .0–21 64/70 56/86 32/27 1.02 0.67–1.54 0.926 0.96 0.71–1.29 0.771 0.90 0.52–1.56 0.7 .21 124/79 82/78 21/22 1.99 1.36–2.91 ,0.001 1.25 0.92–1.71 0.156 0.79 0.44–1.41 0.424 p trend ,0.001 0.102 0.446 interaction pd =0.013; interaction pgene e = 0.039; interaction ppathway f = 0.507 aOdds ratios (ORs) are from models with genotype coded as log-additive (treated as continuous) and adjusted for age, sex, clinic, exam date, study phase, and race among all study participants. Excludes 21 individuals who characterized their race/ethnic group as "other"; bORs for smoking additionally adjusted for alcohol intake (g/d) and dietary folate intake (mcg/day); ORs for alcohol additionally adjusted for smoking pack-years and dietary folate intake (mcg/d); ORs for dietary folate intake, additionally adjusted for alcohol intake (g/d) and smoking pack-years; cORs derived from a common baseline model that included the SNP, smoking, alcohol, dietary folate exposure and interaction terms between genotype and smoking, alcohol, dietary folate exposure levels; dCrude interaction p-value; eWithin gene region, Bonferroni adjusted interaction p-value, based on the number of SNPs within the respective gene region; fPathway wide, Bonferroni adjusted interaction p-value, based on 14 investigated BER gene regions. Genetic Variation in BER Genes, Adenoma Risk and Smoking Genetic Variation in BER Genes, Adenoma Risk and Smoking No statistically significant interactions were observed when we considered smoking status (never/quit/current) or smoking duration, after applying within gene Bonferroni corrections. However, we observed that SNPs in three genes modified the association between smoking pack-years and adenoma risk, with statistically significant interaction tests that survived within gene Bonferroni correction. First, we observed smoking pack-years was modified by MUTYH rs10890324 (interaction pgene =0.007, interaction ppathway =0.091) (Table 5). Whereas among individuals with two copies of the major (A) allele there was no association between increasing pack-years and adenoma risk (p for trend = 0.871), among carriers of one copy of the minor (G) allele, having smoked over 21 pack-years was associated with a 76% increased adenoma risk when compared to never smokers (OR = 1.76; 95%CI = 1.29–2.42; p,0.001; p for trend ,0.001). Among carriers of two minor (G) alleles, smoking more than 21 pack-years was associated with a 3-fold increased risk of adenomas Genetic Variation in BER Genes, Adenoma Risk and Alcohol Among individuals with two copies of the major (C) allele smoking more than 21 pack- years was associated with a 2-fold increased risk of adenomas compared to never smokers (p for trend ,0.001) but there was no association among individuals with either one copy of the minor (T) allele or two copies of the minor (T) allele (Table 5). While a similar significant trend of increasing adenoma risk was observed with increasing smoking years, there was no statistically significant evidence of interaction. Analyses among NHW only were not performed due to sparse data. BER Pathway and Colorectal Adenoma Risk Finally, we found evidence that the LIG3 rs1052536 SNP modified the association between alcohol intake and adenoma risk. In addition, LIG3 SNPs rs1052536 and rs3744358 modified the association between dietary folate intake and adenoma risk. LIG3, a ligase involved in maintaining genomic integrity, encodes proteins present in the mitochondria and nucleus. We found evidence that the MUTYH rs10890324 SNP, which flanks the 39-end of MUTYH, modified the association between smoking and adenoma risk. The MUTYH gene encodes a DNA glycosylase, and germline mutations in highly conserved residues of the MUTYH gene predispose individuals to MUTYH-associated polyposis coli [56] as well as sporadic CRC [57,58]. We also found that the OGG1 rs159153 SNP, located 59-upstream of OGG1, modified the association between smoking and adenoma risk. The 8- oxoguanine glycosylase 1 (OGG1) enzyme can excise the highly mutagenic 8-oxoguanine lesions induced by ROS and normal cellular metabolism [59]. The more commonly investigated OGG1 Ser326Cys SNP (rs1052133) is not in LD with rs159153 among NHW (r2=0.08). Previous studies have investigated BER gene polymorphisms and adenoma risk [25,26,34,35,36,37,38]. With one exception [38], they have been limited to a handful of candidate SNPs within XRCC1, PARP1, OGG1, and APEX genes. Even fewer considered the modifier role of alcohol, smoking or dietary folate intake [26,37,38]. Therefore, to our knowledge, this is the first comprehensive examination of the BER pathway and colorectal adenoma risk taking into account relevant environmental risk factors. Finally, we found evidence that the LIG3 rs1052536 SNP modified the association between alcohol intake and adenoma risk. In addition, LIG3 SNPs rs1052536 and rs3744358 modified the association between dietary folate intake and adenoma risk. LIG3, a ligase involved in maintaining genomic integrity, encodes proteins present in the mitochondria and nucleus. We report a two-fold increased adenoma risk associated with SNP rs17111750 located 59-upstream of APEX1, only among African-Americans. The human APEX1 protein is an apurinic/ apyrimidinic endonuclease that repairs DNA damage caused by oxidative and alkylating agents [39]. A previous study has reported a positive association between this SNP and colorectal adenoma, and another one reported lack of association with prostate cancer risk [38,40]. Among African-Americans APEX1 rs17111750 is not in LD (r2,0.05) with two other APEX1 SNPs, rs1048945 and rs1130409, previously reported by us and others to be associated with CRC and adenoma risk [37,41,42,43]. BER Pathway and Colorectal Adenoma Risk Our study had several strengths, including the relatively large sample size and the use of a comprehensive tagSNP approach to thoroughly investigate genetic variation in 14 BER genes. Among the weaknesses of our study is the fact that results are only applicable to the sigmoid colon and rectum, and the fact that cases had colonoscopy performed but not controls; therefore, some controls might have had more proximal polyps out of reach of sigmoidscope [60]. Even though we conducted a large number of tests as part of our analyses, we believe our approach for multiple comparisons adjustment in the SNP main effect analyses and the gene environment analyses is a conservative method of reducing the number of false positive results. [ ] We observed that the minor alleles of the FEN1 SNPs rs509360 and rs108499 were associated with a two-fold increased and decreased risk of adenoma, respectively, among Asian-Pacific Islanders. Moreover, among all subjects combined, rs108499 was found to modify the effect of smoking on adenoma risk. Both rs509360 and rs108499 are located 59-upstream of FEN1, occurring within intronic regions of C11orf9. A previous study among predominantly NHW found no associations between these FEN1 SNPs and colorectal adenoma [38]. The FEN1 endonucle- ase is involved in BER and DNA replication and has been reported to play important roles in genomic stability [44], chronic inflammation, autoimmunity and cancers [45,46]. In two studies conducted among Chinese populations, polymorphisms in the FEN1 promoter and 39-UTR were associated with reduced FEN1 expression, increased DNA damage and increased risks for lung and CRC [47,48]. In conclusion, our findings suggest that genetic variation in non- coding BER gene regions can modify the risk of adenoma, particularly in combination with key environmental exposures. These findings highlight a relevant role for oxidative damage induced by these environmental exposures in colorectal adenoma development. Table S1 Genes/SNPs included in study and minor allele frequencies. (XLSX) Table S1 Genes/SNPs included in study and minor allele frequencies. (XLSX) Table S1 Genes/SNPs included in study and minor allele frequencies. (XLSX) Table S2 Single SNP analysis for entire study popula- tion and by race/ethnic group. (XLSX) The NTHL1 rs2516781 SNP was associated with a two-fold decreased risk of adenoma only among Asian-Pacific Islanders. The NTHL1 protein has DNA N-glycosylase activity as well as apurinic and/or apyrimidinic endonuclease activity [49,50,51]. The rs2516781 SNP is 39-downstream of the NTHL1 gene, an intronic SNP within the solute carrier family 9 (sodium/hydrogen exchanger), member 3 regulator 2 (SLC9A3R2) gene. SLC9A3R2 is involved in regulation of SLC9A3, the sodium/hydrogen ex- changer involved in intestinal sodium absorption [52]. This SNP has not been previously assessed in studies of colorectal adenoma or CRC. Table S3 Per allele associations by polyp subsite. (XLSX) Acknowledgments We would like to thank all the participants in this study. We would also like to thank Terry Kolb and Jessie Lin for their assistance with data collection, cleaning and management and Anh Diep for her assistance with biospecimen management. Two NEIL2 SNPs, rs11785481 and rs3757949, were associated with risk for rectal adenomas. Among NHW these two SNPs are not in LD (r2,0.1). The NEIL2 protein has DNA glycosylase activity and apurinic/apyrimidinic endonuclease activity [39]. The BER Pathway and Colorectal Adenoma Risk BER Pathway and Colorectal Adenoma Risk among Asian-Pacific Islanders, and the APEX1 gene among African-Americans (one tagSNP). Significant associations were also observed for two unlinked tagSNPs in the NEIL2 gene and rectal adenoma risk. None of the six tagSNPs were found to modify the effects of dietary folate, or alcohol on adenoma risk. However, one of these six tagSNPs, FEN1 rs108499, was found to modify the effects of smoking on adenoma risk. Moreover, we observed evidence that SNPs in other BER genes modified the effect of smoking (MUTYH, OGG1), alcohol (LIG3), and dietary folate (LIG3) on colorectal adenoma risk. Overall, our findings support the hypothesis that oxidative damage induced by these exposures may play an important role in colorectal adenoma development. among Asian-Pacific Islanders, and the APEX1 gene among African-Americans (one tagSNP). Significant associations were also observed for two unlinked tagSNPs in the NEIL2 gene and rectal adenoma risk. None of the six tagSNPs were found to modify the effects of dietary folate, or alcohol on adenoma risk. However, one of these six tagSNPs, FEN1 rs108499, was found to modify the effects of smoking on adenoma risk. Moreover, we observed evidence that SNPs in other BER genes modified the effect of smoking (MUTYH, OGG1), alcohol (LIG3), and dietary folate (LIG3) on colorectal adenoma risk. Overall, our findings support the hypothesis that oxidative damage induced by these exposures may play an important role in colorectal adenoma development. rs3757949 SNP, is an intronic SNP located within GATA4, a gene that codes for a transcription factor relevant for gene expression in gastrointestinal epithelium [53,54]. Promoter hyper-methylation and the subsequent transcriptional silencing of GATA4 are commonly seen in CRC cell lines and primary CRCs [55]. y p y [ ] We found evidence that the MUTYH rs10890324 SNP, which flanks the 39-end of MUTYH, modified the association between smoking and adenoma risk. The MUTYH gene encodes a DNA glycosylase, and germline mutations in highly conserved residues of the MUTYH gene predispose individuals to MUTYH-associated polyposis coli [56] as well as sporadic CRC [57,58]. We also found that the OGG1 rs159153 SNP, located 59-upstream of OGG1, modified the association between smoking and adenoma risk. The 8- oxoguanine glycosylase 1 (OGG1) enzyme can excise the highly mutagenic 8-oxoguanine lesions induced by ROS and normal cellular metabolism [59]. The more commonly investigated OGG1 Ser326Cys SNP (rs1052133) is not in LD with rs159153 among NHW (r2=0.08). Discussion We investigated potential associations between 182 tagSNPs from 14 BER gene regions and their role in modifying the effects of smoking, dietary folate intake and alcohol consumption on colorectal adenoma risk. We observed statistically significant associations between colorectal adenoma risk and polymorphisms in the FEN1 gene (two tagSNPs) and NTHL1 gene (one tagSNP) PLOS ONE \| www.plosone.org August 2013 \| Volume 8 \| Issue 8 \| e71211 August 2013 \| Volume 8 \| Issue 8 \| e71211 8 References 1. ACS (2011) Colorectal Cancer Facts & Figures 2011–2013. Atlanta: American Cancer Society. alcohol on colorectal adenoma risk. Cancer Epidemiol Biomarkers Prev 15: 2384–2390. alcohol on colorectal adenoma risk. Cancer Epidemiol Biomarkers Prev 15: 2384–2390. 27. Lin HJ, Probst-Hensch NM, Ingles SA, Han CY, Lin BK, et al. (1995) Glutathione transferase (GSTM1) null genotype, smoking, and prevalence of colorectal adenomas. Cancer Res 55: 1224–1226. 2. Stewart SL, Wike JM, Kato I, Lewis DR, Michaud F (2006) A population-based study of colorectal cancer histology in the United States, 1998–2001. Cancer 107: 1128–1141. colorectal adenomas. Cancer Res 55: 1224–1226. 3. Goroll AH, Mulley AG (2009) Primary care medicine : office evaluation and management of the adult patient. Philadelphia: Wolters Kluwer/Lippincott Williams & Wilkins. xxix, 1613 p., 1616 p. of plates p. 28. Longnecker MP, Chen MJ, Probst-Hensch NM, Harper JM, Lee ER, et al. (1996) Alcohol and smoking in relation to the prevalence of adenomatous colorectal polyps detected at sigmoidoscopy. Epidemiology 7: 275–280. p p p p 4. Atkin WS, Saunders BP (2002) Surveillance guidelines after removal of colorectal adenomatous polyps. Gut 51 Suppl 5: V6–9. 29. Haile RW, Witte JS, Longnecker MP, Probst-Hensch N, Chen MJ, et al. (1997) A sigmoidoscopy-based case-control study of polyps: macronutrients, fiber and meat consumption. Int J Cancer 73: 497–502. 5. Winawer SJ, Zauber AG, Ho MN, O’Brien MJ, Gottlieb LS, et al. (1993) Prevention of colorectal cancer by colonoscopic polypectomy. The National Polyp Study Workgroup. The New England journal of medicine 329: 1977– 1981. 30. Barrett JC, Fry B, Maller J, Daly MJ (2005) Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21: 263–265. 31. Levine AJ, Lee W, Figueiredo JC, Conti DV, Vandenberg DJ, et al. (2011) Variation in folate pathway genes and distal colorectal adenoma risk: a sigmoidoscopy-based case-control study. Cancer Causes Control 22: 541–552. 6. Winawer SJ (2001) A quarter century of colorectal cancer screening: progress and prospects. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 19: 6S–12S. g py y 32. Conneely KN, Boehnke M (2007) So many correlated tests, so little time! Rapid adjustment of P values for multiple correlated tests. Am J Hum Genet 81: 1158– 1168. 7. Terry MB, Neugut AI, Bostick RM, Sandler RS, Haile RW, et al. (2002) Risk factors for advanced colorectal adenomas: a pooled analysis. References Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 11: 622–629. 33. Storey JD, Tibshirani R (2003) Statistical significance for genomewide studies. Proceedings of the National Academy of Sciences of the United States of America 100: 9440–9445. gy 8. Botteri E, Iodice S, Raimondi S, Maisonneuve P, Lowenfels AB (2008) Cigarette smoking and adenomatous polyps: a meta-analysis. Gastroenterology 134: 388– 395. 34. Hansen R, Saebo M, Skjelbred CF, Nexo BA, Hagen PC, et al. (2005) GPX Pro198Leu and OGG1 Ser326Cys polymorphisms and risk of development of colorectal adenomas and colorectal cancer. Cancer letters 229: 85–91. 9. Duthie SJ, Narayanan S, Sharp L, Little J, Basten G, et al. (2004) Folate, DNA stability and colo-rectal neoplasia. The Proceedings of the Nutrition Society 63: 571–578. 35. Skjelbred CF, Saebo M, Wallin H, Nexo BA, Hagen PC, et al. (2006) Polymorphisms of the XRCC1, XRCC3 and XPD genes and risk of colorectal adenoma and carcinoma, in a Norwegian cohort: a case control study. BMC cancer 6: 67. 10. Mason JB (2009) Folate, cancer risk, and the Greek god, Proteus: a tale of two chameleons. Nutrition reviews 67: 206–212. 36. Gsur A, Bernhart K, Baierl A, Feik E, Fuhrlinger G, et al. (2011) No association of XRCC1 polymorphisms Arg194Trp and Arg399Gln with colorectal cancer risk. Cancer epidemiology 35: e38–41. 11. Pryor WA (1997) Cigarette smoke radicals and the role of free radicals in chemical carcinogenicity. Environmental health perspectives 105 Suppl 4: 875– 882. 37. Berndt SI, Huang WY, Fallin MD, Helzlsouer KJ, Platz EA, et al. (2007) Genetic variation in base excision repair genes and the prevalence of advanced colorectal adenoma. Cancer research 67: 1395–1404. 12. Friedberg EC, ebrary Inc. (2006) DNA repair and mutagenesis. 2nd ed. Washington, D.C.: ASM Press,. pp. xxix, 1118 p. ill. (some col.) 1129 cm. 13. Mannino DM, Mulinare J, Ford ES, Schwartz J (2003) Tobacco smoke exposure and decreased serum and red blood cell folate levels: data from the Third National Health and Nutrition Examination Survey. Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco 5: 357–362. 38. Gao Y, Hayes RB, Huang WY, Caporaso NE, Burdette L, et al. (2011) DNA repair gene polymorphisms and tobacco smoking in the risk for colorectal adenomas. Carcinogenesis 32: 882–887. 39. Author Contributions Conceived and designed the experiments: AJL RWH DJV MCS. Performed the experiments: DJV. Analyzed the data: RC MCS JPL August 2013 \| Volume 8 \| Issue 8 \| e71211 PLOS ONE \| www.plosone.org 9 BER Pathway and Colorectal Adenoma Risk ADJ. Contributed reagents/materials/analysis tools: RWH MCS. Wrote the paper: RC MCS JPL AJL RWH ADJ DJV. References Simonelli V, Mazzei F, D’Errico M, Dogliotti E (2012) Gene susceptibility to oxidative damage: From single nucleotide polymorphisms to function. Mutation research 731: 1–13. 14. Blount BC, Mack MM, Wehr CM, MacGregor JT, Hiatt RA, et al. (1997) Folate deficiency causes uracil misincorporation into human DNA and chromosome breakage: implications for cancer and neuronal damage. Proceedings of the National Academy of Sciences of the United States of America 94: 3290–3295. 40. Barry KH, Koutros S, Berndt SI, Andreotti G, Hoppin JA, et al. (2011) Genetic variation in base excision repair pathway genes, pesticide exposure, and prostate cancer risk. Environmental health perspectives 119: 1726–1732. 41. Brevik A, Joshi AD, Corral R, Onland-Moret NC, Siegmund KD, et al. (2010) Polymorphisms in base excision repair genes as colorectal cancer risk factors and modifiers of the effect of diets high in red meat. Cancer Epidemiol Biomarkers Prev 19: 3167–3173. 15. Secretan B, Straif K, Baan R, Grosse Y, El Ghissassi F, et al. (2009) A review of human carcinogens–Part E: tobacco, areca nut, alcohol, coal smoke, and salted fish. The lancet oncology 10: 1033–1034. 16. American Institute for Cancer Research, World Cancer Research Fund (2007) Food, nutrition, physical activity and the prevention of cancer : a global perspective : a project of World Cancer Research Fund International. Washington, D.C.: American Institute for Cancer Research. xxv, 517 p. p. 42. Kasahara M, Osawa K, Yoshida K, Miyaishi A, Osawa Y, et al. (2008) Association of MUTYH Gln324His and APEX1 Asp148Glu with colorectal cancer and smoking in a Japanese population. Journal of experimental & clinical cancer research : CR 27: 49. 17. Baron JA, Sandler RS, Haile RW, Mandel JS, Mott LA, et al. (1998) Folate intake, alcohol consumption, cigarette smoking, and risk of colorectal adenomas. Journal of the National Cancer Institute 90: 57–62. 43. Pardini B, Naccarati A, Novotny J, Smerhovsky Z, Vodickova L, et al. (2008) DNA repair genetic polymorphisms and risk of colorectal cancer in the Czech Republic. Mutation research 638: 146–153. 18. Seitz HK, Simanowski UA, Garzon FT, Rideout JM, Peters TJ, et al. (1990) Possible role of acetaldehyde in ethanol-related rectal cocarcinogenesis in the rat. Gastroenterology 98: 406–413. 44. Chapados BR, Hosfield DJ, Han S, Qiu J, Yelent B, et al. (2004) Structural basis for FEN-1 substrate specificity and PCNA-mediated activation in DNA replication and repair. Cell 116: 39–50. gy 19. Poschl G, Seitz HK (2004) Alcohol and cancer. BER Pathway and Colorectal Adenoma Risk References Alcohol and alcoholism 39: 155– 165. 45. Zheng L, Dai H, Zhou M, Li M, Singh P, et al. (2007) Fen1 mutations result in autoimmunity, chronic inflammation and cancers. Nature medicine 13: 812– 819. 20. Kune GA, Vitetta L (1992) Alcohol consumption and the etiology of colorectal cancer: a review of the scientific evidence from 1957 to 1991. Nutrition and cancer 18: 97–111. 46. Kucherlapati M, Yang K, Kuraguchi M, Zhao J, Lia M, et al. (2002) Haploinsufficiency of Flap endonuclease (Fen1) leads to rapid tumor progression. Proceedings of the National Academy of Sciences of the United States of America 99: 9924–9929. 21. Brooks PJ, Theruvathu JA (2005) DNA adducts from acetaldehyde: implications for alcohol-related carcinogenesis. Alcohol 35: 187–193. 22. Seitz HK, Maurer B, Stickel F (2005) Alcohol consumption and cancer of the gastrointestinal tract. Digestive diseases 23: 297–303. 47. Yang M, Guo H, Wu C, He Y, Yu D, et al. (2009) Functional FEN1 polymorphisms are associated with DNA damage levels and lung cancer risk. Human mutation 30: 1320–1328. 23. Das SK, Vasudevan DM (2007) Alcohol-induced oxidative stress. Life sciences 81: 177–187. 48. Liu L, Zhou C, Zhou L, Peng L, Li D, et al. (2012) Functional FEN1 genetic variants contribute to risk of hepatocellular carcinoma, esophageal cancer, gastric cancer and colorectal cancer. Carcinogenesis 33: 119–123. 24. Robertson AB, Klungland A, Rognes T, Leiros I (2009) DNA repair in mammalian cells: Base excision repair: the long and short of it. Cellular and molecular life sciences : CMLS 66: 981–993. 25. Stern MC, Siegmund KD, Corral R, Haile RW (2005) XRCC1 and XRCC3 polymorphisms and their role as effect modifiers of unsaturated fatty acids and antioxidant intake on colorectal adenomas risk. Cancer Epidemiol Biomarkers Prev 14: 609–615. 49. Luna L, Bjoras M, Hoff E, Rognes T, Seeberg E (2000) Cell-cycle regulation, intracellular sorting and induced overexpression of the human NTH1 DNA glycosylase involved in removal of formamidopyrimidine residues from DNA. Mutation research 460: 95–104. 50. Aspinwall R, Rothwell DG, Roldan-Arjona T, Anselmino C, Ward CJ, et al. (1997) Cloning and characterization of a functional human homolog of 26. 51. Ikeda S, Biswas T, Roy R, Izumi T, Boldogh I, et al. (1998) Purification and characterization of human NTH1, a homolog of Escherichia coli endonuclease III. Direct identification of Lys-212 as the active nucleophilic residue. The Journal of biological chemistry 273: 21585–21593. 54. Molkentin JD (2000) The zinc finger-containing transcription factors GATA-4, - 5, and -6. Ubiquitously expressed regulators of tissue-specific gene expression. The Journal of biological chemistry 275: 38949–38952. 52. Yun CH, Oh S, Zizak M, Steplock D, Tsao S, et al. (1997) cAMP-mediated inhibition of the epithelial brush border Na+/H+ exchanger, NHE3, requires an associated regulatory protein. Proceedings of the National Academy of Sciences of the United States of America 94: 3010–3015. 53. Temsah R, Nemer M (2005) GATA factors and transcriptional regulation of cardiac natriuretic peptide genes. Regulatory peptides 128: 177–185. References Stern MC, Siegmund KD, Conti DV, Corral R, Haile RW (2006) XRCC1, XRCC3, and XPD polymorphisms as modifiers of the effect of smoking and PLOS ONE \| www.plosone.org August 2013 \| Volume 8 \| Issue 8 \| e71211 August 2013 \| Volume 8 \| Issue 8 \| e71211 August 2013 \| Volume 8 \| Issue 8 \| e71211 10 Escherichia coli endonuclease III. Proceedings of the National Academy of Sciences of the United States of America 94: 109–114. j g 58. Cleary SP, Cotterchio M, Jenkins MA, Kim H, Bristow R, et al. (2009) Germline MutY human homologue mutations and colorectal cancer: a multisite case- control study. Gastroenterology 136: 1251–1260. BER Pathway and Colorectal Adenoma Risk BER Pathway and Colorectal Adenoma Risk BER Pathway and Colorectal Adenoma Risk 55. Zheng R, Blobel GA (2010) GATA Transcription Factors and Cancer. Genes & cancer 1: 1178–1188. 56. Cheadle JP, Sampson JR (2007) MUTYH-associated polyposis–from defect in base excision repair to clinical genetic testing. DNA repair 6: 274–279. 51. Ikeda S, Biswas T, Roy R, Izumi T, Boldogh I, et al. (1998) Purification and characterization of human NTH1, a homolog of Escherichia coli endonuclease III. Direct identification of Lys-212 as the active nucleophilic residue. The Journal of biological chemistry 273: 21585–21593. 57. Farrington SM, Tenesa A, Barnetson R, Wiltshire A, Prendergast J, et al. (2005) Germline susceptibility to colorectal cancer due to base-excision repair gene defects. American journal of human genetics 77: 112–119. 52. Yun CH, Oh S, Zizak M, Steplock D, Tsao S, et al. (1997) cAMP-mediated inhibition of the epithelial brush border Na+/H+ exchanger, NHE3, requires an associated regulatory protein. Proceedings of the National Academy of Sciences of the United States of America 94: 3010–3015. 58. Cleary SP, Cotterchio M, Jenkins MA, Kim H, Bristow R, et al. (2009) Germline MutY human homologue mutations and colorectal cancer: a multisite case- control study. Gastroenterology 136: 1251–1260. 59. Parsons JL, Zharkov DO, Dianov GL (2005) NEIL1 excises 39 end proximal oxidative DNA lesions resistant to cleavage by NTH1 and OGG1. Nucleic acids research 33: 4849–4856. 53. Temsah R, Nemer M (2005) GATA factors and transcriptional regulation of cardiac natriuretic peptide genes. Regulatory peptides 128: 177–185. 54. Molkentin JD (2000) The zinc finger-containing transcription factors GATA-4, - 5, and -6. Ubiquitously expressed regulators of tissue-specific gene expression. The Journal of biological chemistry 275: 38949–38952. 60. Foutch PG, Mai H, Pardy K, DiSario JA, Manne RK, et al. (1991) Flexible sigmoidoscopy may be ineffective for secondary prevention of colorectal cancer in asymptomatic, average-risk men. Digestive diseases and sciences 36: 924–928. August 2013 \| Volume 8 \| Issue 8 \| e71211 PLOS ONE \| www.plosone.org PLOS ONE \| www.plosone.org 11
https://openalex.org/W4396213976	https://link.springer.com/content/pdf/10.1007/s00217-024-04553-5.pdf	English	null	Analysis of the scientific knowledge structure on automation in the wine industry: a bibliometric and systematic review	European food research & technology	2,024	cc-by	10,252	Abstract The objective of this research is to analyze the knowledge structure of the academic literature indexed in the Core Collec‑ tion of the Web of Science on automation in the wine industry, from the first registered article in 1996 to 2022, in order to identify the latest trends in the study of this subject. A bibliometric and systematic analysis of the literature was carried out. First, for the quantitative analysis of the scientific production, the bibliometric study was conducted, using the WoS database for data collection and the VosViewer and Bibliometrix applications to create the network maps. Second, once the literature had been examined quantitatively, content analysis was undertaken using the PRISMA methodology. The results show, among other aspects, the uneven distribution of the examined scientific production from 1996 to 2022, that computer vision, data aggregation, life cycle assessment, precision viticulture, extreme learning machine and collaborative platforms are the major current keywords and the predominance of Spain and Italy in terms of scientific production in the field. There are various justifications which support the originality of this study. First, it contributes to the understanding of academic literature and the identification of the most recent trends in the study of automation in the wine industry. Second, to the best of our knowledge, no prior bibliometric studies have considered this topic. Third, this research evaluates the literature from the first record to the year 2022, thereby providing a comprehensive analysis of the scientific production. Keywords Knowledge structure · Automation · Wine industry · Bibliometric review · Systematic rev Analysis of the scientific knowledge structure on automation in the wine industry: a bibliometric and systematic review Javier Martínez‑Falcó1 · Eduardo Sánchez‑García1 · Bartolome Marco‑Lajara1 · Luis A. Millán‑Tudela1 Received: 6 January 2024 / Revised: 20 March 2024 / Accepted: 6 April 2024 / Published online: 29 April 2024 © The Author(s) 2024 1 Management Department, University of Alicante, Alicante, Spain * Javier Martínez‑Falcó javier.falco@ua.es European Food Research and Technology (2024) 250:2273–2289 https://doi.org/10.1007/s00217-024-04553-5 European Food Research and Technology (2024) 250:2273–2289 https://doi.org/10.1007/s00217-024-04553-5 REVIEW ARTICLE * Javier Martínez‑Falcó javier.falco@ua.es 1 Management Department, University of Alicante, Alicante, Spain TS = ((automation) AND (wine ∗)) The search equation was divided into two categories: automation and the wine industry. The AND operator was utilized to limit the results to papers that provided insights from both groups, while the wildcard (*) was used to include different word forms in the accessible results. It is important to note that only the AND operator was used because we wanted to prioritize the optician of results linked only and exclusively to the pre-established research objective. Like‑ wise, the wildcard symbol was not applied to the automation category to avoid obtaining results that were not directly and explicitly linked to automation. Boolean operators are a major element of bibliometric reviews as they enable users to formulate intricate and specific queries to gain more rel‑ evant information. They can also be employed to narrow or extend the search to particular topics, documents of certain years or types, allowing researchers to get the most mean‑ ingful results while reducing searching time. These param‑ eters were applied to the title, abstract, and keywords of the papers, and the documents added by WOS until 2022. Thus, the study aims to answer the following three Research Questions (RQ): (RQ1) What are the current trends and future prospects for automation in the wine industry? (RQ2) How is the scientific knowledge around this topic structured? (RQ3) What are the implications of these trends for academics, practitioners and policy makers in the wine industry? By addressing these RQs, the investigation aims to improve the understanding of automation in the wine indus‑ try, with the study being valuable for both wine academics and wine industry practitioners. In order to achieve the objective set, the introductory sec‑ tion is followed by Materials and methods, which details the methodology employed, Results and discussion presents the findings of the study, and finally, Conclusions and future research agenda shows the main conclusions derived from the study, the research agenda, as well as the limitations and future research lines. On October 5, 2023, the application of a search algorithm resulted in the acceptance of 39 articles. In order to analyze the scientific output, the “Preferred Reporting Items for Sys‑ tematic Reviews and Meta-Analyses” (PRISMA statement) was utilized due to its potential to enhance the reliability and reproducibility of reviews, its comprehensive nature, and its widespread application in bibliometric studies [43]. Introduction timeframes [4] and ensuring faster and more accurate execu‑ tion [58]. Automation in the wine industry has led to a revolution in reducing costs and improving quality [18], allowing produc‑ ers to focus on innovation and flavor improvement [68], as well as enhancing detailed production record keeping [1], which is essential for early detection of problems and ensur‑ ing consumer satisfaction. Nonetheless, the adoption of automation in the wine sec‑ tor is not without challenges; first, the wine industry is char‑ acterized by its deep roots in traditions and processes that have remained unchanged for years, making the automation of these a task of considerable complexity [61]; second, the acquisition of automated equipment represents a significant investment, forcing wineries to carefully evaluate the prof‑ itability of such investment and the compatibility of new technology with existing processes [54],third, a technical skills gap may exist in the workforce, as winery employ‑ ees lack experience with advanced technologies, which can complicate the effective implementation of automated solu‑ tions [68] and, fourth, although automation promises quality improvements, it is imperative that automated systems be meticulously designed and evaluated to ensure compliance with established quality and safety standards [21]. Automation can be integrated throughout the entire value chain of the wine industry, starting with the implementation of advanced machinery in grape harvesting, which facilitates winemakers to accelerate this essential process [7], continu‑ ing with grape pressing, optimizing the extraction of juice from the skins in an efficient manner [65] and ending with the bottling, labeling and transportation phase, allowing producers to increase their production capacity in reduced The main objective of this study is to examine the struc‑ ture of knowledge associated with automation in the wine industry since, to the best of the authors' knowledge, there (012 3456789) 3456789) European Food Research and Technology (2024) 250:2273–2289 2274 are no previous literature reviews that have addressed this topic, making it possible to discover for the first time the key characteristics of this scientific production, such as the lead‑ ing institutions, prolific authors and countries where produc‑ tion is concentrated, as well as to examine the main topics that currently occupy researchers in this field. TS = ((automation) AND (wine ∗)) The PRISMA methodology is beneficial for augmenting the transparency and communication between authors and readers, thus verifying that the results are dependable and reproducible [41]. This is recommended for the purpose of improving the quality of research studies and allowing read‑ ers to comprehend the results more easily, which reduces the chances of bias and mistakes in data collection [72]. After accepting only scientific production in the form of articles and eliminating research that did not aim to analyze Introduction To achieve this end, a bibliometric analysis is initially conducted, pro‑ ceeding with the quantitative examination of the scientific production, and, subsequently, a systematic analysis is car‑ ried out to review in-depth the 39 records identified from 1996 to 2022, thus allowing to pinpoint the research fronts on the subject and, based on them, to propose future research lines. In fact, such a mixed methodological approach, based on bibliometric (quantitative approach) and systematic (qualitative approach) review, is carefully designed to pro‑ vide a comprehensive view on contemporary research in the specified area, serving as a navigational tool through the complex landscape of prevailing trends, leading scholars and organizations, major publications in the domain, research fronts, and the future trajectory of publications. and press journals [15]. SSCI includes references from approximately 3000 social science journals, featuring both press and conference journals [13]. ESCI is an index of cita‑ tions which encompasses emerging science journals as well as some press and conference journals, in an effort to rep‑ resent the variety of scientific publications, such as those from developing countries, and includes more than 5000 journals [14]. After evaluating the value of the WoS Core Collection, a search was implemented to identify articles related to the topic. Multiple efforts were made to evaluate the most rele‑ vant results and the least pertinent ones in order to eliminate any extraneous discoveries. Ultimately, it was determined that the most appropriate search equation among the avail‑ able options was the following: Materials and methods This study conducted a bibliometric analysis using the Web of Science (WoS) database. Boolean and proximity opera‑ tors, along with markers, were utilized to evaluate the quality and accuracy of the selected works. It should be noted that the WoS Core Collection was chosen for its rigorous inclu‑ sion criteria for articles. The three indexes selected from the WoS Core Collection were the Science Citation Index Expanded (SCI-E), Social Sciences Citation Index (SSCI), and Emerging Sources Citation Index (ESCI). SCI-E is an extensive index of cita‑ tions from scientific and technological journals since 1900, including 8,000 scientific journals and 12,000 conference European Food Research and Technology (2024) 250:2273–2289 2275 Results and discussion automation in the wine industry, the number of documents was reduced from 108 to 39, thus forming the corpus of arti‑ cles to be examined (see Fig. 1). In particular, after the selec‑ tion of articles only, the number of records was reduced from 108 to 77 and, subsequently, articles were checked record by record to ensure that they explicitly addressed automa‑ tion in the wine industry, eliminating 38 records that did not address automation in the wine industry, thus resulting in a sample of 39 articles.i The present study analyzed a collection of articles on auto‑ mation in the wine industry. The findings shown in Table 1 account for the relevant data of the papers, such as the num‑ ber of sources and papers and the average age of the arti‑ cles, as well as the number of citations received and refer‑ ences used. The keywords and authors of each paper are also included. The analysis of the scientific production was conducted by selecting multiple classification variables. Initially, the records were separated according to the year of publication in various journals to determine the level of interest in the topic over time. Subsequently, the main journals for dis‑ seminating research results were specified. In addition, a network and overlay map was generated through VosViewer to find out the main keywords used in the studies analysed, as well as their study over time. Authors were identified and the institutions to which the authors belonged were studied. This analysis was completed with the study of the network of collaborations, as well as the analysis of scientific produc‑ tion by country, both of which were carried out using the Bibliometrix software. Finally, once the scientific produc‑ tion had been quantitatively examined using the VosViewer and Bibliometrix applications, the content of the articles examined was reviewed following the PRISMA guidelines. Table 1 General information on the scientific production analyzed Table 1 General information on the scientific production analyzed Source: own elaboration Main information data Sources 29 Documents 35 Document Average Age 11.4 Average citations per doc 19.08 References 980 Document contents Author’s Keywords (DE) 140 Authorship Authors 154 Authors of single-authored docs 0 Authors collaboration Co-Authors per doc 4.34 International co-authorships % 28.95 Fig. 1 Flow diagram about the bibliometric review procedure developed. Source: own elaboration based on PRISMA guidelines diagram about the bibliometric review procedure developed. Results and discussion Source: own elaboration based on PRISMA guidelines European Food Research and Technology (2024) 250:2273–2289 2276 As for the temporal evolution of the scientific production, Fig. 2 shows how it is distributed irregularly from 1996, the year in which the first academic articles on the subject were published, to 2022. Specifically, the distribution of scien‑ tific production follows the shape of sawtooths, experienc‑ ing three notable peaks with 4 publications relating to the years 2005, 2014 and 2019. However, despite the discon‑ tinuous evolution, it is necessary to highlight the efforts to address the subject throughout the period analyzed. This academic effort on the subject may be due to several fac‑ tors. On the one hand, the study of automation solutions in this sector allows greater efficiency and productivity in an increasingly competitive industry, enabling greater preci‑ sion in manufacturing processes, resulting in higher quality wines [44]. Automation can help reduce labor costs and save time, resulting in higher profits for producers, and can also help improve quality control and food safety, which are of great importance to the industry [22]. On the other hand, the growth of scientific production in the WoS Core Collection in the last decade, derived from the increased indexing of journals in this collection [60], may result in an increasing number of computable articles. Figure 3 shows the main avenues for disseminating research results related to automation in the wine industry. The first journal is Analytica Chimica Acta (4), from the Elsevier publishing house, followed by Journal of Agricul‑ tural Engineering (3), Journal of Chromatography A (3), Journal of AOAC International (2), Water Science and Technology (2), Agriculture and Human Values, (1), Ana‑ lytical Chemistry (1), Chemical Papers (1), Computers and Electronics in Agriculture (1) and Data (1). It should also be noted that the top three publishers in terms of scientific Fig. 2 Evolution over time of the scientific production ana‑ lyzed. Source: own elaboration based on Bibliometrix® Fig. 3 List of the top ten most prolific journals in the field of automation in the wine industry. Source: own elaboration based on Bibliometrix® Fig. 2 Evolution over time of the scientific production ana‑ lyzed. Source: own elaboration based on Bibliometrix® f the top ten most prolific journals in the field of automation in the wine industry. Source: own elaboration based on Fig. Results and discussion 3 List of the top ten most prolific journals in the field of automation in the wine industry. Source: own elaboration based on Bibliometrix® Fig. 3 List of the top ten most prolific journals in the field of automation in the wine industry. Source: own elaboration based on Bibliometrix® European Food Research and Technology (2024) 250:2273–2289 2277 production indexed in one of their associated journals are Elsevier (14), Springer (4) and Wiley (3).i tool to evaluate wine composition, including the detection of ethanol and other chemical components, which is crucial for quality control and to ensure the consistency of the final product [11]. To determine the topics analyzed in the scientific produc‑ tion under study, an analysis of co-occurrence of keywords was carried out, as shown in Fig. 4. For practical reasons, keywords that appear at least 3 times in the records consid‑ ered were included. As can be seen, there are 7 clusters of keywords around the subject matter. Cluster 3, in pink, has as main banners the words fer‑ mentation, design and amperometric glucose. This group emphasizes the design of fermentation technologies and control systems, such as amperometric sensors for glucose monitoring, as such monitoring is vital to control the fer‑ mentation process and ensure that sugars are properly con‑ verted into alcohol and other desired end products [62]. In this context, automation is about optimizing and controlling the fermentation process for consistent, high quality wine production [20]. Cluster 1, in light blue, is headed by the word automation, agricultural robot, gas-chromatography and energy. In the context of viticulture, agricultural robots automate labor- intensive tasks such as pruning, harvesting and monitoring vineyard conditions, thereby increasing efficiency and reduc‑ ing manual labor [51]. Also, gas chromatography is essential for analyzing wine composition, including aroma and flavor compounds, which are crucial for quality control and inclu‑ sion of the keyword energy can be linked to the growing concern for energy-efficient practices in wine production, where automation technologies can play an important role in reducing energy consumption and optimizing resource utilization [36]. Cluster 4, in yellow, is mainly represented by the key‑ words bottle storage, samples, low-cost and detectors. Auto‑ mated bottle storage systems help manage large inventories, ensure optimal aging conditions and track wine provenance [22]. Results and discussion Samplers and detectors refer to automated sampling and detection systems for quality control, which ensure that each bottle meets the desired standards before reaching con‑ sumers [9], and the emphasis on the keyword low cost indi‑ cates that the aim is to make these technologies accessible and economically viable for wineries of different scales [23]. Cluster 2, in red, is headed by the word grape, liquid, ethanol, acetic-acid bacteria and spectroscopy. This cluster covers the transformation of grapes into wine, focusing on the chemical composition of the liquid, such as ethanol pro‑ duction during fermentation. On the one hand, acetic acid bacteria are a concern in winemaking because of their role in wine spoilage, leading to unpleasant vinegar flavors [47]. On the other hand, spectroscopy is an essential analytical f Cluster 5, in lilac, is headed by the keywords: computer vision, image processing, cork and neural networks. These technologies can be used for a variety of purposes, such as inspecting and sorting grapes, detecting defects in corks, and even analyzing wine color and clarity [59]. In this sense, Fig. 4 Network map on the co-occurrence of keywords. Source: elaborated on the basis of WoS and VOSviewer Fig. 4 Network map on the co-occurrence of keywords. Source: elaborated on the basis of WoS and VOSviewer Fig. 4 Network map on the co-occurrence of keywords. Source: elaborated on the basis of WoS and VOSviewer European Food Research and Technology (2024) 250:2273–2289 2278 amalgamating diverse data sets—from weather conditions to vine health metrics—to facilitate informed decision making, given that, in an industry where subtle environ‑ mental variations can significantly influence grape qual‑ ity, the ability to synthesize broad data sets into action‑ able information can enable optimization in the use of resources and maximization of yield quality [39]. Third, life cycle assessment emerges as another fundamental concept, underscoring the industry's growing concern for environmental sustainability, since, by assessing the envi‑ ronmental impact of wine production from vine to bottle, this methodology helps identify areas for improvement, whether in energy use, water management or carbon foot‑ print reduction [19]. Fourth, precision viticulture stands out as a testament to the evolving nature of viticulture, emphasizing the use of technology to adapt vineyard practices to the specific conditions of each plot [8]. Results and discussion Source: elaborated on the basis of WoS and VOSviewer European Food Research and Technology (2024) 250:2273–2289 2279 and data sharing between the various stakeholders, foster‑ ing a more integrated and transparent supply chain [5]. of Cordoba and University of Milan (with 3 articles each). Thus, of the top institutions in terms of scientific production on the subject, Spain and China are the countries with the largest number of institutions (tied with 3). This is related to the data shown in Fig. 6 on production by country, given that the Spain is the country with the highest scientific produc‑ tion on the topic under study (15 articles), followed by Italy (10), Chile (6 articles) and China (5 articles).i Table 2 displays the articles that have collected the highest total number of citations both globally and locally. Global citations, on the one hand, refer to the cumulative citations that a given article has obtained from any given area and location. On the other hand, local citations are the citations that each individual article has acquired from other articles within the analyzed repository. Furthermore, nor‑ malized total citations are the number of citations attributed to a research article or author, corrected for the number of years since publication and the average number of citations received by articles in the same field and time period. This metric takes into consideration variances in citation prac‑ tices between fields and time periods, as well as the tempo‑ ral aspect of citation influence. As can be observed, among the 10 most cited articles globally and among the literature analyzed, four publications coincide. These correspond to the research by Chilla et al. [12], Chang et al. [10], Torrijos and Moletta [67] and Ruíz et al. [53]. As for the classification of authors, Table 4 shows the most prominent authors according to the number of arti‑ cles published. As can be seen, Barroso C, Guillen D, and Perezbustamante J, are the authors with the highest sci‑ entific production on the subject with 3 articles, followed by De Castro M, Moletta R, Pérez-Correa J, Pérez-Correa J, Sánchez-Rojas J and Torrijos M (with 2 articles each author). Figure 7 also shows how the main authors on the subject are organized into 13 collaborative clusters, being the one formed by Barroso C, Guillen D and Perezbusta‑ mante J. the cluster with the greatest weight in terms of jointly published articles. Results and discussion This method uses advanced technologies such as GPS, remote sensing and Internet of Things (IoT) devices to achieve optimal grape quality and sustainable farming practices, allowing to improve not only wine quality, but also ensures more environmentally friendly and economically viable operations [56]. Fifth, extreme machine learning, a type of artificial intelligence, indicates the industry's move towards innovative and efficient computational models for problem solving, being applied to various aspects of wine production, from predictive analysis in vineyards to quality control in wineries [6]. Sixth, the current use of the key‑ word collaborative platforms reflects a digital transforma‑ tion in the wine industry, which facilitate communication image processing and neural networks improve the accuracy and efficiency of these tasks, contributing to overall quality control and process optimization [16]. Cluster 6, in light green, is led by the keywords: aroma and solid-phase microextraction. Solid-phase microextrac‑ tion is a method used to extract volatile compounds from wine, which are fundamental to its aromatic profile [45]. Automation in this field implies the development of high- performance, accurate and consistent methods of aroma analysis, which would contribute to the standardization of the sensory characteristics of wine [50]. Cluster 7, in dark green, is composed of cinerea, ber‑ ries and botrytis. Automation in this context may involve the development of precision agriculture tools for moni‑ toring and managing vineyard health, using data analytics and machine learning to predict and control the spread of such diseases, thereby ensuring the health and quality of the grapes [26]. The analysis of the keywords is complemented by the study of their use over time, In this regard, Fig. 5 shows that the most commonly used keywords currently used are computer vision, data aggregation, life cycle assessment, precision viticulture, extreme learning machine and collabo‑ rative platform. First, computer vision embodies the integration of arti‑ ficial intelligence and image analysis, enabling accurate monitoring of grape maturity, disease detection and yield estimation, its growing importance representing a move towards more efficient, data-driven vineyard manage‑ ment [68]. Second, data aggregation complements it by Fig. 5 Overlay map of the co-occurrence of keywords. Source: elaborated on the basis of WoS and VOSviewer Fig. 5 Overlay map of the co-occurrence of keywords. Source: elaborated on the basis of WoS and VOSviewer ig. 5 Overlay map of the co-occurrence of keywords. TC total citations, LC local citations, GL global citations Table 2 Most cited papers (globally and within dataset) Source: own elaboration based on Bibliometrix® Results and discussion After the bibliometric analysis, in which the literature under study was examined quantitatively, a systematic analy‑ sis of the research was carried out. Results and discussion Thus, as can be seen in Table 5, the objective of the research, its methodological With regard to the main institutions analyzing the subject (see Table 3), it can be seen that the universities that lead the research on automation in the wine industry are Univer‑ sity of Cadiz, University of Castilla La Mancha, University Source: own elaboration based on Bibliometrix® TC total citations LC local citations GL global citations Most cited papers (globally) Paper TC TC per Year Normalized TC Santos T, 2020, Comput Electron Agr 129 32,25 1,00 Mirnaghi FS, 2013, J Chromatogr A 57 5,18 2,34 Torrijos M, 1997, Water Sci Technol 51 1,89 1,74 Kritsunankul O, 2009, Talanta 40 2,67 1,00 Ruíz C, 2002, Water Sci Technol 37 1,68 1,00 Pinto PCAG, 2005, Anal Chim Acta 37 1,95 2,11 Toledo J, 2018, Sensor Actuat B-Chem 37 6,17 1,35 Chilla C, 1996, J Chromatogr A 36 1,29 1,22 Chang SH, 1997, IEEE T Neural Networ 35 1,30 1,19 Rist F, 2018, Sensors-Basel 35 5,83 1,28 Most cited papers (within dataset) Document LC GC Normalized LC Guillen DA, 1996, J Chromatogr A 1 23 0,78 Torrijos M, 1997, Water Sci Technol 1 51 1,74 Jiménez-Márquez F, 2014, Microsyst Technol 1 13 1,44 Chilla C, 1996, J Chromatogr A 0 36 1,22 Guillen DA, 1997, Quim Anal 0 2 0,07 Chang S, 1997, IEEE T Neural Networ 0 35 1,19 Ruíz C, 2002, Water Sci Technol 0 37 1,00 De Castro Mdl, 2003, J Aoac Int 0 9 1,00 Komes D, 2005, Vitis 0 12 0,69 Pinto Pcag, 2005, Anal Chim Acta 6 37 2,11 European Food Research and Technology (2024) 250:2273–2289 2280 European Food Research and Technology (2024) 250:2273–2289 Table 3 Most prolific institutions (institutions with more than two records) Source: own elaboration based on WoS Rank Affiliations Location (Country) Articles 1 University of Cadiz Spain 3 2 University of Castilla La Mancha Spain 3 3 University of Cordoba Spain 3 4 University of Milan Italy 3 5 San Jose State University USA 2 6 Moutai Institute China 2 7 National Institute of Biological Sciences China 2 8 National Tsing Hua University China 2 9 Palacký University Olomouc Czech Republic 2 10 Pontificia Universidad Católica de Chile Chile 2 11 Universita di Bologna Italy 2 12 University of Bonn Germany 2 Source: own elaboration based on WoS focuses on the development of automated methods to improve sample preparation, detection and analysis of com‑ pounds, especially polyphenolics, in wines. Results and discussion There is growing interest in the use of technologies such as high-performance liquid chromatography and mass spectrometry to analyze compounds in wines, suggesting a focus on improving accu‑ racy and efficiency in wine chemical analysis. Second, there is a block of papers focused on identifying efforts to develop automated systems for sorting cork quality and for monitor‑ ing fermentation and aroma production in wine, indicating an interest in optimizing product quality and production process efficiency. The third block of research focuses on sustainability and efficient resource management in the wine industry, with a notable trend towards the implementation of sensors and optoelectronic devices for real-time monitoring of viticulture and winemaking processes. These technologi‑ cal tools provide accurate and constant data, facilitating a more efficient and sustainable management of resources, as well as an improvement in the quality of the final product. This focus on the integration of automation and computeri‑ zation reflects a paradigm shift in the wine industry, given that, by prioritizing both product quality and the efficiency and sustainability of production processes, a new horizon is taking shape for vine cultivation and wine production, where advanced technology plays a crucial role in harmonizing winemaking excellence with environmental responsibility. Fig. 6 Scientific production by country. Source: own elaboration based on Bibliometrix® Fig. 6 Scientific production by country. Source: own elaboration based on Bibliometrix® Table 4 Ranking of leading authors (authors with more than two records) Table 4 Ranking of leading authors (authors with more than two records) Source: own elaboration based on Bibliometrix® A. P. articles published Rank Authors A. P Rank Authors A. P 1 Barroso C 3 5 Moletta R 2 2 Guillen D 3 6 Pérez-Correa J 2 3 Perezbustamante J 3 7 Sánchez-Rojas J 2 4 De Castro M 2 8 Torrijos M 2 approach, the research context and the phase of the wine value chain on which the study is focused were examined. The results show the preponderance of the quantitative ver‑ sus qualitative methodological approach, the selection of a global framework versus a specific wine context, as well as the greater study of automation in the wine production phase within the wine value chain, versus the viticulture and wine distribution phase. Likewise, by analyzing the content of the articles, three lines of research were identified in relation to the subject matter under study. The first block of research Conclusions and future research agenda This research examines the structure of knowledge on automation in the wine industry, becoming a valuable resource for novice and experienced academics interested in exploring the development of the scientific literature on the subject, as well as for wine managers to learn about European Food Research and Technology (2024) 250:2273–2289 2281 Fig. 7 Author collaboration network. Source: own elaboration based on Bibliometrix® Fig. 7 Author collaboration network. Source: own elaboration based on Bibliometrix® This research contributes significantly to the theoreti‑ cal, practical and policy domain in the study of automation in the wine industry. From a theoretical perspective, first, it provides a comprehensive overview of the scientific lit‑ erature devoted to the analysis of automation in this sector; second, it facilitates researchers to identify key organiza‑ tions and geographic regions linked to the topic, thus pro‑ moting research visits and collaboration on joint projects; third, it makes it possible to locate other experts with whom to collaborate and, potentially, to organize specialized con‑ ferences; fourth, it provides guidance in the selection of appropriate journals and publishers for the dissemination of research results; and fifth, the study the study sets the stage for academics to identify emerging trends in the automation of the wine value chain, thus enriching the existing theoreti‑ cal corpus and opening up new avenues for future research. modern trends in automation and, if appropriate, to inte‑ grate these innovations in the different stages of the win‑ emaking process.i In order to advance in the research field of automation in the wine industry, future directions are outlined that address emerging and still unexplored domains in relation to the ana‑ lyzed topic. First, research is proposed on the integration of advanced robotics in viticulture and enology, with special interest in the development of drones and autonomous robots for pruning, harvesting and monitoring of vine and soil con‑ ditions, with the aim of increasing the precision of these fundamental operations. Second, it is proposed to examine the application of nanotechnology in winemaking, propos‑ ing the use of sensors for real-time monitoring of soil qual‑ ity, and the development of nanomaterials to optimize wine preservation and packaging, thus opening new avenues for quality control and wine shelf-life extension. Conclusions and future research agenda Third, it is also suggested to explore the potential of augmented and virtual reality to enrich the wine tasting experience and in the train‑ ing of winery personnel, offering sensory simulations and virtual environments for learning winemaking techniques. Fourth, it is proposed to examine the role of artificial intel‑ ligence in predicting market trends and wine personaliza‑ tion, using advanced algorithms to adapt products to con‑ sumer preferences and market demands. Finally, fifth, it is proposed to investigate energy sustainability in the wine industry, exploring specific renewable energy solutions and wine production methods with lower environmental impact, thus marking a path towards innovation and sustainability in the sector. Thus, while the identification of the current research fronts shown in the results and the future research agenda proposed in this section enable to address RQ 1, the quantitative examination of the research examined presented in the results section enables to answer RQ 2. p p g p From a practical perspective, this study highlights the importance for winery managers to recognize the potential of automation to improve efficiency and quality in wine production. Automation of processes such as fermenta‑ tion monitoring, cork selection and wine component analysis can increase the accuracy of the final product, vitally important in an industry where quality and product characterization are critical to market success. In addi‑ tion, the study highlights the crucial role of automation in the sustainability of the wine industry, urging winery managers to consider adopting automated technologies for efficient resource management and minimizing envi‑ ronmental impact. Further practical implications focus on the integration of artificial intelligence and data analytics in winemaking decision-making, as the ability to process large volumes of data to predict market trends, optimize production processes and improve vine disease manage‑ ment opens up new possibilities for competitiveness in an European Food Research and Technology (2024) 250:2273–2289 2282 Table 5 Analysis of the scientific production examined in the literature review No Authors Journal Research objective Methodology Country/Region Wine value chain 1 Guillén et al. [24] Journal of Chromatography A To automate sample preparation for HPLC analysis of polyphenolic compounds in sherry wine, improving recovery and repeatability values Quantitative Spain Winemaking 2 Chilla et al. [12] Journal of Chromatography A To develop a new method for preconcentrat‑ ing and analyzing phenolic compounds in sherry wine using on-line SPE-HPLC with diode array detection Quantitative Spain Winemaking 3 Guillén et al. Conclusions and future research agenda [25] Quimica Analitica To apply a previously developed method for monitoring phenolic compounds during the fermentation of sherry must, using auto‑ mated SPE and HPLC–DAD analysis Quantitative Spain Winemaking 4 Torrijos and Moletta [67] Water Science and Technology To demonstrate a depollution process for treating effluents from small wineries using a sequencing batch reactor with temporary storage facilities Quantitative Global setting Winemaking 5 Chang et al. [10] IEEE Transactions on Neural Networks To develop an automated cork stopper qual‑ ity classification system using morpho‑ logical filtering, contour extraction, and a fuzzy-neural network to improve accuracy and reduce costs Quantitative Mediterranean countries Winemaking 6 Ruiz et al. (2002) Water Science and Technology To evaluate the effectiveness of an anaerobic sequencing batch reactor in treating winery wastewater, focusing on biogas produc‑ tion, COD removal, and kinetics of VFA removal Quantitative Global setting Winemaking 7 Luque de Castro et al. [35] Journal of AOAC International To review the use of analytical pervaporation in enology, assessing its advantages and comparing it with standard methods for determining analytes in wine Qualitative Global setting Winemaking 8 Komes et al. [31] Vitis To compare three methods for preparing white wine samples for gas chromatogra‑ phy, focusing on replacing liquid–liquid extraction with HS-SPME and SBSE Quantitative Global setting Winemaking 9 Pinto et al. [49] Analytica Chimica Acta To develop an automatic system for evaluat‑ ing the relative antioxidant capacity of wine samples using two different analytical procedures Quantitative Portugal Winemaking Table 5 Analysis of the scientific production examined in the literature review 2283 European Food Research and Technology (2024) 250:2273–2289 ab e 5 (co t ued) No Authors Journal Research objective Methodology Country/Region Wine value chain 10 Pinheiro et al. [48] Analytical Chemistry To monitor the bioproduction of complex aroma profiles in muscatel wine must fermentation using an integrated pervapo‑ ration-electronic nose system, overcoming ethanol interference Quantitative Global setting Winemaking 11 Cuadrado et al. [17] Analytica Chimica Acta To develop an automated method for deter‑ mining laccase activity in musts and wines, offering a new tool for assessing Botrytis cinerea infection Quantitative Global setting Winemaking 12 Jan et al. [28] Food control To explore the use of ultrasound in measur‑ ing sugar and alcohol concentrations in hydroalcoholic solutions, mimicking fermenting musts in the Chilean wine industry Quantitative Chile Winemaking 13 Osorio et al. Conclusions and future research agenda [42] Journal of Food Engineering To develop a cost-effective soft-sensor for on-line estimation of distillate ethanol concentration in brandy production using temperature measurements Quantitative Chile Winemaking 14 Kritsunankul et al. [32] Talanta To develop an automated FID-HPLC system for simultaneous determination of six organic acids in wine, with online dialysis sample pretreatment Quantitative Thailand Winemaking 15 Albanese et al. [2] IEEE Transactions on Instrumentation and Measurement To develop an automated system for moni‑ toring biological processes in winemaking using amperometric biosensors in flow injection analysis Quantitative Global setting Winemaking 16 Rosaldini and Ceccarelli (2012) Geomedia To address the need for automation, comput‑ erization, and traceability in agricultural and wine-devoted farms by developing a GIS-based agrarian wine cellar informa‑ tion system Quantitative Global setting Viticulture 17 Jakubec et al. [27] Journal of Agricultural and Food Chemistry To develop and test a method for analyz‑ ing total antioxidant capacity and total phenolic content in wines using microdi‑ alysis online-coupled with amperometric detection Quantitative Global setting Winemaking 18 Oberti et al. [40] Journal of Agricultural Engineering To develop a robotic system for selective spraying of grapevine diseases, reducing pesticide use by targeting only infected areas Quantitative European Union countries Viticulture European Food Research and Technology (2024) 250:2273–2289 2284 Table 5 (continued) No Authors Journal Research objective Methodology Country/Region Wine value chain 19 Pezzi et al. (2013) Journal of Agricultural Engineering To conduct a technical and economic evalua‑ tion of the maceration process in red grape production for everyday wine Quantitative Global setting Winemaking 20 Mirnaghi et al. [37] Journal of Chromatography A To optimize an automated 96-thin-film SPME system for high-throughput analysis of phenolic compounds in wine, berry, and grape samples using LC–MS/MS Quantitative Global setting Winemaking 21 Jiménez-Márquez et al. [29] Microsystem Technologies To develop an optoelectronic device for automating the monitoring of wine fermen‑ tation kinetics and maceration, enhancing the quality-cost ratio in winemaking Quantitative Global setting Winemaking 22 Teodor et al. [64] Chemical Papers To characterize wine samples in ceramic pots using various methods, focusing on chemical and mineralogical aspects, and identify potential biomarkers for wine residues in archaeological pottery Quantitative Global setting Winemaking 23 Mirzoian and Ammann [38] Journal of AOAC International To develop and validate a direct injection LC/MS/MS method for determining the pesticide oxadixyl in wines, with minimal sample preparation and high throughput Quantitative Global setting Viticulture 24 Lee et al. Conclusions and future research agenda [33] International Journal of Food Science & Technology To develop an automated Folin-Ciocalteu method for measuring total phenolic con‑ tent in wine, aiming for faster processing, reduced errors, and waste minimization Quantitative Global setting Winemaking 25 Yakuba et al. [70] Journal of Analytical Chemistry To evaluate wine quality using discriminant analysis based on volatile substance con‑ centrations and taste test results, aiming to compare with expert evaluations Quantitative Global setting Winemaking 26 Khalafyan et al. [30] Journal of Analytical Chemistry To develop a model for predicting wine quality based on concentrations of volatile substances and organoleptic ratings, using statistical-probability simulation methods Quantitative Global setting Winemaking 27 Toledo et al. [66] Sensors and Actuators B: Chemical To enhance wine fermentation monitoring by designing an AlN-based piezoelectric microresonator for in-line tracking of grape must fermentation, improving automation and accuracy Quantitative Global setting Winemaking 28 Rist et al. [52] Sensors To develop a high-precision phenotyping pipeline using 3D scanning for assess‑ ing grapevine bunch architecture traits in breeding programs Quantitative Global setting Viticulture (continued) thors Journal Research objective Methodology Country/Region Wine value chain zzi et al. (2013) Journal of Agricultural Engineering To conduct a technical and economic evalua‑ tion of the maceration process in red grape production for everyday wine Quantitative Global setting Winemaking rnaghi et al. [37] Journal of Chromatography A To optimize an automated 96-thin-film SPME system for high-throughput analysis of phenolic compounds in wine, berry, and grape samples using LC–MS/MS Quantitative Global setting Winemaking ménez-Márquez et al. [29] Microsystem Technologies To develop an optoelectronic device for automating the monitoring of wine fermen‑ tation kinetics and maceration, enhancing the quality-cost ratio in winemaking Quantitative Global setting Winemaking odor et al. [64] Chemical Papers To characterize wine samples in ceramic pots using various methods, focusing on chemical and mineralogical aspects, and identify potential biomarkers for wine residues in archaeological pottery Quantitative Global setting Winemaking rzoian and Ammann [38] Journal of AOAC International To develop and validate a direct injection LC/MS/MS method for determining the pesticide oxadixyl in wines, with minimal sample preparation and high throughput Quantitative Global setting Viticulture e et al. [33] International Journal of Food Science & Technology To develop an automated Folin-Ciocalteu method for measuring total phenolic con‑ tent in wine, aiming for faster processing, reduced errors, and waste minimization Quantitative Global setting Winemaking kuba et al. Conclusions and future research agenda [70] Journal of Analytical Chemistry To evaluate wine quality using discriminant analysis based on volatile substance con‑ centrations and taste test results, aiming to compare with expert evaluations Quantitative Global setting Winemaking alafyan et al. [30] Journal of Analytical Chemistry To develop a model for predicting wine quality based on concentrations of volatile substances and organoleptic ratings, using statistical-probability simulation methods Quantitative Global setting Winemaking edo et al. [66] Sensors and Actuators B: Chemical To enhance wine fermentation monitoring by designing an AlN-based piezoelectric microresonator for in-line tracking of grape must fermentation, improving automation and accuracy Quantitative Global setting Winemaking t et al. [52] Sensors To develop a high-precision phenotyping pipeline using 3D scanning for assess‑ ing grapevine bunch architecture traits in breeding programs Quantitative Global setting Viticulture 2285 European Food Research and Technology (2024) 250:2273–2289 ( ) No Authors Journal Research objective Methodology Country/Region Wine value chain 29 Yang et al. [71] Analytica Chimica Acta To optimize the kinetic process of continu‑ ous liquid–liquid extraction for real-time analysis of volatile wine components, using an Arduino-controlled system cou‑ pled with mass spectrometry Quantitative Global setting Winemaking 30 Hill et al. [26] Phytopathology To predict botrytis bunch rot risk in wine- grape production using automated analysis of disease, weather, and vine phenology data across multiple regions and seasons Quantitative Global setting Viticulture 31 Phansi et al. [46] Food chemistry To develop a multisyringe flow injection analysis system for the automatic spectro‑ photometric determination of total iron in wine Quantitative Global setting Winemaking 32 Mylonas et al. [39] Information To develop a model for an aggregation platform enhancing smart agriculture in viticulture, enabling improved data annota‑ tions and enrichment through AI automa‑ tion and human–computer collaboration Qualitative Global setting Viticulture 33 Sández et al. [55] Analytica Chimica Acta To design, construct, and evaluate a low-cost microanalyzer for determining the titrat‑ able acidity content of wine using a con‑ tinuous flow system with optical detection Quantitative Global setting Winemaking 34 Santos et al. [57] Computers and Electronics in Agriculture To demonstrate the use of convolutional neu‑ ral networks for detecting, segmenting, and tracking grape clusters in orchards using proximal sensing and affordable cameras Quantitative Global setting Viticulture 35 Giovenzana et al. Conclusions and future research agenda [22] Journal of Agricultural Engineering To analyze an automated yeast nutrition management system for alcoholic fermen‑ tation in wineries, assessing its envi‑ ronmental, management, and economic performance Quantitative Italy Winemaking 36 Signorini et al. [63] Horticulturae To assess the economic feasibility of grape vineyards in the Midwest U.S.A. by ana‑ lyzing different production scenarios using sample budgets and survey data Quantitative United States of America Viticulture 37 Apostolidis et al. [3] Data To create a public image dataset for grape‑ vine canes segmentation to facilitate the automation of grapevine pruning using computer vision and image processing methods Quantitative Global setting Viticulture Table 5 (continued) No Authors Journal Research objective Methodology Country/Region Wine value chain 29 Yang et al. [71] Analytica Chimica Acta To optimize the kinetic process of continu‑ ous liquid–liquid extraction for real-time analysis of volatile wine components, using an Arduino-controlled system cou‑ pled with mass spectrometry Quantitative Global setting Winemaking 30 Hill et al. [26] Phytopathology To predict botrytis bunch rot risk in wine- grape production using automated analysis of disease, weather, and vine phenology data across multiple regions and seasons Quantitative Global setting Viticulture 31 Phansi et al. [46] Food chemistry To develop a multisyringe flow injection analysis system for the automatic spectro‑ photometric determination of total iron in wine Quantitative Global setting Winemaking 32 Mylonas et al. [39] Information To develop a model for an aggregation platform enhancing smart agriculture in viticulture, enabling improved data annota‑ tions and enrichment through AI automa‑ tion and human–computer collaboration Qualitative Global setting Viticulture 33 Sández et al. [55] Analytica Chimica Acta To design, construct, and evaluate a low-cost microanalyzer for determining the titrat‑ able acidity content of wine using a con‑ tinuous flow system with optical detection Quantitative Global setting Winemaking 34 Santos et al. [57] Computers and Electronics in Agriculture To demonstrate the use of convolutional neu‑ ral networks for detecting, segmenting, and tracking grape clusters in orchards using proximal sensing and affordable cameras Quantitative Global setting Viticulture 35 Giovenzana et al. [22] Journal of Agricultural Engineering To analyze an automated yeast nutrition management system for alcoholic fermen‑ tation in wineries, assessing its envi‑ ronmental, management, and economic performance Quantitative Italy Winemaking 36 Signorini et al. [63] Horticulturae To assess the economic feasibility of grape vineyards in the Midwest U.S.A. Conclusions and future research agenda by ana‑ lyzing different production scenarios using sample budgets and survey data Quantitative United States of America Viticulture 37 Apostolidis et al. [3] Data To create a public image dataset for grape‑ vine canes segmentation to facilitate the automation of grapevine pruning using computer vision and image processing methods Quantitative Global setting Viticulture European Food Research and Technology (2024) 250:2273–2289 2286 ever-changing marketplace. Ultimately, this study empha‑ sizes the importance of senior management commitment to training and continuing education in the wine industry, because as automation and new technologies gain ground, it is crucial that wine professionals are equipped with the skills and knowledge necessary to use these tools effec‑ tively. This would not only improve the efficiency of wine production, but also ensure that the industry can evolve and adapt to technological advances. Table 5 (continued) No Authors Journal Research objective Methodology Country/Region Wine value chain 38 Xiao et al. [69] Mathematical Problems in Engineering To develop a multimotor drive control method based on machine vision for an upper-retort-robot to automate wine brew‑ ing, particularly for military use in cold regions of China Quantitative China Winemaking 39 Legun et al. [34] Agriculture and Human Values To explore agricultural managers' percep‑ tions of automation potential in relation to expertise required for work on apple orchards and winegrape vineyards in Aotearoa New Zealand Qualitative New Zealand Viticulture From the policy implications angle, this research under‑ scores the need to formulate policies that encourage inno‑ vation and the adoption of automated technologies in the wine industry. This would involve incentives for research and development, as well as financial support for wineries, especially small and medium-sized enterprises, to adopt new technologies. It would be also crucial to promote the regu‑ lation of automation and artificial intelligence in the wine industry, covering aspects such as security, data privacy and ethics in the use of artificial intelligence. Policies should ensure that the adoption of these technologies is done in a responsible and transparent manner, protecting both con‑ sumers and producers. Similarly, policy makers could direct their efforts to promote sustainable practices in viticulture, such as reducing the use of pesticides and efficient water management, supported by automation technologies, which would also imply the need for policies that encourage the adoption of cleaner and more environmentally friendly pro‑ duction practices. References 22. Giovenzana V, Baroffio S, Beghi R, Casson A, Pampuri A, Tugnolo A, Guidetti R (2021) Technological innovation in the winery addressing oenology 4.0: testing of an automated sys‑ tem for the alcoholic fermentation management. J Agricult Eng 52(4):1–10 1. Adeleke I, Nwulu N, Adebo OA (2023) Internet of Things (IoT) in the food fermentation process: a bibliometric review. J Food Process Eng 46(5):e14321 g 2. Albanese D, Liguori C, Paciello V, Pietrosanto A (2011) Win‑ emaking process monitoring based on a biosensor automatic system. IEEE Trans Instrum Meas 60(5):1909–1916 23. Gonzalez Viejo C, Fuentes S (2022) Digital assessment and classification of wine faults using a low-cost electronic nose, near-infrared spectroscopy and machine learning modelling. Sensors 22(6):2303 3. Apostolidis K, Kalampokas T, Pachidis T, Kaburlasos V (2022) Grapevine plant image dataset for pruning. Data 7(8):110 4. Baiano A (2021) An overview on sustainability in the wine production chain. Beverages 7(1):15 24. Guillén D, Barroso C, Pérez-Bustamante J (1996) Automation of sample preparation as a preliminary stage in the high-perfor‑ mance liquid chromatographic determination of polyphenolic compounds in sherry wines. J Chromatogr A 730(1–2):39–46 5. Baker J, Nenonen S (2020) Collaborating to shape markets: emergent collective market work. Ind Mark Manage 85:240–253 6. Bhardwaj P, Tiwari P, Olejar K Jr, Parr W, Kulasiri D (2022) A machine learning application in wine quality prediction. Mach Learn Appl 8:100261 25. Guillén D, Barroso C, Pérez-Bustamante J (1997) Automated solid phase extraction followed by HPLC-DAD for the monitor‑ ing of phenolic compounds during fermentation of sherry must. Quimica Analitica-Bellaterra 16:21–26 7. Biswas K, Muthukkumarasamy V, Tan WL (2017) Blockchain based wine supply chain traceability system. In: Future tech‑ nologies conference (FTC) 2017. The Science and Information Organization, pp 56–62 26. Hill G, Beresford R, Evans K (2019) Automated analysis of aggregated datasets to identify climatic predictors of botrytis bunch rot in wine grapes. Phytopathology 109(1):84–95 8. Bramley R (2022) Precision viticulture: managing vineyard var‑ iability for improved quality outcomes. Managing wine quality. Woodhead Publishing, pp 541–586 27. Jakubec P, Bancirova M, Halouzka V, Lojek A, Ciz M, Denev P, Hrbac J (2012) Electrochemical sensing of total antioxidant capacity and polyphenol content in wine samples using amper‑ ometry online-coupled with microdialysis. J Agric Food Chem 60(32):7836–7843 9. Conclusions and future research agenda Moreover, it suggests the need to con‑ sider how automation affects the competitiveness of the wine industry in the global market and how national interests can be balanced with the need to compete in an increasingly technologically advanced marketplace. In this way, the theo‑ retical, practical and policy implications derived from this research provide answers to RQ 3. While this bibliometric and systematic literature review offers valuable insights, there are certain limitations that must be acknowledged. On the one hand, while the review effectively highlights key research themes and trends, it does not extensively explore the practical implementation and challenges of automation within the wine industry. This gap suggests an opportunity for further research, particularly through a multiple case study approach to better understand how automation impacts operational efficiency in wineries. On the other hand, the analysis in this review is based solely on the Web of Science Core Collection database. While this database is renowned for its comprehensive and high-qual‑ ity coverage, relying on a single database might result in missing significant articles that are not indexed within it. To address this, future research should aim to expand the bibliometric analysis by including a variety of databases, thereby ensuring a more comprehensive coverage of the sci‑ entific literature in this field. 2287 European Food Research and Technology (2024) 250:2273–2289 Funding Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. Funding Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. 12. Chilla C, Guillén D, Barroso C, Pérez-Bustamante J (1996) Automated on-line-solid-phase extraction—high-performance liquid chromatography-diode array detection of phenolic com‑ pounds in sherry wine. J Chromatogr A 750(1–2):209–214 Data availability Data will be provided upon request. 13. Clarivate. (2021a), "Operadores de Búsqueda", Available online: http://webofscience.help.clarivate.com/es-es/Content/ search-operators.html. (Accessed 2 Feb 2023) Declarations 14. Clarivate. (2021b), "Reglas de Búsqueda", Available online: http://webofscience.help.clarivate.com/es-es/Content/search- rules.htm. (Accessed 2 Feb 2023) Conflict of interest The authors declare no conflict of interest for this research. 15. Clarivate. (2022), "Web of Science Core Collection", Available online: https://clarivate.com/webofsciencegroup/solutions/web- ofscience-core-collection/. (Accessed 2 Feb 2023) Compliance with ethics requirements This article does not contain any studies with human or animal subjects. 16. Costa N, Llobodanin L, Castro I, Barbosa R (2019) Using sup‑ port vector machines and neural networks to classify merlot wines from South America. Inform Proc Agricult 6(2):265–278 Open Access This article is licensed under a Creative Commons Attri‑ bution 4.0 International License, which permits use, sharing, adapta‑ tion, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 17. Cuadrado M, Pérez-Juan P, de Castro M, Gómez-Nieto M (2005) A fully automated method for in real time determination of laccase activity in wines. Anal Chim Acta 553(1–2):99–104 18. Dressler M, Paunovic I (2021) Converging and diverging business model innovation in regional intersectoral coop‑ eration–exploring wine industry 4.0. Eur J Innov Manag 24(5):1625–1652 19. Ferrara C, De Feo G (2018) Life cycle assessment application to the wine sector: a critical review. Sustainability 10(2):395 20. Gajdár J, Herzog G, Etienne M (2022) Amperometric sensor for selective on-site analysis of free sulfite in wines. ACS Sensors 7(8):2209–2217 21. Gayialis S, Kechagias E, Papadopoulos G, Panayiotou N (2022) A business process reference model for the development of a wine traceability system. Sustainability 14(18):11687fi References Singh V, Singh P, Karmakar M, Leta J, Mayr P (2021) The journal coverage of Web of Science, Scopus and Dimensions: a comparative analysis. Scientometrics 126:5113–5142 61. Sinha B, Dhanalakshmi R (2022) Recent advancements and chal‑ lenges of Internet of Things in smart agriculture: a survey. Futur Gener Comput Syst 126:169–184 42. Osorio D, Pérez-Correa J, Agosin E, Cabrera M (2008) Soft-sensor for on-line estimation of ethanol concentrations in wine stills. J Food Eng 87(4):571–577f 43. Page M, McKenzie J, Bossuyt P, Boutron I, Hoffmann T, Mulrow C, Moher D (2021) The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Int J Surg 88:105906 62. Shkotova L, Bohush A, Voloshina I, Smutok O, Dzyadevych S (2019) Amperometric biosensor modified with platinum and pal‑ ladium nanoparticles for detection of lactate concentrations in wine. SN Appl Sci 1:1–8 44. Palacios F, Melo-Pinto P, Diago M, Tardaguila J (2022) Deep learn‑ ing and computer vision for assessing the number of actual berries in commercial vineyards. Biosys Eng 218:175–188 63. Signorini G, Smith M, Dami I (2021) Feasibility assessment of grape vineyards in the Midwest USA. Horticulturae 8(1):18 45. Papageorgiou M, Lambropoulou D, Morrison C, Namieśnik J, Płotka-Wasylka J (2018) Direct solid phase microextraction com‑ bined with gas chromatography–mass spectrometry for the determi‑ nation of biogenic amines in wine. Talanta 183:276–282l 64. Teodor E, Badea G, Alecu A, Calu L, Radu G (2014) Interdiscipli‑ nary study on pottery experimentally impregnated with wine. Chem Pap 68(8):1022–1029 65. Ting SL, Tse YK, Ho GTS, Chung SH, Pang G (2014) Mining logis‑ tics data to assure the quality in a sustainable food supply chain: a case in the red wine industry. Int J Prod Econ 152:200–209 46. Phansi P, Danchana K, Ferreira S, Cerdà V (2019) Multisyringe flow injection analysis (MSFIA) for the automatic determination of total iron in wines. Food Chem 277:261–266 66. Toledo J, Ruiz-Díez V, Pfusterschmied G, Schmid U, Sánchez-Rojas J (2018) Flow-through sensor based on piezoelectric MEMS resona‑ tor for the in-line monitoring of wine fermentation. Sens Actuators, B Chem 254:291–298 47. Philippe C, Krupovic M, Jaomanjaka F, Claisse O, Petrel M, Le Marrec C (2018) Bacteriophage GC1, a novel tectivirus infecting Gluconobacter cerinus, an acetic acid bacterium associated with wine-making. Viruses 10(1):39 67. Torrijos M, Moletta R (1997) Winery wastewater depollution by sequencing batch reactor. Water Sci Technol 35(1):249–257 48. References Cerutti C, Sánchez C, Sánchez R, Ardini F, Grotti M, Todolí J (2019) Determination of trace elements in undiluted wine sam‑ ples using an automatized total sample consumption system coupled to ICP-MS. J Anal At Spectrom 34(4):674–682 28. Jan M, Guarini M, Guesalaga A, Pérez-Correa J, Vargas Y (2008) Ultrasound based measurements of sugar and etha‑ nol concentrations in hydroalcoholic solutions. Food Control 19(1):31–35 p p 10. Chang J, Han G, Valverde J, Griswold N, Duque-Carrillo J, Sanchez-Sinencio E (1997) Cork quality classification system using a unified image processing and fuzzy-neural network methodology. IEEE Trans Neural Networks 8(4):964–974 29. Jiménez-Márquez F, Vázquez J, Úbeda J, Sánchez-Rojas J (2014) High-resolution low-cost optoelectronic instrument for supervis‑ ing grape must fermentation. Microsyst Technol 20:769–782 gy 11. Chapman J, Gangadoo S, Truong V, Cozzolino D (2019) Spec‑ troscopic approaches for rapid beer and wine analysis. Curr Opin Food Sci 28:67–73 30. Khalafyan A, Yakuba Y, Temerdashev Z, Kaunova A, Titarenko V (2016) Statistical-probability simulation of the organoleptic properties of grape wines. J Anal Chem 71:1138–1144 2288 European Food Research and Technology (2024) 250:2273–2289 31. Komes D, Ulrich D, Lovric T, Schippel K (2005) Isolation of white wine volatiles using different sample preparation methods. Vitis-Geilweilerhof 44(4):187 (3-ethylbenzothiazoline-6-sulfonic acid) radical cation assay in wines by sequential injection analysis. Anal Chim Acta 531(1):25–32 50. Rascón A, Azzouz A, Ballesteros E (2019) Use of semi-automated continuous solid-phase extraction and gas chromatography–mass spectrometry for the determination of polycyclic aromatic hydrocar‑ bons in alcoholic and non-alcoholic drinks from Andalucía (Spain). J Sci Food Agric 99(3):1117–1125 32. Kritsunankul O, Pramote B, Jakmunee J (2009) Flow injection on-line dialysis coupled to high performance liquid chromatogra‑ phy for the determination of some organic acids in wine. Talanta 79(4):1042–1049 ( ) 33. Lee E, Nomura N, Patil B, Yoo K (2014) Measurement of total phenolic content in wine using an automatic Folin-Ciocalteu assay method. Int J Food Sci Technol 49(11):2364–2372 51. Ravankar A, Ravankar A, Watanabe M, Hoshino Y, Rawankar A (2020) Development of a low-cost semantic monitoring system for vineyards using autonomous robots. Agriculture 10(5):182 34. Legun K, Burch K, Klerkx L (2022) Can a robot be an expert? The social meaning of skill and its expression through the prospect of autonomous AgTech. Agric Hum Values 40(2):501–517 52. Rist F, Herzog K, Mack J, Richter R, Steinhage V, Töpfer R (2018) High-precision phenotyping of grape bunch architecture using fast 3D sensor and automation. References Sensors 18(3):763 35. Luque de Castro M, Luque-García J, Mataix E (2003) Analyti‑ cal pervaporation: a key technique in the enological laboratory. J AOAC Int 86(2):394–399i 53. Ruíz C, Torrijos M, Sousbie P, Lebrato Martinez J, Moletta R, Del‑ genès J (2002) Treatment of winery wastewater by an anaerobic sequencing batch reactor. Water Sci Technol 45(10):219–224 36. Majchrzak T, Wojnowski W, Płotka-Wasylka J (2018) Classification of Polish wines by application of ultra-fast gas chromatograph. Eur Food Res Technol 244:1463–1471 54. Sá J, Ferreira L, Dieguez T, Sá J, Silva F (2021) Role of the industry 4.0 in the wine production and enotourism sectors. Advances in tourism, technology and systems: selected papers from ICOTTS20, vol 1. Springer Singapore, pp 171–180 37. Mirnaghi F, Mousavi F, Rocha S, Pawliszyn J (2013) Automated determination of phenolic compounds in wine, berry, and grape samples using 96-blade solid phase microextraction system coupled with liquid chromatography–tandem mass spectrometry. J Chroma‑ togr A 1276:12–19 55. Sández N, Calvo-López A, Vidigal S, Rangel A, Alonso-Chamarro J (2019) Automated analytical microsystem for the spectrophoto‑ metric monitoring of titratable acidity in white, rosé and red wines. Anal Chim Acta 1091:50–58 38. Mirzoian A, Ammann J (2014) Determination of oxadixyl in wines by liquid chromatography-tandem mass spectrometry: sin‑ gle-laboratory and interlaboratory validation study. J AOAC Int 97(6):1701–1706 56. Santesteban L (2019) Precision viticulture and advanced analytics. A short review. Food Chem 279:58–62 57. Santos T, de Souza L, dos Santos A, Avila S (2020) Grape detection, segmentation, and tracking using deep neural networks and three- dimensional association. Comput Electron Agricult 170:105247 39. Mylonas P, Voutos Y, Sofou A (2019) A collaborative pilot plat‑ form for data annotation and enrichment in viticulture. Information 10(4):149 58. Saurabh S, Dey K (2021) Blockchain technology adoption, archi‑ tecture, and sustainable agri-food supply chains. J Cleaner Prod 284:124731 40. Oberti R, Marchi M, Tirelli P, Calcante A, Iriti M, Baur J, Ulbrich H (2013) Selective spraying of grapevine’s diseases by a modular agricultural robot. J Agricult Eng 44(s2):1–17 59. Seng K, Ang L, Schmidtke L, Rogiers S (2018) Computer vision and machine learning for viticulture technology. IEEE Access 6:67494–67510 41. Ortiz-Martínez V, Andreo-Martinez P, Garcia-Martinez N, de Los Ríos A, Hernández-Fernández F, Quesada-Medina J (2019) Approach to biodiesel production from microalgae under super‑ critical conditions by the PRISMA method. Fuel Proc Technol 191:211–222 60. 70. Yakuba Y, Temerdashev Z, Khalafyan A (2016) Application of rang‑ ing analysis to the quality assessment of wines on a nominal scale. J Anal Chem 71:205–214 References Pinheiro C, Schäfer T, Crespo J (2005) Direct integration of per‑ vaporation as a sample preparation method for a dedicated “elec‑ tronic nose. Anal Chem 77(15):4927–4935 68. Vrochidou E, Bazinas C, Manios M, Papakostas G, Pachidis T, Kaburlasos V (2021) Machine vision for ripeness estimation in viticulture automation. Horticulturae 7(9):282 49. Pinto P, Saraiva M, Reis S, Lima J (2005) Automatic sequen‑ tial determination of the hydrogen peroxide scavenging activity and evaluation of the antioxidant potential by the 2, 2′-azinobis 69. Xiao J, Kang W, He G, Li X, Yan G (2022) Multimotor drive control method of upper-retort-robot based on machine vision. Math Probl Eng 2022:1–10 European Food Research and Technology (2024) 250:2273–2289 2289 Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. 71. Yang H, Dutkiewicz E, Urban P (2018) Kinetic study of continuous liquid-liquid extraction of wine with real-time detection. Anal Chim Acta 1034:85–91 72. Yepes-Nuñez J, Urrutia G, Romero-Garcia M, Alonso-Fernandez S (2021) The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Rev Esp Cardiol 74:790–799
https://openalex.org/W2121029487	http://www.scielo.cl/pdf/rchnat/v87/09.pdf	English	null	Arbuscular mycorrhizal fungi associated with the rhizosphere of seedlings and mature trees of Swietenia macrophylla (Magnoliophyta: Meliaceae) in Los Tuxtlas, Veracruz, Mexico	Revista chilena de historia natural	2,014	cc-by	7,980	* Correspondence: alejandras@colpos.mx 2Colegio de Postgraduados, Campus Veracruz. Km. 88.5 Carretera Federal Xalapa-Veracruz, Tepetates, Veracruz C.P. 91690, México Full list of author information is available at the end of the article Arbuscular mycorrhizal fungi associated with the rhizosphere of seedlings and mature trees of Swietenia macrophylla (Magnoliophyta: Meliaceae) in Los Tuxtlas, Veracruz, Mexico Arbuscular mycorrhizal fungi associated with the rhizosphere of seedlings and mature trees of Swietenia macrophylla (Magnoliophyta: Meliaceae) in Los Tuxtlas, Veracruz, Mexico Víctor H Rodríguez-Morelos1, Alejandra Soto-Estrada2, Jesús Pérez-Moreno3,4, Alicia Franco-Ramírez3 and Pablo Díaz-Rivera2 © 2014 Rodríguez-Morelos et al.; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 RESEARCH Open Access Abstract Background: Big-leaf mahogany (Swietenia macrophylla King) is the woody species with the highest economic value in Latin America. Currently, it is subject to intensive exploitation, diminishing its natural populations. Due to this decline, the species is a preferred species for reforestation and establishment of commercial tropical plantations. Mycorrhizal symbiosis is a biotic factor scarcely studied in the ecology of this species. Therefore, the objective of this research was to identify the diversity of arbuscular mycorrhizal fungi (AMF) species associated with the rhizosphere of seedlings and mature trees of big-leaf mahogany growing in its natural habitat, a tropical rain forest in Los Tuxtlas, Veracruz, Mexico. Soil samples from a 20-cm depth were taken from the rhizosphere of big-leaf mahogany seedlings and mature trees. Additionally, spores from the rhizosphere soil were propagated on Sorghum vulgare, isolated and identified. The percentage of AMF colonization was also evaluated. Results: Twenty-three AMF morphospecies belonging to four genera were registered: 11 corresponded to Glomus, 10 to Acaulospora, one to Gigaspora and one to Ambispora. Ambispora gerdemannii, Acaulospora spinosa, A. scrubiculata, A. foveata, Septoglomus constrictum, Claroideoglomus etunicatum, Glomus tenebrosum, Sclerocystis sinuosum, Diversispora aurantium, and Rhizophagus fasciculatus were identified to species level. We report for first time the presence of G. tenebrosum and C. etunicatum in natural areas of the humid Mexican tropics. The rhizosphere soil of the trees harbor more morphospecies than soil from seedlings (21 and 11 morphospecies, respectively). Sorghum plants inoculated with rhizosphere soil from big-leaf trees showed higher percentages of total mycorrhizal colonization, arbuscules and hyphae (P < 0.01) compared with plants inoculated with rhizosphere soil from seedlings. Conclusions: Twenty-three AMF morphospecies included in the genera Glomus, Acaulospora, Gigaspora and Ambispora were found associated with rhizosphere soil of mahogany trees growing in its natural habitat. The diversity of AMF genera and species found was around two times greater in mature trees than in seedlings. Some AMF species were only detected when trap-plants culture methods were employed, stressing the importance of this technique. This information has great potential for biotechnological application when performing reintroductions or reforestation with the tropical tree mahogany. Keywords: Arbuscular mycorrhizae; Morphospecies; Seedlings; Spores; Tropical trees Correspondence: alejandras@colpos.mx 2Colegio de Postgraduados, Campus Veracruz. Km. 88.5 Carretera Federal Xalapa-Veracruz, Tepetates, Veracruz C.P. 91690, México Full list of author information is available at the end of the article * Correspondence: alejandras@colpos.mx 2Colegio de Postgraduados, Campus Veracruz. Km. 88.5 Carretera Federal Xalapa-Veracruz, Tepetates, Veracruz C.P. 91690, México Full list of author information is available at the end of the article © 2014 Rodríguez-Morelos et al.; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. Methods Study site The sampling area was a fragment of tropical rainforest with seedlings and trees of S. macrophylla established nat- urally. The study area is located in the town of Maxacapan, municipality of Catemaco, within the region of Los Tuxtlas, Veracruz, Mexico (18° 23' N, 95° 07' W; average elevation of 385 masl). The soil is an ultisol with a light brown color, a sandy-loamy texture and abundant organic matter in the first 10 to 15 cm of soil depth. The vegetation area is disturbed from its original composition due to selective timber harvesting, and is generally surrounded by pastures and coffee plantations. Even though it has a great potential for practical appli- cation, one of the poorly studied biotic factors of this species is its relationship with arbuscular mycorrhizal fungi (AMF), especially in their natural distribution areas. Different studies indicate a clear colonization of vesicles and arbuscules in the secondary roots of seed- ling and mahogany trees in natural areas (Herrera and Ferrer 1980), in young plantations (Noldt and Bauch 2001) and agroforestry systems and tropical forests of Southeast Asia where mahogany has been introduced for cultivation (Dhar and Mridha 2006; Shi et al. 2006; Mridha and Dhar 2007). However, in general terms, the identity of AMF associated with mahogany in natural areas, has received little attention. It is known that most tropical forest species are associated with AMF and have a wide range of dependence on them, depending on suc- cessional stages and soil fertility (Janos 1980a; Le Tacon et al. 1987). Also, it has been shown that pioneer plant species in tropical areas are more dependent on AMF, in soils poor in minerals, than climax plant species (Zangaro et al. 2000). Recently, studies on arbuscular mycorrhiza have increased due to the little knowledge we have regard- ing the diversity and potential of AMF in association with tropical plants. Studies related to the production of mycorrhizal inoculum for the production of tropical plant species are emerging; consequently, despite its paramount importance, currently there is only a limited use of these inocula in reforestation programs on a large scale (Ramos- Zapata and Guadarrama 2004). In Mexico, there is little knowledge of AMF richness and its role in the ecological The climate is warm-humid with an average annual temperature of 27°C (Pérez-Rojas et al. 2000). Methods Study site The average annual rainfall in the region is 4,964 mm with a marked dry season from March to May (Soto and Gama 1997), rain during the summer and abundant rain in autumn (Pérez-Rojas et al. 2000). The Los Tuxtlas region repre- sents the northern limit of the distribution of tropical rainforest in the Americas and the last relic of this type of vegetation in the state of Veracruz (Dirzo and Miranda 1991). The vegetation of the tropical rain forest in the region has lost 84% of its original cover due to human activity causing a high degree of fragmentation (Dirzo and Mc 1992). Background processes of tropical land areas that influence the develop- ment of plants with which they are associated (Guadarrama- Chávez et al. 2007). Most research on AMF in Mexico has been developed in agricultural areas and in many cases, has focused on determining plant responses to symbiosis, regardless of the origin or identity of the AMF (Varela and Trejo 2001). However, it is important to note that the current perspective is that the AMF communities differentially influence the growth and establishment of tree seedlings in tropical ecosystems, in- fluencing the composition of plant communities (Kiers et al. 2000; Husband et al. 2002). In this context, the objective of the present investigation was to identify the species of AMF associated with the rhizosphere of seedlings and mature mahogany trees in a fragment of tropical rain- forest of Los Tuxtlas, Veracruz, Mexico. We also evaluated the mycorrhizal inoculum potential of rhizosphere soil from such seedlings and mahogany trees. g The bigleaf mahogany (Swietenia macrophylla King) is the timber species of greatest economic value in Latin America and is currently the main source of genuine mahogany on the wood market (OIMT 2004). Its nat- ural distribution includes fragmented populations from southeastern Mexico along the Atlantic coast of Central America and northern South America, occupying a large geographical arc south of the Amazon, between Brazil, Colombia, Peru and Bolivia (Lamb 1966; Snook 1996). Mahogany is a tropical species that demands much light for growth (Mayhew and Newton 1998); therefore, its nat- ural regeneration is associated with significant disturbance to sites produced by fires or hurricanes (Snook 1996). This forest tree species is subjected to intense levels of exploit- ation and international trade, showing therefore a decline in its population size and increased population fragmenta- tion in several areas of its natural distribution (Navarro and Hernández 2004; OIMT 2004). In Mexico, over the past three decades, a loss of 76% of the tropical evergreen forest areas containing mahogany trees has been reported (Calvo et al. 2000). Currently, mahogany is a preferred species for reforestation and establishment of commercial plantations in the tropics. Page 2 of 10 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Statistical analysis F h b For the number of spores from the field soil and colonization variables, ANOVA analyses were per- formed using a linear mixed effects model, considering the state of mahogany development (seedlings and adults) as fixed effects and the individual specimens as a random effect nested in developmental stage, with three replicates per specimen. Subsequently, the test for dif- ferences among means (pdiff, P < 0.05) using the t-statistic was applied. The analysis was performed using the GLM procedure in SAS (SAS Institute Inc 2009). The statistical model used was: Y ijk ¼ μþEDi þ Id ED ð Þj ið Þ þ εijk εijk ≈NII; 0; σ2ε Y ijk ¼ μþEDi þ Id ED ð Þj ið Þ þ εijk εijk ≈NII; 0; σ2ε where: Yijk = response variable, EDi = ith stage of develop- ment, Id (ED) j(i) = jth individual nested in the ith stage of development, and €ijk = residual error. The percentages of mycorrhizal colonization and colonization of endophytic fungi were transformed to square-roots to meet the as- sumptions of normality for ANOVA. Identification of AMF species The extraction and counting of spores were carried out using 100 g of rhizosphere soil collected from both, the field and trap-plants and the method of wet sieving and decanting established by Gerdemann and Nicolson (1963). Spores were extracted and separated into morphotypes by color, shape and size. Subsequently, permanent prepara- tions were made with alcohol and polyvinyl-glycerol (PVLG) and PVLG with Melzer’s solution according to Schenck and Pérez (1990). The isolated spores were mea- sured under a phase contrast microscope. Characteristics such as number of spore layers, ornamentation of outer layers, shape and type of hyphal attachments and Determination of mycorhizal colonization After six months of establishment, the sorghum trap-plants were harvested and the roots were examined to determine the formation of AMF structures, quantify the colonization percentage, and estimate the mycorrhizal inoculum po- tential for the rhizosphere soil of seedlings and mature trees. Evaluation of root mycorrhizal colonization was performed by clearing and staining the roots (Phillips and Hayman 1970), and quantifying colonization according to McGonigle et al. (1990) by determining the percentage of arbuscules, vesicles and hyphae in the roots of sorghum. Additionally, the percentage of endophytic fungi was de- termined in the sorghum roots. In order to detect additional AMF species to those found at the time of soil collection, which could only be expressed in soil samples as somatic phases, and to deter- mine the mycorrhizal inoculum potential, a trap-plant method was applied using sorghum (Sorghum vulgare L.). This species was used because of its high germination per- centage, early susceptibility to mycorrhizal colonization and abundant root production. It is important to note that the establishment of trap-plants allows: i) to corroborate the identification of species based on spores obtained in the field, which are often damaged, causing difficulty in accurate identification, and ii) to obtain sporulation of species that do not sporulate under natural conditions (Guadarrama et al. 2014). The methodology first involved the sterilization of the loamy-sandy soil (that was poor in phosphorus) with water vapor at 100°C for eight hours in an autoclave. The soil was then placed in 2 L pots, filling them to 75% capacity. On top of this soil was placed a uni- form layer of 250 g of rhizosphere soil, resulting in a total of 10 pots corresponding to the number of samples. In each pot, a uniform layer of sorghum seed was sown, watered and maintained under a shade mesh for six months at an average temperature and relative humidity of 26°C and 80%, respectively. During this time, frequent irrigation with tap water was performed depending on the needs of the plants. In addition, during the last three months, all potted plants were watered every 15 days with 200 ml of Long Ashton nutrient solution modified by Hewitt (1966). After six months, the irrigations were suspended and the plants were cut from the stem base to favor spore production, following the methods described by Carreón-Abud et al. (2013); Her- nández-Cuevas and García-Sánchez (2008). Collection of rhizosphere soil and establishment of trap-plants Sampling was conducted in June 2008 and consisted of collecting rhizosphere soil surrounding five seedlings and five mature trees of S. macrophylla. The seedlings had an average basal diameter (±SD) of 4.5 ± 1.5 cm and a mean height (±SD) of 35.6 ± 8.5 cm, while trees had an average basal diameter (±SD) of 1.2 ± 0.5 m and an average height Page 3 of 10 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 (±SD) of 19.5 ± 4.5 m. To collect soil, organic matter was first removed from around the plants and a shovel was used to remove the roots of mahogany trees and to collect about two kg of rhizosphere soil from each seedling or tree. Soil samples were placed directly into plastic bags, which were placed in coolers for transport to the Laboratory at the Colegio de Postgraduados and stored at 6°C during two months before analysis. sporogenous cells, and the wall layer reactions to Melzer’s reagent were also recorded. Species identification was made according to species descriptions provided by the International Culture Collection of Vesicular Arbuscular Mycorrhizal Fungi (INVAM 2014) following the classifica- tion of Redecker et al. (2013). Colonization and spore abundance Colonization and spore abundance registered corresponding to the genera Glomus and Acaulospora; while from the soil rhizosphere of trees, 21 morphotypes were recorded from four genera (Glo- mus, Acaulospora, Gigaspora and Ambispora). Nine morphotypes (A. scrobiculata, A. spinosa, Acaulospora sp. 2, Acaulospora sp. 5, Acaulospora sp. 6, D. auran- tium, C. etunicatum, R. fasciculatus and Glomus sp. 3) were common in both plant stages. In contrast, A. ger- demannii, S. constrictum, S. sinuosum, G. tenebrosum, Glomus sp. 1, Glomus sp. 2, Glomus sp. 5, and Giga- spora sp. were found exclusively in the rhizosphere of mature trees. The morphospecies Acaulospora sp. 4 and Acaulospora sp. 7 were recorded specifically asso- ciated with seedlings. There was a greater diversity of genera and species of AMF associated with trees com- pared to seedlings. The percentage incidence in trees and seedlings and their morphological characteristics are shown in Figures 1 and 2, respectively. The variables evaluated for sorghum showed significant differences in relation to the type of rhizosphere soil used as a source of inoculum (Table 2). The rhizosphere soil from S. macrophylla trees originated more spores (152.80 ± 3.2 SEM) than that from seedlings (87.3 ± 3.2 SEM) (P < 0.01). Similarly, the number of spores was higher (P < 0.01) from trap-plants with rhizosphere soil from trees (295 ± 4.4 SEM) than with rhizosphere soil from seedlings (132.3 ± 4.4 SEM) (Table 2). Sorghum plants inoculated with tree soil had higher percentages of total mycorrhizal colonization, arbuscules and hyphae (53.3 ± 2.0 SEM, 26.3 ± 1.9 SEM and 26.5 ± 1.4 SEM, re- spectively), compared with that inoculated with seedling soil (P < 0.01). Percent colonization by vesicles (11.3 ± 1.0 SEM) and by endophytic fungi (6.1 ± 0.9 SEM) did not differ significantly (P > 0.05). The use of sorghum as a trap-plant increased the number of spores by 93% and Table 1 Morphospecies of arbuscular mycorrhizal fungi associated with the rhizosphere of seedlings and adult trees of mahogany in a tropical rainforest in Los Tuxtlas, Veracruz, Mexico Order/family Species of AMF Associated with Seedlings Trees Ambisporaceae Ambispora gerdemannii * Diversisporaceae Diversispora aurantium Diversispora aurantium Acaulosporaceae Acaulospora spinosa Acaulospora spinosa Acaulospora scrobiculata Acaulospora scrobiculata Acaulospora foveata Acaulospora sp. 1 Acaulospora sp. 2 Acaulospora sp. 2 Acaulospora sp. 4 Acaulospora sp. 3 Acaulospora sp. 5 Acaulospora sp. 5 Acaulospora sp. 6 Acaulospora sp. 6 Acaulospora sp. * Detected only in trap-plant cultures. ** Detected only in natural soil. Remaining morphotypes were detected in both trap-plant cultures and natural soil. Species nomenclature follows Redecker et al. (2013). Identification of AMF species A total of 23 morphotypes of AMF corresponding to three orders and four families were recorded from the rhizosphere of mahogany seedlings and trees (Table 1). Ten of these morphotypes were identified to species level. From the 23 morphotypes, a total of 11 species belong to the genus Glomus, 10 to the genus Acaulospora, and one each to the genera Gigaspora and Ambispora. In the rhizosphere soil of seedlings, 11 morphotypes were Page 4 of 10 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Colonization and spore abundance Glomus sp.3 Colonization and spore abundance 7 Gigasporaceae Gigaspora sp.* Glomerales Claroideoglomus etunicatum Claroideoglomus etunicatum Claroideoglomeraceae Glomeraceae Sclerocystis sinuosum Rhizophagus fasciculatus Glomus tenebrosum Septoglomus constrictum Glomus sp.1 Glomus sp.2 Glomus sp.3 Glomus sp.3 Glomus sp.4 Glomus sp.5 * Detected only in trap-plant cultures. ** Detected only in natural soil. Remaining morphotypes were detected in both trap-plant cultures and natural soil. Species nomenclature follows Redecker et al. (2013). s of arbuscular mycorrhizal fungi associated with the rhizosphere of seedlings and adult trees of al rainforest in Los Tuxtlas, Veracruz, Mexico Gigasporaceae Glomerales Claroideoglomeraceae Glomeraceae * Detected only in trap-plant cultures. ** Detected only in natural soil. Remaining morphotypes were detected in both trap-plant cultures and natural soil. Species nomenclature follows Redecker et al. (2013). Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Page 5 of 10 Figure 1 Percentage distribution of the arbuscular mycorrhizal fungi genera associated with the rhizosphere of seedlings (A) and mature trees (B) of Swietenia macrophylla in a tropical rainforest in Los Tuxtlas, Veracruz, Mexico. Figure 1 Percentage distribution of the arbuscular mycorrhizal fungi genera associated with the rhizosphere of seedlings (A) and mature trees (B) of Swietenia macrophylla in a tropical rainforest in Los Tuxtlas, Veracruz, Mexico. 51% compared to soil collected in the field from mahog- any trees and seedlings, respectively. and only a small proportion of species corresponded to the genera Acaulospora and Scutellospora. The results also contrast with those of Shi et al. (2006) who reported that Glomus was the dominant genus in the rhizosphere of 14 genera of Meliaceae (including 2 species of Sweitenia) in a tropical forest in China, and to a lesser extent the genera Acaulospora, Gigaspora, Scutellospora and Entrophospora. These differences in AMF community composition could be linked to geographic environmental variations or the plant genotypes involved. Discussion Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Page 7 of 10 Page 7 of 10 Table 2 Mycorrhizal structures on sorghum plants inoculated with rhizosphere soil from seedlings and mature mahogany trees Original values Transformed values Variables\development stage Trees Seedlings Trees Seedlings Spore number in sorghum 295.0 ± 4.40a 132.3 ± 4.39b Total colonization 53.3 ± 2.01a 41.5 ± 2.01b 51.4 ± 0.03a 40.6 ± 0.03b % Arbuscules 26.3 ± 1.88a 17.6 ± 1.88b 24.6 ± 0.06a 14.1 ± 0.06b % Vesicles 11.3 ± 1.01a 13.23 ± 1.01a 10.6 ± 0.02a 11.8 ± 0.02a % Hyphae 26.5 ± 1.40a 14.6 ± 1.40b 22.6 ± 0.02a 14.21 ± 0.02b % Endophytes 6.09 ± 0.93a 5.5 ± 0.93a 5.2 ± 0.05a 4.12 ± 0.05a Spore number in natural soil 152.8 ± 3.23a 87.3 ± 3.23b Within rows, different letters indicate significant differences (P < 0.01). Values are means ± standard error of the mean. Table 2 Mycorrhizal structures on sorghum plants inoculated with rhizosphere soil from seedlings and mature mahogany trees Table 2 Mycorrhizal structures on sorghum plants inoculated with rhizosphere soil from se mahogany trees tures on sorghum plants inoculated with rhizosphere soil from seedlings and mature trees have been longer periods of time in natural ecosys- tems, the possibility to be colonized by a more diverse community of AMF propagules can be increased. Simi- larly, than in our case Wubet et al. (2009) also found AMF species associated with both mature tropical trees and seedlings, while other species were unique to only one of the two age categories. (Violi et al. 2008) and grassland (Franco-Ramírez et al. 2007; Ramírez-Gerardo et al. 1997). Also, the species re- ported in this paper have been found in Mexico associated with various crops such as maize (Guadarrama-Chávez et al. 2007), sugarcane, coffee and bananas (Varela and Trejo 2001). This demonstrates, in general, enormous eco- logical flexibility and lack of specificity of AMF, although it has also been shown a significant functional variability among fungal species belonging to this group. The AMF species composition thus could alter plant community structure (Smith and Read 2008; Klironomos 2000). g g The production of AMF spores in tropical forests var- ies according to climatic seasonality during the year (Allen et al. 1998; Guadarrama and Álvarez-Sánchez 1999; Picone 2000; Lovelock et al. 2003; Ramos-Zapata et al. Discussion 2006; Vargas et al. 2010). Recently, Guadarrama et al. (2014) demonstrated that seasonality has a strong influence on AMF diversity in subtropical dry forests. Therefore, the additional use of trap-plants allows the evaluation of the mycorrhizal inoculum potential of soil (Guadarrama et al. 2014), thus being useful in the identi- fication of AMF species that do not produce spores dur- ing the period in which samples are collected from the field (Stürmer 2004). In our study, Ambispora gerdeman- nii and Gigaspora sp. were not found in the natural soil collected, but they were recorded when trap-plant cul- tures were used. However, it is important to consider that trap-plant cultures do not necessarily show the whole composition of AMF communities, because the species used as host plants can affect sporulation of AMF communities (Bever et al. 1996). For example, spe- cies such as G. sinuosum and G. clavisporum do not pro- duce spores when using the trap-plant Sorghum vulgare (Guadarrama-Chávez et al. 2007). Our results therefore suggest that in order to have a more complete picture of the AMF communities associated with tropical trees, it is important to use both methodologies, collection of AMF from rizosphere soil and cultivation using trap- plants. Dhar and Mridha (2012) showed colonization percentages for hyphae and vesicles of 60 and 40%, re- spectively, and the percentage of arbuscules of 19% for mahogany plantations in Bangladesh. A lower potential The average number of spores recorded from trees in this study is similar to that found by Mridha and Dhar (2007) in agroforestry systems (141 spores/100 g of soil), but lower than that reported by Dhar and Mridha (2006) and Shi et al. (2006) for mahogany trees in tropical for- ests of Southeast Asia (440 and 346 spores/100 g of soil, respectively). The number of spores produced in inocu- lated sorghum plants was higher than that found in the soil collected from the rhizosphere of trees (93.0% higher) and seedlings (51.0% higher) in the field. This difference could be explained by the fact that there are AMF species present exclusively as somatic propagules in the field that could only be detected by the trap-plant method (Guadarrama et al. 2014). Husband et al. (2002) found that the age of the host can determine the composition of AMF populations in tropical ecosystems. Discussion AMF morphotypes found in the rhizosphere from both seedlings and mature trees of S. macrophylla were identi- fied as primarily belonging to the genera Glomus and Acaulospora. Additionally, in the case of mature trees spe- cies were identified as belonging to the genera Ambispora and Gigaspora. These results differ from those of Dhar and Mridha (2006) who found species from the genera Glomus and Gigaspora, but also species belonging to Scu- tellospora and Entrophospora in the rhizosphere of ma- hogany trees in a natural forest in Bangladesh. Meanwhile, Mridha and Dhar (2007) found that in mahogany trees in agroforestry systems established in Bangladesh, members of the genus Glomus were the dominant taxonomic group The AMF species found in this study have been reported to be associated with a variety of hosts and di- verse vegetation types in Mexico, such as tropical rainforest (Varela-Fregoso et al. 2008; Guadarrama and Álvarez-Sánchez 1999), tropical dry forest (Gavito et al. 2008), deciduous tropical dry forest (Guadarrama-Chávez et al. 2007; Allen et al. 1998), mountain cloud forest Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Page 6 of 10 Figure 2 Micromorphology of arbuscular mycorrhizal fungi morphotypes associated with the rhizosphere of seedlings and mature trees of big-leaf mahogany. a) Ambispora gerdemannii, b) Acaulospora sp. 1, c) Acaulospora sp. 2, d) Acaulospora sp. 3, e) Acaulospora sp. 4, f) Acaulospora sp. 5, g) Acaulospora sp. 6, h) Acaulospora sp. 7, i) A. foveata, j) Gigaspora sp., k) Diversispora aurantium, l) Claroideoglomus etunicatum, m) S. sinuosum, n) R. fasciculatus, o) G. tenebrosum, p) Glomus sp. 1, q) Glomus sp. 2, r) Glomus sp. 3, s) Glomus sp. 4, t) Glomus sp. 5. Figure 2 Micromorphology of arbuscular mycorrhizal fungi morphotypes associated with the rhizosphere of seedlings and mature trees of big-leaf mahogany. a) Ambispora gerdemannii, b) Acaulospora sp. 1, c) Acaulospora sp. 2, d) Acaulospora sp. 3, e) Acaulospora sp. 4, f) Acaulospora sp. 5, g) Acaulospora sp. 6, h) Acaulospora sp. 7, i) A. foveata, j) Gigaspora sp., k) Diversispora aurantium, l) Claroideoglomus etunicatum, m) S. sinuosum, n) R. fasciculatus, o) G. tenebrosum, p) Glomus sp. 1, q) Glomus sp. 2, r) Glomus sp. 3, s) Glomus sp. 4, t) Glomus sp. 5. Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 Page 7 of 10 http://www.revchilhistnat.com/content/87/1/9 Rodríguez-Morelos et al. Acknowledgements We thank Sir David J. Read, Animal and Plant Sciences Department, University of Sheffield, England, UK, for his critical observations, which improved the manuscript. Authors’ information VHRM, Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias, Campo Experimental Las Huastecas. Km. 55 Carretera Federal Tampico- Mante, Villa Cuauhtémoc, Tamaulipas, México. C.P. 89610. ASE, Colegio de Postgraduados, Campus Veracruz. Km. 88.5 Carretera Federal Xalapa-Veracruz, Tepetates, Veracruz, México. C.P. 91690. JPM, Colegio de Postgraduados, Microbiología-Edafología, Campus Montecillo. Km. 36.5 Carretera-Federal México-Texcoco, Montecillo, Estado de México, México. C.P. 56230 Animal and Plant Science Department, University of Sheffield, Sheffield S10 2TN, England, UK. AFR, Colegio de Postgraduados, Microbiología-Edafología, Campus Montecillo. Km. 36.5 Carretera-Federal México-Texcoco, Montecillo, Estado de México, México. C.P. 56230. PDR, Colegio de Postgraduados, Campus Veracruz. Km. 88.5 Carretera Federal Xalapa-Veracruz, Tepetates, Veracruz, México. C.P. 91690. Our results confirm the high diversity of AMF associ- ated with the rhizosphere of S. macrophylla, similar to that reported in previous studies in Los Tuxtlas, Mexico. Varela-Fregoso et al. (2008) cataloged the species of this tropical region and recorded 60 AMF species. There is a relationship between the number and composition of spe- cies in the rhizosphere soil and the stage of development of S. macrophylla. In tropical ecosystems there is a great diversity of AMF, but studies of AMF in these ecosystems are scarce compared to temperate ecosystems or agroeco- systems; additionally the characteristics of AMF found in tropical zones do not fit species previously described in the literature (Lovera and Cuenca 2007). Positive results in terms of growth have been reported by Huante et al. (2012) in a species similar to mahogany, Swietenia humi- lis, following inoculation with AMF. Knowledge of the structure and function of AMF communities is an import- ant factor to be considered in the management of this bi- otic resource so that it can be integrated into future environmental restoration activities, especially in degraded tropical regions where the availability of nutrients such as Authors’ contributions VHRM d i d h VHRM co-designed the study, collected and analyzed data, and drafted the manuscript. ASE co-designed the study, co-directed the research, and revised manuscript. JPM co-directed the research, and revised the manuscript. AFR identified all the arbuscular mycorrhizal fungi species reported en this paper. PDR contributed in the experimental design and the analysis of data. All authors read and approved the final manuscript. Competing interests Th h f hi Competing interests The authors of this paper declare that we have no competing interests. Discussion By using molecular techniques in the extraction of fungal DNA from the colonized roots of Tetragastris panamensis (Engl.) Kuntse, these authors observed that when the age of seedlings of tropical trees increases the diversity of AMF declines. Similarly, Kumar et al. (2009) found higher colonization percent- ages and densities of AMF spores in young plants com- pared with old trees of maidenhair (Ginkgo biloba L.). Our results showed the opposite trend, finding more AMF species in the rhizosphere of mature trees than in seedlings, which can be explained by the fact that when Page 8 of 10 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 for mycorrhizal colonization of rhizosphere soil from seedlings in comparison to mature trees (expressed as lower percentage of total mycorrhizal colonization, arbus- cules and AMF hyphae) was recorded in the present work. phosphorus is a limiting factor in plant growth. Thus, AMF is a key factor in the growth and survival of plants in early successional stages of plant communities (Janos 1980b, 1996; Cuenca et al. 1998). Therefore, knowing the diversity of AMF associated with different growth stages of plant species is vital for maintaining the diversity and sustainability of tropical ecosystems. for mycorrhizal colonization of rhizosphere soil from seedlings in comparison to mature trees (expressed as lower percentage of total mycorrhizal colonization, arbus- cules and AMF hyphae) was recorded in the present work. In natural ecosystems, a great diversity of AMF colonize plants simultaneously (Vandenkoornhuyse et al. 2002), but generally have little taxonomic specificity to associate with plant roots (Smith and Read 2008). However, it is import- ant to consider that tree species from tropical forests exhibit differential responses and compatibility in growth in relation to AMF species (Pouyu-Rojas et al. 2006) and AMF soil communities (Fischer et al. 1994; Kiers et al. 2000; Allen et al. 2003; 2005). Other evidence indicates that tree identity and the composition of the plant community determine the composition of AMF in tropical ecosystems (Lovelock et al. 2003; Lovelock and Ewel 2005). Conclusions h In this research, 23 AMF morphospecies belonging to the genera Glomus, Acaulospora, Gigaspora and Ambispora were found associated with rhizosphere soil of mahogany trees growing in its natural habitat. The diversity of AMF genera and species found was around two times greater in mature trees than in seedlings. Some AMF species were only detected when trap-plants culture methods were employed, stressing the importance of this technique. This information has great potential for application and should be considered when performing reintroductions or reforestation with the native tropical mahogany tree. Anthropogenic disturbances such as loss of vegetation through land use change can reduce AMF diversity in tropical (Cuenca et al. 1998) and subtropical (Guadarrama et al. 2014) ecosystems, and also affect its composition (Gavito et al. 2008). In this regard, several studies have shown that the genera Gigaspora and Scutellospora are more susceptible to disturbances in plant communities (Guadarrama-Chávez et al. 2007; Lovera and Cuenca 2007). The loss of biodiversity in the soil is a little-studied topic that requires more attention because AMF species can influence the diversity and productivity of plant com- munities in natural ecosystems (van der Heijden et al. 1998). The need for using native AMF in restoration activ- ities in degraded tropical areas because of its potential for adapting to the environmental conditions of a particular site has been previously emphasized (Allen et al. 2005; Cuenca et al. 2007; Guadarrama-Chávez et al. 2007). Received: 12 April 2014 Accepted: 23 June 2014 References Huante P, Ceccon E, Orozco-Segovia A, Sánchez-Coronado ME, Acosta I, Rincón E (2012) The role of arbuscular mycorrhizal fungi on the early stage restoration of seasonally dry tropical forest in Chamela, México. Revista Arvore 36:279–289 Allen EB, Rincón E, Allen MF, Pérez-Jiménez A, Huante P (1998) Disturbance and seasonal dynamics of mycorrhizae in a tropical deciduous forest in Mexico. Biotropica 30:261–274 Husband R, Herre EA, Young JPW (2002) Temporal variation in arbuscular mycorrhizal communities colonizing seedlings in a tropical forest. FEMS Microbial Ecol 42:131–136 Allen EB, Allen MF, Egerton-Warburton L, Corkidi L, Gómez-Pompa A (2003) Impacts of early-and late-seral mycorrhizae during restoration in seasonal tropical forest, México. Ecol Appl 13:1701–1717 INVAM (2014) International Culture Collection of (Vesicular) Arbuscular Mycorrhizal Fungi. West Virginia University, Morgantown, West Virginia. URL: http://invam.wvu.edu/the-fungi/species-descriptions (accessed March26 Janos DP (1980a) Mycorrhizae influence tropical succession. Biotropica 12:56–64 Janos DP (1980b) Vesicular arbuscular mycorrhizae affect lowland tropical rain forest plant growth. Ecology 61:151–162 Janos DP (1996) Mycorrhizas, succession and the rehabilitation of deforested lands in the humid tropics. In: Frankland JC, Magan N, Gadd GM (ed) Fungi and Environmental Change: 129–162. Cambridge University Press, Cambridge, England Ki ET L l k CE H EA (2000) Diff i l ff f i l b l INVAM (2014) International Culture Collection of (Vesicular) Arbuscular Mycorrhizal Fungi. West Virginia University, Morgantown, West Virginia. URL: http://invam.wvu.edu/the-fungi/species-descriptions (accessed March26 Janos DP (1980a) Mycorrhizae influence tropical succession. Biotropica 12:56–64 Janos DP (1980b) Vesicular arbuscular mycorrhizae affect lowland tropical rain forest plant growth. Ecology 61:151–162 Janos DP (1996) Mycorrhizas, succession and the rehabilitation of deforested lands in the humid tropics. In: Frankland JC, Magan N, Gadd GM (ed) Fungi and Environmental Change: 129–162. Cambridge University Press, Cambridge, England Allen MF, Allen EB, Gómez-Pompa A (2005) Effects of Mycorrhizae and Nontarget Organisms on Restoration of a Seasonal Tropical Forest in Quintana Roo, Mexico: Factors Limiting Tree Establishment. Restauration Ecol 13:325–333 Bever JD, Morton JB, Antobovics J, Schultz P (1996) Host dependent sporulation and species diversity of arbuscular mycorrhizal fungi in a mown grassland. J Ecol 84:71–82 Janos DP (1996) Mycorrhizas, succession and the rehabilitation of deforested lands in the humid tropics. In: Frankland JC, Magan N, Gadd GM (ed) Fungi and Environmental Change: 129–162. Cambridge University Press, Cambridge, England Calvo J, Bolaños R, Watson V, Jiménez H (2000) Diagnóstico de la caoba (Swietenia macrophylla King) en Mesoamérica: Visión general (Evaluation of Mahogany in Mesoamerica: General Overview). References Interciencia 16:240–247 Lovelock CE, Andersen K, Morton JM (2003) Host tree and environmental control on arbuscular mycorrhizal spore communities in tropical forests. Oecologia 135:268–279 Dirzo R, Mc G (1992) Rates of deforestation in Los Tuxtlas a neotropical area in south east Mexico. Conserv Biol 6:84–90 Lovera M, Cuenca G (2007) Diversidad de hongos micorrízicos arbusculares (HMA) y potencial micorrízico del suelo de una sabana natural y una sabana perturbada de la gran sabana, Venezuela. Interciencia 32:108–114 Fischer CR, Janos DP, Perry DA, Linderman RG, Sollins P (1994) Mycorrhiza inoculums potentials in tropical secondary succession. Biotropica 26:369–377 Mayhew JE, Newton AC (1998) The Silviculture of Mahogany. CABI Publishing, Wallingford, UK Franco-Ramírez A, Ferrera-Cerrato R, Varela-Fregoso L, Pérez-Moreno J, Alarcón A (2007) Arbuscular mycorrhizal fungi in chronically petroleum contaminated soils in Mexico and the effects of petroleum hydrocarbons on spore germination. J Basic Microbiol 47:378–383 McGonigle TP, Miller MH, Evans DG, Fairchild GL, Swan JA (1990) A new method which gives an objective measure of colonization of roots by vesicular- arbuscular mycorrhizal fungi. New Phytol 115:495–501 Gavito ME, Pérez-Castillo D, González-Monterrubio CF, Vieyra-Hernández T, Martínez-Trujillo M (2008) High compatibility between arbuscular mycorrhizal fungal communities and seedlings of different land use types in a tropical dry ecosystem. Mycorrhiza 19:47–60 Mridha M, Dhar PP (2007) Biodiversity of arbuscular mycorrhizal colonization and spore population in different agroforestry trees and crop species growing in Dinajpur, Bangladesh. J For Res 18:91–96 Navarro C, Hernández G (2004) Progeny test analysis and population differentiation of Mesoamerican Mahogany (Swietenia macrophylla). Agronomía Costarric 28:37–51 Gerdemann JW, Nicolson TH (1963) Spores of mycorrhizal Endogone species extrated from soil by wet sieving and decanting. Transations Br Mycol Soc 46:235–244 Noldt G, Bauch J (2001) Colonization of fine roots of mahogany (Swietenia macrophylla King) by vesicular-arbuscular mycorrhizal fungi under plantation conditions in Central Amazon. J Appl Bot 75:168–172 Noldt G, Bauch J (2001) Colonization of fine roots of mahogany (Swietenia macrophylla King) by vesicular-arbuscular mycorrhizal fungi under plantation conditions in Central Amazon. J Appl Bot 75:168–172 Guadarrama P, Álvarez-Sánchez FJ (1999) Abundance of arbuscular mycorrhizal fungi spores in different environments in a tropical rain forest, Veracruz, Mexico. Mycorrhiza 8:267–270 OIMT (2004) Racionalizando el comercio de caoba. Informe del taller sobre el desarrollo de capacidad para la aplicación del listado de la caoba en el Apéndice II de la CITES. Organización Internacional de las Maderas Tropicales. References Tropical Science Center / PROARCA / CAPAS, San José, Costa Rica Kiers ET, Lovelock CE, Herre EA (2000) Differential effects of tropical arbuscular mycorrhizal fungal inocula on root colonization and tree seedling grow: implications for tropical forest diversity. Ecol Lett 3:106–113 Carreón-Abud Y, Jerónimo-Treviño E, Beltrán-Nambo MA, Martínez-Trujillo M, Trejo-Aguilar D, Gavito ME (2013) Aislamiento y propagación de cultivos puros de hongos micorrízicos arbusculares provenientes de huertas de aguacate con diferente manejo agrícola por la técnica de minirizotrón. Revista Mexicana Micología 37:29–39 Klironomos JN (2000) Host-specificity and functional diversity among arbuscular mycorrhizal fungi. In: Bell CR, Brylinsky M, Johnson-Green P (ed) Microbial Biosystems: New Frontiers: 845–851. Atlantic Canada Society for Microbial Ecology, Halifax, Canada Cuenca G, Cáceres A, Oirdobro G, Hasmy Z, Urdaneta C (2007) Las micorrizas arbusculares como alternativa para una agricultura sustentable en áreas tropicales. Interciencia 32:23–29 gy Kumar A, Singh S, Pandey A (2009) General microflora, arbuscular mycorrhizal colonization and occurrence of endophytes in the rhizosphere of two age groups of Ginkgo biloba L. of Indian Central Himalaya. Indian J. Microbiol 49:134–141 Lamb FB (1966) Mahogany of tropical America: Its ecology and management. University of Michigan Press, Ann Arbor, MI Kumar A, Singh S, Pandey A (2009) General microflora, arbuscular mycorrhizal colonization and occurrence of endophytes in the rhizosphere of two age groups of Ginkgo biloba L. of Indian Central Himalaya. Indian J. Microbiol 49:134–141 Cuenca G, De Andrade Z, Escalante G (1998) Diversity of Glomalean spores from natural, disturbed and revegetated communities growing on nutrient-poor tropical soils. Soil Biol Biochem 30:711–719 Lamb FB (1966) Mahogany of tropical America: Its e University of Michigan Press, Ann Arbor, MI Lamb FB (1966) Mahogany of tropical America: Its ecology and managem University of Michigan Press, Ann Arbor, MI Dhar PP, Mridha M (2006) Biodiversity of arbuscular mycorrhizal fungi in different trees of madhupur forest, Bangladesh. J For Res 17:201–205 Le Tacon F, Garbaye J, Carr G (1987) The use of micorrhizas in temperature and tropical forest. Symbiosis 3:179–206 Dhar PP, Mridha M (2012) Arbuscular mycorrhizal associations in different forest tree species of Hazarikhil forest of Chittagong, Bangladesh. J For Res 23:115–122 Lovelock CE, Ewel JJ (2005) Links between tree species, symbiotic fungal diversity and ecosystem functioning in simplified tropical ecosystems. New Phytol 167:219–228 Dirzo R, Miranda A (1991) El limite boreal de la selva tropical húmeda en el continente americano: contracción de la vegetación y solución de una controversia. Author details 1 1Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias, Campo Experimental Las Huastecas. Km. 55 Carretera Federal Tampico-Mante, Tamaulipas, Villa Cuauhtémoc C.P. 89610, México. 2Colegio de Postgraduados, Campus Veracruz. Km. 88.5 Carretera Federal Xalapa-Veracruz, Tepetates, Veracruz C.P. 91690, México. 3Colegio de Postgraduados, Microbiología-Edafología, Campus Montecillo. Km. 36.5 Carretera-Federal México-Texcoco, Montecillo, Estado de México C.P. 56230, México. 4Animal and Plant Science Department, University of Sheffield, Sheffield S10 2TN, England, UK. Received: 12 April 2014 Accepted: 23 June 2014 Received: 12 April 2014 Accepted: 23 June 2014 Page 9 of 10 Page 9 of 10 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 References Serie Técnica Núm 22, Pucalpa, Perú, p 56 Guadarrama-Chávez P, Camargo-Ricalde SL, Hernández-Cuevas L, Castillo-Argüero S (2007) Los hongos micorrizógenos arbusculares de la región de Nizanda, Oaxaca, México. Bol Soc Bot Méx 81:131–137 Pérez-Rojas A, Torres-Orozco BR, Morales-Gutiérrez E, Pérez-Méndez E (2000) Textura, composición y contenido de materia orgánica de los sedimentos de un lago tropical de México. Hidrobiológica 10:41–50 Pérez-Rojas A, Torres-Orozco BR, Morales-Gutiérrez E, Pérez-Méndez E (2000) Textura, composición y contenido de materia orgánica de los sedimentos de un lago tropical de México. Hidrobiológica 10:41–50 Guadarrama P, Castillo S, Ramos-Zapata JA, Hernández-Cuevas LV, Camargo- Ricalde SL (2014) Arbuscular mycorrhizal fungal communities in changing environments: The effects of seasonality and anthropogenic disturbance in a seasonal dry forest. Pedobiologia 57:87–95 Phillips JM, Hayman DS (1970) Improved procedures for clearing and staining parasitic and vesicular arbuscular mycorrhizal fungi for rapid assessment of infection. Transations Br Mycol Soc 55:158–161 Hernández-Cuevas LV, García-Sánchez R (2008) Propagación por esporas: el caso de las micorrizas arbusculares. In: Álvarez-Sánchez J, Monroy-Ata A (ed) Técnicas de estudio de las asociaciones micorrízicas y sus implicaciones en la restauración: 29–42. Universidad Nacional Autónoma de México, México, D.F Picone C (2000) Diversity and abundance of arbuscular mycorrhizal fungal spores in tropical forest and pasture. Biotropica 32:734–747 Herrera RA, Ferrer RL (1980) Vesicular-arbuscular Mycorrhiza in Cuba. In: Mikola P (ed) Tropical Mycorrhizae Research: 156–162. Clarendon Press. Oxford, England Pouyu-Rojas E, Siqueira JO, Donizetti JGS (2006) Symbiotic compatibility of arbuscular mycorrhizal fungi with tropical tree species. Revista Brasileira Ciência Solo 30:413–424 Pouyu-Rojas E, Siqueira JO, Donizetti JGS (2006) Symbiotic compatibility of arbuscular mycorrhizal fungi with tropical tree species. Revista Brasileira Ciência Solo 30:413–424 Hewitt EJ (1966) The composition of the nutrient solution. In: Hewitt EJ (ed) Sand and water culture methods used in the study of plant nutrition: 187–246. Commonwealth Agricultural Bureau, Farmhand, UK Ramírez-Gerardo M, Álvarez-Sánchez J, Guadarrama-Chávez P, Sánchez-Gallen I (1997) Estudio de hongos micorrizógenos arbusculares bajo arboles remanentes en un pastizal tropical. Bol Soc Bot Méx 61:15–20 Page 10 of 10 Page 10 of 10 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Revista Brasileira Ciência Solo 28:611–622 Stürmer SL (2004) Effect of different fungal isolates from the same mycorrhizal community on plant growth and phosphorus uptake in soybean and red clover. Revista Brasileira Ciência Solo 28:611–622 Vandenkoornhuyse P, Baldauf SL, Leyva C, Straczek J, Peter WYJ (2002) Extensive f l di i i l S i 295 2051 Vandenkoornhuyse P, Baldauf SL, Leyva C, Straczek J, Peter WYJ (2002) Extensive fungal diversity in plants roots. Science 295:2051 van der Heijden MGA, Klironomos JN, Ursic M, Moutoglis P, Streitwolf-Engel R, Boller T, Wiemken A, Sanders IR (1998) Mycorrhizal fungal diversity deter- mines plant biodiversity, ecosystem variability and productivity. Nature 396:69–72 Varela L, Trejo D (2001) Los hongos micorrizógenos arbusculares como componentes de la biodiversidad del suelo en México. Acta Zoológica Mexicana 1:39–51 Varela-Fregoso L, Estrada-Torres A, Álvarez-Sánchez FJ, Sánchez-Guillén I (2008) Catálogo ilustrado de hongos micorrizógenos arbusculares de la Reserva de la Biósfera de los Tuxtlas (versión electrónica en CD). Universidad Nacional Autónoma de México. México, D.F Vargas R, Hasselquist N, Allen EB, Allen MF (2010) Effects of a hurricane disturbance on aboveground forest structure, arbuscular mycorrhizae and belowground carbon in a restored tropical forest. Ecosystems 13:118–128 Violi HA, Barrientos-Priego AF, Wright SF, Escamilla-Prado E, Morton JB, Menge JA, Lovatt CJ (2008) Disturbance changes arbuscular mycorrhizal fungal phen- ology and soil glomalin concentrations but not fungal spore composition in montane rainforests in Veracruz and Chiapas, Mexico. For Ecol Manag 254:276–290 Violi HA, Barrientos-Priego AF, Wright SF, Escamilla-Prado E, Morton JB, Menge JA, Lovatt CJ (2008) Disturbance changes arbuscular mycorrhizal fungal phen- ology and soil glomalin concentrations but not fungal spore composition in montane rainforests in Veracruz and Chiapas, Mexico. For Ecol Manag 254:276–290 Wubet T, Kottke I, Teketay D, Oberwinkler F (2009) Arbuscular mycorrhizal fungal community structures differ between co-occurring tree species of dry Afromontane tropical forest, and their seedlings exhibit potential to trap isolates suited for reforestation. Mycol Prog 8:317–328 Zangaro W, Bononi VLR, Trufen SB (2000) Mycorrhizal dependency, inoculum potential and habitat preference of native woody species in South Brazil. J Trop Ecol 16:603–622 doi:10.1186/s40693-014-0009-z Cite this article as: Rodríguez-Morelos et al.: Arbuscular mycorrhizal fungi associated with the rhizosphere of seedlings and mature trees of Swietenia macrophylla (Magnoliophyta: Meliaceae) in Los Tuxtlas, Veracruz, Mexico. Revista Chilena de Historia Natural 2014 87:9. Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Ramos-Zapata J, Guadarrama P (2004) Los hongos micorrizógenos arbusculares en la restauración de comunidades tropicales. Universidad y Ciencia. No. especial I :59–65 Ramos-Zapata JA, Orellana R, Allen EB (2006) Mycorrhizal dynamics and dependence of Desmoncus orthacanthos Martius (Arecaceae), a native palm of the Yucatán península, México. Interciencia 31:364–370 dependence of Desmoncus orthacanthos Martius (Arecaceae), a native palm of the Yucatán península, México. Interciencia 31:364–370 Redecker D, Schüßler A, Stockinger H, Stürmer SL, Morton JB, Walker C (2013) An evidence-based consensus for the classification of arbucular mycorrhizal fungi (Glomeromycota). Mycorrhiza 23:515–531 SAS Institute Inc (2009) SAS/STAT user's guide. SAS, Cary, NC, USA of the Yucatán península, México. Interciencia 31:364–370 Redecker D, Schüßler A, Stockinger H, Stürmer SL, Morton JB, Walker C (2013) An evidence-based consensus for the classification of arbucular mycorrhizal fungi (Glomeromycota). Mycorrhiza 23:515–531 SAS Institute Inc (2009) SAS/STAT user's guide. SAS, Cary, NC, USA Schenck NC, Pérez Y (1990) Manual for the Identification of VA Mycorrhizal Fungi. Synergistic Publications Gainesville Florida USA Redecker D, Schüßler A, Stockinger H, Stürmer SL, Morton JB, Walker C (2013) An evidence-based consensus for the classification of arbucular mycorrhizal fungi (Glomeromycota). Mycorrhiza 23:515–531 g ( y ) y SAS Institute Inc (2009) SAS/STAT user's guide. SAS, Cary, NC, USA Schenck NC, Pérez Y (1990) Manual for the Identification of VA My Synergistic Publications, Gainesville, Florida, USA Shi ZY, Chen YL, Feng G, Liu RJ, Christie P, Li XL (2006) Arbuscular mycorrhizal fungi associated with the Meliaceae on Hainan island, China. Mycorrhiza 16:81–87 Smith SE, Read DJ (2008) Mycorrhizal Symbiosis, 3rd edition. Academic Press, Cambridge, UK Snook L (1996) Catastrophic disturbance, logging and the ecology of (Swietenia macrophylla King): grounds for listing a major tropical timber species in CITES. Bot J Linn Soc 122:35–46 Soto M, Gama L (1997) Climas. In: González-Soriano E, Dirzo R, Vögt R (ed) Historia Natural de Los Tuxtlas:7–23. Universidad Nacional Autónoma de México-CONABIO, México, D. F México CONABIO, México, D. F Stürmer SL (2004) Effect of different fungal isolates from the same mycorrhizal community on plant growth and phosphorus uptake in soybean and red clover. Revista Brasileira Ciência Solo 28:611–622 Vandenkoornhuyse P, Baldauf SL, Leyva C, Straczek J, Peter WYJ (2002) Extensive fungal diversity in plants roots. Science 295:2051 Stürmer SL (2004) Effect of different fungal isolates from the same mycorrhizal community on plant growth and phosphorus uptake in soybean and red clover. Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Rodríguez-Morelos et al. Revista Chilena de Historia Natural 2014, 87:9 http://www.revchilhistnat.com/content/87/1/9 Submit your manuscript to a journal and beneﬁ t from: 7 Convenient online submission 7 Rigorous peer review 7 Immediate publication on acceptance 7 Open access: articles freely available online 7 High visibility within the ﬁ eld 7 Retaining the copyright to your article Submit your next manuscript at 7 springeropen.com Submit your manuscript to a journal and beneﬁ t from: 7 Convenient online submission 7 Rigorous peer review 7 Immediate publication on acceptance 7 Open access: articles freely available online 7 High visibility within the ﬁ eld 7 Retaining the copyright to your article Submit your next manuscript at 7 springeropen.com
