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<table border="1" class="dataframe"> <tr> <th> Variable </th> <th> DrotAA n = 882 </th> <th> Non-DrotAA n = 11,610 </th> <th> Total n = 12,492 </th> <th> value P </th> </tr> <tr> <td> Medical/Surgical Status, n (%): </td> <td> </td> <td> </td> <td> </td> <td> ...
PMC2717475_table_1
<table border="1" class="dataframe"> <tr> <th> Variable </th> <th> DrotAA n = 882 </th> <th> Non-DrotAA n = 11,610 </th> <th> Total n = 12,492 </th> <th> P value </th> </tr> <tr> <td> IV fluid resuscitation, n (%) </td> <td> (n = 782) 718 (91.8) </td> <td> (n = 1...
PMC2717475_table_2
<table border="1" class="dataframe"> <tr> <th> Variable </th> <th> DrotAA n = 882 </th> <th> Non-DrotAA n = 11,610 </th> <th> Total n = 12,492 </th> <th> P value </th> </tr> <tr> <td> Number of organ dysfunctions (OD): </td> <td> (n = 703) </td> <td> (n = 8910) ...
PMC2717475_table_3
<table border="1" class="dataframe"> <tr> <th> Variable </th> <th> DrotAA n = 882 </th> <th> Non-DrotAA n = 11,610 </th> <th> Total n = 12,492 </th> <th> P value </th> </tr> <tr> <td> Diabetes, n (%) </td> <td> (n = 766) 164 (21.4) </td> <td> (n = 10,352) 2441 (2...
PMC2717475_table_4
<table border="1" class="dataframe"> <tr> <th> </th> <th> </th> <th> </th> <th colspan="2"> DrotAA-treated patients </th> </tr> <tr> <th> Country </th> <th> Number of sites </th> <th> Enrolled patients, n (% overall) (n = 12,492) </th> <th> n, (% of total DrotAA patients)...
PMC2717475_table_5
<table border="1" class="dataframe"> <tr> <th> Mode l </th> <th> Hospital Mortality Adjusted by Treatment and </th> <th> n </th> <th> Adjusted R2 Value </th> <th> Goodness of Fit Chi-square </th> <th> P value for Treatment Factor in Multivariate Model </th> <th> Odds Rati...
PMC2717475_table_6
<table border="1" class="dataframe"> <tr> <th> Variable </th> <th> DrotAA n = 882 </th> <th> Non-DrotAA n = 11,610 </th> <th> Total n = 12,492 </th> <th> value P </th> </tr> <tr> <td> Discharge location by DrotAA use, n (%): </td> <td> (n = 807) </td> <td> (n = 1...
PMC2717475_table_7
<table border="1" class="dataframe"> <tr> <th> Virus </th> <th> Serotypes </th> <th> </th> </tr> <tr> <td> Rhinovirus </td> <td> &gt; 101 </td> <td> </td> </tr> <tr> <td> Influenza </td> <td> A, B </td> <td> </td> </tr> <tr> <td> RSV </td> <td> A,...
PMC2717562_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th colspan="2"> Acute (n = 70) </th> <th colspan="2"> Stable (n = 80) </th> <th> Value P </th> </tr> <tr> <th> </th> <th> No. </th> <th> % </th> <th> No. </th> <th> % </th> <th> </th> </tr> <tr> <td...
PMC2717562_table_1
<table border="1" class="dataframe"> <tr> <th> Virus </th> <th colspan="2"> Acute (N = 70) </th> <th colspan="2"> Stable (N = 80) </th> </tr> <tr> <th> </th> <th> No. </th> <th> % </th> <th> No. </th> <th> % </th> </tr> <tr> <td> Total virus (p = 0.018) <...
PMC2717562_table_2
<table border="1" class="dataframe"> <tr> <th> Patient's Characteristics </th> <th> </th> </tr> <tr> <td> Male/Female ratio </td> <td> 1:1 </td> </tr> <tr> <td> Age (y), median (range) </td> <td> 4.5 (6.0 mo-10 y) </td> </tr> <tr> <td> Total serum IgE at baseline (IU/m...
PMC2717565_table_0
<table border="1" class="dataframe"> <tr> <th> W (Kg) mean ± SD </th> <th> H (cm) mean ± SD </th> <th> BMI mean ± SD (centiles) </th> </tr> <tr> <td> All children </td> <td> </td> <td> </td> </tr> <tr> <td> T0 17,3 ± 9,6 </td> <td> T0 100,3 ± 14,9 </td> <td> T...
