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516789	Antimicrobial actions of the human epididymis 2 (HE2) protein isoforms, HE2alpha, HE2beta1 and HE2beta2	Background The HE2 gene encodes a group of isoforms with similarities to the antimicrobial beta-defensins. We demonstrated earlier that the antimicrobial activity of HE2 proteins and peptides is salt resistant and structure dependent and involves permeabilization of bacterial membranes. In this study, we further characterize the antimicrobial properties of HE2 peptides in terms of the structural changes induced in E. coli and the inhibition of macromolecular synthesis. Methods E. coli treated with 50 micro g/ml of HE2alpha, HE2beta1 or HE2beta2 peptides for 30 and 60 min were visualized using transmission and scanning electron microscopy to investigate the impact of these peptides on bacterial internal and external structure. The effects of HE2alpha, HE2beta1 and HE2beta2 on E. coli macromolecular synthesis was assayed by incubating the bacteria with 2, 10 and 25 micro g/ml of the individual peptides for 0–60 min and measuring the incorporation of the radioactive precursors [methyl- 3 H]thymidine, [5- 3 H]uridine and L-[4,5- 3 H(N)]leucine into DNA, RNA and protein. Statistical analyses using Student's t-test were performed using Sigma Plot software. Values shown are Mean ± S.D. Results E. coli treated with HE2alpha, HE2beta1 and HE2beta2 peptides as visualized by transmission electron microscopy showed extensive damage characterized by membrane blebbing, thickening of the membrane, highly granulated cytoplasm and appearance of vacuoles in contrast to the smooth and continuous membrane structure of the untreated bacteria. Similarly, bacteria observed by scanning electron microscopy after treating with HE2alpha, HE2beta1 or HE2beta2 peptides exhibited membrane blebbing and wrinkling, leakage of cellular contents, especially at the dividing septa, and external accumulation of fibrous materials. In addition, HE2alpha, HE2beta1 and HE2beta2 peptides inhibited E. coli DNA, RNA and protein synthesis. Conclusions The morphological changes observed in E. coli treated with epididymal HE2 peptides provide further evidence for their membrane dependent mechanism of antibacterial action. HE2 C-terminal peptides can inhibit E. coli macromolecular synthesis, suggesting an additional mechanism of bacterial killing supplementary to membrane permeabilization.	Introduction Antimicrobial proteins and peptides are widely expressed in both plants and animals. A variety of natural antibiotics belonging to different classes such as defensins, cathelicidins, cercopins and protease inhibitors [ 1 ] are found in epithelial tissues of organs that are most likely exposed to pathogens. Among them, the most studied in humans are the defensins, which are broadly classified into three types viz alpha, beta and theta defensins depending on their disulfide bonding, tissue distribution and genomic organization. They exhibit broad spectrum antimicrobial activity [ 2 - 5 ], thus may form an important component of the innate immune system. Antimicrobial proteins and peptides including defensins are generally cationic in nature [ 6 ] and are believed to exert their bactericidal effect by permeabilizing the bacterial membranes by forming pores [ 7 ], thinning the membrane [ 8 ], or by destabilizing the membrane bilayer [ 9 ]. In addition to membrane permeabilization, antimicrobial proteins and peptides kill bacteria by inhibition of macromolecular biosynthesis [ 10 - 12 ] and/or interacting with specific vital components inside the bacteria [ 13 , 14 ]. In the epididymis, a major organ of the male reproductive tract, immature sperm released from the testis undergo sequential maturation to acquire forward motility and fertilizing ability. A wide variety of proteins including antimicrobial proteins released into the lumen of epididymis bind sperm and are thought to play an important role in epididymal immunity in addition to their role in sperm maturation [ 15 ]. Examples of antimicrobial proteins reported in the male reproductive tract include human cationic antimicrobial protein (hCAP18, a cathelicidin) [ 16 ], defensins [ 17 - 20 ], the epididymal β-defensin member Bin1b [ 21 ], cystatins [ 22 , 23 ], lactoferrin [ 24 ] seminalplasmin [ 25 ] and seminogelin-derived peptides [ 26 ]. Earlier we identified and characterized the sperm binding epididymal proteins of the HE2 family [ 27 ], which show homology to the antimicrobial β-defensins. The HE2 gene located on chromosome 8p23 within the β-defensin gene cluster, encodes a series of isoforms containing identical proregions joined to different C-terminal peptides [ 27 ]. Among them, HE2β1 conserves the characteristic β-defensin-like six-cysteine motif (Figure 1 ). Furthermore, like the β-defensins, HE2 C-terminal peptides are cleaved from their proregions by a furin-like proprotein convertase and these peptides are reported to exist in the epididymal epithelium, luminal fluid and the seminal plasma [ 28 ]. We demonstrated the antimicrobial activity of HE2α, HE2β1 and HE2β2 proteins and their C-terminal peptides [ 29 ] and the epididymis specific defensin DEFB118 [ 30 ] against E. coli . Their antimicrobial activities are structure dependent and salt tolerant and their mechanism of action involves interacting with and permeabilizing bacterial membranes. However, structural evidence for the membrane changes in E. coli induced by these peptides is still lacking. Further, it is not still clear whether bacterial killing by HE2 peptides involves only membrane permeabilization or whether the peptides interact with specific targets inside the bacteria to inhibit metabolic processes as reported for other antimicrobial proteins is not yet demonstrated. In this study, using transmission and scanning electron microscopy, we provide further evidence that HE2 peptides induce significant structural changes in E. coli consistent with their membrane dependent mechanism of action as reported earlier. Further, we show that HE2 peptides inhibit E. coli DNA, RNA and protein synthesis suggesting that their antimicrobial action may also involve targets inside the bacteria as well as membrane permeabilization. Figure 1 Amino acid sequence alignment of epididymal HE2 peptides with human β-defensins 1 and 2. Amino acid sequence shown in blue corresponds to the C-terminal peptides used in this study. The characteristic β-defensin six cysteine motif is represented in red. represents the cleavage site where the full length proteins are cleaved to release the C-terminal peptides. Methods Recombinant peptide preparation and synthesis HE2α and HE2β2 C-terminal peptides were synthesized at the Peptide Synthesis Facility, University of North Carolina, Chapel Hill by standard f-moc solid phase procedures using Rainin symphony multiple peptide synthesizer (Rainin Instrument, Woburn, MA). The purified peptides eluted as single peaks upon reverse phase high performance liquid chromatography (HPLC) and were further demonstrated to have their corresponding molecular weight by MALDI-TOF mass spectrometry. HE2β1 C-terminal peptide was expressed in E. coli and purified as described previously [ 29 ]. Briefly, E. coli strain M15 (pREP4) was transformed with pQE30 vector (Qiagen, Valencia, CA, U.S.A) containing cDNA that codes for HE2β1 C-terminal peptide. Protein expression was induced with 1 mM isopropyl-β-D-thiogalactoside for 1 h at 37°C and the His-tagged recombinant peptide was purified using nickel-nitrilotriacetate agarose column (Qiagen, Valencia, CA, U.S.A). To avoid baseline expression of the protein prior to induction, 1% glucose was maintained in the bacterial medium and the induction time was kept to a minimum (1 h) to minimize the toxic effects of the peptide on E. coli . The peptide was dialyzed extensively against 10 mM sodium phosphate (pH 7.4) to remove urea. Transmission electron microscopy E. coli resuspended in 10 mM sodium phosphate buffer (pH 7.4) were treated with 50 μg/ml HE2α, HE2β1 or HE2β2 for 30 and 60 min. After incubation, bacterial cells were washed with 10 mM sodium phosphate buffer (pH 7.4) and fixed with an equal volume of 4% glutaraldehyde in 0.1 M sodium cacodylate buffer, pH 7.4, followed by centrifugation at 1000 rpm for 10 minutes to concentrate the cells in a pellet. The fixed samples were stored overnight to several days at 4°C in the fixative solution. The pellet was rinsed in 0.1 M sodium cacodylate buffer several times, and post-fixed with a combination of 1.25% potassium ferrocyanide and 1% buffered osmium tetroxide for one hour at room temperature. Following dehydration with a graded series of ethanols (30–100%) and two changes of propylene oxide, the cell pellet was infiltrated and embedded in PolyBed 812 epoxy resin (Polysciences, Inc., Warrington, PA). Ultra thin sections (70 nm) were cut and mounted on copper grids followed by post staining with 4% uranyl acetate and 0.4% lead citrate. The sections were examined and photographed at an accelerating voltage of 80 kV using a LEO EM 910 transmission electron microscope (LEO Electron Microscopy, Inc., Thornwood, NY) equipped with a Gatan BioScan digital camera (Gatan, Inc., Pleasanton, CA). Scanning electron microscopy The structural changes induced by HE2 peptides on E. coli were studied using scanning electron microscopy as described earlier [ 30 ]. Bacterial cells suspended in 10 mM sodium phosphate buffer (pH 7.4) after treating with 50 μg/ml of HE2 peptide were fixed with an equal volume of 4% glutaraldehyde in 0.15 M sodium phosphate buffer, pH 7.4. Immediately following the addition of the fixative solution, the sample tube was mixed by gently inverting the tube up and down for several minutes to prevent clumping of the cells. The fixed samples were stored overnight to several days at 4°C in the fixative solution. Using a microanalysis vacuum filter holder (Fisher Scientific, Suwanee, GA) and a 0.1 μm polycarbonate membrane filter (Poretics Corporation, Livermore, CA), the suspended fixed cells were vacuum-filtered onto the membrane substrate, rinsed with 0.15 M sodium phosphate buffer, and dehydrated through a graded series of ethanols (30–100%). During the entire filtration, rinsing, and dehydration process, the cells were kept covered with fluid to prevent air drying. The filters were transferred in 100% ethanol to a critical point dryer (Balzers CPD-020, Bal-Tec AG, Vaduz, Liechtenstein), and dried using carbon dioxide as the transition solvent. The filters were mounted on aluminum specimen supports with carbon adhesive tabs, and coated with a 15 nm thickness of gold-palladium metal (60:40 alloy) using a Hummer X sputter coater (Anatech, Ltd., Alexandria, VA). Samples were examined with a Cambridge Stereoscan 200 scanning electron microscope (LEO Electron Microscopy, Inc., Thornwood, NY) using an accelerating voltage of 20 kV. Macromolecular synthesis The effects of HE2 peptides on E. coli DNA, RNA and protein synthesis were studied as functions of incorporation of the radioactive precursors [methyl- 3 H]thymidine, [5- 3 H]uridine and L-[4,5- 3 H(N)]leucine respectively as described [ 30 ]. 1 × 10 6 mid-log phase E. coli resuspended in 10 mM sodium phosphate buffer (pH 7.4) were treated with varying concentrations of HE2 peptides and 2.5 μl/ml of either [methyl- 3 H]thymidine (20 Ci/mmol), [5- 3 H]uridine (25.5 Ci/mmol) or L-[4,5- 3 H(N)]leucine (59.5 Ci/mmol) for different time periods. After incubation, bacterial suspensions were added to 10% ice-cold trichloroacetic acid and allowed to stand in ice for 40 min. Samples were then collected on 2.4 cm GF/C glass microfiber filters (Fisher Scientific, Pittsburgh, PA) using vacuum filtration and washed thoroughly with 5% TCA and 70% ethanol. The filters were then dried and placed in scintillation vials containing 5 ml of EcoScint scintillation cocktail (National Diagnostics, Atlanta, GA) and counts were obtained in a LKB 1214 Rackbeta liquid scintillation counter (LKB WALLACE, Turku, Finland) for 1 min for each filter. Statistical analyses using Student's t-test were performed using Sigma Plot software (SPSS Inc., Chicago, IL). Values shown are Mean ± S.D. Results Transmission electron microscopy Transmission electron microscopy revealed striking structural alterations in E. coli exposed to HE2 peptides. The three images shown for each treatment were documented in different fields of view and are intended to represent the range of responses seen in the bacteria. In contrast to the smooth continuous double membrane structure clearly visible in untreated bacteria (Fig. 2A,2B,2C ), the outer membranes of bacteria treated with 50 μg/ml HE2α peptide for 30–60 min showed thickening and the protrusion of irregular blebs. The inner membrane was indistinct in many regions after 30 min and the cytoplasm was retracting from the outer membrane (Fig. 3A,3B,3C ). After 60 min of HE2α treatment, the inner membrane was difficult to discern and fibrous and granular material, presumably cell contents appeared to exude from the damaged membranes (Fig. 3D,3E,3F ). Treatment with 50 μg/ml HE2β1 peptide for 30 min resulted in numerous mushroom shaped blebs and retraction of cytoplasm (Fig. 4A,4B,4C ) and by 60 min, these bacteria appeared to lose cell contents particularly at the division septa (Fig. 4D,4E,4F ). Similarly, the HE2β2-treated bacteria showed loss of the double membrane structure, formation of blebs and outer membrane roughening (Fig. 5A,5B,5C ). By 60 min, numerous large vacuoles accumulated, the cytoplasm was extensively granulated and retracted from the outer membrane and cell contents appeared to escape at division septa (Fig. 5D,5E,5F ). The peptides appeared to induce structural changes specific to each peptide besides the morphological changes that were generally observed. HE2α peptide caused membrane thickenings, which was not observed with the other two peptides. Similarly, HE2β1 peptide caused retraction of cytoplasm when treated for 30 min, whereas HE2β2 peptide induced retraction of cytoplasm after 60 min incubation. Formation of vacuoles was more evident upon treating E. coli with HE2β2 peptide. Figure 2 Transmission electron micrographs of untreated E. coli showing a smooth continuous double membrane structure. Figure 3 E. coli treated with 50 μg/ml HE2α peptide for 30 min (A-C) and 60 min (D-F) visualized by transmission electron microscopy showed membrane thickening and blebbing with subsequent leakage of cellular contents. Figure 4 Transmission electron micrographs showing cytoplasmic retraction and extensive granulation of E. coli treated with 50 μg/ml HE2β1 peptide for 30 min (A-C) and 60 min (D-F). Figure 5 Incubation of E. coli with 50 μg/ml HE2β2 peptide for 30 min (A-C) and 60 min (D-F) show discontinuous membrane structure with extensive vacuole formation. Cellular contents appear to leak at the dividing septa. Scanning electron microscopy E. coli treated with HE2 peptides were observed using scanning electron microscopy to gain further insights into the membrane effects. The three images shown for each treatment were documented in different fields of view and are intended to represent the range of responses seen in the bacteria. Untreated bacterial cells had normal and smooth surface morphology (Fig. 6A,6B,6C ). Bacteria treated with HE2α (Fig. 7A,7B,7C,7D,7E,7F ), HE2β1 (Fig. 8A,8B,8C,8D,8E,8F ) or HE2β2 (Fig. 9A,9B,9C,9D,9E,9F ) peptides showed pronounced changes in their morphology consistent with the changes observed using transmission electron microscopy. E. coli treated with the HE2 peptides for 30–60 min showed pronounced wrinkling, surface roughening and blebbing of the membrane. A majority of the cells appeared to have lost their bacterial membrane integrity. The fibrous material and cellular debris, possibly arising due to leakage and cell lysis accumulated particularly at the dividing septa. Figure 6 Scanning electron micrographs of untreated E. coli revealing a smooth membrane surface morphology. Figure 7 E. coli treated with 50 μg/ml HE2α peptide for 30 min (A-C) and 60 min (D-F) visualized by scanning electron microscopy show membrane blebbing and leakage of cellular contents. Figure 8 Membrane wrinkling and blebbing were evident in E. coli treated with 50 μg/ml HE2β1 peptide for 30 min (A-C) and 60 min (D-F). Figure 9 Scanning electron micrographs of E. coli treated with 50 μg/ml HE2β2 peptide for 30 min (A-C) and 60 min (D-F). Loss of bacterial membrane integrity due to surface blebbing and wrinkling was evident. Macromolecular synthesis To investigate whether HE2 peptides affect macromolecular synthesis of E. coli , the incorporation of radioactive precursors viz [methyl- 3 H]thymidine, [5- 3 H]uridine and L-[4,5- 3 H(N)]leucine into DNA, RNA and protein was studied in the presence of 2–25 μg/ml peptides. A dose and time dependent inhibition of DNA synthesis by HE2α peptide was observed (Fig. 10A ). 2 μg/ml HE2α peptide inhibited DNA synthesis after 60 min incubation, whereas 10 and 25 μg/ml significantly inhibited DNA synthesis after 20 min incubation (Fig. 10A ). RNA synthesis was not inhibited by 2 μg/ml HE2α peptide, whereas inhibition was observed with 10 and 25 μg/ml concentrations (Fig. 10B ). No significant inhibition of protein synthesis by HE2α peptide was observed at any of the concentrations tested (Fig. 10C ). Figure 10 Effect of HE2α peptide on macromolecular synthesis in E. coli . A, [methyl- 3 H]thymidine incorporation into DNA. B, [5- 3 H]uridine incorporation into RNA. C, L-[4,5- 3 H(N)]leucine incorporation into proteins. 0 μg/ml (■); 2 μg/ml (▲); 10 μg/ml (▼); 25 μg/ml (◆). Values shown are mean ± SD. , P < 0.05-0.01, , P < 0.01-0.001, *, P < 0.001 compared to 0 μg/ml at the corresponding time point. In the case of HE2β1 peptide, 2 μg/ml dose did not inhibit DNA synthesis, whereas 10 and 25 μg/ml concentrations showed significant inhibition (Fig. 11A ) after a 20 min incubation. Similarly, significant inhibition of RNA synthesis was not observed with 2 μg/ml. However, 10 and 25 μg/ml concentrations inhibited RNA after 20 min (Fig. 11B ) and protein synthesis (Fig. 11C ) after a 60 min incubation. Figure 11 Effect of HE2β1 peptide on macromolecular synthesis in E. coli . A, [methyl- 3 H]thymidine incorporation into DNA. B, [5- 3 H]uridine incorporation into RNA. C, L-[4,5- 3 H(N)]leucine incorporation into proteins. 0 μg/ml (■); 2 μg/ml (▲); 10 μg/ml (▼); 25 μg/ml (◆). Values shown are mean ± SD. , P < 0.05-0.01, , P < 0.01-0.001, , P < 0.001 compared to 0 μg/ml at the corresponding time point. Inhibition of E. coli DNA synthesis by HE2β2 peptide was dose and time dependent. Significant inhibition of DNA synthesis was observed after a 60 min incubation with 2 μg/ml HE2β2 peptide, whereas the inhibition was observed at a earlier time point with 10 and 25 μg/ml concentrations (Fig. 12A ). However, RNA synthesis was not inhibited by 2 μg/ml HE2β2 peptide, whereas 10 and 25 μg/ml doses were effective after 40 and 10 min incubations respectively (Fig. 12B ). Protein synthesis was inhibited only with 10 and 25 μg/ml HE2β2 peptide after a 60 min incubation (Fig. 12C ). It appears that HE2 peptides inhibit DNA synthesis to a greater extent than RNA and protein synthesis, suggesting that DNA synthesis may be the sensitive target for antimicrobial action after membrane permeabilization. Figure 12 Effect of HE2β2 peptide on macromolecular synthesis in E. coli . A, [methyl- 3 H]thymidine incorporation into DNA. B, [5- 3 H]uridine incorporation into RNA. C, L-[4,5- 3 H(N)]leucine incorporation into proteins. 0 μg/ml (■); 2 μg/ml (▲); 10 μg/ml (▼); 25 μg/ml (◆). Values shown are mean ± SD. , P < 0.05-0.01, , P < 0.01-0.001, *, P < 0.001 compared to 0 μg/ml at the corresponding time point. Discussion Earlier we demonstrated that HE2 proteins and their C-terminal peptides exhibit salt tolerant and structural dependent antimicrobial activities and their mechanism involved permeabilization of both outer and inner bacterial membranes [ 29 ]. In this study, structural changes induced in E. coli by epididymal HE2α, HE2β1 and HE2β2 peptides as visualized by transmission and scanning electron microscopy provide further evidence of the membrane dependent mechanism of bacterial killing. Such structural changes induced in E. col i by other antimicrobial proteins and peptides were reported previously. Membrane thickening as shown in Fig 3A,3B,3C,3D,3E,3F was reported in E. coli treated with human neutrophil peptides 1 and 2 (defensins) [ 14 ]. Similarly, retraction of cytoplasm and the appearance of vacuoles as shown in Fig 4A,4B,4C,4D,4E,4F were reported for E. coli treated with synthetic peptides of the antimicrobial protein apolipoprotein A-II [ 31 ]. Highly granular cytoplasm with discontinuous membrane was reported for E. coli treated with the antimicrobial peptide tigerinin-1 [ 32 ] similar to the changes shown in Fig. 5A,5B,5C,5D,5E,5F . Scanning electron micrographs of E. coli treated with HE2 peptides also revealed striking structural changes in their morphology. HE2 peptides caused membrane wrinkling, blebbing and leakage of fibrous material primarily at the dividing septa in E. coli . Such structural changes shown in Fig. 7 , 8 , 9 were earlier reported for other antimicrobial proteins viz the cathelicidin-derived peptide SMAP-29 [ 33 ], temporin-L [ 34 ], salmon antimicrobial protein [ 35 ] and the epididymal proteins ESC42 (DEFB118) [ 30 ] and EPPIN [ 36 ]. An interesting observation in this study is the leakage of fibrous material primarily at the dividing septa. It is known that cell division in E. coli involves annular constriction of all layers of the cell envelope and synthesis and assembly of new septal materials [ 37 ]. It is possible that during this dynamic remodeling process, the region of division septum formation to be particularly vulnerable to attack by antibacterial proteins. The mechanism of action of antimicrobial proteins is primarily thought to be membrane dependent involving membrane permeabilization and disruption. Structural characteristics of antimicrobial peptides tend to play an important role in their mechanism of action. For example, β-defensins are cationic in nature and with β-sheet rich amphipathic structures stabilized by the three disulfide motif [ 38 ]. The cationic nature of β-defensins favors them to bind to and disrupt target membranes that are rich in anionic phospholipids. Similarly, HE2α, HE2β1 and HE2β2 peptides are cationic in nature with basic pIs. Our three dimensional structural analysis of HE2β1 peptide revealed that it is rich in β-sheet structure and its tertiary structure presents regional concentrations of basic and hydrophobic amino acids similar to β-defensins [ 29 ]. Such structural characteristics of HE2 peptides which resemble to those of β-defensins suggest that they bind to and disrupt the anionic target membranes and mediate bacterial killing similar to β-defensins. However, alternate mechanisms of antimicrobial action such as inhibition of macromolecular synthesis [ 10 - 12 ] and interaction with specific targets inside the bacterial cells [ 13 , 14 ] are proposed. HE2 peptides at 10 and 25 μg/ml concentrations inhibited DNA, RNA and protein synthesis suggesting that their antimicrobial action may include interference with metabolic functions of E. coli . Inhibition of macromolecular synthesis was reported for bactenectins [ 39 ], human neutrophil peptide-1 [ 40 ], pleurocidin derived peptides [ 41 ] and the epididymal defensin DEFB118 [ 30 ]. In this study, it appears that HE2 peptides were more effective in inhibiting the incorporation of [methyl- 3 H]thymidine than [5- 3 H]uridine and L-[4,5- 3 H(N)]leucine, suggesting DNA synthesis is more sensitive to their antimicrobial action. It is possible that in bacteria that are extensively damaged by HE2 peptides, inhibition of macromolecular synthesis may result simply from the total breakdown of the cells. However the electron micrographs show that only some bacteria appear to be exuding cell contents after the 30 minute treatment. Thus during the first 10–20 minutes exposure to HE2 peptides, some peptides may be entering through pores too small for major cytoplasmic release. The early inhibition of DNA and RNA synthesis in bacteria where little loss of cell contents has occurred, may result from specific interaction of the synthetic machinery with HE2 peptides. Further studies are required to identify specific molecular targets within the bacteria and to establish whether HE2 interactions with these targets can be beneficial to the host by slowing bacterial proliferation. Increasing recognition of the ability of a number of proteins on the sperm surface to kill bacteria has led to the proposal that they may defend against microbial attack in both the male and female reproductive tracts. The cathelicidin hCAP18 on sperm is processed by the prostate-derived protease, gastricsin to release the active peptide ALL-38 and is found in the female reproductive tract after intercourse [ 42 ]. A member of the β-defensin family, DEFB126 also appears to have a role in fertility as a capacitation factor on sperm [ 43 ]. Similarly, the rat epididymis specific β-defensin Bin1b, appears to play an important role in sperm maturation [ 44 ]. Thus, these defense proteins may enhance the probability of successful fertilization in addition to helping prevent the spread of sexually transmitted diseases. Conclusions In conclusion, we report that the epididymal antimicrobial peptides HE2α, HE2β1 and HE2β2 induce striking morphological changes in E. coli consistent with their membrane dependent mechanism of action [ 29 ]. In addition to membrane permeabilization, their antimicrobial mechanism involves inhibition of E. coli DNA, RNA and protein synthesis. Author's contributions SY performed the electron microscopy studies, radioactive incorporation assays and wrote majority of the manuscript. KGH prepared the recombinant peptides. SHH and FSF supervised and coordinated the work and the preparation of the manuscript. All authors read, commented upon and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC516789.xml
529425	Is the “3 by 5” Initiative the Best Approach to Tackling the HIV Pandemic?	Background to the debate: The World Health Organization (WHO) and its partners aim to treat 3 million people infected with HIV in poor and middle income countries with antiretroviral treatment by the end of 2005. The ambitious “3 by 5” initiative has had its supporters and its critics since its announcement in 2002.	Jim Yong Kim's Viewpoint: 3 by 5 is a Point of Entry, Not an End in Itself There are no sure prescriptions against great plagues like HIV. We must “learn by doing,” quickly assessing the inevitable missteps and false starts and using this information to improve outcomes. Our best information about the HIV pandemic suggests four clear principles. First, treatment must be a core element. This does not mean treatment alone. Antiretroviral therapy (ART) is in no way more important than education, prevention of mother-to-child transmission, expanded access to testing and counseling, or other pieces of a comprehensive public health effort. But preventing mother-to-child transmission is a pyrrhic victory if, as the latest data suggest, AIDS will cause 15 million of those uninfected children to grow up as orphans [ 1 ]. Education is fruitless when the hope of finding work has disappeared because the loss of so many productive workers has led to the near collapse of industrial enterprise [ 2 ]. The dramatic benefits of ART for patients with advanced HIV disease (“the Lazarus effect”) engage the public imagination, helping to build political will on behalf of all interventions against the pandemic. And treatment can accelerate prevention by offering an incentive to get tested and know one's status, by reducing the stigma of an infection that leads to certain death, and by giving health workers credibility in devastated communities. Treatment is a point of entry, not an end in itself. Second, time is of the essence. Every data point in the arcs of HIV transmission, morbidity, and mortality represents an exponential increase in human suffering and social and economic disruption. Countries that were able to respond early and comprehensively to HIV now have mortality rates comparable to those of Europe and North America and have cut transmission dramatically. Early interventions can provide large cost savings to the public sector and prevent devastating losses of human capital [ 3 ]. There may be risks associated with rapid scale-up—promotion of drug resistance or implementation of care delivery models that are not a perfect fit in all settings [ 4 ]. It is essential that we manage these risks through effective monitoring, evaluation, “real time” operational research, and knowledge management. However, the risks of action are minor compared with the certain failings of deferral. The number of patients on ART has almost doubled in the last two years (Photo: WHO/Michael Jensen) Third, clear consensus targets are indispensable. An effective response to HIV demands the resources and attention of every region, state, and community. Coordinating these many different stakeholders requires clarity of purpose. All the great public projects of the modern era, such as the first manned moon expeditions of the 1960s, began with the establishment of a ringing collective priority. Like the 3 by 5 initiative, these projects were in themselves only surrogate endpoints. But they provided focus for the energies of their many participants. To reach the ultimate goal of universal access to ART we must plan in stages. Fourth, the specific procedures developed to combat HIV must be codified and simplified. Because pandemics, by definition, afflict communities with a broad range of material resources and technical capacities, our methods must be suitable to the most disrupted and impoverished of them. This means effective training modules to increase the supply of health workers; it means inexpensive, rapid tests and diagnostics; and it means streamlined regimens and fixed-dose combinations that facilitate drug procurement and improve rates of adherence. These principles are at the heart of the 3 by 5 effort. When it was announced in 2002, the gap between the damned and the saved had finally begun to narrow after sharp declines in the price of ART and the emergence of large-scale financing through the Global Fund, the World Bank, and the President's Emergency Plan for AIDS Relief. AIDS is unusual in the history of epidemics because proven, effective ways of interrupting the course of the disease have existed since shortly after its emergence, yet those methods were foreclosed to most of the world's population. The announcement of 3 by 5 drew from a widespread sense that this inequality presented unacceptable economic, political, moral, and epidemiological consequences. Scaling up treatment is not only a possibility, but is already a reality. The number of patients on ART has nearly doubled in the last two years, mostly in countries where therapy had been limited to a privileged few [ 5 ]. High-burden countries are doing their part; the rest of the world must now share more fully in combating the pandemic. From sterile debates over prevention and treatment, the task has shifted to upgrading health systems in resource-poor settings to permit a comprehensive response to the epidemic. Those who object to 3 by 5 must address this question: what would be the likely cost if it were never attempted? We can work exclusively to prevent the further spread of HIV, or aim to improve treatment access more slowly, but in the meanwhile high-burden countries will collapse at our feet. Or we can aim for 3 by 5 and move ourselves that much closer to the ultimate goal: preventing all unnecessary deaths from HIV. Arthur Ammann's Viewpoint: The Intentions Are Good, the Approach Is Wrong There is much that is exemplary about the basic principles outlined by WHO for treatment expansion. Improving access to life-saving ART is a moral imperative and everyone agrees that this will take lots of money [ 6 , 7 ]. So where is the debate? The debate lies in the strategy. Reviewing the epidemic over the past 20 years, you would have to conclude that the current international public health approach has failed and that an urgent change is required. There are three fundamental problems with the 3 by 5 approach. First, it is very narrow, and narrow strategies for tackling HIV often fail. For example, we have known for five years that a single dose of nevirapine can help prevent perinatal HIV transmission. The intervention is simpler and cheaper than the 3 by 5 initiative—yet today less than 5% of pregnant women infected with HIV receive any ART [ 8 , 9 ]. WHO should instead focus on a credible overarching public health approach that is commensurate with the severity of the epidemic. Sound global public health policy requires accountability that respects the right of individuals to be protected from fatal infections. This can only be accomplished by universal offering of HIV testing, integration of HIV prevention and treatment into all health-care arenas, contact tracing, and treatment for all who require ART [ 8 , 10 ]. The 3 by 5 initiative fully addresses only one of these issues—treatment—and leaves HIV-exposed individuals at risk for infection and infected contacts unaware of treatment possibilities. These are irreversible missed opportunities and represent a non-accountable approach to an out-of-control epidemic. Second, confusion about realistic costs, sources of funding, and the relation to other critical WHO initiatives abound. Initial WHO estimates of $5 billion annually for the cost of the entire 3 by 5 initiative have been revised upward to $6 billion annually [ 6 , 7 , 11 ]. It is not clear whether the costs for this program are distinct from other WHO initiatives, are incorporated into the Global Fund, will increase dramatically and continue beyond 2006, or are ultimately incorporated into national budgets. If the true cost is $6 billion annually, this is $2,000 per individual per year, which is surely not sustainable for resource-poor countries. Further, of the 40 million individuals infected with HIV worldwide, it is likely that at least 20 million will require treatment, and there will be millions more newly diagnosed patients [ 11 ]. This would conservatively place treatment costs at over $40 billion per year. Only recently has WHO acknowledged what everyone else seemed to know from the beginning—it will take huge investments in infrastructure to sustain ART delivery [ 7 , 12 , 13 , 14 ]. Third, the 3 by 5 initiative is a “top down” unsustainable approach that, without a high level of government investment, fosters dependence on international aid. Countries that have taken ownership of their HIV programs have often been the most successful in tackling the epidemic [ 8 , 14 , 15 ]. Brazil has mounted an effective response to the HIV epidemic whereas South Africa has not. A key difference between these countries is that 84% of Brazil's AIDS programs are funded from domestic sources compared to 0.4% in South Africa [ 6 ]. Furthermore, there are thousands of nongovernmental organizations, clinics, and hospitals already treating patients with HIV and a “top down” approach doesn't work for these organizations. Many are up and running and require only minimal training to move ART distribution forward. The last thing they need is more internationally imposed hurdles that ensure sequestration of ART in costly and inefficient bureaucracies. The HIV epidemic is the worst pandemic in history. Why, then, is the international public health response so disparate from public health responses to other life-threatening infectious diseases? The 3 by 5 initiative, with no requirement for contact tracing, does not ensure the right of uninfected individuals to be protected or of infected contacts to gain access to treatment. It is time to acknowledge that the severity of the epidemic requires universal offering of HIV testing and counseling, contact tracing, and integration of sound public health prevention and treatment principles into all health-care delivery systems [ 8 , 10 ]. Prevention efforts—including education—must be at the heart of tackling HIV (Photo: Rick Maiman, on behalf of the David and Lucile Packard Foundation) Thousands of existing and new teams of health-care workers should be trained in voluntary testing and counseling, and in treatment, using streamlined training courses. Mobile teams could be used to reach rural areas where as many as 50% of infected individuals may live. Cumbersome “top down” training and certification, as is currently planned, will only delay the very therapy that WHO seeks to make more available [ 8 , 14 , 15 ]. It is a paradox that HIV is one of the few diseases that is deemed to require exceptional international and national bodies overseeing access to medicines. The success of ART in developed countries was a result of making ART directly available to those who treat patients, not to governments. Widespread and timely access can only occur when health workers are able to provide ART without repressive procedures. We can distribute drugs more freely for other diseases—why not HIV? Kim's Response to Ammann's Viewpoint I agree with Arthur Ammann that the response of the international community to the HIV epidemic over the last 20 years has been grossly inadequate. I also agree that a more effective strategy must pay close attention to mother-to-child transmission, provide “opt out” testing and counseling integrated into key health-care settings, implement effective partner referral strategies, and train many thousands of health-care workers. These are stated WHO priorities—integral to the 3 by 5 initiative—as any attempt to investigate our position would reveal [ 16 , 17 ]. Dr. Ammann's other charges are also puzzling. Our latest cost projections (which he cites) in fact provide a two-year, not annual, range of $5.1 to $5.9 billion, depending on the price of drugs [ 7 ]. The accusation of a “top down” approach seems misplaced. WHO's primary contact is indeed with ministries of health, given our constitutionally mandated obligation to provide technical assistance for 192 WHO member states. But I strongly dispute that this relationship somehow prejudices the 3 by 5 agenda against nongovernmental organizations or local providers. WHO is far from the only partner in this struggle, and we actively promote broad-based collaborations within the nonprofit sector, the private sector, among traditional healers, and within civil society [ 18 ]. Finally, I must point out a contradiction in Dr. Ammann's arguments. On the one hand, he urges high-burden countries to take ownership of their HIV programs and finance these themselves. On the other, he acknowledges that if the “true cost [of ART] is $6 billion annually, this is $2,000 per individual per year, which is surely not sustainable for resource-poor countries.” The crucial question is whether $6 billion annually is “sustainable” for the world community as a whole. In facing the worst health disaster in several centuries, we simply cannot wait for the poorest countries to self-finance HIV treatment—or else we will be guilty of standing idly by as millions die and societies collapse. Ammann's Response to Kim's Viewpoint There are time-tested prescriptions for halting epidemics, and HIV should be no exception. But “HIV exceptionalism” persists [ 19 ]. Current public health efforts fail to insist on universal HIV testing and contact tracing, thereby limiting treatment and prevention opportunities and contributing to “feminization” of the epidemic (more and more women getting infected at an earlier age) [ 20 ]. Prevention and treatment are inextricably linked. The 3 by 5 initiative should meet the high standards—individual and organizational accountability, justice, and public good—of other public health approaches. Prevention of perinatal HIV transmission cannot be called a victory—not even a pyrrhic one—since less than 5% of pregnant women infected with HIV receive any ART. Further, in most perinatal HIV prevention programs sexual partners are generally not identified, treatment has only recently been offered, and HIV testing has not been universally implemented. Narrowly focused, top-down programs such as the 3 by 5 initiative face similar outcomes when they adopt yet another partial approach that is not fully integrated into countrywide general health care. The 3 by 5 initiative suggests that treatment is the major incentive for HIV testing. But getting tested has two incentives—treatment and prevention. Knowing one's HIV status is a means of saving lives, an incentive that should motivate every individual to be tested even when treatment is not available. We will destine ourselves to an ever-escalating epidemic if we delay universal testing until treatment is available. Both Jim Yong Kim and I want to treat 3 million individuals infected with HIV and more, and we agree that time is of the essence. But why take another decade to learn what we already know from epidemics such as tuberculosis? Lateral, comprehensive approaches that equip health-care workers with testing and the required drugs work best [ 21 , 22 ]. Procedures to combat HIV have already been simplified by such workers in resource-poor areas—so get the tests and the drugs to them and they will do the treating.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC529425.xml
521079	A failed RCT to determine if antibiotics prevent mastitis: Cracked nipples colonized with Staphylococcus aureus: A randomized treatment trial [ISRCTN65289389]	Background A small, non-blinded, RCT (randomised controlled trial) had reported that oral antibiotics reduced the incidence of mastitis in lactating women with Staphylococcus aureus ( S. aureus )- colonized cracked nipples. We aimed to replicate the study with a more rigorous design and adequate sample size. Methods Our intention was to conduct a double-blind placebo-controlled trial to determine if an antibiotic (flucloxacillin) could prevent mastitis in lactating women with S. aureus -colonized cracked nipples. We planned to recruit two groups of 133 women with S. aureus- colonized cracked nipples. Results We spent over twelve months submitting applications to five hospital ethics committees and seven funding bodies, before commencing the trial. Recruitment to the trial was very slow and only ten women were randomized to the trial after twelve months, and therefore the trial was stopped early. Conclusions In retrospect we should have conducted a feasibility study, which would have revealed the low number of women in these Melbourne hospitals (maternity wards and breastfeeding clinics) with damaged nipples. The appropriate use of antibiotics for breastfeeding women with cracked nipples still needs to be tested.	Background Mastitis is a common problem for breastfeeding women [ 1 , 2 ]. Before planning a trial to reduce the number of lactating women who develop mastitis, we reviewed the literature to identify factors that may be associated with mastitis and to examine previous trials. A relatively small number of trials was identified which included mastitis as one of the outcome measures (see Table) [ 3 - 13 ]. Using historical controls, prophylactic topical penicillin ointment was found to be ineffective [ 3 ], while hand disinfectant at the mother's bedside appeared to reduce mastitis [ 7 ]. A Finnish study examined "breast massage" (which appears to be a variation of "nipple toughening") and found no impact of this practice on mastitis [ 10 ]. Table 1 Trials to prevent mastitis Author, date, country Subjects Aim Control(presence/absence/type) Intervention Sample size Outcome: mastitis Hesseltine et al 1948, USA[3] Patients at the Chicago Lying-In Hospital: July – Sept 1946 Does topical penicillin ointment on mother's nipples prevent mastitis? Historical controls: July 1933 to Dec 1946 Penicillin ointment (2,000 units per treatment) on nipples after feeds (6–8 weeks) Intervention 865; Controls 40,629 Intervention: 53 women with mastitis, 6.1%, and 18 with abscess, 2%; Control: 210 women with abscess, 0.51% Sasse 1973, Germany (in German)[4] Postnatal women in the Frauenclinik der Freien Universitat Berlin-Charlottenburg, 1967 Does an antibiotic spray to mother's nipples prevent mastitis? Historical controls Nabectin Puder Spray(neomycin and bacitracin) applied to nipples, plus hand disinfection for nurses and mothers before handling breasts. Intervention130; Controls100 Intervention: 7% mastitis by 2 months; Control: 23% Berger & Pusteria 1981 Switzerland[5] Postnatal women in the Women's Hospital, University of Berne(reported in 1962 [22]) Does nipple ointment prevent mastitis? One group used a nipple ointment without the active ingredient. Not a RCT. Six nipple ointments: (a) boric-acid Vaseline with Peruvian balsam, (a) 1,000 (a) 1.5% (b) chlortetracycline, (b) 1,000 (b) 0.7% (c) chlorquinadol ointment, (c) 1,000 (c) 0.4% (d) base of chlorquinadol ointment (without active ingredient), (d) 1,000 (d) 0.4% (e) calcium pantothenicum, (e) 2,000 (e) 0.8% (f) dihydrofolliculin benzoate and tyrothrycin (f) 1,500 (f) 0.5% Kovalev 1990, Russia (in Russian)[6] Does treating cracked nipples with laser therapy prevent mastitis? Unclear from abstract Laser treatment to damaged nipples 329 women with damaged nipples Intervention reduced mastitis from 18.6% to 3.7% Sytnik 1990, Russia [8] (in Russian)[8] Does bifidobacterium prevent mastitis? Unclear from abstract Bifidobacterium 160 women Mastitis reduced from 6.88% to 1.25% Peters and Flick-Fillies1991, Germany[7,23] Postnatal women in St Hildegardis Hospital, Mainz, 1989–1991 Does the use of bedside hand disinfectant prevent mastitis? Historical controls: 12 months (Sep 1989-Jun 1990, May-Jun 1991) Bed-side disinfectant dispensers: 12 months (Jul 1990-April 1991, Jul-Aug 1991) Intervention: 1095; Control 1230 Intervention 8 women, 0.65%; Control 32 women 2.9%; p <0.001 Waldenstrom and Nilsson 1994, Sweden[9] Women giving birth at South Hospital, Stockhom Is birth centre care beneficial for breastfeeding? Does it increase duration and reduce complications (including mastitis)? RCT Birth centre care compared to standard care Intervention 617; Control 613. Postal questionnaire 2 months postpartum. "Milk stasis" (fever and swelling, redness and tenderness in one of the breasts): Intervention 26%; Control 19% (p = 0.002). "Mastitis" (infective breast treated with antibiotics): Intervention 1%, Control < 1% (p = 0.07) Jonsson & Pulkkinen 1994, Finland[10] Women in South-West Finland Does antenatal / postnatal breast massage prevent mastitis? Concurrent controls. "Breast massage with the hands, a brush, a coarse towel or a sponge before and / or after delivery" Intervention 255, Control 400. Questionnaire 5–12 weeks postpartum at outpatient visit. Overall incidence of mastitis was 24%. No difference in incidence of mastitis (no details given). "This physical training of the nipples neither decreases or increases the frequency of mastitis" (p86) Evans et al 1995, Australia[11] Postnatal women at Flinders Medical Centre, Adelaide Does prolonged feeding on one breast per feed reduce breastfeeding complications, including mastitis? Historical controls: 5 months Advice to feed from one breast per feed and only offer the second breast if the baby still showed signs of hunger rather than standard care of both breasts at each feed: 5 months Intervention 150; Control 152 Telephone interview at 6 months postpartum: Intervention 15%; Control 18% Gunn et al 1998, Australia[12] Women giving birth in one metropolitan hospital and one rural hospital in Victoria, 1995 Does an early visit to a general practitioner reduce problems (including mastitis) compared to the standard six-week postnatal visit? RCT General practitioner visit at one week compared to standard six week visit Intervention 232; Control 243 Postal questionnaire at 3 months. Intervention 11.6%; Control 15.6% (Odds Ratio 0.71, 95%CI: 0.42, 1.20) Livingstone & Stringer, Canada[13] Women attending the Vancouver Breastfeeding Center with a cracked nipple and S. aureus positive culture. Are oral or topical antibiotics more effective in the treatment of S. aureus -colonized cracked nipples than standard care? RCT (not blind to treatment group or outcome) 4 groups: Assessment at 7 days. Oral antibiotics: 1/19, 5%; Other groups: 16/65 (25%) (Fisher exact 0.1) (a) oral antibiotics (a) 19 (b) topical mupirocin (b) 25 (c) topical fusidic acid (c) 17 (d) standard care (d) 23 The authors of one trial were convinced that their intervention was effective, despite methodological difficulties [ 13 , 14 ]. Livingstone and Stringer conducted a randomised trial for women with cracked nipples with positive cultures for Staphylococcus aureus ( S. aureus) , in Canada[ 13 ]. They compared topical antibiotics, oral antibiotics and "optimal breastfeeding advice" and found better improvement in nipple healing in the women given oral antibiotics. In addition, they found 16 women out of 65 (25%) given non-systemic treatment developed mastitis within 7 days, compared to 1 of 19 women (5%) given systemic antibiotics (chi-square, p = 0.065) [not 0.005 as stated in their abstract]. The authors have concluded that cracked nipples colonized with S. aureus should be "treated aggressively with systemic antibiotics". However, the chi-square test used by the authors is inappropriate because one cell contains an expected value less than 5. Using Fisher's exact test, the p value is 0.10 [ 15 ]. As the Livingstone and Stringer trial had been published in a major lactation journal and was likely to be very influential in practice [ 13 ], it needs to be replicated in a more rigorous manner in order to assess the usefulness and safety of the intervention. Our intention was to replicate that study with an adequate sample size, rigorous definitions of nipple damage and mastitis, and double blinding of the intervention. Methods The aim of our study was to prevent mastitis in breastfeeding women with cracked nipples colonized with S. aureus . A randomised controlled trial was conducted: participating women were randomized to receive a seven day course of either an oral antibiotic (flucloxacillin) or identical placebo capsules. A follow-up visit was arranged one week after recruitment for women with positive nipple culture for S. aureus . Women with negative nipple culture were followed up by telephone at one week. All women received a final telephone interview at six weeks. The primary outcome was the incidence of mastitis in each group in the week following recruitment. In the study by Livingstone and Stringer [ 13 ] 30% of women with S. aureus -colonized cracked nipples who received only breastfeeding advice developed mastitis within one week. In order to detect a 50% decrease in incidence, ie mastitis occurring in 15% of women receiving oral antibiotics, a sample size of 133 women in each group is required, with 95% confidence and 80% power. Sample size was calculated using Epi-Info 6. A previous study in Australia found that 62% (13/21) of cultures from breastfeeding women with cracked nipples were positive for S. aureus [ 16 ]. An earlier study by Livingstone and colleagues found that 54% of cracked nipples of mothers with infants younger than one month were positive for S. aureus (27/50) [ 17 ]. Assuming that 50% of cracked nipples are positive for S. aureus , we would need 133 × 2 × 2 = 532 women with cracked nipples, to recruit two groups of 133 women with S. aureus -colonized cracked nipples. To allow for loss to follow-up, it was planned to recruit 570 women. A review of the literature on the topic of nipple damage found a lack of consistency in assessment of nipple damage [ 18 ]. Many reports have not provided a clear description of the assessment process. Some of the more recent studies have provided a more detailed description, such as Brent et al's Nipple Attribute Score and Duffy et al's Nipple Trauma Index [ 19 , 20 ]. The Nipple Trauma Index used by Duffy and colleagues in Western Australia appeared to be useful, however a request for more information about this instrument was not successful (E. Duffy, email 28 February 2001) [ 20 ]. Our definitions of nipple damage are as follows: mild 1 or 2 mm wide; moderate 3–9 mm wide; severe: greater than 10 mm wide and / or yellow colour visible in crack. In addition to a clinical assessment, a more permanent record of nipple damage was created using digital photography. It was planned for the photographs to be reviewed independently by three lactation consultants, in order to allow a thorough assessment of nipple damage and changes over time, rather than relying on the clinical assessment alone. (As the trial ended prematurely, this did not take place). Furthermore, although the WHO defines mastitis as an inflammation of the breast [ 21 ], there is no generally agreed definition of mastitis for research purposes. The definition of mastitis used for this study was that a woman reported: • at least two breast symptoms (pain, redness, lump) and • at least one of fever or 'flu-like symptoms. Foreseen problems Multi-centred trial As we intended to recruit over 500 women we planned a multi-centred trial, involving a number of public and private maternity hospitals in inner Melbourne. All hospitals provide a breastfeeding clinic staffed with International Board Certified Lactation Consultants for women having breastfeeding difficulties following hospital discharge. The public hospitals, where women tend to have shorter hospital stays, also provide home visits by domiciliary midwives post discharge. It was foreseen that there would be replication in the requirements of the hospital ethics committees and logistical difficulties for one researcher (LA) to conduct the study on multiple sites. Each hospital had its own research ethics committee (or committees) and different forms to submit (at the time of this study). Approval was obtained from the Ethics Committees at La Trobe University (20/11/2000), Royal Women's Hospital (6/9/2000), Mercy Hospital for Women (12/2/2001), Frances Perry House (23/8/2001), Freemasons Maternity Hospital (15/3/2001) and Cabrini Private Hospital (24/04/02). One private hospital did not appear to have a procedure in place to deal with a research proposal. Negotiations continued with this hospital from late 2000 until mid-2002 when the hospital insisted that we sign a Sponsor Indemnity Form, which the university advised us against. The researcher visited the postnatal wards and breastfeeding clinics of these hospitals each day or second day and asked a senior member of the nursing staff if there were any breastfeeding women with damaged nipples in the ward. The staff member introduced the researcher to the woman in order to inform the woman about the study and invite her to participate in the trial. Also, the researcher asked the domiciliary midwives to inform women at home with a cracked nipple about the trial. If the woman were interested in the study, the midwife gave the researcher the woman's name and phone number. After a telephone discussion, the researcher would visit her at home to assess her eligibility. Thus, the researcher was visiting a number of hospitals on a daily basis and making home visits to potential participants and follow-up visits to participants one week after recruitment. Therefore, if the researcher was going to be unavailable one week, she could not recruit women the week prior (as she would not be able to follow them up). Funding All potential participants had a specimen collected from their nipple crack for culture and sensitivity. As this was collected for the purpose of research rather than clinical practice, it was necessary to seek funding for the cost of the microbiological assessment. We intended to recruit 570 women, therefore substantial funds were required. A number of applications (seven) were submitted to local, national and international funding bodies in 2001. A funding application to the Medical Research Foundation for Women and Babies for 2002 was successful (A$15,000). Delay between recruitment and randomization We recognized that there would be a delay between recruitment (when the initial data and nipple specimen were collected) and randomization (when the result was available). The Microbiology laboratory faxed the result to the researcher (or the researcher contacted the laboratory on weekends). However, the minimum time was 2 days for the laboratory to identify S. aureus and up to 6 days in one instance (mean 3.6). The delay meant that women would be at home when the results were available and the researcher was required to visit the participant at her home to deliver the capsules. In addition to the inconvenience, a small number of women had already developed mastitis by the time the researcher contacted her with the result. Unforeseen problems Production of placebo capsules It was expected that a local company specializing in the preparation of placebos for drug trials would prepare the identical capsules. A common practice is to cover the active capsule with a larger capsule; participants are unaware if their capsule contains the active capsule or an inert substance. However, when the company realized that the active capsule contained a penicillin-like drug they were unable to participate, as they do not have a license for penicillin. Finally, the pharmaceutical company, CSL Ltd, provided us with identical empty capsules as well as active flucloxacillin capsules. A pharmacy technician at the pharmacy department at the Royal Women's Hospital opened each capsule manually and inserted glucose powder. Randomisation was conducted in blocks of ten, stratified according to hospital. Ten bottles were prepared for each hospital prior to the trial commencing (further capsules were not needed). Participation Not all the women who were eligible for the trial were interested in taking part (see Figure 1 , ROBIn Trial Profile). Some women expressed a reluctance to take antibiotics, others were overwhelmed with the difficulties they were experiencing and preferred not to participate in a trial. The researchers had previously conducted studies involving breastfeeding women which had high rates of participation and had expected women to be more interested in taking part in a trial that aimed to prevent mastitis. We should have expected a lower participation rate as this study involved the possibility of taking a medication, in particular an antibiotic. Figure 1 ROBIn Trial Profile Less than anticipated incidence of cracked nipples A total of approximately 17,000 women give birth in these hospitals each year. We estimated that 80% of women start breastfeeding, 5% develop cracked nipple(s), 80% would be eligible and 95% would agree to participate, thus there would be 537 eligible women per year. We anticipated that we would recruit approximately ten women with cracked nipples per week. It would therefore take 57 weeks (57 × 10) to recruit the total sample. However, recruitment was slow, as very few women were identified with damaged nipples. Hospital staff made unsolicited remarks that nipple damage was seen much less frequently than in the past. Midwives have been trained to help women position the baby and attach the baby at the breast; women are reporting the presence of nipple pain and any nipple damage is usually identified at an early stage. In the past, women may have continued to breastfeed with poor attachment of the baby to the breast, resulting in more severe damage, whereas at the time of the study maternity staff were likely to suggest "resting" the damaged nipple and expressing the milk by hand or electric pump until the damage had healed. Results Recruitment began at two hospitals in November 2001, two others in February 2002 and a fifth hospital in June 2002. Recruitment was slow as few women had damaged nipples. During the months of the trial, the rate of recruitment decreased rather than increased. Additionally, the flucloxacillin supplied by CSL were labeled to use before the end of November 2002. Therefore it was decided to stop recruiting, once a twelve-month recruiting period had elapsed. The trial stopped recruiting on the 14 th November 2002. Of the 158 women referred to the study as possible participants, 48 women were eligible (ie they had a cracked nipple, were not allergic to penicillin, did not have concurrent "nipple thrush" and had adequate English). Twenty-six of these women refused (10 not interested, 9 didn't want to take antibiotics, 7 other reason given). Therefore, 22 were potentially eligible in that they had at least one cracked nipple and consented to take part in the trial if the results of the nipple swab confirmed S. aureus . Thirteen of the nipple cultures were positive and ten women were randomized to receive flucloxacillin (n = 5) or placebo capsules (n = 5). Two women had already developed mastitis prior to receiving the results and the third woman had developed a rash and did not want to take the capsules. All women were followed-up at one week and six weeks. Of the ten women in the RCT, one woman in the placebo group developed mastitis (not in the first week of the trial, baby was 32 days old, 28 days after randomization). Three women reported that they had not taken the capsules. When the study was unblinded it showed that all three were in the placebo group. Discussion This trial experienced a number of problems, both foreseen and unforeseen. In the trial conducted by Livingstone and Stringer, there is no mention of women refusing to participate in the study or not taking the treatment they were allocated [ 13 ]. It is not reported if any woman developed mastitis in the period between collection of the swab, the clinician receiving the result and the woman being given her allocated treatment regime – indeed the paper does not state that women had to return to the breastfeeding clinic for this. Possibly, women attending a breastfeeding clinic are more likely to comply with treatment regimes than women who are invited to participate in a trial. We thought the estimate of 5% of breastfeeding women developing a cracked nipple was a conservative estimate. For example, in Western Australia, Duffy et al had found that 6% of women in their intervention group had cracked nipples, compared to 69% in their control group [ 20 ]. However, on visiting the postnatal wards and breastfeeding clinics in inner Melbourne, it was not unusual to find that the staff were unable to identify any women with damaged nipples. And of the women who were assessed, more than half did not have a cracked nipple. Therefore, nipple damage appears to be uncommon in breastfeeding women in Melbourne. Conclusions In retrospect, we should have conducted a pilot or feasibility study before commencing the trial. The appropriate use of antibiotics for breastfeeding women with cracked nipples still needs to be tested. We hope our experience will be useful for others planning trials of mastitis or nipple damage. Competing interests None declared. Authors' contributions All authors contributed to the design of the trial, LA reviewed the literature, conducted the trial, and wrote the first draft of the paper. All authors approved the final draft of the paper. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC521079.xml
544193	Females do not have more injury road accidents on Friday the 13th	Background This study reinvestigated the recent finding that females – but not males – die in traffic accidents on Friday the 13th more often than on other Fridays (Näyhä S: Traffic deaths and superstition on Friday the 13th. Am J Psychiatry 2002, 159: 2110–2111). The current study used matched setting and injury accident data base that is more numerous than fatality data. If such an effect would be caused by impaired psychic and psychomotor functioning due to more frequent anxiety among women, it should also appear in injury crashes. Methods We used the national Finnish road accident database for 1989–2002. To control seasonal variation, 21 Fridays the 13th were compared in a matched design to previous and following Fridays, excluding all holidays, on number of accidents, male/female responsibility for accidents, and the number of dead, injured and overall number of active participants (drivers, pedestrians and bicyclists) as a consequence of the accident. Results There were no significant differences in any examined aspect of road injury accidents among the three Fridays, either in females or males. Women were not overrepresented in crashes that occurred on Fridays 13th. Conclusion There is no consistent evidence for females having more road traffic crashes on Fridays the 13th, based on deaths or road accident statistics. However, this does not imply a non-existent effect of superstition related anxiety on accident risk as no exposure-to-risk data are available. People who are anxious of "Black Friday" may stay home, or at least avoid driving a car.	Background One widely spread superstition is that Friday the 13th brings bad luck. However, the few studies published on human behaviour and its consequences on that day show inconsistent results, whether they be on economic behaviour [ 1 - 3 ] or health risks [ 4 - 6 ]. A recent nationwide study by Näyhä [ 7 ] on the 1971–97 death statistics in Finland found that men's deaths did not increase on Friday the 13th but females' did by a factor of 1.61, and by 1.63 when adjusted for age, time period, temperature, and extra Poisson variation. The author's conclusion was that Friday the 13th may be a dangerous day for some women, presumably because of anxiety from superstition and, possibly, anxiolytic medications. This interpretation is not without problems. First, although the author repeatedly refers to driving, it should be noted that he also included water and air traffic accidents. Secondly, as the author pointed out himself, his data included passengers killed in accidents, who typically have no control on the task. Impaired psychic and psychomotor functioning due to anxiety, which could indeed be more frequent in females due to their higher neuroticism rate [ 8 ], superstition [ 9 , 10 ] and smaller amount of driving experience [ 11 ] should primarily affect safety in cases where females were active traffic participants. Third, weather conditions were controlled by the mean daily temperature obtained from one place close to the population centered midpoint of the country. However, Finland is more than 1000 km in length, located between the 60th and 70th deg of Northern latitude with much variation in weather. The vicinity of the sea increases variation in weather and road conditions even more in the southern coast where the population and traffic are heavily concentrated. Any adjustment based on one location cannot be effective. Fourth, by excluding only Good Fridays the author had a sample of Fridays the 13th without holidays because no major holiday in Finland falls on the 13th of month. However, there are plenty of holidays among all other Fridays with quite different travel patterns and life style. For example, Midsummer Eve always falls on Friday in the second part of June, which gives 27 such days in study period 1971–1997. The Midsummer Eve is a marked peak in alcohol consumption in Finland [ 12 ], as well as of crashes of male drivers. Friday can also fall on Christmas day, New Years day, First of May and some other holidays with much reduced traffic volumes and exposure to risk. Finally, in spite of the long study period, the data only included 41 female deaths on 43 Fridays the 13th, which means 16 deaths more than expected from all other Fridays during the study period. In spite of Näyhä's fairly conservative conclusion, his results have been widely publicised as evidence that superstitious female drivers die on Fridays the 13th [ 13 ] in marked contrast to men. Due to the shortcomings listed above, and fairly small sample size, the results deserve reinvestigation to avoid premature conclusions and improper interpretations which tend to promote sexist attitudes about women drivers. We reinvestigated the case using the national Finnish road accident data base of injury accidents [ 14 ] for 1989–2002, all years available in a comparable format. These data also include road-traffic fatalities, and for that part they overlap with Näyhä's study period and data. A matched design was selected which makes it possible to control seasonal effects and to avoid the problems due to holidays. Injury accidents are much more numerous than fatalities. If women's assumed more frequent superstitious (and traffic-related) anxiety indeed would result in attentional and psychomotor dysfunctioning on Fridays the 13th, claimed by Näyhä [ 7 ] on the basis of fatality statistics, the effect should also be found in injury crashes. Methods There were 24 Fridays the 13th during the study period. However, three of them were excluded because two were Good Fridays and one followed a Thursday holiday. To control seasonal variation in traffic and weather-type, the remaining 21 Fridays the 13th were compared with the previous Fridays the 6th and the following Fridays the 20th on the number of accidents, male/female responsibility for accidents (police officer judgment), the number of dead, injured and overall number of active participants as a consequence of accident, separately for women and men. Active participants included drivers, bicyclists and pedestrians who actively controlled their motion in traffic and may get involved in crashes. Motor vehicle passengers were excluded. Nine holidays or otherwise unusual control Fridays were replaced by the mean values of the accident variables (e.g. number of accidents, number of injured) from the previous and following years' closest Fridays. For example, Friday the 20th in June 1997 fell on Midsummer holiday eve, and was replaced by mean values gathered from Fridays June 14th, 1996 and June 12th, 1998. This was done to preserve size of the sample. To avoid violating parametric assumptions, the Friedman analysis of variance by ranks [ 15 ] was used to test differences across 21 matched triplets of Fridays. Results Tables 1 , 2 , 3 present accidents and active participants and victims by gender for the Fridays the 13th and the preceding and next Fridays. Figure 1 depicts daily means of active participants by gender on each of three Fridays. Table 1 The number of injury accidents on Fridays the 13th, the previous (the 6th) and following (the 20th) Fridays. N for the matched triplets of Fridays = 21. Friday Total Daily Mean 6th 542.5* 25.83 13th 608 28.95 20th 546.5 26.02 * Decimal numbers in Tables 1-3 are due to replacement of seven holidays or otherwise unusual control Fridays with the mean values of the variables from the previous and following years' closest Fridays. Table 2 The number of active participants* by gender on Fridays the 13th, the previous (the 6th) and following (the 20th) Fridays. Female Male Friday Total Drivers Pedestrians and Bicyclists Total Drivers Pedestrians and Bicyclists 6th 299.5 193.5 106 713.5 618 95.5 13th 317 198 119 824 705 119 20th 299 183 116 748.5 661.5 87 * Active participants included drivers, bicyclists and pedestrians who actively control their motion in traffic and may get involved in crashes. Table 3 The number of victims* by gender on Fridays the 13th, the previous (the 6th) and following (the 20th) Fridays. Female Male Friday Dead Injured Dead Injured 6th 6 (9)* 196 (290.5) 27.5 (33.5) 308.5 (372) 13th 15 (21) 214 (304) 30 (35) 340 (430) 20th 11 (13) 195.5 (296) 22.5 (25) 329.5 (418.5) * Numbers for victims refer to active participants while those in parenthesis also include passengers. Figure 1 The average daily number of active participants involved in injury road crashes by gender on the Fridays 13th and the preceding and following Fridays for 1989–2002. Comparisons of 21 triplets showed no significant difference in injury accidents (Friedman χ 2 = 3.534, df = 2, p = 0.171); in active participants, for females (χ 2 = 0.025, df = 2, p = 0.987) or males (χ 2 = 0.173, df = 2, p = 0.917); in injured active participants, for females (χ 2 = 1.162, df = 2, p = 0.559) or males (χ 2 = 0.532, df = 2, p = 0.767); and in dead active participants, for females (χ 2 = 2.735, df = 2, p = 0.255) or males (χ 2 = 0.448, df = 2, p = 0.799) among three Fridays. To test the Gender × Day interaction, we also computed female/male ratios of active participants for each Friday of each triplet, and applied the Friedman test to check whether this ratio is systematically higher on Fridays 13th, as expected from Näyhä's [ 7 ] results. The ratio was quite similar on each Friday (6th: 0.420, 13th: 0.385, 20th: 0.452; χ 2 = 0.400, df = 2, p = 0.819) indicating that, with respect to men, women are not overrepresented in crashes that occur on Fridays 13th. The odds for women being involved in an injury tend to be even somewhat smaller on Friday 13th. There was no such overrepresentation in injured (χ 2 = 1.615, df = 2, p = 0.446) or dead (χ 2 = 2.1, df = 2, p = 0.350) women among active participants. Finally, we similarly checked a possible Gender × Day effect in legally responsible crashes (responsibility drawn from police reports), computing female/male ratios of guilty participants for each day and triplet, but did not found any effect(Friedman test, χ 2 = 0.514, df = 2, p = 0.774). Discussion This study could not find any indication of overrepresentation of women in injury crashes on Friday the 13th. This is inconsistent with Näyhä's [ 7 ] results and conclusions that were based on less numerous deaths statistics (41 women died in all traffic accidents on Fridays 13th 1971–97) compared to injury road traffic accidents (317 active female participants on Fridays 13th 1989–2002), and also inconsistent with earlier British results [ 4 ]. Given that women's more frequent superstition and related anxiety would cause unsafe traffic behaviour, injury accidents should increase on Friday the 13th as well as fatalities. This was definitely not the case in the Finnish road accident statistics. Although injury accidents are not reported as completely as fatalities, we do not see any reason for biased reporting on Fridays the 13th. Our analysis did not even show any significant gender effect in fatalities. It is to be noted that both Näyhä's study [ 7 ] and this study are based on aggregated data (number of accidents per day in the country). In contrast to individual level analysis, such data mixes individual confounders and outcomes and, therefore, confounding factors cannot be fully controlled [ 16 ]. Our matched countrywide setting is a quasi-experimental design well suited to simple comparisons of crash rates in gender populations which keep constant in each triplet of successive Fridays (see also [ 4 ]). We also assume that this design is quite powerful in controlling seasonal variation (e.g. in traffic and weather). However, our data only implies that, in comparison to men, women are not overrepresented in injury road accidents on Fridays 13th in Finland for 1989–2002. We do not and we cannot conclude anything about women's performance in traffic on Fridays 13th, or about their accident risk (given certain exposure to risk), or about the effect of superstition on those risks. For such conclusions, disaggregated individual level data is needed with detailed information of exposure to risk and respective accident outcome. People themselves adjust their exposure to risk at several levels, while making trip decisions, choosing transport mode, or selecting routes to the destination (see the "multiple sieve model" of accident output [ 17 ]). Therefore, those who are really anxious about Friday 13th may stay at home, use public transportation instead of car, avoid rush hours, choose safer routes, or avoid dangerous junctions. But for one left turn while driving, or for one crossing of street while walking, their risk may be higher. Conclusion We conclude that, in the Finnish traffic accident statistics for 1989–2002, females have not incurred more injury (or fatal) road traffic accidents on Fridays the 13th than expected, as a driver, bicyclist or pedestrian. We suggest that Näyhä's contradicting result on fatalities is due to different sampling, non-optimal setting and chance in a fairly small data. However, this does not imply a non-existent effect on accident risk as no exposure-to-risk data [ 18 ] are available. People who are anxious of "Black Friday" may stay home, or at least avoid driving a car. The only relevant data [ 4 ], suggesting a small decrease in highway traffic, is rather limited and should be confirmed with more extensive research. Competing interests The authors declare that they have no competing interests. Authors' contributions Both authors participated in each stage of research and manuscript preparation. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544193.xml
521086	Identification of the 15FRFG domain in HIV-1 Gag p6 essential for Vpr packaging into the virion	The auxiliary regulatory protein Vpr of HIV-1 is packaged in the virion through interaction with the Gag C-terminal p6 domain. Virion packaging of Vpr is critical for Vpr to exert functions in the HIV-1 life cycle. Previous studies suggest that Vpr interacts with a (Lxx)4 domain in p6 for virion packaging. In the present study, mutational analysis of HIV-1 Gag p6 domain was performed in the context of the HIV-1 genome to examine the effect on virion packaging of Vpr. Surprisingly, Ala substitutions for Leu 44 and Phe 45 in the (Lxx)4 domain or deletion of the whole (Lxx)4 domain (amino acid #35–52 of the Gag p6 domain) did not affect Vpr virion packaging. Vpr virion packaging was normal when amino acid #1–23 of the Gag p6 domain was preserved. Most importantly, Ala substitutions for Phe 15 , Arg 16 and Phe 17 in the context of amino acid #1–23 of the Gag p6 domain abolished Vpr virion packaging. Single Ala substitutions for Phe 15 and Phe 17 also abolished Vpr virion packaging, whereas Ala substitution for Arg 16 had no effect. Our studies have revealed a novel signal sequence for Vpr packaging into the HIV-1 virion. The 15 FRFG domain in p6 resembles the FxFG repeat sequences commonly found in proteins of the nuclear pore complex. These results have provided novel insights into the process of virion packaging of Vpr and suggest for the first time that Vpr may recognize the FxFG domain for both virion packaging and association with nuclear pores.	Findings Vpr is a 15 kDa auxiliary regulatory protein of HIV-1 produced in the late phase of the viral life cycle and packaged in the virion [ 1 - 3 ]. Thus, Vpr has the capacity to function both in the early phase and the late phase of the viral life cycle. A number of biological activities have been assigned to Vpr, including nuclear localization [ 4 - 6 ], transcriptional effects [ 7 , 8 ], cell cycle arrest at the G2/M check point [ 9 - 13 ], and pro- and anti-apoptotic activities [ 14 - 18 ]. In most cases the direct cellular target for Vpr remains to be identified. It is possible that Vpr has multiple unrelated functions to facilitate HIV-1 interaction with the host cells. Alternatively, some of the biological activities of Vpr may be explained by a common mechanism. Transiently expressed Vpr localizes in the nucleus, and specific nuclear localization signals have been identified in Vpr [ 6 ]. Vpr nuclear transport has been correlated with interaction with importin a [ 19 ]. However, the nuclear localization of Vpr appears to be more complicated since Vpr is also found to interact with residents of the nuclear pore complex [ 20 ]. Notably, Vpr is found to interact with the FG repeat domain of rat Poml21, which is a nuclear pore protein [ 20 ]. However, in similar assays Vpr fails to interact with the FG repeat domain of other nuclear pore proteins [ 20 ]. Thus, the exact specificity of this interaction remains uncharacterized. Virion packaging of Vpr is through interaction with the Gag C-terminal p6 domain [ 1 ]. With vaccinia expression of HIV-1 Gag and Vpr, a (Lxx)4 domain (amino acid #35–46) in HIV-1 p6 was determined to be essential for virion packaging of Vpr [ 21 ]. Fusion of MLV Gag with the HIV-1 p6 domain allows the fusion protein to package Vpr [ 22 ]. Under this condition, single point mutations of L45A or F46A within the (Lxx)4 domain abolish Vpr virion packaging [ 22 ]. The direct interaction of HIV-1 p6 with Vpr appears to be rather weak, detectible only by using a sensitive in vitro assay [ 23 ]. The dissociation constant for the p6-Vpr complex is between 18–75 μM [ 23 ]. It is hypothesized that this weak interaction may be enhanced during the process of virion packaging when Gag forms oligomers [ 23 ]. Secondary interactions between Vpr and other regions of Gag may also aid virion packaging of Vpr [ 24 ]. Interestingly, the HIV-1 p6 also has well-characterized domains for binding cellular sorting factors Tsg101 and AIP1 [ 25 , 26 ]. Whether these interactions influence Vpr virion packaging remains unclear. In this study, sequences in HIV-1 Gag p6 domain required for Vpr virion packaging was dissected in the context of the HIV-1 genome. Surprisingly, the previously identified (Lxx)4 domain in p6 is shown non-essential for Vpr virion packaging. Instead, a 15 FRFG domain in HIV-1 Gag p6, 4 amino acid residues downstream of the Tsg101-binding domain, is found critical for Vpr virion packaging. Since FxFG domains also occurs in nuclear pore proteins, the current finding also suggests for the first time that Vpr may recognize the same FxFG domain for both virion packaging and association with nuclear pores. Thus, the FxFG domain appears to be a favorite signal for in vivo recognition by Vpr. We discuss the impact of this finding in the context of the HIV-1 life cycle. To examine the biochemical process of Vpr virion packaging, we introduced various Gag p6 mutations into an HIV-1 genome containing partial deletion of the Pol gene and HA-tagged ubiquitin in place of the Nef gene. This modified HIV-1 genome was used to facilitate construction of p6 mutants and to examine ubiquitination of HIV-1 proteins. All HIV-1 genomic constructs were based on the p89.6 plasmid [ 27 ] and their sequences were confirmed by automatic sequence analysis. p89.6/Po1 - /R + and p89.6/Pol - /R - constructs were described before [ 28 ]. A BamHI site was inserted at the beginning of the Nef ORF in a subclone of p89.6 carrying the 3' half of the HIV-1 genome, p89.6/3'[ 27 ], to generate p89.6/3'-BamHI. This modification also resulted in deletion of the 5' region of Nef ORF up to the KpnI site. Subsequently, the HA-Ub coding sequence was PCR-amplified from the pCMV-HA-Ub plasmid [ 29 ] with primer 1 AGTTACGGATCCATGGCATAGCTACCCTTATGACGTC and primer 2 CATTCAGGATCCTACCCACCTCTGAGACGGAGGACCAG, digested with BamHI and inserted into the p89.6/3'-BamHI plasmid to generate p89.6/3'-HA-Ub. The EcoRI/PstI-blunt fragment of p89.6/3'-HA-Ub was ligated to the EcoRI/SmaI sites of p89.6/Pol - /R + and p89.6/Pol - /R - to generate p89.6/HA-Ub/R + and p89.6/HA-Ub/R - constructs, respectively (labeled as HA-Ub/R + and HA-Ub/R - in Fig. 1 ). Figure 1 HIV-1 genomic constructs and requirements for Vpr virion packaging. A) All viral constructs were based on the p89.6/HA-Ub/R + . Pr - /R + : genomic construct carrying the wild type p6 and a premature stop codon for the protease ORF immediately after the p6 stop codon. All other clones were derived from the Pr - /R + construct. Bold-typed regions represent binding sites for Tsg101, Vpr (this study), and AIP1. B) Effects of p6 mutations on virion packaging of Vpr. Experimental conditions are described in "Findings". Left panels: Gag and Vpr Western blots with virion samples. Right panels: top two panels are Western blots of virion samples, whereas the bottom panel is Western blot of Vpr immunoprecipitated from cell lysates. C) Comparision of the 15 FxFG domain in HIV-1 Gag p6 with the FxFG domains in human Pom121. HIV-1 p6 sequence is derived from isolate 89.6 [27], and the human Poml21 sequence is derived from GenBank accession number BC008794. Numbers indicate the amino acid positions in the proteins. The p89.6/Pr - /R + and p89.6/Pr - (LF) a /R + constructs were prepared by inserting a PstI/StuI digested PCR DNA fragment into the PstI/BalI sites of p89.6/HA-Ub/R + . For p89.6/Pr - /R + , PCR was performed with the p89.6/5' clone as the template [ 27 ], and primer 3 GGTACATCAGGCCATCTCACC and primer 4 CTGACCAGGCCTCCCGGGTTATTTTATTGTGACGAGGGGTCGTTGC. For p89.6/Pr - (LF) a /R + , PCR was performed with the same template and primer 3 and primer 5 CTGACCAGGCCTCCCGGGTTATTTTATTGTGACGAGGGGTCGTTGCCTGCGGC TGATCTGAGGGAAGC. For constructs p89.6/Pr (Lxx) - /R + , p89.6/Pr - (1–23)/R + and p89.6/Pr (FRF) a /R + , the PCR DNA was digested with PstI/SmaI and ligated into the PstI/SmaI sites of p89.6/Pr - (LF) a /R + . For p89.6/Pr - (Lxx) - /R + , PCR was performed with the p89.6/5' template and primer 3 and primer 6 GTACTACCCGGGAGGCCTTTATTCCTTGTCTATCGGCTCCTGC. For p89.6/Pr - (l-23)/R + , PCR was performed with primer 3 and primer 7 GTACTACCCGGGAGGCCTTTATTGAGTTGTTGTCTCCTCCCCAAACC. For p89.6/Pr - (FRF) a /R + , PCR was performed with primer 3 and primer 8 GTACTACCCGGGAGGCCTTTATTGAGTTGTTGTCTCCTCCCCGGCCGCGGCGC TCTCTGCTGG. The construct p89.6/Pr - F15A/R + , p89.6/Pr - R15A/R + , and p89.6/Pr - F17A/R + were prepared in the same way as p89.6/Pr - (1–23)/R + , except that the PCR was performed with primer 3 and a new primer instead of primer 7: primer 9 (for p89.6/Pr - F15A/R + ) ACTCGACCCGGGAGGCCTTTATTGAGTTGTTGTCTCCTCCCCAAACCTGGCGC TCTCTGCTGG, primer 10 (for p89.6/Pr - R16A/R + ) ACTCGACCCGGGAGGCCTTTATTGAGTTGTTGTCTCCTCCCCAAACGCGAAGC TCTCTGC, and primer 11 (for p89.6/Pr - F17A/R + ) ACTCGACCCGGGAGGCCTTTATTGAGTTGTTGTCTCCTCCCCGGCCCTGAAGC TCTC. The construct p89.6/Pr - (l-23)/R + /Δ Ub was prepared by removing the BamHI-BamHI fragment, encoding the HA-tagged Ub gene, from the p89.6/Pr - (1–23)/R + construct. Cell culture and transfection were performed under conditions described previously [ 18 ]. To obtain HIV-1 virions, three days after transfection, culture supernatant was clarified by a low speed centrifugation followed by filtration through a 0.45 nm filter. The clarified culture supernatant was subjected to centrifugation through a 20% sucrose cushion in the SW50.1 rotor at 33,000 rpm for 1 hour. Virions from transfected 293 cells were examined for the presence of Gag and Vpr by Western blot analysis. As shown, Gag p55, p24, p17 as well as Vpr were all detected in the virions with the R + genome (Fig. 1B , lane 1). With the HIV-1 genome containing a premature stop codon in Vpr (R - genome), no Vpr was detected in the virion (lane 2). We subsequently prepared a protease-truncated construct based on the R + genome, named Pr - /R + , and observed normal Vpr virion packaging (Fig. 1B , lane 3). As expected, Gag p55 was not processed with the Pr - /R + construct due to the loss of protease. Surprisingly, normal Vpr virion packaging was still observed with the Pr - (LF) a /R + construct (lane 4), which contains L44A/F45A double mutations in the Gag p6 domain (Fig. 1A ) that are reported to abolish Vpr packaging in the context of the MLV Gag/HIV-1 p6 fusion construct [ 22 ]. The whole (Lxx)4 domain was then deleted from p6 to generate the Pr - (Lxx) - /R + construct, and again normal Vpr packaging was detected (Fig. 1B , lane 5). The Pr - (Lxx) - /R + construct still maintains a 15 FRFG domain in p6 which resembles the FxFG domain frequently observed in resident proteins of the nuclear pore [ 30 ]. To examine the potential involvement of this domain in Vpr packaging, another p6 deletion construct was prepared, with only aa #1–23 of p6 preserved (Fig. 1A ). As shown, normal Vpr virion packaging was also observed for this construct, Pr - (1–23)/R + (Fig. 1B , lane 6). Subsequently, 15 FRF residues were all substituted by Ala residues to generate the Pr - (FRF) a /R + construct (Fig. 1A ). Importantly, this mutant failed to package Vpr into the virion (Fig. 1B , lane 7). To examine the roles of individual amino acid residues in the 15 FRFG domain during Vpr packaging, Phe 15 , Arg 16 and Phe 17 were individually substituted by Ala (Fig. 1A ). As shown, while single F15A and F17A mutations abolished Vpr packaging (Fig. 1B , lanes 8 and 10), R16A mutation had no effect (lane 9). Since all of the HIV-1 constructs expressed HA-tagged ubiquitin (HA-Ub), the HA-Ub coding sequence was removed from the Pr - (1–23)/R + construct. As shown, removal of HA-Ub had no effect on Vpr virion packaging (Fig. 1B , lane 11). Analysis of cell lysates showed that all HIV-1 genomic constructs expressed the same amount of Vpr in the cell (Fig. 1B , lanes 5–11, bottom panel). These results strongly suggest that the 15 FRFG domain is critical for Vpr virion packaging. In this report we provide evidence that HIV-1 Vpr is packaged into the virion through the previously unrecognized 15 FRFG domain in the Gag p6 domain. The Vpr packaging function of the 15 FRFG domain is preserved when amino acid #1–23 of p6 is retained. This function is abolished when 15 FRF are substituted by Ala residues. Our conclusion is further supported by the finding that Ala substitutions for Phe 15 and Phe 17 abolish Vpr packaging whereas Ala substitution for Arg 16 has no effect. Previous studies have shown that a (Lxx)4 repeat domain in Gag p6 is essential for Vpr virion packaging [ 21 , 22 ]. The exact reason for the discrepancy is unclear. However, the previous studies were based on vaccinia expression of Gag and Vpr [ 21 ] or on the MLV Gag/HIV-1 p6 fusion constructs [ 22 ]. It is possible that different experimental conditions affect the virion packaging of Vpr. Alternatively, different HIV-1 strains may prefer the 15 FRFG domain or the (Lxx)4 domain for Vpr packaging. It is noticeable that although the 15 FRFG domain is highly conserved among different HIV-1 strains, it is replaced with 15 FRSG in the HIV-1 Hxb2 strain (GenBank accession number K03455) and 15 VRFG in the Yu-2 strain (GenBank accession number AF287352). Future studies may reveal if an engineered FRFG domain in these HIV-1 strains can allow Vpr packaging in the absence of the (Lxx)4 domain. Significantly, the 15 FRFG domain of p6 resembles the FxFG domains of certain nucleoporins with respect to both the FxFG core and the following hydrophilic residues rich in Ser/Thr residues (Fig. 1C ). Thus, Vpr appears to recognize the same sequence for both virion packaging and association with the nuclear envelope for transport into the nucleus. We hypothesize that the FxFG domain is one of the most important signals for Vpr recognition in vivo. It may govern Vpr function during both the late phase and the early phase of the HIV-1 life cycle. Vpr interaction with nucleoporins has been reported before [ 20 ]. In particular, Vpr is found to interact with the FG repeat domain of Pom121 and more weakly with that of Nsp1p [ 20 ]. It has been suggested that the FG residues in these FG repeats constitute the hydrophobic core that is critical for recognition by other proteins [ 30 ]. However, the property of this hydrophobic core and the specificity of protein-protein recognition are critically dependent on the neighboring residues preceding the FG residues, so that the FxFG, GLFG, and other types of FG repeats may be involved in different protein-protein interactions [ 30 ]. Comparison of the Gag FxFG domain with the seven of the FxFG repeats of the human Pom121 reveals that these FxFG domains are followed by a sequence rich in Ser/Thr residues (Fig. 1C ) which may be critical for the function of the FxFG domain. The roles of these Thr residues in Vpr virion packaging remain to be dissected. It is likely that Vpr recognizes the FxFG domain and not other types of FG repeats. Single Ala substitution for Phe 15 in the 15 FRFG domain of p6 abolishes Vpr virion packaging (Fig. 1 ). The nucleoporin Nup159p does not interact with Vpr [ 20 ], and its FG repeat domain contains eight PxFG repeats and no FxFG repeat. In contrast, the FG repeat domain of the Vpr-interacting nucleoporin Pom121 contains seven copies of the FxFG repeats and six copies of the PxFG repeat. Another nucleoporin that interacts with Vpr weakly, Nsp1p, has a large number of FxFG repeats. However, it is expected that nucleoporins function in the context of a large protein complex and their conformations and interaction with Vpr may be influenced by the presence of other interaction partners. List of abbreviations MLV: murine leukemia virus; Ub: ubiquitin. Competing interests None declared. Authors' contributions HZ and HJ participated in the construction of mutant HIV-1 genomes, cell culture, transfection, and Western blot analyses. LZ conceived of the study and participated in its design, coordination and execution. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC521086.xml
523849	A population-based statistical approach identifies parameters characteristic of human microRNA-mRNA interactions	Background MicroRNAs are ~17–24 nt. noncoding RNAs found in all eukaryotes that degrade messenger RNAs via RNA interference (if they bind in a perfect or near-perfect complementarity to the target mRNA), or arrest translation (if the binding is imperfect). Several microRNA targets have been identified in lower organisms, but only one mammalian microRNA target has yet been validated experimentally. Results We carried out a population-wide statistical analysis of how human microRNAs interact complementarily with human mRNAs, looking for characteristics that differ significantly as compared with scrambled control sequences. These characteristics were used to identify a set of 71 outlier mRNAs unlikely to have been hit by chance. Unlike the case in C. elegans and Drosophila , many human microRNAs exhibited long exact matches (10 or more bases in a row), up to and including perfect target complementarity. Human microRNAs hit outlier mRNAs within the protein coding region about 2/3 of the time. And, the stretches of perfect complementarity within microRNA hits onto outlier mRNAs were not biased near the 5'-end of the microRNA. In several cases, an individual microRNA hit multiple mRNAs that belonged to the same functional class. Conclusions The analysis supports the notion that sequence complementarity is the basis by which microRNAs recognize their biological targets, but raises the possibility that human microRNA-mRNA target interactions follow different rules than have been previously characterized in Drosophila and C. elegans .	Background MicroRNAs (miRNAs) are small, ~18–24 nt. noncoding RNAs that are found in all eukaryotes and are cleaved from larger ~70 nt. precursors via the action of Dicer enzyme [reviews: ref. [ 1 , 2 ]]. MicroRNAs are thought to degrade messenger RNAs via eliciting mRNA degradation (if they bind in a perfect or near-perfect complementarity to the target mRNA), or to arrest translation of the mRNAs (if the binding complementarity is imperfect). Although a number of microRNA targets have been identified in plants, C. elegans and Drosophila [ 1 , 2 ], only one mammalian microRNA target has yet been validated [ 3 , 4 ]. Five different papers have recently appeared that used computational approaches to predict microRNA targets in Drosophila [ 5 - 7 ], and mammals [ 8 , 9 ]. These studies only considered hits occurring within 3'-UTR regions that were conserved across related species, and favored or required a short region of perfect complementarity towards the 5'-end of microRNAs. However, there is reason to suspect that the rules governing microRNA-target interactions may not be universal. For example, in plants, most of the known microRNAs bind in a perfect or near-perfect manner to mRNA targets located within the protein coding region (cds) [ 10 , 11 ]. In contrast, in C. elegans [ 12 ] and Drosophila [ 13 ], known microRNAs lack long stretches (>10) of complementarity with their targets and generally interact within the 3'-untranslated region (3'-UTR). Furthermore, whereas the 5'-ends of many Drosophila microRNAs recognize 5–6 nt. common motifs within the target, these motifs are not a general feature of mammalian microRNAs [ 14 ]. Thus, it is conceivable that human microRNA targets do not follow the same constraints as observed in C. elegans and Drosophila . In the present paper, we have performed an unbiased statistical analysis of the manner in which human microRNAs interact complementarily with human mRNAs present in the NCBI human RefSeq database, looking for characteristics that differ significantly as compared with scrambled versions of the same microRNA sequences. The results demonstrate several novel features of human microRNA-mRNA interactions that differ from C. elegans and Drosophila , and identify a short-list of promising candidate microRNA-mRNA target pairs that are unlikely to have arisen by chance. Results Population-wide statistical analyses were first carried out by examining the types of complementary interactions that occur between the set of microRNAs listed in Lagos-Quintana et al [ 15 ], and the set of human RefSeq mRNAs downloaded in August 2003. To obtain a fuller list of outlier mRNAs, analyses were repeated using all human microRNAs listed on the Sanger microRNA repository [ 16 ] and the set of human RefSeq mRNAs listed as of December 2003 [ 17 ]. To define the types of interactions that can occur by chance, ten independent sets ("replications") of scrambled microRNA counterpart sequences were generated and examined for complementarity with the mRNA population. Our underlying assumption is that scrambled sequences will hit mRNA at random and define the "noise" level in any given situation, whereas microRNA sequences will hit the same number of "noise" interactions plus any true targets. Unless otherwise noted, the scrambled sequences were random permutations of the microRNA sequences, keeping constant the overall nucleotide composition. Because microRNAs have a distinctive nonrandom di-nucleotide composition, we also confirmed that key findings were obtained when using scrambled sequences that had similar di-nucleotide composition to the microRNAs. 1. Human microRNAs tend to have longer exact hits upon mRNAs than do their scrambled counterparts First, we characterized the length distribution of exact complementarity between the population of mRNAs vs. the set of nonredundant microRNAs (i.e. those that overlapped by 10 or more bases were collected into groups and the longest member of the group was chosen as nonredundant). MicroRNAs produced significantly longer exact "hits" on mRNAs than their scrambled counterparts when G:U matches were excluded (fig. 1 ). There was an excess number of hits in the microRNA set relative to scrambled control sequences at all exact hit lengths (10 or greater), and the difference became proportionately greater at longer hit lengths (see below). When microRNAs were compared to scrambled sequences that matched the di-nucleotide composition of microRNAs, similar results were obtained. In contrast, this trend was not observed when G:U matches were included (not shown). Experimental studies suggest that RNA interference and arrested translation can still be elicited when small RNAs are modified to replace a number of Watson-Crick base pairs by G:U matches [ 18 - 20 ]. On the other hand, G:U matches have distinctive binding energy and spatial orientation [ 21 ]. Unless otherwise qualified, "exact hits" will refer to complementarity without G:U matches. 2. Constructing an outlier set of microRNAs based on cut-offs of exact hit length, gapped BLAST score and presence of multiple hits As shown in figure 1 , there are a total of 101, 279 microRNA hits upon RefSeq sequences hitting exactly ≥10 bases in a row, compared to 75,031 hits produced by scrambled microRNA sequences. The difference (26, 248 hits, distributed among 8258 mRNA sequences) is highly significant (p = 3 × 10 -9 ) and suggests that about 1/4 of the total hits in this "10+ set" occur upon "true" biological mRNA targets. Our approach is to identify further the mRNAs that represent statistical outliers (i.e. that are unlikely to be hit by chance) within this larger "10+ set" by comparing properties of hits made by the set of microRNA sequences vs. the set of scrambled sequences. At any given parametric value, the number of hits observed in the microRNA set, minus the number of hits in the scrambled set, provides an estimate of the number of true microRNA targets that satisfy that parametric value. We examined three different hit properties – a) exact hit length, b) gapped BLAST score and c) presence of multiple hits – both alone and combined with each other. Starting from the "10+ set" estimated to contain only 26% true targets (see above), we added additional criteria to compile a list of candidates estimated to contain over 80% true targets. a) Exact hit length The most important single parameter for discriminating hits produced by microRNAs vs. scrambled sequences appears to be exact hit length. At a cut-off of 17 exact hit length, there were 14 mRNAs hit by the microRNA set that satisfied this criterion, vs. an average of 1.9 mRNAs hit by each of the scrambled sequence sets (fig. 1 ). Stated another way, this criterion gives a discrimination ratio of 7.4 to 1. A similar discrimination ratio was observed when comparing scrambled sequences maintaining the same di-nucleotide composition as the microRNAs. b) Gapped-BLAST score Overall complementarity of the microRNA-mRNA alignment was also examined within the "10+ set" of individual mRNAs exhibiting exact microRNA hits of at least 10 bases in a row. A modified gapped-BLAST algorithm [ 22 ] was used to compute the optimal alignment, employing a weighted score that takes gaps and mismatches into account (r = 10, q = -2.5, G = 8, E = 0.5). Although the two curves overlap quite a bit, their means are significantly different from each other (p < 0.0001), and the microRNA distribution exhibits a discrete "tail" at higher scores that differs significantly from the scrambled distribution (fig. 2 ). c) Multiple hits In lower organisms, individual validated microRNA targets tend to receive multiple hits by distinct microRNAs [ 1 , 2 ]. mRNA sequences within the "10+ set" were hit by multiple nonredundant microRNAs more often than by their scrambled counterparts, and this was particularly striking when the hits were located close together (fig. 3 ). d) Combining parameters When combined, all three parameters (exact hit length, gapped-BLAST scores and multiple hits) gave better discrimination power than using any single feature, supporting the idea that they are relevant to identifying biologically relevant mRNA targets. We examined three different combinations of parameter cut-off values: 1) One combination consisted of targets with multiple hits from distinct microRNAs less than 25 bases apart, with at least one exact hit ≥13 bases and with at least one gapped BLAST score ≥185 (not counting G:U). For the next two lists, we scored only exact hits ≥10 bases long and that occurred ≤50 times within the entire mRNA population; this minimized "noise" arising from common or low-complexity target sequences, albeit at the cost of removing some target sequences that are shared within protein families. 2) Criteria required two or more hits from distinct microRNAs ≤100 bases apart, at least one exact hit ≥14 bases and one gapped-BLAST score of ≥190 (not counting G:U). 3) This required hits ≤500 bases apart, at least one exact hit ≥14 bases, and at least one gapped-BLAST score > 89% of the best-possible score including G:U matches (this takes into account the fact that longer microRNAs have greater possible absolute scores than shorter microRNAs). All three approaches produced lists of outlier mRNAs that had overlapping members, shared similar characteristics and exhibited similar discrimination ratios. For simplicity and robustness, these have been combined (together with the candidates identified by exact hit length alone) into a single list consisting of 71 outlier mRNAs (Table 1 ). The combined list was hit by almost the entire set of nonredundant microRNAs (i.e., 107 out of 109). In contrast, scrambled counterpart sequences hit an average of 13.7 ± 1.15 targets and were represented by 54.3 ± 3.5 nonredundant sequences. The combined outlier set gives an overall discrimination ratio of 5.2 to 1, meaning that 57 of the 71 mRNAs are in excess of the number that could be reasonably expected by chance, hence should be accurately assigned as true targets for one or more microRNAs. See for additional data files including a fully annotated outlier mRNA set, a list of all microRNA hits upon this set (extended with and without including G:U matches), and a list of the nonredundant microRNAs together with their putative mRNA targets. 4. Characterizing the mRNA outlier set The 71 mRNAs in the outlier set had a larger number of microRNA hits per kilobase of target sequence than did the scrambled sequences (2.18 ± 0.1 vs. 1.83 ± 0.085, p = 0.006). As well, individual microRNAs hit multiple (up to 17) distinct members of the outlier set, which again happened significantly more often than by chance (fig. 4 ). These findings indicate that the outlier mRNAs are different as a whole from the mRNAs that were hit by scrambled counterparts, even those that satisfied the same cut-off criteria. The outlier mRNA set contained very similar types of targets as predicted by previous computational studies [ 5 - 8 ], including members of the same gene families. For example, Lewis et al. [ 8 ] described E2F1 as a candidate target whereas we found E2F6 (Table 1 ). Transcription factors (including homeobox genes) and nucleic acid-binding proteins are among the top predicted microRNA targets. As well, many other functional categories are represented including kinases, receptors and other signal transduction proteins, membrane and cytokeletal proteins, and effectors of differentiation (Table 1 ). However, surprisingly, we found that the human candidate microRNA target list also had some features that differed significantly from the known targets in C. elegans and Drosophila . For example, there was no preference for microRNA hits to be located within 3'-untranslated regions: 5% of hits were located in the 5'-UTR, 1% at the 5'-UTR/coding junction, 67% in the protein coding region, 1% at the coding/3'-UTR junction, and only 26% in the 3'-UTR. This distribution was not significantly different from hits produced by the scrambled sequences. As well, the best microRNA hits upon candidate mRNA targets did not have relatively better target complementarity near their 5'-end: Only 13% of hits had ≥ 7 exact hit length starting at position 1 or 2 relative to the 5'end of the microRNA (vs. 17.5% of hits produced by scrambled sequences). MicroRNA 145 is particularly interesting because it hits 17 distinct targets on the candidate list, of which a disproportionate number (6) are in the signal transduction category and three of these are related to GTPase activation (Rho GTPase-activating protein (RICS), G protein gamma 7, and hypothetical protein FLJ32810 – containing RhoGAP and SH3 domains; Table 1 ). A recent study showing that miR-143 and miR-145 are both underexpressed in colorectal neoplasia [ 23 ] had previously proposed the first two of these candidates as potential targets. Interestingly, the third target found here is not only novel (XM_350859, RhoGAP-like) but is hit by both miR-143 and miR-145 in close proximity (see additional data file 2 in ), further suggesting that this is likely to be a true biological target for microRNA regulation. Discussion By comparing how the population of microRNAs vs. their scrambled counterparts interact with the population of human RefSeq mRNA sequences, we estimate that the probability of detecting a true microRNA target increases a) as the length of exact complementarity of a "hit" between microRNA and target increases, b) as the overall complementarity of a "hit" increases (allowing for gaps, mismatches and G:U matches), and c) as two or more distinct microRNAs hit the same mRNA in closer proximity. Targets in the outlier mRNA set also received more hits per unit length and more multiple hits from distinct microRNAs than expected by chance. Finally, we found cases in which an individual microRNA hit multiple mRNAs that belonged to the same functional class. The analysis suggests that target complementarity is a major factor in identifying biologically relevant mRNA targets: As values of each parameter increase, the difference between the number of hits in the microRNA set vs. the scrambled set increases steadily, and combining all three parameters gives better discrimination power than using any single feature. So far, these conclusions agree with five different papers that used computational approaches to predict microRNA targets in Drosophila [ 5 - 7 ], and mammals [ 8 , 9 ], using different strategies, criteria and filters than employed here. However, three significant differences were observed between human mRNAs in the outlier set and Drosophila targets: 1) Human microRNAs hit mRNAs with exact hit lengths extending much longer than observed in Drosophila , up to and including perfect complementarity. 2) Human microRNAs hit candidate mRNA targets within the protein coding region about 2/3 of the time. (This resembles the manner in which plant microRNAs hit their mRNA targets [ 10 , 11 ].) 3) The stretches of perfect complementarity within microRNA hits in the outlier mRNA set were not biased to occur near the 5'-end of the microRNA. This is not necessarily at odds with earlier analyses, since our outlier set includes only perfect stretches of 13 bases or more, and the 5' end may be more critical in those cases where only a short perfect stretch of complementarity exists. One might object that our ability to detect certain trends seen in Drosophila and C. elegans was simply obscured by the fact that we searched the large sequence space represented by all human mRNA sequences – the larger the sequence space, the greater the chance that any given target criterion will be satisfied by scrambled sequences, hence the more difficult it can be to detect true targets above the noise level. We agree that this can be a problem using very large sequence databases, such as the human EST database or the entire human genome. As well, using cut-off levels of parameter distributions to define the candidate list probably excludes many true human mRNA targets. However, human RefSeq was demonstrably not too large for our analysis, since very strong trends were observed in a variety of other parameters (figs. 1 , 2 , 3 , 4 ). Based upon sequence complementarity, at least 57 out of the 71 members of the outlier set are predicted to represent true microRNA targets (Table 1 ). Indeed, since this paper was first submitted for publication, one of the mRNAs on this list, HOXB8, has been experimentally confirmed [ 24 ]. Note, however, that accessory factors in the RISC might also help to determine which potential mRNA targets will actually be sites of regulation in vivo. As well, microRNA and target must be expressed in the same times and places in adequate concentrations; secondary structure of the mRNA target region may be important [ 19 , 20 ]; see also [ 8 ]; and RNA A-to-I editing [ 25 , 26 ] might operate to prevent certain target sequences from binding microRNAs adequately. Conclusions In summary, the population-wide characteristics of microRNA-mRNA sequence complementarity indicate that microRNAs recognize a subset of human mRNA sequences better than expected by chance. This outlier set does obey a number of properties expected for true biological mRNA targets, but does not show a bias for target regions to be located within the 3'-UTR of the mRNA, and stretches of perfect complementarity are not biased towards the 5'-end of the microRNA. If the candidate list is representative of the full set of biologically significant targets, then the total number of mRNA targets in humans may be much greater than previously proposed [ 8 ]. Abbreviations 5'-UTR, 5'-untranslated region. CDS, protein coding region. 3'-UTR, 3'-untranslated region. Methods MicroRNAs Statistical analyses were first carried out using the set of mouse and human microRNAs listed in Lagos-Quintana et al [ 15 ], and then repeated to obtain individual candidate mRNA targets using all human microRNAs listed on the Sanger microRNA repository [ 16 ] as of December 2003. These sources were combined to create nonredundant microRNA sets (i.e. microRNAs that have 10 or more consecutive nucleotides in common were collected into groups and the longest member of the group was chosen as nonredundant). Almost all mouse microRNAs have exact human counterparts, but hits were annotated with mouse entries in cases of minor corrections and discrepancies between these two sources. One individual microRNA (mir-207) and several scrambled sequences were found to be low-complexity or complementary to abundant repeats (e.g., Alu) and were removed from consideration. mRNAs Analyses were first carried out using the set of human RefSeq mRNAs available in August 2003, and then supplemented with additional human RefSeq mRNAs listed as of December 2003. A) Sequences in RefSeq > 20,000 bases long were removed from consideration because they were hit by many, if not all microRNAs, and a few sequences > 15,000 bases long were removed from the final candidate list because they had a relatively high false-positive probability. B) When counting the number of hits over the population of mRNAs, two hits were counted as redundant if the entire region around the hit (plus or minus 25 nucleotides on each side) was identical. C) When counting distinct hits by microRNAs on the same target, two hits were counted as redundant if they shared the same exact hit. This minimized possible artifacts due to overlapping microRNAs, as well as removed cases in which microRNAs hit exactly-repeating sequences within the target. D) In tabulating hits onto mRNA targets, we did not count hits that contained low-complexity sequences as detected by the DUST algorithm encoded by a Perl script provided by Lincoln Stein [ 27 ]. E) When assembling the candidate mRNA target list, we chose a single exemplary mRNA and removed other entries that were transcript variants or nearly identical by BLAST searching. In the course of this study, some of the target mRNAs were removed from RefSeq for routine genome annotation processing. If these were subsequently replaced with updated versions of these mRNAs in RefSeq that included the same hits, the latter version is listed here as well. For those entries removed but not replaced in RefSeq at the time of submission of the manuscript, other active entries currently in Genbank are listed if possible. Statistics To decide whether the number of observed microRNA hits were significantly different from chance, 10 replications of scrambled sequences were used to estimate prediction intervals. The prediction interval allows one to say with 95% confidence that any single new replication of the scrambled set will be below the value of the microRNA set. Prediction intervals were chosen as more conservative and more appropriate than confidence intervals. Authors' contributions NS contributed biological expertise, whereas VT contributed statistical and computational expertise. The analyses were carried out together, and both authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC523849.xml
385219	The Genetic Architecture of Parallel Armor Plate Reduction in Threespine Sticklebacks	How many genetic changes control the evolution of new traits in natural populations? Are the same genetic changes seen in cases of parallel evolution? Despite long-standing interest in these questions, they have been difficult to address, particularly in vertebrates. We have analyzed the genetic basis of natural variation in three different aspects of the skeletal armor of threespine sticklebacks (Gasterosteus aculeatus): the pattern, number, and size of the bony lateral plates. A few chromosomal regions can account for variation in all three aspects of the lateral plates, with one major locus contributing to most of the variation in lateral plate pattern and number. Genetic mapping and allelic complementation experiments show that the same major locus is responsible for the parallel evolution of armor plate reduction in two widely separated populations. These results suggest that a small number of genetic changes can produce major skeletal alterations in natural populations and that the same major locus is used repeatedly when similar traits evolve in different locations.	Introduction The number and type of genetic changes that control morphological and physiological changes during vertebrate evolution are not yet known. The evolutionary history of threespine sticklebacks (Gasterosteus aculeatus) provides an unusual opportunity to directly study the genetic architecture of adaptive divergence in natural populations. At the end of the last ice age, marine sticklebacks colonized newly formed freshwater environments throughout the Northern Hemisphere. Over the last 10,000 to 15,000 years, these fish have adapted to a wide range of new ecological conditions, giving rise to diverse populations with striking differences in morphology, physiology, and behavior ( Bell and Foster 1994 ). Major changes in the bony armor have evolved repeatedly in different locations, and several hypotheses have been proposed to explain this morphological transformation, including response to changes in calcium availability ( Giles 1983 ), stream gradients ( Baumgartner and Bell 1984 ), or temperature, salinity, or other factors that may vary in parallel with climate ( Heuts 1947 ; Hagen and Moodie 1982 ); or exposure to different types of predators ( Hagen and Gilbertson 1973a ; Moodie et al. 1973 ; Reimchen 1992 ; Reimchen 1995 ). Three distinctive patterns of body armor, now known as the “lateral plate morphs,” have been recognized as one of the most distinguishing characteristics in sticklebacks since at least the early 1800s ( Cuvier and Valenciennes 1829 ). Most marine sticklebacks have a continuous row of bony plates that covers the lateral side of the body from head to tail (the “complete morph”; see marine fish in Figure 1 ). In contrast, many freshwater sticklebacks show substantial reductions in total plate number, developing either as “partial morphs,” which lose plates in the middle of the row (not shown), or as “low morphs,” which retain only a few plates at the anterior end (see Paxton benthic and Friant California [lower animal] fish in Figure 1 ). The anterior plates present in low morphs are the first to form during larval development. In contrast, the middle plates absent in partial morphs are the last to form during normal development ( Igarashi 1964 ; Igarashi 1970 ; Bell 1981 ). Thus, the adult plate patterns of low and partial morphs resemble early developmental stages of plate patterns in complete morphs, and paedomorphosis has been proposed as a possible explanation for the repeated evolution of low and partial morphs from completely plated ancestors ( Bell 1981 ). Figure 1 Mapping the Genetic Basis of Lateral Plate Reduction in Different Natural Populations of Threespine Sticklebacks Crossing a completely plated Japanese marine fish with a low-plated fish from Paxton Lake, British Columbia, produced a mixture of complete, partial, and low morph phenotypes in F2 progeny animals (Cross 1). In contrast, crossing a completely plated fish and a low-plated fish from an inland freshwater stream in Friant, California, produced only complete and low-plated progeny (Cross 2). Red dots show the geographic origins of the populations studied. Scale bars equal 1 cm. AA , Aa , and aa refer to genotypes at Gac4174 (a microsatellite marker) near the major plate locus on LG 4. The genotype at Gac4174 is missing in ten of the 360 F2s in Cross 1. All fish were stained with alizarin red to reveal bony structures. This dramatic variation in lateral plate patterning has led to repeated efforts to determine the genetic basis of the major plate morphs. Previous studies have shown that plate morphs are reproducibly inherited in the laboratory and that crosses between different morphs generate relatively simple ratios of the three major phenotypes among the progeny. Based on these qualitative results, at least six different genetic models have been proposed for lateral plate patterns in sticklebacks. The simplest models proposed a single major locus with alternative alleles (A and a) ( Munzing 1959 ; Avise 1976 ). The A allele was first proposed to be incompletely dominant to the a allele, generating either complete (AA), partial (Aa), or low-plated (aa) fish ( Munzing 1959 ). In other populations, the A allele may be completely dominant to the a allele, producing either complete (AA, Aa) or low-plated (aa) fish, but no partials ( Avise 1976 ). More complicated models have proposed two major loci controlling plate inheritance (with alternative alleles A, a and B, b ). In one of these models, both major loci contribute equally to plate phenotype, and the total number of A and B alleles determines whether fish develop as complete (three or more A or B alleles), partial (two A or B alleles), or low-plated fish (one or less A or B allele) ( Hagen and Gilbertson 1973b ). Additional models have proposed either epistatic interactions between a single major locus and one modifier locus, or the presence of more than two alternative alleles at the major locus to account for variant results in some populations ( Ziuganov 1983 ; Banbura 1994 ). All of these models were proposed before the development of genomewide genetic markers for sticklebacks ( Peichel et al. 2001 ) and have never been tested by linkage mapping. In this study, we take advantage of these recently developed tools to examine the genetic basis of variation in lateral plate phenotypes in natural populations of sticklebacks. Results To directly analyze the number and location of genetic loci that control plate phenotypes, we crossed a completely plated marine fish with a low-plated benthic fish from Paxton Lake, British Columbia. Three hundred sixty progeny from a single F2 family (Cross 1) were examined in detail for the pattern, number, and size of lateral plates and then genotyped for the inheritance of different alleles at 160 polymorphic loci distributed across all linkage groups. The segregation of plate phenotypes was compared to the segregation of all genetic markers using quantitative trait loci (QTL) analysis (MapQTL; van Ooijen et al. 2002 ). Significance thresholds for detecting linkage were chosen using conservative criteria for genomewide linkage mapping in noninbred populations (log likelihood ratio [LOD] score ≥ 4.5; van Ooijen 1999 ). When plate morph was scored as a qualitative trait, a highly significant QTL on linkage group (LG) 4 was detected (LOD = 117; Table 1 and Figure 2 ). The genotype of the QTL on LG 4 was highly predictive of the major plate morph that developed in a fish. Almost all fish that carried two alleles from the complete morph grandparent in the LG 4 region (hereafter referred to as “AA” animals) showed the complete pattern, whereas fish that carried two alleles from the low morph grandparent in this region (hereafter referred to as “aa” animals) showed the low pattern. In contrast, most fish with one allele from the complete grandparent and one allele from the low grandparent (hereafter referred to as “Aa” animals) developed as either complete or partial fish (see Figure 1 ). Figure 2 Comparison of QTL Positions for Different Traits LOD scores are shown as a function of genetic distance along different stickleback linkage groups. QTL affecting qualitative plate pattern (red line), total plate number (black lines), or plate size (blue lines) show similar shapes on several linkage groups, suggesting that the same or linked genes control multiple aspects of plate phenotype. Points in LOD plots correspond to the following microsatellite markers from left to right along each linkage group: (A) LG 4: Pitx2 (Stn220), Stn38, Gac62, Stn42, Gac4174, Stn45, Stn183, Stn46, Stn47, Stn184, Stn39; (B) LG 7: Stn70, Stn72, Stn76, Stn71, Stn78, Stn79, Stn75, Stn81, Stn80 Stn82, Pitx1; (C) LG 10 : Stn119, Stn120, Stn211, Stn121, Stn124, Stn23, Stn125; (D) LG 25: Stn212, Stn213, Stn214, Stn215, Stn216, Gac1125, Stn217; (E) LG 26: Stn218, Stn219, Bmp6, Stn222, Stn223 . Note that markers Stn183 and Stn184 from LG 18 in the Priest Lake cross ( Peichel et al. 2001 ) map together with LG 4 markers in the larger Cross 1. Table 1 Summary of QTL Affecting Lateral Plate Phenotypes in Cross 1 All QTL that exceed the genomewide significance threshold (LOD ≥ 4.5) are shown with their respective LG, maximum LOD score, and PVE at the most closely linked microsatellite marker. Each trait was initially mapped in the large panel of F2 animals. Because plate number is dominated by the phenotypic effect of the major locus on LG 4, we have separately listed the phenotypic effects of the plate number modifier QTL within all major genotypic classes near the major locus ( AA , Aa , and aa animals). These results are shown even when they do not exceed the LOD ≥ 4.5 threshold, in order to facilitate comparison of the effects of significant modifiers in different genetic backgrounds. Mean plate number and size measurements were calculated for progeny that inherited either two marine alleles (MM) , one marine and one benthic allele (MB) , or two benthic alleles (BB) at the microsatellite most closely linked to each QTL. Plate number is the sum of plate counts on both sides of the body. Plate width and plate height were measured in millimeters at the positions indicated in Figure 2 , summed for both sides of the body, and standardized by overall body length and body depth, respectively. Statistical analysis was done using one-way ANOVA. significantly different from MM mean ( p < 0.05), *highly significantly different from MM mean ( p ≤ 0.0001), # significantly different from MB mean ( p < 0.05), ## highly significantly different from MB mean ( p ≤ 0.0001), “n/a” indicates “not applicable.” When total plate number was scored, the same major LG 4 chromosome region accounted for more than 75% of the total variance in plate number of F2 fish. Three additional QTL were detected that had significant effects on plate number in Aa animals ( Table 1 ; see Figure 2 ). Increasing the number of benthic alleles at any of the individual modifiers led to a reduction in mean total plate number, even in the heterozygous state ( Table 1 ). Increasing the number of benthic alleles at the three modifiers considered together caused a more than 2-fold reduction in mean plate number of Aa animals, largely accounting for whether Aa fish developed as either complete, partial, or low morphs ( Figure 3 A and 3 D). Increasing the number of benthic alleles at the same modifier loci also led to a 2-fold reduction in the mean plate number of aa animals but had relatively little effect on the plate number of AA animals ( Figure 3 B and 3 C). Taken together, these results suggest that at least four different loci influence lateral plate phenotypes in this cross. Homozygosity at the major locus largely determines whether fish develop as low (aa) or complete (AA) morphs, while the modifier loci affect the actual number of plates, particularly in Aa and aa animals. Figure 3 Cumulative Effects of Freshwater Alleles on the Number, Pattern, and Size of Lateral Plates in Cross 1 Increasing the total number of Paxton benthic freshwater alleles at modifier QTL on LGs 7, 10, and 26 significantly reduces plate number in animals with one marine (complete morph) and one Paxton benthic (low morph) allele near the major QTL on LG 4 ( Aa progeny) (A). The same modifier QTL have little effect on fish with two marine alleles near the major QTL ( AA animals) (B) and smaller phenotypic effects on animals with two benthic alleles near the major QTL ( aa animals) (C). Increasing the number of benthic alleles also significantly increases the proportion of Aa fish whose overall plate pattern is classified as partial instead of complete (D). (E–F) show plate size effects. Increasing the number of benthic alleles at plate size QTL on LGs 4, 7, and 25 significantly reduces mean plate width of F2 progeny (E). (F) shows the schema of plate size measurements. Lateral plates are shown numbered from anterior to posterior. Error bars in (A–E) represent standard error. The size of individual lateral plates varies significantly between different stickleback populations ( Miller and Hubbs 1969 ; Avise 1976 ). Although this trait has not been systematically analyzed in previous stickleback crosses, studies of meristic characters in other vertebrates suggest that the size and number of repeating skeletal elements can be controlled separately ( Christians et al. 2003 ). When height and width of specific plates were analyzed, we detected three QTL that accounted for a significant percentage of plate size variability in the cross ( Table 1 ; see Figure 2 ). Increasing the number of benthic alleles at these loci led to a progressive reduction in plate size ( Figure 3 E). Two of the three plate size QTL mapped to the same chromosome regions that also affected plate morph or plate number, suggesting that the pattern, number, and size of plates may be controlled by the same or linked genes on LGs 4 and 7 (see Figure 2 ). In contrast, the QTL affecting lateral plate size mapped to different locations than most QTL controlling the size of dorsal spine and pelvic structures ( Peichel et al. 2001 ; Shapiro et al. 2004 ), suggesting that the size of different bones are controlled separately in the stickleback skeleton. Some of the differences in previously published models of stickleback plate genetics could be due to different genetic mechanisms operating in different populations. To compare the genetic architecture of armor plate patterning in a separate population located over 1300 km from Paxton Lake, we crossed fish from an unusual stickleback population in Friant, California, which is largely dimorphic for complete and low fish with very few partials. A cross between a Friant complete and a Friant low-plated fish resulted in nearly equal numbers of complete and low progeny (see Figure 1 , Cross 2), consistent with previous crosses from this population ( Avise 1976 ). Genotyping studies with microsatellite markers linked to the major and minor QTL defined above showed very tight concordance between lateral plate phenotype and genotype near the same major locus on LG 4 that was seen in Cross 1 (LOD = 11.1). All fish with an inferred Aa genotype at the major locus on LG 4 were completely plated in this cross, suggesting that Aa fish develop more plates in Cross 2 than in Cross 1. This could be due to differences in the dominance relationship of the particular alleles at the LG 4 locus in the Friant population ( Avise 1976 ), or to modification of dominance by the different genetic backgrounds in the two crosses. Although the number of animals in Cross 2 was small, significant differences in the mean total plate count of low fish could also be detected in animals that inherited different alleles at microsatellites linked to two of the modifier QTL detected in Cross 1 (alternative alleles at Stn210 on LG 7: mean total plate counts 14.9 ± 0.31 vs. 14.0 ± 0.23, p = 0.0204; alternative alleles at Stn219 on LG 26: 14.8 ± 0.26 vs. 13.9 ± 0.31 plates, p = 0.0352). Overall, these results suggest that both plate morph and plate number are controlled by similar chromosome regions in different populations. To further test whether the same major locus on LG 4 controls armor plate reduction in both populations, we carried out genetic complementation crosses between two low female fish from Friant and one low male fish from Paxton Lake. All 84 progeny developed as low morphs, suggesting that the low-plated phenotype in both populations is likely to be due to the same major locus on LG 4. Discussion QTL Architecture This study reports the first genomewide linkage mapping of lateral plate phenotypes in crosses between major stickleback plate morphs. Our results confirm previous suggestions that dramatic changes in lateral plate patterning can be controlled by one locus of major effect ( Munzing 1959 ; Avise 1976 ). This major locus on LG 4 can cause a greater than 5-fold change in total plate number and is sufficient to switch the overall morphology of a fish between the complete, partial, and low-plated states. The dramatic phenotypic effects of this locus likely explain why three types of sticklebacks have long been recognized in natural populations ( Cuvier and Valenciennes 1829 ). Further molecular studies will be required to determine whether there are one or multiple mutations in the LG 4 region that account for the major QTL. Plate number within the complete, partial, and low morphs also varies between fish from different locations. Previous studies suggest that sticklebacks with small changes in plate number show differential survival when exposed to predators, suggesting that selection may fine tune the exact number of plates in different environments ( Hagen and Gilbertson 1973a ; Moodie et al. 1973 ; Reimchen 1992 ). We have identified three modifier QTL that cause changes in plate number within all morphs but are unlinked to the major locus. The individual phenotypic effects of these QTL can be as small as a single plate per side ( Table 1 ), while the combined mean effects of the QTL can be as large as 15 plates per side (see Figure 3 A). The number of modifier QTL is larger than predicted in previous models. We suspect that this is because of the general difficulty of predicting genetic architecture from simple phenotypic ratios of progeny in crosses that are segregating more than one or two genes. The magnitude of the phenotypic effects of the modifiers, their linkage relationships, and interactions with the major locus could not be predicted accurately from previous studies, highlighting the value of genomewide linkage mapping for studying the genetic architecture of major morphological variation in natural populations. Postglacial freshwater stickleback populations are thought to be derived from completely plated marine ancestors ( Bell and Foster 1994 ). At all of the plate QTL detected in Cross 1, the net effect of the freshwater alleles from the Paxton benthic grandparent is to cause a progressive reduction in the size or number of armor plates ( Table 1 ). All of the QTL that affect plate morph or plate number also have significant effects in the heterozygous state, showing that plate reduction is likely to evolve through semiadditive genetic changes, rather than through purely recessive or purely dominant mutations. Theoretical studies suggest that semiadditive mutations can be fixed more quickly than purely recessive or dominant mutations when they begin at low frequency, although the overall probability of fixation also depends on whether the mutations arise de novo or are originally present in a founder population ( Crow and Kimura 1970 ; Orr and Betancourt 2001 ). Strong selection on a small number of chromosome regions that have large, semiadditive effects may help explain how dramatic changes in lateral plate patterns have evolved relatively quickly in postglacial stickleback populations. Parallel Evolution Our mapping and complementation results suggest that the same major locus on LG 4 causes major changes in plate pattern in both the Paxton benthic and Friant populations. Phenotypic reduction of lateral plates almost certainly evolved separately in these different locations, given the geographic distance between them (over 1300 km), the presence of completely plated fish in the marine environment separating the sites, and previous studies showing that sticklebacks in nearby lakes have independent mitochondrial haplotypes ( Taylor and McPhail 1999 ). Additional complementation crosses between low-plated fish from Friant and other California populations ( Avise 1976 ; unpublished data), Paxton benthic fish and pelvic-reduced fish from Iceland ( Shapiro et al. 2004 ), and low-plated populations from British Columbia and Japan ( Schluter et al. 2004 ) also produce low-plated progeny. Thus genetic changes at the same major locus may underlie low-plated phenotypes at numerous locations around the world. The present study provides the first genetic mapping evidence that some of the chromosome regions controlling smaller quantitative variation in plate number may also be used repeatedly in different populations. The QTL on LG 26 in Cross 1 maps to a similar position as a QTL influencing plate number within low morph fish from Priest Lake, British Columbia ( Peichel et al. 2001 ). This QTL is also associated with significant variation in plate number of low morphs of the Friant population (Cross 2), suggesting that this chromosomal region on LG 26 contributes to plate number variation in at least three different populations: Paxton, Priest, and Friant sticklebacks. Recent studies suggest that the same genes are also used repeatedly when pigmentation and larval cuticle phenotypes have evolved in parallel in different fly populations ( Gompel and Carroll 2003 ; Sucena et al. 2003 ) or when melanism has evolved independently in birds and mammals (reviewed in Majerus and Mundy 2003 ). Repeated use of particular genes may thus be a common theme in parallel evolution of major morphological changes in natural populations of both invertebrates and vertebrates. Why might some genes be used preferentially when similar phenotypes evolve in parallel in wild populations? Alleles that cause plate reduction may already be present at low frequency in marine populations. In that case, parallel phenotypic evolution could occur by repeated selection for the same preexisting alleles in different freshwater locations. Alternatively, some genes may be particularly susceptible to de novo mutations, either because of the size or structure of coding and regulatory regions, or the presence of hotspots for recombination, insertion, or deletion. Finally, only a limited number of either old or new mutations may actually be capable of producing a specific phenotype without also causing deleterious effects on fitness. Mutations with the largest positive selection coefficients will be fixed most rapidly in evolving populations, and this may lead to parallel selection for mutations in the same genes in different populations. A major goal for future work will be to identify the actual genes and mutations that cause parallel evolution of adaptive traits in wild sticklebacks. This study identifies specific markers that are closely linked to chromosome regions that control the pattern, number, and size of lateral plates. With the recent development of BAC libraries and physical maps of the stickleback genome, it should be possible to use forward genetic approaches to identify the genes responsible for the repeated evolution of major morphological transformations in stickleback armor ( Kingsley et al. 2004 ). Cloning and sequencing of such genes will make it possible to determine the molecular mechanisms that underlie parallel evolution in natural populations and should provide new insight into the nature of genetic, genomic, developmental, and ecological constraints that operate as new characteristics appear during the adaptive evolution of vertebrates. Materials and Methods Fish crosses and husbandry For Cross 1, a wild-caught, completely plated marine female from Onnechikappu stream on the east coast of Hokkaido Island, Japan, was crossed to a wild-caught, low-plated benthic male from Paxton Lake, British Columbia. Both parents showed morphologies typical of the marine and benthic populations at their respective collecting sites. The specific populations were chosen because the large average body size of both parents and the estimated divergence between eastern and western Pacific Ocean fish ( Orti et al. 1994 ) were expected to help maximize the size of the progeny, the number of offspring per clutch, and the informativeness of microsatellites and other markers for genetic mapping. F1 progeny were raised to maturity in 30-gallon aquaria and were mated in pairs. Approximately 2600 F2 progeny were raised to a standard length of greater than 28 mm under the same conditions (30-gallon aquaria in a single 18°C room with 16 hours of light and eight hours of dark per day and twice daily feeding of brine shrimp or frozen blood worms). Although limited phenotypic plasticity has been reported for development of some trophic characters in sticklebacks ( Day et al. 1994 ), previous studies have shown that differences in plate number of wild-caught sticklebacks are stable and reproducible when fish are raised under laboratory conditions (see, for example, Hagen 1967 ). A total of 360 full siblings from a single F2 family were used for genotypic and phenotypic analysis in this study. For Cross 2, one wild-caught, completely plated female from Friant, California, was crossed to one wild-caught, low-plated male from Friant, California. A total of 58 F1 progeny were raised to a standard length of greater than 28 mm in a ZMOD (Marine Biotech, Beverly, Massachusetts, United States). For the complementation cross, two wild-caught, low-plated females from Friant were crossed to one wild-caught, low-plated benthic male from Paxton Lake, British Columbia. At total of 84 F1 progeny were raised to a standard length of greater than 28 mm in 30-gallon aquaria. Genotyping Genotyping of microsatellite markers was performed and analyzed essentially as described in Peichel et al. (2001) . Some PCR products were analyzed on a 48-capillary array on an ABI3730xl with GeneMapper v3.0 software and GeneScan 500 LIZ (Applied Biosystems, Foster City, California, United States) used as an internal size standard. A total of 160 markers were analyzed in Cross 1, including 144 previously described microsatellite markers ( Peichel et al. 2001 ), the genes Pitx1 , Pitx2 (Stn220), and Tbx4 (Stn221), ( Shapiro et al. 2004 ) and 13 new markers: Bmp6 gene and 12 additional microsatellites (Stn210–219, 222–223). A polymorphism within the 3′ UTR of the Bmp6 gene was genotyped using single strand conformation polymorphism analysis with MDE Gel Solution (BioWhittaker Molecular Applications, Rockland, Maine, United States). PCR bands were visualized using autoradiography. PCR conditions were the same as for the microsatellite markers except 2.5 mM MgCl 2 and 10% DMSO were used. Primers for Bmp6 genotyping are: Bmp6F1: 5′ CCCGGTTT AA ATCCTCATCC and Bmp6R1: 5′ AGGAGGTGATTGACAGCTCG. Morphological analysis and QTL mapping Fish were stained with alizarin red to detect skeletal structures as described in Peichel et al. (2001) . Lateral plates were counted on both sides of each fish. For QTL mapping, the total plate number of both sides was used. Plate width was measured on the first lateral plate located under the first dorsal spine and above the ascending process of the pelvis. Plate height was measured on the lateral plate posterior to the last plate that is under the second dorsal spine and touching the ascending process. These correspond to plate positions 5 and 8 in previous nomenclature ( Reimchen 1983 ). All measurements were done with Vernier calipers accurate to 0.02 mm and had repeatabilities of 1.1% ± 0.9% (SD)(plate width) and 3.9% ± 2.9% (SD)(plate height). Plate width and height measurements on both sides of the body were summed and standardized by body length and depth, respectively. Similar QTL were detected when residuals from regressions of plate width and height on standard body length and depth were mapped. When raw plate width and height measurements were used, we also detected one additional significant QTL on LG 19 (plate width: LG 19, LOD = 5.42, 7.3 percent variance explained [PVE]; plate height: LG 19, LOD = 7.3, 11.6 PVE). Standard body length itself maps to LG 19 (LOD = 10, 13 PVE). The LG 19 effect on plate size is not significant when plate measurements are normalized by standard body length, suggesting that the LG 19 QTL is a general body size QTL, while the other size QTLs ( Table 1 ; see Figure 2 ) act on plate size separately from total body size. All morphological traits in Cross 1 were analyzed with MapQTL 4.0 ( van Ooijen et al. 2002 ) using the same parameters as described by Peichel et al. (2001) . Microsatellite markers that were closely linked to QTL detected in Cross 1 were genotyped in all Cross 2 animals ( Gac4174, Stn40, and Stn47 on LG 4; Stn210, Stn71, and Stn76 on LG 7; Stn211 and Stn121 on LG 10; and Stn218, Stn219, and Stn222 on LG 26). LOD scores between LG 4 markers and the major plate locus in Cross 2 were calculated using Map Manager v2.6.6 ( Manly 1993 ). Mean total plate numbers in low-plated fish that inherited different alleles at microsatellite loci on LGs 4, 7, 10, and 26 were compared using one-way ANOVA (Statview v5.0.1, SAS Institute Inc., Cary, North Carolina, United States). Supporting Information The GenBank accession numbers for the Bmp6 gene is AY547294 and for the 12 additional new microsatellites Stn 210–219, 222–223 are BV102488–BV102499.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC385219.xml
550657	Integrating alternative splicing detection into gene prediction	Background Alternative splicing (AS) is now considered as a major actor in transcriptome/proteome diversity and it cannot be neglected in the annotation process of a new genome. Despite considerable progresses in term of accuracy in computational gene prediction, the ability to reliably predict AS variants when there is local experimental evidence of it remains an open challenge for gene finders. Results We have used a new integrative approach that allows to incorporate AS detection into ab initio gene prediction. This method relies on the analysis of genomically aligned transcript sequences (ESTs and/or cDNAs), and has been implemented in the dynamic programming algorithm of the graph-based gene finder EuGÈNE. Given a genomic sequence and a set of aligned transcripts, this new version identifies the set of transcripts carrying evidence of alternative splicing events, and provides, in addition to the classical optimal gene prediction, alternative optimal predictions (among those which are consistent with the AS events detected). This allows for multiple annotations of a single gene in a way such that each predicted variant is supported by a transcript evidence (but not necessarily with a full-length coverage). Conclusions This automatic combination of experimental data analysis and ab initio gene finding offers an ideal integration of alternatively spliced gene prediction inside a single annotation pipeline.	Background Alternative splicing (AS) is a biological process that occurs during the maturation step of a pre-mRNA, allowing the production of different mature mRNA variants from a unique transcription unit. AS is known to play a key role in the regulation of gene expression and transcriptome/proteome diversity [ 1 ]. First considered as an exceptional event, AS is now thought to involve the majority of the human multi-exon genes, from 50% to 74% [ 1 - 3 ]. This observation raises new issues for genome annotation, especially concerning the computational gene finding process that generally provides only one exon-intron structure per sequence. In the context of structural gene prediction, two classes of approaches are usually considered. In the first approach, usually denoted as intrinsic or ab initio , the only type of information used for gene prediction lies in the statistical properties of the various gene elements (exons, splice sites and other biological signals). On the contrary, so-called extrinsic approaches essentially rely on the existence of similarities between the sequence to annotate and other known sequences (either proteins, transcripts or other genomic sequences). Several existing gene finding tools are essentially intrinsic (or ab initio ): this is the case for Genscan [ 4 ], HMMgene [ 5 ] or SLAM [ 6 ]. For such a gene finder, the predicted gene structure is defined as an optimal prediction, that is the most probable according to its underlying probabilistic model. In the presence of AS however, a unique prediction is not sufficient. One obvious possibility is to look for suboptimal predictions. This can be done for a classic HMM-based gene finder by a modification of the Viterbi algorithm, thus providing the set of the k best predictions. This approach has been applied eg . in HMMgene or in FGENES-M (unpub.). Another way to obtain suboptimal solutions from a HMM is to do HMM sampling [ 7 ]. This method, which consists in randomly generating parses according to the posterior probabilities, has been implemented in the gene finder SLAM. Usually, a very large amount of samples are needed to generate just a single prediction that differs from the optimal one. Genscan adopt a different approach and search for alternative exons not represented in the optimal prediction. This is done using a forward-backward algorithm to identify potential exons for which the a posteriori likelihood is larger than a given threshold. In addition to the fact that all these exclusively intrinsic approaches cannot take into account transcript evidences, they suffer from two major problems of sensibility and specificity: First of all, these methods assume that predictions representing AS variants should have a probability which is very close to the optimal probability according to the underlying gene model. This is however quite arguable, especially when the alternative structure significantly differs from the optimal one. Actually, when an AS variant eg . shifts from a strong to a weak or a non-consensus splice site or shows a complete coding exon skipping event, it is quite unlikely that the probability will remain in the neighborhood of the optimum since it will not be able to incorporate the corresponding splicing or coding score. Moreover, a strong specificity problem has been observed for this approach. Since a very large number of alternative predictions can always be produced for any sequence, it is essential to be able to distinguish those reflecting real AS variants from in silico false positives. To perform this, and as long as AS sites dedicated prediction tools are unavailable, the probability of a prediction alone cannot be sufficient and additional evidence is required. In opposition to the purely intrinsic approach, the analysis of experimental data can provide useful information. More specifically, sequences of mature transcripts resulting from AS provide reliable evidence of the existence of the AS event. Large scale studies have already been undertaken to detect AS evidences from transcript alignments and to collect them in databases such as eg . HASDB [ 8 ], ASDB [ 9 ], ASAP [ 10 ], ASD [ 11 ], EASED [ 12 ] or ProSplicer [ 13 ]. Some software tools have also been designed to perform and/or exploit transcript alignment with the aim of identifying alternative gene structures. Such extrinsic annotation tools include GeneSeqer [ 14 ], ASPic [ 15 ], TAP [ 16 , 17 ], and PASA [ 18 ]. Except for GeneSeqer which is more focused on performing spliced alignment, the three other software adopt the same strategy: using genomically aligned transcripts, the aim is to determine the exon-intron structure(s) compatible with the greatest number of transcripts. Another approach, Cluster Merge [ 19 ], has been recently used in the Ensembl annotation system [ 20 ] to identify minimal sets of transcript variants compatible with genomically aligned ESTs evidences. Unlike intrinsic methods, extrinsic approaches take advantage of transcript information. However, they also suffer from some limitations : first they entirely depend on the availability of transcribed sequences which bounds their sensitivity. With little exceptions (like TAP that exploits genomic sequence properties to identify gene boundaries, including eg . a polyA site scanning step, or GeneSeqer, that contains an intrinsic splice sites scoring method), they cannot predict a splice site if it is not represented in a transcript-to-genome alignment and therefore require a total coverage of each gene with all exon-intron boundaries. This can be problematic considering the ESTs fragmented nature. Moreover, when such methods can take advantage of a total gene coverage, the CDS localization remains to be done and the pure transcript predictions may not respect elementary coding gene properties (such as the presence of an ORF w.r.t. a given frame). Furthermore, overlapping transcripts are sometimes assumed to come from the same mature mRNA and are therefore merged. This may lead to the fusion of two overlapping transcripts coming from exclusive inconsistent mRNA variants, thus forcing the prediction to respect a chimeric virtual assembly. Finally, and because experimental transcripts cannot exist for every existing gene, both intrinsic and extrinsic information are needed inside an annotation pipeline [ 20 ]. The predictions provided by two different approaches can be different and even inconsistent, and merging them together requires a careful inspection of human curators, as performed in [ 18 ]. A fully integrative method alleviates all these problems. GrailEXP [ 21 ] seems to be the only gene finder that tried to go in this direction. However, it can only consider AS events leading to complete exon inclusion/retention, ignoring thus approximatively half of the AS cases [ 8 , 18 ]. The underlying approach remains unpublished. To extend the domain of application of gene prediction to alternatively spliced gene structure prediction, we have designed an intrinsic/extrinsic integrative annotation method with the following aims: • For a given genomic sequence, an optimal gene structure prediction is produced, as usual. • In addition to this optimal prediction, for every transcript sequence providing evidence of AS, an optimal prediction consistent with this splicing form is also provided. • Each additional or alternative gene structure prediction has to be supported by some biological evidence. • Full-length transcript coverage is not required for a complete gene structure identification. • Each prediction satisfies the usual constraints on gene structure. A correct proteic coding gene is defined by a succession of one or more exons separated by introns flanked by splice sites. It contains a CDS between a start and a stop codon, and no in-frame stop in coding exons. Our aim is to combine the advantages of the intrinsic and extrinsic approaches in an integrative system allowing for AS detection based on the analysis of genomic aligned transcript sequences. The method has been implemented inside EuGÈNE-M, a new version of the Arabidopsis thaliana EuGÈNE gene finder [ 22 , 23 ], and applied to a reference genes set. Results To evaluate the interest of EuGÈNE-M compared to existing transcripts-based approaches, we applied it on the spl7 Arabidopsis thaliana gene. This gene codes for the squamosa promoter-binding protein-like 7, has 10 exons and two known alternative mature mRNA variants, both supported by a distinct full-length cDNA (accession AY063815 and AF367355, Figure 1 ). The genomic alignments of these cDNAs provide two correct and reliable gene structures used as reference annotations. The structures differ only by the 3' extremity of the 9th exon. However, beyond these 2 complete cDNAs, only the first and the two last exons are covered by ESTs. This partial EST coverage configuration is interesting because without the full-length cDNAs (unavailable in dbEST), finding a correct gene structure with pure extrinsic assembly tools would not be possible. Given only the genomically ESTs alignments, we applied EuGÈNE-M on the genomic sequence containing the spl7 gene. Since two ESTs (T04465 and AI995153) show incompatible alignments (see Methods), EuGÈNE-M computes two additional predictions, each being consistent with one of them. The first alternative prediction is the same as the optimal one and corresponds to one variant; the second corresponds to the other variant. For a more extensive test, we applied EuGÈNE-M on AraSet [ 24 ], a data set of Arabidopsis thaliana curated genes recently used in the assessment of GeneSeqer [ 25 ]. Since EuGÈNE has already been evaluated on this benchmark set, performing as one of the most accurate gene finder [ 22 ], the aim of this test is to provide an estimation of an alternatively spliced genes ratio on a reference set. Predictions are available in the additional files. On the 168 AraSet reference genes, 9 show at least two alternative predictions , that were carefully analyzed. This is summarized in Table 1 . All these predictions but two correspond to potential alternative splicing events. Among the two remaining ones, a first predicted AS event corresponds to an incompatibility caused by an apparently incompletely spliced EST. The other is more interesting since it is caused by two ESTs from two different genes lying on opposite strands and overlapping on their 3' ends. In this case, EuGÈNE-M is forced to predict two overlapping genes, one on each strand, which effectively address the usual impossibility for existing gene models to predict overlapping genes. Of course, these predictions, as all in silico expertise, require experimental verifications to be confirmed. If we assume the 7 remaining genes are effectively subject to AS, this yield to an AS rate of ~4.2%, a ratio in the same order as previously estimated, from 1.5% [ 26 ] to 6.5% (computed from [ 18 ]). Discussion In the recent assessment of GeneSeqer on this AraSet data set, only three AS cases were reported [ 25 ]. However, the authors only reported AS cases that were detected in GeneSeqer high-quality alignments and producing introns differing from the AraSet annotated introns. We therefore verified that our alignments were consistent with the GeneSeqer assessment alignment data available in the Arabidopsis thaliana Genome Database AtGDB [ 27 , 28 ]. We noticed an alignment difference for only one of our alternative EST (CF652136), not present in the AtGDB because of its dbEST entry date (Oct. 2003). We also checked if the AS variants predicted by EuGÈNE-M were already reported in the AS sections of the AtGDB [ 26 , 29 ] and of the TIGRdb [ 18 , 30 ]. Only 3 of our detected AS predictions were already reported in both databases, and 3 were missing in all of them (Table 1 ), confirming that this methodology can help to automatically discover new potential AS cases, even on a well studied dataset. The analysis of these AS cases confirms that AS seems to be much less frequent in A. thaliana than in Homo sapiens . Nevertheless, this AS ratio estimation is expected to increase in the future with the growth of transcript data availability. Another interesting point is the nature of the variants: on this gene set, the majority of AS cases involves a simple acceptor or donor alternative splice site. Notice however that since EuGÈNE-M's underlying model allows arbitrary alternative gene structure to be predicted, it is not limited to the prediction of such simple AS events and can perfectly cope with complex AS events, as found in mammals. This methodology can also be integrated in other existing gene finders where the score of a gene structure is defined as the sum of elementary scores of the signals and nucleotides involved in the gene structure (this includes HMM-based gene finders). Conclusions In this paper we have presented a new method to deal with alternative splicing in annotation and gene prediction. This integrative approach combines the advantages of an intrinsic and an extrinsic process to incorporate AS detection into ab initio gene finding. We showed that this method allows the discovery of new alternative spliced genes, with the reliability of extrinsic annotation and the potential exhaustiveness of ab initio gene prediction. Methods The process that goes from the original genomic sequence and associated aligned transcripts to the AS prediction is composed of three steps which we rapidly describe here : • first, the set of genomically aligned transcripts is analysed to detect AS evidences on the basis of splicing inconsistency between transcripts variants. • Then, the graph-model used in EuGÈNE to model potential gene structures is modified to take into account these aligned transcripts. For each transcript variant, the graph used in EuGÈNE for gene structure prediction is connected to an additional parallel graph subunit where local constraints are injected according to the exon-intron information provided by the corresponding transcript alignment. • Finally, an extended version of the dynamic programming algorithm used for obtaining an optimal prediction allows to identify, for each graph subunit, the best prediction consistent with the corresponding transcript alignment. Detection of AS evidences from transcripts analysis Since EuGÈNE already exploits transcripts information to improve the gene prediction process [ 22 ], the AS prediction only requires to consider transcripts providing evidence of AS. With this purpose, we focus on inconsistencies between transcript alignments. Transcript sequences are first aligned against the genomic sequence using a spliced alignment tool. The choice of the source transcript database and the alignment tool is not a priori imposed by the method. Transcript sequences in our analysis were extracted from the A. thaliana section of dbEST [ 31 ] (release Dec. 2003: 190, 708 entries), and aligned in two steps. For the first step we used sim4 [ 32 ], a fast software that can deal with huge EST datasets. In the second step, we used GeneSeqer [ 14 ], usually more accurate on splice junction identification, to realign all transcripts aligned by sim4 that passed the following filtering process. A first filtering step is performed on the basis of the transcript sequence and alignment quality. To be considered, an alignment has to satisfy some constraints defined by filtering parameters. For Arabidopsis thaliana , default parameters values are set as following: transcript length between 30 and 10000 bp, minimum alignment length = 95% of the transcript length, minimum identity score of 97%, maximum gap length of 5000 bp, maximum match length of 4000 bp. By default, and to avoid genomic contamination, unspliced transcripts are removed from the analysis. Moreover, because of the frequent weak alignment quality at the terminal regions, alignments extremities are shortened (by 15 bp by default). The second filtering step depends on the relation between transcript alignments. To detect AS evidences, every pair of overlapping transcript alignments is analyzed. We consider two special types of pairwise relation : a transcript alignment A is labeled as included in B if and only if for each genomic position of A the same genomic position in B shares the same alignment information (either gap or match). Every transcript included in another transcript is ignored by default. Transcript alignments A and B are labeled as incompatible if and only if there is a genomic position for which both ESTs are informative and give an inconsistent information, that is a gap (representative of the presence of an intron) is faced with a match (representative of the presence of an exon, coding or not). Examples of incompatible ESTs are displayed in Figure 1 and 5 . Since we focus on AS evidences, we only keep transcripts labeled as incompatible after all pairwise comparisons. Considering orientation of ESTs, the information on the clone-sequencing orientation that can be found with ESTs is totally ignored in this filtering process because of its unreliability. In practice, spliced EST can be reliably oriented by looking for splice sites on the hit-match frontier of the EST alignments and by choosing the strand for which such splice sites exist. The parameters of these two automatic filtering steps can be modified by the user through a simple text file. We will denote the resulting transcript alignments kept as alternative transcripts . The gene-finder EuGène General description EuGÈNE is a gene finding software based on a directed acyclic graph gene model [ 22 ]. For each nucleotide of the genomic sequence, every possible annotation of this nucleotide is represented in the graph. The graph is designed to model the whole prediction space: all consistent gene structures can be represented by a path through the graph, whose weight is defined as the sum of its edges weights. The minimum weight path defines the optimal prediction. Several sources of evidence are used to weight the edges of the graph and a shortest-path dynamic programming algorithm (linear in time and space) scans the graph to provide an optimal path which represents the best gene prediction according to available evidences. Structure of the initial graph Each path through the graph represents a potential gene structure prediction for the genomic sequence (Figure 2 ). The graph is composed of k tracks that represent the possible annotations that can be attributed to each nucleotide (coding, intronic, intergenic and UTR, with specific strand and frame). Let ℓ be the genomic sequence length. For a given nucleotide's position i with (1 < i < ℓ) and for each track j with (1 < j < k ) the two flanking vertices and are defined. Two edges are also built : a contents edge linking to and a transition edge linking to (Figure 3 ). Additional transition edges are put from to all according to the occurrence of a potential biological signal allowing a switch from state j for the nucleotide at the position i to the state j ' for the following nucleotide. For example, on the position i before the occurrence of an ATG, a transition edge linking to (where j corresponds to the UTR5' track and j ' is the coding exon track on the appropriate frame) is present, as illustrated in Figure 3 . Two special vertices and are added at the extremities of the graph. They are respectively connected to all and all . Initially, all edges are oriented from left (5') to right (3'). It is easy to see that all possible gene structure can be represented by a path from to . Weighting the graph The weight of a path is the sum of all the weights of the edges in the path. The edges are weighted according to the evidences used. EuGÈNE can combine several sources of evidence such as probabilistic coding models, output of splice site or start codon prediction software and sequence similarities with transcripts, proteins, or other genomic sequences [ 33 ]. Contents and transition edges c and t are penalized respectively by weights Wc and Wt according to a weighting function characterized by parameters specifically set for the corresponding source of evidence. The set of parameters is optimized on a learning dataset by maximizing the overall accuracy of the software. For more information about the weighting methods, please refer to [ 22 ]. Example of transcript alignment integration A transcript-to-genome alignment can easily be taken into account by weighting the appropriate edges of the graph. To favor a gene prediction in the alignment region, the intergenic track edges included in this region can be penalized by increasing their weight. More finely, the exon and the intron tracks edges can also be penalized at all positions involved respectively in a gap and in a match in the alignment. Thus, all gene structure prediction inconsistent with the transcript alignment information tends to be penalized. More drastically, it is possible to force the prediction to be consistent with the alignment by applying infinite penalty weights. Note that there are several such predictions since the start codon used is unknown and the transcript may be incomplete. Initial algorithm To identify the optimal path defined by the lowest weight, EuGÈNE uses a dynamic programming algorithm inspired from Bellman's shortest-path algorithm [ 34 ], also used for HMM in its Viterbi's version. Improvements of this algorithm allow EuGÈNE to take into account constraints on gene element lengths. For simplicity, we will not describe these sophistications in this paper. The algorithm of EuGÈNE associates to each vertex a variable which contains the weight of the optimal path from to and a variable which contains the vertex that precedes in this optimal path. The weight of this path can be computed recursively from 5' to 3' as: A short example is displayed in Figure 3 . The vertex that minimizes this value provides the previous . At vertex , the best path is retrieved by a simple backtracing procedure through all π . This algorithm is linear in time and space in the length of the sequence ( O (ℓ) complexity). It is important to note that the same algorithm can be used in a backward version (from to ), by computing at each vertex the weight of the best path from to as . AS evidences integration Given an alternative transcript genomic alignment, any prediction which is optimal among all the predictions that are consistent with the alignment evidence will be called an alternative prediction . Given the set of the previously detected alternative transcripts , we want EuGÈNE-M to produce a set of alternative predictions such that every alternative transcript has a corresponding prediction in this set. A simple way to produce such an alternative prediction would be to inject the exon-intron structure information given by the transcript alignment into the graph as described above (using infinite weights to force the prediction to strictly respect the alignment evidence), and then to execute EuGÈNE on the resulting graph. However, obtaining all alternative predictions would require one execution for each alternative transcript . n being the number of transcripts and l the genomic sequence length, this would result in a O ( ln ) time complexity, which is not appropriate for long genomic sequences and numerous transcripts. Hopefully, this complexity can be drastically reduced. The general idea to achieve a realistic complexity is to duplicate the subsection of the graph region involved in an alignment to create a so called local "Parallel Graph Subunit" (PGS), connected to the main graph at its extremities. Each alignment information is taken into account as constraints in the corresponding PGS, in such a way that finding the optimal path going through the PGS provides a corresponding optimal alternative prediction. Extending the graph model with PGS For a transcript alignment that extends from position g to h on the genomic sequence, the entire subsection of the graph between g and h is duplicated to create a Parallel Graph Subunit (PGS) (Figure 4 ). This PGS is connected to the main graph at its extremities by special so-called deviation edges. For each track j , a deviation edge links the source vertex in the main graph to its copy at the PGS left extremity, and another connects the source vertex in the main graph to its copy at the PGS right extremity. The deviation edges are all oriented from the main graph to the PGS. The weights of the PGS edges, initially identical to the weight of the original edges, are modified according to the corresponding transcript alignment : gaps and matches forbid respectively the exonic and the intronic tracks, and the entire PGS intergenic track is forbidden. Finding alternative predictions The modified algorithm proceeds in two steps. A first scan starts from to and applies the recursive formula described above to compute all , branching into each PGS (Figure 5 ). Thus, at each nucleotide's position and for each track (including those in the PGS), the weight of the optimal path from the left extremity is identified. At , the optimal path is obtained by backtracing. Furthermore, for any given PGS, the cost of an optimal path going from , through the PGS and then to each of the righmost vertices is known. Then all edges (except the deviation) are reversed, and the backward version of the same shortest-path algorithm is used from to to compute all . This step ignores the PGS. For a given PGS A , if we now consider the vertices at the rightmost extremity of A , then the weight of an optimal path that goes from to through A can be computed as . From the given vertex, backtracing in both directions provides an optimal path that represents an optimal prediction in accordance with the transcript alignment evidence. Output Predictions are produced in the standard GFF format. The entire optimal annotation is first displayed, followed by the alternative ones. To enhance the readability and to avoid redundancy, for each alternative prediction the name of the corresponding transcript is mentioned and the region that differs from the optimal prediction is displayed. Besides, if several predictions are identical (regarding their predicted CDS only, UTR length differences being ignored), a single representative is displayed, along with the list of its associated transcripts. Computation time The initial filtering and incompatible transcripts identification requires O ( n 2 ) pairwise comparisons. Each comparison is itself linear in the maximum number of introns in the transcript compared, which is typically bounded by a small constant and the whole process is therefore in O ( n 2 ). The step that corresponds to the two dynamic programming scans (application of the recursive formula) requires a time and space complexity which is linear in the size of the input data. Indeed, if L is the total nucleic sequences length (genomic + kept alternative transcript ), the weights of all (alternative and optimal) predictions can be computed in O ( L ). For the backtracing and output step, since each alternative prediction has to be displayed in the region where it differs from the optimal one, and because this can extend beyond the alignment region, it is not possible to obtain an algorithm which is linear in the size of the input. However, it is possible to reach a linear complexity in the size of the output. This can be done by a simple modification of the standard backtracing procedure to avoid a full backtrace for each prediction. This is yet not implemented in the current version of the software. A typical run of EuGÈNE-M on an AMD Athlon 1.7 GHz takes 47 sec. for a 500 kb BAC (for which 945 transcript alignments were kept after the first quality filtering step). Authors' contributions SF designed and implemented the filtering algorithm as well as the double dynamic programming algorithm for AS prediction. He also ran the experiments on the Araset dataset. TS directed the research. All authors read and approved the final manuscript. Supplementary Material Additional File 1 EuGène's predictions on AraSet . The additional file (SupplementaryFiles.tar.gz) contains gene structure predictions in the standard GFF text format for every AraSet sequence. ESTs detected as Incompatible by the method are displayed at the top of each prediction (if any). Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC550657.xml
544187	A new mixture model approach to analyzing allelic-loss data using Bayes factors	Background Allelic-loss studies record data on the loss of genetic material in tumor tissue relative to normal tissue at various loci along the genome. As the deletion of a tumor suppressor gene can lead to tumor development, one objective of these studies is to determine which, if any, chromosome arms harbor tumor suppressor genes. Results We propose a large class of mixture models for describing the data, and we suggest using Bayes factors to select a reasonable model from the class in order to classify the chromosome arms. Bayes factors are especially useful in the case of testing that the number of components in a mixture model is n 0 versus n 1 . In these cases, frequentist test statistics based on the likelihood ratio statistic have unknown distributions and are therefore not applicable. Our simulation study shows that Bayes factors favor the right model most of the time when tumor suppressor genes are present. When no tumor suppressor genes are present and background allelic-loss varies, the Bayes factors are often inconclusive, although this results in a markedly reduced false-positive rate compared to that of standard frequentist approaches. Application of our methods to three data sets of esophageal adenocarcinomas yields interesting differences from those results previously published. Conclusions Our results indicate that Bayes factors are useful for analyzing allelic-loss data.	Background Allelic-loss data The goal of studies of allelic loss is to determine those loci in tumor tissue where genetic material has been lost. A tumor suppressor gene (TSG) is much more likely to lie on a chromosome arm where there has been significant allelic loss than elsewhere [ 1 , 2 ]. The statistical challenge lies in distinguishing between "random" allelic loss that is expected in a tumor cell population and "nonrandom" loss that may be biologically meaningful. This corresponds to determining whether there is one group of arms with background allelic loss versus two groups of arms, one with background loss rates and one with elevated loss rates. Three allelic-loss data sets on esophageal adenocarcinomas Esophageal adenocarcinoma is a form of cancer involving the cells along the lining of the esophagus. The cause of esophageal adenocarcinoma is not well understood. The incidence of this cancer has been increasing rapidly. In fact, it is one of the fastest growing cancers in the United States over the past 20 years [ 1 , 3 , 4 ]. A strong association has been established between the pre-malignant condition known as Barretts esophagus and the development of adenocarcinomas of the esophagus. Barretts esophagus is a condition that develops in 10–20% of patients with chronic gastroesophageal reflux disease. The condition is characterized by the metaplastic change from normal squamous to columnar epithelium in the esophagus [ 1 , 4 ]. Approximately 1% of patients with Barretts esophagus progress to esophageal cancer [ 3 ]. Of those who develop the cancer about 90% will die as a result of the disease [ 1 ]. We examine three data sets of allelic-loss on esophageal adenocarcinomas that attempt to identify the tumor suppressor genes (TSGs) involved in the development of this disease. These data sets have been previously analyzed and published. We refer to each data set by the last name of the first author of the publication. Some of the data sets record allelic loss on multiple loci per chromosome arm for some of the arms. However, because the number of loci evaluated per chromosome arm is not random (i.e., chromosome arms suspected of harboring a TSG will be assessed at more loci than others), we consider only one locus per chromosome arm. In these cases, we choose data from the most informative locus for that chromosome arm. Our approach Our general approach to analyzing allelic-loss data can be described in two main steps. The first step is to choose an appropriate model for the data using Bayes factors. The second step is to classify the chromosome arms as harboring TSGs or not according to the selected model. The details involved in these two steps are described below. Results and Discussion Proposed class of models A natural way to model allelic-loss data is in terms of a mixture of two distributions: one distribution corresponds to chromosome arms that harbor TSGs and the other corresponds to arms that do not. It is reasonable to expect considerable variability in the loss rates of arms that harbor TSGs due to the existence of multiple pathways leading to the same tumor type [ 5 ]. For example, deletion of a particular TSG may be in the causal pathway for 60% of tumors of a particular type while another TSG (or other TSGs) may account for the remaining 40% of the cases. In addition, it is conceivable that various factors play a role in background loss rates. For example, factors such as cell viability, fragility of the chromosome arm, and the length of telomeres are believed to influence background loss rates [ 6 ]. It is plausible that the non-TSG loci that contribute to the background loss rate are in fact composed of two biologically different groups of loci. This group includes loci that are essential for cell viability and those that are not essential. The essential loci would be expected to exhibit loss rates considerably lower than that of the non-essential loci as their function controls the cell's survival. We propose a class of mixture models that account for the variation inherent in this type of data. Specifically, the class of models we propose is a mixture of two beta-binomial distributions. Let X i be the number of tumors with allelic-loss for the i th chromosome arm, and let n i be the number of informative tumors for the i th chromosome arm, for i = 1, 2,..., N , where N is the number of chromosome arms in the study. The density function for X i is written as follows: where θ ≡ ( η , π 1 , ω 1 , π 0 , ω 0 ) is a vector of unknown parameters, η is the mixing probability, π j is the average loss rate, and ω j is the dispersion parameter for j = 0,1. The distribution converges to a mixture of two binomial distributions as both dispersion parameters go to 0 ( ω 0 → 0 and ω 1 → 0). If only one of the dispersion parameters goes to 0 ( ω 0 → 0 or ω 1 → 0), the distribution reduces to a mixture of a beta-binomial and a binomial distribution. Note that the model has only one component when the mixing parameter is zero ( η = 0). Model selection using Bayes factors Bayes factors are measures used to compare the fit of two competing models. We suggest using Bayes factors to select an appropriate model for the data from the proposed class of mixture models. Let H 0 and H 1 represent the models under the null and alternative hypotheses, respectively. When comparing two models, it is of interest to examine the posterior odds of one model to another. It is easy to show that the posterior odds of one model to another is Equation (1) shows that the posterior odds is calculated as the product of a term known as the Bayes factor and the prior odds. The Bayes factor is the marginal likelihood of the data under H 1 divided by the marginal likelihood of the data under H 0 , or B 10 ≡ Pr ( X \| H 1 )/ Pr ( X \| H 0 ). Thus, as Bayes factors are proportional to the posterior odds of one model to another, they are desirable measures to use for model selection. Note that if the prior odds are assumed to be 1, then the Bayes factor is equivalent to the posterior odds. One can think of the Bayes factor as a Bayesian likelihood ratio statistic. Like the likelihood ratio statistic, the Bayes factor is a ratio of likelihoods under two models being considered. However, while the likelihood ratio statistic is the ratio of two maximized likelihoods for two competing, nested models, the Bayes factor is the ratio of two likelihoods integrated or averaged over the entire parameter space and the models need not be nested. An important consideration with a Bayesian approach is that a prior distribution is assumed for all of the parameters in the model. The advantage to this is that one can incorporate prior information into determining which model is more appropriate. This is a disadvantage, however, if the Bayes factor is sensitive to the prior and if the prior has been chosen incorrectly. Large Bayes factors are evidence in favor of the alternative hypothesis. Kass and Raftery (1995) discuss guidelines for interpreting the measure [ 7 ]. Following the authors' suggestion, we transform the Bayes factor to the same scale as that of the likelihood ratio statistic and use the criterion that 2 lnB 10 > 2 implies positive evidence in favor of the alternative model. Comparing a uni-component model to a two-component model would address the question of whether there is one versus two groups of chromosome arms. Further, comparing a two-component beta-binomial model to a two-component binomial model would address whether there is overdispersion in either group. The advantage of this is that it provides insight into the number of chromosome arm groups, whereas standard applicable frequentist tests will only indicate whether there is one or more groups [ 8 , 9 ]. Classification Provided there is sufficient evidence to indicate that there are two groups of chromosome arms, it is desirable to identify which chromosome arms belong in which group. Classification of the chromosome arms can be done by calculating the conditional probability of group membership of each arm under a given model. If X i ~ η f 1 ( x i , n i , θ 1 ) + (1 - η ) f 0 ( x i , n i , θ 0 ), then it can be shown using Bayes' rule that where is the maximum likelihood estimate (MLE) of θ , Z i is the group membership of the i th chromosome arm and Z i = 1 implies that the i th chromosome arm is in the TSG group. For the analyses here, chromosome arms with conditional probabilities exceeding 0.5 are classified in the TSG group. Also note that MLEs are computed using the nlminb function in S-Plus. Performance of the Bayes factors Table 1 presents a description of simulated data sets used to evaluate the performance of the Bayes factors. One hundred data sets are generated under each scenario. All parameters chosen to generate the data are based on the Barrett esophageal cancer data set discussed later [ 1 ]. Under the first scenario, data are generated from a two-component binomial mixture model, where each group has a constant loss rate. The two groups are fairly well-separated with the TSG group's loss rate considerably higher than the background loss rate. We specify only five chromosome arms to harbor TSGs, which is believed to be typical. The second scenario is one where there are no TSGs and the background loss rate follows a beta distribution. The distributional parameters are chosen by examining the Barrett data set after removal of the five chromosome arms with the highest rates of allelic loss (these arms are implicated by Barrett et al. (1996) [ 1 ] as potentially harboring TSGs). This gives an expected loss rate of 0.26 and a dispersion parameter of 0.07. Under the third scenario there are two groups of chromosome arms with one group exhibiting a constant background loss rate of 0.22 and the second group of five chromosome arms exhibiting varying and higher rates of allelic loss. In the last scenario, both groups of chromosome arms have varying loss rates. The TSG loss rate distribution follows that of Scenario 3 and the non-TSG loss rate distribution follows that of Scenario 2. Table 2 presents the percentage of time one model is favored over the other based on 2 ln (Bayes factor) for data generated under each of the scenarios described in Table 1 . For each scenario, a 5 × 5 matrix of pairwise comparisons is presented. The rows of the matrix correspond to models considered under H 1 (models appearing in the numerator of the Bayes factor). The columns of the matrix correspond to models considered under H 0 (models appearing in the denominator of the Bayes factor). For data generated from a two-component binomial model (Scenario 1), the true model is mostly favored over the uni-component models. In fact, when comparing the true model to a uni-component beta-binomial model, the latter model is only favored 5% of the time. This can be viewed as a false-negative rate. Note that the Bayes factors never provide evidence in favor of a uni-component model in comparisons with either of the other two-component models for data from this scenario. Furthermore, the true model is selected 75% of the time over the two-component beta-binomial model. The Bayes factors are ambiguous, however, when comparing the true model to a two-component beta-binomial/binomial model, where neither is favored 69% of the time. For data that follow a uni-component beta-binomial distribution (Scenario 2), the results are inconclusive 62% of the time when comparing the true model to the two-component binomial model. For twenty-two percent of the data sets the right model is favored, but 16% of the time, the two-component model is selected. Thus, this comparison results in a 16% false-positive rate. Similar results are found when comparing the true model to a two-component beta-binomial/binomial model. The Bayes factors favor the correct model over the two-component beta-binomial model roughly half the time and favor neither model the other half. Comparisons between the two-component models and the one-component binomial model not surprisingly show a strong preference for the two-component models, as they better accommodate the variability of the data. The third quarter of Table 2 presents results for data generated under Scenario 3. The two-component beta-binomial/binomial model is favored in the majority of the cases over the other models within the class, which makes sense as this model is most similar to the data-generated model. Only once is an alternative hypothesis favored when compared to this model and this is the two-component beta-binomial model. When comparing the two-component beta-binomial/binomial model to the other two-component models, the Bayes factors do not favor either of the models being compared about 20 percent of the time. In general, the two-component models were mostly favored over the one-component models. For data generated under Scenario 4, we expect the two-component beta-binomial model to be chosen over the other models in the class as this model is closest to the truth. The results show that when this model is compared to the two-component binomial or the one-component beta-binomial, it is mostly favored, and these models are never selected. As the two-component beta-binomial model is fairly similar to the two-component beta-binomial/binomial model, however, most of the time neither model is chosen over the other. The two-component beta-binomial is favored only 35% of the time, while the two-component beta-binomial/binomial is favored 9% of the time. Interestingly, when comparing the one-component beta-binomial to the two-component binomial, the one-component model is chosen 72% of the time and the two-component binomial model is chosen only 5% of the time. This suggests that the measure is fairly sensitive to the overdispersion in the two groups. Another example of this is a comparison between the two-component beta-binomial/binomial model and the one-component beta-binomial model. In this case, the two-component model is only favored 54% of the time, where the uni-component model is a better fit to 5% of the data sets, and both models are equally good fits to the data 41% of the time. This simulation study demonstrates that the Bayes factors are an appropriate method of model selection. They perform particularly well for data generated from the two-component models. In particular, most of the time, the correct model is chosen, and furthermore, reasonable false-negative rates are observed for comparisons made on data generated from the two-component binomial model as well as the two-component beta-binomial/binomial model. Data generated from a one-component beta-binomial model produces interesting results. Although the false-positive rates are reasonable when comparing the one-component beta-binomial model to the other two-component models (16%, 7% and 0% for the two-component binomial, two-component beta-binomial/binomial, and two-component beta-binomial, respectively), there is a large percentage of time, when neither model is favored (62%, 69% and 50%). Since both models are often good fits to the data, it would be difficult to decide with confidence whether or not there is a second group of arms in these cases. Application of methods to data sets In this section, we apply the methods discussed to three allelic-loss data sets. Specifically, we use Bayes factors to choose a reasonable model or set of models for the data in order to address whether TSGs exist on any of the chromosome arms, and we classify the chromosome arms as harboring TSGs or not based on the selected model(s). Table 3 presents a summary of the results for the three data sets. The set of models chosen by the Bayes factors is provided along with the individual chromosome arms that were identified as having TSGs based on these models. The set of chosen models was comprised of those with 2 ln (Bayes factors) exceeding 2 when compared to models outside the set and with 2 ln (Bayes factors) less than 2 when compared to models within the set. Details of the analysis for each data set are described below, with slightly more emphasis placed on the first data set. The Barrett data set The Barrett data set records allelic loss on 20 esophageal adenocarcinomas and two high-grade dysplasias. Figure 1 presents a histogram of the proportion of tumors with allelic loss for each of the forty chromosome arms studied (markers were not placed on the short arms of chromosomes 13, 14, 15 and 22 as these are too small to study). Two of the chromosome arms examined do not exhibit allelic loss (arms 20q and 21p) for any of the tumors observed. The mean allelic-loss rate for all arms exhibiting loss is 0.27 and the median allelic-loss rate is 0.24. From the figure, three chromosome arms appear to stand apart from the others in exhibiting considerably higher allelic-loss rates: 9p, 5q, and 17p. Table 4 presents 2 ln (Bayes factors) for the pairwise comparisons of the models for each of the three data sets. In addition, the posterior probability of each model is presented assuming a prior probability for the models such that P (2 Component Model) = P (1 Component Model) = 1/2 This gives P (2 bb) = P (2 bb/bin) = P (2 bin) = 1/6 P (1 bb) = P (1 bin) = 1/4. For the Barrett data set, the two-component models are strongly favored over the one-component models, clearly indicating a group of arms that exhibit higher than background loss rates. In particular, the Bayes factors demonstrate that the two-component beta-binomial/binomial model provides the best fit. Note that the posterior probability of this model is considerably higher than that of the others, providing further evidence of its superiority. Table 5 presents the MLEs of the parameters for the two-component models listed in order of posterior probability (largest to smallest). First note that = 0, reducing the two-component beta-binomial model to a two-component beta-binomial/binomial model. The parameter estimates for these two models are identical and imply that the beta-binomial distribution corresponds to the TSG loss and the binomial distribution corresponds to the background loss. The estimate of the probability that a chromosome arm is in the TSG group is 0.097. The estimated background loss rate is 0.228, and the expected background loss rate for arms with TSGs is estimated at 0.708 with a loss rate variance of 0.07. The fit from the two-component binomial model gives a slightly lower mixing parameter estimate and a slightly higher estimate of the TSG loss rate. The conditional probabilities of group membership based on the two-component beta-binomial/binomial model yield the same classification rule as that based on the other two-component models. Chromosome arms 5q, 9p, and 17p are classified in the TSG group. The conditional probabilities of group membership for these chromosome arms are quite similar across the three models. The Gleeson data set The Gleeson data set consists of 38 esophageal adenocarcinomas. Allelic-loss data were recorded on 39 chromosome arms (as in the Barrett data set, the short arms of chromosomes 13, 14, 15, 21, and 22 were not included in the study). A histogram of the proportion of tumors with allelic loss is presented in Figure 2 . The mean allelic-loss rate is 0.36 and the median allelic-loss rate is 0.32. By simply viewing the histogram, four of the chromosome arms have been identified as having suspiciously high allelic-loss rates. These are chromosome arms 4q, 9p, 18q, and 17p. For the Gleeson data set, the two-component beta-binomial/binomial model, the two-component binomial model and the uni-component beta-binomial model are all favored over the two-component beta-binomial model and the uni-component binomial model (See Table 4 ). Because two of the two-component models as well as the uni-component beta-binomial model are comparable fits to the data, this may imply there is not strong enough evidence of more than one group of chromosome arms. However, while the uni-component beta-binomial model and the two-component beta-binomial/binomial model appear to fit similarly, the two-component binomial model appears to be a slightly better fit than these two as shown by the corresponding posterior probabilities. Maximum likelihood estimates obtained from fitting both the two-component beta-binomial and the beta-binomial/binomial model imply both components follow a binomial distribution as the dispersion parameter estimates are 0. Fits of all three two-component models yield identical parameter estimates, and therefore the rule obtained from the two-component binomial model which has the highest posterior probability is equivalent to that obtained from the other two-component models. Classification using this model places six chromosome arms in the TSG group. These are identified as chromosome arms 4q, 9p, 9q, 12q, 17p, and 18q. Note that three of these chromosome arms (4q, 9q and 12q) exhibit lower than the average background loss rate in the Barrett data set. However, 9p and 17p are categorized along with 5q in the TSG group. Furthermore, although not classified in the TSG group, chromosome arm 18q exhibits the fourth highest allelic-loss rate in the Barrett data set. The Hammoud data set The Hammoud data set consists of 30 esophageal adenocarcinomas on 39 chromosome arms (the same arms included in the Gleeson data set). A histogram of the Hammoud data set is presented in Figure 3 . Chromosome arms 4q and 17p have been identified on the plot as they appear to stand out from the others as having relatively high allelic-loss rates. The mean allelic-loss rate is 0.20 and the median allelic-loss rate is 0.18. The pairwise comparisons using the Bayes factors for the Hammoud data set (See Table 4 ) demonstrate that both the two-component beta-binomial/binomial model and the two-component binomial model give the best fits to the data. Note that the posterior probabilities of these models are practically the same indicating these models are equally good fits to the data. As only two-component models are selected from the class, there is strong evidence to suggest that a second group of chromosome arms with TSGs exists. Classification using both the two-component beta-binomial/binomlal model and the two-component binomial model places chromosome arms 4q and 17p in the TSG group. Both models yield similar conditional probabilities of group membership for the arms, and as in the other data sets, both models yield the same classification rule. Note that chromosome arm 4q is implicated by our analysis of the Gleeson data set and 17p is implicated by our analyses of all three previous data sets. Conclusions Testing of one versus two components in a mixture model is problematic as the likelihood ratio test is not applicable. Bayes factors provide a natural solution to this problem. Although we make only crude comparisons using the Bayes factors, the results favor the right model most of the time for data arising from a two-component model. More importantly, when comparing a two-component model versus a one-component model for these data, the two-component model is generally chosen. For data that arise from a one-component beta-binomial model, the Bayes factors were not able to choose as well between the true model and a two-component model. Specifically, when comparing the true model to the two-component binomial, the false-positive rate was 16%. On the other hand, the Bayes factors are inconclusive for 62% of the data sets when making this comparison. This is actually encouraging when considering some frequentist options. Standard applicable frequentist methods such as an exact Monte Carlo test and the dispersion score test are limited to testing for one versus more than one group of chromosome arms [ 8 , 9 ]. Simulation studies examining these methods for these data reject the hypothesis of one group 93 and 89 percent of the time, respectively [ 10 ]. Based on this, one might conclude that a model with two (or more) groups would be appropriate. The results presented here would not support such a conclusion, at least most of the time. However, it is important to note that if such variability exists in the data as is expected and is ignored, the false-positive rate can be quite high. For example, if comparing a two-component binomial model and a one-component binomial model when there is only one group of chromosome arms exhibiting background loss, the two-component model would likely be favored. Thus, in practice it is recommended that several comparisons are made before selecting a model. In addition, it may be desirable to consider the posterior probabilities of all models jointly. When examining the posterior probabilities of each of the models for the four scenarios considered here, we found that the true model had the highest median posterior probability. Table 3 summarizes the results of applying our approach to three esophageal adenocarcinoma data sets. It is important to note that a common locus on a chromosome arm was rarely chosen across the three studies. In fact, there were only a handful of loci that were investigated by at least two of the three data sets. Not surprisingly, chromosome arm 17p is chosen by the two-component models for all data sets as being in the TSG group. Chromosome arm 17p harbors a well known TSG called p53, which has been implicated in several cancers, including colon cancer, breast cancer and non-small cell lung cancer to name a few [ 1 ]. Also note that chromosome arm 9p is placed in the TSG group for the Barrett data set as well as the Gleeson data set. Similarly, chromosome arm 4q has been identified in both the Gleeson and Hammoud data sets. The Barrett data set also characterizes chromosome arm 5q as harboring a TSG, which has been previously identified in other studies as having a high frequency of allelic loss in colon cancer, non-small cell lung cancer, as well as renal cancer [ 1 ]. Similarly, 18q, identified in the Gleeson data set, is suspected of playing a causal role in colon cancer and osteosarcoma based on high allelic-loss frequencies there [ 1 ]. Also, chromosome arm 3p has been identified as having high loss in renal and non-small cell lung cancer [ 1 ]. The results from applying our methods to the three data sets differ somewhat from those of the previously published analyses. First a potential bias exists in the design of current allelic-loss studies, and is seen in the design of the Barrett and Gleeson studies. Chromosome arms suspected of harboring TSGs are evaluated at more loci than other arms. The proportion of tumors with allelic loss on an arm is then defined as the number of tumors with allelic loss at at least one of the informative loci divided by the number of tumors informative at at least one of the loci. For example in the Barrett study, one locus is investigated for most chromosome arms, but two loci are assessed for loss on arms 13q, 17p, and 18q. This increases the probability that allelic loss will be observed at those arms examined at two loci than at those examined at only one. To address this issue, our analysis considers only one locus (the most informative) per chromosome arm. In the analysis presented by Barrett et al. (1996), the authors consider a uni-component binomial distribution for the background loss [ 1 ]. Frequencies falling far out in the tails of the binomial distribution, assuming a background loss rate of 0.23, correspond to chromosome arms with potential TSGs. However, it should be noted that the model upon which we base our results (two-component beta-binomial/binomial model) is selected over that assumed by Barrett et al. (1996), where our model has a corresponding posterior probability of 0.814 and the uni-component binomial has a posterior probability < 0.001 [ 1 ]. The results from Barrett et al. (1996) indicate that chromosome arms with significantly high loss rates are 5q, 9p, 13q, and 17p (with corresponding p-values < 0.05) [ 1 ]. Our approach also yields classification of 5q, 9p, and 17p in the TSG group. Although the fourth highest conditional probability corresponds to arm 13q, assuming a two-component beta-binomial/binomial model, the probability that it is in the TSG group is estimated to be quite low (0.084) with our approach. Barrett et al. (1996) also implicate chromosome arms 1p and 18q as potentially harboring TSGs (p-values < 0.10 and > 0.05) [ 1 ]. Our analysis demonstrates that these arms are not likely to be classified in the TSG group with conditional probabilities of 0.077 and 0.123, respectively. The analytic approach employed by Gleeson et al. (1997) is to select a chromosome arm with a corresponding allelic-loss rate above an arbitrarily chosen cut-off of 50% as criterion for potentially harboring a TSG [ 11 ]. With this approach, Gleeson et al. (1997) implicate the following 10 chromosome arms; 3p, 4q, 5q, 8p, 9p, 9q, 12q, 13q, 17p, and 18q [ 11 ]. Our method gives the following conditional probabilities of harboring a TSG for these arms respectively: 0.003, 0.982, 0.327, 0.012, 0.916, 0.813, 0.859, 0.121, and 0.998. While our method also selects six of these arms, the conditional probability of the unselected four are estimated to be fairly low. Interestingly our conclusions regarding the Hammoud analysis correspond well to those of the authors. The criterion the authors used for selection of a chromosome arm into the TSG group was that the chromosome arm's allelic-loss rate should exceed two standard deviations above the observed mean allelic-loss rate. This approach is similar to that of Barrett et al. (1996) and more sound than that employed by Gleeson et al. (1997) as it assumes a reasonable model for the allelic-loss rate (in this case a normal distribution) and selects those outliers to the right of the distribution as suspicious [ 1 , 11 ]. Our approach, however, is more flexible in that multiple models consistent with the biological nature of the data are considered and compared and further, conditional probabilities of harboring a TSG are provided for each chromosome arm. For the arms selected by both us and Hammoud et al. (1996), the two arms selected, 4q and 17p, have conditional probabilities of 0.968 and 0.994 for harboring TSGs, respectively [ 4 ]. Results from the Bayes factors for the Gleeson data set are not completely clear. They cast doubt on whether the true underlying distribution really has two components or whether the two-component models chosen also provide a reasonable fit (relative to all the models considered) to overdispersed data exhibiting only background loss. Recall the simulation study where we demonstrate that for data arising from a uni-component beta-binomial model, the Bayes factors indicate that both the true model and the two-component binomial model are often both reasonable fits to the data. This motivates incorporating Bayesian model averaging (BMA) into the inference process [ 12 ]. An alternative would be to compute the posterior odds of a second component. First, the posterior probability of a two-component model could be obtained by averaging over the three two-component models. Second, the posterior probability of a uni-component model could be computed by averaging over the relevant uni-component models. The averaged Bayes factor would then be a ratio of the posterior probability of a two-component model to the posterior probability of a one-component model. Furthermore, one could use Bayesian model averaging when estimating the conditional probability of group membership for each of the chromosome arms. Maximum likelihood estimates from different high probability models could lead to different inferences about parameters. Thus, this approach of averaging the conditional probability over the various models to classify the arms or weighting the parameter estimates by the posterior probability of a given model may be more desirable than choosing a single best model from which to make inference. Specifically, one could weight estimates by P ( H j \| X ). For example, suppose chromosome arm 13q is suspected of harboring a TSG from past experiments and we desire a probability that Z 13 q = 1 based on these data. Because of model uncertainty we may be hesitant to compute the probability based solely on one model. Instead, we could estimate this probability as: where j indexes over all of the models considered. This is a potential alternative to classifying the chromosome arms using the classical maximum likelihood approach that needs to be further explored. It is interesting to note that the two-component beta-binomial mixture model was never chosen for any of the data sets. Although it was certainly favored over the one-component binomial model in all data sets and over the uni-component beta-binomial model in the Barrett data set, it was never chosen to be in the set of candidate models. The class of models considered here is based on our beliefs of the biology of the data. However, the ability to screen the tumor cell genome for chromosome arms which harbor TSGs lies in a better understanding of the background distribution. Characterizing the background distribution would allow a more definitive identification of arms exhibiting abnormal loss. Methods Data The three data sets to which we apply our methods were previously published and analyzed using other techniques [ 1 , 4 , 11 ]. Computing Bayes factors for the proposed class of mixture models Computing Bayes factors can be challenging as non-trivial integration is often required to estimate the marginal probabilities under each model considered. Specifically, calculating Bayes factors involves integrating the likelihood over the entire parameter space for each model considered. Thus, the integrals tend to be high-dimensional. In general, we need to compute I = ∫ Pr ( X \| λ , H ) π ( λ \| H ) d λ . This can be quite computationally intensive. When the integral is of high dimension (> 6), quadrature methods can be unreliable [ 13 ]. In addition, and more relevant to our situation, for moderate to large sample sizes (> 35), numerical methods can be both inefficient and unreliable [ 7 , 14 ]. An alternative approach is to use Gibbs sampling techniques. However, for mixture models, these methods often miss important mass as the chain tends to get stuck near one mode resulting in an underestimate of the integral [ 14 ]. Furthermore, because the sampling is not independent, there is no simple way of self-monitoring convergence. Another method of estimating integrals is simple Monte Carlo, that involves sampling from the prior distribution, π ( λ ). The simple Monte Carlo estimate of the integral is the averaged likelihood at the sampled parameter values or This has been shown to be a good estimate for likelihoods that are relatively flat. However, if the posterior is concentrated relative to the prior, the variance of the estimate will be large, and convergence to a Gaussian will be slow [ 7 ]. Thus, sampling from the prior distribution is often not very efficient. A potential solution to this problem is to do importance sampling that involves sampling from π ( λ ), the importance sampling function [ 7 , 14 ]. The estimate then becomes where is known as the importance sampling ratio. The simple Monte Carlo estimate is a special case of importance sampling where π (·) is chosen to be the prior distribution. However, the importance sampling estimate can be an improvement over the simple Monte Carlo estimate if π (·) is chosen such that the sampling is more efficient, e.g., if π (·) is centered around the mass. There has been some success with importance sampling in a non-mixture model setting [ 14 ]. Our solution is to first write the likelihood in its complete-data form. The likelihood for the mixture of two beta-binomial distributions is written as follows: where z = ( z 1 , z 2 ,..., z N ) T and the z i s are unobserved group membership indicators such that z i = 0 if x i is from the background component and z i = 1 if x i is from the TSG component. Then the marginal probability of X becomes where I denotes the marginal probability of the data (or integrated likelihood) and where g is the prior distribution of θ . We then estimate this integral using a method we developed called the Uniform Distance Method (UDM). This method is a variant on importance sampling and involves a combination of either quadrature or exact integration and sampling of the membership vectors, Z . The idea behind the method is to use P ( Z \| θ = , x ) where is the MLE of θ to provide information on the important groupings, i.e., which chromosome arms are likely to be clustered together. While the membership vectors are sampled independently, the membership values within a group are sampled dependently, making these groupings more likely to be maintained than if the values were sampled independently. The development and assessment of UDM is discussed in detail in Desai (2000) and demonstrates solid performance in estimating these integrals [ 10 ]. Software for implementing the method is available by contacting the first author. Note that for all analyses presented in this paper, uniform priors are assumed for the unknown parameters. Abbreviations TSG, tumor suppressor gene; MLE, maximum likelihood estimate; 2 bb, two-component beta-binomial model; 2 bb/bin, two-component beta-binomial/binomial model; 2 bin, two-component binomial model; 1 bb, uni-coniponent beta-binomial model; 1 bin, uni-component binomial model; BMA, Bayesian model averaging; UDM, uniform distance method Authors contributions Both MD and MJE contributed substantially to the development of the models and the methodology. MD performed the simulation study and analysis of the three data sets. Both authors have read and approved the final version of the manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544187.xml
544839	Optimized expression of Plasmodium falciparum erythrocyte membrane protein 1 domains in Escherichia coli	Background The expression of recombinant proteins in Escherichia coli is an important and frequently used tool within malaria research, however, this method remains problematic. High A/T versus C/G content and frequent lysine and arginine repeats in the Plasmodium falciparum genome are thought to be the main reason for early termination in the mRNA translation process. Therefore, the majority of P. falciparum derived recombinant proteins is expressed only as truncated forms or appears as insoluble inclusion bodies within the bacterial cells. Methods Several domains of PfEMP1 genes obtained from different P. falciparum strains were expressed in E. coli as GST-fusion proteins. Expression was carried out under various culture conditions with a main focus on the time point of induction in relation to the bacterial growth stage. Results and conclusions When expressed in E. coli recombinant proteins derived from P. falciparum sequences are often truncated and tend to aggregate what in turn leads to the formation of insoluble inclusion bodies. The analysis of various factors influencing the expression revealed that the time point of induction plays a key role in successful expression of A/T rich sequences into their native conformation. Contrary to recommended procedures, initiation of expression at post-log instead of mid-log growth phase generated significantly increased amounts of soluble protein of a high quality. Furthermore, these proteins were shown to be functionally active. Other factors such as temperature, pH, bacterial proteases or the codon optimization for E. coli had little or no effect on the quality of the recombinant protein, nevertheless, optimizing these factors might be beneficial for each individual construct. In conclusion, changing the timepoint of induction and conducting expression at the post-log stage where the bacteria have entered a decelerated growth phase, greatly facilitates and improves the expression of sequences containing rare codons.	Background Qualitative and quantitative production of proteins in heterologous systems is essential for the characterization of any molecule, from determination of antigenicity, functional and structural analysis to vaccine development. Malaria antigens are among the most difficult proteins to express with in vitro methods because of their extreme genetic codon usage. Different organisms have been applied for the production of malaria proteins, including Escherichia coli [ 1 , 2 ], baculovirus [ 3 , 4 ], yeast ( Pichia pastoris and Saccharomyces cerevisiae ) [ 5 - 8 ], transgenic tobacco plants [ 9 ] and transgenic mice [ 10 ]. Among these, the E. coli expression system is the most attractive and most frequently used, because it quickly produces large amounts of biomass without sophisticated laboratory equipment and at low costs. However, the quality of many proteins expressed in E. coli has not been satisfactory. In many cases, the recombinant proteins are either expressed as truncated forms or precipitate in insoluble inclusion bodies in the bacterial cells. Although methods have been developed to obtain correctly folded proteins from these inclusion bodies, the process of refolding cannot be successfully applied to all proteins [ 11 , 12 ]. Proteins expressed in insect cells using the baculovirus system are generally correctly folded [ 4 ]. However, so far only a few proteins have been successfully produced using this system because many proteins turned out to be toxic to the insect cells. In addition, the system achieves limited yields, which makes large-scale production cost ineffective. In recent years, expression of malaria proteins in yeast cells including P. pastoris and S. cerevisiae has been established in several laboratories [ 5 - 8 ]. Recombinant CSP, MSP-119, MSP-1-AMA-1 hybrid proteins and the cysteine-rich inter-domain region (CIDR) of a Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) have been produced in P. pastoris for malaria vaccine studies in either primates or pre-clinical trials in humans [ 13 ]. However, for expression in P. pastoris , the codon sequences of these antigens need to be optimized. In most cases, sequences encoding for the amino acids of potential glycosylation sites have to be removed. So far, this system is the most promising one and might be the favourite choice when it comes to the production of recombinant malaria proteins under GMP conditions. It is nevertheless unlikely that this system will replace E. coli as a routine bench bioreactor due to its complicated manipulation and relatively long cultivation times. The use of long synthetic peptides (LSP) has been explored in malaria vaccine antigen production in recent years [ 14 , 15 ]. The advancing technology of peptide biosynthesis has made it possible to produce LSP with a high degree of homogeneity and purity. Furthermore, LSP can be designed in a way that they contain a large number of T cell epitopes, which leads to the generation of stronger CTL-mediated immune responses. However, this technology also has its limitations: it is still difficult to manufacture peptides that are more than 100 amino acids in length and proteins with multiple disulfide bonds are generally complicated to produce. The P. falciparum genome is one of the most A/T-rich genomes. Surface exposed molecules expressed by the parasite such as members of the PfEMP1 family are positively charged, caused by the abundance of arginine and lysine residues in their sequences, which complicates their expression in heterologous systems such as E. coli . The high content of A/T repeats in the mRNA template is a reason for early translation termination and results in heterogeneity of recombinant proteins. Members of the PfEMP1 family are of great interest since they are virulence factors that mediate adhesion of P. falciparum -infected erythrocytes in the post-capillary microvasculature, a process that leads to severe malaria [ 16 ]. Each PfEMP1 molecule is composed of several Duffy-binding like domains (DBL) and CIDR domains. Both DBL and CIDR domains have a distinct number of cysteine residues and several lysine and arginine motifs [ 17 ]. Molecular characterization, including antigenic analysis of this protein family, relies in most cases on the successful in vitro production of the correctly folded protein, and production of these proteins in the native conformation remains particularly difficult. In most studies where E. coli was used as a bioreactor, it has been the main goal to reach as high expression levels of the recombinant protein as possible. However, high expression levels will not guarantee a high quality of the final product. Efficient expression of heterologous proteins in E. coli is impaired by the rarity of certain tRNAs that are abundant in the organisms from which the heterologous protein is derived [ 1 ]. When the process of expression achieves high levels, the limited amounts of the tRNAs will quickly be exhausted. The lack of tRNAs will result in a drop-off of the ribosomal unit from the mRNA template and will terminate the translation process. This study describes a simple method for optimizing the cultivation conditions and especially the timepoint of induction exemplified by the expression of several PfEMP1 domains in E. coli . Induction at the post-log stage of bacterial growth leads to the production of considerably larger amounts of soluble protein of a higher quality compared to standard conditions. Moreover, the method is easily applicable in laboratories where a sophisticated cultivation facility is not available. Methods Parasites The P.falciparum parasite strains FCR3S1.2 and TM284S2 were cultured according to standard methods with 10% AB + Rh + serum added to the buffered medium (RPMI supplemented with Hepes, gentamycin and sodium bicarbonate). Genomic DNA from these parasites was purified using the EasyDNA purification kit (Invitrogen) according to the manufacturer's protocol. Recombinant plasmids Plasmid constructs for the expression of the recombinant proteins GST-DBL1α and GST-CIDR1α of FCR3S1.2 var 1PfEMP1, GST-DBL1α and GST-DBL2β of TM284S2 var 1PfEMP1 were generated as described earlier [ 18 , 19 ]. Codon optimization and gene resynthesis The sequence of the DBL1α domain of FCR3S1.2 var 1PfEMP1 was optimized for codon adaptation in E. coli . The genes were re-synthesized chemically (GeneArt, Germany). The re-synthesized DBL1α was amplified with oligonucleotide primers (rDBL-1 5'-ATG GCT ACT TCC GGA GGA, rDBL-1.1 5'-TTC GAT AAG CAG AAG AAG TAC) and cloned into the pGEX4T-1 vector as described [ 20 ]. E. coli strain The BL21-CodonPlus-RIL strain purchased from Stratagene (California, USA) was used for protein expression. This bacterial strain has been engineered to contain a high copy number of argenine U -, leucine W -and isoleucine Y -tRNA genes for optimal expression of heterologous proteins of organisms with A/T-rich genetic sequences. Expression of PfEMP1 domains in BL21-CodonPlus-RIL bacteria BL21 competent cells were transformed with recombinant pGEX4T-1 plasmids containing FCR3S1.2 DBL1α, TM284S2 DBL1α or TM284S2 DBL2β as inserts. The transformed bacteria were selected on LB agar plates containing ampicillin (100 μg/ml). A single colony of the transformed bacteria was inoculated in 30 ml LB medium containing ampicillin (100 μg/ml) and chloramophenicol (50 μg/ml) for cultivation at 37°C overnight. Aliquots of the culture were inoculated into one litre LB medium with ampicillin (100 μg/ml). The cultivation was carried out with a shaking speed of 225 rpm. The pH value and the optical density at A 600 of the cultures were monitored systematically. Aliquots (50 ml) of each culture were sequentially taken after the OD A 600 reached 0.5 and IPTG (isoprophyl-b-D-thiogalactopyranoside) was added to a final concentration of 0.1 mM to induce the expression. The expression was carried out for three hours at 37°C and the bacteria were harvested afterwards by centrifugation at 4000 rpm for 15 minutes. The recombinant proteins were purified on Glutathione-sepharose (Amersham-Phamacia, Sweden) as described earlier [ 18 , 19 ]. SDS-PAGE analysis of the recombinant proteins To analyse the recombinant proteins, aliquots of the soluble and insoluble fractions of the expressed proteins from each purification were mixed with an equal volume of SDS-PAGE loading buffer containing β-mercaptoethanol and boiled at 100°C for 5 min. The denatured proteins were resolved in 10% acrylamide gels containing 1% SDS and visualized by staining in Coomassie brilliant blue solution. Binding to heparin and blood group A antigen Purified recombinant DBL1α of FCR3S1.2 expressed with pGEX plasmids containing either the wild-type DBL1 sequence or the codon-optimized sequence was further passed through a heparin-HiTrap column (Amersham-Phamacia Biotech, Sweden). After washing with PBS tween-20 buffer, the bound protein was released from the column with 2M NaCl and dialyzed immediately against cold PBS. Aliquots of the eluted proteins were subjected to SDS-PAGE. The binding of recombinant DBL1α of FCR3S1.2 to blood group A antigen was studied using a solid phase assay system as described earlier [ 20 ]. Results and discussion The expression of three different DBL-domains and one CIDR-domain as recombinant proteins in E. coli was induced either at an OD A 600 of 0.6, which is commonly recommended or at an OD A 600 higher than 2.0. SDS-PAGE analysis (Figure 1 ) shows that most of the recombinant proteins of the cultures induced at a low OD A 600 (Figure 1 , lane 1, 3, 5, 7) were truncated at the C-terminal end displaying multiple bands of different molecular weights, while the intact protein represents only a small fraction of the overall protein yield. In contrast, if the expression was induced at a higher OD A 600 (Figure 1 , lane 2, 4, 6, 8), the dominant fraction of the protein was found to be the intact form, which proved to be true for all four domains tested although derived from different PfEMP1s. Figure 1 Comparison of recombinant DBL, CIDR proteins expressed at mid-or post-log phase. Expression of GST-DBL1α and GST-CIDR1α of FCR3S1.2, GST-DBL1α and GST-DBL2β of TM284S2 was induced when the bacterial growth was at mid-log respectively post-log stages. The purified recombinant proteins were analysed in SDS-PAGE. Results presented in lane 1, 3, 5 and 7 are proteins purified from cultures where expressions was initiated at mid-log phase, while lane 2, 4, 6 and 8 show proteins after induction at post-log phase. The intact fraction of each expressed protein is marked with an arrow. Proteins were in addition verified by Western-Blot both with anti-GST-and anti-DBL1-antibodies [26]. In bacterial cultures, the growth will be at log phase between an OD A 600 of 0.3 and 1.5. During the log phase, the number of bacteria in the culture doubles approximately every 20 minutes. Afterwards, the proliferation rate slows down due to the lack of nutrients. If the induction is initiated while the bacteria grow in log phase, the bacterial translation machinery will be highly active and the expression of the recombinant protein follows this profile, because once turned on, the promoter controlling the heterologous sequence on the vector does not underlie further control mechanisms. During expression, the rare codons of arginine, leucine, isoleucine and proline frequently found in PfEMP1 sequences will inhibit the translation process, most likely caused by the exhaustion of the tRNAs for these amino acids. It has been reported that the rare codons of arginine and proline are likely to cause frameshifts and with that undesired products in bacterial expression system [ 21 - 23 ]. The data reported here indicate that these problems mainly occur during the high-level expression stage, since proteins expressed at post-log growth stage are much less truncated. Enzymatic digestion of heterologous proteins in E. coli is thought to be an additional reason for product heterogeneity of recombinant proteins [ 24 ]. The experiments of this study could not confirm degradation by bacterial proteases as one of the major causes, since the use of a protease inhibitor cocktail in the purification protocol did not affect the pattern of the expressed products (data not shown). In addition, expression was carried out using a BL21 Codon Plus bacterial strain (Stratagene) that is deficient in the OmpT and Lon bacterial proteases. We have previously found that a large proportion of the recombinant proteins remain in the insoluble fraction whereas only small amounts appear in the soluble fraction (Figure 2 and data not shown) if expression is initiated at an OD A 600 of 0.6. To check whether the bacterial growth status at the induction timepoint has any effect on protein solubility, induction of expression was carried out on aliquots of the same bacterial stock culture at different bacterial densities (OD A 600 value). Both soluble and insoluble fractions of the same culture were compared. The results (Figure 2A–C ) clearly show that the majority of the three recombinant proteins remain in the insoluble fraction when the expression was induced at an OD A 600 below 2.0. If, on the other hand, the induction is initiated at an OD A 600 greater than 2.0, almost the total amount of the recombinant proteins appears in the soluble fraction. Figure 2 Impact of bacterial growth stages on protein solubility. The expression of the three recombinant proteins was induced at various timepoints chosen gradually from low OD A 600 to higher OD A 600 . The comparison of the soluble and insoluble fractions of the recombinant proteins revealed that after initiation of expression at an OD A 600 of greater than 2.0, the recombinant proteins are found almost completely in the soluble fraction. The amount of each protein loaded is not proportional to the size of the cultivation. The solubility of a protein correlates with its correct structure that is formed during a post-translational folding process. Freshly synthesized polypeptides remain in a stage of intermediate form in the bacterial cytoplasma. After several enzymatic and biochemical processing steps, the peptides are folded into their functional form [ 24 ]. However, if proteins are folded incorrectly, they tend to accumulate as aggregates in the bacterial cell and, in order to avoid toxic effects on the host system, the bacteria store these aggregates in confined structures referred to as inclusion bodies. Formation and accumulation of heterologous proteins as inclusion bodies is a common problem in protein expression. The exact mechanism of this process is still not understood. It has been suggested that factors such as culture pH, temperature and protein amino acid composition might affect the solubility of a recombinant protein [ 24 ]. The data reported here indicate that the expression speed and, with that, the subsequent folding process is the most important factor. Protein expression at the post-log phase resulted in high amounts of soluble protein, which indicates that at this stage the low bacterial growth rate implicates a biosynthesis process that is kept at low speed. The slow synthesis process will allow the protein processing machinery to efficiently assemble the freshly synthesized peptides into the correct structure. Correctly folded proteins are most likely to stay in the soluble form provided that the molecule does not contain large numbers of hydrophobic residues. Although we found that the pH value of the growing culture is influenced by the amino acid composition of the expressed polypeptide, keeping a stable pH value in the bacterial culture does not affect the protein solubility (data not shown) and, therefore, has little influence on the quality of the expressed protein. However, temperature is an important factor to consider. Keeping the culture at 16°C before and after induction slightly improves the protein quality (data not shown), but, on the other hand, slows down bacterial growth considerably and therefore minimizes the final yield of the recombinant protein. It has been reported that codon-optimized sequences for the use in E. coli will improve expression quality. Here we show that C/G versus A/T contents of the heterologous gene sequence are not among the most important factors that determine the quality of the recombinant protein. The expression of GST-DBL1α of FCR3S1.3 (Figure 2A ) optimized for expression in E. coli shows a very similar expression pattern compared to those ones of GST-DBL1α and GST-DBL2β of TM284S2 which were expressed using the wildtype P. falciparum sequences (Figure 2B,C ). This indicates that sequence composition is not always a determinant factor for expression quality. We have previously found that the DBL1α domain of FCR3S1.2var1 PfEMP1 binds to the human erythrocyte surface through heparan sulfate [ 20 , 25 ]. Further, the recombinant GST-DBL1α of FCR3S1.2 protein can be purified through binding to heparin-sepharose. In this study, the same amount of GST-DBL1α purified from cultures of expression started at an OD A 600 of 0.6 and greater than 2.0 was tested for its ability to bind to heparin. Although the truncated forms of the DBL1 display binding to heparin due to the presence of heparin-binding motifs in these peptides, there is a remarkable difference in terms of binding affinity between the proteins expressed at different bacterial densities as shown in Figure 3 . Proteins expressed at a high OD A 600 are not only more intact and more soluble, but also display higher affinity to heparin. Figure 3 Binding to heparin. Recombinant GST-DBL1α of FCR3S1.2 was purified from cultures with induction at mid-log (lane 1) and post-log stage (lane 2) and bound to heparin. Protein expressed by bacteria at post-log stage showed considerably higher affinity to heparin. To further demonstrate functionality of the proteins expressed at high OD A 600 the DBL1α of FCR3S1.2 was subjected to a blood group A binding assay, which confirmed the specific interaction between the DBL1α and the blood group A antigen (data not shown). The expression of P. falciparum derived proteins, especially membrane-bound proteins is still a great challenge due to the high content of amino acids encoded by rare codons in the P. falciparum genome. The method reported here presents an easily applicable tool to express sequences containing rare codons. The key factor for the expression of such proteins is to decelerate the translation machinery inside the bacteria. Low expression speed will not only allow the ribosomal unit to smoothly pass through the mRNA templates and synthesize full-length polypeptide chains, but also enable the proteins to slowly transfer from the unstable intermediate phase to the correctly folded phase. The described expression approach will result in a final product that is soluble, intact and functional, nevertheless, additional factors might influence the expression and need to be optimized for each individual construct. The expression of eukaryotic genes in E. coli is one of the most frequently used tools in modern science. Numerous approaches have aimed at achieving the highest possible level of expression by having a maximum amount of protein expressed per bacterial cell. Our studies suggest on the contrary that increasing the number of bacterial cells in the culture while at the same time keeping the expression process at a low profile, might considerably improve the quality and quantity of the protein. That way, high level expression can simply be achieved by increasing the bacterial density of a culture, whereby problems in form of truncated or insoluble protein factions are almost completely eliminated. Authors' contributions KF carried out the expression assays. SA and AC participated in the expression and optimization experiments. MTB participated in sequence design. QC coordinated the experiments and helped to draft the manuscript. All authors read and approved the final manuscript	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544839.xml
546009	Polymorphisms of the insertion / deletion ACE and M235T AGT genes and hypertension: surprising new findings and meta-analysis of data	Background Essential hypertension is a common, polygenic, complex disorder resulting from interaction of several genes with each other and with environmental factors such as obesity, dietary salt intake, and alcohol consumption. Since the underlying genetic pathways remain elusive, currently most studies focus on the genes coding for proteins that regulate blood pressure as their physiological role makes them prime suspects. The present study examines how polymorphisms of the insertion/deletion (I/D) ACE and M235T AGT genes account for presence and severity of hypertension, and embeds the data in a meta-analysis of relevant studies. Methods The I/D polymorphisms of the ACE and M235T polymorphisms of the AGT genes were determined by RFLP (restriction fragment length polymorphism) and restriction analysis in 638 hypertensive patients and 720 normotensive local blood donors in Weisswasser, Germany. Severity of hypertension was estimated by the number of antihypertensive drugs used. Results No difference was observed in the allele frequencies and genotype distributions of ACE gene polymorphisms between the two groups, whereas AGT TT homozygotes were more frequent in controls (4.6% vs. 2.7%, P = .08). This became significant (p = 0.035) in women only. AGT TT genotype was associated with a 48% decrease in the risk of having hypertension (odds ratio: 0.52; 95% CI, 0.28 to 0.96), and this risk decreased more significantly in women (odds ratio: 0.28; 95% CI, 0.1 to 0.78). The meta-analysis showed a pooled odds ratio for hypertension of 1.21 (TT vs. MM, 95% CI: 1.11 to 1.32) in Caucasians. No correlation was found between severity of hypertension and a specific genotype. Conclusion The ACE I/D polymorphism does not contribute to the presence and severity of essential hypertension, while the AGT M235T TT genotype confers a significantly decreased risk for the development of hypertension in the population studied here. This contrasts to the findings of meta-analyses, whereby the T allele is associated with increased risk for hypertension.	Background Essential hypertension is a common, polygenic, complex disorder resulting from interaction of several genes with each other and with environmental factors such as obesity, dietary salt intake, and alcohol consumption. Since the underlying genetic pathways remain elusive[ 1 ], currently most studies focus on the genes coding for proteins that regulate blood pressure as their physiological role makes them prime suspects. The Renin-Angiotensin System (RAS) has a central role in regulating blood pressure and sodium homeaostasis. Genes encoding components of RAS, including angiotensinogen (AGT), angiotensin-converting enzyme (ACE), angiotensinogen II type-1 receptor (AGTR1), and renin, have been extensively investigated as genetic determinants of essential hypertension [ 2 ]. Polymorphisms of RAS[ 3 ] genes seem also to play a role in the development of diseases that cause secondary hypertension[ 4 , 5 ]. Subjects carrying the ACE D allele have unanimously been shown to have increased ACE serum activity[ 3 , 6 ] while the T235 AGT variant has been associated with elevated angiotensinogen levels [ 7 ]. However, so far there are no consistent findings. In 1992, the M235T AGT TT polymorphism was first reported to be associated with hypertension [ 8 ]. This finding has not been confirmed by all investigators[ 9 , 10 ]. Although no relationship between the ACE gene and hypertension was observed in one early linkage study [ 11 ] and most recent studies including one meta-analysis [ 12 - 14 ], several studies have suggested a role: hypertensive individuals have a high prevalence of the D allele or DD genotype [ 3 , 15 , 16 ]. The inconsistent results might be explained in part by the genetic and environmental heterogeneity among different ethnic groups [ 13 ]. On the other hand, one recent study [ 17 ] reported that the MM, AA, CC, DD/ID genotype combination was associated with a substantially higher prevalence of hypertension in the participants to the Olivetti Heart Study, even though no individual effect of each isolated genotype was detected. The present study investigates the relationship between variants of the I/D ACE gene and M235T AGT gene, and the presence and severity of essential hypertension in a large homogeneous German population. The effect of a combination of ACE and AGT gene polymorphisms on hypertension was also examined. Methods Study design The design of the study followed the guidelines proposed by Cooper et al [ 18 ], and the study was carried out in accordance with the Declaration of Helsinki [ 19 ]. Study population This cross-sectional study comprised a total of 1358 individuals from Weisswasser, a county town of 25,000 in Saxony, Germany. After giving informed consent, 720 normotensive subjects were selected from local blood donors and 638 hypertensive patients from the local renal care center. All hypertensive patients included in the study had been diagnosed as suffering from primary hypertension by the attending consultants on first contact with the clinic. Hypertensives were defined as those who received at least one antihypertensive medication. At the time of blood sampling, 34.2% were diabetic (6 type 1, 212 type 2), and 65.1% were suffering from kidney disease. Of the 37 patients with K/DOQI stage 5 (Kidney failure: GFR, 15 ml/min/1.73 m 2 or dialysis), 15 were due to diabetic nephropathy, 5 to chronic pyelonephritis, 1 to chronic glomerulonephritis, 1 light chain deposits, 1 polycystic kidney disease, and 14 of unknown cause (no biopsy obtained). The severity of hypertension was estimated based on the number of antihypertensive medications used, a surrogate marker for the severity of hypertension[ 8 ]. Age and gender distribution is described in table 1 . Genotyping RFLP (restriction fragment length polymorphism) and restriction analysis were used to determine the frequencies of the I/D polymorphisms of the ACE gene, and homo-/ heterozygoty of the M235T AGT gene[ 20 , 21 ]. ACE I/D polymorphism was studied by PCR based amplification of a 597 bp long gene fragment of the ACE gene, which lacks 287 bp in case of the deletion (D) variant. The primers used were: sense- 5'GATGTGGCCATCACATTCGTCAGAT3', and antisense- 5'CTGGAGACCACTCCCATCCTTTCT3'. AGT M235T polymorphism was studied by first amplifying a 104 bp long fragment of the AGT gene using the following primer sequences: sense- 5'CCGTTTGTGCAGGGCCTGGCTCTCT3', and antisense: 5'CAGGGTGCTGTCCACACTGGACCCC3'. The M -> T point mutation at position 235 creates a detection site for the restriction enzyme Tth 111I . Statistical analysis Statistical analysis was carried out using SPSS personal computer statistical package (version 11.5, SSPS Inc, Chicago, IL). Demographic characteristics were compared by t test for continuous data and Pearson's χ 2 test for categorical data. Allele frequencies were calculated with the gene-counting method. χ 2 test was used for assessment of the Hardy-Weinberg equilibrium for the distribution of genotypes. Odds ratios were calculated with a 95% confidence interval. A P < .05 was considered significant. Meta-analysis A meta-analysis was performed using Review Manager 4.2 (The Cochrane Collaboration) to further examine the association of the AGT M235T gene polymorphisms with essential hypertension in Caucasians. A systematic literature search in PubMed Medline for articles published between April 2002 and June 2004 was carried out using the following MESH-headings: "angiotensinogen/genetics", "hypertension/genetics", "blood pressure/genetics", and "adult". The search was limited to articles published in English and studies on Caucasian human subjects. Only 2 studies were left after strict examination according to the exclusion criteria listed in [ 22 ]. A total of 25 studies were finally included: 22 were from the most recent meta-analysis [ 22 ], which covered articles from January 1992 to March 2002; 2 were selected from the query described above, and the last one was the present study. Homogeneity among studies was assessed on the basis of χ 2 test using P-value < 0.05. The Mantel-Haenszel odds ratios were calculated by applying both fixed effect model and random effect model in case of heterogeneity. Results Demographic data are summarized in Table 1 . Hypertensives were older (58.80 ± 13.22 years) than controls (41.24 ± 12.66 years, p < .0001), and more often male (53.2% vs. 44.4%, p = .001). AGT M/T genotyping was successful in 637 hypertensives and 720 normotensives, and ACE I/D genotype was analyzed in 636 hypertensive and 719 control subjects. The roles of age and gender in the association between hypertension and ACE and AGT gene polymorphisms were examined by comparing the effects of ACE and AGT genotypes for hypertension in men and women, young and elderly subjects respectively. "Young" was defined as "age < 50 years old", and "elderly" was characterized as "age ≥ 50 years old". ACE polymorphism No differences were observed in ACE allele and genotype frequency distribution between hypertensives and controls with respect to gender and age, and no deviations from Hardy-Weinberg equilibrium were observed in any of subgroups (P > 0.1). ACE genotypes I/I, I/D and D/D were of almost identical frequency within both groups (P = 1.0, Figure 1 ). Risk assessment showed that there were no significant risk changes for hypertension in the subjects either with the ACE DD genotype (odds ratio: 1.00, 95% CI: 0.74 to 1.36, P = .98, Table 2 ) or D allele (odds ratio: D vs. I: 1.00, 95% CI: 0.86 to 1.17, P = .98). AGT polymorphism AGT T/T homozygotes tended to be more frequent in controls than in hypertensives (4.6% vs. 2.7%, Figure 2 ). In women, this finding became significant (5.3% vs. 1.7%, Figure 3 ), but no difference in AGT genotype frequency was found in men. The distribution of the AGT genotypes in all subgroups of the sample population was not in Hardy-Weinberg equilibrium (P < .001). AGT TT genotype was associated with a significant 48% decrease in the risk of being hypertensive (Table 2 , odds ratio: 0.52; 95% CI: 0.28 to 0.96; P = .034), and this risk decreased even more to 72% in women (odds ratio: 0.28; 95% CI: 0.1 to 0.78; P = .01). However, no difference was observed in the AGT allele frequency distribution with respect to age and gender (Table 3 , P > 0.05), and the effect of the AGT T allele did not reach a significant level in the decrease of hypertension risk (odds ratio: T vs. M: 0.88; 95% CI: 0.75 to 1.03; P = .12). Meta-analysis of studies on AGT polymorphisms in Caucasians When all studies were pooled, Caucasian individuals with TT genotype had an odds ratio for hypertension of 1.21(95% CI: 1.11 to 1.32) compared with those with MM genotype (Figure 4 ). The studies included in the meta-analysis are [ 8 , 20 , 23 - 43 ]. The pooled odds ratio (odds ratio: TT vs. MM: 1.23; 95% CI: 1.13 to 1.34) increased by 2.5% when the presented study was excluded. Tests for heterogeneity were significant (P < 0.001) in the above two cases, and the odds ratios (TT vs. MM) rose to 1.30 (95% CI: 1.10 to 1.54), and 1.35 (95% CI: 1.15 to 1.59) respectively when applying the random effects model. Combination of ACE and AGT polymorphisms The effect of eight combinations (TT, DD/ID; TT, II/ID; MM, DD/ID; MM, II/ID; DD MM/MT; DD, TT/MT; II, MM/MT; II, TT/MT) on hypertension was examined. No statistically significant association was observed between any combination above and hypertension in all subjects combined. Nonetheless, in women, both genotypes of TT, DD/ID and TT, II/ID were significantly associated with lower prevalence of hypertension (Table 2 , 20% vs. 43.3%, odds ratio: 0.33, P = 0.038; 19% vs.43.6%, odds ratio: 0.31, P = 0.026), while MM, DD/ID genotype significantly increased the risk for hypertension (Table 2 , 49.2% vs. 40.1%, odds ratio: 1.45, P = 0.028). No association could be identified between severity of hypertension and a specific ACE or AGT genotype (Table 4 ). Discussion Although some recent studies [ 15 , 16 , 44 , 45 ] suggested a unique sex-specific role of ACE in essential hypertension, no significant association of essential hypertension with the ACE gene I/D polymorphism was observed in this German population of 1,358 for either gender. This finding confirms earlier observations in another German population [ 31 ], in other Caucasian populations [ 11 , 12 , 14 , 46 ], and in one meta-analysis [ 13 ]. The distribution of the ACE genotypes was in Hardy-Weinberg equilibrium in this German population while that was not the case in Pereira et al's study [ 1 ]. One possible explanation is the ethnic difference. Pereira et al. [ 1 ] showed that there were statistically different ACE I/D polymorphism genotypic frequencies in different ethnic groups. Surprisingly, the cross-sectional study presented here shows a higher prevalence of the T/T M235T AGT gene in the control group compared to the hypertensive group. AGT TT genotype was associated with a decrease in the risk for hypertension (odds ratio-TT vs. MM: 0.52; 95% CI: 0.28 to 0.96) and a more significant association was found in women (odds ratio-TT vs. MM: 0.28; 95% CI: 0.1 to 0.78), compared to men. This is in stark contrast to findings from previous studies, including two German datasets [ 31 , 32 ], and three meta-analyses [ 10 , 22 , 47 ], which reported that the AGT 235 T-allele and/or TT genotype significantly increased the risk for essential hypertension in Caucasians: odds ratio T vs. M was 1.20 (95% CI: 1.11 to 1.29) [ 10 ], odds ratio TT vs. MM was 1.31 [ 47 ], and odds ratio TT vs. MM was 1.19 (95% CI: 1.10 to 1.30)[ 22 ]. In agreement with the previous meta-analyses, the meta-analysis presented here showed increased odds for hypertension (odds ratio: TT vs. MM: 1.21) in Caucasians conferred by TT, and the odds ratio rose by 2.5% when the present study was excluded. Of the 25 studies included in the present meta-analysis, the present study was the only one in which the AGT T235T genotype decreased odds for hypertension. Nevertheless, the quality of meta-analysis results depends on the quality of the individual studies included, and unusual sample sizes might bias the finding. For example, one single study [ 43 ] included in the previously largest meta-analysis [ 22 ] was exceptionally large, giving it enormous weight. The highly variable study quality implies that all interpretations must be made with great caution, as was explicitly pointed out by Kunz et al. [ 10 ] Although no significant difference was observed in AGT T allele frequency distribution between hypertensives and controls with respect to age and gender, the frequency of the AGT T allele among normotensives was higher than that among hypertensives (0.36 vs. 0.33). This was inconsistent with one previous meta-analysis in Caucasians, which showed that among controls, the mean allele frequency for the AGT T allele was 0.41 (95% CI: 0.34 to 0.48), and among cases, increased to 0.45 (95% CI: 0.38 to 0.52) [ 10 ]. In the present study, the frequency of the AGT T allele among hypertensives (0.33) was outside the lower border of the 95% confidence interval (0.38 to 0.52) reported in [ 10 ]. This may reveal the specific genetic background of this particular German population. The AGT genotype distribution is not in Hardy-Weinberg equilibrium (P < 0.001) while no deviations from Hardy-Weinberg equilibrium are observed on the ACE genotype distribution in the same population. This may be explained by a shift toward a higher frequency of MT individuals (62.4%) instead of TT individuals (3.7%) in this specific population. The study population presented here contains a large proportion (65%) of patients with renal disease. While selection of participants based on patient records excluded those patients that had symptoms suggesting the diagnosis of secondary hypertension at first contact, the possibility remains that at least a part of the study population suffers from renal rather than essential hypertension. It should be noted, however, that the majority of studies included in the presented meta-analysis does not give specific information regarding renal function of hypertensives, and the largest study [ 43 ] is population based and does not name any specific, kidney related exclusion criteria. Another possible explanation is that the AGT T allele frequency may decrease with age, which was reported from the United Arab Emirates [ 48 ]. The prevalence of hypertension increases with advancing age. According to the National Health and Nutrition Examination Survey III (NHANES III) prevalence estimates for the years 1988–1994, American Whites aged 55 to 64 years have a more than threefold higher prevalence of hypertension (42.1%) than those aged 35 to 44 years (11.3%) [ 49 ]. Frossard et al detected that AGT T allele frequency decreased with age in the United Arab Emirates[ 48 ]. The ACE DD genotype was found associated with human longevity [ 50 ]. In the present study, normotensives are significantly younger than hypertensives (41 ± 12 yrs vs. 59 ± 13 yrs). It is conceivable that many of the young individuals are at hypertension risk because of their ACE or AGT genotype, but have not yet shown hypertension at the time of genotyping, and may develop hypertension in their older age. This might lead to some misclassifications and hence reduce the power of this study. On the other hand, two studies of German populations [ 32 , 51 ] reported that the AGT T allele was a risk factor for hypertension in individuals younger than 50 years of age. In the present study, young hypertensives had a higher frequency of the AGT T allele than elderly hypertensives (0.36 vs. 0.32), but the difference didn't reach statistical significance (p = .22). It is possible that the small percentage (24.9%) of the studied hypertensives under 50 years of age biased the finding. A number of studies [ 51 - 54 ] examined the relationship between RAS genotype and the severity of hypertension, but their results were contradictory. In accordance with two [ 52 , 54 ] of them including one German dataset, the present study fails to find an effect of the AGT or ACE genotype on the severity of hypertension. Nevertheless, in the present study, hypertensives that carried at least one copy of the AGT T allele (TT or MT: n = 397) were less likely to take two or more antihypertensive medications than those with MM genotype (n = 225) (odds ratio -TT or MT vs. MM: 0.797; 95% CI: 0.57 to 1.12; P = .185), and their average number of antihypertensive drugs was lower (2.09 vs. 2.20; P = .276). Despite not reaching statistical significance, this observation was in contrast to Schunkert et al's study [ 51 ] on another German population (subjects initially participated in the MONICA Augsburg cohort baseline survey), which found that the carriers of the AGT T allele (n = 418) had a 2.1-fold higher probability of taking two or more antihypertensive drugs than individuals with the MM genotype (n = 216). It is worth pointing out that in the present study, the number of subjects taking antihypertensive medications is much larger than in Schunkert et al's study (622 vs. 143). While the data is far from statistical significance, the trend is in line with those findings that associate rather the M allele with hypertension in the present study. The effect of a combination of RAAS genes' polymorphisms on blood pressure has been investigated in the participants to the Olivetti Heart Study [ 17 ], in which the MM, AA, CC, DD/ID genotype was detected to be associated with a substantially higher prevalence of hypertension in the absence of detectable effects of each individual polymorphism at any single locus. The present study showed very similar findings in women: MM, DD/ID genotype significantly increased the odds for hypertension (odds ratio: 1.45; 95% CI: 1.04 to 2.02), while TT, DD/ID and TT, II/ID were significantly associated with lower prevalence of hypertension (odds ratio: 0.33, 95% CI: 0.11 to 0.99; odds ratio: 0.31, 95% CI: 0.10 to 0.92). The risk of hypertension in the women with TT, DD/ID and TT, II/ID, however, didn't change much compared with those with TT alone (odds ratio: 0.31, 95% CI: 0.12 to 0.83). This suggests that there is only a slight synergistic effect between the AGT and ACE genes. Although in most surveys the prevalence of hypertension appears to be equal in women and men [ 55 ], sex-specific effects of ACE or AGT genes on hypertension have been reported recently [ 16 , 43 ]. For instance, Sethi et al. [ 43 ] found the AGT TT associated with an increase in risk for hypertension in women but not in men from the Copenhagen City Heart Study with a population of 9100 subjects, and an association of the ACE DD genotype with increased diastolic blood pressure was detected in men, but not in women from the Framingham Heart Study [ 16 ]. In the present study, the AGT TT genotype was negatively correlated to hypertension in women only while no sex-specific effect of the ACE gene was shown. It is possible that the fact is covered by the different gender distributions: in this population, there are more women in normotensives than in hypertensives (55.6% vs. 46.8%, P = .001). In addition to the factor declared above, the result may be influenced by the study design and the composition of the sample population. The study design itself may influence the results. As mentioned above, this study was a cross-sectional study where subjects were assessed at a single time, and at that time most of the controls were younger than 50 years old. Animal studies have shown that hypertension genes may be activated for only certain periods during the life history of an organism [ 2 ]. Hence, some of them might develop hypertension at an older age, resulting from the activated hypertension genes. Longitudinal studies are needed to further examine the relationship between hypertension and genes at different ages. The population can be described as static population with a mixed Germanic-Slavonic background. Due to the location (a provincial town on the German-Polish border) and political and historical setting (little population fluctuation during the over 140 years of imperial, fascist and socialist rule, no influx due to lack of economic attractivity after reunification), the population may be assumed as homogeneous. Several recent studies [ 56 - 61 ] have reported significant differences in prevalence of hypertension between Germany and Poland, which, however, are assumed to be largely dependent on life-style differences, mostly salt intake. These differences, however, are unlikely to play a role in the study population due to its homogeneity with regards to life style preferences following successful assimilation over many generations. In the case of ACE polymorphism with all allele frequencies greater than 15%, there is no need to examine population stratification [ 62 ]. This becomes more urgent for AGT where there is no Hardy- Weinberg equilibrium. As the sample information, however, does not include data on the ethnic background of the probands, additional haplotyping carried out on the samples would not have allowed to rectify for the historical ethnic background (Germanic versus Slavonic).[ 62 , 63 ] In the meantime, it should be noted that the present study was carried out on an unusually large population (second only to one in 63 studies included in Sethi's meta-analysis[ 22 ]). Given the large homogeneous population-based sample, the findings cannot be attributed to simple selection bias. Therefore, the finding that the AGT TT genotype associated with a decreased risk for essential hypertension is likely to be true for this particular German population. Conclusions Despite the limitations mentioned, this cross-sectional study does not support the notion that the ACE I/D polymorphism contributes to the prevalence and severity of essential hypertension. However, the M235T TT genotype of AGT gene was detected to confer a significantly decreased risk for the prevalence of hypertension in women from this particular population. Despite the large sample size, the present study fails to revise the odds ratio in a meta-analysis of a total of 25 studies on the association between the AGT M235T polymorphisms and hypertension in caucasians. This observation may reflect a very specific local inheritance pattern of the AGT genotypes. If this holds true, studies aiming at drug development based on genomic traits must be scrutinized rigorously as therapeutic recommendations may be valid for selected subpopulations only[ 64 ]. Competing interests The author(s) declare that they have no competing interests. Authors' contributions M.N. designed and initiated the study, analyzed the samples and wrote part of the manuscript. A-L.Z. and M.L. did the statistical analysis. A.M. devised the concept for meta-analysis and wrote the manuscript. L.P. created the figures. M.N. and A.M. should be considered as joint co- authors. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC546009.xml
368178	A Holistic Approach to Evaluating Cellular Communication Pathways	null	To function properly, cells must keep constant tabs on the environmental conditions around them, such as the presence of growth hormones in the blood or the proximity of neighboring cells. These external cues are relayed into the cell through a cascade of chemical and physical reactions referred to as signal transduction. Signal transduction pathways inform and regulate almost all activity within the cell, from protein production to cell division. Understanding these processes is fundamental to biology, but the sheer number of molecules and interactions in some pathways makes thorough documentation difficult. Taking a holistic approach that combines both computational models and experimental manipulations, scientists have described the web of interactions involved in the aryl hydrocarbon receptor (AHR) signal transduction pathway. AHR belongs to the Per–Arnt–Sim (PAS) superfamily of sensor molecules that regulate functions like development, the sleep-wake cycle, and cellular reaction to oxygen deprivation. Unlike many receptors that are embedded in the cell membrane, AHR floats freely in the main body of the cell, called the cytosol. There it waits for a stimulus or ligand, such as a dioxin molecule, to enter the cell and bind to it. Once bound, AHR undergoes a host of changes, glomming on to additional molecules before it enters the cell nucleus and acts as a transcription factor, initiating the production of enzymes to digest foreign, or xenobiotic, compounds. The AHR pathway is a curiosity; though found in all vertebrates, the natural, or endogenous, ligand remains unknown. Without this knowledge, researchers are limited in the kind of experiments they can perform to evaluate the pathway. Protein-interactive-network for AHR signaling Christopher Bradfield and colleagues used yeast as a model system to elucidate the steps involved in this pathway, which regulates vertebrate cell response to pollutants like dioxins. To first assess the molecules involved in the AHR pathway, the team used 4,507 yeast “deletion” strains, each strain missing one gene from its genome. They then inserted the AHR gene into the strains using small rings of movable DNA called plasmids. Though yeast does not naturally possess AHR, it is an ideal genetic model for studying signaling pathways due to its quick generation time, small, well-characterized genome, and similarity to vertebrate systems. Bradfield's team exposed each strain to a receptor stimulus or agonist and screened them for AHR response. If a deletion strain showed significantly reduced activity, they concluded that the missing gene was a key component to the signal pathway. The researchers identified 54 genes that had a significant influence on AHR response. Only two of these genes, termed modifiers, had been previously identified. Signaling pathways usually boil down to a series of discrete steps. To identify steps of the AHR pathway, the researchers constructed a spider web-like map called a "protein interaction network," or PIN, based on previously known interactions between the proteins encoded by the 54 modifier genes. The resulting map revealed groups of highly connected, related modifiers, which the authors proposed to be steps in the pathway. Though other studies have used the newly developed PIN strategy to investigate cellular processes, Bradfield's team also annotated their PIN through a series of experiments both to support the identity of and to better understand the protein groups, referred to as functional modules. With tests based on discrete receptor signaling events, known active structural regions, reaction to different types and concentrations of agonists, and functional location within the cell, Bradfield's team organized the functional modules into five steps. One group of modifiers is involved in AHR folding, the conformational change that occurs when the receptor binds to a toxin. With the help of other modifiers, the new AHR complex is then translocated into the cell nucleus. Once in the nucleus, a series of modifiers assist the AHR in its role as a transcription factor. The researchers also identified a step in the pathway that controls production of AHR itself and another unknown "step" that takes place inside the nucleus. As AHR is thought to be a prototype PAS receptor, understanding the steps in this pathway will likely guide future research on the entire family, allowing scientists to study in detail individual steps in these complex pathways. The highly integrated method reported here could also be used to study most other mammalian signaling pathways, giving scientists a new tool as they attempt to understand how cells respond to their changing environment.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC368178.xml
529431	From Registration to Publication	The PLoS Medicine editors argue that all trial registries, reports, and databases should be freely available online	In a compelling essay in this issue of PLoS Medicine , Mike Clarke, the director of the United Kingdom Cochrane Centre, lays down a challenge to clinical researchers and journal editors [ 1 ]. He argues that researchers should do a study only if there is a systematic review that shows that the new study is needed. If no review exists, the researchers should do one themselves before embarking on their research. And journals, he argues, should publish a study only if an updated systematic review is incorporated into the study, or published alongside it or shortly thereafter. How should editors respond to his challenge? First, we would argue that by the time a paper is sent to a journal, it is surely too late in the process to be insisting on systematic reviews. If a clinical trial report meets our criteria for originality, importance, and quality, it makes little sense for us to reject it just because the authors failed to systematically review the literature when designing their study. The time to mandate that researchers do a review is much earlier—when they apply for funding, register their trial, or seek ethics committee approval. There is no doubt that the best research builds on previous knowledge. But unfortunately, the current medical publishing system hides much of this knowledge behind subscription or “pay per view” charges, which discriminates against researchers who do not work for well-funded institutions. A group of researchers in Indonesia, for example, recently told a depressingly familiar story of trying to search the medical literature in preparation for a research project [ 2 ]; access barriers got in their way. So our second response to Clarke's challenge is that it will remain difficult for researchers, particularly in resource-poor settings, to do systematic reviews unless the medical literature is made a freely available public resource. Many clinical trials, especially negative ones, remain unpublished, which prevents researchers from reviewing all the data on an important health issue. There are two main reasons why certain trials are not published: one is that the pharmaceutical industry has a long history of suppressing data that are commercially unfavorable and the second is that medical journals and the popular media favor publication of positive over negative trials (after all, negative trials do not make for a provocative newspaper headline). While we support the recent announcement on trial registration by the International Committee of Medical Journal Editors—as a condition of considering a trial for publication, member journals will require registration of the trial in a public trials registry [ 3 ]—we believe that this policy addresses only part of the problem. The scientific literature will remain biased unless the publishing industry changes its practices and provides a place where the results from all registered trials can be published. PLoS Medicine is committed to publishing high-quality negative trials. In this issue, for example, we publish an important randomized controlled trial of a malaria vaccine in 372 Gambian men, which found that the vaccine was ineffective at reducing the natural infection rate. The internet makes it possible for every single clinical trial to be publicly and seamlessly tracked through three tiers. The first tier is registration in a publicly available database. The second is the publication of a peer-reviewed summary of every trial, regardless of its outcome, in a traditional journal format, with annotations and critiques that help readers understand the trial's implications. The third is the deposition of detailed trial data in a structured, computable format that allows sophisticated searching and analyses across trials. This format will allow the development of better tools to help clinicians apply trial results to their practice. For trial data to be as useful as possible, all three tiers must be publicly accessible. Assessment of each trial's validity is critical, but should not stop crucial information about all trials being placed in the public domain. Trial registries exist, such as ClinicalTrials.gov and the International Standard Randomised Controlled Trial Number registry. Moreover, many trials are registered in a semi-public database maintained by the United States Food and Drug Administration, and there are compelling arguments (which Turner articulates in an essay published online ahead of our December issue [ 4 ]) for making this a truly public resource. Publicly accessible trial databases (such as the Trial Bank Project at http://rctbank.ucsf.edu ) are under development. And as a publisher committed to open access, PLoS will provide the second, essential tier—journals capable of peer reviewing and publishing an annotated report of every trial. Traditional medical journals, with their subscription-based model, are unlikely to be able to provide this service, because in order to attract subscribers they need to publish only the highest-profile trials. We believe that an open-access model—in which the research funder pays a publication fee to recover the costs of peer review and for hosting the report on a secure server—is the best mechanism for creating such venues. We are working to make that happen. Returning to Clarke's challenge, our final response is to say that we have a bold vision of a freely accessible online world of clinical trials—from registration to annotated summaries to trial databases. That world would be even richer if every systematic review were made freely available. We challenge the Cochrane Collaboration to put the full text of all of its reviews into the public domain. We hope the Cochrane Collaboration will join us in the open-access revolution.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC529431.xml
529419	A Free Community Approach to Classifying Disease	Defining and classifying disease is at the heart of medical practice, but the process is slow and laborious. A new "open source" approach could be faster and more democratic	Defining and classifying disease is at the heart of medical practice. But the standard approach to classification is slow and laborious. A new approach promises to revolutionise the way in which we classify disease. It involves the free and public sharing of information via the Internet—the so-called open-source, or, perhaps more appropriately termed, “free community,” approach (R. M. Stallman, personal communication). The International Society for Neuropathology is the first worldwide professional medical organisation to adopt such an approach with its International Classification of Diseases of the Nervous System (ICDNS; see http://www.ICDNS.org ). The main characteristics of the ICDNS are free collaboration via the Internet, online access to all collaborative tools via the World Wide Web, global participation, and democratic decision making [ 1 ]. Why We Need a New Approach Before a disease can be recognised, its nature and the conditions surrounding it must be determined in order to establish criteria for its definition. The more precise a disease definition, the greater the benefit is for the patient, especially where specific treatments are available. Once individual diseases are defined, they can be classified, resulting in the creation of conceptual links that are fundamentally important for medical practice and the advancement of medical knowledge. One example is the conceptual linking of Pick disease, Alzheimer disease, progressive supranuclear palsy, and corticobasal degeneration as members of the group of tauopathies. However, the way in which medical classifications of disease traditionally evolve is problematic. Usually, small groups of experts meet and decide on a classification that fits best with their personal experience. Classifications then change when new scientific developments are applied to link or separate different conditions. An example is the identification of several pathologically distinct types of frontotemporal dementia based on the application of immunohistochemical staining for tau protein and ubiquitin. The wider medical community subsequently validates these new schemes, provided there is agreement on the basic aspects of any new taxonomic concept. Often, however, consensus only emerges after many years and even decades of controversy and dispute. The World Health Organization's classification of brain tumours [ 2 ] is an example of a classification that has taken decades to mature. Thus, the established process is not very effective and is undoubtedly time consuming. It is also occasionally politicised, as “egos” may be unable to resist the temptation of leaving their personal mark, while ignoring the cultural benefit of consensus agreement that results in knowledge that is usable by everyone. New disease entities are presently emerging at a much higher rate because of advances in biomedicine that were triggered by the Human Genome Project. More and more diseases are being redefined according to molecular criteria. The Lewy body diseases, which share a pathological aggregation of the protein alpha-synuclein (“alpha-synucleinopathies”), are an example of a disease subset now defined by a common molecular pathology. The large field of pathology and the neurosciences are two areas where the translation of morphological phenotypes into molecularly defined entities is already well underway. With the pace of change accelerated by advances in molecular science, we need a much more effective way to develop the debate about medical classifications. Open Source and the ICDNS One effective way to further develop this debate is to adopt the approach used by the free-software and open-source movements [ 3 ], which have spawned free software, free operating systems, and free scientific and medical journals. Open source has profoundly important implications for science, technology, and medicine. The development of global computer networks and the World Wide Web, in particular, have fostered the evolution of free and global sharing of intellectual property. The Open Source Initiative ( http://www.opensource.org ) is a nonprofit venture dedicated to managing and promoting the open-source idea ( Box 1 ). A related but more radical concept is propagated by the Free (as in freedom) Software Foundation ( http://www.fsf.org ). The creation of the GNU/Linux operating system ( http://www.gnu.org and http://www.linux.org ) has resulted from the work of both. Box 1. The Open Source Initiative “The basic idea behind open source is very simple: When programmers can read, redistribute, and modify the source code for a piece of software, the software evolves. People improve it, people adapt it, people fix bugs. And this can happen at a speed that, if one is used to the slow pace of conventional software development, seems astonishing… Open source software is an idea whose time has finally come. For twenty years it has been building momentum in the technical cultures that built the Internet and the World Wide Web. Now it is breaking out into the commercial world, and that's changing all the rules.” (It should be noted that the Open Source Software Initiative of 1998 was preceded by Richard Stallman's Free Software Movement of 1983 [ 5 ].) Source: Open Source Web site ( http://www.opensource.org ). The ICDNS was inspired by the free software and open-source approach to software development. The Council of the International Society for Neuropathology approved the ICDNS as a community activity at its last meeting in Turin, Italy, in September of 2003 [ 4 ]. The implications of ICDNS go far beyond defining neurological diseases. The benefits include the standardisation of neuropathological training programmes across continents and a new means of direct, professional communication between colleagues from countries all over the globe. How ICDNS Works Diagnostic criteria for all recognised neuropathological diseases are being published on the Web at http://www.ICDNS.org , where the global community of neuropathologists can judge them ( Figure 1 ). No named individual or national group is leading the initiative. Existing classifications are translated into a generic format, avoiding personal as well as institutional names to ensure consistent terminology between related disease processes. Figure 1 Pilocytic Astrocytoma Future brain tumour classifications will be decided in a democratic way. (Photo: Dr. F. Roncaroli, Department of Neuropathology, Imperial College London) Although still in its early days, definitions for Lewy body disease, Alzheimer disease, and several tumours are now online. Individual ICDNS members (membership is free) as well as expert interest groups propose core definitions, which are then posted so that the global consultation process begins via the World Wide Web. After an online discussion period, ICDNS members holding a specialist certification in diagnostic neuropathology are invited to vote. Comments made online by contributors become part of the history of a disease definition so that nobody is left out and divergent views are not forgotten. The discussion process is thereby open and democratic, allowing wide participation—including from individuals in developing countries who are often excluded in traditional academic discussions. Different countries around the world show variations in their use of diagnostic criteria and medical classifications, which, in turn, can lead to different treatment approaches. This can certainly create problems when trying to reach a global consensus. However, free access to the information held under the ICDNS open licence may help to minimise these problems by promoting and stimulating collaborative research and the exchange of scientific ideas across the globe. Certain diseases are far more common in particular parts of the world. In India, for example, neurotuberculosis, cerebral malaria, fungal infections of the central nervous system, human rabies, encephalomyelitis, and cerebrovenous thrombosis are more common than in most developed countries. While the conventional pathology of these diseases is well known—and in some cases we also have expert knowledge on their morphological phenotypes—their exact pathogenesis is not understood, and cellular as well as molecular knowledge is missing. The ICDNS is expected to stimulate local researchers to engage in collaborative international projects in which they can receive feedback via the global consultation process. Publication of ICDNS criteria occurs under a general public licence. This means that all text can be freely downloaded and republished, avoiding the need for defining basic facts over and over again. Both core definitions and comments may be used immediately for diagnostic purposes as outlined in the guidance section of the ICDNS Web site. Future Directions In the future, definitions of histopathological phenotypes may be linked to clinical as well as molecular biological datasets, such as those obtained from microarrays and combined with imaging parameters. It is obvious that expert consensus on histological phenotypes is required before “genome matching” and similar procedures can be applied to complex diseases in a meaningful way. Most diseases are presently still defined on the basis of their histopathology. Online forums to find diagnostic consensus will provide a very effective means of correlating descriptive data with molecular data. Subsequently, statistical clusters representing “signatures of disease” may be extracted from multidimensional data spaces that will be available online. This opens new roads to link with diagnostic and therapeutic approaches. It seems reasonable to propose that the adoption of the ICDNS paradigm by other medical specialties would facilitate the development of a comprehensive, global body of medical knowledge. Free access to this knowledge would allow novel, collaborative approaches to be developed to address the most pressing medical problems through supranational concerted efforts. The rather lowly role traditionally ascribed to the exercise of defining and classifying diseases would give way to an appreciation for the key importance of this process as a potentially powerful driver of change.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC529419.xml
544352	Wnt1 is epistatic to Id2 in inducing mammary hyperplasia, ductal side-branching, and tumors in the mouse	Background During pregnancy, the mammary glands from Id2 mutant animals are deficient in lobulo-alveolar development. This failure of development is believed to be due to a proliferation defect. Methods We have asked whether functional Id2 expression is necessary for Wnt induced mammary hyperplasia, side branching, and cancer, by generating mice expressing a Wnt1 transgene in an Id2 mutant background. Results We show in this work that forced expression of Wnt1 in the mammary gland is capable of overcoming the block to proliferation caused by the absence of Id2 . We also show that Wnt1 expression is able to cause mammary tumors in an Id2 mutant background. Conclusions We conclude that functional Id2 expression is not required for Wnt1 to induce mammary hyperplasia and mammary tumors.	Background Basic helix-loop-helix (bHLH) transcription factors such as MyoD, E12, and E47 are key regulators of gene expression and control many differentiation events during development [ 1 - 3 ]. These transcription factors bind E-box or E-box-like sequences as homo-or heterodimers, and control the transcription of target genes containing these sequences in their promoters. The HLH domains dimerize with each other, whereas the basic domains bind to DNA. The Id (Inhibitor of DNA binding) proteins are HLH proteins that lack a basic domain. Id proteins act as dominant inhibitors of bHLH transcription factors by blocking their ability to bind to DNA and activate gene transcription [ 2 , 3 ]. Since the bHLH proteins regulate cell-type specific gene expression during cell commitment and differentiation, the formation of inactive heterodimers of bHLH proteins with Id proteins inhibits the commitment and differentiation the bHLH proteins promote. There are 4 mammalian Id genes, which show differences in their patterns of expression and function [ 2 , 3 ]. One of them, Id2 , is expressed in glandular and ductal epithelium of the mouse mammary gland and has also been implicated in its development. Mammary glands of female mice that are homozygous mutant for Id2 have impaired lobulo-alveolar development [ 4 ]. In several tissues, including colon tumors induced by activation of the Wnt pathway, the expression of Id2 is regulated by Wnt-β catenin signaling [ 5 , 6 ]. It has been proposed that Wnt signaling may inhibit differentiation and promote the maintenance of a proliferative state by increasing Id2 expression, thereby leading to cancer. We have asked therefore whether functional Id2 expression is necessary for Wnt induced mammary hyperplasia, side branching and cancer, by generating mice expressing a Wnt1 transgene in an Id2 mutant background. Methods We used heterozygous Id2 males and females on a 129/Sv background. Id2 genotyping was done by PCR (95C, 5 min; 62C, 1 min, 72C, 1 min, 95C,1 min, 30 cycles; 62C, 1 min, 72C, 5 min) using primers Id2 -S (5'-tctgagcttatgtcgaatgatagc-3'), Id-2AS (5'-cgtgttctcctggtgaaatggctg-3'), and neo 1 (5'-tcgtgctttacggtatcgccgctc-3"). Hemizygous transgenic MMTV-Wnt1 males on a mixed FVB/BL6/SJL background were obtained from Yi Li in the H.Varmus laboratory. Genotyping was done by PCR (94C, 4 min; 94C, 45 sec, 55C, 30 sec, 72C, 60 sec, 30 cycles; 72C, 10 min) using Wnt1 (5'-gaacttgcttctcttctcatagcc-3') and SV40 (5'-ccacacaggcatagagtgtctgc-3') primers that produce a 350 bp product in transgenic mice. Carmine staining Five mammary glands per mouse were removed and fat and muscle were dissected away. The glands were flattened between two slides and flooded with Carnoy's fixative (3:1 95% ethanol to glacial acetic acid) and fixed overnight. They were then de-fatted in 3 changes of acetone, rehydrated, stained overnight in 0.2% carmine and 0.5%KSO 4 , dehydrated, cleared in xylene, and mounted in Permount. Results We used mice carrying a transgene in which Wnt1 is under the control of the promoter of the Mouse Mammary Tumor Virus (MMTV-Wnt1 Tg) [ 7 ] and we crossed these to Id2 loss of function mutant mice [ 4 , 8 ]. Crosses were set up to avoid reliance on Id2 -/- or Wnt1 transgenic mothers, as these animals cannot feed their young [ 4 , 7 ]. Id2 +/- females were crossed with MMTV-Wnt1 hemizygous transgenic males, producing 7 MMTV-Wnt1 Tg; Id2 +/- males (Figure 1 ). These males were then crossed with Id2 +/- females to produce the experimental and control classes of virgin female mice: MMTV-Wnt1 Tg; Id2 -/-, MMTV-Wnt1 Tg ; Id2 +/-, and MMTV-Wnt1 Tg; Id2 , as well as smaller numbers of animals in Id2 -/-; Id2 +/-; and WT classes. (Figure 1 ) The subject animals were kept in mixed groups in autoclaved cages because Id2 -/- mice have an immunologic defect. Even with this care, 50% die before maturity [ 8 ]. Id2 -/- mice were born in sub-Mendelian ratios, they were smaller than litter-mates, and several died of unknown causes. We examined the morphology of the mammary gland. At 3, 4.5, and 6 months the ductal branching patterns in normal mammary glands of 24 virgin mice from all six classes were examined in carmine stained whole mounts (Figure 2 ). As has been previously observed by others, the MMTV-Wnt1 Tg female glands had excessive ductal side branching compared to those of WT females [ 7 ] while Id2 +/- and Id2 -/- females glands were similar to those of WT females [ 4 ]. Glands from MMTV-Wnt1 Tg ; Id2 +/- and MMTV-Wnt1 Tg ; Id2 -/- mice had branching patterns resembling those of MMTV-Wnt1 Tg females at 3 months (Figure 2 ). At six months the three classes of transgenic mammary glands had very extensive, dense hyperplasia and side branching resembling that of pregnant wild type mice, while the six month virgin Id2 +/- and Id2 -/- glands had no additional branching and the six month virgin WT glands had moderate additional branching. Therefore, it appears that forced expression of Wnt1 in virgin mammary glands can overcome the absence of Id2 and lead to a highly branched ductal tree resembling the tree achieved normally during pregnancy. In parallel, we examined tumor incidence in the animals. We excluded MMTV-Wnt1 Tg ; Id2 -/- females that died without developing tumors before 34 weeks, our endpoint, leaving only 8 animals in this group. Mice were examined and palpated weekly for mammary tumors. The smallest tumors detected using this method were 0.5 cm in diameter, but could be as large as 2 cm. The MMTV-Wnt1 Tg ; Id2 +/+ and MMTV-Wnt1 Tg ; Id2 +/- cohorts consisted of 21 and 23 females respectively. All three cohorts showed a similar rate of tumorigenesis (Figure 3 ). We concluded that Wnt1 is epistatic to Id2 in tumorigenesis, just as it is in promoting hyperplasia and side branching of the mammary gland (Figure 2 ). Discussion The lack of Id2 , a Wnt target, has severe consequences for mouse mammary gland development. During pregnancy, the Id2 mammary gland is deficient in lobulo-alveolar development. This failure of development is believed to be due to a proliferation failure rather than precocious differentiation of the mammary epithelia [ 4 ]. We show in this work that forced expression of Wnt1 in the mammary gland is capable of overcoming this block to proliferation. Although many targets of the Wnt pathway have been identified (see ), the mechanism through which hyperplasia and side branching is promoted by Wnt1 expression in the virgin mammary gland is unknown. Our results demonstrate that Wnt1 is not operating solely through Id2 or that it is not operating through Id2 at all. Another known Wnt target with a similar loss of function phenotype is Cyclin D1 [ 9 ], a protein whose expression promotes advancement through the cell cycle and whose over expression results in hyperplasia and tumors in the mammary gland [ 10 ]. However, when Wnt1 is expressed in Cyclin D1 -/- mice, only a slight reduction in tumorigenesis is observed [ 11 ], suggesting that the Wnt1 pathway also does not operate primarily through Cyclin D1. Furthermore, over expression of Cyclin D1 did not promote lobulo-alveolar development in Id2 -/- mice [ 12 ], a result that is in contrast to the dense side branching of the Wnt1 Id2 -/- phenotype, suggesting that Wnt1 signaling is independent of both Cyclin D1 and Id2 in the mammary gland. Conclusions By showing that forced expression of Wnt1 in the mammary gland is capable of overcoming the block to proliferation caused by the absence of Id2 , we conclude that functional Id2 expression is not required for Wnt1 to induce mammary hyperplasia and mammary tumors. Competing interests The author(s) declare that they have no competing interests. Author's contributions SM and CR carried out the experiments. YY participated in the design of the study. SM and RN conceived of the study, participated in its design and coordination and wrote the manuscript. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544352.xml
520818	Additional collection devices used in conjunction with the SurePath Liquid-Based Pap Test broom device do not enhance diagnostic utility	Background We have previously shown that use of an EC brush device in combination with the Rovers Cervex-Brush (SurePath broom) offered no significant improvement in EC recovery. Here we determine if use of additional collection devices enhance the diagnostic utility of the SurePath Pap for gynecologic cytology. Methods After informed consent, 37 women ages 18–56 receiving their routine cervical examinations were randomized into four experimental groups. Each group was first sampled with the SurePath broom then immediately re-sampled with an additional collection device or devices. Group 1: Rover endocervix brush (n = 8). Group 2: Medscand CytoBrush Plus GT (n = 7). Group 3: Rover spatula + endocervix brush (n = 11). Group 4: Medscand spatula + CytoBrush Plus GT (n = 11). Results Examination of SurePath broom-collected cytology yielded the following abnormal diagnoses: atypia (n = 2), LSIL (n = 5) and HSIL (n = 3). Comparison of these diagnoses to those obtained from paired samples using the additional collection devices showed that use of a second and or third device yielded no additional abnormal diagnoses. Importantly, use of additional devices did not improve upon the abnormal cell recovery of the SurePath broom and in 4/10 cases under-predicted or did not detect the SurePath broom-collected lesion as confirmed by cervical biopsy. Finally, in 36/37 cases, the SurePath broom successfully recovered ECs. Use of additional devices, in Group 3, augmented EC recovery to 37/37. Conclusions Use of additional collection devices in conjunction with the SurePath broom did not enhance diagnostic utility of the SurePath Pap. A potential but not significant improvement in EC recovery might be seen with the use of three devices.	Background In gynecologic cytology, sampling of both the ecto and endocervix is critical to increasing Pap test sensitivity [ 1 ]. Controversy still exists, however, as to whether "all-in-one" broom-type devices appropriately sample the cervix. While agreement has been reached on the importance of sampling the transformation zone [ 2 ], concern as to how proximal the transformation zone is to the face of the cervix [ 3 ] has lead to lingering doubt over how effective current broom-type sampling devices are compared to a separate spatula and endocervical brush [ 4 ]. This debate has been re-energized by the generalized adoption of the liquid-based Pap test in the United States. Currently, two FDA approved liquid-based Pap tests are available, one manufactured by Cytyc (Boxborough, MA) and one manufactured by TriPath Care Technologies (Burlington, NC). Currently, the ThinPrep Pap Test (Cytyc) and the SurePath Pap (TriPath Care Technologies) offer two types of sampling devices a broom-type device or a spatula + cytobrush combination. It has been reported, that the use of the broom-type device for both the ThinPrep Pap Test and the SurePath Pap appears to under-sample the endocervix resulting in increased limited-bys due to lack of an EC component [ 4 , 5 ]. We have not observed this phenomenon and have previously shown that the SurePath Pap reduced by 33% the number of limited-by cases due to lack of an EC component when compared to the traditional Pap test when the SurePath Pap utilized the SurePath broom and the traditional Pap test utilized the spatula + EC brush combination [ 6 ]. In that failure to sample the endocervix can coincide with failure to sample the transformation zone we sought, in this study, to determine if additional sampling devices used in conjunction with the SurePath broom improved SurePath Pap EC recovery and/or increased SurePath Pap diagnostic effectiveness. Methods Cervical/endocervical sampling After study design approval from the Carle Clinic Association Institutional Review Board and informed consent, 37 women ages 18–56 receiving their routine cervical examinations were sampled with the SurePath broom. This device, which is packaged with the SurePath Pap, is the Rovers Cervex-Brush (Rovers Medical Devices, Oss, The Netherlands). Its use followed the manufactures recommendations of 5 full clockwise rotations. The same patient was immediately re-sampled with either the Rovers endocervix brush, patient group 1; the Medscand Cytobrush Plus GT (Medscand Medical, Malmö, Sweden), patient group 2: the Rovers endocervix brush + Rovers Spatula, patient group 3; or the Medscand Cytobrush Plus GT + Medscand Pap Perfect Spatula, patient group 4. All devices had "pop-off" heads. The SurePath broom device was collected into CytoRich Preservative vials (TriPath Care Technologies, Burlington, NC) and processed routinely using the PrepStain Slide Processor (TriPath Care Technologies, Burlington, NC). In samples using multiple collection devices, all devices, including the SurePath broom, were placed in a single collection vial and processed as above. Slide diagnosis The diagnostic terminology used was derived from the 1991 revision of the Bethesda System (TBS) [ 7 - 9 ]. The diagnostic categories available were: 1) no intraepithelial lesion (NIL), 2) inflammation/repair (BCC), 3) atypical squamous cells of uncertain significance (ASC-US), 4) low-grade squamous intraepithelial lesion (LSIL), 5) high-grade squamous intraepithelial lesion (HSIL) 6) squamous cancer, 7) atypical glandular cells of uncertain significance (AGUS) and 8) glandular cancer. ECs were considered present if they appeared as a group of 6 or more cells. Slides were reviewed following standard practice. Slide screening was performed blinded to the sample collection device type. Screening of alternate device collections from the same patient were screened by the same cytotechnologist. Screened slides were re-reviewed by a senior cytotechnologist and a pathologist for diagnoses other than NIL. Re-reviewers were blinded to device type and all slides from a particular patient were reviewed by the same senior cytotechnologist and pathologist. Quality control rescreen of slides did not result in revision of a diagnosis. Cytology/cervical biopsy comparison All cases where the cytology diagnosis was ASC-US or more serious underwent colposcopic-guided cervical biopsy (cervical biopsy). Cases were excluded from analysis if the: 1) cytology and corresponding tissue diagnosis were separated in time by more than 6 months; 2) cytology and/or corresponding cervical biopsy were not performed and interpreted within the Carle Clinic Association/Hospital system. In cases where multiple cervical biopsies were performed, the cytology closest in temporal relationship to the cervical biopsy was correlated. No cervical biopsies met the exclusion criteria. Statistical analysis All analyses were performed using SAS statistical software (Cary, NC). Data comparisons were made using the Student's paired t-test, the Sign Test and the Wilcoxon Signed Rank test for analysis of non-parametric data. Results Diagnostic utility of the SurePath broom with supplemental EC sampling We have previously shown that use of the Surgipath C-E brush (Richmond, IL) in combination with the SurePath broom did not increase EC recovery in women undergoing a SurePath Pap [ 6 ]. This previous study, however, did not investigate whether use of an EC brush enhanced SurePath Pap diagnostic utility. Therefore, to determine if an EC brush aided recovery of cytologically abnormal cells, EC brushes from Rovers and Medscand were examined. Tables 1 and 2 show results of women who were first sampled with the SurePath broom then immediately re-sampled with either a Rovers (Table 1 ) or Medscand EC brush device (Table 2 ). In group 1 patients (Table 1 ), 1/8 had LSIL identified by cytology after use of the SurePath broom. In addition, EC cells were identified in all 8 cases. Immediate re-sampling of group 1 patients with the Rover brush did not result in increased abnormal diagnoses. In fact, 3/8 cases had less than 5000 squamous cells/slide and required a diagnosis of QNS. In these QNS cases, no EC cells were seen. Importantly, follow-up cervical biopsy confirmed the SurePath broom-identified LSIL. This case was associated with a Rovers brush QNS. Table 1 Broom Followed By Rovers Endocervix Brush Broom Diagnosis EC Rovers Diagnosis EC Cervical Biopsy Diagnosis NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes QNS No Ø NIL Yes QNS No Ø LSIL Yes QNS No LSIL * EC , endocervical cells; NIL , negative for intraepithelial lesion; QNS , quantity not sufficient for diagnosis; Ø , no biopsy performed P value for diagnosis: paired t test = 0.14, Sign Test = 0.25, Wilcoxon = 0.25 P value for presence of ECs: paired t test = 0.08, Sign Test = 0.25, Wilcoxon = 0.25 Table 2 Broom Followed By Medscand CytoBrush Plus GT Broom Diagnosis EC Medscand Diagnosis EC Biopsy Diagnosis NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes NIL No Ø ASC-US Yes ASC-US Yes NIL HSIL Yes HSIL Yes HSIL HSIL Yes HSIL Yes HSIL * EC , endocervical cells; NIL , negative for intraepithelial lesion; QNS , quantity not sufficient for diagnosis; Ø , no biopsy performed P value for diagnosis: paired t test = 1.0, Sign Test = 1.0, Wilcoxon = 1.0 P value for presence of ECs: paired t test = 0.36, Sign Test = 1.0, Wilcoxon = 1.0 When group 2 patients were examined by cytology after using the SurePath broom (Table 2 ), 1/7 patients had ASC-US and 2/7 had HSIL. As above, adequate EC cells were identified in all SurePath broom cases. Immediate re-sampling of group 2 patients with the Medscand brush did not provide additional diagnostic utility. Importantly, follow-up cervical biopsy confirmed the SurePath broom-identified HSILs. In one of these HSIL cases, the Medscand brush was associated with a QNS. Taken together these findings indicate that addition of a Rover endocervix brush or Medscand CytoBrush Plus GT to the SurePath broom does not improve SurePath Pap abnormal cell or EC recovery. Diagnostic utility of the SurePath broom with supplemental ectocervical and endocervical sampling As shown above, use of an endocervical sampling device in addition to the SurePath broom did not enhance the usefulness of the SurePath Pap. To determine if a spatula plus an EC brush increased recovery of diagnostic cells over the SurePath broom, ectocervical spatulas from Rovers and Medscand were examined. Tables 3 and 4 show results of women who were first sampled with the SurePath broom then immediately re-sampled with either a Rovers spatula + endocervix brush (Table 3 ) or a Medscand PAP Perfect Spatula + CytoBrush Plus GT (Table 4 ). In group 3 patients (Table 3 ), 4/11 had abnormal cytology (1 AGUS, 3 LSIL) identified by use of the SurePath broom. EC cells were identified in 11/11 cases. Immediate re-sampling of group 3 patients using the Rovers devices resulted in 4 abnormal Pap diagnosis (2 ASC-US, 1 LSIL, 1 LSIL + AGUS) in the same four women. Complete diagnosis concordance, however, was seen in only one case. Follow-up cervical biopsy of these abnormals demonstrated 1 chronic cervicitis, 2 LSIL and 1 HSIL. Table 3 Broom Followed By Rovers Endocervix Brush + Rovers Spatula Broom Diagnosis EC Rovers Diagnosis EC Cervical Biopsy Diagnosis NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø AGUS Yes ASC-US Yes Chronic Cervicitis LSIL Yes ASC-US Yes LSIL LSIL Yes LSIL Yes LSIL LSIL Yes LSIL, AGUS Yes HSIL * EC , endocervical cells; NIL , negative for intraepithelial lesion; Ø , no biopsy performed P value for diagnosis: paired t test = 0.34, Sign Test = 1.0, Wilcoxon = 1.0 P value for presence of ECs: paired t test = 1.0, Sign Test = 1.0, Wilcoxon = 1.0 Table 4 Broom Followed By Medscand CytoBrush Plus GT + Medscand Pap Perfect Spatula Broom Diagnosis EC Medscand Diagnosis EC Cervical Biopsy Diagnosis NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes NIL Yes Ø NIL Yes QNS No Ø NIL No NIL Yes Ø LSIL Yes ASC-US Yes LSIL HSIL Yes ASC-US Yes HSIL * EC , endocervical cells; NIL , negative for intraepithelial lesion; QNS , quantity not sufficient for diagnosis; Ø , no biopsy performed P value for diagnosis: paired t test = 0.1, Sign Test = 0.25, Wilcoxon = 0.25 P value for presence of ECs: paired t test = 0.34, Sign Test = 1.0, Wilcoxon = 1.0 When group 4 patients were examined cytologically after sampling with the SurePath broom (Table 4 ), 1/11 patients had LSIL and 1/8 patients had HSIL. EC cells were identified in 10/11 patients. Immediate re-sampling of group 4 patients with the Medscand spatula + EC brush yielded 2 diagnoses of ASC-US and 1 QNS. EC cells were, again, identified in 10/11 patients, however, the patients lacking EC cells with the SurePath and Medscand devices were not concordant. Follow-up cervical biopsy confirmed the SurePath broom results as LSIL and HSIL. Taken together these findings indicate that addition of both a spatula plus a brush device does not alter SurePath Pap diagnoses but may enhance EC cell detection. Discussion We have previously shown that the majority (88%) of SurePath Pap limited by diagnoses are due to lack of an EC component [ 6 ]. To overcome this problem, some clinicians have turned to using additional devices (usually an EC brush) in combination with the SurePath broom to attempt to increase the EC yield. The presumed rationale for use of an EC brush with the SurePath broom is that broom-type instruments do not reach into the cervical os as far as stand-alone brushes nor do they have bristles that are perpendicular to the handle. These concerns appear anecdotal but have concerned clinicians enough that TriPath Imaging sought and received recent approval for expanded labeling claims from the FDA to allow use of a spatula + brush combination with the SurePath Pap [ 10 ]. Our study was designed to test whether additional devices when used in combination with the SurePath broom enhanced recover of ECs or added diagnostic value to the SurePath Pap. The reason this study was undertaken was to demonstrate if the SurePath broom device was sufficient for obtaining an appropriate Pap sample. The strategy involved used a sequential testing method to show that added sampling of the cervix with spatula and/or brush devices did not recovery additional abnormal cells or additional ECs that altered the diagnostic results. These non-broom devices have different shapes and tinctoral qualities than the broom device, therefore, it is possible that they may sample portions of the cervix inaccessible to the broom, although no published evidence of such qualities exists. Importantly, this study was not designed to compare the SurePath broom to other devices used in the collection of SurePath Paps, instead, it was to designed to probe whether the SurePath broom alone was an appropriate device. This is important in light of the aforementioned SurePath Pap expanded labeling claim where clinicians might interpret such new FDA labeling as a repudiation of the broom device in favor of the spatula + brush combination. Currently, there is no available data detailing the results of this expanded labeling claim. In this study, we found that 3% of women sampled with just the SurePath broom lacked EC cells. These findings were consistent with but better than our previous report based on 3,994 women in which we found that 6% of SurePath Paps were "satisfactory for evaluation but limited by no EC cells" [ 6 ]. Other studies using a broom-type device have reported a range of EC absence from as low as 4.38% to as high as 29.2% [ 4 , 11 - 16 ]. This considerable variability in EC recovery is not easily understood nor is it clear why in only one [ 11 ] of these seven other studies was the absence of ECs lower than our previously observed rate of 6%. The next lowest EC absence rate observed in these seven studies was 10.1% [ 13 ]. In our current investigation, the likely reason why our EC absence rate was lower than our previous findings [ 6 ] was the use of a single nurse practitioner to collect all samples. Important to the SurePath broom is the flat and rounded sides to each bristle. Counterclockwise rotation brings the rounded bristle edges in contact with the cervix instead of the flat side reducing device effectiveness. In addition, a single experienced collector is more likely to achieve a satisfactory Pap sample than multiple inexperienced Pap collectors [ 17 ]. Another important reason why our previous and current studies show a relative low EC absence rate is that these studies utilized liquid-based Pap preparation. Most previous studies focusing on broom-type devices have compared their effectiveness to other sampling devices using traditional preparation. As we have shown, the SurePath Pap reduces by 33% limited bys due to lack of ECs when compared to the traditional Pap [ 6 ]. Debate over cervical sampling devices often focuses on EC sampling. Unfortunately, few studies are available that report both the EC absence rate and the abnormal cell detection rate in studies where multiple devices are compared. The retrospective study by Boon et al [ 11 ] stands out in that it suggests that there is a correlation between lack of endocervical cell recover with the Rovers Cervex-Brush and reduced detection of CIN III. Most other studies have shown equivalence between spatula + EC brush and broom-type devices. In fact, Buntinx et al in a meta-analysis of 29 trials that included 85,000 patients concluded that there was no significant difference between spatula + cotton swab or EC brush, extended tip spatula or broom-type device in recovery of abnormal cells [ 18 ]. This analysis did underscore that use of just an EC brush, cotton swab or Ayre spatula alone is inappropriate. Interestingly, they also found that obtaining a second cervical sample immediately after the first, even with the same device, increased abnormal cell detection by nearly 33%. We, as Tables 1 , 2 , 3 , 4 demonstrate, did not see this benefit when using multiple devices. In the 37 patients we immediately re-sampled after use of the SurePath broom, no additional abnormal diagnoses were rendered nor was additional diagnostic material provided that clarified a SurePath broom collected indeterminate diagnosis. As with any study, the strength of statistical analysis increases as the sample size is increased. However, even with small sample sizes, compelling results can be obtained if the statistical significance is large. Here the data was analyzed using three different nonparametric statistical tests (for non-continuous or non-numeric data) to ensure stringency. In addition, we chose to include the p-values for each of these statistical tests to show that multiple analyses yield the same result and that no single statistical test was chosen to favor a desired outcome. The hypothesis being tested, in this study, is that the use of additional collection devices in conjunction with the SurePath broom device does not enhance diagnostic utility. Normally, p-values <0.05 indicate that one should reject the hypothesis being tested and conclude enhanced utility. In this study, the large p-values generated from analysis of the data indicate a very high probability that the hypothesis be rejected and that no enhanced diagnostic utility is realized with the use of additional collection devices. Since liquid-based Pap testing is relatively new, little work has been done to examine sampling device effectiveness utilizing this technology. Selvaggi et al compared the ThinPrep broom to the ThinPrep spatula + cytobrush and the ThinPrep broom +cytobrush [ 4 ]. These authors found that the EC component was missing in 24%, 10% and 13% of cases, respectively. However, no examination of diagnostic utility was included so it is not clear how these findings relate to device effectiveness in a liquid-based setting. In addition, their findings differed significantly from our previous examination of broom + brush combination using liquid-based preparation. When we examined 23 women for EC adequacy using both the SurePath broom and an EC brush, we found that the EC brush provided no additional benefit over the broom in the SurePath Pap [ 6 ]. Like the Selvaggi et al study we did not comment on diagnostic differences when a secondary device was added but unlike the Selvaggi et al study we found all broom-only samples to have EC cells present. Importantly, our current study is the first to examine diagnosis differences that may result from adding additional devices to a broom device in the liquid-based setting. Here we found that 10/37 (27%) of cases had abnormal cytology when the SurePath broom was used. Immediate re-sampling with a second or third device did not increase the number of abnormal cytologies found. In addition, cervical biopsy of all abnormal cytologies was performed and as Tables 1 , 2 , 3 , 4 show use of additional devices did not improve cytology/tissue correlation. In conclusion, the SurePath broom appears to be a very effective cervix sampling device when coupled with the SurePath Pap. In 60 patients examined prospectively (37 in this study, 23 in our previous study [ 6 ]) only one patient (1.6%) failed to have EC cells recovered with the broom device alone. This is in contrast to the Selvaggi et al study that showed in 432 ThinPrep patients a 10% failure to detect ECs using two devices [ 4 ]. We must note, however, that the EC adequacy standard was different between their study and our studies because we defined EC presence as at least one group of 6 or more EC cells and they defined it as 10 or more EC and/or squamous metaplastic cells singly or in groups. Finally, our current work is the first to show in the liquid-based setting that the SurePath broom alone is as effective at identifying abnormal cells as the broom + additional devices. Conclusions Use of additional collection devices in conjunction with the SurePath broom did not enhance diagnostic utility of the SurePath Pap. A potential but not significant improvement in EC recovery might be seen with the use of three devices. Competing interests GGF has served as a speaker for TriPath Care Technologies. Abbreviations Atypical squamous cells (ASC) of uncertain significance (ASC-US), endocervical cell (EC), Food and Drug Administration (FDA), high grade SIL (HSIL), low grade SIL (LSIL), Papanicolaou (Pap), quantity not sufficient for diagnosis (QNS), squamous intraepithelial lesion (SIL), SurePath Liquid-Based Pap Test (SurePath Pap), SurePath Liquid-Based Pap Test Broom Device (SurePath broom), The Bethesda System (TBS). Authors' contributions SJD coordinated the study and analyzed the study data, DLO collected all samples, JCO performed the statistical analysis. GGF constructed the manuscript. Figure 1 Sampling Devices. A , SurePath broom. B , Rover spatula. C , Rover endocervix brush. D , Medscand spatula. E , Medscand CytoBrush Plus GT. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC520818.xml