https://openalex.org/W2963959798	https://ieeexplore.ieee.org/ielx7/42/8782670/08737942.pdf	English	null	RetinaMatch: Efficient Template Matching of Retina Images for Teleophthalmology	IEEE transactions on medical imaging	2,019	cc-by	12,363	IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 38, NO. 8, AUGUST 2019 1993 Chen Gong , N. Benjamin Erichson, John P. Kelly, Laura Trutoiu, Brian T. Schowengerdt, Steven L. Brunton, and Eric J. Seibel and changing attitudes of clinicians, providers and con- sumers. Teleophthalmology is an important component of telemedicine, and it is now arguably the standard of care in linking patients in remote areas to ophthalmologists. Recently, low-cost teleophthalmology has been facilitated by smartphone-based fundus imaging. In addition, the emerging virtual and mixed reality sector may enable new teleophthal- mology scenarios for long-term eye imaging and monitor- ing. However, in the case of portable fundus photography, non-mydriatic image quality is more vulnerable to distortions, such as uneven illumination, noise, blur and low contrast [1]. In this paper, we address the challenging problem of auto- mated retinal image matching and registration to enable future teleophthalmology applications. Abstract— Retinal template matching and registration is an important challenge in teleophthalmology with low-cost imaging devices. However, the images from such devices generally have a small ﬁeld of view (FOV) and image qual- ity degradations, making matching difﬁcult. In this paper, we develop an efﬁcient and accurate retinal matching technique that combines dimension reduction and mutual information (MI), called RetinaMatch. The dimension reduc- tion initializes the MI optimization as a coarse localiza- tion process, which narrows the optimization domain and avoids local optima. The effectiveness of RetinaMatch is demonstrated on the open fundus image database STARE with simulated reduced FOV and anticipated degradations, and on retinal images acquired by adapter-based optics attached to a smartphone. RetinaMatch achieves a success rate over 94% on human retinal images with the matched tar- get registration errors below 2 pixels on average, excluding the observer variability, outperforming standard template matching solutions. In the application of measuring ves- sel diameter repeatedly, single pixel errors are expected. In addition, our method can be used in the process of image mosaicking with area-based registration, providing a robust approach when feature-based methods fail. To the best of our knowledge, this is the ﬁrst template matching algorithm for retina images with small template images from unconstrained retinal areas. In the context of the emerg- ing mixed reality market, we envision automated retinal image matching and registration methods as transforma- tive for advanced teleophthalmology and long-term retinal monitoring. A. Motivation The eye provides a unique opportunity to image internal biological tissue in vivo and many diseases can be diagnosed and monitored through ocular imaging. For example, diabetic retinopathy is a common retinal complication associated with diabetes, causing microaneurysms, exudates and hemorrhages on the retina [2], [3]. Changes of retinal arteries and veins, as well as their ratios, can be indicators of hypertension [4]. The timely detection of these pathological changes via regular retinal screening and analysis is particularly important for early diagnosis and prevention. Index Terms— Retina image template matching, tele- ophthalmology, dimension reduction, mutual information, health monitoring. High-quality fundus images of the retina are traditionally acquired in a laboratory setting with expensive and cum- bersome equipments. Acquiring high-quality fundus images poses a signiﬁcant challenge for patients in rural and other underserved areas who must overcome signiﬁcant hurdles to receive regular checkups in the clinic. Visiting an ophthalmol- ogist is often inconvenient for patients in the city as well. In contrast, emerging portable and low-cost fundus cameras allow fast, accessible imaging of the retina, albeit with a decrease in image quality. Using portable fundus cameras outside the clinic connects rural patients with their doctors [5], [6]. By daily retinal monitoring and trend analysis of the data, ocular disease may no longer be considered the silent disease, as early onset is likely to be detectable and even predicted [7]. I. INTRODUCTION This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/ his work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativeco eative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/ RetinaMatch: Efﬁcient Template Matching of Retina Images for Teleophthalmology Chen Gong , N. Benjamin Erichson, John P. Kelly, Laura Trutoiu, Brian T. Schowengerdt, Steven L. Brunton, and Eric J. Seibel I. INTRODUCTION Alignment functions with respect to translations between the template and the white boxed area. The full FOV image in (a) is taken with the fundus camera in the clinic. The top left image in the magenta square is the template captured by a typical adapter-based fundus camera D-eye, having only translations along two axes. (b)(c)(d) show the alignment function between the template and regions within the white boxed area. The true alignment position is (0, 0) – see red dots. Only NMI shows an obvious maximum at the alignment position. Note that the optimal value of SSD is minimum and NCC and NMI are maximums. from 5◦to 20◦in undilated eyes [5], [8]. In this case, many small images captured in the undilated eye at different loca- tions are necessary to obtain adequate retinal imaging. The same retinal locations need to be re-imaged and matched in order to monitor changes longitudinally over time. Accord- ingly, all of the captured small FOV images can be registered and compared to a stored wide FOV retinal image. This reference image is a baseline which can be stitched together by a series of small FOV images, or can leverage wider FOV images captured from a conventional ophthalmoscope. Taking the small FOV images as the templates to be matched, it is a template matching process, as shown in Fig. 1(a). The template only covers a small area on the retina, thus is unlikely to be affected much by the nonlinear deformation due to the non-planar eyeball surface. The location of the template in the full image may be represented by an afﬁne linear transformation, i.e. including translation, rotation, shear, and scaling. This provides a mathematical framework to formulate template matching as an optimization problem. retinas [12]. Retina images captured by adapter-based optics provide less information and have low image quality, which further increases the difﬁculty of template matching. It is instructive to introduce current retina image registration meth- ods which can be used for template matching and their feasibil- ity in addressing our stated problem. Retina image registration approaches can be classiﬁed into area-based and feature-based methods. Feature-based methods optimize the correspondence between extracted salient objects in retina images [12]–[16]. Bifurcations, fovea, and the optic disc are common features used for retinal image registration. I. INTRODUCTION T T ELEMEDICINE applications are emerging at a rapid pace due to innovations in hardware and software, Manuscript received November 29, 2018; revised June 3, 2019; accepted June 7, 2019. Date of publication June 17, 2019; date of current version July 31, 2019. (Corresponding author: Chen Gong.) y ( p g g ) C. Gong, S. L. Brunton, and E. J. Seibel are with the Mechanical Engineering Department, University of Washington, Seattle, WA 98195 USA (e-mail: chengong@uw.edu). ( g g ) N. B. Erichson is with the Department of Applied Mathematics, Univer- sity of Washington, Seattle, WA 98195 USA. y g , , J. P. Kelly is with the Department of Ophthalmology, University of Washington, Seattle, WA 98195 USA. y g J. P. Kelly is with the Department of Ophthalmology, University of Washington, Seattle, WA 98195 USA. g L. Trutoiu and B. T. Schowengerdt are with Magic Leap, Inc., Plantation, FL 33313 USA. A typical example of a portable fundus camera involves a clip-on lens adapter attached to a smart-phone system [5]. These consumer-grade optical devices have two main disad- vantages: small FOV and lower image quality than lab-based fundus cameras. The FOVs of current clip-on lenses range This paper has supplementary downloadable material available at http://ieeexplore.ieee.org., provided by the author. This paper has supplementary downloadable material available at http://ieeexplore.ieee.org., provided by the author. Color versions of one or more of the ﬁgures in this paper are available online at http://ieeexplore.ieee.org. Color versions of one or more of the ﬁgures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identiﬁer 10.1109/TMI.2019.2923466 Digital Object Identiﬁer 10.1109/TMI.2019.2923466 a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4. IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 38, NO. 8, AUGUST 2019 1994 Fig. 1. Alignment functions with respect to translations between the template and the white boxed area. The full FOV image in (a) is taken with the fundus camera in the clinic. The top left image in the magenta square is the template captured by a typical adapter-based fundus camera D-eye, having only translations along two axes. (b)(c)(d) show the alignment function between the template and regions within the white boxed area. The true alignment position is (0, 0) – see red dots. Only NMI shows an obvious maximum at the alignment position. Note that the optimal value of SSD is minimum and NCC and NMI are maximums. Fig. 1. I. INTRODUCTION A small FOV template has little probability of containing speciﬁc landmarks on the retina, thus the fovea and optic disc are not applicable. Vascular bifur- cations are more common, while similarly, the small number of bifurcations in the template cannot form the basis of a robust registration. Besides, the extraction of the vascular network in poor quality images is difﬁcult. General feature point based approaches are also implemented in retina registration, such as SIFT-based [17], [18] and SURF-based methods [19], [20]. These approaches can register the images in complex scenarios and are computationally efﬁcient. They assume the feature point pairs can be reliably detected and matched to estimate the transformation. Although feasible in most cases, the process can fail on low-quality retina images without enough distinct features. As described above, an accurate template matching method to deal with small FOV and low quality template images is needed in teleophthalmology. Since the method will be imple- mented on portable devices, the efﬁciency of computation is also a driving requirement. Area-based approaches match the intensity differences of an image pair under a similarity measure, such as SSD (sum of squared differences) [21], CC (Cross-Correlation) [22] and MI (mutual information) [23], then optimize the similarity measure by searching in the transformation space. Avoiding pixel-level feature detection, such approaches are more robust to poor quality images than feature-based approaches. How- ever, retina images with sparse features and similar back- grounds are likely to lead the optimization into local extrema. Fig. 1 shows an example of the area-based method with three similarity measures. The small template image is captured by the adapter-based D-eye optics which is registered onto a full fundus image. Both of the images are acquired by the same modality. SSD and normalized CC (NCC) do not have an obvious peak at the alignment position (0,0), giving C. Contributions In this paper, we present RetinaMatch, a new template matching method that overcomes the challenges posed by registering small FOV and low-quality retinal images onto a full image. This approach is an improvement over the area-based methods that only optimize the MI metric [23], since it achieves more accurate and robust template matching near the alignment position, as shown in Fig. 1. zi = Xwi, (1) (1) where zi is the ith principal component (PC) and wi is the weight vector. The ﬁrst PC explains most of the variation in the data, the subsequent PCs then account for the remaining variation in descending order. Thereby, PCA imposes the constraint that the weight vectors are orthogonal. This problem can be expressed compactly as the following minimization: The unique aspect of our approach is that we combine dimension reduction methods with the MI-based registration to reduce the sensitivity to local minima, while improving the matching efﬁciency. An overview of our novel template match- ing framework is shown in Fig. 2. Speciﬁcally, the principal component analysis (PCA) and block PCA are used to localize the template image coarsely, then the resulting displacement parameters are used to initialize the MI metric optimization. The initial parameters provided by the coarse localization are in the convergence domain of MI metric. In this way, the trans- formation search space for optimization is narrowed signiﬁ- cantly. The PCA computation is accelerated with randomized methods [24]–[26], which improves the coarse localization efﬁciency. Both the use of PCA for coarse localization and the use of randomized methods for acceleration are unique meth- ods of implementation. Further, we have carefully compared PCA against several other dimension reduction techniques, and we ﬁnd that PCA offers the best tradeoff in simplicity, accuracy, and efﬁciency. Another contribution is that this paper proposes an efﬁcient image mosaicking algorithm based on the image dimension reduction. It accelerates the matching of overlapped images among unordered data, especially in image mosaicking with area-based registration methods. minimize ∥X −ZW∥2 F subject to W⊤W = I, (2) (2) where ∥.∥F is the Frobenius norm. The weight matrix W that maps the input data to a subspace turns out to be the right singular vectors of the input matrix X. Often a low-rank approximation is desirable, i.e., we compute only the k dominant PCs using a truncated weight matrix Wk = [w1, w2, . . . , wk]. GONG et al.: RETINAMATCH: EFFICIENT TEMPLATE MATCHING OF RETINA IMAGES 1995 Generally, we can categorize dimension reduction tech- niques as either linear or nonlinear. The most prominent linear technique is principal component analysis (PCA), which dates back to the work of [28] and [29]. PCA is selected as the dimension reduction method in RetinaMatch since it is simple and versatile. Speciﬁcally, PCA forms a set of new variables as a weighted linear combination of the input variables. Consider a matrix X = [x1, x2, . . . , xd] of dimension n × d, where n denotes the number of observations and d is the number of variables. Further, we assume that the matrix X is column-wise mean centered. The idea of PCA is to form a set of uncorrelated new variables (so called principal components) as a linear combination of the input variables: no clear information on the alignment quality. Normalized MI (NMI) shows a maximum at the alignment position, while it still has local extrema which can interfere with the global optimization. Besides, when the size difference between the template and full image is too large, registration with MI can be computationally prohibitive. B. Related Work Much of the foundational work on template matching of retinal images is based on more general image registration methods, which have been comprehensively studied in recent years. However, general retina registration methods focus on matching image pairs that both have a large FOV with local deformations or different image modalities. Many existing retinal template matching algorithms are limited to detecting speciﬁc objects from the image, where the template always contains a certain feature, such as the optic disc, exudate and artifacts [9]–[11]. Retinal image registration itself is challenging: the non- vascular surface of retina is homogeneous in healthy reti- nas, while exhibiting a variety of pathologies in unhealthy GONG et al.: RETINAMATCH: EFFICIENT TEMPLATE MATCHING OF RETINA IMAGES II. PRELIMINARIES II. PRELIMINARIES C. Contributions PCA is generally computed by the singular value decom- position (SVD). Many algorithms have been developed to streamline the computation of the SVD and PCA for high-dimensional data that exhibits low-dimensional patterns [30]. In particular, tremendous strides have been made to accelerate the SVD and related computations using ran- domized methods for linear algebra [24]–[26]. Since we have demonstrated high performance with less than 20 principal components, the randomized SVD is used to compute the principal components, improving the efﬁciency in this retinal mapping application for mobile platforms. The randomized algorithm proceeds by forming a sketch Y of the input matrix The proposed method is validated on the STARE retinal dataset [27] with synthetic deformations, and in vivo data cap- tured by a low-cost (<US$400) adapter-based optical device D-eye. The performance of different dimension reduction tech- niques are also compared on the STARE dataset. RetinaMatch can ﬁnd the correct mapping even when the image is of poor quality with non-distinct features, whereas other methods fail due to unstable feature detection and local extrema. Y = X, (3) (3) where is a d × l random test matrix, say with independent and identically distributed random standard normal entries. Thus, the l columns of Y are formed as a randomly weighted linear combination of the columns of the input matrix, provid- ing a basis for the column space of X. Note, that l is chosen to be slightly larger than the desired number of principal components. Next, we form an orthonormal basis Q using the QR decomposition Y = QR. Now, we use this basis matrix to project the input data matrix to low-dimensional space where is a d × l random test matrix, say with independent and identically distributed random standard normal entries. Thus, the l columns of Y are formed as a randomly weighted linear combination of the columns of the input matrix, provid- ing a basis for the column space of X. Note, that l is chosen to be slightly larger than the desired number of principal components. Next, we form an orthonormal basis Q using the QR decomposition Y = QR. Now, we use this basis matrix to project the input data matrix to low-dimensional space III. PROPOSED APPROACH the dominant principal components. Given the SVD of B = UV⊤, we obtain the approximate principal components as In this section, we describe RetinaMatch, which combines dimensionality reduction and mutual information based image registration. From Fig. 1 we can see MI performs better than other similarity metrics even on the same modality images, thus we focus on the MI criterion. Given a large FOV full image and a small FOV template image, our method can be used to localize the template on the full image accurately and efﬁciently. The full image can be a wide-ﬁeld fundus image or a mosaicked one from D-eye images. The underlying concept is to use PCA and block PCA ﬁrst for coarse localization, which can be a warm start to following accurate registration. In accurate registration, the MI metric is optimized to ﬁnd the optimal transformation. Since the optimization domain has been narrowed to a small range near the optimal position with coarse localization, the accurate registration can achieve high accuracy and efﬁciency. Fig. 2 provides an overview of the general approach to RetinaMatch. (5) Z = QU = XV. (5) Here, U and V are the left and right singular vectors and the diagonal elements of are the corresponding singular values. The approximation accuracy can be controlled via additional oversampling and power iterations, for details see [31]. It is important to note that PCA is sensitive to outliers, occlusions, and corruption in the data. In ophthalmological imaging applications, there are several potential sources of corruption and outliers when imaging the full image, including blur, uncorrected astigmatism, inhomogeneous illumination, glare from crystalline lens opacity, internal reﬂections (e.g., from the vitreoretinal interface and lens), transient ﬂoaters in the vitreous, and shot noise in the camera. Further, there is always a trade-off between illumination and image quality, and there is strong motivation to introduce as little light as necessary for the patient comfort and health. The robust prin- cipal component analysis (RPCA) [32], [33] was introduced speciﬁcally to address this issue, decomposing a data matrix into the sum of a matrix containing low-rank coherent structure and a sparse matrix of outliers and corrupt entries. In general, RPCA is more expensive than PCA, requiring an iterative optimization to decompose the original matrix into sparse and low-rank components. A. Coarse Localization With Dimension Reduction We deﬁne the full image and the template as F and S respectively. The full image F is split into target images I1, I2, . . . , IN : Ii = φ(bi, F). (8) (8) The function φ crops Ii from F at bi and bi = [xi, yi, h, w], where (xi, yi) denotes the center position and (h, w) denotes the width and height of the source image. There is a certain displacement f of neighboring target images in the x and y axes. As shown in Fig. 2(a), each target image has a large overlap with its neighbors. The overlap forms the redundancy of the data which can indicate the location distribution between each image and its neighbors. Applying dimension reduction techniques on such data we can obtain the low-dimensional distribution map of all target images. Target images are resized to vectors and form the matrix X ∈Rn×d. We obtain the low-dimensional distribution represen- tation of the target image distribution by implementing PCA on X: A. PCA for Location Estimation A. PCA for Location Estimation Dimension reduction methods allow the construction of low-dimensional summaries, while eliminating redundancies and noise in the data. To estimate the template location in the 2d space, the full image dimension is redundant, thus we apply dimension reduction methods for the template coarse localization. In this section we describe the dimension reduc- tion methods we use in this paper. B = Q⊤X. (4) (4) This smaller matrix B of dimension l × d can then be used to efﬁciently compute the low-rank SVD and subsequently This smaller matrix B of dimension l × d can then be used to efﬁciently compute the low-rank SVD and subsequently IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 38, NO. 8, AUGUST 2019 1996 III. PROPOSED APPROACH Each step of the iteration is as expensive as regular PCA, and typically on the order of tens of iterations are required; however, PCA may be viewed as an ofﬂine step in our procedure, so that this additional computational cost is manageable. RPCA has been applied with success in retinal imaging applications to improve image quality [34], [35]. In the examples presented in this work, the data appears to have few enough outliers so that RPCA is not necessary, although it is important to keep RPCA as an option for data with outliers and corruption. B. Mutual Information (d) The nearest target image is registered h MI. The panels (a) and (b) in green can be pre-processed ofﬂine when the full image is obtained, while panels (c) and (d) are considered as the ine stage. The schematic describes the method without using the improvement of block PCA. Please see Sect. III for more details of block PCA. Fig. 2. Schematic of the proposed retinal template matching method shown in four panels from (a) to (d). In panel (a) the wide-FOV full image is sampled with many overlapping target images. (b) Each target image is mapped into the low-dimensional space according to its positional relationship. (c) An example template is also mapped into this space and its nearest target image is found. (d) The nearest target image is registered with MI. The panels (a) and (b) in green can be pre-processed ofﬂine when the full image is obtained, while panels (c) and (d) are considered as the online stage. The schematic describes the method without using the improvement of block PCA. Please see Sect. III for more details of block PCA. Fig. 2. Schematic of the proposed retinal template matching method shown in four panels from (a) to (d). In panel (a) the wide-FOV full image is sampled with many overlapping target images. (b) Each target image is mapped into the low-dimensional space according to its positional relationship. (c) An example template is also mapped into this space and its nearest target image is found. (d) The nearest target image is registered with MI. The panels (a) and (b) in green can be pre-processed ofﬂine when the full image is obtained, while panels (c) and (d) are considered as the online stage. The schematic describes the method without using the improvement of block PCA. Please see Sect. III for more details of block PCA. The corresponding target image location is used as the coarse location of S. Ideally, the difference between the coarse location and the ground truth in x and y axes should be less than f/2 pixels. image distribution. Each template patch is then mapped to the space with W .1 The nearest target patch for each template patch is determined with the Euclidean distance as described before. The coordinates of each target patch represent the location of the mapped patch. B. Mutual Information In this section, we describe the maximization of MI for multimodal image registration. We deﬁne images S and S as the template and target images, respectively. A transform u is deﬁned to map pixel locations x ∈S to pixel locations in S. Z = XW, (9) (9) where Z = [z1, z2, z3, . . . , zN]T ∈Rn×l, W ∈Rd×l and l ≪d. The image space 1 is mapped to a low-dimensional space 2 with the mapping W. W and Z are saved in the dictionary D. The main idea of the registration is to ﬁnd a deformation u at each pixel location x that maximizes the MI between the deformed template image S(u(x)) and the target image S(x). Accordingly, Given a template S, the coarse position can be estimated by recognizing its nearest target image. The nearest target image in 1 should also be the nearest representation of S in 2. Accordingly, we obtain the low-dimension feature zs of the template in 2 : uopt = arg min u M I(S(u(x)),S(x)), (6) uopt = arg min u M I(S(u(x)),S(x)), (6) (6) where where zs = ˜sW, (10) M I(S(u(x)),S(x)) = i1∈S i2∈S p(i1, i2)log( p(i1, i2) p(i1)p(i2)). (7) (10) where ˜s ∈Rd is the reshaped vector of template S. Let (zs, z) be the Euclidean distance between zs and a feature z in Z. z∗is the nearest target feature of the source image S in 2 : where ˜s ∈Rd is the reshaped vector of template S. Let (zs, z) be the Euclidean distance between zs and a feature z in Z. z∗is the nearest target feature of the source image S in 2 : Here, i1 and i2 are the image intensity values in S(u(x)) and S(x), respectively, and p(i1) and p(i2) are their marginal prob- ability distributions while p(i1, i2) is their joint probability distribution. z∗= arg min z (zs, z). (11) (11) GONG et al.: RETINAMATCH: EFFICIENT TEMPLATE MATCHING OF RETINA IMAGES 1997 . 2. Schematic of the proposed retinal template matching method shown in four panels from (a) to (d). In panel (a) the wide-FOV full image sampled with many overlapping target images. (b) Each target image is mapped into the low-dimensional space according to its positional ationship. (c) An example template is also mapped into this space and its nearest target image is found. B. Mutual Information We use the same weight for each region of the template for localization, thus the average of all template patches location can be taken as the template’s location. Let bm be the mean of the coordinates of selected nearest target patches, which then represents the center of the template on I. Accordingly, the template location on the full image can be estimated and the region is cropped as the image S. The accurate registration is then applied to the template S and image S. In this way, the coarse localization provides an estimate of a good initial point for the accurate registration. In the ﬁrst experiment in Sect. IV, PCA outperforms other non-linear dimension reduction methods, while the error is larger than f/2. The main reason is that the image degradation creates spurious features that contribute to the ﬁnal classi- ﬁcation. To reduce the inﬂuence of local spurious features, we implement block PCA to further improve the accuracy of the coarse localization. By computing the PCA of different local patches in the template, the effect of local features, which leading to the template can not be located correctly, is reduced. Here we introduce the detailed process of the block PCA. Obtaining the nearest target image, we crop a larger image at the same position from the full image as the new target image I. In this way, the template can have more overlap with the new target image when there is a large offset between two images. We segment I and the template S into small patches with the function ˜φ, where the patch size is smaller than the source image with the axial displacement of neighboring patches f . Similarly, all image patches from I are mapped into the low-dimension space 3 with W . Let Z denote the low-dimensional representation of the target In the ﬁrst experiment in Sect. IV, PCA outperforms other non-linear dimension reduction methods, while the error is larger than f/2. The main reason is that the image degradation creates spurious features that contribute to the ﬁnal classi- ﬁcation. To reduce the inﬂuence of local spurious features, we implement block PCA to further improve the accuracy of the coarse localization. By computing the PCA of different local patches in the template, the effect of local features, which leading to the template can not be located correctly, is reduced. 1Fig. S1 in the supplementary material gives an example of the image patch mapping. C. Image Stitching C. Image Stitching Algorithm 1: Coarse Localization: Online Stage 1 Map template S into space 2: zs = ˜sW. 2 Determine closest target image I with corresponding z∗: z∗= arg minz (zs, z). z∗∈Z. 3 Segment S into [S1 p, S2 p, . . . , Sn p]: Si p = ˜φ(bi, S); Segment I into [I 1 p, I 2 p, . . . , I n p]: I i p = ˜φ(bi, I). 4 Map target patches I i p into space 3: Z = IpW , where Ip is formed with vectorized I i p. 5 For each template patch Si p: 6 (i)Map Si p into space 3: ˜zsi = Si pW . 7 (ii)Determine its closest target patch I Idx(i) p with index Idx(i). 8 bm = 1 n n i=1 bIdx(i), where bIdx(i) is the coordinate of selected target patch I Idx(i) p . 9 return localization region S = φ(bm, F)). Algorithm 1: Coarse Localization: Online Stage As pointed out in Sect. I, the full retina image can be stitched into a panorama by using many small templates. Users must capture a series of images in naturally unconstrained eye positions to explore different regions of the retina. It is prob- lematic to determine adjacent images before the registration when we apply area-based registration approaches, since they do not have effective descriptors for matching. 1 Map template S into space 2: zs = ˜sW. 2 Determine closest target image I with corresponding z∗: z∗= arg minz (zs, z). z∗∈Z. p Ip is formed with vectorized I i p. 5 For each template patch Si p: p g Related to the dimension reduction in the proposed template matching method, here we present Algorithm 2 to learn the positional relationship of images to be stitched. In this way, the adjacent images can be recognized and registered efﬁciently. For a series of small images Xi, we form the matrix X, as with the matrix T. PCA is applied to X and returns the low-dimensional features for each image in 2. The distance between features in 2 indicates the distance between images. The nearest neighbor Xj of image Xi is the one with largest overlap; the image pair is then registered with MI-based approach. C. Image Stitching To improve the algorithm robustness, the 3-nearest neighbors for each image are ﬁrst selected to compute MI with, and we keep the one with the largest metric value. p 6 (i)Map Si p into space 3: ˜zsi = Si pW . Id 7 (ii)Determine its closest target patch I Idx(i) p with index Idx(i). 1 n 8 bm = 1 n n i=1 bIdx(i), where bIdx(i) is the coordinate of Idx(i) selected target patch I Idx(i) p . selected target patch I Idx(i) p . selected target patch I Idx(i) p . p 9 return localization region S = φ(bm, F)). B. Accurate Registration In this section, images S and S are accurately registered with maximization of mutual information. The location of S on the full image F becomes the estimated displacement of the template S. As the small FOV of template images, the relationship between the template and the full image can be modeled by linear transformations. In our work, the transform u for alignment is given as an afﬁne transformation: Algorithm 2: Image Stitching 1 Map images into space 2:Z = XW. 2 For each image Xi: 3 (i).Find the nearest 3 neighbors Xj minimizing the feature distance (Zi, Zj). 4 (ii).Compute the Mutual Information between each Xj and Xi and take the adjacent image with highest MI. 5 Panorama R Mosaicking: Align all the adjacent images with mutual information based registration method. 6 Panorama blending. 7 return panorama R. 1 Map images into space 2:Z = XW. g i 3 (i).Find the nearest 3 neighbors Xj minimizing the feature distance (Zi, Zj). 4 (ii).Compute the Mutual Information between each Xj and Xi and take the adjacent image with highest MI. u = ⎡ ⎣ a11 a12 tx a21 a22 ty 1 1 0 ⎤ ⎦. (12) 5 Panorama R Mosaicking: Align all the adjacent images with mutual information based registration method. (12) 6 Panorama blending. 6 Panorama blending. 7 return panorama R. 7 return panorama R. From the MI equation 7, we can see the MI function has a discrete formulation which is not differentiable. Several solutions therefore are proposed to smooth the MI function to compute the MI derivatives and keep its accuracy. We use the method described in [36], where the joint probability distribution between the images S and S is estimated with a Parzen window. B. Mutual Information Here we introduce the detailed process of the block PCA. Obtaining the nearest target image, we crop a larger image at the same position from the full image as the new target image I. In this way, the template can have more overlap with the new target image when there is a large offset between two images. We segment I and the template S into small patches with the function ˜φ, where the patch size is smaller than the source image with the axial displacement of neighboring patches f . Similarly, all image patches from I are mapped into the low-dimension space 3 with W . Let Z denote the low-dimensional representation of the target In the implementation of the proposed coarse localization, the full image is assumed to exist so the dictionary D can be built in advance. This is the pre-computed part as shown in Fig. 2 (a-b). The process after the template being acquired is called the online stage, involving the block PCA for coarse 1Fig. S1 in the supplementary material gives an example of the image patch mapping. IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 38, NO. 8, AUGUST 2019 IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 38, NO. 8, AUGUST 2019 1998 bm of the selected region S. Fig. 3 shows a schematic of the coarse localization process and intermediate results. localization followed by the accurate registration. The online stage of the coarse localization is shown in Algorithm 1. Algorithm 1: Coarse Localization: Online Stage 1 Map template S into space 2: zs = ˜sW. 2 Determine closest target image I with corresponding z∗: z∗= arg minz (zs, z). z∗∈Z. 3 Segment S into [S1 p, S2 p, . . . , Sn p]: Si p = ˜φ(bi, S); Segment I into [I 1 p, I 2 p, . . . , I n p]: I i p = ˜φ(bi, I). 4 Map target patches I i p into space 3: Z = IpW , where Ip is formed with vectorized I i p. 5 For each template patch Si p: 6 (i)Map Si p into space 3: ˜zsi = Si pW . 7 (ii)Determine its closest target patch I Idx(i) p with index Idx(i). 8 bm = 1 n n i=1 bIdx(i), where bIdx(i) is the coordinate of selected target patch I Idx(i) p . 9 return localization region S = φ(bm, F)). Algorithm 2: Image Stitching 1 Map images into space 2:Z = XW. 2 For each image Xi: 3 (i).Find the nearest 3 neighbors Xj minimizing the feature distance (Zi, Zj). 4 (ii).Compute the Mutual Information between each Xj and Xi and take the adjacent image with highest MI. 5 Panorama R Mosaicking: Align all the adjacent images with mutual information based registration method. 6 Panorama blending. 7 return panorama R. IV. EXPERIMENTS Each image pair includes a full fundus image selected randomly from the dataset and an afﬁne transformation is applied to map it from a square into a parallelogram. The area within the mapped square is then cropped and warped (with the inverse afﬁne transformation) to obtain the square template. The FOV of the template images is around 12◦with a size of 200 × 200 pixels. The template dimension is 10% of the full image. The ground truth is available in this experiment, thus root- mean-square (RMS) errors between corrected displacements and ground truth positions are used as a metric to measure the RetinaMatch accuracy. To evaluate the coarse localization, we take the center point distance between the template and the chosen target region. image pairs created from the STARE dataset. The pixel-level errors (coarse localization error as described), success rates, and average runtimes of these methods are shown in Table I. The criterion of successful matches in the coarse localization is a pixel-level error of less than 40 pixels. It is veriﬁed that the PCA based coarse localization is more efﬁcient, accurate and interpretable. Block PCA further improves the accuracy while the time spent is higher than PCA-only method. To further improve the online efﬁciency, the target patches mapping can be precomputed for each target images. The average time spent in this case will decrease to 0.0975s. 1) Validation of the Coarse Localization: First the coarse localization with and without the block PCA reﬁnement are tested. In the implementation, target images are generated with a displacement of f = 10 pixels and f = 5 for the block PCA. We use the top 20 and 10 PCA features in the ﬁrst PCA step and the block PCA respectively. The parameters are ﬁxed in remaining experiments. Additionally, we test the coarse localization with two other non-linear dimension reduction methods: kernel PCA [39] and Isomap [40]. We compare the non-linear dimension reduction methods to see if the non-planar retina surface and the afﬁne transformation affect the performance of the PCA-based linear method. In the kernel PCA, we compared Gaussian kernel and polynomial kernels with different degrees. The Gaussian kernel has better performance and is thus selected for kernel PCA. There may be other better kernels that better separate the data. However, ﬁnding this embedding space is labor-intensive and may need to be re-tuned for new image types, whereas PCA is more generic. IV. EXPERIMENTS We present the performance of our template match- ing method on three experiments using retina images. For comparison, we use the global MI algorithm described in Mattes et al. [37] and ASIFT (modiﬁed SIFT for afﬁne deformation) [38]. In the ﬁrst experiment, each template is extracted from the full fundus image in the STARE dataset and matched back to it. The intermediate results of the coarse localization are also evaluated. In the second experiment, the template captured by the adapter-based optics is matched to the full fundus image captured by the clinical fundus camera. In the third experiment, a panorama is mosaicked from small templates ﬁrst, and subsequently individual templates are matched to the panorama. The optimizer used for the MI maximization is based on Newton’s method. The MI function is a quasi-concave function (Fig. 1(d)), and the parabolic hypothesis of the Newton’s method is only valid near the convergence. When the initial transformation is on the convex part of the cost function, it will cause the optimization to diverge. In the example of Fig. 1(d), the normalized MI measure has local extrema interference. The proposed coarse localization provides a good initialization of the displacement for subsequent optimization of the MI alignment function. In the ﬁgure, the estimated alignment position is (11, 9). The estimation is close to the optimal value and falls in the convex domain of the MI metric, which provides more efﬁcient optimization and avoid local extrema. A. Fundus Images From STARE Dataset In this experiment, we validate our method on simulated fundus images. We use images from the STARE dataset [27], After registration between images S and S, the template S can be matched on the full image F based on the position GONG et al.: RETINAMATCH: EFFICIENT TEMPLATE MATCHING OF RETINA IMAGES 1999 Fig. 3. Schematic of the coarse localization process: PCA and block PCA. Fig. 3. Schematic of the coarse localization process: PCA and block PCA. TABLE I COMPARISON OF COARSE LOCALIZATION WITH DIFFERENT DIMENSION REDUCTION METHODS TABLE I COMPARISON OF COARSE LOCALIZATION WITH DIFFERENT DIMENSION REDUCTION METHODS TABLE I COMPARISON OF COARSE LOCALIZATION WITH DIFFERENT DIMENSION REDUCTION METHODS which consists of 400 raw fundus images of healthy and diseased retinas. Matching image pairs are simulated from this dataset. 2Fig. S2 is in the supplementary material. IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 38, NO. 8, AUGUST 2019 IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 38, NO. 8, AUGUST 2019 2000 Fig. 4. Examples of highest level degradations in each sequence. Please note that (b) is the template generated with afﬁne deformation thus the image content is not the same. In the artiﬁcial features (f), the bright and dark spots simulate the exudate and hemorrhage, respectively. The width of vessels in the circled area is enlarged. (a) Normal. (b) Afﬁne deformation. (c) Gaussian noise. (d) Blur. (e) Brightness. (f) Artiﬁcial features. the RMS error is less than 8 pixels. The accuracy of ASIFT decreases signiﬁcantly at higher degradation levels of noise, blur, and artifacts, due to feature-point instability. The global MI registration method cannot always converge to the correct afﬁne transformation parameters using such small templates, thus it has a low success rate even without degradations. The performance further declines in high-level degradations of artifacts and afﬁne. RetinaMatch has a success rate of 100% in most sequences and degradation levels, except the high-level afﬁne deformation. As described above, the real-world afﬁne deformation would be less than level 3. The improvement of RetinaMatch efﬁciency over global MI depends on the size difference between two matched images. In this experiment, the average runtime of RetinaMatch is around 50% less than that of global MI, since it narrows the search domain of the MI optimization signiﬁcantly. The computation of feature points in ASIFT is expensive and it takes four times longer than RetinaMatch. ASIFT is selected for comparison because it can generate more robust feature points than SIFT. Fig. 4. Examples of highest level degradations in each sequence. Please note that (b) is the template generated with afﬁne deformation thus the image content is not the same. In the artiﬁcial features (f), the bright and dark spots simulate the exudate and hemorrhage, respectively. The width of vessels in the circled area is enlarged. (a) Normal. (b) Afﬁne deformation. (c) Gaussian noise. (d) Blur. (e) Brightness. (f) Artiﬁcial features. B. In Vivo D-eye Data and Full Fundus Image TABLE II SUCCESS RATES OF COARSE LOCALIZATION PER DEGRADATION LEVEL and vessel width changes (enlarge/shrink vessel regions). Fig. 4 provides examples of the highest level degradation in each sequence. For each sequence and degradation level, we create 100 matching image pairs as described above. All degradations are applied to the template in each pair. Fig. S22 shows template examples of the highest degradation in each sequence. The coarse localization achieves high success rates across the dataset in different degradations, with the exception of the highest level of linear deformation sequence. However, the limitation to smaller eye rotation angle is physiologically based. The human eye has a limited range of torsional rotation with respect to the visual axis [41]. Checking a large set of data, we ﬁnd the real afﬁne deformation in the adapter-based optics imaging is less than level three (rotation/shear: 15◦/0.2). i i This experiment is a case study with a series of D-eye data captured from one person with a healthy retina. We converted the iphone 6 to a fundus camera with D-eye, then collected the data in a dim room to provide a larger pupil and proper image contrast. The eyeball was free to rotate which allowed us to obtain images covering different regions of the retina. The collected D-eye images have an average FOV of 4◦and a resolution of about 50 pixels/degree. The full fundus image is taken with a Kowa Nonmyd alpha-D III retinal camera, as shown in Fig. 1(a). It has a 45◦FOV with a resolution of 75 pixels/degree. The D-eye images are around 0.7% of the full image. Captured with different devices, the brightness and contrast varies greatly between the image pair to be matched. We ﬁrst validate our method by matching 100 D-eye tem- plate images onto the full image. The ASIFT and global MI methods are also implemented. Additionally, we add patho- logical artiﬁcial features on the 100 D-eye templates to test the algorithm robustness to retina pathological changes. The accuracy of the template matching is evaluated using target registration error (TRE) [44]. For each template, four corre- sponding landmarks are selected by an trained observer, two trained observers then selected the corresponding landmarks and vessel width changes (enlarge/shrink vessel regions). Fig. 4 provides examples of the highest level degradation in each sequence. For each sequence and degradation level, we create 100 matching image pairs as described above. All degradations are applied to the template in each pair. Fig. IV. EXPERIMENTS The experiment is performed over 100 matching Additional experiments were carried out to test the proposed coarse localization under different image degrada- tions. Five degradation types in ﬁve levels are considered as follows (images are in double format ∈[0, 1]): afﬁne transform with the rotation/shear parameter of {5◦/0.1,10◦/ 0.2,15◦/0.2,15◦/0.3,20◦/0.3}; additive Gaussian noise with standard deviation varied from 10% to 50% of the pixel value; image blurring with Gaussian kernels with stan- dard deviation of {0.5,1,1.5,2,2.5}; intensity changes of {4%,8%,12%,16%,20%} of graylevels in the image, which is the nonlinear brightness change; add artiﬁcial pathological features of 1-5 levels with increasing amount and size, such as the spot of exudate (bright spots), hemorrhage (dark spots) B. In Vivo D-eye Data and Full Fundus Image D-eye is a typical adapter-based optical system which can convert the digital camera on smartphones to a fundus camera (https://www.d-eyecare.com/). Fig. 6 show several examples of D-eye images. The relatively small FOV of D-eye can be useful to monitor the retinal health over time with comparison to a wide FOV baseline image taken at the ophthalmology clinic. With our algorithmic approach, the captured D-eye images can be matched onto the full image for automatic comparison. The latest data with retina changes can also replace the original area on the full image, maintaining a record of longitudinal changes. In this way, it offers the opportunity for a quick overall retina analysis outside the clinic, with automatic diagnostic approaches such as described in [42] and [43]. TABLE II SUCCESS RATES OF COARSE LOCALIZATION PER DEGRADATION LEVEL TABLE II SUCCESS RATES OF COARSE LOCALIZATION PER DEGRADATION LEVEL TABLE II SUCCESS RATES OF COARSE LOCALIZATION PER DEGRADATION LEVEL S22 shows template examples of the highest degradation in each sequence. The coarse localization achieves high success rates across the dataset in different degradations, with the exception of the highest level of linear deformation sequence. However, the limitation to smaller eye rotation angle is physiologically based. The human eye has a limited range of torsional rotation with respect to the visual axis [41]. Checking a large set of data, we ﬁnd the real afﬁne deformation in the adapter-based optics imaging is less than level three (rotation/shear: 15◦/0.2). This experiment is a case study with a series of D-eye data captured from one person with a healthy retina. We converted the iphone 6 to a fundus camera with D-eye, then collected the data in a dim room to provide a larger pupil and proper image contrast. The eyeball was free to rotate which allowed us to obtain images covering different regions of the retina. The collected D-eye images have an average FOV of 4◦and a resolution of about 50 pixels/degree. The full fundus image is taken with a Kowa Nonmyd alpha-D III retinal camera, as shown in Fig. 1(a). It has a 45◦FOV with a resolution of 75 pixels/degree. The D-eye images are around 0.7% of the full image. Captured with different devices, the brightness and contrast varies greatly between the image pair to be matched. We ﬁrst validate our method by matching 100 D-eye tem- plate images onto the full image. The ASIFT and global MI methods are also implemented. Additionally, we add patho- logical artiﬁcial features on the 100 D-eye templates to test the algorithm robustness to retina pathological changes. The accuracy of the template matching is evaluated using target registration error (TRE) [44]. For each template, four corre- sponding landmarks are selected by an trained observer, two trained observers then selected the corresponding landmarks 2) Validation of the Template Matching: We examine Reti- naMatch’s ﬁnal performance under the same sequences and degradations described earlier, but with two additional tem- plate matching approaches: feature-based ASIFT and global MI registration. The success rate of different methods are presented in Fig. 5, where the successful matches are that GONG et al.: RETINAMATCH: EFFICIENT TEMPLATE MATCHING OF RETINA IMAGES 2001 Fig. 5. Performance of template matching methods under different image degradations. In each, the x-axis stands for the increasing levels of image degradation, ranging from 0 (no degradation) to 5 (highest). TABLE II SUCCESS RATES OF COARSE LOCALIZATION PER DEGRADATION LEVEL The y-axis stands for the percentage of successful matches with RMS error less than 8 pixels. All degradations have 100% success rate in RetinaMatch except three high-level afﬁne deformations. (a) ASIFT. (b) Global MI. (c) RetinaMatch. Fig. 5. Performance of template matching methods under different image degradations. In each, the x-axis stands for the increasing levels of image degradation, ranging from 0 (no degradation) to 5 (highest). The y-axis stands for the percentage of successful matches with RMS error less than 8 pixels. All degradations have 100% success rate in RetinaMatch except three high-level afﬁne deformations. (a) ASIFT. (b) Global MI. (c) RetinaMatch. RetinaMatch. TABLE III TARGET REGISTRATION ERROR (TRE) OF TEMPLATE MATCHING METHODS IN E Fig. 6. Features of images to be stitched in the top three dimensional space. Each small black dot indicates one mapped image. The colored dots in red circles show two selected samples (red) with their near- est three neighbors (blue). Note the distance is measured in the top 20 dimensional space. panoramic image allows the going to the clinic for the Inhabitants of remote area professional fundus camera this technique. 1) Full Image Mosaicking is mosaicked with 20 D-ey stitching method. Based o and other limitations of th covering the region around tation, we used the ﬁrst 20 computing the image distan Fig. 6 illustrates the distrib of the features. From the t see the nearest three neig the low dimensional space image space. In the image registration method is appl the mosaicking result with TABLE III TARGET REGISTRATION ERROR (TRE) OF TEMPLATE MATCHING METHODS IN EXPERIMENT 2 TABLE III TARGET REGISTRATION ERROR (TRE) OF TEMPLATE MATCHING METHODS IN EXPERIMENT 2 panoramic image allows the use of this device at home without going to the clinic for the full fundus image as the baseline. Inhabitants of remote areas without local eye clinics having professional fundus camera facilities can beneﬁt greatly from this technique. Fig 6 Features of images to be stitched in the top three dimensional 1) Full Image Mosaicking : The full image in this experiment is mosaicked with 20 D-eye images using the proposed image stitching method. Based on no training for the D-eye user and other limitations of the procedure, we collected images covering the region around the optic disc. TABLE II SUCCESS RATES OF COARSE LOCALIZATION PER DEGRADATION LEVEL In the implemen- tation, we used the ﬁrst 20 dimensions of the features when computing the image distances in the low-dimensional space. Fig. 6 illustrates the distribution of the ﬁrst three dimensions of the features. From the two examples in the ﬁgure, we can see the nearest three neighbors of the selected sample in the low dimensional space also have a large overlap in the image space. In the image patch registration, the MI-based registration method is applied. The last row of Fig. 7 shows the mosaicking result with the proposed method. The MI of the top three candidate neighbors are validated to be effective to selecting the correct neighbor. The stitched full image has a 10◦FOV with the same resolution as the D-eye templates. The image blending is not our focus in this paper and the mosaicked image is not perfectly seamless. Fig. 6. Features of images to be stitched in the top three dimensional space. Each small black dot indicates one mapped image. The colored dots in red circles show two selected samples (red) with their near- est three neighbors (blue). Note the distance is measured in the top 20 dimensional space. from the full image independently. To obtain TRE for each image pair, we compute the root mean square of the distance between the transformed landmark points and the landmarks selected by two trained observers. The TRE results of Reti- naMatch (coarse localization and ﬁnal results), ASIFT and global MI are shown in Table III. Table III lists the success rate, the mean and standard deviation of TRE of successful matches and inter-observer variability. The success rate is the percentage of successful matching pairs with TRE less than 6 pixels. RetinaMatch can reach an accuracy of less than 4-pixel TRE with the observer variability, while the ASIFT and global MI cannot match the D-eye image successfully. from the full image independently. To obtain TRE for each image pair, we compute the root mean square of the distance between the transformed landmark points and the landmarks selected by two trained observers. The TRE results of Reti- naMatch (coarse localization and ﬁnal results), ASIFT and global MI are shown in Table III. Table III lists the success rate, the mean and standard deviation of TRE of successful matches and inter-observer variability. The success rate is the percentage of successful matching pairs with TRE less than 6 pixels. TABLE II SUCCESS RATES OF COARSE LOCALIZATION PER DEGRADATION LEVEL RetinaMatch can reach an accuracy of less than 4-pixel TRE with the observer variability, while the ASIFT and global MI cannot match the D-eye image successfully. 2) Template Matching: Similar to experiment 2, we validate our method by matching 100 D-eye templates with and without pathological artiﬁcial features onto the mosaicked image. The images used for the mosaicking are not contained in the 100 template test set. The TRE results are shown in Table IV. The TRE of successful matches is less than 8 pixels. RetinaMatch can match 96% of image pairs without artifacts and 94% of image pairs with artifacts. The TRE results of success matches were not much different from the observer variability. On the other hand, ASIFT cannot ﬁnd the alignment position since the detected feature points are not sufﬁcient for matching. The MI approach has a low rate C. In Vivo D-eye Data and Mosaicked Full Image IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 38, NO. 8, AUGUST 2019 mage covers the original area and is boxed with magenta lines. Fig. 7. Examples of RetinaMatch results with and without artifacts. The ﬁrst two rows are results of experiment 2 The mapped template on the full image covers the original area and is boxed with magenta lines. of success as well, which has a high probability to cause mis-detection of emerging changes. Fig. 7 shows examples of RetinaMatch matching results with and without artifacts in the second and third experiments. linear deformation exceeding the RetinaMatch limit, therefore we can ignore the poor performance over the third-level afﬁne degradation. To our knowledge, this is the ﬁrst report addressing template matching in retina images whose template contains unconstrained small retinal areas rather than a speciﬁc object. Further algorithm testing is needed on the smartphone or other low cost fundus imaging platforms as all current testing has been limited to a PC workstation. IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 38, NO. 8, AUGUST 2019 IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 38, NO. 8, AUGUST 2019 2002 2002 IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 38, NO. 8, AUGUST 2019 TABLE IV TARGET REGISTRATION ERROR (TRE) OF TEMPLATE MATCHING METHODS IN EXPERIMENT 3. THE SUCCESS RATE OF ASIFT IS 0 BECAUSE THE TEMPLATE CONTAIN AN INADEQUATE NUMBER OF FEATURES. THE SUCCESS RATE OF MI IS ALSO LOW BECAUSE THE OPTIMIZATION GETS STUCK IN LOCAL MINIMA. IN CONTRAST, RETINAMATCH HAS A CONSISTENTLY HIGH SUCCESS RATE Fig. 7. Examples of RetinaMatch results with and without artifacts. The ﬁrst two rows are results of experiment 2 and the third row is experiment 3. The mapped template on the full image covers the original area and is boxed with magenta lines. of success as well, which has a high probability to cause linear deformation exceeding the RetinaMatch limit, therefore TABLE IV TABLE IV TARGET REGISTRATION ERROR (TRE) OF TEMPLATE MATCHING METHODS IN EXPERIMENT 3. THE SUCCESS RATE OF ASIFT IS 0 BECAUSE THE TEMPLATE CONTAIN AN INADEQUATE NUMBER OF FEATURES. THE SUCCESS RATE OF MI IS ALSO LOW BECAUSE THE OPTIMIZATION GETS STUCK IN LOCAL MINIMA. IN CONTRAST, RETINAMATCH HAS A CONSISTENTLY HIGH SUCCESS RATE TABLE IV TARGET REGISTRATION ERROR (TRE) OF TEMPLATE MATCHING METHODS IN EXPERIMENT 3. THE SUCCESS RATE OF ASIFT IS 0 BECAUSE THE TEMPLATE CONTAIN AN INADEQUATE NUMBER OF FEATURES. THE SUCCESS RATE OF MI IS ALSO LOW BECAUSE THE OPTIMIZATION GETS STUCK IN LOCAL MINIMA. IN CONTRAST, RETINAMATCH HAS A CONSISTENTLY HIGH SUCCESS RATE Fig. 7. Examples of RetinaMatch results with and without artifacts. The ﬁrst two rows are results of experiment 2 and the third row is experiment 3 The mapped template on the full image covers the original area and is boxed with magenta lines. Fig. 7. Examples of RetinaMatch results with and without artifacts. The ﬁrst two rows are results of experiment 2 and the third row is experiment 3. The mapped template on the full image covers the original area and is boxed with magenta lines. Fig. 7. Examples of RetinaMatch results with and without artifacts. The ﬁrst two rows are results of experiment 2 and the third row is experimen The mapped template on the full image covers the original area and is boxed with magenta lines. results with and without artifacts. The ﬁrst two rows are results of experiment 2 and the third row is experiment 3. C. In Vivo D-eye Data and Mosaicked Full Image In this experiment we match the D-eye templates onto the full image mosaicked with D-eye images. Using the stitched GONG et al.: RETINAMATCH: EFFICIENT TEMPLATE MATCHING OF RETINA IMAGES Qian, “Human visual system-based fundus image quality assessment of portable fun- dus camera photographs,” IEEE Trans. Med. Imag., vol. 35, no. 4, pp. 1046–1055, Apr. 2016. [2] L. Shi, H. Wu, J. Dong, K. Jiang, X. Lu, and J. Shi, “Telemedicine for detecting diabetic retinopathy: A systematic review and meta-analysis,” Brit. J. Ophthalmology, vol. 99, no. 6, pp. 823–831, Jun. 2015. [3] I. N. Figueiredo, S. Kumar, C. M. Oliveira, J. D. Ramos, and B. Engquist, “Automated lesion detectors in retinal fundus images,” Comput. Biol. Med., vol. 66, pp. 47–65, Nov. 2015. p pp [4] R. Kawasaki et al., “Retinal vessel diameters and risk of hypertension: The multiethnic study of atherosclerosis.,” J. Hypertension, vol. 27, no. 12, pp. 93–2386, Dec. 2009. [5] N. Panwar et al., “Fundus photography in the 21st century—A review of recent technological advances and their implications for worldwide healthcare,” Telemed. e-Health, vol. 22, no. 3, pp. 198–208, Mar. 2016. [6] W. Fink, M. A. Tarbell, and K. Garcia, “Smart ophthalmics: The future in tele-ophthalmology has arrived,” Proc. SPIE, vol. 9836, May 2016, Art. no. 98360W. [7] K. Roesch, T. Swedish, and R. Raskar, “Automated retinal imaging and trend analysis—A tool for health monitoring,” Clin. Ophthalmology, vol. 11, pp. 1015–1020, May 2017. There are different kinds of retina lesions that can be screened with portable fundus cameras. In the medical exam- ple of monitoring hypertension, the larger arteries constrict and the venous vessels enlarge in diameter [4]. For exam- ple, the larger blood vessel cross-sectional diameter is about 20 pixels in the case study, and a change with hypertension will be in the range of 10-60%, so we are looking for over 2-pixel changes from baseline over time. In Tables III and IV, the TRE is shown to be extremely low and most errors are below 2 pixels (1.8 arcmins) excluding observer variability. With advanced trend analytics [45], we can expect template match- ing errors to be well below a threshold of clinical signiﬁcance. For more precise vessel width measurement, RetinaMatch can be combined with vessel segmentation, as described in our previous publication [46]. The vessels of interest can be located on the current templates and the corresponding vessel width is then obtained by segmentation around the mapped location. GONG et al.: RETINAMATCH: EFFICIENT TEMPLATE MATCHING OF RETINA IMAGES Note the vessel segmentation here is applied on very small retina patches (20 × 20 pixels), which is more robust and accurate than segmentation of wide FOV retina images. The segmentation error in [46] is less than 1 pixel, which has been presented using D-eye images. Xu et al. [47] proposed the vessel width segmentation and measurement on retina imaging acquired from the low quality fundus camera as well. They also report similar 1-pixel accuracy. However, the imaging device they used produced higher quality retinal images, having ﬁve times larger FOV than the D-eye. The biomarkers of abusive head trauma (AHT) is another example. The most common retinal manifestation of AHT is multiple [8] C. A. Ludwig, “The future of automated mobile eye diagnosis,” Byers Eye Inst., Stanford Univ. School Med., Palo Alto, CA, USA, Tech. Rep. Journal MTM 5:2:44-50, 2016. doi: 10.7309/jmtm.5.2.7. [9] H. Yu et al., “Fast localization and segmentation of optic disk in retinal images using directional matched ﬁltering and level sets,” IEEE Trans. Inf. Technol. Biomed., vol. 16, no. 4, pp. 644–657, Jul. 2012. [10] X. Zhang et al., “Exudate detection in color retinal images for mass screening of diabetic retinopathy,” Med. Image Anal., vol. 18, no. 7, pp. 1026–1043, Oct. 2014. [11] A. D. Mora, J. Soares, and J. M. Fonseca, “A template matching technique for artifacts detection in retinal images,” in Proc. 8th Int. Symp. Image Signal Process. Anal. (ISPA), Sep. 2013, pp. 717–722. [12] C. V. Stewart, C.-L. Tsai, and B. Roysam, “The dual-bootstrap iterative closest point algorithm with application to retinal image registration,” IEEE Trans. Med. Imag., vol. 22, no. 11, pp. 1379–1394, Nov. 2003. [13] M. Sofka and C. V. Stewart, “Retinal vessel centerline extraction using multiscale matched ﬁlters, conﬁdence and edge measures,” IEEE Trans. Med. Imag., vol. 25, no. 12, pp. 1531–1546, Dec. 2006. g pp [14] J. Xu, O. Chutatape, E. Sung, C. Zheng, and P. C. T. Kuan, “Optic disk feature extraction via modiﬁed deformable model technique for glaucoma analysis,” Pattern Recognit., vol. 40, no. 7, pp. 2063–2076, Jul. 2007. [15] I. N. Figueiredo et al., “Automated retina identiﬁcation based on mul- tiscale elastic registration,” Comput. Biol. Med., vol. 79, pp. 130–143, Dec. 2016. [16] I. N. Figueiredo, J. S. Neves, S. Moura, C. M. Oliveira, and J. D. Ramos, “Pattern classes in retinal fundus images based on function norms,” in Proc. Int. Symp. Comput. GONG et al.: RETINAMATCH: EFFICIENT TEMPLATE MATCHING OF RETINA IMAGES 2003 are independent of various datasets in the implementation of RetinaMatch, which makes it easier to translate our method to other similar imaging device besides D-eye. retinal hemorrhages in multiple layers of the retina [48]. Matching the captured images onto the full retina image, The hemorrhagic spots can be easily segmented after the subtraction of the current retina regions and previous status. The AHT then can be recognized automatically when such spots are detected with portable fundus cameras. The evaluation of the RetinaMatch accuracy is difﬁcult in experiment 2 and 3 without ground truth. Since the goal of template matching is providing accurate alignment for down- stream analysis, we use TRE as the metric. Compared with entropy based measures or the similarity measure itself, TRE measures the result intuitively in pixels and is independent of different regularization methods. RetinaMatch may be used in other medical image applica- tions for template matching. For example, in the case of endo- scopic guidance of therapy by a surgical robot [49], the current limited-sized FOV can be matched onto the panorama for endoscope localization. Thus, this image template matching technique can be used to create a more reliable closed-loop control for the robot arm and surgical tool guidance. The remote monitoring of retina health with template matching is the ﬁrst medical application to be proposed with RetinaMatch. Tele-ophthalmology is a promising application since many diseases are manifested at an early stage that are detectable with optical imaging of the retina. Because early stage retinal diseases do not present with symptoms, routine screening is important for early detection, which requires both high sensitivity and even higher speciﬁcity. The adapter-based optics and the digital cameras from smart phones provide an efﬁcient and economic approach to capture retina images reg- ularly at home. The images of the current state can be mapped with RetinaMatch and then compared with the previous state. With regular screening, the process of lesion formation and therapeutic treatment can be monitored over time. In the experiment, D-eye is chosen just as one low-cost example among many others with small FOV on undilated pupils [5]. Similar fundus imaging techniques can also be implemented in emerging commercial VR, AR, and mixed reality headsets that will be widespread in the future. [1] S. Wang, K. Jin, H. Lu, C. Cheng, J. Ye, and D. V. CONCLUSION AND DISCUSSION We present a new template matching method, RetinaMatch, which can be used in remote retina health monitoring with affordable imaging devices. A PCA-based coarse localization method is proposed to provide a good initialization for the MI-based registration in the template matching. In this way, RetinaMatch can obtain an accurate afﬁne transformation between the image pair with poor quality and large size difference. As demonstrated in the simulation experiment, RetinaMatch does not handle templates with large afﬁne deformations, with the success rate decreasing at level 4 and 5 in Fig. 5. Importantly, the template image captured by adapter-based optics with general operation will not have a To validate RetinaMatch, experiments using both human datasets with simulation and in vivo retina images from a case study were performed. Experiments with simulated datasets allowed evaluation of the accuracy and robustness of RetinaMatch to different levels and sequences of degradations. The in vivo case study ensures that our method can be applied using a consumer product. It was observed that RetinaMatch provided superior performance under different image condi- tions over standard ASIFT and MI algorithms. The parameters, such as the offset f = 10, f = 5 and the dimension d = 20, GONG et al.: RETINAMATCH: EFFICIENT TEMPLATE MATCHING OF RETINA IMAGES GONG et al.: RETINAMATCH: EFFICIENT TEMPLATE MATCHING OF RETINA IMAGES 86, no. 3, pp. 210–215, Jun. 2007. [39] B. Schölkopf, A. Smola, and K.-R. Müller, “Kernel principal component analysis,” in Proc. Int. Conf. Artif. Neural Netw. New York, NY, USA: Springer, Oct. 1997, pp. 583–588. [40] J. B. Tenenbaum, V. de Silva, and J. C. Langford, “A global geometric framework for nonlinear dimensionality reduction,” Science, vol. 290, no. 5500, pp. 2319–2323, Dec. 2000. [24] E. Liberty, F. Woolfe, P.-G. Martinsson, V. Rokhlin, and M. Tygert, “Randomized algorithms for the low-rank approximation of matri- ces,” Proc. Nat. Acad. Sci. USA, vol. 104, no. 51, pp. 20167–20172, Dec. 2007. pp [41] L. J. Van Rijn, “Torsional eye movements in humans,” Investigational New Drugs-Invest New Drug, Jan. 1994. [25] N. Halko, P. G. Martinsson, and J. A. Tropp, “Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions,” SIAM Rev., vol. 53, no. 2, pp. 217–288, 2011. [42] T. Walter, J.-C. Klein, P. Massin, and A. Erginay, “A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in color fundus images of the human retina,” IEEE Trans. Med. Image, vol. 21, no. 10, pp. 1236–1243, Oct. 2002. [26] N. B. Erichson, A. Mendible, S. Wihlborn, and J. N. Kutz, “Randomized nonnegative matrix factorization,” Pattern Recognit. Lett., vol. 104, pp. 1–7, Mar. 2018. pp [43] V. Gulshan et al., “Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus pho- tographs,” J. Amer. Med. Assoc., vol. 316, no. 22, pp. 2402–2410, 2016. pp [27] Structured Analysis of the Retina. Accessed: May 15, 2018. [Online]. Available: http://www.ces.clemson.edu/~ahoover/stare/ [28] F. R. S. K. Pearson, “LIII. On lines and planes of closest ﬁt to systems of points in space,” London, Edinburgh, Dublin Philosoph. Mag. J. Sci., vol. 2, no. 11, pp. 559–572, 1901. [44] J. M. Fitzpatrick, J. B. West, and C. R. Maurer, Jr., “Predicting error in rigid-body point-based registration,” IEEE Trans. Med. Imag., vol. 17, no. 5, pp. 694–702, Oct. 1998. [29] H. Hotelling, “Analysis of a complex of statistical variables into principal components,” J. Educ. Psychol., vol. 24, no. 6, p. 417, 1933. [45] X. Dai and M. Bikdash, “Trend analysis of fragmented time series for mhealth apps: Hypothesis testing based adaptive spline ﬁltering method with importance weighting,” IEEE Access, vol. 5, pp. 27767–27776, 2017. [30] J. N. Kutz, S. L. Brunton, B. W. Brunton, and J. L. GONG et al.: RETINAMATCH: EFFICIENT TEMPLATE MATCHING OF RETINA IMAGES Modeling Objects Represented Images. Cham, Switzerland: Springer, 2014, pp. 95–105. p g pp [17] Y. Wang, J. Shen, W. Liao, and L. Zhou, “Automatic fundus images mosaic based on SIFT feature,” in Proc. 3rd Int. Congr. Image Signal Process. (CISP), vol. 6, Oct. 2010, pp. 2747–2751. [18] C. L. Tsai, C.-Y. Li, G. Yang, and K.-S. Lin, “The edge-driven dual- bootstrap iterative closest point algorithm for registration of multimodal ﬂuorescein angiogram sequence,” IEEE Trans. Med. Imag., vol. 29, no. 3, pp. 636–649, Mar. 2010. IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 38, NO. 8, AUGUST 2019 2004 [19] G. Wang, Z. Wang, Y. Chen, and W. Zhao, “Robust point matching method for multimodal retinal image registration,” Biomed. Signal Process. Control, vol. 19, pp. 68–76, May 2015. [35] Y. Fu, C. Wang, Y. Wang, B. Chen, Q. Peng, and L. Wang, “Automatic detection of longitudinal changes for retinal fundus images based on low-rank decomposition,” J. Med. Imag. Health Informat., vol. 8, no. 2, pp. 284–294, Feb. 2018. [20] C. Hernandez-Matas, X. Zabulis, and A. A. Argyros, “Retinal image registration based on keypoint correspondences, spherical eye modeling and camera pose estimation,” in Proc. 37th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. (EMBC), Aug. 2015, pp. 5650–5654. [36] P. Thevenaz and M. A. Unser, “Spline pyramids for intermodal image registration using mutual information,” Proc. SPIE, vol. 3169, Oct. 1997, pp. 236–248. Med. Biol. Soc. (EMBC), Aug. 2015, pp. 5650–5654. [37] D. Mattes, D. R. Haynor, H. Vesselle, T. K. Lewellen, and W. Eubank, “PET-CT image registration in the chest using free-form deformations,” IEEE Trans. Med. Imag., vol. 22, no. 1, pp. 120–128, Jan. 2003. [21] K. J. Friston, J. Ashburner, C. D. Frith, J.-B. Poline, J. D. Heather, and R. S. J. Frackowiak, “Spatial registration and normalization of images,” Hum. Brain Mapping, vol. 3, no. 3, pp. 165–189, Mar. 1995. Hum. Brain Mapping, vol. 3, no. 3, pp. 165–189, Mar. 19 [38] J.-M. Morel and G. Yu, “ASIFT: A new framework for fully afﬁne invari- ant image comparison,” SIAM J. Imag. Sci., vol. 2, no. 2, pp. 438–469, 2009. [22] A. V. Cideciyan, “Registration of ocular fundus images: An algorithm using cross-correlation of triple invariant image descriptors,” IEEE Eng. Med. Biol. Mag., vol. 14, no. 1, pp. 52–58, Jan./Feb. 1995. g pp [23] Y.-M. Zhu, “Mutual information-based registration of temporal and stereo retinal images using constrained optimization,” Comput. Methods Programs Biomed., vol. GONG et al.: RETINAMATCH: EFFICIENT TEMPLATE MATCHING OF RETINA IMAGES Proctor, Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems, vol. 149. Philadelphia, PA, USA: SIAM, 2016. [46] C. Gong, J. P. Kelly, L. Trutoiu, B. Schowengerdt, S. Brunton, and E. Seibel, “Measurement of retinal vessel width in tele-ophthalmology for mobile health monitoring,” Investigative Ophthalmology Vis. Sci., vol. 59, no. 9, p. 4624, Jul. 2018. [31] N. B. Erichson, S. Voronin, S. L. Brunton, and J. N. Kutz, “Randomized matrix decompositions using R,” 2016, arXiv:1608.02148. [Online]. Available: https://arxiv.org/abs/1608.02148 [47] X. Xu et al., “Smartphone-based accurate analysis of retinal vascula- ture towards point-of-care diagnostics,” Sci. Rep., vol. 6, Oct. 2016, Art. no. 34603. p g [32] E. J. Candès, X. Li, Y. Ma, and J. Wright, “Robust principal component analysis?” J. ACM, vol. 58, no. 3, pp. 11–37, May 2011. [48] I. H. Yusuf, J. K. Barnes, T. H. Fung, J. S. Elston, and C. K. Patel, “Non-contact ultra-wideﬁeld retinal imaging of infants with suspected abusive head trauma,” Eye, vol. 31, no. 3, p. 353, Mar. 2017. [33] T. Bouwmans, S. Javed, H. Zhang, Z. Lin, and R. Otazo, “On the applications of robust PCA in image and video processing,” Proc. IEEE, vol. 106, no. 8, pp. 1427–1457, Aug. 2018. [34] A. Baghaie, R. M. D’souza, and Z. Yu, “Sparse and low rank decompo- sition based batch image alignment for speckle reduction of retinal OCT images,” in Proc. IEEE 12th Int. Symp. Biomed. Imag. (ISBI), Apr. 2015, pp. 226–230. [49] D. Hu, Y. Gong, E. J. Seibel, L. N. Sekhar, and B. Hannaford, “Semi- autonomous image-guided brain tumour resection using an integrated robotic system: A bench-top study,” Int. J. Med. Robot. Comput. Assist. Surg., vol. 14, no. 1, p. e1872, Feb. 2018.
https://openalex.org/W2955252037	https://leicester.figshare.com/articles/journal_contribution/Synthesizing_existing_evidence_to_design_future_trials_survey_of_methodologists_from_European_institutions_/10205030/1/files/18395459.pdf	English	null	Synthesizing existing evidence to design future trials: survey of methodologists from European institutions	Trials	2,019	cc-by	7,083	RESEARCH Open Access Abstract Background: ‘Conditional trial design’ is a framework for efficiently planning new clinical trials based on a network of relevant existing trials. The framework considers whether new trials are required and how the existing evidence can be used to answer the research question and plan future research. The potential of this approach has not been fully realized. Methods: We conducted an online survey among trial statisticians, methodologists, and users of evidence synthesis research using referral sampling to capture opinions about the conditional trial design framework and current practices among clinical researchers. The questions included in the survey were related to the decision of whether a meta-analysis answers the research question, the optimal way to synthesize available evidence, which relates to the acceptability of network meta-analysis, and the use of evidence synthesis in the planning of new studies. Results: In total, 76 researchers completed the survey. Two out of three survey participants (65%) were willing to possibly or definitely consider using evidence synthesis to design a future clinical trial and around half of the participants would give priority to such a trial design. The median rating of the frequency of using such a trial design was 0.41 on a scale from 0 (never) to 1 (always). Major barriers to adopting conditional trial design include the current regulatory paradigm and the policies of funding agencies and sponsors. Conclusions: Participants reported moderate interest in using evidence synthesis methods in the design of future trials. They indicated that a major paradigm shift is required before the use of network meta-analysis is regularly employed in the design of trials. Keywords: Conditional trial design, Sample size, Meta-analysis, Network of interventions for determining research gaps using systematic reviews [1]. Methods for informing aspects of trial design based on a pairwise meta-analysis have also been proposed and include powering a future trial based on a relevant exist- ing meta-analysis [2–4] or investigating how a future trial would alter the meta-analytic summary effect obtained thus far [5, 6]. These methods are limited to situations in which existing evidence consists of two in- terventions. When existing evidence forms a network of interventions, synthesis of available trials can be done using network meta-analysis. Network meta-analysis is increasingly used in health technology assessment (HTA) to summarize evidence and inform guidelines [7]. However, its potential to inform trial design has not re- ceived much attention. © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Synthesizing existing evidence to design future trials: survey of methodologists from European institutions Adriani Nikolakopoulou1* , Sven Trelle2, Alex J. Sutton3, Matthias Egger1 and Georgia Salanti1 Introduction Systematic reviews can identify knowledge gaps that may direct the research agenda toward questions that need further investigation. Knowledge gaps may arise when the available data are insufficient, or when there is no evidence at all that can answer a research question. Once identified, primary research (e.g., trials) may be designed and conducted to fill such gaps. Such considerations, along with implementation strat- egies, have appeared in the literature. The Agency of Healthcare Research and Quality developed a framework * Correspondence: nikolakopoulou.adriani@gmail.com 1Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland Full list of author information is available at the end of the article Switzerland Full list of author information is available at the end of the article Nikolakopoulou et al. Trials (2019) 20:334 https://doi.org/10.1186/s13063-019-3449-6 Nikolakopoulou et al. Trials (2019) 20:334 https://doi.org/10.1186/s13063-019-3449-6 Page 2 of 9 Page 2 of 9 Nikolakopoulou et al. Trials (2019) 20:334 Nikolakopoulou et al. Trials (2019) 20:334 Methodological developments that use network meta- analysis as a basis for further research [3, 8] have been recently collated to form a holistic framework for plan- ning future trials based on a network of interventions [9]. The framework, called ‘conditional trial design’, com- bines considerations relevant to both evidence synthesis and trial design; ‘conditional’ refers to the fact that the design of a new study depends (is conditional) on the existing evidence. The framework consists of three parts. The first part asks whether the existing evidence answers the research question. This part pertains to interpreting meta-analysis results, which is related to deciding whether existing evidence is conclusive, whether multiple testing is needed when a meta-analysis is regularly updated, and how to interpret evidence from multiple outcomes. The second part of the framework is related to how best to use the existing evidence to answer the research question. The third and last part of the framework addresses how to use the existing evidence to plan future research. The condi- tional trial design requires that the assumptions of net- work meta-analysis are plausible and that the credibility of the results is high. In the case of violation of the transitiv- ity assumption (that for each comparison there is an underlying true relative treatment effect which applies to all studies regardless of the treatments compared), or in the presence of studies with a high risk of bias, the exist- ing network of interventions would not provide reliable evidence and thus should not be used to inform the plan- ning of new studies. email to key personnel within each organization, which in- cluded a request to forward it to anyone within their organization who might be interested, or we sent email messages to a mailing list or individuals. We did not track whether an invited person completed the survey, and we sent no reminders. Survey design d d y g We designed an online questionnaire of 24 questions which would take around 15–20 min to complete using Survey Monkey (http://www.surveymonkey.com). We started with questions regarding principal affiliation, ex- perience with systematic reviews, meta-analysis, network meta-analysis, guidelines, clinical trials, and involvement in research funding decisions. Implementation of the framework on which we wanted to capture opinion would require a collaborative process between experi- enced researchers in the areas of evidence synthesis and trial design. Participants were therefore directed to one or both of the survey’s main parts, depending on their expertise, as shown schematically in Fig. 1. For the ma- jority of the questions, it was possible to select more than one answer. The full questionnaire is presented as Additional file 2. The survey was open between 10 October 2016 and 9 December 2016. Responses were collected an- onymously. A pilot version of the questionnaire was tested with three statisticians and two methodologists from the Clinical Trials Unit and Institute of Social and Preventive Medicine of the University of Bern. We conducted a survey of views on the feasibility of the conditional trial design among trial statisticians, methodologists (researchers developing methodology), and users of evidence synthesis research. To this aim, the survey included questions relevant to the three parts of the conditional trial design. In particular, our objec- tives were to capture opinions and current practices regarding: 1) the decision about whether a meta-analysis answers the research question (first part); 2) the accept- ability of network meta-analysis as a technique to enhance the evidence and answer the research question (second part); and 3) the use of evidence synthesis in the planning of future clinical research (third part). The first part of the survey concerned current prac- tices in deciding whether a meta-analysis answers the re- search question at hand. Only participants experienced in evidence synthesis and those who had been involved in deciding about funding clinical research were directed to this part. Certain questions asked participants to choose or report what they are actually doing, in prac- tice, while others asked participants to choose what they think should be done. Topics related to interpretation of the meta-analysis results, how multiple outcomes are in- tegrated, and issues of multiple testing in the context of a continuously updated meta-analysis. A separate section covered issues related to the acceptability of network meta-analysis. Invited participants The next part of the survey contained questions about the use of evidence synthesis, as pairwise or network meta-analysis, for the design of clinical trials. For all questions in this part, the term clinical trials referred to randomized, post-marketing (e.g., phase IV) controlled clinical trials. Participants experienced in clinical trials and those who declared involvement in funding deci- sions were directed to this part (Fig. 1). Some of the questions were formulated so that the participants answered them in their capacity as citizens who fund Our convenience sample consisted of researchers work- ing in Europe either in nonprofit organizations or in the pharmaceutical industry. We contacted researchers from the World Health Organization (WHO), 13 HTA agen- cies, 17 pharmaceutical companies or companies that prepare HTA submissions, and all clinical trial units in the UK, Norway, Switzerland, and Germany. The full list of contacted organizations can be found in Additional file 1. We sent a brief description and the link to the survey by Page 3 of 9 Nikolakopoulou et al. Trials (2019) 20:334 Nikolakopoulou et al. Trials Fig. 1 Schematic representation of the parts of the survey to which participants were directed according to their involvement in several aspects of systematic reviews, guidelines, and clinical trials production Fig. 1 Schematic representation of the parts of the survey to which participants were directed according to their involvement in several aspects of systematic reviews, guidelines, and clinical trials production Fig. 1 Schematic representation of the parts of the survey to which participants were directed according to their involvement in several aspects of systematic reviews, guidelines, and clinical trials production research (such as EU-funded clinical trials or other re- search funded by national funds through their taxation). post-hoc analysis, we used a Pearson’s Chi-squared test to examine whether level of experience with evidence synthesis and clinical trials was related to different views on the acceptability of network meta-analysis and partic- ipants’ likelihood to consider the use of conditional trial design. Whenever any expected frequency is less than 1 or at least 20% of cells had expected counts of 5 or less, a Fisher’s exact test was used instead of a Pearson’s Chi- squared test. The rest of the analyses were planned pro- spectively. All analyses were performed using Stata 14.1. Analysis We derived descriptive statistics as frequencies and per- centages for participants’ characteristics (affiliation, job role, experience in meta-analysis and clinical trials). Per- centages include missing responses in the denominator. Some questions allowed or requested free text answers by participants; we present some illustrative written quotes regarding participants’ willingness to consider a clinical trial design informed by meta-analysis and the biggest barriers to adopting such a design. Where a vis- ual analogue scale was used and for the question of rat- ing clinical research proposals submitted for funding, median, 25th, and 75th percentiles are presented. As a Participants characteristics In total, 76 researchers completed the survey, of whom 29 (38%) were affiliated with a clinical trial unit and 15 (20%) with the pharmaceutical industry. Fifty- Nikolakopoulou et al. Trials (2019) 20:334 Page 4 of 9 network meta-analysis. Among the 68 participants, 15 (22%) preferred network to pairwise meta-analysis. A total of 25 participants (37%) indicated that network meta-analysis should be considered when there are either no or very few direct studies (Table 1). Eight par- ticipants suggested other approaches as indicated by two of their responses: “I would look at both direct and in- direct analysis” and “I see the evaluation as one process and don’t want to disregard one versus the other”. three participants (70%) had performed and/or evalu- ated a systematic review, 46 (61%) had designed a clin- ical trial, and 36 participants (47%) had been involved in decisions about funding clinical research including reviewing grant applications. The involvement of researchers in trials, meta-analyses, and network meta-analyses varied. Sixty-three researchers (83%) had been involved in at least one clinical trial, over half of whom (33) had been involved in more than 20 trials. Sixty-one researchers (80%) reported involvement in at least one pairwise meta-analysis, while 34 (45%) had partici- pated in one or more network meta-analyses. The complete characteristics of participants can be found in Table 1. When asking participants about their interpretation in a more specific scenario, such as the one presented in Fig. 2, nearly twice as many participants indicated that they trusted network meta-analysis more than pairwise meta-analysis when the results are more precise (23 versus 13 participants). A considerable subgroup of par- ticipants claimed that they did not know what to con- clude, or they did not respond to the question (32 total participants, 48%) (Fig. 2). Does the existing evidence answer the research question? Among the 76 participants, 68 (89%) had experience in evidence synthesis and answered questions related to the first part of the conditional trial design framework which is relevant to the interpretation of meta-analysis results (Fig. 1). How to use the existing evidence to plan future research? Among the total of 76 participants, 43 researchers expe- rienced in clinical trial design (57%) were directed to questions related to the third part of the conditional trial design, which is relevant to practices and opinions about using meta-analysis to inform aspects of the design of future clinical trials (Fig. 1). Practices of using meta-analysis in the design of clinical trials Participants rated their use of evidence synthesis in the design of clinical trials on a visual rating scale from 0 (never) to 1 (always). The median value was 0.44 (25th percentile 0.22, 75th percentile 0.67). A total of 29 par- ticipants (67%) reported using meta-analyses of previ- ous trials in the determination of other parameters involved in sample size calculations (such as standard deviations, baseline risk, and so on), 25 participants (58%) considered meta-analyses in defining alternative effect sizes in power calculations, and 22 (51%) used meta-analyses in the determination of health outcomes to be monitored (Table 1). When asked about the best among five approaches to resolve uncertainty regarding the best pharmaceutical treatment for a given condition, a three-arm randomized trial comparing the two most promising interventions and standard treatment, and a network meta-analysis comparing all treatment alternatives were the most popular options (rating medians 2.0 and 1.5, respect- ively). The least favorable research design was a large international registry (rating median 5.0, Table 1). The rating frequencies for each research proposal are given in Additional file 3. Participants characteristics When asked about judging when a summary treatment effect is conclusive and when further research is needed, 39 of these 68 researchers (57%) examined the clinical importance of the summary effect, while slightly fewer (31) examined the statistical significance of the summary effect (Table 1). Most participants examining the statis- tical significance of the summary effect also examine its clinical importance (28 participants, 37%). Participants were asked about adjustment for multiple testing issues when a meta-analysis is updated with new studies. Twenty-two of the 68 participants (32%) indi- cated that adjustment for multiple testing is not required for a repeatedly updated meta-analysis, while 18 partici- pants (27%) reported that such an adjustment is re- quired. The rest (28 participants, 41%) either did not respond or indicated that they did not know. Partici- pants were also asked about interpreting evidence from multiple outcomes that bears upon a preference for one of two treatments. Among the 68 participants, 25 (37%) reported involving stakeholders in deciding which out- comes are more important, while 22 participants (32%) used methods described in the recommendations of the Grading of Recommendations Assessment, Development and Evaluation (GRADE) working group. How best to use the existing evidence to answer the research question? The 68 participants who had experience in evidence syn- thesis were directed to answer questions regarding the second part of the conditional trial design: how to use the existing evidence to answer the research question (Fig. 1). Asked whether they prefer network meta-analysis as an evidence synthesis method to pairwise meta-analysis, participants indicated a comparatively low preference for The 68 participants who had experience in evidence syn- thesis were directed to answer questions regarding the second part of the conditional trial design: how to use the existing evidence to answer the research question (Fig. 1). Asked whether they prefer network meta-analysis as an evidence synthesis method to pairwise meta-analysis, participants indicated a comparatively low preference for Page 5 of 9 Nikolakopoulou et al. Trials (2019) 20:334 Table 1 Opinions and practices of participants regarding evidence-based planning of future trials Question Possible answers Responses (%) What is your primary affiliation? Clinical trials unit 29 (38%) A funding body 3 (4%) Pharmaceutical industry 15 (20%) HTA/Cochrane/WHO 28 (37%) Missing 1 (1%) How do you judge whether a summary treatment effect provides conclusive evidence or whether further research is needed (more than one choice allowed)? I examine the statistical significance of the summary effect and its CI 31 (46%) I examine the clinical importance of the summary effect and its CI 39 (57%) I test whether future studies could change the statistical significance of the summary effect 7 (10%) I follow the GRADE guidelines for judging imprecision 19 (28%) Not involved in interpretation of meta-analysis results/other/missing 29 (43%) Do you think that network meta-analysis should be considered as the preferred evidence synthesis method instead of pairwise meta-analysis? Yes, network meta-analysis should always be preferred 15 (22%) No, network meta-analysis should not be considered 5 (7%) It should be considered only if there are no or few direct studies 25 (37%) Other/missing 23 (34%) According to your experience, results from relevant meta-analyses are considered to (more than one choice allowed): Define the alternative effect size in power calculations 25 (58%) Decide about the intervention in the comparator arm 19 (44%) Define other parameters involved in sample size calculations 29 (67%) Define health outcomes to be monitored 22 (51%) Other/missing 7 (16%) What do you think is the biggest barrier towards adopting the conditional trial design in designing trials? Question As a citizen supporting publicly funded research how would you rank (from 1 being the top priority to 5 being the least) the following proposals tackling the treatments for an important health condition? Consider also the cost for each research proposal (presented in parenthesis in arbitrary units). How best to use the existing evidence to answer the research question? Lack of training 6 (14%) Changing the paradigm of funders and researchers 16 (37%) Lack of good-quality meta-analyses 4 (9%) Other/missing 17 (40%) Question Research proposals Median (25th to 75th percentile) As a citizen supporting publicly funded research how would you rank (from 1 being the top priority to 5 being the least) the following proposals tackling the treatments for an important health condition? Consider also the cost for each research proposal (presented in parenthesis in arbitrary units). A well-powered three-arm randomized trial comparing the three most promising interventions (none of which is standard care) (100) 4.0 (3.0 to 5.0) A well-powered three-arm randomized trial comparing the two most promising interventions and standard treatment (90) 2.0 (1.0 to 2.0) A well-powered two-arm randomized trial comparing a newly launched treatment and standard treatment (70) 3.0 (2.0 to 4.0) A large registry involving many countries (40) 5.0 (3.5 to 5.0) A network meta-analysis comparing all available treatments using existing studies (10) 1.5 (1.0 to 3.0) The full text and questions are presented in Additional file 2 CI confidence interval, GRADE Grading of Recommendations Assessment, Development and Evaluation, HTA health technology assessment, WHO World Health Organization ions and practices of participants regarding evidence-based planning of future trials What is your primary affiliation? How do you judge whether a summary treatment effect provides conclusive evidence or whether further research is needed (more than one choice allowed)? Do you think that network meta-analysis should be considered as the preferred evidence synthesis method instead of pairwise meta-analysis? According to your experience, results from relevant meta-analyses are considered to (more than one choice allowed): Acceptability of sample size calculations based on an existing meta-analysis they were willing to consider it. When asked about rea- sons for not considering such a design, participants justi- fied their answers with arguments mainly associated with concerns about the reliability and validity of the meta-analysis as well as the paradigm of perceiving trials as independent pieces of evidence. Some sample answers are presented in Table 2. When asked to respond from the perspective as citizens supporting publicly funded re- search, 21 of the 43 participants (49%) indicated that pri- ority should be given to conditional trial design compared Twenty-six participants (60%) were aware of the meth- odology of explicitly incorporating results from a meta- analysis in the sample size calculation of a future trial (based on conditional power). Ten participants (23%) said they would consider the approach when planning a trial in the future and another 18 (42%) responded that they would possibly consider it. Half (22 participants, 51%) were aware of the methodology and indicated that Nikolakopoulou et al. Trials (2019) 20:334 Page 6 of 9 Fig. 2 Opinions among researchers on their interpretation of a hypothetical scenario where network meta-analysis provides conclusive evidence that treatment X is better than treatment S while pairwise meta-analysis indicates that further evidence is needed. The question was addressed to the subset of 68 ‘evidence synthesis-experienced’ participants Fig. 2 Opinions among researchers on their interpretation of a hypothetical scenario where network meta-analysis provides conclusive evidence that treatment X is better than treatment S while pairwise meta-analysis indicates that further evidence is needed. The question was addressed to the subset of 68 ‘evidence synthesis-experienced’ participants Fig. 2 Opinions among researchers on their interpretation of a hypothetical scenario where network meta-analysis provides conclusive evidence that treatment X is better than treatment S while pairwise meta-analysis indicates that further evidence is needed. The question was addressed to the subset of 68 ‘evidence synthesis-experienced’ participants analysis is to be preferred (Pearson’s Chi-squared test P value 0.003, Additional file 3). with conventional sample size calculations. Changing the paradigm that trials should be independent experiments was presented as the biggest barrier towards adopting such a trial design (16 participants, 37%) (Table 1). The willingness to consider the use of an existing meta-analysis to inform sample size calculations of a new study did not materially vary according to re- searchers’ experience in clinical trials or evidence syn- thesis (Additional file 3). Table 2 Key free text quotes from responses Medicine in the month of May in the years 1997, 2001, 2005, and 2009. According to their findings, only a small proportion of trial reports attempted to integrate their findings with existing evidence [11, 12, 15, 16]. Out of 446 trial protocols submitted to the UK ethics committees in 2009, only four (less than 1%) used a meta-analysis and 92 (21%) used previous studies to define the treatment difference sought [20]. A review of 1523 trials published from 1963 to 2004 showed that fewer than 25% of relevant previous randomized con- trolled trials were cited by subsequent randomized con- trolled trials [21]. From respondents who answered “No” or “Possibly” to the question “Would you be willing to consider a conditional trial design next time you plan a trial?” Regulators require each study to be ‘significant’ independently of others” • “Wonder whether it would be convincing to authorities” • “In the regulatory context, meta-analyses are typically NOT considered for approval decisions, at least not directly. (Typically). I would answer differently for publicly funded studies. A newish suggestion—most of our trials are phase II/III, where things are a little different” • “In the regulatory context, meta-analyses are typically NOT considered for approval decisions, at least not directly. (Typically). I would answer differently for publicly funded studies. A newish suggestion—most of our trials are phase II/III, where things are a little different” From respondents who answered “No” or “Possibly” to the question “Would you be willing to consider a conditional trial design next time you plan a trial?” • “Lots of examples where a large definitive trial has contradicted the results of a meta-analysis of smaller trials” • “Any meta-analysis is observational research” • “Because when you finalize the trial, the meta-analysis will be outdated. Your study should be a standalone trial” • “Not enough faith in the homogeneity/comparability of the studies” • “The assumptions behind a meta-analysis (homogeneity, no publication bias), are very rarely plausible, so a typical RCT has to offer a chance of providing a definitive conclusion on its own” • “The assumptions behind a meta-analysis (homogeneity, no publication bias), are very rarely plausible, so a typical RCT has to offer a chance of providing a definitive conclusion on its own” Funders of clinical trials often emphasize the import- ance of using existing evidence in grant applications [14, 22, 23]. Thirty-seven (77%) out of 48 trials funded by the National Institute for Health Research (NIHR) Health Technology Assessment program between 2006 and 2008 referenced a systematic review in the funding application; the percentage was 100% for trials funded in 2013 [24]. The interest of funders in research synthe- sis dates back to the 1990s when several organizations responsible for funding clinical research started to require systematic reviews of existing research as a pre- requisite for considering funding for new trials [14]. But as Clayton et al. point out, it is not clear to what extent and in which way funders expect evidence synthesis to be used [10]. Nasser et al. searched the websites of 11 research funding organizations and, while four of them require systematic reviews to show that new clinical trials are needed, only the NIHR requires reference to relevant systematic reviews [22]. We did not specifically survey bodies that fund clinical trials (such as the NIHR or the Swiss National Science Foundation). A survey of funding agencies along with a review of their guidance on how trialists should use existing evidence when designing and implementing new trials would be an important step forward. • “Clinical trials are perceived as independent pieces of evidence. There would need to be a major shift by regulators, HTA bodies and physicians for companies to design trials in the context of meta-analyses” • “Usually the context in which I work is of trials supporting applications for a license. Discussion Experienced researchers in evidence synthesis were more likely to have confidence in network meta-analysis. Among the 27 participants with experience in evidence synthesis who indicated that they either can perform network meta-analysis themselves or have been involved in systematic reviews with network meta-analysis, 11 (41%) responded that, in general, network meta-analysis is preferable to pairwise meta-analysis. Among the 41 participants with little or no experience with network meta-analysis, only four (10%) said that network meta- In this survey of methodologists based in Europe, partic- ipants reported low to moderate use of evidence synthe- sis methods in the design of future trials. Evidence synthesis is used for the design of around half of the trials. The information most used relates to the parame- ters required for sample size calculations and outcome definitions. Our results broadly agree with those of Clay- ton et al. who found that 50% of investigators who responded to their survey had used meta-analysis to Page 7 of 9 Page 7 of 9 Page 7 of 9 Nikolakopoulou et al. Trials (2019) 20:334 From respondents who replied “Other” to the question “What do you think is the biggest barrier towards adopting conditional trial design in designing trials?” • “Although trials can be planned to add just enough power to an existing meta-analysis, there is a high risk that such planning fails because of wrong assumptions, differences in study execution, or other reasons” • “Although trials can be planned to add just enough power to an existing meta-analysis, there is a high risk that such planning fails because of wrong assumptions, differences in study execution, or other reasons” • “It is flawed and too risky (why give an experimental drug in an underpowered study)” • “Guidelines from important regulatory and health economic agencies” • “Lack of dissemination” • “Skepticism as trials should be powered to stand alone, I would think. All other studies in the MA may not be comparable or of high quality” Our study has some limitations that render the generalizability of its results questionable. First, the sample size of our survey was 76 participants, which is relatively small; a bigger sample size would allow us to produce more precise estimates for the outcomes of interest. Furthermore, using referral or snowball sam- pling means that we could not estimate the response rate for our survey. Second, we cannot exclude the pos- sibility that the characteristics of participants systematic- ally differed from those who either did not receive the questionnaire or received it but decided not to partici- pate. Such nonresponse selection bias seems likely considering that a relatively high proportion of partici- pants knew about calculating sample size based on a meta-analysis (60%), despite the fact that the methods have only recently been developed [2, 8, 9] and, in our experience, are not widely used. This indicates that the • “It’s not necessarily logical” • “It’s not necessarily logical” inform a future trial [10]. The scope of the survey by Clayton et al. was similar to ours but it did not focus on issues pertaining to interpreting evidence synthesis and acceptability of network meta-analysis. Empirical evidence has shown lower uptake of sys- tematic reviews in planning new trials than the findings in the current survey and the survey by Clayton et al. [11–19]. Clarke et al. assessed reports of randomized trials published in Annals of Internal Medicine, BMJ, JAMA, The Lancet, and the New England Journal of Page 8 of 9 Nikolakopoulou et al. Funding g AN is supported by the Swiss National Science Foundation (Grant No. 179158). ME was supported by a special project funding (Grant No. 174281) from the Swiss National Science Foundation. GS received funding from a Horizon 2020 Marie-Curie Individual Fellowship (Grant no. 703254). The spon- sors had no role in the design, analysis, or reporting of this study. Acknowledgements The authors thank C. Ritter for his valuable editorial assistance and the three reviewers for their helpful comments that greatly improved this paper. This survey indicates a lack of consensus in aspects re- lated to the interpretation of meta-analysis results. None of the answers to the question regarding interpreting evidence from multiple outcomes was selected by more than about a third of participants. Participants also did not agree on the use of adjustment for multiple testing when a meta-analysis is updated. This lack of consensus is in line with the lack of agreement about using sequen- tial methods in the literature. Opinions range from regu- larly using sequential meta-analysis [27, 28], to adjusting for repeated updates in specific cases [29–31], to never correcting summary treatment effects using sequential methods [32]. Concerns about the reliability of meta- analysis affect the acceptability of the conditional trial design; we think, however, that such concerns are likely to diminish over time as meta-analysis is increasingly used for decision-making and guideline development. The second main pillar of skepticism towards the condi- tional trial design is the perception of trials as independ- ent experiments. It will be interesting to see whether this view will be challenged in the light of increasing awareness of research waste. Consent for publication Not applicable. Consent for publication Not applicable. Not applicable. From respondents who replied “Other” to the question “What do you think is the biggest barrier towards adopting conditional trial design in designing trials?” Trials (2019) 20:334 Page 8 of 9 Page 8 of 9 defining the alternative effect size, the intervention group risk, or by computing the conditional power of the planned trial. Further research on ways in which evi- dence synthesis can be efficiently used in the planning of new trials could use, and possibly combine, consider- ations from value of information analysis, adaptive de- sign methodology, and formal decision analytic methods. Funding agencies and journal editors could contribute to preventing waste by establishing concrete policies on the use of existing evidence when assessing requests for funding or publishing trials. participants were probably a well-informed sample of methodologists who were up to date with recent devel- opments. Moreover, the questionnaire has not been independently validated and some terms used might have different meaning for researchers with different backgrounds. A follow-up survey on a larger scale, in- cluding representatives from funding agencies, could provide more information on the potential of using existing evidence in the design of new studies. We clarified in the survey that the term “clinical trials” should mean “randomized, post-marketing (e.g., phase IV) controlled clinical trials”. This clarification was made because usually little evidence is available before licens- ing which constitutes an important barrier to using the proposed method. However, it might be that trials exam- ining licensed treatments are considered phase III be- cause of their size and scope. Clearer guidance on how comparative effectiveness data can and should be used in the entire process of approval and adoption of new drugs would be of interest [25, 26]. Author details 1 Author details 1Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland. 2CTU Bern, University of Bern, Bern, Switzerland. 3Department of Health Sciences, College of Medicine, Biological Sciences and Psychology, University of Leicester, Leicester, UK. Author details 1Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland. 2CTU Bern, University of Bern, Bern, Switzerland. 3Department of Health Sciences, College of Medicine, Biological Sciences and Psychology, University of Leicester, Leicester, UK. Received: 6 September 2018 Accepted: 13 May 2019 Received: 6 September 2018 Accepted: 13 May 2019 Received: 6 September 2018 Accepted: 13 May 2019 Additional files Additional file 1: List of invitations. (DOCX 22 kb) Additional file 2: Questionnaire. (DOCX 82 kb) Additional file 3: Full results. (DOCX 45 kb) Additional file 1: List of invitations. (DOCX 22 kb) Additional file 2: Questionnaire. (DOCX 82 kb) Additional file 3: Full results. (DOCX 45 kb) Authors’ contributions GS, AN, and ME conceived the study and designed the survey questionnaire. ST critically revised the survey questionnaire. GS contacted the survey participants. AN designed the survey in Survey Monkey, performed the main analyses, and wrote the first draft of the paper. All authors critically revised the manuscript, interpreted the results, and performed a critical review of the manuscript for intellectual content. GS, AN, and ME produced the final version of the submitted article and all co-authors approved it. p g The authors declare that they have no competing interests. Author details 1Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland. 2CTU Bern, University of Bern, Bern, Switzerland. 3Department of Health Sciences, College of Medicine, Biological Sciences and Psychology, University of Leicester, Leicester, UK. 1. Robinson KA, Saldanha IJ, Mckoy NA. Frameworks for determining research gaps during systematic reviews. Rockville: Agency for Healthcare Research and Quality (US); 2011. Ethics approval and consent to participate Ethics approval and consent to participate Not applicable. Not applicable. Competing interests Competing interests The authors declare that they have no competing interests. Resources for health research are limited and thus an economical and ethical allocation of funds for clinical trials requires minimizing human and monetary costs and risks. While certain research funders, clinical trial planners, and journal editors acknowledge the need to consult the existing evidence base before conducting a new trial, in practice these considerations are not con- crete and explicit and quantitative methods are rarely used. We propose that clinical trialists explicitly report (e.g., in published protocols) how they will compute the sample size of their planned trials including the way in which they will use existing evidence, for example by p g The authors declare that they have no competing interests. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. References 1. Robinson KA, Saldanha IJ, Mckoy NA. Frameworks for determining research gaps during systematic reviews. Rockville: Agency for Healthcare Research and Quality (US); 2011. Page 9 of 9 Page 9 of 9 Page 9 of 9 Nikolakopoulou et al. Trials (2019) 20:334 Nikolakopoulou et al. Trials (2019) 20:334 2. Roloff V, Higgins JPT, Sutton AJ. Planning future studies based on the conditional power of a meta-analysis. Stat Med. 2013;32(1):11–24. 28. Thorlund K, et al. Can trial sequential monitoring boundaries reduce spurious inferences from meta-analyses? Int J Epidemiol. 2009;38(1):276–86. 2. Roloff V, Higgins JPT, Sutton AJ. Planning future studies based o 3. Nikolakopoulou A, Mavridis D, Salanti G. Using conditional power of network meta-analysis (NMA) to inform the design of future clinical trials. Biom J Biom Z. 2014;56(6):973–90. 29. Higgins JPT, Whitehead A, Simmonds M. Sequential methods for random- effects meta-analysis. Stat Med. 2011;30(9):903–21. 30. Nikolakopoulou A, Mavridis D, Egger M, Salanti G. Continuously updated network meta-analysis and statistical monitoring for timely decision-making Stat Methods Med Res. 2016;27(5):1312–30. https://doi.org/10.1177/ 0962280216659896. 4. Sutton AJ, Cooper NJ, Jones DR, Lambert PC, Thompson JR, Abrams KR. Evidence-based sample size calculations based upon updated meta-analysis Stat Med. 2007;26(12):2479–500. 5. Langan D, Higgins JPT, Gregory W, Sutton AJ. Graphical augmentations to the funnel plot assess the impact of additional evidence on a meta-analysis. J Clin Epidemiol. 2012;65(5):511–9. 31. Simmonds M, Salanti G, McKenzie J, Elliott J. Living Systematic Review Network, Living systematic reviews: 3. Statistical methods for updating meta-analyses. J Clin Epidemiol. 2017;91:38–46. 32. Cochrane Methods 2012. (2012). https://doi.org/10.1002/14651858. CD201201. 6. Ferreira ML, Herbert RD, Crowther MJ, Verhagen A, Sutton AJ. When is a further clinical trial justified? BMJ. 2012;345:e5913. 7. Kanters S, Ford N, Druyts E, Thorlund K, Mills EJ, Bansback N. Use of network meta-analysis in clinical guidelines. Bull World Health Organ. 2016;94(10): 782–4. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. 8. Nikolakopoulou A, Mavridis D, Salanti G. Planning future studies based on the precision of network meta-analysis results. Stat Med. 2016;35(7):978–1000. 9. Salanti G, et al. Planning a future randomized clinical trial based on a network of relevant past trials. Trials. 2018;19(1):365. https://doi.org/10.1186/ s13063-018-2740-2. 10. Clayton GL, et al. The INVEST project: investigating the use of evidence synthesis in the design and analysis of clinical trials. Trials. 2017;18:1. 11. Clarke M, Hopewell S, Chalmers I. Reports of clinical trials should begin and end with up-to-date systematic reviews of other relevant evidence: a status report. J R Soc Med. 2007;100(4):187–90. 12. Clarke M, Hopewell S, Chalmers I. Clinical trials should begin and end with systematic reviews of relevant evidence: 12 years and waiting. Lancet. 2010; 376(9734):20–1. 13. Fergusson D, Glass KC, Hutton B, Shapiro S. Randomized controlled trials of aprotinin in cardiac surgery: could clinical equipoise have stopped the bleeding? Clin Trials Lond Engl. 2005;2(3):218–229-232. 13. Fergusson D, Glass KC, Hutton B, Shapiro S. Randomized controlled trials of aprotinin in cardiac surgery: could clinical equipoise have stopped the bleeding? Clin Trials Lond Engl. 2005;2(3):218–229-232. 14. Chalmers I, Hedges LV, Cooper H. A brief history of research synthesis. Eval Health Prof. 2002;25(1):12–37. 14. Chalmers I, Hedges LV, Cooper H. A brief history of research synthesis. Eval Health Prof. 2002;25(1):12–37. 15. Clarke M, Alderson P, Chalmers I. Discussion sections in reports of controlled trials published in general medical journals. JAMA. 2002;287(21):2799–801. 16. Clarke M, Chalmers I. Discussion sections in reports of controlled trials published in general medical journals: islands in search of continents? JAMA. 1998;280(3):280–2. 16. Clarke M, Chalmers I. Discussion sections in reports of controlled trials published in general medical journals: islands in search of continents? JAMA. 1998;280(3):280–2. 17. Cooper NJ, Jones DR, Sutton AJ. The use of systematic reviews when designing studies. Clin. Trials Lond. Engl. 2005;2(3):260–4. 17. Cooper NJ, Jones DR, Sutton AJ. The use of systematic reviews when designing studies. Clin. Trials Lond. Engl. 2005;2(3):260–4. 18. Chalmers I, et al. How to increase value and reduce waste when research priorities are set. Lancet Lond Engl. 2014;383(9912):156–65. 18. Chalmers I, et al. Publisher’s Note How to increase value and reduce waste when research priorities are set. Lancet Lond Engl. 2014;383(9912):156–65. 19. Jones AP, Conroy E, Williamson PR, Clarke M, Gamble C. The use of systematic reviews in the planning, design and conduct of randomised trials: a retrospective cohort of NIHR HTA funded trials. BMC Med Res Methodol. 2013;13(1):50. 20. Clark T, Berger U, Mansmann U. Sample size determinations in original research protocols for randomised clinical trials submitted to UK research ethics committees: review. BMJ. 2013;346:f1135. 20. Clark T, Berger U, Mansmann U. Sample size determinations in original research protocols for randomised clinical trials submitted to UK research ethics committees: review. BMJ. 2013;346:f1135. 21. Robinson KA, Goodman SN. A systematic examination of the citation of prior research in reports of randomized, controlled trials. Ann Intern Med. 2011;154(1):50–5. 21. Robinson KA, Goodman SN. A systematic examination of the citation of prior research in reports of randomized, controlled trials. Ann Intern Med. 2011;154(1):50–5. 22. Nasser M, et al. What are funders doing to minimise waste in research? Lancet Lond. Engl. 2017;389(10073):1006–7. 22. Nasser M, et al. What are funders doing to minimise waste in research? Lancet Lond. Engl. 2017;389(10073):1006–7. 23. Clark T, Davies H, Mansmann U. Five questions that need answering when considering the design of clinical trials. Trials. 2014;15:286. 23. Clark T, Davies H, Mansmann U. Five questions that need answering when considering the design of clinical trials. Trials. 2014;15:286. 24. Bhurke S, Cook A, Tallant A, Young A, Williams E, Raftery J. Using systematic reviews to inform NIHR HTA trial planning and design: a retrospective cohort. BMC Med Res Methodol. 2015;15:1. 24. Bhurke S, Cook A, Tallant A, Young A, Williams E, Raftery J. Using systematic reviews to inform NIHR HTA trial planning and design: a retrospective cohort. BMC Med Res Methodol. 2015;15:1. 25. Didden E-M, et al. Prediction of real-world drug effectiveness prelaunch: case study in rheumatoid arthritis. Med Decis Mak. 2018;38(6):719–29. 26. Egger M, Moons KGM, Fletcher C, GetReal Workpackage 4. GetReal: from efficacy in clinical trials to relative effectiveness in the real world. Res. Synth. Methods. 2016;7(3):278–81. 27. Brok J, Thorlund K, Wetterslev J, Gluud C. Apparently conclusive meta- analyses may be inconclusive—trial sequential analysis adjustment of random error risk due to repetitive testing of accumulating data in apparently conclusive neonatal meta-analyses. Int J Epidemiol. 2009;38(1): 287–98.
https://openalex.org/W2765357343	https://pubs.rsc.org/en/content/articlepdf/2017/cp/c7cp04380e	English	null	Roles of conformational disorder and downhill folding in modulating protein–DNA recognition	Physical chemistry chemical physics/PCCP. Physical chemistry chemical physics	2,017	cc-by	15,972	PCCP Physical Chemistry Chemical Physics rsc.li/pccp rsc.li/pccp ISSN 1463-9076 PAPER Xiakun Chu and Victor Muñoz Roles of conformational disorder and downhill folding in modulating protein–DNA recognition PAPER Xiakun Chu and Victor Muñoz Roles of conformational disorder and downhill folding in modulating protein–DNA recognition PCCP PCCP View Article Online View Journal \| View Issue a IMDEA Nanosciences, Faraday 9, Campus de Cantoblanco, Madrid, 28049, Spain b National Biotechnology Center, Consejo Superior de Investigaciones Cientı´ficas, Darwin 3, Campus de Cantoblanco, Madrid, 28049, Spain c Department of Bioengineering, School of Engineering, University of California, 95343 Merced, CA, USA. E-mail: vmunoz@cnb.csic.es † Electronic supplementary information (ESI) available: Models and methods, and tables and additional figures. See DOI: 10.1039/c7cp04380e Roles of conformational disorder and downhill folding in modulating protein–DNA recognition† Cite this: Phys.Chem.Chem.Phys., 2017, 19, 28527 Xiakun Chua and Victor Mun˜oz abc Transcription factors are thought to eﬃciently search for their target DNA site via a combination of conventional 3D diﬀusion and 1D diﬀusion along the DNA molecule mediated by non-specific electrostatic interactions. This process requires the DNA-binding protein to quickly exchange between a search competent and a target recognition mode, but little is known as to how these two binding modes are encoded in the conformational properties of the protein. Here, we investigate this issue on the engrailed homeodomain (EngHD), a DNA-binding domain that folds ultrafast and exhibits a complex conformational behavior consistent with the downhill folding scenario. We explore the interplay between folding and DNA recognition using a coarse-grained computational model that allows us to manipulate the folding properties of the protein and monitor its non-specific and specific binding to DNA. We find that conformational disorder increases the search eﬃciency of EngHD by promoting a fast gliding search mode in addition to sliding. When gliding, EngHD remains loosely bound to DNA moving linearly along its length. A partially disordered EngHD also binds more dynamically to the target site, reducing the half-life of the specific complex via a spring-loaded mechanism. These findings apply to all conditions leading to partial disorder. However, we also find that at physiologically relevant temperatures EngHD is well folded and can only obtain the conformational flexibility required to accelerate 1D diﬀusion when it folds/unfolds within the downhill scenario (crossing a marginal free energy barrier). In addition, the conformational flexibility of native downhill EngHD enables its fast reconfiguration to lock into the specific binding site upon arrival, thereby aﬀording finer control of the on- and oﬀ-rates of the specific complex. Our results provide key mechanistic insights into how DNA-binding domains optimize specific DNA recognition through the control of their conformational dynamics and folding mechanism. rsc.li/pccp Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 \| 28527 This journal is ©the Owner Societies 2017 Protein model The EngHD model represents each amino acid with two beads (except for glycine): one representing the backbone and positioned at the Ca and another one representing the side-chain and positioned at its center of mass. The Hamiltonian for EngHD is expressed as: VEngHD SBM = Vbond + VDihedral + VNative + VNon-native where the first term accounts for the bond-related short-range potential, including bond, angle, and chirality terms.71 The last three terms are folding-related, controlling the conformational properties of EngHD. VDihedral determines the relative orientation of the four adjacent beads, thus controlling the dihedral angles. This term is responsible for defining the formation of the native secondary structure (i.e. the three a-helices of EngHD). The native contact term VNative is represented by a Lennard-Jones-type (LJ) potential. VNon-native includes the excluded volume term and an electrostatic potential with Debye–Hu¨ckel ionic-strength dependence.72,73 To test this hypothesis, we focus on the binding to DNA of EngHD, a three-helix bundle DNA-binding domain from the Drosophila melanogaster transcription factor engrailed. The folding properties of EngHD have been thoroughly characterized in experiments and simulations.52–56 These studies highlight that EngHD folds/unfolds very rapidly, approaching the folding speed limit.42,44,57 EngHD readily changes its conformational properties in response to environmental changes or interactions,55,58,59 and is partially disordered at physiological temperatures.49 Quantitative analysis of thermodynamic and kinetic data, including differential scanning calorimetry, as well as long-timescale atomistic simulations, indicate that EngHD does indeed fold under the downhill scenario.49,60,61 The structural bases for the binding to DNA of homeodomains have also been thoroughly investigated using X-ray crystallography62 and NMR.63 In addition, NMR paramagnetic relaxation enhancement techniques have shown that homeodomains interact with DNA through the same binding interface whether they are bound specifically or non-specifically,64–66 which points to any differences between search and recognition modes being of dynamical rather than structural origin. To fine tune the conformational disorder and stability of EngHD, we modified the strength of native contacts by changing the pre-factor ef of the LJ term in VNative. A small ef leads to large conformational disorder and low folding stability, and vice versa. We thus generated a series of EngHD models with diﬀerent native stabilities by varying ef. These models cover the entire range from completely unfolded at all relevant temperatures (IDP-like chain) to the folding midpoint (i.e. equal populations of native and unfolded states) and to a stable folded state. Introduction dimensionality of facilitated diﬀusion is thought to greatly enhance the search and thus increase the rate. The phenomenon of 1D diﬀusion of DNA-binding proteins on DNA has been observed using single-molecule experiments,7–11 and analyzed by coarse- grained molecular simulations.12–18 The theoretical framework describing facilitated diffusion on protein–DNA interactions is also well established.6,19–21 Specific DNA recognition by regulatory proteins is fundamental to gene expression. These DNA-binding proteins must eﬃciently recognize their specific target sites among the millions of alternative non-specific sites present in genomic DNA. An intriguing implication is that the rate by which these proteins bind to their DNA target greatly exceeds the theoretical limit imposed by the occurrence of random collisions between the protein and the DNA specific site.1,2 To solve this paradox, a ‘‘facilitated diﬀusion’’ mechanism for DNA binding has been proposed.3,4 Such a mechanism involves standard three-dimensional (3D) diﬀusion combined with non-specific DNA binding5 followed by one- dimensional (1D) diﬀusion along the DNA molecule.4,6 The reduced During 1D diﬀusion, the protein remains in contact with DNA by virtue of non-specific binding promoted by electrostatic interactions.22,23 This raises the second paradox of how to simultaneously maximize speed and stability.3,24–28 Non-specific binding should be processive to guarantee an efficient 1D search. However, the stronger the binding the slower the diffusion coefficient because the protein needs to break strong interactions to move forward.3,24–28 DNA-binding domains typically carry a net positive charge and thus bind to the polyanionic DNA molecule in a sequence independent manner.29 As a simple solution to this problem, the DNA-binding domain could just switch between two modes: a ‘‘search’’ mode in which the protein binds to any DNA and undergoes 1D-diﬀusion and a ‘‘recognition’’ mode in which the protein locks into the Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 \| 28527 This journal is ©the Owner Societies 2017 View Article Online Paper between the conformational flexibility and folding mechanism of EngHD and the search and recognition binding modes. We find that intrinsic disorder and downhill folding increase the DNA searching capabilities of EngHD via kinetic and thermodynamic eﬀects. These results strongly support the idea that the highly dynamic conformational ensembles of DNA-binding domains play a key role in the DNA recognition process. Moreover, our work provides a simple theoretical framework for the design and optimization of protein–DNA recognition. specific target site once encountered. Computational procedures and methods To investigate the folding and DNA binding properties of EngHD, we use a structure-based model (SBM)67–70 or native- centric Go model in which the molecular complexity of both protein and DNA is coarse grained. One interesting possibility is that the conformational pliability of downhill folding enables the implementation of search and recognition modes in a single domain together with nimble switching between them.45,46 In the downhill folding scenario, the free energy barrier to folding–unfolding is very small (o3kT),47 which results in ultrafast dynamics and minimally cooperative unfolding.42,44,48,49 It has been in fact proposed that downhill folders can operate as molecular rheostats, dynamically adjusting their characteristically broad conformational ensembles in response to cues.50 The molecular rheostat concept has been effectively exploited to develop ultra-high performance biosensors,51 but its potential role in controlling biological processes remains unknown. This journal is ©the Owner Societies 2017 Introduction This two-mode binding mechanism normally involves separate search and recognition protein domains, as it occurs for zinc finger based transcription factors.16,30–33 According to previous computational studies, the search domain facilitates 1D diffusion by smoothing the energy landscape of the DNA–protein interactions, but engaging the recognition mode involves crossing a kinetic barrier that necessarily lowers the rate of locking into the specific site thus increasing the chance to miss the target.34,35 Therefore, the optimization of DNA recognition requires that the conformational dynamics of the protein are coordinated with the specific binding event. It is, however, unclear how such a dual-mode binding mechanism can be implemented on many DNA-binding proteins that have just one structural domain rather than two. In that respect, it is interesting to note that DNA-binding domains exhibit partial structural disorder under native conditions36–40 and often fold with ultrafast kinetics that are characteristic of the downhill folding scenario.41–44 specific target site once encountered. This two-mode binding mechanism normally involves separate search and recognition protein domains, as it occurs for zinc finger based transcription factors.16,30–33 According to previous computational studies, The overall potential used for the simulations has the form: V = V EngHD SBM + V EngHD–DNA SBM + V EngHD–DNA Ele where V EngHD SBM is the potential for the protein as defined above, V EngHD–DNA SBM includes the SBM potential for the specific complex (defined by the contacts observed between EngHD and the DNA molecule in the X-ray structure62) and a volume repulsive potential between EngHD and DNA. VEngHD–DNA Ele is a Debye– Hu¨ckel term that represents the electrostatic interactions formed between charged beads of EngHD and the DNA molecule. From these simulations, we could dissect the molecular details of the DNA recognition process and its coupling to the conformational dynamics of EngHD. We found that non-specific DNA binding takes place using a hybrid mechanism consisting of three- and one-dimensional (3D and 1D) diﬀusion modes. We could also observe the binding to the specific site, which can be divided into two steps. The first one involves the formation of the transition complex (TC), which occurs when EngHD reaches the specific binding site but has not formed the specific binding interactions yet. The second step (specific binding, or SB) involves EngHD locking into the specific binding site by forming all the interactions involved in the specific EngHD–DNA complex. We considered the protein performing pure 3D diffusion when it is 43 nm away from the DNA molecule to guarantee the absence of interactions between the two molecules. In contrast, we define 1D diffusion along the DNA (sliding) as a process by which the protein remains in constant contact with DNA, a definition that is Simulations were performed on a straight rigid 100 bp-long DNA molecule placed within a 20 20 40 nm3 simulation box aligned along the Z-axis. This DNA molecule includes one extended specific-binding site (10 bp long, same as in the crystal structure62) located in the center of the DNA molecule. EngHD is able to bind non-specifically to any potential binding site within the 100 bp DNA duplex through electrostatic inter- actions. The specific binding site includes additional stabilization energy from the contact interactions observed in the X-ray structure of the complex. Langevin dynamics simulations were performed using the GROMACS software with reduced units applied.80 We used a salt concentration of 0.01 M (low ionic strength) to maximize the probability of EngHD moving in the vicinity of DNA. Protein model The implication is that under downhill folding conditions, the a-helices are well formed in the unfolded ensemble resulting in a folding mechanism similar to the diﬀusion–collision model.78 Under two-state-like conditions, the folding of EngHD is close to the nucleation–condensation mechanism.79 As indicated above, the default parameter for the SBM results in a folding barrier of B1.3kT at the denaturation midpoint, low folding cooperativity and an unfolded state in which the helices are mostly formed. independent simulations of 1 105 reduced time units were performed to monitor the DNA binding properties. For the standard parameters (ef = 1.0 and R = 1), the folding temperature of EngHD is found at kT = 1.40. More details can be found in the ESI.† DNA model In our CGSBM, each nucleotide of the DNA molecule is represented by three beads. One bead represents the phosphate group (negatively charged), another bead the sugar and the third one the nitrogenous base. The double stranded DNA structure was kept rigid during the simulations. Protein model The middle condition produced a folding free energy barrier of B1.3kT separating unfolded and native ensembles, which is fully consistent with the experimental estimates of the folding barrier of EngHD.49,61,74 DNA of homeodomains have also been thoroughly investigated using X-ray crystallography62 and NMR.63 In addition, NMR paramagnetic relaxation enhancement techniques have shown that homeodomains interact with DNA through the same binding interface whether they are bound specifically or non-specifically,64–66 which points to any differences between search and recognition modes being of dynamical rather than structural origin. To control the folding mechanism of EngHD (i.e. barrier height at the denaturation midpoint), we altered the energetic balance between local (close in sequence) and non-local (far away in sequence) interactions.75,76 On the mostly helical EngHD,77 this was simply achieved by changing the relative strength (R) of We investigate the coupling between folding and DNA binding using a coarse-grained structure-based model (CGSBM) that gives us the opportunity to manipulate the folding mechanism and stability of EngHD as well as its binding to DNA in the specific and non-specific modes. Our analysis reveals a concerted interplay 28528 \| Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 This journal is ©the Owner Societies 2017 View Article Online PCCP Paper each individual contribution to VDihedral relative to the strength of each contribution to VNative, with the latter being the term that includes tertiary contacts. Changes in R from 0.1 to 3.0, that is, increasing ef (pre-factor for VDihedral) relative to ef (pre-factor for VNative), R = ef/ef, generate folding scenarios for EngHD ranging from apparent 2-state (i.e. barrier of B4.5kT at the denaturation midpoint) to global downhill (i.e. barrier of only B0.3kT). For clarity, we introduce the parameter downhillness that corresponds to R normalized according to the expression: downhillness = (R 0.1)/(3 0.1). Thus, downhillness ranges from 0 (two-state) to 1 (one-state). Increasing R lowers the free energy barrier and also increases the degree of residual helical structure in the unfolded ensemble (Fig. S1, ESI†). Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Our CGSBM includes a description of the conformational ensemble of the protein, non-specific protein binding to any segment of the dsDNA and specific binding to the target site located in the center of the DNA molecule. The folding behavior of EngHD and the specific binding to DNA are modeled by a standard SBM, which only takes into account interactions observed in the native crystal structures.62,77 Non-specific inter- actions with the DNA are modeled as pure electrostatics using a simple Debye–Hu¨ckel model. In a first step, we investigated the folding behavior of EngHD without DNA. The standard para- meters for the SBM protein model rendered a marginal folding barrier of B1.3kT at the folding temperature (Fig. S2 and S3, ESI†). Therefore, according to these simulations EngHD folds in the downhill regime, consistent with the conclusions derived from the analysis of multiple experimental data.49,61,74 With these parameters, EngHD maintains a large degree of helical structure in the unfolded ensemble (Fig. S1, ESI†), again consistent with the expectation for a downhill folder.74 The helical content in the unfolded ensemble is almost as much as in the native state, indicating that the folding process can be roughly described as docking of the three pre-formed helices to form the bundle. This description is closely similar to the diffusion–collision mechanism.78 Overall, our results are consistent with previous experiments and also with atomistic simulations,54–56,81,82 supporting the significance of our CGSBM.67 To determine the coupling between the folding of EngHD and the binding to DNA, we performed molecular binding simulations at the folding temperature of EngHD starting from different non- associated states (see Computational procedures and methods and the ESI† for details). Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 \| 28529 This journal is ©the Owner Societies 2017 Simulations The overall potential used for the simulations has the form: Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. (B) Snapshots of the EngHD interaction with DNA at different stages with EngHD color-coded as in A. Examples of folded (lighter) and unfolded (darker) conformations are provided. The DNA-interacting helix of EngHD is highlighted in purple and the specific binding site on DNA is shown in light gray. (C) Folding free energy landscape of EngHD along QFolding (i.e. fraction of folding native contacts) for the different binding modes. The data corresponding to 3D diffusion are shown with dashed lines since they were obtained from simulations of EngHD alone due to very low occur- rence of 3D diffusion in the presence of DNA. From the folding free energy landscapes, we can see that EngHD has diﬀerent conformational distributions for the various binding scenarios (Fig. 1C). When EngHD is sliding and/or gliding, and thus associated (even if somewhat loosely) with the DNA, its conformational distribution deviates from that of the free state. The gliding mode favors EngHD conformations that are either fully or partially unfolded, resulting in a net destabilization and also in the lowering of the folding free energy barrier. In contrast, the sliding mode favors the folded conformation, which implies that this mode requires EngHD to be fully folded. At the TC, which defines the transition from non-specific to specific binding, the EngHD conformational ensemble is similar to that of the protein performing sliding but with lower bias towards the native state, indicating that at the TC the protein is more weakly associated with DNA than when bound non-specifically to other DNA regions. Finally, during specific binding (SB), the folded state becomes highly stabilized by the strong specific interactions formed with the DNA target site and thus EngHD is locked into its native state. However, we should emphasize that these binding modes are highly dynamic and in constant exchange, as observed in individual trajectories (Fig. 1A and B). In other words, at the folding temperature (i.e. when is half unfolded), EngHD binds to DNA in a highly dynamical fashion in which binding modes and EngHD conformations are coupled and in constant exchange. Such dynamic folding–binding behavior may have interesting implications for the kinetic efficiency of protein–DNA recognition.37,83 To examine the interactions formed between EngHD and the DNA during non-specific binding, we calculated the minimum distance between each EngHD residue and the closest DNA atoms (Disti, where i is the index of the residue in EngHD). The overall potential used for the simulations has the form: PCCP View Article Online View Article Online View Article Online Paper PCCP similar to the facilitated diffusion mode used by other authors.4 We find that 1D diffusion significantly reduces the dimensionality of the search and thus accelerates the process, as expected.25 A close inspection of the motions undergone by the protein while performing 1D diffusion reveals two sub-categories of 1D diffusion. In the first one, the recognition a-helix of EngHD remains inserted into the major groove, resulting in a spiraling displacement along the DNA length (i.e. rotation around and translation along the Z-axis of DNA) (Fig. S4A and C, ESI†). We term this type of 1D diffusion a sliding search mode. In the second type of 1D diffusion, EngHD is not interacting tightly with the DNA and the displacement along the DNA long axis does not occur coupled to rotation (Fig. S4B and D, ESI†). During this type of motion, the protein remains more loosely associated with DNA but the displacement is still unidirectional along its length. Accordingly, we term this type of motion ‘‘gliding’’. We also observed hopping, defined as events in which the protein becomes completely, but transiently, detached from DNA followed by rebinding to a nearby region in the DNA. Hopping events were observed rarely in our simulations, probably due to the low salt concentration used to increase non-specific binding. Likewise, we did not see many jumping events in which the protein dissociates from DNA, undergoes 3D diffusion and rebinds at a distant position in the DNA. We therefore combined hopping and jumping events together into the 3D diffusion mode. It is worth noting that our gliding mode is in some ways similar to the 2D hopping mode described in previous work by Levy and coworkers.12,14,15,18,39 However, in the limit of strong non-specific binding to DNA (low ionic strength) that we explore here, the protein moves along the DNA without detaching, and thus the term 1D gliding represents this search mode more accurately than the original definition of 2D hopping.4,6 similar to the facilitated diffusion mode used by other authors.4 We find that 1D diffusion significantly reduces the dimensionality of the search and thus accelerates the process, as expected.25 A close inspection of the motions undergone by the protein while performing 1D diffusion reveals two sub-categories of 1D diffusion. Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Fig. 1 DNA recognition trajectory and folding free energy landscape of EngHD in the diﬀerent binding stages. (A) Trajectory for EngHD–DNA recognition. XY-Distance is the distance of the EngHD centroid to the DNA main axis and Z-position its position along the long DNA axis. One specific binding site is placed at the center of the DNA molecule, corresponding to Z-positions between 185 Å and 215 Å. The search process is composed of segments in which the protein performs 3D diffusion, 1D sliding (bound non-specifically to the major groove of the DNA) and gliding (moving along the DNA axis while loosely associated with DNA) modes. The specific binding process is divided into two steps: the formation of the transition complex (TC) and locking into the specific binding site (SB). Trajectory segments corresponding to different binding modes are color-coded: 3D (black), gliding (red), sliding (green), TC (cyan) and SB (dark blue). (B) Snapshots of the EngHD interaction with DNA at different stages with EngHD color-coded as in A. Examples of folded (lighter) and unfolded (darker) conformations are provided. The DNA-interacting helix of EngHD is highlighted in purple and the specific binding site on DNA is shown in light gray. (C) Folding free energy landscape of EngHD along QFolding (i.e. fraction of folding native contacts) for the different binding modes. The data corresponding to 3D diffusion are shown with dashed lines since they were obtained from simulations of EngHD alone due to very low occur- rence of 3D diffusion in the presence of DNA. Fig. 1 DNA recognition trajectory and folding free energy landscape of EngHD in the diﬀerent binding stages. (A) Trajectory for EngHD–DNA recognition. XY-Distance is the distance of the EngHD centroid to the DNA main axis and Z-position its position along the long DNA axis. One specific binding site is placed at the center of the DNA molecule, corresponding to Z-positions between 185 Å and 215 Å. The search process is composed of segments in which the protein performs 3D diffusion, 1D sliding (bound non-specifically to the major groove of the DNA) and gliding (moving along the DNA axis while loosely associated with DNA) modes. The specific binding process is divided into two steps: the formation of the transition complex (TC) and locking into the specific binding site (SB). Trajectory segments corresponding to different binding modes are color-coded: 3D (black), gliding (red), sliding (green), TC (cyan) and SB (dark blue). The overall potential used for the simulations has the form: In the first one, the recognition a-helix of EngHD remains inserted into the major groove, resulting in a spiraling displacement along the DNA length (i.e. rotation around and translation along the Z-axis of DNA) (Fig. S4A and C, ESI†). We term this type of 1D diffusion a sliding search mode. In the second type of 1D diffusion, EngHD is not interacting tightly with the DNA and the displacement along the DNA long axis does not occur coupled to rotation (Fig. S4B and D, ESI†). During this type of motion, the protein remains more loosely associated with DNA but the displacement is still unidirectional along its length. Accordingly, we term this type of motion ‘‘gliding’’. We also observed hopping, defined as events in which the protein becomes completely, but transiently, detached from DNA followed by rebinding to a nearby region in the DNA. Hopping events were observed rarely in our simulations, probably due to the low salt concentration used to increase non-specific binding. Likewise, we did not see many jumping events in which the protein dissociates from DNA, undergoes 3D diffusion and rebinds at a distant position in the DNA. We therefore combined hopping and jumping events together into the 3D diffusion mode. It is worth noting that our gliding mode is in some ways similar to the 2D hopping mode described in previous work by Levy and coworkers.12,14,15,18,39 However, in the limit of strong non-specific binding to DNA (low ionic strength) that we explore here, the protein moves along the DNA without detaching, and thus the term 1D gliding represents this search mode more accurately than th i i l d fi iti f 2D h i 4 6 The overall potential used for the simulations has the form: For each independent set of parameters defining the EngHD folding scenario (varying ef or R), a set of 60 This journal is ©the Owner Societies 2017 Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 \| 28529 Fig. 1 DNA recognition trajectory and folding free energy landscape of EngHD in the diﬀerent binding stages. (A) Trajectory for EngHD–DNA recognition. XY-Distance is the distance of the EngHD centroid to the DNA main axis and Z-position its position along the long DNA axis. One specific binding site is placed at the center of the DNA molecule corresponding to PCCP View Article Online Fig. 1 DNA recognition trajectory and folding free energy landscape of EngHD in the diﬀerent binding stages. (A) Trajectory for EngHD–DNA recognition. XY-Distance is the distance of the EngHD centroid to the DNA main axis and Z-position its position along the long DNA axis. One specific binding site is placed at the center of the DNA molecule, corresponding to Z-positions between 185 Å and 215 Å. The search process is composed of segments in which the protein performs 3D diffusion, 1D sliding (bound non-specifically to the major groove of the DNA) and gliding (moving along the DNA axis while loosely associated with DNA) modes. The specific binding process is divided into two steps: the formation of the transition complex (TC) and locking into the specific binding site (SB). Trajectory segments corresponding to different binding modes are color-coded: 3D (black), gliding (red), sliding (green), TC (cyan) and SB (dark blue). (B) Snapshots of the EngHD interaction with DNA at different stages with EngHD color-coded as in A. Examples of folded (lighter) and unfolded (darker) conformations are provided. The DNA-interacting helix of EngHD is highlighted in purple and the specific binding site on DNA is shown in light gray. (C) Folding free energy landscape of EngHD along QFolding (i.e. fraction of folding native contacts) for the different binding modes. The data corresponding to 3D diffusion are shown with dashed lines since they were obtained from simulations of EngHD alone due to very low occur- rence of 3D diffusion in the presence of DNA. This journal is ©the Owner Societies 2017 Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. This analysis shows that during sliding and gliding, folded EngHD interacts with DNA via the canonical binding interface observed in the crystal structure (Fig. S5A, ESI†). This is consistent with previous theoretical investigations and experiments performed on other homeodomains.12,64–66 To evaluate the effects of non- specific binding on the EngHD conformational ensemble, we calculated Disti as a function of the folding order parameter QFolding for the sliding and gliding modes (Fig. 2A). In the gliding mode, unfolded EngHD manages to get its helix II, and especially residues R29, R30 and R31, significantly closer to DNA than folded EngHD (Fig. 2A and Fig. S5B, ESI†). This is so because in the EngHD native structure helix II is at the farthest 28530 \| Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 This journal is ©the Owner Societies 2017 View Article Online View Article Online PCCP Paper Fig. 2 Structural analysis and free energy landscape of the interactions between DNA and EngHD as a function of QFolding. (A) Non-specific binding: mean minimum distance from each EngHD residue to the closest DNA atom during sliding (left) and gliding (right) as a function of QFolding. Red dots in the secondary structure assignment (rightmost) represent positively charged residues. (B) Specific binding: 2D free energy landscape of specific binding showing the TC and SB stages. QFolding and QDNA are the fraction of native contacts for EngHD folding and for specific DNA binding, respectively. To investigate the mechanistic implications that partial disorder on EngHD may have on DNA recognition, we extracted all of the transitions observed between the TC and SB from the trajectories and computed a free energy landscape for specific binding (Fig. 2B). The landscape highlights two possible pathways to go from TC to SB. The first pathway is a sequential process in which unfolded EngHD reaches the TC, folds up, and then locks into SB. This pathway corresponds to a conformational selection scenario in which the specific interactions select the folded structure from the broad conformational ensemble that EngHD populates while is at the TC.85,86 In the other pathway, EngHD folds and binds specifically in a concerted fashion resulting in an induced-fit binding scenario.87 In our simulations, the conformational selection pathway occurs with much higher probability than induced-fit. Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. That is, the gliding mode favors the structural disorder of EngHD because unfolded conformations can make more non-specific interactions with DNA. In the sliding mode, Disti, electrostatic energy, and the number of protein–DNA salt bridges are independent of the EngHD conformation (Table S1, ESI†), indicating that there are not energetic biases for specific EngHD conformations in this binding mode. Therefore, the strong stabilization of the native state observed during sliding (green line in Fig. 1C) must come from entropic contributions. This entropic effect appears to arise from geometrical constraints since helix III of EngHD must remain inserted into the major groove of DNA during sliding, which impedes the unfolding of the protein without dissociation. The effect is in fact reminiscent of the stabilization of proteins in highly confined spaces.84 The structural preferences for the different binding modes are likely to have significant kinetic implications for DNA recognition. For instance, when the protein arrives at the specific site through gliding, it may be unfolded and thus it would need to refold at the TC before it is able to lock into the target (SB). For a sliding EngHD, the transition from TC to SB should not require conformational readjustments. This analysis reveals that conformational disorder increases the probability of gliding at the expense of sliding (Fig. 3A). Under the strong non-specific binding conditions of our simulations (low ionic strength), 3D diﬀusion remains a minor component of the search motions regardless of the level of conformational disorder. Conformational disorder favors gliding because an unstructured EngHD exposes a larger eﬀective electrostatic interaction surface. Moreover, the enhanced conformational dynamics inherent to a more disordered ensemble facilitates the transient binding–release events that also favor gliding over sliding motions. The effect of disorder on specific binding is the decrease of the relative population of SB and the increase of that of the TC (Fig. 3B). The latter reflects the extra penalty in binding free energy that must be paid to fold up the protein simultaneously with binding at small values of ef (Fig. 2C). The destabilization of SB vanishes as soon as ef is higher than 1 (even though EngHD may still be partly disordered). This is so because the slightly unfolded ensemble that EngHD populates under conditions of marginal stability and minimal folding barrier (i.e. 1.3kT) is able to bind specifically as much as the fully folded state (Fig. S3 and S6, ESI†). Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. (A) Non-specific binding: mean minimum distance from each EngHD residue to the closest DNA atom during sliding (left) and gliding (right) as a function of QFolding. Red dots in the secondary structure assignment (rightmost) represent positively charged residues. (B) Specific binding: 2D free energy landscape of specific binding showing the TC and SB stages. QFolding and QDNA are the fraction of native contacts for EngHD folding and for specific DNA binding, respectively. end of the DNA specific binding interface, but once EngHD is unfolded this region can readily get into contact with DNA by making additional non-specific electrostatic interactions (Table S1, ESI†). These extra electrostatic interactions with DNA favor EngHD to be structurally disordered during gliding, thus biasing the folding free energy landscape slightly towards unfolded conformations (red in Fig. 1C). That is, the gliding mode favors the structural disorder of EngHD because unfolded conformations can make more non-specific interactions with DNA. In the sliding mode, Disti, electrostatic energy, and the number of protein–DNA salt bridges are independent of the EngHD conformation (Table S1, ESI†), indicating that there are not energetic biases for specific EngHD conformations in this binding mode. Therefore, the strong stabilization of the native state observed during sliding (green line in Fig. 1C) must come from entropic contributions. This entropic effect appears to arise from geometrical constraints since helix III of EngHD must remain inserted into the major groove of DNA during sliding, which impedes the unfolding of the protein without dissociation. The effect is in fact reminiscent of the stabilization of proteins in highly confined spaces.84 The structural preferences for the different binding modes are likely to have significant kinetic implications for DNA recognition. For instance, when the protein arrives at the specific site through gliding, it may be unfolded and thus it would need to refold at the TC before it is able to lock into the target (SB). For a sliding EngHD, the transition from TC to SB should not require conformational readjustments. end of the DNA specific binding interface, but once EngHD is unfolded this region can readily get into contact with DNA by making additional non-specific electrostatic interactions (Table S1, ESI†). These extra electrostatic interactions with DNA favor EngHD to be structurally disordered during gliding, thus biasing the folding free energy landscape slightly towards unfolded conformations (red in Fig. 1C). Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 \| 28531 Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. However, the coexistence of the two pathways is a manifestation of mechanistic complexity in line with what has been proposed for processes that involve binding coupled to the folding of a downhill folding protein.45,46,88 Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. This is an interesting observation since EngHD is indeed a very fast folding protein classified as a downhill folder,60,61,74,89 and it is also conformationally flexible at its physiological temperature.49 To further investigate these possible eﬀects, we performed binding simulations at varying degrees of unfolding, but without changing the folding scenario. This was achieved by simply tuning the strength of the native contacts of EngHD in our CGSBM (i.e. ef). ef controls the stability of the native state resulting in increasingly disordered conformational ensembles the smaller its value (Fig. S3, ESI†). However, tuning ef does not aﬀect the magnitude of the free energy barrier at the folding temperature. We thus performed all DNA binding simulations at a common temperature (i.e. the folding temperature for ef = 1.0) to focus exclusively on the eﬀects of structural disorder. Fig. 2 Structural analysis and free energy landscape of the interactions between DNA and EngHD as a function of QFolding. (A) Non-specific binding: mean minimum distance from each EngHD residue to the closest DNA atom during sliding (left) and gliding (right) as a function of QFolding. Red dots in the secondary structure assignment (rightmost) represent positively charged residues. (B) Specific binding: 2D free energy landscape of specific binding showing the TC and SB stages. QFolding and QDNA are the fraction of native contacts for EngHD folding and for specific DNA binding, respectively. Fig. 2 Structural analysis and free energy landscape of the interactions between DNA and EngHD as a function of QFolding. (A) Non-specific binding: mean minimum distance from each EngHD residue to the closest DNA atom during sliding (left) and gliding (right) as a function of QFolding. Red dots in the secondary structure assignment (rightmost) represent positively charged residues. (B) Specific binding: 2D free energy landscape of specific binding showing the TC and SB stages. QFolding and QDNA are the fraction of native contacts for EngHD folding and for specific DNA binding, respectively. Fig. 2 Structural analysis and free energy landscape of the interactions between DNA and EngHD as a function of QFolding. Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. ef is the strength of the EngHD native contacts. DNA length (Z-axis).9,12,83,90,91 In our simulation, gliding is frequent but short-lived, and it quickly alternates with sliding and 3D diﬀusion modes. The short gliding half-life makes it impractical to calculate D1 for pure gliding with suﬃcient accuracy. Instead, we calculate a composite D1 that integrates sliding and gliding onto a global 1D diﬀusion mode. This integrated 1D mode becomes significantly faster (2.5 fold) as the degree of disorder on EngHD increases (Fig. 4A). The increase in diﬀusion coeﬃcient mostly comes from gliding because at ef o 1 sliding becomes very short lived. That is, the more disordered the EngHD the faster it diﬀuses along DNA via gliding. The reason for this acceleration is that the gliding mode is still one-dimensional but the inherent flexibility of EngHD results in weaker binding to DNA and thus in faster motion. presence of disorder on EngHD accelerates the 1D DNA search process. In Fig. 4C, we plot the same type of data but including the population of each of the conformational sub-ensembles. This graph highlights how the net acceleration of 1D diﬀusion is proportional to the population weighted degree of conformational disorder present in the EngHD ensemble. Sliding is faster for more disordered conformations but only occurs when EngHD is suﬃciently folded (QFolding 4 0.7), and thus decreasing ef has a marginal eﬀect on the sliding speed. However, during gliding, EngHD can unfold completely without detaching from DNA, and thus at low ef, gliding is highly accelerated by disorder and eventually becomes the predominant 1D mode. Our results show that overall 1D diﬀusion speeds up as EngHD increases its structural disorder (i.e. always within the marginal folding barrier regime). To analyze the molecular basis of this observation, we introduce a quantity, which we term displacement (dZ) and that corresponds to the distance traveled by EngHD along the Z-axis between two consecutive frames separated by time interval Dt. This quantity is indicative of the 1D diﬀusive speed (dZ/Dt) and can be determined for individual conformations within the EngHD ensemble. Fig. 4B shows such data as a function of the folding order parameter (QFolding). These data show that the 1D diﬀusive speed does indeed increase as EngHD populates more open or unstructured confor- mations (lower QFolding). Interestingly, the speed up happens both for the integrated 1D mode and for pure sliding. Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. (B) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD as a function of ef. The color code is from red to blue for ef increasing from 0.8 to 1.2. Examples of sliding are shown as empty circles and fitted to a straight line; examples of 1D integrated diﬀusion (gliding plus sliding) are shown as solid circles and fitted to a sigmoidal function. (C) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD at three values of ef and with the size of the circles representing the population of the conformer. The corresponding folding free energy landscapes are also shown. PCCP Paper Fig. 3 Relative probability of diﬀerent binding modes as a function of the degree of conformational disorder. (A) Relative probabilities for the various non-specific binding modes: 3D diﬀusion, gliding, and sliding. (B) Relative probabilities for being at the TC or SB stage during specific binding. ef is the strength of the EngHD native contacts. Paper ed under a Creative Commons Attribution 3.0 Unported Licence. Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Fig. 4 The eﬀect of conformational disorder on the diﬀusion of EngHD along DNA. (A) 1D diﬀusion coeﬃcient (in Angstro¨m2 per reduced time unit) as a function of conformational disorder. S corresponds to only sliding and S + G to integrated sliding and gliding. Sliding becomes very transient for ef o 0.95, impeding further determination of its diﬀusion coeﬃcient. (B) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD as a function of ef. The color code is from red to blue for ef increasing from 0.8 to 1.2. Examples of sliding are shown as empty circles and fitted to a straight line; examples of 1D integrated diﬀusion (gliding plus sliding) are shown as solid circles and fitted to a sigmoidal function. (C) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD at three values of ef and with the size of the circles representing the population of the conformer. The corresponding folding free energy landscapes are also shown. Fig. 3 Relative probability of diﬀerent binding modes as a function of the degree of conformational disorder. (A) Relative probabilities for the various non-specific binding modes: 3D diﬀusion, gliding, and sliding. (B) Relative probabilities for being at the TC or SB stage during specific binding. 28532 \| Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 This journal is ©the Owner Societies 2017 Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. We then evaluated the DNA search speed of EngHD by obtaining the 1D diﬀusion coeﬃcient (D1) from the mean squared displacement (MSD) of the protein along the main Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 \| 28531 This journal is ©the Owner Societies 2017 PCCP View Article Online s g t t s s s e g , A g f r s presence of disorder on EngHD accelerates the 1D DNA search process. In Fig. 4C, we plot the same type of data but including the population of each of the conformational sub-ensembles. This graph highlights how the net acceleration of 1D diﬀusion is proportional to the population weighted degree of conformational disorder present in the EngHD ensemble. Sliding is faster for more disordered conformations but only occurs when EngHD is suﬃciently folded (QFolding 4 0.7), and thus decreasing ef has a marginal eﬀect on the sliding speed. However, during gliding, EngHD can unfold completely without detaching from DNA, e s e e Fig. 4 The eﬀect of conformational disorder on the diﬀusion of EngHD along DNA. (A) 1D diﬀusion coeﬃcient (in Angstro¨m2 per reduced time unit) as a function of conformational disorder. S corresponds to only sliding and S + G to integrated sliding and gliding. Sliding becomes very transient for ef o 0.95, impeding further determination of its diﬀusion coeﬃcient. (B) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD as a function of ef. The color code is from red to blue for ef increasing from 0.8 to 1.2. Examples of sliding are shown as empty circles and fitted to a straight line; examples of 1D integrated diﬀusion (gliding plus sliding) are shown as solid circles and fitted to a sigmoidal function. (C) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD at three values of ef and with the size of the circles representing the population of the conformer. The corresponding folding free energy landscapes are also shown. PCCP View Article Online View Article Online PCCP View Article Online Fig. 4 The eﬀect of conformational disorder on the diﬀusion of EngHD along DNA. (A) 1D diﬀusion coeﬃcient (in Angstro¨m2 per reduced time unit) as a function of conformational disorder. S corresponds to only sliding and S + G to integrated sliding and gliding. Sliding becomes very transient for ef o 0.95, impeding further determination of its diﬀusion coeﬃcient. Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. We first performed binding simulations for the indicated range of EngHD folding scenarios, each one at its folding temperature (i.e. ef = 1). The analysis of these simulations showed relatively small changes in both 1D diﬀusion dynamics (sliding and gliding) and specific binding (Fig. S8, ESI†). Therefore, as a first approximation, DNA recognition is mostly insensitive to the folding mechanism of the DNA-binding domain once its thermodynamic bias results in partial disorder. It is apparent in Fig. 6A that the dynamics for sliding and for integrated 1D diﬀusion (sliding and gliding) are essentially unaﬀected by changes in the folding mechanism that maintain an intermediate degree of disorder on EngHD. The relative contributions of gliding and sliding to 1D diﬀusion change only very slightly. The same can be said for the kinetics of specific binding. The search speed (dZ/Dt) as a function of QFolding is similarly unaﬀected (Fig. 6B). However, the analysis of the motions for individual conformations of EngHD (Fig. 6C) reveals that the unresponsiveness of 1D diﬀusion to the folding mechanism comes from compensatory eﬀects. Both gliding and sliding speeds increase as the protein becomes more unstructured. In the presence of a folding barrier, the conformational distribution is split into equally populated folded and unfolded ensembles, which experience slow and fast 1D diﬀusion, respectively (blue in Fig. 6C). On the other hand, a barrierless folding landscape results in 100% population of partially folded conformations, but these conformations also happen to diﬀuse at intermediate speeds (red in Fig. 6C). Therefore, the net balance remains essentially unaltered. Fig. 5 Microscopic kinetics of binding to the specific site as a function of conformational disorder. (A) Kinetic scheme of the diﬀerent steps involved in specific binding. (B) Relative eﬀects of conformational disorder on the rate of arrival at the TC (kS) and the oﬀ-rate from SB to TC (k). (C) Escape number of EngHD (ratio between the specific binding rate (klock) and the rate of escape from the TC (kescape)). 7 and 15), thus resulting in an increase of the TC population. Therefore, the presence of conformational disorder facilitates the arrival of the protein to the specific-binding basin of attraction (TC–SB), but it also decreases the dwell time on the specific binding site (1/k). The latter corresponds to the time EngHD remains functionally active. Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Therefore, the Another issue with functional significance is the kinetics of specific binding to the target site (SB). When the search occurs via 1D diﬀusion, the kinetic mechanism to form SB can be described by 4 basic rates (Fig. 5A): the rate of formation of the TC from adjacent non-specific binding sites (kS); the rate of locking into the SB (klock); the rate of escape from SB onto TC (k); and the rate of escape from the TC to adjacent non-specific binding sites (kescape). The eﬀects of conformational disorder on these rates are significant. For instance, Fig. 5B highlights that conformational disorder increases the two rates that lead to the TC (by factors of 28532 \| Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 This journal is ©the Owner Societies 2017 View Article Online PCCP Paper Fig. 5 Microscopic kinetics of binding to the specific site as a function of conformational disorder. (A) Kinetic scheme of the diﬀerent steps involved in specific binding. (B) Relative eﬀects of conformational disorder on the rate of arrival at the TC (kS) and the oﬀ-rate from SB to TC (k). (C) Escape number of EngHD (ratio between the specific binding rate (klock) and the rate of escape from the TC (kescape)). This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. indicate that the presence of conformational disorder may be functionally advantageous by a combination of: (1) implementation of a faster search by 1D diffusion and (2) facilitation of fast release from the specific binding site. Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. So far, we have investigated the eﬀects of conformational disorder while EngHD was maintained in the downhill regime (folding barrier of 1.3kT at Tf). To investigate the eﬀects of the folding scenario on DNA recognition, we changed the relative strength of local and non-local interactions (R is their ratio) in EngHD. A range of R between 0.1 and 3 varies the free energy barrier at the folding temperature of EngHD from B4.5kT to B0.3kT (Fig. S7, ESI,† Computational procedures and methods section), thus allowing us to explore the entire transition from nearly two-state to one-state downhill folding45,46,89 (or down- hillness from 0 to 1). This journal is ©the Owner Societies 2017 Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 \| 28533 Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. (C) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD at the two extremes in down- hillness with the size of circles representing the population of the conformer. The corresponding folding free energy landscapes are also shown. Fig. 7 1D diﬀusion along DNA of EngHD under conditions of marginal native stability (T o Tf). (A) 1D diﬀusion coeﬃcient as a function of folding downhillness at room temperature. (B) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD as a function of downhillness at room temperature. The color code is from red to blue for downhillness decreasing from 1 to 0. The black lines are fits to the data. Grey lines are fits to the data in Fig. 4 for comparison. (C) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD at the two extremes in down- hillness with the size of circles representing the population of the conformer. The corresponding folding free energy landscapes are also shown. attraction (Fig. 7C). As a consequence, the protein remains rigidly folded and 1D diﬀusion is relatively slow. Increasing downhillness progressively broadens the native basin of attraction resulting in a more flexible ensemble with conformational excursions out of the folded state that grow in probability and amplitude (Fig. 7C). Partially structured conformations are able to glide more eﬃciently (see above), and thus the overall 1D diﬀusion coeﬃcient increases. calorimetry data for EngHD has shown that this protein crosses a marginal folding barrier and has non-cooperative unfolding behavior, which is consistent with the results of our folding simulations using the standard SBM parameters.49,61,74 However, its physiological (i.e. room) temperature is lower than its experimentally determined folding temperature (B325 K),54 which in principle suggests a limited amount of intrinsic disorder in its functional state. To explore conditions that may be more significant biologically, we performed binding simulations at a temperature below the folding temperature. We could do this simply by increasing the interaction strength in our CGSBM (ef 4 1) (see Computational procedures and methods and the ESI†). The eﬀects of the EngHD folding mechanism on the kinetics of specific binding (kinetic scheme of Fig. 5A) are also minor in magnitude compared to the eﬀects of structural disorder. However, it is interesting to note that the trends at the folding temperature and at room temperature are reversed (Fig. 8). Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. The black lines are fits to the d to the data in Fig. 4 for comparison. (C) Displacement al conformational sub-ensembles of EngHD at the two hillness with the size of circles representing the populat The corresponding folding free energy landscapes are Fig. 7 1D diﬀusion along DNA of EngHD under conditions of marginal native stability (T o Tf). (A) 1D diﬀusion coeﬃcient as a function of folding downhillness at room temperature. (B) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD as a function of downhillness at room temperature. The color code is from red to blue for downhillness decreasing from 1 to 0. The black lines are fits to the data. Grey lines are fits to the data in Fig. 4 for comparison. (C) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD at the two extremes in down- hillness with the size of circles representing the population of the conformer. The corresponding folding free energy landscapes are also shown. Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Fig. 6 The eﬀects of folding scenario on the diﬀusion of EngHD along DNA. (A) 1D diﬀusion coeﬃcient as a function of folding downhillness for sliding and the integrated sliding and gliding modes. (B) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD as a function of downhillness at the folding temperature. The color code is from red to blue for downhillness decreasing from 1 to 0. The black lines are fits to the data. Grey lines are fits to the data in Fig. 4 for comparison. (C) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD at three downhillness levels with size of the circles representing the population of the conformer. The corresponding folding free energy landscapes are also shown. Fig. 7 1D diﬀusion along DNA of EngHD under conditions of marginal native stability (T o Tf). (A) 1D diﬀusion coeﬃcient as a function of folding downhillness at room temperature. (B) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD as a function of downhillness at room temperature. The color code is from red to blue for downhillness decreasing from 1 to 0. The black lines are fits to the data. Grey lines are fits to the data in Fig. 4 for comparison. 28534 \| Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Another noteworthy eﬀect that conformational disorder has on the overall kinetics is the increase of the propensity to be released from the specific binding basin of attraction (TC + SB). To quantify this eﬀect, we use the ratio between kescape and klock, which we term the escape number. The escape number increases drastically (up to 150-fold) as a function of the population of unstructured conformations in the EngHD ensemble (i.e. ef o 1.1) (Fig. 5C). The increase in escape number is caused by the large cost of conformational entropy associated with specific binding when EngHD is partially unfolded and needs to fold up to lock into SB (Fig. 2B). This entropic penalty reduces the overall time EngHD spends within the TC–SB basin of attraction and thus decreases the specific binding affinity. At a glance, such an effect may seem to be functionally detrimental, but it has been previously pointed out that nimble control of gene expression requires that transcription factors bind to the target site very dynamically, and thus with fast on- and off-rates.92 From that viewpoint, our results Our analysis indicates that the combination of significant structural disorder and a marginal folding barrier on the DNA binding domain produces a very dynamic DNA recognition process with nimble 1D diﬀusion towards the target site and fast release from it. From a general standpoint, these results shed light onto how the interplay between conformational disorder and folding mechanism of the DNA-binding domain optimizes the search for and release from the target DNA site. This conclusion has mechanistic implications for DNA recognition and gives practical clues for the design and optimization of DNA-binding proteins. From a functional viewpoint, a more relevant question is whether EngHD exploits these features while operating in its biological environment. The analysis of diﬀerential scanning Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 \| 28533 View Article Online Fig. 7 1D diﬀusion along DNA of EngHD under conditions of marginal native stability (T o Tf). (A) 1D diﬀusion coeﬃcient as a function of folding downhillness at room temperature. (B) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD as a function of downhillness at room temperature The color code is from red to blue for downhillness PCCP View Article Online Paper Fig. 6 The eﬀects of folding scenario on the diﬀusion of EngHD along DNA. Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. (A) 1D diﬀusion coeﬃcient as a function of folding downhillness for sliding and the integrated sliding and gliding modes. (B) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD as a function of downhillness at the folding temperature. The color code is from red to blue for downhillness decreasing from 1 to 0. The black lines are fits to the data. Grey lines are fits to the data in Fig. 4 for comparison. (C) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD at three downhillness levels with size of the circles representing the population of the conformer. The corresponding folding free energy landscapes are also shown. Fig. 7 1D diﬀusion along DNA of EngHD under conditions of marginal native stability (T o Tf). (A) 1D diﬀusion coeﬃcient as a function of folding downhillness at room temperature. (B) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD as a function of downhillness at room temperature. The color code is from red to blue for downhillness decreasing from 1 to 0. The black lines are fits to the data. Grey lines are fits to the data in Fig. 4 for comparison. (C) Displacement along DNA for diﬀerent conformational sub-ensembles of EngHD at the two extremes in down- hillness with the size of circles representing the population of the conformer. The corresponding folding free energy landscapes are also shown. Paper PCCP The eﬀects of folding scenario on the diﬀusion of EngHD along A) 1D diﬀusion coeﬃcient as a function of folding downhillness for and the integrated sliding and gliding modes. (B) Displacement DNA for diﬀerent conformational sub-ensembles of EngHD as a on of downhillness at the folding temperature. The color code is ed to blue for downhillness decreasing from 1 to 0. The black lines s to the data. Grey lines are fits to the data in Fig. 4 for comparison. placement along DNA for diﬀerent conformational sub-ensembles HD at three downhillness levels with size of the circles representing pulation of the conformer. The corresponding folding free energy apes are also shown. Fig. 7 1D diﬀusion along DNA of EngHD under co native stability (T o Tf). (A) 1D diﬀusion coeﬃcient as downhillness at room temperature. (B) Displacement al conformational sub-ensembles of EngHD as a functio room temperature. The color code is from red to b decreasing from 1 to 0. This journal is ©the Owner Societies 2017 Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. However, at higher temperature the EngHD ensemble is more disordered and thus excursions towards more extensively unfolded con- formations become much more common. The largely unfolded conformations are marginally compatible with the TC, and the entropic penalty of fixing them into SB is then higher than the binding free energy. Under these conditions a new pathway emerges by which EngHD is highly restrained when at SB and thus acts as a loaded spring that eventually triggers its induced release (top pathway in Fig. 9). In contrast to the middle pathway, the flux of the top pathway is predominantly in the direction of release both from SB to TC and from TC to a free or non-specifically bound EngHD. the mechanism of specific binding coupled to folding. The simulations indicate that this mechanism does in fact involve dynamic selection between alternative pathways (Fig. 9). A fully folded EngHD exchanges between TC and SB exclusively via a conventional lock-and-key process (bottom pathway in Fig. 9). But EngHD can also be partially unfolded at the TC (see Fig. 2C), opening a second pathway to SB in which folding and binding occur concertedly via an induced-fit process (mid- dle pathway in Fig. 9). Most of the flux in the induced-fit pathway is directed towards binding because the binding free energy is larger than the entropic penalty of fixing the chain. These two processes are dominant at low temperature at which EngHD populates a highly native-like ensemble. However, at higher temperature the EngHD ensemble is more disordered and thus excursions towards more extensively unfolded con- formations become much more common. The largely unfolded conformations are marginally compatible with the TC, and the entropic penalty of fixing them into SB is then higher than the binding free energy. Under these conditions a new pathway emerges by which EngHD is highly restrained when at SB and thus acts as a loaded spring that eventually triggers its induced release (top pathway in Fig. 9). In contrast to the middle pathway, the flux of the top pathway is predominantly in the direction of release both from SB to TC and from TC to a free or non-specifically bound EngHD. Some of the key aspects of this mechanism for specific binding to DNA use controlled conformational disorder to facilitate binding to, and release from, the specific DNA site. Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. At the folding temperature, the rate of formation of the TC from neighboring non-specific sites (kS) decreases with downhillness, whereas the rate of formation of the TC from SB (k) increases. At room temperature, the more downhill the folding mechanism the more the kS increases and k* decreases (Fig. 8A). Therefore, at room temperature the one-state downhill scenario (downhillness = 1) results in stronger specific binding and longer residence times in SB, whereas the opposite is true at the folding temperature. Likewise, the one-state downhill scenario decreases the escape number at the folding temperature and increases it at room temperature (Fig. 8B). The results from these simulations are summarized in Fig. 7. In contrast to what occurs at the folding temperature, the data at room temperature show that the EngHD folding mechanism aﬀects the eﬃciency of DNA recognition. In particular, we find that under these conditions the increase in downhillness speeds up both the sliding and gliding 1D diﬀusion modes (Fig. 7A), although the eﬀect is relatively small (about a 25% increase). The analysis of individual conformations reveals that such acceleration arises from the fact that in the downhill scenario the protein experiences conformational fluctuations out of the native state even under native conditions (Fig. 7B and C). At room temperature, the two-state-like scenario (downhillness = 0) has a free energy landscape with a narrow native basin of How can these results be reconciled? The trend reversal at room temperature suggests a temperature dependent switch in 28534 \| Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 This journal is ©the Owner Societies 2017 View Article Online Fig. 9 Scheme illustrating the diﬀerent kinetic transitions occurring between TC and SB for a marginally stable DNA-binding domain. Red and blue arrows signify folding and room temperature. Single headed arrows indicate preferential flux and two headed arrows indicate bidirectional steps. The arrow length reflects the relative population of the pathway at each temperature: red for high temperature and blue for low temperature. Paper View Article Online PCCP Paper Fig. 8 Microscopic kinetics of binding to the specific site for the one- state downhill scenario at folding and room temperature. The color code is the same as in Fig. 5. (A) Relative eﬀects on the rate of arrival at the TC (kS) and the oﬀ-rate from SB to TC (k). (B) Escape number of EngHD. Solid and open circles indicate folding and room temperature, respectively. Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. shed on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. s licensed under a Creative Commons Attribution 3.0 Unported Licence. Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Fig. 9 Scheme illustrating the diﬀerent kinetic transitions occurring between TC and SB for a marginally stable DNA-binding domain. Red and blue arrows signify folding and room temperature. Single headed arrows indicate preferential flux and two headed arrows indicate bidirectional steps. The arrow length reflects the relative population of the pathway at each temperature: red for high temperature and blue for low temperature. Fig. 8 Microscopic kinetics of binding to the specific site for the one- state downhill scenario at folding and room temperature. The color code is the same as in Fig. 5. (A) Relative eﬀects on the rate of arrival at the TC (kS) and the oﬀ-rate from SB to TC (k). (B) Escape number of EngHD. Solid and open circles indicate folding and room temperature, respectively. marginally stable DNA-binding protein folds/unfolds within the downhill scenario. Moreover, it also explains why this phenomenon is not observed when the protein folds two-state (downhillness close to 0). The reason is that in the two-state folding regime the protein needs to cross a free energy barrier to exchange conformations. The barrier crossing event results in a separation of timescales that decouples folding from binding. Accordingly, in the two- state scenario the protein only uses the lock-and-key specific binding pathway (bottom in Fig. 9), regardless of whether it populates only native (low temperature) or both native and highly unfolded conformations (high temperature). the mechanism of specific binding coupled to folding. The simulations indicate that this mechanism does in fact involve dynamic selection between alternative pathways (Fig. 9). A fully folded EngHD exchanges between TC and SB exclusively via a conventional lock-and-key process (bottom pathway in Fig. 9). But EngHD can also be partially unfolded at the TC (see Fig. 2C), opening a second pathway to SB in which folding and binding occur concertedly via an induced-fit process (mid- dle pathway in Fig. 9). Most of the flux in the induced-fit pathway is directed towards binding because the binding free energy is larger than the entropic penalty of fixing the chain. These two processes are dominant at low temperature at which EngHD populates a highly native-like ensemble. This journal is ©the Owner Societies 2017 Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 \| 28535 Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. The eﬀect that intrinsic structural disorder has on the eﬃciency of DNA recognition of EngHD is very apparent. For instance, while binding to the specific site only occurs when EngHD is well folded, a partially unstructured EngHD is capable of binding non-specifically to DNA, and it does so forming additional electrostatic interactions with protein regions that are far from the DNA backbone in the canonical binding site. These delocalized long-range interactions facilitate a gliding mode in which the protein interacts loosely with the DNA resulting in fast 1D diﬀusion. The gliding mode, which is typical (although not exclusive) of unstructured conformations, is fast and results in linear displacements along the DNA length. In contrast, in the sliding mode the well-folded protein remains inserted into the DNA major groove performing a slower, spiral displacement around the DNA length. As a consequence, the presence of partial disorder on EngHD speeds up the 1D-diﬀusive search by facilitating gliding, which is nearly 3-times faster than sliding. Our results add to previous studies of conformational disorder that have reported acceleration of 3D diﬀusion via the ‘‘fly-casting’’ mechanism93,94,128 and enhancement of inter- segment transfer between two diﬀerent DNA fragments via a ‘‘monkey bar’’ mechanism.14,39,129 From all of these findings combined, we conclude that partially disordered conformations are key components of the ‘‘search competent’’ mode of DNA- binding domains. Here, we focused on the connections between intrinsic disorder and folding scenario in determining the mechanism by which DNA-binding domains eﬃciently find and bind to their target site. The connection between folding and DNA recognition is supported by the realization that DNA-binding domains exhibit conformational flexibility under native conditions.38,41 Our working hypothesis was that the specific properties of the one- state downhill folding scenario can enable fast conformational exchange between search competent and recognition competent (specific binding) DNA binding modes. Such fast exchange would thus solve the speed-stability paradox that emerges from the facilitated diﬀusion mechanism that has been proposed for eﬃcient DNA recognition. g We thus investigated the interplay between folding mechanism, disorder and DNA binding of EngHD using simulations with a CGSBM. The standard parameterization of this model67,112 results in a folding mechanism for EngHD characterized by a marginal folding free energy barrier at the denaturation midpoint (i.e. 1.3kT) and a minimally cooperative unfolding process. Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. This eﬀect is similar to the fly-casting mechanism proposed to accelerate bio- molecular recognition.93,94 In this regard, it has been recently reported that the acceleration of conventional 3D-diﬀusion- mediated binding through fly-casting is strongly dependent on the interaction strength at the binding site (the quality of the ‘‘fly lure’’).95 Likewise, we find that a downhill folding DNA- binding domain with marginal stability can either be induced- fitted onto the target site (e.g. low temperature or high fly lure) or induced-released oﬀit (e.g. high temperature or low fly lure) by modulation of its conformational ensemble. Such modulation is mediated by temperature as we investigate here, or alternatively it could be mediated by binding to eﬀectors, such as other components of the transcription complex.96,97 Therefore, the interplay between disorder, folding mechanism and binding free energy produces a sophisticated palette of control mechanisms. Such a control palette is likely to be instrumental for achieving The pathway selection mechanism nicely explains the switch in behavior at diﬀerent temperatures that we observe when a Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 \| 28535 View Article Online Paper Paper PCCP existing experimental procedures to modify folding barriers through site-directed mutations.43,52,58,115,122–127 highly dynamic on- and oﬀ-switching of gene expression required for a rapid response to cellular environments and stimuli.98,99 DNA recognition of EngHD is a complex process involving standard 3D diﬀusion, non-specific binding through electro- static interactions, 1D diﬀusive search along the DNA length via various types of modes, and lock into the target site. Our simulations on a CGSBM reproduce all these processes thus permitting us to dissect how each of them is aﬀected by the conformational properties of EngHD. We find that there is a strong coupling between the conformational status of the protein and the various modes by which it interacts with DNA. Such coupling is mediated by a combination of energetic and entropic factors that plays out in diﬀerential ways for the various binding modes. This journal is ©the Owner Societies 2017 Conclusions Interest in the role that conformational disorder plays in biomolecular function was sparked by the discovery of intrinsically disordered proteins,100–106 and has since then become a major focus of biophysical chemical research.107 Parallel efforts have shown that many single-domain proteins fold in a few microseconds42,44,108 and cross minimal or no barriers to folding, falling in the downhill folding scenario.49 Downhill folding is interesting because it results in gradual, non-cooperative unfolding50,109,110 that could have functional significance, for example by expanding functional diversity through binding to multiple targets,45,46 or via a molecular rheostat mechanism in which the conformational ensemble is subtly manipulated by an effector resulting in allosteric signals.50,51,110 Moreover, intrinsic disorder and down- hill folding are closely related phenomena to the extent that partially structured IDPs have the conformational properties of the one-state downhill folding regime.41,45,46,111 Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. These results are fully consistent with the folding properties of EngHD derived from experiments54,55,82 and their quantitative analysis,49,61,74 as well as from long-timescale MD simulations.60 To explore the potential eﬀects of conformational disorder, we modified the interaction strength in the model, which allowed us to simulate conditions ranging from: (1) fully native, to (2) denaturation midpoint (QFolding B 0.5), and to (3) unfolding-like. Finally, we also modified the folding mechanism of EngHD by tuning the relative balance between non-local and local interactions in stabilizing the native structure, a factor that is well known to be a major determinant of folding cooperativity.45,46,108,113–115 Practically, we achieved this modulation by changing the strength of the native contacts (non-local) and the dihedral term in the model rather than adding desolvation and/or many- body terms.116–121 This approach is simple and recapitulates The eﬀects that conformational disorder has on specific binding are the opposite: structural disorder accelerates the rate of release from SB and greatly increases the escape from the specific basin of attraction. When EngHD populates unstructured conformations its residence time in the specific binding site is thus shortened. This eﬀect is purely entropic, arising from the penalty that the protein pays to fold up while locking into the target site. A shorter SB residence time may be functionally advantageous to a certain extent because it can facilitate dynamical control of gene expression.92 However, binding to the specific site cannot be too weak, or dynamic, at the risk of becoming incompetent to trigger the assembly of the transcription complex and/or of making the protein miss its target site when searching by 1D diﬀusion. These results high- light the double-edged sword of protein conformational disorder in DNA recognition. The implication is that the functional response of the DNA-binding domain must thus involve a certain 28536 \| Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 This journal is ©the Owner Societies 2017 View Article Online PCCP Paper (non-zero) level of intrinsic disorder that optimizes these multi- variate tradeoﬀs. The optimal level of structural disorder is presumably specific for each transcription factor and gene. (and in particular its folding barrier) is also experimentally feasible by introducing mutations designed to enhance the helical propensity of the native helices,43,127,132,133 remove specific long- range interactions134 and/or modify electrostatic interactions.135 The other factor that we have investigated here is the folding scenario of the DNA-binding domain. Acknowledgements This work was funded by Advanced Grant ERC-2012-ADG-323059 from the European Research Council to V. M. V. M. also acknowl- edges support from the Keck foundation and the CREST Center for Cellular and Biomolecular Machines (NSF-CREST-1547848). Conflicts of interest However, the folding scenario becomes really important for DNA recognition under native conditions. This appreciation is functionally significant because the physiological temperature of Drosophila melanogaster is lower than the folding temperature of EngHD.54 For a barrier-crossing folding scenario, the native- like thermodynamic conditions that are biologically relevant imply the absence of structural disorder because partially folded conformations are inherently unstable (i.e. conform the barrier). Under native conditions, a two-state folder is locked into its specific recognition mode, not being able to search eﬃciently. On the other hand, the downhill scenario guarantees some degree of conformational disorder even under stabilizing native conditions (e.g. red profile in Fig. 7C). These partially folded conformations are able to glide eﬃciently (Fig. S9, ESI†), making the implementation of a 1D search mode under native conditions possible. Moreover, the absence of the folding barrier allows downhill folding domains to reconfigure with very fast (micro- second) dynamics. The implication is that a partially folded downhill domain can quickly reconfigure while it stays at the TC, and thus eﬃciently locks into SB through the induced-fit pathway of Fig. 9. The same native conditions guarantee a negligible population of unfolded conformations (QFolding o 0.5), thus eﬀectively blocking the pathway for induced-release oﬀSB. There are no conflicts to declare. This journal is ©the Owner Societies 2017 Open Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Obviously, the folding properties of the DNA-binding domain can only have relevance in as much as the protein exhibits a certain degree of disorder (for a rigid native structure the folding mechanism has no functional relevance). Therefore, any potential role of the folding scenario must be by definition subtle. Our analysis indicates that in the presence of large degree of structural disorder (e.g. at the folding temperature) the folding mechanism has a negligible eﬀect on DNA recognition. This is so because the thermodynamic conditions already guarantee a significant population of eﬃcient gliders (i.e. partially to completely unfolded conformations) and favor quick release from the specific binding site by a spring- loaded mechanism. Summarizing, we can conclude that the fast-folding kinetics and downhill folding mechanism of EngHD enable this protein to swiftly interconvert between a (partially unfolded) search eﬃcient mode and its well-folded target recognition mode even under physiological conditions in which the domain is native- like. These properties fulfill the requirements of the two- binding mode mechanism for eﬃcient DNA recognition26,136 in which a conformationally dynamic EngHD performs fast 1D search via non-specific binding, while is able to quickly change conformation to lock into the specific binding site upon arrival. pen Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. 20 K. V. Klenin, H. Merlitz, J. Langowski and C.-X. Wu, Phys. Rev. Lett., 2006, 96, 018104. 52 T. L. Religa, J. S. Markson, U. Mayor, S. M. V. Freund and A. R. Fersht, Nature, 2005, 437, 1053–1056. 21 A. B. Kolomeisky, Phys. Chem. Chem. Phys., 2011, 13, 2088–2095. A. R. Fersht, Nature, 2005, 437, 1053–1056. 53 S. Gianni, N. R. Guydosh, F. Khan, T. D. Caldas, U. Mayor, G. W. N. White, M. L. DeMarco, V. Daggett and A. R. Fersht, Proc. Natl. Acad. Sci. U. S. A., 2003, 100, 13286–13291. 22 V. K. Misra, J. L. Hecht, A.-S. Yang and B. Honig, Biophys. J., 1998, 75, 2262–2273. 23 M. T. Record, J.-H. Ha and M. A. Fisher, Methods Enzymol., 1991, 208, 291–343. 54 U. Mayor, C. M. Johnson, V. Daggett and A. R. Fersht, Proc. Natl. Acad. Sci. U. S. A., 2000, 97, 13518–13522. 24 M. Slutsky and L. A. Mirny, Biophys. J., 2004, 87, 4021–4035. 55 U. Mayor, N. R. Guydosh, C. M. Johnson, J. G. Grossmann, S. Sato, G. S. Jas, S. M. V. Freund, D. O. V. Alonso, V. Daggett and A. R. Fersht, Nature, 2003, 421, 863–867. 25 S. E. Halford, Biochem. Soc. Trans., 2009, 37, 343–348. 26 L. Mirny, M. Slutsky, Z. Wunderlich, A. Tafvizi, J. Leith and A. Kosmrlj, J. Phys. A: Math. Theor., 2009, 42, 434013. S. Sato, G. S. Jas, S. M. V. Freund, D. O. V. Alonso, V. Daggett and A. R. Fersht, Nature, 2003, 421, 863–867. 56 A. R. Fersht and V. Daggett, Cell, 2002, 108, 573–582. 27 O. Be´nichou, Y. Kafri, M. Sheinman and R. Voituriez, Phys. Rev. Lett., 2009, 103, 138102. 57 W. A. Eaton, V. Mun˜oz, S. J. Hagen, G. S. Jas, L. J. Lapidus, E. R. Henry and J. Hofrichter, Annu. Rev. Biophys. Biomol. Struct., 2000, 29, 327–359. 28 A. Veksler and A. B. Kolomeisky, J. Phys. Chem. B, 2013, 117, 12695–12701. 29 U. Gerland, J. D. Moroz and T. Hwa, Proc. Natl. Acad. Sci. U. S. A., 2002, 99, 12015–12020. 58 U. Mayor, J. G. Grossmann, N. W. Foster, S. M. V. Freund and A. R. Fersht, J. Mol. Biol., 2003, 333, 977–991. 30 A. Tafvizi, F. Huang, A. R. Fersht, L. A. Mirny and A. M. van Oijen, Proc. Natl. Acad. Sci. U. S. A., 2011, 108, 563–568. 59 T. L. Religa, C. M. Johnson, D. M. Vu, S. H. Brewer, R. pen Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. B. Dyer and A. R. Fersht, Proc. Natl. Acad. Sci. U. S. A., 2007, 104, 9272–9277. 31 L. Zandarashvili, A. Esadze, D. Vuzman, C. A. Kemme, Y. Levy and J. Iwahara, Proc. Natl. Acad. Sci. U. S. A., 2015, 112, E5142–E5149. 60 K. Lindorﬀ-Larsen, S. Piana, R. O. Dror and D. E. Shaw, Science, 2011, 334, 517–520. 61 A. N. Naganathan, J. M. Sanchez-Ruiz and V. Munoz, J. Am. Chem. Soc., 2005, 127, 17970–17971. 32 L. Zandarashvili, D. Vuzman, A. Esadze, Y. Takayama, D. Sahu, Y. Levy and J. Iwahara, Proc. Natl. Acad. Sci. U. S. A., 2012, 109, E1724–E1732. 62 E. Fraenkel, M. A. Rould, K. A. Chambers and C. O. Pabo, J. Mol. Biol., 1998, 284, 351–361. 33 J. Iwahara and Y. Levy, Transcription, 2013, 4, 58–61. 63 T. Sprules, N. Green, M. Featherstone and K. Gehring, Biochemistry, 2000, 39, 9943–9950. 34 A. Marcovitz and Y. Levy, Proc. Natl. Acad. Sci. U. S. A., 2011, 108, 17957–17962. 64 J. Iwahara and G. M. Clore, Nature, 2006, 440, 1227–1230. 35 A. Marcovitz and Y. Levy, J. Phys. Chem. B, 2013, 117, 13005–13014. 65 J. Iwahara and G. M. Clore, J. Am. Chem. Soc., 2006, 128, 404–405. 36 J. Liu, N. B. Perumal, C. J. Oldfield, E. W. Su, V. N. Uversky and A. K. Dunker, Biochemistry, 2006, 45, 6873–6888. 66 J. Iwahara, M. Zweckstetter and G. M. Clore, Proc. Natl. Acad. Sci. U. S. A., 2006, 103, 15062–15067. 37 M. Fuxreiter, I. Simon and S. Bondos, Trends Biochem. Sci., 2011, 36, 415–423. 67 C. Clementi, H. Nymeyer and J. N. Onuchic, J. Mol. Biol., 2000, 298, 937–953. 38 P. L. Privalov and A. I. Dragan, Biophys. Chem., 2007, 126, 16–24. 68 J. K. Noel, P. C. Whitford, K. Y. Sanbonmatsu and J. N. Onuchic, Nucleic Acids Res., 2010, 38, W657–W661. 39 D. Vuzman, A. Azia and Y. Levy, J. Mol. Biol., 2010, 396, 674–684. 40 H. J. Dyson, Mol. BioSyst., 2012, 8, 97–104. 69 Y. Levy, S. S. Cho, J. N. Onuchic and P. G. Wolynes, J. Mol. Biol., 2005, 346, 1121–1145. 41 A. N. Naganathan, R. Perez-Jimenez, V. Mun˜oz and J. M. Sanchez-Ruiz, Phys. Chem. Chem. Phys., 2011, 13, 17064–17076. 70 Y. Levy, P. G. Wolynes and J. N. Onuchic, Proc. Natl. Acad. Sci. U. S. A., 2004, 101, 511–516. 42 J. Kubelka, J. Hofrichter and W. A. Eaton, Curr. Opin. Struct. Biol., 2004, 14, 76–88. 71 M. References 1 A. D. Riggs, S. Bourgeois and M. Cohn, J. Mol. Biol., 1970, 53, 401–417. 2 O. G. Berg and P. H. von Hippel, Annu. Rev. Biophys. Biophys. Chem., 1985, 14, 131–158. 3 R. B. Winter, O. G. Berg and P. H. Von Hippel, Biochemistry, 1981, 20, 6961–6977. 4 P. H. von Hippel and O. G. Berg, J. Biol. Chem., 1989, 264, 675–678. 5 H. C. Berg, Random walks in biology, Princeton University Press, 1993. 6 S. E. Halford and J. F. Marko, Nucleic Acids Res., 2004, 32, 3040–3052. Our theoretical predictions can be potentially assessed via targeted biophysical experiments. In that respect, it would be highly informative to determine the eﬀect that certain degrees of intrinsic disorder in EngHD or diﬀerent folding scenarios have on the apparent binding aﬃnity to the specific binding site and to non-specific DNA sequences. Likewise, single-molecule experiments could be used to resolve the sliding and gliding 1D search modes of EngHD on long DNA molecules, thus to measure the relative eﬀects on each diﬀerent binding mode. Changing the level of intrinsic disorder on EngHD is relatively straightforward, as one could perform the experiments at diﬀerent temperatures, or destabilizing EngHD via mutation. An attractive mutation in that regard is the single-point L16A mutation, which makes EngHD partially unfolded under physiological conditions.52 Optimized mutations that lead to thermostable versions of EngHD have also been achieved.130,131 Engineering the folding scenario of EngHD 7 N. Shimamoto, J. Biol. Chem., 1999, 274, 15293–15296. 8 P. C. Blainey, A. M. van Oijen, A. Banerjee, G. L. Verdine and X. S. Xie, Proc. Natl. Acad. Sci. U. S. A., 2006, 103, 5752–5757. 9 Y. M. Wang, R. H. Austin and E. C. Cox, Phys. Rev. Lett., 2006, 97, 048302. 10 J. Elf, G.-W. Li and X. S. Xie, Science, 2007, 316, 1191–1194. 11 P. Hammar, P. Leroy, A. Mahmutovic, E. G. Marklund, O. G. Berg and J. Elf, Science, 2012, 336, 1595–1598. 12 O. Givaty and Y. Levy, J. Mol. Biol., 2009, 385, 1087–1097. 13 A. Marcovitz and Y. Levy, Biophys. J., 2009, 96, 4212–4220. 14 D. Vuzman, M. Polonsky and Y. Levy, Biophys. J., 2010, 99, 1202–1211. 15 D. Vuzman and Y. Levy, Proc. Natl. Acad. Sci. U. S. A., 2010, 107, 21004–21009. This journal is ©the Owner Societies 2017 Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 \| 28537 View Article Online Paper PCCP 16 T. Terakawa, H. References Kenzaki and S. Takada, J. Am. Chem. Soc., 2012, 134, 14555–14562. 47 J. D. Bryngelson, J. N. Onuchic, N. D. Socci and P. G. Wolynes, Proteins: Struct., Funct., Bioinf., 1995, 21, 167–195. y f 48 F. Liu and M. Gruebele, Chem. Phys. Lett., 2008, 461, 1–8. 17 T. Ando and J. Skolnick, PLoS Comput. Biol., 2014, 10, e1003990. 49 A. N. Naganathan, U. Doshi and V. Mun˜oz, J. Am. Chem. Soc., 2007, 129, 5673–5682. 18 A. Bhattacherjee, D. Krepel and Y. Levy, Wiley Comput. Mol. Sci., 2016, 6, 515–531. 50 M. M. Garcia-Mira, M. Sadqi, N. Fischer, J. M. Sanchez- Ruiz and V. Munoz, Science, 2002, 298, 2191–2195. 19 O. G. Berg, R. B. Winter and P. H. Von Hippel, Biochemistry, 1981, 20, 6929–6948. 51 M. Cerminara, T. M. Desai, M. Sadqi and V. Mun˜oz, J. Am. Chem. Soc., 2012, 134, 8010–8013. pen Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. M. Gutin and E. I. Shakhnovich, J. Mol. Biol., 1995, 252, 460–471. 83 X. Chu, F. Liu, B. A. Maxwell, Y. Wang, Z. Suo, H. Wang, W. Han and J. Wang, PLoS Comput. Biol., 2014, 10, e1003804. 114 E. Shakhnovich, Chem. Rev., 2006, 106, 1559–1588. 84 H.-X. Zhou and K. A. Dill, Biochemistry, 2001, 40, 11289–11293. 115 V. Mun˜oz and L. Serrano, Folding Des., 1996, 1, R71–R77. d i d h l i l 85 H. R. Bosshard, Physiology, 2001, 16, 171–173. 116 A. Badasyan, Z. Liu and H. S. Chan, J. Mol. Biol., 2008, 384, 512–530. 86 C.-J. Tsai, B. Ma, Y. Y. Sham, S. Kumar and R. Nussinov, Proteins: Struct., Funct., Bioinf., 2001, 44, 418–427. 117 H. S. Chan, Z. Zhang, S. Wallin and Z. Liu, Annu. Rev. Phys. Chem., 2011, 62, 301. 87 D. E. Koshland, Proc. Natl. Acad. Sci. U. S. A., 1958, 44, 98–104. 118 M. S. Cheung, A. E. Garcı´a and J. N. Onuchic, Proc. Natl. Acad. Sci. U. S. A., 2002, 99, 685–690. 88 A. N. Naganathan and M. Orozco, J. Am. Chem. Soc., 2011, 133, 12154–12161. 119 S. S. Cho, P. Weinkam and P. G. Wolynes, Proc. Natl. Acad. Sci. U. S. A., 2008, 105, 118–123. 89 D. De Sancho and V. Mun˜oz, Phys. Chem. Chem. Phys., 2011, 13, 17030–17043. 120 M. R. Ejtehadi, S. P. Avall and S. S. Plotkin, Proc. Natl. Acad. Sci. U. S. A., 2004, 101, 15088–15093. 90 A. Grane´li, C. C. Yeykal, R. B. Robertson and E. C. Greene, Proc. Natl. Acad. Sci. U. S. A., 2006, 103, 1221–1226. 21 Z. Liu and H. S. Chan, Phys. Biol., 2005, 2, S7 91 H. Qian, M. P. Sheetz and E. L. Elson, Biophys. J., 1991, 60, 910. 122 N. Ferguson, P. J. Schartau, T. D. Sharpe, S. Sato and A. R. Fersht, J. Mol. Biol., 2004, 344, 295–301. 92 G. L. Hager, J. G. McNally and T. Misteli, Mol. Cell, 2009, 35, 741–753. 123 N. Ferguson, T. D. Sharpe, P. J. Schartau, S. Sato, M. D. Allen, C. M. Johnson, T. J. Rutherford and A. R. Fersht, J. Mol. Biol., 2005, 353, 427–446. 93 B. A. Shoemaker, J. J. Portman and P. G. Wolynes, Proc. Natl. Acad. Sci. U. S. A., 2000, 97, 8868–8873. 124 A. R. Fersht, Proc. Natl. Acad. Sci. U. S. A., 2000, 97, 1525–1529. 94 E. Trizac, Y. Levy and P. G. Wolynes, Proc. pen Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. S. Cheung, J. M. Finke, B. Callahan and J. N. Onuchic, J. Phys. Chem. B, 2003, 107, 11193–11200. 43 W. Y. Yang and M. Gruebele, Biophys. J., 2004, 87, 596–608. 72 A. Azia and Y. Levy, J. Mol. Biol., 2009, 393, 527–542. 44 H. Gelman and M. Gruebele, Q. Rev. Biophys., 2014, 47, 95–142. 73 X. Chu, Y. Wang, L. Gan, Y. Bai, W. Han, E. Wang and J. Wang, PLoS Comput. Biol., 2012, 8, e1002608. 45 V. Mun˜oz, L. A. Campos and M. Sadqi, Curr. Opin. Struct. Biol., 2016, 36, 58–66. 46 V. Mun˜oz and M. Cerminara, Biochem. J., 2016, 473, 2545–2559. 74 A. N. Naganathan, U. Doshi, A. Fung, M. Sadqi and V. Mun˜oz, Biochemistry, 2006, 45, 8466–8475. 28538 \| Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 This journal is ©the Owner Societies 2017 View Article Online PCCP Paper 75 M. Knott, H. Kaya and H. S. Chan, Polymer, 2004, 45, 623–632. 106 A. K. Dunker, I. Silman, V. N. Uversky and J. L. Sussman, Curr. Opin. Struct. Biol., 2008, 18, 756–764. H. Kaya and H. S. Chan, Polymer, 2004, 45, 623–632. 76 G. Zuo, J. Wang and W. Wang, Proteins: Struct., Funct., Bioinf., 2006, 63, 165–173. p 107 S. DeForte and V. N. Uversky, RSC Adv., 2016, 6, 11513–11521. 108 V. Mun˜oz, Annu. Rev. Biophys. Biomol. Struct., 2007, 36, 395–412. 77 N. D. Clarke, C. R. Kissinger, J. Desjarlais, G. L. Gilliland and C. O. Pabo, Protein Sci., 1994, 3, 1779–1787. 109 V. Mun˜oz, Int. J. Quantum Chem., 2002, 90, 1522–1528. 78 M. Karplus and D. L. Weaver, Protein Sci., 1994, 3, 650–668. 110 M. Sadqi, D. Fushman and V. Mun˜oz, Nature, 2006, 442, 317–321. 79 A. R. Fersht, Curr. Opin. Struct. Biol., 1997, 7, 3–9. 111 Y. Wang, X. Chu, S. Longhi, P. Roche, W. Han, E. Wang and J. Wang, Proc. Natl. Acad. Sci. U. S. A., 2013, 110, E3743–E3752. 80 H. J. C. Berendsen, D. van der Spoel and R. van Drunen, Comput. Phys. Commun., 1995, 91, 43–56. 81 I. A. Hubner, E. J. Deeds and E. I. Shakhnovich, Proc. Natl. Acad. Sci. U. S. A., 2006, 103, 17747–17752. 112 P. C. Whitford, J. K. Noel, S. Gosavi, A. Schug, K. Y. Sanbonmatsu and J. N. Onuchic, Proteins: Struct., Funct., Bioinf., 2009, 75, 430–441. 82 M. E. McCully, D. A. C. Beck and V. Daggett, Biochemistry, 2008, 47, 7079–7089. 113 V. I. Abkevich, A. pen Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Natl. Acad. Sci. U. S. A., 2010, 107, 2746–2750. 125 F. Liu and M. Gruebele, J. Mol. Biol., 2007, 370, 574–584. 95 K. Umezawa, J. Ohnuki, J. Higo and M. Takano, Proteins: Struct., Funct., Bioinf., 2016, 84, 1124–1133. 126 V. Mun˜oz, M. Sadqi, A. N. Naganathan and D. de Sancho, HFSP J., 2008, 2, 342–353. 127 W. Y. Yang and M. Gruebele, Nature, 2003, 423, 193–197. 96 M.-Y. Tsai, B. Zhang, W. Zheng and P. G. Wolynes, J. Am. Chem. Soc., 2016, 138, 13497–13500. 128 Y. Levy, J. N. Onuchic and P. G. Wolynes, J. Am. Chem. Soc., 2007, 129, 738–739. 97 J. S. Graham, R. C. Johnson and J. F. Marko, Nucleic Acids Res., 2011, 39, 2249–2259. 129 D. Vuzman and Y. Levy, Isr. J. Chem., 2014, 54, 1374–1381. Vuzman and Y. Levy, Isr. J. Chem., 2014, 54, 1374– 98 N. Hao and E. K. O’shea, Nat. Struct. Mol. Biol., 2012, 19, 31–39. 130 M. E. McCully, D. A. Beck and V. Daggett, Protein Eng., Des. Sel., 2012, 26, 35–45. 99 D. E. Levy and J. E. Darnell, Nat. Rev. Mol. Cell Biol., 2002, 3, 651–662. 131 P. S. Shah, G. K. Hom, S. A. Ross, J. K. Lassila, K. A. Crowhurst and S. L. Mayo, J. Mol. Biol., 2007, 372, 1–6. 100 A. K. Dunker, J. D. Lawson, C. J. Brown, R. M. Williams, P. Romero, J. S. Oh, C. J. Oldfield, A. M. Campen, C. M. Ratliﬀ, K. W. Hipps, J. Ausio, M. S. Nissen, R. Reeves, C. Kang, C. R. Kissinger, R. W. Bailey, M. D. Griswold, W. Chiu, E. C. Garner and Z. Obradovic, J. Mol. Graphics Modell., 2001, 19, 26–59. 132 M. B. Prigozhin, Y. Liu, A. J. Wirth, S. Kapoor, R. Winter, K. Schulten and M. Gruebele, Proc. Natl. Acad. Sci. U. S. A., 2013, 110, 8087–8092. 133 E. Larios, J. W. Pitera, W. C. Swope and M. Gruebele, Chem. Phys., 2006, 323, 45–53. 101 H. J. Dyson and P. E. Wright, Nat. Rev. Mol. Cell Biol., 2005, 6, 197–208. 134 F. Liu, D. Du, A. A. Fuller, J. E. Davoren, P. Wipf, J. W. Kelly and M. Gruebele, Proc. Natl. Acad. Sci. U. S. A., 2008, 105, 2369–2374. 102 P. Tompa, Trends Biochem. Sci., 2002, 27, 527–533. 135 Ø. Halskau, R. Perez-Jimenez, B. Ibarra-Molero, J. Underhaug, V. Mun˜oz, A. Martinez and J. M. Sanchez- Ruiz, Proc. Natl. Acad. Sci. U. S. pen Access Article. Published on 18 October 2017. Downloaded on 10/24/2024 5:38:41 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. A., 2008, 105, 8625–8630. 136 H.-X. Zhou, Proc. Natl. Acad. Sci. U. S. A., 2011, 108, 8651–8656. 135 Ø. Halskau, R. Perez-Jimenez, B. Ibarra-Molero, J. Underhaug, V. Mun˜oz, A. Martinez and J. M. Sanchez- Ruiz, Proc. Natl. Acad. Sci. U. S. A., 2008, 105, 8625–8630. 03 V. N. Uversky, Protein Sci., 2002, 11, 739–756. 104 J. Habchi, P. Tompa, S. Longhi and V. N. Uversky, Chem. Rev., 2014, 114, 6561–6588. 105 D. Eliezer, Curr. Opin. Struct. Biol., 2009, 19, 23–30. 136 H.-X. Zhou, Proc. Natl. Acad. Sci. U. S. A., 2011, 108, 8651–8656. Phys. Chem. Chem. Phys., 2017, 19, 28527--28539 \| 28539 This journal is ©the Owner Societies 2017
https://openalex.org/W4362627830	https://figshare.com/articles/journal_contribution/Figure_S3_from_Cell_of_Origin_Influences_Pancreatic_Cancer_Subtype/22535630/1/files/39998906.pdf	English	null	Figure S1 from Cell of Origin Influences Pancreatic Cancer Subtype	null	2,023	cc-by	2,112	D. H&E tdTomato CK19 Trp53fl/LSL-R172H Trp53fl/- Trp53fl/LSL-R270H p53 E. F. BF2020 20x 100um BF1709 20x 100um BF2596 20x 100um plementary Figure 3: Analysis of pancreatic cancer development from adult mouse ductal cells Representative bright-field and fluorescence dissecting scope images of a primary pancreatic tumor in a KT;Sox9CreER;Trp53fl/fl mouse. Scale Bar = 2 cm. (B) Kaplan-Meier analysis of creatic cancer-free survival of KT;Sox9CreER;Trp53fl/x (where x represents different Trp53 alleles) cohorts. Labels indicate the Trp53 status of each cohort. Pancreatic cancer free surviv- KT;Sox9CreER;Trp53fl/LSL-R172H mice (n = 17) and KT;Sox9CreER;Trp53fl/LSL-R270H mice (n = 18) is similar to KT;Sox9CreER;Trp53fl/- mice (n = 19), using the log-rank test. Not significant (C) Kaplan-Meier analysis of overall survival of KT;Sox9CreER;Trp53fl/x (where x represents different Trp53 alleles) cohorts. Labels indicate the Trp53 status of each cohort. Pancreatic cer free survival in KT;Sox9CreER;Trp53fl/LSL-R172H mice (n = 17) and KT;Sox9CreER;Trp53fl/LSL-R270H mice (n = 18) is similar to KT;Sox9CreER;Trp53fl/- mice (n = 19), based on the log-rank Not significant = ns. (D) Table summarizing the percentages of pancreatic tumor-bearing KT;Sox9CreER;Trp53fl/- (n = 3), KT;Sox9CreER;Trp53fl/LSL-R172H (n = 4), and KT;Sox- eER;Trp53fl/LSL-R270H (n = 3) mice presenting with clinical symptoms of pancreatic cancer (ascites, bowel obstruction, and jaundice) at morbidity. (E) Table summarizing the percentages ancreatic tumor-bearing KT;Sox9CreER;Trp53fl/- (n = 3), KT;Sox9CreER;Trp53fl/LSL-R172H (n = 4) , and KT;Sox9CreER;Trp53fl/LSL-R270H (n = 3) mice with the primary pancreatic tumor grade mprising >50% of the tumor) called as moderately/well-differentiated adenocarcinoma, poorly-differentiated adenocarcinoma, or sarcomatoid carcinoma. (F) Representative histological es of the pancreatic ductal adenocarcinomas found in each cohort analyzed by H&E staining and immunohistochemistry of tdTomato, CK19, and p53. Scale Bar = 100 μm. Symptoms Ascites 33% - - Bowel Obstruction - 25% 33% 33% - - Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H Jaundice A. Whole-Mount Bright-field Fluorescent Primary Tumor Grade Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H Moderately/Well-Differentiated Adenocarcinoma 33% 75% 33% Poorly-Differentiated Adenocarcinoma 33% 25% 67% 33% - - Sarcomatoid Carcinoma B. C. 0 100 200 300 400 0 20 40 60 80 100 Days Post-Tamoxifen Pancreatic Cancer Free Survival 0 100 200 300 400 0 20 40 60 80 100 Days Post-Tamoxifen Overall survival Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H n=17 n=18 n=19 ns ns Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H n=17 n=18 n=19 ns ns D. H&E tdTomato CK19 Trp53fl/LSL-R172H Trp53fl/- Trp53fl/LSL-R270H p53 E. F. BF2020 20x 100um BF1709 20x 100um BF2596 20x 100um plementary Figure 3: Analysis of pancreatic cancer development from adult mouse ductal cells Representative bright-field and fluorescence dissecting scope images of a primary pancreatic tumor in a KT;Sox9CreER;Trp53fl/fl mouse. Scale Bar = 2 cm. (B) Kaplan-Meier analysis of creatic cancer-free survival of KT;Sox9CreER;Trp53fl/x (where x represents different Trp53 alleles) cohorts. Labels indicate the Trp53 status of each cohort. Pancreatic cancer free surviv- KT;Sox9CreER;Trp53fl/LSL-R172H mice (n = 17) and KT;Sox9CreER;Trp53fl/LSL-R270H mice (n = 18) is similar to KT;Sox9CreER;Trp53fl/- mice (n = 19), using the log-rank test. Not significant (C) Kaplan-Meier analysis of overall survival of KT;Sox9CreER;Trp53fl/x (where x represents different Trp53 alleles) cohorts. Labels indicate the Trp53 status of each cohort. Pancreatic cer free survival in KT;Sox9CreER;Trp53fl/LSL-R172H mice (n = 17) and KT;Sox9CreER;Trp53fl/LSL-R270H mice (n = 18) is similar to KT;Sox9CreER;Trp53fl/- mice (n = 19), based on the log-rank Not significant = ns. (D) Table summarizing the percentages of pancreatic tumor-bearing KT;Sox9CreER;Trp53fl/- (n = 3), KT;Sox9CreER;Trp53fl/LSL-R172H (n = 4), and KT;Sox- eER;Trp53fl/LSL-R270H (n = 3) mice presenting with clinical symptoms of pancreatic cancer (ascites, bowel obstruction, and jaundice) at morbidity. (E) Table summarizing the percentages ancreatic tumor-bearing KT;Sox9CreER;Trp53fl/- (n = 3), KT;Sox9CreER;Trp53fl/LSL-R172H (n = 4) , and KT;Sox9CreER;Trp53fl/LSL-R270H (n = 3) mice with the primary pancreatic tumor grade mprising >50% of the tumor) called as moderately/well-differentiated adenocarcinoma, poorly-differentiated adenocarcinoma, or sarcomatoid carcinoma. (F) Representative histological es of the pancreatic ductal adenocarcinomas found in each cohort analyzed by H&E staining and immunohistochemistry of tdTomato, CK19, and p53. Scale Bar = 100 μm. Symptoms Ascites 33% - - Bowel Obstruction - 25% 33% 33% - - Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H Jaundice A. Whole-Mount Bright-field Fluorescent Primary Tumor Grade Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H Moderately/Well-Differentiated Adenocarcinoma 33% 75% 33% Poorly-Differentiated Adenocarcinoma 33% 25% 67% 33% - - Sarcomatoid Carcinoma B. C. 0 100 200 300 400 0 20 40 60 80 100 Days Post-Tamoxifen Pancreatic Cancer Free Survival 0 100 200 300 400 0 20 40 60 80 100 Days Post-Tamoxifen Overall survival Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H n=17 n=18 n=19 ns ns Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H n=17 n=18 n=19 ns ns B. C. D. H&E tdTomato CK19 Trp53fl/LSL-R172H Trp53fl/- Trp53fl/LSL-R270H p53 E. F. BF2020 20x 100um BF1709 20x 100um BF2596 20x 100um plementary Figure 3: Analysis of pancreatic cancer development from adult mouse ductal cells Representative bright-field and fluorescence dissecting scope images of a primary pancreatic tumor in a KT;Sox9CreER;Trp53fl/fl mouse. Scale Bar = 2 cm. (B) Kaplan-Meier analysis of creatic cancer-free survival of KT;Sox9CreER;Trp53fl/x (where x represents different Trp53 alleles) cohorts. Labels indicate the Trp53 status of each cohort. Pancreatic cancer free surviv- KT;Sox9CreER;Trp53fl/LSL-R172H mice (n = 17) and KT;Sox9CreER;Trp53fl/LSL-R270H mice (n = 18) is similar to KT;Sox9CreER;Trp53fl/- mice (n = 19), using the log-rank test. Not significant (C) Kaplan-Meier analysis of overall survival of KT;Sox9CreER;Trp53fl/x (where x represents different Trp53 alleles) cohorts. Labels indicate the Trp53 status of each cohort. Pancreatic cer free survival in KT;Sox9CreER;Trp53fl/LSL-R172H mice (n = 17) and KT;Sox9CreER;Trp53fl/LSL-R270H mice (n = 18) is similar to KT;Sox9CreER;Trp53fl/- mice (n = 19), based on the log-rank Not significant = ns. (D) Table summarizing the percentages of pancreatic tumor-bearing KT;Sox9CreER;Trp53fl/- (n = 3), KT;Sox9CreER;Trp53fl/LSL-R172H (n = 4), and KT;Sox- eER;Trp53fl/LSL-R270H (n = 3) mice presenting with clinical symptoms of pancreatic cancer (ascites, bowel obstruction, and jaundice) at morbidity. (E) Table summarizing the percentages ancreatic tumor-bearing KT;Sox9CreER;Trp53fl/- (n = 3), KT;Sox9CreER;Trp53fl/LSL-R172H (n = 4) , and KT;Sox9CreER;Trp53fl/LSL-R270H (n = 3) mice with the primary pancreatic tumor grade mprising >50% of the tumor) called as moderately/well-differentiated adenocarcinoma, poorly-differentiated adenocarcinoma, or sarcomatoid carcinoma. (F) Representative histological es of the pancreatic ductal adenocarcinomas found in each cohort analyzed by H&E staining and immunohistochemistry of tdTomato, CK19, and p53. Scale Bar = 100 μm. Symptoms Ascites 33% - - Bowel Obstruction - 25% 33% 33% - - Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H Jaundice A. Whole-Mount Bright-field Fluorescent Primary Tumor Grade Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H Moderately/Well-Differentiated Adenocarcinoma 33% 75% 33% Poorly-Differentiated Adenocarcinoma 33% 25% 67% 33% - - Sarcomatoid Carcinoma B. C. 0 100 200 300 400 0 20 40 60 80 100 Days Post-Tamoxifen Pancreatic Cancer Free Survival 0 100 200 300 400 0 20 40 60 80 100 Days Post-Tamoxifen Overall survival Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H n=17 n=18 n=19 ns ns Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H n=17 n=18 n=19 ns ns 0 100 200 300 400 0 20 40 60 80 100 Days Post-Tamoxifen Pancreatic Cancer Free Survival 0 100 200 300 400 0 20 40 60 80 100 Days Post-Tamoxifen Overall survival Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H n=17 n=18 n=19 ns ns Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H n=17 n=18 n=19 ns ns B. C 0 100 200 300 400 0 20 40 60 80 100 Days Post-Tamoxifen Pancreatic Cancer Free Survival Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H n=17 n=18 n=19 ns ns C. 0 100 200 300 400 0 20 40 60 80 100 Days Post-Tamoxifen Overall survival Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H n=17 n=18 n=19 ns ns A. Whole-Mount Bright-field Fluorescent C. B. A. H&E tdTomato CK19 Trp53fl/LSL-R172H Trp53fl/- Trp53fl/LSL-R270H p53 F. BF2020 20x 100um BF1709 20x 100um BF2596 20x 100um F. D. E. Symptoms Ascites 33% - - Bowel Obstruction - 25% 33% 33% - - Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H Jaundice F Primary Tumor Grade Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H Moderately/Well-Differentiated Adenocarcinoma 33% 75% 33% Poorly-Differentiated Adenocarcinoma 33% 25% 67% 33% - - Sarcomatoid Carcinoma D. E. ntary Figure 3: Analysis of pancreatic cancer development from adult mouse ductal cells entative bright-field and fluorescence dissecting scope images of a primary pancreatic tumor in a KT;Sox9CreER;Trp53fl/fl mouse. Scale Bar = 2 cm. (B) Kaplan-Meier analysis of cancer-free survival of KT;Sox9CreER;Trp53fl/x (where x represents different Trp53 alleles) cohorts. Labels indicate the Trp53 status of each cohort. Pancreatic cancer free surviv- x9CreER;Trp53fl/LSL-R172H mice (n = 17) and KT;Sox9CreER;Trp53fl/LSL-R270H mice (n = 18) is similar to KT;Sox9CreER;Trp53fl/- mice (n = 19), using the log-rank test. Not significant aplan-Meier analysis of overall survival of KT;Sox9CreER;Trp53fl/x (where x represents different Trp53 alleles) cohorts. Labels indicate the Trp53 status of each cohort. Pancreatic survival in KT;Sox9CreER;Trp53fl/LSL-R172H mice (n = 17) and KT;Sox9CreER;Trp53fl/LSL-R270H mice (n = 18) is similar to KT;Sox9CreER;Trp53fl/- mice (n = 19), based on the log-rank gnificant = ns. (D) Table summarizing the percentages of pancreatic tumor-bearing KT;Sox9CreER;Trp53fl/- (n = 3), KT;Sox9CreER;Trp53fl/LSL-R172H (n = 4), and KT;Sox- p53fl/LSL-R270H (n = 3) mice presenting with clinical symptoms of pancreatic cancer (ascites, bowel obstruction, and jaundice) at morbidity. (E) Table summarizing the percentages c tumor-bearing KT;Sox9CreER;Trp53fl/- (n = 3), KT;Sox9CreER;Trp53fl/LSL-R172H (n = 4) , and KT;Sox9CreER;Trp53fl/LSL-R270H (n = 3) mice with the primary pancreatic tumor grade >50% of the tumor) called as moderately/well-differentiated adenocarcinoma, poorly-differentiated adenocarcinoma, or sarcomatoid carcinoma. D. H&E tdTomato CK19 Trp53fl/LSL-R172H Trp53fl/- Trp53fl/LSL-R270H p53 E. F. BF2020 20x 100um BF1709 20x 100um BF2596 20x 100um plementary Figure 3: Analysis of pancreatic cancer development from adult mouse ductal cells Representative bright-field and fluorescence dissecting scope images of a primary pancreatic tumor in a KT;Sox9CreER;Trp53fl/fl mouse. Scale Bar = 2 cm. (B) Kaplan-Meier analysis of creatic cancer-free survival of KT;Sox9CreER;Trp53fl/x (where x represents different Trp53 alleles) cohorts. Labels indicate the Trp53 status of each cohort. Pancreatic cancer free surviv- KT;Sox9CreER;Trp53fl/LSL-R172H mice (n = 17) and KT;Sox9CreER;Trp53fl/LSL-R270H mice (n = 18) is similar to KT;Sox9CreER;Trp53fl/- mice (n = 19), using the log-rank test. Not significant (C) Kaplan-Meier analysis of overall survival of KT;Sox9CreER;Trp53fl/x (where x represents different Trp53 alleles) cohorts. Labels indicate the Trp53 status of each cohort. Pancreatic cer free survival in KT;Sox9CreER;Trp53fl/LSL-R172H mice (n = 17) and KT;Sox9CreER;Trp53fl/LSL-R270H mice (n = 18) is similar to KT;Sox9CreER;Trp53fl/- mice (n = 19), based on the log-rank Not significant = ns. (D) Table summarizing the percentages of pancreatic tumor-bearing KT;Sox9CreER;Trp53fl/- (n = 3), KT;Sox9CreER;Trp53fl/LSL-R172H (n = 4), and KT;Sox- eER;Trp53fl/LSL-R270H (n = 3) mice presenting with clinical symptoms of pancreatic cancer (ascites, bowel obstruction, and jaundice) at morbidity. (E) Table summarizing the percentages ancreatic tumor-bearing KT;Sox9CreER;Trp53fl/- (n = 3), KT;Sox9CreER;Trp53fl/LSL-R172H (n = 4) , and KT;Sox9CreER;Trp53fl/LSL-R270H (n = 3) mice with the primary pancreatic tumor grade mprising >50% of the tumor) called as moderately/well-differentiated adenocarcinoma, poorly-differentiated adenocarcinoma, or sarcomatoid carcinoma. (F) Representative histological es of the pancreatic ductal adenocarcinomas found in each cohort analyzed by H&E staining and immunohistochemistry of tdTomato, CK19, and p53. Scale Bar = 100 μm. Symptoms Ascites 33% - - Bowel Obstruction - 25% 33% 33% - - Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H Jaundice A. Whole-Mount Bright-field Fluorescent Primary Tumor Grade Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H Moderately/Well-Differentiated Adenocarcinoma 33% 75% 33% Poorly-Differentiated Adenocarcinoma 33% 25% 67% 33% - - Sarcomatoid Carcinoma B. C. 0 100 200 300 400 0 20 40 60 80 100 Days Post-Tamoxifen Pancreatic Cancer Free Survival 0 100 200 300 400 0 20 40 60 80 100 Days Post-Tamoxifen Overall survival Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H n=17 n=18 n=19 ns ns Trp53fl/- Trp53fl/LSL-R172H Trp53fl/LSL-R270H n=17 n=18 n=19 ns ns (F) Representative histological he pancreatic ductal adenocarcinomas found in each cohort analyzed by H&E staining and immunohistochemistry of tdTomato, CK19, and p53. Scale Bar = 100 μm. Supplementary Figure 3: Analysis of pancreatic cancer development from adult mouse ductal cells (A) Representative bright-field and fluorescence dissecting scope images of a primary pancreatic tumor in a KT;Sox9CreER;Trp53fl/fl mouse. Scale Bar = 2 cm. (B) Kaplan-Meier analysis of pancreatic cancer-free survival of KT;Sox9CreER;Trp53fl/x (where x represents different Trp53 alleles) cohorts. Labels indicate the Trp53 status of each cohort. Pancreatic cancer free surviv- al in KT;Sox9CreER;Trp53fl/LSL-R172H mice (n = 17) and KT;Sox9CreER;Trp53fl/LSL-R270H mice (n = 18) is similar to KT;Sox9CreER;Trp53fl/- mice (n = 19), using the log-rank test. Not significant = ns. (C) Kaplan-Meier analysis of overall survival of KT;Sox9CreER;Trp53fl/x (where x represents different Trp53 alleles) cohorts. Labels indicate the Trp53 status of each cohort. Pancreatic cancer free survival in KT;Sox9CreER;Trp53fl/LSL-R172H mice (n = 17) and KT;Sox9CreER;Trp53fl/LSL-R270H mice (n = 18) is similar to KT;Sox9CreER;Trp53fl/- mice (n = 19), based on the log-rank test. Not significant = ns. (D) Table summarizing the percentages of pancreatic tumor-bearing KT;Sox9CreER;Trp53fl/- (n = 3), KT;Sox9CreER;Trp53fl/LSL-R172H (n = 4), and KT;Sox- 9CreER;Trp53fl/LSL-R270H (n = 3) mice presenting with clinical symptoms of pancreatic cancer (ascites, bowel obstruction, and jaundice) at morbidity. (E) Table summarizing the percentages of pancreatic tumor-bearing KT;Sox9CreER;Trp53fl/- (n = 3), KT;Sox9CreER;Trp53fl/LSL-R172H (n = 4) , and KT;Sox9CreER;Trp53fl/LSL-R270H (n = 3) mice with the primary pancreatic tumor grade (comprising >50% of the tumor) called as moderately/well-differentiated adenocarcinoma, poorly-differentiated adenocarcinoma, or sarcomatoid carcinoma. (F) Representative histologica images of the pancreatic ductal adenocarcinomas found in each cohort analyzed by H&E staining and immunohistochemistry of tdTomato, CK19, and p53. Scale Bar = 100 μm.
https://openalex.org/W3088351420	https://hal.science/hal-03027250/document	English	null	A Socio-Seismology Experiment in Haiti	Frontiers in earth science	2,020	cc-by	10,605	ORIGINAL RESEARCH published: 25 September 2020 doi: 10.3389/feart.2020.542654 A Socio-Seismology Experiment in Haiti Eric Calais 1,2, Dominique Boisson 3, Steeve Symithe 3, Claude Prépetit 4, Bétonus Pierre 4, Sophia Ulyse 4, Laennec Hurbon 5, Alain Gilles 5, Jean-Marie Théodat 6, Tony Monfret 2, Anne Deschamps 2, Françoise Courboulex 2, Jér ˆome Chèze 2, Fabrice Peix 2, Etienne Bertrand 2, Jean-Paul Ampuero 2, Bernard Mercier de Lépinay 2, Julien Balestra 2, Jean-Luc Berenguer 2, Remy Bossu 7,8, Laure Fallou 7 and Valérie Clouard 9 Eric Calais 1,2, Dominique Boisson 3, Steeve Symithe 3, Claude Prépetit 4, Bétonus Pierre 4, Sophia Ulyse 4, Laennec Hurbon 5, Alain Gilles 5, Jean-Marie Théodat 6, Tony Monfret 2, Anne Deschamps 2, Françoise Courboulex 2, Jér ˆome Chèze 2, Fabrice Peix 2, Etienne Bertrand 2, Jean-Paul Ampuero 2, Bernard Mercier de Lépinay 2, Julien Balestra 2, Jean-Luc Berenguer 2, Remy Bossu 7,8, Laure Fallou 7 and Valérie Clouard 9 1École Normale Supérieure, Université PSL, Paris, France, 2Université C ˆote d’Azur, Centre National de la Recherche Scientiﬁque, Institut de Recherche pour le Développement, Observatoire de la C ˆote d’Azur, Géoazur, France, 3Faculté des Sciences, Laboratoire URGéo, Port-au-Prince, Haiti, 4Bureau des Mines et de l’Énergie, Port-au-Prince, Haiti, 5Faculté des Sciences Humaines et Sociales, Port-au-Prince, Haiti, 6École Normale Supérieure, Port-au-Prince, Haiti, 7European-Mediterranean Seismological Center, Arpajon, France, 8Commissariat à l’Energie Atomique, Direction des Applications Militaires, Ile de France, Arpajon, France, 9Observatoire Midi-Pyrénées, Laboratoire Géosciences Environnement Toulouse, Toulouse, France Keywords: earthquake, Haiti, seismic network, risk perception, citizen science Edited by: Jenni Barclay, University of East Anglia, United Kingdom Reviewed by: Kiran Kumar Singh Thingbaijam, Institute of Seismological Research, India Max Hope, Leeds Beckett University, United Kingdom Correspondence: Edited by: Jenni Barclay, University of East Anglia, United Kingdom Earthquake risk reduction approaches classically apply a top-down model where scientiﬁc information is processed to deliver risk mitigation measures and policies understandable by all, while shielding end-users from the initial, possibly complex, information. Alternative community-based models exist but are rarely applied at a large scale and rely on valuable, but non-scientiﬁc, observations and experiences of local populations. In spite of risk reduction efforts based on both approaches, changes in behaviour or policies to reduce earthquake risk are slow or even non-existent, in particular in developing countries. Here we report on the initial stage of a project that aims at testing, through a participatory seismology experiment in Haiti—a country struck by a devastating earthquake in January 2010—whether public or community involvement through the production and usage of seismic information can improve earthquake awareness and, perhaps, induce grassroots protection initiatives. This experiment is made possible by the recent launch of very low-cost, plug-and-play, Raspberry Shake seismological stations, the relative ease of access to the internet even in developing countries such as Haiti, and the familiarity of all with social networks as a way to disseminate information. Our early ﬁndings indicate that 1) the seismic data collected is of sufﬁcient quality for real-time detection and characterization of the regional seismicity, 2) citizens are in demand of earthquake information and trust scientists, even though they appear to see earthquakes through the double lens of tectonics and magic/ religion, 3) the motivation of seismic station hosts has allowed data to ﬂow without interruption for more than a year, including through a major political crisis in the Fall of 2019 and the current COVID19 situation. At this early stage of the project, our observations indicate that citizen-seismology in a development context has potential to engage the public while collecting scientiﬁcally-relevant seismological information. Reviewed by: Kiran Kumar Singh Thingbaijam, Institute of Seismological Research, India Max Hope, Leeds Beckett University, United Kingdom Correspondence: Eric Calais eric.calais@ens.fr Specialty section: This article was submitted to Geohazards and Georisks, a section of the journal Frontiers in Earth Science Received: 13 March 2020 Accepted: 04 September 2020 Published: 25 September 2020 INTRODUCTION to the one we may have toward death (Théodat, 2013; Théodat et al., 2020). “The philosopher is the one who learns to die” says a Michel de Montaigne. Since earthquake disasters occur rarely, the time interval between them within a given territory, a time often longer than a human life, establishes a disconnect between stakeholders and the seismic threat that constantly surrounds them (Moon et al., 2019). The scientiﬁc discourse on the reality of the threat—while the Earth is calm!—is listened to passively, even though with sincerity and interest. This holds particularly true in areas where the culture of seismic risk is low—such as Haiti before the devastating earthquake that struck its capital region in 2010 (Bilham, 2010; Desroches, 2011). Over the past 50 years, earthquakes have cost about US$ 800 billions, mostly in developed countries, and 1.3 million human lives, mostly in developing countries (Bilham, 2013; EM-DAT, 2020). Faced with these ﬁgures, which show no sign of inﬂection over time, the classic and rational approach to reduce earthquake risk is “top-down” (e.g., UNISDR, 2015). It consists in formulating a scientiﬁc discourse—an explanation of the natural phenomenon—then in translating it to the public and decision-makers while adapting the wording to these audiences in order to develop risk awareness and trigger protective measures. In a complementary way, community-based, “bottom-up” approaches are more and more common, but are rarely applied at a large scale. They rely on valuable, but non- scientiﬁc, observations and experiences of local populations (e.g., Fischer, 2000; Sim et al., 2017). One would like to believe that these approaches would lead, over time, to changes in behaviour, or even in policies, so that people and property are better protected against a threat that is often known and quantiﬁed. However, each major earthquake puts us face to face with the obvious: these changes are slow, or even non- existent. Why? Here we report on the initial stage of a participatory seismology project in Haiti (Figure 1) that aims at testing whether public involvement can improve earthquake awareness and grassroots protection initiatives. The project investigates under which conditions a community of citizen- seismologists, in a development context, can collect and share information about earthquakes while producing data that is useful for seismologists. Eventually, one could envision a symbiotic relationship between citizen and scientists where it is recognized that one needs the other to reach their goals. Citation: Calais E, Boisson D, Symithe S, Prépetit C, Pierre B, Ulyse S, Hurbon L, Gilles A, Théodat J-M, Monfret T, Deschamps A, Courboulex F, Chèze J ˆo, Peix F, Bertrand E, Ampuero J-P, Mercier de Lépinay B, Balestra J, Berenguer J-L, Bossu R, Fallou L and Clouard V (2020) A Socio-Seismology Experiment in Haiti. Front. Earth Sci. 8:542654. doi: 10.3389/feart.2020.542654 September 2020 \| Volume 8 \| Article 542654 Frontiers in Earth Science \| www.frontiersin.org A Socio-Seismology Experiment in Haiti Calais et al. INTRODUCTION The expected project outcomes are the conditions under which such a relationship is reachable and sustainable. Disaster risk reduction studies have shown that it is difﬁcult for stakeholders—individuals, their governing bodies, the private sector, etc.—to feel directly concerned by a threat that they do not perceive as immediate (e.g., UNISDR, 2014)—an attitude similar In this paper, we describe the seismic instrumentation put in place and the results of a ﬁrst survey aimed at collecting information on the perception of earthquakes and on the expectations of citizens in terms of earthquake information. FIGURE 1 \| Map of Haiti showing the main active faults (dashed lines), the area most affected by the M7.1, January 12, 2010, earthquake, the location of conventional broadband seismic stations, and the location of Raspberry Shake seismic stations installed to date in the framework of the project described here. FIGURE 1 \| Map of Haiti showing the main active faults (dashed lines), the area most affected by the M7.1, January 12, 2010, earthquake, the location of conventional broadband seismic stations, and the location of Raspberry Shake seismic stations installed to date in the framework of the project described here. September 2020 \| Volume 8 \| Article 542654 Frontiers in Earth Science \| www.frontiersin.org Frontiers in Earth Science \| www.frontiersin.org 2 A Socio-Seismology Experiment in Haiti Calais et al. These ﬁrst steps are key to ensure that 1) the seismic instruments provide data of sufﬁcient quality to produce reliable seismological information, and 2) the information extracted from these data is adapted to the needs and demands of the general public. capacity in seismology may be limited, because the available scientiﬁc discourse is not suited to public expectations, or because national and international institutions may not be keen on listening about earthquakes when climate change, for instance, appears to be a much more pressing issue. The situation described above is exacerbated in Haiti, a country affected on January 12, 2010, by one of largest seismic disasters known. In the late afternoon, a Mw7.0 earthquake struck the capital region of Port-au-Prince, killing more than 100,000 people,1 leaving more than 1.5 million homeless, and destroying most governmental, technical, and educational infrastructure. The event caused an estimated $ 8 billion in damage, equivalent to about 120% of the country’s Gross Domestic Product (Haiti Earthquake PDNA, 2010). CONTEXT Any geoscientist engaged in research with developing countries knows their chronic difﬁculty, despite their heightened vulnerability, in maintaining observation networks of environmental variables for the beneﬁt of protecting societies and citizens from natural threats. Complex technology networks are difﬁcult to maintain there because they require sustained technical and ﬁnancial capacity. This applies to seismic networks, which are expensive mechanical and electronic systems that rely on complex communication protocols. Without constant funding and maintenance, they tend to rapidly fail, so that the information that scientists can provide to the public or to decision-makers may become minimal or even inexistent. These failures, in turn, perpetuate the notion that these networks are, apparently, of little use. The lack of earthquake information raises the risk of a misunderstanding of what science can do, and perhaps even a public denial of science, which may appear useless since it does not provide a concrete answer to questions as common as “when will the next earthquake take place?”. On the other hand, the public is placed in a situation of passivity with regard to the scientiﬁc information. Its knowledge of earthquakes progresses little and the threat remains a theoretical possibility not integrated into daily life. Finally, this situation of under-information and/or information provided only by “ofﬁcial” national seismological institutes is conducive to the spread of rumours, false information, and even conspiracy theories. In the end, decision-making in the face of seismic risk may use the rational in a rather limited way. During the 2019 seismic sequence in Mayotte, for example, the lack of communication from the scientiﬁc community and the authorities, added to the local socio-cultural context, led citizens to consider false information and conspiracy theories as the only rational explanations in the face of unexplained seismic events and the silence of these authorities. By organizing themselves on the Facebook social network, citizens compiled information and developed their own expertize (Fallou and Bossu, 2019; Fallou et al., 2020). Following the 2010 event, a national seismological network was set up, maintained by a governmental institution (Bureau of Mines and Energy, BME), which currently operates ﬁve broadband seismic stations (Figure 1; Bent et al., 2018). On October 7, 2018 an earthquake of magnitude 5.9 in the north- western part of the country killed 17 people and caused signiﬁcant structural damage. None of the Haitian seismic stations was functional at the time. 1Estimates vary between 225,000 (SNGRD, 2010), 137,000 (Daniell et al., 2013), 159,000 (Kolbe et al., 2010), and 46,000–8,500 (Schwattz et al., 2017), see also Corbet (2014). INTRODUCTION No earthquake of such moderate magnitude had ever caused so many causalities and such extensive damage (Bilham, 2012). Before that dramatic event, the culture of seismic risk in Haiti was essentially inexistent, even though initiatives from the Civil Protection Agency were in place and scientiﬁc information on the hazard level was available (e.g., Manaker et al., 2008). The previous earthquake disaster had occurred 168 years earlier, in 1842, striking the northern part of the country and killing close to half of the population of Cape Haitian (Scherer, 1912). Frontiers in Earth Science \| www.frontiersin.org CONTEXT technical expertize required is more and more often perceived by citizens as biased toward risky solutions designed to the advantage of the business and political elites. The participation of citizens in the production of scientiﬁc information and in its usage to inﬂuence policies is, in theory, a way to reconcile these two propositions, but there is no ideal model for applying this apparently straightforward concept. pp y g p For instance, Irvin (1995) argues that the public views on environmental risks is largely overlooked and describes a participatory, dialogical approach where citizens are given a prominent role in environmental risk management—though his argument addresses mostly the social aspects of this issue. Other workers, in particular from development and political economy perspectives, are more sceptical. For instance, Hickey and Mohann (2004) argue that, even though the collection of environmental data by citizens or communities may be of some superﬁcial use, participation approaches in international development practices have not led to much transformative and sustainable progress for marginal peoples because “politics matter.” Indeed, environmental issues are dynamically linked to socio-economic ones such as political decision making, poverty reduction, enhancing local democracy, social justice, gender inequalities, etc. For instance, there are evidence that higher-income countries tend to be more sensitive to risks arising from human actions (nuclear, pollution, etc.) while they also tend to underestimate the risks of natural hazards (Johnston et al., 2013; Yamori, 2013). In low-income countries, most poor and vulnerable people live in permanent risk and uncertainty—economic, political, social, etc.—and therefore struggle to determine a future. But if there is no future—ultimately no real world—then the very notion of risk disappears (Hurbon, 2014). In Bangladesh, a country particularly exposed to ﬂooding, Jabeen and Johnston (2013) show that “people do not distinguish between hazards and other life stresses, but instead prepare for a range of possible negative events” and have developed a range of simple coping strategies that allow them to continue living in highly exposed areas. Cultural inﬂuences also play an important role (Solberg et al., 2010) as risk perception is a matter of choice and interpretation of reality rather than open-page reading in a world of unambiguous codes (Théodat, 2010). In Haiti, the pervasive presence of vodoo likely affects risk perception, though in ways that have not yet been investigated (Hurbon, 2014). CONTEXT As a result, the national civil protection agency and the population had to rely on information from the U.S. Geological Survey, which only reports on events of magnitude greater than 4–4.5 in the region. This illustrates the difﬁculty of maintaining the operability of such a system and to provide quick and independent information to the public. It is essential that seismologists monitor earthquakes with high-quality—though expensive—sensors located at carefully chosen sites where environmental noise is minimal, and try to ensure constant real-time data communication, for instance via satellite links. However, in the age of social media and participatory science, complementary ways to produce reliable and actionable earthquake information through the involvement of citizens and/or communities are emerging (e.g., Bossu et al., 2018a; Hicks et al., 2019) that warrant further investigation. The concept of citizen-science has emerged in part as a consequence of the use of professional expertize in the ﬁelds of environmental science, and of the tension that arises between expertize and democratic governance (Fischer, 2000). Indeed, analyzing and ﬁnding solutions to most environmental issues—seismic hazard being one of them—require training or time that is beyond what most citizens can afford, while the In developing countries exposed to earthquakes, which are also the most vulnerable to that threat, relying on ofﬁcial institutions for information production and communication has limitations for ﬁnancial reasons (the state and its donors have limited resources that they must direct to short-term objectives: elections, hunger, poverty, etc.), for reasons of continuity (very fast turn-over within institutions, little or no planning, lack of long-term vision, etc.), and for political reasons (earthquakes are too rare to affect anyone’s election, protection is expensive, etc.). Relying only on the scientiﬁc community has limitations for ﬁnancial reasons as well (maintaining networks is expensive and resources are scarce), but also because technical September 2020 \| Volume 8 \| Article 542654 Frontiers in Earth Science \| www.frontiersin.org 3 A Socio-Seismology Experiment in Haiti Calais et al. increasing public understanding should develop a “culture of risk” (e.g., UNISDR, 2015) and stimulate individuals and communities to take appropriate protective actions (Twigg, 2004). However, this apparently simple logics must face the highly variable values and priorities of people and communities exposed to environmental hazards across cultures, socio-economic classes, genders, etc. (Löfstedt and Frewer, 1998). CONTEXT One may forecast the coexistence of an objective register—where the earthquake is a telluric reality—with a magical and religious one—where scientiﬁc reality is absent but that nevertheless provides other ways to cope with hazards and uncertainties. It is only recently that researchers from the broad ﬁeld of “geosciences,” deﬁned here as “physics and chemistry of our planetary environment,” have embraced the concept of participatory-, or citizen-science. They have been largely absent from the debate described above, as they also are largely absent from the scene of international development. In seismology, early efforts to bridge basic research with the broader public in a systemic way took place in the framework of education programs in primary and/or high schools (e.g., Cantore et al., 2003; Levy and Taber, 2005; Courboulex et al., 2012). These programs paved the way for the design of affordable and low- maintenance seismic instruments, as well as for the realization of the scientiﬁc value of the data they produce (e.g., Anthony et al., 2018; Calais et al., 2019; Schlupp et al., 2019). But the contextualization of such efforts in the broader scheme of risk perception and management, of socio-economic development, or of public policies is rarely accounted for in seismology-driven projects. Clearly, the factors that shape hazard perception are multiple—lack of awareness of infrequent high impact events, poverty, gender inequality, political and economic stresses, etc. The project described in this paper will attempt to better understand the multiplicity of those factors and the interactions between them, using low-cost seismic stations as a way to engage citizens in a dialog with scientists. As this early stage of the project, this paper aims at describing its motivations and setup, as well as the results of a ﬁrst a baseline survey on earthquake and risk perception. The experiment described here aims at using affordable and low-maintenance seismic instruments to go one step further by 1) involving seismologists in development science, taking advantage of the fact that they are—by design!—interested in long-term (>10 years) observations, as opposed to the short-term nature of most international development projects, and 2) using Raspberry Shake (RS) instruments as a sort of “alibi” to probe how citizens of a developing country perceive their seismological environment and how to best work with them in order to build a mutually- beneﬁcial relationship between (seismological) science and society. 2https://raspberryshake.org. Frontiers in Earth Science \| www.frontiersin.org METHODOLOGY Our objective is to test, through a participatory seismology experiment, whether citizen or community involvement through the production and usage of seismic information can improve earthquake awareness and, perhaps, induce grassroots protection initiatives. This experiment is made possible by 1) the recent launch of very low cost seismological stations with minimal maintenance (RS,2), 2) the relative ease of access to the internet, even in developing countries such as Haiti, 3) the That community participation in data or knowledge production enhances risk perception—although it is a tenant of most citizen-science projects—is of course not granted. Enhancing risk perception continues to be at the core of international efforts to reduce environmental risks as September 2020 \| Volume 8 \| Article 542654 Frontiers in Earth Science \| www.frontiersin.org 4 A Socio-Seismology Experiment in Haiti Calais et al. the most likely platform to be available/easy to use for respondent (a simple Google form). We made sure that the questions would be understandable by the broadest audience by ﬁrst testing them on a pilot sample of students from all disciplines. We optimized the content through a series of iterations on the list of questions and their speciﬁc wordings between the sociologists and seismologist of the project. In order to maximize response rates, we used the 10th anniversary of the January 12, in 2020, earthquake to disseminate information about the questionnaire as widely as possible. We did so by using the main national media as well as social platforms such as Facebook and WhatsApp, which are the two most widely used ones in Haiti. We made sure that the survey format was simple and usable on a simple smartphone, without photos or videos that would affect the respondents’ bandwidth, and that it could be answered in less than 15 min. As the January 12, 2020, earthquake has been—and remains—traumatic for a number of Haitians, we introduced as a ﬁrst question “I do not wish to answer this questionnaire because I am still too affected by January 12, 2010.” Finally, the survey was designed to be entirely anonymous. possibility to distribute information through simple smartphone applications that anyone can handle, 4) the existence of social networks as a way to share and disseminate information. A similar initiative using RS instruments is on-going in Nepal, focused on schools (Subedi et al., 2020, submitted). METHODOLOGY This project3 is exploratory in nature as we are embarking on a direction that has not yet been systematically investigated. Indeed, if several hundreds of these very low-cost seismological stations exist in the world, there is not yet an integrated scientiﬁc study of their impact both on regional seismological knowledge or on the perception of seismology and seismic risk amongst their hosts. It is different from a classic community-based approach to risk reduction because it includes a signiﬁcant scientiﬁc element through the usage of RS seismometers. Putting citizens at the core of a scientiﬁc project, while placing scientists in a position of support, is not a natural process. There is no guarantee that this strategy will gain support amongst the public, especially in a development context, but it is important to learn from it both on the standpoint of the usability of the RS instruments and of the perception of risk. Addressing such issues implies research at the boundary between seismology and social/behavioural sciences. We are well aware that such an online survey necessarily samples the Haitian population in a biased manner, as it favours a social class that has easy access to the internet, is literate and urban, and is motivated enough to respond. Indeed, the literacy rate in Haiti is 53%, the unemployment rate 41%, and the percentage of the population below the poverty line (living with less than US$ 3/day) 51%. We tried to reduce the sampling bias by administering the questionnaire in the streets of Port-au-Prince during the week of January 12, 2010, targeting popular neighbourhoods. The seismology part of the project consists in installing RS stations in collaboration with citizens, collecting and processing the resulting data, and making information on earthquake locations and magnitudes available to the public in quasi-real time. The sociology part of this project was intended to capitalize on the availability of RS stations for a low price and of this quasi- real time information on earthquakes. We had envisioned to constitute two groups of individuals, one equipped with RS instruments and duly informed of their signiﬁcance, the other group unequipped and uninformed. This would allow us to evaluate, over time, the impact of using the RS and receiving privileged information on the perception of earthquake and the associated risk. 3“Socio-Seismology of earthquake Risk in HAIti,” acronym “S2RHAI.” METHODOLOGY We identiﬁed two groups around Léogˆane (very much affected in 2010) and Cap Haïtien (high risk but no recent earthquake), to be surveyed by master students from the Faculty of Social Sciences of Port-au-Prince. Unfortunately, the deplorable political and security situation in Haiti from September to December 2019, almost directly followed by the COVID19 sanitary crisis, did not allow students to travel to the provinces. We therefore decided to set up an alternative methodology in order to obtain a minimum of sociological data usable for our project. We put together, distributed, and analyzed an online questionnaire (in French and in Creole) in order to collect quantitative information on the perception of earthquakes and the citizens’ information expectations. The form was built collaboratively by seismologists and sociologists—the ﬁrst tangible interdisciplinary collaboration within the project. Seismology h gy Interacting with citizens requires that we are able to use the information they produce to determine earthquake locations and magnitudes in near-real time on the Haitian territory. This is especially important when events are felt by the population. Since it was unrealistic to try and convince individuals to acquire a RS station and become part of a project that had not even started, we purchased 15 RS4D seismic stations that we installed at private homes across the country (Figure 1). The only required condition was access to electricity and internet, though we prioritized some locations in order to optimize the network geometry. Given that the objective of the project is to test a citizen seismological network, we did not make much efforts to ensure that the site noise conditions were optimal. The stations are placed on the ground ﬂoor of the house, often in the living room, in a place as far as possible from environmental noise disturbances (Figure 2). We deliberately did not provide training to the hosts, as we hope to observe if/how the presence of a RS stations may lead them to spontaneously requests more information earthquakes, preparedness, etc., and under what format. Online surveys have indeed become increasingly prevalent in research inquiries, though they should comply with “good practices” in order to be efﬁcient, useful, and ethical (e.g., Buchanan and Hvizdak, 2009; Alessi and Martin, 2010; McInroy, 2016). The online methodology we used considered So far, the hosts are volunteers known to the project participants. We aim at diversifying the host population in order to increase the number of stations, but also the number September 2020 \| Volume 8 \| Article 542654 Frontiers in Earth Science \| www.frontiersin.org 5 Calais et al. A Socio-Seismology Experiment in Haiti FIGURE 2 \| Example of a Raspberry Shake (RS) station installed in Jérémie (Figure 1) with its host on the right, M. Guild Mézile, a local farmer. The instrument is placed on the ground ﬂoor of his home, with good access to electricity—thanks to a local generator—and to the internet. Steeve Symithe is pointing at the RS station, with the internet modem on the ﬂoor just behind the host. This station has been up and running 75% of the time since it was installed on September 11, 2019. Seismology h Written informed consent was obtained from the individuals for the publication of any potentially identiﬁable images or data included in this article. FIGURE 2 \| Example of a Raspberry Shake (RS) station installed in Jérémie (Figure 1) with its host on the right, M. Guild Mézile, a local farmer. The instrument is placed on the ground ﬂoor of his home, with good access to electricity—thanks to a local generator—and to the internet. Steeve Symithe is pointing at the RS station, with the internet modem on the ﬂoor just behind the host. This station has been up and running 75% of the time since it was installed on September 11, 2019. Written informed consent was obtained from the individuals for the publication of any potentially identiﬁable images or data included in this article. stations in the Dominican Republic, Jamaica, Cuba, Bahamas, and Puerto Rico whose data are publicly available. Third, we conﬁgured an automated near-real-time detection system based on the SEISCOMP3 software (Weber et al., 2007). Automatic detection can be quite complex with RS stations, whose noise level can vary signiﬁcantly from one station to another as well as during the course of a day. We are continuing to investigate how to optimally parameterize this system in the context of Haiti. of individuals with whom we can interact—or who can interact with each other via social media. In order to stimulate this interaction, we created a WhatsApp group dedicated to the hosts, as this media is one of the most prominently used in Haiti. The group, with currently 30 participants, is intended to share information produced by hosts and other citizens that can be veriﬁed and certiﬁed by scientists. We have observed that this generally quiet group becomes very active as soon as an earthquake is felt, with immediate requests for information. On the other hand, there is little activity in the absence of a felt earthquake. How to best use this down-time to keep hosts—and eventually the general public—engaged is a yet unsolved question, part of our upcoming research objectives. Finally, we installed a web server for disseminating the information through a simple, interactive, map interface where earthquake locations and magnitudes are readily visible5. This interface also provides quantitative information to seismologists such as visualization of the seismic traces and statistics on the quality of detections. This server has been continuously operational since August 1, 2019. 5http://ayiti.unice.fr/ayiti-seismes/. 4http://sismoazur.oca.eu. Seismology h Each earthquake detected and automatically characterized ﬁrst appears as “not yet conﬁrmed.” It is then checked and validated, or rejected, by a seismologist. We developed an automated system for rapid and automatic earthquake detection and location/magnitude determination. The system, called “Ayiti-séismes” is portable and meant to be transferred to Haiti. It is based on developments implemented at the Géoazur laboratory4 to display regional earthquake information in the south-east of France. First, we developed a VPN software that we installed on each RS station in order to allow for real-time data recovery via the “seedlink” protocol. The data still also ﬂows to the open-access OSOP server, the default procedure for RS stations worldwide, but our additional link ensures a better control of the data ﬂow. Second, we implemented a server that aggregates data ﬂows in real time from 11 RS stations, 3 broadband stations in Haiti, and 14 regional We used the August 1 to December 31, 2019, time interval for an initial assessment of the performance of Ayiti-séismes by comparing its location and magnitude (M) determinations with those of the Haitian seismological network (BME) and of the Loyola Polytechnic Seismological Observatory (OSPL) in the Dominican Republic (Figure 3). The latter is mainly focused on the south-eastern part of the island (Rodriguez et al., 2018). Within the “Haiti” region (17.04–1.41°N; 71.48–76.31°W), the September 2020 \| Volume 8 \| Article 542654 Frontiers in Earth Science \| www.frontiersin.org 6 A Socio-Seismology Experiment in Haiti Calais et al. FIGURE 3 \| Comparisons of earthquake locations for the August 1, 2019 to December 31, 2019 time interval. Top right: the U.S. Geological Survey uses a global distribution of seismic stations and, for the Haiti region, reports events with magnitude greater than 4–4.5. Top left: the Haiti Bureau of Mines and Energy uses its broadband stations (Figure 1) and several other regional stations. During the time interval considered here, their operations were severely affected by the political crisis in Haiti, which limited the number of events they could detect. Bottom-left: the Loyola Polytechnic Seismological Observatory (OSPL) in the Dominican Republic uses their own stations in the southern part of their country, which explains the larger number of detections in the south-eastern corner of the map. Bottom right: Ayiti-séismes uses Raspberry Shake and broadband stations in Haiti, as well as 20 other regional stations. Its magnitudes may be slightly overestimated, as discussed in the text. Seismology h FIGURE 3 \| Comparisons of earthquake locations for the August 1, 2019 to December 31, 2019 time interval. Top right: the U.S. Geological Survey uses a global distribution of seismic stations and, for the Haiti region, reports events with magnitude greater than 4–4.5. Top left: the Haiti Bureau of Mines and Energy uses its broadband stations (Figure 1) and several other regional stations. During the time interval considered here, their operations were severely affected by the political crisis in Haiti, which limited the number of events they could detect. Bottom-left: the Loyola Polytechnic Seismological Observatory (OSPL) in the Dominican Republic uses their own stations in the southern part of their country, which explains the larger number of detections in the south-eastern corner of the map. Bottom right: Ayiti-séismes uses Raspberry Shake and broadband stations in Haiti, as well as 20 other regional stations. Its magnitudes may be slightly overestimated, as discussed in the text. FIGURE 4 \| Number of Ayiti-séismes determinations as a function of magnitude illustrating a completeness magnitude between 2.5 and 3 Mlv. BME reported 33 events (2.2 < M < 4.8), OSPL 246 events (0.6 < M < 4.4), and Ayiti-séismes 146 events (1.5 < M < 5.0). Of the 33 BME events, 31 were detected by the OSPL and 29 by Ayiti- séismes. During the same time interval, the U.S. Geological Survey reported only two events (M4.8 and M5.0). y y The difference between the OSPL and Ayiti-séismes catalogues concerns, 89% of the time, events of magnitude 0.5–2.25 that are located in the southernmost part of the Dominican Republic, where the OSPL seismological stations are concentrated. These earthquakes are currently undetectable by Ayiti-séismes. Event locations are consistent within 25 km between Ayiti-séismes and OSPL, but can differ from those of the BME by up to 90 km. As both Ayiti-séismes and BME use the IASPEI91 global seismic velocity model, whereas OSLPL uses a more suitable regional model (Rodriguez et al., 2018), we assume that the location differences with BME are the result of the smaller number of seismic stations they use. We also observed that the Ayiti-séismes magnitudes are systematically larger than those of OSPL. Resolving this issue requires discussions with network operators to ascertain the instrumental responses and attenuation equations they use. FIGURE 4 \| Number of Ayiti-séismes determinations as a function of magnitude illustrating a completeness magnitude between 2.5 and 3 Mlv. Seismology h FIGURE 4 \| Number of Ayiti-séismes determinations as a function of magnitude illustrating a completeness magnitude between 2.5 and 3 Mlv. September 2020 \| Volume 8 \| Article 542654 Frontiers in Earth Science \| www.frontiersin.org 7 A Socio-Seismology Experiment in Haiti Calais et al. what was going on. Some thought of “the end of the world” (11%), “a divine punishment that had befallen us” (3%), or that “our contract with Earth had ended” (2%). This latter answer was meant for vodou believers, for whom there is an actual contract between mankind and nature, brokered by the vodou spirits (or “loas”). The proﬁle of the respondents and the mode of survey may underestimate the importance of such religious beliefs. In summary, the installation of RS stations in Haiti, coupled with permanent regional seismic stations and the implementation of an automated, quasi-real time, earthquake detection and characterization system provide rapid seismological information for any earthquake of magnitude greater than ∼2.5 (Figure 4), down to events of magnitude 1.5–2.0 under certain conditions. The current limitations of this system are the small number of RS stations currently in operation and the discontinuous availability of broadband station data from the Haitian seismic network (Figure 1). Regarding the former issue, it is not trivial to ﬁnd hosts who can provide continuous electricity and internet everywhere in Haiti. In addition, road conditions and insecurity prevented repairing internet access at some stations or installing instruments at locations where hosting had been established. Some of these difﬁculties are shared with conventional seismic networks, but in several cases of RS misfunction it only took an email to the host to reboot the RS and solve the issue—an advantage of using plug-and-play technology and involving hosts in station management. When asked about the cause of earthquakes, 92% of the respondents chose “the movement of tectonic plates,” 15% “American military experiments,” 6% “oil drilling,” and 5% “divine anger.” The responses also point to alternative explanations that fall either in the mystical or conspiracy areas. Sometimes plate tectonics and an alternative explanation were answered together by the same respondent. There is therefore a certain level of ambivalence in the understanding of the seismic phenomenon. Sixty ﬁve percent of the respondents believe that the likelihood of an earthquake similar to that of 2010 during their lifetime is “very high” (42%) or “high” (23%). A Trauma Still Present Field investigators reported that a signiﬁcant number of citizens contacted on the streets did not wish to answer the questionnaire. This is partly explained by a lack of time, but also by a desire not to plunge back into the past trauma. This is corroborated by the fact that 2% of the respondents answered the ﬁrst question “I do not wish to answer this questionnaire because I am still too affected by January 12, 2010,” thus interrupting their participation. One percent refused to answer for “other reasons.” We can hypothesize that a larger number of people refused to answer the questionnaire altogether for that same reason, without even going through this ﬁrst question. Despite the trauma still present, interest in the subject is noticeable among the respondents, with more than 90% answering that they are “interested in better understanding earthquakes.” This interest was also reported by the ﬁeld investigators who noted that the respondents were eager to speak about earthquakes. This is conﬁrmed by the length of the write-ups in the open questions. When asked about the means they would use to ﬁnd information in the case of an earthquake, the respondents show voluntarism, declaring that they would not only use traditional means [radio (54%), TV (59%), press (54%)] but also social networks (29% for Facebook and Twitter) and WhatsApp (40%), making themselves not only consumers but also producers of information. hquake Awareness and Vulnerability Earthquake Awareness and Vulnerability The on-line survey described above received a total of ∼1,000 responses, most of them within a week of the questionnaire being announced. We gathered an additional ∼200 responses from administering the questionnaire in the streets. Again, we acknowledge the bias introduced by the on-line sampling methodology, but as no previous similar survey has been performed in Haiti, to our knowledge, its results nevertheless provides important elements that will help us—and perhaps other similar projects elsewhere—better understand the perception of earthquake risk, at least within the section of the Haitian population sampled here. We summarize hereafter the preliminary ﬁndings of this survey. A Need for Information Consistent with the risk awareness improvement noted above, 93% of the respondents want more information about earthquakes. They prioritized customized, actionable information such as earthquake- resistant construction rules, what to do during an earthquake, or which areas are the most at risk. Such information can indeed be applied directly by individuals in order to implement protection measures for their own safety. It is unclear whether such information would actually be put to use by individuals, but this suggest that they may consider acting to reduce their own risk. When it comes to information after an earthquake, the most popular requests are in the categories of “where to get help,” and “how to help.” Information on the earthquake itself or the aftershocks are not the priority. Here again, the need for actionable information dominates over the need for scientiﬁc information. Seismology h Only 9% consider it “low” or “very low.” This awareness is conﬁrmed by the fact that earthquakes are perceived as one of the main risks in Haiti, together with insecurity and violence, political instability, health risks, and cyclones. The vast majority of the respondents answer that they know better than before the 2010 event the safety instructions to follow before, during and after an earthquake. This knowledge seems mainly disseminated by the scientiﬁc community and the media, not by political, educational or religious institutions. All in all, it appears that the January 12, 2010, earthquake signiﬁcantly raised the awareness of seismic risk and understanding of earthquakes in Haiti. 6https://www.bbc.com/news/world-latin-america-12073029; https://www.lemonde.fr/ ameriques/article/2010/12/23/cholera-en-haiti-les-autorites-inquietes-de-lynchages-a- mort_1456914_3222.html. Distrust Toward the Authorities Ninety one percent of the respondents experienced the January 12, 2010, earthquake. While 53% declared that they understood that it was an earthquake, a large percentage did not understand When asked which sources of information they trust most, the respondents rank “scientists” and “the Bureau of Mines and September 2020 \| Volume 8 \| Article 542654 Frontiers in Earth Science \| www.frontiersin.org 8 A Socio-Seismology Experiment in Haiti Calais et al. Energy” at the top, with, respectively, 78 and 68% of “conﬁdence” or “total conﬁdence.” The Government of Haiti only comes in 7th place, after civil protection, international organizations, relatives, and journalists, with 44% or distrust 29% of trust, the remainder being neutral. This is also expressed in numerous open comments that criticize the inaction of the authorities. This distrust in the government is a key element of the political situation in Haiti, caused in part by the weak reaction of the authorities after the 2010 earthquake and an unaccomplished reconstruction phase (Hurbon, 2014) but also, more recently, by a multi-billion dollars corruption scandal and heightened insecurity throughout the country. This permanent turmoil is currently leading to a feeling of chaos amongst the Haitian civil society. should not be underestimated in our future research. In addition, interviews in the streets indicated that they often were less available than men, perhaps because of their role to ensure that daily family logistics is achieved in the Haitian society. A more detailed analysis of their responses to the questionnaire is needed to reveal differences in perception or needs for information. Interviews to come may be an opportunity to establish a more secure framework for collecting their views. The Place of Religion? Religious institutions appear not to be trusted very much either. For example, only 6% of the respondents declare to trust or totally trust the vodou associations, with similar numbers for catholic or protestant churches. This result is however likely biased by the survey method, as mentioned above, which did not allow us to properly sample social groups that are more inclined to trust religious institutions. Directive or semi-directive interviews are needed to shed more light on the role of religion and faith in risk perception and understanding. Survey answers show, in a signiﬁcant number of cases, answers that are dual: there is a scientiﬁc explanation, but also a divine one. Understanding how individuals may be able to juxtapose these two views without conﬂict is an interesting topic for future research. As for the usefulness of RS stations to complement the existing—but hard to operate and maintain—broadband seismic network, the above analysis demonstrates that they bring valuable information for real-time detection and characterization of the regional seismicity. We also better understand their limitations in terms of sensitivity, as well as the limitation of having only one velocimetric component in high noise environment and with interrupted data ﬂow. With an automatic detection system that is operational, portable to Haiti, and scalable to hundreds of stations (RS and other types), we can now start thinking of how to best interface that information with RS hosts, as well as with the general public, beyond a simple web interface with a seismicity map. Designing such a system will require joined efforts from seismologists and sociologists, informed by more in-depth surveys and interviews. This juxtaposition of faith and science also happens in places where magic or ﬁction can lead people to react in a way that can worsen vulnerability. For instance, during the cholera epidemic of late 2010, close to 50 vodou priests were killed by mobs on the accusation that they were using “black magic” to spread diseases.6 That cholera had been brought to Haiti by Nepalese UN soldiers (Frerichs et al., 2012) was suspected, but not yet demonstrated at the time. DISCUSSION AND CONCLUSION As we initiated this project, it was not clear how easy or difﬁcult it would be to ﬁnd hosts for RS stations and to maintain their interest over many months, or possibly years. We were also unsure of the beneﬁt of RS stations for earthquake locations and magnitude determination in a variety of noise environments. Although access to electricity and internet can be a serious issue in Haiti, we found a signiﬁcant number of volunteers motivated to host a RS instrument, even though there is no ﬁnancial support from our side. The seismological analysis of the RS data shows that more stations would be useful, and that redundancy is important: several RS in the same city, for instance, is not a waste as they may not all be operational at the same time. Also, during the difﬁcult months of October and November 2019, when political instability and insecurity locked-up the country causing schools, universities, and most governmental institutions to close—hence ofﬁcial seismic data streams to stop—data from citizen seismometers were ﬂowing at rate no different from the 6-month average. Citizen seismology can therefore be a viable means to alleviate such difﬁculties and provide continuity in seismological information even under duress. In spite of this, from the respondents’ point of view, the solutions to be provided must be national. Eighty percent would like more Haitian scientists to be trained—while only 22% think that more international experts are needed—and 71% want more “measuring devices” to be installed on the national territory. But the respondents also think that “earthquake prediction research” (16%), or “learning how to interpret the signs of nature” (27%) can contribute to understanding earthquakes. The Place of Women? Women represent only 35% of the respondents. At this stage of our research, it is unclear why this number is so much lower than men. They were subjected to a higher risk of post-traumatic symptoms (Nemethy, 2010) which may have detracted them from answering the questionnaire. In particular, beyond the earthquake itself, one must account for the sexual trauma endured by a number of them in refugee camps. This The online survey, in spite of the bias and limitations discussed above, indicates that the January 12, 2010 earthquake raised seismic risk awareness and the level of understanding of earthquakes amongst the population surveyed. Future directive and semi-directive interview are needed to explore this further, but one may hypothesize that this results from the numerous interventions of trusted scientiﬁc ﬁgures in the national media in September 2020 \| Volume 8 \| Article 542654 Frontiers in Earth Science \| www.frontiersin.org 9 A Socio-Seismology Experiment in Haiti Calais et al. the wake of the event. Indeed, the survey reveals an overall trust of scientists, an information that seismologists should use to further develop opportunities to convey basic earthquake information and seismic risk protection messages. However, the survey also reveals a ﬁrst-order need for practical and actionable information—protection measures, where to seek help, etc.—whereas scientiﬁc information—magnitudes, aftershocks, etc.—is not favored by the respondents. This may be a bit disappointing to seismologists, but likely reﬂects the fact that what is learned by studying aftershocks or small unfelt earthquakes is too theoretical and remote from the priorities of most citizens. However, the appetite for information on earthquake protection measures is an indication that, if that information was properly packaged and distributed—it is available, but on the internet pages of government institutions—then it may have a better chance of having an impact. ensure that daily family logistics is achieved. A more detailed analysis of their responses to the questionnaire is needed to reveal differences in perception or needs for information. Interviews to come may be an opportunity to establish a more secure framework for collecting their views. Our preliminary observations indicate that citizen-seismology in a development context has potential to engage the public while collecting scientiﬁcally-relevant seismological information. However, the actual impact of the experiment on risk perception and, in turn, the stimulation of individuals and communities to take protective actions remains be determined. The Place of Women? At this early stage of the project, and because of the recent political situation in Haiti, our interaction with target populations and communities have been limited so that measures of success or failure are not yet available. Many questions remain open—Will there be a sustained engagement of citizens in hosting RS stations? How much involvement from seismologists will be needed to develop and maintain interest? How to anchor the potential achievements of a citizen-seismology into long-term policy goals? How should the citizen-seismology model described here should evolve to better fulﬁll its objectives? The survey highlights the need for information through internet platforms and tools, which is to be expected in this current day and age. Seismological products (quasi real-time earthquake locations and magnitudes, information on protective measures, etc.) must obviously be disseminated that way, but more work is needed to understand the speciﬁc expectations of citizens and communities, in the Haitian context, so that information perceived as relevant is conveyed with an optimal chance of motivating grassroots risk reduction efforts. Finally, a citizen-based source of seismological data in Haiti also has the potential for being used in teaching programs. Educational seismic network experiences have shown that local seismic datasets improve the impact of teaching about earthquakes. They also increase the awareness of seismic risk among students who live in a seismically area, especially when events are detected close by, even though those events may not be felt (Courboulex et al., 2012). The ability to detect and report close-by events may have a similar impact on volunteer citizens. The distrust toward the authorities and the government, understandable in the Haitian context, is an indication that government-only initiatives are likely to be insufﬁcient for efﬁcient disaster risk reduction. That respondents point at the inaction of the state is an indication that there may be a place for informed citizen action. In an economic and governance situation such as Haiti, imposing the “building back better” principle systematically and at a large scale is difﬁcult. Increasing awareness through initiatives such as the one described here may create a public demand for more effective policies, and, perhaps more usefully, instigate grassroots initiatives to build better. ETHICS STATEMENT Ethical review and approval was not required for the study containing human participants in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study. DATA AVAILABILITY STATEMENT The datasets generated for this study are available on request to the corresponding author. The survey highlights other interesting points that cannot be further discussed without directive or semi-directive surveys, such as the juxtaposition of faith and science. We anticipated that the earthquake would be seen through the double lens of tectonics and magic/religion. Our survey provides a hint of this, though its limited social sampling, as well as the methodology used here, likely underestimate this element. In Haiti, the weak state leaves a vacant space—as noted by survey respondents—which is heavily occupied by religious movements. In fact, any social reﬂection must take into account patterns of thought where rationality can vary signiﬁcantly from one individual to another, from one group to another. How to insert earthquake science as yet another element, without conﬂicting or negating other representations of one’s environment, remains an open question. Frontiers in Earth Science \| www.frontiersin.org REFERENCES blogpost. Available at: https://blogs.egu.eu/divisions/sm/2019/03/08/taking-into- account-the-cultural-context-to-improve-scientiﬁc-communication-lessons- learned-from-earthquakes-in-mayotte/. Alessi, E. J., and Martin, J. I. (2010). Conducting an internet-based survey: beneﬁts, pitfalls, and lessons learned. Soc. Work Res. 34, 122–128. doi:10.1093/swr/34.2. 122 Fallou, L., Bossu, R., Landes, M., Roch, J., Roussel, F., Steed, R., et al. (2020). Citizen seismology without seismologists? Lessons learned from Mayotte leading to improved collaboration. Front. Commun. 5, 49. doi:10.3389/fcomm.2020.00049 Fischer, F. (2000). Citizens, experts, and the environment: the politics of local knowledge. Durham, NC: Duke University Press. Anthony, R. E., Ringler, A. T., Wilson, D. C., and Wolin, E. (2018). Do low-cost seismographs perform well enough for your network? An overview of laboratory tests and ﬁeld observations of the OSOP Raspberry Shake 4D. Seismol. Res. Lett. 90, 1–10. doi:10.1785/0220180251 Frerichs, R. R., Keim, P. S., Barrais, R., and Piarroux, R. (2012). Nepalese origin of cholera epidemic in Haiti. Clin. Microbiol. Infect. 18 (6), E158–E163. doi:10. 1111/j.1469-0691.2012.03841.x Seismol. Res. Lett. 90, 1–10. doi:10.1785/0220180251 Bent, A. L., Cassidy, J., Prépetit, C., Lamontagne, M., and Ulysse, S. (2018). Real- time seismic monitoring in Haiti and some applications. Seismol. Res. Lett. 89, 407–415. doi:10.1785/0220170176 Haiti Earthquake Post Disaster Needs Assessment (2010). Assessment of damage, losses, general and sectoral needs. Available at: http://siteresources.worldbank. Haiti Earthquake Post Disaster Needs Assessment (2010). Assessment of damage, losses, general and sectoral needs. Available at: http://siteresources.worldbank. org/INTLAC/Resources/PDNA_Haiti- 2010_Working_Document_EN.pdf. , g p org/INTLAC/Resources/PDNA_Haiti- 2010_Working_Document_EN.pdf. Bilham, R. (2010). Lessons from the Haiti earthquake. Nature 463, 878–879. doi:10. 1038/463878a Hickey, S., and Mohan, G. (2004). Participation – from tyranny to transformation? Exploring new approaches to participation in development. London, UK: Zed Books. Bilham, R. (2013). Societal and observational problems in earthquake risk assessments and their delivery to those most at risk. Tectonophysics 584, 166–173. doi:10.1016/j.tecto.2012.03.023 Hicks, A., Barclay, J., Chilvers, J., Armijos, M. T., Oven, K., Simmons, P., et al. (2019). Global mapping of citizen science projects for disaster risk reduction. Front. Earth Sci. 7 (165), 226. doi:10.3389/feart.2019.00226 Bossu, R., Roussel, F., Fallou, L., Landès, M., Steed, R., Mazet-Roux, G., et al. (2018a). LastQuake: from rapid information to global seismic risk reduction. Int. J. Disaster Risk Reduct. 28, 32–42. doi:10.1016/j.ijdrr.2018.02.024 L. Hurbon (2014). “Catastrophes et environnement, Haïti, séisme du 12 Janvier 2010, collective work under the direction of L. Hurbon,” in Editions de l’EHESS, Collection « Cas de ﬁgure ». Buchanan, E. A., and Hvizdak, E. E. (2009). Online survey tools: ethical and methodological concerns of human research ethics committees. REFERENCES J. Empir. Res. Hum. Res. Ethics 4, 37–48. doi:10.1525/jer.2009.4.2.37 Irwin, A. (1995). Citizen science: a study of people, expertise and sustainable development, London, UK: Psychology Press. Calais, E. (2017). Science et conscience dans la Post-urgence du Séisme d’Haïti. Paris, France: L’Harmattan, 98. Jabeen, H., and Johnson, C. (2013). “Perceptions of climate variability and coping strategies in informal settlements in dhaka, Bangladesh,” in Cities at risk. Advances in natural and technological hazards research. Editors H. Joffe, T. Rossetto, and J. Adams (Dordrecht, Netherlands: Springer), Vol. 33. doi:10.1007/978-94-007-6184-1_9 Calais, E., Boisson, D., Symithe, S., Momplaisir, R., Prepetit, C., Ulysse, S., et al. (2019). Can a Raspberry Shake seismic network complement a national seismic (2019). Can a Raspberry Shake seismic network complement a national seismic network? A case study in Haiti. Eos, 100. doi:10.1029/2019eo123345 Calais, E., Freed, A., Mattioli, G., Amelung, F., Jonsson, S., Jansma, P., et al. (2010). Transpressional rupture of an unmapped fault during the 2010 Haiti earthquake. Nat. Geosci. 3 (11), 794–799. doi:10.1038/ngeo992 Johnston, D. M., Becker, J., McClure, J., Paton, D., McBride, S., Wright, K., et al. (2013). “Community understanding of, and preparedness for, earthquake and tsunami risk in Wellington, New Zealand,” in Cities at risk: Living with perils in the 21st century. Editors H. Joffe, T. Rossetto, and J. Adams (Berlin, Germany: Springer Science & Business Media), 131–148. Cantore, L., Bobbio, A., Di Martino, F., Petrilio, A., Simini, M., and Zollo, A. (2003). The EduSeis project in Italy: an educational tool for training and increasing awareness of seismic risk. Seismol. Res. Lett. 74, 596–602. doi:10.1785/gssrl.74.5. 596 Kolbe, A. R., Hutson, R. A., Shannon, H., Trzcinski, E., Miles, B., Levitz, N., et al. (2010). Mortality, crime and access to basic needs before and after the Haiti earthquake: a random survey of Port-au-Prince households. Med. Conﬂ. Surviv. 26 (4), 281–297. doi:10.1080/13623699.2010.535279 Corbet, A. (2014). “Invisibles omniprésents. Les morts du séisme, in Catastrophes et environnement, Haïti, séisme du 12 janvier 2010,” in Editions de l’EHESS. Editors L. Hurbon, Collection « Cas de ﬁgure », 29–58. doi:10.4000/books. editionsehess.7320 Levy, G., and Taber, J. (2005). Shake up your community with the IRIS, seismographs in schools program. Earth Sci. 21 (2), 28–29. Courboulex, F., Berenguer, J. L., Tocheport, A., Bouin, M. P., Calais, E., Esnault, Y., et al. (2012). SISMOS à l’Ecole: a worldwide network of realtime seismometers in schools. Seismol. Res. Lett. 83 (5), 870–873. doi:10.1785/0220110139 Löfstedt, R., and Frewer, L. (1998). AUTHOR CONTRIBUTIONS The project concept was developed by EC, with input from all co- authors. The Ayiti-séismes system was developed by JC and FP. The daily veriﬁcation and relocation of earthquakes has been performed by TM, AD, and FC. The educational aspects of the project are carried out by JB and J-LB. The survey analysis was carried out by LF and LH. The preparation of the manuscript and ﬁgures was done by EC. All authors discussed the results, and contributed to the ﬁnal manuscript. The gender ratio of respondents remains to be understood, especially in a society where women play a structuring role in most families. Interviews in the streets indicate that they often were less available than men, perhaps because of their role to September 2020 \| Volume 8 \| Article 542654 Frontiers in Earth Science \| www.frontiersin.org 10 A Socio-Seismology Experiment in Haiti Calais et al. FUNDING We deeply thank the individuals and organizations that are currently hosting RS stations in Haiti, they make a difference! We thank the master students from the Faculté des Sciences Humaines et Sociales of Port-au-Prince, Haiti, for carrying out the survey in the streets of Port-au-Prince. We thank Branden Christensen and the OSOP team for their efﬁcient technical support. We are grateful to two reviewers for their comments that signiﬁcantly helped improved the original version of the paper. This research was funded through the CNRS-MITI/IRD program “Risques Naturels,” the “Interreg Caraïbe” program of the European Union through the PREST project, and the URGéo “Jeune Equipe Associée de l’IRD” (JEAI) at the Haiti State University supported by the Institut de Recherche pour le Développement (IRD). EC acknowledges support from the Institut Universitaire de France. This research was funded through the CNRS-MITI/IRD program “Risques Naturels,” the “Interreg Caraïbe” program of the European Union through the PREST project, and the URGéo “Jeune Equipe Associée de l’IRD” (JEAI) at the Haiti State University supported by the Institut de Recherche pour le Développement (IRD). EC acknowledges support from the Institut Universitaire de France. blogpost. Available at: https://blogs.egu.eu/divisions/sm/2019/03/08/taking-into- account-the-cultural-context-to-improve-scientiﬁc-communication-lessons- learned-from-earthquakes-in-mayotte/. blogpost. Available at: https://blogs.egu.eu/divisions/sm/2019/03/08/taking-into- account-the-cultural-context-to-improve-scientiﬁc-communication-lessons- learned-from-earthquakes-in-mayotte/. REFERENCES The Earthscan reader in risk and modern society. London, UK: Earthscan/James & James. Daniell, J. E., Khazai, B., and Wenzel, F. (2013). Uncovering the 2010 Haiti earthquake death toll. Nat. Hazards Earth Syst. Sci. Discuss. 1, 1913–1942. doi:10.5194/nhessd-1-1913-2013 Manaker, D. M., Calais, E., Freed, A. M., Ali, S. T., Przybylski, P., Mattioli, G., et al. (2008). Interseismic plate coupling and strain partitioning in the northeastern Caribbean. Geophys. J. Int. 174, 889–903. doi:10.1111/j.1365- 246x.2008.03819.x Desroches, R., Comerio, M., Eberhard, M., Mooney, W., and Rix, G. J. (2011). Overview of the 2010 Haiti earthquake. Earthq. Spectra 27 (1), S1–S21. doi:10. 1193/1.3630129 McInroy, L. B. (2016). Pitfalls, potentials, and ethics of online survey research: LGBTQ and other marginalized and hard-to-access youths. Soc. Work. Res. 40, 83–94. doi:10.1093/swr/svw005 EM-DAT, Centre for research on the epidemiology of disasters (CRED), School of Public Health, Université Catholique de Louvain, Belgium (2020). Available at: https://www.emdat.be (AccessedMarch 12, 2020). Moon, J., Hwang, H., and Chung, J. (2019). Factors affecting awareness of preparedness after moderate earthquakes: an analysis of the Pohang earthquake in Korea. Disaster Prev. Manag. 29 (3), 405–420. doi:10.1108/ dpm-07-2019-0209 Fallou, L., and Bossu, R. (2019). Taking into account the cultural context to improve scientiﬁc communication—lessons learned from earthquakes in Mayotte. EGU September 2020 \| Volume 8 \| Article 542654 Frontiers in Earth Science \| www.frontiersin.org 11 A Socio-Seismology Experiment in Haiti Calais et al. Development Institute (Humanitarian Practice Network, Good Practice Review #9). Development Institute (Humanitarian Practice Network, Good Practice Review #9). Nemethy, K. (2010). Mental illness and resilience following the Haiti earthquake: an initial assessment. MSc thesis. Paris (France): École des Hautes Études en Santé Publique, 33. UNISDR (United Nations International Strategy for Disaster Reduction) (2014). Progress and challenges in disaster risk reduction: a contribution towards the development of policy indicators for the post- 2015 framework on disaster risk reduction. Summary and main ﬁndings. Geneva, Switzerland. Rodriguez, R. Y., Havskov, J., Sørensen, M. B., and Santos, L. F. (2018). Seismotectonics of south-west Dominican Republic using recent data. J. Seismol. 22 (4), 883–896. doi:10.1007/s10950-018-9738-9 Scherer, J. (1912). Great earthquakes in the island of Haiti. Bull. Seismol. Soc. Am. 2 (3), 161–180. UNISDR (United Nations International Strategy for Disaster Reduction) (2015). Sendai framework for disaster risk reduction 2015–2030. Available at: https:// www.undrr.org/publication/sendai-framework-disaster-risk-reduction-2015- 2030 (Accessed March 11, 2020). Schlupp, A., Chavot, P., Grunberg, M., Bes-De-Berc, M., Jund, H., Ajak, F., et al. (2019). REFERENCES SeismoCitizen: a project combining seismology and human science approaches based on a deployment of a dense low-cost seismic network hosted by citizens. Geophys. Res. Abstr. 21. Weber, B., Becker, J., Hanka, W., Heinloo, A., Hoffmann, M., Kraft, T., et al. (2007). SeisComP3-automatic and interactive real time data processing. Geophys. Res. Abstr. 9, 09219, 2007 ,General Assembly European Geosciences Union. Schwartz, T. T. (2017). The great Haiti humanitarian aid swindle. Scotts Valley, CA: CreateSpace Independent Publishing Platform, 508. Yamori, K. (2013). “A historical overview of social representation of earthquake risk in Japan: fatalism, social reform, scientiﬁc control and collaborative risk management,” in Cities at risk: living with perils in the 21st century. Editors H. Joffe, T. Rossetto, and J. Adams (Berlin, Germany: Springer Science & Business Media), 73–92 Sim, T., Dominelli, L., and Lau, J. (2017). A pathway to initiate bottom-up community-based disaster risk reduction within a top-down system: the case of China. Int. J. SAFE 7, 283–293. doi:10.2495/safe-v7-n3-283- 293Google Scholar SNGRD(Système national de gestion des risques et des désastres – National Risk and Disaster Management Agency) (2010). SNGRD Situation Report 16. Bulletin d’Information du Gouvernement Haïtien – 8 au 12 Mars 2010 (Information Bulletin of the Haitian Government spanning 8th–12th March). Conﬂict of Interest: The authors declare that the research was conducted in the absence of any commercial or ﬁnancial relationships that could be construed as a potential conﬂict of interest. Solberg, C., Rossetto, T., and Joffe, H. (2010). The social psychology of seismic hazard adjustment: re-evaluating the international literature. Nat. Hazards Earth Syst. Sci. 10, 1663–1677. doi:10.5194/nhess-10-1663-2010 Copyright © 2020 Calais, Boisson, Symithe, Prépetit, Bétonus, Ulyse, Hurbon, Gilles, Théodat, Monfret, Deschamps, Courboulex, Chèze, Peix, Bertrand, Ampuero, de Lépinay, Balestra, Berenguer, Bossu, Fallou and Clouard. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Copyright © 2020 Calais, Boisson, Symithe, Prépetit, Bétonus, Ulyse, Hurbon, Gilles, Théodat, Monfret, Deschamps, Courboulex, Chèze, Peix, Bertrand, Ampuero, de Lépinay, Balestra, Berenguer, Bossu, Fallou and Clouard. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). . Frontiers in Earth Science \| www.frontiersin.org September 2020 \| Volume 8 \| Article 542654 REFERENCES The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Théodat, J. M. (2010). Haïti 2010: les leçons d’une catastrophe. EchoGéo, 1–5. doi:10.4000/echogeo.11682,Google Scholar Théodat, J. M. (2013). Port-au-Prince en sept lieux. Outre Terre 35–36, 123–150. Théodat, J. M. (2013). Port-au-Prince en sept lie Théodat, J. M., Simoens, P. J. M., Sobczak, F., and Cornut, P. (Forthcoming 2020). La perception du risque sismique à Canaan: Haïti 2019. Revue Haïtienne d’Histoire et de Géographie. Twigg, J. (2004). Disaster risk reduction: mitigation and preparedness in development and emergency programming. London, UK: Overseas September 2020 \| Volume 8 \| Article 542654 Frontiers in Earth Science \| www.frontiersin.org 12
https://openalex.org/W4367394311	https://link.springer.com/content/pdf/10.1007/s11845-023-03332-7.pdf	English	null	Cost awareness amongst irish ophthalmologists	Irish journal of medical science	2,023	cc-by	2,825	ORIGINAL ARTICLE ORIGINAL ARTICLE Keywords Costs · Healthcare Economics · Ophthalmology · Sustainability Keywords Costs · Healthcare Economics · Ophthalmology · Sustainability Background this, many clinicians receive little or no formal training on the costs of the materials they use and the drugs they prescribe. To manage budgets effectively, clinicians must have a reason- able understanding of the costs associated with their practice. this, many clinicians receive little or no formal training on the costs of the materials they use and the drugs they prescribe. Healthcare expenditure grows year on year. The estimated 2020 health expenditure in Ireland is €20.3 billion [1]. Cli- nicians are responsible for 70% of budget expenditure in healthcare [2]. Pharmaceutical expenditure ranges from 8.5% to 29.6% of health spending within Organisation for Economic Co-operation and Development countries and is increasing faster than other areas of health-care spending in almost all countries [3]. To manage budgets effectively, clinicians must have a reason- able understanding of the costs associated with their practice. In addition to costs to health systems and departments, it is important to understand how much different drugs cost patients. In some cases, patients continue to purchase drugs at high personal cost when suitable alternatives exist [5]. In others, drugs are discontinued unbeknownst to the doctor due to budgetary constraints [6, 7]. High-value, cost-conscious care refers to care that aims to assess the benefits, harms, and costs of interventions and con- sequently to provide care that adds value [4]. Given the fact that we all work within a limited budget, the value of a drug or item cannot be appreciated without knowing the cost. Despite The aim of this study was to gauge the level of knowl- edge possessed by Irish ophthalmologists about the costs of commonly used drugs and clinical equipment. We were also interested to see if there was an association between senior- ity and estimate accuracy. * Barry Power Barry.power.1@ucdconnect.ie 1 Royal Victoria Eye and Ear Hospital, Dublin 2, Ireland 2 Ophthalmology Department, Royal Victoria Eye and Ear Hospital, Adelaide Rd, Dublin 2, Ireland Cost awareness amongst irish ophthalmologists Barry Power1,2 Received: 20 October 2022 / Accepted: 28 February 2023 / Published online: 29 April 2023 © The Author(s) 2023 Abstract Background Healthcare systems have increasingly limited and stretched budgets. Clinicians have a key role in budget alloca- tion. Awareness of the costs of high-use clinical items is important. Aims Assess awareness of the cost of commonly utilised clinical items amongst Irish Ophthalmologists Aims Assess awareness of the cost of commonly utilised clinical items amongst Irish Ophthalmologists Methods Irish ophthalmologists were contacted and asked to fill out an anonymous survey. We assessed knowledge of hos- pital costs of surgical materials, medications and anti VEGF drugs as well as retail pharmacy costs of commonly prescribed medications. The cost of items to the hospital was recorded from pharmacy and ward order receipts from a single university hospital. The costs of items to the patient were calculated by taking an average of 3 prices charged by local retail pharmacies. For each estimate we calculated the absolute error from the true price. We calculated the mean absolute errors (MAE) and percentage errors (MAPE) across the different groups. Results We received responses from 47 participants (15 Senior House Officers, 11 Registrars, 21 Consultant/Community Ophthalmologists). Despite 70% of respondents agreeing that the cost of an item should have a major role in its use, the aver- age estimate was 124% inaccurate. Less than 50% of responses were within 50% of the true cost of the item. Self-perceived knowledge was acknowledged to be limited or very limited in 73% of responses. Conclusions We demonstrate variable and limited levels of cost awareness. Seniority and better were not found to be associated with better estimate accuracy. Irish Journal of Medical Science (1971 -) (2023) 192:3147–3150 https://doi.org/10.1007/s11845-023-03332-7 Irish Journal of Medical Science (1971 -) (2023) 192:3147–3150 https://doi.org/10.1007/s11845-023-03332-7 ORIGINAL ARTICLE Methods All currently practicing Irish ophthalmologists were con- tacted via email. Respondents were asked for estimates, to the nearest Euro, of the cost of a list of common clinical (0121 :(0123 1 3 3456789) 3 Irish Journal of Medical Science (1971 -) (2023) 192:3147–3150 3148 Fig 1 Displays a breakdown the mean average percentage errors of items. We divided the items into 4 categories – cost of: medi- cations to the hospital (9 items), surgical materials to the hospital (15 items), anti-VEGF medications to the hospital (3 items) and medications to the patient (8 items). Partici- pants were asked to record their level of training as Senior House Officer [SHO], Registrar/ Specialist Registrar [SPR] and Consultant/Community Ophthalmologist (COP). The cost of each item was per unit (i.e. per bottle of medi- cation, per pair of gloves etc.) and this was stated clearly in each question. Where different volumes are in common use, a specific volume was indicated. We recorded the hospital costs of items from ward and pharmacy receipts. We calcu- lated average costs to the patient by taking an average from three local retail pharmacies. In our statistical analysis we looked at the 4 categories separately and overall. We also looked at each level of sen- iority separately. Naturally, some estimates were above and some below the true cost. This limits the usefulness of a simple mean estimate per item. The primary measure of the accuracy of estimates that we used was the mean absolute error (MAE). The absolute error of each estimate per item was calculated: Fig. 1 Displays a breakdown the mean average percentage errors of respondents’ estimates Estimate accuracy varied widely across different catego- ries of items. The MAPE was highest in the perioperative material section followed by the hospital medications, anti- VEGF drugs and retail pharmacy medications (243, 124, 75 and 53% respectively). (Δx) = \|\|xi −x\| When the respondents were broken down into 3 groups based on seniority, the Consultant/COP group’s estimates were more accurate but there was no statistical difference between the groups (Table 1, P=0.47; Kruskal Wallis). They had the lowest MAPE in 2 of the four groups (hospital medications and perioperative materials) and the lowest overall MAPE. xi is the estimate; x is the true value. The MAE was then calculated per item. The MAE expressed as percentages of the true cost of each is the mean absolute percentage error (MAPE). Methods This facilitates compari- son between items of different prices. Standard deviation calculations were also performed for each item. Before providing estimates, responders were asked to rate their self-perceived knowledge. No clinicians rated their knowledge as very good, 2 rated it as good with average, limited and very limited selected by 8, 18 and 9 respectively (NR from 10). Self-perceived knowledge was not found to predict better estimates (Table 2, P=0.18, Kruskal Wallis). Respondents also answered questions relating to their self-perceived knowledge of cost of common medications/ items and the level of influence the price of an item should have on its use in clinical practice. 5 10 15 20 25 30 35 40 45 50 Repsonmdents (%) <25% 25-50% 50-100% >100% Fig. 2 Displays a breakdown of the mean average percentage errors in each of the 4 categories Discussion The hospital cost responses (medications, surgical materials and anti-VEGF drugs) highlighted a significant knowledge gap with less than one third of responses being accurate to +/- 25%. For high cost and frequent use items in particular, this lack of awareness is not conducive with efficient use of a departmental budget. The anti-VEGF medications are a good example of similar drugs with very large price differences. There are a small number of conditions that may respond better to the more expensive Aflibercept and Ranabizumab, but the generic drug Avas- tin has been shown in multiple trials to be non-inferior in treatment of AMD and retinal vein occlusions associated with macular oedema [13–15]. In a situation where the non-inferiority of a more cost effective option has been proven, it should be first line. Many respondents to our survey were unaware of the extent of the price difference between these agents. Funding Open Access funding provided by the IReL Consortium. Results There were 47 respondents to the study (21 Consultant/[COP, 11 SPRs/Registrars and 15 SHOs). Just 4% of respondents reported their self-perceived knowledge as very good or good. Limited or very limited knowledge was reported by 47%. Consultants/COPs were more likely to report good or average knowledge than SPR/Reg and SHO groups (43%, 9% and 0% respectively). The majority of respondents agreed that the price of items should factor into their use - 70% responding this should be the case always or as much as patient safety/clinical efficacy allows. Despite this, just 50% of estimates were within 50% of the true cost (Fig. 1). The mean average percentage errors are categorized in Fig. 2. Fig. 2 Displays a breakdown of the mean average percentage errors in each of the 4 categories 1 3 Irish Journal of Medical Science (1971 -) (2023) 192:3147–3150 3149 Table 1 Displays the respondents’ estimate MAPEs by seniority Role Hospital Medications Surgical Materials Anti VEGF Drugs Pharmacy Medications Avg Consultant/ COP 103 212 75 64 111 SPR/Reg 134 259 40 67 131 SHO 134 259 109 58 137 (Tables 1 and 2). The Consultant/COP group had the lowest average error but this difference did not meet statistical sig- nificance. Some Community Ophthalmologists (COPs) may have a limited understanding of surgical costs which may explain some of the outliers in this section. That being said, there were poor estimates across all groups, including those who predicted accurate responses. Senior ophthalmologists are department level decision makers and should set the standard for costs awareness amongst other staff. Clinicians are trained to work up patients, make clinical decisions and formulate treatment plans but these decisions dictate the finances of patients and the health sector as a whole. The dual roles of clinicians and managers are insepa- rable and increasingly consequential. The judicious use of resources is ultimately the clinicians responsibility. Discussion It is clear from the results that the cost of many items are poorly understood by Irish ophthalmologists. This finding has been demonstrated by other studies across a variety of healthcare specialities [8–11]. Allan et al performed a sys- tematic review of 24 studies and found that clinicians con- sistently overestimated the cost of inexpensive products and underestimated the cost of expensive ones [12]. Doctors esti- mates were within 25% of the true cost less than one third of the time. We noted similar findings in our cohort (27%). The hospital cost responses (medications, surgical materials and anti-VEGF drugs) highlighted a significant knowledge gap with less than one third of responses being accurate to +/- 25%. For high cost and frequent use items in particular, this lack of awareness is not conducive with efficient use of a departmental budget. The anti-VEGF medications are a good example of similar drugs with very large price differences. There are a small number of conditions that may respond better to the more expensive Aflibercept and Ranabizumab, but the generic drug Avas- tin has been shown in multiple trials to be non-inferior in treatment of AMD and retinal vein occlusions associated with macular oedema [13–15]. In a situation where the non-inferiority of a more cost effective option has been proven, it should be first line. Many respondents to our survey were unaware of the extent of the price difference between these agents. It is clear from the results that the cost of many items are poorly understood by Irish ophthalmologists. This finding has been demonstrated by other studies across a variety of healthcare specialities [8–11]. Allan et al performed a sys- tematic review of 24 studies and found that clinicians con- sistently overestimated the cost of inexpensive products and underestimated the cost of expensive ones [12]. Doctors esti- mates were within 25% of the true cost less than one third of the time. We noted similar findings in our cohort (27%). Improving cost-consciousness amongst doctors is a chal- lenge. Each treatment decision has multiple factors influenc- ing the final outcome. However, with ever increasing health- care expenditure it is a must. We firmly believe that medical training should include the basics of healthcare economics. Subspecialties of all disciplines should educate their trainees and themselves about the costs of the tests they order and treatments they initiate. Declarations Conflict of interests The author declares no conflicts of interest re- garding this publication. Open Access This article is licensed under a Creative Commons Attri- bution 4.0 International License, which permits use, sharing, adapta- tion, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. It is alarming that neither seniority nor self-perceived knowledge was associated with more accurate estimates Table 2 Displays the respondents’ estimate MAPEs by self-perceived knowledge Rating (N) Hospital Medications Surgical Materials Anti VEGF Drugs Pharmacy Medications Avg Very Good (0) 0 0 0 0 0 Good (2) 81 606 270 40 268 Average (8) 85 139 35 53 92 Limited (18) 114 159 64 62 113 Very limited (9) 137 254 43 60 151 Table 2 Displays the respondents’ estimate MAPEs by self-perceived knowledge 1. Parlimentary Budget Office (2020) https://data.oireachtas.ie/ie/ oireachtas/parliamentaryBudgetOffice/2020/2020-04-17_revised- estimates-2020-health-vote-38_en.pdf . Accessed 5/10/21 2. Hillman A, Nash D, Kissick W et al (1986) Managing the medical- industrial machine. NEMJ 315:511–13 3. OECD Health Division (2006) OECD Health Data Avail- able: http://www.oecd.org/dataoecd/20/51/37622205.xls 4. Stammen LA, Stalmeijer RE, Paternotte E et al (2015) Training Physicians to Provide High-Value, Cost-Conscious Care: A Sys- tematic Review. JAMA. 314(22):2384–2400. https://doi.org/10. 1001/jama.2015.16353 References 1. Parlimentary Budget Office (2020) https://data.oireachtas.ie/ie/ oireachtas/parliamentaryBudgetOffice/2020/2020-04-17_revised- estimates-2020-health-vote-38_en.pdf . Accessed 5/10/21 2. Hillman A, Nash D, Kissick W et al (1986) Managing the medical- industrial machine. NEMJ 315:511–13 3. OECD Health Division (2006) OECD Health Data Avail- able: http://www.oecd.org/dataoecd/20/51/37622205.xls 4. Stammen LA, Stalmeijer RE, Paternotte E et al (2015) Training Physicians to Provide High-Value, Cost-Conscious Care: A Sys- tematic Review. JAMA. 314(22):2384–2400. https://doi.org/10. 1001/jama.2015.16353 1. Parlimentary Budget Office (2020) https://data.oireachtas.ie/ie/ oireachtas/parliamentaryBudgetOffice/2020/2020-04-17_revised- estimates-2020-health-vote-38_en.pdf . Accessed 5/10/21 2. Hillman A, Nash D, Kissick W et al (1986) Managing the medical- industrial machine. NEMJ 315:511–13 4. Stammen LA, Stalmeijer RE, Paternotte E et al (2015) Training Physicians to Provide High-Value, Cost-Conscious Care: A Sys- tematic Review. JAMA. 314(22):2384–2400. https://doi.org/10. 1001/jama.2015.16353 1 3150 Irish Journal of Medical Science (1971 -) (2023) 192:3147–3150 5. Cox ER, Jernigan C, Coons SJ et al (2001) Medicare benefi- ciaries' management of capped prescription benefits. Med Care 39:296–301 13. Chakravarthy U, Harding SP, Rogers CA et al (2013) Alternative treatments to inhibit VEGF in age-related choroidal neovascu- larisation: 2-year findings of the IVAN randomised controlled trial. Lancet 382(9900):1258-67. https://doi.org/10.1016/S0140- 6736(13)61501-9. Epub 2013 Jul 19. PMID: 23870813 6. Spence MM, Hui R, Chan J (2006) Cost reduction strategies used by elderly patients with chronic obstructive pulmonary disease to cope with a generic-only pharmacy benefit. J Manag Care Pharm. 12:377–382 14. Schauwvlieghe AM, Dijkman G, Hooymans JM et al (2016) Comparing the Effectiveness of Bevacizumab to Ranibizumab in Patients with Exudative Age-Related Macular Degeneration. The BRAMD Study. PLoS One 11(5):e0153052. https://doi. org/10.1371/journal.pone.0153052. PMID: 27203434; PMCID: PMC4874598 7. Piette JD, Heisler M, Wagner TH (2004) Cost-related medication underuse: Do patients with chronic illnesses tell their doctors? Arch Intern Med. 164:1749–1755 8. Nethathe GD, Tshukutsoan S, Denny KJ (2017) Cost awareness among healthcare professionals at a south african hospital: A cross-sectional survey. South African Med J 107(11):1010. https:// doi.org/10.7196/samj.2017.v107i11.12513 15. Scott IU, VanVeldhuisen PC, Ip MS et al, SCORE2 Investigator Group (2017) Effect of Bevacizumab vs Aflibercept on Visual Acuity Among Patients With Macular Edema Due to Central Retinal Vein Occlusion: The SCORE2 Randomized Clinical Trial. JAMA 317(20):2072-2087. https://doi.org/10.1001/jama. 2017.4568. PMID: 28492910; PMCID: PMC5710547 9. Barclay LP, Hatton RC, Doering PL et al (1995) Physicians' per- ceptions and knowledge of drug costs: results of a survey. Formu- lary 30:268-70, 272, 277-9 10. Schilling UM (2019) Cost awareness among Swedish physi- cians working at the emergency department. Eur J Emerg Med 16(3):131–134. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References https://doi.org/10.1097/MEJ.0b013e32831cf605 Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. p g 11. Bade K, Hoogerbrug J (2015) Awareness of surgical costs: A mul- ticenter cross-sectional survey. J Surg Educ 2(1):23–27 12. Allan GM, Lexchin J, Wiebe NO (2007) Physician awareness of drug cost: a systematic review. PLoS Med 4(9):e283. https://doi. org/10.1371/journal.pmed.0040283. PMID: 17896856; PMCID: PMC1989748 1 3 3