PMC2717565_table_1
<table border="1" class="dataframe"> <tr> <th> Entry vector type </th> <th> Compatible Destination vectors </th> <th> Incompatible Destination vectors </th> </tr> <tr> <td rowspan="4"> pENTR/pSM2 Series (non-GFP) </td> <td> pLenti X1 Series </td> <td> Seriesb pLenti PGK </td...
PMC2717805_table_0
<table border="1" class="dataframe"> <tr> <th> Vector </th> <th> Inducible expression in a T-REx cell line </th> </tr> <tr> <td> pENTR/pSUPER+ </td> <td> NO </td> </tr> <tr> <td> + pENTR/pTER </td> <td> YES </td> </tr> <tr> <td> pENTR/pSM2(U6) </td> <td> NO ...
PMC2717805_table_1
<table border="1" class="dataframe"> <tr> <th> Vector Series </th> <th> pSUPER, pTER </th> <th> pSM2-CMV, CMV/TO </th> <th> pSM2 CMV-GFP </th> <th> pEF-Series </th> </tr> <tr> <td> Lenti X2 Blast </td> <td> 104 </td> <td> </td> <td> N/A </td> <td> N/A ...
PMC2717805_table_2
<table border="1" class="dataframe"> <tr> <th> Tag sequence </th> <th> Number of tags in disease libraries* </th> <th> Number of tags in normal libraries </th> <th> Gene </th> <th> Fold increase from normal </th> <th> RefSeq accession number </th> </tr> <tr> <td> </td> ...
PMC2717845_table_0
<table border="1" class="dataframe"> <tr> <th> Trait </th> <th> Marker* </th> <th> Beta** </th> <th> t-value </th> <th> R2 Adjusted </th> <th> Signifi cance (P) </th> </tr> <tr> <td rowspan="5"> TLD </td> <td> 825.9 </td> <td> –0.874 </td> <td> 5.404...
PMC2717847_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th rowspan="2"> Total (N = 119) </th> <th rowspan="2"> With Data* (N = 78) N (%) </th> <th rowspan="2"> Without Data* (N = 41) N (%) </th> </tr> <tr> <th> </th> </tr> <tr> <td> Sex </td> <td> </td> <td> </td> <td> ...
PMC2717905_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th rowspan="2"> Total (n = 82) </th> <th rowspan="2"> With Data (N = 52) N (%) </th> <th rowspan="2"> Without Data (N = 30) N (%) </th> </tr> <tr> <th> </th> </tr> <tr> <td> Race/ethnicity </td> <td> </td> <td> </td> ...
PMC2717905_table_1
<table border="1" class="dataframe"> <tr> <th> </th> <th colspan="3"> Cord Blood </th> <th colspan="3"> Maternal Peripheral Blood </th> <th> </th> </tr> <tr> <th> </th> <th> N </th> <th> Median % </th> <th> Range </th> <th> N </th> <th> Median % </th> <t...
PMC2717905_table_2
<table border="1" class="dataframe"> <tr> <th> </th> <th> </th> <th colspan="4"> Proliferation Index (PI)* </th> <th> </th> </tr> <tr> <th> </th> <th> </th> <th colspan="2"> CD25+ Undepleted </th> <th colspan="2"> CD25+ Depleted </th> <th> </th> </tr> <tr> <th> </th...
PMC2717905_table_3
<table border="1" class="dataframe"> <tr> <th rowspan="2"> or </th> <th> lactate+1B </th> <th> lactate+2B </th> <th> lactate+3B </th> </tr> <tr> <td> 0.80% </td> <td> 0.36% </td> <td> 1.89% </td> </tr> <tr> <td> #7 </td> <td> 0.00% </td> <td> 1.83...
PMC2717907_table_0
<table border="1" class="dataframe"> <tr> <th> Compound </th> <th colspan="2"> % [U-13C]-AlaA </th> <th colspan="2"> % [U-13C]-LactateA </th> <th colspan="2"> % [U-13C]-GlucoseA </th> <th colspan="2"> % [13C-2]-GluA </th> </tr> <tr> <th> </th> <th> Non-cancerous </th> ...
PMC2717907_table_1
<table border="1" class="dataframe"> <tr> <th> Compound </th> <th colspan="2"> #6 sqCB, grade II </th> <th colspan="2"> #7 adenoCB, grade II </th> <th colspan="2"> #8 sqCB, grade II-III </th> <th colspan="2"> #9 sqCB, grade II </th> <th colspan="2"> #10 sqCB, grade III </th> ...