538266	Socio-demographic factors and edentulism: the Nigerian experience	Background The rate of total edentulism is said to be increasing in developing countries and this had been attributed mainly to the high prevalence of periodontal diseases and caries. Several reports have shown that non-disease factors such as attitude, behavior, dental attendance, characteristics of health care systems and socio-demographic factors play important roles in the aetiopathogenesis of edentulism. The aim of this study was to assess the relationship between socio-demographic factors and edentulism. Methods A total of 152 patients made up of 80 (52.6%) males and 72 (47.4%) females who presented in two prosthetic clinics located in an urban and a rural area were included in the study. The relationship between gender, age, socio-economic status and edentulism in this study population was established. Results No significant relationship between gender and denture demand was noted in the study. The demand for complete dentures increased with age while the demand for removable partial dentures also increased with age until the 3 rd decade and then started to decline. A significant relationship was found between denture demand and the level of education with a higher demand in lower educational groups (p < 0.001). In addition, the lower socio-economic group had a higher demand more for prostheses than the higher group. Conclusions The findings in this study revealed a significant relationship between socio-demographic variables and edentulism with age, educational level and socio-economic status playing vital roles in edentulism and denture demand.	Background Edentulism (partial or total) is an indicator of the oral health of a population [ 1 ]. It may also be a reflection of the success or otherwise of various preventive and treatment modalities put in place by the health care delivery system [ 2 ]. Many patients also regard edentulism as self-mutilating and may be a strong incentive to seek dental treatment [ 3 ]. While the rate of total edentulism is decreasing in developed countries, the reverse is the case with developing countries and this had been attributed mainly to the high prevalence of periodontal diseases and caries [ 5 - 7 ]. Previous studies have also shown that several non-disease factors such as attitude, behavior, dental attendance, characteristics of health care system and socio-demographic factors play important roles in the aetiopathogenesis of edentulism [ 3 ]. Some studies reported that the incidence of edentulism correlated with educational levels and income status, with those in the lower levels exhibiting higher risks of becoming totally edentulous [ 8 , 9 ]. In addition, a study done in a rural area of Eastern Guatemala showed that social and environmental influence such as poverty, lack of proper education and inadequate diet contributed to widespread premature and heavy losses of permanent teeth [ 10 ]. Although, Hoover and McDermount [ 11 ] reported a higher prevalence of edentulism in males than females, Marcus et al observed that the prevalence of edentulism had no relationship with gender [ 12 ]. They also observed that there was an inverse relationship between the level of education, income and edentulism. Studies among Nigerians have linked some of these socio-demographic factors with the prevalence, pattern and rate of dental diseases [ 13 , 14 ] but there has been no report on the influence of these on edentulism. The aim of this study therefore was to assess the relationship between socio-demographic variables with types of edentulism. Methods All patients that attended and were treated in the removable prosthetic units of Obafemi Awolowo University Teaching Hospitals Complex (OAUTHC), Ile-Ife (a rural area located in the south west of Nigeria) between the months of March and May year 2002 and Lagos University Teaching Hospitals (LUTH), Lagos (an urban area also located in south west Nigeria) between December 2002 and March 2003 were included in the study. Information such as age, gender, occupation and level of education attained were documented. The types of partial denture received following treatment at the clinics were also documented There has not been a consensus on various socio-economic classifications in Nigeria because of the unstructured nature of the society. Therefore, for the purpose of this study, a standard occupational classification system designed by Office of population Census and Surveys, London (OPCS 1991) [ 15 ] modified based on local reality was used and patients were classified into three socio-economic groups: Class 1 = Skilled worker e.g professionals and managerial officers and retirees of this cadre. Class 2 = Unskilled workers e.g. Artisans and traders Class 3 = Dependants. e.g. Retirees of class 2, those not on pensions, house wives of class 2 cadre, students whose parents are unskilled workers Data was analysed using SPSS for Windows version 10.0, (SPSS Inc Chicago Illinois, USA). Analysis included frequency, cross tabulations, calculation of means. Association between discrete variables was tested by Chi-Square and the level of significance was set at 5%. Results One hundred and fifty two patients attended the prosthetic clinics during the study period. Eighty (52.6%) were males while 72 (47.4%) were females (Table 1 ). Their ages ranged from 8 to 84 years. The median age was 22.00 years, while the mean age was 41.8 (±19.5) years. The mean age for Ile-Ife study population was 41.3 (±20.46) years, while that of Lagos was 39.9 (±17.56) years. Table 1 Distribution by gender. Gender Ile-Ife Lagos Total No % No % No % Male 48 48.0 32 61.5 80 52.6 Female 52 52.0 20 38.5 72 47.4 Total 100 100.0 52 100.0 152 100.0 χ 2 = 2.515, df = 1, P = 0.113. There were no statistically significant age (p = 0.312) and gender (p = 0.113) differences between the populations from the two centers. (Tables 1 and 2 ). Table 2 Denture demand by age and center/clinic Age group Ile-Ife Lagos Total N % N % N % ≤20 18 18.0 5 9.6 23 15.13 21–40 35 35.0 22 42.3 57 37.5 41–60 25 25.0 17 32.7 42 27.63 ≥61 22 22.0 8 15.4 30 19.74 Total 100 100.0 52 100.0 152 100.00 χ 2 = 3.568, df = 3, P = 0.312 There was a highly significant difference in the educational status of patients seen at LUTH and OAUTHC with patients seen at LUTH being of higher educational levels than patients seen at OAUTHC. (χ 2 = 7.50 df = 3, P < 0.001) (Figure 1 ). Figure 1 Distribution of patients according to educational level. In terms of socioeconomic status, 28 (18.42%) patients belonged to class I; 43(28.29%) patients belonged to class II while 81(53.29%) belonged to class III. There was no statistically significant difference in the socio-economic status of patients from the two centers ((χ 2 = 5.70, df = 2, p = 0.057). (Figure 2 ) Figure 2 Socio-economic status distribution. In both centers, 134 patients (88.2%) received removable partial dentures, 13 patients (8.6%) received complete dentures while 5 patients (3.3%) received either upper or lower complete dentures. There was no significant difference in the demand for different types of dentures between the study locations. (P = 0.315). (Table 3 ). Table 3 Demand for various types of denture by study location. Types of dentures Ile-Ife Lagos Total N % N % N % Complete 11 11.0 2 3.8 13 8.6 Lower or upper complete denture 3 3.0 2 3.8 5 3.3 Removable partial denture 86 86.0 48 92.3 134 88.2 Total 100 100.0 52 100.0 152 100.0 χ 2 = 3.568, df = 3, P = 0.312 For the purpose of analysis, complete and lower/upper complete denture columns were merged. However, there was a significantly higher demand for removable partial dentures than any other type of prostheses. (P < 0.01). (Table 3 ) It was observed that as the age increased, the proportions demanding for complete dentures also increased. In addition, those in age group 21–40 years demanded more for removable partial denture than any other age groups. While those above 61 years asked more for removable complete dentures than removable partial dentures. (Table 4 ). Table 4 Types of denture demand within each age group. Age group Denture demanded TOTAL Complete Partial no % no % no ≤20 1 4.3 22 95.7 23 21–40 2 3.5 55 96.5 57 41–60 5 11.9 37 88.1 42 ≥61 10 33.3 20 66.7 30 Total 18 11.8 134 88.2 152 Likelihood-ratio χ 2 = 16.579, df = 3, P = 0.001 No significant relationship between gender and pattern of denture demand (p = 0.812) was noted and no statistically significant difference was noted in the pattern of denture demand between the two centers (p = 0.277). (Table 5 and Figure 3 ). Table 5 Demand for various prostheses in relation to gender. Type of Denture male Female Total Complete denture 6 7 13 Complete upper or Lower denture 3 2 5 Partial denture 71 63 134 Total 80 72 152 χ 2 = 0.57, df = 1, p = 0.812 For the purpose of analysis, complete and lower/upper complete denture columns were merged. Figure 3 Types of prostheses demanded by centers The lower educational groups demanded more for complete dentures among those asking for complete denture, while those with higher level of education asked more for removable partial denture. (P < 0.001). (Table 6 ). More over, those with tertiary level of education constituted the majority of the study population. (Table 6 ) Table 6 Demand for dentures according to educational level Educational Level Complete Denture Partial Denture Total No % No % No % Nil 11 61.1 12 8.9 23 15.1 Primary 3 16.7 8 5.9 11 7.2 Secondary 0 0.0 51 38.1 51 33.6 Tertiary 4 22.2 63 47.0 67 44.1 TOTAL 18 100.0 134 100.0 152 100.0 Fishers exact test P < 0.001 For the purpose of analysis, secondary and tertiary educational levels' rows were merged. Also complete denture and either upper or lower complete denture column were merged Among the patients that were completely edentulous, there was no significant difference in the demand for complete dentures between those with lower educational status and those with higher educational status. P = 0.276 (Table 7 ) Table 7 Relationship between age group, educational level and completely edentulous state Age group Educational Level Nil Primary Secondary/Tertiary ≤20 1(9.1%) - - 21–40 2(18.2%) - - 41–60 4(33.4%) 1(33.3%) >60 4(33.4%) 2(66.7%) 4(100%) Likelihood-ratio χ 2 = 7.515, df = 6 P = 0.276 It was noted that the lower the socio-economic status the higher the demand for dentures. This picture was independent of rural or urban dwelling. (Tables 8 and 9 ). However, 28.3 % of those in Class II who need dentures asked for complete as opposed to 3.6% in Class I and 8.6% of those in Class III. Table 8 Relationship between edentulous state and socio-economic status. Socio-economic status Edentulous state Total Partial complete No % No % No % Class I 27 96.4 1 3.6 28 18.4 Class II 33 76.7 10 23.3 43 28.3 Class III 74 91.4 7 8.6 81 53.3 Total 134 88.2 18 11.8 152 100 χ 2 = 7.992, df = 2, P = 0.018 Table 9 Socio-economic status distribution by centers Socio-economic Class Lagos center Ife center TOTAL NO % NO % No % Class I 8 15.4 20 20.0 28 18.4 Class II 21 40.4 22 22.0 43 28.3 Class III 23 44.2 58 58.0 81 53.3 TOTAL 52 100.0 100 100.0 152 100.0 χ 2 = 5.70, df = 2, p = 0.057 Discussion Tooth loss could occur as a result of caries, periodontal diseases, trauma, tooth impaction, orthodontic reasons, hypoplasia, over eruption, supernumerary teeth, attrition, neoplastic and cystic lesions [ 5 - 7 ]. Many studies have consistently shown the role of specific diseases like dental caries and periodontal disease as a major cause of tooth loss [ 7 , 13 , 14 ]. This same picture was noted in similar Nigerian studies [ 5 , 6 ]. Okoisor further established that the disease factors responsible for tooth loss was age related; with caries and periodontal diseases being the major causes of tooth mortality in children and adult respectively [ 5 ]. However, none of the studies done in Nigeria evaluated the role of other factors such as education, socio-economic status, gender, location of patients, dental attitude and behavior in the etiology of edentulism. The older age groups in this study required more of removable complete dentures than the younger age groups while the younger age groups required more of removable partial dentures. This is in agreement with the study done by Marcus et al [ 12 ]. Although there was an over representation of age groups >61 and 21–40 in our study population, the percentages of these age groups in Nigerian population are 4% and 30% respectively in both urban and rural areas [ 16 ]. Hence, these age groups have risk factors that might be responsible for their needing dentures. This age related changes may not be unconnected with the deteriorative physiological changes noticed after adolescence and which gets worse with increase in age, a situation which is changing rapidly in the developed countries due to improved social infrastructure and functional health system [ 17 , 18 ]. Most studies have also shown significant gender difference in edentulism with more males becoming edentulous than females [ 11 , 19 ]. This has been attributed to the fact that males are more active than females and do not pay much attention to oral care. A significant gender difference was not seen in this study although variation in site presentation was observed. In Lagos, an urban area, more males actually demanded for prostheses. However, in Ile-Ife, a rural area more females demanded for prostheses. This is in agreement with the studies done by Eklund and Burt [ 8 ] and Marcus et al [ 12 ]. Although no statistically significant difference was noted in the rural-urban gender presentation, a larger qualitative study alongside a quantitative study may be able to adduce possible reasons for this interesting observation. Majority of our study population belonged to the higher education status. This is because those with higher level of education are more informed about their health needs and may seek dental treatments earlier and more often than those of lower educational status who may only seek dental treatment when there is apparent morbidity. In addition, those of higher educational status are likely to be richer than those of lower educational status. Hence, they are able to afford the cost of dental treatments from time to time. Our study showed that the need for complete dentures decreased with increasing level of education (p < 0.001), hence the likelihood of retaining teeth in the mouth becomes higher as the educational level increases. Although the educational status of the patients from the two centers differ, independent analysis of these centers still showed the same significant effect of educational status on the pattern of denture demand. This is in agreement with the findings of Brodeur et al, where the proportion of completely edentulous adults decreased from 26% in 1980 to 20 % in 1993 due to improved income and educational status [ 1 ]. The association between edentulism and educational status may be as a result of improved dental health awareness, increased utilization of oral health facilities, proper oral hygiene habits acquired during learning process and peer group influence. Interestingly, about 23.3 % of those in class II who need dentures asked for complete dentures as opposed to 3.6% in class I and 8.6% in class III. The reason for this may be as a result of the fact that they may not be able to afford the exorbitant cost of restorative procedures hence they wait until they have lost their set of teeth to have a complete removable denture which is cheaper. The present study showed that people with low socio-economic status demanded for more dentures than the high socio-economic group. Studies have long established a gradient relationship between socio-economic status and health [ 20 ]. In so many intricate ways, socio-economic status tends to affect health behaviors, the environment and social influences an individual is exposed to. Hunter and Arbona found that environmental influences such as land hunger, family poverty, and inadequate diet are of paramount importance in the cause of tooth loss [ 10 ]. They concluded, "Periodontal disease drives the poorest of the poor to spend disproportionately large sums on pain killers and destructive traditional medicine". The importance of socio-economic status is further reflected in the urban-rural variance noted in this study population's demand for denture. The Ile-Ife study group, a rural population with a lower socio-economic status, demanded for more dentures than the Lagos study group. However, this study population was an all-inclusive hospital based sample; the result may not be representative of the population at large. Hence, its use can only be limited to the study population. A randomized population based survey may be able to present a better picture among Nigerians. This study observed that edentulism is due to a combination of various factors. Poor education, a risk factor for poverty, has been identified as a major factor in edentulism. So also is the socio-economic status of the patient. These two factors, which are non-disease factors, affect the mortality of teeth arising from disease factors. There is therefore a need for oral health policy formulators to focus on improving the educational and socio-economic status of its citizens (a down stream approach) rather than the present emphasis on disease control (an up stream approach) in oral health care delivery. On the other hand, with increasing level of literacy, and positive social changes in Nigeria, Prosthodontists should brace up to face the challenges that may arise from increased removable partial denture demand and decreased demand for complete dentures. This is because, with increase in level of education and socio-economic status of patients, the demand for removable partial dentures is likely to increase while dentists may be confronted with a significant increase in the number of difficult edentulous mouths requiring treatment. In addition to addressing the non-disease factors, dental education should be targeted at the uneducated populace, the rural dwellers and low-income groups to reduce the rate of total edentulism. Conclusion No gender relationship with denture demand was noted this study. In addition, the demand for complete dentures increased with age. There was a statistically significant inverse relationship between educational levels and demand for dentures. There was more demand for prostheses among the lower socio economic groups. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC538266.xml
546223	Effect of method of administration on longitudinal assessment of quality of life in gynecologic cancer: An exploratory study	Background Longitudinal assessments of quality of life are needed to measure changes over the course of a disease and treatment. Computer versions of quality of life instruments have increased the feasibility of obtaining longitudinal measurements. However, there remain occasions when patients are not able to complete these questionnaires. This study examined whether changes measured using a computer version of the Functional Assessment of Cancer Therapy – General (FACT-G) on two occasions would be obtained if patients completed a paper version on one of the two occasions. Methods Gynecologic oncology patients completed a computer version of the FACT-G pre-operatively and at six months. Patients were given the option of using the paper version instead of the computer at either time point. Repeated measures analysis of variance was used. Results One hundred nineteen patients completed the FACT-G at both time points. Seventy-one (60%) patients used the computer at both visits, 26 (21.8%) used the computer followed by the paper version, 17 (14.3%) used the paper version followed by the computer version, and five patients (4.2%) used the paper version at both visits. Significant effects over time were obtained in the physical, functional, and emotional well-being domains, and in total scores, but there were no effects of method of administration of the questionnaires and no interaction between method of administration and changes over time. Conclusions These data indicate that women are responding to the content of the questionnaire and not method of data collection. Although using the same method of administration of instruments over time is desirable, using alternate methods is preferable to forgoing data collection entirely. Large scale studies should be conducted to determine if the multiple methods of data collection that are becoming increasingly available are producing interchangeable information.	Background Measurement of changes in quality of life (QoL) has become a standard outcome variable in evaluating different therapeutic regimes in cancer [ 1 - 3 ]. Standardized, validated and reliable questionnaires are available for the measurement of changes in QoL [ 4 - 7 ]. Additionally, the use of these instruments by clinicians caring for patients is being explored [ 8 - 11 ]. Assessing changes in QoL as patients progress through the course of disease and treatment increases the need for longitudinal assessment. Computer versions of these questionnaires have become available and can be used for longitudinal assessments [ 12 - 17 ]. These systems are well accepted by patients [ 12 , 16 - 19 ] and allow for the collection of data without transcription errors [ 12 , 17 , 18 ]. Comparison of data collected at one point in time by computer versus paper suggest that the method of collecting the information does not have a large effect on the data collected [ 19 ], although some differences are obtained. Formatting of the questions has been found to have an effect [ 20 ], and there may be a tendency of patients to give more positive responses with the computer, especially if the format is simplified [ 12 , 20 ]. A potential barrier to longitudinal measurements is that compliance may decrease over time. Patients may be initially willing to answer questions on the computer, but be less willing to do so on subsequent visits [ 14 , 17 ]. Reasons for this may include time constraints due to office and patients' scheduling needs as well as patients feeling unwell. One method to deal with these realities of daily clinical practice is to offer patients the choice of taking home the questionnaires to complete if they state they do not have time or do not want to complete the questionnaires on the computer at that time. This would introduce two principal differences. The method of data collection would be different (paper vs. computer), and the location of completing the forms would be different (home vs. office). Asking patients about their QoL over the past several days would reduce the effect of answering the questions in the office or at home. If the instruments are measuring significant changes in life due to major events such as diagnosis of serious disease, surgery, chemotherapy, and remission, then the location and method of administration of the instrument should have minimal effect on responses. Women attending a gynecologic oncology practice were enrolled in a longitudinal study of QoL. Women completed a computer version of a QoL questionnaire pre-operatively and again at six months. They were given the option of using the paper version at either time point, and the effect of this choice was examined. An additional issue examined was whether use of the paper version was widespread or sporadic. The goal of the study was to compare changes over time obtained when women used a touch-screen computer on two occasions with changes obtained when women used a paper version of the questionnaire on one of the occasions. Methods Patients who were scheduled to undergo surgery for endometrial cancer, ovarian cancer or an adnexal mass were invited to participate in a long term study of QoL, complementary medicine use and diet. Women at two gynecologic oncology offices in Northeast Ohio were recruited from 2001 – 2003. Informed consent was obtained for participation in this IRB approved study. Private office records and hospital discharge records were reviewed to abstract demographics and final pathology diagnosis. Baseline demographics were ascertained by interview with a research assistant pre-operatively. Patients completed the questionnaire pre-operatively and again at six months. Computer kiosks with a 15 inch monitor were programmed with the Functional Assessment of Cancer Therapy-General questionnaire (FACT-G) along with an additional fatigue module [ 21 ]. The FACT is a 27-item questionnaire consisting of four domains: physical, emotional, social and functional well-being. Patients are asked how true each statement has been for them over the past seven days. Each domain is comprised of six to seven questions scored by use of a Likert-type scale ranging from 0 (not at all) to 4 (very much). Each domain appeared on one screen and patients touched their response to each individual question. Patients could change their answers by touching an alternate response on that screen but could not return to a previous screen. All questions had to be completed before the computer continued to the next screen. The touch screen computer was designed so that the format of the questions closely matched the format of the questions on the paper form. Patients utilized the computer kiosk independently during their office visit although the research assistant was available to answer questions. Patients were given the option of completing the questionnaire using the paper version at any time. Statistical analyses Patients were categorized into four groups; those who completed the FACT-G on the computer on both occasions (CC), those who completed the initial assessment by computer and used paper format at six months (CP), patients who completed the initial assessment on paper and the six-month via computer (PC) and patients who completed both assessments on paper (PP). Analysis of variance or chi-square statistic was used to compare baseline demographic variables between patients who always used the computer and those who utilized the paper version at either time point. Repeated measures analysis-of-variance was used to analyze change in the domain score from baseline to six months (time effect), whether there was an effect of group (CC, CP, PC and PP) and whether there was an interaction between group and time. Significance was set at p < 0.01 due to multiple comparisons. SPSS version 10.0 was used for analysis (Chicago, IL). Results A total of 187 patients were asked to participate in this longitudinal study and 151 agreed (81%). Following completion of the initial assessment, 32 patients were lost to follow-up, moved, missed the second appointment entirely or refused to complete the questionnaire the second time (16 patients with benign adnexal mass, 8 with endometrial cancer and 8 with ovarian cancer). A total of 119 patients (79% of patients who agreed to participate in the study) completed the FACT-G assessments at both time points. Forty patients had endometrial cancer, 40 had ovarian cancer and 39 had a benign adnexal mass. Twenty of the cancer patients had Stage III or IV disease. Virtually all of the patients were Caucasian (96.6%). Patients returned the questionnaire by mail within a few days of their scheduled visit. Seventy-one (60%) patients used the computer at both visits (CC), 26 (21.8%) used the computer initially followed by the paper version at six months (CP), 17 (14.3%) used the paper version initially followed by the computer version (PC), and five patients (4.2%) used the paper version at both visits (PP). Patients in the PP group were excluded from statistical analyses as the numbers in that group were small (n = 5). There were no differences in the age (F = 0.225, p = 0.80) or level of education (χ 2 = 2.75, p = 0.60) between the CC, PC and CP groups (Table 1 ). Approximately 60% of the patients within each diagnosis group used the computer at both time points (Table 1 ). A slightly higher percentage of patients with a benign adnexal mass used the paper version of the FACT-G at the six months visit (χ 2 = 11.07, p = 0.026) as they were more likely to decline to come in for an office visit and request the FACT-G be sent home than were the patients with a cancer diagnosis (Table 1 ). Four of the five patients in the PP group had ovarian cancer. Mean age of those in the PP group was similar to the other groups (61.2 years) and all had some college or were college graduates. Table 1 Patient Demographics by Group CC (n = 71) CP (n = 26) PC (n = 17) Age (mean ± SEM) 58.3 ± 1.5 56.4 ± 2.6 57.4 ± 2.9 Diagnosis Benign (n = 39) 24 (61.5%) 14 (35.9%) 1 (2.6%) Endometrial CA (n = 39) 25 (64.1%) 5 (12.8%) 9 (23.1%) Ovarian CA (n = 36) 22 (61.1%) 7 (19.4%) 7 (19.4%) Education HS or less 31 (43.7%) 14 (53.8%) 11 (64.7%) Some college 14 (19.7%) 4 (15.4%) 2 (11.8%) College grad or higher 26 (36.6%) 8 (30.8%) 4 (23.5%) Physical well-being domain scores were significantly higher at six months than at baseline (Figure 1 , F = 8.849, p = .004) and there was no effect of group (CC, CP, PC; p = 0.480) and no interaction between time and group (p = 0.457). Functional well-being scores were also higher at six months (Figure 2 , F = 14.024, p < 0.001) and there was no effect of group (p = 0.453) and no interaction effect (p = 0.583). Emotional well-being scores were significantly higher at six months (Figure 3 , F = 24.334, p < 0.001) and there was no effect of group (p = 0.943) and no interaction between group and time (p = 0.865). Social well-being scores did not increase with time (Figure 4 , p = 0.14) and there was no effect of group (p = 0.185). There was a significant interaction between group and time (F = 5.671, p = 0.005) as the CP group had a higher score at baseline. There was no effect of time, group or interaction on fatigue scores (data not shown). Total scores were significantly higher at six months (Figure 5 , F = 12.174, p = 0.001) and there was no effect of method (p = 0.756) and no interaction effect (p = 0.392). Figure 1 Scores on the Physical Well-Being domain of the Functional Assessment of Cancer Therapy (FACT-G) Figure 2 Scores on the Functional Well-Being domain of the Functional Assessment of Cancer Therapy (FACT-G) Figure 3 Scores on the Emotional Well-Being domain of the Functional Assessment of Cancer Therapy (FACT-G) Figure 4 Scores on the Social Well-Being domain of the Functional Assessment of Cancer Therapy (FACT-G) Figure 5 Total scores on the Functional Assessment of Cancer Therapy (FACT-G) Discussion Physical, functional, emotional well-being, and total scores, improved significantly between baseline and six months. In all cases, there was no effect of group and no interaction between group and time, indicating that the women were not affected by the method of data collection. There were also no significant effects of group even when there was no change in the scores over time (social well-being, fatigue). The one significant interaction effect was observed with the social well-being domain, which appeared due to a high baseline score in the CP group. At baseline, the CP group was the same as the CC group (they all used the computer) so it is not clear why there would be a high baseline score in the group that would use a paper version six months later. It is possible that with the number of tests conducted, one spurious finding would be obtained. The trend across all the tests is very strong, however. There are clear and significant changes with time but not with the method of obtaining the data. Given the choice between using the computer version and the paper version, a small number of women chose the paper version. Of the 238 total measurements, the paper version was used a total of 53 times (22%). Reasons for not using the computer included not wanting to come in to the physician's office at all and patient preference but also instances beyond the patients' control such as scheduling complications and researcher unavailability on a small number of occasions. Designing strategies to increase computer availability may result in further reductions in patient use of the paper versions. If patients can log onto the computer using a unique identifier and complete the questionnaires on their own in the waiting room, the number of women who have to take questionnaires home or forgo completing them should decrease even further. The second assessment occurred six months following major surgery for all women. The majority of women with ovarian cancer received chemotherapy, but were not receiving it at six months. This time point therefore allows a relatively stable point to assess changes in QoL relative to pre-operative scores in these groups of women. It is possible that differences in method of data collection would be obtained if women were acutely ill at the time of measurement, however the time frame of seven days used in the FACT-G reduces the likelihood that a separation in time of a day or two between using the computer in the office or the paper version at home will result in different responses. The time frame used in the FACT-G, and the relatively stable time point chosen may therefore contribute to the lack of measurement effect obtained in these groups of women. A limitation of this study is the lack of minority representation which may reduce the generalizability of these results. Additionally, 19% of patients refused to participate in the study. Of the patients who did participate, 21% did not complete the second assessment, although this figure includes 16 women with a benign adnexal mass who may have returned to their referring physician, and women with cancer who moved or transferred their care. Nonetheless, the women who remained on study may differ from those who did not agree to participate or who did not complete the second assessment. They may, for example, have a greater degree of commitment to the research process. A second limitation is that women were not randomly assigned to use either the computer or the paper versions. This is a preliminary examination of existing data to determine whether there appeared to be a selection bias, or major effect, of using the paper version. Women with QoL scores that differed markedly from the norm, for example, might have chosen to take the paper version home. This did not appear to be the case, however, as highly significant effects of time were observed, but group and interaction effects were markedly non-significant. Related limitations include the remote, but possible, explanation that the first method of administration had an effect on participants at the second time point. Additionally, patient choice itself may have had an unmeasured effect. For example, women with benign adnexal mass were more likely to forego the second office visit and complete the questionnaire at home. Disease and questionnaire administration are therefore confounded. These limitations may have influenced group choice, as well as responses on the second measurement. These exploratory data suggest that women are responding to questionnaires presented on a computer in the same manner as questionnaires on paper. This study therefore differed somewhat from studies that found differences in method of administration [ 12 , 20 ]. An important consideration may be maintaining the same format of the questions in the two methods of administration. In this study, each domain was presented on one large screen so that all questions were listed together. The similarity of the format may have contributed to the finding that modes of administration are interchangeable, however larger scale studies, which include randomization and assessing women at different stages of treatment, should be conducted to verify these findings. Conclusions Longitudinal measurements of health- related QoL are increasingly used in cancer patients. This study examined whether two different methods of measuring QoL (computer and paper) would provide interchangeable data. It appears that patients are dealing with issues of significant concern and they are responding to the content of the questions and not the method of data collection. It is clearly desirable to standardize the method of data collection and have conditions remain constant across time. The results of this study, however, demonstrate that valid data are obtained with alternate methods of data collection and this is preferable to foregoing data collection entirely. Authors' contributions KG and VVG conceived of the study, and participated in its design and coordination. HF, MH, EJ and VVG implemented the study and were responsible for day to day conduct of the study. KG and HF analyzed the data. KG, HF, VVG drafted the manuscript; JE and MH provided critical review. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC546223.xml
509252	Western medical ethics taught to junior medical students can cross cultural and linguistic boundaries	Background Little is known about teaching medical ethics across cultural and linguistic boundaries. This study examined two successive cohorts of first year medical students in a six year undergraduate MBBS program. Methods The objective was to investigate whether Arabic speaking students studying medicine in an Arabic country would be able to correctly identify some of the principles of Western medical ethical reasoning. This cohort study was conducted on first year students in a six-year undergraduate program studying medicine in English, their second language at a medical school in the Arabian Gulf. The ethics teaching was based on the four-principle approach (autonomy, beneficence, non-malfeasance and justice) and delivered by a non-Muslim native English speaker with no knowledge of the Arabic language. Although the course was respectful of Arabic culture and tradition, the content excluded an analysis of Islamic medical ethics and focused on Western ethical reasoning. Following two 45-minute interactive seminars, students in groups of 3 or 4 visited a primary health care centre for one morning, sitting in with an attending physician seeing his or her patients in Arabic. Each student submitted a personal report for summative assessment detailing the ethical issues they had observed. Results All 62 students enrolled in these courses participated. Each student acting independently was able to correctly identify a median number of 4 different medical ethical issues (range 2–9) and correctly identify and label accurately a median of 2 different medical ethical issues (range 2–7) There were no significant correlations between their English language skills or general academic ability and the number or accuracy of ethical issues identified. Conclusions This study has demonstrated that these students could identify medical ethical issues based on Western constructs, despite learning in English, their second language, being in the third week of their medical school experience and with minimal instruction. This result was independent of their academic and English language skills suggesting that ethical principles as espoused in the four principal approach may be common to the students' Islamic religious beliefs, allowing them to access complex medical ethical reasoning skills at an early stage in the medical curriculum.	Background Medical ethics has increasingly become a common component of the undergraduate curriculum at many medical schools, often within a defined humanities program [ 1 - 3 ]. In 1999, the European Federation of Internal Medicine, the American College of Physicians and the American Board of Internal Medicine launched the Medical Professionalism Project, which placed medical ethics at the centre of a charter of behaviour and attitudes for all physicians [ 4 ]. In 2003, the Liaison Committee on Medical Education in the USA identified the teaching of medical ethics as a core curriculum component of modern medical school education [ 5 ]. Medical ethics teaching can occur within the traditional model of medical education, where a separate program of clinical instruction follows several years of medical sciences [ 6 ]. However, there is some evidence to suggest that a vertically integrated learning model where the study of clinical subjects runs parallels to and is integrated with basic sciences may be more effective [ 7 , 8 ]. This has resulted in a trend towards including clinical experience in the early years of the medical school curriculum. There is increasing evidence that this enhances student attitudes towards patients [ 9 ], provides a structure for teaching integrated clinical medicine [ 10 ] and better prepares students for the clinical years [ 11 ]. Although Islam has a long tradition of ethical reasoning, there had been little impetus to establish courses in ethics within medical school curricula in the Arabian Gulf. The Faculty of Medicine and Health Sciences (FMHS) was almost alone in having done so, an initiative introduced by expatriate family physicians from New Zealand who had undertaken training in Western medical ethics. Ethics had been taught at the FMHS since 1997 in a vertically integrated program that spanned all levels of the curriculum, based on the four-principle approach developed by Beauchamp and Childress [ 12 , 13 ] as modified by Herbert; autonomy, beneficence, non-malfeasance and justice [ 14 , 15 ] (See Table 1 ). Although it was less than ideal to focus the medical ethics curriculum on an imported model, there was little support within the UAE University for a course centred on local culture and traditions. Table 1 Ethical Principles utilized in the teaching program Primary Principle Subsection principles 1. Autonomy a) Disclosure b) Truth telling c) Informed consent d) Competence e) Paternalism f) Confidentiality g) Decision-making 2. Beneficence 3. Non-malfeasance 4. Justice English has become the lingua franca of medicine, with most international medical societies, publications and meetings conducted in English [ 16 , 17 ]. This has encouraged the development of English language medical schools in countries where English is a second language, including the Arabian Gulf. There is a significant body of literature describing how people from different cultures utilise different approaches to the clinical application of medical ethics [ 18 , 19 ]. However, there is little information about teaching medical ethics across cultural and linguistic boundaries. Social anthropology has demonstrated that there is a strategic mixing of language with culture and that both culture and social systems are conceptualised in language [ 20 , 21 ]. This would suggest that students learning medicine in English, their second language, could experience dissonance between the content of their courses and the context of their everyday lives, especially in socially formulated issues such as medical ethics. The aim of this study was to investigate whether Arabic speaking students studying medicine in an Arabic country, albeit with the language of instruction being English, would be able to correctly identify some of the principles of Western medical ethical reasoning, a discipline that challenged significant cultural and linguistic boundaries. Methods Setting The FMHS at the United Arab Emirates (UAE) University offers a six-year undergraduate program in medicine. Students are admitted after a one-year post high school tertiary orientation year, which includes additional English language instruction. Although all students are citizens of the UAE, speaking Arabic as their first language, the course is conducted in English therefore students are required to meet an English language proficiency level in order to be accepted into the medical school. Faculty members come from across the globe, with approximately 1/3 with English as their first language, 1/3 with Arabic as their first language and 1/3 with a different primary language. All medical students participated in an introductory course in medical ethics, conducted in the first three weeks of first year and taught by a non-Muslim native English speaker from New Zealand with no knowledge of the Arabic language. Apart from his qualifications in Family Medicine, he had also undergone training in Western medical ethics. Although the course was respectful of Arabic culture and tradition, the content of the introductory course focused on Western medical ethical reasoning and excluded an analysis of Islamic medical ethics. Based on the principles of adult learning, the educational strategy focused on the use of real clinical encounters after minimal orientation, followed by an interactive debriefing session. Rather than provide a sound basis for ethical reasoning, the aim of the introductory course was to introduce the students to the central importance of ethical principles in medical practice, knowing that a more complete and integrated understanding would develop over the ensuing six years of the course. Following two 45-minute interactive seminars, students in groups of 3 or 4 visited a primary health care centre for one morning, sitting in with an attending physician seeing his or her patients. In the absence of any clinical understanding at this early point in their training, the students were encouraged to focus all their energies on medical ethics. Following the visit to the primary health care centre each student submitted a personal report for summative assessment in which they described the ethical situations they had observed and then provided an appropriate label according to the four-principal approach. Although the seminars were in held in English, the clinical sessions were conducted in Arabic. When questioned by the investigator (SM), the clinical staff stated they had never received formal instruction in medical ethics. The clinical staff were discouraged from indicating ethical issues to the students; the educational process was for the students to identify these on their own. Following submission of their personal report, a third seminar of the introductory course was held with the same teacher where students were invited to share and discuss their experiences. Sample This study examined two cohorts of first year students, 33 students from the 2002 – 2003 academic year and 29 students from the 2003 – 2004 academic year (i.e. all students enrolled in these courses). Each cohort experienced the same admission criteria, underwent the same curriculum, was taught ethics by the same native English-speaking teacher and utilised the same group of primary health care physicians. Analysis methodology Although both experienced educators and educational researchers, the investigators (VY and SM) did not teach medical ethics at this level of the curriculum. Each investigator coded all personal reports independently and any discrepancies were resolved by mutual agreement. A positive score for labelling any of the four principles and the subsets of autonomy was only allocated when the accompanying description corresponded with the label given. Merely listing a label was not coded as positive. As an indicator of general academic ability, the students' score on a multidisciplinary unit test held at the end of the fifth week of year one was also considered. The results of this test have been considered as a variable in the study to determine if there was a correlation between general academic ability and the students' competency in identifying ethical principals and to avoid associated bias. This multidisciplinary unit test covered all topics taught in the first 5 weeks including anatomy, chemistry, medical physics and medical ethics. The pass mark was set at 75%. The medical ethics component contributed 5% of the total mark. As not all students had the same clinical experience, each individual student may not have had the opportunity to observe the same range of ethical issues during their clinical experience. For example, some students may not have seen an example of competence to detail in their report. Hence, as this manuscript concerns each individual student's ability to report what he or she as an individual had observed in an experience not shared across the whole group, only numbers of ethical issues identified by individual students are reported rather than the total numbers of students per ethical issue. A third variable included was their score in a standardised test of English, the Test of English as a Foreign Language (TOEFL) [ 22 ], used in the selection process to enter medical school. Although initially designed as a measure of the English language proficiency of international students wishing to study at colleges and universities in the North America, this test was widely used in the Arabian Gulf. The TOEFL is a multiple-choice examination that measured listening, comprehension, vocabulary and reading [ 23 ]. This test measures the English language proficiency of non-native speakers of English and as such has relevance in the FMHS as the medical course there is taught in English. The nominal requirement at the FMHS is a minimum score of 500. As this test has a non-linear scoring system, this is substantially lower than the 550 – 580 required in Western universities in North America, Australasia and the UK. The Statistical Package for the Social Sciences was used for analysing the results [ 24 ]. Simple frequency analysis was used to describe demographics, TOEFL scores, unit test results and quantification of ethics issues. The correlation between the TOEFL score and Multidisciplinary Unit Test Score was assessed by Pearson's correlation coefficient as both variables were normally distributed and held a linear relationship. As the number of ethical issues identified was not distributed in a Gaussian fashion, frequency distributions were reported by median and range from minimum to maximum, while the appropriate non-parametric statistics were used: Mann-Whitney U test for comparisons between variables and Kendall's tau-b test for bivariate correlations. The level of statistical significance was defined as p < 0.05. The Research Ethics Committee of the United Arab Emirates University Faculty of Medicine and Health Sciences, which complies with the ethical rules for human experimentation that are stated in the Declaration of Helsinki, approved the project. Results All members of each class participated in this study. Participant demographics are detailed in Table 2 . The age range was from 19–21 years; all were practicing Muslims and had Arabic as their first language. Table 2 Participant demographics, TOEFL score and test results Class Cohort 2002–2003 Cohort 2003–2004 Male Female Male Female n 13 20 11 18 TOEFL* score prior to entry to medical school 498 +/- 27.8 518 +/- 58.2 514.9 +/- 40.9 505.6 +/- 29.0 Multidisciplinary Unit Test Score [pass = 75%] 82.8 +/- 5.1 82.7 +/- 6.6 81.9 +/- 6.8 83.9 +/- 3.6 [All enrolled students in this course participated] * The Test of English as a Foreign Language The similarities of issues identified and described across the group of students who attended the same clinic were highly suggestive that the events described actually occurred. However, there were sufficient differences in identified principles, evidence provided and labels given, to indicate that reports were written independently. Table 3 details the ethical issues identified. Although the initial expectation was that there were only a limited number of ethical issues that could be identified in a single clinical session, each student acting independently was able to correctly identify a median number of 4 different medical ethical issues (range 2–9) and correctly identify and label accurately a median of 2 different medical ethical issues (range 2–7) There was no significant difference in results between males and females except for 'autonomy mislabelled as a different ethical issue' (male: median = 0, range= 0–2; female median = 0, range = 0–3; p = 0.002) and 'autonomy / confidentiality mislabelled as a different ethical issue' (male: all results = 0; female median = 0, range = 0 – 2; p = 0.03). Table 3 Analysis of Ethics assignments: the median and range from minimum to maximum of the number of issues identified by individual students as detailed in their personal report Median Range Total number of ethical issues identified: Labelled correctly 2 2 – 7 Mislabelled as a different ethical issue or subset of Autonomy not defined 2 3 – 9 [Labelled correctly] + [mislabelled] 4 2 – 9 Total number of issues identified as ethical which were not ethical issues 0 0–4 Total number of autonomy issues identified Labelled correctly 1 0–4 Labelled as Autonomy, no subsection specified 0 0–3 Mis-labelled as a different ethical issue 0 0–3 Total number of autonomy: disclosure issues identified Labelled correctly 0 0–1 Labelled as Autonomy, no subsection specified 0 0–1 Mis-labelled as a different ethical issue 0 0–1 Total number of autonomy: truth telling issues identified Labelled correctly 0 0–1 Labelled as Autonomy, no subsection specified 0 0–1 Mis-labelled as a different ethical issue 0 0 – 0 Total number of autonomy: informed consent issues identified Labelled correctly 0 0 – 2 Labelled as Autonomy, no subsection specified 0 0 – 1 Mis-labelled as a different ethical issue 0 0 – 1 Total number of autonomy: competence issues identified Labelled correctly 0 0 – 0 Labelled as Autonomy, no subsection specified 0 0 – 1 Mis-labelled as a different ethical issue 0 0 – 0 Total number of autonomy: paternalism issues identified Labelled correctly 0 0 – 1 Labelled as Autonomy, no subsection specified 0 0 – 1 Mis-labelled as a different ethical issue 0 0 – 1 Total number of autonomy: confidentiality issues identified Labelled correctly 0 0 – 1 Labelled as Autonomy, no subsection specified 0 0 – 1 Mis-labelled as a different ethical issue 0 0 – 2 Total number of autonomy: decision – making issues identified Labelled correctly 0 0 – 2 Labelled as Autonomy, no subsection specified 0 0 – 2 Mis-labelled as a different ethical issue 0 0 – 2 Total number of beneficence issues identified Labelled correctly 0 0 – 2 Mis-labelled as a different ethical issue 0 0 – 1 Total number of non-malfeasance issues identified Labelled correctly 0 0 – 2 Mis-labelled as a different ethical issue 0 0 – 3 Total number of justice issues identified Labelled correctly 0 0 – 1 Mis-labelled as a different ethical issue 0 0 – 2 The four cohorts of students displayed a wide range of TOEFL scores ranging from the low 400 s through the mid 600 s. There was a moderate correlation between the TOEFL score and the multidisciplinary unit test score (r = 0.616, p < 0.001). There was no statistically significant correlation between the TOEFL score and the number of ethical issues identified. There were weak statistically significant correlations between the multidisciplinary unit test scores and ethical issues identified for 'total number of issues correctly identified' (r = 0.26, p = 0.008) and 'number of autonomy issues correctly identified' (r = 0.21, p = 0.04). There were no other statistically significant correlations between test scores and ethical issues identified. Discussion This study has demonstrated that these first year students were able to identify medical ethical issues in a clinical setting after minimal instruction. Although introductory courses by their very nature aim to build on the students' previously accumulated knowledge, understanding and experience, especially the unstructured kind based on life experience, the students in this study were able to develop this skill with very minimal instruction, when compared to the normal length of introductory medical ethics courses [ 25 ]. Feldman et al found important differences in the ethical practices and beliefs of Internists in the USA and China, even amongst those practicing Western medicine and suggested that some basic bioethical principles may be culturally based rather than universal [ 26 ]. One important feature in this regard is the concept of autonomy, where more traditional or tribal based societies, such as is seen in the Arabian Gulf States, often view autonomy as relating to the group rather than the individual. Hence, students learning ethics that incorporate Western constructs and are delivered in a Western language may fail to see the relevance or appropriateness to their understanding of their culture and society. However, this study has demonstrated that the students were able to correctly identify the concept of autonomy and some of its sub groupings. Although the students in this study demonstrated that they were able to use an imported model of ethical principles, this study did not directly address whether the students embraced the underlying conceptual framework, as the educational objectives of the introductory course were primarily to arouse interest and discussion amongst the students. However, informal review of the performance in examination settings of earlier cohorts of students who underwent similar educational programs suggests that by the end of their pre-registration medical training students do internalise the concepts and appear to understand their clinical applications. Further studies could investigate the impact of ethical training on their eventual behaviour as independent clinicians. This study had an underlying a priori assumption that the students would not be successful in identifying ethical issues due to a combination of the brief nature of the introductory seminars, their relative youth and inexperience with the adult learning model and being at the beginning of their medical training. Hence, the relatively high number of issues identified and the acceptable accuracy in labelling suggests that these students did demonstrate a reasonable level of skill even in the absence of a control group to help validate this conclusion. With little research available on the impact of early education in medical ethics, further studies utilising a control group would prove beneficial to determine what issues students would have been able to identify with no training. With ethics and professionalism being globally recognised as an integral component of primary medical degree curriculum, the results of the project suggest that early exposure may be beneficial in that it would provide a solid base in ethics, an essential requirement for their later clinical training. If ethical principles are clearly established early in the students' training, all future clinical training can be considered from an ethical standpoint. Jackson found that corporate managers' ethical decision-making was more influenced by their home country than by the country in which they resided [ 27 ]. This suggests the overriding importance culture and tradition has on one's values and beliefs systems. Hence the absence of a correlation between English language ability, accuracy in identification of ethical issues and number of issues identified suggests that in this case the basic conceptualization of medical ethics transcended the possible values and beliefs systems implicit in teaching a Western ethical curriculum in the English language in this environment. A number of researchers have suggested that the four principles of Western medical ethics have always existed in Islam [ 28 - 30 ]. Islam has an ethical and moral tradition which is intimately linked to Qur'anic teachings [ 31 ]. While the students would be familiar with ethical principles as enshrined in their religious beliefs, the linguistic constructs and labels of Western medical ethics as outlined in the four principle approach would be unfamiliar to these students. Perhaps the ethical principles embedded in their religion enabled the students to juxtapose Western linguistic constructs onto the ethical events observed in the clinical situation. They demonstrated an ability to correctly identify, describe and label ethical events despite using new language constructs, given that English is their second language. The relative importance of the intervention compared to their background knowledge could be further addressed in an expanded study using a control group. This study found at best a weak correlation between general academic ability and the number and accuracy of ethics issues identified. This suggests that even academically weak students were able to grasp the concepts being taught. Perhaps this outcome was enhanced by two factors; utilizing an adult learning model where students worked together in groups (although assignments were individually prepared) undergoing real rather than simulated experiences and the incorporation of their Islamic religious beliefs and self developed ethical reasoning. The students in this study had a broad range of English language skills as suggested by the large range in TOEFL results. Although there is no clear evidence that TOEFL correlates with the ability to conceptualise theoretical constructs presented in English, there is strong evidence that TOEFL correlates with grade point average at a North American Universities [ 32 , 33 ], and some evidence it correlates with the degree of participation of UAE students in problem based learning sessions [ 34 ]. This study only addressed the ability of medical students at the onset of their medical training to assimilate and conceptualise the basic principles of ethical reasoning. In particular, no assessment was made of the long-term impact of this course on 'moral enculturation' as this study has only described one component of a longitudinal six-year course in medical ethics. Conclusions This study has demonstrated that these students could identify medical ethical issues based on Western constructs, despite learning in English, their second language, being in the third week of their medical school experience and with minimal instruction. This result was independent of their academic and English language skills suggesting that ethical principles as espoused in the four principal approach may be common to the students' Islamic religious beliefs, allowing them to access complex medical ethical reasoning skills at an early stage in the medical curriculum. Competing interests None declared. Authors' contributions SM conceived the study, prepared the ethics application, coded the student's material, analysed the results, prepared and reviewed the manuscript. VY prepared the ethics application, prepared the coding sheet, coded the student's material, analysed the results, prepared and reviewed the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC509252.xml
555539	The effects of quercetin on SW480 human colon carcinoma cells: a proteomic study	Background High fruit and vegetable intake is known to reduce the risk of colon cancer. To improve understanding of this phenomenon the action of different phytochemicals on colon cells has been examined. One such compound is quercetin that belongs to the group known as flavonoids. The purpose of this study was to determine the influence of quercetin on the proteome of the SW480 human colon adenocarcinoma cell line, specifically to identify proteins that could be the molecular targets of quercetin in its amelioration of the progression of colon cancer. To this end, two-dimensional gel electrophoresis and mass spectrometry were used to identify proteins that underwent a change in expression following treatment of the cells with 20 μM quercetin. This could elucidate how quercetin may reduce the progression of colon cancer. Results Quercetin treatment of the SW480 human colon cancer cells was found to result in the decreased expression of three proteins and the increased expression of one protein. The identified proteins with decreased expression were type II cytoskeletal 8 keratin and NADH dehydrogenase Fe-S protein 3. The other protein with decreased expression was not identified. The protein with increased expression belonged to the annexin family. Conclusion Several proteins were determined to have altered expression following treatment with quercetin. Such changes in the levels of these particular proteins could underlie the chemo-protective action of quercetin towards colon cancer.	Background Colorectal cancer is the third most common cancer diagnosed both in men and in women in the United States [ 1 ]. The American Cancer Society estimates that 104,950 new cases of colon cancer (48,290 men and 56,660 women) and 40,340 new cases of rectal cancer (23,530 men and 16,810 women) will be diagnosed in 2005 [ 1 ]. It is estimated that in the United States colorectal cancer will cause about 10% of all cancer-related deaths during 2005 with 56,290 deaths (28,540 men and 27,750 women) [ 1 ]. For 1998–2000 the lifetime probability of men in the United States developing cancer of the colon and rectum was 1 in 17; for women it was 1 in 18 [ 2 ]. Genetic factors account for only 10% of colorectal cancers [ 3 , 4 ] and thus environmental factors must also be involved in colon cancer development. Up to 80% of all colorectal cancer cases and deaths are attributable to diet [ 5 ] and such cases of colorectal cancer and related deaths may be prevented by dietary modifications [ 6 ]. Studies have suggested that a diet with an increased intake of fruit and vegetables correlates with a reduced risk of colorectal cancer [ 7 , 8 ]. For this, the chemical components of plants known as phytochemicals may be crucially involved [ 9 ]. Particular phytochemicals characterized by their phenolic ring structures are termed polyphenols and the most abundant and widely distributed of these are the flavonoids. Quercetin is the most widely distributed flavonoid found in foods, and is most abundant in apples, onions, black tea and red wine [ 10 ]. Studies in vitro and in vivo have suggested that quercetin may have a protective role against breast [ 11 ], lung [ 12 ], liver [ 13 ], ovarian [ 14 ] and colon [ 15 - 17 ] cancers. Knowledge of how quercetin protects against cancer in general and colorectal cancer in particular could be gained by examining how quercetin affects the proteome of colon cancer cells. Specifically, the influence of quercetin on protein expression in the SW480 colon adenocarcinoma cell line could be instructive in elucidating the mechanisms underlying the protective role of the flavonoid against colon cancer. This would strengthen the scientific evidence for advocating a diet rich in fruit and vegetables to decrease the risk of developing colon cancer. Moreover, an identification of those proteins affected by quercetin could enhance understanding of the roles of these proteins in colon neoplasia. Use of proteomic techniques was therefore adopted in this study to determine the influence of quercetin treatment on protein expression in SW480 colon cancer cells. Quercetin treatment was found to result consistently in the decreased expression of three proteins and the increased expression of one protein. All, except one of the down-expressed proteins, were identified by mass spectrometry. Thus protein targets that could be the molecular basis of inhibition of colon cancer by quercetin were obtained. Methods Cell culture SW480 human colon carcinoma cells (ATCC, Rockville, MD) were grown in Leibovitz's L-15 medium with 2 mM L-glutamine (ATCC, Rockville, MD), supplemented with 10% fetal bovine serum (Equitech-Bio Inc., Kerrville, TX). Cells were maintained in 75 cm 2 canted-neck flasks in 15 ml medium and incubated at 37°C without CO 2 . They were subcultured once per week at a ratio of 1:4. Quercetin treatment When cells were about 90% confluent at seven days after passage the medium was discarded and replaced with medium containing 20 μM quercetin (Sigma, St. Louis MO). Cells were incubated for 48 h in the quercetin-containing medium at 37°C in air. Isolation of protein Following incubation of the cells in quercetin for 48 h the medium was discarded and the cells washed three times for 1 min each time with phosphate-buffered saline. After complete removal of the final wash buffer, to each culture flask was added 240 μl boiling sample buffer I (0.3% sodium dodecyl sulfate (SDS), 200 mM dithiothreitol (DTT), 50 mM Tris-HCl, pH 8.0). The lysed cells were scraped together using a cell scraper (Fisher, Pittsburgh PA). The lysate from each culture flask was transferred to a 1.5 ml microfuge tube and heated for 5 min at 100°C. After chilling the tube on ice 24 μl (1/10 volume) of sample buffer II (50 mM magnesium chloride, 0.1% DNAse I, 0.025% RNAse A, 0.5 M Tris-HCl, pH 8.0) was added. Acetone was added to 80% (v/v) and the tube incubated on ice for 20 min. After centrifugation at 12,000 rpm for 10 min the supernatant was discarded and the pellet resuspended in 240 μl freshly prepared immobilized pH gradient (IPG) sample buffer (7 M urea, 2 M thiourea, 4% CHAPS, 1% DTT and 2% pH 3–10 ampholytes). The protein concentrations of the suspensions were measured using the method of Bradford with Bio-Rad reagent and bovine plasma gamma globulin as standard (Bio-Rad, Hercules, CA). Immobilized pH gradient electrophoresis As the first dimension of two-dimensional electrophoresis Bio-Rad pH 3–10 immobilized pH gradient (IPG) strips were used to separate the cell proteins according to their isoelectric points. A volume of the cell protein solution containing 2 mg protein was mixed with rehydration buffer (6 M urea, 2 M thiourea, 2% CHAPS, 0.4% DTT and 0.5% pH 3–10 ampholytes) for a final volume of 300 μl per IPG gel. The IPG strips were loaded with the protein sample and the strips passively rehydrated for 16 h. Isoelectric focusing of the strips was at 250 V for 15 min followed by rapid ramping to10,000 V for 3 h and maintenance at the peak voltage for another 60,000 Vh. Current was limited to 50 μA per gel. Second dimension slab gel The IPG strips were equilibrated with 6 M urea, 30% glycerol, 2% SDS, 1.55 M Tris, 2 mM tributylphosphine (TBP) and 0.00125% bromophenol blue (BPB) for 25 min with shaking at room temperature. The strips were rinsed in cathode buffer and applied to the top of 12% acrylamide slab gels. The cathode buffer contained 50 mM Tris, 384 mM glycine and 6.9 mM SDS. Low-melting point agarose (1% in cathode buffer) was layered over the strips. The anode buffer contained 25 mM Tris, 192 mM glycine and 3.5 mM SDS. The buffers were chilled to 4°C prior to use. A cooling plate maintained the system (Genomic Solutions, Ann Arbor, MI) at low temperature. The gels (22 cm × 22 cm × 1 mm) were run at 20 W per gel until the BPB dye front had migrated to within 1 cm from the bottom of the gel. The gels were stained with Coomassie blue. Quantification of protein spots Second dimension gels were analyzed by Phoretix software (Nonlinear Dynamics, Newcastle, UK). Comparison between gels was achieved using normalized spot volumes. To begin with, differences greater or equal to 1.5-fold were considered to be significant. If these differences were subsequently reproduced in additional experiments, despite possibly being of lower magnitude, they were held to be consistent. Mass spectrometry Differentially expressed protein spots were excised from the gels and digested with trypsin as reported previously [ 18 ]. Each gel plug was incubated with 150 μl of 50 mM ammonium bicarbonate containing 12.2 M acetonitrile. The gels were then dried and rehydrated with 5 μl of 50 mM ammonium bicarbonate containing 0.5 μg trypsin. This solution was added in 5 μl aliquots until the gel piece regained its original size. The gel was then covered with 50 mM ammonium bicarbonate and incubated overnight at 30°C. After the addition of 1.5 μl of 880 mM trifluoroacetic acid the peptides were extracted with 50 mM ammonium bicarbonate containing 14.6 M acetonitrile. The supernatants were dried to approximately 10 μl. The samples were each mixed with MALDI matrix solution prepared as 5 mg/ml α-cyano-4-hydroxycinnamic acid in a solution containing 1:1:1 acetonitrile, ethanol and 0.1% trifluoroacetic acid (pH 2.0). Each mixture was spotted on a MALDI target and allowed to air-dry. Peptide masses were then obtained by MALDI-TOF MS (Applied Biosystems 4700 Proteomics Analyzer). Calibration was performed with the same procedure using mixtures of peptides with known molecular masses. MS/MS ions produced by MALDI-TOF from the tryptic peptides and the results of a Mascot search were used to determine protein identification. The NCBInr database, i.e. the non-identical nr protein database of the National Center for Biotechnology Information, was utilized for the search. Results Two-dimensional gel electrophoresis Fig. 1 demonstrates a gel obtained from two-dimensional gel electrophoresis of protein extracted from SW480 cells. More than 500 protein spots could be observed. The gels obtained from two-dimensional gel electrophoresis of quercetin-treated and untreated (control) SW480 cell proteins were compared (Fig. 2 ). Two mg protein was loaded in each case. Four proteins were revealed to have undergone a consistent change in expression following treatment with 20 μM quercetin for 48 h. Three proteins had a decreased and one protein an increased expression. The changes in these particular proteins were consistent between four separate experiments, i.e. four separate quercetin treatments coupled in each case with an untreated control. Two experiments were run concurrently and then another two on a different occasion. The proteins with altered expression following quercetin treatment, consistent between different experiments, are labeled 1–4 in Fig. 2 . With observation solely by eye some of the differences may not be readily apparent, but they were verified by analysis of the gels using Phoretix 2-D analysis software (Table 1 ). The results in Table 1 are the means from analysis of the gels from two separate experiments conducted concurrently. In parentheses are the means from a second set of two experiments run concurrently at a different time to the first two experiments. The variation between the two sets of results can be attributed to the cells having been subcultured several times between the first and second sets of experiments. Furthermore, the cells could have been in a stage of growth for the second set of experiments different from that for the first. Despite these sources of variation, a consistent effect of quercetin in all four experiments was searched for. From these results proteins 1, 2 and 4 each had decreased expression following quercetin treatment of the cells. Protein 3 had increased expression. Figure 1 Two-dimensional gel of protein from SW480 colon adenocarcinoma cells. SW480 cells were cultured as described in Methods . In this representative case the cells were not treated with quercetin and were thus a control. Cells were harvested; protein was extracted and subjected to two-dimensional electrophoresis as described in Methods . The gel was stained with Coomassie blue. The protein spots indicated were those subsequently determined to be significant in the effects of quercetin. Figure 2 Two-dimensional gels of protein from control and quercetin-treated cells. After 7 days in culture SW480 cells were incubated for 48 h in medium containing A. 0.2% dimethylsulfoxide (DMSO), since DMSO was the vehicle in which stock quercetin had been dissolved, and B. 20 μM quercetin and 0.2% dimethylsulfoxide (DMSO). Cells were harvested, protein extracted and subjected to two-dimensional electrophoresis as described in Methods. The gels represent protein obtained from the control and quercetin-treated cells of one of four separate treatment groups. Treatment was identical for each group. The indicated protein spots differed in levels consistently for each of these treatment groups. Table 1 Effect of quercetin treatment of SW480 cells on the volume of protein spots on 2-D gels. The 2-D gels of protein from the untreated (control) and quercetin-treated SW480 cells were analyzed with Phoretix software. Normalized spot volumes were computed, averaged for two separate experiments run concurrently, and compared between the control and quercetin-treated gels. The 2-D gels obtained from one of the experiments are presented in Fig. 2. Results are the means, from the two experiments, for protein spots that differed in volume consistently in these two experiments and a subsequent two experiments. Alongside these results in parentheses are the mean results from the second set of two experiments. Protein spot number Control volume Quercetin volume Increase/Decrease Fold change 1 6.61 (1.65) 2.89 (1.35) Decrease -2.29 (-1.22) 2 5.91 (4.18) 2.06 (3.26) Decrease -2.87 (-1.28) 3 0.118 (0.036) 0.243 (0.108) Increase +2.06 (+3.00) 4 0.411 (0.102) 0.088 (nd) Decrease -4.67 (-high) Mass spectrometry The protein spots that were differentially expressed following quercetin treatment were excised from the gels and digested with trypsin. The tryptic digests were subjected to matrix-assisted laser desorption and ionization-time of flight (MALDI-TOF) mass spectrometry. The spectra were analyzed and the data entered into appropriate databases to identify the proteins. Table 2 lists the protein identities together with their functions. Protein number 1 could not be identified. Due to its proximity on the 2-D gels to protein number 2, i.e. type II cytoskeletal 8 keratin, it is possible that it is the same protein, but differing in its modification. It is known that this keratin is phosphorylated on serine residues; a process which is enhanced during epidermal growth factor stimulation and mitosis. Table 2 Proteins differentially expressed following quercetin treatment of SW480 cells. Protein spots determined to be present at different levels on gels following quercetin treatment of the SW480 cells were excised from the gels, digested with trypsin and subjected to MALDI-TOF mass spectrometry as described in Methods . From the mass spectra the identities of the proteins were determined using the appropriate databases. Number from gel Protein Function 2 Keratin, type II cytoskeletal 8 Cytoskeletal structure, angiogenesis-related 3 Annexin family Ca 2+ and phospholipid binding, regulation of exocytic and endocytic pathways 4 NADH dehydrogenase (ubiquinone) Fe-S protein 3 Transfer of electrons from NADH to the respiratory chain Discussion Four proteins were found to have their expression consistently altered on quercetin treatment of SW480 colon carcinoma cells. Three of these proteins were down-regulated and one was up regulated following exposure to quercetin. Using mass spectrometry three of the proteins were identified. Those that were down-regulated were type II cytoskeletal 8 keratin and NADH dehydrogenase (ubiquinone) Fe-S protein 3. The up-regulated protein belonged to the annexin family. Type II cytoskeletal 8 keratin (keratin 8) in another proteomic study has been found to have a significantly lower abundance in the normal mucosa compared with the adjacent colon tumor for one specific patient for two out of three gel protein features identified as keratin 8 [ 19 ]. For the same patient, keratins 18 and 19 also had significantly lower concentrations in the normal mucosa compared with the adjacent tumor. Similarly, with paired samples of normal colon mucosa and adenocarcinomas derived from 27 patients, proteomic analysis revealed that keratin 18 was at a significantly lower level in the normal mucosa compared with the tumor tissue [ 20 ]. In these respects down regulation of keratin 8 by quercetin treatment of SW480 cells would be akin to the cells becoming more "normal", i.e. less tumorigenic. Further support for this contention derives from analysis using the cDNA macroarray technique of the differential gene expression in isolated human colorectal cancer and respective normal mucosa from two patients [ 21 ]. The tumors showed up-regulation of expression of type II cytoskeletal 8 keratin and other angiogenesis-related genes to over 5-fold the levels in normal mucosa. In the present study the down-regulation of type II cytoskeletal 8 keratin by quercetin may therefore demonstrate the decreased potential for angiogenesis and hence reduction of any tumor. Further support for the reduction in expression of type II cytoskeletal 8 keratin following quercetin treatment of SW480 colon cancer cells being reflective of decreased neoplasia is derived from a proteomic analysis of lung adenocarcinomas [ 22 ]. Cytoskeletal 8 keratin, in addition to other keratins, had reduced expression in normal lung samples compared with lung adenocarcinomas. Furthermore, several isoforms of cytoskeletal 8 keratin were identified. These had differing pI, but similar molecular weights, and apparently result from differing extents of posttranslational phosphorylation [ 22 ]. This supports our contention that unidentified protein 1 in the present study may be an isoform of type II cytoskeletal 8 keratin. A crucial role for this keratin in the malignant phenotype is suggested by studies on its increased expression by transfecting stratified epithelial cells with the cytoskeletal 8 keratin gene [ 23 ] and the epidermal consequences for transgenic mice expressing the human keratin 8 [ 24 ]. In each case neoplastic transformation of the cells to the malignant phenotype occurred. NADH dehydrogenase (ubiquinone) Fe-S protein 3 is a component of complex 1 of the mitochondrial electron transport chain. It is involved in transfer of electrons from NADH to ubiquinone in the respiratory chain. A similar component of complex 1 of the respiratory chain, NADH-ubiquinone oxidoreductase, has been determined from a proteomic analysis to be present in colon tumor tissue and the surrounding normal mucosa [ 19 ]. Interestingly, its abundance was higher in the tumor than in the normal mucosa. This suggests that the lower level of NADH dehydrogenase (ubiquinone) Fe-S protein 3 in our quercetin-treated colon cancer cells compared with its level in the untreated cells is linked to a decreased tumorigenicity of the cells following quercetin treatment. Furthermore, NADH dehydrogenase (ubiquinone) has also been determined by others to have a decreased abundance in HT-29 human colon cancer cells following exposure for 24 h to 150 μM quercetin [ 25 ]. This supports what we determined for NADH dehydrogenase (ubiquinone) Fe-S protein 3. The implication is that the consequent reduction in oxidative phosphorylation of substrates by quercetin is associated with decreased tumorigenicity. Following quercetin treatment, the only protein to be up-regulated belonged to the annexin family. In another proteomic study annexins I, III, IV and V have been determined to have a greater abundance in normal mucosa compared with neighboring tumor tissue [ 19 ]. Thus the rendering of the SW480 colon cancer cells less tumorigenic by treatment with quercetin could be reflected by the increased abundance of members of the annexin family. To strengthen this argument the level of annexin II, a protein that inhibits cell migration, was found to increase in HT-29 human colon cancer cells following treatment with quercetin for 24 h and 48 h [ 25 ]. Inhibiting the ability of the cells to migrate would contribute to explaining the anti-cancer activity of quercetin. In addition, annexin I, which promotes apoptotic cell engulfment, increased in HT-29 cells exposed to quercetin for 48 h. A role for apoptosis was also suggested when annexin IV, a key regulator of apoptosis, was found to increase in NCOL-1 human preneoplastic colonocytes following treatment with quercetin for 24 h [ 26 ]. Apoptosis, mediated by members of the annexin family, may therefore also underlie the anti-cancer activity of quercetin. Conclusion Three proteins have been identified as potential molecular targets for the proposed action against colon cancer of quercetin the plant flavonoid. The application of proteomic techniques demonstrated the response of these proteins to quercetin treatment of colon cancer cells. Other research in the field supported the response of each of these proteins to quercetin. This serves to validate the previous work. Furthermore, the responses could be rationally described in terms of an anti-cancer action. This strengthens earlier findings of quercetin's protection against colon cancer using cell culture and animal models. A basis is thus provided for further research with quercetin and perhaps even advancement to studies with humans. An intriguing aspect to consider is whether quercetin could form the basis of directed drug design to yield drugs with greater efficacy against the identified molecular targets and thereby provide an effective treatment of colon cancer. List of abbreviations used NADH, nicotinamide adenine dinucleotide, reduced; MALDI-TOF, matrix-assisted laser desorption and ionization-time of flight; MS, mass spectrometry 2-D, two-dimensional; SDS, sodium dodecyl sulfate; DTT, dithiothreitol; IPG, immobilized pH gradient; CHAPS, 3-[(3-cholamidopropyl) dimethylammonio]-1-propane-sulfonate; TBP, tributylphosphine; BPB, bromophenol blue; DMSO, dimethylsulfoxide; NCBI, National Center for Biotechnology Information. Competing interests The authors declare that they have no competing interests. Authors' contributions MFM treated the cells, performed the two-dimensional electrophoresis and gel analysis, submitted protein spots for mass spectrometry, undertook the literature search on the identified proteins, drafted the manuscript, submitted the manuscript and completed all the necessary revisions to make it acceptable for publication. KK carried out trypsin digestion of the protein spots and undertook the mass spectrometry. RO provided oversight for the mass spectrometry. JLH and AG participated in conception and design of the study. All the authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC555539.xml
538272	Prevalence and determinants of diabetes mellitus among Iranian patients with chronic liver disease	Background Alterations in carbohydrate metabolism are frequently observed in cirrhosis. We conducted this study to define the prevalence of diabetes mellitus (DM) and impaired glucose tolerance (IGT) in Iranian patients with chronic liver disease (CLD), and explore the factors associated with DM in these patients. Methods One hundred and eighty-five patients with CLD were enrolled into the study. Fasting plasma glucose and two-hour plasma glucose were measured in patients' sera. DM and IGT were diagnosed according to the latest American Diabetes Association criteria. Results The subjects included 42 inactive HBV carriers with a mean age of 42.2 ± 12.0 years, 102 patients with HBV or HCV chronic hepatitis with a mean age of 41.2 ± 10.9 years, and 41 cirrhotic patients with a mean age of 52.1 ± 11.4 years. DM and IGT were diagnosed in 40 (21.6%) and 21 (11.4%) patients, respectively. Univariate analysis showed that age (P = 0.000), CLD status (P = 0.000), history of hypertension (P = 0.007), family history of DM (P = 0.000), and body mass index (BMI) (P = 0.009) were associated with DM. Using Multivariate analysis, age (OR = 4.7, 95%CI: 1.8–12.2), family history of DM (OR = 6.6, 95%CI: 2.6–17.6), chronic hepatitis (OR = 11.6, 95%CI: 2.9–45.4), and cirrhosis (OR = 6.5, 95%CI: 2.4–17.4) remained as the factors independently associated with DM. When patients with cirrhosis and chronic hepatitis were analyzed separately, higher Child-Pugh's score in cirrhotic patients (OR = 9.6, 95%CI: 1.0–88.4) and older age (OR = 7.2, 95%CI: 1.0–49.1), higher fibrosis score (OR = 59.5, 95%CI: 2.9–1211.3/ OR = 11.9, 95%CI: 1.0–132.2), and higher BMI (OR = 30.3, 95%CI: 3.0–306.7) in patients with chronic hepatitis were found to be associated with higher prevalence of DM. Conclusions Our findings indicate that patients with cirrhosis and chronic hepatitis are at the increased risk of DM occurrence. Older age, severe liver disease, and obesity were associated with DM in these patients.	Background Alterations in carbohydrate metabolism are frequently observed in liver cirrhosis. Glucose metabolism impairment in cirrhotic patients, both in fasting state and in response to oral glucose or meals has been widely documented in the literature [ 1 - 5 ]. There is a wide variability in the prevalence of overt diabetes mellitus (DM) and impaired glucose tolerance (IGT) according to various reports. In fact, the laboratory methods and the criteria used to state glucose metabolism status are different among various studies, considering the fact that the criteria for diagnosing DM and IGT have been modified a couple of times during last decade. On the other hand, the majority of the papers focused on cirrhosis [ 2 , 3 , 6 - 10 ] although a number of studies evaluated patients with chronic hepatitis, as well [ 4 , 5 , 11 , 12 ]. Furthermore, in many studies investigating the correlation between liver disease and glucose tolerance, a number of potent factors for DM such as BMI have been overlooked. In this study, for the first time in Iran, we reported the prevalence of DM and IGT in patients with chronic liver disease (CLD) using the latest generally accepted criteria, and investigated independent correlation of CLD with DM, considering other known possible DM risk factors. Moreover, we explored the factors that might be potentially associated with DM in patients with cirrhosis and chronic hepatitis. Methods From October 2002 to March 2003, all consecutive patients with chronic liver disease referred to "Tehran Hepatitis Center" were enrolled into the study. Tehran Hepatitis Center is a referral specialized clinic for liver diseases where many patients suffering from liver diseases and hepatitis from around Iran are referred to in order to receive consultation and clinical medical care. Pregnant females, patients under 20 years old, those who were on regular corticosteroid or hydrochlorothiazide therapy, known or suspected cases of hemochromatosis, or autoimmune disease were excluded. Having a clinical, biochemical (serum amylase and/or lipase elevation) or ultrasonographic evidence for chronic pancreatitis was also considered an exclusion criterion. No patient had a history of habitual drinking. All of the patients were Moslem and belonged to the white race. A total number of 193 patients who met the criteria were eligible to enter the study. First group included 41 cirrhotic patients. Mean age was 52.1 ± 11.4 years ranging between 26–74 years. Diagnosis of cirrhosis was confirmed by histology in 17 (41.5%) patients. The occurrence of signs or biochemical evidences of liver decompensation, ultrasound features of portal hypertension and/or esophageal varices in gastroscopy were used for the clinical diagnosis in the remaining cases. No cirrhotic patients had evidence of hepatocellular carcinoma, screened by serum alpha-fetoprotein level test and abdominal ultrasonography. Severity of liver cirrhosis was graded according to Child-Pugh's classification. Second group included 102 patients with chronic hepatitis B, or C. Mean age was 41.2 ± 10.9 years ranging between 22–67 years. All patients had adequate documentation of elevated serum aminotransferases for more than 6 months, and viral hepatitis molecular assays by qualitative RT-PCR. In 91 (89.2%) patients liver biopsy reports were accessible. The histological staging and grading in liver biopsy was scored according to Knodell scoring. Third group included 42 inactive hepatitis B virus (HBV) carriers who were hepatitis B s antigen (HBsAg) positive, quantitative HBV DNA level less than 10 5 copies/ml (ROCHE Cobas Amplicore) and normal liver enzymes. The mean age in this group was 42.2 ± 12.0 years ranging between 23–84 years. Eight patients with nonalcoholic steatohepatitis (NASH) were initially enrolled but were not entered in analysis because of the low case number. Therefore analysis was finally performed for 185 patients. Informed consent in writing was obtained from each patient involved and the study protocol conformed to the ethical guidelines of the 1975 Declaration of Helsinki as approved by institutional review board. Initial data were collected by chart review and interview. Then, two venous blood samples were taken: First sample in the morning after a 12-hour overnight fast to measure fasting plasma glucose (FPG) level, triglycerides (TG) level, and cholesterol (Chol) level; and a second sample following 2 hours after eating 75 gr glucose to measure two-hour post-loaded glucose (2-hr PG). FPG and 2-hr PG measurement were repeated on two other samples in second session. Patients receiving therapy with insulin or oral hypoglycemic medications were considered as diabetics. In other patients, FPG ≥ 126 mg/dl or 2-hr PG ≥ 200 mg/dl on more than one occasion was used as diagnostic for DM in agreement with the latest American Diabetes Association (ADA) criteria [ 13 ]. FPG between 110 mg/dl and 126 mg/dl was considered as impaired fasting glucose (IFG), and 2-hr PG between 140 mg/dl and 200 mg/dl was considered as IGT according to ADA definitions [ 13 ]. Body mass index (BMI) was calculated using the standard formula of weight in kilogram divided by square of height in meters (kg/m 2 ). Results were expressed as mean ± standard deviation (SD). Comparison between diabetic and non-diabetic groups was made using Students T test for continuous variables and the Chi-square or Fisher exact test for categorical variables. At univariate analysis the factors possibly associated with DM development were evaluated. A multivariate analysis based on a stepwise logistic regression model was used to assess the independent effect of all variables found significant at the univariate analysis. P-value less than 0.05 was considered significant. All statistical analyses were performed using SPSS for Windows software (version 10.0; SPSS Inc. Chicago, Illinois, USA). Results The sample population contained 150 (81.1%) males and 35 (18.9%) females. The overall mean age was 43.8 ± 12.0 years ranging between 22 and 84 years. In the total of 185 patients, DM was found in 40 (21.6%) patients, and IFG and/or IGT was found in 21 (11.3%) patients. Thirty patients were already aware of their problem whereas the diagnosis of DM was new in 10 patients. By univariate analysis a number of variables including the factors mentioned by ADA as risk factors for type II diabetes [ 13 ] in addition to status and etiology of liver disease, interferon therapy, and history of or ongoing habitual smoking were compared between diabetic and non-diabetic patients (Table 1 ). We found that the prevalence of DM was significantly associated with older age (P = 0.000), CLD status (P = 0.000), history of hypertension (P = 0.007), family history of DM (P = 0.000), and higher BMI (0.009). Excluding the inactive carriers, we compared DM rate in two other groups. The prevalence of DM among cirrhotic cases (53.7%) was significantly higher than that of chronic hepatitis patients (13.7%), (P = 0.000). Table 1 Clinical and epidemiological characteristics of CLD patients with and without DM Diabetic Non-diabetic P-value Number 40 148 Sex NS Female 9 (22.5%) 26 (17.9%) Male 31 (77.5%) 119 (82.1%) Age 50.3 ± 11.4 40.2 ± 10.6 0.000 CLD status 0.000 Inactive carrier 4 (10.0%) 38 (26.2%) Chronic hepatitis 14 (35.0%) 88 (60.7%) Cirrhosis 22 (55.0%) 19 (13.1%) CLD etiology NS HBV 24 (60.0%) 85 (58.6%) HCV 13 (32.5%) 58 (40.0%) Cryptogenic 3 (7.5%) 2 (1.4%) Family history of DM* 0.000 Yes 21 (52.5%) 29 (20.0%) No 19 (47.5%) 116 (80%) History of hypertension † 0.007 Yes 10 (25.0%) 13 (9.0%) No 30 (75.0%) 132 (91.0%) BMI 27.5 ± 4.6 24.7 ± 4.0 0.009 Interferon therapy NS Yes 6 (15.0%) 49 (33.8%) No 34 (85.0%) 96 (66.2%) Smoking NS Yes 13 (32.5%) 37 (25.5%) No 27 (67.5%) 108 (74.5%) TG 179.2 ± 74.1 142.8 ± 71.4 NS Chol 192.4 ± 39.8 174.7 ± 44.4 NS Indicates presence of at least one first-degree relative affected by DM. † Includes patients who require diet or antihypertensive agents. At multivariate analysis age (P = 0.008, OR = 4.7, 95%CI: 1.8–12.2), family history of DM (P = 0.000, OR = 6.6, 95%CI: 2.6–17.6), chronic hepatitis (0.000, OR = 11.6, 95%CI: 2.9–45.4), and cirrhosis (P = 0.000, OR = 6.5, 95%CI: 2.4–17.4) showed up as the only factors independently associated with DM prevalence rate (table 2 ). Table 2 Logistic regression analysis of factors associated with DM among patients with CLD OR 95% CI P-value Age < 45 years 1.0 ≥ 45 years 4.7 1.8 – 12.2 0.001 CLD status Inactive carrier 1.0 Chronic hepatitis 11.6 2.9 – 45.4 0.000 Cirrhosis 6.5 2.4 – 17.4 0.000 Family history of diabetes No 1.0 Yes 6.6 2.6 – 16.7 0.000 History of hypertension No 1.0 Yes 2.3 0.7 – 8.1 NS BMI > 25 1.0 ≥ 25 1.4 0.5 – 3.4 NS Since both cirrhosis and chronic hepatitis were found as independent factors associated with DM occurrence, we analyzed these two groups separately. The results were summarized in table 3 . Table 3 Clinical and epidemiological characteristics of patients with and without DM separated to cirrhosis and chronic hepatitis groups Patients with cirrhosis Patients with chronic hepatitis Diabetic Non-diabetic P-value Diabetic Non-diabetic P-value Number 22 19 14 88 Sex NS NS Female 4 (18.2%) 3 (15.8%) 2 (14.3%) 12 (13.6%) Male 18 (81.8%) 16 (84.2%) 12 (85.7%) 76 (86.4%) Age 56.9 ± 10.6 46.6 ± 10.0 0.003 49.7 ± 7.8 39.9 ± 10.7 0.001 CLD etiology NS NS HBV 11 (50.0%) 13 (68.4%) 10 (71.4%) 37 (42.0%) HCV 8 (36.4%) 4 (21.1%) 4 (28.6%) 51 (58.0%) Criptogenic 3 (13.6%) 2 (10.5%) - - Family history of DM NS 0.01 Yes 9 (40.9%) 3 (15.8%) 8 (57.1%) 21 (23.9%) No 13 (59.1%) 16 (84.2%) 6 (42.9%) 67 (76.1%) History of hypertension NS NS Yes 6 (27.3%) 1 (5.3%) 3 (21.4%) 8 (9.1%) No 16 (72.7%) 18 (94.7%) 11 (78.6%) 80 (90.9%) BMI 26.4 ± 3.4 26.4 ± 4.0 NS 27.7 ± 4.8 24.5 ± 3.1 0.02 Interferon therapy NS NS Yes 2 (9.1%) 3 (15.8%) 4 (28.6%) 46 (52.3%) No 20 (90.9%) 16 (84.2%) 10 (71.4%) 42 (47.7%) Smoking NS NS Yes 5 (22.7%) 5 (26.3%) 7 (50.0%) 25 (28.4%) No 17 (77.3%) 14 (73.7%) 7 (50.0%) 63 (71.6%) TG 145.5 ± 58.6 109.3 ± 75.2 NS 174.9 ± 82.5 140.6 ± 53.8 NS Chol 141.6 ± 50.5 151.8± 32.5 NS 199.8 ± 42.8 163.9 ± 36.1 NS Child-Pugh's score 0.04 Score A 13 (65.0%) 18 (94.7%) - - - Score B 7 (35.0%) 1 (5.3%) Histological staging 0.003 0–1 - - - 1 (8.3%) 33 (41.8%) 2–3 3 (25.0%) 30 (38.0%) 4–6 8 (66.7%) 16 (20.3%) Histological grading* NS 0–4 - - - 2 (16.7%) 36 (45.6%) 5–8 8 (66.7%) 34 (43.0%) ≥ 9 2 (16.7%) 9 (11.4%) * According to Knodell score Out of 41 cirrhotic patients, 22 (53.7%) patients were diabetic and 7 (17.1%) patients had IFG and/or IGT. Univariate analysis showed that only two factors were associated with DM rate. Mean of age in diabetic cases was significantly higher than that of non-diabetic ones (P = 0.003). Moreover, DM was significantly more prevalent in patients with Child-Pugh's score B than score A (P = 0.04). Since there was no score C in study sample, we could not evaluate this class of cirrhosis. After applying logistic model, only Child-Pugh's score kept its significance (P = 0.04, OR = 9.6, 95%CI: 1.0–88.4) as an independent predictive factor for DM in cirrhotic patients (table 4 ). Table 4 Logistic regression analysis of factors associated with DM among cirrhotic patients and patients with chronic hepatitis. OR 95% CI P-value Cirrhosis Age < 45 years 1.0 ≥ 45 years 2.1 0.4 – 10.5 NS Child Pugh's Score Score A 1.0 Score B 9.6 1.0 – 88.4 0.04 Chronic hepatitis Age > 45 years 1.0 ≥ 45 years 7.2 1.0 – 49.1 0.04 Family history of diabetes No 1.0 Yes 2.0 0.3 – 13.9 NS BMI > 25 1.0 ≥ 25 30.3 3.0 – 306.7 0.004 Histological staging 0–1 1.0 2–3 59.5 2.9 – 1211.3 0.008 4–6 11.9 1.0 – 132.2 0.04 In chronic hepatitis group including 102 patients, DM was found in 14 (13.7%) patients and IFG and/or IGT was found in 11 (10.8%) patients. There was no significant difference between diabetic and non-diabetic cases in regard with sex, etiology of chronic hepatitis, hypertension, interferon therapy, smoking, and serum TG and Chol levels. On the other hand, diabetic patients had higher mean age compared with non-diabetic cases (P = 0.001). More cases of diabetic patients compared with non-diabetic ones had a family history of DM (P = 0.01). The mean BMI of patients with DM was higher than that of patients without DM (P = 0.02). Furthermore, liver biopsy showed significantly more fibrosis activity in diabetic patients compared with non-diabetic cases (P = 0.003), whereas no difference in diabetic vs. non-diabetic patients was seen with respect to histological grading. Multivariate analysis revealed that older age (P = 0.04, OR = 7.2, 95%CI: 1.0–49.1), higher BMI (P = 0.004, OR = 30.3, 95%CI: 3.0–306.7), and more severe fibrosis activity (stage 2–3: P = 008, OR = 59.5, 95%CI: 2.9–1211.3; stage 4–6: P = 0.04, OR = 11.9, 95%CI: 1.0–132.2) were the predictive variables for DM in patients with chronic hepatitis (table 4 ). Discussion There is a wide range in the prevalence of glucose metabolism alterations in cirrhotic patients in various studies. The frequency for overt DM has been reported from 10% to 50% and for IGT up to more than 70% [ 1 - 5 , 7 , 8 , 10 , 11 ]. Such variations may be mainly due to the criteria employed in the diagnosis of DM. In our study, we employed latest ADA criteria and DM was presented in 21.6% of patients with CLD (53.7% in cirrhosis, 13.7% in chronic hepatitis, and 9.5% in HBV inactive carrier). In Iran the estimated prevalence of overt DM in general population is in the range of about 7.5–10 percent [ 14 - 16 ], which is about 2 to 3 times less than what we found in this study, indicating that patients with CLD are a high-risk population for DM. In spite of this fact, we showed that 10 out of 40 (25%) diabetic cases found in this study were unaware of their endocrinal problem before being screened as part of this study. This finding highlights the importance of periodical screening of the patients with CLD especially in advanced stages. Literature frequently demonstrated the higher prevalence of DM and IGT in cirrhosis than in chronic hepatitis [ 4 , 5 , 11 ]. However, about the higher DM rate in patients with chronic hepatitis compared with people without liver disease, there is not any widely general agreement. Some studies claimed that DM rate is not appreciably different when compared with general population or individuals without liver disease [ 11 , 17 ]. These studies believed that only cirrhosis but not chronic hepatitis were associated with DM [ 17 ]. In our study, multivariate analysis indicates independent association between chronic hepatitis and DM rate, despite the fact that we compared DM occurrence among three groups who all suffered from liver disease. Moreover, our data indicate that the frequency of DM increases significantly with the severity of the liver disease both in cirrhotic cases and in patients with chronic hepatitis. These findings suggest that liver fibrosis but not cirrhosis itself, is the event associated with glucose intolerance. A weak association between glucose intolerance and severity of liver disease in cirrhosis has already been reported by Muller et al [ 7 ], even though they used different criteria to evaluate liver damage severity. Another study applying Child-Pugh's classification showed similar results [ 11 ]. In this context it is worthy to note that although the underlying mechanism of glucose intolerance in cirrhosis has not been fully elucidated, it can be mainly explained by the insulin resistance [ 9 ], in addition to reduced glucose sensitivity in liver cirrhosis [ 18 , 19 ]. More interestingly, a recent study suggests that insulin resistance occurs already in the early stages of the chronic hepatitis course [ 12 ], and another study investigating chronic hepatitis patients with normal glucose tolerance revealed a strong relationship between insulin sensitivity and fibrosis score [ 20 ]. In contrast, there is another hypothesis that indicates CLD as a consequence of DM. This theory states that occurrence of insulin resistance initially facilitates lipolysis, and increases free fatty acid deposition in liver, which increases products of lipid peroxidation inducing oxidative stress. This results in cytokine-mediated hepatic inflammatory damage that induces collagen deposition and eventually fibrosis [ 21 , 22 ]. Although in this study we could not determine if the onset of DM was before or after of liver disease, our findings show that chronic hepatitis per se has an independent association with DM, and development of DM in chronic hepatitis patients was correlated to the severity of liver fibrosis. No differences in DM rate were found when we studied patients according to CLD etiological categories both in cirrhosis and in chronic hepatitis group. A positive link between hepatitis C infection and development of DM has been suggested in some studies but not completely characterized. Mason et al surveying a large cohort of patients with viral chronic hepatitis showed a relatively strong association between DM and HCV infection [ 23 ]. They suggested that HCV infection may serve as an additional risk factor for the development of DM beyond that attributable to CLD alone [ 23 ]. In contrast, some studies provided evidence against a potential association between these two disorders [ 17 , 24 ]. A more recent study showed that the prevalence of DM among cirrhotic patients with hepatitis C was significantly higher than among those with cirrhosis due to cholestatic liver disease, but this rate difference was not significant when compared with cases with alcohol-induced cirrhosis [ 10 ]. In spite of the fact that they had not enrolled HBV infected cases in their sample population, it suggested that the mechanism of the DM in cirrhotic patients was related more closely to the underlying cause of liver cirrhosis [ 10 ]. Although no single etiological factor was found linked to DM occurrence in our study, we believe that our study was not designed to address this issue considering the fact that we had to exclude patients with NASH as another etiology of CLD because of small number of patients in this group. However, further prospective studies may shed more light on the relationship between DM and the underlying liver disease. BMI did not differ between diabetic and non-diabetic cases among cirrhotic patients. This finding was expectable as reduction in the muscle mass is well described in liver cirrhosis, which can bias the comparison. On the other hand, among patients with chronic hepatitis BMI did remain as an independent predictive factor of DM. Some studies have indicated that obesity could be a potential risk factor for fibrosis in chronic hepatitis [ 25 ]. Our results suggest that increased BMI also has a role in the pathogenesis of DM in chronic hepatitis independent of liver fibrosis. Furthermore, Muller et al reported that basal free fatty acids and basal free glycerol plasma concentrations were increased in diabetic patients with liver cirrhosis when compared with those without diabetes [ 7 ]. In present study, TG and Chol levels in patients with chronic hepatitis and TG level in cirrhotic patients were higher in diabetic cases compared with non-diabetic ones although not statistically significant (table 3 ). These findings may have therapeutic implications in the management of patients with chronic hepatitis. It appears necessary to greatly encourage overweight patients to make a concerted effort to lose weight in order to both decrease the risk of DM development and to prevent the liver damage. Although family history of DM is a well-known risk factor for DM, the correlation between DM and both cirrhosis and chronic hepatitis remained significant even when family history of DM was entered through logistic model. This finding, in concordance with similar studies [ 7 , 11 ], indicates that liver injury per se is associated with DM and a family history of DM is only an adjunctive factor. However, the possible reporting bias of family history of DM should be carefully considered as it is not unreasonable to think that patients with known DM may be more likely to know or think that they have a family history of DM. When cirrhosis and chronic hepatitis groups were analyzed separately, we observed that patients with a positive family history of DM did not show an increased frequency of DM, particularly in cirrhotic patients. Slightly less than 45% of cirrhotic cases with a negative family history of DM were diabetic. This finding does not support the speculation that cirrhotic patients only with a genetic predisposition for DM are prone to glucose intolerance as the manifestation of their liver disease. Age is another definite risk factor for type II DM in the normal population [ 13 ], and it was expected also to be associated with DM in CLD. However, the odds ratio for both cirrhosis and chronic hepatitis was higher than that for age, implying a stronger association of the former factors. Although in the part of our study investigating cirrhotic patients, age lost its significance when it was entered in multivariate analysis, the majority of studies demonstrated that IGT and also DM were more frequently seen at advanced age in cirrhotic patients [ 2 , 7 , 11 ]. While DM was associated with hypertension in univariate analysis (table 1 ), in multivariate analysis it lost its significance as a predictor of DM (table 2 ). These two variables may both be related to the metabolic syndrome and adjustment for other related variables removes this association. On the other hand, it is currently believed that cardiovascular disease is rare in cirrhosis and studies demonstrate that cirrhotic patients, even in the presence of overt DM, have a low prevalence of vascular disease including hypertension [ 26 ]. Our findings support this hypothesis showing no difference in the rate of hypertension between diabetic and non-diabetic patients. A few patients have so far been reported to develop DM during interferon therapy [ 27 ], but the evidences are insufficient in this regard as yet. In our study, interferon therapy had no impact on the prevalence of DM, since 15% of subjects with DM and about 39% without had a recorded use of interferon, and the difference was not significant. This is in line with some previous studies clarifying the impact of long-term administration of interferon on glucose metabolism [ 28 ]. Conclusions In summery, the present study indicates a high prevalence of DM in patients with CLD in Iran although the relatively small number of patients in each of the three subgroups particularly cirrhosis and inactive carriers was a major shortcoming of our study and may have potentially underestimated or overestimated the prevalence of DM in these subgroups of patients. Since a considerable number of diabetic patients were unaware of their problem, it is imperative that the patients be screened for glucose intolerance periodically. For more severe stages of liver disease the screening interval appears to be shorter because of higher probability for DM occurrence. Furthermore, our findings show that weight reduction for overweight patients with chronic hepatitis is of benefit in order to prevent the occurrence of DM. List of abbreviations DM: Diabetes Mellitus; IGT: Impaired Glucose Tolerance; CLD: Chronic Liver Disease; BMI: Body Mass Index; HBV: Hepatitis B virus; HBsAg: Hepatitis B s Antigen; NASH: Nonalcoholic Steatohepatitis; FPG: Fasting Plasma Glucose; TG: Triglycerides; Chol: Cholesterol; 2-hr PG: Two-hour Post-loaded Glucose; ADA: American Diabetes Association; IFG: Impaired Fasting Glucose. Competing interests The author(s) declare that they have no competing interests. Authors' contributions Dr. Alavian participated in the design of the study and coordination and drafted the manuscript. Dr. Hajarizadeh conceived of the study, participated in the design of the study, performed the statistical analysis and drafted the manuscript. Dr. Nematizadeh designed the questionnaire and helped in data collection. Dr. Larijani facilitated the study progress and participated in coordination. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC538272.xml
547897	Modelling the correlation between the activities of adjacent genes in drosophila	Background Correlation between the expression levels of genes which are located close to each other on the genome has been found in various organisms, including yeast, drosophila and humans. Since such a correlation could be explained by several biochemical, evolutionary, genetic and technological factors, there is a need for statistical models that correspond to specific biological models for the correlation structure. Results We modelled the pairwise correlation between the expressions of the genes in a Drosophila microarray experiment as a normal mixture under Fisher's z-transform, and fitted the model to the correlations of expressions of adjacent as well as non-adjacent genes. We also analyzed simulated data for comparison. The model provided a good fit to the data. Further, correlation between the activities of two genes could, in most cases, be attributed to either of two factors: the two genes both being active in the same age group (adult or embryo), or the two genes being in proximity of each other on the chromosome. The interaction between these two factors was weak. Conclusions Correlation between the activities of adjacent genes is higher than between non-adjacent genes. In the data we analyzed, this appeared, for the most part, to be a constant effect that applied to all pairs of adjacent genes.	Background Several studies (Hamilton [ 1 ], Fukuoka[ 2 ]) have found stronger correlation between the expression levels of genes that are located close to each other on the genome than between those of distant genes: when gene expressions of many genes are measured for multiple tissue samples, for example using microarray technology, adjacent genes are sometimes found to be consistently up- or downregulated in a subset of the tissue samples. Gene expression is influenced by many factors (for a review, see Orphanides[ 3 ]), many of which could influence the correlation between the expression of two genes in general, and that between two adjacent genes in particular. Of particular interest are chromatin domains . DNA can exist in either one of two states: a condensed state, termed heterochromatin, which is broadly inaccessible to transcription (although there are exceptions (Orphanides[ 3 ])), and an active state, termed euchromatin. A chromatin domain (a segment of DNA which, in a given cell at a given moment, is either entirely euchromatin or entirely heterochromatin) typically spans several genes (Roy[ 4 ]). Therefore, one would expect the expressions of two adjacent genes to tend to be positively correlated, at least if it was possible to measure transcription in individual cells. If the chromatin state was completely random (Jackson[ 5 ]) suggested a dynamic equilibrium, where chromatin fluctuates, to some extent randomly, between the two states), the effect of chromatin domains would vanish when gene expression is measured in pools of many cells, as with microarray technology. However, there is ample evidence for non-randomness. For example, chromatin states tend to be preserved after cell division (Orphanides[ 3 ]). And Cho[ 6 ] demonstrated that the states of chromatin domains in yeast are related to the cell cycle. In addition to the chromatin theory, several other explanations have been suggested for the apparent correlation between the expressions of adjacent genes. Several authors (Cohen[ 7 ], Kruglyak[ 8 ]) have noted that divergent gene pairs show stronger correlation than tandem and convergent pairs, possibly because divergent pairs share an Upstream Activation Sequence. Lercher[ 9 ] found that many of the co-expressed adjacent genes in Caenorhabditis elegans are either operons or homologues (see also Llorente[ 10 ] and Rossfll]), and it has been suggested that evolution has arranged for functionally related genes to be located close to each other, either in order to promote consistent inheritance (Bleiweiss[ 12 ]), or in order to benefit from the correlation accounted for by the chromatin domains (Cohen[ 7 ]). Parisi[ 13 ] found a nonrandom distribution of the chromosomal location of genes with high expression level in testis and ovaria in Drosophila. Jackson[ 5 ] suggested that the location of a gene in the nucleus plays a role for its transcription, in relation to gradients of the concentration of transcription factors. Finally, since the action of a transcription factor on a promotor gets weaker with distance, genes belonging to the same pathway should show stronger correlation if they are located close to each other (Dorsett [ 14 ]). Due to this abundance of alternative theories, a study of gene-expression correlations should be designed in a way that makes it possible to distinguish correlation structures predicted by one model from those predicted by other models. The same applies to the statistical analysis techniques used. An important consequence of the evolution-based theories is that they predict a consistent coregulation structure. Suppose that two genes (in this case, two adjacent genes) are co-regulated because, for example, they participate in the same pathway. They would, then, show a strong correlation because they would be co-regulated in all tissue samples. This need not necessarily be the case with the chromatin domain model: the segments of euchromatin in one tissue sample may overlap with those in another tissue sample. This latter scenario, we call an inconsistent coregulation structure. With consistent coregulation, adjacent gene pairs will show either strong positive correlation, or they will be uncorrelated. With inconsistent coregulation, all adjacent gene pairs will show a modest positive correlation. In a microarray analysis of gene expressions in 35 pools of drosophila embryos and 54 adult drosophilae (Spellman and Rubin[ 15 ], reviewed by Oliver[ 16 ]), it was shown that adjacent genes with correlated expression levels tend to cluster. The method they used to demonstrate this was the following: let w be a fixed window size, e.g. 10. For each window of w adjacent genes, the average pairwise Pearson correlation coefficient within the window was computed. If that measure was found to be significant at, say, 1 - α = 0.999 (the p-value was estimated in a permutation experiment), all the genes in the sequence were tagged. Doing this for all windows (they were allowed to overlap), the total number of tagged genes was counted. Then the experiment was repeated with shuffled genes (i.e., as it would behave in the absence of positionally related correlation), and the number of tagged genes in the shuffled experiment was subtracted from the number of tagged genes in the original experiment. This difference (called "net genes") grows with window size and starts plateauing for a window size of approximately 10. Spellman and Rubin interpreted this as evidence for gene interaction within regions of approximately that size. One problem with the above method of analysis is that the increasing number of "net genes" would occur even without direct interactions between genes separated by up to ten positions. As shown in figure 1 , the analysis gives similar results when applied to simulated data from a normal distribution, in which an autocorrelation of AC = 0.10 or 0.05 was imposed artificially. So we cannot, on the basis of the analysis described above, reject the hypothesis that the data arose from a simple first-order autocorrelation process, in which no clustering of correlated genes exists. It is true that gene-pairs with high correlation form clusters: the autocorrelation of Pearson's R for adjacent genes is 0.1, with a standard error 0.01. However, this can be explained by the fact that genes that tend to correlate strongly with other genes in general (for example because of low measurement noise) tend to correlate with both their neighbors. If one eliminates that confounder by looking at non-overlapping gene pairs only, the autocorrelation vanishes (0.01, standard error = 0.01). Another way of showing this is by means of cross-tables. We divided the adjacent gene-pairs into three groups: positively correlated pairs(R>0.7), negatively correlated (R< -0.7) and non-correlated. (The threshold of 0.7 was suggested by Cohen[ 7 ]). If the correlated gene-pairs were clustered, one would expect that a gene-pair belonged to the same group as the next gene-pair more often than would happen by chance. This is indeed the case when overlapping gene-pairs are considered: 627 gene pairs out of 12949 (4.8%) had an R > 0.7 while the next (overlapping) gene pair also had an R > 0.7. This is 2.22 times more than what we expected due to chance alone. However, the same was observed when only one of the two overlapping gene-pairs was was a neighbor pair and the other was a random pair (if the genes were labelled ABCD...Z, a strong correlation between A and B predicted a strong correlation between B and C but also between B and X, where X is a random gene). But when non-overlapping adjacent gene pairs were considered (say, AB versus CD), the contingency was 332 out of 12878(2.6%) which is only 1.18 times more than expected due to chance. So the apparent clustering of correlated gene pairs is mainly due to overlap rather than to adjacency. On the other hand, it is clear that there is some higher order correlation structure in Spellman and Rubin's data. This can be seen by computing the average correlation coefficient for subgroups of the gene pairs, based on their physical distance (table 1 ) – it decreases much slower with distance than would a first-order process. Hence, the question remains how the correlation structure should be modelled and analyzed. In this paper, we present a method to separate A) Correlation of gene expression that can be attributed to consistent coregulation, from B) The uniform correlation expected under an hypothesis of inconsistent corregulation. Results Data We used the Drosophila data published by Spellman and Rubin[ 15 ]. This data set consisted of normalized expression levels of 13090 genes in 89 flies (35 pools of embryos and 54 pools of adults), obtained with Affymetrix GeneChip microarrays. For the purpose of analysis based on physical distance between genes, the data set was linked to Flybase[ 17 ] on the basis of the CG-identifiers provided by Spellman and Rubin. 1871 genes had to be omitted from that analysis because of unmatched CG-identifiers. We checked that these omitted genes were not a biased sample with respect to correlation in expression with their neighbor genes. Non-adjacent gene pairs The distribution of the correlation coefficient between gene pairs in general, (i.e., genes that are not necessarily adjacent) was fitted with a three-component normal mixture, based on the Arcus Tangens Hyperbolic-transform (Fisher's z) of the correlation coefficients, which was validated with a Kolmogorov-Smirnov test (p = 0.6). As shown in table 2 , the mean of the middle component, tanh( μ 0 ), was 0.014 with a standard error of 0.002. (In all tables, μ has been transformed back with tanh so that it can be interpreted as a correlation). The fact that the standard deviation of the third component, σ + , is greater than that of the other components, suggests that the co-regulation of some gene pairs was stronger than that of others. Adjacent gene pairs Table 3 shows the fitted parameters in the same model, but for adjacent gene pairs. The results are very similar to those for the random gene pairs, although μ 0 and μ + are substantially higher. This suggests that the effect of adjacency is, for the most part, a mechanism that applies to adjacent-gene pairs in general, not just to specific adjacent-gene pairs. One way to illustrate this is by means of a qq-plot (figure 2 ), which shows that the correlation for random gene pairs and adjacent gene pairs have a similar structure, although the overall correlation is stronger in adjacent gene pairs. This contrasts with the qq-plot in figure 3 , in which the gene-expression correlations in the subset of adult flies is compared to those in a mixed fly group. On average, the correlation is zero in both the adult group and the mixed group. However, the standard deviation of the correlation is much higher in the mixed group, presumably because genes that are expressed specifically in the adults (or specifically in the embryos) correlate strongly with each other in the mixed group. Table 4 shows the fitted values of the parameters μ 0 , μ + and the size of the third component (that is, the fraction of the genes that are positively co-regulated), for random and adjacent gene pairs in four subsets of the flies: one containing all 54 adult pools, one containing all 35 embryo pools, and two random subsets of 35 and 54 pools, respectively. One can observe that μ 0 (which can be attributed to corregulation of gene pairs in general, i.e., inconsistent co-regulation) is always high for adjacent gene pairs and low for random gene pairs. On the other hand μ + and the "+"-fraction (which can be attributed to corregulation of specific gene pairs, i.e., consistent co-regulation) are always high in heterogenous fly groups and low in homogenous one. That difference between heterogenous and homogenous groups is what we expected: In a homogenous fly group, less gene pairs will come up as co-regulated, because some pathways may either be active in all flies, or inactive in all flies. That age groups does not explain all correlation, is hardly surprising: although the adult group and the embryo group are less heterogenous than the mixed group, neither is homogenous. Gene pairs of intermediate distance To get an impression of the size of the segments involved in co-regulation, we fitted the three-component mixture to the correlation coefficient between the expressions of more distant gene pairs. μ 0 was 0.114 for the correlation between the expression of a gene and that of its direct neighbor, and 0.08 for the correlation with its second neighbor. From the fifth neighbor and until at least the tenth, a stable level of 0.03 is reached, which is still higher than for distant gene pairs. One possible interpretation of this is that two different co-regulation effects exist: a short-segment effect accounting for a correlation of approximately 0.114-0.03 = 0.081, and a long-segment effect accounting for a correlation of approximately 0.03-0.014 = 0.016. At first we had the suspicion that this stable level of 0.03 was a whole-chromosome effect, but that was not the case. We found no significant difference between the overall average correlation of random gene pairs from the same chromosome and random gene pairs from different chromosomes. In a first-order autocorrelation process, tanh( μ 0 ) for the second neighbor would be the square of that for the first neighbor. However, the unexpectedly small difference between the two values could be due to the fact that some second neighbors are physically quite close. To confirm or reject the hypothesis of a first-order process, however, the analysis must be based on physical distance rather than simple adjacency. As shown in table 1 , the decrease in average correlation as a function of physical distance is still too slow for a first-order process. Table 5 shows the fitted parameters for gene pairs within a physical distance of between 100 and 1000 bases. Unlike the fitted parameters for neighbor genes, μ + is not significantly higher than for random gene pairs. Simulated data To validate our approach, we computed the correlation coefficients of adjacent and random gene pairs in simulated data, based on either consistent or inconsistent co-regulation. As expected, the simulated data with inconsistent co-regulation resulted in a correlation structure with only one component, whereas those with consistent coregulation showed two components. (Not three, since the segment effect (see Methods) was always positive in the simulated models). Discussion There are many theories that could explain correlation between the expressions of two genes in general, and that of two adjacent genes in particular. For the verification of the specific correlation structures predicted by each theory, Spelmann and Rubin's data turned out to be very useful. Their experimental design was based on two distinct classes of experimental conditions (in this case, embryos and adults), which makes a relatively simple correlation structure plausible. Also, the data from each of their microarrays could be fit nicely with a normal mixture, which makes it possible to analyze their data on the basis of the Pearson R. As expected, most of the consistent correlation was found to be related to age group and unrelated to adjacency. Maybe more surprisingly, most of the correlation that was related to adjacency could not be accounted for by consistent co-regulation. This suggest that, at the statistical level, co-regulation of adjacent genes should be understood in terms of the mechanics of the transcription process, rather than in terms of the evolutionary origin of specific gene groups. In other words, in this particular data set, consistent correlation was very widespread, applying to 40% of all gene pairs (table 2 ), half of this could be attributed to the two age groups (table 3 ), but this consistent correlation was not the most important contributor to the elevated correlation coefficients for adjacent gene pairs. Correlation between the expression of adjacent genes is evident, but it is possible, as suggested by Spellman and Rubin, that such a correlation between expression levels for two adjacent genes does not generally imply a relationship with respect to biological function. Spellman and Rubin concluded that the adjacent genes with correlated expressions were confined to certain domains, which spanned 20% of all genes. Our findings are different, in that we distinguished between two components of the correlation structure. We found a baseline correlation of 0.1 (the difference between μ 0 in table 2 and table 3 ) applying to all adjacent gene pairs. In addition to that, we found that 8% of all adjacent gene pairs (the difference between the "+" -fractions in table 2 and table 3 ) were strongly positively correlated. Finally, unlike Spellman and Rubin, we found no evidence for clustering of the strongly correlated gene pairs. Since this data set contained data from whole animals, we cannot say anything about the role of chromatin domains (or other mechanisms causing correlation of the expression of adjacent genes) in tissue differentiation. Parisi et al. [ 13 ] found clustering of genes that were upregulated in drosophila germ cells, which suggests that one would find elevated consistent coregulation of adjacent genes when applying our model to data sets with different tissue classes. Even for random (non-adjacent) gene pairs, μ 0 was slightly positive. It is hard to imagine a biological effect that could cause μ 0 to be significantly greater than zero, but it could be an artifact of the normalization: if gene g is expressed at the same level in all tissue samples, and gene h as well, they should have a correlation coefficient of zero, but since they will both yield elevated measurements in flies in which the normalization bias is positive, the observed correlation will be positive. The fact that μ 0 is almost zero suggests that normalization bias is not a major problem with this data set. The fact that μ 0 for random gene pairs is not generally higher in mixed age groups than in pure adult or embryo groups (table 4 ) is consistent with the assumption that μ 0 for random gene pairs does not have a biological interpretation. Although looking at adjacent genes is computationally convenient, it would probably be more correct to use physical distance, rather than adjacency, as a covariate. Actually, Fukuoka[ 2 ] found that physical distance is stronger related to correlation of expression levels than is adjacency. Table 5 shows that when a subgroup of the gene pairs is selected on the basis of physical distance, it becomes even more clear that the elevated correlation is a general property of all near-by gene pairs. This is not surprising since the group of adjacent gene pairs is heterogenous, containing gene pairs with vastly varying distances. Unfortunately, there are some problems related to the use of physical distance. First, it is not clear with respect to which anchor the physical distance should be defined. We have chosen to use the minimal distance (using the end nearest to the neighbor as an anchor), because it is not confounded by the length of the gene. However, depending on which co-regulation mechanism one has in mind, other distance measures might be more natural. This question becomes crucial if one wants to make subgroup analysis based on convergent, divergent and tandem gene pairs. Second, physical distance is a continuous variable, which means that the model must be augmented with an assumption regarding the relationship between distance and correlation. The question remains to what biological phenomena the baseline correlation between adjacent genes should be attributed. Several of the theories that have been proposed could account for it, and it is likely that several mechanisms play a role. In addition to the baseline correlation, we also found more consistent correlation between adjacent genes and inconsistent co-regulation, but this does not necessarily imply a combination of two mechanisms: one could imagine a kind of quasi-consistent mechanism, in which groups of adjacent, co-regulated genes could have boundaries everywhere, but with some boundary locations being more likely than others. Finally, it has been suggested that the correlation between the expressions of adjacent genes should be understood in terms of enhancer-promotor interaction, which weakens with distance(Dorsett[ 14 ]). It is possible that such a model would predict a pattern similar to what we have found. Conclusions It is possible to analyze correlation structures in gene expression data on the basis of simple, parametric models with known mathematical properties and parameters with biological interpretations, or at least some candidate interpretations. When applied to the data from Spellman and Rubin, it appeared that the expressions of two genes can show positive correlation for either of two largely distinct reasons: because they share some confounder unrelated to adjacency (this is often the age group, but could also be some other biological parameter, or a technical artefact), or because they are located close to each other on the chromosome. The underlying biological mechanisms remain unknown, but there appears to be a component of the correlation that depends on distance only and not of the biological function of the genes. If this is true, gene clustering algorithms might benefit from making distinction between the adjacency-related and not-adjacency-related co-regulation, for example by subtracting the effect of adjacency from the correlation of adjacent genes. Doing that would, according to our findings, lead to more reliable identifications of gene pairs with related biological functions. Methods Non-adjacent gene pairs First, we constructed a model for those co-regulation effects that were unrelated to the relative location of the two genes. Suppose that a gene can be active either in adults, in embryos, in both, or in neither. Let Y gi be the log-scale measured activity of gene g in fly i , fly i having development stage s (either "adult" or "embryo"). A natural model for Y gi would be a two-component normal mixture: Since the data were normalized so that the average logscale activity across all 89 flies was zero, the activity of gene g in the other development stage should be taken into account. We therefore assumed a three-component normal mixture: Actually, of the 89 flies, the gene expressions in 87 of them could be nicely fitted with a three-component, normal mixture, while in two of the adult flies we identified only two components (the component of genes that were passive in adults while active in embryos vanished in those two cases). If the three-component model is correct, Fisher's z-transform, which is the hyperbolic arcus tangens of the Pearson correlation coefficient R gh for two genes, g and h , is We expected μ 0 to be close to zero. This model was validated by implementing it on the neighbor correlations in a shuffled data set, that is, for each gene its Pearson R with a random gene was computed. This procedure was repeated with 10 shuffled data sets, each generated by shuffling the genes in the original data set and subsequently computing the Pearson R for each pair of adjacent genes. For each shuffled data set, the parameters in the model were estimated with the EM algorithm (Dempster et.al[ 18 ]). Adjacent genes Second, the distribution of the correlation coefficients of the pairs of adjacent genes in the unshuffied data set were compared to the same distribution for the shuffled data sets. Doing that, we could distinguish two different contributions to the correlation; A) co-regulation effects that are unrelated to the fact that two genes are adjacent, and B) co-regulation effects related to the fact that two genes are adjacent. We also analyzed each gene's correlation with its second, third etc. (up to the tenth) neighbor, in order to get an idea of the lengths of the chromatin domains in question. Third, we applied the above two procedures to two subsets of the data, namely the data for adult flies and the data for embryos. If our assumption, that all (or at least most) correlation could be attributed to the development stage, one would expect much less correlation in those subsets. However, those subsets differ from the entire data set by the mere fact that they are smaller. Therefore, we also applied the same procedure to two random subsets of 35 and 54 flies, respectively, stratified by development stage. Physical distance For those gene pairs where the start and the end of the open reading frame (ORF) was available, we defined the physical distance as the distance between the end of the ORF of the first gene and the start of the ORF of the second gene. We chose that definition because other distance definitions (defined on the basis of the direction of transcription, or on the basis of mid-points) would be confounded by the length of the ORFs. Simulated data Finally, in order to validate our method, we applied it to 6 simulated data sets, which we simulated on the basis of the two alternative hypothesis of consistent and inconsistent co-regulation. The simulated data sets contained 100 tissue samples and 1000 genes. The genes were randomly divided into either 67, 200 or 500 segments, corresponding to average segment sizes of 15, 5 and 2. This means that each gene belonged to exactly one segment. For each average segment size, we simulated one data set with consistent co-regulation , in which the same segments were used for all 100 tissue samples, and one data set with inconsistent co-regulation , in which a separate segmentation was sampled for each tissue sample. If gene g belongs to segment s in sample i , the expression Y gi was given by Y gi = x si + ε gi (4) where x si + and ε gi were both sampled from the standard normal distribution. Notice that this model does not account for different tissue classes, so it should be compared to the results from the adults-only and embryos-only subsets. The error term ε gi should be interpreted as a combination of measurement errors and biological effects that are unrelated to the segmentation. Authors' contributions HT did the explorative data analysis and suggested the concept of consistent co-regulation and using three-components mixtures for the correlation structure. AZ suggested using Fisher's z-transform for the correlations. HT did the literature review. Both authors contributed to the manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC547897.xml
546237	An unusual presentation of a malignant jejunal tumor and a different management strategy	Background Malignant small bowel tumors are very rare and leiomyosarcoma accounts for less than 15% of the cases. Management of these tumors is challenging in view of nonspecific symptoms, unusual presentation and high incidence of metastasis. In this case report, an unusual presentation of jejunal sarcoma and management of liver metastasis with radiofrequency ablation (RFA) is discussed. Case presentation A 45-year-old male presented with anemia and features of small bowel obstruction. Operative findings revealed a mass lesion in jejunum with intussusception of proximal loop. Resection of bowel mass was performed. Histopathological findings were suggestive of leiomyosarcoma. After 3-years of follow-up, the patient developed recurrence in infracolic omentum and a liver metastasis. The omental mass was resected and liver lesion was managed with radiofrequency ablation. Conclusion Jejunal leiomyosarcoma is a rare variety of malignant small bowel tumor and a clinical presentation with intussusception is unusual. We suggest that an aggressive management approach using a combination of surgery and a newer technique like RFA can be attempted in patients with limited metastatic spread to liver to prolong the long-term survival in a subset of patients.	Background Malignant tumors of the small bowel are rare and accounts for the <2 % of total gastrointestinal (GI) malignancy [ 1 , 2 ]. The age-adjusted incidence of small bowel malignancy is 1 per 100,000 with prevalence of 0.6% [ 3 ]. Management of these tumors is challenging because of their rarity, relative inaccessibility for diagnosis and diverse histologic types and nonspecific symptoms [ 4 ]. Because of the heterogenous and aggressive nature many of them present with recurrence and visceral metastasis. Radiofrequency ablation has been successfully tried as a minimally invasive but effective local treatment of liver metastasis from a variety of primary sites including small bowel tumors [ 5 ]. In this case report, we present an unusual case of small bowel sarcoma, and discuss the clinical presentation and management using combination of surgery and radiofrequency ablation (RFA). Case presentation A 45-year-old male was referred to our center with the diagnosis of suspected non-Hodgkin's lymphoma (NHL) of the bowel in December 1999. He had generalized weakness for 2-years along with recurrent vomiting, occasional constipation and melaena for last 2 months. The diagnosis was considered after an ultrasound (USG) guided fine needle aspiration cytology (FNAC) from the intra-abdominal mass done elsewhere and showed features suspicious of NHL. At presentation, patient's general condition was poor and he was dehydrated and pale. There was no peripheral lymphaedenopathy. Abdominal examination revealed an ill-defined, mobile, nontendor lump in left paraumblical region extending up to left lumber region. There was no hepato-splenomegaly. Examination of chest and cardiovascular system was normal. After initial resuscitation with crystalloids and blood transfusion, patient was further investigated. At presentation his hemoglobin was low (6.4 gm%) but rest of the routine haematological investigations were within normal limit. The chest X-ray was normal. Abdominal ultrasound (USG) showed a left upper abdominal mass lesion suggestive of bowel mass. The upper GI endoscopy was normal. The barium meal follow through examination was suggestive of intussusception of proximal jejunum and a suspected mass lesion at the leading edge of intussusceptum. An USG guided core needle biopsy of mass was performed because of earlier suspicion of NHL, which showed smooth muscle bundles with areas of necrosis. Based on the above findings and biopsy report, patient was taken up for exploratory laparotomy 3 weeks after initial presentation. Operative findings revealed an intussuscepted proximal jejunum loop 12 cm distal to duodeno-jejunal flexure and a vascular polypoidal growth measuring 6.5 × 5 × 3.5 cms on serosal surface of jejunum. Liver and spleen were normal. There was no evidence of mesenteric or retroperitoneal lymphaedenopathy, ascites or peritoneal disease. The resection of involved segment of jejunum with 5 cm margins and an end-to-end anastomosis was performed. The postoperative course was uneventful. Pathological examination of the specimen revealed two mass lesions measuring 4.5 cm & 3 cm in continuity (total 7.5 cm in maximum diameter) located on mucosal and serosal surface of jejunum respectively. Microscopically it showed spindle cell tumor with a mitotic rate of 5/10 high power fields (HPF). The tumor was negative for desmin, S-100, CD 34 and c-kit (CD117) but focally positive for actin on immunohistochemistry (IHC). The resection margins were free. The final diagnosis of malignant spindle cell tumor – leiomyosarcoma of jejunum was made. Due to negative margins and no evidence of disease elsewhere, no adjuvant therapy was planned and patient was kept on regular follow up. He was assessed clinically at three months interval and an USG of abdomen was performed six monthly. Patient remained disease free for 39 months. After that a follow-up USG showed a space-occupying lesion (SOL) in segment VII of liver and a mass lesion in left upper abdomen. The patient was asymptomatic and abdominal examination revealed no abnormality. A computerized tomographic (CT) scan of abdomen was performed which showed a 2 × 2 cms, brightly enhancing SOL in segment VII of liver (Figure 1 ) and a 3 × 4 cms omental mass lesion abutting the bowel loop in left upper abdomen (Figure 2 ). Upper GI endoscopy and colonoscopy did not reveal any abnormality. A provisional diagnosis of recurrent leiomyosarcoma was made. Patient was planned for resection of the mass and RFA of liver lesion. Figure 1 CT scan image showing the hepatic metastasis in segment VII. Figure 2 CT scan image showing the omental mass adjacent to bowel loop (circle around the omental mass). Patient was explored and two separate well encapsulated, fleshy mass lesions were found in infracolic omentum, measuring 6 × 7 × 3.5 and 2 × 1 × 1 cms. The liver lesion was not palpable and there was no evidence of disease at primary site or anywhere else in peritoneal cavity. An infracolic omentectomy along with tumor nodules was performed. The histopathological features were suggestive of a highly cellular tumor composed of spindle shaped cells arranged in interlacing fascicles. On immunohistochemistry, multiple sections were negative for CD-34, CD-117, S-100 and desmin but focally positive for actin as in the initial tumor. So a diagnosis of recurrent leiomyosarcoma was made. The patient was taken up for an USG guided RFA of liver metastasis 3 weeks after surgery. The RFA was performed by Cool Tip™ RF machine [Radionics, USA] using single tip probe. The procedure was conducted for 12 minutes at temperature of 65°C and the lesion was ablated with 1 cm margin. Follow-up CT scan done 3 days later showed complete ablation of metastatic lesion (Figure 3 ). The patient was kept on regular follow-up and nine months after RFA he was asymptomatic and an abdominal CT scan showed no evidence of recurrence. Figure 3 Post radiofrequency ablation CT scan image showing complete resolution of hepatic metastasis. Discussion The small intestine accounts for 75% of total length of GI tract and more than 90% of mucosal surface. However, it is the site of only 6–25% of GI neoplasms and only 2% of GI malignancies [ 2 , 6 ]. Leiomyosarcoma is the fourth most common malignant tumor of small bowel and it's incidence is 1.2 cases/million/year [ 7 , 8 ].The most frequent site of leiomyosarcoma is jejunum, followed by ileum and duodenum [ 6 , 8 ]. The peak incidence is in 6 th decade and there is a slight male preponderance [ 6 ]. Most of these tumors are slow growing and associated with a long period of symptoms [ 8 ]. The most common presentation is GI bleeding and anemia [ 6 ]. Abdominal pain and palpable mass is present in 5–50% of patients [ 6 ]. Other symptoms include nausea, vomiting and weakness [ 7 ]. Nonetheless, there is no specific sign or symptom that defines presentation of smooth muscle tumors [ 7 ]. Our patient presented with features of GI bleed, anemia and recurrent subacute intestinal obstruction. Intestinal obstruction is seen in less than 5% patients with smooth muscle tumor and is usually caused by tumor infiltration or malignant adhesions [ 6 , 7 ]. In the present case, the cause of obstruction was intussusception. In adult patients, small bowel intussusception is caused mostly by small benign intraluminal ileal tumors like lipoma and leiomyoma [ 6 , 8 ]. However, in this patient intraluminal component of dumb bell jejunal leiomyosarcoma was causing intussusception. Intussusception is a rare phenomenon in patients with leiomyosarcoma and tumors of ileal region presents with intussusception more often than jejunal location [ 6 ]. Review of English literature revealed only one case of jejunal intussusception caused by leiomyosarcoma [ 9 ]. The commonly recommended investigations in cases of suspected small bowel tumor are endoscopy, CT scan and contrast studies and most often the final diagnosis is confirmed after laparotomy and histopathology [ 6 ] as happened in the present case. The preoperative tissue diagnosis is not routinely recommended except in suspected cases of lymphoma, germ cell tumor and unresectable metastatic disease because of theoretical risk of peritoneal seeding and tumor rupture along with difficulty in obtaining definitive diagnosis [ 10 , 11 ]. Majority of leiomyosarcoma grow extraluminally but infrequently tumor can grow both extra and intraluminally. Blanchard et al in their extensive review of small bowel leiomyosarcoma found that 68% of jejunal tumors grow extraluminally and only 14.4% in dumb bell fashion [ 6 ]. Tumor size varied from 1–20 cm and in >3/4 th of patients tumor is >5 cm. In the present case, the tumor was 7.5 cms and had grown in a dumb bell fashion. The surgical resection is the mainstay of treatment in these tumors [ 6 , 7 ]. The surgery usually involves the en bloc resection of tumor with wide margins along with adjacent mesentery [ 6 ]. The lymphatic spread of leiomyosarcoma to regional lymph nodes occurs in 5%–13% of patients and role of lymph node dissection is controversial. However, routine lymph nodal dissection in the absence of nodal disease is not recommended [ 7 ]. Unfortunately, leiomyosarcomas are notoriously radioresistant and attempts at using adjunctive radiotherapy and chemotherapy have failed [ 12 , 13 ]. There is no role of adjuvant therapy and patients with complete resection are kept on close follow-up [ 6 , 7 , 13 ]. Periodic USG or CT scan is recommended, as biologically these tumors are heterogeneous and aggressive in nature [ 10 ]. Similar guidelines were followed in this patient. The differentiation between benign and malignant smooth muscle tumors is difficult and metastasis is the only conclusive evidence of malignancy. Similar to other sarcomas, the most common route of metastasis is hematogenous and common sites are liver and lungs. But unlike other sarcomas peritoneal seeding is more commonly seen [ 6 ]. Blanchard et al reported 41.3% incidence of metastasis in jejunal leiomyosarcoma and liver was the most common site followed by peritoneum and mesentery [ 6 ]. They also found recurrent tumors in 40.9% of patients in conjunction with metastatic disease. A similar picture was present in our patient. Ranchod and Kempson [ 14 ] reported that number of mitosis is the single most criterion for predicting the metastatic potential and tumors with ≥5 mitosis per 10 high power fields (HPFs) behaved more aggressively. A tumor that shows >2 mitosis/HPF is usually considered malignant [ 6 ]. The size of tumor is also considered in risk stratification for metastasis and tumors <5 cms are significantly less likely to metastasize [ 6 ]. With this criterion, our patient falls into high-risk group for relapse. Overall reported survival rate for GI leiomyosarcoma is 10–48% [ 6 ]. But in an analysis of six series, Licht et al [ 15 ] reported only 5–20%, 5-year survival for high-grade tumors (tumors with >10 mitosis per 10 HPFs). O'Riordan et al [ 8 ] reported 5-year survival rate of 27% for tumors >5 cms. In a series of 21 patients with high grade leiomyosarcomas, Chou et al found that 17 of their cases had liver metastasis or local recurrence [ 16 ]. Conlon et al [ 17 ] reported 44% recurrence after complete resection, and mean time to recurrence was 9 months (median 7, ranging from <1 to 37 months). Despite the high-risk, our patient had relapse after 40 months of primary surgery and the relapse sites were omentum and liver, without having any evidence of disease at primary site. A few patients benefit from surgical intervention for removal of metastasis in small bowel leiomyosarcoma [ 7 ]. Karakousis et al , [ 18 ] reported prolongation of survival after metastasectomy in intestinal leiomyosarcoma and 3 year survival of 28%. Kohno et al [ 19 ] described 10-years survival after multiple surgeries in a patient of intestinal leiomyosarcoma. Considering the good general condition of our patient, long disease free interval and limited bulk of disease, we planned for resection of omental recurrence and treat the liver lesion with RFA. Most of the experience of liver metastasis management is in colorectal malignancy and there is limited experience of liver resection in noncolorectal cancers [ 20 ]. There are different types of therapy for the management of liver metastasis – surgical resection, regional treatment modalities, systemic therapy and local or in situ ablation [ 21 ]. Although, the gold standard is surgical resection however only 15–25% of patients with liver metastasis are suitable for hepatic resections [ 20 , 21 ]. In soft tissue sarcoma; in a selected group of patients, metastatectomy is recommended [ 22 ]. Due to high morbidity and mortality and limited survival after liver resection, recently, in situ ablation of liver metastasis with radiofrequency ablation is gaining popularity [ 5 , 20 , 21 ]. RFA is ideally suitable for single lesion <5 cm in size and complication rate of RFA is usually very low [ 23 ]. The effectiveness of RFA has been demonstrated in few retrospective studies but long-term results are awaited [ 24 ]. Considering the very high-risk of relapse in leiomyosarcoma and a deep-seated liver metastasis requiring major hepatic resection, we planned for the RFA of liver lesion. Until now, there are only a few reports of use of RFA in treatment of liver metastasis in leiomyosarcoma [ 25 , 26 ]. Tepetes et al [ 25 ] reported 5-year survival in a case of hepatic metastasis from leiomyosarcoma with combination of liver resection, RFA and systemic chemotherapy. Karakousis et al [ 18 ] reported 3 and 5 years survival as 28% and 4% respectively after complete resection of metastasis in intestinal leiomyosarcoma. However, survival was limited to 6 months for high-grade leiomyosarcoma. Despite a high-risk tumor and having local relapse with liver metastasis, our patient is still disease free after 9 months of second surgery and 4 years after first surgery. Conclusion Jejunal leiomyosarcoma is a rare variety of malignant small bowel tumor with diverse presentation, heterogeneous behavior and a high propensity for relapse. Clinical presentation with intussusception is unusual. We suggest that an aggressive management approach using a combination of surgery and a new technique like RFA can be attempted in patients with limited metastatic spread to liver to prolong the long term survival in a subset of patients. Competing interest The author(s) declare that they have no competing interests. Authors' contributions SVSD, NKS: Surgical management and review of manuscript. AS, SH, SK: Review of literature and preparation of manuscript. ST, DKP: Radiofrequency ablation. All authors have read and approved the contents of manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC546237.xml
533864	Selective inhibition of c-Myb DNA-binding by RNA polymers	Background The transcription factor c-Myb is expressed in hematopoietic progenitor cells and other rapidly proliferating tissues, regulating genes important for proliferation, differentiation and survival. The DNA-binding domain (DBD) of c-Myb contains three tandemly arranged imperfect repeats, designated Myb domain R 1 , R 2 and R 3 . The three-dimensional structure of the DBD shows that only the second and third Myb domains are directly involved in sequence-specific DNA-binding, while the R 1 repeat does not contact DNA and only marginally affects DNA-binding properties. No structural information is available on the N-terminal 30 residues. Since deletion of the N-terminal region including R 1 plays an important role in oncogenic activation of c-Myb, we asked whether this region confers properties beyond DNA-binding to the neighbouring c-Myb DBD. Results Analysis of a putative RNA-binding function of c-Myb DBD revealed that poly(G) preferentially inhibited c-Myb DNA-binding. A strong sequence-selectivity was observed when different RNA polymers were compared. Most interesting, the poly(G) sensitivity was significantly larger for a protein containing the N-terminus and the R 1 -repeat than for the minimal DNA-binding domain. Conclusion Preferential inhibition of c-Myb DNA binding by poly(G) RNA suggests that c-Myb is able to interact with RNA in a sequence-selective manner. While R 2 and R 3 , but not R 1 , are necessary for DNA-binding, R 1 seems to have a distinct role in enhancing the RNA-sensitivity of c-Myb.	Background The transcription factor c-Myb is regulating genes involved in proliferation and differentiation during hematopoiesis in vertebrates (reviewed in [ 1 , 2 ]). c-Myb is expressed at high levels in hematopoietic progenitor cells, but becomes down-regulated when the cells reach terminal differentiation. The critical role of c-Myb in the development of hematopoietic cells is emphasized by the embryonic lethality observed in mice with a c-myb null mutation, caused by failure of fetal hepatic hematopoiesis [ 3 ]. c-Myb expression has also been detected in other rapidly proliferating tissues such as hair follicles and immature epithelial cells from colon, respiratory tract, skin and retina [ 4 , 5 ]. c-Myb is essential for early T cell development [ 6 ] and several c-Myb target genes play an important role during T cell development, like CD4, TCRγ, TCRδ and RAG-2 [ 1 , 7 ]. The best characterized c-Myb target gene is chicken mim-1 , which is encoding a secretable component of granules found in normal promyelocytes [ 8 , 9 ]. The Myb family of proteins is defined by the presence of a well-conserved DNA-binding domain (DBD) composed of Myb repeats [ 10 ]. Each repeat consists of about 50 amino acids with three regularly spaced tryptophans forming a hydrophobic core [ 11 - 13 ]. The c-Myb DBD contains three tandem imperfect Myb repeats (R 1 , R 2 and R 3 ), located in the N-terminus of the protein. Determination of the structure of the c-Myb DBD has revealed that each repeat folds into three well-defined helices forming a helix-turn-helix-related structural motif, where the last helix in R 2 and R 3 makes specific DNA contacts (recognition helices) [ 13 - 15 ]. The c-Myb protein harbours two functional domains in addition to the DBD: a central activation domain and a C-terminal negative regulatory domain. The viral counterpart of the chicken c- myb gene, v- myb , found in the AMV and E26 viruses, has deletions in both ends, leading to a v-Myb protein lacking the N-terminus, most of the first Myb repeat (R 1 ) and a large part of the C-terminal negative regulatory domain (reviewed in [ 16 ]). The c-Myb DBD binds specifically to the sequence PyAAC(T/G)G, termed the Myb recognition element (MRE) [ 17 - 19 ]. The minimal sequence-specific DBD consists of the two carboxy-terminal Myb repeats, R 2 R 3 [ 20 , 21 ]. The role of the first Myb repeat, R 1 , is not fully understood. It has been shown to be dispensable for specific DNA-binding [ 20 , 22 ], but bears striking similarities to the other repeats regarding sequence and structure [ 23 ]. Some groups have reported that R 1 stabilizes the protein-DNA complex [ 24 , 25 ] and it has been proposed to allow for more flexibility in the downstream region of the Myb recognition sequence [ 26 ]. According to the recent three-dimensional structure of the c-Myb DBD, the R 1 repeat does not contact DNA directly [ 15 ]. However, a long-distance electrostatic interaction is suggested to stabilize the protein-DNA complex. Its free position in the complex makes it possible that it could be involved in other functions as well. This possibility is supported by the fact that v-myb -like truncation of the N-terminus of c-Myb (until the end of R 1 ) has been shown to be sufficient for oncogenic transformation of chicken bone marrow cells [ 27 ]. The R 1 repeat could serve as a special regulatory module, either acting as a target for molecular interactions or being subject to post-translational modifications. In the present work we address whether the N-terminal region including the R 1 repeat confers properties beyond DNA-binding to c-Myb DBD. We sought evidence for a putative RNA-binding function, analogous with several other transcription factors harbouring dual DNA-RNA binding properties. The motivation for investigating RNA-interaction was the design of the c-Myb DBD, built of repeating modules, a design resembling the structural logic of zinc finger proteins. Some well-studied zinc fingers have been found to use subsets of the repeats as RNA- or DNA-binding units. The classical example is the Xenopus zinc finger protein TFIIIA, which acts as a DNA-binding activator of 5S ribosomal RNA genes [ 28 , 29 ]. TFIIIAalso forms a stable complex with 5S rRNA in Xenopus oocytes [ 30 , 31 ]. The nine zinc fingers of TFIIIA contribute differentially to DNA- and RNA-binding; the N-terminal triplet (1–3) dominating the DNA recognition event while the middle triplet (4–6) is more important for RNA-binding [ 32 , 33 ]. Another example of a zinc finger with similar dual properties is the Wilms tumor suppressor gene 1 ( WT1 ) [ 34 - 36 ]. One splice variant (the +KTS isoform) seems to be a better RNA-interacting form that co-localizes with splicing proteins in nuclear speckles, whereas another variant (the -KTS isoform) interacts stronger with DNA and co-localizes with transcription factors [ 34 , 35 ]. The capability of specific interaction with both DNA and RNA is not restricted to the zinc finger family of proteins. The homeodomain protein bicoid of Drosophila acts both as a transcription factor, activating zygotic segmentation genes during blastoderm formation, and as a regulator of mRNA translation by binding to the mRNA of another homeodomain transcription factor, caudal [ 37 , 38 ]. Interestingly, the homeodomain bears structural similarities to the Myb domain, especially with respect to the presence of a helix-turn-helix-related motif [ 12 , 13 , 15 , 21 ]. A final example is p53, which has been reported to bind to both single-stranded DNA and RNA in addition to its established role as a sequence-specific DNA-binding protein (reviewed in [ 39 ]). Murine p53 and human Cdk4 translation have actually been shown to be regulated by p53 mRNA binding. Based on these occurrences of dual nucleic acid interactions, we asked whether a similar design was found in c-Myb. In particular, we raised the question whether the N-terminal region including R 1 might be implicated in RNA-binding rather than DNA-binding. As a test of our proposed RNA-binding function of c-Myb, we investigated the effect of different homoribopolymers on c-Myb DNA-binding. The homoribopolymer polyguanylic acid (poly(G)) strongly inhibited the sequence-specific DNA-binding of c-Myb, while poly(A), poly(C) and poly(U) did not, indicative of an RNA-binding activity. The same phenomenon, although weaker, was observed for A- and B-Myb. An order-of-addition experiment indicated that poly(G) bound directly to c-Myb in competition with DNA. Interestingly, the DBD construct containing the N-terminus and R 1 was significantly more sensitive to poly(G) than the minimal DBD. Thus, the N-terminus including R 1 seems to be important for the RNA-sensitivity of c-Myb DBD. Results Differential binding to homoribopolymers has been used as evidence for RNA-binding activity of various proteins [ 40 - 45 ]. To investigate whether c-Myb and its R 1 repeat is involved in RNA-binding we first examined the effects of homoribopolymers on c-Myb DNA-binding. The sequence-specific DNA-binding was analyzed by the electrophoretic mobility shift assay (EMSA) using two purified recombinant human c-Myb protein domains, NR 1 R 2 R 3 (amino acid 1–192) and R 2 R 3 (amino acid 89–192), in mixture. The assay was performed in the presence of increasing amounts of the homoribopolymers poly(A), poly(C), poly(G) and poly(U) (Fig. 1A ). The DNA-binding of both proteins was strongly inhibited by poly(G) but not by the other polymers. NR 1 R 2 R 3 was most sensitive, being inhibited when as little as 1 ng poly(G) was added. We also tested two artificial RNAs, poly(IC) and poly(I). The former is a duplex RNA, and the latter is a variant of poly(G) less prone to forming unusual structures, but retaining some of the pairing properties of guanosines. The duplex did not affect DNA-binding, while poly(I) caused some inhibition at high concentrations (Fig. 1B ). To confirm that the observed inhibition by poly(G) was indeed due to the added RNA, we carried out the poly(G) inhibition experiment in the presence and absence of RNase T1, an endoribonuclease that specifically cuts RNA at the 3'-end of guanosine residues. As shown in Fig. 2 , DNA-binding was no longer inhibited by poly(G) after RNase T1 treatment, confirming the RNA-dependence of the inhibition. Figure 1 Inhibition of c-Myb DNA-binding by homoribopolymers. Panel A: NR 1 R 2 R 3 (40 fmol) and R 2 R 3 (20 fmol) in mixture were incubated with 30 fmol MRE-containing DNA probe and 1 ng (lane 4,7,10 and 13), 10 ng (lane 5, 8, 11 and 14) and 100 ng (lane 6, 9, 12 and 15) of homoribopolymers poly(A) (lane 4–6), poly(C) (lane 7–9), poly(G) (lane 10–12) and poly(U) (lane 13–15). The binding reactions were incubated for 15 minutes at 25°C and subsequently analyzed by EMSA and phosphorimaging. Lane 1, 2 and 3 show binding reactions without homoribopolymer addition, with NR 1 R 2 R 3 alone in lane 1, R 2 R 3 in lane 2 and the mixture of both in lane 3. Panel B: NR 1 R 2 R 3 and R 2 R 3 were combined in a binding reaction as in panel A, but now in the presence of 1 ng, 10 ng or 100 ng of the ribopolymers poly(G) (lanes 3–5), poly(I) (lanes 6–8), poly(I-C) (lanes 9–11) and 100 ng poly(A) (lane 12), respectively. Lane 1 shows free probe, whereas lane 2 shows binding reaction without ribopolymer addition. Figure 2 RNase treatment relieves poly(G)-mediated inhibition of c-Myb DNA-binding. NR 1 R 2 R 3 and R 2 R 3 were incubated with the MRE-containing DNA probe in the presence of 20 ng poly(G) homoribopolymer (lanes 3 and 4). The sample shown in lane 4 was in addition incubated with 2000 U RNase T1. To allow for RNase T1 mediated degradation of poly(G), all samples were incubated for 30 minutes at 37°C prior to addition of Myb-protein mixture. Binding reactions were subsequently incubated for 15 minutes at 25°C and analyzed by EMSA and phosphorimaging. Lanes 1 and 2 show free probe and binding reaction without homoribopolymer addition, respectively. To better compare the sensitivity of the two proteins, we titrated the poly(G) inhibition (Fig. 3 ). The DNA-binding of NR 1 R 2 R 3 was significantly more sensitive to poly(G) competition than R 2 R 3, indicating that the N-terminus including the R 1 repeat was important for the inhibitory effect. Figure 3 Titration of the poly(G) inhibition. NR 1 R 2 R 3 (40 fmol) and R 2 R 3 (20 fmol) were incubated separately with 20 fmol MRE-containing radiolabelled probe and increasing amounts of poly(G). The binding reactions were incubated for 15 minutes at 25°C and subsequently analyzed by EMSA and phosphorimaging. The intensities of the complex bands were quantified by phosphorimaging software and plotted as percentage of the complex band intensity when no homoribopolymers was added. Different plausible mechanisms for the observed poly(G) inhibition of c-Myb sequence-specific DNA-binding may be operating. Poly(G) might bind to c-Myb in direct competition with DNA. Or, the binding of poly(G) to c-Myb might be allosteric, inducing structural changes in c-Myb that reduces its DNA-affinity. A third explanation might be that poly(G) in a subtle way interacts with the DNA-probe and blocks its specific interaction with c-Myb. To clarify the mechanism of inhibition, we studied the importance of the order of addition of probe and homoribopolymers to the binding reaction (Fig. 4 ). Three situations were investigated, designated R, S and D in Fig. 4 : (R) RNA was mixed with the proteins before addition of probe, (S) RNA and probe were mixed and added simultaneously to the proteins, (D) Probe (DNA) was mixed with protein before addition of RNA. The reasoning was that if the inhibition is allosteric of nature, the magnitude of inhibition should be independent of the order of addition. If probe-interference is the mechanism, the strongest inhibition should be observed with the simultaneous addition of RNA and probe. If a competitive binding of poly(G) to c-Myb is the case, the strongest inhibition should be expected with the addition of RNA to protein first and the weakest inhibition when the probe was added first. The last scenario was in fact what we observed, indicating that c-Myb binds to poly(G) in direct competition with DNA-binding (Fig. 4 ). No inhibition at all was observed when 100 ng of poly(A) was added. It is noteworthy that the relative sensitivity of the two Myb forms also changed as a function of the order of addition. Pre-incubation with RNA enhanced the difference between NR 1 R 2 R3 and R 2 R 3 significantly, the first being fully inhibited while the latter seemed to be almost unaffected. In contrast, pre-incubation with DNA allowed the two forms to bind with similar efficiency. This supports the notion that the N-terminal region including the R 1 repeat plays an important role in conferring RNA-sensitivity to the protein. Figure 4 Order-of-addition analysis. A mixture of 40 fmol NR 1 R 2 R 3 and 20 fmol R 2 R 3 was incubated with 30 fmol MRE-containing DNA probe and 1 ng poly(G) (lane 4–6), 10 ng poly(G) (lane 7–9) and 100 ng poly(A) (lane 10–12). In the cases marked R (for "RNA first", lane 4, 7 and 10), the proteins were incubated with homoribopolymers for 15 minutes at 25°C before addition of DNA-probe and further incubation for 15 minutes at 25°C. The cases marked S (for ``simultaneous addition'', lane 5, 8 and 11) represents reactions where homoribopolymers and DNA probe were mixed before addition of protein and 15 minutes of incubation. Finally, the cases marked D (for ``DNA first'', lane 6, 9 and 12) show reactions where the protein were incubated with DNA first and then homoribopolymers were added. The reactions in lane 1–3 contained no homoribopolymers, NR 1 R 2 R 3 protein alone in lane 1 and R 2 R 3 protein alone in lane 2. The binding reactions were subsequently analyzed by EMSA and phosphorimaging. The homoribopolymer experiments reported above were performed with 15 minutes of incubation at 25°C. To exclude that the poly(G) effect was just a consequence of slower complex formation, we repeated the experiment with longer incubation times up to 90 minutes (results not shown). No change in the inhibition pattern was observed. This argues against the possibility that poly(G) only reduces the rate of c-Myb/DNA complex formation and indicates that the complex with RNA is highly stable. We then asked whether the poly(G) inhibition was specific for c-Myb or if other Myb proteins exhibited the same properties. Purified NR 1 R 2 R 3 forms of the vertebrate Myb relatives A- and B-Myb together with c-Myb were analyzed by EMSA in the presence of different concentrations of poly(G) and poly(A). As shown in Fig. 5 , the DNA-binding of A- and B-Myb was clearly inhibited by poly(G), although the effect was somewhat weaker than for c-Myb. A-Myb behaved most similar to c-Myb, consistent with the close resemblance between these two transcription factors [ 46 ]. Figure 5 Comparison of A-, B- and c-Myb's poly(G) inhibition. A-, B- and c-Myb NR 1 R 2 R 3 (40 fmol each) were incubated separately with 20 fmol radiolabelled MRE-containing DNA probe, 0.5 ng poly(G) (lane 2),1 ng poly(G) (lane 3), 5 ng poly(G) (lane 4) and 100 ng poly(A) (lane 5). Homoribopolymers and proteins were first incubated for 15 minutes at 25°C. Then the DNA-probe was added to the mixtures and subjected to a new incubation of the same time and temperature. The binding reactions were analyzed by EMSA and autoradiography. The extra incubation step without probe was added to the experimental setup because it enhanced the inhibitory effect (lanes marked R in Fig. 3). Discussion The DBD of c-Myb contains three tandemly arranged pseudo-repeats, R 1 , R 2 and R 3 , among which R 2 and R 3 together are responsible for sequence-specific DNA-binding. The function of the first repeat, R 1 , has remained elusive in particular because R 1 does not directly contact DNA. Its involvement in the process of oncogenic activation of Myb suggests a specific biological role of R 1 . In this report we have focused on the N-terminal region including the R 1 repeat of c-Myb, trying to find a function beyond DNA-binding. A homoribopolymer inhibition assay revealed a strong preferential inhibition of sequence-specific DNA-binding by poly(G), suggesting that c-Myb can interact with RNA in a sequence-selective fashion. The most interesting observation was the finding that the RNA-interference function of c-Myb was highly dependent on the N-terminal region including R 1 . Upon exposure to RNA before DNA, the protein domain containing this region was severely inhibited by low concentrations of poly(G) while the protein domain lacking this region was almost unaffected. What the precise biological role of this novel RNA-interaction is, remains to be elucidated. Central to our examination of the RNA-binding hypothesis is a homoribopolymer inhibition assay. Differential binding to homoribopolymers has been exploited as evidence for RNA-binding activity of several proteins, like the Ets-related transcription factor PU.1 [ 41 ], the neuronal KH domain containing protein Nova-1 [ 43 ], the chloroplast ribosomal protein CS1 [ 44 ], and the recently cloned RRM domain containing Ciona intestinalis protein RGC [ 45 ]. Whether homoribopolymer binding reflects a sequence-specific RNA binding or a more general RNA-binding, like in the case of polypyrimidine-tract or poly(A) binding proteins, requires further analysis in each case. In addition to the data presented above, the SELEX (systematic evolution of ligands by exponential enrichment) technology was applied to search for more sequence-specific RNA patterns recognized by c-Myb. The SELEX procedure did produce specific patterns, confirming the proper behaviour of the experiment, but the selected RNAs did not seem to mimic the homoribopolymer effect in terms of inhibitory efficiency and content of G-bases (results not shown). This does not argue against RNA-binding per se, but indicates that c-Myb may not interact in a strictly sequence-specific fashion with RNA. Rather, we believe that the inhibitory RNA-effect seen in the homoribopolymer experiments reflects an R 1 -dependent RNA-interaction where G-rich RNA interacts more avidly than other RNAs. Why G-rich species are so much more potent inhibitors is not obvious. G-rich RNA molecules have special folding capacities that could be recognized by c-Myb. This is illustrated by the fact that poly(G) has been reported to fold into several unique structures, including single, double and four-stranded helices [ 47 - 49 ]. To investigate the possibility that poly(dG) had a similar effect on c-Myb DNA binding as poly(G), we added DNA oligonucleotides containing deoxy-guanine stretches of varying length (1 to 5) to EMSA reactions. However, we were not able to correlate the presence of poly(dG) stretches to any inhibitory effects (results not shown). Neither did we observe any strong inhibition when poly(IC) or poly(I) was added. It is quite probable therefore that unique structural properties of poly(G) are critical to the mechanism of inhibition. The poly(G) inhibition was surprisingly strong. Due to the undefined length of the homoribopolymers, it was not evident how to precisely determine their molar concentrations. A fictitious poly(G)-length of 23 nucleotides, which is the length of the probe, gives an RNA-concentration of about 6 nM when 1 ng is added to the binding reactions. Consequently, a six-fold estimated molar excess of poly(G) compared to the probe concentration (1 nM) was sufficient to completely abolish sequence-specific DNA-binding (Fig. 3 ). We also analyzed the effects of a series of mononucleotides (results not shown). Interestingly, specific nucleotide triphosphates did in fact inhibit DNA-binding of c-Myb with differences resembling the pattern observed with ribopolymers in the present work. GTP produced the most prominent effect among the nucleotides, while CTP or UTP had little or no inhibitory effect. However, since the inhibition was observed first in the mM concentration range, significantly higher than the amount of poly(G) producing the same level of inhibition, the GTP phenomenon seems to be only a weak reflection of the strong inhibition we see with poly(G). Still, it is intriguing that we observe the same specificity suggesting some type of specific interactions between guanosines and the DNA-binding domain of c-Myb. The reported results represent evidence for an RNA-binding function of c-Myb. The dependence on the N-terminal region including R 1 is not total, in the sense that without this region all RNA-interference disappears. Rather, the presence of this region seems to enhance the sensitivity to RNA-mediated inhibition several fold, making it possible to find conditions where a Myb DBD containing this region becomes fully inhibited while a minimal DBD remains more or less unaffected (Fig. 4 ). At higher concentrations of poly(G) RNA, however, both proteins become inhibited, suggesting that other parts of the DBD are involved too. An appealing hypothesis would be that the flexible second repeat were involved in interactions with both types of macromolecules, cooperating with R 1 for RNA-binding and with R 3 for DNA-binding. This would explain why this repeat appears to be a more flexible protein domain than the other repeats. It is noteworthy that a DNA-bound protein seems to be resistant to RNA-mediated inhibition and that an RNA-associated protein does not bind DNA even after prolonged incubation. We have previously shown that c-Myb R 2 R 3 undergoes a conformational change upon binding to DNA [ 14 , 50 , 51 ]. It is possible that the DNA-induced conformation is resistant to RNA-interference and that RNA induces another conformation that is unable to bind DNA; in other words that the two nucleic acids lock the protein in two distinct conformations. It could be argued that we have shown mainly experiments of the RNA-interference type, not directly demonstrating RNA-binding. We have, however, several lines of evidence indicating that RNA-interference occurs through direct binding of c-Myb DBD to RNA. c-Myb NR 1 R 2 R 3 was observed to interact with RNA in a North-Western experiment where R 2 R 3 did not, and c-Myb NR 1 R 2 R 3 bound to RNA-linked beads (results not shown). The identification of an increasing number of proteins capable of both DNA- and RNA-binding challenges the established picture of DNA-bound regulators with functions confined to promoter-activation, and suggests a broader function for some transcription factors [ 39 ]. The precise physiological role of the novel RNA-binding property of c-Myb remains to be elucidated. An interesting possibility to investigate is whether c-Myb plays a role beyond transcriptional activation in biological processes involving RNA, like splicing, capping, polyadenylation, nuclear export or transport of RNA. A role in one or several of these processes will fit the forthcoming model of a coupling between transcription and the post-transcriptional fate of mRNA [ 52 , 53 ]. Conclusions We have obtained evidence that c-Myb DNA-binding is preferentially inhibited by poly(G) RNA, indicative of a sequence-selective RNA binding function. The N-terminus of c-Myb, including the R 1 repeat, was shown to contribute substantially to this RNA-sensitivity. This finding suggests a more specific function of the enigmatic first Myb repeat than having a stabilizing effect on DNA-binding only. Methods Homoribopolymers All homoribopolymers were purchased from Sigma Aldrich. Purities were higher than 98% for all polymers. The length distributions of the homoribopolymers were determined by agarose gel electrophoresis and UV-shadowing. When compared to a dsDNA ladder, poly(A), poly(C), poly(G)and poly(U) migrated with a distribution corresponding to the following ranges: 200–1600 bp, 250–1200 bp, 100–700 bp and 250–700 bp, respectively (results not shown). RNase T1 was purchased from Ambion, Inc. Expression and purification of recombinant proteins The following DBD subdomains were expressed in E. coli (strain BL21 (DE3) LysS) using the T7 system [ 54 ]: Human c-Myb residue 1–192 (NR 1 R 2 R 3 ) and 89–192 (R 2 R 3 ), human A-Myb 1–187 (NR 1 R 2 R 3 ) and B-Myb 1–183 (NR 1 R 2 R 3 ). Expression and purification were performed as previously described [ 46 ]. Electrophoretic mobility shift assay Sequence-specific DNA-binding was examined by electrophoretic mobility shift assay (EMSA) as previously described [ 55 ]. The binding reactions were performed in 20 mM Tris-HCl pH 8.0, 0.1 mM EDTA, 10% glycerol, 0.1 mM DTT, 0.005% Triton X-100 and 50 mM NaCl in a total volume of 20 μl. RNAguard (Amersham Biosciences) RNAse inhibitor (6–20 U) was added to each reaction to avoid degradation of the homoribopolymers. The sequence of the MRE-containing DNA probe was from the mim-1 promoter: 5'-GCATTA TAACGGTTT TTTAGCGC-3'. Double-stranded DNA oligonucleotides were 32 P- labelled by T4 polynucleotide kinase according to the specifications of the manufacturer (Ready-To-Go T4 Polynucleotide kinase, Amersham Biosciences). Radiolabelled probe was purified on G-25 MicroSpin columns (Amersham Biosciences) or by polyacrylamide gel electrophoresis with subsequent gel extraction. Phosphorimaging EMSA gels were transferred to 3 MM paper and dried for 90 minutes at 80°C in a vacuum gel drier. Radiolabelled bands were detected with Molecular Imaging Screen BI (Bio-Rad) and analyzed with a Bio-Rad GS-250 PhosphorImager. Quantitation of band intensities was performed with the Molecular Analyst 2.0.1 software (Bio-Rad). Authors' contributions ON performed the majority of the experiments and participated in the writing of the manuscript. TØA was responsible for the experiments shown in Fig. 1B and 2 . OSG designed the study and participated in the writing. All three authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC533864.xml
406388	Mre11 Assembles Linear DNA Fragments into DNA Damage Signaling Complexes	Mre11/Rad50/Nbs1 complex (MRN) is essential to suppress the generation of double-strand breaks (DSBs) during DNA replication. MRN also plays a role in the response to DSBs created by DNA damage. Hypomorphic mutations in Mre11 (which causes an ataxia-telangiectasia-like disease [ATLD]) and mutations in the ataxia-telangiectasia-mutated ( ATM ) gene lead to defects in handling damaged DNA and to similar clinical and cellular phenotypes. Using Xenopus egg extracts, we have designed a simple assay to define the biochemistry of Mre11. MRN is required for efficient activation of the DNA damage response induced by DSBs. We isolated a high molecular weight DNA damage signaling complex that includes MRN, damaged DNA molecules, and activated ATM. Complex formation is partially dependent upon Zn 2+ and requires an intact Mre11 C-terminal domain that is deleted in some ATLD patients. The ATLD truncation can still perform the role of Mre11 during replication. Our work demonstrates the role of Mre11 in assembling DNA damage signaling centers that are reminiscent of irradiation-induced foci. It also provides a molecular explanation for the similarities between ataxia-telangiectasia (A-T) and ATLD.	Introduction Cellular response to DNA damage requires the coordinated activation of cell cycle checkpoints with DNA repair ( Zhou and Elledge 2000 ). Failure to block S-phase entry in response to damaged DNA or to repair the DNA leads to genomic instability, the hallmark of cancer cells. DNA double-strand breaks (DSBs) are particularly harmful to cells; if unrepaired, DSBs generate aneuploidy and chromosomal translocations. DSBs activate a network of signaling pathways that coordinate the sensing and repair of the damage with cell cycle arrest. The major signaling pathway triggered by DSBs involves ataxia-telangiectasia-mutated (ATM) protein kinase ( Zhou and Elledge 2000 ). ATM is a serine-threonine kinase related to the PI3 kinase family. DSBs activate ATM by promoting its autophosphorylation ( Bakkenist and Kastan 2003 ). Activated ATM phosphorylates protein substrates involved in DNA repair, cell cycle arrest, and apoptosis. Phosphorylation of Nbs1 by ATM is critical for S-phase checkpoint ( Gatei et al. 2000 ; Lim et al. 2000 ; Zhao et al. 2000 ). Nbs1 forms a trimeric complex with Mre11 and Rad50 (MRN) that is needed for DSB repair by homologous recombination ( Haber 1998 ; D'Amours and Jackson 2002 ; Symington 2003 ). The three proteins are also essential for vertebrate embryonic development and cell growth ( Luo et al. 1999 ; Yamaguchi-Iwai et al. 1999 ; Zhu et al. 2001 ). MRN prevents the accumulation of DSBs during DNA replication ( Costanzo et al. 2001 ). ATM function is defective in patients carrying the recessive genetic disorder ataxia-telangiectasia (A-T). A-T is characterized by cerebellar degeneration, immunodeficiency, radiation sensitivity, chromosomal instability, and cancer predisposition ( Gatti et al. 2001 ). Hypomorphic mutations in Mre11 and Nbs1 give rise, respectively, to an A-T-like disease (ATLD) and Nijmegen breakage syndrome (NBS) ( Digweed et al. 1999 ; Stewart et al. 1999 ; Tauchi et al. 2002 ). The clinical presentations of A-T and ATLD are indistinguishable. NBS patients display the symptoms of A-T and ATLD and, in addition, microcephaly and mental deficiency ( Tauchi et al. 2002 ). All three diseases have similar cellular phenotypes. The mutant cells do not respond appropriately to DSBs and display chromosome abnormalities, hypersensitivity to ionizing radiations, radio-resistant DNA synthesis, and an S-phase checkpoint defect ( Shiloh and Kastan 2001 ). These similarities strongly suggest that ATM and MRN function in a common signaling pathway. However, the molecular connection between these proteins is yet to be determined. Mre11 binds DNA and is both a 3′-to-5′ exonuclease and an endonuclease that cleaves hairpin DNA structures ( Paull and Gellert 1999 ). Rad50 belongs to the structural maintenance of chromosomes (SMC) family of proteins. Rad50 contains C-terminal and N-terminal Walker A and B domains separated by a long coiled-coil domain ( de Jager et al. 2001 ; Hopfner et al. 2002 ). Intramolecular assembly of the coiled-coil domain brings the Walker A and B motifs together to generate a functional nucleotide-binding module. A zinc-binding motif (CXXC), or “zinc hook,” located at the base of the Rad50 coiled coil, mediates Rad50 dimerization through coordination of a zinc ion by four cysteine residues ( Hopfner et al. 2002 ). Rad50 dimer binds to two Mre11 molecules to form a stable tetrameric complex with enhanced nuclease activities ( Trujillo and Sung 2001 ). hRad50/hMre11 complexes tether linear duplex DNA molecules as demonstrated by scanning force microscopy ( de Jager et al. 2001 ). Based on these observations, a model has been proposed in which the Mre11/Rad50 complex bridges broken DNA ends or sister chromatids (van den Bosch 2003). In yeast and mammalian cells, DSBs provoke the formation of defined nuclear structures called irradiation-induced foci (IRIF). IRIF are believed to originate by chromatin modification, such as H2AX phosphorylation, at the site of the DSB, followed by the recruitment of signaling and repair factors. MRN localizes to DSBs, independently of H2AX phosphorylation, and is critical for the formation of IRIF and the consequent response to DNA damage ( Petrini and Stracker 2003 ). Thus, cells with mutations in Mre11 or Nbs1 form IRIF inefficiently. In ATLD cells, which carry a defective Mre11 , ATM activation is inhibited. Furthermore, ATM fails to localize to sites of DSBs in cells lacking functional MRN ( Uziel et al. 2003 ). Taken together, these results suggest that MRN plays an early and essential role in assembly of functional signaling complexes at the sites of DNA damage. Furthermore, they place MRN upstream of ATM in the DNA damage signaling pathway. Cell-free extracts derived from Xenopus eggs recapitulate signaling pathways triggered by DNA damage and have been instrumental in unraveling the functions of ATM and Mre11 ( Costanzo et al. 2000 , 2001 ). Using this system, we show below that fragmented DNA assembles with proteins into macromolecular structures enriched in activated ATM and MRN. Their assembly requires MRN but not ATM. A truncated form of Mre11 associated with ATLD does not support DNA–protein complex assembly or DSB-induced activation of ATM. This work provides a direct molecular connection between ATM and MRN that can explain the similarities between A-T and ATLD. Results A Rapid Assay for the Response to DNA DSBs Addition of fragmented DNA to Xenopus egg extracts triggers the ATM-signaling pathway ( Costanzo et al. 2000 ). We previously demonstrated this reaction by measuring an ATM-dependent block to DNA replication in extracts treated with DNA fragments ( Costanzo et al. 2000 ). We now describe a rapid assay to monitor the activation of DSB-responsive protein kinases and to assess the contribution of ATM and related protein kinases. Histone H2AX, a well-characterized substrate for DSB-activated protein kinases, is phosphorylated in vivo at serine 139 by ATM and the ataxia-telangiectasia-related protein (ATR) ( Rogakou et al. 1998 ; Burma et al. 2001 ; Costanzo et al. 2001 ; Ward and Chen 2001 ). We used the C-terminal peptide of mouse H2AX (PAVGKKA S 134 QA S 139 QEY) as a reporter substrate to monitor the response to DSBs. This peptide contains two putative SQ phosphorylation sites for ATM or ATR: serines 134 and 139. To test the specificity of the kinase(s) activated by DSBs, we synthesized four peptides: wild-type and alanine substitutions at serine 134 (S134A), serine 139 (S139A), and serines 134 and 139 (S134A/S139A). Incubation of interphase extracts for 30 min with fragmented DNA dramatically enhanced phosphorylation of H2AX peptide ( Figure 1 A). Phosphorylated H2AX peptide could be detected as early as 5 min after addition of fragmented DNA (data not shown). S134A peptide was phosphorylated to a level equivalent to wild-type peptide, whereas S139A and S134/139A peptides were not modified. Thus, phosphorylation of S139 in cell-free extracts in response to DSBs mimics the in vivo situation ( Rogakou et al. 1998 ; Burma et al. 2001 ; Costanzo et al. 2001 ; Ward and Chen 2001 ). Figure 1 Functional MRN Is Required for the Response to DSBs, and Mre11–ATLD Separates Essential and Nonessential Mre11 Functions (A) The activity of protein kinases responsive to DSBs in Xenopus laevis egg extracts was monitored by incorporation of 32 P from γ- 32 P-ATP into H2AX-derived peptides in the presence (plus DSB) or absence (minus DSB) of fragmented DNA. Labels: Wild-Type, H2AX substrate peptide containing serine 134 and serine 139; S134A, H2AX substrate peptide with a substitution of serine 134 to alanine; S139A, H2AX substrate peptide with a substitution of serine 139 to alanine; S134A/S139A, H2AX substrate peptide with a substitution of both serines to alanine. (B) Extract incubated with linear DNA at 50 ng/μl (equivalent to 4.5 × 10 10 breaks/μl) was assayed with H2AX peptide in the presence of buffer (Control), ATM-neutralizing antibodies (ATM Ab), ATR-neutralizing antibodies (ATR Ab), ATM- and ATR-neutralizing antibodies (ATM/ATR Abs), ATM- and ATR-neutralizing antibodies in Ku70-depleted extracts (ATM/ATR Abs; Ku depletion), 5 mM caffeine (Caffeine). (C) DSB-responsive kinase activity was measured in the presence of 0, 5, 10, 25, and 50 ng/μl of linear DNA in control extract (filled diamonds), mock-depleted extract (open diamonds), Mre11-depleted extract (open squares), Mre11-depleted extract supplemented with 500 nM of recombinant MRN (filled squares), or Mre11-depleted extract supplemented with 500 nM MRN-ATLD1/2 (filled triangles). (D) DSB accumulation during DNA replication was monitored by TUNEL assay. Postreplicative nuclei were isolated from a control extract (stripes), Mre11-depleted extract (dots), Mre11-depleted extract supplemented with MRN (diamonds), Mre11-depleted extract supplemented with MRN-ATLD1/2 (gray) or mock-depleted extract (white). We next monitored phosphorylation of H2AX peptide in extracts in which specific DNA damage response signaling pathways were inhibited. X-ATM- and X-ATR-neutralizing antibodies were used to abrogate ATM- and ATR-dependent signaling, respectively. We previously demonstrated that these antibodies completely inhibit ATM- and ATR-dependent checkpoints in extracts ( Costanzo et al. 2000 , 2003 ). H2AX peptide phosphorylation was significantly reduced in extracts treated with either X-ATM or X-ATR antibodies. Inhibition of both ATR and ATM further decreased H2AX peptide phosphorylation to 20% of control levels ( Figure 1 B, column 4). Inhibition of DNA-PK by depletion of Ku70 did not further reduce H2AX peptide phosphorylation in the ATM/ATR-inhibited extract. Finally, caffeine completely abrogated H2AX peptide phosphorylation ( Figure 1 B, column 6). We conclude that most H2AX phosphorylation induced by DSBs in crude extracts is ATM- and ATR-dependent. Functional MRN Is Required for ATM Activation Experiments using cells carrying hypomorphic mutations in Nbs1 or Mre11 ( Carney et al. 1998 ; Varon et al. 1998 ; Stewart et al. 1999 ; Petrini and Stracker 2003 ) suggested that MRN also plays a role in sensing signals triggered by DSBs. However, because Mre11 and Nbs1 are essential genes ( Yamaguchi-Iwai et al. 1999 ; Zhu et al. 2001 ; Tauchi et al. 2002 ), the effect of total Mre11 inactivation on the DNA damage response could not be established. We asked whether MRN was required in our system for DSB-dependent activation of H2AX peptide phosphorylation. We have previously established that Mre11 can be quantitatively depleted from extracts ( Costanzo et al. 2001 ). Figure 1 C shows that depletion of extracts for Mre11 abrogated the response to DSB-containing DNA ( Figure 1 C, open squares). Recombinant human MRN restored the DNA damage response in the Mre11-depleted extract ( Figure 1 C, filled squares). ATLD, a syndrome characterized by failure of the DNA damage response, is caused by hypomorphic mutations in Mre11 ( Stewart et al. 1999 ). In contrast to wild-type protein, MRN containing a mutant Mre11 that lacks the C-terminal DNA-binding domain (MRN-ATLD1/2) ( Stewart et al. 1999 ; Lee et al. 2003 ) did not restore activity to the Mre11-depleted extract ( Figure 1 C, filled triangles). At higher fragmented DNA concentrations (greater than or equal to 100 ng/μl), H2AX peptide phosphorylation became partly independent of ATM and Mre11. This phosphorylation was sensitive to vanillin, a specific inhibitor of DNA-PK ( Durant and Karran 2003 ), and to Ku depletion (data not shown). In contrast to its inactivity in the DSB checkpoint reaction, MRN-ATLD1/2 can fulfill the essential function of MRN in preventing the accumulation of breaks during DNA replication. Figure 1 D shows a TUNEL assay to detect DNA ends. As we previously reported ( Costanzo et al. 2001 ), chromosomal DNA replicated in Mre11-depleted extracts accumulated DSBs. Addition of purified recombinant MRN to depleted extracts largely prevented DNA fragmentation. MRN-ATLD1/2 was as efficient as wild-type MRN in supporting normal DNA replication. These results establish that MRN is required to activate the DSB signal pathway and that the C-terminal region of Mre11 plays a critical role in this activation. Linear DNA Fragments Trigger Mre11-Dependent Assembly of Large DNA–Protein Complexes Scanning force microscopy data ( de Jager et al. 2001 ) show that Mre11–Rad50 binds preferentially to broken DNA ends, implying that direct interaction with linear DNA is essential for MRN function. To investigate interactions between Mre11 and damaged DNA, interphase extract was incubated with 32 P-labeled, 1 kb linear double-strand DNA molecules and applied to a BioGel A15m column. This large-pore gel filtration resin includes most proteins and small DNA fragments, but excludes protein–DNA complexes larger than 1.5 × 10 7 kDa (Yuzakhov et al. 1999). When radio-labeled DNA at the concentration of 50 ng/μl (equivalent to 4.5 × 10 10 ends/μl) was applied to the column in the absence of extract ( Figure 2 A) or with extract but prior to incubation (data not shown), all radioactivity was recovered in the included volume. In contrast, when fragmented DNA was incubated with extract prior to chromatography, radio-labeled DNA resolved into two peaks ( Figure 2 B). Most DNA was still recovered in the included volume (fractions 20–30). However, a separate DNA peak corresponding to 3%–5% of the total DNA loaded appeared in the excluded volume (fractions 9–12). In contrast, labeled double-strand circular plasmid DNA did not assemble into DNA–protein complexes after incubation; all labeled DNA was recovered in the included volume ( Figure 2 C). Figure 2 Requirements for the Assembly of DNA–Protein Complexes Elution profiles of α- 32 P-dATP-labeled 1 kb linear DNA from BioGel A15m chromatography columns. After loading, fractions 1–31 were collected and radioactivity was counted in a scintillation counter. (A–E) Complete elution profile. (A) Linear DNA alone. (B) Linear DNA incubated 2 h in extract at 22°C. (C) α- 32 P-dATP-labeled circular plasmid incubated for 2 h in extract at 22°C. (D) Linear DNA incubated with extract treated with 1 mg/ml proteinase K immediately prior to loading. (E) Linear DNA incubated in Mre11-depleted extract. (F and G) Excluded volume (fractions 6–14). (F) Linear DNA incubated in the following extracts: Mre11-depleted extract (open triangles), Mre11-depleted extract supplemented with 500 nM of MRN (filled triangles), Mre11-depleted extract supplemented with 500 nM of MRN-ATLD1/2 (open squares), or control extract supplemented with MRN (filled squares). (G) Linear DNA incubated in the following extracts: control extract (filled circles), extract treated with 5 mM caffeine (open circles), extract treated with TPEN at 100 μM (open diamonds). The peak in the excluded volume represents large DNA–protein complexes that assembled in the extract, since it was eliminated by treatment of the extract with proteinase K immediately prior to chromatography ( Figure 2 D). Note that the elution buffer contains detergent, ruling out possible membrane aggregation. To determine whether Mre11 plays a role in assembling the DNA–protein complex, we incubated labeled DNA in an Mre11-depleted extract ( Figure 2 E). In the absence of Mre11, almost no radioactive label was recovered in the excluded volume. Addition of recombinant human MRN to the depleted extract restored the peak of high molecular weight DNA–protein complex ( Figure 2 F, filled triangles). We conclude, therefore, that the assembly of DNA–protein complexes requires Mre11. Furthermore, addition of MRN to nondepleted extract increased the amount of DNA in the excluded volume ( Figure 2 F, filled squares), suggesting that MRN is limiting in these extracts. MRN-ATLD1/2 did not restore DNA–protein complex formation in an Mre11-depleted extract ( Figure 2 F, open squares), indicating that an intact Mre11 C-terminal domain is required for complex assembly. Rad50 protein forms intramolecular coiled-coil interactions as well as intermolecular interactions via a Zn 2+ -chelating hinge region coordinated by four cysteine residues, the “zinc-hook” ( Hopfner et al. 2002 ). Addition of TPEN, a chelating agent specific for Zn 2+ ( Shumaker et al. 1998 ), partially inhibited formation of DNA–protein complexes ( Figure 2 G, open circles). Finally, caffeine significantly reduced but did not eliminate the amount of labeled DNA in the excluded peak ( Figure 2 G, open diamonds). This suggests that assembly of the DNA–protein complex is partially independent of ATM/ATR. MRN Complex Is Part of the DNA–Protein Complexes That Tethers Linear DNA Molecules The previous experiments established that Mre11 is required for assembly of DNA–protein complexes. To demonstrate that Mre11 is an integral component of these complexes, we immunoprecipitated Mre11 from chromatographic fractions 10 and 25 and measured the 32 P-DNA content of the precipitate. We found labeled DNA associated with MRN in fraction 10 ( Figure 3 A) but not in fraction 25, although this fraction contains both Mre11 (see Figure 4 A) and 32 P-DNA. As expected, immunoprecipitates of excluded fractions following chromatography of Mre11-depleted extracts did not contain labeled DNA. When Mre11 immunoprecipitated from control extracts was added to Mre11-depleted extract, we again found MRN–DNA complexes in fraction 10, but not in fraction 25 ( Figure 3 A). Figure 3 Mre11 Tethers DSB-Containing DNA (A) Control and treated extracts were incubated with α- 32 P-dATP-labeled DNA fragments and loaded onto BioGel A15 columns. Fractions 10 and 25 were collected and incubated with polyclonal antibodies against Mre11 or protein A beads alone. Beads were collected and washed, and radioactivity was counted in a scintillation counter. Shown are control extract (stripes), Mre11-depleted extract (dots), or Mre11-depleted extract supplemented with Mre11 that had been immunoprecipitated from the extract (diamonds), and extract incubated with beads alone (black). (B) Biotinylated DNA fragments were mixed with α- 32 P-dATP-labeled DNA fragments and incubated with various extracts. The extracts were then loaded onto BioGel A15 columns. Fractions 10 and 25 were collected and incubated with streptavidin-magnetic beads. Beads were collected and washed, and radioactivity was counted in a scintillation counter. Shown are control extract (stripes), Mre11-depleted extract (dots), Mre11-depleted extract supplemented with 500 nM MRN (diamonds), and streptavidin beads (black). Figure 4 DNA–Protein Complexes Are Signaling Centers Containing Active Mre11 and ATM (A) Western blot analysis of eluted fractions. Fraction numbers are indicated at bottom. Fractions were collected following chromatography of extracts incubated with fragmented (plus DSBs) or without fragmented DNA (minus DSBs). Samples from fractions were processed for SDS-PAGE and blotted with polyclonal antibodies against Mre11, ATM, and phosphorylated ATM. (B) Activity of ATM and ATR kinases in fractions 10 and 25. Extracts were incubated with DNA fragments and applied to BioGel A15m columns. Fraction 10 and fraction 25 from control extract were assayed for H2AX activity in presence of buffer (light gray), ATM-neutralizing antibodies (checks), ATR-neutralizing antibodies (dark gray), 300 μM vanillin (stripes), or 5 mM caffeine (black). (C) Activity of ATM and ATR kinases in fraction 10 and total extract. Control extracts or extracts supplemented with 500 nM recombinant MRN were incubated with DSBs and loaded onto BioGel A15m columns. Total control extract and fraction 10 were assayed for H2AX activity in the presence of buffer (light gray), ATM-neutralizing antibodies (checks), ATR-neutralizing antibodies (dark gray), or 5 mM caffeine (black). We conclude that MRN is a component of the DNA–protein complex. To demonstrate that linear DNA molecules were linked in the DNA–protein complex, we incubated extract with two populations of fragmented DNA. DNA molecules of identical sequence were either 32 P-labeled or biotinylated. As expected, the radioactivity elution profile was identical to that observed with a single species of DNA molecules (data not shown). Fraction 10 from the excluded volume and fraction 25 from the included volume were precipitated with PEG, and biotinylated DNA molecules were affinity-purified using streptavidin-magnetic beads. The results of this assay show clearly that 32 P-DNA was associated with biotinylated DNA in fraction 10, but not in fraction 25 ( Figure 3 B, columns 1 and 5). As expected, this association is Mre11-dependent. It was abolished in Mre11-depleted extracts and restored in Mre11-depleted extracts supplemented with recombinant MRN ( Figure 3 B, columns 2 and 3). Mre11-Containing DNA–Protein Complexes Are Signaling Centers We next looked for a molecular connection between the DNA–protein complex and protein kinase activation. We monitored the distribution and modification of Mre11 and ATM in the chromatographic fractions described above. Control extracts or extracts incubated with fragmented DNA were chromatographed, and fractions 9–12 from the excluded volume and fractions 25–28 from the included volume were PEG-precipitated and processed for Western blotting. In untreated control extracts, Mre11 and ATM were recovered only in the included volume. In extracts treated with linear DNA, however, Mre11 and ATM were present in both included and excluded fractions ( Figure 4 A, top four panels). Relative to the total protein content of the fractions, both Mre11 and ATM were enriched 18-fold and 46-fold respectively in the excluded fraction, as determined by image analysis. This confirms that the high molecular weight protein–DNA complexes contain Mre11, and additionally establishes the presence of ATM in the complex. Strikingly, Mre11 in the DNA–protein complex was in the active, phosphorylated form ( Costanzo et al. 2001 ). In contrast, Mre11 in the included fractions was unmodified. Furthermore, using an antibody that recognizes specifically the active form of ATM (phosphorylated on the serine equivalent to serine 1,981 of human ATM; Bakkenist and Kastan 2003 ), we detected phosphorylated ATM only in the excluded fractions ( Figure 4 A, third panel). To confirm that the excluded peak was enriched in active ATM kinase, we compared H2AX peptide kinase activity in fractions 10 and 25. We also determined the relative contribution of ATM, ATR and DNA-PK to this activity ( Figure 4 B). ATM and ATR protein kinase activities were inhibited with the specific neutralizing antibodies described above. DNA-PK activity was inhibited by vanillin, a specific inhibitor of DNA-PK (Durant and Karran 2003). Most H2AX kinase activity in fraction 10 was due to ATM, and to a lesser extent, to ATR ( Figure 4 B). Vanillin had little effect on kinase activity, indicating that the contribution of DNA-PK was small in this fraction. In contrast, the kinase activity in fraction 25 was sensitive to vanillin, but not to ATM- or ATR-neutralizing antibodies ( Figure 4 B). To provide further evidence that formation of MRN–DNA complexes directly promotes ATM activation, we supplemented extracts with recombinant MRN and compared H2AX peptide phosphorylation in total extract and in fraction 10. The proportion of H2AX kinase that was inhibited by ATM antibodies was significantly higher in fraction 10 than in total extract (compare columns 1 and 2 with columns 9 and 10 in Figure 4 C). Incubation of extract with recombinant MRN complex prior to chromatography increased H2AX kinase activity in fraction 10 by 80% (compare columns 1 and 5 in Figure 4 C). The increased kinase activity was entirely abrogated by anti-ATM antibody ( Figure 4 C, columns 2 and 6). Discussion MRN Complex Is Required for ATM Activation The three components of the MRN complex, Mre11, Rad50, and Nbs1, are essential. Mouse embryos or chicken cells carrying inactivating mutations in any of these proteins are not viable ( Luo et al. 1999 ; Yamaguchi-Iwai et al. 1999 ; Zhu et al. 2001 ). This has made studies of MRN and its interacting partners difficult to approach. Although a connection between ATM activation and MRN has long been known ( Petrini 2000 ), the precise mechanism that links these two factors had not, to our knowledge, been elucidated. However, using cell-free Xenopus egg extracts, it has been possible to inactivate biochemically essential gene products. We previously determined that depletion of Mre11 and its associated protein partners lead to DSB formation during DNA replication ( Costanzo et al. 2001 ). We used a similar strategy to relate MRN inactivation and ATM function. We provide several lines of evidence that indicate an MRN requirement for ATM activation. The G1–S checkpoint provoked by DSBs entails the sequential activation of protein kinases, including ATM ( Zhou and Elledge 2000 ). We show that depletion of Mre11 from our extracts abolishes DSB-dependent phosphorylation of H2AX peptide, a readout for this cascade. ATM is the major contributor to H2AX phosphorylation in these extracts. Our data strongly suggest that MRN specifically activates ATM. Fragmented DNA incubated in extracts forms high molecular weight DNA–protein complexes that include MRN and ATM. Of H2AX kinase activity in the complex in fraction 10, 75% is inhibited by antibodies to ATM. Furthermore, addition of recombinant MRN to extracts increases the yield of complex and associated H2AX kinase activity. The enhanced activity is entirely ATM-dependent. ATR also contributes significantly to H2AX phosphorylation in extracts treated with DSB-containing DNA. However, ATM is activated earlier than ATR (data not shown). ATR activation might be triggered by processing of DSBs into single-strand DNA (ssDNA) ( Zou and Elledge 2003 ) . We previously showed that ssDNA specifically stimulates ATR ( Costanzo et al. 2003 ). Since Mre11 depletion completely prevents H2AX phosphorylation, we propose that Mre11 regulates both ATM-dependent early signaling from DSBs and, possibly by its DNA exonucleolytic activity, delayed signaling by ATR. Whereas caffeine completely inhibits H2AX kinase, treatment with ATM/ATR antibodies combined inhibits only 80% of H2AX kinase. This could be accounted by an additional kinase such as ATX ( Abraham 2001 ). Alternatively, the neutralizing antibodies against ATM and ATR might not inhibit 100% of the activity of respective kinase towards H2AX. MRN Tethers Linear DNA Molecules and Assembles DNA Damage Signaling Complexes We propose that MRN interacts with linear DNA to form DNA–protein complexes that induce the phosphorylation cascade responsible for the G1–S checkpoint. MRN assembles with linear DNA molecules in vitro ( de Jager et al. 2001 ). We have isolated DNA–protein complexes from extracts incubated with fragmented DNA as an excluded fraction from a sizing column. The complexes require Mre11 for assembly, contain linear DNA, and are highly enriched in Mre11 and ATM. Immunoprecipitation studies with Mre11 antibodies show the presence of tripartite complexes (Mre11–ATM–fragmented DNA) in the excluded but not the void volume (data not shown). We believe that the formation of these complexes is a critical step in the kinase cascade that leads to the G1–S checkpoint. Several lines of evidence support this idea: (1) Mre11-depleted extracts do not form complexes and fail to activate ATM in response to DSBs. (2) Mre11 is concentrated 18-fold in the DNA–protein complexes and is heavily phosphorylated. We previously established that phosphorylation of Mre11 correlates with increased nuclease activity ( Costanzo et al. 2001 ). (3) ATM is enriched 46-fold in the complexes and is phosphorylated on serine 1,981 ( Bakkenist and Kastan 2003 ). Therefore, activated ATM is only detected in the DNA–protein complexes. ATM, and possibly ATR, participates in the assembly of the complexes. Pretreatment of extracts with caffeine, an inhibitor of ATM and ATR, significantly reduces the yield of complex. Some H2AX kinase activity is not associated with the DNA–protein complex. This activity is principally accounted for by DNA-PK. Both MRN components Mre11 and Nbs1 are phosphorylated in response to DSBs. Nbs1 phosphorylation is ATM-dependent ( Gatei et al. 2000 ; Lim et al. 2000 ; Zhao et al. 2000 ). Once recruited and activated within the signaling complex, ATM might phosphorylate Nbs1 and Mre11, stabilizing the complex and enhancing signaling activity. How might DNA–MRN complexes initiate the cascade of events leading to ATM activation? One of the critical steps could be to bring ATM in close proximity with “chromatinized” DNA fragments. Indeed, it was shown previously that ATM had affinity for DSBs ( Andegeko et al. 2001 ; Uziel et al 2003 ). ATM enrichment at sites of DSBs is consistent with the localized phosphorylation of H2AX observed in vivo on chromatin flanking DSBs ( van den Bosch et al. 2003 ). Our previous work showed that at high doses of DNA fragment (100 ng/μl, equivalent to 9 × 10 10 breaks/μl), the ATM-dependent checkpoint does not require Mre11 function ( Costanzo et al. 2001 ). We also determined that H2AX phosphorylation at 100 ng/μl of linear DNA is partially Mre11-independent (data not shown). This could be due to ATM activation by mass action at this dose of linear DNA as well as to activation of DNA-PK (data not shown). Molecular Bases for the Similarities between A-T and ATLD A powerful argument for placing MRN and ATM in a common signaling pathway derives from the similarities between the clinical and the cellular phenotypes of A-T, NBS, and ATLD ( Digweed et al. 1999 ; Stewart et al. 1999 ; Tauchi et al. 2002 ). Uziel et al. (2003 ) recently showed that the ATM response to DSBs is impaired in ATLD cells, which carry defective Mre11. After our work was completed, additional studies reached similar conclusions using Mre11- or Nbs1-deficient cells ( Carson et al. 2003 ; Mochan et al. 2003 ; Theunissen et al. 2003 ). Our data provide a biochemical framework to explain their observations. The ATLD1/2 mutation, which generates a truncated Mre11 that lacks part of its DNA-binding domain, is compatible with viability. Thus, the mutation cannot abrogate the essential role of Mre11, although the mutant Mre11 is defective in the damaged DNA response. We were able to dissociate the two Mre11 reactions using simple biochemical readouts. MRN-ATLD1/2 cannot activate ATM or form DNA–protein complexes in response to DSBs. It can, however, prevent accumulation of DSBs during chromosomal DNA replication. We speculate that MRN-ATLD1/2 has reduced affinity for damaged DNA, resulting in labile interactions with fragmented DNA and an inability to activate ATM. What differentiates the essential function of Mre11 during DNA replication from its ability to activate ATM? We suggest that MRN association with chromatin during DNA replication and, possibly, during meiotic recombination differs from its association with fragmented DNA. Consistent with this hypothesis, chromatin association of Mre11 was shown, by detergent extraction, to differ between replicative and γ-irradiated chromatin ( Mirzoeva and Petrini 2003 ). We previously demonstrated the association of Mre11 with chromatin during normal DNA replication. One can envisage MRN complexes forming on intact chromatin in a manner similar to other SMC proteins such as cohesins, and involving, perhaps, interactions with cohesins ( Kim et al. 2002 ). These complexes could perform the essential functions of MRN during replication and recombination and would not require an intact Mre11 C-terminal domain. This is consistent with the viability and recombination proficiency of ATLD mutant cells. In contrast, tethering of damaged DNA containing DSBs would require the Mre11 C-terminal DNA-binding domain. Failure to interact with broken DNA would account for the various phenotypes of A-T and ATLD. Alternatively, C-terminal truncation of Mre11 might weaken protein–protein interactions within the MRN complex or between MRN and other proteins. This idea is suggested by the Mre11 crystal structure, which shows that the C-terminal domain in close proximity to a hydrophobic region required for protein–protein interaction ( Hopfner et al. 2001 ). The truncated Mre11 might be unable to form the protein–protein interactions required to stabilize MRN–DNA complexes. MRN–DNA Complexes and IRIF The signaling complexes described above are reminiscent of IRIF observed in mammalian cells ( Maser et al. 1997 ). Indeed, Mre11 is one of the first proteins to localize to IRIF following DNA damage ( Petrini and Stracker 2003 ). Furthermore, cells from ATLD patients fail to establish foci ( Stewart et al. 1999 ), consistent with the inability of MRN-ATLD1/2 to support the formation of DNA–protein complexes in extracts. Recall that the ability to form foci and to activate a DNA damage response in mammalian cells are closely correlated ( Stewart et al. 1999 , 2003 ; Goldberg et al. 2003 ). There are several similarities between the formation of IRIF in vivo and assembly of the signaling structures in extracts. Both require (1) intact Mre11 protein and, presumably, binding of Mre11 to DNA, and (2) that IRIF form independently of ( Mirzoeva and Petrini 2001 ), but are stabilized by, ATM, possibly by phosphorylation of Mre11 and/or Nbs1 ( Gatei et al. 2000 ; Lim et al. 2000 ; Wu et al. 2000 ; Zhao et al. 2000 ; Costanzo et al. 2001 ; Lukas et al. 2003 ). As shown in Figure 5 , our data suggest that MRN concentrates and localizes DNA fragments and signaling proteins such as ATM in IRIF-like structures. MRN may be rate-limiting for assembly of these structures, even though Mre11 can be recovered apart from DNA–protein complexes. It was recently reported that the ends of broken chromosomes localize with phosphorylated H2AX to discrete spots in the nucleus ( Aten et al. 2004 ). The formation of these structures requires functional MRN. We suggest that these are the in vivo counterparts of the MRN-dependent structures that we observe in vitro. We have shown that DNA–protein complexes are essential for the DNA damage checkpoint. The challenge now is to dissect the assembly pathway and to identify the rate-limiting steps in the organization of these signaling centers. Figure 5 Schematic Representation of the Mre11-Dependent Assembly of DNA Damage Signaling Complexes MRN promotes the assembly of DNA–protein structures containing linear DNA fragments enriched with active ATM molecules. These active signaling complexes resemble IRIF in that they are the morphological and functional unit of the DNA damage response. Materials and Methods Xenopus egg extracts CSF-arrested extracts were freshly prepared according to Costanzo et al. (2001 ). For kinase assays, extracts were supplemented with 100 mg/μl cycloheximide and released into interphase with 0.4 mM CaCl 2 . DNA template To prepare DNA fragments containing DSBs, we used pBR322 plasmid digested with restriction endonucleases to yield different types of ends (3′-overhang, 5′-overhang, and blunt). These DNA fragments behaved equivalently in our assay (data not shown). For the experiments shown in Figure 1 , we used DNA digested with HaeIII. The 1 kb DNA fragment used for size fractionation experiments was obtained by PCR on M13 ssDNA template using 22 nt primers complementary to positions 5,570 and 6,584 ( de Jager et al. 2001 ). The 32 P-labeled fragment was obtained by addition of α- 32 P-dATP (10 mCi/μl) to the PCR. The biotinylated 1 kb fragment was obtained by PCR on M13 ssDNA template using a 22 nt primer complementary to position 5,570 and a 22 nt primer complementary to position 6,584, biotinylated on three thymidine residues (Sigma-Genosys, The Woodlands, Texas, United States). Kinase assays Interphase egg extracts were incubated with DNA fragments, DNA fragments and ATM-neutralizing Ab, ATR-neutralizing antibodies or 5 mM caffeine for 30 min at 22°C. Extract (2 μl) was mixed with 20 μl of EB kinase buffer (20 mM HEPES [pH 7.5], 50 mM NaCl, 10 mM MgCl 2 , 1 mM DTT, 1 mM NaF, 1 mM Na 3 VO 4 , and 10 mM MnCl 2 ) supplemented with 0.5 mg/ml histone H2AX peptide (Sigma-Genosys), 50 μM ATP, and 1 μl of γ- 32 P-ATP, 10 mCi/μl (greater than 3,000 Ci/mmol). Samples were incubated at 30°C for 20 min, and reactions were stopped by 20 μl of 50% acetic acid and spotted on p81 phosphocellulose filter paper (Upstate Biotechnology, Lake Placid, New York, United States). Filters were air-dried and washed three times in 10% acetic acid. Radioactivity was quantified in a scintillation counter. For kinase assays of fractionated extracts, 50 ng/μl of 1 kb DNA fragments was incubated in interphase extracts at 22°C for 2 h. Extracts were loaded onto the sizing column, and 250 μl fractions were collected. Fractions were supplemented with 9% PEG-6000, incubated on ice for 15 min, and spun in a microfuge at maximum speed at 4°C for 10 min. Pellets were resuspended in 20 μl of EB buffer, and 2 μl was assayed with histone H2AX peptide substrate, with or without ATM-neutralizing antibodies, ATR-neutralizing antibodies, 300 μM vanillin, or 5 mM caffeine. Egg extract fractionation Interphase egg extracts (200 μl) were incubated with or without 50 ng/μl of 32 P-labeled 1 kb DNA fragments for 2 h at 22°C. They were then mixed with one volume of buffer A, loaded onto a 15 × 300 mm column prepacked with BioGel A15m resin (Bio-Rad, Hercules, California, United States) previously equilibrated with buffer A at 4°C. Extracts were mock-depleted, Mre11-depleted, or Mre11-depleted supplemented with 500 nM MRN or with 500 nM MRN-ATLD1/2. Control extracts were treated with 500 nM MRN and 100 μM TPEN or 5 mM caffeine or 1 mg/ml proteinase K at 37°C. After the samples were loaded, 15 ml of buffer A (100 mM KCl, 40 mM HEPES [pH 8.0], 0.05% Tween-20, 10 mM MgCl 2 , 1 mM ATP, 1 mM DTT, 1 mM NaF, 1 mM Na 3 VO 4 leupeptin, pepstatin, and aprotinin protease inhibitors) were gently applied to the column. We collected 31 fractions of approximately 300 μl, and radioactivity was measured in a scintillation counter. For the elution profile of the circular plasmid in control extracts, a 1.8 kb plasmid derived form pUC19 with the SspI–SapI region deleted ( Ristic et al. 2001 ) was used. Nicked plasmid was isolated and labeled by nick translation in the presence of α- 32 P-dCTP, ligated, and incubated in extracts. After the fractions were collected, radioactivity was counted in a scintillation counter. Precipitation of DNA fragments bound to Mre11 We incubated 200 μl of control, Mre11-depleted, or Mre11-depleted extract supplemented with Mre11 precipitated from the extract with 50 ng/μl of 32 P-labeled 1 kb DNA fragments. Samples were applied to the BioGel A15m sizing column and fractions were collected. Void volume peak fraction 10 and included volume peak fraction 25 were incubated with 50 μl of specific polyclonal antibodies against Mre11 prebound to protein A–Sepharose beads or beads alone overnight at 4°C . Beads were washed with buffer A, and radioactivity was counted in a scintillation counter. Biotinylated DNA pulldown We incubated 200 μl of control, Mre11-depleted, or Mre11-depleted extract supplemented with 500 nM MRN with 50 ng/μl 32 P-labeled 1 kb DNA fragments and 50 ng/μl biotinylated 1 kb fragments for 2 h at 22°C. Samples were applied to the BioGel A15m sizing column, and fractions were collected. Void volume peak fraction 10 and included volume peak fraction 25 were incubated with kilobase-BINDER dynabeads (Dynal Biotech, Oslo, Norway) or mock protein A dynabeads (Dynal Biotech), and DNA fragments were isolated according to the kit protocol. Biotinylated DNA fragments bound to beads were washed with buffer A, and radioactivity was counted in a scintillation counter. Recombinant Mre11/Rad50/Nbs1Proteins Human MRN and MRN-ATLD1/2 were purified from baculovirus-infected cells according to published protocols ( Paull and Gellert 1998 ). The recombinant trimeric complex was used at a concentration of 500 nM, unless otherwise specified. X- Mre11 complex depletion/Ku depletion For X-Mre11 complex depletion, 50 μl of interphase extract was incubated with 25 μl of protein A–Sepharose beads coupled with 50 μl of preimmune serum or with 50 μl of X-Mre11 antiserum for 60 min at 4°C. For Ku70/80 depletion, 50 μl of interphase extract was incubated with 25 μl of protein A–Sepharose beads coupled to 50 μl of Ku antiserum (Covance, Princeton, New Jersey, United States) for 60 min at 4°C. TUNEL assay TUNEL assay was performed according to Costanzo et al. (2001 ). Western blot We incubated 2 μl samples of interphase egg extracts for 30 min at 22°C with 50 ng/μl DNA fragments, DNA fragments and 5 mM caffeine, or with 50 ng/μl circular plasmid, and 2 μl samples were recovered from the BioGel A15m column and precipitated with 9% PEG (see Figure 3 A) were diluted in loading buffer, boiled for 3 min, electrophoresed on 6% or 10% SDS-PAGE, transferred to nitrocellulose, and probed with polyclonal antibodies specific for Xenopus ATM, Xenopus ATR, Xenopus Mre11, phosphoserine 1,981 of human ATM (Rockland Immunochemicals, Gilbertsville, Pennsylvania, United States), and phosphorylated ATM/ATR SQ substrates (New England Biolabs, Beverly, Massachusetts, United States).	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC406388.xml
509246	Patients' perspectives on taking warfarin: qualitative study in family practice	Background Despite the well-documented benefits of using warfarin to prevent stroke, physicians remain reluctant to initiate therapy, and especially so with the elderly owing to the higher risk of hemorrhage. Prior research suggests that patients are more accepting of the risk of bleeding than are physicians, although there have been few qualitative studies. The aim of this study was to employ qualitative methods to investigate the experience and perspective of individuals taking warfarin. Methods We conducted face-to-face interviews with 21 older patients (12 male, 9 female) who had been taking warfarin for a minimum of six months. Participants were patients at a family practice clinic situated in a large, tertiary care teaching hospital. We used a semistructured interview guide with four main thematic areas: decision-making, knowledge/education, impact, and satisfaction. Data were analysed according to the principles of content analysis. Results and Discussion Participants tended to have minimal input into the decision to initiate warfarin therapy, instead relying in great part on physicians' expertise. There appeared to be low retention of information received regarding the therapy; half the patients in our sample possessed only a superficial level of understanding of the risks and benefits. This notwithstanding, participants reported a high level of satisfaction with the care provided and a low level of impact on their day-to-day lives. Conclusions Minimal patient involvement in the initial decision and modest knowledge did not appear to diminish satisfaction with warfarin management. At the same time, care providers exert a tremendous influence on the initiation of warfarin therapy and should strive to incorporate patient preferences and expectations into the decision-making process.	Background Warfarin therapy is an effective anticoagulant indicated for the prophylaxis and/or treatment of venous thrombosis and atrial fibrillation (AF), the most common cardiac arrhythmia in older individuals [ 1 ]. Oral anticoagulation with warfarin is known to reduce the risk of disabling stroke; indeed, the benefits of oral anticoagulation have been demonstrated in a number of systematic reviews, providing high evidential support for prophylaxis [ 2 , 3 ]. Published guidelines on the management of AF emphasize the importance of warfarin therapy for the prevention of stroke [ 4 ]. Likewise, there is convincing evidence that long-term warfarin therapy is a highly effective method of preventing recurrent venous thromboembolism [ 5 ]. Despite the strong evidence base and the endorsement of warfarin therapy by authoritative guidelines, current prescribing patterns of warfarin remain something of a puzzle. Bungard and associates have described the 'real world' use of warfarin therapy as "sub-optimal" [ 6 ] and have estimated that only 15% to 44% of patients eligible for anticoagulation are actually prescribed warfarin [ 7 ]. Hart concurs that the use of warfarin is poor, noting that "it is often given to patients who benefit minimally, while those patients who would benefit most are not treated" [ 8 ]. Bungard and his colleagues recently conducted a systematic review of the reasons for the underuse of warfarin, identifying patient, provider, and system factors as well as identifying limitations in research studies and arguing for further research into these factors [ 6 ]. Studies employing trade-off methods to determine the risk/benefits threshold where therapy becomes acceptable have demonstrated that patients are more willing to assume risk when better informed about the medication [ 9 ]. Physicians, however, are reluctant to prescribe warfarin to elderly patients owing to concerns regarding compliance, a perceived risk of falls, and the lack of randomized controlled trial evidence in this patient population [ 7 ]. A recent study reporting the findings of interviews with individuals with a history of AF indicated that patients' health beliefs and attitudes toward death play an important role in their decision-making [ 10 ]. Clearly, the decision to initiate warfarin therapy is a complex interaction of many variables, involving patient, provider, and system factors. Most studies examining anticoagulation practices in primary care have used surveys or other forms of quantitative methods; however, given the inherent complexity of this subject matter, it is likely that qualitative research methods could provide significant additional insight. A comprehensive literature search failed to find a qualitative investigation of patient perspectives and experiences taking warfarin. The aim of this study, therefore, was to employ qualitative methods to examine the experience and perspective of individuals on long-term warfarin therapy for atrial fibrillation as a means to assess the extent to which the physician-identified barriers reported by Bungard [ 6 ] are in concordance with the unique views of patients. Methods Participants and setting This research was undertaken in a family practice clinic situated in a large, tertiary care teaching hospital. The clinic employs 12 physician full-time equivalents working in three teams; each four-physician team is supported by two registered nurses. The practice, which serves a medium-high socioeconomic status population, has a large proportion of elderly patients and the prevalence of AF is higher than reported elsewhere [ 1 ]. The prevalence of atrial fibrillation in our population as a whole is 3.9 percent. When considering different age groups, the prevalence rises as high as 18.2 percent and 18.5 percent for patients aged 80–89 and 90–99 years, respectively. A recent chart audit study found that the majority of eligible AF patients in the clinic (78%) are being treated with warfarin for stroke prevention [ 11 ]. Comprehensive anticoagulation services are provided and the clinic offers access to physicians on-call 24 hours a day. The nurses maintain an historical record of International Normalized Ratio (INR) results and warfarin dosage changes for each individual patient and, in consultation with the physicians, inform patients of prescribed warfarin dosage changes in a timely fashion, usually on the same day as the INR reading. Potential participants were identified by the clinic nursing staff. The inclusion criteria stated that the patient must currently be on warfarin therapy and have been so for a minimum period of six consecutive months. Patients were excluded from the study if a significant co-morbidity prevented their participation, if they were unable to converse in English, or if they were unwilling/unable to provide informed consent. From a pool of approximately 60 eligible candidates, the nurses purposively sampled in order to achieve an even gender split as well as an equivalent number of patients who were both normally in-range and out-of-range on their INR tests. A total of 24 patients were invited to participate in the study. Three patients declined to take part, two of whom expected to be unavailable during the interview phase, whereas the third declined due to lack of interest. All participants signed informed consent forms in advance of their participation in the study, which was approved by the Research Ethics Board of the host institution. A demographic profile of the sample is presented in Table 1 . The mean age of participants was 74 years; there were 12 males, 9 females. The majority were both married (86%) and retired (86%). The mean length of time participants had been on warfarin therapy was 4.6 years (range = 1 year to 10 years). Table 1 Demographic profile of participants Code Age (years) Sex Marital Status Employment Status Years on Warfarin INR in Range? P1 67 F Widowed Retired 5 Yes P2 73 M Married Retired 10 Yes P3 84 M Widowed Retired 5 Yes P4 83 F Married Retired 4 No P5 81 F Married Retired 1 Yes P6 76 F Married Retired 3 Yes P7 75 M Divorced Retired 2 No P8 60 M Married Working 3 No P9 79 F Married Retired 5 No P10 67 F Married Retired 2 No P11 76 M Married Retired 5 No P12 80 M Married Retired 2 No P13 53 M Married Working 8 No P14 71 M Married Retired 3 Yes P15 69 M Married Retired 4 Yes P16 77 F Married Retired 5 Yes P17 78 M Married Retired 1 No P18 80 M Married Retired 10 Yes P19 71 M Married Working 7 No P20 71 F Married Retired 6 No P21 82 F Married Retired 5 Yes Data collection and analysis We utilized a semi-structured interview guide that was developed on the basis of salient issues identified in the scientific literature, specifically the various barriers to the prescription of warfarin for atrial fibrillation as reported by Bungard et al [ 6 ]. Interviewees were asked to share their experiences with warfarin in relation to four specific content areas or themes: decision-making, knowledge and education, impact on daily life, and patient satisfaction. Throughout the course of the interview, participants were provided several opportunities to raise issues or to describe experiences that had not been specifically addressed. Standard demographic information was also collected. Three of the authors (GCD, JM, and BT) shared the task of conducting the interviews. The protocol for assignment of each individual participant to an interviewing author ensured that there had been no previous clinical contact between the two parties; moreover, interviewers were blind to interviewees' INR status. The interviews lasted an average of 45 minutes and took place either in the clinic (n = 13) or in participants' homes (n = 8), in accordance with each participant's preference. Data collection ceased when, in the consensus of the research team, saturation had been reached; that is, no new ideas or perspectives were emerging. All interviews were audiotaped and transcribed verbatim. Given the pre-determined nature of the themes, as described above, we employed a content analysis approach to the analysis of the interview data. Whereas grounded theory is used to develop data-induced themes or hypotheses, content analysis is the better-suited approach in those instances where the codes, categories, or themes of interest to the investigators have been previously discovered and described [ 12 ], as is the case in the present study. Precise criteria were developed for each of the four pre-determined themes in the codebook, namely decision-making, knowledge/education, impact on daily life, and patient satisfaction. The 21 transcripts were then coded according to these criteria. Each transcript was coded by at least two members of the research team using a standardized coding form. Tests for inter-coder reliability indicated a high level of agreement among the coders; instances of disagreement were resolved through a process of discussion and negotiation that included both the fourth author and the principal investigator (CST & REGU). This process yielded a unit-by-variable matrix that allowed for substantive analysis of the data. In order to strengthen the validity of the findings, the analytic processes of coding and interpretation were reviewed by an independent external reader (DG). Results Decision-making The great majority of participants reported that the decision to initiate warfarin therapy had been made by "the doctor" – a term that was used to refer not only to family physicians and general practitioners, but also to specialists and attending physicians in urgent care settings. Typically, there was little or no patient involvement in the decision-making process (Table 2A ). In most cases, this unilateral decision-making appeared to be related to the high level of trust that patients place in the medical expertise of physicians; indeed, the phrase "doctor knows best" was commonly-used in these accounts (Table 2B ). For a smaller number of participants, the specific circumstances surrounding the initial decision to commence therapy served to preclude any degree of significant involvement on their part (Table 2C ). Table 2 Quotations: Decision-making A. Minimal patient involvement My decision [to take warfarin]? It was the doctor's decision. (P5) I had nothing to say [regarding decision to initiate warfarin]. If the doctor tells me something, I do it. (P17) Q: What influenced your decision to take the drug? A: Well, because I was told to. Q: The main reason is that it was the physician's recommendation? A: Yes. (P20) I don't recall him [the physician] saying anything much. He said a lot of things when he examined me first, and he put me up in the ward overnight, then he started with the medications. That's all there was to it...Not really, no [no much discussion on reasons to start warfarin]. He just said that, " This is what medication we're going to put you on for the myopathy." That was it. (P11) B. Trust of physicians I just figured the doctor knows best... (P1) A: No [trouble to decide to take warfarin], because I knew nothing about it. My doctor, as far as I know, is very competent so... Q: So you are taking it basically because the doctor told you to? A: That's right. (P6) I'm at this hospital and it's got a very good reputation... Doctor knows best, I guess. They know exactly what you have to do for it, and they did it. (P14) I can recall that I had no objection. I said, " You are the experts, you are the doctors. If I get any help, I mostly will appreciate it .".... I don't think I would trust myself that much [to make the right decision]. (P15) C. Constraining effect of circumstances When I went into the [clinic] to see my doctor, they admitted me to the cardiac emergency, and they kept me there all day ... I was in for just about a week. ... and when I was discharged the doctors explained that they were putting me on to certain medications, and Coumadin was one of them. (P10) I had congestive heart failure, that's what I was in hospital for. I don't know what I was on when I was in hospital, but when I came out I had a whole slew of medications and Coumadin was one of them. (P5) I had lymphoma, and then I had a bone marrow transplant for lymphoma, and I had my spleen taken out, and I started getting deep vein thrombosis. Then I had a pulmonary embolism at one point and they started me on it [warfarin] then... I had just about every complication in the book, and this [thrombosis] was one of them. I think it was around that time, or within a year after the thromboses started, they gave me warfarin. (P13) The surgeon said I had to take it, basically. I don't like taking pills, so when I went in to get my one valve replaced, they gave me – they persuaded me – and I agreed to trying out something new that had just been approved. The reason for doing that was that I would not have to take Coumadin... Unfortunately, however, one of my other valves blew when I was in there [during surgery], so I got two for the price of one, and then there was no question I had to go on a blood thinner. (P19) Knowledge and education The level of knowledge and understanding of the benefits and risks associated with warfarin therapy tended to vary with age. Elderly patients (aged 75+) demonstrated poorer knowledge than their younger counterparts; indeed, the knowledge level among older participants appeared to be quite superficial and scattered (Table 3A ). Whereas elderly patients could not explain with any degree of exactitude the rationale for taking warfarin and the associated risks, for a subset of participants, most of whom were less than 75 years old, the knowledge level was higher and, for a small number, considerably higher (Table 3B ). Overall, less than half of our sample was able to name one specific benefit, risk, and lifestyle change/concern associated with warfarin therapy. Table 3 Quotations: Knowledge and education A. Superficial level of knowledge I don't really know what these different pills do for me. (P3) I'm assuming these people know what they're doing. They're not doing this for nothing. They must have good reasons, and they tell me, " Hang on there, you're doing all right. Keep it up. " So I do. I don't question them. Very little, if any. I probably wouldn't know what they were talking about if they started to explain it all, and what's the point of that? (P12) Q: What do you think Coumadin is doing for you and your health? A: It makes the blood sticky, I believe, or thins it. I really don't know. Q: Do you know why they added the Coumadin? A: No idea. Q: It doesn't much matter to you? A: It doesn't matter to me. Q: Everyone's different. Some people like to know all the details. A: Oh, I couldn't care less, just as long as it keeps me alive. (P17) I hope it's [warfarin] keeping everything under control... Well, the stroke that I had, I don't feel sick, I don't have any pain, or anything. (P21) B. Superior knowledge of risks and benefits A 72-year-old male has a 30 percent chance of having a stroke regardless, but if I didn't take the Coumadin, it would be a 70 percent chance of having one. So I'm taking medication to avoid the stroke. (P14) Nobody really explained to me in full what Coumadin is all about, but I did some reading about it. I know it's a blood thinner, an anti-coagulant... helps with the atrial fibrillation that I have, because apparently blood stays longer than it should in the atrium, and if it thickens it can go to your brain and you can have a stroke. (P8) C. Patient education Q: When you started on the Coumadin, did you receive any education about the medication? A: Just that the doctor said to me that it's not 100 %, like anything else, but there's less chance [of stroke]. (P16) I said to the nurses once, " Supposing I stop taking it." They said, " Oh, I wouldn't advise it, you know, because within a month, you'd have the most severe stroke, or it would kill you, one or the other." That scared me. (P3) Q: Do you remember if you received any educational material about Coumadin? A: No. Q: Or any talk about how it works, the benefits? A: Not that I can remember. I cannot recall that, no. Q: Any pamphlets, any coloured paper, anything? A: No. Q: You don't recall? A: If I did have, I read it, then I dismissed it... I have an appetite, I can eat and drink, I can sleep, and I still can work. Anything else, to me, is not quite important. It's probably wrong. I should read them and pay more attention. (P15) Then he [physician] said, " If you go off the Coumadin for your operation, you could get a stroke. You've got a choice: you can either go off the Coumadin or you can stay on it and bleed to death." Not to death, he didn't say that. You'd bleed. The other way, you could have a stroke. That's all he said. So I presume that it could happen. (P9) Q: Is there any sort of educational material that you would like to see on warfarin? A: No. I've got a pile of books to read now, and as soon as I start to read, I fall asleep. The pamphlets would fare worse than the books. I don't think that would help. (P12) Q: Did you have many questions about it at the time [when warfarin was initiated]? A: No. You see, the darn trouble was that my wife would be sitting there, and I'd say, " She knows what it's all about; tell her." ... When you have a sit-in nurse, you know, I don't worry about that stuff [getting education on the therapy]. (P3) According to participants' accounts, educational efforts aimed at informing patients about warfarin were minimal and insufficient (Table 3C ). Those who were able to recall some form of education typically referred to a "booklet" or "sheet" supplied by either the clinic or a pharmacy. In several cases, spouses were more knowledgeable than patients and appeared to play an important role in monitoring the regime. A number of participants lauded the availability of clinic staff to answer questions; however, two others reported the use of "scare tactics" by health care professionals with regard to the need to take warfarin. Impact of warfarin regime While there is tremendous range in the perceived impact of warfarin therapy on the lives of these patients, the vast majority reported that they have not experienced complications (e.g., hemorrhage, drug interactions). Typically, the decision to start taking warfarin did not precipitate significant changes in their day-to-day lives; many participants reported experiencing only minor inconveniences (Table 4A ). For these individuals, warfarin is just another pill to be taken everyday; many reported the use of some reminder strategy, such as calendars, dosettes (pill boxes), or taking the pill right before some regular activity, in order to avoid missing a dose. On the other hand, a sizeable proportion (25%) of interviewees reported that adhering to the warfarin regime does impact upon their day-to-day lives. From the perspective of these patients, who were more likely to have multiple co-morbid illnesses and/or were taking multiple medications, the warfarin regime presents a considerable struggle to be managed, particularly when dosages needed to be adjusted. Regular visits to the clinic, restrictions on diet and alcohol intake, and anxiety regarding bleeding and potential drug interactions counted among the most commonly cited impacts (Table 4B ). Only a small number of participants reported experiencing significant complications related to the warfarin regime, with one case involving repeated gastro-intestinal bleeding. These patients demonstrated a very high level of commitment towards their warfarin management and have placed the ritual of taking the medication at the centre of their daily routine (Table 4C ). Table 4 Quotations: Impact of warfarin regime A. Minor impact Coumadin, it's just a matter of taking the pills each day and coming for a blood test and adjusting the dose. That's all. No other impact, as far as I'm concerned. (P13) I had the test [INR] done before I went to Europe. I arranged it so that two days before we flew to Europe, I had it tested, and it was 2.3, I think... The nurse said: " You might keep it this same way, and enjoy. " And as soon as I got back, I came in and had it checked. (P15) It's inconvenient having to come in every week, but on the other hand, I understand. (P20) B. Moderate impact I will only drink one glass of wine a day. I like a glass of wine. They say just go easy on the single malt, and stuff like that...There wasn't any special [instructions regarding diet]. We like good food, and we eat a good, balanced diet. I like seafood, and I love fish, and I like the odd steak. I try to stay off butter. I'm taking Becel ® just now, which I don't really like, but I try to stay off the butter and cooking with all the white sauce, and butter sauce, and stuff like that. (P10) I come here every 4 or 5 weeks to have the bloodwork done for Coumadin. Whenever I have this done, the nurse calls me that afternoon and says, "S tay on with the same milligrams" or " Change to that and that." But I feel fine [with this routine]... The only disadvantage of the Coumadin is the bruising and bleeding on just the slightest touch... but if that's the worst that happens, I'm not worrying about it. (P11) I'm extremely careful with my alcohol intake, although as I said before, I'm not an everyday drinker. Other than that, the only other thing is I started noticing I have experienced some hair loss. (P8) C. Major impact Three years ago, I had two very serious stomach bleeds and I do not know, to this day, whether I should attribute it to Coumadin. Once I spent a couple of days in intensive care and then three months later, again a couple more days, this time in critical care. (P11) It isn't worth it to risk a stroke by going off the Coumadin to have the hernia fixed. So Coumadin has played a major part in my life, because this hernia is a daily fact I have to live with... The fact that I'm taking Coumadin means that if I want to be operated on, I have to be careful... They [the Hernia Clinic] don't take guys like me that require a bit of time and skill and more facilities than they have. But what do guys like me do? (P14) The thing is, the last 558 times I've taken it, which is right here [referring to the records he keeps], I went through this last night, and I found only three miscues the entire time I've been taking it. That works out to 0.005 percent. It's a very, very low percentage of goofing taking it. I've never forgotten. For at least two of these incidents, I took it at 10:00 or 10:45, instead of at 6:00. That's four hours late. I consider that a goof. Another time I took it in the morning instead of at night, which is a goof. (P14) Patient satisfaction The vast majority of interviewees reported a high level of satisfaction with the care they receive from the nurses and physicians in the clinic (Table 5A ). Most participants were also satisfied with the warfarin regime itself (Table 5B ). Only a very small number of participants expressed significant dissatisfaction. The sources of dissatisfaction, which tended to be highly localized to specific concerns, included the cost and inconvenience of attending the clinic for regular INR tests, a lack of information provided to patients, and insufficient awareness of patient history on the part of clinic staff (Table 5C ). Table 5 Quotations: Patient satisfaction A. Satisfaction with clinic staff Oh, I am more than pleased. I'm absolutely more than pleased. I think they're wonderful. The nurses are wonderful – you know, taking my blood, and phoning me, and giving me instructions. (P1) I think they've been 100 percent. From my cardiologist to the family physician and to the pharmacists, because they're just amazing. (P10) My doctor thought my blood was, I guess, too thick. They did an INR and recommended the Coumadin, which I didn't want to get on, because I knew it was warfarin and you associate that with rat poisoning. Anyway, she took the time and very patiently explained what the purpose of it was, and highly recommended it. I really like her. I like everybody there. They're very caring, supportive people. They're just dear. (P4) B. Satisfaction with warfarin regime This is a pill that keeps your blood thin, and you have to check it out [INR level]. I just do as I'm told and I'm thrilled that they keep me at 2-point-something....I go every week, or every other week, or once a month, depending on my stability. It doesn't bother me going. (P1) It's worked out well [the regime]. I know it has to be done, and I'm lucky in the fact that it has regulated it. It has totally regulated itself – I'm taking 4 mg a day now. I'm only coming in once a month. (P18) Oh, yes [happy with warfarin regime]. They let me know what the status is each week, whether it's going to level out, and whether I'm going to be able to stay on the same dosage and then stop going up there every week. I started going every week, and now it's been levelled to every two weeks. (P7) I really couldn't say anything bad about it [warfarin regime]. Apparently I've been outstanding in how steady I would go with it, and I've been going – normally, for years, I've been going once a month, pretty well. A couple of times it would go up and I'd come back in two weeks, or something. (P2) C. Sources of dissatisfaction Nobody tells me anything. That's one of my problems with this whole bloody business. Nobody tells me how I'm doing. All I know is that I'm supposed to be between 2 and 3 [INR levels]. (P7) I just more or less come when I'm ordered to. From home it's almost an hour on the bus each way, and the parking around here, the cost is wild. They must be financing the place with the parking. No, I would prefer not to come at all. I would prefer to forget the whole deal, but that doesn't seem to be in the offing at the moment. (P12) I haven't been coming here that long, about two years I think... but I wouldn't say they're fully aware of my history and really understand the depth of it... Considering my history, I think they should know more. They certainly don't have my files. (P13) Discussion The findings of this study provide significant and original insight into the perception and experience of patients taking warfarin. The data indicate that patients tend to have minimal input into the decision to initiate warfarin therapy; many have only a superficial level of understanding of the risks and benefits of warfarin; and the majority retain little from the education they received regarding warfarin therapy. This outcome is balanced, however, by the finding that for these patients there was both a high level of satisfaction with the care provided in the family practice setting and a low level of impact on their day-to-day lives. The principal strength of this study is the insight into the lived experience of warfarin therapy as gleaned from the unique perspective of family practice patients currently taking warfarin. We view this as a significant and novel contribution to the literature as we could find no other such study. It is important to note, however, that our sample was drawn from the patient population of an academic primary care practice that is both well-educated and of medium-high socioeconomic status. The applicability of these findings in other patient populations may therefore be limited. Interviewees revealed clear detachment from participation in the decision-making process around initiating warfarin therapy. In some cases, this detachment appeared to stem from the particular circumstances at the time; for instance, if the patient was involved in a medical emergency or was admitted to hospital and had several medications initiated. For others, there was a general belief or understanding that warfarin is a medication without which the patient faced imminent risk of death – it is therefore not a matter to be discussed or negotiated. This finding may be a function of the age of our participants. As a group, elderly patients tend to prefer a directed rather than shared consultation. Prior research indicates that seniors are more likely to be accepting of medical advice without much questioning, rather than assuming a more active role in the decision-making process [ 13 ]. This attitude was reflected in participants' comments that "doctor know best" and "it's the doctor's decision." Patient knowledge of risks, benefits, and issues related to diet and alcohol intake was low, although younger patients demonstrated greater levels of understanding than did those over age 75. This finding is consistent with previous investigations. Lip and colleagues have detected lower levels of knowledge among elderly patients; moreover, longer duration of anticoagulation does not appear to ameliorate patient understanding significantly [ 14 , 15 ]. For the most part, we found that retention of instructions pertaining to the warfarin regime was poor. Many participants reported that they simply follow the nurses' directions and have little interest in learning anything more. The limited knowledge and seemingly low level of interest to learn more could be attributable to the great deal of trust invested in the expertise of the clinic staff as discussed above. The fact that several spouses exhibited greater understanding of the risks and benefits associated with warfarin therapy has implications for educational interventions recognizing the importance of the spousal or care giver role in the monitoring of therapy. With regard to the impact of warfarin therapy on daily life, our results indicate that warfarin is for the most part well tolerated and does not pose heavy additional burdens or lifestyle changes. The majority of participants were already taking several medications and visiting more than one doctor on a regular basis. This sample also had a low incidence of complications and previous studies have shown that the potential for complication does not on its own result in a significant impact [ 16 , 17 ]. That is, the mere possibility of an adverse side-effect does not bring about substantial anxiety unless the complication is actually experienced. These results do not, however, capture the experiences of individuals who have tried and ceased taking warfarin for whatever reasons. This population represents a high priority for future study. Additional support may be required for individuals with multiple medical problems. Continuity of care and a strong relationship and identification with the primary care team that provides anticoagulation services can overcome potential miscommunication and misunderstanding regarding side effects and drug interaction. The importance of the association between patient satisfaction and adherence has been established in prior research on anticoagulation. In a case-control study, Arnsten and colleagues [ 18 ] found that, among patients with a regular physician, the non-adherent cases were those who expressed dissatisfaction. In our sample, the level of patient satisfaction was high, both with the clinic staff and the warfarin regime itself. Based on participants' testimonies, the coordination and continuity of care by a trustworthy team of doctors and nurses were key contributing factors to the high satisfaction ratings. In an evaluation of a telephone-based anticoagulation service, Waterman found that patient satisfaction with warfarin management was associated with the timeliness of receiving blood test results from the service provider [ 19 ]. The high level of patient satisfaction observed in the present study may also be due in part to the low rate of complications (e.g., hemorrhage, drug interactions), which may serve to reinforce patients' trust both in the therapy and in the health care team. Increasingly, theoretical models of the physician-patient encounter advocate the inclusion of patients in the decision-making process [ 20 ]. Of course, shared decision-making presupposes an understanding of the benefits and risks on the part of patients. With regard to warfarin therapy, patient preferences would be expected to vary according to expected benefits or awareness of risks of suffering a stroke. Man-Son-Hing et al have demonstrated that the minimal clinically important difference of warfarin therapy is often considerably smaller for patients than that identified by clinicians [ 21 ]. Protheroe and colleagues, in an observational study of patient-based decision analysis, noted marked disagreement between patient preferences and guideline recommendations [ 22 ]. A patient decision aid was shown to improve knowledge and understanding of the risks and benefits of warfarin for patients with atrial fibrillation, and aided in therapeutic choice [ 23 ]. Given the low level of patient knowledge observed in the present study and elsewhere, the vision of shared decision-making [ 24 ] remains an as yet unachieved, but laudable goal; indeed, the present results highlight the challenges of shared decision-making and increased autonomy in patients with complex chronic diseases. Conclusions In summary, the results of this study suggest that patients tend to have limited input into the decision to initiate warfarin therapy. Moreover, a majority appear to lack a comprehensive understanding of the risks and benefits associated with treatment. These findings, however, were balanced by the minimal impact of warfarin on daily life and the high level of patient satisfaction. Further research is required to assess whether these findings are similar in other patient groups, with different demographic and socioeconomic characteristics, including multi-cultural communities [ 14 ]. Investigation of physician views of the underutilization of warfarin therapy would allow for a comparison of the patient and provider perspectives. Clearly, there is a pressing need for innovative methods of continuing patient education in order to communicate the risks and benefits of warfarin therapy in a friendly, non-threatening manner. Also, these results highlight the tremendous influence that care providers exert on the decision-making of patients. The development of decision aids for anticoagulation may help patients make more informed decisions [ 23 , 25 ], but only if care providers know of their existence and take the time to use them, assuming that such tools are feasible in a busy clinical setting. Competing interests None declared. Author's contributions REGU conceived and initiated the study and will act as guarantor. GCD, JM, and BT conducted the interviews. CST co-ordinated the data analysis process. All authors participated in the analysis of the data and the writing of successive drafts of the manuscript and all have read and approved the final draft. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC509246.xml
514565	A simulation model of African Anopheles ecology and population dynamics for the analysis of malaria transmission	Background Malaria is one of the oldest and deadliest infectious diseases in humans. Many mathematical models of malaria have been developed during the past century, and applied to potential interventions. However, malaria remains uncontrolled and is increasing in many areas, as are vector and parasite resistance to insecticides and drugs. Methods This study presents a simulation model of African malaria vectors. This individual-based model incorporates current knowledge of the mechanisms underlying Anopheles population dynamics and their relations to the environment. One of its main strengths is that it is based on both biological and environmental variables. Results The model made it possible to structure existing knowledge, assembled in a comprehensive review of the literature, and also pointed out important aspects of basic Anopheles biology about which knowledge is lacking. One simulation showed several patterns similar to those seen in the field, and made it possible to examine different analyses and hypotheses for these patterns; sensitivity analyses on temperature, moisture, predation and preliminary investigations of nutrient competition were also conducted. Conclusions Although based on some mathematical formulae and parameters, this new tool has been developed in order to be as explicit as possible, transparent in use, close to reality and amenable to direct use by field workers. It allows a better understanding of the mechanisms underlying Anopheles population dynamics in general and also a better understanding of the dynamics in specific local geographic environments. It points out many important areas for new investigations that will be critical to effective, efficient, sustainable interventions.	Background Not so long ago, in 1998, Sherman declared: "Of all the human afflictions, the greatest toll has been exacted by malaria. Even today, malaria, which is caused by protozoan parasites of the genus Plasmodium , disables and kills more people than any other infectious disease." [ 1 ] In line with the pioneering models of Ross (1911) and Macdonald (1957), malaria interventions such as breeding-site reduction and insecticide use have been considered the most effective and practical ones for reducing malaria transmission. Bednets and house screening serve as personal protection, and bednet-associated effects on malaria prevalence appear to be greater than can be accounted for by personal protection [ 2 ]. These interventions have produced good results, but in much of the world malaria remains uncontrolled. Furthermore, malaria vectors are increasingly developing insecticide resistance. At every level of research, policy and practice, malaria control can be helped by models that are both more comprehensive and closer to the day-to-day realities of malaria (K. Dietz in [ 3 ]). As Bradley (1982) has pointed out, "for real progress, the mathematical modeller, as well as the epidemiologist, must have mud on his boots." The aim of this study is to provide a framework and a tool for modelers to work closely with field workers in malariology, particularly entomologists. The study also aims to achieve a broader analysis and deeper understanding of the complex mechanisms involved in malaria transmission, in order to aid intervention programs. The idea of controlling malaria through the introduction of genetically modified mosquitoes is gaining increasing attention, for instance, but will first need to be tested critically, in trials that will necessarily involve models. Thus the work presented below represents only a beginning, and it has two major aims. First, it introduces an approach to help researchers account for ecological variables that are key determinants of malaria vector population dynamics. When fully calibrated, this approach will provide an integrated platform for hypothesis testing with complex temporal and spatial data; ultimately, it should help by providing forecasting capabilities. Of perhaps even greater importance, this first model provides a vehicle for assembling and structuring existing knowledge, thereby pointing out critical areas in which knowledge is lacking and very much needed. Thus it is a means of identifying and organizing important research priorities and indicating their epidemiological implications. One of the most important strengths of this model is to combine biological and environmental variables. As stated by [ 4 ], the combination of intrinsic and extrinsic determinants of mosquito-borne disease incidence should be the focus of future research. This is critical both in controlling these diseases and reducing the severity of epidemics by predicting them. Approximately 70 species of Anopheles have been implicated in malaria transmission worldwide. In Africa the major vectors are Anopheles gambiae sensu lato, which is considered the most important in most regions, Anopheles arabiensis , which is part of the preceding complex but with distinct characteristics, and Anopheles funestus , which is often reported as the second most important species in terms of malaria transmission and, more particularly, is considered the end-of-rainy-season vector that sustains the parasite. This work focuses on the major vector in sub-Saharan Africa An. gambiae , but much of what follows may be applicable to An. arabiensis , and even to An. funestus separately and all together, with inter-as well as intra-species competition. This paper describes the first model of malaria vector population dynamics integrating both biological and environmental factors. Methods The model incorporates basic biological requirements for Anopheles development on an individual basis and, using local environmental data as input, allows the simulation of the aggregate dynamics of Anopheles populations. The life cycle of each individual proceeds through four stages: three immature stages, which occur in a water body – egg, larva, pupa – and then the mature stage, a flying adult. An adult female disperses from the natal water body and begins a cycle which is maintained throughout the rest of life-alternating between obtaining a bloodmeal and ovipositing in a water body. Five major factors are considered here as characterizing Anopheles population dynamics, by means of mechanisms detailed below (see figure 1 for a schematic): Temperature is a critical regulator of growth and development within each stage, in determining the end of one stage and the beginning of the next and in regulating the length of the gonotrophic cyle. Moisture , in the form of precipitation and relative humidity, is a second key abiotic factor, with effects that in part interact with those of temperature. Nutrient competition is a major potential regulator which is considered to induce mortality in the larval stage. In addition, there is a minimum weight requirement for the transition from larva to pupa, and, through its influence on adult weight, the relation of larval weight to fecundity. Predation and Disease , in which pathogens are included, is a second important mortality-inducing factor, which is considered in local terms relative to the water body. Dispersal , or the adult female's movement in space, is a critical factor in the cycle of seeking blood meals and oviposition sites. The model explicitly represents spatial locations of individual adults, though it does not fully engage this capacity in the analyses presented here. The model is implemented as a software package in the C++ object-oriented programming language, in the Microsoft Windows 98 operating system, and is available from the corresponding author upon request. It was developed and run on a personal computer with a Pentium 3 processor 933 MHz and a relatively small memory of 256 Mb. Temperature Because malaria vectors are poikilothermic, temperature is a critical variable in malaria epidemiology. For instance, in the range of 18°C to 26°C, a change of only 1°C in temperature can change a mosquito's life span by more than a week [ 5 ]. Here, in line with the work of Focks et al. [ 6 ] on Aedes aegypti , the enzyme kinetics model derived by Sharpe and DeMichele [ 7 ] is used, based on absolute reaction rate kinetics of enzymes for the temperature-dependent developmental rates of eggs, larvae and pupae and the duration of the gonotrophic cycle, in the simplified form derived by Schoofield et al. [ 8 ]. This equation is derived on the basic assumption that poikilotherm development is regulated by a single control enzyme whose reaction rate determines the development rate of the organism [ 7 , 8 ]. This is of special interest because each parameter of the equation has a biological significance that may have an epidemiologic impact. At time step t n of t 0 , t 1 , ..., t n , the development within each of the four stages, during the time step Δt k = t k - t k -1 , is defined by: d k = r ( T tk )· Δt k . (1) is the mean temperature (°K) over the time interval k and r ( ) the developmental rate per hour at temperature T (°K), given by the following equation: where ρ 25° C is the development rate per hour at 25°C, under the assumption that there is no temperature inactivation of the critical enzyme; is the enthalpy of activation of the reaction catalyzed by the enzyme ( cal·mol -1 ); ΔH L is the enthalpy change associated with low temperature inactivation of the enzyme ( cal·mol -1 ); is the temperature (°K) where 50% of the enzyme is inactivated by low temperature; ΔH H is the enthalpy change associated with high temperature inactivation of the enzyme (cal·mol -1 ); is the temperature (°K) where 50% of the enzyme is inactivated by high temperature; and R is the universal gas constant (1.987 cal·mol -1 ). The cumulative development, depending only on temperature at each time step t n , of each of the three stages (egg, larvae, pupae) and the length of the adult gonotrophic cycle is defined as: with d k defined above in equation 1. As detailed below, other factors are also considered, including a particular case for the larval stage that takes food requirements into account. Variability is allowed for in the cumulative development time, CD ( t n ), with a default value of 10% and a stage is considered completed, such that the next stage begins when: CD(t) > CD f = 1 + G (0,0.l) (4) where G is a normal random variable. A survey of the literature reveals how very little developmental-rate data is available for Anopheles , even for the most important African malaria vectors. The deficit is striking for all of the three major malaria vector species in Africa. We have fit the curve defined by equation 3 to all of the relevant published data. Those data are compiled in tables 1 and 2 , for An. gambiae sensus lato. One reference provided only the total An. gambiae development time from egg to adult [ 5 ], we have then estimated the development time for each of the three constituent stages in according with the other data, and also assumed longer development times at low temperatures. The only gonotrophic cycle data available in relation to temperature was for An. arabiensis , part of the An. gambiae complex. All three curves shown in figure 2 , for different parameters of equation 2, provide similar fits to the An. gambiae data in tables 1 and 2 . These different curves have important implications for vector population dynamics and reinforce the need for more data for these species, particularly at the temperature extremes (low and high), in order to fit an optimal curve. Until there is data for the extreme temperatures, any number of curves might fit the data. Three such curves are illustrated in figure 2 . For the purposes of this paper the middle of these three curves has been chosen, with parameters shown in table 3 . The curves for all four stages are shown in figures 3 and 4 , with parameters in table 3 . An. gambiae females are one-day old when they take their first blood meal, according to [ 9 ]. This greater length of the first gonotrophic cycle has been taken into account [ 9 ][ 10 ] by defining a coefficient U FirstGon which represents the time lag before the first blood meal expressed as a percentage of the gonotrophic cycle length. Therefore, the first gonotrophic cycle is considered completed if: CD(t) > CD f = 1 + U FirstGon + G (0,0.1) (5) U FirstGon has been set to 0.5 for An. gambiae. All subsequent gonotrophic cycles follow equation 4. Thermal mortality Although the range of variation of water temperature is very wide, it is rarely taken into account in the literature. Some authors have recorded temperatures close to 40°C in small pools [ 5 , 11 , 12 ]. Such temperatures exceed the thermal death point of many species, including An. funestus [ 5 , 12 ]; this may help to explain why these species are rarely found in small pools. Based on these observations [ 5 , 12 ], a daily mortality in the larval stage of 10%, 50% and 100% for a maximum water temperature of 1, 2 and 3°C above the thermal death point, respectively, has been considered. According to [ 5 ] the thermal death point for An. gambiae is set to 40°C. Moisture Anopheles usually develop in natural water bodies, such as puddles, pools or streams [ 11 - 14 ]. The model must take into account two critical parameters in a water body, the temperature and the volume of water. In this stage of the project it was not possible to develop a full water-balance model to estimate those parameters but it should be possible in the future. Cloud coverage is likely to be relatively important because of its impact on the water temperature, but this variable is rarely available in climate data. However, it is known that a relative humidity of 100% is usually associated with complete cloud coverage and rain and a relative humidity less than 50% with dryness and almost no clouds. Hence an estimate of cloud coverage as a function of relative humidity RH was made. A clear sky, without clouds (0), for relative humidity below 50%, linearly increases to completely cloudy (1) for relative humidity above 95%, as follows: The maximum water temperature of a water body depends on the cloud coverage and a user-defined coefficient U SunExpo that describes the water body's sun exposure. This user-defined coefficient represents the coverage or shaded percentage of the particular water body, ranging from 0 for complete shade to 1 for complete sunlight exposure. By default it is set to 1. If the maximum air temperature in degrees Celsius is T M , it is estimated that the maximum water temperature in accord with the water volume x (in liters) is , where: with C SE = U SunExpo ·CloudCover ( RH ). The minimum water temperature is taken as the minimum air temperature. The following formula estimates the daily dynamics of water height W H in a water body: where U IF is the fixed daily water intake in mm·day -1 (e.g. from a stream, pipeline, human activity, etc.); its default value is 0. U IV , the variable daily water intake in mm·day -1 is set in accord with the precipitation and the surrounding area's topology. Its default value is 1, which would apply to a water body in a flat area, such that only direct rainfall fills the water body. The user can set a particular value: for a water body on a slope, this coefficient should reflect the volume of water intake given 1 ml of precipitation in the area. P is the precipitation in mm per day, and R H is the relative humidity. U O , in mm·day -1 , is the daily loss of water due to soil infiltration and evapotranspiration. By default, this parameter is set to a mean value of 3 mm·day -1 . The water bodies are approximated by means of simple geometric objects, such as cubes and cylinders. The default geometric object is a box; its dimensions (length, width, depth) can be entered by the user. Therefore, the volume of water available in the water body is calculated from the particular shape of the water body and the water height calculated above (equation 6). Aestivation and diapause Unlike the eggs of Aedes aegypti , which, it has been shown, can survive in dry soil for more than two months [ 6 ], recent work [ 15 ] indicates that Anopheles eggs cannot survive more than 15 days on dry soil. Thus, since some African regions with endemic malaria experience drought periods longer than two months, the only plausible alternative seems to be adult aestivation. This is another aspect of Anopheles biology in which much more data is needed. The different survival probability during aestivation has been arbitrarily set as shown in table 4 . Aestivation or diapause is triggered by the non-availability of water (when water bodies are completely dry) for all stages. For the adult stage, aestivation is also triggered by a relative humidity arbitrarily chosen here at less than 40%, though even this may prove to be high in some area. Nutrient competition Some combination of regulatory mechanisms limits the size of any population of any species. The most important, for many species, can be described as density-dependent regulation, or competition for space and/or food, which is assumed to summarize or integrate complex, difficult-to-measure mechanisms, such as food mass conversion. For the sake of simplicity and practicality, the basic ecological concept of carrying capacity [ 16 ] has been used here. This concept has been applied primarily to the larval stage since it is the longest immature stage and is the only immature stage in which the mosquitoes feed and is, therefore, likely to be the most sensitive to competition. For each water body i a carrying capacity K ( i ) (in mg ) has been defined as: K ( i ) = L Max · S ( i )· U Carrying (7) where L Max is the maximum larval biomass density, defined for all species j by: where N j is the larval population size per surface unit ( m 2 ) for species j , and W j is the approximate mean weight of species , with and being the maximum and minimum possible weight in species j , respectively), divided by 2 in equation 8 to correct for the greater size of the low-weight larval population. L Max = 300 mg · m -2 has been arbitrarily set for larvae. S ( i ) is the available water surface in water body i , and U Carrying is a positive user-defined coefficient for each water body, to correct for particular water-body characteristics; by default it is set to 1. Thus, for each water body at peak season periods, the maximum larval biomass density L Max is estimated by measuring the larval population size at its maximum. Density-dependent mortality Resource competition is considered as a cause of mosquito mortality only for the larval stage. For species j [ 16 ] the natural increase of the total larval population size, N , (without mortality) can be defined by: where p is the proportion of larvae that is newly-hatched eggs, estimated by: where ΔN e ( t ) is the number of individual eggs entering the larval stage. The carrying capacity K ( i ) of a particular water body i is defined above (Equation 7). In general, the larval population increase is given by: where W ( t ) is the current larval biomass overall (in contrast to W j , the approximate mean weight of species j ; see equation 8). The larval per capita density-dependent mortality rate m for all species can be approximated by: Weight As noted above, the larval stage is the only immature stage with food intake and, therefore, with weight changes. Thus, this stage is the key determinant of the final adult weight. where and is a coefficient that describes food availability for an individual i of species j , is the maximum possible weight for species j, W ( t ) is the current larval biomass, K is the carrying capacity of the water body, and W i , j ( t ) the weight of individual i of species j at time t . For each time step k , for species j , the weight of individual i increases linearly as , where d k is the thermal development in time period k (equation 2). The weight in the larval stage is then calculated as: This formula allows the individual larva to have a maximum weight in accord with its species when the larval biomass W << K . At the other extreme the weight increase will be almost zero if W ≈ K . Note that this formula allows both intra-and inter-species competition for food. From [ 5 , 17 - 19 ] the weight parameters for each species have been set as shown in table 5 . For the purpose of stochastic simulation variability has been allowed, again with a default value of 10%, as follows: W i , j = W i , j + G (0, 0.1) (16) where G is a normal random variable. The larval stage is regarded as completed, such that the pupa stage begins, when the thermal development CD is completed (Eq. 4) and Weight > Weight Min . The relative weight of an individual within its species is used as an important factor in subsequent subsections on fecundity and number of blood meals, in which the following coefficient is used: Predation and Disease Predators and pathogens are an important regulating factor and are sometimes reported to be the major cause of mortality [ 20 ]. Egg Little has been reported about An. gambiae egg mortality, from predation or any other cause, beyond an observation (Beier, personal observation) that up to 83% of eggs hatch after one day of drying on sandy loam soil. Without more information, the total egg mortality for each species was arbitrarily set at 5% as a fixed pre-development mortality for the overall batch and a daily survivorship of 0.99. Larvae and Pupae Service [ 20 ] points out that An. gambiae population sizes rise to a peak just after a drought period and then decrease to a roughly stationary level. Life cycles of predators on immature An. gambiae are generally longer than those of their prey, and during the latter phases predators are found in non-predatory stages (i.e. not preying on immature An. gambiae) [ 20 ]. Intensity of predation appears to be highly related to the early peak in prey, but there is still a regulatory effect even in the absence of predators. Hence, it is likely that predation is not the only major cause of mosquito mortality [ 20 ]. Service [ 20 ] evaluated immature An. gambiae sensu lato mortality from predation in two experiments, one in which predator density was high and another in which spraying had reduced predator density. His results are summarized in table 6 . With respect to pathogens and parasites, he found that 2.1% to 15.9% of An. gambiae were infected. Active predation exhibits a lag time around the mean life-cycle length of the prey [ 20 ]. During the lag period l , if t = 0 is the start of this period, a curve should show a gradual increase in predation. The conditions leading to a new predator lag period could occur, for instance, when a dry water body gains water or after a control intervention killing the predators. If (fig. 5 ): with and p = 0.001, then the total larval and pupal mortality due to predators and pathogens for species j , can be expressed as: Note that Δm j ( t ) differs from m ( t ) in equation 12, which represents density-dependent mortality. For all species j the following were arbitrarily set: = 25% for larvae and = 10% for pupae. = 25% is converted to a daily mortality rate as: where T is the individual's developmental time. Thus at t = 0, the beginning of the lag period, Δm j ( t ) ≈ 0, and at t ≥ l , for species j . On adding to the density-dependent mortality m j the mortality due to predation and pathogens Δm j ( t ), for each species j , we obtain a new equilibrium K p < K , given K in equation 11, where where N j is the larval population size for species j (N ( t ) = . Adult There are several published studies of adult mortality rates [ 9 , 21 ] for An. gambiae and An. funestus. The causal mechanisms are not clear, but some authors report adult predators preying on adult mosquitoes at oviposition sites [ 20 ]. It is assumed that predation-related adult mortality is focused at the water body and that survivorship is greater with fewer predators present. Oviposition typically occurs every two to three days (see above). Accounting for the low predation during the previously-defined predator lag time, the daily adult survival probability is taken to be 0.911 for a non-ovipositing day and 0.911 - 0.1· C Lag ( t ) for An. gambiae sensus lato. Dispersal The mechanisms governing mosquito dispersal in general remain unknown. Wind strength and direction are likely to be important factors, for instance, but relevant data are rarely reported. Very little is known about the relative attractiveness of individual humans and individual water bodies to Anopheles , but these cues, along with distance, must be key factors in dispersal. In most tropical regions, bloodmeals are taken at night, between 6:00 pm and 6:00 am. As the mosquitoes are active during the night, for simplicity bites were modelled only in houses. Bloodmeal source selection is modelled by a two-step process, first a choice of house and second a choice of individual human within the house. Anthropophily, the proportion of bites taken on humans, can be set for each Anopheles species overall; the default value of this parameter is 1. Exophily is expressed as the proportion of fed mosquitoes that leave the house during the first half of the gonotrophic cycle. For An. gambiae the default value of this parameter is 75%. The model explicitly, dynamically represents individual locations in space, but at this stage the adult female alternately chooses at random among some number of water bodies for an oviposition site, and at random among some number of houses and individuals within the chosen house, for a bloodmeal. That is, the choices do not reflect relative distance, attractiveness, wind or other features the model is designed to address in future phases of development. Multiple bloodmeals and multiple bites In addition to the greater length of the first gonotrophic cycle (Equation 5), Brengues [ 9 ] has shown that, to complete their first gonotrophic cycle, 42% of female An. gambiae and 63% of female An. funestus require a second bloodmeal one day after the first one. Here the probability of having a second bloodmeal within the first gonotrophic cycle is related to the weight of the individuals: there is a second bloodmeal when the coefficient C weight is less than 0.4 for An. gambiae. For multiparous females, there is a second bloodmeal when C weight is less than 0.1. According to [ 22 ], 14% of female An. funestus and 19% of female An. gambiae that had just fed had taken only a partial bloodmeal. These figures are used to represent the proportion of females that take a subsequent bite within what is considered the same bloodmeal. Fecundity The number of eggs oviposited by individuals shows a wide range of variation, both within and between experiments [ 17 , 18 , 23 , 24 ]. The mean number of eggs oviposited is defined by m = 100, with a standard deviation s = 50. In the absence of more precise information these values are assumed. The number of eggs oviposited is simulated as: N = G(m, s) · U Egg (21) where U Egg is a positive user-defined coefficient set to fit local observations, by default set to 1, and G is a normal random variable. Because fecundity is closely tied to body size, a variability of 50% of the number of eggs is allowed as a function of the individual's weight, as follows (see [ 18 ][ 23 ]): N ' = N ·(0.5 + 0.5· C weight ) (22) The male-female ratio at emergence from the pupa stage is assumed to be 1:1. Results A simple example is used to show how the model can help to achieve a better understanding of vector population dynamics and determine key underlying factors. In particular, the influence of temperature, moisture, predation and nutrient competition on adult abundance is investigated. The example is taken as a small cluster of six houses, each with five residents, and a total of three oviposition sites (figure 6 and table 7 . An attempt has been made to reproduce some important characteristics of a local environment by considering two types of pools: a semi-permanent pool, P1, and two temporary pools, P2 and P3 (see figure 7 and table 7 . As noted above, at this stage each mosquito in the model chooses at random among oviposition sites and among houses and residents at the appropriate points in her gonotrophic cycle. Temperature and moisture inputs were obtained based on data from Kilifi, on the coast of Kenya. Figures 8 and 9 show daily precipitation, minimum and maximum temperature and relative humidity reported there over the 20 months from May 1, 2000 to December 31, 2001. In this region there are two primary rainy seasons: April-June and October-November. Except where noted, the default values were used for parameters, as given above. Effects of temperature In the first set of simulations there are 300 eggs and 10 adults, with all six houses but only pool P1 present. Figure 10 shows the variability and mean of twenty replicates realizations of the simulation model, an effect of the stochasticity allowed in the cumulative development time (equation 4), length of initial gonotrophic cycle (equation 5) and number of eggs oviposited (equation 21). The abundance curve is predicted from the preceding environmental data, with each run started on May 1, 2000. This An. gambiae adult mean curve shows similarities to several published curves, at much wider scales [ 25 ], in that there are relatively low levels of mosquitoes throughout the year, with fluctuations in abundance that may correspond to the limitations of competition and/or predation and several very high peaks in short time intervals. To analyse the effects of temperature, two additional temperature curves were used, one in which the actual temperatures are increased by two degrees and one in which they are lowered by two degrees Celsius, the results are shown in figure 11 . Table 8 shows the impact of temperature on adult abundance. For An. gambiae (figure 11 ), with increasing temperature there is a general increase in the level and number of peaks. As detailed above in the section on Temperature (table 1 et seq.), the egg-to-adult development time is shortened with higher temperature, thus producing more mosquitoes. The two-degree temperature rise increases An. gambiae adult abundance over the full 19 months by 15%; the two-degree temperature drop decreases it by 17% overall. Recall that multiple factors interact to determine the adult abundance at each point; however, predation is probably not a critical biotic regulating factor by the time of the initial peak, for instance, but nutrient competition/carrying capacity probably can have a strong impact at late stages of this initial peak. In general, although the drought period from March 12, 2001 to March 31, 2001 has the effect of allowing a first big peak in adult abundance for An. gambiae , it also synchronizes the first peak, and might be important for control intervention purposes. The overall pattern of adult abundance appears well-conserved, and the variability relatively minor. However, as noted above, the aim here is simply to suggest the potential of the model. Figure 10 shows the standard deviation (variability) of the twenty replicate for each date. Effects of temporary pools Here An. gambiae is considered and examined for the effect on adult abundance of adding pools P2 and P3 to the semi-permanent pool P1, beginning with 10 adults and 300 eggs in each pool. Pools P2 and P3 may be classified as temporary, since they dry two or three times during the year (see figure 7 ). Beside the expected increase in the total number, there is a much more dramatic fluctuation in the mosquito abundance curve, with six added major peaks (figure 12 ). Effects of interventions Here An. gambiae is considered, with pool P1 only, and show how the model might be of help in reducing peaks in adult abundance by helping to optimize the control of larval and adult populations. Recall that the goal here is not to allege or prove a particular finding, which can depend on a specific environmental situation, but to show how the model could help address a given question in a specific environmental situation, and help in understanding the mechanisms involved. The aim is to show examples, with graphical representation, of how such a model can be a powerful tool in research on malaria vector dynamics. For the purpose of the first analysis the predator population is excluded from any effects of the larval control intervention. Therefore, the impact of the predator as described above (in the Predation section) will remain constant. Although the focus is the first major peak in adult abundance, the analysis could be transposed to any period. Interventions that take effect in two periods are compared, the first beginning on May 6, 2000, at the beginning of the first major peak, and the second beginning 15 days later, on May 21, 2000. A successful one-time larval control intervention is simulated by imposing 80% mortality on all larvae present during 10 consecutive days. An adult control intervention that consists of spraying surfaces inside houses with residual insecticide is simulated by imposing 75% mortality on blood feeding adults during a 25-day period. Figure 13 indicates that the later larval-control intervention (5/21/00), though done at the highest adult abundance rates, would have almost no effect on overall adult abundance, since it happens at a period of lower larval abundance. Still worse, it could lead to the production of bigger mosquitoes by diminishing the nutrient competition. On the other hand, a larval-control intervention that began only 15 days earlier would nearly eliminate the entire first peak in adult abundance. This emphasizes the need of good forecasting tools. Similarly, for an adult-control effort (figure 14 ), the later control intervention would have very little impact, but the first peak in adult abundance could be decreased consequently by an effort that began only 15 days earlier. At this stage the model does not take into account such important factors as insecticide resistance and mosquito avoidance behavior, which would tend to diminish the impact of spray programs. A combined control intervention (figure 15 ) shows similar patterns and suggests that the single most effective intervention approach would be an early focus on larval control. Effects of interventions on predators In this analysis the same conditions are considered as the preceding section but the potential impact of the control interventions on predators is also taken into account. In the case of the larval control intervention, 80% mortality in the predator population is assumed, as was observed by [ 20 ]. The predator pressure returns to its normal level after a time lag of 21 days (see Predator section). To the best of our knowledge, no study has focused on predators on adult Anopheles within houses, but spiders in particular are thought to be very efficient in preying on mosquitoes. Here the impact of the destruction of these predators is investigated under an assumption that they represent an adult mosquito mortality of 5%. It is also assumed that the predator-pressure returns to its normal level after a time lag of 21 days. Figures 16 , 17 and 18 show the impact of predators on the vector population. Figure 16 shows that the removal of predators has a big impact on the effect of a larval control intervention: the first peak is much less flattened, as it was in the previous section, and is displaced by about seven days. The lack of predator pressure allows a much quicker reconstruction of the larval population. For the adult control intervention, the curves in figure 17 show almost no differences. However, the half-life of the adult mosquito population increases by one day (from 4.6 to 5.7 days), which is of great epidemiological interest since this would increase the vectorial capacity by allowing more mosquitoes to become infectious. Figure 18 considers the effects of a combined larval and adult control intervention for 10 and 25 days respectively and makes several points. First, the combined control intervention seems to have a stronger impact in terms of reducing the adult population. However, it was noted that the peak in adult abundance (with the predator simulation) is higher than the one without the predator simulation and also that there is a dramatic three-day increase in adult half-life (from 4.6 to 7.5 days). Furthermore, if the larval control intervention is delayed by 20 days, the consequences include not only the persistence of a fairly high first peak but also a higher second one. Therefore, such a model could be very important in helping to assess the optimal timing for vector control interventions. Discussion This model integrates important mechanisms underlying Anopheles population dynamics in an explicit, transparent way. It focuses on five basic factors, two of them abiotic – temperature and moisture – and three biotic – nutrient competition, predation or death by disease, and dispersal. Little of the published literature takes into account the effects of temperature on vector populations. It may be that temperature shows little fluctuation compared to countries with marked seasonality, but most African regions like Kenya exhibit temperature fluctuations ranging from 16°C to 35°C, which can be critical. Futhermore, temperature range is a key determinant for species dispersal and is, therefore, of high epidemiological importance: the species have different vectorial capacities and require different control programs. Each parameter in equation 2 is individually related to the slopes of the curves for each stage of insect development (see Schoofield et al. [ 8 ]), and therefore may reflect a species' adaptation to different climates. Particularly, , ΔH H and ΔH L , should reflect the sensitivity of each species to temperature changes in temperate, high and low temperature areas respectively, and thus could be highly informative. Many studies focus on vector breeding site characteristics, which the model addresses simply in terms of moisture. As yet no particular variables have been found to be crucial determinants of breeding site selection or success, but when these are determined, the model can implement them relatively easily. The transient patterns of breeding sites are taken into account as key determinants of predator and vector disease dynamics, however. Nutrient competition is considered one of the major regulators of vector populations. Here the carrying capacity concept is used to allow both intra-and inter-species competition. Very few studies of vector predators and pathogens have been undertaken to date, but some literature suggests that this may also be an important determinant, so it has been incorporated accordingly. Little is known about Anopheles dispersal, though this is clearly a critical factor. Here simple random dispersal has been used, but it may be possible to implement a more sophisticated dispersal algorithm soon. Thus, a basic tool has been developed for use by field workers and will be vastly improved by their efforts. First, more complete and precise data on Anopheles biology is needed: if nothing else, the model provides an organized view of the huge gaps in the existing information. A framework has been developed by exploiting what is available, but, at this point, far too many parameters and mechanisms involve arbitrary values or estimates. Nonetheless, as an example, a vector population was simulated for a 20-month period, from May 1, 2000 to December 31, 2001, with meteorological data from Kilifi in Kenya and it was possible to roughly assess the sensitivity of vector population dynamics to four of the five basic factors – temperature, moisture, competition, and predation. The focus was on adult abundance curves. Temperature is very important to the adult abundance curve and, particularly, to the occurrence of the initial peak after a drought period; this may be critical for control purposes. Moisture is a key determinant of particular high peaks that occur not only after a drought period but throughout the year for temporary breeding sites. These peaks were attributed to the lower larval mortality proceeding from lower predation and disease pressure. These peaks may be of great epidemiological importance, in that they could bring malaria prevalence in humans above a threshold at which relatively high transmission could occur despite a low vector density. One concern with such large fluctuations is that the proportion of people susceptible may be very high at the beginning of the peak period. Furthermore, the earliest emergent adult mosquitoes may have a higher vectorial capacity; with almost no food competition, their weight is greater, which implies a longer life [ 26 ]. With different initial conditions, when high density competition induces longer development time, the occurrence of the first peak can be delayed by more than a week. Preliminary results on species competition suggest the existence of competitive exclusion, i.e. the survival of only one species in a given habitat, which highlights the necessity of niche differentiation for species coexistence. The example also suggests that if insecticides impact populations of predators on Anopheles , the resulting de-regulation may backfire, producing a vicious cycle that leads to ever-increasing insecticide use. This further supports the argument that great improvements in our understanding of Anopheles ecology and population dynamics are needed. The model is based on the data and knowledge currently available, and it can reproduce some broad, diverse patterns found in the field; its mechanisms and rules are explicit, and they allow us to provide detailed analyses and explanations of vector population dynamics. However, it requires considerable, continued application in the field to improve the data and our understanding of the underlying mechanisms. This is exactly the plan for subsequent research, to contribute to improved control of the scourge of malaria. Table 9 shows the parameters in the most immediate need of field testing and measurement. However, with the default parameter setting, the model can currently be run by users with only: 1. A description of the geographical area with the pools and houses. 2. Climate information (temperature, precipitation, relative humidity) for the period considered. Conclusions This model made it possible to structure existing knowledge of Anopheles vector population dynamics, and highlight crucial elements that are missing. The data and other information currently available made it possible to build a model that can reproduce diverse patterns found in the field. It incorporates explicit mechanisms and rules that can provide detailed analyses and explanations, and thus is a tool to help the malaria research and intervention community gain a better understanding of vector dynamics. The model should be greatly improved as more precise data and hypotheses become available and as it is applied in the field. Authors contributions • JMD contributed conceptualisation and design of the model, main literature review and authorship of the paper. • CM contributed conceptual and data input, review and comments. • GK, BK, JB and JC contributed conceptual input, review and comments. • JD, PB, HM, JG and AT contributed review and comments. • FEM contributed the initial concept and general supervision. All authors read and approved the manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC514565.xml