https://openalex.org/W2344002312	https://link.springer.com/content/pdf/10.1007/s10354-016-0449-y.pdf	German	null	Pulmonalembolie und direkte orale Antikoagulantien	Wiener medizinische Wochenschrift	2,016	cc-by	2,512	Pulmonalembolie und direkte orale Antikoagulantien Horst Olschewski Eingegangen: 21. Januar 2016 / Angenommen: 25. Februar 2016 © Die Autor(en) 2016. Dieser Artikel ist auf Springerlink.com mit Open Access verfügbar. Eingegangen: 21. Januar 2016 / Angenommen: 25. Februar 2016 © Die Autor(en) 2016. Dieser Artikel ist auf Springerlink.com mit Open Access verfügbar. Zusammenfassung Für die Diagnostik und Therapie der venösen Thromboembolie wurde 2014 eine aktuelle Europäische Leitlinie publiziert. Danach werden wie bisher Hochrisiko- und Niedrigrisiko-Lungenembolien unterschieden. Neu ist die Definition von Lungen- embolien mit intermediärem Risiko. Das Risiko ent- scheidet über das diagnostische und therapeutische Vorgehen. pulmonary embolism is distinguished, however, in the new guideline there is also a definition of intermediate risk PE. The risk finally decides about the diagnostic and therapeutic procedure. Previously, nearly only heparinoids were available for therapy of acute venous thromboembolism and after some days they were switched to a vitamin K antagonist. The direct oral anticoagulants (DOAC) represent a group of drugs that start working as rapidly as heparinoids and can be applied as long-term oral medication. In contrast to vitamin K antagonists, repeated coagulation tests are not necessary. Dosing is easy, although in quite a few cases dose adaptations compared to the standard dose may be necessary. The following article tries to give a rapid orientation. Für die akute Therapie standen früher fast nur Heparinoide zur Verfügung, die nach einigen Tagen auf einen Vitamin K Antagonisten umgestellt wurden. Mit den direkten oralen Antikoagulantien (DOAK) wurde eine Medikamentengruppe verfügbar, die einen Wirkungseintritt wie ein Heparinoid haben und über- gangslos als orale Dauermedikation verfügbar sind. Anders als Vitamin K Antagonisten sind keine wieder- holten Gerinnungskontrollen nötig. Die Dosierung ist unkompliziert, aber nicht ganz selten sind Abweichungen von der Standarddosis erforderlich. Der folgende Artikel versucht eine rasche Orientierung zu bieten. Keywords Pulmonary embolism · Anticoagulation · Thrombolysis · Direct oral anticoagulants Wien Med Wochenschr DOI 10.1007/s10354-016-0449-y Wien Med Wochenschr DOI 10.1007/s10354-016-0449-y Pulmonalembolie und direkte orale Antikoagulantien 1 Pulmonalarterienembolie Schlüsselwörter Lungenembolie · Antikoagulation · Thrombolyse · DOAK Für die Pulmonalarterienembolie wurde 2014 eine neue Leitlinie der europäischen kardiologischen Gesellschaft (ESC) in Kooperation mit der europäischen pneumo- logischen Gesellschaft (ERS) herausgegeben [1]. Diese wurde durch eine Vielzahl neuer Studiendaten unter- mauert. Das führte unter Anderem dazu, dass die Schweregradeinteilung der Lungenembolie revidiert wurde. Auf Basis der aktuellen Evidenz unterscheiden wir jetzt Lungenembolien mit hohem Risiko, inter- mediär hohem Risiko, intermediär niedrigem Risiko und niedrigem Risiko. short communication short communication Diagnostik Der Goldstandard zum Nachweis einer akuten pulmonal arteriellen Embolie ist das Computertomogramm (CT) in Form einer CT-Pulmonalisangiographie (CTPA). Diese Untersuchung hat eine sehr gute Spezifität und Sensitivi- tät. Nur wenn es aufgrund der anamnestischen Angaben und der klinischen Befunde eher unwahrscheinlich ist, dass eine Lungenembolie vorliegt, so sollte zunächst der D-Dimer Test durchgeführt werden. Wenn der dann negativ ist, kann getrost auf eine weitere Abklärung mittels CT verzichtet werden, denn das Risiko für das Vorliegen einer Lungenembolie ist denkbar gering. Ist er positiv, so muss die CTPA erfolgen. Deuten die Anamnese oder der klinische Befund darauf hin, dass tatsächlich eine Lungenembolie vorliegt (mittlere oder hohe Vortestwahrscheinlichkeit), so ergibt das D-Dimer keinen Sinn. Stattdessen wird von vornherein eine CTPA empfohlen. Bei Kontrastmittelunverträglichkeit oder Niereninsuffizienz ist dann die Perfusionsszintigraphie die Methode der Wahl zum Ausschluss einer Lungen- embolie. Das gilt auch in der Schwangerschaft. Wenn das native Röntgenbild normal ist, aber die Perfusions- szintigraphie einen typischen Befund zeigt, dann gilt das als Nachweis der Embolie und eine Ventilationsszinti- graphie ist nicht erforderlich. Allerdings kann hierbei auch eine chronisch thromboembolische pulmonale Hypertonie vorliegen, die eine seltene aber wichtige Differentialdiagnose der akuten Lungenembolie im Szintigramm darstellt. Ist eine venöse Thromboembolie eher unwahrscheinlich (niedrige Vortestwahrscheinlich- keit) und das D-Dimer ist niedrig, so kann auf eine CTPA und auf eine Antikoagulation verzichtet werden. Die Intermediär-niedrig Risikogruppe soll stationär aufgenommen werden, wenn auch nicht primär auf die Intensivstation. Solche Patienten erkennt man daran, dass sie entweder eine normale rechtsventrikuläre Funktion oder ein normales BNP bzw. Troponin haben. Bei der Intermediär-hoch Risikogruppe muss der Patient in Lysebereitschaft überwacht werden. Das heißt in aller Regel: Aufnahme auf der Intensivstation. Diese Patienten erkennt man daran, dass sie eine rechts- ventrikuläre Dilatation und ein erhöhtes BNP bzw. Troponin haben. Nach überstandener Lungenembolie muss jeder Patient antikoaguliert werden. Lag der Lungen- embolie ein transientes Risiko zugrunde, welches jetzt nicht mehr besteht, so genügt eine Antikoagulation von 3 Monaten. Liegt dagegen ein persistierendes Thromboembolierisiko vor, so wird eine längerfristige Antikoagulation empfohlen, sofern es keine Kontra- indikationen dagegen gibt. Die Leitlinie ermahnt aber an mehreren Stellen, im langfristigen Verlauf immer wieder neu eine Abschätzung von Nutzen und Risiko der Anti- koagulation vorzunehmen. Wenn man sich unsicher ist, ob ein persistierendes oder ein transientes Risiko für die Thromboembolie vor- lag, so kann man sich den D-Dimer Test zu Hilfe nehmen. Vier Wochen nach Absetzen der Antikoagulation wird das D-Dimer gemessen. 2 Pulmonalembolie und direkte orale Antikoagulantien Pulmonary embolism and direct oral anticoagulants Summary A new European guideline for the diagnostics and therapy of venous thromboembolism has been published in 2014. As previously, high-risk and low-risk Univ Prof. Dr. med. H. Olschewski () Division of Pulmonology, Department of Internal Medicine, LKH University Hospital Graz – Medical University of Graz, Auenbruggerplatz 15, Graz 8036, Österreich E-Mail: horst.olschewski@medunigraz.at Univ Prof. Dr. med. H. Olschewski () Division of Pulmonology, Department of Internal Medicine, LKH University Hospital Graz – Medical University of Graz, Auenbruggerplatz 15, Graz 8036, Österreich E-Mail: horst.olschewski@medunigraz.at Univ Prof. Dr. med. H. Olschewski () Division of Pulmonology, Department of Internal Medicine, LKH University Hospital Graz – Medical University of Graz, Auenbruggerplatz 15, Graz 8036, Österreich E-Mail: horst.olschewski@medunigraz.at Die Hochrisiko Lungenembolie erkennt man am kardiogenen Schock. Sie stellt nach wie vor eine klare Indikation zur sofortigen Thrombolysetherapie dar. Alternativ kann eine Katheterfragmentation oder eine Pulmonalembolie und direkte orale Antikoagulantien 1 1 3 short communication Embolektomie in Frage kommen, wenn die strukturellen Voraussetzungen erfüllt sind. Faktoren nicht wirklich hilfreich für die Entscheidung für oder gegen eine Antikoagulation [5]. Ausnahme ist ein hochtitriges Lupus Antikoagulans. Die Niedrigrisiko Lungenembolie hat definitions- gemäß ein so niedriges Mortalitätsrisiko, dass es mög- lich ist, diese Patienten vom Anfang an ambulant zu behandeln. Man erkennt sie an einem sPESI von 0. Die Bezeichnung „sPESI“ steht für den simplified PESI (pulmonary embolism severity index). Es handelt sich um ein validiertes Instrument zur Abschätzung der Mortalität bei akuter Lungenembolie [2, 3]. Die Faktoren Alter > 80 Jahre, aktives Krebsleiden, chronische Herz- oder Lungenkrankheit, Puls > 110/min, systolischer Blut- druck < 100 mmHg, Sauerstoffsättigung < 90 % zählen jeweils einen Punkt. Wenn der Patient keinen dieser Faktoren hat, so beträgt sein sPESI 0 Punkte. Der sPESI ist sehr gut geeignet für die Kitteltasche und auch einfach zu merken. Diagnostik Wenn es erhöht ist, hat man ein starkes Argument, die Antikoagulation länger fort- zusetzen. Ist es normal, kann man in Erwägung ziehen, die Antikoagulation endgültig abzusetzen. Eine aktuelle Studie hat festgestellt, dass das Rezidivrisiko bei diesen Patienten noch immer inakzeptabel hoch sein kann, ins- besondere bei Männern [4]. DOAK’s Die direkten oralen Antikoagulantien stellen eine der wichtigsten pharmakologischen Innovationen der letzten Jahre dar. Sie haben im Wesentlichen die Wirkungen wie ein Heparinoid, werden aber als Tabletten ein- genommen. Die Wirkung setzt schnell ein und hat eine im Vergleich zu Vitamin K Antagonisten kurze Halb- wertszeit. Weder Spiegelkontrollen noch funktionelle Kontrollen der Gerinnung sind erforderlich. Die Daten- evidenz für den Vergleich zwischen DOAKs und kon- ventionellen Antikoagulantien wie Marcumar oder Sintrom zeigte, dass die DOAKs den konventionellen Medikamenten keinesfalls unterlegen sind, sofern es sich um die Indikationen akute Lungenembolie, Rezidiv- prophylaxe und Langzeitrezidivprophylaxe handelt. Das gleiche gilt für das nicht-valvuläre Vorhofflimmern und die entsprechende Apoplex Prophylaxe. Dies ist im Die direkten oralen Antikoagulantien stellen eine der wichtigsten pharmakologischen Innovationen der letzten Jahre dar. Sie haben im Wesentlichen die Wirkungen wie ein Heparinoid, werden aber als Tabletten ein- genommen. Die Wirkung setzt schnell ein und hat eine im Vergleich zu Vitamin K Antagonisten kurze Halb- wertszeit. Weder Spiegelkontrollen noch funktionelle Kontrollen der Gerinnung sind erforderlich. Die Daten- evidenz für den Vergleich zwischen DOAKs und kon- ventionellen Antikoagulantien wie Marcumar oder Sintrom zeigte, dass die DOAKs den konventionellen Medikamenten keinesfalls unterlegen sind, sofern es sich um die Indikationen akute Lungenembolie, Rezidiv- prophylaxe und Langzeitrezidivprophylaxe handelt. Das gleiche gilt für das nicht-valvuläre Vorhofflimmern und die entsprechende Apoplex Prophylaxe. Dies ist im Patienten mit einer zweiten venösen Thromboembolie sollten jedenfalls lebenslang antikoaguliert werden, sofern es keine starken Gegenargumente gibt. Ansonsten ist das Risiko für wiederholte thromboembolische Ereig- nisse als sehr hoch einzuschätzen. Der Stellenwert von Thrombophiliefaktoren in der plasmatischen Gerinnung (Faktor V Leiden, etc.) in den Guidelines ist derzeit sehr gering. Auch in der Schwangerschaft sind solche 1 1 3 3 short communication Tab. 1 Aktuell in Österreich zugelassene DOAKs in der Indikation akute venöse Thromboembolie und Rezidivprophylaxe. DOAK’s Substanz Handelspräparat Anfangsdosis bei akuter VTE Langzeitdosis Dosisadaptation Dabigatran Pradaxa® Heparinoid für 5 Tage 2x150 mg Alter > 80 J; GFR < 50 ml/mina; P-gp Inhibitorenb Rivaroxaban Xarelto® 2x15 mg für 3 Wochen 1x20 mg GFR < 30 ml/minc; Vorsicht bei Cyp3A4 und P-gp Inhibitoren und Induktorend Apixaban Eliquis® 2x10 mg für 7 Tage 2x5 mg bis 6 Mon, dann 2x2,5 mg Cr > 1,5 mg%d, e, f; Alter > 80 J; KG < 60 Kg Edoxaban Lixiana® Heparinoid für 5 Tage 1x60 mg GFR < 50 ml/minc; KG < 60 kg; P-gp Inhibitorenb Cr Creatinin, KG Körpergewicht, GFR glomeruläre Filtrationsrate, P-gp P-Glykoprotein aGFR < 30 ml/min und Transaminasen > 2-fach der Norm entsprechen einer Kontraindikation bz. B. Verapamil, Amiodaron, Dronedaron, Chinidin, Cyclosporin ckeine Empfehlung für Patienten mit GFR < 15 ml/min oder Leberzirrhose Child Pugh B oder C dDosisanpassung empfohlen wenn mindestens 2 der 3 Faktoren zutreffen eKeine Anwendung empfohlen bei Leberinsuffizienz Child Pugh C oder GFR < 15 ml/min fKeine Empfehlung bei gleichzeitiger Anwendung von Azol-Antimykotika (z. B. Ketakonazol) oder Ritonavir oder Dronedaron. Wirkungsabschwächung unter Johanniskraut, Phenytoin und anderen P-gp und Cyp3A4 Induktoren. Ohne Gewähr für Richtigkeit und Vollständigkeit. Für verbindliche Angaben wird auf die aktuellen Fachinformationen verwiesen. Die Dosierungsempfehlungen in der Indikation Vorhofflimmern können abweichen Tab. 1 Aktuell in Österreich zugelassene DOAKs in der Indikation akute venöse Thromboembolie und Rez n Österreich zugelassene DOAKs in der Indikation akute venöse Thromboembolie und Rezidivprophylaxe. Übrigen die mit Abstand häufigste Indikation für DOAKs. Dagegen sind die DOAKs nach bisherigem Kenntnis- stand für das valvuläre Vorhofflimmern und die VTE Prophylaxe bei künstlichen Herzklappen nicht geeignet. Diese Patienten brauchen also weiterhin einen Vitamin K Antagonisten, ebenso wie Dialysepatienten und Kinder. Seitens der Nebenwirkungen stehen Blutungen im Vordergrund, wie erwartet. Allerdings gibt es hier Vorteile gegenüber den Vitamin K Antagonisten, insbesondere bezüglich intrazerebraler Blutungen. Auch bei akuten Übrigen die mit Abstand häufigste Indikation für DOAKs. Dagegen sind die DOAKs nach bisherigem Kenntnis- stand für das valvuläre Vorhofflimmern und die VTE Prophylaxe bei künstlichen Herzklappen nicht geeignet. Diese Patienten brauchen also weiterhin einen Vitamin K Antagonisten, ebenso wie Dialysepatienten und Kinder. sein wird, sollte kein DOAK eingesetzt werden, sondern unfraktioniertes Heparin. Die Anwendung von DOAKs bei Tumorpatienten wurde nicht ausreichend geprüft und wird daher nicht offiziell empfohlen. Das Gleiche gilt für Kinder unter 18 Jahren. Tab. Open Access Dieser Artikel unterliegt den Bedingungen der Creative Commons Attribution License. Dadurch sind die Nutzung, Verteilung und Reproduktion erlaubt, sofern der/die Originalautor/en und die Quelle angegeben sind. Allgemein wird die Anwendung von DOAKs nicht empfohlen bei Überempfindlichkeit gegen den Wirkstoff, Schwangerschaft und Stillzeit, klinisch relevanter Blutung oder Koagulopathie, gastrointestinaler ulcerativer Erkrankung und bakterieller Endokarditis. Vorsicht ist geboten bei gleichzeitiger Anwendung von anderen Antikoagulantien oder Thrombozytenaggregations- hemmern. Wenn bei einer akuten Lungenembolie noch nicht absehbar ist, ob eine Lysetherapie notwendig Pulmonalembolie und direkte orale Antikoagulantien 3 Fazit Praktische Überlegungen Bei den DOAKs unter- scheiden wir Faktor II und Xa Antagonisten. Das macht aber keinen prinzipiellen Unterschied hinsichtlich der Handhabung. Für jede einzelne Substanz gibt es ein eigenes Dosierungsschema. Meist gilt eine etwas höhere Dosierung für die ersten Wochen und dann eine etwas niedrigere Dosis für die Langzeittherapie oder die Therapie wird mit einem Heparinoid eingeleitet und dann mit dem DOAK fortgesetzt. Die Präparate werden nach Dosierungsanweisung einmal oder zweimal täg- lich eingenommen. Die Wirkung setzt wenige Stunden nach der Applikation ein und nach einer Pause von 24–48 Stunden (substanzabhängig) sind wieder operative Ein- griffe möglich. Insofern gelten für die DOAKs ähnliche Regeln, wie für ein fraktioniertes Heparinoid. In seltenen Einzelfällen kann es bei den Xa Antagonisten indiziert sein, den Faktor Xa Spiegel zu messen. Der Nutzen solcher Messungen wird aber kontrovers diskutiert. Die ESC/ERS Leitlinien machen klare Vorgaben für das diagnostische und therapeutische Vorgehen bei einer akuten Lungenembolie und für die mittel- und langfristige Thromboembolieprophylaxe. Die direkten oralen Antikoagulantien (DOAKs) stellen eine wichtige Therapieoption dar, die einerseits die Heparinoide und andererseits die Vitamin K Antagonisten ersetzen können. Sie sind trotz der vielen und teils komplexen Regeln zur Dosisadaptation relativ einfach zu handhaben und zeichnen sich gegenüber einer konventionellen Therapie mit Vitamin K Antagonisten durch gleiche bis erhöhte Sicherheit bei gleicher bis erhöhter Effektivität aus. DOAK’s 1 gibt eine Übersicht über die zugelassenen DOAKs in der Indikation „venöse Thromboembolie und Rezidivprophylaxe“ und die ver- schiedenen Faktoren, die zu beachten sind, wenn es um eine Dosisreduktion oder eine Kontraindikation geht. sein wird, sollte kein DOAK eingesetzt werden, sondern unfraktioniertes Heparin. Die Anwendung von DOAKs bei Tumorpatienten wurde nicht ausreichend geprüft und wird daher nicht offiziell empfohlen. Das Gleiche gilt für Kinder unter 18 Jahren. Tab. 1 gibt eine Übersicht über die zugelassenen DOAKs in der Indikation „venöse Thromboembolie und Rezidivprophylaxe“ und die ver- schiedenen Faktoren, die zu beachten sind, wenn es um eine Dosisreduktion oder eine Kontraindikation geht. Seitens der Nebenwirkungen stehen Blutungen im Vordergrund, wie erwartet. Allerdings gibt es hier Vorteile gegenüber den Vitamin K Antagonisten, insbesondere bezüglich intrazerebraler Blutungen. Auch bei akuten Notfalloperationen oder bei Trauma scheinen DOAK vorteilhaft gegenüber Vitamin K Antagonisten zu sein. Einhaltung ethischer Richtlinien Interessenkonflikt H. Olschewski erklärt, dass kein Interessenkonflikt besteht. Interessenkonflikt Pulmonalembolie und direkte orale Antikoagulantien 3 3 3 short communication 4. Kearon C, et al. D-dimer testing to select patients with a first unprovoked venous thromboembolism who can stop anticoagulant therapy: a cohort study. Ann Intern Med. 2015;162:27–34. 4 Pulmonalembolie und direkte orale Antikoagulantien 3. Jimenez D, et al. Prognostic significance of deep vein thrombosis in patients presenting with acute symptomatic pulmonary embolism. Am J Respir Crit Care Med. 2010;181:983–91. 5. Rodger MA, et al. Antepartum dalteparin versus no antepartum dalteparin for the prevention of pregnancy complications in pregnant women with thrombophilia (TIPPS): a multinational open-label randomised trial. Lancet. 2014;384:1673–83. Literatur 1. Konstantinides SV, et al. ESC guidelines on the diagnosis and management of acute pulmonary embolism. Eur Heart J. 2014;35:3033–69k. 1. Konstantinides SV, et al. ESC guidelines on the diagnosis and management of acute pulmonary embolism. Eur Heart J. 2014;35:3033–69k. 5. 5. Rodger MA, et al. Antepartum dalteparin versus no antepartum dalteparin for the prevention of pregnancy complications in pregnant women with thrombophilia (TIPPS): a multinational open-label randomised trial. Lancet. 2014;384:1673–83. 2. Jimenez D, et al. Simplification of the pulmonary embolism severity index for prognostication in patients with acute symptomatic pulmonary embolism. Arch Intern Med. 2010;170:1383–9. 3. Jimenez D, et al. Prognostic significance of deep vein thrombosis in patients presenting with acute symptomatic pulmonary embolism. Am J Respir Crit Care Med. 2010;181:983–91. 1 3 1 3
https://openalex.org/W2020353331	https://europepmc.org/articles/pmc3768109?pdf=render	English	null	Detailed molecular characterisation of acute myeloid leukaemia with a normal karyotype using targeted DNA capture	Leukemia	2,013	cc-by	6,392	1Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK; 2EMBL-European Bioinformatics Institute, Cambridge, UK; 3Instituto de Biomedicina y Biotecnologı´a de Cantabria, University of Cantabria, Santander, Spain; 4Bioinformatic Department, Babraham Institute, Cambridge, UK; 5Department of Haematology, Cambridge University Hospitals NHS Foundation Trust, Hills Road, Cambridge, UK; 6Agilent Technologies, IQ Winnersh, Reading, UK and 7Centre for the Study of Haematological Malignacies, Nicosia, Cyprus. Correspondence: Dr GS Vassiliou, Haematological Cancer Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SA, UK. E-mail: gsv20@sanger.ac.uk 8These authors contributed equally to this work. Received 21 October 2012; revised 17 March 2013; accepted 10 April 2013; accepted article preview online 18 April 2013; advance online publication, 24 May 2013 OPEN OPEN Leukemia (2013) 27, 1820–1825 ed All rights reserved 0887-6924/13 Leukemia (2013) 27, 1820–1825 & 2013 Macmillan Publishers Limited All rights reserved 0887-6924/13 www.nature.com/leu Detailed molecular characterisation of acute myeloid leukaemia with a normal karyotype using targeted DNA capture N Conte1,2,8, I Varela3,8, C Grove1, N Manes1, K Yusa1, T Moreno3, A Segonds-Pichon4, A Bench5, E Gudgin5, B Herman6, N Bolli1,5, P Ellis1, D Haddad1, P Costeas7, R Rad1, M Scott5, B Huntly5, A Bradley1 and GS Vassiliou1 Advances in sequencing technologies are giving unprecedented insights into the spectrum of somatic mutations underlying acute myeloid leukaemia with a normal karyotype (AML–NK). It is clear that the prognosis of individual patients is strongly inﬂuenced by the combination of mutations in their leukaemia and that many leukaemias are composed of multiple subclones, with differential susceptibilities to treatment. Here, we describe a method, employing targeted capture coupled with next-generation sequencing and tailored bioinformatic analysis, for the simultaneous study of 24 genes recurrently mutated in AML–NK. Mutational analysis was performed using open source software and an in-house script (Mutation Identiﬁcation and Analysis Software), which identiﬁed dominant clone mutations with 100% speciﬁcity. In each of seven cases of AML–NK studied, we identiﬁed and veriﬁed mutations in 2–4 genes in the main leukaemic clone. Additionally, high sequencing depth enabled us to identify putative subclonal mutations and detect leukaemia-speciﬁc mutations in DNA from remission marrow. Finally, we used normalised read depths to detect copy number changes and identiﬁed and subsequently veriﬁed a tandem duplication of exons 2–9 of MLL and at least one deletion involving PTEN. This methodology reliably detects sequence and copy number mutations, and can thus greatly facilitate the classiﬁcation, clinical research, diagnosis and management of AML–NK. Leukemia (2013) 27, 1820–1825; doi:10.1038/leu.2013.117 Keywords: acute myeloid leukaemia; diagnosis; classiﬁcation; targeted capture; next generation sequencing; minimal residual disease; MIDAS Keywords: acute myeloid leukaemia; diagnosis; classiﬁcation; targeted capture; next generation sequencing; minimal residual disease; MIDAS Keywords: acute myeloid leukaemia; diagnosis; classiﬁcation; targeted capture; next generation sequencing; minimal residual disease; MIDAS INTRODUCTION cases of AML are composed of several related subclones, arising through the acquisition of different somatic mutations during clonal evolution from a single-ancestral cell.6,10 These clones are often invisible to conventional diagnostic methods, yet they commonly represent a signiﬁcant, if not the main, clone at the time of leukaemia relapse.10 As relapse is the main vehicle for the poor prognosis of AML, the detection of clones carrying adverse mutations at the time of diagnosis can help identify and stratify high-risk patients. Advances in DNA sequencing technologies are revolutionising our understanding of the genetic basis of cancer.1 One of the ﬁrst cancers studied by whole-genome sequencing was acute myeloid leukaemia with a normal karyotype (AML–NK),2,3 a disease whose molecular aetiology was, until recently, poorly understood. As a result, we now know of more than 10 genes mutated in 45% of cases of AML–NK and of several others mutated less often.4–6 Additionally, it has become clear that mutations other than those affecting FLT3,7 NPM18 and CEBPA9 have a signiﬁcant impact on prognosis and can help stratify anti-AML therapy for individual patients.4 In this light, many are calling for a shift towards a classiﬁcation system for AML–NK based primarily on mutational proﬁling.4 Given the above, a full molecular diagnostic evaluation of AML requires the identiﬁcation of all mutations with prognostic or therapeutic signiﬁcance in the main clone, as well as in subclones when these are present. Here we successfully employ targeted DNA capture with cRNA baits followed by deep sequencing and tailored informatics to simultaneously study 24 genes known to be recurrently mutated in AML–NK and 10 control genes. Currently, many diagnostic laboratories routinely screen for mutations in NPM1 and FLT3, both of which show clustering of somatic mutations in 1–3 exons. However, mutational screening for genes such as CEBPA and TET2, which do not exhibit mutation clustering, is only employed in specialist laboratories. Further- more, with the identiﬁcation of an increasing number of mutant genes in AML, detailed molecular genotyping can no longer be practicably performed using conventional molecular methods such as capillary sequencing or melt curve analyses. Moreover, modern sequencing technologies have demonstrated that many Received 21 October 2012; revised 17 March 2013; accepted 10 April 2013; accepted article preview online 18 April 2013; advance o 8These authors contributed equally to this work. q y Received 21 October 2012; revised 17 March 2013; accepted 10 April 2013; accepted article preview online 18 April 2013; advance online publication, 24 May 2013 Mutation calling Alignment and post-processing. Fastq ﬁles were aligned against the human genome (hg19 version) using BWA algorithm (v 0.5.9). Afterwards SAMTOOLS (0.1.18) view, sort, index and ﬁxmate algorithms were used to generate, sort, index and ﬁx co-ordinates of the generated bam ﬁles. PICARD (v1.61) java libraries were used to mark PCR duplicates and ﬁnally GATK (v. 1.4.20) tools were used to perform local realignment around indels. All these steps were automated using a single in-house written script available upon request. Variant calling. SAMTOOLS pileup command was used to generate pileup ﬁles from the generated bam ﬁles (version 0.1.8) (http://samtools.source- forge.net/).15 A ﬂexible in-house Perl script (MIDAS, Mutation Identiﬁcation and Analysis Software; available upon request) was created to parse the pileup ﬁle and to take into account in each position only those reads with a sequence quality higher than 25 and a mapping quality higher than 15, and consider only those positions that had a coverage of at least 10 both in the tumour and in the control sample (unless otherwise stated, P1CR was used as control for all comparisons). On those positions, and taking into account the high coverage obtained in this experiment, we reported the possible existence of a substitution whenever there was at least 20 independent reads reporting a different base vs the reference genome in the tumour sample and less than 5% of the reads reporting the same variant in the control sample. We also discarded those positions with at least one-third of this evidence reporting a third allele, as we consider that those regions would probably represent difﬁcult sequences for the aligner and would likely produce false positives. We considered variants present in 420% of reads as those representing the main/dominant leukaemic clone. In the case of indels (small insertions and deletions), we considered positive those regions with at least 10 independent reads reporting the same indel in the tumour sample and with less than 5 reads in the control sample, and with at least 10 times more reads reporting the indel in the tumour vs the control sample. Similarly to what we did with substitutions, those regions with an evidence of a second indel higher than 40% of the evidence for the primary indel were discarded. Our workﬂow is shown in Figure 1. Coverage and statistical analysis Coverage and statistical analysis Coverage and statistical analysis Coverage histograms and tables describing the coverage distribution for our set of targeted bases were produced using TEQC, ‘Target Enrichment Quality Control’ Bioconductor package.13 To validate the ability of our assay to identify copy number changes, we used read numbers of two X-linked genes (HPRT and KDM6A). First, we generated a list of non- redundant ‘amalgamated exons’, each representing all overlapping annotated exons. Read count normalisation was done using open-source software and bespoke R scripts: for each sample, read counts per position were calculated using Bedtools 2.12.0 (http://code.google.com/p/ bedtools),14 then normalised read counts were calculated by averaging the exon-speciﬁc read counts and dividing by the total number of mapped reads for that sample. As DNA quality can affect capture efﬁciency and thus read counts, we ﬁrst wanted to ensure all 10 samples gave comparable standardised read depths for the majority of target regions. For this, we looked at the average read count for each patient at each gene. Sample P5 was an outlier for 23 of the 34 genes and was removed from copy number calculations. All other samples were outliers for three genes or less (Supplementary Figure S1). To identify copy number variation at individual exons, we calculated the coefﬁcient of variability for each exon for the nine patients. We then used the Tukey boxplot approach to identify the outlier exons (4upper quartile þ 1.5IQR, interquartile range). Data from genes with an increased coefﬁcient of variability at more than one exon were examined manually. The mixed-lineage leukaemia (MLL) deletion was also detected by analysis with ExomeCopy (http://www.bioconductor.org/ packages/2.11/bioc/html/exomeCopy.html). DNA target selection by ‘pull-down’ DNA target selection by pull down DNA fragmentation, library preparation and solution phase hybrid capture were performed according to manufacturer’s instructions (Agilent Technologies) and modiﬁed from previously published protocols.11 Sequencing and mapping Sequencing and mapping We sequenced 10 samples on a single multiplexed lane on an Illumina HiSeq 2000 and aligned the resulting reads to the hg19 reference genome q g pp g We sequenced 10 samples on a single multiplexed lane on an Illumina HiSeq 2000 and aligned the resulting reads to the hg19 reference genome Table 1. MATERIALS AND METHODS Leukaemic DNA samples Leukaemic DNA samples DNA samples from total bone marrow cells, excess to diagnosis, were obtained after informed consent within our ethics-approved study (07/MRE05/44) from seven patients with AML–NK. Remission samples were obtained from two of these patients and a relapse sample from one. q y evised 17 March 2013; accepted 10 April 2013; accepted article preview online 18 April 2013; advance online publication, 24 May 2013 Molecular characterisation of AML by targeted capture N Conte et al Molecular characterisation of AML by targeted capture N Conte et al Bait design We designed a set of Sure Select cRNA biotinylated oligon (Agilent Technologies, Palo Alto, CA, USA) to capture all exon 24 genes known to be recurrently mutated in AML and 10 some known to be mutated in solid tumours (Table 1). Th library was designed using eArray software (Agilent Tech exons of the 34 genes were downloaded from Biomart (h sembl.org/biomart/martview/) and used to create 120 bp every 24 bp. The masking option used was ‘RepeatMa software allowed baits to overlap by a maximum of 20 b masked regions. The centred design strategy was used, whic the tiling level was maintained and baits were not ‘squ speciﬁed interval. As a result, the input region could be expa at each end. The concentration of individual baits was adju depending on the target nucleotide composition to optimis GC-rich regions (n ¼ 1579) had 2x and orphan regions (n ¼ as those covered by a single bait, 5x more bait molecules standard regions (n ¼ 5997). The total target region size nucleotides and the library design is available under the reference: 0324251. DNA target selection by ‘pull-down’ DNA fragmentation, library preparation and solution phase were performed according to manufacturer’s instruct Technologies) and modiﬁed from previously published prot Sequencing and mapping We sequenced 10 samples on a single multiplexed lane o HiSeq 2000 and aligned the resulting reads to the hg19 refe Table 1. Genes analysed by targeted capture Gene ID Chromosome P AML genes NRAS 1 DNMT3A 2 SF3B1 2 IDH1 2 KIT 4 TET2 4 CSF1R 5 NPM1 5 EZH2 7 JAK2 9 PTEN 10 WT1 11 MLL 11 CBL 11 KRAS 12 PTPN11 12 FLT3 13 IDH2 15 TP53 17 NF1 17 CEBPA 19 ASXL1 20 RUNX1 21 KDM6A X Control genes UGT1A1 2 PIK3CA 3 IKZF1 7 EGFR 7 BRAF 7 XRCC2 7 PAX5 9 1821 Coverage and statistical analysis Genes analysed by targeted capture Gene ID Chromosome Position (Mb) AML genes NRAS 1 115.2 DNMT3A 2 25.5 SF3B1 2 198.3 IDH1 2 209.1 KIT 4 55.5 TET2 4 106.1 CSF1R 5 149.4 NPM1 5 170.8 EZH2 7 148.5 JAK2 9 5.0 PTEN 10 89.6 WT1 11 32.4 MLL 11 118.3 CBL 11 119.1 KRAS 12 25.4 PTPN11 12 112.9 FLT3 13 28.6 IDH2 15 90.6 TP53 17 7.6 NF1 17 29.4 CEBPA 19 33.8 ASXL1 20 30.9 RUNX1 21 36.2 KDM6A X 44.7 Control genes UGT1A1 2 234.7 PIK3CA 3 178.9 IKZF1 7 50.3 EGFR 7 55.1 BRAF 7 140.4 XRCC2 7 152.3 PAX5 9 36.8 TLR4 9 120.5 CYP2D6 22 42.5 HPRT1 X 133.6 Abbreviation: AML, acute myeloid leukaemia. with BWA (Burrows–Wheeler Alignment; http://bio-bwa.sourceforge.net/ bwa.shtml).12 1 with BWA (Burrows–Wheeler Alignment; http://bio-bwa.sourceforge.net/ bwa.shtml).12 1 Abbreviation: AML, acute myeloid leukaemia. Bait design g We designed a set of Sure Select cRNA biotinylated oligonucleotide baits (Agilent Technologies, Palo Alto, CA, USA) to capture all exons from a set of 24 genes known to be recurrently mutated in AML and 10 control genes, some known to be mutated in solid tumours (Table 1). The custom bait library was designed using eArray software (Agilent Technologies). The exons of the 34 genes were downloaded from Biomart (http://www.en- sembl.org/biomart/martview/) and used to create 120 bp baits starting every 24 bp. The masking option used was ‘RepeatMasker’ and the software allowed baits to overlap by a maximum of 20 bp with repeat masked regions. The centred design strategy was used, which ensured that the tiling level was maintained and baits were not ‘squeezed’ in the speciﬁed interval. As a result, the input region could be expanded by 20 bp at each end. The concentration of individual baits was adjusted manually depending on the target nucleotide composition to optimise DNA capture GC-rich regions (n ¼ 1579) had 2x and orphan regions (n ¼ 649), deﬁned as those covered by a single bait, 5x more bait molecules per locus than standard regions (n ¼ 5997). The total target region size was 24 2051 nucleotides and the library design is available under the unique ELID reference: 0324251. Mutation calling Of note, MIDAS allows adjustment of tolerance thresholds to suit the type of control sample used (for example, they can be increased to facilitate the use of a remission sample as a control, which may harbour residual low-level mutant reads). Comparison with other software/algorithms. The performance of our software was checked using independent variant calling algorithms. In particular, we run SomaticSniper (v. 1.0.2; http://gmt.genome.wustl.edu/ Leukemia (2013) 1820 – 1825 Leukemia (2013) 1820 – 1825 Molecular characterisation of AML by targeted capture N Conte et al Mutation Mutation C(kli) BWA (aln) BWA (sampe) SAMTOOLS (sort) Mutation Consequence Mutationcalling MIDAS VEP SAMTOOLS (fixmate) SomaticSniper PICARD (MarkDuplicates) GATK (RealignerTargetCreator & IndelRealigner) SAMTOOLS (sort) SAMTOOLS (view) SAMTOOLS (fixmate) SAMTOOLS (index) VarScan Figure 1. Workﬂow diagram for data analysis and mutation calling. After initial parsing of sequencing data through a series of open source software tools, mutation calling is performed by our in-house Perl script (MIDAS). Mutational consequences are then determined by Variant Effect Predictor, Ensembl. For the purposes of comparing MIDAS with other callers, SomaticSniper and VarScan were used instead. Molecular characterisation of AML by targeted capture N Conte et al 2 1822 VarScan Figure 1. Workﬂow diagram for data analysis and mutation calling. After initial parsing of sequencing data through a series of open source software tools, mutation calling is performed by our in-house Perl script (MIDAS). Mutational consequences are then determined by Variant Effect Predictor, Ensembl. For the purposes of comparing MIDAS with other callers, SomaticSniper and VarScan were used instead. Figure 2. Distribution of the depth of sequencing coverage of the target genes. Representative data from sample P1 showing the fraction of bases covered at incremental depth windows (blue bars and left hand y axis) and the cumulative fraction of bases covered at or above the speciﬁed coverage (orange line and right hand y axis). This shows that B88% of bases were covered at by at least 1000x sequencing reads. Validation of mutations and copy number changes identiﬁed by next-generation sequencing All dominant clone mutations were conﬁrmed using PCR and capillary sequencing. PCR was performed with Platinum Taq Polymearse (Invitrogen Corporation, Carlsbad, CA, USA) for 35 cycles at 561C annealing and 721C extension for 30s. To amplify across the breakpoint of the MLL-partial tandem duplication, we used LongAmp 2x Taq mastermix (New England Biolabs, Ipswich, MA, USA) for 35 cycles at 571C annealing and 65 1C extension for 3min. Mutation calling PCR for detection of FLT3-internal tandem duplication was performed as described previously.18 Mutant reads were visualised using IGV (Integrative Genomics Viewer; http://www.broadinstitute.org/igv/bam). To verify the two PTEN deletions, we used six known single-nucleotide polymorphisms within introns of the PTEN gene. We ampliﬁed these by PCR, followed by second- round PCR with barcoded Illumina adapter primers and sequencing on a MiSeq sequencer. We used these results to look for evidence of copy number change for one of the two alleles compared with a reference normal (P6 vs ctrl) or a paired remission sample (P2 vs P2CR). All primer sequences are given in Supplementary Table S1. & 2013 Macmillan Publishers Limited RESULTS Figure 2. Distribution of the depth of sequencing coverage of the target genes. Representative data from sample P1 showing the fraction of bases covered at incremental depth windows (blue bars and left hand y axis) and the cumulative fraction of bases covered at or above the speciﬁed coverage (orange line and right hand y axis). This shows that B88% of bases were covered at by at least 1000x sequencing reads. Analysis of our sequencing data showed a mean coverage depth of 5136 per nucleotide position within the target region (Figure 2). The 10 and 100 coverage were 96.4% and 94.8%, respectively, for the desired target region (that is, all exons of 34 genes) (Supplementary Table S2), with most of the remaining 3.6–5.2% representing repetitive regions for which baits could not be designed. With regards to substitutions and indels among the seven AMLs studied, our mutation caller, MIDAS, identiﬁed 20 exonic and one intronic mutations in the main leukaemic clone (2–4 mutations per AML, Table 2). The same 20 exonic mutations were identiﬁed by the VarScan platform and all were successfully validated using Sanger sequencing (Supplementary Figure S2), giving both MIDAS and VarScan 100% speciﬁcity for this data set. SomaticSniper, which was designed for the identiﬁcation of substitutions but not indels, performed slightly less well (Supplementary Table S3). Of the 20 exonic mutations, 11 were single-base non-synonymous substitu- tions at known sites (9 missense and 2 nonsense) and 9 were small indels (8 associated with premature termination and 1 with a single amino-acid insertion). somatic-sniper/current/)16 on the bam ﬁles using the default parameters and VarScan (v2.3, http://varscan.sourceforge.net/)17 on the pileup ﬁles using both the default mode and a high-sensitivity mode setting a minimum variant frequency of 0.01, a normal purity of 0.95 and a tumour purity of 0.20. In order to be able to compare the results with the calls made by our software, the raw data generated by the other callers were afterwards ﬁltered according to the frequency and ratios criteria speciﬁed in the above paragraph. somatic-sniper/current/)16 on the bam ﬁles using the default parameters and VarScan (v2.3, http://varscan.sourceforge.net/)17 on the pileup ﬁles using both the default mode and a high-sensitivity mode setting a minimum variant frequency of 0.01, a normal purity of 0.95 and a tumour purity of 0.20. RESULTS Diagnostic information and mutations in the dominant leukaemic clone of patient samples Sample ID Age Sex Sample type FAB WCC (x109/l) BM blasts % CD34 þ % CD13 þ % CD33 þ % CD7 þ % CD56 þ % Karyotype Mutations in dominant AML clone P1 45 F P M5a 140 90 3 56 75 26 0 46XX NPM1 L287fs DNMT3A R882C FLT3 D835Y P2 71 M P M4 111 85 0 72 92 0 80 46XY ASXL1 G642fs* TET2 L1119* KRAS K117N NF1 intron 2 P3 73 M P M2 108 95 34 44 75 0 0 46XY CEBPA A111fs* CEBPA T310NT WT1 R145fs* NRAS G12D P4 43 F P M1 24.4 95 0 12 81 0 2 46XX NPM1 L287fs* IDH2 R140Q P5 47 M P M5a 38 80 0 74 33 45 0 46XY NPM1 L287fs* IDH1 R132H FLT3 D835Y P6 80 M P M1 116 95 0 53 99 6 79 46XY ASXL1 C594* TET2 P612fs* KRAS G12V P7 59 F P M4 2.6 60 85 80 7 0 0 46XX DNMT3A G590fs* IDH2 R172K P1CR 45 F CR n/a n/a n/a n/a n/a n/a n/a n/a n/a P2CR 71 M CR n/a n/a n/a n/a n/a n/a n/a n/a n/a P4Rel 45 F Rel1 M1 3 65% nd nd nd nd nd 46XX NPM1c (TCTG) IDH2 R140Q Abbreviations: BM bone marrow; CR complete remission; F female; M male; n/a not applicable; nd not determined Given the above, we went on to look for copy number aberrations involving the target exons using the Tukey Box-plot method. The only autosomal gene loci exhibiting a signiﬁcantly increased coefﬁcient of variability at multiple exons were CYP2D6, MLL and PTEN (Supplementary Figure S4). CYP2D6 is known to exhibit copy number variation and per exon read numbers were in keeping with one individual (P3) having a lower CYP2D6 copy number than the others (Supplementary Figure S5b). In the case of PTEN, two samples (P2 and P6) had lower read numbers (Supplementary Figure S5c), suggesting that these two cases of AML may harbour deletions involving PTEN. To conﬁrm this using our limited material, we looked at differential allelic read counts for six intronic single-nucleotide polymorphisms within the PTEN locus, using PCR ampliﬁcation followed by sequencing on a MiSeq sequencer. RESULTS In order to be able to compare the results with the calls made by our software, the raw data generated by the other callers were afterwards ﬁltered according to the frequency and ratios criteria speciﬁed in the above paragraph. The predicted protein consequences of variations were derived using Variant Effect Predictor from Ensembl, http://www.ensembl.org/info/docs/ variation/vep/index.html. Leukemia (2013) 1820 – 1825 Molecular characterisation of AML by targeted capture N Conte et al 1823 In order to determine whether the read depth for our target regions correlated with DNA copy number, we compared standardised read numbers for two X-linked genes, HPRT and KDM6A, between male and female cases, and contrasted this with the same ratio for the remaining (autosomal) genes. This demonstrated that female cases displayed approximately twice the number of normalised reads of male cases for the two X-linked genes (F:M ratios of 2.0 for KDM6A and 1.91 for HPRT), signifying that read numbers approximately reﬂect copy number in the starting DNA. In keeping with this, male and female cases gave similar normalised read numbers (M:F ratios close to 1) for the 32 autosomal genes (Supplementary Figure S3). Samples that deviated from this ratio were later found to harbour copy number variation at the relevant gene locus in one or more samples (for example, CYP2D6 and PTEN). Furthermore, the quantitative nature of the data was evident at the level of individual exons and not just whole genes (for example, Supplementary Figure S5), demonstrating that the data were quantitative even at the level of small independently captured loci. Table 2. & 2013 Macmillan Publishers Limited DISCUSSION Advances in sequencing technologies are revolutionising cancer research with somatic mutations underlying most major cancers being avidly identiﬁed and characterised in large numbers of cases. Concurrently, clinical and functional studies are deﬁning the diagnostic/prognostic signiﬁcance of mutations and determining their molecular effects in order to device targeted therapeutic strategies. AML is at the forefront of such progress, and as a result a signiﬁcant body of information has already been gathered about this leukaemia that can be used to guide clinical practice. Additionally, after conﬁrming that our data behaved in a quantitative manner with respect to input DNA copy number in 9 of 10 DNAs studied, we went on to identify copy number variants in leukaemic samples, including an instance of MLL-partial tandem duplication and two instances of probable loss of PTEN, one of which we were able to validate. In analysing these data it became clear that the lack or copy number information from neighbouring genomic regions made analysis more difﬁcult, and we recommend that future studies of this kind endeavour to capture several features around regions of possible copy number loss to enhance both the power and the reliability of analyses. Finally, we were able to demonstrate evidence of minimal residual disease in a bone marrow DNA sample in morphological complete remission by mining reads from the speciﬁc mutations in the remission sample. Quantiﬁcation of minimal residual disease after induction chemotherapy may have prognostic implications in a heterogeneous disease such as AML–NK and could be employed in interventional studies to determine its signiﬁcance. To date, most diagnostic laboratories use allele-speciﬁc technologies to identify mutations in genes such as NPM1 and FLT3, which have validated prognostic and therapeutic signiﬁ- cance.7,20,21 Additionally, newer technologies have been shown to reliably identify leukaemia-associated mutations in larger numbers of amplicons using pyrosequencing.22 However, the increasing number of clinically relevant genes found mutated in AML make conventional amplicon-based approaches impractical, particularly as many such genes can harbour mutations in multiple different locations and exons.23,24 Additionally, the clear demonstration that many AMLs are composed of multiple subclones that can be differentially susceptible to existing therapies10 suggests that accurate therapeutic stratiﬁcation of patients would beneﬁt from the identiﬁcation of such clones at ﬁrst presentation. RESULTS Our results conﬁrm copy number change at the PTEN locus for P2 by demonstrating a preferential reduction in read counts from one allele of two independent informative single- nucleotide polymorphisms when compared with the matched remission sample (P2CR) (Supplementary Table S4). In the case of P6, only one single-nucleotide polymorphisms was informative and although this was suggestive of copy number loss, we cannot be completely conﬁdent this is the case in the absence of a matched normal sample. In the case of MLL, one sample (P6) showed an increased number of normalised reads for exons 2–9 only, suggesting the presence of a partial tandem duplication (Figures 3a and b and Supplementary Figure S5d). This was also identiﬁed by analysis using the ExomeCopy package19 (Supplementary Figure S6). The presence of a partial tandem duplication was conﬁrmed using PCR primers to amplify the region spanning the junction (Figure 2c). g p g j ( g ) We went on to analyse our data to identify single-nucleotide substitutions uniquely present in putative leukaemic subclones representing as few as 1% of cells. We identiﬁed putative subclonal mutations representing 3–20% of reads in four leukaemic samples: (i) a FLT3 internal tandem duplication in sample P3, which was ﬂagged as a series of indels and substitutions and conﬁrmed by PCR (we went on to test all seven AML samples for FLT3-internal tandem duplication and only sample P3 was positive—data not shown), (ii) NRAS-G12S and PTPN11-Q506P mutations in sample P5. The latter two mutations occurred in 4.4% and 4.1% of reads, respectively, in keeping with possible co-occurrence in the same subclone, (iii) FLT3-N676K in sample P4 and (iv) TP53-G374fs*8 in sample P4Rel (Supplementary Table S5). Finally, we analysed the two paired diagnosis-remission samples (P1 vs P1CR and P2 vs P2CR) to look for evidence of residual mutant reads in each remission sample. Both remission samples were in morphological complete remission, but sample P1CR was taken after four courses and sample P2CR after one course of chemotherapy. RESULTS At a level of sensitivity of at least 0.1%, Leukemia (2013) 1820 – 1825 P1 P2 P3 P4 P6 P7 P1CR P2CR P4Rel Normalised Read Depth P6 P4 P7 H2O 1.0 2.0 3.0 1.5 2.5 kb 8 9 2 MLL_9F MLL_2R 100kb MLL exons 1-14 1 2 9 14 Putative breakpoint for exon 2-9 duplication Exons with increased read depth from sample P6 6000 5000 4000 3000 2000 1000 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Figure 3. Identiﬁcation of MLL partial tandem duplication (PTD) using sequencing read depth. Normalised per exon sequencing read depths for the ﬁrst 14 exons of MLL show increased depth for exons 2–9 from sample P6 (a). This suggested the presence of an exon 2 to exon 9 PTD with a breakpoint in intron 9 (b). PCR ampliﬁcation across the putative breakpoint using an exon 9 forward (MLL_9F) and an exon 2 reverse (MLL_2R) primer conﬁrms the presence of the PTD in this AML sample (c). Molecular characterisation of AML by targeted capture N Conte et al 4 Molecular characterisation of AML by targeted capture N Conte et al 1824 P1 P2 P3 P4 P6 P7 P1CR P2CR P4Rel Normalised Read Depth Exons with increased read depth from sample P6 6000 5000 4000 3000 2000 1000 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Figure 3. Identiﬁcation of MLL partial tandem duplication (PTD) using sequencing read depth. Normalised per exon sequencing read depths for the ﬁrst 14 exons of MLL show increased depth for exons 2–9 from sample P6 (a). This suggested the presence of an exon 2 to exon 9 PTD with a breakpoint in intron 9 (b). PCR ampliﬁcation across the putative breakpoint using an exon 9 forward (MLL_9F) and an exon 2 reverse (MLL_2R) primer conﬁrms the presence of the PTD in this AML sample (c). we found no mutant reads in sample P1CR, while sample P2CR gave residual mutant reads representing 1.5–2.4% of total reads for all three mutations identiﬁed at diagnosis (Supplementary Table S6). By contrast, no novel polymorphisms or mutations were identiﬁed in 10 control genes known to be mutated in solid tumours or leukaemias other than AML. The sequencing depth reached in this study also enabled us to identify putative mutations present in subclones at the time of diagnosis. RESULTS It is already clear that, compared with the main clone, such subclones may be differentially sensitive to chemotherapy and can expand to become the dominant clone at the time of disease relapse,10 making their identiﬁcation at the time of diagnosis important. Nevertheless, at this stage, such subclonal mutations need to be validated using independent metho- dologies as it remains possible that they represent sequencing or other forms of error. & 2013 Macmillan Publishers Limited REFERENCES 1 Stratton MR, Campbell PJ, Futreal PA. The cancer genome. Nature 2009; 458: 719–724. 1 Stratton MR, Campbell PJ, Futreal PA. The cancer genome. Nature 2009; 458: 719–724. 19 Love MI, Mysickova A, Sun R, Kalscheuer V, Vingron M, Haas SA. Modeling read counts for CNV detection in exome sequencing data. Stat Appl Genet Mol Biol 2011; 10. 2 Ley TJ, Mardis ER, Ding L, Fulton B, McLellan MD, Chen K et al. DNA sequencing of a cytogenetically normal acute myeloid leukaemia genome. Nature 2008; 456: 66–72. 2 Ley TJ, Mardis ER, Ding L, Fulton B, McLellan MD, Chen K et al. DNA sequencing of a cytogenetically normal acute myeloid leukaemia genome. Nature 2008; 456: 66–72. 20 Smith BD, Levis M, Beran M, Giles F, Kantarjian H, Berg K et al. Single-agent CEP-701, a novel FLT3 inhibitor, shows biologic and clinical activity in patients with relapsed or refractory acute myeloid leukemia. Blood 2004; 103: 3669–3676. 3 Mardis ER, Ding L, Dooling DJ, Larson DE, McLellan MD, Chen K et al. Recurring mutations found by sequencing an acute myeloid leukemia genome. N Engl J Med 2009; 361: 1058–1066. 21 Sanz M, Burnett A, Lo-Coco F, Lowenberg B. FLT3 inhibition as a targeted therapy for acute myeloid leukemia. Curr Opin Oncol 2009; 21: 594–600. 4 Patel JP, Gonen M, Figueroa ME, Fernandez H, Sun Z, Racevskis J et al. Prognostic relevance of integrated genetic proﬁling in acute myeloid leukemia. N Engl J Med 2012; 366: 1079–1089. 22 Grossmann V, Kohlmann A, Eder C, Haferlach C, Kern W, Cross NC et al. Molecular proﬁling of chronic myelomonocytic leukemia reveals diverse mutations in 480% of patients with TET2 and EZH2 being of high prognostic relevance. Leukemia 2011; 25: 877–879. 5 Grossmann V, Tiacci E, Holmes AB, Kohlmann A, Martelli MP, Kern W et al. Whole-exome sequencing identiﬁes somatic mutations of BCOR in acute myeloid leukemia with normal karyotype. Blood 2011; 118: 6153–6163. 23 Ley TJ, Ding L, Walter MJ, McLellan MD, Lamprecht T, Larson DE et al. DNMT3A mutations in acute myeloid leukemia. N Engl J Med 2010; 363: 2424–2433. 6 Welch JS, Ley TJ, Link DC, Miller CA, Larson DE, Koboldt DC et al. The origin and evolution of mutations in acute myeloid leukemia. Cell 2012; 150: 264–278. 7 Gale RE, Green C, Allen C, Mead AJ, Burnett AK, Hills RK et al. ACKNOWLEDGEMENTS y Sequence Alignment/Map format and SAMtools. Bioinformatics 2009; 25: 2078–2079. We acknowledge the use of the National Institute of Health Research (NIHR) Biomedical Research Centre, University of Cambridge. We thank Drs J Craig and C Crawley of Cambridge University NHS Hospitals trust for allowing us to approach their patients for samples. GV is funded by a Wellcome Trust Senior Fellowship in Clinical Science. Work in GV’s laboratory is also funded by Leukaemia Lymphoma Research and the Kay Kendal Leukaemia Fund. 16 Larson DE, Harris CC, Chen K, Koboldt DC, Abbott TE, Dooling DJ et al. Soma- ticSniper: identiﬁcation of somatic point mutations in whole genome sequencing data. Bioinformatics 2012; 28: 311–317. 17 Koboldt DC, Zhang Q, Larson DE, Shen D, McLellan MD, Lin L et al. VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res 2012; 22: 568–576. 18 Kiyoi H, Naoe T, Nakano Y, Yokota S, Minami S, Miyawaki S et al. Prognostic implication of FLT3 and N-RAS gene mutations in acute myeloid leukemia. Blood 1999; 93: 3074–3080. CONFLICT OF INTEREST 12 Bullinger L, Armstrong SA. HELP for AML: methylation proﬁling opens new avenues. Cancer Cell 2010; 17: 1–3. Dr Bram Herman is an employee of Agilent Technologies, manufacturer of Sure Select cRNA baits used for targeted capture. His contribution to this work was limited to the bespoke design of our bait set to maximise target DNA capture and the provision of bait sequence ﬁles for bioinformatic analyses. 13 Hummel M, Bonnin S, Lowy E, Roma G. TEQC: an R package for quality control in target capture experiments. Bioinformatics 2011; 27: 1316–1317. 14 Quinlan AR, Hall IM. BEDTools: a ﬂexible suite of utilities for comparing genomic features. Bioinformatics 2010; 26: 841–842. 15 Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N et al. The 15 Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009; 25: 2078–2079. DISCUSSION Nat Biotechnol 2009; 27: 182–189. DISCUSSION p We describe a method based on targeted DNA capture with cRNA baits followed by deep sequencing that enables the simultaneous identiﬁcation of mutations in 24 AML genes, including the 10 most frequently mutated in AML–NK, without recourse to normal constitutional DNA from the same individual. Somatic mutations in the dominant leukaemic clone were identiﬁed in all cases studied using sequence alignment/conﬁ- guration with open source software followed by mutation calling using our in-house mutation caller MIDAS (Figure 2). The same mutations were identiﬁed by the mutation caller VarScan17 and all mutations so identiﬁed were validated using capillary sequencing, demonstrating 100% speciﬁcity for both callers for our data set. We describe a molecular diagnostic method that enables extensive molecular characterisation of AML–NK at diagnosis and can facilitate clinical management of patients as well as clinical research into this disease. The approach is powerful, reliable and can be introduced into routine clinical practice in order to enhance our ability to identify patients at high risk of relapse as well as those that would beneﬁt from molecularly directed therapies and can also be adapted for minimal residual disease monitoring. The sequencing methodology is modular and target regions can be increased to include any newly discovered gene mutations without signiﬁcant changes to laboratory Leukemia (2013) 1820 – 1825 Molecular characterisation of AML by targeted capture N Conte et al 1825 protocols and with only marginal increases in costs. Additionally, we provide a clear analytical workﬂow employing MIDAS, a novel mutation calling algorithm available on request, which correctly identiﬁed 20/20 exonic mutations present in 420% of reads. The blueprint presented here can be used to study other haemato- logical or solid tumours, or groups of tumours with overlapping mutational spectra. 9 Preudhomme C, Sagot C, Boissel N, Cayuela JM, Tigaud I, de Botton S et al. Favorable prognostic signiﬁcance of CEBPA mutations in patients with de novo acute myeloid leukemia: a study from the Acute Leukemia French Association (ALFA). Blood 2002; 100: 2717–2723. (ALFA). Blood 2002; 100: 2717–2723. 10 Ding L, Ley TJ, Larson DE, Miller CA, Koboldt DC, Welch JS et al. Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing. Nature 2012; 481: 506–510. 11 Gnirke A, Melnikov A, Maguire J, Rogov P, LeProust EM, Brockman W et al. Solution hybrid selection with ultra-long oligonucleotides for massively parallel targeted sequencing. Nat Biotechnol 2009; 27: 182–189. targeted sequencing. REFERENCES The impact of FLT3 internal tandem duplication mutant level, number, size, and interaction with NPM1 mutations in a large cohort of young adult patients with acute myeloid leukemia. Blood 2008; 111: 2776–2784. 24 Delhommeau F, Dupont S, Della Valle V, James C, Trannoy S, Masse A et al. Mutation in TET2 in myeloid cancers. N Engl J Med 2009; 360: 2289–2301. This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http:// creativecommons.org/licenses/by/3.0/ This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http:// creativecommons.org/licenses/by/3.0/ 8 Falini B, Mecucci C, Tiacci E, Alcalay M, Rosati R, Pasqualucci L et al. Cytoplasmic nucleophosmin in acute myelogenous leukemia with a normal karyotype. N Engl J Med 2005; 352: 254–266. 8 Falini B, Mecucci C, Tiacci E, Alcalay M, Rosati R, Pasqualucci L et al. Cytoplasmic nucleophosmin in acute myelogenous leukemia with a normal karyotype. N Engl J Med 2005; 352: 254–266. mentary Information accompanies this paper on the Leukaemia website (http://www.nature.com/leu) Leukemia (2013) 1820 – 1825 & 2013 Macmillan Publishers Limited
https://openalex.org/W4288760570	https://www.nature.com/articles/s41419-022-05116-w.pdf	English	null	Germline FOXJ2 overexpression causes male infertility via aberrant autophagy activation by LAMP2A upregulation	Cell death and disease	2,022	cc-by	11,613	INTRODUCTION S i spermatids [8]. Foxj2 overexpression (Foxj2 transgenic mice) had a lethal effect on embryonic development. Among the small number of transgenic mice that survived to adulthood, only two mice (one male and one female) showed mosaic Foxj2 expression and died at 9 w and 12 w, respectively, because of cardio- respiratory failure. The male transgenic mouse did not produce any offspring, while the female transgenic mouse had two pregnancies recorded. Histological analysis of the testes of this male transgenic mouse showed no mature spermatozoa in the seminiferous tubules, suggesting the failure of spermatogenesis. The mosaic and randomly integrated expression of the transgene, as well as the limitation of the number of samples (1 case) and observation time (9 w), made the results unconvincing [7]. Interestingly, our previous study and other research found that Foxj2 mRNA was upregulated in the spermatocytes and round spermatids in miR-34b/c−/−; miR-449−/−sterile mice [9, 10]. Furthermore, it was reported that loss of Foxj2 in the male germline led to meiotic arrest and infertility via an as-yet-unknown mechanism [11]. Spermatogenesis is a highly complex process comprising cell proliferation, differentiation, and migration, which is necessary to produce haploid spermatozoa. There are three main stages of spermatogenesis: mitosis of spermatogonia, meiosis of spermato- cytes, and spermiogenesis of spermatids. Abnormalities in any stage may lead to failure of the entire spermatogenesis process, resulting in a reduced number or abnormal morphology of sperm, which will ultimately affect the reproduction and development of the individual. The successful progression of spermatogenesis is strictly controlled by accurate spatial and temporal regulation of gene expression, including transcriptional regulation through transcription factors binding to gene regulatory elements [1, 2]. Fork head box J2 (FOXJ2) is a transcription factor discovered in mammals and other vertebrates in 2000, which belongs to the Fork head box (Fox) transcription factor family, which shares a conserved DNA-binding domain, known as Fork Head [3, 4]. FOXJ2 participates in the regulation of cell proliferation, differentiation, and migration by targeting downstream genes through its DNA- binding domain, and plays fundamental roles in embryonic development, tumorigenesis, and the progression of certain cancers [5–7]. Previous studies demonstrated that Foxj2 mRNA is speciﬁcally expressed in spermatocytes and round spermatids in mouse testis, but not in spermatogonia or elongating/elongated The above research indicated that FOXJ2 participates in the regulation of spermatogenesis. However, which stage of sperma- togenesis is affected by FOXJ2 and the regulation mechanism remain elusive. 1Department of Histoembryology, Genetics and Developmental Biology, Shanghai Jiao Tong University School of Medicine, 200025 Shanghai, China. 2Shanghai Key Laboratory of Reproductive Medicine, 200025 Shanghai, China. 3School of Medicine, Shanghai Jiao Tong University, 200025 Shanghai, China. 4These authors contributed equally: Fu-Rong Bai, Qi-Qian Wu. ✉email: zpwujw@shsmu.edu.cn Edited by Professor Gian Maria Fimia ARTICLE OPEN Germline FOXJ2 overexpression causes male infertility via aberrant autophagy activation by LAMP2A upregulation Fu-Rong Bai1,2,4, Qi-Qian Wu 1,2,4, Yu-Jie Wu1,2, Yan-Qin Hu1,2, Zhi-Xuan Jiang3, Hao Lv3, Wen-Zhe Qian3, Chang Cai3 and Jing-Wen Wu 1,2✉ © The Author(s) 2022 © The Author(s) 2022 Spermatogenesis is a complex biological process that produces haploid spermatozoa and requires precise regulation by many tissue-speciﬁc factors. In this study, we explored the role and mechanism of Fork head box J2 (FOXJ2, which is highly expressed in spermatocytes) in the regulation of spermatogenesis using a germline-speciﬁc conditional Foxj2 knock-in mouse model (Stra8-Cre; Foxj2 tg/tg mouse). Foxj2 overexpression in mouse testes led to spermatogenesis failure, which started at the initiation of meiosis, and resulted in male infertility. Lysosomes and autophagy-related genes were upregulated in Stra8-cre; Foxj2 tg/tg mouse testes and the number of autolysosomes in the spermatocytes in Stra8-cre; Foxj2 tg/tg mice was increased. Chromatin immunoprecipitation-PCR and Dual-luciferase reporter assays showed that Lamp2 (encoding lysosome‐associated membrane protein‐2) was a target of FOXJ2. Foxj2 overexpression increased the expression levels of Lamp2a and Hsc70 (70-kDa cytoplasmic heat shock protein) in the Stra8-cre; Foxj2 tg/tg mouse testes. Our results suggested that Foxj2 overexpression in the germ cells of mouse testes affects chaperone-mediated autophagy by upregulating LAMP2A, leading to spermatogenesis failure at the initiation of meiosis, thus resulting in male infertility. Our ﬁndings provide a new insight into the function of FOXJ2 in spermatogenesis and the signiﬁcance of autophagy regulation in spermatogenesis. Cell Death and Disease (2022) 13:665 ; https://doi.org/10.1038/s41419-022-05116-w www.nature.com/cddis Received: 8 December 2021 Revised: 15 July 2022 Accepted: 18 July 2022 Overexpression of Foxj2 in mouse testes leads to failure of spermatogenesis p g To explore the role of FOXJ2 in spermatogenesis, we generated a germline-speciﬁc conditional Foxj2 knock-in mouse model (Foxj2- cKI) using the Cre-loxP recombination system (Fig. 2A, B). The successful generation of Foxj2-cKI mice was determined using PCR genotyping (Fig. 2C). In addition, the Foxj2 overexpression vector carried a haemagglutinin (HA)-tag, which was fused with the target protein and expressed without affecting the biological activity and location of the target protein. In addition, the Foxj2 overexpression vector expressed the green ﬂuorescent protein (GFP), therefore the detection of GFP could reﬂect the over- expression of Foxj2. As expected, GFP was only detected in the seminiferous tubules in the testes (Fig. 2D), but not in other tissues of the Stra8-cre; Foxj2 tg/tg mice (Supplementary Fig. S1A). Quantitative real-time reverse transcription PCR (qRT-PCR) demon- strated the testis-speciﬁc overexpression of Foxj2, whose expres- sion levels did not change signiﬁcantly in other tissues (Fig. 2E). WB analysis showed higher levels of FOXJ2 in the spermatocytes of Stra8-cre; Foxj2 tg/tg mice than in the wild-type (WT), conﬁrming the tissue-speciﬁc overexpression of FOXJ2 (Fig. 2F). FOXJ2 affects spermatocytes' autophagy by targeting Lamp2 To explore the molecular mechanism of spermatogenic failure in the Stra8-cre; Foxj2 tg/tg mice, we conducted RNA-sequencing (RNA-seq) to analyze the transcriptome alterations in the germ cells of Stra8-cre; Foxj2 tg/tg mice. Given that there were few spermatocytes and spermatids in the seminiferous tubules of adult Stra8-cre; Foxj2 tg/tg mouse testes, and the morphological difference between the Stra8-cre; Foxj2 tg/tg and control mice began from postanal day 10, we performed RNA-seq on the testicular cells of the 10-day-old Stra8-cre; Foxj2 tg/tg and WT mice. The RNA-seq data presented 7052 differentially expressed genes (DEGs) in the Stra8-cre; Foxj2 tg/tg mice as compared with those in the WT, including 3430 upregulated genes and 3622 downregulated genes, which was in line with the role of FOXJ2 as a transcriptional regulator (Fig. 5A). The Gene Ontology (GO) analysis of the DEGs showed that the genes participating in the Biological Processes (BP) involved in meiosis, such as DNA replication, DNA repair, and DNA recombination, were signiﬁcantly downregulated (Fig. 5B), which was consistent with the infertility phenotype of the Stra8-cre; Foxj2 tg/tg males with reduced spermatocytes in the seminiferous tubules. Notably, in the Cellular Component (CC) category, most of the genes related to lysosomes and vacuoles were upregulated in the Stra8-cre; Foxj2 tg/tg mouse testes (Fig. 5C). RESULTS FOXJ2 is highly ex g y p p y We found that FOXJ2 was localized to spermatocytes, round spermatids, and Sertoli cells in the seminiferous tubules using immunohistochemical and immunoﬂuorescent staining (Fig. 1A, B). To investigate the cellular localization of FOXJ2 in germ cells, we separated spermatogenic cells using STA-PUT velocity sedimentation [12]. Immunoﬂuorescent staining for FOXJ2 revealed its expression in the nuclei of spermatocytes and round spermatids (Fig. 1C). Moreover, western blotting (WB) showed that FOXJ2 was highly expressed in spermatocytes, suggesting a critical role in meiosis (Fig. 1D). INTRODUCTION S i In the present study, using a germline-speciﬁc conditional Foxj2 knock-in mouse model (Stra8-cre; Foxj2 tg/tg Ofﬁcial journal of CDDpress F.-R. Bai et al. 2 [13–15]. To determine which step of spermatogenesis is ﬁrst impacted by Foxj2 overexpression, we observed developing testes in the prepubertal mice. By 7 days after birth, there were only spermatogonia and Sertoli cells in the testes of both Stra8-cre; Foxj2 tg/tg mice and the control littermates (Fig. 4A). When germ cells enter meiosis on day 10, morphological differences began to appear between the Stra8-cre; Foxj2 tg/tg mice and their control littermates (Fig. 4B). Quantitative analysis of the testicular cells in 10-day-old mice using ﬂow cytometry showed that the sperma- tocytes (4C cells) accounted for about 12.41% of the total number of testicular cells in the Stra8-cre; Foxj2 tg/tg mice, which was about half of that in the control mice (26.83%) (Fig. 4C, D), which conﬁrmed the decrease of primary spermatocytes in the 10-day- old Stra8-cre; Foxj2 tg/tg mice. On day 14, early pachytene spermatocytes appeared in some (32.09% ± 4.45%) seminiferous tubules in the testes of the control mice, while only a few (3.16% ± 1.02%) seminiferous tubules contained pachytene sper- matocytes in the Stra8-cre; Foxj2 tg/tg mice (Fig. 4E, F). By day 21, round spermatids were present in some (21.09% ± 11.57%) seminiferous tubules of the control mice, while there were almost no round spermatids (0.81% ± 0.24%) in the Stra8-cre; Foxj2 tg/tg testes, but many vacuoles were observed (Fig. 4G, H). Observation of the developing testes showed that the histological differences of the testes between the Stra8-cre; Foxj2 tg/tg mice and their control littermates began from postnatal day 10 when the spermatogenic cells enter meiosis, suggesting that overexpression of Foxj2 in germ cells led to a failure of meiosis initiation during spermatogenesis. mouse), we showed that Foxj2 overexpression in the germ cells of mouse testes may affect chaperone-mediated autophagy (CMA) by upregulating lysosome-associated membrane protein 2A (LAMP2A), leading to failure of spermatogenesis starting at the initiation of meiosis, ultimately resulting in male infertility. Our data provide a new insight into the role of FOXJ2 in spermatogen- esis and the signiﬁcance of autophagy regulation in spermatogenesis. Overexpression of Foxj2 in mouse testes leads to failure of spermatogenesis Meanwhile, the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of these DEGs showed that expression levels of genes involved in the lysosome and autophagy pathways were signiﬁcantly different between the Stra8-cre; Foxj2 tg/tg and WT mice (Fig. 5D). We then detected the expression levels of genes involved in autophagy pathways using qRT-PCR. The results showed that the mRNA expression levels of Ulk1 (encoding Unc- 51-like kinase 1) and Atg13 (autophagy-related gene 13), which are related to autophagy initiation, were decreased, while the mRNA expression levels of Map1lc3a (microtubule-associated protein 1 light chain 3 alpha), related to autophagosome extension, and Lamp2, related to autophagosome maturation, were upregulated signiﬁcantly in Stra8-cre; Foxj2 tg/tg mouse testes (Fig. 5E) [16–19]. Furthermore, to screen the potential target genes regulated by FOXJ2 in the testes, we obtained 287 predicted target genes of FOXJ2 through bioinformatic analyses using Transcription Factor p p g To test whether Foxj2 overexpression has an impact on male fertility, 2-month-old adult Stra8-cre; Foxj2 tg/tg males, as well as the control male littermates, were mated with fertility-proven adult females. The result showed that the control male littermates could produce an average of 9.67 ± 2.06 pups per litter, whereas Stra8-cre; Foxj2 tg/tg males failed to produce a pregnancy and were completely sterile (Fig. 3A), which suggested that overexpression of Foxj2 has a negative effect on male fertility. The testis size and relative weight (testis weight/body weight) of the Stra8-cre; Foxj2 tg/tg mice decreased signiﬁcantly compared with that of the control mice (Fig. 3B, C), which was likely caused by the loss of germ cells. Indeed, Periodic acid-Schiff (PAS) staining on testes sections showed that the numbers of spermatocytes and spermatids were signiﬁcantly reduced in the seminiferous tubules of Stra8-cre; Foxj2 tg/tg mice (Fig. 3D), resulting in almost no sperm in the epididymis (Fig. 3E) and a decreased sperm concentration in the Stra8-cre; Foxj2 tg/tg mouse epididymis (Fig. 3F). Together, these results account for the infertility phenotype observed in the Stra8-cre; Foxj2 tg/tg males. There are only spermatogonia and Sertoli cells in the seminiferous epithelium of postnatal day 6 mice. Meiosis occurs on day 10, with the appearance of preleptotene spermatocytes (pL) and leptotene spermatocytes (L), reaching the pachytene stage by day 14. Haploid spermatids appear around day 21 Cell Death and Disease (2022) 13:665 F.-R. Bai et al. g. Overexpression of Foxj2 in mouse testes leads to failure of spermatogenesis 1 FOXJ2 localized to spermatocytes, round spermatids, and Sertoli cells in the seminiferous tubules and was highly expressed in spermatocytes. A Expression and localization of FOXJ2 in mouse testes using immunohistochemical staining (IHC). The roman numbers present the stages of the seminiferous epithelia. S Sertoli cell, Rs round spermatid, L leptotene spermatocyte, M metaphase of spermatocyte. Scale bar: 10 μm. B Immunoﬂuorescent staining of SCP3 (showing spermatocytes) and FOXJ2, PNA (showing acrosomes) and FOXJ2, WT1(showing Sertoli cells) and FOXJ2 on testis sections of 8-week-old WT mice. Nuclei were counterstained with DAPI. Long white arrows indicate spermatocytes (Spc). White solid arrowheads indicate round spermatids (Rs). White hollow arrowheads indicate elongating spermatids (Es). Short white arrows indicate meiotic metaphase spermatocytes (M). White thick arrows indicate Sertoli cells (S). Scale bar: 50 μm. C Expression and localization of FOXJ2 in isolated spermatocytes (Spc) and round spermatids (Rs) using immunoﬂuorescent staining (IF). D Western blotting analysis of FOXJ2 protein levels in isolated spermatocytes (Spc) and round spermatids (Rs) with the corresponding average gray levels. H3 was used as a loading control. Data are presented as the mean ± SD (n = 3). P < 0.05. Fig. 1 FOXJ2 localized to spermatocytes, round spermatids, and Sertoli cells in the seminiferous tubules and was highly expressed in spermatocytes. A Expression and localization of FOXJ2 in mouse testes using immunohistochemical staining (IHC). The roman numbers present the stages of the seminiferous epithelia. S Sertoli cell, Rs round spermatid, L leptotene spermatocyte, M metaphase of spermatocyte. Scale bar: 10 μm. B Immunoﬂuorescent staining of SCP3 (showing spermatocytes) and FOXJ2, PNA (showing acrosomes) and FOXJ2, WT1(showing Sertoli cells) and FOXJ2 on testis sections of 8-week-old WT mice. Nuclei were counterstained with DAPI. Long white arrows indicate spermatocytes (Spc). White solid arrowheads indicate round spermatids (Rs). White hollow arrowheads indicate elongating spermatids (Es). Short white arrows indicate meiotic metaphase spermatocytes (M). White thick arrows indicate Sertoli cells (S). Scale bar: 50 μm. C Expression and localization of FOXJ2 in isolated spermatocytes (Spc) and round spermatids (Rs) using immunoﬂuorescent staining (IF). D Western blotting analysis of FOXJ2 protein levels in isolated spermatocytes (Spc) and round spermatids (Rs) with the corresponding average gray levels. H3 was used as a loading control. Data are presented as the mean ± SD (n = 3). P < 0.05. Binding Site (TFBS) Tools (1.18.0) software [20]. Overexpression of Foxj2 in mouse testes leads to failure of spermatogenesis 1 FOXJ2 localized to spermatocytes, round spermatids, and Sertoli cells in the seminiferous tubules and was highly expressed permatocytes. A Expression and localization of FOXJ2 in mouse testes using immunohistochemical staining (IHC). The roman numb resent the stages of the seminiferous epithelia. S Sertoli cell, Rs round spermatid, L leptotene spermatocyte, M metaphase of spermatoc cale bar: 10 μm. B Immunoﬂuorescent staining of SCP3 (showing spermatocytes) and FOXJ2, PNA (showing acrosomes) and FOX WT1(showing Sertoli cells) and FOXJ2 on testis sections of 8-week-old WT mice. Nuclei were counterstained with DAPI. Long white arro dicate spermatocytes (Spc). White solid arrowheads indicate round spermatids (Rs). White hollow arrowheads indicate elongat permatids (Es). Short white arrows indicate meiotic metaphase spermatocytes (M). White thick arrows indicate Sertoli cells (S). Scale 0 μm. C Expression and localization of FOXJ2 in isolated spermatocytes (Spc) and round spermatids (Rs) using immunoﬂuorescent stain F). D Western blotting analysis of FOXJ2 protein levels in isolated spermatocytes (Spc) and round spermatids (Rs) with the correspond verage gray levels H3 was used as a loading control Data are presented as the mean ± SD (n = 3) P < 0 05 F.-R. Bai et al. 3 3 Fig. 1 FOXJ2 localized to spermatocytes, round spermatids, and Sertoli cells in the seminiferous tubules and was highly expressed spermatocytes. A Expression and localization of FOXJ2 in mouse testes using immunohistochemical staining (IHC). The roman numbe present the stages of the seminiferous epithelia. S Sertoli cell, Rs round spermatid, L leptotene spermatocyte, M metaphase of spermatocy Scale bar: 10 μm. B Immunoﬂuorescent staining of SCP3 (showing spermatocytes) and FOXJ2, PNA (showing acrosomes) and FOX WT1(showing Sertoli cells) and FOXJ2 on testis sections of 8-week-old WT mice. Nuclei were counterstained with DAPI. Long white arro indicate spermatocytes (Spc). White solid arrowheads indicate round spermatids (Rs). White hollow arrowheads indicate elongati spermatids (Es). Short white arrows indicate meiotic metaphase spermatocytes (M). White thick arrows indicate Sertoli cells (S). Scale b 50 μm. C Expression and localization of FOXJ2 in isolated spermatocytes (Spc) and round spermatids (Rs) using immunoﬂuorescent staini (IF). D Western blotting analysis of FOXJ2 protein levels in isolated spermatocytes (Spc) and round spermatids (Rs) with the correspondi average gray levels. H3 was used as a loading control. Data are presented as the mean ± SD (n = 3). P < 0.05. Fig. Overexpression of Foxj2 in mouse testes leads to failure of spermatogenesis Only 103 out of 287 predicted target genes were identiﬁed among the DEGs dysregulated between the Stra8-cre; Foxj2 tg/tg and WT mouse testes (Fig. 5F) and GO analyses of the differentially expressed target genes revealed the genes related to lysosomes and lytic vacuoles had signiﬁcantly different expression levels (Supplemen- tary Fig. S2A). As mentioned above, among the DEGs, the genes related to lysosomes and autophagy were upregulated signiﬁcantly in Stra8- cre; Foxj2 tg/tg mouse testes, as compared to the WT. We Cell Death and Disease (2022) 13:665 Conditional knock-in of Foxj2 by Cre-loxP recombination. A Schematic depiction of gene targeting strategy for Foxj2 kno which “047” represents “Foxj2 DNA”. A ROSA26-EGE-STY-047 cKI targeting vector was inserted behind the Lox-stop-Lox s crossed with the germline-speciﬁc Stra8-Cre line, the loxP sites will be recognized and excised by Cre, deleting the stop s to overexpression of Foxj2. B Breeding strategy for Foxj2-cKI mice. C Genotypes of the mice: 1: Foxj2 tg/tg; 2: Stra8-cre; 3: Foxj2 e; Foxj2 tg/+; 6: Stra8-cre; Foxj2 tg/tg; 7: wild-type (WT) mice. D The expression of GFP in the testes in Stra8-cre; Foxj2 tg/tg mi . E Relative mRNA expression levels of Foxj2 in different mouse tissues between Stra8-cre; Foxj2 tg/tg and the control mice quan R. Data are presented as the mean ± SD (n = 3), normalized to Actb (β-actin) transcript levels. P < 0.05. F Western blotting a protein levels in the isolated spermatocytes between Stra8-cre; Foxj2 tg/tg and WT mice with analysis of gray values. H3 was u F.-R. Bai et al. F.-R. Bai et al. 4 2 Conditional knock-in of Foxj2 by Cre-loxP recombination. A Schematic depiction of gene targeting strategy for Foxj2 knock- ong which “047” represents “Foxj2 DNA”. A ROSA26-EGE-STY-047 cKI targeting vector was inserted behind the Lox-stop-Lox sequ en crossed with the germline-speciﬁc Stra8-Cre line, the loxP sites will be recognized and excised by Cre, deleting the stop sequ ding to overexpression of Foxj2. B Breeding strategy for Foxj2-cKI mice. C Genotypes of the mice: 1: Foxj2 tg/tg; 2: Stra8-cre; 3: Foxj2 tg/+ a8-cre; Foxj2 tg/+; 6: Stra8-cre; Foxj2 tg/tg; 7: wild-type (WT) mice. D The expression of GFP in the testes in Stra8-cre; Foxj2 tg/tg mice. / Fig. 2 Conditional knock-in of Foxj2 by Cre-loxP recombination. A Schematic depiction of gene targeting strategy for Foxj2 knock-in (KI), among which “047” represents “Foxj2 DNA”. Overexpression of Foxj2 in mouse testes leads to failure of spermatogenesis A ROSA26-EGE-STY-047 cKI targeting vector was inserted behind the Lox-stop-Lox sequence. When crossed with the germline-speciﬁc Stra8-Cre line, the loxP sites will be recognized and excised by Cre, deleting the stop sequence, leading to overexpression of Foxj2. B Breeding strategy for Foxj2-cKI mice. C Genotypes of the mice: 1: Foxj2 tg/tg; 2: Stra8-cre; 3: Foxj2 tg/+; 4, 5: Stra8-cre; Foxj2 tg/+; 6: Stra8-cre; Foxj2 tg/tg; 7: wild-type (WT) mice. D The expression of GFP in the testes in Stra8-cre; Foxj2 tg/tg mice. Scale: 100 μm. E Relative mRNA expression levels of Foxj2 in different mouse tissues between Stra8-cre; Foxj2 tg/tg and the control mice quantiﬁed by qRT-PCR. Data are presented as the mean ± SD (n = 3), normalized to Actb (β-actin) transcript levels. P < 0.05. F Western blotting analysis of FOXJ2 protein levels in the isolated spermatocytes between Stra8-cre; Foxj2 tg/tg and WT mice with analysis of gray values. H3 was used as a loading control. Data are presented as the mean ± SD (n = 3). P < 0.01. the level of microtubule-associated protein 1 light chain 3 alpha isoform II (LC3 II) using WB [21], and found that the levels of LC3 II/LC3 I did not change. To rule out the impact of LC3 II degradation after autophagosomes fuse with lysosomes in vivo, we injected chloroquine (CQ, an inhibitor of lysosomes) into the mice one day in advance [22], and did not ﬁnd any change in LC3 II levels (Fig. 6B). The above results suggested that the level of autophagy in the spermatocytes of Stra8-cre; Foxj2 tg/tg mice was increased, but there was no obstacle to the formation of autophagosomes, which is a critical process during the macroautophagy. speculated that the autophagy in the Stra8-cre; Foxj2 tg/tg mouse testes was dysregulated. Therefore, we observed the ultrastructure of the testes from 10-day-old Stra8-cre; Foxj2 tg/tg mice and their control littermates using a transmission electron microscope, and observed more autolysosomes in the spermatocytes in the Stra8- cre; Foxj2 tg/tg mice than in their control littermates (Fig. 6A), while there was no difference in the number of autolysosomes in the spermatogonia and Sertoli cells between the Stra8-cre; Foxj2 tg/tg mice and their control littermates (Supplementary Fig. S3A, B). To detect whether autophagosome formation was different between the Stra8-cre; Foxj2 tg/tg and control mice, we detected speculated that the autophagy in the Stra8-cre; Foxj2 tg/tg mouse testes was dysregulated. Cell Death and Disease (2022) 13:665 Overexpression of Foxj2 in mouse testes leads to failure of spermatogenesis Therefore, we observed the ultrastructure of the testes from 10-day-old Stra8-cre; Foxj2 tg/tg mice and their control littermates using a transmission electron microscope, and observed more autolysosomes in the spermatocytes in the Stra8- cre; Foxj2 tg/tg mice than in their control littermates (Fig. 6A), while there was no difference in the number of autolysosomes in the spermatogonia and Sertoli cells between the Stra8-cre; Foxj2 tg/tg mice and their control littermates (Supplementary Fig. S3A, B). To detect whether autophagosome formation was different between the Stra8-cre; Foxj2 tg/tg and control mice, we detected Cell Death and Disease (2022) 13:665 F.-R. Bai et al. F.-R. Bai et al. ra8-cre; Foxj2 tg/tg mice were sterile due to reduced numbers of meiotic and post-meiotic cells in the testis and almost no sperm pididymis. A Pups per litter sired by Con and Stra8-cre; Foxj2 tg/tg males. P < 0.0001. B Gross morphology of the testes from Con and Foxj2 tg/tg males. C Ratio of the testis to body weight from Con and Stra8-cre; Foxj2 tg/tg males. P < 0.0001. D Micrographs of PAS- estes sections from Con and Stra8-cre; Foxj2 tg/tg mice. The roman numbers present the stages of the seminiferous epithelia. Dashed cate the apical borders of the seminiferous epithelia. Scale bar: 10 μm. E Micrographs of H&E-stained epididymides sections from Con 8-cre; Foxj2 tg/tg mice. Scale bar: 50 μm. F Comparison of sperm concentration in the cauda epididymis between the Con and Stra8-cre; g by CASA. Data are presented as the mean ± SD (n = 3). P < 0.01. F. R. Bai et al. 5 tra8-cre; Foxj2 tg/tg mice were sterile due to reduced numbers of meiotic and post-meiotic cells in the testis and almost no sperm 5 Fig. 3 Stra8-cre; Foxj2 tg/tg mice were sterile due to reduced numbers of meiotic and post-meiotic cells in the testis and almost no sperm in the epididymis. A Pups per litter sired by Con and Stra8-cre; Foxj2 tg/tg males. **P < 0.0001. B Gross morphology of the testes from Con and Stra8-cre; Foxj2 tg/tg males. C Ratio of the testis to body weight from Con and Stra8-cre; Foxj2 tg/tg males. P < 0.0001. D Micrographs of PAS- stained testes sections from Con and Stra8-cre; Foxj2 tg/tg mice. The roman numbers present the stages of the seminiferous epithelia. Dashed lines indicate the apical borders of the seminiferous epithelia. Scale bar: 10 μm. Overexpression of Foxj2 in mouse testes leads to failure of spermatogenesis E Micrographs of H&E-stained epididymides sections from Con and Stra8-cre; Foxj2 tg/tg mice. Scale bar: 50 μm. F Comparison of sperm concentration in the cauda epididymis between the Con and Stra8-cre; Foxj2 tg/tg by CASA. Data are presented as the mean ± SD (n = 3). P < 0.01. We next sought to explore the potential target genes regulated by FOXJ2 in the testis. As shown above, there were more autolysosomes in the spermatocytes in the Stra8-cre; Foxj2 tg/tg mice (Fig. 6A). The validation of gene expression changes for autophagy-related DEGs from the RNA-seq data showed that the expression of Lamp2 mRNA was increased signiﬁcantly in the Stra8-cre; Foxj2 tg/tg mouse testes (Fig. 5E). In addition, Lamp2 was predicted to be the target gene of FOXJ2 by bioinformatic analyses (Fig. 5F). Taken together, these data suggested a mechanistic link between FOXJ2 and Lamp2 in spermatocyte autophagy, which warranted further investigation. First, we observed the location of LAMP2 in the testes using Cell Death and Disease (2022) 13:665 F.-R. Bai et al. mmunohistochemical and immunoﬂuorescent staining and found hat LAMP2 was localized to spermatocytes and Sertoli cells (Fig. 7A, B and Supplementary Fig. S4A). Whether LAMP2 and FOXJ2 were co-located in spermatocytes was further detected using the solated spermatocytes (Fig. 7C). The results demonstrated that To further conﬁrm whether FOXJ2 affected spermatogenesis targeting Lamp2, we examined the binding of FOXJ2 to t promoter of Lamp2 in vivo using chromatin immunoprecipitatio PCR (ChIP-PCR). Considering that there is no ChIP-level anti-FOX antibody on the market, and the Foxj2 overexpression vect ig. 4 Morphology of the developing testes revealed histological differences beginning from postnatal day 10. A, B, E, G Micrographs H&E-stained testicular sections from Con and Stra8-cre; Foxj2 tg/tg mice at postnatal day 7 (7 d) (A), 10 d (B), 14 d (E), and 21 d (G). L-leptote permatocytes; P-pachytene spermatocytes; Rs-round spermatids; Scale bar: 50 μm. C Flow cytometry analysis of testicular cell suspensio rom 10-day-old (10 d) Con mice. Red-2C DNA content (65.49%), Blue-4C DNA content (26.83%). D Flow cytometry analysis of testicular c uspensions from 10-day-old (10 d) Stra8-cre; Foxj2 tg/tg mice. Red-2C DNA content (69.44%), Blue-4C DNA content (12.41%). F The percenta of tubules containing pachytene spermatocytes in the seminiferous tubules from testicular sections between 14-day-old Con and Stra8-c oxj2 tg/tg mice. Data are presented as the mean ± SD (n = 3). **P < 0.001. Overexpression of Foxj2 in mouse testes leads to failure of spermatogenesis H The percentage of tubules containing round spermatids in t eminiferous tubules from testicular sections between 21-day-old Con and Stra8-cre; Foxj2 tg/tg mice. Data are presented as the mean ± n = 3). P < 0.05. F.-R. Bai et al. 6 Fig. 4 Morphology of the developing testes revealed histological differences beginning from postnatal day 10. A, B, E, G Micrographs of H&E-stained testicular sections from Con and Stra8-cre; Foxj2 tg/tg mice at postnatal day 7 (7 d) (A), 10 d (B), 14 d (E), and 21 d (G). L-leptotene spermatocytes; P-pachytene spermatocytes; Rs-round spermatids; Scale bar: 50 μm. C Flow cytometry analysis of testicular cell suspensions from 10-day-old (10 d) Con mice. Red-2C DNA content (65.49%), Blue-4C DNA content (26.83%). D Flow cytometry analysis of testicular cell suspensions from 10-day-old (10 d) Stra8-cre; Foxj2 tg/tg mice. Red-2C DNA content (69.44%), Blue-4C DNA content (12.41%). F The percentage of tubules containing pachytene spermatocytes in the seminiferous tubules from testicular sections between 14-day-old Con and Stra8-cre; Foxj2 tg/tg mice. Data are presented as the mean ± SD (n = 3). **P < 0.001. H The percentage of tubules containing round spermatids in the seminiferous tubules from testicular sections between 21-day-old Con and Stra8-cre; Foxj2 tg/tg mice. Data are presented as the mean ± SD (n = 3). P < 0.05. To further conﬁrm whether FOXJ2 affected spermatogenesis by targeting Lamp2, we examined the binding of FOXJ2 to the promoter of Lamp2 in vivo using chromatin immunoprecipitation- PCR (ChIP-PCR). Considering that there is no ChIP-level anti-FOXJ2 antibody on the market, and the Foxj2 overexpression vector carried an HA-tag (Fig. 2A), we used a ChIP-level anti-HA-tag immunohistochemical and immunoﬂuorescent staining and found that LAMP2 was localized to spermatocytes and Sertoli cells (Fig. 7A, B and Supplementary Fig. S4A). Whether LAMP2 and FOXJ2 were co-located in spermatocytes was further detected using the isolated spermatocytes (Fig. 7C). The results demonstrated that both LAMP2 and FOXJ2 were located in spermatocytes. Cell Death and Disease (2022) 13:665 F.-R. Bai et al. Fig. 5 Analysis of the transcriptome alteration in the testes of Stra8-cre; Foxj2 tg/tg mice. A Volcano diagram of differentially expressed genes. Red: 3430 upregulated genes; Green: 3622 downregulated genes; Blue: 23292 genes with no signiﬁcant differences in expression. B–D Functional enrichment analysis of DEGs, including GO category biological process (B), cellular component (C), and KEGG pathway (D). Red arrows point to genes with signiﬁcant differences. E Validation of DEGs related to the autophagy pathway by qRT-PCR. Data are presented as the mean ± SD (n = 3). P < 0.05; P < 0.01. F Venn diagram of DEGs (purple) and the predicted target genes of FOXJ2 (yellow). F. R. Bai et al. 7 7 Fig. 5 Analysis of the transcriptome alteration in the testes of Stra8-cre; Foxj2 tg/tg mice. A Volcano diagram of differentially expressed genes. Red: 3430 upregulated genes; Green: 3622 downregulated genes; Blue: 23292 genes with no signiﬁcant differences in expression. B–D Functional enrichment analysis of DEGs, including GO category biological process (B), cellular component (C), and KEGG pathway (D). Red arrows point to genes with signiﬁcant differences. E Validation of DEGs related to the autophagy pathway by qRT-PCR. Data are presented as the mean ± SD (n = 3). P < 0.05; *P < 0.01. F Venn diagram of DEGs (purple) and the predicted target genes of FOXJ2 (yellow). antibody to conduct ChIP-PCR. The RNA-seq results were based on the testicular cells from 10-day-old Stra8-cre; Foxj2 tg/tg and WT mice; therefore, we chose to use the testicular cell suspension from 10-day-old Stra8-cre; Foxj2 tg/tg mice as the experimental sample for ChIP-PCR. The results showed that in the testicular cells of the 10-day-old Stra8-cre; Foxj2 tg/tg mice, the fold enrichment of FOXJ2 binding to its binding site in the Lamp2 promoter region ampliﬁed by the Lamp2-3077 primers (later termed the Lamp2- 3077 site) was signiﬁcantly higher than that of the negative control (Fig. 7D), which suggested that FOXJ2 can bind to the Lamp2-3077 site. Therefore, we choose the Lamp2-3077 site for further veriﬁcation using a dual-luciferase reporter assay in vitro. spermatogenesis? According to the literature, there are three different isoforms of LAMP2 arising from alternative mRNA splicing, known as LAMP2A, LAMP2B, and LAMP2C, which function in different types of autophagy, namely CMA, macroautophagy, and RNautophagy/DNautophagy, respectively [23, 24]. Cell Death and Disease (2022) 13:665 We then tested the expression of the isoforms of Lamp2 in the testis and found that the mRNA expression level of Lamp2a in the testes of Stra8-cre; Foxj2 tg/tg mice was signiﬁcantly higher than that of the WT, while there were no signiﬁcant differences in the mRNA expression levels of Lamp2b or Lamp2c between the Stra8-cre; Foxj2 tg/tg and WT mice (Fig. 8A). WB veriﬁed the increased level of LAMP2A protein in the testes of Stra8-cre; Foxj2 tg/tg mice (Fig. 8B). At the same time, the levels of the 70-kDa cytoplasmic heat shock protein (HSC70), the cytosolic chaperone required by CMA to form a complex with the substrate protein that recognized by LAMP2A to be delivered to the lysosome for degradation [25], also increased in the testes of the Stra8-cre; Foxj2 tg/tg mice (Fig. 8C). CMA is a selective process that targets and degrades proteins containing a pentapeptide motif (KFERQ-like motif) [25]. To clarify whether CMA involves in the failure of spermatogenesis in the Stra8-cre; Foxj2 tg/tg mice, we performed an in silico screen for KFERQ-like motifs based on our RNA-seq results using the KFERQ ﬁnder [26]. We found that the proportion of proteins containing KFERQ-like motifs encoded by the downregulated genes (98.77%) was higher than the proportion of proteins encoded by the upregulated genes (80.97%) or by whole genome genes (88.02%), implying that more proteins encoded by the downregulated spermatogenesis? According to the literature, there are three different isoforms of LAMP2 arising from alternative mRNA splicing, known as LAMP2A, LAMP2B, and LAMP2C, which function in different types of autophagy, namely CMA, macroautophagy, and RNautophagy/DNautophagy, respectively [23, 24]. We then tested the expression of the isoforms of Lamp2 in the testis and found that the mRNA expression level of Lamp2a in the testes of Stra8-cre; Foxj2 tg/tg mice was signiﬁcantly higher than that of the WT, while there were no signiﬁcant differences in the mRNA expression levels of Lamp2b or Lamp2c between the Stra8-cre; Foxj2 tg/tg and WT mice (Fig. 8A). WB veriﬁed the increased level of LAMP2A protein in the testes of Stra8-cre; Foxj2 tg/tg mice (Fig. 8B). At the same time, the levels of the 70-kDa cytoplasmic heat shock protein (HSC70), the cytosolic chaperone required by CMA to form a complex with the substrate protein that recognized by LAMP2A to be delivered to the lysosome for degradation [25], also increased in the testes of the Stra8-cre; Foxj2 tg/tg mice (Fig. 8C). CMA is a selective process that targets and degrades proteins containing a pentapeptide motif (KFERQ-like motif) [25]. To clarify whether CMA involves in the failure of spermatogenesis in the Stra8-cre; Foxj2 tg/tg mice, we performed an in silico screen for KFERQ-like motifs based on our RNA-seq results using the KFERQ ﬁnder [26]. We found that the proportion of proteins containing KFERQ-like motifs encoded by the downregulated genes (98.77%) was higher than the proportion of proteins encoded by the upregulated genes (80.97%) or by whole genome genes (88.02%), implying that more proteins encoded by the downregulated antibody to conduct ChIP-PCR. The RNA-seq results were based on the testicular cells from 10-day-old Stra8-cre; Foxj2 tg/tg and WT mice; therefore, we chose to use the testicular cell suspension from 10-day-old Stra8-cre; Foxj2 tg/tg mice as the experimental sample for ChIP-PCR. The results showed that in the testicular cells of the 10-day-old Stra8-cre; Foxj2 tg/tg mice, the fold enrichment of FOXJ2 binding to its binding site in the Lamp2 promoter region ampliﬁed by the Lamp2-3077 primers (later termed the Lamp2- 3077 site) was signiﬁcantly higher than that of the negative control (Fig. 7D), which suggested that FOXJ2 can bind to the Lamp2-3077 site. Therefore, we choose the Lamp2-3077 site for further veriﬁcation using a dual-luciferase reporter assay in vitro. HeLa cells endogenously express FOXJ2 (Supplementary Fig. S4B); therefore, there was no need to add a FOXJ2 expression plasmid when performing the dual-luciferase reporter assay. After transfecting the pGL4-Lamp2 plasmid containing the Lamp2-3077 binding site into HeLa cells for 24 h, the luciferase activity was signiﬁcantly higher than that of the control group (pGL4-basic). When the Lamp2-3077-binding site was mutated, the luciferase activity was reduced signiﬁcantly (Fig. 7E). These results indicated that FOXJ2 directly bound to the Lamp2-3077 site in the promoter region of the Lamp2 gene to upregulate its expression antibody to conduct ChIP-PCR. The RNA-seq results were based on the testicular cells from 10-day-old Stra8-cre; Foxj2 tg/tg and WT mice; therefore, we chose to use the testicular cell suspension from 10-day-old Stra8-cre; Foxj2 tg/tg mice as the experimental sample for ChIP-PCR. The results showed that in the testicular cells of the 10-day-old Stra8-cre; Foxj2 tg/tg mice, the fold enrichment of FOXJ2 binding to its binding site in the Lamp2 promoter region ampliﬁed by the Lamp2-3077 primers (later termed the Lamp2- 3077 site) was signiﬁcantly higher than that of the negative control (Fig. 7D), which suggested that FOXJ2 can bind to the Lamp2-3077 site. Therefore, we choose the Lamp2-3077 site for further veriﬁcation using a dual-luciferase reporter assay in vitro. HeLa cells endogenously express FOXJ2 (Supplementary Fig. S4B); therefore, there was no need to add a FOXJ2 expression plasmid when performing the dual-luciferase reporter assay. After transfecting the pGL4-Lamp2 plasmid containing the Lamp2-3077 binding site into HeLa cells for 24 h, the luciferase activity was signiﬁcantly higher than that of the control group (pGL4-basic). When the Lamp2-3077-binding site was mutated, the luciferase activity was reduced signiﬁcantly (Fig. 7E). These results indicated that FOXJ2 directly bound to the Lamp2-3077 site in the promoter region of the Lamp2 gene to upregulate its expression. HeLa cells endogenously express FOXJ2 (Supplementary Fig. S4B); therefore, there was no need to add a FOXJ2 expression plasmid when performing the dual-luciferase reporter assay. After transfecting the pGL4-Lamp2 plasmid containing the Lamp2-3077 binding site into HeLa cells for 24 h, the luciferase activity was signiﬁcantly higher than that of the control group (pGL4-basic). When the Lamp2-3077-binding site was mutated, the luciferase activity was reduced signiﬁcantly (Fig. 7E). These results indicated that FOXJ2 directly bound to the Lamp2-3077 site in the promoter region of the Lamp2 gene to upregulate its expression. As mentioned above, the number of autolysosomes in the spermatocytes of Stra8-cre; Foxj2 tg/tg mice was increased, but there was no obstacle to the formation of autophagosomes. We then asked the question: what is the effect of overexpression of Foxj2 on the autophagy process at the initiation of meiosis in Cell Death and Disease (2022) 13:665 F.-R. Bai et al. 8 Fig. 6 Autolysosomes increased in the spermatocytes in 10-day-old Stra8-cre; Foxj2 tg/tg mouse testes. A Transmission electron microscopy images of spermatocytes from 10-day-old Stra8-cre; Foxj2 tg/tg and control mice. White arrows indicate autolysosomes. Scale bar: 2 μm (left), 500 nm (middle and right). B Western blotting analysis of LC3 II/I protein levels with or without CQ (chloroquine) treatment in wild-type (WT) and Stra8-cre; Foxj2 tg/tg mouse testes followed by gray values analysis. β-Actin was used as a loading control. Data are presented as the mean ± SD (n = 3). Fig. 6 Autolysosomes increased in the spermatocytes in 10-day-old Stra8-cre; Foxj2 tg/tg mouse testes. A Transmission electron microscopy images of spermatocytes from 10-day-old Stra8-cre; Foxj2 tg/tg and control mice. White arrows indicate autolysosomes. Scale bar: 2 μm (left), 500 nm (middle and right). B Western blotting analysis of LC3 II/I protein levels with or without CQ (chloroquine) treatment in wild-type (WT) and Stra8-cre; Foxj2 tg/tg mouse testes followed by gray values analysis. β-Actin was used as a loading control. Data are presented as the mean ± SD (n = 3). cytoplasmic components to maintain cellular homeostasis [27]. Three main types of autophagy have been identiﬁed according to the different ways by which the cytoplasmic components are delivered to lysosomes, namely macroautophagy, microauto- phagy, and CMA [28]. Macroautophagy involves the formation of the double membrane vesicles, called autophagosomes, which subsequently fuse with lysosomes, forming autolysosomes. It comprises four sequential stages, known as initiation, nucleation, maturation, and degradation [29]. Microautophagy is a non- selective degradation process that directly swallows intracellular components into lysosomes [27]. In CMA, the protein substrate containing the KFERQ-like pentapeptide sequence is recognized by a chaperone protein, HSC70, to form a complex, which binds to LAMP2A on the lysosome membrane and is then transferred to the lysosome [17, 25]. Interestingly, we found that Lamp2, a target of FOXJ2, which was veriﬁed by ChIP-PCR and Dual-luciferase reporter assays, was signiﬁcantly upregulated in Stra8-cre; Foxj2 tg/ tg mouse testes. genes were prone to be degraded by CMA in the Stra8-cre; Foxj2 tg/tg mice (Fig. 8D). In addition, we performed a GO enrichment analysis in terms of the downregulated genes that encoded the proteins containing the KFERQ-like motifs. Notably, it revealed that these genes were mainly involved in several biological processes, including mitosis, meiosis, cell cycle, DNA repair/recombination, and spermatogenesis (Fig. 8E), furtherly supporting that CMA involved in the failure of spermatogenesis through degradation of the substrate proteins in the Stra8-cre; Foxj2 tg/tg mice. The above results indicated that the increase in the number of autolysosomes in the spermatocytes of the Stra8-cre; Foxj2 tg/tg mice might be caused by the effects of the abnormally increased expression of Lamp2a on the CMA pathway. DISCUSSION I hi d In this study, we showed that overexpression of Foxj2 in the male germline led to male infertility as a result of the reduced meiotic and post-meiotic cells in the adult Stra8-cre; Foxj2 tg/tg mouse testes and the abnormality began at postnatal day 10, indicating a failure of spermatogenesis, which started at the initiation of meiosis. The transcriptome alterations of the testicular cells between 10-day-old Stra8-cre; Foxj2 tg/tg and WT mice showed that genes related to lysosomes and autophagy were signiﬁcantly upregulated in Stra8- cre; Foxj2 tg/tg mouse testes. At the same time, an increased number of autolysosomes in the spermatocytes of Stra8-cre; Foxj2 tg/tg mice was observed, indicating aberrant autophagy activation in the spermatocytes of the Stra8-cre; Foxj2 tg/tg mice. LAMP2 is a major lysosomal membrane protein, which is an important regulator of the maturation of autophagosomes and phagosomes [19, 30]. There are three different isoforms of LAMP2 arising by alternative mRNA splicing, known as LAMP2A, LAMP2B, and LAMP2C, which have the same luminal domain, but different transmembrane regions and cytoplasmic tails [24]. LAMP2A is highly expressed in tissues such as the placenta, lung, liver, kidney, and pancreas, and is considered to be a receptor on the lysosomal membrane in the CMA process [31]. LAMP2B is more abundantly expressed in the heart, skeletal muscle, and brain [32]. LAMP2B might be related to macroautophagy and affect the maturation of autophagosomes [33]. LAMP2C is mainly expressed in the brain, Autophagy is a conserved, lysosome-dependent catabolic process with the primary function of degrading and recycling Cell Death and Disease (2022) 13:665 F.-R. Bai et al. 9 9 9 g. 7 LAMP2 co-localized with FOXJ2 in spermatocytes and was a target of FOXJ2. A Expression and localization of LAMP2 in testis using mmunohistochemical staining (IHC). Scale bar: 50 μm. B Localization of LAMP2 and SCP3 (showing spermatocytes) on testis sections using mmunoﬂuorescent staining. Scale bar: 50 μm. White arrows indicate spermatocytes (Spc). C Localization of LAMP2 and FOXJ2 in isolated permatocytes using immunoﬂuorescent staining (IF). Scale bar: 50 μm. D The binding sites of FOXJ2 to Lamp2 promoter region in the esticular cells of the 10-day-old Stra8-cre; Foxj2 tg/tg mice analyzed by ChIP-PCR using anti-HA-tag (ChIP level). Data are presented as the mean ± SD (n = 3). P < 0.05. E Veriﬁcation of FOXJ2 binding to the Lamp2 promoter using a Dual-luciferase reporter assay. DISCUSSION I hi d A Relative mRNA expression levels of Lamp2a, Lamp2b, Lamp2c in 10-day-old wild-type (WT) and Stra8-cre; Foxj2 tg/tg mouse testes quantiﬁed by qRT-PCR. Data are presented as the mean ± SD (n = 3). P < 0.05. B, C Western blotting analysis of LAMP2A (B) and HSC70 (C) protein levels in 10-day-old WT and Stra8-cre; Foxj2 tg/tg mice testes with analysis of gray values. β-Actin was used as a loading control. Data are presented as the mean ± SD (n = 3) P < 0.05; *P < 0.01. D The proportion of the proteins containing KFERQ-like motifs encoded by the whole genome genes, upregulated genes, and downregulated genes based on our RNA-seq data. E GO analysis of the downregulated genes that encode the proteins containing KFERQ-like motifs. Fig. 8 CMA pathway involved in the failure of spermatogenesis in the Stra8-cre; Foxj2 tg/tg mouse testes. A Relative mRNA expression levels of Lamp2a, Lamp2b, Lamp2c in 10-day-old wild-type (WT) and Stra8-cre; Foxj2 tg/tg mouse testes quantiﬁed by qRT-PCR. Data are presented as the mean ± SD (n = 3). P < 0.05. B, C Western blotting analysis of LAMP2A (B) and HSC70 (C) protein levels in 10-day-old WT and Stra8-cre; Foxj2 tg/tg mice testes with analysis of gray values. β-Actin was used as a loading control. Data are presented as the mean ± SD (n = 3). P < 0.05; P < 0.01. D The proportion of the proteins containing KFERQ-like motifs encoded by the whole genome genes, upregulated genes, and downregulated genes based on our RNA-seq data. E GO analysis of the downregulated genes that encode the proteins containing KFERQ-like motifs. Fig. 8 CMA pathway involved in the failure of spermatogenesis in the Stra8-cre; Foxj2 tg/tg mouse testes. A Relative mRNA expression levels of Lamp2a, Lamp2b, Lamp2c in 10-day-old wild-type (WT) and Stra8-cre; Foxj2 tg/tg mouse testes quantiﬁed by qRT-PCR. Data are presented as the mean ± SD (n = 3). P < 0.05. B, C Western blotting analysis of LAMP2A (B) and HSC70 (C) protein levels in 10-day-old WT and Stra8-cre; Foxj2 tg/tg mice testes with analysis of gray values. β-Actin was used as a loading control. Data are presented as the mean ± SD (n = 3). P < 0.05; P < 0.01. D The proportion of the proteins containing KFERQ-like motifs encoded by the whole genome genes, upregulated genes, and downregulated genes based on our RNA-seq data. Cell Death and Disease (2022) 13:665 DISCUSSION I hi d E GO analysis of the downregulated genes that encode the proteins containing KFERQ-like motifs. upregulate the expression of Lamp2a, causing aberrant CMA activation, which leads to the increased number of autolysosomes in the spermatocytes in Stra8-cre; Foxj2 tg/tg mice. The mechanisms underlying the regulation of CMA in spermatogenesis, especially during the transition from mitosis to meiosis, are currently unclear. One possibility is that CMA suppression should be controlled at the initiation of meiosis during spermatogenesis, which warrants further investigation. eyes, heart, liver, kidney, and skeletal muscle. LAMP2C is a receptor for selective RNA and DNA degradation autophagy, namely RNautophagy and DNautophagy, respectively [34, 35]. Our results showed that the expression levels of LAMP2A and HSC70 were increased in the Stra8-cre; Foxj2 tg/tg mouse testes. In addition, the bioinformatics analysis demonstrated that more proteins encoded by the downregulated genes contained the KFERQ-like motifs in the Stra8-cre; Foxj2 tg/tg mice. These proteins containing KFERQ-like motifs involved in mitosis, meiosis, DNA repair/recombination, and spermatogenesis, implying that activa- tion of CMA abnormally degraded the substrate proteins necessary for spermatogenesis in the Stra8-cre; Foxj2 tg/tg mice. The above results suggested that overexpression of Foxj2 can Increasing evidence shows that autophagy involved in sperma- togenesis [36–39]. It was reported that germ cells lacking Stra8 (encoding stimulated by retinoic acid 8) failed to enter meiosis, and showed autophagy activation. This revealed the connection between STRA8-mediated autophagy suppression and the Cell Death and Disease (2022) 13:665 DISCUSSION I hi d Data are presented s the mean ± SD (n = 3). P < 0.001; *P < 0.0001. Fig. 7 LAMP2 co-localized with FOXJ2 in spermatocytes and was a target of FOXJ2. A Expression and localization of LAMP2 in testis using immunohistochemical staining (IHC). Scale bar: 50 μm. B Localization of LAMP2 and SCP3 (showing spermatocytes) on testis sections using immunoﬂuorescent staining. Scale bar: 50 μm. White arrows indicate spermatocytes (Spc). C Localization of LAMP2 and FOXJ2 in isolated spermatocytes using immunoﬂuorescent staining (IF). Scale bar: 50 μm. D The binding sites of FOXJ2 to Lamp2 promoter region in the testicular cells of the 10-day-old Stra8-cre; Foxj2 tg/tg mice analyzed by ChIP-PCR using anti-HA-tag (ChIP level). Data are presented as the mean ± SD (n = 3). P < 0.05. E Veriﬁcation of FOXJ2 binding to the Lamp2 promoter using a Dual-luciferase reporter assay. Data are presented as the mean ± SD (n = 3). *P < 0.001; *P < 0.0001. Cell Death and Disease (2022) 13:665 F.-R. Bai et al. eyes, heart, liver, kidney, and skeletal muscle. LAMP2C is a receptor for selective RNA and DNA degradation autophagy, l RN t h d DN t h ti l [34 35] O upregulate the expression of Lamp2a, causing aberrant CMA activation, which leads to the increased number of autolysosomes i th t t i St 8 F j2 tg/tg i Th h i Fig. 8 CMA pathway involved in the failure of spermatogenesis in the Stra8-cre; Foxj2 tg/tg mouse testes. A Relative mRNA expression levels of Lamp2a, Lamp2b, Lamp2c in 10-day-old wild-type (WT) and Stra8-cre; Foxj2 tg/tg mouse testes quantiﬁed by qRT-PCR. Data are presented as the mean ± SD (n = 3). P < 0.05. B, C Western blotting analysis of LAMP2A (B) and HSC70 (C) protein levels in 10-day-old WT and Stra8-cre; Foxj2 tg/tg mice testes with analysis of gray values. β-Actin was used as a loading control. Data are presented as the mean ± SD (n = 3) P < 0.05; *P < 0.01. D The proportion of the proteins containing KFERQ-like motifs encoded by the whole genome genes, upregulated genes, and downregulated genes based on our RNA-seq data. E GO analysis of the downregulated genes that encode the proteins containing KFERQ-like motifs. 10 Fig. 8 CMA pathway involved in the failure of spermatogenesis in the Stra8-cre; Foxj2 tg/tg mouse testes. F.-R. Bai et al. 11 initiation of meiosis [40]. Moreover, the level of autophagy increased in high-fat diet mice with disrupted spermatogenesis and male fertility, and autophagy was also overactivated in sperm samples from obese subfertile male patients [41, 42]. Recent studies have found that LAMP2 was highly expressed in human spermatogonia, and some autophagy-related genes were dysre- gulated in the testicular germ cells of patients with non- obstructive azoospermia (NOA), suggesting that autophagy is related to male infertility [43]. were digested into cell suspension. After centrifugation, the cells were resuspended in 25 ml 0.5% BSA solution and ﬁltered through a 40-µm ﬁlter to obtain a single-cell suspension. Then, the cell suspension was loaded into the cell chamber, with 550 ml of 2% BSA and 550 ml of 4% BSA solution in the two cylinders, respectively. The stopcocks were opened to allow the 4% BSA, 2% BSA, and 0.5% BSA containing the cells to ﬂow slowly into the sedimentation chamber. About 40 min after the solutions were loaded into the sedimentation chamber, the valve was turned off, followed by 3 h of sedimentation. Next, the cells in the sedimentation chamber were collected and examined under a microscope. Fractions containing cells with similar sizes and morphologies were combined for subsequent examination. were digested into cell suspension. After centrifugation, the cells were resuspended in 25 ml 0.5% BSA solution and ﬁltered through a 40-µm ﬁlter to obtain a single-cell suspension. Then, the cell suspension was loaded into the cell chamber, with 550 ml of 2% BSA and 550 ml of 4% BSA solution in the two cylinders, respectively. The stopcocks were opened to allow the 4% BSA, 2% BSA, and 0.5% BSA containing the cells to ﬂow slowly into the sedimentation chamber. About 40 min after the solutions were loaded into the sedimentation chamber, the valve was turned off, followed by 3 h of sedimentation. Next, the cells in the sedimentation chamber were collected and examined under a microscope. Fractions containing cells with similar sizes and morphologies were combined for subsequent examination. In summary, our data showed that overexpression of Foxj2 in the germ cells of mouse testis might affect CMA by upregulating Lamp2a, leading to a failure of spermatogenesis, starting at the initiation of meiosis, and resulting in male infertility. Animals Stra8-cre mice were purchased from the Nanjing Biomedical Research Institute of Nanjing University. Foxj2 knock-in mice (Foxj2 tg/tg) were generated by crossing Foxj2 tg/+ mice, which were prepared by Beijing Biocytogen Co., Ltd. (Beijing, China). All lines were maintained in the C57BL/6J background. Genotypes of the mice were identiﬁed by PCR using DNA extracted from mice tails. The primers used to detect Stra8-Cre and Foxj2 knock-in in this assay are listed in Table S1. All control (Con) mice in this study were littermates of the analyzed Foxj2-cKI mice. All animal experiments were performed with the approval of the Institutional Animal Care and Use Committee of the Shanghai Jiao Tong University School of Medicine. RNA extraction and qRT-PCR Total RNAs were extracted using an RNAsimple Total RNA Kit (TIANGEN, Beijing, China) according to the manufacturer’s instructions. For reverse transcription, cDNA was prepared from 1 μg of RNA using PrimeScript RT Master Mix (Takara, Dalian, China). The quantitative real-time PCR reaction was prepared using the TB Green Premix Ex Taq II (Takara) in accordance with the manufacturer’s protocol and performed using an Applied Biosystems 7500 instrument (ABI, Foster City, CA, USA). Relative quantiﬁcation of the mRNA levels was calculated using the threshold cycle (CT) method 2−ΔΔCt with Actb (encoding β-actin) as the endogenous control [44]. The primers sequences used in this study are listed in Supplementary Table S2, and were synthesized by Sangon Biotech (Shanghai, China). Histology, immunohistochemistry, and immunoﬂuorescence staining staining For hematoxylin and eosin (H&E) staining, freshly dissected testes and epididymides were ﬁxed in Bouin’s solution overnight at room tempera- ture. These tissues were embedded in parafﬁn after dehydration and cut into 5-μm sections, followed by H&E staining after deparafﬁnization and rehydration. Periodic Acid-Schiff (PAS) staining was performed according to the manufacturer’s instructions (Beyotime, Shanghai, China). For immunohistochemistry staining, the testes were ﬁxed in 4% paraformal- dehyde and parafﬁn-embedded. Then, 5-μm sections were cut and rehydrated, followed by antigen retrieval in 10 mM citrate buffer (pH 6.0) for 15 min. The sections were blocked in 5% bovine serum albumin (BSA) for 1 h at room temperature, after being treated with 3% H2O2, and incubated overnight at 4 °C with anti-FOXJ2 antibodies (1:200, ab22857, Abcam, Cambridge, MA, USA), or anti-Lamp2 antibodies (1:200, ab13524, Abcam). On the following day, the sections were incubated with goat anti- rabbit/rat IgG antibody for 1 h at room temperature, followed by diaminobenzidine and hematoxylin counterstaining. Images were observed under a microscope (Nikon, Tokyo, Japan). For immunoﬂuores- cence staining, 4% paraformaldehyde-ﬁxed samples were embedded in optimal cutting temperature compound (OCT) and then cut in 8-μm cryo- sections. After blocking in 5% BSA for 1 h at room temperature, the sections were incubated with primary antibodies recognizing FOXJ2 (1:200, ab22857, Abcam), SCP3 (Synaptonemal complex protein 3) (1:200, ab97672, Abcam), WT1 (Wilms Tumor 1) (1:200, ab89901, Abcam) or Lamp2 (1:200, ab13524, Abcam) at 4 °C overnight, followed 1 h of incubation at room temperature with Alexa ﬂuor 488/594-labeled secondary antibody or PNA (Lectin from Arachis hypogaea/Peanut lectin) (1:400, L7381, Sigma). After counterstaining with 4’, 6-diamidino-2- phenylindole (DAPI), these tissues were observed under a ﬂuorescence microscope (Leica, Germany). Fertility evaluation Each adult Stra8-cre; Foxj2 tg/tg male or their control male littermate was mated with two female mice with normal fertility according to the ratio of one male to two fertility-proven adult females for at least 1 year. The numbers of pups per litter and the date of delivery were recorded. Protein preparation and western blotting analysis Protein preparation and western blotting analysis Samples were homogenized in radioimmunoprecipitation assay (RIPA) lysis buffer (Thermo Fisher Scientiﬁc, Waltham, MA, USA) containing protease inhibitor cocktail (Roche Applied Science, Basel, Switzerland) on ice for around 30 min for total protein extraction. The nucleoprotein was separated according to the manufacturer’s instructions, using a Nuclear and Cytoplasmic Protein Extraction Kit (Sangon Biotech, China). The proteins were collected in the supernatant after centrifugation at 14,000 × g for 10 min at 4 °C, and the protein concentrations were determined using a bicinchoninic acid (BCA) Protein Assay Kit (Thermo Fisher Scientiﬁc). The protein samples were separated using 10% sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE), and then transferred to polyvinylidene diﬂuoride membranes (Millipore, Billerica, MA, USA). The membranes were blocked in 5% BSA for 1 h at room temperature, followed by incubation in primary antibodies recognizing FOXJ2 (1:500, ab22857, Abcam), LC3 (1:1000, Cell Signaling Technology, Danvers, MA, USA), LAMP2A (1:1000, ab125068, Abcam), H3 (Histon H3) (1:1000, ab1791, Abcam) and β-actin (1:1000, ab8227, Abcam), respectively, overnight at 4 °C. On the second day, the membranes were incubated with secondary antibodies conjugated to horseradish peroxidase (HRP) (1:5000, Cell Signaling Technology) for 1 h at room temperature. The signals were visualized via enhanced chemiluminescence (Millipore) and detected by a luminescent image analyzer (ImageQuant LAS 4000 mini, Chicago, IL, USA). The results were quantiﬁed using ImageJ (version 1.46r; National Institutes of Health, Bethesda, MD, USA) and normalized to the level of H3 or β-actin. Computer-assisted sperm analysis (CASA) p p y For each sample, the cauda epididymis was harvested from the adult mouse, and incubated in Human Tubel Fluid (HTF) (Millipore) at 37 °C for 15 min to release the sperm. The supernatant was collected for the evaluation of sperm counts using the CASA system (Hamilton Thorne, Beverly, MA, USA). Our ﬁndings provide a new insight into the function of FOXJ2 in spermatogen- esis and the signiﬁcance of autophagy regulation in spermatogenesis. Dual-luciferase reporter assay 16. Wong PM, Puente C, Ganley IG, Jiang X. The ULK1 complex: sensing nutrient signals for autophagy activation. Autophagy. 2013;9:124–37. y For FOXJ2 target gene validation, the pGL4-Lamp2 plasmid was constructed for the Lamp2-3077 site “CTGTTTA” to which FOXJ2 binds, as shown in the ChIP-PCR results (Fig. 7E). The pGL4-Lamp2-Mutant plasmid containing the mutated Lamp2-3077 binding site “GCCCACC” was generated using a QuickChange Lightning Site-Directed Mutagenesis Kit (Agilent Technologies, Santa Clara, CA, USA). HeLa cells were cultured in 12-well plates and were co-transfected with pGL4-Lamp2 or pGL4-Lamp2- Mutant plasmids using Lipofectamine 3000 reagent (Invitrogen). Renilla luciferase was transfected for normalization of the transfection efﬁciency. After 24 h of transfection, the Dual-Luciferase Reporter Assay System (Promega, Madison, WI, USA) was used to measure the activities of ﬁreﬂy luciferase and Renilla luciferase using the cell lysates, according to the manufacturer’s protocol. The activity of ﬁreﬂy luciferase was normalized to that of Renilla luciferase. 17. Mizushima N, Komatsu M. Autophagy: renovation of cells and tissues. Cell. 2011;147:728–41. 18. Qin Y, Li T, Zhao H, Mao Z, Ding C, Kang Y. Integrated transcriptomic and epi- genetic study of PCOS: impact of Map3k1 and Map1lc3a promoter methylation on autophagy. Front Genet. 2021;12:620241. 19. Saftig P, Beertsen W, Eskelinen EL. LAMP-2: a control step for phagosome and autophagosome maturation. Autophagy. 2008;4:510–2. 20. Tan G, Lenhard B. TFBSTools: an R/bioconductor package for transcription factor binding site analysis. Bioinformatics. 2016;32:1555–6. binding site analysis. Bioinformatics. 2016;32:1555–6. 21. Runwal G, Stamatakou E, Siddiqi FH, Puri C, Zhu Y, Rubinsztein DC. LC3-positive structures are prominent in autophagy-deﬁcient cells. Sci Rep. 2019;9:10147. 22. Mizushima N, Yoshimori T, Levine B. Methods in mammalian autophagy research. Cell. 2010;140:313–26. 23. Pérez L, Sinn AL, Sandusky GE, Pollok KE, Blum JS. Melanoma LAMP-2C modulates tumor growth and autophagy. Front Cell Dev Biol. 2018;6:101. ChIP-PCR h ChIP was performed using a ChIP Assay kit (Millipore) according to the manufacturer’s instructions. In brief, after preparation of single-cell suspensions of testes using DMEM containing collagenase IV, hyaluroni- dase, and DNase I, the cells were cross-linked in 1% formaldehyde for 10 min at room temperature and then neutralized using glycine. The cells were then lysed on ice in the lysis buffer with proteinase inhibitors, and the nuclear lysates were sonicated to break the genome into 200–1000 bp fragments. The lysate was immunoprecipitated with primary antibodies (anti-HA-tag) or control IgG at 4 °C for 1 h, and then captured by protein A/ G beads at 4 °C overnight, followed by washing with different washing buffers. The DNA components in the precipitation were ﬁnally extracted using a standard phenol-chloroform method. Puriﬁed chromatin- immunoprecipitated DNA was subjected to PCR analysis using primers to amplify the FOXJ2 binding sites in the Lamp2 promoter region, which are listed in Supplementary Table S3. 9. Comazzetto S, Di Giacomo M, Rasmussen KD, Much C, Azzi C, Perlas E, et al. Oligoasthenoteratozoospermia and infertility in mice deﬁcient for miR-34b/c and miR-449 loci. PLoS Genet. 2014;10:e1004597. 10. Yuan S, Tang C, Zhang Y, Wu J, Bao J, Zheng H, et al. mir-34b/c and mir-449a/b/c are required for spermatogenesis, but not for the ﬁrst cleavage division in mice. Biol Open. 2015;4:212–23. 11. Miao H, Miao CX, Li N, Han J. FOXJ2 controls meiosis during spermatogenesis in male mice. Mol Reprod Dev. 2016;83:684–91. 12. Bryant JM, Meyer-Ficca ML, Dang VM, Berger SL, Meyer RG. Separation of sperma- togenic cell types using STA-PUT velocity sedimentation. J Vis Exp. 2013;80:e50648. 13. Bellvé AR, Cavicchia JC, Millette CF, O’Brien DA, Bhatnagar YM, Dym M. Sper- matogenic cells of the prepuberal mouse. Isolation and morphological char- acterization. J Cell Biol. 1977;74:68–85. 14. Griswold MD. Spermatogenesis: the commitment to meiosis. Physiol Rev. 2016;96:1–17. 15. Suede SH, Malik A, Sapra A. Histology, spermatogenesis. StatPearls. Treasure Island, FL: StatPearls Publishing LLC; 2021. Statistical analysis 27. Kitada M, Koya D. Autophagy in metabolic disease and ageing. Nat Rev Endo- crinol. 2021;17: 647–61. The data are presented as the mean ± SD and were analyzed using GraphPad Prism 6 (GraphPad Inc., La Jolla, CA, USA). Group comparisons were analyzed using Student’s t test where appropriate. P < 0.05 was considered statistically signiﬁcant. All experiments were performed in triplicate. 28. Gao L, Chen Y. Autophagy controls programmed death-ligand 1 expression on cancer cells (Review). Biomed Rep.2021;15:84. 29. Yoshii SR, Mizushima N. Monitoring and measuring autophagy. Int J Mol Sci. 2017;18:1865. 30. Eskelinen EL, Illert AL, Tanaka Y, Schwarzmann G, Blanz J, Von Figura K, et al. Role of LAMP-2 in lysosome biogenesis and autophagy. Mol Biol Cell. 2002;13:3355–68. Flow cytometry analysis y Testicular germ cells were isolated by STA-PUT according to the publication with minor modiﬁcation [12]. Testes from adult mice were decapsulated and incubated in 10 ml Dulbecco’s modiﬁed Eagle’s medium (DMEM) (Gibco, Grand Island, NY, USA) containing 100 µl of collagenase IV (Sigma, St. Louis, MO, USA), 0.015 g of hyaluronidase (Sigma), 1 ml of trypsin (Sigma), and 100 µl of DNAse I (Sigma) under gentle agitation at 34 °C for about 45 min with pipetting at the mid-time point until the testes y y y A testicular cell suspension from 10-day-old mice was prepared as described above. The cells were stained with 10 mg/ml Hoechst 33342 (Thermo Fisher) for 30 min and propidium iodide (PI) (Invitrogen, Waltham, MA, USA) for 5 min before examination using CytoFlex S (Beckman, Indianapolis, IN, USA). The results were analyzed using CytExpert 2.0 (Beckman). Cell Death and Disease (2022) 13:665 F.-R. Bai et al. 12 REFERENCES RNA-seq and bioinformatic analysis q y Testes from 10-day-old mice were harvested for RNA extraction. The quality of the RNA samples was analyzed by detection of RNA purity (A260/ A280) and integrity. Complementary DNA library construction and quality inspection were performed using the above mRNA as the template. According to the effective concentration and data requirements, the library was pooled and then sequenced using the Illumina system (Illumina, San Diego, CA, USA). Then, DEG analysis and functional enrichment analysis, including GO and KEGG pathway analysis, were carried out. The target genes of FOXJ2 were predicted by using TFBS Tools (1.18.0) software [20]. 1. White-Cooper H, Davidson I. Unique aspects of transcription regulation in male germ cells. Cold Spring Harb Perspect Biol. 2011;3:a002626. 1. White-Cooper H, Davidson I. Unique aspects of transcription regulation in male germ cells. Cold Spring Harb Perspect Biol. 2011;3:a002626. 2. Wang Y, Gray DR, Robbins AK, Crowgey EL, Chanock SJ, Greene MH, et al. Sub- phenotype meta-analysis of testicular cancer genome-wide association study data suggests a role for RBFOX family genes in cryptorchidism susceptibility. Hum Reprod. 2018;33:967–77. 3. Pérez-Sánchez C, Gómez-Ferrería MA, de La Fuente CA, Granadino B, Velasco G, Esteban-Gamboa A, et al. FHX, a novel fork head factor with a dual DNA binding speciﬁcity. J Biol Chem. 2000;275:12909–16. 4. Gómez-Ferrería MA, Rey-Campos J. Functional domains of FOXJ2. J Mol Biol. 2003;329:631–44. Identiﬁcation of KFERQ-like motifs 24. Eskelinen EL, Cuervo AM, Taylor MR, Nishino I, Blum JS, Dice JF, et al. Unifying 24. Eskelinen EL, Cuervo AM, Taylor MR, Nishino I, Blum JS, Dice JF, et al. Unifying nomenclature for the isoforms of the lysosomal membrane protein LAMP-2. Trafﬁc. 2005;6:1058–61. To identify the KFERQ-like motifs in the substrate proteins encoded by the differentially expressed genes of the RNA-seq data, the gene IDs were ﬁrstly transformed to the Uniprot ID using the Uniprot (www.uniprot.org). The KFERQ-like motifs were then retrieved from the KFERQ ﬁnder V0.8 [26]. GO enrichment analysis was performed based on the downregulated genes which encode proteins containing the KFERQ-like motifs. nomenclature for the isoforms of the lysosomal membrane protein LAMP-2. Trafﬁc. 2005;6:1058–61. 25. Kaushik S, Cuervo AM. The coming of age of chaperone-mediated autophagy. Nat Rev Mol Cell Biol. 2018;19:365–81. 26. Kirchner P, Bourdenx M, Madrigal-Matute J, Tiano S, Diaz A, Bartholdy BA, et al. Proteome-wide analysis of chaperone-mediated autophagy targeting motifs. PLoS Biol. 2019;17:e3000301. Transmission electron microscopy analysis 5. Yang Q, Cao X, Tao G, Zhou F, Zhao P, Shen Y, et al. Effects of FOXJ2 on TGF-β1- induced epithelial-mesenchymal transition through Notch signaling pathway in non-small lung cancer. Cell Biol Int. 2017;41:79–83. Testes from 10-day-old mice were immersed in 2.5% glutaraldehyde in 0.1 M phosphate buffer (pH 7.4) overnight at 4 °C and postﬁxed in 1% osmium tetroxide for 2 h at 4 °C. After dehydration, the samples were embedded in Epon 618 (TAAB Laboratories Equipment, Aldermaston, UK) and cut to ultrathin sections (70–90 nm), followed by staining with uranyl acetate and lead citrate. The ultrastructure of germ cells in the testes was observed using a transmission electron microscope (Philips CM-120, Amsterdam, the Netherlands). 6. Shan Y, Chang T, Shi S, Tang M, Bao L, Li L, et al. Foxj2 overexpression is asso- ciated with poor prognosis, progression, and metastasis in nasopharyngeal car- cinoma. Onco Targets Ther. 2017;10:3733–41. g 7. Martín-de-Lara F, Sánchez-Aparicio P, Arias de la Fuente C, Rey-Campos J. Bio- logical effects of FoxJ2 over-expression. Transgenic Res. 2008;17:1131–41. 8. Granadino B, Arias-de-la-Fuente C, Pérez-Sánchez C, Párraga M, López-Fernández LA, del Mazo J, et al. Fhx (Foxj2) expression is activated during spermatogenesis and very early in embryonic development. Mech Dev. 2000;97:157–60. FUNDING 32. Konecki DS, Foetisch K, Zimmer KP, Schlotter M, Lichter-Konecki U. An alter- natively spliced form of the human lysosome-associated membrane protein-2 gene is expressed in a tissue-speciﬁc manner. Biochem Biophys Res Commun. 1995;215:757–67. This work was supported by the Shanghai Natural Science Foundation Grant (20ZR1430700 to JW) and the National Natural Science Foundation of China (81671509 to JW). 33. Nishino I, Fu J, Tanji K, Yamada T, Shimojo S, Koori T, et al. Primary LAMP-2 deﬁciency causes X-linked vacuolar cardiomyopathy and myopathy (Danon dis- ease). Nature. 2000;406:906–10. The authors declare no competing interests. 35. Fujiwara Y, Kikuchi H, Aizawa S, Furuta A, Hatanaka Y, Konya C, et al. Direct uptake and degradation of DNA by lysosomes. Autophagy. 2013;9:1167–71. DATA AVAILABILITY 31. Majeski AE, Dice JF. Mechanisms of chaperone-mediated autophagy. Int J Bio- chem Cell Biol. 2004;36:2435–44. The RNA-seq data have been deposited into the National Center for Biotechnology Information Sequence Read Archive database (accession no. PRJNA824792). Cell Death and Disease (2022) 13:665 F.-R. Bai et al. 13 ADDITIONAL INFORMATION Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41419-022-05116-w. 38. Huang Q, Liu Y, Zhang S, Yap YT, Li W, Zhang D, et al. Autophagy core protein ATG5 is required for elongating spermatid development, sperm individualization and normal fertility in male mice. Autophagy. 2021;17:1753–67. Correspondence and requests for materials should be addressed to Jing-Wen Wu. 39. Zhu Y, Yin Q, Wei D, Yang Z, Du Y, Ma Y. Autophagy in male reproduction. Syst Biol Reprod Med. 2019;65:265–72. Reprints and permission information is available at http://www.nature.com/ reprints 40. Ferder IC, Fung L, Ohguchi Y, Zhang X, Lassen KG, Capen D, et al. Meiotic gatekeeper STRA8 suppresses autophagy by repressing Nr1d1 expression during spermatogenesis in mice. PLoS Genet. 2019;15:e1008084. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional afﬁliations. 41. Mu Y, Yan WJ, Yin TL, Zhang Y, Li J, Yang J. Diet-induced obesity impairs sper- matogenesis: a potential role for autophagy. Sci Rep. 2017;7:43475. 42. Lv C, Wang X, Guo Y, Yuan S. Role of selective autophagy in spermatogenesis and male fertility. Cells. 2020;9:2523. 43. Wang M, Xu Y, Zhang Y, Chen Y, Chang G, An G, et al. Deciphering the autophagy regulatory network via single-cell transcriptome analysis reveals a requirement for autophagy homeostasis in spermatogenesis. Theranostics. 2021;11:5010–27. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http:// creativecommons.org/licenses/by/4.0/. 44. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods. 2001;25:402–8. ETHICAL APPROVAL All animal experimental procedures were approved by the Institutional Animal Care and Use Committee of the Shanghai Jiao Tong University School of Medicine. 36. Yeﬁmova MG, Buschiazzo A, Burel A, Lavault MT, Pimentel C, Jouve G, et al. Autophagy is increased in cryptorchid testis resulting in abnormal spermatozoa. Asian J Androl. 2019;21:570–6. 37. Gao H, Khawar MB, Li W. Autophagy in reproduction. Adv Exp Med Biol. 2019;1206:453–68. ACKNOWLEDGEMENTS We appreciate and acknowledge Dr. Zheng Li for providing clinical samples. We thank the faculty of Core Facility of Basic Medical Sciences, Shanghai Jiao Tong University for technical assistance. COMPETING INTERESTS 34. Fujiwara Y, Furuta A, Kikuchi H, Aizawa S, Hatanaka Y, Konya C, et al. Discovery of a novel type of autophagy targeting RNA. Autophagy. 2013;9:403–9. AUTHOR CONTRIBUTIONS JW conceived and designed the research. FB, QW, YH, ZJ, HL, WQ, and CC performed the bench experiments. JW, FB, and QW analyzed the data. FB and JW wrote the manuscript. All authors reviewed and agreed with the contents of the manuscript. © The Author(s) 2022 Cell Death and Disease (2022) 13:665