PMC2717907_table_2
<table border="1" class="dataframe"> <tr> <th> </th> <th colspan="2"> R2 </th> </tr> <tr> <th> PlotsB </th> <th> Non-cancerous </th> <th> Cancer </th> </tr> <tr> <td> [Ala] versus [succinate] </td> <td> 0.025 </td> <td> 0.761 </td> </tr> <tr> <td> [13C-Al...
PMC2717907_table_3
<table border="1" class="dataframe"> <tr> <th> </th> <th colspan="7"> Fold ChangeA </th> </tr> <tr> <th> GenesB </th> <th> PC </th> <th> GLS </th> <th> IDH3 </th> <th> OGDH </th> <th> SDH </th> <th> FH </th> <th> MDH2 </th> </tr> <tr> <td> Ave...
PMC2717907_table_4
<table border="1" class="dataframe"> <tr> <th> Gene/accession no </th> <th> Forward sequence </th> <th> Reverse sequence </th> </tr> <tr> <td> FH/NM_000143.2 </td> <td> TCTGGTCCTCGGTCAGGTCTG </td> <td> GACAGTGACAGCAACATGGTTCC </td> </tr> <tr> <td> GLS/NM_014905 </td...
PMC2717907_table_5
<table border="1" class="dataframe"> <tr> <th> Patient </th> <th> Tissuea </th> <th> Env clone </th> <th> MDM entryb </th> <th> b12 IC50c </th> <th> b6 IC50c </th> <th> sCD4 IC50c </th> <th> PS IC50c </th> </tr> <tr> <td rowspan="4"> MACS2 </td> <td> ...
PMC2717910_table_0
<table border="1" class="dataframe"> <tr> <th> Stain </th> <th> Stock solution </th> <th> Staining procedure </th> </tr> <tr> <td rowspan="5"> PTA </td> <td> 1% (w/v) phosphotungstic acid in water </td> <td> Mix 30 ml 1% PTA solution + 70 ml absolute ethanol to make 0.3% PTA i...
PMC2717911_table_0
<table border="1" class="dataframe"> <tr> <th> Fixative </th> <th> Notes </th> </tr> <tr> <td rowspan="4"> neutral-buffered formalin (10% NBF) </td> <td> Formalin = 37% formaldehyde solution (aq.). </td> </tr> <tr> <td> Normally used at 10% dilution in phosphate buffer at pH 7.0 ...
PMC2717911_table_1
<table border="1" class="dataframe"> <tr> <th> Employment rights </th> <th colspan="5"> Category of employment </th> </tr> <tr> <th> </th> <th colspan="4"> Non-permanent worker </th> <th> Permanent worker </th> </tr> <tr> <th> </th> <th> Political appointment </th> <th>...
PMC2717912_table_0
<table border="1" class="dataframe"> <tr> <th> Political appointees </th> <th> Permanent workers </th> </tr> <tr> <td> Leave </td> <td> Leave </td> </tr> <tr> <td> Maternity </td> <td> Maternity </td> </tr> <tr> <td> Adoption </td> <td> Adoption </td> </tr...
PMC2717912_table_1
<table border="1" class="dataframe"> <tr> <th> Year </th> <th> Ratio of permanent to non-permanent workers </th> </tr> <tr> <td> 2002 </td> <td> 5.49:1 </td> </tr> <tr> <td> 2003 </td> <td> 3.02:1 </td> </tr> <tr> <td> 2004 </td> <td> 2.35:1 </td> </tr> <...
PMC2717912_table_2
<table border="1" class="dataframe"> <tr> <th> RNAeasy </th> <th> Trizol </th> </tr> <tr> <td> 8.1 </td> <td> 7.3 </td> </tr> <tr> <td> 8.8 </td> <td> 7.4 </td> </tr> <tr> <td> 8.2 </td> <td> 6.7 </td> </tr> </table>
PMC2717914_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th> minus 70°C </th> <th> Boonfix </th> <th> B-RLT </th> <th> RNAlater </th> </tr> <tr> <td rowspan="3"> True cut (dry) </td> <td> 7.9 </td> <td> 7.0 </td> <td> 8.7 </td> <td> 9.2 </td> </tr> <t...
PMC2717914_table_1
<table border="1" class="dataframe"> <tr> <th> </th> <th> Mean score (SD) </th> </tr> <tr> <td> Overall QoL and general health perceptions </td> <td> 2.9 (0.8) </td> </tr> <tr> <td> Physical </td> <td> 13.3 (3.2) </td> </tr> <tr> <td> Psychological </td> <td> 13...