544346	A database for G proteins and their interaction with GPCRs	Background G protein-coupled receptors (GPCRs) transduce signals from extracellular space into the cell, through their interaction with G proteins, which act as switches forming hetero-trimers composed of different subunits (α,β,γ). The α subunit of the G protein is responsible for the recognition of a given GPCR. Whereas specialised resources for GPCRs, and other groups of receptors, are already available, currently, there is no publicly available database focusing on G Proteins and containing information about their coupling specificity with their respective receptors. Description gpDB is a publicly accessible G proteins/GPCRs relational database. Including species homologs, the database contains detailed information for 418 G protein monomers (272 Gα, 87 Gβ and 59 Gγ) and 2782 GPCRs sequences belonging to families with known coupling to G proteins. The GPCRs and the G proteins are classified according to a hierarchy of different classes, families and sub-families, based on extensive literature searchs. The main innovation besides the classification of both G proteins and GPCRs is the relational model of the database, describing the known coupling specificity of the GPCRs to their respective α subunit of G proteins, a unique feature not available in any other database. There is full sequence information with cross-references to publicly available databases, references to the literature concerning the coupling specificity and the dimerization of GPCRs and the user may submit advanced queries for text search. Furthermore, we provide a pattern search tool, an interface for running BLAST against the database and interconnectivity with PRED-TMR, PRED-GPCR and TMRPres2D. Conclusions The database will be very useful, for both experimentalists and bioinformaticians, for the study of G protein/GPCR interactions and for future development of predictive algorithms. It is available for academics, via a web browser at the URL:	Background G protein-coupled receptors (GPCRs), form one of the major groups of receptors in eukaryotes; they possess seven transmembrane α-helical domains, as confirmed by analysis of the crystal structure of Rhodopsin [ 1 ]. The study of GPCRs, and the way that they are activated by their ligands, is of great importance in current research aiming at the design of new drugs [ 2 , 3 ]. The importance of GPCRs in pharmaceutical industry, is reflected in the fact, that an estimated 50% of current prescription drugs target GPCRs [ 4 - 6 ]. Characteristically, the human genome, possesses approximately 700–800 GPCRs [ 7 ]. Understanding and studying the molecular mechanisms, through which the GPCRs transduce their signal into the cell, could also be an issue of great importance. There is a strong and accumulated body of evidence indicating that many GPCRs, form hetero-, or homo-dimers in order to transduce their signal [ 8 ]. Agonist binding to GPCRs leads to association of the hetero-trimeric G protein with the receptor, GDP-GTP exchange in the G protein α subunit followed by dissociation of the G protein into α-GTP and βγ complexes. The dissociated subunits can activate or inhibit several effector proteins such as adenylyl cyclase 1–9, PLCβ 1–4, tyrosine kinases, phosphodiesterases, phosphoinositide 3-kinase, GPCR kinases, ion channels, and molecules of the mitogen-activated protein kinase pathway, resulting in a variety of cellular functions [ 9 ]. However, there is evidence that some GPCRs transduce their signal through in a way that is not G protein-dependent [ 10 ], and also that hetero-trimeric G proteins are involved in mediating the action of some single-spanning membrane receptors [ 11 ]. Furthermore, some GPCRs have been shown to transduce signals into cells by coupling to small G proteins such as ADP ribosylation factor (Arf) and the dimeric Gh protein [ 10 ]. However, in the rest of this paper we will use the term G proteins to refer to hetero-trimeric G proteins, in order to avoid confusion, concerning the subunit composition of the trimers. As mentioned above, G proteins, form hetero-trimers composed of Gα, Gβ and Gγ subunits. G protein α subunits, possess an intrinsic GTPase activity, which enables them to act as time switches: Hydrolysis of the bound GTP to GDP promotes the re-association of the α subunit with the βγ dimer and renders the G protein in an inactive form [ 12 - 14 ]. G protein trimers, are named after their α-subunits, which on the basis of their amino acid similarity and function are grouped mainly into four families [ 15 ]. These include, Gαs and Gαi/o, which stimulate and inhibit respectively an adenylate cyclase [ 16 , 17 ], Gαq/11 which stimulates a phospholipase C [ 18 ], and the less characterized Gα12/13 family that activates the Na+/H+ exchanger pathway [ 19 ]. At least 16 discrete subtypes of α subunits have been identified and classified into the above-mentioned families [ 20 ]. GPCRs, interact specifically with the α subunits of the G proteins, through their intracellular domains, however the same G protein may be activated by several receptors and the same receptor may couple to different G proteins, under different circumstances [ 15 ]. It is interesting to note, that not the whole intracellular loops of GPCRs, but rather the cytoplasmic extensions of the transmembrane helices, are directly involved in the interaction between G protein and GPCRs, as reported in studies involving site-directed mutagenesis and chimeric receptors [ 10 , 15 ]. This is confirmed in part, by a computational study, aiming at finding specific regular expression patterns that discriminate GPCRs with different coupling specificity [ 21 ]. Today, there exist general-purpose databases gathering information for receptors [ 22 ], and others, more specialised, focusing on GPCRs [ 23 ], and receptors of other types i.e. tyrosine kinase receptors [ 24 ], or ligand gated anion channels [ 25 ], but not a database focusing on the coupling specificity of the G proteins to their respective receptors. We have constructed a database, gpDB, built on a sophisticated relational scheme focusing on the coupling specificity of the α subunits of G proteins to their respective receptors. Such a database will be a complement to the already existing databases, and will be a useful tool for the study of the coupling specificity and the interaction of G proteins with GPCRs. Furthermore, the data collected in the database will be useful in the design of algorithms predicting the coupling specificity, and may provide useful insight towards understanding several aspects of protein-protein interactions. Construction and content Datasets In order to construct the database, initial sequence information was retrieved from the publicly available databases: PIR [ 26 ], SWISS-PROT and TrEMBL [ 27 ]. In particular, a total of 418 entries for G proteins were retrieved, while, at the same time, we also retrieved 2782 GPCRs sequences with known coupling preference from SWISS-PROT/TrEMBL. The entries were obtained using suitable scripts written in Perl, in order to parse the DE (description) or the TITLE field in a SWISS-PROT or a PIR entry respectively. The datasets were then checked in order to eliminate duplicates. GPCRs sequences were obtained by using the keyword "G protein coupled receptor" and excluding those that were present in viruses. After the completion of the Uniprot database [ 28 ], all entries were checked again, and now we provide links solely to Uniprot (see below). Additional sequences that were not identified with the above-mentioned procedure were obtained manually after literature search. We used user-written Perl scripts to manipulate the data, whereas the annotations regarding: G Protein coupling specificity and effectors, GPCR dimerization and accessory proteins, and the corresponding references were appended manually in a spreadsheet. Regarding the GPCR/G protein interaction, the data was collected after an exhaustive and detailed literature search, mainly, following the classification of TiPS [ 29 ], and also [ 15 ] and references therein. At this point, we may emphasise, that the database does not report the potential coupling preference of a G protein to a GPCR, but only the naturally occurring coupling specificity. For instance, opsins that normally couple to Gαt (transducin) are expected to be able to functionally couple also to other members of the Gαi/o family. Since these Gα proteins, are not expressed in the same tissues as photoreceptors do, such a coupling is not reported. However, since there are also a lot of GPCRs, showing promiscuous coupling preference in heterologous expression systems [ 30 , 31 ], we could not fully discriminate cases of falsely reported coupling. This could be done, perhaps in a later version, when accumulated evidence of tissue expression patterns of GPCRs could be appended to the database. For G Protein/GPCRs coupling specificity, we provide links to PUBMED corresponding to original articles reporting the coupling preference observed in heterologous expression systems. We also provide links to published original articles, providing information about the dimerization status of a GPCR, and similar links for G Protein effectors and GPCRs accessory proteins. Implementation The data has been organized on the basis of a relational model and is stored in a PostgreSQL database system. The user has supervisory access through our Apache web-server. The database is managed by interferential software, written in Java, which tends to settle any web-server's query. The main innovation of the database, resides on its relational scheme (Figure 1 ). It is well known, that the coupling specificity of G proteins to GPCRs, is not a one-to-one function. Thus, a particular GPCR, may couple to more than one G protein (promiscuous coupling), and vice-versa, one single G protein may couple to several GPCRs of the same organism, which is usually the case, considering the large number of different GPCRs and the much fewer types of G proteins. We have to mention here, that biologically functional complexes, involve trimers of G Proteins [ 10 , 20 ] and in many cases dimers of GPCRs [ 8 , 32 ], whereas there is also a variety of other molecules that could potentially interact with them, such as accessory proteins, scaffolds, and effectors [ 10 ]. Also, there is evidence, that there also exist single-spanning membrane receptors, whose actions are mediated by G Proteins [ 11 ]. However, even though we provide information on these interactions (where available), we did not attempt to organize the database in such a more complicated scheme, for several reasons. Firstly, there is not reported information in the literature for the majority of biological active G Protein heterotrimers, and the role that might play the trimer's different composition regarding subunits Gβ and Gγ. Secondly, even though there is a lot of evidence supporting the idea that GPCRs act as homo-, or hetero-dimers (evidence that the database is pointing to) [ 8 , 32 , 33 ], we could not provide a general scheme involving dimeric GPCRs activation, until more evidence will emerge, without the risk to fall in inaccuracies for the majority of receptors. Such features could be available in later versions of the database. Entry description – detailed view of an entry Each database entry contains the following fields: gpDB name, gpDB id, UniProt accession number, Protein description and classification, sequence, species, organism common name, taxonomy, links to other databases (such as PDB, InterPro, Prints, Prosite, Pfam, GPCRDB, MIM or Smart) and coupling preference (if existent). Information on coupling preference is accompanied by links to PUBMED, corresponding to original articles reporting the interaction. There is also a field showing the reported effector molecules on which G Proteins act, and GPCRs accessory proteins, also accompanied by links to original articles. As we already noted, G proteins are classified into three classes (Gα, Gβ, Gγ). Gα class is further subdivided into four families (Gi/o, Gq/11, Gs, G12/13) and each family is subdivided into different subfamilies and types. This classification is mainly based on proteins present in vertebrates and in the vast majority of invertebrates, while some invertebrates ( C. elegans ) and all plants and fungi do not have such a detailed classification. Gβ and Gγ are subdivided into 6 and 13 different types, respectively. GPCRs are usually classified into several classes, according to the sequence similarity shared by the members of each class. Here, we have to mention that in this classification scheme, the classes are usually termed families, but we chose as before [ 34 , 35 ] to reserve the term family for a lower level of classification. Class A of GPCRs (rhodopsin-like GPCRs) contains the majority of GPCRs, including receptors for structurally diverse ligands (biogenic amines, nucleotides, peptides, glycoprotein hormones etc). Class B (secretin-like GPCRs) contains purely peptide receptors, whereas class C (metabotropic glutamate family receptors) contains metabotropic glutamate and GABA-B receptors and some taste receptors. Class D contains the fungal pheromone receptors, class E contains the cAMP receptors of Dictyostelium and last is the Frizzled/Smoothened class. There are also a number of putative classes of newly discovered GPCRs, whose nomenclature has not been accepted yet from the scientific community. Further details for this higher level of classification can be found in [ 10 , 23 , 36 ] and in the references therein. We further classified GPCRs into 64 different families and each family is further subdivided into different subfamilies, based mainly on TIPS classification scheme that takes into account the native ligand(s) that binds to a particular GPCR. Currently, information on coupling specificity is available only for GPCRs, belonging to the classes A, B, C, D, E and Frizzled/Smoothened, thus only GPCRs belonging to these classes are deposited in the database. A sample entry of the database is shown in Figure 2 . Utility The application possesses a user-friendly environment, through which, the user may retrieve the necessary information, find available resources and cross-references and perform additional tasks such as running predictive algorithms, performing alignments, etc. In the main page of gpDB the user may find links for the following tools: Navigation, Text Search, BLAST Search, Pattern Search. There is also an extensive user's manual page, describing in detail the available tools (Figure 3 ). In summary, the available tools are summarised and described below. Navigation tool Through the navigation tool, the user has the ability to browse the database following the hierarchy (Figure 1 ). The navigation can be performed on either the GPCR or the G PROTEIN hierarchy. Following the link of GPCRs, the user may be navigated through: GPCR CLASSES, GPCR FAMILIES, GPCR SUB-FAMILIES and individual RECEPTORS. Alternatively, following the link of G PROTEINS, the user may browse through: G PROTEIN CLASSES, G PROTEIN FAMILIES, G PROTEIN SUB-FAMILIES, G PROTEIN TYPES and finally to individual G proteins. At each point, the user may navigate up or down the hierarchy tree. Finally, the user may obtain a detailed view of a particular GPCR or G protein (See Entry description). Text search tool In the Text Search area, the user can search for any text in the fields of his/her preference. The user can enter any word in one or more of the available boxes under the name: 'Protein Name', 'Species', 'Description', 'Gene Name' and 'Cross-References'. Advanced queries can be performed using parentheses, and logical operators such as AND, OR, NOT, AND NOT as described in the documentation. Expressions in separate search fields are combined with the AND operator, so every entry of the result set will satisfy the expressions of all the search fields the user has chosen. The user has the option to choose whether the query will be performed against the GPCRs or the G proteins included in the database. BLAST tool With the BLAST search tool [ 37 ], the user may submit a sequence and search the database for finding homologues. The user has the option to choose whether to perform the BLAST search against GPCRs sequences or G proteins sequences or both. The output of the BLAST query consists of a list of sequences in the database having significant E-values in a local pairwise alignment, ranked by statistical significance. Selecting a particular hit, the user may visualize the local alignment, and from there, may retrieve the detailed view of the entry corresponding to the particular target sequence. Pattern search tool Using the Pattern Search tool (a home made tool), the user may perform searches for finding specific patterns in protein sequences of the database. The user, once again, has the option to choose whether to perform the Pattern search against the GPCR sequences or the G proteins sequences. The input of the Pattern Search tool could be either a standard regular expression pattern, or a pattern following the PROSITE [ 38 ] syntax. For example, the regular expression pattern: DRY. [AGS].{3, 6}A taken from the work of Moller and co-workers [ 21 ], that was shown to occur more frequently to the 2 nd intracellular loop of the Gi/o coupled GPCRs, has the simple interpretation, that we must have the consecutive residues Aspartate, Arginine Tyrosine (DRY), followed by any single residue(.), followed by one only of the following residues Alanine (A), Glycine (G) or Serine (S), followed by 3 to 6 residues of any type, ending up to an Alanine (A). We have collected, the 40 most discriminative patterns for each one of the three classes of coupling specificity, reported in [ 21 ] (found at ), and the user has the option, to use them in order to perform searches against the database. The output of the Pattern search application consists of a list of the sequences matching the particular pattern. Following the appropriate links the user may retrieve the detailed view of the target sequence(s). Other tools Furthermore, from the detailed view of an entry the user has the option to perform some additional tasks. These include, running PRED-TMR [ 39 ], PRED-GPCR [ 34 , 35 ] and TMRPres2D [ 40 ]. The aforementioned tools, will be extremely useful when it comes to GPCR sequences, for which the user may obtain predictions regarding the transmembrane segments, the family classification and the visual representation, respectively. Discussion The database that we present here has some innovative and unique features not available in any other publicly accessible resource. The relational scheme, on which the database is organised, is especially designed to capture the coupling preferences of G proteins to GPCRs according to the reported data in the scientific literature. General sequence databases, such as Uniprot, do not include fields showing the coupling preference of GPCRs, but rather contain such information (if they do) in the free-text field of FUNCTION. Other specialised databases already exist focusing only in specific groups of receptors. For example GPCRDB [ 23 ], is the main publicly available resource for the classification of GPCRs. Other such approaches are the RTKdb [ 24 ], focusing on information of tyrosine protein kinase receptors and the Ligand-Gated Ion Channel Database, focusing on the Ligand-Gated Ion Channel receptors [ 25 ]. The database presented here however, not only combines information for both G proteins and GPCRs, but also includes information regarding their coupling specificity, the known effector molecules on which G proteins act, the accessory proteins interacting with GPCRs and information about the dimerization of GPCRs, all accompanied by links to original research articles from which the information was derived, features that are not available in any other publicly accessible resource. We have to note here, that gpDB does not aim at being a universal resource for GPCRs. A simple comparison with GPCRDB will show that the number of sequences included there, is at least two-three times larger than the sequences deposited in gpDB. This discrepancy arises from the fact that we do not report GPCRs, belonging to families, of which not a single member possesses a known coupling preference to G proteins. Thus, this database will be acting complementary to the existing databases regarding GPCRs, and interaction such as cross-referencing, will be useful. The database provides a starting point for the development of algorithms predicting the coupling specificity of GPCRs to G proteins, an issue addressed already in the past by some teams [ 21 , 41 ], but with moderate success. This database consists of a larger, and well-organised dataset, on which we may build and test more effectively, such predictive algorithms. The database will be updated on a regular (yearly) basis, as new information emerges from genome sequencing projects, and verified experimentally. Also we plan to enrich the database in various ways, for instance developing methods for predicting the coupling specificity, and visualising, if possible, the potential interaction. Other possible additions, would be the the update of the relational scheme of the database in order to allow for dimeric receptors, for which information is already available and described in the database, or for hetero-trimeric G proteins, in case where information on specific subunit composition emerges. Furthermore, sequence information on the G proteins' effectors and the GPCRs' accessory proteins, could be combined in order to develop a fully automated computational resource for the study of protein-protein interactions in the cell membrane, that could describe the signal transduction to the interior of the cell. The information, which the database comprises of, is essentially information regarding protein-protein interactions, which in turn, may be utilised in various ways. Currently, the most informative publicly available general purpose resource, concerning protein-protein interaction data, is the Database of Interacting Proteins [ 42 ]. Protein-protein interaction data arising either from databases, or from predictive algorithms may provide useful insight on the study of protein-protein interactions [ 43 ], but also may enable better functional annotation of proteins in the genomic context [ 44 ]. In particular, this kind of information may help in the construction of protein interaction networks, applied in genomic context [ 45 ]. Conclusions We present here a relational database, gpDB, summarizing the existing publicly available information regarding G proteins and their interactions with GPCRs. This database fills a gap in the already available resources, regarding GPCRs, and maintains an excellent functionality and interconnectivity with the publicly available databases and web-tools. The database is unique, since no other such database already exists, and will be useful for both molecular biologists conducting experiments, but also for bioinformaticians that manage large amount of data, building algorithms and performing functional classification of proteins in the genomic context. Availability and requirements The gpDB is freely available for academic users at . Non-academics should contact Prof S. J. Hamodrakas at shamodr@cc.uoa.gr to obtain a license. All comments, suggestions, corrections and additions, should be sent to biodb@biol.uoa.gr . Authors' contributions ALE carried out the data collection and annotation, classified the G proteins and drafted the manuscript, PGB designed the relational scheme of the database, classified GPCRs and drafted the manuscript, ICS implemented the SQL database and the web-server pages and SJH coordinated and supervised the whole project. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544346.xml
520824	Prevention of non-communicable diseases in Pakistan: an integrated partnership-based model	Development and implementation of non-communicable disease (NCD) prevention polices in the developing countries is a multidimensional challenge. This article highlights the evolution of a strategic approach in Pakistan. The model is evidence-based and encompasses a concerted and integrated approach to NCDs. It has been modelled to impact a set of indicators through the combination of a range of actions capitalizing on the strengths of a public-private partnership. The paper highlights the merits and limitations of this approach. The experience outlines a number of clear imperatives for fostering an enabling environment for integrated NCD prevention public health models, which involve roles played by a range of stakeholders. It also highlights the value that such partnership arrangements bring in facilitating the mission and mandates of ministries of health, international agencies with global health mandates, and the non-profit private sector. The experience is of relevance to developing countries that have NCD programs running and those that need to develop them. It provides an empirical basis for enhancing the performance of the health system by fostering partnerships within integrated evidence-based models and permits an analysis of health systems models built on shared responsibility for the purpose of providing sustainable health outcomes.	Background Non-communicable diseases exhort a considerable toll on individuals, societies and health systems [ 1 , 2 ]. Located in South Asia, Pakistan has a population of 150 million and a per-capita health expenditure of US $ 18 [ 3 ]. NCDs and injuries are amongst the top ten causes of mortality and morbidity in Pakistan [ 4 ]; estimates indicate that they account for approximately 25% of the total deaths within the country [ 5 ]. NCDs contribute significantly to adult mortality and morbidity and impose a heavy economic burden on individuals, societies and health systems [ 6 ]. In most cases, it is the economically productive workforce, which bears the brunt of these diseases. Existing population-based morbidity data on NCDs in Pakistan show that one in three adults over the age of 45 years suffers from high blood pressure [ 7 ]. The prevalence of diabetes is reported at 10% whereas 40% men and 12.5% women use tobacco in one form or the other [ 8 , 9 ]. Karachi reports one of the highest incidences of breast cancer for any Asian population [ 10 ]. In addition, estimates indicate that there are one million severely mentally ill and over 10 million individuals with neurotic mental illnesses within the country [ 11 ]. Furthermore, 1.4 million road traffic crashes were reported in the country in the year 1999; of these, 7000 resulted in fatalities [ 12 ]. Established evidence highlights the potential to limit NCD mortality and morbidity through appropriate public health strategies aimed at disease prevention, risk factor control and health promotion [ 13 ]. Addressing NCDs in a developing country such as Pakistan is a multidimensional challenge with implications at different levels and necessitates a two fold action. Firstly, lobbying for appropriate investments and policies to facilitate their inclusion in the development and health agenda [ 14 ], and secondly, developing scientifically valid, culturally appropriate and resource-sensitive models incorporating and integrating the multidisciplinary range of actions relevant for NCD prevention. In Pakistan, the public-private tripartite partnership led by Heartfile (a non-profit NGO registered under the Societies Registration act of 1860 in Pakistan) and constituted additionally by the Ministry of Health and the WHO Pakistan office has recently released the National Action Plan for Non-Communicable Disease Prevention, Control and Health Promotion in Pakistan (NAP-NCD) to achieve national goals for the prevention and control of NCDs [ 15 ]. This paper discusses the strengths and limitations of this initiative and highlights the value that such partnership arrangements bring in facilitating the missions and mandates of various partners. Merits The present exercise is the first opportunity to mount a truly 'national plan of action' aimed at preventing and controlling NCDs with the Governments' commitment to NCD prevention as a priority and to enlist a broad range in inputs from within Pakistan for addressing a challenging issue. The NAP-NCD outlines a concerted and comprehensive approach; one that incorporates both policies and actions. It is set within a long-term and life-course perspective and calls for an institutional, community and public policy level change. It has been designed to overcome the tendency to rely on a disjointed set of small scale projects, factoring integration at six levels: grouping NCDs so that they can be targeted through a set of actions, harmonizing actions, integrating actions with existing public health systems, incorporating contemporary evidence-based concepts, combining prevention and health promotion and harnessing the potential within partnerships. Disease domain integration the term NCDs is technically reserved for a group of preventable diseases that are linked by common risk factors: cardiovascular diseases, some chronic lung conditions, cancer and diabetes fall within this category. However NAP-NCD also includes injuries and mental health within this framework as country requirements necessitate that these be addressed within a combined strategic framework through synchronized public health measures. There are many common grounds for combining public health actions to address these diseases. Action level integration the NAP-NCD delivers an Integrated Framework for Action (IFA) [ 16 ]; this is modelled to impact a set of indicators through the combination of actions across the range of NCDs in tandem with rigorous formative research. The IFA emanates from the concept highlighted in Fig 1 ; within this framework, it encompasses two sets of strategies; those that are common across the entire range of NCDs and others that are specific to each NCD domain. The first strategy includes a behavioural change communication strategy, reorientation of health services strategy and surveillance, while the second pertains to legislative and regulatory matters. Figure 1 Paradigm for NCD prevention, control and health promotion Systems level integration the approach adopted horizontally integrates NCD prevention with existing public health and social welfare infrastructure. It thus contributes to strengthening of the pubic health configuration and reorients health services to a more preventive orientation. Integration of concepts NAP-NCD packages several contemporary and novel approaches. The population approach includes a behavioural research and social marketing-guided communication strategy and active role of local opinion leaders and educational institutions. Reorientation of health services includes scaling up of professional capacity and basic infrastructure in health care facilities and ensuring availability of, and access to, essential drugs at all levels of health care. The IFA packages a common population surveillance mechanism for all NCD's (with the exception of cancer). The model includes population surveillance of common risk factors and combines a module on population surveillance of injuries and mental health. The model has also been adapted for program evaluation. Combining prevention and health promotion prevention is concerned with avoiding diseases whereas health promotion is about improving health and wellbeing. Both approaches are overlapping and complimentary and can be present in the same programme with similar activities and hold different meanings for two groups of targeted populations with different results. The public health approach to NCDs offers one of the best opportunities to combine prevention and health promotion to improve multiple positive outcomes; an approach NAP-NCD has capitalized on. Public-private partnership dimension this initiative created a mechanism for visible involvement and participation of relevant ministries, educational institutions, NGOs and leadership foci at a national consultation level and created avenues for their participation in the process that led to its development. In addition, all the key elements and advantages that stand to be gained from comprehensive grouping and maximizing on partnerships have been built upon: integration with the existing health system, inter-sectoral and intra-health-sector collaborations, linkage with the national health policy and partnerships with the private sector. NAP-NCD recognizes the scope of partnerships in public health activities and outlines a scope of interventions that are built on shared responsibility, allowing for agencies to participate according to their own missions, mandates, interests and resources. NAP-NCD fosters partnerships and interface arrangements between the public and private sectors so that the federal government is not solely responsible for getting these programmes out to the communities, but can rely on groups and national organizations that have complementary mandates. These partnerships are in harmony with national health priorities, complement state initiatives and are optimally integrated with national health systems. Value to participating agencies Ministry of Health Reproductive health and communicable disease prevention and control have traditionally been priority areas for the Ministry of Health. Prevention and control of NCDs did not previously feature as part of the National Health Policy of 2001. There were therefore no specific programs in the national and provincial health departments and no budgetary line for NCD prevention up until the signing of the agreement, which lay the terms of reference for developing NAP-NCD [ 17 ]. By leveraging on the technical strengths of a private sector partner, the MOH was able to acquire a scientifically sound plan incorporating broad-based consensus. By adopting this Plan, the MoH has included NCD prevention and control as part of its policy framework. The Federal Government has also shown commitment to implement the plan. Budgetary allocations have been made from the Ministry of Health's existing resources for its first phase of implementation [ 18 ]; these will support the establishment of a surveillance system and a behavioural change communication campaign through the media; in addition a training program has been introduced into the work-plan of Lady Health Workers (LHWs), Pakistan's field force of health care providers at the grass roots level in 17 districts targeting a population of approximately 10 million. Heartfile has previously pilot tested this approach in partnership with the MoH [ 19 ]. Since Heartfile has the major participatory role in implementing these activities; this approach allows the government to fulfil a policy obligation to include the private sector in national programs outside of a 'contractual' mode. It therefore serves as an empirical basis for health sector reform in the area of public-private collaboration. Overall funding for prevention and health promotion in the national health budget has been increased. The next stage of implementation of NAP-NCD includes reorientation of health services and a comprehensive school health program. A proposal is already in the funding pipeline to seek additional resources from the governments' development budget and from donor sources. World Health Organization As part of its global mandate, WHO provides technical support to 'priority national programs' through its Joint Government/WHO Program Review Mission (JPRM) program; this is a regular biannual budgetary line. In addition, 'extra-budgetary' resources are provided for 'WHO priority programs' such as the polio campaign. In the year 2003, US $ 843 million were allocated for 192 countries under the former and 1.4 billion as part of the latter [ 20 ]. For the year 2001–2003, Pakistan was allocated a budget of US $ 20 million [ 21 ]. However by convention, these resources have always been used by public sector institutes and health professionals with public sector affiliations. Within the context of the implementation of the first phase of NAP-NCD, for the first time in Pakistan, the JPRM 2004–05 has made allocations to support activities which are being implemented by an NGO albeit in an official relationship with the MoH [ 22 ]. WHO will therefore gain experience in working in a country model in which the private sector can be supported through the JPRM resources. Heartfile Heartfile has been planning and implementing national media campaigns and community-based projects for cardiovascular disease prevention incorporating social marking approaches [ 23 , 24 ]. Although pilot activities have previously been conducted in partnership with the MoH; the NGO activities were previously not integrated with national programs. By partnering in this program, NGOs activities will contribute to the country's National Plans within the framework of priorities set by broad-based national consensus; will be implemented through existing structures and monitored through one evaluation mechanism. Its activities will therefore contribute to achieving national goals. Currently, the NGO draws support from donor funds through 'project aid'. In future, the NGOs funding is likely to be compromised with shifting donor focus on 'programme aid', as part of which, donors provide funds through national budgets. Partnering in this program therefore contributes to sustainability of the NGO as this provides a mechanism for sustained funding. Limitations The ingredients in this public health strategy are sound; however there are several limitations of this approach. Firstly, it needs to be supported by a clear, strong and sustained political commitment; secondly, the successful implementation of this plan requires the setting up of appropriate infrastructure and public health workforce with adequate capacity for core public health functions. This has implications for the need to build capacity and related infrastructure as a parallel process. The public-private partnership dimension of this plan emanates from within the overall 'development policy framework', which encourages private-sector participation in state activities. However it does have its own challenges. This experience therefore presents a clear imperative for addressing ethical, methodological, accountability, sustainability and governance issues in public-private and other multi-stakeholder arrangements [ 25 - 27 ]. Implications for generalisability Useful lessons can be learnt from this experience both by developing countries and low resource settings that have NCD programs running and others that do not. Most developing countries have limited capacity for NCD prevention and control [ 28 ]. There is limited experience with building 'integrated models' and 'partnerships' for NCD prevention suited to low resource situations. The Action Plan therefore serves as an empirical basis for an integrated approach to NCDs on one hand, and an experimental basis of health sector reform in the area of public-private collaboration on the other. This example is also relevant to NGOs in other developing countries, who receive financial support from donors through project aid as it serves as an empirical basis for the integration of NGO activities with national plans and goals. Evaluation The desired impact of this intervention is positive change in population health behaviours; therefore its ultimate success can be judged by changes in population outcomes, which can only be assessed over a period of time. However the process evaluation framework of the Action Plan outlined in the IFA is modelled to access how the program achieves its effects and includes the evaluation resource inputs, description of activities and intermediate outcomes. A review of the Logical Framework Analysis of the Action Plan and the IFA has shown progress against many of the process indicators [ 29 ]. Conclusions Notwithstanding that there are several limitations of this strategy, it does provide the empirical basis for an integrated response to NCD prevention and health promotion in a developing country setting. The IFA is an innovative tool, which helps to set country targets and defines integrated actions to meet those targets. However future efforts must also seek to integrate strategies with communicable disease control, particularly in areas where a life course approach is pursued; this will enable the development of sustainable public health systems for all disease. It is hoped that the findings from this program can be a basis for policy change.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC520824.xml
533870	An enigmatic fourth runt domain gene in the fugu genome: ancestral gene loss versus accelerated evolution	Background The runt domain transcription factors are key regulators of developmental processes in bilaterians, involved both in cell proliferation and differentiation, and their disruption usually leads to disease. Three runt domain genes have been described in each vertebrate genome (the RUNX gene family), but only one in other chordates. Therefore, the common ancestor of vertebrates has been thought to have had a single runt domain gene. Results Analysis of the genome draft of the fugu pufferfish ( Takifugu rubripes ) reveals the existence of a fourth runt domain gene, FrRUNT , in addition to the orthologs of human RUNX1 , RUNX2 and RUNX3 . The tiny FrRUNT packs six exons and two putative promoters in just 3 kb of genomic sequence. The first exon is located within an intron of FrSUPT3H , the ortholog of human SUPT3H , and the first exon of FrSUPT3H resides within the first intron of FrRUNT . The two gene structures are therefore "interlocked". In the human genome, SUPT3H is instead interlocked with RUNX2 . FrRUNT has no detectable ortholog in the genomes of mammals, birds or amphibians. We consider alternative explanations for an apparent contradiction between the phylogenetic data and the comparison of the genomic neighborhoods of human and fugu runt domain genes. We hypothesize that an ancient RUNT locus was lost in the tetrapod lineage, together with FrFSTL6 , a member of a novel family of follistatin-like genes. Conclusions Our results suggest that the runt domain family may have started expanding in chordates much earlier than previously thought, and exemplify the importance of detailed analysis of whole-genome draft sequence to provide new insights into gene evolution.	Background Since the initial description of the Drosophila segmentation gene runt over a decade ago [ 1 ], a small family of runt domain (RD) genes has been described and extensively analyzed in several species. The 130 amino acid long runt domain is very highly conserved and is readily identifiable computationally. RD transcription factors are developmental regulators involved both in cell proliferation and differentiation, and their disruption usually leads to disease [ 2 ]. In humans, three different RD genes were identified [ 3 ] and named according to various schemes, currently standardized by the human gene symbols RUNX1 , RUNX2 and RUNX3 . RUNX genes have two promoters (P1 and P2, also called distal and proximal, respectively) [ 4 - 7 ] separated by a long intron; the proximal promoter (P2) is always located within a large CpG island [ 8 ]. Extensive alternative splicing giving rise to many isoforms has been described for all RUNX genes [ 9 - 11 ]. Orthologs of all three human RUNX genes were identified in mouse. A single RD gene was described in Xenopus , presumed to be orthologous to RUNX1 [ 12 ]. An experimental search for RD genes in fugu showed the existence of a fugu ortholog of human RUNX2 , and suggested the existence of a single additional RD gene in fugu [ 13 ], while a computational search of the fugu genomic sequence revealed three RUNX genes [ 14 ]. Four RD genes were identified in Drosophila [ 14 , 15 ], while a single RD gene exists in C. elegans [ 16 ], sea urchin and amphioxus [ 17 ]. Based on these data, current thought on the evolution of the RD gene family posits that a single RD gene was present in the common ancestor of chordates [ 17 ], and this ancestral gene triplicated during early vertebrate evolution, giving rise to the modern RUNX gene complement. The proposed mechanism of expansion involved large-scale genomic duplications, identifiable today as large paralogous segments [ 18 ]. The proper identification of true orthology relationships is often helpful for inferring gene function and translating knowledge between model organisms and more complex species. Under the current model, simple orthology relationships should be expected among vertebrate RUNX genes, but their functional relationship to the ancestral RD gene is unknown. The single known RD gene in C. elegans has been shown to be required for the formation of a functional gut; this role has been claimed to be conserved with mouse Runx3 [ 19 ]. The current availability of genome drafts for several vertebrate species, including Homo sapiens , Mus musculus , Rattus norvegicus , Canis familiaris , Gallus gallus , Takifugu rubripes , Tetraodon nigroviridis , Danio rerio and Xenopus tropicalis , allows us to explore a comprehensive set of vertebrate RD genes and characterize their genomic environments, shedding light on the structure and evolution of this important gene family. Results The fugu genome has at least four runt domain genes Our search for RD genes in the fugu draft yielded four distinct genomic scaffolds (Fig. 1 and Table 1 ), each containing a single, complete RD gene. Each scaffold had one or more sequence gaps, some within the RD genes, others between them and their neighbors. We employed a directed sequencing approach to obtain the additional sequence needed to close the gaps in these four scaffolds and to improve sequence quality. Figure 1 The four fugu scaffolds analyzed and visualized using the GESTALT Workbench. The RD genes are aligned by the position of the proximal promoter. For each scaffold, graphs are shown of the CpG contrast values (observed/expected, typically ~0.5 for the fugu genome), G+C percentage (green – below 43%, blue – between 43% and 50%, red – above 50%), interspersed repeats (SINEs in red, LINEs in green, DNA and LTR elements in brown, other repeats in purple), and gene annotations. Genes and repeats displayed above each black midline are in the forward strand, while those displayed under the midline are in the reverse strand of the sequence. All scaffolds are shown at a resolution of 200 bp/pixel, except for scaffold 835, which includes the tiny FrRUNT gene. For clarity, only the last 17 kb of this scaffold are shown at 20 bp/pixel. The much longer scaffold scaffold 183 is also shown truncated at 182 kb; the LCK locus has been studied in detail elsewhere [42]. Table 1 The four fugu RD genes and their human orthologs. Fugu gene Human ortholog Name Location Size %G+C location Gene size %G+C FrRUNT scaffold_835 3.0 41.2% N.O. N.O. N.O. FrRUNX1 scaffold_682 25.2 42.5% chr21 262 43.6% FrRUNX2 scaffold_260 32.6 45.7% chr6 219 39.9% FrRUNX3 scaffold_183 36.8 47.4% chr1 66 54.8% Sizes are expressed in kb. N.O.: No ortholog. We studied the four scaffold sequences using the GESTALT Workbench [ 20 ] and constructed hypothetical gene structures for the fugu RD genes by maximizing similarity to known vertebrate RD proteins. Three of the four RD genes found in the fugu genome have clear one-to-one similarity relationships with the three mammalian RUNX genes (see phylogenetic analysis below). They have been assumed to be their orthologs [ 14 , 17 ]; we call them FrRUNX1 , FrRUNX2 and FrRUNX3 (Fig. 1 ). Their genomic structures are similar to those of their human counterparts, but their sizes have evolved differently. RUNX3 is the smallest of the three human RUNX genes, while in fugu FrRUNX3 is the largest (Table 1 ), and FrRUNX2 is significantly larger than FrRUNX1 . FrRUNX1 has acquired an additional intron [ 17 ] that is not present in human RUNX1 or in any other RD gene. This intron is just 65 bp long, has canonical splice signals, and is in phase 0 with respect to the protein reading frame, at the beginning of the runt domain. An additional intron has been described at the 5' end of the coding region, yielding a short form that would be locally non-homologous to the other RD genes [ 14 ]. A detailed comparison of human RUNX2 and FrRUNX2 has been published [ 13 ]. In both human and in fugu, RUNX3 has the highest G+C content of the RD genes, while the G+C content of RUNX2 differs significantly between the two species (Table 1 ). The fugu RUNT gene In addition to the three RUNX genes, the fugu genome has a fourth and more divergent runt-domain gene, that we named FrRUNT . FrRUNT is an extremely compact gene, spanning just 3 kb of genomic sequence (Fig. 2 ). Based on sequence analysis only, FrRUNT appears to have two promoters, with an intron separating the hypothetical distal promoter (P1) and first exon from the main body of the gene. This intron is usually very long in RUNX genes. It is indeed the longest intron observed in FrRUNT , but it is nevertheless very short, spanning just 1372 bp. There is a local concentration of CpG dinucleotides 200–300 bp upstream of exon 2 (Figs. 1 , 2 ), suggesting that an incipient CpG island might function as a proximal promoter (P2). The G+C content is not elevated in this area, in similarity to the CpG islands of the fugu RUNX genes (Fig. 1 ). The main body of the gene is split into five exons, separated by much shorter introns (69–190 bp long), all of which have canonical splice signals. The longest predicted FrRUNT product is 294 amino acids long, in contrast with the 496 aa, 463 aa and 421 aa observed for FrRUNX1, FrRUNX2 and FrRUNX3, respectively. The small number of exons in FrRUNT leaves little room for alternative splicing by exon skipping, without compromising functionally important domains of the protein. The overall compactness of the gene makes the incorporation of yet undetected exons improbable. Several cryptic splice sites within the exons could enable splicing variants altering exon length. Figure 2 FrRUNT sequence detail, showing its compact organization and its interlocking with the SUPT3H gene. The two genes are disposed in opposite orientations. The inverted lettering for SUPT3H denotes translation from the reverse strand. The two putative promoters and the extent of the runt domain (RD) are indicated; x1–x6 denote the six exons. The black triangle points at the asparagine residue absent from all previously known runt domain proteins. FrRUNT is exceptional in that the length of the runt domain (131 residues) varies from the universally conserved 130 amino acids, due to the introduction of an asparagine residue after position 47 in the RD (Fig. 2 ). This appears to be the first report of such a mutation within this highly conserved domain. We also noted that the RD sequence of the tunicate Oikopleura dioica (AAS21356 in GenBank) has an insertion at the same position (of two amino acids, a proline and an isoleucine). Comparison to the published structure of this domain [ 21 ] shows that this variable region is located in loop L4, opposite the DNA-binding region, i.e. in the location least likely to disrupt the structure of the protein. A surprising observation is that FrRUNT is "interlocked" with FrSUPT3H (Fig. 2 ), the gene orthologous to the human transcription factor SUPT3H [ 22 ]: The first exon of FrRUNT is located within the first intron of FrSUPT3H , and vice-versa. In the human genome, though, SUPT3H is interlocked with RUNX2 , as shown in [ 13 ]. We discuss the puzzles posed by these differences in genomic organization below. Four RD genes in Tetraodon and in zebrafish A genome draft of another pufferfish species, Tetraodon nigroviridis , has been released [ 23 ]. A computational search into this draft reveals four RD genes with clear orthologous relationships with the four fugu RD genes. We call them TnRUNX1 , TnRUNX2 and TnRUNX3 , and TnRUNT (Table 2 ). The RD portion of TnRUNT has been deposited in the EMBL database (accession CAG00330); in this work we report the complete gene structure of TnRUNT , which is similar to that of FrRUNT . In further similarity with the fugu genomic organization, TnRUNT is "interlocked" with the Tetraodon ortholog of SUPT3H (not shown). The three RUNX gene pairs are conserved between fugu and Tetraodon (Table 2 ) and display a larger percentage of protein identity than nucleotide identity, indicating a prevalence of conservative substitutions. In contrast, TnRUNT is only 83.3% identical to FrRUNT at the protein level, less than their nucleotide identity. Indeed, a striking series of non-synonymous mutations has created a highly divergent segment (only eight identical amino acids out of twenty-two) including the N-terminus of the runt domain (Fig. 3 ). The strong and unexpected divergence is not the result of local low sequence quality, as tested by examining the relevant Tetraodon entries from the NCBI Trace Archive, and by resequencing the fugu gene. The differences between TnRUNT and FrRUNT do not modify the Ig-like β-sandwich core of the runt domain [ 21 ], which is highly conserved as expected. Therefore, the structural integrity of the runt domain appears not to be compromised. We can only speculate that the extensive variation in its N-terminus may reflect species-specific constraints. Table 2 The four Tetraodon nigroviridis RD genes, and their identity levels to their respective fugu orthologs. Tetraodon gene Identity Name Location Size %G+C Nucleotide Protein TnRUNT SCAF14597 2.5 42.3% 87.5% 83.3% TnRUNX1 SCAF15084 () 6.0 44.1% 93.3% 97.0% TnRUNX2 SCAF14590 () 31.8 44.4% 96.4% 99.4% TnRUNX3 SCAF15009 (*) 36.6 45.3% 94.6% 98.1% Sizes are expressed in kb. Asterisks denote minimal sizes due to the presence of gaps within the genes; the gene structure for TnRUNX1 is incomplete at its 3' end. Figure 3 Localized high divergence between TnRUNT and FrRUNT. This alignment between the first 171 bp of the predicted TnRUNT coding sequence, with the first 180 bp of FrRUNT , shows a cluster of mutations (curly brackets) around the N-terminus of the runt domain (gray background). Non-conservative mutations (negative BLOSUM scores) are surrounded with thick black frames; thin frames enclose conservative mutations, and synonymous mutations are not indicated. The first sixteen codons derive from exon 1, the rest of the alignment from exon 2. The secondary structures indicated (alpha helix, beta strands and loops) are after [21]. We also searched for RD genes in the genome draft of the zebrafish, Danio rerio [ 24 ]. Orthologs of RUNX1-3 are present, but no ortholog of FrRUNT could be found. This could be due to the incompleteness of the draft sequence. On the other hand, there are two copies of RUNX2, RUNX2A and RUNX2B , which have been shown to have somewhat different patterns of expression [ 25 ]. We next analyze the phylogenetic relationships between all the observed RD genes. Phylogenetic distribution of runt domain genes We performed exhaustive computational searches for RD genes, and in particular for potential orthologs of FrRUNT , using the available drafts of the human, chimp, mouse, rat, dog, chicken and frog genomes. In all cases, we identified three clear matches corresponding to orthologs of the three RUNX genes. None of these genomes included a potential ortholog of the fugu/Tetraodon RUNT gene. In principle, such orthologs might be found in the future within current sequencing gaps or heterochromatic regions, but considering the virtually finished human genome, and the combined coverage of all the genome drafts, we can infer that the RUNT gene is absent in mammals, and probably in all tetrapods. Using representative protein sequences of the RUNX and RUNT genes (see Methods), we reconstructed a molecular tree (Fig. 4 , top left) showing the relationship between the three RUNX proteins, FrRUNT and TnRUNT, and the runt proteins of Ciona intestinalis and Branchiostoma floridae (amphioxus). In this analysis, the FrRUNT protein is nearly equidistant from the three RUNX proteins and amphioxus RUNT (~72% identical, see Table 3 ). In comparison, the identity level between the RUNX proteins is 90%–98% in the same region (Table 3 ), and they are 90%–95% identical to amphioxus RUNT. Therefore, while the amphioxus RUNT protein is very closely related to the vertebrate RUNX, the pufferfish RUNT proteins are significantly more divergent. Figure 4 Phylogenetic reconstruction of runt domain evolution. Top left: unrooted tree of RD proteins based on the runt domain; X1, X2 and X3 denote the RUNX clades, BfRUNT, FrRUNT, TnRUNT, CiRUNT, OdRUNT, SpRUNT and CeRNT1 represent RUNT proteins from amphioxus, fugu, Tetraodon, Ciona, Oikopleura dioica , sea urchin and C. elegans , respectively, while taxa named Dm- represent D. melanogaster RD proteins. Top right: unrooted tree of first exons of human and fugu runt domain genes. Bottom: expanded species trees for the three RUNX orthologous groups. For all trees, numbers indicate percent bootstrap support; the horizontal bars indicate 10% divergence along each branch. White and gray backgrounds indicate comparisons at the nucleotide and amino acid level, respectively. The dashed branch in the RUNX2 panel represents the position of zebrafish (A) prior to AsaturA analysis. The arrows indicate the change effected by this correction. Table 3 Identity matrix. FrRUNX2 FrRUNX3 HsRUNX1 HsRUNX2 HsRUNX3 FrRUNT FrRUNX1 89.7% 91.4% 95.7% 89.7% 89.7% 72.7% FrRUNX2 95.7% 92.3% 96.6% 96.6% 71.2% FrRUNX3 94.8% 97.4% 97.4% 72.7% HsRUNX1 94.0% 94.0% 72.7% HsRUNX2 98.3% 72.7% HsRUNX3 72.7% Percentages of identity between the human and fugu runt domains. A difficulty has been documented in phylogenetic reconstruction of gene families with anciently duplicated genes [ 26 ], in which saturation of frequently-mutating amino acids leads to erroneous "outgroup topologies". In these incorrect topologies, the duplication event appears to be more ancient than supported by the data, which in turn suggest the existence of lineage-specific gene loss events. We tested our phylogenetic reconstruction using the program ASaturA [ 26 ], which identifies and suppresses saturated amino acids, thereby correcting the affected tree topology. This analysis did not modify the location of FrRUNT and TnRUNT in our reconstruction, suggesting that mutational saturation is not causing the observed divergence age of the pufferfish RUNT genes. In this protein-level comparison of the conserved runt domains, the pufferfish RUNT proteins appear to be surprisingly ancient, predating the divergence between craniates (including vertebrates) and cephalochordates (including amphioxus). On the other hand, when comparing the nucleotide sequences of the first exon from each human and fugu runt domain gene, we observed that FrRUNT is more closely related to RUNX2 (Fig. 4 , top right), suggesting the possibility of a recombination event between these genes (see discussion below). We also studied the relationships between the RUNX1, RUNX2 and RUNX3 orthologs in several vertebrates and found the species trees to be largely as expected (Fig. 4 , bottom row). One of the two zebrafish RUNX2 protein sequences (RUNX2A) appeared to be slightly more closely related to tetrapod RUNX2 genes than to the other RUNX2 genes in fish species, including zebrafish RUNX2B (dashed branch in Fig. 4 , RUNX2 panel). We tested this result using ASaturA [ 26 ], and found it to be an artifact of mutational saturation: in the corrected tree (Fig. 4 ), RUNX2A is more closely related to the other fish RUNX2 genes. Comparative genomics of runt domain genes Four RD genes have been identified in Drosophila [ 14 ], more similar to each other than to the vertebrate RUNX genes: they represent an independent family expansion in insects. The four Drosophila RD genes are all linked on chromosome X. Moreover, three of these genes are clustered within a 150 kb region. There is no linkage of RD genes, however, in the human genome: each gene is on a different chromosome. Their genomic environments usually show some conservation: the three human RUNX genes are followed by CLIC genes in the complementary strand (Fig. 5 ), and linked to members of the DSCR1 family. The RD genes appear not to be clustered in the fugu genome, though this conclusion is limited by the fragmentary nature of the current genome draft. All four fugu RD genes are flanked by at least one non-RD gene on each side. Fugu RUNX genes are followed by CLIC genes except for FrRUNX1 , but a CLIC gene is located ~55 kb upstream of FrRUNX1 and in the same orientation. This organization could have arisen by an inversion event in the fugu lineage. To ensure a misassembly did not cause this apparent inversion, we performed a 3x shotgun sampling of the BAC clone OML73850, which spans the range 1–97413 of scaffold 682. This quality control step failed to uncover any misassemblies, and confirmed the genomic organization observed in this fugu scaffold. FrRUNT does not appear to be linked to any CLIC gene, and no DSCR1 family members can be discerned near any of the fugu RD genes. Figure 5 Comparative genomic organization. The genomic neighborhoods of the human and fugu RD genes are compared and contrasted, highlighting synteny conservation (same color between the two species) and gene loss (green features). Feature widths represent rough gene size but are not exactly proportional to gene lengths; likewise intergenic distances are not meant to be precise. Arcs indicate larger genomic distances with one or more intervening genes (not displayed). The numbers associated with the arcs represent the distance in Mb. When studying the wider genomic environments of fugu and human RD genes, we observed significant synteny conservation, in agreement with the observations reported for chromosome X genes [ 27 ]. Indeed, when comparing each of the genes neighboring fugu RUNX genes to the human genome, we find that their orthologs tend to be located in the corresponding human chromosome, e.g. most of the genes linked to FrRUNX3 have orthologs on human chromosome 1, where human RUNX3 resides (Fig. 5 ). Some inversion events can be inferred, e.g. one involving the genes PHIP and IRAK1BP1 and another involving MUT . Gene order and orientation has changed, and intergenic distances have changed drastically, but the overall gene synteny is largely preserved, lending support to the assignments of orthology between the human and fugu RUNX gene pairs. An exception to the conservation of synteny involves the genes CDC5L and SUPT3H , which in the human genome are found immediately upstream of RUNX2 , but in fugu are instead located upstream of FrRUNT , including the first-exon interlocking with SUPT3H mentioned earlier. Evidence points at a larger duplication in fishes, encompassing at least CDC5L , SUPT3H , RUNX2 , CLIC5 , ENPP4 and ENPP5 , followed by differential gene loss. One duplicate copy would have retained FrRUNX2 , CLIC5 and ENPP5 (see Fig. 5 ), while the other copy (currently represented by scaffolds 835 and 376) would have retained CDC5L , SUPT3H , a second RD gene, a second copy of CLIC5 ( CLIC5L ) and ENPP4 . The presence of remnants of SUPT3H upstream of FrRUNX2 [ 13 ], and of two copies of RUNX2 in zebrafish, lends further support to this hypothesis. Thus, comparative genomic analysis of human, fugu and zebrafish suggests that FrRUNT may be a derivative form of a duplicated RUNX2 gene. However, this contradicts the conclusions from phylogenetic analysis or the protein sequences; we discuss this contradiction below. A new family of follistatin-like genes We find several fugu genes for which no human ortholog can be discerned (green features in Fig. 5 ), among them FrRUNT . Immediately downstream to FrRUNT we identified a novel gene ( FrFSTL6 ) from the follistatin family, most closely related to FSTL1 . A detailed computational search for additional sequences of this family identified two novel, large human follistatin-like genes, which we called FSTL4 and FSTL5 . We then found clear orthologs for both in the fugu genome ( FrFSTL4 and FrFSTL5 , respectively). The genes in this family share a Kazal-type cysteine-rich domain (Fig. 6a ) and a calcium-binding EF-hand domain (not shown). Figure 6 Comparison of selected follistatin-like proteins. FST: follistatin. (a) Multiple alignment of the cysteine-rich domain. Darker shading indicates perfect conservation, lighter shading indicates positions that can be explained assuming one or two mutations. (b) Neighbor-joining tree rooted using human osteonectin/SPARC (NP_003109) as outgroup. Numbers on branches indicate the percent support in 1000 bootstrap replicates. The horizontal bar indicates 10% divergence along each branch. The column on the right indicates the scaffold in which each gene is located (fugu) or its genomic location in Mb coordinates and cytogenetic band (human). Having characterized the complete gene family in both human and fugu, we performed a phylogenetic reconstruction based on the conserved Kazal-type domain (Fig. 6b ). FrFSTL6 appears to have no ortholog in the human genome, nor could we identify a potential ortholog in the mouse and frog genomes. This suggests that FrFSTL6 was also lost in the tetrapod lineage. It is reasonable to hypothesize that the neighboring FrRUNT and FrFSTL6 genes were lost in a single deletion event. Discussion We have taken advantage of the availability of genomic drafts for several vertebrate species, including the finished human genome, to identify the orthologs of all currently known runt-domain (RD) genes, as well as a novel member of this small gene family. Both pufferfish species ( Takifugu rubripes and Tetraodon nigroviridis ) have four RD genes; since these genomes are only available as draft assemblies, additional RD genes might be found when the finished genomic sequences are made available. The function of the novel FrRUNT / TnRUNT gene is currently unknown. Based on the phylogenetic analysis, this novel gene appears to represent an ancestral form of the RD family in vertebrates, subsequently lost in the tetrapod lineage. It is therefore surprising that its gene structure, and not that of RUNX2 as in humans, is interlocked with the SUPT3H gene. Based on the comparative genomics analysis alone, one could hypothesize that FrRUNT is simply a derivative form of RUNX2 , i.e. the ortholog of zebrafish RUNX2A . In this case, though, one would expect FrRUNT to be more similar to FrRUNX2 than it is to either FrRUNX1 or FrRUNX3, but in terms of amino acid sequence similarity, it appears to be equidistant from the three RUNX genes. This discrepancy might be explained by invoking accelerated evolution of the pufferfish RUNT genes, perhaps as a lineage-specific adaptation. Typically, nucleotide sequences diverge much faster than amino acid sequences, and the first exons of RD genes are significantly less conserved than the runt domain itself, on which we based our phylogenetic analysis. Therefore, we find it hard to sustain that, while the first exon of FrRUNT maintains its nucleotide similarity to the first exon of RUNX2 , the amino acid sequence of the (normally highly conserved) runt domain itself has diverged at such an accelerated pace. Furthermore, we found this not to be an artifact of mutational saturation [ 26 ]. A similar situation is observed for the neighboring FSTL6 gene: parsimony considerations could lead one to assume that FSTL6 is a fish-specific duplicate of FSTL1 , though contradicting the phylogenetic reconstruction of the evolution of this gene family (Fig. 6 ). This situation could again be explained by assuming accelerated evolution of FSTL6 , but we consider this to be a remarkable coincidence. The conundrum is whether FrRUNT is an ancestral form, or is derived from RUNX2 . Both hypotheses contradict part of the available data. We propose here a third hypothesis, in the form of an evolutionary history (see Fig. 7 ): An ancestral RD gene duplicated in chordates, after divergence from sea urchin, which has a single RD gene [ 17 ]. One of the two resulting RD genes became the RUNX family founder, which expanded by triplication, and one of the three RUNX genes (namely RUNX2 ) became interlocked with SUPT3H . After the teleost/tetrapod divergence, a regional duplication in teleosts created a second copy of RUNX2 and its neighboring genes. In the tetrapod lineage, the ancestral RUNT gene was lost, in conjunction with FSTL6 . In the pufferfish lineage, the RUNT gene replaced most of RUNX2A , perhaps by recombination (Fig. 8 ). This is supported by the clear similarity between the first exons of FrRUNT and RUNX2 . The copy of SUPT3H interlocked with RUNX2B , apparently superfluous, is being lost by gradual degradation, and only small fragments of it remain [ 13 ]. This scenario is compatible with all the data observed. While it posits a small number of additional evolutionary events, it does not involve highly improbable events like the accelerated evolution of a normally highly conserved protein structural domain. Interestingly, the first duplication event could correspond to the first round of vertebrate genome tetraploidization [ 28 ]. A second round of tetraploidization in the ancestral vertebrate could have produced a set of four paralogous runt domain genes, and a hypothetical gene conversion event may have led to the current complement of three RUNX genes (Fig. 7 inset). Conversion between paralogous copies of genes derived from tetraploidization events has been demonstrated [ 29 ]. Figure 7 Hypothesis for the evolution of vertebrate RD genes. Features with thick edges represent RD genes interlocked with SUPT3H family members. The closed padlock icon represents the interlocking event between the RUNX2 and SUPT3H , and the open padlock represents the degradation of a copy of SUPT3H , releasing RUNX2 from interlocking. Not enough information is yet available to establish which of the zebrafish RUNX2 genes is interlocked with a SUPT3H gene. "dup": duplication. Top right inset: Hypothesis of how the ancestral RD duplication could map to the first vertebrate tetraploidization event. RT and RX represent the ancestral forms of RUNT and RUNX genes. Figure 8 The hypothesized recombination event between the ancestral RUNX2A and RUNT genes. After the recombination, the RUNT gene is linked to SUPT3H and has a RUNX2-like first exon. The derivative RUNX2A gene has not yet been observed in pufferfishes, and may have been lost in evolution. Under the proposed scenario, none of the three extant RUNX genes in mammals represents the ancestral vertebrate RD form. Rather, these derivative genes coexisted with an additional RUNT gene and still do so in teleost genomes. The single known RD gene in amphioxus is more similar to the vertebrate RUNX genes than it is to FrRUNT . It is possible, therefore, that cephalochordates (including amphioxus) have a second RD gene, short and divergent enough to escape experimental detection by DNA hybridization [ 17 ]. Why was one of the ancestral RD genes lost in the tetrapod lineage? The three RUNX genes bind to the same DNA motif and modify the expression of target genes through recruitment of transcriptional modulators, which are also shared [ 30 ]; functional differences between the three RUNX genes are attained by way of tightly regulated spatiotemporal expression patterns. We hypothesize that the ancestral RUNT gene became inessential to amniotes by functional reprogramming of the remaining three RUNX genes. Its loss would therefore represent an example of evolution by reduction in complexity. In pufferfishes, the hypothesized recombination event would have placed the RUNT gene under the regulatory control of the former RUNX2A promoter. The viability of such a sudden regulatory change would in turn suggest a significant level of functional redundancy among the RD genes. Conclusions We identified a fourth runt domain gene in the fugu genome, which appears to represent either a pufferfish-specific, fast-evolving derivative of RUNX2 , or a direct descendant of the ancestral chordate RUNT gene. We find the latter hypothesis more reasonable. This novel gene evolved in parallel with the vertebrate RUNX genes, and while it has been preserved in pufferfishes, it appears to have been lost entirely in tetrapods. This suggests that the ancestral vertebrate was more complex than previously suspected. By studying a very limited set of fugu genomic regions, namely the scaffolds related to RD genes, we have identified seven apparently functional fugu genes that are absent from the human genome (Fig. 5 ), and were probably lost early in tetrapod history. In the process of identifying relevant homologs for one of these genes ( FrFSTL6 ), we have identified a new family of follistatin-like genes in the human genome. Phylogenetic analysis of the RD protein sequences led to results that contradict those derived from comparative genomics, but we showed that the two could be reconciled into a coherent evolutionary model. These results underscore the importance of obtaining complete genomic sequences of strongly divergent vertebrates, and the value to be derived by performing detailed and integrated analyses of their gene complements. Methods Search for RD genes We used the human RUNX1, RUNX2 and RUNX3 proteins (SwissProt entries Q01196, Q13950 and Q13761, respectively) as queries in a TFASTY [ 31 ] search into the Takifugu rubripes "assembly3" genome draft [ 32 ] released after publication of the fugu genome [ 33 ]. These data have been provided freely by the Fugu Genome Consortium for use in this publication only. This search resulted in the unambiguous identification of four complete RD genes in scaffolds 183, 260, 682 and 835. Scaffold 25789 is nearly identical with range 115299–115845 of scaffold 183, partially overlapping the last exon of FrRUNX3 . No further evidence was found for an additional RUNX3 gene: we conclude that scaffold 25789 is an assembly artifact. We similarly searched the genome drafts for Tetraodon nigroviridis produced by the Whitehead Institute and the Genoscope [ 23 ], and Danio rerio (Zv1/06 assembly, which was produced by the Zebrafish Sequencing Group at the Sanger Institute [ 24 ]. We analyzed, visualized and annotated all resulting genomic sequences using the GESTALT Workbench [ 20 , 34 ], and produced a detailed gene model for each RD gene. Lacking cDNA or EST data, we reconstructed the putative gene structures by maximizing similarity to known RD proteins. Genomic sequence data have been submitted to GenBank with accessions AY739093-AY739096; the predicted sequences for fugu RD proteins have accessions AAU14190-AAU14193. In a second round of analysis, we used the newly identified RD genes as queries for renewed TFASTY searches of the genome drafts of human (July 03), mouse (February 03), Xenopus [ 35 ] (December 03 assembly) and Ciona intestinalis [ 36 ]. We also used BLAT to search into the updated "freezes" of human (May 04), chimp (November 03), mouse (May 04), rat (June 03), dog (July 04), and chicken (Feb 04). Sequence finishing Large insert clones spanning the gaps in scaffolds from the version 3 assembly were identified by BLAST searches against the BAC/cosmid database in the v.3.0 JGI website [ 37 ]. Cosmids (cloned in Lawrist4) were grown in LB media with kanamycin at 37 ° C for 14 hrs, and DNA was prepared on the Autogen 740 DNA Isolation system in accordance with the manufacturer's instructions. BACs (cloned in pBeloBAC 11) were similarly prepared by growing in media with chloramphenicol. Primers were designed in both directions, across all gaps. Oligonucleotide-directed sequencing from clones and Polymerase Chain Reaction (PCR) methods were used to fill the gaps. PCR amplification was performed on spanning BAC/cosmid or genomic DNA of Takifugu rubripes , generously provided by Dr. Greg Elgar. PCR products were purified with sephacryl (Amersham Pharmacia) and sequenced directly using Applied Biosystems Big dye terminator kit reagents. Whenever necessary, additional pairs of primers were designed for oligonucleotide-directed sequencing to close gaps. Shotgun sequencing data was obtained from the BAC clone OML73850 (b193C08) for part of scaffold 682. OML73850 was fragmented by sonication, end-repaired and electrophoresed to select insert size of 2–5 kb. Insert was ligated into pUC18 vector, transformed and plasmid DNA was made using Eppendorf – 5 Prime PERFECTprep robot and sequenced from both ends. Assembly was carried out using Phrap [ 38 ]. Analysis of the resulting sequence shows that OML73850 spans the first 97413 bp of scaffold 682, and links it to scaffold 4260. The additional sequence data generated in-house were combined with the consensus sequences of the scaffolds produced by the JGI WGS assembly v.3 for the purpose of producing a contiguous sequence for each scaffold. Phylogenetic reconstruction The sequences were aligned using ClustalW [ 39 ]. Phylogenetic trees were built using the neighbor-joining algorithm [ 40 ] and tested with 1000 rounds of bootstrapping. Graphics were produced with TreeView [ 41 ]. Since full-length protein sequences cannot be reliably aligned for extremely divergent RD genes, we used only the runt domain to reconstruct the relationship between the pufferfish RUNT, human RUNX1, RUNX2 and RUNX3 (NP_00175, NP_033950 and NP_004341, respectively), ciona ( C. intestinalis ) RUNT, Oikopleura dioica RUNT (AAS21356), amphioxus ( B. floridae ) RUNT (AY146617), sea urchin S. purpuratus RUNT (NP_999779) and the four Drosophila melanogaster RD sequences (NP_523424, NP_511099, NP_572693 and NP_608398). The tree was rooted using the C. elegans RUN protein (AB027412) as outgroup. We further excluded the first thirteen amino acids of the runt domain, to avoid the topological distortion expected in this region from the highly divergent pufferfish RUNT sequences. For the separate phylogenetic trees of the three RUNX genes, we used the complete protein sequences, with gap opening and extension penalties of 5 and 0.1, respectively. ASaturA analyses were performed using PAM250, Kimura's correction and a cutoff value of 9, with 1000 rounds of bootstrap. The first exons of human and fugu runt domain genes were compared at the nucleotide level. For each exon, we selected the range from 30 nucleotides upstream of the ATG codon, to 15 downstream of the splicing donor site, i.e. 103 nucleotides for each RUNX gene and 94 nucleotides for FrRUNT . Authors' contributions GG conceived of the study, performed the bioinformatics analyses and prepared the manuscript. AK generated the sequence data required for finishing. LH, the laboratory director, provided guidance and contributed to the preparation of the manuscript. LR supervised the Institute for Systems Biology's contributions to the Pufferfish Finishing Consortium and contributed to the preparation of the manuscript. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC533870.xml
423134	A Specific Interface between Integrin Transmembrane Helices and Affinity for Ligand	Conformational communication across the plasma membrane between the extracellular and intracellular domains of integrins is beginning to be defined by structural work on both domains. However, the role of the α and β subunit transmembrane domains and the nature of signal transmission through these domains have been elusive. Disulfide bond scanning of the exofacial portions of the integrin α IIβ and β 3 transmembrane domains reveals a specific heterodimerization interface in the resting receptor. This interface is lost rather than rearranged upon activation of the receptor by cytoplasmic mutations of the α subunit that mimic physiologic inside-out activation, demonstrating a link between activation of the extracellular domain and lateral separation of transmembrane helices. Introduction of disulfide bridges to prevent or reverse separation abolishes the activating effect of cytoplasmic mutations, confirming transmembrane domain separation but not hinging or piston-like motions as the mechanism of transmembrane signaling by integrins.	Introduction Integrins are major metazoan cell adhesion receptors that have the distinctive property of transducing signals across the plasma membrane in both directions. Intracellular binding of cytoskeletal components to integrin cytoplasmic domains activates the ligand binding competency of the extracellular domain (inside-out signaling). Furthermore, ligand binding to integrin extracellular domains is coupled to alterations in cytoplasmic domains that are linked to downstream signaling (outside-in signaling). The three-dimensional architecture of integrin extracellular domains as well as their rearrangement in activation have been revealed by crystal, nuclear magnetic resonance (NMR), and electron microscopic methods ( Xiong et al. 2001 , 2002 ; Adair and Yeager 2002 ; Beglova et al. 2002 ; Takagi et al. 2002 , 2003 ). NMR structures of integrin α and β subunit cytoplasmic tails ( Vinogradova et al. 2000 , 2002 ; Ulmer et al. 2001 ; Weljie et al. 2002 ) and a crystal structure of the β subunit tail in complex with the cytoskeletal protein talin ( Garcia-Alvarez et al. 2003 ) yield structural insights. It is generally accepted that an intersubunit association at the cytoplasmic domain maintains integrins in the low-affinity state ( Hughes et al. 1996 ); however, specific heterodimeric interaction between the isolated cytoplasmic domains in solution is sometimes not observed ( R. Li et al. 2001 ; Ulmer et al. 2001 ), and when observed the reported structures differ ( Vinogradova et al. 2002 ; Weljie et al. 2002 ). The dynamic nature of cytoplasmic intersubunit association was revealed using live cell imaging ( Kim et al. 2003 ), which demonstrated upon integrin activation a decrease in fluorescent resonance energy transfer between yellow fluorescent protein and cyan fluorescent protein tags fused to the C-termini of the integrin α and β subunit cytoplasmic domains. This finding demonstrated separation of the cytoplasmic domains; however, whether signal transmission through integrin transmembrane (TM) domains involves hinging or pistoning motions or lateral separation in the plane of the membrane has yet to be definitively established ( Hughes et al. 1996 ; Lu et al. 2001 ; Takagi et al. 2001 , 2002 ; Gottschalk et al. 2002 ). Thus far, there are no experimental data on how the two integrin TM segments associate. NMR chemical shift data on the integrin β 3 subunit TM-cytoplasmic domain fragment in dodecylphosphocholine micelles predict that the TM segment comprising residues Ile693 to Ile720 is largely α-helical ( R. Li et al. 2002 ). Close apposition of the C-termini of the α V and β 3 extracellular domains in the crystal structure ( Xiong et al. 2001 ) as well as specific interactions between α and β cytoplasmic tails ( Vinogradova et al. 2002 ; Weljie et al. 2002 ) and cryoelectron microscopy of intact integrin α IIb β 3 ( Adair and Yeager 2002 ) suggest that the two TM segments are associated with each other as two interacting α helices, at least in the low-affinity state to which the crystal structure has been shown to correspond ( Takagi et al. 2002 ). However, heterodimeric association between integrin α and β subunit fragments containing the TM and cytoplasmic domains has thus far not been detected in either detergent micelles ( R. Li et al. 2001 ) or lipid bilayers, and association between the TM domains has never been demonstrated in intact cells. Since glycophorin A TM domains dimerize in lipid and detergent micelles ( Lemmon et al. 1992 ) under conditions similar to those under which integrin TM domains fail to heterodimerize, it has been proposed that the interaction between the integrin TM domains is less stable ( Gottschalk et al. 2002 ). Recently, R. Li et al. (2003) reported that both the integrin α and β subunits' TM helices have the potential to undergo homomeric rather than heteromeric interactions, and that stabilization of homooligomerization of integrin TM segments results in integrin activation. Li et al. hypothesize that the homomeric associations between TM segments provide a driving force for integrin activation. Experimental data on the association between integrin TM domains in intact cells are clearly required to decide between the many different models for how conformational signals are transmitted through the membrane in integrins. Here we present extensive experimental evidence using cysteine mutagenesis and disulfide bond formation that integrin α and β TM segments associate with each other with a specific spatial orientation in the resting state. Mutations in the α subunit cytoplasmic tail known to universally activate integrins disrupt the heterodimeric TM domain interaction, but do not result in homomeric interaction. The effects of activating mutations are reversed by disulfide bond formation between α and β subunit TM domains. The results suggest that lateral separation of TM segments is responsible for the initial conversion to the high-affinity receptor. Results Structure of the TM Domain of Integrin α IIb β 3 in the Resting State Cysteine scanning of integrin TM domains Inspection of the primary sequences of integrin subunits readily identifies putative TM segments of approximately 23 hydrophobic amino acids, as widely reported in the literature and as confirmed using a hidden Markov model approach (TMHMM version 2.0) ( Krogh et al. 2001 ) ( Figure 1 ). However, Armulik et al. (1999) experimentally determined the C-terminal boundary of both TM domains in microsomal membranes by introducing N-glycosylation sites at varying positions relative to the membrane, and found that the TM domains extend five or six residues more C-terminally and include a five-residue Lys-Val-Gly-Phe-Phe (KVGFF) sequence in α and a six-residue Lys-Leu-Leu-Ile-Thr-Ile (KLLITI) sequence in β ( Figure 1 ). Figure 1 Sequences of the α IIb and β 3 TM Regions Segments predicted as TM by TMHMM version 2.0 ( Krogh et al. 2001 ) are boxed. The more C-terminal KVGFF sequence in α IIb and KLLITI sequence in β 3 are additionally predicted to be in the membrane by Armulik et al. (1999) . Charged residues involved in intersub-unit salt bridges (dotted lines) in the NMR cytoplasmic domain structure ( Vinogradova et al. 2002 ) are marked with ovals. Residues used for cysteine scanning in this study are indicated by heavy dots. Arrows show the boundary between residues forming disulfide bonds constitutively and after oxidation. The se-quences of the α IIb * GFFKR truncation and α IIb " GFFKR/GAAKR mutants are also shown. In order to deduce the three-dimensional organization of the integrin TM domains, we utilized cysteine-scanning mutagenesis ( Lee et al. 1995 ). Cysteine mutations were sequentially introduced at Pro965 to Leu974 of α IIb and Pro691 to Gly702 of β 3 ( Figure 1 ) to give ten different α IIb and 12 different β 3 mutants, each containing a single cysteine residue. Mutant α IIb and β 3 chains were then cotransfected into 293T cells, biosynthetically labeled with [ 35 S]-methionine and cysteine, and chased for 17 h with medium containing 500 μg/ml of cysteine and 100 μg/ml of methionine. Detergent cell extracts were immunoprecipitated with a monoclonal antibody (mAb) specific to the α IIb β 3 complex and subjected to sodium dodecyl sulphate polyacrylamide gel elecrophoresis (SDS-PAGE). Because of the extensive chase, only mature, cell-surface α IIb β 3 with complex N-linked glycan was isolated, which can readily be distinguished from the lower M r α IIb and β 3 precursors with high mannose N-linked glycans (data not shown). When the two cysteines on the α and β subunits are spatially close and are oxidized during biosynthesis, they form a disulfide bridge that can be detected by the appearance of a covalently attached αβ heterodimer band in nonreducing SDS-PAGE with a concomitant decrease in the intensity of α and β monomer bands (e.g., Figure 2 A, lane 5 compared to 1). Cysteines located near one another in the extracellular environment or in the membrane near the extracellular surface form disulfide bonds during the normal course of protein biosynthesis and processing. However, cysteines located more deeply in the membrane form disulfides much more efficiently when cells are treated with an oxidation catalyst such as Cu(II)-( o -phenanthroline) 3 (Cu-phenanthroline) (e.g., Figure 2 A, lane 8 compared to 7). Wild-type α IIb and β 3 subunits do not contain any cysteine residues in their TM domains and appear as 135- and 105-kDa bands, respectively, even after oxidation with Cu-phenanthroline ( Figure 2 A, lanes 1 and 2). Figure 2 Formation of Intersubunit Disulfide Bonds in the TM Domain of Resting α IIb β 3 (A) 293T cells were transiently transfected with the indicated integrin constructs and metabolically labeled, and were untreated (–) or oxidized with Cu-phenanthroline on ice for 10 min (+), and then lysates were immunoprecipitated with mouse mAb 10E5 against α IIb β 3 , followed by SDS-7.5% PAGE under nonreducing conditions and fluorography. Positions of molecular size markers are shown on the left. (B) Disulfide bond formation efficiency. For each residue pair, the radioactivity of the αβ heterodimer band divided by the total radioactivity (sum of α, β, and αβ bands) was used to calculate the disulfide bond formation efficiency and is depicted by a gray scale (white for 0% to black for 100% efficiency). The upper and lower halves of the circle indicate the efficiency before (constitutive) and after (oxidized) Cu-phenanthroline treatment at 0 °C, respectively. Residue pairs that form inducible disulfides (i.e., efficiency increases more than 10% after oxidation) are denoted by asterisks. Results are the mean of at least two independent experiments. Solid line shows the predicted TM boundary; dotted line indicates boundary between residues that form constitutive and inducible disulfide bonds. (C) Relative orientation of the α IIb and β 3 TM helices near their N-terminal ends. The TM domains are depicted schematically as α helices, and experimental results from cysteine scanning were used to deduce their relative orientation. The resultant schematic model is shown in both top and side views. Residue pairs that form disulfide bonds at greater than 50% efficiency are connected by solid (constitutive disulfides) or dotted (inducible disulfides) red lines. The gray dotted line represents the boundary between residues that form constitutive and inducible disulfide bonds. Residues are color coded based on the number of constitutive or inducible disulfide bonds formed at greater than 50% efficiency: multiple bonds (interacting residues, red), only one bond (peripheral residues, pink), and no bonds (outside residues, blue). (D) Homodimer formation by the W967C mutant of α IIb . Transfection, radiolabeling, and immunoprecipitation was performed as in (A). Full-length α IIb with the W967C mutation (α-W967C) but not the truncated active mutant α IIb with W697C (α-W967C) produced a homodimer band (α–α) larger than the heterodimer band (α–β). The α972C/βL697C combination that produces efficient inducible heterodimer is shown as a standard (lanes 1 and 2). We tested all possible combinations between the ten α IIb cysteine mutants (965C to 974C) and the 12 β 3 cysteine mutants (691C to 702C), i.e., a total of 120 different cysteine pairs. Transient transfection in 293T cells and CHO cells gave similar results. The disulfide bonding efficiency of all of these pairs is graphically summarized in Figure 2 B. All can be classified into three groups based on their ability to form disulfide-linked αβ heterodimers. The first group includes 17 pairs that constitutively formed disulfides with moderate (20%) to high (100%) efficiency and showed no increase in disulfide-bonded heterodimers upon Cu-phenanthroline treatment ( Figure 2 B, light to dark gray in both the upper and lower halves of individual circles). For example, cysteine pair α-P965C/β-I693C formed a disulfide-bonded dimer with an apparent molecular weight of 200 kDa at greater than 95% efficiency even without Cu-phenanthroline treatment ( Figure 2 A, lanes 5 and 6), suggesting that these two residues are in close proximity to each other near the exofacial membrane surface. The second group includes 13 pairs ( Figure 2 B, asterisk) that formed disulfides that increased in efficiency by 10% or more upon treatment with oxidant. For example, the efficiency of disulfide formation by the α-V971C/β-L697C pair was about 5% in the absence of oxidant ( Figure 2 A, lane 7) and about 70% after treatment of cells with Cu-phenanthroline at 0 °C for 10 min ( Figure 2 A, lane 8). The residues that formed disulfide bonds with increased efficiency after Cu-phenanthroline treatment are located deeper in the plasma membrane. The boundary between positions where disulfide bonds were constitutive and where they were increased by oxidants was between Trp967 and Trp968 in α IIb and Leu694 and Val695 in β 3 (dashed line in Figure 2 B and solid arrows in Figure 1 ). The same results were obtained using oxidation with molecular iodine (I 2 ), except that the efficiency of disulfide induction was slightly lower (data not shown). The third group, corresponding to the remaining 90 pairs, showed little or no intersubunit disulfide bond formation even after treatment with oxidant ( Figure 2 B, white in both upper and lower semicircles, and 2A, lanes 3 and 4). Helical conformation of the TM domain and the interface between two interacting helices The helical portions of the integrin TM domains are predicted to begin with residues α IIb -Ile966 and β 3 -Ile693 ( Krogh et al. 2001 ), and the latter boundary is also suggested by NMR chemical shift data ( R. Li et al. 2002 ) (solid lines in Figure 2 B and the lower portion of 2 C). A helical structure for the integrin α and β subunit TM domains was confirmed by formation of disulfide bonds with a helical periodicity in the entire portions of these segments scanned, corresponding to residues 966–974 in α IIb and 693–702 in β 3 , i.e., approximately three α-helical turns in each ( Figure 2 B). Thus, α IIb residue 965 constitutively formed disulfides while residue 967 did not, residues 968 and 969 formed constitutive and induced disulfides while 970 did not, and residues 971 and 972 formed induced disulfide bonds. A similar pattern was seen in β 3 , with the minima in disulfide formation efficiency occurring at residues 695, 698/699, and 701/702. This periodicity and the disulfide bonding pattern shown below demonstrate a helical structure. To determine the approximate orientation between the α IIb and β 3 TM helices, the data on disulfide formation were mapped onto a helical wheel representation ( Figure 2 C, upper portion) and an orthogonal view with the axes of the helices in the plane of the page ( Figure 2 C, lower portion). Both the overall disulfide-bond-forming efficiency of individual residues and the pattern of disulfide bond formation are consistent with a unique orientation between the two helices in terms of both the faces of the two helices that are apposed ( Figure 2 C, upper portion) and the relation between the two helices in their axial directions ( Figure 2 C, lower portion). Furthermore, the axial relationship deduced from this pattern is identical to that obtained by assuming that the boundary between residues that form constitutive and inducible disulfide bonds should be at the same depth in the membrane for both helices (gray dashed line in the lower portion of Figure 2 C). Single and double cysteine mutants are in the low-affinity state On both CHO-K1 ( Kashiwagi et al. 1999 ) and 293T transfectants, α IIb β 3 has low affinity for soluble ligand. As shown below, none of the double mutants that formed disulfide bonds bound ligand spontaneously. Furthermore, none of the ten β 3 or 12 α IIb single-cysteine mutants studied here showed elevated ligand binding activity (data not shown). Consistent with this, studies on dimerization of the glycophorin A TM domains have shown that cysteine substitutions are on average less disrupting than substitutions with any other hydrophobic residue ( Lemmon et al. 1992 ). We conclude that the α/β TM domain association depicted in Figure 2 C is that of the resting (low-affinity) integrin conformation. Formation of tetrameric receptors with the α-W967C mutant When cysteine mutant α-W967C was used, a high-molecular-weight species that migrated more slowly than the heterodimer appeared in nonreducing gel electrophoresis, accompanied by a decrease in the intensity of the α IIb band but not of the β 3 band ( Figure 2 D, lanes 3 and 5 compared to lane 9). Treatment with Cu-phenanthroline did not further increase the intensity of the new band ( Figure 2 D, lanes 4 and 6). In reducing SDS-PAGE, the high-molecular-weight band disappeared and was converted into monomeric α IIb (data not shown). Furthermore, the same high-molecular-weight band was observed when α-W967C was cotransfected with any of the β 3 cysteine mutants (β-V695C and β-L698C are shown as examples in lanes 3–6 in Figure 2 D) as well as with wild-type β 3 ( Figure 2 D, lanes 7 and 8) at a similar efficiency of about 80%, confirming that it was an α–α dimer. Furthermore, α–α cross-linking did not affect α–β association, because a stoichiometric amount of β 3 was immunoprecipitated ( Figure 2 D), and the amount of immunoprecipitation by the αβ complex-specific mAb 10E5 was unaffected. Therefore, disulfide linkage through α-W967C results in the formation of a tetramer in which two α IIb β 3 heterodimers are covalently linked through a Cys967–Cys967 disulfide bond to form a (α IIb β 3 ) 2 tetramer. Notably, among the ten α and 12 β cysteine mutants used in this study, only α-W967C formed a homodimeric disulfide bond. This is consistent with the model of α–β TM domain association deduced here ( Figure 2 C), because residue Trp967 faces outward, away from the interface with β 3 . Furthermore, constitutive formation of the Cys967–Cys967 disulfide bond is consistent with the location of Trp967 in the exofacial portion of the α IIb TM α helix, where disulfide bonds form constitutively ( Figure 2 C, lower portion). Disulfide-bonded Receptor Can Be Activated from Outside by Mn 2+ and mAb Previous work has shown that substitution of integrin α L and β 2 subunit cytoplasmic domains for α helices that form a noncovalently associated α-helical coiled-coil heterodimer stabilizes the low-affinity state and is dominant over intracellular signaling pathways that activate integrins; nonetheless, such constructs can be activated from outside the cell by activating mAb or Mn 2+ ( Lu et al. 2001 ). Consistent with this finding, activation of integrin α L β 2 with Mn 2+ does not result in separation of the native cytoplasmic domains tagged with fluorescent proteins ( Kim et al. 2003 ). To test whether the covalent disulfide linkage of the integrin α and β subunit TM domains prevents α IIb β 3 from being activated from the outside by mAb and Mn 2+ , soluble ligand binding was measured. The 293T cell transfectants expressing wild-type α IIb β 3 did not bind soluble fibrinogen in a physiological buffer containing Ca 2+ and Mg 2+ , but high-affinity binding was observed in the presence of Mn 2+ and the activating mAb PT25–2 ( Figure 3 ). Two cysteine mutants with approximately 100% constitutive disulfide bond formation, α-P965C/β-I693C and α-W968C/β-I693C (see Figure 2 A and 2 B), were tested in parallel. Fibrinogen binding by these disulfide-bonded mutants was activated by Mn 2+ and PT25–2 mAb indistinguishably from wild type ( Figure 3 ). Similar results were obtained after Cu-phenanthroline–induced disulfide bond formation in mutants with cysteine substitutions deeper in the membrane, α-V971C/β-L697C and α-G972C/β-L697C (data not shown). These data demonstrate that even a covalent clasp at the TM domain cannot maintain integrins in the inactive state if they are activated from outside the cell by mAb and Mn 2+ . Figure 3 Disulfide-bonded Receptors Can Be Activated from Outside the Cell Transiently transfected 293T cells expressing wild-type (αwt/βwt) or mutant α IIb β 3 heterodimers that form constitutive disulfide bonds (α965C/β693C and α968C/β693C) or are reported elsewhere to be activated (αwt/βG708N) ( R. Li et al. 2003 ) were incubated with FITC-fibrinogen in a physiological buffer (control, white bars) or in the presence of 1 mM Mn 2+ and the activating mAb PT25–2 (+Mn/PT25–2, black bars). Binding of FITC-fibrinogen was determined by flow cytometry as the mean fluorescence intensity and normalized by dividing by the mean fluorescence intensity with Cy3-labeled anti-β 3 mAb AP3 and multiplying by 100. Separation of TM Helices Upon Integrin Activation from Inside the Cell Is the specific TM helix association defined here disrupted in response to activation from inside the cell? We mimicked physiological inside-out integrin activation by using α IIb β 3 containing a truncation before the Gly-Phe-Phe-Lys-Arg (GFFKR) motif in the α IIb subunit ( O'Toole et al. 1994 ), or a Gly-Ala-Ala-Lys-Arg (GAAKR) sequence in place of the GFFKR sequence ( Lu and Springer 1997 ; Kim et al. 2003 ) (see Figure 1 ). When cotransfected with the wild-type β 3 subunit, α IIb truncated at Gly991 (denoted α) formed a heterodimer on the cell membrane and appeared as an approximately 130-kDa band, slightly smaller than wild-type α IIb in nonreducing SDS-PAGE ( Figure 4 A, lane 2). Transfectants expressing the mutant α/β receptor bound soluble fibrinogen in the absence of any activation, confirming the activating effect of C-terminal truncation ( Figure 4 B). Furthermore, the α/β heterodimers constitutively expressed three independent activation-dependent epitopes called ligand-induced binding sites (LIBSs) in the absence of ligand ( Figure 4 C, α/βwt), demonstrating conversion of the extra-cellular domain to the extended conformation ( Takagi et al. 2002 ). Figure 4 Formation of Intersubunit Disulfide Bonds in the TM Domain of α IIb β 3 and Effect on Ligand Binding and LIBS Epitopes (A) Immunoprecipitation. Immunoprecipitation of [ 35 S]-labeled receptors and nonreducing SDS-PAGE and fluorography was as described in Figure 2 . (B) FITC-fibrinogen binding. Binding was determined by immunofluorescence as described in Figure 3 . (C) LIBS exposure. Three different anti-LIBS mAbs (LIBS6, D3, and AP5) were used to probe the conformational state. mAb binding is expressed as the mean fluorescence intensity in the absence (control, open bars) or presence (+Mn/RGD, black bars) of Mn 2+ and RGD peptide. (D) Disulfide bond formation efficiency. Disulfide bond formation in α IIb β 3 heterodimers with the indicated residues mutated to cysteine was determined as described in Figure 2 B. Using this active α mutant, cysteine scanning was performed. As shown in Figure 4 D, the results were very different from those obtained with full-length α IIb β 3 in two important respects. (1) No periodicity in disulfide formation was observed ( Figure 4 D). The only pattern was that the more N-terminal exofacial residues preferentially bonded to more exofacial residues in the other subunit, whereas more buried residues preferentially bonded to more buried residues in the other subunit. The lack of periodicity is highly unlikely to result from a loss of helical secondary structure in such a large portion of the TM domains ( S. C. Li and Deber 1993 ). Furthermore, even in a dodecylphosphocholine detergent environment and in the absence of association with α IIb , this portion of the β 3 TM domain retains an α-helical structure as shown by NMR experiments ( R. Li et al. 2002 ). Therefore, the loss of periodicity in disulfide formation suggests that there is no longer a preferred orientation between the α and β subunit TM helices. (2) Oxidant-induced disulfide bond formation at 0 °C was not observed ( Figure 4 D). As shown below, this is because in the absence of constitutive disulfide bond formation, the TM domains of the α/β heterodimers are not, or are only transiently, associated with one another in the membrane. We thought it important to confirm these results with an activated integrin that was not truncated and therefore used α IIb with the GFFKR sequence mutated to GAAKR, designated α IIb ". A smaller number of cysteine-scanning substitutions were introduced into α IIb ", and tested together with the β 3 cysteine mutants ( Figure 5 A). The same two major trends were found as with α IIb /β 3 . (1) Just as in α IIb /β 3 , in α IIb "/β 3 , the helical periodicity of disulfide bonding was lost, as evidenced by the results with the β 3 scanning mutants β-I693 to β-V700 ( Figure 5 A). (2) As found with α IIb /β 3 and not with α IIb /β 3 , none of the α IIb "/β 3 mutants showed increased disulfide bond formation when treated with Cu-phenanthroline at 0 °C ( Figure 5 A and 5 B). Figure 5 Formation of Intersubunit TM Disulfide Bonds in GFFKR/GAAKR Mutant α IIb ′′β 3 Receptors and Effect on Ligand Binding (A) Disulfide bond formation efficiency in α IIb "β 3 . Disulfide bond formation in α IIb "β 3 heterodimers with the indicated residues mutated to cysteine was determined as in Figure 2 B. Boxed residue pairs were also subjected to Cu-phenanthroline oxidation at 37 °C in (B and C). (B) Radiolabeled 293T cells expressing the indicated mutant integrins were treated with Cu-phenanthroline at 0 °C or 37 °C, followed by immunoprecipitation with anti-α IIb β 3 , SDS-PAGE, and fluorography to probe disulfide bond formation. (C) Efficiency of intramembranous disulfide bond formation in the context of the α IIb "β 3 mutant receptor was assessed after Cu-phenanthroline oxidation at 0 °C or 37 °C and expressed as in Figure 2 B. (D) FITC-fibrinogen binding. Binding was determined before (–) and after (+) Cu-phenanthroline oxidation at 37 °C and expressed as in Figure 3 . It is significant that a number of α/β and α"/β cysteine-scanning mutants could form disulfide-bonded heterodimers during biosynthesis, but in contrast to α/β, none showed increased disulfide formation after oxidation at 0 °C. During biosynthesis at 37 °C, the membrane is fluid. Disulfide bond formation is catalyzed in the endoplasmic reticulum by disulfide isomerases, and because the redox balance is oxidizing in the endoplasmic reticulum, disulfide bond formation can covalently trap protein complexes that form only transiently. Therefore, a complex that would not be stable energetically by noncovalent interactions alone may nonetheless be stabilized by a covalent disulfide bond. This may particularly be the case for interactions between integrin TM domains, because the noncovalent association between the α and β subunits in the headpiece in the extracellular domain increases the probability of collision between the α and β subunit TM domains. If disulfide formation is the result of a stable noncovalent interaction between TM domains, it should occur at 0 °C when membranes are in a gel phase and proteins do not diffuse, as well as at 37 °C when membranes are liquid-crystalline and proteins diffuse. On the other hand, if disulfide formation is the result of transient interactions that are energetically unfavored, it should occur at 37 °C but not at 0 °C. To confirm the hypothesis that in α/β and α"/β transient collision between TM helices can result in disulfide formation, Cu-phenanthroline oxidation was performed both at 0 °C and 37 °C. As described above, the α-G972C/β-L697C pair in the context of the wild-type receptor shows greatly increased disulfide bond formation upon oxidation by Cu-phenanthroline at 0 °C ( Figure 6 A, lane 3 compared to 1). In contrast, the same residue pair in the context of the truncated active mutant, α-G972C/β-L697C, did not show increased disulfide bond formation after oxidation at 0 °C ( Figure 6 A, lane 6 compared to 4). When oxidation was performed at 37 °C, however, this intramembranous disulfide bond formed in the context of the truncated α/β mutant ( Figure 6 A, lane 5). This strongly supports the hypothesis that association of the TM segments in the α/β receptor is not energetically favored—and is thus present only in an undetectably small subpopulation of molecules at any one moment—but is a kinetically accessible state in a fluid membrane at 37 °C that can be trapped by disulfide formation. Increased disulfide bond formation by α/β mutants by oxidation at 37 °C was not due to increased catalysis by Cu-phenanthroline or other nonspecific factors, because in full-length α/β, disulfide linkage induced by Cu-phenanthroline was the same at 37 °C (data not shown) as at 0 °C (see Figure 2 B). Oxidation-induced cross-linking at both 0 °C and 37 °C was extended to all other cysteine pairs in the context of the α/β mutant ( Figure 6 B). Nine of them showed significant enhancement in cross-linking at 37 °C compared to 0 °C ( Figure 6 B), whereas none of the same pairs in full-length αβ showed enhanced cross-linking at 37 °C compared to 0 °C ( Figure 6 A, lanes 1–3, and data not shown). Figure 6 Formation of an Intersubunit Disulfide Bridge within the Membrane Reverses the Active Phenotype of the α IIb β 3 Receptor (A) Radiolabeled 293T cells expressing the indicated mutant integrins were treated with Cu-phenanthroline at 0 °C or 37 °C, followed by immunoprecipitation with anti-α IIb β 3 , SDS-PAGE, and fluorography to probe disulfide bond formation. (B) Efficiency of intramembranous disulfide bond formation in the context of the truncated α IIb β 3 receptor was assessed after Cu-phenanthroline oxidation at 0 °C or 37 °C and expressed as in Figure 2 B. (C) Ligand binding by wild-type or mutant α IIb β 3 expressed on 293T cells was determined before (–) and after (+) Cu-phenanthroline oxidation at 37 °C and expressed as in Figure 3 . The above results were confirmed with the full-length α"/β receptor containing the Phe-Phe/Ala-Ala substitution (see Figure 5 B and 5 C). Thus, Cu-phenanthroline did not increase disulfide bond formation between buried residues at 0 °C ( Figure 5 A and 5 B), but it markedly increased disulfide bonding at 37 °C ( Figure 5 B and 5 C). Taken together, the above results demonstrate that (1) integrin α and β subunit TM helices separate from one another upon activation from inside the cell, (2) transient association between TM helices in activated receptors can be trapped either by disulfide bond formation during biosynthesis or by Cu-phenanthroline oxidation at 37 °C, and (3) in activated receptors the specific pattern of association between the TM helices seen in the resting state is not present. A further important finding was that none of the cysteine mutants, including the W967C mutant of α IIb which mediated α–α homodimerization in the wild-type receptor, underwent α–α homodimerization in the context of the activated α/β receptor (see Figure 2 D, lanes 11–14). In contrast, the same cysteine combinations formed α–α homodimers in the context of the full-length αβ receptor without the activating mutation ( Figure 2 D, lanes 3–8). This result is inconsistent with the notion that homooligomerization of TM domains occurs concomitantly with separation of the α and β subunit TM domains and represents the major mechanism for inside-out activation of integrins. TM Helix Separation Is Responsible for Activation of Integrins from within the Cell As described above, integrins with disulfide-linked TM domains can be activated from the outside by Mn 2+ and mAb; however, we now demonstrate that such a linkage prevents activation from the inside. We first examined the activation state of receptors with activating α or α" mutations that constitutively form disulfide bonds during biosynthesis. When α-W968C was coexpressed with β-I693C, nearly 100% formation of the intersubunit disulfide linkage was observed (see Figure 4 A, lane 4). This cross-linked receptor showed low basal ligand binding activity, like the wild-type receptor ( Figure 4 B). By contrast, α-W968C/βwt ( Figure 4 B) and α/β-I693C (data not shown), which did not form cross-links, were basally active ( Figure 4 B). The disulfide cross-link had no deleterious effect on ligand binding itself because, as already mentioned above, α-W968C/β-I693C bound ligand upon activation by Mn 2+ and activating mAb ( Figure 4 B). Furthermore, in α-W968C/β-I693C but not in α-W968C/βwt or α/β-I693C (data not shown), the exposure of activation-dependent epitopes was reduced to the level of the wild-type receptor ( Figure 4 C). This result suggests that the shift from the bent to the extended conformation induced by the activating α mutation was reversed by the TM disulfide bond. The same reversal of basal ligand binding, but not Mn 2+ /PT25–2-activated ligand binding, was found for all constitutively disulfide-bonded α/β pairs that we examined. These included α-I966C/β-I693C, α-I966C/β-L694C, α-I966C/β-V965C, α-W968C/β-L694C, α-W968C/β-V695C, α-W968C/β-V696C, and α-W968C/β-L697C (data not shown). The same reversal of basal ligand binding was also found for all constitutively disulfide-bonded α"/β pairs examined, including α"-I966C paired with either β-I693C, β-L694C, β-V695C, or β-V696C (see Figure 5 D). Therefore, a wide range of distinct intersubunit cross-links in the outer leaflet of the membrane reverse, and are hence dominant over, activating mutations in the α subunit at the boundary between the membrane and the cytoplasm. Could a receptor that was already present at the cell surface and active in ligand binding be converted to an inactive receptor by introduction of a disulfide bond between the α and β subunit TM domains? We were able to answer this question by using the more buried pairs of cysteine residues that formed disulfide bonds upon oxidation catalyzed by Cu-phenanthroline. In α/β we studied the α-G972C/β-L697C pair, which shows greatly enhanced disulfide bond formation after treatment with Cu-phenanthroline at 37 °C (see Figure 6 A and 6B). Under basal conditions, the α-G972/β-L697C mutant actively binds fibrinogen ( Figure 6 C). However, after Cu-phenanthroline treatment at 37 °C, basal ligand binding was almost completely lost, but ligand binding activatable by Mn 2+ /PT25–2 mAb was still present ( Figure 6 C). Cu-phenanthroline treatment at 37 °C was not toxic for basal ligand binding, because the same treatment did not reverse basal ligand binding by α-G972C/βwt ( Figure 6 C) or α/βwt (data not shown). These results were extended to the α"/β mutant using a different pair of cysteines in the α"-V971C/β-L697C mutant that shows Cu-phenanthroline-induced disulfide bond formation at 37 °C (see Figure 5 B and 5 C). Cu-phenanthroline treatment at 37 °C almost completely reversed the elevated basal ligand binding by α"-V971C/β-L697C, but had no effect on α"-V971C/βwt ( Figure 5 D). We conclude (1) that at 37 °C, the α-G972C/β-L697C and α"-V971C/β-L697C heterodimers are predominantly in an active conformation with separated TM domains but equilibrate with a conformation in which the TM domains are transiently associated, and (2) that when association of the TM domains is trapped by disulfide bond formation, the ligand binding site in the extracellular domain returns to the low-affinity state. Discussion We have obtained for the first time structural information regarding the helix–helix interface between integrin α and β subunit TM domains in the membrane bilayer, and demonstrate that dissociation at this interface occurs upon changes at the cytoplasmic face of the plasma membrane bilayer that activate integrins. Extensive mutagenic cysteine cross-linking experiments revealed the presence of a specific α/β TM helix contact in a resting integrin heterodimer, which is lost upon receptor activation from inside the cell. The data establish the approximate orientation between the integrin TM α helices in the outer leaflet of the membrane bilayer in the resting, low-affinity integrin conformation (see Figure 2 C). The mode of association experimentally determined here may be compared to that suggested by computational models ( Gottschalk et al. 2002 ). For comparisons, we used our cross-linking data to construct a model by selecting an alignment to the glycophorin A TM homodimer NMR structure ( Mac-Kenzie et al. 1997 ) that minimized the distances between residues with more than 80% cross-linking efficiency (see Materials and Methods ). The overall orientation in our model is not too dissimilar from that of a model for the resting conformation of the α IIb β 3 TM domains ( Gottschalk et al. 2002 ), but our model fits the data better, with a root mean square distance for three Cβ–Cβ and two Cβ–Gly Cα atom distances of 4.8 Å, compared to 8.9 Å for the computational model. Furthermore, our cross-linking data on the activated receptor are completely incompatible with a model for the activated TM domain interface ( Gottschalk et al. 2002 ) because the cross-linked regions in α IIb and β 3 are close together in this model, yet a specific pattern of cross-linking predicted by the model was not observed. Integrin TM domain homodimerization and heterodimerization has been assayed using a qualitative assay of induction of β-galactosidase in Escherichia coli ( Schneider and Engelman 2003 ). However, the chimeras that were assayed contain truncated integrin TM domains with only 17 residues of the α and β subunit TM domains, lack the GFFKR motif demonstrated here to be required for physiologic TM domain association, and insert as type II rather than type I membrane proteins. These assays were designed to test the hypothesis that the Gly-Val-Met-Ala-Gly (GVMAG) homodimerization motif in glycophorin is equivalent to G972/VLGG in α IIb and S699/VMGA in β 3 ( Schneider and Engelman 2003 ). However, the use of the glycophorin template ( MacKenzie et al. 1997 ) to fit our experimental data demonstrates that the GVMAG dimerization interface is more equivalent to α IIb -W968/VLVG and β 3 -V696/LLSV (see Materials and Methods ). Our cysteine cross-linking data not only define the nature of the interface between the α and β subunit TM domains within integrin heterodimers but also provide information about the spatial relationship between neighboring integrin heterodimers on the cell surface. The formation of a cross-link between the α IIb subunits of two neighboring integrin molecules by the α IIb -W967C mutant demonstrates the lateral accessibility of this site in the resting state. Consistent with this finding, our data demonstrate that the α IIb -W967 residue points away from the TM interface with the β 3 subunit (see Figure 2 C). It further should be noted that in the bent, low-affinity integrin conformation present on the cell surface ( Takagi et al. 2002 ), the headpiece is folded such that the juxtamembrane portion of the α IIb subunit, including Trp967, is exposed, whereas the juxtamembrane segment of β is occluded ( Figure 7 ). This is consistent with the absence of homodimer cross-linking through β 3 . Figure 7 Model for Integrin Activation The α and β subunits are red and blue, respectively. The membrane is shown as a solid gray line in (A–H) and as two dashed lines in (I and J). (A–H) Cartoon models. The ligand-binding α subunit β-propeller and β subunit I-like domains are symbolized as a semicircle with a shallow (low-affinity) or deep (high-affinity) ligand binding site. The headpiece additionally contains the α subunit thigh domain (red straight line) and the β subunit hybrid domain (blue straight line); the swing out of the latter is linked to ligand binding affinity. (A–D) Activation from within the cell initiated by TM domain separation. (E–H) Activation from outside the cell initiated by integrin extension, followed by ligand binding and finally TM domain separation. (I and J) Ribbon models. (I) Bent, low-affinity conformation corresponding to (A and E). (J) Extended, high-affinity conformation with the open headpiece corresponding to (D and H). Models are based on the TM domain association results described here, and negative stain electron microscopy ( Takagi et al. 2002 , 2003), crystallography ( Xiong et al. 2001 ), NMR ( Beglova et al. 2002 ; Vinogradova et al. 2002 ), and fluorescent resonance energy transfer ( Kim et al. 2003 ). The TM and cytoplasmic domains are schematic, and show the proposed salt bridge (– and +). It is most interesting that we observed no homodimerization with constitutively active mutant receptors. The α and β residues mutated to cysteine in active receptors spanned two and three α-helical turns in the α IIb and β 3 TM domains, respectively. The same mutations in resting receptors robustly disclosed heterodimeric interactions. Therefore, if homodimeric interactions between the TM domains were present, they should have been detected. Why were homodimer interactions observed in the resting state, albeit only through cross-linking of one residue, and not in the active state? A full answer to this question would require more knowledge about the dynamics of integrins on cell surfaces; however, based on observations on the heterogeneity of integrin structure from quantitative negative stain electron microscopy of soluble integrins ( Takagi et al. 2002 ), a preliminary answer can be proposed. These studies reveal that the integrin adopts a single homogenous, bent conformation in the resting state. By contrast, in the extended conformation, there are two discrete angles between the β subunit I-like and hybrid domains. Furthermore, the region between the β subunit hybrid domain and the TM domain, which contains four I-EGF domains and the β-tail domain, is quite flexible. Therefore, motion of the headpiece may sweep out a large area and prevent neighboring integrins from coming close. Moreover, motions of the membrane proximal α subunit calf-2 domain relative to the α TM domain and of the β-tail domain relative to the β TM domain would also be much greater after TM domain and tailpiece separation, and would also hinder the close approach of other TM domains. What about observations that integrin fragments consisting of the TM and cytoplasmic domains form dimers (α IIb ) and trimers (β 3 ) in detergent micelles ( R. Li et al. 2001 )? We think that these findings should be interpreted with caution. It is important to point out that the physiological, heterodimeric interaction between the α IIb and β 3 TM domains cannot be reconstituted in the same detergents, i.e., in sodium dodecyl sulfate or dodecylphosphocholine ( R. Li et al. 2001 ). There are many important differences between dodecyl detergent micelles and lipid bilayers, including a shorter hydrocarbon chain (12 versus 16 or 18), one (as opposed to two) fatty acyl chains per headgroup, and a spherical (as opposed to a bilayer) shape. The same characteristics that prevent physiological heterodimeric integrin TM interactions in dodecyl detergent micelles may conspire to cause nonphysiologic homomeric interactions. A β 3 -G708N mutation increases trimerization in detergent by more than 10-fold and is also reported to activate ligand binding in transfectants ( R. Li et al. 2003 ); however, β 3 trimerization in membrane bilayers or intact cells has yet to be demonstrated. In 293T transfectants the β 3 -G708N mutation fails to detectably activate soluble ligand binding by α IIb β 3 (see Figure 3 ). We could confirm that the G708N mutation in CHO cells increased ligand binding, but to a level only 17% of that of the maximally activated receptor, whereas the G708L mutation is maximally activating (data not shown). Gly708 is in the TM heterodimer interface defined here, and we have additional unpublished data suggesting that the weak activating effect of the G708N mutation is a consequence of the disruption of this interface. The lack of homomeric disulfide cross-linking of integrin α and β subunit TM domains found here with activated α IIb β 3 in intact cells strongly suggests that integrin activation from inside the cell is not sufficient to drive homomeric interactions. Studies with fluorescent resonance energy transfer probes attached to integrin cytoplasmic domains also fail to find homomeric interactions when integrins are activated from within the cell or bind to monomeric ligand outside the cell ( Kim et al. 2003 ; M. Kim, C. Carman, and T. Springer, unpublished data). However, we should point out that binding to multimeric ligands induces integrin clustering ( Buensuceso et al. 2003 ) and that we have not examined homomeric interactions under these conditions. In conclusion, our results suggest that lateral separation of the TM segments of the α and β chains leads to affinity upregulation within a single receptor molecule without facilitating α–α or β–β interactions. Therefore, if the tendency of integrin TM domains to undergo homomeric interactions in detergent micelles also holds for lipid bilayers, it may strengthen adhesion and contribute to outside-in signaling after the initial engagement of multimeric physiological ligands. Our results show that the α IIb and β 3 TM domains are associated in a specific manner in the outer leaflet of the membrane bilayer in the resting state and are unassociated in the active state. Upon activation, association between the α and β subunits is also broken at the interface between the TM and cytoplasmic domains ( Hughes et al. 1996 ; Vinogradova et al. 2002 ), and furthermore, the cytoplasmic domains also separate ( Kim et al. 2003 ). The simplest explanation for separation at all three of these locations is separation of the TM domains in the plane of the membrane. Perhaps a counterargument could be made that a hinge-like motion of the TM domains relative to one another about a pivot point near the middle of the bilayer would also give rise to separation at each of these three positions. We point out that only one specific TM hinge model has been proposed, that it does not give rise to separation in the TM regions scanned in this study ( Gottschalk et al. 2002 ), that our data rule it out, and that much more extreme hinging is unprecedented and is unlikely, because the size of the TM interface would be markedly decreased and hence less likely to stabilize association. Bidirectional signal transmission by integrins across the plasma membrane is not necessarily symmetric ( Figure 7 A– 7 D compared to 7 E– 7 H). We show that separation of the TM domains is sufficient to prime the extracellular domain for ligand binding and exposes activation epitopes that report the switchblade-like extension of the extracellular domain ( Figure 7 A– 7 D). Furthermore, prevention or reversal of TM domain separation abolishes priming and extension signaled from the inside. The same is not true in the opposite direction ( Figure 7 E– 7 H); thus, addition of Mn 2+ and an activating mAb to the extracellular environment could prime ligand binding in the absence of TM domain separation. The implication is that with the wild-type receptor, under conditions in which high concentrations of ligand drive the equilibrium toward ligand binding, ligand could bind in the absence of TM domain separation ( Figure 7 G) and subsequently drive TM domain separation ( Figure 7 H). Similarly, when separation of fluorescent resonance energy transfer tags fused to the C-termini of the cytoplasmic domains of integrin α L β 2 is measured, priming from inside the cell results in TM domain separation ( Figure 7 B– 7 D), priming from outside the cell by Mn 2+ does not result in separation ( Figure 7 F and 7 G), and priming with Mn 2+ combined with binding to ligand results in separation ( Figure 7 H) ( Kim et al. 2003 ). Therefore, in Mn 2+ , integrins on the cell surface appear to adopt an intermediate conformation, with the headpiece extended and the TM domains associated ( Figure 7 F and 7 G). The above results are consistent with the existence of multiple conformational states visualized for integrin extra-cellular domains by electron microscopy, and linked equilibria relating these states ( Takagi et al. 2002 ). Furthermore, extended conformations with both closed and open headpieces are present in Mn 2+ ( Figure 7 F and 7 G), whereas only the extended conformation with the open headpiece is present in high concentration of ligand ( Figure 7 H) ( Takagi et al. 2002 , 2003 ). How does TM domain separation trigger integrin extension? In the bent α V β 3 crystal structure ( Xiong et al. 2001 ), the last residue visualized in β 3 is Gly690, immediately before the first TM domain residue mutated to cysteine here. In the α subunit, only four to six residues intervene between the last crystal structure residue and the first residue mutated to cysteine. This very tight linkage between the C-terminal extracellular domains and the TM domains ( Figure 7 I) implies that separation of the α and β TM domains would also lead to separation of the membrane proximal α calf-2 and β-tail domains in the integrin tailpiece. In turn, this separation in the tailpiece would destabilize the extensive interface with the headpiece and lead to switchblade opening ( Figure 7 J) ( Takagi et al. 2002 ). Separation of TM domains in the plane of the membrane is a novel mechanism for activation of a cell surface receptor. One of the best-known mechanisms for receptor activation, exemplified by receptor tyrosine kinases ( Schlessinger 2000 ), works in almost the opposite manner, in which distinct or identical receptor subunits are brought together in a specific orientation in the plane of the membrane by ligand binding. In the neu (ErbB-2) member of the epidermal growth factor receptor family, enforced dimerization along a series of α-helical TM dimer interfaces gives rise to periodicity in activation, such that dimerization only in certain orientations is activating ( Burke and Stern 1998 ; Bell et al. 2000 ). In our study, the αβ and α"β receptors with activating mutations were captured with disulfide bonds in many different rotational orientations between the α and β subunit TM α helices. Similarly, disulfide bonding between cysteines located at different depths in the membrane would be expected to give rise to some piston-like motion of one helix relative to the other. It is notable that none of the enforced orientations between disulfide-bonded α and β integrin TM domains were activating. These results argue against hinging, rotation, or piston models in which a relative change in orientation between the two TM domains is activating, and are in agreement with the model that separation of the α and β subunit TM domains in the plane of the membrane is the activation mechanism. Integrins in the extended conformation have their ligand binding site far above the plasma membrane, as appropriate for binding to ligands in the extracellular matrix and on opposing cell surfaces. However, transmission of conformational information over such distances is inefficient, because it is attenuated by interdomain flexibility. Integrins solve the problem of long distance communication by equilibrating between an extended conformation and a bent conformation, and by altering the equilibrium between these conformations by the novel mechanism of separation of the α and β subunit TM domains. Materials and Methods Plasmid construction and transient transfection Plasmids coding for full-length human α IIb and β 3 were subcloned into pEF/V5-HisA and pcDNA3.1/Myc-His(+), respectively, as described by Takagi et al. (2002) . To mimic inside-out signaling, α IIb cytoplasmic domain mutant receptors were made by introducing a stop codon at residue Gly991 to obtain α IIb 1–990 (denoted α), or by mutating G991/FFKR to GAAKR (denoted α"). Single amino acid substitutions to cysteine were made in α IIb , α IIb *, α IIb ", and β 3 in the positions indicated in the text. All mutants were made using site-directed mutagenesis with the QuikChange kit (Stratagene, La Jolla, California, United States), and DNA sequences were confirmed before transfection of 293T cells using calcium phosphate precipitates, or CHO-K1 cells using Fugene transfection kit (Roche Diagnostics, Indianapolis, Indiana, United States). Cross-linking and immunoprecipitation Twenty-four hours after transfection, 293T cells were metabolically labeled with [ 35 S]cysteine/methionine for 1.5 h before adding chase medium containing 500 μg/ml of cysteine and 100 μg/ml of methionine, and cells were cultured 17 h overnight ( Lu et al. 2001 ). Then cells were detached and suspended in Tris-buffered saline (TBS) containing 1 mM Ca 2+ /1 mM Mg 2+ (10 6 cells in 100 μl). After chilling on ice for 5 min, 20 μM CuSO4/100 μM o -phenanthroline was added by 10-fold dilution from stock solutions, and cells were incubated on ice for another 10 min. Oxidation at 37 °C was similar, except cells were suspended at room temperature and after Cu-phenanthroline addition were incubated at 37 °C for 10 min. Oxidation was stopped by adding an equal volume of TBS containing Ca 2+ /Mg 2+ and 5 mM N-ethyl maleimide. Cells were centrifuged and resuspended in 100 μl of TBS containing 1 mM Mg 2+ , 1 mM Ca 2+ , and 5 mM N-ethylmaleimide, and lysed by addition of an equal volume of 2% Triton X-100 and 0.1% NP-40 in the same buffer for 10 min on ice. Cell lysate was immunoprecipitated with 10E5 (anti-α IIb β 3 -complex-specific mAb) and protein G Sepharose at 4 °C for 1.5 h. After three washes with lysis buffer, precipitated integrin was dissolved into 0.5% SDS sample buffer and subjected to nonreducing 7.5% SDS-PAGE and fluorography ( Huang and Springer 1997 ). The efficiency of disulfide bond formation was quantitated using a Storm PhosphorImager after 1 to 3 h of exposure of storage phosphor screens (Molecular Dynamics, Sunnyvale, California, United States). Efficiency was defined as the ratio of the intensity of the disulfide-bonded heterodimer band to the sum of the intensity of all bands including α IIb , β 3 , and heterodimer. Two-color ligand binding and flow cytometry Binding of fluorescein-labeled human fibrinogen was performed as previously described ( Pampori et al. 1999 ; Takagi et al. 2002 ). To determine the effect of inducible disulfide bond on the ligand binding, oxidation by Cu-phenanthroline was carried out at either 0 °C or 37 °C for 10 min, followed by washing with TBS containing 1 mM Ca 2+ /Mg 2+ and 5 mM N-ethyl maleimide. Cells were suspended in 20 mM Hepes (pH 7.4), 150 mM NaCl, 5.5 mM glucose, and 1% bovine serum albumin, and incubated with 1 mM Ca 2+ /Mg 2+ or a combination of 1 mM Mn 2+ and 10 μg/ml of activating mAb PT25–2. Then cells were incubated with FITC-conjugated fibrinogen with a final concentration of 60 μg/ml at room temperature for 30 min, Cy3-conjugated AP3 was added to a final concentration of 10 μg/ml, and cells were incubated on ice for another 30 min before subjected to flow cytometry. Binding of soluble fibrinogen was determined and expressed as the percentage of mean fluorescence intensity relative to immunofluorescent staining with Cy3-labeled AP3 mAb. LIBS epitope expression Anti-LIBS mAbs AP5 was from the Fifth International Leukocyte Workshop ( Lanza et al. 1994 ), LIBS-6 was from M. H. Ginsberg, and D3 was from Lisa K. Jennings ( Jennings and White 1998 ). LIBS epitope expression was determined as described previously ( Luo et al. 2003 ). In brief, transiently transfected 293T cells were incubated with either 5 mM Ca 2+ or 1 mM Mn 2+ and 100 μM GRGDSP peptide at room temperature for 30 min. Anti-LIBS mAbs (AP5, D3, and LIBS6) was added to a final concentration of 10 μg/ml, and cells were incubated on ice for 30 min before staining with FITC-conjugated antimouse IgG and flow cytometry. LIBS epitope expression was determined and expressed as the percentage of mean fluorescence intensity of anti-LIBS mAbs relative to the conformation-independent mAb AP3 ( Luo et al. 2003 ). Structural model of integrin TM domain at resting state Model building was performed using the NMR structure of glycophorin A TM dimer (PDB code: 1AFO, model 1) as a template. The entire TM domains of α IIb and β 3 were aligned, with no gaps. Eighteen different alignments roughly compatible with the observed α–β interface orientation were submitted to the SWISS-MODEL server ( Peitsch 1996 ). For each model, the average Cβ–Cβ or Cβ–Gly Cα atom distance between residues that formed disulfides at greater than 80% efficiency (Trp968–Val696, Val969–Val696, Val971–Leu697, Gly972–Leu697, and Gly972–Val700) was calculated. The alignment where α IIb sequence W968/VLVG and β 3 sequence V696/LLSV were aligned with glycophorin A sequence G79/VMAG in each monomer gave the lowest root mean square distance (4.8 Å) and thus was chosen as the final model. Models for clusters 11 and 12 were kindly provided by the authors of Gottschalk et al. (2002) and subjected to the same analysis for Cβ–Cβ and Cβ–Gly Cα atom distances.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC423134.xml
514571	A dual function fusion protein of Herpes simplex virus type 1 thymidine kinase and firefly luciferase for noninvasive in vivo imaging of gene therapy in malignant glioma	Background Suicide gene therapy employing the prodrug activating system Herpes simplex virus type 1 thymidine kinase (HSV-TK)/ ganciclovir (GCV) has proven to be effective in killing experimental brain tumors. In contrast, glioma patients treated with HSV-TK/ GCV did not show significant treatment benefit, most likely due to insufficient transgene delivery to tumor cells. Therefore, this study aimed at developing a strategy for real-time noninvasive in vivo monitoring of the activity of a therapeutic gene in brain tumor cells. Methods The HSV-TK gene was fused to the firefly luciferase ( Luc ) gene and the fusion construct HSV-TK-Luc was expressed in U87MG human malignant glioma cells. Nude mice with subcutaneous gliomas stably expressing HSV-TK-Luc were subjected to GCV treatment and tumor response to therapy was monitored in vivo by serial bioluminescence imaging. Bioluminescent signals over time were compared with tumor volumes determined by caliper. Results Transient and stable expression of the HSV-TK-Luc fusion protein in U87MG glioma cells demonstrated close correlation of both enzyme activities. Serial optical imaging of tumor bearing mice detected in all cases GCV induced death of tumor cells expressing the fusion protein and proved that bioluminescence can be reliably used for repetitive and noninvasive quantification of HSV-TK/ GCV mediated cell kill in vivo . Conclusion This approach may represent a valuable tool for the in vivo evaluation of gene therapy strategies for treatment of malignant disease.	Background Treatment with the suicide gene/ prodrug activating system herpes simplex virus type I thymidine kinase/ ganciclovir (HSV-TK/ GCV) is highly efficient in animal models of malignant glioma [ 1 - 3 ]. In contrast, clinical trials employing the HSV-TK/ GCV system and a retroviral vector have demonstrated only a limited effect in glioblastoma patients [ 4 - 8 ], implying that transfer and distribution of the transgene in human brain tumors were very low in vivo and differed obviously from the findings in animal experiments. Presently, the standard method for assessing delivery of therapeutic transgenes to tumors relies on ex vivo analysis of explanted tumor tissue [ 7 , 9 , 10 ]. Time course analysis of transgene expression thus requires a multitude of animals to be sacrificed. In the past few years, noninvasive imaging techniques such as positron emission tomography (PET), magnetic resonance imaging, and optical imaging methods using fluorescence and bioluminescence were introduced and increasingly used for temporal and spatial monitoring of transgene expression [ 11 - 13 ]. Bioluminescence imaging (BLI) using luciferase ( Luc ) from the North American firefly Photinus pyralis as a reporter has several advantages compared to other imaging methods: (1) the technique is very sensitive (possibly 10 -15 – 10 -17 mole of luciferase/L are detectable in vivo , [ 13 ]) and detects tumor cells at a stage where radiography and PET cannot [ 14 , 15 ], (2) bioluminescence imaging using a cooled CCD camera does not require great technical expertise and (3) it is faster and less expensive than many other imaging techniques. Furthermore, in contrast to fluorescence imaging, where autofluorescence may interfere with the signal of interest [ 13 ], background luminescence is negligible. This study aimed at generating a sensitive tool for noninvasive in vivo monitoring of the activity of a therapeutic transgene by fusing the bioluminescent reporter gene Luc to the bioactivating "suicide" gene HSV-TK . We investigated whether this fusion construct could be used to monitor HSV-TK mediated cytotoxicity in malignant glioma by serial optical imaging in vivo . Noninvasive real time evaluation of localization, activity and persistence of a therapeutic gene in living animals may represent an important step towards optimization of gene therapy protocols. Methods Vector construction The HSV-TK cDNA from the retroviral vector G1Tk1SvNa ([ 16 ], kind gift from E. Otto, GTI Inc., Gaithersburg, MD) and the "humanized" firefly luciferase ( Luc ) gene from the pGL3 vector (Promega) were ligated into pCDNA 3.1(-) (Invitrogen). For the fusion construct, EGFP in the pEGFPLuc vector (BD Biosciences) was exchanged for HSV-TK cDNA, which had been amplified from G1Tk1SvNa by PCR. The resulting HSV-TK-Luc fusion gene contained a humanized form of the firefly Luc gene to ensure high expression in mammalian cells [ 17 ]. The full length HSV-TK cDNA was inserted in frame upstream of the Luc cDNA, and both genes were separated by a linker sequence of 33 nucleotides. All transgenes were expressed under the control of the CMV promoter. The correct sequence of the fusion construct HSV-TK-Luc was confirmed by DNA sequencing. Cell culture and transfection The human glioblastoma cell lines U87MG, T98G, LN18, U343, LN-Z308 and human embryonic kidney 293 cells were cultured under standard conditions. Cells were seeded in 6-well plates at a density of 3 – 5 × 10 5 cells/ well 16 to 24 h prior to transfection. Cells were transfected under serum-free conditions with the indicated amounts of DNA and Lipofectamine (Invitrogen) according to the manufacturer's protocol. For selection of stable clones transfected cells were replated at low density 48 h after transfection and incubated with 1 mg/ml (final concentration) geneticin (Calbiochem, Bad Soden, Germany) for 4 weeks. Colonies were picked and analyzed for transgene expression. Cytotoxicity assay Transiently or stably transfected U87MG cells were seeded at 4 × 10 3 cells/ well in a 96-well plate. GCV was added at final concentrations of 0 – 10 μg/ml and cells were incubated at 37°C/ 5% CO 2 for 4 days. MTT (Sigma, Deisenhofen, Germany) was added at a final concentration of 0.5 mg/ml for 2 h. Absorbance was measured in a microplate reader (Victor2, Perkin Elmer Life Sciences, Turku, Finland) at 590 nm (reference 660 nm). Experiments were performed in quadruplicates and repeated at least twice. Results are reported along with the standard deviation (SD). Cell culture assays for luciferase activity Transiently transfected U87MG cells were lysed in CCLR lysis buffer (Promega) 2 days after transfection. Stably transfected cells were lysed in the same buffer when they had reached ~90% confluence. Protein content of all cell lysates was determined by the Bradford Protein assay (Bio-Rad, Munich, Germany). Equal amounts of protein were analyzed luminometrically for luciferase activity with a microplate reader (Victor2) using the Luciferase Assay System reagent (Promega). All experiments were repeated at least twice and mean values are reported along with the SD. For bioluminescence imaging of intact cells HSV-TK-Luc expressing U87 glioma cells were transferred to a black microtiter plate in order to minimize light scattering, and MTT assay was performed in quadruplicates as described above. On day 4 after addition of GCV, D-Luciferin was added to a final concentration of 500 μM to the culture medium. Cells were placed in a dark box and light emission was imaged using a cooled CCD camera (Visiluxx Imager, Visitron). Light emitted from a region of interest (ROI) drawn over each well was quantified and mean values from quadruplicate measurements were compared with MTT results. Immunohistochemistry and Hematoxylin-Eosin (HE) staining Immunohistochemistry on paraffin sections using a rabbit polyclonal anti-Luc antibody (CR2029RAP, Europa Bioproducts) was performed essentially as described by Lee et al [ 18 ]. HE staining was performed according to standard protocols. Animal experiments All animal protocols were approved by the Animal Care and Use Committee at Martin-Luther-University Halle-Wittenberg. Six week old male NMRI nu/nu mice (Charles River) were injected s.c. at four sites, each with 2 × 10 6 human U87MG glioma cells stably expressing the HSV-TK-Luc fusion protein. When xenografts had reached a size of ~5 mm in diameter, in general on days 7 to 9 post tumor implantation GCV therapy was initiated. Mice were injected twice daily i.p. with 30 mg/ kg GCV for 14 days. Control mice with xenografts (n = 3) received saline injections. Tumor size was measured every 2 to 4 days by caliper. Tumor volume was calculated according to the formula 0.52 × width 2 × length. Bioluminescence imaging For BLI animals were anesthetized with ketamine/xylazine and injected i.p. with 150 mg/ kg D-Luciferin. Approximately 8 minutes after D-Luciferin injection mice were placed in a dark box and a grayscale image was acquired at low light (exposure time 2 seconds). Bioluminescence was measured in the dark by a CCD camera cooled to -120°C (VisiLuxx Imager), using an acquisition time of 15 min and binning 6. Bioluminescent signals were displayed in pseudocolors and superimposed on the grayscale image using Metamorph software (Visitron). Mice receiving GCV were imaged at least on days 7, 15, 22, 29, and 56 post tumor implantation (corresponding to start and day 8 of GCV therapy, as well as days 1, 8, and 35 after end of GCV therapy), while untreated control animals were subjected to BLI on days 7, 22, 29 and 35. In each animal a region of interest (ROI) was drawn over a single tumor or over all tumors as indicated in the text. Integrated as well as maximum light units (= counts) within this area were calculated after background subtraction. Final values are reported as the mean of the integrated or maximum counts obtained from all mice within one group. The CCD camera in use has a quantum efficiency approaching 90% at wavelengths between 550 and 770 nm, indicating that one photon is converted to ~0.9 electrons. One photoelectron corresponds to 4.52 counts. For serial quantification of light emission the conditions for image acquisition (e.g. exposure time, time between D-Luciferin application and image acquisition, stage position) were kept constant. Statistics Statistical analysis was performed using the ANOVA and Student's t test (SPSS and Microcal Origin Software). A p value of <0.05 was considered significant. Results Characterization of the HSV-TK-Luc fusion construct To achieve a strictly equimolar coexpression of a therapeutic and a reporter gene, the HSV-TK cDNA was fused in frame with the Luc cDNA in 2 ways: one fusion protein contained HSV-TK N-terminally, in the other construct Luc preceded the HSV-TK moiety. Both constructs were expressed under control of the CMV promoter. Several human glioma cell lines as well as 293 cells were transiently transfected with these constructs. In general, Luc activity was found to be up to 50-fold higher in cells expressing the HSV-TK-Luc construct compared to cells expressing the Luc-HSV-TK construct (data not shown). Therefore, all further studies were performed with the HSV-TK-Luc fusion construct. In order to characterize this fusion construct more thoroughly, both transient and stable transfection experiments were performed using the human U87MG glioma cell line (Figures 1 and 2 ). For transient transfection experiments, cells were transfected with 50 ng (~11.2 fmol) – 2 μg (~450 fmol) of plasmid DNA harboring either HSV-TK , Luc , or HSV-TK-Luc transgenes, respectively. As all 3 vectors were of equal size, equal amounts of DNA corresponded to equimolar amounts of plasmid. Cytotoxic activity as measured by MTT assay was compared to luminometrically determined light production and found to be tightly correlated in HSV-TK-Luc transfected cells (Figure 1 , R 2 = 0.99; p < 0.0001). Photon emission above background levels was not detectable in cells that had been transfected with HSV-TK only, while no cytotoxic activity was conferred to cells expressing only Luc. Figure 1 Cytotoxic and bioluminescent activity in U87MG glioma cells transiently transfected with different amounts of HSV-TK-Luc plasmid. (A) Cytotoxic activity as measured by MTT assay and (B) luciferase activity as determined luminometrically in cell lysates. Results are displayed as counts per second (cps)/ μg protein. (C) Linear regression analysis of cytotoxic activity plotted against luciferase activity for the different amounts of plasmid DNA. Results from 3 independent experiments were used. Figure 2 Comparison of the enzymatic activities of the HSV-TK-Luc fusion protein, HSV-TK, and Luc. U87MG cells were transiently transfected with 0.05 – 2 μg of HSV-TK-Luc , Luc , or HSV-TK plasmid. Cells transfected with equimolar amounts of DNA were analyzed for cytotoxic and bioluminescent activity. (A) Cytotoxic activity of cells transfected with HSV-TK-Luc or HSV-TK . For reasons of clarity only the graphs for 0.1 μg and 2 μg of transfected DNA are shown. (B) Luciferase activity in U87MG cells transfected with HSV-TK-Luc or Luc only. Results represent 3 independent experiments. Cytotoxic and Luc activity in cells transiently transfected with the HSV-TK-Luc fusion construct were also compared to the respective activities in cells transiently transfected with equimolar amounts (50 ng – 2 μg DNA) of HSV-TK or Luc alone. The overall cytotoxic activity of the fusion construct proved to be 60% of that measured in cells transfected with HSV-TK alone. Representative curves for 2 μg and 0.1 μg of transfected DNA are shown in Figure 2A . Luc activity of the fusion protein was also lower compared with native Luc: light production in cells transfected with HSV-TK-Luc was 22% of that seen in cells transfected with Luc only (Figure 2B ). A tight linear correlation of bioluminescence to cell kill was achieved with the fusion protein, suggesting that light emission can indeed be used as a measure for the cytotoxic effect of transgenic HSV-TK. Stable expression of the HSV-TK-Luc fusion gene in human glioma cells Having demonstrated in transient transfection experiments that Luc could be employed as a reporter for monitoring the therapeutic effect of HSV-TK, U87MG cell clones stably expressing the HSV-TK-Luc fusion protein were generated by selection of transfected cells with geneticin. Comparison of 18 of these clones for Luc and cytotoxic activity revealed a good correlation between both enzymatic activities (R 2 = 0.79; p < 0.001, data not shown). Enzymatic activity in the U87MG clone with both the highest Luc and HSV-TK activity was compared with U87MG clones expressing unfused HSV-TK or Luc. Cells stably expressing HSV-TK did not luminesce upon addition of D-Luciferin while Luc expressing cell clones were resistant to GCV mediated cell killing (data not shown). The dual function fusion protein compared favorably to the respective clones with the highest HSV-TK or Luc activity. Light production in the HSV-TK-Luc expressing cell clone was ~41% of that seen in Luc expressing U87MG cells while cytotoxic activity of the HSV-TK-Luc labeled U87MG clone was ~84% of that seen with the most active HSV-TK expressing U87MG clone (data not shown). Photon emission determined luminometrically was found to be linearly correlated with cell number over a range of at least 5 orders of magnitude (R 2 = 0.99; p < 0.001, data not shown). Photon emission from as few as 500 intact cells expressing the fusion construct was detectable by the CCD camera while the lower detection limit for the Luc expressing U87MG cell clone was 125 cells. We further examined whether the cytotoxic activity of the HSV-TK moiety could be visualized by monitoring light emission from intact cells that had been treated with GCV at different concentrations. Signals captured by the CCD camera showed a close correlation to the cytotoxic effect as measured by MTT assay (Figure 3 , R 2 = 0.94; p = 0.029). These data demonstrate that both enzyme activities were also preserved in U87MG cells stably expressing the HSV-TK-Luc fusion construct. Figure 3 Correlation of light emission with cytotoxicity in intact U87MG glioma cells stably expressing the HSV-TK-Luc fusion construct and treated with GCV. (A) Cytotoxic activity as determined by MTT assay. (B) Bioluminescence imaging of quadruplicates of intact U87MG cells treated with the indicated amounts of GCV or left untreated (control). (C) Linear regression analysis of photon emission detected by the CCD camera plotted against cytotoxicity (R 2 = 0.94; p = 0.029). Correlation of HSV-TK with luciferase activity in vivo The above high expresser U87MG cell clone was used for xenograft experiments in nude mice. For sensitivity testing, 2 × 10 3 , 2 × 10 4 and 2 × 10 5 cells were injected s.c. on the back of the animals. Although not palpable, 2 × 10 4 cells expressing the fusion construct were detected by the CCD camera immediately after injection (= day 0), either when injected alone or mixed with 1.8 × 10 5 (90%) non-luminescent parental U87MG cells prior to injection, while 2 × 10 3 cells injected s.c. were not seen (data not shown). This high level of detectability by BLI proves the usefulness of the HSV-TK-Luc construct as a highly sensitive reporter in vivo. For therapeutic studies, mice received injections with 2 × 10 6 HSV-TK-Luc labeled U87MG cells at four different sites on the back and the flanks, respectively (Figure 4 ). When tumors had reached a size of ~5 mm in diameter, a bioluminescence image was acquired and GCV therapy was initiated (n = 7). GCV treatment did not cause any significant toxicity and treated mice displayed normal patterns of food intake and physical activity. Control animals (n = 3) received saline injections. Initial tumor volumes in all mice were 309 ± 37 mm 3 and light intensity units (= counts) measured on day 7 were 122961 ± 22155. Serial measurements (during and after GCV therapy) of tumor volumes and integrated light intensity units within a region of interest (ROI) including all tumors were plotted against each other (Figure 5 ). Within the 2 weeks of GCV treatment, all 7 mice showed a rapid decline in photon emission from their tumors (mean decrease: 92 ± 7%, Figure 5A ), which was accompanied by a somewhat slower decrease in tumor volume (65 ± 19%, Figure 5B ). A linear regression analysis of mean tumor volumes in treated mice on days 7, 15, 22, 29, and 56 post tumor implantation plotted against the respective mean integrated light units is displayed in Figure 6A . Light emission and tumor volumes correlated closely with each other (R 2 = 0.93; p = 0.008), thus confirming our cell culture data (Figures 1 and 3 ). Figure 4 Bioluminescence imaging of nude mice carrying HSV-TK-Luc expressing U87MG gliomas. (A) Serial images from a mouse with 4 s.c. xenografts treated with GCV from day 7 to day 21 post tumor implantation and (B) saline treated control mouse, sacrificed on day 35 post tumor implantation due to massive tumor growth. The largest tumor in this mouse on the upper right back has already become necrotic. The day 35 image is also displayed at a broader grayscale range for better visualization of tumor localization. Note that control tumors also showed decreased light emission and a reduction in tumor size within the first 3 weeks post tumor implantation. Figure 5 Comparison of (A) bioluminescence signals detected by the CCD camera and (B) tumor volumes in GCV-treated mice (n= 7, M1 – M7) harboring HSV-TK-Luc tagged U87MG glioma xenografts. GCV (60 mg/kg per day) was administered for 14 days starting at day 7 post tumor implantation. All mice were imaged at least on days 7, 15, 22, 29, and 56 post tumor implantation. BLI signals and tumor volumes at the beginning of therapy were set as 100%. Identical symbols in both graphs correspond to identical animals. Figure 6 Linear regression analysis. Light emission as determined by the CCD camera was plotted against tumor volume. Mean values for all animals in a group along with the S.E.M are reported. (A) GCV treated mice: mice (n = 7) were imaged at start of therapy, after 1 and 2 weeks of GCV treatment, and 1 and 5 weeks after end of GCV therapy (R 2 = 0.93, p = 0.008). In some mice additional images were acquired (Figure 5), but these were not included in this plot. (B) Saline treated control mice: these mice (n = 3) were imaged on days 7, 22, 29, and 35 and were sacrificed after the last BLI due to massive tumor growth (R 2 = 0.98, p = 0.010). Regarding therapeutic efficacy in these mice on an individual basis, photon emission and tumor volumes showed a significant correlation, with R 2 values ranging from 0.78 to 0.96 and p ranging from 0.004 to 0.047, except for one mouse (R 2 = 0.731; p= 0.065). In this mouse a significant correlation between light emission and tumor volume could be demonstrated, when tumor volumes were plotted against the maximum light emission within a ROI (R 2 = 0.81; p = 0.037) instead of integrated light units. In general, integrated light units within a ROI correlated closely with maximum light emission from this ROI: correlation coefficients (R 2 ) for all tumors in treated mice varied between 0.97 and 0.99, all p values were <0.003. Five weeks after end of GCV therapy (day 56) light emission was no longer detectable in 5 of the 7 GCV-treated mice, while in 4 of them small residuums at the tumor site were still visible. Two mice still showed very weak light emission from one of their flank tumors which also disappeared in subsequent imaging studies. All GCV treated mice survived and tumor recurrence was not observed until closure of the study at day 90 post tumor implantation. The 3 untreated control mice were imaged on days 7, 22, 29, and 35 post tumor implantation and had to be sacrificed on weeks 5 to 6 post cell injection due to massive tumor growth. Although 2 tumors with relatively strong light emission on day 7 post tumor implantation regressed within 4 weeks in one of the control mice, overall tumor growth in all control animals plotted against light emission from these tumors still showed a tight correlation (R 2 = 0.98; p = 0.010; Figure 6B ). Within 4 weeks, tumor volumes increased by ~11-fold while photon emission concomitantly rose ~6-fold. When tumors had become very large (>12–15 mm in diameter) further increase in light emission was much less than the increase in volume. This was mirrored by a less stringent linear correlation of BLI signal and tumor size in large tumors. The control mouse shown in Figure 4B serves as an example: on day 35 the tumor on the right upper back shows an attenuated bioluminescent signal although being the largest tumor. While linear regression analysis demonstrated a very good correlation of tumor volume to light emission for the other 3 tumors (R 2 = 0.99 and p = 0.002 for tumors on the back and the right flank; R 2 = 0.98 and p = 0.011 for the tumor on the left flank), R 2 was 0.90 (p = 0.050) for this large tumor. When serially determined maximum light emission was used for quantification in this particular tumor, R 2 dropped to 0.37 (p = 0.4). When control mice were sacrificed, tumors were explanted, and immediately reimaged. Bioluminescence imaging confirmed reduced light emission from hemorrhagic and necrotic areas in large tumors (Figure 7A ). Immunohistochemical analysis of these tumor regions using a polyclonal anti-Luc antibody also showed a relatively scarce positive staining of necrotic areas as compared to areas with strong photon emission (Figure 7B ). Figure 7 Ex vivo bioluminescence imaging and histological analysis of a large HSV-TK-Luc tagged U87MG glioma in a control mouse. (A) Bioluminescence image (exposure time 10 min) of the freshly explanted tumor after D-Luciferin injection in the mouse prior to sacrifice. The tumor was cut in the middle and placed with the cut side facing the CCD camera. One part of the tumor was obviously hemorrhagic while the other part looked vital. Photon emission displayed in pseudocolors precisely reflected the macroscopic findings. (B, a and b) HE staining of paraffin sections from the same tumor as seen in (A) vital tumor region (a); hemorrhagic and necrotic tumor area (b); (B, c and d) immunohistochemistry on corresponding sections using a polyclonal anti-Luc antibody; vital tumor area (c) and hemorrhagic and necrotic region (d) with only scarce positive staining. Original magnification × 400. Discussion This study demonstrates that firefly luciferase is a valuable tool for monitoring noninvasively the efficacy of the prodrug activating system HSV-TK / GCV in cell culture and in vivo . The HSV-TK-Luc fusion protein was successfully used in a brain tumor animal model for serial and sensitive real time quantification of the cytotoxic effect of HSV-TK by BLI. Correlation of enzymatic activities Fusion of two enzymes is the only way to guarantee stoichiometric, and thus correlated expression of both fusion partners. We chose this approach because coexpression of two separate transgenes from either one or separate promoters has been reported to result in severely impaired gene expression, e.g. due to inefficient internal ribosome entry site (IRES)-mediated translation [ 19 ] or to promoter interference [ 20 ]. The HSV-TK protein contains several nuclear targeting signals and is usually located predominantly in the nucleus [ 21 ]. The enzyme may form a homodimer, and it has been proposed that only dimeric HSV-TK is transported to the nucleus [ 21 ]. On the other hand, in the commercially available firefly Luc we have used, the peroxisomal targeting sequence present in wild type Luc has been removed to ensure strict cytosolic compartmentalization, and thus reliable reporter function [ 17 ]. Fusing both enzyme moieties together resulted in a protein with predominant localization in the cytosol, as shown by the immunohistochemical analysis of HSV-TK-Luc expressing glioma cells (Figure 7B ). In contrast, we have shown previously that fusion of the 27 kDa protein EGFP to HSV-TK allowed for predominant nuclear transfer of the enzyme while resulting in only minor loss of cytotoxic activity [ 22 ], suggesting that cytosolic localization and/ or reduced homodimer formation of the HSV-TK-Luc fusion protein may have some impact on its cytotoxic activity. A decrease in HSV-TK activity of up to 80% compared to unfused HSV-TK has also been observed by Ray et al. when fusing the enzyme to Renilla Luc [ 23 ]. N2A neuroblastoma cells harboring the fusion construct could be detected by PET and BLI in nude mice, but the cytotoxic activity of HSV-TK was not examined in the study. Renilla Luc activity in the above construct was found to be ~6 – 8-fold higher than seen with its unfused counterpart. As this enzyme is structurally unrelated to firefly Luc and has a lower molecular weight (36 kDa vs. 62 kDa), the study cannot be directly compared to our data. Notably, the authors mention that their attempt to fuse HSV-TK to firefly Luc resulted in a "poorly active" fusion protein [ 23 ]. Recently, the generation of several triple fusion proteins for imaging with different modalities was reported by two groups [ 24 , 25 ]. These triple reporters consisted of wild type or mutated HSV-TK, a fluorescent protein (EGFP, DsRed2, or monomeric red fluorescent protein (mRFP)) and firefly Luc [ 24 , 25 ] or Renilla Luc [ 25 ], respectively. Both groups showed that such triple fusion constructs could be used for simultaneous imaging in vivo with bioluminescence, fluorescence, and PET. Cytotoxicity generated by enzymatic conversion of prodrug by HSV-TK was however not measured in either of the above studies. Ponomarev et al. [ 24 ] did not present data on the correlated expression of the three reporters within the triple fusion protein (HSV-TK-EGFP-Luc), nor were the activity levels of the different fusion partners compared to those of their unfused counterparts. Despite these limitations, the study confirms that Luc remains functional if fused N-terminally to other proteins, and that enzymatic activity is sufficient for in vivo BLI. Ray et al. [ 25 ] compared the enzymatic and fluorescent activities of several triple fusion constructs transiently transfected into 293 cells to the respective activities of the unfused proteins. The described fusion proteins contained either Renillla or firefly Luc at the NH 2 -terminus, followed by a fluorescent protein and a mutated HSV-TK enzyme. This orientation of the fusion partners as well as the use of mutated HSV-TK optimized for use with PET limits the direct comparison of the presented data to our results. Bioluminescent activity of the 4 fusion constructs containing firefly Luc was reduced to 22 – 63% of the activity of unfused Luc, which is similar to our findings when expressing HSV-TK-Luc in U87MG glioma cells. One of the 4 constructs (Luc-mRFP-mutant HSV-TK) fully retained HSV-TK PET reporter activity while in the others HSV-TK activity (as assessed by intracellular radiotracer accumulation) was reduced to 30 – 61% of the activity of the corresponding unfused enzyme. This is in line with our findings when expressing HSV-TK-Luc transiently in U87MG glioma cells. Although it seems attractive to perform BLI with different luciferase enzymes, the following facts argue in favor of firefly Luc instead of Renilla Luc: (1) light emission of Renilla Luc peaks at 480 nm and thus shows only limited tissue penetration, (2) coelenterazine, the Renilla Luc substrate is prone to autoluminescence, resulting in high background if injected i.p. [ 26 ], (3) coelenterazine transport (and thus the bioluminescent signal) is modulated by the multidrug resistance MDR1 P-glycoprotein, a protein known to be overexpressed in cancer cells [ 27 ], and (4) coelenterazine is much more expensive than D-Luciferin. Iyer et al. [ 28 ] examined noninvasive imaging using PET and BLI in CD-1 mice after simultaneous i.v. delivery of the HSV-TK and Luc genes residing on different plasmids. The time point of peak activity of both reporters differed by ~19 hours, most likely due to differences in half lives of the two enzymes. This finding supports our approach of expressing both enzymes as one molecule as this should greatly diminish differences in protein stability. Attenuation of both enzymatic activities is most likely a result of steric hindrance and might be substantially reduced by selecting another linker sequence. Longer intervening sequences as well as introduction of flexible polyglycine linkers may contribute to an increase in enzyme activity [ 23 , 29 ]. Recently, De et al. [ 15 ] introduced into a lentiviral vector a mutant HSV-TK (optimized for PET imaging) and firefly Luc, separated by an IRES sequence. N2a neuroblastoma cells stably transduced with this construct and implanted s.c. into nude mice showed correlated expression of both enzymes as verified by PET and BLI (R 2 = 0.86). In contrast to our study, GCV treatment in vivo resulted in a decrease in light emission while the tumors continuously grew in size. Most likely, this reflects the relatively poor cytotoxic activity of the mutant HSV-TK used in these experiments, implying that engineered HSV-TK optimized for use as a PET reporter may not retain its full cytotoxic activity when substrates such as GCV are used. Data on the cytotoxic potential of the virus construct in cell culture were not presented. Cytotoxic effects of the fusion construct We show here for the first time that a HSV-TK-Luc fusion protein in conjunction with GCV treatment can confer a curative effect on glioma bearing animals. While HSV-TK-Luc expressing glioma cells in culture were not killed completely when using GCV concentrations of up to 10 μg/ml, xenografts consisting of these cells were fully eliminated in all GCV treated mice. It has been shown by several groups that HSV-TK expressing tumor cells can elicit an antitumor immune reaction even in immunocompromised animals such as nude mice, most likely mediated by natural killer (NK) cells, activated in vivo by GCV induced cell killing [ 30 , 31 ]. We suggest that such an immune response may also have contributed to the elimination of HSV-TK-Luc expressing U87MG glioma cells in GCV-treated mice. This issue could be further addressed by in vivo depletion of NK cells through administration of appropriate antibodies [ 30 ]. Optical detection of transgene expression Our study used a subcutaneous glioma model for "proof of concept" to allow for simultaneous bioluminescence imaging and measurement of tumour size by caliper. HSV-TK-Luc expressing U87MG glioma cells were also detected by the CCD camera after inoculation of 2 × 10 6 cells intracerebrally in nude mice (data not shown), confirming the high sensitivity of BLI. Indeed, it has already been demonstrated in a murine orthotopic pituitary tumor model that bioluminescent light can travel through skull [ 32 ]. The cooled CCD camera system we used allows for quantification of emitted light. Some authors suggested that the level of transgene expression could be more reliably quantified by maximum light emission than by integrated light units within a ROI [ 33 ]. Although quantification is important if strategies for transgene delivery are to be examined, a systematic comparison of these two parameters in BLI has not been published until now. This prompted us to analyze these parameters in more detail in our study. If maximum and integrated light units within a ROI over single tumors were compared, we consistently found that both parameters tightly correlated with tumor size in tumors up to ~1 cm in diameter. In larger tumors (maximum diameter examined = 2 cm) the increase in size was in general less closely correlated with both integrated and maximum light units, but light emission from a ROI drawn over the entire tumor was still far more accurately mirroring tumor growth than maximum light units emitted from this region. With the increase in tumor thickness, maximum light emission from the tumor core is reduced due to necrosis, light scattering, and reduced supply of oxygen and D-Luciferin to tumor cells. On the other hand, the increase in tumor length and width is better reflected by light signals integrated over the entire tumor area, while a concomitant change in maximum light signal does not necessarily have to occur. Therefore, integrated light signals emitted from tumor ROIs seem to be the measure of choice for serial imaging of transgene expression in growing tumors. The fact that tumor volume and photon emission are less tightly correlated in large tumors as compared to smaller ones implies that photon emission reflects mainly the presence of viable tumor cells within a tumor and is a more precise measure for cytotoxic efficacy than tumor size, as has also been suggested by others [ 34 , 35 ]. Herpes simplex virus type I thymidine kinase has also been used as a reporter gene for monitoring therapeutic success with PET [ 11 , 36 ]. However, using optical imaging methods to quantify transgene expression has several advantages. The much greater sensitivity of BLI as compared to PET (10 -15 – 10 -17 vs. 10 -11 – 10 -12 mole/L of reporter probe are detectable, [ 13 ]) in combination with very low background signals render this imaging method particularly attractive for studying therapeutic strategies in animal models of cancer. In addition, high costs, the need for a radiopharmacy and considerable technical experience currently preclude widespread application of PET in experimental gene therapy of cancer. Conclusions We showed that therapeutic efficacy of a suicide gene/ prodrug activating system can be accurately monitored in vivo by BLI, when the bioluminescent reporter luciferase is fused in frame to the therapeutic gene HSV-TK . We used a clonal human glioma cell line stably expressing the HSV-TK-Luc fusion construct, thus guaranteeing high level transgene expression. Despite the somewhat attenuated activity of both fusion partners, a high degree of cytotoxicity by HSV-TK mediated GCV bioactivation as well as strong bioluminescent signals upon administration of D-luciferin were consistently demonstrated. In order to mirror more closely in vivo gene therapy of malignant brain tumors, experiments are underway to insert the HSV-TK-Luc fusion gene (and an improved version of it) into appropriate viral vectors and subsequently use them for treatment of orthotopically established gliomas in mice. Serial assessment of transduction levels, transgene localization and time course of fusion gene expression in living animals by BLI can aid in developing more potent gene therapy vectors for treatment of malignant glioma. List of abbreviations CCD, charged coupled device; CMV, cytomegalovirus; cps, counts per second; EGFP, enhanced green fluorescent protein; GCV, ganciclovir; HSV-TK, herpes simplex virus type 1 thymidine kinase; Luc, luciferase; mRFP, monomeric red fluorescent protein, PET, positron emission tomography; ROI, region of interest; SD, standard deviation, SEM, standard error of the mean. Competing interests None declared. Authors contributions AS constructed the plasmids, performed the animal experiments together with CT and set up the in vitro assays. CT and SJ participated in the cell culture experiments and enzymatic assays. SJ and AS carried out the immunohistochemical studies. NGR and AS designed the experiments and evaluated the data. All authors have read and approved the manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC514571.xml
517722	Enhanced diagnostic immunofluorescence using biopsies transported in saline	Background The demonstration of tissue-bound immunoreactants by direct immunofluorescence microscopy (DIF) is a valuable parameter in the diagnosis of various autoimmune and immunecomplex-mediated skin diseases. For preservation of tissue-bound immunoreactants, biopsies are usually fresh-frozen in liquid nitrogen or transported in Michel's fixative. But even optimally preserved tissue specimens are no guarantee for the correct diagnosis by DIF, especially when weak to moderate IgG fluorescence of the epidermal basement membrane zone is involved. In such cases false negative results are easily obtained due to the relatively high dermal "background" fluorescence produced by polyclonal anti-human IgG fluorescein conjugates. Methods In the present study we have compared the use of normal saline (0.9% NaCl) with liquid nitrogen and Michel's fixative as transport medium for skin biopsies. From 25 patients with an autoimmune skin disease (pemphigus, pemphigoid, lupus erythematosus and vasculitis) four matched skin biopsies were obtained and transported in either saline for 24 and 48 hours, liquid nitrogen, or Michel's fixative for 48 hours. Results Direct IF microscopy showed significant reduction of background fluorescence (p < 0.01) and relatively enhanced desired specific (IgG, IgA) staining in biopsies transported in saline. A conclusive or tentative IF diagnosis was reached in 92% after 24 h saline, 83% after 48 h saline, 68% after freezing in liquid nitrogen, and 62% after 48 h Michel's medium (n = 25). Conclusions We conclude that transporting biopsies without freezing in normal saline for 24 hours is an adequate and attractive method for routine IF diagnosis in autoimmune and immune complex-mediated dermatoses. The superior results with saline incubation are explained by washing away of IgG background in dermis and epidermis.	Background The demonstration of tissue-bound immunoreactants by direct immunofluorescence microscopy (DIF) is a valuable parameter in the diagnosis of various autoimmune skin diseases[ 1 ]. Reliable diagnosis by DIF not only requires an experienced observer, but first of all proper skin (or mucosal) biopsies with well-preserved immunoreactants. For the latter purpose biopsies are usually snap-frozen in liquid nitrogen or, alternatively, placed in Michel's fixative that facilitates transport of biopsies from outside hospitals [ 2 - 6 ]. But even representative and optimally preserved tissue specimens are no guarantee for the correct diagnosis by DIF, especially when weak to moderate desired specific staining (DSS) of the epidermal basement membrane zone (BMZ) is involved [ 7 ]. In such cases, specific IgG fluorescence is easily masked by the relatively high dermal "background" fluorescence produced by polyclonal anti-human IgG fluorescein conjugates. The background fluorescence, consisting of both undesired specific staining (USS) and non-specific staining (NSS), largely determines the signal-to noise ratio [ 7 ]. This ratio in turn determines the detection threshold and thereby the diagnostic sensitivity of the DIF technique. A low ratio for IgG resulting from weak DSS and high USS plus NSS will undoubtedly yield false negative cases. So far, the signal- to noise ratio in diagnostic IF has received little attention. The present study was initiated by the unexpected finding of significant increase of the signal-to noise ratio in a skin biopsy submitted for DIF and accidentally kept overnight in normal saline. The biopsy, obtained from a patient suspect of pemphigoid, showed substantial reduction of IgG background fluorescence and relatively bright specific IgG fluorescence along the BMZ. This finding encouraged us to compare diagnostic results of DIF in matched skin biopsies using standard snap-freezing, Michel's fixative and normal saline. Methods Patients The 25 patients included in this study were selected on the basis of previously confirmed positive direct immunofluorescence (IF) in skin biopsies transported in liquid nitrogen. The final diagnosis was reached by clinical, routine laboratory, histological and direct IF findings. In case of bullous autoimmune diseases, serum samples were characterized by indirect IF on 1.0 M NaCl-split skin [ 8 , 9 ], immunoblotting [ 10 ], and ELISA (desmoglein 1 and 3) [ 11 ]. The patients had one of the following diagnoses: bullous pemphigoid (BP; n = 5); mucous membrane pemphigoid with skin involvement (MMP; 1); linear IgA dermatosis (LAD; 1), anti-epiligrin cicatricial pemphigoid (AECP; 1); epidermolysis bullosa acquisita (EBA; 1); dermatitis herpetiformis (DH; 1); pemphigus vulgaris (PV; 3); pemphigus foliaceus (PF; 3); subacute and systemic lupus erythematosus (LE; 5); and small vessel IgA vasculitis (4). Skin biopsies and processing From each patient four skin specimens were obtained by punch biopsy (4 mm) using lidocaine as the local anaesthetic. The biopsies were taken from perilesional skin within an area of 2 cm 2 to minimize the risk of local variation of immunoreactants. The matched skin specimens from each patient were immediately placed in one of the following transport media: (a) liquid nitrogen, (b) Michel's fixative 48 hours with appropiate pH, (c) saline 24 hours and (d) saline 48 hours. We used 5 ml screw-capped polypropylene vials for transporting biopsies in Michel's fixative and saline. Freezing Biopsies were placed in aluminum vials, snap-frozen in liquid nitrogen and stored at -80°C until further processing within two weeks for DIF (see below). Fixative Michel's fixative and buffer solution were prepared monthly according to the original description. 1 Biopsy specimens were kept in 5 ml Michel's fixative for 48 hours (Mi48) at room temperature, followed by washing for 30 minutes in Michel's buffer solution. The specimens were then blotted on filter paper to remove excess moisture, and stored at -80°C until further processing. Saline We used normal saline solution (0.9% NaCl in aqua dest.) without addition of calcium or magnesium. Skin specimens were kept in 5 ml saline solution for 24 hours (S24) and 48 hours (S48) at room temperature. Preliminary experiments with saline time of 6 hours did not result in improvement of the signal-to noise ratio. The specimens were then blotted on filter paper and stored at -80°C until further processing for DIF. Direct immunofluorescence microscopy For comparative purposes, matched skin specimens of each patient were processed for direct IF microscopy at the same occasion. Cryosections of 4 μm thickness were mounted on polysine™ glass slides, air-dried for 30 min before a fan, and encircled with a hydrophobic emulsion (PAP-pen; DAKO; Glostrup). The sections were then stained for 30 min in a moist chamber at room temperature, using fluorescein (FITC)-labeled, Fc-specific goat F(ab') 2 antibodies against human IgG, IgA and IgM (Protos Immunoresearch, Burlingame CA), and rabbit antibodies against human C3c and fibrinogen/fibrin (DAKO; Glostrup). Proper conjugate dilutions were made in phosphate-buffered saline (0.01 M PBS, pH 7.3) supplemented with bovine serum albumin 1%. After washing in 1000 ml PBS for 30 min, the sections were coverslipped under fresh PBS/glycerol (50% v/v). The slide preparations were kept at 4°C until microscopic examination within two days. The sections were examined with a Leica DMRA microscope (Leica, Wetzlar, Germany) for selective incident light fluorescence using a xenon arc (XBO 75W) as light source and PL Apo ×40/0.80 dry objective. The fluorescent staining was graded as follows: - (negative), ± (doubtful), + (weak), ++ (moderate), +++ (bright). The desired specific staining (DSS) of the following target structures was scored 12;13 .: (a) epidermal in vivo ANA, (b) epidermal intercellular spaces, (c) basement membrane zone (dermo-epidermal junction), and (d) blood vessel walls. In addition, the background staining (USS plus NSS) of the upper dermis was scored. All sections were read blindly by the same experienced observer (MCJMdJ). The diagnosis made by direct IF was regarded as conclusive if the DSS score of the relevant target structure was at least weak but definite (Table). The diagnosis was regarded as tentative in case of weak staining that was not consistently distributed at the relevant target structure. A case was regarded as non-diagnostic if target structures showed negative to doubtful DSS scores. Statistical analysis of IgG and IgA background fluorescence in matched biopsies was done by the McNemar test. Results A total of 95 biopsies from 25 patients were examined; three biopsies were missing, and two biopsies proved unsuitable at cryosectioning. Cutting of 4 μm cryosections was easiest with biopsies transported in saline and hardest with biopsies transported in Michel's fixative. Biopsies kept in saline for 24 and 48 hours showed statistically significant reduction of background fluorescence in the dermis, especially with IgG, as compared with fresh-frozen and fixed biopsies (p < 0.01). After 24 hours, this resulted in enhanced signal-to noise ratios and accordingly more easy detection of immunoreactants at target structures, in particular the epidermal basement membrane zone (BMZ) and subepidermal blood vessel walls (Fig. 1 ). In comparison, fresh-frozen and fixed biopsies showed a relatively poor signal- to noise ratio for IgG (and IgA). In these biopsies, weak (+) specific fluorescence of IgG at the BMZ or IgA in vessel walls was found to be masked easily by relatively high background staining. Biopsies kept for 48 hours in saline showed a variable degree of diminution of specific staining, and tended to become negative in case of weak (+) specific fluorescence. The IgG fluorescence of epidermal in vivo ANA, present in fresh-frozen and fixed biopsies of two cases with (S)LE, became negative in saline biopsies (both 24 h and 48 h). In general, biopsies with moderate to bright (++/+++) specific fluorescence remained positive in all transport media. The reduced background fluorescence in saline biopsies occasionally revealed doubtful to weak focal IgG fluorescence of the BMZ that was regarded as non-relevant. Furthermore, we observed dermo-epidermal split formation in saline biopsies, not present in matched fresh-frozen and fixed biopsies. The extent of split formation varied among saline biopsies and increased with time (48 h > 24 h). In cases with pemphigoid, IgG was found predominantly at the epidermal side of splits, in contrast with e.g. SLE where IgG was found at the dermal side (Fig. 2 ). In case an artificial split is induced because of saline incubation a BMZ signal stand more out because of the dark background of the blister cavity (Fig. 2 ). The overall morphology in saline biopsies was quite fair and largely sufficient for the purpose of diagnostic IF microscopy. Figure 1 Comparison of direct immunofluorescence in cryosections of matched skin biopsies transported in liquid nitrogen, Michel's fixative or saline. Note the substantially reduced background fluorescence in saline-transported biopsies. Pemphigus foliaceus showing characteristic IgG fluorescence at the epidermal intercellular space. Additional granular IgG staining at the basement membrane zone (arrow) stands out most clearly in saline transported biopsy. (obj. ×20) Mucous membrane pemphigoid with skin involvement showing weak linear IgG fluorescence at the basement membrane zone that is only visible in the saline transported biopsy (arrow). (obj. ×20) Lupus erythematosus showing granular IgG fluorescence at the dermo-epidermal junction. Additional IgG staining of subepidermal vessel walls is best visible in the saline-transported biopsy. (obj. ×20) Vasculitis showing fine-granular IgA fluorescence in subepidermal capillary walls (arrows) which is most distinct in the saline-transported biopsy. (obj. ×40) Figure 2 Direct immunofluorescence (IgG, combined with transmitted light) in saline transported skin specimen of lupus erythematosus. After 48 hours in saline there is subepidermal split formation, not present in fresh-frozen (N 2 ) and fixed (Mi48) skin. Note the still obvious granular IgG fluorescence at the dermal side of the split. (obj. ×40) The diagnostic results of direct IF in matched biopsies are summarized in Table I . By interpreting these data it should be realized that the minority of cases (20%) showed bright (+++) specific fluorescence in standard frozen biopsies, whereas the majority (52%) showed only weak to moderate (+/++) specific fluorescence of the relevant target structure(s). Two originally positive cases, one pemphigus and one IgA vasculitis became doubtful or negative (non-diagnostic) in all transport media. The highest rate of conclusive cases by direct IF was obtained in biopsies kept in saline for 24 hours (S24, 84%), and the lowest in fixed biopsies (Mi48, 50%). The case of mucous membrane pemphigoid with weak IgG (+) and IgA (+) fluorescence at the BMZ was obvious in saline biopsies (S24, S48) but non-diagnostic in matched fresh-frozen and fixed biopsies. The highest non-diagnostic percentage was obtained in fixed biopsies (32%) and the lowest in S24 saline biopsies (8%). In one case, classified as misdiagnosed, the fresh-frozen biopsy led to the diagnosis of LAD as IgA (+) and C3c (+) were the only immunoreactants observed, whereas the matched fixed and saline biopsies showed additional linear IgG (+/++) fluorescence at the BMZ (suggestive of mixed IgG/IgA pemphigoid). After correction for the missing biopsies, the results were only statistically significant comparing Mi and S24 (p < 0.05). Other comparisons (N2 versus Mi, S24 and S48 or Mi versus S48 or S24 versus S48) were not significant. Table 1 Results of direct immunofluorescence (DIF) of matched skin biopsies transported in different media. N2 Mi48 S24 S48 Diagnosis by DIF DSS n = 25 n = 22 § n = 25 n = 23 § a. conclusive +/+++ 14 (56%) 11 (50%) 21 (84%) 16 (70%) b. tentative ±/+ 5 (20%) 4 (18%) 2 (8%) 3 (13%) c. non-diagnostic -/± 5 (20%) 7 (32%) 2 (8%) 4 (17%) d. mis-diagnosed 1 (4%) - - - N 2 , snap-frozen specimens in liquid nitrogen; Mi48, specimens in Michel's fixative for 48 hours; S24 and S48, specimens in saline for 24 and 48 hours respectively; DSS, desired specific staining; n, number of cases § Two S48 and three Mi48 matched biopsies were either lacking or considered unsuitable. Discussion Perilesional skin biopsies kept in saline for 24 hours yielded a higher diagnostic rate in direct IF than fresh-frozen biopsies in liquid nitrogen or biopsies kept in Michel's fixative. Several authors have described the positive effect of saline in increasing the sensitivity of IF analysis. Judd and Lever showed that skin biopsies stored for 24 hours in 0.15 M phosphate buffered saline prior to freezing gave a very high incidence of positive readings in direct IF [ 14 ]. Similarly, the use of 1.0 M NaCl split skin as a diagnostic tool for direct and indirect IF has been reported to increase the sensitivity of these methods [ 9 , 15 - 17 ]. It has been suggested that the increase of IF sensitivity by saline incubation is due to improved exposure of epitopes and/or by a decrease of background staining [ 16 ]. Our data suggest that the improved DIF sensitivity in saline biopsies is primarily due to decreased background staining resulting in better image contrast (signal-to noise ratio). We know that our visual perception is sensitive for light contrast and not for intensity [ 18 ]. The staining intensity perceived of a given specific fluorescent signal is strongly correlated with the intensity of the background (compare looking at the stars in daylight and at night; the intensity is the same, but seems multiplied at night). In this respect, IgG (and IgA) fluorescence in skin tissue is hampered by relatively strong background fluorescence in the dermis that may mask weak specific fluorescence at the BMZ and in vascular walls. Saline appears to reduce this background staining, resulting in relative increase of desired specific staining and thereby enhanced diagnostic sensitivity. A disadvantage of saline is the limited time of transport (24 h) for consistently reliable results. If biopsies are kept longer than 24 hours in saline, decreased fluorescence of tissue-bound immunoreactants may be encountered, although we have observed bright specific fluorescence of the BMZ in biopsies kept in saline for at least 5 days. Michel's fixative seems to have a similar limitation: Skeete and Black found that biopsies stored in this fixative should be received within 1 day of biopsy for consistently reliable results [ 4 ]. The second disadvantage of saline is the loss of at least some epidermal in vivo ANAs, possibly due to extraction or degradation of nuclear antigens. Another disadvantage of saline might be, from a histopathological point of view, morphological disturbances such as hydropic degeneration [ 19 ], and splitting at the dermo-epidermal junction, not found with Michel's fixative [ 6 ]. That is why saline is not suitable for antigen mapping in the diagnosis of genetic diseases [ 20 ]. Neither are biopsies kept in saline suited for immuno-electron microscopy [ 5 , 6 , 20 ]. However, for the diagnosis of autoimmune and immune complex-mediated diseases by DIF, it is not optimal morphology that counts, but the low detection threshold of immunoreactants. In this regard, (artificial) dermo-epidermal split-formation may add value to the method, rather than being a problem, by darkening of the juxtaposed background and mapping of the linear epidermal BMZ deposition [ 21 ]. Besides the diagnostic benefit, the preference would also go to the use of saline because it is a ready available, inexpensive, and convenient transport medium, and it certainly improves cutting properties of skin biopsies compared to biopsies fixed in Michels' medium. Saline can be used as standard medium at room temperature for express postal delivery of IF biopsies to the laboratory, if delivery is guaranteed within 24 hours. Transport of biopsies by express postal delivery or in-house airtube post is much more cost-effective than courier delivery necessary for biopsies transported in liquid nitrogen. If it is expected to tide over a longer period we advise to store the biopsy in saline for 24 hours and then to place it in Michel's fixative for further transport. Practically, place the biopsy in a screw-capped 5 ml polypropylene tube filled to the top with saline. The saline does not have to be sterile. If the specimen arrives in the laboratory the same day after biopsy, we advise to keep it overnight in saline at room temperature, followed by snap-freezing and (optional) storage at -80°C the next day. Conclusions The use of normal saline offers an attractive alternative to liquid nitrogen and Michel's fixative for diagnostic IF in autoimmune and immune complex-mediated dermatoses, but is only consistently reliable if the specimens are received within 24 hours after biopsy. Competing interests None declared. Abbreviations BMZ: basement membrane zone BP : bullous pemphigoid DH: dermatitis herpetiformis DIF: direct immunofluorescence microscopy DSS: desired specific staining EBA: epidermolysis bullosa acquisita IF: immunofluorescence microscopy LAD: linear IgA dermatosis LE : lupus erythematosus MMP: mucous membrane pemphigoid NSS: non-specific staining PF : pemphigus foliaceus PV : pemphigus vulgaris USS: undesired specific staining Authors' contributions RV carried out the studies, participated in the design and data analysis and drafted the manuscript. MdJ participated in patient selection and carried out the immunofluorescence microscopy and imaging. HM performed the immunofluorescence technical work up. MW participated in material harvesting. HP participated in patient diagnosis. MJ conceived the study, and participated in its design and coordination. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC517722.xml
509291	A New Model for Open Sharing: Massachusetts Institute of Technology's OpenCourseWare Initiative Makes a Difference	M.I.T. offers an education to the world through its OpenCourseWare program	Imagine a fledgling biology instructor at a university in the developing world. Heading into her first semester of teaching, she is armed with nothing but her college degree, some old notebooks, and—if she is lucky—a late-edition textbook. Forging a curriculum that is both current and engaging for her students could be a daunting challenge. But what if that same young instructor was given free and open access to a syllabus, complete lecture notes, and problem sets and solutions from two members of the faculty of the Massachusetts Institute of Technology (MIT)? And not just any faculty members, but David Page—the recipient of a MacArthur Foundation Prize Fellowship in 1986, a Searle Scholar's Award in 1989, and the Amory Prize for advances in reproductive biology from the American Academy of Arts and Sciences in 1997—and Chris Kaiser, who won a 1999 fellowship from MIT that recognizes his teaching excellence? This is the premise of MIT's OpenCourseWare project. Utilizing the Internet, MIT OpenCourseWare (MIT OCW) has opened MIT's curriculum and educational materials to a global audience of teachers and learners—an instructor at a new engineering university in Ghana, a precocious highschool biology student in suburban Chicago, a political scientist in Poland, a literature professor in upstate New York—who are all now able to use the same materials that MIT's professors rely on to teach their full-time students. The Makings of a Movement Ten years from now, we expect that MIT OCW will have become firmly planted in MIT's educational landscape. But MIT OCW was just a leap of faith when the concept was originally proposed by a group of faculty four years ago. In the fall of 1999, Provost Robert A. Brown asked the faculty committee to provide strategic guidance on how the institute should position itself in the e-learning environment. At first, many members of the group assumed that their work would lead to an “MIT.com” venture. But after a year of analysis, market research, and development of business scenarios, the committee concluded that a revenue-generating distance-education model was not desirable for MIT. The committee went back to the drawing board and, convinced that open software and open systems were the wave of the future, came to a very simple conclusion: that MIT should use the Internet to give its teaching materials away. Brown and MIT President Charles Vest instantly recognized the simplicity and brilliance of the idea. “It seemed to me that it would be a way to advance education, by constantly widening access to our information and inspiring other institutions to do the same with theirs,” Vest said. While the 701 courses currently available represent just a third of the ultimate goal of 2,000 courses by the year 2008, MIT OCW has already had an impact on MIT's campus. We have published teaching materials from almost half of MIT's 950 faculty members, and a significant portion of the faculty have told us that they are already using materials available on MIT OCW—the lecture notes, syllabi, problem sets, and exams of their colleagues—to prepare for their classes, do research, and help their students. But the real payoff of what we hope will become the “opencourseware movement” will be its effect on educators and learners around the world. Our goal is to create a model that other universities can follow and improve upon. Ultimately, the trend toward open knowledge will help bring people of all backgrounds together and promote improved educational systems across the globe. Measuring Success Since April 2001, we have received more than 20,000 e-mail messages from around the world endorsing the vision and potential benefits of sharing knowledge freely. A typical message came from Andrew Wilson in the United Kingdom in October 2003: There can be no greater hope for humankind than the belief that wisdom generated through increased learning will ultimately lead to a better world. With OCW, MIT has taken an ethical stand against the belief that knowledge should only be accessible to those who can pay for it or are in proximity to it.” Just after its “official launch” in fall 2003, MIT began a rigorous data collection process to find out who is accessing MIT OCW, why and how they use it, and what difference the initiative makes. The results of this first baseline evaluation confirm what we have heard anecdotally through those e-mails: that educators, students, and self-learners around the world are using our course materials, and that, overwhelmingly, they find the materials useful in meeting their own learning and teaching goals. Who Is Accessing MIT OCW? On average, MIT OCW clocks over 11,000 visits per day, with nearly a quarter-million unique visitors per month. About 45% of these visitors are from the United States and Canada. Outside North America, the top countries of origin are China, the United Kingdom, Germany, India, and Brazil. About 52% of visitors identify themselves as “self-learners,” 31% as “students” enrolled in a formal course of study, and 13% as “educators.” We view educators as a particularly important target audience because it is through them that MIT course materials can touch the greatest number of people and have the most profound impact on education around the world. Why and how are they using it? MIT OCW asked visitors their primary purpose in using MIT course materials. Of educators who responded, about 57% answered that they use it for course or curriculum development, 33% to enhance their subject matter understanding or support research, and 7% for student advising. Elements of MIT materials have been adapted for classroom use by 47% of educators who answered our survey, while 41% report they are considering it. Critical Mass Among the 33 academic disciplines available are 15 courses from the MIT Department of Biology (see Figure 1 ), 63 from the Department of Brain and Cognitive Sciences, and 13 from the Harvard–MIT Division of Health Sciences and Technology. Figure 1 Sample MIT OCW Course Homepage for Graduate Biochemistry Course (Image of DNA courtesy of Lawrence Livermore National Laboratory.) Educators, students, and self-learners from a wide variety of fields will find materials they can use in their teaching and learning activities. And as the opencourseware concept spreads to other colleges and universities, we expect that access to the work of faculty from diverse disciplines and institutions will increase, by an order of magnitude, the benefits to educators and learners who (whether for reasons of geography, cost, or culture) would not otherwise have access to such materials. History has proved that education and discovery are best advanced when knowledge is shared openly. Our agenda must evolve to shape the future, and to respond to new challenges and opportunities. At MIT, we believe the idea of opencourseware is one such opportunity, which we must seize during the next decade. For more information about MIT OCW, please contact Jon Paul Potts, MIT OCW Communications Manager, at E-mail: jpotts@mit.edu or 617-452-3621.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC509291.xml
520830	The contrast-enhanced Doppler ultrasound with perfluorocarbon exposed sonicated albumin does not improve the diagnosis of renal artery stenosis compared with angiography	There are no studies investigating the effect of the contrast infusion on the sensitivity and specificity of the main Doppler criteria of renal artery stenosis (RAS). Our aim was to evaluate the accuracy of these Doppler criteria prior to and following the intravenous administration of perfluorocarbon exposed sonicated albumin (PESDA) in patients suspected of having RAS. Thirty consecutive hypertensive patients (13 males, mean age of 57 ± 10 years) suspected of having RAS by clinical clues, were submitted to ultrasonography (US) of renal arteries before and after enhancement using continuous infusion of PESDA. All patients underwent angiography, and haemodynamically significant RAS was considered when ≥50%. At angiography, it was detected RAS ≥50% in 18 patients, 5 with bilateral stenosis. After contrast, the examination time was slightly reduced by approximately 20%. In non-enhanced US the sensitivity was better when based on resistance index (82.9%) while the specificity was better when based on renal aortic ratio (89.2%). The predictive positive value was stable for all indexes (74.0%–88.0%) while negative predictive value was low (44%–51%). The specificity and positive predictive value based on renal aortic ratio increased after PESDA injection respectively, from 89 to 97.3% and from 88 to 95%. In hypertensives suspected to have RAS the sensitivity and specificity of Duplex US is dependent of the criterion evaluated. Enhancement with continuous infusion of PESDA improves only the specificity based on renal aortic ratio but do not modify the sensitivity of any index.	Introduction Renal artery stenosis is the most frequent cause of secondary hypertension [ 1 ] which is potentially treatable with angioplasty, endovascular stent placement or surgical revascularization [ 2 , 3 ]. The angiography remains the gold standard, however, is invasive, expensive, and potentially harmful specially in patients with compromised renal function or diabetes [ 4 ]. Over the past few years, there has been extensive research for a reliable, noninvasive, and nonionizing imaging method to screen for renal artery stenosis (RAS) [ 5 ]. Magnetic resonance (MR) angiography, captopril renography and duplex ultrasonography have all been assessed for this purpose [ 6 , 7 ]. Duplex ultrasonography (US) is safe and widely available, but its use as a screening tool of renal artery stenosis does not have universal acceptance because of the lack of standardization in examination protocols and diagnostic criteria, as well as the wide differences in reported accuracy among different laboratories [ 8 , 9 ]. In addition, despite the use of color Doppler and other technological improvements, the localization of the main renal arteries deep within the abdomen has rendered direct visualization of these vessels difficult [ 10 ]. There is a 10 to 20 percent rate of failure due to the operator's inexperience, the presence of obesity, overlying bowel gas or respiratory motion [ 11 ]. The proposed criteria for the detection of renal artery stenosis by direct Doppler include an increased peak systolic velocity, an increase in renal aortic ratio and also an increased resistance index [ 12 ]. The mean sensitivity and specificity of the Duplex US based on these criteria varies, respectively, from 10 to 93% and from 37% to 100%, according to different reports [ 8 - 10 , 12 - 20 ]. There are few reports comparing these criteria for the detection of RAS [ 15 ]. Recently, the use of microbubble echo-enhancing agents in combination with harmonic Doppler imaging has been proposed to improve Doppler signal intensity in multiple vascular sites [ 21 ]. Thus, it would be expected to improve the operator's ability to visualize the renal arteries, and to significantly reduce the number of equivocal examinations [ 11 , 21 - 23 ]. In addition, contrast-enhanced harmonic Doppler US can currently provide objective functional assessment of RAS through analysis of time-intensity renal enhancement curve [ 22 ]. MISSOURIS et al [ 23 ] have reported data of microbubble Levovist ® echo-enhancing ultrasonography in hypertensives with renal artery stenosis. They demonstrated a sensitivity of 85% and a specificity of 79% without contrast and a sensitivity of 94% and a specificity of 88% with contrast, besides an important reduction in the time of procedure. The echo-enhancing agent PESDA (perfluorocarbon exposed sonicated albumin) is a second-generation agent, containing high molecular weight gas, whose use results in higher stability and better reflections of Doppler signs [ 24 ]. The PESDA is broadly used in echocardiography [ 24 ], but till date there is no studies using PESDA contrast in echo-enhanced US of renal arteries. Also there are no studies that investigate the effect of the contrast infusion on the sensitivity and specificity of the different Doppler criterion mentioned above. The purpose of our study was to evaluate the accuracy of the main color Doppler criteria of the renal arteries prior to and following the intravenous administration of PESDA in patients suspected of having renal arterial stenosis. These results were compared with those from conventional angiography, which was regarded as the standard of reference. As a secondary objective, the feasibility, time of examination and safety of US with PESDA infusion was analyzed. Methods Study Population Thirty patients (13 males/ 17 females), with a mean age of 57 ± 12 years (range 16–77 years) were enrolled in the study, that was performed at Heart Institute of São Paulo University. The only inclusion criterion was a clinical suspicion of renal arterial stenosis that required conventional or digital subtraction angiography for diagnosis. The suspicion of renovascular hypertension was based on the presence of one or more of the following clinical features: resistant hypertension, progressive renal failure with no recognized cause, atherosclerotic disease in other circulatory site (coronary, peripheral or cerebrovascular disease), renal failure induced by ACE inhibitors; renal asymmetry; retinopathy grade lll or lV (Keith Wagener) with diastolic blood pressure over 125 mmHg [ 1 ]. Exclusion criteria were as follows: patients with a renal transplant; patients who had a renal arterial stent and those referred because they were suspected of having renal arterial restenosis; patients who received any iodinated agent in the previous 24 hours, and patients with acute myocardial infarction or stroke. All patients underwent conventional angiography or digital subtraction angiography. The patients were assigned randomly in a 2-steps imaging protocol: 1) acquisition of a baseline non-enhanced Doppler ultrasound study by a Sequoia Echography System (Acuson, Siemens, Mountain View, CA, USA); 2) a continuos infusion of contrast PESDA, 0,1 ml per kg of weight in a rate of infusion of 2 ml per minute; c) after infusion, we adjust the gain according to the observed gain intensity increase for optimal filling of the vessel lumen in color mode and delineation of the spectrum envelope in duplex mode. The ultrasound scans were done in different positions to evaluate all segments of the main renal arteries: a) supine position to visualize the origin and proximal portion, b) epigastric transverse scans of the aorta to identify the right artery (anterolateral) and left artery (posterolateral), c) the sagital or coronal scan from a flank approach to identify the medium and distal portions of the arteries [[ 20 ],26,27]. Peak systolic (PSV) and diastolic (PDV) velocities of the aorta and renal arteries, and calculation of resistance index (RI), pulsatility index (PI) and renal aortic ratio (RAR) were obtained in all segments of renal arteries [[ 20 ],26-27]. The following spectral Doppler diagnostic criterion for renal arterial stenosis were used: a) PSV > 150 cm/s [26-27]; b) RAR > 3.0 [ 18 ]; c) RI > 0,80 [ 17 ]. The same examiner performed all examinations and the confirmation of the presence of stenosis was done in consensus with another examiner, both of them blinded to the results of the angiography. We also collected clinical data, including number of drugs, serum creatinine and values of blood pressure in baseline conditions. The results of PESDA-enhanced and non-enhanced ultrasound examinations were compared with those from intraarterial angiography. A hemodynamically significant stenosis was defined as diameter reduction of 50% or more at angiography, because it has been widely used in the recent literature [ 13 ]. The radiologist and clinician interpreting the study were blinded to the Doppler examination results. Secondary efficacy variables included the duration of each Doppler examination, the detection of supernumerary arteries and adverse effects. The study was approved according to local legal requirements and informed consent was obtained before ultrasound examination from all patients. Results Patient Characteristics All patients underwent digital subtraction angiography and non-enhanced US. One patient did not receive the infusion of contrast, because the venous access was not possible. Renal arterial stenosis of 50% or greater was detected at angiography in 18 (60%) patients, 5 of whom had bilateral stenosis. Renal arterial stenosis was excluded in 12 patients. Thus, stenosis by angiography was detected in 23 arteries, while 37 arteries did not present. The clinical and demographic data of patients according to the presence of stenosis are presented in the Table 1 . The patients with stenosis were older than patients with no stenosis (p = 0.013), while we did not observe differences in the other demographic and clinical data. Table 1 Demographic and clinical data of 30 patients according to the presence of RAS at angiography Patients with no stenosis (n = 12) Patients with stenosis (n = 18) p Age (years) 43 ± 15 57 ± 14 0,013* BMI 25,5 ± 5,2 26,5 ± 3,4 0,528 SP (mmHg) 158 ± 29 162 ± 26 0,738 DP (mmHg) 97 ± 15 96 ± 16 0,900 HR 74 ± 12 74 ± 11 0,866 Cr 1,21 ± 0,51 2,01 ± 1,50 0,088 BMI: corporeal mass index SP: systolic pressure DP: diastolic pressure; HR: heart rate Cr: serum creatinine (normal < 1,50 mg/dl); RAS = renal artery stenosis Feasibility Overall, all patients had the renal arteries assessable with non-enhanced US or after injection of PESDA, although in one patient with a high body mass index, the assessment was better after contrast. Despite an expectation of at least 20% accessory arteries, we did not find any in our population. Accuracy As stenosis is mostly in ostium and proximal portion of the arteries, we considered for diagnosis of renal artery stenosis the indexes obtained by echo-Doppler in these arterial segments. The mean values of PSV, PDV, RAR, RI and PI in these segments are showed in the tables 2 and 3 . In the ostium, the values of PSV and RAR were higher in arteries with stenosis, in either enhanced or non-enhanced US. In the proximal segment, only RAR values were higher in arteries with stenosis, in both enhanced and non-enhanced US. Table 2 Mean values of Doppler indexes obtained with non-enhanced or enhanced with PESDA ultrassonography in the ostium of renal arteries Non-enhanced Enhanced p Arteries without stenosis n = 37 Arteries with stenosis n = 23 Arteries without stenosis n = 37 Arteries with stenosis n = 23 Stenosis vs no stenosis Enhanced vs no enhanced PSV (cm/s) 1,49 ± 0,76 2,26 ± 1,15 1,49 ± 0,65 2,01 ± 1,27 0,001 0,975 PDV (cm/s) 0,31 ± 0,25 0,42 ± 0,34 0,32 ± 0,19 0,37 ± 0,38 0,229 0,596 RRA 1,43 ± 0,67 2,36 ± 1,34 1,19 ± 0,54 2,19 ± 1,45 <0,001 0,145 RI 0,77 ± 0,20 0,84 ± 0,12 0,79 ± 0,11 0,76 ± 0,27 0,601 0,291 PI 1,83 ± 0,90 2,23 ± 0,97 1,97 ± 0,77 1,97 ± 0,99 0,332 0,588 PSV: peak systolic velocity; PDV: peak diastolic velocity; RAA: renal/aortic ratio RI: resistance index; PI: pulsatility index; US = ultrasonography Table 3 Mean values of Doppler indexes obtained with non-enhanced or enhanced with PESDA ultrassonography in the proximal portion of renal arteries Non-enhanced Enhanced p Arteries without stenosis n = 37 Arteries with stenosis n = 23 Arteries without stenosis n = 37 Arteries with stenosis n = 23 Stenosis vs no stenosis Enhanced vs no enhanced PSV (cm/s) 1,56 ± 0,79 2,12+/-1,22 1,68+/-0,86 2,01+/-1,27 0,059 0,973 PDV (cm/s) 0,36+/-0,22 0,38+/-0,31 0,33+/-0,21 0,38+/-0,36 0,589 0,618 RAR 1,54+/-0,84 2,16+/-1,25 1,30+/-0,60 1,98+/-1,36 0,008 0,103 RI 0,76+/-0,11 0,83+/-0,11 0,78+/-0,13 0,76+/-0,26 0,193 0,793 PI 1,74+/-0,68 2,31+/-0,91 2,06+/-1,01 2,05+/-1,07 0,526 0,375 PSV: peak systolic velocity; PDV: peak diastolic velocity; RAA: renal/aortic ratio RI: resistance index; PI: pulsatility index; US = ultrasonography The sensitivity, specificity, positive predictive value and negative predictive value of each Doppler index for the detection of RAS (Table 4 ) were calculated based on the values standardized in the literature. In terms of renal arteries, we observe that the sensitivity and specificity depend on the index used. Thus, in non-enhanced US the sensitivity was better when based on RI (82.9%) while the specificity was better when based on RAR (89.2%). The PPV was stable for all indexes (74.0%–88.0%) while NPV was low (44%–51%). The specificity and PPV based on RAR increased after PESDA injection respectively, to 97.3% and 95%. Table 4 Sensitivity and specificity of non-enhanced and enhanced Doppler US for the detection of RAS in 60 arteries a) Non-enhanced Sensitivity Specificity PPV NPV RRA (<3,0) 56,2% 89,2% 88% 44% PSV (<150) 69,7% 64,9% 75% 45% RI (<0,80) 82,9% 56,8% 74% 51% b) Enhanced Sensitivity Specificity PPV NPV RRA (<3,0) 33,3% 97,3% 95% 40% PSV (<150) 61,9% 64,9% 72% 42% RI (<0,80) 76,2% 43,2% 66% 42% RRA: ratio renal/aortic PSV: peak sistolyc velocity(cm/s) RI: resistive index PPV = positive predictive value, NPV = negative predictive value RAS = Renal artery stenosis; US = ultrasonography The receiver operating characteristic curves for each Dopplerdiagnostic criterion showed that the area under the receiver operating characteristic curve for resistance index was greater than the area under the curve for peak systolic velocity and renal aortic ratio. For renal aortic ratio, the cutoff point that provided the best accuracy, 2.7 gave a specificity of 96% but a low sensitivity (60%). For peak systolic velocity, no precise cutoff point could be identified between arteries with stenosis and those without stenosis. For resistance index, a threshold of 0.8 led to a sensitivity of 70% and a low specificity of 56.8%. Secondary variables and safety The median examination time was 35 minutes for enhanced Doppler US and 29 minutes for non-enhanced Doppler US, i.e., a small but significant reduction of 17% (p = 0.03). Only one patient presented adverse events to be potentially related to the injection of PESDA, including sensation of coldness, palpitation and dyspnea. There was no severe adverse event. Discussion Although the technique of renal arterial US scanning has been well established for years, a lot of difficulties in reliably identifying main and accessory renal arteries remain [ 8 - 10 , 25 ]. Most of these dificulties are related to the patient obesity, the presence of bowel gas, excessive respiratory movement, and the depth and tortuosity of the renal arteries [ 8 , 16 ]. The time expended in the examination can be too long as almost 60 minutes [ 19 ], and failure of technique varies from 9 to 25%. In our study, non-enhanced Doppler US showed a feasibility rate of 100%, similar to some single centers, but higher than the majority of studies using this technique (58–90%) [ 11 ]. Indeed, two recently published studies reported feasibility not exceeding 11% and 12% [ 22 , 23 ]. One of the reasons of our high rate of feasibility probably is related to the quality of the machine, which allowed a scan imaging with an excellent definition. To our knowledge, the present study is the first randomized study in a selected group of hypertensive patients in which renal arterial color Doppler flow US with and without a continuous infusion of PESDA was compared against the reference standard of angiography. The infusion of PESDA did not alter the feasibility that remains 100%. In a multicentric study [ 11 ] using Levovist as the US contrast, the infusion increased by 20% the number of patients in whom renal arteries could be evaluated, including difficult cases such as those involving patients who are obese and patients with impaired renal function. However, some centers participating of the study also presented a feasibility of 100% and the Levovist infusion did not interfere in the results. In our study only one obese patient had a better visualization of renal artery after contrast infusion, and in all patients with renal failure, the non-enhanced US was able to localize renal arteries. The most important conclusion from this study is that both sensitivity and specificity of Doppler US of renal arteries are strongly dependent on the criterion used, and the infusion of PESDA contrast seems not to improve it significantly, although we observe a slight increase in specificity. Thus, the best sensitivity was obtained when based on resistance index <0.8 (82.9%) but at expense of a low specificity (56.8%). On the other hand, the best specificity was obtained with renal aortic ratio >3 (89.2%), but the sensitivity was low (56.2%). In addition, the sensitivity and specificity for a peak systolic velocity of 1.5 m/sec showed intermediate values, respectively, 61.9% and 64.9%. An analysis of previously published studies [ 8 - 10 , 12 , 15 , 16 , 20 ] based on non enhanced Doppler evaluation of the renal artery clearly shows that the diagnostic criteria and respective threshold values fluctuate from one report to the other. Miralles et al [ 15 ] reported a sensitivity of 87.3% and a specificity of 91.5% for a higher peak systolic velocity (>1.98 m/sec) and a higher renal aortic ratio (>3.3), while Olin et al [ 12 ] reported a sensitivity of 98% and specificity of 98% for a quite similar criteria. Helenon et al [ 10 ] quoted a sensitivity of 89% and a specificity of 99% with use of a peak systolic velocity cutoff point similar to our study (1.5 m/sec) but taking into account the presence of poststenotic turbulence and not renal aortic ratio. Moreover, in the multicentric study cited above comparing non enhanced and enhanced Doppler US [ 11 ], renal aortic ratio was more accurate than peak systolic velocity in the diagnosis of a renal arterial stenosis greater than 50%, but it was difficult to determine a precise cutoff point. In the same study, the authors demonstrated, in terms of patients, a sensitivity of 80.0% and a specificity of 80.8%, but according to renal arteries the sensitivity was lower (66.7%) and the specificity was higher (90.4%). These latter results were quite similar to our results based on RAR criteria, also evaluated according to renal arteries. These facts, determination of accuracy in terms of renal arteries and not in terms of patients, can explain in part the differences encountered between our conclusions and those from the studies mentioned above. The continuous infusion of PESDA contrast increased moderately the specificity for renal aortic ratio criteria from 89.2% to 97.3% but at the expense of a significant decrease of sensitivity from 56.2% to 33.3%. For the another criteria, peak systolic velocity and resistance index the infusion of PESDA decreased mildly or did not affect the sensitivity and specificity. MISSOURIS et al [ 23 ] have reported an increase of sensitivity from 85% to 94% and of specificity from 79% to 88% after injection of microbubble Levovist ® in hypertensives with renal artery stenosis. In a more recent multicentric study the contrast Levovist did not affect either sensitivity or specificity: sensitivity was 80.0%–83.7%, whereas specificity moderately increased from 80.8% to 83.6% or 86.2%, depending on the subgroups of comparable patients. In two single-center studies in which the value of Doppler US examination after intravenous injection of contrast agents for the diagnosis of renal arterial was also evaluated it was demonstrated an improvement in sensitivity, which increased from 83% to 95% in one study and from 75% to 100% in the other [ 22 , 23 ]. However, both of these studies were based on a limited number of patients with a very low feasibility rate of 11% and 12% at baseline examination, respectively. In addition, Melany et al [ 22 ] reported that contrast Levovist injection did not improve specificity, as we also demonstrated with PESDA infusion. There is no consensus whether contrast agent injection potentially reduces examination duration. In our study, we found a significant reduction of mean examination time after contrast infusion (17%). In other study, it was reported that the use of Levovist dramatically reduced the mean examination time from 24.5 minutes to 13.5 minutes [ 23 ]. This advantage could be of potential economic interest, but subsequent studies have to confirm more significant differences. PESDA was well tolerated and did not compromise the safety of US. This excellent patient tolerance has already been demonstrated in stress echocardiograph studies that used PESDA as contrast agent [ 24 ]. The small number of patients impose some limitations to the present study, However, the high prevalence of renal artery stenosis in this selected group of hypertensives counterbalance this limitation. In conclusion, the detection of renal artery stenosis by Doppler US depends on the criteria used and infusion of PESDA contrast seems not to improve the accuracy, despite a reduction in the examination duration and an increase in specificity based on one Doppler criterion. Also, the feasibility of US is dependent of the quality of the machine, and the infusion of contrast does not add advantages if the performance of the US machine is excellent. However, it remains unknown if the PESDA infusion can improve feasibility if the machine does not have a good imaging quality. So, there is a need for establishing a consensus opinion regarding Doppler useful criteria and thresholds for the diagnosis of renal arterial stenosis, regardless of the US equipment used or infusion of ultrasonographic contrast.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC520830.xml
545070	CD28 expression in sentinel node biopsies from breast cancer patients in comparison with CD3-ζ chain expression	Background Immunosuppression is documented in several malignant diseases, including breast cancer. Subsequently, future therapeutic concepts might include immunological approaches. However, detailed knowledge about tumor immunogenicity and host immunoreactivity, and how to assess these adequately, is still limited. We studied CD28 and CD3-ζ expression in sentinel node biopsies (SNB) from breast cancer patients to analyze tumor-related changes in T cell activity. Method 25 women underwent surgery for primary breast cancer, including SNB. Frozen sections from 21 sentinel nodes could be analyzed with a double-staining technique. CD28 expression was studied in CD4+ and CD8+ T-lymphocyte subsets and compared with CD3-ζ expression in three specified nodal regions. Results The degree of CD28 expression varied between the different lymph node areas. The lowest degree of CD28 expression was observed in CD4+ T-lymphocytes in the paracortex and germinal centers. Here, a good agreement with CD3-ζ expression was found. A higher CD28 expression was noted in CD4+ T-cells in the primary follicles, where concordance with CD3-ζ expression was weaker. The CD8+ T-lymphocyte subset displayed generally a higher degree of CD28 expression than the CD4+ subset. Conclusion Sentinel lymph nodes from breast cancer patients displayed local immunosuppression of varying extent. In the areas with the lowest degree of CD28 expression an accordingly low CD3-ζ expression was found. The SNB might prove an important diagnostic tool for the evaluation of interactions between tumor and the host immune system, helping to select patients who might benefit from adjuvant immunotherapy.	Background Numerous studies [ 1 ] portray a decreased anti-tumor immunoreactivity in patients with malignancies, including breast cancer [ 2 - 4 ], and its correlation with disease progression and survival [ 5 , 6 ]. Antigen presentation and subsequent T-cell activation play a major role in initiating and maintaining an adequate anti-tumor response. However, the complex signaling cascades engaged in this process are not yet fully understood, rendering it difficult to be successfully addressed in therapeutical approaches. Better knowledge of these mechanisms is therefore essential for further development of immunological treatment strategies. The CD28 surface receptor is normally expressed on 95% of CD4+ T-cells and approximately 50% of CD8+ T-cells in human peripheral blood [ 7 ]. Its natural ligands, the B7 molecules, are found on various antigen-presenting cells [ 8 ]. CD28 expression increases in activated T-cells [ 9 ]. Ligation of CD28 possesses major importance as a second, co-stimulatory signal during antigen/MHC complex presentation [ 10 ], hereby leading to a lower T-cell activation threshold and a longer duration of the proliferative response [ 11 ]. However, activation via the T-cell receptor alone induces transient T-cell proliferation [ 12 ], T-cell anergy, or deletion [ 13 ]. Decreased CD28 expression is described in dysfunctional peripheral T-lymphocytes from patients with hairy cell leukemia [ 14 ] and chronic lymphocytic leukemia [ 15 ]. In colorectal cancer, tumor-infiltrating lymphocytes (TIL) lack CD28 in contrast to those in normal colon interstitium [ 16 ]. This is consistent with findings in TIL from primary melanoma patients [ 17 ]. In melanoma metastases, CD28 down-regulation is more pronounced in areas of tumor regression [ 18 , 19 ]. Compared to healthy controls, breast cancer patients display significantly lower percentages of CD28+ T cells in peripheral blood [ 20 ]. To our knowledge, no studies as to the expression of CD28 in sentinel node biopsies from breast cancer patients have yet been published. The expression of the zeta chain of the T-cell receptor (CD3-ζ) is decreased in sentinel node biopsies from breast cancer patients [ 21 ]. This down-regulation is most pronounced in the paracortex, the main T-cell activation area. In the present study, CD28 expression was analyzed in the same material and subsequently compared with CD3-ζ expression in parallel sections. Methods Study population The study comprised 25 patients who underwent surgery for primary breast cancer, using the sentinel node biopsy technique. Inclusion criteria for enrolment in the study protocol were informed patient consent and a newly diagnosed palpable invasive breast cancer. Exclusion criteria were palpable axillary metastases, multifocality of the cancer, ongoing pregnancy or preoperative cytotoxic treatment. In two cases, the sentinel node could not be immunologically analyzed due to lack of technical quality. In two other cases, nodal tumor growth was too abundant and remaining lymphoid tissue too little to analyze the sections. Thus, the remaining study population comprised 21 patients. Patient and tumor characteristics are presented in Table 1 . Table 1 Tumor and other selected characteristics of 21 women operated on for primary breast cancer. Median (range) n (%) Age 60 (36–86) Menopausal status premenopausal 5 (24) postmenopausal 16 (76) Nodal status negative SNB 12 (57) positive SNB 9 (43) only positive SNB 7 (33) 3–4 positive lymph nodes 2 (10) Tumor stage I 7 (33) IIa 7 (33) IIb 7 (33) Histological type ductal invasive 17 (81) lobular 3 (14) mucinous 1 (5) Tumor size (mm) 21 (1–60) Estrogen receptor status positive 19 (90) negative 2 (10) DNA ploidy status euploid 9 (43) aneuploid 12 (57) S phase high 3 (14) low 18 (86) (Elston) histological grade I 2 (10) II 11 (52) III 7 (33) Not measured 1 (5) SNB = sentinel node biopsy The study protocol was approved by the ethics committees at the University of Uppsala and the University Hospital of Linköping. Identification of sentinel node Sentinel nodes were identified by injection of a radioactive tracer (Tc-99-nanocolloid) close to the tumor site, preoperative lymphoscintigrams, and injection of Patent blue dye (Guerbet, Paris, France). After biopsy, the sentinel nodes were sent fresh to the pathology department. Specimens were snap-frozen and tissue sections (6–7 μm thick) were obtained for immediate diagnostic analysis regarding the occurrence of metastasis in the sentinel node. Additional frozen sections were wrapped in parafilm and stored at -70°C until processed further at University Hospital of Linköping. Routine diagnostic studies of both tumor tissue and lymph nodes were performed at the pathology department of Central Hospital, Västerås and comprised all parameters listed in Table 1 . Monoclonal antibodies The monoclonal antibodies used were as follows: CD4 (Clone SK3, Becton-Dickinson, Stockholm, Sweden), CD8 (Clone SK1, Becton-Dickinson, Stockholm, Sweden), CD28 (Clone L293, Becton-Dickinson, Stockholm, Sweden), CD3 (Clone UCHT1, DAKO Stockholm, Sweden), TCR-zeta (Clone 2H2D9 (TIA-2), Immunotech, Stockholm, Sweden). Preparation of node biopsies and immunological staining of tissue sections Tissue sections obtained as described above were fixed with 4% paraformaldehyde (pH 7.4) (Riedel-de Haen AG, Seelze, Germany), supplemented with 5.4 g/L of glucose for 5 min and soon afterward washed three times in Hanks' balanced salt solution (BSS; Gibco, Paisley, United Kingdom) supplemented with 0.01 M HEPES solution. To avoid unspecific binding, sections were blocked with normal rabbit serum before the first staining and subsequently incubated with the primary antibodies CD3 (1/40), CD4 (1/25) and CD8 (1/50) for 30 minutes. After the slides had been washed in BSS/saponin, biotinylated rabbit anti-mouse immunoglobulin was added at a 1/100 dilution in BSS/saponin. Mouse IgG (Sigma, Stockholm, Sweden) was used as a negative control. The slides were then incubated with peroxidase-labeled streptavidine (P0397; Dako, Stockholm, Sweden) at a 1/100 dilution in BSS/saponin for 30 minutes. DAB (3,3'-diaminobenzidine, D-5637, Sigma, Stockholm, Sweden) was used as a substrate, which resulted in a brown color. The expression of the zeta chain or CD28 was identified using mouse monoclonal antibodies to these substances. The sections were first blocked by incubation with normal goat serum and subsequently incubated with the primary antibodies. Sections stained for the zeta chain (1/2.5) were incubated for 30 minutes while sections stained for CD28 (1/25) were incubated over night. The slides were again washed in BSS/saponin and incubated with goat anti-mouse immunoglobulin for 30 minutes and then with the alkaline phosphatase-anti-alkaline phosphatase (APAAP) mouse monoclonal antibody (Dakopatts D 651) at a dilution of 1/25 in BSS/saponin. After washes in BSS/saponin and Tris-buffered saline (TBS) and incubation with the alkaline phosphatase substrate (Naphthol AS-MX), 2 mg phosphate (Sigma N4875), 0.2 ml dimethylformamide, 9.8 ml 0.1 M Tris buffer pH 8.2, 50 μl 1 M levamisole (Sigma L-9756) and 10 mg Fast-Red TR salt (Sigma F 1500) for 20 minutes, the sections were again washed in TBS. Thereafter, the sections were counterstained in Mayer's haematoxylin for 15 minutes and mounted in Glycergel (Dakopatts, Sweden). All antibody solutions contained 2% normal blood donor AB serum and all incubations were performed in a moist chamber. The APAAP technique resulted in bright red staining for CD3-ζ and CD28. Double-stained cells appeared as red-brown; those with down-regulated CD3-ζ or CD28 were dominated by a brown color. Evaluation of occurrence and distribution of CD28 Two independent investigators (A.H., B.G.) analyzed whole sections of the sentinel nodes. The degree of CD28 expression was evaluated in both CD4+ and CD8+ T-cell subsets within three lymph node areas: primary follicles, secondary follicles (germinal centers) and paracortex. The number of CD4+ and CD8+ T-lymphocytes expressing CD28 was semiquantitatively scored as "high" (>75% CD28+), "moderate" (50–75% CD28+) and "low" (<50% CD28+). The regional scores were then put into correlation with our earlier data on expression of CD3-ζ in parallel sections of the same patients where the same scoring system was applied [ 21 ]. There was good agreement between the scores of the two investigators (80%). The few discrepancies between scores were discussed and the reasons for the difference in the scores could be identified. Thus, a consensus regarding the proper evaluation could always be reached. Statistical analysis For testing correlations between the patient data depicted in Table 1 and expression of CD28 and CD3-ζ, the Mann-Whitney U test was used. The Kruskal-Wallis test was applied for comparing the three analyzed lymph node regions regarding the expression of the respective markers and for the comparison of CD28 expression in the T-cell subgroups (CD4+ and CD8+) within the same lymph node region. A p-value less than 0.05 was considered significant. For testing the agreement between the expression of CD28 (in the two separate T-cell subsets) and the expression of CD3-ζ for every nodal area separately, the Prevalence-Adjusted Bias-Adjusted Kappa (PABAK) was used. It has the same interpretation as Cohen's Kappa [ 22 ]. A value of >0.80 indicates excellent agreement, 0.61–0.80 good agreement, 0.41–0.60 moderate agreement, 0.21–0.40 fair and 0.00–0.20 poor agreement. Values less than zero suggest that the agreement is worse than expected by chance. Results Expression of CD28 The degree of CD28 expression varied considerably, both between individual patients and between different regions of the sentinel lymph nodes. The lowest degree of CD28 expression was seen in CD4+ T-lymphocytes located in the paracortex and the secondary follicles. CD8+ T-lymphocytes displayed a significantly higher degree of CD28 expression than CD4+ T-cells in both paracortex (p < 0.001) and primary follicles (p < 0.001). There were statistically significant differences in CD28 expression in CD4+ T-cells comparing the three nodal regions (p < 0.01), with CD28 expression being higher in primary follicles than in secondary follicles and paracortex. No such differences were found analyzing CD28 expression in CD8+ T-lymphocytes. No significant correlation could be found between the degree of CD28 expression and tumor size, histological type, hormone receptor status, DNA ploidy status, Elston histological grade, S-phase, patient age, nodal status or tumor stage following the TNM classification of malignant tumors, neither were there any significant correlation detected regarding clinical data and the degree of CD3-ζ expression in our previously published material [ 21 ]. Primary follicles Primary follicles are cortical lymph node areas housing predominantly B-lymphocytes. The analysis could be performed in 20 cases. In the CD4+ subset (Table 2 ), 7 of 20 patients displayed a high degree of CD28 expression (Figure 1a ), 5 of 20 a moderate and 8 of 20 a low degree of CD28 expression (Figure 1b ). Table 2 Degree of CD28 expression in the CD4+ T-lymphocyte subset in different areas of the sentinel nodes from 21 breast cancer patients (numbers are frequencies). Expression of CD28 on CD4+ High Moderate Low Primary follicles 7 5 8 Secondary follicles 1 3 12 Paracortex 0 5 15 Figure 1 Double staining of a sentinel node for CD4 (brown staining) and CD28 (red staining). 1a). Primary follicle showing a high expression of CD28. 1b). Primary follicle showing a low expression of CD28. 1c). Germinal center showing a moderate expression of CD28. 1d). Germinal center showing a low expression of CD28. 1e). Paracortical area showing a moderate expression of CD28. 1f). Paracortical area showing a low expression of CD28. 1g). Double staining of a sentinel node for CD3 (brown staining) and the zeta chain (red staining). Paracortical area showing a low expression of the zeta chain. 1h). Double staining of a sentinel node for CD8 (brown staining) and CD28 (red staining). Corresponding paracortical area showing a high expression of CD28. In the CD8+ subset of T-lymphocytes (Table 3 ), a high degree of CD28 expression was found in all cases except two, which displayed a moderate degree. Table 3 Degree of CD28 expression in the CD8+ T-lymphocyte subset in different areas of the sentinel nodes from 21 breast cancer patients (numbers are frequencies). Expression of CD28 on CD8+ High Moderate Low Primary follicles 19 2 0 Paracortex 15 5 1 Germinal centers These B-cell areas, which develop as secondary follicles upon antigenic stimulation, could be analyzed in 16 patients. In the remaining five cases, no or very few germinal centers were found. In the CD4+ subset (Table 2 ), 4 of 16 patients exhibited a high or moderate degree of CD28 expression (Figure 1c ), and 12 of 16 a low degree (Figure 1d ). The small numbers of CD8+ T-lymphocytes in this compartment did not permit immunological analysis in any of the cases. Paracortex A markedly low expression of CD28 was observed in the paracortex, the principal T-cell activation area. Sections of 20 sentinel nodes could be analyzed. In the CD4+ subset (Table 2 ), none of the cases established a high CD28 expression, while it was moderate in 5 of 20 patients (Figure 1e ), and low in 15 (Figure 1f ). In contrast, 15 of 21 cases displayed a high CD28 expression in the CD8+ subset, 5 of 21 cases a moderate, and only one case a low CD28 expression (Table 3 ). Comparison between CD28 and CD3-ζ expression As described in a previous paper of our group [ 21 ], a low expression of CD3-ζ was seen in the primary follicles in 6 of 24 patients, in the germinal centers in 13 of 18 patients and in the paracortex in 19 of 24 patients. In the present study, the expression of CD28 was analyzed in parallel sections from the same patients. The expression of CD28 and CD3-ζ was always compared in the same area of the same lymph node. Degrees of expression were only considered corresponding if a patient displayed exactly the same degree of expression (i.e. low, moderate or high) of both markers in that area. In primary follicles, corresponding degrees of expression were found in 12 of 20 patients analyzing the CD4+ subset (Table 4 ), with a PABAK value of 0.40. Nevertheless, some sentinel node biopsies with a high CD3-ζ expression indicated a low (n = 3) or moderate (n = 3) CD28 expression on CD4+ T-cells. This discrepancy is hardly due to the presence of CD8+ T-cells as these cells presented a low or moderate CD28 expression in only one of these six biopsies. In the CD8+ subset, only 10 of 21 patients showed corresponding degrees (Table 7 ), resulting in a PABAK value of 0.21. Table 4 Degree of CD28 expression on CD4+ T-lymphocytes in comparison with CD3-ζ expression in primary follicles . The table comprises 20 cases, where both analyses could be done in the same sentinel node biopsies (numbers are frequencies). Expression of CD3-ζ Expression of CD28 on CD4+ High Moderate Low High 5 3 3 Moderate 1 2 0 Low 1 0 5 Table 7 Degree of CD28 expression on CD8+ T-lymphocytes in comparison with CD3-ζ expression in the primary follicles . Parallel sections of all 21 sentinel node biopsies were analyzed (numbers are frequencies). Expression of CD3-ζ Expression of CD28 on CD8+ High Moderate Low High 10 1 0 Moderate 4 0 0 Low 5 1 0 In secondary follicles, 11 of 15 patients had the same degrees of CD28 and CD3-ζ in the CD4+ subset (Table 5 ), corresponding a PABAK value of 0.60. As earlier mentioned, the CD8+ subset was excluded from immunological analysis in this area due to the small numbers of CD8+ T-cells present. Table 5 Degree of CD28 expression on CD4+ T-lymphocytes in comparison with CD3-ζ expression in secondary follicles (germinal centers). The table comprises 15 cases, where both analyses could be done in the same sentinel node biopsies (numbers are frequencies). Expression of CD3-ζ Expression of CD28 on CD4+ High Moderate Low High 0 1 1 Moderate 0 1 1 Low 0 1 10 In the paracortex, the degree of CD28 and CD3-ζ expression was corresponding in 15 of 20 cases in the CD4+ subset (Table 6 ). Here, the highest PABAK was observed, reaching a value of 0.62. As the vast majority of T-lymphocytes in the paracortex belonged to the CD4+ subset, the expression of the zeta chain by CD3+ T-cells actually represented the expression by CD4+ lymphocytes. In the CD8+ subset, only 2 of 21 patients displayed corresponding degrees (Table 8 ), leading to a PABAK value of -0.36. Instead, 11 patients with a low degree of CD3-ζ expression (figure 1g ) showed a high CD28 expression in parallel sections (figure 1h ). Table 6 Degree of CD28 expression on CD4+ T-lymphocytes in comparison with CD3-ζ expression in the paracortex . The table comprises 20 cases, where both analyses could be done in the same sentinel node biopsies (numbers are frequencies). Expression of CD3-ζ Expression of CD28 on CD4+ High Moderate Low High 0 0 1 Moderate 0 2 1 Low 0 3 13 Table 8 Degree of CD28 expression on CD8+ T-lymphocytes in comparison with CD3-ζ expression in the paracortex . Parallel sections of all 21 sentinel node biopsies were analyzed (numbers are frequencies). Expression of CD3-ζ Expression of CD28 on CD8+ High Moderate Low High 1 0 0 Moderate 3 0 0 Low 11 5 1 Discussion CD28 expression was studied in CD4+ and CD8+ T-lymphocyte subsets and compared with CD3-ζ expression in sentinel node biopsies from breast cancer patients. The lowest expression of CD28 was found in the CD4+ subset in the paracortex and germinal centers. In these areas, a moderate to good agreement between expression of CD28 on CD4+ T-cells and expression of CD3-ζ was observed. In the primary follicles, where CD28 expression on CD4+ T-cells was higher, the concordance between the two markers was less pronounced. The CD8+ subset of T-lymphocytes displayed generally a higher degree of CD28 expression than the CD4+ subset. This applied for all analyzed regions of the lymph nodes. Moreover, the congruence with CD3-ζ expression was weaker than in the CD4+ subset. The different functions of CD4+ and CD8+ T lymphocyte subsets are well documented. Some investigators suggest that CD8+ T-lymphocytes be closer connected to the CD28/B7 pathway than CD4+ T-cells [ 23 ]. Moreover, higher levels of B7 seem to be necessary to evoke an activation of CD8+ T-cells equivalent to CD4+ T-cells [ 24 ]. CD8+ T-cells from HIV positive individuals illustrate a more pronounced CD28 down-regulation than CD4+ T-cells, and their weakened proliferative response is marked by decreased Ca influx [ 25 ]. The presented data show a higher CD28 expression in CD8+ than in CD4+ T-cells, which stands in contrast to findings described in peripheral blood from healthy donors [ 7 ]. Thus, our results might suggest altered functions of CD4+ and CD8+ T-lymphocytes in the context of anti-tumor immunoreactivity. It was proposed that T-lymphocytes from secondary lymphoid organs, rather than from peripheral blood, should be used to assess host immunoreactivity [ 26 ]. In bone marrow-derived T-cells from breast cancer patients, immunological changes are more pronounced than in peripheral blood lymphocytes [ 27 , 28 ]. Several studies document decreased CD28 and CD3-ζ expression in peripheral blood from breast cancer patients [ 2 , 4 , 20 ] in comparison to healthy individuals. However, there are no immunological data from axillary sentinel lymph nodes from normal controls. Even if such data would be most valuable in the interpretation of the present findings, it seems ethically unjustifiable to obtain such material. Still, the sentinel node biopsy might be the method of choice for assessing early immunological alterations in that the host immune response against tumors is initiated here. To confirm its distinct key position, future studies should include the comparative analysis of non-sentinel axillary lymph nodes in a distance-dependent fashion. In the present study, the down-regulation of CD28 and CD3-ζ clearly seems to be more accentuated in sentinel node biopsies than otherwise described in breast cancer patients. Induction of T-cell anergy is one of the major tumor escape mechanisms [ 1 ], and its abrogation is therefore a main focus in the development of immunological anti-cancer strategies. Co-stimulation via the CD28/B7 pathway can prevent the induction of anergy in T-cell clones [ 29 ], but it is assumed that this might not be sufficient to reverse T-cell anergy once it is established [ 30 ]. Addition of exogenous IL-2 promotes reversal of T-cell anergy in this situation [ 31 ]. It was even suggested that decreased CD28 expression might be the result of continuous antigenic stimulation, aiming at reconstituting the non-responsiveness of T-cells [ 32 ]. The high numbers of CD4+/CD28- T-cells found in patients with rheumatoid arthritis are consistent with this theory [ 33 ]. Thus, the functional significance of decreased CD28 expression remains complex to interpret. The functions of CD28 and CD3-ζ might be closely linked together. Engineered T-cells co-delivering CD28 activation in addition to the T-cell receptor (TCR) subunit CD3-ζ are more effective to activate an anti-tumor response in vivo than T-cells with TCR-CD3-ζ only [ 34 ]. Without co-stimulatory signaling via CD28/B7, tyrosine phosphorylation of the zeta chain of the T-cell receptor is inhibited [ 35 ]. Moreover, signaling via CD3-ζ could activate protein-tyrosine kinases that subsequently augment signal transduction via CD28/B7 [ 36 ]. The present data document a good agreement in the expression of the two markers in areas of pronounced down-regulation. Several studies point towards a role for immunological treatment approaches in breast cancer [ 37 - 39 ]. The present data on decreased expression of CD28 and CD3-ζ in sentinel lymph nodes confirm that breast cancer has an impact on local immunoreactivity. However, the occurrence of varying individual patterns could be explained by the existence of both non-immunogenic and immunogenic, if not immunotoxic tumor types. Tumors with little inherent immunogenicity might not be as susceptible to immunotherapy as immunogenic tumor types [ 40 ]. Therefore, the decision whether to include immunotherapy in a treatment could be facilitated by analyzing the individual patient's immunological anti-tumor response. In this context, the sentinel node biopsy offers a unique opportunity to study early indicators of host-tumor interaction, and contributes valuable information for further conception and development of immunological treatment strategies. Conclusions The axillary lymph node status is of utmost importance for breast cancer prognosis and the choice of adequate adjuvant treatment. Today, the sentinel node biopsy technique is widely used as a diagnostic tool to gain that valuable information while limiting the operative procedure to a necessary minimum. However, it is also in the sentinel node that the immunoreactivity against the tumor is initiated. In this study, a varying extent of immunosuppression was observed, represented by a decreased expression of CD28 and CD3-ζ in certain areas of the lymph node. The concordance between both markers was highest in the areas of most pronounced down-regulation, namely the paracortical region and the germinal centers. As immunological reactivity was not distributed evenly over the different areas of the lymph node, this might illustrate the dynamic nature of the immunological response to malignant disease within the complex functional anatomy of the lymph node. Thus, the immunohistochemical analysis of the sentinel node biopsy with respect to its preserved architecture might prove an important instrument for the evaluation of interactions between the tumor and the host immune system, helping to select patients who might benefit from adjuvant immunotherapy. Authors' contributions All authors participated in the study design and contributed with the collection of material and data. The microscopic analysis was carried out by AH and BG. All authors read and approved the manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545070.xml
545064	Third generation cephalosporin use in a tertiary hospital in Port of Spain, Trinidad: need for an antibiotic policy	Background Tertiary care hospitals are a potential source for development and spread of bacterial resistance being in the loop to receive outpatients and referrals from community nursing homes and hospitals. The liberal use of third-generation cephalosporins (3GCs) in these hospitals has been associated with the emergence of extended-spectrum beta- lactamases (ESBLs) presenting concerns for bacterial resistance in therapeutics. We studied the 3GC utilization in a tertiary care teaching hospital, in warded patients (medical, surgical, gynaecology, orthopedic) prescribed these drugs. Methods Clinical data of patients (≥ 13 years) admitted to the General Hospital, Port of Spain (POSGH) from January to June 2000, and who had received 3GCs based on the Pharmacy records were studied. The Sanford Antibiotic Guide 2000, was used to determine appropriateness of therapy. The agency which procures drugs for the Ministry of Health supplied the cost of drugs. Results The prevalence rate of use of 3GCs was 9.5 per 1000 admissions and was higher in surgical and gynecological admissions (21/1000) compared with medical and orthopedic (8 /1000) services (p < 0.05). Ceftriaxone was the most frequently used 3GC. Sixty-nine (36%) patients without clinical evidence of infection received 3Gcs and prescribing was based on therapeutic recommendations in 4% of patients. At least 62% of all prescriptions were inappropriate with significant associations for patients from gynaecology (p < 0.003), empirical prescribing (p < 0.48), patients with undetermined infection sites (p < 0.007), and for single drug use compared with multiple antibiotics (p < 0.001). Treatment was twice as costly when prescribing was inappropriate Conclusions There is extensive inappropriate 3GC utilization in tertiary care in Trinidad. We recommend hospital laboratories undertake continuous surveillance of antibiotic resistance patterns so that appropriate changes in prescribing guidelines can be developed and implemented. Though guidelines for rational antibiotic use were developed they have not been re-visited or encouraged, suggesting urgent antibiotic review of the hospital formulary and instituting an infection control team. Monitoring antibiotic use with microbiology laboratory support can promote rational drug utilization, cut costs, halt inappropriate 3GC prescribing, and delay the emergence of resistant organisms. An ongoing antibiotic peer audit is suggested.	Background Appropriate use of antibiotics is central to limiting the development and the spread of resistant bacteria in hospitals and communities. Use of broad-spectrum antibiotics, in particular the 3GCs in nosocomial infections have been linked to the emergence of antibiotic resistance and increase in costs [ 1 ]. The hospital setting is particularly conducive to the development of antibiotic resistance as patients who are severely ill, immuno-compromised or have devices and/or implants in them are likely to receive frequent courses of empirical or prophylactic antibiotic therapy [ 2 ]. Furthermore, the absences of guidelines for antibiotic use, protocols for rational therapeutics and infection control committees have led to overuse and misuse of antimicrobials in different specialized units in hospitals. The increasing resistance to 3GCs accompanied by an increasing cost burden has raised concerns about the detection, prevalence, and clinical implications of infections with Escherichia coli and Klebsiella spp . An important source of this resistance results from the production of extended-spectrum beta-lactamases (ESBLs) by bacteria. ESBLs are modified beta-lactamase enzymes mainly derived from the ubiquitous TEM1/2 and SHV-1 plasmid-mediated enzymes, which hydrolyse expanded spectrum cephalosporins to varying degrees. Many beta-lactamases result in resistance to 3GCs in Enterobacteriaceae. Genera such as Enterobacter, Citrobacter and Serratia posses chromosomal broad spectrum beta-lactamases which are normally repressed, and when induced result in resistance to 3GCs. Klebsiella and E. coli usually have the SHV- or Tem- type beta-lactamases, and key mutations in these result in true "ESBLs". ESBLs have received attention in the last decade because although penicillins, cephalosporins, or aztreonam appear to be susceptible in vitro, ESBL producing E. coli or Klebsiella spp. may demonstrate clinical resistance to these antibiotics leading to treatment failures. Liberal use of the 3GC antibiotics has resulted in the ESBLs conferring resistance among Enterobacter[ 3 ] and Enterobacteriacae worldwide [ 4 - 6 ] compromising their clinical use. Prior antibiotic use is an important risk factor for colonization and bacterial infection and though generally antibiotic use cannot always be correlated with emergent antibiotic resistance, studies have reported the association of resistant K pneumoniae and other Enterobacteriaceae and vancomycin-resistant enteroccocci with cephalosporin use [ 7 - 11 ]. Recent increases in multidrug resistant gram-negative bacilli, particularly ESBLs is of great concern. The association between emergent ESBL-mediated infections and 3GC use emphasizes the importance of better describing 3GC drug utilization to best optimize their use. Few data are available in this regard from developing countries. In the Caribbean 3GC resistance amongst the Enterobacteriaceae has been reported from Barbados [ 12 ], and extended spectrum beta-lactamase producing Enterobacteriaceae has recently been observed in tertiary care in Jamaica [ 13 ] and Trinidad [ 14 ]. From unpublished reports of drug procurements for the public sector, the third generation cephalosporins are widely used at the General Hospital Port of Spain, which is the largest tertiary health care institution in the country. In order to assess the appropriateness of prescribing 3GCs and to determine the direct cost of treatment, an audit of prescriptions of these agents was undertaken at the POSGH, between January to June 2000. Methods Setting In Trinidad and Tobago, health care is delivered through the public sector, though several private facilities are also available. At the publicly-financed health care institutes patients undergo investigations and receive treatment without cost. There are 2 tertiary general hospitals in Trinidad, the General Hospitals at Port of Spain and San Fernando and several secondary and primary health care facilities where patients can access medical care. The POSGH is the country's major health care institute and receives referrals from all over the country including the sister isle of Tobago. This hospital is a 900-bed institute providing out-patient services and health care for warded patients for over one third of Trinidad and Tobago's population of 1.3 million. Medical students undergoing training at the University of the West Indies, also attend clinical rotations at this hospital. Patients Between January to June 2000, we conducted a cross sectional study of adult in- patients (over 13 years) who had received one or more courses of treatment with one of the 3GCs (cefotaxime, ceftriaxone, ceftazidime) available at the POSGH. The Hospital Pharmacy identified warded patients from the respective services based on the prescriptions dispensed. Patient characteristics, clinical data and laboratory investigations were obtained from the hospital records. While we did consider the course of antibiotic duration in defining appropriateness of therapy, we did not analyse data based on use per patient days because these data were not clearly available from the records. Specific data on the category of service, concomitant disease and drug therapy, organ system with infection, invasive/indwelling devices and the 3GC used were collected using a standardized instrument. Case definition of infection An infection was deemed to be present when the physician's diagnosis of infection was a differential diagnosis stated in the chart and/or in a patient who had a fever (>100.4 C) and elevated WBC Count >12,000/cmm. On review all patients with diabetes and HIV had a clinical diagnosis of infection stated in the records. Criteria for appropriate prescription The appropriateness of antibiotic therapy was determined using the criteria described in the Sanford Antibiotic Guide, 2000. Therapy was deemed to be inappropriate based on any of the following parameters: the type of therapy (prophylactic and empiric), combination of antibiotics, the route of administration, the dose, and the duration of therapy. The Sanford guide is widely accepted in Trinidad and the Caribbean as a reference for making appropriate therapeutic recommendations and is also used as a reference manual by medical microbiologists. No other guidelines are currently available in Trinidad. The course of therapy was considered a parameter of appropriate therapy, but a separate analysis based on this parameter was not possible since the information was not always available from the patient records. Cost of antibiotic treatment The direct cost of total antibiotic treatment was computed using the data obtained from the National Insurance Property Development Corporation, which is the agency contracted by the Ministry of Health for procurement and distribution of drugs in the public sector health institutes. Statistical analysis Data were analysed using EPI Info 6.4 (CDC, Atlanta GA) and categorical variables were compared using the Odds Ratio (95% CI) and the chi-square (X 2 ) tests. Results One hundred and ninety two (192) adult patients admitted to the POSGH were treated with 3GCs during the first six months of 2000, providing a prevalence rate of use of 9.5 patients per 1000 admissions, (192/20146). The rate of use was higher (p < 0.05) in those patients utilizing the surgical and gynecological services (21 per 1000 admissions) compared with those admitted in the medical and orthopedic services (8 per 1000 admissions). One hundred and twenty seven (66%) patients received ceftriaxone, cefotaxime was prescribed for 51 (26.5%) patients, and ceftazdime was administered to 14 (7.5%) patients. The demographic characteristics of patients who received a 3GC and factors related to infection and treatment in the study population are shown in Table 1 . Fifty eight percent (58%) of patients were females. The mean age of patients was 45 ± 20.56 (SD), years. The use of the third generation cephalosporins was highest in patients utilizing the surgical facilities (44%), followed by patients in the medicine (27.5%), gynecology (15%), and orthopedic (12.5%) divisions. Ceftriaxone was the most widely used agent particularly in surgical patients (61, 48%) compared with those admitted to the medicine 24 (19%), gynecology 17(13%)and orthopedic wards 13(10%). In at least one third of patients (63, 32.8%) factors, which could predispose to infection, were identified, diabetes mellitus and HIV/AIDS were diagnosed in 24.5% and 4.7% of patients respectively. There were 107(56%) patients who had fever and a high WBC count with leucocytosis and who were considered to have a clinically suspected infection. Thirty six percent of patients who had no clinical evidence of infection had received treatment with a 3GC. The most common site of suspected infection (20.3%) was the skin and soft tissue followed by the respiratory (10.9 %), gastrointestinal (10.7%), and urinary (9.3%) tracts. Sixty eight percent (131) of patients in this study received empirical antibiotic treatment and in 29.7% of patients these antibiotics were prescribed as prophylactic therapy. Only 4% of patients received 3GCs based on recommended therapeutic regimens. More patients (87%) who were admitted to the medical services received empirical antibiotic treatment compared with patients in the surgical services (68%), (p < 0.05). Prophylactic antibiotic regimens were most frequently prescribed in the orthopedic (50%) and gynecological services (45%) in contrast to patients in surgery (31%) who received 3GCs as prophylactic therapy. However patients in the surgical units (61%) were more likely to be administered two or more antibiotics compared with those receiving medical care in the orthopedic (33%) or gynecological (45%) services (p < 0.01). Single antibiotic therapy was prevalent in the medical, orthopedic, and gynecological services (66%, 55%, and 55% respectively). Seventy-eight percent of those patients who did not display any clinical evidence of infection were treated with one antibiotic. Patients with infections of the skin and soft tissue (75%) and the urinary tract (61%) were more likely to receive treatment with two or more antibiotics compared with patients admitted with respiratory tract infections (48%) (p < 0.05). Biological samples were not sent to the laboratory in as many as 73% of patients to determine a bacteriological etiology of suspected infection. (Table 2 ). Of the 52 (27%) patients who were submitted to laboratory investigation, a bacteriological etiology could be established in 25 (48 %) patients. The organisms which were isolated were; Pseudomonas spp (7), Acinetobacter spp (3) , Enterobacter spp (2) , Klebsiella spp (2) , Proteus (2) S. aureus (3) , and others (8). An analysis of factors that were associated with the inappropriate use of 3GCs in the patient sample is shown in Table 3 . There was an independent association between the type of service and inappropriate use of third generation cephalosporins and the odds of inappropriate therapy with these agents was six times more for patients in the gynecology services (odds ratio 6.58, p < 0.003) compared with patients utilizing the orthopedics (odds ratio, 2.47) and medical (odds ratio 1.80)hospital services More patients received inappropriate antibiotic treatment when the site of infection was not determined (odds ratio 5.05) compared with those in whom the site of infection was located to the skin and soft tissue infection (odds ratio 3.10), and the respiratory tract (odds ratio 2.74). The 3GCs were significantly associated with inappropriate use (odds ratio. 3.50 CI 1.73–7.11) when used as single therapy than when used with multiple antibiotics. The average duration of patient stay in the hospital was 14 ± 22 days (range 1 day -150 days). Patients in the orthopedic wards were hospitalized for more days (24.5 ± SD 35.28) compared with the number of days patients spent in the medical (12.45), surgical (13.7) and gynecology (7 days) services. Interestingly, the mean duration of stay of patients in whom antibiotic treatment was appropriate, was not significantly different from the number of days that patients who were treated inappropriately were warded. The overall direct costs from use of these antibiotics in this study was TT$ 117,432 (US$ 19251.00). The cost of treatment with these antibiotics in patients who were inappropriately treated was (TT $79,487.00, US$ 13, 30.00) and was twice as high as the cost of treatment for those patients who were treated appropriately (TT$ 35, 138.00, US$ 5767) Discussion The extensive use of third generation cephalosporin antibiotics has caused the emergence of extended spectrum beta-lactamases in Gram-negative bacteria worldwide [ 3 - 6 ]. More third generation cephalosporins are being widely used in hospitals for empirical and prophylactic therapy, and as their use extends across the board, more organisms will develop resistance to them presenting the threat of antimicrobial ineffectiveness in life threatening infections. Several investigators have developed and evaluated cost effective programs and adherence to hospital antibiotic guidelines to control antibiotic abuse [ 15 - 17 ]. The active promotion of guidelines increased appropriate prescribing of 3GCs from 21–52% over three years [ 18 ]. Though an Infection Control Committee at the POSGH had developed an antibiotic policy earlier for rational use of antimicrobial agents, the Committee did not formally approve the guidelines, they were not disseminated to all physicians and several were unaware of their formulation. A systematic review and evaluation of the guidelines was never conducted despite increasing antimicrobial resistance to third generation cephalosporins in this hospital [ 14 ]. It was therefore believed to be timely to undertake a pharmacy audit of use and cost of third generation cephalosporins in this teaching hospital. In our study, the prevalence rate of use of 3GCs was lower than the reported rate of 43 per 1000 admissions for ceftriaxone in 51 Victorian Hospitals in Australia of which 82% was prescribed as empirical treatment [ 19 ]. Our data reveals extensive overall inappropriate use of these drugs (62%) at the POSGH in Trinidad, with a rate that is higher than an earlier literature report (31%) [ 20 ]. Inappropriate use of the cephalosporins was seven times more common in the gynecological services compared with other services (odds ratio 6.58 P < 0.003) in this hospital which provides clinical clerkship teaching for graduating medical students from the University of the West Indies. Inappropriate antibiotic use has been reported from teaching hospitals in Aberdeen with significant empirical overuse [ 21 ] in New York [ 22 ] in the surgical practice [74%], in China [ 23 ] where inappropriate 3GC use was an independent risk factor for significant high mortality, in Malaysia [ 24 ] for patients in the medical wards (22–65%), in South Africa [ 25 ] for patients in the gynaecology ward (54%), and in Thailand (91%) for all departments [ 26 ]. There were twice as many patients who received inappropriate prophylactic or empirical therapy with the 3GCs compared with those who received appropriate treatment. We found higher inappropriate use of cefotaxime and ceftriaxone when these agents were used as single agents rather than in combination therapy with other antimicrobial agents. We believe this practice may have followed from the convenience of a single daily dose by intramuscular injection particularly for ceftriaxone, which was the most frequently used 3GC. Third generation cephalosporins were introduced in the Caribbean between the late eighties and the early nineties and soon after in 1993, the first isolation of resistant Gram-negative bacilli resistant to them was demonstrated in Barbados [ 12 ]. In Jamaica, K. pneumoniae isolates confirmed to be ESBL producers have recently been reported in the University Hospital of the West Indies [ 13 ]. The 3GCs were introduced to the POSGH formulary in 1990 and their use increased by 48% and 22% from 1995 to1998 and 1998 to 2001 respectively. Cefotaxime was then, the most widely used member of the class and the only member to be available in the public sector health institutes. Resistance to cefotaxime and ceftriaxone in Trinidad, has been demonstrated for isolates of enterobacter (35%,15%), proteus (28%, 8%), acinetobacter (75%, 61%), providencia (75%, 50%) and klebsiella (6%,5%) for all specimens between January to June 2001 at the Port of Spain General Hospital (unpublished data), but blood culture isolates such as klebsiella (25%) and pseudomonas (90%) were resistant to cefotaxime and/or ceftriaxone. The resistance rate of Enterobacter spp to cefotaxime and ceftriaxone was 53% and 37% respectively in the Intensive Care Unit at this hospital. It is interesting that only 4% of prescriptions were based on therapeutic regimen following culture and sensitivity results in our study, and in 73% of patients with suspected infection bacteriological confirmatory tests were never done and 3GCs were prescribed. We believe high inappropriate use of these antibiotics has contributed to increasing multiple antibiotic resistance and extended spectrum beta-lactamase producing enterobacteriaceae observed in this hospital [ 14 ]. The cost of inappropriate antibiotic use was twice as much for patients who were treated appropriately and highlights irrational antibiotic consumption at the hospital, prompting protocols for rational antibiotic prescribing and utilization review. The World Health Organization has recommended multifaceted strategies to improve hospital-prescribing practices such as the development of consensus guidelines, educational activities and rapid feedback to prescribers about inappropriate use to reduce overuse of antibiotics in the hospital [ 27 ]. Restriction of cephalosporin use has demonstrated significant cost savings and improved antibiotic susceptibility with reduced infection-related hospital mortality in critically ill patients [ 28 ]. Restructuring the formulary to rationalize antimicrobial use with restricted use of third generation cephalosporins would impact positively in curtailing antibiotic resistance and decrease selective pressure from the overuse of these agents. Moreover the spiraling costs of unwanted antibiotic therapy will be limited with resultant benefits for the consumer and the health care provider in the public health sector. The study highlights the need for an antibiotic audit and invites an ongoing peer audit. Conclusions This first audit on 3GC use from the Caribbean demonstrates inappropriate use of these drugs in tertiary care and presents opportunities to develop consensus guidelines for rational use of these drugs in hospitals. We recommend microbiological services in the hospitals undertake continuous surveillance of resistance patterns, to guide in the development of prescribing guidelines. Such guidelines should be widely disseminated and implemented in these institutions, so that prescribers remain informed of rational therapeutics. This study highlights the need to constitute an antibiotic monitoring team comprising a pharmacist, physician, medical microbiologist and infection control nurse to periodically review and evaluate the use and cost of antibiotics at the major tertiary care hospital in Trinidad, to assist clinicians in optimizing clinical care of patients with Gram-negative infections. List of abbreviations 3GCs Third generation cephaosporins ESBLs Extended spectrum Beta lactamses POSGH General Hospital, Port of Spain Competing interests The author(s) declare that they have no competing interests. Authors' contributions LMPP conceived the study, the design, co-ordinated it and prepared the final manuscript. MP, HR and KT did the data collection. PP assisted with the co-ordination, did the analysis and prepared the draft manuscript. All authors saw the final manuscript and made contributions. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545064.xml
545058	Discs-large (DLG) is clustered by presynaptic innervation and regulates postsynaptic glutamate receptor subunit composition in Drosophila	Background Drosophila discs-large (DLG) is the sole representative of a large class of mammalian MAGUKs, including human DLG, SAP 97, SAP102, and PSD-95. MAGUKs are thought to be critical for postsynaptic assembly at glutamatergic synapses. However, glutamate receptor cluster formation has never been examined in Drosophila DLG mutants. The fly neuromuscular junction (NMJ) is a genetically-malleable model glutamatergic synapse widely used to address questions regarding the molecular mechanisms of synapse formation and growth. Here, we use immunohistochemistry, confocal microscopy, and electrophysiology to examine whether fly NMJ glutamate receptor clusters form normally in DLG mutants. We also address the question of how DLG itself is localized to the synapse by testing whether presynaptic innervation is required for postsynaptic DLG clustering, and whether DLG localization requires the presence of postsynaptic glutamate receptors. Results There are thought to be two classes of glutamate receptors in the Drosophila NMJ: 1) receptors that contain the subunit GluRIIA, and 2) receptors that contain the subunit GluRIIB. In DLG mutants, antibody staining for the glutamate receptor subunit GluRIIA is normal, but antibody staining for the glutamate receptor subunit GluRIIB is significantly reduced. Electrophysiological analysis shows an overall loss of functional postsynaptic glutamate receptors, along with changes in receptor biophysical properties that are consistent with a selective loss of GluRIIB from the synapse. In uninnervated postsynaptic muscles, neither glutamate receptors nor DLG cluster at synapses. DLG clusters normally in the complete absence of glutamate receptors. Conclusions Our results suggest that DLG controls glutamate receptor subunit composition by selectively stabilizing GluRIIB-containing receptors at the synapse. We also show that DLG, like glutamate receptors, is localized only after the presynaptic neuron contacts the postsynaptic cell. We hypothesize that glutamate receptors and DLG cluster in response to parallel signals from the presynaptic neuron, after which DLG regulates subunit composition by stabilizing (probably indirectly) receptors that contain the GluRIIB subunit. The mechanism(s) stabilizing GluRIIA-containing receptors remains unknown.	Background The molecular mechanisms that target postsynaptic glutamate receptors to the postsynaptic membrane, and keep receptors clustered there, remain unknown. Membrane-associated guanylate kinase proteins (MAGUKs) are cell-cell junction proteins with multiple protein-interaction domains (PDZ, SH3, 4.1/Hook, and a catalytically inactive guanylate kinase/GUK domain) [ 1 - 3 ]. Synaptic MAGUKs are widely believed to be required for recruitment and/or stabilization of a variety of synaptic proteins, including glutamate receptors in the postsynaptic density (PSD) [ 2 , 4 - 6 ]. Although genetic evidence for MAGUK-dependent clustering of NMDA receptors is strongest, and consistent with a model wherein MAGUKs traffick NMDARs to the membrane [ 7 , 8 ], the evidence for scaffolding or trafficking of non-NMDA ionotropic glutamate receptors by MAGUKs is largely based on biochemical interactions and overexpression [ 9 - 12 ]. There is little evidence showing that glutamate receptors fail to cluster appropriately in the absence of MAGUKs – a critical prediction of the 'MAGUK scaffold' model. Drosophila DLG is a prototypical MAGUK, containing three PDZ domains, an SH3 domain, a hook/4.1-binding domain, and a GUK domain [ 3 , 13 ]. DLG is the sole fly representative of a large group of mammalian MAGUKs, including SAP-90/PSD-95, SAP-102/NE-dlg, Chapsyn-110/PSD-93, and SAP97/human DLG [ 3 ]. DLG was originally isolated as a tumor suppressor due to loss of apicobasal polarity in dlg mutants and consequent tumorous overgrowth in imaginal disc epithelia [ 14 , 15 ]. Since then, DLG has been shown to be present at several types of cell junction, including the glutamatergic larval neuromuscular junction (NMJ) [ 16 - 19 ]. The Drosophila NMJ is a widely-used model glutamatergic synapse that is molecularly and developmentally similar to glutamatergic synapses in the mammalian CNS. Drosophila NMJs in DLG mutants show a variety of changes, including disrupted organization of synaptic shaker potassium channels and fasciclin II, plus subtle alterations in larval synaptic growth [ 17 , 20 - 22 ]. It is clear from previous studies that DLG is not absolutely required for glutamate receptor expression and localization in the NMJ. In fact, DLG mutant larvae display larger excitatory postsynaptic potential amplitudes [ 17 ]. However, this phenotype depends specifically on presynaptic, but not postsynaptic loss of DLG [ 17 ]; presynaptic loss of DLG has subsequently been shown to increase synaptic vesicle diameter and quantal size [ 23 ]. Thus, based on measures of NMJ transmission, it is difficult to determine,, whether subtle changes in glutamate receptor cluster formation have occurred. Another complication is that DLG mutant larvae show dramatic underdevelopment of the subsynaptic reticulum (SSR), a dense infolding of postsynaptic membrane that appears during larval NMJ growth [ 16 , 17 , 19 , 24 ]. This loss of postsynaptic membrane in DLG mutant larvae makes it difficult to evaluate changes in postsynaptic transmembrane proteins, such as receptors. Thus, there has so far been no answer to the question of whether DLG is involved in the formation of postsynaptic glutamate receptor clusters in Drosophila . However, the aforementioned phenotypic and technical obstructions can be completely avoided in two ways. First, we can examine glutamate receptors in DLG mutant embryos rather than larvae. In embryos, the SSR has not yet formed [ 24 ]; therefore there are not yet any differences in postsynaptic membrane abundance between DLG mutant and control NMJs. Second, we can assay postsynaptic glutamate receptors directly, by immunohistochemistry and pressure ejection of glutamate onto voltage-clamped postsynaptic muscle cells [ 25 ]. This circumvents any presynaptic alterations. Immunocytochemical techniques are particularly valuable, because antibodies that recognize different receptor subunits can show whether DLG differentially regulates subpopulations of receptors that differ in subunit composition. Mammalian studies have made it increasingly apparent that many aspects of receptor assembly and trafficking depend on the presence of specific subunits. Evidence for molecularly distinct subpopulations of glutamate receptors in Drosophila NMJs has only recently been presented [ 26 , 27 ]. Differential regulation of these receptors has never before been demonstrated. The Drosophila NMJ contains five different ionotropic glutamate receptor subunits, each encoded by a different gene: GluRIIA, GluRIIB, GluRIIC (also referred to as 'GluRIII'), GluRIID, and GluRIIE [ 26 - 30 ]. By sequence, fly NMJ subunits are most similar to mammalian kainate receptors. Mutations in GluRIIC, GluRIID, or GluRIIE are lethal, show loss of functional NMJ glutamate receptors, and eliminate immunoreactivity for other subunits [ 26 , 27 , 30 ]. Thus, GluRIIC, GluRIID, and GluRIIE are thought to be essential subunits contained by each glutamate receptor at the NMJ. In contrast, null mutations in either GluRIIA or GluRIIB individually are viable, but deletion of both GluRIIA and GluRIIB simultaneously is lethal [ 29 , 31 ]. Evidence from ligand binding studies and partial crystal structures strongly suggests that ionotropic glutamate receptors are tetramers [ 32 - 34 ]. Thus, it is thought that Drosophila NMJ glutamate receptors are heterotetramers composed of one GluRIIC subunit, one GluRIID subunit, and one GluRIIE subunit, plus either one subunit of GluRIIA or one subunit of GluRIIB [ 26 , 27 ]. This model is consistent with immunocytochemical results: immunoreactivity for GluRIIA only partially overlaps that of GluRIIB [ 30 ], suggesting that at least some receptors contain either GluRIIA or GluRIIB, but not both. In other words, the Drosophila NMJ contains two subclasses of ionotropic glutamate receptor: 1) GluRIIA-containing receptors and 2) GluRIIB-containing receptors. Here, we use electrophysiology and immunocytochemistry to demonstrate selective loss of GluRIIB, but not GluRIIA, in DLG mutant Drosophila embryos. This is the first demonstration that DLG regulates synaptic glutamate receptor abundance in Drosophila , and the first evidence that fly NMJ receptors can be differentially regulated, based on subunit composition. We also explored the mechanisms by which DLG itself is localized at the NMJ. Neither GluRIIA nor GluRIIB are localized unless a presynaptic neuron first contacts the postsynaptic cell. DLG is also not clustered in the absence of presynaptic innervation. This neuronal contact-dependent clustering of DLG does not depend on the clustering or expression of glutamate receptors, because DLG is clustered properly in the absence of all postsynaptic glutamate receptors. Our results are consistent with a model in which an unknown signal from the presynaptic neuron triggers parallel clustering of both DLG and glutamate receptors, after which DLG promotes the synaptic stability of receptors containing GluRIIB, but not GluRIIA. Results DLG, GluRIIA, and GluRIIB are localized postsynaptically at the Drosophila NMJ As previously demonstrated [ 16 - 19 ], DLG is abundantly expressed throughout the postsynaptic membrane surrounding presynaptic motor axon terminals (aka 'boutons') (Fig. 1A–B ). DLG appears distributed throughout the postsynaptic membrane; there are no discernible DLG-positive domains smaller than the size of a bouton. In contrast, immunoreactivity for NMJ glutamate receptors has been shown to be restricted to specific postsynaptic domains directly opposite presynaptic active zones [ 26 , 35 ]. This restricted immunoreactivity is visible as distinct clusters within the bouton-wide area delimited by DLG staining (Fig. 1C–D ). Thus, not all postsynaptic DLG appears associated with glutamate receptors. We cannot determine by light microscopy whether all glutamate receptors colocalize with DLG, although our staining is consistent with that conclusion. Figure 1 DLG, GluRIIA, and GluRIIB are localized postsynaptically at the Drosophila NMJ A: Confocal projection of two boutons in a Drosophila third instar neuromuscular junction, visualized using the neuronal membrane marker anti-HRP (red) and anti-DLG antibodies (green). Scale bar = 2 μm. B: Isosurface projection generated from the confocal stack shown projected in A. At this stage of development, larval boutons are partially embedded in postsynaptic muscle membrane. DLG immunoreactivity surrounds the boutons, consistent with postsynaptic localization. C, D: Confocal projections of larval NMJs visualized using antibodies that recognize DLG (green) and the glutamate receptor subunits GluRIIA or GluRIIB (magenta, in panels C and D, respectively). Note the incomplete overlap of DLG and glutamate receptors; glutamate receptor immunoreactivity falls within the area stained by DLG, but not all DLG immunoreactivity overlaps with glutamate receptor immunoreactivity. Scale bar = 10 μm. GluRIIB, but not GluRIIA, is lost from synapses in DLG mutants In Drosophila embryos and larvae, the intersegmental nerve branch b (ISNb) innervates the ventral longitudinal muscles of each abdominal hemisegment [ 36 ]. In the confocal images shown in Fig. 2 , ISNb is visualized using anti-HRP antibodies, which stain all neuronal membranes (green). Three NMJs on four muscles (not stained) are shown in each image (Fig. 2A–B ). Ventral longitudinal muscles 7 and 6 are innervated via a NMJ that lies in the cleft between the two adjacent muscles. Muscles 13 and 12 are innervated by arborizations distal to the 7/6 NMJ. Each of these body wall NMJs contains multiple clusters of postsynaptic glutamate receptors that can be visualized using antibodies specific to either GluRIIA (Fig. 2A ) or GluRIIB (Fig. 2B ). Figure 2 GluRIIB, but not GluRIIA, is lost from synapses in DLG mutants A: Confocal projections of late stage 17 embryonic NMJs visualized using antibodies to the neuronal membrane marker anti-HRP (green) and anti-GluRIIA subunit antibodies (magenta). Each panel shows NMJs on interior-most ventral longitudinal muscles in one hemisegment. Major anatomical landmarks are labelled: Intersegmental nerve branch b (ISNb) enters from the left (medial) and branches to form NMJs on muscles 7 & 6, 13, and 12. The top row of panels shows images from control embryos; the lower row of panels shows images from dlg mutant embryos. B: As in A, except anti-GluRIIB subunit antibodies (magenta) were used. Scale bar = 5 μm. C: Cumulative frequency plot of glutamate receptor cluster sizes, measured from images such as those shown in A &; B. GluRIIA cluster sizes (black squares) do not differ between control (filled squares) and dlg mutant (open squares) embryos. GluRIIB cluster sizes (magenta circles), however, are significantly smaller in dlg mutant embryos (open circles), compared to controls (filled circles). To determine whether DLG is required for clustering of postsynaptic glutamate receptors, we visualized NMJ glutamate receptors in control and DLG mutant embryonic NMJs using GluRIIA and GluRIIB specific antibodies [ 30 ]. To manipulate DLG levels, we used embryos homozygous for the mutation dlg X 1–2 . In dlg X 1–2 mutants, the S97N isoform of DLG, which is predominantly expressed in neurons and muscle, is reduced to undetectable levels [ 37 ]. Other isoforms of dlg ( Drosophila expresses at least five) are expressed only at extremely low levels (approximately 5% normal) [ 37 ]. In addition, all isoforms (including S97) are truncated such that the C-terminus and GUK domains are completely removed [ 20 ]. Both control and dlg X 1–2 mutant NMJs contain highly visible clusters of GluRIIA-containing receptors (Fig 2A ; magenta). In Drosophila embryonic NMJs, the cluster area is directly proportional to the number of functional postsynaptic receptors measured using patch-clamp electrophysiology [ 25 ]. GluRIIA cluster area does not differ significantly between control and dlg X 1–2 mutants (control cluster area = 0.68 ± 0.03 μm 2 , N = 103 clusters from 10 embryos; dlg = 0.75 ± 0.03 μm 2 , N = 99 clusters from 16 embryos; P = 0.15). Immunoreactivity for GluRIIB, on the other hand, appears dramatically decreased in dlg X 1–2 mutants compared to controls (Fig. 2B ). Indeed, GluRIIB cluster size is significantly decreased in dlg X 1–2 mutants compared to controls (control cluster area = 0.45 ± 0.03 μm 2 , N = 88 clusters from 6 embryos; dlg = 0.31 ± 0.02 μm 2 , N = 57 clusters from 6 embryos; P < 0.001). Cumulative frequency histograms of GluRIIA and GluRIIB cluster sizes (Fig. 2C ) represent the entire distribution of cluster sizes measured in control and mutant embryos. Fig. 2C shows that the distribution of GluRIIA cluster sizes is almost identical in control and dlg mutants. The GluRIIB cluster size curve in dlg mutants, however, is shifted toward smaller values. The largest shift occurs in the section of the curve where cluster sizes are largest, suggesting that the largest GluRIIB clusters are preferentially lost in dlg mutants. However, the smallest clusters approach the resolution limit of light microscopy, where reductions in object size are no longer detectable. Thus, the reduction in small cluster size is probably underestimated, and the average decrease of GluRIIB in dlg mutants may be larger than is measurable by immunocytochemistry. Postsynaptic glutamate receptor current properties change in DLG mutants The immunocytochemistry in Fig. 2 suggests that dlg X 1–2 mutants specifically lose receptors that contain GluRIIB, but do not lose receptors containing GluRIIA. GluRIIA null mutants are viable, but mEJP amplitudes are smaller, glutamate receptor channel open times are reduced, and receptors show decreased sensitivity to the GluR antagonist argiotoxin 636 [ 31 ]. GluRIIB null mutants are also viable, but show no significant change in receptor function, suggesting that either the GluRIIB subunit plays a lesser role in channel function, or that the majority of native receptors lack GluRIIB. To confirm our immunocytochemical results, and explore the functional changes resulting from loss of GluRIIB-containing receptors, we used electrophysiology. First, we compared single glutamate receptor channel properties in control and dlg mutant embryonic muscle 6 (Fig. 3A–B ). Because Drosophila glutamate receptor conductance is relatively large and embryonic muscle input resistance is relatively high, single glutamate receptor channel currents are visible during the falling phase of some spontaneous synaptic events (Fig. 3B ). DiAntonio et al. [ 31 ] showed that extrasynaptic larval muscle glutamate receptors in GluRIIB null mutants have slightly larger single channel currents (8.8 pA and 9.2 pA at -60 mV, for wild-type larvae and GluRIIB null mutants, respectively). We saw a similar, but larger increase in synaptic receptor single channel amplitudes in dlg mutant embryos (Fig. 3A ; control = 9.3 ± 0.7 pA at -60 mV, N = 17; dlg = 14.1 ± 0.06 pA at -60 mV, N = 42; P < 0.001). Figure 3 Postsynaptic glutamate receptor current properties change in DLG mutants A: Single glutamate receptor channel current amplitudes from synaptic glutamate receptors are significantly larger in dlg mutants, compared to controls. Single channel amplitudes were measured from channels displaying delayed closing during the falling phase of spontaneous synaptic currents; examples of sEJCs showing single channel currents are shown in B. C: Glutamate-gated currents, evoked using pressure ejection of 1 mM glutamate onto embryonic NMJs, are smaller in dlg mutants, compared to controls. Sample glutamate-gated currents are shown in D. E: The frequency of spontaneous excitatory junction currents (sEJCs) is reduced in dlg mutants, compared to controls. F: sEJC amplitudes are not significantly different in dlg mutants, compared to controls. DiAntonio et al. [ 31 ] also examined single channel kinetics in the absence of GluRIIA or GluRIIB. Although loss of GluRIIA resulted in a dramatic decrease in average open channel times, loss of GluRIIB did not result in any significant change in open channel duration, compared to wildtype. If dlg mutants selectively lose GluRIIB, but not GluRIIA, then there should correspondingly be no change in single glutamate receptor channel kinetics in dlg mutants. Consistent with this, we observed no change in average duration of single channel currents visible during the falling phase of spontaneous synaptic currents (control channel open time = 14.3 ± 1.5 ms, N = 17; dlg mutant channel open time= 12.1 ± 0.7 ms, N = 42; P = 0.13). All evidence strongly suggests that there are two subtypes of ionotropic glutamate receptors at the Drosophila NMJ: 1) receptors that are made up of the subunits GluRIIA+IIC+IID+IIE, and 2) receptors that consist of GluRIIB+IIC+IID+IIE. Our immunocytochemical results (Fig. 2 ) suggest that in dlg mutants, GluRIIB-containing receptors are selectively lost without any compensatory increase in GluRIIA-containing receptors. If this is true, the total number of glutamate receptors measurable electrophysiologically should decrease. To test this prediction, we measured the amplitude of glutamate-gated currents triggered by pressure ejection of 1 mM glutamate onto postsynaptic muscles. Figure 3C–D shows that, glutamate-gated currents were significantly smaller in dlg mutants, compared to controls (control = 1842 ± 255 pA at -60 mV, N = 10; dlg = 1044 ± 173 pA at -60 mV, N = 10; P = 0.018). Dividing by the single channel current amplitudes allows us to calculate the number of individual receptors opened. Control currents represent the opening of approximately 198 (1842/9.3) receptors. Currents in dlg mutants represent the opening of approximately 74 (1044/14.1) receptors. Since pressure ejection of glutamate onto embryonic muscles activates extrasynaptic as well as synaptic receptors, this decrease in electrophysiologically detectable glutamate receptors also demonstrates that the loss of immunocytochemically visible receptors shown in Fig. 2 is not due to dispersal of GluRIIB-containing receptors away from postsynaptic sites. Recent studies suggest that Drosophila NMJ glutamate receptors are specifically localized opposite active zones, and that GluRIIA-containing receptors and GluRIIB-containing receptors are segregated from each other [ 26 , 30 , 35 ]. In other words, it is thought that individual postsynaptic densities (PSDs) contain either GluRIIA or GluRIIB, but not both. If this is true, then loss of one receptor subtype should cause some active zones to be without apposing receptor fields, while other active zones have relatively normal receptor fields. Our electrophysiological results (Fig. 3C–D ) show that 63% (±12%) of all receptors are missing in dlg mutants. If GluRIIA and GluRIIB are segregated into different PSDs, and GluRIIB-containing receptors are selectively lost in dlg mutants, then 63% (±12%) of the individual synapses (active zone-PSD pairs) should be silent in dlg mutants. This should show up as a decrease in spontaneous excitatory synaptic current (sEJC) frequency, without a corresponding decrease in sEJC amplitude. sEJC frequency drops to 54% (±14%) of normal in dlg mutants (Figure 3E ; control = 9.3 ± 1.6 Hz, N = 13; dlg = 5.0 ± 1.0 pA, N = 13; P = 0.03). sEJC amplitude in dlg mutants, however, is not significantly different compared to controls (Fig. 3F ; control = 79 ± 7 pA, N = 13; dlg = 69 ± 9 pA, N = 13; P = 0.41). These results are consistent with selective loss of GluRIIB-containing receptors in NMJs where individual postsynaptic densities are composed exclusively of receptors containing GluRIIA or GluRIIB. DLG mutants have fewer postsynaptic glutamate receptor clusters per presynaptic active zone If postsynaptic glutamate receptor clusters are composed of receptors containing either GluRIIA or GluRIIB, and GluRIIB-containing receptors are selectively lost in DLG mutants, then there should be fewer postsynaptic glutamate receptor clusters per presynaptic active zone in dlg mutants. We tested this by triple staining the first instar NMJs with anti-HRP antibodies to visualize the presynaptic nerve, NC82, an antibody that marks presynaptic active zones [ 38 ], and anti-GluRIID antibodies [ 26 ], which label all postsynaptic glutamate receptors. The results are shown in Figure 4 . NC82 and GluRIID immunoreactivity appear as distinct puncta where motor neurons contact postsynaptic muscle (Fig. 4A ). In control larvae, each NC82 punctum is associated with a GluRIID punctum. Not every GluR cluster is associated with NC82 or HRP immunoreactivity, however, consistent with the previously-described presence of extrasynaptic glutamate receptors [ 39 - 41 ]. Thus, the ratio of postsynaptic glutamate receptor clusters to presynaptic active zones is greater than one (Fig. 4B ). Specifically, control larvae show an average glutamate receptor cluster to active zone ratio of 1.33. In dlg mutants, however, this ratio is reduced to approximately one-half normal (Fig. 4B ; control = 1.326 ± 0.15 GluR clusters/active zone, N = 312 GluR clusters from 5 animals; dlg = 0.64 ± 0.11 GluR clusters/active zone, N = 231 GluR clusters from 5 animals; P = 0.006). These results are consistent with a model in which: 1) GluRIIB-containing receptors are clustered independently of GluRIIA-containing receptors, 2) GluRIIB-containing receptor clusters are selectively lost in dlg mutants, and 3) selective loss of GluRIIB-containing receptors causes some presynaptic active zones to no longer be associated with postsynaptic glutamate receptor clusters. Figure 4 DLG mutants have fewer postsynaptic glutamate receptor clusters per presynaptic active zone. A: Confocal projections of first instar NMJs visualized using three different antibodies: 1) the neuronal membrane marker anti-HRP (blue), 2) anti-GluRIID subunit antibodies which label all postsynaptic glutamate receptors (red), and 3) NC82 antibodies that label presynaptic active zones (green). Each panel shows NMJs on interior-most ventral longitudinal muscles in one hemisegment. Scale bar = 10 um. B: Number of postsynaptic glutamate receptor clusters relative to number of presynaptic active zones, showing that dlg mutants have fewer postsynaptic receptor clusters. C: High magnification images from dlg mutant NMJs showing glutamate receptor dispersion (arrows). Interestingly, some receptor clusters opposite active zones in dlg mutants were visibly less distinct (Fig. 4C , arrows), suggesting that GluRIIB-containing receptors are not only lost, but some receptors are slightly mislocalized. Postsynaptic localization of GluRIIA, GluRIIB, and DLG requires contact by the presynaptic neuron Broadie & Bate [ 42 ] showed electrophysiologically that innervation triggers clustering and expression of functional glutamate receptors at the site of neuron-muscle contact. However, it has never been determined whether neuronal contact triggers localization of receptor protein, or local conversion of non-functional receptors to functional receptors. To answer this question, we repeated the critical experiments of Broadie & Bate but detected glutamate receptors immunocytochemically instead of electrophysiologically (Figures 5A–B ). Figure 5 Postsynaptic localization of GluRIIA, GluRIIB, and DLG requires contact by the presynaptic neuron, but localization of DLG does not depend on the presence of glutamate receptors A: Confocal projections of late stage 17 embryonic NMJs visualized using antibodies to the neuronal membrane marker anti-HRP (green) and anti-GluRIIA subunit antibodies (magenta). This image shows NMJs on interior-most ventral longitudinal muscles in two neighbouring hemisegments in a prospero null mutant. The muscles in the upper hemisegment are normally innervated; the muscles in the lower hemisegment are not innervated. Major anatomical landmarks are labelled: In the upper hemisegment, intersegmental nerve branch b (ISNb) enters from the right (medial) and branches to form NMJs on muscles 7 & 6, 13, and 12. ISNb is absent in the uninnervated hemisegment. Note the lack of GluRIIA clusters in this hemisegment. B: Uninnervated muscles 6 & 7 in a prospero mutant embryo, stained using antibodies against GluRIIB, DLG, and the neuronal membrane marker HRP. Note the lack of GluRIIB clusters, and dispersal of DLG throughout the muscle membrane. C: Innervated muscles 6 & 7 in a GluR-less Df(2L)SP22 mutant embryo, stained using antibodies against the synaptic vesicle protein cysteine string protein (CSP, green)) and DLG (magenta). Note that DLG clusters properly at the synapse. Scale bars (A, B, C) = 15 μm. In prospero null mutants, motor axon outgrowth is delayed and impaired, such that embryonic body wall muscles are variably innervated [ 42 ]. Fig. 5A shows two neighboring hemisegments in a late stage (24 h AEL) prospero 17 mutant embryo stained with anti-HRP to visualize motor axon terminals (green), and anti-GluRIIA antibodies (magenta). Ventral longitudinal muscles 12, 13, 6, and 7 (all unstained) are labelled in each hemisegment. The locations where the intersegmental nerve normally enter the ventral longitudinal muscle field in each hemisegment is marked with arrowheads. The muscles in the top hemisegment are innervated; ISNb (green) forms appropriate branches to each of the muscles, and GluRIIA clusters (magenta) are visible at the sites of innervation. As shown in Fig. 5A (top hemisegment, muscle 12), GluR clusters were typically visible even under growth cones, suggesting that receptors cluster at synaptic sites within minutes of nerve-muscle contact. In the neighboring uninnervated hemisegment (bottom of image), however, no GluRIIA clusters are visible. Thus, GluRIIA protein does not cluster in the absence of innervation. Similar results were obtained for GluRIIB (Fig. 5B ). These results support the conclusion that postsynaptic glutamate receptors (containing either GluRIIA or GluRIIB) are clustered and upregulated only after contact by the presynaptic neuron. The signal between presynaptic neuron and postsynaptic muscle that triggers receptor clustering remains unknown. Fig. 1 and previous studies [ 16 - 19 , 43 ] show that DLG (like GluRs) is largely restricted to the postsynaptic region. We used prospero mutants to determine whether DLG localization also depends on contact by the presynaptic neuron. Figure 5B shows muscles 6 and 7 in a non-innervated prospero 17 mutant hemisegment triple-stained for GluRIIB (green), DLG (magenta), and HRP (blue). As previously noted, glutamate receptor clusters are not visible in uninnervated muscles. Without innervation, DLG is also not localized; DLG remains dispersed throughout the muscle membrane in a pattern reminiscent of that seen when DLG is missing PDZ domains 1 and 2 [ 13 ]. In innervated muscles, DLG clusters appropriately at sites of muscle-nerve contact (Fig. 5C ). Postsynaptic localization of DLG does not depend on the presence of glutamate receptors Because glutamate receptor clustering requires neuron-muscle contact, and DLG clustering requires neuron-muscle contact, it is possible that DLG clustering requires glutamate receptors. We tested this by visualizing DLG in homozygous Df(2L)SP22 mutant embryos. Df(2L)SP22 mutants contain a deletion that removes the genes encoding GluRIIA and GluRIIB, resulting in complete loss of NMJ glutamate receptors [ 26 , 27 , 31 ]. Figure 5C shows an innervated hemisegment from a homozygous Df(2L)SP22 embryo, stained with antibodies to the presynaptic vesicle protein CSP (green) and DLG (magenta). The innervation-dependent clustering of DLG does not depend on glutamate receptors; DLG clusters opposite presynaptic boutons even in homozygous Df(2L)SP22 mutants (Fig. 5C ). Note, however, that some extrasynaptic DLG remains. Extrasynaptic DLG remains prominent until approximately 48–60 h after hatching (mid second instar stage; data not shown). Discussion We have tested for the first time whether DLG is required for formation and/or stability of postsynaptic glutamate receptors in Drosophila . Our results show that DLG is indeed required, but only for a subset of receptors, those that contain the subunit GluRIIB. The molecules required for similar assembly and/or stabilization of GluRIIA-containing receptors remain unidentified. The molecular mechanism by which DLG regulates GluRIIB stability remains unclear. There is currently no evidence for a direct interaction between DLG and any Drosophila glutamate receptor subunit. Genome-wide yeast two-hybrid assays failed to identify any interactions between DLG and any Drosophila glutamate receptor subunit [ 44 ]. Similar results were obtained in two other independent and otherwise successful yeast two-hybrid screens: One, using the C-termini of GluRIIA, GluRIIB, and GluRIIC as baits failed to identify any interaction with DLG (S Sigrist, personal communication). Another screen independently used the SAP97-like N-terminus, the PDZ1-2 domains and the GUK domain of DLG as baits, but failed to identify any glutamate receptor subunits (U Thomas, personal communication). Despite the fact that DLG clearly regulates the number of GluRIIB-containing receptors in the Drosophila NMJ, we do not believe that DLG specifies the location of GluRIIB-containing glutamate receptors. First, glutamate receptors are clearly not localized based on DLG alone, because DLG is present extrasynaptically in uninnervated muscle (cf. Fig. 5 ), and abundant throughout the postsynaptic membrane (c.f. Fig. 1 ), but glutamate receptors are tightly localized to discrete puncta that are mostly (but not exclusively) found opposite presynaptic active zones [ 26 , 35 ]. Thus, DLG is not sufficient for glutamate receptor clustering or stability. Second, as described above, there is no evidence for a direct interaction between DLG and glutamate receptors. Our data are most compatible with a model wherein DLG participates in the stability of receptors (possibly by regulating the assembly of a 'stability-promoting complex'), but does not 'scaffold' receptors. This conclusion derives from the observations that immunoreactive GluRIIB-containing receptor clusters are largely absent in dlg mutants, and glutamate-gated currents are smaller in dlg mutants. If receptors were dispersed, clusters would disappear but glutamate-gated currents should remain normal. However, some declustering of receptors was observed in dlg mutants (Fig. 4C ), and it is possible that unclustered receptors are endocytosed and/or rendered nonfunctional. If DLG does not determine where receptors go, then something else must. We do not know the identity of this protein. We show that localization of postsynaptic DLG, like localization of postsynaptic glutamate receptors, depends on contact by the presynaptic neuron. We do not know the mechanism by which presynaptic contact triggers localization of either glutamate receptors or DLG. However, the identification of DLG as a target for this process should help identify the molecules involved in this critical initial trans-synaptic signal. Our results are the first evidence that glutamate receptors in Drosophila can be differentially regulated based on subunit composition. Mammalian ionotropic glutamate receptors also undergo subunit-dependent assembly and trafficking, suggesting that receptor subunit-dependent interactions are a conserved method for 'tuning' postsynaptic properties. In the Drosophila NMJ, the most critical role for DLG may therefore be as part of the machinery for regulating subunit composition. One possible mechanism for this process could be as follows. In the Drosophila NMJ, active CamKII phosphorylates DLG [ 19 ]. Constitutively active CamKII increases extrasynaptic DLG and phenocopies dlg mutants [ 19 ]. Our results therefore predict that synaptic activity, via activation of CamKII, would decrease the number of GluRIIB-containing receptors and silence some synapses (active zone-PSD pairs). Sigrist et al. [ 45 ] showed that NMJ activity leads to enhanced translation and insertion of GluRIIA-containing receptors (they did not assay GluRIIB). Thus, the overall result of increased NMJ activity is probably replacement of GluRIIB-containing receptors with GluRIIA-containing receptors – a 'switch' in postsynaptic receptor subunit composition. DiAntonio et al. [ 31 ] studied the effects of selectively expressing GluRIIA or GluRIIB transgenes in Df(2L)SP22 mutant Drosophila , where endogenous GluRIIA and GluRIIB were eliminated. The most dramatic changes in receptor properties resulted from overexpression of GluRIIA in the absence of GluRIIB: mEJP amplitudes increased several-fold, receptor channel open times increased, and sensitivity to the antagonist argiotoxin decreased. Thus, their results show that switching from 'B-type' receptors (e.g. those containing GluRIIB) to 'A-type' receptors (e.g. those containing GluRIIA) at the NMJ leads to changes in postsynaptic properties. Overexpression of GluRIIA increases presynaptic growth in larval NMJs [ 46 ], suggesting that postsynaptic subunit switching might also play a role in presynaptic development. Conclusions Our results demonstrate that mutation of DLG causes loss of glutamate receptors containing GluRIIB, but not GluRIIA. We also show that, like glutamate receptors, DLG localization requires contact between pre and postsynaptic cells. DLG localization does not depend on the presence of glutamate receptors, since DLG is localized normally in the complete absence of postsynaptic glutamate receptors. Since glutamate receptor localization does not entirely depend on DLG, and DLG localization does not depend on glutamate receptors, we hypothesize that presynaptic nerve contact triggers localization of receptors and DLG in parallel, after which DLG promotes the stability of GluRIIB-containing receptors. Methods Genetics 'Control' genotypes were either Oregon R (OR) or non-homozygous mutant siblings of the appropriate genotype. No statistically significant difference in any measurement was observed between OR and any other control genotype used in this study. Homozygous mutant embryos were identified through the use of an appropriate balancer chromosome expressing GFP. prospero[17] mutants are nulls that were a gift from Dr Chris Doe, University of Oregon. Df(2L)SP22 mutants remove both GluRIIA and GluRIIB, as previously described [ 31 ]. dlg[X1–2] mutants [ 20 ] were gifts from Dr Vivian Budnik (University of Massachusetts Medical School). Immunocytochemistry Embryos and larvae were dissected and stained for immunocytochemistry and electrophysiology as previously described [ 43 ]. When antibodies against any of the glutamate receptor subunits were used, preparations were fixed 30 min in Bouin's fixative. Otherwise, fixations were 30 min in 4% paraformaldehyde. Antibodies against GluRIIA (8B4D2, used at 1:100) [ 25 ] were produced from hybridoma cells and obtained from the University of Iowa Developmental Studies Hybridoma Bank (DSHB). Mouse NC82 antibodies were a gift from Erich Buchner and used at 1:100. Rabbit polyclonal GluRIIB antibodies [ 30 ] were used at 1:1000. Rabbit polyclonal anti-DLG antibodies [ 16 ] were used at 1:1000. Rabbit polyclonal GluRIID antibodies [ 26 ] were a gift from Stephan Sigrist and used at 1:500. All primary antibodies were visualized using fluorescently-conjugated (fluorescein, rhodamine, or CY-5) secondary antibodies (Jackson Immuno Labs, West Grove, PA) generated against the appropriate species (mouse or rabbit) and viewed using an Olympus FV-500 laser-scanning confocal microscope. Presynaptic terminals were visualized using fluorescently conjugated anti-HRP antibodies (Jackson Immuno Labs) directly conjugated to FITC, TRITC, or CY-5. Receptor cluster sizes (Fig. 2C ) were measured using an automated edge-finding/threshold-based macro run within NIH ImageJ software (v. 10.2 for OS X). Results using the automated procedure avoid experimenter bias and agree quantitatively with careful manual measurements [ 25 ]. The 3D reconstruction of the portion of a larval NMJ shown in Fig. 1B was generated using Amira 3.1 (Mercury Computer Systems, Chelmsford, MA). The number of glutamate receptor clusters per active zone (Fig. 4 ) was quantified as follows: first instar larvae of the appropriate genotype were dissected and triple-stained with antibodies against NC82, which marks presynaptic active zones, GluRIID, which marks all postsynaptic glutamate receptor clusters, and HRP to visualize the NMJ. These preparations were subsequently imaged using confocal microscopy. Z-projections from each image (which contained several NMJs and dozens of clusters) were split into the separate color channels using ImageJ, and the number of clusters in each channel (NC82 or GluRIID) was counted using ImageJ's particle analysis function. The number of GluRIID clusters in each image was then divided by the number of NC82 clusters in each image to calculate ratios that were then compared using a Student's T-test (Fig. 4B ). Electrophysiology All electrophysiology (Fig. 3 ) was performed on ventral longitudinal muscle 6. whole-cell patch clamp measurements from embryonic muscles were performed as previously described [ 41 , 43 ]. Briefly, temporally and morphologically staged embryos were dechorionated in bleach, manually devitellinated and dissected, then treated with 1 mg/ml collagenase type IV (Sigma-Aldrich) for 60–90 s. Muscle 6 was whole-cell voltage clamped (-60 mV) in standard Drosophila embryonic saline using standard patch-clamp techniques. Data were acquired and subsequently analyzed using an Axopatch 1D amplifier and PClamp 9 (Axon Instruments, Union City CA). Statistics Statistical significance in figures is represented as follows: * = p < 0.001; = p < 0.01; * = p < 0.05. Unless otherwise specified (e.g. Fig. 2C , 3F ), all statistical comparisons were made using unpaired T-tests, or (in the case of distributions) Kolmogorov-Smirnov tests. All error bars represent S.E.M. Authors' contributions All immunocytochemistry and microscopy was performed and analyzed by DEF. All electrophysiology was performed and analyzed by KC. The manuscript was written by DEF with input from KC; both authors reviewed and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545058.xml