https://openalex.org/W2046017900	https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0083927&type=printable	English	null	Use of Indocyanine Green for Detecting the Sentinel Lymph Node in Breast Cancer Patients: From Preclinical Evaluation to Clinical Validation	PloS one	2,013	cc-by	8,338	Abstract Assessment of the sentinel lymph node (SLN) in patients with early stage breast cancer is vital in selecting the appropriate surgical approach. However, the existing methods, including methylene blue and nuclides, possess low efficiency and effectiveness in mapping SLNs, and to a certain extent exert side effects during application. Indocyanine green (ICG), as a fluorescent dye, has been proved reliable usage in SLN detection by several other groups. In this paper, we introduce a novel surgical navigation system to detect SLN with ICG. This system contains two charge-coupled devices (CCD) to simultaneously capture real-time color and fluorescent video images through two different bands. During surgery, surgeons only need to follow the fluorescence display. In addition, the system saves data automatically during surgery enabling surgeons to find the registration point easily according to image recognition algorithms. To test our system, 5 mice and 10 rabbits were used for the preclinical setting and 22 breast cancer patients were utilized for the clinical evaluation in our experiments. The detection rate was 100% and an average of 2.7 SLNs was found in 22 patients. Our results show that the usage of our surgical navigation system with ICG to detect SLNs in breast cancer patients is technically feasible. Citation: Chi C, Ye J, Ding H, He D, Huang W, et al. (2013) Use of Indocyanine Green for Detecting the Sentinel Lymph Node in Breast Cancer Patients: From Preclinical Evaluation to Clinical Validation. PLoS ONE 8(12): e83927. doi:10.1371/journal.pone.0083927 Editor: Jonathan A Coles, Glasgow University, United Kingdom Received February 28, 2013; Accepted November 10, 2013; Published December 16, 2013 Copyright: © 2013 Chi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits Copyright: © 2013 Chi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This paper is supported by the National Basic Research Program of China (973 Program) under Grant No. 2011CB707700, the National Natural Science Foundation of China under Grant No. 81027002, and the Chinese Academy of Sciences Visiting Professorship for Senior International Scientists under Grant No. 2012T1G0036. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Use of Indocyanine Green for Detecting the Sentinel Lymph Node in Breast Cancer Patients: From Preclinical Evaluation to Clinical Validation hi1, Jinzuo Ye1, Haolong Ding2, De He2, Wenhe Huang2, Guo-Jun Zhang2, Jie Tian1 1 Intelligent Medical Research Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China, 2 The Breast Center, Cancer Hospital, Shantou University Medical College Shantou China 1 Intelligent Medical Research Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China, 2 The Breast Center, Cancer Hospital, Shantou University Medical College, Shantou, China Abstract Competing interests: The authors have declared that no competing interests exist. December 2013 \| Volume 8 \| Issue 12 \| e83927 Introduction higher signal-to-background ratio (SBR) [7-20], and in addition cheap and of low toxicity [7,21,22]. The fluorescent dyes, such as ICG, with a high SBR and detection depth in real-time observation enable superior SLN detection compared to the other two reagents. The only concern of the drug is allergic reaction occasionally [23]. A sentinel lymph node (SLN) is the first lymph node (LN) or a group of LNs draining from the breast [1]. Since SLN mapping, as introduced for the management of breast cancer by Giuliano et al., is currently thought to be the standard for staging clinically negative axilla [2-4], sentinel lymph node biopsy (SLNB) for breast cancer is a promising surgical technique to avoid unnecessary axillary lymph node (ALN) dissection, leading to the improvement of post-operative quality of life [5]. Presently, three detection reagents are used for detecting SLNs in clinical settings: (1) blue dye, which is widely used due to its inexpensiveness, but has limited ability to visualize afferent lymphatic vessels and SLNs [6]; (2) radioactive colloids, which require a physician specializing in nuclear medicine, to use a handheld gamma counter, making SLN localization difficult; and (3) indocyanine green (ICG), which gives a fluorescent signal has been used by several other groups for locating SLNs in breast cancer to give a reliable Since ICG emits near-infrared (NIR) fluorescence, undetectable by human eyes, an appropriate intraoperative detection system is required to produce real-time images with a high SBR. Current systems, in breast cancer research, use a single-camera for NIR imaging , requiring the shadowless surgical lights to be turned off to detect SLNs, and then turned on to resume the surgery. This on/off switching of shadowless light is inconvenient and extends the duration of the operation. A system with three-cameras has advantages in multispectral imaging and superior background noise reduction [2,6,24-28]. However, the complexity of the system in reducing background noise increases the number of operation complication during PLOS ONE \| www.plosone.org December 2013 \| Volume 8 \| Issue 12 \| e83927 1 Application of the Surgical Navigation System Figure 1. Schematic diagram of the surgical navigation system and its application in surgery. a. The principle figure of the surgical navigation system clarifying the operation course of the system. When the LED light illuminated the surgical area, the ICG dye emitted NIR light. The emission and reflection of the halogen light went through the lens to the prism. Introduction Then, the light was equally divided into two beams by the prism. One beam went through the filter to the color CCD and the other to the EMCCD. All of the data collected from the CCD were transferred to the computer, and the computer controlled the CCD. b. The hardware of the surgical navigation system. c. User interface of the software offering exposure time and auto capture interval time parameter settings. d. Image acquisition interface as an example of the capture mode results. e. Preoperative preparation in the operating room. f. Intraoperative diagnosis with a surgical navigation system carried out during the surgery. doi: 10.1371/journal.pone.0083927.g001 Figure 1. Schematic diagram of the surgical navigation system and its application in surgery. a. The principle figure of the surgical navigation system clarifying the operation course of the system. When the LED light illuminated the surgical area, the ICG dye emitted NIR light. The emission and reflection of the halogen light went through the lens to the prism. Then, the light was equally divided into two beams by the prism. One beam went through the filter to the color CCD and the other to the EMCCD. All of the data collected from the CCD were transferred to the computer, and the computer controlled the CCD. b. The hardware of the surgical navigation system. c. User interface of the software offering exposure time and auto capture interval time parameter settings. d. Image acquisition interface as an example of the capture mode results. e. Preoperative preparation in the operating room. f. Intraoperative diagnosis with a surgical navigation system carried out during the surgery. doi: 10.1371/journal.pone.0083927.g001 surgery [26-29]. Therefore, an easily operated system that provides real-time images with a high SBR is needed. (ProEM 1024B Excelon, Princeton Instrument, USA); a color CCD was used to collect visible color images (Pilot piA1400-17gc, Basler, Germany), in which two beams of light, separated by a beam splitter cube (NT49-683, Edmund Optics, USA), were received by the camera that then produced the video images on an external monitor. A fluorescence filter (wavelength 810nm-870nm) was placed in front of the EMCCD camera, while a visible light filter (wavelength 400nm-650nm) was put in front of the color CCD camera. The F-mount flange distance of the Nikon lens (Nikon Nikkor 70-300mm, f/ 4.5-5.6G) was 46.5mm and was chosen for this design for clear imaging. The hardware parts are shown in Figure 1b. Introduction In this study, we proposed a new surgical navigation system with two cameras for high SBR real-time imaging. To ensure convenience and practicality for clinical application, our surgical navigation system was designed to localize the SLN by providing an automatic real-time color and fluorescent image display recording during surgery. We assessed ICG as a fluorescent dye for SLN detection. In order to identify an optimized dose/concentration of ICG for future clinical use, we performed a preclinical test, in which serial ICG dilutions are evaluated in SLN resection experiments in nude mice and rabbits. Subsequently, clinical studies were further conducted in breast cancer patients to evaluate the feasibility of the surgical navigation system in detecting SLNs. Our study provides evidence that our surgical navigation system could provide surgeons with real-time images to accurately locate and resect SLNs during surgery. Illumination was provided by a light emitting diode (LED) (NIR light source, center wavelength 760nm, maximum power 20W) for fluorochrome excitation and a 150W halogen lamp (KL1500LCD, SCHOTT, Germany) for white light color imaging. The white light was also coupled with a fiber optic bundle and homogenized by a beam expander. According to the separation of the light spectrum, it was ensured that when the shadowless surgical light was closed, the doctors could see the operative field via a halogen light. Under these conditions, the visible light did not affect the fluorescence imaging results. Based on the hardware system, the surgical navigation system control software was developed in two modes. One was the real-time video imaging mode, in which the color and fluorescence real-time videos were displayed separately. The other was the camera capture mode. After setting the parameters of the two cameras, one click could complete the Illumination was provided by a light emitting diode (LED) (NIR light source, center wavelength 760nm, maximum power 20W) for fluorochrome excitation and a 150W halogen lamp (KL1500LCD, SCHOTT, Germany) for white light color imaging. The white light was also coupled with a fiber optic bundle and homogenized by a beam expander. According to the separation of the light spectrum, it was ensured that when the shadowless surgical light was closed, the doctors could see the operative field via a halogen light. Under these conditions, the visible light did not affect the fluorescence imaging results. Imaging Agents ICG was purchased from the Yichuang Pharmaceutical Limited Liability Company (Dandong, China). To prevent exposure to the sunlight and fluorescence bleaching, the ICG was stored at 4°C. Two hours prior to surgery, 25 mg ICG was dissolved in 5 ml of water to yield a concentration of 5 mg/ml, which was an optimal concentration based on our preclinical study. sentinel lymph node biopsy (SLNB). Informed consent was given formally to all patients before surgery. All subjects gave written informed consent after the experimental procedures were fully explained. This study was approved by the Institutional Review Board (IRB) of the Cancer Hospital of Shantou University Medical College and performed in accordance with the ethical standards of the Declaration of Helsinki. Surgical navigation system Based on the hardware system, the surgical navigation system control software was developed in two modes. One was the real-time video imaging mode, in which the color and fluorescence real-time videos were displayed separately. The other was the camera capture mode. After setting the parameters of the two cameras, one click could complete the The prototype surgical navigation system (Figure 1a) used in this study was developed by the Institute of Automation, Chinese Academy of Sciences (CASIA). The system had two charge-coupled device (CCD) cameras: an electron-multiplying CCD (EMCCD) was used to collect NIR fluorescent images December 2013 \| Volume 8 \| Issue 12 \| e83927 PLOS ONE \| www.plosone.org 2 Application of the Surgical Navigation System Table 1. Specifications of the surgical navigation system. System Features Performance parameters Chip area EMCCD 1.3’’; COLOR CCD 2/3’’ Lens focal length 70-300mm Working distance 600mm Surgical field of view 79mmW79mmH to 125mmW125mmH Sensor resolution (spatial) 1024*1024 imaging pixels 13 x 13 μm pixels 13.3 x 13.3 mm imaging area (optically centered) Sensor resolution (temporal) 8.5fps(full frame),16.7fps(binning 2Xver) Image windows Visible, fluorescent, overlay doi: 10.1371/journal.pone.0083927.t001 simultaneous acquisition of the two camera images. The user interface (Figure 1c) provided complete control of the system including the camera EM mode, exposure time, image display, image overlay and image archiving. In the camera capture mode, after a set of images was acquired, the fluorescence and color images were displayed (Figure 1d). All pictures and videos could be acquired automatically during the surgery. The image processing function was designed in the software. The registration point of white light and fluorescent images was automatically calculated by the similarity matching algorithm. Then, these two images converged according to the results in the software. This feature allowed doctors to clearly locate the lesion. doi: 10.1371/journal.pone.0083927.t001 Lymphatic mapping in animal models Before surgery, the surgical navigation system was moved above the operating field and prepared for imaging where the NIR light source and halogen fiber were covered by sterile sheets. In this setting, the lens of the camera was situated approximately 60 cm above the patient. Preoperative and intraoperative pictures are shown in Figures 1e and f. The injection concentration of ICG was 5mg/ml, which was based on a published paper and our pre-clinical trials [30]. ICG was subcutaneously injected into 2-4 points of the areola. With continuous massage for 5-10 minutes, the lymph vessels connecting to the injection point were visualized, using the surgical navigation system, along with a light spot showing SLN on the fluorescent image window. With the assistance of the video showing the maximum gray value, the surgeons could trace the SLN according to the fluorescent image. SLNs detected were then removed under the navigation of real-time NIR fluorescence imaging. The excised SLNs were also examined by NIR imaging, and then sent in for pathological examination. The Institutional Animal Care and Use Committee of Shantou University Medical College approved all animal studies. Five nude mice (nu/nu, Vital River Laboratory Animal Technology Co., Ltd., Beijing, China) and 10 rabbits (New Zealand white rabbits, Experimental Animal Center of Guangdong, Foshan, China) were used to map the lymphatic vessels and lymph nodes. In the mouse study, female mice were anesthetized by an injection of a 0.2mL mixture of ketamine, xylene and sterile distilled water at a ratio of 7:3:4. Fluorescent images were acquired with the imaging system after subcutaneous injection of 0.1mL ICG on the right side of the second mammary pad. After gently massaging the surrounding breast tissue to develop the lymph channels the skin was cut and the SLNs were removed. Similarly, female New Zealand rabbits were anesthetized with an injection of sodium pentobarbital (30 mg/kg intravenously) through the ear vein and placed in a prone position on a fixation bed. After the rabbits were sedated (typically 4–5 min), fluorescent images were then acquired after subcutaneous injection of 0.1 ml ICG around the areola. A varied concentration of ICG was administered into the second armpit areola to locate the SLN and to quantitate the light intensity. The light intensity statistics were performed using the Prism 5.0 (GraphPad-Prism) computer program. Surgical navigation system test The spatial resolution, field of view and working distance were the main parameters tested after finishing the prototype of the surgical navigation system. The detailed specifications of the system are shown in Table 1. In a practice setting, the distance between the LED light source and surgical area was around 10-20cm; if the distance was beyond 20cm, the fluorescent image became indistinguishable. The results of the standard television card tests with this system are shown in Figure S1. Patient characteristics and surgical procedure Our software to evaluate the changes of the light intensity value at each time point tested the light intensity of SLN in rabbits. The results are shown in Figures a-e. The error bars mean the variance of light intensity from 3 rabbit experiments per group at a certain concentration and time point. Then, we entered data into the computer program Prism 5.0 (GraphPad-Prism). The light intensity statistics were performed using the software. From the results we could obtain the time point of the surgery and the effective time of the operation. doi: 10.1371/journal.pone.0083927.g002 Detection of SLN in breast cancer patients by ICG Clinical statistical results are shown in Table 2. Five minutes after injection, the draining lymph vessels and SLNs were visualized on the fluorescent image window, using the color and overlay images (Figure 5). According to the light-emitting position, an incision was executed with a scalpel. Then the light-emitting region could be targeted with the assistance of our system. The surgeons were able to identify the SLN according to the fluorescent image (Figure 5d) and accurately locate it on the color image (Figure 5e). The fluorescent and color images were overlaid together by using our software (Figures 5f and i). After removal of the light-emitting region Patient characteristics and surgical procedure Twenty-two breast cancer patients, ranging from 32 to 68 years of age (median age of 49 years) with early stage breast cancer were admitted to the Breast Center of the Cancer Hospital of Shantou University Medical College and were enrolled in the study. Of those, twelve (54.5%) were premenopausal women and ten were postmenopausal (45.5%). All patients had a tumor size less than 5 cm (i.e., T1-2N0M0) and negative lymph nodes, and were eligible for December 2013 \| Volume 8 \| Issue 12 \| e83927 PLOS ONE \| www.plosone.org 3 Application of the Surgical Navigation System Figure 2. Pharmacokinetic experiments on rabbits. Five pharmacokinetic experiments using ICG with five concentrations were done on rabbits with the injection doses of 0.1 ml in the areolar area. Our software to evaluate the changes of the light intensity value at each time point tested the light intensity of SLN in rabbits. The results are shown in Figures a-e. The error bars mean the variance of light intensity from 3 rabbit experiments per group at a certain concentration and time point. Then, we entered data into the computer program Prism 5.0 (GraphPad-Prism). The light intensity statistics were performed using the software. From the results we could obtain the time point of the surgery and the effective time of the operation. doi: 10 1371/journal pone 0083927 g002 Figure 2. Pharmacokinetic experiments on rabbits. Five pharmacokinetic experiments using ICG w Figure 2. Pharmacokinetic experiments on rabbits. Five pharmacokinetic experiments using ICG with five concentrations were done on rabbits with the injection doses of 0.1 ml in the areolar area. Our software to evaluate the changes of the light intensity value at each time point tested the light intensity of SLN in rabbits. The results are shown in Figures a-e. The error bars mean the variance of light intensity from 3 rabbit experiments per group at a certain concentration and time point. Then, we entered data into the computer program Prism 5.0 (GraphPad-Prism). The light intensity statistics were performed using the software. From the results we could obtain the time point of the surgery and the effective time of the operation. doi: 10.1371/journal.pone.0083927.g002 Figure 2. Pharmacokinetic experiments on rabbits. Five pharmacokinetic experiments using ICG with five concentrations were done on rabbits with the injection doses of 0.1 ml in the areolar area. In vivo detection of SLN by ICG in rabbits SLNs could be detected as early as 3 to 5 minutes after injection and the enabling time for surgery was 10 minutes after injection (Figures 2a to e). The peak of intensity at a concentration of 5mg/ml and dose of 0.1ml of the ICG solution appeared 90 minutes after injection (Figure 2a). Based on our experiments, we chose three concentrations (0.025mg/ml, 1mg/ml, and 5mg/ml) for a feasibility test. In preclinical studies, strong light intensity was visible in the EP tube at a concentration of 0.025mg/ml in vitro, but could not be detected in vivo. The 1mg/ml concentration was suitable for animal detection, but sufficient for clinical usage. Finally a concentration of 5mg/ml was recommended for clinical use due to its strong light intensity and long duration. Five experiments were conducted on rabbits to ensure that SLNs could be located by using ICG. During the surgical experiment, real-time videos were shown on the monitor (Figures 4a and b). Figure 4c is the overlay of the pseudocolor fluorescent signal on top of the color image. Following excision of the SLN, a fluorescent image was taken (Figure 4d). The visible image and the merged image are shown in Figures 4e and f. The video of the fluorescence for the entire surgical procedure is shown in Video S1. Detection of SLN by ICG in nude mice in vivo All of the tissue sections were judged to be the SLN. d i 10 1371/j l 0083927 003 Figure 3. The SLN resection experiments in nude mice. There were two groups of figures directly acquired by the CCD cameras. The last column images were obtained after the processing of the two images in the front. When the ICG solution with a concentration of 1mg/ml was injected into the third areola of a nude mouse, ten minutes later we got a. fluorescent image for mapping the SLN. At the same time, we got b. the color image. According to the software computation, the pseudo-green fluorescent image was overlaid on top of the color image. The result of the image fusion was c. the overlay image. After dissection of the SLN, d. fluorescent image and e. color image were acquired simultaneously. From the f. overlay image, we could clearly see the fluorescence information in the color image. All dissections were sent in for pathological examination. All of the tissue sections were judged to be the SLN. doi: 10 1371/journal pone 0083927 g003 Figure 3. The SLN resection experiments in nude mice. There were two groups of figures directly acquired by the CCD cameras. The last column images were obtained after the processing of the two images in the front. When the ICG solution with a concentration of 1mg/ml was injected into the third areola of a nude mouse, ten minutes later we got a. fluorescent image for mapping the SLN. At the same time, we got b. the color image. According to the software computation, the pseudo-green fluorescent image was overlaid on top of the color image. The result of the image fusion was c. the overlay image. After dissection of the SLN, d. fluorescent image and e. color image were acquired simultaneously. From the f. overlay image, we could clearly see the fluorescence information in the color image. All dissections were sent in for pathological examination. All of the tissue sections were judged to be the SLN. doi: 10.1371/journal.pone.0083927.g003 (Figure 5h), the SLN kept lighting up (Figure 5g). The surgery video is shown in Video S2. patients revealed metastases, but not in the ALN. The slice in Figure 6a is from the patients who did not have SLN metastases. The slice in Figure 6b is from a patient whose SLN was diagnosed with metastases. Detection of SLN by ICG in nude mice in vivo No side effects were reported after the injection of ICG. SLNB using the surgical navigation system was performed on all patients and all resected LNs were evaluated by pathological examination. One or more SLNs were found in all 22 patients (100%). The total number of identified SLNs was 59, or 2.7 per patient (range 1-6). All 59 SLNs detected by the surgical navigation system gave a fluorescent signal and the pathology results confirmed they were LN tissues (detection rate=100%). All patients then received axillary dissection with a total of 361 LNs removed. The mean number of LNs removed was 16.4 per patient (range 9-32). Detection of SLN by ICG in nude mice in vivo To determine the feasibility of the system in a preclinical setting, 0.1mL of a 1mg/ml ICG solution was injected into the armpit of a mouse (Figure 3). The fluorescent and visible images are shown in Figures 3a and b. Using the software alignment operation, the fluorescent image was overlaid with the visible image (Figures 3c and f). Finally, the light-emitting tissue was confirmed as the SLN (Figures 3d and e) by pathological examination. December 2013 \| Volume 8 \| Issue 12 \| e83927 PLOS ONE \| www.plosone.org 4 Application of the Surgical Navigation System Figure 3. The SLN resection experiments in nude mice. There were two groups of figures directly acquired by the CCD cameras. The last column images were obtained after the processing of the two images in the front. When the ICG solution with a concentration of 1mg/ml was injected into the third areola of a nude mouse, ten minutes later we got a. fluorescent image for mapping the SLN. At the same time, we got b. the color image. According to the software computation, the pseudo-green fluorescent image was overlaid on top of the color image. The result of the image fusion was c. the overlay image. After dissection of the SLN, d. fluorescent image and e. color image were acquired simultaneously. From the f. overlay image, we could clearly see the fluorescence information in the color image. All dissections were sent in for pathological examination. All of the tissue sections were judged to be the SLN. doi: 10.1371/journal.pone.0083927.g003 Figure 3. The SLN resection experiments in nude mice. There were two groups of figures directly acquired by the CCD cameras. The last column images were obtained after the processing of the two images in the front. When the ICG solution with a concentration of 1mg/ml was injected into the third areola of a nude mouse, ten minutes later we got a. fluorescent image for mapping the SLN. At the same time, we got b. the color image. According to the software computation, the pseudo-green fluorescent image was overlaid on top of the color image. The result of the image fusion was c. the overlay image. After dissection of the SLN, d. fluorescent image and e. color image were acquired simultaneously. From the f. overlay image, we could clearly see the fluorescence information in the color image. All dissections were sent in for pathological examination. Discussion Radiology approaches such as X-rays, computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET) and single photon emission computed tomography (SPECT) have been considered to assist surgical procedures, but most of them were non- applicable for intraoperative surgery. In contrast, the fluorescence imaging approach offers superior application of non-radiation and high resolution and sensitivity, compared Eight out of 59 SLNs (13.6%) contained metastases, while 27 out of 361 LNs (7.5%) showed metastases. One patient possessed to have pathological LN metastases, but not SLN metastases, whereas pathological examination of another three PLOS ONE \| www.plosone.org December 2013 \| Volume 8 \| Issue 12 \| e83927 5 Application of the Surgical Navigation System Figure 4. The SLN resection experiments in rabbits. When the SLN was dissected, we took a photo as shown in a. fluorescent image. The b. color image was acquired at the same time. c. The overlay image also showed the fluorescent position in the color image. After resection, the SLN was put on medical gauze. It was shining brightly as d. the fluorescent image. Although in the e. color image there was no difference in the light, the f. overlay image showed that it was illuminated. All of the dissections were sent in for pathological examination. All of the tissue sections were judged to be the SLN. doi: 10.1371/journal.pone.0083927.g004 Figure 4. The SLN resection experiments in rabbits. When the SLN was dissected, we took a photo as shown in a. fluorescent image. The b. color image was acquired at the same time. c. The overlay image also showed the fluorescent position in the color image. After resection, the SLN was put on medical gauze. It was shining brightly as d. the fluorescent image. Although in the e. color image there was no difference in the light, the f. overlay image showed that it was illuminated. All of the dissections were sent in for pathological examination. All of the tissue sections were judged to be the SLN. doi: 10.1371/journal.pone.0083927.g004 detection method had certain obvious shortcomings resulting in significantly lower identification rates by themselves [8,10,33-38]. With the usage of ICG in our study, the detection rate was 100%, which was almost the same as or even better than using the combination method. Discussion In future work, we plan a large sample study using our system to specifically compare ICG and blue dyes in terms of testifying their sensitivity and specificity during the surgical procedure [8]. with radiological imaging visual inspection and palpation during surgery [31]. So, for the intraoperative application, the instrument with fluorescence imaging would be provided with the following standards: high SBR real-time imaging of the surgical procedure, easy operation, non-radiation and non- physical contact to patients. Our surgical navigation system fulfilled the above criteria. Compared to other current intraoperative systems, ours not only kept the advantage of easy operation in a single-camera system with improved quality of imaging and convenience of operation during surgery, but also ensured the core function of high SBR real-time imaging in three-camera systems. In comparison of new approach named goggle system [32], our system takes the advantage of high image resolution and low temporal noise. Therefore, with the guidance of our system, the surgeons could accurately and rapidly locate the SLN with the high quality visible images and the fluorescent images during the surgical procedure. To explore the optimized injection dosage and time of ICG for system detection, a series of trials was performed in our preclinical study. The results showed that, the SLN could be clearly visualized by using 1mg/ml ICG solution. However, the light intensity and duration were not enough for surgical purposes. Pre-clinical trials showed that the 5mg/ml ICG solution had strong fluorescence light intensity and the duration was long enough for 2.5 hours. The surgery of SLN dissection usually took 20-30 minutes, so that the fluorescence of ICG at 5mg/ml could be adequate for the whole process. Therefore, for clinical studies, we chose the concentration of 5mg/ml ICG solution. In future research, we will develop a surgical navigation system with improved sensitivity, which can detect weaker fluorescent signal and perform experiments that clarify the lowest concentration of the solution suitable for clinical use. Since the detection rate was 100% and an average of 2.7 SLNs was detected in all patients in our study, this demonstrated that SLN detection with our system was practical and applicable, especially for the early stage breast cancer patients. December 2013 \| Volume 8 \| Issue 12 \| e83927 Discussion It was reported that, a combination of radioactive colloid and blue dye was used for SLN mapping, which ensured the identification rate reaching 95%-97%, while each Although our surgical navigation system proved feasible in detecting SLN in breast cancer research with the usage of ICG, PLOS ONE \| www.plosone.org December 2013 \| Volume 8 \| Issue 12 \| e83927 6 Application of the Surgical Navigation System Table 2. Characteristics of 22 patients who underwent ICG-guided SLNB. Study no. Age Menstrual state Tumor location Tumor size (cm) cTNM pTNM ICG dose (ml) SLN no. SLN metastasis ALN no. Discussion Accurate navigation and reliable treatment results will aid surgeons with better judgment during surgery. Our approach delivers valuable information and provides a useful method that facilitates more detailed exploration for surgical navigation research. it also took the potential of application in other clinical areas, such as cervical cancer SLN detection studies [39]. In the future, with the aid of our surgical navigation system, we will try to dissect the orthotopic breast tumor by using the targeted NIR probe, which can distinguish the margins between the tumor and normal tissues, and guide the surgical resection appropriately [40,41]. Discussion ALN metastasis Surgery 1 43 pre Right upper outer 3×1.9 T2N1M0 T2N1M0 2 2 1/2 11 1/11 MRM +SLNB 2 46 pre Left lower inner 1.2×0.8 T1N0M0 T1N0M0 1 1 0/1 32 0/32 BCS +ALND+SLNB 3 50 pre Left upper outer 0.5×0.3 T1N0M0 T1N0M0 1 3 0/3 21 0/21 MRM +SLNB 4 68 post Left upper outer 2.9×2.4 T2N1M0 T2N0M0 0.5 3 0/3 21 0/21 MRM +SLNB 5 38 pre Left lower outer 1.8×0.6 T1N0M0 T1N0M0 1 1 0/1 18 0/18 MRM +SLNB 6 48 pre Right upper outer 4.0×2.8 T2N1M0 T2N0M0 1 6 0/6 30 0/30 MRM +SLNB 7 66 post Left upper inner 4.2×3.7 T2N1M0 T1N0M0 1 2 0/2 16 0/16 MRM +SLNB 8 47 pre Left lower outer 5.7×1.6 T3N1M0 T3N2M0 1 3 1/3 25 4/25 MRM +SLNB 9 62 post Left lower borderline 0.9×0.8 T1N0M0 T1N0M0 1 3 0/3 13 0/13 MRM +SLNB 10 55 post Right upper inner 4.0×4.0 T2N1M0 T2N0M0 1 4 0/4 9 0/9 MRM +SLNB 11 59 post Left upper inner 3.0×2.2 T2N1M0 T2N3M0 1 1 1/1 17 11/17 MRM +SLNB 12 67 post Right upper outer 1.8×1.6 T1N0M0 T1N1M0 1 1 0/1 12 2/12 BCS +ALND+SLNB 13 32 pre Right upper borderline 3.6×2.9 T2N1M0 T2N0M0 1 4 0/4 12 0/12 MRM +SLNB 14 40 pre Left middle 1.8×1.2 T1N1M0 T2N0M0 2 4 0/4 10 0/10 MRM +SLNB 15 45 pre Left lower outer 1.5×0.8 T1N0M0 T1N0M0 2 4 0/4 15 0/15 BCS +ALND+SLNB 16 57 post Left lower outer 2.0×1.0 T2N0M0 T1N0M0 2 3 0/3 11 0/11 MRM +SLNB 17 33 pre Right lower 2.3×1.2 T2N1M0 T2N1M0 2 4 1/4 20 0/20 MRM +SLNB 18 63 post Left upper outer 2.4×2.6 T2N1M0 T2N0M0 2 3 0/3 5 0/5 MRM +SLNB 19 53 post Right upper outer 2.5×1.7 T2N1M0 T2N1M0 2 2 1/2 14 0/14 MRM +SLNB 20 33 pre Left upper outer 3.1×1.6 T2N0M0 T2N1M0 2 1 1/1 6 0/6 MRM +SLNB 21 50 post Left upper 5.3×4.5 T3N1M0 T3N3M0 2 2 2/2 19 9/19 MRM +SLNB 22 43 pre Left upper outer 1.6×1.2 T1N0M0 T1N0M0 2 2 0/2 24 0/24 MRM +SLNB ALN axillary lymph node, ALND axillary lymph node dissection, SLNB sentinel lymph node biopsy, MRM modified radical mastectomy, BCS breast conserving surgery doi: 10.1371/journal.pone.0083927.t002 surgical navigation system and presented an efficient method for detecting SLN during surgeries with the advantage of real- time tracing of lymph flow and the one-step procedure. Conclusions In this paper, to solve the problem of positioning the SLN in early stage breast cancer research, we have developed a PLOS ONE \| www.plosone.org 7 PLOS ONE \| www.plosone.org December 2013 \| Volume 8 \| Issue 12 \| e83927 7 Application of the Surgical Navigation System Figure 5. ICG-guided intraoperative detection and resection of the SLN in humans. According to the preclinical trials, 22 cases of patients were taken from the SLNB surgery. In the beginning, the ICG solution was injected into the areolar region. About 3 minutes later, the lymphatic drainage and SLN would be clearly displayed on the monitor as shown in a. the fluorescent image in vivo. Because near-infrared light is not visible, there was no light information in the b. color image in vivo. Through the software of the surgical navigation system, the location of the SLN is shown in c. where the overlay image in vivo could be distinguished accurately. According to the guidelines of the fluorescent image, the surgery could quickly find the location of the SLN. d. The fluorescent image was captured before dissection. From the e. color image and the f. overlay image, SLN could be located with tweezers. The SLN was carefully removed and put on gauze. With the near-infrared light irradiation, the SLN was bright as shown in g. the fluorescent image during dissection. Such a visible image was displayed in h. the color image during dissection. Finally, the merged image of the pseudo-green fluorescence image and the color image is shown in i. the overlay image during dissection. All dissections were sent in for pathological examination. All of the tissue sections were judged to be the SLN. doi: 10.1371/journal.pone.0083927.g005 Figure 5. ICG-guided intraoperative detection and resection of the SLN in humans. According to the preclinical trials, 22 cases of patients were taken from the SLNB surgery. In the beginning, the ICG solution was injected into the areolar region. About 3 minutes later, the lymphatic drainage and SLN would be clearly displayed on the monitor as shown in a. the fluorescent image in vivo. Because near-infrared light is not visible, there was no light information in the b. color image in vivo. Through the software of the surgical navigation system, the location of the SLN is shown in c. where the overlay image in vivo could be distinguished accurately. References (2013) Clinical trial of combined radio- and fluorescence-guided sentinel lymph node biopsy in breast cancer. Br J Surg 100: 1037-1044. doi:10.1002/bjs.9159. PubMed: 23696463. 6. Hutteman M, Mieog JSD, Vorst JR, Liefers GJ, Putter H et al. (2011) Randomized, double-blind comparison of indocyanine green with or without albumin premixing for near-infrared fluorescence imaging of sentinel lymph nodes in breast cancer patients. Breast Cancer Res Treat 127: 163-170. doi:10.1007/s10549-011-1419-0. PubMed: 21360075. g j 17. Matsui A, Winer JH, Laurence RG, Frangioni JV (2011) Predicting the survival of experimental ischaemic small bowel using intraoperative near-infrared fluorescence angiography. Br J Surg 98: 1725-1734. doi: 10.1002/bjs.7698. PubMed: 21953541. 18. Sevick-Muraca EM (2012) Translation of Near-Infrared Fluorescence Imaging Technologies: Emerging Clinical Applications. Annual Review of Medicine, Vol 63 63: 217-231. 7. Hirche C, Murawa D, Mohr Z, Kneif S, Hünerbein M (2010) ICG fluorescence-guided sentinel node biopsy for axillary nodal staging in breast cancer. Breast Cancer Res Treat 121: 373-378. doi:10.1007/ s10549-010-0760-z. PubMed: 20140704. 19. Gioux S, Choi HS, Frangioni JV (2010) Image-guided surgery using invisible near-infrared light: fundamentals of clinical translation. Mol Imaging 9: 237-255. PubMed: 20868625. 8. Sugie T, Sawada T, Tagaya N, Kinoshita T, Yamagami K et al. (2013) Comparison of the indocyanine green fluorescence and blue dye methods in detection of sentinel lymph nodes in early-stage breast cancer. Ann Surg Oncol 20: 2213-2218. doi:10.1245/ s10434-013-2890-0. PubMed: 23429938. g g 20. Vahrmeijer AL, Hutteman M, van der Vorst JR, van de Velde CJ, Frangioni JV (2013) Image-guided cancer surgery using near-infrared fluorescence. Nat Rev Clin Oncol 10: 507-518. doi:10.1038/nrclinonc. 2013.123. PubMed: 23881033. 21. Alford R, Simpson HM, Duberman J, Hill GC, Ogawa M et al. (2009) Toxicity of Organic Fluorophores Used in Molecular Imaging: Literature Review. Mol Imaging 8: 341-354. PubMed: 20003892. 9. Motomura K, Inaji H, Komoike Y, Kasugai T, Noguchi S et al. (1999) Sentinel node biopsy guided by indocyanine green dye in breast cancer patients. Jpn J Clin Oncol 29: 604-607. doi:10.1093/jjco/29.12.604. PubMed: 10721942. 22. Gilmore DM, Khullar OV, Gioux S, Stockdale A, Frangioni JV et al. (2013) Effective low-dose escalation of indocyanine green for near- infrared fluorescent sentinel lymph node mapping in melanoma. Ann Surg Oncol 20: 2357-2363. doi:10.1245/s10434-013-2905-x. PubMed: 23440551. 10. Motomura K, Inaji H, Komoike Y, Hasegawa Y, Kasugai T et al. (2001) Combination technique is superior to dye alone in identification of the sentinel node in breast cancer patients. J Surg Oncol 76: 95-99. doi: 10.1002/1096-9098(200102)76:2. References 1. Denninghoff VC, Kahn AG, Falco J, Curutchet HP, Elsner B (2004) Sentinel lymph node: detection of micrometastases of melanoma in a molecular study. Mol Diagn 8: 253-258. doi: 10.2165/00066982-200408040-00007. PubMed: 15887981. breast cancer. Breast Cancer 12: 211-215. doi:10.2325/jbcs.12.211. PubMed: 16110291. breast cancer. Breast Cancer 12: 211-215. doi:10.2325/jbcs.12.211. PubMed: 16110291. 12. Tagaya N, Yamazaki R, Nakagawa A, Abe A, Hamada K et al. (2008) Intraoperative identification of sentinel lymph nodes by near-infrared fluorescence imaging in patients with breast cancer. Am J Surg 195: 850-853. doi:10.1016/j.amjsurg.2007.02.032. PubMed: 18353274. 2. Mieog JSD, Troyan SL, Hutteman M, Donohoe KJ, Vorst JR et al. (2011) Toward Optimization of Imaging System and Lymphatic Tracer for Near-Infrared Fluorescent Sentinel Lymph Node Mapping in Breast. Cancer - Annals of Surgical Oncology 18: 2483-2491. doi:10.1245/ s10434-011-1566-x. 850-853. doi:10.1016/j.amjsurg.2007.02.032. PubMed: 18353 13. Sugie T, Kassim KA, Takeuchi M, Hashimoto T, Yamagami K et al. (2010) A novel method for sentinel lymph node biopsy by indocyanine green fluorescence technique in breast cancer. Cancers (Basel) 2: 713-720. doi:10.3390/cancers2020713. PubMed: 24281090. 3. Giuliano AE, Hunt KK, Ballman KV, Beitsch PD, Whitworth PW et al. (2011) Axillary Dissection vs No Axillary Dissection in Women With Invasive Breast Cancer and Sentinel Node Metastasis: A Randomized. Clinical Trials - Archives of Surgery 146: 980-980. 14. Ogawa Y, Ikeda K, Ogisawa K, Tokunaga S, Fukushima H et al. (2013) Outcome of sentinel lymph node biopsy in breast cancer using dye alone: a single center review with a median follow-up of 5 years. Surg Today. 4. Valsecchi ME, Silbermins D, de Rosa N, Wong SL, Lyman GH (2011) Lymphatic Mapping and Sentinel Lymph Node Biopsy in Patients With Melanoma: A Meta-Analysis. J Clin Oncol 29: 1479-1487. doi:10.1200/ JCO.2010.33.1884. PubMed: 21383281. 15. Yamamoto S, Maeda N, Yoshimura K, Oka M (2013) Intraoperative detection of sentinel lymph nodes in breast cancer patients using ultrasonography-guided direct indocyanine green dye-marking by real- time virtual sonography constructed with three-dimensional computed tomography-lymphography. Breast, 22: 933–7. PubMed: 23726129. 5. Kootstra J, Hoekstra-Weebers JE, Rietman H, de Vries J, Baas P et al. (2008) Quality of life after sentinel lymph node biopsy or axillary lymph node dissection in stage I/II breast cancer patients: a prospective longitudinal study. Ann Surg Oncol 15: 2533-2541. doi:10.1245/ s10434-008-9996-9. PubMed: 18597146. omography-lymphography. Breast, 22: 933–7. PubMed: 2372612 16. Schaafsma BE, Verbeek FPR, Rietbergen DDD, van der Hiel B, van der Vorst JR et al. (MOV) Video S2. This is a video of ICG-guided surgery of the SLN in humans. The course was just like the experiment for the rabbit. It also includes the whole course of finding the SLN in humans during surgery. Lymphatic vessels and SLN are clearly displayed in this video. (MOV) Figure S1. The resolution test of the surgical navigation system. The aim was to find the highest spatial frequency at which two lines could be distinguished from each other. Figure a (color image) and b (fluorescent image) were the images taken by the surgical navigation system. Figure c whose horizontal axis represents the pixel number and the vertical axis represents the gray value was the analysis of Figure a. Correspondingly, Figure d showed the analysis results of Figure b. The numbers, such as 350, 400, 550…, in figure a and b were the television line numbers which represented the ability of the resolution of the video system. Acknowledgements The authors thank Adjunct Assistant Professor Dr. Karen M. von Deneen from the University of Florida, Dr. Yang Du and Dr. Zhenhua Hu for their modifications of this paper. Author Contributions Video S1. This is a video of ICG-guided removal of the SLN in the rabbit. It includes the whole course of finding the SLN in the rabbit. This was the epitome of all rabbit removal experiments. Conceived and designed the experiments: cc GJZ JT. Performed the experiments: CC JY HD DH WH GJZ. Analyzed the data: CC JY. Contributed reagents/materials/analysis tools: CC JY. Wrote the manuscript: CC GJZ JT. Conclusions Application of the Surgical Navigation System Conclusions According to the guidelines of the fluorescent image, the surgery could quickly find the location of the SLN. d. The fluorescent image was captured before dissection. From the e. color image and the f. overlay image, SLN could be located with tweezers. The SLN was carefully removed and put on gauze. With the near-infrared light irradiation, the SLN was bright as shown in g. the fluorescent image during dissection. Such a visible image was displayed in h. the color image during dissection. Finally, the merged image of the pseudo-green fluorescence image and the color image is shown in i. the overlay image during dissection. All dissections were sent in for pathological examination. All of the tissue sections were judged to be the SLN. doi: 10.1371/journal.pone.0083927.g005 PLOS ONE \| www.plosone.org PLOS ONE \| www.plosone.org December 2013 \| Volume 8 \| Issue 12 \| e83927 8 8 Application of the Surgical Navigation System Figure 6. The normal and tumor-metastasis pathology slices of SLN dissected by ICG-guided surgery. All of the dissected SLNs were sent in for pathological examination. After the conventional Hematoxylin-Eosin (HE) staining, the results proved that all of the dissected tissue specimens were lymph nodes. Figure a. shows normal sentinel lymph node cells with no cancer metastasis. Figure b. shows infiltrating ductal breast cancer. doi: 10.1371/journal.pone.0083927.g006 Figure 6. The normal and tumor-metastasis pathology slices of SLN dissected by ICG-guided surgery. All of the dissected SLNs were sent in for pathological examination. After the conventional Hematoxylin-Eosin (HE) staining, the results proved that all of the dissected tissue specimens were lymph nodes. Figure a. shows normal sentinel lymph node cells with no cancer metastasis. Figure b. shows infiltrating ductal breast cancer. doi: 10.1371/journal.pone.0083927.g006 PLOS ONE \| www.plosone.org PLOS ONE \| www.plosone.org December 2013 \| Volume 8 \| Issue 12 \| e83927 9 Supporting Information Figure S1. The resolution test o system. The aim was to find the h which two lines could be distinguish a (color image) and b (fluorescen taken by the surgical navigation horizontal axis represents the pixe axis represents the gray value wa Correspondingly, Figure d showe Figure b. The numbers, such as 3 and b were the television line num ability of the resolution of the video s (TIF) Video S1. This is a video of IC SLN in the rabbit. It includes the SLN in the rabbit. This was the ep experiments. Application of the Surgical Navigation System Application of the Surgical Navigation System fluorescein angiography and indocyanine green angiography. J Ocul Pharmacol Ther 28: 410-413. doi:10.1089/jop.2011.0221. PubMed: 22372690. 33. Goyal A, Newcombe RG, Chhabra A, Mansel RE (2006) Factors affecting failed localisation and false-negative rates of sentinel node biopsy in breast cancer--results of the ALMANAC validation phase. Breast Cancer Res Treat 99: 203-208. doi:10.1007/ s10549-006-9192-1. PubMed: 16541308. 24. Themelis G, Yoo JS, Soh K-S, Schulz R, Ntziachristos V (2009) Real- time intraoperative fluorescence imaging system using light-absorption correction. J Biomed Opt 14: 064012. doi:10.1117/1.3259362. PubMed: 20059250. 34. Zavagno G, De Salvo GL, Scalco G, Bozza F, Barutta L et al. (2008) A Randomized clinical trial on sentinel lymph node biopsy versus axillary lymph node dissection in breast cancer: results of the Sentinella/ GIVOM trial. Ann Surg 247: 207-213. doi:10.1097/SLA. 0b013e31812e6a73. PubMed: 18216523. 25. Gibbs-Strauss SL, Rosenberg M, Clough BL, Troyan SL, Frangioni JV (2009) First-in-human clinical trials of imaging devices: an example from optical imaging. Conf Proc IEEE Eng Med Biol Soc 2009: 2001-2004. PubMed: 19964033. 35. Straver ME, Meijnen P, van Tienhoven G, van de Velde CJ, Mansel RE et al. (2010) Sentinel node identification rate and nodal involvement in the EORTC 10981-22023 AMAROS trial. Ann Surg Oncol 17: 1854-1861. doi:10.1245/s10434-010-0945-z. PubMed: 20300966. 26. Hutteman M, Choi HS, Mieog JS, van der Vorst JR, Ashitate Y et al. (2011) Clinical translation of ex vivo sentinel lymph node mapping for colorectal cancer using invisible near-infrared fluorescence light. Ann Surg Oncol 18: 1006-1014. doi:10.1245/s10434-010-1426-0. PubMed: 21080086. 36. Krag DN, Anderson SJ, Julian TB, Brown AM, Harlow SP et al. (2010) Sentinel-lymph-node resection compared with conventional axillary- lymph-node dissection in clinically node-negative patients with breast cancer: overall survival findings from the NSABP B-32 randomised phase 3 trial. Lancet Oncol 11: 927-933. doi:10.1016/ S1470-2045(10)70207-2. PubMed: 20863759. 27. Lee BT, Hutteman M, Gioux S, Stockdale A, Lin SJ et al. (2010) The FLARE Intraoperative Near-Infrared Fluorescence Imaging System: A First-in-Human Clinical Trial in Perforator Flap Breast Reconstruction. Plast Reconstr Surg 126: 1472-1481. doi:10.1097/PRS. 0b013e3181f059c7. PubMed: 21042103. 37. van der Vorst JR, Schaafsma BE, Verbeek FP, Hutteman M, Mieog JS et al. (2012) Randomized comparison of near-infrared fluorescence imaging using indocyanine green and 99(m) technetium with or without patent blue for the sentinel lymph node procedure in breast cancer patients. Ann Surg Oncol 19: 4104-4111. doi:10.1245/ s10434-012-2466-4. PubMed: 22752379. 28. Crane LMA, Themelis G, Arts HJG, Buddingh KT, Brouwers AH et al. References PubMed: 11223834. 23. Su Z, Ye P, Teng Y, Zhang L, Shu X (2012) Adverse reaction in patients with drug allergy history after simultaneous intravenous fundus 11. Kitai T, Inomoto T, Miwa M, Shikayama T (2005) Fluorescence navigation with indocyanine green for detecting sentinel lymph nodes in 10 PLOS ONE \| www.plosone.org December 2013 \| Volume 8 \| Issue 12 \| e83927 Application of the Surgical Navigation System (2011) Intraoperative near-infrared fluorescence imaging for sentinel lymph node detection in vulvar cancer: First clinical results. Gynecol Oncol 120: 291-295. doi:10.1016/j.ygyno.2010.10.009. PubMed: 21056907. 29. Pleijhuis RG, Langhout GC, Helfrich W, Themelis G, Sarantopoulos A et al. (2011) Near-infrared fluorescence (NIRF) imaging in breast- conserving surgery: Assessing intraoperative techniques in tissue- simulating breast phantoms. Eur J Surg Oncol 37: 32-39. doi:10.1016/ j.ejso.2011.03.127. PubMed: 21106329. 38. Schaafsma BE, Verbeek FP, Rietbergen DD, van der Hiel B, van der Vorst JR et al. (2013) Clinical trial of combined radio- and fluorescence- guided sentinel lymph node biopsy in breast cancer. Br J Surg 100: 1037-1044. doi:10.1002/bjs.9159. PubMed: 23696463. 39. Crane LM, Themelis G, Pleijhuis RG, Harlaar NJ, Sarantopoulos A et al. (2011) Intraoperative multispectral fluorescence imaging for the detection of the sentinel lymph node in cervical cancer: a novel concept. Mol Imaging Biol 13: 1043-1049. doi:10.1007/ s11307-010-0425-7. PubMed: 20835767. 30. Imai K, Minamiya Y, Saito H, Nakagawa T, Ito M et al. (2013) Detection of pleural lymph flow using indocyanine green fluorescence imaging in non-small cell lung cancer surgery: a preliminary study. Surg Today 43: 249-254. doi:10.1007/s00595-012-0237-2. PubMed: 22729459. 40. Nguyen QT, Olson ES, Aguilera TA, Jiang T, Scadeng M et al. (2010) Surgery with molecular fluorescence imaging using activatable cell- penetrating peptides decreases residual cancer and improves survival. Proc Natl Acad Sci U S A 107: 4317-4322. doi:10.1073/pnas. 0910261107. PubMed: 20160097. 31. van Dam GM, Themelis G, Crane LMA, Harlaar NJ, Pleijhuis RG et al. (2011) Intraoperative tumor-specific fluorescence imaging in ovarian cancer by folate receptor-α targeting: first in-human results. Nat Med 17: 1315-1319. doi:10.1038/nm.2472. PubMed: 21926976. 32. Liu Y, Njuguna R, Matthews T, Akers WJ, Sudlow GP et al. (2013) Near-infrared fluorescence goggle system with complementary metal– oxide–semiconductor imaging sensor and see-through display. J Biomed Opt 18: 101303-101303. doi:10.1117/1.JBO.18.10.101303. PubMed: 23728180. 41. Savariar EN, Felsen CN, Nashi N, Jiang T, Ellies LG et al. (2013) Real- time in vivo molecular detection of primary tumors and metastases with ratiometric activatable cell-penetrating peptides. Cancer Res 73: 855-864. doi:10.1158/0008-5472.CAN-12-2969. PubMed: 23188503. PLOS ONE \| www.plosone.org PLOS ONE \| www.plosone.org December 2013 \| Volume 8 \| Issue 12 \| e83927 11
W2586179993.txt	https://journals.library.brocku.ca/index.php/voixplurielles/article/download/1448/1326	fr		Christensen, Andrée. Epines d’encre	Voix plurielles	2,016	cc-by	456	Voix plurielles 13.2 (2016) 198 Christensen, Andrée. Epines d’encre. Ottawa : Vermillon / David, 2016. 160 p. La rose est depuis longtemps déclinée dans les littératures les plus diverses, fleur emblématique de la poésie depuis les roses de l’amour et de la mort dans les quatrains d’Omar Khayyam au douzième siècle ou d’« Ode à Cassandre » de Pierre de Ronsard au seizième, jusqu’aux plantes plus politiques, par exemple dans « La rose et le réséda » de Louis Aragon. Dans Epines d’encre, Andrée Christensen remplit toutes les pages du recueil de roses qu’elle catalogue, comme dans un herbier, selon les images qu’elles évoquent. La poète distingue quatre catégories : les « méditatives », qui « tiennent peu de place [et] vénèrent le silence » ; les « dionysiaques », dont le « parfum est celui de l’animal [alors que] leur beauté indomptable a l’âpreté lumineuse de l’orage » ; les « infernales », qui « convoquent les anges charognards [et] lient conscient et inconscient » ; et les « alchimistes », dont le « terreau est celui du rêve, jonction de deux univers ». Chaque rose reçoit un nom, entre autres « La rose-de-l’effacement », « La rose-corneille », « La rose-de-la-nuit-blanche » ou encore « La rose-jardinière », et chacune des quatre parties débute par la reproduction d’une peinture acrylique de l’auteure représentant une rose sur fond noir. S’inspirant de la roseraie de son père, jardinier passionné, la poète développe un langage délicat et patient, attentif aux détails, aux couleurs changeantes et aux plis et au dépliage d’une idée ou d’une image. Par exemple, « La rose-fatale » se montre « Gourmande au rire érubescent, / coupable de toutes les couleurs greffées » ; « La rose-des-cicatrices » « donne sa langue à l’abeille meurtrière » et « écrit un sabbat de dards noirs » ; « La rose-de-l’étoile » réside dans un « charnier d’étoiles jaunes / aux récits de cendre ». Dans sa préface, Christensen expose les intentions à l’origine du recueil. Elle énonce le lien affectif et biographique qui anime son amour des roses et son présent projet d’écriture. Elle souligne aussi son mûrissement de longue date, comment il est basé sur des notes délaissées et comment il l’a accompagnée dans d’autres réflexions poétiques. Certes, sa roseraie littéraire, confie-t-elle, abrite « les roses de la mémoire », mais elle s’emploie également à un « nouveau langage des roses », celui-ci « à caractère onirique ». La poète souhaite « des roses parlantes qui se racontent, dialoguent, interrogent, hantent », ou qui restent silencieuses. De la sorte, Epines d’encre recherche « quelque chose d’indéfinissable » dans un terreau poétique déjà fleuri par « cinq millions […] d’une longue lignée ». Emilienne Rue
https://openalex.org/W2549207365	https://europepmc.org/articles/pmc5356723?pdf=render	English	null	Combination of COX-2 expression and <i>PIK3CA</i> mutation as prognostic and predictive markers for celecoxib treatment in breast cancer	Oncotarget	2,016	cc-by	10,575	Sandrine Tury1, Véronique Becette2, Franck Assayag3, Sophie Vacher1, Camille Benoist1, Maud Kamal4, Elisabetta Marangoni3, Ivan Bièche1, Florence Lerebours4, Céline Callens1 1Pharmacogenomic Unit, Genetics Laboratory, Institut Curie, Paris, France 2Department of Pathology, Institut Curie, Hôpital René Huguenin, Saint-Cloud, France 3Laboratory of Preclinical Investigations, Translational Research Department, Institut Curie, Paris, France 4Department of Medical Oncology, Institut Curie, Paris and Saint-Cloud, France Correspondence to: Céline Callens, email: celine.callens@curie.fr Keywords: breast cancer, PIK3CA, celecoxib, prognosis, predictive biomarker Received: April 29, 2016 Accepted: October 26, 2016 Published: November 08, 2016 1Pharmacogenomic Unit, Genetics Laboratory, Institut Curie, Paris, France 2Department of Pathology, Institut Curie, Hôpital René Huguenin, Saint-Cloud, France 3Laboratory of Preclinical Investigations, Translational Research Department, Institut Curie, Paris, France 4Department of Medical Oncology, Institut Curie, Paris and Saint-Cloud, France Correspondence to: Céline Callens, email: celine.callens@curie.fr Keywords: breast cancer, PIK3CA, celecoxib, prognosis, predictive biomarker Received: April 29, 2016 Accepted: October 26, 2016 Published: November 08, 2016 Correspondence to: Céline Callens, email: celine.callens@curie.fr Keywords: breast cancer, PIK3CA, celecoxib, prognosis, predictive biomarker Received: April 29, 2016 Accepted: October 26, 2016 Published: November 08, 2016 ABSTRACT COX-2 expression level and prognostic value are still a matter of debate in breast cancer (BC). We addressed these points in the context of PIK3CA mutational status. Based on an interesting study of aspirin efficacy in colorectal cancer, we hypothesized that celecoxib antitumoral activity may be restricted to PIK3CA mutated BC. COX-2 mRNA expression was analyzed in 446 BC samples and in 61 BC patient- derived xenografts (PDX) using quantitative RT-PCR. The prognostic impact of COX-2 expression level was assessed independently and according to PIK3CA mutational status in our cohort and in a validation set of 817 BC. The antitumoral activity of celecoxib was tested in two triple-negative (TN) PDX with a PIK3CA wild-type (wt) or mutated genotype.i COX-2 mRNA was overexpressed in 2% of BC and significantly associated with TN subtype. Metastasis-free survival (MFS) was significantly better in patients with high COX-2 expression level, the prognosis of whom was similar to patients with PIK3CA mutations. TCGA validation cohort confirmed that patients with low COX-2 expression PIK3CA wt tumors had the worse disease-free survival (DFS) compared to all other subgroups. Celecoxib had a significant antitumoral effect in PIK3CA mutated PDX only. Celecoxib antitumoral activity involved S6 ribosomal protein and AKT phosphorylation. Low expression of COX-2 has a significant negative impact on the MFS/DFS of BC patients. Antitumoral effect of celecoxib is restricted to PIK3CA mutated PDX. These results suggest that PIK3CA mutation may be a new predictive biomarker for celecoxib efficacy. INTRODUCTION reports are controversial. COX-2 expression levels in ductal carcinoma in situ (DCIS) and invasive carcinoma were reported to be similar in a meta-analysis of COX- 2 expression levels in breast cancers (BC). No clear conclusion on COX-2 expression levels in normal breast epithelium was however reported in the latter study [4]. A recent study using immunohistochemistry (IHC) assessed COX-2 expression on BC and adjacent normal tissues from 96 premenopausal women. COX-2 expression in the normal breast epithelium fluctuated (more than 40-fold) The cyclooxygenase-2 (COX-2) also known as the prostaglandin-endoperoxide synthase-2 (PTGS-2) is an inducible enzyme involved in inflammatory and oncogenic processes. It is responsible for the synthesis of prostaglandins from arachidonic acid [1] and is reported to induce the expression of aromatase in breast tissue [2, 3]. COX-2 expression level in breast carcinomas and normal breast tissue is not well established and www.impactjournals.com/oncotarget www.impactjournals.com/oncotarget Oncotarget 85124 among women and was correlated with COX-2 expression levels in DCIS and invasive cancer, independently of known prognostic features. The authors suggested that factors regulating physiological COX-2 expression may be the primary drivers of COX-2 expression in BC. Thus, baseline COX-2 expression level may be an indicator of BC risk, and predict chemo preventive and therapeutic efficacy of COX-2 inhibitors in young women [5]. The prognostic value of COX-2 is still debated. Several studies suggested that COX-2 is implicated in BC progression, where COX-2 overexpression was shown to be associated with poorer outcome. On the other hand, this negative prognostic impact may be counterbalanced by hormonal treatment [6–10]. early relapse in patients with DCIS and may help in the clinical decision for treatment of DCIS [16]. Despite the different encouraging results, it remains to be established whether BC patients might actually benefit from celecoxib treatment. In 2012 Liao et al. showed that aspirin, a non- selective COX inhibitor, increased overall survival in patients with colorectal cancer harboring an activating mutation in the PIK3CA gene. These results substantiate an interaction between the cyclooxygenase activity and the PI3K/AKT pathway [19]. Other studies confirmed the benefit of aspirin treatment on overall survival in PIK3CA mutated colorectal cancer [20]. As PIK3CA mutations are reported in 10-40% of BCs [21] we hypothesized that mutated-PIK3CA breast tumor expressing COX-2 could benefit from treatment with a COX-2 inhibitor such as celecoxib. Giving the putative prognostic role of COX-2, the potential therapeutic benefit of COX-2 inhibitors has been investigated. Celecoxib, a non-steroidal anti-inflammatory drug (NSAID), is a specific COX- 2 inhibitor. Celecoxib acts mainly by decreasing the formation of downstream target proteins prostaglandin, prostacyclin or thromboxane involved in cell proliferation and angiogenesis. Celecoxib has thus been examined for its antitumoral properties [11, 12]. In the present study we first evaluated COX-2 expression levels and prognostic value according to the PIK3CA mutational status in a large retrospective cohort of BC patients. We then investigated the antitumoral effect of celecoxib depending on PIK3CA mutation in triple-negative patients-derived xenograft models (PDX). Finally, we assessed potential predictive biomarkers and secondary resistance mechanisms associated with celecoxib antitumoral properties. In vitro and in vivo studies have shown an antitumoral effect of celecoxib in BC. Celecoxib significantly decreased tumor volume by 32% in rats with chemically induced mammary tumor [13]. www.impactjournals.com/oncotarget Celecoxib was also reported to significantly decrease tumor incidence rate and delayed tumor emergence in similar animal models [14]. COX-2 overexpression is rare and associated with TNBC Although preclinical data were optimistic, the clinical trials results testing the efficacy of celecoxib in BC patients were disappointing. The combination of celecoxib and aromatase inhibitors was tested in clinical trials since celecoxib may enhance aromatase inhibitors’ efficacy. In DCIS, two studies have led to conflicting results [15, 16]. In a phase II trial for advanced BC women with progressive disease under tamoxifen, celecoxib in association with exemestane did not improve clinical outcome as compared to exemestane alone [17]. Another multicentric randomized phase II study of neoadjuvant epirubicin/cyclophosphamide followed by docetaxel (EC- D) with or without celecoxib showed that celecoxib is not likely to improve complete pathological response rates in addition to EC-D in patients with HER2-negative tumor [18]. A trial on 90 DCIS postmenopausal patients with ER-positive carcinoma showed that two weeks presurgical treatment with celecoxib alone or in combination with exemestane had no effect on proliferation or apoptose [15]. More recently, a monocentric phase II neoadjuvant trial in postmenopausal women with ER-positive DCIS (n=95) showed that concomitant administration of celecoxib and exemestane during 12 weeks induced a significant reduction in tumor cell proliferation and COX-2 expression. These results suggest that COX-2 high expression levels may be a predictive marker for We first quantified the expression level of COX-2 transcript by quantitative RT-PCR (qRT-PCR) in a cohort of 446 BC samples composed of 68 HR-ERBB2-, 42 HR- ERBB2+, 285 HR+ERBB2- and 51 HR+ERBB2+ cases. COX-2 transcript was underexpressed (relative expression <0.3 compared to normal tissue as detailed in material and method section) in 74% (332/446) and overexpressed (relative expression >3 compared to normal tissue) in 2% (8/446) of cases. By comparison with normal tissue COX-2 mRNA relative expression was significantly higher in triple-negative subtype than in HR+ERBB2- and in HR+ERBB2+ subtypes (Figure 1A). This result was identical when evaluating COX-2 mRNA expression without normal tissue comparison (Supplementary Figure S1A). Considering the relative expression cut-off of 3, COX-2 overexpression is strongly associated with the triple-negative subtype (10%, 7/68 tumors, p<0.0001)i COX-2 transcript was also quantified by qRT-PCR in 61 tumors collected on PDX (15 HR+, 6 ERBB2+ and 40 triple negative tumors). In PDX, the strongest expression levels of COX-2 were found in triple-negative (median 36 [0–1673]) compared to luminal (median 0 [0–202]) (p=0.0006) and ERBB2 positive subtypes (median 6 [0– 601]) (p=ns) (Supplementary Figure S1B). COX-2 overexpression is rare and associated with TNBC www.impactjournals.com/oncotarget Oncotarget 85125 COX-2 IHC staining in 26 primary tumors representative of our cohort revealed no labeling when the expression of COX-2 transcript was inferior to 2 (relative expression compared to normal tissue) and the staining becomes more intense as the level of expression of transcript increases (Table 1 and examples are shown in Figure 1B). The same observation was made in 14 PDX where COX- 2 IHC staining was more intense when COX-2 transcript was more expressed (Table 2). These data show a good correlation between the COX-2 mRNA and the COX-2 protein expression levels except for two cases (2/26, 8%) of primary tumor (3395 and 5015). Technical difficulties Oncotarget 85126 mpactjournals.com/oncotarget re 1: COX-2 mRNA and protein expression in patient breast tumors. A. COX-2 mRNA expression levels in 446 breast samples (68 HR-ERBB2-, 42 HR-ERBB2+, 285 HR+ERBB2- and 51 HR+ERBB2+) and in 10 normal breast tissues using qRT- HR for hormone receptors. COX-2 mRNA expression in breast tumor samples is expressed compared to COX-2 mRNA expression mal tissue. B. COX-2 protein expression in a mRNA COX-2 expressing tumor, weak (a) and strong (c). b and d: the same tumors d with the isotypic control antibody. Figure 1: COX-2 mRNA and protein expression in patient breast tumors. A. COX-2 mRNA expression levels in 446 breast tumor samples (68 HR-ERBB2-, 42 HR-ERBB2+, 285 HR+ERBB2- and 51 HR+ERBB2+) and in 10 normal breast tissues using qRT- PCR. HR for hormone receptors. COX-2 mRNA expression in breast tumor samples is expressed compared to COX-2 mRNA expression in normal tissue. B. COX-2 protein expression in a mRNA COX-2 expressing tumor, weak (a) and strong (c). b and d: the same tumors stained with the isotypic control antibody. Figure 1: COX-2 mRNA and protein expression in patient breast tumors. A. COX-2 mRNA expression levels in 446 breast tumor samples (68 HR-ERBB2-, 42 HR-ERBB2+, 285 HR+ERBB2- and 51 HR+ERBB2+) and in 10 normal breast tissues using qRT- PCR. HR for hormone receptors. COX-2 mRNA expression in breast tumor samples is expressed compared to COX-2 mRNA expression in normal tissue. B. COX-2 protein expression in a mRNA COX-2 expressing tumor, weak (a) and strong (c). b and d: the same tumors stained with the isotypic control antibody. Figure 1: COX-2 mRNA and protein expression in patient breast tumors. A. COX-2 overexpression is rare and associated with TNBC COX-2 mRNA expression levels in 446 breast tumor samples (68 HR-ERBB2-, 42 HR-ERBB2+, 285 HR+ERBB2- and 51 HR+ERBB2+) and in 10 normal breast tissues using qRT- PCR. HR for hormone receptors. COX-2 mRNA expression in breast tumor samples is expressed compared to COX-2 mRNA expression in normal tissue. B. COX-2 protein expression in a mRNA COX-2 expressing tumor, weak (a) and strong (c). b and d: the same tumors stained with the isotypic control antibody. www.impactjournals.com/oncotarget www.impactjournals.com/oncotarget Oncotarget 85126 Table 1: Correlation between COX-2 mRNA and COX-2 protein expression level on 26 primary breast tumors samples ID COX-2 mRNA expression COX-2 protein expression positive cells (%) staining intensity 4410 <0.05 negative 0 0 4207 <0.05 negative 0 0 5396 <0.05 negative 60 1 6645 0.03 negative 0 0 5461 0.04 negative 0 0 4393 0.20 negative 0 0 5470 0.20 negative 0 0 6605 0.79 negative 2 2 3395 1 positive (moderate) 25 3 6189 1 negative 80 1 6189a 1 6601 1 negative 80 1 6891 1 negative 0 0 5708 1.47 negative 0 0 2421 1.67 negative 0 0 2690 1.91 negative 0 0 6602b 2.05 5295 2.53 positive (moderate) 50 2 to 3 5295 2.53 positive (moderate) 20 2 to 3 5015 5.85 negative 0 0 6874 6.33 positive (moderate) 40 2 to 3 6889 7.07 positive (high) 70 2 to 3 6889 7.07 positive (moderate) 20 2 to 3 5392 8.46 positive (moderate) <<1 3 2346 8.58 positive (high) 100 2 to 3 6876 47.31 positive (high) 70 2 aCorresponding to ductal carcinoma in situ (DCIS) case. bCorresponding to neuroendocrine carcinoma case etween COX-2 mRNA and COX-2 protein expression level on 26 primary breast tumors bCorresponding to neuroendocrine carcinoma case. We then tested the relation between COX-2 mRNA expression levels and both EGFR mRNA level and PIK3CA mutation status, previously determined in these tumor samples [33, 34]. PIK3CA mutations were detected in 33% of patients (148/446). COX-2 mRNA level was tightly linked to EGFR mRNA levels (p<10-4) and to PIK3CA mutations (p<10-4) (Table 3). prevented us from accurately determine the percent of positive cells and intensity of the staining in particular histological types of breast carcinomas like ductal carcinoma in situ (6189), neuroendocrine carcinoma (6602) and metaplastic carcinoma (HBCx-60). Prognostic impact of COX-2 mRNA expression level Low COX-2 expression and PIK3CA wild-type status allowed to identify patients with the worse MFS in the total cohort (p=0.0004, HR: 1.761 [1.289 to 2.405]) and among HR+ tumors (p= 0.0002, HR: 2.018 [1.397 to 2.914]) (Figure 3A and 3B). Given the limited number of triple-negative and HR-ERBB2+ cases, it was not appropriate to evaluate the prognostic impact of COX-2 expression according to the PIK3CA status in these two subtypes. (Figure 2B). COX-2 expression level had no impact on MFS in the PIK3CA mutated patients’ subgroup (Figure 2C). However in the PIK3CA wild-type patients’ subgroup MFS was significantly better in patients with high COX- 2 expression as compared to patients with low COX-2 expression (p=0.01, HR 1.617 [1.113-2.350]) (Figure 2C). Interestingly, the same result was observed in HR+ tumors where PIK3CA mutations are clearly associated with good prognosis (p=0.0004, HR 2.377 [1.473-3.835]) [35–37]. Patients with high COX-2 expression and PIK3CA wild- type had a similar MFS as PIK3CA mutated patients (p=0.07, HR 1.717 [0.9458-3.116]) (Figure 2D). Low COX-2 expression and PIK3CA wild-type status allowed to identify patients with the worse MFS in the total cohort (p=0.0004, HR: 1.761 [1.289 to 2.405]) and among HR+ tumors (p= 0.0002, HR: 2.018 [1.397 to 2.914]) (Figure 3A and 3B). Given the limited number of triple-negative and HR-ERBB2+ cases, it was not appropriate to evaluate the prognostic impact of COX-2 expression according to the PIK3CA status in these two subtypes. off determined as described in material and methods section) was observed (p=0.05) (Table 4). This trend became statistically significant when evaluating the prognostic impact of low COX-2 expression for the complete follow-up delay of this cohort (p=0.007) (Figure 2A). Multivariate analysis (Cox proportional hazards model) was also used to assess the influence of COX-2 mRNA level on MFS, together with histological grade, lymph-node status, tumor size, estrogen and progesterone receptor status and PIK3CA mutations. Lymph node status >3 (p=0.02), SBR grade III (p=0.04), tumor size >25mm (p=0.02) and low COX-2 mRNA expression (p=0.01) were statistically associated with poor prognosis (Supplementary Table S1). Prognostic impact of COX-2 mRNA expression level The characteristics of the 446 breast tumors according to the individual COX-2 mRNA level are shown in Table 3. Age of patients, SBR histological grade, lymph node status, tumor size and Ki67 mRNA expression were not statistically different in patients with different COX-2 expression levels. Hormone receptor status was the only parameter associated with COX-2 mRNA level (ERα: p<10-4; PR: p=0.0016) (Table 3). SBR grade (p=1.5.10-4), lymph node status (p=1.9.10-3), tumor size (p=1.4.10-5), ER (p=8.4.10-6) and PR (p=8.6.10-6) status as well as PIK3CA mutations (p=0.02) all had prognostic value as measured by the 5-years MFS. A trend towards a worse MFS among patients with low COX-2 expression (using optimal cut- www.impactjournals.com/oncotarget Oncotarget 85127 off determined as described in material and methods section) was observed (p=0.05) (Table 4). This trend became statistically significant when evaluating the prognostic impact of low COX-2 expression for the complete follow-up delay of this cohort (p=0.007) (Figure 2A). Multivariate analysis (Cox proportional hazards model) was also used to assess the influence of COX-2 mRNA level on MFS, together with histological grade, lymph-node status, tumor size, estrogen and progesterone receptor status and PIK3CA mutations. Lymph node status >3 (p=0.02), SBR grade III (p=0.04), tumor size >25mm (p=0.02) and low COX-2 mRNA expression (p=0.01) were statistically associated with poor prognosis (Supplementary Table S1). COX-2 expression presents a prognostic value in PIK3CA wild-type patients We then assessed the prognostic impact of COX-2 (Figure 2B). COX-2 expression level had no impact on MFS in the PIK3CA mutated patients’ subgroup (Figure 2C). However in the PIK3CA wild-type patients’ subgroup MFS was significantly better in patients with high COX- 2 expression as compared to patients with low COX-2 expression (p=0.01, HR 1.617 [1.113-2.350]) (Figure 2C). Interestingly, the same result was observed in HR+ tumors where PIK3CA mutations are clearly associated with good prognosis (p=0.0004, HR 2.377 [1.473-3.835]) [35–37]. Patients with high COX-2 expression and PIK3CA wild- type had a similar MFS as PIK3CA mutated patients (p=0.07, HR 1.717 [0.9458-3.116]) (Figure 2D). Low COX-2 expression and PIK3CA wild-type status allowed to identify patients with the worse MFS in the total cohort (p=0.0004, HR: 1.761 [1.289 to 2.405]) and among HR+ tumors (p= 0.0002, HR: 2.018 [1.397 to 2.914]) (Figure 3A and 3B). Prognostic impact of COX-2 mRNA expression level Given the limited number of triple-negative and HR-ERBB2+ cases, it was not appropriate to evaluate the prognostic impact of COX-2 expression according to Table 2: Correlation between COX-2 mRNA and COX-2 protein expression level on 14 PDX samples samples ID COX-2 mRNA expression COX-2 protein expression positive cells (%) staining intensity HBCx-10 0 negative 0 0 HBCx-51 0 negative 0 0 HBCx-22 1 negative 0 0 HBCx-28 7 negative 0 0 HBCx-43 26 negative 0 0 HBCx-16 38 negative 0 0 HBCx-49 38 positive (weak) 1 3 HBCx-30 39 positive (weak) <1 2 HBCx-4Bb 218 positive (moderate) 15 2 to 3 HBCx-23 264 positive (moderate) 5 3 HBCx-8 339 positive (high) 50 2 to 3 HBCx-60a 504 HBCx-52b 579 positive (high) 60 2 to 3 HBCx-15 658 positive (moderate) 15 2 to 3 aCorresponding to metaplastic carcinoma case. bCorresponding to PDX selected for in vivo experiments. Table 2: Correlation between COX-2 mRNA and COX-2 protein expression level on 14 PDX samples samples ID COX-2 mRNA expression COX-2 protein expression positive cells (%) staining intensity HBCx-10 0 negative 0 0 HBCx-51 0 negative 0 0 HBCx-22 1 negative 0 0 HBCx-28 7 negative 0 0 HBCx-43 26 negative 0 0 HBCx-16 38 negative 0 0 HBCx-49 38 positive (weak) 1 3 HBCx-30 39 positive (weak) <1 2 HBCx-4Bb 218 positive (moderate) 15 2 to 3 HBCx-23 264 positive (moderate) 5 3 HBCx-8 339 positive (high) 50 2 to 3 HBCx-60a 504 HBCx-52b 579 positive (high) 60 2 to 3 HBCx-15 658 positive (moderate) 15 2 to 3 aCorresponding to metaplastic carcinoma case. bCorresponding to PDX selected for in vivo experiments. orrelation between COX-2 mRNA and COX-2 protein expression level on 14 PDX samples p g p bCorresponding to PDX selected for in vivo experiments. (Figure 2B). COX-2 expression level had no impact on MFS in the PIK3CA mutated patients’ subgroup (Figure 2C). However in the PIK3CA wild-type patients’ subgroup MFS was significantly better in patients with high COX- 2 expression as compared to patients with low COX-2 expression (p=0.01, HR 1.617 [1.113-2.350]) (Figure 2C). Interestingly, the same result was observed in HR+ tumors where PIK3CA mutations are clearly associated with good prognosis (p=0.0004, HR 2.377 [1.473-3.835]) [35–37]. Patients with high COX-2 expression and PIK3CA wild- type had a similar MFS as PIK3CA mutated patients (p=0.07, HR 1.717 [0.9458-3.116]) (Figure 2D). COX-2 expression presents a prognostic value in PIK3CA wild-type patients We then assessed the prognostic impact of COX-2 expression depending on the PIK3CA mutational status in the cohort of 446 patients. Independently of the subtype of BC and adjuvant treatment received (chemotherapy, hormone therapy, both or none) MFS was significantly better in patients with high COX-2 expression (p=0.007, HR 1.560 [1.130-2.153]) (Figure 2A) and in patients with PIK3CA mutations (p=0.02, HR 1.455 [1.058-2.002]) COX-2 expression and PIK3CA mutational status did not impact overall survival (OS) in this cohort with very long follow-up (Supplementary Figure S2). In the TCGA validation set, high COX-2 expression was associated with a better DFS (p=0.0014, HR 2.206 [1.356-3.587]) and PIK3CA mutations did not have www.impactjournals.com/oncotarget cInformation available for 437 patients www.impactjournals.com/oncotarget Oncotarget 85129 teristics of the 446 primary breast tumors and relation to metastasis-free survival Table 4: Characteristics of the 446 primary breast tumors and relation to metastasis-free survival Number of patients 5 years MFS p valuea Total 446 72.6% Age ≤50 94 70.6% 0.33 >50 352 74.6% SBR histological gradeb,c I 57 92.4% 1.5.10-4f II 223 76% III 157 64.2% Lymph node statusd 0 118 79.4% 1.9.10-3f 1-3 232 76.5% >3 92 59.2% Macroscopic tumor sizee ≤25 220 82.9% 1.4.10-5 >25 218 64.1% ERα Negative 115 60.2% 8.4.10-6 Positive 331 78.3% PR Negative 190 63.5% 8.6.10-6 Positive 256 81.3% ERBB2 Negative 353 75.1% 0.11 Positive 93 68.5% Subgroups HR-ERBB2- 68 61.4% 1.5.10-5f HR-ERBB2+ 42 53.8% HR+ERBB2- 285 78.3% HR+ERBB2+ 51 81% PIK3CA status wild type 298 70.4% 0.02 mutated 148 80.2% COX-2 expression ≤0.22 294 70.6% 0.05 >0.22 152 80.1% aLog-rank test.i umors and relation to metastasis-free survival mber of patients 5 years MFS p valuea 446 72.6% 94 70.6% 0.33 352 74.6% 57 92.4% 1.5.10-4f 223 76% 157 64.2% 118 79.4% 1.9.10-3f 232 76.5% 92 59.2% 220 82.9% 1.4.10-5 218 64.1% 115 60.2% 8.4.10-6 331 78.3% 190 63.5% 8.6.10-6 256 81.3% 353 75.1% 0.11 93 68.5% 68 61.4% 1.5.10-5f 42 53.8% 285 78.3% 51 81% 298 70.4% 0.02 148 80.2% 294 70.6% 0.05 152 80.1% mber of patients 5 years MFS p valuea 446 72.6% 94 70.6% 0.33 352 74.6% 57 92.4% 1.5.10-4f 223 76% 157 64.2% 118 79.4% 1.9.10-3f 232 76.5% 92 59.2% 220 82.9% 1.4.10-5 218 64.1% 115 60.2% 8.4.10-6 331 78.3% 190 63.5% 8.6.10-6 256 81.3% 353 75.1% 0.11 93 68.5% 68 61.4% 1.5.10-5f 42 53.8% 285 78.3% 51 81% 298 70.4% 0.02 148 80.2% 294 70.6% 0.05 152 80.1% Total Age ≤50 >50 SBR histological gradeb,c I II III Lymph node statusd 0 1-3 >3 Macroscopic tumor sizee ≤25 >25 ERα Negative Positive PR Negative Positive ERBB2 Negative Positive Subgroups HR-ERBB2- HR-ERBB2+ HR+ERBB2- HR+ERBB2+ PIK3CA status wild type mutated COX-2 expression ≤0.22 Total Age ≤50 >50 SBR histological gradeb,c I II III Lymph node statusd 0 1-3 >3 Macroscopic tumor sizee ≤25 >25 ERα Negative Positive PR Negative Positive ERBB2 Negative Positive Subgroups HR-ERBB2- HR-ERBB2+ HR+ERBB2- HR+ERBB2+ PIK3CA status wild type mutated COX-2 expression ≤0.22 >0 22 www.impactjournals.com/oncotarget www.impactjournals.com/oncotarget Oncotarget 85128 Table 3: Relationship between COX-2 transcript expression level and classical clinical and biological parameters in a series of 446 breast cancers p p p g p series of 446 breast cancers Total population (%) Number of patients (%) p valuea COX-2 mRNA expression <0.3 relative to normals COX-2 mRNA expression >0.3 relative to normals Total 446 (100) 332 (74.4) 114 (25.6) Age ≤50 94 (21.1) 67 (71.3) 27 (28.7) 0.59 >50 352 (78.9) 261 (74.1) 91 (25.9) SBR histological gradeb,c I 57 (13) 43 (75.4) 14 (24.6) 0.36 II 223 (51) 172 (77.1) 51 (22.9) III 157 (35.9) 111 (71) 46 (29) Lymph node statusd 0 118 (26.5) 89 (75.4) 29 (24.6) 0.69 1-3 232 (52.1) 169 (72.8) 63 (27.2) >3 92 71 (77.2) 21 (22.8) Macroscopic tumor sizee ≤25 220 (50.2) 166 (75.4) 54 (24.6) 0.62 >25 218 (49.8) 160 (73.4) 58 (26.6) ERα Negative 115 (25.8) 64 (55.6) 51 (44.4) <10-4 Positive 331 (74.2) 264 (79.7) 67 (20.3) PR Negative 190 (42.6) 125 (65.8) 65 (34.2) 0.0016 Positive 256 (57.4) 203 (79.3) 53 (20.7) ERBB2 Negative 353 (79.1) 263 (74.5) 90 (25.5) 0.95 Positive 93 (20.9) 69 (74.2) 24 (25.8) Subgroups HR-ERBB2- 68 (15.2) 32 (47) 36 (53) <10-4 HR-ERBB2+ 42 (9.4) 28 (66.7) 14 (33.3) HR+ERBB2- 285 (63.9) 231 (81.4) 54 (18.6) HR+ERBB2+ 51 (11.4) 41 (80.4) 10 (19.6) PIK3CA status Wild type 298 (66.8) 208 (69.8) 90 (30.2) <10-4 Mutated 148 (33.2) 120 (81) 28 (19) Ki67 mRNA expression Median 12.4 (0.80-117) 12 (0.80-117) 13.2 (1.05-94.5) 0.42f EGFR mRNA expression Median 0.22 (0-106) 0.17 (0.02-7.56) 0.47 (0-106) <10-4f Metastasis No 282 (63.2) 198 (70) 84 (30) <10-4 Yes 164 (36.8) 134 (82) 30 (18) aChi2 test bScarff bloom Richardson classification. www.impactjournals.com/oncotarget www.impactjournals.com/oncotarget Oncotarget 85130 Oncot 85131 ww.impactjournals.com/oncotarget Figure 2: Prognostic value of COX-2 mRNA expression and PIK3CA mutations on patients’ metastasis-free surviv Kaplan-Meier estimates of metastasis-free survival according to COX-2 mRNA expression. B. Kaplan-Meier estimates of metastas survival according to PIK3CA mutations. C. Kaplan-Meier estimates of metastasis-free survival according to COX-2 mRNA expressi PIK3CA mutations in the global cohort. wt for wild-type, mut for mutated. D. Kaplan-Meier estimates of metastasis-free survival acc to COX-2 mRNA expression and PIK3CA mutations in HR+ patients. Figure 2: Prognostic value of COX-2 mRNA expression and PIK3CA mutations on patients’ metastasis-free survival. A. Kaplan-Meier estimates of metastasis-free survival according to COX-2 mRNA expression. B. Kaplan-Meier estimates of metastasis-free survival according to PIK3CA mutations. C. Kaplan-Meier estimates of metastasis-free survival according to COX-2 mRNA expression and PIK3CA mutations in the global cohort. wt for wild-type, mut for mutated. D. Kaplan-Meier estimates of metastasis-free survival according to COX-2 mRNA expression and PIK3CA mutations in HR+ patients. www.impactjournals.com/oncotarget www.impactjournals.com/oncotarget Oncotarget 85131 ostic value of low COX-2 mRNA expression and wild-type PIK3CA status vers tastasis and disease free survival A Kaplan Meier estimates of metastasis free surviv O 8 132 i tj l / t t Figure 3: Prognostic value of low COX-2 mRNA expression and wild-type PIK3CA status versus other subgro on patients’ metastasis and disease-free survival. A. Kaplan-Meier estimates of metastasis-free survival according to CO mRNA expression and PIK3CA mutations in the global cohort. B. Kaplan-Meier estimates of metastasis-free survival according to CO mRNA expression and PIK3CA mutations in HR+ patients. C. Kaplan-Meier estimates of disease-free survival according to COX-2 mR expression and PIK3CA mutations in the global TCGA cohort. D. Kaplan-Meier estimates of disease-free survival according to CO mRNA expression and PIK3CA mutations in HR+ patients. “Other” refers to low COX-2 PIK3CA mutated tumors and high COX-2 PIK3 wild-type and mutated tumors. Figure 3: Prognostic value of low COX-2 mRNA expression and wild-type PIK3CA status versus other subgroups on patients’ metastasis and disease-free survival. A. Kaplan-Meier estimates of metastasis-free survival according to COX-2 mRNA expression and PIK3CA mutations in the global cohort. B. Kaplan-Meier estimates of metastasis-free survival according to COX-2 mRNA expression and PIK3CA mutations in HR+ patients. C. Kaplan-Meier estimates of disease-free survival according to COX-2 mRNA expression and PIK3CA mutations in the global TCGA cohort. D. Kaplan-Meier estimates of disease-free survival according to COX-2 mRNA expression and PIK3CA mutations in HR+ patients. www.impactjournals.com/oncotarget “Other” refers to low COX-2 PIK3CA mutated tumors and high COX-2 PIK3CA wild-type and mutated tumors. ue of low COX-2 mRNA expression and wild-type PIK3CA status versus other subgroups www.impactjournals.com/oncotarget Oncotarget 85132 prognostic impact on DFS (Supplementary Figures S3A and S3B). After combination of these two parameters, COX-2 expression level did not have prognostic impact in PIK3CA wild-type patients but high COX-2 level expression was associated with a better DFS among mutated patients (p=0.0007, HR 4.667 [1.917-11.36]) (Supplementary Figure 3C). In the luminal subtype, high COX-2 expression was associated with a better DFS (p=0.012, HR 2.682 [1.243-5.785]) and PIK3CA mutations did not have prognostic impact on DFS (data not shown). Among PIK3CA wild-type patients, high COX-2 patients had a better DFS than low COX-2 patients (p=0.012, HR 3.206 [1.287-7.984]) (Supplementary Figure S3D). In contrast, in the PIK3CA wild-type model (HBCx- 52) no significant difference in RTV was observed between the treated and control groups (day 25, p=0.94) (Figure 4B). HBCx-4B and HBCx-52 PDX models both express high COX-2 mRNA level and COX-2 protein (Table 2). However antitumoral effect was observed in HBCx-4B model only. We can therefore ascertain that celecoxib had no effect on the tumor growth in tumors expressing COX- 2 and PIK3CA wild-type. Antitumoral effect of celecoxib in PIK3CA mutated tumors involves phosphorylation of PI3K/AKT pathway main actors Similarly to Institut Curie BC cohort, low COX- 2 expression and PIK3CA wild-type status allowed to identify TCGA patients with the worse DFS in the entire cohort (trend, p=0.105, HR: 1.584 (0.9090 to 2.758) and among HR+ tumors (p=0.024, HR: 2.698 [1.142 to 6.376]) (Figure 3C and 3D). Western-blot analysis in both PDX showed a significant decrease of COX-2 expression in the celecoxib treated group compared to controls (p=0.018 for HBCx-4B and p=0.02 for HBCx-52) confirming the pharmacological effect of this molecule. Celecoxib treatment did not affect angiogenesis as shown by the MVD assays in treated and control tumors of both PDX models (Table 5). In the TCGA BC cohort overall survival data showed a better prognosis for high COX-2 patients (p=0.0011, HR 2.452 [1.428-4.208] but not for PIK3CA mutated patients (Supplementary Figure S4A and S4B). Among wild-type PIK3CA patients, high COX-2 patients had a better overall survival than low COX-2 patients (p=0.018, HR 2.183 [1.146-4.157]). The same significant difference was observed in PIK3CA mutated patients (p=0.015, HR 3.494 [1.273-9.592]) (Supplementary Figure S4C). In the luminal subtype, high COX-2 expression was associated with a better OS (p=0.0051, HR 1.831 [0.999-3.357]) and PIK3CA mutations did not have a prognostic impact on OS (data not shown). Among mutated PIK3CA patients, high COX-2 patients had a better overall survival than low COX-2 patients (p=0.023, HR 3.206 [1.177-8.734]) (Supplementary Figure S4D). In the HBCx-4B responder model, exploration of the PI3K pathway showed a significant decrease of S6 ribosomal protein phosphorylation in the treated group compared to controls (p=0.0003) (Figure 5A). We observed a significant increase in the expression of this phospho-protein in two tumors, which progressed under celecoxib as compared to responders (p=0.02) (Figure 5A). These two non-responder tumors showed also a significant increase of AKT phosphorylation by comparison to responders (p=0.02) (Figure 5A). In HBCx-52 similar phosphorylation levels of S6 ribosomal protein and AKT were observed in controls and treated tumors (Figure 5B). PTEN, another major component of the PI3K/AKT pathway, was not differentially expressed in these two PDX models. INPP4B expression was lost in the HBCx- 4B responder model but also in several HBCx-52 tumors (Figure 5A and 5B). Celecoxib antitumoral effect is only observed in breast tumor harboring a PIK3CA mutation Since COX-2 overexpression was associated with TNBC subtype, we chose triple-negative PDX to investigate celecoxib antitumoral effect. Moreover there is a need for targeted therapies in TNBC. DISCUSSION In BC, COX-2 expression level and its prognostic value have been controversial for several decades. In the present study, we observed an overexpression of COX- 2 only in a small percentage of BCs, predominantly belonging to the triple-negative subtype. More importantly the under-expression of COX-2 is an independent pejorative prognostic factor. Low COX-2 and PIK3CA wild-type status was identified as the worse prognostic factor for MFS in our cohort and confirmed for DFS in an independent validation set. g p In the PIK3CA mutated TNBC PDX model (HBCx- 4B) a significant reduction in tumor volume (RTV) was observed in mice receiving celecoxib as compared to control mice from day 22 (p=0.03) and until the end of the experiment (day 61, TGI=57%, p=0.01) (Figure 4A). These results clearly showed that celecoxib induced a significant antitumor effect in tumors expressing COX-2 and harboring a PIK3CA mutation [31]. The TGI obtained with celecoxib in this model was near to the 60% proposed by Wang et al. as a cut-off for mice xenografts likely to lead to a positive clinical outcome [38]. Of note celecoxib is not a chemotherapy and was given as monotherapy in this experiment. Several published studies reported variable expression levels of COX-2 in BCs but most of them assessed COX-2 expression at the protein level. In the present study, we applied qRT-PCR on RNA extracted www.impactjournals.com/oncotarget Oncotarget 85133 l / t t fect of celecoxib on tumor growth of HBCx-4B and HBCx-52 PDX. Tumor growth was evaluated by e RTV±SD over time. A. HBCx-4B bearing mice were treated with celecoxib (n=18), (40 mg/kg per os daily fiv s (n=20) received MCT (methylcellulose 5% and 0,2% tween per os daily five times a week). B. HBCx-52 bear th celecoxib (n=6), (40 mg/kg per os daily five times a week). Controls (n=7) received MCT (per os daily five times Figure 4: Effect of celecoxib on tumor growth of HBCx-4B and HBCx-52 PDX. Tumor growth was evaluated by plotting the mean of the RTV±SD over time. A. HBCx-4B bearing mice were treated with celecoxib (n=18), (40 mg/kg per os daily five times a week). Controls (n=20) received MCT (methylcellulose 5% and 0,2% tween per os daily five times a week). B. HBCx-52 bearing mice were treated with celecoxib (n=6), (40 mg/kg per os daily five times a week). Controls (n=7) received MCT (per os daily five times a week). DISCUSSION using qRT-PCR found in 40 infiltrating carcinomas and 40 matched adjacent non-cancerous tissue (ANCT) that COX-2 mRNA copy number per µg of RNA was two- fold higher in ANCT compared to the cancerous tissue (p=0.01) [42]. Using the robust and reproductive tool of qRT-PCR, our results are therefore similar to the above reports and confirm that COX-2 mRNA overexpression is not a hallmark in all BCs. cell but also in stromal cell using different antibodies and scoring algorithms. Although they showed that COX-2 expression in stromal cells and not in epithelial cells is an independent adverse prognostic factor and is relatively insensitive to variations of antibodies used, they finally explained the variability of published results by the use of different antibodies and scoring algorithms [45]. So we prefer to remain cautious about the IHC results and it should be reminded that our conclusions concerning the prognostic value of COX-2 expression is based on COX-2 mRNA expression level. Published results concerning the changes of COX- 2 protein expression during the disease progression and its prognostic significance are contradictory, even in the groups working with the same type of primary antibodies [45]. Miglietta et al. published that COX- 2 immune positivity and percentage of positive cells correlated significantly with the size, grading, extent of primary tumor and vascular invasion of carcinoma but not with biological parameters (HR and ERBB2 status). Nevertheless, for Park et al. there was no significant association between COX-2 over-expression and tumor size, histologic grade, and estrogen receptor expression [46, 47]. In the work of Kim et al. COX-2 positivity was significantly correlated with high grade, negative ER, high Ki67, luminal B and triple-negative tumors [48].i To the best of our knowledge we conducted the first COX-2 mRNA expression prognostic impact study in a large cohort of BC patients. Under-expression of COX- 2 transcript was associated with poor prognosis and HR status but was not with other classical criteria like high grade, tumor size or lymph node status. Multivariate analysis showed that COX-2 under-expression, high grade, higher tumor size and lymph node involvement were predictive of poor prognosis. COX-2 under- expression should be thus considered as an independent poor prognostic factor. Moreover this under expression combined with a PIK3CA wild-type status allowed to identify a poor prognosis subgroup of patients who might benefit from more intensive treatment regimens. DISCUSSION Figure 4: Effect of celecoxib on tumor growth of HBCx-4B and HBCx-52 PDX. Tumor growth was evaluated by plotting the mean of the RTV±SD over time. A. HBCx-4B bearing mice were treated with celecoxib (n=18), (40 mg/kg per os daily five times a week). Controls (n=20) received MCT (methylcellulose 5% and 0,2% tween per os daily five times a week). B. HBCx-52 bearing mice were treated with celecoxib (n=6), (40 mg/kg per os daily five times a week). Controls (n=7) received MCT (per os daily five times a week). Oncotarget 85134 Table 5: Assessment of celecoxib treatment on angiogenesis (microvessel density) performed by ERG immunostaining control group celecoxib-treated group p valuec HBCx-52 40.4 ± 5.8 33.8 ± 9.0 p=0.35 HBCx-4B 23.5 ± 3.4 16.7 ± 3.0a p=0.058 18.1 ± 2.2b p=0.14 Results are expressed as the mean (+/− SD) of the number of blood vessels by mm2 aResponders tumors bNon-responders tumors cT-test ssessment of celecoxib treatment on angiogenesis (microvessel density) performed by ERG aining from a large cohort of samples all infiltrated with more than 70% of tumor cells to assess COX-2 expression. With the exception of few cases in triple-negative subtype, we showed that the majority of BCs under-express COX- 2 mRNA or express COX-2 mRNA at a similar level to normal breast tissue. Few studies assessed COX-2 mRNA expression level. Contrary to our results, several authors found an overexpression of COX-2 mRNA in BC tissues when compared to benign breast lesions [39] or breast normal tissues [2, 40]. All these results were obtained using qualitative RT-PCR in very small cohorts of BCs (13, 10 and 9 cases), which might explain the discrepancy. One report by McCarthy et al. using qRT-PCR, showed that the median COX-2 mRNA expression in 45 primary invasive BC samples was not significantly different as compared to the median COX-2 mRNA expression in 22 normal breast tissues [41]. These authors also showed that COX-2 mRNA levels were significantly higher in estrogen (p < 0.02) and progesterone (p < 0.0001) receptor negative tumors but they did not assess the ERBB2 status of the tumors and consequently no conclusions can be drawn as for the level of mRNA expression of COX-2 in the triple- negative subtype [41]. According to our results Kirkpatrick et al. DISCUSSION This result was confirmed with the DFS analysis in a TCGA validation cohort. High COX-2 expression is significantly We have demonstrated a good correlation between COX-2 mRNA and protein level suggesting that we would expect to find the same minority overexpressed cases with an IHC-based study. This result was obtained by examining few cases using IHC and is contradictory with the majority of published studies describing COX- 2 overexpression in invasive BCs [8, 11, 40, 43] but not all [44]. Like the majority of these studies we focused on COX-2 expression in epithelial cells and did not examine stroma. Recently Urban et al. analyzed the prognostic value of COX-2 expression not only in breast epithelial www.impactjournals.com/oncotarget Oncotarget 85135 gure 5: Analysis of tumors. A. Western-blot analysis of COX-2, phospho-AKT, phospho-S6 ribosomal protein, PTEN and INPP HBCx-4B control mice (n=6) and celecoxib treated mice: responders (n=6) and non-responders (n=2). B. Western-blot analysis of CO phospho-AKT, phospho-S6 ribosomal protein, PTEN and INPP4B in HBCx-52 control mice (n=7) and celecoxib treated mice (n= APDH served as loading control. One representative blot is presented for each model. The densitometric analysis is the mean ± SE =3 experiments). For statistical analysis, treated group was compared with controls, and responders compared with non-responders .05 and **P < 0.001. Figure 5: Analysis of tumors. A. Western-blot analysis of COX-2, phospho-AKT, phospho-S6 ribosomal protein, PTEN and INPP4B in HBCx-4B control mice (n=6) and celecoxib treated mice: responders (n=6) and non-responders (n=2). B. Western-blot analysis of COX- 2, phospho-AKT, phospho-S6 ribosomal protein, PTEN and INPP4B in HBCx-52 control mice (n=7) and celecoxib treated mice (n=6). GAPDH served as loading control. One representative blot is presented for each model. The densitometric analysis is the mean ± SEM. (n=3 experiments). For statistical analysis, treated group was compared with controls, and responders compared with non-responders. P < 0.05 and **P < 0.001. Figure 5: Analysis of tumors. A. Western-blot analysis of COX-2, phospho-AKT, phospho-S6 ribosomal protein, PTEN and INPP4B in HBCx-4B control mice (n=6) and celecoxib treated mice: responders (n=6) and non-responders (n=2). B. Western-blot analysis of COX- 2, phospho-AKT, phospho-S6 ribosomal protein, PTEN and INPP4B in HBCx-52 control mice (n=7) and celecoxib treated mice (n=6). GAPDH served as loading control. One representative blot is presented for each model. The densitometric analysis is the mean ± SEM. (n=3 experiments). Patients Samples of 446 primary breast tumor, excised from women treated at Institut Curie - Hôpital René Huguenin (Saint-Cloud, France) from 1978 to 2008, have been analyzed. All patients treated at Institut Curie before 2007 were informed that their tumor samples might be used for scientific purposes and had the opportunity to decline. Since 2007, patients treated at Institut Curie have given their approval by signing an informed consent. This study was approved by the local ethics committee (Breast Group of René Huguenin Hospital). The samples were immediately stored in liquid nitrogen until RNA extraction. A tumor sample was considered suitable for this study if the proportion of tumor cells exceeded 70%. p p In accordance with the observations made by Liao et al. in colorectal cancer, our in vivo PDX experiments showed that celecoxib antitumoral effect was restricted to PIK3CA mutated breast tumors. PIK3CA status has never been explored in BC clinical trials assessing concomitant administration of exemestane or chemotherapy with celecoxib. Our findings led to the hypothesis that the negative results of these clinical trials might come from the fact that patients were not selected according to tumor PIK3CA status. Consequently a retrospective analysis of results of these trials regarding PIK3CA status could be very interesting. Eventually, new prospective trials combining celecoxib with hormone therapy or chemotherapy may screen patients for tumor PIK3CA mutations to confirm its predictive value. It is also important to underline that our in vivo experiments were done with TNBC PDX whereas clinical trials were designed for luminal BCs. We cannot exclude that in this subtype of BCs some other unknown factors could interact negatively with antitumoral properties of celecoxib. All patients (mean age 61.8 years, range 31 – 91 years) met the following criteria: primary unilateral non metastatic breast carcinoma for which complete clinico- pathological data and follow-up were available; no radiotherapy or chemotherapy before surgery; and full follow-up at Institut Curie - Hôpital René Huguenin. Adjuvant therapy was administered to 361 patients, consisting of chemotherapy alone in 87, hormone therapy alone in 175, and both treatments in 99 patients. p Estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (ERBB2) statuses were determined at the protein level by using biochemical methods (Dextran-coated charcoal method, enzyme immunoassay or immunohistochemistry) and confirmed by real-time quantitative RT-PCR assays [22, 23]. Patients The population was divided into 4 groups according to HR (ER and PR) and ERBB2 status as follows: two luminal subtypes [HR+ (ERα+ or PR+)/ERBB2+ (n=51)], and [HR+ (ERα+ or PR+)/ERBB2- (n=285)]; an ERBB2+ subtype [HR- (ERα- and PR-)/ERBB2+ (n=42)]; and a triple-negative subtype [HR- (ERα- and PR-)/ERBB2- (n=68)]. Standard prognostic factors are shown in Table 3. Within a median follow-up of 8.6 years (range 6 months to 29 years), 164 patients developed distant metastasis. Ten specimens of adjacent normal breast tissue from BC patients (n=2) and normal breast tissue from women undergoing cosmetic breast surgery (n=8) were used as sources of normal RNA [24]. There were two non-responders tumors in our PIK3CA mutated PDX model. The protein expression analysis on collected tumor xenografts revealed an increase of AKT phosphorylation in these two tumors. In ovarian tumors and MCF-7 breast tumor cell line COX-2 overexpression is associated with an increase of AKT phosphorylation [50, 51], which might explain resistance to celecoxib in both tumors. Antitumoral effect of celecoxib is associated with the inactivation of PI3K/ AKT pathway as observed with the decrease of S6 kinase phosphorylation whereas secondary resistance is explained by AKT reactivation. In conclusion, treatment with celecoxib may be an additional therapeutic option for patients with BCs expressing COX-2 protein and mutated for PIK3CA whatever the level of COX-2 mRNA expression. Thus the detection of COX-2 protein should be the only pre- requisite criteria for mutated tumors treatment with celecoxib. Noteworthy, PIK3CA mutation screening and COX-2 IHC staining are very easy to implement in diagnostic laboratory and could be used routinely for patient selection. These results were obtained with two PDX models only and need to be validated in a clinical trial. In this way we note that no published clinical trials with celecoxib in BC patients reported cardiac toxicity restricting the use of this FDA approved NSAID so it should not be a limiting factor for future trials. Public data of 817 breast invasive carcinomas from TCGA were used as a validation set [25]. This cohort was obtained by using www.cbioportal.org. [26, 27]. The population was divided into 5 molecular subtypes: basal (n=136), ERBB2+ (n=65), luminal A (n=415), luminal B (n=176) and normal (n=25). Median follow-up was 25 months (range 0 – 281.1 months) and 28.9 months (range 0 - 282.7 months) for disease-free survival and overall survival respectively. DISCUSSION For statistical analysis, treated group was compared with controls, and responders compared with non-responders. P < 0.05 and **P < 0.001. Figure 5: Analysis of tumors. A. Western-blot analysis of COX-2, phospho-AKT, phospho-S6 ribosomal protein, PTEN and INPP4B in HBCx-4B control mice (n=6) and celecoxib treated mice: responders (n=6) and non-responders (n=2). B. Western-blot analysis of COX- 2, phospho-AKT, phospho-S6 ribosomal protein, PTEN and INPP4B in HBCx-52 control mice (n=7) and celecoxib treated mice (n=6). GAPDH served as loading control. One representative blot is presented for each model. The densitometric analysis is the mean ± SEM. (n=3 experiments). For statistical analysis, treated group was compared with controls, and responders compared with non-responders. P < 0.05 and **P < 0.001. www.impactjournals.com/oncotarget Oncotarget 85136 MATERIALS AND METHODS correlated with better OS of PIK3CA wild-type and mutated patients in the TCGA cohort but this result was not observed in our BC cohort with a longer median follow-up delay (8.6 years for the Curie cohort versus 28.9 months for the TCGA cohort). Interplays between COX-2 and the PI3K/AKT pathway have been already well described in colorectal cancer [49] but still need to be deciphered in BC to explain effects of their combination. Real-time RT-PCR Quantitative values were obtained from the cycle number (Ct value) at which the increase in the fluorescence signal associated with exponential growth of PCR products started to be detected by the laser detector of the ABI Prism 7900 Sequence Detection System (Perkin-Elmer Applied Biosystems, Foster City, CA), using PE Biosystems analysis software according to the manufacturer’s manuals. RNA extraction detected according to the ECL Western Blotting Analysis System procedure (GE Healthcare, Buckinghamshire, UK). The intensity of the protein bands was quantified using ImageJ software. Total RNA was extracted from breast tumor samples and PDX tumors by using acid-phenol guanidium as previously described [28]. RNA quality was determined by electrophoresis through agarose gels, staining with ethidium bromide, and visualization of the 18S and 28S RNA bands under ultraviolet light. Patients COX-2 mRNA expression is expressed in z-Scores (RNA Seq V2 RSEM (RNA-Seq by Expectation-Maximization)). www.impactjournals.com/oncotarget Oncotarget 85137 In vivo experiments In vivo studies were performed on female Swiss nude mice purchased from Charles River. Mice care and housing were conformed to the institutional guidelines as put forth by the French Ethical Committee. Human TNBC xenografted models were established as previously detailed [31, 32]. The effect of celecoxib (purchased from Pfizer) was evaluated in two PDX: HBCx-4B which presents a PIK3CA mutation and HBCx-52, wild-type for this gene, both expressing COX-2. A toxicity study was first performed on mice-bearing human BC xenografts which received 20 or 40 mg/kg of celecoxib by gavage five times a week. As no toxicity was observed, the dose of 40 mg/kg was retained for the next experiments. For HBCx- 52, a control group (n=7) received gavage with MCT (methylcellulose 5% + 0.2% tween) five times a week and the treated group received five times a week 40 mg/kg of celecoxib (n=6). For HBCx-4B, the same groups were established: a MCT control group (n=20) and a celecoxib treated group (n=20). Tumor growth was evaluated with a calliper twice a week. Tumor growth inhibition (TGI) of treated tumors versus controls was calculated as the ratio of the mean relative tumor volume (RTV) in the treated Primers’ sequences are available on request. Agarose gel electrophoresis was used to verify the specificity of PCR amplicons. The conditions of cDNA synthesis and PCR were previously described [22]. Assays for microvessel density (MVD) on tumor tissues The TBP gene (Genbank accession NM_003194) encoding the TATA box-binding protein (a component of the DNA-binding protein complex TFIID) was quantified as an endogenous RNA control, and each sample was normalized on the basis of its TBP content [22]. Microvessels in tumor tissues were immunostained using anti-ERG antibody (reference AC-0105, clone EP111, Abcam) on 14 xenografts (HBCx-4B, control tumors n=3, celecoxib treated tumors, n=5 (3 responders and 2 non-responders), HBCx-52, control tumors n=3, celecoxib treated tumors n=3). MVD was assessed according to a method adapted of Weidner et al., 1991 [30]. The entire tumor section was first observed at low- power magnification (40x) to select the most vascularized areas (hotspots). Individual microvessels, immunoreactive for ERG, were counted at high–power magnification (400x) within 10 consecutive fields. In each tumor tissue, the microvessel count was expressed by mm2. Results, expressed as N-fold differences in target gene expression relative to the TBP gene and termed “Ntarget”, were determined as Ntarget = 2ΔCtsample, where the ΔCt value of the sample was determined by subtracting the average Ct value of the target gene from the average Ct value of the TBP gene. The Ntarget values of the samples were subsequently normalized such that the median of the Ntarget values for the ten normal breast tissues was 1. In tumor samples values of 3 or more were therefore considered to represent overexpression, and values of 0.3 or less were considered to represent underexpression of the 10 quantifiable mRNAs, as in previous studies [22, 29] Immunohistochemical staining Patient and xenografted tumors were fixed in 10% neutral buffered formalin, paraffin embedded, and hematoxylin-eosin-saffron (HES) stained. The anti-COX-2 antibody (Dako reference M3617) and its isotypic control (Sigma reference F5636) were used on 26 primary breast tumors and 14 xenografted tumors. Staining (intensity and fraction of positive cells) was taken into consideration in the cytoplasm of epithelial cells only. Statistical analysis Statistical analyses were performed using GraphPad Prism 5 software. The data are expressed as the mean ± SEM. The results were considered statistically significant at a p-value <0.05 (), <0.01 (), or <0.001 (*). 5. Fornetti J, Jindal S, Middleton KA, Borges VF, Schedin P. Physiological COX-2 expression in breast epithelium associates with COX-2 levels in ductal carcinoma in situ and invasive breast cancer in young women. Am J Pathol. 2014; 184:1219-1229. Relationships between mRNA levels and clinical parameters were identified by using non parametric tests, namely the Chi-square test, Fischer’s test and the Mann- Whitney U test. Metastasis-free survival (MFS) was determined as the interval between initial diagnosis and detection of the first metastasis. Overall survival (OS) was determined as the interval between initial diagnosis and death of any cause. Survival distributions were estimated by the Kaplan-Meier method, and the significance of differences between survival rates was ascertained with the log- rank test. The optimal cut-off value for COX-2 mRNA expression prognostic value was determined with the AUC-ROC analysis defining “high” COX-2 mRNA expression >0.22 and “low” COX-2 mRNA expression <0.22. The Cox proportional hazards regression model was used to assess prognostic significance in the multivariate analysis and the results are presented as hazard ratios and 95% confidence intervals (CIs). 6. van Nes JG, de Kruijf EM, Faratian D, van de Velde CJ, Putter H, Falconer C, Smit VT, Kay C, van de Vijver MJ, Kuppen PJ, Bartlett JM. COX2 expression in prognosis and in prediction to endocrine therapy in early breast cancer patients. Breast Cancer Res Treat. 2011; 125:671-685. 7. Denkert C, Winzer KJ, Muller BM, Weichert W, Pest S, Kobel M, Kristiansen G, Reles A, Siegert A, Guski H, Hauptmann S. Elevated expression of cyclooxygenase-2 is a negative prognostic factor for disease free survival and overall survival in patients with breast carcinoma. Cancer. 2003; 97:2978-2987. 8. Ristimaki A, Sivula A, Lundin J, Lundin M, Salminen T, Haglund C, Joensuu H, Isola J. Prognostic significance of elevated cyclooxygenase-2 expression in breast cancer. Cancer Res. 2002; 62:632-635. GRANT SUPPORT 13. Alshafie GA, Abou-Issa HM, Seibert K, Harris RE. Chemotherapeutic evaluation of Celecoxib, a cyclooxygenase-2 inhibitor, in a rat mammary tumor model. Oncol Rep. 2000; 7:1377-1381. This work was supported by La Ligue contre le Cancer du département des Hauts-de-Seine (grants number WB2014-51) and SIRIC of Curie Institute (grants INCa- DGOS-4654). 14. Dai ZJ, Ma XB, Kang HF, Gao J, Min WL, Guan HT, Diao Y, Lu WF, Wang XJ. Antitumor activity of the selective cyclooxygenase-2 inhibitor, celecoxib, on breast cancer in Vitro and in Vivo. Cancer Cell Int. 2012; 12:53. CONFLICTS OF INTEREST 11. Koki AT, Masferrer JL. Celecoxib: a specific COX-2 inhibitor with anticancer properties. Cancer Control. 2002; 9:28-35. No potential conflicts of interest are reported by authors. 12. Thun MJ, Jacobs EJ, Patrono C. The role of aspirin in cancer prevention. Nat Rev Clin Oncol. 2012; 9:259-267. ACKNOWLEDGMENTS 9. Singh-Ranger G, Salhab M, Mokbel K. The role of cyclooxygenase-2 in breast cancer: review. Breast Cancer Res Treat. 2008; 109:189-198. We thank Martial Caly, Sophie Chateau-Joubert and Jean-Luc Servely for their technical assistance in IHC staining. We thank Rania El Botty for her technical assistance for western-blot. 10. Zerkowski MP, Camp RL, Burtness BA, Rimm DL, Chung GG. Quantitative analysis of breast cancer tissue microarrays shows high cox-2 expression is associated with poor outcome. Cancer Invest. 2007; 25:19-26. Western blot analysis Proteins were extracted from frozen tumors using RIPA buffer (50 mM Tris–HCl (pH 8), 150 mM NaCl, 0.5% deoxycholic acid, 0.5% triton) supplemented with protease and phosphatase inhibitors. Proteins were separated by SDS-PAGE and then electrophoretically transferred into nitrocellulose membrane and probed using the following primary antibodies: anti-GAPDH (V18 clone, 1/20000) purchased from Santa Cruz Biotechnology, anti-COX-2 (12282, 1/1000), anti- phospho Serin 473-AKT (4060, 1/2000), anti-PTEN (9552, 1/2000), anti-INPP4B (14543, 1/2000) and anti- phospho-S6 ribosomal protein (2211, 1/8000) purchased from Cell Signaling Technology (Ozyme). Proteins were www.impactjournals.com/oncotarget Oncotarget 85138 3. Brueggemeier RW, Quinn AL, Parrett ML, Joarder FS, Harris RE, Robertson FM. Correlation of aromatase and cyclooxygenase gene expression in human breast cancer specimens. Cancer Lett. 1999; 140:27-35. group to the mean RTV in the control group at the same time. Statistical significance of TGI was calculated using the paired Student t test comparing the individual RTVs in the treated and control groups. 4. Glover JA, Hughes CM, Cantwell MM, Murray LJ. A systematic review to establish the frequency of cyclooxygenase-2 expression in normal breast epithelium, ductal carcinoma in situ, microinvasive carcinoma of the breast and invasive breast cancer. Br J Cancer. 2011; 105:13-17. www.impactjournals.com/oncotarget REFERENCES A multicenter randomized phase II study of sequential epirubicin/cyclophosphamide followed by docetaxel with or without celecoxib or trastuzumab according to HER2 status, as primary chemotherapy for localized invasive breast cancer patients. Breast Cancer Res Treat. 2010; 122:429-437. 29. Bieche I, Onody P, Tozlu S, Driouch K, Vidaud M, Lidereau R. Prognostic value of ERBB family mRNA expression in breast carcinomas. Int J Cancer. 2003; 106:758-765. 30. Weidner N, Semple JP, Welch WR, Folkman J. Tumor angiogenesis and metastasis—correlation in invasive breast carcinoma. N Engl J Med. 1991; 324:1-8. 31. Marangoni E, Vincent-Salomon A, Auger N, Degeorges A, Assayag F, de Cremoux P, de Plater L, Guyader C, De Pinieux G, Judde JG, Rebucci M, Tran-Perennou C, Sastre- Garau X, et al. A new model of patient tumor-derived breast cancer xenografts for preclinical assays. Clin Cancer Res. 2007; 13:3989-3998. 19. Liao X, Lochhead P, Nishihara R, Morikawa T, Kuchiba A, Yamauchi M, Imamura Y, Qian ZR, Baba Y, Shima K, Sun R, Nosho K, Meyerhardt JA, et al. Aspirin use, tumor PIK3CA mutation, and colorectal-cancer survival. N Engl J Med. 2012; 367:1596-1606. 20. Paleari L, Puntoni M, Clavarezza M, DeCensi M, Cuzick J, DeCensi A. PIK3CA Mutation, Aspirin Use after Diagnosis and Survival of Colorectal Cancer. A Systematic Review and Meta-analysis of Epidemiological Studies. Clin Oncol (R Coll Radiol). 2015. 32. Reyal F, Guyader C, Decraene C, Lucchesi C, Auger N, Assayag F, De Plater L, Gentien D, Poupon MF, Cottu P, De Cremoux P, Gestraud P, Vincent-Salomon A, et al. Molecular profiling of patient-derived breast cancer xenografts. Breast Cancer Res. 2012; 14:R11. 21. Dumont AG, Dumont SN, Trent JC. The favorable impact of PIK3CA mutations on survival: an analysis of 2587 patients with breast cancer. Chin J Cancer. 2012; 31:327-334. 33. Cizkova M, Susini A, Vacher S, Cizeron-Clairac G, Andrieu C, Driouch K, Fourme E, Lidereau R, Bieche I. PIK3CA mutation impact on survival in breast cancer patients and in ERalpha, PR and ERBB2-based subgroups. Breast Cancer Res. 2012; 14:R28. 22. Bieche I, Onody P, Laurendeau I, Olivi M, Vidaud D, Lidereau R, Vidaud M. Real-time reverse transcription- PCR assay for future management of ERBB2-based clinical applications. Clin Chem. 1999; 45:1148-1156. 34. Meseure D, Vacher S, Drak Alsibai K, Trassard M, Susini A, Le Ray C, Lerebours F, Le Scodan R, Spyratos F, Marc Guinebretiere J, Lidereau R and Bieche I. REFERENCES 15. Bundred NJ, Cramer A, Morris J, Renshaw L, Cheung KL, Flint P, Johnson R, Young O, Landberg G, Grassby S, Turner L, Baildam A, Barr L, Dixon JM. Cyclooxygenase-2 inhibition does not improve the reduction in ductal carcinoma in situ proliferation with aromatase inhibitor therapy: results of the ERISAC 1. Smith WL, Dewitt DL. Prostaglandin endoperoxide H synthases-1 and -2. Adv Immunol. 1996; 62:167-215. 1. Smith WL, Dewitt DL. Prostaglandin endoperoxide H synthases-1 and -2. Adv Immunol. 1996; 62:167-215. 2. Parrett M, Harris R, Joarder F, Ross M, Clausen K, Robertson F. Cyclooxygenase-2 gene expression in human breast cancer. Int J Oncol. 1997; 10:503-507. www.impactjournals.com/oncotarget Oncotarget Oncotarget 85139 randomized placebo-controlled trial. Clin Cancer Res. 2010; 16:1605-1612. 26. Gao J, Aksoy BA, Dogrusoz U, Dresdner G, Gross B, Sumer SO, Sun Y, Jacobsen A, Sinha R, Larsson E, Cerami E, Sander C, Schultz N. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal. 2013; 6:pl1. 16. Generali D, Buffa FM, Deb S, Cummings M, Reid LE, Taylor M, Andreis D, Allevi G, Ferrero G, Byrne D, Martinotti M, Bottini A, Harris AL, Lakhani SR, Fox SB. COX-2 expression is predictive for early relapse and aromatase inhibitor resistance in patients with ductal carcinoma in situ of the breast, and is a target for treatment. Br J Cancer. 2014; 111:46-54. 27. Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, Jacobsen A, Byrne CJ, Heuer ML, Larsson E, Antipin Y, Reva B, Goldberg AP, Sander C, Schultz N. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2012; 2:401-404. 17. Dirix LY, Ignacio J, Nag S, Bapsy P, Gomez H, Raghunadharao D, Paridaens R, Jones S, Falcon S, Carpentieri M, Abbattista A, Lobelle JP. Treatment of advanced hormone-sensitive breast cancer in postmenopausal women with exemestane alone or in combination with celecoxib. J Clin Oncol. 2008; 26:1253-1259. 28. Bieche I, Parfait B, Le Doussal V, Olivi M, Rio MC, Lidereau R, Vidaud M. Identification of CGA as a novel estrogen receptor-responsive gene in breast cancer: an outstanding candidate marker to predict the response to endocrine therapy. Cancer Res. 2001; 61:1652-1658. 18. Pierga JY, Delaloge S, Espie M, Brain E, Sigal-Zafrani B, Mathieu MC, Bertheau P, Guinebretiere JM, Spielmann M, Savignoni A, Marty M. REFERENCES Profiling of EGFR mRNA and protein expression in 471 breast cancers compared with 10 normal tissues: a candidate biomarker to predict EGFR inhibitor effectiveness. Int J Cancer. 2012; 131:1009-1010. 23. Bieche I, Parfait B, Laurendeau I, Girault I, Vidaud M, Lidereau R. Quantification of estrogen receptor alpha and beta expression in sporadic breast cancer. Oncogene. 2001; 20:8109-8115. 24. Finak G, Sadekova S, Pepin F, Hallett M, Meterissian S, Halwani F, Khetani K, Souleimanova M, Zabolotny B, Omeroglu A, Park M. Gene expression signatures of morphologically normal breast tissue identify basal-like tumors. Breast Cancer Res. 2006; 8:R58. 35. Kalinsky K, Jacks LM, Heguy A, Patil S, Drobnjak M, Bhanot UK, Hedvat CV, Traina TA, Solit D, Gerald W, Moynahan ME. PIK3CA mutation associates with improved outcome in breast cancer. Clin Cancer Res. 2009; 15:5049-5059. 25. Ciriello G, Gatza ML, Beck AH, Wilkerson MD, Rhie SK, Pastore A, Zhang H, McLellan M, Yau C, Kandoth C, Bowlby R, Shen H, Hayat S, et al. Comprehensive Molecular Portraits of Invasive Lobular Breast Cancer. Cell. 2015; 163:506-519. 36. Loi S, Haibe-Kains B, Majjaj S, Lallemand F, Durbecq V, Larsimont D, Gonzalez-Angulo AM, Pusztai L, Symmans WF, Bardelli A, Ellis P, Tutt AN, Gillett CE, et al. PIK3CA mutations associated with gene signature of www.impactjournals.com/oncotarget Oncotarget 85140 Ogawa K. Expression of cyclooxygenase-2 in malignant and benign breast tumors. Anticancer Res. 2003; 23:3215-3221. low mTORC1 signaling and better outcomes in estrogen receptor-positive breast cancer. Proc Natl Acad Sci U S A. 2010; 107:10208-10213. 44. Hwang D, Scollard D, Byrne J, Levine E. Expression of cyclooxygenase-1 and cyclooxygenase-2 in human breast cancer. J Natl Cancer Inst. 1998; 90:455-460. 37. Ellis MJ, Lin L, Crowder R, Tao Y, Hoog J, Snider J, Davies S, DeSchryver K, Evans DB, Steinseifer J, Bandaru R, Liu W, Gardner H, et al. Phosphatidyl-inositol-3-kinase alpha catalytic subunit mutation and response to neoadjuvant endocrine therapy for estrogen receptor positive breast cancer. Breast Cancer Res Treat. 2010; 119:379-390. 45. Urban J, Kuzbicki L, Szatkowski G, Stanek-Widera A, Lange D, Chwirot BW. Stromal, rather than epithelial cyclooxygenase-2 (COX-2) expression is associated with overall survival of breast cancer patients. BMC Cancer. 2014; 14:732. 38. Wong H, Choo EF, Alicke B, Ding X, La H, McNamara E, Theil FP, Tibbitts J, Friedman LS, Hop CE, Gould SE. Antitumor activity of targeted and cytotoxic agents in murine subcutaneous tumor models correlates with clinical response. Clin Cancer Res. 2012; 18:3846-3855. REFERENCES 46. Miglietta A, Toselli M, Ravarino N, Vencia W, Chiecchio A, Bozzo F, Motta M, Torchio B, Bocca C. COX-2 expression in human breast carcinomas: correlation with clinicopathological features and prognostic molecular markers. Expert Opin Ther Targets. 2010; 14:655-664. 39. Yoshimura N, Sano H, Okamoto M, Akioka K, Ushigome H, Kadotani Y, Yoshimura R, Nobori S, Higuchi A, Ohmori Y, Nakamura K. Expression of cyclooxygenase-1 and -2 in human breast cancer. Surg Today. 2003; 33:805-811. 47. Park K, Han S, Shin E, Kim HJ, Kim JY. Cox-2 expression on tissue microarray of breast cancer. Eur J Surg Oncol. 2006; 32:1093-1096. 40. Half E, Tang XM, Gwyn K, Sahin A, Wathen K, Sinicrope FA. Cyclooxygenase-2 expression in human breast cancers and adjacent ductal carcinoma in situ. Cancer Res. 2002; 62:1676-1681. 48. Kim HS, Moon HG, Han W, Yom CK, Kim WH, Kim JH, Noh DY. COX2 overexpression is a prognostic marker for Stage III breast cancer. Breast Cancer Res Treat. 2012; 132:51-59. 41. McCarthy K, Bustin SA, Ogunkolade B, Khalaf S, Laban CA, McVittie CJ, Carpenter R, Jenkins PJ. Cyclo- oxygenase-2 (COX-2) mRNA expression and hormone receptor status in breast cancer. Eur J Surg Oncol. 2006; 32:707-709. 49. Cathomas G. PIK3CA in Colorectal Cancer. Front Oncol. 2014; 4:35. 50. Uddin S, Ahmed M, Hussain A, Assad L, Al-Dayel F, Bavi P, Al-Kuraya KS, Munkarah A. Cyclooxygenase-2 inhibition inhibits PI3K/AKT kinase activity in epithelial ovarian cancer. Int J Cancer. 2010; 126:382-394. 42. Kirkpatrick K, Ogunkolade W, Elkak A, Bustin S, Jenkins P, Ghilchik M, Mokbel K. The mRNA expression of cyclo- oxygenase-2 (COX-2) and vascular endothelial growth factor (VEGF) in human breast cancer. Curr Med Res Opin. 2002; 18:237-241. 51. Bocca C, Ievolella M, Autelli R, Motta M, Mosso L, Torchio B, Bozzo F, Cannito S, Paternostro C, Colombatto S, Parola M, Miglietta A. Expression of Cox-2 in human breast cancer cells as a critical determinant of epithelial-to-mesenchymal transition and invasiveness. Expert Opin Ther Targets. 2014; 18:121-135. 43. Watanabe O, Shimizu T, Imamura H, Kinoshita J, Utada Y, Okabe T, Kimura K, Hirano A, Yoshimatsu K, Aiba M, www.impactjournals.com/oncotarget www.impactjournals.com/oncotarget www.impactjournals.com/oncotarget Oncotarget 85141
https://openalex.org/W4253646657	http://www.vliz.be/imisdocs/publications/343574.pdf	English	null	Interannual Variability of Summer Surface Mass Balance and Surface Melting in the Amundsen Sector, West Antarctica	null	2,019	cc-by	18,886	Interannual variability of summer surface mass balance and surface melting in the Amundsen sector, West Antarctica , , , g 1Université Grenoble Alpes/CNRS/IRD/G-INP, IGE, 38000, Grenoble, France 2Laboratoire des Sciences du Climat et de l’Environnement, IPSL/CEA-CNRS-UVSQ UMR 8212, CEA Saclay, 91190, Gif-sur-Yvette, France 1Université Grenoble Alpes/CNRS/IRD/G-INP, IGE, 38000, Grenoble, France 2Laboratoire des Sciences du Climat et de l’Environnement, IPSL/CEA-CNRS-UVSQ UMR 8212, CEA Saclay, 91190, Gif-sur-Yvette, France 3F.R.S.-FNRS, Laboratory of Climatology, Department of Geography, University of Liège, 4000 L Correspondence: Marion Donat-Magnin (marion.donatmagnin@gmail.com) Received: 14 May 2019 – Discussion started: 24 May 2019 Revised: 29 November 2019 – Accepted: 12 December 2019 – Published: 27 January 2020 Received: 14 May 2019 – Discussion started: 24 May 2019 Revised: 29 November 2019 – Accepted: 12 December 2019 – Published: 27 January 2020 explained variance (increasing westward). While high sum- mer SMB and melt rates are both favored by positive phases of El Niño–Southern Oscillation (ENSO), the Southern Os- cillation Index (SOI) only explains 5 % to 16 % of SMB or melt rate interannual variance in our simulations, with mod- erate statistical signiﬁcance. However, the part explained by SOI in the previous austral winter is greater, suggesting that at least a part of the ENSO–SMB and ENSO–melt relation- ships in summer is inherited from the previous austral winter. Possible mechanisms involve sea ice advection from the Ross Sea and intrusions of circumpolar deep water combined with melt-induced ocean overturning circulation in ice shelf cavi- ties. Finally, we do not ﬁnd any correlation with the Southern Annular Mode (SAM) in summer. Abstract. Understanding the interannual variability of sur- face mass balance (SMB) and surface melting in Antarc- tica is key to quantify the signal-to-noise ratio in climate trends, identify opportunities for multi-year climate predic- tions and assess the ability of climate models to respond to climate variability. Here we simulate summer SMB and sur- face melting from 1979 to 2017 using the Regional Atmo- sphere Model (MAR) at 10 km resolution over the drainage basins of the Amundsen Sea glaciers in West Antarctica. Our simulations reproduce the mean present-day climate in terms of near-surface temperature (mean overestimation of 0.10 ◦C), near-surface wind speed (mean underestimation of 0.42 m s−1), and SMB (relative bias < 20 % over Thwaites glacier). The simulated interannual variability of SMB and melting is also close to observation-based estimates. Interannual variability of summer surface mass balance and surface melting in the Amundsen sector, West Antarctica For all the Amundsen glacial drainage basins, the in- terannual variability of summer SMB and surface melting is driven by two distinct mechanisms: high summer SMB tends to occur when the Amundsen Sea Low (ASL) is shifted southward and westward, while high summer melt rates tend to occur when ASL is shallower (i.e. anticyclonic anomaly). Both mechanisms create a northerly ﬂow anomaly that increases moisture convergence and cloud cover over the Amundsen Sea and therefore favors snowfall and downward longwave radiation over the ice sheet. The part of interannual summer SMB variance explained by the ASL longitudinal migrations increases westward and reaches 40 % for Getz. Interannual variation in the ASL relative central pressure is the largest driver of melt rate variability, with 11 % to 21 % of 1 Introduction From 1992 to 2017, the Antarctic continent has contributed 7.6 ± 3.9 mm to the global mean sea level (Shepherd et al., 2018), and this contribution may increase over the next cen- tury (Ritz et al., 2015; DeConto and Pollard, 2016; Edwards et al., 2019). The recent mass loss from the Antarctic ice sheet is dominated by increased ice discharge into the ocean (Shepherd et al., 2018), but both surface mass balance (SMB) and ice discharge may signiﬁcantly affect the Antarctic con- tribution to future sea level rise (Asay-Davis et al., 2017; Favier et al., 2017; Pattyn et al., 2018). Despite recent im- provements of ice sheet models motivated by newly available The Cryosphere, 14, 229–249, 2020 https://doi.org/10.5194/tc-14-229-2020 © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License. The Cryosphere, 14, 229–249, 2020 https://doi.org/10.5194/tc-14-229-2020 © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 230 satellite products over the last 10–20 years, large uncertain- ties remain in both the SMB and ice dynamics projections, hampering our ability to accurately predict future sea level rise (Favier et al., 2017; Shepherd and Nowicki, 2017). ability in the tropical Paciﬁc. It is the strongest climate ﬂuc- tuation at the interannual timescale and can bring seasonal to multi-year climate predictability (e.g. Izumo et al., 2010). Global climate models predict an increasing number of ex- treme El Niño events in the future, with large global im- pacts (Cai et al., 2014, 2017). Interannual and decadal vari- ability in the tropical Paciﬁc affects air temperature (Ding et al., 2011), snowfall (Bromwich et al., 2000; Cullather et al., 1996; Genthon and Cosme, 2003), sea ice extent (Pope et al., 2017; Raphael and Hobbs, 2014) and upwelling of circum- polar deep water favoring ice shelf basal melting (Dutrieux et al., 2014; Steig et al., 2012; Thoma et al., 2008) in West Antarctica. Recent studies found concurrences between El Niño events and summer surface melting over West Antarctic ice shelves (Deb et al., 2018; Nicolas et al., 2017; Scott et al., 2019). These connections are generally explained in terms of Rossby wave trains excited by tropical convection during El Niño events and inducing an anticyclonic anomaly over the Amundsen Sea (Ding et al., 2011). Paolo et al. (2018) re- ported a positive correlation between ENSO and the satellite- based ice shelf surface height in the Amundsen Sea over 1994–2017. Based on a detailed study of the extreme El Niño–La Niña sequence from 1997 to 1999, these authors suggested that El Niño events could increase snow accumula- tion but also increase ocean melting even more, thus leading to an overall ice shelf mass loss. The impact of ENSO was found to be stronger for the Dotson ice shelf and eastward and weaker for Pine Island and Thwaites (Paolo et al., 2018). However, the aforementioned studies were based on the anal- ysis of a few recent ENSO events and did not account for the highly variable properties of ENSO over multi-decadal peri- ods (e.g. Deser et al., 2012; Newman et al., 2011). ( , ; p , ) The largest ice discharge changes in Antarctica are ob- served in the Amundsen sector with an increase of 77 % over the last decades (Mouginot et al., 2014). M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector Current changes in the dynamics of glaciers ﬂowing into the Amundsen Sea are dominated by ocean warming rather than changes in surface conditions over the ice sheet (Thoma et al., 2008; Pritchard et al., 2012; Turner et al., 2017; Jenkins et al., 2016, 2018). Increased oceanic melting can trigger marine ice sheet insta- bility, leading to increased ice discharge, thinning ice, and retreating grounding lines (Weertman, 1974; Schoof, 2007; Favier et al., 2014; Joughin et al., 2014). In parallel, in- creased surface air temperature can lead to surface melting, subsequent hydrofracturing and possibly major thinning and retreat of outlet glaciers after the collapse of ice shelves (De- Conto and Pollard, 2016). Surface melting, leading to melt- water ponding, drainage into crevasses and hydrofracturing, is thought to be the main cause of the Larsen ice shelf col- lapse over the last decades in the Antarctic Peninsula (van den Broeke, 2005; Scambos et al., 2009; Vaughan et al., 2003). While surface melting is currently limited to relatively rare events over the Amundsen Sea ice shelves (Nicolas and Bromwich, 2010; Trusel et al., 2012) and underlying reasons for melt pond formation versus active surface drainage net- work remain unclear (Bell et al., 2018), the rapid surface air warming observed (Steig et al., 2009; Bromwich et al., 2013) and projected (Bracegirdle et al., 2008) in this region suggests that surface melting could increase in the future. Our study focuses on the two atmospheric-related aspects that can signiﬁcantly affect the contribution of the Amund- sen Sea sector to sea level rise, i.e., snowfall accumulation that is expected to increase in a warmer climate and therefore to reduce the mean sea level and surface melting that could potentially induce more ice discharge and therefore increase the mean sea level. The Southern Annular Mode (SAM; Hartmann and Lo, 1998; Limpasuvan and Hartmann, 1999; Thompson and Wal- lace, 2000) is the dominant mode of atmospheric variability in the Southern Hemisphere and corresponds to a variation in the strength and position of the circumpolar westerlies. Over the last 3 to 5 decades, the SAM has exhibited a posi- tive trend; i.e., westerly winds have been strengthening and shifting poleward (Chen and Held, 2007; Jones et al., 2016; Marshall, 2003). Medley and Thomas (2019) found similar patterns for the SAM trends and the reconstructed snow ac- cumulation trend over 1801–2000. Published by Copernicus Publications on behalf of the European Geosciences Union. Published by Copernicus Publications on behalf of the European Geosciences Union. 2.1 Model We use 30 snow layers, resolving the ﬁrst 20 m of the snowpack, with a ﬁne vertical resolution at the surface (1 mm) increasing with depth; snow layer thickness varies dynamically depending on the physical properties of overly- ing snow layer properties. If neighboring layers have simi- lar properties, then layers are associated together. The radia- tive scheme and cloud properties are the same as in Datta et al. (2019) and the surface scheme including snow den- sity and roughness is the same as in Agosta et al. (2019). The model is forced, over the period 1979–2017, by ERA- Interim reanalysis (Dee et al., 2011), which performs well over Antarctica (Bromwich et al., 2011; Huai et al., 2019), at 6-hourly temporal resolution and relaxed over ∼50 km later- ally (pressure, wind, temperature, speciﬁc humidity; the re- laxation zone is shown in Fig. 1), at the top (i.e. above 10 km) of the troposphere (temperature, wind) and at the surface (sea ice concentration, sea surface temperature). The Bedmap2 surface elevation dataset is used for the ice sheet topography (Fretwell et al., 2013). The snowpack density and tempera- ture are initialized from the pan-Antarctic simulation from Agosta et al. (2019). Drifting snow is relatively infrequent in the Amundsen region (Lenaerts et al., 2012) so that the drift- ing snow module has been switched off in our conﬁguration, similar to in Agosta et al. (2019). g In this study we revisit the inﬂuence of ENSO, SAM and ASL on summer SMB and melting over the drainage basins of the Amundsen sector in West Antarctica for the 1979– 2017 period. While the summer focus on melt rates is ob- vious, SMB in DJF (i.e. December–January–February) only represents 15 % of the annual SMB. It is nonetheless in- teresting to analyze the similarities and differences in what drives SMB and melting, and the modes of variability and their teleconnections to the Amundsen Sea region both have strong seasonal characteristics, so that each season needs to be considered separately. To do so, we simulate the sur- face conditions of the Amundsen Sea region over 1979– 2017 using the polar-adapted Regional Atmosphere Model (MAR) forced by the ERA-Interim reanalysis. Section 2 de- scribes the methodology followed in the study and presents the model and observations used for comparison. The model results are analyzed and evaluated against observations in Sect. 3. After evaluating the model skills (Sect. 2.1 Model To estimate SMB and surface melt over the Amundsen sec- tor we use the Regional Atmosphere Model (MAR; Gallée and Schayes, 1994) and speciﬁcally version 3.9.3 (http://mar. cnrs.fr, last access: 25 September 2019). The model solves the primitive equations under the hydrostatic approximation. It solves conservation equations for speciﬁc humidity, cloud droplets, raindrops, cloud ice crystals and snow particles (Gallée, 1995; Gallée and Gorodetskaya, 2010). MAR repre- sents coupled interactions between the atmospheric surface boundary layer and the snowpack using the Soil Ice Snow Vegetation Atmosphere Transfer (SISVAT) originally devel- oped by De Ridder and Gallée (1998). The snow–ice part of SISVAT includes submodules for surface albedo, melt- water percolation, and refreezing and snow metamorphism based on an early version of the CROCUS model (Brun et al., 1992). MAR has been largely evaluated in polar regions (e.g. Amory et al., 2015; Gallée et al., 2015; Lang et al., 2015; Fettweis et al., 2017; Kittel et al., 2018; Agosta et al., 2019; Datta et al., 2019). Importantly, ENSO and SAM are not independent of each other, and both modes of climate variability impact the ASL (Fogt and Wovrosh, 2015). SAM inﬂuences the ASL cen- tral pressure since it affects the mean sea level pressure over Antarctica (Turner et al., 2013a). The second and third lead- ing modes of variability in the South Paciﬁc have been sug- gested to be affected by Rossby wave trains induced by trop- ical convection anomalies (Mo and Higgins, 1998). In terms of ASL, it corresponds to a migration further west (east) dur- ing the La Niña (El Niño), but the difference has a low sta- tistical signiﬁcance (Turner et al., 2013b). Scott et al. (2019) recently reported that El Niño conditions favored blocking in the Amundsen Sea as well as a negative SAM phase, both leading to warm surface air anomalies in West Antarctica. ; , ) Our domain includes the drainage basins of the Amund- sen Sea Embayment glaciers and a large part of the Amund- sen Sea until 65◦S using oblique stereographic projection (EPSG: 3031). It covers an area of 2800 km × 2400 km at 10 km horizontal resolution (Fig. 1) and 24 vertical sigma levels located from approximately 1 to 15500 m above the ground. 2 Materials and method ASL is important regionally and variations in its central pres- sure and position respectively reﬂect the second and third leading modes of the Southern Hemisphere climate (Scott et al., 2019, their Fig. 3). A westward shift of the ASL induces northerly ﬂow anomalies over the Amundsen Sea, leading to warmer conditions and increased moisture transport over the ice sheet (Hosking et al., 2013, 2016; Thomas et al., 2015; Raphael et al., 2016; Fyke et al., 2017). Variations in the ASL central pressure also largely impact the West Antarc- tic climate: anticyclonic anomalies near 120◦W lead to ma- rine air intrusion over the ice sheet, thereby increasing cloud cover, longwave downward radiations and surface air tem- perature over the West Antarctic Ice Sheet (WAIS; Scott et al., 2019). While a deepening of the ASL is predicted for the twenty-ﬁrst century in response to greenhouse gas emissions, its high regional variability makes future changes of the ASL difﬁcult to predict (Hosking et al., 2016; Turner et al., 2009). M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 231 M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector By contrast, the tempera- tures above the melting point over the Amundsen ice shelves were found to be largely insensitive to the polarity of the SAM (Deb et al., 2018). The SAM phase has also been sug- gested to inﬂuence the ENSO teleconnection to the south Pa- ciﬁc: in-phase ENSO and SAM events (i.e. El Niño–SAM− or La Niña–SAM+) favor anomalous transient eddy momen- tum ﬂuxes in the Paciﬁc that make the ENSO teleconnection to the South Paciﬁc stronger than average (Fogt et al., 2011). Understanding the interannual variability of SMB and sur- face melting is key to (i) quantify the signal-to-noise ra- tio in climate trends, (ii) identify opportunities for seasonal predictions and (iii) assess the capacity of climate models to respond to global climate variability. Furthermore, years with particularly strong surface (or oceanic) melting could trigger irreversible grounding line retreat without the need for a long-term climate trend. Interannual variability in the Amundsen Sea region is usually described in terms of con- nections with the El Niño–Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and the Amundsen Sea Low (ASL). Our study revisits these connections through dedi- cated regional simulations based on the MAR model (Fet- tweis et al., 2017; Agosta et al., 2019). Hereafter, we start by reviewing recent literature on these climate connections. The Amundsen Sea Low (ASL; Raphael et al., 2016; Turner et al., 2013a) is a dynamic low-pressure system lo- cated in the Paciﬁc sector of the Southern Ocean and mov- ing across the Ross, Amundsen and Bellingshausen seas. The The El Niño–Southern Oscillation (ENSO; Philander et al., 1989) is the leading mode of ocean and atmosphere vari- www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020 2.3 Climate indices To describe the ENSO, we use the Southern Oscillation Index (SOI) from the Global Climate Observing System (GCOS) Working Group on Surface Pressure (Ropelewski and Jones, 1987; https://www.esrl.noaa.gov/psd/gcos_wgsp/ Timeseries/SOI/, last access: 25 September 2019). The SOI corresponds to the normalized pressure difference between Tahiti and Darwin based on observations. The Rossby wave trains connecting the equatorial Paciﬁc to Antarctica are ex- pected to develop within a few weeks in response to ENSO anomalies (e.g. Hoskins and Karoly, 1981; Mo and Higgins, 1998; Peters and Vargin, 2015), so we ﬁrst use the syn- chronous (DJF) SOI in Sect. 3. The lagged relationship to ENSO is discussed in Sect. 4, where we use other 3-month averages of SOI such as JJA (June–July–August). SOI is pre- ferred to NINO3.4 because it gives slightly stronger correla- tions with the variability in the Amundsen Sea region (as also found by Scott et al., 2019; Holland et al., 2019), but very similar results were obtained using NINO3.4 (not shown). To evaluate the simulated SMB, we use airborne-radar data from Medley et al. (2013, 2014) covering the period 1980–2011. These data were collected through NASA’s Op- eration IceBridge campaign over the Thwaites and Pine Is- land basins. They are based on the CReSIS radar (Center for Remote Sensing of Ice Sheets), which is an ultra-wideband radar system able to measure the stratigraphy of the upper 20–30 m of the snowpack with a few centimeters in vertical resolution. Airborne-radar data were veriﬁed with 190 ﬁrn core accumulation records. To evaluate the SMB regional pattern at a broader scale, we also compared the simulated SMB with the observations gathered in the GLACIOCLIM- SAMBA dataset thoroughly described by Favier et al. (2013) and updated by Wang et al. (2016) that are covered by our do- main. Similar to Kittel et al. (2018) and Agosta et al. (2019), we selected the observations for which the measurement pe- riod extends from 1950 to 2018. Observations before 1979 (i.e., the beginning of our study period) were compared to the average SMB simulated by MAR provided they cover a period of at least 5 years, while observations after 1979 were compared to the SMB modeled by MAR for the observa- tion period. We then compared the modeled SMB computed by using a four-nearest inverse-distance-weighted method for each of the 124 selected SMB observations. 2.2 Antarctic surface observations days at 25 km resolution over Antarctica. This product is based on passive microwave observations from the Scanning Microwave Multichannel Radiometer (SMMR), the Special Sensor Microwave/Imager (SSM/I) and the Special Sen- sor Microwave Imager/Sounder (SSMIS) spaceborne sen- sors and covers the 1978–2017 period. For a given grid cell and a given day, melt is assumed to occur as soon as one of the two daily observations of brightness tempera- ture exceeds a threshold value. As the identiﬁcation of melt days may be sensitive to the algorithm, we also use the dataset from Picard et al. (2007), extended to 2018 (http:// pp.ige-grenoble.fr/pageperso/picardgh/melting/, last access: 25 September 2019). This dataset is also based on SMMR and SSM/I but uses the algorithms from Torinesi et al. (2003) and Picard and Fily (2006) to retrieve melt days. It is pro- vided as daily melt status at 25 km resolution over the Antarctic continent from 1979 to 2018. We make use of meteorological data from the SCAR database including observations from the Italian Antarctic Research Program (http://www.climantartide.it, last access: 25 September 2019), the Antarctic Meteorological Research Center (AMRC program) (http://amrc.ssec.wisc.edu/, last ac- cess: 25 September 2019) and the Australian Antarctic auto- matic weather station (AWS) dataset (http://aws.acecrc.org. au/, last access: 25 September 2019). Among the 243 AWSs available over Antarctica since 1980, we selected the 41 sta- tions (see Table S1 in the Supplement for station names) located no more than 15 km from the closest continental MAR grid point (even if the domain resolution is 10 km, sta- tions over islands or capes that are not resolved can be lo- cated farther than 15 km from the closest continental MAR grid point). For each location, modeled values (surface pres- sure, near-surface temperature and near-surface wind speed) are computed as the average-distance-weighted value of the four nearest continental grid points. A second selection crite- rion is also applied in order to reduce comparison errors due to the difference between the model surface elevation and the actual AWS elevation: we only retain observations with an el- evation difference lower than 250 m. This two-stage selection leaves 41 suitable AWSs in our domain (Fig. 1). M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 232 2.1 Model 3.1), we analyze and discuss our results on the potential impact of large-scale climate variabilities on the SMB and melting in Sects. 3.2 and 4. The conclusions are provided in Sect. 5. In Sect. 3.2 we provide the SMB constituents averaged over individual drainage basins. www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020 M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 233 We use two other indices to describe the evolution of the migration and intensity variations in the Amund- sen Sea Low (ASL). The datasets are provided by the British Antarctic Survey (https://legacy.bas.ac.uk/ data/absl/ASL-index-Version2-Seasonal-ERA-Interim_ Hosking2016.txt, last access: 25 September 2019) and calculated from the ERA-Interim reanalysis. To describe the migration, we use the longitudinal position of the ASL deﬁned as the position of the minimum pressure within the box 80–60◦S, 170–298◦E (Hosking et al., 2016), deﬁned in degrees east. A decrease in the longitudinal position index hence corresponds to a westward shift of the ASL. To describe the intensity of the ASL, we use the relative central pressure of the ASL calculated as the minimum pressure in the aforementioned box minus the average pressure over that box (Hosking et al., 2016). A more intense ASL (deeper depression) is therefore represented by a lower index. We use two other indices to describe the evolution of the migration and intensity variations in the Amund- sen Sea Low (ASL). The datasets are provided by the British Antarctic Survey (https://legacy.bas.ac.uk/ data/absl/ASL-index-Version2-Seasonal-ERA-Interim_ Figure 1. Simulation domain. The drainage basins (Rignot et al., 2019) under consideration in this paper are shaded in color and Au- tomatic Weather Stations (AWSs) are indicated with red points. The hatched area represents ice shelves and contour lines the surface el- evation (every 200 m). Station names from 1 to 41: (1) Brianna, (2) Byrd, (3) Cape Adams, (4) Doug, (5) Elizabeth, (6) Evans Knoll, (7) Harry, (8) Janet , (9) Kominko-Slade, (10) Martha II, (11) Martha I, (12) Mount McKibben, (13) Noel, (14) Patriot Hills, (15) Siple Dome, (16) Ski Hi, (17) Swithinbank, (18) Theresa, (19) Backer Is- land, (20) Bean Peaks, (21) Bear Peninsula, (22) Clarke Mountains, (23) Gomez Nunatak, (24) Haag Nunatak, (25) Howard Nunatak, (26) Inman Nunatak, (27) Kohler Glacier, (28) Lepley Nunatak, (29) Lower Thwaites Glacier, (30) Lyon Nunatak, (31) Mount Pater- son, (32) Mount Sidley, (33) Mount Suggs, (34) Patriot Hills, (35) Steward Hills, (36) Thurston Island, (37) Toney Mountain, (38) Up Thwaites Glacier, (39) Whitmore Mountains, (40) Wilson Nunatak, (41) Russkaya. The relaxation zone is shown in white (∼50 km). The SAM and ASL indices are deﬁned regionally, and we do not expect any lag with summer SMB, so these indices are therefore calculated as DJF averages. All the correlations are calculated using detrended time series. Figure 1. Simulation domain. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector The drainage basins (Rignot et al., 2019) under consideration in this paper are shaded in color and Au- tomatic Weather Stations (AWSs) are indicated with red points. The hatched area represents ice shelves and contour lines the surface el- evation (every 200 m). Station names from 1 to 41: (1) Brianna, (2) Byrd, (3) Cape Adams, (4) Doug, (5) Elizabeth, (6) Evans Knoll, (7) Harry, (8) Janet , (9) Kominko-Slade, (10) Martha II, (11) Martha I, (12) Mount McKibben, (13) Noel, (14) Patriot Hills, (15) Siple Dome, (16) Ski Hi, (17) Swithinbank, (18) Theresa, (19) Backer Is- land, (20) Bean Peaks, (21) Bear Peninsula, (22) Clarke Mountains, (23) Gomez Nunatak, (24) Haag Nunatak, (25) Howard Nunatak, (26) Inman Nunatak, (27) Kohler Glacier, (28) Lepley Nunatak, (29) Lower Thwaites Glacier, (30) Lyon Nunatak, (31) Mount Pater- son, (32) Mount Sidley, (33) Mount Suggs, (34) Patriot Hills, (35) Steward Hills, (36) Thurston Island, (37) Toney Mountain, (38) Up Thwaites Glacier, (39) Whitmore Mountains, (40) Wilson Nunatak, (41) Russkaya. The relaxation zone is shown in white (∼50 km). The correlations between these four indices are indicated in Table 1. A signiﬁcant anticorrelation is obtained between the SAM index and ENSO (i.e. −SOI) as previously reported by Fogt et al. (2011). There is no signiﬁcant relationship be- tween the ASL longitudinal position and ENSO or SAM, as previously reported by Turner et al. (2013a). The relative central pressure also varies independently from SAM, ENSO and the ASL longitudinal position. Numerous previous stud- ies used the absolute rather than relative central pressure to characterize the ASL, but this index is strongly correlated to the SAM index and cannot be considered independently (Table 1). As proposed by Hosking et al. (2013), the ASL relative central pressure (i.e. actual central pressure minus pressure over the AS sector) allows for a better understand- ing of West Antarctic climate as it removes the inﬂuence of large-scale variability such as ENSO and SAM. (90th percentile) and a mean bias varying from −1.97 to 1.31 ◦C for the whole year (see Supplement for more details). The model tends to overestimate the lowest observed wind and underestimate the highest observed wind speeds (regres- sions in Fig. 2b). The model agreement with observations is nonetheless good on average, with a mean underestimation of 0.42 m s−1. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector The statistics per station show a RMSE vary- ing from 1.73 to 3.69 m s−1 and a mean bias varying from −3.08 to 0.85 m s−1 for the whole year. The variance of the wind speed simulated by MAR is lower than observed. Less satisfactory results are generally found for the stations lo- cated on an island. This can be explained by the resolution of 10 km, which is still too coarse to resolve small topographic features. For both near-surface temperature and wind speed, the statistics for the summer period (DJF) are very similar to the statistics for the whole year. Our results show very sim- ilar model skills compared to other simulations in the same region (Deb et al., 2018; Lenaerts et al., 2017) or at coarser resolution over the whole ice sheet (Agosta et al., 2019). 3 Results We ﬁrst evaluate the simulations with regard to observations (Sect. 3.1). Then we analyze the interannual variations in SMB and melting (Sect. 3.2). 3.1 Model evaluation We ﬁrst evaluate the near-surface temperature and near- surface wind speed in comparison to AWS data (Fig. 2). Our MAR conﬁguration reproduces the daily near-surface temperatures, with a mean bias of 0.10 ◦C and a mean corre- lation of 0.93 for the whole year and 0.86 for summer months (Fig. 2a). The statistics per station show a root-mean-square error (RMSE) varying from 2.66 (10th percentile) to 4.15 ◦C 2.3 Climate indices g We use the SAM index from NOAA/CPC (https: //stateoftheocean.osmc.noaa.gov/atm/sam.php, last access: 25 September 2019) to describe the primary mode of at- mospheric variability in the Southern Ocean (e.g., Marshall, 2003). The SAM index is calculated as the difference of mean zonal pressure between the latitudes of 40 and 65◦S based on NCEP/NCAR reanalysis which produces a SAM that is consistent with other reanalyses after 1979 (Ger- ber and Martineau, 2018). In the negative (positive) phase, the mean sea level pressure anomaly between the Antarc- tic and midlatitudes is positive (negative) and leads to a weaker (stronger) polar jet. Thus, positive (negative) values of the SAM index correspond to westerlies that are stronger (weaker) than average over the middle to high latitudes (50– 70◦S) and weaker (stronger) westerlies in the midlatitudes (30–50◦S). To evaluate simulated surface melt, we use satellite- derived estimates of surface meltwater production over 1999–2009 from Trusel et al. (2013), provided at 4.45 km resolution, and based on the QuickSCAT backscatter and calibrated with in situ observations. We also use data from Nicolas et al. (2017), who provide the number of melt www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020 M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020 234 M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector Table 1. Correlation between climate indices (−SOI, SAM, ASL longitudinal position, ASL relative central pressure, ASL actual central pressure) in austral summer (DJF). Values in brackets represent the percentage of signiﬁcance. ASL relative ASL actual Statistical ASL longitudinal central central correlation (R) −SOI SAM position (◦east) pressure (hPa) pressure (hPa) −SOI −0.45 (99 %) −0.22 (82 %) 0.00 (1 %) 0.40 (99 %) SAM 0.18 (73 %) −0.25 (88 %) −0.88 (99 %) ASL longitudinal −0.23 (84 %) −0.15 (63 %) position (◦east) Figure 2. Scatter plots of observed vs. simulated daily near-surface temperature (a) and daily near-surface wind speed (b) for the selected AWSs (see corresponding locations and names in Fig. 1). The statistics, including RMSE, correlation (R), bias, and standard deviations (σ), are calculated for individual stations and provided as multi-station mean over the whole year and over the summer months (DJF). The range of RMSE and biases across individual stations is also indicated with the 10th percentile and the 90th percentile of all RMSE values. The lines represent least-mean-square linear ﬁt between simulated data and observations. The complete statistical analyses for individual AWSs are provided in the Supplement (Tables S1–S2). M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 234 g g Table 1. Correlation between climate indices (−SOI, SAM, ASL longitudinal position, ASL relative central pressure, ASL actual central pressure) in austral summer (DJF). Values in brackets represent the percentage of signiﬁcance. Table 1. Correlation between climate indices (−SOI, SAM, ASL longitudinal position, ASL relative central pressure, ASL actual central pressure) in austral summer (DJF). Values in brackets represent the percentage of signiﬁcance. Table 1. Correlation between climate indices (−SOI, SAM, ASL longitudinal position, ASL relative central pressure, ASL actual central pressure) in austral summer (DJF). Values in brackets represent the percentage of signiﬁcance. correlation (R) −SOI SAM position ( east) pressure (hPa) pressure (hPa) −SOI −0.45 (99 %) −0.22 (82 %) 0.00 (1 %) 0.40 (99 %) SAM 0.18 (73 %) −0.25 (88 %) −0.88 (99 %) ASL longitudinal −0.23 (84 %) −0.15 (63 %) position (◦east) Figure 2. Scatter plots of observed vs. simulated daily near-surface temperature (a) and daily near-surface wind speed (b) for the selected AWSs (see corresponding locations and names in Fig. 1). 3.2 Drivers of summer interannual variability grove and the eastern part of Pine Island ice shelf, while more extreme values (> 200 mm w.e. a−1) are found near the peninsula in both simulated and observed datasets (Fig. 5). Even if the simulated and observed patterns are similar, the simulated surface melt is a factor of 2 lower than observa- tions locally (e.g. over Abbot ice shelf and the peninsula). While the interannual melt rate variability is well reproduced with a correlation of 0.80, the surface melt rate simulated by MAR is underestimated by 18 % on average compared to QuickSCAT estimates (Fig. 6a). Surface melt rate over Pine Island basins is well simulated by MAR (Fig. 6b) with R equal to 0.80 compared to drainage basins with low sur- face melt (i.e. Crosson, Dotson) where R is equal to 0.14 and 0.24, respectively. This melt underestimation, particu- larly pronounced over drainage basins with low surface melt rate, could be explained by the slight overestimation of the snowfall accumulation (10 %–20 %), as the presence of a fresh snow layer of high albedo overlying snow or ice lay- ers of lower albedo likely reduces melt. MAR surface melt presents a slight overestimation over Getz ice shelf (Fig. 5) possibly explained by wind advection, foehn effect or even snow metamorphism simulated by MAR. Further work is needed to understand such local biases. MAR is fully driven by low-resolution ERA-Interim sea ice cover and tempera- ture; therefore possible underestimation of the presence of polynyas can also play a role in the melt biases. In this subsection, we ﬁrst investigate the large-scale con- ditions leading to interannual anomalies in summer SMB or surface melting. For sake of clarity, we only consider the Pine Island and Thwaites basins (together) as a ﬁrst approach. To identify large-scale conditions leading to high (low) SMB, we calculate composites deﬁned as the average of summers presenting a SMB greater than the 85th (lower than the 15th) interannual percentile, and we proceed similarly for surface melt composites. We choose the 85th and 15th percentiles to optimize the signal-to-noise ratio. Sea surface pressure composites show that distinct mecha- nisms affect the interannual variability of summer SMB and surface melting (Fig. 8). www.the-cryosphere.net/14/229/2020/ The statistics, including RMSE, correlation (R), bias, and standard deviations (σ), are calculated for individual stations and provided as multi-station mean over the whole year and over the summer months (DJF). The range of RMSE and biases across individual stations is also indicated with the 10th percentile and the 90th percentile of all RMSE values. The lines represent least-mean-square linear ﬁt between simulated data and observations. The complete statistical analyses for individual AWSs are provided in the Supplement (Tables S1–S2). Figure 3. Annual mean (1979–2017) simulated SMB (blue–green scale) and relative error of the simulated SMB compared to the airborne-radar data from Medley et al. (2013, 2014) (blue–red color bar). Grey contours indicate the surface height (every 1000 m). The drainage basins under consideration are the same as in Fig. 1 (large grey contours here). We now assess the simulated SMB compared to the SMB from Medley et al. (2013, 2014) derived from airborne radar over the period 1980–2011. The simulated SMB is well cap- tured by MAR with a mean relative overestimation of ap- proximately 10 % over the Thwaites basin and local errors smaller than 20 % at all locations (Fig. 3). The interannual variability is also well simulated by MAR with a correlation of 0.90 (Fig. 4). In order to have a broad overview of the SMB evaluation, we also compared the simulated SMB with the GLACIOCLIM-SAMBA dataset (Favier et al., 2013) over the Ross and Siple Coast sector (See Fig. S1 in the Sup- plement). The bias of simulated SMB compared to obser- vation SMB is less than 10 mm w.e. a−1 and local bias can reach 30 mm w.e. a−1. However, the relative bias between the GLACIOCLIM-SAMBA dataset and simulated SMB is more pronounced with only 44 % of GLACIOCLIM-SAMBA sites showing a relative error with simulated SMB lower than 20 %. All SMB components are shown in Table 2. Figure 3. Annual mean (1979–2017) simulated SMB (blue–green scale) and relative error of the simulated SMB compared to the airborne-radar data from Medley et al. (2013, 2014) (blue–red color bar). Grey contours indicate the surface height (every 1000 m). The drainage basins under consideration are the same as in Fig. 1 (large grey contours here). The areas of highest surface melt (> 100 mm w.e. a−1) are located near the coast and particularly over Abbot, Cos- The Cryosphere, 14, 229–249, 2020 www.the-cryosphere.net/14/229/2020/ www.the-cryosphere.net/14/229/2020/ 235 M. www.the-cryosphere.net/14/229/2020/ Donat-Magnin et al.: SMB and surface melting in the Amundsen sector M. Donat-Magnin et al.: SMB and surface melting in the A Figure 4. Time series of the annual mean (January to Decem- ber) simulated and radar-derived SMB from 1980 to 2011 over the Thwaites basins. 1 mm w.e. d−1 (as in Datta et al., 2019) gives a mean under- estimation of 4.8 d per year compared to observation from Nicolas et al. (2017), while a threshold of 3 mm w.e. d−1 (as in Deb et al., 2018; Lenaerts et al., 2017) gives a mean un- derestimation of 4.9 d per year. This underestimation is less pronounced (0.8 to 0.9 d per year depending on the thresh- old) when using Picard et al. (2007) as a reference. The inter- annual variability in the number of melt days is reproduced with correlations of 0.69 and 0.43 to the two satellite prod- ucts (Fig. 7). Previous study on the Antarctic peninsula also found that MAR melt occurrence is comparable to satellite products, but slightly underestimated over the western coast of the Peninsula (Datta et al., 2019). Overall, MAR simulates the interannual variability of the Amundsen sector well, and we are now going to use these simulations to investigate the drivers of interannual variabil- ity of SMB and surface melting. Figure 4. Time series of the annual mean (January to Decem- ber) simulated and radar-derived SMB from 1980 to 2011 over the Thwaites basins. 3.2 Drivers of summer interannual variability Summers with high SMB are on av- erage characterized by a far westward (by ∼30◦) and south- ward (by 3–4◦) migration of the ASL center, while the re- verse migration is found for summers with low SMB, al- though with a smaller displacement (∼15◦eastward). In contrast, years with high surface melt rates are character- ized by a much smaller ASL migration, and no migration is found for years with low surface melt rates, but the pres- sure gradients differ between the high and low composites. Therefore, we hereafter consider the variability of SMB and surface melting separately. To further characterize the tropospheric circulation associ- ated with years of low or high summer SMB, we plot com- posites of both the 500 hPa geopotential height (Fig. 9a, b) and the 500 hPa geopotential height divided by the domain- averaged value for each season (Fig. 9c, d). The latter has the advantage of highlighting changes in regional gradi- ents (related to the regional circulation) rather than larger- scale changes in geopotential height. Both provide simi- lar composites, but the statistical signiﬁcance is higher in Fig. 9c, d. On average, low-SMB summers are characterized by a northward and eastward ASL migration (shown through a dipole in the 500 hPa normalized geopotential composite We also compare the number of melt days to the satellite products from Nicolas et al. (2017) and Picard et al. (2007). To avoid no-melt-day areas in the time series computation, we use the area where the annual number of melt days for each dataset is more than 3 melt days per year, which cor- responds approximately to the ice shelf zone. As with the amount of surface melt, the number of melt days over the domain is underestimated by MAR (Fig. 7). The amplitude of the underestimation is not very sensitive to the melt rate threshold used to deﬁne a melt day in MAR. A threshold of www.the-cryosphere.net/14/229/2020/ www.the-cryosphere.net/14/229/2020/ www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020 M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 236 Figure 5. Annual surface melt rate (a) simulated by MAR over 1999–2009 and (b) derived from QuickSCAT satellite data over the same period (Trusel et al., 2013) and interpolated over the MAR grid. Figure 5. Annual surface melt rate (a) simulated by MAR over 1999–2009 and (b) derived from QuickSCAT satellite data over the same period (Trusel et al., 2013) and interpolated over the MAR grid. Figure 6. (a) Time series of surface melt rates in mean over the model domain derived from satellite data and simulated by MAR; years labeled on the X axis refer to the second year of a given austral summer (e.g., summer 1999–2000 is labeled 2000). (b) Surface melt modeled versus surface melt interpolated from satellite data (QuickSCAT) over drainage basins (only where surface melt > 0 mm w.e. a−1) and over the period 1999–2009. Figure 6. (a) Time series of surface melt rates in mean over the model domain derived from satellite data and simulated by MAR; years labeled on the X axis refer to the second year of a given austral summer (e.g., summer 1999–2000 is labeled 2000). (b) Surface melt modeled versus surface melt interpolated from satellite data (QuickSCAT) over drainage basins (only where surface melt > 0 mm w.e. a−1) and over the period 1999–2009. previously done for SMB, we plot composites of both the 500 hPa geopotential height (Fig. 12a, b) and the 500 hPa geopotential height divided by the domain-averaged value for each season (Fig. 12c, d), the latter better highlighting regional circulation changes (geopotential gradients). Sum- mers with high surface melt rates show a signiﬁcant in- crease in the 500 hPa geopotential height over the Belling- shausen Sea (Fig. 12b), i.e. an anticyclonic anomaly, and small westward ASL migration as shown in the 500 hPa nor- malized geopotential composite (Fig. 12d). This anomaly is against the ASL mean circulation and creates a northerly ﬂow anomaly over the ice sheet in the Amundsen sector (Fig. 12e, f). This anticyclonic anomaly was described by Scott et al. (2019) in terms of enhanced blocking activity. As in Scott et al. (2019), we ﬁnd that high-melt summers are as- sociated with denser cloud cover (Fig. 11c, d) and increased downward longwave radiation (Fig. www.the-cryosphere.net/14/229/2020/ Now that we have described the mechanisms in play for summers with high and low SMB or surface melt rates, we investigate the connections between the leading modes of cli- mate variability (ENSO, SAM and ASL variability) and sum- mer SMB and surface melting over the individual Amundsen drainage basins (shown in Fig. 1). In line with the previous composite analysis for high- and low-SMB composites, the SMB in all the drainage basins is anticorrelated to the ASL longitudinal position (Ta- ble 3, fourth column). This anticorrelation has little statisti- cal signiﬁcance for Abbot and Cosgrove, but for Dotson and Thwaites the ASL longitudinal position explains nearly 40 % of the SMB interannual variance (explained variance given by square correlations). The ENSO–SMB relationship has moderate levels of statistical signiﬁcance, with positive SMB correlations to −SOI for all basins but a part of SMB vari- ance explained by ENSO that remains below 16 % (Table 3, second column). −SOI and the ASL longitudinal location are not signiﬁcantly connected together (Table 1); therefore their connection to SMB can be considered independent from each other. Finally, the SMB is signiﬁcantly correlated to neither the ASL relative central pressure (Table 3, ﬁfth row) nor the SAM index (Table 3, third column) for all the basins. To bet- ter describe interplays, we also calculate a multi-linear re- gression of SMB on the four indices (last column of Table 3). Accounting for several indices increases the explained SMB variance compared to a single index, indicating an interplay of the ASL and ENSO. Overall, 16 % to 49 % of the summer The part of explained variance never exceeds 50 % of the summer melt and SMB variance. Possible reasons for this are as follows. (i) The modes of variability do not explain all the variance locally; for example, the leading EOF of sea sur- face temperature (SST) in the equatorial Paciﬁc (representing ENSO) only accounts for 50 % to 70 % of the SST variance (e.g. Roundy, 2014), meaning that the tropical convection thought to inﬂuence Antarctica is not completely described by SOI or NINO3.4. www.the-cryosphere.net/14/229/2020/ 11e, f), and therefore surface air warming, while the opposite occurs for low-melt in Fig. 9a, c), which is associated with an offshore surface wind anomaly over the glaciers of the Amundsen Sea sector (Fig. 9e). Conversely, high-SMB summers are characterized by a southward and westward ASL migration (Fig. 9b, d), which is associated with an onshore surface wind anomaly over the glaciers of the Amundsen sector (Fig. 9f). The cir- culation anomalies typical of high-SMB summers favor the southward transport of precipitable water as indicated by the composites of integrated vapor transport (Fig. 10a, b). In- creased moisture transport towards the Amundsen Sea Em- bayment leads to denser cloud cover (Fig. 10c, d) and in- creased SMB. On average, high-melt summers are also associated with increased moisture transport towards the Amundsen Sea Em- bayment and conversely for low-melt summers (Fig. 11a, b), but the mechanism is somewhat different from the case of SMB. The ASL migration during high-melt summers is much smaller than for the high-SMB summers (Fig. 8b). As www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020 237 M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector Figure 7. Time series of the number of melt days per summer (DJF) averaged over the part of the domain with more than 3 melt days per year on average (which approximately corresponds to the ice shelf zone), derived from two satellite products and simulated by MAR (deﬁned using a melt rate threshold of either 1 or 3 mm w.e. d−1). SMB variance (increasing westward) can be explained by a linear combination of the climate indices. We now investigate similar relationships, but with surface melt rates instead of SMB. By contrast to SMB, the sur- face melt connection to the ASL relative central pressure is stronger than its connection to the ASL longitudinal posi- tion (Table 4, fourth and ﬁfth columns), which again high- lights the two distinct mechanisms explaining high or low melt rates vs. high or low SMB. The part of the melt rate variance explained by the ASL relative central pressure in- creases westward, from 12 % for Abbot to 21 % for Getz. www.the-cryosphere.net/14/229/2020/ Even though the effect of the ASL central pressure domi- nates, there is still a moderate anticorrelation between melt rates and the ASL longitudinal position, suggesting that the mechanism explaining high and low SMB can explain a small part of the melt rate variance (less than 10 %). In a way similar to SMB, SOI explains less than 9 % of the melt rate’s variance, with moderate statistical signiﬁcance (Table 4, sec- ond column), and as for summer SMB there is no signiﬁcant relationship to the SAM. We have repeated the calculations considering the number of melt days, and we ﬁnd very sim- ilar results in terms of correlations (Table 4, second line in each row). Relatively similar conclusions can be drawn from observational estimates of the number of melt days (values in italic in Table 4), except that satellite estimates indicate a stronger correlation to −SOI, even exceeding the correla- tion to the ASL central pressure in the case for most drainage basins (the variance explained by −SOI reaching 25 %). As the SAM index is signiﬁcantly anticorrelated to ENSO (Ta- ble 1), the stronger melt–SOI correlation in the observational products goes together with a stronger melt–SAM anticorre- lation than in our simulations. To better describe interplays, we also calculate a multi-linear regression of melt rates on the four indices (last column of Table 4). Accounting for sev- eral indices increases the explained melt rate variance com- pared to a single index, which indicates an interplay of the fours modes of variability. Overall, 21 % to 30 % of the sum- mer melt rate variance can be explained by a linear combina- tion of the climate indices. Figure 7. Time series of the number of melt days per summer (DJF) averaged over the part of the domain with more than 3 melt days per year on average (which approximately corresponds to the ice shelf zone), derived from two satellite products and simulated by MAR (deﬁned using a melt rate threshold of either 1 or 3 mm w.e. d−1). summers. Composites of sensible heat ﬂux indicate that heat is lost by the snow surface to the atmosphere for high-melt summers, i.e. high melt summers are not caused by foehn events on average (Fig. S2). www.the-cryosphere.net/14/229/2020/ (ii) Assuming that a large part of the tropospheric circulation variability is explained by ENSO, SAM and ASL indices, there are reasons why the connection may be weaker for SMB and surface melting because of their nonlinear dependence on sea ice and evaporation in coastal regions, the evolution of snow properties, etc. (iii) Strong modulation of the southeast Paciﬁc extratropical circulation by Rossby wave trains is not only due to the existence of El www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020 M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 238 Figure 8. Summer sea surface pressure composites for high–low SMB (a) and high–low surface melt (b). The ice sheet height is indicated by thin grey contours (every 500 m). Figure 8. Summer sea surface pressure composites for high–low SMB (a) and high–low surface melt (b). The ice sheet height is indicated by thin grey contours (every 500 m). Table 2. Annual SMB decomposition for all drainage basins over 1979–2017 with SMB = snowfall + rainfall −sublimation −runoff. The middle rows indicate other terms that are not directly part of the SMB. The last two rows give snowfall and melt rates averaged over the ice shelves. Table 2. Annual SMB decomposition for all drainage basins over 1979–2017 with SMB = snowfall + rainfall −sublimation −runoff. The middle rows indicate other terms that are not directly part of the SMB. The last two rows give snowfall and melt rates averaged over the ice shelves. (mm w.e. yr−1) Abbot Cosgrove Pine Island Thwaites Crosson Dotson Getz SMB 959.5 660.5 429.1 504.5 867.7 895.0 843.0 Sublimation 26.5 30.3 12.7 0.6 22.6 25.6 22.8 Snowfall 981.9 688.5 441.3 505.0 887.6 919.5 864.9 Rainfall 4.0 2.3 0.4 0.1 2.8 1.1 0.8 Runoff 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Refreezing 36.4 27.0 4.3 1.0 6.2 7.2 9.6 Surface melt 32.5 24.8 3.9 0.9 3.4 6.1 8.8 Snowfall (only over ice shelf) 795.4 296.9 422.7 811.5 1051.5 672.0 789.9 Surface melt (only over ice shelf) 57.9 83.2 82.0 26.5 18.5 23.7 26.7 Niño events but also depends on the exact spatial distribu- tion of deep convection in the tropical central Paciﬁc and the strength of the polar jet (Harangozo, 2004). (iv) A part of the variability of SMB and melting may be stochastic, i.e. not necessarily driven by variability with spatiotemporal coher- ence at large scales. the Amundsen–Bellingshausen region experiences blocking, i.e. www.the-cryosphere.net/14/229/2020/ anticyclonic conditions, which tends to decrease the cli- matological southerly ﬂow (western ﬂank of the ASL) and to favor marine air intrusions that make cloud cover denser with increasing downward longwave radiation, as described by Scott et al. (2019). While the role of the ASL now appears to be quite clear, the exact impact of ENSO on SMB and surface melt rates re- mains elusive. Earlier studies analyzing the impact of ENSO on precipitation in West Antarctica had difﬁculties under- standing the mechanisms and the robustness of the signal, because they had to rely on relatively short observation and reanalysis periods (Bromwich et al., 2000; Cullather et al., 1996; Genthon and Cosme, 2003). Using a dedicated SMB model over a longer time period, we have shown here that the ENSO–SMB relationship in austral summer exists, but it is relatively weak as SOI alone cannot explain more than 16 % of the interannual variance in summer SMB. The re- lationship between ENSO and the number of melt days was identiﬁed by Deb et al. (2018) using both regional simula- tions and a satellite product. It was then thoroughly described 4 Discussion SMB regression Abbot 0.25 (87 %) 0.14 (59 %) −0.15 (65 %) −0.01 (3 %) 0.40 Cosgrove 0.26 (88 %) 0.16 (65 %) −0.21 (80 %) 0.08 (36 %) 0.46 Pine Island 0.32 (95 %) 0.03 (17 %) −0.25 (87 %) −0.17 (69 %) 0.47 Thwaites 0.33 (96 %) 0.02 (8 %) −0.45 (99 %) −0.10 (47 %) 0.57 Crosson 0.40 (99 %) −0.00 (2 %) −0.53 (99 %) −0.14 (60 %) 0.66 Dotson 0.36 (97 %) 0.00 (2 %) −0.61 (99 %) 0.15 (65 %) 0.70 Getz 0.30 (93 %) −0.15 (62 %) −0.64 (99 %) 0.27 (90 %) 0.68 www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020 Table 3. Correlation R between ENSO, SAM, and ASL indices and the SMB over individual drainage basins in austral summer. The statistical signiﬁcance (Welch’s t test) is written within brackets. The last column shows the correlation of a multi-linear regression to the four indices using a least absolute shrinkage and selection operator (LASSO; Tibshirani, 1996). Table 3. Correlation R between ENSO, SAM, and ASL indices and the SMB over individual drainage basins in austral summer. The statistical signiﬁcance (Welch’s t test) is written within brackets. The last column shows the correlation of a multi-linear regression to the four indices using a least absolute shrinkage and selection operator (LASSO; Tibshirani, 1996). Table 3. Correlation R between ENSO, SAM, and ASL indices and the SMB over individual drainage basins in austral summer. The statistical signiﬁcance (Welch’s t test) is written within brackets. The last column shows the correlation of a multi-linear regression to the four indices using a least absolute shrinkage and selection operator (LASSO; Tibshirani, 1996). Table 3. Correlation R between ENSO, SAM, and ASL indices and the SMB over individual drainage basins in austral summer. The statistical signiﬁcance (Welch’s t test) is written within brackets. The last column shows the correlation of a multi-linear regression to the four indices using a least absolute shrinkage and selection operator (LASSO; Tibshirani, 1996). ASL relative Drainage −SOI vs. SAM index ASL longitudinal central pressure Multi-linear basins SMB vs. SMB location vs. SMB vs. 4 Discussion The composite analysis and the correlation of SMB and melt rates to the ASL indices give a consistent picture. Summers tend to be associated with high SMB when the ASL migrates westward and southward because this places the northerly ﬂow (ASL eastern ﬂank) over the Amundsen Sea, thereby increasing the southward humidity transport and snowfall. This corresponds to the large-scale features described by Hosking et al. (2013) but is here described for the SMB of individual drainage basins. By contrast, longitudinal migra- tions of the ASL are not the main driver of surface melting variability, as previously noted by Deb et al. (2018). Sum- mers tend to be associated with high surface melt rates when www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020 M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 239 Figure 9. (a, b) The 500 hPa geopotential height (m), (c, d) 500 hPa geopotential height divided by the domain-averaged value for each season and (e, f) 10 m wind (m s−1) anomalies during low-SMB summers (left) and high-SMB summers (right); scales of arrow lengths are shown near the upper right corner of panels (e) and (f). Anomalies are calculated as high or low composites minus the climatology over 1979–2017. The hatched area (a–d) represents signiﬁcance > 90 % calculated with Welch’s t test. Figure 9. (a, b) The 500 hPa geopotential height (m), (c, d) 500 hPa geopotential height divided by the domain-averaged value for each season and (e, f) 10 m wind (m s−1) anomalies during low-SMB summers (left) and high-SMB summers (right); scales of arrow lengths are shown near the upper right corner of panels (e) and (f). Anomalies are calculated as high or low composites minus the climatology over 1979–2017. The hatched area (a–d) represents signiﬁcance > 90 % calculated with Welch’s t test. Table 3. Correlation R between ENSO, SAM, and ASL indices and the SMB over individual drainage basins in austral summer. The statistical signiﬁcance (Welch’s t test) is written within brackets. The last column shows the correlation of a multi-linear regression to the four indices using a least absolute shrinkage and selection operator (LASSO; Tibshirani, 1996). ASL relative Drainage −SOI vs. SAM index ASL longitudinal central pressure Multi-linear basins SMB vs. SMB location vs. SMB vs. The Cryosphere, 14, 229–249, 2020 www.the-cryosphere.net/14/229/2020/ M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 240 Table 4. Correlation R between −SOI, SAM, and ASL indices and MAR surface melt rates (bold), MAR number of melt days (regular), number of melt days from satellite products (italic, ﬁrst value for Nicolas et al. (2017) and second for Picard et al. (2007)), over individual ice shelves in summer. The statistical signiﬁcance (Welch’s t test) is written within brackets. The last column shows the correlation of a multi-linear regression to the four indices using a least absolute shrinkage and selection operator (LASSO, Tibshirani 1996). Table 4. Correlation R between −SOI, SAM, and ASL indices and MAR surface melt rates (bold), MAR number of melt days (regular), number of melt days from satellite products (italic, ﬁrst value for Nicolas et al. (2017) and second for Picard et al. (2007)), over individual ice shelves in summer. The statistical signiﬁcance (Welch’s t test) is written within brackets. The last column shows the correlation of a multi-linear regression to the four indices using a least absolute shrinkage and selection operator (LASSO, Tibshirani 1996). M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector Drainage SAM ASL longitudinal ASL relative Multi-linear basins −SOI index location central pressure regression Abbot 0.23 (84 %) −0.05(24%) −0.25(86%) 0.35 (97 %) 0.46 0.25 (86 %) −0.04 (19 %) −0.23 (84 %) 0.30 (93 %) 0.44 0.37 (97 %) −0.22(79%) −0.29(91%) 0.32 (94 %) 0.49 0.37 (98 %) −0.18(71%) −0.18(72%) −0.24(92%) 0.47 Cosgrove 0.24 (86 %) −0.08(36%) −0.30(93%) 0.37 (98 %) 0.50 0.25 (87 %) −0.06 (29 %) −0.29 (92 %) 0.32 (95 %) 0.47 0.37 (97 %) −0.20(76%) −0.37(97 %) 0.32 (94 %) 0.52 0.38 (98 %) −0.25(87 %) −0.16(65%) 0.27 (90 %) 0.46 Pine Island 0.30 (86 %) −0.07(33%) −0.31(94%) 0.38 (98 %) 0.54 0.29 (92 %) −0.03 (13 %) −0.34 (96 %) 0.35 (97 %) 0.55 0.48 (99 %) −0.29(91%) −0.21(78%) 0.42 (99 %) 0.62 0.44 (99 %) −0.19(75%) −0.13(56%) 0.37 (98 %) 0.59 Thwaites 0.29 (92 %) −0.13(56%) −0.25(87%) 0.39 (98 %) 0.51 0.35 (95 %) −0.11 (43 %) −0.19 (69 %) 0.51 (99 %) 0.67 0.48 (99 %) −0.23(81%) −0.11(45%) 0.29 (91 %) 0.55 0.44 (99 %) −0.28(89%) −0.06(26%) 0.26 (87 %) 0.52 Crosson 0.28 (91 %) −0.14(60%) −0.23(84%) 0.41 (99 %) 0.51 0.29 (86 %) −0.08 (30 %) −0.11 (42 %) 0.40 (97 %) 0.52 0.48 (99 %) −0.35(95%) −0.20(76%) 0.39(98 %) 0.61 0.35 (96 %) −0.35(96%) −0.10(45%) 0.41 (98 %) 0.52 Dotson 0.27 (90 %) −0.14(60%) −0.24(86%) 0.42 (99 %) 0.52 0.26 (86 %) −0.13 (54 %) −0.25 (86 %) 0.44 (99 %) 0.53 0.36 (95 %) −0.27(84%) −0.03(11%) 0.36 (94 %) 0.52 0.33 (93 %) −0.28(86%) 0.13 (51 %) 0.32 (91 %) 0.50 Getz 0.22 (82 %) −0.16(65%) −0.26(88%) 0.46 (99 %) 0.53 0.22 (82 %) −0.16 (67 %) −0.29 (92 %) 0.46 (99 %) 0.54 0.50 (99 %) −0.42(99%) −0.24(84%) 0.41 (99 %) 0.64 0.34 (96 %) −0.41(98%) −0.15(63%) 0.34 (96 %) 0.46 et al., 2019). More work will be needed to understand these differences. by Scott et al. (2019), who found that SOI could explain 20 % of the melt variance when considering all the Amundsen ice shelves together and using satellite products (correlation of 0.45 in their Table 3). While we obtain results similar to those of Scott et al. 4 Discussion SMB regression Abbot 0.25 (87 %) 0.14 (59 %) −0.15 (65 %) −0.01 (3 %) 0.40 Cosgrove 0.26 (88 %) 0.16 (65 %) −0.21 (80 %) 0.08 (36 %) 0.46 Pine Island 0.32 (95 %) 0.03 (17 %) −0.25 (87 %) −0.17 (69 %) 0.47 Thwaites 0.33 (96 %) 0.02 (8 %) −0.45 (99 %) −0.10 (47 %) 0.57 Crosson 0.40 (99 %) −0.00 (2 %) −0.53 (99 %) −0.14 (60 %) 0.66 Dotson 0.36 (97 %) 0.00 (2 %) −0.61 (99 %) 0.15 (65 %) 0.70 Getz 0.30 (93 %) −0.15 (62 %) −0.64 (99 %) 0.27 (90 %) 0.68 www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020 M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector (a, b) Vertical integrated vapor transport (IVT) along the y axis (negative toward the continent) calculated as IVT [kg m−2] = R 700 925 q · v dP g , with q the speciﬁc humidity (g kg−1), v the wind speed (m s−1), P the pressure (Pa), and g the gravity (9.81 m s−2) and (c, d) cloud cover (no units, from 0 to 1) anomalies during low-SMB summers (left) and high-SMB summers (right). Anomalies are calculated as high or low composites minus the cli- matology over 1979–2017. The hatched area represents signiﬁcance > 90 % calculated with Welch’s t test. connection in summer was supported by Steig et al. (2012), Figure 11. (a, b) Vertical integrated vapor transport (IVT) along the y axis (negative toward the continent (kg m−2, same formula as for Fig. 10), (c, d) cloud cover (no units, from 0 to 1) and (e, f) downward longwave radiation (W m−2) anomalies during low- Figure 11. (a, b) Vertical integrated vapor transport (IVT) along the y axis (negative toward the continent (kg m−2, same formula as for Fig. 10), (c, d) cloud cover (no units, from 0 to 1) and (e, f) downward longwave radiation (W m−2) anomalies during low- melt summers (left) and high-melt summers (right). Anomalies are calculated as high or low composites minus the climatology over 1979–2017. The hatched area represents signiﬁcance > 90 % cal- culated with Welch’s t test. Figure 10. (a, b) Vertical integrated vapor transport (IVT) along the y axis (negative toward the continent) calculated as IVT [kg m−2] = R 700 925 q · v dP g , with q the speciﬁc humidity (g kg−1), v the wind speed (m s−1), P the pressure (Pa), and g the gravity (9.81 m s−2) and (c, d) cloud cover (no units, from 0 to 1) anomalies during low-SMB summers (left) and high-SMB summers (right). Anomalies are calculated as high or low composites minus the cli- matology over 1979–2017. The hatched area represents signiﬁcance > 90 % calculated with Welch’s t test. Figure 11. (a, b) Vertical integrated vapor transport (IVT) along the y axis (negative toward the continent (kg m−2, same formula as for Fig. 10), (c, d) cloud cover (no units, from 0 to 1) and (e, f) downward longwave radiation (W m−2) anomalies during low- melt summers (left) and high-melt summers (right). M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector Anomalies are calculated as high or low composites minus the climatology over 1979–2017. The hatched area represents signiﬁcance > 90 % cal- culated with Welch’s t test. connection in summer was supported by Steig et al. (2012), who found the weakest correlations between NINO3.4 and wind stress anomalies in the Amundsen Sea in DJF com- pared to other seasons. Therefore, we investigated possible lags in the relationships to ENSO. While ENSO peaks in DJF, it starts to develop in MAM (March–April–May), as indicated by the growing SOI autocorrelation from a 9- to 6-month lag (Fig. 13a). The ﬁrst implication of this is that any signal correlated to SOI in DJF will be correlated to SOI in the previous JJA without the need for a lagged physical mechanism. Nevertheless, the correlation between SMB or melt rates in DJF and SOI in the preceding JJA is higher than the synchronous correlation for all the drainage basins (solid curves in Fig. 13b–h), which suggests that the lagged relationship is not only a simple statistical artifact. The re- sults of Ding et al. (2011) and Steig et al. (2012) suggest that there could be a lagged mechanism whereby ENSO would inﬂuence West Antarctica in austral spring or winter, with a delayed response of SMB and melting in the following aus- tral summer. The number of melt days derived from satellite data also gives 6-month-lagged correlations to SOI that are as high or higher than synchronous correlations for most ice shelves (dashed curves in Fig. 13b–h). connection in summer was supported by Steig et al. (2012), who found the weakest correlations between NINO3.4 and wind stress anomalies in the Amundsen Sea in DJF com- pared to other seasons. Therefore, we investigated possible lags in the relationships to ENSO. While ENSO peaks in DJF, it starts to develop in MAM (March–April–May), as indicated by the growing SOI autocorrelation from a 9- to 6-month lag (Fig. 13a). The ﬁrst implication of this is that any signal correlated to SOI in DJF will be correlated to SOI in the previous JJA without the need for a lagged physical mechanism. Nevertheless, the correlation between SMB or melt rates in DJF and SOI in the preceding JJA is higher than the synchronous correlation for all the drainage basins (solid curves in Fig. 13b–h), which suggests that the lagged relationship is not only a simple statistical artifact. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector (2019) when using the number of melt days derived from satellite products, both the number of melt days and the melt rates simulated by MAR indicate less vari- ance explained by SOI, that is, between 5 % and 9 % for the individual drainage basins. Our MAR simulations certainly contain biases in the representation of the melting process and the way it affects surface properties such as albedo and roughness, but it is also possible that the number of melt days derived from microwave satellite data is biased due to vari- ability in surface conditions, percolation within fresh snow, meltwater ponding (observed on Pine Island; Kingslake et al., 2017) and satellite overpass time (Tedesco, 2009; Scott Numerous publications have explained the remote effects of ENSO on the West Antarctic climate through Rossby wave trains that connect the convective anomalies associated with ENSO in the equatorial Paciﬁc to Antarctica (e.g., Yuan and Martinson, 2001). However, austral winter and spring con- ditions are more favorable for Rossby wave trains to be formed and to propagate to high southern latitudes than sum- mer conditions (Harangozo, 2004; Lachlan-Cope and Con- nolley, 2006; Ding et al., 2011, and references therein). The poleward propagation of tropically sourced Rossby waves in summer is indeed inhibited by the strong polar front jet in the South Paciﬁc sector at that time of the year, which leads to Rossby wave reﬂection away from the Amundsen Sea region (Scott Yiu and Maycock, 2019). This lack of direct www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020 The Cryosphere, 14, 229–249, 2020 M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 241 M. Donat-Magnin et al.: SMB and surface melting in the A Figure 10. (a, b) Vertical integrated vapor transport (IVT) along the y axis (negative toward the continent) calculated as IVT [kg m−2] = R 700 925 q · v dP g , with q the speciﬁc humidity (g kg−1), v the wind speed (m s−1), P the pressure (Pa), and g the gravity (9.81 m s−2) and (c, d) cloud cover (no units, from 0 to 1) anomalies during low-SMB summers (left) and high-SMB summers (right). Anomalies are calculated as high or low composites minus the cli- matology over 1979–2017. The hatched area represents signiﬁcance > 90 % calculated with Welch’s t test. M. Donat Magnin et al.: SMB and surface melting in the Amundsen sector 241 Figure 10. www.the-cryosphere.net/14/229/2020/ M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector Partial correlations used to disen- tangle the SAM and ENSO inﬂuences on SMB do indicate a slightly stronger SMB–ENSO correlation when the effect of SAM is removed (in particular for Abbot and Cosgrove; see second and third columns of Table 5), but the effect is relatively small. For melt rates, the SAM modulation is very weak for all the basins (Table 5, fourth and ﬁfth columns). Figure 12. (a, b) The 500 hPa geopotential height (m) and (c, d) 500 hPa geopotential height divided by the domain-averaged value for each season and (e, f) 10 m wind (m s−1) anomalies dur- ing low-melt summers (left) and high-melt summers (right); scales of arrow lengths are shown near the upper right corner of panels (e) and (f). Anomalies are calculated as high or low composites mi- nus the climatology over 1979–2017. The hatched area represents signiﬁcance > 90 % calculated with Welch’s t test. ing in MAM created a dipole of sea ice anomalies, with de- creased (increased) concentration in the Ross Sea (Amund- sen and Bellingshausen seas). Using a novel sea ice budget analysis, they showed that the decreased concentration in the Ross Sea was then advected eastward, reaching the Amund- sen Sea in SON and DJF. Lastly, we discuss the relationship between surface melt and snowfall over the ice shelves of the Amundsen sector (last rows of Table 2). According to Table 2, runoff is null over all the ice shelves, which means that the ﬁrn is never saturated. In other words, all surface meltwater and rainfall refreeze within the ﬁrn. This is consistent with Pfeffer et al. (1991), who estimated that the melt rate needed to sat- urate the ﬁrn with water and lead to hydrofracturing can be estimated as 0.7 times the snowfall rate (both melt and snow- fall rates expressed in kilograms per square meter per second or millimeter water equivalent). This indicates that meltwa- ter ponding and complex surface hydrological ﬂows are un- likely to develop over West Antarctic ice shelves under the current climate. To reach saturation at the scale of the entire ice shelf in the future (and therefore to initiate hydrofractur- ing), the 0.7 ratio of Pfeffer et al. (1991) suggests that melt There is also another possible pathway for a lagged ENSO–sea ice relationship. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 242 Figure 12. (a, b) The 500 hPa geopotential height (m) and (c, d) 500 hPa geopotential height divided by the domain-averaged value for each season and (e, f) 10 m wind (m s−1) anomalies dur- ing low-melt summers (left) and high-melt summers (right); scales of arrow lengths are shown near the upper right corner of panels (e) and (f). Anomalies are calculated as high or low composites mi- nus the climatology over 1979–2017. The hatched area represents signiﬁcance > 90 % calculated with Welch’s t test. the surface (Jourdain et al., 2017; Merino et al., 2018), the connection through CDW intrusions may also explain a part of the lag between ENSO and DJF sea ice in the Amundsen Sea. We suggest that both mechanisms (eastward advection of sea ice anomalies and anomalous intrusions of CDW) may explain the 6-month lag between DJF SMB or melting and ENSO, and we leave the details of the ocean–sea ice pro- cesses for future research. Beyond the ASL and ENSO, we also ﬁnd that the SAM is not signiﬁcantly related to summer SMB and sur- face melt over individual drainage basins at interannual timescales, which agrees with Deb et al. (2018). This may appear contradictory to the results obtained by Medley and Thomas (2019), showing that the positive SAM trend from 1957 to 2000 largely explains the pattern of annual SMB trends over the Antarctic ice sheet. First of all, their resid- ual SMB trend (i.e. not related to SAM) is particularly strong in the Amundsen Sea Embayment (their Fig. 1e), highlight- ing that only a part of the SMB trend in that region may be related to the SAM trend. The multi-decadal SAM trend is also related to ozone depletion and emissions of greenhouse gases, and the interannual SAM variability may have differ- ent characteristics and impacts on SMB. Furthermore, the ab- sence of a SMB–SAM relationship in our MAR simulations is speciﬁc to the austral summer, which represents 15 % of the annual SMB, and correlations are more signiﬁcant for the other seasons (Table S3). Therefore, the signiﬁcant SAM– SMB relationship suggested by Medley and Thomas (2019) for annual SMB is not necessarily contradictory to our re- sults. Lastly, previous studies have suggested that the SAM– ENSO anticorrelation may diminish the impact of ENSO on surface melting and SMB. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector The re- sults of Ding et al. (2011) and Steig et al. (2012) suggest that there could be a lagged mechanism whereby ENSO would inﬂuence West Antarctica in austral spring or winter, with a delayed response of SMB and melting in the following aus- tral summer. The number of melt days derived from satellite data also gives 6-month-lagged correlations to SOI that are as high or higher than synchronous correlations for most ice shelves (dashed curves in Fig. 13b–h). within a few weeks in response to ENSO convective anoma- lies (e.g. Hoskins and Karoly, 1981; Mo and Higgins, 1998; Peters and Vargin, 2015). Therefore, the lag has to come from anomalies stored in a slower medium, such as snow- pack, ocean or sea ice. Snow surface melting in DJF is cor- related neither to the temperature of snow layers within the ﬁrst 2 m in the previous months (not shown) nor to the snow accumulated over the previous months (not shown). This in- dicates that heat diffusion in snow or preconditioned poros- ity or albedo of snow is not responsible for the 6-month lag. By contrast, we ﬁnd that El Niño events in JJA sig- niﬁcantly reduce the sea ice cover in the following DJF (Fig. 14). This is reminiscent of Clem et al. (2017), who found stronger lagged correlation between SON ENSO and DJF sea ice cover than synchronous correlation in DJF, with consequences on summer air temperatures. We suggest two possible explanations for this lagged ENSO–sea ice relation- ship. First, it could be slowly advected from the Ross Sea. Pope et al. (2017) indeed found that El Niño events develop- We now discuss possible explanations for this lag. As mentioned previously, the Rossby wave trains connecting the equatorial Paciﬁc to Antarctica are expected to develop www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020 M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector The Cryosphere, 14, 229–249, 2020 M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector MAR gives good results for near-surface temperatures (mean overestimation of 0.10 ◦C), near-surface wind speeds (mean underestimation of 0.42 m s−1) and SMB (local rela- tive bias < 20 % over the Thwaites basin). The mean surface melt rate over the Amundsen Sea region is underestimated by 18 % compared to the estimates derived from QuickSCAT (Trusel et al., 2013), and the interannual variability of sur- face melting is relatively well reproduced in terms of melt M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 243 Table 5. Partial correlation of −SOI vs. SMB or melt rates, removing the inﬂuence of SAM (columns 2 and 4). Corresponding full correlations are indicated in columns 3 and 5 (same as Tables 3 and 4). SOI vs. SMB or melt rates, removing the inﬂuence of SAM (columns 2 and 4). Corresponding full correlations 5 (same as Tables 3 and 4). Figure 13. Correlation between lagged 3-month averaged −SOI (i.e. DJF at zero lag, previous JJA at −6 lag) and (a) DJF SOI. (b–h) Simulated SMB and melt rates in individual drainage basins. The dashed curves correspond to the number of melt days derived from satellite data by Picard et al. (2007). Figure 14. Summer sea ice cover (%) anomaly (composites minus Figure 14. Summer sea ice cover (%) anomaly (composites minus the climatology over 1979–2017) during El Niño events in JJA (6 months before). Contours represent signiﬁcance with Welch’s t test. gional Atmosphere Model, MAR. We have ﬁrst evaluated our model conﬁguration in comparison to observational products (i.e. AWS, airborne-radar and ﬁrn-core SMB, melt days from satellite microwave, and melt rates from satellite scatterom- eter). MAR gives good results for near-surface temperatures (mean overestimation of 0.10 ◦C), near-surface wind speeds (mean underestimation of 0.42 m s−1) and SMB (local rela- tive bias < 20 % over the Thwaites basin). The mean surface melt rate over the Amundsen Sea region is underestimated by 18 % compared to the estimates derived from QuickSCAT (Trusel et al., 2013), and the interannual variability of sur- face melting is relatively well reproduced in terms of melt rate (R = 0.80) or number of melt days (R = 0.43 to 0.69 depending on the satellite product) as also found by previous studies using the same MAR version (i.e. Datta et al., 2019). M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector Similar underestimation was also found in another regional atmospheric model of the Amundsen region (underestima- tion of 30 %–50 % found by Lenaerts et al., 2017). Overall, Figure 13. Correlation between lagged 3-month averaged −SOI (i.e. DJF at zero lag, previous JJA at −6 lag) and (a) DJF SOI. (b–h) Simulated SMB and melt rates in individual drainage basins. The dashed curves correspond to the number of melt days derived from satellite data by Picard et al. (2007). rates would need to be multiplied by 2.5 (Cosgrove) to 40 (Crosson) compared to present conditions. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector The zonal wind stress over the Amundsen Sea continental shelf break is a good proxy for the transport of Circumpolar Deep Water (CDW) onto the continental shelf (Thoma et al., 2008; Holland et al., 2019). Steig et al. (2012) noted signiﬁcant correlations between wind stress and ENSO in JJA and SON but not in DJF. All these studies as well as Paolo et al. (2018) pointed out scales of a few months for the buildup and advection of CDW on the continental shelf and then into the ice shelf cavities where they produce basal melting, and Paolo et al. (2018) reported correlations between ENSO and ice shelf thinning 6 months later. As stronger ice shelf melt rates tend to decrease sea ice in this region due to the entrainment of warm CDW towards www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020 M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 243 Table 5. Partial correlation of −SOI vs. SMB or melt rates, removing the inﬂuence of SAM (columns 2 and 4). Corresponding full correlations are indicated in columns 3 and 5 (same as Tables 3 and 4). Partial correlation Partial correlation Drainage −SOI vs. SMB −SOI vs. surface melt Correlation −SOI basins (without SAM) −SOI vs. SMB −SOI vs. SMB (without SAM) vs. surface melt Abbot 0.36 0.25 0.21 0.23 0.23 Cosgrove 0.37 0.26 0.21 0.23 0.24 Pine Island 0.38 0.32 0.26 0.30 0.30 Thwaites 0.38 0.33 0.23 0.25 0.29 Crosson 0.45 0.40 0.29 0.24 0.28 Dotson 0.40 0.36 0.25 0.23 0.27 Getz 0.26 0.30 0.18 0.17 0.22 Figure 13. Correlation between lagged 3-month averaged −SOI (i.e. DJF at zero lag, previous JJA at −6 lag) and (a) DJF SOI. (b–h) Simulated SMB and melt rates in individual drainage basins. The dashed curves correspond to the number of melt days derived from satellite data by Picard et al. (2007). rates would need to be multiplied by 2.5 (Cosgrove) to 40 (Crosson) compared to present conditions. Figure 14. Summer sea ice cover (%) anomaly (composites minus the climatology over 1979–2017) during El Niño events in JJA (6 months before). Contours represent signiﬁcance with Welch’s t test. gional Atmosphere Model, MAR. We have ﬁrst evaluated our model conﬁguration in comparison to observational products (i.e. AWS, airborne-radar and ﬁrn-core SMB, melt days from satellite microwave, and melt rates from satellite scatterom- eter). 5 Conclusions In this paper we have analyzed possible drivers for summer surface melt and SMB interannual variability over the last decades in the Amundsen sector, West Antarctica. For this, we have simulated the 1979 to 2017 period with the Re- M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 244 our results indicate that MAR is a suitable tool to study in- terannual variability in the Amundsen sector. to reach ice shelf cavities where increased basal melting fa- vors the entrainment of this water towards the ocean surface (Jourdain et al., 2017). It should nonetheless be noted that even accounting for this 6-month lag, the inﬂuence of ENSO on summer SMB and melt rates remains weak, not explain- ing more than 15 % variance. to reach ice shelf cavities where increased basal melting fa- vors the entrainment of this water towards the ocean surface (Jourdain et al., 2017). It should nonetheless be noted that even accounting for this 6-month lag, the inﬂuence of ENSO on summer SMB and melt rates remains weak, not explain- ing more than 15 % variance. Then, we have analyzed the interannual variability of sum- mer SMB. The strongest summer SMB occurs over Thwaites and Pine Island glaciers when the ASL migrates far westward (by typically 30◦) and southward (by typically 3–4◦). This promotes a southward ﬂow on the eastern ﬂank of the ASL, towards the glaciers, with resulting increased moisture con- vergence, precipitation and therefore SMB. Our study hence provides further support for the connection between Antarc- tic precipitation and the ASL longitudinal position that was previously described by Hosking et al. (2013) based on the ERA-Interim reanalysis. In terms of climate indices, this cor- responds to an anticorrelation between SMB and the ASL longitudinal position. This anticorrelation is found for all the drainage basins of the Amundsen Sea Embayment, and the part of the SMB variance explained by the ASL longitudinal migrations ranges from 2 % to 41 % (increasing westward). A small part of the SMB variance is also related to ENSO, with higher SMB during El Niño events and lower SMB dur- ing La Niña, but less than 8 % of the SMB variance is ex- plained by ENSO variability. This SMB connection to ENSO is independent from its connection with the ASL longitudinal position. Lastly, we propose that the rate of surface water needed to saturate the ﬁrn and lead to hydrofracturing has to increase by a factor of 2.5 to 40 depending on the ice shelf. Such an increase could be reached under strong warming scenarios given the exponential temperature dependence described by Trusel et al. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector (2015), although snowfall is also expected to in- crease (Krinner et al., 2008; Agosta et al., 2013; Ligtenberg et al., 2013; Lenaerts et al., 2016; Palerme et al., 2017), re- quiring even more meltwater to reach saturation. In their pro- jections, Kuipers Munneke et al. (2014) found that the west- ern part of Abbot as well as Cosgrove could become water- saturated before the end of the twenty-second century, but the other ice shelves of the Amundsen sector remained non- saturated. Further work will be needed to assess the robust- ness of these projections, with other ﬁrn models and global projections. Code and data availability. The MAR code (version 3.9.1) is avail- able on the MAR website (http://mar.cnrs.fr/, last access: 17 Jan- uary 2020); outputs from the Amundsen simulation presented in this study are available on https://doi.org/10.5281/zenodo.2815907. We have also analyzed the interannual variability of sum- mer surface melt rates. The strongest surface melting occurs over Thwaites and Pine Island glaciers when the ASL under- goes an anticyclonic anomaly (likely the signature of block- ing activity), which is visible through anomalies of the ASL relative central pressure. Such an anomaly promotes a south- ward anomaly of near-surface winds and moisture conver- gence over the Amundsen Sea Embayment. As recently de- scribed by Scott et al. (2019), this leads to increased cloud cover and downward longwave radiation, which in turn in- creases surface melting. As for SMB, we do not ﬁnd that surface melt rate variability in our simulations is strongly connected to ENSO as it does not explain more than 9 % of the total variance in simulated summer surface melt rate (or 12 % of the number of melt days). By contrast and for un- known reasons, the variance in number of melt days derived from satellite products indicates that as much as 25 % of the variance in these products could be explained by −SOI. Supplement. The supplement related to this article is available on- line at: https://doi.org/10.5194/tc-14-229-2020-supplement. Author contributions. The study was designed by MD-M and NCJ. Setup of the MAR domain conﬁguration was made by MD-M, CA, AD and NCJ. CA, XF, HG, CK and CA developed and tuned the MAR model for Antarctica, and they contributed to improving and interpreting our simulations. CK developed the scripts used to com- pare MAR to AWS data. www.the-cryosphere.net/14/229/2020/ www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020 References Agosta, C., Favier, V., Krinner, G., Gallée, H., Fettweis, X., and Genthon, C.: High-resolution modelling of the Antarctic sur- face mass balance, application for the twentieth, twenty ﬁrst and twenty second centuries, Clim. Dynam., 41, 3247–3260, https://doi.org/10.1007/s00382-013-1903-9, 2013. Clem, K. R., Renwick, J. A., and McGregor, J.: Large-Scale Forc- ing of the Amundsen Sea Low and Its Inﬂuence on Sea Ice and West Antarctic Temperature, J. Climate, 30, 8405–8424, https://doi.org/10.1175/JCLI-D-16-0891.1, 2017. Cullather, R. I., Bromwich, D. H., and Van Woert, M. L.: Inter- annual variations in Antarctic precipitation related to El Niño- Southern Oscillation, J. Geophys. Res.-Atmos., 101, 19109– 19118, https://doi.org/10.1029/96jd01769, 1996. Agosta, C., Amory, C., Kittel, C., Orsi, A., Favier, V., Gallée, H., van den Broeke, M. R., Lenaerts, J. T. M., van Wessem, J. M., van de Berg, W. J., and Fettweis, X.: Estimation of the Antarctic sur- face mass balance using the regional climate model MAR (1979– 2015) and identiﬁcation of dominant processes, The Cryosphere, 13, 281–296, https://doi.org/10.5194/tc-13-281-2019, 2019. Datta, R. T., Tedesco, M., Fettweis, X., Agosta, C., Lher- mitte, S., Lenaerts, J., and Wever, N.: The Effect of Foehn- Induced Surface Melt on Firn Evolution Over the North- east Antarctic Peninsula, Geophys. Res. Lett., 46, L21805, https://doi.org/10.1029/2018GL080845, 2019. Amory, C., Trouvilliez, A., Gallée, H., Favier, V., Naaim-Bouvet, F., Genthon, C., Agosta, C., Piard, L., and Bellot, H.: Compar- ison between observed and simulated aeolian snow mass ﬂuxes in Adélie Land, East Antarctica, The Cryosphere, 9, 1373–1383, https://doi.org/10.5194/tc-9-1373-2015, 2015. Deb, P., Orr, A., Bromwich, D. H., Nicolas, J. P., Turner, J., and Hosking, J. S.: Summer drivers of atmospheric variabil- ity affecting ice shelf thinning in the Amundsen Sea Embay- ment, West Antarctica, Geophys. Res. Lett., 45, 4124–4133, https://doi.org/10.1029/2018gl077092, 2018. Asay-Davis, X. S., Jourdain, N. C., and Nakayama, Y.: Devel- opments in simulating and parameterizing interactions between the Southern Ocean and the Antarctic Ice sheet, Curr. Clim. Change Rep., 3, 316–329, https://doi.org/10.1007/s40641-017- 0071-0, 2017. Deconto, R. M. and Pollard, D.: Contribution of Antarctica to past and future sea-level rise, Nature, 531, 591–597, https://doi.org/10.1038/nature17145, 2016. Bell, R. E., Banwell, A. F., Trusel, L. D., and Kingslake, J.: Antarctic surface hydrology and impacts on ice- sheet mass balance, Nat. Clim. Change, 8, 1044–1052, https://doi.org/10.1038/s41558-018-0326-3, 2018. Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector JDW and VF contributed to the interpreta- tion of our results related to interannual variability. All the authors signiﬁcantly contributed to this paper. p p y We also suggest that at least a part of the ENSO–SMB and ENSO–melt relationships in summer is inherited from the previous austral winter (JJA). Rossby wave trains gener- ated by convective anomalies related to developing El Niño events in austral winter signiﬁcantly affect the Antarctic re- gion, and we suggest that this has some impact on SMB and surface melting in the Amundsen sector 6 months later. Such a delay could be related either to sea ice anomalies gener- ated by ENSO in the Ross Sea in austral winter and taking 6 months to be advected to the Amundsen Sea (Pope et al., 2017) or to marine intrusions of Circumpolar Deep Water that are favored by El Niño events in austral winter (Steig et al., 2012). Circumpolar Deep Water may take 6 months Competing interests. The authors declare that they have no conﬂict of interest Acknowledgements. This work was funded by the French National Research Agency (ANR) through the TROIS-AS (ANR-15-CE01- 0005-01) project. The development of MAR was partly funded by Labex OSUG@2020 (ANR10 LABX56) through the “Tout le Monde se MAR” project. All the computations presented in this paper were performed using the GRICAD infrastructure (https:// gricad.univ-grenoble-alpes.fr, last access: 17 January 2020), which is partly supported by the Equip@Meso project (ANR-10-EQPX- 29-01) of the program “Investissements d’Avenir” supervised by The Cryosphere, 14, 229–249, 2020 www.the-cryosphere.net/14/229/2020/ 245 M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector ANR, by the Rhône-Alpes region (GRANT CPER07_13 CIRA: http://www.ci-ra.org, last access: last access: 17 January 2020) and by France-Grilles (http://www.france-grilles.fr, last access: last ac- cess: 17 January 2020). We thank Ghislain Picard, Luke Trusel, Julien Nicolas, Yetang Wang and Brooke Medley for making their data available. Bromwich, D. H., Nicolas, J. P., Monaghan, A. J., Lazzara, M. A., Keller, L. M., Weidner, G. A., and Wilson, A. B.: Central West Antarctica among the most rapidly warming regions on Earth, Nat. Geosci., 6, 139–145, https://doi.org/10.1038/ngeo1671, 2013. Brun, E., David, P., Sudul, M., and Brunot, G.: A numer- ical model to simulate snow-cover stratigraphy for op- erational avalanche forecasting, J. Glaciol., 38, 13–22, https://doi.org/10.1017/s0022143000009552, 1992. Financial support. This research has been supported by the French National Research Agency (ANR) (grant no. ANR-15-CE01-0005- 01), the Labex OSUG@2020 (grant no. ANR10 LABX56) and the ANR-10-EQPX-29-01 (grant no. CPER07_13 CIRA: http://www. ci-ra.org). Cai, W., Borlace, S., Lengaigne, M., Van Rensch, P., Collins, M., Vecchi, G., Timmermann, A., Santoso, A., McPhaden, M. J., Wu, L., England, M. H., Wang, G., Guilyardi, E., and Jin, F.-F.: Increasing frequency of extreme El Niño events due to greenhouse warming, Nat. Clim. change, 4, 111–116, https://doi.org/10.1038/nclimate2100, 2014. Cai, W., Wang, G., Santoso, A., Lin, X., and Wu, L.: Deﬁnition of extreme El Niño and its impact on projected increase in ex- treme El Niño frequency, Geophys. Res. Lett., 44, 11184–11190, https://doi.org/10.1002/2017gl075635, 2017. Review statement. This paper was edited by Kenichi Matsuoka and reviewed by two anonymous referees. Chen, G. and Held, I. M.: Phase speed spectra and the recent pole- ward shift of Southern Hemisphere surface westerlies, Geophys. Res. Lett., 34, L21805, doi;10.1029/2007gl031200 , 2007. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 246 thickness datasets for Antarctica, The Cryosphere, 7, 375–393, https://doi.org/10.5194/tc-7-375-2013, 2013. thickness datasets for Antarctica, The Cryosphere, 7, 375–393, https://doi.org/10.5194/tc-7-375-2013, 2013. Deser, C., Phillips, A. S., Tomas, R. A., Okumura, Y. M., Alexan- der, M. A., Capotondi, A., Scott, J. D., Kwon, Y.-O., and Ohba, M.: ENSO and Paciﬁc Decadal Variability in the Community Climate System Model Version 4, J. Climate, 25, 2622–2651, https://doi.org/10.1175/jcli-d-11-00301.1, 2012. Fyke, J., Lenaerts, J. T. M., and Wang, H.: Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variabil- ity, The Cryosphere, 11, 2595–2609, https://doi.org/10.5194/tc- 11-2595-2017, 2017. Ding, Q., Steig, E. J., Battisti, D. S., and Küttel, M.: Winter warming in West Antarctica caused by central tropical Paciﬁc warming, Nat. Geosci., 4, 398, https://doi.org/10.1038/ngeo1129, 2011. Gallée, H.: Simulation of the mesocyclonic activ- ity in the Ross Sea, Antarctica, Mon. Weather Rev., 123, 2051–2069, https://doi.org/10.1175/1520- 0493(1995)123<2051:sotmai>2.0.co;2, 1995. Dutrieux, P., De Rydt, J., Jenkins, A., Holland, P. R., Ha, H. K., Lee, S. H., Steig, E. J., Ding, Q., Abrahamsen, E. P., and Schröder, M.: Strong sensitivity of Pine Island ice- shelf melting to climatic variability, Science, 343, 174–178, https://doi.org/10.1126/science.1244341, 2014. Gallée, H. and Gorodetskaya, I. V.: Validation of a limited area model over Dome C, Antarctic Plateau, during winter, Clim. Dy- nam., 34, 61, https://doi.org/10.1007/s00382-008-0499-y, 2010. Edwards, T. L., Brandon, M. A., Durand, G., Edwards, N. R., Golledge, N. R., Holden, P. B., Nias, I. J., Payne, A. J., Ritz, C., and Wernecke, A.: Revisiting Antarctic ice loss due to marine ice-cliff instability, Nature, 566, 58, https://doi.org/10.1038/s41586-019-0901-4, 2019. Gallée, H. and Schayes, G.: Development of a three-dimensional meso-γ primitive equation model: katabatic winds simu- lation in the area of Terra Nova Bay, Antarctica, Mon. Weather Rev., 122, 671–685, https://doi.org/10.1175/1520- 0493(1994)122<0671:doatdm>2.0.co;2, 1994. Gallée, H., Preunkert, S., Argentini, S., Frey, M. M., Genthon, C., Jourdain, B., Pietroni, I., Casasanta, G., Barral, H., Vi- gnon, E., Amory, C., and Legrand, M.: Characterization of the boundary layer at Dome C (East Antarctica) during the OPALE summer campaign, Atmos. Chem. Phys., 15, 6225– 6236, https://doi.org/10.5194/acp-15-6225-2015, 2015. Favier, L., Durand, G., Cornford, S., Gudmundsson, G., Gagliar- dini, O., Gillet-Chaulet, F., Zwinger, T., Payne, A., and Le Brocq, A.: Retreat of Pine Island Glacier controlled by ma- rine ice-sheet instability, Nat. Clim. Change, 4, 117–121, https://doi.org/10.1038/nclimate2094, 2014. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector Favier, V., Agosta, C., Parouty, S., Durand, G., Delaygue, G., Gallée, H., Drouet, A.-S., Trouvilliez, A., and Krinner, G.: An updated and quality controlled surface mass bal- ance dataset for Antarctica, The Cryosphere, 7, 583–597, https://doi.org/10.5194/tc-7-583-2013, 2013. Genthon, C. and Cosme, E.: Intermittent signature of ENSO in west-Antarctic precipitation, Geophys. Res. Lett., 30, 2081, https://doi.org/10.1029/2003gl018280, 2003. Gerber, E. P. and Martineau, P.: Quantifying the variabil- ity of the annular modes: reanalysis uncertainty vs. sam- pling uncertainty, Atmos. Chem. Phys., 18, 17099–17117, https://doi.org/10.5194/acp-18-17099-2018, 2018. Favier, V., Krinner, G., Amory, C., Gallée, H., Beaumet, J., and Agosta, C.: Antarctica-Regional Climate and Surface Mass Budget, Curr. Clim. Change Reports, 3, 303–315, https://doi.org/10.1007/s40641-017-0072-z, 2017. Harangozo, S. A.: The relationship of Paciﬁc deep tropical convec- tion to the winter and springtime extratropical atmospheric circu- lation of the South Paciﬁc in El Niño events, Geophys. Res. Lett., 31, L05206, https://doi.org/10.1029/2003GL018667, 2004. Fettweis, X., Box, J. E., Agosta, C., Amory, C., Kittel, C., Lang, C., van As, D., Machguth, H., and Gallée, H.: Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model, The Cryosphere, 11, 1015–1033, https://doi.org/10.5194/tc-11-1015-2017, 2017. Hartmann, D. L. and Lo, F.: Wave-driven zonal ﬂow vacillation in the Southern Hemisphere, J. Atmos. Sci., 55, 1303–1315, https://doi.org/10.1175/1520- 0469(1998)055<1303:wdzfvi>2.0.co;2, 1998. Fogt, R. L. and Wovrosh, A. J.: The Relative Inﬂuence of Tropical Sea Surface Temperatures and Radiative Forcing on the Amundsen Sea Low, J. Climate, 28, 8540–8555, https://doi.org/10.1175/jcli-d-15-0091.1, 2015. Holland, P. R., Bracegirdle, T. J., Dutrieux, P., Jenkins, A., and Steig, E. J.: West Antarctic ice loss inﬂuenced by internal climate variability and anthropogenic forcing, Nat. Geosci., 12, 718–724, https://doi.org/10.1038/s41561-019-0420-9, 2019. Fogt, R. L., Bromwich, D. H., and Hines, K. M.: Understanding the SAM inﬂuence on the South Paciﬁc ENSO teleconnection, Clim. Dynam., 36, 1555–1576, https://doi.org/10.1007/s00382- 010-0905-0, 2011. Hosking, J. S., Orr, A., Marshall, G. J., Turner, J., and Phillips, T.: The inﬂuence of the Amundsen–Bellingshausen Seas low on the climate of West Antarctica and its representation in cou- pled climate model simulations, J. Climate, 26, 6633–6648, https://doi.org/10.1175/jcli-d-12-00813.1, 2013. Fretwell, P., Pritchard, H. D., Vaughan, D. G., Bamber, J. L., Bar- rand, N. E., Bell, R., Bianchi, C., Bingham, R. G., Blanken- ship, D. D., Casassa, G., Catania, G., Callens, D., Conway, H., Cook, A. J., Corr, H. F. J., Damaske, D., Damm, V., Ferracci- oli, F., Forsberg, R., Fujita, S., Gim, Y., Gogineni, P., Griggs, J. A., Hindmarsh, R. References M., van de Berg, I., Biblot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Greer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Holm, E. V., Isak- sen, L., Kallberg, P., Kohler, M., Matricardi, M., McNally, A. P., Mong-Sanz, B. M., Morcette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thepaut, J. N., and Vitart, F.: The ERA- Interim reanalysis: Conﬁguration and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597, https://doi.org/10.1002/qj.493, 2011. Bracegirdle, T. J., Connolley, W. M., and Turner, J.: Antarctic cli- mate change over the twenty ﬁrst century, J. Geophys. Res.- Atmos., 113, D03103, https://doi.org/10.1029/2007jd008933, 2008. Bromwich, D. H., Rogers, A. N., Kåallberg, P., Cullather, R. I., White, J. W., and Kreutz, K. J.: ECMWF analyses and reanalyses depiction of ENSO signal in Antarctic precipita- tion, J. Climate, 13, 1406–1420, https://doi.org/10.1175/1520- 0442(2000)013<1406:EAARDO>2.0.CO;2, 2000. De De Ridder, K. and Gallée, H.: Land surface–induced re- gional climate change in southern Israel, J. Appl. Me- teorol., 37, 1470–1485, https://doi.org/10.1175/1520- 0450(1998)037<1470:LSIRCC>2.0.CO;2, 1998. Bromwich, D. H., Nicolas, J. P., and Monaghan, A. J.: An Assess- ment of Precipitation Changes over Antarctica and the Southern Ocean since 1989 in Contemporary Global Reanalyses, J. Cli- mate, 24, 4189–4209, 2011. The Cryosphere, 14, 229–249, 2020 www.the-cryosphere.net/14/229/2020/ M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 247 MAR forced by MIROC5, The Cryosphere, 9, 945–956, https://doi.org/10.5194/tc-9-945-2015, 2015. MAR forced by MIROC5, The Cryosphere, 9, 945–956, https://doi.org/10.5194/tc-9-945-2015, 2015. tic near surface air temperature, Atmos. Res., 226, 181–191, https://doi.org/10.1016/j.atmosres.2019.04.029, 2019. tic near surface air temperature, Atmos. Res., 226, 181–191, https://doi.org/10.1016/j.atmosres.2019.04.029, 2019. Lenaerts, J., den Broeke, M., Déry, S., Meijgaard, E., Berg, W., Palm, S. P., and Sanz Rodrigo, J.: Modeling drifting snow in Antarctica with a regional climate model: 1. Methods and model evaluation, J. Geophys. Res.-Atmos., 117, D05108, https://doi.org/10.1029/2011jd016145, 2012. Izumo, T., Vialard, J., Lengaigne, M., de Boyer Montegut, C., Behera, S. K., Luo, J.-J., Cravatte, S., Masson, S., and Yamagata, T.: Inﬂuence of the state of the Indian Ocean Dipole on the following year’s El Niño, Nat. Geosci., 3, 168, https://doi.org/10.1038/ngeo760, 2010. Jenkins, A., Dutrieux, P., Jacobs, S., Steig, E. J., Gudmundsson, G. H., Smith, J., and Heywood, K. J.: Decadal Ocean Forcing and Antarctic Ice Sheet Response: Lessons from the Amundsen Sea, Oceanography, 29, 106–117, 2016. Lenaerts, J. T., Vizcaino, M., Fyke, J., Van Kampenhout, L., and van den Broeke, M. R.: Present-day and future Antarc- tic ice sheet climate and surface mass balance in the Com- munity Earth System Model, Clim. Dynam., 47, 1367–1381, https://doi.org/10.1007/s00382-015-2907-4, 2016. Jenkins, A., Shoosmith, D., Dutrieux, P., Jacobs, S., Kim, T. W., Lee, S. H., Ha, H. K., and Stammerjohn, S.: West Antarctic Ice Sheet retreat in the Amundsen Sea driven by decadal oceanic variability, Nat. Geosci., 11, 733–738, https://doi.org/10.1038/s41561-018-0207-4, 2018. Lenaerts, J. T., Ligtenberg, S. R., Medley, B., Van de Berg, W. J., Konrad, H., Nicolas, J. P., Van Wessem, J. M., Trusel, L. D., Mulvaney, R., Tuckwell, R. J., Hogg, A. E., and Thomas, E. R.: Climate and surface mass balance of coastal West Antarctica re- solved by regional climate modelling, Ann. Glaciol., 59, 29–41, https://doi.org/10.1017/aog.2017.42, 2017. Jones, J. M., Gille, S. T., Goosse, H., Abram, N. J., Canziani, P. O., Charman, D. J., Clem, K. R., Crosta, X., de Lavergne, C., Eisenman, I., England, M. H., Fogt, R. L., Frankcombe, L. M., Marshall, G. J., Masson-Delmotte, V., Morrison, A. K., Orsi, A. J., Raphael, M. N., Renwick, J. A., Schneider, D. P., Simpkins, G. R., Steig, E. J., Stenni, B., Swingedouw, D., and Vance, T. R.: Assessing recent trends in high-latitude Southern Hemisphere surface climate, Nat. Clim. Change, 6, 917–926, https://doi.org/10.1038/nclimate3103, 2016. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector Ligtenberg, S., Van de Berg, W., Van den Broeke, M., Rae, J., and Van Meijgaard, E.: Future surface mass balance of the Antarctic ice sheet and its inﬂuence on sea level change, simulated by a re- gional atmospheric climate model, Clim. Dynam., 41, 867–884, https://doi.org/10.1007/s00382-013-1749-1, 2013. Limpasuvan, V. and Hartmann, D. L.: Eddies and the annular modes of climate variability, Geophys. Res. Lett., 26, 3133– 3136, https://doi.org/10.1029/1999gl010478, 1999. Joughin, I., Smith, B. E., and Medley, B.: Marine ice sheet collapse potentially under way for the Thwaites Glacier Basin, West Antarctica, Science, 344, 735–738, https://doi.org/10.1126/science.1249055, 2014. Marshall, G. J.: Trends in the Southern Annular Mode from observations and reanalyses, J. Cli- mate, 16, 4134–4143, https://doi.org/10.1175/1520- 0442(2003)016<4134:titsam>2.0.co;2 2003. Jourdain, N. C., Mathiot, P., Merino, N., Durand, G., Le Som- mer, J., Spence, P., Dutrieux, P., and Madec, G.: Ocean circu- lation and sea-ice thinning induced by melting ice shelves in the Amundsen Sea, J. Geophys. Res.-Oceans, 122, 2550–2573, https://doi.org/10.1002/2016jc012509, 2017. Medley, B. and Thomas, E.: Increased snowfall over the Antarc- tic Ice Sheet mitigated twentieth-century sea-level rise, Nat. Clim. Change, 9, 34, https://doi.org/10.1038/s41558-018-0356- x, 2019. Medley, B., Joughin, I., Das, S., Steig, E., Conway, H., Gogi- neni, S., Criscitiello, A., McConnell, J., Smith, B., van den Broeke, M., Lenaerts, J. T. M., Bromwich, D. H., and Nico- las, J. P.: Airborne-radar and ice-core observations of an- nual snow accumulation over Thwaites Glacier, West Antarc- tica conﬁrm the spatiotemporal variability of global and re- gional atmospheric models, Geophys. Res. Lett., 40, 3649–3654, https://doi.org/10.1002/grl.50706, 2013. Kingslake, J., Ely, J. C., Das, I., and Bell, R. E.: Widespread move- ment of meltwater onto and across Antarctic ice shelves, Nature, 544, 349, https://doi.org/10.1038/nature22049, 2017. Kittel, C., Amory, C., Agosta, C., Delhasse, A., Doutreloup, S., Huot, P.-V., Wyard, C., Fichefet, T., and Fettweis, X.: Sensi- tivity of the current Antarctic surface mass balance to sea sur- face conditions using MAR, The Cryosphere, 12, 3827–3839, https://doi.org/10.5194/tc-12-3827-2018, 2018. g g Medley, B., Joughin, I., Smith, B. E., Das, S. B., Steig, E. J., Conway, H., Gogineni, S., Lewis, C., Criscitiello, A. S., Mc- Connell, J. R., van den Broeke, M. R., Lenaerts, J. T. M., Bromwich, D. H., Nicolas, J. P., and Leuschen, C.: Constrain- ing the recent mass balance of Pine Island and Thwaites glaciers, West Antarctica, with airborne observations of snow accumula- tion, The Cryosphere, 8, 1375–1392, https://doi.org/10.5194/tc- 8-1375-2014, 2014. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector C. A., Holmlund, P., Holt, J. W., Jacobel, R. W., Jenkins, A., Jokat, W., Jordan, T., King, E. C., Kohler, J., Krabill, W., Riger-Kusk, M., Langley, K. A., Leitchenkov, G., Leuschen, C., Luyendyk, B. P., Matsuoka, K., Mouginot, J., Nitsche, F. O., Nogi, Y., Nost, O. A., Popov, S. V., Rignot, E., Rippin, D. M., Rivera, A., Roberts, J., Ross, N., Siegert, M. J., Smith, A. M., Steinhage, D., Studinger, M., Sun, B., Tinto, B. K., Welch, B. C., Wilson, D., Young, D. A., Xiangbin, C., and Zirizzotti, A.: Bedmap2: improved ice bed, surface and Hosking, J. S., Orr, A., Bracegirdle, T. J., and Turner, J.: Future cir- culation changes off West Antarctica: Sensitivity of the Amund- sen Sea Low to projected anthropogenic forcing, Geophys. Res. Lett., 43, 367–376, https://doi.org/10.1002/2015gl067143, 2016. J. A., Hindmarsh, R. C. A., Holmlund, P., Holt, J. W., Jacobel, , Jenkins, A., Jokat, W., Jordan, T., King, E. C., Koh J., Krabill, W., Riger-Kusk, M., Langley, K. A., Leitchenkov, Hoskins, B. J. and Karoly, D. J.: The steady linear response of a spherical atmosphere to thermal and orographic forcing, J. Atmos. Sci., 38, 1179–1196, https://doi.org/10.1175/1520- 0469(1981)038<1179:tslroa>2.0.co;2, 1981. Huai, B., Wang, Y., Ding, M., Zhang, J., and Dong, X.: An as- sessment of recent global atmospheric reanalyses for Antarc- www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020 M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector E.: On the Interpretation of EOF Analysis of ENSO, Atmospheric Kelvin Waves, and the MJO, J. Climate, 28, 1148– 1165, https://doi.org/10.1175/JCLI-D-14-00398.1, 2014. Pattyn, F., Ritz, C., Hanna, E., Asay-Davis, X., DeConto, R., Durand, G., Favier, L., Fettweis, X., Goelzer, H., Golledge, N. R., Kuipers Munneke, P., Lenaerts, J. T. M., Nowicki, S., Payne, A. J., Robinson, A., Seroussi, H., Trusel, L. D., and van den Broeke, M.: The Greenland and Antarctic ice sheets un- der 1.5◦C global warming, Nat. Clim. Change, 8, 1053–1061, https://doi.org/10.1038/s41558-018-0305-8, 2018. Scambos, T., Fricker, H. A., Liu, C.-C., Bohlander, J., Fas- took, J., Sargent, A., Massom, R., and Wu, A.-M.: Ice shelf disintegration by plate bending and hydro-fracture: Satel- lite observations and model results of the 2008 Wilkins ice shelf break-ups, Earth Planet. Sci. Lett., 280, 51–60, https://doi.org/10.1016/j.epsl.2008.12.027, 2009. Peters, D. H. and Vargin, P.: Inﬂuence of subtropical Rossby wave trains on planetary wave activity over Antarctica in September 2002, Tellus A, 67, 25875, https://doi.org/10.3402/tellusa.v67.25875, 2015. Schoof, C.: Ice sheet grounding line dynamics: Steady states, sta- bility, and hysteresis, J. Geophys. Res.-Earth Surf., 112, F03S28, https://doi.org/10.1029/2006jf000664, 2007. Pfeffer, W. T., Meier, M. F., and Illangasekare, T. H.: Retention of Greenland runoff by refreezing: Implications for projected future sea level change, J. Geophys. Res.-Oceans, 96, 22117–22124, https://doi.org/10.1029/91JC02502, 1991. Scott, R. C., Nicolas, J. P., Bromwich, D. H., Norris, J. R., and Lu- bin, D.: Meteorological Drivers and Large-Scale Climate Forc- ing of West Antarctic Surface Melt, J. Climate, 32, 665–684, https://doi.org/10.1175/jcli-d-18-0233.1, 2019. Philander, S., Lau, N., Pacanowski, R., and Nath, M.: Two Different Simulations of the Southern Oscillation and El Nino with Coupled Ocean–Atmosphere General Circulation Models, Philos. Trans. Roy. Soc. London A, 329, 167–177, https://doi.org/10.1098/rsta.1989.0068, 1989. Scott Yiu, Y. Y. and Maycock, A. C.: On the Seasonality of the El Niño Teleconnection to the Amundsen Sea Region, J. Climate, 32, 4829–4845, https://doi.org/10.1175/JCLI-D-18- 0813.1, 2019. Picard, G. and Fily, M.: Surface melting observations in Antarctica by microwave radiometers: Correcting 26-year time series from changes in acquisition hours, Remote Sens. Environ., 104, 325– 336, https://doi.org/10.1016/j.rse.2006.05.010, 2006. Shepherd, A. and Nowicki, S.: Improvements in ice-sheet sea-level projections, Nat. Clim. Change, 7, 672–674, https://doi.org/10.1038/nclimate3400, 2017. Shepherd, A., Ivins, E., Rignot, E., et al.: Mass balance of the Antarctic ice sheet from 1992 to 2017, Nature, 558, 219–222, https://doi.org/10.1038/s41586-018-0179-y, 2018. Picard, G., Fily, M., and Gallée, H.: Surface melt- ing derived from microwave radiometers: a climatic indicator in Antarctica, Ann. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 248 Rev., 126, 1581–1596, https://doi.org/10.1175/1520- 0493(1998)126<1581:TPSAMA>2.0.CO;2, 1998. Pritchard, H., Ligtenberg, S., Fricker, H., Vaughan, D., Van den Broeke, M., and Padman, L.: Antarctic ice-sheet loss driven by basal melting of ice shelves, Nature, 484, 502–505, https://doi.org/10.1038/nature10968, 2012. Mouginot, J., Rignot, E., and Scheuchl, B.: Sustained increase in ice discharge from the Amundsen Sea Embayment, West Antarc- tica, from 1973 to 2013, Geophys. Res. Lett., 41, 1576–1584, https://doi.org/10.1002/2013gl059069, 2014. Raphael, M., Marshall, G., Turner, J., Fogt, R., Schneider, D., Dixon, D., Hosking, J., Jones, J., and Hobbs, W.: The Amundsen Sea low: Variability, change, and impact on Antarctic climate, B. Am. Meteorol. Soc., 97, 111–121, https://doi.org/10.1175/bams- d-14-00018.1, 2016. Newman, M., Shin, S.-I., and Alexander, M. A.: Natural vari- ation in ENSO ﬂavors, Geophys. Res. Lett., 38, L14705, https://doi.org/10.1029/2011gl047658, 2011. Raphael, M. N. and Hobbs, W.: The inﬂuence of the large-scale atmospheric circulation on Antarctic sea ice during ice ad- vance and retreat seasons, Geophys. Res. Lett., 41, 5037–5045, https://doi.org/10.1002/2014gl060365, 2014. Nicolas, J. P. and Bromwich, D. H.: Climate of West Antarctica and Inﬂuence of Marine Air Intrusions, J. Climate, 24, 49–67, https://doi.org/10.1175/2010JCLI3522.1, 2010. Nicolas, J. P., Vogelmann, A. M., Scott, R. C., Wilson, A. B., Cadeddu, M. P., Bromwich, D. H., Verlinde, J., Lubin, D., Rus- sell, L. M., Jenkinson, C., Powers, H. H., Ryczek, M., Stone, G., and Wille, J. D.: January 2016 extensive summer melt in West Antarctica favoured by strong El Niño, Nat. Commun., 8, ncomms15799, https://doi.org/10.1038/ncomms15799, 2017. Rignot, E., Mouginot, J., Scheuchl, B., van den Broeke, M., van Wessem, M. J., and Morlighem, M.: Four decades of Antarctic Ice Sheet mass balance from 1979–2017, P. Natl. Acad. Sci. USA, 116, 1095–1103, https://doi.org/10.1073/pnas.1812883116, 2019. Ritz, C., Edwards, T. L., Durand, G., Payne, A. J., Peyaud, V., and Hindmarsh, R. C.: Potential sea-level rise from Antarctic ice- sheet instability constrained by observations, Nature, 528, 115– 118, https://doi.org/10.1038/nature16147, 2015. Palerme, C., Genthon, C., Claud, C., Kay, J. E., Wood, N. B., and L’Ecuyer, T.: Evaluation of current and projected Antarc- tic precipitation in CMIP5 models, Clim. Dynam., 48, 225–239, https://doi.org/10.1007/s00382-016-3071-1, 2017. Ropelewski, C. F. and Jones, P. D.: An Extension of the Tahiti–Darwin Southern Oscillation Index, Mon. Weather Rev., 115, 2161–2165, https://doi.org/10.1175/1520- 0493(1987)115<2161:AEOTTS>2.0.CO;2, 1987. Paolo, F., Padman, L., Fricker, H., Adusumilli, S., Howard, S., and Siegfried, M.: Response of Paciﬁc-sector Antarctic ice shelves to the El Niño/Southern Oscillation, Nat. Geosci., 11, 121–126, https://doi.org/10.1038/s41561-017-0033-0, 2018. Roundy, P. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector Krinner, G., Guicherd, B., Ox, K., Genthon, C., and Mag- and, O.: Inﬂuence of Oceanic Boundary Conditions in Sim- ulations of Antarctic Climate and Surface Mass Balance Change during the Coming Century, J. Climate, 21, 938–962, https://doi.org/10.1175/2007jcli1690.1, 2008. Kuipers Munneke, P., Ligtenberg, S. R. M., Van Den Broeke, M. R., and Vaughan, D. G.: Firn air depletion as a precur- sor of Antarctic ice-shelf collapse, J. Glaciol., 60, 205–214, https://doi.org/10.3189/2014JoG13J183, 2014. Merino, N., Jourdain, N. C., Le Sommer, J., Goosse, H., Mathiot, P., and Durand, G.: Impact of increasing antarc- tic glacial freshwater release on regional sea-ice cover in the Southern Ocean, Ocean Modell., 121, 76–89, https://doi.org/10.1016/j.ocemod.2017.11.009, 2018. Lachlan-Cope, T. and Connolley, W.: Teleconnections between the tropical Paciﬁc and the Amundsen-Bellinghausens Sea: Role of the El Niño/Southern Oscillation, J. Geophys. Res.-Atmos., 111, D23101, https://doi.org/10.1029/2005JD006386, 2006. Mo, K. C. and Higgins, R. W.: The Paciﬁc–South American Modes and Tropical Convection during the Southern Hemisphere Winter, Mon. Weather Lang, C., Fettweis, X., and Erpicum, M.: Future climate and surface mass balance of Svalbard glaciers in an RCP8.5 climate scenario: a study with the regional climate model The Cryosphere, 14, 229–249, 2020 www.the-cryosphere.net/14/229/2020/ M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector 249 Turner, J., Phillips, T., Hosking, J. S., Marshall, G. J., and Orr, A.: The Amundsen Sea low, Int. J. Climatol., 33, 1818–1829, https://doi.org/10.1002/joc.3558, 2013a. the Amundsen Sea Embayment, West Antarctica, Ann. Glaciol., 53, 19–28, https://doi.org/10.3189/2012aog60a110, 2012. Tedesco, M.: Assessment and development of snowmelt retrieval algorithms over Antarctica from K-band spaceborne brightness temperature (1979–2008), Remote Sens. Environ., 113, 979– 997, https://doi.org/10.1016/j.rse.2009.01.009, 2009. Turner, J., Hosking, J. S., Phillips, T., and Marshall, G. J.: Tem- poral and spatial evolution of the Antarctic sea ice prior to the September 2012 record maximum extent, Geophys. Res. Lett., 40, 5894–5898, https://doi.org/10.1002/2013GL058371, 2013b. Thoma, M., Jenkins, A., Holland, D., and Jacobs, S.: Modelling circumpolar deep water intrusions on the Amundsen Sea con- tinental shelf, Antarctica, Geophys. Res. Lett., 35, L18602, https://doi.org/10.1029/2008gl034939, 2008. Turner, J., Orr, A., Gudmundsson, G. H., Jenkins, A., Bing- ham, R. G., Hillenbrand, C.-D., and Bracegirdle, T. J.: Atmosphere-Ocean-Ice Interactions in the Amundsen Sea Embayment, West Antarctica, Rev. Geophys., 55, 235–276, https://doi.org/10.1002/2016rg000532 2017. Thomas, E. R., Hosking, J. S., Tuckwell, R. R., Warren, R. A., and Ludlow, E. C.: Twentieth century increase in snowfall in coastal West Antarctica, Geophys. Res. Lett., 42, 9387–9393, https://doi.org/10.1002/2015GL065750, 2015. Van den Broeke, M.: Strong surface melting preceded collapse of Antarctic Peninsula ice shelf: Melting on Antarctic ice shelves, Geophys. Res. Lett., 32, L12815, https://doi.org/10.1029/2005GL023247, 2005. Thompson, D. W. and Wallace, J. M.: Annular modes in the extratropical circulation, Part I: month-to-month variabil- ity*, J. Climate, 13, 1000–1016, https://doi.org/10.1175/1520- 0442(2000)013<1000:amitec>2.0.co;2, 2000. Vaughan, D. G., Marshall, G. J., Connolley, W. M., Parkin- son, C., Mulvaney, R., Hodgson, D. A., King, J. C., Pudsey, C. J., and Turner, J.: Recent Rapid Regional Climate Warm- ing on the Antarctic Peninsula, Clim. Change, 60, 243–274, https://doi.org/10.1023/A:1026021217991, 2003. Torinesi, O., Fily, M., and Genthon, C.: Variability and trends of the summer melt period of Antarctic ice margins since 1980 from microwave sensors, J. Cli- mate, 16, 1047–1060, https://doi.org/10.1175/1520- 0442(2003)016<1047:vatots>2.0.co;2, 2003. Wang, Y., Ding, M., van Wessem, J. M., Schlosser, E., Altnau, S., van den Broeke, M. R., Lenaerts, J. T. M., Thomas, E. R., Isaksson, E., Wang, J., and Sun, W.: A Comparison of Antarc- tic Ice Sheet Surface Mass Balance from Atmospheric Climate Models and In Situ Observations, J. Climate, 29, 5317–5337, https://doi.org/10.1175/JCLI-D-15-0642.1, 2016. Trusel, L. D., Frey, K. E., and Das, S. B.: Antarctic surface melting dynamics: Enhanced perspectives from radar scat- terometer data, J. Geophys. M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector Glaciol., 46, 29–34, https://doi.org/10.3189/172756407782871684, 2007. Steig, E. J., Schneider, D. P., Rutherford, S. D., Mann, M. E., Comiso, J. C., and Shindell, D. T.: Warming of the Antarctic ice- sheet surface since the 1957 International Geophysical Year, Na- ture, 457, 459–462, https://doi.org/10.1038/nature07669, 2009. Pope, J. O., Holland, P. R., Orr, A., Marshall, G. J., and Phillips, T.: The impacts of El Niño on the observed sea ice bud- get of West Antarctica, Geophys. Res. Lett., 44, 6200–6208, https://doi.org/10.1002/2017GL073414, 2017. Steig, E. J., Ding, Q., Battisti, D., and Jenkins, A.: Tropical forcing of Circumpolar Deep Water inﬂow and outlet glacier thinning in The Cryosphere, 14, 229–249, 2020 www.the-cryosphere.net/14/229/2020/ M. Donat-Magnin et al.: SMB and surface melting in the Amundsen sector Res.-Earth Surf., 117, F02023, https://doi.org/10.1029/2011JF002126, 2012. Trusel, L. D., Frey, K. E., Das, S. B., Munneke, P. K., and Broeke, M. R.: Satellite-based estimates of Antarctic sur- face meltwater ﬂuxes, Geophys. Res. Lett., 40, 6148–6153, https://doi.org/10.1002/2013gl058138, 2013. Weertman, J.: Stability of the junction of an ice sheet and an ice shelf, J. Glaciol., 13, 3–11, https://doi.org/10.3189/s0022143000023327, 1974. Yuan, X. and Martinson, D. G.: The Antarctic dipole and its predictability, Geophys. Res. Lett., 28, 3609–3612, https://doi.org/10.1029/2001gl012969, 2001. p g g Trusel, L. D., Frey, K. E., Das, S. B., Karnauskas, K. B., Munneke, P. K., Van Meijgaard, E., and Van Den Broeke, M. R.: Divergent trajectories of Antarctic surface melt under two twenty-ﬁrst-century climate scenarios, Nat. Geosci., 8, 927, https://doi.org/10.1038/ngeo2563, 2015. Turner, J., Comiso, J. C., Marshall, G. J., Lachlan-Cope, T. A., Bracegirdle, T., Maksym, T., Meredith, M. P., Wang, Z., and Orr, A.: Non-annular atmospheric circulation change induced by stratospheric ozone depletion and its role in the recent increase of Antarctic sea ice extent, Geophys. Res. Lett., 36, L08502, https://doi.org/10.1029/2009gl037524, 2009. The Cryosphere, 14, 229–249, 2020 www.the-cryosphere.net/14/229/2020/ The Cryosphere, 14, 229–249, 2020
https://openalex.org/W2584024931	https://www.nature.com/articles/bcj20176.pdf	English	null	The role of the extracellular matrix in primary myelofibrosis	Blood cancer journal	2,017	cc-by	11,029	PRIMARY MYELOFIBROSIS, ITS CLINICAL MANIFESTATIONS AND COMMON MUTATIONS PMF patients.9 The JAK2V617F mutation affects the pseudokinase domain of JAK2 and makes JAK2 constitutively active.13 Another common mutation in PMF is in the Calreticulin (CALR) gene, which accounts for 25% of PMF patients.14,15 CALR functions as an ER chaperone and its mutation activates both the thrombopoietin receptor, c-mpl and JAK2.16 Patients with PMF and CALR mutations are younger and have lower risk of death than their JAK2 and MPL-mutated counterparts, despite their higher platelet count.17 Another identiﬁed mutation that leads to 5% of PMF cases is due to a somatic gain-of-function at amino acid residues W515 (W515K/L) and S505 mutation in the transmembrane domain of c-mpl, a receptor that activates downstream JAK/STAT signaling.18 Chronic myeloproliferative neoplasms (MPNs) are a heteroge- neous group of disorders arising from clonal proliferation of hematopoietic stem cells. Primary myeloﬁbrosis (PMF), polycythe- mia vera and essential thrombocythemia (ET) are the main Philadelphia chromosome negative MPNs.1 The clinical presenta- tion of each of these disorders varies, although all have the potential for leukemic transformation and thrombohemorrhagic events. PMF is described as either pre-ﬁbrotic PMF (prePMF) or overt PMF according to the 2016 WHO diagnostic criteria. Compared to the 2008 WHO diagnostic criteria, the 2016 WHO criteria make a distinction between prePMF and overt PMF (Table 1). This distinction is especially important because prePMF can present similarly and be mistaken for ET. Making the correct diagnosis is important given the poorer prognosis, increased mortality and leukemic transformation rate for prePMF compared to ET.2,3 The prognosis of patients with PMF is generally poor, but depending on the mutations involved it appears that survival and adverse outcomes can vary. As mentioned before, JAK2, CALR and c-mpl are driver mutations that account for 90% of PMF cases, while 10% can be viewed as ‘triple negative’. One study found differences in median survival in patients with PMF that either had JAK2, CALR, c-mpl mutations or were triple negative. The role of the extracellular matrix in primary myeloﬁbrosis O Leiva1, SK Ng1, S Chitalia1, A Balduini2,3, S Matsuura1 and K Ravid1 Primary myeloﬁbrosis (PMF) is a myeloproliferative neoplasm that arises from clonal proliferation of hematopoietic stem cells and leads to progressive bone marrow (BM) ﬁbrosis. While cellular mutations involved in the development of PMF have been heavily investigated, noteworthy is the important role the extracellular matrix (ECM) plays in the progression of BM ﬁbrosis. This review surveys ECM proteins contributors of PMF, and highlights how better understanding of the control of the ECM within the BM niche may lead to combined therapeutic options in PMF. Blood Cancer Journal (2017) 7, e525; doi:10.1038/bcj.2017.6; published online 3 February 2017 PMF patients.9 The JAK2V617F mutation affects the pseudokinase domain of JAK2 and makes JAK2 constitutively active.13 1Department of Medicine and Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, MA, USA; 2Department of Molecular Medicine, University of Pavia, Pavia, Italy and 3Laboratory of Biotechnology, IRCCS San Matteo Foundation, Pavia, Italy. Correspondence: Dr K Ravid, Department of Medicine and Whitaker Cardiovascular Institute, Boston University School of Medicine, 700 Albany Street W-601, Boston, MA 02118, USA. E-mail: kravid@bu.edu Received 12 December 2016; accepted 20 December 2016 OPEN OPEN Citation: Blood Cancer Journal (2017) 7, e525; doi:10.1038/bcj.2017.6 www.nature.com/bcj PRIMARY MYELOFIBROSIS, ITS CLINICAL MANIFESTATIONS AND COMMON MUTATIONS Patients with CALR-mutated PMF have a more favorable prognosis, while triple negative PMF patients have the worst prognosis (median survival in one study of CALR-mutated PMF is 15.9 years vs 2.3 years in triple negative PMF).9,19 Mutations in IDH1/2, SRSF2 and ASXL1 in PMF were shown to have an increase risk of leukemic transformation.20 In one study, patients with CALR mutations and no ASXL1 mutation (CALR+ASXL1−) had the longest survival, while CALR-ASXKL+ had the shortest survival (median survival of 10.4 years vs 2.3 years respectively).21 Interestingly, ASXL1, EZH2 and IDH1/2 have been shown to play a role in chromatin structure, suggesting that epigenetic dysregulation may play a role in PMF progression and leukemic transformation.22 Although a substantial number of patients with polycythemia vera and ET are asymptomatic at presentation, patients with PMF commonly complain of fatigue and symptoms due to splenomegaly.4,5 Hallmarks of PMF include expansion of the megakaryocytic lineage, bone marrow (BM) ﬁbrosis and extra- medullary hematopoesis (EMH), which occurs predominantly in the liver and spleen, but can manifest anywhere.6,7 Patients with PMF can also have portal hypertension primarily through increased splenic blood ﬂow, hepatic EMH and sinusoidal ﬁbrosis.8 Overall survival for PMF is signiﬁcantly lower than for polycythemia vera and ET, and one study showed PMF patients were also more likely to have leukemic transformation.9 y Several somatic mutations have been identiﬁed in PMF, including in JAK2, MPL, CALR and several other genes. Janus kinase 2 (JAK2) is a cytoplasmic tyrosine kinase engaged with numerous intracellular signaling pathways involving receptors for erythropoetin, thrombopoetin, interleukin-3, granulocyte colony- stimulating factor and granulocyte–macrophage colony- stimulating factor.10 A single acquired somatic point mutation at V617F in JAK2 causes MPN in patients.11,12 JAK2V617F is found in 95% polycythemia vera patients and detected in ~ 60% of ET and Received 12 December 2016; accepted 20 December 2016 THE BONE MARROW NICHE AND EXTRACELLULAR MATRIX The BM is a spongy tissue within the central cavity of several bones of the body.23 The BM space is evenly occupied by sinusoids. The endosteal surface of the bones and cells constitute Extracellular matrix in primary myeloﬁbrosis O Leiva et al Table 1. Changes in the WHO Diagnostic Criteria for PMF 2008 Criteria for PMF 2016 Criteria for pre-PMF 2016 Criteria for overt PMF Major criteria MK proliferiferation and atypia with ﬁbrosis (reticulin and/or collagen) or increased marrow cellularity, granulocytic proliferation and decreased erythropoesis in the absence of ﬁbrosis MK proliferation and atypia without reticulin ﬁbrosis with increased marrow cellularity, granulocytic proliferation and often decreased erythropoesis MK proliferiferation and atypia with ﬁbrosis (reticulin and/or collagen) Does not meet WHO criteria for other myeloid neoplasms Does not meet WHO criteria for other myeloid neoplasms Does not meet WHO criteria for other myeloid neoplasms Presence of JAK2V617F or other clonal marker or no evidence of reactive ﬁbrosis. Presence of JAK2, CALR or MPL mutation or other clonal marker with no evidence of reactive ﬁbrosis Presence of JAK2, CALR or MPL mutation or other clonal marker with no evidence of reactive ﬁbrosis Minor criteria Leukoerythroblastosis Leukocytosis (⩾11 × 109/L) Leukoerythroblastosis Increased serum lactate dehydrogenase Increased serum lactate dehydrogenase Increased serum lactate dehydrogenase Anemia Anemia (not due to comorbidities) Anemia (not due to comorbidities) Palpable splenomegaly Palpable splenomegaly Palpable splenomegaly Leukocytosis (X11 × 109/L) Abbreviations: MK, megakaryocyte; PMF, primary myeloﬁbrosis. Changes from the 2008 WHO criteria have been given in bold. 2 MK proliferation and atypia without reticulin ﬁbrosis with increased marrow cellularity, granulocytic proliferation and often decreased erythropoesis Does not meet WHO criteria for other myeloid neoplasms Presence of JAK2, CALR or MPL mutation or other clonal marker with no evidence of reactive ﬁbrosis Leukoerythroblastosis Increased serum lactate dehydrogenase Anemia (not due to comorbidities) Palpable splenomegaly Leukocytosis (X11 × 109/L) the stem cell niche in which the hematopoietic stem cells (HSCs) reside and differentiate to different lineages.24–27 The BM niche is separated into two compartments. The osteoblastic niche The osteoblastic niche is composed of several types of cells that aid in the maintenance of HSC. Expansion of HSCs by osteoblast factors has been shown in vitro (via production of granulocyte colony-stimulating factor) as well as in vivo, suggesting that osteoblasts play an important role in HSC maintenance.24,32–34 However, activated osteoblasts have also been shown to produce osteopontin and angiopoietin-1, which limit HSC expansion and contribute to their quiescence state.28 N-cadherin at the niche helps HSCs to adhere to the osteoblastic niche through tight cell– cell interactions, and overexpression of N-cadherin promotes quiescence.30 Osteoclasts also appear to be important in the osteoblastic niche by releasing calcium during bone resorption. HSCs were found to express calcium-sensing receptors. Mice deﬁcient in calcium-sensing receptors were found to have hypoplastic BM with decreased localization of HSCs in the osteoblastic niche but had normal number of HSCs in the fetal liver.35 Interactions between the niche and hematopoietic cells are reciprocal. For instance, megakaryocytes (MKs) overexpressing BMP 2, 4 and 6 at the endosteum have been shown to stimulate osteoblasts.36 Hence, HSCs and its cell lineages are involved in bone formation and activities within the niche.37 Non-bone components are also important in the maintenance of HSCs within the osteoblastic niche. CXCL12 is a chemokine that plays an important role in the maintenance and quiescence of HSCs The vascular niche The vascular niche The vasculature niche is located in the perivascular space and helps to activate HSCs to differentiate into other blood lineage.42 The vascular niche is located around small sinusoidal blood vessels associated with various stromal elements and together with ﬁbronectin, type IV collagen and laminin at the ECM helps to regulate HSC differentiation and ultimately mobilization of differentiated blood cells to the peripheral circulation.26,30 Endothelial cells at the vascular niche secrete E-selectin and promote HSC proliferation.37 The walls of venous sinusoids consists of a layer of endothelial cells which acts as a conduit for mature blood cells and platelets to enter the blood stream from the BM compartment.43 Simultaneously, blood vessels provide a conduit for distal systemic signals, such as inﬂammatory and other circulatory cells into the niche.44 Besides the effect of cytokine and chemokine, a hypoxic environment in the osteo- blastic niche helps to maintain HSCs in a quiescent state, while a more oxygen rich environment in the vascular niche allows HSCs to proliferate and differentiate.42 The osteoblastic niche THE BONE MARROW NICHE AND EXTRACELLULAR MATRIX The ﬁrst compartment is the osteoblastic niche found near the endosteum and the second compartment is the vascular niche near the sinusoids.28 These two niches consist of different cell types such as adipocytes, osteoblasts and smooth muscle cells, Schwann cells, reticular cells, endothelial cells and hematopoietic cells.14,25 However, there is no distinct separation between the two niches as HSCs can move freely and can receive inputs from the two compartments simultaneously.29 The niches also contain stromal cells and unique extracellular matrix (ECM) components that support stem cells by HSCs interaction with other cells through cell surface receptors, gap junctions and soluble factors.30 That is, the molecular crosstalk between HSCs and the cellular constituents of these niches determine the balance between HSC self-renewal and differentiation.31 through its receptor CXCR4 in both the osteoblastic and vascular niches.38 Interestingly, the sympathetic nervous system appears to modulate CXCL12 expression in a circadian pattern through the release of norepinephrine which downregulates CXCL12. Circulat- ing HSCs were found to peak at ﬁve hours after the initiation of light with ablation of sympathetic nerve ﬁbers decreasing the numbers of circulating HSCs in mice.39,40 Sympathetic nerve ﬁbers also appear to have an important role in BM regeneration as evidenced by impaired HSC recovery after treatment with cisplatin (a neurotoxic chemotherapeutic drug) in mice.41 DISRUPTION OF BM NICHES IN PMF Schwann cells and MPN progression was slowed by the administration of β3 adrenergic agonists that compensated for the neuropathy seen in the BM of these mice.46 In addition, mutated MKs release excessive amount of ﬁbrotic factors, which activate mesenchymal cells, leading to MF.14 In one study of PMF patients, several genes that may be related to the maintenance of the BM niche homeostasis were found to be dysregulated. Genes such as hypoxia inducible factor 1A, CXCR4 and PAX5 were found to be downregulated in BM mononuclear cells from patients with PMF, while cyclooxygenase 2 was found to be signiﬁcantly upregulated.47 Furthermore, malignant stem cells from a mouse model of MPN appear to modify the osteoblastic niche to beneﬁt their survival at the expense of the survival of non-malignant HSC by causing mesenchymal stromal cells to overproduce osteoblas- tic lineage cells that promote inﬂammation and MF.48 Further- more, malignant stem cells have also been shown to produce high levels of lipocalin2, which was shown to increase proliferation of PMF HSC while decreasing the numbers of normal HSC.49 Stromal cells in BM undergo changes associated with myeloproliferation which include excessive ECM deposition leading to ﬁbrosis, neoangiogenesis and osteosclerosis.50–52 The JAK2V617F mutation has not only been shown in HSC and myeloid cells, but also in endothelial cells in patients with PMF and other MPNs.53,54 One study suggests that JAK2V617F mutated endothelial cells in the vascular niche could promote malignant stem cell proliferation.55 These changes may eventually disrupt normal HSC niches and result in the establishment of EMH.56,57 Although advances have been made in the understanding of how the BM niches are altered in MPNs and PMF in particular, our current understanding is incomplete. components as compared to healthy tissues.64,65 Furthermore, the level of tissue stiffness can be used as a predictive indicator for disease stage.66 Hence, there is a correlation between stiffness of the matrix and ﬁbrosis, which may contribute to the clinical manifestations seen in PMF (thrombocytopenia, EMH). DISRUPTION OF BM NICHES IN PMF y p In PMF there is progressive deposition of ECM components in the BM, and PMF patients have more ECM materials than healthy population.67–69 MKs are known to secrete ECM components such as ﬁbronectin, laminin and type IV collagen, which contribute to MK development and ECM homeostasis, therefore, dysfunctional MKs can potentially play a role in pathogenesis of PMF by secreting excessive amount of ECM components.70,71 Below we summarize the components of the ECM and their role in PMF (Figure 1). Collagens Type I, III and V collagens form ﬁbers in the ECM, which provides elasticity and ﬂexibility to the matrix.75,76 Collagens g MKs secrete various types of collagens found in the BM ECM and their abundance differ between the BM osteoblast and vascular niches.23 For instance, in the osteoblastic niche, collagen I is the most abundant component, and binding of MKs to collagen through integrin inhibits proplatelet formation.72,73 In addition, collagen I creates an environment for HSCs to differentiate through the megakaryocytic lineage but inhibit pro-platelet formation and release is inhibited through adhesion to type I collagen via activation of the Rho/ROCK signaling cascade.73,74 In the vascular niche, MKs interact with collagen IV at the microenvironment which allow MKs to mature and form proplatelet.26 Beside differences in abundance at the osteoblastic and vascular niche, different collagens are localized in various regions of the ECM niche. Type I, III and V collagens form ﬁbers in the ECM, which provides elasticity and ﬂexibility to the matrix.75,76 Interestingly, unlike type I collagen, type III and V collagens were found to support proplatelet formation in vitro.70 Type IV, VIII and XVIII collagens are expressed directly beneath the endothelial cells in the basement membrane and are commonly associated with laminin.75 BM ﬁbroblast activated by factors released from PMF MKs, such as TGF-β, upregulate the expression of collagen, leading to augmented level deposition of this protein in the ECM in PMF patients.77 MKs from PMF patients also have increased expression of type III and type IV collagens as compared to MKs derived from healthy controls.71 Interestingly, in patients with PMF, as the grade of ﬁbrosis increases the platelet count drops, which may be partly explained by changes in the ECM in later stages of the disease.78 MKs secrete various types of collagens found in the BM ECM and their abundance differ between the BM osteoblast and vascular niches.23 For instance, in the osteoblastic niche, collagen I is the most abundant component, and binding of MKs to collagen through integrin inhibits proplatelet formation.72,73 In addition, collagen I creates an environment for HSCs to differentiate through the megakaryocytic lineage but inhibit pro-platelet formation and release is inhibited through adhesion to type I collagen via activation of the Rho/ROCK signaling cascade.73,74 In the vascular niche, MKs interact with collagen IV at the microenvironment which allow MKs to mature and form proplatelet.26 Beside differences in abundance at the osteoblastic and vascular niche, different collagens are localized in various regions of the ECM niche. EXTRACELLULAR MATRIX The ECM is a three-dimensional, non-cellular structure providing physical support for tissue integrity and elasticity.58 It is comprised of various matrix proteins, such as collagens, laminin, ﬁbronectin, vitronectin and ﬁbrinogen as well as soluble proteins, including cytokines and chemokines.59 These components deﬁne the biochemical and biomechanical properties of the ECM and are able to inﬂuence the attachment of cells to the ECM and directly affect their biological functions, such as cell division, differentia- tion, tissue polarity and cell migration.30 At the same time, cells can sense ECM compositions and transmit appropriate signals at the adhesion sites.30 The adhesion interaction requires integrins and signaling pathways, including Ras/MAPK, PI3K/Akt, RhoA/ ROCK, Wnt/β-catenin and TGF-β that link the actomyosin cytoskeleton with the ECM.30 At the BM niche, the ECM provides the microenvironment for HSCs to maintain a quiescence stage or to undergo differentiate to form various progenitors.60,61 Interestingly, unlike type I collagen, type III and V collagens were found to support proplatelet formation in vitro.70 Type IV, VIII and XVIII collagens are expressed directly beneath the endothelial cells in the basement membrane and are commonly associated with laminin.75 BM ﬁbroblast activated by factors released from PMF MKs, such as TGF-β, upregulate the expression of collagen, leading to augmented level deposition of this protein in the ECM in PMF patients.77 MKs from PMF patients also have increased expression of type III and type IV collagens as compared to MKs derived from healthy controls.71 Interestingly, in patients with PMF, as the grade of ﬁbrosis increases the platelet count drops, which may be partly explained by changes in the ECM in later stages of the disease.78 DISRUPTION OF BM NICHES IN PMF Abnormal interactions between the HSCs and its microenviron- ment in the BM can affect PMF disease progression.45 HSCs harboring mutated genes such as JAK2V16F can alter the niche to favor their clonal expansion at the expense of normal HSCs.14 One example of this is that JAK2V617F mutant HSCs secrete interleukin-1β, which activates the apoptotic pathway in mesench- ymal and Schwann cells. This will, in turn, affect the survival rate of normal HSCs via disruption of the interactions between the mesenchymal cells, and injury to sympathetic nerves innervating the BM. Mice with JAK2V617F MPN had decreased numbers of Blood Cancer Journal Extracellular matrix in primary myeloﬁbrosis Extracellular matrix in primary myeloﬁbrosis O Leiva et al 3 Schwann cells and MPN progression was slowed by the administration of β3 adrenergic agonists that compensated for the neuropathy seen in the BM of these mice.46 In addition, mutated MKs release excessive amount of ﬁbrotic factors, which activate mesenchymal cells, leading to MF.14 In one study of PMF patients, several genes that may be related to the maintenance of the BM niche homeostasis were found to be dysregulated. Genes such as hypoxia inducible factor 1A, CXCR4 and PAX5 were found to be downregulated in BM mononuclear cells from patients with PMF, while cyclooxygenase 2 was found to be signiﬁcantly upregulated.47 Furthermore, malignant stem cells from a mouse model of MPN appear to modify the osteoblastic niche to beneﬁt their survival at the expense of the survival of non-malignant HSC by causing mesenchymal stromal cells to overproduce osteoblas- tic lineage cells that promote inﬂammation and MF.48 Further- more, malignant stem cells have also been shown to produce high levels of lipocalin2, which was shown to increase proliferation of PMF HSC while decreasing the numbers of normal HSC.49 Stromal cells in BM undergo changes associated with myeloproliferation which include excessive ECM deposition leading to ﬁbrosis, neoangiogenesis and osteosclerosis.50–52 The JAK2V617F mutation has not only been shown in HSC and myeloid cells, but also in endothelial cells in patients with PMF and other MPNs.53,54 One study suggests that JAK2V617F mutated endothelial cells in the vascular niche could promote malignant stem cell proliferation.55 These changes may eventually disrupt normal HSC niches and result in the establishment of EMH.56,57 Although advances have been made in the understanding of how the BM niches are altered in MPNs and PMF in particular, our current understanding is incomplete. Glycoproteins g p g MKs differentiation and proplatelet formation depend on the stiffness of the matrix. One study found that MKs cultured on a methylcellulose hydrogel media that mimics BM stiffness exhib- ited higher ploidy levels than MKs cultured on liquid media. Furthermore, MKs cultured on the stiffer media produced twice as many proplatelets when placed in liquid media than those that were cultured in the liquid media.62 In a study looking at ex vivo platelet production on a three-dimensional silk BM niche, the authors found that low and medium stiffness silk ﬁlm supported a higher percentage of long and branched proplatelets compared to high stiffness silk ﬁlm, although adhesion was not different, suggesting that increased ECM stiffness may reduce platelet production.23 Interestingly, MKs on silk ﬁlms entrapped with type I collagen had a signiﬁcantly reduced proplatelet formation as compared to MKs on silk ﬁlms entrapped with ﬁbrinogen.23 Another study also showed that type I collagen is a negative regulator of proplatelet formation through activation of the integrinα2β1/Rho/ROCK axis.63 It has been noted by clinicians that ﬁbrotic tissues are usually stiff and enriched with ECM Fibronectin. Fibronectin is involved in various cellular interactions in the ECM and is important in cell adhesion, migration and growth and differentiation.79 Human MKs expresses and secrete cellular ﬁbronectin which is involved in MKs maturation, platelet extension and subsequent release.80 Fibronectin is abundantly found in BM niche and it is able to stimulate HSCs and MKs proliferation via ﬁbronectin receptors VLA-4 and VLA-5.26 Fibro- nectin assembly in the matrix can be inﬂuence by integrin activation and contractility of the MKs cytoskeleton.80 Fibronectin surrounds cells and provide structural scaffolding for tissues.58 In vitro, ﬁbronectin cause a threefold increase in mouse HSCs proliferation with a subsequent higher MK output when compared to control treated with thrombopoetin only, suggesting the importance of ﬁbronectin in MKs development.70 In patients with pre-ﬁbrotic MPNs, mesenchymal stromal cells were found to secrete more ﬁbronectin than in controls. The amount of ﬁbronectin expression was correlated to reduced hemoglobin levels in patients with MPN in the absence of reticulin ﬁbrosis.81 In another study, patients with PMF were found to have Blood Cancer Journal Extracellular matrix in primary myeloﬁbrosis O Leiva et al Extracellular matrix in primary myeloﬁbrosis O Leiva et al Extracellular matrix in primary myeloﬁbrosis O Leiva et al Figure 1. Glycoproteins Schematic presentation of major components in ECM derived from MKs and involved in PMF progression. The parentheses includ reference numbers corresponding to the illustrated pathway. BM, bone marrow; bFGF, basic ﬁbroblast growth factor; ECM, extracellular matr IL-1β, interleukin-1 beta; LOX, lysyl oxidase; MK, megakaryocyte; MMP, matrix metalloproteinase; MSC, mesenchymal stromal cell; PDGF- PDGF receptor; TGF-β, transforming factor beta; TIMP, tissue inhibitor of metalloproteinases; TSP-1, thrombospondin-1; PDGF, platelet derive growth factor; VEGF, vascular endothelial growth factor. O Leiva et al 4 Figure 1. Schematic presentation of major components in ECM derived from MKs and involved in PMF progression. The parentheses include reference numbers corresponding to the illustrated pathway. BM, bone marrow; bFGF, basic ﬁbroblast growth factor; ECM, extracellular matrix; IL-1β, interleukin-1 beta; LOX, lysyl oxidase; MK, megakaryocyte; MMP, matrix metalloproteinase; MSC, mesenchymal stromal cell; PDGF-R, PDGF receptor; TGF-β, transforming factor beta; TIMP, tissue inhibitor of metalloproteinases; TSP-1, thrombospondin-1; PDGF, platelet derived growth factor; VEGF, vascular endothelial growth factor. elevated mesenchymal stromal cell expression of ﬁbronectin compared to patients with ET and controls.82 One study showed that ﬁbronectin can activate monocytes in patients with MF via increased monocytic production of substance P, a proinﬂamma- tory cytokine.83 and in PMF.88,89 TSP-1 was signiﬁcantly overexpressed in all stages of PMF independently of the degree of MF, when compared to controls. Individual follow-up biopsies showed involvement of TSP-1 during progressive MF. TSP-2 is only strongly expressed in 40% of cases with advanced MF. Interestingly, MKs and interstitial proplatelet formations were shown to be the relevant source for TSP-1 in PMF. In addition, TSP-1 inhibits the activity of matrix metalloproteinases (MMPs), which are primarily involved in proteolysis of collagens and other matrix components, which allows the accumulation of ECM.86 Thrombospondin. Thrombospondin (TSP) was identiﬁed in thrombin-stimulated platelets, and is also expressed by a variety of cells, such as endothelial cells, ﬁbroblasts and smooth muscle cells.84 TSPs are matricellular proteins that interact with cell surface receptors and with components of the ECM, thereby mediating cell–matrix interactions.85 Currently, there are 5 known members of TSP1 family. TSP-1, TSP-2, TSP-3, TSP-4 and TSP-5. TSP-1 and TSP-2 are better understood as compared to the other 3 members.86 TSP are involved in MK development and platelet function.87 Osteonectin. Blood Cancer Journal Glycoproteins Osteonectin (also known as SPARC) is an adhesive calcium-binding ECM glycoprotein that binds various ECM components such as TSP-1 and ﬁbrillar collagens.90 In adults, osteonectin is expressed during processes requiring ECM turnover such as wound healing and tumor progression.90 Osteonectin prevents cell spreading in vitro suggesting they play an important role in cellular proliferation and migration.91 High levels of tissue TSP-1 is also an activator of latent TGF-β1, which is an inducer of ﬁbroblast activation and matrix synthesis in the ﬁbrotic response Blood Cancer Journal Extracellular matrix in primary myeloﬁbrosis Extracellular matrix in primary myeloﬁbrosis O Leiva et al 5 osteonectin has been associated with reduced collagen type IV deposition.92 cytokines have been shown to enhance mutant HSC proliferation and survival in vitro.108 Other cytokines released by malignant HSCs are proﬁbrotic, such as transforming growth factor beta1 (TGF-β1), basic ﬁbroblast growth factor, and PDGF, and angiogenic factors such as vascular endothelial growth factor (VEGF).23 Interestingly in healthy individuals and in myeloid neoplasms without associated stromal changes, osteonectin expression was conﬁned to MKs.50 In contrast, in cases with signiﬁcant stromal changes (such as PMF), osteonectin reactivity extends to stromal cells. Hence, osteonectin is part of BM response to myeloprolifera- tion. That is, the expression level of osteonectin in BM stromal cells correlates with the degree of stromal changes and correspond to the severity of PMF.50 This is further shown in osteonectin knockout mice in which there is impairment in BM ﬁbrosis.50 Transforming growth factor beta (TGF-β) TGF-β1 plays a key role in regulation of genes involved in the synthesis of the ECM components and of ECM-degrading enzymes.58 For instance, TGF-β1 enhances the production of types I, III and type IV collagen and ﬁbronectin, as well as increases the synthesis of TIMP.94,109 There is also a strong correlation between MK release of TGF-β1 and its activity, resulting in a dose- dependent increase of ECM component synthesis.110 In the ECM, reactive oxygen species activate a number of proteases such as MMPs and TSP1, which can digest and convert the latent TGF-β to its active form.111,112 Platelet derived growth factor and vascular endothelial growth factor Platelet derived growth factor and vascular endothelial growth factor LOX is a copper-dependent amine oxidase that catalyzes oxidative deamination of lysine and hydroxylysine residues on collagen and elastin precursors, leading to crosslinking within these proteins.96 The crosslinking results in a dense ECM with altered elasticity.97 LOX is highly expressed in proliferating, low ploidy MKs, but its expression decreased dramatically in mature, higher ploidy mouse MKs.98 Following this observation, the Ravid laboratory was also the ﬁrst to identify LOX as regulator of BM ﬁbrosis in a mouse models of PMF.98 This link was demonstrated in a GATA-1low mouse model where LOX was found to be abundantly expressed within abnormally high levels of low ploidy MKs coupled with an extensively ﬁbrotic ECM.98,99 Importantly, administration of β- aminopropionitrile (a LOX inhibitor) to the GATA-1low mice inhibited the progression of MF.98 Similarly, LOX was reported to be upregulated in human PMF cells and plasma.100 MKs are an important source of PDGF and VEGF, which contribute to MK role in the development of BM ﬁbrosis and production of collagen.23 PDGF participates in BM ﬁbrogenesis in PMF through its role in the proliferation and activation of medullary ﬁbroblasts.59 VEGF functions by binding to its receptor VEGFR1 to promote MK maturation and migration from osteoblastic niche to the vascular niche where proplatelets formation and platelet release occur.118 Matrix MMPs MMPs are a family of zinc-dependent endopeptidases and function in remodeling the ECM by its ability to degrade and cleave ECM components with wide substrate speciﬁcities.93 For instance, MMP2 and MMP9 are effective in degrading collagen and gelatine structures in the ECM.93 In addition, by producing MMP9, mature MKs are able to free themselves from the BM matrix at the osteoblastic niche and travel to the vascular niche. In patients with PMF, MMPs are downregulated while tissue inhibitors of MMPs (TIMP) are increased.94,95 This leads to decreased degradation and increased accumulation of ECM components. TGF-β1 is involved in the pathophysiology of PMF and is a strong inducer of ﬁbrosis.113 Not surprising, high TGF-β concen- tration is found in PMF BM and is correlated to BM ﬁbrosis in vivo.89 In PMF, TGF-β1 affects ECM biosynthesis by decreasing the amount of MMP and increasing the synthesis of TIMPs, particularly of TIMP-1.114 TGF-β leads to an increase in production of types I, III, IV and V collagens, and to overexpression of ﬁbronectin in advanced stage of the disease, which further accelerate ECM accumulation.109 MKs and platelets are the main source of TGF-β in PMF with intraplatelet levels being 2–3 times higher in PMF patients compared to healthy controls.115–117 Current treatment of PMF Current management of PMF is primarily palliative and aimed at relieving symptoms of (anemia, splenomegaly, constitutional symptoms and bone pain). Only allogenic hematopoietic cell transplant is curative although few patients are eligible for this treatment.119 Subsequently, it has been noted that abnormalities in MK expansion and proliferation are associated with increased levels of extracellular platelet derived growth factor (PDGF) and TGF-ß1, which can lead to ﬁbrosis.101,102 PDGF, TGF-β1 and the cytokine interleukin-1β are able to increase LOX and collagen expression, all of which have been found to be elevated in PMF.101,102 LOX has also been shown to oxidize and activate PDGF receptor and LOX activity appears to be important for PDGF-mediated MK expansion.98,103 Hence, there appears to be positive feedback in which LOX is highly secreted from abnormal MKs, and soluble factors secreted by these MKs can further increase LOX level, which will enhance the ﬁbrotic phenotype (Figure 1). Hydroxyurea (HU) is a medication commonly used to treat symptomatic PMF and has been shown to signiﬁcantly improve bone pain, constitutional symptoms and splenomegaly.120 Inter- estingly, response to HU may be related to the presence of JAK2V617F mutation in PMF with those harboring the mutation more likely to respond to HU.121 Anemia can be treated in PMF with red blood cell transfusions (although frequent transfusions can put patients at risk for iron overload), androgens and danazol. Thalidomide or lenalidomide with prednisone can be used for persistent anemia.120,122,123 Importantly, none of the aforemen- tioned palliative therapies have been convincingly shown to decrease BM ﬁbrosis.122 ECM bound growth and secreted factors ECM bound growth and secreted factors JAK1 and 2 inhibitors have been introduced as treatment of PMF, the only Food and Drug Administration (FDA) approved drug being ruxolitinib. In the phase 3 COMFORT I and II trials, ruxolitinib was shown to be more effective than best available therapy for reduction of splenomegaly and constitutional symptoms although it was associated with higher rates of anemia and cytopenias. Ruxolitinib also appears to reduce BM ﬁbrosis in some patients.124,125 Although the COMFORT I and II trials failed to The ECM is maintained by several cytokines and growth factors. Dysfunctional HSCs and MKs have abnormal production and release of several cytokines and chemokines, which are associated with ﬁbrosis and enhanced survival and proliferation of mutant HSCs, thus contributing to ECM disruption in PMF.23,104–107 Inﬂammatory cytokines have been found to be elevated in PMF regardless of the mutational status, including interleukin-1β and tumor necrosis factor alpha. Both of these pro-inﬂammatory Blood Cancer Journal Extracellular matrix in primary myeloﬁbrosis O Leiva et al Extracellular matrix in primary myeloﬁbrosis 6 show a survival advantage in ruxolitinib, long-term follow-up studies from COMFORT trials suggest a modest decrease in mortality in patients with intermediate-2 and high-risk disease.124,126–128 Although ruxolitinib is the only non-allo HCT treatment currently available that may improve survival, the beneﬁts appear to be modest and leave a lot to be desired in the treatment of PMF. Inhibition of cytokines involved in PMF is another potential future ECM-based treatment of PMF. In the GATA-1low mouse model, inhibition of tyrosine kinase of TGF-β1 receptor decreased MF, EMH and neoangiogenesis.140 Another potential unexplored treatment in PMF is nintedanib, a multikinase inhibitor that inhibits VEGFR and PDGF receptor. Although bevacizumab (anti- VEGF antibody) was ineffective in treating PMF, inhibition of multiple cytokine receptors involved in the pathogenesis may be efﬁcacious by interrupting cytokine-mediated disruptions of the BM niches and ECM.141,142 TNF inhibitors have shown promise in treating the constitutional symptoms of PMF, although larger trials are necessary to assess safety and efﬁcacy.143 p p Given the poor prognosis of PMF and limitations of current treatment options, novel drugs are needed to improve the quality of life and survival of patients. One such novel drug is the telomerase inhibitor imetelstat. A recent pilot study looked at 33 patients with intermediate-2 or high-risk MF and showed that four patients had complete response and three had partial response to imetelstat. REFERENCES p y tors are promising given the known mutations in PMF that affect the epigenome. Combination therapy with ruxolitinib and other agents are also in development including the histone deacetylase panabinostat, which showed promise in a preclinical trial and there is a current phase I/II trial looking at this combination's beneﬁt in patients with PMF (PRIME trial, clinicaltrials.gov NCT01693601).137 1 Tefferi A, Vardiman JW. Classiﬁcation and diagnosis of myeloproliferative neo- plasms: the 2008 World Health Organization criteria and point-of-care diagnostic algorithms. Leukemia 2008; 22: 14–22. 1 Tefferi A, Vardiman JW. Classiﬁcation and diagnosis of myeloproliferative neo- plasms: the 2008 World Health Organization criteria and point-of-care diagnostic algorithms. Leukemia 2008; 22: 14–22. g 2 Barosi G. Essential thrombocythemia vs. early/preﬁbrotic myeloﬁbrosis: why does it matter. Best Pract Res Clin Haematol 2014; 27: 129–140. 2 Barosi G. Essential thrombocythemia vs. early/preﬁbrotic myeloﬁbrosis: why does it matter. Best Pract Res Clin Haematol 2014; 27: 129–140. 3 Arber DA, Orazi A, Hasserjian R, Thiele J, Borowitz MJ, Le Beau MM et al. The 2016 revision to the World Health Organization classiﬁcation of myeloid neoplasms and acute leukemia. Blood 2016; 127: 2391–2405. 3 Arber DA, Orazi A, Hasserjian R, Thiele J, Borowitz MJ, Le Beau MM et al. The 2016 revision to the World Health Organization classiﬁcation of myeloid neoplasms and acute leukemia. Blood 2016; 127: 2391–2405. 4 Visani G, Finelli C, Castelli U, Petti MC, Ricci P, Vianelli N et al. Myeloﬁbrosis with myeloid metaplasia: clinical and haematological parameters predicting survival in a series of 133 patients. Br J Haematol 1990; 75: 4–9. 4 Visani G, Finelli C, Castelli U, Petti MC, Ricci P, Vianelli N et al. Myeloﬁbrosis with myeloid metaplasia: clinical and haematological parameters predicting survival in a series of 133 patients. Br J Haematol 1990; 75: 4–9. CONCLUSIONS AND FUTURE DIRECTIONS A recent study showed that MLN8237 (AURKA inhibitor) induced differ- entiation of JAK2 and MPL-mutated cells as well as decreased BM ﬁbrosis and spleen size in mouse models of MPN and MF, with no obvious myelosupression seen.131–133 Other novel drugs currently in early clinical development for the treatment of PMF include the hedgehog pathway inhibitor PF-0444913, JAK2 speciﬁc inhibitors (such as NS-018), and histone deacetylase inhibitors (givinostat, panabinostat and belinostat).22,134–136 Histone deacetylase inhibi- tors are promising given the known mutations in PMF that affect the epigenome. Combination therapy with ruxolitinib and other agents are also in development including the histone deacetylase panabinostat, which showed promise in a preclinical trial and there is a current phase I/II trial looking at this combination's beneﬁt in patients with PMF (PRIME trial, clinicaltrials.gov NCT01693601).137 ECM bound growth and secreted factors All four patients with complete response had reversal of BM ﬁbrosis with three having molecular remission. The study also showed symptomatic spleen reduction in 35% of patients and 31% of transfusion-dependent patients before the study became transfusion-independent for at least 3 months. Myelosupression was a common adverse requiring protocol-mandated dose reduction. Interestingly, response rates were seen in 27% of patients with JAK2 mutation and 0% seen in those without.129 More long-term studies with larger cohort are needed but imetelstat remains a promising prospective drug. ACKNOWLEDGEMENTS KR ,an Established Investigator with the American Heart Association, is supported by NHLBI grant HL080442. S-KN is supported by NHLBI HL007224 Multidisciplinary Program in Cardiovascular Research. OL is supported by American Society of Hematology and Alpha Omega Alpha. in early clinical development for the treatment of PMF include the hedgehog pathway inhibitor PF-0444913, JAK2 speciﬁc inhibitors (such as NS-018), and histone deacetylase inhibitors (givinostat, panabinostat and belinostat).22,134–136 Histone deacetylase inhibi- CONCLUSIONS AND FUTURE DIRECTIONS Considerable advances have been achieved in the understanding of the ECM in BM and its effects on hematopoietic cell biology in health and disease. However, treatment of MF, which is found not only in PMF but also secondary to many hematological diseases, is still a challenge and options are scarce. One reason for this could be the focus of current therapies on controlling MPN cell proliferation, with the expectation that this in turn would result in amelioration of MF. At present, this approach is at best of minor efﬁcacy in early MF and not indicated in cases of severe MF. Speciﬁc targeting of ECM dysregulation to prevent and diminish MF may prove the frontline of research and therapy development in PMF with the greatest promise of relieving symptoms and extending life expectancy of patients. MKs in PMF have an impaired ability to polypoidize, yielding another potential target for therapy. Aurora kinase A (AURKA) appears to be important in maturation and polypoidization of MKs and studies have shown that inhibition of AURKA induces polypoidization in mouse models of acute megakaryocytic leukemia.130 Mature MKs have also been shown to have reduced expression of AURKA. Interestingly, AURKA activity was found to be elevated in cells with JAK2, CALR or MPL mutations. A recent study showed that MLN8237 (AURKA inhibitor) induced differ- entiation of JAK2 and MPL-mutated cells as well as decreased BM ﬁbrosis and spleen size in mouse models of MPN and MF, with no obvious myelosupression seen.131–133 Other novel drugs currently MKs in PMF have an impaired ability to polypoidize, yielding another potential target for therapy. Aurora kinase A (AURKA) appears to be important in maturation and polypoidization of MKs and studies have shown that inhibition of AURKA induces polypoidization in mouse models of acute megakaryocytic leukemia.130 Mature MKs have also been shown to have reduced expression of AURKA. Interestingly, AURKA activity was found to be elevated in cells with JAK2, CALR or MPL mutations. ECM AND POTENTIAL NEW THERAPEUTICS New therapeutics targeting the ECM may be beneﬁcial in ameliorating the debilitating symptoms due to BM ﬁbrosis. One such novel target might be LOX, considering its above-mentioned inﬂuences on BM ﬁbrosis and on promotion of MK proliferation through PDGF-R activation. Another potential novel ECM-based therapy could be targeted against monocyte-derived ﬁbrocytes that may play a role in the pathogenesis of BM ﬁbrosis in PMF. One study showed that neoplastic monocyte-derived ﬁbrocytes were overrepresented in the BM of PMF patients and inhibiting monocytes from differentiating to ﬁbrocytes with recombinant serum amyloid P reduced BM ﬁbrosis in two mouse models of MF.138 There is an ongoing phase 2 clinical trial looking at PRM-151 (recombinant serum amyloid P) for the treatment of MF. Preliminary data showed no signiﬁcant myelosupression and improvement of BM ﬁbrosis in six patients.139 5 Tefferi A. Myeloﬁbrosis with myeloid metaplasia. N Engl J Med 2000; 342: 1255–1265. 6 Koch CA, Li CY, Mesa RA, Tefferi A. Nonhepatosplenic extramedullary hemato- poiesis: associated diseases, pathology, clinical course, and treatment. Mayo Clin Proc 2003; 78: 1223–1233. 7 Mizoguchi M, Kawa Y, Minami T, Nakayama H, Mizoguchi H. Cutaneous extra- medullary hematopoiesis in myeloﬁbrosis. J Am Acad Dermatol 1990; 22: 351–355. 7 Mizoguchi M, Kawa Y, Minami T, Nakayama H, Mizoguchi H. Cutaneous extra- medullary hematopoiesis in myeloﬁbrosis. J Am Acad Dermatol 1990; 22: 351–355. 8 Wanless IR, Peterson P, Das A, Boitnott JK, Moore GW, Bernier V. Hepatic vascular disease and portal hypertension in polycythemia vera and agnogenic myeloid metaplasia: a clinicopathological study of 145 patients examined at autopsy. Hepatology 1990; 12: 1166–1174. 9 Tefferi A, Guglielmelli P, Larson DR, Finke C, Wassie EA, Pieri L et al. Long-term survival and blast transformation in molecularly annotated essential thrombocythemia, polycythemia vera, and myeloﬁbrosis. Blood 2014; 124: 2507–2513. 9 Tefferi A, Guglielmelli P, Larson DR, Finke C, Wassie EA, Pieri L et al. Long-term survival and blast transformation in molecularly annotated essential thrombocythemia, polycythemia vera, and myeloﬁbrosis. Blood 2014; 124: 2507–2513. Blood Cancer Journal Extracellular matrix in primary myeloﬁbrosis Extracellular matrix in primary myeloﬁbrosis O Leiva et al 7 10 O'Sullivan LA, Liongue C, Lewis RS, Stephenson SE, Ward AC. Cytokine receptor signaling through the Jak–Stat–Socs pathway in disease. Mol Immunol 2007; 44: 2497–2506. 38 Sugiyama T, Kohara H, Noda M, Nagasawa T. Maintenance of the hematopoietic stem cell pool by CXCL12-CXCR4 chemokine signaling in bone marrow stromal cell niches. Immunity 2006; 25: 977–988. ECM AND POTENTIAL NEW THERAPEUTICS 11 Levine RL, Wadleigh M, Cools J, Ebert BL, Wernig G, Huntly BJ et al. Activating mutation in the tyrosine kinase JAK2 in polycythemia vera, essential thrombo- cythemia, and myeloid metaplasia with myeloﬁbrosis. Cancer Cell 2005; 7: 387–397. 39 Katayama Y, Battista M, Kao WM, Hidalgo A, Peired AJ, Thomas SA et al. Signals from the sympathetic nervous system regulate hematopoietic stem cell egress from bone marrow. Cell 2006; 124: 407–421. 40 Mendez-Ferrer S, Lucas D, Battista M, Frenette PS. Haematopoietic stem cell release is regulated by circadian oscillations. Nature 2008; 452: 442–447. 12 Baxter EJ, Scott LM, Campbell PJ, East C, Fourouclas N, Swanton S et al. Acquired mutation of the tyrosine kinase JAK2 in human myeloproliferative disorders. Lancet 2005; 365: 1054–1061. 41 Lucas D, Scheiermann C, Chow A, Kunisaki Y, Bruns I, Barrick C et al. Chemotherapy-induced bone marrow nerve injury impairs hematopoietic regeneration. Nat Med 2013; 19: 695–703. 13 Zhao R, Xing S, Li Z, Fu X, Li Q, Krantz SB et al. Identiﬁcation of an acquired JAK2 mutation in polycythemia vera. J Biol Chem 2005; 280: 22788–22792. 42 Klamer S, Voermans C. The role of novel and known extracellular matrix and adhesion molecules in the homeostatic and regenerative bone marrow micro- environment. Cell Adh Migr 2014; 8: 563–577. 14 Vainchenker W, Constantinescu SN, Plo I. Recent advances in understanding myeloﬁbrosis and essential thrombocythemia. F1000Res 2016; e-pub ahead of print 19 April 2016; doi:10.12688/f1000research.8081.1. 43 Kopp H-G, Avecilla ST, Hooper AT, Raﬁi S. The bone marrow vascular niche: home of HSC differentiation and mobilization. Physiology 2005; 20: 349–356. 15 KlampﬂT, Gisslinger H, Harutyunyan AS, Nivarthi H, Rumi E, Milosevic JD et al. Somatic mutations of calreticulin in myeloproliferative neoplasms. N Engl J Med 2013; 369: 2379–2390. 44 Christiansen A, Detmar M. Lymphangiogenesis and cancer. Genes Cancer 2011; 2: 1146–1158. 16 Chachoua I, Pecquet C, El-Khoury M, Nivarthi H, Albu R-I, Marty C et al. Throm- bopoietin receptor activation by myeloproliferative neoplasm associated calre- ticulin mutants. Blood 2015; 127: 1325–1335. 45 Varricchio L, Mancini A, Migliaccio AR. Pathological interactions between hematopoietic stem cells and their niche revealed by mouse models of primary myeloﬁbrosis. Expert Rev Hematol 2009; 2: 315–334. 17 Rumi E, Pietra D, Pascutto C, Guglielmelli P, Martínez-Trillos A, Casetti I et al. Clinical effect of driver mutations of JAK2, CALR, or MPL in primary myeloﬁbrosis. Blood 2014; 124: 1062–1069. ECM AND POTENTIAL NEW THERAPEUTICS 46 Arranz L, Sanchez-Aguilera A, Martin-Perez D, Isern J, Langa X, Tzankov A et al. Neuropathy of haematopoietic stem cell niche is essential for myeloproliferative neoplasms. Nature 2014; 512: 78–81. 18 Pardanani AD, Levine RL, Lasho T, Pikman Y, Mesa RA, Wadleigh M et al. MPL515 mutations in myeloproliferative and other myeloid disorders: a study of 1182 patients. Blood 2006; 108: 3472–3476. 47 Livun A, Newberry KJ, Manshouri T, Kusec R, Verstovsek S. Genes involved in maintaining the bone marrow stroma are dysregulated in patients with mye- loﬁbrosis: lenalidomide treatment up-regulates SOCS3. Anticancer Res 2015; 35: 5219–5223. 19 Tefferi A, Lasho TL, Finke CM, Knudson RA, Ketterling R, Hanson CH et al. CALR vs JAK2 vs MPL-mutated or triple-negative myeloﬁbrosis: clinical, cytogenetic and molecular comparisons. Leukemia 2014; 28: 1472–1477. 48 Schepers K, Pietras EM, Reynaud D, Flach J, Binnewies M, Garg T et al. Myelo- proliferative neoplasia remodels the endosteal bone marrow niche into a self- reinforcing leukemic niche. Cell Stem Cell 2013; 13: 285–299. 20 Tefferi A, Jimma T, Sulai NH, Lasho TL, Finke CM, Knudson RA et al. IDH mutations in primary myeloﬁbrosis predict leukemic transformation and shortened survival: clinical evidence for leukemogenic collaboration with JAK2V617F. Leukemia 2012; 26: 475–480. 49 Lu M, Xia L, Liu YC, Hochman T, Bizzari L, Aruch D et al. Lipocalin produced by myeloﬁbrosis cells affects the fate of both hematopoietic and marrow microenvironmental cells. Blood 2015; 126: 972–982. 21 Tefferi A, Wassie EA, Guglielmelli P, Gangat N, Belachew AA, Lasho TL et al. Type 1 versus Type 2 calreticulin mutations in essential thrombocythemia: a colla- borative study of 1027 patients. Am J Hematol 2014; 89: E121–E124. 50 Tripodo C, Sangaletti S, Guarnotta C, Piccaluga PP, Cacciatore M, Giuliano M et al. Stromal SPARC contributes to the detrimental ﬁbrotic changes associated with myeloproliferation whereas its deﬁciency favors myeloid cell expansion. Blood 2012; 120: 3541–3554. y 22 Mascarenhas J, Roper N, Chaurasia P, Hoffman R. Epigenetic abnormalities in myeloproliferative neoplasms: a target for novel therapeutic strategies. Clin Epigenetics 2011; 2: 197–212. 51 Mesa RA, Hanson CA, Rajkumar SV, Schroeder G, Tefferi A. Evaluation and clinical correlations of bone marrow angiogenesis in myeloﬁbrosis with myeloid metaplasia. Blood 2000; 96: 3374–3380. 23 Di Buduo CA, Wray LS, Tozzi L, Malara A, Chen Y, Ghezzi CE et al. Programmable 3D silk bone marrow niche for platelet generation ex vivo and modeling of megakaryopoiesis pathologies. ECM AND POTENTIAL NEW THERAPEUTICS Blood 2015; 125: 2254–2264. 52 Tripodo C, Di Bernardo A, Ternullo MP, Guarnotta C, Porcasi R, Ingrao S et al. CD146(+) bone marrow osteoprogenitors increase in the advanced stages of primary myeloﬁbrosis. Haematologica 2009; 94: 127–130. 24 Calvi L, Adams G, Weibrecht K, Weber J, Olson D, Knight M et al. Osteoblastic cells regulate the haematopoietic stem cell niche. Nature 2003; 425: 841–846. 53 Rosti V, Villani L, Riboni R, Poletto V, Bonetti E, Tozzi L et al. Spleen endothelial cells from patients with myeloﬁbrosis harbor the JAK2V617F mutation. Blood 2013; 121: 360–368. 25 Yin T, Li L. The stem cell niches in bone. J Clin Invest 2006; 116: 1195–1201. 26 Machlus KR, Italiano JE. The incredible journey: from megakaryocyte develop- ment to platelet formation. J Cell Biol 2013; 201: 785–796. 54 Sozer S, Fiel MI, Schiano T, Xu M, Mascarenhas J, Hoffman R. The presence of JAK2V617F mutation in the liver endothelial cells of patients with Budd-Chiari syndrome. Blood 2009; 113: 5246–5249. 27 Seita J, Weissman IL. Hematopoietic stem cell: self‐renewal versus differentiation. Wiley Interdiscip Rev Syst Biol Med 2010; 2: 640–653. syndrome. Blood 2009; 113: 5246–5249. 28 Boulais PE, Frenette PS. Making sense of hematopoietic stem cell niches. Blood 2015; 125: 2621–2629. 55 Lin CH, Kaushansky K, Zhan H. JAK2V617F-mutant vascular niche contributes to JAK2V617F clonal expansion in myeloproliferative neoplasms. Blood Cells Mol Dis 2016; 62: 42–48. 29 Guerrouahen BS, Al-Hijji I, Tabrizi AR. Osteoblastic and vascular endothelial niches, their control on normal hematopoietic stem cells, and their con- sequences on the development of leukemia. Stem Cells Int 2011; 2011: 375857. 56 Vannucchi AM, Guglielmelli P, Tefferi A. Advances in understanding and management of myeloproliferative neoplasms. CA Cancer J Clin 2009; 59: 171–191. 30 Gattazzo F, Urciuolo A, Bonaldo P. Extracellular matrix: a dynamic micro- environment for stem cell niche. Biochim Biophys Acta 2014; 1840: 2506–2519. 57 Tripodo C, Sangaletti S, Piccaluga PP, Prakash S, Franco G, Borrello I et al. The bone marrow stroma in hematological neoplasms--a guilty bystander. Nat Rev Clin Oncol 2011; 8: 456–466. 31 Wilson A, Trumpp A. Bone-marrow haematopoietic-stem-cell niches. Nat Rev Immunol 2006; 6: 93–106. 32 Zhang J, Niu C, Ye L, Huang H, He X, Tong WG et al. Identiﬁcation of the haematopoietic stem cell niche and control of the niche size. Nature 2003; 425: 836–841. 58 Bonnans C, Chou J, Werb Z. Remodelling the extracellular matrix in development and disease. ECM AND POTENTIAL NEW THERAPEUTICS Nat Rev Mol Cell Biol 2014; 15: 786–801. 59 Le Bousse-Kerdilès M-C, Martyré M-C, Samson M. Cellular and molecular mechanisms underlying bone marrow and liver ﬁbrosis: a review. Eur Cytokine Netw 2008; 19: 69–80. 33 Taichman RS, Reilly MJ, Emerson SG. Human osteoblasts support human hematopoietic progenitor cells in vitro bone marrow cultures. Blood 1996; 87: 518–524. 60 Fuchs E, Tumbar T, Guasch G. Socializing with the neighbors: stem cells and their niche. Cell 2004; 116: 769–778. 34 Taichman RS, Emerson SG. Human osteoblasts support hematopoiesis through the production of granulocyte colony-stimulating factor. J Exp Med 1994; 179: 1677–1682. 61 Morrison SJ, Spradling AC. Stem cells and niches: mechanisms that promote stem cell maintenance throughout life. Cell 2008; 132: 598–611. 35 Adams GB, Chabner KT, Alley IR, Olson DP, Szczepiorkowski ZM, Poznansky MC et al. Stem cell engraftment at the endosteal niche is speciﬁed by the calcium- sensing receptor. Nature 2006; 439: 599–603. 62 Aguilar A, Pertuy F, Eckly A, Strassel C, Collin D, Gachet C et al. Importance of environmental stiffness for megakaryocyte differentiation and proplatelet for- mation. Blood 2016; 128: 2022–2032. 36 Krause DS, Scadden DT, Preffer FI. The hematopoietic stem cell niche—home for friend and foe? Cytometry B Clin Cytom 2013; 84: 7–20. 63 Malara A, Gruppi C, Pallotta I, Spedden E, Tenni R, Raspanti M et al. Extracellular matrix structure and nano-mechanics determine megakaryocyte function. Blood 2011; 118: 4449–4453. 37 Mendelson A, Frenette PS. Hematopoietic stem cell niche maintenance during homeostasis and regeneration. Nat Med 2014; 20: 833. homeostasis and regeneration. Nat Med 2014; 20: 833. Blood Cancer Journal Blood Cancer Journal Extracellular matrix in primary myeloﬁbrosis O Leiva et al Extracellular matrix in primary myeloﬁbrosis O Leiva et al 8 64 Lieber MM. Towards an understanding of the role of forces in carcino- genesis: a perspective with therapeutic implications. Riv Biol 2006; 99: 131–160. 64 Lieber MM. Towards an understanding of the role of forces in carcino- genesis: a perspective with therapeutic implications. Riv Biol 2006; 99: 131–160. 91 Sage H, Vernon RB, Funk SE, Everitt EA, Angello J. SPARC, a secreted protein associated with cellular proliferation, inhibits cell spreading in vitro and exhibits Ca+2-dependent binding to the extracellular matrix. J Cell Biol 1989; 109: 341–356. 65 Wolfe JN. Risk for breast cancer development determined by mammographic parenchymal pattern. Cancer 1976; 37: 2486–2492. 92 Sangaletti S, Stoppacciaro A, Guiducci C, Torrisi MR, Colombo MP. ECM AND POTENTIAL NEW THERAPEUTICS 98 Eliades A, Papadantonakis N, Bhupatiraju A, Burridge KA, Johnston-Cox HA, Migliaccio AR et al. Control of megakaryocyte expansion and bone marrow ﬁbrosis by lysyl oxidase. J Biol Chem 2011; 286: 27630–27638. 73 Pallotta I, Lovett M, Rice W, Kaplan DL, Balduini A. Bone marrow osteoblastic niche: a new model to study physiological regulation of megakaryopoiesis. PLoS ONE 2009; 4: e8359. 99 Papadantonakis N, Matsuura S, Ravid K. Megakaryocyte pathology and bone marrow ﬁbrosis: the lysyl oxidase connection. Blood 2012; 120: 1774–1781. 74 Chang Y, Auradé F, Larbret F, Zhang Y, Le Couedic J-P, Momeux L et al. Pro- platelet formation is regulated by the Rho/ROCK pathway. Blood 2007; 109: 4229–4236. 100 Tadmor T, Bejar J, Attias D, Mischenko E, Sabo E, Neufeld G et al. The expression of lysyl‐oxidase gene family members in myeloproliferative neoplasms. Am J Hematol 2013; 88: 355–358. 75 Bergmeier W, Hynes RO. Extracellular matrix proteins in hemostasis and thrombosis. Cold Spring Harb Perspect Biol 2012; 4: a005132. 101 Green RS, Lieb ME, Weintraub AS, Gacheru SN, Rosenﬁeld C-L, Shah S et al. Identiﬁcation of lysyl oxidase and other platelet-derived growth factor-inducible genes in vascular smooth muscle cells by differential screening. Lab Invest 1995; 73: 476–482. 76 Watson SP. Platelet activation by extracellular matrix proteins in haemostasis and thrombosis. Curr Pharm Des 2009; 15: 1358–1372. 77 Terui T, Niitsu Y, Mahara K, Fujisaki Y, Urushizaki Y, Mogi Y et al. The pro- duction of transforming growth factor-beta in acute megakaryoblastic leu- kemia and its possible implications in myeloﬁbrosis. Blood 1990; 75: 1540–1548. 102 Hong H-H, Uzel MI, Duan C, Sheff MC, Trackman PC. Regulation of lysyl oxidase, collagen, and connective tissue growth factor by TGF-beta1 and detection in human gingiva. Lab Invest 1999; 79: 1655–1667. 78 Thiele J, Kvasnicka HM. Grade of bone marrow ﬁbrosis is associated with relevant hematological ﬁndings-a clinicopathological study on 865 patients with chronic idiopathic myeloﬁbrosis. Ann Hematol 2006; 85: 226–232. 103 Lucero HA, Ravid K, Grimsby JL, Rich CB, DiCamillo SJ, Maki JM et al. Lysyl oxidase oxidizes cell membrane proteins and enhances the chemotactic response of vascular smooth muscle cells. J Biol Chem 2008; 283: 24103–24117. vascular smooth muscle cells. J Biol Chem 2008; 283: 24103–24 79 Yamada K. Provisional matrix. In: Clark R (ed.). The Molecular and Cellular Biology of Wound Repair, Plenum Press: New York, NY, USA, 1996, pp 51–82. ECM AND POTENTIAL NEW THERAPEUTICS Leukocyte, rather than tumor-produced SPARC, determines stroma and collagen type IV deposition in mammary carcinoma. J Exp Med 2003; 198: 1475–1485. 66 Frantz C, Stewart KM, Weaver VM. The extracellular matrix at a glance. J Cell Sci 2010; 123: 4195–4200. 67 Ciurea SO, Merchant D, Mahmud N, Ishii T, Zhao Y, Hu W et al. Pivotal con- tributions of megakaryocytes to the biology of idiopathic myeloﬁbrosis. Blood 2007; 110: 986–993. 93 Maral S, Acar M, Balcik OS, Uctepe E, Hatipoglu OF, Akdeniz D et al. Matrix metalloproteinases 2 and 9 polymorphism in patients with myelopro- liferative diseases: a STROBE-compliant observational study. Medicine 2015; 94: e732. 68 Bock O, Höftmann J, Theophile K, Hussein K, Wiese B, Schlué J et al. Bone morphogenetic proteins are overexpressed in the bone marrow of primary myeloﬁbrosis and are apparently induced by ﬁbrogenic cytokines. Am J Pathol 2008; 172: 951–960. 94 Lin P-S, Chang H-H, Yeh C-Y, Chang M-C, Chan C-P, Kuo H-Y et al. Transforming growth factor beta 1 increases collagen content, and stimulates procollagen I and tissue inhibitor of metalloproteinase-1 production of dental pulp cells: Role of MEK/ERK and activin receptor-like kinase-5/Smad signaling. J Formos Med Assoc 2016; e-pub ahead of print 6 October 2016; doi:10.1016/j.jfma.2016.07.014. 69 Hasselbalch HC. The role of cytokines in the initiation and progression of myeloﬁbrosis. Cytokine Growth Factor Rev 2013; 24: 133–145. 70 Malara A, Currao M, Gruppi C, Celesti G, Viarengo G, Buracchi C et al. Megakaryocytes contribute to the bone marrow‐matrix environment by expressing ﬁbronectin, type IV collagen, and laminin. Stem Cells 2014; 32: 926–937. 95 Wang JC, Novetsky A, Chen C, Novetsky AD. Plasma matrix metalloproteinase and tissue inhibitor of metalloproteinase in patients with agnogenic myeloid metaplasia or idiopathic primary myeloﬁbrosis. Br J Haematol 2002; 119: 709–712. 71 Abbonante V, Di Buduo CA, Gruppi C, Malara A, Gianelli U, Celesti G et al. Thrombopoietin/TGF‐β1 loop regulates megakaryocyte extracellular matrix component synthesis. Stem Cells 2016; 34: 1123–1133. 96 Lucero HA, Kagan HM. Lysyl oxidase: an oxidative enzyme and effector of cell function. Cell Mol Life Sci 2006; 63: 2304–2316. 97 Eliades A, Papadantonakis N, Matsuura S, Mi R, Bais MV, Trackman P et al. Megakaryocyte polyploidy is inhibited by lysyl oxidase propeptide. Cell Cycle 2013; 12: 1242–1250. 72 Reddi AH, Gay R, Gay S, Miller EJ. Transitions in collagen types during matrix- induced cartilage, bone, and bone marrow formation. Proc Natl Acad Sci 1977; 74: 5589–5592. ECM AND POTENTIAL NEW THERAPEUTICS 104 Martyre M, Romquin N, Bousse‐Kerdiles M, Chevillard S, Benyahia B, Dupriez B et al. Transforming growth factor‐β and megakaryocytes in the pathogenesis of idiopathic myeloﬁbrosis. Br J Haematol 1994; 88: 9–16. 80 Malara A, Gruppi C, Rebuzzini P, Visai L, Perotti C, Moratti R et al. Megakaryocyte- matrix interaction within bone marrow: new roles for ﬁbronectin and factor XIII-A. Blood 2011; 117: 2476–2483. 105 Martyré MC, Magdelenat H, Calvo F. Interferon‐γin vivo reverses the increased platelet levels of platelet‐derived growth factor and transforming growth factor‐ β in patients with myeloﬁbrosis with myeloid metaplasia. Br J Haematol 1991; 77: 431–435. 81 Schneider RK, Ziegler S, Leisten I, Ferreira MS, Schumacher A, Rath B et al. Activated ﬁbronectin-secretory phenotype of mesenchymal stromal cells in pre- ﬁbrotic myeloproliferative neoplasms. J. Hematol Oncol 2014; 7: 92. 106 Le Bousse-Kerdiles M-C, Chevillard S, Charpentier A, Romquin N, Clay D, Smadja- Joffe F et al. Differential expression of transforming growth factor-beta, basic ﬁbroblast growth factor, and their receptors in CD34+ hematopoietic progenitor cells from patients with myeloﬁbrosis and myeloid metaplasia. Blood 1996; 88: 4534–4546. 82 Abbonante V, Gruppi C, Catarsi P, Avanzini MA, Tira ME, Barosi G et al. Altered ﬁbronectin expression and deposition by myeloproliferative neoplasm-derived mesenchymal stromal cells. Br J Haematol 2016; 172: 140–144. 83 Chang VT, Yook C, Rameshwar P. Synergism between ﬁbronectin and trans- forming growth factor-beta1 in the production of substance P in monocytes of patients with myeloﬁbrosis. Leuk Lymphoma 2013; 54: 631–638. 107 Di Raimondo F, Azzaro M, Palumbo G, Bagnato S, Stagno F, Giustolisi G et al. Elevated vascular endothelial growth factor (VEGF) serum levels in idiopathic myeloﬁbrosis. Leukemia 2001; 15: 976–980. 84 Bornstein P. Thrombospondins as matricellular modulators of cell function. J Clin Invest 2001; 107: 929–934. 108 Sollazzo D, Forte D, Polverelli N, Romano M, Perricone M, Rossi L et al. Crucial factors of the inﬂammatory microenvironment (IL-1beta/ TNF-alpha/TIMP-1) promote the maintenance of the malignant hemopoietic clone of myeloﬁbrosis: an in vitro study. Oncotarget 2016; 7: 43974–43988. 85 Bornstein P. Thrombospondins function as regulators of angiogenesis. J Cell Commun Signal 2009; 3: 189–200. 86 Muth M, Engelhardt BM, Kroger N, Hussein K, Schlue J, Busche G et al. Thrombospondin-1 (TSP-1) in primary myeloﬁbrosis (PMF) - a megakaryocyte- derived biomarker which largely discriminates PMF from essential thrombo- cythemia. Ann Hematol 2011; 90: 33–40. an in vitro study. Oncotarget 2016; 7: 43974–43988. Extracellular matrix in primary myeloﬁbrosis O Leiva et al O Leiva et al 9 113 Kreipe H, Büsche G, Bock O, Hussein K. Myeloﬁbrosis: molecular and cell biolo- gical aspects. Fibrogenesis Tissue Repair 2012; 5: 1. 131 Wen QJ, Yang Q, Goldenson B, Malinge S, Lasho T, Schneider RK et al. Targeting megakaryocytic-induced ﬁbrosis in myeloproliferative neoplasms by AURKA inhibition. Nat Med 2015; 21: 1473–1480. 114 Wang JC. Importance of plasma matrix metalloproteinases (MMP) and tissue inhibitors of metalloproteinase (TIMP) in development of ﬁbrosis in agnogenic myeloid metaplasia. Leuk Lymphoma 2005; 46: 1261–1268. 132 Goldenson B, Kirsammer G, Stankiewicz MJ, Wen QJ, Crispino JD. Aurora kinase A is required for hematopoiesis but is dispensable for murine megakaryocyte endomitosis and differentiation. Blood 2015; 125: 2141–2150. 115 Assoian RK, Komoriya A, Meyers CA, Miller DM, Sporn MB. Transforming growth factor-beta in human platelets. Identiﬁcation of a major storage site, puriﬁcation, and characterization. J Biol Chem 1983; 258: 7155–7160. 133 Krause DS, Crispino JD. Molecular pathways: induction of polyploidy as a novel differentiation therapy for leukemia. Clin Cancer Res 2013; 19: 6084–6088. 116 Dong M, Blobe GC. Role of transforming growth factor-beta in hematologic malignancies. Blood 2006; 107: 4589–4596. 134 Lin TL, Matsui W. Hedgehog pathway as a drug target: smoothened inhibitors in development. Onco Targets Ther 2012; 5: 47–58. 135 Verstovsek S, Talpaz M, Ritchie E, Wadleigh M, Odenike OM, Jamieson C et al. A Phase I, open-label, dose-escalation, multicenter study of the JAK2 inhibitor NS-018 in patients with myeloﬁbrosis. Leukemia 2017; 31: 393–402. 117 Martyré MC, Magdelenat H, Bryckaert MC, Laine‐Bidron C, Calvo F. Increased intraplatelet levels of platelet‐derived growth factor and transforming growth factor‐β in patients with myeloﬁbrosis with myeloid metaplasia. Br J Haematol 1991; 77: 80–86. 136 Odenike O, Halpern A, Godley LA, Madzo J, Karrison T, Green M et al. A phase I and pharmacodynamic study of the histone deacetylase inhibitor belinostat plus azacitidine in advanced myeloid neoplasia. Invest New Drugs 2015; 33: 371–379. 118 Pitchford SC, Lodie T, Rankin SM. VEGFR1 stimulates a CXCR4-dependent translocation of megakaryocytes to the vascular niche, enhancing platelet pro- duction in mice. Blood 2012; 120: 2787–2795. 119 Kroger N, Giorgino T, Scott BL, Ditschkowski M, Alchalby H, Cervantes F et al. Impact of allogeneic stem cell transplantation on survival of patients less than 65 years of age with primary myeloﬁbrosis. Blood 2015; 125: 3347–3350. 137 Evrot E, Ebel N, Romanet V, Roelli C, Andraos R, Qian Z et al. Extracellular matrix in primary myeloﬁbrosis O Leiva et al JAK1/2 and Pan- deacetylase inhibitor combination therapy yields improved efﬁcacy in preclinical mouse models of JAK2V617F-driven disease. Clin Cancer Res 2013; 19: 6230–6241. 120 Cervantes F. Modern management of myeloﬁbrosis. Br J Haematol 2005; 128: 583–592. 138 Verstovsek S, Manshouri T, Pilling D, Bueso-Ramos CE, Newberry KJ, Prijic S et al. Role of neoplastic monocyte-derived ﬁbrocytes in primary myeloﬁbrosis. J Exp Med 2016; 213: 1723–1740. 121 Sirhan S, Lasho TL, Hanson CA, Mesa RA, Pardanani A, Tefferi A. The presence of JAK2V617F in primary myeloﬁbrosis or its allele burden in polycythemia vera predicts chemosensitivity to hydroxyurea. Am J Hematol 2008; 83: 363–365. 139 Stein BL, Cervantes F, Giles F, Harrison CN, Verstovsek S. Novel therapies for myeloﬁbrosis. Leuk Lymphoma 2015; 56: 2768–2778. 122 Mesa RA, Yao X, Cripe LD, Li CY, Litzow M, Paietta E et al. Lenalidomide and prednisone for myeloﬁbrosis: Eastern Cooperative Oncology Group (ECOG) phase 2 trial E4903. Blood 2010; 116: 4436–4438. 140 Zingariello M, Martelli F, Ciaffoni F, Masiello F, Ghinassi B, D'Amore E et al. Characterization of the TGF-beta1 signaling abnormalities in the Gata1low mouse model of myeloﬁbrosis. Blood 2013; 121: 3345–3363. 123 Cervantes F, Alvarez-Larran A, Domingo A, Arellano-Rodrigo E, Montserrat E. Efﬁcacy and tolerability of danazol as a treatment for the anaemia of myeloﬁ- brosis with myeloid metaplasia: long-term results in 30 patients. Br J Haematol 2005; 129: 771–775. 141 Schliemann C, Gerss J, Wiebe S, Mikesch JH, Knoblauch /, Sauer T et al. A phase I dose escalation study of the triple angiokinase inhibitor nintedanib combined with low-dose cytarabine in elderly patients with acute myeloid leukemia. PLoS ONE 2016; 11: e0164499. 124 Harrison CN, Vannucchi AM, Kiladjian JJ, Al-Ali HK, Gisslinger H, Knoops L et al. Long-term ﬁndings from COMFORT-II, a phase 3 study of ruxolitinib vs best available therapy for myeloﬁbrosis. Leukemia 2016; 30: 1701–1707. 142 Mesa RA, Silver RT, Verstovsek S, Mascarenhas J, Kessler CM, Rondelli D et al. Single agent bevacizumab for myeloﬁbrosis: results of the Myeloproliferative Disorders Research Consortium Trial. Haematologica 2013; 98: 1421–1423. 125 Wilkins BS, Radia D, Woodley C, Farhi SE, Keohane C, Harrison CN. Resolution of bone marrow ﬁbrosis in a patient receiving JAK1/JAK2 inhibitor treatment with ruxolitinib. Haematologica 2013; 98: 1872–1876. 143 Steensma DP, Mesa RA, Li CY, Gray L, Tefferi A. Etanercept, a soluble tumor necrosis factor receptor, palliates constitutional symptoms in patients with myeloﬁbrosis with myeloid metaplasia: results of a pilot study. ECM AND POTENTIAL NEW THERAPEUTICS 109 Pohlers D, Brenmoehl J, Löfﬂer I, Müller CK, Leipner C, Schultze-Mosgau S et al. TGF-β and ﬁbrosis in different organs—molecular pathway imprints. Biochim Biophys Acta 2009; 1792: 746–756. 87 Kyriakides TR, Rojnuckarin P, Reidy MA, Hankenson KD, Papayannopoulou T, Kaushansky K et al. Megakaryocytes require thrombospondin-2 for normal pla- telet formation and function. Blood 2003; 101: 3915–3923. 110 Vannucchi AM, Bianchi L, Paoletti F, Pancrazzi A, Torre E, Nishikawa M et al. A pathobiologic pathway linking thrombopoietin, GATA-1, and TGF-β1 in the development of myeloﬁbrosis. Blood 2005; 105: 3493–3501. 88 Wynn T. Cellular and molecular mechanisms of ﬁbrosis. J Pathol 2008; 214: 199–210. 111 Zhou Y, Koli K, Hagood JS, Miao M, Mavalli M, Rifkin DB et al. Latent transforming growth factor-β-binding protein-4 regulates transforming growth factor-β1 bioavailability for activation by ﬁbrogenic lung ﬁbroblasts in response to bleo- mycin. Am J Pathol 2009; 174: 21–33. 89 Chagraoui H, Komura E, Tulliez M, Giraudier S, Vainchenker W, Wendling F. Prominent role of TGF-beta 1 in thrombopoietin-induced myeloﬁbrosis in mice. Blood 2002; 100: 3495–3503. 112 Munger JS, Sheppard D. Cross talk among TGF-β signaling pathways, integrins, and the extracellular matrix. Cold Spring Harb Perspect Biol 2011; 3: a005017. 90 Sage EH. Terms of attachment: SPARC and tumorigenesis. Nat Med 1997; 3: 144–146. Blood Cancer Journal Extracellular matrix in primary myeloﬁbrosis Extracellular matrix in primary myeloﬁbrosis O Leiva et al © The Author(s) 2017 Extracellular matrix in primary myeloﬁbrosis O Leiva et al Blood 2002; 99: 2252–2254. 126 Harrison C, Kiladjian JJ, Al-Ali HK, Gisslinger H, Waltzman R, Stalbovskaya V et al. JAK inhibition with ruxolitinib versus best available therapy for myeloﬁbrosis. N Engl J Med 2012; 366: 787–798. 127 Verstovsek S, Mesa RA, Gotlib J, Levy RS, Gupta V, DiPersio JF et al. A double- blind, placebo-controlled trial of ruxolitinib for myeloﬁbrosis. N Engl J Med 2012; 366: 799–807. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/ by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/ by/4.0/ 128 Passamonti F, Mafﬁoli M, Cervantes F, Vannucchi AM, Morra E, Barbui T et al. Impact of ruxolitinib on the natural history of primary myeloﬁbrosis: a com- parison of the DIPSS and the COMFORT-2 cohorts. Blood 2014; 123: 1833–1835. 129 Tefferi A, Lasho TL, Begna KH, Patnaik MM, Zblewski DL, Finke CM et al. A pilot study of the telomerase inhibitor imetelstat for myeloﬁbrosis. N Engl J Med 2015; 373: 908–919. 130 Wen Q, Goldenson B, Silver SJ, Schenone M, Dancik V, Huang Z et al. Identiﬁ- cation of regulators of polyploidization presents therapeutic targets for treat- ment of AMKL. Cell 2012; 150: 575–589. Blood Cancer Journal Blood Cancer Journal
W2983475697.txt	https://www.mdpi.com/1996-1073/12/22/4333/pdf?version=1573710597	en		Fault Current Tracing and Identification via Machine Learning Considering Distributed Energy Resources in Distribution Networks	Energies	2,019	cc-by	5,533	energies Article Fault Current Tracing and Identification via Machine Learning Considering Distributed Energy Resources in Distribution Networks † Wanghao Fei and Paul Moses * School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK 73019, USA; whf@ou.edu * Correspondence: pmoses@ou.edu † This paper is an extended version of our paper published in In Proceedings of the 2019 IEEE 7th International Conference on Smart Energy Grid Engineering (SEGE), Oshawa, ON, Canada, 12–14 August 2018; pp. 196–200. Received: 11 October 2019; Accepted: 11 November 2019; Published: 14 November 2019 Abstract: The growth of intermittent distributed energy sources (DERs) in distribution grids is raising many new operational challenges for utilities. One major problem is the back feed power flows from DERs that complicate state estimation for practical problems, such as detection of lower level fault currents, that cause the poor accuracy of fault current identification for power system protection. Existing artificial intelligence (AI)-based methods, such as support vector machine (SVM), are unable to detect lower level faults especially from inverter-based DERs that offer limited fault currents. To solve this problem, a current tracing method (CTM) has been proposed to model the single distribution feeder as several independent parallel connected virtual lines that traces the detailed contribution of different current sources to the power line current. Moreover, for the first time, the enhanced current information is used as the expanded feature space of SVM to significantly improve fault current detection on the power line. The proposed method is shown to be sensitive to very low level fault currents which is validated through simulations. Keywords: current tracing; fault current; distributed energy resources; network model 1. Introduction Due to the increasing penetration rate of distributed energy sources (DERs), such as solar power injected at the distribution side of the power system, during the past decade, distribution grids have become large, complex, interconnected networks. The infusion of DERs onto distribution grids raises some new state estimation challenges, such as fault current identification, which was less of an issue in conventional distribution grids operating without DERs. The traditional distribution grid was not affected by irregular back power feeds caused by intermittent DER activity, as it was originally designed for single direction power flow from the substation to the customers. The ordinary fault current identification process is based on the fault current threshold where no DERs are injected into the distribution grid. With DERs, excess power can be generated and consumed by the customer or feed back to the distribution feeder. This raises new challenges, especially in grid modeling methods for fault current identification, where the impact of back feed power flow has to be considered for determining the fault current threshold. Failure to do so may have far reaching and costly consequences such as inadvertent tripping of circuits or overlooking faults in the system. Researchers have proposed many grid modeling methods for different types of power grids such as averaged models [1,2] and the port-Hamiltonian-based dynamic power system model [3]. Energies 2019, 12, 4333; doi:10.3390/en12224333 www.mdpi.com/journal/energies Energies 2019, 12, 4333 2 of 12 Certain modeling methods are suited for specific parts of the grid such as cyber-physical power systems framework modeling [4,5], topology modeling [6,7], load flow modeling [8,9], lightning protection models [10], and traveling wave modeling [11]. In [12,13], the author used pattern recognition to identify the fault current with the waveform data, which is an efficient tool for power transmission line fault detection. In addition, with the benefit of fast developing artificial intelligence (AI) technologies, many AI-based power system fault identification methods have been proposed as well, such as support vector machine (SVM) [14], k-nearest neighbors algorithm (KNN) [13], pattern recognition [15], and deep learning [16]. Although different AI methods have been used to improve the accuracy of power system fault identification, the approaches still heavily rely on grid modeling methods for some part of the power grid. Most importantly, almost all of these AI-based fault current identification methods based on existing grid modeling methods totally depend on the existing power line infrastructure, in that currents from different power sources are congested to one end of a single power line and flow towards the other end [17–19]. These methods are very effective when it comes to the identification of larger fault currents, but some detailed current information such as those from inverter-based DERs are difficult to detect. A much more detailed grid modeling method is needed to augment the AI method to be more sensitive to detect some lower level faults. This is particularly important in modern distribution grids, as inverter-based DERs are known to produce exceptionally small fault current contributions, due to inverter current limiting action, and are very difficult to detect through conventional means. For addressing the aforementioned grid modeling problems, a detailed grid model (referred to herein as the CTM) was proposed by the authors in a companion paper [20], which has sufficient detail of the current flows on the power line from each individual DER connected to the grid. The main objectives of this paper are as follows. First, for the first time, it is shown how the accuracy of implementing AI algorithms on such a detailed grid model can be improved. Specifically, implementing SVM algorithm on the proposed CTM model is explored. Second, in addition to using fault current flows as the only input feature, the “traced” current information to expand the dimension of the feature space is exploited. That is, the traced current is used along with the power line current as the expanded feature space to identify the fault current which is a departure from existing methods. Finally, the performance of the combination of CTM with the SVM is demonstrated in the practical scenario of fault identification with DERs operating in distribution grids. Specifically, this work shows how applying this hybrid method can improve sensitivity in detecting very low level faults. This paper is organized as follows. In Section 2, the weaknesses of using traditional grid models for fault current identification are pointed out, and applying CTM for multiple current sources of a distribution grid is proposed. The SVM method is implemented for fault current identification using the traced current in Section 3. Simulation results are presented in Section 4 and are discussed in Section 5, with concluding remarks given in Section 6. 2. Proposed Tracing Method 2.1. Single Power Line Fault Current Threshold Consider the case where a DER group consists for example of solar and wind generation, a vehicle-to-grid support battery storage, and loads that are attached to bus 1 are connected to the end of the power distribution grid through a single power line as shown in Figure 1. Energies 2019, 12, 4333 3 of 12 Figure 1. Single power line with distributed energy source (DER) customers. ~ 1 and U ~ 2 are the voltages on buses 1 and In Figure 1, ~IL represents the power line current, and U ~ ~ 2, respectively. The applied voltage difference angle of U1 − U2 is ψ. Without the impact of the DER group, ~IL flows from bus 2 to bus 1 and the fault current can be easily identified by setting the fault current threshold. However, when the impact of renewable energy sources is considered, as in this case, the fault current threshold is difficult to determine, as the DERs may contribute to the fault current and the detection threshold varies. The power line’s current value and direction may also vary with the impact of DERs, which complicates the discrimination of faults from the normal condition. It is therefore necessary to know significantly more details of the current to determine if there is a fault on the power line or at the load. 2.2. Current Tracing Using Figure 1 to demonstrate the CTM deduction, without loss of generality, it is assumed that the power line impedance is Z = R + jX, (1) where R > 0 and X > 0 are the resistance and reactance of the power line, respectively. An alternative case, when X < 0, is discussed in the companion conference paper [20]. In this paper, only the X > 0 case is considered. The impedance angle is θ. Based on Kirchhoff’s current law, it follows that ~IL = ∑ Ii e jφi . (2) where ~Ii = Ii e jφi is the current of the ith DER, and Ii > 0 and φi are the magnitude and phase angle of ~Ii , respectively. Figure 1 can be expressed with an equivalent circuit as shown in Figure 2a. The equivalence holds as shown in Equations (3) and (4): R2 + X 2 , R R2 + X 2 XE = , X RE = (3) (4) where R E > 0 and XE > 0 are the equivalent resistance and reactance respectively. Naturally, the equivalent circuit has the same total resistance, current, and power of the original circuit. Energies 2019, 12, 4333 4 of 12 (a) Active-reactive current (b) Multiple current sources tracing Figure 2. Equivalent circuit. In the equivalent circuit, the power line current ~IL is virtually split into two parts defined as active current ~ILR and reactive current ~ILX , which flows through R E and XE , respectively: ~IL = ~ILR + ~ILX , (5) ~ILR = ILR e jψ , (6) ILR = IL cos(θ ), (7) ~ILX = ILX e j(ψ− π2 ) , ILX = IL sin(θ ), (8) (9) where ILR and ILX are the magnitude of the active current and reactive current, respectively. Likewise, all current sources attached to bus 1 follow the same rule: ~Ii = ~IRi + ~IXi = IRi e jψ + IXi e j(ψ− π2 ) , (10) IRi = ILi cos(ψ − φi ), (11) IXi = ILi sin(ψ − φi ), (12) where IRi and IXi are the magnitude of the active and reactive current from ~Ii , respectively, which could either be positive or negative. From Kirchhoff’s current law, ∑ (~IRi ) + ∑ (~IXi ) + IRi >0 IXi >0 where ∑ (~IRi ) and IRi >0 ∑ (~IRi ) = ∑(~IRi ) = ~ILR , (13) ∑ (~IXi ) = ∑(~IXi ) = ~ILX , (14) IRi <0 IXi <0 ∑ (~IRi ) stand for the positive and negative part of ~ILR , respectively, and IRi <0 ∑ (~IXi ) and ∑ (~IXi ) represent the positive and negative part of ~ILX , respectively. The positive part IXi >0 IXi <0 is responsible for supplying the load as well as feeding extra current to the power distribution grid. Energies 2019, 12, 4333 5 of 12 The negative part is responsible for absorbing current from positive part. The jth positive current source flowing through the power line is ~I + = I + e jψ , LRj LRj ~I + LXj π + j(ψ− 2 ) , = ILXj e + = ILRj (15) (16) ILR IRj , ∑ ( IRi ) (17) ILX IXj . ∑ ( IXi ) (18) IRi >0 + = ILXj IXi >0 + where ~ILRj is the active part of the jth positive current source flowing through the power line with magnitude of I + , and ~I + is the reactive part of the jth positive current source flowing through the LRj LXj + power line with magnitude of ILXj . Therefore, the distribution grid model where each of the currents are independent from one another can be shown in Figure 2b. Combining the active and reactive components of the jth positive current source flowing through the power line, the equivalent circuit with part of the jth positive current source that flows through + + + the power line can also be derived such that ~ILZj = ~ILRj + ~ILXj , with its impedance, ZEj , as shown in Figure 3. The complete derivation of this situation can be found in the companion paper [20]. Figure 3. Equivalent circuit of impedance lines. 3. Support Vector Machine and Current Tracing Kernel 3.1. Binary Classification Problem Formation Given a set of power line current measurements Z = {zi , i = 1...n}, zi ∈ Rm that may or may not contain fault current and the set of labels Y = {yi , i = 1...n}, yi ∈ {0, 1}, m stands for the dimension of the measurement, and n is the number of observations. The fault current identification problem can be modeled as a binary classification problem by establishing the connection between the above two sets such that ( −1 if ai = 0, yi = (19) 1 if ai 6= 0. yi = 1 indicates that the ith current measurement is fault current, or, alternatively, there are no fault currents for yi = −1. Energies 2019, 12, 4333 6 of 12 3.2. Support Vector Classifiers The classification problem is reformatted into the optimization problem in [21]. The objective function can be defined as m 1 min \|\|ω \|\|2 + C ∑ ξ i , (20) 2 i =1 where C is used to control the penalty of the misclassification, ω is a constant such that ω = [ω0 , ω1 , ...ωm ] T , and ξ i is the slack variable. The objective function is subject to the constraint that ω0 + ω T zi ≥ 1 − ξ i if yi = 1, T ω0 + ω zi ≤ ξ i − 1 if yi = −1. (21) (22) 3.3. Support Vector Machines As an extension of the support vector classifier, SVM is established by enlarging the feature space using kernel. Kernel is a function that is used to quantify the similarity of two observations. A linear Kernel is defined as the inner product of two observations [21]: m K ( zi , zi 0 ) = ∑ zi,j zi0 ,j , (23) j =1 where zi and zi0 are the two observations, and zi,j and zi0 ,j are the observations on jth dimension. In addition, some commonly used kernels are [21] • d Polynomial kernel: K (zi , zi0 ) = (1 + ∑m j=1 zi,j zi0 ,j ) • Radial kernel: K (zi , zi0 ) = exp(−γ ∑m ( xi,j − xi0 ,j )2 ) j =1 where γ and d are positive constants and r is a constant. 3.4. Current Tracing Kernel In [22], the author applied principle component analysis to select the best features with highest information content to identify faults. This study concluded that the top three features for fault identification were reactive power, real power, and angle of voltage. Interestingly, current is not one of them. The author concluded that with all of the three selected features, the accuracy of identification is almost 96%. With all of the six features, i.e., the above features plus magnitude and angle of current and magnitude of voltage, the accuracy of identification is no more than 97%. In the proposed approach, current is used as the only feature. Without current tracing, the feature space consists of only the line current magnitude and angle. Based on Equations (15)–(18), the line current can be decomposed into several traced currents flowing through virtual impedance lines as shown in Figure 3. The feature space of line currents can be enlarged by using the traced currents: + K ( IL , e j(ψ−θ ) ) = ~ILZj . (24) where K represents the linear mapping from power line current to the traced current. 4. Simulation Results 4.1. Current Tracing Kernel Results In this simulation, the proposed CTM is applied to the single line system of Figure 4. Both sides of the single line have a group of DERs and loads, and bus 2 is connected directly to the external distribution grid. All of the loads are of the constant power type, and the DERs are static generators. Energies 2019, 12, 4333 7 of 12 Figure 4. Multiple source to multiple source on single power line. The current sources parameters are listed in Table 1, which are given in the format of active and reactive power. DERs that connect to bus 1 cannot support the AC loads attached to bus 1 so that the currents flow from bus 2 to bus 1, which is opposite from the case shown in the companion paper [20]. Bus 2 is selected as the reference bus and the single power line is 20 km length with series impedance of 0.121 + j0.107 Ω/km. Table 1. The current source parameters. Bus Power Label Active/MW Reactive/MVar 1 1 2 3 4 −20 −20 30 20 −10 −5 15 5 2 1 2 3 −20 40 30.872544 −10 15 10.771589 In Table 1, the positive elements indicate an absorption of power whereas negative elements represents generating power. The third current source attached to bus 2 is the external grid and is calculated by the power flow. Equations (15) and (16) are applied to find the traced current on the power line from each bus as shown in Table 2. All of the traced currents are listed in per unit value. The traced current magnitude and phase in radians are selected as the kernel for fault current identification. Table 2. Current tracing results with Equations (15)–(18). Bus Label Active Current Tracing Reactive Current Tracing Mag Phase/° Mag Phase/° 1 1 2 3 4 0 0 5.3677 3.8535 0 0 13.5251 13.5251 0 0 5.6267 2.5276 0 0 −76.4749 −76.4749 2 1 2 3 0 3.5366 5.6847 0 13.5251 13.5251 0 3.6588 4.4955 0 −76.4749 −76.4749 In Table 2, a zero value indicates that the corresponding current source does not contribute to the current on the power line. It can be observed that the zero value occurs at bus 1; labels 1 and 2; and bus 2, label 1. This does not violate common sense as these are all labeled as loads that are Energies 2019, 12, 4333 8 of 12 consuming active and reactive power and do not contribute to the power line current. Moreover, all of the traced active currents have the same phase angle regardless of how the current is traced from bus 1 or bus 2 in either direction. The same rationale applies to the reactive currents. This is also consistent with the fact that the voltages applied on the buses do not change when the current is decomposed into its traced components. The reactive current is 90 degrees out of phase from the active current, which complies with Equations (15) and (16). It is observed that, if all of the traced currents from the same bus are summed, the result is equivalent to the total power line current. This proves the equivalence of the current tracing theory as the current tracing will not lose or generate new currents in addition to the line current. 4.2. SVM Results In distribution systems with DERs, the fault current can be very small, as inverter-based DERs can only produce exceptionally small fault current contributions due to inverter current limiting action. Moreover, injected currents on different loads are continuously fluctuating in the normal condition. To obtain representative currents in the single line system, sample noises are injected to the specified load powers in Table 1 and the power flow is recalculated to obtain the traced current. This process is then repeated to obtain the load profile and a continuous currents curve. The injected noise follows the normal distribution such that, X ∼ N (µ, σ2 ), (25) where X represents active or reactive power sample noises; µ represents the average of the sample noises, which is set to 0; and σ stands for the standard deviation, which is set to 0.1. All the sample noises are independent from each other. The sample noises were injected cumulatively to the loads such that the kth point on the load profile is k Pk = P + ∑ X pi , (26) i =1 k Qk = Q + ∑ Xqi , (27) i =1 where Pk and Qk represent the active and reactive power of the kth point of the load profile, respectively; P and Q represent the given active and reactive power (Table 1); and X pi and Xqi stand for the ith active or reactive power sample noises, respectively. This process is repeated 500 times, and all of the parameters that are used for current tracing and SVM training purpose are recorded. In addition to sample noises, a small fault is also injected by increasing the active power consumption of bus 1, with current source 3 increased by 10% and decreasing the reactive power by 10% of the same current source. Again, the process is repeated 500 times, and all parameters are recorded. Only the traced current on the power line from bus 2 side is used as the current tracing kernel; however, it is the same as if the traced current from bus 1 side was used as the current tracing kernel, as in the conference paper [20]. The first 500 parameters are taken as normal condition, i.e., yi = −1, and the last 500 parameters are considered as fault condition, i.e., yi = 1. The penalty of misclassification C is set to be 1. Seventy percent of the parameters are randomly selected as the training data, and the remaining 30% are taken as the testing data. In this work, the non-waveform phasor current information is used for the fault identification problem. Other alternative measurement data have been considered in other research, such as exploiting sub-cycle waveform distortion features in pattern recognition algorithms as a part of the identification process [12,15]. Energies 2019, 12, 4333 9 of 12 The confusion matrix is used to represent the testing results as defined in [23]. The f-score, recall, and precision parameters are used to evaluate the performance of fault current identification based on the confusion matrix such that, tp , tp + f p tp rec = , tp + f n prec ∗ rec fs = 2 , prec + rec prec = (28) (29) (30) where tp, fp, tn, and fn represent true positive, false positive, true negative, and false negative, respectively. To show the advantage of using the current tracing kernel, the fault current identification results using different feature spaces is compared. First, only the power line current ~IL is used as the feature space. Then, the polynomial kernel, radial kernel, and current tracing kernel are added as the expanded feature space. All of the confusion matrices are calculated based on the same training and testing data. The confusion matrices and the performance based on the confusion matrices are shown in Tables 3 and 4, respectively. Table 3. Confusion matrix using different feature space. Feature Space Fault Normal No Kernel Predict Fault Predict Normal tp = 90 fn = 13 fp = 61 tn = 136 Polynomial Kernel Predict Fault Predict Normal tp = 100 fn = 19 fp = 51 tn = 130 Radial Kernel Predict Fault Predict Normal tp = 95 fn = 16 fp = 56 tn = 133 Current Tracing Kernel Predict Fault Predict Normal tp = 145 fn = 0 fp = 6 tn = 149 Table 4. Performance using different feature space. Feature Space Precision Recall f1-Score No Kernel Polynomial Kernel Radial Kernel Current Tracing Kernel 0.596 0.662 0.629 0.96 0.874 0.840 0.856 1 0.709 0.74 0.725 0.98 It is clearly seen that among all the feature spaces used, the current tracing kernel has the best performance. All three performance parameters are significantly higher than the other feature spaces that were used. The recall value equals 1, which indicates that when there is a fault current on the power line; the SVM method using current tracing kernel will definitely detect it. In addition, the polynomial kernel and radial kernel have a better performance than if only ~IL is used as feature space. However, the performance parameters do not increase significantly. When comparing with the results shown in [22], which have 97% overall accuracy, the overall current tracing kernel result in this paper has improved, i.e., an f1-score value of 98%. 5. Discussion In the companion paper, it has been verified that the proposed tracing method is mathematically and physically identical to the original network. In this paper, the developed technique has been applied to a simple single power line system; however, it could be generalized to be as a part of a larger Energies 2019, 12, 4333 10 of 12 distribution grid. Using the proposed CTM, pipelines of each current sources’ contribution towards the fault currents were established in the form of virtually decomposed traced currents. The expanded features of the traced currents have the distinct advantage of containing more detailed information of the fault current, such as the change in contribution of each current source and the phase shift caused by the fault. These features can be exploited by the SVM algorithm for improved classification of faults, particularly where the fault levels are very low from the current limiting action of inverter-based DERs. By choosing a large sample set of 1000 data points for faulted and normal cases, the proposed SVM method combined with the current tracing kernel is shown to be much more sensitive to very low-level faults on the power line compared to the polynomial and radial kernel methods, where the accuracy of detection was at most 74%. Compared to the other methods, such as the one in [22] where the accuracy of detection was at most 97%, the proposed method has improved accuracy of 98% while using significantly less measurement features. These results are relevant in the context of smart grids aiming to improve distribution system state estimation, extending supervisory control and data acquisition processes beyond the substation domain as DERs proliferate. In these simulations, only the batch data is used for training and testing. However, the proposed model can be easily applied to practical streaming data obtained from intelligent electronic devices used in advanced metering infrastructure such as protection relays and phasor measurement units. With the enhanced features extracted through the proposed CTM, more intelligent protection relay coordination and fault isolation may be possible, particularly when considering multiple inverter-based DER operation from energy storage and renewable energy. 6. Concluding Remarks In this paper, we propose a CTM augmented with SVM method to model and test a distribution feeder for power line fault current identification. The CTM modeled the distribution network by providing a detailed map of how current flows from each current source that is connected to one bus towards another source tied to a different bus. The proposed method does not violate any physical circuit laws. After applying the proposed current tracing, the virtual traced currents and the corresponding circuit are exactly equivalent to the original current and circuit. The traced current provides sufficient details and sensitivity for identifying faults and abnormal conditions in the distribution feeder. With these details, the feature space of the power line current is enlarged through the “current tracing kernel”. In addition, the results proved and demonstrated the proposed method on a single power line distribution system, and the SVM method’s performance was evaluated and compared by using different kernel methods. The results indicate that with the benefits of the proposed current tracing kernel, the SVM method is enhanced with more sensitivity to very low level faults compared to the commonly used kernel such as polynomial kernel and radial kernel. The proposed method is a good fit for the distribution grid primary side overcurrent protection scheme. In the companion paper, the multicurrent sources to multicurrent source current tracing are already introduced, and they can be used to further expand the feature spaces of fault current. In the future, the authors will explore the implementation aspects of the proposed CTM described herein with the distribution grid backup protection scheme, especially the multicurrent sources to multicurrent sources case, which would undoubtedly occur with higher DER penetration in the future. Furthermore, in future work, the authors will explore how to implement and test this approach on a laboratory scale distribution test feeder to further verify the implementation of the SVM detection scheme using the proposed tracing method. Author Contributions: Conceptualization, W.F.; methodology, W.F. and P.M.; software, W.F.; validation, W.F. and P.M.; formal analysis, W.F.; investigation, W.F.; resources, W.F.; data curation, W.F.; writing–original draft preparation, W.F.; writing–review and editing, P.M.; visualization, W.F.; supervision, P.M.; project administration, P.M.; funding acquisition, P.M. Funding: This research was funded in part by the Oklahoma Center for the Advancement of Science and Technology (Project No. AR18-073) and the Oklahoma Gas & Electric Company (Project No. A18-0274). Energies 2019, 12, 4333 11 of 12 Conflicts of Interest: The authors declare no conflicts of interest. Abbreviations The following abbreviations are used in this manuscript. AI CTM DER KNN SVM Artificial Intelligence Current Tracing Method Distributed Energy Resource K-nearest Neighbors Support Vector Machine References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. Saad, H.; Peralta, J.; Dennetiere, S.; Mahseredjian, J.; Jatskevich, J.; Martinez, J.; Davoudi, A.; Saeedifard, M.; Sood, V.; Wang, X.; et al. Dynamic averaged and simplified models for MMC-based HVDC transmission systems. IEEE Trans. Power Deliv. 2013, 28, 1723–1730. [CrossRef] Daryabak, M.; Filizadeh, S.; Jatskevich, J.; Davoudi, A.; Saeedifard, M.; Sood, V.; Martinez, J.; Aliprantis, D.; Cano, J.; Mehrizi-Sani, A. Modeling of LCC-HVDC systems using dynamic phasors. IEEE Trans. Power Deliv. 2014, 29, 1989–1998. [CrossRef] Runolfsson, T. On the dynamics of three phase electrical energy systems. In Proceedings of the IEEE American Control Conference (ACC), Boston, MA, USA, 6–8 July 2016; pp. 6827–6832. Aravinthan, V.; Balachandran, T.; Ben-Idris, M.; Fei, W.; Heidari-Kapourchali, M.; Hettiarachchige-Don, A.; Jiang, J.N.; Lei, H.; Liu, C.C.; Mitra, J.; et al. Reliability modeling considerations for emerging cyber-physical power systems. In Proceedings of the 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), Boise, ID, USA, 24–28 June 2018; pp. 324–330. Davis, K.R.; Davis, C.M.; Zonouz, S.A.; Bobba, R.B.; Berthier, R.; Garcia, L.; Sauer, P.W. A cyber-physical modeling and assessment framework for power grid infrastructures. IEEE Trans. Smart Grid 2015, 6, 2464–2475. [CrossRef] Fei, W.; Jiang, J.N.; Wu, D. Impacts of Modeling Errors and Randomness on Topology Identification of Electric Distribution Network. In Proceedings of the 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), Boise, ID, USA, 24–28 June 2018; pp. 1–6. Ji, G.; Sharma, D.; Fei, W.; Wu, D.; Jiang, J.N. A Graph-theoretic Method for Identification of Electric Power Distribution System Topology. In Proceedings of the 1st Global Power, Energy and Communication Conference (GPECOM), Nevsehir, Turkey, 12–15 June 2019; pp. 403–407. Garces, A. A linear three-phase load flow for power distribution systems. IEEE Trans. Power Syst. 2016, 31, 827–828. [CrossRef] Yang, J.; Zhang, N.; Kang, C.; Xia, Q. A state-independent linear power flow model with accurate estimation of voltage magnitude. IEEE Trans. Power Syst. 2017, 32, 3607–3617. [CrossRef] Vita, V.; Ekonomou, L.; Christodoulou, C.A. The impact of distributed generation to the lightning protection of modern distribution lines. Energy Syst. 2016, 7, 357–364. [CrossRef] Fei, W.; Ji, G.; Sharma, D.; Jiang, J.N. A New Traveling Wave Representation for Propagation of Energy Transients in Power Lines from a Quantum Perspective. In Proceedings of the North American Power Symposium (NAPS), Fargo, ND, USA, 9–11 September 2018; pp. 1–6. Pavlatos, C.; Vita, V. Linguistic representation of power system signals. In Electricity Distribution; Springer: Berlin, Germany, 2016; pp. 285–295. Harrou, F.; Taghezouit, B.; Sun, Y. Improved k NN-Based Monitoring Schemes for Detecting Faults in PV Systems. IEEE J. Photovolt. 2019, 9, 811–821. [CrossRef] Abid, F.B.; Zgarni, S.; Braham, A. Distinct bearing faults detection in induction motor by a hybrid optimized SWPT and aiNet-DAG SVM. IEEE Trans. Energy Convers. 2018, 33, 1692–1699. [CrossRef] Pavlatos, C.; Vita, V.; Dimopoulos, A.C.; Ekonomou, L. Transmission lines’ fault detection using syntactic pattern recognition. Energy Syst. 2019, 10, 299–320. [CrossRef] Energies 2019, 12, 4333 16. 17. 18. 19. 20. 21. 22. 23. 12 of 12 Guo, M.F.; Zeng, X.D.; Chen, D.Y.; Yang, N.C. Deep-learning-based earth fault detection using continuous wavelet transform and convolutional neural network in resonant grounding distribution systems. IEEE Sens. J. 2017, 18, 1291–1300. [CrossRef] Park, J.D.; Candelaria, J.; Ma, L.; Dunn, K. DC ring-bus microgrid fault protection and identification of fault location. IEEE Trans. Power Deliv. 2013, 28, 2574–2584. [CrossRef] Vaseghi, B.; Takorabet, N.; Meibody-Tabar, F. Fault analysis and parameter identification of permanent-magnet motors by the finite-element method. IEEE Trans. Magn. 2009, 45, 3290–3295. [CrossRef] Cheng, F.; Peng, Y.; Qu, L.; Qiao, W. Current-based fault detection and identification for wind turbine drivetrain gearboxes. IEEE Trans. Ind. Appl. 2016, 53, 878–887. [CrossRef] Fei, W.; Moses, P. Modeling Power Distribution Grids through Current Tracing Method. In Proceedings of the IEEE International Conference on Smart Energy Grid Engineering (SEGE), Oshawa, ON, Canada, 12–14 August 2019; pp. 196–200. James, G.; Witten, D.; Hastie, T.; Tibshirani, R. An Introduction to Statistical Learning; Springer: Berlin, Germany, 2013; Volume 112. Zhang, Y.; Ilic, M.D.; Tonguz, O.K. Mitigating blackouts via smart relays: A machine learning approach. Proc. IEEE 2010, 99, 94–118. [CrossRef] Sammut, C.; Webb, G.I. Encyclopedia of Machine Learning and Data Mining; Springer Publishing Company, Incorporated: Berlin, Germany, 2017. © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