PMC2717916_table_0
<table border="1" class="dataframe"> <tr> <th colspan="3"> INPUT FACTORS (controlled on-line) </th> <th colspan="5"> MEASURABLE OUTPUT (measured offline) </th> </tr> <tr> <th> T (°C) </th> <th> pH </th> <th> DO (%) </th> <th> OD595 </th> <th> RFU (mL-1) </th> <th> ...
PMC2717918_table_0
<table border="1" class="dataframe"> <tr> <th> Source </th> <th> Degrees of Freedom </th> <th> Sum of Squares </th> <th> Mean Square </th> <th> F statistic </th> <th> p value </th> </tr> <tr> <td> Regression </td> <td> 6 </td> <td> 1288405 </td> <td> ...
PMC2717918_table_1
<table border="1" class="dataframe"> <tr> <th> T(°C) </th> <th> pH </th> <th> DO(%) </th> </tr> <tr> <td> 20 </td> <td> 7.5 </td> <td> 60 </td> </tr> <tr> <td> 20 </td> <td> 7.7 </td> <td> 80 </td> </tr> <tr> <td> 27 </td> <td> 8 </td> ...
PMC2717918_table_2
<table border="1" class="dataframe"> <tr> <th> Time (min) </th> <th> T (°C) </th> <th> pH </th> <th> DO (%) </th> </tr> <tr> <td> 0 </td> <td> 30 </td> <td> 6 </td> <td> 30 </td> </tr> <tr> <td> 15 </td> <td> 28 </td> <td> 6.4 </td> <td...
PMC2717918_table_3
<table border="1" class="dataframe"> <tr> <th> No. (sample code) (bleeding date) </th> <th> PR3-ANCA (U/ml) </th> <th> MPO-ANCA (U/ml) </th> </tr> <tr> <td> 1. (Q9-40) (5/9/1996) </td> <td> 29.2 </td> <td> &lt; 1.3 </td> </tr> <tr> <td> (R9-10) (9/27/1996) </td> <...
PMC2717921_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th> Patient without palsy (n = 56) </th> <th> Patient with Palsy (n = 18) </th> </tr> <tr> <td> Sex (M/F) </td> <td> 36/20 </td> <td> 12/6 </td> </tr> <tr> <td> Mean age at surgery (years) </td> <td> 60.63 </...
PMC2717922_table_0
<table border="1" class="dataframe"> <tr> <th> JOA SCORE </th> <th> </th> </tr> <tr> <td rowspan="5"> I. Motor function of the upper extremity </td> <td> 0. Impossible to eat with chopsticks or spoon </td> </tr> <tr> <td> 1. Possible to ear with spoon, but not with chopsticks </td> ...
PMC2717922_table_1
<table border="1" class="dataframe"> <tr> <th> Case no. </th> <th> Age (yr)/Sex </th> <th> Etiology </th> <th colspan="3"> Presentation </th> <th> Onset (days) </th> <th> Duration of recovery (days) </th> <th> Laterality </th> <th> Level of involvement </th> <t...
PMC2717922_table_2
<table border="1" class="dataframe"> <tr> <th> </th> <th> Pure dysesthesia (n = 10) </th> <th> Dysesthesia with motor deficit (n = 8) </th> <th> P </th> </tr> <tr> <td> Mean age (years) </td> <td> 58.2 </td> <td> 65.9 </td> <td> 0.199 </td> </tr> <tr> <td> ...
PMC2717922_table_3
<table border="1" class="dataframe"> <tr> <th> </th> <th> Patient without palsy (n = 56) </th> <th> Patient with palsy (n = 18) </th> <th> P </th> </tr> <tr> <td> Pavlov ratio (mean) </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> C3 </td> <td> 0.7125 ...
PMC2717922_table_4
<table border="1" class="dataframe"> <tr> <th> </th> <th> Patient without palsy (n = 56) </th> <th> Patient with palsy (n = 18) </th> <th> OR </th> <th> p </th> </tr> <tr> <td> Average Pavlov ratio &lt; 0.65 </td> <td> 10 (17.9) </td> <td> 8 (44.4) </td> <td> ...
PMC2717922_table_5
<table border="1" class="dataframe"> <tr> <th> </th> <th> High expressing (LA/LA) </th> <th> Intermediate expressing (LA/SA) </th> <th> Low expressing (SA/SA and LG/SA) </th> </tr> <tr> <td> Male </td> <td> 4 </td> <td> 3 </td> <td> 5 </td> </tr> <tr> <td> ...
PMC2717925_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th> Exercisers n = 52 </th> <th> Non-exercisers n = 69 </th> <th> Total MS sample n = 121 </th> </tr> <tr> <td> Age (yr) </td> <td> 50 ± 10 </td> <td> 50 ± 11 </td> <td> 50 ± 10 </td> </tr> <tr> <td> Sex...