509285	Small B cell lymphocytic lymphoma presenting as obstructive sleep apnea	Background Most lymphomas that involve the tonsil are large B cell lymphomas. Large B-cell lymphoma is a high grade malignancy which progresses rapidly. Tonsillar lymphoma usually presents as either a unilaterally enlarged palatine tonsil or as an ulcerative and fungating lesion over the tonsillar area. Small lymphocytic lymphomas (SLL) of the Waldeyer's ring are uncommon. Case presentation We report a 41-year-old male who presented with a ten-year history of snoring. Physical examination revealed smooth bilateral symmetrically enlarged tonsils without abnormal surface change or cervical lymphadenopathy. Palatal redundancy and a narrowed oropharyngeal airway were also noted. The respiratory disturbance index (RDI) was 66 per hour, and severe obstruction sleep apnea (OSA) was suspected. No B symptoms, sore throat, odynophagia or dysphagia was found. We performed uvulopalatopharyngoplasty (UPPP) and pathological examination revealed incidental small B-cell lymphocytic lymphoma (SLL). Conclusion It is uncommon for lymphoma to initially present as OSA. SLL is an indolent malignancy and is not easy to detect in the early stage. We conclude that SLL may be a contributing factor of OSA in the present case.	Background Adenotonsillar enlargement is the main cause of obstructive sleep apnea (OSA) in the pediatric population. However, this prevalent syndrome is more complicated in adults [ 1 ]. OSA has also been described in cases of benign lymphoid hyperplasia, plasmacytoma, amyloidosis, pharyngeal tumors and diseases that involve the nasopharyngeal structures. A series of careful examinations of the upper airway should be performed in every adult patient to check for anatomic causes related to upper airway obstruction [ 2 ]. We report here a patient with severe obstructive sleep apnea treated by uvulopalatopharyngoplasty (UPPP). Case presentation A 41-year-old man presented with complaints of snoring, excessive daytime sleepiness, and pavor nocturnes for more than 10 years. Systemic diseases were denied. Physical examination revealed bilateral symmetric and enlarged palatine tonsils without abnormal surface change. There were no palpable cervical lymph nodes or B symptoms (fever, body weight loss and cold sweats). White and red blood cell counts, biochemistry and chest radiographs were within normal limits. The results of an overnight polysomnography (PSG) showed mean SaO 2 , 91%, minimal SaO 2 , 62%, and a desaturation index (≥ 4%) of 61.8/h. The arousal index was 64.8/h and the respiratory disturbance index (RDI) was 66.0/h. Believing that the patient was suffering from severe OSA and hyperplastic palatine tonsils, he received UPPP. The postoperative course was uneventful and sleep apnea improved. PSG performed 4 months after surgery demonstrated that the RDI had reduced to 23.9/h. Pathology indicated small B cell lymphocytic lymphoma (Figure 1 , 2 ) with bone marrow involvement. During the whole course, the patient was free from B symptoms and no further abnormal lymphadenopathy was detected even after head and neck computed tomography (CT) and thallium scan (figure 3 ). Chemotherapy was started after evaluation at the oncology clinic. The patient is doing well and is on regular follow-up in the ENT and oncology clinics. Figure 1 a) surgical specimen of palatine tonsils; b) picture of oropharynx post UPPP 3 months later Figure 2 Photomicrograph a) effacement of normal architecture and infiltration of monotonous small lymphoid cells is visible (Hematoxylin and Eosin 100X); b) Bone marrow showing monotonous small lymphoid cells infiltration (Hematoxylin and Eosin 100X). Figure 3 a):Mild lymphadenopathy over bilateral posterior neck area; b:Gallium scan: gallium-avid lymphoma in bilateral submandibular regions and suspected lesions in the mid-abdomen Discussion Adenotonsillar enlargement is the leading cause of OSA in the pediatric population [ 1 ] though it is not so rare disorder in adults as well. The morbidity of OSA includes hypertension, arrhythmia, heart disease, erythrocytosis, and hyperlipidemia. Malignancy should be considered a potential contributing factor that rarely contributes to OSA and has never been shown to be related to it[ 2 ]. Small lymphocytic lymphoma (SLL) is an indolent but relentless malignancy, with a median survival of about 10 years. Because It usually presents as neck lymphadenopathy in the later stages, SLL is not easy to diagnose in the early stage. The effectiveness of chemotherapy for treating SLL is controversial. Most studies have found no benefit in treating patients until they develop symptoms [ 3 ]. Lymphoma presenting as OSA is extremely rare, but this case report illustrates that malignancy should be considered a potential contributing factor of OSA; a careful oropharyngeal examination in patients with OSA is necessary. Both tonsillectomy and UPPP can improve the patency of upper airway in OSA patients presenting with abnormally enlarged palatine tonsils. However, pathology of unsuspicious tissues can reveal malignancy with specific staining, and structural abnormalities secondary to a hidden malignancy might present initially as OSA. Therefore, a thorough physical examination should be performed and the pathological results should be closely traced. Nolan described a case of adenotonsillar enlargement due to chronic lymphatic leukemia which caused severe OSA [ 4 ]. His report highlights the need to consider OSA as a cause of constitutional symptoms in adults with lymphoreticular disease, especially when there is involvement of the Waldeyer's ring. Zorick et al ., [ 5 ] reported that upper airway sleep apnea was exacerbated by lymphocytic lymphoma but that chemotherapy led to complete remission of well differentiated lymphocytic lymphoma and subsidence of OSA [ 5 ]. Abe et al ., [ 6 ] described a patient with Non-Hodgkin's lymphoma who was successfully treated by tonsillar surgery and chemotherapy. In one published case, complete remission of centrocytic-centroblastic diffuse B cell lymphoma was found after tonsillectomy with UPPP, as in our case [ 7 ]. Conclusions Tonsillar surgery should be performed even on patients highly suspected of having lymphoma to improve OSA [ 8 - 10 ]. Neck CT is also suggested as a preoperative examination for patients with OSA and neck lymphadenopathy. Whether the prognosis or the outcome of chemotherapy or radiation therapy will be affected by tonsillar surgery is controversial. We conclude that SLL might be a contributing factor of OSA. Therefore careful neck examination should also be performed on patients complaining of snoring or sleep disturbances. Competing interest None declared. Authors' contributions YT, YC, CL, WC and MT made substantial contributions to the intellectual content of the paper, in the interpretation of results and in drafting the manuscript. All authors read and approved the manuscript	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC509285.xml
535568	G-protein inwardly rectifying potassium channel 1 (GIRK 1) gene expression correlates with tumor progression in non-small cell lung cancer	Background G-protein inwardly rectifying potassium channel 1 (GIRK1) is thought to play a role in cell proliferation in cancer, and GIRK1 gene expression level may define a more aggressive phenotype. We detected GIRK1 expression in tissue specimens from patients with non-small cell lung cancers (NSCLCs) and assessed their clinical characteristics. Methods Using reverse transcription-polymerase chain reaction (RT-PCR) analyses, we quantified the expression of GIRK1 in 72 patients with NSCLCs to investigate the relationship between GIRK1 expression and clinicopathologic factors and prognosis. Results In 72 NSCLC patients, 50 (69%) samples were evaluated as having high GIRK1 gene expression, and 22 (31%) were evaluated as having low GIRK1 gene expression. GIRK1 gene expression was significantly associated with lymph node metastasis, stage (p = 0.0194 for lymph node metastasis; p = 0.0207 for stage). The overall and stage I survival rates for patients with high GIRK1 gene expressed tumors was significantly worse than for those individuals whose tumors had low GIRK1 expression (p = 0.0004 for the overall group; p = 0.0376 for stage I). Conclusions These data indicate that GIRK1 may contribute to tumor progression and GIRK1 gene expression can serve as a useful prognostic marker in the overall and stage I NSCLCs.	Background Lung cancer is one of the leading causes of cancer death in North America [ 1 ]. Lung cancer is divided into two morphological types: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). The results of surgery still remain unsatisfactory; even in stage I NSCLC (no lymph node metastasis and no distant metastasis) about 30% of patients die due to disease recurrence within 5 years after curative resection [ 2 ]. Despite major advances in cancer treatment in the past decades, the prognosis of patients with NSCLC has improved only minimally [ 1 ]. A new knowledge of the molecular pathogenesis of cancer has emerged from investigative advances in the field of molecular biology [ 3 ]. Increased knowledge of the biologic role of genetic changes has provoked an intriguing search for clinical applications of these alterations [ 4 ], and has enabled the more aggressive tumors from the less aggressive ones to be distinguished [ 5 ]. G-protein inwardly rectifying potassium channels (GIRK) are found in both the heart and the brain, where they are associated with a slowing of the heart rate and suppression of neuronal response [ 6 ]. The channel found in the sinoatrial node and on atrial myocytes is formed from the homologous channel subunits GIRK1 and GIRK4 [ 7 ]. Although the function of GIRK1 still remains unclear except in cell proliferation in cancer, GIRK1 gene expression has been found to correlate with lymph node metastasis in breast carcinomas [ 8 ], but the correlation with GIRK1 gene expression and prognosis has never been analyzed in NSCLC. To our knowledge, this is the first report to analyze the prognostic influence of GIRK1 gene expression in NSCLC and the possible associations between this parameter and other clinical factors. In this study, we used RT-PCR for detecting GIRK1 in tumor tissues. We compared with GIRK1 gene expression with autocrine motility factor-receptor (AMF-R) gene expression, known as a marker of lymph node metastasis and tumor progression, and we investigated how GIRK1 gene expression is related to tumor progression and prognosis in a series of 72 cases of curatively resected NSCLC. Methods Tissue specimens Tumor tissue was collected from 72 patients with NSCLC who underwent curative surgery between 1993 and 1995 at Department of Surgery, Teikyo University School of Medicine. Patients who died within one month after surgery and patients with a past history of another cancer were excluded from the study. Of the 72 patients included, 52 were men and 20 were women and their ages ranged from 34 to 80 years (mean of 66 years). With regard to histological type, 41 were adenocarcinomas, 28 were squamous cell carcinomas and 3 were large cell lung carcinomas. The lesions of these 72 patients were staged on both operative and pathologic findings according to the UICC TNM classification (1997) [ 9 ]. There were 24 patients with stage IA, 11 patients with stage IB, 1 patients with stage IIA, 13 patients with stage IIB, and 23 patients with stage IIIA. These patients were performed curative operation with lymph node dissection. The mean follow-up time was 52.0 months (range, 2.7–120.0 months). Freshly removed pulmonary cancer tissues for RNA extraction were immediately frozen in liquid nitrogen and stored at -80°C until further use. And in five of the cases, adjacent normal pulmonary material from the same patient was also used in this study. Tissue samples to be used for hematoxylin-and-eiosin were fixed in formalin and paraffin embedded. Reverse transcription-polymerase chain reaction (RT-PCR) analysis Total RNA was purified from fresh soft tissues by the acid guanidinium-thiocyanate procedure [ 10 ]. The human pulmonary adenocarcinoma cell line PC-14 (Riken Gene Bank Co., Ltd. Tokyo, Japan) was used as a positive control. All the RNA (5 μg) was used for cDNA synthesis, and the first-standard cDNA solution was then used for the PCR, with primers designed to amplify a 230 bp sequence (sense primer sequence: 5'-GGGATTTGGACATGGCTAAGTC-3' ; antisense primer sequence: 5'-GGCCTGTTTTCATTCTCTTAACTGATAC-3'). The reaction mixture was overlaid with 20 μl of mineral oil. PCR was performed for forty cycles (10 s at 95°C; 60 s at 60°C, and 120 s at 72°C) as previously described [ 8 ]. S14 cDNA amplification using the same temperature profile for 30 cycles served as the internal control [ 11 ]: the sense and antisense primers for S14 cDNA amplification were 5'-GGCAGACCGAGATGAATCCTC-3' and 5'-CAGGTCCAGGGGTCTTGGTCC-3'. The amplified DNA samples were electrophoresed on 1% agarose gels, and photographed with a Polaroid camera. Densitometric analysis of the photographic negatives was used for band quantification. Specimen classification based on RT-PCR results The densitometric value obtained for the GIRK1 band of a given tumor tissue sample was divided by the corresponding S14 value, and was referred to as the GIRK1 gene expression rate. The level of the GIRK1 mRNA expression in PC-14 cell line is elevated. The expression ratio of the tumor was then divided by that of the human pulmonary adenocarcinoma cell line PC-14 to obtain the GIRK1 conservation rate. When the conservation rate of a given specimen was ≧ 0.8, it was considered to indicate high expression of the GIRK1 gene, and if the rate was < 0.8, it was defined as low expression. Comparison with GIRK1 gene expression and AMF-R gene expression To ascertain whether links between GIRK1 gene expression and another gene expression, known as a marker of lymph node metastasis and tumor progression in NSCLC, we examined the relationships between GIRKI gene expression and AMF-R gene expression in 46 cases [ 12 ]. The studies of AMF-R gene expression were performed as described previously [ 12 ]. The expression ratio of the tumor was divided by that of the cell line PC-14, and the conservation rate of a given specimen was larger than the mean ratio , it was considered to indicate high expression of the AMF-R gene, and if the rate was lower than the mean ratio , it was defined as low expression of the AMF-R gene. Statistical analysis All data regarding the clinical and histopathological variables were stored in a Macintosh computer. The Stat View program (Aracus Concepts, Berkeley, Ca, USA) was used for all statistical analyses. The relationship between the incidence of GIRK1 expression and clinico-pathologic factors, and AMF-R gene expression was examined by the chi-squared test with Fisher correlation. Survival curves were calculated using the Kaplan-Meier method and analyzed by the log-rank test. Statistical significance was identified as p < 0.05. Results Detection of GIRK1 using RT-PCR in NSCLC tissues To determine the number of PCR cycles appropriate for quantification, from 20 and 50 cycles of PCR were performed, in 5-cycle increments. The expression ratios of GIRK1 to S14 were reasonably constant 35 to 45 cycles (data not shown). Therefore, in the subsequent experiments the values obtained at 40 cycles were defined as the expression of the target genes. Using forty RT-PCR cycles, we found that the ratio of GIRK1/cell line PC-14 expression ranged from 0 to 2.2 (means, 0.8) in tumor specimens (Fig. 1 ). Of 72 NSCLCs studied, 50 (69%) were classified as GIRK1 high gene expression, and 22(31%) were classified as having GIRK1 low gene expression. Five adjacent normal pulmonary materials ranged from 0 to 0.1 (means = 0.1), and all of them were classified as GIRK1 low gene expression. Relationship between GIRK1 gene expression and clinicopathological factors The relationships between GIRK1 gene expression and various clinicopathological factors are shown in Table 1 . There were no statistically significant relationships between gene expression and age, gender, T factor and histology. In contrast, GIRK1 gene expression was associated with N factor and stage (p = 0.0194 for lymph node metastasis, p = 0.0207 for stage). The relationships between GIRK1 gene expression and AMF-R gene expression Of 46 NSCLCs studied, 33 (72%) were classified as AMF-R high gene expression, and 13(28%) were classified as having AMF-R low gene expression. In most GIRK1 high gene expression cases, AMF-R gene was also expressed. As shown Table 2 , the results of GIRK1 gene expression agreed significantly with AMF-R gene and 72% of cases had no discrepancy (p = 0.0303). Association of tumor GIRK1 gene expression and survival The survival was compared between the high GIRK1 gene expression group and the low GIRK1 gene expression group in overall, stage I and stage II/III. Figures 2 and 3 show the significance in survival between the high GIRK1 gene expression group and the low GIRK1 gene expression group in overall and stage I groups (P = 0.0004 for the overall group; P = 0.0376 for the stage I group). Although the 5-year survival in low GIRK1 gene expression group is better than that in the high GIRK1 gene expression group in the stage II/III, there is not a difference in survival between the 2 groups (Figure 4 ). Discussion In spite of significant advances in surgery and the use of new, more effective chemotherapeutic regimens, the overall 5-year survival of patients with NSCLC is 17% [ 13 ]. Identification of new prognostic factors might be of value in directing therapy and intensifying follow-up for a select group of patients. Lymph node metastasis and stage are the most powerful prognostic markers for NSCLC. Identifying new genes that are associated with tumor growth, metastasis, and prognosis is very important in advancing the understanding of cancer biology. Human carcinomas exhibit hyperpolarized membrane potential as compared with surrounding normal tissue [ 14 , 15 ]. GIRK1 acts to conduct potassium ions into the cell rather than out of the cell, and play a role in maintaining membrane potential. Though GIRK1 act to hyperpolarizing the cell membrane, the function of GIRK1 still remains completely unclear in cancer. Cell proliferation and the density of intracellular potassium are controlled at specific stages of the cell cycle [ 16 ], and cell membrane potential indeed changes during the cell cycle [ 14 ]. And GIRK1 is reported to play a role in cell proliferation [ 3 ]. Receptors known to activate GIRK1 belong to the family of G-protein coupled receptors, and the G-protein-coupled receptors are reported to be able to induce cell proliferation and activate a pathway leading to angiogenesis in tumor [ 17 ]. GIRK1 gene overexpression is reported to follow a general trend of increasing expression if lymph node metastasis is involved in breast carcinomas [ 8 ]. Though the mechanical role of GIRK1 in lymph node metastasis in cancer is not clear, angiogenesis is reported to be correlated with lymph node metastasis, tumor progression and poor prognosis in most of solid tumors [ 18 , 19 ]. Therefore, GIRK1 is thought to be able to act not only in cell proliferation but also as an angiogenesis activator as well as G-protein-coupled receptors. S-kinase-associated protein 2 (Skp2) plays a critical role in regulating cell cycle progression and human factor-8-related antigen (F8RA) is assessed to show angiogenesis by microvessel density. So we determined whether or not expression of GIRK1 mRNA correlated with immunohistochemical assays of Skp2 and F8RA. Patients with high expression of GIRK1 mRNA were tendency to show high MVD and positive Skp2 expression without significance (data not shown). GIRK1 could be a candidate for a pharmaceutical target, depending upon further functional studies. In this study, we used human pulmonary adenocarcinoma cell line PC-14 as a positive control for GIRK1 gene expression. The patients were classified into two groups according to the cutoff point of mean ration of GIRK1/cell line PC-14 expression in tumor specimens. The mean number has been widely used as the cutoff point to divide the patients into two groups [ 20 , 21 ]. GIRK1 was expressed at higher levels in cancer tissue than in adjacent normal lung tissue. It was shown that a high GIRK1 gene expression was detected in 69% of the tumor samples in our patient population with NSCLC. Furthermore, GIRK1 gene expression was also associated with nodal status, and tumor stage. These results, in correlation with nodal status, were similar to a previous report on breast carcinomas [ 8 ]. We examined the relationships between GIRKI gene expression and AMF-R gene expression, known as a marker of lymph node metastasis and tumor progression in NSCLC [ 12 ], and the results of GIRK1 gene expression agreed significantly with AMF-R. Statistical associations between GIRK1 expression and clinicopathological variables (age, T-factor, histology, and AMF-R) were examined by regression analysis. This analysis also showed that GIRK1 was correlated with AMF-R (data not shown). It was observed that patients with high GIRK1 expression NSCLC showed an unfavorable prognosis compared with those whose tumors had low GIRK1 expression in overall. Many patients in stage II/III disease had high GIRK1 expression than low GIRK1 expression. Therefore the poorer survival in overall was possible to be due to stage. So we compared patients in each stage, and we found a positive correlation between GIRK1 expression and surgical outcome in stage I cancer but not a positive correlation in stage II/III disease. Our results suggest that a high GIRK1 gene expression was strongly associated with an increased recurrence in stage I cancer and that patients with high GIRK1 gene expression may be prone to metastasis, or may already have occult micrometastasis to the lymph node in stage I cancer. On the other hand, GIRK1 expression does not seem to be a prognostic predictor for stage II/III disease individuals. GIRK1 gene expression level may play one of a key role in the biology of lung cancer and define a more aggressive tumor phenotype. Further studies are needed on GIRK1 to evaluate the mechanism of GIRK1 and more studies with a larger group of patients will be necessary to substantiate these data. A real quantative PCR amplication is now the standard approach, and more sensitive and accurate than RT-PCR. We would use the real-time quantative PCR amplication instead of RT-PCR in the next study for estimating the gene expression. In conclusion, the present study suggests GIRK1 may be contribute to tumor progression and could be a useful prognostic marker in patients with overall and stage I NSCLC. Thus the current findings provide evidence to support a potential utility of this gene in developing a diagnostic test for NSCLC patients. Competing interests The author(s) declare that they have no competing interest. Authors' contributions IT: Data analysis and writing of manuscript. YI, MG: Critical appraisal of manuscript. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC535568.xml
534104	Direct visualization of electroporation-assisted in vivo gene delivery to tumors using intravital microscopy – spatial and time dependent distribution	Background Electroporation is currently receiving much attention as a way to increase drug and DNA delivery. Recent studies demonstrated the feasibility of electrogene therapy using a range of therapeutic genes for the treatment of experimental tumors. However, the transfection efficiency of electroporation-assisted DNA delivery is still low compared to viral methods and there is a clear need to optimize this approach. In order to optimize treatment, knowledge about spatial and time dependency of gene expression following delivery is of utmost importance in order to improve gene delivery. Intravital microscopy of tumors growing in dorsal skin fold window chambers is a useful method for monitoring gene transfection, since it allows non-invasive dynamic monitoring of gene expression in tumors in a live animal. Methods Intravital microscopy was used to monitor real time spatial distribution of the green fluorescent protein (GFP) and time dependence of transfection efficiency in syngeneic P22 rat tumor model. DNA alone, liposome-DNA complexes and electroporation-assisted DNA delivery using two different sets of electric pulse parameters were compared. Results Electroporation-assisted DNA delivery using 8 pulses, 600 V/cm, 5 ms, 1 Hz was superior to other methods and resulted in 22% increase in fluorescence intensity in the tumors up to 6 days post-transfection, compared to the non-transfected area in granulation tissue. Functional GFP was detected within 5 h after transfection. Cells expressing GFP were detected throughout the tumor, but not in the surrounding tissue that was not exposed to electric pulses. Conclusions Intravital microscopy was demonstrated to be a suitable method for monitoring time and spatial distribution of gene expression in experimental tumors and provided evidence that electroporation-assisted gene delivery using 8 pulses, 600 V/cm, 5 ms, 1 Hz is an effective method, resulting in early onset and homogenous distribution of gene expression in the syngeneic P22 rat tumor model.	Background Despite some promising early results, gene therapy does not, as yet, live up to expectation [ 1 ]. The main stumbling block remains gene delivery, and all advances in the control of gene expression and selection of therapeutic genes are hampered by inefficient gene transfection. Hence the development of a safe and effective method of gene delivery in vivo is of utmost importance if gene therapy is to move from the experimental to the clinical stage. Electroporation is currently receiving much attention as a way to increase drug and DNA delivery [ 2 - 5 ]. Electroporation has long been used as an effective in vitro gene delivery system in both prokaryotes and eukaryotic cells. Electroporation is a physical means of importing small molecules and macromolecules into cells via increased cell membrane permeability. Electroporation combined with chemotherapeutic drugs bleomycin and cisplatin (electrochemotherapy) has shown to be very promising antitumor therapy. It was tested on many different tumor types on the preclinical level demonstrating high antitumor effectiveness resulting in tumor cures at very low chemotherapeutic doses. It was also tested in clinical trials for the treatment of accessible cutaneous tumors of different histological types in cancer patients resulting in up to 100% objective responses [ 4 , 6 , 7 ]. Recent studies demonstrated the feasibility of electrogene therapy using a range of therapeutic genes for the treatment of experimental tumors [ 4 , 8 - 14 ]. However, the transfection efficiency of electroporation-assisted DNA delivery is still low compared to viral methods and there is a clear need to optimize this approach [ 5 , 14 , 15 ]. In studies designed to determine transfection efficiency in tumors, tissue homogenates, tissue sections or measurement of fluorescence in whole-tumor specimens using fluorescence stereomicroscope have been employed. Different plasmids have also been used to analyze transfection efficiencies, such as those encoding the green fluorescence protein (GFP), β-galactosidase or luciferase [ 5 , 14 , 15 ], making direct comparisons difficult. In order to optimize treatment, knowledge about spatial and time dependency of gene expression following delivery is of utmost importance in order to improve gene delivery. This information is also important for the timing of gene therapy with other cancer treatment modalities. Intravital microscopy of tumors growing in dorsal skin fold window chambers is a useful method for monitoring gene transfection, since it allows non-invasive dynamic monitoring of gene expression in tumors in a live animal [ 16 , 17 ]. So far, only one study has used this technique to monitor the activity of an adenovirus in infecting a mammary cell carcinoma over the course of several days [ 16 ]. In the present study, we used intravital microscopy to monitor real time spatial distribution of gene transfection using the GFP reporter gene in rat P22 tumors. We followed time dependency of transfection efficiency; compared liposome-DNA complexes and electroporation assisted DNA delivery using two different sets of electrical parameters. Methods Animals and tumors All animal experiments were carried out in accordance with the UK animals (Scientific Procedures) Act 1986, following the UKCCCR guidelines and with approval from the local Ethical Review Committee of the Gray Cancer Institute. Early generations of the P22 transplanted rat carcinosarcoma were used in experiments. Donor tumors were grown subcutaneously in the left flank of 8–10 week old male BD9 rats [ 18 ]. Surgery Surgery was carried out under general anesthesia using intraperitoneal injection of fluanisone (10 mg/kg), fentanyl citrate (0.315 mg/kg) ('Hypnorm', Janssen Animal Health, UK) and midazolam (2 mg/kg) ('Hypnovel', Roche Products Ltd., UK) as described previously [ 18 ]. Briefly, animals were kept warm using heating pads throughout the surgical procedure and aseptic technique was used throughout. Window chambers, consisting of a double-sided aluminum frame, holding two parallel glass windows approximately 200 μm apart, were surgically implanted into the dorsal skin of male BD9 rats, weighing approximately 200 g. Surgery involved removal of the epidermal and dermal layers of both skin layers of a dorsal skin flap, except for the deepest fascia layer on each side, and then securing the two sides of the chamber to the skin using stainless steel screws and sutures. The two fascia layers moved freely between the two glass windows, following these procedures. Early generation subcutaneous transplants of the P22 rat carcinosarcoma were used as donor tumors, when they reached approximately 0.5 cm in diameter. A tumor fragment (~0.5 mm diameter) was placed onto one of the fascia layers within the window chamber on the day of surgery. Animals were given an intraperitoneal injection of a few milliliters dextrose-saline, immediately following surgery and kept on a warmed pad until recovery from anesthesia. Subsequently, animals were kept in a warm room (30–34°C) until the day of experiment. Three animals were used for each experimental group. Study design Transfection was carried out 7 to 14 days following surgery, when tumors measured 3–4 mm in diameter, using a plasmid encoding the green fluorescent protein (GFP; p-EGFP-N1, Clontech, Basingstoke, UK). Animals were anaesthetized with Hypnorm and midazolam. The window on the tumor side was removed and 40 μg of DNA alone or encapsulated in lipofectin (30 μl; Life Technologies, Paisley, UK) vesicles was carefully placed on the tumor surface in a total volume of 75 μl in phosphate buffered solution [ 5 ]. One minute thereafter, electroporation was carried out by application of 8 square electric pulses generated by an electroporator (built in-house). Pulses were delivered by two flat, parallel stainless steel electrodes (two stainless steel strips: length 15 mm, width 4 mm with rounded corners) 3 mm apart that were placed at the diametrically opposed edges of the tumor. Two different electroporation protocols were used: EP1 – amplitude 180 V (voltage/distance ratio 600 V/cm); pulse length 5 ms; repetition frequency 1 Hz and EP2 – amplitude 390 V (voltage/distance ratio 1300 V/cm); pulse length 0.1 ms; repetition frequency 1 Hz. Immediately after the procedure, the glass window was replaced and GFP fluorescence monitored at selected time points for 6 days. Intravital microscopy Intravital microscopy was carried out using an inverted Nikon Diaphot 200 fluorescence microscope, with a stage modified in-house for holding rats. Animals were anaesthetized with Hypnorm and midazolam and placed on the stage, in such a way that the window chamber was located centrally above the objectives using location screws. Rectal temperature was maintained between 34–37°C throughout the experiment, using a thermostatically controlled heating pad beneath the rat and an infrared overhead lamp for maintenance of tumor temperature. Tumor preparations were alternatively viewed at each time point under transmitted visible light for measurement of tumor diameter and under fluorescence epi-illumination using a 100 W mercury arc lamp, for visualization of GFP fluorescence (excitation filter of 450–490 nm, emission filter of 520 nm) using x1.6, x4, x10 and x20 objective. Prior to transfection, two different regions of interest (ROI) using x10 objective were selected, one in the center of the tumor and one in the tumor periphery. Tumor preparations were monitored at each time point for 15 s using transmitted or epi-illumination. Data analysis Observations were recorded in digital format, using a Sony DSR-30P digital videocassette recorder, for off-line analysis. Multiple frames (typically 10) were captured onto computer and the images averaged for the analysis of the fluorescence intensity using the Visilog Image Processing package (Noesis, France). Increase in fluorescence intensity in the tumors was determined by subtracting the values of fluorescence intensity of non-transfected granulation tissue from the values of tumors and normalizing them to the values of non-transfected tissue. The calculations were performed for each animal at all time points. Statistical analysis Statistical analysis was carried out using SigmaStat Statistical software (Systat Software GmbH, Erkrath, Germany). Data were tested for normality using Kolmogorov-Smirnov test and differences between the groups were tested for significance using Holm-Sidak method, after one-way repeated measures analysis of variance was performed. A value of p < 0.05 for the comparisons was considered to represent a significant difference between groups. Results and discussion Three different types of non-viral transfection methods were compared: DNA alone, liposome-DNA complex and electroporation-assisted DNA delivery, using two different sets of electric pulse parameters. Transfection of GFP was monitored using intravital microscopy on syngeneic P22 rat carcinosarcoma tumors growing in the dorsal skin flap window chamber of BD9 rats (Figure 1 ). The transfection efficiency was evaluated by monitoring real time spatial distribution and time dependence of GFP fluorescence. Among the tested transfection methods, electroporation-assisted gene delivery was the most effective method for transfection of tumors growing in the window chamber. Two different sets of electric pulse parameters were tested; EP2 resulted in up to 17%, while EP1 in up to 22% increase in fluorescence intensity in the tumors. EP2 has previously been proven to be effective in electrochemotherapy of accessible cutaneous tumors in patients with histologically different types of tumors [ 6 , 7 ], and also for electrogenetherapy [ 8 ]. On the other hand, EP1 electric pulses have already been shown to be effective for gene delivery of solid tumors of different histology and origin (rat, mouse and human) [ 5 ]. Transfection efficiency using either DNA alone or liposome-DNA complex was lower (7% and 12%, respectively) compared to electroporation-assisted gene delivery. Spatial distribution of transfected cells differed between the two sets of electric pulses parameters. When using EP1 electric pulse parameters, cells expressing GFP were more spread out through the whole tumor, compared to EP2 conditions, where cells expressing GFP were limited to the areas that were close to the positioning of the electrodes (Figure 2 ). Electroporation of the cell membrane is a physical phenomenon that occurs above a certain threshold of induced transmembrane potential and is dependent on electric pulse parameters such as pulse length, pulse amplitude, number and pulses sequence [ 4 ]. According to the current knowledge at a single cell level, DNA electro-transfer is a process involving attachment of DNA to the electropermeabilized side of the cell facing the cathode, aggregation of DNA and its translocation to the cytoplasmic side of the cell [ 19 ]. Therefore, in the case of EP2, the conditions suitable for DNA electro-transfer (above the threshold level) in vivo appeared to be obtained only in the vicinity of the electrodes, whereas in the case of EP1 a larger area of the tumor was prone to DNA transfer. Effectiveness of electroporation-assisted gene delivery was also evident by lack of transfection efficiency in the granular tissue surrounding the tumor that was not exposed to electric pulses, but to DNA only (Figure 2 ). In addition, more homogenous distribution of transfection efficiency using EP1 conditions compared to EP2 conditions could be due to the electrophoresis of the DNA caused by longer duration of the EP1 pulses. Functional GFP was formed within 5 h after transfection regardless of the transfection method used (Figures 3 , 4 ). Detectable green fluorescence is the end result of a series of events, including transfer of the DNA encoding GFP into the cell, evasion of intracellular nucleases, transfer to the nucleus, transcription and translation, and finally, folding of the protein into a functional protein's fluorophore. Topical administration of DNA to the tumors in the window chamber (40 μg of DNA) resulted in very low transfection efficiency, the increase in fluorescence intensity in the tumors was up to 7% at day 2 post-transfection, and remained at this level up to day 6. Administration of liposome-DNA complexes resulted in increased transfection efficiency in the tumors compared to DNA alone (P = 0.032). The increase was up to 12% with the similar level of GFP expression on day 6 post-transfection as after the administration of DNA only (Figure 3 ). Similar results were obtained in our previous study on dense cell suspensions and solid subcutaneous P22 tumors where liposome-DNA complexes resulted in significantly higher GFP transfection efficiency compared to DNA injection only [ 5 ]. These results are in accordance with several preclinical and clinical studies demonstrating efficient gene-transfer to solid tumors using liposome-DNA complexes [ 20 , 21 ]. The highest increase in fluorescence intensity was obtained with electroporation-assisted gene delivery using EP1 in the present study. The fluorescence intensity increased to 22% at day 2 post-transfection and then remained at this level over the observation period of 6 days. Electroporation assisted gene delivery with EP2 was less effective than with EP1, although it was better than liposome-DNA complex alone. These results are in accordance with our previous study, where electroporation assisted gene delivery using either of the electric pulse parameters yielded higher transfection efficiency compared to lipofectin-enhanced method. The transfection efficiencies that were obtained in the present study were much higher compared to the transfection efficiency that we obtained in our previous study on P22 solid tumors growing subcutaneously in SCID mice [ 5 ]. The possible reason for this is the absence of the skin overlying the tumors in the window chamber. In subcutaneously growing tumors, the presence of the stratum corneum of the skin causes the electric field intensity to drop substantially, especially in the centre of the tumor, compared to the electric field intensity in the skin [ 22 , 23 ]. The absence of this effect in the window tumors may account for the increased transfection efficiency observed in the current study, as predicted from theoretical analyses [ 22 , 23 ]. It is worth noting that the fluorescence level remained approximately constant throughout the observation period for all transfection methods. This means that, as the tumors grew during the 6-day observation period (tumor diameter increased approximately 2-fold), plasmid DNA appeared to be present in the progeny cells. In addition, intravital microscopy demonstrated that application of electric pulses to the tumors did not induce major cell damage as no effect on the tumor growth was observed compared to untreated controls. Six days post transfection there was no difference in increase in tumor diameter between the tumors that were transfected with DNA alone (2.2 fold), liposome-DNA complexes (2.3 fold), and electroporation-assisted DNA delivery using EP1 (2.4 fold) or EP2 (2.2 fold). Conclusions In conclusion, this study showed that intravital microscopy is useful for monitoring the spatial and temporal efficacy of electroporation methods for gene transfection in animal tumor models. As such, it will be valuable for the evaluation of new methods of optimizing gene delivery. Electroporation-assisted gene delivery using EP1 was found to result in early onset and homogenous distribution of gene expression in the P22 tumor model. Further improvement in transfection efficiency may be gained by optimizing electric pulse parameters. Competing interests The author(s) declare that they have no competing interests. Authors' contributions MC conceived the study, participated in its design and experiments, and drafted the manuscript. IW participated in design of the study and experiments. GUD participated in design of the study and critically revised the draft. GMT participated in design of the study and coordination, and critically revised the draft. GS helped to draft the manuscript and participated in analysis and interpretation of the data. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC534104.xml
514559	Recovery of frog and lizard communities following primary habitat alteration in Mizoram, Northeast India	Background Community recovery following primary habitat alteration can provide tests for various hypotheses in ecology and conservation biology. Prominent among these are questions related to the manner and rate of community assembly after habitat perturbation. Here we use space-for-time substitution to analyse frog and lizard community assembly along two gradients of habitat recovery following slash and burn agriculture ( jhum ) in Mizoram, Northeast India. One recovery gradient undergoes natural succession to mature tropical rainforest, while the other involves plantation of jhum fallows with teak Tectona grandis monoculture. Results Frog and lizard communities accumulated species steadily during natural succession, attaining characteristics similar to those from mature forest after 30 years of regeneration. Lizards showed higher turnover and lower augmentation of species relative to frogs. Niche based classification identified a number of guilds, some of which contained both frogs and lizards. Successional change in species richness was due to increase in the number of guilds as well as the number of species per guild. Phylogenetic structure increased with succession for some guilds. Communities along the teak plantation gradient on the other hand, did not show any sign of change with chronosere age. Factor analysis revealed sets of habitat variables that independently determined changes in community and guild composition during habitat recovery. Conclusions The timescale of frog and lizard community recovery was comparable with that reported by previous studies on different faunal groups in other tropical regions. Both communities converged on primary habitat attributes during natural vegetation succession, the recovery being driven by deterministic, nonlinear changes in habitat characteristics. On the other hand, very little faunal recovery was seen even in relatively old teak plantation. In general, tree monocultures are unlikely to support recovery of natural forest communities and the combined effect of shortened jhum cultivation cycles and plantation forestry could result in landscapes without mature forest. Lack of source pools of genetic diversity will then lead to altered vegetation succession and faunal community reassembly. It is therefore important that the value of habitat mosaics containing even patches of primary forest and successional secondary habitats be taken into account.	Background Evaluation of the importance of various processes determining community structure and function is an important topic in ecology. Unlike just a decade or so ago, few studies today question whether or not community assembly is strictly random, recognizing the role of both stochastic and deterministic processes [ 1 ]. This change can be attributed to accumulating data on organisation in experimental and natural communities, and new perspectives gained from the fields of evolutionary population ecology and phylogenetics ([ 2 ] e.g., [ 3 , 4 ]). It is worth noting that empirical tests for much of this theory have been attempted relatively recently in experimental microcosms research in particular, yielding valuable insights into the role of processes in driving long-term community dynamics [ 5 ]. This newfound view of community ecology is an excitingly realistic one, and has the potential to make valuable contributions to conservation biology as well [ 6 , 7 ]. However, though studies on long term dynamics of communities are obviously important, they are extremely difficult to implement. A vast majority of field studies are restricted to exploring correlates and predictors of species diversity and other emergent community properties. This is in part due to the problems associated with studying complex natural communities. But to a great extent, difficulties also arise because community ecology studies have traditionally been skewed towards relatively long-lived vertebrate groups, or are restricted to short study periods due to logistical constraints, especially in the tropics [ 8 , 9 ]. Although these studies yield valuable information, they are carried out at timescales that at best, give insight into short-term processes, providing limited information about community organization, persistence, or assembly. Circumventing this problem is obviously very difficult. One possible approach is to study communities along gradients of habitat succession using space-for-time substitution (SFT) to obtain chronosequential communities [ 10 ]. Thus, instead of studying changes in a single community over time, successional habitats of known ages that can be arranged on a temporal gradient are compared. This method can reveal changes in community structure, environmental predictors of these changes, and provide estimates of the rate of community change [ 11 - 14 ]. Although many studies have examined recovery of faunal communities with tropical forest regeneration, a vast majority have been restricted to one or two vertebrate (birds, small mammals) and invertebrate (ants, beetles) groups [ 10 ]. For example, 19 of the 33 studies reviewed by Dunn [ 10 ], were on vertebrates, out of which only two were on amphibians and/or reptiles. Considering that amphibians and reptiles are ectothermic and have life history traits different from mammals and birds [ 9 ], more data on these taxonomic groups is important to test the generality of conclusions about effects of tropical habitat alteration on fauna. This study takes an SFT approach to compare changes in frog and lizard community structure in two contrasting habitat succession gradients: (a) 1-yr jhum fallows giving way to mature forest, and (b) 1-yr jhum fallows planted over with teak, leading to monoculture stands. Slash-and-burn or shifting cultivation ( jhum ) agriculture involves clearing and burning of forest patches, so the original rainforest communities are effectively obliterated, and succession involves recovery of communities from scratch. The following questions were addressed in this study: 1. How much does frog and lizard community succession differ between the two gradients of habitat recovery? 2. Does composition of the entire community change in synchrony, or does the recovery pattern differ between subcommunities such as frogs vs. lizards and guilds? 3. What aspects of habitat change influence frog and lizard community recovery, and if habitat parameters are linked to niche axes, do they predict changes in guild composition? 4. Do successional changes in guilds also show trends in phylogenetic structure? This last question is expected to yield interesting insights into possible evolutionary mechanisms underlying changes in community composition [ 15 ], but has not explicitly been addressed in previous work on faunal recovery during tropical forest regeneration (cf. [ 10 ], and references therein). In this paper, a chronosere is defined as a habitat that has recovered from perturbation for a known length of time, and can be assigned a place in the SFT. An assemblage is the set of all species of a taxonomic group in a landscape of interest. Ecological groups (EGs) are species' subsets of the assemblage with similar niche characteristics. Communities comprise species of the assemblage which share a habitat stratum (i.e., chronosere) in the landscape. Guilds are members of the EGs that actually coexist in the same chronosere i.e., belong to the same community, and are thus likely to have ecological and evolutionary interactions (cf. [ 16 ]). To draw inferences about what aspects of habitat change determine sequential communities, habitat and frog-lizard community data were analysed hierarchically. As a first step, species richness and turnover of frog and lizard communities along habitat recovery gradients was summarised, and the entire assemblage classified into ecological groups (EGs) based on niche similarities. Guilds identified from this classification were then examined for phylogenetic structure. Using factor analysis, orthogonal combinations of variables that described biotic and abiotic aspects of habitat transition were extracted. We then tested for correspondence between these composite variables and composition of frogs and lizard communities and guilds. Based upon the relationships between different habitat factors and frog and lizard communities, variables were interpreted as composite adaptive zones, and we tested whether they predicted successional changes at different levels of community organization. Results and Discussion Gradients of vegetation recovery Table 1 shows details of the chronosere sampling plots (see Additional file 2 for photographs of chronoseres). Both the 1-yr post- jhum fallows (plots jh1A and B) were dominated by herbaceous plants, tall grass, shrubs and wild bananas, along with saplings and surviving crop plants. The 4 to 5-yr post- jhum plot (jh5) was dominated by almost homogeneous stands of the bamboo Melocanna baccifera , interspersed with a few shrubs and trees. Herbs were rare, and the understorey sparse. The 7 to 10-yr post- jhum plot (jh10) was very similar to jh5. However, here the bamboo culms were more sparsely distributed, and along with M. baccifera , two other bamboos- Dendrocalamus longispathus and Bambusa tulda were in greater abundance, and woody plants were relatively more common. Compared to the other plots, a larger area was included in the 30 to 35-yr jhum plot (jh35) because it contained a greater range of ages and hence perhaps more variability. Also, this was the only accessible site in the study area that represented a chronosere aged between 30–50 years. Although M. baccifera was common, this site had a greater abundance of other bamboos and trees than any of the previous stages. Though most trees were small, woody vegetation formed a significant part of the canopy. Herbs and shrubs were rare, and the understorey generally sparse. Table 1 Details of sampling plots. Plot ages were determined by consultation with local people. The labels in the first column are used to identify plots throughout the rest of the paper. Plot Details Size (ha.) jh1A 1 year jhum fallows, cultivated and abandoned in 1998 3–4 jh1B 1 year jhum fallows, cultivated and abandoned in 1998 3–4 jh5 Two adjoining, indistinguishable 4–5 year jhum fields cultivated and abandoned in 1994 & 1996 respectively 4–6 jh10 Three adjoining, indistinguishable 7–10 year jhum fields cultivated and abandoned between 1988 & 1991 4–6 jh35 Five adjoining, indistinguishable 30–35 year post- jhum fields cultivated and abandoned between 1963 & 1969 8–10 tk4 4 year old teak plantation, planted in 1994 3–4 tk 22 Subset of a 22 year old teak plantation, planted in 1977 4–6 matA Subset of slightly disturbed contiguous mature forest 4–6 matB Subset of undisturbed contiguous mature forest 4–6 matC Subset of undisturbed contiguous mature forest 4–6 The three mature forest plots (matA, B, and C) were of untraceable age (probably >100 years old; [ 12 ]). They were characterized by high tree density, canopy cover, and a sparse understorey with few herbs or true shrubs (not tree saplings). One of the sites (matA) was slightly disturbed by dead wood and palm leaf extraction, and had a relatively dense understorey in places. Bamboos were mainly restricted to moist gullies, and occasionally in the understorey. The 4-yr teak plot (tk4) was a young plantation characterized by a monodominant stand of teak trees. The understorey was sparse, with some tall grass, shrubs (mainly Lantana camara ) and occasional herbs. The 22-yr teak plantation site (tk22) had a monotonous, uniform structure characteristic of a mature, managed teak monoculture. Undergrowth was sparse, consisting mostly of tall grass and Lantana sp. Table 2 summarises differences in four habitat parameters that show broad contrasts between chronoseres. These results are very similar to those of a another study in the same region [ 12 ]. For the purposes of these comparisons, data for the two undisturbed mature forest plots matB and matC are presented together because they are were very similar in macrohabitat characteristics. Table 2 Differences in four macro-habitat parameters across plots. All variables were normally distributed, but not homoscedastic (Levene's test, p < 0.001), so Tamhane's T2 (a conservative pair wise comparisons test based on a t test) was used as a post-hoc multiple range test (F ⇒ F-ratio of one-way parametric ANOVA; ** ⇒ p < .005; * ⇒ p < .05; – ⇒ Not significant;). (a) Tree density (F = 79.232) Plot Mean / 250 m 2 ± S.E. jh1A&B jh5 jh10 tk4 tk22 jh35 matA jh1A&B 00.41 ± 0.26 jh5 01.52 ± 0.96 - jh10 03.38 ± 0.95 - - tk4 34.05 ± 3.04 tk22 24.45 ± 0.87 jh35 15.32 ± 1.30 matA 27.67 ± 2.05 - - matB+C 20.33 ± 1.76 - - - (c) Bamboo culm density (F = 194.30) Plot Mean / 25 m 2 ± S.E. jh1A&B jh5 jh10 tk4 tk22 jh35 matA jh1A&B 00.00 jh5 96.36 ± 5.05 jh10 62.86 ± 4.85 tk4 00.00 - tk22 00.00 - - jh35 30.26 ± 3.85 matA 00.01 ± 0.21 - - - matB+C 01.14 ± 0.15 - - - - (b) Canopy cover (F = 139.38) Plot Mean (%) ± S.E. jh1A&B jh5 jh10 tk4 tk22 jh35 matA jh1A&B 12.07 ± 1.67 jh5 67.91 ± 2.79 jh10 69.79 ± 1.71 - tk4 37.25 ± 2.58 tk22 51.33 ± 4.61 jh35 76.70 ± 1.62 - - matA 72.64 ± 2.03 - - - matB+C 80.68 ± 1.86 ** * - - (d) Shrub density (F = 12.21) Plot Mean / 25 m 2 ± S.E. jh1A&B jh5 jh10 tk4 tk22 jh35 matA jh1A&B 25.85 ± 2.86 jh5 25.59 ± 3.31 - jh10 19.58 ± 2.29 - - tk4 11.28 ± 1.19 - - tk22 13.99 ± 2.08 - - - jh35 27.58 ± 3.21 - - - * - matA 45.24 ± 4.26 ** * matB+C 39.37 ± 4.04 * - ** - - Eight factors were extracted after Principal Component Analysis (PCA), and by Varimax rotation of the factor structure, which explained a cumulative 85.8% of the variation (see methods). Eigenvalues, factor loadings and factor scores are given in Additional file 3 . The ordination of the sampling plots based on scores of the first two PCA factors is shown in Figure 1 . This ordination was very similar to one obtained by non-metric multidimensional scaling (NMDS) [ 17 ]. The two gradients of vegetation recovery have very different trajectories of change in habitat attributes. The predominant macro-habitat characteristic along the factor 1 axis is high bamboo abundance, while high positive loading on the factor 2 axis indicates tree-forest dominated habitat. The gradient towards mature forest succession includes intermediate stages dominated by bamboo, which are succeeded by a tree dominated forest. Figure 1 Plot of scores of first two PCA factors. Vectors are drawn to show the trajectories of the two gradients of habitat recovery. The chronosere codes are as follows- jh1A , 1B , 5 , 10 & 35 : jhum fallows ranging from 1 to 35 years; tk4 & 22 : teak plantation 4 and 22 years old; matA , B , & C : mature forest plots. See methods and Table 1 for more details. In general, although there is a change towards a tree dominated habitat in both recovery gradients, the end result is very different because the 22 year teak plantation is a monoculture, whereas the mature forest consists of a diverse tree community. Successional changes in frog and lizard communities The three sampling techniques used in conjunction during the study (see methods) yielded sixteen frog and seventeen lizard species. Figure 2 shows changes in species richness, and Figure 3 differences in community composition for frogs and lizards along the two recovery gradients. Clearly, there are distinct similarities in overall community composition between the early jhum fallows and teak plantation communities on one hand, and the mature forest and the 35 year jhum fallows on the other. Figure 2 Change in species richness of frogs and lizards with chronosere age along teak plantation and mature forest recovery gradients. Both gradients have 1 yr jhum fallows (jh1A&B) as the starting point. The number of species increases logarithmically with succession towards mature forest for both taxonomic groups, but the change is much more striking in the case of frogs. Species richness does not seem to change much with recovery time on the teak gradient. The age of mature forest, known to be >100 years old, was assigned an arbitrary value of 150 years. Figure 3 Dendrogram of similarities in frog and lizard (combined) communities across plots. See text for explanation. Community overlap was calculated with the Bray-Curtis measure, and sites clustered using the UPGMA algorithm. The pattern of recovery is very different for the two gradients. For the mature forest succession gradient, the rate of frog and lizard community recovery is similar to that found for birds by Raman [ 12 ] in the same region in Northeast India, with the community approaching mature forest characteristics after about 30 years. Even more remarkably, this timescale is also comparable with those reported by similar studies on other fauna elsewhere in the tropics [ 10 ]. The gradient from jhum to mature teak plantations on the other hand, seems to show little change in species richness or composition even after 22 years of plantation growth. It is worth noting that there are dissimilarities in the manner of species accumulation for frogs vs. lizards. There is much less augmentation of species number in the case of the latter, the main reason for this being that younger chronoseres support more lizard than frog species richness. Species accumulation curves (see Additional file 4 ) show that these differences are not sampling artefacts. Moreover, across chronosere species turnover (see methods) for lizards is significantly higher than that for frogs (Student's t-test, two tail p < 0.05), indicating that lizard community succession was characterized by relatively high replacement and low accumulation of species. Guilds Ecological groups defined by non-metric multidimensional scaling (NMDS) of the niche based dissimilarity matrix for the entire assemblage are shown in Figure 4 . The NMDS configuration was derived in 2 dimensions with low stress and high RSQ values, indicating a very good representation of actual niche dissimilarities [ 18 ]. On dimension 1, the dominant niche characteristic determining high negative loadings is arboreality, and high positive values indicate that the species is predominantly terrestrial. On dimension 2, higher positive values indicate predominantly diurnal diel activity pattern, and negative values indicate crepuscular and/or nocturnal activity pattern. Identities of species in each group are in Additional file 4 . Of the five EGs, two consist of both frogs and lizards: the nocturnal arboreal (NA) group with eight species of frogs (mostly tree frogs) and four species of lizards (all gekkonid lizards), and the crepuscular-nocturnal terrestrial (CT) group, which consists of seven frogs and one crepuscular-nocturnal lizard. The diurnal arboreal group (DA) consists of five agamid lizards, some of whom are occasionally terrestrial. The diurnal terrestrial (DT) group consists of six skinks and one lacertid lizard. More detailed natural history descriptions of these species can be found in Pawar [ 17 ]. Figure 4 NMDS configuration showing ecological groups (EGs) of frogs and lizards in the assemblage. Each point represents a species. For this configuration, stress = 0.14712 and RSQ =.90076 [17]. Broad characteristics of EGs are as follows: DA= Diurnal, arboreal; NA(L)= Nocturnal, arboreal, all lizards; NA(F)= Nocturnal, arboreal, all frogs; CT= Crepuscular-nocturnal, terrestrial; DT= Diurnal, terrestrial. See Additional file 4 for EG species' identities. Figure 5 shows how EGs are represented along the two recovery gradients. In this paper, representatives of each EG in a sampling plot are considered guilds of that chronosere. Clearly, the number of guilds as well as number of species per guild increases with succession along the gradient leading to mature forest, but not along the one leading to teak monoculture. The species accumulation during natural forest succession is mainly due to augmentation of crepuscular and nocturnal guilds. It is also worth noting that the DT and DA groups, which are consistently present along both gradients of recovery, also have the maximum niche overlap (distance between pairs of species is the smallest for these groups in the NMDS niche space). The implication of this fact is discussed below. It is due to these two guilds that successional lizard communities show the high species turnover and low accumulation noted above. Figure 5 Representation of ecological groups along gradients of habitat recovery. Each EG for a particular habitat is effectively a guild. Note that the number of guilds increases with succession along the jhum to mature forest gradient, but not along the teak gradient. See Figure 4 for guild identities, and Additional file 4 for species' that make up each EG. Phylogenetic structure Figure 6 shows the ratio of species to genera (S/G ratio) of guilds in different chronoseres. The S/G ratio increased with succession towards mature forest in the NA guild, and to a lesser extent, in the CT guild. The S/G ratio of the NA, DT and DA guilds was variable, and did not change directionally with habitat recovery. In general, across all chronoseres irrespective of which recovery gradient they belonged to, the number of guilds represented in each chronosere was positively correlated with phylogenetic structure (S/G ratio averaged across guilds; Spearman R = 0.92, p < 0.0002) and the species richness of the chronosere (R = 0.88, p < 0.01). This suggests that the ability of chronoseres to support a larger number of guilds predicts species number as well as phylogenetic structure. Figure 6 Trends in phylogenetic structure (species/genus ratio) in five guilds across chronoseres. An "x" indicates that a guild is absent. The S/G ratio increases with time of habitat recovery in the nocturnal guilds, but not for the diurnal guilds. See text for discussion. These results on successional changes in guild structure and representation indicate a distinctly non-random sequence of community assembly, as certain guilds appear in later stages, followed by increase in their species richness and in many cases, phylogenetic structure. Habitat attributes that determine these changes are explored in the next section (see below). Correspondence between habitat factors and frog-lizard community succession Table 3 shows the results of correspondence tests between Euclidean dissimilarity matrices calculated from the eight PCA factors and frog-lizard species compositional dissimilarity matrices for different levels of community structure. As the factor structure of the PCA analysis was rotated to maximize the orthogonality of factor loadings, these matrix correspondence tests are statistically similar to performing partial mantel tests (partial correlation) with multiple variables [ 19 ]. The hierarchical nature of the correlations in Table 3 and the fact that guilds are correlated with different, orthogonal composite variables is interesting, and offers answers to the third question addressed this paper: what aspects of habitat change influence frog and lizard community recovery at different levels of community organization? Table 3 Correlation between dissimilarity matrices based on eight PCA factors (unsquared Euclidean distances), and different levels of community organisation (Jaccard's index). The correlation coefficients are followed by significance (p) values in parentheses. The p-values were estimated by 1000 Monte Carlo randomizations of each pair of matrices. Correlations with p values >0.05 not reported. See the text and Additional file 3 to see loadings of habitat variables for the PCA factors. Community/guild Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 Factor 7 Factor 8 Frogs + Lizards 0.762 (0.003) Frogs 0.5031 (0.003) 0.467 (0.019) Lizards 0.672 (0.005) 0.375 (0.033) CT 0.331 (0.035) 0.417 (0.016) 0.402 (0.016) DA 0.630 (0.008) DT 0.608 (0.003) NA(F) 0.347 (0.025) 0.482 (0.037) NA(L) 0.362 (0.004) 0.417 (0.030) Higher-order community structure The strongest association is between factor 2 and overall species composition (frogs and lizards combined) across chronoseres. Factor 2 was strongly and non-linearly correlated with age along both teak and mature forest succession gradients (logarithmic fit, R 2 = 0.85, and 0.97, respectively), and represents deterministic, linear aspects of vegetation succession. It has high positive loadings for tree species richness, and macro-habitat variables such as tree density, canopy cover, and canopy height, most of which increase deterministically along both gradients of habitat change. Among the measured variables, these are primary and independent, which over time drive changes in secondary (microhabitat) variables such as bamboo density, shrub abundance, and various measures of habitat heterogeneity (see methods). This factor clearly influences species composition at all levels of frog and lizard community structure. Frog vs. Lizards Along with factor 2, the frog subcommunity was also associated with factor 7, which shows no significant age determinacy along either gradient of habitat recovery. This factor has high positive loading for soil moisture content, which is an important limiting factor for frogs. The lizard subcommunity was associated with factor 8 along with factor 2. Factor 8 has high loading for soil moisture variability, which is highest in chronoseres with spatial variation in insolation. This factor is crucial for diurnal lizards, many of which are heliotherms. Factors 7 and 8 are probably also surrogates of unmeasured or unclassified variables which influence successional changes in these two communities. Guilds Three out of five guilds are secondarily correlated with factors orthogonal to factor 2. The two that were not, i.e., the diurnal-arboreal (DA) and diurnal-terrestrial (DT) groups, were correlated with factor 2. This suggests that in contrast to other guilds, these two, which are both made up only of lizards, are directly influenced by a hierarchically higher order of habitat attributes. These were also the two groups that showed non directional trends in species richness as well as phylogenetic trends along habitat recovery gradients (Figures 5 and 6 ). Along with factor 2, the crepuscular-nocturnal terrestrial (CT) group was correlated with factor 1 and 4. Factor 1 scores increase and then decrease with plot age along both habitat recovery gradients (2 nd order polynomial fit, R 2 = 0.99, and 0.82, respectively). This factor had high loading (defined as ≥ ± 0.65; see Additional file 3 ) positive for both macro- and micro-habitat variables such as bamboo density canopy cover, leaf litter cover and depth and negative loadings for many habitat heterogeneity variables such as CVs of canopy cover and litter cover. These variables are interpretable as ones that are associated with, or influence ground microhabitat conditions. Factor 4 decreased logarithmically with age along both teak and mature forest gradients (R 2 = 0.62, and 0.34, respectively). This factor had no strong loadings, but is associated with shrub density, canopy height variability and tree density, all of which also affect ground cover, and can be considered macrohabitat variables. The nocturnal arboreal frog group (NA(F)), was correlated with factor 7, which is non-deterministic with respect to chronosere age. This factor as a high loading for soil moisture, which by itself is difficult to interpret as a variable directly affecting this ecomorphological group. It is likely that this factor is a surrogate for an unmeasured or unclassified variable. Lastly, the nocturnal arboreal lizard group (NA(L)) is correlated with factor 8 along with factor 2. Factor 8 shows a weak negative linear relationship with recovery age along both gradients gradient (R 2 = 0.209 and 0.18 for teak and mature forest gradients, respectively). It has high positive loading for CV of soil moisture, which as mentioned above, is highest in chronoseres with spatial and/or temporal variation in insolation. Among the measured variables, factor 2 probably subsumes most habitat parameters that affect both NA groups directly (see next section). Adaptive zones? Can biologically meaningful adaptive zones be interpreted from these associations? As each factor is orthogonal with respect to the others, factors subsume different habitat variables, or their variability in the same variable. Note that the composite variable represented by each factor consists of negative as well as positive loadings of variables. This means that if a guild was associated with a factor, both positive and negative trends in different variables affected it simultaneously, together representing a composite adaptive zone. However, an important fact to consider here is that these "adaptive zones" thus identified may actually be surrogates for actual sets of unmeasured variables. Raman [ 12 ] inferred that floristics (tree species composition) and physiognomy (vertical stratification) were the dominant habitat attributes that independently predicted changes in bird species composition at the level of communities, but not at much at the level of guilds. In the case of frogs and lizards, factor 2, which includes a measure of floristic attributes (tree species diversity), is a strong predictor of frog and lizard community composition at all levels. But factor 2 also includes numerous structural attributes that are correlated with tree species diversity, from canopy height to understorey and ground habitat structure, all of which have equal or higher positive loadings. Also, Figure 7 shows that understorey habitat complexity increases with post- jhum succession towards mature forest. Figure 7 The relationship between transect sampling time and habitat complexity. The NAW time varies across habitat, and increases with habitat complexity, whereas DAW is constant. The reason for this is that more complex habitats needed more searching time. The index of complexity was calculated by summing the coefficients of variance for various understorey habitat structure variables. Sample sizes of transects were: jh1A = 15, jh1B = 13, jh5 = 14, jh10 = 16, tk4 = 15, tk22 = 15, jh35 = 38, matA = 17, matB = 28, matC = 21. Thus, it is difficult to infer the extent to which tree species diversity per se influences frog and lizard community structure. Previous work has shown that unlike endothermic vertebrates, amphibian and reptile distributions are likely to be influenced more strongly by abiotic rather than biotic features [ 20 ]. The effect of physiognomy on the other hand, is definitely important, though at a different scale than for birds. The idea that a habitat with higher structural complexity will support more species [ 21 - 25 ], and have a strong influence on re-colonisation success [ 26 ], has been shown for amphibians and reptiles (but see [ 27 ]). It can therefore be inferred that factor 2 subsumes nested subsets of biotic and abiotic variables that directly affect the (mean) fitnesses of species' populations in different guilds. Also, it is clear that guilds are also associated with other, independent variables sets that can be considered to comprise additional aspects of each member species' adaptive zone. Factors 3, 5, and 6 showed no significant association with any level of community composition. The obvious reason for this appears to be that unlike other factors, these are completely non-deterministic with respect to age of succession, thus representing temporally and/or spatially stochastic attributes that were unlikely to show any influence on the conspicuously deterministic nature of frog and lizard community and guild (except for the DT and DA groups) succession (See Figures 2 , 3 , 5 and 6 ). At this resolution, it is impossible to say whether these variables are adaptively significant for certain subgroups/species of frogs and lizards or not. Nevertheless, this complex, nested pattern of these alleged adaptive zones, is ecologically realistic (see [ 28 ]). Although difficult to interpret at this level of resolution, this hierarchical partitioning of variables is an indicator of which attributes of habitat change influence community assembly and turnover with such gradients of vegetation succession. Composite variables and successional changes in community characteristics Table 4 shows the predictive ability of the different habitat factors for species richness, guild abundance, and phylogenetic structure in communities and guilds. As expected, factor 2 predicts increase in overall species richness, number of guilds represented, and number of species per guild. However, it does not predict overall phylogenetic structure (measured as the average of S/G ratios across guilds represented in each chronosere). Instead, it predicts the phylogenetic structure of all guilds except DT. Factor 1 predicts species richness as well as S/G ratio in the DA group, and factor 4 predicts the S/G ratio of NA(L). No community characteristics were correlated with factors 3,5,6,7 or 8. Table 4 Correlation between availability of composite variables (factor scores) and various measures of community change. Coefficients are Spearman's R, with p-levels in parentheses. Correlations with p > 0.05 not reported. No community characteristics were correlated with Factors 3,5,6,7 or 8. Factor 1 Factor 2 Factor 4 Species Richness Overall 0.77 (0.009) DA 0.81 (0.004) DT CT 0.91 (0.000) NA(F) 0.82 (0.003) NA(L) Number of Egs 0.69 (0.028) Species per EG Overall 0.72 (0.019) CT DA DT NA(F) NA(L) S/G ratio Averaged across EGs CT 0.66 (0.036) DA 0.85 (0.002) DT NA(F) 0.71 (0.020) NA(L) 0.80 (0.006) The DT group does not show correlation with any of the factors. Interestingly, this ecological group along with the DA group, also occupies the smallest niche space (having the maximum niche overlap in the NMDS space; see Figure 4 ), has the most consistent presence across chronoseres (but with species turnover) and a phylogenetic structure that varies non-directionally along successional gradients (Figure 6 ). Similar patterns have been observed for diurnal terrestrial herpetofauna (which are largely lizards) elsewhere [ 29 ]. Members of this group also have the highest population densities, and most have wide geographic distributions (Pawar, unpublished data). All these data strongly suggest that this guild is not resource constrained in chronoseres along the habitat recovery gradients, and is more randomly assembled during recovery than any of the other groups. In general, these results help explain the trends seen in Figures 2 , 3 , 5 and 6 by indicating attributes of habitat change that drive changes in community structure in successional frog and lizard communities. The succession of jhum fallow towards mature forest involves a deterministic, directional change in attributes that allow coexistence of successively more speciose and phylogenetically structured communities. In terms of change in species richness, these results are qualitatively similar to those of similar work on bird, butterfly, and reptile communities [ 11 - 13 ]. Previous work has not however attempted to look at phylogenetic structure for such successional communities. The jhum to teak monoculture gradient also has many aspects of deterministic habitat change, but apparently not for the variables that are essential for a diverse community. The trajectory of habitat change also indicates that this pattern is unlikely to change with transition towards older plantations either. No previous data exists on herpetofaunal community changes in post- jhum monoculture plantations. Conclusions By comparing disparate trajectories of habitat change and recovery of different taxonomic groups, this study provides useful insights into faunal community change in response to habitat recovery. To summarise, the results show that (1) The two gradients of habitat recovery are very different and accordingly affect frog and lizard community assembly differently, (2) Although both groups increased in species richness with habitat recovery, lizards had higher species turnover, combined with lower species augmentation within each recovery gradient (3) Looking at a finer scale of community organization, assembly appears to be driven by changes in guild representation and composition, where some guilds change directionally with age of habitat recovery by species augmentation, while others change by species turnover (4) Guilds that showed directional increase in species richness also increased in phylogenetic structure (5) Hierarchies of community organisation were affected by composite, nested habitat attributes that correspond to particular niche axes, and (6) the increase in species richness along the mature forest gradient in contrast to lack of change along the teak gradient was due to availability (or lack thereof) of variables that comprise these complex adaptive zones. Also, the results show that a niche-based guild classification reveals patterns that would have been hidden in the gross response pattern of the entire community. Some indication of the qualitative nature of potential evolutionary and ecological processes in community turnover comes from the fact that changes in phylogenetic structure are tied to guild structure in the communities. Using phylogenetic techniques, recent work has demonstrated the importance of evolutionary adaptation in assembling ecological communities [ 4 ]. It is clear that specialisation on different subsets of resources, in a habitat drive the origin and as well as persistence of diversity [ 30 ]. Frogs and lizards have incongruent patterns of community succession, mainly because they generally differ in fundamental niche dimensions axes such as diel activity [ 31 ]. However, although most lizards are diurnal and most frogs nocturnal, there are many sub-lineages that are an exception, and species do share niche space transcending taxonomic boundaries (ecological groups in this paper). Such subgroups probably have congruent ecological and evolutionary dynamics. It is an open question as to what extent vegetation succession leads to changes in the number of adaptive peaks and corresponding changes in mean fitnesses of species' populations such that multiple species can persist in the same habitat. In more ecological terms this is same as asking how habitat succession leads to changes in niche availability, occupancy, and overlap (due to character displacement, for example). Another related question, that was partly explored using the S/G ratios in this paper, is whether similar adaptive zones (or niches or adaptive peaks) tend to be occupied by more closely related taxa. The results here do indicate that this may be true for such gradients of community change, as phylogenetic and guild structure increase directionally and in tandem with succession towards mature forest. Whether this change is driven by immigration from the regional gene pool or due to local divergent adaptation is an interesting question [ 15 ]. Reptiles, and to a greater extent amphibians, have limited dispersal ability compared to most vertebrates. This distinction in itself may drive differences in local adaptation and community assembly from other biotic groups. Conservation issues The time scale of recovery on the jhum -rainforest succession gradient, which is about 30 years for both frogs and lizards, and suggests that recovery of diverse communities can be relatively fast, as has been reported for other fauna [ 10 ]. However, this pattern of community recovery (or re-assembly) is tightly coupled to changes in certain sets of habitat attributes, which in turn are dependent upon vegetation succession wherein post- jhum chronoseres are gradually replaced by trees. This vegetation succession is obviously reliant on seed rain/dispersal from nearby mature forests. In this region and many other areas Southeast Asia, apart from continued pressure from shifting cultivation and shortening cultivation cycles, it has also become popular practice to plant and maintain monocultures of timber species. As the results of this study indicate, such plantations are unlikely to support natural recovery of faunal communities, and will harbour lower biological diversity compared to primary forest. It is possible that the combined effects of short jhum cycles, plantation forestry and invasion by non-native species such as Lantana and Eupatorium will lead to the local extirpation of even remnant forest patches. This loss of recolonisation pools for flora and fauna, will alter natural trajectories of succession, and strongly impact the biological diversity supported by the landscape. It is therefore important that conservation and prioritisation agencies in these areas consider the value of habitat mosaics containing even small patches of primary forest vegetation. Methods The study was carried out from November 1998 to April 1999 in and around Ngengpui Wildlife Sanctuary (WLS; 21°56'N – 24°31'N and 92°16'E – 93°26'E) in south Mizoram, Northeast India. The study area covers about 200 sq. km. (see Additional file 1 for maps). A combination of high annual precipitation and temperature, and low elevation supports a predominantly tropical evergreen [ 32 ] climax vegetation in the area. Shifting cultivation is the primary mode of agriculture here. While most of the area within Ngengpui WLS is mature or primary forest, the surrounding areas are a mosaic of bamboo-dominated sites, mature forest fragments, teak Tectona grandis plantations and abandoned shifting cultivation ( jhum ) fallows of varying ages. All primary forest is referred to as "mature forest" throughout the paper because it is often difficult to determine the age of ostensibly primary tropical forest, especially in areas with poorly known history of land use and recovery [ 12 , 33 ]. Further details and supporting literature about the geology, vegetation, and land use patterns in the study area can be found in Pawar [ 17 ]. Sampling plots Ten sampling plots representing mature and successional vegetation stages of known ages were established [ 17 ] (Table 1 ). To control for recolonisation potential, all secondary plots were selected such that at least 50% of the perimeter abutted mature forest, and the edge was within 100 m from contiguous mature forest. All plots had a slope of 0–20° and were within an altitudinal range of ca. 150–350 m above sea level. As the study was focused on terrestrial frogs and lizards, all plots were at least 100 m away from large perennial water bodies. To minimize spatial autocorrelation, all plots were at least 2 km (straight distance) from each other, with the replicates (e.g., the two 1 yr fallows) being the furthest apart (ca. 10 km). Vegetation sampling, habitat variables and gradients of habitat recovery Vegetation composition and habitat structure variables were sampled on randomly located 10 × 25 m belt transects [ 13 , 17 ]. Transects were cut short whenever an edge of the site was reached. The number of transects sampled were, six each in Jh1A, Jh1B, Jh5, Jh10, and Jh35, and five each in tk4, tk22, matA, matB and matC. Tree density and tree species richness was sampled on the whole area of each transect. All trees >20 cm GBH were enumerated, while the rest were classified as 'shrubs'. Density of bamboo culms, shrubs, palms, bananas, and tall grass clumps was estimated in each of six 2 m radius circular plots laid at 5 m intervals on the transect, beginning from the starting point of the transect. Percentage cover of herbaceous forms and leaf litter, dead woody matter abundance and liana abundance in each circular plot were estimated visually. Percentage canopy cover from ground level was estimated with a hand-held canopy densiometer from the centre of each circular plot. Litter depth was gauged by pressing a blunt rod of 0.5-cm diameter at 5 random points in each circular plot, and counting the number of leaves pinned under it. Principal Components Analysis (PCA) was used to identify different aspects of habitat change with vegetation succession and collapse the list of raw variables into composite factors that could potentially predict frog and lizard community structure. The factor structure was rotated using the Varimax method to obtain clear loading patterns [ 18 ]. As additional variables, within-habitat coefficient of variation (CV) of variables was also used along with the raw data as measures of habitat heterogeneity. Within habitat variation was considered potentially informative as it is an important feature of the adaptive landscape [ 30 ]. Habitat data were collected at comparable times of each month for all plots, and these CVs are unlikely to be due to temporal fluctuations. Data were square root transformed if they deviated from normality. For a list of variables used in the analyses, see Additional file 3 . As the objective of the analysis was to combine variables into composite, orthogonal factors that could potentially account for community and guild structure, all factors with eigenvalues = 0.8 were extracted, irrespective of the number of factors thus extracted. Although somewhat arbitrary, in essence this eigenvalue threshold ensured that a factor was included only if it extracted approximately as much as one raw variable [ 18 ]. Although all extracted factors were used as predictors of community structure (see below), in order to obtain a graphic, low dimensional representation of the two gradients of habitat recovery, scores of only the first two factors were plotted. Deterministic sets of variables that changed directionally with chronosere age were identified by regressing scores of each factor against chronosere ages. Frog and lizard sampling The low abundance of amphibians and reptiles and unstandardised sampling methodology in tropical Asia reduces the reliability of species diversity estimates and hence community structure analyses [ 8 ]. Taking this problem into consideration, three techniques were used in conjunction to maximize inventorying effort – (i) belt transects, (ii) pitfall trapping and (iii) systematic searching. All these techniques are oriented towards sampling terrestrial, and non-canopy arboreal species, and to further increase the sampling efficiency, the study was restricted to terrestrial, non-fossorial, and non-canopy frogs (Amphibia: Anura) and lizards (Reptilia: Sauria, excluding family Varanidae). Although this excluded a few amphibian and reptile groups, it ensured that taxonomic groups unsuited for the chosen sampling techniques were not unnecessarily included, thus augmenting the reliability of the data. To distribute sampling effort effectively among the ten plots, sampling was carried out in sampling 'sessions' of ten days each. Eleven such sessions (= 110 days) were completed, starting from 15th December 1998, to the end of April 1999. Sufficient time was allocated to all three sampling techniques during each session. Belt transects To improve detection and gather information for delineation of EGs (see below), the traditional transect method was modified by eliminating pseudoreplication and sampling both nocturnal and diurnal species on the same transect [ 34 , 35 ]. The former was achieved by establishing fresh 50(length) × 3(width) × 3(height) m transects during each session, which were sampled only once. To detect both nocturnal and diurnal taxa, each transect was walked in both directions (to and fro) by two observers. The diurnal animal walk (DAW) was first, and was conducted at a steady pace fixed for all plots (ca. 20 min/50 m). Any animal seen leaving the transect area was recorded as being present on it. Care was taken to cause minimal disturbance to the habitat, and no active searches were done. The nocturnal animal walk (NAW), conducted in the direction opposite to the DAW, was focused on intensive microhabitat searching within the same 50 × 3 × 3 m area. All nocturnal animals found on the DAW were included in the analyses, but to reduce the possibility of re-recording the same animal, diurnal animals found on the NAW were not. Behavioural and microhabitat data were recorded for every animal detected (see below). All transects were sampled immediately after they were established, between 1000–1400 hrs during winter (mid-December to February) and 0900–1300 during summer (March and April). There was no noticeable species turnover with season, so winter and summer data were not analyzed separately [ 17 ]. The belt transects also yielded abundance data, which are not used in this paper [ 17 ]. Although time taken for the NAW was more or less constant within a chronosere, it varied considerably across plots. The DAW time on the other hand, was more or less consistent. This strategy was used because just as sampling effort needs to be proportional to habitat heterogeneity, higher microhabitat complexity calls for proportionally greater searching effort. Figure 7 shows how well this sampling strategy was implemented. There is a strong positive correlation between an index of microhabitat complexity (calculated as the sum of the coefficients of variance for various understorey habitat structure variables listed in Additional file 3 ) and time spent on the NAW, but not the DAW. Thus, though no extra time was needed to sight active (diurnal) animals in more complex habitats, the time needed for microhabitat searching (and hence NAW time) increased along a gradient of increasing habitat complexity from the 1-yr fallows and teak plots to mature forest. A total of 192 belt transects were completed, from a minimum of thirteen in jh1B to thirty-eight in jh35 (See Figure 7 for sample sizes). Pitfall trapping This technique was used to supplement species inventorying from the belt transects, and for an unbiased measure of the effects of weather on herpetofaunal activity and hence sampling efficiency. Comparisons of trapping frequency across plots over the study period are not used in this paper. Each pitfall array was, 'Y'-shaped, with three terminal (30 cm diam. × 60 cm depth) and one central (50 cm diam. × 70 cm depth) cylindrical aluminium funnel pitfall traps buried in the ground. The traps were connected with three opaque plastic-sheet fences (the arms of the 'Y') 0.4 m high and 5 m long, held up by bamboo stakes. In all, 22 arrays were placed, with two in each plot except for the large Jh35, which had four. Arrays were at comparable distance from plot edges, and on similar slope. Systematic trapping was initiated ten days after trap were established. Traps were opened for 5–10 consecutive days, and checked according to habitat characteristics, taking into consideration the level of exposure trapped animals were likely to be subjected to; plots with open habitat, such as jh1A were checked most (every alternate day) and those with relatively closed habitat such as matA were checked least frequently (every third day). Most specimens (95.2 %) obtained from pitfall trapping were released a minimum of 100 m away from the array, either in the same site, or in similar habitat elsewhere. A few were retained as voucher specimens. Systematic searching At the end of a sampling session in a plot, far ranging searches were carried out. This augmented species inventorying, and provided information crucial for EG classification (see below). Periodically, nocturnal searches were also made to collect information about the refuge of diurnally active animals, and also to confirm the presence or absence of species in different chronoseres. Identification of taxa Irrespective of the sampling technique, animals detected were caught whenever possible, and identified in hand. All those that escaped were identified to a justifiable level or excluded from the analyses. A few individuals of taxonomically problematic species or taxa were preserved for later identification. Sampling efficiency The effectiveness of sampling was evaluated by species accumulation curves (see Additional file 4 ), and the effort adjusted after a mid-fieldwork examination of species richness data across chronoseres. While all the early succession stages and teak plantations reach an asymptote very soon, the 30–35 year fallow stopped yielding new species only by the eighth sampling session, while mature forest continued to yield new species till the final sampling session. Characterization of frog and lizard community succession Overlap between recovering frog and lizard communities was measured with the Bray-Curtis measure between all possible pairs of chronoseres using presence absence data of all species (see Additional file 4 ). The resultant dissimilarity matrix was then used to generate a dendrogram using the UPGMA clustering algorithm [ 18 ]. Species turnover in sequential frog vs. lizard communities was compared using the mean Jaccard's dissimilarity value between all chronosere pairs calculated from separate presence absence data for the two groups [ 36 ]. Ecological group classification and phylogenetic structure Life history and behavioural traits were used to group species. These are often called guilds (e.g., [ 37 ]), but are referred to as ecological groups (EGs) here because the classification covers species from all chronoseres, including those that belonged to separate, non-interacting communities. The representatives of each EG in a particular community or chronosere on the other hand, can be considered a guild of that habitat's community. The life history and behavioural traits used for the EG classification were: diel activity period, habitat use when active, habitat use when resting, substrate temperature when active, air temperature when active, relative humidity when active, substrate moisture when active, resting refuge, resting refuge temperature, resting refuge substrate moisture and foraging tactic. To validate this data, information from literature and consultations with regional herpetologists was also used. These data, collected at different measurement scales, were rescaled to discrete categories to which species were allocated as absent or present. From this binary data, a dissimilarity matrix was calculated between all species using the Bray-Curtis measure [ 19 ]. The dissimilarity matrix was then scaled using non-metric multidimensional scaling (NMDS). NMDS geometrically represents dissimilarities in a graphical, low-dimensional space, and is a robust method to represent ecological distance [ 18 , 19 ]. See Additional file 4 for the list of species included in the EG classification. Phylogenetic structure was measured as the ratio of number of species to the number of genera (S/G ratio) in each EG. A similar approach has been used in studies addressing questions about phylogenetic structure in ecological communities [ 15 ]. Community – Habitat interrelationships To test which habitat attributes influenced community structure, Mantel tests of correspondence between dissimilarity (distance) matrices [ 18 , 19 , 38 , 39 ] were used. Dissimilarity matrices between sites were generated based on differences in set of composite variables (factors) extracted by the PCA analysis (unsquared Euclidean distances), and for different levels of frog and lizard community composition (from entire community to guilds defined by the EG classification using Jaccard's index) [ 18 , 19 ]. Significance of correlation coefficients was tested by 1000 row-column Monte Carlo randomizations for each pair of matrices. To test whether the availability of composite variables (PCA factors) that predicted community and guild structure identified by the matrix correspondence tests did indeed influence community succession and phylogenetic structure along gradients of habitat recovery, correlations between sums of factor scores and species richness, ratio of species number/guild number and S/G ratios across chronoseres were tested. Authors' contributions SSP conceived the study, carried out the fieldwork, performed the data analyses, and drafted the manuscript. BCC and GSR participated in design and coordination of the study. GSR also supervised the vegetation identification and habitat classification. All authors read and approved the final manuscript. Supplementary Material Additional File 2 Photographs of habitat types. Representative photographs of habitat types Click here for file Additional File 3 Results of PCA along with list of habitat variables used. PCA Results Click here for file Additional File 4 Species accumulation curves and frog and lizard species' lists. Species accumulation curves and lists Click here for file Additional File 1 Maps of study area. Location map of study area sampling plots with respect to vegetation types Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC514559.xml
517939	Rapid and reliable extraction of genomic DNA from various wild-type and transgenic plants	Background DNA extraction methods for PCR-quality DNA from calluses and plants are not time efficient, since they require that the tissues be ground in liquid nitrogen, followed by precipitation of the DNA pellet in ethanol, washing and drying the pellet, etc. The need for a rapid and simple procedure is urgent, especially when hundreds of samples need to be analyzed. Here, we describe a simple and efficient method of isolating high-quality genomic DNA for PCR amplification and enzyme digestion from calluses, various wild-type and transgenic plants. Results We developed new rapid and reliable genomic DNA extraction method. With our developed method, plant genomic DNA extraction could be performed within 30 min. The method was as follows. Plant tissue was homogenized with salt DNA extraction buffer using hand-operated homogenizer and extracted by phenol:chloroform:isoamyl alcohol (25:24:1). After centrifugation, the supernatant was directly used for DNA template for PCR, resulting in successful amplification for RAPD from various sources of plants and specific foreign genes from transgenic plants. After precipitating the supernatant, the DNA was completely digested by restriction enzymes. Conclusion This DNA extraction procedure promises simplicity, speed, and efficiency, both in terms of time and the amount of plant sample required. In addition, this method does not require expensive facilities for plant genomic DNA extraction.	Background Molecular biological studies of plants require high-quality DNA. Several DNA extraction procedures for isolating genomic DNA from various plant sources have been described, including the salt extraction method and the cetyltrimethyl ammonium bromide (CTAB) method [ 1 ] and its modifications [ 2 , 3 ]. The need for a rapid and simple procedure is urgent, especially when hundreds of samples need to be analyzed. Most methods require the use of liquid nitrogen [ 4 ] or freeze-drying (lyophilization) [ 5 , 6 ] of tissue for the initial grinding, and these processes are unavailable in many regions of the world. After grinding the tissues in various extraction buffers, DNA is extracted with phenol-chloroform, or the extract is dialyzed against EDTA and a buffered Tris-HCl solution [ 7 ]. After extraction, the aqueous phase is concentrated, either by ethanol or isopropanol precipitation [ 8 , 9 ], or with microconcentrators ( e.g ., the Wizard genomic DNA purification system; Promega, USA). However, these methods are not time efficient for consistently obtaining PCR-quality DNA from calluses and plants, since they require that the tissues be ground in liquid nitrogen, followed by precipitation of the DNA pellet in ethanol, washing and drying the pellet, etc. In our laboratory, we investigate the stability of transgenes expressed in calluses or plants transformed by nuclear or chloroplast transformation in tobacco, lettuce, potato, etc. In addition, we need high-quality genomic DNA for Southern blot analysis to confirm homologous recombination in chloroplast transformation [ 10 ]. For our purposes, we desire a simple and fast procedure for obtaining plant genomic DNA for PCR, and good-quality DNA for complete enzyme digestion for Southern blot analysis. Therefore, we present a protocol for extracting genomic DNA from fresh calluses and plant leaves that is applicable to a variety of organisms, regardless of the complexity of their genomes. In addition, we present a rapid and reliable procedure for extracting genomic DNA for PCR or Southern blot analysis from a small amount (~0.5 cm 2 ) of leaf tissue. Results and discussion We describe a simple and reproducible procedure for RAPD or PCR amplification of transgenes from various plant sources. Three different variations of the genomic DNA extraction protocol for RAPD analysis were compared. After simple plant leaf and callus tissue homogenization with DNA extraction buffer using a hand-operated homogenizer, the leaf and callus cells were lysed with 20% SDS. Then, genomic DNA was extracted with the same volume of phenol/chloroform/isoamyl alcohol (25:24:1). An aliquot of the supernatant (~5 μl) was diluted 5 fold with sterile dH 2 O, and PCR was performed using 1 μl of the diluted supernatant as a template (Figure 1 , lane 1). Alternatively, after phenol/chloroform/isoamyl alcohol (25:24:1) extraction, the supernatant was transferred to a fresh tube for a second phenol/chloroform/isoamyl alcohol (25:24:1) extraction followed by a chloroform extraction. An aliquot of the supernatant (~5 μl) was diluted 5 fold with sterile dH 2 O, and PCR was performed using 1 μl of the diluted supernatant as the DNA template (Figure 1 , lane 2). In the third variation, after chloroform extraction the supernatant was transferred to a fresh tube and precipitated with two volumes of ethanol. After washing the DNA pellet with 70% ethanol, the DNA pellet was dissolved in 50 μl of sterile dH 2 O containing 20 μg ml -1 DNase-free RNase A. For PCR, 50 ng of the DNA were used as the template (Figure 1 , lane 3). DNA samples prepared using the three different extraction procedures (lanes 1, 2, and 3 in Figure 1 ) were subjected to PCR amplification using two 10-mer random primers: RAPD-1 and RAPD-2 (Genotech, Korea) (Figure 1 ). All the genomic DNA samples produced a clear, sharp, and reproducible PCR product when primer RAPD-1 was used for PCR amplification (Figure 1A ). Although three variations of the DNA extraction procedure were used, there was little difference between lanes 1, 2, and 3. Only a difference in the intensity of the band was observed, which may be due to the different template concentrations used for the PCR reaction. This result suggests that the supernatant after the first phenol treatment (protocol 1) was sufficiently pure to be used as the DNA template for PCR amplification. Therefore, PCR amplification with another random primer, RAPD-2, was performed using the DNA template extracted using the simplest protocol (Figure 1B ). The PCR amplification was successful, and the same banding pattern was seen when we repeated the PCR amplification. Therefore, we confirmed that the DNA template extracted using the simplest method was sufficient for RAPD, and it was used as the DNA template to amplify specific DNA or transgenes from transgenic calluses or plants. To examine the presence of bar [ 11 , 12 ] or the LTB gene [ 13 ] at a directed site in the chloroplast DNA after homologous recombination in transplastomic tobacco plants, putative transformants were screened by PCR analysis (Figure 2 ). PCR amplification using primer combinations Bar-F/Bar-R, 1-F/1-R, and LTB-F/LTB-R resulted in 550-, 1700-, and 380-bp fragments, respectively. Primers 2-F/2-R produced 2200- or 1900-bp fragments containing bar and LTB, respectively, which confirmed the site-specific integration in the chloroplast genome (Table 1 ). No detectable product was produced using genomic DNA from wild-type plants (Figure 2B , lane 1), demonstrating the specificity of these primers and genomic DNA extracts. Therefore, we concluded that chloroplast DNA was also amplified, although we did not use liquid nitrogen, but simply used a hand-operated homogenizer with a plastic tip. We also successfully amplified specific foreign genes from transgenic tobacco plants transformed using the nuclear transformation method, including the α-interferon (550 bp) [ 14 ], the core epitope of the PEDV gene (420 bp) [ 15 , 16 ], the LTB gene (380 bp) [ 17 ], and the A plus B subunit of the Helicobacter pylori urease gene (2450 bp) [ 18 ] (Figure 3 ). Specific PCR amplification was also conducted using transgenic calluses as well as transgenic plants. In transgenic calluses derived from Siberian ginseng plants, α-interferon was successfully amplified, showing a 580-bp fragment in 1% agarose gels. Using the third protocol, the DNA concentrations obtained were between 20 and 30 μg/0.5 cm 2 plant leaf, and the absorbance ratios (A 260 /A 280 ) were between 1.7 and 2.0. However, the DNA concentrations from rice, maize, and poplar were relatively low (< 3 μg). This may be because homogenization using a hand-operated homogenizer with a plastic tip is incomplete, since the leaves of these plants are stronger than the leaves of tobacco, potato, cabbage, lettuce, and Siberian ginseng. Genomic DNA from various plant sources was electrophoresed on 1% agarose gels, and high-molecular-weight DNA was obtained (Figure 4A ). When the genomic DNA was digested with Eco RI and Hin dIII, the DNA was completely digested, and could be used for Southern blot analysis. Therefore, we concluded that the purity and quality of the genomic DNA was sufficient for enzyme digestion. There are many advantages in using our genomic DNA extraction method to obtain template for PCR amplification. Many different plants could be amplified using the same DNA extraction method and the same PCR protocol. Using this protocol, we successfully amplified DNA repeatedly from all eight plant sources examined. Our procedure is not only very simple, but is also time and cost effective. After homogenization in DNA extraction buffer using a hand-operated homogenizer, the template DNA for PCR could be extracted by phenol/chloroform/isopropyl alcohol treatment. Since this method does not require liquid nitrogen, expensive commercial DNA extraction kits, or ethanol precipitation to produce DNA template for PCR, we can save considerable time and expense. The time required for our DNA extraction method is less than 30 min, which is extraordinary compared with other genomic DNA extraction methods. With our procedure, leaf tissue (~0.5 cm 2 ) is put in a 1.5-ml microfuge tube and homogenized directly; consequently, a very small sample is required for DNA extraction. There is no sample waste with our method, whereas much larger samples are required when plant samples are ground in a mortar and pestle with liquid nitrogen and transferred to a tube. Previously reported techniques require several steps [ 19 ], use of expensive enzymes such as proteinase K [ 20 ], or beads and shakers [ 21 ]. Although the protocol for one-step plant DNA isolation was developed by Burr et al. [ 22 ], if plant material more than 1 mm 2 was used in the extraction, co-extracts (e.g., chlorophyll) were extracted alongside the DNA and inhibited the PCR. On the contrary, our protocol does not require appropriate sample size to extract DNA. Warner et al. [ 23 ] also reported a rapid DNA extraction method in barley, which requires NaOH. However, the extracted DNA samples were easily degraded. The DNA samples extracted by our protocol were very stable and could be stored for a long time without degradation. We find the new method very useful in our laboratory, since limited transgenic plant tissue or callus is sometimes available in a culture bottle. Therefore, the simplicity, efficiency, speed, and lack of a requirement for expensive facilities make our method an attractive alternative to existing methods of genomic DNA extraction. Conclusions Our objective was to extract genomic DNA with a simple and fast procedure for PCR and enzyme digestion. The present protocol is for extracting genomic DNA from fresh calluses or plant leaf tissues that is applicable to a variety of organisms, regardless of the complexity of their genomes. Our procedure is not only very simple, but is also time and cost effective. Since this method does not require liquid nitrogen, expensive commercial DNA extraction kits, or ethanol precipitation to produce DNA template for PCR, we can save considerable time and expense. In addition, a very small sample is required for DNA extraction. Methods Plant material We examined plant material from plant collections commonly used for foreign gene expression: tobacco ( Nicotiana tabacum ), potato ( Solanum tuberosum ), cabbage ( Brassica oleracea ), rice ( Oryza sativa ), lettuce ( Lactuca sativa ), maize ( Zea mays ), poplar ( Populus nigra ), and Siberian ginseng ( Eleutherococcus senticosus ). The plants used for genomic DNA extraction were grown in a culture room or greenhouse. Tobacco, potato, cabbage, lettuce, and Siberian ginseng were grown in a culture room. Seeds were surface-sterilized with 70% ethanol for 3 min, and then with 10% sodium hypochlorite for 15 min. The seeds were washed five times in sterile water and placed in Petri dishes containing 4.6 g l -1 MS salts [ 24 ], 30 g l -1 sucrose, and 7.5 g l -1 bactoagar at pH 5.7. The seeds were grown in a controlled environment at 25°C on a 16-h continuous light and 8-h dark daily cycle. Rice, maize, and poplar plants were grown in a greenhouse for genomic DNA extraction. Transgenic tobacco plants and Siberian ginseng calluses were also used to extract genomic DNA and to confirm foreign gene insertion by PCR amplification. DNA extraction (Figure 5 ) We tested three different variations of the genomic DNA extraction procedure. About 0.5 cm 2 of culture room- or greenhouse-grown plant leaves were put in a 1.5-ml microfuge tube. The leaf tissue was homogenized in 50 μl DNA extraction buffer (500 mM NaCl, 100 mM Tris-HCl pH 7.5, and 50 mM EDTA pH 7.5), using a hand-operated homogenizer (Sigma, Z35997-1) with a plastic pestle, for 15~20 s. After an initial homogenization, another 150 μl of DNA extraction buffer were added and homogenized with the same homogenizer for 15~20 s. Then, 20 μl of 20% SDS were added and vortexed for 30 s. The samples were incubated at 65°C for 10 min for cell lysis. At this point, three different DNA extraction protocols were used for PCR amplification. Protocol 1: An equal volume of phenol/chloroform/isoamyl alcohol (25:24:1) was added to the samples, mixed by vortexing for 30 s, and then centrifuged at 10,000 g for 3 min at 4°C. The supernatant was diluted 5 fold, and 1 μl of the supernatant was used as the DNA template for PCR analysis. Protocol 2: The supernatant from protocol 1 was transferred to a fresh tube and extracted one more time with phenol/chloroform/isoamyl alcohol (25:24:1) and then with chloroform. The supernatant was diluted 5 fold, and 1 μl of the supernatant was used as the DNA template for PCR analysis. Protocol 3: The supernatant from protocol 2 was transferred to a fresh tube, and a double volume of ethanol was added to each sample, mixed well, and the samples were incubated at -20°C for 30 min. The samples were then centrifuged at 10,000 g for 10 min at 4°C. The pellet was washed with 70% ethanol, dried, and resuspended in sterile dH 2 O containing 20 μg/ml DNase-free RNase A. The concentration and purity were determined from the A 260 /A 280 ratio using a spectrophotometer. Five micrograms of each genomic DNA sample were incubated at 37°C for 3 h for complete digestion with 20 U of Eco RI and Hin dIII (Life Technologies, USA) in a total volume of 100 μl and analyzed on 1.0% agarose gels using 15 μl aliquots of the reaction mixture. Analysis of DNA and PCR amplifications Five micrograms of each genomic DNA sample measured by spectrophotometer were incubated at 37°C for 3 h for complete digestion with 20 U of Eco RI and Hin dIII in a total volume of 100 μl and analyzed on 1.0% agarose gels using 15 μl aliquots of the reaction mixture. By using the genomic DNA isolated from the leaves or calluses of wild-type and transgenic plants, PCR amplifications were performed on a Perkin Elmer GeneAmp PCR System 2400 (Biorad, USA) in a total volume of 25 μl containing 1 × PCR buffer, 0.2 mM dNTP, 10 pmol of each primer (Table 1 ), 50 ng template DNA from plants, and 0.25 U Ex-Taq DNA polymerase (Takara, Japan) using the following profile: a 3-min denaturation at 94°C and 40 cycles of 1-min denaturation at 94°C, 1-min annealing at 37°C for RAPD or 55°C for specific transgene amplification, and a 2-min extension at 72°C, followed by a final extension at 72°C for 7 min. The PCR products were resolved by electrophoresis in 1.0% agarose gels. Authors' contributions TJK developed the method and performed majority of the experiments. MSY provided technical assistance, funding and supervision for the work. All authors have read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC517939.xml
534110	Enhanced Dupuytren's disease fibroblast populated collagen lattice contraction is independent of endogenous active TGF-β2	Background Dupuytren's disease (DD) is a debilitating fibro-proliferative disorder of the hand characterized by the appearance of fibrotic lesions (nodules and cords) leading to flexion contractures of the fingers and loss of hand function. Although the molecular mechanism of DD is unknown, it has been suggested that transforming growth factor-β 2 (TGF-β 2 ) may play an important role in the underlying patho-physiology of the disease. The purpose of this study was to further explore this hypothesis by examining the effects of TGF-β 2 on primary cell cultures derived from patient-matched disease and normal palmar fascia tissue using a three-dimensional collagen contraction assay. Methods Fibroblast-populated collagen lattice (FPCL) contraction assays using primary cell cultures derived from diseased and control fascia of the same DD patients were studied in response to exogenous TGF-β 2 and neutralizing anti-TGF-β 2 antibodies. Results Contraction of the FPCLs occurred significantly faster and to a greater extent in disease cells compared to control cells. The addition of TGF-β 2 enhanced the rate and degree of collagen contraction in a dose-dependent fashion for both control and diseased cells. Neutralizing anti-TGF-β 2 antibodies abolished exogenous TGF-β 2 stimulated collagen contraction, but did not inhibit the enhanced basal collagen contraction activity of disease FPCL cultures. Conclusions Although exogenous TGF-β 2 stimulated both disease and control FPCL contraction, neutralizing anti-TGF-β 2 antibodies did not affect the elevated basal collagen contraction activity of disease FPCLs, suggesting that the differences in the collagen contraction activity of control and disease FPCL cultures are not due to differences in the levels of endogenous TGF-β 2 activity.	Background Dupuytren's disease (DD) is a fibro-proliferative disorder of the palmar fascia (PF) characterized by the formation of fibrous nodules and cords [ 1 ]. The disease results in digital contractures, leading to loss of hand function. Surgical excision of the diseased PF is currently the principal form of management since the lack of a clear etiology has precluded the development of other effective and rational forms of treatment. Since Baron Guillaume Dupuytren's classical description of the disease in 1831, multiple clinical associations have been described, however, no clear molecular mechanism for the disease has been established [ 2 ]. Histochemical studies of DD have demonstrated the presence of myofibroblasts [ 3 ], increased production of type III collagen [ 4 - 7 ], and alterations in other extra-cellular matrix proteins including various fibronectin isoforms [ 8 - 14 ]. These biological features are characteristic of abnormal growth factor regulation, specifically fibrogenic cytokines such as transforming growth factor-beta (TGF-β). Several studies have documented TGF-β expression in DD palmar fascia using RT-PCR [ 15 ], in-situ hybridization [ 16 ], and immunohistochemistry [ 16 - 18 ], while others have shown that TGF-β can stimulate cell proliferation [ 18 - 20 ] and promote myofibroblast differentiation in vitro [ 21 ]. As a result of these and other studies it has been suggested that an aberrant TGF-β activity may be involved in the pathogenesis of DD. In this study, we chose to focus on TGF-β 2 and its effects on collagen contraction in vitro using a three-dimensional fibroblast populated collagen lattice (FPCL) contraction assay and DD patient-matched disease and control primary cell cultures. Previous reports have examined the role of TGF-β in DD by comparing disease fibroblasts to 'control' fibroblasts obtained from transverse carpal ligament material obtained from patients undergoing carpal tunnel release (CTR). By contrast, the control fibroblast cultures used in this study were established from unaffected PF tissue from the same patient, thus providing us with unique patient- and tissue- matched control cultures. The observed phenotypic differences between patient/tissue-matched control and disease FPCL cultures, specifically elevated collagen contraction activity, and β-catenin and fibronectin (Fn) expression in disease cells [ 22 - 24 ], raises the intriguing possibility that pro-fibrotic factors, such as TGF-β 2 , may be regulating these disease-associated events in vitro , since TGF-βs are known to promote fibroblast mediated collagen contraction [ 21 , 25 , 26 ] and up-regulate collagen, Fn and β-catenin [ 20 , 27 - 30 ]. As described in detail below, we have found that exogenous TGF-β 2 could significantly stimulate 'normal' and disease FPCL contraction in a dose-dependent manner. While neutralizing anti-TGF-β 2 antibodies completely blocked exogenous TGF-β 2 stimulated FPCL contraction they had no effect on the enhanced basal collagen contraction activity of disease FPCL cultures. Methods Patient samples and primary cell cultures Our study protocol was cleared through the UWO Ethics Committee for Research Involving Human Subjects. Areas of diseased fascia and uninvolved normal (control) PF tissue were collected during surgery. DD explant cultures were initially cultured in starter media consisting of α-MEM (Gibco, Invitrogen Corporation) supplemented with 20% fetal bovine serum (FBS, Clontech Laboratories, Palo Alto, CA), and antibiotics (Penicillin G and streptomycin sulfate) and fungizone (Gibco, Invitrogen Corporation) as previously described [ 23 ]. Established primary culture lines were maintained in α-MEM + 10% FBS + antibiotics + fungizone. Culture flasks were incubated at 37°C in a humidified chamber with 5% CO 2 . Medium was changed every 4–5 days and the cells sub-cultured using 0.05% Trypsin-EDTA (Gibco, Invitrogen Corporation, Grand Island, NY) when confluent. Fibroblast Populated Collagen Lattice (FPCL) contraction assay Collagen contraction was carried out using patient-matched disease (D) and control (C) primary cultures (passages 2 – 6) established from patient-matched DD lesions and uninvolved palmar fascia (control). Collagen lattices were prepared by mixing cell suspensions with a neutralized solution of collagen type I matrix (8 parts Vitrogen100 collagen type I, 2.9 mg/ml, Collagen Corp, Santa Clara, CA, USA + 1 part 10 × α-MEM + 1 part HEPES buffer, pH 9.0). The cell-collagen concentrations were adjusted with sterile phosphate buffered solution (PBS) to attain a final collagen concentration of 2.0 mg/ml and a final cell concentration of 8.6 × 10 4 cells/ml of matrix. The cell-collagen mixture was then aliquoted into 24 well culture dishes (0.5 ml/well) that were pre-treated with a PBS solution containing 2% (w/v) bovine serum albumin (BSA). Following FPCL polymerization (1 hr, 37°C) culture medium (0.5 ml) consisting of α-MEM + 10% fetal bovine serum (FBS) was added atop each lattice. After 2 days of culture the attached FPCLs were mechanically released from the sides of the culture plates. Digital images of the contracting FPCL were captured at various time points over a 5-day assay period using a conventional flatbed scanner. Collagen lattice areas were then quantified using the Image J program [ 31 ]. Each assay was done in quadruplicate. TGF-β 2 and neutralizing anti-TGF-β 2 antibody treatments Commercially available human recombinant TGF-β 2 (expressed in NSO murine myeloma cells) was acid activated in a solution of 4N HCl + 0.1% (w/v) BSA according to the manufacturer's instructions (Product # T 2815, Sigma, St. Louis, MO). Acid activated human recombinant TGF-β 2 was then aliquoted and frozen for extended storage at -70°C. The indicated concentrations of activated human recombinant TGF-β 2 were added to complete culture media immediately following FPCL polymerization. Neutralizing anti-TGF-β 2 antibodies (R&D Systems, Minneapolis, MN) were added to complete culture media either immediately following FPCL polymerization or added to the cell suspension prior to mixing with the neutralized Vitrogen collagen type I solution. Control FPCL cultures were treated with appropriate carrier solutions. Cell proliferation assay FPCL cultures were assayed using a commercially available CellTiter 96 ® A queous One Solution cell proliferation assay according to the manufacturer's instructions (Promega, Madison, WI, USA). This cell proliferation assay is a colorimetric method that uses a tetrazolium compound 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium salt (MTS) in combination with a stable electron coupling reagent PES (phenazine ethosulfate). This produces a chemically stable MTS tetrazolium compound that can be bio-reduced by cells to form a soluble colored formazan product [ 32 , 33 ]. Briefly, cells from patient-matched primary cultures were cultured as stressed-relaxed FPCLs as described above. Each primary cell line was plated as quadruplicate FPCL cultures for each of the indicated time points with 0.5 ml of culture media ± TGF-β 2 (1 ng/ml) atop each FPCL. At each of the designated contracting time points 100μl of CellTiter 96 ® A queous One solution reagent was added to the FPCL cultures and incubated for 3 hours (37°C, 5% CO 2 atmosphere, humidified chamber). FPCL media was then collected and aliquoted into a 96-well culture plate for absorbance reading at 450 and 650 nm (background reference λ) using a 96-well BIO-RAD microplate reader. Media was also collected from FPCLs containing no cells (negative control) for background absorbance readings. The assay was conducted over 5 days during the course of FPCL contraction. A standard curve was also generated to calculate relative cell numbers per FPCL (range of 4 × 10 3 –10 5 cells/FPCL). Statistical analysis Student two-tailed t test was used to compare data between two groups. Values were expressed as mean ± standard deviation of the mean (SDM). P values < 0.05 were considered statistically significant. Results TGF-β 2 stimulates FPCL contraction We first examined the basal collagen contraction activity of three independent patient-matched early passage control and disease primary FPCL cultures. As shown in Figure 1 , disease FPCL cultures contracted collagen faster and to a greater degree when compared to patient-matched control FPCL cultures. This is in agreement with previous results that show distinct phenotypic differences between control and disease primary DD cultures [ 22 , 24 ], including enhanced collagen contraction by disease FPCL cultures [ 23 ]. Next, we explored the role of exogenous TGF-β 2 on FPCL contraction. Initial experiments showed a typical dose-dependent response for TGF-β 2 stimulated FPCL contraction (Fig. 2 ). Because maximum collagen contraction was achieved in response to 1 ng/ml of TGF-β 2 , all subsequent experiments used this dose. As shown in Figure 3a , we observed enhanced contraction rates and total collagen contraction for both control and disease cells treated with exogenous (1 ng/ml) TGF-β 2 . This enhanced collagen contraction activity observed in disease FPCL cultures was not due to differences in cell proliferation/viability between control or disease FPCL cultures. In fact, TGF-β 2 appears to exert a significant pro-apoptotic effect on relaxed disease FPCL cultures that is absent in the 'control' FPCL cultures (Fig 3b ). Thus, the amount of collagen contraction exerted by disease FPCL cultures is more pronounced if one also considers the changes in cell viability over the course of FPCL contraction. Neutralizing anti-TGF-β 2 antibodies block TGF-β 2 stimulated FPCL contraction but do not alter basal FPCL contraction Exogenous TGF-β 2 stimulated collagen contraction in both control and disease FPCL cultures was inhibited in a dose-dependent manner by neutralizing anti-TGF-β 2 antibodies. As shown in Figure 4 , lower concentrations of neutralizing antibodies (100 ng/ml) partially inhibited FPCL contraction, while higher concentrations of neutralizing antibodies (1000 ng/ml) completely inhibited TGF-β 2 stimulated FPCL contraction, thus confirming the ligand-dependent nature of this response in vitro . We also examined the effect of neutralizing anti-TGF-β 2 antibodies on the basal collagen contraction activity of primary disease and control FPCL cultures. As shown in Figure 5 , high concentrations (1000 ng/ml) of neutralizing anti-TGF-β 2 antibodies had no effect on the basal levels of collagen contraction observed in either control or disease FPCL cultures, suggesting that there is little or no endogenous active TGF-β 2 that could account for the FPCL contraction in vitro . To preclude that more localized interactions between endogenously produced TGF-β 2 and its cell-surface receptors may account for the observed increase in disease FPCL contraction, we also pre-incubated the cells with neutralizing anti-TGF-β 2 antibodies prior to forming FPCL. Regardless, the blocking antibodies had no effect on the basal levels of FPCL contraction (data not shown). Discussion Members of the TGF-β family are potent fibrogenic factors that play an important role in the patho-physiology of numerous fibro-proliferative disorders, including DD [ 34 ]. The study presented here focused on the effect of TGF-β 2 on collagen contraction using primary FPCL cultures derived from patient-matched disease and control unaffected PF tissue. Here, we found that disease FPCL cultures contracted collagen faster and to a greater degree than patient-matched control FPCL cultures. Although neutralizing anti-TGF-β 2 antibodies effectively blocked exogenous TGF-β 2 stimulated FPCL contraction for both control and disease cultures, the same neutralizing antibodies had no effect on the basal collagen contraction activity of either disease or control FPCL cultures, suggesting that enhanced disease FPCL contraction is not due to elevated levels of endogenous active TGF-β 2 . These results, however, do not exclude the possibility that there may be differences in the levels of latent TGF-β 2 produced by these cell cultures that may be subsequently activated in vivo . Recent work by Kuhn et. al. (2002) reported reduced DD FPCL contraction in response to tamoxifen, which was associated with a decreased TGF-β 2 production [ 35 ]. However, the TGF-β 2 assayed in this study required an acid-activation step, suggesting that TGF-β 2 produced by these cells is largely in its latent, non-activate form. Thus, it is possible that TGF-β 2 produced by DD fibroblasts and/or other resident cell types in vivo may be important to disease cord contraction, provided appropriate regulators of latent TGF-β activation are also present and active. However, it does not explain the enhanced basal FPCL contraction rates of disease cell cultures, suggesting that other signalling factors may be regulating this disease cell function in vitro . It is interesting to note that both TGF-β and β-catenin signalling pathways show some degree of 'cross-talk' [ 29 , 30 , 36 - 38 ], suggesting that β-catenin plays an important role in TGF-β signalling. The degree and significance of signalling 'cross-talk' between β-catenin and TGF-β in the context of DD is unknown and needs further examination. Although previous DD studies have used different 'control' primary fibroblast as 'disease-free' controls, namely fibroblasts derived from transverse carpal ligament material obtained from patients undergoing carpal tunnel release (CTR), they have the disadvantage of being of different anatomical origin than PF derived 'control' fibroblast cultures. This is an important consideration given that fibroblasts exhibit functional heterogeneity depending on their origin [ 39 - 41 ]. For example, human fibroblasts that express the cell surface antigen Thy-1 are capable of TGF-β 1 stimulated myofibroblast differentiation, while Thy-1 negative fibroblasts appear to be only capable of lipofibroblast differentiation [ 42 ]. Phenotypic differences have also been attributed to fibroblasts of different dermal origins [ 43 ]. For example, Chipev and colleagues showed that TGF-β 1 had a pro-apoptotic effect on non-palmoplantar (keloid) fibroblasts and an anti-apoptotic effect on palmoplantar fibroblasts. Similar to what we have observed for detached or contracting DD FPCL cultures, they showed that TGF-β 1 treated (in the presence of serum) keloid FPCL cultures underwent the most extensive apoptosis response upon mechanical release compared to dermal fibroblasts from different body sites [ 43 ]. Perhaps the similar myofibroblast phenotype attributed to both DD and keloid fibroblast cultures also dictates a similar apoptotic fate to relaxed FPCL cultures in response to TGF-βs. Although the loss of tension in these cultures triggered a mostly uniform loss in cell viability across all groups, unlike disease FPCL cultures TGF-β 2 did not appear to have any significant pro-apoptotic effect on relaxed 'control' FPCL cultures. In light of these and other findings, it appears that the patient-matched control fibroblast cultures employed in these studies may truly represent a suitable 'control' phenotype, with the added advantage of having the same PF origins as the disease cell cultures. While this does not exclude the possibility that the control cultures may harbour some residual disease cells, this is not supported by the distinct phenotypic differences we have observed between these two types of patient-matched PF cultures in the current and previous studies. In these earlier studies, we reported elevated levels of β-catenin and fibronectin isoforms in disease FPCL cultures [ 22 - 24 ], as well as enhanced disease FPCL contraction rates which we have subsequently confirmed in these studies. This together with the distinctive pro-apoptotic affects of TGF-β 2 on disease FPCL cultures described here, further support the notion that the patient/tissue-matched 'control' cultures have a non-disease phenotype that is suitable for these types of investigations. Although the 'synthetic' myofibroblast features of the disease cells described in previous studies are known to be stimulated by TGF-β [ 20 , 21 , 25 - 30 , 35 ], our results suggests that endogenous TGF-β 2 does not play a role in regulating these phenotypic differences in vitro . Nevertheless, aberrant expression of various TGF-β signalling components have been previously shown to trigger this 'synthetic' myofibroblast phenotype in other fibro-proliferative disorders, specifically keloids and burn hypertrophic scarring [ 34 , 44 , 45 ], that can to some extent be inhibited by neutralizing anti-TGF-β 2 antibodies [ 46 , 47 ]. Hopefully future studies will unravel the extent of these phenotypic differences between these patient/tissue-matched control and disease FPCL cultures with respect to pro-fibrotic factors like TGF-β 2 , tension and other important intersecting signaling pathways. Conclusions Primary disease FPCL cultures contract collagen faster and to a greater extent than control PF-matched FPCL cultures. While neutralizing anti-TGF-β 2 antibodies can block exogenous TGF-β 2 stimulated collagen contraction for both control and disease FPCL cultures, it had no effect on the basal contraction rates of either control or disease FPCL cultures. We, therefore, conclude that the enhanced collagen contraction activity of disease FPCL cultures is not due to differences in the levels of endogenous active TGF-β 2 . List of abbreviations DD, Dupuytren's disease; PF, palmar fascia; CTR, carpal tunnel release; TGF-β, transforming growth factor-beta; FPCL, fibroblast populated collagen matrix; PBS, phosphate buffered saline; RT, room temperature; HEPES, 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid; α-MEM, alpha-minimal essential medium; FBS, fetal bovine serum; Fn, fibronectin; MTS, 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium salt; PES, phenazine ethosulfate; RT-PCR, reverse transcriptase polymerase chain reaction; SDM, standard deviation of the mean. Competing interests The authors declare that they have no competing interests. Authors' contributions RT and YW carried out the experiments. RT drafted the manuscript. JCH and BSG designed and coordinated the research, and reviewed and edited the manuscript. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC534110.xml
449851	Human Population Density and Extinction Risk in the World's Carnivores	Understanding why some species are at high risk of extinction, while others remain relatively safe, is central to the development of a predictive conservation science. Recent studies have shown that a species' extinction risk may be determined by two types of factors: intrinsic biological traits and exposure to external anthropogenic threats. However, little is known about the relative and interacting effects of intrinsic and external variables on extinction risk. Using phylogenetic comparative methods, we show that extinction risk in the mammal order Carnivora is predicted more strongly by biology than exposure to high-density human populations. However, biology interacts with human population density to determine extinction risk: biological traits explain 80% of variation in risk for carnivore species with high levels of exposure to human populations, compared to 45% for carnivores generally. The results suggest that biology will become a more critical determinant of risk as human populations expand. We demonstrate how a model predicting extinction risk from biology can be combined with projected human population density to identify species likely to move most rapidly towards extinction by the year 2030. African viverrid species are particularly likely to become threatened, even though most are currently considered relatively safe. We suggest that a preemptive approach to species conservation is needed to identify and protect species that may not be threatened at present but may become so in the near future.	Introduction Mammals have been severely affected by the current extinction crisis: around a quarter of extant species are considered to be threatened with extinction ( Hilton-Taylor 2000 ). Understanding the ecological processes that cause some species to decline, while others remain relatively safe, may help to predict future declines and focus conservation efforts on species in urgent need. The underlying cause of virtually all recent and ongoing declines of mammal species is the growth of human populations and associated impacts such as habitat loss, hunting, and the spread of invasive species. Threatening processes such as these vary in intensity across the surface of the Earth, and species that inhabit more heavily impacted regions are expected to have a higher risk of extinction ( Forester and Machlis 1996 ; Woodroffe 2000 ; Brashares et al. 2001 ; Harcourt et al. 2001 ; McKinney 2001 ; Ceballos and Ehrlich 2002 ; Harcourt and Parks 2002 ; Parks and Harcourt 2002 ). Although exposure to threatening processes is the ultimate cause of extinction, a species' biology determines how well it is able to withstand the threats to which it is exposed. Biological traits that confer ecological flexibility and allow populations to recover rapidly from depletion may offer a degree of protection from external threats. A number of recent studies have linked variation in extinction risk or decline among species to biological traits ( Gaston and Blackburn 1995 ; Bennett and Owens 1997 ; Owens and Bennett 2000 ; Purvis et al. 2000 ; Cardillo and Bromham 2001 ; Cardillo 2003 ; Fisher et al. 2003 ; Jones et al. 2003 ), and, indeed, biology accounts for over a third of the variation in extinction risk among carnivore and primate species ( Purvis et al. 2000 ). However, only one study to date, using Australian marsupials ( Fisher et al. 2003 ), has explicitly examined the relative importance of biological versus external, anthropogenic predictors of extinction risk. Hence, we know little about the extent to which adding external predictors might increase the explanatory power of models of extinction risk based on biology alone. Furthermore, we do not know whether the combined effects of biological and external predictors are simply additive, or whether interactions exist: does the influence of biology vary depending on the degree of external threat a species faces? Here we present a global-scale analysis of biological and external predictors of extinction risk in the mammal order Carnivora. As well as including many symbols of conservation such as the giant panda, tiger, and sea otter, carnivores in general are a good model taxon for the development of a predictive science of conservation: their biology and phylogeny are well studied, they are near-global in distribution, they represent a wide range of biological strategies, and they include species at all levels of extinction risk. Our analysis emphasizes those threatened species that have suffered measurable declines, rather than those simply with small populations or ranges that may be considered “naturally” rare. We use human population density (HPD) as a summary measure of anthropogenic impact. Although not all types of impact are necessarily associated with high-density human populations, on a global scale HPD is more reliably quantified than direct threatening processes such as habitat loss or hunting, which are difficult to measure accurately in ways that are consistent across regions and biomes. Therefore, HPD represents one of the best available means of summarizing the impact faced by mammal species on a global scale. At local or regional scales, high HPD is often associated with some measure of mammal decline ( Forester and Machlis 1996 ; Woodroffe 2000 ; Brashares et al. 2001 ; Harcourt et al. 2001 ; McKinney 2001 ; Ceballos and Ehrlich 2002 ; Harcourt and Parks 2002 ; Parks and Harcourt 2002 ). Here we ask whether HPD influences carnivore extinction risk at the species level, whether it is more or less important than species biology, and how biology interacts with HPD to determine risk. Results We followed the international standard for species-level extinction risk classification, the IUCN Red List ( Hilton-Taylor 2000 ), which has also been used in previous studies of species-level extinction risk ( Purvis et al. 2000 ; Harcourt and Parks 2002 ; Jones et al. 2003 ). We used multiple linear regression to find minimum adequate models (MAMs) predicting extinction risk from HPD and a set of biological traits. Confounding effects of phylogeny were controlled for by calculating phylogenetically independent contrasts in all variables before analysis. Using a Geographic Information System, we derived seven summary measures of HPD for each species: mean HPD across the species' geographic range and the proportion of the range with HPD of at least 2, 5, 10, 20, 50, and 100 people/km 2 . With the exception of the last two of these, all showed significant nonlinear effects on extinction risk as separate predictors ( Table 1 ). In the multiple regression, however, biological variables were of overriding importance compared to HPD as predictors of extinction risk ( Table 2 ). A MAM based on main effects alone explained 45.1% of variation in risk, with four biological variables independently associated with high extinction risk: small geographic range size, long gestation, low species population density and high trophic level. No HPD variables added significant explanatory power to this model. However, when interactions between HPD and biological variables were added to the model, a HPD–gestation length interaction was significant, and the variance explained by the model increased to 51.4% ( Table 2 ). Using the Akaike information criterion (AIC), the model with the interaction term provided a better fit to the data (AIC = 57.38) than the model based on main effects only (AIC = 61.98). However, the partial variance explained by HPD (0.5%) in this model was very small compared to that explained by the combined biological variables (44%). So, although HPD variables were significant separate predictors of extinction risk, the independent effect of HPD virtually disappeared once the effects of biology were accounted for. Table 1 Regressions of Extinction Risk against HPD Using Phylogenetically Independent Contrasts * p ≤ 0.05, p ≤ 0.01, * p ≤ 0.001 Results are shown for linear and nonlinear (quadratic and cubic) terms for each variable. The results presented are for a reduced dataset ( n = 143 contrasts) in which four datapoints with studentized residuals greater than or equal to 3 have been removed. For all variables, the effect of removing these outliers was to reduce slightly the slope of the relationship Table 2 MAMs from Multiple Regression of HPD and Biological Predictors of Extinction Risk in Carnivores * p ≤ 0.05, p ≤ 0.01, * p ≤ 0.001 Model with main effects only: n = 67 contrasts, model r 2 = 0.451, AIC = 61.98. Model with interactions: n = 67 contrasts, model r 2 = 0.514, AIC = 57.38. The HPD variable is the percent of a species' geographic range in which HPD is 10/km 2 or greater (other HPD variables were tested but had lower predictive power) The importance of interactions between HPD and biology was confirmed by separate analyses of the subsets of carnivore species with relatively low and high exposure to human populations ( Table 3 ). For “low-exposure” species the final MAM included only two predictors, species population density and geographic range size, and explained 37.9% of the variation in extinction risk. However, for “high-exposure” species the model included geographic range size, species population density, and gestation length, and the explanatory power increased sharply, to 80.1%. Therefore, despite the fact that independent main effects of HPD were relatively unimportant, HPD did appear to be a significant modifier of the effects of biology on extinction risk. Table 3 MAMs for Carnivore Species with Low and High Exposure to Human Populations * p ≤ 0.05, p ≤ 0.01, * p ≤ 0.001 See Materials and Methods for definitions of “low exposure” and “high exposure.” Low-exposure species: n = 48 contrasts, model r 2 = 0.379. High-exposure species: n = 19 contrasts, model r 2 = 0.801 Discussion While the ultimate sources of current threats to species are virtually all anthropogenic, intrinsic ecological and life-history traits determine how well populations are able to withstand exposure to threatening processes. In our models, four biological traits accounted for nearly half of the variation in extinction risk among carnivore species. Small geographic ranges and low population densities determine the maximum population size a species can attain; gestation length is an important indicator of life-history speed ( Gittleman 1993 ), which determines how quickly populations can recover from low levels; and extinction risk for species at high trophic levels may be compounded by their need for large hunting areas and their dependence on prey species that may themselves be threatened ( Carbone and Gittleman 2002 ). Of these traits, geographic range size is of particular importance. As an example, the Ethiopian wolf (Canis simensis) is the most threatened species of the Canidae family despite the fact that its population density is not especially low, nor its gestation especially long, compared to other Canis species. However, it has a geographic distribution only a fraction of the size of its congenerics, and within that distribution is limited to afroalpine habitat ( Sillero-Zubiri and Macdonald 1997 ). In contrast, independent, main effects of HPD on extinction risk were weak once the effects of biology were accounted for: HPD explained only 0.5% of variation in extinction risk in the final model, compared to 44% for biological traits. That extinction risk in carnivores should be so strongly determined by biology rather than HPD is surprising, given that carnivores inhabit regions as disparate in human impact as western Europe and the Canadian Arctic, and that their requirements often conflict with human interests ( Gittleman et al. 2001 ). Based on previous studies, HPD is expected to be a good proxy for threats to mammal populations ( Forester and Machlis 1996 ; Woodroffe 2000 ; Brashares et al. 2001 ; Harcourt et al. 2001 ; McKinney 2001 ; Ceballos and Ehrlich 2002 ; Harcourt and Parks 2002 ; Parks and Harcourt 2002 ), and, indeed, it has been suggested that HPD be incorporated into a scheme for quantifying extinction risk for primate species ( Harcourt and Parks 2002 ). However, no previous study has examined the effects of HPD on extinction risk after controlling for the effects of a wide range of biological traits. The strength of HPD as a predictor of risk may also be compromised by the fact that the relationship between HPD and threat intensity may be a complex one ( McKinney 2001 ): for example, habitat loss, the most important threat to mammals ( Hilton-Taylor 2000 ), is often not associated with high HPD. Recent work suggests that number of households may be a better demographic indicator of threat intensity than number of people ( Liu et al. 2003 ), although this is based on coarse-scale, country-level data that cannot easily be incorporated into phylogenetically explicit analyses. Furthermore, differences in the degree of technological development of different human societies may contribute to differences in the effect of HPD. For example, a small human population with access to highly mechanized means of habitat destruction may have a level of impact on carnivores equal to that of a far larger or denser population without such means. Another possibility is that a species' current extinction risk status may reflect patterns of human impact in the past more closely than it does current impact. Extinction filter effects ( Balmford 1996 ) may mean that the most vulnerable species have already disappeared or contracted away from regions of highest HPD, obscuring any underlying positive association between HPD and extinction risk. Unfortunately, the difficulty of reliably reconstructing historical ranges of species from available evidence probably precludes thorough testing of this idea. Clearly, the importance of HPD on current extinction risk of carnivores is less as an independent main effect than as a modifier of the effects of biology. For “low-exposure” species (for which HPD was 10 people/km 2 or higher in less than half of the range), life history did not predict extinction risk, and the only variables included in the model were those that determine the maximum population size a species can achieve (geographic range size and species population density). For “high-exposure” species, life history (gestation length) became additionally significant, and the explanatory power of the model as a whole was very high (80%). Evidently, a small species population contributes to high extinction risk no matter what the threat level, but where exposure to human populations is high, the disadvantage of a small species population is compounded by the disadvantage of a slow life history. This might suggest a difference in the major threat types experienced by carnivore species with different levels of exposure to human populations. For example, habitat loss, the predominant threat type for the great majority of mammals ( Hilton-Taylor 2000 ), can be severe even far from centers of human population. Hence, species with restricted distributions and small populations may be susceptible to habitat loss even in regions of relatively low HPD. Where people are more numerous, species may be threatened by direct persecution and exploitation as well as habitat loss. In such regions, species with slow life histories and low population growth rates would become additionally susceptible. This could explain our finding that biology becomes a more powerful predictor of risk status as exposure to human populations increases. If species in regions of high HPD are threatened by direct persecution and exploitation as well as habitat loss, we should expect top-level predators to be particularly threatened in these regions ( Woodroffe 2000 ). Why, then, was trophic level not a predictor of extinction risk for “high-exposure” species? One possibility is an extinction filter effect, whereby species at the highest trophic levels, which live at low densities and are relatively rare, have already disappeared from regions of high HPD ( Diamond 1984 ; Woodroffe 2001 ). This explanation appears to be supported by a negative correlation across species between trophic level and the proportion of a species' range with a HPD of 10 people/km 2 or higher (r = −0.23, p = 0.003, d.f. = 166). The strong effect of biological traits on extinction risk status for “high-exposure” species suggests that, as human populations increase globally over coming decades, the importance of biology in determining which species persist and which decline will also increase. This is worrying for species that possess traits making them more vulnerable to external threats, as their extinction risk can be expected to increase more sharply. Of particular concern are species that not only have unfavorable biology, but also live in regions of rapid human population growth. We have identified the carnivore species with the greatest expected increase in extinction risk over the next few decades, given HPD projected to the year 2030 based on recent growth rates. We acknowledge the problems with converting the ordinal categories of the Red List to an interval scale, and these have been discussed previously ( Purvis et al. 2000 ). However, we emphasize that we are not attempting to make accurate quantitative predictions about the future status of species. We are simply illustrating a way of identifying those species likely to move most rapidly towards extinction in coming decades based on projected growth in human populations, all else being equal. Figure 1 shows those species with the greatest discrepancy between current and predicted risk status. These species are from a wide range of carnivore families, but the Viverridae (civets and genets) are particularly well represented: five of the top seven species on the list are viverrids. Most of the species in Figure 1 are from Africa, much of which has rates of human population growth far higher than the global average. It is particularly worrying that most are currently rated as “least concern” in the Red List, so they are unlikely to be receiving as much conservation attention as species currently rated as threatened. Furthermore, our estimates are conservative in that they treat species' geographic range sizes and population densities as static—they do not account for ongoing declines. Figure 1 Carnivore Species Predicted to Move Most Rapidly towards Extinction by the Year 2030 Species listed are those expected to move from the “low-exposure” into the “high-exposure” group (see Materials and Methods for definitions), and for which the extinction risk rating is predicted to increase by at least one index value. Bars indicate the discrepancy between current Red List rating at the left, and the predicted rating at the right. General distributions of each species are shown on the far right. Abbreviations for Red List categories: LC, least concern; NT, near threatened; CD, conservation dependent; VU, vulnerable; EN, endangered; CR, critically endangered; EW, extinct in the wild; EX, extinct. We conclude that there is no room for complacency about the security of species simply because they are not currently considered globally threatened. There is a strong case to be made for preemptive conservation of species, such as the African viverrids, that live in regions of rapid human population growth and have a biology predisposing them to decline. Preemptive action could include, for example, establishing population-monitoring programs, or listing species under national species protection laws on the basis of potential future susceptibility. Arguably, maintaining the stability of particularly susceptible species before they become threatened could be more cost-effective in the long term than postdecline attempts to rescue them from the brink of extinction. Materials and Methods Data As the response variable in our analyses, we followed Purvis et al. (2000) in converting the IUCN Red List categories ( Hilton-Taylor 2000 ) to a continuous linear index as follows: least concern = 0, near threatened = 1, conservation dependent/vulnerable = 2, endangered = 3, critically endangered = 4, extinct in the wild/extinct = 5. Among our predictor variables were geographic range size and species population density, both of which may contribute to the criteria for determining the Red List category ( Hilton-Taylor 2000 ). To avoid potential circularity, our analyses excluded the 15% of carnivore species listed based on these criteria, and included threatened species only when they were listed under criterion A (a measured recent decline in geographic range or population size), which is independent of absolute geographic range or population density. We used the database of biological variables used by Purvis et al. (2000) , updated to include more recently published information. This database consists of information compiled from the published literature on species' geographic range size, body size, interbirth interval, age at sexual maturity, litter size, gestation length, home range size, population density, group size, trophic level, activity timing, sociality, and island endemicity. Continuous variables were log-transformed before analysis. For our measures of HPD, we used the Gridded Population of the World ( CIESIN 2000 ), a spatially explicit global database of HPD for 1995, coarsened to a resolution of 0.5 ° × 0.5 ° to speed analyses. We used two methods to summarize the spatial variation in HPD within the geographic range of each species, each of which captures different aspects of HPD variation. Firstly, we used the log-transformed mean HPD across the geographic range of each species: this measure is sensitive to relatively small areas of very high HPD (e.g., around major cities). Secondly, we calculated the logit-transformed proportion of each species' range in which HPD exceeded a given threshold value. This measures a more explicitly spatial aspect of HPD variation and is less sensitive to small areas of very high HPD. Because it is difficult to know a priori the HPD threshold that is most critical to carnivore extinction risk, we repeated all analyses using threshold values of 2, 5, 10, 20, 50, and 100 people/km 2 . Geographic variation in both HPD and the distribution of threatened species may be confounded with net primary productivity ( Balmford et al. 2001 ), so we included in the models a measure of actual evapotranspiration (AET) ( UNEP 2003 ), as a proxy for primary productivity. The above calculations were all done with the Spatial Analyst extension in the program ArcGIS, using equal-area projections of the HPD map and each carnivore species' estimated current geographic distribution (compiled as part of the IUCN Global Mammal Assessment). The datasets used in the analyses are provided in Supporting Information (Datasets S1 and S2 ). Analyses To test the predictors of extinction risk we used linear regression through the origin ( Garland et al. 1992 ) on phylogenetically independent contrasts generated using the program Comparative Analysis by Independent Contrasts ( Purvis and Rambaut 1995 ). Although the extinction risk index itself does not evolve along phylogenies, it is closely associated with biological variables that do, making it necessary to use analyses that control for phylogeny to ensure statistical independence of data points ( Jones et al. 2004 ; Purvis et al. 2000 , 2004 ). The carnivore phylogeny of Bininda-Emonds et al. (1999) was used to define the contrasts, with branch lengths set to equal. The decision to use equal branch lengths was based on previous analyses ( Purvis et al. 2000 ) using the same phylogeny and essentially the same biological dataset that showed that equal branch lengths gave contrasts with more homogeneous variances than those based on divergence times. We first carried out univariate regressions of each HPD predictor against extinction risk (this had already been done for biological predictors by Purvis et al. [2000] using essentially the same dataset). We then combined external and biological predictors in multiple regressions. To find MAMs, we used backwards elimination of predictor variables from a full model ( Crawley 2002 ) . The large number of missing values in the dataset, and the need to recalculate contrasts at each step, meant that this process could not be automated without discarding most of the information in the dataset. We therefore used the following manual procedure to find MAMs, following Purvis et al. (2000) . We began by fitting a model with all predictors included, then identifying the predictor that contributed the smallest amount of marginal variance to the model. This predictor was then dropped, a new set of contrasts calculated, and the process repeated. In some cases dropping a predictor with many missing values resulted in a substantial increase in the number of contrasts at the next step; when this happened, other predictors previously dropped were reintroduced in turn and the model retested for each. A MAM was found when all remaining predictors contributed a significant ( p ≤ 0.05) amount of variance to the model. Previously dropped predictors were then once again reintroduced in turn and the model retested each time. It should be noted that this method cannot guarantee to find the best-fitting model: it is essentially a heuristic search for the best model, and simulations on a dataset in which associations between variables are known would be needed to fully test the accuracy of the method. To avoid potential problems of colinearity among the seven variables derived from HPD, the variables were included one at a time in the multiple regression models in the process of finding MAMs. At each step we substituted each of the seven HPD variables into the model in turn, retesting the model each time. Once the final MAM was found, we added terms describing the interactions between HPD and biological variables, again testing the model for significance each time. Finally, we compared the predictive power of biological variables for subsets of species with low and high levels of exposure to human impact. “Low-exposure” and “high-exposure” species were defined, respectively, as species with less than or greater than 50% of their geographic range with HPD of at least 10 people/km 2 . The procedure for finding MAMs, using biological variables only, was then repeated for each of these two subsets of species. Predictions of future risk increases From global-scale spatial HPD data for 1990 and 1995 ( CIESIN 2000 ) we calculated a mean annual rate of change, which we used to project HPD to the year 2030. For each species we then recalculated the proportion of the geographic range with HPD of at least 10 people/km 2 . Those species which moved from the “low-exposure” into the “high-exposure” group were identified, and the MAM for “high-exposure” species ( Table 3 ) was used to predict extinction risk for these species. This method is more rigorous than simply identifying currently stable members of higher taxa that have declined in response to human population pressure, because it accounts for the unique biology and geographic distribution of each species. Supporting Information Dataset S1 Definitions of Variable Names in the Dataset (1 KB TDS). Click here for additional data file. Dataset S2 External and Biological Data for Carnivores Used for Analyses (38 KB TDS). Click here for additional data file.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC449851.xml
539352	Constraint Logic Programming approach to protein structure prediction	Background The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Results Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known) secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. Conclusions The results obtained on small proteins show that Constraint Logic Programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of Constraint Logic Programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space.	Background Notwithstanding the continuous improvement in predictive methods, witnessed every two years by the world wide CASP experiment [ 1 , 2 ], predicting the structure of a protein, given its sequence, is still in general beyond our capabilities. Brute force approaches, like exhaustive conformational searches or molecular dynamics simulations of the folding process, are precluded by the computing power available at present. Alternative, faster methods have been developed along two main lines: 1. assemblying the structure of a protein using structural fragments of similar sequences, available in the protein structure repository (the Protein Databank [ 3 ]), and later screening the feasibility of the resulting structures, using energetic criteria; 2. representing the protein chain by a highly simplified model which is, hopefully, treatable. This second class of approaches is appealing in many respects [ 4 ]: first, the linkage between kinetics and thermodynamics of protein folding process and the basic intramolecular interactions is more easily addressable, because of the lesser number of variables. Second, the use of a simplified model agrees with the idea that details of atomic interactions between aminoacids are less important than the overall character of these interactions, because protein structure is flexible and can accommodate changes in the volume and shape of aminoacids much better than changes in their character (e.g. polar vs. hydrophobic [ 5 ]). Besides aiming at catching essential features of the protein folding process, simplified models have important computational advantages: generating and evaluating the energy of a conformation is efficiently done due to the reduced number of variables. A less evident benefit is that sampling (e.g. by molecular dynamics simulation or Monte Carlo methods) may be much more efficient due to the smoothness of energy surface due, once again, to the reduced number of degrees of freedom. Many lattice models have been used for simplified representation of proteins, up to date. Their capability of reproducing the secondary structure of proteins, as well as their relative arrangement has been reviewed by Godzik et al. [ 6 ]. A reasonable tradeoff between accuracy and the need to keep limited the number of base vectors is achieved by the face centered cubic ( ) lattice studied by Toma and Toma [ 7 ]. In particular both α -helices and β -strands are modelled with a very low RMSD from standard regular structures. Lattice models have been used mainly for understanding general properties of proteins, rather than for real predictive tasks, although their use, especially in hierarchical protocols has been proposed and realized. In particular, the (210) lattice has been used successfully by Skolnick and Kolinski in prediction of a small beta protein [ 8 ] and many other useful applications have been reported since these earlier works (see e.g. for recent successful applications [ 9 , 10 ] and also the two recent reviews [ 4 , 11 ]). A deep analysis of realistic lattice models of proteins proposed so far is definitely out of the scope of the present work, but there are few aspects of lattice models of proteins which need to be mentioned. The successful application of a lattice model depends obviously on the efficiency in generating conformations and searching for local minima. This aspect is dealt in the present work using Constraint Logic Programming, and taking advantage of all theoretical and implementative developments that have been realized in this context. The approach (and related languages) has been very seldom applied in the context of protein modeling and it has not been used for realistic protein structural predictions, to the best of our knowledge. A different, but equally important, aspect concerns the reliability of the model itself and of the forcefield used to evaluate conformational free energy. This aspect will not be dealt with by this work. An appropriate forcefield must take into account both local propensities to adopt a particular secondary structure (which ultimately depend on aminoacids' covalent structure and bulkiness) and their tendency to be in contact (which ultimately depends on their physico-chemical character). Contact potentials have been derived by many groups (see e.g. [ 12 , 13 ]) based on the observed versus expected contacts stored in the database. A similar approach could be followed in order to derive a torsional potential in order to describe local conformational propensities. However, it is not obvious how these potentials should be derived for lattice models and how the two potentials are to be considered together. These problems are not investigated here. Rather we consider contact potentials previously derived by our group from statistical analysis of the database [ 13 ], which are expected not to be accurate for a lattice model, but nevertheless should be able to reproduce essential features of aminoacid interactions. The local propensity to adopt a particular secondary structure can be computed by predictive methods [ 14 ]. However, for the small peptides analyzed in this paper, the correct secondary structure is selected from the deposited structures for testing purposes. Constraint Logic Programming (briefly, ) [ 15 , 16 ] is a declarative programming paradigm particularly well-suited for encoding combinatorial minimization problems. It is the natural merger of the two declarative paradigms known as Constraint Solving and Logic Programming . One of the peculiar features of is the independence of the problem modeling and of the search's strategy. Problem modeling is based on traditional declarative programs in which one can use the built-in notion of constraint . Constraints are first-order formulas concerning variables that can assume values in some domains . The scheme is general. Various possible constraints and domains can be used. However, for combinatorial problems it is common to use finite domain constraints , namely arithmetic constraints between arithmetic expressions, where variables range over finite subsets of ℕ. Constraint Logic Programming over Finite Domains is known as ( ). We briefly introduce this programming paradigm with a simple example. Let us consider three variables X , Y , Z that denote the number of possible items of some kind. domain([ X , Y , Z ], 1, 10) is a constraint that states that the three variables X , Y , Z have (finite) domain {1, 2, ..., 10}. Suppose we wish to state that the weight of each item of X is 3, of Y is 4, and of Z is 5 and the total weight of selected items must be less than or equal to 40. Moreover, we wish to state that the number of items of X plus those of Y must be less than those of Z . This can be simply stated as: 3 * X + 4 * Y + 5 * Z ≤ 40, X + Y < Z We have modeled a sort of knapsack problem using ( ). In general, in the modeling stage we can use constraints as well as declarative programs involving them. Solution's search is performed by a constraint solver that is available in the language. The constraint solver uses constraints for sensibly pruning the search tree. One of the main capabilities is called constraint propagation . Constraint propagation reduces the domains of the variables eliminating those values that cannot lead to constraint solutions. For instance, in the considered example, constraint propagation reduces the domains of the variables X , Y , and Z to {1, ..., 4}, {1, ..., 4}, and {3, ..., 6}, respectively. For finding a possible solution, a further built-in capability – the labeling predicate – can be used. We can look for a generic solution as well as for a solution minimizing some function. In the example above, we could ask for minimizing the function -2 X 2 + Y + 4 Z . This can be done by adding a constraint of the form: F = -2 * X * X + Y + 4 * Z , labeling([minimize ( F )], [ X , Y , Z ]). The constraint solver then exploits the solution's search using constraint propagation and branch-and-bound techniques returning the answer: F = 3, X = 3, Y = 1, Z = 5 The library clpfd of SlCStus Prolog [ 17 ] allows to effectively program in this framework. Let us observe that it is not required that F be a linear function. The above described approach to optimization combinatorial problems is the so-called Constrain & Generate technique introduced as opposed to the Generate & Test technique of the classical Logic Programming approach (see, e.g. [ 18 ]). In the latter approach, a first phase generates non-deterministically a possible solution, and then the deterministic test-phase checks whether the solution is acceptable or not. If the search space is exponential, this technique is not applicable. In the former approach, a first deterministic phase introduces a number of constraints, then a non-deterministic phase starts the generation of the solutions' space. The constraints introduced allow to sensibly prune the solutions' space in order to make the procedure effective. Moreover, in this phase one can take advantage from language built-in strategies (such as constraint propagation, branch and bound) and it is possible to further drive the solution search by means of problem-dependent heuristics. We have followed the Constrain & Generate programming style for encoding the protein structure prediction problem. As a matter of fact, the main predicate of our solution is of the form reported in Figure 1 . In the definition of the predicate constrain the protein structure prediction problem is modeled using constraints. In particular, the energy function is encoded in the Energy parameter, The predicate solution_search is aimed at looking for the solution minimizing the Energy parameter. The other predicates are auxiliary predicates. initialization resets some parameters, protein recovers the relevant input (see also Methods Section), writetime and print_results are output predicates. The constraint predicate is defined using several predicates each of them modeling one of the properties of the problem. For instance, the predicate next_constraints sets the distance between consecutive aminoacids (see Figure 2 ). Briefly, next_constraints recursively calls the predicate next for each pair of consecutive aminoacids. Assume that < X 1, Y 1, Z 1> and < X 2, Y 2, Z 2> are the variables that will store the positions of a consecutive pair of aminoacids, then the predicate next states that \| X 1 - X 2\| + \| Y 1 - Y 2\| + \| Z 1- Z 2\| = 2 and that \| X 1 - X 2\| ∈ {0, 1}, \| Y 1 - Y 2\| ∈ {0, 1}, \| Z 1 - Z 2\| ∈ {0, 1}. This is exactly the notion of adjacency in the face-centered cubic lattice of size 2 that we have used (see also the Methods Section). Results and discussion Constrained optimization problem in ( ) In Table 1 we report the results of the experiments with the ( ) code described in the Methods Section. All tests are done using SICStus PROLOG 3.11.1 [ 17 ] and a PC P4, 3.06 GHz. The structures of the protein model systems analyzed are known and stored in the PDB [ 3 ]. In the protein model systems 1LE3, 1PG1, and 1ZDD terminal protecting groups have been neglected. From left to right, the meaning of each column is as follows: the protein PDB identification code, the number N of aminoacids, the execution time, the energy of the best model found and its RMSD from the native structure for all the residues and for the core residues only. When there is not explicitly written "limit" it means that the program successfully terminated in the time reported; otherwise the program terminated due to time limit. We wish to observe that the results with time limit 10 h/24 h are typically computed in few hours. The rest of the time is used to further explore the solutions' space. When a CF = η is reported a further constraint on the compactness ratio η is added before the search. CF = η bounds the linear distances \| X i - X j \|, \| Y i - Y j \|, and \| Z i - Z j \| between all pair of residues i and j to η N where N is the length of the primary list. If η is low (e.g. 0.2), this constraint imposes a compact form to the protein and strongly reduces the running time. One of the structural constraints considered is the presence of disulfide bonded residues (ssbonds). The rigid structure of the lattice is such that a low value of Euclidean distance (e.g., 2) between ssbonds often precludes all possible solutions. For this reason the default is chosen as 6. However, in some cases we tried computations with lower value. In these cases in the table the text ss = γ is reported. The secondary structure, as computed from the deposited structure in PDB, has been input as constraint. As a unique exception, in the case of 1VII() we have instead predicted it using the GOR IV secondary structure prediction method [ 19 ]. The predicted structures have been also transformed into all atoms models as described in the Detailed models from lattice models Section. There is some improvement in general on RMSD from native structure. This is especially significant when the starting structure is already close to the native one, being not merely due to increasing compactness of the structure. It is moreover reassuring that the procedure we are discussing is able to recover realistic models starting from the very simplified lattice models. The RMSDs of the resulting detailed models from the corresponding native structures are reported in Table 2 . In order to assess the quality of the detailed model, the trace of the native structure and the reconstructed and optimized all-atom model are shown in Figure 3 for the core residues (7 to 30) of the WW domain (PDB id.: 1E0M). We conclude the section comparing some results of our prediction with those returned by the well-known HMMSTR/Rosetta Prediction System [ 20 ]. This program does not use a lattice as underlying model: aminoacids are free to take any position in ℝ 3 . For the sake of comparison, we have used it as an ab-initio predictor (precisely, we have disabled the homology and psi-blast options). The comparison is obviously not fair because in our case secondary structure is known and not predicted. Times are obtained from the result files, but it is not clear to which machine/CPU occupation they refer. Results are reported in Table 3 . HMMSTR/Rosetta prediction runs presumably faster, but our predictions (which however include known secondary structure) improve the RMSD (except for one case). Constrained molecular dynamics simulation We have used secondary structure information in conjunction with the well-established methodology of molecular dynamics simulations in order to implement a procedure similar to the one implemented using on the lattice. Secondary structure elements have been imposed through a constraining potential as described in the Methods Section. In order to search the conformational space a simulated annealing procedure has been adopted. Globularity of the simulated proteins is forced by a harmonic constraint on the radius of gyration. The simulation time, ranging approximately between one and four CPU days, required for folding each protein on a 1.533 GHz AMD Athlon processor is reported in Table 2 . The columns (from left to right) in Table 2 report the PDB identification code of the protein, the number of residues, the RMSD from native structure computed on C α atoms on the whole protein and only on core residues and the simulation time. The last column reports the RMSD from native structure for models obtained by after addition of all atoms and energy minimization as described in the Methods Section. The simulation time needed for obtaining structures similar to native structures increases with the size of the protein both for the increasing size of the system and for the longer simulated annealing runs needed because of increasing complexity of the free energy landscape. Unfortunately a safer scheme would employ substantially longer simulation times. This fact prompts for searching alternative ways to employ the same ideas. The results in terms of RMSD from native structure support the idea that folding may be achieved, at least in simulation, by a hierarchical approach where local secondary structure elements are formed first and later their arrangement and contacts are optimized. A similar conclusion has been reached using a different model by Maritan and coworkers [ 21 ]. The RMSD on core residues is, in all but one case, less than 5.0 Å. In four out of six cases the RMSD on core residues is close to 4.0 Å. In the worst case, which is also the longest simulated chain, the RMSD on core residues is 7.1 Å. Conclusions The purpose of the present work was to demonstrate that the protein folding problem can be approached by a well-established programming paradigm like . With respect to the few applications reported in the literature so far using the same methodology [ 22 ], mainly on the HP protein model [ 23 , 24 ], the present work takes a step further towards more realistic modeling. Notwithstanding the use of a protein simplified lattice model with a simple contact potential realistic models for a few small proteins have been generated by using . In the present application the known secondary structure of the protein has been imposed as a constraint. has been applied on face centered cubic lattice models of proteins where every aminoacid is represented by a single point on the lattice that can take one out of six possible positions with respect to the previous three aminoacids. It is immediately seen that the time needed for a systematic space search for such model grows exponentially with the number of free aminoacids. is a programming paradigm that is suited for the solution of optimization combinatorial problems. In the problem and the related heuristics are extremely natural to be programmed. Moreover, the constraint propagation allows to control the search in the huge solution's space. The results obtained using this approach and reported in Tables 1 to 3 show that for small proteins a solution for the optimization problem is obtained in less than few hours. For the larger proteins studied here the inaccuracies of both the lattice model and contact potential prevent finding a compact solution. These problems are more likely to appear with increasing size of the protein and when the length of non-constrained chain connecting two secondary structure elements is short, because the lattice allows a limited set of conformations. Further work is being devoted towards a more realistic modeling representation of the protein, with at least two centers of interaction per residue, and towards refinement of the potential function by including a term for rotamer preferences. This term should map on the lattice the directional preferences of each unit with respect to the previous three units. Each of the six possible next positions for each unit should be weighted by an energy term derived from database analysis. Also the optimal size of non constrained parts of the chain will be determined in order to allow more possible relative orientations among constrained secondary structure elements, possibly without increasing significantly the computation time. At present, however, when the positions of all atoms are reconstructed from the lattice C α trace, the RMSD on core residues of the resulting models, after energy minimization, compared to native structures, is as low as 4.8 Å for the thermostable domain of villin headpiece (PDB id.: 1VII), 3.6 Å for the WW domain (PDB id.: 1E0M), 2.3 Å for the coat protein-binding domain of bacteriophage P22 (PDB id.: 2GP8). It should be also noted that both the thermostable domain of villin headpiece and the WW contain three secondary structure elements that can be arranged in different ways in order to produce a compact structure. The low RMSD is therefore significant. A comparable protocol employing a molecular dynamics simulated annealing procedure still leads to superior results for larger proteins, as expected because the protein representation is more accurate, but it takes longer execution times between one and four days on a 1.5 GHz P3 machine. Recent results have shown that simplified models and more refined models can be employed successfully in hierarchical modeling procedures [ 9 , 10 ]. The results obtained in the present work suggest that could be useful for finding starting conformations for further refinement. Methods The protein structure prediction problem as a minimization problem The sequence of aminoacids defining a protein is called primary structure . This structure uniquely determines the (3D) native conformation, also known as tertiary structure . The protein structure prediction problem is the problem of predicting the tertiary structure of a protein given its primary structure. The native tertiary structure minimizes the global free energy of the protein. Abstraction level We consider each aminoacid as a single sphere centered in its C α atom; the distance between two consecutive C α atoms is assumed to be 3.8 Å Recent results (see, e.g., [ 13 ]) show that a contact between two residues, when represented only by their C α atoms, is optimally defined for C α - C α distances shorter than 6.4 Å The number is obtained as the sum of the radius of the two C α carbon atoms we are dealing with (2 x 1.9 Å) and the value of 2.6 Å empirically determined in [ 13 ] for van der Waals surface contact. A table that points out the energy associated to pairs of aminoacids in contact has been developed [ 12 , 13 ]. Let us denote by Pot( x , y ) the energy value associated to a contact between aminoacids x and y (the order is immaterial); this value can either be positive or negative, according to the pair x , y . Lattice model According to [ 25 ] we use the Face-Centered Cubic Lattice ( ) that allows realistic angles between consecutive residues. The lattice is composed by cubes of size 2, where the central point of each face and the vertices are admitted. Thus, the domain consists in a set of triples < x , y , z > where < x , y , z ∈ >. We recall that given a point < x , y , z >, its 2-norm is: \|\|< x , y , z >\|\| = . Given two points p 1 and p 2 , \|\| p 1 - p 2 \|\| is known as their Euclidean distance . Going back to the lattice, two points at Euclidean distance are linked together, forming a lattice unit , corresponding to the distance of 3.8 Å. In this lattice, each point is adjacent to 12 neighboring points. A contact is defined between two non adjacent residues placed on two vertices of a side of a cube (i.e. they have Euclidean distance equal to 2, corresponding to 5.4 Å). This number can be considered a good approximation of the limit of 6.4 Å described above. Mathematical formalization In this setting, it is possible to formalize the protein folding problem as an optimization problem. Given a sequence S = s 1 ... s n , with s i aminoacids, a fold of S is a function ω : {1, ..., n } → such that: \|\| ω ( i ) - ω ( i + 1)\|\| = and \|\| ω ( i ) - ω ( j )\|\| ≥ 2 for i ≠ j . The first constraint states that consecutive aminoacids have a fixed distance, corresponding to one lattice unit; the second that each aminoacid occupies a unitary sphere and that two spheres cannot overlap. The protein folding problem can be reduced to the optimization problem of finding the fold ω of S such that the following energy is minimized [ 26 , 27 ]: where contact( ω ( i ), ω ( j )) is 1 if \|\| ω ( i ) - ω ( j )\|\| = 2, 0 otherwise. To avoid solutions equivalent modulo simple symmetries, other constraints can be added on the first positions. Complexity issues The decision version of this problem (and even of its HP-abstraction) is proven to be NP-complete on various lattices [ 28 , 29 ]. However, we do not want to solve the problem for proteins of arbitrary length. Solving it for length N = 200–300 could be considered as an important contribution to biological sciences and there are yet such results using the HP-abstraction [ 30 ]. Thus, in spite of its NP-completeness, it is important to understand the size of the solution's space. The size of the solution's space is the number of self-avoiding walks on the lattice that can be approximated by the formula (cf., e.g., [ 31 ]) SAW fcc = 1.26 N 0.162 (10.0364) N (2) This formula should modify in the presence of additional constraints as mentioned later. Main implementation issues Our implementation of the protein folding minimization problem described in the above sections is based on the code briefly introduced in the Background Section. The complete program and related material can be found in [ 32 ]. The program consists of ~2000 lines and, once loaded in SICStus Prolog, one may call goals of the kind reported in Figure 4 , where Protein_Name is a standard PDB identification code, such as 1ENH. Time is the maximum amount of time in seconds that we let to the runtime; the default is 10 hours. CompactFactor allows to impose an additional constraint on the maximal distance between every pair of aminoacids. The rationale behind this additional constraint stems from the observation that protein structures are more compact than expected based on a freely rotating chain model [ 33 ]. In particular, the average end-to-end distance for a freely rotating chain model is approximated by where ℓ is the length of each unit and α is the cosine of the angle made by each unit with the direction of the preceding unit. The average end-to-end distance is clearly related to the average maximal dimension of the chain. Based on a survey of protein structures Huang and Powers derived the following approximated formula for the radius of gyration (in Å): 2.2 N 0.38 [ 34 ]. Note that the exponent is less than 0.5 which is an underestimate of the exponent for a self avoiding walk. For a uniform density sphere the diameter is the radius of gyration. The default value for CompactFactor was therefore assumed to be approximately equal to times the radius of gyration which in turn was computed by the empirical formula 2.2 N 0.38 [ 34 ]. The auxiliary file data.pl stores the Primary and Secondary structures of the proteins that one wishes to test, as, for instance in the example reported in Figure 5 . The output in standard PDB format [ 3 ] is printed either on the screen or in a file named output-Protein_name.pdb. Constraints The intrinsic complexity of the problem forces us to introduce several other constraints. For instance, we constrain the sum of the coordinates of each aminoacid in the lattice to be even (a property of the lattice) and we add some constraints for avoiding equivalent symmetric solutions. In what follows, we refer to predicate names as used in the code. avoid_symmetries removes redundant admissible conformations equivalent to others modulo some symmetries and/or rotations. The predicate assigns immediately three consecutive aminoacids positions (in the Tertiary list). With distance_constraints, we also impose that two non consecutive residues must be separated by more than one lattice unit, to reflect the steric interaction between the C α s modelling aminoacids. As described above, compact_constraints imposes that, for every pair of aminoacids, the norm of the projection of their distance on each x , y , z coordinate, is smaller than CompactFactor × N. Further constraints are related to angles. In the lattice, the angle between three consecutive residues can assume values in {60°, 90°, 120°, 180°}. In real proteins, steric occupancy and energetic potential show a clear distribution of bend angles in the range 90°–150° [ 7 , 35 ]. When transferring on lattice, it is a good approximation to exclude 60° and 180° angles, as unfeasible. This constraint allows us to restrict the search space from a number close to 10 N (cf. formula (2)) to a number close to 5 N . As said in the Lattice model Section, a contact is generated by two non consecutive aminoacids with Euclidean distance less than or equal to 2. As a consequence of the constraints applied, it suffices to check for a contact when the lattice distance equals 2, since distance_constraints excludes from the domain the possibility to place two non consecutive aminoacids at one lattice unit. We also impose constraints coming from secondary structure information. Secondary structure can be predicted with good approximation (e.g., [ 36 ]). In our set of data we have collected such information from the Protein Data Bank. We represent secondary structure information as helix( i , j ): elements i , i + 1, ..., j of the input sequence form an α -helix; strand( i , j ): elements i , i + 1, ..., j are in a β -strand; ssbond( i , j ): there is a disulfide bridge between element number i and j . We use an auxiliary list called Indexes that stores torsional angles defined by four consecutive aminoacid positions. Due to lattice structure and our constraints, every four consecutive aminoacids can form only 6 discrete angles. Thus, each variable in Indexes can assume a value i from {0, ..., 5}, representing torsional angles of 0°, 60°, 120°, 180°, 240°, 300°, respectively. With these conventions, helices are approximated by sequences of indexes of the form 5, 5, 5, ... while β -strands are associated to sequences of the form 3, 3, 3, .... Note that specifying the coordinates of three points (i.e. to place and orient the protein) and the indexes, uniquely determines the conformation, ssbond( i , j ), introduces a maximum distance constraint between the aminoacids i and j . The predicate energy_constrain is developed using an auxiliary symmetric matrix M . The optimal fold is reached when the sum of M elements is minimal. During the labeling phase, the information stored in M is used to control the minimization process and to cut the search tree. Labeling stage To reduce the size of the solution's space visited during execution, we have replaced the built-in labeling predicate with an ad-hoc constraint-based solution search predicate, called solutions_search . We describe here briefly the main features of this predicate and of its auxiliary predicates. solutions_search • If the Tertiary list or the Indexes list is ground (already computed), then it terminates the folding process (possibly, after a call to the built-in labeling). • Otherwise, it calls choose_labeling . When this procedure terminates, it calls recursively solutions_search . Termination is guaranteed by the fact that each call to choose_labeling reduces the number of non-ground variables. choose_labeling • If the number of variables to be instantiated is low (in our code less than 4), it calls the built-in labeling. • Otherwise, it calls selection_strategy . This predicate computes several subsequences of the list of Indexes . Each subsequence consists of alternations of ground elements and non-ground variables. selection_strategy selects the most known subsequence , namely the one containing the smallest ratio of variable over ground indexes, preferring the ones that include a ssbond. If in the selected subsequence there are too many variables, an arbitrary subsequence cut is done. After the subsequence is selected, the procedure labeling_new_launch is called. labeling_new_launch It calls the auxiliary predicate labeling_new but stops the solution search when the global runtime is greater than the input time limit. If this is the case, the best computed solution is returned. labeling_new This procedure receives the chosen sublist to be folded. Each index variable in it, is assigned an admissible value between 0 and 5. The order of values that is tried for each index is described by a pre-computed auxiliary list. For each torsional index, a frequency statistics of the 6 indexes is pre-computed and extracted from the PDB, according to the specific aminoacid sequence involved locally. We use this information to direct the search and explore first the most common torsional angles, in the hope that this selection rule reflects nature's strategy. Moreover, the energy associated to the fold is minimized. For doing that, after each instantiation of a fixed number t of variables in a phase, we collect the best known ground admissible solution, its energy and its associated potential matrix. We compare the current status to history and decide if it is reasonable to cut the search tree. In particular, we designed a heuristic that allows to control the effectiveness of the cut, adapting it dynamically to the status of the fold. Practically, when the protein is partially specified, we estimate the ratio between ground and non-ground variables in the potential matrix. If the ratio is low (i.e. the protein is poorly determined), we allow the current energy to be worse than the corresponding counterpart in the best fold so far reached. When the ratio is high (i.e. protein almost folded) we constrain the current energy to be slightly lower than the previous best known. Molecular dynamics simulations In order to have a fair comparison with a similar approach using all-atom protein models we built detailed all atom models for six proteins in the studied set (namely those with PDB id. code: 1VII, 1E0M, 2GP8, 1ENH, 2IGD, 1YPA) and imposed, through torsional constraints, the secondary structure geometry found in the native structure. The constraining potential was 100 ( θ - θ 0 ) 2 kcal/(mol rad 2 ). The reference target angles (i.e. θ 0 in the previous formula) were set to φ = -139 and ψ = 135 for residues in β -strand and to φ = -48 and ψ = -57 for residues in α -helices. For all constrained residues also the ω dihedral angle was constrained at 180 degrees. The chain was first built fully extended and minimized by 400 steepest descent minimization steps and by 500 conjugate gradients minimization steps. The protein was then heated in 10 ps up to 900 K in 20000 steps using a timestep of 0.0005 ps. Then the temperature was lowered down to 270 K in 20 steps. During each step molecular dynamics simulation was carried out for 100 ps for a total simulation time of 2 ns. Simulations used the Generalized Born implicit solvent method [ 37 ] as implemented in the program CHARMM [ 38 ] with standard parameters for proteins. The forcefield used was CHARMM v.27 [ 39 ]. In order to obtain globular protein during simulation a constraint on the radius of gyration (computed only on C α atoms) was imposed. The target radius was decreased during the simulation from a value proper of an extended conformation down to the value given by 2.2 N 0.38 [ 34 ] where N is the number of residues. The potential used for enforcing compactness was: kcal/mol, where , n is the number of atoms, r cg is the center of geometry of the same group of atoms, and R g 0 is the target gyration radius which is decreased during simulated annealing down to the theoretical value based on the formula cited above. Detailed models from lattice models The models obtained by described here may be converted into all-atom models which are realistic models of proteins. As a test the structures of all the proteins tested by simulated annealing described above were converted using the Maxsprout server [ 40 ] into an all heavy atom model. Hydrogens have been added using the module HBUILD in the program CHARMM [ 38 ] and the resulting structure was relaxed by energy minimization (using a distance dependent dielectric constant). First a minimization was performed with all backbone atoms fixed, then only C α atoms were fixed and finally a 100 ps molecular dynamics simulation (following a heating phase of 10 ps) using the Generalized Born implicit solvent model was performed. The resulting structure at the end of the simulation was energy minimized. The initial minimizations required 1500 minimization steps each, because the starting structures were built from the lattice models. The final minimization, on the structure relaxed by molecular dynamics simulation, employed 900 minimization steps. During molecular dynamics simulation the radius of gyration and backbone torsion angles corresponding to residues constrained in the ( ) procedure were constrained as described above.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC539352.xml
526258	Readmission and overstay after day case nasal surgery	Background A readmission is classified as a patient necessitating readmission to hospital due to a post-operative complication following discharge. An overstay however, is classified as a patient having to stay longer than the planned duration in hospital (not having been discharged in the interim) due to a post-operative complication. This study aims to investigate patient-related factors that predispose to readmission or overstay and thus make recommendations to decrease the likelihood of readmission or overstay. Method In this retrospective study 312 'day-case nasal procedures', were selected from a total cohort of 4274 ENT patients over a 17-month period. This sub-group was investigated for a range of demographic factors including, age, gender and ethnicity with regards to their relationship to readmission rates and overstay frequency and duration. Results The rates were 2.88% and 9.62% for readmission and overstay respectively. The total number of days spent in hospital as a result of readmission was 27. Epistaxis was the leading cause for readmission/overstay (28.9%) followed by high levels of post-operative pain preventing them from being discharged (23.7%). All procedures in this study had readmission rates that were below those recommended in the guidelines set by the Royal College of Surgeons of England. Women overstayed significantly longer (t = 1.65, p < 0.05) than men. Conclusions Suitable candidates for day-case ENT surgery highlighted by this study include healthy individuals between the ages of 20 and 60. Operating in the morning would increase the immediate post-operative recovery time, which may reduce the numbers of patients who complain of high levels of pain at the time of discharge. Procedures such as septorhinoplasty being performed routinely in the ambulatory setting require additional research into more effective methods of pain control. Standards need to be improved so that the causes of overstay and readmission are clearly identifiable in patient records.	Background Day-case surgery has rapidly expanded as a cost-effective and resource-conserving surgical intervention to the point that well in excess of two million operations are performed in a day-case/ambulatory setting in the United Kingdom alone each year [ 1 ]. Day-case surgery is based on operating on a patient and aiming to discharge them on the same day. Ear, nose and throat procedures account for a significant proportion of these ambulatory procedures and include operations such as functional endoscopic sinus surgery and rhinoplasty. It has been suggested that day-case surgery should be confined to those procedures where less than 3% of patients require admission post-operatively [ 1 ]. Septorhinoplasty is generally considered to be a traumatic procedure with risks of epistaxis and periorbital haematoma. However, the decision to perform septorhinoplasty in a day case setting may be made on the basis of its cost-effectiveness and rapid post-operative recovery in suitable operative candidates. Through the NHS Plan, the Department of Health has stated its aim of three-quarters of operations will being performed on a day case basis within the next decade [ 2 ]. It states that in these procedures there will be no overnight stay required so that traditional waiting lists for surgery will 'become a thing of the past'. A King's College Hospital Study commissioned by the Department of Health has suggested that day-case surgery may not be saving the NHS money [ 3 ]. However, previous reports have advocated day case septal surgery as a safe and effective practice [ 4 - 6 ]. Furthermore, a subjective patient based study showed that septoplasty is generally acceptable to the patient in terms of pain and overall satisfaction parameters [ 5 , 7 ]. Studies have shown that day-case septorhinoplasty is associated with a low complication rate and is a safe and acceptable procedure provided that stringent patient selection criteria are adhered to [ 8 ]. A specific area of dissatisfaction previously identified is inadequate pain control following discharge and this may lead to higher costs for the general practitioner. However, a recent study investigating parental satisfaction with 100 paediatric otorhinolaryngology day-case procedures concluded that with careful patient selection the degree of satisfaction with day surgery is high for a wide variety of procedures [ 9 , 10 ]. There have been no studies performed, which have directly investigated the 'patient demographic factors' which predict the likelihood readmission or overstaying the electively planned period in hospital following day-case ENT operations. This is of importance as it would be beneficial to know if certain groups of patients require more rigorous screening pre-operatively in an attempt to reduce readmission and 'overstay' rates. By identifying this cohort of patients, the NHS could save substantial amounts of acute and primary care expenditure in the backdrop of ever-rising day-case ENT procedure numbers. Many studies have suggested that ENT procedures currently performed as overnight cases could be performed as day-cases provided strict criteria are applied in the selection of patients [ 1 , 11 ]. However, none of these studies provide a clear description as to which patient groups are potentially unsuitable for undergoing day-case procedures based upon their predisposition to require readmission or stay in hospital longer than electively planned. Previous data fails to distinguish between readmissions and overstays following nasal day-case surgery [ 11 ]. They also fail to investigate demographic indices such as age, gender, and ethnicity [ 5 ]. The present study has been conducted in the climate of an ever-advancing quality-driven clinical environment in which meticulous patient selection is vital in optimal patient post-operative care and recovery. This study of 312 elective day-case nasal operations selected from a cohort of 4274 ENT patients investigated a range of patient variables that influenced readmission and overstay frequency and duration. This study investigates departmental day-case nasal surgery at Guy's hospital and aims to determine: a) If it has readmission rates below that of the accepted standard for day-case surgery stipulated by the Royal College of Surgeons of England. b) If readmission rate and unplanned overnight stay are related to epidemiological characteristics of the sample such as age, gender, and ethnicity. and to report results in the context of clinical management by making recommendations to improve the readmission rates in each category proposed. Method This is a retrospective study in which the total number of ENT operations performed between the period of 3 rd January 2002 and 28 th June 2003 were investigated. All ENT patients operated on during this period were selected from the Guy's & St. Thomas' NHS Trust database. The hospital database has a limited range of broad categories and this can limit interpretation of results thus all available patient notes were also reviewed. All planned day-case procedures were selected from the total cohort of elective ENT operative procedures. The day-case procedures were then further narrowed down to 'nasal day-case procedures'. Firstly the total number of readmission episodes, overstay frequency and duration in the 'day-case nasal procedures' were calculated. A readmission is classified as a patient necessitating readmission to hospital due to a post-operative complication following discharge. An overstay however, is classified as a patient having to stay longer than the planned duration in hospital (not having been discharged in the interim) due to a post-operative complication. The groups of nasal operations of interest in this study in the light of previous studies are (septo)rhinoplasty, excision of lesion, polypectomy, sinus operation and other (which includes procedures such as intranasal ethmoidectomy, and division of adhesions of turbinate of nose etc). A range of demographic factors including, age, gender and ethnicity were investigated with regards to their relationship to readmission rates and overstay frequency and duration. Statistical analysis including Chi-square tests, t-tests and ANOVA were performed on the above variables. Results The total number of ENT operations performed between the period of 3 rd January 2002 and 28 th June 2003 were 4274. From this cohort 501 operations (11.72%) were planned as elective ENT day-case procedures. This selected sub-sample of 501 day-cases was further narrowed down to those, which pertained to 'nasal procedures' and this group numbered 312 (62.28%). There were a total of 9 readmission episodes following 'day-case nasal procedures' during the 17-month period, which equates to a readmission rate of 2.88%. The total number of days spent in hospital as a result of readmission was 27. All patients readmitted following day-case nasal procedures were male (Fischer Exact Test = 4.41, p < 0.05). The nasal operations were grouped into (septo)rhinoplasty, excision of lesion, polypectomy, sinus operation and other. Those patients that were required to stay longer than electively planned i.e. one day, are termed by the Guy's & St. Thomas' NHS Trust and indeed in this study as 'over-stays'. The minimum duration of overstay in our sample was one day and the maximum was 2 days. The total incidence of patients overstaying was 30 (overstay rate = 9.62%) during the timeframe studied and this equates to a total of 48 overstayed days. Cause of readmission and overstay Epistaxis was the leading cause for readmission/overstay n = 11/38 (28.9%) followed by levels of post-operative pain unacceptable to the patient and thus preventing them from being discharged (23.7%). Type of procedure The readmission rate for (septo)rhinoplasty is 1.38% and the overstay rate is 9.22%. From the analysis of days overstayed expressed as a fraction of the number of procedures performed, polypectomy and sinus operations have the highest number of days overstayed per procedure. Although the (septo)rhinoplasty overstay rate is 9.22% the number of days overstayed expressed in the context of the number of actual (septo)rhinoplaties performed is equal to the average (see Figure 1 ). Figure 1 Days overstayed as a fraction of the procedures performed. Gender Women overstayed significantly longer (t = 1.65, p < 0.05) than men. Age The frequency of readmission is highest in those patients aged <20 followed by those in the 60–70 year age category. Although the patients aged above 70 years have the lowest readmission frequency, the sample size is low (n = 5) and thus the 30–40 year age category is more reliable a sample representative of a low readmission frequency. Analysis of the age of patients and frequency of day-case procedures revealed that the group containing those patients aged between 30–40 underwent the greatest number of nasal day-case procedures. However, when considering the number of overstays in terms of the numbers of procedures performed, the 30–40 age category has the lowest overstay duration as opposed to the >70 which has the highest. Ethnicity Analysis of variance (ANOVA) shows that the difference in overstay rates between ethnic groups did not reach statistical significance (F = 1.22, p = 0.40). Discussion In July 2000, the Department of Health published that 75% of surgical procedures carried out by the NHS should be performed in a day-case setting by 2010. This initiative was supported by the both The Royal College of Surgeons of England and The Royal College of Physicians of England. Within the period of the current study there were a total of 4274 ENT operations performed at Guy's during the time-frame of investigation. Of this group 501 (11.72%) were planned as elective ambulatory procedures with the intention of same day discharge. Primarily the government target was ambiguous with regard to the types of procedure for which it aimed to conduct on a routine day-case basis. Whilst it is conceivable that some ENT procedures such as myringotomy could be performed safely as a day-case procedure, more complex and involved procedures such as deep exploration of the neck and tumour excision would be unsuitable for such rapid discharge. With no clear guidelines as to which procedures are suitable for the day-case setting, the responsibility of advancing the boundaries of ambulatory surgery rests on the clinicians, with the patients' wellbeing being at the forefront of interest. The readmission in this study is 2.88%. These readmission rates are lower than those reported in the contemporary literature [ 4 , 8 , 11 ]. The readmission rate for (septo)rhinoplasty is 1.38% and the overstay rate is 9.22%. These rates are lower than those stipulated by the Royal College of Surgeons of England which pertain to day-case surgery in general (2–3%) as opposed to ENT cases per se. Epistaxis was the leading cause for readmission/overstay (28.9%) followed by levels of post-operative pain unacceptable to the patient and thus preventing them from being discharged (23.7%). The cause of epistaxis was not recorded in the notes nor was the reason behind why some patients experience more pain than others. These results are in contrast to previous subjective patient based studies, which show that septorhinoplasty is generally acceptable to the patient in terms of pain and overall satisfaction parameters [ 5 ]. Women overstayed significantly longer (t = 1.65, p < 0.05) than men. A similar phenomenon has been reported in a study of cardiothoracic patient readmissions [ 12 ]. In this study the female predilection to increased in-hospital recovery time was attributed to various gender-associated factors. Age is not a contraindication for ENT day-case surgery. The low readmission rate of patients over 70 years of age could be attributed to a number of factors including, heightened caution of the clinician in patient discharge, a low sample number and age-related variation of procedure type are dominant. There have been no previous studies, which have investigated the effects of ethnicity on readmission rates or overstay duration. The current study shows that mixed race patients followed by black patients have the highest number of days overstayed per procedure. Analysis of variance (ANOVA) shows that there is no significant difference between ethnic groups and the length of overstay (F = 1.22, p = 0.40). Conclusions Day-case procedures should be performed on suitable candidates on a sound clinical basis. This includes meticulous patient selection, both on the part of the surgeon and the health care professionals in the preoperative assessment. Suitable candidates for day-case ENT surgery highlighted by this study include healthy individuals between the ages of 20 and 60. A protocol for day-case surgery does exist and this may need revision. In the clinical setting however, epistaxis needs to be made a clinical priority by ensuring that all levels of healthcare professionals are aware of its causes and its effective immediate management. We suggest from experience that operating in the morning would increase the immediate post-operative recovery time, which may reduce the numbers of patients who complain of high levels of pain at the time of discharge. Procedures such as septorhinoplasty being performed routinely in the ambulatory setting require additional research into more effective methods of pain control. Clinical administration standards need to be improved so that the causes of overstay and readmission are clearly identifiable in patient records. Competing interests The authors declare that they have no competing interests. Authors' contributions Mr. Gurminder Singh (first and corresponding author) performed the data collection and wrote the paper with assistance from Mr. David McCormack (second author). Mr. David Roberts supervised the study and reviewed the completed manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC526258.xml
524471	BMAL1 and CLOCK, Two Essential Components of the Circadian Clock, Are Involved in Glucose Homeostasis	Circadian timing is generated through a unique series of autoregulatory interactions termed the molecular clock. Behavioral rhythms subject to the molecular clock are well characterized. We demonstrate a role for Bmal1 and Clock in the regulation of glucose homeostasis. Inactivation of the known clock components Bmal1 (Mop3) and Clock suppress the diurnal variation in glucose and triglycerides. Gluconeogenesis is abolished by deletion of Bmal1 and is depressed in Clock mutants, but the counterregulatory response of corticosterone and glucagon to insulin-induced hypoglycaemia is retained. Furthermore, a high-fat diet modulates carbohydrate metabolism by amplifying circadian variation in glucose tolerance and insulin sensitivity, and mutation of Clock restores the chow-fed phenotype. Bmal1 and Clock, genes that function in the core molecular clock, exert profound control over recovery from insulin-induced hypoglycaemia. Furthermore, asynchronous dietary cues may modify glucose homeostasis via their interactions with peripheral molecular clocks.	Introduction The master clock, which, in mammals, resides in the hypothalamic suprachiasmatic nucleus (SCN), is thought to synchronize multiple peripheral oscillators to ensure temporal coordination of behavior and metabolism. Peripheral clocks amplify or dampen central rhythms or exhibit autonomous behavior to facilitate local adaptive responses ( Hastings et al. 2003 ). The central clock may communicate to modulate or entrain rhythms in the periphery via hormones ( McNamara et al. 2001 ) or hemodynamic cues. Asynchronous environmental cues, such as eating, also influence the autonomous behavior of peripheral clocks ( Damiola et al. 2000 ; Stokkan et al. 2001 ). The variation in sleep and wakefulness (activity) is perhaps the most well-known circadian rhythm. Surgical ablation of the SCN in mice ( Ibuka et al. 1980 ; Welsh et al. 1988 ) and rats ( Ibuka et al. 1977 ; Mosko and Moore 1979 ) abolishes the nocturnal burst in locomotor activity. Similarly, disruption and/or mutation of Bmal1 ( Bunger et al. 2000 ) or Clock ( Vitaterna et al. 1994 ), transcription factors that compose the positive limb of an autoregulatory feedback loop in the core molecular clock ( Young and Kay 2001 ; Reppert and Weaver 2002 ), also impairs circadian behavior. Bmal1 and Clock may influence behavioral rhythms by regulating the firing rate of SCN neurons ( Herzog et al. 1998 ; Deboer et al. 2003 ). Genes relevant to the molecular clock are also expressed in peripheral tissues ( Akhtar et al. 2002 ; Kita et al. 2002 ; Panda et al. 2002 ; Storch et al. 2002 ; Oishi et al. 2003 ) where approximately 5%–10% of the transcriptome is subject to circadian oscillation ( Albrecht and Eichele 2003 ). Although the precise role of peripheral clocks and the mechanisms that link them to the SCN remain largely obscure, genetic mutation or deletion has implicated peripheral clocks in the regulation of some aspects of cellular function, including division ( Matsuo et al. 2003 ), estrous cyclicity ( Miller et al. 2004 ), and phospholipid metabolism ( Marquez et al. 2004 ). Glucose and lipid homeostasis are also known to exhibit circadian variation ( Seaman et al. 1965 ; Malherbe et al. 1969 ; Gagliardino and Hernandez 1971 ; Schlierf and Dorow 1973 ). Surgical ablation of the SCN impairs the control of glucose homeostasis ( la Fleur et al. 2001 ). However, the proximity of satiety centres to the SCN has potentially confounded interpretation of these results. Indeed, there is no direct evidence implicating the molecular clock in the regulation of glycaemia or insulin sensitivity (S i ). Our studies revealed a profound role for core clock genes— Bmal1 and Clock —in regulating recovery from insulin-induced hypoglycaemia. Furthermore, the impact of a high-fat diet (HF) was to amplify the diurnal variation in glucose tolerance and S i in a manner dependent on the Clock gene. These studies suggest that the temporal distribution of a caloric load may influence the response to insulin and that circadian variability in glucose homeostasis may be subject to modulation by asynchronous dietary cues. Results We examined the role of the molecular clock in glucose homeostasis by using mice in which core clock genes are impaired (Clock mut ) or deficient (Bmal1 −/− ) . Both plasma glucose and triglycerides were subject to circadian variation in wild-type (WT) mice, peaking at approximately circadian time point 4 (CT4) and CT28 (where CT0 is subjective day beginning at 7 AM, and CT12 is subjective night beginning at 7 PM) ( Figure 1 A and 1 B), as reported previously ( Seaman et al. 1965 ; Schlierf and Dorow 1973 ). We also observed that corticosterone ( Figure 1 C), which stimulates gluconeogenesis during hypoglycaemia ( Cryer 1993 ), and adiponectin ( Figure 1 D), which has been associated with insulin resistance ( Yamauchi et al. 2001 ; Maeda et al. 2002 ), oscillated significantly, but out of phase with the glucose and triglyceride rhythms. Diurnal variation in glucose and triglycerides, but not in corticosterone, was disrupted in the mutant mice ( Table 1 ). Figure 1 Circadian Variation of Glucose, Triglyceride, and Hormone Levels in Circulating Blood Plasma from whole blood isolated from unchallenged WT mice at different CTs was analyzed for glucose (A), triglyceride (B), corticosterone (C), and adiponectin levels (D) ( n = 12 per time point). Results for Bmal1 −/− and Clock mut mice are shown in Table 1 . Table 1 Clock-Controlled Metabolic Rhythms Utilizing peak and trough CTs described in Figure 2A, WT mice showed circadian variation in glucose and triglycerides at CT5 and CT17 that was absent in Bmal1 −/− mice, though corticosterone rhythms were preserved in the mice with disrupted circadian rhythms. Values are presented as mean ± SEM; n = 7–12 * p < 0.05 versus corresponding time point (one-way ANOVA with the Kruskal-Wallis test) ND, no data Although there was no clear rhythm in the hypoglyacemic response to insulin, recovery of blood glucose exhibited a robust circadian variation ( Figure 2 A), with an excessive rebound from the effects of insulin evident at subjective dawn (CT19 and CT25) ( Figure 2 A). Insulin caused a profound hypoglyacemic response, independent of clock time, in both Bmal1 −/− and Clock mut mice ( Figure 2 B). This response was more pronounced in the former, consistent with the comparative severity of the molecular and behavioral phenotypes between the Bmal1 −/− and Clock mut animals ( King et al. 1997 ; Bunger et al. 2000 ). Despite exacerbation of the hypoglycaemic response to insulin in the mutants, the counterregulatory responses of both corticosterone and glucagon were retained ( Figure 2 C and 2 D). Figure 2 Disruption of Genes in the Core Molecular Clock Alters the Response to Insulin (A) Insulin tolerance (IT) was examined in WT mice on CT7, CT13, CT19, and CT25 at 30 min, 60 min, and 90 min after insulin injection ( n = 12 per time point, * p < 0.01). (B) IT was examined in WT (black line), Bmal1 −/− (blue line), and Clock mut mice (green line) at CT1 (i) and CT13 (ii) ( n = 6–10, * p < 0.05, † p < 0.01, †† p < 0.001). (C and D) Plasma levels of the counterregulatory hormones corticosterone (C) and glucagon (D) were assessed 60 min after insulin injection in Bmal1 −/− and Clock mut mice ( n = 7, corticosterone assay; samples were pooled for glucagon assay, * p < 0.05). Gluconeogenesis also contributes to restoration of blood glucose after insulin-induced hypoglycaemia. Consistent with this observation, conversion of exogenously administered pyruvate to glucose, which reflects gluconeogenesis ( Miyake et al. 2002 ), was impaired in the Clock mut animals. This impairment was most marked in Bmal1 −/− mice, while Bmal1 +/− and Clock mut mice exhibited an intermediate phenotype when compared with WT littermate controls ( Figure 3 A). Furthermore, activity of the key rate-limiting enzyme of gluconeogenesis, phosphoenolpyruvate carboxykinase (PEPCK), exhibited diurnal variation in the liver and aorta that was blunted in Clock mut mice ( Figure 3 B). PEPCK activity in kidney was antiphasic to the rhythm in aorta and liver and was unimpaired in Clock mut mice ( Figure 3 B), suggesting tissue-specific regulation of enzyme activity. Figure 3 Impaired Gluconeogenesis in Mice with a Disrupted Circadian Clock (A) Pyruvate tolerance was compared among WT (black line), Bmal1 +/− (blue line), and Bmal1 −/− (purple line), and Clock mut (green line) mice at CT7 ( n = 6–10). (B) Relative PEPCK activity (units are expressed as luciferase activity × 10 3 ) was measured in liver (i), aorta (ii), and kidney (iii) from WT (white bars) and Clock mut mice (green bars). The frequent sampling intravenous glucose tolerance test (FSIGT) was performed to assess more precisely the impact of the molecular clock on sensitivity to insulin. This test provides an estimate of S i , consistent with that obtained by the euglycaemic clamp ( Pacini et al. 2001 ). Additionally, data modeling provides estimates of glucose-mediated glucose disposal (S g ), insulin secretion, and S i . S i and insulin secretion, but not S g , exhibited a diurnal variation in WT mice fed a regular chow diet (RC) ( Table 2 ). Circadian variation of glucose and lipid homeostasis might condition the metabolic response to asynchronous environmental cues, such as diet, that impinge on S i . Dyslipidemia coincides with insulin resistance in the metabolic syndrome ( Brotman and Girod 2002 ), and a diet high in fat impairs S i ( Grundleger and Thenen 1982 ; Coulston et al. 1983 ). Both HF-fed WT and HF-fed Clock mut mice increased body weight significantly and to a similar degree in comparison to their age-matched, RC-fed controls ( Table 3 ). Body fat composition averaged 17.6% of lean body mass in RC-fed WT mice, rising to 27.7% ( p < 0.002) on high-fat feeding. Again, fat composition was not significantly altered by the presence of the Clock mutation ( Table 3 ). Table 2 Indices of Noninsulin- and Insulin-Mediated Parameters of Glucose Disposal Derived from Modelling of FSIGT Data at CT1 and CT13 Values are presented as mean ± fractional standard deviation ( n = 6–7 per group) a p < 0.001 versus HF group (two-tailed, Student's t-test) b p < 0.001 versus respective group at CT1 G 0 , blood glucose concentration at 1 minute post-glucose bolus; ND, valid S i value could not be determined Table 3 Body Mass Index Was Assessed in Mice Feeding on RC and HF Values are presented as mean ± SEM; n = 13 per group for WT; n = 7 per group for subsequent parameters * p < 0.05 compared to RC (two-tailed Student's t-test); ** p < 0.01 (two tailed Student's t-test) BMC, bone mineral content Glucose tolerance on an RC trended towards an intolerant phenotype at CT1 versus CT13, but this difference did not attain significance ( Figure 4 A). This is consistent with the temporal variation in insulin secretion observed in RC-fed WT mice in the FSIGT experiment ( Table 2 ). However, when the mice were fed HF for 2 mo, this glycaemic excursion at CT1 evoked by the environmental challenge was amplified and significant (two way analysis of variance [ANOVA]; F = 63.2, p < 0.001) ( Figure 4 A). Similarly, although the hypoglycaemic response to insulin was not different in mice fed regular chow at CT1 and CT13 ( Figure 4 B), the HF induced a significant temporal variation ( Figure 4 B). Thus, the impact of a high fat intake on carbohydrate metabolism in WTs includes an amplification of the diurnal variation in the response to both glucose and insulin. This coincides with a modest impairment in the ability to restore euglycaemia after insulin. A similar impairment resulting from a defect in gluconeogenesis has been observed in rats ( Oakes et al. 1997 ). The mutants failed to exhibit a significant time-dependent variation in their response to glucose or insulin, again reminiscent of the RC-fed, WT phenotype ( Figure 4 ). Figure 4 The Molecular Clock Conditions HF-Induced Circadian Variation in Glucose Homeostasis (A) Glucose tolerance (GT) in RC-fed WT mice (i), HF-fed WT mice (ii), and HF-fed Clock mut mice (iii). (B) IT in RC-fed WT mice (i), HF-fed WT mice (ii), and HF-fed Clock mut mice (iii) at respective times ( n = 6–8; * p < 0.05, † p < 0.01). Mice were also subjected to extended high-fat feeding (11 mo versus 2 mo). Long-term hyperlipidemia is known to induce frank diabetes with impaired release of insulin ( Johnson et al. 1990 ), in contrast to short-term, high-fat feeding, which increases release of insulin, but impairs the response to it ( Linn et al. 1999 ). The extended HF impaired insulin secretion, reflected by its marked reduction to negative values in HF-fed WT mice ( Table 2 ). The lack of insulin secretion resulted in calculated values of S i that were imperceptibly low (see Material and Methods). However, S g , insulin secretion, and S i were restored to a WT phenotype in Clock mut mice that were also HF-fed for 11 mo ( Table 2 ). This is, again, consistent with a role for the molecular clock in conditioning the response of glucose metabolism to the intake of dietary fat. Remarkably, mutation of the molecular clock protected against the development of frank diabetes caused by chronic high-fat feeding. Discussion Maintenance of blood glucose levels within a narrow range is critical to mammalian survival, and environmental cues can trigger appropriate tissue disposition of glucose through adaptive behaviors such as in hibernation ( Castex and Hoo-Paris 1987 ) or the “fight-or-flight” response ( Surwit et al. 1992 ). In this sense, glucose regulation is a fundamental and ancestral defence mechanism. Our studies suggest that Bmal1 and Clock, core components of the molecular clock, contribute substantially to regulation of recovery from the hypoglycaemic response to insulin. However, other mechanisms also impinge on this ancient adaptive response. Thus, impaired recovery from insulin-induced hypoglycaemia is observed in mice lacking proopiomelanocortin. These animals lack adrenal glands and melanocortins and exhibit a defective glucagon response to insulin-induced hypoglycaemia ( Hochgeschwender et al. 2003 ). They contrast with the Bmal1 −/− and Clock mut mice, where the counterregulatory hormone response is unimpaired. Thus, steroids, epinephrine, and glucagon appear to facilitate recovery from insulin-induced hypoglycaemia in a manner distinct from, but complementary to, the molecular clock. An assumption intrinsic to our studies is that the phenotypes revealed in the mutant mice are attributable to their function as core elements of the molecular clock. However, as trans-activators, both Clock and Bmal1 may have pleiotropic effects independent of the circadian clock that could impinge on metabolism. Several lines of evidence argue against this hypothesis. First, genes relevant to these metabolic phenotypes display circadian oscillations in their steady-state mRNA levels ( Young et al. 2001 ; Oishi et al. 2003 ). In addition, the mRNA levels of many of these key proteins are phase-aligned with Per1 (e.g., Enolase 3, Pgam, Transketolase, Lipase, Lpl, Dgat1, Ppar alpha ) or Per2 (e.g., Mod1, Lpl, Pepck, lipin 1 ) (unpublished data). In addition, many of their mRNAs are at lower levels in Bmal1 −/− (e.g., Mod1, Pepck, Enolase3, Pgam ) (unpublished data), consistent with a direct role of Bmal1 in their transcription. Thirdly, these metabolic parameters are disrupted in both circadian mutants with the same rank order of potency as the locomotor activity phenotypes (Bmal1 −/− > Clock mut ) . Thus, the most parsimonious interpretation is that the observed metabolic deficiencies in the Bmal1 −/− and Clock mut mice are due to their roles in the circadian clock, rather than to “off-clock” effects. We observed that the impact of HF on glucose homeostasis was apparently to emphasize the role of the molecular clock. Diet has previously been shown to interact with peripheral clocks. Changes in feeding shift the circadian pattern of gene expression in the liver, but not in the master clock in the SCN ( Damiola et al. 2000 ), demonstrating the importance of food as a cue to circadian control. Individual constituents of food could also provide discrete stimuli. For example, glucose alone can induce rhythmic gene expression in isolated fibroblasts ( Hirota et al. 2002 ). Thus, dietary composition, the size and timing of a feed might all be expected to interact differentially with an underlying circadian regulation of metabolic control. Alterations in dietary content, the availability of “fast food,” inactivity, and sociocultural factors have all been implicated in the emergence of the metabolic syndrome as a major challenge to the public health ( Zimmet et al. 2001 ). However, while mechanistic integration of the diverse elements of the syndrome has proven elusive, our studies suggest that timing may influence the functional consequences of ingesting a caloric load. Materials and Methods Animals Mice were acclimatized for 2 wk in 12 h light–12 h dark cycles before being subjected to a 36-h period of constant darkness followed by experimentation in darkness. Experimental chronology is measured in CT, subjective day beginning at 7 AM (CT0), and subjective night beginning at 7 PM (CT12). Diet WT and Clock mut mice were placed on an HF (Teklad, TD02435) and compared to age-matched WT mice on a regular chow diet (RC). Mice were on RC for 8 wk except for those subjected to FSIGT where they received RC for 11 mo. Body mass composition was measured by dual energy X-ray absorptiometry at 10 mo. Intraperitoneal tolerance Tests were performed as described ( Klaman et al. 2000 ) with a diminution in the glucose bolus (0.1 g/kg). Intravenous glucose tolerance test and minimal modeling The tolerance test was performed as described ( Pacini et al. 2001 ) in unanesthetized mice, and the minimal model of Bergman et al. (1979) was applied to the data using MINMOD software ( Boston et al. 2003 ). The derived values were S i , S g , and acute insulin response to glucose, which measures insulin secretion. S i is the ratio of insulin delivery rate to the interstitium to insulin extraction rate from the interstitium. Long-term feeding of HF to WT mice resulted in imperceptibly small insulin sensitivity values. This could be the consequence of impaired delivery of insulin to the interstitium, exacerbated extraction rate, or a combination of both factors. Insulin secretion is derived from area under the insulin curve, above basal, from 0 to 10 min after glucose infusion; and disposition index, which equals the product of insulin sensitivity multiplied by insulin secretion and measures the degree to which insulin sensitivity can be compensated for by elevated insulin secretion ( Pacini et al. 2001 ). Assay methods Insulin, leptin, corticosterone, and glucagon levels were measured by immunoassays from Crystalchem (Downers Grove, Illinois, United States), ICN Biochemicals (Costa Mesa, California, United States), and Linco Research (St. Charles, Missouri, United States). Plasma glucose was measured by the glucose oxidase method using a glucose analyzer machine for FSIGT and by glucometer for the intraperitoneal tolerance test. PEPCK activity was quantitated by a bioluminescent method ( Wimmer 1988 ). Statistical analysis The significance of differences amongst the tolerance test curves was assessed by distribution-free two-way ANOVA with a Bonferroni correction. FSIGT data were tested by one-way ANOVA with the Kruskal-Wallis test. Paired Student's t-tests were used to perform comparisons of corticosterone levels before and after insulin injection in Bmal −/− mice and between WT and Clock mut mice. Plasma samples for glucagon analysis were pooled and were thus not compared by a formal statistical analysis. Results are presented as mean ± standard error of the mean (SEM), except for the FSIGT data ( Table 2 ), presented as mean ± fractional standard deviation. Differences were considered significant when p < 0.05.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC524471.xml
524473	Sleeping, Waking, … and Glucose Homeostasis	null	We often think of ourselves as either a day person or a night person—one who rises with the sun, raring to go, or one who prefers to stay up through the night to get things done. Regardless, we each have our regular waking and sleeping cycles. It's been known for some time that variations in sleep and wakefulness are part of our circadian rhythm, or molecular clock. A portion of the brain called the hypothalamic suprachiasmatic nucleus (SCN) regulates this biorhythm. When this area of the hypothalamus is destroyed in animal models, the circadian rhythm is disrupted. Two transcription factors (proteins that regulate gene expression) called Bmal1 and Clock regulate aspects of circadian rhythm, possibly by regulating neurons in the SCN. Other aspects of human physiology are also regulated in a circadian manner. Besides altering sleep and wakefulness patterns, ablation of the SCN alters the ability to regulate sugar levels. Sugar (glucose) levels must be maintained within fairly narrow limits for survival. This regulation is controlled in part by a balance between blood sugar level and insulin production (insulin lowers the blood sugar level). In people and in mouse models, both glucose level and insulin level are subject to circadian rhythms. It isn't clear, however, if this is a behavioral effect, whereby the disruption of the SCN might alter our feeling of being well fed—that is, being sated—as eating has a profound effect on blood sugar levels. Metabolic clock regulation of glucose homeostasis Garret FitzGerald and colleagues tested the effect of the molecular clock genes in glucose regulation (homeostasis) by examining mice in which Clock and Bmal1 were impaired. In normal mice they observed a peak in glucose levels early in the day. This diurnal regulation was lost in the mutant mice. Furthermore, whereas the normal mice could fairly easily return their glucose levels to normal when they were artificially treated with insulin, this ability was severely impaired in the mutant mice. What's more, a high-fat diet amplified this circadian variation in the normal animals, but the rhythm was abolished in the mutants on a high-fat diet. Thus, the authors demonstrated that circadian control of blood glucose levels is due directly to the presence of these transcriptional factors rather than due to some other behavioral effect that ablation of the hypothalamus might have caused. It's possible, therefore, that besides what we eat, our internal circadian clock could also be an important regulator of blood sugar levels. What is still left to be explored is whether the change in glucose that results from disruption of the Clock and Bmal1 genes is due to the transcription factors' effect as circadian regulators or to an activity of these transcription factors that is unrelated to circadian rhythm generation. But the study does raise the possibility that when you eat may be as important to your health as what you are eating.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC524473.xml
535540	Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia I. Patterns of lagged weather effects reflect biological mechanisms	Background Malaria epidemics due to Plasmodium falciparum are reported frequently in the East African highlands with high case fatality rates. There have been formal attempts to predict epidemics by the use of climatic variables that are predictors of transmission potential. However, little consensus has emerged about the relative importance and predictive value of different factors. Understanding the reasons for variation is crucial to determining specific and important indicators for epidemic prediction. The impact of temperature on the duration of a mosquito's life cycle and the sporogonic phase of the parasite could explain the inconsistent findings. Methods Daily average number of cases was modeled using a robust Poisson regression with rainfall, minimum temperature and maximum temperatures as explanatory variables in a polynomial distributed lag model in 10 districts of Ethiopia. To improve reliability and generalizability within similar climatic conditions, we grouped the districts into two climatic zones, hot and cold. Results In cold districts, rainfall was associated with a delayed increase in malaria cases, while the association in the hot districts occurred at relatively shorter lags. In cold districts, minimum temperature was associated with malaria cases with a delayed effect. In hot districts, the effect of minimum temperature was non-significant at most lags, and much of its contribution was relatively immediate. Conclusions The interaction between climatic factors and their biological influence on mosquito and parasite life cycle is a key factor in the association between weather and malaria. These factors should be considered in the development of malaria early warning system.	Background Malaria epidemics due to Plasmodium falciparum are reported frequently in the East African highlands [ 1 - 6 ]. Immunity to malaria in the populations of these epidemic-prone regions is often incomplete, so that epidemics cause high case fatality rates among all age groups. In 1958, a malaria epidemic covering over 250,000 square kilometers resulted in an estimated three million cases and 150,000 deaths in Ethiopia [ 2 ]. Since then, large scale epidemics of malaria have been noted every five to eight years. Thus, there is an urgent need for the development of malaria early warning systems [ 7 - 9 ] to predict where and when malaria epidemics will occur, with adequate lead-time to target scarce resources for prevention activities. Unusual meteorological conditions, such as especially high rainfall or high temperature, are often cited retrospectively as the precipitating factors for epidemics [ 10 , 11 ]. There have also been formal attempts to predict epidemics by the use of local weather and/or global climatic variables that are predictors of vector abundance and, therefore, of transmission potential [ 12 - 20 ]. However, little consensus has emerged about the relative importance and predictive value of different factors [ 2 , 6 , 21 - 27 ]. Woube [ 27 ] showed that although one epidemic in Ethiopia was associated with higher rainfall, an epidemic in another year was preceded by very little rainfall. Lindsay et al. [ 23 ] found a reduction in malaria infection in the Usambara Mountains of Tanzania following 2.4 times more rainfall than normal, while excessive rainfall during the same period was associated with increased malaria in south-western highlands of Uganda [ 3 ]. Moreover, Mbogo et al. [ 24 ] found variation in the relationship between the mosquito population and rainfall in different districts of Kenya and attributed the variation to environmental heterogeneity. Similarly, Zhou et al. [ 28 ] showed that there was high spatial variation in the sensitivity of malaria outpatient numbers to climate fluctuations in East African highlands. Similarly, determination of the amount of lead time between weather factors and malaria cases is necessary to develop prediction models, but results from different studies have revealed a range of lead times [ 3 , 4 , 22 , 24 , 29 ]. Despite the varying results of these studies, there has not been critical examination of the sources of variation in the association and lag structure (the magnitude of association between weather and malaria at a later time) between weather and incidence of malaria. The inconsistency of findings from different studies may be due in part to the interaction of weather factors affecting vector abundance and survival, and parasite maturation, key determinants of malaria transmission. Deposition of mosquito eggs, and their maturation into larvae and then into adults, requires aquatic breeding sites, and is, therefore, dependent on rainfall [ 30 , 31 ]. The time required for mosquito maturation shortens as temperature increases [ 30 , 32 ]. At 16°C, larval development may take more than 45 days (reducing the number of mosquito generations and putting the larvae at increased risk of predators), compared to only 10 days at 30°C (Table 1 ). By affecting the duration of the aquatic stage of the mosquito life cycle, temperature determines the timing and abundance of mosquitoes following adequate rainfall. Table 1 The effect of mean temperature on the duration of mosquito's life cycle and sporogonic cycle and its effect on the amount of lead time from the availability of breeding sites to the occurrence of malaria cases. Weather factors Stages and duration of mosquito's life cycle and sporogony cycle affected by weather factors Mean temperature (Rainfall temperature) Availability of breeding sites ----------------→ Malaria Mosquito's life cycle* Sporogony† Incubation period in human host Larva ----→ Adult(days) Adult first bite ----→ Infectious bite (days) 16°C 47 111 (10–16 days) 17°C 37 56 18°C 31 28 20°C 23 19 22°C 18 7.9 30°C 10 5.8 35°C 7.9 4.8 39°C 6.7 4.8 40°C 6.5 4.8 * see references [32, 44]; †see references [35, 45] Once female adult mosquitoes emerge, they look for a blood meal, and in the process they ingest malaria parasites (gametocytes) with the blood. The feeding frequency of mosquitoes increases with temperature, resulting in increased proportions of infective mosquitoes [ 33 ]. The duration of the extrinsic phase of the parasite (sporogony cycle), which is the development of the ookinete, the egg of the parasite, in the midgut of the anopheline mosquito, depends on temperature. The sporogony cycle on average lasts about 10 days, but shortens as temperature increases [ 34 , 35 ], becoming as short as five days when the temperature exceeds 30°C (Table 1 ). These data on the timing of the mosquito life cycle suggest that malaria cases should follow, at defined intervals, periods of increased temperature and increased rainfall. Moreover, because temperature accelerates several steps in the process of mosquito and parasite development, the time lag between the appearance of suitable weather conditions and the appearance of new malaria cases should shorten as temperature rises. Although based largely on laboratory findings, these data suggest quantitative hypotheses about the precise time lag between increases in temperature and rainfall, and increases in malaria cases. At an average temperature of 20°C, the aquatic phase of the mosquito will be completed in about 28 days (five days for eggs to hatch and 23 days for the larva to develop into adult stage); and sporogony is completed in 28 days (Table 1 ). At this temperature, malaria cases should, therefore, appear 9–10 weeks following rainfall, assuming an average incubation period of about 10–16 days. Similarly, in this situation, the number of malaria cases should be positively related to increases in temperature three to seven weeks beforehand (during the aquatic and sporogony stages). When the mean temperature is higher (30°C), the aquatic stage of mosquito and the sporogony cycle are completed in about 12 and 8 days respectively (Table 1 ). In this relatively hot environment, malaria cases should appear 4–5 weeks following rainfall and the lag in the effect of temperature should also be shorter. The purpose of the investigations reported here is to test these hypotheses using weekly data on weather and malaria cases. Specifically, we used Polynomial Distributed Lag Models (PDL) to determine the effect of weather factors and their lag distribution on malaria in relatively hot and cold environments using a data set consisting of weekly parasitologically confirmed malaria cases collected from health facilities and locally collected meteorological factors in 10 districts of Ethiopia for the years 1990 to 2000. Methods Data Microscopically confirmed malaria cases were collected from a health facility in each of ten districts of Ethiopia over an average of 10 years. Each of these health facilities serve people living in the surrounding localities with few exceptions coming from other places. The data were extracted from records of outpatient consultations for the years 1990 through 2000. These data were compiled by residency (urban and rural) and Plasmodium species; the analysis was restricted to P. falciparum . The original data collected on the basis of Ethiopian weeks were normalized to obtain mean daily cases for each Ethiopian week [ 36 ]. Daily meteorological data (minimum and maximum temperature and rainfall) recorded at the local weather stations nearest to the health facility were obtained from the National Meteorological Services Agency (NMSA) for the same period. The assumption is that the meteorological data from the local weather stations represent the surrounding localities whose inhabitants are served by the respective health facilities. These daily data were collapsed into weekly data to correspond with the weekly malaria cases. The weekly mean for minimum and maximum temperature and the total weekly amount of rainfall were calculated from the daily records. Missing data The data set consists of records with missing values for some of the variables (4.4%, 10.2% and 9.9% for rainfall, minimum and maximum temperature respectively). Because of the multiple time lags considered in the analysis (see below), discarding estimates with a single missing value results in multiple records lost for each missing value. To avoid this substantial loss of data, missing values of the independent variables (weather variables) were interpolated by fitting a linear regression using the value from the previous week and a dummy variable for that week. A new variable was created with original values for non-missing data points and interpolated values for missing data points. Model The daily average number of cases (of the weekly microscopically confirmed malaria cases) was modeled using a robust Poisson regression (implemented in Splus), using weekly rainfall, minimum and maximum temperature as explanatory variables in a distributed lag model. The model was: where E ( Y st ) denotes the expected value for the daily average number of malaria cases at site s on week t ; , and R t - i are the weekly minimum and maximum temperature and the rainfall i weeks previously; α s and β s represent the intercept and coefficient for time trend ( t ), which are specific to the site under consideration. As described in the introduction, biological considerations suggest that the lag between rainfall and associated malaria cases will be different from that between temperature and associated cases. Therefore, lags of 4–12 weeks were considered for rainfall, and relatively shorter lags of 3–10 weeks for the minimum and maximum temperature. The assumption is that changes in temperature and rainfall at a particular time do not have an important influence after 10 and 12 weeks respectively. The overall effect of a unit increase in minimum temperature (for example) is the sum of the coefficients β i . A large number of variables (a total of 25; eight lags each for minimum and maximum temperatures and nine lags for rainfall) were introduced for the three weather factors in this model. The efficiency of the coefficient estimates may be affected due to the large number of parameters to be estimated and the possibility of multicollinearity between the lagged weather factors. When lag terms are put in the same model, correlation between measurements of weather on weeks close together will cause a high degree of collinearity that may result in unstable estimates. Polynomial Distributed Lag Model A polynomial distributed lag (PDL) model [ 37 ] imposes constraints on the coefficients β i , γ i , θ i , forcing each of them to take the form of a (separate) 4 th -degree polynomial in i. This reduces the number of degrees of freedom for each weather factor from the number of lags considered to five and circumvents some of the difficulties associated with estimation of coefficients for multiple lags, including instability of estimates due to collinearity of the different lags of the same variable. With this model the coefficients for lagged minimum temperature, for example, are assumed to take the form: where φ k is the parameters of the d-th degree (here d = 4) polynomial distributed lag. To estimate the parameters describing the polynomial lag φ k equation (2) was substituted into the unconstrained distributed lag model (1) to obtain a constrained polynomial distributed lag model: Grouping of districts The effects of weather factors on the number of malaria cases were distributed over multiple weeks and the separate analysis for each district (not shown) indicated heterogeneity in magnitude and direction of the effects of the weather factors. Districts with similar climatic characteristics were grouped, in order to reduce the effect of random error and to produce more reliable and precise estimates of weather effects. Moreover, this approach will produce more generalizable results within similar climatic conditions. Thus, the districts were grouped into hot (altitude < 1700 mm above sea level) and cold on the basis of altitude and temperature. The hot districts included Diredawa, Nazareth, Wolayita and Zeway; and the cold districts included Alaba, Awasa, Bahirdar, Debrezeit, Hosana and Jimma. Two separate PDL models were fitted to estimate the effects of different weather factors. A basic issue in epidemiological analysis is controlling for the effect of confounding factors. Malaria transmission is affected by different factors and shows a systematic variation over time. To control for other factors that may affect the long-term trend, a time variable was included in the model, which would remove the long-term wavelength patterns, leaving the deviations representing short fluctuations. Since the long-term trend and the numbers of weekly cases vary between districts, an interaction term between the time variable and district (dummy variable) was introduced. Urban areas may have other sources of breeding sites for mosquito not driven by rainfall. To examine the influence of these and other unmeasured factors that vary between urban and rural environments, separate models were fitted for urban and rural cases. Results The data set consists of microscopically confirmed P. falciparum cases from a health facility in each of 10 districts over an average of 10 years and meteorological data from local stations in each of the districts. Table 2 presents the descriptive analysis of cases, meteorological variables and altitude of each district. The daily averages treated by each of the 10 health facilities ranged from 11–39 malaria cases and over 300 cases during the peak transmission season. Minimum temperature was positively correlated with rainfall, significantly (rho = 0.37) in the cold districts and nonsignificantly (rho = 0.06) in the hot. Maximum temperature, however, was negatively correlated with rainfall, significantly (rho = -0.33) in the cold districts and nonsignificantly (rho = -0.033) in the hot. Table 2 Characteristics of the study districts (average daily malaria cases and meteorological variables) District Altitude Malaria cases Maxt Mint Rain Group (m) Mean Min Max (°C) (°C) (mm) Alaba 1750 39 0 163 27.4 11.7 19.6 cold Awasa 1750 11.3 0 17 27.4 12.6 19.3 cold Bahirdar 1770 22.1 1 83 27.2 13 25.2 cold Debrezeit 1900 25.2 1 147 26.5 12.1 16.5 cold Hosana 2200 19.4 0 96 22.4 10.7 23.4 cold Jima 1725 13.2 0 85 27.6 11.6 30 cold Diredawa 1260 25.3 0 330 31.8 19 13.8 hot Nazareth 1622 17.7 0 109 27.5 14.3 17.1 hot Wolayita 13.9 0 113 25.3 14.4 24.4 hot Zeway 1640 11.4 1 102 27.5 13.9 13.7 hot maxt-maximum temperature, mint-minimum temperature The effect of rainfall and temperature on daily average microscopically confirmed cases was estimated by lag in the 10 districts grouped into two climatic zones, hot and cold (Table 2 ). Figure 1a shows the estimates of the distributed lag between rainfall and cases in cold areas. Coefficients represent the multiplicative effect of one additional millimeter of rain at a given lag on the number of malaria cases at a site. Rainfall is significantly associated with the number of malaria cases in the cold districts. The magnitude and direction of the association varies with lags. At shorter lags of 4 and 5 weeks, rainfall is negatively and significantly associated with malaria cases. At lags of six, seven and eight, rainfall is not significantly associated with malaria cases. Lags of nine, 10, 11 and 12 are positively associated with malaria cases and the magnitude of effect increases almost linearly with maximum effect at lag 12. The conclusion is that rainfall in the cold districts is associated with a much delayed increased malaria cases and immediate decrease in malaria cases. Figure 1 Distributed lag structure for the association between 1 mm increase in rainfall, 1°C increase in minimum and maximum temperature and average daily malaria cases. (a) & (b) for rainfall, (c) & (d) for minimum temperature, and (e) & (f) for maximum temperature in the cold and hot districts respectively. The shaded areas represent 95% confidence intervals. Similarly, rainfall is significantly associated with malaria cases in the hot districts. Compared to the cold districts, a significant and positive effect of rainfall in the hot districts manifests at relatively shorter lags (six, seven, eight, nine and ten weeks) and remains positive afterwards but declines and becomes non-significant for the longer lags (Figure 1b ). Much of the contribution of rainfall to the increase in malaria cases in the hot districts occurs at relatively shorter lags (compared to its effect in cold districts) and wanes slowly with increasing lags. Thus, the results for rainfall agree qualitatively with biological expectations. Figure 1c shows the estimated distributed lag relationship between minimum temperature and malaria cases in the cold districts; coefficients represent the multiplicative effect of one degree Celsius increase in temperature at a given lag on the number of malaria cases at a site. Minimum temperature is positively associated with the number of malaria cases, with a significant increase extending from 7 to 10 weeks prior to cases and the size of the effect growing over that range. In the hot districts, by contrast, the effect of minimum temperature on malaria cases is more complicated. At short lags, its effect is small and non-significantly positive (Figure 1d ). A significant positive association at longer lags is also observed. In summary, minimum temperature contributed significantly to the estimated increase in malaria cases in the cold districts with a delayed effect. In the hot districts, while its effect is non-significant, much of the contribution is relatively immediate. Unexpectedly, the only significant contribution of minimum temperature in the hotter districts occurs at long lags. Figures 1e and 1f show the relationship between maximum temperature and malaria cases in the cold and hot district groups respectively. Maximum temperature is not significantly associated with the estimate of malaria cases in either group of districts. However, the trend of the estimates along the lags shows that at shorter lags of three, four and five weeks, maximum temperature is negatively associated with the number of malaria cases in hot districts, while it is positively associated at lags of six, seven and eight weeks in the cold districts. To test the linearity of the association between the weather factors and malaria cases, a three dimensional relationship between weather factors, lag and the magnitude of effect at each lag was explored (See Additional file 1 for the method and figure). In that figure, a positive effect of a factor at a given lag is seen as a positive slope of the surface cut at the given lag; the magnitude of that slope corresponds to the linear effect estimated by the PDL model. The effect of rainfall plateaus at higher rainfall levels; beyond a given quantity of rain, additional rain adds little to the malaria risk. Similarly, although the effect of minimum temperature in the cold districts is linear, it levels off at higher temperature (>16°C) in the hot districts. The results of analysis stratified by rural versus urban sites are shown in Figure 2 . The association between rainfall and cases varies by residency (a & b). Rainfall is significantly associated with cases originated from rural residents but not generally among urban residents, however, the magnitude of effect of rainfall looks similar in both rural and urban areas,. The effect of minimum temperature on malaria cases does not vary by residency (c & d). Figure 2 Distributed lag structure of the effects of rainfall and minimum temperature on average daily malaria cases by residency. (a) & (b) for rainfall in rural and urban respectively, (c) & (d) for minimum temperature in rural and urban respectively. The shaded areas represent 95% confidence intervals. Predicted case numbers for hot and cold districts were compared against actual values to assess how well the models predict the seasonal peaks and interannual variability. Plots of the actual data and predicted values showed that the models predicted the seasonal fluctuations very well (Figure 3 ). However, the models were not able to differentiate clearly between years with high and low peaks. Figure 3 Plot of observed number of cases and predicted cases from the polynomial distributed lag models of 4 districts. Discussion The development of malaria early warning systems [ 7 , 8 ] to predict where and when malaria epidemics will occur, in order to target scarce resources for prevention activities [ 9 , 38 ], has motivated many studies [ 13 - 15 , 18 , 19 ]. However, little consensus has emerged as to which factors should be used as indicators, because multiple studies have yielded differing results on the main determinants of increased malaria transmission [ 2 , 6 , 21 - 23 , 25 , 27 ] and the lead time prior to observable effects [ 3 , 4 , 22 , 24 , 29 ]. In this study a polynomial distributed lag model was used to assess the lag distribution of the effects of weather factors on Plasmodium falciparum malaria in relatively hot (Diredawa, Nazareth, Wolayita and Zeway) and cold (Alaba, Awasa, Bahirdar, Debrezeit, Hosana and Jimma) environments in Ethiopia. The findings are largely consistent with hypotheses based on the relationship between weather factors and mosquito and parasite development. Rainfall is associated with malaria cases in both hot and cold districts with a lagged effect, and as expected, this lag is shorter in hot districts. The effect of rainfall on malaria is linear with saturating effects at higher rainfall levels (See Additional file 1 for the method and figure). Interestingly, malaria in the urban areas is not associated with rainfall. Although the maximum temperature is not generally associated with malaria cases in either group of districts, the minimum temperature is significantly associated with malaria cases in the cold districts with delayed effect, and the lag for the minimum temperature is shorter than that for rainfall, reflecting the two factors' effects on different stages of the transmission cycle. The detection of a positive effect of the minimum temperature at long lags (9–10 weeks) in the warmer districts was not predicted by biological considerations. One of the most striking uncertainties in the literature on weather and malaria is the variability in the reported relationship between rainfall and malaria, with several studies showing the importance of rainfall as a precipitating factor for malaria transmission [ 3 , 4 , 10 , 11 , 29 ], while other studies show negative or neutral effects [ 21 , 23 , 26 , 27 ]. For rainfall to have a positive effect on malaria cases, the temperature must be warm enough to support mosquito and parasite development [ 39 ], and, as the data confirm, the effect of rainfall on cases becomes more immediate in warmer temperatures. This is consistent with the laboratory findings that a mosquito population peaks early at higher temperatures, while a mosquito population at low temperatures experiences slow, steady growth with a delayed peak [ 40 ]. Increases in rainfall may also fail to produce additional malaria cases if aquatic breeding sites are not limiting for mosquitoes; this mechanism is consistent with the observed saturating effect of rainfall in our data. Furthermore, malaria in the urban areas is not significantly associated with rainfall, which may have been one of the sources of inconsistent findings of such analysis. The weak association may be due to the presence of other sources of breeding sites that may persist during the dry season such as brick pits, puddles, blocked drains and cisterns [ 41 ]. Moreover, developmental activities, aggregation of migrant labor forces and overall population movement affect urban malaria. It is also interesting to note that the effect of rainfall in the cold districts is negative at shorter lags, which may be due to breeding sites being flushed away during the rainy season [ 23 ]. Another possible explanation for the negative effect could be that low temperature during the rainy season might suppress malaria transmission. Maximum temperature was lower during the rainy season (shown by negative correlation with rainfall), however, the effect of maximum temperature on malaria is non significant. Moreover, minimum temperature seems to be elevated during the rainy season (positive correlation). Although the effect of rainfall in the hot districts declines after longer lags (due to evaporation and drying up of breeding sites), making the main transmission season shorter, the overall effect of rainfall (sum of the lag coefficients) is bigger in the hot than cold districts. Taken together, the analyses suggest that temperature requirements, saturating effects of rainfall, and urban-rural differences in the effect of rain on malaria transmission are all plausible mechanisms that could explain the inconsistent relationship between excessive rainfall and malaria epidemics. The minimum temperature contributes significantly to the estimated increase in malaria cases with a delayed effect in the cold districts, but not in the hot districts. At lower temperatures, the larval and pupal stages of mosquitoes take longer to complete (for example, 47 days at 16°C) and a small increase in temperature substantially shortens the duration of these phases (to 37 days at 17°C). Similarly, the duration of the sporogony cycle will be short with increasing temperatures (Table 1 ). In addition, raised temperature increases the frequency of mosquito feeding and, hence, the probability of transmitting infection [ 33 ]. Although all such effects of minimum temperature increase malaria transmission in the cold districts, the effect will be seen after a lag. The effect of minimum temperature in the hot districts, on the other hand, is immediate but non-significant. These findings are consistent with reports that small increases in temperature will have a greater effect on malaria transmission in areas with relatively lower average temperatures than areas with higher temperatures [ 42 , 43 ]. The significant effect of minimum temperature at relatively long (9–10 week) lags is not explainable, to our knowledge, on biological grounds. The maximum temperature is not significantly associated with cases in either hot or cold districts. However, the negative (but non-significant) correlation between weekly malaria cases and maximum temperature at shorter lags seen in hot districts may be due to its inhibitory and lethal effect on the survival of the parasites in the mosquitoes [ 30 ]. The survival rate of Anopheles gambiae is also reduced at higher temperatures. Nonetheless, the maximum temperature is not very extreme even in the relatively hot districts, thus the negative effect is not significant. As with all observational studies of malaria incidence and weather, a limitation of this study is the likely presence of some confounding factors that may have influenced the number of malaria cases and may have been associated with weather. Existing interventions such as insecticide residual spraying and other methods are routinely applied and were not included in this analysis. The results would have been biased by such confounding factors if interventions were undertaken on the basis of weather, or if they were undertaken on the basis of incidence and their effect was differential depending on the weather. Another minor problem is with the assumption of a finite length for the delayed effect of the different weather factors. However, the lag length was chosen based on the inter-relationship between weather, mosquitoes and parasites (Table 1 ) and it was assumed that this is biologically plausible. Weather factors alone explain seasonal cycles but were not accurate in explaining the magnitude of unusually bad years (Figure 3 ). This study was a scientific not a predictive exercise and suggests that no other factor is required for explaining seasonal cycles. A good early warning system has not been created, but some principles have been suggested for one. The first principle is that the lag length from time of rain to the expectation of malaria cases varies with climatic zone (with a saturating effect at higher rainfall levels), and rainfall may not be a key factor in urban malaria transmission. Secondly, minimum temperature is only important in the cold climatic zones, but not in the hot. Finally, maximum temperature makes little difference in either climatic zone. These key points need to be considered in the development of an early warning system for malaria. Such an early warning system would also include autoregressive terms or other terms that could improve prediction, but would have complicated the interpretation of coefficients in a model of the sort used, which was designed to detect the effects of weather factors on cases, rather than to predict case numbers. Such an early warning system is now being evaluated. Conclusions The findings are largely consistent with hypotheses, based on experimental data on mosquito and parasite development, about the interactions of climatic factors in determining the strength and lag structure of weather effects on falciparum malaria incidence. In the examined Ethiopian districts, weather-based predictors of malaria incidence are more useful in rural than in urban settings. These key points should be considered in the development of an early warning system for malaria. Authors' contributions HDT and ML conceived the study, undertook statistical analysis and drafted the manuscript. AT initiated the study and made data available in collaboration with WHO and Ministry of Health of Ethiopia. JS made major contributions to the study design and statistical analysis. All authors contributed to the writing of the manuscript and approved the submitted version of the manuscript. Supplementary Material Additional File 1 Three dimensional relationships between weather, lags and magnitude of effect at each lag Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC535540.xml
509287	Cancer immunotherapy: avoiding the road to perdition	The hypothesis that human cancers express antigens that can be specifically targeted by cell mediated immunity has become a scientifically justifiable rationale for the design and clinical testing of novel tumor-associated antigens (TAA). Although a number of TAA have been recognized and it has been suggested that they could be useful in the immunological treatment of cancer, the complexity of human beings leads us to reflect on the need to establish new criteria for validating their real applicability. Herein, we show a system level-based approach that includes morphological and molecular techniques, which is specifically required to improve the capacity to produce desired results and to allow cancer immunotherapy to re-emerge from the mist in which it is currently shrouded.	Introduction Although considerable advances have been made in terms of our molecular and cellular knowledge, for most human disease states a fundamental understanding of causal disease onset, disease mechanism and progression, and optimal treatment is still significantly limited. In part, this advancement has been hampered by our inability to fully and rapidly delineate complex cellular metabolic processes and molecular pathways. Organisms are complex self-organizing entities made up of such parts: organs, tissues, cells, organelles and ultimately molecules and atoms. One question that arises, concerns the relationship between the whole and its component parts. The issue at stake is sometimes called "the question of reduction" or "the problem of reductionism" [ 1 ]. The inefficacy of contemporary science to describe biological systems, consisting of non-identical parts that have different and non-local interactions has tended to limit progress in the human healthcare. Many biological systems remain incomprehensible because their multifarious nature has been combined with a reductionist approach based on the linear conception of cause and effect . The use, however, of a more holistic multidimensional system level-based approach may provide new insights into the understanding of disease processes and mechanisms of action of therapeutical agents [ 2 ]. Herein we aim to introduce a system level-based approach that includes morphological and molecular techniques for validating the appropriateness of using novel tumor-associated antigens (TAA) for clinical purposes. This approach might be easily implemented for identifying prognostic, diagnostic and alternative biomarkers. Finally, this type of analysis of appropriately designed cohorts might also provide a key to understanding the differences in patients who do or do not respond to any particular therapy. This information may be helpful for a more effective (and therefore more cost-effective ) design of clinical trials [ 2 ]. Immunotherapy and the human complexity The recognition and characterization of novel TAA is fundamental to the advance of cancer immunotherapy. The original hypothesis of Boon [ 3 ] and Rosenberg [ 4 ] that human cancers express antigens that can be specifically targeted by cell mediated immunity has become a scientifically justifiable rationale for the design and clinical testing of novel TAA based immunotherapies and therapeutic vaccines [ 5 - 7 ]. However, although a number of TAA have been discovered and it has been suggested that they could be useful in the immunological treatment of cancer, the complexity of human beings leads us to reflect on the need to establish compelling new criteria for validating their real applicability. Biological complexity can be intuitively appreciated – at least in terms of morphological or behavioral complexity, or the variety of cell types in an organism – but the term itself is notoriously difficult to define [ 8 ]. Human beings are complex hierarchical system s consisting of a number of levels of anatomical organization (genes, cells, tissues, organs, apparatuses, and organism) that interrelate differently with each other to form networks of growing complexity. The concept of anatomical entities as hierarchy of graduated forms, and the increasing number of known structural variables, have highlighted new properties of organized biological matter and raised a series of intriguing questions. In order to understand biology at the system level , we need to examine the structure and dynamics of the functions of organisms rather than the characteristics of their constitutive isolated parts [ 8 - 13 ]. The expression of TAA in biological materials has mainly been studied at the level of gene expression and gene level measurement by Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) analysis and the Quantitative real-time PCR (qrt-PCR) technology [ 14 - 17 ]. However, the information provided by these approaches is limited by the fact that the phenomena observed at each level of anatomical organization have properties that do not exist at a lower or higher level: RT-PCR and qrt-PCR may offer a satisfactory qualitative/quantitative description of small-scale structures , but this is likely to be irrelevant when it comes to large-scale features . The above considerations, in conjunction with the complexity of tumor-host interactions within the tumor microenvironment caused by temporal changes in tumor phenotypes and an array of immune mediators expressed in the tumor microenvironment [ 18 ] might clarify the limited reliability and applicability of current immunotherapeutic approaches. Here, we suggest a system level-based approach (Figure 1 ) for validating the appropriateness of using TAA for clinical purposes, which includes the following never defined before key points: Figure 1 System level-based approach for validating candidate TAA for clinical application. Aside from the well defined experimental procedure, the method presented here is based on the complex hierarchical nature of the human beings. The analysis begins at level of gene expression and then continues to higher levels of anatomical organization, (cell, tissue, organ, apparatuses and organism). This approach includes both morphological and molecular techniques. It also introduces the concept of dynamics of TAA expression at the level of the cell cycle , the physiological status of the organism and the process of aging . • Discriminating the cell types expressing the candidate antigen on the basis of the morphological visualization of all of the parts making up the organ under investigation. • Discriminating the candidate antigen's sub-cellular localization (at the level of cell nucleus , cytoplasm and/or plasma membrane ) by ultra-structural morphological visualizations. • Mapping candidate antigen expression in all of the organs making up the apparatuses . • Mapping candidate antigen expression in all of the apparatuses making up the living organism . • Estimating the percentage of normal cells and their neoplastic counterparts expressing the candidate antigen. • Evaluating the dynamics of candidate antigen expression at the level of the cell cycle , the physiological status of the organism ( i.e. the woman's menstrual cycle) and the process of aging . In order to advance our knowledge in a currently widely debated field of investigation, a clearer distinction must be made between in vitro laboratory results (the discovery and validation of target antigens) and their in vivo application ( in vivo validation), and it is necessary to adopt a more complete experimental approach that forcefully includes both morphological and molecular techniques [ 19 ]. Conclusions Translational science which is aimed to test, in humans, novel therapeutic strategies developed through experimentation [ 20 ] should begin to consider the role of emergence in other words the appearance of unexpected structures and/or the occurrence of surprising behaviors in large systems composed from microscopic parts, whether physical or biological. By unexpected and surprising we mean structures and behaviors which are not intuitive and are not simply predictable . Since our understanding of complex human disease such as cancer, is still limited and pre-clinical models have shown a discouraging propensity [ 2 , 6 ] to fail when applied to humans, a new way of thinking is strongly needed that unites physicians, biologists, mathematicians and epidemiologists, in order to develop a better theoretical framework of tumor development, progression and tumor-host interactions. Although the model presented here is based on a multidisciplinary system-level approach probably within the reach of only very large and multi-talented laboratories, it is aimed to introduce a different way of investigating human cancer, which takes into account the complexity of the human being as a system. The use of a holistic approach, which enables a more accurate selection of immunotherapeutic target antigens in the first phase of the experimental research, will reduce the notable fragmentation of the biological information in the post-genomic era, and will facilitate a more accurate transfer of the acquired knowledge to the bedside. Further, this new multidisciplinary approach is specifically required to improve the capacity to produce desired results with a minimum expenditure of energy , time , or resources for immunotherapeutic treatments and to allow cancer immunotherapy to re-emerge from the mist in which it is currently shrouded.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC509287.xml
535554	The Molecular Pages of the mesotelencephalic dopamine consortium (DopaNet)	Background DopaNet is a Systems Biology initiative that aims to investigate precisely and quantitatively all the aspects of neurotransmission in a specific neuronal system, the mesotelencephalic dopamine system. The project should lead to large-scale models of molecular and cellular processes involved in neuronal signaling. A prerequisite is the proper storage of knowledge coming from the literature. Methods DopaNet Molecular Pages are highly structured descriptions of quantitative parameters related to a specific molecular complex involved in neuronal signal processing. A Molecular Page is built by maintainers who are experts in the field, and responsible for the quality of the page content. Each piece of data is identified by a specific ontology code, annotated (method of acquisition, species, etc.) and linked to the relevant bibliography. The Molecular Pages are stored as XML files, and processed through the DopaNet Web Service, which provides functionalities to edit the Molecular Pages, to cross-link the Pages and generate the public display, and to search them. Conclusions DopaNet Molecular Pages are one of the core resources of the DopaNet project but should be of widespread utility in the field of Systems Neurobiology.	Background Although the use of Systems Biology to understand the function of neurons recently started to gain momentum, it is still in its infancy. A crucial step leading to meaningful simulations is the reconstruction of large neuronal systems based on the elementary building blocks. However, this approach suffers from the lack of truly quantitative values. Some projects of functional genomics have been recently launched to try to remedy the problem, e.g. the Genes to Cognition consortium ([ 1 , 2 ]). Another problem impairing the integration process resides in the large diversity of protocols and model systems used to gather the data. Since a large proportion of the data is potentially shared by numerous different systems, it is sensible to focus the effort on a restricted and well delineated system. This approach has been pioneered by the Alliance for Cellular Signaling , launched by Alfred Gilman ([ 3 , 4 ]), which originally focused on the B-lymphocyte and the cardiac myocyte. DopaNet Similarly, we started at the end of 2001 the mesotelencephalic dopamine consortium (DopaNet, [ 5 ]). The initiative aims to investigate precisely and quantitatively all the aspects of neurotransmission – at the levels of the molecule, the supra-molecular assembly, the neuronal cell and the neuronal network – in a specific neuronal system involved in many neuropathologies, such as Parkinson's disease, schizophrenia and drug addiction [ 6 - 8 ]. The resulting integrated knowledge will not only provide relevant, up-to-date information about such pathologies, but will also form a firm substrate to link the function of the neurobiological structures and the implementation of cognitive and mental abilities. As of June 2004, 35 European teams from 8 countries are part of the project. DopaNet became a network of the European Science Foundation (ESF) in January 2003. A first step, prior to the design of large-scale dedicated experiments, consists in data mining the current literature in molecular and cellular neurobiology for existing quantitative knowledge. The resulting data has to be properly stored and annotated. DopaNet Molecular Pages A DopaNet Molecular Page is a collection of annotated numerical data relative to a "molecular complex" present in one or several DopaNet target cells. The "molecular complex" is taken here in the sense of the DopaNet Neuronal Ontology (see below), as a "stable assembly of molecules", a "molecule" being described as a "set of atoms linked together by covalent bounds". As a consequence, we can have a Molecular Page storing data relative to a molecular complex made up of components, that are themselves described in other Molecular Pages. An anticipated example is an heterotrimeric G protein and its α and βγ subunits. The information collected deals with the structure of the complex, its anatomical distribution within DopaNet target cells, and its functional properties. Each page is under the responsibility of its maintainer(s), who decide which data is to be included or not, and acknowledge the input of the various contributors. All the data included in a Molecular Page is annotated (Species, Methods, variability etc.), and linked to bibliographic references. In addition, each single data stored in the databases of DopaNet is attached to one or several terms of the DopaNet Neuronal Ontology. This ontology will therefore act as a glue, relating the various pieces of data one to the other. DopaNet Neuronal Ontology An ontology is defined here in its information science meaning, as a hierarchical structuring of knowledge. In our case, it is a relational vocabulary, that is a set of terms linked together, aiming to describe a neuron. Each term has a definition and a unique identifier. Terms are related by "is a" inheritances, which represent sub-classing, and "part of" inheritances which represent deepening knowledge. For instance, the nicotinic receptor subunit alpha6 "is a" nicotinic receptor subunit, and is "part of" the (alpha6) 2 (beta2) 3 nAChR. Each term can be the child of several others. Therefore the complete picture is not a genealogical tree, but rather a network or relationships. There are several biological ontologies, the most famous (and complete) being Gene Ontology ([ 9 , 10 ]). Numerous other projects can be found at repository of the Open Biological Ontologies ([ 11 ]). See the discussion below for the relation between Gene Ontology and DopaNet Neuronal Ontology. In DopaNet Neuronal Ontology, a "molecular complex" is defined as a "stable assembly of molecules". An obvious example of a molecular complex is a protein. A molecular complex contains one or several components. Those components are all "molecule", a molecule being defined as a "set of atoms linked together by covalent bounds". For instance, "(alpha4)_2(beta2)_3 nAChR" is a "nicotinic acetylcholine-gated receptor". It is made up of two components: "alpha4 nicotinic receptor subunit" and "beta2 nicotinic receptor subunit", that are present in the "molecule" subtree as "nicotinic receptor subunit". The "polypeptide" subtree of "molecule" is built following the sequence resemblances, and then the 3D structure, similarly to the Structural Classification Of Protein database ([ 12 , 13 ]) and InterPro ([ 14 , 15 ]). Contrary to the "molecular complex" branch, the "molecule" branch should not contain any group based on the function. Construction and content Molecular page structure A Molecular Page is made up of a header followed by several lists, each list containing a sequence of identical elements. There are currently twelve main lists, described below. Several other lists of items are used to described the page data at a finer level. According to the molecular complex described in the page, some of the lists can be empty. The Molecular Page header contains the name of the molecular complex described in the page, an abbreviation, the unique ontology code used to identify the page, the dates of creation and last modification of the page, and the page status. The possible status are: stable The Molecular Page has been submitted by the maintainers and is ready for public release. unstable A new version of the Molecular Page, not yet ready for public release. forthcoming A new Molecular Page in construction, that has never been submitted for public release. For instance, the nicotinic acetylcholine receptor ( α 4) 2 ( β 2) 3 is described in the Page describing the complex "(alpha4)_2(beta2)_3 nAChR" . The related Ontology term can be found at <molecularPage DopaNetontology="DA:0000027" abbreviation="nAChRa4_2b2_3" creation="2003-01-05T00:00:00" modification="2004-09-02T15:49:41" name="(alpha4)_2(beta2)_3 nAChR" status="stable"> The main lists that compose a Molecular Page are: List of maintainers Maintainers are the only people authorized to directly modify the Molecular Pages. They are responsible for the quality and the completeness of the data included in the Page. However, maintainers are not assumed to systematically gather the information all by themselves. They are encouraged to contact experts to help them. Helpful people should be acknowledged as contributors. List of contributors Contributors are all the people who bring new information about a Molecular Page, or correct an existing piece of information. Contributors can be seen as the equivalent of authors of an article. Except maintainers (who are contributors by definition), they cannot directly modify a Molecular Page. They have to contact a maintainer instead. Note that the database administration team can directly modify the Molecular Pages to comply with the guidelines. List of components A Molecular Page describes a molecular complex. This complex is made up of components (at least one). The listOfComponents describes those components, their stoichiometry, and lists useful related resources. Each component is annotated by its ontology code. The complex "(alpha4)_2(beta2)_3 nAChR" [DA:0000027] is made up of two components, the subunit α 4 and the subunit β 2. <listOfComponents> <component DopaNetontology="DA:0000188" name="alpha4 nicotinic receptor subunit" stoichiometry="2"> <listOfResources> <resource identifier="ACHa4hosa" name="Ligand-Gated Ion Channel database" references="1" url=" "> <taxon>Homo sapiens</taxon> </resource> </listOfResources> </component> </listOfComponents> List of states The function of a molecular complex is most often modulated by permutations between various states (conformational transitions, covalent modifications etc.). Accordingly, most of the quantitative data are actually relevant only for one state or a subset of states. Those states should therefore be listed, described and annotated. The quantitative data described in the "functional" lists (see below) will refer both to the states of the molecular complex itself, listed here, and the list of states of other relevant Molecular Pages. The complex "(alpha4)_2(beta2)_3 nAChR" may exist under (at least) three different states: "basal", "active", and "desensitized". <listOfStates> <state identifier="basal" name="basal"> <description> In the basal state, the ionic pore is closed. This state displays a weak affinity for agonists such as acetylcholine or nicotine. </description> </state> </listOfStates> List of generic properties A list of properties that depends solely on the molecular complex itself, and not on its relationships with other entities, such as ligands or substrates. Example of such properties are molecular weight or Stoke radius. <listOfGenericProperties> <property name="MW" stateMolecule="basal"> <taxon>Homo sapiens</taxon> <listOfValues> <value mean="310971" unit="Dalton"> <comment>without covalent modifications.</comment > </value> </listOfValues> </property> </listOfGenericProperties> List of cells The distribution of the molecular complex and its components is described within the relevant DopaNet target cells: cortical glutamatergic pyramidal neuron, mesencephalic dopaminergic neuron, striatal cholinergic interneuron, striatal enkephalinergic/GABAergic medium spiny neuron, striatal substance p/GABAergic medium spiny neuron. It is likely that a listOfExtracellular shall be necessary at some point. Each cell is divided into compartments, where the distribution of transcripts and molecules can be described. The approach used to explore the distribution is specified, since both the accuracy and the quantitativeness of the observations strongly depends on the method chosen. As for all the following data, the species where the study has been conducted is also mandatory. One entry in the complex "(alpha4)_2(beta2)_3 nAChR" is the fact that in the cell soma of the rat mesencephalic dopaminergic neuron, single cell RT-PCR experiments showed that α 4 is present in 100% of neurons and β 2 is probably also present in 100% of neurons. <listOfCells> <cell cellName="mesencephalic dopaminergic neuron" DopaNetontology=" DA:0000702"> <listOfCompartments> <compartment DopaNetontology="DA:0000137" name="cell soma"> <listOfTranscripts> <transcript method="single cell RT-PCR" references="17"> <taxon>Rattus norvegicus</taxon> <description> a4 is present in 100% of neurons. b2 is probably also present in 100% of neurons . </description> </transcript> </listOfTranscripts> </compartment> </listOfCompartments> </cell> </listOfCells> List of ligands The ligands of a molecular complex are molecules or ions that bind to it. The size of the ligand relative to the molecular complex is irrelevant. Within the Molecular Page of "transforming growth factor receptor type I", one ligand is "transforming growth factor betal". Conversely, in the Molecular Page of "transforming growth factor beta1", one ligand is "transforming growth factor receptor type I"! See table 1 for an example of receptor-ligand reversion. The endogenous ligands are identified by their ontology code. Functional parameters such as k on , k off or K m can be stored in a controlled manner, in order to be easily retrieved later. Whenever possible, the quantitative values are related to the states of the molecular complexes involved, not only the state of the molecular complex subject of the Molecular Page but also the state of the ligand. This remark holds for the substrates, the translocators and the modulated substances as well (see below). See table 1 for an illustration of the use of state references. The desensitized "(alpha4)_2(beta2)_3 nAChR" of the rat binds acetylcholine with a Ki versus the epibatidine of 8.6 ± 1.98 nM. <listOfLigands> <ligand DopaNetontology="DA:0000184" name="acetylcholine" origin="endogenous"> <listOfProperties> <property name="Ki_epibatidine" references="10 18" stateMolecule="desensitized"> <taxon>Rattus norvegicus</taxon> <listOfValues> <value mean="8.6" sd="1.98" unit="nanomole per litre"/> </listOfValues> </property> </listOfProperties> </ligand> </listOfLigands> List of substrates All substances modified as a result of an interaction with the molecular complex. The parameters stored here are for instance K m , k cat or V max . List of translocators The translocators are substances that go from one subcellular compartment to another, the translocation being mediated by the molecular complex. Typical parameters are conductance or relative permeability. The active complex "(alpha4)_2(beta2)_3 nAChR" of the rat translocates cations with a conductance of 13.3 ± 1.5 pS. <listOfTranslocators> <translocator DopaNetontology="DA:0000264" name="cation" origin="endogenous"> <listOfProperties> <property name="conductance" references="14" stateMolecule="active"> <taxon>Rattus norvegicus</taxon> <listOfValues> <value mean="13.3" sd="1.5" unit="picosiemens"/> </listOfValues> </property> </listOfProperties> </translocator> </listOfTranslocators> List of modulated In many case, one knows about the effect of a molecular complex on a substance, without knowing the detailed mechanism of action. The modulated entries are to be avoided as much as possible, since they generally reflect a set of binding and/or enzymatic events. List of transitions Possible conversions between the states described in the listOfStates, such as a conformational transition, or a covalent modification. The complex "(alpha4)_2(beta2)_3 nAChR" undergoes conformational transitions between the basal and active states. <listOfTransitions> <transition state 1="basal" state2="active"> <comment> In the absence of ligand, the equilibrium is strongly displaced toward the basal state. Agonists, such as acetylcholine and nicotine, stabilise the active state and shift the equilibrium. The transition from basal to active corresponds to an opening of the ionic pore. </comment> </transition> </listOfTransitions> List of bibitems The list of bibliographic resources used to gather and annotate the data. Each piece of data included in the Molecular Page should be linked to those bibliographic items by internal references. Molecule Page storage Molecular Pages are saved as XML files [ 16 ], and their structure is described by an XML schema [ 17 ] available at Molecular Pages XML files are stored within two different repositories, depending on the status of the Page. One repository contains only the stable Pages ready for public release (22 pages as of October 21, 2004), while the other repository contains also the unstable and the forthcoming Pages (39 pages as of October 21, 2004). In addition to the two XML repositories, there is also a third HTML repository, containing the human-readable HTML versions of the stable Pages, automatically generated from their XML counterparts using XSL Transformations [ 18 ] with the Xalan processor [ 19 ]. Based on the identifier attributes, this processing generates the links within the Molecular Pages, but also between different, although related, Molecular Pages. Processing As described above, Molecular Pages are continuously modified and updated by the maintainers, with the help of the contributors. In order to automatize, safe-guard and simplify as much as possible the work required by a maintainer to create and edit a Molecular Page, an application called the DopaNet Web Service has been designed and implemented, which provide functionalities to: 1. authenticate Page maintainers 2. browse pages by maintainers 3. grant exclusive Page editing rights to a maintainer 4. create and edit a Page via a rich user interface 5. save or submit the edited Page, setting the "stable/unstable" status The DopaNet Web Service is made of both server-side and client-side components, all written in Java, and communicating via either the SOAP [ 20 ] or the HTTP protocol. The server is deployed into an Apache Tomcat server [ 21 ], while the clients are both a Java Applet and a collection of dynamic (Java Server Pages) and static (HTML) pages. The Applet provides a very rich interface to edit a Molecular Page, but due to the Applet technology limitations (security sandbox, download time, etc.), a form-based HTML Page editor is current under development. Most of the Applet and the HTML editor components are derived directly from the DopaNet Molecular Page XML schema, using a mapping between XML schema types and Java GUI or HTML form widgets. Both server- and client-side, Molecular Page XML data is handled using Apache tools such as the Xerces parser [ 22 ] and the Xalan processor. In addition to support the remote creation and editing of Molecular Pages, the DopaNet Web Service provide also functionalities to: 1. register new DopaNet contributors 2. update existing DopaNet contributor information 3. browse Molecular Pages by status 4. search Molecular Pages Searching of Molecular Pages is implemented by using the API provided by the Apache Xindice [ 23 ] native XML database, which has proved to be adequate in terms of speed for the amount of data we currently have in DopaNet. Utility and discussion Although in their early stage of development, DopaNet Molecular Pages provide a unique source of structured, annotated quantitative data about the molecules involved in neuronal signaling. They will feed both the experimental biologist and the theoretician with the best available estimates for all kind of knowledge, whether biochemical, anatomical or functional. This will allow them to design better experiments or formal models, and to benchmark their results. As a side-effect triggered by the mandatory annotations, DopaNet Molecular Pages will also a bibliographic resource, each page being the equivalent of a small review of the literature. DopaNet Neuronal Ontology Gene Ontology is now a fully grown project, and is being widely used in several biological domains. Nevertheless, in its present form, Gene Ontology was not found suitable to be directly used by the DopaNet project. We hope to collaborate with Gene Ontology maintainers in the future. In particular, effort will be made to complete Gene Ontology in the area of Neurobiology. However, DopaNet Neuronal Ontology will never actually be a subset of Gene Ontology. Indeed, the purpose of the latter is to classify the gene products – and one of its most useful application so far has been the annotation of sequence database entries. The purpose of DopaNet Ontology is broader in term of knowledge, and not limited to the classification of gene products. At the same time it is focused onto a specific system, and therefore of interest for a narrower audience. The Gene Ontology consortium defined three different vocabularies molecular function , biological process , and cellular component . Only the latter is at the moment relevant to DopaNet purposes, that is the Molecular Pages. However, it is anticipated that the biological process vocabulary will be needed in the near future, for instance to annotate electrophysiological data. DopaNet cellular component vocabulary is larger than Gene Ontology one, since it contains the different kinds of neuronal cells (see the Cell Type ontology [ 24 ]) In addition, one can foresee the need of other types of vocabularies to handle more integrated information such as mutant phenotypes, for instance Molecular function or vocabularies dealing with behaviors (other efforts have already started in that direction, see for instance the Mammalian Phenotype Ontology , ([ 25 ]). A cellular component may be for instance an anatomical structure, e.g. "dendrite" or "synaptic vesicle" but also a cell or a protein. Note that a "molecule" is defined in the Neuronal Ontology as a set of atoms covalently linked. A molecule cannot contains other molecules. Hence, a protein made up of several subunits, or a polypeptide and a co-enzyme are not "molecules", but "molecular complexes". Although our ontology is built for DopaNet purposes, it can be viewed as a more general "Neuronal Ontology". Therefore, we incorporate terms related to components present (or events taking place) in any neuron, not necessarily DopaNet target cells. In particular, such additions are advised if they clarify some hierarchical relationship. As described above, a "molecular complex" in DopaNet Neuronal Ontology contains one or several components, also present in the "molecule" branch. It could be considered redundant that all monomeric proteins are represented by two terms, as a "molecule" part of a "molecular complex". However, the meanings of the two branches are different. The "molecule" can be seen as an ideal entity, while the latter would rather represent an actual physical object of the cell. Moreover, the hierarchical structures of the two branches are different. In addition, a lot of proteins have only recently been discovered as functional complexes (e.g. the polymeric G-protein coupled receptors), and more are to be discovered. Finally, the systematic dissociation between the functional molecular complex and its components is handy when it comes to write the Molecular Pages. Molecular Pages The Alliance for Cellular Signaling was a pioneer in designing Molecule Page. Contrary to DopaNet Molecular Pages, their focus is truly a "molecule" rather than a "molecular complex". For instance, an heteropolymeric receptor will not be represented by a Molecule Page, but rather by a collection of Pages, one per subunit. DopaNet Molecular Pages are highly structured. While this could appear as an obvious choice, it actually comes with a double burden. First, the edition interface has to be sufficiently complex to reflect the underlying structure. This complexity certainly acts as a repellent for the biologist who wish to build a Molecular Page. Second, the high quality required, in particular concerning the annotations, leads to the rejection of a significant portion of the published knowledge. However, we think that a piece of data that cannot be properly annotated is of limited use for the community. For instance, a large amount of pharmacological properties is published without the species. Since those properties vary from one species to the other, one cannot easily re-use the value provided. Similarly, a numerical piece of knowledge cannot be used without caution if one does not know the method used to collect it, and the variability attached to it. Currently, the access to the data is only possible through the web interface. Moreover, although the user is able to search the content of the Molecular Pages using various criteria, the result is always presented as one or several Molecular Pages. However, the DopaNet Web Service should be enriched on a steady pace, and specific pieces of data should be served soon. One can envision interfaces providing precise and meaningful responses to queries like "All Kd for the ligand X of all molecules that bind it", under the form of a list of K d In addition, pieces of quantitative knowledge, like binding or enzymatic reactions, should be provided in standardized format such as the Systems Biology Markup Language [ 26 ]. The Molecular Pages are maintained in a distributed fashion, with one or several experts in charge of each complex. Such an approach is mandatory for two reasons. Firstly, the knowledge accumulated by the project will soon become much too large to be handled by one individual, or even one team. Secondly, the level of detail and accuracy sought by the resource is such that only experts can fruitfully mine the adequate literature for relevant information. To extract the simple affinity of a receptor for a ligand can be a daunting prospect. Not only that affinity can be expressed by various parameters with different meaning, K a , K d , K i , K p , IC 50 , but all those quantities can only be analyzed in regards of the knowledge about the various states of the complex, and its conformational transitions. The distributed annotation can cause concerns related to peer-validation and quality control. With the help of Nature Publishing Group, a peer review process has been set-up by the Alliance for Cellular Signaling to survey the edition of its Molecule Pages. Such an infrastructure is currently out of reach of DopaNet. However, we ensure that the maintainers are always recognized experts in the fields, or, for members of the EBI group, work in close relation. In addition, we included as much as possible guidance through the constraints imposed by the Page editing environment. That way, any Molecular Page complies with at least a minimal set of quality rules. Such an approach has already been successful in other areas. One of the most striking example is the Debian operating system project ([ 27 ]), that maintains around 9000 software packages for 11 computer architectures, with the help of about 1000 developers. The project has been running since 1993, and it is recognized as one of the most robust operating systems. On the contrary of the Molecular Pages, the Neuronal Ontology is currently developed only by the EBI team. Everyone can contribute by sending their suggestions, but for the sake of coherence the final building is centralized. Conclusions DopaNet Molecular Pages allow to store annotated numerical data about molecular complexes involved in neuronal signaling. Although the Pages are one of the core resources of the DopaNet project, and therefore their focus on the mesotelencephalic dopamine system, the repository should be of widespread utility in the field of Systems Neurobiology. This is also the case of The DopaNet Neuronal Ontology. The resource is in its early stage of development and will benefit much from the feedback of users. Availability and requirements All data contained in the DopaNet Molecular Pages may be copied and redistributed freely, under terms derived from the MIT license [ 28 ]. More information about the DopaNet project can be found at the URL . DopaNet ontology is available at the URL DopaNet Molecular Pages are available at the URL Authors' contributions NLN designed the database DTDs and schemas, wrote the XSL and acted as the final editorial authority on Molecule Pages. MD implemented all the edition and validation software, as well as the user interface, including the servers.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC535554.xml