https://openalex.org/W3013248482	https://repository.ubn.ru.nl//bitstream/handle/2066/217635/217635.pdf	English	null	Exploring the views of successful applicants for medical school about gender medicine using a gender-sensitive video assignment	BMC medical education	2,020	cc-by	8,025	Exploring the views of successful applicants for medical school about gender medicine using a gender-sensitive video assignment Scholte, J.K.; Meulen, F.W.M. van der; Teunissen, T.A.M.; Albers, Mieke; Laan, R.F.J.M.; Fluit, C.R.M.G.; Lagro-Janssen, A.L.M. 2020, Article / Letter to editor (BMC Medical Education, 20, 1, (2020), article 25) Doi link to publisher: https://doi.org/10.1186/s12909-020-1936-9 Version of the following full text: Publisher’s version Downloaded from: https://hdl.handle.net/2066/217635 Download date: 2024-10-24 Exploring the views of successful applicants for medical school about gender medicine using a gender-sensitive video assignment Scholte, J.K.; Meulen, F.W.M. van der; Teunissen, T.A.M.; Albers, Mieke; Laan, R.F.J.M.; Fluit, C.R.M.G.; Lagro-Janssen, A.L.M. 2020, Article / Letter to editor (BMC Medical Education, 20, 1, (2020), article 25) Doi link to publisher: https://doi.org/10.1186/s12909-020-1936-9 Note: Note: To cite this publication please use the final published version (if applicable). To cite this publication please use the final published version (if applicable). Scholte et al. BMC Medical Education (2020) 20:25 https://doi.org/10.1186/s12909-020-1936-9 Open Access Abstract Background: Sex and gender influence health and disease outcomes, therefore, doctors should be able to deliver gender-sensitive care. To train gender-sensitive doctors, relevant sex and gender differences have to be included in medical education. In order to develop appealing, relevant, and effective education for undergraduate medical students, education should be tailored to students’ level and anticipated on their ideas and assumptions. Therefore, we wanted to answer the following research questions: 1. What do aspiring medical students want to learn about gender medicine?; 2. How would they like to learn about gender medicine?; and 3. What are their ideas and assumptions about sex and gender differences in health and disease? Methods: We performed an explorative thematic document analysis of educational assignments made by successful applicants (n = 50) during the selection procedure of their entry into medical school. To test aspirants’ capacity for self-directed learning, students were asked to formulate their own study plan after they watched a video that resembled a future practical experience (a consultation with a patient). As the content of this video was gender-sensitive, the assignments of the successful applicants gave us the unique opportunity to examine aspiring medical students’ views about gender medicine. Results: Aspiring medical students were eager to start their training to become gender-sensitive doctors. They believed in better care for all patients and thought doctors should obtain gender competences during their medical training. Students preferred to start with acquiring basic biomedical knowledge about differences between men and women and continue their training by developing gender-sensitive communication skills in (simulated) practical settings. Students differed in their interpretation of the gender-sensitive video, some generalized potential differences to all men and all women. Teachers were considered as important role models in learning about gender medicine. Conclusions: We advise medical schools to teach gender medicine from the beginning of medical school, by focusing on sex differences first and adding gender related themes later on in the curriculum. As students may interpret gender-sensitive information differently, structurally embedding reflection on gender medicine with gender competent teachers is necessary. Keywords: Gender medicine, Sex, Gender, Undergraduate medical education, Curriculum development, Gender Bias, Sex/gender stereotyping, Reflection * Correspondence: joni.scholte@radboudumc.nl * Correspondence: joni.scholte@radboudumc.nl © The Author(s). 2020 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. * Correspondence: joni.scholte@radboudumc.nl 1Department of Primary and Community Care, Gender & Women’s Health, Radboud University Medical Center, Post box 9101, 6500 HB Nijmegen, The Netherlands Full list of author information is available at the end of the article 1Department of Primary and Community Care, Gender & Women’s Health, Radboud University Medical Center, Post box 9101, 6500 HB Nijmegen, The Netherlands © The Author(s). 2020 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Exploring the views of successful applicants for medical school about gender medicine using a gender-sensitive video assignment Joni K. Scholte1* , Francisca W. M. van der Meulen1, Theodora A. M. Teunissen1, Mieke Albers1, Roland F. J. M. Laan2, Cornelia R. M. G. Fluit2 and Antoine L. M. Lagro-Janssen1 Background support, such as accessible educational materials, is an important facilitating factor for implementing gender into medical education [9, 14, 20, 21]. Various projects, therefore, have identified, developed, and disseminated modules and educational materials on gender medicine [9, 22]. However, gender medicine education is a rela- tively young scientific domain and to our knowledge no attention has yet been paid to the evaluation of these educational materials. Sex and gender differences in health and disease are extensively discussed in recent literature [1–4]. Sex dif- ferences in the functioning of the reproductive systems are considered in health care, however, a wider range of biological factors and social, psychosocial, and cultural factors influence the health of men and women and also need to be taken into account [5–7]. Gender medicine strives to generate, apply, and implement knowledge on sex and gender differences in medicine that is beyond reproduction. Sex differences are defined as the nature that differentiates men from women and gender differ- ences as the nurture by Oliffe & Greaves [8]. To make sure teachers give adequate and inspiring instructions, we need to understand how educational as- signments for medical students can cultivate a more gender-sensitive view and increase knowledge of gender medicine. Students enter a learning environment with conceptions about how the world works, mostly without being aware of their own ideas [23]. Values and norms in society shape students’ preconceptions about gender [24]. Although, gender may have been discussed in their earlier learning environments, as far as we know students have generally not learned to reflect on their implicit ideas. Gender-sensitive health care can be achieved if doctors apply their knowledge of gender medicine and under- stand the role of their own gender in their profession [1]. To provide the best care to both their male and fe- male patients, doctors need to know what sex and gen- der differences they should take into consideration in their practice. Subsequently, they must be able to reflect on their attitudes or stereotyped beliefs and must achieve the competences to bring gender-sensitive medi- cine into practice. Combined with persistent support from gender medicine research, the need to develop gender-sensitive curricula has become more and more widely acknowledged [6, 9, 10]. Education will be more effective if it matches students’ learning objectives and preferred learning activities. © The Author(s). 2020 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Scholte et al. BMC Medical Education (2020) 20:25 Scholte et al. BMC Medical Education (2020) 20:25 Page 2 of 9 Page 2 of 9 Background By studying the views of medical students, it is possible to cater to students’ level and anticipate on their ideas and assumptions. In this study, we focused on exploring the views of aspiring medical students about gender medicine. With these insights we aim to improve education mate- rials about gender medicine by making it more appealing and relevant for students and include instructions to re- flect on implicit ideas and assumptions. We were specific- ally interested in the opinions and ideas of medical students before they started medical school, since they were not influenced by the medical curriculum. Gender medicine is included as a milestone, i.e. competency-based development outcome, in both na- tional [11] and international competence frameworks [12], highlighting medical students’ need to gain an un- derstanding of sex and gender differences in health and illness. During their medical study, students need to be- come aware of their norms and values and when they start working in health care continue to take these into account [11]. However, sex and gender differences are currently neglected in medicine and insufficiently inte- grated into the international and national medical cur- ricula [7, 9]. To cater to the students’ level at the start of medical school, it is important to know how students approach an educational assignment on a gender-sensitive theme: what questions come up, what would they like to learn, and how would they like to approach their learning ob- jectives. We were also interested in the ideas and as- sumptions students have on sex and gender differences in general and specifically in medicine. We defined the following research questions: 1. What do aspiring med- ical students want to learn about gender medicine?; 2. How would they like to learn about gender medicine?; and 3. What are their ideas and assumptions about sex and gender differences in health and disease? Verdonk et al. (2009) reported the objectives of suc- cessful implementation of sex and gender health issues into medical curricula. For example, medical education should focus on both biomedical and socio-cultural dif- ferences between men and women; students should re- ceive education on sex and gender differences in several study years (min. 2 years); and health issues involving relevant sex and gender differences should be included, e.g. coronary heart disease, depression, pharmacother- apy, and sexual violence and abuse [13]. Methods Study design Several studies have expressed the importance of inte- grating sex and gender issues into medical education [6, 7, 10, 14–16] and have focused on incorporating gender medicine in educational training programs, learning ob- jectives, and the hidden curriculum [9, 17–19]. In estab- lishing a gender-sensitive medical curriculum, practical Study design We performed an explorative thematic document ana- lysis [25] of educational assignments made by successful applicants during the selection procedure of their entry into a Dutch medical school in 2015. This qualitative Page 3 of 9 Page 3 of 9 Scholte et al. BMC Medical Education (2020) 20:25 study design was used to explore the opinions and thoughts of future medical students. the portfolio assignment of the selection procedure and offered a perfect opportunity to study our research ques- tions. Hence, the students watched the twelve-minute video called ‘Heart and Women’ (Additional file 1, Tran- script video Heart and Women). This video showed fragments of a consultation of a general practitioner (GP) followed by a gender expert providing explanation regarding this consultation. The patient in the consult- ation is a 50-year-old woman with stress issues due to a combination of several stress factors: her husband may lose his job, she cares for her elderly mother, and she ex- pects it may partly be due to menopause. Only when questioned by the GP does it turn out that the patient suffers from tiredness, vertigo, and shortness of breath on physical exertion such as cycling or vacuum-cleaning, these are pointed out as possible symptoms of angina pectoris in female patients. The gender expert explains gender differences in communication styles, in symp- toms, and in the risk factors of angina pectoris. Setting and procedure At the Radboud university medical center (RUMC, the Netherlands), applicants for medical school were selected through a selection procedure in which applicants’ cap- acity to be successful in medical school was tested. In 2015, this procedure included two homework assignments (digital portfolio) and two exams at the faculty (Fig. 1). At the RUMC, students have to be capable to use their prac- tical experiences to partly create their own study program (self-directed learning). To test their capacity for self- directed learning, aspirants were asked to watch a video that resembled a future practical experience (a consult- ation with a patient) and afterwards formulate their own study plan (Fig. 1, step 1.2 ‘Angina pectoris video assign- ment’). This plan included the formulation of learning ob- jectives and learning activities they would like to attend if they were given 40 h (one study week). For both parts, ap- plicants were limited in their word counts. The study plans of the applicants were merely assessed by the selec- tion committee of the university on the basis of content and not on their attitudes/ideas about gender medicine. This content assessment included establishing students’ ability to formulate their questions, learning objectives, and learning activities. Participants To be able to improve educational materials, we wanted to find out how and what future medical students wanted to learn about gender medicine. Therefore, for this study, we were merely interested in the views of suc- cessful applicants of the selection procedure, as these persons would enter medical school. The assignments of the successful applicants gave us the unique opportunity to examine medical students’ views about gender medicine before their enrolment in medical education. The gender-sensitive video was com- pletely new and developed for implementation in the forthcoming years of undergraduate medical education, but had not yet been used. As said earlier, the video served as an example of a future practical experience for Overarching themes Five overarching themes emerged from the students’ as- signments. Two themes emerged from the first assign- ment concerning what questions came up and what aspiring students would like to learn: 1. Gender medicine as a self-evident part of doctor’s competence profile and 2. Eagerness to learn about gender. The next two themes emerged from the second assignment concerning how they would like to approach their learning objectives: 3. Basic biomedical knowledge first; and 4. The importance of teachers as role models. The last theme emerged from both assignments, concerning the ideas and assumptions students expressed in their assignments about sex and gender differences in health and disease: 5. Differences in interpreting gender medicine in health care. The assignments were entered into Atlas.ti7, a soft- ware program for detailed coding in qualitative data ana- lysis. We followed the analysing steps as described by Braun and Clarke [25]. This iterative process started with familiarizing with the data by reading the assign- ments and generating codes, then we searched for pat- terns by reading all the quotes that were coded, and reviewed these patterns in our data by reading the as- signments again. We ended our process by defining themes. In our analysis, we paid specific attention to how gender was reflected in the learning objectives and activities that the aspiring students conceived. Results We chose to analyse 50 of 76 assignments because we es- timated that 20–25 documents (as commonly used in qualitative research) for qualitative analysis of documents with such a limited number of words would be insufficient to reach saturation. No variation other than age and sex was known and the age of the students was uniform. As we expected that male and female students would differ in their answers, we selected all assignments of the successful male applicants (n = 19) and randomly selected 31 of 57 assignments of the successful female applicants. We de- cided to select the assignments of the female students whose family names came first alphabetically. Descriptive statistics We analysed the assignments of 50 successful applicants, consisting 31 women and 19 men. The mean age at the time of application was 18.4 years (female: 17–21 years; male 17–22 years). Data collection All applicants received an e-mail to evaluate the selec- tion procedure of the RUMC. In this e-mail, applicants were asked for permission to use their assignments as research material for our study. Of the 621 applicants who submitted their portfolio assignment, 297 applicants were admitted to medical school via the selection Fig. 1 Selection procedure of medical school Scholte et al. BMC Medical Education (2020) 20:25 Page 4 of 9 Page 4 of 9 speaker. In the results section, it is indicated whether the patterns had been brought up by a few (1–10), some (10– 25), many (25–40), most (40–49), or all (50) applicants. In this study, we applied the consolidated criteria for report- ing qualitative research (COREQ) [26]. Finally, demo- graphic data (age and sex) were analysed using SPSS version 22. procedure and were successful applicants. In total 76 successful students gave permission to use their assign- ments for our study. The response rate of successful ap- plicants was 26% (76 of 297). At time of application, students were asked for their demographic characteris- tics (age and sex). Gender medicine as a self-evident part of Doctor’s competence profile Few students mentioned that they actively want to learn by making a patient brochure, doing a re- search project, or discussing literature in group sessions. literature and national guidelines, watching videos, at- tending lectures, writing research reports, or giving oral presentations. Few students mentioned that they actively want to learn by making a patient brochure, doing a re- search project, or discussing literature in group sessions. student. She mentioned the influence her own gender might have on the doctor-patient relation. student. She mentioned the influence her own gender might have on the doctor-patient relation. How can I reach out to patients of the opposite gen- der? […] I would like to be able to take the perspec- tive of the opposite gender so that I can interpret their complaints properly. (P20, female) I will be doing a literature review with a couple of other students, and so I will be consulting medical sources and scientific papers. By talking about the subject, we improve our understanding of the con- tent. And by allocating tasks, we can go more deeply into the content. Then we will produce a written re- port, an information leaflet, and a presentation on coronary atherosclerosis for women. (P29, female) The importance of teachers as role models All students mentioned teacher-centered education, such as attending lectures given by experts and asking teachers about their professional experiences. Doctors played a pivotal role as experts not only in teaching stu- dents through their observations and lectures, but also as coaches by providing feedback, answering questions, and guiding students’ learning processes. Overall, stu- dents considered teachers as role models. The information presented in the video triggered dif- ferent responses from the students. Some students asked questions about specific female risk factors, while few others, which were all female students, extrapolated the given case to the discussion of gender duality: differ- ences may also influence treatment and health care out- comes for men. You will be watching an experienced doctor conduct- ing a consultation with a patient. You should be paying attention to how the doctor communicates with the patient and compare this with what you have learned. Afterwards, you will assess and discuss the consultation with the doctor and you will be given the opportunity to ask questions. (P39, male) As there are so many differences between men and women, I am wondering in this specific case [angina pectoris] whether the incidence is higher in women than in men, or the other way around. I now know the main risk factors for women, but there will be some for men as well, I suppose. (P13, female) Differences in interpreting gender medicine in health care Students varied in their interpretation of gender. Some stu- dents assumed that the male body could be seen as normal and the female body as a deviation from this norm. Eagerness to learn about gender After watching the video, most students stressed the im- portance of sex and gender in medicine and were in- stantly eager to learn more about this subject. A few students reported that they had never been aware of spe- cific risk factors for women or men. A few female stu- dents also mentioned that they did not know about the existence of any gender differences in communication styles, which are relevant for medical practice. They de- clared that the video had raised several questions on sex and gender differences in other issues that possibly have to be taken into consideration in patient contacts. With regard to psychosocial differences, many stu- dents focused to gain insight into communication styles and differences between men and women. They pre- ferred to develop communication skills in practice, such as internships or simulated situations with other stu- dents or actors. In order to become gender-sensitive, it appeared essential to the students to be given feedback by peers, teachers, and patients. Are there any other diseases where women show dif- ferent symptoms than men? (P20, female) I am wondering what therapies there are, what med- icines are appropriate and whether there are any differences between men and women in this area too. There might well be medicines that are not suitable for women when they are pregnant, for instance. (P8, female) Gender medicine as a self-evident part of Doctor’s competence profile The first phase of the analysis consisted of reading ten assignments. This was a random selection of the assign- ments of those students who had given permission for their assignments to be used as research material for our study. Key terms in the text were underlined and coded by inductive open coding by two researchers separately (FvdM and MA). Next, the researchers compared their code list and coded text segments. Differences in coding were discussed until consensus was reached. As a result, some codes were renamed, put together or split apart. No major disagreements emerged at this stage. A final code list was made by which all 50 assignments were coded line-by-line. Saturation was reached after analys- ing 30 assignments. However, to verify the saturation and warrant sex diversity, we decided to analyse the remaining chosen 20 assignments. All students felt that gender medicine was a self-evident topic that doctors should be able to handle in their fu- ture practice. In their eyes, a good doctor should be able to reassure both male and female patients and make them feel comfortable in the consulting room. Appar- ently, the students expressed no doubts that doctors therefore needed to have the appropriate theoretical knowledge as well as communication skills. I want to acquire appropriate communication skills to be able to help my patients properly in my subse- quent career. In these lessons, I will focus on the cor- rect way of addressing people and on learning to conduct an open conversation with both men and women. (P2, female) Next, two researchers (FvdM and CF) re-examined the codes and assignments to develop patterns deductively. These patterns were then discussed with all members of the research team (JS, FvdM, TT, MA, RL, CF, and ALJ) to construct themes. The quotations used in this study have been translated from Dutch to English by a bilingual It really matters a lot for a doctor to be aware of these [gender] differences. (P36, female) In their answers, all students focused on the patients’ gender rather than on their own gender, except for one Page 5 of 9 Page 5 of 9 Scholte et al. BMC Medical Education (2020) 20:25 literature and national guidelines, watching videos, at- tending lectures, writing research reports, or giving oral presentations. Basic biomedical knowledge first In addition, I would look up how people communi- cate and in what way women deviate from this. (P37, female) In addition, I would look up how people communi- cate and in what way women deviate from this. (P37, female) If they were given 40 h (one study week), most students preferred to gain basic biomedical knowledge of gender medicine concerning differences between men and women first and then acquire gender-sensitive commu- nication skills. Many students mentioned that they want to obtain biomedical knowledge in an educational set- ting by reading background information from scientific Where the video said that women might present atyp- ical symptoms and might present their complaints differ- ently, some students generalized these differences to all Page 6 of 9 Page 6 of 9 Page 6 of 9 Scholte et al. BMC Medical Education (2020) 20:25 men and all women. Besides, we found examples of stereotypical ideas in the students’ assignments. professionals tend to be sceptical about the importance of gender in health care [27]. Nowadays, medical students grow up in a society in which gender equality is openly discussed [29], hence they might be more open to gender- related themes than older health care professionals. This would mean resistance may fade away over time. How- ever, maybe students become less open to gender medi- cine at a higher level of medical school or when they start working. Therefore, the need to explicitly give and receive adequate feedback concerning gender issues from gender competent teachers and peers becomes even more crucial at the beginning of medical school. An international quali- tative study by Mann et al. (2011) concluded that under- graduate students perceive feedback as an essential part of their learning process [30]. men and all women. Besides, we found examples of stereotypical ideas in the students’ assignments. In this course, I would like to learn how I should com- municate with patients: that I should spend more time talking to women, for instance. (P39, male) A few students indicated that they considered gender as being part of diversity. They also wanted to learn about different age groups, ethnic groups, patients with different cultures, personalities, and educational level, and were cautious in formulating specific aims to learn about differences between men and women. Basic biomedical knowledge first Next to that I need to know about the differences in symptoms, risk factors and their impact between men and women I also need to know about differ- ences between age groups and ethnicities, so I will not be overlooking things when patients present their problems. (P49, male) The answers of the students show that they first want to focus on basic biomedical knowledge about differences be- tween men and women in an educational setting and then focus on acquiring gender-sensitive communication skills in a practical setting. This seems to be in conflict with modern medical curricula, in which real-life problems or tasks are the starting point, and learners are simultan- eously integrating knowledge, skills, and attitudes. Maybe, beginning learners are afraid of excessive cognitive load when studying in a more integrated way [31]. A few students argued that a doctor’s first priority should be the best health care tailored to each individual patient. They observed that differences between patients should indeed be taken into account, but that specific at- tention to sex was unnecessary, as this patient-centered approach would automatically include differences be- tween men and women. In other words, these students want to treat every patient as an individual taking irre- spective of sex. In our previous study, medical teachers emphasize that the timing of introducing gender issues is crucial [14]. We believe that addressing gender at the start of medical school is effective in enhancing gender awareness. In our study, students believe that teachers play a piv- otal role in learning about gender medicine and see teachers as their role models. To provide adequate in- struction and feedback, teachers should also be prepared to reflect on their own perspectives and assumptions on sex and gender. Earlier research argues that students not only learn from what is said, but also, when rethinking personal beliefs, take into account their teachers’ per- spectives on gender [28, 32]. Therefore, teachers should be able to discuss students’ implicit attitudes and stereo- typed beliefs [29, 33, 34]. Implications Another limitation is that we could not use the assignments of the successful applicants who did not give us permission as input for our research. Next to this, as the students were limited in their answers by word count, moreover, they may have left out aspects, such as the consequences of gender inequality or their By evaluating students’ questions, learning objectives, and learning activities about gender medicine, we gained knowledge of the ideas and views students have towards sex and gender upon entering medical school. Our study shows that students are eager to learn about sex and gen- der differences during medical school, but it also shows their different interpretations of gender including gender bias and stereotyping. In forthcoming research, it is inter- esting to compare the answers of the applicants with the experiences of senior clinicians or to contrast the students’ views with the results from a questionnaire to reveal exist- ing gender stereotypes (triangulation). The Nijmegen Gender Awareness in Medicine Scale (N-GAMS) can serve as a validated questionnaire for this research. Fur- thermore, based on the results of our study, conducting a study with two different groups, one watching the video including the gender sensitive knowledge, and one group without, can be of great interest in order to assess the con- tribution of the gender sensitive video. Lastly, further re- search is needed to indicate if and, if so, how students’ ideas and assumptions about gender medicine change throughout medical school. Teachers should be supported with educational mate- rials that engage their students’ interests and that facili- tate the process of their students becoming more gender-sensitive starting at the beginning of medical school. Moreover, medical teachers need to improve their gender teaching competences to be able to discuss sex and gender with students, to guide them towards gender sensitivity, and to redirect stereotyped percep- tions. Teachers could be supported to improve their competences by organizing a ‘Teach the teacher’ gender training program on their medical faculty. In this train- ing, teachers e.g. can follow an introductory e-learning and attend group meeting(s) which are guided by gender experts. This training program will help teachers to im- prove their knowledge, share their experiences with other teachers, and become aware of their attitudes re- garding sex and gender. This awareness is important, as students not only learn about sex and gender in formal medical education. Implications To our knowledge this is the first study to offer in-depth information on pupils’ knowledge of and views towards sex and gender issues before entering medical school. Examining these views from such an early stage provides interesting insights and helps to develop education that matches students’ own learning objectives and learning strategies in order to optimize learning about gender medicine. The strengths of our study is that we exam- ined medical student’s views at a very early stage before entering medical school. As in the field of gender aspects stereotypes are very common, educational recommenda- tions should not be based on the ideas derived from one perspective. To develop a gender-based curriculum the applicants’ suggestions should be combined with sugges- tions from experienced clinicians or experts in gender medicine. This study has some limitations. We explored answers to an assignment that was part of the selection procedure for medical school. This means that the aspir- ing students knew that their selection partly depended on their answers to this assignment, which may have provoked socially desirable answers about gender. Even though the gender-sensitive video assignment was only a small part of the selection procedure and the theme gen- der medicine was not specifically highlighted in the se- lection procedure, one cannot exclude social desirability bias, as applicants would not express a negative eager- ness to learn about gender medicine. One also can argue that the title of the video “Heart and Women” indicates the gender aspect of the intervention which students di- rected (and biased) to emphasize on that. In this respect it would have been better if the video had received a neutral title. However, the video was intended to serve as an example of the knowledge that is required to re- flect on this particular issue. The video provides factual knowledge and does not make any recommendations for the students’ learning objectives nor for any preferred learning strategies. In the assignment it was clearly stated that students had to make their own study plan based on the practical experiences they obtained by watching the video consult. We believe students focused on creating appropriate learning objectives and corre- sponding learning activities about gender medicine and felt that they could openly discuss their views and be- liefs. Discussion First of all, our study shows that students want to learn about sex and gender differences and that they are sur- prised about the role sex and gender play in health care. Moreover, we find that students identify themselves with their future role as doctors and think dealing with patients’ sex and gender differences is a self-evident part of their professional competence. Secondly, students prefer to learn about gender medicine by first gaining basic biomedical knowledge of gender medicine and then learn to communicate in a gender-sensitive manner by practicing with (simulation) patients. Furthermore, teachers have an important position in students’ learning activities. Thirdly, students showed different ideas and assumptions about sex and gender differences in health care including gender bias, generalization and stereotyp- ing, considering gender as part of diversity, and treating every patient as an individual. Aspiring students show different interpretations of gender in the context of health care. They make connec- tions with their assumptions about good health care, which is common for students at the novice level [35, 36]. Beginners are more likely than experts to approach problems by searching for correct explanations that fit their everyday intuitions [36]. They try to connect what they see with their prior knowledge and beliefs and values that are accepted in society. This results in a var- iety of interpretations of gender, including the idea that women are a deviation from the male norm, which is a form of gender bias [21], and the generalization of differ- ences to all men and women (stereotyping). Therefore, it is essential that a gender assignment is openly discussed, While our study shows that aspiring medical students respond with enthusiasm to gender issues in medical education, earlier studies revealed that there is consider- able resistance to gender among health care profes- sionals [7, 27, 28]. Celik et al. (2009) observed that Page 7 of 9 Page 7 of 9 Scholte et al. BMC Medical Education (2020) 20:25 Scholte et al. BMC Medical Education (2020) 20:25 to make sure students become aware of their own norms and values and take these into account when working in health care. to make sure students become aware of their own norms and values and take these into account when working in health care. knowledge of other gender-sensitive health issues. Discussion Yet, the latter limitation could also be considered a strength, as students were forced to prioritize what they thought were the most important issues. None. 18. Cheng LF, Yang HC. Learning about gender on campus: an analysis of the hidden curriculum for medical students. Med Educ. 2015;49(3):321–31. Author details 1 f ut o deta s 1Department of Primary and Community Care, Gender & Women’s Health, Radboud University Medical Center, Post box 9101, 6500 HB Nijmegen, The Netherlands. 2Radboudumc Health Academy, Research in Learning and Education, Radboud University Medical Center, Post box 9101, 6500 HB Nijmegen, The Netherlands. Acknowledgements None. 13. Verdonk P, Benschop YW, De Haes JC, Lagro-Janssen AL. Making a gender difference: case studies of gender mainstreaming in in medical education. Med Teach. 2009;30(7):e194–201. 13. Verdonk P, Benschop YW, De Haes JC, Lagro-Janssen AL. Making a gender difference: case studies of gender mainstreaming in in medical education. Med Teach. 2009;30(7):e194–201. Supplementary information 7. Lagro-Janssen T. Gender and sex: issues in medical education. Tijdschrift voor Medisch Onderwijs [Journal of Medical Education]. 2010;29(1):48–53. pp y Supplementary information accompanies this paper at https://doi.org/10. 1186/s12909-020-1936-9. pp y Supplementary information accompanies this paper at https://doi.org/10. 1186/s12909-020-1936-9. pp y Supplementary information accompanies 1186/ 12909 020 1936 9 7. Lagro Janssen T. Gender and sex: issues in medical education. Tijdschrift voor Medisch Onderwijs [Journal of Medical Education]. 2010;29(1):48–53. 8. Oliffe JL, Greaves L: Designing and conducting gender, sex, and Health Research. Thousand Oaks, California, USA: SAGE Publishing; 2012. 9. WHO: Integrating gender intro curricula for health professionals. Geneva: World Health Organization; 2006 j 8. Oliffe JL, Greaves L: Designing and conducting gender, sex, and Health Research. Thousand Oaks, California, USA: SAGE Publishing; 2012. 9. WHO: Integrating gender intro curricula for health professionals. Geneva: 8. Oliffe JL, Greaves L: Designing and conducting gender, sex, and Health Research. Thousand Oaks, California, USA: SAGE Publishing; 2012. Additional file 1. Transcript video ‘Heart and Women’. Additional file 1. Transcript video ‘Heart and Women’. 9. WHO: Integrating gender intro curricula for health professionals. Geneva: World Health Organization; 2006. 10. Hochleitner M, Nachtschatt U, Siller H. How do we get gender medicine into medical education? Health Care Women Int. 2013;34(1):3–13. Implications The so-called hidden curriculum is also an important determinant of students’ gender sensi- tivity [18, 32]. The training program should be explicitly targeted to both the female and male teachers of a med- ical faculty, as research of Risberg et al. (2003) showed that male teachers were more likely to avoid or simplify sex and gender issues and were less likely to have gender-sensitive attitudes [28]. Another possibility to Page 8 of 9 Page 8 of 9 Scholte et al. BMC Medical Education (2020) 20:25 Scholte et al. BMC Medical Education (2020) 20:25 support teachers is by endorsing existing gender net- works [37, 38], which can facilitate collaboration be- tween medical teachers on medical faculty level, on regional level, and national and international level. This collaboration can both be online via a website or appli- cations or in real-life settings (e.g. conferences for med- ical education). Teachers can share educational materials and experiences. Consent for publication All participants gave consent to publish quotes in the manuscript. All participants gave consent to publish quotes in the manuscript. Received: 13 July 2017 Accepted: 15 January 2020 Received: 13 July 2017 Accepted: 15 January 2020 Received: 13 July 2017 Accepted: 15 January 2020 Competing interests The authors declare they have no competing interests. p g The authors declare they have no competing interests. Availability of data and materials Th d d d/ l d d The data used and/or analysed during the current study are available from the corresponding author on reasonable request. 19. Erickson SS, Bachicha J, Bienstock J, Ciotti MC, Hartmann DM, Cox S, Metheny WP, Puscheck E, Krueger PM, Ernest JM 3rd. The process of translating women's health care competencies into educational objectives. Am J Obstet Gynecol. 2002;187(3 Suppl):S25–7. Abbreviations COREQ: Consolidated criteria for Reporting Qualitative research; GP: General Practitioner; N-GAMS: Nijmegen Gender Awareness in Medicine Scale; RUMC: Radboud university medical center 11. Van Herwaarden CLA, Laan RFJM, Leunissen RRM. Raamplan Artsopleiding 2009 [blueprint undergraduate medical education 2009]; 2009. 12. Milestones [https://www.acgme.org/acgmeweb/tabid/430/ ProgramandInstitutionalAccreditation/NextAccreditationSystem/Milestones.aspx]. Accessed 2 Mar 2016. 12. Milestones [https://www.acgme.org/acgmeweb/tabid/430/ ProgramandInstitutionalAccreditation/NextAccreditationSystem/Milestones.aspx]. Accessed 2 Mar 2016. References 1. Lagro-Janssen ALM. Sex, gender and health: developments in medical research. New York: Palgrave; 2010. research. New York: Palgrave; 2010. 2. Medina KL, McQueeny T, Nagel BJ, Hanson KL, Schweinsburg AD, Tapert SF. Prefrontal cortex volumes in adolescents with alcohol use disorders: unique gender effects. Alcohol Clin Exp Res. 2008;32(3):386–94. 3. Soldin OP, Mattison DR. Sex differences in pharmacokinetics and pharmacodynamics. Clin Pharmacokinet. 2009;48(3):143–57. 4. Baggio G, Corsini A, Floreani A, Giannini S, Zagonel V. Gender medicine: a task for the third millennium. Clin Chem Lab Med. 2013;51(4):713–27. 5. Doyal L. Sex, gender, and health: the need for a new approach. BMJ (Clin Res Ed). 2001;323(7320):1061–3. research. New York: Palgrave; 2010. 2. Medina KL, McQueeny T, Nagel BJ, Hanson KL, Schweinsburg AD, Tapert SF. Prefrontal cortex volumes in adolescents with alcohol use disorders: unique gender effects. Alcohol Clin Exp Res. 2008;32(3):386–94. 3. Soldin OP, Mattison DR. Sex differences in pharmacokinetics and pharmacodynamics. Clin Pharmacokinet. 2009;48(3):143–57. 4. Baggio G, Corsini A, Floreani A, Giannini S, Zagonel V. Gender medicine: a task for the third millennium. Clin Chem Lab Med. 2013;51(4):713–27. 5. Doyal L. Sex, gender, and health: the need for a new approach. BMJ (Clin Res Ed). 2001;323(7320):1061–3. 2. Medina KL, McQueeny T, Nagel BJ, Hanson KL, Schweinsburg AD, Tapert SF. Prefrontal cortex volumes in adolescents with alcohol use disorders: unique gender effects. Alcohol Clin Exp Res. 2008;32(3):386–94. 3. Soldin OP, Mattison DR. Sex differences in pharmacokinetics and pharmacodynamics. Clin Pharmacokinet. 2009;48(3):143–57. 4. Baggio G, Corsini A, Floreani A, Giannini S, Zagonel V. Gender medicine: a task for the third millennium. Clin Chem Lab Med. 2013;51(4):713–27. 6. Miller VM, Rice M, Schiebinger L, Jenkins MR, Werbinski J, Nunez A, Wood S, Viggiano TR, Shuster LT. Embedding concepts of sex and gender health differences into medical curricula. J Women’s Health. 2013;22(3):194–202. Viggiano TR, Shuster LT. Embedding concepts of sex and gender health differences into medical curricula. J Women’s Health. 2013;22(3):194–202. 7. Lagro-Janssen T. Gender and sex: issues in medical education. Tijdschrift voor Medisch Onderwijs [Journal of Medical Education]. 2010;29(1):48–53. 8. Oliffe JL, Greaves L: Designing and conducting gender, sex, and Health Research. Thousand Oaks, California, USA: SAGE Publishing; 2012. 9. WHO: Integrating gender intro curricula for health professionals. Geneva: World Health Organization; 2006. Conclusions By offering aspiring medical students an educational tool, such as a gender-sensitive video assignment, they are encouraged to gain knowledge about sex and gender differences in health care. Most students feel that gender medicine matters and are interested to learn more about it. We advise medical schools to teach gender medicine from the beginning of medical school, by focusing on sex differences first and adding gender related themes later on in the curriculum. As students may interpret gender-sensitive information differently, structurally em- bedding reflection on gender medicine with gender com- petent teachers is necessary. Authors contributions ALJ, TT, CF, and RL participated in the study design. FvdM, MA, and CF performed the data collection. JS, FvdM, CF, ALJ, and TT were involved in the data analysis and the interpretation of the data. JS and FvdM were major contributors in writing the manuscript. All authors read and approved the final manuscript. All authors agree to be personally accountable for the author’s own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. 14. Van der Meulen FWM, Fluit CRMG, Albers M, Laan RFJM, Lagro-Janssen ALM. Successfully sustaining gender medicine in undergraduate medical education: a case study. Adv Health Sci Educ. 2017. 14. Van der Meulen FWM, Fluit CRMG, Albers M, Laan RFJM, Lagro-Janssen ALM. Successfully sustaining gender medicine in undergraduate medical education: a case study. Adv Health Sci Educ. 2017. 15. Wong YL. Review paper: gender competencies in the medical curriculum: addressing gender bias in medicine. Asia Pac J Public Health. 2009;21(4): 359–76. 15. Wong YL. Review paper: gender competencies in the medical curriculum: addressing gender bias in medicine. Asia Pac J Public Health. 2009;21(4): 359–76. 16. Henrich JB. Women's health education initiatives: why have they stalled? Acad Med. 2004;79(4):283–8. 16. Henrich JB. Women's health education initiatives: why have they stalled? Acad Med. 2004;79(4):283–8. 17. Weiss LB, Levison SP. Tools for integrating women's health into medical education: clinical cases and concept mapping. Acad Med. 2000;75(11): 1081–6. 17. Weiss LB, Levison SP. Tools for integrating women's health into medical education: clinical cases and concept mapping. Acad Med. 2000;75(11): 1081–6. Ethics approval and consent to participate Maintaining gender sensitivity in the family practice: facilitators and barriers. J Eval Clin Pract. 2009;15(6):1220–5. 28. Risberg G, Johansson EE, Westman G, Hamberg K. Gender in medicine - an issue for women only? A survey of physician teachers' gender attitudes. Int J Equity Health. 2003;2(1):10. 28. Risberg G, Johansson EE, Westman G, Hamberg K. Gender in medicine - an issue for women only? A survey of physician teachers' gender attitudes. Int J Equity Health. 2003;2(1):10. 29. Andersson J, Verdonk P, Johansson EE, Lagro-Janssen T, Hamberg K. Comparing gender awareness in Dutch and Swedish first-year medical students--results from a questionaire. BMC Med Educ. 2012;12(3). https://doi. org/10.1186/1472-6920-12-3. 30. Mann K, Van der Vleuten C, Eva K, Armson H, Chesluk B, Dornan T, Holmboe E, Lockyer J, Loney E, Sargeant J. Tensions in informed self-assessment: how the desire for feedback and reticence to collect and use it can conflict. Acad Med. 2011;86(9):1120–7. 31. van Merriënboer JJG, Sluijsmans DMA. Toward a synthesis of cognitive load theory, four-component instructional design, and self-directed learning. Educ Psychol Rev. 2009;21(1):55–66. y 32. Phillips SP, Clarke M. More than an education: the hidden curriculum, professional attitudes and career choice. Med Educ. 2012;46(9):887–93. 33. Thistlethwaite JE, Ewart BR. Valuing diversity: helping medical students explore their attitudes and beliefs. Med Teach. 2003;25(3):277–81. 34. Seeleman C, Selleger V, Essink-Bot ML, Bonke B. Teaching communication with ethnic minority patients: ten recommendations. Med Teach. 2011; 33(10):814–9. 34. Seeleman C, Selleger V, Essink-Bot ML, Bonke B. Teaching communication with ethnic minority patients: ten recommendations. Med Teach. 2011; 33(10):814–9. 35. Daley BJ. Novice to expert: an exploration of how professionals learn. Adult Educ Quart. 1999;49(4):133–47. 35. Daley BJ. Novice to expert: an exploration of how professionals learn. Adult Educ Quart. 1999;49(4):133–47. 36. Bransford JD, Brown AL, Cocking RR. How people learn. Brain, mind, experience, and school. Washington DC: National Academy Press; 2000. 36. Bransford JD, Brown AL, Cocking RR. How people learn. Brain, mind, experience, and school. Washington DC: National Academy Press; 2000. 37. EUGIM European curriculum in Gender Medicine [ https://gender.charite.de/ en/research/research_group_cvd/projects_with_the_eu/eugim/]. Accessed 2 Oct 2017. 38. Institute of Gender and Health [http://www.cihr-irsc-igh-isfh.ca/]. Accessed 2 Oct 2017. 38. Institute of Gender and Health [http://www.cihr-irsc-igh-isfh.ca/]. Accessed 2 Oct 2017. Ethics approval and consent to participate 20. Verdonk P, Mans LJ, Lagro-Janssen AL. Integrating gender into a basic medical curriculum. Med Educ. 2005;39(11):1118–25. The study protocol was approved by the Ethical Review Board of the Netherlands Association for Medical Education (NVMO-ERB). The Board decided that the study was carried out in accordance with the rules pertaining to the review of research ethics committees and informed consent (NERB-file number 539, 8-7-2015). The authors confirm that all personal identifiers were removed or disguised so that the student(s) described are not identifiable and cannot be identified through story details. 21. Verdonk P, Benschop YW, de Haes HC, Lagro-Janssen ALM. From gender bias to gender awareness in medical education. Adv Health Sci Educ Theory Pract. 2009;14(1):135–52. 22. Mans LJL, Verdonk P, Lagro-Janssen ALM. De rol van het Digitaal Kenniscentrum Seksespecifiek Medisch Onderwijs bij de integratie van sekse in het medisch 22. Mans LJL, Verdonk P, Lagro-Janssen ALM. De rol van het Digitaal Kenniscentrum Seksespecifiek Medisch Onderwijs bij de integratie van sekse in het medisch Page 9 of 9 Scholte et al. BMC Medical Education (2020) 20:25 Scholte et al. BMC Medical Education (2020) 20:25 onderwijs [the role of the digital knowledge Centre on gender specific medical education in the integration of gender in medical education]. Tijdschrift voor Medisch Onderwijs [Journal of Medical Education]. 2006;25(2):66–74. onderwijs [the role of the digital knowledge Centre on gender specific medical education in the integration of gender in medical education]. Tijdschrift voor Medisch Onderwijs [Journal of Medical Education]. 2006;25(2):66–74. onderwijs [the role of the digital knowledge Centre on gender specific medical education in the integration of gender in medical education]. Tijdschrift voor Medisch Onderwijs [Journal of Medical Education]. 2006;25(2):66–74. nderwijs [the role of the digital knowledge Centre on gender specific medica 23. Bolhuis SM. Leren en veranderen. Emotie, gedrag en denken. [learning and changing. Emotions, behaviour and thinking]. Coutinho: Bussum; 2016. 24. Wingrave M. Perceptions of gender in early years. Gend Educ. 2016:1–20. 25. Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77–101. 26. Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care. 2007;19(6):349–57. 27. Celik H, Lagro-Janssen ALM, Klinge I, Tvd W, Widdershoven G. Maintaining gender sensitivity in the family practice: facilitators and barriers. J Eval Clin Pract. 2009;15(6):1220–5. 27. Celik H, Lagro-Janssen ALM, Klinge I, Tvd W, Widdershoven G. Scholte et al. BMC Medical Education (2020) 20:25 Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
https://openalex.org/W2094142833	https://eejournal.ktu.lt/index.php/elt/article/download/8027/4033	English	null	An Improved Risk Assessment Method for SCADA Information Security	Elektronika ir elektrotechnika	2,014	cc-by	3,570	ELEKTRONIKA IR ELEKTROTECHNIKA, ISSN 1392-1215, VOL. 20, NO. 7, 2014 ELEKTRONIKA IR ELEKTROTECHNIKA, ISSN 1392-1215, VOL. 20, NO. 7, 2014 http://dx.doi.org/10.5755/j01.eee.20.7.8027 Manuscript received January 21, 2014; accepted May 26, 2014. This research was funded by a grant (No. TR 32025) from the Ministry of Education, Science and Technological Development of Serbia. J. D. Markovic-Petrovic1, M. D. Stojanovic2 1CE Djerdap Hydroelectric Power Plants Ltd., HPP Djerdap 2, Kraljevica Marka 2, 19300 Negotin, Serbia 2University of Belgrade, Faculty of Transport and Traffic Engineering, Vojvode Stepe 305, 11000 Belgrade, Serbia jasna.markovic@djerdap.rs meet high standards in terms of reliability, availability and transfer of correct and timely information for the purposes of production planning, efficient utilization of the energy potential, remote management in production, transmission and distribution areas, reporting and successful business management of the system in general. From the remote management aspect, measuring, control and management of the electric energy production in hydroelectric power plants, SCADA has a central role. Fig. 1 shows a block diagram of SCADA implementation based on stand-alone concepts. Such concepts enable the highest reliability level of the production cycle because in the instance of an outage of any of the production-transfer units, generator-transformer, other areas and all other production-transfer units remain in the production cycle undeterred. The ICT structure of such units is enjoined into one synergy at the level of SCADA systems. 1Abstract—In this paper, we address information security risk analysis in SCADA systems and propose an improved security risk assessment method in the case of attacks on the SCADA information and communication infrastructure. The assumption is that intrusion prevention/detection systems are implemented as security mechanisms. The proposed method has been demonstrated on an example of the SCADA system in a hydropower plant. Cost-benefit analysis has been performed on the basis of the Return on Security Investment. Index Terms—Cyber-attack, information security, return on security investment, risk assessment, SCADA. An Improved Risk Assessment Method for SCADA Information Security J. D. Markovic-Petrovic1, M. D. Stojanovic2 1CE Djerdap Hydroelectric Power Plants Ltd., HPP Djerdap 2, Kraljevica Marka 2, 19300 Negotin, Serbia 2University of Belgrade, Faculty of Transport and Traffic Engineering, Vojvode Stepe 305, 11000 Belgrade, Serbia jasna.markovic@djerdap.rs J. D. Markovic-Petrovic1, M. D. Stojanovic2 1CE Djerdap Hydroelectric Power Plants Ltd., HPP Djerdap 2, Kraljevica Marka 2, 19300 Negotin, Serbia 2University of Belgrade, Faculty of Transport and Traffic Engineering, Vojvode Stepe 305, 11000 Belgrade, Serbia jasna.markovic@djerdap.rs ELEKTRONIKA IR ELEKTROTECHNIKA, ISSN 1392-1215, VOL. 20, NO. 7, 2014 ELEKTRONIKA IR ELEKTROTECHNIKA, ISSN 1392-1215, VOL. 20, NO. 7, 2014 and vulnerabilities that malicious users are familiar with. Information Security Risk Analysis Method (ISRAM) [7] is a quantitative method that allows effective participation of managers and staff into the process. Structured in seven steps, ISRAM provides a guideline for risk assessment that considers the probability of occurrence as well as the consequences of occurrence of security breaches. A risk management framework using Bayesian networks has been proposed in [8], with the objective to determine the network compromise probability under different levels of attack. Iheagwara [9] represents a model that introduces the Cascading Threat Multiplier (CTM), multiplying factor that will be included into expanded definition of Single Loss Expectancy (SLE). CTM is somewhat subjective and is introduced mainly for the purpose to think in broader terms and look at the bigger picture when considering the risks associated to the compromise of a given asset. In the method proposed by Suh and Han [10] the significance of various business functions of the business model and the necessity of various IS assets are determined. Considering that the available risk assessment methods and tools are expensive and designed for large enterprises, a simplified risk assessment algorithm that is tailored for the small and medium enterprises has been proposed in [5]. It is particularly difficult to detect and prevent distributed attacks where several attackers simultaneously attack a target (i.e. a vital network server). This type of an attack is known as distributed Denial of Service (DDoS) and can be launched at any layer of the protocol stack. Research shows that such attacks on industrial control systems are quite frequent and may have severe consequences [3], [4]. Design of security system assumes a detailed risk analysis, which should be periodically repeated (in parts or entirely) during system exploitation and upgrade. The main objective of this work is to propose a risk assessment method suitable for industrial SCADA systems that will allow the determination of the optimum level of security investment and definition of different levels of acceptable risk. II. INFORMATION SECURITY RISK MANAGEMENT The sum of system vulnerabilities, threats to the system and impacts makes up the risk. Risk is a function of the probability that a particular source of threat will use a potential vulnerability, resulting in detrimental and unwanted impact on the business. In order to undertake risk analysis, the following factors must be recognized, assessed and defined: (1) asset; (2) vulnerability; (2) threat; (4) impact and (5) controls. Although quantitative approaches enable precise risk assessment, methods which propose expressing ICT resources value only by their book value are inadequate for SCADA systems. Security risk assessment in such systems assumes definition of risk metrics based on the probability of attacks occurrence and their impact to the continuity and performance of the industrial process [11], [12]. Loss assessment pertaining to a realized risk is complex and there is no reliable methodology to enable forecasting loss with high precision. For better results, more parameters should be included in the analysis. The main novelty of this work is the proposal of an improved risk assessment method, which calculates loss expectancy taking into account the impact of attack strength to SCADA system’s performance and the set of different conditions that may increase indirect losses. There are no risk-free systems, and the costs of such a solution would surpass the asset value to be protected or the value of the losses caused by the risk. Therefore, the focus is directed from avoiding to managing the risk, with pre- defining the acceptable risk level. Risk management includes several steps: (1) identification of the system and system components; (2) identification of asset and its value; (3) establishing of the security objectives; (4) risk analysis through identification of vulnerabilities and threats; (5) risk assessment; (6) making decisions on acceptable risk; (7) selection and implementation of measures to decrease the level of risk. Risk management is a continuing process and all steps are cyclically repeated in order to improve the security system and decrease the level of risk. I. INTRODUCTION Evolution of the Supervisory Control and Data Acquisition (SCADA) systems has in the previous decade created a substantial problem pertaining to their security. Reasons for their vulnerabilities to different forms of cyber- attacks include the following: (1) implementation of open communication standards, (2) connectivity of the control systems with other networks, (3) limitations in the existing security technologies, (4) remote access, and (5) availability of technical information on control systems. Because the security of SCADA systems is of high importance due to their indispensable role in the industry, this is a current field of research with the expectation of specific solutions for security and information security risk management. Fig. 1. An example of SCADA system in a hydroelectric power plant. A secure ICT system should, in general, provide the following, by order of priority: confidentiality, integrity and availability. Industrial remote monitoring and control systems have the same security requirements, however in a reversed order. The pathway towards the fulfilment of the security requirements dictates the adoption of a security policy that clearly defines regulations, business process protocols, staff roles, permissible activities, actions and processes [1], [2]. Regulations define methods for protecting the integrity of the information, determine the confidentiality of information, data availability, as well as the access control of resources and applications. . 1. An example of SCADA system in a hydroelectric power plan Modern telecommunication systems supporting SCADA rely on the Internet protocol (IP) and Ethernet technologies. SCADA-specific protocols are being developed at the application layer (including data models and presentation) and use the IP protocol stack. SCADA systems are typically integrated into a common IP-based network, together with the other operational and corporate telecommunication services. Networks thus designed have certain weaknesses ICT systems in the electric power utilities are required to 69 III. THE PROPOSED SCADA RISK ASSESSMENT METHOD In discussing ICT security, risk pertaining to a particular resource is assessed on the basis of the asset value, resource vulnerabilities, threats that might abuse those vulnerabilities, probability that the threat will be realized and impact caused if the threat is realized [5]. Risk management includes identification, selection and implementation of controls that will decrease the assessed risk to the acceptable level. The objective of investing in ICT security is increasing the security of information assets from all types of threats. Investments in ICT security can be financially represented, which is not the case with their benefits in terms of decreased potential losses. The questions that need to be answered are: (1) when is a system secure enough and (2) what is the price of such a protection, because a greater investment in security does not necessarily ensure a higher level of security. The most important part of the risk management process is risk assessment, which is also the area most susceptible to errors. Literature lists different approaches, methods and tools for the information security risk assessment. Qualitative assessment proposes methods that interpret loss as a subjective measure, i.e. risk level is assessed as low, middle or high. Quantitative assessment is based on a mathematical approach (numerical analysis, statistical methods) that interprets risk in numerical values of appropriate units. These can include economic values such as the expected annual loss, investment return, etc. A comparative analysis of the different approaches to risk assessment can be found in [6]. An expected result of the information security risk management process is a quantitative value assigned to each risk that can be used for ranking all risks, complete with defining of critical levels and priorities, measures to ensure feasibility of investing in security and preparations for unexpected costs. Traditional risk assessment assumes calculation of the SLE as a function of two variables: Asset Value (AV) and Exposure Factor (EF). Variable EF denotes the ratio of lost assets in a particular incident. On the basis of Annual Rate 70 of Occurrence (ARO) the value of the An ELEKTRONIKA IR ELEKTROTECHNIKA, ISSN 1392-1215, VOL. 20, NO. 7, 2014 of Occurrence (ARO) the value of the Annual Loss Expectancy (ALE) can be determined, as follows to carry out the analysis of historical data in order to obtain statistical values. Second, the probability of the attack(s) occurrence should be determined. IV. CASE STUDY We observe a run-off-river hydropower plant with the total installed power of 270 MW. The assumption is that two Network IDS/IPS are installed, the first towards the corporate network, the second towards the process network, and one Host IDS per each key server (Fig. 3). Fig. 3. Architecture of SCADA network in hydroelectric power plant. S I M / . 1 i Y C C C Y i             (3) (3) Costs caused by attacks can be divided into: (1) direct, that come as a consequence of the disruption of the production process, and (2) indirect, that include system recovery costs and numerous additional costs, i.e. penalties for failing to meet obligations, irrecoverable loss in natural resources, damage to the environment, etc. To determine the costs created as a consequence of a realized attack, the basic ALE formula is used whereby the sum of all maximum direct losses (DL) during an attack is multiplied by the number of potential attacks during a year. The formula is then modified by the weighting factors that quantify indirect costs (W) and weighting factor WA which role is to scale the proposed maximum direct losses as a function of strength of attack. In general, the assumption is that there are M types of direct losses and N different conditions that can contribute to indirect losses. This way we obtain the following expression for the ALE ig. 3. Architecture of SCADA network in hydroelectric power pl In this scenario, the direct loss is caused by the outage in the electric energy production which can come as a consequence of the outage of the production unit, if the target of the attack was the controller of the aggregate block, or as a consequence of failure in power regulation due to the outage of the remote management system. The above costs correspond with the duration of the attack (tA), time required for system recovery, installed power of the plant (P) and unit price of electric energy (cE). The recovery time is stipulated to be proportionate to the WA weighting factor with the recovery time after a maximum strength attack (tRmax). Consequences of the attack can be classified into several groups, i.e.: (1) control disabled without impact on the management; (2) control and management from the remote A ( ) . III. THE PROPOSED SCADA RISK ASSESSMENT METHOD Relying on those results, the attacks' effects on the overall costs (direct and indirect) should be predicted. Finally, in order to measure the attacks' impact on the performance, it is desirable that a company defines its key performance indicators (KPIs). KPIs are defined according to company’s key performance objectives (productivity, availability, reliability, security, network outage impact reduction, integrity, downtime, etc.) that should support fulfilment of business objectives [15]. (1) . ALE SLE ARO AV EF ARO      The indicator of cost effectiveness of investing in ICT security is Return on Security Investment (ROSI), calculated as investment return ratio within the stipulated period and represents the balance of ALE reduced by the ratio of prevented attacks and capital invested in security mechanisms (CS) [13], i.e. Figure 2 illustrates the calculation defined by (4).   S S % / . ROSI ALE RiskMitigated C C    (2) (2) Fig. 2. The factors of Annual Loss Expectancy in SCADA system. We further propose a modification of the traditional method for risk assessment in calculating the efficiency of the Intrusion Detection System (IDS) and Intrusion Prevention System (IPS) for protection against a particular class of attacks (e.g., DDoS) on the infrastructure of the SCADA systems. SCADA systems use specific IDS/IPS equipment due to dedicated application layer protocols [12], [14]. To calculate ROSI, it is necessary to estimate the value of the investment in security mechanisms, costs created by occurred attacks and the ratio of prevented attacks. Fig. 2. The factors of Annual Loss Expectancy in SCADA system. Investing in a security system can incorporate a single investment into the implementation of a security system (CI) and annual maintenance that includes system updates and technical support (CM). Because the initial investment is substantial, an average costing over a number of years (Y) needs to be factored, beginning with the first year of the implementation of security, as follows REFERENCES TABLE I. WEIGHTING FACTORS. Impact Very low Low Medium High Very high WA Probability 40 % 25 % 20 % 10 % 5 % Value 0.01 0.2 0.25 0.5 1 WE Probability 5 % 20 % 50 % 20 % 5 % Value 1 2 3 4 5 WH Probability 0 % 50 % 35 % 15 % 0 % Value n.a. 1 1.5 2 n.a. [1] CIGRÉ Technical Brochure TB 317: “Security for Information Systems and Intranets in Electric Power Systems”, JWGD2/B2/C2.01, 2007. [2] CIGRÉ Technical Brochure TB 419: “Treatment of Information Security for Electric Power Utilities (EPUs)”, WGD2.22, June, 2010. [3] Ponemon Institute: “Cyber Security on the Offense: A Study of IT Security Experts”, November 2012. [4] J. Markovic–Petrovic, M. Stojanovic, “Analysis of SCADA System Vulnerabilities to DDoS Attacks”, in Proc. of the 11th Int. Conf. TELSIKS 2013, Nis, Serbia, 2013, vol. 2, pp. 591–594. Literature [9] stipulates that the probability of detected attacks on the IDS systems falls within the 61.5 % to 86.2 % band. In SCADA systems the intensity of traffic does not show substantial variation, which increases the probability of detection / prevention of attacks (the example proposes the value of 90 %). According to the research [3] the highest probability of downtime caused, for example, DDoS attacks is 30 minutes. The maximum recovery time is stipulated to be 120 minutes. The ROSI value depends on the predicted number of attacks on the annul level. In the provided example (Fig. 4) a positive value is achieved if ARO 3. The same graph shows the correlation of ROSI with the weighting factor WA, which varies depending on the defined probability function. [5] S. Japertas, G. Cincikas, R. Sestaviskas, “Company’s Information and Telecommunication Networks Security Risk Assessment Algorithm”, Elektronika ir Elektrotechnika, no. 5, pp. 33–36, 2012. [6] T. Tsiakis, “Information Security Expenditures: a Techno-Economic Analysis”, Int. Journal of Computer Science and Network Security, vol. 10, no. 4, pp. 7–11, 2010. [7] B. Karabacak, I. Sogukpinar, “ISRAM: information security risk analysis method”, Computers & Security, vol. 24, no. 2, pp. 147–159, 2005. [Online]. Available: http://dx.doi.org/10.1016/j.cose. 2004.07.004 [8] N. Poolsappasit, R. Dewri, I. Ray, “Dynamic Security Risk Management Using Bayesian Attack Graphs”, IEEE Trans. Dependable and Secure Computing, vol. 9, no. 1, pp. 61–74, 2012. [Online]. Available: http://dx.doi.org/10.1109/TDSC.2011.34 [9] C. Iheagwara, A. Blyth, M. Singhal, “Cost effective management frameworks for intrusion detection systems”, Journal of Computer Security, vol. ELEKTRONIKA IR ELEKTROTECHNIKA, ISSN 1392-1215, VOL. 20, NO. 7, 2014 ELEKTRONIKA IR ELEKTROTECHNIKA, ISSN 1392-1215, VOL. 20, NO. 7, 2014 control centre disabled without impact on the local management and production; (3) control and management from the remote and local control centres disabled without production outage; (4) all control and management systems outage with minor impact on the production process; (5) all control and management systems outage with major impact on the production process. An example for the indirect costs would be the penalties paid for not delivering contracted energy (WE) and losses created by the evacuation of excess hydro-potential (WH), if the attack occurred during a period of high inflow, i.e. systems in the industrial systems and the consequences that a denial of remote management service will have on the society (the graph shows a definition of threshold 1 that accepts the investment for the predicted number of 2 attacks per year, notwithstanding the negative value of ROSI). V. CONCLUSIONS The paper proposes and investigates an improved method for information security risk assessment, which is suitable for industrial SCADA systems. The method introduces weighting factors that quantify losses in accordance with the attack conditions and its strength. We also discuss the prerequisites for determining the values of weighting factors, according to company-specific needs. The case study refers to security risk assessment of the SCADA system in a hydropower plant. Applying the proposed method in a real system enables the assessment of potential loss expenses and cost-benefit analysis of the stipulated security mechanism. Establishment of a predefined threshold for ROSI should contribute to determining the optimal level of investment in security. (5) A E H A A Rmax E ( ) . ALE W W W P t W t c ARO    (5) An attack can occur at any time of day or year and it is difficult to forecast potential effects. However, it is possible to assess the impact on the costs if an outage in the remote management system caused overflow of excess water. An example pertaining to the defining of weighting factors is provided in Table I. On the basis of thus defined probability functions for weighting factors, expected annual loss can be determined. IV. CASE STUDY 1 1 i j N M ALE W W DL ARO j i       (4) (4) Selection of weighting factors might be a delicate process, which depends on a number of techno-economic conditions and is, certainly, company-specific. The first prerequisite is 71 REFERENCES 12, no. 5, pp. 777–798, 2004. [10] B. Suh, I. Han, “The IS risk analysis based on a business model”, Information & Management, vol. 41, pp. 149–158, 2003. [Online]. Available: http://dx.doi.org/10.1016/S0378-7206(03)00044-2 Fig. 4. ROSI as a function of: a) ARO (WA def. Table I), b) WA (ARO = 1). ig. 4. ROSI as a function of: a) ARO (WA def. Table I), b) WA (ARO = 1). [11] S. Papa, W. Casper, S. Nair, “Availability-based risk analysis for SCADA embedded computer systems”, Proc. World Congress in Computer Science, Computer Engineering and Applied Computing, pp. 541–547, 2011. [12] G. Dondossola, F. Garrone, J. Szanto, “Cyber Risk Assessment of Power Control Systems - A Metrics weighed by Attack Experiments”, IEEE Power and Energy Society General Meeting, pp. 1-9, San Diego, CA, 2011. g [13] W. Sonnenreich, J. Albanese, B. Stout, “Return on Security Investment (ROSI) - A Practical Quantitative Model”, Journal of Research and Practice in Information Technology, vol. 38, no. 1, pp. 45-56, 2006. Fig. 4. ROSI as a function of: a) ARO (WA def. Table I), b) WA (ARO = 1). pp [14] B. Zhu, S. Shankar, “SCADA-specific Intrusion Detection/Prevention Systems: A Survey and Taxonomy”, in Proc. of the 1st Workshop on Secure Control Systems (SCS), 2010. In making decisions regarding the cost effectiveness of investing in security mechanisms it is important to set a threshold which considers the importance of SCADA [15] ITU-T Recommendation E.419: “Business oriented key performance indicators for management of networks and services”, 2006. 72
https://openalex.org/W4319037888	https://pure.iiasa.ac.at/id/eprint/18602/1/fclim-05-946712.pdf	English	null	Gender equality and climate change mitigation: Are women a secret weapon?	Frontiers in climate	2,023	cc-by	14,343	OPEN ACCESS OPEN ACCESS EDITED BY Monirul Mirza, Environment and Climate Change Canada, Canada REVIEWED BY Susan Buckingham, Independent Researcher, Cambridge, United Kingdom Marielle Feenstra, Delft University of Technology, Netherlands CORRESPONDENCE Mathilde Rainard pt15mr@leeds.ac.uk SPECIALTY SECTION This article was submitted to Climate and Decision Making, a section of the journal Frontiers in Climate RECEIVED 17 May 2022 ACCEPTED 12 January 2023 PUBLISHED 02 February 2023 CITATION Rainard M, Smith CJ and Pachauri S (2023) Gender equality and climate change mitigation: Are women a secret weapon? Front. Clim. 5:946712. doi: 10.3389/fclim.2023.946712 OPEN ACCESS EDITED BY Monirul Mirza, Environment and Climate Change Canada, Canada REVIEWED BY Susan Buckingham, Independent Researcher, Cambridge, United Kingdom Marielle Feenstra, Delft University of Technology, Netherlands CORRESPONDENCE Mathilde Rainard pt15mr@leeds.ac.uk SPECIALTY SECTION This article was submitted to Climate and Decision Making, a section of the journal Frontiers in Climate RECEIVED 17 May 2022 ACCEPTED 12 January 2023 PUBLISHED 02 February 2023 CITATION Rainard M, Smith CJ and Pachauri S (2023) Gender equality and climate change mitigation: Are women a secret weapon? Front. Clim. 5:946712. doi: 10.3389/fclim.2023.946712 OPEN ACCESS EDITED BY Monirul Mirza, Environment and Climate Change Canada, Canada REVIEWED BY Susan Buckingham, Independent Researcher, Cambridge, United Kingdom Marielle Feenstra, Delft University of Technology, Netherlands CORRESPONDENCE Mathilde Rainard pt15mr@leeds.ac.uk SPECIALTY SECTION This article was submitted to Climate and Decision Making, a section of the journal Frontiers in Climate RECEIVED 17 May 2022 ACCEPTED 12 January 2023 PUBLISHED 02 February 2023 CITATION Rainard M, Smith CJ and Pachauri S (2023) Gender equality and climate change mitigation: Are women a secret weapon? Front. Clim. 5:946712. doi: 10.3389/fclim.2023.946712 Mathilde Rainard1, Christopher J. Smith1,2 and Shonali Pachauri2 1School of Earth and Environment, University of Leeds, Leeds, United Kingdom, 2Energy, Climate and Environment Program, International Institute for Applied Systems Analysis, Laxenburg, Austria Mathilde Rainard1, Christopher J. Smith1,2 and Shonali Pachauri2 Mathilde Rainard1, Christopher J. Smith1,2 and Shonali Pachauri2 1School of Earth and Environment, University of Leeds, Leeds, United Kingdom, 2Energy, Climate and Environment Program, International Institute for Applied Systems Analysis, Laxenburg, Austria 1School of Earth and Environment, University of Leeds, Leeds, United Kingdom, 2Energy, Climate and Environment Program, International Institute for Applied Systems Analysis, Laxenburg, Austria An orthodox assumption frames gender equality as a panacea to the climate crisis, whereby empowering women is assumed to have tremendous positive efects on countries’ environmental performances. TYPE Original Research PUBLISHED 02 February 2023 DOI 10.3389/fclim.2023.946712 TYPE Original Research PUBLISHED 02 February 2023 DOI 10.3389/fclim.2023.946712 climate change mitigation action, gender mainstreaming, equality, ecofeminism, Sustainable Development Goal (SDG) 13, gender equality OPEN ACCESS However, the gender-climate nexus literature often disregards feminist epistemology, detrimentally integrating harmful gendered assumptions within its analyses, and therefore policy recommendations. To remedy this, links between gender equality and climate change mitigation action were investigated, through a mixed-method approach, which includes feminist theories. Two metrics of gender equity, the Global Gender Gap Index and the Gender Inequality Index, and their correlations to a sustainability metric, the Environmental Performance Index, were analyzed. This quantitative analysis was enriched by 13 interviews with gender-climate experts. Results showed that, despite statistically signiﬁcant correlations between both gender equality indices and the Environmental Performance Index, the positive relationship between gender equality and environmental performances is contextual and multi-faceted. Disregarding situated gender constructs, understanding gender as binary, and positing women as a homogeneous group, all mask multiple interactions between gender equality and climate change mitigation. Unveiling these interactions necessitates better integration of radical gender theories within climate change science through interdisciplinary research, permitting epistemological pluralism. To further this, a methodological framework is proposed, to help guide environmental researchers willing to consider gender in their work. Furthermore, the impact of gender mainstreaming within climate policies is explored, presenting subsequent policy recommendations. Finally, ﬁndings and the systemic transformation potential of gender equality, amongst other forms of equality, are discussed, reinforcing the idea that there is no climate justice without gender justice, and that justice and equality are cornerstones of sustainable societies. COPYRIGHT © 2023 Rainard, Smith and Pachauri. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which 1. Introduction On the other hand, within the climate change mitigation literature, transformation and gender have also garnered attention, notably amongst advocates of radical and systemic approaches to mitigate GHG emissions (Shove, 2010; Koch, 2013, 2020; Raworth, 2017). However, when links between gender equality and climate action are appraised, the concept of transformation is often absent, and feminist epistemology considered within adaptation is substituted by quantitative analysis of sex-disaggregated data through cross-country regression analysis, concluding gender equality would foster climate change mitigation action (see Ergas and York, 2012; Mavisakalyan and Tarverdi, 2019; McGee et al., 2020). The reality is more complex, as understanding women as a homogenous group masks the contextual implications of increased gender equality on climate change mitigation action (Knight and Givens, 2021; Lau et al., 2021). Gender has mainstreamed in climate change science, following the process of gender mainstreaming established by the 1995 Beijing Platform and Declaration, which highlighted 12 key socioeconomic areas needing urgent action to ensure equal opportunities between men and women (UNWOMEN, 2021). Gender mainstreaming is the process of incorporating a gender lens to any political response to limit perpetuation of gender inequalities through institutional means (Alston, 2014). Beneﬁcial to a certain extent (Resurrección, 2013), gender mainstreaming has resulted in a dilution of radical gender and feminist theories explaining its marginal impact in practice (Prügl, 2010; Wittman, 2010). Moreover, the hegemonic positivist epistemology in climate change adaptation limits the integration of qualitative and feminist methods (Thompson-Hall et al., 2016; Lau et al., 2021). Thus, paradoxically, many researchers study gender without engaging with feminist epistemology resulting in the spread of harmful gendered assumptions in climate policy responses, like perceiving women as innately connected to nature or gender equality as solely a women’s issue (Lau et al., 2021). We call for more research that integrates feminist epistemology into climate change mitigation. This paper contributes to this call by utilizing a pragmatic research paradigm and mixed-methods approach through a critical ecofeminist lens (Plumwood, 1997, 2002; Gaard, 2017). We deﬁne gender equality as equality of treatments and opportunities between individuals of diﬀerent gender, where gender is considered as a social construct per Beauvoir (1949), recognizing that gender is not a binary construct (Butler, 1988). Critical ecofeminism was chosen for a framing because it goes beyond classic ecofeminist theories (Badoux, 1974; Merchant, 1980, 1981) and avoids essentializing women’s relation to nature. 1. Introduction while gender-sensitive policies disparately cater to males and females without addressing the causes behind diﬀering gendered experiences (Resurrección et al., 2019). The gender-transformative approach is not solely aimed at women, rather the concept is holistic and intersectional (Resurrección et al., 2019). Generally, the notion of transformation arising from adaptation research transcends the climate change adaptation/mitigation dualism to tackle the climate crisis holistically (O’Brien, 2012; Resurrección et al., 2019). Nevertheless, progress is non-linear with mostly gender-sensitive approaches being used in practice (Bee et al., 2013; Resurrección et al., 2019). while gender-sensitive policies disparately cater to males and females without addressing the causes behind diﬀering gendered experiences (Resurrección et al., 2019). The gender-transformative approach is not solely aimed at women, rather the concept is holistic and intersectional (Resurrección et al., 2019). Generally, the notion of transformation arising from adaptation research transcends the climate change adaptation/mitigation dualism to tackle the climate crisis holistically (O’Brien, 2012; Resurrección et al., 2019). Nevertheless, progress is non-linear with mostly gender-sensitive approaches being used in practice (Bee et al., 2013; Resurrección et al., 2019). Climate change is the biggest challenge faced by humanity (Anderson et al., 2014; Steﬀen et al., 2015; Pearse, 2017; MacGregor, 2021; IPCC, 2022). Climate change is commonly understood as a “wicked” problem meaning it deﬁes conventional solutions and cannot be solved by the same means that helped create it (FitzGibbon and Mensah, 2012; Carter, 2018). Solutions to climate change are often categorized as either climate change adaptation or climate change mitigation (IPCC, 2022). The impacts of climate change are unequally distributed throughout the world, therefore, adaptation studies are most focused in developing countries (Pielke et al., 2007; Global Gender and Climate Alliance, 2016) whilst developed countries must urgently mitigate greenhouse gas (GHG) emissions through innovative policies and systemic changes (Anderson et al., 2014; Creutzig et al., 2018; IPCC, 2022). In this context, a growing body of literature centered upon the gender-climate nexus explores links between achieving gender equality and increasing individuals’ resilience to a changing climate or enhancing climate change mitigation action (MacGregor, 2010; Global Gender and Climate Alliance, 2016; Andrijevic et al., 2020; McGee et al., 2020). The gender-climate nexus highlights how solutions and causes to climate change are not gender neutral (MacGregor, 2010, 2014; Nightingale, 2017; Pearse, 2017). Highlights - A mixed-methods approach is used to explore the role of gender in mitigation. - Correlations between gender equity and sustainability were explored with 13 gender experts. g - Lack of feminist theories in climate science leads to maladaptive policies. - Interdisciplinary research is needed to implement gender-transformative policies. - A suggested project design framework is provided to support future research. Frontiers in Climate Frontiers in Climate frontiersin.org frontiersin.org 01 10.3389/fclim.2023.946712 10.3389/fclim.2023.946712 Rainard et al. Frontiers in Climate frontiersin.org Rainard et al. 1. Introduction 10.3389/fclim.2023.946712 Gender-climate related deﬁnitions Gender mainstreaming The process of incorporating a gender lens within all political responses to ensure gender inequalities are not perpetuated through institutional means Gender-sensitive policies Policies that cater diﬀerently to males and females acknowledging gender inequalities embedded in climatic impacts but do not address the root causes of inequalities Gender-responsive policies Right-based policy responses to gendered climatic impacts to address part of the root causes behind gender inequalities Gender-transformative policies Policy responses that systematically address root causes of inequalities beyond just gender to consider multiple social factors at play in gendered climatic impacts However, for clarity, both are presented separately below (Sections 2.2 and 2.3), despite them conjointly answering the project’s aims: to assess links between gender equality and climate change mitigation action through a feminist lens whilst interrogating hegemonic methodologies and tools in the literature, and to provide a methodological framework to engage with feminist theories within the gender-climate nexus. better integrate feminist epistemology when exploring the gender- climate nexus. It also provides practical recommendations to answer the points raised in that section. Section 4.2 discusses the policy implications of the research. Sections 4.3 and 4.4, respectively, present the recommendations derived from the quantitative and qualitative analyses and their integration. Finally, we discuss the contribution of this paper to the gender-climate nexus literature in Section 5, examining the place gender equality holds in transformation and the limitations of our research. Section 6 concludes. 2. Methodology To appraise possible links between SDG5 and SDG13, the three indices and some of their selected indicators were analyzed. First, correlations between the aggregated scores of all indices were investigated. Second, dividing countries by income categories according to the World Bank classiﬁcation (Supplementary material), the same correlations were run for 2020 and 2010 data series, highlighting the importance of national context. Third, correlations between the Climate Change component of the EPI (EPI-CC), composed of eight sub-indicators and the GGGI aggregated score were run. Then, correlations between two sub-indicators of the EPI- CC (the GHG emission per capita, EPI-GHG-PC and the GHG emissions intensity of GDP, EPI-GHG-GDP) and the aggregated score of the GGGI were run. The same analysis was undertaken with the aggregated score of the GII. Finally, correlations between two sub-components of the GGGI [the Women Economic Opportunities (GGGI Economic) composed of 5 indicators, and the Women Political Empowerment (GGGI Political) composed of 3 indicators] and the aggregated score of the EPI were investigated. All analyses run are summarized in Table 2. These were distilled into four hypotheses (H1–H4): Frontiers in Climate 1. Introduction It calls for the reconciliation of all agents of society within a holistic ecofeminist sustainable movement (Gaard, 2017), and aligns with the transformation literature (O’Brien, 2012; Dow et al., 2013; Pelling et al., 2015). The aims of this work are to explore the links between Sustainable Development Goal (SDG) 5 (gender equality) and SDG 13 (Climate Action) (UNSDG, 2015), whilst interrogating hegemonic methodologies and tools in the literature and to provide a methodological framework to engage with feminist theories within the gender-climate nexus research space. On the one hand, the climate adaptation literature increasingly explores gender through feminist lenses, utilizing qualitative methods and considering intersectionality (Crenshaw, 1989; Global Gender and Climate Alliance, 2016), particularly in vulnerability studies. Vulnerability in this context is the potential for an individual or a system to be adversely impacted by climate change (Füssel, 2007). Vulnerability researchers have highlighted the intersectional origins of inequalities to climatic impacts, identifying power dynamics’ roles (O’Brien et al., 2004, 2007; Tschakert, 2007, 2012; Ford et al., 2010; Thomas et al., 2019; Barnett, 2020; Rahman and Hickey, 2020). This has subsequently challenged the “one size ﬁts all” approach implied by gender mainstreaming (Alston, 2014). At the same time, a growing body of literature is advocating for “gender-transformative” responses to climate change adaptation, as opposed to gender- responsive or gender-sensitive policies (Global Gender and Climate Alliance, 2016; Resurrección et al., 2019; Table 1). Gender-responsive policies are right-based responses to gendered climatic impacts, In what follows, how gender equality relates to climate policy, climate action, and general mitigation eﬀorts is investigated. The vast scope of this ﬁeld is supported by the mixed-method global approach adopted for this research and detailed below (Section 2). Section 3 presents the results of the quantitative analysis undertaken. However, to untangle the links between gender equality and climate mitigation action further, more empirical research integrating feminist epistemology is needed. To help achieve this, Section 4.1 discusses methodological issues and suggests a methodological framework (Figure 5) to inform future researchers willing to integrate gender into their work. The framework takes the shape of a decision tree guiding project design, helping to guide the choices one can make at the early stages of a project’s development, and to 02 frontiersin.org Rainard et al. frontiersin.org performances of countries (Joireman and Liu, 2014; Mavisakalyan and Tarverdi, 2019). conducted in a collaborative style (Rapley, 2001, 2014), including self-disclosing introductory remarks to establish rapport, following feminist methods (Moser et al., 1981; Oakley, 2016). The experts were ﬁrst presented with preliminary results and interpretations from the quantitative analysis, as well as a general script of talking points (Supplementary material). They were asked to comment on the document, discussing results and interpretations. Before proceeding with the interview script, they were probed to present their main research interests and to explain any ongoing projects related to gender-climate issues. The questions focused on the following key points: The regression analyses in Table 2 contribute to understanding whether the indices are appropriate tools to appraise links between SDG5 and SDG13. Correlation coeﬃcients are expected to be negative for the GII in the case of a positive relationship between gender equality and sustainability, as the GII ranges from 1 to 0, where 0 is no disadvantage for women (UNDP, 2020a), whereas the GGGI is expected to show positive correlations, as the index ranges from 0 to 1, where 1 is perfect institutional equality between men and women (World Economic Forum, 2020a). • Perceptions of links between gender equality and climate change mitigation action. The use of mainstream indices (GGGI, GII, and EPI) rather than indices attentive to questions of non-binarity, happiness or wellbeing is justiﬁed by their prevalence in the literature and by their wide availability, noting both are linked. Subsequently, understanding their potential caveats and criticisms by gender experts have implications for further research and future data gathering eﬀorts, while also informing the insights that may be gleaned from this analysis and that of aforementioned studies (Ergas and York, 2012; Mavisakalyan and Tarverdi, 2019; McGee et al., 2020). Furthermore, these indices consider a large sample of countries (142), beneﬁcial in highlighting diﬀerences between groups of countries, and permitting for better contextualization of results. Moreover, comparing two indices of gender equality (GGGI and GII) highlighted diﬀerences in their respective deﬁnitions of gender equality and the implications of these deﬁnitions on results of correlation with the EPI. The GGGI understands gender equality as equal institutionalized opportunities between males and females (World Economic Forum, 2020a) and the GII is a measure of gender-based disadvantages (UNDP, 2020a). Finally, these indices were familiar to most experts interviewed, so also facilitated discussion (Section 2.3). performances of countries (Joireman and Liu, 2014; Mavisakalyan and Tarverdi, 2019). • Methodologies used in the literature to uncover these links and how experts perceived potential methodological strengths and weaknesses. • The way experts overcome methodological weaknesses in their work. • Implications for policy of using these methods and experts’ recommendations to policymakers. Questions were catered to each interviewee, owing to the semi-structured approach and the variety of their contributions to the gender-climate nexus. Questions were open ended, to avoid steering interviewees answers (Bryman, 2016; Mason, 2018). However, sharing preliminary data interpretations and self-disclosing remarks may have inﬂuenced discussions (Rapley, 2001). To limit the intrusion of the interviewer’s preconceptions in the results, self-reﬂexivity was maintained throughout the analysis (Bryman, 2016). Self-reﬂexivity is illustrated by the diﬀerence between the interpretation of data in the results compared to the interpretations in the document provided to experts before the interview (Supplementary material). The content of interviews was analyzed using a thematic semantic approach (Mason, 2018), extracting explicit themes arising across interviews (Bryman, 2016; Mason, 2018), considering pre-deﬁned categories, while allowing unforeseen themes to develop. Five out of 15 categories, resulting from the project’s objectives, were pre-deﬁned: methodological issues and recommendations, impacts on policy and recommendations, and gendered perspectives on mitigation (Supplementary material). First, nodes (categories) were created, then, interlinked nodes were reorganized according to the aims and hypotheses, and within the nodes, themes were extracted and structured during the interpretation of the results (Maguire and Delahunt, 2017). The experts’ interviews enabled in-depth reinterpretation of quantitative results, including the deﬁnition of H4 2.1. Operationalization TABLE 2 Correlations performed in the quantitative analysis, and the hypothesis tested. TABLE 2 Correlations performed in the quantitative analysis, and the hypothesis tested. Indicators GII score GGGI score GGGI economic GGI political EPI Score (aggregated) H1 H1 H4 H4 EPI Score (aggregated) by national income category H2 H2 EPI climate change H3 H3 EPI GHG emissions H3 H3 EPI GHG intensity H3 H3 performances of countries (Joireman and Liu, 2014; Mavisakalyan and Tarverdi, 2019). Frontiers in Climate 2.1. Operationalization The mixed-methods approach adopted for this research is justiﬁed by three considerations. First, utilizing mixed methods aligns with the pragmatic research paradigm. Pragmatism considers that natural reality exists outside of humans’ perceptions, but societies and social norms shape and co-create that reality, consciously and subconsciously (Rorty, 1982). Thus, pragmatism is the most relevant paradigm to foster the idea of interactions between technical and social solutions to climate change mitigation (Rayner, 2012; Mason, 2018; Westholm and Arora-Jonsson, 2018). Second, the mixed-methods approach reinforces the idea of complementarity between quantitative methods utilized in mainstream appraisals of links between SDG5 and SDG13, and the qualitative methods used by feminists and gender researchers. Finally, the mixed-methods approach is an attempt to avoid the pitfalls of both methods when used separately, notably, the lack of generalization attached to qualitative approaches, and the potentially misleading results fostered by quantitative approaches (Bryman, 2016; Mason, 2018; Tracy, 2019). • Hypothesis 1: Increased gender equality relates to the environmental sustainability of countries (Ergas and York, 2012; Joireman and Liu, 2014). Two indices of gender equality, the Gender Inequality Index (GII) (UNDP, 2020a) and the Global Gender Gap Index (GGGI) (World Economic Forum, 2020a) are analyzed to highlight correlations with the Environmental Performance Index (EPI) (Wendling et al., 2020) in a cross-country regression analysis. To critically assess results of the quantitative analysis, 13 feminist and gender researchers, whose work focusses on the gender-climate nexus, were interviewed, and these interviews were used in coordination with the regression analysis to provide guidance for researchers willing to incorporate gender in their work, and inform the development of the decision tree presented in Section 4.1. • Hypothesis 2: The relationship between gender equality and environmental performances is contextual and inﬂuenced by countries’ national aﬄuence, rather than a universal truth (Chan et al., 2018; Knight, 2019; Knight and Givens, 2021). H2 was also tested on 2010 data series of the indices, to highlight evolution over time. • Hypothesis 3: Gender equality inﬂuences the speciﬁc climate change indicators of GHG emissions per capita and GHG intensity of GDP (McGee et al., 2020; Ergas et al., 2021). The pragmatic research paradigm and subsequent mixed methods approach called for an abductive analysis, where the quantitative and qualitative analyses informed each other iteratively. • Hypothesis 4: Women’s political empowerment and economic opportunities make a diﬀerence on environmental 03 frontiersin.org 10.3389/fclim.2023.946712 Rainard et al. frontiersin.org 2.3. Interviews: Sampling, method, and analytical approach A total of 13 gender experts were interviewed. All experts interviewed and willing to be named have been listed in the Acknowledgments, and provided informed consent. The procedures of the University of Leeds Ethics Committee were followed. The interviewees were selected by reviewing relevant literature, mixing purposive and snowball sampling. Experts were selected based upon their work, as well as on the countries and context in which they base their research, to foster a variety of perceptions and viewpoints. The interviews were semi-structured (Mason, 2018) and Frontiers in Climate 04 frontiersin.org 10.3389/fclim.2023.946712 Rainard et al. sub-indicators in total (UNDP, 2020a). Beyond these diﬀerences in strength of correlation, the composite nature of the indices’ ﬁnal scores questions the relevance of H1 statistical signiﬁcance in revealing causality between gender equality and environmental performances, as highlighted by participant D: “I do not put much weight or faith in this type of analysis” and participant H: “we do not have the data to fully understand this link.” For participant G, looking at composite and aggregated data was: “neglecting scale.” Experts explained how overlooking the contextuality of gendered experiences was considering women as a homogenous group, an assumption neglecting the contextuality of gender norms’ construction and intersections between gender, race, age, and class inequalities. and reﬁnement of H3, to include the GHG intensity of GDP. Finally, the experts’ remarks enabled consideration of the paper’s implications for policy, discussed in Section 4. 2.4. Methodological framework: Aim and design for a useful tool Following the quantitative and qualitative analyses, and guided by the literature reviewed to design this paper, a pattern emerged, showing what was missing from the available literature and data to deepen our understanding of the links between gender equality and climate change mitigation action. The mixed-methods results allowed for building a methodological framework, in the shape of a decision tree (Section 4.1, Figure 5), to inform the design of future environmental research projects willing to include gender. 3. Results 3. Results 3.2. H2: Links between gender equality and environmental performance are contextual, inﬂuenced by countries’ national afuence The framework was built with the help of the experts interviewed, by analyzing their answers when discussing key points 2 and 3 (“Methodologies used in the literature to uncover these links and how experts perceived potential methodological strengths and weaknesses” and “The way experts overcome methodological weaknesses in their work.”). The data analysis was useful too, by showing what was missing from the available data, and how indices’ construction could lead to misleading interpretations of statistical analysis. In other words, the data showed gaps, and the expert interviews helped inform how to ﬁll these gaps in future research. Figure 2 illustrates the relationship between gender equality and climate change mitigation action contextually, with the importance of national inﬂuence (Knight and Givens, 2021) represented by countries’ income, as per the World Bank’s classiﬁcation (World Economic Forum, 2020b). Hypothesis 2 is partially conﬁrmed in the case of high income (higher gender equity) in both GGGI and GII indices. The lack of correlation for low-income countries is also partly explained by a lack of data. Middle-income countries reveal some interesting subtleties. The strong correlation between GII and EPI in lower-middle-income countries compared to upper- middle-income countries (Figure 2G) was intuitively justiﬁed by four participants as caused by gender mainstreaming within institutional funding bodies. As participant E explained: “donors push for the implementation of gender,” meaning lower-middle-income countries receiving international development aid are compelled to integrate gender issues in their development plans, that are considered as part of the EPI (Wendling et al., 2020). Gender mainstreaming within international politics and funding bodies highlighted by experts is illustrated by stronger correlations between GGGI and GII and EPI over time in higher-middle income countries as they continue to develop (Table 3). The shape of the methodological framework was justiﬁed by the need to address the root of the most common methodological issues encountered in the literature discussed in Section 4.1. Indeed, the project design stages are fundamental to avoid perpetuating gender bias and harmful assumptions. Moreover, addressing issues arising at the project design stage allows a deeper integration of feminist epistemology. Finally, shaping the methodological framework as a decision tree renders it more accessible, making it a useful resource for ﬁrst-time gender-climate nexus researchers. Frontiers in Climate frontiersin.org 3.1. H1: Gender equality inﬂuences countries’ environmental performances However, the more comprehensive deﬁnition of gender equality built within the GGGI, and weaker correlations associated with this index show that the reality of women’s integration in public and private sectors pushed by gender mainstreaming is to be nuanced. The experts agreed gender mainstreaming made gender a “box to tick,” as expressed by participant B, where underlying power dynamics creating gendered diﬀerences are ignored, never achieving true integration of women within decision-making. Furthermore, the slightly weaker correlations over time for higher-income countries question the strength of the relationship between gender equality and environmental performances. Subsequently, interviewees insisted on the contextuality of gendered experiences and norms. Participant B explained: “[women] need to be integrated within the climate debates (...) they have a microcosmic understanding of what is happening to the climate (...) we neglect that information at our peril.” As such, women’s experiences, knowledge, and roles to overcome the climate crisis need to be contextualized and acknowledged, and women’s absence needs to be recognized. This was investigated further by testing H3 and H4. H1 was conﬁrmed by the quantitative analysis (Figure 1), with a stronger correlation between the GII and the EPI (Figure 1B), compared to the correlation between the GGGI and EPI (Figure 1A). In both cases, there is a statistically signiﬁcant relationship between gender equality and countries’ environmental performances. The diﬀerence between the strong correlation observed between GII and EPI and the weaker correlation between GGGI and EPI can be explained by the composition of the indices. The GII is intrinsically linked to the Human Development Index of the United Nations (UNDP, 2020a), highlighted as showing similar ranking of countries as the EPI (Wendling et al., 2020), whereas the GGGI data is mainly drawn from the World Economic Forum data sets (World Economic Forum, 2020a). Furthermore, the GGGI is a complex aggregation of indicators to measure women’s political involvement (three sub-indicators) and women’s economic opportunities (ﬁve sub-indicators) (World Economic Forum, 2020a). In comparison, the GII measures these political and economic aspects through three Frontiers in Climate 05 frontiersin.org 10.3389/fclim.2023.946712 Rainard et al. FIGURE 1 Correlation of (A) Global Gender Gap Index (GGGI) with Environmental Performance Index and (B) Gender Inequality Index (GII) with EPI. Correlations show composite indices for 2020. FIGURE 1 Correlation of (A) Global Gender Gap Index (GGGI) with Environmental Performance Index and (B) Gender Inequality Index (GII) with EPI. Correlations show composite indices for 2020. 3.1. H1: Gender equality inﬂuences countries’ environmental performances FIGURE 2 (A–D) Correlations between GGGI and EPI per income category: (A) low income, (B) lower-middle income, (C) higher-middle income, and (D) high income. (E–H) Correlations between GII and EPI per income category: (E) low income, (F) lower-middle income, (G) higher-middle income, and (H) high income. Regression lines are drawn in the cases of statistically signiﬁcant correlations (p < 0.05). FIGURE 2 (A–D) Correlations between GGGI and EPI per income category: (A) low income, (B) lower-middle income, (C) higher-middle income, and (D) high income. (E–H) Correlations between GII and EPI per income category: (E) low income, (F) lower-middle income, (G) higher-middle income, and (H) high income. Regression lines are drawn in the cases of statistically signiﬁcant correlations (p < 0.05). frontiersin.org 4.1. Methodological issues and progress according to interviewees Figure 4 shows correlations between the Economic Opportunities subcategory of the GGGI (GGGI Economic) and EPI (Figure 4A) and the Political Empowerment component of GGGI (GGGI Political) and EPI (Figure 4B). The weak correlations in Figure 4 are revealing of two dynamics according to experts. First, there is a long way to go before achieving equality in the economic and political domains. Second, women are not the expected panacea to solve the climate crisis. Participant C injuncted: “They should not be! It’s not up to women to clean everyone’s mess,” summarizing most interviewees’ perspectives. This also follows from the fact that relationships between gender equality and environmental performances are more multifaceted than they appear in Figure 1. The dynamics revealed by the cross-country regression analysis are dependent upon indices’ construction, value-laden, and subject to reverse causality (Rodriguez and Rodrik, 2001; Rayner, 2012). Four themes arose from the analysis of the experts’ interviews regarding methodological weaknesses: the impact of gender mainstreaming at the project design stage, the ambivalence of sex-disaggregated data, the diﬃcult equilibrium between depth and breadth, and the problematic conceptualization of gender. Gender mainstreaming’s main positive impact was opening the discussion about gender; however, forcing a gender lens can be detrimental according to all the experts interviewed. Gender mainstreaming made gender an “add-on” according to participant E, reﬂecting most (10/13) experts’ opinions. This translates into gender-climate nexus literature adding a gender section rather than integrating gender when designing research projects, the risk being to consider: “gender is done” as participant J put it, meaning the gender agenda would disappear despite little eﬀective progress achieved. Interviewees agreed that the little gender equality achieved globally, notably, in the political sphere, is symptomatic of unchanged systemic power dynamics inﬂuencing the state of the global climate. The Global South will suﬀer the most from the consequences of climate change, relying on the Global North’s assistance to adapt to climatic impacts (IPCC, 2018). The dichotomy between adaptation and mitigation was challenged by all the experts. Participant A expressed: “I feel adaptation is muddling through (...) there has to be some kind of transformation”. All interviewees mentioned achieving gender equality as participating in the necessary systemic transformation of neoliberal societies to overcome the climate crisis, discussing reproduction of inequalities embedded All the participants agreed that most research: “simpliﬁes gender (...) [as] men vs. women (...) and we know gender is non-binary,” summarized participant G. 3.3. H3: Gender equality inﬂuences climate change, GHG emissions per capita, and GHG intensity of GDP (EPI-GHG-GDP). Participant G highlighted the possibility of reverse causality being revealed. Developed countries have institutionalized gender equality earlier in time, therefore, achieving better scores on gender equality indices due to historical and ongoing gender debates (Beer, 2009). They are also responsible for most GHG emissions and environmental degradation (Herzog, 2009) whereas low-income countries have historically contributed little to climate change (Sarkodie and Strezov, 2019), despite cases of high-income countries oﬀshoring high-emitting sectors such as manufacturing to Both indicators aligned when investigating H3, with expected stronger correlations between the GII and EPI sub-indicators compared to GGGI. Gender equality indicators are correlated to climate change (EPI-CC) and GHG emissions per capita indicators (EPI-GHG-PC) but are uncorrelated with GHG intensity of GDP Frontiers in Climate 06 frontiersin.org 10.3389/fclim.2023.946712 Rainard et al. TABLE 3 Correlation coefcients between GGGI and EPI and between GII and EPI for each income category, using EPI composite scores for 2010 and 2020. ients between GGGI and EPI and between GII and EPI for each income category, using EPI composite scores for 2010 and 2020. Income Low Lower-middle Higher-middle High EPI year 2010 2020 2010 2020 2010 2020 2010 2020 GGGI vs. EPI 0.15 −0.08 0.25 0.14 0.21 0.38 0.61 0.58 GII vs. EPI −0.2 −0.13 −0.52 −0.63 −0.06 −0.34 −0.82 −0.78 Statistically signiﬁcant (at the 5% level) results are in bold. Statistically signiﬁcant (at the 5% level) results are in bold. in neoliberal systems. The notion of transformation transcends the idea of gender equality to address inequalities holistically and requires to “change the way we conceive our relationships” said participant I, before explaining that systemic transformations required “paradigm shifts”, in political, technical, and personal realms. Participant I also mentioned “animals (...) and trees rights” and emphasized the importance of “indigenous knowledge,” like most (9/13) experts, aligning with critical ecofeminist theories (Plumwood, 1997, 2002; Gaard, 2017). Furthermore, most interviewees (9/13) discussed individualism and hierarchical relationships between individuals imposed by neoliberal, patriarchal and neo-colonial systems’ hegemony as inﬂuencing the solutions implemented to overcome the climate emergency, “the elephant in the room,” according to participant A. However, technical solutions still prevail within academia and the political sphere. developing countries to service their own consumption. frontiersin.org Frontiers in Climate 3.3. H3: Gender equality inﬂuences climate change, GHG emissions per capita, and GHG intensity of GDP As such, what can be highlighted from Figures 2, 3 is the link between economic growth and environmental harm, acknowledging that developed countries tend to have greater institutionalized gender equality, as gender equality beneﬁts economic growth (Kabeer and Natali, 2013). Furthermore, absence of correlation between gender equality indices and the GHG intensity of GDP indicator is revealing of women’s absence from decision making, which was discussed with all experts. This leaves women with little inﬂuence on economic or political decisions impacting the GHG intensity of GDP. However experts agreed that assuming increasing female presence in decision-making would result in decreasing the GHG intensity of GDP is misleading. Deconstructing the GGGI to understand the links between women’s economic opportunities and political empowerment with environmental performances, showed that gender equality in these domains was weakly correlated to the EPI. 4.1. Methodological issues and progress according to interviewees Thus, gender-climate focused research often disregards the fact that gender is not a binary construct, problematically ignoring contextual social constructs underlying gendered dynamics. This translates into the predominant use of sex-disaggregated data. Sex-disaggregated data is convenient, and experts agreed that striving for more quantitative analyses integrating sex-disaggregated information would be beneﬁcial, if weaknesses of such data are acknowledged. Sex-disaggregated data is an entry point to study gender, but lacks the depth and breadth necessary 07 Rainard et al. 10.3389/fclim.2023.946712 FIGURE 3 (A–C) GGGI (blue) and (D–F) GII (green) correlations with (A, D) EPI climate change indicator, (B, E) GHG emissions per capita, and (C, F) GHG GDP intensity sub-indicators. FIGURE 4 (A) Correlation between EPI and the economic opportunities sub-component of the GGGI. (B) Correlation between EPI and the political empowerment sub-component of the GGGI. 10.3389/fclim.2023.946712 Rainard et al. FIGURE 3 (A–C) GGGI (blue) and (D–F) GII (green) correlations with (A, D) EPI climate change indicator, (B, E) GHG emissions per capita, and (C, F) GHG GDP intensity sub-indicators. FIGURE 3 (A–C) GGGI (blue) and (D–F) GII (green) correlations with (A, D) EPI climate change indicator, (B, E) GHG emissions per capita, and (C, F) GHG GDP intensity sub-indicators. FIGURE 3 (A–C) GGGI (blue) and (D–F) GII (green) correlations with (A, D) EPI climate change indicator, (B, E) GHG emissions per capita, and (C, F) GHG GDP intensity sub-indicators. FIGURE 4 (A) Correlation between EPI and the economic opportunities sub-component of the GGGI. (B) Correlation between EPI and the political empowerment sub-component of the GGGI. FIGURE 4 (A) Correlation between EPI and the economic opportunities sub-component of the GGGI. (B) Correlation between EPI and the political empowerment sub-component of the GGGI. recommendations based on academic research but without an in- depth understanding of gendered social phenomena at the individual and household level, risks failing to solve the problems addressed. To ﬁnd the right balance between depth and breadth, the gender component in academic literature needs to be conceptualized appropriately, deﬁning gender and the issue to be addressed clearly. Therefore, the experts agreed that the right tools need to be deployed at the research project design stage. to understand constructed social phenomena. The generalization of sex-disaggregated data was also discussed by experts to highlight inequalities, deepening the understanding of the links between one’s biological sex and position in society, but neglecting other forms of identity. Frontiers in Climate Frontiers in Climate frontiersin.org 4.1. Methodological issues and progress according to interviewees Women are burdened with even more responsibilities and men and their struggles are ignored. p j g g Beyond integrating gender for the sound conceptualization of research projects, experts highlighted how interdisciplinary research avoids siloed solutions to a “wicked” issue (Carter, 2018, p. 310) like climate change, allowing for more holistic approaches. Most experts (9/13) criticized Enlightenment thinking and its modern expressions, characterized by the object/subject and nature/culture dualisms fundamentally hierarchizing individuals and knowledge as well as emphasizing technical solutions to problems. Both Enlightenment thinking and its critiques are rooted in Western culture and as such should be recognized as situated, as per Haraway (2020), noting that the prevalence of such critiques here can be explained by the interviewees’ knowledge situation. Thus, the promotion of interdisciplinary research is a natural ﬁrst step, whereby diﬀerently situated pieces of knowledge (Haraway, 2020) can converse. Beyond the promotion of interdisciplinary research, acknowledging that available data is inadequate in describing social phenomena and developing alternative measures is another way to avoid reproducing neoliberal narratives inherited from the Enlightenment. This can open the way to integrate narratives other than the dominant western ones. Increasingly, these alternative measures, like the carbon intensity of wellbeing (Jorgenson, 2014; Gough, 2017; Ergas et al., 2021), the Happy Planet Index (2016), or measurements of the 12 social foundations depicted by Raworth (2017) in Doughnut Economics are considered, as they avoid purely economic representation of prosperity. The fourth theme, in most interviewees’ perceptions (11/13), was how this dilution mechanism causing maladaptation triggers the exclusion of certain individuals. Notably, exclusion of poorer individuals’ voices, indigenous knowledge, and social justice considerations from climate debates, thus depriving humanity of invaluable knowledge, creativity and understanding of natural dynamics, all necessary to answer the climate emergency. Subsequently, for all experts, the main link between gender equality and climate change mitigation action was how equality opens the way toward social justice, paramount to the organization of sustainable societies. Both participants B and K said: “climate justice is social justice (...) and there is no social justice without gender justice.” Finally, for nearly all participants (11/13), the dilution- maladaptation-exclusion trilemma is an expression of established power dynamics. Paraphrasing Phillips (2017) book, participant H simply said: “to those in power, equality is a threat.” Nuancing their ideas, all experts appreciated that gender mainstreaming allowed pushing these issues in the public space: “opening the way” explained participant L. 4.1. Methodological issues and progress according to interviewees Furthermore, ﬁve interviewees talked about how the climate emergency was changing international power dynamics, whereby poorer or less developed countries are now the focus of eﬀorts to protect biodiversity, which might illuminate a hopeful trend. However, all experts acknowledged there was still a long way to go, participant B noted: “women remain the supplicants banging at the door,” positing policy suggestions to remedy this. The recommendations of the experts are summarized in the decision tree in Figure 5, which aims to practically inform the design of environmental research projects seeking to consider gender. 4.2. Implications for policy according to interview analysis Gender mainstreaming and the increasing interest in gender within climate change science has had policy impacts globally. In the following part we will consider the implications for policy of gender mainstreaming in environmental research through the analysis of experts’ interviews. Five intertwined themes arose from the analysis of experts’ interviews. 4.1. Methodological issues and progress according to interviewees The diﬃcult balance between breadth and depth when studying gender was also recognized by all interviewees. Producing broad knowledge regarding gender is fundamental to provide policy frontiersin.org 08 frontiersin.org Rainard et al. 10.3389/fclim.2023.946712 FIGURE 5 Decision tree to inform environmental projects’ design seeking to integrate gender. Methodological issues highlighted by experts are easily overcome with theoretically sound and practical research project design, considering feminist epistemology and more radical gender theory, notably, understanding the intersectional and contextual nature of gender inequalities as well as the centrality of collecting appropriate data. However, as participant A put it: “with gender (...) you need learning by doing” and according to participants, since the Beijing platform instituted gender mainstreaming, progress has been made in this regard. Participants noted progress regarding the integration of more radical gender theories, to overcome the “radical potential paradox” (Wittman, 2010, p. 51) brought in by gender mainstreaming. Radical here was deﬁned according to the Latin etymology meaning “roots” (Oxford English Dictionary, 1989), highlighting the necessity of grounding gendered research in gender Finally, all interviewees highlighted that theoretical and practical reﬂections are central to conceptualization. For example, participants A and D suggested linking contextual research back to existing feminist frameworks to inform policy, for instance the four Rs (recognition, reduction, redistribution, responsibility) (Oxfam, 2008; Butt et al., 2020). Seven participants reﬂected upon past experiences sharing anecdotes of misaligned research projects’ means and objectives. Participant H remembered: “I was brainstorming with (...) engineers, they were developing this hydrogen [stove] for use in developing countries (...) to reduce wood [consumption and] in-home pollution. (...) I said what do women want to cook on it? (...) They had [not] asked them! (...) They had a brilliant solution to a technical problem, but it wasn’t necessarily the right problem.” 09 frontiersin.org frontiersin.org 10.3389/fclim.2023.946712 Rainard et al. 10.3389/fclim.2023.946712 10.3389/fclim.2023.946712 theories and feminist epistemology. According to participants, it implied developing interdisciplinary research, including gender at the research project design stage. research informing policies, assumptions such as women being a homogeneous group can be transcribed into policies, which ignores the role of other social factors, resulting in maladaptive policies that only address part of the issue. The third, Participant D explained, was conceiving gender equality as meaning: “women’s rights (...) [excluding] males and masculinities,” which neglects the voices of others and consideration of gender as a non-binary construct. Frontiers in Climate frontiersin.org 4.3. Recommendations based on interview analysis Second, cross-country analysis of available data is subject to caveats and the links between gender equality and climate change mitigation action need to be investigated further through interdisciplinary research, considering radical gender theories, more comprehensive sex-disaggregated data and alternative measures of wealth, prosperity, and aﬄuence, as the climate change emergency is shifting international dynamics. decision-makers, experts acknowledged how listening and creating the space for open discussions was a recommendation to be followed by all parties. Diﬀerences of opinion need to be overcome to foster creative solutions to the climate emergency. In other words, listening meant creating a space for collaborative and inclusive learning. According to experts, learning was not just increasing each other’s knowledge, but also reconsidering situated norms and values by understanding their constructions and acknowledging their lack of universality, better enabling transformation. Listening, then learning could lead to the necessary radicalization and re-politicization of western societies in most (8/13) interviewees’ perceptions. The radicalization advocated by experts was justiﬁed by the need for transformational paradigm shifts already outlined by social theorists (Stern and Dietz, 2015; Urry, 2015) and echoed by environmentalists (Anderson and Bows, 2012; O’Brien, 2016; Eizenberg and Jabareen, 2017). Once again, radicalization does not mean extreme, rather it is a call toward integration of alternative societal theoretical conceptions, away from the models which created the current climatic situation, rooting back social norms to end “remoteness” (Plumwood, 2002, p. 73) between humans and nature. This radical movement is inseparable from a re- politicization of neoliberal societies, in which citizens’ faith in democratic institutions is restored through the implementation of participatory and deliberative democratic tools to restructure power dynamics. This would foster equality without forcing it upon individuals by laying the ground for equalitarian participation and discussions, creating a virtuous cycle where individuals ultimately listen and learn from each other permanently. These suggestions intrinsically link back to the notion of transformation (O’Brien, 2012) and the need to transcend “all the -isms” as participant I put it. Gender mainstreaming has exposed the gendered causes and impacts of climate change, but radicalization of the gender- climate nexus literature is needed to overcome the harmful assumptions perpetuated by the dilution of gender theories through mainstreaming. Furthermore, theories’ dilution has led to maladaptation inseparable from the exclusion of certain individuals from climate change debates. 4.3. Recommendations based on interview analysis The ways forward suggested by experts can be grouped in four themes: listening, learning, radicalizing, and re-politicizing, which all rely on three underlying arguments: morality, practicality, and the logical argument, summarized in a famous quote attributed to Albert Einstein: “No problem can be solved from the same level of consciousness that created it,” paraphrased by two experts. The ﬁrst of these themes was regarding the deradicalization of gender theories, understood as inevitable by all experts for gender to mainstream. As participant L said: “It is the way in international treaties,” as for all countries to ratify a global agreement, what is deemed “extreme” by some is often diluted. Two participants highlighted that it was the case with the Paris Agreement too, during which a lot of debates surrounding women and their role for adaptation and mitigation ended up as: “maybe one paragraph” sighed participant H, before adding: “[they have] taken all the teeth out of the tiger. It might lick you to death, but it’s not going to savage you,” reﬂecting upon the non-binding nature of international agreements. More recently, the ﬁnal COP26 agreement in Glasgow disappointed many for similar reasons (UN NEWS, 2021). The morality argument relies on the idea that the climate crisis and its related inequalities should be solved simply because it would be immoral not to (Shove, 2010). The practicality argument can be summed by the idea that, because humanity is facing disastrous events, it cannot deprive itself of most of its creativity. Without necessarily mentioning critical ecofeminism, all interviewees implored decision-makers to “listen” (Gaard, 2017, p. xvi). This implied listening to multiple actors, including activists and academics but also citizens, without hierarchizing their contributions using neoliberal preconceptions, overvaluing the opinions of the Western Educated Industrialized Rich and Democratic (the WEIRDs, term used by three participants). However, beyond addressing The second theme relates to the constant dilution of gender theories within research, which translates into maladaptive policies (Lau et al., 2021). When gender theories are overlooked in 10 frontiersin.org 10.3389/fclim.2023.946712 10.3389/fclim.2023.946712 Rainard et al. for a fairer organization, which is paramount in achieving sustainable societies. Therefore, gender equality is inseparable from social and climate justice. In other words, climate justice depends on social justice and social justice cannot be achieved without bridging gender inequalities among other inequalities. 5.1. Contribution and contextualization The quantitative analysis undertaken in this study ﬁnds similar results to that found in the wider literature (Ergas and York, 2012; Mavisakalyan and Tarverdi, 2019; McGee et al., 2020). All these studies ﬁnd a statistically signiﬁcant link between composite indices of gender equality and environmental performances of countries. The similarity in results can be explained by the homogeneity of the data considered. Mavisakalyan and Tarverdi (2019) used the Climate Laws, Institutions and Measures Index, similar in its construction to the EPI, but simpler (Steves et al., 2011; Wendling et al., 2020). Ergas and York (2012) and McGee et al. (2020) used World Bank data sources to measure CO2 emissions per capita (World Bank, 2010, 2017), which is also accounted for in the EPI (Wendling et al., 2020). Ergas and York (2012) used a women’s political status index developed by Nugent and Shandra (2009) and based on the GII and GGGI. McGee et al. (2020) used the GII, and Mavisakalyan and Tarverdi (2019) used World Bank indicators of female seats in parliaments, a sub-indicator of the GGGI Political component. 4.3. Recommendations based on interview analysis Overcoming the dilution- maladaptation-exclusion trilemma necessitates emphasizing listening to all parties in policy making, learning from one another and accepting radicalization through societies’ re-politicization thanks to inclusive and participatory democratic actions. This could lead to systemic transformations that holistically tackle climate change. Frontiers in Climate frontiersin.org 5.2. The place for gender equality in transformation diﬀerences in results. Nevertheless, the Paris Agreement’s eﬀects on environmental performances and integration of gender are relative, as pre-Glasgow NDC trajectories would require a further 80% decrease in emission rate to respect the 2◦C limit determined by the agreement (Liu and Raftery, 2021). Furthermore, gender within NDCs is predominantly framed using gender-sensitive approaches (Remteng et al., 2021) rather than gender-responsive or gender- transformative approaches (Resurrección et al., 2019). In the context of climate change, the transformation notion, arising from adaptation literature (Moser and Ekstrom, 2010; Dow et al., 2013; O’Brien and Sygna, 2013; O’Brien, 2016) considers rethinking human systems holistically, and challenging the current state of relationships between humans and nature (Pelling et al., 2015). Remarkably, it considers the multi-layered interactions between social and natural systems to oﬀer policy responses that go beyond adapting systems to climatic impacts by transforming them, while at the same time increasing adaptive capacities, limiting future impacts, and enabling sustainable development (O’Brien, 2012; Pelling et al., 2015). Thus, transcending the adaptation/mitigation dualism. Enriching the quantitative analysis with evidence gathered through expert dialogue, allowed this research to consider diﬀerent interpretations of the results. For example, Mavisakalyan and Tarverdi (2019) concluded female parliamentarians made a diﬀerence to climate mitigation action, like McGee et al. (2020) and other studies (see Lambrou and Piana, 2006; Cook et al., 2019). In this study, the relationship between women’s political empowerment and environmental performances is understood as contextual and dependent upon culturally diverse gendered constructs similarly to Chan et al. (2018) and Knight and Givens (2021), so as to avoid essentializing women’s relation to nature, also integrating Lau et al. (2021) ﬁndings. Female parliamentarians should not be expected to make a diﬀerence, rather political systems allowing gender diverse representation can be expected to support equalitarian social values that are paramount to achieving sustainable societies (Lee and Zusman, 2018). Furthermore, comparing two indices of gender equality, as done in this work, helped to exemplify the relativity of the link between female representation and environmental performances, such that the more complex indicators embedded in the GGGI were more weakly correlated with the EPI. Moreover, the mixed-method approach allowed us to draw upon the experts’ methodological insights to create the decision tree (Figure 5) and highlighted the limits of employing positivist epistemological approaches to appraise links between gender equality and climate change mitigation action. 5.2. The place for gender equality in transformation The feminist perspective was fundamental in challenging harmful gendered assumptions still present in the literature, and ﬁlling a gap, where little consideration is given to feminist theories when studying the gender-climate nexus (Global Gender and Climate Alliance, 2016; Thompson-Hall et al., 2016; Lau et al., 2021). Transformation is by essence radical (Dow et al., 2013; Pelling et al., 2015), addressing root causes of climate change by incrementing non-linear changes, i.e., paradigm shifts. As such, concepts underpinning transformation are shared by post-growth (Koch, 2013; Raworth, 2017), critical ecofeminism (Shiva, 2005; Gaard, 2017) and even quantum social change (O’Brien, 2016) thinkers alike. The common assumptions that encompass this thinking include recognition of neoliberal systems’ failure to address climate change (Shiva, 2005; Dow et al., 2013; Gaard, 2017; Koch, 2020), overcoming social contracts inherited from the Enlightenment (Pelling, 2010; O’Brien, 2012; Gaard, 2017) and radicality (Pelling et al., 2015; Gaard, 2017; Raworth, 2017). Therefore, gender equality, as deﬁned here, appears as one paradigm shift, and part of the equation to reshape relationships between humans, among addressing inequalities globally, and to alter existing social contracts (O’Brien et al., 2009). Despite a ﬂourishing literature interested in various forms of transformation (Pelling, 2010; Dow et al., 2013; Harvey, 2013; Tschakert et al., 2013; Pelling et al., 2015; O’Brien, 2016), the concept’s visibility in decision making is limited to isolated systems and is potentially undermined, as requiring power redistribution (Pelling et al., 2015). During the interviews, the experts equally insisted on the transformational power of gender equality, and the lack of progress in this domain. In their recommendations to policymakers, the re- politicization of western societies held a central place in enabling gender equality and the power redistribution necessary to solve the climate emergency. It was understood that changes in the personal realm, through individuals’ re-politicization, could enable shifts in power dynamics, and thus, transformation (Pelling et al., 2015; O’Brien, 2018). Over the past 5 years, neoliberal societies have witnessed an increase in demonstrations, illustrating new forms of citizens’ political engagement, and a step toward re-politicization (Amnesty International, 2019). Whether within the Fridays4Future youth movement; the Extinction Rebellion actions; indigenous revendications in Brazil and Canada, equality holds a central place between individuals of diﬀerent genders, ages, races or even across species (Amnesty International, 2019). 4.4. Integration To summarize, the links between gender equality and climate change mitigation action are multidimensional and integrated with other power dynamics underlying neoliberal societies. Women have not played the same role as men in creating carbon-intensive systems of production with women’s voices only recently included in the debate. This does not mean women would have done diﬀerently than their male counterparts, and assuming this essentialises women’s relationship to nature and the environment and fails to challenge constructed power dynamics underlying gender norms, ignoring gendered experiences’ contextuality. If women had beneﬁted from the same privileges as men, there is no way of knowing if societies would have developed the same carbon-intensive systems of production or not. Assuming they would not have done so is viewing women as inherently closer to nature and the environment, which is an assumption constructed by gendered modern and western worldviews. The ecofeminist literature (Plumwood, 2002; Gaard, 2017) emphasizes how equality is one tool in societies’ belt alongside economic and environmental improvements to ensure the planet thrives. In contrast to McGee et al. (2020) we ﬁnd no statistically signiﬁcant link between GHG intensity of GDP and gender equality. Their study suggested greater institutional gender equality was linked to decoupling CO2 emissions from economic growth. This could be due to the addition of developing countries in our analysis. The importance of national aﬄuence in the correlation between gender equality and climate action found in this study is comparable to that found by Knight (2019) and Knight and Givens (2021), underlining the contextuality of gendered phenomena (Schwartz and Rubel- Lifschitz, 2009; Chan et al., 2018). Furthermore, consideration of gender mainstreaming in the Paris Agreement, not considered by the aforementioned studies, was integrated in this work through the use of 2020 EPI data (Wendling et al., 2020), and could explain Statistically signiﬁcant relationships highlighted in the quantitative analysis are revealing of two trends according to experts. First, rather than gender equality positively impacting climate change mitigation action, it is understood that greater equality between a society’s members is revealing of society striving 11 Rainard et al. 10.3389/fclim.2023.946712 Frontiers in Climate frontiersin.org 5.3. Limitations and future research implications Firstly, we employed only 2020 index data for the EPI and GII, as these were only available for 2020 despite GGGI data available for 2021, though we did monitor changes over time using 2010 values of these indices. The COVID-19 pandemic and its eﬀects on both gender equality and environmental performances are thus not fully accounted for in the quantitative analysis. The economic crisis that has resulted from the pandemic has had tremendous eﬀects on the gender gap, as it will now take 135 years for women to reach equality compared to the 99 years predicted earlier in the WEF 2020 report (World Economic Forum, 2020a, 2021). Simultaneously, the pandemic has aﬀected countries’ environmental performances, with a 7–8% reduction of GHG emissions over 2020 due to global lockdowns and a slowdown of the global economy (Forster et al., 2020; Le Quéré et al., 2020; Liu et al., 2020). While emissions have since rebounded to pre pandemic levels (Davis et al., 2022), beyond the direct eﬀect of lockdown restrictions on GHG emissions, the pandemic brought environmental considerations to the heart of the political debate (UNDP, 2020b). As such, using updated data accounting for COVID- 19 eﬀects is an avenue for future research, as is exploring the crisis’s potential for enabling transformative changes. Understanding the links between gender equality and climate change mitigation requires the development of more comprehensive and detailed indices and better data collection eﬀorts. These eﬀorts could focus on the fact that gender is not a binary construct, the lack of sex-disaggregated data, and also recognize alternative measures of wealth and prosperity. Data collection eﬀorts that recognize gender as a non-binary construct are in their infancy, but research on gender equality and climate change action can be informed by eﬀorts in the health realm, where such data is collected and these diﬀerences have been analyzed (Cicero et al., 2020). Recognition and construction of alternative measures of wealth and wellbeing are also in their infancy, but include eﬀorts such as those that deﬁne decent living standards and access to these across populations (Rao and Min, 2018). Secondly, understanding the multi-layered relationship between gender equality and environmental performances at diﬀerent scales necessitates the investigation of currently scattered or unavailable sex-disaggregated data. As recommended by experts, this is an opportunity for future interdisciplinary research. 6. Conclusion This paper presents a mixed-methods approach to assessing the drivers of gender equity and its relationship to environmental performance. The quantitative analysis carried out in this research analyzed country-level regressions between gender equity metrics (the GII and GGGI) and a measure of environmental sustainability, the EPI. The GGGI, composed of a more complex aggregation of indicators (Women’s Economic Opportunities and Women Political Empowerment indicators) was found to be more weakly correlated with the EPI, as compared to the GII. This suggests that the relationship (though not necessarily causality) between gender equality and climate change mitigation action is multi-faceted and contextual. This is also reinforced by the income categories analysis, which underlines the role of countries’ national aﬄuence in moderating this relationship. 