PMC2717927_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th> BDI </th> <th> SF36PF </th> <th> SF36RP </th> <th> SF36BP </th> <th> SFGH </th> </tr> <tr> <td> Exercise Status </td> <td> 5.632* </td> <td> 12.983** </td> <td> 1.236 </td> <td> 2.149 <...
PMC2717927_table_1
<table border="1" class="dataframe"> <tr> <th> </th> <th colspan="2"> H. sapiens versus M. musculus % sequence identity </th> <th colspan="2"> H. sapiens versus G. gallus % sequence identity </th> </tr> <tr> <th> </th> <th> Whole length </th> <th> Signal peptide </th> <th> Wh...
PMC2717928_table_0
<table border="1" class="dataframe"> <tr> <th> Year </th> <th> 1% </th> <th> 2% </th> <th> 5% </th> <th> 7% </th> <th> 10% </th> <th> 20% </th> <th> 30% </th> </tr> <tr> <td> 2002 </td> <td> 0.60 </td> <td> 0.56 </td> <td> 0.49 </td>...
PMC2717929_table_0
<table border="1" class="dataframe"> <tr> <th> Treatment </th> <th colspan="3"> Maximal changes in </th> </tr> <tr> <th> </th> <th> MSAP (mmHg) </th> <th> HR (bpm) </th> <th> Power Density (mmHg2) </th> </tr> <tr> <td> aCSF </td> <td> +3.3 ± 0.4 </td> <td> ...
PMC2717931_table_0
<table border="1" class="dataframe"> <tr> <th> N </th> <th> AGE </th> <th> SIDE </th> <th> GENDER </th> <th> CEAP </th> <th> Total Vol. </th> <th> Volume Post-rest </th> <th> Volume Post-exercise </th> </tr> <tr> <td> 01- </td> <td> 60 </td> <td...
PMC2717934_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th> Geometric Mean </th> <th colspan="7"> Selected Percentiles </th> </tr> <tr> <th> </th> <th> </th> <th> 10th </th> <th> 25th </th> <th> 50th </th> <th> 75th </th> <th> 90th </th> <th> 95th </t...
PMC2717935_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th> Molecular weight </th> <th> Mean </th> <th colspan="8"> Selected Percentiles </th> </tr> <tr> <th> </th> <th> </th> <th> </th> <th> Min. </th> <th> 10th </th> <th> 25th </th> <th> 50th </th> <...
PMC2717935_table_1
<table border="1" class="dataframe"> <tr> <th> </th> <th colspan="2"> Wet-weight concentrations </th> <th colspan="2"> Lipid-standardized </th> </tr> <tr> <th> </th> <th> All samples; n = 266 </th> <th> Excluding baseline; n = 178 </th> <th> All samples; n = 173 </th> <th...
PMC2717935_table_2
<table border="1" class="dataframe"> <tr> <th> </th> <th colspan="3"> Follicular fluid </th> <th colspan="3"> Serum </th> </tr> <tr> <th> </th> <th> Phase 1 (1994–1998); n = 31 </th> <th> Phase 2 (1999–2003); n = 41 </th> <th> p-value </th> <th> Phase 1 (1994–1998); n ...
PMC2717935_table_3
<table border="1" class="dataframe"> <tr> <th> Characteristics </th> <th> No. of Patients </th> <th> No. of Deaths </th> <th> MST (months) </th> <th> P* </th> </tr> <tr> <td> Total subjects Age (mean) </td> <td> 167 </td> <td> 60 </td> <td> </td> <td> ...
PMC2717936_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th> Experimentals (n = 3) </th> <th> Controls (n = 2) </th> </tr> <tr> <td> Brain </td> <td> 3/3 </td> <td> 0/2 </td> </tr> <tr> <td> Spinal cord </td> <td> 1/3 </td> <td> 0/1b </td> </tr> <tr> <td...
PMC2717941_table_0
<table border="1" class="dataframe"> <tr> <th> Day </th> <th> Pattern I </th> <th> Pattern II </th> <th> Total </th> </tr> <tr> <td> 7 </td> <td> 9 (40.9%) </td> <td> 13 (59.1%) </td> <td> 22 </td> </tr> <tr> <td> 10 </td> <td> 7 (29.2%) </td> ...