524498	Feasibility of rapid and automated importation of 3D echocardiographic left ventricular (LV) geometry into a finite element (FEM) analysis model	Background Finite element method (FEM) analysis for intraoperative modeling of the left ventricle (LV) is presently not possible. Since 3D structural data of the LV is now obtainable using standard transesophageal echocardiography (TEE) devices intraoperatively, the present study describes a method to transfer this data into a commercially available FEM analysis system: ABAQUS © . Methods In this prospective study TomTec LV Analysis TEE © Software was used for semi-automatic endocardial border detection, reconstruction, and volume-rendering of the clinical 3D echocardiographic data. A newly developed software program MVCP FemCoGen © , written in Delphi, reformats the TomTec file structures in five patients for use in ABAQUS and allows visualization of regional deformation of the LV. Results This study demonstrates that a fully automated importation of 3D TEE data into FEM modeling is feasible and can be efficiently accomplished in the operating room. Conclusion For complete intraoperative 3D LV finite element analysis, three input elements are necessary: 1. time-gaited, reality-based structural information, 2. continuous LV pressure and 3. instantaneous tissue elastance. The first of these elements is now available using the methods presented herein.	Background Intraoperative TEE is currently available in most cardiac surgical operating rooms. In some centers, intraoperative 3D echocardiography is used to evaluate geometry and to plan surgical interventions prior to LV remodeling surgery. However, quantitation of LV geometry is limited to rather imprecise measures such as ejection fraction. Thus the cardiac surgeon has no sophisticated, immediate, quantitative analysis of the preoperative 3D LV geometry. Intraoperative quantitative analysis of the dynamic behavior of the LV might provide optimal information upon which to base precise patient-specific planning of the surgical intervention, as well as to assess the adequacy of the completed surgical repair. Because the LV cannot be realistically described by a symmetric mathematical model, the modern approach consists of using a FEM mesh which approximates LV geometry [ 1 ] or whole heart geometry [ 2 ]. Initial attempts at FEM in the heart have been carried out with 3D segmentation and tracking using sophisticated and expensive cardiac MRI [ 3 ]. MRI is impractical in the cardiac surgical operating room and is complicated by the fact that the LV and the papillary muscles are active materials, behaving differently during systole and diastole. An ideal model would provide material properties specific to each patient as first mentioned by McCulloch [ 4 ], but untill now patient-specific modeling in the operating room is not been possible. FEM modeling of 3D intraoperative echo data provides an excellent tool for incorporating material properties, volumetric data and boundary pressures to more accurately record and then to simulate LV dynamic performance. Accurate simulation will be the foundation of surgical planning. The limitation until now in applying FEM intraoperatively has been the technical complexity of this technique. The purpose of this study is to take the first step towards introducing FEM into the operating room environment. The goal is to facilitate transfer of geometric data from 3D ultrasound data set into FEM. Methods After obtaining institutional review board approval, LV images from clinical TEE data sets were obtained in five patients via the midesophageal window using a Philips 5500/7500 or and Acuson Sequoia ultrasound system. After induction of general anesthesia and airway protection, the esophagus was intubated using an omniplane TEE probe. 3D TEE data sets of the LV structures including mitral annulus and leaflets, chordae tendinae, papillary muscles and ventricular wall were obtained using the automated Philips/Acuson acquisition protocol at 10° increment. Images were gaited for both beat-to-beat variability and respiratory motion. In order to facilitate acquisition in the shortest possible timeframe, ventilation was modified to provide a tidal volume of 510 -6 m -3 kg -1 at a respiratory rate sufficient to maintain end-tidal CO 2 levels between ~4.410 3 m kg -1 s -1 and ~5.1*10 3 m kg -1 s -1 . All images were stripped of patient identifiers. For LV geometry reconstruction, the TomTec LV-Analysis TEE © software module [ 5 ] was employed. This software runs on a standard Dell Inspirion laptop computer with Microsoft Windows™ 2000 operating system which imports, analyzes, reports and archives the time-resolved 3D-ultrasound data. The TomTec system automatically detects endocardial borders and produces a 3D shell reconstruction of the LV [ 5 ]. It also provides for an analysis of global and regional LV parameters in which a landmark-setting method is used (see Fig. 1 ). Figure 1 Scheme of the LV (left ventricle). Section through left atrium and ventricle shown schematically. In the LV Analysis TomTec TEE program, three landmarks are taken from each second frame per data set. This means that each 10° a frame is taken as the sampling point for the LV Analysis TEE program. AV is aortic valve, MV is mitral valve and Ap is apex. The first landmark was set in the middle of the mitral valve at the level of its annulus. Care was taken to avoid having the mitral valve cusps cross this landmark. Two additional landmarks were placed in the middle of the aortic valve at the level of its annulus and at the endocardial level of the LV apex. With this landmarking procedure, a time-resolved LV geometric analysis with 18 models per heart cycle was obtained (see Fig. 2 ). Figure 2 Screenshot-TomTec. Screenshot of the workspace of the TomTec LV Analysis TEE program. The LV is segmented using color coding in (c). In (a) the LV model is shown in 3D as calculated from the sampling points set according to Fig. 1. The shadowed plane in (a) indicates the position of the actual original US gray-value frame in 3d as shown in (b). In (d) the volume content is displayed in terms of the actual model step indicating the actual phase with a green line. The screenshot of the actual phase shows the LV model at near systole. The rendered LV geometry resulting from the TomTec analysis tool was transferred to an ABAQUS input file using software written in Delphi. In this program, the TomTec file structure was reformatted to an ABAQUS system (version 6.3) input file based on standard ABAQUS FEM elements. ABAQUS creates a time series of LV model files and requires continuous intraventricular pressure and tissue elastance parameters to process the model. For this analysis LV pressure was modeled using wave forms obtained from Columbia University's HeartSim © cardiac simulator [ 6 ]. A single tissue elastance parameter was applied. These modeled values were used to demonstrate the concept. Actual values will be needed for accurate simulations. The time required for each step in this process was recorded for each patient data set. Results Both, the Philips Sonos 5500/7500 or the Acuson Sequoia ultrasound systems required less than 10 minutes acquistion time per patient. The application of the TomTec LV analysis algorithms with manual placement of the necessary landmarks took approximately 7 minutes per patient. In five patient data sets conversion from TomTec data to the FEM model was carried out in less than a minute for a heart cycle using the conversion tool MVCP FemCoGen © [ 7 ]. ABAQUS processing time on the above computer was 20 seconds per sequence or approximately 6 minutes per patient. Total time for the procedure was approximately 24 minutes per patient (see Table). Fig. 3 shows the ABAQUS FEM program system interface (ABAQUS/viewer) including the LV models in default mesh mode. All 774 triangles of the FEM mesh from the diastolic state (14 th image out of a set of 18 images per heart cycle) are displayed and can be visualized using ABAQUS viewer options. Each mesh element can be analyzed separately. This is shown in Fig. 4 : In Fig. 4a and 4b the rendered LV using a standard constant-shading model is displayed in systolic and diastolic states. Fig. 4c and 4d show both the FEM mesh and the normal vectors orthogonally placed (orthonormals) on each triangle indicating the force direction. These figures demonstrate the quantification of movement during the heart cycle directly using modeled continuous LV pressure and tissue elastance parameters. Table 1 Data acquisition and processing times Data acquisition and processing times Data set Ultrasound acqusition [s] TomTec analysis [s] FemCoGen transfer [s] Abaqus processing [s] 1 715 475 50 355 2 580 364 45 340 3 670 320 55 390 4 640 390 45 410 5 597 423 45 430 Mean ± (standard deviation) [s] 640.4 ± 41.7 394.4 ± 43.7 48 ± 3.6 385 ± 30 Total time [s] 1467.8 ± 29.7 Figure 3 LV in finite element analysis program. Left ventricle FEM model in ABAQUS FEM program interface. Shown is the LV in diastole. At the top of the mesh is the aortic valve depicted as a cavity. The LV apex appears at the bottom of the mesh. Figure 4 Pressure direction at systole and diastole. Rendered LV at systole on the left (a) and (c) and diastole on the right (b) and (d). Shown is the mesh generated with FEM program including all 774 FEM elements rendered with a standard constant shading model in (a) and (b). (c) and (d) show the mesh together with the surface vectors (normals) orthogonally placed on each element (triangle) indicating the pressure directions. Discussion The general intention of this study was to demonstrate the feasibility of transporting individual patient's LV geometry data into a FEM model. Standard laptop computer technology was utilized to accomplish the transfer from common TEE-machines (Philips Sonos 5500/7500 and Acuson Sequoia). The software running on the laptop was the commercially available TomTec LV Analysis TEE © package and ABAQUS FEM system, plus the recently developed MVCP FemCoGen © . Accomplishing this transfer will form the foundation for intraoperative surgical planning and quantitative outcome assessment of valvular and LV reconstructive surgery. The scope of this study was to produce a prototype in which the feasibility of the method could be assessed. In a fully operational system, we could postulate clinical applications such as enhanced/automated wall motion abnormality detection, assessment of regional relaxation which encompases the entire ventricle, assessment and guidance of ventricular remodeling operations, and serial assessment of recovery of regional wall function post myocardial stunning. FEM meshes have been used for approximately 30 years [ 8 ] in the analysis of many anatomical structures and organs e.g such as major vessels [ 9 , 10 ], heart valves [ 11 ] and ventricles [ 12 ], lung [ 13 ], corneoscleral shell [ 14 ], plastic and reconstructive craniofacial surgery [ 15 ] and the femur [ 16 ]. A FEM model can be created to determine the deformation of the LV loaded by intraventricular pressure. Steady-state fluid dynamics and structural analyses can be carried out using commercial codes based on FEM [ 17 ]. At a sequence of time-steps of the cardiac cycle, the model can be considered to be a quasi-incompressible transversely isotropic hyperelastic material based on the analysis of Feng [ 18 ]. Until now, biomechanical cardiac FEM models have been based on simplified ellipsoidal and cylindrical geometries [ 18 ]. A FEM created in this way is not patient-specific and does not accurately represent precise regional deformations in the LV loaded by intraventricular pressure. The method described here will allow patient specifity and the precise representation of deformation. Our method would be applicable to the "live 3D" systems assuming that the entire ventricle could be seen throughout the cardiac cycle in the transthoracic (or epicardial) matrix array acquisition. This would be most feasible in small adults and children and can be proved in further studies. The total time required for acquisition to a completed FEM model was approximately 24 minutes and can be accomplished during the time period when the patient is being prepared for cardiopulmonary bypass (generally 1 to 1.5 h). Thus the feasilbility in terms of duration is clearly demonstrated. In terms of procedure accuracy, reproducibility and duration, the primary limitation is the dependence of the TomTec software on manual entries of the three registration landmarks. This requirement is iterative. Manual entries must be done for multiple frames within the TEE data sets. Inter- and intraobserver variability is a general problem for ultrasonic imaging. The validation of the TomTec border detection has not been published. TomTec LV Analysis TEE © Software is under review by the US FDA, but despite of lack of validation TEE is the only practical technology in the cardiac operating room for the forseeable future. Ultrasound tissue Doppler technologies may be developed in the future to allow automation of the registration process. A limitation of the present study is that it is focused on the deployment of the transfer method. The entire process will require extensive validation. The validation strategy will most likely involve comparision with preoperative cardiac MRI as well as comparison with bypass and post bypass tissue geometry in the same patients. Creating models from MRI based data sets analogous to the TomTec LV analysis and transfering these models to ABAQUS might lead to a new validation strategy which is not been possible up to now. The tool for modeling presented here facilitates vector-subtraction analysis for different points within the cardiac cycle. Quantification is therefore immediately available for both global and regional wall motion, shape and volume analysis. The future use of such instantaneous analysis has a number of potential applications for LV function assessment and surgical planning. This technology could enable a comprehensive automated regional wall motion analysis. A significant challenge in the evaluation and management of patients with coronary artery disease is determining the viability of myocardium. A biomechanical FEM of the LV myocardium can be imported to evaluate dynamic mechanical properties of regions of the myocardium. This approach could provide the basis for a new index of regional myocardial viability. Conclusions For complete intraoperative 3D LV finite element analysis, three input elements are necessary: 1. time-gaited, reality-based structural information, 2. continuous LV pressure and 3. instantaneous tissue elastance. The first of these elements is now available using the methods presented herein. The later two parameters will be required for robust modeling and analysis. Pressure data will be easily available in the cardiac operating room. Strategies for computing elastance are presently under development. With all three parameters, it will be possible to begin to develop the computational strategies which will allow virtual procedures to be performed utilizing 3D display technology and a haptic-feedback robotic "instruments". Whether this new intraoperative information will be useful in assessing the effectiveness of surgical interventions such as LV remodeling remains to be studied. FEM analysis has not been feasible for LV in the intraoperative setting. The major roadblock was the complexity and the practicality of transfer of structural 3D data to a FEM analysis program. This study describes a method to rapidly transfer 3D structural data from the TEE device into a FEM analysis program. Once mesured pressure and calculated elastance are added to the model, near real-time dynamic stress-strain information in the operating room will be achievable. Authors' contributions JFV did the technical part implementing the FEM model in ABAQUS ® , NSN did the data acquisition and the medical part. Both authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC524498.xml
535542	Saposin C promotes survival and prevents apoptosis via PI3K/Akt-dependent pathway in prostate cancer cells	Background In addition to androgens, growth factors are also implicated in the development and neoplastic growth of the prostate gland. Prosaposin is a potent neurotrophic molecule. Homozygous inactivation of prosaposin in mice has led to the development of a number of abnormalities in the male reproductive system, including atrophy of the prostate gland and inactivation of mitogen-activated protein kinase (MAPK) and Akt in prostate epithelial cells. We have recently reported that prosaposin is expressed at a higher level by androgen-independent (AI) prostate cancer cells as compared to androgen-sensitive prostate cancer cells or normal prostate epithelial and stromal cells. In addition, we have demonstrated that a synthetic peptide (prosaptide TX14A), derived from the trophic sequence of the saposin C domain of prosaposin, stimulated cell proliferation, migration and invasion and activated the MAPK signaling pathway in prostate cancer cells. The biological significances of saposin C and prosaposin in prostate cancer are not known. Results Here, we report that saposin C, in a cell type-specific and dose-dependent manner, acts as a survival factor, activates the Akt-signaling pathway, down-modulates caspase-3, -7, and -9 expression and/or activity, and decreases the cleaved nuclear substrate of caspase-3 in prostate cancer cells under serum-starvation stress. In addition, prosaptide TX14A, saposin C, or prosaposin decreased the growth-inhibitory effect, caspase-3/7 activity, and apoptotic cell death induced by etoposide. We also discovered that saposin C activates the p42/44 MAP kinase pathway in a pertussis toxin-sensitive and phosphatidylinositol 3-kinase (PI3K) /Akt-dependent manner in prostate cancer cells. Our data also show that the anti-apoptotic activity of saposin C is at least partially mediated via PI3K/Akt signaling pathway. Conclusion We postulate that as a mitogenic, survival, and anti-apoptotic factor for prostate cancer cells, saposin C or prosaposin may contribute to prostate carcinogenesis at its early androgen-dependent or metastatic AI state.	Background Androgens, growth factors, neuropeptides, and other trophic agents are involved in normal and neoplastic growth of the prostate. Prosaposin is the intracellular precursor of four lysosomal glycoproteins, saposins A-D, that are involved in lysosomal hydrolysis of sphingolipids. These saposins, through their interaction with glycosphingolipid hydrolases and their substrates, increase lysosomal hydrolytic activities. Saposins and prosaposin are expressed by various cell types and as a secretory protein in body fluids including blood, seminal plasma, seminiferous tubular fluid, and prostatic secretions [ 1 - 5 ]. Prosaposin and its active domain, saposin C, are known for their potent neurotrophic activities and are involved in neuro-embryological development [ 6 , 7 ]. The neurotrophic activity of prosaposin has been attributed to the NH 2 -terminal portion of the saposin C domain of the molecule which is the source for a number of biologically active synthetic peptides such as prosaptides TX14A [ 4 - 6 ]. Prosaptides (i.e., TX14A), saposin C, and prosaposin exert their biological effects by binding to a partially characterized single high-affinity G-protein coupled receptor (GPCR) [ 6 - 8 ]. It has been reported that mice with an inactivated prosaposin gene die at 35–40 days of age due to neurological disorders. These mice also develop several abnormalities in their reproductive organs, such as atrophy and involution of the prostate gland and inactivation of MAPK and Akt in the prostate epithelium [ 9 , 10 ]. The spectrum of biological activities of prosaposin or saposin C in cancer biology in general and in prostate cancer has not been specifically addressed. We have recently reported a higher expression of prosaposin in androgen-independent (AI) prostate cancer cells (PC-3 and DU-145) than in androgen-sensitive (AS) LNCaP or in normal prostate epithelial and stromal cells. In addition, we have found that prosaptide TX14A stimulates prostate cancer cell proliferation, migration, and invasion, activates the Raf-MEK-ERK-Elk-1 signaling cascade of the mitogen-activated protein kinase (MAPK) pathway, and inhibits the growth-inhibitory effects of sodium selenite administered at apoptogenic concentrations [ 11 ]. In the present study, we show for the first time that saposin C also functions as a survival factor, activates PI3K/Akt-signaling pathway, and in a cell type-specific manner, modulates the expression of procaspase- and caspase-3, -7, and -9 in prostate cancer cells under serum-starvation stress. We demonstrated that prosaptide TX14A, saposin C, or prosaposin decreased the growth-inhibitory effects, caspase-3/7 enzymatic activity, and apoptotic cell death induced by etoposide. In addition, our data show that saposin C activation of a p42/44 MAPK in prostate cancer cells is not only pertussis toxin-sensitive, but also PI3K/Akt-dependent. Moreover, the PI3K-inhibitor, LY294002, restores the apoptogenic effect of etoposide in prostate cancer cells studied. We propose that as a survival and anti-apoptotic factor, saposin C or prosaposin may contribute to prostate carcinogenesis or to the development of hormone-refractory prostate cancer. Results Saposin C acts as a survival factor for prostate cancer cells The effect of saposin C as a survival factor was assessed under serum-starvation stress. Androgen-sensitive (AS) LNCaP cells did not maintain their viability when cultured in serum-free, 0.25% FBS-RPMI, or 0.5% FBS-RPMI media, for more than 36 h. These cells started to detach from tissue culture plates and cell viability was decreased to less than 40% as determined by the trypan blue dye-exclusion method. However, in the presence of 1% FBS, cells remained attached to the tissue culture plate and their growth increased 31% at day 4 and 20% on day 6 as compared with the control values at day 2 (Fig. 1 ). Saposin C stimulated proliferation of these cells by 13% at day 2, 35% at day 4, and 33% at day 6 compared to the controls. PC-3 cells appeared to be more sensitive to serum deprivation and the number of live cells decreased 30% by day 4 and 60% by day 6 compared to the control values at day 2. However, saposin C (at 1.0 nM) increased cell proliferation by 9% at day 2, 19% at day 4, and 88% at day 6, compared to control plates at the same time period. The growth-response of DU-145 cells was different from PC-3 or LNCaP cells. In the absence of saposin C, the number of live cells increased 10% at day 4 and 29% at day 6 compared to day 2. These cells also demonstrated the highest proliferative response to saposin C at day 4 by 93% (Fig. 1 ). Taken together, these data indicate that saposin C in a dose-dependent and cell type-specific manner, promotes the survival of the serum-deprived prostate cancer cells. Figure 1 Saposin C acts as a survival factor for prostate cancer cells. Cells were cultured in their complete media for 3 days and shifted to their basal (serum-free) media or RPMI-1% FBS (only for LNCaP) in the presence or absence of the indicated concentrations of saposin C for 2, 4, or 6 days. Tissue culture media and saposin C were refreshed every 2 days. At the end of incubation periods, cells were trypsinized and cell number was determined using a hemocytometer and trypan blue exclusion method. PC-3 and DU-145 were used as androgen-independent and LNCaP cells were used as androgen-sensitive prostate cancer cell lines. Data represent the average of three independent experiments in triplicate samples; bars , ± SEM. * indicates P < 0.05, and ** indicates P < 0.01 compared to control. Statistical significance was determined by one-way ANOVA with Bonferroni's corrections. Saposin C activates the PI3K/Akt signaling pathway in prostate cancer cells Several studies have demonstrated that the serine/threonine kinase Akt is a pivotal survival effector for prostate cancer cells and protects them from apoptotic-cell death induction by various types of stresses. Hence, we next evaluated the effect of saposin C on the Akt signaling pathway in cells. Direct immunoblotting of serum-starved cells for 24 h showed that saposin C upregulates phosphorylative activity of Akt at serine 473 in androgen-independent (AI) PC-3 and DU-145 cells (Fig. 2A ). This response was biphasic. The response of LNCaP cells was distinct and started at 1.0 nM that subsequently returned to a basal level at higher treatment concentrations. Under our experimental conditions, we did not detect any changes in the phosphorylative activity of Akt at threonine 308. Since Akt is a downstream effector of PI3K, we tested the effect of the PI3K-specific inhibitor, LY294002. Pretreatment of cells with LY294002 (50 μM, 3 h) followed by saposin C treatment substantially reduced phosphorylation levels of both serine and threonine residues of Akt in AI- and AD-prostate cancer cells (Fig. 2A ). Figure 2 Saposin C activates Akt signaling pathway in prostate cancer cells. A , cells were cultured up to 70% confluency in their complete media, serum-deprived for 24 h, and treated with 10% FBS or saposin C at 0.1, 1, or 10 nM for 10 min. A representative culture plate was also treated with LY294002 (LY; 50 μM) before treating with saposin C (at 1 nM for LNCaP and 10 nM for PC-3 and DU-145). Fifteen μg protein per sample was subjected to SDS-PAGE under reducing conditions and immunoblotting was carried out using phospho-specific Akt antibodies against serine 473 or threonine 308. B , non-radioactive in vitro kinase assay was performed to determine the effect of saposin C on Akt kinase activity as described in details in Materials and Methods. Briefly, cells were grown as described above and Akt was selectively immunoprecipitated from 250 μg protein using 20 μl of immobilized Akt 1G1 monoclonal antibody. Immunocomplexes were pelletted and resuspended in kinase buffer in the presence of 200 μM ATP and 1 μg of Akt/PKB substrate-glycogen synthase kinase fusion protein (GSK-3α/β) and incubated for 30 min at 30°C, allowing immunoprecipitated Akt (if activated) to phosphorylate GSK-3. After terminating the kinase reaction, phosphorylated GSK-3 was detected by SDS-PAGE and immunoblotting using phospho-GSK-3α/β antibody. Control loading was evaluated with anti-Akt antibody to determine total Akt-level. Each experiment was performed in duplicate, and the assays were repeated three times. To determine whether the upregulation of Akt-phosphorylation by saposin C is associated with its kinase activity, in vitro kinase assays were performed. After 5 or 10 min exposure of cells to saposin C, activated-Akt induced phosphorylation of glycogen synthetase kinase-3 (GSK-3; a well-characterized Akt substrate) in both AS and AI prostate cancer cells (up to 3-fold compared to basal levels) at concentrations as low as 0.1 nM, was followed by a slight increase at higher concentrations (Fig. 2B ). Using purified human milk prosaposin, we observed similar responses (data not shown). The above results indicate that saposin C activates the Akt-signaling pathway in a PI3K-dependent manner in both AS and AI prostate cancer cells. Saposin C differentially modulates the expression or activity of caspases and PARP in prostate cancer cells under serum-starvation stress An essential component of the programmed death pathway in many cell types involves proteolytic cleavage of inactive caspases to catalytically active products. We investigated the expression of cleaved (active) and non-cleaved (inactive) forms of the initiator caspase-9, its active downstream effectors (caspases-3 and -7), and poly (ADP-ribose) polymerase (PARP, a nuclear substrate for caspase-3) in the cells after a 48 h serum deprivation period. Caspase-9 is closely coupled to proapoptotic signals and we found that the expression of procaspase-9 was not affected by saposin C; however, we were able to detect a reduction in its cleaved form at 10 nM saposin C in all cells investigated (Fig. 3 ). Figure 3 Effect of saposin C on expression/activity of caspases and PARP under serum-starvation stress. Cells were cultured routinely up to 60% confluency, washed with PBS, and incubated in their respective serum-free media supplemented with or without saposin C for 48 h. Cell lysates were prepared as described in Materials and Methods and 75 μg of clarified protein samples was subjected to SDS-PAGE under reducing conditions. Western analysis was carried out using monoclonal antibodies against non-cleaved and cleaved caspases-3, -7, and -9 and PARP. For control loading, membranes were probed or reprobed with anti-actin antibody. Each experiment was performed in duplicate, and the assays were repeated three times. With respect to the effector caspases, we noticed a dramatic dose-dependent increase in the expression of procaspase-3 in the AI PC-3 and DU-145 cell lines. However, we observed a reduction in expression of caspase-3 in both AS and AI cancer cells. Furthermore, our data showed that procaspase-7 expression in these cells was not affected by saposin C and under our experimental conditions we did not detect caspase-7 in AI prostate cancer cells. In LNCaP cells, we found a reduction in the level of caspase-7 at 1 or 10 nM of saposin C (Fig. 3 ). To further follow the mechanistic response of cells to saposin C in the death cascade, we examined the expression of one of the final death substrates, PARP, and its cleaved product. The intensity of PARP expression was considerably higher in PC-3 and DU-145 cells than in LNCaP cells. Saposin C, in a dose-dependent manner, increased PARP expression and this effect was associated with a parallel dose-dependent reduction of the cleaved (active) PARP levels (Fig. 3 ). Interestingly, the ratio of PARP: cleaved PARP expression in AI PC-3 and DU-145 cells, either at its basal level or after stimulation with saposin C, was higher than AS LNCaP cells. In general, saposin C induced a cell type-specific (AI versus AS) alteration in the expression level of initiator and effector caspases. This effect suggests a better survival and anti-apoptotic activity of saposin C in AI prostate cancer cells than in AS LNCaP cells. Saposin C protects prostate cancer cells from etoposide-induced apoptotic cell death Next, we decided to evaluate the effect of an apoptogenic agent, etoposide, on cell growth, apoptosis, and caspase activity in the presence or absence of various effectors. Cells were treated in complete culture media for three days, and then subjected to the MTS assay. Using these experimental conditions, we empirically determined the lowest concentration of etoposide that would lead to the highest growth inhibition. We found that the growth inhibitory effect of etoposide on prostate cancer cells is also cell type-specific. For example, a 20 μM etoposide concentration was sufficient to reduce the cell number to 53% in PC-3 and to 58% in LNCaP cells as compared to their control values. However, DU-145 cells were more sensitive and treating these cells with only 2 μM etoposide led to a 69% reduction in the cell number compared to control values (Fig. 4A ). Compared to etoposide-treated cells, saposin C increased cell growth by 13% in PC-3, 24% in DU-145, and 27% in LNCaP cells. Like saposin C, prosaposin reduced etoposide-induced growth inhibition to relatively the same degree. The highest increase in cell number was achieved with synthetic peptide TX14A treatment; however treatment of cells with the mutant 769M peptide showed only a negligible effect (2–5% increase the cell number) (Fig. 4A ). These results indicate that TX14A peptide, saposin C, or prosaposin can reduce etopside growth-inhibition on prostate cancer cells. Figure 4 Saposin C reduces growth inhibitory effect of etoposide and acts as an anti-apoptotic factor for prostate cancer cells. A , cells were seeded at 2000 per well in 96-well plates in their complete culture media for 3 (for PC-3 and DU-145) or 4 days (for LNCaP), treated with vehicle (DMSO), saposin C (0.1, 1, or 10 nM), prosaptide TX14A (10 nM), inactive mutant peptide 769M (10 nM), or prosaposin (1 ng/ml) at the indicated concentrations in the presence or absence of etoposide at the indicated concentrations for 3 days. After this period cell number was determined using MTS assay and cell type-specific OD/cell number calibration curve as described in Materials and Methods. B , apoptosis was determined by TUNEL assay. Cells were cultured in multiwell chamber slide up to 40% confluency in their complete culture media, and treated with etoposide in the presence or absence of saposin C (0.1, 1, or 10 nM) for 3 days. Percentage of apoptosis was determined by random selection of 10 microscopic field (at × 200 magnification) and cell count with a hemocytometer. Data expressed at the average of three independent experiments and twelve replicate samples; bars , ± SEM. * indicates P < 0.05, and ** indicates P < 0.01 compared to control (etoposide). Statistical significance of the effect of saposin C on cell growth and apoptosis was evaluated by one-way ANOVA with Bonferroni's corrections. Differences of vehicle (or etoposide)-only treated cells and any other single experimental group of interest (TX14A or prosaposin) was evaluated by Student's t -test and statistical significance was set at P < 0.05. Using the TUNEL assay and above experimental conditions, we next evaluated the effect of saposin C on the percentage of apoptotic cells after treating cells with etoposide for three days. Apoptotic cells were identified as dense, bright, and punctate, with brownish pigmentation of poly-fragmented nuclei. Among the three cell lines investigated, PC-3 proved to be the most resistant cell line to apoptosis induction by etoposide. Overall, there was a dose-dependent reduction (with a peak effect at 10 nM) of apoptotic cells in the three cell lines investigated. Saposin C decreased apoptotic cells by 47% in PC-3, 89% in DU-145, and 58% in LNCaP cells (Fig. 4B ). This result demonstrates the counteracting influence of saposin C and etoposide on apoptosis in prostate cancer cells. We also employed a sensitive fluorometric assay to measure caspase-3/7 (based on DEVDase) activity using the experimental conditions described above. Saposin C, at 1 nM concentration, demonstrated the highest reduction in caspase-3/7 activity in AS LNCaP (21%) and in AI PC-3 (35%) and DU-145 cells (30%) (Fig. 5A ). Prosaposin-treated cells also demonstrated a similar effect. TX14A peptide not only decreased the growth-inhibitory effect of etoposide (data not shown), but also proved to be a potent anti-apoptotic peptide, reducing caspase-3/7 activity by 43% in PC-3, 36% in DU-145, and 30% in LNCaP cells. However, the control (inactive mutant) peptide's (769M) effect was minimal (with a 2–5% reduction) (Fig. 5A ). These results clearly indicate that the anti-apoptotic activity of saposin C is at least partially associated with modulation of caspase-activity. Figure 5 Effects of saposin C on caspase-3/7 activity (A) and the influence of PI3-kinase inhibitor (B) in etoposide-treated cells. Cell culture, treatment period, growth and caspase activity was described in Figure 4. Caspase-3/7 activity was determined using the Apo-ONE Homoheneous Caspase-3/7 assay kit based on the cleavage of a profluorescent caspase-3/7 substrate (Z-DEVD-R110) and fluorimetric quantitation was performed at an excitation and emission wavelength of 485+20 and 535+25 nm, respectively. After correction of the fluorimetric reading with the blank (vehicle control), final fluorescent intensity was depicted as an arbitrary endpoint relative fluorescent unit, RFLU. PI3-kinase inhibitor (LY294002; LY) was used at final 1.5 μM concentration and saposin C was added at optimal 1 nM (for PC-3 and LNCaP) or 10 nM (for DU-145) concenration. Etoposide (Et) was added at optimal 20 μM (for PC-3 and LNCaP) or 2 μM (for DU-145). Data expressed are the average of three independent experiments and twelve replicate samples; bars , ± SEM. * indicates P < 0.05, and ** indicates P < 0.01. Statistical significance of the effect of saposin C on cell growth and apoptosis was evaluated by one-way ANOVA with Bonferroni's corrections. Differences of vehicle (or etoposide)-only-treated cells and any other single experimental group of interest (TX14A or prosaposin) was evaluated by Student's t -test and statistical significance was set at P < 0.05. The PI3K/Akt inhibitor restores apoptogenic activity of etoposide in saposin C treated cells To determine whether or not saposin C anti-etoposide apoptotic activity is PI3-kinase dependent, the effect of PI3K/Akt inhibitor (LY294002) on caspase-3/7 activity in the cells was examined in the presence or absence of saposin C ± etoposide. Through our initial studies, using trypan blue exclusion and MTS assays, we found 1.5 μM of LY294002 was a non-toxic and tolerable dosage for experimental period (3 days). Compared to DMSO-treated cells, LY294002 slightly increased (up to 10%) the caspase-3/7 enzymatic activity in PC-3 and DU-145 and showed almost no change in LNCaP (Fig. 5B ). As described above, saposin C significantly decreased induction of caspase-3/7 activity by etoposide. Saposin C also reduced the induction of casapases activity by LY294002 under our experimental conditions. Addition of LY294002 to the cells treated with saposin C and etoposide increased caspase-3/7 enzymatic activity, but to a level below than etoposide-only treated cells (Fig. 5B ). These results indicate that antiapoptotic activity of saposin C and its effect on caspase activity is at least partially mediated via the PI3K/Akt signaling pathway. Saposin C activation of MAPK is pertussis toxin-sensitive and PI3K/Akt-dependent In neuro-glial derived cells, neurotrophic activity, cell-death protection and the activation of MAPK by prosaptides (i.e., TX14A), saposin C, or prosaposin are mediated by their binding to a pertussis toxin-sensitive GPCR [ 6 , 7 , 12 , 13 ]. Our previous data demonstrated that prostate cancer cells were differentially responsive to the TX14A peptide in a number of biofunctional assays [ 11 ]. Our current results indicate the presence of a sensitive and /or responsive receptor-ligand interaction that could be accountable for the subsequent activation of downstream signaling effectors in MAPK- and Akt-signal transduction pathways. In addition, there is also emerging data indicating that signaling proteins such as PI3K and Akt can also activate MAPK pathways [ 14 - 16 ]. We have previously demonstrated MAPK-activation by the TX14A peptide derived from a trophic sequence of saposin C [ 11 ]. To examine the involvement of GPCR in saposin C-activation of the Akt-signaling pathway as well as the possibility of MAPK and Akt cross-signaling initiated by saposin C, we evaluated the effect of saposin C on p42/44 MAP kinase activation in prostate cancer cells in the presence or absence of various inhibitors. Treatment of cells with saposin C increased the phosphorylative activity of p42/44 MAPK, which was substantially inhibited by pretreating cells with the specific MEK inhibitor (U0126; Fig. 6 ). We used 10% FBS treatment as an external positive control for induction of p42/44 activity in the cells. Saposin C treatment of cells pretreated with PT showed a modest (in LNCaP cells) to strong reduction (in AI prostate cancer cells) in the level of phospho-p42/44 MAPK. This result clearly indicates a cell type-specific PT-sensitivity and/or the potential involvement of one or more G-proteins in saposin C-activation of MAPK pathway in the cells. Figure 6 Saposin C activation of MAPK pathway is pertussis toxin-sensitive and PI3K/Akt-dependent. Cells were cultured up to 60% confluency in their maintenance media, washed with PBS, serum-deprived for 20 h, and then fresh basal culture media was added for an additional 4 h in the presence or absence of LY294002 (50 μM, 3 h), Wortmannin (10 μM, 15 min), U0126 (10 μM, 1.5 h), or pertussis toxin (200 ng/ml, 4 h). After pretreatment, saposin C (0.1 nM) was added directly to the cells and incubated for 5 min at 37°C. Cell lysates were prepared and 10 μg protein per sample was subjected to SDS-PAGE and immunoblotting using phospho-specific p42/44 MAPK antibody. For control loading, membranes were also probed or reprobed with p42/44 antibody to detect total p42/44 MAPK. Parallel tissue culture plates, treated in the same manner, were also tested for cell viability by trypan blue dye-exclusion assay. FBS at 10% final concentration was used as a positive control. Each experiment was performed in duplicate, and the assays were repeated three times. The intensity of reduction of p42/44 activity and its cell type-specific pattern was very similar to PT plus saposin C- or PT-treated values. Interestingly, we observed a more profound reduction in p42/44 phosphorylative activity in cells pretreated with LY294002 and then treated with saposin C. To rule out the potential cytotoxic effect of the inhibitors, viability of cells was also determined by trypan blue dye-exclusion. We observed essentially similar results using the other structurally and mechanistically different PI3-kinase inhibitor (wortmannin). This experiment revealed that at the end of the pre-treatment incubation period, cell viability was equal to or more than 95%. These results indicate that MAPK activation by saposin C is at least partially mediated by saposin C-regulated PI3K/Akt pathways in prostate cancer cells. This result also provides additional proof for simultaneous activation of multiple (inter-related) signal transduction pathways by saposin C. Discussion Induction of apoptosis by androgen-ablation therapy significantly reduces androgen-dependent (AD) prostate cancer cells, but fails to cure the majority of patients due to the presence of apoptosis-resistant cancer cells that are androgen-independent [ 17 ]. It is likely that the development of these cells is an adaptive response to hormonal therapy rather the overgrowth of resistant cells. In-depth understanding of apoptotic phenomena, identification of its intracellular components, and characterization of its extracellular effectors as inducers or inhibitors may contribute to therapeutic approaches for prostate cancer. The prosaposin knock-out mouse model has revealed a number of interesting findings specifically in the male reproductive organs. Among these are atrophy of the prostate gland, epididymis, and seminal vesicles. Microscopic evaluation of affected tissues also shows undifferentiated phenotypes in prostate ventral and dorsal lobules and atrophy of the tubuloalveolar glands and their epithelial cell lining [ 9 ]. These data are suggestive of a primary role for prosaposin in development of the prostate gland. In a variety of neuro-glial derived cells, synthetic peptides encompassing a trophic sequence of saposin C and/or prosaposin have been found to induce growth, survival, and/or differentiation, or to prevent apoptotic cell-death in vitro and in vivo [ 11 , 18 - 20 ]. For example, prosaptide-TX14A and prosaposin, in a dose- and time-dependent manner reduced apoptotic cell-death induction of primary Schwann cells cultured in low serum concentrations, and PI3K inhibitors (wortmannin or LY294002) blocked their anti-apoptotic effects [ 21 ]. Here, we found that under prolonged serum starvation (2 to 6 days), although the responses of androgen-sensitive (AS) LNCaP and AI PC-3 and DU-145 prostate cancer cells were different from each other, saposin C in a dose- and time-dependent manner, proved to increase proliferation and survival of both cell types (Fig. 1 ). Normal prostatic epithelial cells neither tolerated the basal medium nor responded to saposin C (data not shown). Like many other cancer cells, withdrawal of mitogens, growth factors, and other trophic factors by serum-starvation, serves as a potent stimulus and driving force activating different survival mechanisms that eventually lead to apoptotic cell-death in AD- and Al-prostate cancer cells [ 22 , 23 ]. Since the PI3-Kinase/Akt signaling pathway is known as a central cell-survival mechanism and an important mediator of survival signals driven by growth or trophic factors, we were also interested in examining the level of PI3K/Akt activity during serum starvation. Interestingly, we found that saposin C upregulated Akt-p473 Ser phosphorylative activity in the prostate cancer cells under investigation. This effect was substantially inhibited by LY294002, an inhibitor of the upstream Akt effector, PI3K (Fig. 2A ). In addition, using an in vitro kinase assay, we proved that saposin C induction of PI3K/Akt activity in cells was associated with increased phosphorylation of GSK3α/β, as a downstream key target of the Akt kinase (Fig. 2B ). Unlike Akt-p473 Ser , our study showed a considerably higher level of constitutively activated Akt-p308 Thr in all cells and remained unaffected by saposin C. Other studies have also supported a central role for the PI3K/Akt pathway as a dominant growth factor-induced survival pathway for prostate cancer cells [ 14 , 16 ]. Constitutive activation of the PI3K/Akt survival pathway has been described as a mechanism that enables endocrine-related breast, lung, and prostate cancer to become refractory to cytotoxic therapy [ 24 - 27 ]. Interestingly, immunohistochemical analyses have demonstrated a direct correlation between Akt phosphorylation and the Gleason's score in prostate cancer [ 28 ]. Our results provide evidence that implicate the involvement of PI3K/Akt activity in saposin C (growth factor)-induced survival of prostate cancer cells. With respect to prosaposin, immunohistochemical staining of the involuted and atrophied prostate tissues from homozygous knock-out mice also showed inactivation of the MAPK and Akt signaling pathways [ 9 , 10 ]. Apoptotic-death signal transduction pathways are not limited to PI3K/Akt and may involve multiple redundant physiological pathways. Several studies have shown the involvement of caspases in the apoptosis of the prostate gland in normal development or malignant conditions [ 29 , 30 ]. For example, immunohistochemical evaluation in castrated mice and rats showed the presence of (activated) caspases in prostate and a correlation between caspase-3 expression and the Gleason's grade of tumors [ 29 ]. In vitro studies also revealed that caspase-inhibitory mechanisms might be involved in metastasis of prostate cancer cells [ 15 ]. We found that saposin C, in a dose-dependent manner, increased procaspase-3 and PARP levels and decreased the cleaved form of caspase-9 and -3 and PARP (a caspase-3 substrate) in both AS and AI prostate cancer cells. PARP cleavage has been recognized as a sensitive marker of caspase-mediated apoptosis and its cleavage paralyzes the enzyme's ability to repair DNA strand breaks. Therefore, reduction of the PARP cleavage is a strong indicator for anti-apoptotic activity of saposin C. Although procaspase-7 expression was not affected in any of the cells investigated, its active form was reduced only in LNCaP cells and was not detected in AI prostate cancer cells (Fig. 3 ). This special pattern for alteration in the level of procaspase-3, its cleaved form, and PARP was coincident with saposin C-induced cell survival under serum-deprivation culture condition (Fig. 1 ). Such divergent regulation of caspase-3 and PARP has rarely been reported in prostate cancer cells [ 31 ]. However, it has been demonstrated frequently in the nervous system and therefore might represent a unique characteristic of prosaposin or saposin C as a neurotrophic molecule [ 32 ]. Next, we exposed cells to a universal apoptogenic agent, etoposide, and found that prosaposin or its active derivatives (saposin C or TX14A peptide), were able to decrease the growth-inhibitory effect of etoposide-treated prostate cancer cells (Fig. 4 ). TUNEL assay, as a direct measure of apoptotic death showed a dose-dependent reduction in the percentage of apoptotic cells by saposin C (Fig. 4B ). Under similar experimental conditions, we also showed that saposin C, prosaptide TX14A, or prosaposin reduce caspase-3/7 activity in cells treated with etoposide. This effect could be counteracted by administration of a PI3-kinase inhibitor (LY294002) (Fig. 5A and 5B ). These data are a clear indication that saposin C-inhibition of the apoptogenic activity of etoposide is at least partially dependent on the upstream Akt effector, PI3K (Fig. 5B ). Together, the above findings suggest that the two closely inter-connected cell survival/apoptotic pathways (PI3K/Akt and caspases) activated by saposin C or prosaposin might potentially synergize and provide a growth and survival advantage to both AD- and AI-prostate cancer cells. Induction of mitogenic, survival, and anti-apoptotic signals in physiological and pathological conditions may begin from a wide array of extracellular stimuli and receptors, including receptor tyrosine kinases (RTKs) and G-protein coupled receptors (GPCRs). From a historical point of view, considerable attention has been given to the role of RTKs and their cognate polypeptide ligands in prostate cancer. However, accumulating evidence support the involvement of lysophosphatidic acids, neurotransmitters, and neuropeptides such as bombesin and neurotensin through GPCR signaling in the initiation or progression of prostate cancer [ 32 , 33 ]. GPCRs also use pathways that are very similar to those utilized by RTKs to activate survival and anti-apoptotic signaling pathways such as the prototypic Raf-MEK-MAPK and PI3K/Akt signal transduction pathways and caspase cascades [ 32 , 34 - 37 ]. Here, we showed that saposin C, in a pertussis toxin-sensitive manner, activated p42/44 MAPK (Fig. 6 ). Our study demonstrated the involvement of GPCR as a responsible receptor system interacting with saposin C and therefore activating the subsequent signaling pathways. Due to the considerable importance of activation of MAPK signal transduction activation by saposin C-GPCR and activation of the Akt signaling pathways, we tested whether inhibition of PI3K/Akt could affect saposin C-induced p42/44 MAPK activation. Pretreatment of cells with LY294002 inhibited saposin C activation of p42/44 MAPK (Fig. 6 ). These data not only indicate cross-communication between MAPK- and PI3K/Akt-signaling pathways, but also might suggest that simultaneous activation of the two important signal transduction pathways by saposin C provide a potent cell survival and apoptotic-death protection program for prostate cancer cells. Conclusion Our data for the first time show that by activation of multiple inter-related signaling pathways (PI3K/Akt and MAPK) and cell type-specific modulation of expression or activity of caspases, saposin C and/or its precursor (prosaposin) serve as a survival and anti-apoptotic factor for both AS- and AI-prostate cancer cells. Elucidation of such intricate mechanisms could potentially provide a therapeutic option that combines cytotoxic therapy and inhibition of survival/anti-apoptotic signals for AI metastatic prostate cancer. Finally, our observations provide novel insights into the diversity of biological activities of prosaposin in prostate cancer cells. Methods Cell lines Androgen-independent (PC-3, DU-145) and -sensitive (LNCaP) prostate cancer cell lines were obtained from the American Type Culture Collection (Manassas, VA) and grown in defined media (PC-3 and DU-145 in DMEM-10% FBS and LNCaP in RPMI-1640-10% FBS supplemented with 1 mM sodium pyruvate, 10 mM HEPES). Purified recombinant human saposin C and prurified human milk-prosaposin were characterized and provided by Dr. K. Sandhoff (University of Bonn, Germany) and Dr. M. Hiraiwa (University of California, San Diego), respectively. Cell survival assays Cells were initially grown in 100 mm plates in their respective culture media for 3 days, and after washing with PBS were incubated in serum-free DMEM (PC-3 and DU-145) or RPMI-1% FBS (LNCaP) in the presence or absence of saposin C (at 0.1, 1, or 10 nM) for 2, 4, or 6 days. Saposin C and culture media were replaced every 2 days. At the end of the incubation periods, cells were trypsinized and cell number was determined using a hemocytometer and the trypan blue exclusion method. Western analysis Protein expression analysis was performed according to standard procedures [ 38 ]. Briefly, the cell extract was prepared by washing cell monolayers with cold-PBS, lysing the cells on ice for 15 min with lysis buffer (20 mM PIPES [pH 7.4], 150 mM NaCl, 1 mM EGTA, 1% Triton X-100, 1.5 mM MgC1 2 ) supplemented with a protease inhibitor cocktail (Roche Diagnostic, Inc., Indianapolis, IN) and 1 mM sodium orthovandate, plus sodium dodecyl sulfate (SDS) at a final concentration of 0.1%. The lysates were then centrifuged (15 min, 4°C, 16,000 × g), aliquoted, and stored at -70°C until use. Protein concentration was determined by BCA assay (PIERCE, Rockford, IL). Each experiment was repeated at least two times. For western analysis, membranes were blocked with 5% BSA in the rinse buffer (150 mM NaCl, 20 mM Tris, 0.1% Tween 20) for 1 h, washed in rinse buffer for 10 min, and then incubated with the respective primary antibody at the indicated concentrations (see below). The membranes were then washed and incubated with the appropriate horseradish peroxidase-conjugated secondary antibody (1:1000 dilution; Santa Cruz Biotechnology, Santa Cruz, CA) for 1 h at room temperature, washed for 10 min and four more cycles of 5 min, and treated with an enhanced chemiluminescence (ECL) detection system (Amersham, Piscataway, NJ). In some cases, when the signal was very weak or undetectable, we used ECL-plus (Amersham). (i) Effect of PI3K/Akt and MEK-inhibitors, or Pertussis Toxin on Saposin C Activation of p42/44 MAPK Cells were grown in their respective complete culture media for 2–3 days (up to 60% confluency), washed with PBS, incubated in their serum-free (basal) media for 20 h, and then fresh basal media was added to all plates for an additional 4 h. Various inhibitors [LY294002 (50 μM, 3 h), Wortmannin (10 μM, 15 min), U0126 (10 μM, 1.5 h), and Pertussis toxin (200 ng/ml, 4 h)] were added to the culture medium, just before treating cells with saposin C (at 0.1 nM, 5 min). We used 10% FBS as a positive control. Cells were lysed and 10 μg of clarified protein samples was subjected to SDS-PAGE under reducing conditions. Phospho-specific p42/44 antibody (1:1000; Cell signaling Technologies, Bedford, MA) was used as the primary antibody and as a loading control. Filters were also probed or reprobed with anti-p42/44 antibody. Additional tissue culture plates that had been treated with or without inhibitors were also tested for cell viability by trypan blue dye-exclusion assay. (ii) Saposin C and PI3K/Akt signaling pathway Cells were cultured up to 70% confluency in their complete media and after washing with PBS, they were serum-starved for 24 h, and then treated with 10% FBS or saposin C at 0.1, 1 or 10 nM for 10 min. A representative tissue culture plate was also pretreated with the PI3K-inhibitor (LY294002, 50 μM for 3 h) before treating cells with saposin C (at 1 nM for LNCaP and at 10 nM for PC-3 and DU-145 cells). After preparation of the cell lysate, 15 μg of protein per sample was subjected to SDS-PAGE under reducing conditions. Immunoblotting was performed using phospho-specific Akt antibodies against serine 473 or threonine 308 (Cell Signaling Technology). A loading control was evaluated with anti-Akt antibody. Each experiment was performed in duplicate, and the assays were repeated three times. Immunoprecipitation and in vitro Akt kinase activity assay A non-radioactive Akt kinase assay kit (Cell Signaling Technologies) was used to determine whether saposin C treatment of cells under serum-starvation stress would lead to Akt-activation. For Akt-kinase assays, cells were grown up to 70% confluency in their maintenance media, serum-starved for 24 h, and then treated for 5 or 10 min in the presence or absence of saposin C at 0.1, 1, or 10 nM. Cells were washed once with ice-cold PBS and harvested under nondenaturing conditions using 1X ice-cold cell lysis buffer (from the Kit) supplemented with 1 mM phenylmethylsulfonyl fluoride (PMSF) on ice for 5 (or 10) minutes. Akt was selectively immunoprecipitated from 250 μg protein (whole cell lysates) using 20 μl of immobilized Akt 1G1 monoclonal antibody, and then incubated with gentle rotation for 4 h at 4°C. Samples were then centrifuged briefly (30 sec, 2000 × g) and pellets were washed twice with 1X lysis buffer and once with 1X kinase buffer. Immunocomplexes (pellets) were resuspended in 40 μl 1X kinase buffer [composed of 25 mM Tris (pH 7.5), 5 mM β-glycerolphosphate, 2 mM DTT, 0.1 mM Na 3 VO 4 , and 10 mM MgC1 2 supplemented with 200 μM ATP and 1 μg glycogen synthase kinase-3 [GSK-3; a well characterized Akt/PKB substrate] of fusion protein (GSK-3α/β) and incubated 30 minutes at 30°C, allowing immunoprecipitated Akt (if activated) to phosphorylate GSK-3. The kinase reaction was terminated by adding 20 μl of 3 × SDS sample buffer. Phosphorylated GSK-3 was then detected by western analysis using phospho-GSK-3α/β (for Ser 21 of GSK-3α and ser 9 of GSK-3β) antibody. The above in vitro kinase assay is based on the fact that phosphorylated-Akt (active) regulates GSK-3α/β kinase activity via phosphorylation at ser 21/9. For control loading, 10 μg protein per sample from the same whole cell lysates were subjected to western analysis using monoclonal anti-Akt antibody or actin. Each experiment was performed in duplicate, and the assays were repeated three times. Apoptosis assays (i) Effect of saposin C on expression of caspases by western analysis Cells were cultured up to 60% confluency in their complete culture media. After washing with PBS, they were incubated with their respective serum-free media in the presence or absence of saposin C at 0.1, 1, or 10 nM for 48 h; whole cell lysates were prepared as described above. Clarified protein samples (75 μg) were subjected to SDS-PAGE under reducing conditions. Western analyses were carried out using monoclonal antibodies against non-cleaved and cleaved caspases-3, -7, and -9 and poly (ADP-ribose) polymerase (PARP) provided in an Apoptosis Sampler Kit (Cell Signaling Technology). Each experiment was performed in duplicate, and the assays were repeated three times. (ii) Fluorometric measurement of caspase-3/7 activity in cells treated with etoposide We next examined the effect of an apoptogenic agent, etoposide, on cell growth and caspase activity in the presence or absence of saposin C, prosaposin, prosaptide TX14A, or an analogous inactive mutant peptide (769M; 4). Cells were seeded at 1,000 per well in 96-well plates in their complete culture medium for 3 to 4 days. After this period, cells were treated in complete culture media for 3 days with etoposide (2, 20, or 200 μM) to find the lowest concentration that led to the highest growth inhibition, as measured by MTS assay (described above). Using the optimal cell type-specific etoposide concentration (20 μM for PC-3 and LNCaP and 2 μM for DU-145), cells were treated with the vehicle (DMSO), saposin C (0.1, 1, 10 nM), TX14A (10 nM), mutant peptide (769M, 10 nM), or prosaposin (at 1 ng/ml). Using the cell type-specific OD/cell number calibration curve as obtained by MTS assay (Promega, WI), cell number per well was determined for the above treatment conditions. Parallel tissue culture plates were also used to determine caspase-3/7 activity using the Apo-ONE™ Homogeneous Caspase-3/7 assay (Promega, WI). This assay provides a homogeneous Caspase-3/7 reagent (Promega, Technical Bulletin-TB295) which performs a dual function, by rapidly and efficiently permeabilizing the cultured cells and at the same time exposing the intracellular space to the profluorescent caspase-3/7 substrate, rhodamine 110 (Z-DEVD-R110). After cleavage and removal of the DEVD peptides by caspase-3/7 activity, the fluorescence in each well was quantitated at an excitation wavelength of 485 + 20 nM and an emission wavelength of 535 + 25 nM and after correction based on blank control (DMSO-treated cells at a concentration equal to what used for dissolving etoposide) or the homogeneous caspase-3/7 reagent. Final fluorescent intensity was depicted as endpoint relative fluorescent unit, RFLU. Using similar experimental conditions but as an independent study, the effect of LY294002 (a PI3-kinase inhibitor) was also evaluated on growth and caspase-3/7 activity of cells treated with saposin C ± etoposide. After initial studies to find the optimal concentration, we used a non-toxic tolerable dosage of 1.5 μM for LY294002. In addition, we chose the most effective (optimal) concentration of etoposide (20 μM for PC-3 and LNCaP and 2 μM for DU-145) and saposin C (1.0 nM for PC-3 and LNCaP and 10 nM for DU-145) for this study. (iii) Terminal deoxynucleotide transferase-mediated nick end-labeling (TUNEL) Cells were cultured in multiwell chamber slides and treated with etoposide in the presence or absence of saposin C at 0.1, 1, or 10 nM as indicated above. In situ determination of apoptosis by Terminal dUTP nick-end labeling (TUNEL) was performed using an ApopTag Peroxidase In Situ kit as recommended by the manufacturer (Chemicon International, Temecula, CA). The ApopTag Kit detects single- and double-stranded DNA breaks associated with apoptosis. Drug-induced DNA damage is not identified by the TUNEL assay unless it is coupled with the apoptotic response. Briefly, at the end of the incubation period, cells were fixed in 1% paraformaldehyde in PBS, pH 7.4 for 10 min at room temperature, washed with PBS-twice, and permeabilized in pre-cooled ethanol: acetic acid (2:1) for 5 min at -20°C. After washing twice in PBS, 5 min each time, endogenous peroxidase activity in the cells was quenched in 3% H 2 O 2 in PBS for 5 min at room temperature, incubated with terminal deoxynucleotidyl transferase (TdT enzyme) and then with peroxidase-conjugated anti-digoxigenin antibody. Nuclear staining of the apoptotic cells was detected by 3',3'-diaminobenzidine tetrahydrochloride dihydrate substrate, as recommended by the manufacturer. Cells were then counterstained in 0.5% (w/v) methyl green and slides were mounted under a glass coverslip in permount mounting medium. For control staining, the enzyme incubation step was deleted. Microscopic examination of cells was carried out using a phase contrast microscope. Cells were counted by choosing ten random fields and the percentages of apoptotic cells were determined. Apoptosis was indicated by the presence of apoptotic bodies, exhibiting brightly labeled punctuated nuclei. Statistical analyses For cell survival and other quantitative data, a one-way analysis of variance (ANOVA) was employed to evaluate the influence of one variable on multiple independent groups. Bonferroni's corrections were also applied whenever a significant group effect was observed. To compare a control group with a single experimental group of interest, we used the Student's t-test. For cell survival studies, each treatment concentration was examined three times and in triplicate samples. The effect of saposin C or other effectors in the presence of etoposide on cell growth, apoptosis, or caspase-3/7 activity was studied in twelve replicates and repeated three times. Statistical significance was set at p < 0.05 or 0.01. Statistical analyses were performed using GraphPad Prism version 3.00 for Windows (GraphPad Software, San Diego, CA). Authors' contributions Author 1 (T-JL) carried out experiments described in figure 4 and 5B . Author 2 and 3 (OS and RL) reviewed the manuscript and provided valuable comments in different sections of the manuscript. Author 4 (SK) conceived the study, designed all the experiments, performed experiments described in figures 1 , 2 , 3 , 5A , and 6 , carried out the statistical analysis, and drafted the paper and wrote the final version of the manuscript. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC535542.xml
539350	The effect of cigarette price increase on the cigarette consumption in Taiwan: evidence from the National Health Interview Surveys on cigarette consumption	Background This study uses cigarette price elasticity to evaluate the effect of a new excise tax increase on cigarette consumption and to investigate responses from various types of smokers. Methods Our sample consisted of current smokers between 17 and 69 years old interviewed during an annual face-to-face survey conducted by Taiwan National Health Research Institutes between 2000 to 2003. We used Ordinary Least Squares (OLS) procedure to estimate double logarithmic function of cigarette demand and cigarette price elasticity. Results In 2002, after Taiwan had enacted the new tax scheme, cigarette price elasticity in Taiwan was found to be -0.5274. The new tax scheme brought about an average annual 13.27 packs/person (10.5%) reduction in cigarette consumption. Using the cigarette price elasticity estimate from -0.309 in 2003, we calculated that if the Health and Welfare Tax were increased by another NT$ 3 per pack and cigarette producers shifted this increase to the consumers, cigarette consumption would be reduced by 2.47 packs/person (2.2%). The value of the estimated cigarette price elasticity is smaller than one, meaning that the tax will not only reduce cigarette consumption but it will also generate additional tax revenues. Male smokers who had no income or who smoked light cigarettes were found to be more responsive to changes in cigarette price. Conclusions An additional tax added to the cost of cigarettes would bring about a reduction in cigarette consumption and increased tax revenues. It would also help reduce incidents smoking-related illnesses. The additional tax revenues generated by the tax increase could be used to offset the current financial deficiency of Taiwan's National Health Insurance program and provide better public services.	Background One of the problems in controlling tobacco in Taiwan is that cigarette prices are lower in Taiwan than in most countries [ 1 , 2 ]. In India, smokers have to work 77 minutes to afford a pack of cigarettes, in Indonesia 62 mins, in China 56 mins, but in Taiwan they need only work 7 to 10 mins to afford a pack [ 1 ]. As long as the domestic cigarette price remains rather low, we probably will not see much of a decrease in the number of smokers. The smoking population increased to 4.5 million persons (total population 22,520,776) in 2002 [ 3 ]. One out of three adults smoked. Currently, due to illnesses and death associated with cigarette smoking, smokers currently account for approximately 20 billion NT dollar of extra medical expense annually and account for a 160 billion NT dollar loss in GDP (Gross Domestic Product)[ 4 ]. This economic burden in putting pressure on the government to further increase the existing Health and Welfare Tax on tobacco. Because high excise taxes on cigarettes have been found able to reduce cigarette consumption [ 5 - 8 ], such measures are becoming one of the most important means of controlling tobacco [ 9 - 11 ]. The new tax scheme enacted on 1 January 2002 in Taiwan resulted in NT $16.8 tax excise. This tax included the existing taxes for NT $11.8 and a NT $5 Health & Welfare Tax for a 20-pack of cigarettes. The government also levies 5% sales taxes. Under that tax scheme, the cigarette tax revenues account for 40% of the retail price, which is about NT $42.2. While 40% sounds high, it is actually lower than the taxes imposed on cigarettes in developed countries that have seen some success at lowering cigarette consumption. The government should take elasticity of demand into consideration when deciding whether to increase or add an excise tax levy. If there is a price elasticity below 1, a tax increase brings about a decline in consumption and an increase in total tax revenues. Since Hsieh, Hu and Lin (1999) found that figure to be -0.6 in Taiwan, it can be reasonable to assume that a tax increase would be more likely to reduce cigarette consumption more significantly in Taiwan than in other countries with lower price elasticities at least in the short-term and medium term [ 12 ]. Higher taxes would also generate higher total tax revenues. Taiwan's Tobacco and Wine Tax Law is currently under review in the Legislative Yuan of Taiwan. Some legislators are seeking to increase the Tobacco Health and Welfare Tax by NT $3 per pack, raising it from NT $5 to NT $8 per pack. Just as they have done in the past, cigarette sellers will probably shift the tax increase to the consumers letting them be responsible for the increase. The effect of the price increase on demand depends on cigarette price elasticity – the larger the elasticity, the larger the reduction in consumption. Therefore, an estimation of price elasticity for domestic cigarettes could be a very important indicator of the possible effect a "Tobacco Health and Welfare Tax" would have on cigarette consumption and could be used to adjust Tobacco Health and Welfare Tax accordingly. Price elasticity of cigarette in Taiwan has been mostly estimated using time-series data [ 12 , 13 ], though this method might overlook the impact of smuggled cigarettes on the price elasticity and overestimate the price elasticity. It might be more appropriate and useful to use cross-section data from the Health Interview Survey to estimate the effect of cigarette tax on cigarette consumption and to compare differences in cigarette price elasticity with various smoker characteristics. Methods This study uses data on current smokers from 17 to 69 years of age during years 2000 to 2003. First, the demand function of the current smokers was established. Respondents who answered "everyday" or "some of the days" to the question how often you smoke were classified as "current smokers". Then, we used a random sampling of how they consumed and how much they paid for it between 2000 to 2003 to calculate cigarette price elasticity. We then analyzed differences in cigarette price elasticity in smokers categorized according to gender, age, education, income standard, and how much they smoked. Demand function Cigarette demand function was estimated by OLS and expressed by double logarithm function. The estimated demand function we used was: ln Q ig = α 0 + β 1 ln P ig + γ 2 ln I ig (1) where lnQ ig is i'th current smokers' logarithm representing monthly amount smokers consumed per person in group g. Current smokers were categorized according to age, gender, education, monthly income, and amount smoked. lnP ig is i'th current smokers' logarithm representing cigarette price per pack (NT$) for smoking characteristics group g. lnI ig is i'th current smokers' logarithm representing income per capita (NT$) for various categories of smokers in group g. The α 0 , β 1 , and γ 2 are parameters to be estimated. In order to measure how price change might affect cigarette consumption, the determination of price elasticity was particularly important. Price elasticity of demand for cigarettes is defined as the percent change in consumption resulting from a price increase. Cigarette price elasticity of demand β 1 and income elasticity of demand γ 2 can be derived from logarithmically differentiation (1) according to price and income. Data collection Using an annual face-to-face survey on cigarette consumption from 2000 to 2003 by Taiwan National Health Research Institutes, we collected data on how many packs current smokers consumed, how much they paid for a pack of cigarettes, how much they earned per month and how much they spent on cigarettes per month. Current smokers were categorized into gender, age, education, income, and amount smoked. Calculations of cigarette price were based on the average retail price of the top 3 most consumed cigarettes, calculations of number of packs smoked per month were done by dividing the monthly cigarette consumption by the average retail price. Calculations of income were based on personal monthly income. Certain background characteristics are listed in Table 1 . More than 90% of the smokers were men; less than 10% women. The numbers of young smokers were rising at the time of the study. Young people between the ages of 17 and 24 years old made up 5.4% of the sample in 2000, while they made up 12.8% in 2003, a 1.4 percent increase. The number of elderly smokers above the age of 55 gradually declined from 15.5% in 2000 to 10.8% in 2003. People with higher educational backgrounds tended to smoke more. More than 60% of the current smokers had senior or junior high school educations between 2000 and 2002. Second only to smokers with senior high school degrees, the percentage of the smokers with college degree increased by 27.2% in 2003, accounting for almost 40% of all the smokers. Thirty-five to forty percent earned between NT $20,000 to NT $30,000 per month. Those who smoked less than one pack were defined as light smokers; 1~2 packs (2 packs excluded), medium smokers; and 2 packs and above, heavy smokers. The proportion of light smokers had gradually increased from 50% in 2000 to 60% in 2003, and the proportion of heavy smokers gradually decreased from 11.8% in 2000 to 6.5% in 2003, showing an overall tendency toward reducing consumption. Table 1 Background characteristics of the current smokers in Taiwan, 2000–2003 2000 2001 2002 2003 Characteristics No. % No. % No. % No. % Total 856 632 521 493 Gender Male 789 92.2 599 94.8 496 95.0 460 93.3 Female 67 7.8 33 5.2 25 5.0 33 6.7 Age 17–24 46 5.4 35 5.5 41 7.9 63 12.8 25–34 179 20.9 133 21.0 94 18.0 101 20.5 35–44 299 34.9 222 35.1 190 36.5 177 35.9 45–54 199 23.2 149 23.6 122 23.4 99 20.1 55- 133 15.5 93 14.7 74 14.2 53 10.8 Education College and above 168 19.6 128 20.3 107 20.5 134 27.2 Senior high school 317 37.0 245 38.8 195 37.4 196 39.8 Junior high school 216 25.2 153 24.2 136 26.1 98 19.9 Primary school or lower 155 18.1 106 16.8 83 15.9 65 13.2 Month income No income 98 11.4 93 14.7 63 12.1 75 15.2 <NT $20,000 146 17.1 94 14.9 94 18.0 84 17.0 NT $ 20,000–39,999 335 39.1 237 37.5 192 36.9 174 35.3 NT $ 40,000–59,999 181 21.1 144 22.8 117 22.5 105 21.3 ≥ NT $ 60,000 96 11.2 64 10.1 55 10.6 55 11.2 Smoking degree Light smokers 445 50.0 319 50.5 281 53.9 296 60.0 Medium smokers 310 36.2 250 39.6 200 38.4 165 33.5 Heavy smokers 101 11.8 63 10.0 40 7.7 32 6.5 Results Cigarette consumption, retail price and personal monthly income were used in equation (1), the OLS method, to calculate cigarette price and income elasticities. The overall cigarette price elasticity was negative, less than one, indicating that cigarette consumption or demand in Taiwan was inelastic during the study period (Table 2 ). Taken into consideration that cigarette price elasticity is inelastic and that reduction of the cigarette consumption is done with a strategy of raising domestic cigarette price, we speculate that cigarette prices need to be even higher, to lower consumption enough to have a clear, strong impact in improved public health outcomes. While income elasticities were not statistically different from 2000 to 2002, they did reach a statistically significant level (5%) in 2003. At that time, estimated income elasticity was positive, indicating that cigarettes were normal goods. A positive value normally means that demand for normal goods would increase as incomes rise. But the value could vary greatly among normal goods. Interestingly, in our study, we found that as incomes were rose, income elasticity became low, indicating that income increases in 2003 only had a slight effect on cigarette consumption. Table 2 The estimated overall cigarette price and income elasticities of the current smokers, 2000–2003 a 2000 2001 2002 2003 Price elasticity -0.3134 (-2.894)* -0.3684 (-3.482)* -0.5274 (-3.143)* -0.3090 (-1.531) Income elasticity 0.0069 (0.708) 0.0042 (0.504) -0.0012 (-0.125) 0.0320 (2.916)* a. t ratios are shown in parentheses. * p < 0.05. After Taiwan's accession to WTO in 2002, Taiwan's first Tobacco Health and Welfare Tax added NT $5 the price of cigarettes, resulting in an increase in cigarette retail price from NT $35.2 in 2001 to NT $42.2 in 2002, about an NT $7 increase. In 2001, smokers 15 years old or older consumed an average 126.52 packs/person [ 14 ]. In 2002, the cigarette price elasticity became -0.5274, meaning that this price increase caused a reduction of cigarette consumption by 13.27 packs/person (10.5% per person) and a reduction of about 0.235 billion packs in the total consumption. Meanwhile, new cigarette consumption in 2002 was reduced to 2 billion packs for the population at and above the age of 15 in 2001. Provided there was a NT $16.8 tax on every pack of cigarettes, the tax revenue for the government would be 33.6 billion NT dollar. However, the tax has been in force for two years, and a significant reduction in consumption has been shown to date. Cigarette taxes accounted for 40% of the retail price in 2002. Although forty percent sounds high, this proportion is still rather low when, as mentioned earlier, comparing it with the 66% or more of the retail price going for cigarettes prices in high-income countries (with the notable exception of the United States)[ 9 ]. Consequently, cigarette prices in Taiwan are well below those of many high-income countries, who have seen significant reductions in cigarette consumption. Those successes certainly impose a pressure on the government to implement another tax increase in the existing Health and Welfare Tax. Inter-party negotiations at the Legislative Yuan resulted in changes to Tobacco and Liquor Tax Law which led to a NT $3 rise in the health tax levied on cigarettes, from NT$5 to NT$8 per pack. The cigarette industry is likely to pass the tax increase in the form of higher prices on to the consumer. A price increase of 3 NT per pack in cigarette would reflect a consumption reduction of 2.47 packs per capita, totaling 44.7 million packs, 2.2% per capita, in cigarette consumption. Cigarette consumption would be reduced to 2 billion packs (based on a population count of 2003), and the government tax revenue would be 33.46 billion, including the Health and Welfare Tax of 16 billion. We estimate that with a Health and Welfare Tax increase from 5 NT to 8 NT per pack, there would be a 6 billion NT increase in revenue from the Health and Welfare Tax. In 2000 and 2001, the cigarette price elasticities of the current smokers were -0.3134 and -0.3684, respectively. In 2002, it had reached its maximum of -0.5274, indicating that as cigarette prices increased, so did the price elasticity. Consumers responded to the higher prices by cutting consumption. Then in 2003, after Taiwan's accession to WTO, cigarette price elasticity then lowered to -0.309, indicating that the effect of a cigarette price hike can diminish over time. Two sets of previous data concerning the cigarette consumption, retail price and personal monthly income of the current smokers obtained during 2000–2001 and during 2002–2003, were made available to us. Using the OLS method and the rise of cigarette price in 2002 as the baseline, we computed the cigarette price and income elasticities for these two sets of data. Table 3 shows the differences in the overall cigarette price elasticity of the current smokers between before and after Taiwan's accession to WTO in 2002: before -0.4062 and after -0.3352. Our result clearly indicated that smokers were more responsive to the price after the cigarette price rose in 2002–2003. Yet, -0.4062 and -0.3352 also revealed that there was no big change in cigarette price elasticity before and after Taiwan's accession to WTO. The reason for this might be that the rise of average cigarette price was only NT $7 per pack. We speculate that a possible continuous and substantial rise in cigarette prices in the future might increase the overall price elasticity, which in turn could allow for a more effective use of the tax increases or price increases to control tobacco. Table 3 The estimated cigarette price and income elasticities of different types of current smokers during 2000–2001 and during 2002–2003 a 2000–2001 2002–2003 Characteristics Price elasticity Income elasticity Price elasticity Income elasticity Overall -0.3352 (-4.355)* 0.0055 (0.849) -0.4062 (-3.102)* 0.0174 (2.331)* Gender Male -0.3107 (-4.036)* 0.0020 (0.291) -0.3930 (-2.935)* 0.0194 (2.450)* Female -0.1223 (-0.312) -0.0206 (-0.820) -0.1406 (-0.251) -0.0476 (-1.903) Age 17–24 -0.4022 (-0.645) 0.0368 (1.151) -0.1057 (-0.144) 0.0420 (1.532) 25–34 -0.0528 (-0.274) -0.0038 (-0.227) 0.2300 (0.734) 0.0315 (1.822) 35–44 -0.1835 (-1.425) -0.0028 (-0.206) -0.2154 (-1.023) -0.0060 (-0.422) 45–54 -0.1540 (-1.087) 0.0048 (0.388) -0.4100 (-1.624) -0.0107 (-0.724) 55- -0.2453 (-1.073) -0.0080 (-0.608) -0.0475 (-0.118) 0.0008 (0.044) Education College and above -0.1070 (-0.514) -0.0133 (-0.584) -0.7007 (-2.047)* 0.0919 (4.148)* Senior high school -0.2772 (-2.273)* 0.0211 (1.825) -0.5369 (-2.703)* 0.0233 (2.069)* Junior high school -0.5766 (-4.093)* 0.0275 (2.552)* 0.1789 (0.833) 0.0279 (2.058)* Preliminary or lower 0.0560 (0.302) -0.0056 (-0.440) -0.0392 (-0.118) -0.0191 (-1.244) Month income No income -0.5103 (-2.193)* -0.8363 (-2.014)* <NT $20,000 -0.4570 (-2.373)* -0.7478 (-2.316)* NT $ 20,000–39,999 -0.4805 (-3.953)* -0.2861 (-1.345) NT $ 40,000–59,999 -0.1562 (-0.951) -0.2624 (-1.022) ≥ NT $ 60,000 0.2341 (1.050) -0.1152 (-0.301) Smoking degree Light smokers -0.1984 (-2.046)* 0.0087 (1.120) -0.5320 (-3.293)* 0.0172 (1.956) Medium smokers -0.0228 (-0.914) -0.0005 (-0.198) -0.2600 (-5.068)* -0.0046 (-1.514) Heavy smokers 0.2573 (1.973)* -0.0083 (-0.820) -0.0006 (-0.005) 0.0010 (0.137) a. t ratios are shown in parentheses. * p < 0.05. Cigarette price elasticity for the male smokers reached statistically significance (5%), which was higher than the price elasticity of the female smokers, indicating that men were more responsive to price elasticity than the women. The cigarette price elasticity of the male smokers in 2002–2003 was -0.393, which was higher than -0.3107 male smokers in 2000–2001. The income elasticity of male smokers in 2002–2003 was 0.0194, reaching statistical significance (5%). There was no statistical difference found in estimated cigarette price and income elasticity of smokers among the different age sub-groups, though, according to some reports in foreign countries, teenagers are more sensitive changes to cigarette prices than adults [ 15 - 17 ]. Education level seemed to make a difference. The price elasticity smokers with junior high school educations was -0.5766 in 2000–2001, which was higher than that of senior high school level smokers, -0.2772. In 2002-2003, the price elasticity of college level smokers was -0.7007, which was higher than that of the smokers of senior high school level, -0.5369. Therefore, between 2000 and 2001, the more educated group had a larger price elasticity, though the less educated group had the higher coefficient in 2002–2003. Our findings cover two time spans and are different from those reported by foreign researchers who have found that consumers at lower education levels respond stronger to the change of cigarette price [ 18 ]. In our study, those with no income had the greatest cigarette price elasticity, -0.5103 in 2000–2001 and -0.8363 in 2002–2003. Those with no income were more sensitive to the price rise than those with income. Light smokers had the highest cigarette price elasticity, -0.1984 in 2000–2001 and -0.532 in 2002–2003. Heavy smokers had a price elasticity of 0.2573 in 2000–2001, indicating that with the rise of cigarette price, these smokers increased their consumption of tobacco. Conclusions In this study, we evaluate the effect of a new tax on the consumption of tobacco by calculating the cigarette price elasticities of various kinds of smokers and comparing those values with their reactions to an increase cigarette, and then using knowledge gained from that study, we assess the possible effect of another increase on consumption. We found that the new tax scheme implemented after Taiwan joined the WTO reduced cigarette consumption by 13.27 packs/person (10.5%). We estimated that an additional NT $3 increase in Taiwan's Health and Welfare Tax would reduce cigarette consumption here by 2.47 packs/person (2.2%). In this study, cigarette price elasticity was less than one, meaning that in addition to reducing cigarette consumption, an additional tax would also generate additional tax revenues. Continuing price increases should reduce cigarette consumption significantly. Provided that the tax increases are proportionately larger than the resulting reduction in cigarette consumption, cigarette tax revenues will increase and can be used to reduce current National Health Insurance deficits and possibly reduce the damage and death caused by smoking related diseases. Based on estimated cigarette price elasticities for various kinds of current smokers, we found that male smokers without income and light smokers were more sensitive to changes in cigarette prices. Teenagers (17 – 24 years old), however, were not found to be significantly influenced by the change in cigarette price, which means it will take more than just tax increases to decrease consumption among our youth. Schools will need to commit to preventive education by inculcating the students with the knowledge of tobacco hazards. Only through early preventive education starting from their childhood can we expect to see significant reduction in cigarette consumption. Finally, the R-squared statistics of the each empirical estimation was below 0.1 for probably sake of to calculate elasticity and exclude variables like advertisement. Future research should also attempt to include these factors with cigarette demand function. Competing interests The author(s) declare that they have no competing interests. Authors' contributions JML performed physical measurements, collected data, and drafted the manuscript. TCH reviewed the manuscript. CYY and SHC carried out the statistical analysis and participated in data collection. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC539350.xml
534106	Healthcare professionals' perceptions of pain in infants at risk for neurological impairment	Background To determine whether healthcare professionals perceive the pain of infants differently due to their understanding of that infant's level of risk for neurological impairment. Method Neonatal Intensive Care Units (NICU's) at two tertiary pediatric centers. Ninety-five healthcare professionals who practice in the NICU (50 nurses, 19 physicians, 17 respiratory therapists, 9 other) participated. They rated the pain (0–10 scale and 0–6 Faces Pain Scale), distress (0–10), effectiveness of cuddling to relieve pain (0–10) and time to calm without intervention (seconds) for nine video clips of neonates receiving a heel stick. Prior to each rating, they were provided with descriptions that suggested the infant had mild, moderate or severe risk for neurological impairment. Ratings were examined as a function of the level of risk described. Results Professionals' ratings of pain, distress, and time to calm did not vary significantly with level of risk, but ratings of the effectiveness of cuddling were significantly lower as risk increased [ F (2,93) = 4.4, p = .02]. No differences in ratings were found due to participants' age, gender or site of study. Physicians' ratings were significantly lower than nurses' across ratings. Conclusion Professionals provided with visual information regarding an infants' pain during a procedure did not display the belief that infants' level of risk for neurological impairment affected their pain experience. Professionals' estimates of the effectiveness of a nonpharmacological intervention did differ due to level of risk.	Background Research on pain in infants has progressed considerably over the past twenty years. The nature and frequency of procedural pain in the neonatal intensive care unit (NICU) is now understood [ 1 ], many measures have been developed for assessment of acute pain in the NICU [ 2 ] and many pain interventions have now been evaluated [ 3 ]. However, much less is known about the pain experienced by neonates who are at risk for neurological impairment (NI), as most studies of neonatal pain have either excluded this group or have not examined data specific to them within larger data sets. We do know that this group represents approximately 10% of infants admitted to the Neonatal Intensive Care Unit [ 4 ] and that they experience more painful procedures in the NICU during the first days of life than infants who are not at risk for NI [ 5 ]. It also appears this vulnerable group may be particularly susceptible to potential long-term negative consequences of pain because of their neurological fragility, concomitant illnesses, and repeated exposure to painful stimuli [ 6 ]. The crucial first step of pain management is pain assessment. Without a valid and reliable approach to assessing pain, and the demonstrated efficacy of interventions for pain, decisions about pain management may not improve care. However, even with valid, reliable pain assessment tools, the characteristics of healthcare providers may affect ratings provided by them. These characteristics can include the healthcare providers' views of pain interventions [ 7 ], lack of awareness of advances in pain management [ 8 ], and use of pain cues that are not reliable [ 9 ]. The present study was designed to move beyond self-report of beliefs to examine whether healthcare professionals' judgments of pain in neonates are affected by their perception that a neonate has mild, moderate or severe risk for neurological impairment. Research in this area is only emerging, but has important implications for how healthcare professionals deliver care to this vulnerable population. In a previous study using questionnaires, we found that caregivers of children with severe cognitive impairment view the pain of children with more severe impairment as reduced [ 10 ]. A second study using the same questionnaire with healthcare professionals and students revealed a similar pattern of beliefs [ 11 ]. Most recently, we adapted that questionnaire to assess the beliefs of healthcare professionals' regarding the pain of infants with varying degrees of risk for neurological impairment and again found that those who took part believed that the degree of pain experienced decreases as risk for neurological impairment increases [ 12 ]. These studies suggest that those who manage the pain of infants at risk for, or children with, intellectual deficits believe that pain is less for those at greater risk or who have greater impairment. These results may explain why we also found infants at risk for neurological impairment receive less pain treatment in the NICU [ 13 ]. However, to extrapolate from questionnaires to clinical behaviour can be problematic. Thus, the current study was designed as a step to linking these two sets of results. Specifically, we felt it was important to know if professionals' beliefs about pain in this group influence their assessment of infants' pain, which could lead to those infants' being provided with less pain treatment. As with any experimental study, the circumstances could not completely replicate those in a clinical setting. For example, the participants would not have access to physiological data or to the infants' recent history of pain. However, we hypothesized that the participants in this study would rate the pain lower for infants described as having greater risk for neurological impairment, corresponding with the beliefs expressed in our three previous studies. Methods Participants One hundred and one healthcare professionals, with at least one year of experience working with infants with neurological impairment in the NICU, were recruited from two tertiary level university affiliated NICU settings in central and eastern Canada. They were recruited through information provided by the research nurses and notices posted within their centers. Each participant was paid a small honorarium for their participation, and all provided informed consent. The study was approved by each health centre's Research Ethics Board. Materials Demographic information Participants completed a questionnaire that requested information regarding their age, gender, education and work experience. Video clips Nine video clips were viewed by each participant. The 30 second video clips depicted term and preterm neonates of Caucasian descent experiencing a heel stick and squeezing for blood collection. Video clips were of the infants' faces only, with most lying on their sides and all bundled. Audio was not included. Prior to each videoclip, a verbal description of the neonate suggesting he/she was at mild, moderate or severe risk for neurological impairment was provided to the participant. These descriptions had been previously recorded on audio tape by a researcher to ensure each participant was read the description in an identical fashion. Descriptions were counterbalanced such that each videoclip was described for some participants as having either mild risk, moderate risk, or severe risk within each of two orders of presentation. Thus, each participant viewed three infants that were described as having mild, moderate or severe risk for neurological impairment, but the level of risk, and the order in which the clips were presented varied. Examples of the descriptions provided to participants are shown in Table 1 . Table 1 Sample descriptions of infants viewed on videotape provided Mild Risk Moderate Risk Severe Risk Brianna is 6 days old and has been treated for neonatal jaundice. She will make a complete recovery. Otherwise she is healthy. Samuel was born 4 weeks prematurely and was mildly asphyxiated at birth because the cord was wrapped around his neck during delivery. An MRI shows a small area of damage in the brain. Matthew was born with a serious metabolic condition which caused significant brain damage. He will likely not survive past 2 years of age. Jason was born prematurely and is gaining weight slowly. He is now one month old. He suffered a unilateral Grade I bleed in his brain and will likely have no permanent damage from that. Matthew was born with a serious metabolic condition which caused moderate brain damage. With the aid of a special diet, he will develop fairly well but will likely have significant learning disabilities. Samuel was born 4 weeks prematurely and was severely asphyxiated at birth because the cord was wrapped tightly around his neck at delivery. An MRI shows extensive damage throughout the brain. Ratings of pain and distress Participants rated the pain of infants shown on videotape from 0 (no pain) to 10 (extreme pain). They also rated each infant's pain using a Faces Pain Scale (0 = no pain, 6 = extreme pain). These measures were chosen because they are easy to use and were feasible for this experimental task. Although many validated measures of neonatal pain exist, these are multidimensional in nature. As such, they require the person using them to have access to information regarding the infant's physiological status, something we were unable to provide in the context of this task. The 7 face scale [ 14 ], was included to allow a check of the validity of the 0–10 pain rating, since the latter is not commonly used in clinical neonatal settings. The Faces Pain Scale is also not typically used in a neonatal setting, but research indicates most adults find it easy to use [ 15 ], making it a useful check of participants' 0–10 pain ratings. Preliminary analyses indicated there was a significant relationship, similar to results for reliability computed for other sets of observational pain tools used in pediatric research [ 16 ], between 0–10 pain ratings and Faces Pain Scale ratings for infants at mild ( r = .74), moderate (. r = .56) and severe risk for neurological impairment ( r = .60). Ratings of cuddling and calm Participants provided a rating of how effective they believed a behavioural intervention (i.e. cuddling) would be for minimizing the procedural pain for each infant (0 = no effect, 10 = very effective) and of how long (seconds) they believed it would take each infant to calm without intervention. Ratings of risk for neurological impairment To ensure that the descriptions provided were valid depictions of infants at each level of risk and were understood and accepted by participants, participants were asked to rate the level of risk they believed each infant had for future neurological impairment (0 = no risk, 10 = certain impairment). Procedure Participants took part in small groups of 5 to 6 professionals that were randomly assigned to one of the two orders of presentation. They completed the demographic questionnaire and the rating tasks were explained to them. They were then shown the nine video clips. After each videoclip was viewed, the participants were provided with time to make their independent ratings for that videoclip before the next was shown. Participants were not permitted to interact with each other until all tapes had been viewed and rated. After ratings were complete, they were debriefed regarding the purpose of the study and a discussion of their experience was facilitated by the research assistant. Preliminary analyses Exclusions due to missing data Preliminary analyses indicated that two participants were missing more than 10% of ratings. As per an a priori decision as to how to handle missing data, their data were excluded from further analyses. The remaining 99 participants were missing 0% ( n = 88) to 7% ( n = 1) of responses ( M = 0.2, SD = 0.6). Exclusions due to presentation order effects A 2 (group) X 6 (rating) Repeated Measures Analysis of Variance (RM ANOVA) was conducted on the six ratings provided by participants who viewed the tapes in the two orders to determine whether order of presentation had affected ratings. This analysis revealed a significant effect of order of presentation [ F (1,97) = 4.4, p = .04). A more detailed look at the data using stem and leaf plots revealed 4 participants in one group had extreme scores for ratings of Time to Calm ( M = 192.8, SD = 39.2) relative to the other participants in that group ( M = 37.4, SD = 28.7). The data of these four participants were removed. A second RM ANOVA revealed no significant effect due order of presentation of the video clips [ F (1,93) = 1.7, p = .20). Thus, 95 professionals formed the final sample for the study. Manipulation check To determine if the descriptions provided to the participants were effective in leading them to believe the infants viewed had mild, moderate or severe risk for neurological impairment, each participant's mean rating for degree of risk for future impairment for the infants they were told had a mild (3), moderate (3) or severe risk (3) for impairment were computed. These ratings were then compared using a RM ANOVA. There was a significant difference in the ratings provided to those clips described as having mild ( M = 3.8, SD = 2.8), moderate ( M = 4.9, SD = 2.0) and severe risk ( M = 6.1, SD = 2.8; F (2, 93) = 13.9, p < .001). Post-hoc paired t-tests indicated these differences were significant between infants described as having mild and moderate risk ( t ((94) = -3.2, p = .002), mild and severe risk ( t ((94) = -4.8, p < .001), and moderate and severe risk ( t ((94) = -5.0, p < .001), Thus, participants believed the infants had different levels of risk when they provided ratings for the video clips. Statistical procedures The data were analyzed using SPSS Version 10.0.7 [ 17 ]. Power computations were completed using Sample Power 1.2 [ 18 ] or based on tables prepared by Stevens [ 19 ]. Alpha was set at .05 for all tests and Bonferroni corrections were applied to sets of post hoc matched sample t-tests to maintain alpha at .05 for each set. Because the corrected p values varied with the number of tests in each set, raw p values are reported. Wilks Lambda was used to test significance for all RM ANOVA's. There was .80 power or greater to detect medium size effects using repeated measures analyses with 3 to 5 levels of factors and greater than .99 power to detect medium size differences in means using matched sample t-tests. Power was .86 to detect a significant medium size correlation between ratings and years of experience. Descriptive statistics Descriptive statistics were generated for the demographic characteristics of the participants (Table 2 ) and for the ratings provided for each set of video clips (Table 3 ). Table 2 Characteristics of the participants (N = 95) Characteristic n % Site Toronto 46 48 Halifax 49 52 Profession Nurse 50 53 Physician 19 20 Respiratory Therapist 17 18 Occupational Therapist 2 2 Physiotherapist 2 2 Psychologist 1 1 Other Clinician 4 4 Gender Female 82 86 Age 20–30 years 19 20 31–35 years 15 16 36–40 years 32 34 41–45 years 11 12 46 years or more 18 19 Note. Percentages rounded. Table 3 Mean ratings given to infants described as at risk for mild, moderate or severe risk for neurological impairment (N = 95) Rating Mild Risk Moderate Risk Severe Risk M SD M SD M SD Pain (0–10) 6.3 1.7 6.6 1.7 6.2 1.6 Faces pain Scale (0–6) 4.7 1.0 4.8 0.8 4.8 1.0 Distress (0–10) 6.1 1.7 6.5 1.5 6.3 1.6 Effectiveness of Cuddling (0–10) 7.0 2.1 7.1 1.9 6.5 2.2 Time to calm (Seconds) 35.2 34.8 34.9 28.3 32.8 31.8 Effect of risk for neurological impairment on ratings To compare the ratings provided for the 9 video clips, a 3 (level of risk) X 5 (rating type) RM ANOVA was conducted on the scores of the 95 participants. This was followed by 5 one-way RM ANOVA's on each rating (0–10 pain rating, Faces Pain Scale rating, distress rating, effectiveness of cuddling rating, time to calm) and matched sample t-tests on ratings when the one-way ANOVA was significant. Effect of participants' characteristics on ratings The effect of participants' characteristics on ratings was examined using Mixed Measures ANOVA's on the five ratings at three levels of risk. The first three included Gender, Age, and Site (Toronto, Halifax) as between-subjects effects. The fourth included three levels of profession (i.e. staff nurse, physician, respiratory therapist) as the between-subjects effect. Other professionals were not included due to small numbers. The relation between the participants' years of experience in a neonatal setting and their ratings were investigated using Pearson Correlations. Results Participants The characteristics of the participants are displayed in Table 2 . The majority were nurses and the number of years experience in a neonatal setting ranged from 1.5 to 36 years ( M = 11.8, SD = 7.7). The 50 nurses included staff nurses ( n = 34), advanced practice nurses ( n = 9) and nurse managers/educators ( n = 7). The physicians specialized in neonatology ( n = 10), neurology ( n = 4), pediatrics ( n = 3) and other specialties ( n = 2). Six of the 19 physician participants were residents or fellows. Additional professions are listed in Table 2 . Effect of risk for neurological impairment on ratings The mean ratings provided for video clips of infants described as having mild, moderate or severe risk for neurological impairment are depicted in Table 3 . The RM ANOVA on the five ratings revealed a nonsignificant effect of Level of Risk [ F (2,93) = 0.6, p > .05], a significant effect of Rating [ F (4,91) = 91.6, p < .001] and a significant interaction between the two [ F (8,87) = 3.4 p = .002]. Thus, there was no overall effect due to the level of risk described, but level of risk described did affect some ratings. One-way RM ANOVA's revealed Level of Risk had a marginal effect on participants' ratings of pain on the 0–10 scale [ F (2,93) = 2.9, p = .06] and a significant effect on ratings of the perceived effectiveness of cuddling [ F (2,93) = 4.4, p = .02], but nonsignificant effects on Faces Pain Scale ratings [ F (2,93) = 0.3, p = .70], distress [ F (2,93) = 2.2, p = .12] and time to calm [ F (2,93) = 0.4, p = .65]. As Table 3 shows, there was a slight tendency for participants to rate pain lower for infants who were described as having greater risk for impairment. Participants did believe cuddling would be less effective when risk for neurological impairment was greater. Ratings of the effectiveness of cuddling were significantly lower for infants described as at high risk than they were for those described as at mild risk [ t (94) = 2.5, p = .01] or moderate risk [ t (94) = 3.0, p = .004]. The difference in ratings between those described as at mild or moderate risk were nonsignificant [ t (95) = -0.2, p = .77]. Thus, participants believed that beyond a moderate level of risk, the effectiveness of cuddling dropped significantly. In summary, participants did not view the pain of the infants as varying due to level of risk for neurological impairment. Nor did they perceive the distress or time to calm after pain as differing between groups of infants described as having mild, moderate or severe risk for neurological impairment. However, they did perceive that cuddling would be less effective as an intervention for infants with high risk, than for those with mild or moderate risk of neurological impairment. Effect of participants' characteristics Site, gender and age Three Mixed Measures ANOVA's were used to examine the effect of participants' characteristics on the five ratings ratings. The first result indicates a nonsignificant main effect of Site [ F (1,93) = 0.7, p = .39], the second revealed a nonsignificant main effect of Gender [ F (1,93) = 0.9, p = .34], and the third indicated Age also did not significantly effect ratings on the five measures [ F (4,90) = 0.2, p = .95]. Thus, participants' ratings did not vary due to their institution, gender or age. Profession To examine the effect of participants' profession on their ratings, three groups were included in a Mixed Measures ANOVA: staff nurses (n = 34), physicians (n = 11), and respiratory therapists (n = 17). Residents and Fellows, Nurse Managers and Educators and Specialists, and other professionals were not included due to small numbers in those groups. The analysis revealed a significant main effect of Rating Scale [ F (4,56) = 3.9, p = .001]. However, the main effect of Level of Risk was nonsignificant and the main effect of Profession only approached significance [ F (2,59) = 2.7, p = .07]. Participants' ratings were not affected by their professional background. The interaction between Rating and Level of Risk was significant [ F (8,52) = 36.6, p < .001], but all other interactions were nonsignificant. Games-Howell post-hoc comparisons revealed a significant difference in the ratings provided by staff nurses and physicians ( p = .004) and a difference between respiratory therapists and physicians that approached significance ( p = .06). As shown in Table 4 , Nurses' ratings did not appear to differ greatly due to level of risk for impairment, while Physicians' showed a tendency to rate all aspects of the experience higher as level of risk increased, and respiratory therapists tended to provide lower ratings as the infants' level of described risk for neurological impairment increased. Table 4 Mean pain, distress, effectiveness of cuddling and time to calm scores given to infants described as at risk for mild, moderate or severe risk for neurological impairment by physicians and other clinicians Rating Level of Risk Staff Nurses (n = 34) Physicians (n = 11) Respiratory Therapists (n = 17) M SD M SD M SD 0 – 10 Pain rating Mild 6.4 1.6 4.8 2.3 6.9 1.3 Moderate 6.9 1.5 5.6 2.4 6.9 1.8 Severe 6.4 1.7 5.8 2.1 5.8 1.6 Faces pain rating (0–6) Mild 4.6 1.0 3.7 0.8 5.3 0.6 Moderate 4.9 0.7 4.8 0.6 4.9 1.1 Severe 4.9 1.0 5.4 0.6 4.3 1.3 0 – 10 Distress rating Mild 6.4 1.6 4.3 2.1 6.9 1.3 Moderate 6.8 1.3 5.6 2.2 6.8 1.9 Severe 6.4 1.6 6.3 1.9 5.4 1.6 0–10 Effectiveness of cuddling rating Mild 6.4 1.6 4.3 2.1 6.9 1.3 Moderate 7.2 2.0 6.9 1.9 6.5 2.4 Severe 6.6 2.3 5.8 2.6 4.9 2.1 Time to calm estimate (seconds) Mild 40.0 36.1 14.9 15.5 46.8 43.8 Moderate 39.8 28.9 18.4 13.8 42.2 35.4 Severe 40.5 40.3 23.3 15.7 31.3 33.0 Professional experience Eighty-nine participants provided information regarding their amount of professional experience. Correlations indicated that years of experience were not correlated significantly with any of the five ratings provided after corrections for multiple tests. Thus, the importance of an infants' level of risk for neurological impairment was neither greater nor less as experience in this setting increased. Discussion Overall, the professionals in this study did not rate the pain of neonates differently when provided with information indicating those infants had mild, moderate or severe risk for neurological impairment. The professionals' perception of the infants' level of risk also did not affect their ratings of the infants' distress, or their belief in how long the infant would take to calm after pain without intervention. Professionals did perceive that cuddling would be significantly less effective for infants at high risk for neurological impairment than for infants with mild or moderate impairment. However, this effect was not large, and, although it was statistically significant, it may be spurious. Further research should examine whether beliefs regarding pain experience in this group and beliefs regarding the effectiveness of cuddling and other nonpharmacological interventions are truly independent. These results are inconsistent with the results of our previous questionnaire study indicating professionals, with similar levels of experience in neonatal intensive care settings, perceive the pain experience of infants as reduced as their level of risk for neurological impairment increases [ 12 ]. There are several possible reasons for these discrepant results. The professionals who participated in this study were asked to rate the risk for neurological impairment of each infant they viewed on videotape. Asking them to do this may have alerted them to the purpose of the study and elicited efforts on their behalf to provide ratings that were unbiased. However, their ratings of the perceived effectiveness of cuddling did vary by level of risk for impairment, suggesting attempts to appear unbiased do not fully explain the results found. In our previous studies, questionnaires elicited beliefs about the pain experience of infants and children with varying levels of risk relative to the pain experience of those without risk [ 10 - 12 ]. In contrast, no infants in the current study were described as having no risk for neurological impairment. This was because the infants' appearance made it apparent that they were not healthy full-term infants. It may be that the comparative nature of the questions in the previous studies made the possibility of differences in pain experience due to neurological risk more salient to participants. Thus, the pain ratings provided here did not differ among levels of risk, but had ratings of healthy infants been included in the task, they may have differed significantly from them. It is also possible that the beliefs expressed by professionals in our previous study [ 12 ] do not moderate professionals' behaviour in relation to pain assessment for specific infants, as was found here. A discordance between expressed beliefs and behaviour, in regard to pediatric pain management, has been reported elsewhere [ 20 , 21 ]. Thus, the professionals here may hold similar beliefs to the professionals in our previous study, but these beliefs did not alter their behaviour when asked to judge pain in a specific infant based on observable behaviour. This interpretation is supported by the current results because no differences were found due to level of risk for ratings that the professionals could base on behaviour they observed on the video clips: pain, distress, time to calm. In contrast, professionals' judgments of the effectiveness of cuddling were influenced by the descriptions of the infants' level of risk for neurological impairment. This may be because there was no visual information to base this rating upon, so professionals used the descriptions of risk provided, presumably in light of their previous experience with these groups in the neonatal setting. The finding that pain ratings did not vary due to level of risk for neurological impairment raises questions about our previous study that revealed infants at risk for neurological impairment receive less pain treatment in the NICU [ 13 ]. When a group is provided less medication for pain, it is typically assumed that this is because their pain was judged as less. However, it is possible that professionals hold beliefs about pain treatment that directly impact upon treatment decisions, irregardless of pain assessment. For example, they may hold beliefs about the appropriateness of medication for specific groups that are unrelated to beliefs about the amount of pain that group experiences. In support of this perspective, research indicates that nurses hold negative attitudes towards pharmacological treatment for pain [ 7 ] and that steps to improve pain assessment do not necessarily result in changes in pain management [ 22 ]. Further research is needed to reconcile the current results with beliefs that risk for neurological impairment does affect pain experience expressed by a similar group of professionals in our previous survey [ 12 ] and the results of our study indicating procedural pain is not treated as frequently for infants in the NICU who have greater risk for neurological impairment [ 13 ]. If this reflects a disconnect between pain beliefs related to assessment and those related to treatment for infants at risk for neurological impairment, then educational interventions aimed at improving care through changes in pain assessment may be ineffective. In that case, other avenues to changing professionals' pain management for this group should be explored. Another finding in this study warrants discussion. Professionals' judgments of the effectiveness of cuddling decreased with increasing risk for neurological impairment, despite their having judged pain as similar in intensity. This result is similar to a finding by Fanurik et al. [ 23 ]. They found nurses, but not physicians, responding to vignettes of children undergoing painful procedures, indicated nonpharmacological interventions would be less appropriate as level of cognitive impairment increased. The same professionals' ratings of the pain intensity experienced by the children in that study did not differ due to perceived level of cognitive impairment. The current results, along with those of Fanurik's group [ 23 ], raise the question of whether professionals perceive the pain experienced by those at risk for or with neurological impairment as similar in intensity, but differing in quality from those at lesser risk. Because the current study elicited ratings only of the intensity of pain and distress and professionals were not asked about the nature of the pain the infants experienced, the results cannot confirm this possible explanation, as data regarding pain quality was not collected. However, professionals in our survey study differentiated between physiological aspects of pain and internal and external responses to pain, such as emotional reaction, behavioural reaction and communication of pain [ 12 ]. They also believed the experience of infants at greater risk was more reduced along the latter aspects that are more psychological in nature. Caregivers' have expressed similar beliefs, and also perceived the behaviour of children with more severe impairment is more closely related to their physiological pain experience [ 10 ]. From this finding, we could suggest that there is a belief, on the part of professionals and caregivers, that the pain behaviour of those at greater risk for, or with, neurological impairment is more reflexive in nature. We could further speculate that the underlying rationale may be that they are seen as less able to interpret their pain, both cognitively and emotionally, due to their neurological impairment. However, we would need to conduct further research to substantiate this rationale. If professionals and caregivers do believe pain behaviour is more reflexive, and that pain experience is more physiologically based when a child has neurological impairment, it could explain the current results regarding the effectiveness of cuddling. Professionals viewing the video clips may have perceived the behavioural responses of the infants with different levels of risk for impairment as being similar in intensity. Nonetheless, they may have interpreted the behaviour of those with more risk as more of a reflexive response to a physiological insult, while they saw the behaviour of those with lesser risk as reflecting a more multidimensional pain experience incorporating both physical and psychological suffering. Thus, we could again speculate that they may have felt cuddling, an intervention that would address physical and psychological aspects of pain, would be more effective for the less impaired groups. This phenomenon would not be novel or unique. For most of recorded history, there has been a belief that cognitive interpretation of pain was necessary for pain to result in long-term negative consequences. This belief was often the justification for poorer pain management for both children and infants [ 24 ]. Although this belief is fading in regard to children and infants in general, it is still held in relation to those who are most severely at risk for, or have neurological impairment, and are perceived as least capable of interpreting their pain. Alternatively, this belief may be based on the actual experience of professionals in this study, that it is more difficult to calm an infant at risk for neurological impairment. This experience may also be an accurate perception of the difficulty infants at greater risk for impairment may have in responding to behavioural interventions because of their reduced ability to organize behavioural state and biobehavioural responses. Further research should examine these areas of speculation to specifically determine whether the perception that a behavioural intervention will be less effective for infants at greater risk for neurological impairment does reflect professionals' direct experience with this group or their understanding of how the pain experience may be affected by neurological impairment that may affect pain interpretation. The current study has several limitations. Professionals were asked to rate the pain experience of infants receiving heel sticks from videotape. Although this may approximate the real situation in a NICU setting, it is not identical. In a NICU setting, professionals would have rich information from the environment, previous contact with an infant, physiological data, and medical records that guide their assessment of pain. They would also view this infant within the context of all other infants in the unit. Professionals here were also asked only to provide ratings of pain intensity. As the results suggest, this is only one dimension of pain and may not be the dimension that plays the largest role in their judgments regarding pain in a clinical setting. The professionals here were experienced in the types of pain experienced in the NICU and may have held a priori beliefs about the painfulness of this procedure that moderated their judgments. Research suggests professionals' beliefs regarding the painfulness of a procedure play a large role in their assessments of children's pain [ 7 , 9 , 25 ]. Conclusions The current study indicates professionals' perception of the pain intensity of infants does not differ due to their understanding of the infants' level of risk for neurological impairment. Professionals also view cuddling as less effective for infants at greater risk for neurological impairment. Further research is needed to examine the reasoning behind the judgments made by healthcare professionals and to clarify why they might view an intervention as less effective for infants with greater risk of neurological impairment, despite having rated their pain intensity as similar to that of infants at lesser risk. Competing interests The authors declare that they have no competing interests. Authors' contributions The study was conceived and designed by BS, PM & LB with assistance from all remaining authors. The study was conducted under the supervision of PM, BS, KO, AO. Statistical analyses were conducted by LB, with assistance from PM, BS and JB. Interpretation of results were conducted by LB, PM, BS, JB, CC, LF, KB and AO. The manuscript was prepared by LB, and edited by PM and BS, with review and assistance from all remaining authors. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC534106.xml
533858	Models of chronic obstructive pulmonary disease	Chronic obstructive pulmonary disease (COPD) is a major global health problem and is predicted to become the third most common cause of death by 2020. Apart from the important preventive steps of smoking cessation, there are no other specific treatments for COPD that are as effective in reversing the condition, and therefore there is a need to understand the pathophysiological mechanisms that could lead to new therapeutic strategies. The development of experimental models will help to dissect these mechanisms at the cellular and molecular level. COPD is a disease characterized by progressive airflow obstruction of the peripheral airways, associated with lung inflammation, emphysema and mucus hypersecretion. Different approaches to mimic COPD have been developed but are limited in comparison to models of allergic asthma. COPD models usually do not mimic the major features of human COPD and are commonly based on the induction of COPD-like lesions in the lungs and airways using noxious inhalants such as tobacco smoke, nitrogen dioxide, or sulfur dioxide. Depending on the duration and intensity of exposure, these noxious stimuli induce signs of chronic inflammation and airway remodelling. Emphysema can be achieved by combining such exposure with instillation of tissue-degrading enzymes. Other approaches are based on genetically-targeted mice which develop COPD-like lesions with emphysema, and such mice provide deep insights into pathophysiological mechanisms. Future approaches should aim to mimic irreversible airflow obstruction, associated with cough and sputum production, with the possibility of inducing exacerbations.	Introduction The global burden of disease studies point to an alarming increase in the prevalence of chronic obstructive pulmonary disease (COPD) [ 1 ] which is predicted to be one of the major global causes of disability and death in the next decade [ 2 ]. COPD is characterized by a range of pathologies from chronic inflammation to tissue proteolysis and there are no drugs specifically developed for COPD so far. Cessation of cigarette smoking is accompanied by a reduction in decline in lung function [ 3 ] and is a most important aspect of COPD management. The mainstay medication consists of beta-adrenergic and anticholinergic bronchodilators; addition of topical corticosteroid therapy in patients with more severe COPD provides may enhance bronchodilator responses and reduce exacerbations [ 4 ]. In contrast to the large amount of experimental studies on allergic asthma and the detailed knowledge that exists on mediators of allergic airway inflammation [ 5 , 6 ], much less has been conducted for COPD. More effort and resources have been directed into asthma research in comparison to COPD. The available insights into the pathogenesis and pathophysiology of asthma may help to improve research in COPD [ 7 ]. Many research centres that previously focused on asthma now also investigate mechanisms of COPD. Using molecular and genetic approaches, an increasing range of molecules has been identified that could underlie the pathogenic inflammation of chronic allergic airway inflammation [ 8 ]. Based on these findings and on new ways of administering drugs to the lungs [ 9 ], a new image of overwhelming complexity of the underlying pathophysiology of COPD has emerged (Figure 1 ). The current challenge in COPD research is to identify the role of the various mediators and molecular mechanisms that may be involved in its pathophysiology, and obtain new treatments. In addition, it is incumbent to understand the effect of smoking cessation on the pathogenetic process. Figure 1 Potential pathogenetic mechanisms involved in COPD Exogenous inhaled noxious stimuli such as tobacco smoke, noxious gases or indoor air pollution and genetic factors are proposed to be the major factors related to the pathogenesis of COPD. These factors may influence protease activity and may also lead to an imbalance between pro-inflammatory and anti-inflammatory mediators. Studying the molecular pathways in human subjects is restricted to the use of morphological and molecular assessment of lung tissues obtained at surgery or performing limited in vitro studies at one single point in time [ 10 ]. There is a need for in vivo animal models to examine more closely pathogenesis, functional changes and the effects of new compounds or treatments. However, animal models have limitations since there is no spontaneous model, and models do not necessarily mimic the entire COPD phenotype. The best model remains chronic exposure to cigarette smoke, since this is the environmental toxic substance(s) that cause COPD in man. However, other substances are also implicated such as environmental pollution due to car exhaust fumes. The present review draws attention to specific aspects of functional and structural features of COPD that need to be realized when interpreting molecular mechanisms identified in animal models of COPD. It identifies important issues related to the ongoing experimental COPD research which may in the future provide optimized COPD diagnosis and treatment. COPD Clinical features Before characterizing and discussing the different animal models of COPD which have been established so far, it is crucial to reflect that within COPD, different disease stages exist and that only some of them may be mimicked in animal models. The diagnosis of COPD largely relies on a history of exposure to noxious stimuli (mainly tobacco smoke) and abnormal lung function tests. Since COPD has a variable pathology and the molecular mechanisms are only understood to a minor extent, a simple disease definition has been difficult to establish. However, the diagnosis of COPD relies on the presence of persistent airflow obstruction in a cigarette smoker [ 4 ]. A classification of disease severity into four stages has been proposed by the GOLD guidelines based primarily on FEV1 [ 4 ]. The staging on the basis of FEV1 alone as an index of severity for COPD has been criticised. A composite measure essentially based on clinical parameters (BODE) has been shown to be better at predicting mortality than FEV1 [ 11 ]. The natural history of COPD in terms of evolution of FEV1 remains unclear and the temptation is to regard the stages as evolving from Stage 0 to Stage 4. Just as many smokers do not develop COPD, it is possible that the disease may not progress from one stage to the next. Some patients with severe COPD are relatively young and it is not clear if early stages of their disease are similar to those found in patients with mild COPD. COPD is a heterogeneous disease and different possible outcomes may occur at each of the stages. Experimental modeling of each stage of severity may be a way of providing an answer to this issue. Animal models may also help to provide a better classification of severity by correlating biochemical, molecular and structural changes with lung function and exercise tolerance. Pathophysiology The presence of airflow obstruction which has a small reversible component, but which is largely irreversible is a major feature of COPD as indicated by the Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines [ 4 ]. It is proposed to be the result of a combination of small airways narrowing, airway wall inflammation [ 12 ] and emphysema-related loss of lung elastic recoil [ 13 , 14 ]. These features differ to a large extent to findings observed in bronchial asthma (Table 1 ) where airflow obstruction is usually central, while involvement of the small airways occurs in more severe disease. The degree of airflow obstruction in COPD can be variable, but loss of lung function over time is a characteristic feature. Ideally, the development of airflow obstruction which is largely irreversible but has a small reversible component should be a feature of animal models of COPD, but this has not been reproduced so far. One of the important limitations of animal models of COPD is the difficulty in: reproducing small airways pathology particularly when working in small animals, particularly the mouse and rat where there are few levels of airway branching. This is a problem inherent to small laboratory animal models but provides an advantage for developing models in larger animals such as the pig or sheep. Part of the problem of analyzing small airways is also due to the lack of sophistication of lung function measurements, particularly in mice, but there has been recent development in the methodology of lung function measurement [ 15 ]. A new ex-vivo method of analyzing the airway periphery is by the technique of precision cut lung slices combined to videomorphometry [ 16 , 17 ]. Table 1 Currently known phenotype differences between COPD and asthma Feature COPD Asthma Limitation of Airflow Largely irreversible Largely reversible Parenchymal integrity destruction intact Bronchial Hyperresponsiveness Variable (small) significant Steroid response reduced or absent present In addition to pulmonary alterations, other organ systems may be affected in COPD [ 18 ]. Systemic effects of COPD include weight loss, nutritional abnormalities and musculoskeletal dysfunction. These systemic manifestations will gain further socioeconomic importance with an increasing prevalence of COPD in the next years [ 19 ]. Therefore, these systemic effects should be present in animal models of COPD and further analysis of mechanisms underlying these systemic effects in experimental models may help to optimize disease management. Inflammatory cells An important feature of COPD is the ongoing chronic inflammatory process in the airways as indicated by the current GOLD definition of COPD [ 4 ]. There are differences between COPD and asthma: while mast cells and eosinophils are the prominent cell types in allergic asthma, the major inflammatory cell types in COPD are different (Table 2 ) [ 20 - 22 ]. Table 2 Differences in inflammatory cells between COPD and asthma. Ranked in relative order of importance. COPD Asthma Neutrophils Eosinophils Macrophages Mast cells CD8-T-lymphocytes CD4-T-lymphocytes Eosinophils (exacerbations) Macrophages, Neutrophils Neutrophils play a prominent role in the pathophysiology of COPD as they release a multitude of mediators and tissue-degrading enzymes such as elastases which can orchestrate tissue destruction and chronic inflammation [ 8 , 23 ]. Neutrophils and macrophages are increased in bronchoalveolar lavage fluid from cigarette smokers [ 24 ]. Patients with a high degree of airflow limitation have a greater induced sputum neutrophilia than subjects without airflow limitation. Increased sputum neutrophilia is also related to an accelerated decrease in FEV 1 and sputum neutrophilia is more prevalent in subjects with chronic cough and sputum production [ 25 ]. The second major cell type involved in cellular mechanisms are macrophages [ 26 ]. They can release numerous tissue-degrading enzymes such as matrix metalloproteinases (MMPs). In an animal model of tobacco smoke-induced tissue matrix degradation, not only neutrophil enzymes but also macrophage-derived enzymes such as MMP-12 are important for the development of emphysema-like lesions [ 27 ]. A further key enzyme is the macrophage metalloelastase which was reported to mediate acute cigarette smoke-induced inflammation via tumor necrosis factor (TNF)-alpha-release [ 28 ]. Neutrophils and macrophages can communicate with other cells such as airway smooth muscle cells, endothelial cells or sensory neurons, and release inflammatory mediators that induce bronchoconstriction [ 29 ], airway remodelling [ 30 ], and mucin gene induction and mucus hypersecretion involving the induction of mucin genes [ 31 - 33 ]. Lymphocytes are also involved in cellular mechanisms underlying COPD [ 34 , 35 ]. Increased numbers of CD8-positive T-lymphocytes are found in the airways of COPD patients [ 21 , 22 ] and the degree of airflow obstruction is correlated with their numbers [ 36 ]. However, the T-cell associated inflammatory processes largely differ from those in allergic asthma, which is characterized by increased numbers of CD4-positive T-lymphocytes [ 7 , 37 ] (Table 2 ). Although eosinophils may only play a major role in acute exacerbations of COPD [ 38 ], their presence in stable disease is an indicator of steroid responsiveness [ 39 - 41 ]. Different inflammatory cell types have also been characterized in airway tissues. Epithelial neutrophilia has been seen in proximal and distal airways of patients with COPD [ 42 , 43 ]. The airway wall beneath the epithelium shows a mononuclear inflammation with increased macrophages and T cells bearing activation markers [ 20 , 36 ] Di Stefano 1996;. An excess od CD8+ T cells are particularly observed in central airways, peripheral airways and parenchyma [ 20 , 43 ]. In the small airways from patients with stage 0 to (at risk) stage 4 (very severe) COPD, the progression of the disease is strongly associated with the accumulation of inflammatory exudates in the small airway lumen and with an increase in the volume of tissue in the airway wall [ 10 ]. Also, the percentage of airways containing macrophages, neutrophils, CD4 cells, CD8 cells, B cells, and lymphoid follicle aggregates and the absolute volume of CD8+ T-cells and B cells increased with the progression of COPD [ 10 ]. The changes are also most likely associated with an induction of mucin gene expression [ 44 ]. The presence of increased numbers of B cells begs the question regarding the role of these cells in the pathophysiology of COPD. In the airway smooth muscle bundles in smokers with COPD, increased localisation of T- cells and neutrophils has been reported, indicating a possible role for these cells interacting with airway smooth muscle in the pathogenesis of airflow limitation [ 45 ]. Mechanisms of COPD On the basis of the different pathophysiological mechanisms illustrated in Fig. 1 , different animal models have been developed in past years. Protease-antiprotease imbalance An imbalance between protease and antiprotease enzymes has been hypothesized with respect to the pathogenesis of emphysema [ 46 ]. This concept derives from early clinical observations that alpha1-antitrypsin-deficient subjects develop severe emphysema and the role of protease-antiprotease imbalance was later demonstrated in animal models of COPD [ 47 , 48 ]. Although alpha1-antitrypsin-deficiency is a very rare cause of emphysema [ 49 , 50 ], it points to a role of proteases and proteolysis [ 51 , 52 ]. Neutrophil elastase-deficient mice were significantly protected from emphysema-development induced by chronic cigarette smoke [ 48 ]. Depletion of the macrophage elastase gene also led to a complete protection from emphysema induced by cigarette smoke [ 47 ]. Each of these elastases inactivated the endogenous inhibitor of the other, with macrophage elastase degrading alpha1-antitrypsin and neutrophil elastase degrading tissue inhibitor of metalloproteinase-1 [ 48 ]. In tobacco smoke exposure-induced recruitment of neutrophils and monocytes was impaired in elastase gene-depleted animals and there was less macrophage elastase activity due to a decreased macrophage influx in these animals. Thus, a major role for neutrophil elastase and macrophage elastase in the mediation of alveolar destruction in response to cigarette smoke has been shown [ 47 , 48 ]. This experimental evidence derived from animal models points to an important pathogenetic role for proteases that correlates well with the imbalance of proteases present in human COPD. However, many pathways of tissue destruction can be found in animal models that lead to a picture similar to human disease, and it is important to examine whether these mechanisms are operative in the human disease itself. Oxidative stress Oxidative stress arising from inhaled noxious stimuli such as tobacco smoke or nitrogen dioxide may be important cause of the inflammation and tissue damage in COPD. This potential mechanism is supported by clinical reports of increased levels of oxidative stress indicators in exhaled breath condensates of COPD patients [ 53 - 55 ]. Apart from elevated levels of 8-isoprostane [ 55 ], nitrosothiol levels were increased in COPD patients [ 56 - 58 ]. Studies in a mouse model of tobacco smoke-induced COPD also demonstrated the presence of tissue damage due to oxidative stress [ 59 ]. These changes could be blocked by superoxide dismutase [ 60 ]. Oxidative stress has also been implicated in the development of corticosteroid resistance in COPD. Mediators Many mediators have been identified which may contribute to COPD pathogenesis [ 8 ]. As in bronchial asthma, pro- and anti-inflammatory mediators of inflammation such as tachykinins [ 61 ], vasoactive intestinal polypeptide (VIP) [ 62 ], histamine [ 63 ], nitric oxide [ 64 , 65 ], leukotrienes [ 66 ], opioids [ 67 ] or intracellular mediators such as SMADs [ 68 , 69 ] have been implicated. The balance of histone acetylases and deacetylases [ 70 ] is a key regulator of gene transcription and expression by controlling the access of the transcriptional machinery to bind to regulatory sites on DNA. Acetylation of core histones lead to modification of chromatin structure that affect transcription, and the acetylartion status depends on a balance of histone deacetylase and histone acetyltransferase. This is also likely to play a role in the regulation of cytokine production in COPD. Cigarette smoke exposure led to altered chromatin remodelling with reduced histone deacetylase activity with a resultant increase in transcription of pro-inflammatory genes in lungs of rats exposed to smoke, linked to an increase in phosphorylated p38 MAPK in the lung concomitant with an increased histone 3 phospho-acetylation, histone 4 acetylation and elevated DNA binding of NF-kappaB, and activator protein 1 (AP-1) [ 70 ]. In addition, oxidative stress has also been shown to enhance acetylation of histone proteins and decrease histone deacetylase activity leading to modulation of NF-κB activation [ 71 ], similar to the effect of cigarette smoke. A Th2 cytokine that has been proposed to be implicated in the pathophysiology of COPD is IL-13. It is also overexpressed and related to the pathogenesis of the asthmatic Th2 inflammation and airway remodelling process [ 72 ]. The effects of IL-13 in asthma have been elucidated in a series of experiments that demonstrated the an airway-specific constitutive overexpression of IL-13 leads to a process of airway remodelling with subepithelial fibrosis and mucus metaplasia combined with an eosinophil-, lymphocyte-, and macrophage-rich inflammation and increased hyperresponsiveness [ 73 ]. Since asthma and COPD pathogenesis may be linked, similar mechanisms may contribute to the development and progression of both diseases [ 74 ]. In this respect, IL-13 may also play a role in COPD since the inducible overexpression of IL-13 in adult murine lungs leads to alveolar enlargement, lung enlargement and an enhanced compliance and mucus cell metaplasia [ 75 ] with activation of MMP-2, -9, -12, -13, and -14 and cathepsins B, S, L, H, and K in this model. Parallel to protease-based and extracellular mediator-based concepts, altered intracellular pathways may also play a role in COPD. MAPK signalling pathways i.e. p38 and c-Jun N terminal kinase (JNK) [ 76 , 77 ] seem to be important signal transducers in the airways and airway-innervating neurons [ 78 - 80 ] and may therefore display an interesting target for COPD research. For some cells, the activation of p38 or JNK pathways may promote apoptosis rather than proliferation [ 81 , 82 ]. Viral infections Previous studies showed an association between latent adenoviral infection with expression of the adenoviral E1A gene and chronic obstructive pulmonary disease (COPD) [ 83 , 84 ]. It may therefore be assumed that latent adenoviral infection can be one of the factors that might amplify airway inflammation. Human data [ 35 ] demonstrating the presence of the viral E1A gene and its expression in the lungs from smokers [ 85 , 86 ], animals [ 87 ] and cell cultures [ 88 ] support this hypothesis. A small population of lung epithelial cells may carry the adenoviral E1A gene which may then amplify cigarette smoke-induced airway inflammation to generate parenchymal lesions leading to COPD. Inflammatory changes lead to collagen deposition, elastin degradation, and induction of abnormal elastin in COPD [ 89 , 90 ]. Also, latent adenovirus E1A infection of epithelial cells could contribute to airway remodelling in COPD by the viral E1A gene, inducing TGF-beta 1 and CTGF expression and shifting cells towards a more mesenchymal phenotype[ 84 ]. Genetics Since only a minority of smokers (approximately 15 to 20%) develop symptoms and COPD is known to cluster in families, a genetic predisposition has been hypothesized. Many candidate genes have been assessed, but the data are often unclear and systematic studies are currently performed to identify disease-associated genes. Next to alpha1-antitrypsin deficiency, several candidate genes have been suggested to be linked to COPD induction. Genetic polymorphisms in matrix metalloproteinase genes MMP1, MMP9 and MMP12 may be important in the development of COPD. In this respect, polymorphisms in the MMP1 and MMP12 genes, but not MMP9, have been suggested to be related to smoking-related lung injury or are in a linkage disequilibrium with other causative polymorphisms [ 91 - 93 ]. An association between an MMP9 polymorphism and the development of smoking-induced pulmonary emphysema was also reported in a population of Japanese smokers [ 94 ]. Also, polymorphisms in the genes encoding for IL-11 [ 95 ], TGF-beta1 [ 96 ], and the group-specific component of serum globulin [ 97 ] have been shown to be related to a genetic predisposition for COPD. Since it was difficult to replicate some of these findings among different populations, future studies are needed. Also, whole genome screening in patients and unaffected siblings displays a promising genetic approach to identify genes associated with COPD. Experimental models of COPD There are three major experimental approaches to mimic COPD encompassing inhalation of noxious stimuli, tracheal instillation of tissue-degrading enzymes to induce emphysema-like lesions and gene-modifying techniques leading to a COPD-like phenotype (Figure 2 ). These approaches may also be combined. Ideally a number of potential indicators for COPD which have been proposed by the GOLD guidelines should be present in animal models of COPD (Table 3 ). Since COPD definition still rests heavily on lung function measures (airflow limitation and transfer factor), it would be ideal to have lung function measurements in experimental models [ 15 ]. The challenge is in the measurement of lung function in very small mammals such as mice and since the use of the enhanced pause (Penh) in conscious mice as an indicator of airflow obstruction is not ideal [ 98 ], invasive methods remain the gold standard and these should be correlated with inflammatory markers and cellular remodelling. Figure 2 Experimental approaches to mimic COPD There are three major experimental approaches to mimic COPD or emphysema consisting of inhalation of noxious stimuli such as tobacco smoke, tracheal instillation of tissue-degrading enzymes to induce emphysema-like lesions and gene-modifying techniques leading to COPD-like murine phenotypes. Table 3 Indicators for COPD. These indicators are related to the presence of COPD and should ideally be present in animal models and available for analysis. Indicator Human features Experimental approach History of exposure to risk factors Tobacco smoke. Occupational dusts and chemicals. Indoor / outdoor air pollution Exposure-based experimental protocol Airflow obstruction Decrease in FEV 1 Lung function tests Hypersecretion Chronic sputum production Functional and morphological assessment of hypersecretion Cough Chronic intermittent or persistent cough Cough assessment Dyspnea Progressive / Persistent / worse on exercise / worse during respiratory infections Assessment of hypoxemia Emphysema Progressive impairment of lung function Morphological analysis of airspace enlargement Inhalation models – tobacco smoke A variety of animal species has been exposed to tobacco smoke. Next to guinea pigs, rabbits, and dogs, and also rats and mice have been used. Guinea pigs have been reported to be a very susceptible species. They develop COPD-like lesions and emphysema-like airspace enlargement within a few months of active tobacco smoke exposure [ 99 ]. By contrast, rat strains seem to be more resistant to the induction of emphysema-like lesions. Susceptibility in mice varies from strain to strain. The mode of exposure to tobacco smoke may be either active via nose-only exposure systems or passive via large whole-body chambers. The first species to be examined in detail for COPD-like lesions due to tobacco smoke exposure was the guinea pig [ 99 ]. Different exposure protocols were screened and exposure to the smoke of 10 cigarettes each day, 5 days per week, for a period of either 1, 3, 6, or 12 months resulted in progressive pulmonary function abnormalities and emphysema-like lesions. The cessation of smoke exposure did not reverse but stabilized emphysema-like airspace enlargement. On the cellular level, long term exposure lead to neutrophilia and accumulation of macrophages and CD4+ T-cells [ 83 , 100 ]. Latent adenoviral infection amplifies the emphysematous lung destruction and increases the inflammatory response produced by cigarette-smoke exposure. Interestingly, it was shown that the increase in CD4+ T-cells is associated with cigarette smoke and the increase in CD8+ T-cells with latent adenoviral infection [ 83 ]. Mice represent the most favoured laboratory animal species with regard to immune mechanisms since they offer the opportunity to manipulate gene expression. However, it is more difficult to assess lung function and mice tolerate at least two cigarettes daily for a year with minimal effects on body weight and carboxyhemoglobin levels. Mice differ considerably in respiratory tract functions and anatomy if compared to humans: they are obligate nose breathers, they have lower numbers of cilia, fewer Clara cells and a restriction of submucosal glands to the trachea. Next to a lower filter function for tobacco smoke, mice also do not have a cough reflex and many mediators such as histamine or tachykinins have different pharmacological effects. The development of emphysema-like lesions is strain-dependent: enlarged alveolar spaces and increased alveolar duct area are found after 3–6 months of tobacco smoke exposure in susceptible strains such as B6C3F1 mice [ 101 ]. At these later time points, tissue destruction seems to be mediated via macrophages. At the cellular level, neutrophil recruitment has been reported to occur immediately after the beginning of tobacco smoke exposure and is followed by accumulation of macrophages. The early influx of neutrophils is paralleled by a connective tissue breakdown. The early stage alterations of neutrophil influx and increase in elastin and collagen degradation can be prevented by pre-treatment with a neutrophil antibody or alpha1-antitrypsin [ 102 ]. Rats are also often used for models of COPD. However, they appear to be relatively resistant to the induction of emphysema-like lesions. Using morphometry and histopathology to assess and compare emphysema development in mice and rats, significant differences were demonstrated [ 101 ]: Animals were exposed via whole-body exposure to tobacco smoke at a concentration of 250 mg total particulate matter/m3 for 6 h/day, 5 days/week, for either 7 or 13 months. Morphometry included measurements of tissue loss (volume density of alveolar septa) and parenchymal air space enlargement (alveolar septa mean linear intercept, volume density of alveolar air space). Also, centroacinar intra-alveolar inflammatory cells were assessed to investigate differences in the type of inflammatory responses associated with tobacco smoke exposure. In B6C3F1 mice, many of the morphometric parameters used to assess emphysema-like lesions differed significantly between exposed and non-exposed animals. By contrast, in exposed Fischer-344 rats, only some parameters differed significantly from non-exposed values. The alveolar septa mean linear intercept in both exposed mice and rats was increased at 7 and 13 months, indicating an enlargement of parenchymal air spaces. In contrast, the volume density of alveolar air space was significantly increased only in exposed mice. The volume density of alveolar septa was decreased in mice at both time points indicating damage to the structural integrity of parenchyma. There was no alteration in Fischer-344 rats. Morphologic evidence of tissue destruction in the mice included irregularly-sized and -shaped alveoli and multiple foci of septal discontinuities and isolated septal fragments. The morphometric differences in mice were greater at 13 months than at 7 months, suggesting a progression of the disease. Inflammatory influx within the lungs of exposed mice contained significantly more neutrophils than in rats. These results indicated that B6C3F1 mice are more susceptible than F344-rats to the induction of COPD-like lesions in response to tobacco smoke exposure [ 101 ]. Recent work on cigarette exposure in rats indicate that this model also achieves a degree of corticosteroid resistance that has been observed in patients with COPD [ 103 , 104 ]. Thus, the inflammatory response observed after exposure of rats to cigarette smoke for 3 days is noty inhibited by pre-treatment with corticosteroids [ 70 ]. This may be due to the reduction in histone deacetylase activity, which could result from a defect in recruitment of this activity by corticosteroid receptors. Corticosteroids recruit hitone deacetylase 2 protein to the transcriptional complex to suppress proinflammatory gene transcription [ 105 ]. Modifications in histone deacetylase 2 by oxidative stress or by cigarette smoke may make corticosteroids ineffective [ 106 ]. Therefore, models of COPD that show corticosteroid resistance may be necessary and could be used to dissect out the mechanisms of this resistance. Generally, tobacco smoke exposure may be used to generate COPD features such as emphysema and airway remodelling and chronic inflammation. Although the alterations still differ from the human situation and many involved mediators may have different functional effects especially in the murine respiratory tract, these models represent useful approaches to investigate cellular and molecular mechanisms underlying the development and progression of COPD. As a considerable strain-to-strain and species-to-species variation can be found in the models used so far, the selection of a strain needs to be done with great caution. Animal models of COPD still need to be precisely evaluated as to whether they mimic features of human COPD, and their limitations must be appreciated. Findings obtained from these models may provide significant advances in terms of understanding novel mechanisms involved in COPD. Inhalation models – sulfur dioxide Sulfur dioxide (SO 2 ) is a gaseous irritant which can be used to induce COPD-like lesions in animal models. With daily exposure to high concentrations of SO 2 , chronic injury and repair of epithelial cells can be observed in species such as rat or guinea pig. The exposure to high-levels of this gas ranging from 200 to 700 ppm for 4 to 8 weeks has been demonstrated to lead to neutrophilic inflammation, morphological signs of mucus production and mucus cell metaplasia and damage of ciliated epithelial cells in rats [ 107 , 108 ]. These changes are directly dependent on the exposure to the gas: signs of mucus production and neutrophilic inflammation are almost entirely reversed within a week after termination of exposure [ 108 ]. Acute exposure to SO 2 also leads to loss of cilia and exfoliation of ciliated cells as demonstrated in SO 2 -exposed dogs using transmission electron microscopy [ 109 ]. After a longer period of exposure the epithelial layer regenerates and airway wall thickening and change in cilia structure can be observed [ 110 ]. Long-term exposure also increases in mucosal permeability both in vivo and in vitro [ 111 ]. Mucus hypersecretion is an important indicator for COPD and experimental models should encompass features of hypersecretion. After chronic exposure to SO 2 in rats, visible mucus layers and mucus plugs may sometimes be observed in the large airways [ 107 ] and an elevation of mucus content may be found in bronchoalveolar lavage fluids [ 112 ]. Parallel to these findings, there is an increase of PAS- and Alcian Blue-staining epithelial cells in chronically SO 2 exposed rats [ 113 ] but there is substantial variation present as with human COPD [ 114 ]. Tracheal mucus glands are also increased in size after SO 2 -exposure [ 115 ] and increased levels of mucin RNA can be found in lung extracts [ 112 ]. The mechanisms underlying mucus hypersecretion have not been elucidated so far and also, functional studies assessing basal and metacholine-induced secretion have not been conducted so far. Airway inflammation with cellular infiltration is an important feature of COPD. After exposure to SO 2 , increases in mononuclear and polymorphonuclear inflammatory cells are present in rat airways. However, the influx is confined to large but not small airways which are important in human COPD [ 107 ]. Even after one day of exposure, polymorphonuclear inflammatory cells are found and their influx can be inhibited with steroid treatment [ 116 ]. SO 2 -based models of COPD have also been shown to be associated with an increase in pulmonary resistance and airway hyperresponsiveness [ 107 ] and it was hypothesized that elevated levels of mucus may account for the increased responsiveness [ 117 ]. Since sensory nerve fibres may function as potent regulators of chronic inflammation in COPD by changes in the activation threshold and the release of pro-inflammatory mediators such as tachykinins [ 61 , 118 ] or CGRP [ 6 , 119 ], this class of nerve fibres was examined in a number of studies [ 120 , 121 ]. The results of these studies supported the hypothesis that rather than contributing to the pathophysiological manifestations of bronchitis, sensory nerve fibres limit the development of airway obstruction and airway hyperresponsiveness during induction of chronic bronchitis by SO 2 -exposure. In this respect, the enhanced contractile responses of airways from neonatally SO 2 -exposed capsaicin-treated rats may result from increased airway smooth muscle mass and contribute to the increased airway responsiveness observed in these animals [ 121 ]. To obtain coexisting expression of emphysema and inflammatory changes as seen in COPD, neutrophil elastase instillation and SO 2 -exposure were performed simultaneously [ 108 ]. The pre-treatment with elastase aimed to render the animals more susceptible to the inflammation induced by SO 2 . However, neither allergy-phenotype Brown Norway nor emphysematous Sprague–Dawley rats displayed an increased sensitivity to SO 2 -exposure. With regard to the observed histopathological changes, it can be concluded that SO 2 exposure leads to a more diffuse alveolar damage with a more extensive damage with destruction of lung tissue after longer exposure. Therefore, the outcome is more or less a picture of tissue destruction with close resemblance to end stages of emphysema but not a complete picture of COPD. Inhalation models – nitrogen dioxide Nitrogen dioxide (NO 2 ) is a another gas that may lead to COPD-like lesions depending on concentration, duration of exposure, and species genetic susceptibility [ 122 ]. Concentrations ranging from 50–150 ppm (94–282 mg/m3) can lead to death in laboratory animals due to extensive pulmonary injury including pulmonary oedema, haemorrhage, and pleural effusion. Short-term exposure to NO2 leads to a biphasic response with an initial injury phase followed by a repair phase. Both increased cellular proliferation and enzymatic activity occur during the repair phase. Exposure of rats to 15 ppm NO 2 for 7 days leads to an increased oxygen consumption in airway tissues. The increase in oxidative capacity reflects an increase in mitochondrial activity consistent with observations of increased DNA synthesis [ 123 ]. Exposure to 10 ppm NO 2 for more than 24 h causes damage to cilia and hypertrophy of the bronchiolar epithelium [ 124 ]. Also, exposure to 15–20 ppm NO 2 leads to a type II pneumocyte hyperplasia [ 125 , 126 ]. As with the exposure to other noxious stimuli, there is also a significant inter-species variability. In comparison to mice and rats, guinea pigs exhibit changes in lung morphology at much lower NO 2 concentrations. It was shown that a 2 ppm NO 2 3-day exposure causes increased thickening of the alveolar wall, damage to cilia and pulmonary oedema [ 127 ]. Other changes are an influx of inflammatory cells and increases in connective tissue formation [ 128 ]. There is also a significant mode of inheritance of susceptibility to NO 2 -induced lung injury in inbred mice. Susceptible C57BL/6J (B6) and resistant C3H/HeJ (C3) mice, as well as F1, F2, and backcross (BX) populations derived from them, were acutely exposed to 15 parts per million NO 2 for 3 h to determine differences [ 122 ]. Significant differences in numbers of lavageable macrophages, epithelial cells, and dead cells were found between inbred strains: distributions of cellular responses in F1 progeny overlapped both progenitors, and mean responses were intermediate. It was shown that in C3:BX progeny, ranges of responses to NO 2 closely resembled C3 mice. Ranges of cellular responses to NO 2 in B6:BX and intercross progeny were reported to overlap both progenitor and mean responses of both populations were intermediate to progenitors. Therefore, there were likely two major unlinked genes that account for differential susceptibility to acute NO 2 exposure [ 122 ]. Based on the genetic background of C57BL/6 mice, a model of long-term NO 2 exposure was recently established leading to signs of pulmonary inflammation and progressive development of airflow obstruction [ 129 ]. Inhalation models – oxidant stimuli and particulates The administration of oxidants such as ozone also causes significant lung injury with some features related to inflammatory changes occurring in human COPD [ 130 ] and this causes numerous effects in airway cells [ 131 - 135 ]. As a gaseous pollutant, ozone targets airway tissues and breathing slightly elevated concentrations of this gas leads to a range of respiratory symptoms including decreased lung function and increased airway hyper-reactivity. In conditions such as COPD and asthma, ozone may lead to exacerbations of symptoms. Ozone is highly reactive: the reaction with other substrates in the airway lining fluid such as proteins or lipids leads to secondary oxidation products which transmit the toxic signals to the underlying pulmonary epithelium. These signals include cytokine generation, adhesion molecule expression and tight junction modification leading to inflammatory cell influx and increase of lung permeability with oedema formation [ 130 ]. However, the nature and extent of these responses are often variable and not related within an individual. The large amount of data obtained from animal models of ozone exposure indicates that both ozone- and endotoxin-induced animal models are dependent on neutrophilic inflammation. It was shown that each toxin enhances reactions induced by the other toxin. The synergistic effects elicited by coexposure to ozone and endotoxin are also mediated, in part, by neutrophils. [ 136 , 137 ]. Further animal models focus on the exposure to ultrafine particles, silica and coal dust [ 138 , 139 ]. Ultrafine particles are a common component of air pollution, derived mainly from primary combustion sources that cause significant levels of oxidative stress in airway cells [ 140 , 141 ]. The animal models are predominantly characterized by focal emphysema and it was suggested that dust-induced emphysema and smoke-induced emphysema occur through similar mechanisms [ 142 ]. Exposure to diesel exhaust particles (DEP) may also lead to chronic airway inflammation in laboratory animals as it was shown to have affect various respiratory conditions including exacerbations of COPD, asthma, and respiratory tract infections [ 143 ]. Both the organic and the particulate components of DEP cause significant oxidant injury and especially the particulate component of DEP is reported to induce alveolar epithelial damage, alter thiol levels in alveolar macrophages (AM) and lymphocytes, and induce the generation of reactive oxygen species (ROS) and pro-inflammatory cytokines [ 144 ]. The organic component has also been shown to generate intracellular ROS, leading to a variety of cellular responses including apoptosis. Long-term exposure to various particles including DEP, carbon black (CB), and washed DEP devoid of the organic content, have been shown to produce chronic inflammatory changes and tumorigenic responses [ 144 ]. The organic component of DEP also suppresses the production of pro-inflammatory cytokines by macrophages and the development of Th1 cell-mediated mechanisms thereby enhancing allergic sensitization. The underlying mechanisms have not been fully investigated so far but may involve the induction of haeme oxygenases, which are mediators of airway inflammation [ 145 ]. Whereas the organic component that induces IL-4 and IL-10 production may skew the immunity toward Th2 response, the particulate component may stimulate both the Th1 and Th2 responses [ 146 ]. In conclusion, exposure to particulate and organic components of DEP may be a helpful approach to simulate certain conditions such as exacerbations. Also, the development of lung tumours after long term exposure may be useful when studying interactions between COPD-like lesions and tumorigenesis. A further toxin is cadmium chloride, a constituent of cigarette smoke. Administration of this substance also leads to alterations in pulmonary integrity with primarily interstitial fibrosis with tethering open of airspaces [ 147 ]. A combination of cadmium and lathyrogen beta-aminopropionile enhances emphysematous changes [ 148 ]. Tissue-degrading approaches Emphysema-like lesions can also be achieved by intrapulmonary challenge with tissue-degrading enzymes and other compounds [ 149 ] (Figure 2 ). Proteinases such as human neutrophil elastase, porcine pancreatic elastase, or papain produce an efficient enzymatic induction of panacinar emphysema after a single intrapulmonary challenge [ 150 , 151 ]. Since bacterial collagenases do not lead to the formation of emphysema, the effectiveness of the proteinases is related to their elastolytic activity. While these models may not be as useful as smoke exposure studies to achieve COPD-like lesions, they can lead to a dramatic picture of emphysema and may be used to study mechanisms related specifically to emphysema and to the repair of damaged lung. However, the method of inducing emphysema-like lesions by intratracheal instillation of these enzymes may not very closely relate to mechanisms found in the human situation. Among the different emphysema models, elastase-induced emphysema has also been characterized to be accompanied by pulmonary function abnormalities, hypoxemia, and secretory cell metaplasia which represent characteristic features of human COPD. Recent studies suggested that exogenous retinoic acid can induce alveolar regeneration in models of elastase-induced experimental emphysema [ 152 ] and that retinoic acid may have a role for alveolar development and regeneration after injury [ 153 , 154 ]. However, the role of retinoic acid in relation to alveolar development has only been analysed in a rat model and models in other animals did not show similar effects [ 155 ]. Also, the ability of alveolar regeneration which is present in rats does not occur to a similar extent in humans; a recent clinical trial using retinoic acid in COPD did not show positive results [ 156 ]. The mechanisms of emphysema induction by intratracheal administration of elastase encompass an initial loss of collagen and elastin. Later, glycosaminoglycan and elastin levels normalize again but collagen levels are enhanced. The extracellular matrix remains distorted in structure and diminished with resulting abnormal airway architecture [ 157 ]. The enlargement of the airspaces immediately develops after the induction of elastolytic injuries and is followed by inflammatory processes which lead to a transformation of airspace enlargement to emphysema-like lesions. This progression most likely occurs due to destructive effects exerted by host inflammatory proteinases. Addition of lathyrogen beta-aminopropionile leads to an impairment of collagen and elastin crosslinking and therefore further increases the extent of emphysema-like lesions [ 158 ]. Effects seem to be mediated via IL-1β and TNFα receptors since mice deficient in IL-1β Type1 receptor and in TNFalpha type 1 and 2 receptors are protected from developing emphysema following intratracheal challenge with porcine pancreatic elastase. This was associated with reduced inflammation and increased apoptosis [ 159 ]. In general, intrapulmonary administration of tissue-degrading enzymes represents a useful tool especially when focusing on mechanisms to repair emphysematic features. However, the lack of proximity to the human situation needs to be realized since the mechanisms of emphysema induction are clearly not related to the human situation. An advantage of proteinase-based models is the simple exposure protocol with a single intratracheal administration leading to significant and rapid changes. However, extrapolating these findings to slowly developing features of smoking induced human COPD is very difficult since a large number of mediators may not be involved in the rapid proteinase approach. Therefore, these models may not encompass important features of human COPD which may be more closely mimicked by inhalation exposures and it is clear that tissue-degrading enzyme models always represent the picture of an "induced pathogenesis". Gene-targeting approaches The genetic predisposition to environmental disease is an important area of research and a number of animal strains prone to develop COPD-like lesions have been characterized [ 160 - 162 ] (Figure 2 ). Also, genetically-altered monogenic and polygenic models to mimic COPD have been developed in recent years using modern techniques of molecular biology [ 163 , 164 ]. Gene-depletion and -overexpression in mice provide a powerful technique to identify the function and role of distinct genes in the regulation of pulmonary homeostasis in vivo . There are two major concepts consisting of gain-of-function and loss-of-function models. Gain-of-function is achieved by gene overexpression in transgenic mice either organ specific or non-specific while loss of function is achieved by targeted mutagenesis techniques [ 165 , 166 ]. These models can be of significant help for the identification of both physiological functions of distinct genes as well as mechanisms of diseases such as COPD. A large number of genetically-altered mice strains have been associated to features of COPD and a primary focus was the assessment of matrix-related genes. As destruction of alveolar elastic fibres is implicated in the pathogenic mechanism of emphysema and elastin is a major component of the extracellular matrix, mice lacking elastin were generated. It was shown that these animals have a developmental arrest development of terminal airway branches accompanied by fewer distal air sacs that are dilated with attenuated tissue septae. These emphysema-like alterations suggest that in addition to its role in the structure and function of the mature lung, elastin is essential for pulmonary development and is important for terminal airway branching [ 167 ]. Also, deficiency of the microfibrillar component fibulin-5 and platelet derived growth factor A (PDGF-A) leads to airspace enlargement [ 168 , 169 ]. PDGF-A(-/-) mice lack lung alveolar smooth muscle cells, exhibit reduced deposition of elastin fibres in the lung parenchyma, and develop lung emphysema due to a complete failure of alveogenesis [ 170 ]. The postnatal alveogenesis failure in PDGF-A(-/-) mice is most likely due to a prenatal block in the distal spreading of PDGF-R alpha+ cells along the tubular lung epithelium during the canalicular stage of lung development [ 170 ]. The importance of integrins in causing emphysema has been demonstrated in mouse. Epithelial restricted integrin α vβ 6-null mice develop age-related emphysema through the loss of activation of latent TGF-beta which leads to an increase in macrophage MMP-12 expression [ 171 ]. Fibroblast growth factors are known to be essential for lung development. Mice simultaneously lacking receptors for FGFR-3 and FGFR-4 have an impaired alveogenesis with increased collagen synthesis [ 172 ]. It is crucial to distinguish developmental airspace enlargement from adult emphysema which is defined as the destruction of mature alveoli. However, the identification of numerous factors influencing lung development is an important step towards identifying potential mechanisms underlying the development and progression of emphysema in human COPD. Next to developmental airspace enlargement also spontaneous emphysema may occur in genetically-modified mice strains and a gradual appearance of emphysema-like lesions has been found in mice lacking the surfactant protein D (SP-D) gene [ 173 ] and in mice lacking the tissue inhibitor of metalloproteinase-3 (TIMP-3) gene [ 174 ]. In these strains, matrix metalloproteinases were suggested to be the primary mediators of tissue destruction. A further mechanism to induce emphysema-like lesions is to expose developmentally normal genetically-modified animals to exogenous noxious stimuli such as tobacco smoke. This also allows identifying potential molecular mechanisms involved in the pathogenesis of COPD. Using macrophage elastase (MMP-12) gene-depletion studies it was shown that in contrast to wild type mice, the lung structure of MMP-12 gene-depleted animals remains normal after long term exposure to cigarette smoke [ 47 ]. These animals also fail to develop macrophage accumulation in response to cigarette smoke, an effect that could be related to MMP-12 induced generation of elastin fragments that are chemotactic for monocytes [ 175 , 176 ]. In summary, gene-targeting techniques display very useful tools to examine potential molecular mechanisms underlying human COPD. In combination with inhalation protocols they may identify important protective or pro-inflammatory mediators of the disease. Other models Various other agents have also been characterized to induce airway inflammation injury. In this respect, administration of toxins such as endotoxin leads to a recruitment of neutrophils and macrophage activation with concomitant airspace enlargement [ 177 , 178 ]. Non-inflammatory emphysema-like lesions may also be accomplished by intravascular administration of a vascular endothelial cell growth factor receptor-2 (VEGFR-2) blocker [ 179 ]. VEGF is required for blood vessel development and endothelial cell survival and its absence leads to endothelial cell apoptosis [ 180 ]. An increased septal cell death in human emphysematous lungs and a reduced expression of VEGF and VEGFR-2 is found in emphysema lungs [ 181 ]. Also, chronic blockage of VEGFR-2 causes alveolar septal cell apoptosis and airspace enlargement [ 179 ]. These findings of airspace enlargement point to a role of the vascular system in the development and progression of emphysema. Conclusions In contrast to the variable pathology and different stages of severity in human COPD, currently available animal models are restricted to mimicking a limited amount of characteristic features of COPD. Animal models need to be precisely evaluated based on whether they agree with features of human COPD in order to advance the understanding of mechanisms in human COPD. Based on inhalative exposure to noxious stimuli such as cigarette smoke, the administration of tissue-degrading enzymes or gene-targeting techniques, a number of experimental approaches to mimic acute and chronic features of COPD have been established in the past years. Due to the complexity of the disease, and species-specific differences they are all limited concerning their clinical significance. While the induction of the COPD lesions by tissue-degrading enzymes may appear artificial in many cases, it does not mean that these models are not valuable because they can be used to study many aspects of pulmonary pathophysiology of end-stage emphysema. Cellular mechanisms can be studied efficiently and underlying molecular mechanisms and potential therapeutic approaches can be revealed if the data is extrapolated cautiously. Combined models of inhalative exposure, proteinase-based tissue degradation to produce emphysema and gene-targeting techniques may provide models of COPD which encompass more features of the disease. However, one cannot assume that reproducing COPD with a high degree of fidelity in the animal necessarily means that the model simulates the human condition. In fact, a model that only produces a single pathologic COPD feature may be more useful as long as it produces this feature via a relevant mechanism that allows exploratory research. By contrast, a model producing all kinds of COPD features via irrelevant mechanisms may be less useful. In this respect, validation of models as being relevant is an extremely important issue in the early steps of model development. Animal models should not only assess histopathological features but also attempt to focus on functional features of human COPD such as airflow limitation, mucus hypersecretion, chronic cough and exacerbations, and also on pharmacological features such as corticosteroid resistance or diminished β-adrenergic bronchodilator responses. In conclusion, there are many benefits that can accrue from the development of animal models of COPD, most important of which is understanding of mechanisms and development of specific drugs for COPD.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC533858.xml
520826	Daily rhythms in plasma levels of homocysteine	Background There is accumulated evidence that plasma concentration of the sulfur-containing amino-acid homocysteine (Hcy) is a prognostic marker for cardiovascular morbidity and mortality. Both fasting levels of Hcy and post methionine loading levels are used as prognostic markers. The aim of the present study was to investigate the existence of a daily rhythm in plasma Hcy under strictly controlled nutritional and sleep-wake conditions. We also investigated if the time during which methionine loading is performed, i.e., morning or evening, had a different effect on the resultant plasma Hcy concentration. Methods Six healthy men aged 23–26 years participated in 4 experiments. In the first and second experiments, the daily rhythm in Hcy as well as in other amino acids was investigated under a normal or an inverse sleep-wake cycle. In the third and fourth, Hcy concentrations were investigated after a morning and evening methionine loading. To standardize food consumption in the first two experiments, subjects received every 3 hours 150 ml of specially designed low-protein liquid food (Ensure ® formula). Results In both the first and second experiments there was a significant daily rhythm in Hcy concentrations with a mid-day nadir and a nocturnal peak. Strikingly different 24-h patterns were observed in methionine, leucine, isoleucine and tyrosine. In all, the 24-h curves revealed a strong influence of both the sleep-wake cycle and the feeding schedule. Methionine loading resulted in increased plasma Hcy levels during both morning and evening experiments, which were not significantly different from each other. Conclusions There is a daily rhythm in plasma concentration of the amino acid Hcy, and this rhythm is independent of sleep-wake and food consumption. In view of the fact that increased Hcy concentrations may be associated with increased cardiovascular risks, these findings may have clinical implications for the health of rotating shift workers.	Background Experimental results accumulated in recent years have revealed that plasma concentration of the sulfur-containing amino-acid homocysteine (Hcy) is a prognostic marker for cardiovascular morbidity and mortality [ 1 - 5 ]. Plasma concentrations of Hcy in excess of 15 μmol/L under fasting conditions were associated with increased risk of cardiovascular mortality [ 6 ]. Furthermore, some patients having normal fasting levels of plasma Hcy were shown to have abnormally high levels of Hcy after methionine loading [ 7 ]. In most epidemiological studies, the differences between fasting concentrations of Hcy of cardiovascular patients and normal controls did not amount to more than 10–15%. Studies conducted during the 1960s have demonstrated that plasma levels of several amino acids vary in a daily manner. Feigin, Klainer and Beisel [ 8 ] were the first to report on daily rhythms in serum levels of total amino acids in adult men. The peak levels of the total integrated amino acids occured between 1200 and 2000 with a minimum level at 0400. Wurtman, Chou and Rose [ 9 ] reported on a daily rhythm in plasma concentration of tyrosine with a nocturnal nadir and a morning peak, which represented a two-fold increase in plasma tyrosine level. This rhythm persisted when subjects were maintained on a two-week low protein diet. Subsequently, the same group [ 10 ] extended their findings to 15 additional amino acids. Tyrosine, tryptophan, phenylalanine, methionine, cysteine, and isoleucine, underwent the greatest daily changes while alanine, glycine and glutamic acid showed the least. Hussein et al [ 11 ] reported that the daily fluctuations of plasma free amino acids were significantly affected by the dietary conditions. In none of these studies, however, were the levels of amino acids determined during the sleep period or under uniform dietary conditions. More recently, plasma Hcy levels were also shown to vary in a daily manner in humans with an evening peak and a morning nadir [ 12 ]. Significant daily rhythmicity was found in obese diabetic patients but not in normal controls. Since plasma samples were obtained every 3 hours and no attempt was made to examine how sleep affected the pattern of secretion, it is difficult to determine whether these findings bear any clinical significance. In rats, plasma Hcy demonstrated a 24-h rhythm with a nocturnal peak and a daytime nadir. Pinealectomy did not change the phase of the rhythm or its nocturnal elevation, but it did significantly increase mean plasma Hcy [ 13 ]. In the present study, we further investigated the possible existence of a daily rhythm in plasma Hcy under strictly controlled nutritional and sleep-wake conditions. We also investigated if the time during which methionine loading is performed, i.e., morning or evening, had a different effect on the resultant plasma Hcy concentration. Methods Subjects Six healthy men aged 23–26 years participated in 4 experiments. All were students who maintained a normal and regular sleep-wake cycle for at least three months prior to the studies. They were screened to ensure an adequate state of health by physical examination, detailed medical history and blood testing. All had a normal body weight (mean body mass index (BMI) = 23.5 ± 1.6 Kg/m 2 ). They were instructed to avoid alcohol and coffee beverages during the 24 hours that preceded each of the experimental periods. The study was approved by the local Human Ethics Committee, and subjects gave written informed conset before being enrolled in the first experiment. Subjects were paid for their participation. Procedure In the first and second experiments, daily rhythms in Hcy as well as in other amino acids were investigated under a normal or an inverse sleep-wake cycle. In the third and fourth experiments, Hcy concentrations were investigated after morning and evening methionine loading. Experiment 1 Subjcts were admitted to the laboratory at 1800 for a period of 24 hours, after having a normal day. A catheter was inserted into an antecubital vein and was kept patent by a drip of saline. Electrodes were attached for polysomnographic monitoring to determine sleep stages. These included EEG, EMG, EOG, respiration by respiratpry belt and nasal thermistor, and oximetry. Starting at 1900, 5-ml blood samples were drawn every hour until 1900 on the next day. Thoughout this period subjects were either in a supine or a sitting position in individual rooms where they could read, use their personal computers or watch television. From 2300 to 0800 the room lights were turned off during the sleep period. Blood samples were collected into EDTA treated tubes, immediately centrifuged at 4°C, and plasma was stored at -70°C until assay. Hourly blood sampling during sleep continued with minimal disturbance to subjects' sleep. To standardize food consumption and to provide adequate energy intake, subjects received every 3 hours 150 ml of specially designed liquid food (Ensure ® formula) with the following composition: proteins (5.49 g, 84% caseinate, 16% soy – 14.7% of the calories), fat (5.3 g, 32% of calories), carbohydrates (20 g, 77% corn syrup, 23% sucrose, 53.3% of calories), vitamins and minerals, in 77 ml water. No other food except for water was allowed. Experiment 2 Thes second experiment was identical to Experiment 1 except for the fact that the sleep period was delayed from 2300-0800 to 0720-1500. As before, subjects were admitted to the laboratory at 1800 and blood was withdrawn every hour starting at 1900 until 1900 on the next day. Sleep was monitored polygraphically as described before. Food was provided as in Experiment 1. Experiments 3 and 4 In these experiments, we conducted a methionine loading test at two times: 0900 and 2100. The selection of these times was based on the results of the first two experiments that demonstrated a daily nadir and a nocturnal peak in Hcy levels (see below). At the start of each methionine loading test, subjects were administered 100 mg/kg body weight methionine, mixed in fruit juice. Blood samples (5 ml) were taken into EDTA treated tubes before methionine loading, designated as time 0, and then at +2, +4, +6 and +8 hours after methionine administration. Light carbohydrate rich meals were provided at +1 and +6 hours after the methionine loading in each of the test periods. Measurement of amino acids and vitamins Plasma amino acids levels (Hcy, methionine, leucine, isoleucine and tyrosine) were measured in duplicates using a Biochrom 20 Amino-Acid analyzer (Pharmacia Biothech, Cambridge, UK) as described before [ 5 ]. The mean intra-assay CV was less than 3%. All samples from a single individual were analysed in a single run. In view of their involvment in Hcy metabolism, serum levels of folic acid and vitamin B 12 were also measured in all samples of all subjects using commercially available kits from Abbott. The assays were performed on an Abbott IMX analyzer that utilizes ion capture technology for folate determination and microparticle enzyme immunoassay (MEIA) technology for B 12 . The assays were performed according to the manufacturers' instructions and used quality control sera supplied by Abbott. Statistical analysis Repeated measurements ANOVA was used to compare the means of the amino acids between the first two experiments. To obtain the average 24-h Hcy curves, each individual data point was replaced by a z-transformation based on the individual 24-h mean and standard deviation, before averaging across subjects. Then, each of the individual time series was subjected to Cosinor analysis to determine its amplitude and acrophase. Since Experiment 1 was perfomed during the summer (August) and Experiment 2 was performed during early winter (late November), approximately 2 months after the change from Summer daylight-saving time to Winter time, during which the clock in Israel was advanced by one hour, the 24-h curves of the first experiment were advanced by 1 hour before the analysis. Then repeated measurements ANOVA was used to determine differences in acrophase between the experiments. In the third and fourth experimens, the concentrations of Hcy at times 0, 2, 4, 6, and 8 hours after methionine loading were analysed by repeated measures ANOVA to determine if there were any significant morning-evening differences in Hcy levels. Results All subjects successfully completed the four experiments. In experiment 1 when they slept from 2300 to 0700, average sleep latency was 22.2 ± 7.3 min, total sleep time was 407.3 ± 51.8 min, and sleep efficiency was 77.7 ± 9.2%. In experiment 2 when they slept from 0720 to 1500, average sleep latency was 4 ± 3.1 min, total sleep time was 371.5 ± 59.4 min, and sleep efficiency was 83.6 ± 12.2%. In spite of the reversal of the sleep-wake cycle, the 24 h means and coefficients of variation of Hcy in the two experiments were very similar to each other, 8.82 μmol/L and 29.7% and 8.51 μmol/L and 27.7%, in experiments 1 and 2, respectively. None of the subjects had abnormal Hcy levels (>15 μmol/L) at any point across the 24 hours. Figure 1 presents the average z-transformed 24-h curves of Hcy in the two experiments. In spite of the reversal of the sleep-wake cycle, the 24-h pattern of Hcy was remarkeably similar. In both experiments there was a midday nadir and a nocturnal peak in Hcy levels. In absolute terms, the daily rhythm in Hcy represents a change from nadir to peak values of 6.7 to 9.83 μmol/L (46.7%) and 7.4 to 10.55 μmol/L (42.6%), in experiments 1 and 2, respectively. Analysis of variance showed no significant difference in the average amplitude of the z-transformed rhythms of the two experiments, as determined by the cosinor analysis: 0.81 ± 0.19, and 1.07 ± 0.22 μmol/L, for experiment 1 and 2, respectively. There was, however, a significant difference between the timing of the average acrophase which was earlier by approximately 2 hours in experiment 1 than in experiment 2 (22:47 ± 0:45 vs. 0:54 ± 1:14, t = 3.77; p < .01). Figure 1 Daily rhythms in plasma concentration of Homocysteine. Rhythms were measured in 6 subjects who slept from 23:00 to 07:00 (Night sleep) or from 07:20 to 15:00 (Day sleep). Blood was withdrawn every hour starting at 19:00 until 19:00 the next day. Individual data points were transformed to Z-scores before averaging across subjects. For clarity purposes standard errors of data points are not presented. Magnitude of standard errors was approximatly 10% of mean values. Strikingly different 24-h patterns were observed for the other amino acids: methionine, leucine, isoleucine and tyrosine. In all, the average z-transformed 24-h curves revealed a strong influence of both the sleep-wake cycle and the feeding schedule. Their level was notably lower during the sleep period, regardless of its timing, and increased every two hours in synchrony with the times of feeding. This pattern is exemplified in Figure 2 for methionine. Identical patterns were observed for leucine, isoleucine and tyrosine (data not shown). Figure 2 Daily rhythms in plasma concentration of methionine. Rhythms were measured in 6 subjects who slept from 23:00 to 07:00 (Night sleep) or from 0720 to 1500 (Day sleep). Blood was withdrawn every hour starting at 19:00 until 19:00 the next day. Individual data points were transformed to Z scores before averaging across subjects. For clarity purposes standard errors of data points are not presented. Magnitude of standard errors was approximatly 10% of mean values. Note the large pulses in methionine concentrations that appeared in synchrony with the times of feeding. We did not find any evidence for rhythmicity in the concentrations of B 12 and folic acid. While folic acid showed a linear increase throughout the study period, the 24-h pattern of B 12 was rather constant with slight elevation during the night time (data not shown). Methionine loading As expected, methionine loading resulted in increased plasma Hcy levels during both morning and evening experiments (Figure 3 ). Analysis of variance did not reveal overall significant differences between morning and evening post-methionine Hcy levels. However, inspection of Hcy levels at each of the time points separately revealed some interesting trends. Before methionine loading, as could be expected from the daily rhythm in Hcy found in experiments 1 and 2, morning Hcy level tended to be lower by 1.18 μmol/L than the evening level (p < .11, paired t-test, two tailed). Moreover, the increase in Hcy from time 0 to 2 hours after loading was greater by a mean of 2.8 μmol/L in the evening than in the morning (p < .09, paired t-test, two tailed). This resulted in evening and morning levels of Hcy of 26.66 and 23.86 μmol/L, respectively. These differences became much smaller at +4, +6 and +8 after the loading. Figure 3 Plasma concentration of homocysteine before and after methionine loading. Shown are the means and standard deviations of plasma concentration of homocysteine in 6 subjects before (0 hr) and 2, 4, 6 and 8 hours after methionine loading at 09:00 and 21:00. Discussion The present study demonstrated that under strictly controlled dietary conditions plasma levels of Hcy shows significant daily rhythmicity, which is independent of the 24-h cycle of sleep and wake, with a peak at around 2200 to 2400. Previously, similar rhythmicity in Hcy with an evening peak was reported in obese diabetic patients by Bremner et al [ 12 ] and with nocturnal peak in rats by Baydas et al [ 13 ]. We further extended these findings by demonstrating that daily rhythms exist also in normal young adults. In contrast to Hcy, there was no daily rhythmicity in methionine, leucine, isoleucine and tyrosine, in which the 24-h pattern followed both the timing of sleep and the feeding schedule. Homocysteine is a non-protein sulfur containing amino acid, and an intermediate in the metabolism of the essential amino acid methionine. The metabolism of Hcy is accomplished by two major pathways, remethylation into methionine and transsulfuration to cystationine [ 14 ]. In remethylation, Hcy acquires a methyl group from N-5-methyltetrahydrofolate or from betaine to form methionine. The reaction with N-5-methyltetrahydrofolate is vitamin B 12 dependent while the reaction with betaine is not. In the transsulforation pathway, Hcy condenses with serine to form cystationine in an irreversible reaction catalyzed by the pyridoxal-5'-phosphate (PLP)-containing enzyme, cystationine beta synthase. Although we do not have any information as yet on the underlying mechanism responsible for the daily rhythm in plasma Hcy, it is most probably related to the balance between its rates of production and disposal. A high Hcy concentration could be due to an elevated production rate, a decreased rate of transsulforation, a decreased rate of remethylation to methionine, or any combination of these processes. The fact that the range of the daily variations in the plasma levels of Hcy is on the same order of magnitude as those seen in mild hyperhomocysteinemia, may suggest that the two phenomena share a common underlying mechanism. Mild hyperhomocystenemia seen under fasting conditions is due to mild impairement in the methylation pathway. This may be caused by folate or B 12 deficiencies, or by methylenetetrahydrofolate reductase thermolability. The variations in plasma vitamin concentrations, however, could not provide an explanation for the daily rhythms in Hcy. The 24-pattern of folate levels showed a linear increase from the beginning to the end of the study. Although the plasma concentrations of vitamin B 12 varied across the 24 hours – in contrast however to what was expected if B 12 were involved in the daily rhythm in Hcy, ie, increasing levels of B 12 associated with decreasing levels of Hcy – the 24-h pattern in B 12 was parallel to that of Hcy with a daytime nadir and a night time peak. Thus, it is unlikely that a daily rhythm in plasma vitamin concentrations can explain the daily rhythm in Hcy. The methionine loading test has been used to test the individual's ability to dispose of methionine through the transsulforation pathway [ 14 ]. The fact that the differences between Hcy levels after morning and evening methionine loading were rather small and limited to the first 2 hours after the loading may indicate that the transsulforation pathway does not play a role in generating Hcy rhythmicity. A different possibility that cannot be ruled out at this point is the involvement of the Hcy cellular export mechanism. The small amount of plasma Hcy is the result of a cellular export mechanism that is essential for keeping intracellular concentrations low to avoid potentially Hcy cytotoxic effects. Thus the daily rhythm in plasma Hcy may reflect variations in the activity of the cellular export mechanism, which result in varying levels of Hcy disposed to the plasma at different phases of the 24 hours rather than in its rate of metabolism. Further studies are needed to test this possibility. Finally, what may be the clinical implications of the present findings? We would like to suggest that the existence of a daily rhythm in Hcy concentration may have possible health-related consequences to shift workers, who were shown to be at an increased cardiovascular risk [ 15 ]. Firstly, reversing the meals' schedule to a nocturnal orientation such that the time of major meal coincides with the time of the physiological peak of Hcy may have at least transient cardiovascular consequences. It was shown that an increase in Hcy concentration rapidly induces impaired elasticity of the coronary microvascular and central arterial circulation [ 16 , 17 ], conditions predictive of increased cardiovascular events rate [ 18 ]. Furthermore, even small physiological increments in Hcy concentration, induced by low-dose methionine or dietary animal protein meals that are more relevant to shift workers, induce a dose-related graded impairement in endothelial functioning [ 19 ]. Thus, consuming methionine or animal-protein-rich foods during the middle of the night may result in a greater risk of severe transient impairment in endothelial function than when a similar meal is consumed at the habitual lunch time during the day. Although we did not find significant differences in Hcy concentrations after methioning loading at 0900 and 2100, as expected, morning levels tended to be lower, and the initial increase in Hcy during the first 2 hours after loading was greater by a mean of 2.8 μmol/L in the evening than in the morning. This difference bordered on statistical significance. It is possible that, had we performed the methinine loading closer to the time of the nocturnal peak in Hcy, between 10 PM and midnight, this day-night difference would have been larger. Secondly, we do not know how the desynchronization between the circadian system and the enviornment which occurs in rotating shift workers may affect the rhythm in Hcy concentrations and its overall plasma concentration. Recently, Martins et al [ 20 ] reported that long-haul bus drivers working shifts had higher concentrations of Hcy than a control group of day workers. In a study just completed in our laboratory we found that rotating shift workers who complained of disturbed sleep had significantly higher concentrations of Hcy than permanent day workers, or shift workers without sleep disturbances (paper submitted to press). Furthermore, life-style related factors like smoking and heavy coffee consumption that were shown to be associated with increased Hcy concentration [ 21 , 22 ], are more prevalent among shift workers than among day workers [ 23 ], and may also contribute to increased Hcy concentration. Of note, decreasing levels of melatonin induced by pinealectomy in rats were reported to be associated with increased plasma concentrations of Hcy, while treatment with exogenous melatonin restored it to basal concentrations [ 24 ]. Thus, suppression of melatonin by bright light during night work may be also associated with increased Hcy concentration. In view of the fact that Hcy is a risk factor for cardiovascular morbidity, more research is needed on the possible role of hyperhomocysteinemia as a cardiovascular risk factor in shift workers. Conclusions Our results demonstrated a daily rhythm in plasma concentrations of Hcy with a nocturnal peak that was independent of sleep-wake cycle and food consumption. There were no comparable rhythms in the concentrations of methionine, leucine, isoleucine and tyrosine, nor in the concentrations of B 12 and folic acid. Methionine loading at 9 AM and 9 PM produced a comparable time-dependent increase in Hcy concentrations with a tendency toward a higher increase in the evening during the first 2 hours after loading. In view of the possible involvement of Hcy in cardiovascular morbidity, and of the increased cardiovascular morbidity in shift wokers, these findings may have implications to shift workers health. List of abbreviations Hcy – homocysteine EEG – Electroencephalography EMG – electromyography EOG – electrooculography EDTA – ethylanediaminetetraacetic acid CV – coefficient of variation ANOVA – analysis of variance Competing interests None declared. Author's contribution PL and LL co-designed the study, supervised the data collection and data analysis and wrote the paper.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC520826.xml
535556	The architecture of chicken chromosome territories changes during differentiation	Background Between cell divisions the chromatin fiber of each chromosome is restricted to a subvolume of the interphase cell nucleus called chromosome territory. The internal organization of these chromosome territories is still largely unknown. Results We compared the large-scale chromatin structure of chromosome territories between several hematopoietic chicken cell types at various differentiation stages. Chromosome territories were labeled by fluorescence in situ hybridization in structurally preserved nuclei, recorded by confocal microscopy and evaluated visually and by quantitative image analysis. Chromosome territories in multipotent myeloid precursor cells appeared homogeneously stained and compact. The inactive lysozyme gene as well as the centromere of the lysozyme gene harboring chromosome located to the interior of the chromosome territory. In further differentiated cell types such as myeloblasts, macrophages and erythroblasts chromosome territories appeared increasingly diffuse, disaggregating to separable substructures. The lysozyme gene, which is gradually activated during the differentiation to activated macrophages, as well as the centromere were relocated increasingly to more external positions. Conclusions Our results reveal a cell type specific constitution of chromosome territories. The data suggest that a repositioning of chromosomal loci during differentiation may be a consequence of general changes in chromosome territory morphology, not necessarily related to transcriptional changes.	Background It is a longstanding observation that chromatin distribution in the interphase cell nucleus varies with the cell type. Flemming described differences in nuclear appearance in 1882 [[ 1 ], p.100]. Since then methodological advancements have made it possible to study nuclear chromatin architecture in much more detail. The spatial restriction of each chromosome to a limited area of the interphase nucleus, the chromosome territory, has been unequivocally demonstrated by fluorescence in situ hybridization (FISH) [ 2 , 3 ]. However, although progress has been made over the last decade [for reviews see [ 4 - 7 ]], the internal organization of chromosome territories is still largely unknown. Here we asked whether chromosome territories display differences between cell types in their internal chromatin organization. We amended our experimental approach with the determination of the position of a gene locus relative to its chromosome territory. In several previous studies it was observed that a number of active genes located preferentially at the surface of their chromosome territories or even outside [ 8 - 12 ], while others noted that active genes could also be positioned in the chromosome territory interior [ 13 ]. A general labeling of transcription sites resulted in signals throughout chromosome territories [ 14 , 15 ] demonstrating that the periphery of chromosome territories is not the only region where transcription occurs. Fluorescence in situ hybridization (FISH) studies investigating the major histocompatibility complex MHC [ 10 ] or the epidermal differentiation complex EDC [ 11 ] showed looping beyond the surface of the chromosome territory upon activation in up to 25% of the cases. Both loci are in the megabase size range with multiple co-regulated genes. Even higher frequencies of a location outside the territory were described for a gene rich human region without coordinate gene expression on chromosome 11p15.5 [ 16 ] and for genes of the Hoxb cluster in mouse embryonic stem cells entering differentiation [ 12 ]. It has thus been suggested that strongly expressed genes may be on chromatin loops that loop to the periphery of the territory, while genes expressed at low levels may occupy either a more interior or a random position [ 13 ]. Difficult to interpret were data concerning looping out of the β-globin gene locus from its chromosome territory in mouse erythroleukemia cells. In unstimulated cells where the locus shows DNase-hypersensitive sites but is not yet expressed, nearly half of the loci looped out. In stimulated cells where expression occurs, however, this was found only in about a third of the cases [ 17 ]. Consistent with the looping out of endogenous loci found in FISH studies, an opening of GFP-labeled artificial chromosomal regions was observed upon transcriptional activation or binding of transcription factors [ 18 - 24 ]. So far, a correlation of gene activation with increasing looping-out from the chromosome territory has only been shown for gene clusters but not for single genes. In the present study we have chosen the chicken lysozyme gene ( cLys ), which is highly active in macrophages, as a model system to explore the possibility of positional changes during activation of a single gene. cLys does not have co-regulated neighbors. Recently the gene cGas41 was found only 200 bp downstream of the polyA-site of cLys . cGas41 is expressed on a low level in all chicken tissues and cell lines tested, including all cell lines used here [ 25 ]. Macrophage differentiation is an interesting model system for studies of cell fate decisions. As all blood cells, macrophages originate from pluripotent hematopoietic stem cells and develop via defined multipotent and then progressively restricted precursor types. The developmental regulation of lysozyme in this differentiation system is well characterized. Expression is not detectable in multipotent myeloid precursors, which are able to differentiate to either the erythroid, granulocytic or the macrophage lineage (Figure 1 ). The gene is also not expressed in the erythroid lineage. Expression is first detected at a low level in granulocyte-macrophage precursors (myeloblasts) and is further upregulated in macrophages. By the addition of bacterial lipopolysaccharide (LPS) to macrophages, another tenfold increase in lysozyme expression is caused [ 26 ]. Studies of cLys regulation were greatly facilitated by cell lines representing these differentiation stages [ 27 , 28 ]. Figure 1 Cell lines used in this study. Pluses and minuses indicate the expression state of the lysozyme gene. Colors are the same as used in Figures 4, 5 and 7. The chicken karyotype consists of several pairs of so called macrochromosomes with sizes comparable to that of mammalian chromosomes and many much smaller microchromosomes [for review see [ 29 , 30 ]]. cLys is located on the short arm of chromosome 1 which is with about 190 Mbp comparable in length to human chromosome 4 [ 31 ]. In the present study, we investigated the large-scale chromatin organization of chromosome territories in well characterized cell lines representing the five chicken cell types described above (Figure 1 ). Multi-color 3D FISH was applied to cells with structurally preserved nuclei, followed by confocal microscopy and three-dimensional image analysis. We assessed the morphology of chromosome territories 1 and 8 by visual inspection and measured the dispersion of the painted territories in each cell type. We demonstrate that chromosome territory dispersal increases in the more differentiated cell types. Further, we determined the 3D positions of the chicken lysozyme gene domain (including cGas41 ) and the chromosome 1 centromere relative to their chromosome 1 territory. We found that not only the lysozyme gene domains but also the centromeres were mostly in the chromosome territory interior in multipotent myeloid precursor cells and relocated to the territory periphery in further differentiated cell types. In addition, we determined the radial positioning of the chromosome territories 1 and 8 within the nuclei of each cell type and measured nuclear volumes. Results The morphology of chromosome territories changes during differentiation 3D FISH was performed on formaldehyde fixed, structurally preserved nuclei. Visual examination of painted chromosome 1 and chromosome 8 territories revealed differences between the cell types (Figure 2 , Figure 3 ). Territories in multipotent myeloid precursor cells were relatively compact and homogeneously stained (Figure 2b , Figure 3a ). In proerythroblasts, territories were more diffuse and borders became less definable (Figure 2f,2g , Figure 3d ). These changes cannot be explained with an increase in nuclear volume since nuclei of proerythroblasts were smaller than those of myeloblasts (see below and Figure 4 ). In a minority of proerythroblasts, in addition to the labeled territories our paint probe labeled DNA-clusters in the center of the nucleus. These clusters had low DNA counterstain but were often associated with strongly counterstained regions (see arrow in Figure 2g ). The clusters may play a role in forming heterochromatin as observed during differentiation of human erythroid cells [ 4 ]. Chromosome territories in myeloblasts (Figure 2c , Figure 3b ) appeared less compact than in precursors but more compact than in proerythroblasts. Territories in unstimulated macrophages (Figure 2d ) had even more diffuse borders. In their interior we observed agglomerations of labeled DNA and lacunas in some cases. A maximum of dispersal was noted in stimulated macrophages (Figure 2e , Figure 3d ). Here, territories had grooved, fuzzy surfaces and a heterogeneous label throughout. Lacunas were frequent in the larger chromosome 1 territories. Figure 2 FISH with a chromosome 1 paint probe (red) and the lysozyme gene domain probe (green/yellow). (a) FISH on metaphase chromosomes. The chicken lysozyme gene domain is located on the short arm of chromosome 1. Note that the library probe mix used gives particularly strong signals at the centromeres (arrows). (b-g) 3D-FISH on structurally preserved nuclei. For each cell type, single confocal sections of one nucleus are shown. In b-f, nuclear outlines were drawn after the DNA counterstain which was omitted from the figure to avoid obstruction of the territory signals. In addition to the cLys domain signals, centromeres are in focus in some of the sections (arrows). (b) Multipotent myeloid precursor cell. (c) Myeloblast. (d) Macrophage without LPS-activation. (e) Macrophage with LPS-activation. On the right hand side, a threshold of 80 was applied to the territory signal of the central image to visualize disaggregation into several objects. While usually only few objects are present in any given focal plane, in this particular example the breakup is well recognizable. The algorithm applied in the calculations works on 3D-stacks, however. The macrophage cell line is aneuploid (see Methods), the cells shown in d and e have three territories with chromosome 1 material, each containing a cLys signal. (f) Erythroblast. (g) An additional section of the erythroblast shown in f visualizes a cluster of chromosome 1 material (red in left image) in a central nuclear area (arrow) with low DNA-counterstain but associated with a brightly stained region (see main text). Such clusters were less pronounced when only paint probes from early DOP-PCR-amplification rounds were used (see Methods for details). DNA counterstain is blue in left, gray in right image. Scalebar 5 μm for b-g. Whereas in precursor cells the lysozyme gene domain signal was found nearly always inside the territory, in differentiated cells more external positions were frequent. Note that the multipotent myeloid precursor cell has a relatively small nucleus and nuclear volume is increased in the further differentiated cell types. Figure 3 3D-FISH on structurally preserved cell nuclei with paints for chromosome 1 (red) and chromosome 8 (green). For each cell type, two confocal sections of one nucleus are shown. Nuclear outlines were drawn after the DNA counterstain which was omitted to avoid obstruction of the territory signals. (a) Multipotent myeloid precursor. (b) Myeloblast. (c) Macrophage activated with LPS. (d) Proerythroblast. Scalebar 5 μm. Figure 4 Nuclear volumes. Each dot indicates the volume of one nucleus. Nuclei from experiments with hybridization of chromosome 1 and cLys probes (left) and those with chromosome 1 and 8 probes (right) were sorted by size to allow an easier comparison by eye. See main text for mean values. A comparison of chromosome territory surface and chromatin texture by visual inspection is bound to subjective influences. To allow an unbiased, quantitative evaluation of chromosome territory morphology, we counted the number of objects to which chromosome territories disaggregate at increasing threshold levels. With a computer program newly developed for this purpose (for details see Methods and Figure 2e ) we could confirm the visual impression of relatively compact chromosome 1 territories in multipotent precursors by showing that at higher thresholds they disaggregate to smaller numbers of objects than the fuzzier territories of more differentiated proerythroblasts (Figure 5a ). Statistical inferences about the means of the maximal number of objects in these three cell types were highly significant as determined by Analysis of Variance (one-way ANOVA; F(2,119) = 58.5, p < 0.001; see Methods for details). Post-hoc Sidak tests revealed a significant difference between precursor cells and myeloblasts (p = 0.013) and highly significant differences between proerythroblasts and the two other cell types (p < 0.001). Chromosome 1 territories in macrophages also yielded high numbers of objects. However, macrophages of the utilized cell line contain an additional fragment of the short arm of chromosome 1 and sometimes complete additional chromosomes 1. Due to this aneuploidy object numbers are biased towards higher numbers. Results are thus not directly comparable with other cell lines. Notably, in stimulated macrophages territories disaggregate into more objects than in unstimulated ones, suggesting that stimulation triggered a change to a more dispersed chromatin texture (p < 0.001). The stronger dispersion of chromosome 1 territories in more differentiated cells was confirmed in a second experimental series with painted chromosome 1 and chromosome 8 territories (Figure 3 ) in multipotent precursors, proerythroblasts, myeloblasts and activated macrophages (data not shown). The DNA content of chicken chromosome 8 is about 30 Mbp [ 31 ]. This is roughly one sixth of the DNA content of chicken chromosome 1 and about two thirds of the smallest human chromosome, 21. Chromosome 8 was diploid in all utilized cell lines. As expected due to its smaller size, it disaggregated in all cell types to a much smaller number of objects (Figure 5b ). ANOVA analysis of all groups showed a highly significant aberration from the assumption of similar distributions in all cell types (F(3,116) = 38.2, p < 0.001). A difference between multipotent precursors, proerythroblasts or myeloblasts was not detectable (p > 0.9 in post-hoc Sidak tests) but in activated macrophages chromosome 8 territories did break up to a larger number of objects than in other cell types over a wide threshold range (p < 0.001 with all other cell lines). Figure 5 Disaggregation of chromosome territories in objects. (a,b) mean number of objects at increasing thresholds for chicken chromosome 1 (a) and chromosome 8 (b) territories. When the starting threshold of 20 is gradually increased, the nuclear background produces at first few and then many objects (around threshold 40). Suppression of nuclear background occurs at thresholds between 60–70, leaving chromosome territories only. The range above these thresholds is thus the most interesting since it is here where the territories start to break up in several objects (compare Fig. 2). These objects are gradually lost at further increasing thresholds. Values for macrophages are not directly comparable to other cell types since they contain additional chromosomes (see Methods). (c, d) Chromatin content per surface. Signal intensity of objects was divided by object surface area and averaged (see Methods for details). Since additional chromosomal parts add intensity as well as surface, this parameter is unsusceptible to aneuploidy. To allow a comparison of chromosome 1 territories in the aneuploid macrophages with those of other cell types, we analyzed the intensity of objects, i.e. their chromatin content, per surface area (Figure 5c,5d , see Figure legend and Methods for details). The chromatin content per object surface area was measured in multipotent precursor cells for both, chromosomes 1 and 8, again confirming their more compact structure in this cell type as compared to more differentiated cells. As a third parameter, we measured the average amount of labeled chromatin (signal intensity) per voxel (volume pixel) of the segmented objects. This parameter did not show differences between the cell types. Thus in all cell types a given amount of chromatin within the segmented objects was distributed over a similar volume over a wide threshold range (data not shown). The positions of the lysozyme gene domain and of the chromosome 1 centromere change during myeloid differentiation To determine the positioning of the lysozyme gene domain relative to the chromosome 1 territory, we performed dual color FISH with a chromosome 1 paint probe and a 20 kb plasmid probe for the lysozyme gene domain (Figure 2 ). By using a particular probe mix (see Methods) we were able to obtain an especially bright signal at the centromere in the same color channel as the paint probe. The positions of both, the lysozyme gene domain and the centromere, differed largely between the cell lines representing the various differentiation stages. To classify the positions of the signals, we used the scheme shown in Figure 6a . In multipotent precursor cells (Figure 2b ) we found the cLys gene domain inside the harboring chromosome territory, away from the territory border (categories A and B) in 48% of the cases (Figure 6b ). In additional 46% the gene signal was inside the territory touching the border (cat. C). It was previously shown that these cells do not express lysozyme but do show low level expression of the neighboring cGas41 [ 25 ]. We conclude that a location inside the territory is compatible with low-level expression. In further differentiated cells, the lysozyme gene locus was found more often in the periphery of chromosome 1 territories (Figure 2 , Figure 6b ). This is true for myeloblast/macrophage lineage cells with lysozyme expression as well as for proerythroblasts in which the expression of cLys and cGas41 does not differ from the precursor cells. The most peripheral localization, sometimes outside of the painted territory, was found in activated macrophages (Figure 2e ) where the cLys expression level is highest. Here 82% of the gene signals were on the surface or further outside (cat. D-F). The difference in distribution between precursor cells and all other cell types was highly significant (p < 0.001) as was the difference between activated macrophages and all other cell types (p < 0.001). The difference between unstimulated macrophages and proerythroblasts (p = 0.003) or myeloblasts (p = 0.024) was also significant whereas the difference between myeloblasts and proerythropblasts was not (p = 0.5). To test the robustness of our results, we repeated statistical analysis after reducing the number of applied categories of localization to only three: internal (A+B), peripheral (C-E) and external (F+G). We confirmed highly significant differences when precursor cells or activated macrophages were compared to any other cell type (p = 0.003 or smaller). In summary, for the lysozyme gene we found a change in position from interior when not expressed in myeloid precursor cells to peripheral when strongly expressed in activated macrophages. This would fit the hypothesis that highly expressed genes are preferentially located in the territory periphery, as it was found previously for large gene clusters [ 10 , 11 ]. However, this hypothesis does not explain the difference in positioning between the precursors and the proerythroblasts. Figure 6 Classification of cLys gene domain and centromere signals. (a) Scheme used to classify the localization of gene and centromere signals relative to their chromosome 1 territory [adopted from 11]. The red ellipsoid represents the territory, the yellow dots the signals of genes or centromeres. Categories are: A, inside the territory delineated by the paint probe, away from the surface. B, inside, closer to the territory surface but not touching it. C, inside and touching the surface. D, on the surface. E, outside and touching the surface. F, without contact to the territory but in immediate neighborhood. G, away from the territory. (b, c) Distribution of the lysozyme gene domain (b) and the centromere (c) relative to the chromosome 1 territory in 5 different cell types. Between 79 and 95 cLys gene domain and centromere signals were evaluated for each cell line and assigned to the categories A-G. Surprisingly, the centromeres of chromosome 1 showed a change in distribution very similar to the cLys gene domain (Figure 6c ). In no cell type we found a significant difference between the two (p = 0.255 or larger). For example, in multipotent precursors all detected centromeres were inside the territory, either without (cat. A, B) or with contact to the surface (cat. C). In contrast, in activated macrophages 93% of the centromeres were on the surface (cat. D) or outside with contact to the surface. Again, the difference in distribution between precursor cells and all other cell types was highly significant (p < 0.001) as was the difference between activated macrophages and all other cell types (p < 0.001). Myeloblasts and unstimulated macrophages showed a moderately significant difference (p = 0.044) whereas the differences between proerythroblasts and myeloblasts (p = 0.654) or unstimulated macrophages (p = 0.084) were not significant. When applying only three categories of localization as described above, differences between precursor cells or activated macrophages and any other cell type again where highly significant (p = 0.001 or smaller) with the exception of precursor cells compared to myeloblasts showing a moderate significant difference (p = 0.035). Silent lysozyme genes do not colocalize with centromeric heterochromatin Brown et al. [ 32 , 33 ] showed examples of genes in hematopoietic cell types, which were tethered to centromeric heterochromatin when silent, but located remote from heterochromatin when active [ 4 , 32 , 34 ]. We asked whether the same nuclear location could be found for silent and active lysozyme genes. A probe that would label all centromeres of chicken chromosomes is not available. We reasoned that if the inactive lysozyme gene would be tethered to centromeric heterochromatin, at least in a number of cases this centromeric heterochromatin should include the centromere of its own chromosome. High precision 3D-distance measurements [ 35 , 36 ] from the lysozyme gene domain to the corresponding chromosome 1 centromere in the data sets described above showed that there is no such colocalization (Table 1 ). In those cell types where the lysozyme gene is completely shut off, the smallest distances found were 0.6 μm in proerythroblasts and 0.5 μm in multipotent precursor cells. This finding rules out a colocalization of the two loci. Distances in multipotent precursors are on average somewhat smaller than in the other cell types (Table 1 ). This can be attributed to a more compact chromosomal shape and to a smaller nuclear volume in this cell type (see below). Table 1 3D-Distance measurements between the lysozyme gene domain and the centromere of the corresponding chromosome 1 in interphase nuclei of different cell lines. multipotent precursor cells proerythroblasts myeloblasts macrophages LPS induced macrophages evaluated territories 70 85 80 89 78 mean value 1,5 μm 2,1 μm 2,5 μm 2,2 μm 2,2 μm median 1,4 μm 2,0 μm 2,2 μm 2,2 μm 2,1 μm Standard-deviation 0,8 0,8 1,1 0,8 0,9 Smallest value 0,5 μm 0,6 μm 0,7 μm 0,7 μm 0,5 μm Largest value 4,8 μm 5,8 μm 5,3 μm 4,4 μm 5,1 μm Radial positioning of chromosome territories 1 and 8 within the nucleus Habermann et al. [ 37 ] showed that in embryonic chicken neuronal and fibroblast nuclei the gene poor macrochromosomes 1–5 are located at the nuclear periphery. Intermediate chromosomes 6–10 were found further inside but not as central as the gene rich microchromosomes. Respective results were also found in human and other primate cells [ 38 - 43 ]. According to the current release of the chicken genome sequence [ 31 ] chromosome 1 has a length of 188 Mbp with ~11 genes/Mbp and chromosome 8 has 30 Mbp with ~19 genes/Mbp. These numbers are likely to change somewhat with further releases of the sequence. They do suggest however that the relative gene content is higher for the smaller chromosome 8. To test for a difference in the radial distribution of individual chicken chromosome territories, we measured 3D radial distributions in the nuclei painted with chromosomes 1 and 8 from experiments described above (Figure 7 ). Figure 7 Radial distribution of chromosomes 1 (red) and 8 (green) in nuclei of (a) multipotent precursor cells (n = 37), (b) myeloblasts (n = 27), (c) activated macrophages (n = 23) and (d) proerythroblasts (n = 40). Unlike in the median distribution used for determination of significance levels, in the graphs shown here all voxels of a segmented signal are represented. Chromosome 8 has only about one sixth of the size of chromosome 1. Accordingly, its interphase territories are much smaller, leading to a smaller sample of voxels and thus accounting for less smooth curves than for chromosome 1 territories, e.g. in myeloblasts. All curves for each chromosome are shown in one graph in a supplemental figure in additional file 1. In multipotent myeloid precursor cell nuclei, chromosome 1 territories were located more peripheral than chromosome 8 territories (p < 0.005). The same was true for proerythroblasts (p < 0.001) but no significant difference was present in myeloblasts (p > 0.1). These three cell types grow in suspension and have round nuclei. In flat nuclei of LPS-stimulated macrophages we again found chromosome 1 territories more peripheral than chromosome 8 territories (p < 0.005). The radial distribution is also reflected by the signal median values. It indicates at which nuclear radius half of the signal voxels are more internal and half are more external. In 73% of the precursor cells the chromosome 1 signal median is more external than the chromosome 8 signal median. The respective values are 52% for myeloblasts, 82% for proerythroblasts and 91% for activated macrophages. When comparisons between cell types were made, chromosome territories 8 showed a rather similar radial distribution in all cell types (p > 0.1 or >0.05 for all combinations with a frequency maximum of ~10% at or near 80% of the nuclear radius, Figure 7 , supplemental figure in additional file 1 ). Chromosome 1 territory distribution did show significant differences between cell types (Figure 7 , supplemental figure). Chromosome 1 territory radial distribution was compared between nuclei co-hybridized either with the cLys -probe (series 1, Figure 2 , not shown as graph) or the chromosome 8 paint probe (series 2, Figure 3 and Figure 7 ). In LPS-stimulated macrophages chromosome 1 territories were further outside than in proerythroblasts (p < 0.001 in series 1 and series 2), in myeloblasts (p < 0.001 in series 1 and p < 0.01 in series 2) and in precursors (p < 0.01 in series 1 and p < 0.05 in series 2). No significant difference was found between stimulated and unstimulated macrophages (p > 0.1, series 1 only). A significant difference in radial distribution of chromosome 1 territories between precursors and myeloblasts was found in series 1 (p < 0.01) but not in series 2 (p > 0.1). The same was true for the comparison of precursors and proerythroblasts (series 1: p < 0.001; series 2: p > 0.1). Proerythroblasts and myeloblasts did not show a significant difference (p > 0.1 in both series). The radial distribution of the lysozyme gene domain did not differ significantly between the cell lines (p > 0.1). The mean value of the signal medians was between 71 and 76% of the nuclear radius for all cell lines. In erythroblasts, chromosome 1 territory signal medians were more internal than cLys signal medians (66% vs. 72%, p < 0.005). In unstimulated macrophages the opposite was true (76% vs. 73%, p < 0.05). In the other cell types the differences between the signal medians of cLys and chromosome 1 territories were between 0–2% and not significant. Our results are compatible with previous data [ 37 ] in describing an external location for chromosome 1 and a somewhat more internal location for chromosome 8. In addition we find differences in the radial distribution of chromosome territories between the chicken cell types that have not been observed previously. Nuclear volumes The volume of nuclei was measured in confocal stacks of DNA counterstain of data sets described above by the same program that was used for the calculation of the radial distributions (Figure 4 ). The mean value for nuclear volumes for multipotent myeloid precursors was 212 μm 3 (± 75 standard deviation, n = 76) and for myeloblasts 327 ± 101 μm 3 (n = 50). The difference between the two cell types was highly significant (p < 0.001). The mean nuclear volume of proerythroblast was 296 ± 109 μm 3 (n = 78). Proerythroblasts did not consistently show significant differences when compared to precursor cells or myeloblasts. Since the macrophage cell line carries additional chromosomes, its nuclear volume cannot be directly compared to the other cell lines. For unstimulated macrophages we determined nuclear volumes of 459 ± 91 μm 3 (n = 42) and for LPS stimulated macrophages 554 ± 139 μm 3 (n = 78). This difference was not significant. The measured nuclear volume depends on the chosen signal threshold. Since the volume increases by the power of 3 with the nuclear radius, small differences in the segmentation can lead to large volume differences. A cautious interpretation of such measurements is thus advised. The difference between multipotent myeloid precursors and myeloblasts is so large however that we are confident that it is real and not a thresholding artifact. Discussion Cell type specific chromatin distributions on the nuclear level have been described for over a century [[ 1 ], p.100]. Differences between cell types have also been described for the distribution of heterochromatin detected with antibodies against methylated histones [ 44 ], for the radial distribution of gene rich and gene poor chromosomes [[ 37 , 40 , 45 ] this study] and the occurrence of clustering between specific chromosome territories [ 45 ]. Here we show an example were large-scale chromatin organization of chromosome territories changes during differentiation, and thus add a new feature to the list of nuclear architectural properties that can differ between cell types. To quantify chromatin dispersal of labeled chromosomes in cells of various differentiation stages, we counted the number of separate, labeled chromatin objects to which the chromosome territories disintegrated at increasing thresholds. In the investigated chicken cell types, chromosome territories of further differentiated cell types disaggregated into more objects. An increase in object number during differentiation may indicate that a significant number of compact chromatin domains with silent genes separate from each other into several, more decondensed, "open" chromatin domains. This would increase the accessibility to transcription factor complexes from the interchromatin compartment by increasing the available chromatin surface area of the chromosome territory. In human lymphoblasts gene rich chromosome 19 territories were found more decondensed than gene poor chromosome 18 territories [ 38 ] and electron microscopic evidence suggests that active genes are exposed at chromatin domain surfaces in a zone called the perichromatin region, a transitional zone that marks the transition form the chromatin domain periphery to the interchromatin compartment [ 46 ]. A caveat of this interpretation is that so far no unequivocal proof for a profound influence of higher order chromatin compaction on gene activation and gene silencing has been presented. A further possibility is that inactive loci in the more differentiated cells do not require a tight spatial silencing by chromatin compaction anymore because the set of available molecular activators and repressors has changed. At present we can only speculate whether the correlation of increased dispersal of chromosome territories with differentiation state is a widespread feature or restricted to a few chicken blood cell types. At the highest, nuclear level of chromatin organization it was described for mammalian nuclei that heterochromatin shows distinct patterns of large blocks in terminally differentiated cells but not in blood stem cells and tumor cells [ 47 , 48 ]. This indicates a compaction of chromatin in differentiated cells rather than in their precursors, unlike in our current data on the chromosome territory level. It is possible, that heterochromatin (consisting mainly of repetitive sequences) and the bulk of labeled chromosome territories behave differently in these aspects. Due to their suppression with unlabeled repetitive DNA, repetitive sequences are underrepresented in chromosome territories detected by FISH as in the present study. Also, the rather small amount of repetitive sequences and heterochromatin in the chicken genome (genome size ~1.2 Gbp according to [ 29 ], 1.1 Gbp according to [ 31 ]) as compared to mouse and human genomes (~3.2 Gbp each, [ 31 ]) may lead to differences in nuclear organization. Multipotent myeloid precursor cells have the smallest nuclei of the cell types investigated here. Myeloblasts have on average larger nuclei than proerythroblasts. If the observed disaggregation of chromosome territories were based on a nuclear volume increase, the larger myeloblast nuclei should have a stronger dispersion of chromosome territories than proerythroblasts. However, the opposite is true (Figure 5 ). We thus conclude that chromosomal dispersion is not related to nuclear size. In general, we observed larger nuclear volumes for further differentiated cell types. Increasing nuclear size was also observed during maturation of nerve ganglia cells [ 49 ] while a volume decrease was described during the maturation of lymphocytes [ 47 ]. Accordingly, unlike recently suggested [ 50 ], a decrease of nuclear size does not appear to be a phenomenon generally associated with terminal differentiation events. The lysozyme gene domain is positioned inside the chromosome 1 territory in multipotent myeloid precursor cells where the lysozyme gene is inactive, but on the surface or outside in most of the territories in activated macrophages where the gene is strongly expressed. We thus did find a tendency to more exterior regions of the chromosome territory for the highly expressed gene from in activated macrophages although actual looping-out (without visible contact to the territory) was observed in only about 6%. Interestingly, while the radial distribution of the lysozyme gene domain within the nucleus is about the same in all cell types, the harboring chromosome 1 territories show differences. The finding that in erythroblasts the cLys signal is more exterior than the chromosome 1 territory signal median but in unstimulated macrophages the opposite is true also argues for a cell type specific organization of chromosome territories. A similar observation has been described for a IL-3 induced differentiation of human leukemic K562 cells where the β-globin gene cluster does not change nuclear position but the harboring chromosome 11 territory does [ 51 ]. However, in human hematopoietic cells a relocation of a gene to a different preferential radial position [ 52 ] or to or away from heterochromatic nuclear compartments has been observed for some genes, correlated with transcriptional regulation at different developmental stages [e.g. [ 33 , 53 ]]. Unfortunately, the harboring chromosome territories were not labeled in these studies. While we can exclude a tethering of the inactive lysozyme gene to the centromere, at first glance this result seems compatible with the hypothesis that inactive genes are stored away in internal regions of the chromosome territory and active genes are on their surface or even looped out. However, several aspects suggest an alternative explanation. (i) Embedded in the chicken lysozyme gene domain is a second gene, cGas41 , which, albeit on a low level, is expressed in all cell types used in this study, including multipotent myeloid precursor cells [ 28 ]. Thus we found an example of an active gene with a location inside the territory as it was described previously for some mammalian genes [ 13 ]. (ii) Although the position of the lysozyme gene domain is most peripheral in activated macrophages where the expression is highest, we also found a shift towards more external positions from multipotent myeloid precursor cells to further differentiated proerythroblasts, both non-expressing cell types. (iii) In addition to the lysozyme gene domain, we investigated the chromosome 1 centromere. Surprisingly, both loci showed a very similar distribution in all cell types investigated. Transcription from centromeres has been observed in yeast [reviewed in [ 54 ]] and from a human neocentromere [ 55 ]. Formally, we thus cannot fully exclude that centromeric transcription may occur in chicken. We regard it as extremely unlikely, however, that tissue dependent differences in centromeric transcription play a role in the cell type specific spatial positioning found here. The observed modification in the morphology of chromosome territories during differentiation rather invites to hypothesize that the positional changes observed for the lysozyme gene domain are not restricted to this particular chromatin loop or only to those chromatin loops which harbor genes that become activated during cell differentiation. Instead, these positional changes may reflect a more general, differentiation dependent change in large-scale chromatin structure. Differentiation processes may thus have a more global impact on chromatin structure than previously suspected. Conclusions We describe several features of chromosome territory organization that differ between various hematopoietic chicken cell lines. While multipotent myeloid precursor cells had compact chromosome territories, the more differentiated cell types investigated here displayed somewhat disaggregated, diffuse territories. Although nuclear volumes generally are larger in the more differentiated cell types, they do not correlate with the changes in chromosome territory morphology. The chicken lysozyme locus as well as the chromosome 1 centromere is located preferentially in the interior of the chromosome territory in precursor cells and more external in more differentiated cells. Our data suggest that such a repositioning of chromosomal loci during differentiation may be a consequence of general changes in chromosome territory morphology, not necessarily related to transcriptional changes. The radial distribution of chromosomes 1 and 8 also differed between cell types. In summary our data argue for a cell type specific chromosome territory organization in the investigated cell lines. Methods Cells All cells are from retrovirally transformed chicken cell lines [ 56 , 57 ]. HD50MEPs represent multipotent myeloid precursor cells before the separation of erythroid and monoblast/macrophage lineages. Proerythroblast-like HD37 were used as an example for a differentiated cell type that is negative for lysozyme expression. Myeloblasts (HD50 myl, a cell line derived from the same precursors as HD50MEP) are an intermediate stage in the differentiation to macrophages (HD11). While macrophages grow adherent, all others grow in suspension. Cytogenetic analysis showed that all lines were diploid for chromosome 1 except HD11. The latter had 2 to 4 normal chromosomes 1 plus a translocation chromosome with the short arm of #1 including cLys but not the #1 centromere and also other karyotype aberrations, e.g. a trisomy of chromosome 2. All lines were diploid for chromosome 8. Cells were cultured in IMDM supplemented with 2% chicken serum, 8% fetal calf serum and 2 mmol L-Glutamin and maintained at 37°C with 5% CO 2 . For 3D-FISH experiments cells were cultured on #1.5 glass coverslips (170 μm thick). Except for macrophages, coverslips were pretreated for 35 min with poly-L-lysine (0.1 mg/ml; MW 300000, Sigma, Deisenhofen, Germany, P5899). Activation of HD11 was achieved by the addition of 5 μg LPS (Sigma, L-8275) per ml medium and subsequent cultivation over night [ 58 ]. Activated macrophages become postmitotic. Coverslips with attached cells were washed with PBS, fixed in 1,2% formaldehyde freshly made from paraformaldehyde [ 59 ] for 15 min, washed in PBS 3 × 3 min, incubated in 0,5% Triton X-100 in PBS for 20 min and equilibrated in 20% glycerol in PBS for 60 min. Dipping in liquid nitrogen and thawing at room temperature in 20% glycerol/PBS was performed five times. After washing 3 × 3 min in PBS and incubation in 0,1 M HCl for 10 min, coverslips were washed 2 × 3 min in 2 × SSC and stored in 50% formamid/ 2 × SSC for at least 1 h but usually overnight or longer at 4°C. FISH Chromosome-specific paint probes for chicken chromosomes 1 and 8 were kindly provided by Dr. Felix Habermann and Dr. Johannes Wienberg, Munich. They were generated by flow sorting of metaphase chromosomes and subsequent degenerated oligonucleotide primed (DOP)-PCR [ 60 ]. They produce a uniform labeling of metaphase chromosomes. When the amplification products were repeatedly reamplified using the same PCR conditions, however, we noted after about a dozen rounds that the label on metaphase chromosomes became non-uniform in appearance indicating a reduction in complexity by the loss of sequences. The higher likelihood of retaining repetitive sequences was reflected by the finding that the by far brightest spot was found at the centromere as identified by the primary constriction in the DNA counterstain. To identify chromosome 1 centromeres together with completely delineated chromosome 1 territories, we used a mixture of an early amplification product with repeatedly reamplified probe. We thus obtained intense painting of the entire chromosome and a particular bright signal at the centromere (Figure 2a ). In experiments where chromosomes 1 and 8 were cohybridized, detection of centromeres was not necessary and thus only early amplification products were used. DOP-PCR for amplification and labeling (biotin-16-dUTP for #1 and digoxigenin-16-dUTP for #8, both from Roche Applied Science, Mannheim, Germany) was performed as described [ 61 ]. The lysozyme gene domain is contained on the pPoly-III-i Lys-plasmid [ 62 ]. It was labeled by nick-translation with digoxigenin-dUTP. Chicken cot 1 DNA was prepared from liver using standard procedures. The same result was obtained for the chicken chromosome 8 paint probe (data not shown). All DNA for a given assay was mixed, precipitated and solved in deionized formamide. The same volume of 20% dextransulfat in 2 × SSC was added. In experiments with cLys the following amounts of DNA were precipitated for each μl hybridization mix: 2 μl label-DOP-PCR product of an early amplification round of the #1 paint plus 2 μl of a highly amplified paint probe for centromere detection, 50 ng pPoly-III-i Lys, 2.5 μg cot 1 DNA. When paint probes for #1 and #8 were cohybridized, 2 μl label-DOP-PCR product of an early amplification round was used for each chromosome and supplemented with cot1 DNA as above. Denaturation was 5 min at 85°C. Preannealing with the cot 1 DNA was performed for 25 min at 37°C. For 3D FISH, coverslips with cells were denatured in 70% formamide for 3 min at 70°C, and placed immediately in ice-cold 50% formamide/2 × SSC. They were then incubated with 5 μl hybridization mix under a sealed 18 × 18 mm 2 coverslip at 37°C for 24 h-72 h. Air-drying was carefully avoided at all steps. Metaphase chromosomes were hybridized as described [ 37 ]. Detection was performed as described [ 63 ], using rabbit anti-digoxigenin (1:500) and goat anti-rabbit-Alexa488 (both from Sigma) and for biotin detection Avidin-Cy3 (Dianova, Hamburg, Germany). Slides were counterstained with DAPI and TOPRO-3 (Molecular Probes, Eugene, Oregon) and mounted in Vectashield (Vector Laboratories, Burlingame, CA). Confocal laser scanning microscopy 3D image stacks (8 bit) were recorded with a Leica TCS SP confocal laser scanning microscope equipped with an argon (488, 514 nm) and a HeNe laser (633 nm) (Leica Mikrosysteme, Bensheim, Germany). A 100 × N.A. 1,4 oil objective was used to obtain stacks with a voxel size of 0.08 × 0.08 × 0.24 μm. Nuclei with separated homologous chromosome territories were preferably selected for recording. To measure the chromatic aberration, 0.5 μm multi-color latex beads (Polysciences Europe, Eppelheim, Germany) were fed to activated macrophages. After phagocytosis the cells were fixed and embedded like 3D-FISH preparations. The beads were in the cytoplasma and thus their optical environment was closer to the situation of FISH signals than beads mounted directly on a glass cover slip. The chromatic aberration in x, y and z was corrected before the assignment of signals to categories or distance measurements were performed. Image analysis The program used for object counting was first applied by Cremer et al. [ 44 ]. The original 8-bit gray level image stack is first subjected to Gaussian filtering and then normalized, i.e. the lowest existing gray value is set to zero, the highest to 255 and the values in-between are recomputed accordingly. A starting threshold of 20 was chosen and voxels above the threshold were determined. Of those, all touching voxels (26 voxel neighborhood) were combined to objects. Only structures with at least 10 voxels were regarded as 'objects' and included in the further analysis. After counting the objects and calculating the other parameters, the threshold was raised for 5 gray levels, object determination and calculation was repeated and so on until the highest applied threshold of 250 was reached. For statistical calculations, from each nucleus the maximum number of objects occurring at any threshold of 80 or higher was used. The restriction to thresholds of 80 or higher was made to confidently exclude background objects. Statistical inferences about the means of the maximum values of objects were based on one-way analyses of variance (ANOVA). Post-hoc comparisons generating p-values relied on Sidak tests. These test were performed with SPSS version 12 (SPSS Inc., Chicago, IL). For the second parameter, for each nucleus at each threshold the ratio (object intensity)/(object surface voxels) was measured for all objects and averaged. Object surface voxels are defined as voxels belonging to an object and having at least one of the 26 neighbors not belonging to the object. The unit is 1/μm 2 . This value reflects the amount of intensity (chromatin) that is enclosed in a given surface area. Chromosome territories with a richly folded surface thus have a rather low value whereas compact, homogeneous territories have a higher value. Most nuclei had zero or few objects at very high threshold levels (Figure 5a,5b ). Therefore, the calculation of meanvalues for the intensity/surface parameter was stopped when less than five nuclei with at least one object where left. For the third parameter, average amount of labeled chromatin per volume, the intensity of all voxels belonging to an object was summed up and divided by the number of object voxels and the average over the objects was computed. Localization of cLys and centromere signals with regard to chromosome 1 territories: Image stacks were imported in ImageJ (freely available on the internet at [ 64 ]) and each fluorochrome was assigned to one channel of an RGB-Stack. A Gaussian Blur filter was applied before using the 'brightness & contrast' function to enhance signals and decrease background. The 'make montage' function was then used to show all planes of the RGB-stack side by side. For each gene or centromere signal the z-plane was selected where it was brightest. This plane was then used for the categorization (Figure 6a ) [ 11 ]. The Mann-Whitney-U test from SPSS was used for statistical analysis. For the aneuploid cell line HD11 an evaluation was performed only if normal chromosomes were unequivocally distinguishable from the translocated p-arm (without centromere). The latter was excluded from further analysis. High precision 3D-distance measurements [ 35 , 36 ]: Gravity centers of the signals were determined with Showpos, a program written by Kurt Sätzler, Heidelberg, for Silicon Graphics Workstations running under Irix. The 3D coordinates of cLys and the respective centromere were corrected for the chromatic aberration and the distance was calculated. The quantitative assessment of 3D radial distributions of painted chromosome territories and the measurement of nuclear volumes was performed using a program developed by Dr. Johann von Hase, Heidelberg which is described in detail elsewhere [ 42 ]. To determine the statistical significance of radial distribution differences, we used the medians of each signal in each nucleus and applied the two-sided Kolmogorov-Smirnov test [ 65 ]. The same test was applied to nuclear volumes. Authors contributions The study was designed by SD together with CB and TC. First experiments and development of techniques were performed by RM. S Stadler and VS performed 3D-FISH, microscopy, determination of cLys and centromere 1 localization and high precision distance measurements of all evaluated cells. RM carried out radial distribution statistics and volume measurements. All three were supervised by SD and TC. S Stein programmed and adapted the object counting program, supervised by CC. Object counting and statistical analysis was performed by SD. The manuscript was written by SD with substantial contributions by CB, TC and VS. All authors read and approved the final manuscript. Supplementary Material Additional File 1 Radial distribution of chromosomes 1 and 8 in nuclei of different cell types. These graphs show the same curves as presented in Figure 7 , but now all curves for chromosome 1 are combined in (a) and those for chromosome 8 are combined in (b). Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC535556.xml
509293	The Regenerative Plasticity of Isolated Urodele Myofibers and Its Dependence on Msx1	The conversion of multinucleate postmitotic muscle fibers to dividing mononucleate progeny cells (cellularisation) occurs during limb regeneration in salamanders, but the cellular events and molecular regulation underlying this remarkable process are not understood. The homeobox gene Msx1 has been studied as an antagonist of muscle differentiation, and its expression in cultured mouse myotubes induces about 5% of the cells to undergo cellularisation and viable fragmentation, but its relevance for the endogenous programme of salamander regeneration is unknown. We dissociated muscle fibers from the limb of larval salamanders and plated them in culture. Most of the fibers were activated by dissociation to mobilise their nuclei and undergo cellularisation or breakage into viable multinucleate fragments. This was followed by microinjection of a lineage tracer into single fibers and analysis of the labelled progeny cells, as well as by time-lapse microscopy. The fibers showing morphological plasticity selectively expressed Msx1 mRNA and protein. The uptake of morpholino antisense oligonucleotides directed to Msx1 led to a specific decrease in expression of Msx1 protein in myonuclei and marked inhibition of cellularisation and fragmentation. Myofibers of the salamander respond to dissociation by activation of an endogenous programme of cellularisation and fragmentation. Lineage tracing demonstrates that cycling mononucleate progeny cells are derived from a single myofiber. The induction of Msx1 expression is required to activate this programme. Our understanding of the regulation of plasticity in postmitotic salamander cells should inform strategies to promote regeneration in other contexts.	Introduction There is currently a significant focus on strategies to promote regeneration in adult mammals and therefore a renewed interest in the mechanisms that underlie regeneration in urodele amphibians. An adult salamander such as the newt or axolotl can regenerate its limbs and tail, jaws, ocular tissues such as the lens, and small sections of the heart ( Goss 1969 ; Eguchi et al. 1974 ; Oberpriller and Oberpriller 1974 ; Okada 1991 ; Ghosh et al. 1994 ; Brockes 1997 ; Nye et al. 2003 ). A key feature of urodele regeneration is the local plasticity of differentiated cells at the site of tissue injury or removal ( Brockes and Kumar 2002 ; Odelberg 2002 ; Del Rio-Tsonis and Tsonis 2003 ; Tanaka 2003 ). This has been investigated for pigment epithelial cells of the iris ( Eguchi et al. 1974 ; Simon and Brockes 2002 ; Imokawa and Brockes 2003 ; Imokawa et al. 2004 ), cardiomyocytes ( Oberpriller et al. 1995 ; Bettencourt-Dias et al. 2003 ), and skeletal myofibers and myotubes ( Hay 1959 ; Lo et al. 1993 ; Tanaka et al. 1997 , 1999 ; Kumar et al. 2000 ; Echeverri et al. 2001 ), all of which reenter the cell cycle during regeneration, in contrast to their mammalian counterparts. A second aspect of plasticity is the ability of multinucleate skeletal muscle cells to fragment into viable mononucleate cells that then contribute to the regenerate. This process, sometimes referred to as cellularisation, was described in classical studies of limb regeneration ( Thornton 1938 ; Hay 1959 ), but was first analysed with marked cells by implantation of cultured newt myotubes labelled by microinjection with a lineage tracer ( Lo et al. 1993 ) or by an integrated retrovirus ( Kumar et al. 2000 ). The myotubes were effectively converted to mononucleate cells that proliferated in the blastema, and this process occurred in cells that were blocked from cell cycle reentry ( Velloso et al. 2000 ), thus showing that the two aspects of plasticity are not linked mechanistically. In an important recent contribution, myofibers were labelled in situ by microinjection in the tail of the larval axolotl ( Echeverri et al. 2001 ). After amputation of the tail, the myofibers fragmented into viable mononucleate cells, thus establishing that cellularisation occurs during regeneration and contributes to the proliferative zone or blastema. Our understanding of this intriguing process has received considerable impetus from the recognition of two manipulations that induce mammalian myotubes to undergo fragmentation. The first is exposure to myoseverin, a trisubstituted purine derivative isolated from a combinatorial library ( Rosania et al. 2000 ). It evokes depolymerisation of microtubules, apparently by interacting directly with tubulin, as well as inducing changes in the expression of genes that are implicated in tissue remodelling and wound healing. The second is the conditional expression of the homeobox gene Msx1 in mouse myotubes ( Odelberg et al. 2000 ). Msx1 has been studied as an antagonist of myogenic and osteogenic differentiation (reviewed in Bendall and Abate-Shen 2000 ) and is expressed in the migrating precursor cells of limb muscle during chick development, apparently to prevent precocious differentiation ( Bendall et al. 1999 ). The expression in mouse C2C12 myotubes evokes two aspects of plasticity that occur in 5%–10% of the cells; the first is cleavage of the cells into smaller multinucleated myotubes, which remain viable, and the other is the formation of mononucleate cells capable of division ( Odelberg et al. 2000 ). In the latter case, the clonal progeny of a single myotube were shown to be capable of several pathways of mesenchymal differentiation. The studies on cellularisation by myoseverin and Msx1 have underlined that mammalian as well as urodele cells are capable of this response ( Rosania et al. 2000 ; Odelberg 2002 ). Msx1 is expressed during urodele limb regeneration ( Carlson et al. 1998 ; Koshiba et al. 1998 ), as well as during fin ( Akimenko et al. 1995 ; Nechiporuk and Keating 2002 ) and heart regeneration in the zebrafish ( Raya et al. 2003 ), along with other Msx family genes. Therefore, it becomes important to investigate whether it controls cellularisation during regeneration. Although prior studies of this process have used the multinucleate myotube as the target cell in culture, the critical target during epimorphic regeneration is the more differentiated striated myofiber. The regeneration of muscle fibers in vertebrates proceeds by the mobilisation of reserve satellite cells ( Chargé and Rudnicki 2004 ), and these have been described in myofibers of larval salamander limbs ( Popiela 1976 ). Their participation in cellularisation was excluded in the earlier experiments on urodele cells by selective injection of a lineage tracer into myotubes in culture ( Lo et al. 1993 ) or myofibers in the salamander tail ( Echeverri et al. 2001 ). In order to address these various questions, we have established a culture system in which striated myofibers are dissociated from the limb of larval salamanders and attach to a culture substrate where they can be observed by time-lapse microscopy. The fibers are found to be activated by dissociation to undergo cellularisation and viable fragmentation, and this depends on expression of Msx1 . Results Dissociated Myofibers in Culture In order to obtain striated myofibers, tissue was isolated from the limbs of two species of larval salamander ( Ambystoma maculatum or Ambystoma mexicanum ), which have been used interchangeably with comparable results. After removing the epidermis, the tissue was dissociated by proteolytic digestion, filtered through a sieve to remove most of the mononucleate cells, and plated in serum-free medium. The striated myofibers readily attached to the culture dish ( Figure 1 ; Figure S1 ) and were found to express myosin heavy chain (MHC) and titin after antibody staining. In view of the potential contribution of satellite type cells to the issues under investigation, cultures were treated with a viable nuclear stain and the myofibers were examined carefully at 2 d after plating. Of 1,290 fibers examined in seven independent cultures, there were only 46 examples of mononucleate cells adherent to myofibers, and such cells were not observed in the cases of plasticity that are discussed here. Figure 1 A Live Striated Myofiber from the Larval Salamander Photomicrograph of a live striated myofiber dissociated from the larval limb musculature and adhering to the culture dish in serum-free medium. This cell has the appearance of a normal quiescent fiber and was photographed with VAREL optics at 48 h after plating. Scale bar, 50 μm. When cultures were labelled with tritiated thymidine, no labelled nuclei were observed in multinucleate cells after labelling for 24 h (540 myofibers, five cultures) or 48 h (263 myofibers, three cultures), while 16% of the mononucleate cells were labelled in the latter case. It is noteworthy that the absence of S-phase entry in nuclei within multinucleate cells includes the population of myofibers that undergoes the events of cellularisation or fragmentation described below. Cellularisation of Myofibers after Implantation The dissociation of viable myofibers has allowed us to evaluate their plasticity after implantation into a limb blastema, a procedure that has previously been performed only on myotubes formed in cell culture. Fibers were labelled with a cell tracker dye in suspension after dissociation, and single fibers were examined to verify the absence of any adherent mononucleate cells and were drawn into a glass micropipette ( Figure 2 A). A few fibers (see Materials and Methods ) were injected from the pipette into the early forelimb regenerate of a larval axolotl. The regenerating limbs were sectioned 2–4 d later, and many examples were observed of mononucleate cells labelled with the tracker dye ( Figure 2 B). Such cells were clearly mononucleates, as determined by analysis of serial sections, and were observed in 17 out of 23 animals implanted with labelled myofibers. We conclude that these cells readily undergo cellularisation in the environment of the limb blastema. Figure 2 Cellularisation of Striated Myofibers after Implantation into a Larval Limb Blastema (A) Schematic diagram of procedure. After dissociation of larval limb musculature, the cells were loaded with a cell tracker dye and single myofibers taken up into a suction micropipette, prior to injection into a larval limb blastema as detailed in the Materials and Methods . (B) Section of a limb at 48 h after implantation of CellTracker Orange-labelled myofibers. The section has been counterstained with the nuclear stain Sytox green. Note the dye-labelled mononucleate cells (arrowed). Scale bar, 20 μm. Plasticity in Culture After 48 h in culture, some of the striated fibers remained viable, but showed no significant change in morphology and retained the appearance of the cell shown in Figure 1 . The remainder of the fibers showed various changes in morphology, and these were investigated either by microinjection of single fibers with the lineage tracer Texas red (TR)–dextran and subsequent analysis of the progeny cells or by sequential digital time-lapse observation. Cellularisation. Approximately 10% of the total population of myofibers underwent changes in nuclear localisation within the cells such that a lobulated or ‘cauliflower’ structure formed in the middle or end of the cell ( Figure 3 A and 3 B). This occurred without labelling by tritiated thymidine or any participation by adherent mononucleate cells, which were rarely present on such fibers. The lobules, each of which contained a nucleus, were rapidly resolved into adherent mononucleate cells. In order to analyse these events, single myofibers were microinjected with TR–dextran so as to fill the cells with tracer ( Figure 3 C). We employed the 70 kDa dextran, which is not transferred across gap junctions ( Coelho and Kosher 1991 ; Landesman et al. 2000 ). In cases in which fibers formed the cauliflower structure and underwent cellularisation, the mononucleate cells in the initial colony were labelled with the tracer in a rim of cytoplasm around the nucleus ( Figure 3 D). In some cases, adjacent fibers were injected and the progeny of the myofibers gave rise after 5–7 d to overlapping dense colonies with many labelled cells ( Figure 3 E). These cells did not express detectable levels of MHC after staining by indirect immunofluorescence. Figure 3 Plasticity of Isolated Myofibers (A) Phase-contrast micrograph of a live cell at 3 d after plating, showing a lobulated structure in the middle of the fiber. (B) Micrograph of a live fiber at 2 d after plating, showing budding of nuclei at one end. The cell has been counterstained with Syto 13. (C) Fluorescence micrograph of a myofiber at 24 h after microinjection with TR–dextran. The cell has been counterstained with Syto 13 dye to show the nuclei. (D) Fluorescence micrograph of a colony formed from a single myofiber injected 24 h earlier with TR–dextran. The cell has flattened on the substrate and the nuclei are stained with Syto 13 dye. (E) Fluorescence micrograph of a colony formed from the progeny of several myofibers in proximity that were injected 5 d earlier with TR–dextran. (F) Analysis of the DNA content of cells derived from myofibers injected 5 d earlier with TR–dextran. The DNA content was determined by image analysis of the nuclei of mononucleate TR-positive cells that had been stained with Hoechst (see Materials and Methods ). The green arrow is the value for G 0 nuclei in quiescent myofibers, while the blue arrow is the G 2 /M value determined for mononucleate cells with anti-phosphohistone H3. The red arrow is the G 1 value determined for mononucleate cells. (G) Photomicrograph of a live myofiber, 48 h after plating, showing a binucleate bud formed at the end. The cell was stained as for (B). (H) Fluorescence micrograph of a bud containing three nuclei stained with Syto13 (yellow) derived from a myofiber that contained at least five nuclei and that was injected with TR–dextran (red). Scale bars: (B), (C), and (G), 100 μm; (A), (E), and (H), 50 μm; and (D), 10 μm. We have analysed the DNA content of single Hoechst-stained nuclei by normalised measurements of fluorescence intensity in TR-labelled cells within such colonies, and an example of a representative distribution for a single colony is shown in Figure 3 F. This also shows the corresponding values (shown by arrows in Figure 3 F) for G 0 nuclei in myofibers, G 1 nuclei in mononucleate cells, and G 2 /M nuclei in mononucleate cells labelled with antibody to phosphohistone H3. The histogram of DNA content for cells in the colony is comparable to that previously observed for cycling newt mononucleate cells ( Tanaka et al. 1997 ). The relatively long S-phase in urodele cells leads to a prominent contribution of cells with DNA content between 2N and 4N. In addition, there were examples of TR-labelled mononucleate cells in M-phase, as determined with anti-phosphohistone H3. We conclude that the progeny mononucleate cells are able to traverse S-phase and enter mitosis after cellularisation. Fragmentation. In a second aspect of plasticity, which was shown by 40%–70% of the total population of myofibers, the initial stages also involved the migration of nuclei to form local aggregates, often of two or three nuclei, within the fiber. The migration of nuclei into a terminal aggregate is illustrated by selected images from a time-lapse video analysis ( Figure 4 A; Video S1 ). The series of Figure 4 B illustrates a trinucleate terminal aggregate that fragments from the body of the myofiber (yellow arrows). This fragment remained adherent and extended cytoplasmic processes. In some cases, the nuclear aggregate formed a bud that was discharged into the medium. An example of a multinucleate bud formed at the end of a fiber is shown in Figure 3 G. In cases in which fibers containing at least five nuclei had been injected with TR–dextran, such buds were often observed to adhere as viable bi- or trinucleate-labelled cells (see Figure 3 H). The multinucleate progeny resulting from these processes did not label with tritiated thymidine or undergo division. Figure 4 Analysis of Nuclear Migration and Fragmentation by Time-Lapse Microscopy (A) Single frames illustrating the migration of three nuclei (yellow arrows) along a myofiber, of which two are incorporated into a terminal aggregate by 11.4 h. One nucleus (green arrow) remained stationary during this period. (B) Single frames illustrating the production of viable multinucleate fragments from a myofiber. Note the presence of a trinucleate aggregate (arrowed green) that separates after lateral breakage of the fiber (0 min, arrowed yellow). This fragment subsequently extends cytoplasmic processes (14.3 and 15.4 h) and migrates over the culture substratum. Series (A) and (B) begin at 6 h after plating. Scale bars: (A) 50 μm; (B) 200 μm. Inhibition by taxol. In view of the evidence that implicates microtubules as a target for myoseverin, we stained the cultures with antibody to β-tubulin. Although tubulin was polymerised in microtubules parallel to the axis of the fibers, the regions of nuclear aggregation were associated with depolymerised tubulin ( Figure 5 A). In order to assess the functional relevance of depolymerisation, we exposed the cultures to 2 μM taxol, an agent that stabilises microtubules and inhibits division of mononucleate urodele cells without effects on cell viability or adhesion of myofibers to the culture substrate. Whereas 80% of the control fibers showed the morphologies associated with plasticity, as described above (see Materials and Methods for the criteria), only 16% were observed in the case treated with taxol ( Figure 5 B), although the total number of adherent cells was unaffected. This suggests that localised depolymerisation of microtubules may be a significant target for the regulation of these responses. Figure 5 Plasticity and Microtubule Depolymerization (A) The distribution of microtubules surrounding a multinucleate aggregate on a myofiber, as analysed by staining with anti-β-tubulin. Note the relatively disordered state of the tubulin (arrowed) in the vicinity of the nuclei. The fiber was stained at 48 h after plating. Scale bar, 50 μm. (B) Taxol inhibits the activation of myofibers after dissociation. Myofibers were dissociated and cultured in the presence of taxol as described in the Materials and Methods . The number of active fibers was determined as described. Expression of Msx1 The cultures were reacted with a digoxygenin-substituted antisense riboprobe to axolotl Msx1 . The mononucleate cells and inactive myofibers showed little or no reactivity, but active fibers showed strong reactivity with the probe in the vicinity of nuclear aggregations ( Figure 6 A and 6 B). Several control probes were negative on both classes of fibers, while the quiescent fibers as well as the active ones were reactive to antisense probes to urodele EF1a and Nrad ( Figure 6 C). In view of the relationship between Msx1 expression and plasticity in mouse myotubes ( Odelberg et al. 2000 ), the expression in the active fibers is suggestive of a role in the endogenous urodele programme. Figure 6 Analysis of mRNA Expression in Myofibers at 48 h by In Situ Hybridisation (A) Expression of Msx1 mRNA in active myofiber. Note the accumulation of reaction product around nuclear aggregates (arrowed). (B) Absence of significant Msx1 mRNA expression in a quiescent fiber. This image is taken from the same culture as (A). (C) Expression of NRad mRNA in nuclei of quiescent fibers (arrowed). Comparable intensity was observed for NRad expression by active fibers. (D) Expression of Msx1 mRNA in nuclei of fibers (arrowed) made quiescent by culture in taxol. Note the difference in Msx1 expression levels between the taxol-induced inactive fibers and normal quiescent myofibers in (B). Scale bar, 50 μm. In an initial investigation of this possibility, cultures were arrested as before by treatment with taxol, followed by reaction with the Msx1 antisense probe. In parallel control cultures, only 4.2% of the inactive fibers ( n = 404) showed any reaction with the probe, whereas 51% of all myofibers ( n = 820) showed reactivity. After treatment with taxol, 56.3% of inhibited fibers ( n = 765) were positive, whereas 63% of all myofibers ( n = 901) showed expression of Msx1 . It is clear, therefore, that the arrest of nuclear mobilisation does not prevent the early expression of Msx1 in activated myofibers. These data are consistent with an upstream role for Msx1 in the activation of plasticity, but direct evidence for functional activity has come from antisense perturbation. Activity of Morpholino-Substituted Oligonucleotides In order to evaluate the uptake of morpholino-substituted oligonucleotides, larval myofibers were dissociated as usual in the presence of 10 μM biotinylated morpholinos or underivatised morpholinos. The cells were cultured for 48 h and then analysed by a detection procedure involving tyramide signal amplification (see Materials and Methods ). Approximately 70%–90% of the fibers showed uptake of the biotinylated oligonucleotides in different experiments ( Figure 7 A), and no signal was detectable in the absence of oligonucleotide or with underivatised morpholinos ( Figure 7 B). The cells are thus effectively loaded by dissociation in the presence of morpholinos. Figure 7 Analysis of the Functional Role of Msx1 Expression by Exposure to Morpholino Antisense Oligonucleotides (A and B) Uptake of morpholino by myofibers. Myofibers were dissociated in the presence of biotinylated (A) or control (B) morpholinos and analysed by tyramide signal amplification at 24 h after plating. Note the positive signal in (A), dependent on the presence of biotin moiety. In three different experiments 70%–90% of the fibers were loaded as determined with this assay. Scale bar, 50 μm. (C) Functional effect of loading various morpholinos. Note that loading Msx1 antisense leads to a specific decrease in the proportion of active fibers relative to controls. (D–G) Staining of myofibers with antibody to Msx1 protein. (D and E) Fluorescence micrograph of a nucleus in a quiescent myofiber stained with Hoechst for DNA (D) and Msx1 protein (E). (F and G) Fluorescence micrograph of a nucleus in an active myofiber stained for DNA (F) and Msx1 protein (G). These images (D–G) were taken from the same culture. Scale bar, 20 μm. (H) Distribution of fluorescence intensity of nuclei in myofibers after staining with antibody to Msx1. The distributions for control active fibers and control quiescent fibers were determined for cells in the same culture and are significantly different (ANOVA, p < 0.001 at 95% confidence level). The distribution for antisense-treated quiescent fibers is not significantly different from that for control quiescent fibers. Limb tissue was dissociated in the presence of control morpholinos or a morpholino antisense reagent directed at the translation initiation sequence of axolotl Msx1 . The resulting cultures were analysed in parallel for the proportion of active fibers and the antisense reagent reproducibly and specifically decreased this by 60%–70% ( Figure 7 C). This led, as expected from the mechanism of such reagents, to the presence of inhibited fibers that expressed Msx1 mRNA after in situ hybridisation, and the proportion of such Msx1 positive and inhibited cells was increased by 5-fold relative to parallel cultures incubated with control oligonucleotides. The myofiber cultures were stained by indirect immunofluorescence with a rabbit antibody to Msx1 in order to evaluate the level of expression of the homeoprotein in the nuclei. There was a significant difference is staining of nuclei between active and quiescent fibers in the same culture ( Figure 7 D– 7 G). The level of expression in nuclei of different fibers was estimated by quantitative image analysis, and the distribution of intensities is shown in Figure 7 H. There was a significant difference in the fluorescence intensity of nuclei in active and quiescent fibers in control cultures ( Figure 7 H), consistent with the difference in mRNA levels observed by in situ hybridisation (see Figure 6 A and 6 B). The distribution of intensities for nuclei in quiescent fibers in parallel cultures treated with antisense oligonucleotides to Msx1 was not significantly different from the control quiescent distribution ( Figure 7 H). It should be noted that more than half of the quiescent fibers were inhibited as a result of the antisense treatment, thus indicating that the antisense distribution reflects a significant decrease in protein expression in the nucleus relative to active fibers. We conclude that expression of a critical level of Msx1 protein is necessary for the fibers to exhibit plasticity in this culture system. Discussion The plasticity of isolated urodele myofibers as described here has not been observed in previous work on dissociated mouse myofibers ( Rosenblatt et al. 1995 ; Blaveri et al. 1999 ). These apparently retain their morphological identity in culture without undergoing viable fragmentation or cellularisation. In preliminary work on myofibers dissociated from the forelimb of Xenopus tadpoles (stages 56–63), we have observed fragmentation comparable to that described here for fibers of the larval salamander, but no cellularisation. It is possible, therefore, that there is a gradation in the degree of plasticity after dissociation, and this may be related to the ability to undergo reversal during regeneration, although more work is required to investigate these comparative issues. It is interesting that the mononucleate progeny of cellularisation were observed to reenter the cell cycle, while multinucleate fragments retained the postmitotic arrest of the parental fibers. At least half of the salamander fibers were activated after dissociation and could be scored by morphological criteria as an index of plasticity, as well as by analysis of gene expression in situ. The occurrence of cellularisation did not reflect the activation of adherent mononucleate cells since the injection of a nontransferable tracer into the fibers resulted in labelling of the mononucleate progeny, and furthermore the mobilisation of nuclear aggregates occurred without any detectable S-phase reentry. It is probable that the process of enzymatic and mechanical dissociation mimics the activation events after amputation, either in terms of mechanical factors sensed by the fibers or the release of signals from the tissue or matrix. Earlier experiments on microinjected fibers in the larval tail have explored the stimuli required to trigger cellularisation and concluded that activation apparently required both ‘clipping’ at the end of the fiber as well as tissue injury in the vicinity ( Echeverri et al. 2001 ). It has also been reported that crude extracts from early regenerates of the adult newt limb are able to induce cellularisation of newt and mouse myotubes in culture ( McGann et al. 2001 ). The precise nature of the signal(s) that couples tissue injury to activation of this response remains an important subject for future investigation, particularly as it may be a key difference between urodeles and mammals. One striking consequence of fiber activation is the appearance of the Msx1 transcript, and our work strongly supports the hypothesis that Msx1 is a pivotal regulator of plasticity in differentiated cells. Although taxol treatment is able to block the internal reorganisation in activated fibers, it does not inhibit the induction of Msx1 , suggesting that microtubule depolymerisation, while being a direct target of myoseverin ( Rosania et al. 2000 ), may also be a downstream target for regulation by Msx1 . The striated myofibers are more highly differentiated than the newt A1 myotubes employed for implantation or the C2C12 mouse myotubes used to assay myoseverin and Msx1 . The events of cellularisation, cleavage, or budding off from myofibers are preceded by migration of nuclei to generate local concentrations, reminiscent of the events leading to formation of the neuromuscular junction ( Merlie and Sanes 1985 ; Englander and Rubin 1987 ), although mouse myotubes seem to undergo lateral breakage without such reorganisation ( Rosania et al. 2000 ). This migration is inhibited by taxol, and nuclear migration in other contexts is dependent on microtubule function ( Morris 2003 ). All of the events described for the myofibers occur without entry into S-phase, as determined previously for cellularisation of myotubes after implantation ( Velloso et al. 2001 ). The formation of mononucleate cells is followed by rapid division and loss of myosin expression, and these cells are presumably the culture equivalent of muscle-derived blastemal cells. The activity of the Msx1 gene has recently been implicated in digit tip regeneration in fetal and neonatal mice by comparing regeneration in normal and Msx1 mutant animals ( Reginelli et al. 1995 ; Han et al. 2003 ). It has also been shown that transgenic expression of an activated Msx1 protein can induce tail regeneration in larval Xenopus during the refractory period between stages 45 and 47 ( Beck et al. 2003 ). This evidence, taken in conjunction with the present study and that of Odelberg et al. (2000) , indicates that this gene is an important regulator of regeneration. Various activities have been associated with the protein, including a role as a repressor of transcription (reviewed in Bendall and Abate-Shen 2000 ), for example, of various myogenic differentiation genes in C2C12 myotubes ( Odelberg et al. 2000 ) and also as a positive regulator of genes that promote cell cycling such as cyclin D ( Hu et al. 2001 ). Our analysis of the myofiber cultures provides evidence for its ability to mobilise a postmitotic cell, for example, by nuclear migration and cellularisation, without S-phase reentry in the syncytium, and this suggests a different aspect of its activity as a regulator. Studies on mammalian myotubes should continue to be informative, while the present system, with its ready incorporation of antisense oligonucleotides, should be helpful for relating such studies to the endogenous programme of urodele regeneration. This in turn should assist the long-term goal of promoting the reversal of cellular differentiation as a strategy for mammalian regeneration ( Chargé and Rudnicki 2004 ). Materials and Methods Tissue dissociation and culture of myofibers The forelimbs and hind limbs of the larval spotted salamander ( A. maculatum ) or axolotl ( A. mexicanum ) (3–5 cm size) were removed, the epidermis was peeled off, and the tissue was rinsed in serum-free amphibian MEM (AMEM) ( Ferretti and Brockes 1988 ) prior to dissociation for 3 h at 26 °C in PBS containing 0.15% collagenase (Type 1A, Sigma, St. Louis, Missouri, United States), 0.8% Dispase II (Roche, Basel, Switzerland), 0.15% crystalline bovine serum albumin, 0.3% D-glucose, and 0.15 mg/ml DNase I (Roche). After 30 min of incubation, the tissues were gently triturated through a fire-polished glass pasteur pipette to aid the detachment of myofibers from the bone. After incubation, the suspension was triturated several times, centrifuged at 400 rpm for 10 min, resuspended in AMEM, and filtered through a 35 μm sieve (VWR International, Poole, United Kingdom) to remove most of the mononucleate cells. The retentate was rinsed with AMEM and plated on 35 mm Falcon Primaria (Becton-Dickinson, Palo Alto, California, United States) tissue culture dishes. Cultures were maintained at 25 °C with 2.5% CO 2 in a humidified incubator as described elsewhere ( Ferretti and Brockes 1988 ). After attachment of the myofibers to the culture dish by overnight incubation, the culture media was replaced with serum-free AMEM or AMEM supplemented with 10% foetal bovine serum. Labelling and implantation of myofibers Myofibers were dissociated as above, retained in suspension in a sterile bacteriological dish (Bibby Sterilin, Stone, United Kingdom), and incubated with 10 μM CellTracker Orange CMTMR (Molecular Probes, Eugene, Oregon, United States) for 30 min at 25 °C. The labelling was terminated by addition of 10% AMEM, and the cells were incubated for 45 min at 25 °C to permit enzymatic activation of the dye. The cell suspension was diluted several fold to allow observation of myofibers at low density. The forelimbs of axolotl larvae (7–10 cm size) were amputated at mid humerus level under tricaine (0.1%) anaesthesia 48 h before injection of labelled myofibers (see Figure 2 A). The animals were anaesthetized, and the forelimbs were positioned under a stereo zoom microscope. The myofiber suspension was placed under inverted microscope, and the myofibers were drawn into a glass micropipette (30 μm tip diameter) using an oil-driven manual microinjector (Sutter Instruments, Novato, California, United States) mounted on a Narishige (Tokyo, Japan) MMO-1 micromanipulator. The skin was punctured with a tungsten needle in order to introduce the blunt end of the micropipette. Three to eight myofibers were picked, examined carefully to verify the absence of any adherent mononucleate cells, and injected into each limb regenerate. Contralateral limbs were mock injected with medium from the suspension. The regenerates were removed at 48 h and 96 h after injection, fixed in 4% paraformaldehyde (PFA), and processed ( Kumar et al. 2000 ). Serial longitudinal sections of 60 μm were cut on a cryostat (Leica, Solms, Germany), air dried, dehydrated in PBS, and counterstained with 2.5 μM Sytox Green (Molecular Probes). The sections were observed under epifluorescence on an Axiophot microscope (Zeiss, Jena, Germany). Microinjection of cultured myofibers with conjugated dextran Myofibers were incubated in AMEM containing 2,3-butanedionne monoxime (BDM) (4 mM) for 30 min to prevent contraction of the myofibers ( Bettencourt-Dias et al. 2003 ) and maintained in the same medium during microinjection. The culture dishes were placed under a Zeiss Axiovert microscope and microinjected with TR-conjugated dextran (TR–dextran, 70 kDa; Molecular Probes). The medium was changed immediately after injection and the cultures were returned to the incubator. To identify the labelled myofibers and their mononucleate progeny, cultures were counterstained in Syto13 (200 nM; Molecular Probes) live nucleic acid stain for 30 min and observed under fluorescence microscope with a dual band pass (FITC/TRITC) filter. Live imaging of myofiber plasticity To record the coordinates of the myofibers in culture, the dish was scored underneath with a scalpel, and cells in each grid square were observed daily and images were acquired with a CCD camera (Sony, Tokyo, Japan). For time-lapse microscopy, myofiber cultures were placed under an Axiovert microscope fitted with an incubation chamber maintained at 26 °C and 3% CO 2 , and phase contrast or variable relief contrast (VAREL) (Zeiss) images were acquired using a digital camera controlled through Image-Pro Plus software (Media Cybernetics, Silver Spring, Maryland, United States). A sequence gallery was created using Image Pro-Plus and images of interest were selected, digitally enhanced, and processed in Adobe Photoshop 6.0 (Adobe, San Jose, California, United States). [ 3 H]thymidine labelling. Myofibers were incubated in 1 μCi/ml [ 3 H] thymidine (Amersham Biosciences, Little Chalfont, United Kingdom) for 24 h, fixed in 1% glutaraldehyde, and processed for autoradiography ( Velloso et al. 2000 ). DNA cytometry DNA content in myofiber nuclei and TR–dextran-labelled mononucleate progeny was measured quantitatively after fixation and staining of the nuclei with Hoechst 33258 (2 μg/ml; Sigma). Baseline values for nuclear DNA content in cycling axolotl mononucleate cells were measured in parallel after incorporation of 5-deoxy-2′-bromouridine (BrdU) (1 μM; see Tanaka et al. 1997 ). The BrdU-labelled cells were processed for double immunofluorescence with monoclonal antibody against BrdU and rabbit antibody to anti-phosphohistone H3 ( Velloso et al. 2000 ; Bettencourt-Dias et al. 2003 ). The nuclei were counterstained with Hoechst dye as above. All images were acquired using 12-bit cooled CCD camera (Photonic Sciences, Robertsbridge, United Kingdom), maintaining camera and microscope settings identical between various samples, corrected for uneven illumination and background using software functions, and processed using classification and measuring routines in Image-Pro Plus software. Scoring of plasticity in myofibers A viable nucleic acid stain such as Syto 13 or Hoechst 33342 (Molecular Probes) was routinely used in cultures to visualize and score the myofibers. The quiescent or inactive myofiber nuclei were aligned along the fiber (see Figures 1 and 7 D), and the cell did not show any cytoplasmic extensions from the axis. The nuclei in active fibers moved along the axis of the fiber to form aggregations that were localized either in the middle or towards the end of the cell (see Figure 3 A, 3 B, and 3 G). In most cases, this resulted in formation of localised cytoplasmic protrusions in the vicinity of the nuclei. Myofibers were classified and counted based on the above criteria. Taxol inhibition assay. Dissociated myofibers were plated in medium containing taxol (2 μM; Sigma). Parallel control cultures were incubated in vehicle (DMSO) in a similar way. The cultures were fixed at 48 h after treatment and processed for tubulin immunofluorescence or in situ hybridisation. Functional assay for Msx-1 using morpholino antisense oligonucleotides Morpholino-based antisense oligonucleotides of 25 oligomere were prepared to target the translation initiation site of axolotl Msx1 gene (5′-CGGTCTGCATCCTCTGCTTGCTTAG-3′) by Gene Tools Inc. (Corvallis, Oregon, United States). Invert control oligos of Msx1 (5′-GATTGCTTCGTCTCCTAGCTCTGGC-3′) and standard control oligos (5′-CCTCTTACCTCAGTTACAATTTATA-3′) from the supplier were used as controls. 3′-Biotin-end-labelled standard control oligos were used for evaluating the uptake of morpholino oligonucleotides by myofibers. Oligo stock solutions were prepared according to guidelines from the manufacturer and stored at 4 °C. The morpholino oligos were added at a concentration of 10 μM to the dissociation cocktail and the myofibers were dissociated as described. After purification of myofibers, fresh morpholino oligos were added to the culture medium. After sequential washes to remove any adherent morpholino ( McKeon et al. 2001 ), cultures were fixed at 48 h after treatment, prior to analysis. Detection of morpholino uptake by immunofluorescence. Tyramide signal amplification (PerkinElmer Life Sciences Inc., Wellesley, Massachusetts, United States) coupled with enzyme-linked immunofluorescence (ELF97, Molecular Probes) was employed to localize the uptake of morpholino oligos in cultured myofibers. Myofiber cultures were fixed at 48 h in 0.5% PFA containing 0.05% glutaraldehyde for 15 min on ice. The fixative was replaced with freshly made 0.1% NaBH 4 solution and incubated for 5 min. The manufacturer's protocol was employed for TSA amplification with the ELF97 modification. The samples were developed in ELF reaction buffer under fluorescence microscope for 10–20 s and images were acquired using a cooled digital camera. In situ hybridisation The axolotl Msx1 cDNA (a kind gift from H. Ide, Tohoku University, Sendai, Japan) was cloned into Bluescribe vector (Stratagene, La Jolla, California, United States), and probes were generated as described elsewhere ( Koshiba et al. 1998 ). A 0.7 kb axolotl EF-1α fragment (kindly provided by D. Gardiner and S. Bryant, University of California, Irvine, United States) was cloned into PCR II vector (Invitrogen, Carlsbad, California, United States) and linearised with XhoI (antisense), and a riboprobe was generated with SP6 RNA polymerase. Newt Rad ( NRad , a gift from K. Yoshizato, Hiroshima University, Hiroshima, Japan) probe was generated from a fragment of approximately 400 bp from Bluescribe vector after linearising with either HindIII (antisense) or EcoRI (sense), and riboprobes were synthesized using T3 and T7 RNA polymerase respectively ( Shimizu-Nishikawa et al. 2001 ). Axolotl EF1α and NRad probes were used as positive controls, while neomycin ( Cash et al. 1998 ), NRad sense, and Msx1 sense probes served as negative controls. For in situ hybridisation, the myofiber cultures were incubated in BDM (4 mM), fixed in chilled 1% glutaraldehyde for 15 min, postfixed in 4% PFA, and washed in 0.3% PBT. In situ hybridisation was essentially as described elsewhere ( Kumar et al. 2000 ), with minor modifications in the hybridisation temperature. Antibodies and immunofluorescence Myofiber cultures were routinely fixed in ice-cold 0.5% PFA containing 0.05% glutaraldehyde for 10 min on ice. For β-tubulin staining, 5 μM Taxol (Sigma) was incorporated into the fixative. After fixation, the culture was treated with freshly prepared 0.1% NaBH 4 for 5 min to reduce nonspecific fluorescence. The samples were post-fixed in ice-cold methanol at −20 °C for 10 min, washed three to four times in 0.3% PBT, and blocked in PBT containing 10% goat serum. The primary antibodies were to MHC and titin, and BrdU monoclonal antibody and rabbit polyclonal antibodies to phosphohistone H3, were all as described elsewhere ( Tanaka et al. 1997 ; Kumar et al. 2000 ; Velloso et al. 2000 ; Bettencourt-Dias et al. 2003 ). For localisation of β-tubulin, the culture was fixed and washed overnight in 0.3% PBT and incubated with mouse monoclonal β-tubulin antibody (1:100; clone TUB 2.1; Sigma) overnight at 4 °C. The samples were washed extensively in GS/PBT and incubated in TR-conjugated goat anti-mouse antibody (1 μg/ml; Molecular Probes). The nuclei were counterstained with Hoechst 33258 (2 μg/ml). A rabbit polyclonal antibody raised against the full-length mouse Msx1 homeoprotein was used to detect expression of Msx1 protein (BAbCO, Richmond, California, United States). When a full-length expression construct of axolotl Msx1 was expressed in mouse cells by transient transfection, the antibody gave strong and specific staining of nuclei in transfected cells ( Figure S2 ). The samples were fixed and processed as before and incubated with Msx1 antibody (1:1000) overnight at 4 °C. After several washes, the cultures were incubated with FITC-conjugated goat anti-rabbit antibodies (1:100; DakoCytomation, Cambridgeshire, United Kingdom), and the nuclei were counterstained with Hoechst. A control rabbit polyclonal antibody was processed in parallel to obtain a baseline value for quantitative fluorescence measurements on immunostained nuclei. The myofiber cultures stained for β-tubulin, MHC, or titin, or cultures injected with TR–dextran were observed under confocal laser scanning microscope (Leica). The images were acquired as z -stacks, and composite maximum projection images were generated through Leica software. Samples stained for Msx1 protein were observed under a Zeiss Axioplan microscope and images were acquired with an Axiocam digital camera. The fluorescence intensity in myofiber nuclei was measured in Axiovision software (Zeiss), and the data were analysed by one-way analysis of variance (ANOVA) followed by multiple range test using Instat (Graphpad Software Inc., San Diego, California, United States). Supporting Information Figure S1 Live Striated Myofiber Dissociated from the Limb of a Larval Salamander The myonuclei incorporate Syto13 live nuclear stain. The myofiber was observed with VAREL optics at 24 h after plating. Scale bar, 100 μm. (4.1 MB TIF). Click here for additional data file. Figure S2 Expression of Newt Msx1 in Mouse PS Cells by Transient Transfection Nuclear localisation of Msx1 protein (green) was detected with a rabbit polyclonal antibody generated against the full-length mouse Msx1 homeoprotein. (5.6 MB TIF). Click here for additional data file. Video S1 Time-Lapse Video Analysis of Nuclear Migration in a Myofiber Time-lapse sequence was begun 6 h after plating of the myofiber on to a culture dish. The images were taken at 6 min intervals under 32× VAREL objective magnification. (110 KB AVI). Click here for additional data file.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC509293.xml