5.2. The place for gender equality in transformation The newly invented “ecocide” crime, referring to harmful actions toward ecosystems enacted by states or corporations is an illustration of environmental claims penetrating established systems (Siddique, 2021). Similarly, legal actions have been taking place across the globe to address governments’ inaction in the face of climate change as “unlawful” (Schiermeier, 2021). Academics and citizens alike are forcing governments to acknowledge neoliberalism’s weaknesses, with social and environmental calls converging (Worms and Butler, 2021). Recognizing how knowledge is situated (Haraway, 2020) is primordial in environmental research, as diﬀerent epistemological positions highlight diﬀering solutions to the climate emergency (Rayner, 2012). Here, the feminist epistemology skewed results toward societal and systemic considerations. This paper does not intend to hierarchize and oppose technical or social solutions to the climate urgency, rather, by embracing pragmatism (Rorty, 1982), it is understood that all solutions are complementary and should be considered holistically. However, less attention has been given in the past to social considerations in environmental research (Rayner, 2012; Urry, 2015; O’Brien, 2016), whereas climate change is a “wicked issue” (Carter, 2018, p. 310) and requires drawing upon the expertise of several disciplines. To overcome this, interdisciplinary research that promotes epistemological pluralism was recommended (Miller et al., 2008; Rayner, 2012). Nevertheless, interdisciplinarity in research is subject to established power dynamics (Miller et al., 2008), and is gendered, appealing more to women (Rhoten and Pﬁrman, 2007). Subsequently, creating an equalitarian space is fundamental to ensure dialogue is maintained in interdisciplinary teams (Miller et al., 2008). Beyond academia, creating egalitarian spaces, where diﬀerent voices can contribute to the climate debate, can enable systemic transformations (Dow et al., 2013; Pelling et al., 2015; O’Brien, 2016). Frontiers in Climate 12 frontiersin.org 10.3389/fclim.2023.946712 10.3389/fclim.2023.946712 Rainard et al. However, despite the COVID-19 pandemic, acknowledged by scientists as caused by environmental harm (Daszak, 2020; Dobson et al., 2020), and numerous catastrophic climatic events riddling the global North (UNFCCC, 2021), NDCs and green-recovery pledges still fall short (Liu and Raftery, 2021; UNFCCC, 2021). Nonetheless, these events might be the necessary crises to disrupt social practices, change personal realms, and enable access to deep leverage points that empower systemic transformation (Meadows, 2008). Establishing these links further requires an in-depth investigation of complex concepts, and constitutes avenues for future research. unveil synergistic potential in their common underpinning concepts. 5.2. The place for gender equality in transformation Furthermore, increasing the visibility of these discourses in the public sphere could enable their self-fulﬁlling potential, disseminating changes in the personal realm, and initiating transformative actions. Frontiers in Climate frontiersin.org Supplementary material The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fclim.2023. 946712/full#supplementary-material Funding research, which can inform policies accordingly. Beyond academia, re-politicization and radicalization of climate debates can enable paradigm shifts, in the political, technical, and personal realms. Therein lies the potential for systemic transformation. Transformation of current systems requires rethinking relationships beyond current hierarchies imposed by neoliberal pre-conceptions. As such, gender equality is no panacea to the climate crisis, as there is no simple remedy to this “wicked issue” (Carter, 2018, p. 310), but it can participate in reshaping relationships. Equality, between genders, but also between classes, ages, races, and species, is fundamental to alter established social contracts to overcome the climate crisis. Promoting equality challenges established power dynamics, and, therefore, can represent a diﬃcult task. However, the pandemic and climate crisis could represent deep leverage points for empowering systemic transformation, but only time will tell. CS was supported by a NERC-IIASA Collaborative Research Fellowship (grant number NE/T009381/1). Acknowledgments The authors express their sincerest gratitude toward the incredibly interesting academics willing to lend their time and expertise to being interviewed: Babette Resurrección, Margaret Alston, Sherilyn MacGregor, Katharine Vincent, Beth Bee, Karen Morrow, Karen O’Brien, Susan Buckingham, Virginie Le Masson, Irene Dankelman, Marina Andrijevic, and Maureen Reed. The authors are also truly grateful for advice from Natalie Suckall during the project’s design. Data availability statement The authors declare that the research was conducted in the absence of any commercial or ﬁnancial relationships that could be construed as a potential conﬂict of interest. The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary material. Ethics statement All claims expressed in this article are solely those of the authors and do not necessarily represent those of their aﬃliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. Written informed consent was obtained from the individual(s) for the publication of any potentially identiﬁable images or data included in this article. Author contributions MR and CS conceived the work. MR, CS, and SP designed the project and carried out further critical revisions of the manuscript. MR undertook the data collection and analysis with advice from CS and SP. MR drafted the initial version of the manuscript. All authors contributed to the article and approved the submitted version. 5.3. Limitations and future research implications Moreover, it points to the need for new data collection eﬀorts that consider gender as a non-binary construct and goes beyond mere sex-disaggregated data and indicators. The qualitative analysis carried out in this research revealed the contribution of gender equality toward climate and social justice, explaining how greater gender equality is revealing of fairer societies’ organization, paramount to achieving sustainable futures. The critical ecofeminist lens, pragmatic paradigm and mixed-methods approach applied here challenged mainstreamed appraisals of the gender-climate nexus and allowed for deriving methodological recommendations regarding the integration of gender in environmental research projects whilst investigating the impact on policy. Thirdly, there are limitations associated with the interviews and subsequent ﬁndings. All interviews were conducted with English speakers and interviewees were mostly located in the Global North, potentially skewing results toward western viewpoints (Temple and Edwards, 2002; Mason, 2018), though interviewees’ research primarily focused on the Global South. As such, future research could draw upon the present ﬁndings, enriching them through a larger number of more diverse interviewees. Alternatively, conducting interdisciplinary focus groups, exploring similar themes, would also beneﬁt the gender-climate nexus literature, enabling epistemological pluralism (Miller et al., 2008). Gender inequality, and other forms of inequalities, were highlighted as inherited from the Enlightenment, and as central issues to solve to overcome the climate crisis, by the qualitative interviews undertaken in this research. Not only are climatic impacts unequally felt, but voices carrying solutions to these impacts are unequally heard, in political debates, but also academia. Moreover, technical solutions still prevail despite recognition of their limitations in holistically tackling the crisis. Listening to these alternative voices is a cornerstone of critical ecofeminism, aligning with other emerging discourses considering transformation, like post-growth movements. Listening means creating egalitarian spaces in which all voices can be heard. In academia, this can be translated into the acceptance of epistemological pluralism embedded in interdisciplinary Finally, this project touched upon the complex interactions between diﬀerent epistemological and ontological perspectives. Exploring further the interactions between ecofeminism, post- growth, post-development, and quantum social changes could 13 Rainard et al. 10.3389/fclim.2023.946712 10.3389/fclim.2023.946712 References 10.3389/fclim.2023.946712 10.3389/fclim.2023.946712 Carter, N. (2018). The Politics of the Environment: Ideas, Activism, Policy. Cambridge: Cambridge University Press. doi: 10.1017/9781108642163 Roberts, E. S. Poloczanska, K. Mintenbeck, M. Tignor, A. Alegr?a (Cambridge: Cambridge University Press). Joireman, J., and Liu, R. L. (2014). Future-oriented women will pay to reduce global warming: Mediation via political orientation, environmental values, and belief in global warming. J. Environ. Psychol. 40, 391–400. doi: 10.1016/j.jenvp.2014.09.005 Chan, H. W., Pong, V., and Tam, K. P. (2018). Cross-national variation of gender diﬀerences in environmental concern: testing the sociocultural hindrance hypothesis. Environ. Behav. 51, 81–108. doi: 10.1177/0013916517735149 Jorgenson, A. K. (2014). Economic development and the carbon intensity of human well-being. Nat. Clim. Change 4, 186–189. doi: 10.1038/nclimate2110 Cicero, E. C., Reisner, S. L., Merwin, E. I., Humphreys, J. C. and Silva, S. G. (2020). The health status of transgender and gender nonbinary adults in the United States. PLoS ONE 15, e0228765. doi: 10.1371/journal.pone.0228765 Kabeer, N., and Natali, L. (2013). Gender equality and economic growth: Is there a win-win? IDS Working Papers 2013, 1–58. doi: 10.1111/j.2040-0209.2013.00417.x Cook, N. J., Grillos, T., and Andersson, K. P. (2019). Gender quotas increase the equality and eﬀectiveness of climate policy interventions. Nat. Clim. Change 9, 330–334. doi: 10.1038/s41558-019-0438-4 Knight, K. W. (2019). Explaining cross-national variation in the climate change concern gender gap: a research note. Soc. Sci. J. 56, 627–632. doi: 10.1016/j.soscij.2018.08.013 Crenshaw, K. (1989). Demarginalizing the Intersection of Race and Sex: A Black Feminist Critique of Antidiscrimination Doctrine, Feminist Theory and Antiracist Politics. Chicago, IL: The University of Chicago Legal Forum. Knight, K. W., and Givens, J. E. (2021). Gender and climate change views in context: a cross-national multilevel analysis. Soc. Sci. J. 2021, 1–18. doi: 10.1080/03623319.2021.1913041 Creutzig, F., Roy, J., Lamb, W. F., Azevedo, I. M., De Bruin, W. B., Dalkmann, H., et al. (2018). Towards demand-side solutions for mitigating climate change. Nat. Clim. Change 8, 260–263. doi: 10.1038/s41558-018-0121-1 Koch, M. (2013). “Employment standards in transition: from fordism to ﬁnance-driven capitalism,” in Non-Standard Employment in Europe, eds. Taylor and Francis (London: Palgrave Macmillan), 29–45. doi: 10.1057/9781137267160_3 Daszak, P. (2020). We are entering an era of pandemics—it will end only when we protect the rainforest. The Guardian. Available online at: https:// www.theguardian.com/commentisfree/2020/jul/28/pandemic-era-rainforest- deforestation-exploitation-wildlife-disease (accessed July 7, 2021). Daszak, P. (2020). We are entering an era of pandemics—it will end only when we protect the rainforest. The Guardian. Available online at: https:// www.theguardian.com/commentisfree/2020/jul/28/pandemic-era-rainforest- Koch, M. (2020). References Structure, action and change: a Bourdieusian perspective on the preconditions for a degrowth transition. Sustain. Sci. Pract. Policy 16, 4–14. doi: 10.1080/15487733.2020.1754693 Lambrou, Y., and Piana, G. (2006). Gender: The Missing Component of the Response to Climate Change. Rome: FAO, 1–58. Davis, S. J., Liu, Z., Deng, Z., Zhu, B., Ke, P., Sun, T., et al. (2022). Emissions rebound from the COVID-19 pandemic. Nat. Clim. Change 2022, 1–3. doi: 10.1038/s41558-022-01332-6 Lau, J. D., Kleiber, D., Lawless, S., and Cohen, P. J. (2021). Gender equality in climate policy and practice hindered by assumptions. Nat. Clim. Change 11, 186–192. doi: 10.1038/s41558-021-00999-7 Dobson, A. P., Pimm, S. L., Hannah, L., Kaufman, L., Ahumada, J. A., Ando, A. W., et al. (2020). Ecology and economics for pandemic prevention. Science 369, 379–381. doi: 10.1126/science.abc3189 Le Quéré, C., Jackson, R. B., Jones, M. W., Smith, A. J., Abernethy, S., Andrew, R. M., et al. (2020). Temporary reduction in daily global CO2 emissions during the COVID-19 forced conﬁnement. Nat. Clim. Change 10, 647–653. doi: 10.1038/s41558-020-0797-x Dow, K., Berkhout, F., Preston, B. L., Klein, R. J., Midgley, G., and Shaw, M. R. (2013). Limits to adaptation. Nat. Clim. Change 3, 305–307. doi: 10.1038/nclimate1847 Lee, S. Y., and Zusman, E. (2018). “Participatory climate governance in Southeast Asia: Lessons learned from gender-responsive climate mitigation,” in Routledge Handbook of Climate Justice, eds T. Jafry, K. Helwig, and M. Mikulewicz (London: Routledge), 393–404. doi: 10.4324/9781315537689-29 Eizenberg, E., and Jabareen, Y. (2017). Social sustainability: a new conceptual framework. Sustainability 9, 68. doi: 10.3390/su9010068 Ergas, C., Greiner, P. T., McGee, J. A., and Clement, M. T. (2021). Does gender climate inﬂuence climate change? The multidimensionality of gender equality and its countervailing eﬀects on the carbon intensity of well-being. Sustainability 13, 3956. doi: 10.3390/su13073956 Liu, P. R., and Raftery, A. E. (2021). Country-based rate of emissions reductions should increase by 80% beyond nationally determined contributions to meet the 2◦C target. Commun. Earth Environ. 2, 1–10. doi: 10.1038/s43247-021-00097-8 Ergas, C., and York, R. (2012). Women’s status and carbon dioxide emissions: a quantitative cross-national analysis. Social Sci. Res. 41, 965–976. doi: 10.1016/j.ssresearch.2012.03.008 Liu, Z., Ciais, P., Deng, Z., Lei, R., Davis, S. J., Feng, S., et al. (2020). Near-real-time monitoring of global CO 2 emissions reveals the eﬀects of the COVID-19 pandemic. Nat. Commun. 11, 1–12. doi: 10.1038/s41467-020-20254-5 FitzGibbon, J., and Mensah, K. O. (2012). References Alston, M. (2014). “Gender mainstreaming and climate change,” in Women’s Studies International Forum, Vol. 47 (Oxford: Pergamon), 287–294. doi: 10.1016/j.wsif.2013.01.016 Barnett, J. (2020). Global environmental change II: political economies of vulnerability to climate change. Prog. Human Geogr. 44, 1172–1184. doi: 10.1177/0309132519898254 Beauvoir, S. D. (1949). Le deuxième sexe. Paris: Gallimard. Beauvoir, S. D. (1949). Le deuxième sexe. Paris: Gallimard. Amnesty International (2019). Protests Around the World Explained. Available online at: https://www.amnesty.org/en/latest/news/2019/10/protests-around-the-world- explained/ (accessed August 30, 2021). Bee, B., Biermann, M., and Tschakert, P. (2013). “Gender, development, and rights-based approaches: lessons for climate change adaptation and adaptive social protection,” in Research, Action and Policy: Addressing the Gendered Impacts of Climate Change, eds M. Alston, and K. Whittenbury (Dordrecht: Springer), 95–108. doi: 10.1007/978-94-007-5518-5_7 Anderson, K., and Bows, A. (2012). A new paradigm for climate change. Nat. Clim. Change 2, 639–640. doi: 10.1038/nclimate1646 Anderson, K., Quéré, C. L., and Mclachlan, C. (2014). Radical emission reductions: the role of demand reductions in accelerating full decarbonization. Carbon Manage. 5, 321–323. doi: 10.1080/17583004.2014.1055080 Beer, C. (2009). Democracy and gender equality. Stud. Comp. Int. Dev. 44, 212. doi: 10.1007/s12116-009-9043-2 Beer, C. (2009). Democracy and gender equality. Stud. Comp. Int. Dev. 44, 212. doi: 10.1007/s12116-009-9043-2 Bryman, A. (2016). Social Research Methods. Oxford, Oxford University Press. Bryman, A. (2016). Social Research Methods. Oxford, Oxford University Press. Andrijevic, M., Cuaresma, J. C., Lissner, T., Thomas, A., and Schleussner, C. F. (2020). Overcoming gender inequality for climate resilient development. Nat. Communi. 11, 1–8. doi: 10.1038/s41467-020-19856-w Butler, J. (1988). Performative acts and gender constitution: an essay in phenomenology and feminist theory. Theatre J. 40, 519–531. doi: 10.2307/3207893 Butler, J. (1988). Performative acts and gender constitution: an essay in phenomenology and feminist theory. Theatre J. 40, 519–531. doi: 10.2307/3207893 Butt, M. N., Shah, S. K., and Yahya, F. A. (2020). Caregivers at the frontline of addressing the climate crisis. Gender Dev. 28, 479–498. doi: 10.1080/13552074.2020.1833482 Butt, M. N., Shah, S. K., and Yahya, F. A. (2020). Caregivers at the frontline of addressing the climate crisis. Gender Dev. 28, 479–498. doi: 10.1080/13552074.2020.1833482 Badoux, C. (1974). “Françoise d’Eaubonne,” in Le Féminisme ou la Mort, Vol. 4, ed P. Horay (Paris: Les cahiers du GRIF), 66–67. Butt, M. N., Shah, S. K., and Yahya, F. A. (2020). Caregivers at the frontline of addressing the climate crisis. Gender Dev. 28, 479–498. doi: 10.1080/13552074.2020.1833482 14 Frontiers in Climate frontiersin.org Rainard et al. Rainard et al. References Climate change as a wicked problem: an evaluation of the institutional context for rural water management in Ghana. SAGE Open 2, 215824401244848. doi: 10.1177/2158244012448487 MacGregor, S. (2010). ’Gender and climate change’: from impacts to discourses. J. Indian Ocean Region 6, 223–238. doi: 10.1080/19480881.2010.536669 MacGregor, S. (2014). Only resist: feminist ecological citizenship and the post-politics of climate change. Hypatia 29, 617–633. doi: 10.1111/hypa.12065 Ford, J. D., Keskitalo, E. C. H., Smith, T., Pearce, T., Berrang-Ford, L., Duerden, F., and Smit, B. (2010). Case study and analogue methodologies in climate change vulnerability research. Wiley Interdiscip. Rev. Clim. Change 1, 374–392. doi: 10.1002/wcc.48 MacGregor, S. (2021). Making matter great again? Ecofeminism, new materialism and the everyday turn in environmental politics. Environ. Politics 2021, 1–20. doi: 10.1080/09644016.2020.1846954 Forster, P. M., Forster, H. I., Evans, M. J., Gidden, M. J., Jones, C. D., Keller, C. A., et al. (2020). Current and future global climate impacts resulting from COVID-19. Nat. Clim. Change 10, 913–919. doi: 10.1038/s41558-020-0883-0 Maguire, M., and Delahunt, B. (2017). Doing a thematic analysis: a practical, step-by- step guide for learning and teaching scholars. Ireland J. Higher Educ. 9. Füssel, H. M. (2007). Vulnerability: a generally applicable conceptual framework for climate change research. Glob. Environ. Change 17, 155–167. doi: 10.1016/j.gloenvcha.2006.05.002 Mason, J. (2018). Qualitative Researching. London: Sage. Mavisakalyan, A., and Tarverdi, Y. (2019). Gender and climate change: do female parliamentarians make diﬀerence? Eur. J. Polit. Econ. 56, 151–164. doi: 10.1016/j.ejpoleco.2018.08.001 Gaard, G. (2017). Critical Ecofeminism. Pennsylvania: Lexington Books. doi: 10.4324/9781315640051-57 McGee, J. A., Greiner, P. T., Christensen, M., Ergas, C., and Clement, M. T. (2020). Gender inequality, reproductive justice, and decoupling economic growth and emissions: a panel analysis of the moderating association of gender equality on the relationship between economic growth and CO2 emissions. Environ. Sociol. 6, 254–267. doi: 10.1080/23251042.2020.1736364 Global Gender and Climate Alliance. (2016). Gender and Climate Change: A Closer Look at Existing Evidence. New York, NY: Global Gender and Climate Alliance. Gough, I. (2017). Climate Capitalism: Emissions, Inequality, Green Growth: Climate Change, Capitalism and Sustainable Wellbeing. Cheltenham: Edward Elgar Publishing. Happy Planet Index (2016). The Happy Planet Index, 2016: A Global Index of Sustainable Wellbeing. Available online at: https://static1.squarespace.com/static/ 5735c421e321402778ee0ce9/t/57e0052d440243730fdf03f3/1474299185121/Brieﬁng+ paper+-+HPI+2016.pdf (accessed July 23, 2021). Meadows, D. H. (2008). Thinking in Systems: A Primer. Chelsea: Chelsea Green Publishing. Merchant, C. (1980). The Death of Nature: Women, Ecology, and the Scientiﬁc Revolution. Washington, DC: Georgetown University, 164. Haraway, D. (2020). Frontiers in Climate References Climate science is supporting lawsuits that could help save the world. Nature 597, 169–171. doi: 10.1038/d41586-021-02424-7 O’Brien, K. (2018). Is the 1.5 C target possible? Exploring the three spheres of transformation. Curr. Opin. Environ. Sustain. 31, 153–160. doi: 10.1016/j.cosust.2018.04.010 Schwartz, S. H., and Rubel-Lifschitz, T. (2009). Cross-national variation in the size of sex diﬀerences in values: eﬀects of gender equality. J. Personal. Soc. Psychol. 97, 171. doi: 10.1037/a0015546 O’Brien, K., Eriksen, S., Nygaard, L. P., and Schjolden, A. N. E. (2007). Why diﬀerent interpretations of vulnerability matter in climate change discourses. Clim. Policy 7, 73–88. doi: 10.1080/14693062.2007.9685639 Shiva, V. (2005). Earth Democracy: Justice, Sustainability and Peace. London: Zed Books. doi: 10.5040/9781350219755 O’Brien, K., Hayward, B., and Berkes, F. (2009). Rethinking social contracts: building resilience in a changing climate. Ecol. Soc. 14, 12. doi: 10.5751/ES-03027-140212 Shove, E. (2010). Beyond the ABC: climate change policy and theories of social change. Environ. Plan. A 42, 1273–1285. doi: 10.1068/a42282 Siddique, H. (2021). Legal experts worldwide draw a ’historic’ deﬁnition of ecocide. The Guardian. Available online at: https://www.theguardian.com/environment/2021/jun/22/ legal-experts-worldwide-draw-up-historic-deﬁnition-of-ecocide (accessed August 29, 2021). O’Brien, K., Leichenko, R., Kelkar, U., Venema, H., Aandahl, G., Tompkins, H., et al. (2004). Mapping vulnerability to multiple stressors: climate change and globalization in India. Glob. Environ. Change 14, 303–313. doi: 10.1016/j.gloenvcha.2004.01.001 O’Brien, K., and Sygna, L. (2013). “Responding to climate change: the three spheres of transformation,” in Proceedings of Transformation in a Changing Climate, vol. 16, 23. Steﬀen, W., Richardson, K., Rockström, J., Cornell, S. E., Fetzer, I., Bennett, E. M., et al. (2015). Planetary boundaries: guiding human development on a changing planet. Science 347, 6223. doi: 10.1126/science.1259855 O’Brien, K. L. (2016). Climate change and social transformations: is it time for a quantum leap? Wiley Interdiscip. Rev. Clim. Change 7, 618–626. doi: 10.1002/wcc.413 Stern, P. C., and Dietz, T. (2015). IPCC: social scientists are ready. Nature 521, 161–161. doi: 10.1038/521161a Oxfam (2008). Business Brieﬁng on Unpaid Care and Domestic Work. Available online at: https://oxfamilibrary.openrepository.com/bitstream/handle/10546/ 620764/bp-unpaid-care-domestic-work-business-040619-en.pdf;jsessionid$= $70E48646F7CE3B75206A955B1D11DA7C?sequence$=$3 (accessed August 08, 2021). Steves, F., Treisman, D., and Teytelboym, A. (2011). The Political Economy of Climate Change Policy in the Transition Region. The Low Carbon Transition. Brussels: European Bank for Reconstruction and Development (EBRD). Oxford English Dictionary. (1989). s.v. Radical. Available online at: https://www.oed. com/oed2/00196105 (accessed August 09, 2021). Temple, B., and Edwards, R. (2002). Interpreters/translators and cross- language research: reﬂexivity and border crossings. Int. J. Qual. Methods 1, 1–12. References “Situated knowledges: The science question in feminism and the privilege of partial perspective,” in Feminist Theory Reader (Routledge), 303–310. Merchant, C. (1981). Earthcare: women and the environment. Environ. Sci. Policy Sustain. Dev. 23, 6–40. doi: 10.1080/00139157.1981.99 33143 Harvey, D. (2013). The enigma of capital and the crisis of capitalism. Estado Comunes 1, 1. doi: 10.37228/estado_comunes.v1.n1.2013.9 Miller, T. R., Baird, T. D., Littleﬁeld, C. M., Koﬁnas, G., Chapin, I. I. I., F. S., and Redman, C. L. (2008). Epistemological pluralism: reorganizing interdisciplinary research. Ecol. Soc. 13, e246. doi: 10.5751/ES-02671-130246 Herzog, T. (2009). World Greenhouse Gas Emissions in 2005. Washington, DC: World Resources Institute. IPCC (2018) “Summary for policymakers,” in Global Warming of 1.5◦C. An IPCC Special Report on the Impacts of Global Warming of 1.5◦C Above Pre-Industrial Levels and Related Global Greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development, and Eﬀorts to Eradicate Poverty, eds. V. Masson-Delmotte, P. Zhai, H.-O. P?rtner, D. Roberts, J. Skea, P. R. Shukla (Cambridge: Cambridge University Press). Moser, C. A., Kalton, G., and Oakley, A. (1981). “Interviewing women: a contradiction in terms,” in Doing Feminist Research, (London: Routledge). Moser, S. C., and Ekstrom, J. A. (2010). A framework to diagnose barriers to climate change adaptation. Proc. Natl. Acad. Sci. 107, 22026–22031. doi: 10.1073/pnas.1007887107 IPCC (2022) “Summary for policymakers,” in Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, eds H.-O. P?rtner, D. C. Nightingale, A. J. (2017). Environment and Gender. The International Encyclopedia of Geography. Wiley: New York, NY. doi: 10.1002/9781118786352.wbie g0667 15 frontiersin.org Rainard et al. Rainard et al. 10.3389/fclim.2023.946712 10.3389/fclim.2023.946712 Nugent, C., and Shandra, J. M. (2009). State environmental protection eﬀorts, women’s status, and world polity: a cross-national analysis. Organ. Environ. 22, 208–229. doi: 10.1177/1086026609338166 Rorty, R. (1982). Consequences of Pragmatism: Essays, 1972–1980. Minneapolis, MN: University of Minnesota Press. Sarkodie, S. A., and Strezov, V. (2019). Eﬀect of foreign direct investments, economic development and energy consumption on greenhouse gas emissions in developing countries. Sci. Total Environ. 646, 862–871. doi: 10.1016/j.scitotenv.2018. 07.365 Oakley, A. (2016). Interviewing women again: power, time and the gift. Sociology 50, 195–213. doi: 10.1177/0038038515580253 O’Brien, K. (2012). Global environmental change II: From adaptation to deliberate transformation. Prog. Human Geogr. 36, 667–676. doi: 10.1177/0309132511425767 Schiermeier, Q. (2021). References doi: 10.1177/160940690200100201 Pearse, R. (2017). Gender and climate change. Wiley Interdiscip. Rev. Clim. Change 8, e451. doi: 10.1002/wcc.451 Thomas, K., Hardy, R. D., Lazrus, H., Mendez, M., Orlove, B., Rivera-Collazo, I., et al. (2019). Explaining diﬀerential vulnerability to climate change: a social science review. Wiley Interdiscip. Rev. Clim. Change 10, e565. doi: 10.1002/wcc.565 Pelling, M. (2010). Adaptation to Climate Change: From Resilience to Transformation. London: Routledge. doi: 10.4324/9780203889046 Pelling, M., O’Brien, K., and Matyas, D. (2015). Adaptation and transformation. Clim. Change 133, 113–127. doi: 10.1007/s10584-014-1303-0 Thompson-Hall, M., Carr, E. R., and Pascual, U. (2016). Enhancing and expanding intersectional research for climate change adaptation in agrarian settings. Ambio 45, 373–382. doi: 10.1007/s13280-016-0827-0 Phillips, J. (2017). Everywoman: One Woman’s Truth About Speaking the Truth. Fremont: Random House. Tracy, S. J. (2019).Qualitative Research Methods: Collecting Evidence, Crafting Analysis, Communicating Impact. New York, NY: John Wiley and Sons. Pielke, R., Prins, G., Rayner, S., and Sarewitz, D. (2007). Climate change 2007: lifting the taboo on adaptation. Nature. 445, 597–598. doi: 10.1038/445597a Tschakert, P. (2007). Views from the vulnerable: understanding climatic and other stressors in the Sahel. Glob. Environ. Change 17, 381–396. doi: 10.1016/j.gloenvcha.2006.11.008 Plumwood, V. (1997). Babe: the tale of the speaking meat-part I. Anim. Issues 1, 3. Plumwood, V. (2002). Feminism and the Mastery of Nature. London: Routledge. doi: 10.4324/9780203006757 Tschakert, P. (2012). From impacts to embodied experiences: tracing political ecology in climate change research. Geogr. Tidsskrift-Danish J. Geogr. 112, 144–158. doi: 10.1080/00167223.2012.741889 Prügl, E. (2010). Feminism and the postmodern state: gender mainstreaming in European rural development. J. Women Cult. Soc. 35, 447–475. doi: 10.1086/605484 Tschakert, P., van Oort, B., St. Clair, A. L., and LaMadrid, A. (2013). Inequality and transformation analyses: a complementary lens for addressing vulnerability to climate change. Clim. Dev. 5, 340–350 doi: 10.1080/17565529.2013.8 28583 Rahman, H. M., and Hickey, G. M. (2020). An analytical framework for assessing context-speciﬁc rural livelihood vulnerability. Sustainability 12, 5654. doi: 10.3390/su12145654 Rao, N. D. and Min, J. (2018). Decent living standards: material prerequisites for human wellbeing. Soc. Indic. Res. 138, 225–244. doi: 10.1007/s11205-017-1650-0 UN NEWS (2021). COP26 Closes With ”Compromise” Deal on Climate, But it’s Not Enough, Says UN Chief. Available online at: https://news.un.org/en/story/2021/11/ 1105792 (accessed November 30, 2021). Rapley, T. (2014). “Sampling strategies in qualitative research,” in The SAGE Handbook of Qualitative Data Analysis (London: Sage), 49–63. doi: 10.4135/9781446282243.n4 UNDP (2020a). Gender Inequality Index. Available online at: http://hdr.undp.org/en/ content/gender-inequality-index-gii (accessed May 19, 2021). References Rapley, T. J. (2001). The art (fulness) of open-ended interviewing: some considerations on analysing interviews. Qual. Res. 1, 303–323. doi: 10.1177/146879410100100303 UNDP (2020b). Global Institutions Unite for a Green and Fair COVID Recovery. Available online at: https://www.undp.org/content/undp/en/home/news-centre/news/ 2020/global-institutions-unite-around-key-actions-for-green-and-fair-.html(accessed July 28, 2021). Raworth, K. (2017). Doughnut Economics: Seven Ways to Think Like a 21st-Century Economist. Chelsea: Chelsea Green Publishing. Rayner, S. (2012). Uncomfortable knowledge: the social construction of ignorance in science and environmental policy discourses. Econ. Soc. 41, 107–125. doi: 10.1080/03085147.2011.637335 UNFCCC (2021). Climate Change Leads to More Extreme Weather Events but Early Warnings Saves Lives. Available online at: https://unfccc.int/news/climate-change-leads- to-more-extreme-weather-but-early-warnings-save-lives (accessed August 28, 2021). Remteng, C., Nkem, J., Mofor, L., and Murombedzi, J. (2021). Gender in the nationally determined contributions of African countries: a way forward for eﬀective implementation of adaptation and mitigation strategies. Ecofemin. Clim. Change. doi: 10.1108/EFCC-01-2021-0001 UNSDG (2015). The 17 Goals. Available online at: https://sdgs.un.org/fr/goals (accessed May 03, 2021). UNWOMEN (2021). 12 Critical Areas. Available online at: https://www.unwomen.org/ en/news/in-focus/csw59/feature-stories (accessed July 29, 2021). Resurrección, B. P. (2013). “Persistent women and environment linkages in climate change and sustainable development agendas,” in Women’s Studies International Forum, Vol. 40. (Oxford: Pergamon). doi: 10.1016/j.wsif.2013.03.011 Urry, J. (2015). Climate change and society. In Why the social sciences matter (45-59). Palgrave Macmillan, London. doi: 10.1057/9781137269 928_4 Resurrección, B. P., Bee, B. A., Dankelman, I., Park, C. M. Y., Haldar, M., and McMullen, C. P. (2019). Gender-Transformative Climate Change Adaptation: Advancing Social Equity. Paper commissioned by the Global Commission on Adaptation (GCA). Wendling, Z. A., Emerson, J. W., de Sherbinin, A., Esty, D. C., et al. (2020). 2020 Environmental Performance Index. New Haven, CT: Yale Center for Environmental Law and Policy. Available online at: epi.yale.edu (accessed 22 May 2021). Rhoten, D., and Pﬁrman, S. (2007). Women in interdisciplinary science: exploring preferences and consequences. Res. Policy 36, 56–75. doi: 10.1016/j.respol.2006.08.001 Westholm, L., and Arora-Jonsson, S. (2018). What room for politics and change in global climate governance? Addressing gender in co-beneﬁts and safeguards. Environ. Polit. 27, 917–938. doi: 10.1080/09644016.2018.14 79115 Rodriguez, F. and Rodrik, D. (2001). ’Trade Policy and Economic Growth: A Skeptic’s Guide to the Cross-national Evidence’, in B. S. Bernanke and K. Rogoﬀ(eds), NBER Macroeconomics Annual 2000, Cambridge: MIT Press doi: 10.1086/654419 Frontiers in Climate 16 frontiersin.org Rainard et al. Rainard et al. 10.3389/fclim.2023.946712 10.3389/fclim.2023.946712 World Economic Forum (2020b). The World Bank’s 2020 Country Classiﬁcations Explained. Rainard et al. References Available online at: https://www.weforum.org/agenda/2020/08/ world-bank-2020-classiﬁcations-low-high-income-countries/ (accessed July 6, 2021). Wittman, A. B. (2010). What Happens to the Radical Potential of Gender Mainstreaming? Problems of Implementation and Institutionalisation in Gendered Organisations Edimburgh: Edimburgh Research Archive (ERA). World Bank (2010). CO2 Emissions (Metric Tons Per Capita). Available online at: https://data.worldbank.org/indicator/EN.ATM.CO2E.PC (accessed August 26, 2021). World Bank (2010). CO2 Emissions (Metric Tons Per Capita). Available online at: https://data.worldbank.org/indicator/EN.ATM.CO2E.PC (accessed August 26, 2021). World Economic Forum (2021). Global Gender Gap Report 2021. Available online at: https://www.weforum.org/reports/ ab6795a1-960c-42b2-b3d5-587eccda6023 (accessed April 27, 2021). World Economic Forum (2021). Global Gender Gap Report 2021. Available online at: https://www.weforum.org/reports/ ab6795a1-960c-42b2-b3d5-587eccda6023 (accessed April 27, 2021). World Bank (2017). CO2 Emissions (Metric Tons Per Capita). Available online at: https://data.worldbank.org/indicator/EN.ATM.CO2E.PC (accessed August 26, 2021). World Bank (2017). CO2 Emissions (Metric Tons Per Capita). Available online at: https://data.worldbank.org/indicator/EN.ATM.CO2E.PC (accessed August 26, 2021). World Economic Forum (2020a). Global Gender Gap Report 2020. Available online at: https://www.weforum.org/reports/gender-gap-2020-report-100-years-pay- equality (accessed May 24, 2021). Worms, F., and Butler, J. (2021). Le vivable et l’invivable. Paris: Presses Universitaires de France. 17 frontiersin.org Frontiers in Climate Frontiers in Climate frontiersin.org
https://openalex.org/W2922123106	https://europepmc.org/articles/pmc6418266?pdf=render	English	null	Effects of Neonicotinoid Insecticides on Physiology and Reproductive Characteristics of Captive Female and Fawn White-tailed Deer	Scientific reports	2,019	cc-by	10,950	Effects of Neonicotinoid Insecticides on Physiology and Reproductive Characteristics of Captive Female and Fawn White- tailed Deer Received: 19 September 2018 Accepted: 22 February 2019 Published: xx xx xxxx Elise Hughes Berheim1, Jonathan A. Jenks 1, Jonathan G. Lundgren2, Eric S. Michel1, Daniel Grove3 & William F. Jensen3 Over the past decade, abnormalities have been documented in white-tailed deer (Odocoileus virginianus) in west-central Montana. Hypotheses proposed to explain these anomalies included contact with endocrine disrupting pesticides, such as imidacloprid. We evaluated the effects of imidacloprid experimentally at the South Dakota State University Wildlife and Fisheries Captive Facility where adult white-tailed deer females and their fawns were administered aqueous imidacloprid (an untreated control, 1,500 ng/L, 3,000 ng/L, and 15,000 ng/L). Water consumption, thyroid hormone function, behavioral responses, and skull and jawbone measurements were compared among treatments. Additionally, liver, spleen, genital, and brain imidacloprid concentrations were determined by an enzyme-linked immunosorbent assay (ELISA). Results indicated that 1) control deer consumed more water than treatment groups, 2) imidacloprid was present in the organs of our control group, indicating environmental contamination, 3) as imidacloprid increased in the spleen, fawn survival, thyroxine levels, jawbone lengths, body weight, and organ weights decreased, 4) adult female imidacloprid levels in the genitals were negatively correlated with genital organ weight and, 5) behavioral observations indicated that imidacloprid levels in spleens were negatively correlated with activity levels in adult females and fawns. Results demonstrate that imidacloprid has direct effects on white-tailed deer when administered at field–relevant doses. Neonicotinoids are a broad-spectrum insecticide predominantly used as seed dressings on major field crops and are additionally used as sprays in crop production, in managing household pests, and in deterring pests on domesticated animals1. Neonicotinoids derive their toxicity from agonistically binding to nicotinic acetylcholine receptors (nAChRs) on the post-synaptic nerve membrane and firing nerve impulses in a manner that is uncon- trollable and uninterrupted1–7. Neonicotinoids were first developed in the 1990s8, gained popularity from 2003- 20119, and are now the most widely used pesticides in the world10. y p Popularity of neonicotinoids is due to their advertised high toxicity to insects and low toxicity to vertebrates1. Additionally, neonicotinoids have gained popularity by their ability to systemically protect plants while reducing application inputs for farmers10. In 2014, over 3.3 million kg of neonicotinoids (including acetamiprid, clothiani- din, dinotefuran, imidacloprid, thiacloprid, and thiamethoxam) were used in the United States (excluding Hawaii and Alaska) on pasture hay, alfalfa, orchards, grapes, rice, vegetables, fruit, cotton, wheat, soybeans, corn, and other crops11. www.nature.com/scientificreports www.nature.com/scientificreports www.nature.com/scientificreports Received: 19 September 2018 Accepted: 22 February 2019 Published: xx xx xxxx Methods h Our research study was conducted at the South Dakota State University Wildlife and Fisheries Captive Research Facility in Brookings County, South Dakota (44°20′N, 96°47′W). This facility housed white-tailed deer (begin- ning in about 1998) on 4 ha; the facility is double fenced with 3-m high woven wire. The facility is situated adja- cent to agricultural fields normally planted to corn or soybeans, and is surrounded by a shelterbelt of trees. Mean annual temperatures were 7.4 °C (ranged from −28.8 °C and 34.4 °C) and 7.8 °C (−35 °C to 32.8 °C) in 2015 and 2016, respectively. Additionally, daily annual precipitation was 0.18 cm (0.03 cm to 5.2 cm) and 0.2 cm (from 0.3 cm to 7 cm) in 2015 and 2016, respectively. Finally, daily annual snowfall was 0.3 cm (0.3–17.8 cm) and 0.3 cm (0.3–11.4 cm) in 2015 and 2016, respectively24. y Twenty adult white-tailed deer were randomly selected for the experiment and bred; parturition occurred in May and June of each experimental year. Adult females were separated into four treatments (care was taken to separate adult females so that age and weight were uniformly distributed): control (n = 4), low (n = 4), moderate (n = 5), and high (n = 7) (the moderate and high treatment groups had a larger sample size to reduce the standard error for our response variable). Deer were housed in pens of similar size (control = 130 m2/deer, low = 175 m2/ deer, moderate = 123 m2/deer, high = 112 m2/deer in 2015 and 165 m2/deer in 2016). All deer were fed rations that included soy hulls, shelled corn, and alfalfa hay ad libitum. Adult females were administered aqueous imidacloprid (Product # 37984, Sigma Aldrich St. Louis, MO) from May until October to mimic free water availability within the Dakotas. We added 0 ng/L, 1,500 ng/L, 3,000 ng/L, and 15,000 ng/L of imidacloprid to the control, low, moderate, and high treatments, respectively. The low and moderate concentrations were similar to wetland levels found in groundwater in Wisconsin (detected in 24% of the groundwater sample and ranged from 260–3,340 ng/L); however, they were greater than levels found in rural streams in Iowa (detected in 23% of streams sampled and ranged from <2–42.7 ng/L) or in Canadian (Saskatchewan) wetlands (detected in 12% of wetlands and ranged from 7.1–256 ng/L)25. Effects of Neonicotinoid Insecticides on Physiology and Reproductive Characteristics of Captive Female and Fawn White- tailed Deer In South Dakota, more than 94% of U.S. corn and at least 50% of U.S. soybeans12 are treated with one of the three neonicotinoids: clothianidin, imidacloprid, or thiamethoxam13–15. Neonicotinoids are widely found in the environment for numerous reasons. First, only a small quantity (2–20%) of the seed-coated insecticide is absorbed by the developing plant; the remainder is released into the environment through leaching, drainage, run-off, or snowmelt16,17. Neonicotinoids are highly water soluble18; 1Department of Natural Resource Management, South Dakota State University, Brookings, SD, USA. 2Ecdysis Foundation, Estelline, SD, 57234, USA. 3North Dakota Game and Fish Department, Bismarck, ND, USA. Correspondence and requests for materials should be addressed to J.A.J. (email: jonathan.jenks@sdstate.edu) Scientific Reports \| (2019) 9:4534 \| https://doi.org/10.1038/s41598-019-40994-9 1 www.nature.com/scientificreports/ they are prevalent in diverse water bodies in the United States, Canada, Australia, Europe, and Asia17. Moreover, under the right conditions, neonicotinoids can persist in the soil, sometimes for many years1. Finally, untreated plants associated with cropland are often contaminated by neonicotinoids due to the systemic nature of these chemicals19. The widespread use of neonicotinoids provides numerous opportunities for exposure to non-target, beneficial species via the water, soil, and contaminated plant tissues.fif i p p In addition to their documented effects on beneficial insects, neonicotinoids adversely affect non-target verte- brates as well, including rats (Rattus norvegicus: reduced sperm production, reduced offspring weight, increased abortions, skeletal abnormalities, thyroid lesions, atrophy of retina, reduced weight gain of offspring, oxidative stress, and neurobehavioral deficits), mice (Mus musculus: suppressed cell-mediated immune response and prom- inent histopathological alterations in spleen and liver), rabbits (Sylvilagus sp: increased frequency of miscar- riage and premature births), red-legged partridges (Alectoris rufa: reduced adult and chick survival, fertilization rate, and immune response), Nile tilapia (Oreochromis niloticus: extensive disintegration of testicular tissue and changes to gonads), Medaka (Oryzias latipes: juvenile stress led to ectoparasite infestation), and black-spotted pond frogs (Rana nigromaculata: DNA damage at very low concentrations)20. To our knowledge, no information is available on potential effects on large mammals, such as white-tailed deer (Odocoileus virginianus). pf g ( g ) Over the past decade, morphological and developmental abnormalities have been documented in white-tailed deer in west-central Montana. Of 254 male deer of various ages, 67% showed genital developmental abnormali- ties such as mispositioned and undersized scrota and ectopic testes21; these abnormalities were documented for accident-killed and injured cervids21. Effects of Neonicotinoid Insecticides on Physiology and Reproductive Characteristics of Captive Female and Fawn White- tailed Deer Hoy et al.21 suggested that genital anomalies could be caused by endocrine disrupting pesticides but stated that, based on the information available, no cause and effect could be justified. In addition, from 2000 to 2009, brachygnathia superior (i.e., mandibular prognathia or underbite) increased from 0% to 70% for white-tailed deer that were collected from west-central (accident killed) and throughout (hunter harvested) Montana22. Underbite is a characteristic of congenital hypothyroidism, which has been documented in South Dakota23, and is nearly always associated with fetal thyroid hormone function22, but the cause has not been empirically determined for this observation. p y We hypothesized that imidacloprid would have sub-lethal and potentially lethal effects on adult female and fawn white-tailed deer. We predicted that adult females, especially in the high treatment group, would have reduced Free Triiodothyronine (FT3) and Free Thyroxine (FT4) levels, presence of imidacloprid in milk, and reduced activity associated with exposure to imidacloprid. We also predicted that fawns exposed to imidacloprid at relatively high treatment levels would have abnormal genital organs, lowered FT3 and FT4 levels, reduced activity, and a high prevalence of under bite. Methods h Our high treatment was intended to invoke an effect and therefore, was much greater than documented in free water. Deer were provided with a 60.6 L tub that contained 37.8 L of water treated with the appropriate amount of imidacloprid depending on the group (control, low, moderate, high). Deer consumed the water treated with imidacloprid ad libitum. Water levels were checked daily and refilled with the appropriate imidacloprid treated water when empty or less than 3 cm from the bottom (every 1–2 d) of containers. When refilling occurred, each tub was rinsed thoroughly and excess water was poured into 189 L tubs provided by the SDSU Environmental Health and Safety office. fi Fawns born to adult females in the study were included in our experiment. On the day of parturition, each fawn was handled minimally with gloves to determine body mass and sex; fawns also were fitted with ear tags. To mimic natural water availability, fawns were not prevented from consuming the imidacloprid in water. Facilities and techniques for research were approved by the South Dakota State University Institutional Animal Care and Use Committee (IACUC number 15–055 A) and followed guidelines by the American Society of Mammologists26. Solution consumed. During experiments, water tubs housing aqueous imidacloprid were weighed daily to etermine the volume of water consumed per group. Analysis of variance (ANOVA) was performed to compare Scientific Reports \| (2019) 9:4534 \| https://doi.org/10.1038/s41598-019-40994-9 2 www.nature.com/scientificreports/ water consumption among treatment and control groups with date used as a covariate. To detect imidacloprid concentrations as the imidacloprid water was consumed, a 3-d experiment was conducted. On day 1, the appro- priate treatment or control group concentrations were created in five, 63 L galvanized tubs. On day 2, 50% of the water was removed from all tubs. On the third day, nearly all water was removed from the tubs, leaving only enough water to coat the bottom of tubs. Samples (15 mL) were collected daily from each tub. This procedure mimicked water level reductions due to deer consumption. Imidacloprid samples were analyzed using ELISA (enzyme-linked immunosorbent assay; Abraxis, Warminister, PA; See Section 4.7 for procedures). Collection of blood samples. Blood samples were collected from adult females and fawns in treatments using BD Vacutainer Serum tubes (Becton, Dickinson, and Company, Franklin, NJ). Methods h We collected up to 12 mL of blood from the saphenous vein approximately monthly during treatments while deer were held in a chute (Priefert Wildlife Equipment Deer Chute; Priefert®, Mount Pleasant, TX). We collected blood samples (1–10cc from the saphenous or jugular) from fawns twice; 1 wk after parturition and at approximately 5 mo of age. Blood samples were refrigerated until processed to extract serum (1 h to 2 d). Upon reaching the lab, blood samples were centrifuged (Ultra-8V; LW Scientific, Lawrenceville, GA) for 15 min at 280 × g to separate serum for testing FT3 (free triiodothyronine) and FT4 (free thyroxine) hormones.l y y FT3 and FT4 thyroid hormones reflect the ability of the deer to utilize body fat reserves, regulate basal meta- bolic rate, and control thermal regulation27. Serum from blood samples was transferred to labeled 1.5 mL micro- centrifuge tubes (BrandTech® Scientific Inc., Essex, CT), sealed, and frozen at −20 °C. These samples were then overnighted to the Diagnostic Center for Population and Animal Health at Michigan State University (Lansing, MI) for FT3 and FT4 testing. These assays were performed with commercially available solid-phase radioim- munoassay kits (FREE T3 Solid Phase Component System and Free T4 Solid Phase Component System, MP Biomedicals Diagnostics Division Orangeburg NY 10962). The volumes of sample, assay standards, and radioli- gand were used according to the manufacturer’s protocol. Incubation times for free T3 and free T4 assays were 2.5 h and 1.5 h, respectively, at 37 °C. Behavioral Observations. Focal sampling of behavioral observations were collected on treatment and control groups prior to death. Behaviors included eat, lay, lay/groom, lay/ruminate, stand/ruminate, run, stand, stand/groom, stand/nurse, and walk; for fawns, the behaviors lay/curl and lay/sleep also were recorded. Observations were conducted in 1 h blocks using an ethogram28. During time blocks, occurrences of behaviors were tallied and the duration of each behavior (in s) was recorded. Observations occurred between 6:00 and 16:00. In each session, an adult female or fawn was randomly chosen (without replacement) from each treatment and control group (n = 28 h for 2016 fawns and n = 21 h for adult females). Necropsies. All deer in the experiment (adult females and fawns) were euthanized and subsequently necrop- sied using IACUC approved protocols. Fawns were euthanized at the end of each field season (October 2015 and 2016) and adult females were euthanized at the completion of the study (October 2016). Methods h The standard curve on the ELISA plate contained 25 µL control organ in solution with 25 µL of the stock solution of imidacloprid, creating eight wells with concentrations that comprised one standard curve. We were unable to use the control organs in our standard curve because our experiment was unintentionally contaminated with imidacloprid; therefore, we used the deer sample with the lowest absorbance value as our baseline for quantifying imidacloprid quantities. We optimized the tissue prepa- ration approach for this ELISA on solid samples using peer-reviewed methods29–34. ELISA Testing. Imidacloprid levels were determined for each organ collected. Brain, liver, spleen, and genital samples were removed from the freezer, and a portion of each organ (0.5–0.75 g) was minced using a sterilized scalpel and placed into a polypropylene micro centrifuge tube. Water was added to the tube at a ratio of 1 mL:1 g tissue sample. Each mixture was shaken using a vortex (Thermo Scientific), heated in an 80 °C water bath for 10 min, and frozen at −20 °C. Frozen mixtures were thawed and centrifuged (Centrifuge 5424, Eppendorf) at 21,130 g for 1 min. The liquid was extracted and placed into separate micro centrifuge tubes; remaining solids in the organ samples and remaining liquid were refrozen. Liquid samples were vortexed and a 25 μL portion was extracted and placed into a separate microcentrifuge tube. The excess liquid also was stored frozen. The remaining liquid was mixed with 25 μL of water, vortexed for 5 s, and centrifuged for 2 s in preparation for the ELISA assay. All samples were read at 450 nm using a microplate reader (uQuant, Biotek Instruments, Winooski, VT). Each plate had at least two standard curves of purified imidacloprid (Product number: 37894 SIGMA-ALDRICH, St. Louis, MO, USA). In preparation for the standard curve on each plate, samples from negative adult females were mixed together to account for the matrix effect of the organs and a stock solution of imidacloprid was created at 0.0, 0.03, 0.06, 0.13, 0.25, 0.5, 1.0, and 2.0 ppb. The standard curve on the ELISA plate contained 25 µL control organ in solution with 25 µL of the stock solution of imidacloprid, creating eight wells with concentrations that comprised one standard curve. Methods h Adult females and fawns were first tranquilized using xylazine (Bayer, Englewood, Colorado) and telezol (Zoetis, Parsippany-Troy Hills, New Jersey) when held in a Priefert deer chute and, once immobilized, were euthanized using euthanasia solution (MWI Veterinary Supply, Boise, ID) according to manufacturer’s suggested dosage. Once does and fawns were euthanized, they were frozen at −20 °C. All fawns and does in the experiment were necropsied at the South Dakota Animal Disease Research and Diagnostic Laboratory, South Dakota State University, Brookings, South Dakota. Necropsies were performed by Dr. David Knudsen (assisted by E. Hughes Berheim). Liver, brain, spleen, and genital organs were extracted, weighed, and 2.54 cm3 samples were collected. Additionally, we collected fawn jaw- bones to determine length. Organ samples were then frozen at −20 °C until they could be analyzed using ELISA. ELISA Testing. Imidacloprid levels were determined for each organ collected. Brain, liver, spleen, and genital samples were removed from the freezer, and a portion of each organ (0.5–0.75 g) was minced using a sterilized scalpel and placed into a polypropylene micro centrifuge tube. Water was added to the tube at a ratio of 1 mL:1 g tissue sample. Each mixture was shaken using a vortex (Thermo Scientific), heated in an 80 °C water bath for 10 min, and frozen at −20 °C. Frozen mixtures were thawed and centrifuged (Centrifuge 5424, Eppendorf) at 21,130 g for 1 min. The liquid was extracted and placed into separate micro centrifuge tubes; remaining solids in the organ samples and remaining liquid were refrozen. Liquid samples were vortexed and a 25 μL portion was extracted and placed into a separate microcentrifuge tube. The excess liquid also was stored frozen. The remaining liquid was mixed with 25 μL of water, vortexed for 5 s, and centrifuged for 2 s in preparation for the ELISA assay. All samples were read at 450 nm using a microplate reader (uQuant, Biotek Instruments, Winooski, VT). Each plate had at least two standard curves of purified imidacloprid (Product number: 37894 SIGMA-ALDRICH, St. Louis, MO, USA). In preparation for the standard curve on each plate, samples from negative adult females were mixed together to account for the matrix effect of the organs and a stock solution of imidacloprid was created at 0.0, 0.03, 0.06, 0.13, 0.25, 0.5, 1.0, and 2.0 ppb. Results D d Doe and Fawn Survival. A total of 24 and 39 fawns was born in 2015 and 2016, respectively. In 2015, 12 of the fawns were born in August and September due to late breeding. Number of single, twin, triplet, and quadru- plet litter sizes, respectively, per treatment were 1, 4, 1, 1 (control), 5, 3, 0, 0 (low), 2, 3, 2, 0 (moderate), and 2, 7, 2, 0 (high); 3 fawns were found outside treatment pens and were not included in analyses. Sex ratio (females:males) of fawns was 0.46:0.54 and did not differ by treatment (X2 3 = 2.98, p = 0.394). In 2016, a control female died and was replaced with another adult female, totaling 21 adult females in our experiment. Fawn and adult female sur- vival decreased over the two field seasons: survival of fawns was 75% and 62% in 2015 and 2016, respectively. Of 20 adult females in 2015, 0% died (100% survival); in 2016, 19% of 21 adult females died (n = 4, 81% survival). Survival of fawns did not differ (p > 0.05) between 2015 and 2016. Additionally, sample size for adult females was too small to evaluate change in survival between the two field seasons. Imidacloprid Solution Consumption. Water consumption rates in 2015 and 2016 were monitored, and daily consumption was recorded. There were significant interactions in water consumption between treatment and date in 2015 (F15, 436 = 2.22, p = 0.01) and 2016 (F15, 555 = 2.19, p = 0.01). In 2015, when the control was removed from the analysis, date was still significant (F5, 327 = 21.48, p = 0.01) relative to consumption; however, water consumption per adult female was similar across treatments (F2, 327 = 0.60, p = 0.55), indicating the control group consumed significantly more water than the treatment groups. In 2016, when excluding the control group, the high treatment group consumed less water per adult female than the low and moderate groups (F2, 421 = 12.83, p = 0.01), even though consumption of water increased throughout the field season (F5, 421 = 14.25, p = 0.01) (Table 1). Necropsy Data. Organ weights were collected from adult females and fawns, and jawbone measurements were collected solely from fawns. Adult females had mean organ weights of 159 ± 8 g for brain, 809 ± 104 g for liver, 388 ± 41 g for spleen, and 87 ± 28 g for genitals. Methods h Average water consumed daily by fawns is also included in the table as it was used as a covariate in the ANOVA analysis of water consumption between treatment and control groups. in addition to ANOVA, ordinary least square (OLS) linear regression was used to assess relationships between imidacloprid concentrations in all organ samples and the response variables birth weight, fawn age, FT3, FT4, jawbone length, and organ weights; alpha was set at 0.05. Data collected on behavioral observations for adult females and fawns were analyzed separately but com- bined over observation period (morning and afternoon). Furthermore, we separated deer into three groups (high, moderate, and low) based on organ imidacloprid concentrations. Finally, we used Chi-square tests to determine significant differences among behaviors observed in high, moderate, and low imidacloprid groups for adults and fawns. If Chi-square tests were significant, we used confidence intervals (90%) to assess which behaviors differed among groups (high, moderate, and low). Methods h We were unable to use the control organs in our standard curve because our experiment was unintentionally contaminated with imidacloprid; therefore, we used the deer sample with the lowest absorbance value as our baseline for quantifying imidacloprid quantities. We optimized the tissue prepa- ration approach for this ELISA on solid samples using peer-reviewed methods29–34. Analysis. Data collected in experiments were analyzed using Systat 13 (Systat Software Inc., San Jose, CA). Male and female fawn organ concentrations for those fawns that survived versus those that died were compared using t-tests. Our ELISA results indicated that there was contamination of our control group. As a consequence, Scientific Reports \| (2019) 9:4534 \| https://doi.org/10.1038/s41598-019-40994-9 3 www.nature.com/scientificreports/ Group Date Total Liters Consumed (SEM) Average Liters Per Day (SEM) Average Liters Per Doe (SEM) Average Liters Per Fawn (SEM) Low 2015 1616.7 (0.61) 12.7 (0.61) 3.3 (0.2) 1.72 (0.1) Moderate 2015 2345.9 (0.78) 17.5 (0.78) 3.5 (0.2) 2.42 (0.1) High 2015 2806.4 (1.13) 20.8 (1.13) 3.1 (0.2) 3.98 (0.2) Control 2015 2574.1 (0.78) 19.5 (0.78) 5.2 (0.2) 4.23 (0.3) Low 2016 2216.5 (9.7) 17 (0.85) 4.2 (0.2) 2.78 (0.1) Moderate 2016 2323.2 (8.9) 17.7 (0.78) 3.6 (0.1) 3.89 (0.2) High 2016 2430.3 (13.2) 19.1 (1.2) 3.3 (0.2) 6.06 (0.3) Control 2016 2295.2 (8.6) 18.4 (0.77) 4.7 (0.2) 4.81 (0.2) Table 1. Water consumed by deer in treatments in 2015 and 2016 field seasons (May to October). Average liters consumed, average liters consumed per day, and average liters consumed daily per doe were recorded for each treatment and control group. Average water consumed daily by fawns is also included in the table as it was used as a covariate in the ANOVA analysis of water consumption between treatment and control groups. Table 1. Water consumed by deer in treatments in 2015 and 2016 field seasons (May to October). Average liters consumed, average liters consumed per day, and average liters consumed daily per doe were recorded for each treatment and control group. Average water consumed daily by fawns is also included in the table as it was used as a covariate in the ANOVA analysis of water consumption between treatment and control groups. Table 1. Water consumed by deer in treatments in 2015 and 2016 field seasons (May to October). Average liters consumed, average liters consumed per day, and average liters consumed daily per doe were recorded for each treatment and control group. Results D d Sample sizes are as follows: adult female n = 21, fawn n = 61 for the brain, spleen, and genital and n = 62 for the liver, male fawns n = 30 for brain, spleen, genital, and n = 31 for the liver, and female fawns n = 31 (all organs). Table 2. Mean organ (brain, liver, spleen, and genital) weights (g) of adult females and fawns including standard error. Sample sizes are as follows: adult female n = 21, fawn n = 61 for the brain, spleen, and genital and n = 62 for the liver, male fawns n = 30 for brain, spleen, genital, and n = 31 for the liver, and female fawns n = 31 (all organs). Age/Sex Group Survived/died Liver (ng/g) (SEM) Brain (ng/g) (SEM) Spleen (ng/g) (SEM) Genital (ng/g) (SEM) AF Control All 0.351 (0.09) 0.222 (0.22) 0.012 (0.01) 0.388 (0.12) AF Low All 0.133 (0.04) 0 0.077 (0.05) 0.380 (0.11) AF Moderate All 0.495 (0.18) 0.010 (0.01) 0.111 (0.11) 0.287 (0.08) AF High All 0.590 (0.12) 0 0.188 (0.10) 0.210 (0.06) AF All Died 0.153 (0.04) 0.277 (0.21) 0.030 (0.02) 0.191 (0.13) AF All Survived 0.487 (0.08) 0.003 (0) 0.124 (0.05) 0.330 (0.04) AF All All 0.423 (0.07) 0.055 (0.05) 0.106 (0.04) 0.694 (0.05) FF Control All 0.416 (0.06) 0.058 (0.03) 0.156 (0.04) 0.273 (0.04) FF Low All 0.430 (0.05) 0.053 (0.02) 0.114 (0.02) 0.402 (0.04) FF Moderate All 0.357 (0.05) 0 0.126 (0.02) 0.174 (0.02) FF High All 0.426 (0.12) 0.008 (0) 0.294 (0.13) 0.222 (0.04) FF All Died 0.443 (0.09) 0 0.268 (0.06) 0.219 (0.03) FF All Survived 0.401 (0.07) 0.044 (0.03) 0.177 (0.08) 0.290 (0.06) FF All All 0.417 (0.06) 0.028 (0.02) 0.210 (0.05) 0.264 (0.04) MF Control All 0.681 (0.10) 0.065 (0.02) 0.223 (0.03) 0.102 (0.03) MF Low All 0.350 (0.04) 0 0.037 (0.01) 0.168 (0.05) MF Moderate All 0.566 (0.08) 0.044 (0.02) 0.252 (0.07) 0.148 (0.04) MF High All 0.532 (0.09) 0.057 (0.04) 0.176 (0.06) 0.157 (0.03) MF All Died 0.654 (0.08) 0.006 (0) 0.489 (0.07) 0.259 (0.04) MF All Survived 0.518 (0.08) 0.057 (0.03) 0.116 (0.03) 0.115 (0.03) MF All All 0.553 (0.07) 0.046 (0.02) 0.193 (0.04) 0.146 (0.03) Fawn All Died 0.528 (0.04) 0.002 (0) 0.342 (0.03) 0.232 (0.02) Fawn All Survived 0.463 (0.05) 0.051 (0.02) 0.144 (0.04) 0.200 (0.03) Table 3. Results D d Average imidacloprid levels in organs (ng of imidacloprid per gram of tissue) liver, brain, spleen genital in adult females (AF, n = 21), fawns (n = 65), female fawns (FF, n = 32), and male fawns (MF, n = 3 t t t d t l AF FF d MF l t d i t f th th t d d Table 3. Average imidacloprid levels in organs (ng of imidacloprid per gram of tissue) liver, brain, spleen, and genital in adult females (AF, n = 21), fawns (n = 65), female fawns (FF, n = 32), and male fawns (MF, n = 32) per treatment and control groups. AF, FF, and MF are also separated into averages for those that were dead, and alive at the end of the experiment, and the sum of all AF, FF, or MF in our study. 0.42 ± 0.06 ng/g for liver, 0.03 ± 0.02 ng/g for brain, 0.21 ± 0.05 ng/g for spleen, and 0.26 ± 0.04 ng/g for genital (Table 3). Mean imidacloprid values in organs for male fawns were 0.55 ± 0.07 ng/g for liver, 0.05 ± 0.02 ng/g for brain, 0.19 ± 0.04 ng/g for spleen, and 0.15 ± 0.03 ng/g for genital (Table 3). Analyses. Spleen concentrations of imidacloprid were significantly higher (T59 = 2.76, p = 0.007) in fawns that died compared to the fawns that survived. However, an outlier of 1.49 ng/g of spleen tissue was removed from analyses (mean of data with outlier 0.20, range 0–1.49; mean of data without outlier 0.18, range 0–0.91 ng/g of tissue); the revised result also was significant (T58 = 4.36, p < 0.001) (Fig. 1). The fawn with this high spleen imidacloprid concentration survived, which was not consistent with the overall trend in the data. Mean imida- cloprid in spleens of fawns that died was 0.33 ± 0.26 ng/g whereas imidacloprid in spleens of fawns that survived averaged 0.10 ± 0.14 ng/g. Birth weight was not correlated with imidacloprid levels in any of the organs evaluated (Table 4). Fawn body weight at death was negatively correlated with imidacloprid levels in the spleen (F1,55 = 8.22, p = 0.005) and genital organs (F1,56 = 4.26, p = 0.04) (Table 4). Fawn age at death was correlated with imidacloprid levels in the spleen (F1,57 = 10.5, p = 0.002) but not in any of the other organs evaluated (Table 4). Results D d Mean organ weights of fawns were 106 ± 3.9 g for brain, 413 ± 37 g for liver, 102 ± 11.4 g for spleen, and 6 ± 0.9 g for genitals. Female fawn mean organ weights were 96 ± 6 g for brain, 342 ± 55 g for liver, 95 ± 18 g for spleen, and 3 ± 0.6 g for genitals. Male fawn mean organ weights were 115 ± 5 g for brain, 479 ± 48 g for liver, 109 ± 14 g for spleen, and 9 ± 1 g for genitals (Table 2). Average jawbone length results were 13.8 ± 0.4 cm. ELISA Results. ELISA results indicated imidacloprid was found in the control group organs (Table 3), indi- cating that our treatments were contaminated; there were no significant differences across treatments for liver (F3,18 = 0.511, p = 0.14), brain (F3,18 = 0.058, p = 0.388), genital (F3,18 = 0.17, p = 0.286), or spleen (F3,18 = 0.17, p = 0.328) in adult females, or liver (F3,34 = 0.04, p = 0.943), brain (F3,35 = 0.018, p = 0.576), genital (F3,34 = 0.05, p = 0.707), or spleen (F3,35 = 0.20, p = 0.199) in fawns; gender of fawns was not significant (p > 0.07) in these anal- yses. However, imidacloprid concentration in spleen samples of adults approached significance (r = 0.36, p = 0.06) when regressed versus control and treatment categories. Nevertheless, this changed our focus from separating ELISA results by treatments to viewing the results relative to concentration of imidacloprid. Mean imidacloprid values in organs for all adult females were 0.42 ± 0.07 ng/g for liver, 0.06 ± 0.05 ng/g for brain, 0.11 ± 0.04 ng/g for spleen, and 0.69 ± 0.05 ng/g for genital (Table 3). Mean imidacloprid values in organs for female fawns were Scientific Reports \| (2019) 9:4534 \| https://doi.org/10.1038/s41598-019-40994-9 4 www.nature.com/scientificreports/ Brain (g) (SEM) Liver (g) (SEM) Spleen (g) (SEM) Genital (g) (SEM) Adult female 161 (8) 1015 (63) 408 (40) 64 (15) Fawn 105 (3.9) 432 (35) 103 (11) 6 (0.8) Male fawn 115 (5) 479 (47) 109 (14) 9 (1) Female fawn 95 (6) 385 (53) 99 (17) 3 (0.6) Table 2. Mean organ (brain, liver, spleen, and genital) weights (g) of adult females and fawns including standard error. Table 3. Average imidacloprid levels in organs (ng of imidacloprid per gram of tissue) liver, brain, spleen, and genital in adult females (AF, n = 21), fawns (n = 65), female fawns (FF, n = 32), and male fawns (MF, n = 32) per treatment and control groups. AF, FF, and MF are also separated into averages for those that were dead, and alive at the end of the experiment, and the sum of all AF, FF, or MF in our study. Results D d Results of regression analyses for imidacloprid concentrations in organ samples and physical results: birth weight, fawn body weight, fawn age, FT3 and FT4, organ weights, fawn jawbone length. P-values were considered significant when < 0.05. Indicates P-values that are significant and indicates a negative correlation so as imidacloprid increases the physical response decreases. (F2,54 = 5.55, p = 0.021) (Table 4) imidacloprid concentrations. Fawn jawbone length was negatively correlated with imidacloprid values in the spleen (F1,57 = 9.98, p = 0.002) but not with other organ concentrations (Table 4). I id l id t ti i l l t d ith f i l th f l d l ti hi with imidacloprid values in the spleen (F1,57 = 9.98, p = 0.002) but not with other organ concentrations (Table 4). Imidacloprid concentrations in spleen were correlated with fawn survival; therefore, we explored relationships between spleen imidacloprid concentrations and deer behavior. Adult female (n = 21) imidacloprid concentra- tions in spleen were separated into low (n = 12, range = 0), moderate (n = 4, range 0.056–0.224), and high groups (n = 5, range = 0.248–0.909); the duration of behaviors were compared among groups (all spleens that had 0 ppb concentration were placed in the low group). The low imidacloprid group differed (90% CI) from the high group in the behaviors eat (groups; high = 2.4%, low = 6%), lay (high = 27%, low = 19%), lay/groom (high = 7%, low = 3%), stand/ruminate (high = 1%, low = 2%), run (high = 1%, low = 5%), and stand/groom (high = 8%, low = 5%) indicating that adult deer in the low group had higher activity levels than those in the high group. The moderate group also differed from the low group in the behaviors eat (group; moderate = 10%, low = 6%), lay (moderate = 4%, low = 19%), lay/ruminate (moderate = 2%, low = 5%), stand/ruminate (moderate = 1%, low = 2%), run (moderate = 1%, low = 5%), stand (moderate = 34%, low = 23%), stand/groom (moderate = 13%, low = 5%), and stand/nurse (moderate = 0%, low = 2%); indicating variation in behavior between the two groups (Table 5). Results D d Adult female FT3 and FT4 values were not correlated with imidacloprid levels in organs (Table 4). Fawn FT3 values were not correlated with imidacloprid concentrations in organs; however, FT4 values in fawns were negatively correlated (F1,39 = 7.48, p = 0.0092, Table 4) with spleen imidacloprid concentrations. Adult female organ weights were neg- atively correlated with imidacloprid concentrations in genitals (F1,19 = 5.00, p = 0.04) but not with other organ levels evaluated. Fawn organ weights were negatively correlated with spleen (F1,57 = 8.78, p = 0.0044) and genital Scientific Reports \| (2019) 9:4534 \| https://doi.org/10.1038/s41598-019-40994-9 5 www.nature.com/scientificreports/ Figure 1. Average Imidacloprid levels (ng/g) in spleen tissue of 2015 and 2016 fawns (n = 62) that died prematurely compared to those that survived. Imidacloprid levels differed between those that were dead compared to alive. Figure 1. Average Imidacloprid levels (ng/g) in spleen tissue of 2015 and 2016 fawns (n = 62) that died prematurely compared to those that survived. Imidacloprid levels differed between those that were dead compared to alive. Results D d Physical Responses Brain Liver Spleen Genital Imidacloprid Concentration Birth Weight F1,60 = 0.04, P = 0.83 F1,60 = 0.25, P = 0.61 F1,58 = 1.25, P = 0.26 F1,59 = 0.08, P = 0.77 Fawn Body Weight at Death F1,57 = 0.98, P = 0.32 F1,56 = 0.35, P = 0.55 F1,55 = 8.22, P = 0.0058* F1,56 = 4.26, P = 0.04 Fawn Age (in Days) F1,59 = 1.78, P = 0.18 F1,60 = 0.0008, P = 0.97 F1,57 = 10.5, P = 0.0019* F1,58 = 1.71, P = 0.19 AF FT3 F1,19 = 2.96, P = 0.10 F1,19 = 0.04, P = 0.85 F1,19 = 1.89, P = 0.18 F1,19 = 0.04, P = 0.83 AF FT4 F1,19 = 4.1, P = 0.06 F1,19 = 0.09, P = 0.76 F1,19 = 1.30, P = 0.27 F1,19 = 0.57, P = 0.46 Fawn FT3 F1,39 = 0.41, P = 0.52 F1,39 = 2.9, P = 0.09 F1,38 = 0.74, P = 0.39 F1,39 = 0.20, P = 0.65 Fawn FT4 F1,40 = 0.01, P = 0.90 F1,40 = 0.0002, P = 0.98 F1,39 = 7.48, P = 0.009* F1,40 = 0.017, P = 0.89 AF Organ Weights F1,19 = 0.04, P = 0.84 F1,19 = 1.15, P = 0.3 F1,19 = 0.29, P = 0.6 F1,19 = 5.0, P = 0.04* Fawn Organ Weights F1,59 = 2.42, P = 0.12 F1,60 = 0.10, P = 0.75 F1,57 = 8.78, P = 0.004* F1,58 = 5.55, P = 0.02* Fawn Jawbone Length F1,59 = 1.5, P = 0.22 F1,60 = 0.11, P = 0.73 F1,57 = 9.98, P = 0.002* F1,58 = 2.38, P = 0.12 Table 4. Results of regression analyses for imidacloprid concentrations in organ samples and physical results: birth weight, fawn body weight, fawn age, FT3 and FT4, organ weights, fawn jawbone length. P-values were considered significant when < 0.05. Indicates P-values that are significant and indicates a negative correlation so as imidacloprid increases the physical response decreases. Table 4. Results of regression analyses for imidacloprid concentrations in organ samples and physical result birth weight, fawn body weight, fawn age, FT3 and FT4, organ weights, fawn jawbone length. P-values were considered significant when < 0.05. Indicates P-values that are significant and indicates a negative correlatio so as imidacloprid increases the physical response decreases. Table 4. Discussion Our study provides the first overview of effects of imidacloprid on white-tailed deer. We documented that deer in our experiment avoided imidacloprid-contaminated water. Moreover, we discovered that fawns that died during our experiment had greater concentrations of imidacloprid in spleens compared to those that survived. Fawns with relatively high concentrations of imidacloprid in spleen and genital organs also tended to be smaller and less healthy than those with relatively low concentrations of imidacloprid in these organs. Finally, our study provides support for reduced activity of adult and fawn white-tailed deer with relatively high concentrations of imidaclo- prid in spleens. p p ELISA results indicated that our control experimental tissues were unintentionally contaminated with imida- cloprid. Potential sources of contamination included seed-treated food and vegetation. Deer were fed soy hulls and a corn, oats, and distiller’s mixture ad libitum. Unfortunately, it was unknown if the soybeans and grains fed to our deer were from imidacloprid-treated plants. However, corn and soybeans are commonly (≥94% of U.S. corn, ~50% of U.S. soybeans12) coated with one of the neonicotinoid active ingredients: clothianidin, imidaclo- prid, or thiamethoxam13. Additionally, deer in our study would often reach through the fence to browse on nat- ural vegetation. The fields adjacent to the captive wildlife facility were a matrix of agricultural crops with a corn field about 50 m north of the facility. It is unknown what pesticides were used on the corn, but it is likely that there was a seed treatment of imidacloprid or clothianidin. In Indiana, neonicotinoid dust was documented to disperse as far as 100 m from the site35. Imidacloprid from fields could be washed off during rain events and be absorbed by other plants, although this transfer is poorly understood19,36. Therefore, uptake of imidacloprid by vegetation adjacent to the facility is a likely source of this contamination. j y y Water containing imidacloprid was avoided by deer in treatments in our experiment as evidenced by variable concentrations of the neonicotinoid in captive deer. Deer that avoided consumption of treated water likely drank rain water, which was available (up to 0.3 m deep) after storm events during our experiment. Research on cervid avoidance of imidacloprid is unavailable, but avoidance of imidacloprid has been recorded in red-legged par- tridge (Alectoris rufa) when offered treated seeds37. Results D d Percentages that are significantly (90%CI) different than the low group percentages in the spleen for adult females. ^Percentages that are significantly (90%CI) different than the low group percentages in the spleen for fawns. Table 5. Behavioral observations closest to individual adult female (AF: n = 21) and fawn (n = 38) deaths (time ranged from 1 week to 2 months) were compared to their spleen imidacloprid concentrations. Not all fawns had observations collected as: 1) fawn observations were only collected in 2016 and 2) some fawns died prior to an observation being completed. Behavioral observations are separated into three groups (low, moderate, high) according to spleen organ concentrations (with the high group having the greatest imidacloprid levels and the low group having the lowest). Behavioral observations eat, lay, lay/groom (lay/grm), lay/ruminate (lay/rum), stand/ruminate (sta/rum), run, stand, stand/groom (sta/grm), stand/nurse (sta/nur), and walk (additionally for fawns the behaviors Lay/Curl and Lay/Slp (lay/sleep)) percentages were compared between spleen organ imidacloprid concentrations. Percentages that are significantly (90%CI) different than the low group percentages in the spleen for adult females. ^Percentages that are significantly (90%CI) different than the low group percentages in the spleen for fawns. Results D d ( ) Fawn spleen concentrations of imidacloprid (n = 38) also were placed in low (n = 20, range = 0), moder- ate (n = 9, range = 0.053–0.121), and high (n = 9, range = 0.148–0.786) groups and the durations of particular behaviors were compared among groups. The low group differed (90% CI) from the high group in the behaviors lay (group; high = 43%, low = 24%), run (high = 0%, low = 4%), stand (high = 16%, low = 22%), stand/groom (high = 2%, low = 6%), and walk (high = 9%, low = 15%); indicating that the high group was less active than the low group. The moderate group also differed from the low group in the behaviors eat (group; moderate = 12%, low = 8%), lay/curl (moderate = 1%, low = 6%), and lay/groom (moderate = 15%, low = 8%); indicating variation in behavior between the two groups (Table 5). 6 Scientific Reports \| (2019) 9:4534 \| https://doi.org/10.1038/s41598-019-40994-9 www.nature.com/scientificreports/ A.F./Fawn Group Eat Lay Lay/Curl Lay/Slp Lay/Grm Lay/Rum Sta/Rum Run Stand Sta/Grm Sta/Nur Walk AF High 2%* 27%* N/A N/A 7%* 4% 1%* 1%* 25% 8%* 1% 24% AF Moderate 10%* 4%* N/A N/A 3% 2%* 1%* 1%* 34%* 13%* 0%* 32% AF Low 6% 19% N/A N/A 3% 5% 2% 5% 23% 5% 2% 30% Fawn High 7% 43%^ 8% 2% 7% 7% N/A 0%^ 16%^ 2%^ N/A 9%^ Fawn Moderate 12%^ 20% 1%^ 1% 15%^ 5% N/A 3% 21% 5% N/A 17% Fawn Low 8% 24% 6% 2% 8% 5% N/A 4% 22% 6% N/A 15% Table 5. Behavioral observations closest to individual adult female (AF: n = 21) and fawn (n = 38) deaths (time ranged from 1 week to 2 months) were compared to their spleen imidacloprid concentrations. Not all fawns had observations collected as: 1) fawn observations were only collected in 2016 and 2) some fawns died prior to an observation being completed. Behavioral observations are separated into three groups (low, moderate, high) according to spleen organ concentrations (with the high group having the greatest imidacloprid levels and the low group having the lowest). Behavioral observations eat, lay, lay/groom (lay/grm), lay/ruminate (lay/rum), stand/ruminate (sta/rum), run, stand, stand/groom (sta/grm), stand/nurse (sta/nur), and walk (additionally for fawns the behaviors Lay/Curl and Lay/Slp (lay/sleep)) percentages were compared between spleen organ imidacloprid concentrations. Discussion From our observations and previous research, we predict that imidacloprid is suppressing the immune function and size of the spleen. p As imidacloprid increased in the genital organs of fawns and adult females, weights of the genital organs decreased. Vohra and Khera56 found that, as oral consumption of imidacloprid increased, the ovaries of lab rats became smaller but the uterus increased in size. Additional research has shown that liver and spleen sizes will decrease as imidacloprid concentration increases; however, there was not an indication that the genital weight decreased54–56. Consequently, more research is needed to better understand how imidacloprid and other neonic- otinoids affect reproductive tissues in mammals. f p Behavioral observations indicated that high concentration of imidacloprid in the spleen resulted in less activity in adult females and fawns. This finding was similar to results on female rats and their offspring that showed sig- nificant decreases in grip time as imidacloprid concentrations from intraperitoneal injection increased, an indi- cation of fatigue45. Rat movement was similarly impaired as imidacloprid (via oral consumption) increased55,57. g y p p ( p ) Samples of liver and spleen organs were collected from white-tailed deer brought to the NDGF Wildlife Health Laboratory for a variety of reasons (e.g., illegal harvest investigations, disease, deer-vehicle collisions) from 2009– 2017 throughout North Dakota.; imidacloprid concentrations were evaluated in 367 samples using the same ELISA methods as in our captive experiment. Results indicated that levels of imidacloprid in liver samples were 2.8 times higher in free-ranging deer in North Dakota [average 1.32 (0.10)] than in livers of our captive deer [average 0.46 (0.03)], Table 6. Furthermore, concentrations of imidacloprid in spleen samples from free-ranging deer in North Dakota [0.60 (0.06)] were 3.5 times higher than those in spleens of captive deer [0.17 (0.02), Table 6] in our experiment. Deer exposure to imidacloprid averaged 52.3 ± 4.6% over the years 2009 to 2017. For those free-ranging deer in North Dakota exposed to imidacloprid, average concentrations in spleens increased (r = 0.22, p = 0.002) an average of 0.11 ng/g per year from 2009 to 2017. Furthermore, 77.5% of these deer had imidacloprid levels in spleens equal to or above 0.33 ng/g (i.e., mean level of imidacloprid in spleens of fawns in captivity that died in our experiment). Discussion Liver Spleen North Dakota Captive North Dakota Captive Maximum 8.42 1.36 6.61 1.48 Minimum 0 0 0 0 Average 1.32 0.46 0.60 0.18 STD 1.68 0.34 1.12 0.26 SEM 0.10 0.03 0.06 0.03 Table 6. Comparison of liver and spleen imidacloprid concentrations (ng/g of tissue) between North Dakota free-ranging deer (n = 367) and our captive facility deer (n = 86). Liver Spleen North Dakota Captive North Dakota Captive Maximum 8.42 1.36 6.61 1.48 Minimum 0 0 0 0 Average 1.32 0.46 0.60 0.18 STD 1.68 0.34 1.12 0.26 SEM 0.10 0.03 0.06 0.03 Table 6. Comparison of liver and spleen imidacloprid concentrations (ng/g of tissue) between North Dakota free-ranging deer (n = 367) and our captive facility deer (n = 86). Table 6. Comparison of liver and spleen imidacloprid concentrations (ng/g of tissue) between North Dakot free-ranging deer (n = 367) and our captive facility deer (n = 86). difference in weights of imidacloprid exposed Wister rat pups. However, imidacloprid levels in spleen and genital tissues were negatively associated with body weight in fawns at the time of death. difference in weights of imidacloprid exposed Wister rat pups. However, imidacloprid levels in spleen and genital tissues were negatively associated with body weight in fawns at the time of death. g y y g FT3 and FT4 results are indicative of basal metabolic rate and thermoregulation27. Fawn and adult female FT3 values were similar to those reported in other studies, but FT4 results were elevated compared to previous stud- ies27,46–48. We do not believe that this was the result of imidacloprid, as this pesticide decreases thyroid function in rats49, Indian wild birds50, and fish51. Rather, the elevated FT4 values may be due to a combination of pregnancy in adult females, the time of year, and artificial feed. Hamr et al.52 found that thyroid hormones of artificially fed deer were elevated compared to deer that consumed natural browse. Additionally, this study also found that hormones were increased in the spring and summer. Bahnak et al.53 documented that pregnant, penned deer have elevated levels of thyroid hormones. y As imidacloprid increased in the spleen, we noted that FT4 levels and spleen size decreased. As stated previ- ously, imidacloprid has been shown to decrease FT4 levels in other vertebrates49–51. Additionally, research on rats has shown that organ weights (specifically liver and spleen) decrease as imidacloprid treatment increases54–56. Discussion These results indicate that wild populations of deer exposed to imida- cloprid are potentially experiencing effects similar to those seen in our captive facility experiment; i.e., reduced activity in adult females and fawns, and specifically in fawns, decreased survival, size, and health. Consequently, additional research is needed to confirm these relationships in free-ranging deer in agricultural landscapes where imidacloprid and other neonicotinoid insecticides are utilized. Data Availability Data Availability Data are available for upload upon the publication of our manuscript. y Data are available for upload upon the publication of our manuscript. Discussion Other animals detect and avoid toxins in their diets; for exam- ple, kudus (Tragelpahus imberbis), impalas (Aepyceros melampus), and goats (Capra aegagrus hircus) in South Africa avoided plants with 5% condensed tannins during the wet season38, likely due to the astringency of these compounds.i p Significantly higher concentrations of spleen imidacloprid levels were found in fawns that died compared to those that survived. The spleen produces white blood cells that fight infection and synthesize antibodies39. Imidacloprid can reduce the production of spleen lymphocytes40–42, which results in an impaired immune sys- tem20. Therefore, immune suppression in our fawns caused by imidacloprid likely was a factor in their deaths. Complimentary results were found in the FT4 values that are a pre-cursor to FT3 hormone, which is instrumental in regulating basal metabolic rate and thermal regulation in deer27. FT4 was inversely correlated with imidaclo- prid in spleens of fawns. Reduced metabolic rate in fawns with relatively high concentrations of imidacloprid likely explain the lower activity documented in captive deer. Imidacloprid values in brain were low to undocumented, which was surprising considering that the pesticide affects the central nervous system; we hypothesize that this could be due to an inability of the chemical to cross the blood-brain barrier. The California Environmental Protection Agency found that imidacloprid penetrates the blood-brain barrier. However, Gupta et al.43 found high imidacloprid quantities in rat liver, kidney, lung, and skin, but concentrations in the brain were low. Additionally, Krieger44 noted that the blood-brain barrier in vertebrates blocks access of imidacloprid to the central nervous system, which reduces toxicity. Fawns had similar birth weights regardless of the level of imidacloprid in their organs. Similarly, in Sprague-Dawley rats, there were no differences in litter size or weight gain in the offspring whether or not mothers were given an intraperitoneal injection of imidacloprid45. Additionally, Gawade41 found no significant Scientific Reports \| (2019) 9:4534 \| https://doi.org/10.1038/s41598-019-40994-9 7 www.nature.com/scientificreports/ Liver Spleen North Dakota Captive North Dakota Captive Maximum 8.42 1.36 6.61 1.48 Minimum 0 0 0 0 Average 1.32 0.46 0.60 0.18 STD 1.68 0.34 1.12 0.26 SEM 0.10 0.03 0.06 0.03 Table 6. Comparison of liver and spleen imidacloprid concentrations (ng/g of tissue) between North Dakota free-ranging deer (n = 367) and our captive facility deer (n = 86). References 1. Goulson, D. An overview of the environmental risks posed by neonicotinoid insecticides. Journal of Applied Ecology 50, 977–987 (2013). 2. Tomizawa, M. & Yamamoto, I. Binding of neonicotinoids and the related compounds to the insect nicotinic acetylcholine receptor. Journal of Pesticide Science 17, 231–236 (1992). 3. Buckingham, S., Lapied, B., Corronc, H. & Sattelle, F. Imidacloprid actions on insect neuronal acetylcholine receptors. The Journal of Experimental Biology 200, 2685–2692 (1997). 4. Matsuda, K. et al. Neonicotinoids: insecticides acting on insect nicotinic acetylcholine receptors. Trends in Pharmacological Sciences 22, 573–580 (2011). 5. Rose, P. H. Nicotine and the Neonicotidnoids in Mammalian toxicology of insecticides (ed. Marrs, T. C.) 184–220 (Marrs, 2012). 6. Van Dijk, T. C., Staalduinen, M. A. & Van der Sluijs, J. P. Macro- invertebrate decline in surface water polluted with imidacloprid. Plos One 8, e62374 (2013). gy f 6. Van Dijk, T. C., Staalduinen, M. A. & Van der Sluijs, J. P. Macro- invertebrate decline in surface water polluted with imidacloprid. Plos One 8, e62374 (2013). www.nature.com/scientificreports/ Immune Suppression by Neonicotinoid Insecticides at the Root of Global Wildlife Declines. Journal of Environmental Immunology and Toxicology 1, 3–12 (2013). f gy gy 17. Maloney, E., Morrissey, C. A., Headley, J. & Peru, K. Cumulative toxicity of neonicotinoid insecticide mixtures to chironomus dilutus under acute exposure scenarios. Environmental Toxicology and Chemistry 9999, 1–11 (2017). 8. Morrissey, C. A. et al. Neonicotinoid contamination of global surface waters and associated risk to aquatic invertebrates: a review Environment International 74, 291–303 (2015). 9. Mogren, C. L. & Lundgren, J. G. Neonicotinoid-contaminated pollinator strips adjacent to cropland reduce honey bee nutritiona status. Scientific Reports 6, 29608 (2016).fi i 20. Gibbons, D., Morrissey, C. & Mineau, P. A review of the direct and indirect effects of neonicotinoids and fipronil on vertebrate wildlife. Environmental Science and Pollution Research 22, 103–118 (2014). 1. Hoy, J. A., Hoy, R., Seba, D. & Kerstetter, T. H. Genital abnormalities in white-tailed deer in west-central Montana: pesticide exposure as a possible cause. Journal of Environmental Biology 23, 189–197 (2002). p p f gy 2. Hoy, J. A., Haas, G. T., Hoy, R. D. & Hallock, P. Observations of brachygnathia superior in wild ruminants in Western Montana, USA Wildlife Biology in Practice 7, 15–29 (2011). 23. Zimmerman, T. J., Jenks, J. A., Holler, L. D., Jacques, C. N. & Morlock, W. W. Congenital Hypotrichosis in a white-tailed deer fawn from South Dakota. Journal of Wildlife Diseases 40, 145–149 (2004). f f 24. NOAA National Weather Service Cooperator Observer Program. NOAA homepage, http://www.nws.noaa.gov/om/coop/ (20 25 Gi i C A t l A d f h ld id i d (WIA) i i i id P 1 l 24. NOAA National Weather Service Cooperator Observer Program. NOAA homepage, http://www.nws.noaa.gov/om/coop/ (2017). 25. Giorio, C. A. et al. An update of the worldwide integrated assessment (WIA) on systemic insecticides. Part 1: new molecules, metabolism, fate, and transport. Environmental Science and Pollution Research 1–33, https://doi.org/10.1007/s11356-017-0394-3 (2017). ( ) 26. Sikes, R. and the Animal Care and Use Committee of the American Society of Mammologists. Guidelines of the American Society of Mammologists for the use of wild mammals in research and education. Journal of Mammalogy 97, 663–688 (2016). 7. Bergman, E. J., Doherty, P. F., Bishop, C. J., Wolfe, L. L. & Banulis, B. A. Herbivore body condition response in altered environments mule deer and habitat management Plos One 9:e106374, http://journals plos org/plosone/article?id=10 1371/journal pone 0106374 27. www.nature.com/scientificreports/ www.nature.com/scientificreports/ 7. Sánchez-Bayo, F. P., Tennekes, H. A. & Goka, K. Impact of systemic insecticides on organisms and ecosystems in Insecticides Development of Safer and More Effective Technologies 365–414 (2013).f p f f ff g 8. Tokumato, J. M. et al. Effects of exposure of clothianidin on the reproductive system of male quails. Journal of the Veterinary Medica Science 75, 755–760 (2013). ( ) 9. Douglas, M. R. & Tooker, J. F. Large-Scale Deployment of Seed Treatments has Driven Rapid Increase in Use of Neonicotinoid Insecticides and Preemptive Pest Management in U.S. Field Crops. Environmental Science & Technology 49, 5088–5097 (2015). 9. Douglas, M. R. & Tooker, J. F. Large-Scale Deployment of Seed Treatments has Driven Rapid Increase in Use of Neon Insecticides and Preemptive Pest Management in U S Field Crops Environmental Science & Technology 49 5088 5097 (2 9. Douglas, M. R. & Tooker, J. F. Large-Scale Deployment of Seed Treatments has Driven Rapid Increase in Use of Neon Insecticides and Preemptive Pest Management in U.S. Field Crops. Environmental Science & Technology 49, 5088–5097 (2 0. Jeschke, P., Nauen, R., Schindler, M. & Elbert, A. Overview of the Status and Global Strategy for Neonicotinoids. Journal o Agricultural and Food Chemistry 59, 2897–2908 (2011). g y 1. United States Geological Survey [USGS]. Estimated Annual Agricultural Pesticide Use. Pesticide Use Maps, https://water.usgs.gov / / / / h h ? 2015& IMIDACLOPRID&hil L&di I id l id (2017) g y 11. United States Geological Survey [USGS]. Estimated Annual Agricultural Pesticide Use. Pesticide Use Maps, https://water.usgs.gov/ nawqa/pnsp/usage/maps/show map.php?year=2015&map=IMIDACLOPRID&hilo=L&disp=Imidacloprid (2017). q p p g p p p p y p p 12. Stockstad, E. Pesticides under fire for risks to pollinators. Science 340, 674–676 (2013). i 13. Main, A. R. et al. Widespread use and frequent detection of neonicotinoid insecticides in wetlands of Canada’s Prairie Pothole Region. Plos One 9, e101400 (2014).f 4. Seagraves, M. P. & Lundgren, J. G. Effects of neonicitinoid seed treatments on soybean aphid and its natural enemies. Journal of Pes Science 85, 125–132 (2012).hff ( ) 5. Bredeson, M. M., Reese, R. N. & Lundgren, J. G. The effects of insecticide dose and herbivore density on tri-trophic effects o thiamethoxam in a system involving wheat, aphids, and ladybeetles. Crop Protection 69, 70–76 (2015). y g p y p 16. Mason, R., Tennekes, H., Sánchez-Bayo, F. & Jepsen, P. U. www.nature.com/scientificreports/ Nature Publishing Group 5, 606–616 (2005).f . Mebius, R. E. & Kraal, G. Structure and function of the spleen. Na p g p 40. Mohany, M., Badr, G., Refaat, I. & El-Feki, M. Immunological and histological effects of exposure to imidacloprid insecticide in albino rats. African Journal of Pharmacy and Pharmacology 5, 2106–2114 (2011). 40. Mohany, M., Badr, G., Refaat, I. & El-Feki, M. Immunological and histological effects of exp albino rats. African Journal of Pharmacy and Pharmacology 5, 2106–2114 (2011). African Journal of Pharmacy and Pharmacology 5, 2106–2114 (201 1. Gawade, L., Dadarkar, S. S., Husain, R. & Gatne, M. A detailed study of developmental immunotoxicity of imidacloprid in Wistar rats. Food and Chemical Toxicology 51, 61–70 (2013).h 42. Mohany, M., El-Feki, M., Refaat, I., Garraud, O. & Badr, G. Thymoquinone ameliorates the immunological and histological changes induced by exposure to imidacloprid insecticide. The Journal of Toxicological Sciences 37, 1–11 (2012). l d d k l l h 3. Gupta, R. C. & Milatovic, D. Insecticides. Pages 389–407 in R. C. Gupta, editor. Biomarkers in Toxicology. Elsevier Inc. San Diego California, USA.h 2010. Hayes’ Handbook of Pesticide Toxicology. Third Edition. Acad 44. Krieger, R. 2010. Hayes’ Handbook of Pesticide Toxicology. Third Edition. Academic Press Cambridge. Massachusetts, USA (2014). 45 Ab D i M B l I id l id i d b h i l d fi i d i i f li l fib ill idi i i 44. Krieger, R. 2010. Hayes’ Handbook of Pesticide Toxicology. Third Edition. Academic Press Cambridge. Massachusetts, USA (2014). 45. Abou-Donia, M. B. et al. Imidacloprid induces neurobehavioral deficits and increases expression of glial fibrillary acidic protein in the motor cortex and hippocampus in offspring rats following in utero exposure. Journal of Toxicology and Environmental Health 71, h 45. Abou-Donia, M. B. et al. Imidacloprid induces neurobehavioral deficits and increases expression of glial fibrillary acidic protein in the motor cortex and hippocampus in offspring rats following in utero exposure. Journal of Toxicology and Environmental Health 71, 119–30 (2008).h 46. Watkins, B. E., Nachreiner, R. F., Schmitt, S. M., Cooley, T. M. & Ullrey, D. E. Thyroid function in fed and fasted white-tailed fawns. Canadian Journal of Zoology 60, 1331–1338 (1981). f gy ( ) 47. Creekmore, T. E. & Creekmore, L. H. Health assessment of white-tailed deer of the Cuyahoga Valley National Recreation Area. U.S. Department of the Interior. www.nature.com/scientificreports/ Bergman, E. J., Doherty, P. F., Bishop, C. J., Wolfe, L. L. & Banulis, B. A. Herbivore body condition response in altered environm mule deer and habitat management. Plos One 9:e106374, http://journals.plos.org/plosone/article?id=10.1371/journal.pone.010 (2014). 28. Altmann, J. Observational study of behavior: sampling methods. Behavior 49, 227–267 (1974).fl undgren, J. G. Non-target effects of clothianidin on monarch butter cenka, J. R. & Lundgren, J. G. Non-target effects of clothianidin on m g gfl f 30. Bredeson, M. M. & Lundgren, J. G. The effect of a thiamethoxam seed treatment on pests and yield in cultivated sunflowers. Journal of Economic Entomology 108, 2665–2671 (2015).hff f gy 1. Bredeson, M. M., Reese, R. N. & Lundgren, J. G. The effects of insecticide dose and herbivore density on tri-trophic effects o thiamethoxam in a system involving wheat, aphids, and lady beetles. Crop Protection 69, 70–76 (2015). 2. Mogren, C. L. & Lundgren, J. G. Neonicotinoid-contaminated pollinator strips adjacent to cropland reduce honey bee health Scientific Reports 6, 29068 (2016).h fi R p , ( ) 33. Pecenka, J. R. & Lundgren, J. G. The importance of dung beetles and insect communities on degradation of cattle dung pats in eastern South Dakota. PeerJ 6, e5220 (2018).hl 34. Bredeson, M. M. & Lundgren, J. G. Thiamethoxam seed treatments reduce foliar predator and pollinator populations in sunflowers (Helianthus annuus), and extra-floral nectaries as a route of exposure for seed treatments to affect the predator, Coleomegilla maculate (Coleoptera: Coccinnellidae). Crop Protection 106, 85–92 (2018). p p 35. Krupke, C. H., Holland, J. D., Long, E. Y. & Eitzer, B. D. Planting of neonicotinoid-treated maize poses risks for honey bees and non-target organisms over a wide area without consistent crop yield benefit. Journal of Applied Ecology 54, 1449–1458 (2017).i non target organisms over a wide area without consistent crop yield benefit. Journal of Applied Ecology 54, 1449 1458 (2017). 36. Bonmatin, J. M. et al. Environmental fate and exposure; neonicotinoids and fipronil. Environmental Science and Pollution Research 22, 35–67 (2015). 37. Lopez- Antia, A., Ortiz-Santaliestra, M. E. & Mateo, R. Experimental approaches to test pesticide-treated seed avoidance by under a simulated diversification of food sources (2014). i 38. Cooper, S. M. & Owen-Smith, N. Condensed tannins deter feeding by browsing ruminants in a South African savanna. Oeco 67, 142–146 (1985). ( ) 39. Mebius, R. E. & Kraal, G. Structure and function of the spleen. References 1. Goulson, D. An overview of the environmental risks posed by neonicotinoid insecticides. Journal of Applied Ecology 50, 977–987 (2013). 1. Goulson, D. An overview of the environmental risks posed by neonicotinoid insecticides. Journal of Applied Ecology 50, 977–987 (2013) Scientific Reports \| (2019) 9:4534 \| https://doi.org/10.1038/s41598-019-40994-9 8 www.nature.com/scientificreports/ Effect of imidacloprid on Reproduction of Female Albino Rats in Three Generation Study. Journal o Veterinary Science & Technology 7, 340, https://doi.org/10.4172/2157-7579.1000340 (2016). p f gy gy 56. Vohra, P. & Khera, K. S. Effect of imidacloprid on Reproduction of Female Albino Rat Veterinary Science & Technology 7, 340, https://doi.org/10.4172/2157-7579.1000340 (2016) 7. Najafi, G., Razi, M. & Feyzi, S. The effect of chronic exposure with imidacloprid insecticide on fertility in mature male rats International Journal of Fertility and Sterility 4, 9–16 (2010). 57. Najafi, G., Razi, M. & Feyzi, S. The effect of chronic exposure with imidacloprid insecticide on fertility in mature male rats. International Journal of Fertility and Sterility 4, 9–16 (2010). Acknowledgements Funding for this study was provided by the South Dakota Agricultural Experiment Station and Federal Aid to Wildlife Restoration (Study No. 3M5842) administered through South Dakota Department of Game, Fish and Parks. Funding for analysis of free-ranging deer in North Dakota was provided by North Dakota Department of Game and Fish. Special thanks to technicians C. Lee, B. Becher, J. Christenson, A. Wieseler, S. Carstens, and J. Jensen at South Dakota State University and R. Herigstad, M. Kietzman, J. Mortenson, H. Prichert, and A. Pachl at North Dakota Game and Fish Department. Author Contributions Berheim, collected data, wrote paper; Jenks obtained funding, conducted analyses, edited paper; Lundgren, conducted laboratory analyses; Michel, provided support for data collection and analysis; Grove, obtained funding and provided samples for analysis; Jensen, obtained funding and provided samples for analysis. www.nature.com/scientificreports/ 48. Bishop, C. J., Watkins, B. E., Wolfe, L. L. & White, G. C. Evaluating mule deer body condition using serum thyroid horm concentrations. The Journal of Wildlife Management 73, 462–467 (2009).f 48. Bishop, C. J., Watkins, B. E., Wolfe, L. L. & White, G. C. Evaluating mule deer body condition using serum thyroid hormone concentrations. The Journal of Wildlife Management 73, 462–467 (2009). 49 Abb M A M k M A N H M & M A S Eff t f i id l id d t t l i h t l i l d h f f g 9. Abbassy, M. A., Marzouk, M. A., Nasr, H. M. & Mansy, A. S. Effect of imidacloprid and tetraconazole on various hematological and biochemical parameters in male albino rats. Journal of Political Sciences & Public Affairs 2, 122, https://doi org/10.4172/23320761.1000122 (2014).h g 50. Pandey, S. P. & Mohanty, B. The neonicotinoid pesticide imidacloprid and the dithiocarbamate fungicide mancozeb disrupt the pituitary–thyroid axis of a wildlife bird. Chemosphere 122, 227–234 (2014).f p y y p 51. Priya, P., Maruthi, Y. A. & Chaitanya, D. A. Proceedings of the second International Summit on Integrative Biology. Effect of imidacloprid insecticide stress on levels of serum thyroid hormones and minerals of fresh water fish clarias batrachus (walking cat fish): interaction with cortisol. Hilton-Chicago/Northbrook, Chicago, USA (2014). p y fish): interaction with cortisol. Hilton-Chicago/Northbrook, Chic i g g 2. Hamr, J. & Bubenik, G. Seasonal thyroid hormone levels of free-ranging white-tailed deer in Ontario. Canadian Journal of Zoology 68, 2174–2180 (2011).l i 52. Hamr, J. & Bubenik, G. Seasonal thyroid hormone levels of free-ranging white-tailed dee 68, 2174–2180 (2011).l 3. Bahnak, B. R., Holland, J. C., Verme, L. J. & Ozoga, J. J. Seasonal and nutritional influences on growth hormone and thyroid activity in white-tailed deer. The Journal of Wildlife Management 45, 140–147 (1981). h f f g 4. Vohra, P., Khera, K. S. & Sangha, G. K. Physiological, biochemical and histological alterations induced by administration o imidacloprid in female albino rats. Pesticide Biochemistry and Physiology 110, 50–56 (2014). y y gy 5. Memon, S. A., Memon, N., Mal, B., Shaikh, S. A. & Shah, M. A. Histopathological changes in the gonads of male rabbits on exposure to imidacloprid insecticide. Journal of Entomology and Zoology Studies 2, 159–163 (2014).fh p f gy gy ( ) 6. Vohra, P. & Khera, K. S. www.nature.com/scientificreports/ Ohio Madison, WI, U.S (1999). Scientific Reports \| (2019) 9:4534 \| https://doi.org/10.1038/s41598-019-40994-9 9 www.nature.com/scientificreports/ Additional Informationh Competing Interests: The authors declare no competing interests. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Cre- ative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not per- mitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2019 Scientific Reports \| (2019) 9:4534 \| https://doi.org/10.1038/s41598-019-40994-9 10
https://openalex.org/W2917334266	https://www.arca.fiocruz.br/bitstream/icict/35292/2/SergioMorgado_ANAVicente_IOC_2019.pdf	English	null	Global In-Silico Scenario of tRNA Genes and Their Organization in Virus Genomes	Viruses	2,019	cc-by	8,427	Received: 28 November 2018; Accepted: 30 January 2019; Published: 21 February 2019 Received: 28 November 2018; Accepted: 30 January 2019; Published: 21 February 2019 Abstract: Viruses are known to be highly dependent on the host translation machinery for their protein synthesis. However, tRNA genes are occasionally identiﬁed in such organisms, and in addition, few of them harbor tRNA gene clusters comprising dozens of genes. Recently, tRNA gene clusters have been shown to occur among the three domains of life. In such a scenario, the viruses could play a role in the dispersion of such structures among these organisms. Thus, in order to reveal the prevalence of tRNA genes as well as tRNA gene clusters in viruses, we performed an unbiased large-scale genome survey. Interestingly, tRNA genes were predicted in ssDNA (single-stranded DNA) and ssRNA (single-stranded RNA) viruses as well in many other dsDNA viruses of families from Caudovirales order. In the latter group, tRNA gene clusters composed of 15 to 37 tRNA genes were characterized, mainly in bacteriophages, enlarging the occurrence of such structures within viruses. These bacteriophages were from hosts that encompass ﬁve phyla and 34 genera. This in-silico study presents the current global scenario of tRNA genes and their organization in virus genomes, contributing and opening questions to be explored in further studies concerning the role of the translation apparatus in these organisms. Keywords: tRNA gene; tRNA gene cluster; virus; bacteriophages; ssRNA; translation apparatus; host range; codons; ssDNA www.mdpi.com/journal/viruses Global In-Silico Scenario of tRNA Genes and Thei Organization in Virus Genomes Sergio Morgado * and Ana Carolina Vicente Fundação Oswaldo Cruz, Instituto Oswaldo Cruz, Laboratório de Genética Molecular de Microrganismos, Rio de Janeiro, 22745-271, Brazil; anapaulo@ioc.ﬁocruz.br * Correspondence: sergio.morgado@ioc.ﬁocruz.br; Tel.: +55-21-3865-8168 viruses Article Global In-Silico Scenario of tRNA Genes and Their Organization in Virus Genomes Sergio Morgado * and Ana Carolina Vicente Fundação Oswaldo Cruz, Instituto Oswaldo Cruz, Laboratório de Genética Molecular de Microrganismos, Rio de Janeiro, 22745-271, Brazil; anapaulo@ioc.ﬁocruz.br * Correspondence: sergio.morgado@ioc.ﬁocruz.br; Tel.: +55-21-3865-8168 Received: 28 November 2018; Accepted: 30 January 2019; Published: 21 February 2019 Abstract: Viruses are known to be highly dependent on the host translation machinery for thei protein synthesis. However, tRNA genes are occasionally identiﬁed in such organisms, and i addition, few of them harbor tRNA gene clusters comprising dozens of genes. Recently, tRNA gen clusters have been shown to occur among the three domains of life. In such a scenario, the viruse could play a role in the dispersion of such structures among these organisms. Thus, in order to revea the prevalence of tRNA genes as well as tRNA gene clusters in viruses, we performed an unbiase large-scale genome survey. Interestingly, tRNA genes were predicted in ssDNA (single-strande DNA) and ssRNA (single-stranded RNA) viruses as well in many other dsDNA viruses of familie from Caudovirales order. In the latter group, tRNA gene clusters composed of 15 to 37 tRNA gene were characterized, mainly in bacteriophages, enlarging the occurrence of such structures withi viruses. These bacteriophages were from hosts that encompass ﬁve phyla and 34 genera. This in-silic study presents the current global scenario of tRNA genes and their organization in virus genome contributing and opening questions to be explored in further studies concerning the role of th translation apparatus in these organisms. viruses Article Global In-Silico Scenario of tRNA Genes and Their Organization in Virus Genomes Sergio Morgado * and Ana Carolina Vicente Fundação Oswaldo Cruz, Instituto Oswaldo Cruz, Laboratório de Genética Molecular de Microrganismos, Rio de Janeiro, 22745-271, Brazil; anapaulo@ioc.ﬁocruz.br * Correspondence: sergio.morgado@ioc.ﬁocruz.br; Tel.: +55-21-3865-8168 Received: 28 November 2018; Accepted: 30 January 2019; Published: 21 February 2019 Abstract: Viruses are known to be highly dependent on the host translation machinery for thei protein synthesis. However, tRNA genes are occasionally identiﬁed in such organisms, and i addition, few of them harbor tRNA gene clusters comprising dozens of genes. Recently, tRNA gen clusters have been shown to occur among the three domains of life. In such a scenario, the viruse could play a role in the dispersion of such structures among these organisms. Thus, in order to revea the prevalence of tRNA genes as well as tRNA gene clusters in viruses, we performed an unbiase large-scale genome survey. Interestingly, tRNA genes were predicted in ssDNA (single-strande DNA) and ssRNA (single-stranded RNA) viruses as well in many other dsDNA viruses of familie from Caudovirales order. In the latter group, tRNA gene clusters composed of 15 to 37 tRNA gene were characterized, mainly in bacteriophages, enlarging the occurrence of such structures withi viruses. These bacteriophages were from hosts that encompass ﬁve phyla and 34 genera. This in-silic study presents the current global scenario of tRNA genes and their organization in virus genome contributing and opening questions to be explored in further studies concerning the role of th translation apparatus in these organisms. viruses viruses 1. Introduction Viruses are highly dependent on the host translation machinery for their protein synthesis, presenting compact genomes with a high density of coding regions. However, genes related to replication, transcription and/or translation, mainly tRNA (transfer RNA) genes, are occasionally identiﬁed in viruses [1–4]. Contrasting with this scenario, some giant viruses carry several genes from the translation apparatus, particularly the recently characterized Tupanviruses, lacking only the ribosomal genes [5,6]. To date, tRNA genes have been only observed in some double-stranded DNA virus families, such as Myoviridae, Siphoviridae, Podoviridae, Mimiviridae, Phycodnaviridae, Baculoviridae and Herpesviridae [7–11]. Besides, some tRNA genes occurring in these viruses are organized in clusters comprising up to dozens of tRNA genes [2,4,11–16]. Interestingly, such tRNA gene organization is particularly common in mitochondrial genomes [17–19], but large clusters have been observed in the three domains of life (Archaea, Bacteria and Eukarya) [16,20–25]. Studies indicate that the presence of tRNA genes in virus genomes would be to compensate for differences in codon and/or amino acid usage between virus and hosts, favoring an efﬁcient protein synthesis and/or expanding the host range [2,4]. Besides the canonical role of the tRNA genes, some viruses use tRNA genes in regulation of translation, packaging and priming reverse transcription [11]. Since tRNA gene clusters have been shown to be prevalent among the three domains of life and occasionally occurs in viruses, we hypothesized that viruses could play a role in the dispersion of such structures among these Viruses 2019, 11, 180; doi:10.3390/v11020180 www.mdpi.com/journal/viruses 2 of 14 Viruses 2019, 11, 180 organisms. In order to test this hypothesis, and due to the availability of thousands of virus genomes, we performed a large-scale genome survey aiming to identify tRNA genes and tRNA gene clusters in these viruses. This in-silico analysis revealed an unsuspected scenario on the prevalence and organization of tRNA genes within viruses, revealing also the presence of tRNA genes in ssDNA and ssRNA genomes. 2.3. Taxonomic Designation, Sequence Annotation, and Gene Content Analysis .3. Taxonomic Designation, Sequence Annotation, and Gene Content Analysis Taxonomic information of the virus sequences was obtained using Kraken v0.10.5 [28], and their annotation performed by Prokka v1.12 using “Viruses” parameter [29]. The gene content and orthologous genes within and ﬂanking (2 kb) the tRNA gene cluster regions were analyzed and compared using GET_HOMOLOGUES v3.0.5 [30] and AcCNET [31] considering 60% of coverage and 40% of identity. The generated networks were visualized using Cytoscape v3.6.0 [32]. .2. Trna Gene Prediction, Identiﬁcation, and Classiﬁcation of tRNA Gene Clusters The tRNA gene prediction of the data set was mainly performed by ARAGORN v1.2.38 [26] using the standard genetic code. The false-positive rate of this software is correlated with the genome GC (guanine-cytosine) content, being 0.6–3.5 false positives per Gb considering a GC content of 0.2–0.5 and 14 false positives per Gb with a GC content of 0.6 [26]. Since the median GC content of the genomes analyzed here is 0.44, with only one viral family having GC content of 0.62 (Herpesviridae), and in general, the viruses have small genomes, the expected rate of false positives is low. In some cases, the isotype and anticodon of the tRNA gene predicted by ARAGORN were not accurately discriminated (i.e., the software indicated two isotypes for a single tRNA gene; e.g., Glu or Gly), requiring a reanalysis using other tRNA gene predictor, tRNAscan-SE 2.0 [27]. The tRNA genes were considered clustered if presenting a tRNA gene density ≥2 tRNA/kb [22]. Here we surveyed tRNA gene clusters with a minimum of 15 tRNA genes using an in-house script described in a previous study [16]. The identiﬁed tRNA gene clusters were classiﬁed in groups according to their tRNA gene isotype arrangement (using the single-letter amino acid code abbreviation). 2.4. Phylogenetic Analysis The maximum-likelihood tree based on the major capsid protein (MCP) from the Caudovirales viruses harboring tRNA gene clusters was reconstructed using PhyML v3.1 [33] with GTR+G+I (general time-reversible + gamma + invariant) substitution model and 100 bootstrap replicates. These amino acid sequences were previously aligned and the low-quality alignment columns were removed by GUIDANCE2 v2.02 [34]. The genetic relationship of the tRNA genes from the tRNA gene clusters was assayed concatenating their nucleotide sequence and submitting to Maximum-likelihood analysis with the GTR substitution model and 100 bootstrap replicates using PhyML v3.1. The substitution models were chosen based on ModelGenerator v85 software [35] and the generated tree ﬁgures were edited using iTOL [36]. 2.1. Genomes Analyzed The 13,200 viral sequences were retrieved from NCBI FTP (File Transfer Protocol) site (ftp: //ftp.ncbi.nlm.nih.gov/genomes/genbank/viral/) in December 2017. 2.2. Trna Gene Prediction, Identiﬁcation, and Classiﬁcation of tRNA Gene Clusters 2.2. Trna Gene Prediction, Identiﬁcation, and Classiﬁcation of tRNA Gene Clusters 2.5. Codon Bias and Comparative Analyzes of the tRNA Genes In order to verify whether the codons associated with the tRNA genes from the tRNA gene clusters match with the most used codons in the genome and MCP gene (RSCU >1), we performed a relative synonymous codon usage (RSCU) analysis. A RSCU value of 1 indicates no bias, while values >1 and <1 indicate that the codon occurs more and less frequently than expected, respectively. The RSCU values 3 of 14 Viruses 2019, 11, 180 were calculated using the software CodonW v1.4.2 (https://sourceforge.net/projects/codonw/). The MCP was chosen to be analyzed because is a fundamental component of the virus structure, so it is expected to be highly translated. A high proportion of matching codons would mean that the tRNA gene clusters strongly support the virus ﬁtness. were calculated using the software CodonW v1.4.2 (https://sourceforge.net/projects/codonw/). The MCP was chosen to be analyzed because is a fundamental component of the virus structure, so it is expected to be highly translated. A high proportion of matching codons would mean that the tRNA gene clusters strongly support the virus ﬁtness. To explore the possible source of the tRNA gene clusters, all the unique tRNA gene sequences from the tRNA gene clusters were compared to tRNA sequences deposited in the tRNA gene database curated manually by experts (tRNADB-CE) v11.0 [37] considering a global sequence identity of ≥90% with CD-HIT [38]. 2.6. Statistical Analysis Statistical analyzes were performed with R language R-3.5.2 [39] and RStudio software v1.1.463 [40]. Comparisons between groups were performed using non-parametric tests. A value of p < 0.05 was considered statistically signiﬁcant. 3.1. Data Set Classiﬁcation and tRNA Gene Distribution In order to deﬁne the order/family of the viruses from our data set, we performed a taxonomic designation analysis using Kraken. From 13,200 sequences, 10,249 were designed in 103 families, six of them being the most abundant (~70% of all genomes) (Table S1). To explore the occurrence of tRNA genes in these sequences we applied the ARAGORN software. From the initially 13,200 sequences, approximately 14% (n = 1824) presented at least one tRNA gene. The classiﬁed organisms and their tRNA gene sequences are provided in Table S2 and Supplementary File. A high proportion of the classiﬁed genomes carrying at least one tRNA gene belonged to the Caudovirales order (~95%), and the others were from Herpesvirales, Ligamenvirales, “Megavirales” and Picornavirales orders. They were assigned in 22 families, mostly dsDNA, with few ssRNA (+) and ssDNA (Table 1). The ssRNA/DNA viruses are from Dicistroviridae, Inoviridae, Luteoviridae, Retroviridae and Virgaviridae families [41–44]. Considering the relative abundance of these genomes, few families presented a high proportion of tRNA genes, such as Myoviridae (71%), Mimiviridae (83%) and Phycodnaviridae (87%). The length of the genomes ranged from ~5 kb to 1.2 Mb, harboring from 1 to 43 tRNA genes (Table 1). The median length of the genomes harboring tRNA genes was signiﬁcantly higher than those without, 97 kb (IQR, 52–170 kb) and 12 kb (IQR, 5–29 kb) (p = 10−16), respectively, and the median GC content of the genomes harboring tRNA genes was slightly higher, 43% (IQR, 39–58%) vs. 42% (IQR, 35–48%) (p = 10−16). A positive correlation was observed between the number of tRNA genes and the genome length (Figure 1A). 4 of 14 Viruses 2019, 11, 180 Table 1. Number and features of viral families harboring tRNA genes. Table 1. Number and features of viral families harboring tRNA genes. 3.1. Data Set Classiﬁcation and tRNA Gene Distribution # Genomes w tRNA/Total Genomes Family Order DNA/RNA Hosts Length (Kb) # tRNAs Avg GC% 1/24 Dicistroviridae Picornavirales ssRNA(+) Invertebrates 9 1 45.31 1/9 Lipothrixviridae Ligamenvirales dsDNA Archaea 32 1 35.66 1/47 Luteoviridae Unassigned ssRNA(+) Plants 6 1 50.70 1/7 Marseilleviridae Unassigned dsDNA Amoeba 372 2 44.19 1/6 Nudiviridae Unassigned dsDNA Insects and marine crustaceans 145 1 25.53 1/97 Polyomaviridae Unassigned dsDNA Mammals and birds 5 1 52.35 1/69 Virgaviridae Unassigned ssRNA(+) Plants 11 1 48.53 2/48 Poxviridae “Megavirales” dsDNA Humans, vertebrates and arthropods ~140 1 51.65 2/8 Polydnaviridae Unassigned dsDNA Parasitoid wasps 185–564 7–8 33.72 3/6 Ascoviridae “Megavirales” dsDNA Insects 173–198 1–3 42.67 3/47 Inoviridae Unassigned ssDNA Bacteria ~5 1 44.30 3/67 Retroviridae Unassigned ssRNA(+) Vertebrates 6–8 1 48.80 4/21 Iridoviridae Unassigned dsDNA Amphibia, ﬁsh and invertebrates 123–190 1 39.92 5/11 Fuselloviridae Unassigned dsDNA Thermophilic archaea ~16 1 38.37 5/6 Mimiviridae “Megavirales” dsDNA Amoeba 600–1200 2–15 26.12 6/78 Herpesviridae Herpesvirales dsDNA Vertebrates 119–203 1–18 62.38 7/97 Adenoviridae Unassigned dsDNA Vertebrates 33–46 1 52.50 9/84 Baculoviridae Unassigned dsDNA Arthropods and crustacean 81–178 1 44.01 21/24 Phycodnaviridae Unassigned dsDNA Alga 170–469 2–14 39.77 115/584 Podoviridae Caudovirales dsDNA Archaea and Bacteria 36–145 1–23 44.78 620/1981 Siphoviridae Caudovirales dsDNA Archaea and Bacteria 14–280 1–43 55.51 776/1079 Myoviridae Caudovirales dsDNA Archaea and Bacteria 32–497 1–36 41.59 5 of 14 5 f 14 5 of 14 5 f 14 Viruses 2019, 11, 180 Vi 11 FO , , Viruses 2019, 11, x FOR PEER REVIEW 5 of 14 Figure 1. Correlations between tRNA gene number and genome length. (A) Correlation between the total number of tRNA genes in each genome and their length (Spearman's correlation coefficients: R = 0.5, p = 10−16). (B) Correlation between the number of clustered tRNA genes and the genome length of viruses carrying tRNA gene clusters (Spearman's correlation coefficients: R = −0.49, p = 10−15). 3 2 Identification Characterization and Organization of tRNA Gene Clusters in Phage and Virus Genomes Figure 1. Correlations between tRNA gene number and genome length. (A) Correlation between the total number of tRNA genes in each genome and their length (Spearman’s correlation coefﬁcients: R = 0.5, p = 10−16). (B) Correlation between the number of clustered tRNA genes and the genome length of viruses carrying tRNA gene clusters (Spearman’s correlation coefﬁcients: R = −0.49, p = 10−15). 3.2. Identiﬁcation, Characterization, and Organization of tRNA Gene Clusters in Phage and Virus Genomes ure 1. 3.1. Data Set Classiﬁcation and tRNA Gene Distribution Correlations between tRNA gene number and genome length. (A) Correlation between the to mber of tRNA genes in each genome and their length (Spearman's correlation coefficients: R = 0.5, p = 10− Correlation between the number of clustered tRNA genes and the genome length of viruses carrying tRN ne clusters (Spearman's correlation coefficients: R = −0.49, p = 10−15). Figure 1. Correlations between tRNA gene number and genome length. (A) Correlation between the total number of tRNA genes in each genome and their length (Spearman’s correlation coefﬁcients: R = 0.5, p = 10−16). (B) Correlation between the number of clustered tRNA genes and the genome length of viruses carrying tRNA gene clusters (Spearman’s correlation coefﬁcients: R = −0.49, p = 10−15). . Identification, Characterization, and Organization of tRNA Gene Clusters in Phage and Virus Genomes Identiﬁcation, Characterization, and Organization of tRNA Gene Clusters in Phage and Virus Genomes 3.2. Identification, Characterization, and Organization of tRNA Gene Clusters in Phage and Virus Genomes 3.2. Identiﬁcation, Characterization, and Organization of tRNA Gene Clusters in Phage and Virus Genomes We identified the presence of tRNA gene clusters in 228/1824 virus genomes harboring tRNA genes (~2% of the total data set and ~12% of the genomes harboring tRNA genes; Table S3). Considering the genomes carrying tRNA genes, those with tRNA gene clusters presented a median length higher than those without tRNA gene clusters, 148 kb (IQR, 106–160 kb) and 77 kb (IQR, 51– 171 kb) (p = 10−14), respectively. 124/228 genomes with tRNA gene clusters have all their tRNA genes clustered, while the others presented a fraction from 55 to 97% (mean of 80%) of their tRNA genes clustered. The majority of genomes from this latter group (n = 33) presented 7 tRNA genes outside the clusters, while 22 genomes present only 1 tRNA gene outside the cluster. On the other hand, Streptomyces phages carry a total of ~42 tRNA genes, and from these, 16–17 tRNA genes are outside the cluster. The genomes harboring tRNA gene clusters ranged from 72 to 617 kb and the clusters were composed of 15 to 37 tRNA genes, with eight of them harboring the universal 20 tRNA isotypes (most of the clusters harbor 16/20 tRNA isotypes). A negative correlation was observed between the number of the clustered tRNA genes and the genome length (Figure 1B). Interestingly, 44/55 mycobacteriophages present an unusual tRNA isotype, pyrrolysine. 3.1. Data Set Classiﬁcation and tRNA Gene Distribution The tRNA gene density of these tRNA gene clusters ranged from ~2–10 tRNA/kb. Most of these genomes with tRNA gene clusters are from bacteriophages, while only two are from Archaea and Eukarya virus. Nevertheless, almost all genomes belong to the Caudovirales order, organized in the Podoviridae (~4% of the genomes with tRNA gene clusters), Myoviridae (~72%) and Siphoviridae (~24%) families; and one genome belongs to the “Megavirales” proposed order. The phages were from hosts that encompass five phyla and 34 genera. The phylum Proteobacteria represents the majority of the genomes (125/228) and genera (24/34) (Table 2) We identiﬁed the presence of tRNA gene clusters in 228/1824 virus genomes harboring tRNA genes (~2% of the total data set and ~12% of the genomes harboring tRNA genes; Table S3). Considering the genomes carrying tRNA genes, those with tRNA gene clusters presented a median length higher than those without tRNA gene clusters, 148 kb (IQR, 106–160 kb) and 77 kb (IQR, 51–171 kb) (p = 10−14), respectively. 124/228 genomes with tRNA gene clusters have all their tRNA genes clustered, while the others presented a fraction from 55 to 97% (mean of 80%) of their tRNA genes clustered. The majority of genomes from this latter group (n = 33) presented 7 tRNA genes outside the clusters, while 22 genomes present only 1 tRNA gene outside the cluster. On the other hand, Streptomyces phages carry a total of ~42 tRNA genes, and from these, 16–17 tRNA genes are outside the cluster. The genomes harboring tRNA gene clusters ranged from 72 to 617 kb and the clusters were composed of 15 to 37 tRNA genes, with eight of them harboring the universal 20 tRNA isotypes (most of the clusters harbor 16/20 tRNA isotypes). A negative correlation was observed between the number of the clustered tRNA genes and the genome length (Figure 1B). Interestingly, 44/55 mycobacteriophages present an unusual tRNA isotype, pyrrolysine. The tRNA gene density of these tRNA gene clusters ranged from ~2–10 tRNA/kb. Most of these genomes with tRNA gene clusters are from bacteriophages, while only two are from Archaea and Eukarya virus. Nevertheless, almost all genomes belong to the Caudovirales order, organized in the Podoviridae (~4% of the genomes with tRNA gene clusters), Myoviridae (~72%) and Siphoviridae (~24%) families; and one genome belongs to the “Megavirales” proposed order. The phages were from hosts that encompass ﬁve phyla and 34 genera. 3.1. Data Set Classiﬁcation and tRNA Gene Distribution The phylum Proteobacteria represents the majority of the genomes (125/228) and genera (24/34) (Table 2). 6 of 14 Viruses 2019, 11, 180 Table 2. Taxonomic information of the hosts of viruses harboring tRNA gene clusters. # Genomes Genus Family Phylum Domain 55 Mycobacterium Mycobacteriaceae Actinobacteria Bacteria 9 Streptomyces Streptomycetaceae Actinobacteria Bacteria 1 Gordonia Gordoniaceae Actinobacteria Bacteria 7 Cellulophaga Flavobacteriaceae Bacteroidetes Bacteria 2 Synechococcus Synechococcaceae Cyanobacteria Bacteria 1 Halogranum Haloferacaceae Euryarchaeota Archaea 13 Bacillus Bacillaceae Firmicutes Bacteria 1 Enterococcus Enterobacteriaceae Firmicutes Bacteria 1 Staphylococcus Staphylococcaceae Firmicutes Bacteria 1 Lactobacillus Lactobacillaceae Firmicutes Bacteria 10 Listeria Listeriaceae Firmicutes Bacteria 5 Acinetobacter Moraxellaceae Proteobacteria Bacteria 14 Aeromonas Aeromonadaceae Proteobacteria Bacteria 12 Caulobacter Caulobacteraceae Proteobacteria Bacteria 4 Citrobacter Enterobacteriaceae Proteobacteria Bacteria 5 Cronobacter Enterobacteriaceae Proteobacteria Bacteria 3 Erwinia Enterococcaceae Proteobacteria Bacteria 23 Escherichia Enterobacteriaceae Proteobacteria Bacteria 7 Klebsiella Enterobacteriaceae Proteobacteria Bacteria 1 Pectobacterium Enterobacteriaceae Proteobacteria Bacteria 1 Providencia Enterobacteriaceae Proteobacteria Bacteria 7 Pseudomonas Pseudomonadaceae Proteobacteria Bacteria 1 Roseobacter Rhodobacteraceae Proteobacteria Bacteria 17 Salmonella Enterobacteriaceae Proteobacteria Bacteria 4 Shigella Enterobacteriaceae Proteobacteria Bacteria 1 Sphingobium Sphingomonadaceae Proteobacteria Bacteria 3 Stenotrophomonas Xanthomonadaceae Proteobacteria Bacteria 9 Vibrio Vibrionaceae Proteobacteria Bacteria 1 Yersinia Enterobacteriaceae Proteobacteria Bacteria 1 Agrobacterium Rhizobiaceae Proteobacteria Bacteria 1 Enterobacter Enterobacteriaceae Proteobacteria Bacteria 1 Pseudoalteromonas Pseudoalteromonadaceae Proteobacteria Bacteria 1 Ralstonia Burkholderiaceae Proteobacteria Bacteria 3 Serratia Enterobacteriaceae Proteobacteria Bacteria 1 Sulﬁtobacter Rhodobacteraceae Proteobacteria Bacteria 1 Cafeteria Cafeteriaceae Stramenopiles Eukarya Table 2. Taxonomic information of the hosts of viruses harboring tRNA gene clusters. Based on the tRNA gene isotype synteny we could deﬁne 23 tRNA gene cluster groups and 25 singletons (Figure S1). Mycobacterium phages presented three groups, Bacillus phages/two groups, Aeromonas phages/three groups, Cronobacter phages/two groups, Salmonella phages/three groups, Escherichia phages/three groups, Vibrio phages/two groups, Klebsiella phages/two groups. The G1, G3, G8, G14, G17, G19, G23 groups are exclusively composed of phages infecting enterobacteria, including Citrobacter, Cronobacter, Enterobacter, Escherichia, Erwinia, Klebsiella, Salmonella, Serratia, Shigella and Yersinia genera (Proteobacteria phylum). Some groups are genus associated, like G6, G9, and G11 (Mycobacterium exclusive), while others present several phage genus hosts, as G1 with several phage genus hosts from Proteobacteria. The G1 group is also present in a Staphylococcus phage, isolated from Firmicutes phylum, however, it mainly differs from the others in G1 group by the deletion of the ﬁrst four tRNA genes, which correspond to the isotypes [PEMN] (Figure S1). 3.1. Data Set Classiﬁcation and tRNA Gene Distribution The same groups, deﬁned by the tRNA isotype synteny, were also observed when the tRNA gene sequences were considered (Figure S2). Besides that, some singletons presented relation with tRNA gene cluster groups from same/different genus, e.g., Streptomyces phage BRocK and Gordonia phage GMA2 (both infecting Actinobacteria) with G4 group, composed by Streptomyces phages (Actinobacteria host); and Roseobacter phage DSS3P8 and Agrobacterium phage Atu ph07 (both infecting Proteobacteria) with G2 group, composed by Caulobacter phages (Proteobacteria host). Viruses 2019, 11, 180 7 of 14 Viruses 2019, 11, 180 Considering the tRNA gene clusters carried by the Caudovirales viruses, their grouping is consistent with the MCP phylogeny, except for the sequences from the G12 group, composed by Cellulophaga phages, clustered into two groups (Figure S3). In fact, these phages present a conserved central block of tRNA isotypes, however, the two groups differ by the presence of exclusive block isotype in the right and left sides of the central block (Figure S1). Besides that, these two groups presented differences in genome length (~145 kb vs. ~72 kb) and GC content (0.32 vs. 0.38) (p = 0.03) (Table S3). In addition, some genomes presenting unique tRNA isotype arrangement (i.e., not assigned to any tRNA gene cluster group) were grouped considering MCP phylogenetic clusters (e.g., Synechococcus phage S-PM2/S-CRM01, Stenotrophomonas phage vB SmaS-DLP6/IME-SM1 and Ralstonia phage RSP15), suggesting a common origin. In order to identify whether there was a bias concerning the presence of tRNA gene clusters in virulent or temperate bacteriophages, we search for the presence of integrase genes, which would characterize a temperate one, in the genomes. Among the 226 bacteriophages, only 23 presented an integrase gene, therefore most of the bacteriophages carrying tRNA gene clusters are virulent (p = 10−16). The temperate bacteriophages were restricted to G2 (Caulobacter phages), G6 (Mycobacterium phages) and G18 (Bacillus phages), besides two singletons (Roseobacter and Sphingobium phages). The integrase from G6 Mycobacterium phages was a serine integrase, while the others harbored tyrosine integrase (Table S3). 3.3. Codon Patterns in the tRNA Gene Clusters Based on the codons provided by the tRNA genes from the tRNA gene clusters it was possible to discriminate codon patterns among the tRNA gene cluster groups, besides slight intragroup differences. The AUGMet codon was the one presenting, in general, the higher copy number for most tRNA gene clusters (Figure 2). The number of codons per tRNA gene cluster ranged from 5 to 34, however, almost all clusters provided at least 13 codons (Table S4). Only the tRNA gene cluster from Cafeteria roenbergensis virus BV-PW1 presented a low number of codons (n = 5) even though the higher number of tRNA genes (n = 15). This codon redundancy suggests the occurrence of duplication events in this tRNA gene cluster. In order to verify a possible contribution of the codons provided by the tRNA genes from the tRNA gene clusters to the host translational machinery, we compared these codons with those most used by the whole genome and MCP gene, an expected highly expressed gene. Therefore, we performed RSCU analyzes based on the whole genomes and MCP genes, comparing them with the codons from the clusters. Among the 228 tRNA gene clusters, 134 provided codons that matched with at least 50% of the MCP codons with RSCU > 1, while that considering the whole genomes, only 39 tRNA gene clusters provided codons that matched with ≥50% of the codons most used by the genomes (Table S4). The median percentage of the MCP matching codons was higher (0.50; IQR, 0.39-0.56) than that of the whole genomes (0.42; IQR, 0.31-0.48) (p = 10−15). These results suggest that the tRNA gene clusters, in general, could participate in the expression of different virus genes, but would provide higher support to highly expressed genes as the MCP gene. 8 of 14 Viruses 2019, 11, 180 Figure 2. Codon patterns of the tRNA gene clusters. The heatmap shows the tRNA gene copy number (codons and isotypes) of each tRNA gene cluster. The background color of the labels is associated with each tRNA gene cluster group (indicated by the red labels or shown in Figure S1). The yellow background labels represent the Cellulophaga phages with the same tRNA gene cluster group. Genomes having identical codon pattern were collapsed, represented by the bold label. A larger version of this ﬁgure is provided in Figure S4. Figure 2. Codon patterns of the tRNA gene clusters. 3.3. Codon Patterns in the tRNA Gene Clusters The heatmap shows the tRNA gene copy number (codons and isotypes) of each tRNA gene cluster. The background color of the labels is associated with each tRNA gene cluster group (indicated by the red labels or shown in Figure S1). The yellow background labels represent the Cellulophaga phages with the same tRNA gene cluster group. Genomes having identical codon pattern were collapsed, represented by the bold label. A larger version of this ﬁgure is provided in Figure S4. Viruses 2019, 11, 180 9 of 14 3.5. Source of the Phage tRNA Gene Clusters To infer the possible source of the bacteriophage tRNA gene clusters we performed a BLAST analysis using as query the tRNA gene cluster regions against bacteria and archaea genomes, and as result none highly similar regions were observed between these two groups. Next, we determined any similarity between the tRNA gene sequences from the clusters (2156 unique sequences) with tRNA gene sequences from bacteria and archaea. 118/2156 tRNA genes from the clusters, comprehending 62 phages, presented high similarity with bacterial tRNA sequences from the same phylum (bacteria/bacteriophage), e.g., Mycobacterium phage with similar sequence from Actinobacteria. However, in many cases, it was not observed the relation between bacteria phylum and bacteriophage host, e.g., Mycobacterium phage Bxz1 with similar sequences to Cyanobacteria, Bacteroidetes and Parcubacteria phyla; and Streptomyces phage BRock with similar sequences to Firmicutes and Proteobacteria phyla (Table S6). 3.4. CDS and tRNA Gene Cluster Groups To ﬁnd out whether the tRNA gene clusters were associated with particular CDS (coding DNA sequence), we investigated the genes within and ﬂanking the clusters. Most of these genes encoded hypothetical proteins, and a large portion of them was only identiﬁed in the carrier virus. Each tRNA gene cluster group presented core genes (i.e., a set of genes present in all clusters from a group), except the G1 group. Among the groups with putative genes: the G4 group presented 13 core genes, one of them being an exonuclease; the G5 group presented 14 core genes, one of them being a dNMP kinase; the G6 group presented four core genes, one of them being an HNH endonuclease; the G9 group presented 14 core genes, being three of them an HNH endonuclease, phosphoribosyl transferase, and tyrosine phosphatase; and the G11 group presented one core gene, a DNA helicase. In a bipartite network analysis of these CDS, we observed that only a few CDS associated with the tRNA gene cluster groups were shared among them (Figure S5). Besides that, the groups sharing CDS are mostly related to a same bacterial host phylum (Table S5). Considering the 25 singleton clusters, 11 share CDS with other tRNA gene cluster or singletons. Contrasting with this, a bipartite network analysis considering the whole genome gene content revealed a large network including all genomes but Cafeteria roenbergensis virus BV-PW1, Halovirus HGTV-1 and Sulﬁtobacter phage phiCB2047-B (data not shown). This indicates that the phages harboring tRNA gene cluster, even with different groups, are involved in lateral gene transfer events and may share the same niches. 4. Discussion Viruses are dependent on the protein synthesis machinery of their hosts, and therefore, they usually do not harbor translation-related genes. However, eventually, tRNA genes have been identiﬁed in virus genomes from lower organisms. The current availability of thousands of virus genomes leads us to perform an in-silico survey aiming to identify tRNA genes in viruses. To date, tRNA genes had only been observed in dsDNA viruses [11,45], however, here is revealed a diverse scenario, since tRNA genes were also identiﬁed in ssRNA (+) and ssDNA viruses, belonging to Retroviridae, Virgaviridae, Luteoviridae, Dicistroviridae and Inoviridae families. Bailly-Bechet et al. [2] analyzed a small set of phages and concluded that the main difference between the phages with and without tRNA genes was at the length of the genome since phages containing tRNAs were signiﬁcantly longer than those without these genes (average length of 74 kb vs. 32 kb). In the present study with a huge virus genome data set, this same bias was observed, since tRNA genes were observed in longer genomes (average length of 97 kb vs. 12 kb). Stressing again the of correlation between the number of tRNA genes and genome length. Viruses 2019, 11, 180 Viruses 2019, 11, 180 10 of 14 Since the presence of tRNA genes in virus genomes is supposed to be intriguing [2], the presence of large repertoires of these genes is much more intriguing. In this study, considering the large data set analyzed, tRNA gene clusters were only observed in ~2% of the genomes. Interestingly, we observed a correlation between the number of tRNA genes and their organization in clusters. Considering the genomes with 15 or more tRNA genes, 228 (~98%) tended to have their tRNA genes organized in clusters. Besides, although there is a positive correlation between the total number of tRNA genes and the genome length, the inverse occurs considering the clustered tRNA genes. In fact, the organization of tRNA genes in clusters would favor the compaction of the genome, which is a common characteristic of viruses [2,4], especially considering those of small size. Therefore, large viruses would not have a trend to carry highly dense tRNA gene clusters, instead, the tRNA genes are dispersed along the genome. 4. Discussion Interestingly, the two recently characterized Tupanviruses that have the highest number of tRNA genes so far identiﬁed in viruses (up to 70) [5], presented most of them not arranged in large clusters, as identiﬁed in the present study in viruses carrying a large number of tRNA genes. Each one carries 10-11 tRNA genes in small clusters (data not shown). In the present study that considered genomes from 5 kb to 2.5 Mb, tRNA gene clusters were identiﬁed in genomes ranging from 72 to 617 kb, being concentrated in those from 100 to 200 kb length, even within viral families with longer genomes. Even though tRNA genes had been identiﬁed in several viral families, their arrangement in clusters seems to be restricted to dsDNA viral families: Myoviridae, Podoviridae, and Siphoviridae from Caudovirales order. The identiﬁcation of hundreds of virus genomes harboring tRNA gene clusters contrasts with the previous scenario in which tRNA gene clusters were identiﬁed only in few bacteriophages, mainly mycobacteriophages [4,15,16], enlarging signiﬁcantly the presence and distribution of these structures within viruses. The Streptomyces phages were those presenting the higher number of tRNA genes within and outside the clusters. Curiously, their hosts (Streptomyces spp.) are supposed to not carry tRNA arrays [24]. In contrast to this scenario, mycobacteriophages also had a high number of tRNA genes inside and outside the clusters, as well as their hosts (Mycobacterium spp.), and in addition, they would act as vectors in the dissemination of tRNA gene clusters in the host [16]. The presence of virus-encoded tRNA genes was associated with selective acquisitions since in several viruses these genes correspond to the codons/amino acids that are enriched in their most expressed genes/proteins, while the remaining tRNA genes would be supplied by the host [2–4,11,46]. In fact, in this study, it was shown that different tRNA genes from tRNA gene clusters appear to have been acquired from different bacterial sources. Therefore, it would be expected that the presence of a large repertoire of tRNA genes provided by the virus would ensure greater independence of the host tRNA genes. Indeed, concerning a highly expressed gene, MCP, some tRNA gene clusters presented a high percentage of matching codons that could participate in the translational process. 4. Discussion Although the tRNA gene clusters may support the expression of the virus genes, mainly the highly expressed ones, they do not seem to have a fundamental role, and/or they are still under evolutionary process, i.e., a recent acquisition. q Among the bacteriophages harboring the tRNA gene clusters, there was a higher proportion of virulent than temperate ones, and this lifestyle trend was also observed considering tRNA genes [2,4]. Virulent and temperate bacteriophages interact differently with their hosts. Virulent bacteriophages exploit host resources in order to optimize their replicative cycles. The presence of extra tRNA genes would minimize host dependence and extend the host spectrum, improving their ﬁtness [47,48]. In fact, some of the bacteriophages harboring the tRNA gene clusters have been reported presenting a wide range of hosts [49–55]. Like plasmids, bacteriophages could have a role as vectors of the tRNA arrays/tRNA gene clusters dissemination [16,24]. Indeed, in a study focusing in the Mycobacterium genus, there was evidence of the role of mycobacteriophages in the horizontal transfer of tRNA arrays in some Mycobacterium species [16]. However, here, we did not ﬁnd clear evidence supporting this hypothesis considering viruses infecting genera other than Mycobacterium. In fact, some mycobacteriophages Viruses 2019, 11, 180 11 of 14 11 of 14 are temperate phages, whereas most of the viruses carrying tRNA gene clusters, revealed here, are virulent. The temperate lifestyle, which involves a direct genome integration step, raise the chance of traits acquisition by the host, being much more common than virulent ones. Most of the CDS associated with the tRNA gene clusters are hypothetical, however, in some mycobacteriophages, there was an HNH endonuclease, and it is implicated in the generation of tRNA repertoire diversity [15]. HNH endonuclease belongs to the family of the homing endonuclease that acts as a mobile element, inducing the transfer of its own gene and the ﬂanking regions. It was shown in T4-related phages that the homing endonuclease SegB acts spreading its own gene and the surrounding tRNA genes among related phages [56]. Therefore, the HNH endonuclease in the mycobacteriophages could play the role of dissemination of tRNA gene clusters among related organisms. 4. Discussion Supplementary Materials: The following are available online at http://www.mdpi.com/1999-4915/11/2/180/s1, Figure S1: tRNA isotype organization, Figure S2: Maximum likelihood tree based on concatenated tRNA gene nucleotide sequences from tRNA gene clusters, Figure S3: Maximum likelihood tree based on Major Capsid Protein (MCP) amino acid sequences, Figure S4: Codon patterns of the tRNA gene clusters, Figure S5: Bipartite network of gene content associated to the tRNA gene clusters, Table S1: Number of genomes and corresponding viral families identiﬁed in the data set, Table S2: List of the predicted tRNA genes in the classiﬁed virus genomes, Table S3: Features of viral genomes harboring tRNA gene clusters, Table S4: Number of matching codons, Table S5: CDS associated with tRNA gene clusters shared among the phages, Table S6: List of tRNA gene sequences presenting ≥90% identity. Author Contributions: S.M. performed the in-silico analysis, discussed the results and wrote the paper; A.C.V. conceived and supervised all steps of the study, discussed the results and wrote the paper. Funding: This study was ﬁnanced in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Super Brasil (CAPES) - Finance Code 001. Funding: This study was ﬁnanced in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. Acknowledgments: We are particularly grateful to Edson Delatorre for helpful discussion. Conﬂicts of Interest: The authors declare that the research was conducted in the absence of any commercial or ﬁnancial relationships that could be construed as a potential conﬂict of interest. Conﬂicts of Interest: The authors declare that the research was conducted in the absence of any commercial or ﬁnancial relationships that could be construed as a potential conﬂict of interest. References 1. Weinbauer, M.G. Ecology of prokaryotic viruses. FEMS Microbiol. Rev. 2004, 28, 127–181. [CrossRef] 2. Bailly-Bechet, M.; Vergassola, M.; Rocha, E. Causes for the intriguing presence of tRNAs in phages. Genome Res. 2007, 17, 1486–1495. [CrossRef] . Bahir, I.; Fromer, M.; Prat, Y.; Linial, M. Viral adaptation to host: A proteome-based analysis of codon us and amino acid preferences. Mol. Syst. Biol. 2009, 5, 311. [CrossRef] 4. Delesalle, V.A.; Tanke, N.T.; Vill, A.C.; Krukonis, G.P. Testing hypotheses for the presence of tRNA genes in mycobacteriophage genomes. Bacteriophage 2016, 6, e1219441. [CrossRef] 5. Abrahão, J.; Silva, L.; Silva, L.S.; Khalil, J.Y.B.; Rodrigues, R.; Arantes, T.; Assis, F.; Boratto, P.; Andrade, M.; Kroon, E.G.; et al. Tailed giant Tupanvirus possesses the most complete translational apparatus of the known virosphere. Nat. Commun. 2018, 9, 749. [CrossRef] 6. Schulz, F.; Yutin, N.; Ivanova, N.N.; Ortega, D.R.; Lee, T.K.; Vierheilig, J.; Daims, H.; Horn, M.; Wagner, M.; Jensen, G.J.; et al. Giant viruses with an expanded complement of translation system components. Science 2017, 356, 82–85. [CrossRef] 7. Bowden, R.J.; Simas, J.P.; Davis, A.J.; Efstathiou, S. Murine gammaherpesvirus 68 encodes tRNA-like sequences which are expressed during latency. J. Gen. Virol. 1997, 78 Pt 7, 1675–1687. [CrossRef] 8. Amgarten, D.; Martins, L.F.; Lombardi, K.C.; Antunes, L.P.; de Souza, A.P.S.; Nicastro, G.G.; Kitajima, E.W.; Quaggio, R.B.; Upton, C.; Setubal, J.C.; et al. Three novel Pseudomonas phages isolated from composting provide insights into the evolution and diversity of tailed phages. BMC Genom. 2017, 18, 346. [CrossRef] 9. Dreher, T.W. Viral tRNAs and tRNA-like structures. Wiley Interdiscip. Rev. RNA 2010, 1, 402–414. [CrossRef] 10. Colson, P.; Fournous, G.; Diene, S.M.; Raoult, D. Codon usage, amino acid usage, transfer RNA and amino-acyl-tRNA synthetases in Mimiviruses. Intervirology 2013, 56, 364–375. [CrossRef] 11. Albers, S.; Czech, A. Exploiting tRNAs to Boost Virulence. Life 2016, 6, 4. [CrossRef] 12. Fischer, M.G.; Allen, M.J.; Wilson, W.H.; Suttle, C.A. Giant virus with a remarkable complement of genes infects marine zooplankton. Proc. Natl. Acad. Sci. USA 2010, 107, 19508–19513. [CrossRef] 12 of 14 Viruses 2019, 11, 180 12 of 14 13. Hatfull, G.F.; Jacobs-Sera, D.; Lawrence, J.G.; Pope, W.H.; Russell, D.A.; Ko, C.C.; Weber, R.J.; Patel, M.C.; Germane, K.L.; Edgar, R.H.; et al. Comparative genomic analysis of 60 Mycobacteriophage genomes: Genome clustering, gene acquisition, and gene size. J. Mol. Biol. 2010, 397, 119–143. [CrossRef] 14. References Senˇcilo, A.; Jacobs-Sera, D.; Russell, D.A.; Ko, C.C.; Bowman, C.A.; Atanasova, N.S.; Österlund, E.; Oksanen, H.M.; Bamford, D.H.; Hatfull, G.F.; et al. Snapshot of haloarchaeal tailed virus genomes. RNA Biol. 2013, 10, 803–816. [CrossRef] 15. Pope, W.H.; Anders, K.R.; Baird, M.; Bowman, C.A.; Boyle, M.M.; Broussard, G.W.; Chow, T.; Clase, K.L.; Cooper, S.; Cornely, K.A.; et al. Cluster M mycobacteriophages Bongo, PegLeg, and Rey with unusually large repertoires of tRNA isotypes. J. Virol. 2014, 88, 2461–2480. [CrossRef] 16. Morgado, S.M.; Vicente, A.C.P. Beyond the Limits: tRNA Array Units in Mycobacterium Genomes. Front. Microbiol. 2018, 9, 1042. [CrossRef] 17. Jung, P.P.; Friedrich, A.; Souciet, J.L.; Louis, V.; Potier, S.; de Montigny, J.; Schacherer, J. Complete mitochondrial genome sequence of the yeast Pichia farinosa and comparative analysis of closely related species. Curr. Genet. 2010, 56, 507–515. [CrossRef] 18. Friedrich, A.; Jung, P.P.; Hou, J.; Neuvéglise, C.; Schacherer, J. Comparative Mitochondrial Genomics within and among Yeast Species of the Lachancea Genus. PLoS ONE 2012, 7, e47834. [CrossRef] 9. Li, E.; Li, X.; Wu, X.; Feng, G.; Zhang, M.; Shi, H.; Wang, L.; Jiang, J. Complete nucleotide sequence and g rearrangement of the mitochondrial genome of Occidozyga martensii. J. Genet. 2014, 93, 631–641. [Cross 19. Li, E.; Li, X.; Wu, X.; Feng, G.; Zhang, M.; Shi, H.; Wang, L.; Jiang, J. Complete nucleotide sequence and gene rearrangement of the mitochondrial genome of Occidozyga martensii. J. Genet. 2014, 93, 631–641. [CrossRef] 20. Morgado, S.M.; Vicente, A.C.P. Exploring tRNA gene cluster in archaea. Mem. Inst. Oswaldo Cruz 2019, 114, e180348. [CrossRef] 20. Morgado, S.M.; Vicente, A.C.P. Exploring tRNA gene cluster in archaea. Mem. Inst. Oswaldo Cruz 2019, 114, e180348. [CrossRef] 21. Tawari, B.; Ali, I.K.; Scott, C.; Quail, M.A.; Berriman, M.; Hall, N.; Clark, C.G. Patterns of evolution in the unique tRNA gene arrays of the genus Entamoeba. Mol. Biol. Evol. 2008, 25, 187–198. [CrossRef] 22. Bermudez-Santana, C.; Attolini, C.S.-O.; Kirsten, T.; Engelhardt, J.; Prohaska, S.J.; Steigele, S.; Stadler, P.F. Genomic organization of eukaryotic tRNAs. BMC Genom. 2010, 11, 270. [CrossRef] 23. Puerto-Galan, L.; Vioque, A. Expression and processing of an unusual tRNA gene cluster in the cyanobacterium Anabaena sp. PCC 7120. FEMS Microbiol. Lett. 2012, 337, 10–17. [CrossRef] 24. Tran, T.T.T.; Belahbib, H.; Bonnefoy, V.; Talla, E. A Comprehensive tRNA Genomic Survey Unravels the Evolutionary History of tRNA Arrays in Prokaryotes. Genome Biol. Evol. 2016, 8, 282–295. [CrossRef] 25. References Abe, T.; Inokuchi, H.; Yamada, Y.; Muto, A.; Iwasaki, Y.; Ikemura, T. tRNADB-CE: tRNA gene database well-timed in the era of big sequence data. Front. Genet. 2014, 5, 114. [CrossRef] 38. Li, W.; Godzik, A. Cd-hit: A fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 2006, 22, 1658–1659. [CrossRef] 39. R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2018; Available online: https://www.R-project.org (accessed on 31 December 2018). 40. RStudio Team. RStudio: Integrated Development for R; RStudio, Inc.: Boston, MA, USA, 2015; Available online: http://www.rstudio.com (accessed on 31 December 2018). 41. Hunnicutt, L.E.; Hunter, W.B.; Cave, R.D.; Powell, C.A.; Mozoruk, J.J. Genome sequence and molecular characterization of Homalodisca coagulata virus-1, a novel virus discovered in the glassy-winged sharpshooter (Hemiptera: Cicadellidae). Virology 2006, 350, 67–78. [CrossRef] 42. Oude Munnink, B.B.; Canuti, M.; Deijs, M.; de Vries, M.; Jebbink, M.F.; Rebers, S.; Molenkamp, R.; van Hemert, F.J.; Chung, K.; Cotten, M.; et al. Unexplained diarrhoea in HIV-1 infected individuals. BMC Infect. Dis. 2014, 14, 22. [CrossRef] 43. Ibaba, J.D.; Laing, M.D.; Gubba, A. Pepo aphid-borne yellows virus: A new species inthe genus Polerovirus. Virus Genes. 2017, 53, 134–136. [CrossRef] 44. Shirako, Y.; Wilson, T.M. Complete nucleotide sequence and organization of thebipartite RNA genome of soil-borne wheat mosaic virus. Virology 1993, 195, 16–32. [CrossRef] 45. Chithambaram, S.; Prabhakaran, R.; Xia, X. Differential codon adaptation between dsDNA and ssDNA phages in Escherichia coli. Mol. Biol. Evol. 2014, 31, 1606–1617. [CrossRef] 46. Rak, R.; Dahan, O.; Pilpel, Y. Repertoires of tRNAs: The Couplers of Genomics and Proteomics. Ann. Rev. Cell Dev. Biol. 2018, 34, 239–264. [CrossRef] 47. Chopin, A.; Bolotin, A.; Sorokin, A.; Ehrlich, S.D.; Chopin, M.-C. Analysis of six prophages in Lactococcus lactis IL1403: Different genetic structure of temperate and virulent phage populations. Nucleic Acids Res. 2001, 29, 644–651. [CrossRef] 48. Mavrich, T.N.; Hatfull, G.F. Bacteriophage evolution differs by host, lifestyle and genome. Nat. Microbiol. 2017, 2, 17112. [CrossRef] 49. Miller, E.S.; Heidelberg, J.F.; Eisen, J.A.; Nelson, W.C.; Durkin, A.S.; Ciecko, A.; Feldblyum, T.V.; White, O.; Paulsen, I.T.; Nierman, W.C.; et al. Complete genome sequence of the broad-host-range vibriophage KVP40: Comparative genomics of a T4-related bacteriophage. J. Bacteriol. 2003, 185, 5220–5233. [CrossRef] 50. Lehman, S.M.; Kropinski, A.M.; Castle, A.J.; Svircev, A.M. Complete Genome of the Broad-Host-Range Erwinia amylovora Phage ΦEa21-4 and Its Relationship to Salmonella Phage Felix O1. Appl. References Alamos, P.; Tello, M.; Bustamante, P.; Gutiérrez, F.; Shmaryahu, A.; Maldonado, J.; Levicán, G.; Orellana, O. Functionality of tRNAs encoded in a mobile genetic element from an acidophilic bacterium. RNA Biol. 2018, 15, 518–527. [CrossRef] 26. Laslett, D.; Canback, B. ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences. Nucleic Acids Res. 2004, 32, 11–16. [CrossRef] 27. Lowe, T.M.; Chan, P.P. tRNAscan-SE On-line: Integrating search and context for analysis of transfer RNA genes. Nucleic Acids Res. 2016, 44, W54–W57. [CrossRef] 28. Wood, D.E.; Salzberg, S.L. Kraken: Ultrafast metagenomic sequence classiﬁcation using exact alignments. Genome Biol. 2014, 15. [CrossRef] 29. Seemann, T. Prokka: Rapid prokaryotic genome annotation. Bioinformatics 2014, 30, 2068–2069. [CrossRef] 30 Contreras-Moreira B ; Vinuesa P GET HOMOLOGUES a versatile software package for scalable and 29. Seemann, T. Prokka: Rapid prokaryotic genome annotation. Bioinformatics 2014, 30, 2068–2069. [CrossRef] 29. Seemann, T. Prokka: Rapid prokaryotic genome annotation. Bioinformatics 2014, 30, 2068–2069. [CrossRef] 30. Contreras-Moreira, B.; Vinuesa, P. GET_HOMOLOGUES, a versatile software package for scalable and robust microbial pangenome analysis. Appl. Environ. Microbiol. 2013, 79, 7696–7701. [CrossRef] 31. Lanza, V.F.; Baquero, F.; de la Cruz, F.; Coque, T.M. AcCNET (Accessory Genome Constellation Network): Comparative genomics software for accessory genome analysis using bipartite networks. Bioinformatics 2017, 33, 283–285. [CrossRef] 32. Shannon, P.; Markiel, A.; Ozier, O.; Baliga, N.S.; Wang, J.T.; Ramage, D.; Amin, N.; Schwikowski, B.; Ideker, T. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 2003, 13, 2498–2504. [CrossRef] 33. Guindon, S.; Dufayard, J.F.; Lefort, V.; Anisimova, M.; Hordijk, W.; Gascuel, O. New algorithms and methods to estimate maximum-likelihood phylogenies: Assessing the performance of PhyML 3.0. Syst. Biol. 2010, 59, 307–321. [CrossRef] 34. Sela, I.; Ashkenazy, H.; Katoh, K.; Pupko, T. GUIDANCE2: Accurate detection of unreliable alignment regions accounting for the uncertainty of multiple parameters. Nucleic Acids Res. 2015, 43, W7–W14. [CrossRef] Viruses 2019, 11, 180 13 of 14 13 of 14 35. Keane, T.M.; Creevey, C.J.; Pentony, M.M.; Naughton, T.J.; Mclnerney, J.O. Assessment of methods for amino acid matrix selection and their use on empirical data shows that ad hoc assumptions for choice of matrix are not justiﬁed. BMC Evol. Biol. 2006, 6, 29. [CrossRef] 36. Letunic, I.; Bork, P. Interactive tree of life (iTOL) v3: An online tool for the display and annota phylogenetic and other trees. Nucleic Acids Res. 2016, 44, W242–W245. [CrossRef] 37. © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). 55. Merabishvili, M.; Vandenheuvel, D.; Kropinski, A.M.; Mast, J.; De Vos, D.; Verbeken, G.; Noben, J.P.; Lavigne, R.; Vaneechoutte, M.; Pirnay, J.P. Characterization of newly isolated lytic bacteriophages active against Acinetobacter baumannii. PLoS ONE 2014, 9, e104853. [CrossRef] 56. Brok-Volchanskaya, V.S.; Kadyrov, F.A.; Sivogrivov, D.E.; Kolosov, P.M.; Sokolov, A.S.; Shlyapnikov, M.G.; Kryukov, V.M.; Granovsky, I.E. Phage T4 SegB protein is a homing endonuclease required for the preferred inheritance of T4 tRNA gene region occurring in co-infection with a related phage. Nucleic Acids Res. 2008, 36, 2094–2105. [CrossRef] References Environ. Microbiol. 2009, 75, 2139–2147. [CrossRef] 51. Santos, S.B.; Kropinski, A.M.; Ceyssens, P.J.; Ackermann, H.W.; Villegas, A.; Lavigne, R.; Krylov, V.N.; Carvalho, C.M.; Ferreira, E.C.; Azeredo, J. Genomic and proteomic characterization of the broad-host-range Salmonella phage PVP-SE1: Creation of a new phage genus. J. Virol. 2011, 85, 11265–11273. [CrossRef] 52. Kim, J.H.; Son, J.S.; Choi, Y.J.; Choresca, C.H., Jr.; Shin, S.P.; Han, J.E.; Jun, J.W.; Park, S.C. Complete genome sequence and characterization of a broad-host range T4-like bacteriophage phiAS5 infecting Aeromonas salmonicida subsp. salmonicida. Vet. Microbiol. 2011, 157, 164–171. [CrossRef] 53. Schwarzer, D.; Buettner, F.F.; Browning, C.; Nazarov, S.; Rabsch, W.; Bethe, A.; Oberbeck, A.; Bowman, V.D.; Stummeyer, K.; Mühlenhoff, M.; et al. A multivalent adsorption apparatus explains the broad host range of phage phi92: A comprehensive genomic and structural analysis. J. Virol. 2012, 86, 10384–10398. [CrossRef] 54. El-Arabi, T.F.; Grifﬁths, M.W.; She, Y.-M.; Villegas, A.; Lingohr, E.J.; Kropinski, A.M. Genome sequence and analysis of a broad-host range lytic bacteriophage that infects the Bacillus cereus group. Virol. J. 2013, 10, 48. [CrossRef] Viruses 2019, 11, 180 14 of 14 14 of 14 55. Merabishvili, M.; Vandenheuvel, D.; Kropinski, A.M.; Mast, J.; De Vos, D.; Verbeken, G.; Noben, J.P.; Lavigne, R.; Vaneechoutte, M.; Pirnay, J.P. Characterization of newly isolated lytic bacteriophages active against Acinetobacter baumannii. PLoS ONE 2014, 9, e104853. [CrossRef] 56. Brok-Volchanskaya, V.S.; Kadyrov, F.A.; Sivogrivov, D.E.; Kolosov, P.M.; Sokolov, A.S.; Shlyapnikov, M.G.; Kryukov, V.M.; Granovsky, I.E. Phage T4 SegB protein is a homing endonuclease required for the preferred inheritance of T4 tRNA gene region occurring in co-infection with a related phage. Nucleic Acids Res. 2008, 36, 2094–2105. [CrossRef] 56. Brok-Volchanskaya, V.S.; Kadyrov, F.A.; Sivogrivov, D.E.; Kolosov, P.M.; Sokolov, A.S.; Shlyapnikov, M.G.; Kryukov, V.M.; Granovsky, I.E. Phage T4 SegB protein is a homing endonuclease required for the preferred inheritance of T4 tRNA gene region occurring in co-infection with a related phage. Nucleic Acids Res. 2008, 36, 2094–2105. [CrossRef] © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.