PMC2717942_table_0
<table border="1" class="dataframe"> <tr> <th> Day </th> <th> Pattern Vpr </th> <th> Pattern Tat </th> <th> Total </th> </tr> <tr> <td> 3 </td> <td> 6 (42.8%) </td> <td> 8 (57.2%) </td> <td> 14 </td> </tr> <tr> <td> 7 </td> <td> 9 (52.9%) </td> ...
PMC2717942_table_1
<table border="1" class="dataframe"> <tr> <th> </th> <th> Number screened </th> <th> Number positive </th> <th> Number negative </th> </tr> <tr> <td> Males </td> <td> 97 </td> <td> 13(13.40%) </td> <td> 84(86.59%) </td> </tr> <tr> <td> Females </td> <td...
PMC2717943_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th colspan="5"> AGE GROUP </th> </tr> <tr> <th> </th> <th> 18–27 </th> <th> 28–37 </th> <th> 38–47 </th> <th> 48–57 </th> <th> 58–67 </th> </tr> <tr> <td> No. Screened </td> <td> 44 </td> <td> ...
PMC2717943_table_1
<table border="1" class="dataframe"> <tr> <th rowspan="2"> As </th> <th colspan="5"> AGE GROUP </th> </tr> <tr> <th> 18–27 </th> <th> 28–37 </th> <th> 38–47 </th> <th> 48–57 </th> <th> 58–67 </th> </tr> <tr> <td> as No. Screened </td> <td> 41 </td> <...
PMC2717943_table_2
<table border="1" class="dataframe"> <tr> <th> VARIABLE </th> <th> TOTAL NOS(%) </th> <th> NOS OF POSITIVE (%) </th> <th> P VALUE </th> </tr> <tr> <td> Marital status </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> Married </td> <td> 95 (50.53%) <...
PMC2717943_table_3
<table border="1" class="dataframe"> <tr> <th> </th> <th colspan="2"> Men </th> <th colspan="2"> Women </th> </tr> <tr> <th> </th> <th> AST (%) </th> <th> ALT (%) </th> <th> AST (%) </th> <th> ALT (%) </th> </tr> <tr> <td> Nos showing normal level </td> <t...
PMC2717943_table_4
<table border="1" class="dataframe"> <tr> <th> Quality Statistic1 </th> <th> Description </th> </tr> <tr> <td> mean.raw.int, sd.raw.int, median.raw.int, interQuartile.raw.int </td> <td> mean, standard deviation, median and inter-quartile range of raw log intensity distribution. </td> </t...
PMC2717951_table_0
<table border="1" class="dataframe"> <tr> <th> Quality Statistic1 </th> <th> Description </th> </tr> <tr> <td> pm.mean </td> <td> mean of the raw intensity for all PM probes, prior to any normalizations. </td> </tr> <tr> <td> bgrd.mean </td> <td> mean of the raw intensity fo...
PMC2717951_table_1
<table border="1" class="dataframe"> <tr> <th colspan="3"> % Example of the DOTcvp simple input file for the drug displacement problem </th> </tr> <tr> <th> data.name </th> <th> = 'DrugDisplacement'; </th> <th> % name of the problem </th> </tr> <tr> <td> data.odes.parameters(1) <...
PMC2717952_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th colspan="2"> Men </th> <th colspan="2"> Women </th> </tr> <tr> <th> </th> <th> General Workforce/1 </th> <th> Index Group </th> <th> General Workforce </th> <th> Index Group </th> </tr> <tr> <td> Number ...
PMC2717954_table_0
<table border="1" class="dataframe"> <tr> <th> Organizational model </th> <th> Definition </th> <th> Example </th> </tr> <tr> <td> Small family doctor based models (registration at a </td> <td> family doctor practice) </td> <td> </td> </tr> <tr> <td> Individual general f...
PMC2717955_table_0
<table border="1" class="dataframe"> <tr> <th> Country </th> <th> # </th> </tr> <tr> <td> Australia </td> <td> 2 </td> </tr> <tr> <td> Austria </td> <td> 3 </td> </tr> <tr> <td> Belgium </td> <td> 7 </td> </tr> <tr> <td> Canada </td> <td> 2 ...
PMC2717955_table_1
<table border="1" class="dataframe"> <tr> <th> Country </th> <th> Respondents (N) </th> <th> Models (N) </th> <th> Dominant model* </th> <th> Planned changes </th> </tr> <tr> <td> Croatia </td> <td> 1 </td> <td> 3 </td> <td> Emergency department </td> ...
PMC2717955_table_2
<table border="1" class="dataframe"> <tr> <th> </th> <th colspan="2"> Small family doctor based models </th> <th colspan="3"> Large family doctor based models </th> <th colspan="3"> Hospital based and national models </th> </tr> <tr> <th> </th> <th> Individual general family practic...