533866	Itch and skin rash from chocolate during fluoxetine and sertraline treatment: Case report	Background The skin contains a system for producing serotonin as well as serotonin receptors. Serotonin can also cause pruritus when injected into the skin. SSRI-drugs increase serotonin concentrations and are known to have pruritus and other dermal side effects. Case presentation A 46-year-old man consulted his doctor due to symptoms of depression. He did not suffer from any allergy but drinking red wine caused vasomotor rhinitis. Antidepressive treatment with fluoxetine 20 mg daily was initiated which was successful. After three weeks of treatment an itching rash appeared. An adverse drug reaction (ADR) induced by fluoxetine was suspected and fluoxetine treatment was discontinued. The symptoms disappeared with clemastine and betametasone treatment. Since the depressive symptoms returned sertraline medication was initiated. After approximately two weeks of sertraline treatment he noted an intense itching sensation in his scalp after eating a piece of chocolate cake. The itch spread to the arms, abdomen and legs and the patient treated himself with clemastine and the itch disappeared. He now realised that he had eaten a chocolate cake before this episode and remembered that before the first episode he had had a chocolate mousse dessert. He had never had any reaction from eating chocolate before and therefore reported this observation to his doctor. Conclusions This case report suggests that there may be individuals that are very sensitive to increases in serotonin concentrations. Dermal side reactions to SSRI-drugs in these patients may be due to high activity in the serotonergic system at the dermal and epidermo-dermal junctional area rather than a hypersensitivity to the drug molecule itself.	Background The skin contains a system for producing serotonin as well as serotonin receptors. Serotonin can also cause pruritus when injected into the skin. SSRI-drugs increase serotonin concentrations and are known to have pruritus and other dermal side effects e.g. exanthema, purpura, urticaria and pruritus [ 1 ]. In contrast, SSRI-medication has also been used to treat pruritus associated with cholestasis [ 2 ] and polycythemia vera [ 3 ]. In this report we describe a patient who developed pruritus and skin rash from chocolate, but only when he was under SSRI-treatment. The case is presented and we provide a putative biological rationale for the described phenomenon. Case presentation A 46-year-old man consulted his doctor in September 2003 due to depression. He had then experienced symptoms for a few years that had aggravated during the last six to eight months. Using the Montgomery-Åsberg Depression Rate Scale (MADRS) the patient scored 24 points and was diagnosed as having a clinical depression. He did not take any medication and had no regular medical contact. The patient did not have any history of allergy or dermatological diseases. However, he sometimes suffered from vasomotor rhinitis after drinking red wine. The doctor prescribed fluoxetine 20 mg daily as antidepressive treatment. At the revisit three weeks later the patient was very pleased with the fluoxetine treatment and reported that he "had not felt better in 20 years" although he initially had experienced slight nausea and insomnia. A week later, he visited his doctor due to an itching rash that had started the day before. The doctor noted partly confluent urticae on the abdomen, a modest periorbital oedema and red, warm palms and wrists. An ADR induced by fluoxetine was suspected and fluoxetine treatment was discontinued. The symptoms were treated with 2 mg clemastine and 6 mg betametasone orally and disappeared within 48 hours. However, the symptoms of depression returned. Sertraline medication was initiated 10 days after the cessation of fluoxetine treatment since SSRI medication had shown good effect. During the weeks of sertraline treatment no urticarial symptoms appeared. The patient improved in his depression although full recovery was not achieved this time. After approximately two weeks of sertraline treatment he noted an intense itching sensation in his scalp after eating a piece of chocolate cake. The itch spread to the arms, abdomen and legs within a few hours. This time the patient did not seek his doctor but treated himself with clemastine and the itch disappeared during the night. He now remembered that he had had a chocolate mousse dessert before the first episode. Since he had never had any reaction from eating chocolate before, he found this observation so striking that he reported it to his doctor. The patient, himself a scientist, later tried small doses of chocolate and skin rash and itch appeared at an intensity that to him seemed dependent on the "dose" of chocolate ingested. It has been known for 30 years that serotonin can stimulate cutaneous C-fibres [ 4 ], the type of fibres that is also known to transmit itch [ 5 ]. Moreover, serotonin injections into the skin can induce itch [ 6 ] and pruritus is a component in 24% of reported skin reactions to fluoxetine in Sweden, the corresponding figure for sertraline is 15 % [ 1 ]. However, attempts to treat pruritus using 5-HT3-receptor-antagonists have not given clear-cut results [ 6 - 8 ]. The enzymes necessary for conversion of tryptophan to serotonin are expressed in human skin [ 9 ]. In addition, 5-HT2AR are present in one third of unmyelinated axons at the dermal and epidermo-dermal junctional area [ 10 ]. An altered localisation pattern of serotonin receptors 5-HT1AR, 5-HT2AR and 5-HT3R has been reported in contact eczematous skin together with increased serotonin concentrations [ 11 , 12 ] indicating the presence of a serotonin system in the skin that can be altered in pathologic conditions. Moreover, a cross-sensitivity has been reported when skin rash developed after both paroxetine and sertraline medication [ 13 ]. Since these substances are structurally different, one interpretation is that the skin can react to an SSRI-induced increase in serotonin concentrations. In the present case the patient experienced skin symptoms from two different SSRIs. However, these symptoms occurred only when he had eaten chocolate. Chocolate contains serotonin, at concentrations which depend on the type of chocolate [ 14 ]. A concentration of 1.4 – 5 μg / g has been reported in dark chocolate [ 14 ]. The present report suggests an interaction between SSRI-medication and chocolate leading to pruritus and rash. A plausible explanation is that SSRI together with serotonin-containing chocolate has increased serotonin concentration to a level where 5-HT receptors system at the dermal and epidermo-dermal junctional area are affected. Moreover, the patient in this case had previously noted nasal congestion and cough when he was drinking red wine. Red wine can induce release of serotonin from platelets [ 15 ] and from the gut [ 16 ]. Serotonin can induce nasal itch, sneeze and hypersecretion [ 17 , 18 ]. Conclusions Apart from the SSRI – chocolate interaction this patient had another possible sign of sensitivity to serotonin. The present case thus suggests that there may be individuals that are very sensitive to increases in serotonin concentrations. Skin side reactions to SSRI-drugs in these patients may be due to high activity in the serotonergic system system at the dermal and epidermo-dermal junctional area rather than a hypersensitivity to the drug molecule itself. However, the reaction of skin to serotonin from food is poorly studied and further studies are necessary to determine how much alimentary serotonin can increase serum serotonin concentrations and to what extent SSRI-medication affects this process. More knowledge in this field could be of help for physicians who encounter patients with dermal reactions to SSRI-drugs and there might be food and beverages containing serotonin that these patients should avoid. Moreover, possible individual differences in the serotonergic system at the dermal-epidermal junction remain to be studied. What happened to the patient and his depression? Due to poor anti-depressive effect of sertraline, the treatment was altered back to fluoxetine. He is now free from his depression and experiences no rash or oedema-like adverse reactions as long as he is avoiding chocolate. List of abbreviations 5-HT: 5-hydroxytryptamine, ADR: Adverse Drug Reaction, SSRI: serotonin selective reuptake inhibitors Competing interests The author(s) declare that they have no competing interests. Authors' contributions SS first described the case, JC and HM performed literature searches and JC first drafted the manuscript. HM and SK took part in the scientific discussion and in finalising the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC533866.xml
545066	Mycophenolate mofetil modulates adhesion receptors of the beta1 integrin family on tumor cells: impact on tumor recurrence and malignancy	Background Tumor development remains one of the major obstacles following organ transplantation. Immunosuppressive drugs such as cyclosporine and tacrolimus directly contribute to enhanced malignancy, whereas the influence of the novel compound mycophenolate mofetil (MMF) on tumor cell dissemination has not been explored. We therefore investigated the adhesion capacity of colon, pancreas, prostate and kidney carcinoma cell lines to endothelium, as well as their beta1 integrin expression profile before and after MMF treatment. Methods Tumor cell adhesion to endothelial cell monolayers was evaluated in the presence of 0.1 and 1 μM MMF and compared to unstimulated controls. beta1 integrin analysis included alpha1beta1 (CD49a), alpha2beta1 (CD49b), alpha3beta1 (CD49c), alpha4beta1 (CD49d), alpha5beta1 (CD49e), and alpha6beta1 (CD49f) receptors, and was carried out by reverse transcriptase-polymerase chain reaction, confocal microscopy and flow cytometry. Results Adhesion of the colon carcinoma cell line HT-29 was strongly reduced in the presence of 0.1 μM MMF. This effect was accompanied by down-regulation of alpha3beta1 and alpha6beta1 surface expression and of alpha3beta1 and alpha6beta1 coding mRNA. Adhesion of the prostate tumor cell line DU-145 was blocked dose-dependently by MMF. In contrast to MMF's effects on HT-29 cells, MMF dose-dependently up-regulated alpha1beta1, alpha2beta1, alpha3beta1, and alpha5beta1 on DU-145 tumor cell membranes. Conclusion We conclude that MMF possesses distinct anti-tumoral properties, particularly in colon and prostate carcinoma cells. Adhesion blockage of HT-29 cells was due to the loss of alpha3beta1 and alpha6beta1 surface expression, which might contribute to a reduced invasive behaviour of this tumor entity. The enhancement of integrin beta1 subtypes observed in DU-145 cells possibly causes re-differentiation towards a low-invasive phenotype.	Background With the improved long-term outcome of allograft recipients in the cyclosporine or tacrolimus era, malignant tumors have become increasingly important. Malignant tumours develop in 15–20% of graft recipients after 10 years, and thus contribute substantially to the morbidity and mortality of these patients [ 1 ]. Malignancies can develop in three ways: de-novo occurrence in the recipient, recurrent malignancy in the recipient or transmission of malignancy from the donor. In all cases, the post-transplant treatment regimen and the level of immunosuppression are high risk factors due to the long-term modification of the immune system. During the last years, the novel immunosuppressive drug mycophenolate mofetil (MMF) has been introduced into the clinical protocol to overcome severe side effects associated with cyclosporine or tacrolimus. Meanwhile, it has become part of the immunosuppressive regimen after liver, kidney or heart transplantation [ 2 ]. Still, the influence of MMF on tumor recurrence or de novo malignancy has not been explored. MMF effects are based on the inhibition of inosine monophosphate dehydrogenase (IMPDH) and prevention of guanosine monophosphate synthesis from inosine monophosphate, a rate-limiting step in the purine biosynthesis in lymphocytes. Consequently, MMF blocks the proliferation and clonal expansion of T and B lymphocytes, and prevents the generation of cytotoxic T cells, as well as other effector T cells [ 3 ]. Additional mechanisms may also contribute to the efficacy of MMF in preventing allograft rejection. By depleting guanosine nucleotides, MMF suppresses glycosylation and the expression of some adhesion molecules, thereby decreasing the recruitment of lymphocytes and monocytes into sites of inflammation and graft rejection [ 3 ]. Immunoprecipitation studies have shown that one of the glycoproteins affected is the lymphocytic alpha4beta1 integrin, the ligand for VCAM-1 on activated endothelial cells. Further experiments have revealed inhibition of the integrin LFA-1, the counter-receptor of ICAM-1, after MMF administration [ 4 , 5 ]. The integrins constitute a family of transmembrane receptor proteins composed of heterodimeric complexes of noncovalently linked alpha and beta chains. Integrins function in cell-to-cell and cell-to-extracellular matrix (ECM) adhesive interactions and transduce signals from the ECM to the cell interior and vice versa. For various types of cancers, different changes in integrin expression are closely associated with tumor growth and metastasis. Based on the knowledge that MMF modulates integrin expression, we postulated that MMF might not only suppress leukocyte recruitment to the donor graft, but also prevent integrin-dependent tumor dissemination. To explore how far MMF might serve as a metastasis-blocking agent, we investigated the beta1 integrin subunit expression pattern of colon, kidney, pancreas and prostate tumor cells before and after MMF treatment, as well as MMF effects on tumor cell adhesion to human endothelium in vitro. The present study indicates that MMF possesses anti-tumoral properties particularly to colon and prostate carcinoma cells. Alterations of the beta1 integrin profile are responsible for blocking tumor cell adhesion to vascular endothelium. Methods Cell cultures Kidney carcinoma Caki I cells, pancreatic carcinoma DanG cells and colonic adenocarcinoma HT-29 cells G were obtained from the tumor cell bank of Johannes Gutenberg University, Mainz, Germany. Prostate carcinoma DU-145 cells were purchased from DSMZ (Braunschweig, Germany). Tumor cells were grown and subcultured in RPMI1640 medium (Seromed, Berlin, Germany) supplemented with 10% FCS, 100 IU/ml penicillin and 100 μg/ml streptomycin at 37°C in a humidified, 5% CO 2 incubator. Endothelial cells (HUVEC) were isolated from human umbilical veins and harvested by enzymatic treatment with chymotrypsin. HUVEC were grown in Medium 199 (Biozol, Munich, Germany), 10% fetal calf serum (FCS; Gibco, Karlsruhe, Germany), 10% pooled human serum (Blood Bank of The German Red Cross, Frankfurt am Main, Germany), 20 μg/ml endothelial cell growth factor (Boehringer, Mannheim, Germany), 0.1% heparin (Roche, Basel, Switzerland), 100 ng/ml gentamycin (Gibco) and 2% 1 M HEPES-buffer (Seromed, Berlin, Germany). To control the purity of HUVEC cultures, cells were stained with fluorescein isothiocyanate (FITC)- labelled monoclonal antibody against Factor VIII-associated antigen (Von Willebrand factor; clone F8/86; Dako, Hamburg, Germany) and analyzed microscopically or by FACscan (Becton Dickinson, Heidelberg, Germany; FL-1H (log) channel histogram analysis; 1 × 10 4 cells/scan). Cell cultures with a purity > 95% were serially passaged. Subcultures from passages 2–4 were selected for experimental use. Mycophenolate mofetil (MMF) Tumor cells were pretreated with MMF (Roche Bioscience, Grenzach-Wyhlen, Germany) (0.1 μM, 1 μM). Before adding the MMF-treated tumor cells to HUVEC (monolayer adhesion assay), cell cultures were washed to remove MMF from the medium. Results were compared to untreated controls. Viability of tumor cells in presence of MMF was assessed by propidium iodide dsDNA-intercalation or quantitative fluorescence analysis of enzyme-catalyzed fluorescein-diacetate metabolism. Monolayer adhesion assay HUVEC were transferred to six-well multiplates (Falcon Primaria; Becton Dickinson, Heidelberg, Germany) in complete HUVEC-medium. When confluency was reached, 0.5 × 10 6 tumor cells of each entity/well were carefully added to the HUVEC monolayer for 60 min. Subsequently, non-adherent tumor cells were washed off using warmed (37°C) Medium 199. The adherent cells were fixed with 1% glutaraldehyde and counted in five different fields (5 × 0.25 mm 2 ) using a phase contrast microscope (20 × objective) to calculate the mean cellular adhesion rate. Evaluation of integrin surface expression Tumor cells were washed in blocking solution (PBS, 0.5% BSA) and then incubated for 60 min at 4°C with the FITC-conjugated monoclonal antibody anti-alpha2beta1 (Becton Dickinson; clone AK-7), anti-alpha4beta1 (Cymbus Biotechnology, Hofheim, Germany; clone HP2I1), anti-alpha5beta1 (Cymbus Biotechnology; clone SAM-1), anti-alpha6beta1 (Becton Dickinson; clone GOH3), or with the PE-conjugated monoclonal antibody anti-alpha1beta1 (Becton Dickinson; clone SR84), or anti-alpha3beta1 (Becton Dickinson; clone C3II1). Integrin expression of tumor cells was then measured using a FACscan (Becton Dickinson; FL-1H (log) channel histogram analysis; 1 × 10 4 cells/scan) and expressed as mean fluorescence units (MFU). A mouse IgG1-FITC was used as an isotype control for FITC conjugated antibodies. To evaluate background staining of PE conjugated antibodies, goat anti mouse IgG-PE was used (all: Cymbus Biotechnology). To analyze integrin beta1 distribution on the cell membrane, tumor cells were transferred to round cover slips (pretreated with 2% 3-aminopropyl-triethoxysilan) placed in a 24 well multiplate. Upon reaching confluency, cell cultures were washed and fixed in cold (-20°C) methanol/acetone (60/40 v/v). Subsequently, cells were incubated for 60 min with unconjugated anti-integrin monoclonal antibodies. Indocarbocyanine (Cy 3™; Dianova; working dilution: 1:50) conjugated goat-anti-mouse IgG was then added as the secondary antibody. To prevent photobleaching of the fluorescent dye, cover glasses with stained cells were taken out of the wells and the residual liquid was removed. These were then embedded in an antifade reagent / mounting medium mixture (ProLong™ Antifade Kit, MoBiTec, Göttingen, Germany) and mounted on slides. The slides were viewed using a confocal laser scanning microscope (LSM 10; Zeiss, Jena, Germany) with a plan-neofluar ×100 / 1.3 oil immersion objective. mRNA expression of beta1 integrins mRNA expression of beta1 integrins was evaluated by reverse transcriptase-polymerase chain reaction (RT-PCR). Tumor cells were seeded in 50 ml culture flasks (25 cm 2 growth area; Falcon Primaria, Becton Dickinson) and cultured with or without MMF. Total RNA was extracted by using RNeasy kit (Qiagen, Hilden, Germany) and RNA samples were then treated with 80 U/ml of Rnase-free Dnase I (Boehringer Mannheim, Mannheim, Germany) for 60 min at 37°C, to eliminate amplifiable contaminating genomic DNA. Subsequently, samples were incubated for 10 min at 65°C to inactivate Dnase. Complementary DNA was synthesized from 1 μg of total RNA per sample with a 60 min incubation at 42°C, using the Moloney murine leukaemia virus reverse transcriptase (Invitrogen, Karlsruhe, Germany) and oligo-(dT) priming (Boehringer Mannheim). Amplification was carried out using gene specific primers and Platinum-Taq polymerase (Invitrogen) in a Mastercycler Gradient thermocycler (Eppendorf, Hamburg, Germany). Reactions were performed in the presence of 0.5 μl cDNA, with an initial incubation step at 95°C for 2 min. Cycling conditions consisted of denaturation at 95°C for 30 sec, annealing at 60°C for 30 sec and extension at 72°C for 30 sec over a total of 30 cycles. The reaction was completed by another 10 min incubation step at 72°C. The specific sequences for sense and anti-sense primers are shown in table 1 . The PCR products were subjected to electrophoresis in 1.5% agarose gel and visualized by ethidium bromide. Statistical analysis All studies were performed 3–6 times. Statistical significance was investigated by the Wilcoxon signed rank test showing two-sided probabilities and using normal approximation. Differences were considered statistically significant at a p value less than 0.05. Results MMF modulates tumor cell adhesion to HUVEC The 60 min adhesion rates of tumor cells were calculated at 22.5 ± 4.1 DanG cells/0.25 mm 2 , 39,8 ± 10.5 DU-145 cells/0.25 mm 2 , 55,3 ± 11.7 Caki I cells/0.25 mm 2 , or 80,5 ± 17.2 HT-29 cells/0.25 mm 2 . MMF differentially modulated the adhesive capacity of the tumor cells which was strongly dependent on the drug concentration and the cell line used (figure 1 ). Adhesion of DanG cells was weakly reduced by 1 μM MMF. A modest down-regulating effect was seen on Caki I cells at a MMF concentration of 0.1 μM. Strong and significant adhesion blockade was achieved when HT-29 cells were treated with 0.1 μM MMF (p = 0.0079). This effect was reverted at a dosage of 1 μM. Furthermore, MMF dose-dependently and significantly reduced the adhesive capacity of DU-145 cells with a maximum effect at 1 μM (p = 0.0079). In all experiments, cell viability was not impaired by MMF. beta1 integrin expression pattern Figures 2 and 3 depict the integrin beta1 surface expression pattern on untreated tumor cell cultures. Figure 2 is related to FITC-labelled antibodies, figure 3 to PE-labelled antibodies. Each tumor entity was characterized by a specific integrin pattern. Integrins were expressed in the following order (MFU ± SD; n = 4): DanG: alpha3beta1 (455.6 ± 71.0) > alpha2beta1 (175.7 ± 24.3) > alpha6beta1 (54.8 ± 9.2) > alpha1beta1 (27.3 ± 3.2). Caki I: alpha3beta1 (601.3 ± 82.0) > alpha1beta1 (139.2 ± 24.0) > alpha5beta1 (22.9 ± 4.2). HT-29: alpha3beta1 (202.0 ± 33.8) > alpha6beta1 (119.6 ± 14.5) > alpha2beta1 (69.2 ± 9.0) > alpha1beta1 (25.4 ± 3.4). DU-145: alpha3beta1 (942.5 ± 112.9) > alpha2beta1 (95.4 ± 12.4) > alpha5beta1 (69.1 ± 8.9) > alpha6beta1 (50.9 ± 7.2) > alpha1beta1 (31.4 ± 4.8). Mean IgG1-FITC isotype control was 8.6 ± 1.8 MFU, mean IgG1-PE isotype control was 9.9 ± 1.7 MFU. Analysis of the mRNA expression level confirmed the flow cytometry data (see below). The distribution pattern of those integrins which were predominantly expressed on the respective tumor cell line was further explored by confocal microscopy (figure 4 ). alpha2beta1 (DanG cells), alpha3beta1 (Caki I, DanG HT-29 cells), and alpha6beta1 integrins (HT-29 cells) were distributed homogenously among the cell surface. In contrast, alpha1beta1 integrins on Caki I cells accumulated mainly at the sites of cell-cell-contacts. MMF modulates beta1 integrin surface expression MMF evoked distinct alterations of the beta1 integrin expression pattern (figure 5 ). MMF only slightly changed alpha1beta1, alpha3beta1, and alpha5beta1 integrin surface levels on Caki I cells (figure 5A ), and weakly down-regulated alpha2beta1 on DanG cells when applied at 1 μM (figure 5B ). However, 0.1 μM MMF strongly and significantly diminished alpha3beta1 (p = 0.0022) and alpha6beta1 integrins (p = 0.035) on HT-29 cells (figure 5C ). This effect was reverted at concentrations of 1 μM MMF. The alpha3beta1 receptor became even slightly enhanced, compared to control values. alpha1beta1, alpha2beta1, alpha3beta1, alpha5beta1 on DU-145 cells were up-regulated significantly by MMF in a dose-dependent fashion, whereby strongest effects were seen on alpha2beta1 surface level in the presence of 1 μM MMF (>70% fluorescence enhancement, compared to non-treated controls; p = 0.0022; figure 5D ). Influence of MMF on beta1 integrin coding mRNA To allow a clear interpretation of the strong effects of MMF on adhesion and beta1 integrin surface expression of HT-29 and DU-145 cells, MMF evoked alterations of gene activity was also evaluated in these cell lines (figure 6 ). Control experiments using non-treated HT-29 cells revealed high alpha2beta1, alpha3beta1, alpha6beta1 mRNA expression level (figure 6A ). Application of 0.1 μM MMF induced down-regulation of alpha3beta1 and alpha6beta1 coding mRNA, which paralleled MMF's influence on receptor surface expression. The effect was reverted at a dosage of 1 μM. alpha3beta1 and alpha6beta1 coding mRNA became even slightly enhanced, compared to control experiments. With respect to the prostate tumor cell line DU-145, alpha1beta1, alpha2beta1, alpha3beta1 and alpha6beta1 coding mRNA was clearly detected in untreated cell cultures. Both, 0.1 μM and 1 μM MMF reduced mRNA of beta1 integrin subtypes, although the effect was more pronounced in the presence of 0.1 μM MMF (figure 6B ). Discussion Although MMF has become part of the standard regimen after organ transplantation its impact on tumor development and dissemination is still not clear. Our adhesion experiments demonstrate that MMF down-regulates binding of tumor cells to endothelium, which might argue for anti-tumoral properties of this compound. Notably, HT-29 and DU-145 cells responded well to MMF (-70% adhesion reduction), while Caki I and DanG tumor cells were influenced only modestly. From a clinical viewpoint, distinct adhesion-blocking properties of MMF might be limited to colon and prostate carcinoma cells. Interestingly, HT-29 cells were more susceptible to MMF than DU-145 cells: 0.1 μM MMF was sufficient to significantly diminish adhesion of HT-29 cells, whereas 1 μM MMF was necessary to evoke maximum effects on DU-145 cells. The different sensitivity of the tumor cell lines to MMF might be caused by an unequal metabolic activity, coupled with variable IMPDH levels. Recent data have shown that the level of expression of IMPDH mRNA and protein differ among several cell lines [ 6 ], and that IMPDH is selectively up-regulated in neoplastic and replicating cells [ 7 ]. Although this has not yet been proven, MMF might be more effective in rapidly proliferating tumor cells than in tumors with a lower replicating activity. In this context, the average doubling times of HT-29 and DU-145 cultures during their exponential growth phase were calculated to be 13–16 h or 22 h, respectively [ 8 - 10 ], whereas the mean population doubling times of renal or pancreatic carcinoma cell lines ranged between 24–104 h or 16–40 h, respectively [ 11 - 14 ]. It should also be considered that MMF might switch on/off different intracellular signaling cascades in colon versus prostate tumor cells. Indeed, adhesion blockade of HT-29 cells was accompanied by reduced alpha3beta1 and alpha6beta1 surface expression, while adhesion blockade of DU-145 cells was accompanied by a dose-dependent up-regulation of integrins alpha1beta1, alpha2beta1, alpha3beta1, alpha5beta1 on the cell membrane. Studies on integrin receptors presented evidence that beta1 integrin expression by colon carcinoma cells qualifies these cells to successfully adhere to secondary sites. Recent experiments have demonstrated that colon cancer cells adhere to endothelial cells via beta1 integrins and that addition of beta1 integrin blocking antibodies reduces tumor cell adhesion [ 15 , 16 ]. Based on a murine spleen injection-liver metastasis protocol, the alpha3beta1 integrin subtype was identified to predominantly facilitate the metastatic activity of colon cancer cells [ 17 ]. A converse scenario might be created during prostate carcinogenesis, as levels of beta1 integrins have been found reduced in neoplastic versus normal prostate tissue [ 18 , 19 ], and in malignant versus non-tumorigenic prostate cell lines [ 20 ]. An in vitro cell culture model revealed that TGF-beta stimulates the expression of alpha2beta1 integrin on prostate cancer cell lines and concomitantly reduces tumor cell adhesion to human bone marrow endothelium [ 21 ]. Down-regulation in the expression of the alpha3beta1 integrins may also allow prostate tumor cells to become more invasive and lead to an increased propensity for metastasis: When human alpha3beta1 high and alpha3beta1 low expressing prostate carcinoma cells were injected into immunocompromised SCID mice, only those cells with a drastically reduced integrin level were found to form tumors at the primary sites and to be highly invasive and metastatic [ 22 ]. This is in context with our data demonstrating beta1 integrin elevation on DU-145 prostate tumor cells in the context with diminished adhesion behaviour. When discussing the relevance of integrins in tumor recurrence and malignancy, we should keep in mind that integrin receptors serve as mechanistic binding as well as differentiation triggering elements. Therefore, up-regulation of the same integrin type might either lead to enhanced cell adhesion by coupling the receptor to its ligand, or to a reduced cell adhesion by activating integrin driven differentiation signals. Based upon our in vitro assay, we conclude that MMF blocks adhesion of colon and prostate carcinoma cells by two different mechanisms: a) Loss of alpha3beta1 and alpha6beta1 surface expression directly contributes to the reduced adhesive behaviour of HT-29 cells, b) Enhancement of integrin beta1 subtypes might cause re-differentiation of DU-145 cells towards a low-adhesive phenotype. However, it still remains to be determined if MMF indeed acts as a differentiation inducing drug in prostate tumor cells. Beside the hypothesis that beta1 upregulation might activate differentiation inducing signals, selective inhibition of tumor-promoting pathways should also taken into consideration. Presumably, down-regulation of alpha3beta1 and alpha6beta1 surface expression on HT-29 tumor cells might be caused by inhibition of receptor glycosylation and/or receptor de novo synthesis. The latter hypothesis seems to be more likely because MMF's effects at the cell surface were also observed at the mRNA level. This was not the case with DU-145 cells where MMF evoked up-regulation of membranous beta1 integrins was not paralleled by similar modifications of the beta1 integrin coding mRNA. There is still no clear concept why MMF causes integrin up-regulation in one tumor entity but down-regulation in another entity, both coupled with reduced tumor cell adhesiveness. Presumably, HT-29 and DU-145 tumor cells might be equipped with different enzyme systems, the intracellular signaling cascade might be activated differentially in colon versus prostate tumor cells, or sensitivity of specific pathways to MMF might differ between both tumor types. Speculatively, alterations of post-translational events might change the receptor surface presentation in prostate carcinoma cells. Elegant experiments by Liang and coworkers demonstrated that over-expression of alpha5beta1 or beta1 integrin induced the decrease of protein kinase B (PKB) phosphorylation and subsequent accumulation of cyclin-dependent kinase inhibitor p21 [ 23 ]. A yeast-based two-hybrid system was employed which identified IMPDH as specifically interacting with PKB [ 24 ]. Furthermore, MMF treatment significantly increased p21 proteins, which could be reversed by the simultaneous addition of guanine or guanosine [ 25 , 26 ]. Hypothetically, p21 may act as an MMF triggered upstream signal (via PKB?), which contributes to enhanced beta1 integrin surface expression. Conclusions The present study indicates that MMF possesses anti-tumoral properties particularly to colon and prostate carcinoma cells. Alterations of the beta1 integrin profile are responsible for blocking tumor cell adhesion to vascular endothelium. MMF might also act on further adhesion proteins which are relevant for tumor recurrence and dissemination. An in vitro study published recently refers to the sLeX-selectin pathway targeted by MMF [ 27 ]. CD44 glycoproteins as well as receptors of the cadherin family might also be modulated under MMF-based immunosuppressive regimen. From a clinical viewpoint, further studies must be undertaken which evaluate the tumor recurrence rate and classify the tumor type in MMF versus non-MMF treated transplant patients. Competing interests The author(s) declare that they have no competing interests. Authors' contributions TE performed parts of the in vitro studies, contributed toward the design of the study and drafted the manuscript. JM carried out confocal microscopy, BR and IN performed FACS-analyses. IM designed PCR primers and carried out the PCR studies. WDB contributed to the manuscript design and finalisation. DJ participated in the conception and design of the study. RAB carried out the adhesion assays, participated in the conception and design of the study and its coordination. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545066.xml
534112	Mucosal delivery of anti-inflammatory IL-1Ra by sporulating recombinant bacteria	Background Mucosal delivery of therapeutic protein drugs or vaccines is actively investigated, in order to improve bioavailability and avoid side effects associated with systemic administration. Orally administered bacteria, engineered to produce anti-inflammatory cytokines (IL-10, IL-1Ra), have shown localised ameliorating effects in inflammatory gastro-intestinal conditions. However, the possible systemic effects of mucosally delivered recombinant bacteria have not been investigated. Results B. subtilis was engineered to produce the mature human IL-1 receptor antagonist (IL-1Ra). When recombinant B. subtilis was instilled in the distal colon of rats or rabbits, human IL-1Ra was found both in the intestinal lavage and in the serum of treated animals. The IL-1Ra protein in serum was intact and biologically active. IL-1-induced fever, neutrophilia, hypoglycemia and hypoferremia were inhibited in a dose-dependent fashion by intra-colon administration of IL-1Ra-producing B. subtilis . In the mouse, intra-peritoneal treatment with recombinant B. subtilis could inhibit endotoxin-induced shock and death. Instillation in the rabbit colon of another recombinant B. subtilis strain, which releases bioactive human recombinant IL-1β upon autolysis, could induce fever and eventually death, similarly to parenteral administration of high doses of IL-1β. Conclusions A novel system of controlled release of pharmacologically active proteins is described, which exploits bacterial autolysis in a non-permissive environment. Mucosal administration of recombinant B. subtilis causes the release of cytoplasmic recombinant proteins, which can then be found in serum and exert their biological activity in vivo systemically.	Background The use of recombinant proteins as drugs has deeply modified the therapeutic approach to many severe diseases. However, a variety of practical problems limits the use of biotechnological protein drugs. Stability of the active proteins, need for parenteral administration, and high costs of the final purified materials are among the most significant drawbacks. A way of circumventing these issues is represented by the direct administration of recombinant bacteria, acting simultaneously as cell factory and delivery system for pharmacologically active proteins. This approach has been already extensively experimented for the mucosal delivery of vaccine antigens [ 1 , 2 ]. In recent years, the local delivery of therapeutic antibodies [ 3 , 4 ], adjuvant cytokines [ 5 , 6 ], and anti-inflammatory cytokines [ 7 - 9 ] has been successfully attempted with food-grade bacteria ( e.g. , Lactococcus lactis , Streptococcus gordonii ), although limited to the therapy of localised pathologies ( e.g. , inflammatory bowel diseases, IBD, in the gastro-intestinal tract). Among anti-inflammatory strategies, both at systemic and local level, the use of the IL-1 receptor antagonist (IL-1Ra) has received vast attention. IL-1 is a family of cytokines highly active in the modulation of immune amplification and inflammation. The IL-1 family includes two agonist proteins, IL-1α and IL-1β, and one antagonist protein, IL-1Ra. IL-1β is a very potent immunostimulatory and inflammatory cytokine, responsible for initiating and amplifying the host response to invasion. If not properly controlled, IL-1 can cause fever, acute inflammation, tissue destruction, organ failure, and eventually shock and death (reviewed in [ 10 ]). IL-1Ra inhibits IL-1 by acting as a competitive receptor antagonist with no detectable agonist activity, thus representing a natural powerful mechanism to control IL-1-dependent responses and avoid pathological derangement (reviewed in [ 11 , 12 ]). In experimental animal models, IL-1Ra has demonstrated excellent therapeutic effects against acute and chronic inflammatory pathologies, being also effective at high doses in prolonging survival in endotoxic shock [ 11 - 17 ]. In human trials, IL-1Ra has been administered to patients with septic shock, rheumatoid arthritis, graft- versus -host disease, and multiple sclerosis (reviewed in [ 11 , 12 , 16 ]). While only a modest benefit was achieved in patients with septic shock [ 11 , 12 , 16 , 18 ], IL-1Ra had a clear beneficial effect in reducing joint destruction in rheumatoid arthritis [ 11 , 12 , 19 - 21 ]. From the clinical experience with purified recombinant IL-1Ra it became clear that most of the problems of variability of efficacy were due to difficulties in adequate timing and dosage of the drug [ 12 ]. To overcome these problems, gene therapy with adenoviral vectors carrying the IL-1Ra gene has been attempted in experimental animals, yielding promising results in models of type 1 diabetes and ischemic brain damage [ 22 , 23 ]. The clinical application of the gene therapy approach may however meet with difficulties for safety reasons, besides the problems of controlling drug release, concentration, and localisation. Based on previous experience of using recombinant bacteria as in vivo cell factory, here we describe a novel system of local delivery of IL-1Ra, able to achieve systemic effects. The system exploits the ability of certain bacteria (such as Bacillus subtilis ) to undergo autolysis in non-permissive conditions (as it occurs in the mammalian intestine) thereby releasing the cytoplasmic proteins. Intra-colon instillation of B. subtilis expressing recombinant human mature IL-1Ra induces significant serum levels of the recombinant protein in rats and rabbits, and prevents the inflammatory effects of systemic IL-1. Intra-peritoneal administration of recombinant B. subtilis in the mouse could inhibit LPS-induced shock and death. Further experimental evidence with a B. subtilis strain producing human IL-1β demonstrates that this delivery system can be generalised to other recombinant proteins. Results The ability of B. subtilis to generate spores by autolysis of the cell wall, thereby releasing cytoplasmic proteins, was exploited as system for delivery of proteins in vivo . Following a sporulation signal ( e.g. , nutrient depletion) bacteria undergo an autolytic process with release of most of their cellular components and formation of a highly resistant spore containing DNA and few essential proteins (Figure 1A ). As already shown in a previous study [ 24 ], in vitro sporulation of B. subtilis engineered for endocellular expression of human IL-1Ra (strain pSM539) caused the release of large amounts of intact and active recombinant protein within a few hours after the sporulation signal (Figure 1B ). The in vitro release of intracellular recombinant IL-1Ra was equally evident in pSM539 Spo + (normally sporulating) and Spo - bacteria, i.e. genetically modified cells which, in response to the sporulation signal, start the autolysis process but are unable to form a complete spore thus undergoing complete cell destruction (Figure 1C ). Both Spo + and Spo - strains of pSM539 were used in subsequent in vivo experiments with identical results. The IL-1Ra recovered after B. subtilis autolysis in vitro retained full biological activity, with a specific activity of 1.1 × 10 6 inhibitory units (IU)/mg vs. 0.9 × 10 6 IU/mg of reference standard IL-1Ra [ 24 ]. To assess whether the recombinant protein could also be released in vivo by engineered B. subtilis , the bacterial strain engineered with IL-1Ra was administered intra-peritoneally in the mouse, in the small and large intestine of rats, and in the rabbit distal colon. The presence of human IL-1Ra was assessed at different times after administration, both locally and in the serum of treated animals, by Western blotting, ELISA, and BIAcore analysis (Table 1 ). Intact human IL-1Ra was found locally at high levels 3 hours after administration of recombinant bacteria and persisted for several hours. In the serum, intact human IL-1Ra could be found at measurable levels when B. subtilis was administered intra-peritoneally (2/2 mice) or in the colon (5/9 rats, 27/31 rabbits), but not when bacteria were administered in the small intestine (0/5 rats). The delivery of IL-1Ra at the intestinal mucosal level was examined. Live cells of the IL-1Ra-producing pSM539 strain were instilled in the rat distal colon, a non-permissive environment that does not allow B. subtilis vegetative life [ 26 ]. As a control, animals received equal numbers of the pSM214 strain, i.e. B. subtilis cells transformed with the β-lactamase-expressing control plasmid pSM214. Data in Figure 2 show that the presence of intact IL-1Ra can be measured both locally (in the intestinal washings) and in serum for several hours after intra-colonic inoculum of the IL-1Ra-producing B. subtilis strain pSM539, whereas serum of animals receiving B. subtilis pSM214 remained negative. As a control, pSM539 bacteria delivered in the small intestine released detectable amounts of IL-1Ra locally, but no IL-1Ra could be found at the serum level (data not shown; Table 1 ). The serum pharmacokinetic parameters of IL-1Ra released by recombinant B. subtilis , as compared to the purified protein administered intra-colonically, show a few differences (Table 2 ). The C max was higher and the T max quicker for the purified protein, as compared to IL-1Ra released from intra-colonically administered B. subtilis . On the other hand, the AUC/dose was almost identical. Administration of control bacteria pSM214 intra-colonically together with the purified protein did not significantly change the pharmacokinetics parameters of IL-1Ra, except for a slight decrease of the total dose absorbed, indicating that the physical presence of bacteria has little effect on IL-1Ra absorption. It is concluded that engineered B. subtilis delivered intra-colonically releases, conceivably by autolysis, the cytoplasmic recombinant protein, which is subsequently absorbed and can be detected intact at measurable levels in the bloodstream. To verify that IL-1Ra found in serum after B. subtilis administration at the mucosal level is functional, its ability to inhibit IL-1 was evaluated both in vitro and in vivo . In vitro , activity of standard IL-1β was assessed with the classical co-stimulation assay on thymocytes of LPS-unresponsive C3H/HeJ mice. Inhibition by IL-1Ra was evaluated as capacity to decrease IL-1-induced thymocyte proliferation. The presence of biologically active IL-1Ra was measured as inhibition of IL-1β-induced thymocyte proliferation by the IL-1Ra-containing serum of rabbits administered pSM539 intra-colonically. The presence and amount of IL-1Ra was measured by ELISA in the serum of pSM539-treated rabbits and of control pSM214-treated or untreated animals. As shown in Figure 3 , IL-1Ra-containing serum from pSM539-treated rabbit (used at dilutions containing from 0.1 to 10 ng/ml IL-1Ra) was as effective in inhibiting IL-1β activity as the same concentrations of standard purified recombinant IL-1Ra (Figure 3 , left), whereas the same dilutions of serum from pSM214-treated or from untreated animals (devoid of IL-1Ra) did not possess any IL-1-inhibiting activity (Figure 3 , left and right panels). To confirm that the IL-1β-inhibiting activity observed in sera of pSM539 treated animals is indeed due to IL-1Ra, data in the Figure 3 (right) show that the inhibitory capacity of pSM539 serum is significantly decreased or abolished by an antiserum against human IL-1Ra. Thus, it can be concluded that the IL-1Ra present in serum after intra-colonic administration of pSM539 is biologically active. The in vivo efficacy of IL-1Ra released by intra-colonic pSM539 was evaluated in antagonising the effects of parenterally administered IL-1 [ 27 ]. As shown in Figure 4 (upper left), the increase in body temperature induced in rabbits by i.v. administration of 75 ng/kg human IL-1β was significantly reduced by preventive intra-colonic treatment with 2 × 10 9 cells of B. subtilis pSM539. The reduction of IL-1β-induced fever was more pronounced with lower doses of IL-1β (90% reduction of peak fever induced by 50 ng/kg IL-1β), but it was still highly significant when fever was induced by 100 ng/kg IL-1β (>60% reduction of peak fever) (data not shown). To confirm these data, the effect of intra-colonic treatment with IL-1Ra-producing pSM539 was evaluated on other inflammation-related parameters induced by IL-1β, i.e. , granulocytosis and decrease of blood glucose and iron concentrations. As shown in Figure 4 (upper right), the increase in circulating PMN induced in rats by IL-1β i.p. was abrogated by previous intra-colonic administration of IL-1Ra-producing pSM539 but not by the control strain pSM214. Likewise, the IL-1β-induced decrease in the blood levels of iron (Figure 4 , lower left) and glucose (Figure 4 , lower right) was still evident in animals administered control pSM214 bacteria but was significantly reduced by intra-colonic instillation of IL-1Ra-producing pSM539 bacteria. It is inferred that human recombinant IL-1Ra delivered in vivo by intra-colonic administration of engineered B. subtilis is biologically active and able to counteract the systemic inflammatory effects of IL-1. That IL-1Ra delivered by B. subtilis can have an anti-inflammatory protective effect in vivo was shown in a model of shock and death induced by bacterial endotoxin (LPS) in the mouse (Figure 5 ), an acute syndrome in which IL-1β plays a major role [ 14 - 16 , 25 ]. LPS-sensitive C3H/HeOuJ mice receiving recombinant pSM539 bacteria intra-peritoneally 24 hours before administration of a lethal dose of bacterial LPS could survive significantly longer than mice administered the control pSM214 bacteria or PBS, in agreement with previous data on the efficacy of IL-1Ra in inhibiting LPS-induced shock [ 13 - 15 ]. To validate the concept of delivery of bioactive recombinant proteins via the colonic mucosa by means of recombinant B. subtilis , another B. subtilis strain was constructed (pSM261, engineered for production of human mature IL-1β) and administered in vivo to rabbits. As shown in Figure 6 , the intra-colonic administration of 1 × 10 9 live cells of B. subtilis pSM261 induced a significant increase in body temperature, superimposable to that caused by intra-colonic instillation of purified recombinant IL-1β. Furthermore, in agreement with the systemic effects of massive doses of IL-1β administered parenterally [ 25 , 28 ], intra-colonic administration of pSM261 caused shock and death in 9/14 animals (64%). It is concluded that the mucosal delivery of engineered B. subtilis in the large intestine is a suitable system for attaining significant blood levels of bioactive recombinant proteins and systemic effectiveness. Discussion The use of live bacteria is very common in particular in vaccinology, where attenuated or mutant bacteria have been employed for decades as antigen carriers. The advantage of live bacteria relies on their capacity of colonising the host and enter the host organs/tissues with the same modalities as their virulent counterparts, thus eliciting the relevant immune response and immune memory, at variance with killed bacteria or purified bacterial components. Thus, attenuated strains of Salmonella , Listeria monocytogenes , Mycobacterium tuberculosis , Vibrio cholerae are being developed and used as vaccine carriers [ 29 - 31 ]. A further development in the use of live bacteria as antigen carriers in vaccination exploits the technologies of genetic engineering for introducing multiple antigens from different micro-organisms into a single non-virulent bacterial carrier ( e.g. , food-grade lactic acid bacteria), with the possibility of including T- and B-stimulating epitopes from different antigens, and also to engineering into the same carrier adjuvant sequences derived for instance from an immunostimulating cytokine [ 30 - 34 ]. Among bacterial systems developed for antigen delivery in vaccination, some strains of non-pathogenic, food-grade or GRAS (generally regarded as safe) bacteria have been examined for the topical delivery of pharmacologically active protein drugs, after cell engineering with the DNA coding for the protein of interest. This is the case of Lactococcus lactis and of Streptococcus gordonii , which have been engineered to produce recombinant antibodies, adjuvant and anti-inflammatory cytokines, and used to deliver these proteins locally at the mucosal surface after oral administration [ 3 - 9 ]. The goal of these delivery approaches was that of making the recombinant proteins available for therapy of local pathologies or for local effects: antibodies for passive immunotherapy of local infections [ 3 , 4 ], cytokines as adjuvants for mucosal vaccines [ 5 , 6 ], inhibitory cytokines for anti-inflammatory therapy of localised chronic inflammatory diseases (IBD-like pathologies) [ 7 - 9 ]. Although undoubtely promising and susceptible of vast applications, the method of mucosal delivery of therapeutic protein through recombinant bacteria acting as cell factories needs further and deeper investigation. This should include the central issue of safety and contained/controlled release of recombinant micro-organisms [ 8 ], the problem of assessing the mucosal permanence of bacteria (extent and duration of colonisation depending on the changes in the mucosal environment in different conditons of health and nutrition) and the extent of protein release, and the issue of pharmacodynamics of the delivered protein in particular for its systemic effects, beyond the boundaries of the local delivery environment. The delivery system proposed here is not based on the permanence/colonisation capacity of bacteria in the host mucosal surfaces, but it relies on the capacity of sporulating bacteria of releasing intracellular proteins in non-permissive environments. B. subtilis cells engineered to produce human IL-1Ra were able to release the recombinant protein (intact and biologically active) following a sporulation signal in vitro [ 24 ]. This observation could be repeated in vivo , when recombinant B. subtilis cells were inoculated in the intestine of rats or rabbits (a non-permissive environment that does not allow the vegetative life of B. subtilis ). The recombinant protein could be detected locally shortly after administration of bacteria and persisted at measurable levels for several hours. Release and recovery of recombinant IL-1Ra was much more abundant and consistent in the large intestine as compared to the small intestine. Most interestingly, the recombinant protein released from sporulating bacteria delivered in the large intestine was absorbed in the bloodstream at detectable levels, whereas no circulating IL-1Ra could be found after bacterial delivery in the small intestine. IL-1Ra present in the blood was intact, as judged by its molecular mass in Western blotting, and retained full IL-1-inhibiting activity, as judged by its capacity of dose-dependent neutralisation of IL-1β in vitro . The passage of an intact protein from the intestinal lumen to the bloodstream is not a new concept. Indeed, transcytosis has been extensively described in intestinal epithelial cells, and allows transport of intact proteins and macromolecules from the intestinal lumen to the circulation through an endocytic non-degradative pathway in physiological conditions of integrity of the intestinal mucosal barrier [ 35 - 39 ]. This mechanism of transcytotic transport, quantitatively scarce as compared to the degradative pathway of protein absorption, may have a role in physio-pathological passage of antigens, allergens, and toxins. Delivery of IL-1Ra through engineered sporulating bacteria apparently had some pharmacokinetics advantages as compared to the purified protein. Whereas the absorption into the bloodstream was quick after administration of the purified protein (T max at 60 min), IL-1Ra released from intra-colonically administered B. subtilis had a much slower kinetics of absorption (T max 200 min), as expected by the fact that the protein must be released from bacteria before being absorbed. Furthermore, although the C max was decreased for B. subtilis IL-1Ra (136 ng/ml vs. 482 ng/ml for the purified protein; only partially attributable to the higher dosage of the purified protein), the AUC/dose were almost identical. Thus, IL-1Ra delivered intra-colonically by B. subtilis is absorbed into the bloodstream at a slower and more constant rate than the purified protein delivered in the same site, which is absorbed quickly into the bloodstream and rapidly disappears thereafter. Thus, it appears that bacteria do not undergo sporulation all at the same time (which would result in a rapidly appearing and disappearing peak of protein), but release the protein constantly from the moment of administration for about 8 h. This would allow a controlled and sustained circulating level of the protein, thus a more favourable pharmacodynamic profile, with a single administration. The protein selected for in vivo delivery with B. subtilis is the IL-1 receptor antagonist IL-1Ra, a competitive non-activating ligand of the IL-1 receptor with IL-1 inhibitory activity [ 11 , 12 ]. IL-1 is a potent inflammatory cytokine which, in pathological conditions, is responsible of chronicisation of inflammation, tissue destruction, organ failure, hypotensive shock [ 10 ]. Anti-IL-1 strategies have been attempted in acute an chronic inflammatory diseases with the use of recombinant IL-1Ra protein [ 11 , 12 ]. The poor outcome of clinical trials in septic shock has highlighted the problems of a therapy based on the systemic administration of a purified recombinant protein, whose efficacy is hampered by its rapid pharmacokinetics [ 11 , 12 , 18 ]. At present, experimentation of therapeutic IL-1Ra is being targeted to slowly progressive chronic diseases with defined organ/tissue targets ( e.g. , rheumatoid arthritis) [ 40 , 41 ]. To achieve sustained IL-1Ra levels, gene therapy approaches have been attempted with promising results in animal models of experimental arthritis, ischemic brain damage, autoimmune diabetes [ 19 - 23 ]. However, the risk remains of side effects due to the uncontrolled inhibition of the physiologically important IL-1 activity. Indeed, a precise balance between between IL-1β and IL-1Ra should be maintained for achieving proper tissue homeostasis, as shown for the intestinal mucosa [ 42 ]. The drug delivery strategy here described merges the well-known approach of vaccination with live bacteria with that of gene therapy. The delivery of pharmacologically active proteins by live sporulating bacteria, as described here, presents a series of advantages over other similar approaches. At variance with conventional gene therapy, the gene coding for the drug protein is introduced in a bacterial carrier rather than in host cells, a situation that would allow a complete control of its permanence in the body. In a previous study, intragastric or vaginal administration of Streptococcus gordonii engineered to release human IL-1Ra resulted in a prolonged local delivery of the protein, consequent to the capacity of S. gordonii to colonise the mucosal surfaces [ 9 ]. Mucosal delivery of IL-1Ra (by intragastric administration of engineered S. gordonii ) also had a local therapeutic effect in a model of ulcerative colitis [ 9 ]. The delivery system with sporulating bacteria described here differs from that with S. gordonii , as it causes rapid local release of the recombinant protein ( e.g. in the large intestine, where IL-1Ra peaks at 4 h and decreases towards background at 24 h), followed by absorption into the bloodstream. In preliminary experiments in the mouse, IL-1Ra-expressing bacteria were also administered intragastrically or subcutaneously. This achieved appearance of human IL-1Ra in the serum, and systemic effects of inhibition of LPS-induced shock and death (data not shown). This is a new finding, that opens the possibility of exploiting localised bacterial administration ( e.g. at mucosal sites) for systemic drug delivery. The amount of protein released at the mucosal site directly correlates with the number of administered bacteria, since the internal body environment does not sustain bacterial replication but induces sporulation. This allows an exact control of the dose of drug delivered and, based on the pharmacokinetics parameters, of the blood levels that can be reached. The same result could not be easily obtained with S. gordonii , as amount and timing of protein release may be influenced by variation of the colonisation capacity depending on variations of environmental conditions of the host tissues. A problem that should be faced when using recombinant bacteria in vivo for therapy or vaccination is that of safety and contained release of genetically modified organisms (GMO). The use of suicidal genes or the deletion of genes vital for survival outside the host organism have been explored with very promising results [ 8 , 43 ]. The bacterial system proposed here can be modified in the sporulation mechanism for the control of its survival. In preliminary experiments, the recombinant B. subtilis pSM539 strain was engineered in order to inactivate a gene involved in sporulation control. As a consequence, in response to in vitro sporulation signals (adverse environmental conditions) the mutated Spo - strain could regularly initiate the sporulation process, undergoing cell autolysis and release of the cytoplasmic proteins (including the recombinant IL-1Ra), but it was incapable of eventual spore formation and further survival. Likewise, release of the recombinant protein from Spo - in vivo was comparable to that of Spo + bacteria, but spores could never be recovered from intestinal lavage and faeces (data not shown). This suggests that the system can be optimised to full biological containment and environmental safety without altering its delivery properties. Conclusions The novel system of protein drug delivery here proposed links some of the advantages of gene therapy (endogenous production of the relevant protein, targeted delivery) to the possibility of controlled release in terms of timing and protein amount. Exploitation of the mechanism of bacterial autolysis in non-permissive environments allows release of intracellular proteins, including the known amount of the pharmacologically active recombinant protein drug. The release is persistent for several hours, allowing to maintain more constant protein levels in the bloodstream. The system is simple, cheap, and can be developed to full environmental safety ( i.e. , avoiding the risk of release of genetically modified bacteria in the environment). The concept that pharmacologically active proteins released at the colonic mucosal surface can be absorbed and reach the circulation intact and retaining full activity (validated with two proteins with opposite effects, IL-1Ra and IL-1β) opens promising avenues to the use of local delivery for the therapy of systemic diseases. Methods Bacterial strains Engineered B. subtilis strains were constructed as previously described in detail [ 44 , 45 ]. Briefly, cDNA coding for mature human IL-1Ra (encompassing the mutation N91>R), and cDNA coding for mature human IL-1β were cloned between Eco RI and Hind III in pSM214, a B. subtilis plasmid which promotes the synthesis of recombinant products intracellularly, to obtain recombinant plasmids pSM539 (carrying the cDNA for IL-1Ra) and pSM261 (carrying the cDNA for IL-1β). Plasmids were used to transform the B. subtilis SMS118 strain. The pSM539-harbouring B. subtilis strain SMS118(pSM539) could produce 1.0–2.0 mg IL-1Ra/10 9 cells/0.35–0.49 g (wet weight), after conventional culture overnight in 1 liter flasks. The SMS118(pSM261) strain in the same culture conditions produced 0.15–0.25 mg IL-1β/10 9 cells/0.35–0.49 g. As negative control, B. subtilis strain SMS118 was transformed with the pSM214 plasmid, which contains the gene of β-lactamase (conferring resistance to penicillin). All strains were leu - , pyrDI, npr - , apr - . Sporulation-defective (Spo - ) strains were constructed by mutation in the srfA gene, as previously described [ 46 ] and were kindly provided by Dr. G. Grandi (Chiron S.r.l., Siena, Italy). Bacterial preparations Bacteria were grown in LB medium containing 5 mg/l chloramphenicol for 7 h at 37°C under shaking and harvested by centrifugation (3,000 × g, 20 min, 4°C). For sporulation supernatant preparation, 0.25 g wet weight of bacteria (corresponding to 0.5–0.7 × 10 9 cells) were suspended in Difco sporulating medium (bacto beef extract 3 g/l, peptone 5 g/l, NaOH 0.25 mM, MgSO 4 10 mM, KCl 0.1%, MnCl 2 0.1 mM, Ca(NO 3 ) 2 1 mM, FeSO 4 1 mM, pH 6.8) without chloramphenicol and incubated at 35°C with shaking. Aliquots of sporulation supernatant were harvested by centrifugation (14,000 × g, 5 min) at different time points. Following sporulation signals, both Spo + and Spo - bacteria initiate the autolysis process, which ends in cell autolysis with release of cytoplasmic content. However, whereas in Spo + bacteria there is formation of a spore with preservation of strain survival, Spo - bacteria are unable to form a spore thus undergoing complete cell destruction (Figure 1A ). Upon sporulation signals, both Spo + and Spo - bacteria released 100% of intracellular recombinant products in a time-dependent fashion, with maximal relaease between 2 an 8 h (Figure 1C ) [ 24 ]. SDS-PAGE analysis Protein samples were run on 13.5% mini SDS-PAGE according to Lämmli [ 47 ] and stained with Coomassie R-250. The gel was subjected to laser scanning on a Molecular Dynamics Personal Densitometer, and the densitometric analysis was made using Image Quant software (Molecular Dynamics, Sunnyvale, CA). Animals Experimental animals were: female C3H/HeOuJ mice of 10–12 weeks of age (20–25 g) (for all in vivo experiments), female C3H/HeJ mice of 5–8 weeks of age (for thymocyte proliferation), female Sprague-Dawley rats (around 300 g), and female New Zealand rabbits (1.9–2.5 kg). All animals were purchased from Charles River Italia (Calco, Italy) and were housed in standard cages at 22 ± 1°C with 12 h light-12 h dark cycle. Animals received standard diet and tap water ad libitum . In vivo administration of B. subtilis Bacteria were harvested and resuspended in LB medium or sterile PBS. Mice received a single intra-peritoneal injection of 0.2 ml of bacterial suspension in PBS. Rats were fasted overnight before the surgical procedure and maintained under urethane anaesthesia throughout. Bacteria (in LB medium diluted 1:1 in PBS) were instilled in the small intestine (duodenum) with a 22 1/2 G needle, in a volume of 1–10 ml. Two surgical ligatures were applied, one at the beginning of the duodenum immediately below the needle entry puncture (to avoid exit of instilled bacteria), and another one near the ileocecal valve, to limit to the small intestine the transit of bacteria. Intra-colon instillation was performed again with a 22 1/2 G needle in the ceacum immediately below the ileo-caecal valve, in a volume of 5–10 ml. Two surgical ligature were applied just below the needle entry point and at the colon terminal region, to avoid loss of bacteria. Animals were sacrificed by exanguination at different times after treatment, to collect blood and intestinal washings. For intra-colonic administration of bacteria in rabbits, animals were fasted overnight prior to treatment, then lightly restrained in conventional stocks and maintained conscious throughout the experiment. A rounded-tip urethral catheter (Rüsh, Germany) was carefully inserted 10 cm into the distal colon via the anal route and 2 ml of B. subtilis suspension were administered. Serum samples were prepared from blood collected from the rabbit marginal ear vein at different times (0–8 h) after intra-colonic administration of bacteria. In some experiments, animals were sacrificed, to collect the large intestine content (saline washing). Protocols of animal experimentation were reviewed by the institutional ethical board for adherence to ethical guidelines for animal research conduct (Italian D. L.vo 27/01/1992 n. 116 and corresponding EU directive 86/609; policy of refinement, reduction and replacement towards the use of animals for scientific procedures 99/167/EC – Council Decision of 25/1/99), and previously authorised by the Italian Ministry of Health. Detection of human IL-1Ra in animal samples Western blotting: samples were subjected to reducing 15% mini SDS-PAGE and analysed by Western blotting using a polyclonal rabbit serum anti-human IL-1Ra and a goat anti-rabbit IgG secondary antibody conjugated with horseradish peroxidase, as described in detail elsewhere [ 48 ]. Serum samples were filtered on Microcon 100 (MWCO 100,000; Amicon, Beverly, MA) before analysis. ELISA measurement: samples were subjected to quantitative determination of human IL-1Ra using a specific ELISA (Amersham, Little Chalfont, UK), following the manufacturer's instructions. The lower detection limit was 20 pg/ml. Purified human recombinant IL-1Ra was used as standard. Serum samples were filtered on Microcon 100 (Amicon) before analysis. Biosensor measurement: detection of IL-1Ra in serum samples and intestinal washings was confirmed with the biosensor BIAcore™ system (Pharmacia Biosensor AB, Uppsala, Sweden), which allows real time biospecific interaction analysis by means of the optical phenomenon of surface plasmon resonance, as previously described in detail [ 49 ]. The lower detection limit for human IL-1Ra was 2 pg/ml. IL-1-induced thymocyte proliferation The classical assay of co-stimulation of murine thymocyte proliferation was used to evaluate the bioactivity of IL-1 and IL-1Ra. Briefly, thymocytes from 5–8 week-old C3H/HeJ mice (preferentially used because of their LPS unresponsiveness) were cultured at 6 × 10 5 cells/well of Cluster 96 plates (Costar, Cambridge, MA) in 0.2 ml of RPMI-1640 medium (Life Technologies, Paisley, Scotland) supplemented with 2 mM L-glutamine, 25 mM HEPES buffer, 50 μg/ml gentamycin sulfate, 1.25 × 10 -5 M 2-ME (all from Sigma Chemical Co.), 5% fetal bovine serum (Hyclone, Logan, UT) for 72 h in moist air with 5% CO 2 [ 50 ]. The biological activity of IL-1β was assessed as co-stimulation of thymocyte proliferation, by adding to the culture wells a selected amount of human recombinant IL-1β (30–300 pg/ml) [ 51 ] and a suboptimal concentration of purified PHA (1.5 μg/ml; Murex Diagnostics, Dartford, UK). Cells were then pulsed for 18 h with 18.5 kBq/well of [ 3 H]TdR (sp. act. 185 GBq/mmol; Amersham) and their proliferation was measured as radiolabel incorporation with a β-counter. The biological activity of IL-1Ra was evaluated as inhibition of IL-1β-dependent thymocyte proliferation. To this end, cells were stimulated to proliferate (with IL-1β and PHA) in the presence of increasing concentrations of human recombinant IL-1Ra [ 51 ] or serial dilutions of serum from rabbits receiving pSM214 or pSM539 intra-colonically, or from untreated rabbits. The concentration of IL-1Ra in serum of pSM539-treated rabbits was determined by ELISA and serum was added to the cultures after appropriate dilution. Control sera from pSM214-treated or untreated rabbits were used at the same dilutions as IL-1Ra-containing serum. Cell proliferation was then evaluated as radiolabel incorporation as described above. To assess that the effect of IL-1Ra-containing serum was indeed due to IL-1Ra, a polyclonal rabbit antibody against human IL-1Ra [ 48 ] was added to the cultures at a dilution of 1:300, i.e. the dilution previously found to inhibit 50% of the activity of 10 ng/ml IL-1Ra in the thymocyte assay (not shown). IL-1-induced fever Rabbits were lightly restrained in conventional stocks throughout the experiment, and accustomed to the stocks over a period of 2 h, to minimise variations in body temperature. Body temperature was measured by means of a cutaneous thermistor probe (TM-54/S and TMN/S; LSI-Lastem, Settala Premenugo, Italy) placed between the left posterior paw and the abdomen and allowed to stabilise for 2 min. B. subtilis suspensions (2 × 10 9 live cells/rabbit) were instilled in the distal colon 1 h before i.v. administration of 50–100 ng/ml highly purified LPS-free human recombinant IL-1β in pyrogen-free saline through the marginal ear vein. Temperature was recorded every 20 min for 3 h starting from IL-1β administration. In experiments with IL-1β-producing strain pSM261, rabbits received an intra-colonic administration of 1 × 10 9 pSM214 (control) or pSM261 (IL-1β) bacteria, or 250 μg purified human IL-1β. Temperature was recorded up to 22 h after treatment. IL-1-induced neutrophilia, hypoferremia, hypoglycemia Live cells of B. subtilis strains pSM214 and pSM539 were instilled in the distal colon (1 × 10 9 cells/kg), 2 h before administration of IL-1β. Blood samples were drawn 2, 4, 6, 8 and 24 h after intra-peritoneal inoculum of 0.1 μg/kg human recombinant IL-1β. The number of circulating neutrophils was assessed by flow cytometry. The plasma iron concentration was determined colorimetrically with a commercially available kit (Fe; Boehringer Mannheim, Mannheim, Germany). Hypoferremia (60–75% decrease of plasma iron level) was evident from 4 to 24 h after IL-1β inoculum. The blood glucose concentration was measured in serum samples by the glucose/glucose oxidase/peroxidase method with commercially available kits (Glucose GOD Perid; Boehringer Mannheim) or by biosensor detection with devices for diagnostic monitoring (Roche Diagnostics, Milano, Italy). Overlapping results were obtained in rats and rabbits. LPS-induced shock in the mouse LPS-sensitive C3H/HeOuJ mice received an intra-peritoneal inoculum of 0.5 ml PBS alone or containing bacterial suspensions (control pSM214, IL-1Ra-producing pSM539; 3 × 10 6 bacteria/mouse), 24 h before i.p. administration of 15–20 mg/kg of LPS (from E. coli 055:B5; Sigma Chemical Co., St. Louis, MO). LPS inoculum was delayed to 24 h after bacteria administration to avoid interference of pre-inoculum. In fact, preliminary experiments showed that intra-peritoneal inoculum of PBS decreased significantly LPS toxicity when administered at shorter times before LPS (data not shown). Mice were observed for 7 days after LPS administration and deaths recorded. Statistical analysis Results are presented as mean ± SEM. Statistical significance was assesed by two-tailed Student's t test. Comparison of survival curves was performed by the χ 2 test. Calculation of percentiles was performed by survival analysis. All calculations were performed with the Stratgraphics Plus 5 programme (Manugistics, Inc., Rockville, MD). List of abbreviations IL, interleukin; IL-1, interleukin-1; IL-1Ra, interleukin-1 receptor antagonist; IBD, inflammatory bowel disease; LPS, bacterial lipopolysaccharide, AUC, area under the curve; PMN, polymorphonuclear leukocytes; GRAS, generally regarded as safe; GMO, genetically modified organisms. Authors' contributions SP carried out the in vivo and pharmacokinetics studies in rats and rabbits, and performed the statistical analysis. PB designed and performed the bioactivity studies. PR designed and performed the microbiological and biochemical work. DB coordinated the bioactivity studies, organised the data, and wrote the manuscript. AT designed and coordinated the entire study. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC534112.xml
520832	The C677T methylenetetrahydrofolate reductase variant and third trimester obstetrical complications in women with unexplained elevations of maternal serum alpha-fetoprotein	Introduction The C677T MTHFR variant has been associated with the same third trimester pregnancy complications as seen in women who have elevations of maternal serum α-fetoprotein (MSAFP). We hypothesized that these women with third trimester pregnancy complications and MSAFP elevations would have an increased frequency of the variant compared to an abnormal study control group (women with MSAFP elevations without pregnancy complications) as well as to normal population controls. Methods Women who had unexplained elevations of MSAFP in pregnancy were ascertained retrospectively. The frequency of the C677T MTHFR variant among those women with unexplained elevations of MSAFP who had experienced later pregnancy complications was compared to that of women with unexplained elevations of MSAFP without complications as well as to that of the previously established Manitoba frequency. Results Women who had complications of pregnancy and an unexplained MSAFP elevation had a higher allele frequency for the C677T MTHFR variant (q = 0.36,) compared to women with MSAFP elevations and normal pregnancy outcomes (q = 0.25, OR 1.73 95% CI 1.25–2.37, p = 0.03). The frequency was also higher than that of the population controls (q= 0.25, OR 1.70 95% CI 1.11–2.60, p = 0.007). The frequency in women with MSAFP elevations without pregnancy complications was not significantly different from that of the population controls ( p = 0.41). Conclusion Women with unexplained elevations of MSAFP and who experience complications in later pregnancy are more likely to have one or two alleles of the C677T MTHFR variant.	Background Significant elevations of amniotic fluid and maternal serum alpha-fetoprotein (MSAFP) have been shown to be associated with spina bifida and other neural tube defects (NTD). The province of Manitoba, Canada offers province-wide midtrimester MSAFP screening to all pregnant women. It has been recognized that some pregnant women with midtrimester unexplained elevations of MSAFP [ 1 , 2 ]. Increased total plasma homocysteine alters placental function and has been associated with the same complications that are associated with unexplained elevated MSAFP [ 3 - 7 ]. The C677T MTHFR variant has also been associated with complications of pregnancy in some, but not all, studies [ 8 - 10 ] C677T MTHFR may therefore contribute to complications of pregnancy by elevating serum homocysteine. Poor placental function could result in both an unexplained elevation of MSAFP and complications of pregnancy. We therefore hypothesized that women with third trimester pregnancy complications and MSAFP elevations (cases) would have an increased frequency of the variant compared to the Manitoba population (population controls) or women with MSAFP elevations without pregnancy complications (study controls) if they had low folate intake. Methods Background to methods In a small pilot study of 32 couples, we found that women who had an unexplained elevation of MSAFP and a normal midtrimester fetal ultrasound, and their partners, had a significantly increased C677T MTHFR frequency compared to Manitoba newborns (RR 1.42, 95% CI 1.08–1.85, p = 0.012, two tailed) [ 11 ]. The newborn study that examined 977 anonymous consecutive neonatal screening blood spots showed that 36% of Manitoba newborns were heterozygous and 7% were homozygous for C677T MTHFR [ 12 ] (q = 0.25). Subsequently, on evaluation of the pregnancy outcomes of our pilot study women, we noted that, among eight women who had gone on to experience complications of pregnancy, the odds ratio for having the C677T MTHFR allele was 2.3 times higher than in the Manitoba population. However, the result was not statistically significant ( p = 0.151, two tailed) indicating the frequency was increased but, this could have been a random result. Ascertainment and recruitment of study population All pregnant women in Manitoba are eligible for routine serum screening through the voluntary MMSSP. In Manitoba, an elevation of MSAFP is defined as 2.3 multiples of the median (MOM) or greater. Candidates for inclusion in this study were women with an unexplained MSAFP elevation (i.e. not due to fetal anomalies, incorrect estimation of gestational age, previously unrecognized fetal demise, or multiple gestation) with either a complicated or uncomplicated pregnancy outcome. After appropriate approvals had been obtained from The University of Manitoba Health Research Ethics Board, review of the screening records began in 1999 and took three years. For a study using a two step consent to participate methodology administered by mail, the expected response rate (after excluding lost to follow-up) would be 20% [ 13 ]. Our goal was 1000 invitations. We anticipated this would result in approximately 120 participants. This would be double the minimum number of participants suggested by the power analysis we had conducted for the pilot study. To increase our response rate further, we added telephone follow-up for invited potential participants who were non-responders [ 14 ]. All screening records from 1995–1999 were reviewed, accounting for 783 invitations. Records for 2000–2002 were reviewed systematically as outcome information on each pregnancy became available to MMSSP. Records for 1990–1994 were then reviewed systematically in order to bring the total up to 1000. If a woman had more than one pregnancy with an elevation of MSAFP screened by the MMSSP, only the first pregnancy encountered in the retrospective review was used for the study. Previous or subsequent pregnancies were not included. Women with preexisting conditions known to influence pregnancy outcome, such as essential hypertension, and mothers of babies with major congenital anomalies were excluded. Eight women who had relinquished their babies for adoption or whose babies were placed in foster care were also excluded. Women who met the inclusion criteria were divided into two groups for analysis. Cases were defined as women with pregnancies complicated by one of the complications previously shown to be associated with an unexplained elevation of MSAFP at midtrimester [ 2 ]. These include: intrauterine growth restriction (IUGR) (<10 th percentile), pregnancy induced hypertension, preeclampsia, eclampsia, postpartum hemorrhage, retained placenta requiring manual delivery, abruptio placenta, premature delivery (<36 weeks gestation or requiring specialized neonatal care for prematurity) and unexplained fetal demise. Study controls were women with normal outcomes which were defined as those with delivery at term ≥ 36 weeks gestation), no complications of pregnancy, a normal placenta and a healthy baby. Definition of complications was based on ICDC-9 codes in the MMSSP outcome charts for each patient [ 15 ] which are then confirmed later by chart review for all those with a positive MMSSP result. All women ascertained as having unexplained MSAFP elevations and who fit the inclusion criteria above, were invited by letter to participate. The previously reported newborn study provided population control group data [ 12 ]. Study questionnaires Women who agreed to participate in the study were mailed the appropriate questionnaires and blood requisitions. The questionnaire included a semi-quantitative food frequency questionnaire (FFQ) based on standard methodology but, modified to suit Manitoba residents and previously validated for this population by biochemical analysis during the pilot study [ 11 , 16 ]. The survey included questions on vitamin supplement intake to determine preconceptional or prenatal supplementation as well as current use of vitamins. Dietary intake of folate and folic acid from supplements, and intake of the cofactors B 12 and B 6 , were calculated from the FFQ for intake both during pregnancy and at the time of the study. A correction of an additional 0.1 mg for folic acid fortification that began in Canada in 1998 was included for pregnancies that began after fortification [ 17 ]. FFQ analyses were performed with the researcher blinded as to the status of the mother. Laboratory analysis Total plasma homocysteine, red blood cell folate, and serum folate were determined using established methodology [ 18 , 19 ]. Samples were processed on site with clotting and separation by spinning. Sera was stored at 4°C during shipping to the central laboratory and until processing. DNA was extracted from whole blood and C677T MTHFR genotyping was performed using previously established methodology [ 11 , 20 , 21 ]. Genotyping and biochemical analyses were performed also blinded. Statistical analysis Chi-squared analysis (one tailed unless otherwise noted) was used for allele frequency. Comparisons of potentially confounding factors between the case group and the study control group were undertaken. Parametric data were analyzed with the Student's t test for difference between means with Bonferroni correction for multiple comparisons. Data not normally distributed were analyzed using the nonparametric Mann-Whitney Rank Sum Test. Linear regression was used to test the validity of the dietary survey. A multivariate analysis included age, smoking, maternal weight at the time of MSAFP testing, presence of C677T MTHFR, gender and weight of infant, biochemical parameters, and FFQ results for folate, B 12 and B 6 , both at the time of the survey and for during the pregnancy was undertaken. In order to avoid convergence due to the large number of variables, the analysis was completed in subsets of six variables. Variables with the higher association scores from these analyses were then combined for further testing in various combinations using stepwise multiple linear regression. Also linear regression analysis of each continuous variable with genotype results was performed. Corrections for multiple comparisons were included. Software used was NCSS Statistical Systems for Windows [ 22 ]. Results Participation rates Nine hundred and ninety four women were identified as eligible (342 cases and 652 controls). Of the 590 women successfully contacted, 130 (22%) agreed to participate (56 cases and 74 controls). Four hundred and four women were lost to follow-up. Cases were more likely to choose to participate than controls and this difference was significant (1.5, p = 0.030). There was no difference in the proportions of cases and controls that were lost to follow-up ( p = 0.157). We had anticipated a 20% response rate and we achieved 24%. Genotype results Genotypes were available for 54 cases and 73 controls for this analysis. Results are summarized in Table 1 . The allele frequency for the C677T MTHFR variant in the Manitoba population has been previously established to be q = 0.25. Women who had complications of pregnancy and an unexplained MSAFP elevation had a higher allele frequency for the C677T MTHFR variant (q = 0.36) compared to women with MSAFP elevations and normal pregnancy outcomes (q = 0.25, OR 1.73 95% CI 1.25–2.37, p = 0.03). The frequency was also higher than in the population controls (q = 0.25, OR 1.70 95% CI 1.11–2.60, p = 0.007). The frequency in women without pregnancy complications and MSAFP elevations (study controls) was not significantly different than that seen in population controls ( p = 0.41). Table 1 Comparison of allele frequency of C677T MTHFR between cases, study controls, and population controls. Subjects C/C (%) C/T (%) T/T (%) Comparing to study controls* OR (95%CI) Comparing to population* OR (95%CI) Cases N = 54 21 (39) 27 (50) 6 (11) 1.73 (1.25–2.37) ( p = 0.033) 1.70 (1.11–2.60) ( p = 0.007) Study Controls N = 73 40 (55) 30 (41) 3 (4) ~ 0.98 (0.46–1.55) ( p = 0.410) Population N = 977 557 (57) 352 (36) 68 (7) 0.98 (0.46–1.55) ( p = 0.410) ~ * χ 2 comparison of allele frequency (total T and C) in each group, one tailed. Cases: women with unexplained elevations of MSAFP who had subsequent complications of pregnancy, (C = 69, T = 39) Controls: women who had unexplained elevations of MSAFP and no subsequent complications (C = 110, T = 36) Population controls were 977 newborns (C = 1466, T = 488) [12]. C/C = normal type, C/T = heterozygous for thermolabile variant, T/T = homozygous for thermolabile variant. The case and study control groups included women at various stages of their child bearing years. Only one woman recruited as a control subject had a previous or subsequent pregnancy with an unexplained elevation of MSAFP and complications. She was a heterozygote for C677T MTHFR. No case subjects had a previous or subsequent pregnancy with an unexplained elevation of MSAFP and a normal outcome, but four case subjects had had a previous or subsequent pregnancy with complications after an elevated MSAFP. If the case versus control classification had been based on whether or not a woman had ever had a pregnancy with an unexplained elevation of MSAFP followed by complications, the association would still be present when compared to the population control (q = 0.3636, OR 1.72, 95%CI 1.27–2.61, p = 0.0055). Biochemical results Heterozygotes and homozygotes for C677T MTHFR had lower average values (r = 0.978, p = 0.019) for serum folate than those who did not have the variant. None of the women were deficient in either serum folate (defined as <7.0 nmol/L) or red blood cell folate (defined as <430 nmol/L RBC). There was no significant difference in mean homocysteine levels (Table 2 ). Table 2 Comparison of the parametric characteristics of women with unexplained elevations of MSAFP according to those with and without complications of pregnancy Characteristic Mean Cases (SD) Mean Controls (SD) p value MSAFP result 2.78 (± 0.62) 3.16 (± 3.76) 0.398 weeks gestation 17.1 (± 1.61) 16.9 (± 1.40) 0.432 μg/folate/day in pregnancy 2 1216 (± 915) 1010 (± 892) 0.206 μg/folate/day at time of study 2 557 (± 341) 523 (± 498) 0.588 erc folate (nmol/L RBC) 1234 (± 289) 1208 (± 317) 0.632 serum folate (nmol/L) 32.3 (± 5.80) 32.3 (± 5.71) 0.956 serum homocysteine (μmol/L) 7.8 (± 2.26) 8.4 (± 2.80) 0.246 μg B 12 /day in pregnancy 2 12.4 (± 5.37) 13.4 (8.31) 0.488 μg B 12 /day at time of study 2 8.9 (± 12.26) 8.6 (± 10.83) 0.899 mg B 6 /day in pregnancy 2 8.4 (± 9.69) 7.2 (± 9.01) 0.461 mg B 6 /day at time of study 2 6.0 (± 13.35) 5.5 (± 11.10) 0.792 mother's age at delivery 31 (± 4.19) 30 (± 5.19) 0.251 mother's weight in Kg 76 (± 17.26) 69 (± 16.09) 0.013 1 1 This value is not significant after Bonferroni correction for multiple comparisons. See discussion. 2 Data was skewed due to a small number of women in both groups taking large dose vitamin supplements. When these women were removed from the analysis the result remained nonsignificant. Validity of surveys Seven cases and one study control declined to fill out their dietary surveys. Mean values were inserted in the multivariate analysis for these eight women. The validity of the dietary survey was demonstrated again for this study by linear regression analysis. Consistent with known homocysteine metabolism [ 23 ], a negative correlation existed between serum homocysteine and both red blood cell folate (r = 0.945 p = 0.0052) and serum folate (r = 0.932, p = 0.0001). Higher intake of dietary folate (including synthetic folic acid from supplements) as reported by the FFQ for the time of study was associated with higher serum folate (r = 0.941, p = 0.0001) and higher red blood cell folate (r = 0.949, p = 0.0166). We did several checks to determine that the women were answering their surveys accurately. Comparisons of specific data items available in the women's MMSSP charts at the time of pregnancy with the data reported in the surveys showed excellent agreement for every item examined indicating women answered questions accurately. Women who reported smoking (as a quantitative value from 0–3 based on 1/2 packs/day smoked) showed a negative correlation with serum folate (r = 0.923, p = 0.0062) consistent with accurately reporting their smoking habits [ 24 ]. Based on the results of these tests of the validity of our surveys, we are confident that the information provided by our participants was accurate. Analysis of FFQ survey and MMSSP data The ethnicity of the infants born to the case mothers (based on the ethnicity reported for the infants grandparents) was 84% Caucasian, 5% Aboriginal. Mixed ethnicity was reported for 11% of the infants with one parent Caucasian and the other parent Aboriginal, or rarely Black or Asian. The ethnic distribution was the same for controls and is typical for the Manitoba population [ 25 , 26 ]. There were also no significant differences between cases and controls with respect to their place of residence within the province (such as rural versus urban address). There were no significant differences in dietary and supplemental intake of folate, B 12 , or B 6 , or in the biochemical parameters of case and control mothers. There was no difference in the percentage of cases and controls who reported taking prenatal vitamin supplements during pregnancy (37/48 cases and 55/72) or taking vitamin and/or folate supplements preconceptionally (17/48 cases and 25/72 study controls). We attempted to divide our cases into smaller groups by type of pregnancy complication. We also separated isolated IUGR and IUGR associated with hypertensive disorders of pregnancy. Most of the groups lacked power for statistical analysis due to small numbers. However, normotensive women whose fetus had IUGR (N = 12) had a higher frequency of the C677T MTHFR variant compared to the population controls (q = 0.33, OR 2.58 95% CI, 1.78–3.73, p = 0.013). Homozygosity for the C677T MTHFR variant is associated with IUGR in women who do not take vitamin supplements according to one large study of Canadian women [ 10 , 27 ]. Our findings are in agreement with this result as only 3/12 women took supplements. We found this effect in a group of combined heterozygous and homozygous women. There was a trend towards higher mean weight for mothers who had complications at the time of MSAFP test in the individual comparisons, but this was not significant after correction for multiple comparisons (Table 2 and 3 ). The multivariate analysis did not reveal any unexpected associations, but it did show the importance of maternal weight as a variable (r = 0.933, p = 0.024). This was also not unexpected given that some of the complications we were examining are associated with obesity [ 28 ]. Even after controlling for women's weight in the multivariate analysis, the higher frequency of C677T MTHFR among cases remained significant (r = 0.734, p = 0.0462). There was no association between weight and MTHFR status (r = 0.431, p = 0.679). Table 3 Comparison of the nonparametric characteristics of women with unexplained elevations of MSAFP according to those with and without complications of pregnancy. Nonparametric Characteristics Cases Controls p value Location Winnipeg 44 63 0.854 southern city 3 2 southern town 3 5 southern rural 8 8 northern city 2 1 northern town 1 4 northern rural 5 7 ethnicity 0.972 Caucasian 52 66 Aborginal 2 2 Mixed Caucasian/Aboriginal 7 6 Mixed Caucasian/Black 1 3 Asian 1 1 Mixed Caucasian/Asian 1 1 Unknown 3 1 diabetes in pregnancy 2/67 1/80 0.207 maternal smoking present (0 = nonsmoker, 1–3 = half pks/day increments) 0 = 47, 1 = 11, 2 or more = 9 0 = 60, 1 = 8, 2 or more = 12 0.721 gender of baby 27 females, 40 males 42 females, 38 males 0.352 parity = number of women 0 = 37, 1 = 20, 2 = 7, 3 or more = 3 0 = 40, 1 = 29, 2 = 7, 3 or more = 4 0.254 previous miscarriages 11/67 15/80 0.203 previous case pregnancy 1 0 0.967 Discussion Unexplained elevations in MSAFP are known to be associated with an increased risk for complications of pregnancy [ 2 ]. Others have reported that presence of the C677T MTHFR variant in pregnant women with low folate intake is associated with increased risk for pregnancy complications [ 2 , 29 - 31 ]. The unique finding of this study is an increase in the frequency of the C677T MTHFR variant among women with normal folate intake, who went on to have complications of pregnancy after an unexplained elevation of MSAFP (Table 1 ). The lack of folate deficiency in this population was unexpected, given previous research which showed that 23.6% of Newfoundland and Labrador women are folate deficient at their first prenatal visit [ 32 ]. As our study was retrospective, we did not have data on levels during pregnancy. It has recently been shown that the C677T MTHFR variant does not affect maternal serum homocysteine levels in pregnancy among women who take prenatal multivitamins [ 8 ]. Also a recent prospective study shows that there is no difference in homocysteine levels at midtrimester between women who later develop preeclampsia and those who do not [ 33 ]. As is the situation with NTDs, lack of folate deficiency by current definitions in a non-pregnant woman may not indicate that her folate intake is adequate for pregnancy. This would especially be true for women with the C677T MTHFR variant. Reexamination of the current definition of what constitutes a normal biochemical result for folate intake for women of child bearing age should be undertaken to clarify this. We suggest that the negative effects of the C677T MTHFR variant are more likely to occur in early pregnancy before women began taking prenatal vitamins because the majority of our study participants took prenatal vitamins, but only 35% took preconceptional supplements. We suspect that reduced methylation interfering with cell proliferation in the placenta as originally suggested by Eskes (2000) [ 3 ]. In conclusion, using a retrospective case/control study, we have found that women with unexplained MSAFP elevations who have complications in later pregnancy are more likely to have the C677T MTHFR allele. Our resultsdo not suggest that C677T MTHFR predisposes a woman to having an elevation of MSAFP level (as we did not compare the C677T MTHFR frequency in women with and without elevated MSAFP), but having one or more copies of this variant predisposes such screen positive women to having complications in later gestation. It remains to be seen if other risk factors can be identified which can more accurately define this high risk group. Authors' contributions All authors participated in original study design except CS. CG, BC and CS all acted as principal investigators for funding. NB assisted with all grant proposals. NB undertook the review of the individual MSAFP files and MMSSP database searches, designed the dietary and family history surveys, classified cases and controls, acted as study coordinator handling all aspects of participant contact, and provided data analysis. All authors also participated actively with NB for various aspects of the study. CG provided MTHFR genotyping. LS provided biochemical analysis. NB drafted the original manuscript with assistance from BC. CG and BC handled ethics approval assisted by NB. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC520832.xml
517720	Vitamin D deficiency and causative factors in the population of Tehran	Background There are multiple studies in different countries regarding the prevalence of vitamin D deficiency. These studies showed high prevalence of vitamin D deficiency in Asian countries. This study tries to elucidate the prevalence of vitamin D deficiency and its influencing factors in population of Tehran. Methods 1210 subjects 20–64 years old were randomly selected. 25 (OH) D serum levels were measured. Duration of exposure to sunlight, the type of clothing and level of calcium intake and BMI were quantified based on a questionnaire. Results A high percentage of vitamin D deficiency was defined in the study population. Prevalence of severe, moderate and mild Vitamin D deficiency was 9.5%, 57.6% and 14.2% respectively. Vitamin D serum levels had no significant statistical relation with the duration of exposure to sunlight, kind of clothing and BMI. Calcium intake in the normal vitamin D group was significantly higher than the other groups (714.67 ± 330.8 mg/day vs 503.39 ± 303.1, 577.93 ± 304.9,595.84 ± 313.6). Vitamin D serum levels in young and middle aged females were significantly lower than the older group. Conclusions Vitamin D deficiency has a high prevalence in Tehran. In order to avoid complications of vitamin D deficiency, supplemental dietary intake seems essential.	Background Vitamin D is an essential element for establishing and maintananing bone structure. Vitamin D deficiency results in rickets and osteomalacia. Even slight vitamin D deficiency results in secondary hyperparathyroidism and increased bone resorption [ 1 , 2 ]. In addition, there has been increased attention to the physiologic importance of vitamin D in non-skeletal tissues [ 3 ]. Vitamin D is supplied by consumption of vitamin D-rich foods and by vitamin D synthesis in skin. Natural nutrient materials are not a sufficient source of vitamin D to supply the body requirements; therefore where there is no supplementation of foodstuffs, the main source for vitamin D is produced by UV light [ 4 , 5 ]. Regarding the significant role of sunlight in vitamin D synthesis, it is quite logical to suggest low prevalence of vitamin D deficiency in tropical countries. However the studies carried out in the preceding two decades have shown a high prevalence of vitamin D deficiency in tropical countries such as China, Turkey, India, Iran and Saudi Arabia [ 6 - 14 ]. The prevalence of vitamin D deficiency varied between 30% and 93%. However, the majority of these studies were limited to specific age and sex groups. Therefore, elucidation of vitamin D status at the community level and in different climates of a country seems essential. The present study is a part of a national project of prevention, diagnosis and treatment of osteoporosis that investigates the prevalence of vitamin D deficiency and its influencing factors in the population of Tehran. Methods 1272 healthy men and women aged 20–69 years were selected based on randomized clustered sampling from 50 blocks in Tehran. Exclusion criteria were known hepatic or renal disease, metabolic bone disease, malabsorption, sterility, oligomenorrhea, type I diabetes, hypercortisolism, malignancy, immobility for more than one-week, pregnancy, lactation, and medications influencing bone metabolism. The study protocol was approved by research ethics committee of Endocrinology & Metabolism Research Center (EMRC). Sampling was performed after taking informed consent at the beginning of 2001 in the subjects place of residence. 1210 of 1272 selected subjects participated in this study (response rate was 95%). One fasting blood sample was taken from each participant in his/her place of residence. Sample centrifuge and serum extraction were done in the field. Then samples were sent to the EMRC laboratory for analysis and were frozen immediately. 25-hydroxy vitamin D (25(OH) D) level was measured with RIA method (Biosource Europes.A,Ò). Normal range for serum vitamin D (25(OH) D) was 23 to 113 nmol/l. Serum PTH measurement was done using RIA method (Diasorin,Ò). Normal range for PTH is 13 to 54 nmol/l. Interassay and Intrassy for 25(OH) D were 8%, 6.8% and for PTH were 8.9% and 6.1% respectively. The subjects were asked to complete a questionnaire at the time of bone mineral densitometry analysis. The questionnaire included details of duration of exposure to sun light in previous month (less than 30 minutes/day; between 30 to 60 minutes/day; between 60 to 120 minutes/day; more than 120 minutes/day), sunscreen cream usage, clothing (exposure of hand and face or more than). In order to quantify the level of vitamin D and calcium consumption in the previous month, a food frequency questionnaire which was designed and standard by the Iranian Nutrition Institute was completed. Height and weight were measured at this stage. 25(OH)D equal or less than 12.5 nmol/l was considered as severe vitamin D deficiency or group 1 and vitamin D more than 12.5 nmol/l and less than 25 nmol/l was considered as moderate deficiency or group 2 [ 15 ]. PTH changes in various vitamin D serum levels were applied to detect mild vitamin D deficiency which has 25 (OH)D more than 25 nmol/l and less than or equal to 35 nmol/l. Threshold for mild vitamin D deficiency was measured by applying PTH changes in different serum levels of 25(OH) D. SPSS software (version 10) was used for data analysis. In descriptional statistics 5, 50, 95 percentiles were used. Results were expressed as mean ± SD or median. To find any significant difference between groups, X 2 test Kruskal-Wallis were used. Results In order to quantify serum levels of vitamin D and other biochemical parameters, serum samples were taken from 1210 subjects (response rate was 95%). 41% of subjects were male and 59% were female. Age and sex distribution of participants are shown in table 1 . In the second part of study (recall for bone mineral densitometry) for 666 subjects the questionnaire was completed. Table 1 Age and Sex distribution of participants Age(year) Total number Female Male 20–29 241 128 113 30–39 308 203 105 40–49 294 191 103 50–59 209 116 93 60 > 158 77 81 Figure 1 demonstrates vitamin D levels histogram in the study population. Total prevalence of severe, moderate and mild vitamin D deficiency was 9.5 %, 57.6% and 14.2 % respectively (Figure 2 ). Figure 1 Histogram of Vitamin D serum levels in study population Figure 3 demonstrates 95, 50 and 5 percentiles of vitamin D according to age and sex. Figure 3 Median, 5, and 95 percentile of Vitamin D in variable age and sex groups Serum levels of vitamin D in females above 60 years was higher than in other age groups (P < 0.001: Kruskal-Wallis test). Vitamin D serum levels in females between 20–29 years and 30–39 years was less than other age groups (P < 0.001). Median vitamin D level in females in age range of 20–29 years and above 60 years was 17 nmol/l and 39 nmol/l, respectively. Prevalence of high level of vitamin D (more than 150 nmol/l) in 60–69 years old female age group was significantly more than other age and sex group (P < 0.01). In recalling for bone densitometry, 666 returned (55% of study population) in whom the effect of influencing factors was evaluated. Table 2 shows mean BMI and daily calcium intake in different vitamin D groups. BMI was not significantly different in vitamin D groups but calcium intake in normal vitamin D group was significantly higher than other groups. Table 2 Mean BMI and daily calcium intake in variable vitamin D groups Groups Parameters Vitamin D ≤ 12.5 (nmol/l) 12.5<vitamin D ≤ 25 25<vitamin D ≤ 35 35.1<vitamin D ≤ 150 BMI (kg/m 2 ) 27.32 ± 5.02 26.44 ± 4.52 27.66 ± 5.16 26.99 ± 4.93 Calcium intake (mg/day) 503.39 ± 303.1* 577.93 ± 304.9* 595.84 ± 313.6* 714.67 ± 330.8 *Significant difference with normal group (35.1<vitamin D ≤ 150) P < 0.05 Discussion In our study the prevalence of severe and moderate vitamin D deficiency was 9.5 % and 57.6%, respectively. Mild vitamin D deficiency had a prevalence of 14.2%. Multiple studies have been carried out about the prevalence of vitamin D deficiency but they were mostly limited to a small sample size or assessed a specific age group (especially elderly). In countries where vitamin D fortified foodstuffs are available (USA and some Scandinavian countries), prevalence of vitamin D deficiency is between 1.6–14.8% in different age groups [ 16 - 18 ]. In other European countries where there is no vitamin D supplementation, deficiency is more prevalent. The studies which assessed middle-aged and elderly people showed vitamin D deficiency prevalence of 14% to 59.6% in these age groups [ 19 - 22 ]. Vitamin D deficiency prevalence is much higher in Asian countries. Fonseca and colleagues, demonstrated vitamin D level above 10 ng/ml in only 3 saudian females out of 31 [ 13 ]. Sedrani and colleagues showed vitamin D deficiency prevalence of 44%–100% in Saudian young females with different coverage and race [ 9 , 10 ]. Azizi & colleagues showed vitamin D level less than 18 ng/ml in half of the study population. Vitamin D deficiency prevalence in 10–19, 20–24, 30–41 was 47.4%, 59.5%, 44.8% respectively [ 11 ]. In the present study 81.3 % of subjects had vitamin D deficiency. Most studies have shown higher prevalence of vitamin D deficiency in the elderly [ 15 - 18 ]. Elderly females demonstrated statistically significant higher serum levels of vitamin D compared with young and middle aged females. Parenteral vitamin D intake by elderly was the major differentiating factor between various age groups that could explain high prevalence of a high level of vitamin D in elderly females. Subjects who took vitamin D in the sampling period were excluded from the study, but those who had taken vitamin D in the preceding months were not omitted. Vitamin D has a long half-life and its frequent prescription especially in elderly women with musculo-skeletal complaints can explain differences in serum vitamin D. Regarding the essential role of sunlight in vitamin D synthesis, it is quite unexpected to see a high prevalence of vitamin D deficiency in countries such as Saudi Arabia. Different hypotheses can be made such as insufficient sun exposure, clothing habits, hyper pigmentation, air pollution, insufficient intake of vitamin D and special dietary habits [ 27 ]. Although sunlight plays an essential role in vitamin D synthesis, its' role in vitamin D deficiency of Asians is not obvious. Tehran, which is located in 36° 21''N, has a mean sun exposure of 8 hours per day [ 28 ]. In the present study sun exposure was not significantly different between subjects with vitamin D deficiency and those with normal vitamin D status. Although there is sufficient sunlight in all seasons in Saudi Arabia, Sedrani showed that half of people who had more than 30 minutes of sun exposure had vitamin D less than 8 ng/ml (20 nmol/l) [ 10 ]. Holick & colleagues showed similar rate of vitamin D synthesis in Asians as of Europeans; but Asians required greater duration of exposure [ 29 ]. Other studies showed the same degree of increase in 25 (OH) D in summer months in Asians compared with Europeans [ 30 ]. In our study, there was no difference in clothing habits of vitamin D deficient group and normal group. Sedrani showed 70% vitamin D deficiency in males compared with30 % in young females in spite of greater clothing in females [ 10 ]. Another hypothesis says that air pollution prevents enough UV exposure to skin. Insufficient vitamin D intake is another hypothesis for high prevalence of vitamin D deficiency in Asians. Insufficient dietary supplies of vitamin D in countries where foodstuffs are not supplemented, leads to generally low dietary intake of vitamin D. In the Omdahl study, daily vitamin D intake in elderly healthy women was 54 units [ 16 ]. Our study does not assess daily dietary vitamin D intake. Decreased dietary calcium level induces increased serum PTH level and increased catabolism of 25 (OH) D, therefore decreased 25(OH)D is induced by dietary calcium deficiency [ 15 ]. Average calcium intake was 660 ± 350 mg/day in this study. There was no significant difference in dietary calcium intake among the different vitamin D groups. Although consumption of phytates and animal-derived proteins was not investigated in present study, high dietary consumption of phytates and low dietary intake of animal proteins is one of the suggested hypothesis for vitamin D deficiency [ 24 , 26 , 27 ]. There are other hypotheses to explain vitamin D deficiency among Asians. Awumey et al showed higher activity level of 24-hydroxylase in fibroblasts of Indian-Americans compared with controls [ 31 ]. Therefore, increased vitamin D catabolism may cause vitamin D deficiency in Asians. In order to elucidate specific etiologies responsible for high prevalence of vitamin D deficiency in Asians further studies should be carried out. It is possible that vitamin D deficiency is induced by combination of above mentioned etiologies. In order to clarify the significance of each etiologic factor, randomized controlled trials are necessary. Conclusions Given the high prevalence of vitamin D deficiency in Iran, effective solution to overcome its consequences seems indispensable. Competing interest None declared. Figure 2 Frequency of variable Vitamin D groups Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC517720.xml
517708	SED, a normalization free method for DNA microarray data analysis	Background Analysis of DNA microarray data usually begins with a normalization step where intensities of different arrays are adjusted to the same scale so that the intensity levels from different arrays can be compared with one other. Both simple total array intensity-based as well as more complex "local intensity level" dependent normalization methods have been developed, some of which are widely used. Much less developed methods for microarray data analysis include those that bypass the normalization step and therefore yield results that are not confounded by potential normalization errors. Results Instead of focusing on the raw intensity levels, we developed a new method for microarray data analysis that maps each gene's expression intensity level to a high dimensional space of SEDs (Signs of Expression Difference), the signs of the expression intensity difference between a given gene and every other gene on the array. Since SED are unchanged under any monotonic transformation of intensity levels, the SED based method is normalization free. When tested on a multi-class tumor classification problem, simple Naive Bayes and Nearest Neighbor methods using the SED approach gave results comparable with normalized intensity-based algorithms. Furthermore, a high percentage of classifiers based on a single gene's SED gave good classification results, suggesting that SED does capture essential information from the intensity levels. Conclusion The results of testing this new method on multi-class tumor classification problems suggests that the SED-based, normalization-free method of microarray data analysis is feasible and promising.	Background DNA microarray technology is now playing an increasingly important role in biomedical research. Microarray technology gives one the opportunity to measure gene expression levels of thousands to tens of thousands of genes simultaneously, in order to study the differential gene expression pattern between different developmental stages, diseases states and samples treated with drugs or other compounds. Before comparing data from different arrays to address these biological questions, however, a "much more mundane but indispensable " normalization step [ 1 ] is currently used in most microarray analyses. Because of the slight difference in RNA quantities, imaging settings and other variables, even in very controlled experiments the intensity levels from different arrays are of different scales and need to be normalized before they can be compared with each other. Various normalization methods have been developed and some are widely used. The simplest method is total intensity based normalization [ 2 ]; this approach scales intensity levels of every gene by a constant factor so that total intensities of all the arrays are the same. "Spiked-in" based normalization methods scale intensity based on spiked-in standards [ 3 ]. Nonlinear normalization methods use local regression to scale intensities to compensate for the intensity-dependent differences between arrays [ 4 - 6 ]. For most current applications, these normalization methods seem to be adequate. However, the residual left by a less than perfect normalization procedure is another source of non-biological variation that is usually non-desirable, especially when the differences in expression levels are expected to be small [ 7 ]. In addition, if the goal is meta-analysis of multiple sets of microarray data [ 8 , 9 ] systematic differences between experiments may result in a normalization artifact. We were therefore interested in developing an approach to analyse microarray data without first performing a normalization step. Our approach was partly inspired by non-parametric statistical methods [ 10 ]. For example, nonparametric methods that use ranks [ 11 , 12 ] to compare microarray results, in addition to being distribution free, have the additional advantage of being normalization free. DNA microarray technology has been used widely in biomedical studies. One interesting application is in the area of molecular classification; one popular use is in the comparison of tumor samples. Since clinical and histopathological classification is sometimes difficult and labor-intensive, the use of genome wide expression patterns to classify tumor samples has recently become a very active research area [ 13 - 16 ]. Although some tumors appear to be amenable to classification using microarray data [ 17 , 18 ], general multiple tumor classification using microarray data has proved to be an interesting and challenging task for several reasons: the general difficulties inherent in multi-class classification problems, the small number of samples available, and the inherent biological variation between specimens, etc . We decided to use multi-class tumor classification as a test case to illustrate the power of our approach. We compared our results for a multi-class tumor classification problem with more conventional approaches published by Ramaswamy et al . [ 19 ] and Yeang CH et al. [ 20 ]. These authors compared the accuracies of using k-Nearest Neighbors (kNN, 60–70%), Weighted Voting (WV, 60–70%) and Support Vector Machine (SVM, 80%) algorithms in a multi-class tumor classification problem and concluded that SVM is a more powerful machine learning algorithm for this application. Results Normalization Free approach to microarray data analysis Generally, measurements on single microarrays give a real-valued intensity level x i (1<= i <= N) for each gene i on the array, where N is the total number of genes on the array. Without first doing some type of normalization, the intensity level of gene i from array A, x i A , cannot be directly compared with the intensity level of gene i from array B, x i B . In this study, we sought an alternative quantity or quantities that can be directly compared between different arrays without compromising important biological information. One obvious candidate is r i , the rank of intensity level of gene i on the array. However, we felt that rank is not an adequate measure because information about relative expression level is not represented explicitly. Instead, we decided to use the following measures. Let s ij = 1 if(x i - x j > 0) 0 otherwise (1) , where 1<= i, j <= N. Basically, s ij is the sign of the intensity difference of gene i and j on a single microarray and therefore will remain unchanged under any monotonic transformation of x. Therefore, instead of computing with the absolute expression level of a gene, its relative level to all the other genes on the microarray is used. For each gene i, instead of one real valued x i , the approach uses s i = (s i1 , ..., s ij , ..., s iN ), a binary vector of size N. For ease of reference, we will simply refer to this value as the SED (Signs of Expression Difference) of gene i; and the entire matrix (s ij ) the SED of the array. Given (x i ), s ij is simply and uniquely defined but (s ij ) does not uniquely determine x i so some information is lost by only using (s ij ) instead of (x i ). Since r i = Σ j = 1,...,N s ij is the rank of gene i in terms of intensity levels, rank information is preserved in (s ij ). What is lost in the transformation from (x i ) -> (s ij ) is just the intensity differences between the closest ranked genes, which in most cases are small, considering that microarray data are generally considered "very noisy". It was our major goal to demonstrate that (s ij ) has indeed captured important components of the information from (x i ). Instead of directly using the intensity levels x, and its derivatives such as the mean μ, the standard deviation σ and the signal to noise ratio (S2N) between two sample groups A and B, [(μ A + μ B )/(σ A + σ B )], we will use (s ij ) to compare gene expression differences between arrays. Since we expect measurement variations within an array will be less than those between arrays and we take the signs of relative expression differences to get SED, we expect the SED will be less "noisy". However, the value of any single s ij may still vary between technical and biological replicates. One would expect more s ij would change values randomly if the technical replicates was done on arrays that were fabricated in a different run than arrays from same run, for example. Biological variations are expected to be even more frequent. However, we hypothesize that we can perform statistical analysis on the SED, which contains tens of thousands of s ij for a single gene, and minimize the impact of such noises. We will also consider (sp ij ), a natural generalization of the SED concept. Here, sp ij is the probability of x i > x j . In other words, imagining one can get a large number, n, of either technical or biological replicates of the sample of interest, then sp ij = m/n as n -> 8, where m = Σ K = 1,...,n s ij K and s K is for replicate K. We will call (sp i ) = (sp i1 , ..., sp ij , ..., sp iN ) the SED probabilities of gene i. Note that in calculating both SED and SED probabilities, only intensity comparisons within arrays are involved and therefore forego the normalization step. For example, if gene i is more highly expressed in sample A than B we would expect that more s ij A than s ij B would be 1 instead of 0 and the overall (very loosely defined) sp ij A would be larger than sp ij B . Since rank can be calculated from SED, any rank based method can be expanded to use SED. A gene i's SED can be viewed in two different perspectives. On one hand, it provides information about gene i's expression level relative to every other gene on the array, and therefore can be used to examine gene i's expression patterns between samples. On the other hand, it also provides information about the expression levels of all the other genes on the array, using the gene i as a control, in essence. Therefore, SED can be used to study questions either at the gene level or at the array level. In this paper, we focus on solving a simpler problem at the array level where it is not necessary to decide whether the expression level of an individual gene is increased or decreased between array A and B and by how much. Rather, it is focused on whether the overall expression patterns are different at all between array A and B. Multi-class classification of tumor samples To test whether (s ij ) and (sp ij ) extracts most of the information from (x i ), we used these values in a test case of a multi class classification problem described by Ramaswamy et al. and Yeang et al [ 19 , 20 ]. Two algorithms were used to classify each of the 144 tumor samples into one of 14 tumor classes. One is the Naive Bayes (NB) classifier [ 21 ] using SED probabilities. The other is the Nearest Neighbor (NN) classifier using SED. In the NB method, to classify a sample T, we first calculate (sp ij C ) for each class C (1 <= C <= 14) using training samples, i.e. the 144 samples with T taken away (for details see methods). Then sample T is classified according to: score(T, C) = Σ i = 1,...N Σ j = 1,...,N log(p ij ), (2) where p ij = sp ij C if s ij T = 1 1 - sp ij C otherwise T is simply classified to the class C that has the maximum score. In the NN method, we compute instead, for each training sample t, matches(T, t) = Σ i = 1,...N Σ j = 1,...,N δ(s ij T , s ij t ), (3) where δ(x, y) = 1 if x = y. 0 otherwise Then T is classified to class C of the sample t that has the maximum matches. If one is to give a statistical interpretation of these scores, one can simply view (sp ij ) as defining a multi-binomial probability model. In addition, one could consider each s ij as a draw from a binomial distribution with probability p ij = sp ij . Then, the score(T, C) is simply a logarithm of the probability p to get all the s ij exactly the same as s ij T under the probability model C where p ij = sp ij C . (Since each class defines a different probability model, score(T,C) for difference class C, in theory, should not be directly compared. Instead, a P value should be calculated from the probability model for Pr(p<exp(Score(T, C))) and used to evaluate the closeness of sample T to each class C. For simplicity, we are not considering such issues here.) When the NB algorithm was applied to the 144 samples, the accuracy obtained was about 63%; the NN algorithm performed slightly better and gave an accuracy of 70%. Feature selection Depending on the algorithm, a better classification result can sometimes be obtained by using a subset of genes [ 22 , 23 ]. We were interested to know whether feature selection helps to increase accuracy in our approach. Within our framework, it is easier to treat (i,j) pairs as selection units. We therefore filtered out (i,j) pairs where the variance of sp ij across the 14 tumor classes was less than a pre-determined value and left the rest of the algorithm unchanged. We reasoned that the filtered-out part of the matrix has less discriminating power across the tumor spectrum and might add noise due to the small sample sizes used. Using the NB algorithm, the best result achieved was 70% with a cutoff σ 2 = 0.06, while the NN method with σ 2 = 0.05 gave 77%. Table 1 lists the accuracies achieved using different feature cutoffs. "Single gene's SED" based classifier The above procedure utilized the entire SED matrix as a classifier. In other words, all the relations between genes were considered in the classification. To determine whether the inclusion of the whole matrix was actually required to achieve the current accuracy, we investigated the efficacy of using single gene's SED as classifiers. In these cases, we define a classifier based on gene i and its relative expression to every other gene. Therefore, the score i (T, C) = Σ j = 1,...,N log(p ij ), where p ij is as same as mentioned previously. Similarly, matches i (T, t) = Σ j = 1,...,N δ(s ij T , s ij t ) defines a classifier based on gene i's SED. Fig. 1 shows a display of the cumulative frequency of single gene SED based classifiers versus accuracy for all the 16063 classifiers. In general, single gene-based classifiers performed worse than the whole genome-based classifiers, as expected. Nevertheless, most of the classifiers performed reasonably well, compared with just using single gene expression levels. About 80% of the single gene based classifiers resulted in an accuracy between 40% and 60%, while about half of the classifiers had an accuracy greater than 50%. These results suggest that there is a lot of redundant information in the SEDs and SED probabilities and that our method should be reasonably robust. We then investigated the number of genes that are required to achieve the current accuracy. Fig. 2 shows the combined results for classifiers using only a subset of genes. Our results suggest that a subset of genes (~200) is sufficient for predictions and that the prediction accuracy is stable after 1000 genes. Different classification accuracy between tumor classes From the analyses described above, we noticed that there was a significant difference in accuracy between different tumor classes. For 3 classes (LY, LE, CNS) we obtained either 100% or close to 100% accuracy (see Table 2 for detail). Since these happen to correspond to the 3 classes with more than double the number of training samples than the other classes, we tested whether this high accuracy is due to the larger sample sizes by using only 8 training samples for every tumor classes. The results were essentially the same, indicating that sample size is not the issue. On the other hand, there are classes where we obtained very poor results; these often happen to be the same classes where SVM in [ 19 , 20 ] performed poorly as well (see Table 2 ). We were interested in exploring the possible reasons for misclassification. In Fig. 3 , a scatterplot of the SED Match scores (without feature selection) between 8 OV samples and 8 CNS samples is displayed. The OV and CNS class were selected since one is "very hard" and the other is "very easy" to classify. Without trying to be statistically correct, the plot does suggest that samples of the OV class are in general "farther away" from each other, compared with those from the CNS class. As this may be one of the reasons that the OV class is harder to classify, algorithms that take this kind of information into account may perform better than the simple ones we have presented here. Discussion Although we used the multi-class tumor classification problem as our test case, our major goal was to illustrate the feasibility of the normalization free SED approach, and not in sample classification per se . Therefore, we chose the algorithms NB and NN for their simplicity and not for their performance in solving this specific problem. The performance of a classifier depends, in this case, mainly on the power of its algorithm, and the data representation it used. From a machine learning perspective, one can simply view the intensity -> SED transformation as a change in data representation, a mapping from the gene's attribute, intensity x, to some features SED. It was our goal to demonstrate that the new features (SED and SED probability), in addition to being normalization free, still convey the essential information in the original attribute, the intensity x. Since the data representation is quite different between the intensity x (a real valued quantity) and SED (a binary valued vector of rather large size N), it is difficult to directly compare the two. No obvious yet non-trivial algorithms work with both representations; even if there were such an algorithm it is not clear that it would be the right one to use for comparison as it might well be the case that different data representation works best with different algorithms. Here, we have limited the presentation to some empirical results with SED representation, which are comparable with results using several different algorithms that are based directly on raw intensity [ 19 , 20 ]. Our classification results are close to those obtained with WV and kNN methods, which are based on directly focusing on intensity levels. Previous results using SVM were significantly better, but we feel the differences are due more to the power of the algorithm [ 24 ] than the way information is coded. In fact, slightly more accurate results are obtained with modification of algorithms that directly manipulate intensity levels [ 25 , 26 ]. We do not imply that the algorithms (NB and NN) we chose are better than other alternatives (and we do not have empirical evidence pointing either way). Instead, we fully expect more sophisticated algorithms would work better with the SED approach as well. Certainly, SED probability is more information rich than SED. We expect that an SED probability based analysis would perform better than the simple binary valued SED. In this paper, we mainly tested the SED. SED probability is only used for a group of samples, not for single samples. If one limits oneself to use only raw data, then for single arrays one can only get SED. However, if some assumptions about the patterns of gene expression levels can be made, one can certainly get an estimation of SED probability even for a single array. For example, as in some nonlinear normalization algorithms, if one assumes that the variation of expression levels are similar for genes with similar expression levels, then one can estimate SED probability from a probability model. Also, the magnitude of the intensity difference can also be used to help such an estimation. Alternatively, as more and more microarray data become available, one can use other similar samples to get an estimation of a prior SED probability, and then use a Bayesian approach to estimate the sample's SED probability. The obvious disadvantage of our SED based approach is that for each gene expression level, one is not dealing with a single real number but instead a vector of size N, where N is in the tens of thousands. This could significantly increase both computing time and memory requirement (however, see methods for details) On the other hand, it also has certain advantages: 1) It is free of normalization noise. Since it is generally believed that biological variation is larger than technical variation and normalization noise is just another source of technical variation, the benefit here is only of a limited scope. However, it may be important when the expression level difference one is interested in is small. 2) In addition to being normalization free, SED and SED probability also have the advantage in being distribution free, and therefore could perform better if the intensity levels were non-normal. 3) SED and SED probability are easier to interpret. SED values can easily be checked against raw intensity levels according to Eq. (1). While SED probability is one step further away from intensity levels, one could still have an intuitive sense of it and make comparisons between different experiments. It would be much harder to have a real grasp of the absolute gene expression level, except that it is "high" or "low" or somewhere "in between"; it is certainly harder to compare between experiments intuitively. We have only tested the SED approach on datasets that are from the same chip format. Data from different chip formats or complete different technology platforms, of course, would be harder to compare. But they are also challenge for normalization based method. It would certainly be interesting to compare SED and normalization based method under these more challenging conditions. If this normalization-free approach (SED) proves to retain the essential biological information in general, its application may be extended to meta-analysis where different datasets could be integrated and intervalidated. The method could also be used when the number of arrays is a limiting factor for experiments. For example, one could take advantage of the massive amount of public array data, obtain prior distribution of SED probabilities from datasets with similar conditions, and analyze new data within a Bayesian framework. If the performance of the nearest neighbor method in general is anywhere close to what we demonstrated in the multi tumor classifications here (as is clear from Eq. (3) and Fig. 3 , the nearest neighbor method, without feature selection at least, allows direct sample vs. sample comparison. Note also that the samples in the multi tumor problems are from different biological specimens, therefore, large between-sample-variation is expected), it might be used as a microarray database query method, i.e. , to find similar microarray results in the database that are "similar" to one's own, independent of array annotations. It might also be worth noting that the SED approach could easily be applied to other kinds of comparative data analysis for samples with very large numbers of "noisy" attributes. The SED approach may also perform better when between-sample-variation is large, especially if such variation contains some rather uninteresting technical measurement errors that would not affect within-sample-variations. Conclusions We have proposed a new approach to analyze microarray data and tested the method on a set of publicly available datasets. The results were comparable to those obtained with some widely used normalization based algorithms. We hope that we have demonstrated that this normalization free method is feasible and promising. We think the SED based, normalization free approach could be used to complement the more popular normalization based approaches in microarray data analysis. Methods Microarray data for multiple tumor samples were downloaded from . Naive Bayes and Nearest Neighbour Classifiers were implemented in the Java programming language. Ad hoc analysis was done with perl scripts. Graphics were generated using the R computing environment. Naive Bayes method Because of the uneven and relatively small sample sizes for each tumor class (mostly 8 but up to 24), extra care was taken in computing sp ij . Assuming a prior probability of 0.5, sp ij was estimated by Bayesian posterior probability (m+1)/(n+2) where n is the total number of samples in the class and m is the total number of samples where x i > x j . For classes that were over-represented (sample size > 8), the threshold of sp ij was set to [0.125, 0.875], since the NB method is sensitive to the extreme values of sp, and samples can be over-predicated without thresholds. In addition, several alternatives were tested to demonstrate that our results were reasonably robust and not sensitive to the particular choices we made: 1) To examine the influence of the sample size, in a separate analysis the sample size of ME, LE, CNS class was artificially reduced to 8, i.e. only the first 8 samples were used to calculate sp ij with no significant change of results observed; 2) Since sp ij depends on the sample size n for each tumor class, we have applied a "sample replacement" strategy in addition to the usual "take-one-sample-out" approach for cross-validation, i.e. when one sample is taken out as the test sample, another sample from the same class is duplicated to take its place to keep the sample size constant. Essentially the same results were obtained. Results reported are from the sample replacement runs. In Feature Filtering, the variance of sp ij between all 14 classes was calculated as: σ 2 = (Σ C = 1,...,14, sp ij C * sp ij C )/14 - ((Σ C = 1,...,14 sp ij C )/14) 2 (4) with the test sample taken out, and used as the criterion for feature exclusion. Nearest neighbor method Feature filter was done as in the Naive Bayes Method. Software implementation and availability The analysis was done on a computer (Pentium M 1.5 GHz) operating under Microsoft XP. Both Naïve Bayes and Nearest Neighbor Classifiers are implemented in Java. Since SED can be easily calculated from the raw intensities only the later are kept in memory and SED are computed from the intensities on an as-needed bases. Memory needed to analysis the 144 samples is less than 64 MB. The most computationally intensive algorithm that we tried is the Nearest Neighbor method without any feature selections and it takes about 10 sec to calculate SED score for one pair of tumor samples with about 16000 genes. A Java program named SED (including source code) to perform nearest neighbor analysis of microarray samples is freely available by contacting author at hw14@columbia.edu . Authors' contributions H.W. conceived of the SED study and performed implementations. H.H. refined the approach and provided additional statistical insight on SED. Both authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC517708.xml
509278	Characterization of yeast histone H3-specific type B histone acetyltransferases identifies an ADA2-independent Gcn5p activity	Background The acetylation of the core histone NH 2 -terminal tails is catalyzed by histone acetyltransferases. Histone acetyltransferases can be classified into two distinct groups (type A and B) on the basis of cellular localization and substrate specificity. Type B histone acetyltransferases, originally defined as cytoplasmic enzymes that acetylate free histones, have been proposed to play a role in the assembly of chromatin through the acetylation of newly synthesized histones H3 and H4. To date, the only type B histone acetyltransferase activities identified are specific for histone H4. Results To better understand the role of histone acetylation in the assembly of chromatin structure, we have identified additional type B histone acetyltransferase activities specific for histone H3. One such activity, termed HatB3.1, acetylated histone H3 with a strong preference for free histones relative to chromatin substrates. Deletion of the GCN5 and ADA3 genes resulted in the loss of HatB3.1 activity while deletion of ADA2 had no effect. In addition, Gcn5p and Ada3p co-fractionated with partially purified HatB3.1 activity while Ada2p did not. Conclusions Yeast extracts contain several histone acetyltransferase activities that show a strong preference for free histone H3. One such activity, termed HatB3.1, appears to be a novel Gcn5p-containing complex which does not depend on the presence of Ada2p.	Background Histones H3 and H4 are among the most evolutionarily conserved proteins (>90% identity from yeast→humans) [ 1 ]. Octamers composed of one histone H3/H4 tetramer and two histone H2A/H2B dimers package 146 bp of DNA into the basic repeating subunit of chromatin, the nucleosome [ 1 ]. Hence, as fundamental components of chromatin, these proteins are an integral part of all cellular processes involving chromosomal DNA. The physical characteristics of the histones are precisely regulated in the cell by an elaborate network of post-translational modifications that include acetylation, methylation, phosphorylation, ubiquitination and ADP-ribosylation [ 2 - 4 ]. These modifications are found primarily on the NH 2 -terminal tails of the histones. These domains, which protrude from the core of the nucleosome, are free to interact with, and be acted upon by, the nuclear environment. The past several years has seen the identification of numerous enzymes that are capable of modifying the histones. These enzymes are generally found in large, multi-subunit complexes and have activities that are not only specific for a given histone but are specific for particular amino acid residues within the histone [ 5 , 6 ]. The most well characterized histone modifying enzymes are the histone acetyltransferases (HATs). HATs catalyze the transfer of an acetyl moiety from acetyl-coenzyme A to the ε-amino group of lysine residues in the histone NH 2 -terminal tails. Historically, these enzymes have been classified as either type A or type B, based upon substrate specificity and cellular localization [ 7 ]. Found in the nucleus, type A HATs utilize nucleosomal histones as substrates. A number of Type A HATs have been identified in yeast. These include Gcn5p (SAGA, ADA, SLIK, SALSA and HAT-A2 complexes), Sas2p (SAS complex), Sas3p (NuA3 complex), Esa1p (NuA4 and picNuA4 complexes) and Elp3 (Elongator complex) [ 8 - 22 ]. These enzymes have been characterized primarily in the context of transcriptional activation but are likely to be involved in other chromatin mediated events as well [ 23 , 24 ]. Type B HATs were initially described as cytoplasmic enzymes that acetylate free histones in conjunction with chromatin assembly [ 7 ]. The de novo assembly of chromatin is a complex, multi-step process that occurs most prominently during DNA replication (but also accompanies other cellular processes involving DNA synthesis) [ 25 , 26 ]. Following induction of histone mRNA synthesis, histone proteins are translated in the cytoplasm. For histones H3 and H4, synthesis is rapidly followed by the acetylation of specific lysine residues in their NH 2 -terminal tail domains [ 27 ]. For newly synthesized histone H4, this acetylation occurs on lysine residues at positions 5 and 12 in all eukaryotic organisms examined to date [ 28 , 29 ]. For newly synthesized histone H3, acetylation appears to occur in distinct patterns that can differ from organism to organism [ 28 , 30 , 31 ]. The acetylated H3 and H4 form tetramers that are translocated into the nucleus and loaded onto DNA [ 32 ]. Following completion of the histone octamer by histone H2A/H2B addition, mature chromatin is formed following the deacetylation of histones H3 and H4 [ 33 , 34 ]. In contrast to the type A HATs, only one type B HAT has been characterized to date, Hat1p. Hat1p is an evolutionarily conserved enzyme that specifically acetylates free histone H4 [ 35 - 38 ]. Consistent with its identification as a type B HAT, recombinant yeast Hat1p, as well the Xenopus and Human Hat1p homologs, acetylates both lysine 5 and lysine 12 [ 35 - 39 ]. Hat1p was originally purified from yeast cytoplasmic extracts in a complex with Hat2p, a yeast homolog of the mammalian Rbap46/48 proteins [ 36 , 40 , 41 ]. Subsequent studies have shown that yeast Hat1p, as well as its higher eukaryotic counterparts, can also localize to the nucleus [ 37 , 38 , 42 ]. These results suggest that, while specificity for free histones is a bona fide characteristic, cytoplasmic localization may not be a strict criterion for classification as a type B HAT. Evidence has accumulated indicating that the acetylation of newly synthesized histones H3 and H4 play over-lapping roles in chromatin assembly. While yeast strains carrying a deletion of either the H3 or H4 NH 2 -terminal tail are viable, concomitant deletion of both NH 2 -termini (or combining tail deletions with alterations in specific sites of acetylation) results in a defect in nucleosome assembly and cell death [ 43 , 44 ]. In addition, while deletion of the HAT1 gene produces no observable phenotype, combining a deletion of HAT1 with specific lys→arg mutations in the NH 2 -terminus of histone H3 generates defects in both telomeric silencing and DNA damage repair [ 45 , 46 ]. However, despite the importance of the acetylation of newly synthesized histone H3 in chromatin assembly, there have been no type B histone acetyltransferases described that specifically target histone H3. To identify potential histone H3-specific type B HATs, we have systematically surveyed yeast extracts for candidate activities. Here we detail one such activity, termed HatB3.1. We provide evidence that this is a novel complex that utilizes Gcn5p as its catalytic subunit. Intriguingly, unlike previously identified Gcn5p-containing HAT complexes, HatB3.1 contains Ada3p, but not Ada2p. Results Identification of histone H3-specific type B histone acetyltransferase activities in yeast The highly selective activity of the native Hat1p/Hat2p complex for free versus nucleosomal histone H4 is the primary characteristic that distinguishes this enzyme from the type A histone acetyltransferases [ 35 , 36 ]. Therefore, to identify putative histone H3-specific type B HAT complexes, we systematically surveyed yeast extracts for activities that acetylated free histone H3 but not histone H3 packaged into chromatin. Extracts were prepared from cell cultures grown to mid-log phase to enrich for actively dividing cells, as the most robust period of chromatin assembly occurs during DNA replication. Yeast cell walls were digested with zymolyase and cytosolic extracts were produced by the lysis of the cells in low salt buffer followed by centrifugation to remove nuclei and large cell debris. Hence, this extract contained soluble cytoplasmic proteins as well as proteins loosely associated with the nucleus. The nuclear extract was obtained by incubating the nuclear pellet in buffer containing 1.0 M NaCl to extract proteins that are more tightly associated with the nucleus. It is difficult to reliably detect histone acetyltransferase activities in the relatively crude cytosolic and nuclear extracts. Therefore, to evaluate the intrinsic HAT activities present in each of the extracts, they were fractionated by anion and cation exchange chromatography. Fractions were assayed for HAT activity using 3 H-acetyl Coenzyme A and equivalent amounts of either free histones or chromatin as substrate. Histones were then resolved by SDS-PAGE and acetylated species visualized by fluorography. Fractionation of the cytosolic extract on a DEAE column is shown Figure 1A . As expected, the predominant type B activity present in these preparations was attributable to Hat1p, as indicated by robust, free histone H4 acetylation (Fig. 1A , lanes 28–34). The identity of the Hat1p/Hat2p complex was confirmed by western blot analysis using polyclonal antibodies against both Hat1p and Hat2p (data not shown). Figure 1 Identification of putative histone H3-specific type B histone acetyltransferases. Cytosolic and nuclear extracts were prepared and fractionated as outlined in the flow chart. Inherent HAT activities were identified by assaying column fractions with 3 H-Acetyl-Coenzyme A and equivalent amounts of either free histones or chromatin (as indicated). Reaction products were resolved by 18% SDS-PAGE and visualized by fluorography. The relative migrations of the core histones, as determined from coomassie blue staining, are denoted at the side of each fluorogram. The positions of Hat1p and putative H3-specific type B HATs are indicated by brackets. The cytosolic extract also contained at least two additional HAT activities. The first showed a clear peak that was centered on fraction 14 and acetylated free histones H3, H2B and H4. The activity of this HAT on chromatin was more difficult to determine as the H3 and H4 labeling seen in these fractions does not show a marked peak in fraction 14 and may be due to the leading edge of a HAT activity eluting at higher salt. Therefore, this activity may be a candidate type B HAT. There was also a distinct peak of HAT activity at fractions 18–20. With free histone substrates, this activity primarily acetylated histone H3. However, there was also a coincident peak of chromatin H3 and H4 acetylating activity in these fractions suggesting this activity is likely to be a type A HAT. Figure 2 HatB3.1 is a chromatographically distinct activity. DEAE fractions encompassing HatB3.1 activity were pooled and subjected to further fractionation. Fluorograms of liquid HAT assays, using free histones or chromatin as substrates, representative of gradient eluted Mono Q column fractions, showed that HatB3.1 activity can be separated from the overlapping activities present in the initial DEAE fractionation. Migration of the core histones is indicated. Migration of free histone H3 activity attributable to HatB3.1 is marked with an arrow. DEAE fractionation of the nuclear extract also revealed several distinct HAT activities (Figure 1B ). There were two H4-specific type A HAT activities that peaked at fractions 14 and 18, as indicated by activity on both free and nucleosomal histones. There was also a significant peak of activity that acetylated free histone H3 (there was also slight acetylation of histone H2B that is more easily seen in Figure 3 ) that was coincident with a minor nucleosomal H3 HAT activity (Fig. 1B right panel, lanes 16–34). This activity also partly overlapped the nucleosomal H4 activities. This peak of activity was rather broad and most probably results from the partial overlap of at least two distinct activities. In fact, the separation of these activities was readily apparent in Figures 3 and 4 . The strong overall preference of these activities for free histone H3 makes them good candidates for H3-specific type B HATs. As these are chromatographically distinct activities we have termed them HatB3.1 and HatB3.2 as indicated (Figure 1B , right panel). Figure 3 HatB3.1 activity is dependent upon GCN5. Nuclear extracts, generated as depicted in Figure 1 from the indicated isogenic deletion strains, were fractionated via DEAE anion exchange chromatography. Fluorograms of HAT assays resolved by 18% SDS-PAGE are shown with the migration of the core histones as indicated. Fractions of equivalent conductance are aligned for each strain. Regions containing HatB3.1, HatB3.2 and Hat1p are identified by brackets. Figure 4 Highly purified HatB3.1 contains Gcn5p and Ada3p in a high molecular weight complex. A) Flowchart outlining the partial purification of HatB3.1. B) Fluorograms of liquid HAT assays of the Superose 6 column fractionation of HatB3.1 activity (top 2 panels). Assays used either free histones or chromatin as substrate (as indicated). The relative elution of molecular weight standards is shown along the top, while the migration of histones H3 and H4 is indicated at the right. Column fraction aliquots (15 μL) were also resolved by SDS-PAGE and visualized by silver staining (bottom panel, protein ladder mobility is represented at right). Corresponding fraction numbers for both the fluorograms and silver stained gel are indicated along the bottom. C) Peak HatB3.1 containing Superose 6 fractions, as indicated at top of blots, were resolved by three identical 10% SDS gels, transferred to nitrocellulose and probed with the indicated antibodies (left of blots). Presence of Gcn5p, Ada2p and Ada3p in nuclear extract and/or column fractions was visualized via chemifluoresence. Relative migration of protein standards is shown on the right. Unbound material from the initial DEAE fractionation of the cytosolic and nuclear extracts was analyzed by cation exchange chromatography (carboxymethyl sepharose (CM)). While this fraction from the cytosolic extract appeared inactive, there were several additional HAT activities resolved from the nuclear extract (Figure 1C , data not shown). The presence of these activities in the DEAE flowthrough fraction is not simply due to column overloading as recycling the flowthrough fraction over the DEAE column a second time did not result in significant protein retention. Hence, these activities are chromatographically distinct from those that bind the DEAE resin. Two activities, centered on fractions 22 and 30, acetylated primarily histone H4. These appeared to be typical type A HAT's as they were active on both free histones and chromatin. A broad peak of histone H3-specific activity eluted from the CM column from fraction 10 through fraction 24 (with activity trailing through the remainder of the gradient). Comparison of the free histone and chromatin activities in these fractions suggested that this region of the gradient actually contained overlapping type A and type B activities. There was a distinct peak of free histone H3 acetylating activity centered on fractions 12 – 14 while acetylation of chromatin associated H3 peaked in fraction 16. Hence, the activity in fractions 12–14 is another candidate H3-specific type B HAT (labeled HatB3.3). HatB3.1 is specific for free histone H3 The fractions from the DEAE column that contained the activity that we have termed HatB3.1 modified not only free histone H3 but also free H4. In addition, a low level of nucleosomal H3 activity could also be seen in these fractions. To determine whether these activities were the result of a single enzyme complex or were due to multiple, overlapping complexes, these fractions were pooled, dialyzed and fractionated over a Mono-Q column (Figure 2 ). Inspection of the HAT activity profile of the fractions eluting from the Mono-Q column clearly demonstrated that multiple HAT activities overlapped with HatB3.1 during the initial fractionation of the nuclear extract. The HatB3.1 activity eluted from the Mono-Q column very early in the gradient and appeared to be highly specific for free histone H3. The second activity to elute from the Mono-Q column was specific for chromatin-associated histone H4. The third activity acetylated both free and nucleosomal histones H3, H2B and H4. These results indicated that the acetylation of multiple histones in the DEAE elution profile was the result of at least three overlapping activities and confirmed that HatB3.1 is a chromatographically distinct free histone H3-specific activity. Therefore, HatB3.1 was a good candidate for further characterization. HatB3.1 activity is dependent on GCN5 To gain insight into the identity of the catalytic subunit of HatB3.1, we constructed null mutants for each of the yeast HAT's that have demonstrated histone H3 activity as well as the known type B HAT, HAT1 . Isogenic deletion strains (Δ gcn5 , Δ sas2 , Δ sas3 and Δ hat1 ) were grown and protein extracts prepared exactly as for the wild type strain. Nuclear extracts were again fractionated via DEAE column chromatography and fractions of equivalent conductivity assayed for HAT activity as described above. Parallel comparison of the HAT activity profiles from each strain provided biochemical evidence for the dependency of specific histone acetyltransferase activities on the presence of a particular HAT catalytic subunit (compare Figure 3 with Figure 1B ). While subtle variations in observed specificity and intensity of HAT activity were seen throughout the profiles of the Δ sas2 and Δ sas3 strains, the robust H3 acetylation attributed to the HatB3.1 activity appeared unaffected by deletion of these enzymes (Figure 3 , lanes 26–34). Conversely, HatB3.1 activity was abolished in a Δ gcn5 strain (Figure 3 , lanes 26–34). In addition, the HatB3.2 activity also appeared to be absent in extracts from a gcn5 strain indicating that both of these putative type B HAT activities are dependent on Gcn5p. Additionally, the integrity, in a Δ gcn5 strain, of the overlapping free histone and chromatin (data not shown) activities in this region of the gradient confirmed that HatB3.1 was a chromatographically distinct HAT activity exhibiting specificity for free histone H3. Analysis of the activity profile from nuclear extracts derived from a Δ hat1 strain identified a broad peak of Hat1p dependent activity that spanned fractions ~22–34. Western blot analysis using antibodies against Hat1p and Hat2p confirmed the presence of these proteins in fractions from this region of the gradient from the wild type extract (data not shown). As with the Hat1p-dependent activity in cytosolic extracts, this activity also appeared to be specific for free histone H4. This result confirmed previous observations indicating that Hat1p is localized to both the cytoplasm and the nucleus [ 37 , 42 ]. In addition, the presence of an authentic type B HAT activity in our nuclear extracts validated our use of these extracts for the identification of putative histone H3-specific type B HAT activities. HatB3.1 activity is dependent on ADA3 but not ADA2 There are two proteins, Ada2p and Ada3p, that are components of all known Gcn5p-containing HAT complexes and that are required for the activity of these complexes [ 9 - 11 , 13 , 14 ]. To determine whether the HatB3.1 activity was also dependent on these proteins, nuclear extracts were prepared from isogenic Δ ada2 and Δ ada3 strains and the status of the HatB3.1 activity determined by DEAE chromatography. As shown in Figure 4 , the loss of ADA2 did not affect either the HatB3.1 or HatB3.2 activity but did cause a substantial increase in the free histone H4 specific activity that eluted late in the DEAE gradient. However, the HAT activity profile of the Δada3 extracts was strikingly similar to that seen for the gcn5 extracts with both the HatB3.1 and HatB3.2 activities absent. These results indicated that the HatB3.1 activity was dependent on ADA3 and that Ada2p is either not a component of the HatB3.1 activity or is not required for its stability. Partial purification of HatB3.1 To further characterize HatB3.1, this activity was purified through several chromatographic steps. The purification scheme is diagramed in Figure 5A . HatB3.1 containing fractions from the DEAE column were pooled, dialyzed to a conductivity similar to that of the loading buffer (DN(50)) and the dialysate applied to a cation exchange column (CM sepharose). HAT activity assays indicated that the HatB3.1 activity flowed through the CM sepharose column while bound proteins, resolved by a linear salt gradient, contained co-purifying HAT activities that acetylated both free and nucleosomal, H3 and H4 (data not shown). The presence of HatB3.1 in the CM sepharose flow through also confirmed that HatB3.1 and HatB3.3 were distinct activities. Figure 5 ADA3, but not ADA2, is essential for HatB3.1 activity. Nuclear extracts from isogenic Δada2 and Δada3 strains were prepared and fractionated as previously described for wild type and HAT deletion strains (Figures 1 and 3). Fluorograms reflecting HAT activity assays from fractions of equivalent conductivity from each strain, using free histones, are shown (fraction numbers are displayed at bottom [compare lanes to those in figure 3 as well]). Regions of HatB3.1 and HatB3.2 are highlighted by brackets. The proteins that flowed through the CM sepharose column were applied to a Mono-Q column and then eluted with a linear salt gradient. Fractions containing free histone H3 activity were pooled and concentrated by precipitation with 75% ammonium sulfate. The sample was then fractionated by size exclusion chromatography using a Superose 6 column. As seen in Figure 5B , the HatB3.1 activity peaked at fractions 48–50, indicating that a high molecular weight complex of ~500 kDa was responsible for this activity. The size of HatB3.1 remained stable throughout the course of purification as Superose 6 fractionation of the pooled HatB3.1 activity from the initial DEAE column displayed an identical mass (data not shown). The highly purified HatB3.1 retained its high degree of specificity for free histone versus chromatin substrates. There were also two peaks of free histone H4 specific activity seen in the Superose 6 elution profile. Western blot analysis indicated that Hat1p co-eluted with the low molecular weight species. The second peak of H4 activity co-purified with HatB3.1. Whether this acetylation of histone H4 was the result of a weak specificity of HatB3.1 for H4 or due to a second, co-eluting, HAT activity has not been resolved. Gcn5p and Ada3p, but not Ada2p, co-purified with the HatB3.1 activity The absence of HatB3.1 activity in extracts from a Δgcn5 strain indicated that HatB3.1 was dependent on Gcn5p, either indirectly via Gcn5p-mediated transcriptional regulation, or directly, as its catalytic subunit. While the HatB3.1 activity was highly purified relative to the initial nuclear extract, the peak Superose 6 fractions were still too complex to allow the definitive identification of specific bands that co-purified with the activity (Figure 5B ). Extensive efforts to purify HatB3.1 to homogeneity have been unsuccessful. To determine whether Gcn5p was likely to be functioning as the catalytic subunit of HatB3.1, fractions across the peak of HatB3.1 activity from the Superose 6 column were probed with anti-Gcn5p antibodies. As seen in Figure 5C , Gcn5p was present in the fractions containing the peak of HatB3.1 activity from the Superose 6 column. This result is consistent with direct association of Gcn5p with the HatB3.1 complex. Duplicate blots were probed with anti-Ada2p and anti-Ada3p antibodies to determine whether these proteins also co-fractionated with the HatB3.1 complex. As expected, both Ada2p and Ada3p are present in the nuclear extracts (Figure 5C ). However, while Ada3p precisely co-purified with Gcn5p and the peak of HatB3.1 activity, Ada2p did not appear to be associated with this complex. The absence of the Ada2p from the peak of HatB3.1 activity is consistent with the observation that HatB3.1 activity is independent of the ADA2 gene and suggests that Ada2p is not a component of the HatB3.1 complex. The absence of an Ada2p signal on the Western blot was not due to problems with sensitivity as comparison of the relative signals of Gcn5p, Ada2p and Ada3p in the nuclear extracts and Superose 6 fractions demonstrated that the presence of Ada2p in the Superose 6 fractions would have been readily apparent. While the HatB3.1 activity is enriched in the Superose 6 peak fractions relative to the original nuclear extract, the amount of Gcn5p and Ada3p present in these fractions is not enriched relative to the nuclear extract due to the fact that these proteins are components of at least five other histone acetyltransferase complexes. Hence, only a fraction of the Gcn5p and Ada3p present in the cell extracts was associated with HatB3.1. Discussion Considerable genetic and biochemical evidence indicates that, in most organisms, newly synthesized histone H3 is acetylated and that this acetylation plays a role in the de novo assembly of chromatin [ 28 , 30 , 31 , 43 - 48 ]. However, the enzymes responsible for this modification have remained elusive. In the present study we have comprehensively surveyed yeast extracts for putative, histone H3-specific, type B histone acetyltransferase activities. At least three candidate activities were identified, HatB3.1, HatB3.2 and HatB3.3. Further characterization of HatB3.1 indicated that this activity is a novel ~500 kDa HAT complex. In addition, our results suggest that Gcn5p and Ada3p are components of this complex but that, contrary to all previously isolated Gcn5p complexes, HatB3.1 is not associated with Ada2p. It does not appear that the HatB3.1 complex is merely an unstable form of one of the previously characterized Gcn5p-containing complexes as the apparent molecular weight of HatB3.1 did not vary during the course of its purification. There have been at least a dozen distinct HAT complexes identified in yeast [ 8 - 22 , 36 , 42 ]. Conservative analysis of our systematic fractionation of yeast cytosolic and nuclear extracts resolved 12 chromatographically separable activities. However, many of these activities were represented by rather broad peaks, likely to be composed of partially overlapping activities that may differentiate upon further purification (as seen in Figure 2 ). While many of the activities identified here may correspond to previously characterized complexes, it is difficult to determine these relationships, as our initial purification steps differ from those typically used for the isolation of other yeast HAT complexes. In particular, the purification of the SAGA, ADA, SLIK, SALSA, NuA3 and NuA4 complexes start from Ni 2+ -NTA agarose fractionated whole cell extracts, as these enzymes fortuitously bind to this resin [ 9 , 10 , 13 , 14 , 17 , 22 ]. Most histone acetyltransferases have substrate specificities that direct the acetylation of specific residues within one or more of the core histones [ 5 ]. However, these substrate specificities are not fixed and can be altered by the association of the catalytic subunits with different protein complexes [ 19 , 49 ]. The presence of numerous HAT complexes expands the repertoire of modification states that can be generated on the chromatin template. Therefore, as growing evidence indicates that specific cellular processes are associated with precise patterns of histone modification, the presence of multiple HAT complexes in cells is likely to be a reflection of the myriad events that must take place in the context of chromatin [ 50 ]. Despite the importance of histone acetylation in regulating chromatin structure, with the exception of Esa1p, none of the yeast histone acetyltransferases are essential for viability [ 51 , 52 ]. Also, the deletion of most HAT genes results in only relatively mild phenotypes [ 35 , 36 , 53 - 57 ]. One explanation for this observation is that some HATs perform functionally redundant roles in the cell [ 58 , 59 ]. Alternatively, examination of the HAT activity profiles of fractionated extracts derived from HAT deletion strains presented here suggests that there may be mechanisms that can compensate for the lack of one histone acetyltransferase by increasing the activity of other HAT complexes. For example, in a Δ sas2 strain, there is a dramatic increase in an activity present in nuclear extracts that acetylates free histone H4 and which elutes from a DEAE column at a salt concentration similar to that of the nuclear form of Hat1p (Figure 3 ). In addition, deletion of the HAT1 gene causes a large increase in an activity that is coincident with the HatB3.1 activity. These results suggest the possibility that cells may monitor levels of histone modification and adjust specific HAT activities accordingly. HatB3.1 is the third native HAT complex identified from yeast that is only capable of acetylating free histones [ 15 , 36 ]. In addition to the histone H4 specific Hat1p/Hat2p complex, the SAS complex, composed of Sas2p, Sas4p and Sas5p, was recently shown to acetylate free histones H3 and H4. The potential classification of the SAS complex as a type B HAT is supported by the fact that the SAS complex has also been shown to be physically associated with the histone deposition proteins Cac1p and Asf1p [ 16 , 60 , 61 ]. However, the specific target of SAS complex acetylation, histone H4 lysine 16, has not been found to be acetylated in the pool of newly synthesized histones in any organism [ 15 , 30 ]. Therefore, it remains to be determined whether the SAS complex participates in the acetylation of newly synthesized histones H3 and H4 prior to histone deposition or whether it is involved in the post-assembly modification of histones. Gcn5p is the prototypical type A histone acetyltransferase. While rGcn5p is only capable of acetylating free histones under most experimental conditions, it has been identified as the catalytic subunit of five native HAT complexes that acetylate nucleosomal substrates (SAGA, ADA, A2, SLIK and SALSA) [ 9 - 11 , 13 , 14 , 31 , 62 ]. The most straightforward interpretation of the dependence of the HatB3.1 activity on a functional GCN5 gene and the co-elution of Gcn5p with highly purified HatB3.1 is that Gcn5p is also the catalytic subunit of HatB3.1. In the context of the type A HAT complexes, the Ada2p, Ada3p and TAF II 68 proteins have been shown to be important for expanding the substrate specificity of Gcn5p to allow for the acetylation of nucleosomal histones [ 49 , 63 - 68 ]. Hence, the ability of Gcn5p to acetylate histones in chromatin is a property that must be conferred upon it by association with other proteins. The identification of Gcn5p as a component of a type B histone acetyltransferase activity suggests that classification as either type A or type B may not be an inherent property of an enzyme but, rather, may be a function of the association of the enzyme with specific accessory factors. Several properties of HatB3.1 indicate that it is distinct from previously identified Gcn5p-containing complexes. First, HatB3.1 is the only native Gcn5p-containing complex that does not have detectable activity on nucleosomal substrates. Second, the apparent molecular weight of HatB3.1 (~500 kDa), as determined by size exclusion chromatography, is much lower than that of the SAGA, ADA, SALSA and SLIK complexes but is similar to that reported for the A2 complex [ 9 , 13 , 14 , 64 ]. However, unlike HatB3.1, the A2 complex is both dependent upon, and co-purifies with, Ada2p. These results clearly distinguish HatB3.1 as a novel Gcn5p-containing HAT complex [ 64 ]. Ada2p, Ada3p and Gcn5p form a module that provides the catalytic activity to their associated type A HAT complexes [ 5 ]. In these complexes, there does not appear to be any direct physical interaction between Ada3p and Gcn5p but, rather, their association is mediated through Ada2p [ 55 , 67 , 69 , 70 ]. The absence of Ada2p from the HatB3.1 activity suggests that Ada3p and Gcn5p can directly associate under certain circumstances or that another subunit(s) of the HatB3.1 complex can replace the function of Ada2p in bridging the interaction of Ada3p and Gcn5p. The identification of a Gcn5p-containing complex that is independent of Ada2p also suggests that there are cellular processes, such as histone deposition, that are influenced by Gcn5p (and Ada3p) but that do not require Ada2p. However, with the exception of the specific synthetic lethality seen with Δ gcn5 Δ sas3 mutants, deletions of the GCN5 , ADA2 and ADA3 genes have similar in vivo consequences [ 22 , 59 , 71 , 72 ]. The absence of phenotypes unique to Δ gcn5 and Δ ada3 mutants may be the result of the complex functional redundancies observed in the assembly of chromatin. For example, Δ hat1 and Δ hat2 mutants only display phenotypes when combined with mutations in multiple lysine residues in the histone H3 NH 2 -terminal tail [ 45 , 46 ]. Uncovering these redundancies and deciphering the potential role of Gcn5p in the acetylation of newly synthesized histones is likely to require the characterization of the complete set of complexes that display type B histone acetyltransferase activity. Conclusions In conclusion, we have fractionated yeast cytoplasmic and nuclear extracts and resolved several putative histone H3-specific type B histone acetyltransferase activities. One of these activities, HatB3.1, is highly specific for histone H3 that is free in solution. A combination of genetic and biochemical evidence indicates that HatB3.1 is a novel complex that depends on GCN5 and ADA3 but that is independent of ADA2 . Methods Yeast strains UCC1111 was used as the wild type yeast strain that serves as the genetic background for all deletion strains [ 45 ]. Null mutants for GCN5 , SAS3 , SAS2 , ADA2 , ADA3 and HAT1 were constructed using PCR-mediated gene disruption with the HIS3 reporter gene [ 73 ]. Extract preparation Cells were grown to mid-log phase in 1% yeast extract, 2% peptone, 2% glucose and 50 μg/mL ampicillin at 30°C. Cells were harvested at 4000 × g, 10', 4°C and total grams of cells recorded. All buffers contain 1.0 mM PMSF. Spheroplasts were prepared essentially as described previously using 0.25 mg of Zymolyase (U.S. Biologicals) per gram of cells for spheroplasting [ 74 ]. Spheroplasts were burst in 0.5 mL/g cells Lysis Buffer (18% Ficoll 400, 10 mM HEPES [pH 6.0]) followed by dilution in 1.0 mL/g cells Buffer A (50 mM NaCl, 1.0 mM MgCl 2 , 10 mM HEPES [pH 6.0]). Supernatant from a 1500 × g, 15' spin at 4°C was retained as a cytosolic extract. Pelleted material was washed once with Buffer A then resuspended in DN(1000) (DN buffers contain 25 mM Tris [pH 7.5], 10% glycerol, 0.1 mM EDTA and mM [NaCl] listed in parentheses). Supernatant from another 1500 × g spin as above yielded the nuclear extract. This extract was dialyzed O/N at 4°C into DN(0) to a conductivity similar to that of the cytosolic extract. Extracts were cleared by high speed centrifugation (~30,000 × g) prior to their chromatographic fractionation. Extract fractionation All columns were equilibrated with and run using DN Buffers. HPLC (ÄKTA purifier – Pharmacia) was employed for all column runs. Anion and cation exchange chromatography DEAE – Cleared extracts were loaded onto a HiPrep 16/10 DEAE FF column (Pharmacia). Following a 5 C.V. wash with DN(50), proteins were eluted with a linear, 20 C.V., salt gradient from 50 mM to 1.0 M NaCl. A flow rate of 1.0 mL/min. was used and 3.0 mL fractions were collected. CM – Either pooled peak fractions, dialyzed into DN(0) until at similar conductivity as DN(50) start buffer, or Flowthrough from the DEAE were loaded onto a HiPrep 16/10 CM FF column (Pharmacia). The column was washed and proteins eluted as described above. Mono Q – The flowthrough fraction from the CM column was loaded onto a Mono Q HR 5/5 column (Pharmacia). Following a 5 C.V. wash with DN(50), a 20 C.V., linear, salt gradient was employed as above and 0.5 mL fractions were collected. Ammonium sulfate precipitation Peak fractions of HatB3.1 activity from the Mono Q column were pooled and brought to 75% (NH 4 ) 2 SO 4 (0.516 g/mL) over 30' at 4°C. Following an additional 30' equilibration period at 4°C, precipitated protein was pelleted (10,000 × g, 10', 4°C) and resuspended in 300 μL cold, DN(0). Gel filtration chromatography A 250 μL aliquot of resuspended ammonium sulfate precipitate was loaded onto a Superose 6 HR 10/30 column (Pharmacia). The column was equilibrated with and run in DN(350) at a flow rate of 0.3 mL/min. and 0.25 mL fractions were collected. Molecular weight standards (Sigma, MW-GF-1000) were run using the same parameters and 24 μL aliquots of every other fraction run on a 10% SDS-polyacrylamide gel. The elution profile of the MW standards was determined by protein visualization via Coomassie blue staining. Liquid HAT assays Chicken erythrocyte core histones and chromatin were isolated as previously described [ 75 , 76 ]. Typically 10 μL aliquots of column fractions were incubated with 0.1 μM 3 H-Acetyl Coenzyme A (5.50 Ci/mmol, Pharmacia) and ~1.0 mg/mL core histones or chromatin in a final volume of 100 μL at 1X [DN(75)]. 50 μL of each reaction was analyzed for HAT activity via liquid scintillation counting. The remaining assay mixture was brought to 1X [SDS Load Dye] to stop the reaction. In general, aliquots (24 μL) of these remaining assay mixtures were run on 18% SDS-polyacrylamide gels to resolve the histones. Gels were incubated in Autofluor (National Diagnostics), dried down and acetylated histone species visualized via fluorography. Western blot and gel analysis Superose 6 fractions exhibiting HAT B3 activity, as determined above, were run on 10% SDS-polyacrylamide gels and proteins were either visualized by silver staining or transferred to nitrocellulose using a semi-dry transfer apparatus (Biorad). Blots were processed following standard procedures. Goat, polyclonal antibodies against Gcn5p, Ada2p and Ada3p (Santa Cruz Biotechnology, Inc.) were used at 1:100 dilutions in 5% Milk/TBS-T. Donkey, HRP-labeled Anti-Goat IgG secondary antibody (Santa Cruz Biotechnology, Inc.) was used at 1:2500 dilution followed by detection with ECL+Plus (Pharmacia) and visualization via phosphoimager (STORM 860, Pharmacia). Authors' contributions A.R.S. performed all of the experiments presented here and drafted the manuscript. M.R.P. directed the project and edited the manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC509278.xml
509250	Evaluation of reporting timeliness of public health surveillance systems for infectious diseases	Background Timeliness is a key performance measure of public health surveillance systems. Timeliness can vary by disease, intended use of the data, and public health system level. Studies were reviewed to describe methods used to evaluate timeliness and the reporting timeliness of National Notifiable Diseases Surveillance System (NNDSS) data was evaluated to determine if this system could support timely notification and state response to multistate outbreaks. Methods Published papers that quantitatively measured timeliness of infectious disease surveillance systems operating in the U.S. were reviewed. Median reporting timeliness lags were computed for selected nationally notifiable infectious diseases based on a state-assigned week number and various date types. The percentage of cases reported within the estimated incubation periods for each disease was also computed. Results Few studies have published quantitative measures of reporting timeliness; these studies do not evaluate timeliness in a standard manner. When timeliness of NNDSS data was evaluated, the median national reporting delay, based on date of disease onset, ranged from 12 days for meningococcal disease to 40 days for pertussis. Diseases with the longer incubation periods tended to have a higher percentage of cases reported within its incubation period. For acute hepatitis A virus infection, which had the longest incubation period of the diseases studied, more than 60% of cases were reported within one incubation period for each date type reported. For cryptosporidiosis, Escherichia coli O157:H7 infection, meningococcal disease, salmonellosis, and shigellosis, less than 40% of cases were reported within one incubation period for each reported date type. Conclusion Published evaluations of infectious disease surveillance reporting timeliness are few in number and are not comparable. A more standardized approach for evaluating and describing surveillance system timeliness should be considered; a recommended methodology is presented. Our analysis of NNDSS reporting timeliness indicated that among the conditions evaluated (except for acute hepatitis A infection), the long reporting lag and the variability across states limits the usefulness of NNDSS data and aberration detection analysis of those data for identification of and timely response to multistate outbreaks. Further evaluation of the factors that contribute to NNDSS reporting timeliness is warranted.	Background Public health surveillance is defined as the "ongoing systematic collection, analysis, and interpretation of data essential to the planning, implementation, and evaluation of public health practice, closely integrated with the timely dissemination of these data to those who need to know"[ 1 ]. Reasons for conducting public health surveillance can include the need to assess the health status of a population, establish public health priorities, and reduce the burden of disease in a population by appropriately targeting effective disease prevention and control activities [ 2 ]. Timeliness is a key surveillance system metric and should be periodically evaluated [ 3 , 4 ] because it can reflect the time delay between any number of response steps in the public health surveillance process. Surveillance system timeliness depends on a number of factors and its assessment should include a consideration of how the data will be used and the nature of the condition under surveillance (e.g., for infectious diseases, this includes the communicability of the disease) [ 3 ]. If the data are to be used to implement immediate disease control and prevention activities for infectious diseases that are acute, severe, and highly transmissible, timeliness is critical. Timeliness requirements for a surveillance system might vary by different levels of public health system (e.g., local, state, or national), on the basis of the intended uses of the surveillance data at that level (Table 1 ). For example, timely data are needed within a state for identifying cases or clusters of disease that will prompt an immediate public health response. Timely national surveillance data aggregated from a number of jurisdictions may be used for identifying multistate outbreaks or disease clusters and enable the federal public health system to assist the states in performing and coordinating their prevention and control activities. In reportable disease surveillance systems, health care providers and diagnostic laboratories usually report information regarding persons with notifiable conditions to the local public health system. Then, reporting proceeds in a hierarchical fashion to the state and then to the national level. Health care provider and public health system actions at each successive level of the reporting hierarchy contribute to reporting timeliness delays at the national level. Table 1 Potential uses of infectious disease surveillance data, by level of the public health system Intended Uses Used at which level(s) of the public health system?* Identify individual cases or clusters in a jurisdiction to prompt intervention or prevention activities Local, State (National) Identify multi-state disease outbreaks or clusters. State, National Monitor trends to assess the public health impact of the condition under surveillance. State, National (Local) Demonstrate the need for public health intervention programs and resources, as well as allocate resources. State, National (Local) Monitor effectiveness of prevention, control, and intervention activities. State, National (Local) Formulate hypotheses for further study. National (State) Public health system level in parentheses represents secondary use of the data for that purpose. State and national surveillance processes Before data can be used for public health action, health-related data must be collected by the public health system, analyzed, and disseminated to those responsible for taking action (Figure 1 ). Within a state (Steps 1–7), the public health system can use surveillance data for a number of purposes, including outbreak detection and intervention planning and implementation (Table 1 ). The number and sequence of actions a state conducts before reporting data to the national public health system might vary by state, depending on state policies and protocols (Figure 1 ). For example, for nationally notifiable infectious disease reporting, CDC recommends that states report as soon as they first receive information about a suspect, probable, or confirmed case. However, some states only report confirmed cases, which usually requires laboratory confirmation, and decreases reporting timeliness at the national level. Figure 1 Sequence of actions needed to gather and use health-related information for public health purposes Each week, states and the U.S. territories report case information on persons suspected of having or diagnosed with a nationally notifiable infectious disease to the Nationally Notifiable Diseases Surveillance System (NNDSS), maintained by the Centers for Disease Control and Prevention (CDC) [ 5 ]. A nationally notifiable disease is one for which "regular, frequent, and timely information regarding individual cases is considered necessary for prevention and control of the disease" [ 6 ]. At the national level, NNDSS data are used for monitoring trends, program planning, evaluation, policy development, research, and monitoring the effectiveness of prevention and control activities. Although NNDSS reporting timeliness for these long-range goals and objectives is not critical, the threat of terrorism prompted consideration of whether NNDSS could be enhanced in the future to support public health response for either naturally occurring diseases or terrorism preparedness and response efforts. Therefore, the timeliness of NNDSS data was evaluated to determine if NNDSS could support timely notification and state response to multistate outbreaks. To provide a context for the evaluation of NNDSS timeliness, published studies reporting timeliness measures for infectious disease surveillance systems in the United States were reviewed. Methods Literature review Infectious disease surveillance evaluation studies reporting timeliness measures that were published between January 1970 and March 2003 in biomedical and public health literature were reviewed. English-language papers were identified by using the Medline database (U.S. National Library of Medicine). The search strategy used various combinations of the following key words "timeliness," "reporting delay," "time delay," "lag time," "disease surveillance," "disease outbreaks," "communicable diseases," and "infectious diseases." Reference lists of the studies identified through the Medline search and studies citing CDC's surveillance evaluation guidelines were also reviewed [ 3 , 7 ] Reports were included if they evaluated a public health surveillance system operating in the United States and provided a quantitative estimate of disease-specific timeliness (e.g., interval in days). Studies without quantitative timeliness estimates or that reported a quantitative estimate for a group of infectious diseases (versus a disease-specific estimate) were excluded. In addition, studies describing the timeliness of syndromic surveillance systems were excluded. Information abstracted for the review included the disease(s) under surveillance, the geographic area and time period studied, the purpose of the surveillance evaluation, the surveillance time interval measured, the surveillance processes or actions (steps in Figure 1 ) covered within the measured time interval, the timeliness measure, and the study's assessment of whether surveillance data timeliness met the surveillance goals. NNDSS timeliness Information available for assessing NNDSS reporting timeliness includes the Morbidity and Mortality Weekly Report [ MMWR ] week number the state assigns to each case and one of the following earliest known dates associated with the incidence of this disease (earliest known date) from the following list of hierarchical date types: onset date, diagnosis date, date of laboratory result, or date of first report to the community health system. National reporting delay was calculated as the difference in days between the midpoint of the MMWR week and the earliest known date reported in association with the case. This time interval reflects various state-specific surveillance intervals in the surveillance process that occur between the occurrence of a health event and the reporting of that health event to NNDSS, but at a minimum it includes Intervals 1–4 (Figure 1 ). National median reporting timeliness was calculated overall for the years 1999–2001, for each disease in our study, by date type and state, and across all states. Median reporting delay was calculated using Proc means in SAS version 8 software for Windows (SAS Institute, Inc., Cary, North Carolina). To assess whether analysis of NNDSS data could support the timely identification of multistate outbreaks at the national level, the percentage of NNDSS cases reports reported within one to two incubation periods for each of the diseases was determined. Incubation periods were used as a surrogate measure for period of communicability which is critical to consider when implementing effective, disease-specific prevention and control measures. For this analysis, estimated incubation periods were used for the seven nationally notifiable infectious diseases selected for this study: 7 days for cryptosporidiosis, 4 days for Escherichia coli O157:H7 ( E. coli ), 30 days for acute hepatitis A virus infection, 4 days for meningococcal disease, 20 days for pertussis, 1.5 days for salmonellosis, and 3 days for shigellosis [ 8 ]. These diseases were selected because they were confirmed on the basis of laboratory criteria; they have the potential to occur in epidemics; they were designated nationally notifiable five years or more before the study period began; and the magnitude of reported disease incidence supported this analysis. Only finalized case-specific data reported from U.S. states and two autonomous reporting entities (New York City and Washington D.C., referred to as states, hereafter) that designated the reported condition as notifiable (reportable by law or regulation) and that met NNDSS publication criteria [ 9 ] were included in the analysis. Data were analyzed for MMWR years 1999, 2000, and 2001. Results Literature review Eight papers were identified that met the inclusion criteria for this study (Table 2 - see Additional file: 1 ) [ 10 - 17 ]. Seven of the eight papers met the inclusion criteria resulting from the literature review; an additional paper was identified from the review of reference lists of studies identified through the Medline search and studies citing CDC's evaluation guidelines [ 3 , 7 ]. Three of the eight papers in this study assessed national reporting timeliness; the remaining five papers focused on local or state reporting timeliness. The studies of national reporting timeliness focused on the following diseases: acquired immunodeficiency syndrome (AIDS) [ 17 ]; Neisseria meningitidis and Haemophilus influenzae infections [ 16 ]; and shigellosis, salmonellosis, hepatitis A, and bacterial meningitis [ 11 ]. The studies of local or state reporting timeliness analyzed data for AIDS [ 14 , 15 ], tuberculosis [ 13 ], influenza-like illness [ 10 ], and meningococcal disease [ 12 ]. In seven of the eight papers, timeliness was calculated as the median reporting delay between the date of disease occurrence (e.g., disease onset date, diagnosis date, or laboratory result date) and the date the public health system was notified or as the proportion of cases reported to the public health system in a specific time interval. In one study [ 10 ], epidemic curves were compared for two influenza surveillance systems and timeliness was assessed as the time interval between the epidemic peaks noted in each system. In addition, two studies described the factors associated with delayed reporting [ 13 , 15 ]. Seven of the eight studies addressed whether the calculated timeliness measure met the needs of the surveillance process being evaluated [ 10 , 12 - 17 ]. Measured timeliness was compared with recommended reporting timeliness in two papers – a national recommendation for local tuberculosis reporting timeliness [ 13 ] and a state mandate for reporting meningococcal disease cases to local public health [ 12 ]. The adequacy of the timeliness measure for the surveillance purpose was also assessed in other ways: 1) by comparing the timeliness of the same surveillance interval in an AIDS surveillance system before and after a major revision in the AIDS surveillance case definition [ 17 ], 2) by comparing the timeliness of the same surveillance interval across an active and a passive AIDS surveillance system [ 14 ], 3) by comparing outbreak detection abilities of an existing sentinel health care provider-based surveillance system for influenza-like illness with a new school-based system monitoring illness absenteeism [ 10 ], 4) by assessing whether reporting timeliness for Neisseria meningitidis and Haemophilus influenzae was adequate to initiate a rapid public health response [ 16 ], and 5) by comparing the timeliness of reporting by whether the case-patient's initial AIDS-defining condition was included in the 1997 or 1993 AIDS surveillance case definition [ 15 ]. The reporting timeliness of AIDS and bacterial meningitis (including meningococcal disease) surveillance systems were more frequently assessed than those for other infectious diseases. The AIDS reporting timeliness studies indicate that local and national AIDS reporting timeliness meets the goals of the AIDS surveillance systems monitoring trends, targeting prevention programs, estimating needs for medical and social services, and allocating resources [ 14 , 15 , 17 ]. Timeliness of AIDS surveillance improved after the revision of the AIDS surveillance case definition in 1993 [ 14 , 15 , 17 ]. Evaluation of Tennessee's Neisseria meningitidis infection surveillance system for 1989–1992 indicated that the lengthy reporting interval limited the usefulness of the system for supporting rapid response for control and prevention [ 16 ]. In contrast, a 1991 evaluation of New York State's meningococcal surveillance system indicated that the majority of cases (66%) were being reported within the recommended time frame (i.e., within one day of the diagnosis to ensure chemoprophylaxis for exposed persons) and therefore, supported prevention and control efforts [ 12 ]. In addition, on the basis of nationally notifiable infectious disease data from 1987, bacterial meningitis had the shortest reporting timeliness (median 20 days) of the other infectious diseases studied [ 11 ]. The definition of reference dates used in the timeliness evaluations varied. The initial date associated with the case varied among date of disease onset, date of diagnosis, and date of positive culture result. The ending date for the timeliness studies evaluated was the date the case report was received by the public health system, whether at the local, state, or national level. This time period corresponds to the sum of Intervals 1 and 2 or Interval 2 alone for local or state timeliness studies (Figure 1 ). For national evaluations of timeliness, the time period assessed was the sum of Intervals 1, 2, 3, and 4 or only Intervals 2, 3, and 4 (with or without inclusion of Intervals 5, 6, 7, and 8, dependent upon state protocol). NNDSS timeliness For MMWR years 1999–2001, a total of 9,276 cases of cryptosporidiosis, 12,332 cases of E. coli O157:H7 infection, 41,058 cases of hepatitis A virus acute infection, 7,090 cases of meningococcal disease, 22,735 cases of pertussis, 120,688 cases of salmonellosis, and 60,693 cases of shigellosis and were reported to NNDSS. Of those, 7,079 (76.3%) cryptosporidiosis case reports, 9,674 (78.4%) case reports of E. coli O157:H7 infection, 32,953 (80.3%) case reports of acute hepatitis A virus infection, 5,580 (78.7%) case reports of meningococcal disease, 19,904 (87.5%) case reports of pertussis, 84,746 (70.2%) case reports of salmonellosis, and 41,643 (68.6%) case reports of shigellosis were eligible for analysis. A total of 72,293 (26.4%) case reports were excluded for one or more of the following reasons: reported as a summary or aggregate record in which individual cases may have different event dates (20,194 cases), unknown or missing date types (20,019 cases), date type coded to MMWR report date (11,851 cases), and calculated reporting lag had a value of zero (indicating the event date and midpoint of the MMWR week matched) or had a negative value (indicating the event date was later than the mid-point of the MMWR week [67,557 cases]). Timeliness of reporting varied by disease and date type (Table 3 ). For cases reported with a disease onset date, the median reporting delay across all reporting states varied from 12 days for meningococcal disease to 40 days for pertussis. For cases reported with a laboratory result date, median reporting delay varied from 10 days for both meningococcal disease and shigellosis to 19 days for pertussis. There was also substantial variation in state-specific median reporting delays for each disease (Table 3 ). For example, for meningococcal disease cases reported with a laboratory result date, state-specific median reporting delay varied from a median of 2 days in one state to 117 days in another. Table 3 Timeliness of reporting of selected nationally notifiable infectious diseases, by date type, NNDSS, 1999–2001 Date type (Intervals from Figure 1) Disease (incubation period), Characteristic Disease onset (Intervals 1,2,3,4) Diagnosis date (Intervals #2,3,4) Lab result date (Intervals #2,3,4) Date of first report to the community health system (Intervals #3,4) Cryptosporidiosis (7 day incubation period) Median time interval (days) 22 14 13 26 State-specific reporting range a 2–149 1–73 2–58 1–53 No. cases 4,130 956 1,825 168 No. states 44 24 41 15 % within 1, 2 incubation periods b 24%, 39% 37%, 50% 35%, 54% 19%, 33% E. Coli O157:H7 (4 day incubation period) Median time interval (days) 17 21 11 15 State-specific reporting range a 2–81 2–41 1–53 1–49 No. cases 6,891 473 2,206 104 No. states 48 22 39 14 % within 1, 2 incubation periods b 15%, 27% 13%, 25% 19%, 39% 21%, 33% Hepatitis A, acute (30 day incubation period) Median time interval (days) 23 18 12 12 State-specific reporting range a 2–54 2–80 2–29,231 + 1–126 No. cases 21,570 4,394 6,695 294 No. states 49 36 39 14 % within 1, 2 incubation periods b 62%, 84% 67%, 83% 82%, 94% 79%, 91% Meningococcal disease (4 day incubation period) Median time interval (days) 12 13 10 10 State-specific reporting range a 2–56 1–54 2–117 4–62 No. cases 3,804 450 1,255 71 No. states 50 30 39 7 % within 1, 2 incubation periods b 23%, 39% 26%, 40% 25%, 44% 31%, 42% Pertussis (20 day incubation period) Median time interval (days) 40 31 19 23 State-specific reporting range a 2–124 1–106 2–190 2–48 No. cases 18,750 289 758 107 No. states 50 26 34 15 % within 1, 2 incubation periods b 24%, 50% 34%, 60% 53%, 78% 45%, 68% Salmonellosis (1.5 day incubation period) Median time interval (days) 17 7 12 16 State-specific reporting range a 2–44 1–54 2–61 1–27 No. cases 49,659 5,558 28,172 1,357 No. states 47 35 42 28 % within 1, 2 incubation periods b 4%, 13% 17%, 43% 6%, 17% 7%, 19% Shigellosis (3 day incubation period) Median time interval (days) 15 10 10 9 State-specific reporting range a 2–43 1–51 2–34 1–26 No. cases 26,635 2,850 11,603 555 No. states 46 28 41 17 % within 1, 2 incubation periods b 15%, 22% 33%, 39% 22%, 35% 29%, 41% *Source: Control of Communicable Diseases Manual 17 th Edition [8]. + The maximum state-specific median reporting delay for this disease and date type is from a state that reported 19 cases having event years 1919 or 1920. Excluding these cases as data entry errors, the maximum state-specific median reporting delay is 78 days. a State-specific median reporting range (minimum, maximum) in days b % of cases reported within 1 and 2 incubation periods, respectively For the same date type, NNDSS diseases with longest incubation periods tended to have a higher percentage of cases reported within one or two incubation periods than NNDSS diseases with shorter incubation periods (Table 3 ). For example, for acute hepatitis A virus infection, which had the longest incubation period of all the study diseases, more than 60% of cases were reported within one incubation period, for each date type reported. For all other diseases except pertussis, less than 40% of cases were reported within one incubation period for each reported date type. For pertussis, the percentage of cases reported within one incubation period varied from 24% for reports with disease onset date to 53% for case reports with laboratory result dates. In addition, state-specific percentage of cases reported within one or two incubation periods varied for a given disease and date type (data not shown). Comparison of NNDSS timeliness and literature review results The 1999–2001 NNDSS meningococcal disease median reporting interval between date of disease onset and date of report to CDC in this study was 8 days shorter than a previous study reported [ 11 ] using 1987 notifiable disease data for bacterial meningitis (median 20 days); and, the meningococcal disease median reporting delay was 9 days shorter in this study than in a previous study [ 16 ] using Tennessee's data for the years 1989–1992 for Neisseria meningitidis infection (median 21 days). In addition, the median reporting delay between disease onset and the date of report to CDC was shorter in this study than in a previous study (which used 1987 notifiable disease data) by 10 days for hepatitis A, 5 days for salmonellosis, and 8 days for shigellosis [ 11 ]. Discussion Few published studies evaluating surveillance systems presented timeliness measures. When timeliness was evaluated, standard methods were not used. Information collected by public health surveillance systems should support the quantitative assessment of timeliness by various steps in the pubic health surveillance process. Public health programs should periodically assess timeliness of specific steps in the surveillance system process to ensure that the objectives of the surveillance system are being met. A more structured approach to describing timeliness studies should be considered. Published papers describing local or state surveillance system reporting timeliness generally do not explicitly describe the surveillance system processes contributing to the timeliness measure, such as processing and analyzing the data or implementing a public health action before data are reported from a state to CDC. To facilitate future comparisons of reporting timeliness across jurisdictions, studies should include an explicit description of the public health surveillance reporting process and the surveillance process interval being measured. Additionally, surveillance information systems must support the collection of appropriate reference dates to allow the assessment of the timeliness of specific surveillance processes. A more structured approach to describing timeliness studies could include a description of the following characteristics: 1) the level of the public health system being assessed (e.g., local, state, or national), 2) the purpose of the surveillance evaluation, 3) goals of the surveillance system, 4) the surveillance interval being measured and a description of the reference dates that define the upper and lower boundaries of the surveillance interval, 5) the surveillance steps (processes or activities) that contribute to the surveillance interval being measured, 6) whether the measured timeliness met the needs of the surveillance step being evaluated, and 7) whether the timeliness met the goals of the surveillance system. No single timeliness measure will achieve the purpose of all evaluations or meet all the goals of the surveillance system. In addition, if the goal of the surveillance evaluation is to identify ways to improve timeliness, the analysis should identify factors associated with delayed reporting, such as the role of specific case ascertainment sources. The 1999–2001 national notifiable diseases data were timely enough to support the following surveillance objectives: monitoring trends over time, informing allocation of public health resources, monitoring the effectiveness of disease control, identifying high risk populations, and testing hypotheses. If NNDSS data are to be used to support timely identification of and response to multistate outbreaks at the national level, the timeliness of reporting needs to be enhanced for all diseases, but especially for diseases with the shortest incubation periods (e.g., cryptosporidiosis, E. coli O157:H7, meningococcal disease, salmonellosis, and shigellosis). Until reporting timeliness is enhanced, the application of aberration detection analytic methods to NNDSS data to aid in the identification of changes in disease reporting that may indicate a multistate outbreak in time to alert states for the purposes of disease control and prevention may be of limited use. Future work to improve reporting timeliness will need to address the substantial variation across states. As states enhance their reporting mechanisms with the use of automated electronic laboratory reporting systems [ 18 ], there may be less variation in state-specific reporting timeliness, but this should be assessed. NNDSS timeliness improved compared to timeliness of notifiable infectious diseases measured in previous reports [ 11 , 16 ]. However, the methods or variables used in these analyses were different. A few factors may have contributed to improvements in timeliness seen in this study. Since 1992, states have been routinely transmitting electronic case-specific records intended to improve reporting procedures and protocols. In addition, the use of automated electronic laboratory reporting to enhance infectious disease case reporting may have contributed to increased timeliness. Our study findings are subject to several limitations. The variables available for assessing NNDSS reporting timeliness are based on the MMWR week numbers that are assigned by states and the earliest known date reported in association with the case. While these variables might provide an estimate of national reporting timeliness, NNDSS data do not include a fixed date defining when a case report was initially transmitted to CDC or received at CDC, which would provide a more precise measure of national reporting timeliness. NNDSS data management protocols should be modified to permit direct calculation of national reporting timeliness. If the ability to support outbreak detection at the national level using NNDSS data is generally viewed as an important and sustainable enhancement for the NNDSS, states and CDC programs should facilitate reporting that more closely approximates real-time and define reporting protocols and data requirements to ensure that reporting timeliness can be improved and accurately monitored. The current NNDSS practice of weekly reporting and data processing limits reporting timeliness to CDC. Lastly, 72,293 (26.4%) cases were excluded from our analysis because the information contained in the database would not permit calculation of timeliness and this exclusion may have resulted in our study results either falsely overestimating or underestimating the magnitude of NNDSS reporting lags. The reporting timeliness variations across states may result from different reporting protocols in the states (e.g., centralized versus distributed reporting within the state's public health system) or from variations in how states assign MMWR week numbers. Other factors that might have contributed to reporting delay in our study included: the patient's recognition of symptoms; the patient's acquisition of medical care; the use of confirmatory laboratory testing; reporting by the health care provider or the laboratory to the local, county, or state public health authority; the volume of cases identified in the state; case follow-up investigations to verify the case report or to collect additional case information; periods of decreased surveillance system activity due to variable staffing levels; computer system down-time for maintenance, upgrades, or new application development; and data processing routines, such as data validation or error checking. Following a structured approach to evaluation of timeliness by specifying the surveillance objectives and the process(es) being measured may allow better definition of the factors that contribute to reporting delay. It was beyond the scope of this study to assess how these factors contribute to NNDSS reporting timeliness. In addition to reporting timeliness, other surveillance system attributes are important to assess (e.g., completeness of reporting). Completeness of notifiable infectious diseases reporting in the United States varies from 9% to 99% [ 7 ]. Six of the eight papers reviewed for this study assessed completeness of reporting [ 12 - 17 ]. One paper [ 14 ] noted that although the timeliness of the AIDS passive and active surveillance systems were comparable, the completeness of the active AIDS reporting system far exceeded the reporting completeness for the passive system. This highlights the importance of evaluating completeness and timeliness and other surveillance system attributes concurrently, before contemplating any changes to a surveillance system based on the assessment of a single attribute. To improve public health surveillance infrastructure and performance in the United States, CDC and local and state health agencies are integrating a number of public health surveillance systems monitoring infectious diseases in the United States, including the NNDSS, into the National Electronic Disease Surveillance System (NEDSS) [ 19 , 20 ]. NEDSS outlines a standards-based approach to disease surveillance and intends to connect public health surveillance to the clinical information systems infrastructure. As a result, NEDSS promises to improve the accuracy, completeness, and timeliness of disease reporting to state and local health departments and CDC. Conclusions To facilitate comparisons of surveillance system timeliness studies across jurisdictions or health conditions, a more standardized approach to describing timeliness studies is warranted. Public health surveillance systems should ensure that timeliness can be measured for specific surveillance system processes and in the context of the goals of surveillance. In addition, when timeliness is being measured, it is important to be explicit about how it is being measured. Our analysis of NNDSS reporting timeliness suggests that current acute hepatitis A infection reporting timeliness may be sufficient to support a timely public health response in the event of a multistate outbreak. However, for the other conditions evaluated, the long reporting lag and the variability across states limits the usefulness of NNDSS data and aberration detection analysis of those data for identification of and response to multistate outbreaks. The NNDSS timeliness data presented in this paper represents a baseline against which timeliness can be measured in the future. Further study is needed to identify the major sources of reporting delay and to assess how NNDSS reporting timeliness may be improved for the timely detection of cases and disease clusters. Competing interests None declared. Author's contributions Both authors contributed equally to project conception and write-up of the manuscript. RAJ was responsible for data analysis. Both authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: Supplementary Material Additional File 1 Published reports quantitatively measuring timeliness of reporting infectious disease surveillance data. Table summarizes the findings of the review of published literature about quantitative measurements of infectious disease surveillance system timeliness Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC509250.xml
546209	Doxycycline-regulated gene expression in the opportunistic fungal pathogen Aspergillus fumigatus	Background Although Aspergillus fumigatus is an important human fungal pathogen there are few expression systems available to study the contribution of specific genes to the growth and virulence of this opportunistic mould. Regulatable promoter systems based upon prokaryotic regulatory elements in the E. coli tetracycline-resistance operon have been successfully used to manipulate gene expression in several organisms, including mice, flies, plants, and yeast. However, the system has not yet been adapted for Aspergillus spp . Results Here we describe the construction of plasmid vectors that can be used to regulate gene expression in A. fumigatus using a simple co-transfection approach. Vectors were generated in which the tetracycline transactivator (tTA) or the reverse tetracycline transactivator (rtTA2 s -M2) are controlled by the A. nidulans gpdA promoter. Dominant selectable cassettes were introduced into each plasmid, allowing for selection following gene transfer into A. fumigatus by incorporating phleomycin or hygromycin into the medium. To model an essential gene under tetracycline regulation, the E. coli hygromycin resistance gene, hph , was placed under the control of seven copies of the TetR binding site ( tetO 7 ) in a plasmid vector and co-transfected into A. fumigatus protoplasts together with one of the two transactivator plasmids. Since the hph gene is essential to A. fumigatus in the presence of hygromycin, resistance to hygromycin was used as a marker of hph reporter gene expression. Transformants were identified in which the expression of tTA conferred hygromycin resistance by activating expression of the tetO 7 - hph reporter gene, and the addition of doxycycline to the medium suppressed hygromycin resistance in a dose-dependent manner. Similarly, transformants were identified in which expression of rtTA2 s -M2 conferred hygromycin resistance only in the presence of doxycycline. The levels of doxycycline required to regulate expression of the tetO 7 - hph reporter gene were within non-toxic ranges for this organism, and low-iron medium was shown to reduce the amount of doxycycline required to accomplish regulation. Conclusions The vectors described in this report provide a new set of options to experimentally manipulate the level of specific gene products in A. fumigatus	Background Aspergillus fumigatus is a saprophytic filamentous fungus that has become the leading mould pathogen in leukemia treatment centers and transplantation units in developed countries, second only to Candida spp . as a cause of systemic mycosis [ 1 ]. Despite some advances in therapy, currently available drugs for the treatment of aspergillosis continue to be hampered by problems with efficacy, toxicity, and the emergence of drug resistance. Moreover, a recent review of the Aspergillus case-fatality rate demonstrated that more than 50% of patients die with, or as a result of, aspergillosis, despite having received the reference standard of therapy [ 2 ]. The continued expansion of the immunosuppressed population emphasizes the need for increased understanding of both the basic biology and virulence of this mould so that more effective antifungal therapies can be developed. The completion of the annotated sequence of the A. fumigatus genome is expected to greatly facilitate efforts to determine the contribution of specific gene products to the virulence of this opportunistic pathogen. Unfortunately, the genetic tractability of A. fumigatus has lagged behind some other fungal systems, particularly in the area of conditional expression systems. Inducible promoter systems have proven to be instrumental for the elucidation of gene function in a number of species, most notably with essential genes. Experimental manipulation of gene expression in A. fumigatus is presently accomplished through the use of DNA cassettes that are introduced into the organism as transgenes [ 3 - 5 ], inserted into specific chromosomal loci [ 3 , 6 ] or expressed from a multi-copy nonintegrating vector [ 7 ]. An inducible expression system based upon the ethanol-inducible alcA promoter from A. nidulans has been successfully used in A. fumigatus [ 8 ]. However, the conditions required to regulate the alcA promoter can have significant effects on the metabolism of the organism and thus remain a concern for many applications, particularly for in vivo studies. The tetracycline operator system has been used to regulate gene expression in a number of species. The system is based upon the E. coli tetracycline-resistance operon, a regulatory unit that detects minute concentrations of tetracycline and mounts an appropriate resistance response. Expression of the operon is controlled by a repressor protein, TetR that binds to operator sequences ( tetO ) in the promoter/enhancer region of the operon and prevents transcription. In the presence of tetracycline TetR is unable to bind tetO , which releases the repression and allows the operon to be expressed. This system has been adapted for experimental gene regulation in eukaryotes by fusing TetR to the VP16 transcriptional activating domain of herpes simplex virus VP16, thereby creating a synthetic tetracycline-regulatable transcriptional activator protein (tTA) that can be used to regulate a gene that is under the control of a tetracycline-responsive promoter (reviewed in [ 9 ] and shown schematically in Fig. 1 ). A tetracycline-regulated promoter is constructed by introducing one or more copies of the tetO sequence upstream of a minimal promoter region and the gene of interest (Fig. 1 ). In the absence of tetracycline, tTA is free to bind to the tetO -promoter and drive the expression of the downstream gene. The addition of tetracycline to the medium prevents tTA from binding the tetO sequences and the promoter is inactive. A variation of this system uses a 'reverse' tetracycline transactivator, rtTA that only binds tetO in the presence of tetracycline. In this case, a gene under tetO control is expressed in the presence of tetracycline, but not in its absence [ 10 ]. The TetR/ tetO system is biologically active in a number of eukaryotes [ 11 - 13 ], including yeasts [ 14 - 17 ], but has not yet been adapted to the filamentous fungi. In this report we demonstrate that the tetracycline-regulated promoter system can be used to manipulate gene expression in Aspergillus fumigatus using a simple co-transfection procedure. Results Vector construction Details on plasmid construction are provided in Methods. The plasmids are shown schematically in Fig. 2 and the individual components are summarized in Table- 1 . Effects of doxycycline on the growth of A. fumigatus Tetracyclines are small lipophilic antibiotics that readily diffuse into eukaryotic cells by passive diffusion. Doxycycline was selected for this study since it has the highest association equilibrium constant to TetR among the common tetracycline derivatives [ 18 ], and has been reported to be most effective in the regulation of tetracycline-regulated promoters in S. cerevisiae [ 19 ]. For the doxycycline system to be effective, the levels of doxycycline required to regulate a tetO promoter must not be within a toxic range for the organism. To determine the range of doxycycline concentrations that are tolerated by A. fumigatus , conidia were spotted onto the center of plates of Aspergillus minimal medium containing 0 – 500 μg/ml of doxycycline and colony diameter was measured with time. Concentrations up to 100 μg/ml had little effect on radial growth rates, all of which were within 5% of each other (Fig. 3 ). However, growth rate was reduced by 16% at 200 μg/ml and by 34% at 500 μg/ml of doxycycline. These results indicate that doxycycline can be used up to 100 μg/ml in minimal medium with no detectable effects on growth rate. Regulated expression of an essential gene by the 'tet-off' system Inducible promoter systems are particularly useful for creating strains that can be inducibly depleted of an essential gene product [ 20 ]. To model an essential gene under tetO control we used heterologous expression of the E. coli hygromycin resistance gene, hph . The hph gene encodes a phosphotransferase that is essential to A. fumigatus in the presence of toxic concentrations of the aminoglycoside antibiotic hygromycin. The hph gene was cloned into a plasmid downstream of a hybrid promoter comprised of seven copies of the TetR binding sequence ( tetO 7 ) linked to a 175 bp minimal gpdA promoter from A. nidulans (p482, Fig. 2 ). The linearized tetO 7 - hph reporter plasmid was co-transfected into A. fumigatus protoplasts together with a linearized plasmid expressing the tetracycline transactivator, tTA (p444, Table- 1 ) and transformants were selected on the basis of their resistance to hygromycin. Although p444 carries the ble gene, phleomycin selection was not included in this experiment. Thirteen hygromycin-resistant colonies were obtained from protoplasts transformed with the tetO 7 - hph reporter construct alone. Since these are integrative plasmids, the observed background colonies are presumed to be a consequence of positional effects at the site of integration, resulting in basal levels of expression of the hph reporter construct. By contrast, 192 colonies were obtained following co-transfection with p444 and the tetO 7 - hph reporter plasmid, suggesting that expression of tTA was driving expression of the tetO 7 - hph transgene and thus conferring hygromycin resistance. Fifty of these hygromycin-resistant colonies were randomly isolated and plated onto secondary hygromycin selection plates in the presence or absence of 100 μg/ml doxycycline. A total of five transformants showed increased hygromycin sensitivity in the presence of doxycycline, two of which were selected for further analysis: one showing marked hygromycin sensitivity in doxycycline (tTA-2) and one showing moderate hygromycin sensitivity (tTA-1). Conidia from each of these transformants were spotted into the center of a plate of minimal medium containing both doxycycline and hygromycin and the radial growth of the colony was monitored with time. The pH of the medium in this experiment was adjusted to 8 in order to maximize the hygromycin toxicity. As shown in Fig. 4A , the tTA-2 transformant showed tight regulation of the phenotype of hygromycin sensitivity. Doxycycline concentrations as low as 30 μg/ml completely arrested growth, indicating that a concentration of doxycycline that is inert to the growth of A. fumigatus (Fig. 3 ) can be used to modulate expression of an essential gene under tetO control in this fungus. Importantly, concentrations of doxycycline below 30 μg/ml could be used to manipulate the degree of hygromycin resistance; at 5 μg/ml and 2 μg/ml of doxycycline, the radial growth rate of the organism was reduced by 68% and 55%, respectively (data not shown). Higher levels of doxycycline were required to suppress the growth of the tTA-1 transformant on hygromycin medium (Fig. 4A ). Northern blot analysis showed that the tTA-1 strain expressed about 5-fold more hph RNA than tTA-2 (Fig. 4B ), which was consistent with the fact that tTA-1 grew faster than tTA-2 in the presence of the same concentration of hygromycin (Fig. 4A , compare tTA-1 and tTA-2, no doxycycline). The doublet shown in Fig. 4B was occasionally seen on Northern blots hybridized to the hph probe and is presumed to represent alternative splicing of the primary hph transcript. The higher levels of hph RNA in the tTA-1 strain could be due to a combination of increased tTA expression (which would be expected to be susceptible to doxycycline regulation) and/or basal expression from one or more integrated copies of the tetO 7 - hph reporter gene (which would not be affected by doxycycline). Since there was a clear dose-response effect of doxycycline on hph expression and hygromycin resistant growth in this strain (Fig. 4A and 4B ), it is likely that the two strains differ primarily in the amount of tTA that they express. Although Northern blot analysis showed barely detectable levels of tTA in either strain (data not shown), undetectable levels of tTA have been reported in other applications of the tetracycline regulatory system and are thought to be due to the toxic effects of overexpression [ 21 ]. Since very low levels of tTA protein are actually required to regulate a tetO promoter [ 21 ], even a small difference in tTA expression level that is beyond the limit of detection of a Northern blot could influence the amount of doxycycline required to suppress tTA activity in this transformant. Regulated expression of an essential gene by the 'tet-on' system A limitation of the tTA-regulated system is that it requires inhibition of transcription rather than activation. To address this, a 'reverse' tTA has been generated (rtTA) that requires interaction of the transactivator with tetracyclines before tetO binding can occur, a system that is referred to as 'tet-on' [ 10 ]. Unfortunately, the mutations that reverse the response to doxycycline also reduce binding affinity for doxycycline ten-fold, thus requiring higher levels of doxycycline for maximal induction. Since there may be adverse effects associated with high doxycycline concentration in A. fumigatus under some conditions [ 22 ], we chose a derivative of rtTA that contains additional mutations that restore binding affinity for doxycycline [ 23 ]. One particular variant, rtTA2 S -M2, also contains a multimerized minimal VP16 activation domain to enhance transcriptional activity, and its sequence has been manipulated to optimize expression in eukaryotic cells [ 23 ]. Using the same co-transfection approach used for the tTA system, the tetO 7 - hph reporter (p500, Fig. 2 ) was co-transfected into A. fumigatus protoplasts together with a linearized plasmid that expresses rtTA2 S -M2 (p474, Fig. 2 ) and the transformants were plated onto medium containing both hygromycin and doxycycline. In this experiment, a modified tetO 7 - hph reporter was used in which a 280 bp terminator sequence from the A. fumigatus cgrA gene [ 29 ] was inserted upstream of the tetO 7 repeats to minimize read-through from flanking sequences (p500). Doxycycline was incorporated into the medium at 100 μg/ml to ensure that the tetO 7 - hph transgene would be expressed at sufficient levels to protect against hygromycin toxicity. Approximately 15% of 27 hygromycin resistant colonies showed reduced growth when shifted to hygromycin medium without doxycycline, one of which was selected for further analysis. As shown in Fig. 5 , the inability of this transformant to grow in the presence of hygromycin was restored by the incorporation of as little as 5 μg/ml of doxycycline into the medium, indicating that low levels of doxycycline are biologically active as regulators of the tetO promoter in A. fumigatus . A further increase in hygromycin resistance was achieved at 15 μg/ml of doxycycline, but concentrations above 15 μg/ml had no additional effect. Northern blots analysis confirmed that the levels of hph RNA in the rtTA transformant were increased by the addition of doxycycline to the medium (Fig. 5 ). When hybridization intensity was normalized to SYBR-green II-stained rRNA bands by phosphorimager analysis, the levels of hph expression in the presence of both concentrations of doxycycline (Fig. 5 ) were thirty-fold greater than in the absence of added doxycycline. Doxycycline-regulation is enhanced by low- iron medium A recent report has shown that iron blocks the accumulation and activity of tetracyclines in bacteria [ 24 ]. Since iron is a standard component of Aspergillus minimal medium, its presence may limit the efficiency of doxycycline-mediated gene regulation, particularly if transcriptional modulators with lower affinity for doxycycline are used. Fig. 6 shows the effects of lowering the iron concentration on doxycycline-mediated suppression of the tetO 7 - hph transgene in the tTA-1 clone showed in Fig. 4 . In comparison to standard minimal medium, where 200 μg/ml of doxycycline was required to reduce expression in this strain (Fig. 4A and 4B ), only 5 μg/ml was required in medium containing one tenth the normal concentration of FePO 4 ·4H 2 0 (Fig. 6 ). This indicates that iron may also impair the accumulation of doxycycline in A. fumigatus and that the choice of medium could have significant effects on doxycycline-mediated gene regulation. Wild type A. fumigatus showed no reduction in radial growth rate on this low-iron minimal medium (data not shown). Discussion The tetracycline-inducible method of gene regulation has become one of the most popular tools to manipulate gene expression in eukaryotes [ 25 ]. The efficacy of the system is attributed to the use of prokaryotic regulatory elements that respond to low concentrations of tetracyclines without affecting eukaryotic physiology, allowing control of gene expression without the concern for pleiotropic effects mediated by the effector. Although widely used in higher eukaryotes, including the model yeast S. cerevisiae [ 19 ], the system has not yet been reported in filamentous fungi. Candida albicans and C. glabrata are the only pathogenic fungi in which the system has been successfully applied thus far, however neither of these studies used the tetR -VP16 fusions upon which the tTA and rtTA systems are based [ 15 - 17 ]. In this study we show that both the tet-off (tTA) and tet-on (rtTA) systems can be used to regulate the expression of a hygromycin resistance reporter gene in A. fumigatus . Since the hph gene is essential in the presence of toxic levels of hygromycin, the ability to control hygromycin resistance by modulating the levels of hph transcription validates the system as a tool for analysis of essential genes in A. fumigatus . In the tTA system we found that individual transformants varied in the amount of doxycycline that was necessary to regulate expression of the tetO 7 - hph reporter gene. Since doxycycline prevents the tTA protein from binding to the tetO sequence, this is most likely due to variability in the amount of tTA protein that is expressed in each transformant. A limitation of the tTA approach described here is that the majority of the hygromycin-resistant transformants from the tTA/ tetO 7 - hph co-transfection were not susceptible to regulation by doxycycline. This may be due in part to leaky expression of the tetO 7 - hph reporter, caused by enhancers in the proximity of the integration site [ 21 , 25 ]. A second possibility is that the levels of tTA coming from the gpdA promoter used in this study were too high to be removed by non toxic concentrations of doxycycline. Since lower levels of tTA expression are more readily suppressed by doxycycline, it is conceivable that a weaker promoter used to drive tTA would increase the frequency with which doxycycline-regulatable transformants can be isolated. Lower levels of tTA expression could also be accomplished by using a shorter segment of the gpdA promoter used in this study. The ability to quantitatively control expression from the tetO 7 - hph reporter gene was also observed in a strain expressing the reverse transactivator, rtTA. Concentrations of doxycycline from 2 μg/ml to 15 μg/ml gave a graded response of hygromycin resistance, indicating that A. fumigatus is responsive to concentrations of doxycycline that are similarly effective in S. cerevisiae [ 19 ] and C. albicans [ 15 ]. Moreover, this level of sensitivity falls within the range of doxycycline concentrations that can be achieved in mouse tissues [ 15 , 16 ], raising the possibility of using this system to modulate the expression of virulence-related genes in pathogenesis studies on A. fumigatus . Only 15% of the hygromycin-resistant colonies from an rtTA/ tetO 7 - hph co-transfection showed doxycycline-dependent hygromycin resistance however, suggesting that some of the hygromycin resistance was due to leaky expression of the tetO 7 - hph gene. Leakage of tetO 7 -regulated genes has been described in other systems, and is attributed to enhancers located in the proximity of the integration site that increase expression of the tetO -linked gene [ 21 , 25 ]. This type of problem will affect tetO 7 -controlled genes regardless of whether they are integrated randomly in the genome or targeted to specific loci. Conclusions This report establishes the utility of the tetracycline-regulated system as an approach to regulate gene expression in A. fumigatus . A limitation of the system was that only 10–15% of the transformants could be regulated by doxycycline, either when tTA or rtTA were used, emphasizing the need to screen for regulatable transformants. A recent approach to limit the problem of leakiness of a tetO -driven gene is the use of trans-silencer proteins comprised of fusions between tetR and a transcriptional silencing domain [ 26 , 27 ]. It is conceivable that the incorporation of a synthetic A. fumigatus -derived trans-silencer protein into the co-transfection approach described in this study would improve the efficiency of the system. Methods Vector construction All vectors are based on the pBluescript plasmid (Stratagene) and were linearized prior to transfection. PCR amplification of components were performed using standard amplification protocols using PfuTurbo DNA polymerase (Stratagene). Hph Reporter Constructs (p482 and p500) A segment containing seven copies of the tet operator sequence ( tetO 7 ) was PCR amplified from pUHD10-3 [ 12 ] with the forward primer 5'- aagctt gcgtatcacgaggccctttc and the reverse primer 5'- aagctt ctcgacccgggtaccgag (added Hin dIII cloning sites are underlined) and cloned into the Hin dIII site of pBluescript. A 1.6 kb fragment containing a minimal gpdA promoter from A. nidulans (-175 relative to the ATG of the hph open reading frame), the hph gene encoding resistance to hygromycin, and the trpC terminator from A. nidulans , was then PCR amplified from pAN7-1 [ 28 ] with forward primer 5'- gagctc cccatcttcagtatattcatc (added Sst I cloning site underlined) and reverse primer 5'- tctaga tcgcgtggagccaagagcgg (added Xba I cloning site underlined) and cloned downstream of tet0 7 into the Sst I and Xba I sites of the plasmid, creating p482. To minimize read-through from flanking sequences into tet0 7 , a 280 bp segment of the terminator region of A. fumigatus cgrA [ 29 ] was inserted upstream of tet0 7 PCR to create p500. The cgrA terminator was PCR amplified from genomic DNA of A. fumigatus isolate H237 using the forward primer 5' aagctt acagcagaagaatctctc (added Hin dIII cloning site underlined) and reverse primer 5' ctcgag atgattcatgacgtatattc (added Xho I cloning site underlined), cloned into pCR2.1-Topo (Invitrogen), excised with Hin dIII, and inserted upstream of tetO 7 in p482 to create p500. tTA expression vectors (p473, p434, and p444) A segment of the A. nidulans gpdA promoter was amplified from pAN7-1 [ 28 ] (position -679 to -1, with +1 being the start of the hph open reading frame) using the forward primer 5'- aagctt cggagaatatggagctt (added Hin dIII cloning site underlined) and the reverse primer 5'- gaattc ggtgatgtctgctcaag (added Eco RI cloning site underlined) and cloned into pBluescript at the same sites. The tTA gene was then PCR amplified from pUHD15-1 [ 12 ] with the forward primer 5'- gaattc tggcaatgtctagattagataaaag (added Eco RI cloning site underlined) and reverse primer 5'-atcatgtct ggatcc tcgcg (internal Bam HI site underlined) and cloned into the Eco RI and Bam HI sites downstream of the gpdA (-679) promoter. A 280 bp segment of the terminator region of A. fumigatus cgrA [ 29 ] was then amplified from H237 genomic DNA using the forward primer 5'- actagt acagcagaagaatctctc (added Spe I site underlined) and reverse primer 5'- gcggccgc atgattcatgacgtatattc (added Not I site underlined) and inserted into the Spe I and Not I sites downstream of tTA. To introduce phleomycin selection into this construct, a phleomycin resistance cassette containing the A. nidulans gpdA promoter, the Streptoalloteichus hindustanus ble gene encoding resistance to phleomycin, and the S. cerevisiae CYC1 terminator was amplified from pBCphleo (Fungal Genetics Stock Center) using the forward primer 5'-cctcaggcggagaatatggagcttcatcg and the reverse primer 5'-cctcaggaattaaagccttcgagcgtccc. The PCR product was cloned into pCR-Blunt II-TOPO (Invitrogen), excised with Kpn I and Xho I and inserted into the P gpdA -tTA construct to create p444. The phleomycin cassette was excised from p444 with Hin dIII and re-ligated to create p473. To introduce hygromycin selection into p444, the phleomycin cassette was excised with Kpn I and Hin dIII and replaced with a hygromycin resistance cassette (containing the A. nidulans gpdA promoter, the hph gene encoding resistance to hygromycin, and the trpC terminator from A. nidulans ) that was amplified from pAN7-1 [ 28 ] with forward primer 5'- ggtacc cggagaatatggagcttc (added Kpn I cloning site underlined) and reverse primer 5'- aagctt gcttgagagttcaaggaag (added Hind III cloning site underlined) to make p434. rtTA expression vectors The tTA gene was excised from p473 with Eco RI and Bam HI and replaced with an Eco RI- Bam HI fragment containing the rtTA2 s -M2 variant of rTA from pUHrT62-1 (generous gift from C. Berens, Erlangen, FRG) to create p474. To introduce phleomycin resistance into p474, the phleomycin resistance cassette was excised from p444 with Kpn I and Hind III and cloned into the same sites in p474 to create p480. To introduce hygromycin resistance into p474, the hygromycin resistance cassette described in p434 was excised from an unrelated plasmid as a Hin dIII fragment and cloned into the Hin dIII site of p474 to make p502. Strains and culture conditions The A. fumigatus strains used in this study are listed in Table- 1 . The wild-type strain, H237, is a clinical isolate. Conidia were harvested from strains grown on Aspergillus minimal medium plates [ 30 ]. This minimal medium contains 4.5 μM FePO 4 ·4H 2 0. For low-iron minimal medium, the FePO 4 ·4H 2 0 concentration was reduced to 0.45 μM. Plasmids were introduced into A. fumigatus protoplasts as previously described [ 3 ]. Following transformation, protoplasts were plated onto 20 ml of osmotically stabilized minimal medium containing 100 μg/ml doxycycline (for transformations involving rtTA-expressing plasmids) or no added doxycycline (for transformations involving tTA-expressing plasmids). After incubating at room temperature overnight, each plate was overlaid with 10 ml of minimal medium top agar containing 0.5% agar, 1M sorbitol, and 8 mg hygromycin B (Invivogen, San Diego, CA). Doxycycline was also incorporated into the top agar overlay (100 μg/ml) for experiments involving rtTA-expressing plasmids. Colonies arising on these primary plates were transferred onto secondary selection plates containing the same selective agents, and conidia from the secondary plates were replated onto selective medium at low density to isolate colonies derived from single conidia. All subsequent experiments were performed on monoconidial isolates. For co-transfection experiments, 5 μg of the linearized tetO 7 - hph reporter construct was co-transfected with 5 μg of the linearized tTA plasmid (p444), or 50 μg of the linearized rtTA plasmid (p474). For experiments addressing the effects of doxycycline on hygromycin sensitivity, ten thousand conidia were spotted onto the surface of Aspergillus minimal medium agar containing hygromycin and doxycycline at the concentrations specified in the Figure legends. The plates were then incubated at 37°C, and colony diameter was measured with time. Radial growth rates were calculated from the exponential part of the resulting growth curves. Northern blot analysis For analysis of hph gene expression, RNA was isolated from overnight cultures in minimal medium supplemented with the indicated concentrations of doxycycline by crushing in liquid nitrogen and extracting RNA from the crushed mycelium with phenol/chloroform. Twenty micrograms of total RNA were fractionated by formaldehyde gel electrophoresis as previously described [ 20 ], transferred to positively charged nylon membranes (MSI, Inc., Westborough, MA, USA) and hybridized to a 32 P-labeled hph DNA probe under stringent conditions in 50% (v/v) formamide/5XSSC (1X SSC is 0.15 M NaCl/0.015 M Na 3 ·citrate, pH 7.6)/2X Denhardt's solution/10% (w/v) dextran sulfate/1% (w/v) sodium dodecyl sulfate (SDS). The hph probe was an 800 bp Eco RI- Bam HI fragment from pAN7-1 [ 28 ] containing a segment of the hph open reading frame. Hybridization intensity was quantified with a Phosphorimager (Molecular Dynamics) and normalized for differences in gel loading by quantitating the relative levels of SYBR-green II-stained rRNA (Molecular Probes, Inc., Eugene, OR, USA). List of abbreviations tTA tetracycline transactivator rtTA reverse tetracycline transactivator TetR tetracycline repressor tetO TetR binding sequence hph hygromycin resistance gene ble phleomycin resistance gene Authors' contributions KV participated in vector construction, gene transfer into A. fumigatus , screening of transformants and drafting the manuscript. RB participated in plasmid construction. JCR contributed to the planning of the study. DSA conceived of the project and directed its design and execution. All authors have read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC546209.xml
514573	"Is there nothing more practical than a good theory?": Why innovations and advances in health behavior change will arise if interventions are used to test and refine theory	Theoretical and practical innovations are needed if we are to advance efforts to persuade and enable people to make healthy changes in their behavior. In this paper, I propose that progress in our understanding of and ability to promote health behavior change depends upon greater interdependence in the research activities undertaken by basic and applied behavioral scientists. In particular, both theorists and interventionists need to treat a theory as a dynamic entity whose form and value rests upon it being rigorously applied, tested and refined in both the laboratory and the field. To this end, greater advantage needs to be taken of the opportunities that interventions afford for theory-testing and, moreover, the data generated by these activities need to stimulate and inform efforts to revise, refine, or reject theoretical principles.	Background Even with the dramatic advances in our understanding of the biological processes that determine health and illness, it has never been more clear that rates of disease morbidity and premature mortality reflect people's behavioral practices. [ 1 ] The benefits, both for individuals and the societies in which they live, that would come from systematic improvements in diet, physical activity, and use of substances such as tobacco, alcohol, and illicit drugs are tantalizing and provide ample motivation to develop initiatives to elicit changes in health behavior. Yet, health behavior change has proven a worthy adversary. Despite the commitment of considerable time and effort, innovations and advances in our ability to improve health behaviors have been modest. In particular, the specification of methods that produce sustained improvements in behavior have been elusive [ 2 - 5 ]. At the same time, innovations in theories of health behavior have also been modest. Investigators continue to advocate for a broad range of theories and there has been limited progress in demonstrating the unique value of any specific theory. [ 6 - 8 ] Although there may be consensus in the professional community that there are considerable gaps in our understanding of health behavior change, critiques of the current state of affairs more often that not reflect the professional interests of the critic. Investigators who strive to specify the structural and psychological processes that regulate people's behavior lament the fact that too many interventions are not guided by a theoretical framework that specifies how they are supposed to elicit health behavior change. At the same time, investigators who design and implement health behavior interventions lament that the preponderance of theories of health behavior make it difficult to discern what factors are likely to be the most effective targets for intervention. Moreover, it is argued that theories are not sufficiently specified to determine when or how to modify factors that are to be targeted in an intervention. Of course, concerns regarding the link between theory and practice are not new and efforts to address this problem have taken several forms. Considerable effort has been given to provide practitioners with a comprehensive and concise understanding of the array of theories that have been developed to address health behavior. [ 9 ] Moreover, conceptual frameworks such as PRECEDE-PROCEED [ 10 ] and Intervention Mapping [ 11 ] have been developed to provide investigators with a structured process to improve the accuracy and ease with which theoretical concepts are used to address a practical problem. In both cases, these efforts have targeted improving how theoretical principles are applied and, in doing so, have relied on the assumption that current theories of health behavior are useful and productive. Is this assumption valid? Could the often repeated plea for investigators to ground their intervention efforts in theory be a sign that there are significant limitations to the practical principles that can be derived from current theories of health behavior? If so, merely improving how people use theories will not be sufficient. What is needed is a shift in how we engage the interplay between theory and practice, with an emphasis placed on developing initiatives that target opportunities to develop, test, refine health behavior theory. In this paper, I describe and advocate for a model of collaboration between basic and applied behavioral scientists. Although I recognize the value of improving the manner in which theoretical principles are matched to problems and methods, I propose that innovations in our understanding of and ability to promote health behavior change will not arise if theory is construed as a fixed entity that is delivered to interventionists for implementation. To date, although theories may fluctuate in their popularity, their properties have remained strikingly static over time. I believe greater attention must be paid to refining and, when necessary, rejecting theoretical principles. For this process to take shape, there needs to be an on-going series of exchanges between theorists and interventionists in which theory is treated as a dynamic entity whose value depends on it being not only applied and tested rigorously, but also refined based on the findings afforded by those tests. A fundamental implication of this perspective is that improvements in both health behavior theory and intervention methods depend on each other. If investigators are more receptive to the opportunities interventions afford for theory testing, there will be a dramatic increase in data that can reveal the adequacies and inadequacies of a given theory. These data will, in turn, enable theorists to improve the quality of the theoretical models available to guide subsequent intervention efforts. Discussion When is an intervention effective? Interventions are designed to address important practical problems (e.g., obesity) and thus their value is inextricably linked to their ability to alleviate the targeted problem. Interventions need to provide a meaningful return on the time, money, and effort invested such that the outcomes afforded by a intervention strategy are proportional to the resources utilized. Of course, determining what is a sufficient return on an investment can be a challenge. Small effects may be impressive if the intervention is directed at a construct or behavior that is considered difficult to move. [ 12 ] In addition, interventions can have minimal impact on an individual's behavior but when disseminated widely have a dramatic impact at the societal level. [ 13 ] What conditions are likely to facilitate a successful intervention? Broadly speaking, an intervention is most likely to be effective if it is appropriately grounded in the practical problem targeted. [ 11 ] For example, consider an intervention to promote healthy food choices. The intervention design team must possess a clear understanding of who is engaging in the targeted behavior (e.g., who is making unhealthy food choices), the underlying nature of the behavior (e.g., the frequency and function of food choices), and the context in which the behavior is performed (e.g., where and with whom do people make choices about food). In a similar manner, the intervention needs to be appropriately grounded in the biological, structural and psychological processes that shape and regulate people's behavioral practices. [ 14 - 16 ] For example, the expected value of altering a feature of the environment in which people make food choices (e.g., increasing the cost of high-fat foods) is predicated on the assumption that the intervention will directly, or indirectly through an intervening construct, influence people's food choice in that setting. Health behavior theories provide an explicit statement of the structural and psychological processes that are hypothesized to regulate behavior (e.g., increasing the cost of high-fat foods will curtail consumption of these foods by making it more aversive or, perhaps, more difficult to purchase them). If theories describe the factors that guide people's behavior and justify how an intervention is designed and implemented, interventionists depend on the quality and predictive value of a theory. What determines a theory's value? From the perspective of a theoretician, a theory's value rests on its ability to provide an accurate account of the factors that regulate people's behavior. [ 17 ] Although investigators may recognize that behavior is affected by factors at different levels of analysis (i.e., biological, psychological, social, environmental), a theory's value is not necessarily predicated on its ability to provide linkages across these levels. Because of this emphasis, theory testing tends to occur in controlled contexts, typically a laboratory setting, that afford the social and behavioral version of a Petrie dish. This approach allows investigators to observe the relation between a given set of constructs with greater precision, but it renders the generalizability and strength of the observed effect difficult to discern. For example, investigators may determine that focusing people's attention on the undesirable aspects of an object increases their interest in avoiding it, but be unable to specify the conditions under which this relation is and is not most likely to obtain. From the perspective of an interventionist, the accuracy of the relations specified in a theory is an important but not sufficient determinant of its value. Interventionists need theories that are accurate and applicable; that specify not only the relation between two constructs, but also whether that relation does or does not change across contexts (e.g., does the impact of risk perceptions on behavior differ whether one is examining decisions to test for radon or to start smoking?). Given a set of a factors hypothesized to regulate people's behavior, interventionists need to be able to discern which of these factors are the most appropriate targets for intervention. In fact, a common complaint regarding theories is that they are not useful (See Jeffery, this issue). A theory may specify a host of factors that regulate a person's behavior, but in the absence of information regarding the relative importance of each factor leave an interventionist unsure as to where to direct her or his resources. For example, the Theory of Planned Behavior [ 18 ] and Theory of Reasoned Action [ 19 ] propose that people's attitudes toward the behavior and their perceived subjective norm regarding the behavior are critical determinants of behavior (albeit mediated by behavioral intention), but the relative contribution of these constructs is allowed to fluctuate from setting to setting. In any given context, it is unclear how to determine a priori which set of constructs should be prioritized as a target for intervention. The interest interventionists have shown in stage-based models of health behavior may reflect the fact that the models attempt to specify the conditions under which specific constructs affect behavioral decisions. [ 8 ] Little guidance is also given as to how or even whether critical constructs can be manipulated. For example, my colleagues and I have proposed that satisfaction with the outcomes afforded by a pattern of behavior is a critical determinant of behavioral maintenance. [ 20 , 21 ] Claims such as this are typically predicated on evidence that measures of a construct, in this case satisfaction, uniquely predict a behavioral outcome. Yet, the observation that someone who is satisfied is more likely to sustain a pattern of behavior does not indicate what causes someone to be satisfied and, thus, little guidance is given as to what can be done to heighten the satisfaction people derive from changes in their behavior. In the absence of this type of information, interventionists may find little difference between developing intervention strategies that are or are not grounded in a health behavior theory. In fact, given these practical needs, it is not be surprising that interventionists are more likely to rely on health behavior theories (e.g., Social Cognitive Theory [ 22 ]) that specify the determinants of its primary constructs and thus provide guidance as to how to construct an intervention protocol. Breakdown in the evolution of health behavior theories If the design and implementation of intervention strategies rely on assumptions regarding the factors that regulate people's behavior, why haven't current theories of health behavior evolved in ways that would enable them to more effectively guide intervention development? I believe the critical problem is that there has been a breakdown in the relation between basic and applied scientists who study health behavior. [ 23 ] As scholars such as Kurt Lewin [ 24 ] have asserted, the development and specification of theories of human behavior depend upon an iterative series of research activities in which theoretical principles initially formulated by basic behavioral scientists are tested and evaluated by applied behavior scientists. These tests provide critical information that enables basic scientists to revise, refine, or reject their initial principles. Moreover, an applied setting can afford investigators the opportunity to assess the relative impact of different processes hypothesized to regulate people's behavior. It is through this on-going cycle of specification, application, and evaluation that accurate and applicable theoretical models arise. To the extent that behavioral theories are not tested in complex social settings such as those afforded by interventions to change health practices, the process by which theories develop is curtailed. Because the manner in which a theory is specified reflects, in part, the contexts in which it has been operationalized and tested, theories that are tested primarily in tightly controlled laboratory settings will likely be characterized by a rich description of the myriad of factors that could affect people's behavioral choices. The laboratory setting allows investigators to minimize noise and potential confounding or moderating factors and thus optimizes their ability to detect processes that can affect people's behavior without determining whether, in a more complex setting, they do affect behavior. [ 17 ] Thus, in the absence of initiatives that empirically test theoretical principles in complex social environments, investigators run the risk of developing a "hot house" theory of health behavior that has limited practical value. Interventions afford an invaluable opportunity to discern the context dependence of causal relations that have been revealed in the laboratory. Some factors may be shown to always be critical, whereas others may be critical only under certain conditions. [ 25 ] For example, self-efficacy may be a critical determinant of the decision to initiate a new pattern of behavior, but have a limited impact on the decision to maintain that behavior over time. [ 21 ] It is critical to understand that restricting the conditions under which a construct affects behavior does not mean that a given factor is not important. Information that would help delimit these conditions would enable theorists to develop more precise models. The case for why interventions should be more receptive to theory There are two sets of reasons why we must take better advantage of the opportunities interventions provide to implement and test theories of health behavior. One set focuses on what theory can do to improve the implementation and evaluation of an intervention, whereas the other set focuses on how interventions can be used to improve the accuracy and quality of prevailing health behavior theories. First, by grounding their work on theoretical principles regarding processes that regulate people's behavior, investigators can readily specify the critical assumptions that underlie their intervention protocol. These formal statements of cause and effect relations not only provide a clear justification for the proposed research activities (i.e., why an investigator believes a given intervention strategy will be effective), but also increase the likelihood that the proposed methodology will allow the investigator to detect whether and why the intervention had its intended effect. [ 10 , 11 ] When faced with unambiguous evidence of a successful intervention effect, investigators might be able to move forward without knowing why the intervention was effective. However, more often than not, investigators are faced with the task of determining why an intervention failed to produced the desired effect or why it worked under a limited set of conditions. An a priori set of theoretical principles can provide an important conceptual and analytic framework for determining why an intervention was ineffective. In particular, it increases the likelihood that investigators have not only identified the constructs that may determine whether an intervention will prove effective, but also assessed them at the appropriate points in the decision process. The second set of reasons why interventions should take advantage of opportunities to test theories of health behavior is that by providing a context in which some or all of the facets of a theory can be tested, interventionists are in a position to generate evidence that will enhance the accuracy and applicability of theory and thus, over time, improve the quality of the theories to which interventionists can turn. By systematically testing principles specified in health behavior theories, investigators are able to not only verify the accuracy of these predictions, but also develop a better understanding of their practical value. Across studies, evidence should accumulate that will allow investigators to differentiate between factors that should and should not be targeted for intervention. Because current theories of health behavior often provide a list of factors that may affect behavior, the set of potential mediating variables suggested by a theory may pose a daunting if not untenable measurement burden. However, the implementation of consistent and methodologically sound assessment of these factors should provide the empirical evidence needed to constrain and prioritize the variables on that list. The characteristics of intervention strategies that prove to be effective should also provide investigators with a better understanding of the determinants of a given construct. As was previously mentioned, theories may propose that a construct (e.g., satisfaction) is a critical determinant of decisions to maintain a new pattern of behavior, but provide limited guidance as to how to alter people's standing on that construct (e.g., how to help feel satisfied with the outcomes afforded by their new behavior). [ 21 ] An intervention protocol that is shown to successfully heighten people's satisfaction with process and outcomes associated with weight loss not only has clear practical value, but also can shed light on the process by which people determine whether they are satisfied with their experiences. If theorists can develop a more detailed account of the processes that shape the primary constructs identified in a health behavior theory, interventionists will find that theories can provide a more useful set of guidelines for how to develop strategies to target these constructs. Testing theoretical principles across a diverse array of settings and populations will also enable investigators to better specify the scope of a theory. Although interventions provide a wonderful opportunity to test theoretical principles in diverse samples and settings, formal and appropriately powered tests of moderators can put a considerable strain on sample size and resources. However, if investigators have appropriately assessed the critical constructs, systematic comparisons can be drawn across studies that taken together have tested a theoretical principle across a range of settings or people. The increase in public access to data sets should facilitate opportunities for this type of comparisons. With the information that is gleaned from these types of activities, it should be easier to determine which moderators are worth testing in a single, appropriately powered study design. The identification of situational or personal factors that moderate the impact of a theoretical principal can be indicative of a number of different scenarios. For example, what might one conclude if an intervention that promoted the health benefits of eating a balanced diet altered the eating habits of college students but not those of high school students? It could indicate that health benefits do not affect what high school students choose to eat. Alternatively, it might be that high school students are responsive to perceptions of the health benefits afforded by a balanced diet, but that other factors (e.g., control over access to food) preclude them from acting on those beliefs. The practical and theoretical conclusions that can be drawn from the identification of moderating factors are dramatically increased if investigators can identify the causal processes that underlie the observed impact of the moderator. In particular, can investigators discern whether the moderated effect was obtained because the moderator altered the ability of the intervention strategy to change the proposed mediating construct (e.g., the intervention raised perceptions of the health benefits held by college but not high school students) or because it altered the effect the mediator has on the primary outcome measure (e.g., perceived health benefits predicted the eating habits of college but not high school students)? Greater attention to the causal processes invoked by a moderator may also help investigators grapple with the daunting number of potential moderators. It is quite possible that moderators that differ at the level of description (e.g., gender, ethnicity) can be accounted for by the same underlying process. Finally, it is important to recognize that progress in theory development can arise from the failure to obtain evidence in support of a specific prediction. Empirical evidence that provides investigators with a better sense of the potential factors that do not affect health practices will allow them to reduce the number of constructs (and, in time, theories) invoked to predict and explain health behavior. What can be done to make interventions more theory-friendly? If one assumes that there is interest in rendering interventions more receptive to theory-testing, what can be done to enhance an intervention's ability to assess principles derived from current health behavior theories? One issue is the appropriate evaluation of the critical manipulation(s) imbedded in the intervention. Any conclusions that can be drawn from the intervention, regardless of whether it reveals the predicted pattern of results, is predicated on the success with which the independent variable was manipulated. To this end, investigators need to at least consider assessing several constructs: the degree to which the intervention was implemented (e.g., did the interventionists consistently provide participants with the intervention exercises?), the degree to which participants correctly identified the emphasis of the intervention (e.g., did participants assigned to the optimistic outcome condition report their was a greater emphasis on favorable outcomes than did those assigned to the control condition?), and finally the degree to which the intervention altered the targeted set of opportunities, thoughts or feelings (e.g., did those assigned to the optimistic outcome condition develop more favorable expectations regarding the benefits afforded by behavior change than did those assigned to the control condition?). Although it is important that interventionists explicitly specify the constructs that determine the influence of the intervention on participant behavior, the quality of the evidence that can be gathered depends on the assessment procedures that are utilized. The persuasiveness of any claims regarding the importance (or lack of importance) of a particular construct is contingent on the use of measures that have been shown to be reliable and valid. Given that many of the constructs specified in theories of health behavior are conceptually similar, it is difficult to draw strong conclusions regarding the specific contributions of different variables in the absence of well-designed measures. [ 26 , 27 ] In addition, the inclusion of a pool of potential mediators enables the investigators to make stronger claims as he or she can demonstrate that not only does the construct specified in the model serve as a mediator but that other factors do not operate as mediators. Adequately testing basic principles also depends on a well-timed assessment schedule. Assessments are often too infrequent to detect meaningful changes on the construct. This is particularly true if the constructs of interest are psychological states that both affect and are affected by behavioral practices. However, specifying the optimal time to assess the primary constructs can be difficult. To the extent that one wants to determine whether an intervention strategy (e.g., a tailored message about dietary changes) alters the predicted mediating variable (e.g., willingness to modify one's diet), one might consider minimizing the length of time between the delivery of the intervention and the assessment of the mediator. However, at the same time, interest in the association between the hypothesized mediator and the outcome variable (e.g., change in diet) would also benefit from a shorter window of time between the two assessments. In many cases, the length of these two time windows are inversely related to each other and thus efforts to improve the chance of detecting one relation may hinder effects to detect the other. Of course, there are practical constraints on an investigator's ability to adequately assess constructs. What is needed is for investigators to take advantage of the measurement and testing opportunities when they do arise. Although what can be concluded from any single assessment effort may be limited, the cumulative impact of well designed tests of a theoretical principle can be substantial. If investigators consistently wait for another time or another investigator to conduct the relevant assessments, innovations in theory and practice will continue to be slow. As interventionists specify the degree to which a given study can test all or a facet of a given theory, they are more likely to articulate the contribution a proposed study could make to the empirical literature. This process not only makes the justification for the intervention clear, but also improves the likelihood that investigators will recognize when their and their colleagues' efforts have focused consistently on a single or limited aspect of a given theory. Research activities motivated by the Transtheoretical Model [ 28 ] provide an excellent example of a domain where researchers have consistently relied on a limited number of methodological strategies and thus, despite an enormous amount of research activity, provided a very narrow test of the theory. [ 8 ] The commitment of time and effort to using interventions to test theoretical principles will in the end be for naught, if there is not an equal commitment to the dissemination of the findings generated by these activities. In particular, investigators who are engaged in the development of health behavior theories must take advantage of the information afforded by intervention activities and demonstrate that they are responsive to this information as they refine and revise their theories. Enhanced communication should also provide an opportunity for basic and applied behavioral scientists to recognize the strengths and weakness of current theories of health behavior and thus help formulate a fuller understanding of what needs to be done to improve the quality of our theories. Summary With an eye toward the future Although Lewin may have been right that there is "nothing more practical than a good theory" (p.169; [ 24 ]), his dictum rests on the assumption that good theories are available to address practical problems. The development of "good" theories – that is, theories that are both accurate and applicable – has been hindered by a breakdown in the on-going collaboration between basic and applied behavioral scientists. Research and professional activities that are able to foster a stronger sense of interdependence between these two groups are likely to provide a base for collaboration and, in turn, a opportunity for innovation. If critical advances in health behavior theory depend on an iterative process by which theoreticians and interventionists cooperate in the testing and evaluation of theoretical principles, individuals in both camps need to not only recognize the goals and values of each group, but also trust each other's ability to advance our understanding of both theory and practice. Competing Interests None declared.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC514573.xml
423136	Virtual Labs: E-Learning for Tomorrow	At Stanford University, the Virtual Labs project takes full advantage of information technology to provide innovative resources for learning and teaching	Because of the explosive growth in our scientific understanding, today's students are required to learn and maintain a rapidly expanding knowledge base. Students are also expected to understand and follow the crossover of information between different disciplines. As a result, they often have to understand the fundamentals of several disciplines, and be able to integrate that knowledge. Students of every discipline are facing these new challenges, and it is clear that today's students are markedly different from those of the past. Influenced by a lifetime surrounded by media, computers, and the Internet, they bring with them different expectations. As educators, we need to meet these expectations in order to motivate students to move forward. And it's not just the student population that is driving change. The National Institutes of Health, which sponsors many biological and medical advances in the United States, has a new initiative called “Digital Biology: The Emerging Paradigm,” whose goal is to merge biomedical computation with biology and medicine over the next ten years. One way to facilitate this movement is to use information technology (IT) as a teaching tool, so that students, in turn, learn how to use IT most effectively. Using IT to Teach IT presents educators and teachers with a unique opportunity to devise innovative methods of teaching. Students today are more likely than ever to use new tools and technologies to advance their understanding of the sciences. Currently, this usage is mainly limited to searching the Web for information. However, computers and the Web can be used for much more—with computers, you can create learning scenarios like virtual patient simulations, and with the Web, these learning resources can be disseminated to the global community. Educators must harness the power of these enabling technologies, which students have already adopted, to create new and more powerful methods of teaching that will better prepare the students for the next phase of their lives. The Virtual Labs Project at SUMMIT (Stanford University Medical Media and Information Technologies) in the Stanford University School of Medicine has been funded by the Howard Hughes Medical Institute (Chevy Chase, Maryland, United States) since 1998. It is an initiative to augment the Department of Biological Sciences and the Program in Human Biology at Stanford University by developing technology-enhanced materials for these curricula. A major goal of the Virtual Labs Project is to increase scientific literacy by using interactive multimedia to teach the fundamental concepts of biology, and to share those resources via the Internet. The Virtual Labs material is currently hosted on a password-protected site and is freely available to interested parties for educational use. A wise individual once said that a picture is worth a thousand words; with Virtual Labs we use not just pictures, but also animations and interactive simulations. Students are able to visualize and interact with dynamic processes in the body. We have developed learning modules in cardiovascular, gastrointestinal, respiratory, renal ( Video 1 ), visual ( Video 2 ), and neurophysiological systems. The concepts in these modules lay the foundation for medicine and for an increasing number of interdisciplinary programs, such as biomedicine, medical informatics, and bioengineering. For example, a medical student learns how the kidney filters blood in order to understand kidney failure in diabetic patients. A bioengineer could apply the same knowledge to build an artificial kidney. The modules are flexible, and the content can be woven together to highlight the intersections of different disciplines. Virtual Labs also strives to make learning science fun. The more engaged the user is, the more likely the learning experience is to be positive. For example, after learning about how the kidney filters blood (see the online link for Figure 1 ) and controls water levels, students apply their new knowledge by playing a simulation game. The goal of the game is to maintain water balance in order to survive on a deserted island, which helps to reinforce conceptual understanding and to ensure that students understand how those concepts fit together. Responses from students have shown that these goals are being met. Over the past four years, our undergraduate and medical students have reported that Virtual Labs was fun, engaging, and that it helped them learn: “Virtual Labs was an excellent resource for the class! [It was] a lot of fun to use and the graphics are awesome.” “It was a great interactive way to reinforce what I already had learned from the book and lectures and I think it really helped me better understand.” Similarly, faculty who have used our material during lectures have found it useful to illustrate concepts with animations. Reaching Beyond the Local Community Local schools and other universities are looking for opportunities to bring IT into their classrooms. Access to resources like Virtual Labs, and expertise on how to develop and integrate multimedia content into curricula, are on the rise. In 2003, the Virtual Labs Project began building a network of collaborators in the community and abroad. Together with H.E.L.P for Kids ( http://www.stanford.edu/group/help ,) we are designing content for the education of local schoolchildren. Abroad, we are working with global partners in Sweden via the Wallenberg Global Learning Network ( http://www.wgln.org ). We have also partnered with the MedFarmDoIT group at Uppsala University in Uppsala, Sweden ( http://doit.medfarm.uu.se/multimedia.html ) to help them with multimedia development and IT integration in the classroom. The MedFarmDoIT group shares our vision of bringing IT into the classroom, and together, we are designing content for their medicine/pharmacy program. The Virtual Labs Project is dedicated to supporting its partners by distributing customized Virtual Labs content and offering consultation or workshops to train teachers and developers. As integrated partners, we can bridge the gap between the physical and information sciences, and in doing so, can improve the learning process of students for years to come. Video 1 The “Big Picture” of the Blood Flow through the Vasculature in the Kidney The rich visuals and moving media of this Virtual Labs animation capture the attention of the students. (The animation can be accessed online on computers with Shockwave by clicking and dragging the file into the browser window. A free version of Shockwave can be downloaded from http://sdc.shockwave.com/shockwave/download .) Video 2 Understanding Center–Surround Receptive Fields in Retinal Neurons The virtual experiment in this Virtual Labs interactive program is similar in design to the receptive field experiments from Hubel and Wiesel in the 1960s. The user places an electrode in the retina to take a recording from a neuron. The user moves a spot of light on the screen and then maps correlating changes in the activity level (using the symbols: + − 0 to indicate the strength of the response). The map reveals a center–surround organization. Each time the user moves the electrode, the size, shape, location, and type of receptive field changes (on-center or off-center), as they would during a real experiment. Supporting questions adapt dynamically to each experimental condition and further encourage the student to answer more conceptual questions. (The interactive program can be accessed online on computers with Shockwave by clicking and dragging the file into the browser window. A free version of Shockwave can be downloaded from http://sdc.shockwave.com/shockwave/download .)	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC423136.xml
544350	Micronutrient malnutrition and wasting in adults with pulmonary tuberculosis with and without HIV co-infection in Malawi	Background Wasting and micronutrient malnutrition have not been well characterized in adults with pulmonary tuberculosis. We hypothesized that micronutrient malnutrition is associated with wasting and higher plasma human immunodeficiency virus (HIV) load in adults with pulmonary tuberculosis. Methods In a cross-sectional study involving 579 HIV-positive and 222 HIV-negative adults with pulmonary tuberculosis in Zomba, Malawi, anthropometry, plasma HIV load and plasma micronutrient concentrations (retinol, α-tocopherol, carotenoids, zinc, and selenium) were measured. The risk of micronutrient deficiencies was examined at different severity levels of wasting. Results Body mass index (BMI), plasma retinol, carotenoid and selenium concentrations significantly decreased by increasing tertile of plasma HIV load. There were no significant differences in plasma micronutrient concentrations between HIV-negative individuals and HIV-positive individuals who were in the lowest tertile of plasma HIV load. Plasma vitamin A concentrations <0.70 μmol/L occurred in 61%, and zinc and selenium deficiency occurred in 85% and 87% respectively. Wasting, defined as BMI<18.5 was present in 59% of study participants and was independently associated with a higher risk of low carotenoids, and vitamin A and selenium deficiency. Severe wasting, defined as BMI<16.0 showed the strongest associations with deficiencies in vitamin A, selenium and plasma carotenoids. Conclusions These data demonstrate that wasting and higher HIV load in pulmonary tuberculosis are associated with micronutrient malnutrition.	Background Approximately one-third of the world's population is infected with Mycobacterium tuberculosis , and the majority live in less developed countries where human immunodeficiency virus (HIV) infection is spreading rapidly. The World Health Organization (WHO) estimates that the number of new cases of tuberculosis and the proportion with coexisting HIV infection will continue to increase [ 1 ]. Immunosuppression increases the risk of developing clinical tuberculosis, which contributes to the increased prevalence of tuberculosis in association with HIV infection. Malnutrition and wasting are associated with tuberculosis, and co-infection with HIV and tuberculosis may potentially exacerbate the wasting that occurs in tuberculosis or HIV infection alone [ 2 - 5 ]. Micronutrient deficiencies have been described in individuals with tuberculosis [ 6 - 17 ] and in those with HIV infection [ 17 - 23 ]. Several cross-sectional studies suggest that patients with tuberculosis are at high risk of deficiencies of vitamin A [ 7 , 10 - 12 ], thiamin [ 13 ], vitamin B 6 [ 14 ], folate [ 6 , 15 ], vitamin E [ 16 ], and zinc [ 10 ]. Poor selenium status has recently been shown to increase the risk of developing mycobacterial disease among HIV-infected injection drug users [ 24 ], but selenium status among HIV-infected adults with pulmonary tuberculosis has not been well characterized. Selenium plays an important role in the selenoenzyme glutathione peroxidase that protects cells against free radical damage and oxidative stress. The relationship between severity of HIV disease and micronutrient malnutrition needs further elucidation. Such information would help identify subgroups that might benefit the most from nutritional interventions. Plasma HIV load was used as an indicator of severity of HIV disease, as HIV load tends to be higher in more active HIV disease. We hypothesized that wasting in pulmonary tuberculosis is associated with micronutrient malnutrition and that HIV-infected adults with pulmonary tuberculosis who have more active HIV disease, as reflected by higher HIV load, also have more severe micronutrient malnutrition. To test these hypotheses, we conducted a cross-sectional study to examine the relationship between wasting and micronutrient malnutrition in HIV-positive and HIV-negative adults with pulmonary tuberculosis in Zomba, Malawi. Methods The study population consisted of adults who presented with new sputum-positive pulmonary tuberculosis in Zomba Central Hospital between July 1999 and April 2003. Subjects were offered HIV testing and were screened for HIV antibodies after signing a written informed consent form. All subjects were given appropriate pre- and post-test HIV counseling. Subjects commenced treatment after enrollment and received standard short course chemotherapy for tuberculosis as per guidelines of the Malawi National Tuberculosis Program [ 25 ]. Adults with a previous history of treated pulmonary tuberculosis were excluded. Three sputum samples from each subject were examined with Auramine-O dark-fluorescent staining method. Sputum positive pulmonary tuberculosis was considered proven when at least one out of three sputum stains showed acid-fast bacilli. HIV infection was diagnosed on the basis of a positive rapid test (Determine 1/2 Rapid test by Abbott, Abbott Laboratories, Johannesburg, SA) and confirmed by a positive enzyme-linked immunosorbent assay for HIV-1 antibodies (Wellcozyme; Wellcome Diagnostics, Dartford, Kent, UK). Plasma HIV load was measured using quantitative HIV-1 RNA PCR (Roche Amplicor Monitor, version 1.5, Branchburg, NJ, USA) with a sensitivity limit of 400 HIV RNA copies mL. CD4 + lymphocyte counts were not conducted due to limited resources. None of the participants were taking antiretroviral treatment. The protocol was approved by the institutional review boards at the Johns Hopkins School of Medicine (Baltimore, Maryland, USA) and the College of Medicine, University of Malawi (Blantyre, Malawi), with final approval by the Office for Protection from Research Risk of the National Institutes of Health. Nutritional assessment Body weight was determined to the nearest 0.1 kg using an adult balance (Seca 700 balance, Seca Corporation, Hanover, MD, USA), and standing height was determined to the nearest cm. Body mass index (BMI) was calculated as body weight/height 2 . Plasma micronutrient concentrations A venous blood sample was collected by venipuncture (Sarstedt Monovette, Newton, NC). Blood samples were shielded from bright light and immediately aliquoted and stored in cryotubes at -70°C. α-carotene, β-carotene, β-cryptoxanthin, lycopene, lutein, zeaxanthin, retinol, and α-tocopherol concentrations were measured in 100 uL of plasma by high performance liquid chromatography using a modified method from the Nutrition Laboratory, Inorganic Toxicology and Nutrition Branch Division of Laboratory Sciences, National Center of Environmental Health, Centers of Disease Control and Prevention (Rosemary Schleicher, personal communication) [ 27 ]. Total plasma carotenoids were defined as the sum of α-carotene, β-carotene, β-cryptoxanthin, lycopene, lutein and zeaxanthin in μmol/L. Plasma trace element concentrations were measured using a Perkin Elmer model AAnalyst 600 atomic absorption spectrometer equipped with Zeeman background correction, a THGA graphite furnace, and an AS800 auto sampler (Perkin Elmer Corp., Norwalk, CT). Quality control was assessed by repeated analysis of pooled human plasma controls run at the beginning and the end of each analysis. Standard curves were run periodically using standard reference material 986C (National Institute of Standards and Technology, Gaithersburg, MD). Throughout all analyses, the plasma samples were run in a masked fashion. Data and statistical analysis Data and statistical analysis were conducted using SAS 8.01 (SAS Institute Cary, NC, USA) and SPSS 9.0 (SPSS, Inc., Chicago, IL, USA). Comparisons between groups were made using t -tests and nonparametric Mann-Whitney U -tests. Univariate analysis of variance was used to test for linear trends across categories of plasma HIV load and BMI. HIV load was categorized into tertiles. HIV negative subjects were assigned a fourth category of HIV load (category 0) when groups were merged for analysis. Nutritional status was assessed in adults with pulmonary tuberculosis with and without HIV co-infection. Subjects were separated into groups according to their extent of wasting. Mild wasting was defined as BMI 17.0–18.49, moderate wasting as BMI 16.0–16.99, and severe wasting as BMI <16.0, conform the WHO strata for BMI grading of severity of malnutrition [ 27 ]. Plasma retinol <0.70 μmol/L was considered consistent with vitamin A deficiency [ 28 ]. Vitamin E deficiency was defined as plasma α-tocopherol <11.6 μmol/L [ 28 ]. Zinc deficiency was defined as plasma zinc <11.5 μmol/L and selenium deficiency as plasma selenium <0.89 μmol/L [ 28 ]. Because there is no standard cut-off for deficiency of carotenoids, we divided total plasma carotenoids into quartiles, with the lowest quartile considered to be the most consistent with deficiency. To examine the risk of micronutrient deficiencies at different severity level of wasting, logistic regression models were fitted with retinol <0.70, α-tocopherol <11.6, zinc <11.5, selenium <0.89, and the lowest quartile of total carotenoids as the outcome variable. Multivariate logistic regression models were conducted to adjust for sex, age and HIV load. A significance level of P < 0.01 was used in this study. Results The study population consisted of 579 HIV-positive and 222 HIV-negative adults with sputum-positive pulmonary tuberculosis. Among the total study population, 66% (232/352) of male and 77% (347/449) of female participants were HIV-positive. The mean age among all subjects was 33 years (range 18–59 years). The majority of subjects were wasted, as 59% of subjects had a BMI <18.5, 32% of subjects had a BMI <17.0, and 17% of all subjects were severely wasted as defined by BMI<16.0. Plasma retinol concentrations <0.70 μmol/L occurred in 61% of all subjects. Vitamin E, zinc, and selenium deficiency occurred in 13%, 85% and 87% respectively. Table 1 shows characteristics of study participants, such as sex, age, BMI, and plasma carotenoids, retinol, α-tocopherol, zinc and selenium by categories of plasma HIV load. BMI, plasma retinol, total carotenoids and selenium concentrations decreased by increasing plasma HIV load. Age, the proportion of individuals with BMI <18.5, BMI <16.0 and selenium deficiency were increased with increasing plasma HIV load. Plasma α-tocopherol, zinc or the proportion of individuals with vitamin A, vitamin E, or zinc deficiencies were not significantly different across the categories of plasma HIV load. When exploring across the categories separately, there were no significant differences between HIV-negative individuals compared with HIV-positive individuals in the lowest tertile of viral load. Table 2 shows adjusted odds ratios (O.R.) and 95% confidence intervals (C.I.) for independent associations between wasting and micronutrient deficiencies. Wasting defined as BMI<18.5 was associated with vitamin A deficiency, low plasma carotenoids and selenium deficiency. The odds ratio for an independent association with vitamin A deficiency was 2.86 (95% C.I. 2.11–3.89) when adjusted for sex, age, and plasma HIV load. The adjusted odds ratio for an independent association with the lowest quartile of total carotenoids was 2.96 (95% C.I. 1.99–4.44). The adjusted odds ratio for an independent association with selenium deficiency was 1.59 (95% C.I. 1.04–2.43). When separating severity levels of wasting; mild wasting did not show association with deficiencies, moderate wasting was associated with vitamin A deficiency and severe wasting was significantly associated with vitamin A deficiency, low plasma carotenoids and selenium deficiency. (Table 2 ) Wasting was not associated with vitamin E or zinc deficiency. Figures 1 , 2 and 3 show plasma retinol, total plasma carotenoids, and plasma selenium concentrations with 95% C.I by severity of wasting and categories of plasma HIV load. Plasma retinol concentrations significantly decreased with the increase of plasma HIV load among non-wasted adults with pulmonary tuberculosis ( P = 0.004). Total carotenoid concentrations significantly decreased with the increase of plasma HIV load among non-wasted, mildly wasted, moderately wasted and severely wasted adults ( P = 0.0001, P = 0.002, P = 0.001 and P = 0.001, respectively). Selenium concentrations decreased significantly with the increase of plasma HIV load among non-wasted and severely wasted adults with pulmonary tuberculosis ( P = 0.0001 and P = 0.03, respectively). Among the HIV negative adults and those in the 1 st and 2 nd tertile of HIV load, plasma retinol, total carotenoids and selenium concentrations significantly decrease with the increasing severity of wasting. Among those in the 3 rd tertile of HIV load, only plasma retinol concentrations significantly decreased with the increasing severity of wasting. This trend did not reach significance for plasma carotenoid and selenium concentrations. Discussion The present study shows that micronutrient malnutrition and wasting are more severe in adults with pulmonary tuberculosis who have higher plasma HIV load. The association between high plasma HIV load and nutrient deficiencies was strongest for the major plasma carotenoids and selenium. Overall in this study population, both HIV-positive and HIV-negative adults with pulmonary tuberculosis were extremely malnourished as indicated by BMI and plasma micronutrient concentrations. About one-third of the adults in this study had a BMI <17.0, a cut-off that is predictive of mortality in adults co-infected with tuberculosis and HIV [ 29 ]. To our knowledge, this is the first study to demonstrate that selenium status is extremely poor among HIV-infected adults with pulmonary tuberculosis, and that the extent of selenium deficiency is associated with higher plasma HIV load. This observation may be of potential importance because selenium deficiency has been associated with increased mortality during HIV infection [ 30 ], and selenium supplementation for HIV-infected adults has been shown to reduce morbidity [ 31 ]. In the present study, selenium deficiency occurred in 87% of the participants, which, to our knowledge, may be the highest prevalence of selenium deficiency reported in an HIV-infected group of patients. It is unknown whether selenium supplementation will reduce morbidity and mortality among HIV-infected adults with pulmonary tuberculosis. Carotenoids are among the most important dietary antioxidants found in human plasma, and this study shows that poor carotenoid status was associated with higher HIV load and with wasting. Plasma carotenoid concentrations are widely considered to be the most accurate indicator of dietary carotenoid intake [ 32 ]. It is not known whether adults with pulmonary tuberculosis and higher HIV load have lower plasma carotenoid concentrations because of increased oxidative stress, or whether these individuals are sicker and unable to consume enough carotenoid-rich foods. Further studies are needed in the future to address dietary intake of carotenoids in HIV-infected adults with pulmonary tuberculosis. Low BMI is a known risk factor for mortality [ 5 , 29 ], and the present study showed that the risk of micronutrient deficiencies is highest in those with low BMI. HIV-infected adults with wasting and high viral load were at the highest risk of more severe micronutrient malnutrition, suggesting that this subgroup might potentially benefit the greatest from nutritional interventions. The cross sectional design of this study restricts our conclusions and does not provide information on whether poor nutritional status is a predictor of more severe pulmonary tuberculosis. It is unknown whether nutritional interventions will slow progression of disease or reduce wasting associated with morbidity and mortality if added to tuberculosis chemotherapy. Controlled clinical trials currently in progress in developing countries should help provide insight into the role of micronutrient supplementation for HIV-positive and HIV-negative adults with pulmonary tuberculosis. Conclusions The present study shows that micronutrient malnutrition and wasting are more severe in adults with pulmonary tuberculosis who have higher HIV load. The association between high plasma HIV load and nutrient deficiencies was strongest for the major plasma carotenoids and selenium. Further longitudinal investigations are needed to determine whether deficiencies in micronutrients are independent risk factors for increased morbidity and mortality. Competing interests The author(s) declare that they have no competing interests. Authors' contributions Overall guidance and initial study design was provided by RS. MvL has been in charge of the collection and analysis of data and writing of the manuscript. Provision of advice was given by AH, JK, EZ, TC and TT. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544350.xml