PMC2717955_table_3
<table border="1" class="dataframe"> <tr> <th> Trial characteristic </th> <th> </th> <th> Number of Included RCT Reports (%) </th> </tr> <tr> <td rowspan="6"> Journal </td> <td> NEJM </td> <td> 39 (29.3) </td> </tr> <tr> <td> Lancet </td> <td> 31 (23.3) </td> <...
PMC2717957_table_0
<table border="1" class="dataframe"> <tr> <th> Journal </th> <th> Yes completely (%) </th> <th> Yes partially (%) </th> <th> No (%) </th> </tr> <tr> <td> JAMA (n = 25) </td> <td> 20 (80.0) </td> <td> 5 (20.0) </td> <td> 0 </td> </tr> <tr> <td> Annals Int...
PMC2717957_table_1
<table border="1" class="dataframe"> <tr> <th> Current stagea </th> <th> Next stagea </th> <th> Number of studiesb </th> <th> Median progressing to next stage </th> <th> First and third quartiles </th> <th> Minimum and maximum </th> </tr> <tr> <td> Invited to eligibilit...
PMC2717957_table_2
<table border="1" class="dataframe"> <tr> <th> </th> <th> Number of studiesa </th> <th> Median % of sample size required </th> <th> First and third quartiles </th> <th> Minimum and maximum </th> </tr> <tr> <td> Invited to screening </td> <td> 12 </td> <td> 410% </...
PMC2717957_table_3
<table border="1" class="dataframe"> <tr> <th> </th> <th colspan="3"> Screened and eligible </th> <th colspan="3"> Eligible and randomised </th> <th colspan="3"> Randomised and outcome assessed </th> </tr> <tr> <th> Factor &amp; level </th> <th> Median </th> <th> IQR </t...
PMC2717957_table_4
<table border="1" class="dataframe"> <tr> <th> Total number of patients </th> <th> </th> <th> 47 </th> </tr> <tr> <td> Male </td> <td> </td> <td> 24 </td> </tr> <tr> <td> Female </td> <td> </td> <td> 23 </td> </tr> <tr> <td> Age at start of ART (months) ...
PMC2717958_table_0
<table border="1" class="dataframe"> <tr> <th> Total no. of visits with appointments given (%) </th> <th> 401 (100) </th> </tr> <tr> <td> As scheduled </td> <td> 206 (51) </td> </tr> <tr> <td> Before appointment </td> <td> 58 (15) </td> </tr> <tr> <td> Within 1 week...
PMC2717958_table_1
<table border="1" class="dataframe"> <tr> <th> Demographics </th> <th> N = 395* </th> </tr> <tr> <td> Gender (% females) </td> <td> 28.9% </td> </tr> <tr> <td> Age, years; mean (SD) </td> <td> 39.1 (8.2) </td> </tr> <tr> <td> Age at onset of disease, years; mean (SD...
PMC2717959_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th> QLS Intrapsychic </th> <th> QLS Intpersonal </th> <th> Processing Speed </th> <th> Working Memory </th> <th> Verbal Memory </th> <th> Neg </th> <th> Pos </th> <th> PANSS Overall </th> </tr> <tr> <t...
PMC2717959_table_1
<table border="1" class="dataframe"> <tr> <th> </th> <th> QLS Intrapsychic </th> <th> QLS Interpersonal </th> <th> Processing Speed </th> <th> Working Memory </th> <th> Verbal Memory </th> <th> Neg </th> <th> Pos </th> <th> PANSS Overall </th> </tr> <tr> ...
PMC2717959_table_2
<table border="1" class="dataframe"> <tr> <th> </th> <th> Sample Size </th> <th> Age (years) </th> <th> Follow-up (months) </th> <th> Baseline GFR (ml/min/1.73 m2) (inulin clearance) </th> <th> Baseline creatinine (μmol/L) </th> <th> Number of GFR measurements </th> <th>...
PMC2717960_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th> Accuracy 10% (95% CI) </th> <th> Accuracy 30% (95% CI) </th> <th> Accuracy 50% (95% CI) </th> </tr> <tr> <td> Cockcroft-Gault formula </td> <td> 43.6% [35% – 52%] </td> <td> 41.3% [33% – 50%] </td> <td> 15% [...
PMC2717960_table_1
<table border="1" class="dataframe"> <tr> <th> </th> <th> Method of GFR estimation </th> <th> Slope of GFR (ml/min/1.73 m2/year) Median and [range] </th> <th> p value in the Friedman test (non parametric ANOVA) </th> <th> P value in Dunn's multiple comparison post-test </th> </tr> <tr...