545072	Characterisation of cytotoxicity and DNA damage induced by the topoisomerase II-directed bisdioxopiperazine anti-cancer agent ICRF-187 (dexrazoxane) in yeast and mammalian cells	Background Bisdioxopiperazine anti-cancer agents are inhibitors of eukaryotic DNA topoisomerase II, sequestering this protein as a non-covalent protein clamp on DNA. It has been suggested that such complexes on DNA represents a novel form of DNA damage to cells. In this report, we characterise the cytotoxicity and DNA damage induced by the bisdioxopiperazine ICRF-187 by a combination of genetic and molecular approaches. In addition, the well-established topoisomerase II poison m-AMSA is used for comparison. Results By utilizing a panel of Saccharomyces cerevisiae single-gene deletion strains, homologous recombination was identified as the most important DNA repair pathway determining the sensitivity towards ICRF-187. However, sensitivity towards m-AMSA depended much more on this pathway. In contrast, disrupting the post replication repair pathway only affected sensitivity towards m-AMSA. Homologous recombination (HR) defective irs1SF chinese hamster ovary (CHO) cells showed increased sensitivity towards ICRF-187, while their sensitivity towards m-AMSA was increased even more. Furthermore, complementation of the XRCC3 deficiency in irs1SF cells fully abrogated hypersensitivity towards both drugs. DNA-PK cs deficient V3-3 CHO cells having reduced levels of non-homologous end joining (NHEJ) showed slightly increased sensitivity to both drugs. While exposure of human small cell lung cancer (SCLC) OC-NYH cells to m-AMSA strongly induced γH2AX, exposure to ICRF-187 resulted in much less induction, showing that ICRF-187 generates fewer DNA double strand breaks than m-AMSA. Accordingly, when yeast cells were exposed to equitoxic concentrations of ICRF-187 and m-AMSA, the expression of DNA damage-inducible genes showed higher levels of induction after exposure to m-AMSA as compared to ICRF-187. Most importantly, ICRF-187 stimulated homologous recombination in SPD8 hamster lung fibroblast cells to lower levels than m-AMSA at all cytotoxicity levels tested, showing that the mechanism of action of bisdioxopiperazines differs from that of classical topoisomerase II poisons in mammalian cells. Conclusion Our results point to important differences in the mechanism of cytotoxicity induced by bisdioxopiperazines and topoisomerase II poisons, and suggest that bisdioxopiperazines kill cells by a combination of DNA break-related and DNA break-unrelated mechanisms.	Background Type II topoisomerases are essential nuclear enzymes found in all living organisms [ 1 ]. Their basic role in cells is to catalyse the transport of one DNA double helix through a transient double strand break in another DNA molecule [ 2 ]. This activity helps relieve tensions built up in DNA during various DNA metabolic processes such as DNA replication, chromosome condensation and de-condensation, chromosome segregation and transcription [ 3 ]. Topoisomerase II is also a major drug target in human cancer therapy, where a number of clinically active drugs such as the epipodophyllotoxins VP-16 and VM-26, the aminoacridine m-AMSA, and antracyclines such as doxorubicin, daunorubicin and epirubicin are widely used. These drugs have collectively been called topoisomerase II poisons due to their mechanism of action on topoisomerase II. Rather than inhibiting the basic catalytic activity of the enzyme, these drugs perturb the topoisomerase II catalytic cycle resulting in an increase in the level of a transient reaction intermediate, where DNA is cleaved and covalently attached to DNA [ 4 ]. Catalytic inhibitors of topoisomerase II have a different mode of action. These drugs exemplified by merbarone, aclarubicin, F11782 and the bisdioxopiperazines work by inhibiting topoisomerase II at other stages in the reaction cycle where DNA is not cleaved as reviewed in [ 5 , 6 ]. Amongst these, the bisdioxopiperazines have gained much attention due to their distinct and well-characterised mode of action. These compounds exemplified by ICRF-187, ICRF-159 and ICRF-154 inhibit the DNA strand passage reaction of topoisomerase II by sequestering this protein as a salt-stable closed clamp on DNA whose formation depends on the presence of ATP [ 7 - 9 ]. This closed clamp complex has retained the capability to hydrolyse ATP, although at a reduced level [ 10 ]. Several studies indicate that the closed clamp complex on DNA represents a novel form of DNA lesion to cells, – and that inhibition of topoisomerase II catalytic activity (DNA strand passage activity) is not responsible for bisdioxopiperazine-induced cell kill: ( i ) Expression of bisdioxopiperazine-sensitive topoisomerase II in cells also expressing bisdioxopiperazine-resistant topoisomerase II confers dominant sensitivity to these drugs [ 7 , 11 ] – a modality reminiscent of that of topoisomerase II poisons. ( ii ) Mouse embryonic stem cells [ 12 ] and chicken lymphoma DT40 cells [ 13 ] having one topoisomerase II α allele knocked out with concomitant reduced levels of topoisomerase II, are resistant to both ICRF-193 and the topoisomerase II poison etoposide, – while the opposite result is to be expected if ICRF-193 kill cells by depriving them of essential topoisomerase II catalytic activity. ( iii ) Killing of yeast cells by exposure to ICRF-193 occurs more rapidly and to a higher level than killing of yeast cells induced by the depletion of endogenous topoisomerase II catalytic activity [ 7 ]. ( iv ) The ICRF-193-induced topoisomerase II closed clamp complexes on DNA work as a "road block" signalling selective degradation of topoisomerase II β as well as p53 activation in a transcription dependent fashion [ 14 ]. Some studies have recorded elevated levels of DNA breaks in cells after exposure to the bisdioxopiperazine analog ICRF-193. In one study, ICRF-193 was found to increase the level of topoisomerase II-DNA covalent complexes in vitro and in vivo [ 15 ]. However, in this study efficient trapping of this covalent intermediate was only evident when guanidine was used to denature topoisomerase II attracted to DNA, while the agent normally used to trap the topoisomerase II-DNA cleavage complex, SDS, was not effective. In another study, the comet assay and pulsed field gel electrophoresis were used to demonstrate elevated levels of DNA breaks in mammalian cells after exposure to ICRF-193 [ 16 ]. In this study, inhibiting DNA replication with aphidicolin reduced the level of DNA breaks induced by the topoisomerase II poison m-AMSA, but had no effect on DNA breaks induced by ICRF-193. These results point towards bisdioxopiperazines poisoning DNA topoisomerase II in cells by a mechanism different from that of the classical topoisomerase II poisons such as etoposide and m-AMSA. In a recent paper, it was directly demonstrated that m-AMSA-induced dominant cytotoxicity only required the DNA cleavage activity of topoisomerase II, while dominant cytotoxicity towards ICRF-193 depended strictly on the DNA strand passage reaction of the enzyme[ 17 ]. Based on these observations, the present study aims to further elucidate the mechanism of cytotoxicity induced by the bisdioxopiperazines. We here characterise the effect of the clinically approved analog ICRF-187 (dexrazoxane) by using a number of different cell-based pharmacological assays, taking advantage of genetically modified yeast and mammalian cells. Results ICRF-187 sensitivity of yeast cells depends on their homologous recombination status, albeit to a lesser extent than for m-AMSA sensitivity To pinpoint the mechanism of cytotoxicity of ICRF-187 versus m-AMSA, we employed a panel of human topoisomerase II α-transformed haploid single-gene knockout yeast strains, defective in various aspects of DNA repair, checkpoint control, membrane transport and protein degradation. All yeast strains are depicted in table 1 . We used doses of these two drugs equitoxic to wild-type cells having no mutations. Clonogenic survival of all yeast strains is depicted in additional file 1 , and the degree of drug resistance / hypersensitivity is also listed in table 2 . Table 1 Yeast strains used in the study BY4741 + pMJ1 BY4741Δ rad9 + pMJ1 BY4741Δ rad51 + pMJ1 BY4741Δ tel1 + pMJ1 BY4741Δ rad52 + pMJ1 BY4741Δ chk1 + pMJ1 BY4741Δ rad54 + pMJ1 BY4741Δ mhl1 + pMJ1 BY4741Δ rad55 + pMJ1 BY4741Δ pms1 + pMJ1 BY4741Δ rad57 + pMJ1 BY4741Δ msh2 + pMJ1 BY4741Δ rad59 + pMJ1 BY4741Δ msh3 + pMJ1 BY4741Δ dcm1 + pMJ1 BY4741Δ atr1 + pMJ1 BY4741Δ sae2 + pMJ1 BY4741Δ pdr5 + pMJ1 BY4741Δ rad50 + pMJ1 BY4741Δ yor1 + pMJ1 BY4741Δ mre11 + pMJ1 BY4741Δ ubc4 + pMJ1 BY4741Δ xrs2 + pMJ1 BY4741Δ ubc13 + pMJ1 BY4741Δ rad6 + pMJ1 BY4741Δ doa4 + pMJ1 BY4741Δ rad18 + pMJ1 BY4741Δ qri8 + pMJ1 BY4741Δ rev1 + pMJ1 BY4741Δ rnr3 + pMJ1 BY4741Δ rev3 + pMJ1 BY4741Δ sml1 + pMJ1 BY4741Δ rad1 + pMJ1 BY4741 + PYX112 BY4741Δ rad14 + pMJ1 BY4741Δ rad6 + pYX112 BY4741Δ apn1 + pMJ1 BY4741Δ rad50 + pYX112 BY4741Δ yku70 + pMJ1 BY4741Δ rad52 + pYX112 BY4741Δ yku80 + pMJ1 BY4741Δ sae2 + pYX112 BY4741Δ mec3 + pMJ1 BY4741Δ yku70 + pYX112 BY4741Δ dcc1 + pMJ1 BY4741Δ rad17 + pMJ1 JN362A t2-4 + pMJ1 Table 2 Hypersensitivity (or resistance) scoring of pMJ1-transformed BY4741 deletion strains towards ICRF-187 and m-AMSA as determined in clonogenic assay using 22.5 hours drug exposure. Drug ICRF-187 m-AMSA Gene deleted WT 0 0 Nucleotide Excision Repair (NER) Single Strand Annealing (SSA) Recombination Anti-Recombination Δ rad1 R 0 Δ rad14 0 0 Mismatch Repair (MMR) Anti-Recombination Δ msh2 R 0 Δ msh3 0 0 Δ mhl1 R 0 Δ pms1 R 0 Base Excision Repair (BER) Δ apn1 0 0 Post Replication Repair (PRR) Δ rev1 0 0 Δ rev3 0 0 Δ rad18 0 + Δ rad6 0 ++ Homologous Recombination (HR) Non-Homologous End Joining (NHEJ) Δ rad50 + ++ Δ mre11 + ++ Δ xrs2 + ++ Homologous Recombination (HR) Δ rad52 + ++ Δ rad51 + + Δ rad54 + ++ Δ rad57 + ++ Δ rad55 + ++ Δ rad59 0 0 Δ dmc1 0 0 Δ sae2 + + Non-Homologous End Joining (NHEJ) Δ yku70 + 0 Δ yku80 0 0 DNA Damage Checkpoints Δ tel1 0 0 Δ rad9 0 0 Δ mec3 0 0 Δ ddc1 0 0 Δ rad17 0 0 Δ chk1 0 0 ABC Transporters (Yeast MDR1 homologous) Δ atr1 0 0 Δ pdr5 + 0 Δ yor1 0 0 Ubiquitin conjugation / hydrolysis Δ ubc4 0 0 Δ ubc13 0 0 Δ doa4 0 R Δ qri8 0 0 Ribonucleotide-reductase regulation Δ rnr3 0 0 Δ sml1 0 0 R : Cells are more than a 1/2 log resistant at any drug concentration. 0 : Cells are no more than a 1/2 log resistant and no more than a 1/2 log hypersensitive at any drug concentration. + : Cells are at least a 1/2 log but no more than 2 log hypersensitive at any concentration. ++ : Cells are more than 2 log hypersensitive at any concentration. Hypersensitivity (resistance) was graduated as follows The products of the three genes RAD50 , MRE11 and XRS2 together form the Rad50/Mre11/Xrs2 hetero-trimer protein complex that has catalytic and structural functions in many kinds of DNA metabolic processes including HR as reviewed in [ 18 ]. We observed that Δ rad50 , Δ mre11 , and Δ xrs2 single knockout strains were extremely hypersensitive towards m-AMSA, while they displayed considerably less hypersensitivity towards ICRF-187 ( additional file 1 and table 2 ). We also tested the effect of deleting a number of genes exclusively involved in HR namely RAD51 , RAD52 , RAD54 , RAD55 , RAD57 , RAD59 , DMC1 and SAE2 [ 18 ]. Deleting RAD51 , RAD52 , RAD54 , RAD55 , RAD57 and SAE2 had a profound effect on the sensitivity of the yeast cells towards m-AMSA while having a smaller, but significant, effect on the sensitivity of these cells towards ICRF-187 ( additional file 1 and table 2 ), again pointing to the HR pathway as being most important for the repair of DNA damage caused by cleavage complex stabilising drugs. We found that deleting RAD59 had no effect on drug sensitivity, confirming reported data that RAD59 only becomes functionally important in the absence of functional Rad51 protein [ 19 ]. We also observed no effect of deleting DMC1 ( additional file 1 and table 2 ). This may be explained by the fact that Dmc1p is primarily involved in meiotic recombination [ 20 ]. NHEJ represents another DNA repair-pathway. In yeast, this repair pathway is generally less important than HR for the repair of DNA breaks [ 21 ]. In accordance with this we observed no effect of deleting the NHEJ genes YKU70 and YKU80 on the sensitivity towards m-AMSA. We did however, observe some hypersensitivity of Δ yku70 cells towards ICRF-187, while Δ yku80 cells were not hypersensitive ( additional file 1 and table 2 ). This is a surprising result, because Yku70p and Yku80p have been demonstrated to play equally important roles for NHEJ activity in yeast [ 21 ]. These results suggest that the effect of deleting YKU70 is unrelated to its DNA repair functions. The DNA binding Rad18p forms a hetero-dimer with Rad6p that is involved in post replication repair (PRR) [ 22 ]. We found that although Δ rad18 cells were clearly hypersensitive towards m-AMSA, Δ rad6 cells were markedly more sensitive. Δ rad6 cells were actually among the most sensitive towards m-AMSA (figure 1 , additional file 1 and table 2 ). Interestingly, the sensitivity of Δ rad6 and Δ rad18 cells towards ICRF-187 is indistinguishable from that of wild-type cells (figure 1 ). The vast difference in the sensitivity of Δ rad 6 cells towards ICRF-187 and m-AMSA confirms the notion that the DNA lesions induced by these drugs are different in nature. The finding that Δ rad6 cells are much more sensitive towards m-AMSA than Δ rad18 cells is surprising, and may indicate that Rad6p functions unrelated to DNA repair affect cellular sensitivity towards m-AMSA. Rad6p has ubiquitin conjugating activity [ 22 ], and therefore such Rad18p-unrelated functions could involve protein degradation via the 26S proteasome pathway. To test this hypothesis, we analysed the drug sensitivity of four yeast strains with impaired protein degradation; Δ ubc4 , Δ ubc13 , Δ doa4 and Δ qri8 . These deletion strains were not hypersensitive towards m-AMSA (or ICRF-187) ( additional file 1 and table 2 ), suggesting that Δ rad6 cells are hypersensitive towards m-AMSA due to impaired PRR activity. The involvement of both HR repair and PRR in determining the sensitivity of yeast cells towards the topoisomerase II cleavage complex stabilising drugs mitoxantrone and idarubicin has previously been reported [ 23 ]. The observed lack of hypersensitivity of the Δ rev1 and Δ rev3 strains ( additional file 1 and table 2 ) suggests that trans-lesion DNA synthesis plays no role in determining the sensitivity towards ICRF-187 or m-AMSA. Figure 1 Clonogenic sensitivity of PRR defective Δ rad6 and Δ rad18 yeast cells towards equitoxic doses of ICRF-187 and m-AMSA. A Δ rad52 strain is included for comparison. Error-bars represent SEM of at least 3 experiments. We also analysed the effect of deleting genes belonging to the nucleotide excision repair (NER) pathway – RAD1 and RAD14 , the base excision repair (BER) pathway – APN1 , and the mismatch repair (MMR) pathway – MLH1 , PMS1 , MSH2 and MSH3 . None of these deletions caused cells to become more sensitive towards ICRF-187 and m-AMSA, indicating that these pathways are not involved in repairing DNA damage induced by these drugs. Interestingly, deleting genes involved in the MMR and NER pathways caused cells to become somewhat resistant to ICRF-187, and to a lesser extent towards m-AMSA ( additional file 1 and table 2 ). The products of these genes have been implicated to have anti-recombination activities [ 24 ]. Increased levels of recombination in these cells could therefore be responsible for the observed low-level resistance towards ICRF-187. Deletion of DNA damage checkpoint genes has little effect on both ICRF-187 and m-AMSA sensitivity of yeast cells While deleting genes involved in DNA repair caused cells to be hypersensitive towards both drugs tested, we observed little effect of deleting the DNA damage checkpoint genes MEC3 , DDC1 , RAD17 , TEL1 , RAD9 and CHK1 ( additional file 1 and table 2 ). Our finding that checkpoint control regulation plays no important role for bisdioxopiperazine sensitivity supports earlier data showing that arresting yeast cells in G1 phase did not protect against ICRF-193 cytotoxicity [ 7 ]. The lack of importance of checkpoint function in determining sensitivity towards m-AMSA is also in accordance with published observations [ 23 ], where sensitivity towards the cleavage complex stabilising topoisomerase II poisons mitoxantrone, idarubicin, daunorubicin and doxorubicin were only marginally affected by inactivating the RAD9 , RAD17 , MEC1 , and RAD53 genes, while the sensitivity of yeast cells towards the topoisomerase I poison camptothecin showed a strong dependency on these pathways. ICRF-187 is a possible substrate for the Pdr5 ABC transporter in yeast In mammalian cells resistance towards various structurally-unrelated anti-neoplastic agents is often associated with over-expression of ABC-type drug efflux transporters such as p-glycoprotein and multi-drug resistance protein (MRP) as reviewed in [ 25 ]. Among the three yeast ABC transporters assessed in our study, Pdr5 is by far the best characterised [ 26 ]. While deleting YOR1 and ATR1 had no effect on drug sensitivity, Δ pdr5 cells were clearly hypersensitive towards ICRF-187 but not towards m-AMSA ( additional file 1 and table 2 ), suggesting that ICRF-187 is a substrate for the Pdr5 pump in yeast. It has to be emphasized, that over-expression of drug efflux pumps has not been associated with resistance towards bisdioxopiperazines in mammalian cells. Transcriptional profiling of yeast cells after exposure to equitoxic concentrations of ICRF-187 and m-AMSA In order to assess the effect on global gene expression of the interaction between human topoisomerase II α and the two drugs in yeast cells, transcriptional profiling was performed using Affymetrix gene chip technology. We exposed pMJ1-transformed JN362A t2–4 yeast cells expressing human topoisomerase II α as their sole active topoisomerase II to equitoxic doses of ICRF-187 and m-AMSA for two hours at 34°C. This treatment resulted in a 50 % reduction in clonogenic survival after exposure to both drugs ( additional file 2 ). Genes whose average expression in two independent experiments was up- or down-regulated more than 1.5 fold by exposure to the drugs were filtered out. 138 transcripts were induced by exposure to ICRF-187 while the number was 90 for m-AMSA. 26 transcripts were repressed by exposure to ICRF-187 while the number was 16 for m-AMSA. Additional file 3 lists transcripts induced or repressed by ICRF-187 while additional file 4 lists transcripts induced or repressed by m-AMSA. The expression profile of selected genes is listed in Table 3 and discussed below. Table 3 Selected genes induced or repressed by exposure of pMJ1-transformed yeast cells to equitoxic concentrations of ICRF-187 and m-AMSA for 2 hours Transcriptional activation Gene function Gene Name Effect of ICRF-187 Effect of m-AMSA DNA damage RNR3 3.2 4.0 HUG1 3.1 5.0 RAD51 1.9 2.0 RAD54 1.7 1.6 RNR2 1.5 1.8 Membrane transport PDR12 2.4 1.0 PDR15 2.0 1.0 Stress response HSP12 2.8 1.6 HSP26 1.7 1.8 WSC4 1.6 1.3 XBP1 1.6 1.5 HSP42 1.5 1.5 Others SWI1 1.6 1.1 Transcriptional repression Others SNZ1 0.6 1.1 PCL9 0.7 0.6 Genes induced by both drugs Both compounds induced the expression of a number of genes known to be up-regulated by DNA damage. The expression of four well-established DNA-damage inducible genes; RNR2 , RNR3 [ 27 , 28 ] and RAD51 , RAD54 [ 29 ] was thus induced by both drugs. Both compounds also stimulated the expression of HUG1 recently shown to be up-regulated by DNA damage and replication arrest [ 30 ] (See Table 3 , additional files 3 and 4 ). Furthermore, both drugs stimulated expression of the stress-inducible XBP1 gene whose protein product is a transcription factor. XBP1 expression is reportedly induced in response to heat shock, high osmolarity, oxidative stress, glucose starvation and DNA damage, and induces a slow-growth phenotype with lengthening of the G1 cell cycle phase [ 31 ]. The PCL9 gene product has cyclin-dependent protein kinase regulator activity suggesting a role for Pcl9p in cell cycle regulation [ 32 ]. Repression of PCL9 by exposure to both drugs (table 3 , additional files 3 and 4 ) may thus be indicative of drug-induced cell cycle arrest in accordance with the XBP1 expression data. Finally, both drugs induced the expression of general stress-induced HSP genes as expected (table 3 , additional files 3 and 4 ). Although expression of the RNR3 and HUG1 genes was up-regulated by both drugs, pMJ1-transformed cells having RNR3 or SML1 deleted (the latter is a functional non-inducible homolog of HUG1 ) have wild-type sensitivity towards both drugs (table 2 , additional file 1 ), showing that although these genes are induced by both drugs, they are probably not involved in determining their cytotoxicity. Genes specifically induced by ICRF-187 We found that ICRF-187 specifically induced the expression of two genes encoding the ABC efflux transporters Pdr12 and Pdr15, while m-AMSA had no effect on the expression of these genes (table 3 , additional files 3 and 4 ). Transcription of the stress-inducible WSC4 gene was likewise enhanced by exposure to ICRF-187 (table 3 , additional files 3 and 4 ). Knocking out WSC4 in yeast cells has been found to enhance their sensitivity towards various stresses including heat, ethanol and DNA damage [ 33 ]. Recently, the SWI/SNF complex was directly shown to repress transcription in S. cerevisiae cells [ 34 ]. We found that SWI1 was specifically induced by ICRF-187 (table 3 , additional files 3 and 4 ). Finally, we found that ICRF-187 specifically repressed the expression of the stationary phase-induced SNZ1 gene [ 35 ] (table 3 , additional files 3 and 4 ). Exposure of yeast cells to ICRF-187 causes less transcriptional induction of DNA damage-inducible genes than exposure to m-AMSA at equitoxic drug concentrations To verify the array data we performed real-time PCR to assess the expression of the RNR3 , HUG1 , RAD51 and RAD54 genes after exposure to the two drugs using the actin gene ACT1 as internal control (figure 2 ). Real-time PCR confirmed induction of these established DNA damage-inducible genes by both drugs assessed. Furthermore, exposure of the cells to m-AMSA resulted in a higher level of induction than did exposure to ICRF-187 for the four genes tested, especially for HUG1 . These data suggest that when yeast cells are exposed to equitoxic concentrations of the two drugs, m-AMSA generates more extensive DNA damage than ICRF-187. Figure 2 Analysis of gene expression by real time PCR. Real-time PCR was used to determine the expression of the DNA-damage inducible genes RNR3 , HUG1 , RAD51 , and RAD54 by using the 2- ΔΔCt method. Gene expression was normalized to that of the actin gene ACT1 . It can be seen that exposure of yeast cells to m-AMSA results in higher levels of induction of transcription of these four genes than exposure to ICRF-187 when the two drugs are applied at equitoxic concentrations. Error-bars represent SEM of two independent experiments each performed in duplicate. ICRF-187 sensitivity of mammalian hamster cells depends on their homologous recombination status, albeit to a lesser extent than seen for m-AMSA sensitivity The yeast clonogenic assays presented above point to an important role of HR in the repair of m-AMSA-induced DNA damage, while the importance of this pathway in the repair of ICRF-187-induced DNA damage is less so. Because HR is the major repair pathway in yeast [ 21 ], while both NHEJ and HR are important for the repair of DNA breaks in mammalian cells [ 36 ], we next turned to assess the importance of these pathways in mammalian cells having reduced levels of HR and NHEJ. In this analysis we used a panel of four hamster cell lines; AA8 cells (wild-type), irs1SF cells [ 37 ] (recombination defective caused by non-functional XRCC3), CXR3 cells [ 37 ] (recombination proficient due to ectopic expression of human XRCC3), and V3-3 cells [ 38 ] (reduced level of NHEJ due to non-functional DNA-PK cs ). We observed a strong dependence on HR for the sensitivity towards m-AMSA (figure 3A ). Thus, only 1 % relative survival was seen for the irs1SF cells (recombination defective) at 6 nM of this drug, while wild-type AA8 cells were only slightly sensitive to15 nM m-AMSA. Furthermore, ectopic expression of human XRCC3 fully reversed the m-AMSA hypersensitivity as CXR3 cells were no more hypersensitive than AA8 wild-type cells, confirming the notion that HR plays a role in the repair of topoisomerase II-induced DNA breaks in mammalian cells. We also observed that irs1SF cells were hypersensitive towards ICRF-187 (figure 3B ), but the degree of hypersensitivity was much less than observed for m-AMSA, as also seen for recombination deficient yeast cells. Again, ectopic expression of the human XRCC3 homolog reversed the hypersensitivity as CXR3 cells displayed near wild-type sensitivity towards ICRF-187. Figure 3 Assessing the clonogenic sensitivity of HR and NHEJ deficient and proficient hamster cells towards ICRF-187 and m-AMSA. To determine the sensitivity of the four cell lines AA8 (wild-type), irs1SF (recombination defective caused by non-functional XRCC3), CXR3 (recombination proficient due to ectopic expression of human XRCC3), and V3-3 (defective in NHEJ due to non-functional DNA-PK cs ) towards ICRF-187 and m-AMSA, a clonogenic assay with continuous drug exposure was used. Error-bars represent SEM of two independent experiments. DNA-PK cs deficient hamster cells show slightly increased sensitivity towards both m-AMSA and ICRF-187 To assess the effect of NHEJ on drug sensitivity we also employed the V3-3 cell line (DNA-PK cs deficient, with concomitant reduced level of NHEJ). The results of these experiments are depicted in figure 3A and 3B . The V3-3 cells were slightly hypersensitive towards both drugs suggesting a role for NHEJ in the repair of DNA lesions induced by both drugs. AA8, irs1SF, CXR3 and V3-3 cells have similar levels of topoisomerase II catalytic activity The sensitivity of cells towards topoisomerase II directed drugs depends both on their levels of topoisomerase II catalytic activity, and on their capability to repair topoisomerase II-induced DNA damage. We therefore determined the level of topoisomerase II catalytic (DNA strand passage) activity in crude protein extracts isolated from the four cell lines used in clonogenic assays, by applying a radioactive decatenation assay. No significant difference in the level of topoisomerase II DNA strand passage activity was recorded between the four cell lines ( additional file 5 ). This result rules out the possibility that varying levels of topoisomerase II catalytic activity in these cells is responsible for their differential drug sensitivity. ICRF-187 induces lower levels of homologous recombination in hamster cells than m-AMSA at equitoxic concentrations The hypersensitivity of the recombination defective irs1SF cells towards both drugs suggests that HR is involved in repairing DNA lesions induced by both drugs. To address this directly we applied a mammalian recombination assay to measure stimulation of HR by ICRF-187 and m-AMSA by using SPD8 hamster cells [ 39 ]. This assay measures the repair of a defective chromosomal hprt gene by the activity of HR. From figure 4A it is evident that both drugs stimulated the level of HR in a dose dependent manner. When recombination frequency is expressed as a function of surviving cells (figure 4C ) it becomes evident that the recombination frequency increases with increasing cell mortality for both drugs tested. From figure 4C it is also evident that at equitoxic concentrations of the two drugs, m-AMSA stimulated HR to much higher levels than did ICRF-187. Thus, at 50 % survival, no induction of HR was seen with ICRF-187 (in three independent experiments), while m-AMSA caused an approximately 10-fold induction at equitoxic doses. Figure 4 Assessing the effect of equitoxic concentrations of ICRF-187 and m-AMSA on the level of HR in SPD8 hamster cells. The SPD8 cell line has a defective hprt gene that can be repaired by HR. Panel A depicts the induction of HR induced by increasing concentrations of the two drugs. Panel B depicts the relative survival of cells exposed to similar concentrations of the two drugs. The data represented in Panel A and B was used to generate Panel C, where recombination frequency is plotted against the surviving fraction of cells. This data presentation allows a direct comparison of recombination levels at equitoxic concentrations of the two drugs. Representative data from one of three independent experiments is shown. ICRF-187 induces only low levels of H2AX phosphorylation in human SCLC cells as compared to m-AMSA Induction of γH2AX is a well-established marker for topoisomerase-induced DNA double strand breaks in mammalian cells [ 40 - 42 ]. We therefore assessed the effect of exposing human SCLC OC-NYH cells to 10 μM m-AMSA and 1 mM of ICRF-187 at increasing time points (figure 5A and 5B ). Exposure to 10 μM m-AMSA quickly resulted in γH2AX induction. Thus, induction was evident after 30 min, and after 24 hours more than 10-fold induction was observed. In contrast, when cells were exposed to 1 mM ICRF-187, much less γH2AX induction was observed, and after 24 hours the level of induction was less that three-fold. Figure 5 Assessing the effect of m-AMSA and ICRF-187 on γH2AX induction in human SCLC OC-NYH cells. To assess the level of DNA breaks in human cells after exposure to 10 μM m-AMSA and 1 mM ICRF-187 for increasing time points, total histones were isolated after incubation with the drugs. 10 μg of purified histones was then used in western blotting experiments. Panel A depicts a typical Western blot showing increased γH2AX induction with increasing drug incubation times. Panel B depicts fold γH2AX induction plotted against drug incubation time to analyse the kinetics of induction of DNA double strand breaks by the two drugs. Insert shows γH2AX induction from 0 to 2 hours for better resolution. Error-bars represent SEM of three independent experiments for ICRF-187 treatment and SEM of two independent experiments for m-AMSA treatment. Discussion We initiated the study by assessing the clonogenic sensitivity of yeast single-gene deletion mutants ectopically expressing human topoisomerase II α towards m-AMSA and ICRF-187. The results presented in table 2 and additional file 1 indicates that HR plays a role in the repair of ICRF-187-induced DNA damage. Previous studies addressing the bisdioxopiperazine sensitivity of yeast cells have generated different results. In one study rad52 -cells had the same sensitivity towards ICRF-187 and ICRF-193 as did RAD52 + cells [ 7 ], while in other studies, HR deficient cells were found to be hypersensitive towards bisdioxopiperazines, although to a much lesser extent than towards topoisomerase II cleavage complex stabilising drugs [ 43 , 44 ]. Our present study involving numerous other genes involved in various aspects of HR clearly establishes this pathway as being a functional determinant for bisdioxopiperazine sensitivity in yeast cells. In a recent work by Simon and colleagues, where a panel of yeast deletion strains was also applied to pinpoint the mechanism of action of various anticancer drugs, a given drug was classified as selective if one single pathway was mainly involved in determining cellular sensitivity [ 23 ]. The selective involvement of the HR pathway in determining the sensitivity towards ICRF-187 classifies this drug as highly selective according to this definition. However, it is important to note that although HR clearly does play a role in protecting yeast cells from ICRF-187 cytotoxicity, the importance of this pathway on cell survival in the presence of m-AMSA is much greater ( additional file 1 , table 2 ) – in accordance with this drug being a topoisomerase II poison killing cells solely by the generation of topoisomerase II-mediated DNA breaks. We find that the relative sensitivity of AA8, irs1SF, and CXR3 cells towards m-AMSA (figure 3 ) closely resembles their sensitivity towards etoposide [ 45 ], showing that the hypersensitivity of XRCC3 deficient irs1SF cells is general to topoisomerase II poisons, suggesting a role for HR in the repair of topoisomerase II-induced DNA breaks in these cells. The involvement of HR in the repair of DNA lesions induced by topoisomerase II poisons in higher eukaryotes is also supported by a recent work suggesting that RAD51 plays an important role in the repair of etoposide-induced DNA damage in human small cell lung cancer cells [ 46 ], and by work by Adachi and colleagues who recently found that knocking out RAD54 in chicken DT40 cells enhances their sensitivity towards the topoisomerase II poison etoposide [ 13 ]. We find that XRCC3 defective irs1SF cells are more sensitive towards ICRF-187 than the parental AA8 cells, although the XRCC3 defect has a much more pronounced effect on m-AMSA sensitivity (figure 3A versus figure 3B ) – as seen with the yeast deletion mutant panel. Adachi and colleagues have found that knocking out RAD54 in DT40 chicken cells does not increase sensitivity towards ICRF-193 [ 13 ]. The reason for this discrepancy in not clear. The difference observed between the DT40 and irs1SFcells may relate to the fact that different DNA repair genes are deleted in the two cell lines possibly resulting in different processing of bisdioxopiperazine-induced DNA damage. In any case, this discrepancy does not challenge the overall finding that HR plays a more important role in protecting cells of various origin from cytotoxicity induced by topoisomerase II poisons as compared to cytotoxicity induced by bisdioxopiperazines. To study the importance of NHEJ in determining the sensitivity towards m-AMSA and ICRF-187 we employed a DNA-PK cs defective hamster cell line, V3-3, which has reduced levels of NHEJ activity. We find that V3-3 cells are hypersensitive towards m-AMSA (figure 3A ). This result is in accordance with a recent publication by Willmore and colleagues who found that a specific small-molecule inhibitor of DNA-PK cs NU7026 could potentate the sensitivity of human leukemic K562 cells towards various topoisomerase II poisons [ 47 ]. Our result is also in accordance with a recent report by Adachi and colleagues showing that DNA-PK cs knockout chicken DT40 cells are hypersensitive towards etoposide [ 48 ]. These result points towards an important role of DNA-PK cs in determining the sensitivity of higher vertebrate cells towards topoisomerase II poisons. Different studies have demonstrated a more pronounced effect of inactivating Ku as compared to DNA-PK cs on cellular sensitivity towards topoisomerase II poisons [ 48 - 50 ]. Consequently, the importance of NHEJ in determining the sensitivity towards topoisomerase II poisons in mammalian cells is likely to be underestimated from our V3-3 cell data. This notion is confirmed by early publications demonstrating that Ku deficient hamster cells are highly sensitive towards m-AMSA and etoposide [ 51 , 52 ]. Our finding that V3-3 cells are more sensitive towards ICRF-187 than AA8 cells (figure 3B ) is also in accordance with observations by Adachi and colleagues who find that DNA-PK cs deficient chicken DT40 cells are hypersensitive towards another bisdioxopiperazine analog, ICRF-193. These authors found the effect of inactivating DNA-PK cs to be much more pronounced than seen in our present study. While the reason for this difference is not clear, it has to be mentioned that studies addressing the effect of DNA-PK cs on the sensitivity towards topoisomerase II targeting drugs and ionising radiation have produced varying results. Thus, in a study by Jin and colleagues, DNA-PK cs defective murine cells were much less sensitive towards etoposide than Ku70 and Ku80 deficient cells [ 50 ], while in a study by Gao and colleagues the importance of DNA-PK cs on the sensitivity towards ionising radiation was found to depend on cell type and/or cell cycle distribution [ 49 ]. Such variation could well explain the different importance of DNA-PK cs observed in our study and in the work by Adachi and colleagues. In order to study directly the effect of exposing mammalian cells to ICRF-187 and m-AMSA on the levels of HR, we employed a mammalian recombination assay previously described [ 39 ]. In this assay, m-AMSA enhanced the level of recombination in SPD8 cells to higher levels than ICRF-187 at all cytotoxicity levels tested (figure 4C ), demonstrating directly pronounced differences in the mechanism(s) by which topoisomerase II poisons and bisdioxopiperazines kill cells. This notion is further confirmed by our γH2AX induction experiments, where ICRF-187 causes much lower levels of induction (figure 5 ), demonstrating that ICRF-187 induces less DNA breaks in cells than m-AMSA. Our observation that ICRF-187 induces both HR and γH2AX induction in mammalian cells, is in agreement with a recent paper demonstrating by the use of comet assay and pulsed field gel electroforesis that ICRF-193 induces DNA breaks in mammalian cells [ 16 ]. This result is also in agreement with our real-time PCR results where ICRF-187 tended to induce the expression of established DNA damage-inducible genes. The finding that ICRF-187 induces lower levels of HR than m-AMSA in SPD8 cells at equitoxic doses may be explained in at least two ways. Bisdioxopiperazine-induced DNA breaks could be more toxic to cells than breaks induced by topoisomerase II poisons, or the DNA breaks could be only partly responsible for killing the cells. Three lines of evidence support the latter possibility. ( i ) Functional ATR, but not ATM, is required for a cell cycle checkpoint arrest induced by ICRF-193 [ 53 ], suggesting that DNA breaks are not involved in triggering the checkpoint signal. ( ii ) Exposure of mammalian cells to the topoisomerase II poison etoposide induces degradation of the large subunit of RNA polymerase II indicative of DNA breaks, while this is not the case for ICRF-193 [ 14 ]. ( iii ) Our finding that cell survival in the presence of ICRF-187 depends less on HR than cell survival in the presence of m-AMSA suggests that ICRF-187-induced DNA breaks contribute less to overall cytotoxicity than m-AMSA-induced DNA breaks. If ICRF-187-induced DNA breaks were more toxic to cells than m-AMSA-induced DNA breaks, cell survival in the presence of ICRF-187 would be expected to depend at least as much on HR as cell survival in the presence of m-AMSA. This is not the case. What mechanisms are then responsible for producing the DNA breaks induced by bisdioxopiperazines in cells? In a recent work by Oestergaard and colleagues).)[ 17 ], it is suggested that the toxic intermediate causing bisdioxopiperazine cytotoxicity is topoisomerase II stably bound to two DNA segments – a conformation they suggested would only be attainable if the DNA strand passage reaction of topoisomerase II is functioning. HR could then be required for the repair of DNA breaks generated by the collision of DNA tracking complexes with such four-way DNA junctions / topoisomerase II closed clamp complexes on DNA. It has recently been demonstrated by the use of pulsed field gel electrophoresis, that inhibiting DNA replication by aphidicolin does not reduce the level of DNA breaks generated by exposure of mammalian cells to ICRF193, while the level of m-AMSA-induced DNA breaks was reduced by aphidicolin treatment [ 16 ]. This result suggests that collision of the DNA replication complex with bisdioxopiperazine-induced topoisomerase II closed clamp complex on DNA is not involved in generating the DNA breaks. In a recent study by Lundin and colleagues, it was demonstrated that inhibiting DNA replication by exposing cells to hydroxyurea resulted in the generation of DNA breaks [ 54 ]. Furthermore, in this work as well as in a subsequent work [ 45 ], HR was shown to be functionally involved in repairing such DNA breaks. The first of these two studies used the same four hamster cell lines that are also used in our present study. Remarkably, the relative sensitivity of these cell lines towards hydroxyurea exactly resembles their sensitivity towards ICRF-187 seen in our present work. This may suggest that replication arrest is involved in generating DNA breaks induced by bisdioxopiperazines in cells. Here, replication forks stalled at the bisdioxopiperazine-induced closed clamp complexes could be the source of DNA breaks in newly replicated DNA [ 54 ]. This would also explain the lack of effect of aphidicolin on the level of ICRF-193-induced DNA breaks observed by Hajji and colleagues [ 16 ]. If the DNA breaks result from arrested replications forks, and not from the collision of the DNA replication complex with the closed clamp complex on DNA, no effect of aphidicolin would be expected. This mechanism would also explain why yeast cells arrested in intra-S phase are not protected from ICRF-193 cytotoxicity [ 7 ]. We therefore suggest that this mechanism is responsible for generating DNA breaks induced by bisdioxopiperazines in cells. Together our HR, γH2AX, and cytotoxicity data suggest that bisdioxopiperazines kill cells by a combination of DNA break-related and DNA break-unrelated mechanisms. This raises the question as to which mechanism(s) is / are involved in mediating the DNA break-unrelated part of bisdioxopiperazine cytotoxicity. Exposure of mammalian cells to ICRF-193 represses global transcription and mediates selective degradation of topoisomerase II β via a transcription dependent mechanism [ 14 ]. Inhibition of the RNA polymerase II – transcription complex by bisdioxopiperazine-induced topoisomerase II complexes on DNA could therefore be involved in mediating the DNA break-unrelated component of bisdioxopiperazine cytotoxicity. Treatment of mammalian cells with high doses of ICRF-187 for one hour is capable of antagonising DNA breaks and the cytotoxicity of topoisomerase II poisons [ 55 , 56 ], and this antagonism can be extended to animal models, where ICRF-187 can antagonise etoposide toxicity [ 57 , 58 ] and bone marrow depression (unpublished results). How are bisdioxopiperazines capable of antagonising the effects of topoisomerase II while at the same time producing DNA breaks? Two independent studies assessing the dose- and schedule-dependency of combinations of bisdioxopiperazines and topoisomerase II poisons on cytotoxicity in mammalian cells may provide important clues. One study investigated the effect of combinations of ICRF-193 and etoposide [ 59 ]. Here, continuous administration of low doses of both drugs resulted in synergistic cell kill, while treatment with high concentrations of ICRF-193 for one hour efficiently antagonised etoposide-mediated cytotoxicity. A similar effect of schedule and concentration on cytotoxicity has also been observed for combinations of ICRF-187 and daunorubicin [ 60 ], but here long time exposure of the cells to both drugs resulted in an additive effect on cell kill. We have previously shown that exposure of mammalian cells to high concentrations of ICRF-187 (500 – 1000 μM) alone for 60 min is non-toxic, and that this treatment efficiently antagonises etoposide-induced DNA breaks and cytotoxicity [ 61 , 62 ]. In these studies, exposure of cells to 200 μM ICRF-187 was found to trap most cellular topoisomerase II α and β as non-extractable complexes on DNA. The inability of topoisomerase II poisons to act on bisdioxopiperazine-stabilised closed clamp complexes on DNA could therefore explain the antagonistic effect of high concentrations of bisdioxopiperazines generally observed in one-hour drug exposure experiments [ 59 - 62 ]. When a low concentration of bisdioxopiperazine is administered, it is most likely that only a small fraction of the topoisomerase II molecules in the cell is trapped as closed clamp complexes on DNA, leaving some or most topoisomerase II molecules available for the action of topoisomerase II poisons. Therefore, after long-time exposure of cells to low concentrations of bisdioxopiperazine and a topoisomerase II poison, covalent and non-covalent complexes of topoisomerase II on DNA could both contribute to cytotoxicity by generating DNA breaks via different mechanisms, thus explaining the additive or synergistic effect on cell kill observed under these circumstances. To summarise, our data are consistent with a model where bisdioxopiperazine-induced cytotoxicity results from a combination of DNA break-related and -unrelated mechanisms, where the DNA-break unrelated mechanism is clearly not mediated by the inhibition of catalytic topoisomerase II activity in the cells. Conclusion Since the discovery by Andoh and colleagues in 1991, that the bisdioxopiperazines target eukaryotic topoisomerase II [ 63 , 64 ], their mode of cytotoxicity has been the cause of debate. While early publications tended to classify these compounds as "pure" catalytic inhibitors of topoisomerase II, expected to kill cells by depriving them of essential topoisomerase II catalytic activity, numerous recent reports present data that are not consistent with this view [ 7 , 11 - 14 , 16 , 17 ]. In the present report we have characterised bisdioxopiperazine (ICRF-187) induced cytotoxicity in yeast and mammalian cells by using a combination of genetic and molecular approaches. Our results are consistent with a model where bisdioxopiperazines cause cytotoxicity by stabilising a topoisomerase II reaction intermediate / complex on DNA inducing DNA breaks in cells which are repaired by HR and NHEJ. We propose that cells exposed to bisdioxopiperazines die by a combination of DNA break-related and-DNA break-unrelated mechanisms. Our study clearly establishes that bisdioxopiperazines do not kill cells solely by depriving them of topoisomerase II catalytic activity. Methods Drugs ICRF-187 (Cardioxane, Chiron group) was dissolved in sterile water at 20 mg/ml and kept at – 80°C. To avoid hydrolysis of the drug, fresh aliquots were used for each experiment. m-AMSA (Pfizer) was diluted in DMSO and stored at – 80°C at 1 mg/ml. L-azaserine and thymidine (both from Sigma) were added directly to tissue culture medium. 6-thioguanine and hypoxanthine (both from Sigma) were dissolved in 5 M NaOH and immediately added to the tissue culture medium. Yeast strains and constructs BY4741 haploid Saccharomyces cerevisiae cells ( MAT a his3 Δ 1 leu2 Δ 0 met15 Δ 0 ura3 Δ 0 ) and a panel of single-gene deletion derivatives hereof (table 1 ) were purchased from EUROSCARF, Institute of Microbiology, Johann Wolfgang Goethe University Frankfurt, Germany. The construction of BY4741 and its deletion derivatives have been described [ 65 ]. JN362A t2–4 cells with the relevant genotype ( MAT a ura3 – 52 leu2 trp1 his7 ade1 – 2 ISE2 top2 - 4 ) were kindly provided by Dr. John L. Nitiss, St. Jude Children's Research Hospital, Memphis TN, USA. This strain and the construct for functional expression of human topoisomerase II α in yeast pMJ1 ( URA3 ) have been described previously [ 66 ]. All yeast strains were transformed with pMJ1 to functionally express human topoisomerase II α in a cell cycle independent fashion. BY4741 wild-type and Δ rad6 , Δ rad50 , Δ rad52 , Δ sae2 and Δ yku70 cells were also transformed with an empty URA3 vector (pYX112). The ICRF-187 and m-AMSA sensitivity of pYX112-transformed cells was assessed to assure that the drug sensitivity of the pMJ1-transformed cells (Table 2 , S1) is related to the ectopic expression of human topoisomerase II α in the cells, which was the case. Transformation and selection was carried out according to standard procedures using lithium acetate cell wall permeabilisation and PEG-mediated DNA uptake by using single-stranded DNA as carrier as described [ 67 ]. Selection was done on SC-URA plates. Three independent pMJ1-transformed yeast clones were selected and propagated for each transformation. All strains were propagated at 30°C, to be subsequently used in clonogenic assays at 34°C. Yeast clonogenic assay The clonogenic sensitivity of the yeast cells towards ICRF-187 and m-AMSA was determined using a clonogenic assay essentially performed as described in [ 7 ]. Briefly, overnight cultures of the strains were grown in SC-URA medium at 34°C at 200 rpm. Cells in log phase were diluted to 2 × 10 6 cells/ml in pre-warmed YPD medium, and 3 ml cultures were exposed to different concentrations of drug at 34°C for 22.5 hours. After drug exposure the samples were diluted up to 10 5 times (depending on the combination of strain and drug used) in distilled sterile water. Yeast cells that were not diluted before plating were spun down by brief centrifugation, and re-suspended in the same volume of sterile water. Next, 200 μl of diluted cells were transferred to SC-URA plates, which were incubated for 5 days at 30°C before counting. 200 to 600 colonies were typically counted for each drug concentration in each single experiment. Finally, the relative survival at the different drug concentrations as compared to the no drug sample was calculated to generate dose-response curves. For each combination of yeast strain and drug, at least three dose-response curves were generated using pMJ1-transformed cells from at least two independent clones (mostly from three). Yeast microarray gene expression analysis Microarray experiments were performed with yeast strain JN362 t2–4 transformed with pMJ1 to functionally express human topoisomerase II α. Fresh colonies were inoculated into YPD medium and grown overnight at 34°C, 180 rpm. The cultures were then diluted to obtain an OD 600 of 0.2. Cultures of 50 ml in YPD medium were first grown for two hours to assure exponential growth of the cells. 1 mg/ml ICRF-187 or 50 μg/ml m-AMSA (equitoxic concentrations) were then added to the cell cultures (a no-drug sample was also included), and the cells were grown for an additional two hours. Each treatment was performed in duplicate. The used concentration of both drugs resulted in a reduction in the clonogenecity of the cells of 50 %. After treatment cells were harvested by centrifugation. Total RNA was isolated by the hot acidic phenol method [ 69 ]. All the steps for cDNA synthesis, cRNA synthesis, biotin labeling and array hybridization to Affymetrix S98 yeast arrays were performed as described in the Affymetrix GeneChip Expression Analysis Technical Manual (Affymetrix), and performed at the microarray core facility at Rigshospitalet, Copenhagen Denmark. Briefly, cDNA was synthesized from 5 μg RNA using a (dT) 24 primer containing a T7 RNA polymerase promoter sequence and SuperScript II reverse transcriptase (Invitrogen) for 1 h at 42°C followed by second-strand synthesis using DNA polymerase I and RNase H digestion followed by isolation of cDNA using GeneChip Sample Cleanup Module (Affymetrix). The cDNA was used as template for synthesis of biotin-labeled cRNA by incubation with biotin-labeled ribonucleotides and T7 RNA polymerase for 5 h at 37°C. Biotin-labeled cRNA was purified using GeneChip Sample Cleanup Module. Biotinylated cRNA was fragmented and 15 μg used for hybridization to Affymetrix Yeast Genome S98 arrays at 45°C for 16 h as described in the Affymetrix users' manual. Washing and array staining with streptavidin-phytoerythrin were performed using the GeneChip Fluidics Station 400 and scanning was performed with a Gene Array Scanner G25 (Agilent technology). Data was analyzed using the DNA-Chip Analyzer (dChip) software [ 70 ]. Real-time PCR analysis The RNA preparations used for microarray analyses were also used for real-time PCR. This analysis was performed on an ABIPrism 7900HT (Applied Biosystems). RNA samples were DNase treated using the DNA-free™ DNase treatment and removal kit (Ambion), and RNA concentrations were measured before conversion to cDNA using the TaqMan RT kit (Applied Bioscience). Priming was performed by random hexamers converting 2 μg RNA pr 100 μl reaction volume, to make 20 ng/μl cDNA. Primers were designed for coding sequences from the Saccharomyces genome database using the Primer 3 input program . All primers were purchased at DNA Technology A/S, with melting temperatures close to 60°C. Reaction mixtures containing the following components at the indicated end-concentrations were prepared. To make a total of 40 μl in sterile water, 20 μl 1x SYBR ® green PCR master mix (Applied Biosystems), 250 nM forward primer, 250 nM reverse primer, and 5 ng template was mixed. Cycling conditions: 95°C for 10 min, followed by 40–45 cycles of 95°C for 15 s and 60°C for 60 s. Relative values of gene expression were calculated with untreated samples as calibrator, and normalized to levels of actin, according to the 2 -ΔΔCt method [ 71 ] and (User bulletin #2, AbiPrism 7700 Sequence Detection System, Applied Biosystems) after primer optimisation and target efficiency evaluation. The following primers were used: HUG1 -forward, AGGCCTTAACCCAAAGCAAT; HUG1 -reverse, TCTTGTTGACACGGTTGCTC; RNR3 -forvard, ATGCATCTCCAGTTCCATCC; RNR3 -reverse, GGGGCAACACTATCTTCCAA; RAD51 -forward, GTGGCGGTGAAGGTAAGTGT; RAD51 -reverse, GTCTAATCCGAACCGCTGAG; RAD54 -forward, CTAAAGCAGGTGGGTGTGGT; RAD54 -reverse, CTTGTTGATCAGCAGCAGGA; ACT1 -forward, CGGTGATGGTGTTACTCACG; ACT1 -reverse, GGCCAAATCGATTCTCAAAA. Mammalian cells The CHO cell lines AA8, irs1SF, CXR3, V3-3, and the hamster lung fibroblast cell line SPD8 were kindly provided by Dr Thomas Helleday, University of Sheffield, UK. AA8 is a wild-type cell line. The AA8-derived irs1SF cell line is XRCC3-defective and has reduced levels of HR [ 37 ]. CXR3 is a human- XRCC3 -cosmid complemented strain of irs1SF, which is proficient in HR [ 37 ]. The V3-3 cell line is DNA-PK cs -deficient and consequently deficient in NHEJ [ 38 ]. The SPD8 cells carry a non-functional hprt gene that can be repaired by HR [ 39 ]. HPRT + cells can then be selected on HAsT medium containing hypoxanthine, L-azaserine and thymidine. When SPD8 cells were not used in the recombination assay they were propagated in medium supplemented with 6-thioguanine to select against spontaneous reversion to the HPRT + phenotype. Human SCLC OC-NYH cells have been described [ 72 ]. Hamster cells were propagated in DMEM medium and OC-NYH cells were propagated in RPMI-1640 medium. All cell culture media were supplemented with 10 % fetal calf serum and 100 U/ml penicillin-streptomycin. Cells were grown in a humidified atmosphere containing 5 % CO 2 in the dark at 37°C. Determination of topoisomerase II activity in crude cell extracts Topoisomerase II activity in crude extract was determined by using a decatenation assay previously described [ 68 ]. Briefly, 200 ng 3 H labeled kDNA isolated from C. fasciculata was incubated with increasing amounts of crude extracts in 20 μl reaction buffer containing 10 mM TRIS-HCl pH 7.7, 50 mM NaCl, 50 mM KCl, 5 mM MgCl 2 , 1 mM EDTA, 15 μg/ml BSA and 1 mM ATP for 20 min at 37°C. After addition of 5x stop buffer (5 % Sarkosyl, 0.0025 % bromophenol blue and 50 % glycerol), unprocessed kDNA network and decatenated DNA circles were separated by filtering, and the amount of unprocessed kDNA in each reaction was determined by scintillation counting. The amount of crude extract required to fully decatenate 200 ng of kDNA under these assay conditions (which is equivalent to 1 U of catalytic activity) was then determined, and the specific activity of the crude extract was calculated as U/μg protein. Mammalian clonogenic assay Four hours prior to continuous treatment with either ICRF-187 or m-AMSA, 250 cells of each of the hamster cell lines were plated onto 100 mm dishes. After 7 days colonies were fixed and strained in methylene blue in methanol (4 mg/ml), and colonies with more than 50 cells were counted. Finally, the relative survival compared to the no drug treatment was calculated, and plotted against drug concentrations to generate dose-response curves. 150 – 250 colonies were typically counted in the "no drug" dishes. Mammalian homologous recombination assay A mammalian recombination assay was performed as described [ 39 ]. Briefly, 1 × 10 6 SPD8 cells were inoculated into 75 cm 2 flasks. When transferred, 6-thioguanine was omitted from the medium. Cells were trypsinised and resuspended in 10 ml medium at 100,000 cells/ml, and exposed to the indicated drug concentrations for 24 hours. To determine clonogenic survival, for each drug-treatment 500 cells were transferred to each of two 100 mm petri dishes containing 10 ml of non-selecting medium and the cells were cultured for 7 days. For selection of recombination events, 300,000 cells were transferred to each of three 100 mm petri dishes containing 10 ml medium supplemented with 50 μM hypoxanthine, 10 μM L-azaserine and 5 μM thymidine and selection was carried out for 10 days. Colonies were fixed by using methylene blue in methanol (4 mg/ml) and counted. Finally, the recombination frequency was determined as the plating efficiency in recombination selective medium divided by the plating efficiency in normal medium, for all concentrations of ICRF-187 or m-AMSA. To enable comparison of recombination frequency at equitoxic levels of m-AMSA and ICRF-187, the recombination frequency was plotted against the relative clonogenic survival of cells receiving only drug. Histone purification Human SCLC OC-NYH cells were grown to sub-confluence and histones were extracted as follows. After the relevant drug treatments, the cells were pelleted and washed in cold PBS, and lysed in lysis buffer (10 mM TRIS-HCl pH = 6.5, 50 mM Sodium Bisulphate, 1% Triton X-100, 10 mM MgCl, 8.6% sucrose) at 4°C by applying 20 strokes in a tight fitting Dounce homogenizer. Released nuclei were pelleted by centrifugation at 2500 g for 10 min at 4°C, and washed in lysis buffer followed by wash buffer (10 mM TRIS-HCl, 13 mM EDTA pH 7.4). The pellet was next resuspended in 100 μl ice-cold 0.4 M H 2 SO 4 , and incubated for 1 hour at 4°C prior to centrifugation. The supernatant was transferred to a clean tube and 1 ml ice-cold acetone was added followed by incubation overnight for histone precipitation. After centrifugation, the pellet was air-dried and resuspended in 40 μl H 2 O, and the protein concentration was determined by Bradford protein assay (Bio-Rad Laboratories) γH2AX western blot Western blotting was performed by loading 10 μg of total histones on a 4–12% gradient gel (NuPageTM Bis-Tris Gel, Invitrogen). Separated proteins were transferred to nitrocellulose membranes (Bio-Rad) which were blocked in 10% skimmed milk (Fluka) and incubated overnight with anti γH2AX primary antibody diluted 1:500 (Upstate Technology, cat no 16–193) followed by detection with goat-anti-mouse (Amersham) 1:2000 for one hour. Detection with ECL Plus™(Amersham) was performed by scanning on STORM™ 840 (Molecular Dynamics Inc), on which the image was optimized and bands quantified by Image Quant™ version 5.0 (Molecular Dynamics). List of abbreviations used BER, Base Excision Repair; CHO, chinese hamster ovary; HR, Homologous Recombination; ICRF-187, (+)-1,2-bis(3,5-dioxopiperazinyl-1-yl)propane; m-AMSA, (N-[4-(9-acridinylamino)-3-methoxyphenyl]methanesulphonanilide); MMR, Mismatch Repair; NER, Nucleotide Excision Repair; NHEJ, Non-Homologous End Joining; PCR, Polymerase Chain Reaction; PRR, Post Replication Repair; SCLC, Small Cell Lung Cancer; SC-URA, Synthetic medium lacking uracil; SSA, Single Strand Anealing; YPD, Medium containing Yeast extract, Peptone and Dextrose. Authors' contributions Lars H. Jensen: Participated in planning the experiments, performed yeast transformations and clonogenic assays, and prepared the manuscript. Marielle Dejligbjerg : Performed γH2AX western blots, primer design, real-time PCR experiments, and data quantitation. Lasse T. Hansen : Performed mammalian clonogenic assays and recombination assays. Morten Grauslund: Performed RNA purification and microarray analysis. Peter B. Jensen : Participated in planning and monitoring the study. Maxwell Sehested: Participated in the initiation and conduction of the study. All authors read and approved the final manuscript. Supplementary Material Additional file 1 Clonogenic sensitivity of mutant single-gene deletion yeast strains towards ICRF-187 and m-AMSA. Clonogenic sensitivity of a panel of human topoisomerase II α-transformed haploid yeast deletion strains towards equitoxic (to wt cells) concentrations of ICRF-187 and m-AMSA. Error-bars represent SEM of 3 – 10 independent experiments. Click here for file Additional file 2 Level of killing of yeast cells used in transcriptional profiling experiments. Fresh colonies of pMJ1-transformed JN362A t2–4 cells were inoculated into YPD medium and grown overnight at 34°C, 150 rpm. The cultures were then diluted into 50 ml YPD medium to obtain an OD 600 of 0.2. After growing the cells for 2 hours to assure exponential growth, equitoxic concentrations of ICRF-187 and m-AMSA were applied and the cells were grown for an additional 2 hours before RNA was isolated. The figure depicts the clonogenecity of drug treated and untreated cells. Exposure of the cells to the two drugs resulted in a reduction of their clonogenecity of approx. 50 %. Error bars-represent SEM of three independent experiments. Click here for file Additional file 3 Transcriptional response towards ICRF-187. A list of yeast genes whose average expression in two independent experiments is induced or repressed more than 1.5 fold by exposure to ICRF-187. Click here for file Additional file 4 Transcriptional response towards m-AMSA. A list of yeast genes whose average expression in two independent experiments is induced or repressed more than 1.5 fold by exposure to m-AMSA. Click here for file Additional file 5 Topoisomerase II activity levels in hamster cell lines. The levels of topoisomerase II catalytic activity in crude extracts from wt and recombination defective hamster cell lines. Error-bars represent SEM of two independent experiments. No difference in the level of topoisomerase II catalytic (DNA strand passage activity) is observed. Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545072.xml
546221	Stable expression of constitutively-activated STAT3 in benign prostatic epithelial cells changes their phenotype to that resembling malignant cells	Background Signal transducers and activators of transcription (STATs) are involved in growth regulation of cells. They are usually activated by phosphorylation at specific tyrosine residues. In neoplastic cells, constitutive activation of STATs accompanies growth dysregulation and resistance to apoptosis through changes in gene expression, such as enhanced anti-apoptotic gene expression or reduced pro-apoptotic gene expression. Activated STAT3 is thought to play an important role in prostate cancer (PCA) progression. Because we are interested in how persistently-activated STAT3 changes the cellular phenotype to a malignant one in prostate cancer, we used expression vectors containing a gene for constitutively-activated STAT3, called S3c, into NRP-152 rat and BPH-1 human benign prostatic epithelial cells. Results We observed that prostatic cell lines stably expressing S3c required STAT3 expression for survival, because they became sensitive to antisense oligonucleotide for STAT3. However, S3c-transfected cells were not sensitive to the effects of JAK inhibitors, meaning that STAT3 was constitutively-activated in these transfected cell lines. NRP-152 prostatic epithelial cells lost the requirement for exogenous growth factors. Furthermore, we observed that NRP-152 expressing S3c had enhanced mRNA levels of retinoic acid receptor (RAR)-α, reduced mRNA levels of RAR-β and -γ, while BPH-1 cells transfected with S3c became insensitive to the effects of androgen, and also to the effects of a testosterone antagonist. Both S3c-transfected cell lines grew in soft agar after stable transfection with S3c, however neither S3c-transfected cell line was tumorigenic in severe-combined immunodeficient mice. Conclusions We conclude, based on our findings, that persistently-activated STAT3 is an important molecular marker of prostate cancer, which develops in formerly benign prostate cells and changes their phenotype to one more closely resembling transformed prostate cells. That the S3c-transfected cell lines require the continued expression of S3c demonstrates that a significant phenotypic change occurred in the cells. These conclusions are based on our data with respect to loss of growth factor requirement, loss of androgen response, gain of growth in soft agar, and changes in RAR subunit expression, all of which are consistent with a malignant phenotype in prostate cancer. However, an additional genetic change may be required for S3c-transfected prostate cells to become tumorigenic.	Introduction Signal transducers and activators of gene transcription (STATs) are, as their name suggests, proteins that regulate gene expression by affecting transcription. They are part of the signal transduction pathway used by many growth factors and cytokines, and are activated by phosphorylation of tyrosine and serine residues by up-stream kinases [ 1 ]. For example, signaling by IL-6 and other members of this cytokine family generally induces phosphorylation of STAT3 [ 1 , 2 ]. In the example given in Figure 1 , IL-6-induced binding to its receptor leads to homodimerization of the receptor, which in turn leads to autophosphorylation of the cytosolic domain of gp130; this in turn causes the phosphorylation of one of 3 kinases, JAK1, JAK2, or Tyk 2. The activated up-stream kinase phosphorylates STAT3, which allows for dimerization of STAT3 although this concept is currently being revisited, since it has been shown in hepatic cells under inflammatory stress, there is evidence for STAT3 association on lipid rafts prior to phosphorylation [ 3 , 4 ] in association with chaperone proteins such as Hsp90 (reviewed in [ 5 ]); however only the dimer form of STAT3 can translocate and bind to DNA at specific binding sites, thereby directing transcription of target genes. In benign cells, the signaling by STAT3 is under tight regulation, so that the signal delivered to the cell is transient. However aberrant signaling by STAT3 has been noted in many types of malignancies, such as myeloma, head and neck cancer, breast cancer, and prostate cancer [ 6 - 9 ]. Such persistent signaling by IL-6 leading to aberrant activation of STAT3 is thought to play a role in neoplastic progression of prostate cells [ 10 ]. Importantly, we and others have shown that malignant prostate cells expressing persistently-activated STAT3 become dependent upon this transcription factor for survival, resulting in apoptosis [ 11 - 13 ]. Thus, persistently-activated STAT3 fulfills the criteria of a proto-oncogene [ 14 , 15 ]. Figure 1 An example of cytokine-mediated activation of STAT3. In this example, IL-6-induced binding to its receptor leads to homodimerization of the receptor, which in turn leads to autophosphorylation of the cytosolic domain of gp130; this in turn causes the phosphorylation of one of 3 kinases, JAK1, JAK2, or Tyk 2. The activated up-stream kinase phosphorylates STAT3, which allows for dimerization of STAT3; only the dimer can translocate and dock to DNA at target genes, thereby directing transcription. Prostate cancer (PCA) is the second most frequently diagnosed non-cutaneous malignancy in American males, affecting approximately 35% of them according to recent data [ 16 , 17 ]. This translates into approximately 35,000 deaths last year in the United States alone; 189,000 new cases were diagnosed in 2002 and over 220,000 cases were projected for 2003 [ 18 , 19 ]. Moreover, in a recent report the authors claimed that 30% of male mortality overall may be due to prostate cancer [ 20 ]. For the most effective therapy with the fewest side-effects, a thorough understanding of the genes involved in the neoplastic process is essential. Androgens are known to play a critical role in the tumorigenic process, with activity mediated by the androgen receptor. Initially, prostate cancers are androgen-sensitive (that is, they cease growing when deprived of androgens or when treated with androgen receptor antagonists, such as flutamide or bicalutamide), and therefore most patients respond to androgen ablation therapy. However, there are side-effects to this therapy that make it unpleasant for the patient [ 21 ]. Even with androgen ablation therapy, the disease often recurs and when it does, it usually becomes androgen-insensitive or hormone-refractory [ 22 ]. There is evidence that STAT3 activation via IL-6 plays a role in the conversion of normal prostate cells to prostate cancer cells, and from androgen-responsive to the androgen insensitive phenotype [ 10 , 23 , 24 ]. The progression to androgen-independence has been found to be associated with IL-6, with c-myc expression, and with insulin-like growth factors, all of which can signal through the activation of STAT3 [ 25 - 28 ]. STAT3 is negatively regulated by a retinoid-sensitive protein, GRIM-19, which may explain the positive effects retinoids show against prostate cancer cells in vitro [ 29 - 31 ]. Retinoid therapy for the treatment of prostate cancer is currently being tested, due to the ability of these compounds to rapidly induce apoptosis [ 32 ]. Indeed, the recent addition of Taxotere to the pharmacopeia for prostate cancer may well be due to its demonstrated effect on retinoid receptors [ 33 ]. The regulation of the expression of the 3 retinoid receptors type A (RAR-α, -β, and -γ) in the progession to prostate cancer has been partially addressed by Richter, et al., who showed the differential effects of all- trans retinoic acid in human prostate cancer lines [ 34 , 35 ] To this end we are studying the oncogenic role of STAT3 activation in rat prostate epithelial cell lines NRP-152 [ 36 ] and human benign prostatic hyperplasia line BPH-1 [ 37 , 38 ]. Our main hypothesis is that constitutively-activated STAT3 (cSTAT3) plays an essential role in the development of PCA and the maintenance of the malignant phenotype. Because prostate epithelial cells become hypertrophic, but rarely malignant, they are useful for studying the progression to neoplasia to see how a relatively transformation-resistant cell type becomes neoplastic through cSTAT3. We previously determined that STAT3 was constitutively phosphorylated (hence activated) in malignant NRP-154 but not in NRP-152 cells, even when the NRP-152 cells were treated with testosterone [ 10 ]. We hypothesized that cSTAT3 may account for the tumorigenicity of NRP-154 cells, and therefore may play a determining role in the progression from hyperplasia to neoplasia. To test our hypothesis, we transfected a plasmid containing a mutated gene for STAT3 known as S3c, in which a Cys residue was substituted for an Ala residue, thereby allowing the dimerization of the mutated STAT3, which can then translocate across the nuclear membrane and effect gene transcription in much the same way as the phosphorphylated wild-type STAT3 gene product [ 14 , 39 ] into NRP-152 and BPH-1 cells. We then examined the phenotype of the selected transfected cells after cloning by limit dilution. Our results, indicating that NRP-152 and BPH-1 cells underwent changes in phenotype consistent with that of malignant cells, are presented here. Results Selection of Transfected NRP-152 and BPH-1 Cells Two weeks after transfection with either pIRES or pIRES-S3c and selection with G418, no surviving cells were observed in the wells that received Clonfectin only. Growth of cells was observed in all wells that received either of the plasmids plus Clonfectin. Transfected cells were expanded for further analysis in complete medium. A summary of cells and clones and what their phenotypes were is given in Table 1 . To summarize briefly, since the full results will be discussed in this section, we observed the following changes: Table 1 Summary of transfected cells Growth Factor G418 FLAG EGFP Growth In Cell Plasmid Dependence Sensitivity Epitope Expression Simple Medium NRP-152 none x x - - - 152-pIRES pIRES-EGFP x - - x - 152-S3c pIRES-S3c - - x x x BPH-1 none n/a x - - n/a BPH-pIRES pIRES-EGFP n/a - - x n/a BPH-S3c pIRES-S3c n/a - x x n/a The table summarizes the cells used or made in the experiments described. Cells were transfected with the indicated plasmid, as described in Materials & Methods. G418 was added at 400 μg/ml. Growth factors were those added to 152 medium, but not to 154 medium, as described in Materials and Methods, for NRP-152 cells and transfectants. X = presence of characteristic; --- = absence of characteristic. NRP-152 cells require a variety of growth factors and additives in their medium (see Materials and Methods Section; [ 36 ]); 152-pIRES cells (NRP-152 cells transfected with pIRES-EGFP) required the same medium as NRP-152 cells. But 152-S3c cells grew in DMEM/Ham's F12 supplemented only with 10% newborn calf serum. Moreover, 152-S3c cells expressed EGFP (as did 152-pIRES, which was expected since they were transfected with pIRES-EGFP) and the FLAG epitope, which is part of the S3c gene [ 40 ]. Both 152-pIRES and 152-S3c cells grew in the presence of G418. BPH-1 cells grow in RPMI-1640 supplemented with bovine serum; therefore this line does not have growth factor dependence to begin with. BPH-pIRES and BPH-S3c cells, aside from exhibiting G418 resistance, expressed EGFP, but only BPH-S3c expressed the FLAG epitope of the S3c gene. The evidence for these observations given in Table 1 is presented in the rest of this section. Expression of FLAG and EGFP in 152-S3c and BPH-S3c Cells Was Observed After Transfection and Selection with Antibiotics After no viable cells were observed following antibiotic treatment, we analyzed transfected cells for the presence of the markers flanking the S3c gene on the plasmids used, FLAG and EGFP. The analyses were done by flow cytometry on a FACScan; also by Western blot using specific Abs, and the results are presented in Figure 2 . In Panels A through D, the mean fluorescence intensities of representative clones of 152-S3c and BPH-S3c cells stained with monoclonal Ab to FLAG plus fluorescent goat anti-mouse F(ab 2 )', as well as the enhanced green fluorescent protein fluorescence intensities of transfected cells, are shown. Panel A displays the anti-FLAG fluorescence intensity of 1 representative clone of 152-S3c (thin line) compared to untransfected NRP-152 cells (thick line); approximately 95% of the 152-S3c cells stained with the anti-FLAG antibody. Similary, Panel B shows the fluorescence intensity of anti-FLAG-stained BPH-1 cells (thin line) compared to anti-FLAG-stained BPH-S3c clone (thick line), where approximately 76% of the BPH-S3c cells stained with the anti-FLAG antibody. Panels C and D display the EGFP fluorescence for clones of 152-S3c and BPH-S3c cells, compared with untransfected cells, respectively. In Panel C , the thick line shows the fluorescence intensity of EGFP in 152-S3c and the thin line shows the lack of EGFP fluorescence in the untransfected NRP-152 cells. Approximately 67% of the 152-S3c cells showed EGFP fluorescence. In Panel D , the thin line shows the EGFP fluorescence intensity of BPH-S3c cells, while the thick line shows it for untransfected BPH-1 cells. Approximately 45% of the BPH-S3c cells showed fluorescence due to EGFP. We concluded that in addition to antibiotic resistance, the transfected cells expressed markers flanking the S3c gene, and therefore we could attribute any change in phenotype of the cells to the expression of the S3c, in comparison to the vector-transfected cells. Panel E shows the results of immunoprecipitation with anti-FLAG Ab, followed by Western blot to detect EGFP. We used anti-FLAG Ab for the immunoprecipitation because (1) a S3c-specific Ab is not available, and (2) because all cells express STAT3. Thus, because expression of FLAG equates with expression of S3c specifically, immunoprecipitating with anti-FLAG would reveal the S3c-expressing cells. As seen in Figure 2E , the bands corresponding to 27 kD EGFP are visible only in the lanes from 152-S3c and BPH-S3c cells, while no EGFP bands are visible in the bands from the parental lines NRP-152 and BPH-1 cells. Since the EGFP gene is 3' to the S3c gene in the pIRES-S3c plasmid we constructed (the plasmid codes for a bicistronic message with 1 promoter for EGFP and S3c), these results confirm the flow cytometry data shown in Panels A through D. Figure 2 FLAG and EGFP expression in representative NRP-152 and BPH-1 clones transfected with either pBABE-S3c or pIRES-S3c. NRP-152 and BPH-1 cells were transfected with pBABE-S3c or pIRES-S3c, which bear the FLAG epitope on the S3c gene. Clones were derived by limit dilution, as described in Materials & Methods. Panels A–D: In all histograms, the marker M1 sets the region of positively fluorescent cells for determining the percent positive cells. Panels A & B: Fixed cells were permeabilized and stained with anti-FLAG M1 Ab (Sigma), as described in Materials & Methods. Controls for staining were included, as described. Panel A: Transfected NRP-152 cells. Thin line = 152-S3c; thick line = NRP-152. Panel B: Transfected BPH-1 cells. Thin line = BPH-1; thick line = BPH-S3c. Panels C & D : NRP-152 and BPH-1 cells transfected with pIRES-S3c were analyzed for EGFP fluorescence, following selection. Panel C: Transfected NRP-152 cells. Thin line = NRP-152; thin line = 152-S3c. Panel D : Transfected BPH-1 cells. Thick line = BPH-1; thin line = BPH-S3c. Panel E: Immunoprecipitation followed by Western blot showing EGFP expression in transfected NRP-152 and BPH cells. Note the lack of EGFP bands for parental lines NRP-152 and BPH-1, whereas EGFP was detected using EGFP-specific Ab (Pharmingen) in lanes for 152-S3c and BPH-S3c. Methods: NRP-152, 152-S3c, BPH-1, and BPH-S3c cells were lysed in buffer. Equal amounts of protein in cell lysates were pre-cleared with Protein A/G beads, then precipitated with anti-FLAG AB plus Protein A/G beads with rotation in the cold. The pelleted beads plus proteins were separated on 12% SDS gels, transferred to PVDF membranes, then blotted with Ab to EGFP. Enhanced chemifluorescence was used to reveal the 27 kD bands corresponding to EGFP. 152-S3c Cells Grew in the Absence of Exogenous Growth Factors To demonstrate that 152-S3c cells grew in the absence of growth factors required by untransfected NRP-152 cells, transfected and untransfected NRP-152 cells were grown in microtiter wells. Proliferation was quantified by the oxidation of MTT after 48 hr. Figure 3 shows the results of these experiments. NRP-152 and 152-pIRES cells grew more slowly in unsupplemented 154 medium than they did in 152 medium. However, 152-S3c cells (3 representative clones, D5, A12, and H4, are shown) grew nearly as well in 154 medium as in 152 medium, and grew significantly better in 154 medium than either NRP-152 or 152-pBABE cells (p < 0.001; Figure 3A ). Therefore, clones of 152-S3c cells, stably transfected with pBABE-S3c, grew in vitro as if they lost the requirement for additional growth factors in the cell culture medium. Figure 3 Growth of NRP-152, NRP-154, 152pBABE, and 152-S3c clones on 154 medium compared to growth on 152 medium. 10 3 cells were seeded in microtiter wells, in the indicated medium. After incubation for 48 hr, MTT (15 μl at 25 μg/ml) were added to each well, and incubation was continued for 4 hr more. The formazan was dissolved in 0.1% SDS, and the absorbance was quantified on a DynaTech plate reader at 570 nm. Unpaired Student t-tests (InStat3 software) were performed to assess the statistical significance of the growth of S3c-transfected cells relative to pBABE transfected and untransfected NRP-152 cells. Panel A: Comparison of growth as measured by MTT absorbance at 48 hours; Panel B: Comparison of growth rates over 72 hours. Stable Expression of S3c in BPH-1 Cells Resulted in STAT3-Dependence for Survival In order to show that the persistent expression of activated STAT3 was required for the survival of the transfected cells, as we have previously shown for hormone-refractory prostate cancer cells lines [ 11 , 12 ], we transfected pIRES-S3c into human BPH-1 cells [ 38 ] for studies with antisense STAT3 oligonucleotides. We used BPH-1 cells and transfected lines only for these experiments, because the antisense oligonucleotide was designed for use in human cells, and we wanted to maximize the efficacy of the antisense oligonucleotide. Figure 4 shows that transfection of 125 nM of sense STAT3 oligonucleotide decreased viability by only 5% at 48 hours, whereas transfection of the same amount of antisense STAT3 oligonucleotide decreased viability to 18% at 48 hours. Furthermore, transfection of antisense STAT3 oligonucleotide into untransfected BPH-1 cells did not decrease viability any more than did transfection of sense oligonucleotide. Figure 4B shows that 24 hours after transfection with 125 nM of antisense STAT3, BPH-S3c cells displayed a 66% reduction in intracellular STAT3 protein levels. We concluded from these experiments that the S3c expressed in BPH-S3c cells was functionally active, and that BPH-S3c cells were dependent upon continued STAT3 expression for their very survival, just like hormone-refractory prostate cancer cell lines [ 11 , 13 ]. These data are more evidence for a profound difference in phenotype between BPH-1 cells and BPH-S3c cells. Figure 4 Functional activity of STAT3 in S3c-transfected cells. Panel A: To show the functional activity of STAT3 expressed by the S3c gene, BPH-1 cells stably transfected with pIRES-S3c were treated with either 125 nM sense or antisense STAT3 oligonucleotide. Percent viability over time was determined by staining with propidium iodide, then quantifying fluorescence on a FACScan flow cytometer. Panel B: Treatment with 125 nM antisense STAT3 oligo reduced the amount of intracellular STAT3 protein in the clone of BPH-S3c cells shown in 3A. Twenty-four hours after transfection, BPH-S3c cells were harvested, fixed, and permeabilized, then stained with antibody to STAT3, as described in Materials and Methods. Quantification was performed on a FACScan flow cytometer. The black line indicates the amount of intracellular STAT3 in BPH-S3c cells treated with sense STAT3, while the grey line shows the amount of STAT3 in BPH-S3c cells given antisense STAT3. STAT3 expression was reduced by 66% in this experiment. 152-cS3 Cells Have Decreased Expression of RAR-β and -γ mRNA, and Increased Expression of RAR-α mRNA In prostate cancer cell lines and archived specimens, we previously found that RAR-β and -γ have decreased mRNA levels, while RAR-α mRNA increased, relative to non-malignant prostate cell lines and the normal margins of the same specimens [ 34 , 35 ]. This finding is also true of NRP-152 and NRP-154 cells: the expression of RAR-β and -γ is decreased in NRP-154 cells relative to NRP-152 cells. In order to see if the same change in retinoic acid receptor subunit expression occurred when S3c is expressed, which is consistent with the malignant phenotype, we did the following experiments. For these, we used 152-S3c and 152-pIRES cells, so that we could compare the RAR levels with those of NRP-154 and parental NRP-152 cells, because these 2 related cell lines are believed to represent two stages in the progression and development of prostate cancer [ 36 , 41 ]. Figure 5 depicts the northern blot hybridization results for RAR-β (Figure 5A ) and -γ (Figure 5B ) in transfected and untransfected cells. Lane 1 in both panels shows the hybridized mRNA for untransfected NRP-152 cells, while both lanes 2 show the hybridized band for NRP-154 cells. Note the decreased amount of RAR-β and -γ in lanes 2 (from NRP-154 cells, the prostatic carcinoma line) relative to the amount in lanes 1, obtained from NRP-152 cells, the benign prostatic hyperplasia line. Lanes 3 show the hybridized mRNA obtained from NRP-152 cells transfected with the vector, pIRES-EGFP, while the bands displayed in both lanes 4 shows that when NRP-152 cells were transfected with pIRES-S3c, the hybridization of RAR-β and -γ decreased similarly to what is observed in lanes 1 and 2. Figure 5C compares RAR-α mRNA expression in the 4 cell lines: lane 1 again is NRP-152 and lane 2 is NRP-154; there is more mRNA hybridized in lane 2 than in lane 1, and the band appears as a doublet in lane 2 as well. Lane 3 shows the results from NRP-152 cells transfected with pIRES-EGFP, while lane 4 shows the results from NRP-152 transfected with pIRES-S3c: note the similar pattern to that of lanes 1 and 2 – lane 4 shows more hybridization and a doublet band for RAR-α as well. We concluded from these results that transfection of NRP-152 cells with pIRES-S3c, but not pIRES-EGFP, induced a change in RAR mRNA expression that is often observed in prostate cancer cell lines and archived specimens. Figure 5 S3c expression inhibited RAR-β and -γ expression and increased expression of RAR-α in NRP-152 cells. Panel A: Effect of S3c on RAR-β mRNA levels. Panel B: Effect of S3c on RAR-γ mRNA levels. Panel C: Effect of S3c on RAR-α mRNA levels. NRP-152, NRP-154, NRP-pBABE, and 152-S3c cells were grown to confluence, and RNA was harvested as described in Materials & Methods. Electrophoretic separation of RNA was followed by transfer to nitrocellulose, then hybridization with 32 P-labeled probe, followed by autoradiography. Lane 1 = NRP-152 (rat benign prostatic hyperplasia line); lane 2 = NRP-154 (rat prostatic carcinoma line); lane 3 = 152-pBABE; lane 4 = 152-S3c. The comparison to 18S RNA is shown for each. BPH-S3c Cells Were Androgen-Insensitive In many human prostate cancers, overexpression of the androgen receptor has been noted [ 42 , 43 ]. Therefore, the development of the hormone-refractory state apparently occurs even when there is no disruption of the expression of the androgen receptor, at least in some prostate cells. To clarify these contradictory data and to check for the development of functional androgen-insensitivity, we examined the growth rate of human BPH-1 and BPH-S3c cells in the presence and absence of dihydrotestosterone (DHT), and also DHT in the presence of the antagonist flutamide (F). Our results, presented in Table 2 , show that while BPH-1 cells respond to DHT and are blocked by F, the same is not true of BPH-S3c. Thus, the persistent expression of S3c in BPH-1 cells resulted in a functionally androgen-insensitive state for these cells. Table 2 Androgen-Insensitivity is conferred by S3C expression in BPH-1 cells Cell nM DHT %Stimulation μM F + nM DHT %Inhibition BPH 10 200 1 10 97 BPH-pIRES 10 250 1 10 99 BPH-S3c 10 2 1 10 -4 DU145 10 3 1 10 3 Cells were grown in 96-well plates for 72 hr, in the presence or absence of drugs (DHT = dihydrotestosterone; F = flutamide, bolded and underlined ) as indicated. The MTT assay was used to assess proliferation. %Enhancement = (absorbance + drug/absorbance - drug) × 100; % Inhibition = 1-(absorbance + drug/absorbance - drug) × 100. The responses of DU145 cells, a human prostate cancer cell line that is androgen-insensitive and resistant to flutamide, is shown for comparison. 152-S3c Cells Lost Sensitivity to the JAK2 Inhibitor AG490 In non-malignant cells, the activation of STAT3 is effected by a specific upstream kinase, JAK1 or JAK2 or sometimes Tyk2. Previously we had shown that the constitutive activation of STAT3 in NRP-154 cells rendered those cells insensitive to apoptosis induced by the JAK2 inhibitor AG490 [ 10 ]. In order to see if insensitivity to AG490 was conferred on 152-S3c cells, we added AG490 to cells and assessed apoptosis 48 hr later by annexin V binding and PI inclusion. Table 3 shows the data we obtained. Whereas NRP-152 and 152-pIRES cells were 45 ± 10% and 38 ± 5% apoptotic, respectively, 48 hr after treatment with 100 μM AG490, only 6.3 ± 3% of 152-S3c cells and 7.5 ± 4% of the NRP-154 cells were apoptotic after 100 μM AG490 treatment. We conclude from these experiments that S3c expression in NRP-152 cells decreased their sensitivity to AG490, which is consistent with what we observed in malignant NRP-154 cells. Table 3 NRP-152 Cells Transfected with S3c lost sensitivity to JAK2 inhibitor AG490 Cell S3c? Rx μM % Apoptotic +/- SD NRP-154 YES AG490 0 8 ± 4 100 7.5 ± 5 5152-S3c YES AG490 0 7.5 ± 4 100 6.3 ± 3 152-pIRES NO AG490 0 11 ± 2 100 38 ± 5* NRP-152 NO AG490 0 7.5 ± 4 100 45 ± 10* Cells were placed in 60 mm wells for 48 hr with compound at the concentrations indicated. Zero concentration of the compound is the vehicle (DMSO) control. At the end of the incubation period, cells were harvested, washed, and stained with FITC-annexin V, to demonstrate apoptotic cells. Quantification of fluorescence was performed on a Becton-Dickinson FACScan flow cytometer using CellQuest software. * p < 0.005 by Student t-test, compared to vehicle-treated cells. 152-S3c Cells Grew in Soft Agar As an in vitro indication of tumorigenic potential, soft agar cloning assays were performed as described [ 44 ]. S3c-transfected cells were compared to NRP-152 and to pIRES-EGFP-transfected cells in these experiments. We observed that 152-S3c cells grew significantly better (p < 0.0001 by 2-tailed Student t-test) in soft agar than either untransfected NRP-152 or pIRES-transfected NRP-152 cells (Table 4 ). We conclude from these experiments that 152-S3c cells have the potential to form tumors in vivo, whereas it has previously been established that NRP-152 cells are not tumorigenic [ 36 ], and we would not expect 152-pIRES cells to be tumorigenic either. Table 4 NRP-152 Cells transfected with S3c grew in soft Agar CELL S3c? #WELLS #COLONIES +/- SEM NRP-152 NO 12 2.6 ± 0.9 152-pIRES NO 12 5.8 ± 1.8 152-S3c YES 12 35 ± 4.5* Cells were placed in 60 mm wells in soft agar for 10 days. Colonies of more than 1 mm in size were counted were counted using an inverted phase contrast microscope. * p < 0.001 by Student t-test Expression of S3c Did Not Confer Tumorigenicity on Benign NRP-152 Cells Based on our previous data, especially the soft agar cloning data, we expected that 152-S3c cells would form tumors in SCID mice. However, in 3/3 experiments (in two them, Matrigel was used to enhance tumorigenicity of the cells), an average of 1/5 mice developed tumors; these were 1 mm in diameter or less. We chose to use only transfected NRP-152 cells for these experiments, because in certain in vivo environments, untransfected BPH-1 cells have been observed to form tumors [ 38 ]. We conclude that while persistent S3c expression altered the phenotype of 2 different benign prostatic hyperplasia lines in ways consistent with the development of the malignant phenotype, an additional change in gene expression may be required for tumorigenicity in prostate cancer development. Discussion We have demonstrated that NRP-152 and BPH-1 cells transfected with a constitutively-activated form of the STAT3 gene, S3c, gained a phenotype which more closely resembled that of NRP-154 cells. Specifically, the transfected cells expressed resistance to the antibiotic G418, and also expressed the FLAG epitope, as revealed by intracellular flow cytometry following staining with anti-FLAG Ab in Figure 2B–C , while Figure 2A shows the FLAG expression in mock transfected cells. As additional evidence of S3c expression, we looked for EGFP expression in 152-pIRES cells, since the bicistronic message from this vector (pIRES-EGFP) places the S3c gene 3' to the EGFP, so that S3c would have to be translated before EGFP is translated. Figure 2D shows the EGFP expression in the same clone whose FLAG expression is shown in Figure 2C . These results were confirmed by immunoprecipitation/Western blot analysis, which is shown in Figure 2E , whereupon cell lysates were precipitated with Ab to the FLAG peptide on the S3c gene, then blotted with anti-EGFP Ab. Only the transfected and selected 152-S3c and BPH-S3c cells revealed EGFP bands, not the parental lines. After obtaining these results, we characterized the phenotype of the transfected cells. Parental NRP-152 cells are fastidious in their growth factor requirement, whereas NRP-154 cells and 152-S3c clones grew in medium supplemented only with serum (Figure 3 ). Therefore, we assessed the change in growth of transfected NRP-152 cells by comparing their growth in unsupplemented medium. We found that clones of 152-S3c cells grew nearly as well as NRP-154 cells in simple medium, whereas NRP-152 and 152-pIRES cells grew poorly in the absence of growth factors included in the medium (Figure 3 ). The change in growth factor requirement is one often observed for neoplastic cells, and is consistent with the role of STAT3 as a proto-oncogene with the capability of transforming benign cells into malignant cells [ 15 , 45 ]. As for dependence on survival of constitutively-activated STAT3, which has been observed in NIH-3T3 transfected with S3c [ 40 ] and in hormone-refractory prostate cancer cell lines [ 11 ], BPH-S3c cells treated with 125 nM antisense STAT3 oligonucleotides died over time, going from 100% viable to less than 20% viable 48 hours after transfection (Figure 4A ); the reduction in viability could be attributed to the effect of antisense STAT3 on STAT3 protein expression, which was reduced by 66% at 24 hours after transfection (Figure 4B ). These data mean that like hormone-refractory prostate cancer cells, BPH-1 cells transfected with S3c became dependent upon the continued expression of S3c for their survival. As for RAR expression, we observed decreased mRNA levels of RAR-β and -γ, but increased RAR-α expression in S3c-transfected NRP-152 cells; the results shown in Figure 5 are consistent with the expression levels of these receptor mRNAs previously observed by us in prostate cancer lines [ 34 ] and in prostate cancer patient specimens [ 35 ]. These findings are echoed in those of Yang, et al., who observed that IL-6-induced STAT3 signaling in lung epithelial cell lines lead to increased RARα expression, which was abrogated when the STAT3 DNA-binding domain was substituted by the corresponding STAT1 domain [ 46 ]. The importance of our results with respect to prostate cancer is that this disease is often refractory to retinoid therapy, the molecular basis for which is not known at this time. Our results gives possible insight into the mechanism of retinoid insensitivity, and might also indicate that treatment of prostate cancer with STAT3 inhibitors and with retinoids may be beneficial. In terms of androgen receptor function, S3c expression in BPH cells changed their response to androgens so that BPH-S3c cells were no longer stimulated by DHT, and the growth of BPH-S3c cells was not inhibited by flutamide treatment (Table 2 ). These findings with respect to the androgen receptor and responses to DHT and flutamide are especially important, as it may be the one of the first indications of a direct effect of STAT3 on androgen receptor responses, and may indicate a possible molecular mechanism for the development of the hormone-refractory state in prostate cancer patients. The progression to androgen-independence has been found to be associated with IL-6, with c-myc expression, and with insulin-like growth factors, all of which can signal through the activation of STAT3 [ 25 - 28 ]. It has been postulated that cross-talk between STAT3 and the androgen receptor plays a role in the development and maintenance of the hormone-refractory state in prostate cancer [ 47 ]; our data indicate that persistently-activated STAT3 may obviate the need for expression of the androgen receptor, since the androgen receptor did not respond to either DHT or F in S3c-transfected BPH-1 cells (Table 2 ). Further work is warranted in this area. Prior to performing in vivo tumorigenicity experiments, we wanted to see if S3c-transfected cells could grow in soft agar as clones. We observed that S3c expression in NRP-152 cells allowed them to grow as clones in soft agar (Table 4 ). However, even though 152-S3c cells grew in soft agar, a phenotype usually consistent with tumorigenicity, in 3 out of 3 experiments we failed to observe tumors in more than 20% of the mice, and these tumors were not more than 1 mm in diameter (data not shown). Therefore, we concluded from these data that persistent expression of activated STAT3 alone was not sufficient to produce tumorigenicity in prostatic epithelial cells, although it had been sufficient in NIH-3T3 cells, as previously reported [ 40 ]. Furthermore, recent observations by Zhang and coworkers point to an important function for STAT3 in both tumorigenesis and metastasis formation in leiomyosarcoma [ 48 ], due to signaling by hepatocyte growth factor/scatter factor. Among the candidate genes regulated by STAT3 in this regard are matrix metalloproteinase-2, which is essential for tumor invasion and metastasis formation [ 49 ]. Perhaps STAT3 cooperates with another factor regulated by hepatocyte growth factor/scatter factor, which is not expressed by either NRP-152 or BPH-1 cells. Only more experiments will reveal whether this is the case. Indeed, we are planning experiments to see what genes are regulated by S3c, to gain insight into the phenotypic changes induced by S3c expression. For example, very recently it was reported that STAT3 and the microphthalmia-associated transcription factor were both required for optimal upregulation of c-fos , and subsequent tumorigenicity, in NIH-3T3 cells [ 50 ]. Whether the prostatic lines NRP-152 or BPH-1 express microphthalmia-associated transcription factor has not been determined; the levels of c-fos in S3c-transfected lines can be determined. As well, Dechow and coworkers reported that transfection of S3c into mammary epithelial cells rendered those cells tumorigenic in irradiated SCID mice [ 51 ]; whether our results are an indication of a difference between mammary epithelial cellls and prostatic epithelial cells or a reflection of irradiated vs. non-irradiated SCID mice remains to be elucidated. As more information is revealed about gene expression changes that accompany the progression of prostate cancer from the benign to the hormone-refractory state, the other genetic changes needed for tumorigenicity of S3c cells should be revealed. Conclusions Our data indicate that transfection of NRP-152 and BPH-1 prostatic epithelial cells with a gene for persistently-activated STAT3, S3c, changed the phenotype of the cells into one resembling a malignant phenotype, thereby giving even more importance to the role of activated STAT3 in the transformation of normal cells into neoplastic cells. Importantly, we found that cells expressing S3c depended on its continued expression for survival. Two kinds of evidence are presented: first, S3c-transfected cells became sensitive to the effect of antisense STAT3 oligonucleotide. When transfected with antisense STAT3, both BPH-S3c and 152-S3c underwent apoptosis. Second, the S3c-transfected cells were not sensitive to the commonly-used STAT3 inhibitors, which are really JAK inhibitors, because activation of STAT3 by the upstream JAK is not required when S3c is expressed. We observed that growth factor-dependent NRP-152 cells grew without growth factor supplementation when transfected with S3c gene, whereas the medium for vector-transfected NRP-152 cells still required supplementation with growth factors. Moreover, we observed that 152-S3c cells grew in soft agar, whereas neither vector-transfected nor untransfected NRP-152 cells did. Furthermore, we observed that the expression of RAR subunits in 152-S3c cells was different from vector-transfected and untransfected NRP-152 cells, and that the changes were consistent with what we previously observed in specimens from prostate cancer patients, as well as in primary prostatic epithelial cells compared with prostate cancer cell lines [ 34 , 35 ]. These data may have implications for the relative lack of sensitivity of PCA to retinoid therapy. As for BPH-1 cells, which do not require growth factor supplementation, we observed that when transfected with S3c, this cell line lost its responses to testosterone and to the testosterone antagonist flutamide. Neither of these changes was observed in vector-transfected BPH-1 cells. However, neither S3c-transfected cell line was tumorigenic when injected into SCID mice, leading us to conclude that additional genetic changes are possibly needed for tumorigenicity in prostate cells. Methods Cell Lines NRP-152 and NRP-154 cells were the gift of Dr. David Danielpour, Ireland Cancer Center, University Hospitals, Cleveland, OH [ 36 ]. Growth factor-dependent NRP-152 cells were grown in DMEM/Ham's F12 medium (1:1; GIBCO) supplemented with 10% newborn bovine serum (Hyclone), 2 mM glutamine (GIBCO), epidermal growth factor (20 ng/ml), insulin (5 μg/ml), dexamethasone (0.1 μM) and cholera toxin (10 μg/ml; all, Sigma), pH 7.3 (152 medium). NRP-154 cells were grown in DMEM/Ham's F12 medium plus 10% newborn calf serum (154 medium). Growth factor-independent BPH-1 cells [ 37 , 38 ] were the gift of Dr. Simon Hayward, Vanderbilt University, Nashville, TN. They were grown in RPMI-1640 medium supplemented with 10% newborn bovine serum. For transfections, cell were seeded into wells of 6-well plates and grown until 50–80% confluent monolayers of cells were present, as assessed by observation under inverted phase-contrast microscopy. Transfections Derivation of the pBABE-S3c plasmid containing a constitutively-activated STAT3 gene, S3c (gift of Dr. Jacqueline Bromberg, Memorial Sloan-Kettering Cancer Institute) has been previously described [ 14 , 45 ]. The S3c gene was excised along with its FLAG tag, and inserted into pIRES-EGFP (Clontech), resulting in the plasmid called pIRES-S3c. For stable transfections, Clonfectin reagent (Clontech) was mixed with plasmid DNA (6 μl Clonfectin and between 1 and 3 μg plasmid), according to the manufacturer's instructions. The complete medium was removed from the plates of cells and replaced with 1.8 ml IMDM (Invitrogen). The Clonfectin-plasmid mixtures (100 μl) were added to the cells; replicate cultures of cells received Clonfectin only at the time of transfections. The plasmid-Clonfectin mixtures were left on the cells in the incubator for 4 hr, at which time the supernatant fluids were aspirated and replaced with 5 ml/well pre-warmed complete medium. Twenty-four hr following transfections, G418 (Invitrogen) was added at a final concentration of 800 μg/ml. The medium plus G418 was replaced 3 times/wk until no surviving cells were observed on the Clonfectin-only wells, usually 2 weeks. At that time, G418 was added at 100 μg/ml to maintain the transfected cells. When the transfected cells reached confluence, they were used for further analyses. Table 1 gives a summary of transfected cells and phenotypes obtained. For transient transfections, LipoFectamine 2000 in Opti-MEM I medium (both, Invitrogen) was used according to the manufacturer's directions. For subconfluent (~50%) cells, 2 μl of LipoFectamine 2000 was used with varying amounts of antisense or sense STAT3 oligonucleotide (gift of Dr. James Karras, ISIS Pharmaceuticals). The oligonucleotides were left on the cells for 6 hours before cell culture medium supplemented with 30% was added to each well. Cells were incubated until assays were performed. Limit-Dilution Cloning In order to analyze clonal populations of cells, transfected cells (pIRES-S3c or pIRES-EGFP) were harvested, diluted to 10 cells/ml in complete medium, and seeded into microtiter plates at 100 μl/well. The total volume of each well was brought to 200 μl with additional medium, and the plates were incubated until growth of seeded cells was observed, usually at 10 days to 2 weeks. Determination of Stable Transfection by Expression of FLAG in 152-S3c and BPH-S3c Cells by Intracellular Flow Cytometry Expression of the FLAG epitope engineered onto the constitutively-activated STAT3 gene in transfected NRP-152 cells was performed by intracellular flow cytometry, as described [ 52 ]. Briefly, 152-S3c or BPH-S3c cells were harvested, washed, and fixed in 4% paraformaldehyde/PBS (Pharmingen) for 30 min on ice. Fixed cells were washed and permeabilized with 0.1% sapononin (Pharmingen) for 15 min at room temperature, then washed. Mouse monoclonal Ab M1 to FLAG (Sigma) was added (1 μg/10 6 cells/100 μl permeabilization buffer) to the cells for 1 hr on ice. The cells were washed 3 times, then incubated with phycoerythrin (PE)-labeled goat anti-mouse F(ab 2 )' (Caltag) for 1 hr on ice in permeabilization buffer. After washing 3 times, cells were resuspended in 1 ml PBS and analyzed on a Becton-Dickinson FACScan. CellQuest software was used to acquire and analyze the fluorescence. The Kolmogorov-Smirnov 2-sample test was used to determine the level of significance of the change in fluorescence intensity between control-stained (F(ab 2 )'-stained only) and Ab-stained populations of cells, thereby ascertaining that the populations observed in the histograms were truly separate populations of cells [ 53 ]. Immunoprecipitation/Western Blot Studies For immunoprecipitation, cells lysed in Lysis Buffer (10 mM PBS, pH 7.4, 1% NP-40, 0.5% sodium deoxycholate, 0.1% sodium dodecylsulfate (SDS), 1 mM sodium orthovanadate, 1 mM phenylmethyl-sulfonyl fluoride, 40 μg/ml aprotinin) were precleared with Protein A/G agarose (Santa Cruz Biotechnology), then precipitated with 1–5 μg rabbit Ab (Cell Signaling or Pharmingen) plus Protein A/G (Santa Cruz Biotechnology) agarose overnight. After washing, the beads were eluted by heating in Laemmli buffer for 5 min at 95°C, followed by electrophoretic separation on 12% SDS-polyacrylamide gels (Novex Nu-PAGE pre-cast gels). Transfer of separated protein species to nylon membrane (Millipore) was followed by blocking in 10% non-fat dry milk in TBST (50 mM Tris HCl, pH 7.4, 150 mM NaCl, 0.3% Tween 20). Incubation of the membrane with rabbit Ab was followed by incubation with alkaline phosphatase-linked goat anti-rabbit antibody (Amersham ECF kit). After addition of substrate from the kit, the membranes were read by the Typhoon imager, with ImageQuant software for resolution of images (Molecular Dynamics). Measurement of In Vitro Growth of Cells NRP-152, NRP-154, BPH-1, and transfected cells were seeded at 10 3 cells/well in microtiter plates in appropriate medium, as indicated. After 48 hr, 15 μl MTT (Sigma; 25 μg/ml) was added to each well for 4 hr, then the resulting formazan was dissolved in 0.1% SDS. Absorbance was determined at 570 nm on a Dynatech microplate reader. Statistical determinations of significance were performed by unpaired Student t-test for multiple independent assays, using GraphPad software. Determinations of Androgen Insensitivity and Presence of Retinoid Receptors The effect of dihydrotestosterone (DHT) as growth agonist, and the effect of flutamide (F) as growth antagonist, was assessed by use of the MTT assay described above. DHT and F were obtained from Boeringer-Mannheim, and cells were treated with 1 or both drugs at concentrations ranging from 1 to 100 nM for DHT, and 0.1 to 3 μM for F. These are within the published ranges of efficacy for these drugs [ 34 , 54 ]. Vehicle controls were included. Replicate plates were harvested at 24, 48, 72, and 96 hrs after treatment. Northern blot hybridizations to detect the retinoid receptors RARα, RARβ, and RARγ were performed as previously published [ 34 ]. In brief, RNA was isolated from cells using RNAEasy (Qiagen) and quantified spectrophotometrically. RNA was separated by size on agarose gels, then transferred to nitrocellulose membranes (Schleucher & Schuell). The probe was labeled with 32 P-dCTP (New England Nuclear), then allowed to hybridize to the blot overnight in hybridization buffer. After washing, hybridization was detected by use of a PhosphoImager (Molecular Dynamics). Apoptosis Assays Forty-eight hr after transient transfection, cells were harvested using Enzyme-Free Cell Dissociation Buffer. After two washes with PBS, they were stained with FITC-annexin V (5 μl/10 6 cells; Caltag) for 15 min at room temperature. Apoptotic cells (cells staining with FITC-annexin V) were quantified by measuring green fluorescence in FL1 on the flow cytometer. In some experiments, cells were also stained with propidium iodide (PI), which is detected by the FL3 detector. CellQuest software was used to acquire and analyze the data on a Becton-Dickinson FACScan flow cytometer. For studies using the tyrphostin JAK2 inhibitor AG490 (Calbiochem), the dissolved compound was added to subconfluent cells, as described [ 11 ]. A vehicle control was included for the 0 μM concentration. Forty-eight hrs later, cells were harvested and processed for quantification of apoptosis by annexin V binding and PI incorporation. Assay for Growth in Soft Agar Transfected cells were subjected for growth in soft agar to assess their change in phenotype with regards to colony formation. After selection and cloning, 10 4 cells were trypsinized and washed in Ca2+/Mg2+-free PBS (Life Technologies) and plated in 1 ml of medium plus serum without supplements containing 0.3% (w/v) Noble Agar (Difco/Becton-Dickinson) over a 2 ml layer of the same medium with 0.6% agar in six-well plates. The number of colonies was counted using low magnification microscope (4×) after 10 days. In Vivo Tumorigenicity Studies Our protocol was reviewed and approved by the Institutional Animal Care and Use Committee of UMDNJ. Severe-combined immunodeficient (SCID) mice (Charles River Laboratories) were obtained at 5 weeks of age, and acclimatized in the barrier vivarium for 1 week. At that time they were injected subcutaneously with 8 × 10 6 S3c or vector-transfected (pIRES-EGFP) control cells. Each group consisted of 5 animals. In some experiments, the cells were mixed with Matrigel (Collaborative Research) prior to injection. Tumor growth was monitored weekly using engineer's caliper's to measure the 2 perpendicular diameters, over the course of 12 weeks. List of abbreviations STAT signal transducer and activator of transcription cSTAT3 constitutively-activated STAT3 JAK Janus activated kinase PCA prostate cancer S3c constitutively-activated STAT3 gene having a Cys substitution FLAG an immunogenic peptide fused to gene of protein to be expressed for identification and/or purification purposes SCID severe combined immunodeficient PBS phosphate-buffered saline DMEM Dulbecco's modifcation of Eagle's medium IMDM Iscove's modification of Eagle's medium FITC fluorescein isothiocyanate PE phycoerythrin PI propidium iodide FL1, 2, or 3 fluorescence detectors on a flow cytometer that collect fluorescence data within a set range of wavelengths, FL1 being the lowest and FL3 being the highest EGFP enhanced green fluorescence protein RAR retinoic acid receptor DHT dihydrotestosterone F flutamide Authors' contributions HFH conceived of the retinoic acid receptor subunits experiments, and perofrmed the northern blot hybridizations. TFM performed the growth factor dependence and growth rate experments, performed some of the in vivo experiments, and prepared cells for flow cytometry. PS performed some of the transfections, participated in the in vivo experiments, the western blots, and prepared cells for flow cytometry. ABB made the pIRES-S3c plasmid from pBABE-S3c, and performed the soft-agar cloning experiments. BEB conceived of the project, performed most of the transfections, performed some of the in vivo experiments, and performed all flow cytometry acquisitions and analyses. All authors read and approved the manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC546221.xml
529433	The Quest for a Vaccine That Yields Tumor-Killing T cells	null	The immune system has a remarkable capacity for fending off infectious diseases, and it has become clear that these same defenses can recognize and destroy cancer cells. In fact, they do so on an ongoing basis, and cancer develops only when immune surveillance breaks down. Many patients with established tumors also mount an immune response against some antigens that are specific to, or enriched in, the tumor. This response, however, is rarely effective against the disease. The idea of enlisting the immune system to fight cancer has been around for a long time, and has led to the development of various cancer vaccines designed to alert the immune system to the presence of a tumor and to induce a response that, selectively and potently, will eliminate tumor cells. Vaccines include whole tumor extracts or specific proteins and peptides that are selectively expressed or enriched in tumors, by themselves or with a variety of adjuvants. There have been some spectacular successes, in particular with immune therapy to malignant melanoma, a tumor type that seems naturally to be more immunogenic than others. However, even in melanoma, success is usually restricted to a fraction of the patients, with no obvious explanation of why the strategy works for a particular patient and fails in most others. The emphasis has consequently shifted from clinical outcomes to monitoring a patient's immune response. What type of response is necessary and sufficient to eliminate tumor cells is still unclear, but the hope is that understanding the immune response in patients that show clinical benefit will answer that question. Peter Lee and colleagues used state-of-the art technology to dissect the endogenous immune response to vaccination with heteroclitic melanoma peptides, i.e., melanoma-associated peptides that have been engineered to elicit a stronger immune response. They focused on cytotoxic T lymphocytes (CTLs), and compared CTL clones from four melanoma patients who had vaccine-induced T cell responses and two melanoma patients with spontaneous anti-tumor T cell responses. The researchers analyzed several hundred CTL clones (to get a sense for the complexity of the responses in individual patients) for T cell receptor variable chain beta expression, recognition efficiency, and ability to lyse target melanoma cells. Most T cells isolated from vaccinated patients were poor at tumor cell lysis compared with T cells from endogenous responses to cancer. Melanoma—a prime target of cancer vaccines (Photo: Timothy Triche, National Cancer Institute) The authors suggest that the high doses of peptides administered in vaccinations and the increased binding capacity of heteroclitic peptides to major histocompatibility complex molecules—the very quality that makes them more immunogenic—induce many T cells with low recognition efficiency for the native peptides they encounter on the tumor cells. Their findings also bring into question the ability to deduce the recognition efficiency and tumor reactivity of T cell responses from ELISPOT and tetramer staining assays—the two standard measures of T cell responses to vaccines—which has implications for rational vaccine design in general.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC529433.xml
529427	Reconsidering Early HIV Treatment and Supervised Treatment Interruptions	Another study casts doubt on the value of early treatment and treatment interruptions. What are the implications of this study for our understanding of HIV pathogenesis, treatment, and vaccine development?	The devastating effects of HIV infection worldwide are reason enough for AIDS researchers to grasp at thin rays of hope. But seldom has a single anecdotal case stimulated as much hope as the 1999 report of an acutely infected patient who appeared to control HIV replication after two short treatment interruptions [ 1 ]. This report generated the hypothesis that early antiretroviral treatment (during or very soon after symptomatic seroconversion) allows the incompletely damaged immune system to recover and respond appropriately to virus antigens during treatment interruptions. This, in turn, according to the hypothesis, leads to control of viral replication by a healed and appropriately stimulated immune response to the patient's HIV infection. Consistent with this hypothesis was the prior finding that early antiretroviral therapy led to induction of HIV-specific proliferative responses similar to those that had been observed in patients with long-term, non-progressing HIV [ 2 ]. This led Rosenberg and colleagues to ask whether HIV-specific proliferative responses were a necessary and sufficient cause of long-term non-progression or just an immunologic consequence of controlled virus replication. Their report of virologic control in patients who interrupted therapy after early treatment raised hope that if HIV infection was treated early enough, the immune system could be repaired sufficiently to allow for long-term immunologic control of HIV replication [ 3 ]. Unfortunately, that's where the good news ends. Enthusiasm Fades A series of discoveries from clinical trials began to chip away at the enthusiasm for both early treatment of HIV infection and supervised treatment interruptions (STIs) as a way to boost the immune response. Several small trials of STIs in chronically infected patients were carried out [ 4 ], buoyed by the reasonable desire of patients for respite from the unpleasant side effects of the drugs. These trials gave disappointing results, up to and including the emergence of antiretroviral drug resistance in patients randomized to receive STIs. HIV-specific immune responses did increase off therapy, but so did viral loads. The so-called immune boosting probably reflected an immune response to greater viral antigen load but did not represent constructive immune enhancement. Larger trials clearly showed that STIs were of little if any benefit in chronic infection and that when therapy was stopped, viral loads invariably returned to pre-treatment levels [ 5 ]. Other studies indicated that HIV-specific CD4+ T cells were being preferentially infected, often massively, during treatment interruptions [ 6 ], and that proliferative responses were more likely to be a consequence—rather than a cause—of decreased HIV replication [ 7 ]. Despite multiple attempts, early reports of an inverse correlation between simple HIV-specific T cell responses and virologic control were not confirmed [ 8 ]. Where complex T cell functions did show such a correlation, the data indicated that viral replication was adversely affecting the character of the T cell immune response to HIV, and not the other way around [ 9 ]. Thus, no evidence of “immune boosting” during STIs and subsequent viral control in the absence of antiretroviral drugs was ever established. Finally, one of the acutely treated patients within Rosenberg's cohort became superinfected with a second strain of HIV despite excellent control of viral replication and significant recognition of the superinfecting strain by the pre-existing T cell response [ 10 ]. STIs offered patients hope of respite from taking complex regimens, but trials have been disappointing (Photo: J Troha) New Findings Now comes a study in this month's PLoS Medicine that found that in 14 patients who were treated early and who had controlled viral loads for at least 90 days, the virologic control was only transient [ 11 ]. While one could look at this as a glass half full—these patients achieved a reasonable period of time off antiretroviral therapy—closer scrutiny of the data limits this view. There was a disconnect between the low viral loads and an unexpectedly high rate of CD4+ T cell decline in several patients. While the small number of patients and the single-arm nature of the study preclude definitive comparisons, it is possible that the early treatment and STIs did not result in a delay in CD4+ T cell decline (and, therefore, initiation of antiretroviral therapy) beyond what would have occurred had the patients received no early treatment. Implications of the Study This study raises important questions in our understanding of HIV pathogenesis, treatment, and vaccine development. First, why is it that early antiretroviral treatment, even if it does lead to better control of viral replication, does not protect against CD4+ T cell depletion? It is possible that by the time patients present with acute retroviral syndrome their CD4+ T cell reserves (in gut and lymphoid tissues) have been severely depleted, despite the fairly normal CD4+ profile of their peripheral blood. Thus, even low-level viral replication is then sufficient to deplete the remaining central and peripheral reserves [ 12 ]. Second, how do these findings affect treatment guidelines during acute infection? None of the current treatment guidelines in either resource-rich or resource-poor settings recommend early antiretroviral therapy. In the light of these new data [ 11 ], there does not appear to be a rationale for early antiretroviral therapy in the absence of a clinical trial to assess other interventions in concert with early therapy. The use of therapeutic vaccination is an obvious intervention that still needs to be tested, despite limited efficacy results in treated chronic infection. As such, practice guidelines should continue to caution against early treatment unless associated with a randomized clinical trial. Finally, is this good or bad news for HIV vaccine development? Since most current vaccine strategies are based upon the hypothesis that induction of T cell immunity will lead to control of viral replication, it is difficult to be optimistic when a strong and broad immune response is unable to prevent disease progression. However, one must recall that phenotypic and functional assessments of HIV-specific T cell responses, even in antiretroviral-treated patients, show that these responses clearly differ from responses against viruses that are normally cleared or controlled by the immune system [ 9 ]. Therefore, the T cell responses in the patients treated for acute HIV infection in Kaufmann et al.'s study were induced upon a dramatically altered immune background. It remains to be determined how much this adversely affects the HIV-specific immune response, and whether an immune response generated by vaccination before any HIV replication (a prophylactic vaccine) might be better able to control virus replication. Far be it for us to stop grasping at rays of hope.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC529427.xml
544191	A suite of web applications to streamline the interdisciplinary collaboration in secondary data analyses	Background We describe a system of web applications designed to streamline the interdisciplinary collaboration in outcomes research. Description The outcomes research process can be described as a set of three interrelated phases: design and selection of data sources, analysis, and output. Each of these phases has inherent challenges that can be addressed by a group of five web applications developed by our group. QuestForm allows for the formulation of relevant and well-structured outcomes research questions; Research Manager facilitates the project management and electronic file exchange among researchers; Analysis Charts facilitate the communication of complex statistical techniques to clinicians with varying previous levels of statistical knowledge; Literature Matrices improve the efficiency of literature reviews. An outcomes research question is used to illustrate the use of the system. Conclusions The system presents an alternative to streamline the interdisciplinary collaboration of clinicians, statisticians, programmers, and graduate students.	Background In the last decade, the number of relevant data sources available for outcomes research has grown exponentially. In contrast, the number of individual researchers with clinical and statistical expertise required to explore these data sets increase at a much slower pace. As a result, an immense quantity of valuable clinical data are left untouched, never becoming clinical publications that could potentially improve health care. The disproportion between data volume and number of qualified researchers can be explained by the growing complexity involved in outcomes research projects using secondary data analyses. Researchers have to formulate of a clinically relevant and methodologically sound research question, find appropriate data sources, perform statistical analyses, and generate a final manuscript that will be submitted for peer-review. Frequently, individual researchers have the training and time to perform a few of these steps, but the integration of all tasks calls for an interdisciplinary systems approach [ 1 , 2 ]. This interdisciplinary effort, however, is often challenged by communication problems among researchers with different backgrounds, particularly when physicians with an exclusive clinical education attempt to work in collaboration with quantitative researchers such as statisticians [ 3 ]. As a consequence, the output of such collaboration is either scarce or absent. This article describes a suite of web applications developed to facilitate the process of converting outcome databases into clinical manuscripts, to streamline the interdisciplinary collaboration of researchers, and to connect all different steps of the outcomes research process. To illustrate its use, we will describe how a research project has been conducted using this system from its early phase of research question formulation to the completion of the final manuscript. Construction and content The system of Web applications is composed by five different tools: QuestForm, Research Manager, Analysis Charts, and Literature Matrices. These tools were designed to assist researchers in each of the phases encountered in an outcomes research project involving secondary data analysis (Figure 1 ). All tools are freely available at a designated web site . The following sections will describe each of the Web applications and their application in the answer of a real outcomes research question. Figure 1 Research phases, challenges, and respective tools QuestForm General description QuestForm, an acronym for "Question Formulation", is an application designed to assist researchers in the location of clinical databases and formulation of outcome research questions (Figure 2 ). Clinical databases contain raw data (observations from individual patients) from national administrative claim data, cohort studies, clinical trials, and registries (see for an updated list). All databases have been de-identified and do not contain protected health information as specified by the Health Insurance Portability and Accountability Act ( , accessed on Aug/04/2004). The application The application is built using Extensible HyperText Markup Language 1.0 (XHTML) [ 4 ], Java, and a relational database (MySQL 4.0)[ 5 ]. Figure 2 QuestForm application – Database search engine QuestForm starts by presenting researchers with three main strategies to find research databases: use of pre-determined key words that describe the database as a unit (Figure 2 ), user-defined key words to describe variables present in the data dictionary of each database, and the presentation of a complete list of all databases. Once databases are located, researchers can read an overall summary about the database including details about number of subjects, sampling strategy, data ownership, and overall characteristics of the study population and associated procedures (Figure 3 ). Researchers then determine that the database most appropriate to answer the research question at hand, a JAVA screen is displayed for research question formulation (Figure 4 ). This screen presents all variables displayed in hierarchical categories. Variables are presented with the corresponding question and alternative responses. All variables can be inserted into a research question (Question Diagram) divided into the classical categories for an epidemiological question: Outcomes, Predictors, Confounders, Inclusion and Exclusion Criteria. Search engines are provided for ICD9-CM diagnosis and procedure codes (Figure 5 ), which can also be inserted into the Question Diagram. Finally, previously formulated Question Diagrams can be shared among researchers. This latter functionality allows researchers to both share Question Diagrams among members of the ongoing project as well as share previously formulated Question Diagrams with researchers from other teams. Once the question is fully formulated, researchers can save the question as in a graphical format known as Question Diagram. Figure 3 QuestForm application – Overall description of the database Figure 4 QuestForm application – Formulation of a Question Diagram Figure 5 QuestForm application – Search engine for ICD9 codes Outcomes research application Dr. Guller initiated the project searching for an existing database that would allow him to compare surgical outcomes between laparoscopic and open appendectomy procedures in the treatment of acute appendicitis. The outcomes were pre-specified as mortality and infection, although other existing outcomes would also be of interest. Although there are multiple single-institution studies attempting to answer this question [ 6 , 7 ], few studies have taken a population approach to test whether one procedure is superior to the other. As a first step, Dr. Guller searched across previously formulated Question Diagrams to evaluate whether other studies could have used a similar research design. Since none was found in QuestForm, Dr. Guller searched across more than forty different databases for an existing database that would have the variables to answer his research question. After navigating through multiple data dictionaries, Dr. Guller found that the Nationwide Inpatient Sample (NIS) Release 6, 1997 [ 8 ] presented the variables and an adequate number of patients to answer his question. Once the database was located, Dr. Guller selected the outcomes of interest (length of hospital stay, in-hospital complications, in-hospital mortality, rate of routine discharge), main predictors (laparoscopic versus open procedures), and confounders (age, gender, race, household income, comorbidity, hospital volume, location of the hospital, teaching status of hospital, and appendix perforation), inserting each of them into the research question fields in QuestForm. Using built-in search engines for ICD9 codes, Dr. Guller created the definition for each of the above-mentioned variables and defined the inclusion and exclusion criteria. The final research question was then saved as a Question Diagram and immediately submitted to Dr. Pietrobon for feasibility evaluation. Dr. Pietrobon judged that the project was feasible and could be completed using the database indicated by Dr. Guller. At this point, the project was initiated and a detailed project management plan was established using Research Manager. Research manager Research Manager is a Web application developed by our group designed to facilitate the project management of clinical research projects. Similar to QuestForm, Research Manager is licensed under the GNU Public License [ 10 ], which allows individuals to copy, modify, and freely distribute the software as long as the source code is provided. Research Manager provides multiple features to facilitate project management of clinical research projects. All projects are displayed by category (e.g., cardiology, general surgery, etc) with a brief description. The internal content of all projects is password protected. All internal tasks within a project are assigned to individual researchers. Project administrators initially assign deadlines that can be modified by task leaders within three days. All participating members of the project receive weekly reports containing details about the activity and the latest electronic file within each task (Figure 6 ). These files can include research questions, data analysis files, synthesis of a literature review, and manuscript drafts. Project members can also customize the application to receive updates for every single file uploaded to Research Manager in real time if they decide to closely track the project. Expired tasks are marked in the weekly report sent to the entire team, thus providing an incentive for investigators to keep tasks within planned deadlines. Figure 6 Research Manager Research Manager helps identifying such problems and enables their early elimination, thus avoiding delays in the project completion. Finally, since weekly reports are generated to all participating members, Research Manager also provides peer-incentive for project members to complete their tasks in a timely manner. Outcomes research application Once the Question Diagram was evaluated by the clinical epidemiologist, this project was transferred to Research Manager. Contact information for each of the researchers involved and deadlines for completion of the main phases of the research process were set, including data extraction and cleaning, data analysis, literature review, and manuscript writing. Weekly reports were generated to update investigators on all tasks of the project, including different versions of the statistical analysis, modifications in the research question, and manuscript sections. With an established project plan, the statistician in charge selected the best methods for analysis. Since the database is a random sample of the United States and requires special survey analysis methods, it was necessary that all involved researchers understood the statistical approach by using Analysis Charts. Analysis charts Analysis Chart is a tool designed to enhance the understanding of statistical methods to a format that is understandable by clinical researchers with different previous levels of statistical knowledge. As such, it is important in the design as well as the analysis phases of a project (Figure 7 ). The application was built using Extensible HyperText Markup Language (XHTML 1.0) [ 4 ] in combination with Cascading Style Sheets [ 11 ]. Figure 7 Analysis Chart Analysis charts are composed by cascading links that display information about quantitative methods in progressive levels of complexity called "layers of information". Each layer explains the statistical method with an increasing level of complexity. In this manner, clinicians interested in simply understanding the method to evaluate whether it can be applied to a research project can simply read the first three layers. In contrast, researchers interested in a direct application of the method to available research data can follow all layers and their respective references. Most commonly, complex techniques are presented using five layers of information . Layer 1 summarizes the general goal of the method. Layer 2 presents previous clinical applications so that the researcher can visualize situations in which the method may be realistically applied. Layer 3 describes the data requirements for the application of the statistical technique. Layer 4 describes the basic statistical underpinnings of the method, initially breaking down equations and then reassembling them. Finally, layer 5 presents a list of available software packages for the implementation of the technique as well as cases studies where all previous layers are applied to real data sets. Each layer ends with a section containing selected references that explain the topic in more detail. Outcomes research application While deciding on the most appropriate analysis strategy for the Question Diagram, Drs. Pietrobon and Guller consulted the Analysis Chart searching for the most appropriate statistical methods of analysis. Given the nature of the research question and that the NIS database has a sample design, Drs. Guller and Pietrobon opted for an approach involving multiple and logistic regression models while adjusting for sampling weights, strata, and clusters. With a defined analysis protocol, the research question was then transferred to a statistical programmer trained in the translation of Question Diagrams into statistical code. This process was closely evaluated by Drs. Pietrobon and Guller, who scrutinized the statistical code and results from a clinical and statistical perspectives. Once the results were deemed to be accurate, Dr. Pietrobon started the literature review using a Literature Matrix. Literature matrices Literature matrices consist of a comprehensive but not necessarily exhaustive review of the literature focused on a narrow clinical topic (Figure 8 ). Each article is analyzed using the following criteria: study objectives, data sources, outcome variables, primary predictor variables, confounders, statistical analysis, results, established knowledge, and shortcomings. Each literature matrix is saved as an XHTML file that can be visualized in web browsers as well as imported in any commercial or open source spreadsheet applications such as Microsoft Excel ® or Open Office Calc [ 12 ]. Figure 8 Literature Matrix The advantage of the Literature Matrix as implemented in the Web suite is its availability over the web to the whole outcomes research community. This allows Literature Matrices to be constantly updated, with authors receiving their due credit in a list of contributors. Literature Matrices also enable researchers to obtain a complete summary of the literature without going through the cumbersome process of copying and reading a manuscript for the first time. In contrast, researchers' time can be spent more efficiently in reviewing what has already been compiled and attempting to expand the Literature Matrix with other relevant bibliographic references. Outcomes research application In order to evaluate the literature, a graduate student performed a thorough literature search. All relevant articles were copied, read, and the data extracted according to the established categories. Once the Literature Matrix had been completed, Drs. Guller compared the current project results with results published in the literature. The structured information in Literature Matrices also allowed Dr. Guller to compare the strengths and weaknesses of the current project in relation to previous publications. Once this phase was completed, Dr. Guller proceeded to the final writing of the manuscript using Output Templates. Outcomes research application At the end of the project, Dr. Guller combined the Question Diagram, Analysis Chart, and Literature Matrices to write the final manuscript. While Analysis Charts provided the information concerning the statistical techniques used in this study, Literature Matrices provided the basis for comparison of the study results against previous publications. Although not included in the final manuscript, Dr. Guller also had access to multiple analysis files through Research Manager to orient him in each of the steps taken during the research question formulation, data analysis, and literature review. Use of web application by clinical researchers The use of web applications by individual clinical researchers can be summarized in Figure 9 . Figure 9 Integration between UR tools and clinical researchers Utility Since the concept of streamlining the interdisciplinary collaboration preceded the existence of the current suite of web applications, different versions of the central idea have been gradually applied since the second half of 2002. Although our usability, qualitative, and economic studies to evaluate this application are still ongoing, we have noticed a significant improvement in the number and quality of our publications as evidenced by the increasing acceptance rates of our manuscripts for publication in peer-reviewed journals. The Web applications are currently used in research projects involving Duke University and other universities in the United States and abroad, where they have been shown to facilitate inter-institutional collaborations. Discussion Improving the efficiency of an interdisciplinary approach to secondary data analyses has multiple potential benefits. These include an increase in the overall clinical significance of the final publication, decrease in the number of failed projects, decrease in the time for completion of individual projects, improvement in the education of future outcomes researchers, decrease in the cost-benefit ratio for individual outcomes research projects, and, perhaps most importantly, an automation of repetitive tasks. This last factor is crucial since eliminating repetitive tasks will allow researchers to concentrate on the design of innovative projects [ 2 ]. Surprisingly, few systems and applications have been described to solve the problem of complex interdisciplinary collaboration between clinicians and statisticians. Isolated approaches have usually focused on specific portions of the outcomes research process, without attempting to integrate them into a cohesive system. For example, Marshall [ 13 ] has proposed the use of a secure Internet web site for collaborative medical research and data collection. While this system seems to achieve its proposed objectives, it does not improve the process of guiding teams in the translation of data into useful clinical information. Other systems have approached the process in a more comprehensive manner. The Research Toolbox [ 14 ], for example, is a software application that combines databases for literature searches in addition to providing templates for the scientific output. The system is applicable to any type of research, but lacks the ability to connect researchers over the World Wide Web. It also does not address the formulation of research questions from existing databases, selection of statistical techniques, exchange of manuscripts, or project management. Finally, the Web-based Medical Information Retrieval System (WebMIRS) project, funded by the National Library of Medicine [ 15 ], allows researchers not only to evaluate the database content but also to perform the data extraction of specific subsets of the data set. In spite of its high performance as a research tool, WebMIRS is currently restricted to one single publicly available database (National Health and Examination Survey – NHANES), and does not contribute to other phases of the outcomes research process. Although this newly developed system of applications provides a significant improvement in the way secondary data analyses are conducted, it still has limitations. First, because of the lack of a formal evaluation of the effectiveness of this system, we are unable to quantify its real time and cost saving benefits. Second, the system is currently restricted to secondary analyses and does not allow for the planning of prospective data collection. Although one of the main advantages of formulating a research question based on existing data sets is the bounded nature of the process, future applications should attempt to create rules and algorithms that may guide prospective data collection. Conclusion In summary, we have experienced that this system has significant advantages over the traditional manner of conducting outcomes research based on secondary data analyses. This tool may have important applications, not only resulting in an improvement in the overall efficiency of the outcomes research process, but also affecting the way new outcomes researchers are trained and introduced to a research environment. Availability and requirements The Web application is available at Abbreviations XHTML Extensible HyperText Markup Language 1.0 JAVA: by Sun Microsystems ICD9-CM: International Classification of Diseases, Ninth Revision – Clinical Modification NIS: Nationwide Inpatient Sample GNU: GNU's Not linux General Public License WebMIRS: Web-based Medical Information Retrieval System NHANES: National Health and Examination Survey UR: Uniform Resource Competing interests The author(s) declare that they have no competing interests Authors' contributions Ricardo Pietrobon – design, manuscript drafting Ulrich Guller – design, manuscript revision for important intellectual content Henrique Martins – design, manuscript revision for important intellectual content, software programming Andreia P Menezes – design, manuscript revision for important intellectual content Laurence D. Higgins – design, manuscript revision for important intellectual content Danny O. Jacobs – design, manuscript revision for important intellectual content Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544191.xml
544344	Protein family comparison using statistical models and predicted structural information	Background This paper presents a simple method to increase the sensitivity of protein family comparisons by incorporating secondary structure (SS) information. We build upon the effective information theory approach towards profile-profile comparison described in [Yona & Levitt 2002]. Our method augments profile columns using PSIPRED secondary structure predictions and assesses statistical similarity using information theoretical principles. Results Our tests show that this tool detects more similarities between protein families of distant homology than the previous primary sequence-based method. A very significant improvement in performance is observed when the real secondary structure is used. Conclusions Integration of primary and secondary structure information can substantially improve detection of relationships between remotely related protein families.	Background Detecting an evolutionary relationship between proteins is the basis for functional inference. Existing methods most often rely on sequence information in an attempt to quantify the evolutionary divergence or similarity between the sequences compared. A significant similarity would suggest that the proteins are related. However, in many cases sequences have diverged to the extent that their similarity is undetectable by standard sequence comparison algorithms. Nevertheless, they may still have similar structures and functions [ 1 , 2 ]. It has long been postulated that evolutionary pressure acts upon the three-dimensional structure of proteins and intra-protein interactions rather than at the level of the primary sequence [ 3 , 4 ]. Indeed, there is plenty of evidence to suggest that 3D structure is more conserved than sequence [ 5 , 6 ]. Since the protein structure usually prescribes the function of a protein, relying on structural information (for example, through structure comparison) for functional inference is more effective and reliable than using only the primary sequence. However, although methods of sequencing proteins have become faster and more cost-efficient due to recent technological advancements, methods to determine structure are still in their infancy. In fact, less than 5% of newly sequenced proteins have a known structure. Current empirical processes used to determine structure of proteins are neither efficient nor scalable to use upon the entire known protein space. There have been many attempts to build algorithms that predict protein structure from amino acid sequence. Unfortunately, this is a hard problem, and existing methods are only partially successful [ 7 ]. On the other hand, predicting the secondary structure of a protein has been more successful. There are various algorithms that predict the secondary structure from primary amino acid sequence information alone [ 8 - 13 ]. The accuracies of these algorithms have been steadily increasing, and one of the most successful algorithms to date is PSIPRED [ 13 ], which has an average accuracy of about 80%. Since the architecture of the secondary structure elements of a protein affects its global structure, it has been suggested that secondary structure information can be used to detect subtle similarities between proteins that have diverged substantially in the course of evolution. This principle was tested in [ 14 ] where a dynamic programming algorithm with a secondary-structure based scoring matrix was used to compare protein sequences over the alphabet of secondary structures. However, relying solely on secondary structure information might lead to poor performance overall, as much of the original information about the individual amino acids is lost. Alternatively, one can use both representations to assess protein similarity. Incorporating secondary structure information into protein comparison is not a new idea. Several researchers have attempted to boost performance and sensitivity of various methods by adding this extra degree of information with some success. Yu et al. encoded functionally conserved sequence patterns into probabilistic structural models (that comprise a family of hidden Markov models) [ 15 ]. The models were benchmarked against the trypsin-like serine protease family and the globin family, and in both cases proved to have high specificity and sensitivity compared to the models in use at the time (primarily, BLAST) in remote homology detection. One of the limitations of this model, however, was the reliance on threading methods requiring at least one determined structure to build a model. Hedman et al. [ 16 ] included information about predicted transmembrane segments into the standard Smith-Waterman and profile-search algorithms for membrane proteins by adding an extra delta (score) when two residues that are both predicted to belong to transmembrane segments are aligned. This method was found to improve the detection rate, mainly by increasing specificity (ie. decreasing the number of false positives). Ginalski et al. [ 17 ] generalized a method of creating "meta profiles" by combining sequence information with predicted secondary structure information. Total scores were calculated by summing the raw score obtained from the shifted dot product of the sequence profile vectors and the shifted dot product of the secondary structure probability vectors (weighted by some factor). This technique was derived from hybrid threading approaches and was found to be more sensitive than the sequence-only approach or sequence-to-structure threading approach. Teodorescu et al. [ 18 ] proposed a linear combination of threading and sequence-alignment to produce a single (mixed) scoring table. This method was found to be particularly sensitive in detecting sequences with less than 25% of sequence identity, yet with similar structures. The final model outperforms the individual scoring methods. These and similar studies have indicated that the incorporation of secondary structure information, even if predicted, can increase sensitivity and specificity of a protein comparison model. Here we describe a method that integrates secondary structure information with primary sequence information in a single scoring scheme, using a single statistical representation. The model can be applied to any protein family and does not require the application of expensive threading algorithms. Our method extends our previous work on profile-profile comparison [ 19 ]. Specifically, we use the profile representation (generated by PSI-BLAST) as a statistical model of a protein family and augment the profile with structural information. We then compare profiles of different protein families, in search of possible remote kinship, using an information theory-based scoring function. By comparing models of protein families we can detect similarities that are not detected when comparing individual sequences. We show that the new algorithm improves performance and can detect more similarities between remote protein families. These similarities can be used to classify protein families into super-families and detect higher order structure within the protein space. Methods and Results Data sets We use a data set of domain families derived from the SCOP classification of protein structures [ 20 ], release 1.50. This set contains 23,780 protein domains classified into 1,287 protein families. Each of the 1,287 families is represented by a profile that was generated using PSI-BLAST [ 21 ]. The seed of the profile was selected to be the sequence whose average distance from all other members of the family is the smallest. Families for which there is only one member, or for which PSI-BLAST failed to generate a profile, were represented by a profile generated directly from the seed sequence by using probabilities derived from the original BLOSUM62 frequency matrix [ 22 ]. A subset of 456 families was used in our study, all of which belong to superfamilies that contain at least 3 families. A smaller subset of 120 families was used for parameter optimization. Sequence profiles The PSI-BLAST profiles are the basis for our representation of a protein family. Each profile is a n -tuple of probability distributions of amino acids, derived from a group of related proteins, where n is the length of the multiple alignment of these proteins. It is represented in software as a two dimensional matrix of 20 rows and n columns, where each column (known as a profile column), is a probability distribution p over the 20 amino acids in one position in the multiple alignment. These profile columns form the basis of profile-profile comparisons. Secondary structure information We use two types of secondary structure information in our experiments: true information and predicted information. The true secondary structure information is gleaned from the PDB files of the seed proteins using STRIDE [ 23 ]. Stride defines eight types of secondary structures b , B , C , E , H , I , G , T where b and B stand for Bridge, C = Coil, E = Strand, H = AlphaHelix, I = PiHelix, G = 310Helix and T = Turn. We reduce this set to the three main secondary structures (helix, strand and coil) by mapping H, I, G to H, and b, B, C, T to C. The predicted secondary structure information is predicted using PSIPRED [ 13 ]. PSIPRED uses the intermediate sequence profiles generated by PSI-BLAST as input for the prediction algorithm. This profile matrix is fed into a standard feed-forward back-propagation neural network with a single hidden layer using a window of 15 residues. This net has three output units corresponding to each of the three states of secondary structures. Another window of 15 positions of these three outputs (per amino acid) are then used as input into a second neural network to filter and smooth outputs from the main network. The final output is the probability that a certain amino acid position in the seed sequence of a profile is in a coil, helix, or strand. PSIPRED reports an average Q3 score of approximately 80% accuracy. Integrating secondary structure with primary structure Apriori, it is unclear how one should integrate secondary structure with primary structure in a single model. For example, one might think of a representation over a generalized alphabet, that considers all possible pair combinations of amino acids and secondary structure elements. Assuming independence between positions (which is the underlying assumption of position specific scoring matrices, as well as of HMMs that are used in computational biology), then this representation implies that for each position i we have a statistical source that emits amino acid a and secondary structure s with probability P i ( a , s ) such that and every position can be represented by a vector of 60 probabilities over this pair alphabet. This representation implicitly implies that the amino acid emitted and the secondary structure are two different features of the objects generated by the source, while in reality the secondary structure is not a "character" or an independent property of the emitted objects, but rather a characteristic of the source itself that is usually unknown. This property introduces some special constraints on the distribution of amino acids that are emitted by the source. In other words, the secondary structure and the amino acid distribution in a position are strongly dependent on each other, but one is hidden while the other is visible . Noting that P i ( a , s ) can be written as P i ( a / s ) P i ( s ), we can decompose the parameter space into the parameters of the secondary structure distribution, and the parameters of the conditional probability distributions over amino acids. However, the typical amino acid distributions that are available from multiple alignments of protein families differ from these conditional probability distributions by definition. Furthermore, there are other subtleties that one should bear in mind when designing an integrated statistical model for a protein family. More precisely, assume we have a protein family, where all proteins adopt a certain structural conformation of length n . This conformation can be described in terms of the set of 3D coordinates of the n positions, or in terms of the set of distances between coordinates S = ( ) where is the set of distances from the i -th residue to all other residues – the latter being more amenable for a representation as a statistical source, as it is invariant to translations and rotations. Although there is structural variation across the different instances of the protein family, it is significantly smaller than the sequence variation, and we will assume that a single consensus conformation S reliably describes the protein family. The structural conformation determines the statistical properties of the source distributions. Namely, it induces certain constraints on the sequence space that can be mapped to that conformation, based on the physical properties of its topology. In other words, it induces a probability distribution over the sequence space of O (20 n ) sequences that can be mapped to that conformation P ( a 1 , a 2 , ..., a n / S ). Note that due to convergent evolution it is possible that two disconnected regions in the sequence space (two families of homologous proteins) will be mapped to the same conformation (although experimental evidence and simulation results [ 24 ] suggest that this is not very likely, and for most protein families it is reasonable to assume that the sequence space that is mapped to a structural conformation is connected). This 20 n -dimensional distribution clearly introduces dependencies between remote positions, and the exact probability distribution in a position depends on the amino acids observed in all other positions P ( a i / a 1 , a 2 , ..., a i -1 , a i + 1 , ..., a n , S ). Accurate knowledge of the all-position probability distribution P ( a 1 , a 2 , ..., a n / S ) would allow one to compare two sources of protein families theoretically by comparing these high-dimensional distributions. However, because of (limited) data availability and for mathematical simplicity, the marginal probabilities are usually used in practice to describe the source. Given a multiple alignment of a specific protein family, and the corresponding profile, the empirical distribution of amino acids at position i , denoted by , is essentially the marginal probability of amino acids at that position, as constrained by the global conformation , i.e. The complete model is represented as a set of marginal probability distributions, one per position. So far we have not considered the secondary structures explicitly. The secondary structure sequence s is a reduced representation of S that, while incomplete, describes quite accurately the topology of the protein. Given S , the knowledge of s however does not affect the distribution of amino acids at a position, i.e. P i ( a / s , S ) = P i ( a / S ) Nevertheless, the secondary structure information can still be useful when comparing protein families. This is because some information is lost if one is to use just the marginal amino acid distributions. For example, the same marginal amino acid distribution can be observed in different secondary structure conformations and on the other hand, even highly similar fragments of secondary structures can be associated with different amino acid distributions. The most effective way of comparing two protein families is by comparing their (consensus) structural conformations S 1 and S 2 . Indeed, it has been shown that structure comparison is much more effective in detecting remotely related families [ 19 , 20 , 25 ]. In statistical terms, one can formulate the problem of comparing consensus structures S 1 and S 2 as comparing two sources that induce different probability distributions over the conformation space P 1 ( S ) and P 2 ( S ). However, characterizing these distributions is very difficult. Moreover, convergent evolution might result in two different sequence sources with structurally similar conformations. These relations are usually perceived weaker than families that are similar both in sequence and structure [ 20 ]. Therefore, a proper comparison should account for both the primary and tertiary structure. In statistical terms, we are interested in comparing the joint distributions and , where the distributions are again marginalized over all positions other than i , and is a vector of inter-residue distances. The joint distributions can be rewritten as where the last step uses the more accurate marginal probabilities P i ( a / S ) that are based on all vectors of inter-residue distances (and match the empirical distributions ). As was mentioned earlier, obtaining S is difficult (and therefore also characterizing the distributions of inter-residue distances). On the other hand, secondary structure (which can be viewed as an approximation of S ) is more readily available, and can be predicted quite reliably from sequence information. Therefore we suggest to approximate where P i ( s ) is the probability to observe a secondary structure s at the i -th position. (When the secondary structure is known the distribution over secondary structures assigns probability 1 to one of the structures and zero otherwise. However, with predicted information, each state is usually assigned a non-zero probability based on the amino acids in that position and neighboring positions.) Plugging in the empirical distributions for P i ( a / S ) we get i.e., the empirical distribution of amino acids at a position, , is conditionally independent of the distribution P i ( s ). Therefore, to completely describe the source one needs to provide the parameters of the marginal distribution of amino acids, and the parameters of the secondary structure distribution. Since the two distributions are assumed independent, they are amenable to a representation in which their parameters are appended together. I.e. the secondary structure probabilities are appended to the probabilities of the 20 amino acids. Our method is based on an extension of the original profile representation in [ 19 ]. Using the three PSIPRED probabilities, we augment the profile columns of primary information to make a probability distribution over 23 values (the 20 amino acids plus 3 secondary structures). Note that by doing so, each profile column is now dependent upon and contains information about its neighbors, since PSIPRED uses the profile columns surrounding each profile column to deduce the probability that the position in question is in a specific secondary structural conformation. This is the key element that enhances the accuracy of this tool in protein family comparisons. Moreover, the method is "self-contained" in the sense that for the secondary structure prediction, PSIPRED uses the same profiles that are generated by PSI-BLAST. To use the profile-profile metrics described next, the 23-dimensional profile columns have to be normalized to conform with probability distributions. However, apriori it is not clear if the primary information and the secondary structure information should be weighted equally. To control the impact of the secondary structure information on the representation we introduce a mixing parameter γ that ranges from 0 to 1. The secondary structure probabilities are normalized such that they sum to γ while the amino acid probabilities are normalized such that they sum to 1 - γ . The higher γ is, the more dependent the profile column is upon secondary structure information. This parameter is optimized as described in section 'Parameter optimization'. Note that our normalization maintains the conditional independence of the two types (primary and secondary), as described above. Each component of the extended profile can be viewed as a sub-profile. Since each one of the two components is summed independently to a non-zero probability then two symbols must be "emitted": an amino acid and a secondary structure. Profile-Profile comparison In this section we review the main elements of our profile-profile comparison algorithm that was introduced in [ 19 ]. We compare profiles using the dynamic programming algorithm with an information theoretic-based scoring function to score pairs of profile columns. Given two profiles P = p 1 p 2 p 3 ... p n and Q = q 1 q 2 q 3 ... q m , where n and m are the lengths of the profiles (the number of positions or columns) and p i , q j are probability distributions over the 23 letter alphabet of amino acids and secondary structures, we define the similarity score between two columns p i and q j based on their statistical similarity. The similarity score is composed of two elements: the divergence score and the significance score. The divergence score To estimate the divergence of two probability distributions we use the Jensen-Shannon (JS) divergence measure [ 26 ]. Given two (empirical) probability distributions p and q , for every 0 ≤ λ ≤ 1, the λ -JS divergence is defined as where D KL [ p \|\| q ] is the Kullback-Leibler (KL) divergence [ 27 ], defined as and r = λ p + (1 - λ ) q can be considered as the most likely common source distribution of both distributions p and q , with λ as a prior weight (here set to 0.5). We call the corresponding measure the divergence score and denote it by D JS . This measure is symmetric and ranges between 0 and 1, where the divergence for identical distributions is 0. Besides being symmetric and bounded, an attractive feature of the D JS divergence measure is that it is proportional to the minus logarithm of the probability that the two empirical distributions represent samples drawn from the same ("common") source distribution [ 28 ]. It has also been shown that is a metric [ 29 ]. The significance score The divergence score measures one aspect of the statistical similarity of p and q : their relative distance. However, it does not consider the uniqueness of the two distributions. A match between two distributions that resemble the background distribution is not as significant as a match of two distributions that resemble each other, but are very different from the background distribution. In other words, the more unique the distributions are (and hence, also their common source), the more significant is a match between them. To assess the significance score S of a match we measure the JS divergence of the (common) source distribution, r , from the base (background) distribution P 0 . S = D JS [ r \|\| P 0 ] In this study the background distribution is composed of two components: the background distribution of amino acids (estimated from a large sequence database) and the background distribution of secondary structure elements (estimated from all PDB structures). The components are mixed using the same mixing parameter γ described in section 'Integrating secondary structure with primary structure'. The significance measure reflects the probability that the source distribution, r , could have been obtained by chance. The higher r is, the more distinctive the common source distribution, and the lower the probability that it could have been obtained by chance. The similarity score We define the similarity score of two probability distributions p and q as a combination of the divergence score and the significance score: With this expression, the similarity score of two similar distributions ( D → 0) whose common source is far from the background distribution ( S → 1), tends to one. On the other hand, the similarity score of two dissimilar distributions ( D → 1) whose most likely common source distribution resembles the background distribution ( S → 0) tends to zero. This scoring scheme also distinguishes two distributions that each are similar to the background distribution ( D → 0 and S → 0 giving Score - 1/2) from two dissimilar distributions, but whose common source is similar to the background distribution ( D → 1 and S → 0 giving Score = 0). In a recent study [ 30 ] it has been shown that this scoring function is one of the best, when compared to other methods for profile-profile comparison. Note that our measures are functionals of the probability distributions, based on variations of the entropy function, and specifically the KL divergence function. One of the nice properties of this function is that it is additive in the following sense. Assume we have a probability distribution p over a set X that is obtained by "mixing" two probability distributions over two disjoint subsets: p 1 over the subset X 1 and p 2 over the subset X 2 (where X = X 1 ∪ X 2 and X 1 ∩ X 2 = θ ). Let γ be the mixing parameter, i.e. the total weight of the first distribution p 1 in the combined distribution p . Assume q is obtained in a similar manner from q 1 and q 2 . Then, In other words, this measure preserves independence between the two subsets. Therefore, with our extended profile representation, the new functionals are simply a weighted sum of the individual functionals over the subsets X 1 (the secondary structure) and X 2 (the primary structure). Note however that this property holds for the divergence and the significance measures but not for the final similarity score that is a combination of the divergence and the significance scores. An alternative would be to compute the divergence, significance and similarity scores independently for the secondary and primary structures, and then combine the two similarity scores into one, with weights γ and (1 - γ ) respectively. The effect of secondary structure on the pairwise scores It is interesting to compare the similarity scores before and after the addition of secondary structure information. To assess the impact of this information, we computed the distribution of similarity scores for five types of profile columns, depending on the type of their seed amino acid. We refer to the amino acid at position i of the seed sequence (see section 'Data sets') as the seed amino acid of the i -th profile column. Two seed amino acids are defined as similar, neutral, or dissimilar based on their BLOSUM62 scoring matrix [ 22 ], with positive, zero and negative substitution scores respectively. The five types of column pairs are: (1) a column with itself ( identical columns ), (2) different columns that are associated with the same seed amino acid ( strongly similar columns ) (3) different columns that are associated with similar seed amino acids ( similar columns ), (4) different columns with mutually neutral seed amino acids ( neutral columns ), and (5) different columns with dissimilar seed amino acids ( dissimilar columns ). We repeated this calculation before and after the integration of true secondary structure information (using the optimal mixing parameter γ , see section 'Parameter optimization') and the results are plotted in Figure 1 . As the figure indicates, there is a slight shift between the distributions, and the addition of secondary structure information pushes the distributions further apart, decreasing the distribution overlap, as desired. Although the differences are small (due to the very small value of the optimal mixing parameter), the effect on the performance is significant as is demonstrated in section 'Discussion'. Comparison of scoring functions We compared our information-theoretic scores to other popular scoring schemes. We tested the correlation scores based on the scalar product of the vectors (as was suggested in [ 31 ]). We also tested the ALLR (Average Log Likelihood Ratio) scoring function that was suggested in [ 32 ]. This scoring function is also based on information-theoretic principles, and resembles ours. Given two empirical probability distributions p and q , their ALLR score is defined as where n p ( n q ) is the number of total counts from which p ( q ) is derived, and P0 is the background distribution. We computed the correlation scores and ALLR scores for the same sets of columns defined in the previous section and compared it to the information-theoretic scores (Figure 2 ). Note that the correlation scores are less successful in distinguishing related columns from columns which are likely to be unrelated (compare Figure 2a and Figure 2b ). The overlap is larger and the tail of the fifth distribution (dissimilar columns) falls well within the first distribution (identical columns). Specifically, 24% of the pairs of dissimilar columns have correlation scores that overlap with scores of identical columns, compared to only 2.1% when using our similarity scores. We believe that this may affect the performance significantly. On the other hand, the ALLR scores have very similar properties to ours, although the overlap between dissimilar columns and identical columns is greater (4.4%). Parameter optimization Our algorithm ( prof _ ss ) depends on several parameters: (1) a shift parameter is introduced to convert the similarity scores to scores that are suitable for local protein comparison (other transformations were tested in [ 19 ] and proven less effective); (2) gap penalties for the dynamic programming algorithm; (3) the mixing parameter γ Shift parameter and gap penalties as Figure 2a shows, the distributions of identical columns (red line) and distributions with dissimilar seed amino acids (black line) are quite well separated around 0.5. In addition, distributions with mutually neutral seed amino acids peak at a similarity score around 0.45. Note that the new similarity scores (after the addition of the secondary structure information) preserve the overall behavior (quantitatively and qualitatively) as the old similarity scores (see Figure 1 ). The mean of the scores is unchanged and only the variance has increased. Therefore, we decided to maintain the same set of parameters that were optimized in [ 19 ]. Specifically, we used the same shift value of 0.45 and the same gap penalties of 2 (gap opening) and 0.2 (gap extension). We have also tested position-specific gap penalties based on the SS information, but without any apparent improvement in performance. Mixing parameter To estimate the best value for γ we used a subset of 120 families and assessed the performance for different values of γ . Our performance evaluation procedure works as follows: true relationships are defined to be between those families that share a superfamily and all others are defined as false relationships. For each family within the test set, we calculate the profile-profile similarity against all 1287 families for a single value of the mixing parameter γ . These results are sorted by raw score and the number of true family-family relationships are counted before the first false relationship is detected (this is basically a sum of ROC1 scores). The tradeoff between the primary sequence information and secondary structure probabilities was varied from zero to one. With zero dependence on secondary structure the method is equivalent to prof _ sim (profile-profile comparison based on just primary structure). The results are shown in Figure 3 . As the graph indicates, setting γ = 0.055 (i.e. 0.055 weight on the secondary structure information and 0.945 on the sequence information) gave the best performance. (Note that if each secondary structure was given as much weight as a single amino acid γ would be or ~0.13). When only secondary structure information was used ( γ = 1), the performance was much worse than when only sequence information was used ( γ = 0). These corner-case results and the fact that the best results were obtained with γ << 0.5 suggest that for protein family comparison, the coarse-grained secondary structure information is noisier and less reliable than sequence information. However, as the graphs indicate, using both sources of information clearly improves performance. Our tests were done using actual secondary structure information in the profile; however, similar results were obtained when the predicted information was used for one or both of the profiles (see Figure 3b ). Statistical significance To differentiate true similarity values from those that may be observed by chance, it is essential to establish a baseline empirical distribution for the scores. Here we used the statistical framework of the extreme value distribution (EVD). Although rigorous mathematical proof has not been found for local gapped similarity scores, empirical studies have shown that the distribution of these scores can be approximated by this distribution. An empirically fit EVD also has the benefits of being a true fit to the quirks of a particular protein family. Three such distributions were established to assess the significance of the profile-profile matches. All distributions were fit with the 'fit' function in gnuplot using the nonlinear least-squares (NLLS) Marquardt-Levenberg algorithm. The first distribution is based upon comparisons between unrelated families (defined as families that belong to different SCOP classes and do not share significant structural similarity). This distribution is useful in that it can be used to assess the significance of a score in comparing any pair of protein families, without further need for computations. Practically, this aggregates all comparisons between non-related families into a single list. This is essentially the distribution of similarity scores of random profiles, as shown in Figure 4a . By fitting an EVD to this distribution we can estimate the statistical significance (e-value) of any raw similarity score. We refer to this method as the uniform approach (uniform parameters). The second distribution is similar to the first, except a correction was made for the length of a profile, similar to the approach employed by FASTA [ 33 ]. By chance, the raw score of a profile-profile comparison is greater for those profiles with many more residues than the score of two smaller profiles. To correct for this occurrence, all raw scores were fit to a logarithmic curve of the product of the two profile lengths. The mean and variance of this fit was used to calculate a zscore. Accounting for undersampling at the ends of the spectrum, the means were fit to a linear curve and the variance was constant throughout. The distribution of zscores was then fit to an EVD, as is shown in Figure 4b . This distribution estimates better the statistical significance of raw similarity scores since it accounts for the biases introduced due to the lengths of the profiles. The third distribution proves to be the best approach in assessing significance of matches with a particular profile. This distribution is created on a per-family basis. The scores of each family against all (unrelated) SCOP families were fit to an EVD. Since many of the family profiles are unrelated to the query family, the corresponding scores provide a relatively reliable baseline distribution. This approach is a robust method to assessing the significance of matches for a particular profile since it allows for any unusual properties of the query profile (like unusual amino acid composition) and the parameters are adjusted accordingly (see Figure 5 ). Once again, from the fitted EVD, the e-value of the raw similarity scores is estimated from this fit. The third method of measuring statistical significance is self-calibrating and provably more accurate than the previous two methods, and our performance evaluation tests indicate that this is the best method overall (see Figure 6 ). However, it is an intractable method when given a single pair of profiles to compare, since there is no prior knowledge about the baseline distributions of either profile. As a result, we must rely on the second method to measure statistical significance in these cases. Discussion We evaluate the performance of our algorithm using the SCOP database as a benchmark and two measures of performance. The first counts the number of weak relationships between protein families (as implied by the SCOP classification) that can be detected with our method. Specifically, each family in our test set is compared with all other protein families and the results are sorted based on the p-value. Given the sorted list we count the number of true family-family relationships that are detected before the first false positive occurs. This measure is applied to each family individually , and the results, summed over all families in the test set are given in Table 1 . We compare our results to Gapped-BLAST, PSI-BLAST and prof _ sim (as reported in [ 19 ]). Usually a false positive is defined as a relation between families that do not belong to the same superfamily. This popular criterion, however, is somewhat strict as relations between families that belong to the same fold can also be considered as positives. We use the following terminology to distinguish between the different types of "false positives". We define a relationship between two protein families to be a true relationship if both families belong to the same superfamily, a possible relationship if both families belong to the same SCOP fold, a weak relationship if they belong to the same class, suspicious if they belong to different classes (excluding the case of an all-alpha ↔ all-beta pair) and an error if one family is all-alpha and the second is all-beta. We repeat the procedure described above, each time using a different definition of a false positive. The results are summarized in Table 1 . The second measure we use is the receiver operator characteristic (ROC) measure, a common measure in assessing sensitivity and selectivity. Given a sorted list of results, the ROC index measures the area under the curve that plots the positives versus the negatives. Maximal performance translates to a perfect separation and a maximal normalized ROC score of 1. The ROC-N measure is a variation over the ROC measure, where the plot is truncated at N negatives. In other words, the ROC-N measure is the number of true positives detected up to N false positives. Here we used the popular ROC-50 measure. To obtain the ROC-50 scores for each method we pool together all pairwise comparisons for all protein families, and sort them by their normalized e-value. The number of true positives is aggregated until 50 false positives occur. As before, we repeated this procedure with different definitions of false positives, and the results are summarized in Table 2 . A detailed break-up of the pairwise similarities detected with each method is given in Table 3 (using the most strict definition of a false positive). Note that prof _ ss improves over prof _ sim (for all types of false positives) although the improvement is smaller compared to the one reported in Table 1 . The difference in performance is striking when the true secondary structure information is used. Despite the moderate contribution to the profile (the optimal γ was set to 0.055), the new algorithm almost doubles the number of pairwise relationships that are detected. Examples In this section we give several interesting examples of alignments between remote protein families that exemplify the differences between sequence-based profile-profile alignments and the new generalized profile alignments. The "winged helix" DNA-binding domain superfamily This superfamily is part of the DNA/RNA-binding 3-helical bundle fold. We compared two families from that superfamily: the restriction endonuclease FokI, N-terminal recognition domain (family a.4.5.12, seed scop domain d2foka3), and the replication terminator protein (family a.4.5.7, seed scop domain dlbm9a_). Although designated as all-alpha, proteins in this superfamily contain a small beta-sheet at the core. The similar substructures have three alpha helices and a couple beta strands, prof _ sim is able to roughly match up the helices but not the beta strands with a rms of 11.96. The predicted secondary structure does not improve the alignment in this case, however, when the true secondary structure is used, prof _ ss is able to completely align the helices as well as most of the strands with a much better rms of 4.45 (Figure 7 and Figure 8 ). The concanavalin A-like lectins/glucanases superfamily This superfamily belongs to the concanavalin A-like lectins/glucanases fold, characterized by a sandwich structure with 12–14 strands in 2 sheets. We compared two families in this superfamily: the beta-Glucanase-like family (b.29.1.2, seed domain dlcpm__) and the vibrio cholerae sialidase, N-terminal and insertion domains (b.29.1.8, seed domain dlkit_2). These class beta proteins have complex topology and are hard to align even with structure alignment algorithms. In this example, the two sets of beta sheets are nicely aligned by prof _ ss both when using the predicted information and the true secondary structure information. On the other hand, prof _ sim is unable to align the sheets at all (see Figure 9 and Figure 10 ). The alpha/beta-Hydrolases superfamily The alpha/beta-Hydrolases belong to the fold by the same name. Proteins with that fold are composed of 3 layers at the core, of alpha/beta/alpha. We compared two families in this superfamily: the carbon-carbon bond hydrolase family (c.69.1.10, seed domain dlc4xa_) and the bromoperoxidase A2 family (c.69.1.12, seed domain dlbrt__). These are large and complex proteins with many helices and strands. prof _ sim reports an alignment that aligns perfectly one small alpha helix and two beta strands. With predicted secondary structures, prof _ ss is able to generate a much longer alignment, with γ alpha helices and 4 beta strands. The alignment is not perfectly in sync, but all secondary structures are roughly in position. When using the true secondary structure information in prof _ ss the alignment improves and a better overlap is observed (see Figure 11 and Figure 12 ). Conclusion This paper presents a simple method to improve remote homology detection between protein families. We use statistical models of protein families in the form of profiles, and by incorporating secondary structure information within that model, we can reuse existing comparison methods for comparing profiles. It is shown that this method improves over the previous method that is based only on primary sequence information. As opposed to other methods that compare single proteins, our method compares models of protein families. Instead of summing over different models, our model combines structural and primary sequence information within the profile itself. Our method allows us to explore a wide range of scenarios, between purely sequence-based representation and a purely secondary-structure based representation. The optimization of the single mixing parameter shows that the slight incorporation of predicted secondary structural information is invaluable. Since predicted structure information in PSIPRED comes from neighboring profile columns, this proves that each profile column confers extra information that is relevant to its neighbors and is useful to inferring protein relationships. Furthermore, it is shown that if true secondary structure information is used, performance improvements are very significant and the number of relationships that can be detected is almost doubled. We conclude that despite the high overall accuracy of the secondary structure prediction method, its imperfect nature can greatly affect the performance. However, our method can be generalized to any secondary structure prediction method that produces estimated probabilities for secondary structure, so should a new prediction method be found that performs better than the current methods, the model presented here is expected to reflect the improved performance and consequently improve homology detection. Authors' contributions RC extended the prof _ sim program and integrated secondary structure information, optimized the model, ran experiments, and analyzed the result sets. GY conceived of the study, designed the model and analyzed the results.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544344.xml
538270	Comparative study of matrix metalloproteinase expression between African American and Caucasian Women	To date there are 26 human matrix metalloproteinases (MMPs) which are classified according to their substrate specificity and structural similarities. The four major subgroups of MMPs are gelatinases, interstitial collagenases, stromelysins, and membrane-type matrix metalloproteinases (MT-MMPs). This study investigates the expression of 26 MMPs, which have been shown to play a role in cancer metastasis. Breast tissues and cell lines derived from African American patients and Caucasian patients were assayed to demonstrate alterations in the transcription of genes primarily responsible for degrading the extracellular matrix (ECM). The expression levels of the extracellular matrix and adhesion molecules were analyzed using the gene array technology. Steady state levels of mRNAs were validated by RT-PCR analysis. Total RNA was isolated from tissue and cell lines and used in the RT-PCR assays. From this data, differential expression of MMPs between 6 breast cancer cell lines and 2 non-cancer breast cell lines was demonstrated. We have performed an in vitro comparison of MMP expression and established differences in 12 MMPs (3, 7, 8, 9, 11–15, 23B, 26, and 28) expression between African American and Caucasian breast cell lines. Thus, evidence indicates that altered expression of MMPs may play a role in the aggressive phenotype seen in African American women.	Introduction In 2003, it was estimated that approximately 1.3 million Americans would be diagnosed with invasive cancer. Of this group, racial/ethnic minorities account for a disproportionate number of these cancers [ 1 , 2 ]. Invasive breast cancer usually begins in either the lobules or the ducts of the breast. These tumors then metastasize via the breast associated and thoracic lymphatic tissue [ 3 ]. The incidence of breast cancer in Caucasian women (112 out of 100,000) is higher than in African American women (AA) (95 out of 100,000) after the age of 40, however, the mortality suffered by (AA)(37 out of 100,000) is higher than Caucasian women (CAU) (31 out of 100,000) at every age [ 4 ]. Thus a greater percentage of AA women die from breast cancer and resulting metastasis. In 2004, an estimated 215,990 new cases of invasive breast cancer is expected to occur among women in the United States [ 5 ]. Breast cancer is the most common cancer among AA women; however, the rate of newly diagnosed cases is about 13% lower than CAU women [ 6 ]. There is accumulating evidence that AA women have a higher frequency of more aggressive tumor types, which have been shown to lead to higher mortality rates. Studies show that compared Caucasian women (CAU), African American women (AA), regardless of age had proportionally more Grade III tumors and fewer Grade I and II tumors for all stages combined and for each individual stage group [ 7 ]. The grade of cancer has been shown to be a prognostic factor with higher-grade tumors being associated with reduced survival [ 7 ]. The most common cause of death in breast cancer patients is metastasis of breast cancer cells to bones, lungs, liver and brain and the progressive growth of the cancer at these sites [ 7 , 8 ]. Therefore, controlling breast cancer metastasis represents an effective method of preventing or slowing disease progression. The extracellular matrix (ECM) is a complex structural entity surrounding and supporting organs and tissues of the body. The ECM plays a key role in cell-cell signaling, wound repair, cell adhesion and tissue function. Recent studies suggest that cell adhesion proteins located on breast cancer cells interact with the ECM [ 7 ]. This interaction induces increased production by the breast cancer cells of proteins that degrade the ECM. This degradation enables the tumor cells to invade the surrounding tissue and ultimately enter the circulatory system. Once they are in circulation, tumor cells travel to other organ sites where they progressively grow [ 7 ]. The matrix metalloproteinases (MMPs) are a family of structurally and functionally related endoproteinases that are involved in the degradation of the ECM. Currently, there are 26 identified human matrix metalloproteinases, which are classified according to their substrate specificity and structural similarities [ 8 ]. Abnormal expression of these proteins contributes to various pathological processes including rheumatoid arthritis and tumor growth, invasion and metastasis. The four main subgroups of MMPs are the interstitial collagenases, which catalyze degradation of fibrillar forms of collagen, the gelatinases which degrade gelatin and collagen that are abundant in basement membranes, the stromelysins, which degrade various substrates including proteoglycans, laminin and collagen I, II, and III and the membrane-type MMPs which have been shown to catalyze activation of progelatinase A, to degrade a variety of ECM substrates and to function as a fibrinolytic enzyme in the absence of plasmin [ 9 ]. MMP expression has bee shown to be elevated during development, pregnancy, and involution and has been shown to be related to tumor cell invasiveness [ 10 ]. This study investigates the expression levels of the 26 identified MMPs, which have been shown to play a role in the metastatic process using breast tissues and cell lines derived from AA and CAU women. Materials and Methods Cell Culture and Tissue RNA All cell lines were purchased from American Type Culture Collection (Rockville, MD, USA). Cells were propagated in the recommended media and given new media every 2 to 3 days until 90% confluent (see table 1 ). Human Breast Tissue RNA was purchased from Ambion (Austin, TX). RNA Extractions RNA was extracted from the cell line using the RNAqueous (Ambion, Austin, TX). Cells were collected by low speed centrifugation and lysed by adding 200 μl of Lysis/Binding Solution. An equal volume of 64% ethanol was added to the lysate. The lysate/ethanol mixture was transferred to the RNAqueous Filter Cartridge and centrifuged for 1 minute at 13,400 rpm. The flow through was discarded and 700 μl of Wash Solution 1 was added to the RNAqueous Filter Cartridge and centrifuged for 1 minute. The column was washed twice with 500 μl of Wash Solution 2/3 and eluted with 110 μl Elution Solution. Isolated RNA was quantitated using the UltraSpec 2000 (Pharmacia Biotech). All RNA samples were stored at -70°C in RNA elution solution until further use. Gene array The Extracellular Matrix and Adhesion Molecule gene arrays were obtained from SuperArray (Frederick, MD). The array membranes were pre-hybridized with GEA hybridization solution and denatured salmon sperm DNA at 60°C for two hours. For each RNA sample, a labeling mix consisting of 4 μl 5X GEA labeling buffer, 2 μl biotin-16-dUTP, 1 μl RNase inhibitor, 1 μl reverse transcriptase, and 2 μl RNase-free water was prepared and an aliquot of 3 μg of RNA was added to each respective thin-walled PCR tube. The cDNA labels were created using a cycle of 3 minutes at 70°C, 2 minutes at 42°C, and an additional 90 minutes at 42°C. Two microliters of stop buffer was added and the mix denatured at 94°C for 5 minutes. The labeled cDNA was added to the membrane and allowed to hybridize overnight. The membranes were washed with 2X SSC/0.1% SDS and 0.1X SSC/0.5% SDS, blocked with blocking solution, and the probes were detected using AP-Strepavidin, specific buffers, CDP-Star and subsequent exposure to X-ray film for 30 seconds to 5 minutes. The autoradiograms were analyzed using ScanAlyzer and GEArray Analyzer (SuperArray, Frederick, MD). Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) The RT-PCR reactions were performed in a P/E GeneAmp 9700 thermocycler (Perkin-Elmer Co., Norwalk CT), using the Access RT-PCR system (Promega, Madison, WI). The reaction mixes were prepared by combining 27. 5 μl of nuclease free water, 10 μl of AMV, 1 μl Tfl 5X reaction buffer, 2 μl dNTP mix, 50 pM of upstream primer, 50 pM of downstream primer in 1.5 μl volume each, 3 μl 25 mM MgSO 4 , 1.0 μl AMV reverse transcriptase, Tfl DNA polymerase and 1 μg of total RNA in a 0.5 ml thin walled Eppendorf tube on ice. The reaction mixes were then vortexed for 5 seconds and centrifuged. The PCR cycling profile was as follows: 48°C for 1 minute for reverse transcription of the RNA into cDNA, 94°C for 4 minutes to deactivate the reverse transcriptase, and 30 cycling sequences of denaturing at 94°C for 45 seconds, annealing at 55°C for 30 seconds, and extension at 72°C for 1 minute with a final extension at 72°C for 10 minutes. An aliquot of 20 μl of each RT-PCR reaction were run on 1.2% agarose gels, stained with ethidium bromide, photographed and subjected to densitometic measurements using the Chemi-Imager Tm 4000 (Alpha Innotech, Corporation, San Leandro, CA). Results Gene Array Analysis Gene arrays were utilized to explore and compare the expression levels of extracellular matrix adhesion molecules in AA and CAU breast cancer cells. The array revealed elevated expression in 36% of the genes in AA samples when compared to their CAU counterparts. Of those elevated genes, 31% were from the cell membrane adhesion molecules group, 17% from the extracellular matrix proteins functional gene group, 37% from the proteases category, and 14% were protease inhibitors. Initial results of the gene array indicated a significant elevation of the proteases (data not shown). To further evaluate this, we proceeded with direct analysis of all known MMPs. MMP RT-PCR Analysis Comparison of the individual relative densities between AA and CAU women revealed elevated expression in 12 of the 26 MMPs (3, 7, 8, 9, 11, 12, 13, 14, 15, 23B, 26, and 28) (Figure 1 and Table 2 ). Elevated expression of MMP-3, 7, 8, 9, 11, 12, 13, 14, 23B, 26 and 28 in AA breast cancer cells was observed when the overall averages of the expression levels of all AA and CAU women cell lines were compared (Table 3 ). Figure 1 RT-PCR expression of MMPs in African American and Caucasian breast cell lines and tissue. Table 2 Matrix Metalloproteinase Expression Assessment by RT-PCR African American Normal Caucasian Cell Lines 2315 2320 2329 A1N4 10A MCF7 Hs578t 2336 MMPs 1 6 ± 2.7 12 ± .58 11 ± 1.15 5 5.7 6 ± 2.7 15 ± 2 11 ± 2.1 2 45.3 ± 4.2 32 ± .58 13.3 ± .58 6.7 11 11.7 ± 7.8 59 ± 1 33 ± 11 3 53 ± 11.5 47.3 ± 11 64 ± 7 9 14.3 26.5 18.3 40 7 73.3 ± 2.3 40.67 ± 2.1 17.6 ± 2.5 5.3 45.3 9 ± 1.7 38 ± 14.53 36.7 ± 4 8 14 ± 2.5 17 ± 2.5 16 ± 2.1 5 6 10 ± 1 15 ± 1.2 12 ± 1 9 66 ± 3 43 ± 5.2 18 ± 5.5 42.3 74.3 7.3 ± 1.5 28 ± 2.7 20.3 ± 5.13 10 7.3 ± .58 26 ± 1.7 18.7 ± 5.5 5.3 5 9.3 ± 1.15 66.3 ± 4 11.3 ± 1.5 11 11 ± 2 15.7 ± 2.9 15 ± 5 5 4 10 ± 4 13 ± 3.79 14 ± 0.58 12 10 ± 4 18 ± 8.9 16 ± 3.6 4 7 5 ± 1.15 5 ± 1 7 ± 2.1 13 10 ± 2 21.7 ± 4.2 7.7 ± 1.2 4 73.67 8.3 ± 2.1 18.7 ± 3.5 6.7 ± 1.15 14 12 ± 3 13.7 ± 1.5 16 ± 5 7 10 13 ± 8.5 11 ± 1.5 14 ± 3.1 15 70 ± 2.7 30 ± 0.58 57.7 ± 6.3 18 7.67 46.3 ± 4.5 81.3 ± 7.5 26.3 ± 6.8 16 8.7 ± 4 7.7 ± 1 15.7 ± 4 7.67 7.67 16 ± 2.9 16 ± 1 8 ± 2.7 17 N/D N/D N/D N/D N/D N/D N/D N/D 19v1 4 ± 1 7.3 ± .58 5 ± 1 5.33 4.33 5.3 ± 1.5 4.7 ± .58 11 ± 3.5 19v3 16 ± 6 13.3 ± 2.9 21.3 ± 8.7 15.3 10 18.3 ± 6.1 24 ± 4.2 25 ± 5 19v6 9.7 ± 4.6 9 ± .58 8 ± 5.2 7 6 12 ± 2.1 11 ± 2.1 9 ± 2.7 19v9 10 ± 1.0 10 ± 3.5 11 ± 2.0 7 7 10 ± 5 10 ± 2.0 10 ± 2.3 20 10.3 ± 3.2 45 ± .58 12.3 ± 2.1 11 9.3 23.7 ± 12.4 37.7 ± 6.0 11 ± 1 23A 5.7 ± 1.5 12 ± 2.0 8.7 ± 1.5 7 7 10 ± 2.8 5.7 ± .58 6.3 ± .58 23B 7 ± 1.1 32 ± 10.6 19.3 ± 1.5 3 7.3 10 ± 1.4 9.7 ± 1.5 12.7 ± 3.2 24 33 ± 1.2 19.7 ± 1.2 36 ± 1 18.67 30.2 33.7 ± 1 35 ± .58 37 ± 1.5 25 8 ± 1 12 ± 5.2 9 ± 1.0 5 6 13 ± 1.5 12.7 ± 1.0 7 ± 2.0 26 11 ± 1.0 11 ± 1.7 9 ± 2.5 11 8 10 ± 2 7 ± .58 9 ± 1.0 27 19 ± 7.2 19 ± 6.0 18 ± 8.0 6.7 11.67 15 ± 2.0 20 ± 13.2 19 ± 1.0 28 9 ± 5.6 14 ± 5.7 7 ± 2.0 15 18 7 ± .58 10 ± .58 9 ± 6.0 RT-PCR expression of MMPs in AA and CAU cells. Elevated expression in AA vs. CAU denoted in bold. Mean ± SD N/D: not detected Table 3 Averaged Relative Density of MMP Expression For AAW CAU and Normal Cell Lines AAW CAU Normal MMPs 1 3.2 3.4 5.35 2 9.6 11.5 11.3 3 18.3 8.4 11.6 7 14.63 9.3 25.3 8 5.37 4.18 5.5 9 14.1 6.2 58.3 10 5.8 9.7 5.1 11 4.62 4.2 4.5 12 4.9 2 5.5 13 4.4 3.7 38.8 14 4.63 4.3 8.5 15 17.5 17.1 12.8 16 3.6 4.5 7.67 17 N/D N/D N/D 19v1 1.8 2.3 4.83 19v3 5.6 7.5 12.65 19v6 3.0 3.6 6.5 19v9 3.4 3.4 7 20 7.5 8.0 10.1 23A 2.9 2.4 7 23B 6.5 3.7 5.1 24 9.9 11.7 24.4 25 3.2 3.7 5.5 26 3.5 2.9 9.5 27 6.1 6 9.1 28 3.3 2.96 16.5 RT-PCR expression of MMPs in AA, CAU cancer cell lines and Normal cell lines.. Elevated expression in AA -vs- CAU denoted in bold. N/D: not detected Discussion Little is known as to why the incidence of breast cancer is lower yet mortality is higher in African American women. Many studies speculate that this is only a socio-economical problem [ 11 ]. However this investigation provides another possibility that may reveal molecular mechanisms that contribute to the increased mortality of AA women with breast cancer. The major threat to patients with breast cancer is tumor invasion and metastasis [ 12 ]. Tumor invasion is a complex process that requires interaction between the invasive cells and the ECM [ 13 ]. This process involves a cascade of events including angiogenesis, local invasion, and intravasation. One of these critical steps involves the proteolytic degradation of the ECM and basement membrane. This is partially done by the matrix metalloproteinases. One aspect related to cancer progression has been considered in numerous studies is the association of MMP expression with tumor grade and aggressiveness [ 14 ]. The GEArray Q Series Human Extracellular Matrix and Adhesion Molecules Gene Array were used to determine the expression profiles of various types of matrix and adhesion molecules. The array was divided into four components: cell adhesion molecules, extracellular matrix proteins, proteases and protease inhibitors. From analysis of the gene array, altered expression was observed in many of the proteases. These findings led to further study of the matrix metalloproteinases (data not shown). Gene Array analysis of AA and CAU breast cancer cells indicates that there is altered expression of the genes in the Extracellular matrix and adhesion molecules, particularly the proteases. This group included 17 MMPs of which ten displayed elevated expression in AA women. RT-PCR was performed to confirm the results of the gene array. We observed elevated expression of 12 MMPs in AA cell lines when compared to their CAU counterparts. These include one gelatinase (MMP-9), two interstitial collagenases (MMP-8, and 13), 3 stromelysins (MMP-3, 7, 11), two MT-MMPs (MMP-14 and -15) and 4 uncategorized MMPs (MMP-12, 23B, 26, and 28). There was no MMP-17 expression detected in any of the cell lines (Figure 1 ). Studies have shown that normal mammary gland expression of MMPs is low except during times of development, pregnancy, and involution [ 10 , 15 , 16 ]. However, during pathologic states such as breast cancer, increased levels of MMPs have been reported in breast tumor cells as well as in the surrounding non-cancerous breast tissue [ 17 ]. Our results suggest that there is altered expression of MMPs in cell lines derived from AA and CAU women. It also demonstrates that there is greater expression of MMPs in AA women than in CAU women. This investigation indicates that altered expression of MMPs may play a role in the aggressive phenotype seen in AA women. This evidence suggests that the elevated expression levels of 12 MMPs may be a contributing factor in the higher mortality rates of AA breast cancer patients. This study is significant because it may reveal biomarkers of metastasis in AA women. To date, this is the first study to extremely investigate MMP expression in cell lines derived from African American patients. Abbreviations used MMP-Matrix metalloproteinases, MT-MMP-Membrane-type matrix metalloproteinases, AA-African American women, CAU-Caucasian, RT-PCR-Reverse transcriptase Polymerase Chain Reaction, ECM-Extracellular matrix Author's Contributions JAM performed the microarrays and RT-PCR experiments, was involved in tissue culture and prepared the first draft of the manuscript. HFY was responsible for primer design, and performed data analysis and densitometric readings of the gene arrays and RT-PCR. KL maintained all cells and tissues and assisted in the editing of this manuscript. MJ provided cell lines, training in microarray performance and editing. AAD conceived the study and participated in its design, coordination and funding, as well as preparation of the manuscript. All authors read and approved the final manuscript. Table 1 Cell Lines and Tissue Samples Human Breast Tissue Normal breast tissue (derived from CAU) MCF-10A Mammary gland, fibrocystic disease (CAU) A1N4 Mammary epithelial, chemically transformed (CAU) CAUCASIAN (CAU) HS578T Mammary gland; breast; carcinoma MCF-7 Mammary gland; breast; epithelial; metastatic site: pleural effusion adenocarcinoma CRL-2336 Mammary gland epithelial, primary ductal carcinoma AFRICAN AMERICAN (AA) CRL-2315 Breast, primary ductal carcinoma CRL-2329 Carcinoma, ductal, primary; breast; mammary gland CRL-2320 Carcinoma, ductal, breast; mammary gland; from metastatic site: lymph node	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC538270.xml
509244	8-Cl-Adenosine enhances 1,25-dihydroxyvitamin D3-induced growth inhibition without affecting 1,25-dihydroxyvitamin D3-stimulated differentiation of primary mouse epidermal keratinocytes	Background Epidermal keratinocytes continuously proliferate and differentiate to form the mechanical and water permeability barrier that makes terrestrial life possible. In certain skin diseases, these processes become dysregulated, resulting in abnormal barrier formation. In particular, skin diseases such as psoriasis, actinic keratosis and basal and squamous cell carcinomas are characterized by hyperproliferation and aberrant or absent differentiation of epidermal keratinocytes. We previously demonstrated that 8-Cl-adenosine (8-Cl-Ado) can induce keratinocyte growth arrest without inducing differentiation. Results To determine if this agent might be useful in treating hyperproliferative skin disorders, we investigated whether 8-Cl-Ado could enhance the ability of 1,25-dihydroxyvitamin D 3 [1,25(OH) 2 D 3 ], a known keratinocyte differentiating agent and a clinical treatment for psoriasis, to inhibit keratinocyte growth. We found that low concentrations of 8-Cl-Ado and 1,25(OH) 2 D 3 appeared to act additively to reduce proliferation of primary mouse epidermal keratinocytes. However, another agent (transforming growth factor-beta) that triggers growth arrest without inducing differentiation also coincidentally inhibits differentiation elicited by other agents; inhibition of differentiation is suboptimal for treating skin disorders, as differentiation is often already reduced. Thus, we determined whether 8-Cl-Ado also decreased keratinocyte differentiation induced by 1,25(OH) 2 D 3 , as measured using the early and late differentiation markers, keratin 1 protein levels and transglutaminase activity, respectively. 8-Cl-Ado did not affect 1,25(OH) 2 D 3 -stimulated keratin 1 protein expression or transglutaminase activity. Conclusions Our results suggest that 8-Cl-Ado might be useful in combination with differentiating agents for the treatment of hyperproliferative disorders of the skin.	Background The epidermis of the skin serves as a mechanical and water permeability barrier essential for terrestrial life (reviewed in [ 1 ]) and is composed primarily of epidermal keratinocytes. These keratinocytes stratify to form several layers. The deepest layer, the stratum basalis or basal layer comprises proliferating cells that continuously divide to regenerate cells lost to the environment. As the cells migrate upward into the first differentiated layer, the stratum spinousum or spinous layer, they cease proliferating and begin to express the intermediate filament proteins, the mature keratins 1 and 10. This early differentiation is followed by a late differentiation program in the stratum granulosum or granular layer, which is marked by the expression of other structural proteins, such as filaggrin and loricrin, and by increased activity of the enzyme, transglutaminase, which forms highly durable γ-glutamyl-ε-lysyl bonds to cross-link the proteins into a tough and resistant shell underneath the plasma membrane. At the boundary of the granular layer and the outermost stratum corneum, or cornified layer, the keratinocytes terminally differentiate, degrading their nuclei and other organelles and releasing lamellar bodies, the lipid contents of which form a water-impermeant barrier. The squames, the flattened remnants of the keratinocytes, and the lipids from the lamellar bodies form a sort of brick and mortar, to prevent water loss, microbial invasion and/or other mechanical insults (reviewed in [ 2 - 4 ]). 1,25-Dihydroxyvitamin D 3 [1,25(OH) 2 D 3 ] is a known regulator of this process of keratinocyte growth and differentiation (reviewed in [ 2 , 5 ]). In vitro , 1,25(OH) 2 D 3 inhibits keratinocyte proliferation and stimulates the expression of numerous keratinocyte differentiation markers (reviewed in [ 2 , 6 ]). In vivo a physiologic role for 1,25(OH) 2 D 3 in regulating keratinocyte differentiation is suggested by several lines of evidence: (1) keratinocytes express both the 25-hydroxylase and the 1α-hydroxylase which converts inactive vitamin D 3 to its active 1,25-dihydroxy metabolite (reviewed in [ 2 , 6 ]); (2) receptors for 1,25(OH) 2 D 3 are present in the skin and in epidermal keratinocytes in vitro [ 7 - 11 ]; and (3) Vitamin D receptor null mice exhibit altered skin function, characterized by abnormal hair follicles and reduced expression of several keratinocyte differentiation markers [ 12 ]. Furthermore, 1,25(OH) 2 D 3 and its structural analogs have been used as effective treatments for psoriasis, a human skin disease characterized by inflammation and by hyperproliferation and abnormal differentiation of keratinocytes (reviewed in [ 13 , 14 ]). 8-Chloro-cyclic-adenosine monophosphate (8-Cl-cAMP) is known to inhibit growth and to induce apoptosis in a variety of cancer cells [ 15 - 18 ], suggesting its potential utility as an anti-cancer drug. Indeed, phase I trials with 8-Cl-cAMP have been performed ([ 19 , 20 ] and reviewed in [ 21 ]) and phase II trials are in progress [ 22 ]. However, the mechanisms by which this agent acts are incompletely understood, and several investigators have proposed that an 8-Cl-cAMP metabolite, 8-chloro-adenosine (8-Cl-Ado) is the active anti-proliferative compound [ 16 , 23 ]. Indeed, 8-Cl-Ado has been shown to inhibit growth in a variety of cell types [ 24 - 28 ]. Previously, we demonstrated that 8-Cl-Ado arrests the growth of primary mouse epidermal keratinocytes without triggering differentiation [ 29 ]. Thus, 8-Cl-Ado functions in an analogous fashion to transforming growth factor-β (TGF-β), which also triggers growth arrest, but not differentiation,, of keratinocytes (reviewed in [ 30 ]). In contrast with a polypeptide such as TGF-β, 8-Cl-Ado, as a small molecule rather than a protein, could potentially be taken orally or applied topically to skin. Thus, 8-Cl-Ado may represent a novel therapy for treatment of skin disorders, such as psoriasis, actinic keratoses and basal and squamous cell carcinomas, characterized by hyperproliferation of keratinocytes. One potential problem, however, is that TGF-β also inhibits the expression of differentiation markers elicited by other differentiating agents [ 31 ]. Since another characteristic typical of hyperproliferative skin diseases such as psoriasis is impaired differentiation [ 32 ], a therapy that inhibits both proliferation and differentiation would be less than ideal. To determine whether 8-Cl-Ado, as a potent keratinocyte growth arrestor, could potentially be used to treat hyperproliferative skin diseases in combination with a current treatment, we investigated the effect of 8-Cl-Ado on 1,25(OH) 2 D 3 -induced inhibition of keratinocyte proliferation and stimulation of keratinocyte differentiation. We found that low concentrations of 8-Cl-Ado acted additively with 1,25(OH) 2 D 3 to inhibit DNA synthesis, without affecting the ability of 1,25(OH) 2 D 3 to enhance keratin 1 expression, a marker of early differentiation, or transglutaminase activity, a marker of late differentiation. Thus, our results suggest that a combination therapy with 1,25(OH) 2 D 3 and 8-Cl-Ado could potentially be an effective treatment for hyperproliferative skin disorders including psoriasis, actinic keratosis and non-melanoma skin cancers. Results and discussion To determine if 8-Cl-Ado could function with the growth inhibiting agent 1,25(OH) 2 D 3 to enhance its antiproliferative effect, we incubated primary epidermal keratinocytes for 24 hours with various concentrations of 8-Cl-Ado in the presence and absence of low concentrations of 1,25(OH) 2 D 3 prior to assessing effects on de novo DNA synthesis as measured by [ 3 H]thymidine incorporation into DNA. As shown in Figure 1A , 8-Cl-Ado inhibited [ 3 H]thymidine incorporation at concentrations of 5–25 μM with an estimated half-maximal inhibitory concentration (IC 50 ) of 5 μM. This value agrees well with our previously determined IC 50 of 7.5 μM [ 29 ]. In agreement with previous reports [ 33 , 34 ], 1,25(OH) 2 D 3 also inhibited DNA synthesis at concentrations of 1 to 100 nM with an estimated IC 50 of approximately 4 nM (Figure 1B ). As shown in Figure 2 , when the two agents were combined, their effect on DNA synthesis appeared to be additive, as evidenced by the comparable slopes of the [ 3 H]thymidine incorporation curves at the three different concentrations of 0 (a portion of which is replotted from Figure 1 ), 1 and 10 nM 1,25(OH) 2 D 3 . The combination of 1 or 5 μM 8-Cl-Ado with 10 nM 1,25(OH) 2 D 3 yielded a greater inhibition than 8-Cl-Ado alone, and conversely, the combined effect of 5 and 10 μM 8-Cl-Ado with 1 nM 1,25(OH) 2 D 3 was significantly larger than 1 nM 1,25(OH) 2 D 3 alone. Importantly, the combination of 10 nM 1,25(OH) 2 D 3 with 10 μM 8-Cl-Ado produced an inhibition of [ 3 H]thymidine incorporation that was significantly greater than that elicited by either agent alone. Indeed, the inhibition elicited by 10 μM 8-Cl-Ado and 10 nM 1,25(OH) 2 D 3 was comparable to the inhibition produced by 100 nM 1,25(OH) 2 D 3 alone (compare Figures 1B and 2 ). Thus, our results suggest that not only does 8-Cl-Ado not prevent the growth inhibitory action of 1,25(OH) 2 D 3 , but, in fact, the two agents seem to act in an additive fashion to more effectively inhibit keratinocyte proliferation. Figure 1 8-Cl-Ado and 1,25(OH) 2 D 3 Inhibit Keratinocyte Proliferation. Near-confluent primary mouse epidermal keratinocytes were treated with the indicated concentrations of (A) 8-Cl-Ado or (B) 1,25(OH) 2 D 3 for 24 hours, and [ 3 H]thymidine incorporation was determined as indicated in Materials and Methods. Data represent the mean ± SEM of five experimentsperformed in triplicate; p < 0.05, p < 0.01 versus the control value. Figure 2 8-Cl-Ado and 1,25(OH) 2 D 3 Act Additively to Inhibit Keratinocyte Proliferation. Near-confluent primary mouse epidermal keratinocytes were treated with the indicated concentrations of 8-Cl-Ado in the presence of no (closed circles), 1 nM (open squares) or 10 nM (open triangles) 1,25(OH) 2 D 3 for 24 hours, and [ 3 H]thymidine incorporation was determined as indicated in Materials and Methods. Data represent the mean ± SEM of five experiments performed in triplicate; p < 0.05, *p < 0.01 versus the control value, †p < 0.01 versus the corresponding concentration of 1,25(OH) 2 D 3 alone, §p < 0.01 versus the corresponding concentration of 8-Cl-Ado alone. TGF-β, another agent that, like 8-Cl-Ado, induces growth arrest but not differentiation of keratinocytes ([ 31 ] and reviewed in [ 30 ]), can inhibit the ability of differentiating agents to elicit keratinocyte differentiation [ 31 ]. However, for an agent to have therapeutic potential as a treatment for hyperproliferative skin disorders, such an inhibition of differentiation would be counterproductive to its efficacy as a medication. To determine if 8-Cl-Ado also inhibited keratinocyte differentiation, we investigated whether 8-Cl-Ado inhibited the ability of 1,25(OH) 2 D 3 to induce the late differentiation marker, transglutaminase activity. For this experiment we chose the concentrations of 8-Cl-Ado (10 μM) and 1,25(OH) 2 D 3 (10 nM) shown in Figure 2 to produce a greater growth inhibition than either agent alone. As illustrated in Figure 3 , 10 μM 8-Cl-Ado alone had little or no effect on transglutaminase activity, as reported previously [ 29 ]. On the other hand, 10 nM 1,25(OH) 2 D 3 significantly elevated transglutaminase activity by approximately 75%. The combination of 8-Cl-Ado and 1,25(OH) 2 D 3 was not significantly different from 1,25(OH) 2 D 3 alone, with a significant approximate 60% increase relative to the control value. Thus, our results indicate that 8-Cl-Ado did not prevent the differentiative effect of 1,25(OH) 2 D 3 , suggesting that these two agents might be combined to treat keratinocyte hyperproliferative disorders, such as psoriasis. Figure 3 8-Cl-Ado Has No Effect on 1,25(OH) 2 D 3 -Stimulated Transglutaminase Activity. Near-confluent primary mouse epidermal keratinocytes were treated with and without 10 μM 8-Cl-Ado in the presence and absence of 10 nM 1,25(OH) 2 D 3 for 24 hours, and transglutaminase activity was determined as indicated in Materials and Methods. Data represent the mean ± SEM of four experiments performed in triplicate; p < 0.01 versus the control value. Transglutaminase activity is a marker of late keratinocyte differentiation. We also examined the effect of 8-Cl-Ado on a marker of early keratinocyte differentiation, namely keratin 1 protein expression, using an even higher concentration of 8-Cl-Ado (25 μM). Western analysis demonstrated that 1,25(OH) 2 D 3 induced an approximate 45% increase in keratin 1 protein levels with the combination of 1,25(OH) 2 D 3 and 8-Cl-Ado producing a comparable 46% increase (Figure 4 ). Thus, early differentiation in response to 1,25(OH) 2 D 3 also was not affected by 8-Cl-Ado. Interestingly, however, in contrast to previous results [ 29 ], in these experiments 8-Cl-Ado alone elicited a small but significant increase in keratin 1 protein expression (32%). The reason for this disparity is unclear but may result from differences in the lot of anti-keratin 1 antibody used in the western analysis and/or the increased sensitivity of the method used for detecting and quantifying immunoreactive protein in this work. Figure 4 8-Cl-Ado Has No Effect on the 1,25(OH) 2 D 3 -Induced Increase in Keratin 1 Protein Levels. Near-confluent keratinocytes were incubated for 24 hours with and without 25 μM 8-Cl-Ado in the presence and absence of 20 nM 1,25(OH) 2 D 3 and were then processed for western analysis. (A) A representative immunoblot is shown. (B) Keratin 1 levels were quantified, corrected for background and normalized for loading, as described in Materials and Methods. Data represent the mean ± SEM of four experiments performed in duplicate; *p < 0.05 versus the control value. Most current treatments for psoriasis suffer from one or more disadvantages including lack of efficacy, contraindications due to deleterious side effects and/or aesthetic deficiencies ([ 35 ] and reviewed in [ 36 ]). Indeed, monotherapies tend to be less efficacious than combination therapies with two or more agents used concurrently, sequentially or in a rotational fashion (reviewed in [ 36 ]). Treatment with 1,25(OH) 2 D 3 and its analogs has proven successful, although the possibility of toxicity as the result of 1,25(OH) 2 D 3 's ability to affect calcium metabolism has led to the search for topically effective analogs with little or no effect on serum calcium levels (reviewed in [ 32 ]). If the amount of 1,25(OH) 2 D 3 (or its analog) required for treatment could be reduced, this decrease in dosage would presumably minimize systemic effects on calcium, which is the primary dose-limiting factor in the use of 1,25(OH) 2 D 3 analogs in the treatment of psoriasis [ 32 ]. Thus, our results indicating that 8-Cl-Ado enhances the growth inhibitory effect of 1,25(OH) 2 D 3 , a known keratinocyte differentiating agent and possible treatment for psoriasis [ 32 ], suggests the potential for combination therapy. Moreover, the fact that 8-Cl-Ado does not interfere with the promotion of differentiation by 1,25(OH) 2 D 3 further supports the possible combined use of these two agents for treatment of hyperproliferative skin disorders. Several lines of evidence suggest that 8-Cl-Ado is not simply acting through cyototoxicity to inhibit keratinocyte growth. First, we have previously shown that 8-Cl-Ado growth arrests keratinocytes in the G 0 /G 1 phase of the cell cycle with no increase in the sub-G 0 /G 1 (apoptotic) population of cells [ 29 ]. Second, we also showed that the effect of 8-Cl-Ado to inhibit proliferation is reversible in that washout of the compound returned DNA synthesis essentially to basal (untreated) levels [ 29 ]. Finally, in this report we demonstrate that 8-Cl-Ado did not inhibit the 1,25(OH) 2 D 3 -stimulated increase in transglutaminase activity (Figure 3 ) or keratin 1 protein expression (Figure 4 ). Together, these results indicate that 8-Cl-Ado is acting in a specific manner to decrease keratinocyte proliferation. Nevertheless, the mechanism by which 8-Cl-Ado exerts its growth inhibitory effects in keratinocytes is not clear. Our previous results indicate that 8-Cl-Ado must enter the cells to trigger growth arrest, since inhibiting uptake with an adenosine transporter, NBTI, prevented the arrest in the G 0 /G 1 phase of the cell cycle [ 29 ]. We also reported in a prior publication that 8-Cl-Ado induced the expression of the cyclin-dependent kinase inhibitor, p21 [ 29 ], which is known to contribute to growth arrest in keratinocytes and other cell types ([ 37 ] and reviewed in [ 30 ]). However, other investigators have reported 8-Cl-Ado-mediated inhibitory effects on RNA synthesis and the levels of cellular ATP [ 16 ]. Clearly, further research is necessary to define the pathways used by 8-Cl-Ado to regulate keratinocyte proliferation. Conclusions In summary, our data show that 8-Cl-Ado functions with the keratinocyte-differentiating agent 1,25(OH) 2 D 3 to inhibit keratinocyte proliferation without altering the ability of 1,25(OH) 2 D 3 to induce differentiation. Thus, our results support the possibility of using 8-Cl-Ado alone or in combination with differentiating agents such as 1,25(OH) 2 D 3 or its analogs to treat hyperproliferative keratinocyte disorders including psoriasis. Methods Materials Tissue culture reagents were obtained from standard suppliers as indicated in a previous publication [ 29 ]. 1,25(OH) 2 D 3 was a generous gift of Dr. Maurice Pechet (Research Institute for Medicine and Chemistry, Cambridge, MA). 8-Cl-Ado was obtained from Biolog (La Jolla, CA). [ 3 H]Thymidine and [ 3 H]putrescine were purchased from Dupont/NEN (Boston, MA). Dimethylated casein was obtained from Sigma (St. Louis, MO). All other reagents were from standard suppliers. Keratinocyte culture Primary cultures of mouse epidermal keratinocytes were prepared from neonatal ICR CD-1 mice and cultivated in a 25 μM calcium-containing serum-free keratinocyte medium as in [ 29 ]. Measurement of DNA synthesis For measurement of [ 3 H]thymidine incorporation into DNA, as in [ 29 ], near-confluent cultures were refed with SFKM containing various concentrations of 8-Cl-Ado with or without different concentrations of 1,25(OH) 2 D 3 . After 24 hours, cells were labeled with 1 μCi/ml [ 3 H]thymidine for an additional hour in the continued presence of 8-Cl-Ado and/or 1,25(OH) 2 D 3 . Cultures were washed twice with phosphate-buffered saline without calcium or magnesium (PBS - ) and macromolecules were precipitated using ice-cold 5% trichloroacetic acid (TCA). After additional washing with 5% TCA and distilled water, cells were solubilized in 0.3 M NaOH, and the amount of [ 3 H]thymidine incorporated into DNA was determined by liquid scintillation counting. Measurement of transglutaminase activity Transglutaminase activity was assessed essentially as described in [ 33 ]. Briefly, near-confluent keratinocytes were incubated for 24 hours with the indicated agents in SFKM. The cells were scraped into homogenization buffer (0.1 M Tris-acetate, pH 7.8, 2 μg/ml aprotinin, 2 μM leupeptin, 1 μM pepstatin A, 0.2 mM EDTA and 0.2 mM PMSF), collected by centrifugation and subjected to one freeze-thaw cycle prior to disruption by sonication. Aliquots of the homogenate were removed for determination of protein content and transglutaminase activity. Transglutaminase activity was measured as the [ 3 H]putrescine radioactivity incorporated into casein after an overnight incubation at 37°C. Casein was precipitated with TCA, collected onto glass fiber filters and counted by liquid scintillation spectrometry. The cellular protein content of the samples was determined using the Bio-Rad DC protein assay system (Bio-Rad, Hercules, CA), with BSA as standard, and transglutaminase activity was expressed as cpm/μg protein. Western analysis of keratin 1 protein levels Keratinocytes were treated and solubilized in sample buffer (31.2 mM Tris, pH 6.8, 1% SDS, 12.5% glycerol). Equal sample volumes were separated by SDS polyacrylamide gel electrophoresis on an 8% gel and transferred to Immobilon PVDF membrane (Millipore, Billerica, MA). Membranes were blocked with Odyssey blocking buffer (Licor Biosciences, Lincoln, NE), probed with a rabbit polyclonal anti-keratin 1 antibody (Covance, Princeton, NJ) and a mouse monoclonal anti-actin antibody (Sigma, St. Loius, MO). Immunoreactive proteins were visualized with IRDye800-coupled donkey anti-rabbit IgG (Rockland Immunochemicals, Gilbertsville, PA) or IR Alexa Fluor 680-coupled goat anti-mouse IgG (Molecular Probes, Eugene, OR) on a Licor Odyssey Infrared Imaging System. Keratin-1 protein levels were corrected for background and normalized using background-corrected actin levels. Statistical analysis Significance of differences was determined with the computer program InStat (Graphpad Software, San Diego, CA) using ANOVA with a Student-Newman-Keuls post-hoc test. Abbreviations 1,25(OH) 2 D 3 , 1,25-dihydroxyvitamin D 3 ; 8-Cl-Ado, 8-chloro-adenosine; 8-Cl-cAMP, 8-chloro-cyclic-adenosine monophosphate; IC 50 , half-maximal inhibitory concentration; TGFβ, transforming growth factor-beta Authors' contributions WBB conceived of the study, planned the experiments, analyzed the data and drafted the manuscript; XZ and SJ planned, conducted and analyzed the keratin 1 expression experiments.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC509244.xml
538258	Immunological parameters in girls with Turner syndrome	Disturbances in the immune system has been described in Turner syndrome, with an association to low levels of IgG and IgM and decreased levels of T- and B-lymphocytes. Also different autoimmune diseases have been connected to Turner syndrome (45, X), thyroiditis being the most common. Besides the typical features of Turner syndrome (short stature, failure to enter puberty spontaneously and infertility due to ovarian insufficiency) ear problems are common (recurrent otitis media and progressive sensorineural hearing disorder). Levels of IgG, IgA, IgM, IgD and the four IgG subclasses as well as T- and B-lymphocyte subpopulations were investigated in 15 girls with Turners syndrome to examine whether an immunodeficiency may be the cause of their high incidence of otitis media. No major immunological deficiency was found that could explain the increased incidence of otitis media in the young Turner girls.	Introduction Recurrent otitis media is often a problem in children with Turner syndrome (TS) [ 1 , 2 ]. More than 60% of the Turner girls (60–80%) aged 4–15 years suffer from repeated attacks of acute otitis media, as compared to 5% of children (aged 0–6 years) in the normal population [ 3 , 4 ]. These problems among the Turner girls are more extensive and last longer (up in their teens) than in an non Turner population. Frequent insertions of myringeal tubes are often necessary and in order to try to prevent chronic ear problems regular and frequent controls are necessary. However, sequelae like chronic otitis media are frequently seen, even if controls have been meticulous. A sensorineural hearing loss is also common among these patients, with a typical dip in the mid frequencies, declining over time. This sensorineural dip has been identified already in 6-year-old Turner girls [ 3 ]. Later in life (~35 years) a progressive high frequency hearing loss is added to the dip, leading to more prominent hearing problems and hearing aids often become necessary [ 2 , 5 , 6 ]. The cause of the associated ear and hearing problems is not known but the ear problems later in life could be influenced by the loss of estrogen. TS is caused by the presence of only one normally functioning X-chromosome. The other sex chromosome can be missing (45, X) or abnormal and mosaicism is often present. Occurring in one of every 2000 female births, TS is one of our most common sex chromosome abnormalities [ 7 ]. TS is characterized by short stature, no spontaneous puberty and infertility due to ovarian dysgenesis with no estrogen production [ 8 ]. Mental retardation is not connected to the syndrome. Since the early 80's, treatment is given with growth hormone from birth and estrogen therapy to induce puberty. Immunological disturbances have previously been described in TS, with an association to reduced levels of serum IgG and IgM, increased IgA and decreased levels of circulating T- and B-lymphocytes. However, the results have not been conclusive [ 9 - 12 ]. In the normal population children with IgG 2 deficiency commonly develop recurrent acute otitis media. It is believed that these infections are secondary to impaired antibody response, rather than Eustachian tube dysfunction [ 13 ]. As immunological derangements seem to be common in TS, an immunological deficiency could be a potential cause to parts of the ear problems. The aim of this study was to investigate immunoglobulin and lymphocyte subpopulations in girls with Turners syndrome to examine whether an immunodeficiency may be the cause of their high incidence of otitis media. Immunotherapy would then be a possible treatment. Materials and methods Subjects Blood samples from patients with the diagnosis TS, genetically confirmed, were investigated according to the Swedish ethical record no 88–265. Analyses regarding immunoglobulin- and lymhpocyte subpopulations were performed in 15 girls, aged 5–17 years (median age 11 years), randomly selected from all girls in this age group with TS attending the Karolinska Hospital, Stockholm (total 29 patients). Of these 53% (n = 8) had suffered from repeated attacks of otitis media. All TS girls had been treated with growth hormones and their karyotypes were: 45, X (n = 8); 45, X/46, XX (n = 4); 45, X/46, X, i(Xq) (n = 2); and 45, X/46, X, r(X) (n = 1) (r = ring chromosome). A medical history was attained, focusing on autoimmune diseases, previous and current ear diseases and other infectious diseases, ear operations, and hearing problems. Lymphocyte subpopulations Leukocyte counts (10 9 /L) were analysed in a Coulter MicroDiff II (Beckman-Coulter). The differential leukocyte (lymphocytes, monocytes and granulocytes) counts and percentages were obtained by 2-color FACS-analysis with CD14/CD45 markers. The number and percentage of lymphocyte subpopulations were obtained by standardized 2- or 3-color FACS-analysis on Epics XL or Elite flowcytometer (Beckman-Coulter) using commercial reagents. CD19 + was marker for B-cells and CD3 + for T-cells, CD3 + CD4 + for helper T-cells, CD3 + CD8 + for cytotoxic T-cells, CD56 + CD3 - for NK-cells and HLA-DR + for activated T-cell subsets. The ratio of CD4 + /CD8 + was also calculated. The monoclonal antibody clones used were: UCHT1 (CD3 + ), SFCI12T4D11/T4 (CD4 + ), SFCI21Thy2D3/T8 (CD8 + ), 116/Mo2 (CD14 + ), 89B/B4 (CD19 + ), KC56 (CD45 + ), NKH1 (CD56 + ) and 9-49/I3 (HLA-DR + ), all from Cytostat, Beckman-Coulter. All FACS-analyses were performed at the routine laboratory, Department of Clinical Immunology, Karolinska Hospital and the results were compared to age-related in-house and published reference ranges (5 to 95 percentiles) [ 14 ] except for CD56 + CD3 - for which an adult reference was used (10–90 percentile). Complement and antibodies Hemolytic complement (classical and alternative pathways), IgA antibodies to gliadin and endomysium, IgG antibodies to pneumococcal polysaccharide and tetanus toxoid antigen, the serum concentrations (g/L) of circulating IgA, IgG, IgM, IgD, IgG 1 , IgG 2 , IgG 3 and IgG 4 as well as the Gm(23)-allotyping of IgG 2 were analysed by standard methods and compared to age related reference ranges used at the routine laboratory, Department of Clinical Immunology, Karolinska Hospital, Stockholm. Statistical analysis Medians of continuous parameters were compared between groups by Mann-Whitney U-test and correlations were performed by Spearman rank analysis. A two-tailed p < 0.05 was considered significant. Results Lymphocyte subpopulations The leukocyte counts as well as the absolute counts and percentages of lymphocytes, monocytes, and granulocytes were within normal limits for all 15 Turner girls. Likewise most girls had normal counts and percentages of lymphocyte subpopulations as compared to the 5 to 95% percentiles age-related reference ranges (Fig. 1a and 1b ) including activated CD4 + and CD8 + T-cells (HLA-DR + ). However, the CD4 + /CD8 + ratio was in the lower range (girls aged ≥10), with one girl having a very low ratio (0.6). Figure 1 1a and b Percentages (Fig 1a) and absolute counts (Fig 1b) of lymphocyte subpopulations in 15 girls with Turner's syndrome divided into two age groups. Group A aged <10 years (n = 4) and group B aged ≥10 years (n = 11). Girls with recurrent otitis media are illustrated with open symbols (n = 8) and those who are otitis free with filled symbols (n = 7). The horizontal lines indicate medians and the shaded boxes the 5 to 95 percentiles of age-related reference ranges except for CD56 + CD3 - cells for which the 10 to 90 percentiles reference range of adults was used. Complement and Immunoglobulin levels Hemolytic complement (classical and alternative pathway) was within normal limits for all 15 Turner girls. The serum concentrations of IgG, IgA, IgM, IgD and the four IgG subclasses were for most Turner girls within the age-related 95% confidence intervals (Fig. 2 ). The exceptions were one girl with elevated IgM (2.3 g/L), five with elevated IgD (0.1–0.23 g/L), two with elevated IgG 1 (10.2 and 10.8 g/L), one with low IgG 2 (0.4 g/L) and two girls with low IgG 4 (<0.01 g/L). Figure 2 Immunoglobulin levels in 15 Turner girls. The shaded boxes indicate the 95% confidence interval for the 5–20 years age group. Girls with recurrent otitis media are illustrated with open symbols (n = 8) and those who are otitis free with filled symbols (n = 7). The frequency of homozygous G2m(23)-negative Turner girls was 33% (5/15). Antibodies Normal levels of IgG antibodies to tetanus toxoid and polysaccharide antigen were detected among most Turner girls, except for two respectively one, having too low levels. Slightly elevated IgA antibodies to gliadin were observed in 3 (20%) girls, whereas no IgA antibodies to endomysium could be detected in any of the 15 girls. Age When comparing girls aged <10 years (n = 4) and ≥10 years (n = 11) the following parameters were found to be influenced by age with decreased values among the older girls: total counts of leukocytes (p = 0.0093), lymphocytes (p < 0.05), monocytes (p = 0.0093), granulocytes (p = 0.015), CD19 + (p = 0.0053) and CD4 + HLA-DR + (p = 0.035), as well as the percentage of CD19 + (p = 0.023). Also IgG 2 increased with age (p = 0.05). These findings are in line with the reference literature for the normal population [ 14 ]. Recurrent Otitis Media The girls with TS were divided into two groups according to their history of recurrent otitis media. As age influenced some of the parameters we only considered girls ≥10 years old (n = 11). Significant increases in absolute counts of lymphocytes (p = 0.004), CD3 + T-cells (p = 0.0087), CD4 + T-cells (p = 0.012) and CD4 + HLA-DR + (p = 0.05) as well as in the percentage of CD3 + T-cells (p = 0.05) in otitis prone (n = 5) compared to otitis free (n = 6) Turner girls was shown. No such differences were noticed for any immunoglobulin levels, antibody titers, CD4 + /CD8 + -ratio or CD8 + , CD19 + , CD56 + CD3 - lymphocyte subpopulations. Karyotype Any apparent influence, of the different karyotypes, on any of the parameters studied was not observed within the group. Discussion In this study no major derangement in the immune status was found among the girls with TS. Normal levels of most lymphocyte- and immunoglobulin subpopulations were registered. The few outliers noted must be considered as a normal individual variation. However, as described in an earlier study of Turner girls, the present study confirmed a CD4 + /CD8 + ratio in the lower range [ 12 ], supposedly as a consequence of a slightly increased CD8 + population. Although, the patients were few, we noticed some differences between the otitis prone and otitis free Turner girls. The elevated counts of lymphocytes, CD3 + , CD4 + cells and CD4 + HLA-DR + cells seen among the otitis prone girls, probably reflects a secondary effect of an activated immune system involving T-helper cells, rather than any immune deficient state. Moreover, the levels of IgG antibodies to pneumococcal polysaccharide antigen, which are important in the defense of bacteria, were normal. A homozygous lack of the IgG2m(23) allotype was seen in 33% of the girls, which is the same frequency as in the normal population [ 15 ]. A negative IgG2m(23) allotype have been correlated to an impaired immune response to haemophilus influenzae vaccination with subnormal levels of IgG 2 . In the study group a negative IgG2m(23) allotype was not correlated to a positive history of recurrent otitis media, neither could the different karyotypes be associated to the levels of immunoglobulin- or lymphocyte subpopulations. Perhaps the cause of the repeated attacks of otitis media in Turners syndrome is not to be found in the periphery, but rather more locally. Even if earlier computed tomography scans of the temporal bone have not shown any abnormalities [ 2 ], the Eustachian tube may be dysfunctional and/or the cell system might be underdeveloped. Recently new aspects on the growth of the temporal bone have been proposed, with a hypothesis that the loss of X-chromosome material leads to a prolonged cell cycle and otic growth disturbances during fetal life [ 16 ]. The SHOX-gene located on the p-arm of the X-chromosome has been found to code for growth and could potentially also code for growth of the skull base and temporal bone where the middle ear is located. [ 17 ]. As the girls investigated were 5–17 years old, transient hypogammaglobulinemia in the first years is still possible. However, the girls suffered otitis media up in their teens. Our findings of normal immunoglobulin- and lymphocyte subpopulations are not entirely in concordance with some earlier studies, where a reduction of circulating IgM and IgG as well as T- and B-lymphocytes has been observed [ 9 , 10 ]. However, in these studies the values were not dramatically decreased, but rather within the lower range of the normal reference values. On the other hand, some other studies have not shown low T- and B-lymphocyte counts [ 11 ] or low concentrations of immunoglobulins [ 12 ], agreeing with the present study. In the normal population there is a difference between IgG and IgM levels in women and men with decreased values in men [ 12 ], but this difference cannot be found in newborns or children. Earlier there have been suggestions that the difference is caused by the amount of X chromosome material, as men with 47, XXY have higher values than men with normal karyotype (46, XY) and women with 47, XXX have even higher values than normal women (46, XX) [ 18 ]. There have also been suggestions that the sex hormones influence the immune system and that the lack of estrogens might influence the immune response negatively [ 11 ]. As most of the girls studied were prepubertal, the influence from sex hormones should not be as important. In some earlier studies the age span has been wider and the size of the study groups relatively small. There have also been discussions that the regular treatment with growth hormones may influence the immune system. However, in a previous study no major effects on the immunoglobulin levels or lymphocyte subpopulations could be demonstrated in Turner girls treated with growth hormones [ 12 ]. In conclusion, we did not find any major immunological deficiency in immunoglobulins or lymphocyte subpopulations that could explain the increased incidence of otitis media observed in girls with TS. Therefore, treatment with immunotherapy is not an option in this patient group. Further studies are warranted to elucidate local pathology, both from an immunological and anatomical point of view. Authors' contributions AES participated in the design of the study, performed the statistical analysis and drafted the manuscript. LS participated in the design of the study and collected the blood samples. CGMM performed the statistical analysis. MH participated in the design and coordination of the study and collected the blood samples. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC538258.xml
533872	The use of Open Reading frame ESTs (ORESTES) for analysis of the honey bee transcriptome	Background The ongoing efforts to sequence the honey bee genome require additional initiatives to define its transcriptome. Towards this end, we employed the Open Reading frame ESTs (ORESTES) strategy to generate profiles for the life cycle of Apis mellifera workers. Results Of the 5,021 ORESTES, 35.2% matched with previously deposited Apis ESTs. The analysis of the remaining sequences defined a set of putative orthologs whose majority had their best-match hits with Anopheles and Drosophila genes. CAP3 assembly of the Apis ORESTES with the already existing 15,500 Apis ESTs generated 3,408 contigs. BLASTX comparison of these contigs with protein sets of organisms representing distinct phylogenetic clades revealed a total of 1,629 contigs that Apis mellifera shares with different taxa. Most (41%) represent genes that are in common to all taxa, another 21% are shared between metazoans (Bilateria), and 16% are shared only within the Insecta clade. A set of 23 putative genes presented a best match with human genes, many of which encode factors related to cell signaling/signal transduction. 1,779 contigs (52%) did not match any known sequence. Applying a correction factor deduced from a parallel analysis performed with Drosophila melanogaster ORESTES, we estimate that approximately half of these no-match ESTs contigs (22%) should represent Apis -specific genes. Conclusions The versatile and cost-efficient ORESTES approach produced minilibraries for honey bee life cycle stages. Such information on central gene regions contributes to genome annotation and also lends itself to cross-transcriptome comparisons to reveal evolutionary trends in insect genomes.	Background The honey bee, Apis mellifera , occupies a prominent place in biological research due to its social behavior, learning capabilities, haplodiploid mechanism of sex determination, and plasticity in phenotype (caste) and longevity. Thus, it is a model organism for classical and sociogenetic studies. In addition, bees drive a large-scale apicultural industry, and also generate important income in small-scale subsistence beekeeping. And finally, bees are of great economic and ecological relevance for their role as generalist pollinators. The decision to include the honey bee amongst the current organisms for complete genome sequencing, was, therefore, well founded, yet information on its transcriptome is still meager. When starting this study, little over 250 genes were annotated as partial or full length coding sequences, and only about 15,500 expressed sequence tags (mainly 5'-ESTs generated from a normalized bee brain cDNA library [ 1 ]) were available in public databases. Thus, even after sequencing of the honey bee genome will be completed a considerable transcriptome sequencing effort will still be required for unequivocal genome annotation, gene identification, and subsequent functional studies. We used the ORESTES (Open Reading frame Expressed Sequence Tags) strategy to generate ESTs from different life cycle stages of the honey bee, such as appropriate for a genome annotation initiative. This strategy preferentially generates ESTs of the central, and thus most informative portion of the transcript [ 2 ], and frequently also identifies less abundant mRNAs [ 3 ]. The efficacy of the Open Reading frame ESTs strategy, in the context of an organism for which there is limited genomic information, has recently been demonstrated for Schistosoma mansoni [ 4 ]. This cost-efficient approach increased the already existent Apis EST database by 30% new reads. Of the 5,021 ORESTES, only 35.2% matched with previously deposited Apis ESTs. When assembled with the existent Apis ESTs in the NCBI database, the ORESTES sequences extended 66% of the mixed contigs. Together these data indicate that the ORESTES methodology could effectively complement the current efforts towards the definition of the Apis transcriptome. Results and discussion Honey bee Open Reading frame ESTs We generated a total of 87 mini-libraries from the four major life cycle stages of honey bee workers (embryo, larva, pupa, adult) by the use of arbitrary primers and a low-stringency RT-PCR protocol [ 2 ]. From these libraries we obtained 5,021 sequences of appropriate standard quality (sequence > 100 bases; Phred 15) and with an average size of 373.9 bp. These sequences were deposited in the GenBank EST database (accession numbers CK628548 to CK633568). In the annotation pipeline, these were first submitted to BLASTN searches against Apis mellifera sequences deposited in the NCBI EST database (dbEST). At this step, 35.2% (1,769) of the validated sequences matched Apis ESTs (Table 1 ). In a subsequent step, a BLASTX comparison of the remaining sequences against the nr-NCBI database permitted the annotation of an additional 22.4% (1,123) of the honey bee ORESTES, while the remaining 42.4% (2,129) did not match any known sequence. This rather large set of ESTs that did not result in significant alignment with any sequence deposited in non-redundant databases contains candidates for novel honey bee genes. Table 1 Apis mellifera Open Reading frame ESTs. Sequencing results Number of reads Total analyzed reads 5021 - Embryos 1358 - Larval stages 720 - Pupae 1219 - Adults 1479 - Stage mix 245 Local alignment matches - Apis ESTs from dbEST 1769 a - Apis mellifera sequences in GenBank 16* b - Genes of other organisms (orthologs) 1123 b - No matches in GenBank 2129 Clusterization results - Number of contigs 488 - Number of singlets 893 - Total number of clusters 1381 a BLASTN against dbEST using an E-score of 10 -30 as cutoff value; b BLASTX against the nr database used <10 -15 as the cutoff. *This set is also represented by ESTs in the dbEST database. It is included here as additional information only and is not to be summed up with the other matches. The 5,021 Apis ORESTES were assembled by CAP3 into 488 contigs of a mean size of 519 bp, leaving 893 singlets. In a second round of BLASTX comparisons against the nr-NCBI database, 28.5% of the contigs and 9.2% of the singlets were classified as putative orthologs. When the respective best matches were classified according to species or higher order taxa (Figure 1 ), 89.6% were from the arthropod clade (including fully or partially sequenced Apis mellifera genes). The largest fraction of these putative orthologs showed best matches with predicted Anopheles genes (43.9%), followed by ORESTES that were classified as putative orthologs of Drosophila (29.5%). Figure 1 Distribution of Best-BLASTX-matches for assembled Apis mellifera Open Reading frame ESTs. After assembly into contigs and singlets the sequences were submitted to a search against a non-redundant protein database (NCBI). Independent of its E-score, the best match in each BLASTX result was listed according to organism category. Gene Ontology classification We assigned level 3 Gene Ontology (GO) classifications to 326 of the total of 488 assembled contigs; 162 contigs did not match any sequence in the nr-protein database. In the manual annotation preceding the GO analysis we preferentially assigned the contigs with respect to their Drosophila orthologs. The cellular component, biological process, and molecular function classifications of the honey bee sequences are shown in Table 2 . In the biological process categories there is a clear prevalence for ESTs representing cell communication, cell growth and maintenance, metabolism and morphogenesis. For molecular function, the dominant assignments were to enzymatic activity and to nucleic acid binding and related functions (translation factor, transcription factor). When compared to the corresponding GO results obtained for the bee brain ESTs [ 1 ], we noted a similar distribution in category dominance structure, except for the molecular functions 'transporter and ligand binding/carrier' which have a higher representation in the bee brain ESTs than in our ORESTES contigs. This discrepancy most probably reflects functional differences in the tissues used in these two studies. Table 2 Gene Ontology classification of Apis mellifera ORESTES contigs according to the Drosophila genes that they represent. Gene Ontology Number of genes Cellular Component extracellular matrix 4 extracellular space 5 intracellular 99 membrane 29 others 8 Biological Process reproduction 18 cell motility 7 response to stress 6 cell communication 25 pattern specification 10 cell growth and/or maintenance 55 metabolism 79 response to external stimulus 10 morphogenesis 24 embryonic development 9 cell differentiation 9 others 41 Molecular Function nucleotide binding 14 nucleic acid binding 40 RNA polymerase II transcription factor activity 7 antimicrobial peptide activity 3 helicase activity 4 receptor signaling protein activity 5 structural constituent of cytoskeleton 5 microfilament motor activity 5 transcription factor activity 6 kinase activity 14 oxidoreductase activity 22 transferase activity 23 hydrolase activity 38 protein binding 29 metal ion binding 9 ion transporter activity 8 others 70 GO levels were set at 3. In either of the GO categories, individual contigs may be listed in more than one category. This GO classification only includes Apis mellifera orthologs to Drosophila genes that are represented by a Flybase code. Clustering of honey bee ESTs We clustered the contigs generated in this study (AmORESTES contigs) with the Apis mellifera ESTs already present in the NCBI dbEST database (further referred to as AmNCBI contigs). Clustering performed by CAP3 resulted in a total of 3,408 contigs and led to a general increase in read depth (Figure 2A ). This increase in read depth is reflected in the CAP3 assembled mixed sequences of the two databases. Mean length is 696 bp for the AmNCBI contigs and 496 bp for the AmORESTES contigs (Figure 2B ). For the mixed contigs we noted a mean increase of about 150 bp in contig length, thus documenting that the ORESTES sequences add considerable information to the characterization of the honey bee transcriptome and for subsequent studies of specific genes. Figure 2 CAP3 assembly of Apis mellifera Open Reading frame ESTs (AmORESTES) with Apis mellifera ESTs previously deposited in dbEST (AmNCBI). A) Read depth distribution of pure AmNCBI or AmORESTES and of mixed contigs; B) EST size distribution of these contigs, C) Details of individual mixed contigs showing the extension and gap-closing characteristics. In all graphs, AmORESTES sequences are in blue, AmNCBI contigs are in red, and mixed contigs are in green. Within the total contig population, 9.5% of the assembled sequences (323) are represented by mixed contigs of both AmORESTES and AmNCBI sequences, and within this group 66.3% (214) of the original AmNCBI contigs were considerably extended, or were joined across gaps by the AmORESTES contigs, as illustrated in Figure 2C . The fact that the number of mixed contigs is relatively low compared to total contig number may be attributed to two aspects. First, most of the AmNCBI contigs were obtained from a single tissue (brain) library, whereas the AmORESTES sequences represent whole body transcripts of all life cycle stages of the honey bee. Second, the AmNCBI sequences are mainly 5'-ESTs, whereas the AmORESTES sequences are expected to cover more central cDNA regions. Genome comparison Even though the total number of ESTs available for Apis mellifera is still low when compared to established genomic model organisms, we performed an across genome analysis with the set of 3,408 honey bee contigs. This involved sequential BLASTX searches, using the honey bee sequences as query entries against protein databases of Drosophila melanogaster, Anopheles gambiae, Caenorhabditis elegans , human, protozoan and fungal origin. With this selection of organisms we intended to extract information on the percentage of genes that Apis shares (i) with all organisms, (ii) with animals, (iii) with different sets of metazoans, (iv) and exclusively with insects. The cutoff E-value in these comparisons was set at 10 -6 , as used in comparisons of similar nature [ 4 ], and the representation of the respective putative orthologs was listed across taxonomic levels. We found that 1,629 Apis contigs presented significant match with sequences belonging to at least one of the taxa genomes. From these, 460 contigs (28.2%) correspond to genes with a representation in all the above taxa (Figure 3 ). In addition, further 211 contigs (12.9%) could also be classified as common to all organisms since they were represented in all but in one of the members of this set of taxa (at this level, Anopheles and Drosophila were considered as a single group representing Diptera). This increases the set of EST contigs that the honey bee may share with all organisms to 41.2%, or, when considering the entire set of 3,408 contigs, to 19.7%. The second largest set of ESTs (312 + 37 contigs) is the one that is represented as genes common to the bilaterian clade (or metazoans in general), and only the third largest set (198 + 68 ESTs) contains genes that are represented solely in hymenopterans and dipterans, and thus in the insect clade. Figure 3 Similarity and representation pattern of assembled Apis mellifera ESTs (ORESTES + NCBI dbESTs) with predicted proteins of other organisms. In this comparison we included eukaryotes with completely sequenced genomes ( Drosophila melanogaster , Anopheles gambiae , Caenorhabditis elegans and human), plus higher taxon groups, such as protozoans (primarily represented by Plasmodium falciparum and P. yoelii ) and fungi (primarily represented by Saccharomyces cerevisiae , Schizosaccharomyces pombe and Neurospora crassa ). These BLASTX comparisons were performed with an E-value cut-off level set at 10 -6 . Subsequently, the representation pattern of each of the Apis ESTs in each of the eukaryotic genomes was listed. Out of the total 3,408 Apis EST contigs, 1,629 could be classified as putative orthologs, and these were grouped according to the representation of these genes at the different taxonomic levels. Since deep-level phylogeny relationships within the bilateria are still a matter of debate, we separated our dataset according to the two prevalent hypotheses. The traditional view clusters arthropods within the coelomate clade. In our set of genomes, this tree architecture would be represented by genes shared between insects and the human genome. The alternative, more recently proposed hypothesis joins arthropods with nematodes to form an ecdysozoan clade [ 5 ]. The result of our comparison, which places emphasis on shared genes and not on the frequency of gene losses, is more consistent with the traditional view, since the coelomate clade is represented in this analysis with almost five times more shared genes than the ecdysozoan clade. To infer on functional aspects within this pattern of genes that different clades appear to have in common we performed a Gene Ontology classification on biological process. In the set of Apis ESTs that stands for genes putatively shared with all organisms, the majority was classified as having a role in metabolism, and thus can be considered to represent basic functions. In contrast, the majority of Apis ESTs that are shared within the insect clade was represented in the biological process categories of cell growth and/or maintenance and cell communication. The corresponding insect-specific genes are therefore supposedly involved in more specialized functions. A similar conclusion can be reached from the micro- and macroarray analyses of transcripts detected in adult honey bee workers performing different tasks during their adult life cycle [ 6 , 7 ]. A total of 70 putative ortholog ESTs did not comply with any of the plausible phylogenies, yet nevertheless, this set may contain ESTs of interesting information content, especially when considering that the main set of genes within this group consists of Apis mellifera contigs that overlap with a mammalian genome. A manual analysis of these 23 contigs by BLASTX against the nr-NCBI database revealed that they are (at least by three orders of magnitude in E-values) more similar to mammals (especially to humans) than to other vertebrates and even other insects. This suggests that these genes may have diverged less in Apis and mammals and, therefore, may be subject to related selection pressure. Alternatively, at least some of them may have been modified in Diptera, and thus would show up as insect genes only once further non-dipteran insect genomes or transcriptomes have been sequenced and annotated. As shown in Table 3 , this set of bee/human contigs contains a considerable number of predicted proteins related to cell signaling/signal transduction and transcription factors. Such a bias to information processing in our dataset of genes shared between honey bees and a mammalian genome may reveal system properties related to complex functions. Table 3 Annotation and Gene Ontology characteristics of 11 honey bee EST contigs sharing significant similarity with mammalian but not with other vertebrate or invertebrate sequences. In all cases, the best match was with human proteins. For these 11 out of 23 contigs we could retrieve functional information. Apis EST contig E-score value a GO, Biological process b Human LOCUS ID GenBank annotation Additional information Human Insect 437 2e-67 NA without result NM_019116: ubiquitin binding protein ubiquitin-specific protease domain 663 3e-10 NA without result NM_182830: MAM domain contactin 5; neural adhesion molecule 1081 5e-07 9.7 without result NM_013041: RAB3A interacting protein (rabin3)-like1 guanin nucleotide exchange factor domain 1425 8e-27 NA without result NM_182565: hypothetical protein MGC29814 TBP-associated factor 4; TATA box binding protein 1674 4e-82 NA without result NM_172374: interleukin 4 induced 1 none 1953 7e-11 NA without result NM_024707: gem (nuclear organelle) associated protein spliceosomal snRNP biogenesis 2807 8e-07 5e-04 regulation of physiological process NM_138457: forkhead box P4 transcription factor activity 2896 4e-05 0.002 reproduction, metabolism NM_004654: ubiquitin-specific protease 9 ubiquitin thiolesterase activity 3167 2e-27 7e-05 cell communication NM_033046: rhotekin signal transduction 3347 5e-26 7.5 without result NM_014006: PI-3-kinase-related kinase SMG-1 involved in nonsense-mediated mRNA decay 3374 1e-10 0.18 cell communication, NM_014035: sorting nexing 24 intracellular signaling cascade a E-value of the contig alignment with human or known insect sequences, NA: did not show any alignment; b Gene Ontology results on Biological Process, FatiGO level 3, c additional information obtained from Entrez Gene – NCBI and GOA link (GOAnnotations@EBI – European Bioinformatics Institute). Finally, we found that 1,779 (52,2%) of the assembled EST contigs did not match with any sequence of the analyzed organisms. Such a large proportion of Apis- specific contigs is likely to be an overestimate. As noted in a previous study [ 1 ], this might be partly due to technical problems, such as, sequencing of cDNA inserts consisting mainly of 3'-untranslated regions, the presence of unspliced intron sequences, cDNAs with a negative reading frame, or chimaeric cDNAs. However, the major portion of the Apis -specific contigs may have become classified as species-specific due to their relatively short ORFs. We performed an ESTScan analysis on the Apis -specific contigs which detected ORFs in 56% of the assembled ESTs. These ORFs are, however, relatively short, with a mean ORF length around 280 bp. Short ORF length represents a notorious problem to alignment algorithms resulting in low match scores, and consequently, a more frequent classification of short ORF ESTs as species-specific transcripts. For the honey bee, this has been shown for the brain cDNA library where 84% of the ESTs with ORFs shorter than 450 bp were classified as species-specific, against 24% in the EST set that had ORFs larger than 450 bp [ 1 ]. In order to gain a general perspective on the representation of species-specific ESTs we also directed our attention to estimates obtained in whole-genome cross-species analyses. For instance, a figure of 18.6% of species-specific genes was ascertained for Drosophila melanogaster in a genome comparison which included Anopheles gambiae as the other insect representative [ 8 ]. Based on this information, and taking advantage of a set of Drosophila melanogaster ORESTES, generated in a parallel project, we calculated the frequency of Drosophila -specific ORESTES sequences to obtain a more realistic estimate on Apis -specific genes in relatively small sets of ESTs. In this analysis, a set of 5,000 CAP3 assembled Drosophila ORESTES (409 contigs) was submitted to sequential BLASTX searches against protein databases of Drosophila melanogaster , Anopheles gambiae , Caenorhabditis elegans , human, protozoan and fungal, as described for the Apis contigs. For comparison, this same analysis was also performed with Apis ESTs, using separately 5,000 AmORESTES (486 contigs) and 5,000 AmNCB (632 contigs). The Drosophila and Apis EST contigs consistently showed relatively low proportions of insect-specific genes (6–13%). Still lower (ca. 1% each) was the proportion of ESTs that had significantly higher similarity scores with eukaryotes other than Insecta. In all EST sets we found a large fraction of sequences that were classified as either Drosophila -specific (40%) or Apis -specific (51% for AmNCBI dbESTs and 47% for AmORESTES). This high proportion of species-specific genes, therefore appears to be generated independent of the method used in EST sequencing, as it is represented in similar proportions in both the ORESTES set and the conventional 5'-EST set (Figure 4 ). Figure 4 Percentage of honey bee and Drosophila ESTs representing putative species-specific genes (blue bars) in relation to ESTs that represent genes solely shared within the insect clade (pink bars), or that have higher similarity with eukaryotes other than the insect clade (yellow bars). In separate comparisons, the Apis mellifera contigs (ORESTES + NCBI dbESTs, n = 5,000), AmORESTES (n = 5,000), AmNCBI dbESTs (n = 5,000), and Drosophila melanogaster ORESTES contigs (n = 5,000) were analyzed against protein databases of an insect ( Anopheles gambiae ) and several non-insect species ( C. elegans , protozoans, fungi and H. sapiens ) with completely sequenced genomes. The cut-off E-value in these comparisons was set at 10 -6 . The figure of 40% Drosophila -specific genes obtained for our Drosophila ORESTES set can be directly set in contrast with the estimate of 18,6% species-specific genes reported in the Drosophila genome based study [ 8 ], and this would predict an overestimate factor of 2.15 for species-specific genes in the EST sets. When this factor is applied to the honey bee ORESTES, the 47% estimate for species-specific AmORESTES can thus be corrected to a more realistic figure of 22%. This estimate is in agreement with the results of Whitfield et al. [ 1 ] who observed that 24% of the honey bee genes represented by ESTs with ORFs larger than 450 bp did not have matches to any known protein sequences. This Apis -specific gene estimate is also in range when considering that the two dipteran species are thought to have separated from a common ancestor approximately 250 million years ago, whereas the postulated sister-group relationship of Hymenoptera and Mecopteroidea [ 9 ] suggests a pre-permian divergence, with a predicted separate lineage evolution of over 280 million years for honey bees and dipterans [ 10 ]. Conclusions The generation of a relative small set of Open Reading frame ESTs (ORESTES) that match and complement the already existent Apis EST database shows that this approach is sufficiently robust and favorably complements other strategies, such as ESTs prepared from normalized cDNA libraries. Its inherent properties of detecting transcripts of low abundance and aligning with central regions of transcripts [ 2 , 3 ] also make it a suitable tool in searches for novel honey bee genes and their annotation in parallel with ongoing genome sequencing projects. Furthermore, the genome comparisons performed in this and other studies [ 1 , 11 ] highlight that the elevated number of putative Apis -specific genes will still require extensive transcriptome sequencing for high quality genome annotation, and will play an important role in the question of insect genome organization and model systems in comparative studies [ 12 ]. Methods Biological samples and RNA extraction Samples of the four major stages of the honey bee life cycle were collected from Apis mellifera colonies (Africanized hybrids) kept in the experimental apiary of the Dept. Genetics, Univ. São Paulo, Campus Ribeirão Preto, Brazil. Each embryo sample contained approximately 300 eggs retrieved from a frame on which the queen had been caged for up to 72 hours. This assured that we covered the entire embryonic period. The larval sample was a representation of all five instars and included also spinning-stage larvae. Prepupae and pupae, including white-eyed, pink-eyed, brown-eyed and pigmenting pupae, were pooled into the pupal samples. For the adult sample we collected newly emerged bees, a random sample of hive bees (picked from a brood frame), and returning foragers. All these samples were snap frozen in liquid nitrogen. Total RNA was isolated using TRIzol reagent (Invitrogen). The lipid-rich larval and pupal samples required two additional extraction steps with phenol/chloroform and chloroform to obtain RNA of adequate purity. In the case of Drosophila melanogaster , dechorionated embryos, larvae plus prepupae and pupae, as well as adult flies were collected from an isogenic y , w 1118 stock of Drosophila melanogaster . These were immediately frozen in liquid nitrogen and stored at -80°C until use. Total RNA was extracted with TRIzol, as described for Apis mellifera . Generation of Open Reading frame ESTs (ORESTES) From high quality DNA-free total RNA samples we isolated poly(A) + RNA using an Oligotex II (Qiagen) kit. To assess poly(A) + RNA quality of the samples we performed Northern blot hybridizations with an actin ( Apis mellifera ) or tubulin ( Drosophila melanogaster ) probe. The probes were labeled by a random priming reaction in the presence of [α- 32 P]dCTP. The actin fragment was amplified using the primers described in Table 4 . The Drosophila tubulin probe was already available from previous studies. High quality total RNA preparations were subjected to a DNase I treatment, and the absence of DNA contaminants was assessed by Southern blot hybridization of PCR products amplified with Apis or Drosophila 16S mitochondrial DNA primers, respectively. High quality poly(A) + RNAs were aliquoted and stored at -80°C. Table 4 Specific primers used to assess quality and absence of DNA contaminants of the RNA samples, and randomly selected primers used to generate cDNA profiles. Primer code Sequence actin F (Apis) 5' AGCTATGAACTTCCAGATGGT 3' actin R (Apis) 5' CCACATCTGTTGGAAGGT 3' 16S mitochondrial F (Apis) 5' TTATTCACCTGTTTATCAAAACAT 3' 16S mitochondrial R (Apis) 5' 'TATAGATAGAAACCAAYCTG 3' 16S mitochondrial F (Drosophila) 5' CCGGTCTGAACTCAGATCACGT 3' 16S mitochondrial R (Drosophila) 5' CGCCTGTTTAACAAAAACAT 3' p3_2 5' TTGGGGATCGTATGTAGTATG 3' pA82_1 5' CACTTCAGGATCCCTTGTAAGC 3' pA82_2 5' CCAACATTGAATTCTCTTTGAC 3' pA82_4 5' CAATAACAATGAATTCCAGAATCTCG 3' pPT7C4_B 5' GCTTACAAGGGATCCTGAAGTGTTTCC 3' pPT7C4_XS 5' GCAGGTAAACTCTACTCGAGTTACG 3' M-RON-AS 5' CCAGGATGTTTGGGTGATGTA 3' CREB-S 5' TCATGCAACATCATCTGCTCC 3' H-SPARC-S 5' CTAACCCAAGACATGACATTC 3' M-CD151-S 5' AAAGCTCGGAGGCAGCGAACT 3' H-CD151-AS 5' CATGTGGCTGCAAGGCAAAGC 3' M-SPARC-AS 5' GCCCAATTGCAGTTGAGTGAT 3' M-ETS1-AS 5' GTCTTGATGATGGTGAGAGTC 3' FUT-3-S 5' TCATGTCCAACCCTAAGTCAC 3' FUT-3-AS 5' TCCAGCAGGCCTTGCAGAAAT 3' M-CMET-S 5' TATCTCAAACGATCGAGAGAC 3' M-CMET-AS 5' GCACATCTATTACCAGCTTTG 3' H-CMET-S 5' TTTCAAATGGCCACGGGAC 3' H-CMET-AS 5' GCACATTTATGACCATTCTCG 3' H-Rhoc-AS 5' AGAAACAACTCCAGGGGCCTG 3' M-Rhoc-AS 5' CTACCCAAAGCAGAAACCCCA 3' H-Sparc-AS 5' CCAAAACCATCCTTGACAACA 3' H-RON-AS 5' TGATGAGGTCCTTCACGGTG 3' B237-2 5' CGGAATTCACCAGATTTGAACAGAAGAG 3' B237-3 5' AACTGCAGTTAACCAGATTTGAACAGAAA 3' GST_(PGEX)_NHE_I-S 5' CCGCTAGCATGTCCCCTATACTAGGTTA 3' HOXA_I-F 5' CGCTCCCGCTGTTTACTCT 3' P21-RasaI-F 5' GACCGCTCCTCCAACTAACC 3' P21-RasaI-R 5' CCGGCCCACCTCTTCTACTA 3' SRY8299.2 5' TCTCTTTATGGCAAGACTTACG 3' SRY1532.1 5' TCCTTAGCAACCATTAATCTGG 3' 92R7.2 5' GCCTATCTACTTCAGTGATTTCT 3' TAFIEX.1R 5' ATCCAAGGTTCTCCCAATA 3' ORESTES profiles were generated according to Dias-Neto et al. [ 2 ]. Briefly, aliquots of 15 ng of purified mRNA were subjected to reverse transcription reactions utilizing SuperScript II Reverse Transcriptase (Invitrogen) and a set of randomly selected primers (Table 4 ). First-strand cDNA synthesis occurred at 37°C for 60 min in a total volume of 20 μl. The products of this reaction were diluted 1:5 in water and stored at -20°C. The cDNAs contained in 1 μl of each diluted RT-product were then amplified by PCR using the same or a single alternative random primer in a PCR mix (Ready-to-Go PCR bead, Amersham Biosciences). The amplification protocol consisted of an initial step at 75°C for 5 min, followed by a 45 cycles touchdown series (95°C for 30 s, a gradually decreasing annealing temperature from 66 to 44°C lasting 10 s per step and a decrease of 2°C per step, 72°C for 1 min), and a final extension reaction at 72°C for 7 min. Aliquots of the PCR products (3–5 μl) were run on 1% agarose gels and stained with ethidium bromide. From profiles that presented near-even smears we excised two sets of amplification products, one covering a size range from 300 to 700 bp and a second one from 700 to 1500 bp. For cloning, these were extracted from the agarose gels (QIAquick Gel Extraction kit, Qiagen) and ligated into pUC18 (SureClone Ligation kit, Amersham Biosciences) for transformation of competent E. coli DH5α-cells by heat shock. Bacteria were grown in 2 × YT medium before aliquots were plated on 2 × YT agar containing ampicillin. Blue-white selected positive colonies were picked, grown overnight in 2 × YT medium in 96-well plates, and used as templates for PCR using vector primers (M13 forward and reverse). An aliquot of each amplification product was analyzed on a 1% agarose gel before another 1 μl aliquot was submitted to DNA sequencing using standard protocols of the DYEnamic™ ET Terminator kit (Amersham Biosciences). The reaction products were analyzed in a MegaBACE™ 1000 automated sequencer. Only profiles with more than 80% positive PCR reactions were sequenced. Sequence analysis After passing through the Base Caller Cimaron 1.53 Slim Phredfy (insert size > 100, "N" nucleotides less than 20%, and "N" repetitions of less than 6 nucleotides) and ScoreCard procedure (MegaBACE™) to check sequences quality, reads that were larger than 100 nt were submitted to an automated protocol for data analysis (Gene Annotation Pipeline) of the Apis mellifera or Drosophila melanogaster ORESTES. The protocol consisted of the following steps: conversion of electropherograms (Phred, to formats .fasta, .phd and .qual), primer and vector detection and trimming (Cross_match) and masking of repeats (RepeatMasker). Validated fasta format sequences were then submitted to a general BLASTN search against GenBank entries for mitochondrial and rRNA, as well as bacterial and fungal RNA to detect and eliminate contaminant sequences. For the Apis mellifera ORESTES, subsequent BLASTN searches were performed against the approximately 15,500 Apis mellifera EST sequences deposited in GenBank dbEST. In this case, significant E values were set at 10 -30 . Searches against the non-redundant protein database entries used the BLASTX option with E-values set at 10 -10 as significance cut-off level. CAP3 was used to clusterize the ORESTES sequences of both species. For Apis mellifera , the annotation of the 488 contigs was manually checked, giving preference to Drosophila sequences in the Unigene assignment. Subsequently, the contigs were batch submitted to a Gene Ontology procedure utilizing the FatiGO tools [ 13 ] . Clusterization of the Apis ORESTES contigs and singletons with the Apis mellifera ESTs deposited in GenBank dbEST was also performed using a CAP3 routine (standard parameters). Authors' contributions Apis ORESTES: FMFN and JFS participated in all steps of library preparations data and analyses; MAVC and DGP performed the bioinformatics analyses; RMM, PMVP and MFRS participated in the library preparations and GO analysis; MCRC sequenced libraries; AMN performed validation PCRs on selected ORESTES; AEE participated in the design of the study and preparation of biological material; MMGB, EME, FSE and ZLPS participated in the design of the study, library preparations and conceptual data analysis; MLPL, VV and KH participated in the design of the study, library preparations and prepared the manuscript; WASjr coordinated the design of the study and the bioinformatics analysis. Drosophila ORESTES: VV, JFS, DDA, RMM and EDN participated in all steps of library preparations and analyses; NM and RGRP participated in the design of the study and preparation of biological material; LFLR, WKM and AFC participated in RNA sample preparation; SJS, MAVC and WASjr participated in the design of the study and performed the bioinformatics analyses; AJGS, MAZ, EME and MLPL conceived and coordinated the study. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC533872.xml
546235	A finite element method model to simulate laser interstitial thermo therapy in anatomical inhomogeneous regions	Background Laser Interstitial ThermoTherapy (LITT) is a well established surgical method. The use of LITT is so far limited to homogeneous tissues, e.g. the liver. One of the reasons is the limited capability of existing treatment planning models to calculate accurately the damage zone. The treatment planning in inhomogeneous tissues, especially of regions near main vessels, poses still a challenge. In order to extend the application of LITT to a wider range of anatomical regions new simulation methods are needed. The model described with this article enables efficient simulation for predicting damaged tissue as a basis for a future laser-surgical planning system. Previously we described the dependency of the model on geometry. With the presented paper including two video files we focus on the methodological, physical and mathematical background of the model. Methods In contrast to previous simulation attempts, our model is based on finite element method (FEM). We propose the use of LITT, in sensitive areas such as the neck region to treat tumours in lymph node with dimensions of 0.5 cm – 2 cm in diameter near the carotid artery. Our model is based on calculations describing the light distribution using the diffusion approximation of the transport theory; the temperature rise using the bioheat equation, including the effect of microperfusion in tissue to determine the extent of thermal damage; and the dependency of thermal and optical properties on the temperature and the injury. Injury is estimated using a damage integral. To check our model we performed a first in vitro experiment on porcine muscle tissue. Results We performed the derivation of the geometry from 3D ultrasound data and show for this proposed geometry the energy distribution, the heat elevation, and the damage zone. Further on, we perform a comparison with the in-vitro experiment. The calculation shows an error of 5% in the x-axis parallel to the blood vessel. Conclusions The FEM technique proposed can overcome limitations of other methods and enables an efficient simulation for predicting the damage zone induced using LITT. Our calculations show clearly that major vessels would not be damaged. The area/volume of the damaged zone calculated from both simulation and in-vitro experiment fits well and the deviation is small. One of the main reasons for the deviation is the lack of accurate values of the tissue optical properties. In further experiments this needs to be validated.	Introduction Laser radiation is now used routinely in surgery to incise, coagulate, or vaporize tissues. The laser light power is converted into heat in the target volume with ensuing coagulative necrosis, secondary degeneration and atrophy, and tumour shrinkage with minimal damage to surrounding structures [ 1 ]. The use of lasers in surgery introduces some desirable features over normal surgical methods such as increased precision, improved hemostasis, and less tissue manipulation. Laser light power is thereby delivered to the targeted area by an optical fibre. The use of an optical fibre as applicator for interstitial light delivery was demonstrated, among others, by Bown [ 2 ] in 1983 as a method of heating and destroying deep-seated tumours [ 3 ]. The biological effects of laser energy depend on the laser wavelength, laser power, the duration of irradiance, blood perfusion, and both the optical and thermal properties of the tissue involved. Laser-tissue interaction mechanisms may be thermal, photochemical, or mechanical in nature [ 4 ]. Photochemical like PhotoDynamic Therapy (PDT). Mechanical like the effects induced using pulsed lasers (photoacoustic, photodisruptive). The surgical procedures that involve coagulation or ablation of tissue are thermal. Clinical studies have yet to demonstrate that LITT is practical for the palliation of hepatic and nasopharyngeal tumours (e.g. [ 5 - 9 ]). The criteria for the clinical success of the thermotherapy for tumours in homogeneous tissues, for example, in the liver or brain, was described, among others, by Vogl [ 3 ], who placed applicator/diffuser at the centre of the tumour, using MRI online monitoring of the thermal changes to control the treatment [ 6 ]. In contrast to homogeneous and simple tissues, however, normal anatomical structures are more complicated. Especially for small tumours near main vessels a positioning of the laser applicator at the centre of the lesion is difficult and maybe not the optimum choice. Modelling the laser-tissue interaction is beneficial for the analysis and optimisation of the parameters governing planned laser surgical procedures. Nevertheless, we still lack an adequate model that grants accuracy. Most of the models suggested depend greatly on simplifications of the real problem, either in the geometry they offer or in the system of equations they use. Some models, which use the bioheat equation, neglect the role of the changes in the tissue properties during temperature elevation process [ 10 ], which deem such a model unrealistic, especially considering high temperatures. Few modelling methods have simulated the behaviour of LITT in human tissue. Best known is the Monte-Carlo method described, among others, by Roggan et al. [ 11 ]. This method can simulate the use of multiple applicators but is limited to symmetric geometries and has not been correlated to real anatomic datasets. Similar to this is the finite difference method described in [ 12 ], where the authors did not include the coagulation process with its irreversible changes in optothermal tissue properties. In order to overcome these limitations, we included the damage function as well as perfusion terms in the modelling process, taking dependencies of these parameters into account. This paper describes in detail the bases for a modelling method to simulate the effect of LITT for the treatment in various indications near large vessels, such as the carotid artery in the neck region. We thereby propose the use of LITT, frequently applied in the treatment of liver tumours [ 6 ], in more sensitive areas such as the neck region to treat tumours in lymph node metastases or epithelial carcinomas with dimensions of 0.5 cm – 2 cm in diameter. The actual response of tissue to laser irradiation is a time-dependent phenomenon. Initially, there are thermal and possibly photochemical changes of the tissue at the molecular level. Next are changes in tissue perfusion caused by thermally induced vascular relaxation and/or vessel damage. Heat deposited at the application site is transferred to adjacent structures. This may be desirable for coagulation purposes – or it may cause unexpected thermal damage to otherwise viable tissues adjacent to the irradiation site. The rate of heat transfer depends on the composition and organization of tissues involved. Blood perfusion during and after irradiation has significant effects on the size of the damage zone. We discuss in this paper our mathematical approach, its considerations and restrictions. In the main part we present the mathematical and physical backgrounds used to achieve the model. Then we present and discuss the results of our simulation in comparison with the results of our in-vitro experiment. Materials and methods Our model of LITT considers both optical and thermal effects. It is based on calculations describing the light distribution using the diffusion approximation of the transport theory; the temperature rise using the bioheat equation, including the effect of microperfusion in tissue to determine the extent of thermal damage, and the dependence of thermal and optical properties on the temperature and the injury. Injury is estimated using a damage integral, which depends on the temperature elevation history. The order and flow of the modelling steps are described in the following sections in detail. The geometry of the 3D model The head and neck area consists of complex anatomical structures in close proximity. In sonographic 3D volume datasets of the neck area the sternocleidomastoideus muscle and the neck vessels (common carotid artery, internal carotid artery, external carotid artery and the internal jugular vein) serve as leading structures [ 13 ]. Because of the almost superficial anatomic position of the vessels and their straight course (Fig. 1a ) especially the common carotid artery is easily shown sonographically. Differentiation of inflammed lymph nodes and metastases located parallel to the large neck vessels [ 14 ] can be achieved 90% of the time with the help of signal-enhanced colour duplex sonography [ 15 , 16 ], making ultrasound preferable to other imaging techniques. Figure 1 The geometry used. The left carotid artery is shown in this figure labelled with ca . The following letters indicate the orientation: s for superior, i for inferior, p for posterior, a for anterior, l for left, r for right. (a) is a photo of the human anatomy in the neck area. The carotid artery is shown here after moving the vein to the cranial direction. (b) shows the corresponding freehand 3D ultrasound dataset of the human neck region acquired axially. The 3D image in the top of (b) shows the 3D ultrasound volume together with the carotid artery segmented with 3D Slicer software [17]. The 3D model is displayed with 40% transparency. (c) displays the model used in the simulation approximated according to the geometry of the human neck shown in (a) and (b). The segmentation of the 3D ultrasound dataset in (b), is available as a video stream, too, showing the geometry of the carotid artery (see Additional file 1 ). One can easily segment the carotid artery from 3D sonographical, MRI or CT volume datasets. For the segmentation of our 3D ultrasound dataset (Fig 1b ) we used the software package 3D Slicer [ 17 ]. The real geometry is complex and needs to be simplified to reflect limited computational capacity. We thus obtained the 3D base model consisting of a cube of 447 cm 3 shown in Fig. 1c . The cube contains the blood vessel approximated either by the cylindrical shape or much better by a shape of cone. The applicator is shown as a thin tube of 2.5 cm perpendicular to the vessel (Fig. 1c ). Commercially available laser applicator fibres for thermotherapy frequently have a water jacket to cool the surface. The applicator is assumed to be a cylinder, and the cooling effect is implemented as a boundary condition at the diffuser surface. The tissue surrounding the vessel is treated as a homogeneous muscle tissue. According to the geometry described using a mesh is generated to perform a finite element method calculation (Fig. 2 ). The model was implemented with FEMLAB 2.3 as an add-on to Matlab 6.5 for finite element modelling [ 18 ]. Figure 2 The finite element method (FEM) mesh. The values of each variable and of each property value are evaluated at each point of the mesh. In other words, the "simulation loop" in Fig. 3 is performed at each of point of the mesh. The bi-points variables' values are evaluated using an interpolation process. The light distribution equation In most tissues, both absorption and scattering are present simultaneously. A mathematical description of the absorption and scattering characteristics of light can be performed analytically or by using the transport theory. Transport theory has been extensively used when dealing with laser-tissue interactions. Furthermore, experimental results have confirmed its validity in most cases [ 19 ]. The photon propagation described using the transport theory has been dealt with already in [ 4 , 19 - 23 ]. Exact analytical solutions to the radiative transport equation have been found for only few special simple cases. However, when scattering processes dominate absorption in the medium, a high penetration depth of the light is the consequence. This is the case in LITT treatment in human tissue using an Nd:YAG 1064 nm laser or even a diode 830 nm laser: The penetration depth of both types ranges from between 1300 μm – and 1400 μm, whereas the penetration depth of other laser types like argon 514 nm laser or CO 2 10600 nm laser is less than 350 μm. This leads us to the possibility of applying light diffusion approximation to the transport theory [ 4 ]. Because of the high penetration depth of the Nd:YAG laser in turbid media, diffusion theory provides a relatively accurate description of light propagation. In three dimensions the diffusion equation needs to be solved numerically, because an analytical solution is not possible [ 4 ]. FEM is the most practical method; moreover a number of different efficient solutions using FEM are now available. An exact derivation of the light diffusion equation can be found in [ 4 , 20 ]. Here, we give the light diffusion approximation to the transport theory, which is implemented in our model (Fig. 3 : Light Distribution Equation): Figure 3 The simulation loop. The figure shows the simulation flow chart as a step in the imagined surgical planning system (left side). The future goal of the surgical planning system is to verify the three parameters governing a laser treatment: the applicator position, the laser power, and the exposure duration. The temperature starting point of the volume is set to normal body temperature. Three input parameters are taken: average blood velocity, laser power, and application time (right side: input). The main part of the simulation is the loop, which calculates the variables in the forward steps, then updates the values of the different properties (parameters) in the backward step according to the results of the forward step. The loop follows the section materials and methods and uses its nomenclature for variables and functions (right side: loop). The output of the solver consists of three parts: the light energy fluence rate φ ( r . t ), the temperature distribution T ( r , t ), and the damage Ω( r , t ) (right side results). The results are explicity shown in figures Fig. 4 and Fig. 5. The roman numbers (I-VI) refer to the equations in the text. φ being the light fluence rate [W cm -2 ], D the diffusion coefficient [cm], and Q the source term [W cm -3 ]. μ a is the absorption coefficient and μ ' s the reduced scattering coefficient in tissue. The roman number (I) indicates the position in Fig. 3 . The relationship between the reduced scattering coefficient and the scattering coefficient, μ s is described by μ ' s = μ s (1-g) , with g being the anisotropy factor incorporating the effects of directionally dependent scattering. The absorption coefficient μ a for visible and for near infrared radiation ranges between 0.001 mm -1 < μ a < 10 mm -1 for biological tissues. While for the scattering coefficient μ s is in the order of 1 mm -1 < μ s < 100 mm -1 [ 20 ]. The optical properties μ a and μ ' s depend on the tissue, and they change their values during a real treatment. In order to simulate this effect, the optical properties of the tissue are functions of the damage Ω [ 20 ] (see section on "damage function"). The damage function Ω describes the pathologic state of the tissue during treatment. In general, for simple geometries like a point-source, the solution of the light diffusion equation will be an exponentially decreasing function with effective attenuation coefficient given by: As an example, the solution of eq. 1 for a light source similar to a medical applicator in a homogeneous medium takes the shape of an ellipsoid [ 24 ] as shown in Fig. 4 . Figure 4 Solution of the light distribution equation. Left: the energy density colour index. The solution is elliptical as expected. The penetration depth in the vessel is less than in the tissue, because of different scattering and absorption coefficients. The heat distribution equation in tissue The aim of irradiation with laser energy is to produce heat in the targeted tissue. Excess heat is either stored or extracted, leading to changes in the local temperature. The bioheat equation was repeatedly used to describe the heat changes in biological tissue [ 4 , 19 , 20 ]. The bioheat equation is the realizing of the principle of conservation of the energy applied to tissue volume, (Fig. 3 : Heat Distribution Equation, in Normal Tissue), where T is the temperature [°C], ρ the density of tissue [kg cm -3 ], c the specific heat of tissue [J kg -1 °C -1 ], k the thermal conductivity of tissue [W cm -1 C -1 ], r the position vector [cm], t the time [s], T art the temperature of arterial blood [°C], S the deposited light power [W cm -3 ], w b [ml/(g.min)] is the tissue average volumetric blood perfusion rate (but because the density of blood ρ b is to be considered as a constant value, it is possible to call ρ b · w b [kg s -1 cm -3 ] the average volumetric blood perfusion rate , unfortunately usually denoted in the literature also with w b ), and c b the specific heat of blood [J kg -1 C -1 ]. The coefficients ρ , k and w b are functions of temperature T . As a basis for the optical and thermal parameters for the simulations, we used values published by Mueller et al. [ 1 ]. Especially for normal body muscle tissue the physical properties are collected in Table 1 . Table 1 Listing of physical parameters. The table shows the physical parameters for native tissue and for coagulated-tissue, as well as for blood [25]. The small letters indicate the references where the material parameters are taken from: a) [20], b) [26], c) [27], d) [28], e) [29]. Muscle Blood Native Coagulated Absorption coefficient, μ a (cm -1 ) a) 0.23 a) 0.22 b) 0.44 Scattering coefficient, μ s ' (cm -1 ) a) 1.3 a) 13 b) 2.78 Density, ρ (kg cm -3 ) c), d) 1.04·10 -3 d) 1.06·10 -3 Specific heat capacity, c (J kg -1 °C -1 ) d) 3.64·10 3 d) 3.89·10 3 Heat conductivity, k (W cm -1 °C -1 ) c) 5.18·10 -3 e) 5.4·10 -3 The heat distribution equation in large vessels 1. The incompressible Navier-Stokes equation In order to make the model adaptable to individual shapes of segmented vessels, we considered the geometry of a large vessel as a volume in which an incompressible fluid (blood) flows. The direction of the blood flow and the initial speed profile are implemented as boundary conditions. The incompressible Navier-Stokes equation for the blood (Newtonian fluid) reads: Here, η is the dynamic viscosity [kg s m -1 ], ρ the density [kg m -3 ], u the velocity field, p the pressure [N/m 2 ], and F a volume force field such as gravity. Implementing the Navier-Stokes equation in the model allows us to present a time-periodic change in the blood flow rate, i.e., to simulate the beat cycle effect in the vessel. The main effect here on the result of the simulation lies in the accuracy of the estimated heat elevation in the tissue: A continuous blood flow has a different profile than the cycled flow (laminar and not laminar, or rather complex with four beat phases), which yields a different final cooling effect. For vessels away from the heart, the pumping cycle does not clearly appear; it tends to be a normal laminar flow. In this case ( u ( r , t ) = u ( r )) and eq. 5 is reduced to the following: 2. The bioheat equation in large vessels The heat convection between tissue and a large vessel occurs as a direct energy transfer rather than perfusion. The vessel is a heat sink in the treated volume. Therefore, the perfusion term in the bioheat equation has to be modified to consider heat conduction and blood flow. A new term, the so-called enthalpy transport , is added to retain the validity of the bioheat equation. The term serves for interpreting the internal energy flow out of the control tissue volume by means of the blood flow [ 30 ]. Considering the blood velocity field ( ) in a large vessel the bioheat equation becomes: The damage function The thermal damage in cells and tissue is described mathematically by a first-order thermal-chemical rate equation, in which temperature history determines damage. Damage is considered to be a unimolecular process, whereby native molecules transform into a denatured/coagulated state through an activated state leading to cell death [ 4 , 19 ]. Damage is quantified using a single parameter, Ω, which ranges on the entire positive real axis and is calculated from the Arrhenius law: where A [s -1 ] is the frequency factor, Ea [J/mole] the activation energy, R [J mole -1 K -1 ] the universal gas constant, and T [K] the temperature. C( r , 0) and C( r , τ ) are the concentrations of the undamaged molecules at the beginning and at time τ , respectively. Damage Ω (eq. 8, Fig. 3 , Damage Function) is dimensionless, exponentially dependent on temperature, and linearly dependant on time of exposure. The activation energy E a and the frequency factor A are derived from thermodynamic variables. They describe the denaturation process of proteins and other cellular constituents. A ranges from 10 40 s -1 to 10 105 s -1 , and E a from 10 5 J/mole to 10 6 J/mole [ 4 ]. The equation above indicates that the measure of damage describes the probability for tissue being destructed. It is the logarithm of the ratio of the initial concentration of undamaged tissue to the concentration after damage has accumulated, for the time interval t = 0 to t = τ . Therefore, Ω = 1 corresponds to the reduction in concentration of native molecules to a 37% level for a unimolecular system – an irreversible damage of 100% of the affected cells. However, in terms of the thermal damage to tissue, Ω ( r , t) is a function of the observer's definition of damage. In [ 31 ] a limit of Ω >0.6 has been discussed as a margin of final tissue destruction (Fig. 5 ). A value of Ω = 0.6 corresponds to reduction in concentration of native molecules to 50% level. Figure 5 The heat distribution and the damage in the volume. Left: the heat colour index in °C. The damage appears when the value of the damage function Ω (eq. 8) reaches the threshold of 0.6. Here the image shows the results after 200 s. The damage zone is shown in grey. Fig. 5 is available also as a video stream demonstrates the temperature rise inside the tissue. The video stream shows where, how, and when this damage appears (see additional file 1 ). The dependences of the tissue properties on tissue temperature and damage Heat capacity is assumed to be constant over a wide temperature range. The temperature dependence of thermal conductivity and density is taken into consideration by the following linear approximations [ 20 ] (Fig. 3 : Properties): On the other hand, the optical properties are influenced directly by the damage Ω. The scattering coefficient of coagulated tissue is much higher than that of native tissue. The optical properties change during the process of tissue coagulation, leading to a higher scattering coefficient and a nearly constant absorption coefficient. This becomes obvious by the change of the colour of the irradiated area (bleaching) and leads to reduction in penetration depth. The actual property set is calculated from the actual damage value as well as the optical properties in the native and coagulated tissue states [ 20 ] (Fig. 3 , Properties): Here, μ s , native and μ s , coagulated denote the scattering coefficients of native and coagulated tissue, respectively, g being the anisotropy factor. In literature g is mostly considered constant. Anyhow, some authors [ 20 , 31 ] reported the possibility of different values for g according to the damage state. Model implementation The diagram in Fig. 3 illustrates the flow of the simulation. There are three main parts to the modelling of laser-tissue interaction (Fig. 3 , right part): • First, the irradiance distribution in the different tissues is determined by directly applying eq. 1. As shown in equations eq. 11, eq. 12, and eq. 13 the values of the properties depend on damage Ω (eq. 8). In the first loop step Ω is zero, and it starts to increase according to the rise in temperature, i.e., the different optical properties have as their starting point native tissue and as end point coagulated tissue. The actual value lies between both limits as determined according to Ω. • In the second step, the temperature distribution in the tissue caused by laser energy deposition is estimated by solving the two bioheat equations for tissue and large vessel. The source term in both equations is defined by the absorbed energy at each mesh point (Fig. 2 ) from the distributed light energy calculated in the first step (light-energy to heat-source coupling) using: • A by-step here is the estimation of the blood speed field ( ) from the Navier-Stokes equation (either eq.5 or eq. 6). In our solved model, because we suggested treatment as taking place in the neck near the carotid vessel, we considered to use eq. 6 for obtaining the speed field, which is valid for laminar flow. • In the third and main part, thermal damage is predicted from spatial and temporal temperature distribution (eq. 8). • After estimating the heat distribution and the damage value, we perform a backward step to calculate the new values of the properties according to eq. 9 through eq. 12, which are updated in the equations set for the next loop iteration. For our calculations we used FEMLAB's standard mesh generator with its default settings for modelling [ 18 ]. The mesh consists of 5354 nodes, more dense near the applicator and becomes coarser moving towards the walls. The time-dependent equation set described in the previous sections was solved using FEMLAB's time-dependent solver "femtime". The default settings for the solver were used: 0.01 for relative error tolerance and 0.001 for absolute error tolerance. Because of the non-linearity of this problem, the special time stepping algorithm "fldaspk" offered by FEMLAB was used in order to obtain a stable and convergent numerical solution [ 18 ]. A normal numerical solution to initial value problem of differential equation generates a sequence of values for the independent variable (time) t n and a corresponding sequence of values for the dependent variable ( φ , T , u , Ω, and all other variables depend on them in this case) so that each φ n , T n ,... approximates the solution at t n [ 32 ]. Modern numerical methods automatically determine the step sizes h n = t n +1 - t n so that the estimated error in the numerical solution is controlled by a specified tolerance [ 32 ]. The "fldaspk" solver uses the algorithm of the known DASPK solver written by Linda Petzold, which uses variable-order variable-stepsize backward differentiation formulas (for independent variable, time t in this case) [ 33 ]. There is no control on the time step itself, rather on the specified tolerance of each variable. Light is considered to be emitted from an interstitial fibre with a fibre-diameter of 1 mm; it was modelled as an isotropically radiating cylindrical source (Fig. 4 ). In the real treatment a cooling process using a special cooling catheter is performed to keep the temperature at the surface of the applicator low, preventing damage at its surface. A special boundary condition at the applicator surface should be applied in order to simulate this cooling effect. In the model this is realized by setting the outer surface temperature of the applicator to a constant value (normal body temperature T = 37°C). At the modelled volume surfaces the insulation boundary conditions, optical and thermal, are used, where n is the outward unit vector normal to the surface. This means the gradients of light fluence rate and of temperature vanish at the surface. Even though this condition is more suitable for light fluence rate, as small amount of radiations reach the surface, but in general the temperature and light fluence rate will not be constant. The need to set this condition in this way is because that the numerical solver demands defined fixed boundary conditions, which sometimes do not agree with the real situation. According to the NCRP-data [ 34 ] the perfusion rate w b over the entie tissue is set to 1.4·10 -6 kg of blood s -1 cm -3 for T < 60°C and to 0 when T ≥ 60°C, which is to be considered as a normal result of stopping the blood perfusion according to temperature elevation in the tissue [ 31 ]. In order to solve the Navier-Stokes equation, we set the dynamic viscosity, η , to 3.5·10 3 kg·s·m -1 . To evaluate the damage, Ω, the activation energy E a is set to 670000 J/mol and the frequency factor A to 9.4·10 104 s -1 [ 22 , 35 ]. Damage is considered to appear when Ω reaches the value of 0.6 [ 31 ]. The simulation takes around 2 hours on Sun Blade 2000 with Solaris 9 OS, 6 GB RAM and Ultra SPARC IIIi processor. Experimental validation We performed a single in-vitro experiment to check our model. The setup is shown in Fig. 6 . The experimental work was performed using a fresh piece of porcine muscle tissue. In order to simulate the cooling effect of the blood flow in a vessel, a transparent tube (Polyethylene) and a porcine blood were used. An electronically controlled roller pump system (Storz Endomat LC203303) was used to pump the blood through the tube. We used the online ultrasound sonography to situate the applicator in its right position in front of the tube and to get the 3D ultrasound data analogy to the base geometry shown in Fig. 1 . The sample has dimensions of 1265 cm 3 . The tube inner diameter is 5 mm and the outer diameter is 7 mm. The blood and the laser cooling liquid had the room temperature of 21.4°C while the sample itself 17.6°C. A laser power of 30 W and blood average flow speed of 40 ml·s -1 were used. We measured the exact distance between the laser applicator and the tube edge, 3 mm, at the end of the experiment after performing the cut in the sample. We fixed our application time to 300 s. Figure 6 The experiment setup. 1- laser applicator, 2- transparent tube (considered as a blood vessel), and 3- is ultrasound sonography prob. The tube was introduces by pulling it through a hole made using dipped knife. The online sonography was used to verify the position of the applicator. In the simulation model we omit the perfusion term, as there is no perfusion to be considered in-vitro. We simulated the tube (blood vessel) with diameter of 6 mm. All other experimental conditions are implemented in the model as they are in the experiment. Because of the lack of data, which describe the properties of the porcine tissues, in all literature available to us, we used the same data presented in Table 1 to complete this simulation. The highest temperature and widest damage are reached in front of the centre of the applicator. Taking into account the perpendicular surface to the applicator at centre, which is the most critical in the volume as all effects participate together: applicator, vessel, and blood flow, we complete the comparisons of the results between the experiment and the simulation using this plane. Hence, we made a cut in the probe at the level equivalent to this plane. Coagulation of tissue is immediately apparent and always indicates lethal thermal effect [ 4 ]. Anyhow, and in order to comment on, a damage boundaries have to be identified. For most tissues, coagulation can be seen with naked eye as whitening of the tissue associated with turgor and opacity [ 4 ]. The damage boundary in the probe cut is determined by applying a grey threshold of 50% on the picture of the cut after changing it to grey scaled image. Away from the applicator position in a certainly undamaged area, applying this threshold led to 92.68% of the pixels to be black and 7.32% white, while in the damaged tissue 6.64% of the pixels were black and 93.3% white. The Matlab 6.5 R13, its Image Processing 4.0 Toolbox, and Paint Shop pro 8 were used to perform these steps. A comparison in the z-direction needs an up-down cut (y-z plane) through the applicator position perpendicular to the tube/vessel, which was not possible after the cut in x-y direction. Results In [ 25 ] we presented results from different geometries. Here, we focus on the results from the physical and mathematical points of view. We present also a comparison between the results of our model and the results of the in-vitro experiment. Theoretical results Fig. 4 shows that the light energy is distributed, as expected, in a shape of ellipsoid, because of the absorption in the tissue. It also shows that the light penetration depth in blood is less than in the normal tissue, because of the different values of the absorption and scattering coefficients. Fig. 5 shows the heat elevation. The cooling effect of the blood vessel may be clearly identified here. Fig. 5 is available as a video stream, too. This video stream demonstrates the temperature rise inside the tissue as a result of the irradiation. The video stream shows where, how, and when this damage appears (see Additional file 2 ). The dimensions of the damage zone, which may be considered the target goal of the simulation, can be calculated directly by producing grided axes in all the 3D and 2D results as well as with routines written especially for this aim. Comparison with experimental results Fig. 7 shows the interpreted development of the damage zone. The calculation shows that the damage starts with an application time of 72 s using laser power of 30 W. It starts at a distance of 2.5 mm from the centre of the applicator in the opposite direction of the vessel. After that, the damage zone will spread to all directions as it is shown in Fig. 7 . Fig. 8 shows the solution of the heat and light distribution equations for this model. In the first 60 s there is no noticeable change in the light distribution. In the next 30 s the damage zone appears, which leads to changes in the scattering and absorption coefficients (eq. 11 and eq. 12). Figure 7 The interpreted development of the damage zone as a result of the simulation model using the experimental conditions. The applicator is recognized as a grey point in the middle and is indicated with (App). The damage zone starts with an application time of 72 s. The damage zone is presented here at 73 s, 120 s, 180 s, 240 s, and 300 s of application time as indicated in the figure. Figure 8 Dispersion of heat and light distribution considering the experiment conditions. The figure shows the results at 60 s, 90 s, and 300 s of application time. The isolines show the light distribution, which represent the deposition of the energy irradiated from the laser applicator. The major change occurred to the energy penetration depth happens between 60 s and 90 s of application time. The dashed area presents the damage zone at these times. Fig. 9 shows the overlaid damage zones of both model and experiment. The kidney-shaped lesion is about 21.2 cm 2 , while our model shows a damaged zone of 2.11.45 cm 2 . We obtain calculation errors of 5% in the x-axis parallel to the blood vessel, and of 20% in the y-direction perpendicular to the vessel. This deviation happens mainly due to inaccurate optical properties values. Figure 9 The results from simulation and experiment. For the experiment the following settings were used: time of application: 300 s, laser power: 30 W, blood flow rate: 40 ml/s, and applicator-vessel edge distance: 3 mm. Using these conditions a simulation is performed. In the figure the damage zones of both model and experiment are overlaid to show the deviation. The black oval shows the damage zone obtained from the simulation using the above conditions. The two parallel black lines indicate the vessel position and diameter in the simulation. The lesion is about 21.2 cm 2 , while the calculated damage zone is 2.11.45 cm 2 . The calculation error ranges from 5% in the x-axis parallel to the blood vessel to 20% in the y-direction perpendicular to the vessel. Both cutting the tissue with scalpel and the opening induced a tissue movement. This movement is a reason for the error in y-direction beside the error obtained from the optical properties, which affect all directions. The discoloration in the top of the image at the opposite side of the artificial vessel is due to the cut and the opening of the probe. Discussion To date most simulation models of LITT have used the Monte-Carlo method (MC) to calculate the light distribution, then combine its results with Finite Difference method (FDM) to calculate the heat distribution. Because of its formulation, this combination fits very well for a radially symmetric problem. A weakness arises, however, when dealing with asymmetric volumes in real human anatomy. Arbitrarily curved surfaces separate the different tissues. Consequently, calculations from the FDM becomes so complex that errors start to appear in the results presented stemming from the dependency of FDM on dividing the volume into voxels. One way to overcome this is to increase the voxels' number. Indeed, this leads to less error at the tissue-separating surfaces, although it increases the resources and calculation steps, making the procedure inconvenient. In principle, combining MC and FEM (instead of FDM) is possible theoretically, and seems to be promising as it overcomes the latter problems, but to our knowledge has not implemented yet. From another perspective, MC solution converges to the exact solution of the transport equation only when the number of traced photons increases infinitely [ 4 , 21 ], which yield time consuming calculations. Because we are dealing with an asymmetric geometry, we chose the FEM. It allows us to define and refine the mesh in the volume of interest in order to obtain more precise results. Furthermore, using a FEM mesh we are able to adapt individually the mesh for each patient's dataset. Never the less, it was not necessary to combine methods, FEM is used for all equations. The model we propose depends on the following considerations: • The coupling of a set of time-dependent equations, which simulate the whole process of the LITT treatment (Fig. 3 ). The set of equations includes the light diffusion equation, the bioheat equation, the Navier-Stocks equation, the damage function, and the dependencies of the properties on temperature and ensued damage. • We consider the functional dependence of the various tissue properties at the various spatial and temporal points, according either to the tissue type, or temperature, or the damage value – or even a combination thereof. • We take into account the irreversible changes in the tissue stemming from the treatment as they directly affect the solution of the set of equations. Our model remains a mathematical model, meaning errors could appear from the considerations and simplifications made to realize it. Generally, such errors appear because of the following reasons: • The inaccuracy of the optical, thermal, and damage properties are main point in the model's set of equations. In fact, these properties play a key role in the accuracy of the model's results. Many methods have been presented to calculate these properties [ 4 , 19 , 21 ], but still we see differences in the values presented by the different groups, which reflect the difficulty of measuring these properties. The problem is increased by the dependencies of the properties on the different variables (temperature, damage) over time. This makes the deviation neither linear nor regular. • An error appears because of machine performance limitations: The available memory limits the number of mesh nodes and the degrees of freedom (DOF) used to build the model. This causes a deviation from an otherwise accurate result [ 18 ]. On the other hand, it is useless to increase the nodes number or the DOF arbitrarily: This would result in more time consuming calculations, since one would always have to run an interpolation and smoothing process as next to last step. In practice, a suitable number of nodes/DOF should be chosen, so that the interpolation routines estimate smoothly the value of all variables between nodes. Our model is based on what was mentioned above, with FEMLAB's standard refining processes at the critical areas (around the diffuser and vessel). It is important to refine the mesh around such surfaces, something that can be done much more conveniently using FEM rather than FDM. The convenience of the FEM-based modelling may be found in this very point of its ability to have different degrees of refining in the mesh according to how critical the region is. • Absolute tolerance: All numerical methods have an allowed error (absolute tolerance) that reflects the criterion of the convergence. Normally, different solvers use different tolerances. In our model we used the FEMLAB's default tolerance value of 0.01 which leads to a final error of 1%, considered as a reasonable value for modelling. One way to follow these errors and deviations from a real treatment result is to estimate them and to eliminate their effects from the final results of the model. This can be realized and implemented in the model by adding an error-correcting factor from the first degree (or even higher) in the set of equations correcting the result of each equation at each time step. These corrective factors should be measured practically by comparing the results of the model and the results from real experiments on test tissues or probes. Our experiment shows a deviation of 5% in x-direction and 20% in y-direction. As the main reason for this deviation we propose inaccurate values for the optical tissue properties. Fig. 7 and Fig. 8 clearly show the kidney-shaped damage zone caused by the cooling effect of the blood vessel (or the tube in the experiment), which keeps its neighbouring in the native state for longer time. In literature [ 20 , 31 ], the value of the absorption coefficient μ a for both native and coagulated different biological tissues are close. Baring that in mind, and knowing that the value of the scattering coefficient μ s becomes normally, for biological tissue, 10 times greater than its starting value, i.e. native state, we can judge that as soon as the damage zone appears and the moving from native to coagulated state according to eq. 11, eq. 12, and eq. 13 the deviation in the calculations will increase as well. Thus, accurate values of the different tissue properties, and especially the optical properties are key points in obtaining realistic results from the simulation. One promising technique for determination of optical properties was presented by Dam et al. [ 36 ]. There method provides an online values of the optical properties at 660 nm, 785 nm, 805 nm, 974 nm using a cylindrical probe head situated on the skin. It still require further researches. Anyhow, thinking of developing such a method to be able to gather information about optical properties at 1064 nm interstitially using a catheter during the irradiation can be of great value for modelling. Our model gives the possibility to implement such a gathered information directly. Thinking of using it online to predict the damage and controlling the irradiation power needs for sure more researches. Finally, beside the error obtained from the optical properties, which affect all directions, both cutting the tissue with scalpel and the opening induced a tissue movement. This movement is a reason for deviation, especially in y-direction, as we perform the cutting in this direction. Conclusions For several years now LITT has been a well-known and approved therapy system for tumour ablation in the liver and some other anatomical regions. Minimally invasive LITT procedures use a Nd:YAG 1064 nm laser. Therapy planning, however, remains unsolved and is still a challenging issue. Today's simulations are based on symmetric geometries. Without exact therapy planning systems, the usage of LITT is limited to homogeneous tissues or the respective surgeon's experience. The finite element technique proposed in this paper can overcome both limitations. We propose a model to validate in the future the LITT method in other anatomic regions. The model enables the efficient simulation for predicting the damaged zone induced with the diffuser of the LITT. The simulation is performed for tissue ablation near vessels, though obviously FEM is not limited to this. Exemplarily, we implemented the model for tissue ablation near the carotid artery in the neck region using an approximation for the artery shape. We describe the bases necessary to calculate the effects of the temperature rise caused by the absorption of light energy in the tissue, using the bioheat equation and including the cooling effects of vessel blood flow and micro-perfusion in tissue in order to determine the extent of thermal damage. The shape of the carotid artery is derived from a real segmented geometry based on, but not limited to, 3D ultrasound. Experimentally, we performed a laser irradiation in a porcine muscle tissue sample. The results of our model diverge between 5% to 20% from the lesion obtained in the experimental work. From the authors' point of view two major reasons can be identified. The lack of accurate data describing the thermal and optical properties leads definitely to deviations. Furthermore the cut of the probe with scalpel induces a certain tissue shift, especially in the y-direction. Anyhow, more experiments with different conditions are necessary to be able to carry out a statistical study and find the exact origin of the deviation, and, if necessary, define an error correction factors and add them to equation set. But that does not set aside the desire of accurate values for the properties of the tissue. From another hand, still our model practical, it presents a step in using segmented data as basis for much more detailed surgical therapy planning. Combining LITT and adequate planning system could increase both the anatomical application range and the quality of therapy procedures. Supplementary Material Additional File 1 Animated gif file, the Geometry . The animated gif shows the 3D ultrasound volume together with the carotid artery segmented using 3D Slicer software [ 17 ]. The movie belongs to Fig. 1b . The gif file can be played using the internet browser. Click here for file Additional File 2 Animated gif file, The heat distribution and the damage zone in the volume . The video stream demonstrates the temperature rise inside the tissue. The video stream shows where, how, and when this damage appears. The damage zone is shown in grey colour. The gif file can be played using the internet browser. Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC546235.xml