PMC2717960_table_2
<table border="1" class="dataframe"> <tr> <th> </th> <th> </th> <th> Original Cockcroft and Gault formula (CG) </th> <th> BSA-modified- Cockcroft and Gault formula (BSA-CG) </th> <th> Abbreviated MDRD equation (A-MDRD) </th> <th> Mayo Clinic Quadratic equation (MCQ) </th> </tr> <t...
PMC2717960_table_3
<table border="1" class="dataframe"> <tr> <th> Cell population </th> <th colspan="2"> ANTEROGRADE EVENTS (μm/sec Mean Velocity ± SE) </th> <th colspan="2"> RETROGRADE EVENTS (μm/sec Mean Velocity ± SE) </th> </tr> <tr> <th> Hippocampal neurons </th> <th> Axons </th> <th> Dendr...
PMC2717962_table_0
<table border="1" class="dataframe"> <tr> <th> Socioeconomic characteristic </th> <th> – The least poor 'Abagaiga' </th> <th> – 'Abafuni' (The Medium wealth category) </th> <th> Abaavu – The poorest </th> </tr> <tr> <td> Income (financial capital) </td> <td> Income generating ...
PMC2717964_table_0
<table border="1" class="dataframe"> <tr> <th> Category </th> <th> Total number of participants </th> <th> Men </th> <th> Women </th> <th> Occupations of participants </th> <th> Other observations </th> </tr> <tr> <td> Least Poor "Abagaiga" </td> <td> 8 </td> ...
PMC2717964_table_1
<table border="1" class="dataframe"> <tr> <th> Village name </th> <th> Least Poor </th> <th> Medium wealth category </th> <th> Poorest </th> <th> Total </th> </tr> <tr> <td> Nawangisa </td> <td> 8 </td> <td> 15 </td> <td> 12 </td> <td> 35 </td> <...
PMC2717964_table_2
<table border="1" class="dataframe"> <tr> <th> </th> <th> </th> <th> </th> <th colspan="5"> Weight of tumor (g) </th> </tr> <tr> <th> Group (n = 12) </th> <th> Dose (mg/kg) </th> <th> Inhibition rate (%) </th> <th> Mean </th> <th> SD </th> <th colspan="3"> P...
PMC2717966_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th> </th> <th> </th> <th> </th> <th colspan="3"> Percentiles </th> </tr> <tr> <th> Group (n = 10) </th> <th> Dose (mg/kg) </th> <th> Mean </th> <th> SD </th> <th> 25th </th> <th> 50th (median) </th>...
PMC2717966_table_1
<table border="1" class="dataframe"> <tr> <th> Accession </th> <th> Name </th> <th> Def allele </th> </tr> <tr> <td> JI 116 </td> <td> cv. Parvus </td> <td> Def (wild type) </td> </tr> <tr> <td> JI 2822 </td> <td> RIL, research line </td> <td> Def (wild ...
PMC2717967_table_0
<table border="1" class="dataframe"> <tr> <th> Gene identification/Gene description </th> <th> E value/ID (%) </th> <th> Primer sequence/Amplicon size </th> <th> Amplification efficiency ± SD* </th> <th> GeneBank Accession Number </th> </tr> <tr> <td> BbrizEF1 Elongation facto...
PMC2717968_table_0
<table border="1" class="dataframe"> <tr> <th> Exons </th> <th> PCR product size (bp) </th> <th> PCR anealing temperature (°C) </th> <th> Primers </th> </tr> <tr> <td rowspan="2"> 1A </td> <td> 305 </td> <td> 62 </td> <td> F 5'-CTTGAACCCGCGAACAGGCGA </td> </tr...
PMC2717975_table_0
<table border="1" class="dataframe"> <tr> <th> </th> <th> </th> <th> </th> <th> </th> <th colspan="2"> Haemoglobinuria Kinh N = 82 </th> <th> Healthy Kinh N = 266 </th> <th> Healthy S'tieng N = 258 </th> </tr> <tr> <th> Variant </th> <th> Variant name </th> <th> ...
PMC2717975_table_1
<table border="1" class="dataframe"> <tr> <th> G6PD </th> <th> Hburiac Kinh N = 82 </th> <th> Healthy Kinh N = 266 </th> <th> Hburia Kinh G6PD- N = 48 </th> <th> Healthy Kinh G6PD- N = 23 </th> <th> OR </th> <th> 95%CI </th> <th> P value </th> </tr> <tr> <td>...
PMC2717975_table_2