555739	Desmoplastic small round cell tumour: Cytological and immunocytochemical features	Background Desmoplastic small round cell tumor (DSRCT) is a rare and highly aggressive neoplasm. The cytological diagnosis of these tumors can be difficult because they show morphological features quite similar to other small round blue cells tumors. We described four cases of DSRCT with cytological sampling: one obtained by fine needle aspiration biopsy (FNAB) and three from serous effusions. The corresponding immunocytochemical panel was also reviewed. Methods Papanicolaou stained samples from FNAB and effusions were morphologically described. Immunoreaction with WT1 antibody was performed in all cytological samples. An immunohistochemical panel including the following antibodies was performed in the corresponding biopsies: 34BE12, AE1/AE3, Chromogranin A, CK20, CK7, CK8, Desmin, EMA, NSE, Vimentin and WT1. Results The smears showed high cellularity with minor size alteration. Nuclei were round to oval, some of them with inconspicuous nucleoli. Tumor cells are clustered, showing rosette-like feature. Tumor cells in effusions and FNA were positive to WT1 in 3 of 4 cytology specimens (2 out 3 effusions and one FNA). Immunohistochemical reactions for vimentin, NSE, AE1/AE3 and WT1 were positive in all cases in tissue sections. Conclusion The use of an adjunct immunocytochemical panel coupled with the cytomorphological characteristics allows the diagnosis of DSRCT in cytological specimens.	Introduction Desmoplastic small round cell tumor (DSRCT) is a rare and highly aggressive neoplasm described as a distinct clinicopathologic entity in 1989 by Gerald and Rosai [ 1 ]. Usually affecting young males and presenting as an abdominal mass, the tumor grows along serosal membranes with multiple nodules attached to the peritoneal surface [ 2 ]. Other primary sites have been reported as pleura [ 3 ], paratesticular region [ 4 ], bone and soft tissues [ 5 ] and ovary [ 6 , 7 ]. Histologically, a typical feature of DSRCT is the presence of clusters of tumor cells distributed within a cellular stroma. The shape of clusters varies from round to elongate. Tumor cells are small to medium-sized with round to oval hyperchromatic nuclei, with inconspicuous nucleoli. Necrotic cells and mitosis are common features. Cytoplasm is usually scanty, and cell borders are indistinct. Intracytoplasmic eosinophilic rhabdoid inclusions may be found in larger cells with nuclear pleomorphism [ 8 ]. The immunohistochemical profile shows divergent differentiation, a striking feature of this tumor. DSRCT may present a problem in the differential diagnosis with other round cell tumors. Tumor cells are immunoreactive for epithelial, neural and myogenic markers [ 2 ]. Cytogenetical studies have demonstrated a reciprocal chromosome translocation between the Ewing's sarcoma gene on chromosome 22 and the Wilms' tumour gene WT1 on chromosome 11, which is distinct from the translocation observed in Ewing sarcoma/peripheral neuroectodermal tumor (PNET) [ 9 ]. The cytological smears of DSRCT obtained by FNAB are moderately cellular. Tumor cells show round to oval nuclei with fine chromatin and inconspicuous nucleoli. Cytoplasm is scanty to moderate, with variable number of vacuoles. Tumor cells are arranged in loose clusters. Occasionally, spindle fibroblast-like cells are observed. Stromal fragments may be detected [ 10 ]. Effusion samples show cohesive cell clusters and similar cytological features. Mitoses or individual necrotic cells may be present, as nuclear molding [ 3 ]. In the current study, we describe the morphological and immunocytochemical features of four cytologic specimens, one of them obtained by FNAB and three from serous effusions (2 peritoneal fluid samples and one pleural effusion), from 3 patients with a diagnosis of DSRCT. Materials and methods We retrieved from the cytological files of Hospital do Cancer – A. C. Camargo four cytological specimens from 3 patients diagnosed with DSRCT, including one fine-needle aspiration sample and 3 fluid samples, during the last five years (2000–2004). FNA was performed on an inguinal mass of one patient. Alcohol-fixed smears were stained with Papanicolaou technique. Serous effusions were prepared with Cytospin (Shandon, Pittsburgh, Pennsylvania, USA). We evaluated two peritoneal fluid samples and one pleural fluid sample. One case (patient 1, peritoneal fluid) had a cellblock available. All cases were confirmed by histological analysis and immunohistochemical reactions. The histological sections were cut in sections of 4 μm and stained with H&E and immunohistochemistry. Immunocytochemical study was also performed on all cases. Immunohistochemical and immunocytochemical reactions were performed using streptavidin-biotin peroxidase technique with positive and negative controls. Diaminobenzidine was the chromogen. Table 1 shows the antibodies used and dilutions. All antibodies were from DAKO Corporation, Capinteria, CA, U.S.A. Table 1 Antibodies and dilutions used in this study Marker Antibody clone Dilution 34BE12 34BE12 1:100 AE1/AE3 AE1/AE3 1:500 Chromogranin A DAK-A3 1:100 CK20 KS20.8 1:50 CK7 OV-TL 12/30 1:100 CK8 35BH11 1:100 Desmin D33 1:100 EMA E29 1:2000 NSE BBS/NC/V1-H14 1:1500 Vimentin Vim 3B4 1:200 WT1 6F-H2 1:400 Cases Patient 1 22-year-old white female, with abdominal pain. Video-laparoscopy showed a liver mass and multiple peritoneal implants diagnosed as DSRCT. Six months after the diagnosis, she started chemotherapy for four months, and reduction of tumor mass was observed. One month after the end of chemotherapy, the tumor was removed. Macroscopically, tumor mass measured 5.0 × 4.0 × 3.8 cm and was involving uterus, pericolic tissue, and vagina. Histological analysis shows also involvement of both ovaries and large bowel wall. Ten out of 13 lymph nodes showed metastasis of DSRCT. The peritoneal fluid colleted during surgery was negative for neoplastic cells. Eight months after the first surgery, she presented with a recurrence in the abdominal cavity and a new resection of the tumor mass showed involvement of cecal appendix. Peritoneal fluid sample collected at that time was positive for malignant cells. In the follow up examination, seven months after the second surgery, it was found an inguinal tumor mass of 15 mm. FNA was performed and showed DSRCT metastasis. After the diagnosis, this patient was transferred to another institution. Patient 2 Seven year-old male with back pain and fever. CT scan showed pleural effusion and a mediastinal mass measuring 16.0 × 9.0 cm. Tumour mass showed involvement of soft tissues. Surgical biopsy and pleural drainage were performed. The patient was treated with radiotherapy and chemotherapy, but died 8 months after the diagnosis. Patient 3 Male, 15-year-old had acute abdominal pain and was submitted to an exploratory laparotomy that disclosed a large pelvic mass, involving epiplon and sigmoid, cecum, liver and peri-aortic lymph nodes. This patient had multiple nodules on peritoneal surface. The biopsy of tumor was performed. One month after the diagnosis, chemotherapy was initiated. The patient was submitted to chemotherapy during 8 months, with reduction of more than 50% of tumor mass. A second laparotomy was done to excise retroperitoneal and retrovesical mass. At this time peritoneal fluid sample was collected. After surgery, chemotherapy was continued. The patient is alive, with residual disease. Results Cytological findings Case 1 (Fine needle aspiration) The smears showed high cellularity. The tumor cells exhibited a slight variation in size. Nuclei were round to oval, some of them with small nucleoli. The cytoplasm was scanty. Tumor cells are clustered, with rare clusters showing rosette-like features. The background of the smears showed lymphocytes. (Figure 1 ). Figure 1 Clusters of small round tumor cells showing rosette-like features in smear of fine needle aspiration specimen of DSRCT. Cases 1, 2 and 3 All fluid samples showed similar features. The samples showed high cellularity. Tumor cells were more frequently arranged in tridimentional clusters, but occasionally, isolated cells are also seen. Additionally, clusters showing rosette-like features are rarely observed. Nuclei were round to oval, some of them with small nucleoli. The cytoplasm was scanty (Figure 2 ). Figure 2 Effusion from patient with DSRCT exhibiting high cellularity. Observe tridimentional clusters of neoplastic cells. Nuclei were round to oval, some of them with small nucleoli and the cytoplasm is scanty. Immunohistochemical and Immunocytochemical findings The distribution of immunoreactivity in histological and cytological samples from the patients are summarized in Table 2 . Tumor cells in effusions from patients 1 and 2 and, the smear obtained by FNA (Patient 1) were positive to WT1 (Figure 3 ). Table 2 Distribution of immunoreactions in patients 1, 2 and 3 histological and cytological samples. Marker Patient 1 Biopsy Patient 2 Biopsy Patient 3 Biopsy Patient 1 Cytology Patient 2 Cytology Patient 3 Cytology 34BE12 - - ND ND ND ND AE1/AE3 + + + ND ND ND Chromogranin A + + ND ND ND ND CK20 - - ND ND ND ND CK7 - - ND ND ND ND CK8 + - ND ND ND ND Desmin + - ND ND ND ND EMA + + ND ND ND ND NSE + + + ND ND ND Vimentin + + + ND ND ND WT1 + + + + + - (Effusion & FNA) N.D. = not done. Figure 3 DSRCT tumor cells in effusion showing nuclear positive reaction to WT1. Patient 1 the histological sample collected before chemotherapy, exhibited immunohistochemical positivity for vimentin, epithelial membrane antigen (EMA), neuron specific enolase (NSE), chomogranin A, and desmin in dot-like perinuclear pattern. Cytokeratin expression was observed with anti-cytokeratin cocktail (AE1/AE3) and Cytokeratin 8. Tumor cells also expressed WT1 protein. Patient 2 tumor cells exhibited positivity for vimentin, EMA, NSE, chomogranin A, AE1/AE3 and WT1. Desmin and cytokeratins 7, 20 and 34BE12 were negative. Patient 3 tumor cells exhibited positivity for vimentin, NSE, AE1/AE3 and WT1. The immunohistochemical study was performed before chemotherapy. Discussion DSRCT is a rare neoplasm that affects young patients. It may present a problem in the differential diagnosis with other small round cell tumors. The diagnosis of DSRCT however can be established with correlation of clinical, cytological and immunocytochemical features. The cytological features that we found in the smears obtained by FNA are similar to other descriptions in the literature. Similar to reports of Zeppa et al [ 11 ], we did not detect in our smears fragments of fibrosis or cytoplasmic granules or vacuoles. The finding of stromal fragments, frequently seen in FNA is not a common finding in liquid based preparations [ 12 ]. One of the characteristics of DSRCTs is its dissemination along serous surfaces. Due to this fact, development of serous effusions is a common clinical finding in DSRCTs patients, with detection of tumor cells in the fluid. In effusions, tumor cells may be present in aggregates but no obviously architectural arrangement is seem. Demonstration of a divergent phenotype and the reciprocal translocation characteristic of DSRCT are critical to the diagnosis. In a reported series of 32 cases of DSRCTs [ 13 ], 88% of cases were immunoreactive for AE1/AE3, 84% for NSE, 81% for desmin. These results were similar to other previous studies [ 2 ]. Lae et al [ 13 ] detected positivity to WT1 antibody in 29 out of 32 cases. Our immunohistochemical results are in agreement with other previous studies. Strong membrane expression of HER2/neu and immunoreactivity to c-kit protein are not common findings [ 14 ]. The establishment of a specific reciprocal translocation t (11; 22)(p13;12) as diagnostic in DSRCT was based on the results of Sawyer et al [ 9 ]. Shen et al [ 15 ] and Roberts et al [ 16 ] described variants of with other chromosome involved in addition to chromosome 11 and 22. The translocation t (11; 22)(p13;12) involve the EWS gene in 22q24 and WT1 gene in 11p13. This translocation produces the chimeric transcript EWS/WT1 and the related WT1 protein, which can be detected by immunohistochemical method. EWS gene encodes a protein which the precise function and normal role has not yet been elucidated. Recently, Thomas et al [ 17 ] proposed that the protein product of the EWS gene interacts with Brn-3a cellular transcription factor via a direct protein-protein interaction. Native WT1 protein function has not completely known, but it represses transcription in vitro of many genes. WT1 is a tumor-suppressor gene that encodes a protein, which mediates transcriptional repression and interacts with p53 protein [ 18 ], product of another tumor suppressor gene, TP53, frequently deleted or mutated in many human tumors. In absence of intact p53 protein, WT1 acts as a transcriptional activator [ 19 ]. Normal WT1 protein is expressed in tissues, which undergo mesenchymal-epithelial conversion derived from mesoderm, in a specific period of development [ 20 ] and it plays a role in mesothelial formation in embryonic development [ 21 ]. Immunohistochemical detection of WT1 in DSRCTs is predictive of the translocation and it also demonstrates that the chimeric protein is expressed in significant amount in tumour cells 22, 23 . In addiction to consistent WT1 expression, the typical serosal involvement in DSRCT has raised the possibility that this tumor might be a blastematous tumour derived of primitive mesothelium [ 24 ]. Mesothelin is a glycoprotein of unknown function strongly expressed in mesothelial cells. Although lack of specificity of expression of mesothelin for mesothelial origin, the expression of this protein in DSRCT may have some significance on histogenisis of this tumor [ 25 ]. We detected WT1 immunoreactivity in all tumors tissues and in 2 out of 3 serous effusions with malignant cells, as well as on FNAB smears. The high frequency of DSRCTs with WT1 protein expression suggests that in consensus with clinical tomographic and cytological findings, this antibody may be used to confirm the diagnosis of DSRCT in cytological samples. We observed a negative WT1 reaction in the cytological sample of patient 3. This sample was collected 10 months after the end of chemotherapy protocol. We can hypothesize if chemotherapy hampered a different antigenic pattern in malignant cells, and influenced this result. Among other small round cell tumors, most of cases of rhabdomyosarcomas and neuroblastomas do not disclose nuclear WT1 staining [ 26 , 27 ]. Comparing DSRCT and Ewing Sarcoma/PNET, Hill et al. [ 28 ] detected WT1 nuclear immunoreactivity in all 13 DSRCT cases studied; conversely, all 11 cases of Ewing Sarcoma/PNET were negative. Additionally, Wilm's tumor was demonstrated to present a high percentage of cases with nuclear WT1 staining; for this reason, correlation with clinical findings is necessary to do a differential diagnosis between Wilm's tumour and DSCRT in effusions [ 26 ]. On the other hand, it is important to emphasize that malignant mesothelioma should also be considered in the differential diagnosis, since it can show varied histological appearances including sarcomatoid differentiation with desmoplastic areas, or even resembling undifferentiated sarcomas [ 29 ]. WT1 might also decorate nuclei of both epithelioid or biphasic mesothelioma but in general, WT1 stain most frequently epithelioid mesotheliomas [ 30 ]. The use of a panel of markers can also help in the differential diagnosis. In conclusion, cytological and immunophenotypical findings in an appropriate clinical context is sufficient to suggest DRSTC, what sounds highly contributive for us, considering the high aggressiveness of this tumor.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC555739.xml
514567	Thermal modeling of lesion growth with radiofrequency ablation devices	Background Temperature is a frequently used parameter to describe the predicted size of lesions computed by computational models. In many cases, however, temperature correlates poorly with lesion size. Although many studies have been conducted to characterize the relationship between time-temperature exposure of tissue heating to cell damage, to date these relationships have not been employed in a finite element model. Methods We present an axisymmetric two-dimensional finite element model that calculates cell damage in tissues and compare lesion sizes using common tissue damage and iso-temperature contour definitions. The model accounts for both temperature-dependent changes in the electrical conductivity of tissue as well as tissue damage-dependent changes in local tissue perfusion. The data is validated using excised porcine liver tissues. Results The data demonstrate the size of thermal lesions is grossly overestimated when calculated using traditional temperature isocontours of 42°C and 47°C. The computational model results predicted lesion dimensions that were within 5% of the experimental measurements. Conclusion When modeling radiofrequency ablation problems, temperature isotherms may not be representative of actual tissue damage patterns.	Introduction The mitigation of primary and metastatic tumors by radiofrequency ablation is a developing research area. The goal of ablation is to necrose treatment volumes by raising the temperature of targeted tissues. Ablation probes are inserted percutaneously, laparoscopically, or during surgery into cancerous tumors. Once positioned, high frequency alternating current (450–550 kHz) is delivered through an uninsulated electrode into the surrounding tissues to a dispersive ground pad that is applied to the patient. The electromagnetic energy is converted to heat by resistive heating. While the usage of radiofrequency ablation devices is well established, efforts to optimize treatment strategies are ongoing. An important consideration in optimizing ablation is determining what treatment volumes are necessary and acceptable. In liver ablation, for example, treatment volumes generally extend a centimeter beyond the dimensions of a tumor [ 1 - 3 ]. Since the liver possesses regenerative characteristics, it is more critical to insure that necrosis is achieved in 100% of the cancerous cell volume than to minimize damage to healthy tissues. In contrast, a centimeter margin in cardiac ablation is generally unacceptable since many vital substructures are in close proximity. The growth of ablation lesions remains a central issue in the development of radiofrequency ablation devices. Knowing the expected shape of lesions is essential for treatment planning and procedure optimization. To date, many approaches have been attempted to characterize lesion size. The results have varied widely. Ablation lesions generated in vitro and in vivo in animal models show wide variations, since many of the key parameters (i.e. tissue perfusion) cannot be controlled [ 4 , 5 ]. In addition, the boundaries of lesions in animal models are often "fuzzy" and are subject to interpretation. Computational modeling is a valuable tool in the optimization process, since it allows the systematic examination of the various parameters affecting the outcome of ablation. However, most computational models fail to capture essential physiologic phenomena. Many computational studies have been reported in the literature to predict the growth of lesion size during ablation [ 6 - 19 ]. However, the majority of these models do not directly calculate lesion size. Surrogate endpoints, such as temperature [ 20 - 22 ] and thermal dosing [ 23 ] are calculated and are interpreted as being equivalent to lesion size. In many cases, these surrogate endpoints do not correlate well with clinical outcome and vary considerably. The microwave hyperthermia literature, for example, cites 42 degrees Celsius as the point at which thermal damage occurs to tissues [ 24 , 25 ]. In the cardiac ablation literature, 47 degrees Celsius is generally accepted as the onset of tissue damage [ 23 , 24 , 26 , 27 ]. Neither of these values can be derived directly from gross histological measurements of lesion size, since the tissue pathology does not provide a record of temperature. Many computational studies justify these surrogate endpoints by showing a high correlation between temperature isotherms and lesion size. However, temperature isotherms and lesion size have never actually been shown to be equivalent. Several investigators have demonstrated that tissue damage is a function of both temperature and time [ 28 - 30 ]. As tissue temperature is increased, the amount of time necessary to achieve a threshold of damage decreases. Tissue damage can be characterized using the Arrhenius equation which relates temperature and exposure time using a first order kinetics relationship. Data from experimental studies, where tissues are exposed to uniform temperatures for controlled time intervals, are fit to the Arrhenius equation to determine the frequency factor A (s -1 ), and the activation energy Δ E (J mol -1 ). Arrhenius parameters have been determined in skin [ 31 - 35 ], artery [ 36 , 37 ], blood [ 38 - 40 ], pancreas [ 41 , 42 ], heart [ 43 ], cornea [ 44 - 46 ], muscle [ 47 ], prostate [ 48 ], ovary [ 49 ], kidney [ 50 - 52 ], and liver [ 30 , 52 , 53 ]. For a specified exposure temperature and time, the fit parameters A and Δ E determine the amount of cell damage incurred for a specific tissue type. In combination with computational modeling techniques, it is then possible to calculate the distribution of cell damage surrounding ablation probes. In this study, we compare the temperature distribution and tissue necrosis patterns for a hepatic ablation probe at body temperatures. At each time step, the specific absorption rate (SAR), temperature, and the tissue damage are calculated. The level of tissue perfusion is varied for the models to determine the maximum variation in lesion size resulting from a typical ablation. These data are validated experimentally using an ablation probe in liver tissue. Methods Radiofrequency ablation probes operate between 460–550 kHz. At these frequencies, the wavelength of the electromagnetic energy is several orders of magnitude larger than the size of the ablation electrodes. Thus, the primary mode of energy transfer is through electrical conduction and can be modeled as a coupled quasistatic electrical conduction and heat conduction problem. The electric field is solved by using Laplace's equation, ∇·[ σ ( T )∇ V ] = 0 (Eq.1) where ∇ is the gradient operator, σ (T) is the temperature-dependent conductivity (Siemens/meter), and V is the electric potential (Volts). Temperature is solved by using a modified Pennes bioheat equation [ 54 ], where ρ is the density, 1060 kg/m 3 [ 55 ]; C is the heat capacity of tissues, 3600 J/kg-K [ 55 ]; k is the heat conduction coefficient, 0.502 W/K-m [ 55 ]; ρ b is the density of blood, 1000 kg/m 3 [ 9 ]; C b is the heat capacity of blood, 4180 J/kg-K [ 9 ];α is a tissue state coefficient; ω is the blood perfusion coefficient, 6.4 × 10 -3 sec -1 [ 9 ];T amb is the ambient body temperature, 37°C; and Q m is the metabolic heat source term. For all cases, we assumed that the metabolic heat source was insignificant. The tissue state coefficient (α) ranges from 0–1 depending on the local level of tissue damage At each time step, the cumulative damage integral is computed using the well established Arrhenius equation where Ω(t) is the degree of tissue injury, c(t) is the concentration of living cells, R is the universal gas constant, A is a "frequency" factor for the kinetic expression (s -1 ), and Δ E is the activation energy for the irreversible damage reaction (J-mol -1 ) [ 50 ]. The kinetic parameters account for morphologic changes in tissue relating to the thermal degradation of proteins [ 56 ]. The parameters A and Δ E are dependent on the type of tissue and have been characterized for liver tissues by Jacques et. al. (A = 7.39 × 10 39 s -1 and ΔE = 2.577 × 10 5 J-mol -1 ) [ 52 ]. In the context of finite element modeling of tissue damage, a damage integral of Ω = 1, corresponds to a 63% percent probability of cell death at a specific point. A damage integral of Ω = 4.6, corresponds to 99% percent probability of cell death at a point in the model. The significance of Ω = 1 has been reported as the point at which tissue coagulation first occurs [ 36 ]. Once tissue coagulation occurs, tissue perfusion ceases. This corresponds to a tissue state coefficient of α = 0. Intermediate levels of the tissue state coefficient are calculated as α = 1/exp(Ω). Figure 1 shows a diagram of a typical needle ablation electrode used in clinical practice for hepatic tumor ablation. The probe is 6.0 cm long with a diameter of 0.15 cm. The distal 2.0 cm of the probe is uninsulated and the proximal 4.0 cm of the probe is covered with a thin electrically insulating material. Figure 2 shows a three-dimensional representation of the axisymmetric two-dimensional geometry of the model. The active portion of the probe is situated in the center of a cylindrical model that is 6.0 cm in radius and 12.0 cm in height. Electrical and thermal properties of liver are used in the model to simulate a fully-embedded insertion of the needle electrode. The electrical properties of tissue are assumed to be temperature dependent and solved according to Chang [ 57 ], where the electrical conductivity appears as Figure 1 Ablation probe geometry diagram of a single needle ablation electrode that is used for hepatic tumor ablation. Therapeutic treatment is achieved by applying a source voltage to the conducting tip. A conducting pad applied to the patient skin serves as an electrical ground return. Figure 2 Model geometry three dimension representation of the axisymmetric two-dimensional finite element model. All external surfaces of the cylindrical model serve as the electrical ground and are at body temperatures (37°C). The entire ablation probe is assumed to be thermally insulating. σ(T, N ) = σ(25, N ) {1.000-1.962 × 10 -2 Δ + 8.08 × 10 -5 Δ 2 - N Δ [3.020 × 10 -5 + 3.922 × 10 -5 Δ + N (1.721 × 10 -5 Δ - 6.584 × 10 -6 Δ)]} (Eq.4) where σ (25, N ) = N [10.394-2.3776 N + 0.68258 N 2 - 9.13538 N 3 + 1.0086 × 10 -2 N 4 ] ;N is the normality of an electrically equivalent sodium chloride solution, N = 0.0111; and Ä = 25-T, which produces an equivalent electrical conductivity of liver tissues at 37°C (approximately 0.134 S/m). The thermal properties of liver used in the model were acquired from Tungjitkusolmun et al. [ 9 ] and Duck [ 55 ]. A source voltage (V o ) is applied to the conducting tip of the ablation probe. The outer surface of the model serves as an electrical ground return (V = 0). An electrically insulating boundary condition is applied to the non-conducting portions of the probe such that n ·(σ∇ V) = 0; where n is the unit vector normal to the surface, σ is the electrical conductivity, and V is the voltage at the insulating surface. A thermal boundary condition of T = T amb is applied to the outer surfaces of the model to simulate ambient temperature. Since the thermal mass of the probe is small compared to the surrounding tissue, we assumed that heat conduction into the probe itself was minimal. Thus, all other surfaces of the ablation probe are considered to have a thermally insulating boundary condition such that n ·(k ∇ T) = 0. A hybrid finite element model was developed using Femlab (Comsol, Burlington MA, USA) and Matlab (Mathworks, Natick MA, USA) to calculate temperature and tissue damage. While conventional finite element models effectively solve field solutions using a nonuniform geometrical mesh, tissue exposure calculations are integrated at each point in the model over the course of ablation and are more easily calculated using uniform rectilinear grids. As shown in Figure 3 , Femlab is used to solve the coupled electromagnetic and heat conduction equations simultaneously at each timestep. This is done to insure that the temperature-dependent electrical conductivity is updated with each iterative calculation of temperature for a given timestep. The converged temperature is mapped from the finite element mesh into a rectilinear grid, which is passed into the Matlab environment. The amount of tissue damage occurring at each timestep is calculated using the Arrhenius equation and tracked at each point in the model. Once the level of damage exceeds 63% cell damage, it is assumed that tissue coagulation has occurred, causing a cessation in tissue perfusion. The 63% cell damage point is historically used because it corresponds to the earliest onset of visible tissue coagulation. A rectilinear grid containing the perfusion characteristics at each point in the model is mapped back into the finite element mesh and used in subsequent Femlab calculations. The rectilinear grid of temperature is also used to calculate the change in the electrical conductivity which is an explicit function of temperature. This data is also mapped back into the finite element mesh and is used to change the electromagnetic sourcing characteristics. Augmented matrices are used to insure that calculations made on the geometric borders of the Femlab model are interpolated correctly. Figure 3 Computational technique diagram of data flow used in a hybrid finite element model implemented in Femlab/Matlab to calculate temperature and tissue damage. The electric field and temperature are solved simultaneously in Femlab (blue blocks). The data structure is changed from finite element meshing to rectilinear gridding so that the resulting temperature can be used to calculate tissue exposure and electrical conductivity change in Matlab (orange blocks). A tissue damage level of 63% corresponds to the onset of tissue necrosis and is associated with a cessation in local blood flow. The Matlab results are then imported into Femlab as inputs for calculation at the next time step. Given the axial symmetry of the problem, we used a 2D-axisymmetric mesh consisting of 13,641 nodes and 26,880 elements. The Femlab 'Fldaspk' ordinary differential equation solver was used to achieve convergence. This is a robust variant of the traditional ODE15s stiff differential equation solver used in solving finite element problems in Matlab. Ablations were simulated at source voltages of 0, 2.5, 5, 7.5, 10, 12.5, 15, 17.5, 20, 22.5, 25, 27.5, and 30 volts. For each of the source voltages, we varied the initial level of tissue perfusion at 0%, 20%, 40%, 60%, 80%, and 100% normal tissue perfusion (6.4 × 10 -3 cubic meters of blood/ cubic meter of tissue/ second) [ 9 ]. Ambient tissue temperature was assumed to be 37°C. The model simulates a 15 minute ablation and updates tissue parameters at 2 second timestep intervals. Once the 15 minute ablation has ended, the model continues to solve solutions for 15 minutes post-ablation. For each simulation, the electric field (E), the current density (J), the temperature (T), and the tissue damage (D) were calculated. All calculations were implemented on a Dual 3.02 GHz Xeon processor workstation with 4 GByte RAM. Each simulation takes approximately 3 hours to run. Experimental Validation To validate the computational model, experimental measurements were made in 6 freshly excised porcine liver sections. A single needle ablation probe with a 2 cm uninsulated tip was inserted 3 cm into each liver tissue. Since commercial RF ablation generators operate using either constant temperature or constant power feedback algorithms, an experimental constant voltage RF generator (500 kHz) was used [ 5 ]. Tissue samples were allowed to equilibrate to room temperature (approximately 22°C) prior to the start of ablation. Two samples were ablated at 20 volts for 15 minutes. After allowing the tissue to cool for an additional 15 minutes, the probes were removed and the tissue was bisected to expose the lesion. The tissues were immediately placed in a 1% 2,3,5-triphenyltetrazolium chloride (red) solution for 20 minutes to stain for tissues containing active dehydrogenase, an indicator of cell viability [ 58 , 59 ]. This stains healthy tissue brick red, leaving the ablated region a pale grey color. The maximum width and depth of the macroscopically pale ablated regions were measured. This procedure was repeated for two samples at 25 volts and for the last two samples at 30 volts. Computational model calculations were made at 20, 25, and 30 volts following the same experimental protocol. Ambient temperature for these calculations was 22°C instead of the 37°C temperature used in the main simulations. The calculated lesion sizes were directly compared with the measurements in tissue. Results Table 1 shows the maximum temperatures attained in tissue for the computational models for a range of voltages (2.5–30 Volts) and tissue perfusion rates (0–100% normal tissue perfusion.). The table shows a nonlinear relationship between the source voltage and the maximum temperature that results from the use of a temperature-dependent electrical conductivity. The maximum variation in the temperature data for a given source voltage did not exceed 17%. The data show that the rate of temperature increase accelerates as a function of the source voltage. As the level of tissue perfusion increases, tissue temperature decreases. Table 1 Maximum Temperature (Degrees Celsius) 1 Values represent the maximum temperature attained in tissue for the computational models. Source Voltage (Volts) 0% 2 Perfusion (0.0 × 10 -3 m b 3 /m t 3 /s) 20% 2 Perfusion (1.3 × 10 -3 m b 3 /m t 3 /s) 40% 2 Perfusion (2.6 × 10 -3 m b 3 /m t 3 /s) 60% 2 Perfusion (3.8 × 10 -3 m b 3 /m t 3 /s) 80% 2 Perfusion (5.1 × 10 -3 m b 3 /m t 3 /s) 100% 2 Perfusion (6.4 × 10 -3 m b 3 /m t 3 /s) 2.5 37.3 37.3 37.2 37.2 37.2 37.2 5.0 38.6 38.5 38.4 38.3 38.2 38.2 7.5 41.0 40.6 40.3 40.1 40.0 39.9 10.0 44.3 43.6 43.1 42.8 42.5 42.3 12.5 48.8 47.7 46.9 46.3 45.8 45.4 15.0 54.6 52.9 51.6 50.7 50.0 49.4 17.5 62.0 59.5 57.7 56.2 55.2 54.3 20.0 71.1 67.9 65.5 63.4 61.9 60.7 22.5 82.4 78.6 75.4 73.0 70.7 69.0 25.0 96.1 91.8 88.0 84.8 82.1 79.7 27.5 112.7 3 107.8 3 103.4 3 99.5 96.1 93.4 30.0 132.5 3 126.9 3 121.8 3 117.4 3 113.4 3 109.9 3 1 – The maximum temperature for the case of 0% perfusion was located along the center of the conducting electrode. In all other cases, the maximum temperature occurred at the tip of the probe; 2 – The units for tissue perfusion are cubic meters of blood (m b 3 ) per cubic meter of tissue (m t 3 ) per second; 3 – These temperatures do not account for energy loses associated with tissue desiccation or gas formation. Table 2 shows the maximum electrical conductivity in the tissue after heating for 15 minutes at a variety of source voltages. All tissues initially have an electrical conductivity of 0.144 S/m at 37°C. The data show that tissue electrical conductivity is primarily a function of the source voltage, changing 320% over the course of a 15 minute ablation using a 30 volt source. With normal tissue perfusion (6.4 × 10 -3 m b 3 / m t 3 /s), the electrical conductivity changes as much as 260% using a 30 volt source. The electrical conductivity is indirectly a function of tissue perfusion since tissue perfusion is zero in the necrosed treatment volume. Tissue perfusion lowers the tissue temperature outside the treatment volume which helps to conduct heat away from temperatures within the ablated area.. Table 2 Maximum Electrical Conductivity (Siemens/meter) 1 Values represent the maximum electrical conductivity attained in tissue for the computational models. Source Voltage (Volts) 0% 2 Perfusion (0.0 × 10 -3 m b 3 /m t 3 /s) 20% 2 Perfusion (1.3 × 10 -3 m b 3 /m t 3 /s) 40% 2 Perfusion (2.6 × 10 -3 m b 3 /m t 3 /s) 60% 2 Perfusion (3.8 × 10 -3 m b 3 /m t 3 /s) 80% 2 Perfusion (5.1 × 10 -3 m b 3 /m t 3 /s) 100% 2 Perfusion (6.4 × 10 -3 m b 3 /m t 3 /s) 2.5 0.144 0.144 0.144 0.144 0.143 0.143 5.0 0.147 0.147 0.146 0.146 0.146 0.146 7.5 0.153 0.152 0.151 0.151 0.150 0.150 10.0 0.162 0.160 0.159 0.158 0.157 0.156 12.5 0.173 0.170 0.168 0.167 0.165 0.164 15.0 0.189 0.185 0.181 0.179 0.177 0.175 17.5 0.210 0.203 0.198 0.194 0.191 0.189 20.0 0.238 0.228 0.221 0.215 0.210 0.207 22.5 0.274 0.262 0.251 0.244 0.237 0.232 25.0 0.321 0.306 0.293 0.282 0.273 0.265 27.5 0.383 0.364 0.348 0.334 0.321 0.312 30.0 0.463 0.440 0.419 0.401 0.385 0.372 1 – The maximum electrical conductivity for the case of 0% perfusion was located along the center of the conducting electrode. In all other cases, the maximum temperature occurred at the tip of the probe; 2 – The units for tissue perfusion are cubic meters of blood (m b 3 ) per cubic meter of tissue (m t 3 ) per second. Table 3 shows the maximum SAR computed for a range of voltages and tissue perfusion rates. The SAR is defined as SAR = σ /ρ*\|E\| 2 , where σ is the electrical conductivity, ρ is the tissue density, and \|E\| is the magnitude of the electric field. The data shows that the SAR is highest with increasing source voltage with no tissue perfusion. Initially, this seems counterintuitive as one would expect a higher maximum SAR for perfused flows, where a greater amount of power is needed to compensate for the convective heat loss. This observation can be explained by the large changes in the electrical conductivity (Table 2 ). Since higher temperatures are achieved for cases with no tissue perfusion, the change in the electrical conductivity is highest with no tissue perfusion. Since, at a given point, the density and the magnitude of the electric field are essentially constant (<0.02% change), the SAR will vary as a function of the electrical conductivity only. Table 3 Maximum Specific Absorption Rate (Watts/kg) 1 Values represent the maximum specific absorption rate (SAR) attained in tissue for the computational models. Source Voltage (Volts) 0% 2 Perfusion (0.0 × 10 -3 m b 3 /m t 3 /s) 20% 2 Perfusion (1.3 × 10 -3 m b 3 /m t 3 /s) 40% 2 Perfusion (2.6 × 10 -3 m b 3 /m t 3 /s) 60% 2 Perfusion (3.8 × 10 -3 m b 3 /m t 3 /s) 80% 2 Perfusion (5.1 × 10 -3 m b 3 /m t 3 /s) 100% 2 Perfusion (6.4 × 10 -3 m b 3 /m t 3 /s) 2.5 645.6 645.3 645.1 644.9 644.8 644.8 5.0 2608 2603 2600 2598 2596 2595 7.5 5966 5940 5924 5912 5903 5896 10.0 10850 10770 10720 10680 10650 10630 12.5 17450 17260 17120 17030 16950 16900 15.0 26030 25620 25330 25120 24970 24860 17.5 36940 36140 35600 35190 34900 34680 20.0 50590 49180 48230 47480 47000 46620 22.5 67470 65210 63520 62510 61610 60990 25.0 88170 84890 82360 80440 78940 77910 27.5 113300 108900 105300 102400 100100 98390 30.0 143400 137700 133000 129000 125700 123000 1 – The maximum current density was always located at the tip of the ablation probe. Therefore, all values listed above are comparable with each other; 2 – The units for tissue perfusion are cubic meters of blood (m b 3 ) per cubic meter of tissue (m t 3 ) per second. Figure 4 shows the tissue temperature and the cell death penetration into tissue for a 15 minute ablation using a 30 volt constant voltage source for perfusion rates ranging from no perfusion to 100% normal tissue perfusion. The data show that cell death decreases more rapidly than tissue temperature. At the center of the active electrode, temperatures decrease as a function of the inverse of the radius squared (1/r 2 ), whereas cell damage exhibits an S-shaped curve. Figure 4 shows that 63% tissue damage is roughly correlated with the 60°C isotherm for liver tissues. Conventional temperature isotherms for tissue damage for hyperthermia (42°C) and radiofrequency ablation (47°C) substantially overestimate the size of the lesions. Figure 4 Tissue temperature and cell death penetration for a 15 minute ablation using a 30 volt constant voltage source. Simulation results for a 15 minute ablation using a 30 volt constant voltage source measured from the center of the active electrode. The graph shows temperature (solid) and cell death (dotted) penetration into liver tissue for a range of tissue perfusion rates. The units for tissue perfusion are cubic meters of blood (m b 3 ) per cubic meter of tissue (m t 3 ) per second (s). Figure 5 shows a plot of tissue temperature and cell damage calculated at a distance of 4 millimeters from the center of the active electrode for a 15 minute ablation using a 30 volt constant voltage source. Temperature decrease and cell damage that occurs after the ablation is monitored for an additional 15 minutes. The data show that near the electrode, tissue damage will reach 100% well within the first few minutes of energy application. For cases of no tissue perfusion, 100% tissue damage occurs after 5 minutes at a distance of 4 millimeters. For cases with normal tissue perfusion, 100% tissue damage occurs approximately 8 minutes into the ablation. At a distance of 10 millimeters from the center of the active electrode under the same conditions (Figure 6 ), the data show that tissue damage will not always reach 100%. For the case of no perfusion, 100% cell damage is reached a minute after the termination of radiofrequency energy. In cases with varying levels of tissue perfusion, cell damage is significantly reduced and, in some cases, insignificant. Although the overall temperatures are lower at 10 millimeters than at 4 millimeters, temperatures near 60°C are reached but do not result in complete tissue damage because the length of time in which the tissue is exposed is not sufficient. Figure 5 Tissue temperature and cell death at a distance of 4 millimeters from the center of the active electrode using a 30 volt constant voltage source. Ablation simulation results attained 4 millimeters from the center of the active electrode for a 15 minute ablation using a 30 volt constant voltage source. The graph shows temperature (solid) and cell death (dotted) penetration into liver tissue for a range of tissue perfusion rates. The units for tissue perfusion are cubic meters of blood (m b 3 ) per cubic meter of tissue (m t 3 ) per second (s). Figure 6 Tissue temperature and cell death at a distance of 10 millimeters from the center of the active electrode using a 30 volt constant voltage source. Ablation simulation results attained 10 millimeters from the center of the active electrode for a 15 minute ablation using a 30 volt constant voltage source. The graph shows temperature (solid) and cell death (dotted) penetration into liver tissue for a range of tissue perfusion rates. The units for tissue perfusion are cubic meters of blood (m b 3 ) per cubic meter of tissue (m t 3 ) per second (s). Figure 7 and 8 show comparisons of temperature distribution and lesion size development with no tissue perfusion (Figure 7 ) and with normal tissue perfusion (Figure 8 ) for a 30 volt constant voltage source ablation at 1, 3, 5, 10 and 15 minutes. The data demonstrate that the shapes of the temperature isotherms do not correlate well with tissue damage profiles. Tissue perfusion greatly affects the size of the resulting ablated region. At 15 minutes, lesion volumes are 267% larger without perfusion than with tissue perfusion. Figures 9 and 10 show a comparison of the temperature distribution and lesion size development with no tissue perfusion (Figure 9 ) and with normal tissue perfusion (Figure 10 ) at 1, 3, 5, 10, and 15 minutes following a 15 minute constant 30 volt ablation. In the case of no tissue perfusion, the lesion size continues to grow 14% within the first 5 minutes after radiofrequency energy is terminated. The lack of tissue perfusion prolongs the time needed to conduct the heat away from tissues near the surface of the ablation electrode. For cases with normal tissue perfusion, heat is quickly dissipated by tissue perfusion causing the lesion volume to stabilize in less than 2 minutes. By definition, the area of coagulative necrosis has no tissue perfusion. This accounts for the residual heating pattern within the ablated region as seen up to 3 minutes following the ablation. Figure 7 Comparison of temperature and lesion size development with no tissue perfusion for a 30 volt constant voltage source ablation. Ablation simulation results for a 30 volt constant voltage source ablation with no tissue perfusion. The results on the top half of the figure represent the temperature distribution surrounding the ablation probe in degrees Celsius. The results on the bottom half of the figure represent the percent tissue damage. The numbers listed at the bottom are the lesion volume sizes computed from the 63% cell damage isocontours at each time interval shown. Figure 8 Comparison of temperature and lesion size development with normal tissue perfusion (6.4 × 10 -3 m b 3 /m t 3 /s) for a 30 volt constant voltage source ablation. Ablation simulation results for a 30 volt constant voltage source ablation with normal tissue perfusion (6.4 × 10 -3 m b 3 /m t 3 /s). The results on the top half of the figure represent the temperature distribution surrounding the ablation probe in degrees Celsius. The results on the bottom half of the figure represent the percent tissue damage. The numbers listed at the bottom are the lesion volume sizes computed from the 63% cell damage isocontours at each time interval shown. Figure 9 Comparison of temperature and lesion size development post ablation with no tissue perfusion for a 30 volt constant voltage source ablation. Ablation simulation results following a 15 minute ablation without perfusion for a 30 volt constant voltage source ablation. The results on the top half of the figure represent the temperature distribution surrounding the ablation probe in degrees Celsius. The results on the bottom half of the figure represent the percent tissue damage. The numbers listed at the bottom are the lesion volume sizes computed from the 63% cell damage isocontours at each time interval shown. Figure 10 Comparison of temperature and lesion size development post ablation with normal tissue perfusion (6.4 × 10 -3 m b 3 /m t 3 /s) for a 30 volt constant voltage source ablation. Ablation simulation results following a 15 minute ablation with normal tissue perfusion (6.4 × 10 -3 m b 3 /m t 3 /s) for a 30 volt constant voltage source ablation. The results on the top half of the figure represent the temperature distribution surrounding the ablation probe in degrees Celsius. The results on the bottom half of the figure represent the percent tissue damage. The numbers listed at the bottom are the lesion volume sizes computed from the 63% cell damage isocontours at each time interval shown. A comparison of lesion volumes with no tissue perfusion computed using 63% and 100% iso-damage threshold contours and 42°C, 47°C, 60°C, and 90°C isothermal contours is presented for the cases of no tissue perfusion (Table 4 ) and normal tissue perfusion (Table 5 ). The sensitivity of the cell damage function (Figure 4 ) results in less than 10% differences in the size of lesions calculated using tissue damage thresholds of 63% and 100% cell damage. In contrast, volume sizes based on isothermal contours varies considerably at each temperature. When using traditional isothermal contours of 42°C and 47°C, the calculated lesion volumes are grossly overestimated by 500% and 167%, respectively. In both the case of no tissue perfusion and normal tissue perfusion, the 60°C isothermal contour resembles the lesion sizes calculated using the iso-damage contours. Table 4 Lesion Volume with No Tissue Perfusion Values represent the total volume of tissue necroses calculated over the course of the simulated ablation using various cell damage thresholds (D) and isothermal temperatures (IT). Source Voltage (Volts) D = 63% (mm 3 ) D = 100% (mm 3 ) IT = 42°C (mm 3 ) 1 IT = 47°C (mm 3 ) 1 IT = 60°C (mm 3 ) IT = 90°C (mm 3 ) 2.5 0 0 0 0 0 0 5.0 0 0 0 0 0 0 7.5 0 0 0 0 0 0 10.0 0 0 89 0 0 0 12.5 0 0 444 13 0 0 15.0 0 0 942 216 0 0 17.5 9 3 1649 526 6 0 20.0 121 67 2508 915 87 0 22.5 314 242 3549 1414 296 0 25.0 577 495 4860 2070 547 6 27.5 923 809 6452 2866 870 55 30.0 1388 1228 8386 3830 1243 202 1 – The 42°C and 47°C isothermal volumes were chosen specifically because they are frequently used to establish damage thresholds in hyperthermia and radiofrequency ablation, respectively. Table 5 Lesion Volume with 100% Normal Tissue Perfusion. Values represent the total volume of tissue necroses calculated over the course of the simulated ablation using various cell damage thresholds (D) and isothermal temperatures (IT). Source Voltage (Volts) D = 63% (mm 3 ) D = 100% (mm 3 ) IT = 42°C (mm 3 ) 1 IT = 47°C (mm 3 ) 1 IT = 60°C (mm 3 ) IT = 90°C (mm 3 ) 2.5 0 0 0 0 0 0 5.0 0 0 0 0 0 0 7.5 0 0 0 0 0 0 10.0 0 0 1 0 0 0 12.5 0 0 47 0 0 0 15.0 0 0 185 6 0 0 17.5 0 0 358 68 0 0 20.0 4 2 513 177 1 0 22.5 23 19 784 287 15 0 25.0 131 89 1068 488 107 0 27.5 251 222 1502 759 241 3 30.0 433 364 2014 1064 423 24 1 – The 42°C and 47°C isothermal volumes were chosen specifically because they are frequently used to establish damage thresholds in hyperthermia and radiofrequency ablation, respectively. Table 6 shows a comparison of lesion width and depth computed using 63% and 100% iso-damage threshold contours and 42°C, 47°C, 60°C, and 90°C isothermal contours. The data show overestimations of 30–77% in the width and 18–54% in the depth of lesions when using traditional isothermal temperatures for a 15 minute ablation with no perfusion. Table 7 shows that in cases with normal tissue perfusion, calculations using traditional isothermal contours results in overestimations of 25–88% in the width and 15–41% in the depth of lesions. Table 6 Lesion Dimensions with no Tissue Perfusion Values represent the maximum lesion width and depth calculated over the course of the simulated ablation using various cell damage thresholds (D) and isothermal temperatures (IT). Width (mm) Depth (mm) Source Voltage (Volts) D = 63% D = 100% IT = 42°C 1 IT = 47°C 1 IT = 60°C IT = 90°C D = 63% D = 100% IT = 42°C 1 IT = 47°C 1 IT = 60°C IT = 90°C 2.5 0 0 0 0 0 0 0 0 0 0 0 0 5.0 0 0 0 0 0 0 0 0 0 0 0 0 7.5 0 0 0 0 0 0 0 0 0 0 0 0 10.0 0 0 8 0 0 0 0 0 19 0 0 0 12.5 0 0 16 0 0 0 0 0 26 0 0 0 15.0 0 0 22 8 0 0 0 0 31 13 0 0 17.5 6 4 28 14 4 0 7 5 35 24 6 0 20.0 10 8 32 18 10 0 21 16 39 28 18 0 22.5 14 12 36 22 14 0 25 24 43 31 24 0 25.0 18 18 40 26 18 4 28 26 45 34 28 6 27.5 22 22 44 30 22 8 31 30 49 37 30 14 30.0 26 26 46 34 26 12 33 33 51 39 33 23 1 – The 42°C and 47°C isothermal volumes were chosen specifically because they are frequently used to establish damage thresholds in hyperthermia and radiofrequency ablation, respectively. Table 7 Lesion Volume with 100% Normal Tissue Perfusion Values represent the maximum lesion width and depth calculated over the course of the simulated ablation using various cell damage thresholds (D) and isothermal temperatures (IT). Width Depth Source Voltage (Volts) D = 63% D = 100% IT = 42°C 1 IT = 47°C 1 IT = 60°C IT = 90°C D = 63% D = 100% IT = 42°C 1 IT = 47°C 1 IT = 60°C IT = 90°C 2.5 0 0 0 0 0 0 0 0 0 0 0 0 5.0 0 0 0 0 0 0 0 0 0 0 0 0 7.5 0 0 0 0 0 0 0 0 0 0 0 0 10.0 0 0 2 0 0 0 0 0 2 0 0 0 12.5 0 0 8 0 0 0 0 0 16 0 0 0 15.0 0 0 10 0 0 0 0 0 25 0 0 0 17.5 0 0 14 6 0 0 0 0 27 7 0 0 20.0 4 4 16 8 2 0 5 4 29 23 2 0 22.5 6 6 20 10 6 0 10 8 31 25 8 0 25.0 10 8 24 14 8 0 23 23 33 27 23 0 27.5 12 12 26 18 12 4 25 25 36 29 25 5 30.0 16 14 30 20 16 6 27 27 38 31 27 9 1 – The 42°C and 47°C isothermal volumes were chosen specifically because they are frequently used to establish damage thresholds in hyperthermia and radiofrequency ablation, respectively. To validate the computational model, ablation experiments were performed at room temperature (22°C) in excised porcine liver tissue using 20, 25, and 30 volt constant voltage radiofrequency sources (500 kHz). Ablations were made for a 15 minute exposure time. Figure 11 shows that no visible lesion can be seen in tissues where the 20 volt constant voltage ablation was performed, as predicted by the computational simulation. A lesion that was approximately 10 millimeters in width and 22 mm in depth resulted from the 30 volt constant voltage ablation. Table 8 shows a high correlation between the computational data calculated at 22°C and the experimental results. Figure 11 Experimental validation radiofrequency ablation lesions in excised porcine liver tissue produced by a 20 volt (left) and 30 volt (right) constant voltage radiofrequency generator (500 kHz) for a 15 minute exposure time. The lesions were produced using a single needle ablation probe with a 2 centimeter uninsulated tip. Table 8 Comparison of Computational Data to Experimental Validation Data at 22°C. Lesion Width Lesion Depth Source Voltage (Volts) D = 63% (mm) Experimental (mm) D = 63% (mm) Experimental (mm) 20.0 0 0 0 0 22.5 0 -- 0 -- 25.0 4 5 5 6 27.5 8 -- 9 -- 30.0 10 10 21 22 Simulated lesion dimensions with no tissue perfusion at an ambient temperature of 22°C using a 63% cell damage threshold (D) were compared to experimental measurements made at 20, 25, and 30 volts using an experimental constant voltage radiofrequency ablation source. Lesions were generated with a single needle ablation probe with a 2.0 cm active electrode. All lesion measurements were measured visually under a micrsope at 10× magnification. Discussion To date, several computational studies have been performed to described the rate of lesion growth in radiofrequency ablation applications. In many cases, these studies use surrogate endpoints such as temperature isotherms and thermal dosing to calculate equivalent expressions for lesion size. While many models exists that account for far-more elaborate parameters such as tissue perfusion through large blood vessels, the interpretation of such models is difficult since most do not account for transient changes in tissue properties and often report tissue temperature only [ 6 - 9 , 12 , 14 - 19 , 56 , 57 , 60 ]. Several studies have identified that both exposure time and temperature contribute to tissue damage, however, few have actually calculated tissue damage. Those that do, have not allowed tissue damage to transiently influence the electrical and thermal properties of tissues [ 6 , 56 ]. In this study, we created a computational simulation that tested some of the basic assumptions made in modeling lesion growth problems. We developed a model where tissue perfusion and the electrical conductivity are allowed to vary at each time step and spatial position as a function of tissue damage and temperature. These simulations are significantly more time-consuming since gross simplifications to heating mechanisms are not made. Although our model geometry is simpler than others that appear in the literature, we chose to ignore large vessels since their position and impact are highly variable. We chose a simpler geometry so that the impact of damage-dependent tissue perfusion and temperature-dependent electrical conductivity could be assessed more directly. The damage-dependent tissue perfusion accounts for physiological observations of tissue coagulation and local cessation of blood flow. Unlike thermal dosing, where thermal injury is calculated globally over the entire duration of an ablation, tissue damage is calculated at every time step. The intermediate tissue damage that results at every timestep influences the local tissue perfusion and creates a moving boundary condition which changes the local heat sink properties. Ignoring the intermediate timesteps causes tissue perfusion to remain constant throughout the entire ablation, which results in an underestimation of the true lesion size. The use of temperature-dependent electrical conductivity greatly affects modeling results, as the electrical conductivity has been shown to increase dramatically over the course of tissue heating [ 57 ]. When constant electrical conductivity is used, the SAR is grossly underestimate, which also results in an underestimation in lesion size. An important outcome of this study is the demonstration that, temperature isotherms and tissue damage patterns are not synonymous. Traditional use of temperature isotherms that are used to define lesion size rely on coagulation temperature for protein (42–47°C) and grossly overestimate lesion dimensions. Our studies show that temperature decrease is gradual, while tissue damage decreases rapidly as a function of distance. It is this sharp decrease in tissue damage that causes lesion boundaries to appear fuzzy, as predicted by our model. The results also demonstrate that ablation lesions continue to grow after the applied power is terminated. Lesions continue to grow while temperature envelopes collapse after ablation since sufficiently high temperature are present to accrue tissue damage. In nearly all cases, lesions continued to grow several minutes following the ablation. A comparison of the resulting lesion dimensions between fully perfused and non-perfused tissues show that the lesion width decreases 38–46% and the lesion depth decreases 18–20% when tissue perfusion is accounted for in the model. Previous studies have shown that tissue perfusion can account for as much as 50% change in the size of the lesions generated during ablation [ 59 ]. An important observation in this study is the resemblance of the 60°C isocontour to lesion size. While the 42°C and the 47°C isotemperature contours are poor indicators of lesion size, 60°C is highly correlated with the lesion volumes. Seemingly, this would suggest that time-intensive tissue damage calculations need not be made since a critical temperature of 60°C can be used to identify lesion size. However, this is only true if the calculated temperature is a function of both transient changes in tissue perfusion and the electrical conductivity. In the absence of either of these phenomena, lesion sizes calculated at 60°C would underestimate lesion size. The validation data demonstrate that the model accurately accounts for the behavior of lesion growth in tissue. There are, however, a few limitations to this model. First, it is well established that temperature elevation of tissues results in the denaturing of proteins, which may drastically change the electrical conductivity of tissue in a nonlinear fashion [ 51 , 57 ]. Preliminary data suggests that the electrical conductivity substantially increases, which would likely increase the rate of tissue damage. The results of this study show that as a first order approximation the conductivity of equivalent sodium chloride solutions produces results that are within 5% of the experimental measurements. Although the phenomena described in this reporting are applicable to different tissues, the resulting lesion dimensions and temperature profiles in this study apply only to liver tissue. Similar studies can be made in other tissues, but were not pursued in this study. A second limitation in our model is that it is only valid for temperatures below 100°C. At temperatures above 100°C, tissues begin to boil and generate gas. When this occurs, some of the energy that contributes to temperature increase is used to change the water content of tissues into gas. At substantially higher temperatures, the composition of gas may be highly complex as tissue begins to burn and break down. Although gas generation is commonly seen in clinical use of radiofrequency ablation, impedance rises due to tissue charring limit the progressive rise in temperature. The complexity of multi-phasic ablation was beyond the scope of this study. Disclaimer The mention of commercial products, their sources, or their use in connection with material reported herein is not to be construed as either an actual or implied endorsement of such products by the Department of Health and Human Services.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC514567.xml
521084	Anogenital distance in human male and female newborns: a descriptive, cross-sectional study	Background In animal studies of the effects of hormonally active agents, measurement of anogenital distance (AGD) is now routine, and serves as a bioassay of fetal androgen action. Although measurement of AGD in humans has been discussed in the literature, to our knowledge it has been measured formally in only two descriptive studies of females. Because AGD has been an easy-to-measure, sensitive outcome in animals studies, we developed and implemented an anthropometric protocol for measurement of AGD in human males as well as females. Methods We first evaluated the reliability of the AGD measures in 20 subjects. Then measurements were taken on an additional 87 newborns (42 females, 45 males). All subjects were from Morelos, Mexico. Results The reliability (Pearson r) of the AGD measure was, for females 0.50, and for males, 0.64. The between-subject variation in AGD, however, was much greater than the variation due to measurement error. The AGD measure was about two-fold greater in males (mean, 22 mm) than in females (mean, 11 mm), and there was little overlap in the distributions for males and females. Conclusion The sexual dimorphism of AGD in humans comprises prima facie evidence that this outcome may respond to in utero exposure to hormonally active agents.	Background In animal studies of the effects of hormonally active agents, measurement of anogenital distance (AGD) is now routine [ 1 - 16 ], and serves as a bioassay of fetal androgen action. In rodents, perineal growth is dihydrotestosterone-dependent [ 17 ], males have a greater AGD than females, and use of AGD to sex newborns is standard [ 18 ]. In animals AGD is correlated at only modest levels with body weight [ 19 ], because these measures reflect the effects of endocrine axes that are largely independent. AGD usually tracks through life, varies by dose of antiandrogen, and can be predictive of other androgen-responsive outcomes [ 20 ]. Although measurement of AGD in humans has been discussed in the literature [ 19 , 21 - 23 ], to our knowledge it has been measured formally in only two descriptive studies of females [ 24 , 25 ]. Because AGD has been an easy-to-measure, sensitive outcome in animal studies, we developed and implemented an anthropometric protocol for measurement of AGD in human males as well as females. This work constitutes a modest step towards evaluation of AGD in human males as a potentially useful anthropometric measure and indicator of in utero androgen status. Methods Subjects A cross-sectional study was conducted among the newborn children of women admitted for delivery to the Dr. Ernesto Meana San Román General Hospital in Jojutla, Morelos, Mexico, in 1999. This hospital provides medical care to low socioeconomic status and uninsured populations. The study included 87 newborn infants, none of whom had congenital defects or had been admitted to the neonatal intensive care unit. All infants were born at term (≥38 weeks gestation), except for one (32 weeks). The infants were of both sexes and were born after spontaneous cephalic delivery or caesarean section. Within 6 hours of birth, a structured questionnaire about family background and obstetric history was administered to the mothers, and anthropometric measurements were taken on the newborns. Anthropometry Anthropometric measurements were taken of weight, length, head circumference, and AGD. AGD was measured as follows: the newborn infant was in the dorsal decubitus position; both hips were flexed and light pressure was exerted on the infant's thighs until the examiner's hand touched the subject's abdomen. Measurements were made with Vernier calipers. Distance was measured from the center of the anus to the posterior convergence of the fourchette (where the vestibule begins) in female infants [ 24 ]; and from the center of the anus to the junction of the smooth perineal skin with the rugated skin of the scrotum in male infants (Figure 1 ). Gestational age was estimated according to the Dubowitz scoring system [ 26 ]. Figure 1 Schematic Diagram of Measurements Done, by Sex Reliability Before any contact with the 87 subjects in the main study, the personnel performing the anthropometry examined 20 other neonates; all of whom were born after ≥38 weeks gestation. In this standardization training, 7 female infants and 13 male infants were measured twice by each observer. A sufficient time interval (30 minutes) was allotted between each measurement so that the second would not be influenced by the observer's memory of the first. These data were used to examine the reliability of measures and sources of variance. Statistical analysis The reliability of the anthropometric measures was calculated as the Pearson correlation coefficient between the paired measures. The observations taken by the two observers were not statistically different when compared using a paired t-test (results not shown). Analysis of variance (ANOVA) with a random effect term for subject was used to estimate between-subject, between-observer, and within-observer components of variance, by sex. For the main study, a linear regression analysis was used to evaluate birth weight, birth length, and gestational age as predictors of AGD. Age of the mother, number of pregnancies, and time elapsed between birth and measurement were not important predictors (or confounders) of AGD in univariate or multivariate models and were not considered further in the analysis. To examine influential values and the overall fit of the model, we conducted an analysis of residuals, but found nothing of note. The protocol was approved by human subjects committees at the National Institute of Public Health in Mexico and the National Institute of Environmental Health Sciences in the U.S. Results Among the 20 subjects in the standardization exercise, the between-subject coefficient of variation was greater for measures of AGD in females than for the other measures (Table 1 ). The reliability of the AGD measures were lower than for the traditional measures of anthropometry, with the female value being slightly lower than that for males. The variances estimated from the ANOVA were, for females: between-subjects, 7.9; between-observers, 0.6; and within-observer, 0.0. For males, the values were: between-subjects, 3.5; between-observers, 0.0; and within-observer, 0.1. The relative size of the variance components was unchanged when birth weight was included in the models. Thus, the between-subject variation in AGD was much greater than the variation due to measurement error. Table 1 Mean, coefficient of variation (CV), and reliability of anthropometric measurements in 20 newborns a Measurement Mean CV Reliability Weight (kg) 3.01 0.13 1.00 Length (cm) 48.9 0.03 0.97 Head Circumference (cm) 34.2 0.03 0.98 Anogenital distance 18 0.31 0.91 Female 11 0.27 0.50 Male 21 0.09 0.64 a 7 females and 13 males. Among the 87 subjects in the main study, the birth weight, length, and head circumference were as expected in a population from southern Mexico (Table 2 ) [ 27 ]. The AGD measure was about two-fold greater in males than in females, and there was little overlap in the distributions for males and females (Figure 2 ). The correlation of AGD with body weight was 0.64 in females and 0.48 in males. Table 2 Distribution of selected characteristics in 87 newborns, Mexico, 1999 a Variable Female n = 42 Male n = 45 Anogenital distance (mm) Mean 11 21 SD 2 3 Median 11 22 25 th percentile 10 20 75 th percentile 11 23 Weight (g) Mean 3070 3060 SD 408 440 Median 3060 3110 25 th percentile 2870 2800 75 th percentile 3310 3290 Length (cm) Mean 48.6 48.7 SD 1.4 2.2 Median 48.6 48.7 25 th percentile 47.5 48.0 75 th percentile 49.6 49.9 Head circumference (cm) Mean 337 341 SD 10.9 16.7 Median 337 341 25 th percentile 330 334 75 th percentile 345 350 a SD, standard deviation Figure 2 Distribution of Anogenital Distance (AGD), by Sex In the crude models of AGD in females, weight, length, and gestational age all appeared to be predictive (Table 3 ). The adjusted results, however, suggested that weight of the newborn was the most important correlate, based on the p value being lower than for length or gestational age. For males, weight and length were more important than gestational age as determinants, and this pattern was seen also in the adjusted results (Table 4 ). Length had a slightly larger R 2 and slightly lower p value, suggesting it may be a marginally better predictor than weight in males. In a model of data for males that included weight, length, and gestational age, the p values for both length and gestation were less than 0.05, although the coefficient for gestation was negative. In a model of AGD based on data for males and females combined (results not shown), after adjustment for weight, the term for sex was clearly important (β for males = 10.9 mm, standard error = 0.4, p < 0.0001; change in R 2 due to addition of sex to model = 0.86). Table 3 Regression coefficients for anogenital distance as a function of characteristics at birth, females a Variable Crude Adjusted b Coefficient 95% CI p value R 2 Coefficient 95% CI p value R 2 Birth weight 0.002 0.002 0.003 0.000 0.41 0.002 c 0.001 0.003 0.000 0.43 Birth length 0.319 -0.005 0.642 0.061 0.09 0.141 c -0.189 0.471 0.407 0.22 Gestational age 1.296 0.516 2.076 0.002 0.21 0.501 d -0.282 1.283 0.217 0.43 a Units for regression coefficients are mm of AGD per unit characteristic (g, cm, or weeks). Results based on 42 females. CI, confidence interval. b Multivariate adjusted regression coefficients (adjustment factors listed below). c Adjusted for gestational age. d Adjusted for weight of newborn infant. Table 4 Regression coefficients for anogenital distance as a function of characteristics at birth, males a Variable Crude Adjusted b Coefficient 95% CI p value R 2 Coefficient 95% CI p value R 2 Birth weight 0.003 0.001 0.005 0.001 0.23 0.004 c 0.002 0.006 0.001 0.27 Birth length 0.671 0.348 0.995 0.000 0.28 0.914 c 0.499 1.329 0.000 0.33 Gestational age 0.356 -0.258 0.971 0.262 0.03 -0.560 d -1.284 0.165 0.137 0.27 a Units for regression coefficients are mm of AGD per unit characteristic (g, cm, or weeks). Results based on 45 males. CI, confidence interval. b Multivariate adjusted regression coefficients (adjustment factors listed below). c Adjusted for gestational age. d Adjusted for weight of newborn infant. Discussion The AGD measures employed in the present study reflect the location of the caudal border of the genital swelling, an embryologic structure that differentiates into the labia majora in females and the scrotum in males. After the indifferent stage of the external genitalia, the critical events determining the sexual dimorphism of AGD in humans begin when, relative to the anus, the genital swelling, urethral folds, and possibly the genital tubercle, move ventrally under the influence of androgens [ 28 ]. Elongation of the genital tubercle, which becomes the phallus, also occurs at this time. The difference between males and females in our data demonstrates sexual dimorphism of this particular measure of AGD. The two-fold difference in the aspect of AGD that we measured is not reflected in the schematic diagrams of human sexual differentiation we have seen [ 29 , 30 ], which is likely due to the previous lack of formal measures. Direct comparison of our results with those in the two other studies with measures of anus-to-fourchette (AF) distance in female newborns [ 24 , 25 ] is hampered by different eligibility criteria, and possibly different ethnicities, in the three studies. For example, Callegari et al.'s subjects had a mean weight of 2,530 g; Phillips et al. did not present mean birth weight but subjects were required to have a birth weight above 2,750 g; and in our study the mean birth weight among females was 3,060 g. The mean AF distance in the Callegari et al. study was 10.9 mm; in the Phillips et al. study was 16.1 mm in Jews and 16.5 in Bedouins, and in the present study was 11 mm. Callegari reported no ethnic differences in their population (62.6% Hispanic, 28.7% black, and 8.7% white). Despite the ethnic-specific mean values noted above, Phillips et al. reported that Jewish females had a greater AF distance than did Bedouins. The similarity of the mean AF distance measures in the present study and the Callegari et al. study is surprising given the difference in mean birth weights, and suggests ethnic differences, or a systematic difference in how the measurements were done. Compared with established anthropometric measures on newborns, the reliability of the AGD measures were lower. The lower reliability of the AGD measures is likely due to several factors. The AGD measures depend on indistinct landmarks on soft tissues. Structures such as "the center of the anus" or the posterior fourchette are not clearly demarcated. Any slight traction or pressure applied to the perineum or surrounding structures could alter measures. Finally, compared with established anthropometric measures on newborns, the AGD dimensions are smaller, thus measures done with the naked eye on a subject unlikely to hold still are inherently at a disadvantage. Use of two observers, one to restrain the subject and one to do the measurements could result in improved reliability compared to our approach, which employed one observer. Compared with adult humans, the size of the genitals at birth is large relative to the body overall [ 28 ]. Yet the genital size is, of course, still determined in part by overall body dimensions and age. The need to adjust AGD for overall body dimension is well known in animal experiments [ 19 ]. In humans, the best approach to such adjustment remains unclear. Our data suggest that for the aspect of AGD we measured, adjustment for body weight is reasonable. A complete assessment of AGD in humans would include more measurements than were done in our study. In neonatal rodents, measurement of AGD is relatively straightforward and is the distance from the genital tubercle to the anus. In older animals or humans of any age, however, questions arise as to which measure is most informative. For example, in human males, rather than a genital tubercle, the presence of the phallus and testicles at birth means that a number of measurements are possible. The measurement in the present study, from the posterior scrotal-perineal junction, represents only one such measurement. Ideally we would have done genital tubercle measurements in males and females, but we did not. Whether sexual dimorphism exists in the distance from the anus to the genital tubule (penile base in males) would be useful to know. While one might expect that penile length may be a good measure of androgenization among males, difficulties obtaining a reliable measure mean that alternative measures, such as AGD, are worth investigating. Effects of endocrinopathies on AGD in humans have been described, but only to a limited degree. A rare form of congenital adrenal hyperplasia that causes incomplete masculine development has been reported to cause decreased AGD in boys [ 21 ]. Details on how the measurement was done (and the measured values), however, were not presented [ 22 , 23 ]. Callegari et al. [ 24 ] measured the distance from the anus to the fourchette (same as what we did) and in addition measured the distance from the anus to the clitoris; the ratio of these two measures in three newborn females with congenital adrenal hyperplasia was increased relative to normal newborn females. Earlier case reports on females with adrenogenital syndrome noted labiosacral fusion, but again, no formal measures were published [ 23 ]. The utility of AGD measures in humans is further supported by experimental data in primates showing that in utero exposure of females to androgenic agents increased AGD [ 1 ]. The purported mechanism by which androgens increase AGD in females is by inducing "labioscrotal fusion" (in normal males fusion begins caudally and proceeds ventrally, presumably androgens in females act the same way) [ 24 ]. This mechanism, however, does not account for why males who are not fully androgenized would have a decreased AGD, unless AGD in males is defined as being from tip of penis to the center of the anus. A set of formal AGD measures on subjects with selected congenital endocrinopathies or birth defects could be useful in evaluating whether this outcome is uniformly responsive to gross stimuli, and may help discern details of normal embryology and the consequences of disrupting it. Conclusions In summary, we have shown that an aspect of genital dimension that reflects migration of the genital swelling is sexually dimorphic in humans. Whether this particular measure, or other measures of AGD in humans, has any utility as markers of exposure in utero to hormonally active agents remains to be seen. Abbreviations AF: anus-fourchette AGD: anogential distance ANOVA: analysis of variance CI: confidence interval Competing interests None declared. Authors' contributions ES participated in the design of the study, carried out the measurements, and wrote the first draft of the manuscript. PR participated in the study coordination and data management. EY carried out and coordinated the measurements. ML originated the idea that AGD measurements in human males may be useful, revised the manuscript, and analyzed the data. MH conceived of the study and participated in its design and coordination. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC521084.xml
406407	Open Access and Scientific Societies	Societies are encouraged to consider their own open-access experiments within the context of the communities they serve	This is the second in a series of three editorials that aim to address recurring concerns about the benefits and risks associated with open-access publishing in medicine and the biological sciences. Scientific societies serve their members, their broader scholarly communities, and the different components of their missions in many important ways. Making peer-reviewed literature immediately accessible, searchable, and reusable to anyone in the world with an Internet connection is a uniquely direct means of achieving a number of goals that are common to most scholarly associations and of advancing the diverse interests of their constituencies. Setting aside for the moment the question of how feasible it is for societies to alter their journals' access policies, there is by now a broad consensus that widespread open access to scientific publications is good for scientists and good for science. Society members want to maximize the impact of their work—and articles that are freely available online are cited more frequently than those that are not ( Lawrence 2001 ). Most societies are committed to catalyzing innovations within and across scientific disciplines—and open-access archives of full-text literature provide a valuable tool for sharing information globally in order to accelerate the rate of scientific progress. Many societies articulate in their mission statements the goal of communicating the benefits of their members' discoveries with the public—and open-access publishing is a direct means to accomplish this goal. In addition to an interest in exploring new ways to serve their members and their missions, societies have another compelling reason to investigate open access for their journals: the rapidly changing landscape of scholarly publishing. From 1990 to 2000, the average price of an academic journal subscription increased 10% per year ( Create Change 2000 ). While society-run and nonprofit journals may not be the major contributors to those spiraling costs, societies that rely on revenues from subscriptions and site licenses may bear a disproportionate share of the negative consequences of skyrocketing serials prices. As libraries are forced for a variety of reasons (including decreased budgets and the increasing prevalence of “big deals” and journal bundling) to eliminate subscriptions, society journals may be among the hardest hit. Journals that appeal to a relatively specialized readership and those that are not part of larger publishing groups are particularly vulnerable to the contraction of serials collections that has already begun and will likely accelerate ( Create Change 2000 ). A Society Is More Than a Journal The confluence of forces in favor of open access says nothing about its fiscal implications for scientific societies. As any systemic change in research or publishing would, the movement toward open access has generated concern about its ramifications for the scholarly associations that often serve as the backbones of scientific communities. However, the strength of those societies and their essential role in the communities they serve are precisely what should allay fears about the revenue-eroding effect that some argue would plague societies if they converted their traditional subscription-based journals to open access. Scientific societies perform an array of tremendously valuable functions for their constituents and disciplines. Researchers, educators, and others join societies for the many benefits of membership beyond simply discounted or “free” subscriptions to journals, so the concern that open-access publications would be the death knell of voluntary academic associations is misguided. As Elizabeth Marincola, executive director of the American Society for Cell Biology, recently noted, her society “offers a diverse range of products so that if publications were at risk financially, we wouldn't lose our membership base because there are lots of other reasons why people are members” ( Anonymous 2003 ). While open-access publication can, in fact, be paid for in a number of different ways, there is no question that a transition toward the elimination of online access barriers requires most societies to restructure the business models for their journals. If journal subscriptions generate surplus revenue that supports other society activities, then the business model of the society as a whole may need to be examined. This is not to say that open-access journals cannot generate a surplus or profit—simply that they do not do so by restricting access to their primary research content. Testing the Open-Access Waters There are a number of societies that have already begun to take transitional steps to wean themselves from subscription revenues. One of the earliest societies to commit to open-access publication, the American Society for Clinical Investigation (ASCI) has since 1996 provided the Journal of Clinical Investigation (JCI) freely online and recently reaffirmed its commitment to open access: “The financing having been resolved, through author charges and other means,” John Hawley, the executive director of the ASCI writes, “the JCI hopefully can bring the greatest benefit to its authors and readers, regardless of who they might be. It is in this spirit that the JCI has always been free online, and will remain so” ( Hawley 2003 ). In order to experiment cautiously with new access policies, several societies have implemented hybrid models of access-restriction for their publications. The American Physiological Society, for example, offers authors in Physiological Genomics the option to pay a surcharge for their articles to be made freely available online immediately upon publication. A recent survey by the Joint Information Systems Committee (JISC) in the United Kingdom suggests that many authors would use such an option if it were more widely available: 48% of authors who had never published in an open-access journal and 60% of authors who had done so indicated that they would be willing to “pay a publisher of a journal sold according to the traditional subscription model an additional fee for them to make [the author's] particular paper ‘open access’” ( JISC 2004 ). JISC is also directly encouraging society and nonprofit publishers to implement hybrid models and other open-access experiments and to launch new open-access journals by providing grants to offset the publication charges for authors during this transitional phase. In the long run, of course, open access will prove sustainable when more funders of research, in addition to interested third parties, designate funds specifically for the costs of publishing articles to be made freely available, searchable, and reusable online. Starting the Dialogue Reaching a “steady-state” system of open-access publishing by scientific societies will require three critical components: recognition that open access serves societies' members and missions; diversified revenue streams not solely dependent on subscription or site-license fees; and society publishers' making use of recent innovations in journal production and dissemination, which can dramatically reduce the costs of publishing. It is, after all, the increased efficiencies born of new technologies—from the Internet itself to electronic journal management systems—that have made the idea of open access possible. And while proponents of open access are confident that publication charges of around $1,500 per article will be sufficient to cover the costs of publishing an efficiently operated society journal, there is no question that many existing journals may need to update their infrastructure in order to make open access financially viable ( PLoS 2004 ). There is also no question that many societies do not, at present, have a wealth of revenue streams beyond the proceeds from their journals, which they often use to fund valuable activities from education initiatives to annual meetings. As open-access journals become more established, however, and as the benefits of open access to scientific and medical literature become more apparent to society members, the demand for the broadest possible dissemination of research is only likely to grow. Those societies that embrace the developments taking place in scholarly publishing may well see their membership and publications thrive more than societies that cling to the potentially unstable status quo. In any case, a constructive discussion about the pitfalls to be avoided and the benefits to be gained through a transition to open-access publishing would be a worthy first step for any scientific society to take—and PLoS welcomes the questions, comments, and feedback of those who are intrigued by the potential that open access affords and want to learn more.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC406407.xml
550669	An AFLP-based genetic linkage map of Plasmodium chabaudi chabaudi	Background Plasmodium chabaudi chabaudi can be considered as a rodent model of human malaria parasites in the genetic analysis of important characters such as drug resistance and immunity. Despite the availability of some genome sequence data, an extensive genetic linkage map is needed for mapping the genes involved in certain traits. Methods The inheritance of 672 Amplified Fragment Length Polymorphism (AFLP) markers from two parental clones (AS and AJ) of P. c. chabaudi was determined in 28 independent recombinant progeny clones. These, AFLP markers and 42 previously mapped Restriction Fragment Length Polymorphism (RFLP) markers (used as chromosomal anchors) were organized into linkage groups using Map Manager software. Results 614 AFLP markers formed linkage groups assigned to 10 of 14 chromosomes, and 12 other linkage groups not assigned to known chromosomes. The genetic length of the genome was estimated to be about 1676 centiMorgans (cM). The mean map unit size was estimated to be 13.7 kb/cM. This was slightly less then previous estimates for the human malaria parasite, Plasmodium falciparum Conclusion The P. c. chabaudi genetic linkage map presented here is the most extensive and highly resolved so far available for this species. It can be used in conjunction with the genome databases of P. c chabaudi , P. falciparum and Plasmodium yoelii to identify genes underlying important phenotypes such as drug resistance and strain-specific immunity.	Background Plasmodium chabaudi chabaudi is a malaria parasite of murine rodents. It has been widely used as a model to study various aspects of parasite biology and disease which are difficult to investigate using human malaria parasites. For instance, P. c. chabaudi is being used to study the genetic basis of drug resistance [ 1 - 4 ] and strain-specific immunity [ 5 ], because the execution and analysis of genetic crosses is relatively straightforward in this species [ 6 ]. The analysis of the genetic basis of aspects of malaria biology has been facilitated by recent developments in malaria genomics. Firstly, the Plasmodium falciparum genome has been fully sequenced and mapped [ 7 ] and there is also extensive sequence data now available for three of the four main malaria parasites of murine rodents [ 8 ]. Secondly, the degree of homology and conservation of gene synteny between the various species of malaria [ 4 , 9 , 10 ] allows the undertaking of comparative genomics and facilitates the elaboration of accurate genomic maps in these species. However, a genetic linkage map of the 14 chromosomes of P. c. chabaudi is still important for the identification of loci which influence phenotypes such as drug resistance. A previous genetic linkage map of P. c. chabaudi was generated using over 40 RFLP markers [ 11 ]. However, due to the small number of markers available, this linkage map had limited usefulness. The authors have recently developed a large number of genome-wide polymorphic AFLP markers for P. c. chabaudi [ 11 ]. AFLP markers have previously been used to generate genetic linkage maps in another apicomplexan parasite, Eimeria tenella [ 12 ], as well as in Trypanosoma brucei [ 13 ]. This article presents a high-resolution genetic linkage map of P. c. chabaudi and an estimate of map unit size. The value of the genetic linkage map in the identification of genes determining selectable phenotypes is also described. Methods Mouse strains used in experiments Inbred female CBA mice, obtained from the University of Edinburgh, were used for the growth of P. chabaudi parasites. Mice were housed in propylene cages with sawdust bedding and were fed on Harlan, SDS formula number I (Special Diet Services Ltd.) and drinking water supplemented with 0.05% paraminobenzoic acid (PABA) to aid parasite growth [ 14 ]. Temperature was maintained between 22 and 25°C with a 12 hour light/12 hour dark cycle. Parasite lines Clones of the genetically distinct isolates AS and AJ, originally isolated from wild thicket rats, Thamnomy rutilans [ 15 ] were used as parents in genetic crosses. 28 recombinant clones were analysed here. 20 clones originated from a cross between AJ and AS (3CQ) (a chloroquine-resistant clone derived from AS) [ 1 ], while 8 clones originated from a cross between AJ and AS (30CQ) (a clone with higher resistance to chloroquine, derived from AS (3CQ) [ 16 ]. Maintenance of parasites For routine maintenance of parasites, parasitized red blood cells collected from the tail veins of infected mice were passaged in citrate saline into uninfected mice. Cryopreservation of infected blood was performed by exsanguination of mice anaesthetised with halothane. Blood was collected in a tube containing 2–3 volumes of citrate saline (0.9% NaCl, 1.5% tri sodium citrate dihydrate, adjusted to pH 7.2). The mixture was spun at 2000 rpm for five minutes, the supernatant discarded and the red cell pellet mixed with two volumes of a solution containing 28% (v/v) glycerol, 3% sorbitol and 0.65% NaCl. The mixture was then aliquoted into several glass capillaries, which were sealed by flame and deep-frozen in liquid nitrogen. 50 μl of cryopreserved blood was recovered by thawing capillaries into 10 μl of 12% NaCl and mixing for 3–5 mins. Nine volumes of 1.6% NaCl were then added dropwise and samples centrifuged at 2000 rpm for 3–5 mins. The supernatant was removed and nine volumes of 0.9% NaCl/ 0.2% dextrose solution were added dropwise. After mixing, the mixture was centrifuged again, supernatant removed and red blood cells resuspended in a 0.9% NaCl/ 0.2% dextrose solution for injection. Estimation of parasitaemia Parasitaemia was estimated by microscopic observation of thin blood smears taken 4–6 days after parasite injection and stained with 20% Giemsa staining solution (BDH) for 15 minutes. Parasitaemia was estimated by calculating the percentage of red blood cells infected in at least five microscopic fields. Preparation of parasite DNA Each parasite DNA preparation was obtained from five infected CBA female mice. Blood samples were taken from mice infected with AS, AJ and recombinant clones having high parasitaemias in the mid-afternoon, when parasites were trophozoites. Host lymphocytes or nucleated cells present in the blood were removed as described previously [ 11 ]. Parasites were pelleted and stored at -70°C. DNA was extracted and purified as previously described [ 11 ] and stored at -20° for future use. Amplified Fragment Length Polymorphism (AFLP) technique The AFLP method was carried out according to the original protocol [ 17 ] with slight modifications, as described by Grech et al [ 11 ]. Briefly, parasite genomic DNA was digested with two enzymes, Eco RI and Mse I, and ligated with adapters, to provide the complementary sequences for AFLP primers. The first round of amplification used primers containing the Eco RI or Mse I recognition sequences at their 3' end. The second round of (selective) amplification use two additional (selective) bases (3' terminus) in both primers, one of which (the Eco RI primer) was radiolabeled with γ-[ 33 P] ATP. PCR products were run on acrylamide gels and AFLP bands visualised on autoradiography films. Polymorphic bands between the two parental strains were used as markers for the genetic linkage map. Organization of AFLP markers in a genetic linkage map For every marker, the parental alleles identified in each of the progeny clones were entered in an Excel spreadsheet. The absence of a band in one parent was treated as the presence of the other parental allele at that locus. Data were then prepared for analysis with the Map Manager QTX software [ 18 ] according to the instruction manual. The dataset was designated as "Backcross" for the purpose of computer analysis. Prior to linkage analysis, markers were tested for random assortment using a chi-square test, to exclude markers segregating in a non-random fashion from the initial analysis with Map Manager, and thus to avoid spurious linkage inferences between such markers. Because of the large number of tests for non -random assortment performed (n = 672), some markers showing apparent non-random assortment may have been falsely excluded from our analysis; i.e. some valid markers may indeed show non-random assortment and should be included. A Bonferroni correction was therefore applied to the chi-square test to decrease the stringency of the statistical test. The value of the Bonferroni correction represents the number of 'independent' comparisons and here was arbitrarily set at 24. This value was chosen as representing the likely number of chromosomal fragments at meiosis, and is supported by data presented in this paper. Markers within these fragments are not independently inherited. The chosen value (24) is a compromise between 672 (which assumes that all 672 markers are independently inherited) and 14 (the number of chromosomes, and which assumes that no pair of markers on one chromosome are inherited independently). Markers not following random assortment in the initial test were thus divided into two groups, i.e. those segregating in a non-random fashion before and after Bonferroni correction, and those segregating in a non-random fashion before but not after the Bonferroni correction. The markers in the latter group were added separately after linkage groups had been determined (see below). Linkage groups using AFLP and RFLP markers were formed with an initial p-value of 0.0001 using the "Make Linkage Groups" command in Map Manager. p-values in Map Manager indicate the probability of a Type 1 error; that is, the probability of a false positive linkage. Following formation of linkage groups, the p-value was raised to 0.001. Linkage at p < 0.001 is considered significant. Using the command "Distribute", linkage groups were brought together. Then, other previously unlinked markers were allocated to these new linkage groups, again using the "Distribute" command. Markers with non-random assortment after statistical analysis without Bonferroni correction were added next, and those still segregating in a non-random fashion after Bonferroni correction were added last. The "Ripple" function was then used to position markers in an order which maximizes the total LOD (logarithmic odds) score for linkage. The software also estimated the optimum order and genetic distance between markers in centiMorgans (cM) by using the "Kosambi" function in the software. It was then possible to calculate a map unit size (i.e the physical distance corresponding to 1 cM). The presence of 42 previously characterised RFLP markers which had been physically mapped onto P. c. chabaudi chromosomes [ 1 ] served as anchors for the placement of AFLP linkage groups onto specific chromosomes. Results The inheritance of 672 AFLP markers was determined in 28 progeny clones derived from two crosses between P. c. chabaudi AJ and either clone AS (3CQ) or AS (30CQ). The majority of the AFLP markers showed independent assortment in the 28 progeny clones, as illustrated previously [ 11 ]. However, 66 markers failed the chi-square test at 5%, 15 of which failed it after the Bonferroni correction. Markers were allocated to linkage groups using the Map Manager program and groups assigned to chromosomes using 42 previously mapped RFLP markers as anchors [ 1 ]. Estimated numbers of recombination events, genetic lengths of chromosomes and recombination frequencies were also determined for the identified chromosomes using Map Manager. Allocation of markers to linkage groups The 672 AFLP markers formed a total of 22 linkage groups with a final p-value of 0.001. Additional file 1 summarises the numbers of AFLP and RFLP markers assigned to each chromosome or to unassigned linkage groups, the estimated physical size of each chromosome [ 19 ] and the number of AFLP markers per Mb. 400 AFLP markers in 10 linkage groups could be assigned to P. c. chabaudi chromosomes 1 and 5–13, by virtue of their linkage to RFLP markers previously assigned to specific chromosomes by physical mapping [ 1 ]. 272 AFLP markers could not be assigned to a specific chromosome. 214 were placed in 12 unassigned linkage groups, each with between 2 and 51 AFLP markers. At least four of these linkage groups are likely to map to chromosomes 2, 3, 4 or 14. The failure to assign these linkage groups occurred because RFLP markers previously mapping to chromosomes 2, 3, 4 and 14 were not allocated to linkage groups. This was probably due to insufficient characterization of the inheritance patterns of these RFLP anchors which were determined in a small number of recombinant clones [ 1 ]. For instance, the inheritance of a RFLP marker assigned to chromosome 2, Ca-ATPase, was only determined for 7 out of the 28 recombinant clones. No independent physical mapping of unassigned linkage groups was attempted here. 58 AFLP markers, 21 of which segregated in a non-random fashion, could not be allocated to any linkage groups. Physical mapping of these markers would be required to assign them to specific chromosomes. Alternatively, unassigned linkage groups or unallocated markers might map to the small mitochondrial or apicoplast genomes, although these combined represent only 0.2% of the genome. Several RFLP markers could not be allocated to linkage groups by the Map Manager software, probably due to the small numbers of clones analysed for these markers. These markers were added to assigned linkage groups according to their chromosomal assignment, as previously determined by physical mapping [ 1 ]. With the exception of chromosomes 2, 3, 4 and 14 (discussed above), chromosomes 9 and 10 showed the lowest density per Mb of AFLP markers. Chromosome 7 showed the highest density. This may simply reflect natural variation in the frequency of AFLP polymorphisms on particular chromosomes. However, for chromosomes with a low apparent density of AFLP markers such as chromosomes 9 and 10, it is likely that some of the markers in unassigned linkage groups would physically map to these chromosomes. These unassigned groups may not show genetic linkage with (groups of) assigned markers because of factors such as a high rate of recombination between two linkage groups (one linked to the RFLP anchor) or because of an intervening region with a low density of AFLP markers. Both factors, or a combination of the two, may prevent two physically linked groups from being identified as genetically linked. Conversely an apparent unusually high frequency of AFLP markers (as in chromosome 7) may arise from strong linkage disequilibrium between loci on two different chromosomes. Some markers located on one chromosome may thus appear to be genetically linked to markers on another. This could arise where one locus exerts a strong constraint on another unlinked locus. For instance, the AJ allele of an enzyme in a metabolic pathway may only function with the presence of the product of the AJ allele encoding another enzyme in the same pathway. This constraint might be structural or functional. The same may be true of AS alleles of the same enzymes. In this case, the genes encoding these enzymes, and markers strongly linked to them, may appear in the same genetic linkage group. Order of markers in the linkage groups AFLP markers were initially ordered on the linkage groups as described in Materials and Methods. After inspection of the predicted marker order, occasional manual adjustments were made to correct markers which appeared to be inappropriately positioned. Because Map Manager failed to allocate some RFLP markers to an assigned linkage group, these were positioned manually. The final distribution of the markers on the 10 linkage groups assigned to chromosomes is shown in Fig. 1 , 2 , 3 (See also Additional file 2 , Additional file 3 . and Additional file 4 ). 7 unassigned linkage groups containing 9 or more markers each are shown in Fig. 4 (see also Additional file 5 ). Figure 1 Linkage map for chromosomes 1, 5, 6 and 7 of the P. c. chabaudi genome. The AFLP and RFLP markers assigned to chromosomes are displayed with genetic distances (in cM). AFLP markers were named as follows: the first two letters identify the clone to which a marker is specific, the next two letters indicate the Eco RI primer selective bases, the numbers identify the marker for that clone and primer combination in order of its molecular size, and the last two letters identify the Mse I selective bases. RFLP markers were based on genes previously identified [1]. Figure 2 Linkage map for chromosomes 8–11 of the P. c. chabaudi genome. The AFLP and RFLP markers assigned to chromosomes are displayed with genetic distances (in cM). Figure 3 Linkage map for chromosomes 12 and 13 of the P. c. chabaudi genome. The AFLP and RFLP markers assigned to chromosomes are displayed with genetic distances (in cM). Figure 4 Unassigned linkage groups containing more than 8 markers. The AFLP markers assigned to unassigned linkage groups are displayed with genetic distances (in cM) Number of recombination events per chromosome If markers and recombination events were both uniformly distributed across the genome, then we would expect the number of predicted recombination events (totalled from 28 clones characterised here) in each chromosome to correlate with its physical size. The predicted total number of recombination events occuring in each linkage group is shown in the Additional file 1 . Uniformity was evaluated by comparison of the frequency of recombination events (from the 28 clones) in each chromosome. This varies between 6.7/Mb (chromosome 10)) and 31.1/Mb (chromosome 7), with an overall value of 13.3/Mb. Chromosomes 1 and 11 also showed low frequencies. These differences may reflect natural variation in recombination rates across the genome. However, other factors may also contribute. For instance, there is likely to be a systematic underestimation of recombination frequency because the physical extent of the linkage groups assigned to particular chromosomes will be less than their actual size. For instance, if the chromosome 10 linkage group extends across only half of the chromosome, then the real density of markers and recombination events (per Mb) is likely to be about twice the apparent value given. Indeed, Additional file 1 shows that when data from the unassigned linkage groups are included, the recombination frequency (across the whole genome) increases to 15.9 events per Mb. Regardless of the number of markers assigned to each chromosome, we would expect the number of recombination events per AFLP marker to remain relatively constant, if both the frequency of polymorphism and the rate of recombination vary little between chromosomes. This is indeed the case. For the different chromosomes, the measure varies only between 0.4 and 0.9 recombination events per AFLP marker (see Additional file 1 ). Assuming that the P. c. chabaudi genome consists of about 20 Mb [ 19 ] the value of 13.3 recombination events in 28 recombinant clones/Mb converts to about 9.5 recombination events/clone/genome which is very close to the value of 10 estimated for Plasmodium falciparum [ 21 ]. A significant number of double crossover events around a single AFLP marker were observed in many linkage groups. Any such occurrences were re-evaluated on the original X-ray film to detect any possible errors or ambiguous bands. Many distinct double crossover events were observed. The same phenomenon was also commonly observed in P. falciparum , and were interpreted as being due to non-reciprocal conversion events [ 20 ]. Genetic length of linkage groups The apparent genetic length of each linkage group in cM was calculated by Map Manager based on the number of recombination events ( Additional file 1 ). When added together, the linkage groups assigned to chromosomes combined to give a total genetic length of 1180 cM and the unassigned linkage groups a further 497 cM, giving a total for the genome of 1676 cM. Due to the limited number of clones available (28), the smallest genetic distance that could be measured between two markers was approximately 3.6 cM, corresponding to the presence of a single recombination event between two markers in 28 clones. In general, the estimated genetic lengths of the linkage groups assigned to chromosomes 1, 5–13 increased with the estimated physical sizes of the chromosomes (Figure 5 ). The Pearson correlation coefficient was 0.794 (p < 0.005). The estimated sizes of map unit for chromosomes 1 and 5–13 are shown in the Additional file 1 . These values varied from 8.9 kb/cM (chromosome 5) to 24.1 kb/cM (chromosome 11) with an overall estimated mean of 15.1 kb/cM. It is likely that there is some overestimation of physical size of a map unit because individual identified linkage groups are unlikely to cover the full extent of any chromosome. Indeed, when the genetic lengths of the unassigned linkage groups are included in the analysis, the overall map unit size is reduced to 13.7 kb/cM. The inclusion of additional unallocated markers may reduce this value even further. Figure 5 Relationship between genetic size and physical size of each chromosome. The relationship between the estimated genetic sizes and physical sizes of chromosomes 1, 5–13 (Table 1) is shown. The correlation between these two variables is 0.794. However, some overestimation of genetic length in linkage groups is also possible, which leads to an underestimation of map unit size. For instance, Figure 2 shows that chromosomes 9 and 10 both show two abnormally large sections bounded by RFLP anchors without intervening AFLP markers. Specifically, chromosome 9 shows, at one end, an RFLP marker, ran , 40 cM from its nearest AFLP marker. At its other end, an RFLP marker, Ag 3027, lies about 35 cM from its nearest AFLP marker. Chromosome 10 has RFLP marker cDNA121 about 70 cM from its nearest AFLP marker and RFLP marker, 5S rRNA, a further 70 cM distant. These large gaps may be artefacts which arise for two reasons. Firstly, some unreliability in the typing of clones using RFLPs was previously noticed [ 4 ]. Secondly, the inheritance patterns of these markers were not determined in all 28 recombinant clones. Markers ran , Ag3027, cDNA121 and 5S rRNA were typed for only 9, 17, 9 and 16 clones, respectively. The characterisation of inheritance of RFLP markers in all of the 28 progeny clones, and the correction of possible mistakes may reduce the estimated genetic length. This would lead to an increase in map unit size. Nevertheless, it is notable that the value reported above (13.7 kb/cM) is close to estimates made for P. falciparum (15–30 kb/cM [ 21 ] or 17 kb/cM [ 20 ]), although slightly smaller. It is likely that the recombination rate may vary within as well as between chromosomes or genomic loci [ 22 ]. Estimate of potential alleles due to indel mutations Of the 400 AFLP markers placed on chromosomes, 37 AS-AJ pairs (74 markers i.e. 18% of the total) shared the same selective bases at both primer ends and showed complementary segregation in the cross-progeny clones. Most of these markers also differed in size by only a few base pairs. They are likely to be alleles at the same loci. This was confirmed by sequencing two such pairs, namely ASTA01AC and AJTA01AC (chromosome 5), and ASTT02CA and AJTT02CA (chromosome 13) (sequence data not shown). This suggests that a significant proportion of the polymorphisms observed between AS and AJ may be due to small insertions or deletions. In fact, it was observed that small indels tend to occur in introns or intergenic regions (data not shown). Reliability of the AFLP markers in the progeny clones A few AFLP markers which were originally identified between clones AJ and AS [ 11 ] were not found in the progeny clones. Also, a few bands appeared in the progeny clones that were absent in the parents. All of these markers were ignored during the generation of the linkage map. It is possible that such markers could indicate genetic re-arrangements in the drug-resistant clones AS (3CQ) and AS (30CQ). However, they did not segregate with chloroquine resistance phenotype (data not shown). Some other markers were difficult to investigate because of their proximity to other bands or their location at the bottom of the gel, where bands tend to be fuzzier and more difficult to interpret. Effect of typing mistakes in the markers Ongoing work on linkage between chloroquine resistance and markers on chromosome 11 [ 4 ] suggested that AFLP and/or RFLP markers were occasionally incorrectly characterised in one ore more of the 28 clones. To test the effect of incorrect typing in AFLP markers, some deliberate mistakes were introduced by changing the parent from which a particular marker was inherited in a particular recombinant clone. The effect of such changes ranged from the appearance or disappearance of predicted double-crossover events and consequent change in the estimated genetic length, to a larger scale change in the order of markers within a linkage group. Occasionally markers were reallocated to a different linkage group. It was concluded that patterns of linkage may be sensitive to errors in genotyping individual clones. Discussion Genetic or physical linkage maps have been determined and reported for a number of apicomplexan parasites, including P. falciparum [ 20 ], P. c. chabaudi [ 11 ], Eimeria tenella [ 13 ], Toxoplasma gondii [ 23 ], Theileria parva [ 24 ] and Cryptosporidium parvum [ 25 ]. The map reported here is very extensive in terms of the numbers and density of markers included. Only the genetic map of P. falciparum exceeds its resolution Of the AFLP markers analysed, most were assigned to 10 of the 14 chromosomes, while some were placed on 12 unassigned linkage groups, which probably include groups located on chromosomes 2, 3, 4 and 14. The remaining AFLP markers could not be allocated to any linkage group. Unallocated AFLP markers and unassigned linkage groups may arise in a number of possible ways, discussed in the Results section above, including mistakes or considerable gaps in the recorded inheritance pattern of RFLP markers and, to a lesser extent, AFLP markers. Other factors include variations in the density of AFLP markers or polymorphism in general, areas of the genome where the rate of recombination is particularly high, linkage disequilibrium between loci on different chromosomes and non-random representation of clones in our sample. The numbers of markers allocated, the approximate genetic lengths and the number of recombination events were estimated for each of the linkage groups. The genetic length of the entire genome was estimated to be 1684 cM and the overall size of map unit 13.7 kb/cM. The genetic length and number of recombination events were expected to increase with the size of chromosomes. This was generally found to be the case, although a number of factors may influence these data. These factors include the failure to assign some linkage groups, incomplete or incorrect inheritance data, particularly for RFLPs, variation in the frequency of AFLP markers across the genome, variation in the recombination rate across the genome, and incorrect assignation of some linkage groups due to linkage disequilibrium. The presence and frequency of small indel mutations was confirmed. These markers could prove suitable for rapid typing of clones by size polymorphism and quantitative analysis by Real Time Quantitative PCR. The generation of a complete AFLP genetic linkage map for P. chabaudi was originally conceived as an essential step towards the identification of loci linked to genes encoding important phenotypes, such as drug resistance. Indeed, the identification of a locus underlying chloroquine resistance in P. chabaudi within approximately 250 kb of chromosome 11 [ 4 ] relied upon elements of the present map in the analysis of linkage between phenotype (chloroquine resistance) and genotype (inheritance of parental AFLP markers) in individual recombinant clones. However we have also developed a novel strategy called Linkage Group Selection [ 5 , 26 ] which more rapidly identifies loci linked to genes underlying selectable phenotypes, such as drug resistance. For example, a drug resistant parasite is crossed with a genetically different drug sensitive parasite. The uncloned recombinant progeny are drug treated, and AFLP markers which are linked to loci underlying drug resistance may be identified as those reduced in their representation or intensity [ 27 ]. A genetic linkage map enables us to determine whether AFLP markers which are significantly reduced in intensity lie in the same linkage group, prior to further sequence analysis. Genome sequence data are now available for P. c. chabaudi (partial) [ 8 ] and P. falciparum (complete) [ 7 ], and sequenced AFLP markers can sometimes be mapped to the P. falciparum genome. Because of the extensive gene synteny between P. chabaudi (and other rodent malarias) and P. falciparum [ 4 , 9 , 10 ], markers closely linked in P. falciparum are likely to be closely linked in P. chabaudi too. The correspondence between the genetic linkage map reported here and the mapping of AFLP markers to the P. falciparum genome in the studies discussed above [ 4 , 5 , 26 ] has increased our confidence both in the genetic linkage map reported here, and the extent of gene synteny between the P. c. chabaudi , Plsmodium yoelii and P. falciparum genomes [ 9 , 10 ]. The existence of a rodent malaria genome map, complete with syntenic relationships between it and the P. falciparum genome (Taco Kooij and Andy Waters, personal communication), will allow us to assign unallocated AFLP markers and unassigned linkage groups to particular chromosomes on the assumption that gene synteny is conserved. Authors' Contributions AM characterized the AFLP markers in the cross progeny, generated the genetic linkage map and drafted the article, PH helped in the generation of the linkage map, analysed genetic data from it and drafted the article, RF helped in the characterization of the AFLP markers in the cross progeny, PC and DW provided the recombinant clones and revised the article, RC designed and coordinated the study, revised the article and gave final approval. All authors read and approved the final manuscript. Supplementary Material Additional File 1 The file (.XLS) contains the following data for markers assigned to chromosomes and, where possible, for markers in unassigned linkage groups and the overall genome: – physical size of each chromosome (Mb), the number of markers (either RFLP or AFLP and total), the number of AFLP markers per Mb, the number of recombination events predicted for the 28 clones, the frequency of recombination events per Mb and per AFLP marker, the predicted genetic length of all linkage groups, and the estimated size of map unit (kb/cM). Click here for file Additional File 2 This file is the original PPT files from which figure 1 was derived.Figures 1-3 contain the linkage map for the chromosomes 1 and 5-13. Click here for file Additional File 3 This file is the original PPT files from which figure 2 was derived.Figures 1-3 contain the linkage map for the chromosomes 1 and 5-13. Click here for file Additional File 4 This file is the original PPT files from which figure 3 was derived.Figures 1-3 contain the linkage map for the chromosomes 1 and 5-13. Click here for file Additional File 5 This file is the original PPT files from which figure 4 was derived. Figure 4 contains various unassigned linkage groups. Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC550669.xml
314476	Visualizing Noncentrosomal Microtubules during Spindle Assembly	null	As cells can only arise from cells that already exist, continuity of life depends on the highly regulated sequence of events that control cell division. This process is mediated by a complex macromolecular structure called the mitotic spindle. The most conspicuous components of the spindle are microtubules, which are made of tubulin and other associated proteins. In most animal cells—body cells and male germline cells (spermatocytes)—spindle assembly is orchestrated by organelles called centrosomes, which actively polymerize (that is, add tubulin subunits) and stabilize microtubules. The spindles found in these cells are known as astral because of the star-shaped asters—structures made of centrosome-anchored microtubules—that can be observed associating with each spindle pole. Some cells—such as the cells of the female germline (oocytes)—do not contain centrosomes, and the chromosomes themselves seem to arrange and stabilize the microtubules into spindles. These spindles are referred to as anastral . To gain insight into the mechanisms of spindle assembly, scientists are increasingly relying on techniques that allow them to directly observe dynamic, complex processes in the living cell. Using time-lapse microscopy of fluorescently labeled fruitfly ( Drosophila melanogaster ) spermatocytes, Cayetano Gonzalez and his colleagues at the European Molecular Biology Laboratory in Germany (and now at the Centro Nacional de Investigaciones Oncológicas in Spain) have been able to observe the assembly and sorting of microtubules of noncentrosomal origin in cells that contain centrosomes. The task of flagging such microtubules is complicated by the fact that centrosomes become quite active microtubule organizers once cell division begins. Thus, as soon as the membrane around the nucleus breaks down, microtubules from the centrosome invade the nuclear region, making it hard to identify any noncentrosomal microtubules that might appear. To get around this problem, Elena Rebollo in the Gonzalez lab set up two experimental conditions under which centrosomes remain functional but are kept affixed to the cell membrane—and, therefore, away from the nucleus—in Drosophila spermatocytes. One takes advantage of a genetic mutation (called asp , for abnormal spindle); the other uses a transient treatment with a drug (called colcemid) that depolymerizes microtubules. In these modified cells, microtubules can be seen growing not only over the membrane-bound centrosomes, as expected, but also over the nuclear region, away from the centrosomes. Nucleation, or formation, of such noncentrosomal microtubules has a relatively late onset, starting only once chromosomes are condensed, and takes place on the inner side of the remnants of the nuclear envelope. In a fraction of cells, these microtubules are sorted into bipolar spindle-shaped structures, highly reminiscent of the anastral spindles found in oocytes. Chromosome segregation—a critical stage of cell division—and cell division itself tend to be aberrant in these cells. These results, Rebollo et al. propose, strongly suggest that microtubules of noncentrosomal origin may significantly contribute to spindle assembly even in cells that contain active centrosomes. Moreover, by facilitating the nucleation of such noncentrosomal microtubules, the degraded nuclear envelope may play a previously unsuspected role in spindle assembly in Drosophila spermatocytes. It is unlikely, the researchers also conclude, that the anastral spindles they have observed can fill in as a backup to ensure successful cell division. More likely, they argue, both centrosomal and noncentrosomal microtubules are required for proper spindle assembly and robust cell division in cells with centrosomes. As the authors point out, Drosophila is a rich model system that should help scientists further investigate the intricacies of spindle assembly. The answers will help us understand how the cell executes one of its most important duties: safeguarding genomic stability for future generations. Centrosome-independent spindle assembly	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC314476.xml
538264	Gene expression profiling reveals novel TGFβ targets in adult lung fibroblasts	Background Transforming growth factor beta (TGFβ), a multifunctional cytokine, plays a crucial role in the accumulation of extracellular matrix components in lung fibrosis, where lung fibroblasts are considered to play a major role. Even though the effects of TGFβ on the gene expression of several proteins have been investigated in several lung fibroblast cell lines, the global pattern of response to this cytokine in adult lung fibroblasts is still unknown. Methods We used Affymetrix oligonucleotide microarrays U95v2, containing approximately 12,000 human genes, to study the transcriptional profile in response to a four hour treatment with TGFβ in control lung fibroblasts and in fibroblasts from patients with idiopathic and scleroderma-associated pulmonary fibrosis. A combination of the Affymetrix change algorithm (Microarray Suite 5) and of analysis of variance models was used to identify TGFβ-regulated genes. Additional criteria were an average up- or down- regulation of at least two fold. Results Exposure of fibroblasts to TGFβ had a profound impact on gene expression, resulting in regulation of 129 transcripts. We focused on genes not previously found to be regulated by TGFβ in lung fibroblasts or other cell types, including nuclear co-repressor 2, SMAD specific E3 ubiquitin protein ligase 2 ( SMURF2 ), bone morphogenetic protein 4 , and angiotensin II receptor type 1 ( AGTR1 ), and confirmed the microarray results by real time-PCR. Western Blotting confirmed induction at the protein level of AGTR1, the most highly induced gene in both control and fibrotic lung fibroblasts among genes encoding for signal transduction molecules. Upregulation of AGTR1 occurred through the MKK1/MKK2 signalling pathway. Immunohistochemical staining showed AGTR1 expression by lung fibroblasts in fibroblastic foci within biopsies of idiopathic pulmonary fibrosis. Conclusions This study identifies several novel TGFβ targets in lung fibroblasts, and confirms with independent methods the induction of angiotensin II receptor type 1, underlining a potential role for angiotensin II receptor 1 antagonism in the treatment of lung fibrosis.	Background Transforming Growth Factor beta (TGFβ) is a multifunctional cytokine that regulates a variety of physiological processes, including cell growth and differentiation, extracellular matrix production, embryonic development and wound healing [ 1 ]. Altered expression of TGFβ plays a crucial role in organ fibrosis, hypertrophic scarring, cancer, autoimmune and inflammatory diseases [ 2 ]. In the lung, TGFβ is consistently linked with progressive fibrosis [ 3 - 5 ]. Increased expression of TGFβ has been reported in a variety of fibrotic lung diseases [ 6 , 7 , 3 ], including idiopathic pulmonary fibrosis (IPF), a relentlessly progressive fibrotic lung disease with a median survival from diagnosis of only two years [ 8 ], and pulmonary fibrosis associated with systemic sclerosis, one of the leading causes of death in scleroderma patients [ 9 ]. Animal models also support a central role played by TGFβ in lung fibrosis. Intra-tracheal adenovirus-mediated TGFβ gene transfer causes severe lung fibrosis extending to the periphery of the lungs [ 5 ]. Mice lacking alphavbeta 6, an integrin which is crucial to the release of active TGFβ from latent extracellular complexes, develop lung inflammation but are strikingly protected from bleomycin-induced lung fibrosis [ 10 ]. IL-13 overexpression induces lung fibrosis which is mediated via TGF-β1 induction and activation [ 11 ]. Experimental inhibition of TGFβ with neutralizing antibodies, soluble receptors, or gene transfer of the TGFβ inhibitor Smad7, inhibits fibrosis in animal models [ 12 - 14 ]. Lung fibroblasts are the main cell type responsible for excessive extracellular matrix synthesis and deposition in fibrosing lung disorders [ 15 ]. TGFβ modulates fibroblast function through several mechanisms, including induction of extracellular matrix protein synthesis and inhibition of collagen degradation [ 1 ]. However, knowledge of TGFβ targets in adult lung fibroblasts is still limited to a small number of genes. Oligonucleotide array technology allows the simultaneous assessment of thousands of genes providing a global gene expression profiling of the response to a stimulus. The response to TGFβ has been investigated using oligonucleotide microarrays in keratinocytes [ 16 ] as well as in dermal [ 17 ] and in a human fetal lung fibroblast line [ 18 ], but not in primary human adult lung fibroblasts. Fibroblastic responses are likely to vary with the origin and developmental state of the cells [ 19 ], and a detailed study of TGFβ responses in adult lung fibroblasts is needed to gain further insights into the fibroproliferative process in the lung. We therefore quantified gene expression by oligonucleotide microarrays of adult lung fibroblasts (derived from biopsies of normal and both idiopathic and scleroderma-associated pulmonary fibrosis) in response to TGFβ, and identified several novel TGFβ targets among the wide variety of genes regulated by this cytokine. Of these, we particularly focused on angiotensin II receptor type 1 , the most highly TGFβ-induced gene among those encoding for signal transduction molecules. Methods Cell culture Primary adult lung fibroblasts were cultured from three control samples (unaffected lung from patients undergoing cancer-resection surgery) and from open-lung biopsy samples of lung fibrosis patients, three with idiopathic pulmonary fibrosis (IPF) [ 8 ] and three with pulmonary fibrosis associated with the fibrotic disease systemic sclerosis [ 9 ]. Independent reviews of the clinical (SV, ER) and histopathologic diagnosis (AGN) were performed. All the idiopathic pulmonary fibrosis biopsies were characterized by a usual interstitial pneumonia pattern (UIP), whereas all of the scleroderma-associated pulmonary fibrosis were classified as non-specific interstitial pneumonia (NSIP) [ 8 ]. Verbal and written consent was given by all subjects; authorization was given by the Royal Brompton Hospital Ethics Committee. Fibroblast culture conditions were as previously described [ 20 ]. At confluence, lung fibroblasts (all between passages 4–5) were serum-deprived for 16 hours, and exposed to either 4 ng/ml of activated TGF-β1 (R&D Systems) or serum-free culture medium for four hours. The concentration and time point of TGFβ used in our experiments was determined from ongoing studies within our laboratory, in which a 4 hour treatment with TGFβ 4 ng/ml was found to show significant induction of selected known direct TGFβ target genes, including CTGF. RNA isolation and gene array analysis At the end of the treatment period with or without TGFβ, total RNA was harvested (Trizol, Life Technologies), quantified, and integrity was verified by denaturing gel electrophoresis. Preparation of RNA samples for chip hybridization followed Affymetrix (Affymetrix, Santa Clara, California) protocols. Each RNA sample derived from an individual fibroblast line was hybridized on a separate microarray chip. Hybridization of cRNA to Affymetrix human U95Av2 chips, containing approximately 12,000 well characterized human genes, signal amplification and data collection were performed using an Affymetrix fluidics station and chip reader, following Affymetrix protocol. Scanned files were analyzed using Affymetrix Version 5.0 software (MAS5). Chip files were analyzed by scaling to an average intensity of 150 per gene, as recommended by Affymetrix. Reproducibility was assessed using two pairs of RNA samples from the same control line, TGFβ-treated/untreated; the concordance correlation coefficients were of 0.979 and 0.983, respectively. TGFβ response was analyzed by using a combination of the MAS5 Affymetrix change algorithm and of ANOVA models. According to Affymetrix criteria, in each TGFβ-treated/medium only pair, genes were defined as differentially regulated (either up or down) by TGFβ only when identified as significantly increased (I) or decreased (D) as determined by the Affymetrix change algorithm, with a change p value<0.001, and were detected as Present (according to the "absolute call"obtained by an Affymetrix algorithm) at least in the samples with the highest count (i.e. medium only in the case of D and TGFβ in the case of I). Genes were defined as TGFβ-responsive in normal human lung fibroblasts when they fulfilled all of the following three conditions: a) they were detected as TGFβ-regulated by Affymetrix criteria (see above) in at least two of the three control pairs; b) they showed a mean fold change after TGFβ of at least 2 (or lower than 0.5) in control fibroblasts; c) either a two-way ANOVA including only control fibroblasts detected a significant (p < 0.05) increase or decrease in control fibroblasts after TGFβ or they were also found to be responsive in at least four of the six fibrotic fibroblast lines and a significant effect (p < 0.05) of treatment (with TGFβ) was detected by a repeated measure ANOVA model including all the samples and adjusting for individual samples, disease, and interaction between treatment and disease. All statistical analyses were performed on log transformed data to reduce inequalities of variance. Thus, the latter ANOVA model could detect genes which were equally up- or down-regulated in normal and fibrotic fibroblasts, taking advantage of the larger number of samples, while the first model (equivalent to a paired t test) could detect changes possibly occurring in controls but not in fibrotic cell lines. Except for unknown genes, all gene symbols and names are given according to the nomenclature proposed by the Human Genome Organization (HUGO) Gene Nomenclature Committee. Real time-PCR Real time PCR (RT-PCR) was performed to confirm selected novel TGFβ targets in lung fibroblasts. Adult lung fibroblast lines [three control and three fibrotic (IPF)] were treated with or without TGFβ (4 ng/ml) for four hours. Total RNA was isolated from treated and untreated samples using Trizol (Life Technologies) and the integrity of the RNA was verified by gel electrophoresis. Total RNA (1 microgram) was reverse transcribed in a 20 μl reaction volume containing oligonucleotide dTs (dT 18 ) and random decamers (dN 10 ) using M-MLV reverse transcriptase (Promega) for 1 hour at 37°C. The cDNA was diluted to 100 μl with DEPC-treated water and 1 μl was used per real-time PCR reaction. A set of eight standards containing a known concentration of target amplicon was made by PCR amplification, isolation by gel electrophoresis through a 2% agarose gel followed by gel purification using QIAquick PCR purification spin columns (Qiagen). The concentration of the amplicon was measured by spectrophotometry and diluted in DEPC-treated water containing transfer RNA (10 μg/ml) to make standards of 10 fold dilutions from 100 pg/ μl to 0.01 fg/ μl. The target was measured in each sample and standard by real-time PCR using FastStart DNA Master SYBR Green (Roche Applied Science) as described by the manufacturer, in half the reaction volume (10 μl). Samples and standards were amplified for 30 to 40 cycles with the appropriate primers (Molecular Biology Unit, KCL School of Biological Sciences) at least in duplicate. The amount of target in the sample in picograms was read from the standard curve and values were normalised to 28S ribosomal RNA (pg of target/pg of 28S ribosomal-RNA). The oligonucleotide primer sequences are listed (5'-3'): angiotensin II receptor type1 ( AGTR1 ) primers: forward TGC TTC AGC CAG CGT CAG TT and reverse GGG ACT CAT AAT GGA AAG CAC; SMAD specific E3 ubiquitin protein ligase 2 ( SMURF2 ): forward AAC AAG AAC TAC GCA ATG GGG and reverse GTC CTC TGT TCA TAG CCT TCT G; nuclear receptor co-repressor 2 ( NCOR2 ): forward CAG CAG CGC ATC AAG TTC AT and reverse GTA ATA GAG GAC GCA CTC AGC; bone morphogenetic protein 4 ( BMP4 ) primers: forward CTA CTG GAC ACG AGA CTG GT and reverse GAG TCT GAT GGA GGT GAG TC. The results were analyzed using Student's paired t-test after logarithmic transformation, and statistical significance was taken as a p value of <0.05. Western blot analysis of TGFβ-induction of angiotensin II receptor 1 Lung fibroblasts were grown to confluence in DMEM with 10% FCS. At confluence, lung fibroblasts (all between passages 2–5) were serum-deprived overnight, and exposed to either 4 ng/ml of activated TGF-β1 (R&D Systems) or serum-free culture-medium with the addition of 0.1% BSA for 24 hours. To determine the signalling pathways through which TGFβ induces AGTR1, lung fibroblasts were treated with specific inhibitors 30 minutes before treatment with TGFβ. These included the dual MKK1/MKK2 inhibitor U0126 (10 μM) and predominant MKK1 inhibitor PD98059 (50 μM), known to inhibit MKK2 only weakly [ 21 ], as well as the p38 MAPK inhibitor SB 202190 (30 μM). Cell layer lysates were examined. Cell protein (10 μg/sample) was heated to 99°C for 5 min, loaded into sample wells, resolved on a 12% tricine SDS-polyacrylamide gel (Novex, San Diego, CA), and run at 120 V for 2 h. The separated proteins were transferred onto nitrocellulose membranes at 30V for 90 minutes. Membranes were blocked by incubation for one hour with 5% non-fat milk in phosphate buffered saline (PBS) containing 0.1% Tween 20. They were then washed and incubated overnight at 4°C in a 1:500 dilution of rabbit anti-angiotensin II receptor 1 polyclonal antibody (Santa Cruz Biotechnology), followed by a three-time wash in PBS and incubation in 1:1000 goat anti-rabbit biotinylated IgG (Vector Laboratories, Peterborough, UK) for 60 min at room temperature. Membranes were washed three times in PBS, and the signal was amplified/detected by using the ECL protocol as described by the manufacturer (Amersham plc, Little Chalfont, UK). Films were analysed by laser scanning densitometry on an Ultrascan XL (LKB-Wallac, UK). Data were analyzed by using Student's paired t test after log transformation and a p value<0.05 was considered significant. Immunohistochemistry The distribution of staining for AGTR1 was assessed by immunohistochemistry in surgical lung biopsies from four patients with idiopathic pulmonary fibrosis (IPF), meeting the diagnostic criteria of the American Thoracic Society/European Respiratory Society Consensus Classification [ 8 ], and in control biopsies (normal periphery of resected cancer) from three patients undergoing cancer resection surgery. Paraffin-embedded sections were dewaxed with xylene, hydrated and heated in the microwave at 120 degrees for 30 minutes in citrate buffer (10 mM pH 6.0). Slides were then briefly rinsed in PBS, blocked with 10% normal goat serum for 20', incubated with rabbit polyclonal anti-human AGTR1 antibody (N-10, 1:50, Santa Cruz Biotechnology, Santa Cruz, Calif) for one hour at room temperature. After washing with PBS, sections were incubated with biotinylated goat anti-rabbit IgG diluted in PBS (1:200) for 30 minutes, rinsed, and finally incubated with Vectastain Elite STR-ABC reagent (Vector Laboratories) for 30 minutes. After washing, sections were visualized using 3-amino-9-ethylcarbazole chromogen and H 2 O 2 as substrate (SK-4200; Vector Laboratories). Sections were then washed in tap water, counterstained with Carrazzis hematoxylin, and mounted with Gelmount (Biomeda, Foster City, CA) for examination using an Olympus BH-2 photomicroscope. Controls included an exchange of primary antibodies with goat matched antibodies. To confirm staining specificity, sections were also incubated with either nonimmune rabbit IgG control or secondary antibody only. Results Microarray analysis of TGFβ-response in primary adult lung fibroblasts According to the criteria outlined in the methods, a four hour treatment with TGFβ was found to regulate 129 transcripts in human lung fibroblasts. TGFβ-responsive transcripts included genes with roles in gene expression, matrix formation, cytoskeletal remodelling, signalling, cell proliferation, protein expression and degradation, cell adhesion and metabolism. A complete list of TGFβ-regulated genes is provided (see Additional file 1 ). The complete set of gene array data has been deposited in the Gene Expression Omnibus database with GEO serial accession number GSE1724 . We did not observe a substantial degree of difference in the response to TGFβ between the two fibrotic groups (idiopathic pulmonary fibrosis and scleroderma-associated pulmonary fibrosis) and control lung fibroblasts. Once the criteria outlined in the methods section and the p-value for interaction with treatment had been taken into account, there were no significant differences in the response to TGFβ among the three groups except for two genes, KIAA0261 (probe N: 40086_at), an unknown gene more upregulated in IPF (median fold change 2.2) than in scleroderma-associated pulmonary fibrosis (1.5) and in controls (1.3), and BTG1 (probe N: 37294_at), which was only slightly more downregulated in scleroderma-associated pulmonary fibrosis (fold change:0.4) than in IPF (0.6) and in controls (0.7). As both the number of genes and the magnitude of the differences were minimal, they were not considered meaningful and were not investigated further. Among genes responding significantly to TGFβ in control lung fibroblasts, as assessed by ANOVA analysis, none changed in opposite directions in either of the fibrotic groups. All the genes that responded significantly in the control group alone, were also TGFβ-responsive when analysis was extended to include the fibrotic cell lines. Furthermore, none of these genes responded differently to TGFβ between the two fibrotic groups, which are thus presented together in Tables 1 and 2 . Table 1 Transcription factor genes regulated by TGFβ in control and fibrotic lung fibroblasts (LF) Gene Symbol Affymetrix Probe N Control LF* Fibrotic LF* Gene name BHLHB2 40790_at 6.0 5.1 basic helix-loop-helix domain containing, class B, 2 CBFB 41175_at 2.9 2.8 core-binding factor, beta subunit EGR2 37863_at 52.0 3.3 early growth response 2 (Krox-20 homolog, Drosophila) ETV6 38491_at 2.0 2.6 ets variant gene 6 (TEL oncogene) FOXO1A 40570_at 3.8 6.0 forkhead box O1A (rhabdomyosarcoma) JUNB 2049_s_at 3.7 4.2 jun B proto-oncogene JUNB 32786_at 4.4 3.0 jun B proto-oncogene LRRFIP1 41320_s_at 2.1 1.5 leucine rich repeat (in FLII) interacting protein 1 MKL1 35629_at 2.7 2.6 megakaryoblastic leukemia (translocation) 1 MSC 35992_at 2.4 1.7 musculin (activated B-cell factor-1) NCOR2 39358_at 2.2 2.2 nuclear receptor co-repressor 2 NPAS2 39549_at 2.4 3.1 neuronal PAS domain protein 2 NR2F2 39397_at 0.4 0.5 nuclear receptor subfamily 2, group F, member 2 NRIP1 40088_at 2.3 1.8 nuclear receptor interacting protein 1 RUNX1 393_s_at 2.3 2.6 runt-related transcription factor 1 (aml1 oncogene) RUNX1 39421_at 3.1 2.3 runt-related transcription factor 1 (aml1 oncogene) RUNX1 943_at 2.2 2.7 runt-related transcription factor 1 (aml1 oncogene) SKI 41499_at 2.5 2.1 v-ski sarcoma viral oncogene homolog (avian) SMURF2 33354_at 2.2 2.2 E3 ubiquitin ligase SMURF2 SRF 1409_at 2.1 1.9 serum response factor SRF 40109_at 2.2 2.0 serum response factor TCF21 37247_at 0.2 0.4 transcription factor 21 TCF8 33439_at 2.8 1.8 transcription factor 8 (represses interleukin 2 expression) TIEG 224_at 2.2 2.1 TGFB inducible early growth response TIEG 38374_at 3.2 2.7 TGFB inducible early growth response ZFP36L2 32587_at 0.3 0.4 zinc finger protein 36, C3H type-like 2 ZFP36L2 32588_s_at 0.3 0.3 zinc finger protein 36, C3H type-like 2 ZNF365 35959_at 14.2 2.5 zinc finger protein 365 Mean fold change in mRNA abundance in TGFβ treated/untreated control and fibrotic lung fibroblasts (LF), respectively. Fibrotic lung fibroblast ratios represent the average values of idiopathic and scleroderma-associated pulmonary fibrosis lung fibroblasts. Table 2 TGFβ-regulated signalling and ECM/cytoskeletal genes in control and fibrotic lung fibroblasts Gene Symbol Affymetrix Probe N Control LF Fibrotic LF* Gene name Signal transduction ACVR1 39764_at 2.2 1.7 activin A receptor, type I ADM 34777_at 0.3 0.4 adrenomedullin AGTR1 346_s_at 3.8 3.2 angiotensin II receptor, type 1 AGTR1 37983_at 5.1 5.9 angiotensin II receptor, type 1 BDKRB2 39310_at 0.4 0.4 bradykinin receptor B2 BMP4 1114_at 0.2 0.2 bone morphogenetic protein 4 BMP4 40333_at 0.1 0.3 bone morphogenetic protein 4 DYRK2 40604_at 3.0 3.0 dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 2 DYRK2 760_at 2.9 3.3 dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 2 DYRK2 761_g_at 3.3 2.2 dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 2 MLP 36174_at 2.4 1.7 MARCKS-like protein PLK2 41544_at 0.4 0.6 polo-like kinase 2 (Drosophila) RRAD 1776_at 3.0 5.2 Ras-related associated with diabetes RRAD 39528_at 3.6 5.1 Ras-related associated with diabetes SMAD3 38944_at 0.4 0.4 SMAD, mothers against DPP homolog 3 (Drosophila) SMAD7 1857_at 2.3 2.2 SMAD, mothers against DPP homolog 7 (Drosophila) SOCS1 41592_at 0.1 0.1 suppressor of cytokine signaling 1 SPRY2 33700_at 2.0 1.8 sprouty homolog 2 (Drosophila) STK38L 32182_at 3.7 3.8 serine/threonine kinase 38 like TGFBR3 1897_at 0.3 0.5 transforming growth factor, beta receptor III (betaglycan) TNFRSF1B 1583_at 0.4 0.6 tumor necrosis factor receptor superfamily, member 1B TNFRSF1B 33813_at 0.4 0.4 tumor necrosis factor receptor superfamily, member 1B TSPAN-2 35497_at 4.2 5.0 tetraspan 2 Extracellular matrix remodelling/Cytoskeletal COL4A1 39333_at 2.2 2.0 collagen, type IV, alpha 1 COMP 40161_at 2.7 5.3 cartilage oligomeric matrix protein COMP 40162_s_at 5.0 18.9 cartilage oligomeric matrix protein CTGF 36638_at 4.8 6.1 connective tissue growth factor CYR61 38772_at 4.4 3.5 cysteine-rich, angiogenic inducer, 61 ELN 31621_s_at 4.9 3.7 elastin ELN 39098_at 8.4 11.6 elastin PLAUR 189_s_at 2.7 2.8 plasminogen activator, urokinase receptor PLOD2 34795_at 2.5 1.8 procollagen-lysine, 2-oxoglutarate 5-dioxygenase 2 SERPINE1 38125_at 3.7 4.0 serine (or cysteine) proteinase inhibitor, clade E, member 1 SERPINE1 672_at 6.0 5.5 serine (or cysteine) proteinase inhibitor, clade E, member 1 TIMP3 1034_at 2.0 1.5 tissue inhibitor of metalloproteinase 3 TIMP3 1035_g_at 2.4 1.6 tissue inhibitor of metalloproteinase 3 TPM1 36790_at 2.3 1.7 tropomyosin 1 (alpha) TPM1 36791_g_at 2.7 2.1 tropomyosin 1 (alpha) TPM1 36792_at 2.5 2.0 tropomyosin 1 (alpha) Mean fold change in mRNA abundance in TGFβ treated/untreated control and fibrotic lung fibroblasts (LF), respectively. Fibrotic lung fibroblast ratios represent the average of idiopathic and scleroderma-associated pulmonary fibrosis lung fibroblasts. For the purpose of this study, we will concentrate on genes involved in transcriptional regulation, cytoskeletal/extracellular matrix organization, and signal transduction (Tables 1 and 2 ). Control of transcription TGFβ regulated a wide array of transcription factors (Table 1 ), including the known TGFβ target JUNB . Other TGFβ targets in lung fibroblasts identified by this study included Smad co-activators RUNX1 and CBFB , recently implicated in the targeted subnuclear localization of TGFβ-regulated Smads [ 22 , 23 ]. Transcriptional regulators involved in cell cycle control/cell differentiation induced by TGFβ included FOXO1A , NPAS2 , and TIEG ( TGFβ-inducible early growth response ), while ZFP36L2 , a zinc finger transcription factor linked to cell proliferation induction, was repressed by TGFβ. Serum response factor ( SRF ) and MKL1 were also induced by TGFβ. Transcriptional repressors induced by TGFβ included Ski , which together with Sno interacts with Smad molecules to inhibit transcription and may contribute to terminating TGFβ response [ 24 ] and TCF8 , a previously reported TGFβ target in fetal lung fibroblasts [ 18 ]. Other transcriptional co-repressors upregulated by TGFβ were nuclear co-repressors NCOR2 (or SMRT ) and BHLHB2 , which repress transcription by recruiting histone deacetylases [ 25 ], and musculin ( MSC ). Cytoskeletal/Extracellular matrix organization Most genes in this category were known TGFβ targets. As expected, transcripts involved in promoting extracellular matrix formation and cell adhesion such as connective tissue growth factor ( CTGF ) were upregulated, while we observed inhibition of bone morphogenetic protein 4 ( BMP4 ), a member of the TGFβ superfamily whose activity has recently been shown to be inhibited by CTGF through direct binding [ 26 ]. TGFβ also induced matrix genes including elastin ( ELN ), collagens ( COL4A1 ), plasminogen activator inhibitor ( PAI1 or SERPINE1 ) and PLOD2 , an enzyme which stabilizes collagen cross-links (Table 2 ). Tissue inhibitor of matrix metalloproteinase 3 ( TIMP3 ) was upregulated by TGFβ. Genes involved in cytoskeletal organization induced by TGFβ included known target tropomyosin ( TPM1 ). Interestingly, smoothelin , a smooth muscle gene recently reported to be highly induced by TGFβ in fetal lung fibroblasts [ 18 ], was also induced by TGFβ in this study, but at a slightly lower fold ratio than that chosen for the selection criteria (1.8). Control of signal transduction Among signalling molecules (Table 2 ), known targets included upregulation of SMAD7 and downregulation of SMAD3 [ 18 , 16 ]. Novel targets in lung fibroblasts included SMURF2 , a recently identified E3 ubiquitin ligase, which negatively regulates TGFβ signalling by targeting both TGFβ receptor-Smad7 complexes and Smad2 for ubiquitin-dependent degradation [ 27 , 28 ]. At the investigated timepoint, TGFβ downregulated the accessory receptor betaglycan , a membrane anchored proteoglycan which increases the affinity between TGFβ and type I and II receptors. Interestingly, TGFβ upregulated activin A type I receptor , a receptor for TGFβ family member activin, whose stimulation induces fibroblast-mediated collagen gel contraction [ 29 ]. Members of the Ras family of GTPases, ARHB and RADD (Ras-related GTP-binding protein), involved in cytoskeleton remodelling, were also upregulated by TGFβ. TGFβ also induced Dickkopf1 ( DKK1 ), a potent inhibitor of Wnt/beta-catenin signalling. Of particular interest was the novel observation that TGFβ upregulated angiotensin II receptor 1 ( AGTR1 ) in lung fibroblasts; conversely, the gene encoding for vasodilatory peptide adrenomedullin ( ADM ) was inhibited by TGFβ. Validation of selected TGFβ-induced genes by real time RT-PCR Several of the genes regulated by TGFβ confirmed previously published findings, thus validating our methods, including JUN-B , SMAD7 , connective tissue growth factor , elastin , and SERPINE1 [ 17 , 18 , 16 , 30 ]. To further consolidate our analysis, we selected a small group of novel TGFβ targets to be confirmed by RT-PCR in both control and fibrotic lung fibroblasts. These novel fibroblast TGFβ-responsive genes included potential key candidates in the regulation by TGFβ of lung tissue fibrosis and included angiotensin II receptor type 1 ( AGTR1 ), SMURF2 , a gene involved in terminating TGFβ signalling, NCOR2 , a transcriptional co-repressor and BMP4 , a member of the TGFβ family. Compared to untreated samples, we confirmed that TGFβ upregulated AGTR1 (ratio = 2.4; p = 0.002), SMURF2 , (ratio = 1.8, p = 0.003), NCOR2 (ratio 1.4; p = 0.004), and downregulated BMP4 (ratio = 0.4; p = 0.009), with no difference in the response between control and fibrotic fibroblasts (Figure 1 ). Figure 1 Independent verification of microarray results by measurement of gene expression with real time-PCR . TGFβ treatment (4 ng/ml) for four hours induces expression of mRNA for angiotensin receptor 1 (panel a), nuclear receptor co-repressor 2 ( NCOR2 ) (panel c) and SMURF2 (panel d) as well as inhibition of bone morphogenetic protein 4 (panel b) in three control lung fibroblast cell lines (dashed lines) and three fibrotic lung fibroblasts (solid lines). Induction of angiotensin II receptor type 1 by TGFβ We focused on AGTR1 protein because, as shown by microarray analysis, it was the most highly TGFβ-induced gene among signaling molecules in both control and fibrotic fibroblasts (Table 2 ). To verify whether AGTR1 mRNA upregulation corresponded to an increase in protein levels, we performed Western analysis on primary human adult lung fibroblasts exposed to TGFβ or medium alone in serum-free conditions for 24 hours. The intensity of the angiotensin II receptor 1 immunoreactive band was significantly increased in TGFβ-treated fibroblasts compared to those treated with medium alone (2.4 fold; p < 0.001) (Figure 2 ). To identify the signalling pathways through which TGFβ induces AGTR1, we evaluated whether the ability of TGFβ to induce AGTR1 expression in lung fibroblasts was blocked by specific signaling pathway inhibitors. A 30 minute preincubation with the dual MKK1/MKK2 inhibitor U0126 significantly inhibited TGFβ induction of AGTR1 protein (p < 0.01), whereas predominant MKK1 inhibitor PD98059 and p38 MAPK inhibitor SB202190 had no significant effect (Figure 2 ). Figure 2 TGFβ treatment induces angiotensin II receptor 1 (AGTR1) protein expression in adult lung fibroblasts; the induction is mediated by MKK1/MKK2 . Representative Western Blot (top) and average values (± SD) of angiotensin II receptor type 1 protein expression in lung fibroblasts treated with TGFβ (4 ng/ml)with or without 1/2 hour pre-incubation with of one the following signalling inhibitors: U0126, PD98059, SB202190. A 24 hour treatment with TGFβ induced an upregulation of AGTR1 protein (mean: 2.4 fold, *p < 0.001, Student's paired t-test). The induction of AGTR1 by TGFβ was specifically blocked by MKK1/MKK2 inhibitor U1026 (p < 0.01 compared with TGFβ-induced AGTR1, Student's paired t-test), but not by predominant MKK1 inhibitor PD98059 or p38 inhibitor SB202190). The results are representative of three independent experiments on both control and fibrotic cell lines. As a loading control, Western analysis with an anti-GAPDH antibody was also performed. AGTR1 expression in idiopathic pulmonary fibrosis lung biopsies We assessed staining for AGTR1 in lung biopsies from four patients with idiopathic pulmonary fibrosis and compared it to that of three control lungs. In particular we aimed to evaluate AGTR1 staining in fibroblastic foci, aggregates of fibroblasts/myofibroblasts in close contact with alveolar epithelial cells. Both in control and in idiopathic pulmonary fibrosis lung biopsies, AGTR1 immunoreactivity was observed in alveolar epithelial cells and alveolar macrophages. In addition, the fibroblasts within the fibroblastic foci present in idiopathic pulmonary fibrosis biopsies stained positive for the receptor (Figure 3 ). Figure 3 Angiotensin II receptor 1 staining in lung biopsies from control patients (A) and from patients with idiopathic pulmonary fibrosis (B) . Immunohistochemistry for the angiotensin II receptor 1 (AGTR1), counterstained with haematoxylin. AGTR1 positive staining is seen in alveolar macrophages, in epithelial cells and in fibroblastic foci (arrows) in usual interstitial pneumonia biopsies (panel B). Epithelial cells and alveolar macrophages express AGTR1 in control lung biopsies (panel A). Discussion In this study we report, for the first time, the transcriptional profile in response to TGFβ in adult primary human lung fibroblasts both from control and from fibrotic lungs. Our analysis of the response to TGFβ focused on TGFβ gene targets involved in transcription and signalling, identifying a series of genes previously unknown to respond to TGFβ in lung fibroblasts. These included angiotensin II receptor 1, providing further insights into links between TGFβ and angiotensin in the pathogenesis of fibrosis [ 31 , 32 ]. Although gene expression profiling in response to TGFβ has been investigated previously, earlier work has been confined to skin fibroblasts [ 17 ], keratinocytes [ 16 ], and a human fetal lung cell line [ 18 ], which is likely to respond differently to TGFβ from the adult lung fibroblast. Our data cannot be directly compared with the fetal lung fibroblast profiling because of methodological disparities, chiefly due to differences in the timing of the RNA collection. However, even restricting the comparison to results obtained at similar time points, we found a significant dissimilarity. Among transcription factors, only JUNB and TCF8 were upregulated by TGFβ both in fetal [ 18 ] and in adult lung fibroblasts, while all others differed between the two cell types. Interestingly, in this study, TGFβ caused an induction of both MKL1 and serum response factor , while neither were upregulated in fetal lung fibroblasts. The recently reported cooperation between these two transcription factors in determining smooth muscle cell differentiation [ 33 ] suggests that they may play a similar role in lung fibroblasts and suggests differences between fetal and adult lung fibroblasts in the transcriptional programs involved in the TGFβ-induced acquisition of the myofibroblastic phenotype. In this study, we did not observe a substantial difference in the response to TGFβ between lung fibroblasts from two patterns of fibrotic lung disease and control lung fibroblasts. In vivo heterogeneity between interstitial lung fibroblasts may occur in fibrotic and normal lung, obscuring the demarcation between normal and abnormal phenotypes, when cell lines are isolated using standard techniques [ 34 , 35 ]. This may explain discrepancies among studies on growth rate and resistance to apoptosis in fibroblasts derived from fibrotic lungs [ 34 , 36 ]. In particular, the fibroblasts/myofibroblasts forming the fibroblastic foci, observed to be linked to disease progression [ 37 ], could differ from the remaining fibroblasts found in the interstitium. The issue of sampling a population of homogeneous lung fibroblasts will be the subject of further investigation by using laser microdissection techniques targeting fibroblastic foci coupled with new technologies to amplify RNA from limited quantities of tissue [ 38 ]. Further, it is possible that the absence of striking differences in the response to TGFβ between disease groups and controls is due to a loss of the pro-fibrotic phenotype in vitro, even though the gene expression patterns of different passages of the same fibroblast line have been observed to cluster together, indicating that the in vitro phenotypes are stable through several passages in culture [ 19 ]. Further, we ensured that RNA was extracted from all fibroblast lines at comparable passages. Thus, even though our study cannot exclude the presence of subtle differences in the response to TGFβ, we have observed that, overall, fibrotic lung fibroblasts retain the capacity to respond to TGFβ, which could therefore be targeted by pharmacological means. Among the novel TGFβ targets identified by microarray analysis in lung fibroblasts, we focused our attention on the induction of angiotensin II receptor type 1 ( AGTR1 ), as its involvement is likely to significantly amplify the pro-fibrotic actions of TGFβ. The ligand for this receptor is angiotensin II, a vasoactive peptide which has been linked to fibrogenesis in the kidney and in the heart [ 39 , 40 ]. Recent studies have indicated that a local renin-angiotensin system could also be involved in the development of lung fibrosis [ 41 , 42 ]. Elevated angiotensin converting enzyme levels have been found in bronchoalveolar lavage (BAL) fluid from patients with idiopathic pulmonary fibrosis [ 41 ]. Compared to controls, lung fibroblasts from patients with idiopathic pulmonary fibrosis produce higher levels of angiotensin II, shown to induce apoptosis in alveolar epithelial cells through AGTR1 [ 31 , 43 ]. Blockade of angiotensin II or of AGTR1 attenuates lung collagen deposition in animal models of lung fibrosis [ 42 , 32 ]. Interestingly, the modulation of AGTR1 could be cell specific, as suggested by the report that TGFβ reduces AGTR1 expression in cardiac fibroblasts [ 44 ]. In addition to Smad molecules, the classic signalling pathway used by TGFβ family members, TGFβ also signals through the mitogen-activated protein kinase (MAPK) signalling pathways [ 16 ]. In this study, TGFβ was found to induce AGTR1 via mitogen-activated protein kinase kinase (MKK1/MKK2). The finding that the MKK1/MKK2 inhibitor U0126, but not the MKK1 inhibitor PD98059, was able to suppress TGFβ-induced AGTR1 expression, suggests that both MKK1 and MKK2 must be antagonized in order to inhibit transcription. The functional effects of AGTR1 stimulation in lung fibroblasts are only partially known. Although two isoforms of angiotensin II receptor exist, AGTR1 and AGTR2, the effects described so far of angiotensin II on lung fibroblasts are ascribed to the type 1 receptor. AGTR1 has been found to mediate mitogenesis in human lung fibroblasts [ 45 ] and extracellular matrix synthesis in lung [ 46 ] as well as in cardiac and dermal fibroblasts [ 47 ]. Whereas angiotensin II is known to induce TGFβ [ 46 ], the regulation of AGTR1 by TGFβ has not, to our knowledge, been previously reported in lung fibroblasts. Our data support the concept of a positive feed back loop by which TGFβ potentiates the pro-fibrotic actions of angiotensin II by increasing AGTR1 expression, providing a mechanism for the attenuation of the proliferative response to angiotensin II by TGFβ blockade [ 45 ]. Thus, cooperation and amplification of pro-fibrotic effects between TGFβ and AGTR1 are likely to be implicated in lung fibrosis. Interestingly, adrenomedullin, a multifunctional vasodilatory peptide that downregulates angiotensin II-induced collagen biosynthesis in cardiac fibroblasts [ 48 ], was inhibited by TGFβ, confirming a previous report [ 49 ], and suggesting that TGFβ exerts a complex regulation over vasoactive peptides and/or their receptors in lung fibroblasts. AGTR1 was found to localize to fibroblasts within fibroblastic foci in IPF/UIP biopsies. An increase in AGTR1 staining has been reported in the fibrotic regions surrounding the bronchioles in chronic obstructive pulmonary disease [ 50 ]. The finding that AGTR1 localizes to fibroblastic foci in IPF biopsies supports the potential relevance of the angiotensin system in this disease and suggests that the pro-fibrotic role of AGTR1 in IPF is not limited to epithelial cells [ 31 ]. Further studies are needed to assess the functional effects of AGTR1 stimulation in lung fibroblasts and to evaluate the biological role of AGTR1 in lung fibrosis. Conclusions Our findings confirm that in response to TGFβ, both control and fibrotic lung fibroblasts are potent effector cells expressing a very wide range of genes that are likely to contribute to the fibrotic process. In particular, we have shown that TGFβ has the capacity to influence the expression of angiotensin II receptor type 1 both at the mRNA and at the protein level. In view of the known induction of TGFβ by angiotensin II [ 45 ], our findings support the existence of a self-potentiating loop between TGFβ and angiotensin II, resulting in the amplification of the pro-fibrotic effects of both systems. Future treatment strategies could be based on the disruption of such interactions. Authors' contributions EAR participated in the design and interpretation of the study, carried out the cell culture work and participated in the microarray work, performed immunohistochemistry staining, and drafted the manuscript. DJA participated in the design and coordination of the study and in the preparation of the manuscript, SH performed the RT-PCR assays, XSW carried out the Western Blot analysis, PS performed the statistical analysis and participated in the interpretation of results and preparation of the manuscript, GBG participated in the microarray work, AUW participated in the interpretation of results, SV participated in cell line selection and clinical characterization, AGN reviewed fibrotic lung biopsies and interpreted immunohistochemistry staining, CD and CMB contributed towards the overall organizational setup for the study of lung fibroblast lines and participated in the interpretation of results, AL and JDP participated in the preparation of the manuscript, KIW conceived of the study and participated in the design, RdB participated in study design, interpretation and coordination. All authors read and approved the final manuscript. Supplementary Material Additional File 1 Complete list of genes regulated by a four hour treatment with TGFβ in control and fibrotic fibroblasts This data set contains all the genes up- or down-regulated by a four hour treatment with TGFβ (according to the criteria described in the methods) in control and fibrotic lung fibroblasts. Fibrotic lung fibroblast fold ratios are the average of the fold ratios for lung fibroblasts from idiopathic pulmonary fibrosis and pulmonary fibrosis associated with systemic sclerosis. Genes are sub-grouped into functional classes. Affymetrix probe set numbers, approved gene symbols, gene names and GenBank accession numbers are provided in the table. Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC538264.xml
517495	Molecular clock in neutral protein evolution	Background A frequent observation in molecular evolution is that amino-acid substitution rates show an index of dispersion (that is, ratio of variance to mean) substantially larger than one. This observation has been termed the overdispersed molecular clock. On the basis of in silico protein-evolution experiments, Bastolla and coworkers recently proposed an explanation for this observation: Proteins drift in neutral space, and can temporarily get trapped in regions of substantially reduced neutrality. In these regions, substitution rates are suppressed, which results in an overall substitution process that is not Poissonian. However, the simulation method of Bastolla et al. is representative only for cases in which the product of mutation rate μ and population size N e is small. How the substitution process behaves when μN e is large is not known. Results Here, I study the behavior of the molecular clock in in silico protein evolution as a function of mutation rate and population size. I find that the index of dispersion decays with increasing μN e , and approaches 1 for large μN e . This observation can be explained with the selective pressure for mutational robustness, which is effective when μN e is large. This pressure keeps the population out of low-neutrality traps, and thus steadies the ticking of the molecular clock. Conclusions The molecular clock in neutral protein evolution can fall into two distinct regimes, a strongly overdispersed one for small μN e , and a mostly Poissonian one for large μN e . The former is relevant for the majority of organisms in the plant and animal kingdom, and the latter may be relevant for RNA viruses.	Background Kimura has argued that the majority of nucleotide substitutions that accumulate in genes over time are selectively neutral, and go to fixation purely by chance [ 1 ]. One major prediction of Kimura's neutral theory is that the substitution process should be a Poisson process, with the mean number of substitutions per unit time equal to the variance. In contrast to this theory, empirical studies often find the variance to be significantly larger than the mean [ 2 - 8 ]. This observation has been termed the "overdispersed molecular clock". (For an excellent review of both empirical evidence and mathematical theories, see Ref. [ 9 ].) It is possible to reconcile Kimura's theory with the overdispersed molecular clock via Takahata's fluctuating neutral space model [ 10 - 12 ]. If the neutral mutation rate fluctuates slowly, then the substitution process ceases to be Poissonian, and becomes indeed overdispersed. However, the problem with the fluctuating neutral space model is that it does not offer any argument for why the neutral mutation rate should fluctuate, and thus ultimately fails to explain the observed substitution patterns. An explanation for fluctuations in neutral mutation rate was recently proposed by Bastolla et al. [ 13 - 16 ]. Different proteins with identical structure naturally vary in their neutrality, that is, in the fraction of single-point mutants that are viable. Therefore, as a gene slowly drifts through sequence space, the neutral mutation rate will fluctuate in correlation to the changing neutrality, and this fluctuation alone could be sufficient to explain the overdispersed molecular clock. Bastolla et al. studied the substitution process in a variety of models of neutral protein evolution in silico , and found significant overdispersion in all cases they considered. However, the simulations that Bastolla et al. carried out were limited to cases in which the product of mutation rate μ and population size N e is small (because Bastolla et al. used only a single sequence as the representative of the whole population, an approach that is justified for μN e ≲ 1). Since population size and mutation rate can be substantial in some species (most notably in RNA viruses), it is justified to ask how general this result is for arbitrary values of μN e . It is known that large populations and populations evolving under high mutation pressure experience a strong selective pressure to avoid regions of low neutrality, an effect that has been termed "evolution of mutational robustness" [ 17 - 20 ]. In equilibrium, such populations settle in areas of sequence space that have above-average neutrality. As a result, regions of low neutrality are not represented in the population, and the distribution of neutralities in the population is much narrower than the total distribution of neutralities in sequence space. Therefore, we should expect that the neutral mutation rate does not fluctuate strongly under these conditions, and that the molecular clock will not be significantly overdispersed. For the present paper, I have studied the behavior of the substitution process under neutral protein evolution as a function of mutation rate μ and population size N e . I have found that the accumulation of non-synonymous mutations is substantially overdispersed for small μN e , in agreement with the results of Bastolla et al., but approaches a Poisson process when μN e ≫ 1. The accumulation of synonymous substitutions is always Poissonian, regardless of the value of μN e . Results I carried out simulations with DNA sequences of length L = 75. I determined the fitness of a DNA sequence by translating it into the corresponding amino-acid sequence, and determining its native fold within the framework of a lattice-protein model. (A sequence would have fitness 1 if it folded into a pre-determined target structure, and fitness 0 otherwise.) I used a simple model of maximally compact proteins on a 5 × 5 lattice. This protein-folding model is much simpler than the ones used by Bastolla et al. [ 13 , 14 ], but has been shown to produce realistic distributions of folding free energies and neutralities [ 21 - 23 ]. The advantage of the simpler model is that entire populations of evolving sequences can be simulated, instead of just individual sequences. First, I have found that my model produces overdispersion (that is, an index of dispersion R substantially above 1) for non-synonymous substitutions, but not for synonymous substitutions. The finding for synonymous mutations is not surprising, because changes in the protein's neutrality do not affect the probability with which a synonymous mutation is neutral (which is always one). Neutral evolution could produce overdispersion in the synonymous substitutions only if the number of synonymous sites in the sequence were undergoing significant fluctuations. While these fluctuations do occur, they are apparently not large enough to affect the index of dispersion. Second, I have found that for non-synonymous substitutions, R decays quickly with increasing population size N e at fixed μ (Fig. 1 ). Since one reason for a decaying index of dispersion could be a reduced number of accumulated mutations, I have studied how the mean number of accumulated mutations behaves as a function of population size. Instead of staying constant or decreasing, the mean increases with increasing N e , while the variance decreases (Fig. 2 ). This result shows that the reduction in R is not caused by a mere reduction in the accumulated mutations, and that the substitution process does indeed shift from overdispersed to Poissonian as the population size increases. Figure 1 Index of dispersion as a function of population size N e for synonymous and non-synonymous substitutions ( τ = 1000, μ = 0.075). Figure 2 Mean, and variance, of lineage-adjusted number of non-synonymous substitutions as a function of population size N e ( τ = 1000, μ = 0.075). Quantities were calculated from all 500 replicates at each population size. For non-synonymous substitutions, R decays with N e because of evolution of mutational robustness. However, mutational robustness is caused by large μN e , rather than large N e alone, and the parameter region in which mutational robustness becomes relevant is μN e ≳ 10 [ 17 ]. Therefore, it is more instructive to plot R as a function of μN e . The only problem with a naive plot of that sort is that R increases as a function of μτ , where τ is the length of the time window during which mutations accumulate [ 9 ]. Thus, in Fig. 3 , I show R for constant μτ as a function of μN e . Note that in this figure, instead of the sequence-wide mutation rate μ , I use the non-synonymous mutation rate μ n = 0.76 μ , which is corrected for the fact that only approximately 76% of mutations hit non-synonymous sites. (76% is the expected fraction of non-synonymous sites in a random DNA sequence.) Figure 3 shows that the transition from an overdispersed to a Poissonian substitution process occurs for μN e between approximately 10 and 100, in agreement with Ref. [ 17 ], and that the transition region seems to be largely independent of the value of μτ . Figure 3 Index of dispersion for non-synonymous mutations as a function of the product of non-synonymous mutation rate μ n (= 0.76 μ ) and population size N e . Figure 3 also shows that R increases with μτ . This dependency becomes clearer in Fig. 4 , where I display R as a function of μτ for fixed μN e . The figure shows substantial increase in R with increasing μτ for small to moderate μN e . However, even for μN e well above 50, there is still a slight increase in R with μτ . Therefore, my results do not settle the question of whether the substitution process becomes truly Poissonian for sufficiently large μN e , or whether it just approaches a Poisson process but always remains slightly overdispersed. To settle this question, one would have to carry out simulations with much larger τ and N e . Unfortunately, the protein folding model I use is still too computationally intensive to permit such simulations with current computational resources. Figure 4 Index of dispersion for non-synonymous mutations as a function of the product of non-synonymous mutation rate μ n (= 0.76 μ ) and divergence time τ . Discussion My results show that the size of the product μN e has a substantial effect on the index of dispersion under neutral evolution. The substitution process is strongly overdispersed for small μN e, but approaches a Poisson process as μN e grows large. Therefore, the next question is which of the two regimes has more biological relevance. As discussed by Cutler [ 9 ], the biggest problem in explaining the overdispersed molecular clock is not to come up with mechanisms that produce overdispersion, but to find a general mechanism that does not depend on special conditions or finely-tuned parameters. To assess the likelihood that fluctuations in neutrality contribute to the overdispersed molecular clock, we have to know the mutation rate and population size for the species of interest. It is notoriously difficult to obtain accurate data for these parameters, and only a few species have been studied in depth. One of the best data sets available is probably the one for Drosophila . Keightley and Eyre-Walker estimated the per-nucleotide substitution rate in Drosophila to be u = 2.2 × 10 -9 [ 24 ]. If we assume that the average gene in Drosophila is 1770 bp long [ 24 ], and that 76% of the nucleotides are non-synonymous (this number stems from averaging the number of non-synonymous sites over all codons with equal weight), then the average number of non-synonymous sites per gene is 1345 bp. Thus, the average rate of non-synonymous mutations per gene is μ n = 3.0 × 10 -6 . With an effective population size of approximately 3 × 10 5 [ 25 ], we get a product of population size and per-gene-non-synonymous mutation rate of approximately 1. Since selection for mutational robustness starts to take effect when this product is substantially larger than 1, Drosophila lies well within the parameter region in which we expect overdispersion to be caused by neutral evolution. For other higher organisms, in particular mammals, which tend to have comparatively small population sizes, we can expect that the product μ n N e falls into the same parameter region. On the other hand, for microorganisms, which can have very large population sizes, mutational robustness may play a role in their evolution. In particular, RNA viruses have genomic mutation rates on the order of one [ 26 , 27 ] and their genomes consist typically of only a handful of genes. Because RNA viruses undergo severe bottlenecks on a regular basis, their effective population size N e is much smaller than the number of virus particles in infected individuals (which can exceed 10 12 ), and is more closely related to the number of infected individuals. For HIV-1, N e has been estimated to be approximately 10 2 for subtype A, and 10 5 for subtype B [ 28 ]. The preceeding paragraph shows that neutral evolution of proteins is probably one source of overdispersed non-synonymous substitutions in Drosophila and other organisms. However, overdispersion has been observed in synonymous substitutions as well. For example, Zeng et al. [ 29 ] found an index of dispersion R significantly above one for synonymous, but not for non-synonymous substitutions in Drosophila . For mammals, some studies found R significantly above one for both synonymous and non-synonymous substitutions [ 8 ], while others found only the non-synonymous substitution process to be overdispersed [ 30 ]. Therefore, it is likely that other processes than neutral protein evolution also contribute to overdispersion. Such processes can be selection for optimal codon usage in the case of synonymous mutations, and positive selection on the amino acid level in the case of non-synonymous mutations. I have demonstrated that large μN e results in a substitution process with little overdispersion. However, I have not yet given an explanation for how overdispersion is reduced in populations with large μN e . There are two elements: First, selection for mutational robustness reduces the fraction of sequences with low neutrality, and increases the fraction of sequences with high neutrality, thus making the population more homogeneous and reducing the overall range of neutralities [ 17 - 20 ]. Second, a sequence with low neutrality will experience a real selective disadvantage in comparison to a sequence with high neutrality for large μN e , and will therefore have a reduced probability to end up on the line of descent. While this selective disadvantage is often small, it can nevertheless determine the evolutionary fate of a sequence in a large population. The larger the population, the more sensitive it becomes to small fitness differences, so that in a very large population a sequence with only a moderate reduction in neutrality will have a small probability to end up on the line of descent. (The fact that the mean substitution rate increases with the population size, as seen in Fig. 2 , is also consistent with this reasoning. The larger the population size, the more high-neutrality sequences end up on the line of descent, which is reflected in the increase in the mean substitution rate.) Throughout this paper, I have considered only neutral or lethal mutations. It is a reasonable question to ask if and how deleterious mutations would change my results. The answer is that they probably have only a minor impact, and the less so the larger N e , unless they are very slightly deleterious. In order to affect the molecular clock, the deleterious mutations must end up on the line of descent, that is, they must go to fixation. The probability of fixation p fix of deleterious mutants drops exponentially with the population size, p fix = [1 - exp(2 s )]/ [1 - exp(2 sN e )], where s is the selective disadvantage of the deleterious mutation [ 31 ]. Therefore, for reasonable population sizes, only very slightly deleterious mutations can go to fixation and thus affect the molecular clock. This reasoning is independent of the size of μN e , as long as N e is large in comparison to s . Conclusions The present study supports the following conclusions: • Neutral drift of proteins can lead to an overdispersed substitution process for non-synonymous mutations, but not for synonymous mutations. • The amount of overdispersion in the non-synonymous substitution process depends strongly on the product of mutation rate and population size. As this product increases, the substitution process becomes more and more Poissonian. The transition region starts at μN e ≈ 10, and extends to values well above 100. • It is not clear whether there are any species that have a sufficiently large population size and mutation rate to prevent overdispersion through neutral drift. In Drosophila , the product of mutation rate and population size is close to one, which is well below the parameter region in which the substitution process turns Poissonian. Methods Lattice protein model I implemented a version of the 5 × 5 lattice protein model put forward by Goldstein and coworkers [ 21 - 23 , 32 ]. In this model, proteins are sequences of n = 25 residues that fold into a maximally compact structure on a two-dimensional grid of 5 × 5 lattice points. There are 1081 distinct possible conformations in this model, and the partition function can be evaluated exactly by summing over the contact energies of all distinct conformations. The contact energy of a conformation i is where is the contact energy between amino acids at location j and at location k in the sequence, and is 1 if the two amino acids are in contact in conformation k , and 0 otherwise. The partition function is where the sum runs over all 1081 conformations. A sequence folds into conformation f if the contact energy for that conformation is lower than the contact energies of all other formations, E f < E i for all i ≠ f , and if the free energy of folding, which is defined as is smaller than some cutoff Δ G cut . Throughout this study, I used kT = 0.6 and Δ G cut = 0. The contact energies where taken from Table VI in Ref. [ 33 ]. Sequence evolution I simulated the evolution of populations of DNA sequences in discrete, non-overlapping generations. Population size is denoted by N e . The fitness of a sequence was 1 if the DNA sequence translated into a peptide sequence that could fold into a chosen target structure, and had a free energy of folding smaller than G cut . Otherwise, the fitness of the sequence was 0. All sequences had length L = 75. In each successive generation, sequences with fitness 1 were randomly chosen to reproduce, until the new generation had N e members. At reproduction, the sequences were mutated, with an average of μ base pair substitutions per sequence. I let each population evolve for several thousand generations, and kept track of the full genealogic information of all sequences in the population. In order to measure the molecular clock of fixed mutations only, I studied the pattern of base substitutions in a window of τ generations along the line of descent backwards in time, starting from the most recent common ancestor of the final population. I varied the parameters N e (10, 33, 100, 330, 1000, 3300), μ (0.0075, 0.075, 0.75), and τ (500, 1000). For each set of parameters, I carried out 500 replicates (each with a different, randomly chosen target structure), to obtain a distribution for the number of synonymous and non-synonymous substitutions S d and N d . Since there was some variation in the number of synonymous and non-synonymous sites across different target structures (on the order of approximately ± 5% variation from the mean), I then applied a correction factor to S d and N d to bring them into comparable units: I calculated the corrected number of synonymous substitutions as Here, S is the mean number of synonymous sites for the given replicate, and ( S ) is the average of S over all 500 replicates. Likewise, I calculated (Indices of dispersion calculated without this correction factor are slightly larger than the ones reported here, because the variation in S and N creates additional variance in S d and N d ). Similar correction factors have been used in sequence analysis [ 7 ], and are generally referred to as lineage adjustments. They control for differences among lineages that are primarily related to the expected number of substitutions in a lineage, and thus should not enter the index of dispersion. To obtain an estimate for mean and standard error of the index of dispersion, I subdivided the 500 results into 10 blocks of 50 each, and calculated mean and variance of the number of substitutions for each block. The ratio of variance to mean for a given set of substitutions (synonymous or non-synonymous) in a block is the index of dispersion for this data set. I then calculated mean and standard error for the index of dispersion from the individual results of the 10 blocks. The total CPU time needed to carry out all simulations was several months on a small cluster of Pentium II 500 MHz machines. Calculation of synonymous and non-synonymous substitutions and sites I calculated the number of synonymous and non-synonymous sites S and N and the number of synonymous and non-synonymous substitutions S d and N d according to the method proposed by Nei and Gojobori [ 34 ]. In short, under this method the number of synonymous sites s i of a codon i is the fraction of possible substitutions to that codon that leave the residue unchanged. The number of non-synonymous sites n i for the same codon is n i = 3 - s i . For the complete sequence, S and N are calculated as and where i runs over all codons in the sequence. The number of synonymous or non-synonymous substitutions s d, i or n d, i between two codons is the average number of such substitutions, where the average is taken over all paths that lead from one codon to the other. The total number of synonymous or non-synonymous substitutions between two sequences is the sum over all individual constributions, and (again, i runs over all codons in the sequence). To calculate the number of synonymous or non-synonymous substitutions along the line of descent, I simply summed up all synonymous or non-synonymous substitutions that occurred from generation to generation. Because the full evolutionary history was known, a correction for multiple mutations such as the Jukes-Cantor correction [ 35 ] was not necessary. I also averaged the number of synonymous and non-synonymous sites over all sequences along the line of descent, to get the mean number of synonymous and non-synonymous sites for the given evolutionary trajectory. Authors' contributions COW carried out all aspects of this study.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC517495.xml
550655	The PECACE domain: a new family of enzymes with potential peptidoglycan cleavage activity in Gram-positive bacteria	Background The metabolism of bacterial peptidoglycan is a dynamic process, synthases and cleavage enzymes are functionally coordinated. Lytic Transglycosylase enzymes (LT) are part of multienzyme complexes which regulate bacterial division and elongation. LTs are also involved in peptidoglycan turnover and in macromolecular transport systems. Despite their central importance, no LTs have been identified in the human pathogen Streptococcus pneumoniae . We report the identification of the first putative LT enzyme in S. pneumoniae and discuss its role in pneumococcal peptidoglycan metabolism. Results Homology searches of the pneumococcal genome allowed the identification of a new domain putatively involved in peptidoglycan cleavage (PECACE, PE ptidoglycan CA rbohydrate C leavage E nzyme). This sequence has been found exclusively in Gram-positive bacteria and gene clusters containing pecace are conserved among Streptococcal species. The PECACE domain is, in some instances, found in association with other domains known to catalyze peptidoglycan hydrolysis. Conclusions A new domain, PECACE, putatively involved in peptidoglycan hydrolysis has been identified in S. pneumoniae . The probable enzymatic activity deduced from the detailed analysis of the amino acid sequence suggests that the PECACE domain may proceed through a LT-type or goose lyzosyme-type cleavage mechanism. The PECACE function may differ largely from the other hydrolases already identified in the pneumococcus: LytA, LytB, LytC, CBPD and PcsB. The multimodular architecture of proteins containing the PECACE domain is another example of the many activities harbored by peptidoglycan hydrolases, which is probably required for the regulation of peptidoglycan metabolism. The release of new bacterial genomes sequences will probably add new members to the five groups identified so far in this work, and new groups could also emerge. Conversely, the functional characterization of the unknown domains mentioned in this work can now become easier, since bacterial peptidoglycan is proposed to be the substrate.	Background The bacterial cell wall resists intracellular pressure and gives the bacterium its particular shape. Cell wall reinforcement is brought about by a strong scaffolding structure, the peptidoglycan, which is formed by glycan strands and peptide chains held together by covalent bonds, resulting in a mono- or multilayered network. The glycan strands are composed of N -acetylglucosamine (Glc N Ac) and N -acetylmuramyl (Mur N Ac) residues linked together by β-1,4 glycosidic bonds. Peptides are covalently attached to the lactyl group of the muramic acid and their cross-linking results in the net structure of the peptidoglycan (Fig. 1a ). Figure 1 Schematic representation of peptidoglycan and of cleavage enzymes in S. pneumoniae . (a) Scheme of the pneumococcal peptidoglycan, indicating the chemical bonds cleaved by identified hydrolases in blue. The Mur N Ac residue containing the 1, 6-anhydro bond resulting from LT reaction is in a green circle. The putative LT pneumococcal enzyme appears in red, while enzymes CBPD and PcsB for which no enzymatic specificity is yet characterized are in black. (b) Topological representation of the glycan strand hydrolases described in S. pneumoniae . Black and hatched boxes indicate the signal peptide and the transmembrane anchor, respectively. The blue boxes illustrate the respective enzymatic active domains. Purple rectangles correspond to the Choline-Binding repeats. Green and orange boxes correspond to SH3b and coiled-coil regions, respectively. The topology was designed with the help of SMART server [39]. Peptidoglycan is synthesized in a multi-stage process. The first steps occur in the cytoplasm, where a set of enzymatic reactions gives rise to the assembly of the Mur N Ac-pentapeptide. This unit is in turn linked to the carrier undecaprenol lipid via a pyrophosphate group; afterwards the Glc N Ac group is added, generating the lipid II precursor. The saccharidic and peptidic moieties of lipid II are subsequently exposed to the periplasmic space. At this stage, peptidoglycan biosynthesis involves polymerization of the glycan chains, catalyzed by glycosyltransferases [ 1 ] as well as interpeptide bridge formation performed by transpeptidases [ 2 ]. These two enzymatic reactions are resident on the extracellular domains of Penicillin-Binding Proteins (PBPs) which are membrane-associated molecules, present in all eubacteria [ 2 ]. Peptidoglycan metabolism is a dynamic process since this structure grows and divides in perfect synchronization with cell growth and division. Furthermore, it is well established that peptidoglycan is subject to maturation, turnover and recycling in Gram-negative bacteria [ 3 ]. To fullfil these processes, it is expected that peptidoglycan cleavage enzymes must exert their functions in coordinated action with PBPs. Indeed, a large range of different peptidoglycan hydrolases have been identified in numerous bacterial species and specific peptidoglycan hydrolases exist for almost each covalent bond [ 3 ] (Fig. 1a ). The polysaccharidic component of peptidoglycan is the target of several hydrolases: the β-1,4 glycosidic bond between Mur N Ac and Glc N Ac residues is cleaved by lyzosyme and by lytic transglycosylases (LT), the β-1,4 glycosidic bond between Glc N Ac and Mur N Ac is hydrolyzed by glucosaminidases and amidases are responsible for the cleavage of the Mur N Ac-L-alanine bond (Fig. 1a ). Lyzosyme and LT enzymes cleave the same β-1,4-Mur N Ac-GlcNAc bond but generate different reaction products: while lyzosymes catalyze a hydrolytic reaction, LTs cleave the β-glycosidic linkage with the concomitant formation of 1,6-anhydromuramyl residues, blocking the reducing end of the glycan strands. The significance of the ring structure is not known but it has been speculated that the bond energy may be utilized for glycan strand rearrangements. In addition, the 1,6-anhydro ring may also be considered as a specific product of peptidoglycan turnover. Despite the lack of understanding of the physiological function of anhydromuropeptide product, LT enzymes must play a significant cellular role. Indeed, it has been observed that deletions of genes encoding LT proteins lead to E. coli and Neisseria meningitidis with altered cell separation phenotypes, indicating that LTs cleave septal peptidoglycan [ 4 , 5 ]. Macromolecular transport systems (secretion types II, III, IV and IV pilus synthesis) of Gram-negative bacteria contain LT enzymes, suggesting that peptidoglycan hole formation (essential for transport functions) is specifically performed by this enzyme family [ 6 ]. As mentioned above, the enlargement of the bacterial stress-bearing peptidoglycan structure requires the well coordinated action of synthases (PBPs) and hydrolase enzymes. The "three-for-one" growth mechanism described by Höltje proposes that a triplet of glycan strands cross-linked to each other (resulting from PBPs synthesis) is attached to the peptidoglycan layer. Subsequently, the docking strand is removed by hydrolases resulting in the insertion of the peptidoglycan triplet. The hydrolases involved in such multienzyme complexes are endopeptidases and LT enzymes [ 3 ]. This hypothesis is supported by experimental data as LT and PBPs could be co-purified from E. coli extracts [ 7 - 9 ]. In conclusion, LT enzymes play an important cellular role in diverse aspects of cell biology as expected from their presence in a very wide range of eubacteria as well as archaebacteria [ 3 , 10 , 11 ]. Surprinsingly, no such LT enzyme has been identified to date in the human pathogen Streptococcus pneumoniae , the causative agent of ear infections in children, as well as meningitis and pneumonia. The pattern of peptidoglycan hydrolases in this Gram-positive bacteria includes, besides a D, D-carboxypeptidase, five glycan strand cleaving enzymes (Fig 1b ). Four of these are surface-exposed proteins harboring Choline-Binding Domains which are non-covalently bound to choline residues present on cell wall pneumococcal teichoic and lipoteichoic acids [ 12 - 14 ]. The Choline-Binding Proteins (CBPs) catalyzing peptidoglycan hydrolysis are LytA, LytB, LytC and potentially CBPD (Fig 1b ). LytA is an amidase and also appears as an autolytic enzyme, causing bacteriolysis when acting in an uncontrolled manner [ 15 ]. LytB is a glucosaminidase involved in cell separation as lytB mutants form very long chains of over 100 cells [ 16 ]. LytC is a lysozyme with an autolytic behavior at 30°C [ 17 ]. Finally, CBPD and PcsB contain a CHAP domain (Cysteine, Histidine-dependent amidohydrolase/peptidase) predicted to hydrolyse the peptidoglycan in pneumococcus, but definitive biochemical data are still lacking [ 18 - 20 ]. Our interest in the biology of S. pneumoniae led us to investigate the presence of LT enzymes in this bacteria. Homology searches of enzyme sequences within the pneumococcus genome using bioinformatics tools allowed the identification of a new domain harboring motifs that infer potential peptidoglycan cleavage activity. For this reason we named this domain PECACE ( PE ptidoglycan CA rbohydrate C leavage E nzyme). This domain sequence was found exclusively in Gram-positive bacterial species, suggesting a significant cellular role. Finally, the PECACE domain is in some instances found in association with other domains, known to catalyze peptidoglycan hydrolysis: this observation reinforces the predicted function of PECACE as participating in peptidoglycan cleavage and represents another example of multifunctional proteins involved in peptidoglycan metabolism. Results and discussion Identification of a protein harboring the PECACE domain in S. pneumoniae The C-terminal domain of Escherichia coli Slt70 (Soluble Lytic Transglycosylase) has a lysozyme-like fold and its amino acid sequence was employed in a search of Bacilli genomes within the NCBI Conserved Domain Search server [ 11 , 21 - 23 ]. Thirty-four Slt70-homologue sequences were retrieved using an inclusion threshold of 0.01. None of these sequence originated from the S. pneumoniae translated genome. Subsequently, each of these 34 sequences was compared with the non-redundant protein database using PSI-BLAST with a E-value threshold of 0.005 and 5 sequences showed significant matches with a unique protein in S. pneumoniae . This sequence (accession numbers NP358524, gi:15902974) contains 204 amino acids: the first 21 amino acids are predicted to form a transmembrane anchor and the subsequent 192-residue region is putatively exposed to the extracellular space (Fig. 1b ). This S. pneumoniae NP358524 sequence has been tested as a pneumococcal vaccine antigen on the basis of preliminary screens for novel vaccine candidates [ 24 ]. A three-dimensional fold prediction of the S. pneumoniae NP358524 protein was performed with the 3D-PSSM server [ 25 ] which identified two matches: E. coli Slt70 (d1qsaa2, E-value:10 -7 ) and LysG (G-type goose lyzozyme, d1531, E-value:10 -3 ). The sequence alignment between NP358524 and Slt70 is shown in Fig. 2 , defining the PECACE domain in the pneumococcal protein. The secondary structures are also reported, based on three-dimensional structures of Slt70 and on computational predictions for PECACE and suggest that the latter is highly α-helical (Fig. 2 ). It is of note that both Slt70 and LysG are highly similar, and both lack the catalytic aspartate residue commonly found in the active site of lysozymes [ 10 , 11 , 21 , 22 ]. Therefore, the PECACE domain of the NP358524 sequence appears to belong to this group of bacterial lysozymes, characterized by the absence of an aspartate residue in the catalytic site and is part of the Glycoside Hydrolase family 23 based upon CAZy classification . The catalytic acid residue in the PECACE domain is most probably Glu61 since it aligns with the catalytic Glu478 residue in the Slt70 sequence (Fig. 2 ). The serine residue following the catalytic glutamate and the GLMQI/V motif are essential for active-site architecture and are conserved between Slt70 and LysG. In the PECACE sequence, a threonine residue follows the catalytic glutamate and the GLMQI/V motif differs since the corresponding sequence is D(68)VMQS (Fig. 2 ). Finally, the second motif AYNxG which has been shown to be involved in the interaction with the substrate for Slt70 (A551YNxG) is well conserved in the PECACE sequence (A117YNxG). Figure 2 Alignment of the PECACE domain with Slt70. Protein fold recognition was performed with the 3D-PSSM server. The NP358524 sequence (residues 31–145) from S. pneumoniae (PECACE domain) is aligned with Slt70 from E. coli (P03810, residues 478–616). Amino acids of Slt70 involved in the catalytic reaction and in ligand recognition are underlined while residues conserved in each alignment are highlighted in red. The structural prediction for S. pneumoniae PECACE domain was determined (H = helix, C = coil) while Slt70 secondary-structure information was obtained from PDB file 1QSA. Based on this sequence analysis, we infer that the S. pneumoniae NP358524 protein, through its PECACE domain, probably catalyzes the peptidoglycan cleavage of the β-1,4-Mur N Ac-Glc N Ac bond by employing Glu61 as the catalytic residue. Identification of the PECACE domain in Gram-positive bacteria The 204 amino acid sequence from S. pneumoniae NP358524, containing the PECACE domain, was used as a PSI-BLAST search query. In total, 29 distinct proteins, all from Gram-positive bacteria, were identified (E-value: 10 -5 ) and no sequences from Gram-negative bacteria were retrieved. These sequences were aligned with ClustalW and manually edited. A conserved pattern could be extracted from this alignment: E- [ST]-X-G-X(1,16)-D-X-M-Q- [SA]- [SA]-E- [SG] which was used to search for additional sequences, but no new sequence could be detected from databases, even with a degenerated pattern. PSI-BLAST performed through the GOLD server led to the identification of 10 new sequences from Gram-positive bacteria [ 26 ]. In summary, out of the about 50 Gram-positive bacteria for which the whole genome sequence is available, 34 of them contain at least one protein harboring the PECACE domain. The final alignment of these sequences with the S. pneumoniae PECACE domain is shown in Fig. 3 . The putative catalytic glutamate residue, Glu61 in the S. pneumoniae PECACE domain, is conserved in all sequences and the following residue is a Ser or Thr in accordance with Slt70 and LysG patterns. In addition, the D(68)VMQS motif in the S. pneumoniae PECACE domain is also well represented in the large majority of sequences with the consensus sequence DI/VMQSSES. Finally, the second motif AYNxG is also conserved while the Ala residue is often replaced by a Ser. In conclusion, the features identified in the S. pneumoniae PECACE domain regarding the potential enzymatic properties of peptidoglycan polysaccharide cleavage are also shared by the similar PECACE domains in Gram-positive bacteria. Figure 3 Sequence alignment of PECACE domains identified in Gram-positive bacteria . Multiple sequence alignment was constructed using ClustalW. The lengths of the insertions in the sequences are shown in parentheses. The sequences are denoted by their GenBank Identifier (gi). The domain limits are indicated by the residue positions (first-end). The amino acids identified as catalytic or involved in ligand recognition are marked with asterisks under PECACE sequence. Alignments are coloured using the CHROMA tool using default parameters [40]. Full sequence details, group (i): Streptococcus pneumoniae R6 (gi:15902974), Streptococcus mitis NCTC 12261 (§SMT1418), Streptococcus sanguinis SK36 (&:SS_A352_G10), Streptococcus gordonii (gi:18389219), Streptococcus suis P1/7 (suis166b12), Streptococcus uberis 0140J (sub49a04), Streptococcus equi (equi324d3), Streptococcus equi subsp. Zooepidemicus (zoo26g07), Streptococcus pyogenes M1 GAS (gi:15675124), Streptococcus agalactiae 2603V/R (gi:22537230), Lactococcus lactis subsp. Cremoris SK11 (scaffold18), Streptococcus mutans UA159 (gi:24379517), Streptococcus thermophilus LMD-9 (scaffold3), Lactococcus lactis subsp. Lactis (gi:15672584), Enterococcus faecium DO (2351355_Cont543), Enterococcus faecalis V583 (gi:29376084), Bacillus subtilis subsp. subtilis str. 168 (gi:16078973), Bacillus cereus ATCC 14579 (gi:30020591), Oceanobacillus iheyensis HTE831 (gi:23100516), group (ii): Bacillus anthracis : (pXO2-08) (gi:10956398), Enterococcus faecalis : (pRE25) (gi:12957015), Enterococcus faecium (gi:22992993), Enterococcus faecalis V583 (gi:29376781), Clostridium difficile 630 (Cd81d2), Enterococcus faecalis V583 (gi:29376405), Clostridium perfringens (gi:13274506), Staphylococcus aureus subsp. aureus Mu50 (gi:15923390), Listeria monocytogenes EGD-e (gi:16803144), Streptococcus agalactiae 2603V/R (gi:22537089), Enterococcus faecium (gi:22993467), Bacillus subtilis subsp. subtilis str. 168 (gi:16077564, group (iii): Bacillus cereus ATCC 14579 (gi:30021796), group (iv): Enterococcus faecalis BM4518 (gi:33355845), group (v): Bacillus anthracis str. A2012: (pXO1) (gi:21392795), Bacillus cereus ATCC 10987 : (pBc10987) (gi:44004362). Genomic organization of pecace genes The genomic organization of pecace genes has been analyzed in a variety of Gram-positive bacteria and a conserved distribution was observed in various streptococci species (Fig. 4 ). This feature indicates that genetic transfer of the whole cluster may have occured within the streptococci family, providing further evidence regarding the significant importance of the PECACE domains in bacterial physiology. However, the pneumococcal cluster is more related to the S. mitis one than to S. mutans , S. agalactiae and S. pyogenes ones, while clusters of the latter three species are related to each other. Genes located upstream and downstream of pecace are in some instances well characterized but the function of the corresponding proteins could not bring any clues about the role of PECACE, nor any evidence on pecace gene transcription. However, pecace is in all cases found in association with the same gene (whose locus name in S. pneumoniae is spr0929) but no information about the function of the protein encoded by this locus is available in databases. Transcriptional analysis of these two genes may bring informations about their potential co-regulation, a first stage in deciphering cellular function. Figure 4 Schematic representation of the gene cluster containing pecace in Streptococci species. The coding regions and their direction of transcription are indicated by arrows. Gene names are given on top of the corresponding region. Domain organization of proteins containing the PECACE domain The PECACE domain is found in a large range of protein architectures, commonly associated with other peptidoglycan hydrolases, suggesting that these proteins have multiple peptidoglycan cleavages activities (Fig. 5 ). The identification of proteins displaying the PECACE domain was carried out using NCBI Conserved Domain Search and Pfam servers. In addition, prediction of membrane anchoring was performed with the DAS-Transmembrane Prediction server while extracellular secretion of the protein was deduced from the identification of a signal peptide. Figure 5 Domain architecture of PECACE proteins. The domain architecture of the proteins containing the PECACE domain was organized according to searches with NCBI Conserved Domain Search server against Pfam database: CHAP/NlpC-P60 (Pfam: PF05257/PF00877), M37 peptidase (Pfam: PF01551), unknown domain 1 (gi: 33355845) and unknown domain 2 (gi: 30021796). The size of the domains is not respected in these representations. PECACE-containing proteins appear to fall into 5 main categories (Fig. 5 ): (i) those which display no additional domain, (ii) CHAP-Nlpc/P60 as the associated group, (iii) CHAP-Nlpc/P60 and an unknown domain as associated groups, (iv) domains with no ascribed functions and finally (v) CHAP-Nlpc/P60 and M37 peptidase as associated groups. The 19 proteins which contain only the PECACE domain belong to group (i) and harbor either a signal peptide or a transmembrane helix (as for the S. pneumoniae protein), leading in both cases to cell surface expression. The CHAP-Nlpc/P60 domain is commonly associated with the PECACE domain in different modular organizations, namely in groups (ii), (iii), and (v) [ 18 , 19 , 27 ]. The CHAP domain has been recently described as a Cysteine, Histidine-dependent Amidohydrolase/Peptidase and it has been proposed to hydrolyse peptidoglycan containing γ-glutamyl [ 18 , 19 ]. Indeed, proteins such as N -acetylmuramyl-L-alanine amidase and D-alanyl-glycyl endopeptidase have been described as CHAP-containing enzymes [ 18 , 19 ]. However, while the substrate and the reaction mechanism have not been yet experimentally characterized for the CHAP domain, its role in peptidoglycan hydrolysis is inferred from its presence in multifunctional proteins recognizing peptidoglycan as substrate. Recently, hydrolytic activity of peptidoglycan has been attributed to the CHAP-containing protein PcsB in S. pneumoniae due to abnormal and uncontrolled cell wall synthesis at misplaced septa and formation of long cells in pcsB deleted mutant strains [ 20 ]. Proteins from group (ii) are expressed at the cell surface through a transmembrane anchor or are secreted, 12 members have been identified with this topology. Only one sequence (AAQ16265, gi:33355845) from Enterococcus faecalis BM4518 is part of the group (iii), and no function could be identified for the N-terminus domain preceding the PECACE domain. However the former domain is Lys-rich (14%) suggesting an electrostatic interaction with the peptidoglycan as proposed for B. subtilis endopeptidase [ 28 ]. Group (iv) is composed of an unique sequence from B. cereus ATCC 14579 (NP 833427, gi:30021796). Neither a signal peptide nor a transmembrane anchor have been detected. Furthermore, the domain of unknown function, which is different from the ones identified in groups (iii) and (v) is present in other multimodular proteins of B. cereus , in association with peptidoglycan hydrolysis enzymes. Finally, two sequences share the architecture defining the group (v) which harbor CHAP-Nlpc/P60 and Peptidase M37 domains [ 29 ]. Members of the Peptidase M37 family are generally glycylglycine endo-metallopeptidases; the archetypal member is the lysostaphin enzyme from Staphylococcus species which cleaves the pentaglycine bridge in the peptidoglycan [ 30 ]. One group (v) protein (NP 652875, gi:21392795) is encoded by Bacillus anthracis plasmid pXO1 and is required for synthesis of various anthrax toxin proteins [ 31 ]; this sequence has neither a signal peptide nor a transmembrane region. The second sequence of group (v) is located on Bacillus cereus ATCC 10987 plasmid pBc10987 (NP 982030, gi:44004362) and contains, in addition to CHAP-Nlpc/P60, Peptidase M37 and PECACE domain as well as an extra sequence to which no function has been attributed but with significant similarity with a B. anthracis plasmid pXO1 sequence (NP 652874, gi:21392794) [ 32 ]. Conclusions In summary, a new domain named PECACE, putatively involved in peptidoglycan cleavage has been identified in S. pneumoniae . The probable enzymatic activity deduced from the detailed analysis of the amino acid sequence suggests a LT-type or goose lyzosyme-type mechanism; we are currently characterising the enzymatic properties and cellular role of the PECACE domain from S. pneumoniae . This new putative pneumococcal peptidoglycan cleavage enzyme differs largely from the other hydrolases already identified in this bacteria. Indeed, LytA, LytB, LytC and CBPD proteins are all bound to the cell wall choline residues and thus expressed at the cell surface. The presence of a signal peptide within the amino acid sequence of PcsB suggests that it is either exposed on the cell surface or secreted. On the contrary, the pneumococcal NP358524 protein displaying the PECACE domain is embeded in the cytoplasmic membrane by a hydrophobic helix. The physiological role of this membranous peptidoglycan cleavage enzyme might differ from the other peptidoglycan hydrolysing enzymes. Interestingly, the PECACE domain has only been found in Gram-positive bacteria. It is tempting to speculate that the multilayered structure of Gram-positive peptidoglycan relates to the PECACE putative activity. The architecture of multimodular proteins containing the PECACE domain is another example of the pattern of multiple activities harbored by many peptidoglycan hydrolases, probably needed for the regulation of peptidoglycan metabolism. The release of new bacterial genomes sequences will probably add new members that will complete the five groups identified so far in this work and new groups could also emerge. Conversely, the functional characterization of the unknown domains mentioned in this work should now be easier, as their substrate, the peptidoglycan, is now identified. Methods The non-redudant database of protein sequences (National center for Biotechnology Information, NIH, Bethesda) and whole bacterial genomes sequences [ 26 ] was searched using BLASP and PSI-BLAST programs with (E) value threshold of 0.005 [ 33 ]. Multiple alignments were constructed with ClustalW program [ 34 ] followed by manual correction based on PSI-BLAST results. Protein fold recognition through 3D-profiles was searched using 3D-PSSM server [ 25 ]. Conserved (and degenerated) amino acid patterns was designed and searched against non-redudant database of protein sequences . Identification of domains associated with PECACE proteins was realized using NCBI Conserved Domain Search [ 35 ] and Pfam servers [ 36 ]. Finally, prediction of transmembrane anchor and secretory signal peptide were performed with DAS server and SignalP-2.0 servers respectively [ 37 , 38 ]. Authors' contributions OD conceived of the study and participated in the sequences alignment. EP carried out the sequences analysis and the writing of the manuscript with AMDG. TV coordinated the study. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC550655.xml
503386	Attentional influences on functional mapping of speech sounds in human auditory cortex	Background The speech signal contains both information about phonological features such as place of articulation and non-phonological features such as speaker identity. These are different aspects of the 'what'-processing stream (speaker vs. speech content), and here we show that they can be further segregated as they may occur in parallel but within different neural substrates. Subjects listened to two different vowels, each spoken by two different speakers. During one block, they were asked to identify a given vowel irrespectively of the speaker (phonological categorization), while during the other block the speaker had to be identified irrespectively of the vowel (speaker categorization). Auditory evoked fields were recorded using 148-channel magnetoencephalography (MEG), and magnetic source imaging was obtained for 17 subjects. Results During phonological categorization, a vowel-dependent difference of N100m source location perpendicular to the main tonotopic gradient replicated previous findings. In speaker categorization, the relative mapping of vowels remained unchanged but sources were shifted towards more posterior and more superior locations. Conclusions These results imply that the N100m reflects the extraction of abstract invariants from the speech signal. This part of the processing is accomplished in auditory areas anterior to AI, which are part of the auditory 'what' system. This network seems to include spatially separable modules for identifying the phonological information and for associating it with a particular speaker that are activated in synchrony but within different regions, suggesting that the 'what' processing can be more adequately modeled by a stream of parallel stages. The relative activation of the parallel processing stages can be modulated by attentional or task demands.	Background This study explores attentional modulation within the 'what'-stream of the auditory modality during phoneme processing. Knowledge of speech sound representation in the auditory domain is still sparse. However, parallels to the extensively studied visual modality and also to the somatosensory domain are becoming evident. For example, columnar mapping of several stimulus properties (as known from the visual cortex) has been revealed in human and animal research: acoustic parameters like spectral bandwidth, periodicity, stimulus intensity [ 1 , 2 ] or – for human speech sounds – distance between spectral peaks [ 3 , 4 ] appear to be mapped perpendicularly to the main cochleotopic gradient. Recently, a segregation of a ventral 'what' and a dorsal 'where' stream – as long established in the visual system [ 5 ] – has also been proposed for the auditory system. This conclusion was based on neuroanatomical and functional studies in macaques [ 6 - 8 ] and has been substantiated in humans [ 9 , 10 ]. Given these parallels between sensory domains and the increasing preference for complex stimuli along the auditory central pathway, more complex topologies such as language-specific maps in auditory cortex are also plausible, and evidence for individually ordered mapping of speech sounds is growing [ 11 - 15 ] (for speech-specific vocalizations in animals see [ 8 , 16 ]). More specifically, data from our lab imply map dimensions along phonological features which build the basic components of speech sounds: In Obleser et al. [ 15 ], responses to DORSAL vowels (which are articulated with the back of the tongue and which exhibit a small distance between spectral peaks, i.e., small F 1 -F 2 distance) were located more posterior in auditory association cortex than responses to CORONAL vowels (which are articulated with the tip of the tongue and which exhibit a large distance between spectral peaks, i.e., larger F 1 -F 2 distance), and a topographical shift between these classes of vowels even when embedded in non-words has been reported [ 15 , 17 ]. Research has long been tackling the question of attention and attentional top-down modulation that may tune cortical neurons and with it functional maps in a context-specific manner: In the visual domain, a top-down influence on receptive fields of areas as basic as VI has been shown [ 18 , 19 ], and in the somatosensory domain Ergenzinger and colleagues reported that drastic changes in functional maps can be experimentally induced even on a thalamic level [ 20 ]. The thalamic homuncular representation of a monkey's hand becomes blurred and distorted when top-down modulation from somatosensory cortex is blocked neurochemically within the cortex. These results emphasize the possibility of attention-dependent modulation of maps, a topic exemplified in a somatosensory MEG mapping study by Braun and colleagues [ 21 ]: In a somatosensory stimulation with small brushes moving back and forth across the digit tips, subjects either attended the movement of single brushes on single digits and reported the movement direction or they attended and reported the global direction of all brushes on all five digits. Magnetic source imaging of the somatosensory evoked field revealed a typical homuncular representation of the single digits spread along the post central gyrus only in the condition where the focus of attention was on single digits rather than on the hand as a whole. In the latter condition, top-down attentional demands temporarily seemed to blur the single digit mapping. For the developing field of speech sound mapping, top-down influences of attentional demands on functional organization at the different stages in the processing streams have not been sufficiently studied. Nevertheless, it becomes a central issue when the functional architecture of the effortless and robust perception of speech shall be understood. It is common to study speech perception either in passive oddball paradigms [ 22 , 23 ] where the subject's attention is deliberately forced to a movie or to reading a book, or in passive listening conditions where no attentional control is experimentally induced (e.g. [ 24 , 25 ]), or in active target detection tasks where the attention is commonly focused on the phonological content of the speech material [ 14 , 15 , 26 ]. We analyzed the magnetic N100 (N100m) response to two vowels [o] and [ø], both produced by a male and a female speaker. Subject's attention was either on the vowel or on the speaker difference, in a counterbalanced order. How would a controlled shift of attention from specific phonological features of speech to features of speaker identity affect the speech sound mapping in timing and topography of the brain response? Two concurrent outcomes are conceivable here: First, from the numerous parallels between the auditory and other sensory domains, one might expect a blurring of differences of the phonological map in auditory cortex when features such as the speaker identity rather than phonological differences are attended over minutes. Second, phonological processing could be the default process needed in all speech-listening situations and should therefore activate phonological feature maps irrespectively of attentional demands. We would then expect that the separate mapping of DORSAL and CORONAL vowels described previously [ 15 ] is unaffected by an attentional focus on speaker identity. However, a shift of activational patterns as an entity would reveal more about the staging of parallel processing in the flow of the 'what' stream. Results In 21 of 22 subjects, a clear waveform deflection around 100 ms post vowel onset was observed (Fig. 2 ) in all conditions over both hemispheres and sensor space parameters peak latency and amplitude were obtained. Satisfying and physiologically plausible dipole fits (see methods) in both hemispheres could be obtained in 17 subjects and were subjected to statistical analysis. N100m latency, amplitude and source strength Analysis of the N100m root mean square (RMS) peak latency revealed foremost a main effect of vowel (F 1,20 = 44.8, p < .0001, Fig. 2 ), whereby the DORSAL vowel [o] consistently elicited N100m peaks 5 ms later than the CORONAL vowel [ø]. In sensor space, an enhancement of RMS peak amplitude for the [ø] vowel by 10 fT (Fig. 2 ) almost attained significance (F 1,20 = 4.12, p < .06). However, the effect was significant in source space that is not influenced by varying head-to-sensor positions: The [ø] dipole source strength, an estimate for the amount of massed neuronal activity, was larger for the [ø] vowel than for the [o] by 25 % or 6 nAm (F 1,16 = 9.36, p < .01). No hemispheric differences in signal power between vowel categories or tasks were apparent. N100m source location and orientation In agreement with previous findings with a more comprehensive set of vowels [ 15 ], the vowel categories [o] and [ø] elicited statistically different centers of activity along the anterior-posterior axis (F 1,16 = 7.73, p < .01), that is, the auditory processing in the DORSAL vowel [o] was reflected by a more posterior ECD location (Fig. 3 ). A difference in source configuration was also evident from a more superior position of the [o] source (F 1,16 = 12.28, p < .01), a more vertical orientation (F 1,16 = 5.81, p < .05) than the [ø] source, and from an angular difference between the two vowel categories in the sagittal plane (i.e. the [o] source was located more posterior and inferior, F 1,16 = 10.91, p < .01) and in the axial plane (i.e. the [o] source was also located more posterior and lateral, F 1,16 = 6.82, p < .05, relative to the [ø] source). None of these effects showed an interaction with hemisphere, but data gained further validity as the right-hemispheric sources were all located more posterior (F 1,16 = 8.88, p < .01), more inferior (F 1,16 = 4.27, p < .06) and were tilted more vertically (F 1,16 = 14.29, p < .01) than their left-hemispheric counterpart. Such a difference is to be expected from previously reported N100 asymmetries between cerebral hemispheres [ 27 - 30 ]. The relative mapping of phonological features of the speech signal [ 14 , 15 ] was not affected by the task-induced shifts of attention. However, shifts of subjects' attentional focus from phonological categorization to identification of the speaker's voice shifted vowel sources as a whole to more posterior and superior locations within the supratemporal plane. Statistically, the speaker categorization task produced more superior (F 1,16 = 4.72, p < .05) and marginally more posterior (F 1,16 = 3.36, p < .10) ECD locations, which was also evident by an angular displacement in the sagittal plane (F 1,16 = 4.6, p < .05). The effect seemed to be driven by changes in the left hemisphere but the task × hemisphere interaction never attained significance (all F < 1). When brain responses were analyzed separately for stimuli spoken by male and female speaker, which yielded satisfying dipole solutions only in 12 subjects, the most striking finding was a consistent speaker × task interaction of the dipole location in both the sagittal plane (F 1,11 = 10.83, p < .01) and the axial plane (F 1,11 = 7.16, p < .03). That is, subjects' attentional focus slightly affected the relative displacement of male and female voice-evoked brain responses: In both the sagittal plane and the axial plane, a significant 4° difference emerged in the phonological categorization task (both p < .05), which vanished in the speaker categorization task. In contrast, as reported above, no such task influence was evident in the relative position of vowel-evoked brain responses. Performance Overall target detection rate was 94.1 %, false alarms occurred in 5.5% of all trials. Responses of the 17 subjects whose brain responses were subjected to magnetic source imaging were analyzed in detail: The phonological categorization task (93.2 ± 3.0 % correct, 4.9 ± 2.2 % false alarms, M ± SEM) and the speaker categorization task (95.0 ± 2.9 % correct, 6.2 ± 3.2 % false alarms) did not differ significantly (one-way repeated measures ANOVAs, all F < 1). Discussion This study was set up to explore potential influences of the attentional focus on the mapping of speech sounds within the auditory cortex. With subject's attention either on the phonological differences or on the speaker difference between vowel stimuli, we mapped the auditory evoked N100m and localized its sources that fitted well with a single dipole per hemisphere. All responses were located in the perisylvian region. Furthermore, the relative distribution of sources indicated an interesting pattern. As hypothesized and expected from previous studies, the fundamental location difference between the sources of the DORSAL vowel [o] source and the CORONAL vowel [ø] [ 15 , 17 ] could be replicated under both attentional conditions. In contrast, the corresponding difference between speaker-dependent sources was subject to task influences. That is, a shift of subjects' attention to a non-phonological acoustic feature, the speaker identity, did not blur the spatial segregation within the speech sound map. In contrast, the [ø] and [o] generators were slightly displaced towards more posterior and more superior locations when subjects focused on speaker identity. In most situations, a listener may automatically extract the phonological invariants from the speech signal in order to access lexical information, for example the meaning of the information inherent in speech. Speaker-dependent features such as pitch and periodicity should not play a crucial role in this phonological decoding process. This is what we mimicked by asking our subjects to detect a certain vowel in a stream of varying speech sounds. However, in cocktail-party-like situations there is the additional demand to attend acoustic properties of certain speech streams or speakers, and we implemented it by asking our subjects to detect a certain voice in a stream of varying speakers. Speaker identification comprises an important but not necessarily orthogonal process to phonological decoding in speech perception: areas in the upper bank of the superior temporal sulcus (STS) have been identified previously [ 31 ] to be voice-selective (as opposed to other environmental sounds), and in many situations the selective tracking of one voice amongst others is a prerequisite for decoding the phonological content of this speaker's utterances. The displacement of dipolar sources seen here may mirror the involvement of additional cortical areas, such as the voice-specialized part in the STS [ 31 ] or pitch-specialized areas in the primary auditory cortex. An additional STS activation would most likely elicit an inferior shift of the dipole sources during speaker categorization. However, a shift into the opposite direction was obtained. This might indicate that the contribution of the voice-specialized part of the STS around 100 ms post-stimulus onset is small compared to other additional cortical areas, such as pitch-specialized areas in the primary auditory cortex. It is now well-established that a finegrained analysis of the speech signal takes place mainly in anterior parts of the supratemporal gyrus [ 17 , 32 - 34 ], thereby anterior of primary auditory areas. Consequently, the activity shift towards more posterior sites we observed in the speaker categorization task strongly argues for an additional involvement of these primary auditory areas. Unfortunately, we cannot dissociate speaker identification processes from pitch processing in the current study. However, pitch differences are among the primary cues dissociating male and female voices, and a clear involvement of auditory core areas in pitch processing has been shown in a recent MEG study focusing on pitch detection mechanisms [ 35 ]. Conclusions Data presented here suggest that the systematic mapping of speech sounds within the auditory cortex is robust under changing attentional demands and not tied to phonological awareness. However, the general shift of activity when a non-phonological speaker categorization must be accomplished shows that speech sound representations are modulated in their locations in a context-dependent manner. Situational demands obviously influence the differential but time-synchronous involvement of specialized neuronal assemblies that contribute to speech sound decoding in a top-down fashion. Hence, the spectrally high-resolving analysis of the incoming speech stream is performed at the same time but in different locations, i.e. in a different mix of cell assemblies than the analysis of speaker-dependent features (such as pitch, periodicity, or other features inherent to voice quality). Further spatially high-resolution brain imaging studies are needed to quantify as to which extent voice-selective areas in the upper bank of the STS [ 31 ] become involved when speaker categorization is accomplished. For the time being, this study increases our understanding of speech sound processing, as it replicates previous findings of an orderly mapping of phonological vowel features and as it shows that changing attentional foci affect the absolute but not the relative distribution of vowel-evoked activity within the auditory cortex. Methods Subjects 22 subjects (11 females, mean age 24.3 ± 4 years, M ± SD) participated in the procedure. All subjects were monolingual native speakers of German. Only right-handers as ascertained by the Edinburgh Handedness Questionnaire [ 36 ] were included. Subjects gave written informed consent and were paid €10 for their participation. Experimental design In an auditory target detection task, subjects listened to randomized sequences of four German natural vowel exemplars: The DORSAL rounded vowel [o] in two exemplars, in one spoken by a male voice and in the other by a female voice, and the CORONAL rounded vowel [ø], also produced by both voices (Fig. 1 ). 200 ms long vowels free of formant transitions were cut out of spoken words, digitized with a 10 kHz sampling rate and faded with 50 ms Gaussian on- and offset ramps. Table 1 summarizes exact pitch and formant frequencies of the four exemplars. Prior to the measurement, individual hearing thresholds were determined for both ears and all four vowel exemplars. Stimuli were presented binaurally with at least 50 dB SL (respective to the vowel exemplar which showed the weakest sensation level, if any differences between exemplars occurred) via a non-magnetic echo-free stimulus delivery system with almost linear frequency characteristic in the critical range of 200–4000 Hz. In a test sequence, subjects repeated vowels aloud and recognized all stimuli correctly, i.e. they distinguished between both vowel categories and voices without difficulty. Binaural loudness was slightly re-adjusted where necessary to ensure perception in the head midline. In the actual measurement, vowel exemplars were presented in two randomized sequences with equal probability and a randomized stimulus onset asynchrony of 1.6 – 2 s. All subjects performed – in a counterbalanced order – two different tasks during these two sequences: In a task A (hereafter called phonological categorization ), subjects had to press a button with their right index finger whenever a given vowel ([o] or [ø], counterbalanced across subjects) occurred, irrespective of the speaking voice. In a task B (hereafter called speaker categorization ), subjects had to press a button whenever a given voice (the male or the female voice, counterbalanced across subjects) uttered a vowel, irrespective of the uttered vowel category. Fig. 1 (lower panel) which clarifies and visualizes the task. That is, in the phonological categorization task, subject's attention was focused on a categorical distinction between speech sounds, [o] or [ø], which closely resembles the tasks applied in most brain imaging studies testing active speech sound processing (e.g. [ 14 , 15 , 37 ]) – a process ubiquitously taking place when decoding running speech. In contrast, the speaker categorization task was intended to shift subject's attention to more general and more basic acoustic properties of the material [ 31 ] presented to accomplish speaker distinction. Data reduction and statistical analyses Data acquisition and analysis, including source modeling, closely followed the procedure described in [ 15 ]: Auditory magnetic fields were recorded using a whole head neuromagnetometer (MAGNES 2500, 4D Neuroimaging, San Diego) in a magnetically shielded room (Vaccumschmelze, Hanau, Germany). Epochs of 800 ms duration (including a 200 ms pre-trigger baseline) were recorded with a bandwidth from 0.1 to 200 Hz and a 687.17 Hz sampling rate. If the peak-to-peak amplitude exceeded 3.5 pT in one of the channels or the co-registered EOG signal was larger than 100 μV, epochs were rejected. Button-presses did not affect the auditory evoked field topography in the N100m time range. We analyzed up to 150 artifact-free vowel responses that remained for both vowel categories [o] and [ø] after off-line noise correction, and averaged them separately for vowel category but across speaker voice. Splitting up vowel conditions into male and female speaker sub-conditions was not possible due to a resulting small number of averages. However, we also performed separate averages and analyses of male and female speaker across vowel categories. In any case, the resulting averages thus contained brain responses to two acoustically variant exemplars which makes results more comparable to our previous studies [ 15 , 17 ]. A 20 Hz lowpass filter (Butterworth 12 dB/oct, zero phase shift) was subsequently applied to the averages. The N100m component was defined as the prominent waveform deflection in the time range between 90 and 160 ms (Fig. 2 ). Isofield contour plots of the magnetic field distribution were visually inspected to ensure that N100m and not P50 m or P200 m were analyzed. N100m peak latency was defined as the sampling point in this latency range by which the first derivative of the Root Mean Square (RMS) amplitude reached its minimum and second derivative was smaller than zero. RMS was calculated across 34 magnetometer channels selected to include the field extrema over the left and the right hemisphere, respectively. Prior to statistical analyses, all brain response latencies were corrected for a constant sound conductance delay of 19 ms in the delivery system. Using the same sets of channels, an equivalent current dipole (ECD) in a spherical volume conductor (fitted to the shape of the regional head surface) was modeled at every sampling point separately for the left and the right hemisphere [ 38 ]. The N100m source parameters were determined as the median of 5 successive ECD solutions in the rising slope of the N100m. The resulting ECD solution represents the center of gravity for the massed and synchronized neuronal activity. To be included in this calculation, single ECD solutions had to meet the following criteria: (i) Goodness of fit greater than .90, (ii) ECD location larger than 1.5 cm in medial-lateral direction from the center of the brain and 3–8 cm in superior direction, measured from the connecting line of the pre-auricular points. Statistical analysis of dependent variables N100m peak latency, amplitude and N100m source generator strength, location and orientation focused on 2 × 2 × 2 repeated measures analysis of variance with repeated factors hemisphere (left vs. right), vowel ([o] vs. [ø]) and task (attend phonology vs. attend speaker). As source location displacements do not appear exactly and exclusively along the Cartesian axes of the source space (cf. [ 21 ]), we additionally calculated differences in the polar angle Φ and the azimuth angle θ which here describe angular displacements in the sagittal and the axial plane, respectively. Authors' contributions J.O., T.E. and C.E. conceived the experiment and drafted the manuscript. J.O. and C.E. prepared the exact experimental setup. J.O. supervised data acquisition, and performed all data and statistical analyses. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC503386.xml
546194	Patient involvement in medical decision-making and pain among elders: physician or patient-driven?	Background Pain is highly prevalent among older adults, but little is known about how patient involvement in medical decision-making may play a role in limiting its occurrence or severity. The purpose of this study was to evaluate whether physician-driven and patient-driven participation in decision-making were associated with the odds of frequent and severe pain. Methods A cross-sectional population-based survey of 3,135 persons age 65 and older was conducted in the 108-county region comprising West Texas. The survey included self-reports of frequent pain and, among those with frequent pain, the severity of pain. Results Findings from multivariate logistic regression analyses showed that higher patient-driven participation in decision-making was associated with lower odds (OR, 0.82; 95% CI, 0.75–0.89) of frequent pain, but was not significantly associated with severe pain. Physician-driven participation was not significantly associated with frequent or severe pain. Conclusions The findings suggest that patients may need to initiate involvement in medical decision-making to reduce their chances of experiencing frequent pain. Changes to other modifiable health care characteristics, including access to a personal doctor and health insurance coverage, may be more conducive to limiting the risk of severe pain.	Background Persons age 65 years and older commonly endure a multitude of chronic and debilitating conditions which contribute to persistent pain [ 1 ]. Estimates of the prevalence of pain among the community-dwelling elderly range between 25% and 50% [ 2 , 3 ]. Pain has been found to have a substantial effect on health-related quality of life [ 2 ], the use of over the counter and prescription drugs [ 1 , 4 ], and the utilization of medical care [ 5 ]. As the number of elderly persons in the United States rises, more research is needed to determine how the delivery of medical care could be altered to limit the onset of pain and its subsequent burden on health status and the health care system. Increasing patients' involvement in the medical decision-making process is one potentially fruitful means of improving pain management. Several studies suggest that patients, especially those with chronic conditions, who have opportunities to participate in care have more positive health outcomes than those who do not [ 6 , 7 ]. While other studies have pointed out that the positive correlation between patient participation and health outcomes is more suggestive than conclusive, Guadagnoli and Ward have stated that physicians should nevertheless strive to engage their patients in decision-making for humanitarian reasons [ 8 ]. Although patients' participation may improve their health outcomes, the effect can be diminished among elderly patients. Elderly patients, as compared to younger patients, have been shown to be less participatory in medical-decision making [ 9 - 11 ]. Using a longitudinal cohort, the Medical Outcomes Study found that patients older than 75 years were less participatory [ 12 ]. Other studies have also shown that older people tend to exhibit more conversational behaviors [ 13 ], give more socially desirable responses [ 14 ], and defer to physicians' authorities [ 15 ]. The primary objective of the present study was to examine how participation in decision-making was associated with the occurrence of pain among a cohort of community-dwelling elders. In contrast to previous studies, we differentiated two types of participation in decision-making. The first type is physician-driven in which the physician takes the initiative to ask questions and offer choices to patients. The second type is patient-driven, in which the patient takes the initiative to ask questions and express preferences. We hypothesized that stronger physician and patient-driven participation in decision-making would be associated with lower odds of frequent pain and, among those with frequent pain, lower odds of severe pain. We also tested for the effects of other health care factors which might be conducive to pain management, such as tenure with a personal doctor. The findings have implications for how older patients interact with their physicians as well as how physicians and clinic managers organize health services. Methods Sample and setting Data were obtained through a longitudinal, population-based study of community-dwelling elders, the Texas Tech 5000 Survey. The Texas Tech 5000 Survey was conducted in a 108-county region of West Texas, a geographically and ethnically diverse area encompassing approximately half of the state's land mass. The survey has been described in detail elsewhere [ 16 - 21 ]. Briefly, approximately 65,000 households were randomly selected from residential telephone listings and screened to identify a cohort of 5,000 individuals age 65 years and older. Age-qualified individuals were subsequently tested for cognitive impairment using a telephone version of the Mini Mental State Evaluation [ 22 ]. Ninety-three percent of individuals did not have impairment and thus were eligible for participation in the study. Excluding telephone numbers that were never reached, those who refused the cognitive screener, and individuals who failed the cognitive screener, the eligible sample size was 6,942. Two follow-up surveys have since been conducted among the original cohort. Selected questions measuring satisfaction with care and health-related quality of life were included in each wave. To limit respondent burden, most questions were asked only during one wave (the patient and physician-driven participation in decision-making and perceived pain questions were only asked during Wave 3). Of the 6,942 households that were eligible for participation in Wave 1 of the survey, 5,006 persons participated, yielding a baseline response rate of 72%. The data presented here are from 3,135 subjects who participated in all three waves of the survey, yielding an overall response rate of approximately 45%. While some subjects were obviously lost to follow-up, the demographic composition of the study samples remained similar over the study period. The Texas Tech Health Sciences Center Institutional Review Board for the Protection of Human Subjects approved the study. Measures Frequent and severe pain The occurrence and severity of pain were measured in Wave 3 using items developed for and included in two nationally representative surveys of older persons, the Health and Retirement Study (HRS) and Assets and Health Dynamics among the Oldest Old (AHEAD) [ 23 ]. First, the frequency of pain was measured by asking respondents if they were "often troubled with pain?" Responses were categorized to distinguish those persons who were often troubled (referred to hereafter as frequent pain) and those who were not often troubled by pain, as has been done in previous studies [ 2 ]. The severity of pain was assessed among those persons who reported frequent pain through a single item asking, "how bad is the pain most of the time?" Responses were categorized to differentiate those persons with mild or moderate pain versus severe pain. Sociodemographic factors A number of sociodemographic, health care, and health status measures were included. Sociodemographic factors were gender, age (continuous), marital status, educational status (high school graduate vs. less than high school education), and place of residence (urban, rural, and frontier). An urban area is a metropolitan county, or a county with a total population of at least 50,000, whereas a rural area is a county with fewer than 50,000 persons. Rural counties were further classified according to whether they were frontier areas, or counties with fewer than 7 persons per square mile [ 24 ]. Health care factors Health care variables were health insurance coverage, the number of physician visits in the last 6 months, tenure with a personal doctor, an index measuring physician-driven participation in decision-making, and an index measuring patient-driven participation in decision-making. Health insurance coverage was coded as Medicaid, Medicare, Medicare plus other private or government coverage, other private or government coverage, and no insurance. Tenure with a personal doctor was measured using a single question asking if the individual had a personal doctor and, if so, the duration of tenure with the physician (less than 1 year, 1 to 2 years, 3 to 4 years, and 5 or more years). An index of physician-driven participation in decision-making was created using three items taken from the Medical Outcomes Study [ 12 ]. The physician-driven participation in decision-making questions included: 1) How often does your doctor ask you to help make the decision when there is a choice between treatments?, 2) How often does your doctor give you some control over your treatment?, and 3) How often does your doctor ask you to take some of the responsibility? Response options for each item ranged from 0 (never) to 4 (very often). The aggregation of the three items divided by the total number of items produces a score between 0 and 4 with a higher index score indicating greater involvement. For the present data set, the physician-driven participation index had reasonable internal consistency (Cronbach's alpha = 0.69), which was similar to that found in the Medical Care Outcomes Study (Cronbach's alpha = 0.74) [ 12 ]. Three questions adopted from a study of older patients' communication during medical visits [ 25 ] were used to measure patient-driven participation in decision-making. These questions included: 1) How often do you write out a list of symptoms, complaints, and medications before visiting a doctor?, 2) How often do you express preferences for tests, medications, and treatments?, and 3) How often do you call to clarify information or report symptoms or side effects after a visit? As was the case for the physician-driven index, the patient-driven participation index ranges between 0 and 4 with a higher score indicating greater involvement. The Cronbach's alpha for the patient-driven participation index was 0.58. Health status Overall health status (categorized as excellent, very good, good, and fair or poor) was measured using a general health item from a brief health-related quality of life instrument (the SF-12) [ 26 ]. Mental health status was assessed with the mental component score (MCS) of the SF-12. Additional health status variables included whether the individual had ever been diagnosed with arthritis and the number of additional comorbid conditions (categorized as none, one, two, and three or more). Statistical analysis Chi-square tests were first conducted to determine whether there was an association between each categorical sociodemographic, health care, and health status factor and frequent and severe pain. T-tests were conducted to determine if there was a difference in each continuous sociodemographic, health care, and health status factor between individuals with and without frequent pain and individuals with and without severe pain. Next, multivariate logistic regression analyses were conducted to determine if physician or patient-driven participation in decision-making were associated with the odds of frequent pain and, among those with frequent pain, the odds of severe pain. The potential for multicollinearity between the covariates was assessed by calculating their variance inflation factors; no problems with multicollinearity were found. Results Description statistics for individuals with frequent pain A total of 1,333 (42.5%) of the 3,135 survey participants had frequent pain. Table 1 presents percentages for frequent pain by categorical sociodemographic, health care, and health status variables. Several categorical sociodemographic variables were significantly associated with frequent pain. Frequent pain was less common among males (compared to females) and among married persons (compared to single persons). Frequent pain was more common among persons with less than a high school degree as compared to those with at least a high school degree. Health insurance was insignificant, but tenure with a personal doctor was associated with frequent pain. Specifically, pain was least common among individuals with no personal doctor, compared to those who had a personal doctor. Frequent pain was more common among persons with more comorbid diseases or conditions (compared to those with none), those with arthritis (compared to those without arthritis), and those with poorer self-rated general health. As shown in Table 2 , persons with frequent pain had a higher number of physician visits in the previous six months but lower physician and patient-driven participation than those without frequent pain. Moreover, those with frequent pain had worse (lower) mental component scores (MCS) than those without frequent pain. Table 1 Prevalence of frequent and severe pain by categorical independent variables Sociodemographics N = 3,135 Frequent Pain % Severe Pain % Gender Male 952 35.7 1 6.3 3 Female 2,183 45.5 10.4 Race/Ethnicity White 2,678 42.5 8.4 1 Hispanic 327 42.5 11.6 Other 130 43.9 19.2 Education < high sch. grad. 785 45.9 3 13.3 1 High school grad. 2,350 41.4 7.8 Marital Status Married 1,661 40.8 3 8.1 Not married 1,474 44.5 10.3 Rural / urban residency Urban 1,720 43.9 9.6 Rural, non-frontier 1,072 40.8 8.7 Frontier 343 41.1 8.5 Income <$10,000 491 47.9 1 14.3 2 $10–20,000 658 47.7 10.3 $21–30,000 505 43.0 7.7 $31,000 and higher 892 36.0 5.7 Health care Insurance Uninsured 93 46.2 21.5 1 Medicare 917 41.8 9.2 Medicaid 341 43.7 12.6 Medicare+other ins. 1,498 43.4 7.9 Other private/gov. ins 286 37.8 7.7 Tenure with doctor No personal doctor 426 37.8 1 10.6 Less than 1 yr 227 44.9 9.2 1–2 yrs 414 45.7 10.1 3–4 yrs 454 42.3 8.4 5 or more yrs 1,614 42.7 8.7 Health status No. of comorbidities 0 1,690 37.2 3 6.3 2 1 874 47.1 10.5 2 384 48.7 14.1 3 or more 187 56.7 18.7 Ever diagnosed with arthritis Yes 1,988 55.0 1 12.8 2 No 1,147 20.8 2.9 General health status Excellent 316 15.2 3 2.2 3 Very good 720 31.1 5.6 Good 1,040 41.0 3.1 Fair 687 55.8 13.8 Poor 360 69.2 29.2 1 p < 0.0001, 2 p < 0.01, 3 p < 0.05 note: Analyses of severe pain were limited to those with frequent pain. Table 2 Means and standard deviations for continuous independent variablesby frequent and severe pain Frequent pain Severe pain Yes No Yes No Sociodemographics Mean age (SD) 75.4(6.3) 75.3(6.3) 75.7(6.7) 75.3(6.3) Health care Mean no. physician visits (SD) 6.3(8.5) 1 3.9(6.1) 8.0(9.5) 1 5.8(8.1) Mean physician-driven participation index (SD) 1.8(1.2) 3 1.9(1.2) 1.9(1.2) 3 1.7(1.2) Mean patient-driven participation index (SD) 2.4(1.0) 1 2.7(1.0) 2.4(1.0) 2.4(1.1) Health status Mean SF-12 mental component score (SD) 52.5(9.9) 1 54.8(7.4) 48.7(12.1) 1 53.6(9.0) 1 p < 0.0001, 2 p < 0.01, 3 p < 0.05 note: Analyses of severe pain were limited to those with frequent pain. Description statistics for individuals with severe pain Among the 1,333 individuals with frequent pain, a total of 287 (21.5%) had severe pain. As shown in Table 1 , severe pain was less common among males (compared to females) but more common among other races/ethnicities (compared to non-Hispanic whites), persons with less than a high school degree (compared to at least a high school degree), and persons with lower household income. Severe pain was most common among individuals without health insurance. It was more common among persons with more comorbid diseases or conditions (compared to those with none), those with arthritis (compared to those without arthritis), and those with poorer self rated general health status. As shown in Table 2 , those with severe pain had more physician visits and higher physician participation in decision-making. Those with severe pain had lower or worse mental component scores and a higher number of physician visits in the previous six months (compared to those without severe pain). Multivariate analyses of the odds of frequent pain Findings from multivariate logistics analyses are shown in Table 3 . Males had lower odds (OR, 0.81; 95% CI 0.67, 0.98) of frequent pain than females. Race/ethnicity was not significantly associated with frequent pain. Compared to urban residents, those residing in a rural area had lower odds (OR, 0.77; 95% CI 0.64, 0.92) of frequent pain than urban residents. Income, marital status, and frontier residence were not significantly associated with the odds of frequent pain. Individuals who had more physician visits in the previous six months had a higher odds of frequent pain (OR, 1.02; 95% CI 1.01, 1.04). Table 3 Multivariate logistic regression of sociodemographic, health care, and health status factors on frequent and severe pain Variable (reference group) Frequent pain OR (95% CI) Severe pain OR (95% CI) Sociodemographics Age 0.99 (0.97, 1.00) 1.00 (0.98, 1.02) Male (vs. female) 0.81 (0.67, 0.98) 3 0.78 (0.54, 1.14) Race/ethnicity Hispanic (vs. non-Hispanic white) 0.74 (0.54, 1.01) 0.74 (0.44, 1.26) Other (vs. non-Hispanic white) 0.84 (0.56, 1.26) 2.28 (1.24, 4.21) 2 Less than high school grad. (vs. grad.) 0.97 (0.78, 1.20) 1.08 (0.76, 1.55) Married (vs. single) 0.92 (0.77, 1.10) 1.00 (0.72, 1.39) Residence Rural (vs. urban) 0.77 (0.64, 0.92) 3 0.89 (0.65, 1.23) Frontier (vs. urban) 0.86 (0.66, 1.12) 0.78 (0.48, 1.28) Income $10–20,000 (vs. < $10,000) 1.06 (0.81, 1.39) 0.81 (0.52, 1.26) $21–30,000 (vs. < $10,000) 1.02 (0.75, 1.38) 0.96 (0.57, 1.62) $31,000 and higher (vs. < $10,000) 0.90 (0.67, 1.20) 0.87 (0.52, 1.46) Missing (vs. < $10,000) 0.95 (0.72, 1.25) 0.99 (0.63, 1.56) Health care Insurance Medicare (vs. uninsured) 0.69 (0.41, 1.16) 0.41 (0.19, 0.86) 3 Medicaid (vs. uninsured) 0.72 (0.44, 1.18) 0.35 (0.17, 0.71) 2 Medicare plus other. (vs. uninsured) 0.85 (0.52, 1.39) 0.31 (0.15, 0.64) 2 Other private/gov. ins. (vs. uninsured) 0.64 (0.37, 1.09) 0.34 (0.15, 0.76) 2 No. of physician visits past 6 months 1.02 (1.01, 1.04) 2 1.02 (1.00, 1.03) Physician-driven participation index 0.99 (0.91, 1.06) 1.14 (0.99, 1.30) Patient-driven participation index 0.82 (0.75, 0.89) 3 0.93 (0.80, 1.09) Tenure with doctor Less than 1 year (vs. no personal doctor) 0.92 (0.64, 1.33) 0.51 (0.27, 0.98) 3 1–2 years (vs. no personal doctor) 0.95 (0.70, 1.30) 0.74 (0.43, 1.25) 3–4 years (vs. no personal doctor) 0.87 (0.64, 1.18) 0.56 (0.33, 0.96) 3 5 or more years (vs. no personal doctor) 0.92 (0.71, 1.19) 0.65 (0.42, 0.99) 3 Health status No. of comorbidities 1 (vs. none) 1.06 (0.87, 1.27) 1.18 (0.84, 1.66) 2 (vs. none) 0.96 (0.74, 1.25) 1.50 (0.99, 2.28) 3 or more (vs. none) 1.01 (0.71, 1.43) 1.51 (0.90, 2.50) Ever diagnosed with arthritis (vs. never) 3.62 (3.03, 4.33) 1 1.54 (1.01, 2.35) 3 SF-12 mental component score 0.99 (0.98, 1.00) 0.98 (0.97, 1.00) General health status Excellent (vs. poor) 0.14 (0.09, 0.22) 1 0.49 (0.20, 1.19) Very Good (vs. poor) 0.30 (0.21, 0.41) 1 0.24 (0.14, 0.42) 1 Good (vs. poor) 0.41 (0.31, 0.54) 1 0.33 (0.21, 0.50) 1 Fair (vs. poor) 0.69 (0.52, 0.92) 2 0.56 (0.39, 0.81) 3 1 p < 0.0001, 2 p < 0.01, 3 p < 0.05 note: Analyses of severe pain were limited to those with frequent pain. Physician-driven participation was not significantly associated with the odds of frequent pain. However, elders with higher patient-driven participation had lower odds (OR, 0.82; 95% CI 0.75, 0.89) of frequent pain, confirming our hypothesis that persons who take a more active role in their medical treatment are less likely to experience pain. Individuals who had been diagnosed with arthritis at some point in their lives had a higher odds of frequent pain (OR, 3.62; 95% CI 3.03, 4.33) than those without arthritis. Those who rated their general health as excellent (OR, 0.14; 95% CI 0.09, 0.22), very good (OR, 0.30; 95% CI 0.21, 0.41), good (OR, 0.41; 95% CI 0.31, 0.54), and fair (OR, 0.69, CI 0.52, 0.92) had lower odds of frequent pain than those who rated their health as poor. Multivariate analyses of the odds of severe pain Among those with frequent pain, there were no gender difference in the odds of severe pain. Persons of other race/ethnicity (primarily Black/African Americans) had a higher odds (OR, 2.28; 95% CI 1.24, 4.21) of severe pain than non-Hispanic whites. Income, marital status, rural residence, and frontier residence were not significantly associated with the odds of severe pain. The number of physician visits was not significantly associated with severe pain. However, having insurance had a significant impact on the odds of severe pain. Compared to those without health insurance coverage, those with Medicare (OR, 0.41; 95% CI 0.19, 0.86), Medicaid (OR 0.35; 95% CI 0.17, 0.71), Medicare plus other private or government coverage (OR 0.31; 95% CI 0.15, 0.64), and those with other private or government coverage (OR 0.34; 95% CI 0.15, 0.76) had a significantly lower odds of severe pain. Although physician and patient-driven participation were not significantly related to the odds of severe pain, tenure with one's personal doctor was a significant factor. Elders who had been seeing their doctor for less than 1 year (OR, 0.51; 95% CI 0.27, 0.98), 3–4 years (OR, 0.56; 95% CI 0.33, 0.96), or 5 or more years (OR, 0.65; 95% CI 0.42, 0.99) had lower odds of severe pain than elders who had no personal doctor. As expected, several health status measures were also significant. Those who had arthritis had higher odds of severe pain (OR, 1.54; 95% CI 1.01, 2.35) than those without arthritis. Finally, individuals who rated their general health as very good (OR, 0.24; 95% CI 0.14, 0.42), good (OR, 0.33; 95% CI 0.21, 0.50), and fair (OR, 0.56; 95% CI 0.39, 0.81) had lower odds of severe pain than those who rated their health as poor. Discussion We found that patient-driven participation in decision-making was associated with lower odds of frequent pain, which is supported by previous research indicating that adult patients who are more actively engaged in their treatment have greater reductions in symptoms and improvement in health status [ 27 ], better psychological outcomes [ 28 ], and higher satisfaction with health care [ 29 ]. Thus, to delay or prevent the development of frequent pain, elderly patients may need to initiate discussions about symptoms with their physicians when they first experience them. However, because many elderly patients often defer to the doctor to initiate involvement in medical decisions [ 9 - 15 ], this may prove to be a difficult task. Little research has investigated how to promote active participation in medical care decision-making, but one prior study which involved sharing of a patient's medical record and the delivery of brief education about his/her disease prior to a physician visit demonstrated that patient involvement in decision making increased [ 30 ]. While neither physician nor patient-driven participation in decision making were significantly associated with pain severity, another factor related to the strength of the doctor-patient relationship was significant. In the present study, having a personal doctor, no matter how long the tenure of the relationship was, reduced the odds of severe pain. The finding of a beneficial effect of having a personal doctor, at least in terms of the severity of pain, is consistent with prior studies which have shown that having a usual source of care is positively correlated with an individual's access to the health care system [ 31 - 33 ], satisfaction with medical care [ 34 ], and promotion of proper medication use [ 35 ]. A usual, personal doctor undoubtedly has a more thorough knowledge of a patient's medical history and problems, which could enable him/her to more effectively manage pain treatment and coordinate care with specialists, if necessary. If this is the case, managers and leaders of physician clinics that have a high mix of elderly patients should ensure that patients can visit a regular doctor to promote better pain management. In addition to having a personal doctor, access to any type of health insurance coverage was associated with the odds of severe pain. Approximately 12 percent of persons in the study sample reported that they had no health insurance coverage at all, including Medicare, and 21.5% of those without insurance had severe pain. The percentage of patients in this group with severe pain was nearly 2 times higher than the percentage of patients in the other insurance categories. Many older persons may not be eligible for public health insurance because they have not contributed to the social security system for a minimal amount of time. This may be particularly common in the southwestern United States where there are larger numbers of Hispanic immigrants. Expansion of health insurance coverage to this group could improve their ability to visit physicians and other health providers when they experience pain and, ultimately, lead to better pain management. Further research is warranted to more clearly elucidate how characteristics of different health insurance plans, such as gatekeeping and cost sharing, affect access to physician services for pain treatment. Several demographic indicators were also significantly associated with frequent and severe pain. The gender differences beckon the question of whether medical care providers treat older women's pain less effectively or appropriately than men's. No differences were found between Hispanics and non-Hispanic whites, but other races (the majority of whom were Black/African American) had higher odds of severe pain than non-Hispanic whites. However, because of the heterogeneity of the other racial category, it is difficult to discern which particular racial groups experience severe pain. Research which includes greater numbers of other racial categories is thus warranted. In regard to health status, the results support that individuals with three or more comorbid diseases have a relatively higher odds of frequent pain and severe pain than those with no comorbid diseases. One disease, arthritis, was of particular interest and therefore was treated as a separate variable. Almost two-thirds of the subjects had arthritis, which is not unexpected for persons age 65 and older. Persons with arthritis had a much higher odds (over 3 times the odds) odds of frequent pain than individuals without arthritis. Moreover, those with arthritis had approximately 1.5 times the odds of severe pain. The magnitudes of these associations imply that efforts to more effectively treat arthritis could lead to improvements in pain management. While the present study has contributed to our understanding of the relationship between doctor-patient interactions and persistent pain, it is not without several limitations. Because the study was cross-sectional in design, it is impossible to infer any causal relationships. Although the pain measures were adapted from a nationally representative cohort study of older persons [ 23 ], they may not adequately reflect the frequency, duration, and severity of pain. The generalizability of the findings may be limited to regions of the southwestern United States that are similar in geographic and ethnic makeup, such as Texas, New Mexico, Colorado, Arizona, and California. However, we suspect that the associations found in the present study would hold true among elders residing in other parts of the United States. In summary, future studies should employ longitudinal designs, include more detailed measures of pain and be conducted among other populations. Conclusions Despite these potential limitations, the present study suggests that several strategies could be implemented to limit the incidence and severity of pain among community-dwelling elders. Health policy makers and insurance companies might implement new reimbursement schemes to encourage visits to a personal physicians in order to improve pain and other health outcomes. Managers of physician clinics should consider organizing practices to ensure that older patients are able to make timely appointments with a personal provider. Finally, patients themselves could help reduce their chances of having frequent pain by becoming more involved in their care. These are just a few examples of how changes to the organization and delivery of care might affect pain-related health outcomes. Future research should evaluate how a range of physician characteristics (e.g. specialty and age), physician clinic characteristics (e.g. solo or group practice), insurance characteristics (e.g. HMO, PPO, or FFS coverage), and patient characteristics (e.g. trust in physician) influence pain and pain treatment. Competing interests The author(s) declare that they have no competing interests. Authors' contributions TFB conceived the overall study, performed the statistical analyses, and led the drafting of the manuscript. KTX assisted with the study design, interpretation of statistical findings, and drafting of the manuscript. JH assisted with interpretation of the findings and drafting of the clinical implications. GK contributed to data management, statistical analyses, and drafting of the methods section. All authors read and approved the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC546194.xml
545489	A population-based study of anxiety as a precursor for depression in childhood and adolescence	Background Anxiety and depression co-occur in children and adolescents with anxiety commonly preceding depression. Although there is some evidence to suggest that the association between early anxiety and later depression is explained by a shared genetic aetiology, the contribution of environmental factors is less well examined and it is unknown whether anxiety itself is a phenotypic risk factor for later depression. These explanations of the association between early anxiety and later depression were evaluated. Methods Anxiety and depressive symptoms were assessed longitudinally in a U.K. population-based sample of 676 twins aged 5–17 at baseline. At baseline, anxiety and depression were assessed by parental questionnaire. Depression was assessed three years later by parental and adolescent questionnaire. Results Shared genetic effects between early anxiety and later depression were found. A model of a phenotypic risk effect from early anxiety on later depression provided a poor fit to the data. However, there were significant genetic effects specific to later depression, showing that early anxiety and later depression do not index entirely the same genetic risk. Conclusions Anxiety and depression are associated over time because they share a partly common genetic aetiology rather than because the anxiety phenotype leads to later depression.	Background Anxiety and depressive disorders are some of the most common psychiatric diagnoses in children and adolescents respectively. Both are known to be associated with major impairment in childhood and adverse consequences in later life [ 1 - 4 ]. Estimates of the prevalence of any childhood anxiety disorder are in the order of 3 to 12 % [ 1 , 4 ] and rise to as high as 40% or over if impairment is not required for a diagnosis [ 4 ]. In general, epidemiological studies show that rates of any anxiety disorder are higher in children than adolescents [ 5 ]. In contrast, rates of depressive disorder in young people show higher rates in adolescence (2 to 8 %) than in childhood (1 to 3 %) [ 6 ]. Depression and anxiety in childhood and adolescence have long-term deleterious outcomes for a significant proportion of young people. Depression and anxiety, once experienced in childhood are very likely to recur in adulthood [ 2 , 7 ]. Early onset depressive and anxiety disorders are also associated with substantial social impairment [ 8 ]. Even sub-clinical levels of depression in children and adolescents are associated with significant morbidity in the form of psychosocial impairment and service utilisation [ 9 , 10 ]. Furthermore, adolescents identified as having high levels of depressive or anxiety symptoms are significantly more likely to experience depressive disorder in adulthood than adolescents with depression levels within the normal range [ 11 , 12 ]. The observations that sub-clinical symptoms of depression are associated with significant morbidity, and that high levels of depression and anxiety symptoms predict depressive and anxiety disorders add to the evidence that depression and anxiety can be regarded as continua [ 13 - 15 ]. Depression and anxiety co-occur more commonly than would be expected by chance in children and adolescents. This co-occurrence has been identified both in clinical studies of children and adolescents and general population samples that have examined sub-clinical levels of depression and anxiety symptoms [ 16 , 17 ]. More specifically, anxiety symptoms or disorders most often precede depressive symptoms or disorders [ 18 - 21 ]. Moreover, although certain sub-types of anxiety, namely social phobia and panic rarely precede depression [ 22 ], individuals with these disorders and depression are very likely to have had a different anxiety disorder that predated the onset of depression [ 20 ]. Twin studies provide a means of examining the extent to which the genetic and environmental aetiological factors contributing to two disorders or symptom groups overlap and to what extent they are distinct. Longitudinal data, collected at more than one time point provide a further test, namely, that one set of symptoms or disorder is a risk factor for another. This approach is especially useful in the study of anxiety and depression. Several groups have suggested that anxiety may be a developmental precursor of depression, particularly in young people who are at increased risk of depression due to parental depression [ 23 - 25 ]. Indeed Kovacs & Devlin [ 17 ] suggested that children may be biologically 'prepared' to experience symptoms of anxiety rather than depression. The results of other studies are consistent with this proposal. For example, in a sample of depressed children, in those children who had a comorbid anxiety disorder, the anxiety disorder was found to have preceded depressive disorder in two thirds of cases [ 18 ]. Similar evidence that anxiety disorders tend to precede depression has been reported in longitudinal epidemiological [ 19 , 21 , 26 ] and clinical studies [ 20 ]. Indeed, a recently convened National Institute for Mental Health (NIMH) workgroup recommended research into childhood anxiety as a known precursor of depression as a priority [ 27 ]. Despite clear indications that anxiety and depression in childhood and adolescence are associated, it remains unclear as to how the transition from anxiety to depression is mediated over time. Possible factors include aetiological factors in common – these may be 1) genetic or 2) psycho-social risk factors, or 3) a direct risk effect of anxiety leading to later depression. Cross-sectional twin studies of children [ 28 , 29 ] and adults [ 30 ] and one longitudinal twin study of girls [ 31 ] have shown that to a large extent, the overlap between anxiety and depression is due to a common set of genes that influence both depression and anxiety. However, shared environmental factors have also been shown to be important sources of covariation between anxiety and depression symptoms for children but not adults [ 28 , 31 ] which suggests the importance of shared psycho-social risk factors for anxiety and depression. Nevertheless, two out of these three twin studies were based on cross-sectional data and were therefore not able to determine the genetic and environmental associations between anxiety and depression over time. Furthermore, despite the importance of understanding why anxiety tends to precede depression, [ 27 ] no twin study of children and adolescents has yet specifically tested the hypothesis that anxiety is a phenotypic risk factor for depression. The present study also adds to the existing literature in that data on depression symptoms from different raters (mother and child) are available, thus allowing associations to be examined with data from different informants. In the present study, we set out to examine two hypotheses that may explain the observed associations between early anxiety and later depression. 1. Early anxiety symptoms and later depression symptoms are associated because of shared risk factors. 2. The association between anxiety symptoms and later depression symptoms is mediated by a risk effect of the phenotype of anxiety. Method Participants Families from a systematically ascertained, population-based register of all twin births between 1980 and 1991 in South Wales, U.K. were invited to participate. This register forms a sub-sample of the Cardiff Study of All-Wales and North West of England Twins (CASTANET). Twins who had emigrated were excluded, as were cases in which one of the twins had died or had a serious illness. At the first wave of data collection in 1997, there were a total of 1109 pairs of twins aged 5–17 years although not all of these individuals were eligible to participate at both time points (see below). Data were collected by postal questionnaire. Families received three reminders and telephone reminders when numbers could be traced. The same methods were used three years later to collect longitudinal data except that families received four reminders. To be invited to participate in the follow-up study, we required that the twins were living together in the same home and were under the age of 18 years. Twins were required to live in the same home in order to minimise heterogeneity of environmental risk factors that can impact on genetic and environmental parameter estimates. The focus of the follow-up study was childhood psychopathology and for that reason young people aged 18 and over were not included. At time 1, there were 986 twin pairs who were within the age range of the study at both time points. In the first wave of the study (1997; time 1), 670 families provided questionnaire responses giving a response rate of 61%. Comparison of responders and non-responders using Townsend Scores [ 32 ] which index the level of deprivation of an electoral area revealed no significant socio-demographic differences between the two groups at time 1 (t = .373, p = 0.709). Families with children aged 8–17 were re-contacted in 2000 (time 2). Of the 670 families who replied at time one, 85 had moved away, there were 8 new contraindications and there were 123 children who were out of the age range of the study and did not live in the same home. This left a total of 454 families who were eligible at time 2. Of these, 338 families replied, giving a total response rate of 75%. There were no significant socio-demographic differences between responders and non-responders at time 2 (t = 1.71, p = 0.09). Zygosity was assigned using a twin similarity questionnaire which has been shown to be over 90% accurate in distinguishing identical (monozygotic; MZ) from fraternal (dizygotic; DZ) twins [ 33 ]. There were 198 MZ girls (99 pairs), 134 MZ boys, 128 DZ girls, 116 DZ boys, 270 opposite sex DZ twins. Measures At time 1, parents were asked to complete the Children's Revised Manifest Anxiety Scale [ 34 ] which assesses symptoms over the past three months. It has previously been found to be a reliable and valid instrument [ 35 ] (Cronbach's α = .8662 twin 1, α = .8708 twin 2). Parents also completed the general functioning scale of the McMasters Family Assessment Device (FAD) [ 36 ]. At both time points, parents completed the short version of the Mood and Feelings Questionnaire (MFQ) [ 37 ]. At the second wave children aged 11 or above also completed the MFQ. The MFQ is based on DSM-III-R symptoms of depression and has been successfully used as a screening questionnaire for clinical depression in community populations [ 38 ] (α = .9231 twin 1, α = 9320 twin 2). Analysis Descriptive statistics For descriptive statistics, (correlations and mean comparisons), the survey commands in the program STATA [ 39 ] were used. These commands take into account the clustering of the data from twin pairs (i.e. each twin pair provides two data points) by likening the twin data to a two-stage cluster design with the twin pairs as the primary sampling unit. Since reliability coefficients can not be calculated using these commands these were presented for first and second-born twins separately. Univariate Analysing data from twins provides a means of estimating the relative contribution of genetic and environmental effects on individual variation in behaviour. In the basic (ACE) model, variation can arise from three sources: 1) additive genetic effects (A); 2) common environmental effects (C); 3) unique environmental effects (E). Common environmental effects are non-genetic factors that serve to make twins more similar to one another while unique environmental effects are non-genetic factors that uniquely influence one individual within a twin pair and tend to make the individuals in a twin pair different from each other. Model fitting was carried out using the programs Mx [ 41 ] and LISREL [ 42 ] and continuous measures of anxiety and depressive symptoms were analysed. The significance of the A, C and E parameters can be tested by dropping them from the model and comparing the fit of the reduced model to that of the full model using the χ 2 critical value for the number of degrees of freedom gained in the reduced model. Bivariate Bivariate analysis allows the covariance of two traits to be partitioned into covariance that is due to additive genetic factors, common environmental factors and unique environmental factors. The covariance parameters for the Cholesky model presented (see figure 1 ) include those factors in trait 1 (anxiety) that also influence trait 2 (depression). A bivariate model in which anxiety symptoms at time 1 precede depressive symptoms at time 2 was fitted consistent with clinical and epidemiological data showing that anxiety precedes depression more often than vice versa. In addition, a 3 variable model that included anxiety and depressive symptoms at time 1 and depressive symptoms at time 2 was fitted. This model estimated the genetic and environmental associations between anxiety at time 1 and depression at time 2 when the effects of concurrent depression were included. A causal model was then fitted (see figure 2 ). Comparing the fit of this causal model to that of the general bivariate (Cholesky) model allows two competing explanations of the association between anxiety (time 1) and depression (time 2) to be tested: 1) the association of anxiety and depression is due to genetic and /or environmental risk factors common to both anxiety and depression: 2) the association is due to a risk effect of the phenotype of early anxiety on later depression. A unidirectional causal model from anxiety to depression was fitted given that the data presented are longitudinal. Although the reliabilities of the anxiety and depression scales were good and comparable, a causal model that included residual error was included in line with the suggestion of Neale & Cardon [ 43 ]. This was fitted since in direction of causation models it cannot be assumed that measurement error will be confounded with non-shared environmental effects [ 44 ]. Fitting this type of model does not constrain measurement error to be transmitted phenotypically and thus is likely to provide more realistic parameter estimates than a casual model without residual error terms. Figure 1 Bivariate Cholesky decomposition of anxiety at time 1 and depression at time 2. Aanx genetic influences on anxiety Canx common environmental influences on anxiety Eanx non shared environmental influences on anxiety Ac genetic influences on anxiety that also influence depression Cc common environmental influences on anxiety that also influence depression Ec non shared environmental influences on anxiety that also influence depression Adep genetic influences specific to depression Cdep common environmental influences specific to depression Edep non shared environmental influences specific to depression Figure 2 Unidirectional causal model from anxiety at time 1 to depression at time 2 Aanx genetic influences on anxiety Canx common environmental influences on anxiety Eanx non shared environmental influences on anxiety Adep genetic influences specific to depression Cdep common environmental influences specific to depression Edep non shared environmental influences specific to depression Sex effects Univariate analyses were performed to test for both quantitative and qualitative sex differences. Quantitative sex differences, are tested by estimating the size of parameter estimates for the genders ('the common effects sex limitation model'). Qualitative sex differences test whether the set of genes influencing the phenotype differs by gender i.e. different genes ('the general effects sex limitation model'), this is done by estimating the genetic correlation for opposite sex DZ pairs and comparing the fit of this model to one that constrained the genetic correlation to 0.5. In addition, a bivariate sex limitation model was tested [ 45 ]. This model estimates whether the covariation between anxiety and depression is different for boys and girls. All analyses reported were based on the five twin groups (MZ male, MZ female, DZ male, DZ female, DZ opposite sex). Results Descriptive statistics There were no significant mean differences on anxiety or depressive symptoms by gender (t = -0.047, p = .962; t = -1.628, p = .104). Age was not associated with anxiety or depressive symptoms (r = .014, p = .707; r = .082, p = .078). The mean age of children at time 1 was 10.58, range 5.58–17.83, and at time 2, was, 12.64, range 8.75–17.25. Symptoms of early anxiety and later depression were strongly correlated (parent-rated symptoms r = .479. The correlation was slightly lower for symptoms across rater (parent rated anxiety and adolescent rated depression), r = .335. Sex effects For anxiety, univariate analysis of parent-rated data showed no significant gender differences in the magnitude of genetic parameter estimates (Δ χ 2 = 1.505, Δ df = 3), nor were there qualitative genetic differences (Δ χ 2 = 0, Δ df = 1). For depression, univariate models for parent-rated and self-rated scores indicated no significant gender effects for the magnitude of genetic effects (parent rated, Δ χ 2 = 2.679, Δ df = 3; self-rated, Δ χ 2 = 0.586, Δ df = 3) nor qualitative gender differences (parent rated, Δ χ 2 = 0, Δ df = 1; self-rated, Δ χ 2 = 0, Δ df = 1). Finally, for parent rated symptoms, results from the bivariate sex limitation Cholesky model showed no significant gender differences in the covariation between anxiety and depression in that the genetic and environmental covariation could be equated across the genders with no significant deterioration in fit (parent-rated, Δ χ 2 = 0.445, Δ df = 3). However, for self-rated symptoms, one parameter, i.e., the non-shared environmental covariation parameter, could not be equated across the genders (Δ χ 2 = 6.107, Δ df = 1). Estimates from this model for boys were; Aanx = 50, Canx = 17, Eanx = 32, Ac = 10, Cc = 47, Ec = -11, Adep = 9, Cdep = 5, Edep = 40; and for girls were; Aanx = 47, Canx = 22, Eanx = 30, Ac = 12, Cc = 13, Ec = 8, Adep = 30, Cdep = 12, Edep = 24; χ 2 = 30.93, df = 32, AIC = -33.07). These results are presented in addition to those for the combined sample (see table 1 ). Table 1 Bivariate model fitting for time 1 anxiety and time 2 depression Rater Aanx Canx Eanx Ac Cc Ec Adep Cdep Edep χ 2 AIC Parent rated total sample NMZ = 138 NDZ = 210 46* 24* 30* 13 36*** 2 ns 24* 0 ns 26* 15.36 df = 11 -6.64 Parent rated – adolescents only (8–14 at time 1 and 11–17 at time 2) NMZ = 90 NDZ = 136 46* 23 31* 11* 34** 4 ns 25* 0 ns 25* 15.02 df = 11 -6.98 Parent rated anxiety time 1 and self rated depression time 2 NMZ = 92 NDZ = 128 53* 15 ns 32*** 13* 17 ns 2 ns 36 0 ns 31* 5.80 df = 11 -16.20 Ns = non significant * p = .05 p = .01 * p = .001 Aanx genetic influences on anxiety Canx common environmental influences on anxiety Eanx non shared environmental influences on anxiety Ac genetic influences on anxiety that also influence depression Cc common environmental influences on anxiety that also influence depression Ec non shared environmental influences on anxiety that also influence depression Adep genetic influences specific to depression Cdep common environmental influences specific to depression Edep non shared environmental influences specific to depression NMZ = number of MZ twin pairs NDZ = number of DZ twin pairs Parameter estimates equated to sum 100 in direction of arrows on each trait (anxiety time 1 & depression time 2) Bivariate analysis Table 1 shows results from bivariate analyses of anxiety and depression. Both the genetic covariation (Ac) between anxiety and depression as well as the common environmental covariation (Cc) were significant, while unique environmental covariation (Ec) was negligible. However, despite significant covariation, there were also significant genetic (Adep) and unique environmental effects (Edep) specific to later depression. Thus, although significant genetic covariation between anxiety and depression was observed, the genetic effects on depression were not entirely mediated through genetic effects that were common with anxiety. This illustrates that the genetic covariation between anxiety and depression over time is not complete. Moreover, this observed genetic covariation does not appear to derive from the association of early depression with later depression in that the genetic covariation between anxiety and later depression remained significant when early depressive symptoms were included in the model (see figure 3 ). Figure 3 shows that there is a significant genetic path linking early anxiety and later depression (Ac (anx1 dep2) = 11, p = .001). Figure 3 Trivariate Cholesky decomposition of anxiety at time 1, depression at time 1 and depression at time 2 χ 2 = 39.74, df = 24, AIC = -8.26 Ns = non significant * p = .05 p = .01 * p = .001 Parameter estimates equated to sum 100 in direction of arrows on each trait (anxiety time 1, depression time 1 & depression time 2) It has been shown that the aetiology of depression varies significantly according to age, with greater common environmental effects in children aged 8–10 than in adolescents aged 11–17 [ 28 , 46 , 47 ]. The three year follow-up period of the study meant that we were unable to analyse children's and adolescent's symptoms separately. However, given previous findings of age effects, we carried out analyses including only those twins who were 'adolescents', that is, aged 11 or over at the second time point with the expectation that the common environmental covariation path (Cc) might decrease. Nonetheless, a significant common environmental component of variance remained. Family functioning and rater effects Following this finding of significant common environmental covariation the nature of this latent factor was further examined. Information on a potential common environmental variable, general family functioning (all twins lived in the parental home) was available. Family functioning was correlated with anxiety symptoms at time 1 (r = .210, p = .001). Bivariate analyses controlling for family functioning are shown in table 2 and it can be seen that this exerted only a slight effect on the estimate of common environmental covariation (drop of Cc from .36 to .31). However, associations between anxiety and depression symptoms could be due to the fact that a single informant (parents) rated their children's anxiety and depression symptoms at both time points. In bivariate analyses, similarities between variables that are due to shared rater effects will be partitioned into the common environmental component of covariance. A distinction should be made here between shared rater effects and rater bias. Rater biases that result in common environmental effects arise when a proxy informant, usually a parent rates a pair of twins as more similar than more objective measures would find them. This sort of rater bias results in deflated MZ phenotypic variance compared to DZ variance [ 43 ]. This pattern of variance has not been observed in this sample (anxiety DZ standard error = .035, MZ standard error = .048, t = 1.89, p = .06; depression DZ standard error = .056, MZ standard error = .067, t = .514, p =.608), in fact the MZ variance is greater than the DZ variance. Thus, rater bias can not account for the observed common environmental effects. On the other hand, shared rater effects come about simply as an effect of the same informant rating two sets of symptoms or risk variable and outcome and are therefore not exclusive to parental ratings. In order to test any potential shared rater effects, a bivariate model with data from different informants was tested (parent-rated anxiety symptoms at time 1 and adolescent-rated depression symptoms at time 2). It can be seen from Table 1 that the common environmental covariance influencing anxiety and depression (Cc) is no longer significant when cross-informant information is used. This suggests that at least a proportion of the Cc estimate observed in analyses that used only parent-rated data is likely to be due to shared rater effects, i.e. that part of the shared environmental covariation is due to the fact that the same informant rated both phenotypes. The observation that when family functioning was included as a measured environmental variable in the analyses of parent-rated information, the common environmental covariance estimate was only slightly reduced is consistent with the possibility that these Cc effects may be due to shared rater effects. However, given the small effect sizes of most single measured risk factors (genetic or environmental) [ 48 ], one might not expect single environmental risk factors to account for large proportions of variance. Indeed, risk variables for symptoms of depression and anxiety are likely to have multiplicative effects [ 48 , 49 ]. With this in mind, the same family functioning was also included in a cross-informant model. As can be seen from table 2 , including family functioning resulted in a small decrease in the Cc estimate (17 to 14). Table 2 Bivariate model fitting for time 1 anxiety and time 2 depression controlling for measured environmental variables Rater Aanx Canx Eanx Ac Cc Ec Adep Cdep Edep χ 2 AIC Parent rated total sample - family functioning at time 1 regressed out 47* 21 32* 12 31** 1 ns 24* 0 ns 26* 12.59 df = 11 -9.41 Parent rated anxiety and self rated depression - family functioning at time 1 regressed out 56* 11 ns 33*** 14* 14 ns 2 ns 38 0 ns 33* 6.75 df = 11 -15.25 Ns = non significant * p = .05 p = .01 * p = .001 Aanx genetic influences on anxiety Canx common environmental influences on anxiety Eanx non shared environmental influences on anxiety Ac genetic influences on anxiety that also influence depression Cc common environmental influences on anxiety that also influence depression Ec non shared environmental influences on anxiety that also influence depression Adep genetic influences specific to depression Cdep common environmental influences specific to depression Edep non shared environmental influences specific to depression NMZ = number of MZ twin pairs NDZ = number of DZ twin pairs Parameter estimates equated to sum 100 in direction of arrows on each trait (anxiety time 1 & depression time 2) Phenotypic "causal" model Finally, a model that included a direct causal path from anxiety to depression was fitted (see figure 2 ). This model allows for testing whether the phenotype of anxiety (rather than shared genetic and environmental aetiological factors) was responsible for the observed covariance between anxiety and later depression symptoms. That is, testing whether anxiety (independent of shared genetic and environmental risk factors) is itself an early risk factor for depression. The full causal model provided a significantly poorer fit than the general bivariate model (Δ χ 2 = 48.82, Δ df = 1, p < .001). Thus, it does not appear that anxiety leads to depression through direct phenotypic effects, but that, anxiety and depression symptoms are associated over time because they share aetiological factors in common. Discussion This investigation has used a longitudinal, epidemiological and genetically sensitive design to examine two possible explanations of the association between early anxiety and later depression symptoms in children and adolescents: 1) a common genetic/environmental aetiology or 2) a phenotypic risk effect of early anxiety. There was significant genetic covariation between anxiety and later depression. (Moreover, the genetic covariation was not explained by the effects of early depression). This result is consistent with the association between early anxiety and later depression being due to a common genetic aetiology. However, the genetic overlap between early anxiety and later depression was far from complete in that there were significant, separate genetic effects on anxiety and genetic influences specific to later depression. Thus, in this sample, symptoms of anxiety and depression in children and adolescents share only a partly common genetic aetiology. In addition to genetic covariation, significant shared environmental covariation between anxiety and depression was also observed. It appeared that some of the shared environmental covariation between anxiety and depression observed in parent ratings of anxiety and depression was due to shared rater effects as the common environmental covariation (Cc) was no longer significant when analyses were performed with data across different informants. However, including family adversity as a measured environmental risk factor into a model with data from different informants also resulted in a small decrease in the Cc parameter estimate. The model that included a direct causal path from early anxiety symptoms to later depression symptoms provided a significantly poorer fit than the general bivariate model. These results suggest that anxiety is not an aetiologically distinct phenotype that is in itself a risk factor for future depression symptoms, but rather that the covariation over time arises from the common genetic and environmental architecture. It should be noted though, that some of the common environmental covariation is likely due to shared rater effects, because we found that this path became non significant in cross-informant analyses. The present findings are consistent with those of several other twin studies that have reported strong genetic correlations between symptoms of anxiety and depression in children and adolescents [ 28 , 29 , 31 ] and adults [ 30 ] and with a study that found significant genetic effects specific to depression [ 29 ]. However, only one of these studies was longitudinal [ 31 ] and this included girls only, and none of these studies included information from more than one informant. Sex effects The lack of significant univariate and bivariate gender differences in genetic and environmental parameters estimates for parent reports in the present sample is of interest. The results for self reports of depression are less clear, previous analysis of a larger sample, from which the present sample was drawn, did find sex differences for self rated depressive symptoms as measured by the long version of the Mood and Feelings Questionnaire (MFQ) [ 47 ], which were not detected in the present sample. However, a previous cross-sectional analysis of the full time 1 self-rated depression data did not find significant gender differences [ 54 ]. The only significant gender difference in the present analysis was for the non-shared environmental covariation between anxiety and self-rated depression. The lack of significant effects for univariate analysis for self-rated depression may be due to the smaller sample size and thus lower power to detect effects in the present sample, or it could be due to the fact that different versions of the MFQ that were used in the present (short version) and a previous analysis (long version) [ 47 ]. Moreover, the bivariate Cholesky sex limitation analysis for self-reported depression was likely under-powered as few of the parameter estimates reached statistical significance. The sample size is small for those who provided self-reports (NMZ = 92 and NDZ = 128, see table 1 ) and it is therefore uncertain how reliable these results are. The non-shared environmental covariation estimate for boys also yields a negative parameter estimate (-.11) (albeit non-significant) which indicates the non-shared environment for anxiety is negatively correlated with the non-shared environment for depression. This finding is difficult to interpret, further suggesting caution in conferring too much confidence to the gender-specific findings in this model. Given the sample size for cross informant models in this study, it is not safe to draw firm conclusions about gender differences in the covariance of anxiety and depression when depression is self rated. This needs to be examined in a larger sample. However, although the prevalence of depression shows gender differences in adolescence, this does not necessarily suggest gender differences in aetiology. How do the present findings fit with results from family studies? Several family studies of the offspring of depressed parents have found increased rates of anxiety rather than depressive disorders [ 23 , 25 ] and Rende and colleagues [ 24 ] found that sibling resemblance for anxiety disorders was increased in the offspring of depressed parents. This familial aggregation of anxiety disorders could be due to common environmental or genetic factors. There is now consistent evidence from cross-sectional and longitudinal twin studies of children and adolescents that this observed familial association between anxiety and depression symptoms has a partly common genetic aetiology. Limitations As mentioned previously, several groups have shown that the aetiology of depressive symptoms differs between children (8–10) and adolescents (11–17) [ 28 , 46 , 47 ]. The majority, though not all, of the present sample were 'children' aged under 10 (range 5–14) at time 1 and 'adolescents' aged 11 and above (range 8–17) at time 2. Thus, as there is age heterogeneity in aetiology, high levels of effects specific to each time point might be expected such as shown in the present study. Nonetheless, we might not expect to find complete genetic overlap between anxiety and depression. For instance, the genetic liability to depression and antisocial behaviour in children and adolescents has also been shown to overlap [ 50 ]. Thus, there may be different developmental pathways to depressive symptoms in adolescence. In addition, previous studies have suggested that gene-environment correlation [ 51 , 52 ] and gene-environment interaction [ 49 , 53 ] involving life events also contribute to genetic variance in adolescent depression and such effects would also be subsumed within the estimate of genetic variance. Clinical implications Anxiety and depressive symptoms are strongly associated over time. This association does not appear to be due to a phenotypic risk effect of early anxiety. Rather, early anxiety and later depression are associated due to a common aetiology. This was primarily a common genetic aetiology although family functioning and a single informant rating on both sets of symptoms also contributed to this association. Some of the common genetic aetiology may act as indirect genetic effects via behaviour (gene-environment correlation and gene-environment interaction). Competing interests The author(s) declare that they have no competing interests. Author contributions AT and FR conceived the paper. FR carried out statistical analysis and wrote the paper. AT and MBM wrote and edited the paper. MBM provided statistical support. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here:	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545489.xml
314462	Science on the Rise in Developing Countries	The disparity in the scientific output between developed and developing counties is dramatic, but, as the Americas show, this grim picture is improving	Kofi Annan, the Secretary-General of the United Nations, recently called attention to the clear inequalities in science between developing and developed countries and to the challenges of building bridges across these gaps that should bring the United Nations and the world scientific community closer to each other ( Annan 2003 ). Mr. Annan stressed the importance of reducing the inequalities in science between developed and developing countries, asserting that “This unbalanced distribution of scientific activity generates serious problems not only for the scientific community in the developing countries, but for development itself.” Indeed, Mr. Annan's sentiments have also been echoed recently by several scientists, who present overwhelming evidence for the disparity in scientific output between the developing and already developed countries ( Gibbs 1995 ; May 1997 ; Goldemberg 1998 ; Riddoch 2000 ). For example, recent United Nations Educational, Scientific, and Cultural Organization (UNESCO) estimates ( UNESCO 2001 ) indicate that, in 1997, the developed countries accounted for some 84% of the global investment in scientific research and development, had approximately 72% of the world researchers, and produced approximately 88% of all scientific and technical publications registered by the Science Citation Index (SCI). North America and Europe clearly dominate the number of scientific publications produced annually, with 36.6% and 37.5%, respectively, worldwide ( UNESCO 2001 ). North America and Europe clearly dominate the number of scientific publications produced annually. It is rather obvious that richer countries are able to invest more resources in science and therefore account for the largest number of publications. It is also likely that there is a statistical bias on the part of the SCI as a bibliometric database, since it represents North American and European publications far better than those of the rest of the world ( Gibbs 1995 ; May 1997 ; Alonso and Fernández-Juricic 2001 ; Vohora and Vohora 2001 ). But is the disparity in scientific contributions between the developed and developing worlds actually remaining unchanged or even increasing, as Mr. Annan has implied? A closer look at the trends over the last decade reveals important advances in developing countries. For example, Latin America and China, although representing, respectively, only 1.8% and 2% of scientific publications worldwide, have increased the number of their publications between 1990 and 1997 by 36% and 70%, respectively, which is a much higher percentage than the increments reached by Europe (10%) and industrial Asia (26%). The percentage of global scientific publications from North America actually decreased by 8% over the same period ( UNESCO 2001 ). Publishing Trends in the Americas Using the SCI databases produced by the Institute for Scientific Information (ISI), as well as data compiled by the Red Iberoamericana de Indicadores de Ciencia y Tecnología (RICYT), we examined the differences in the number and proportion of scientific publications between the developed world and the developing world from 1990 until 2000, focusing on the Americas as a case study. Not surprisingly, there was a huge disparity in the number of publications from 1990 until 2000, with the United States contributing the lion's share (84.2%), followed by Canada (10.35%). Latin America as a whole contributed only 5.45% to the total number of scientific publications in these ten years ( RICYT 2002 ). The total number of publications, however, is not necessarily the best measure for assessing scientific productivity or technical advances ( May 1997 ). More relevant measurements for these factors include the proportional change in the number of publications and the total number of publications when corrected for investment in research and development ( May 1997 ). The proportional change in the number of publications, using 1990 as a comparison, revealed that scientific publishing in Latin America increased the most rapidly in the Americas, far outpacing the United States and Canada ( Figure 1 ). Further analyses, correcting the number of overall publications for the amount of money invested in research and development for each region, also show that, in contrast to both Canada and United States, the trend in Latin America has been an increase in relative output throughout the 1990s ( Figure 2 ). Moreover, when taking into account the amount of research money available to researchers, Latin America actually out-published the United States and Canada by the year 2000 ( Figure 2 ). Although the cost of research is undoubtedly cheaper in the developing world due to relatively low researcher salaries, overhead and other work standards, these factors do not explain the substantial increase in the number of publications per amount of money allocated to research and development in Latin America, particularly from 1995 until 2000 ( Figure 2 ). Figure 1 Relative Increase in Scientific Publications in the Americas This figure shows the relative increase in publication in the Americas measured as the proportional change (%) in the number of SCI publications compared with the number of publications in 1990 ( RICYT 2002 ). Figure 2 Number of SCI Publications per Million Dollars This figure shows the number of SCI publications per million dollars that are invested in research and development in the Americas ( RICYT 2002 ). Other relative indicators of scientific productivity, such as the number of publications picked up by the SCI in relation to the number of scientists in a particular country, also demonstrate that such developing regions as Latin America are making substantial contributions to science, despite the fact that the average proportion of gross domestic product (GDP) invested in science in Latin America throughout this 10-year period was only 21% of the amount invested in United States ( RICYT 2002 ). Indeed, this scientific productivity is remarkable when we compare it with the relatively low investment in science itself as compared with the GDP of Latin America as a whole. In fact, Albornoz (2001) concluded that, as a group, Latin America could afford to invest a much higher proportion of its resources in scientific research and development. Latin American investment in research and development represented only 0.59% of the regional GDP in 1998, a very weak effort compared with that of the United States (2.84%) and Canada (1.5%). Among Latin American countries, there is a high degree of variability in publication rate as well as in financial investment in science and technology. Some countries have performed particularly well. For example, Uruguay, Chile, Panama, and Cuba averaged, respectively, 6.8, 5.3, 5.2, and 3.4 publications per million dollars of research and development investment in the 10 years studied, which is notoriously high compared with United States (1.5) and even Canada (3.3) ( RICYT 2002 ). Other countries, such as Costa Rica, Cuba, Brazil, and Chile, have invested a much greater proportion of their GDP in research and development than the other countries of this region ( Albornoz 2001 ). Why has the number of publications per dollar invested in research and development been increasing in Latin America while decreasing in United States and Canada? Explaining the Increase in Publishing Productivity in Latin America One potential explanation for the increase in scientific productivity in Latin America is that scientific development during the 1990s was particularly strong for many countries of this region. Indeed, this would explain the rapid rise in the number of publications in Latin America compared with the relatively flat increases in the United States and Canada, which were publishing just as well at the beginning of the decade. A potentially more important question, however, is why the number of publications per dollar invested in research and development has been increasing in Latin America while decreasing in the United States and Canada. This pattern could be the result of a variety of factors, none of which are mutually exclusive. It is possible that publishing in international journals as a measure of scientific productivity is becoming more important in Latin America. Increased funding to the most productive scientists from the national science development programs might have been an important stimulus. International cooperation resulting in more scientific collaborations among scientists in Latin America, Europe, and the United States may also have increased the relative number of publications in Latin America. In contrast, the decreasing trends in the number of publications per investment dollar in Canada and United States could reflect a trend towards more costly research in larger scientific programs. Scientific Impact from Latin America What, exactly, is the relative impact of such developing regions as Latin America on the scientific community? We used SCI 2001 data to examine the proportion of publications in the area of ecology (including the fields of evolutionary biology, conservation biology, and global change biology) between 1990 and 2002 in both the two top general science journals ( Nature and Science ; with impact factors of 27.96 and 23.33, respectively) and in the 20 top ecological journals (with impact factors of 10.51–2.47) ( ISI 2001a ). We credited a region with a publication if any of the authors were affiliated with institutions from that region. Thus, more than one region would receive credit for a single publication if that publication had been written by multiple authors from institutions of different regions. For the top 20 ecological journals, the American subcontinents of South, Central, and North America accounted for 62% of the publications worldwide. Within the Americas, however, Latin America represented only 6%, while Canada and United States accounted, respectively, for 13% and 82% of the top 20 ecological publications. When we examined the data as contributions to the top 10 ecological journals (impact factors 10.51–3.31) versus the top 11–20 (impact factors 3.28–2.47), the Latin American countries contributed nearly twice as many publications to journals in the second category (8% in the top 11–20 compared with 4% in the top 10). These findings suggest that publications from such developing regions as Latin America are falling short of reaching the top journals. In contrast, the United States contributed somewhat more publications to the top 10 journals (84%) than the top 11–20 journals (79%). The difference in the proportion of publications contributed by the United States to the top 10 and top 20 journals was even more pronounced when we examined it in respect to worldwide publications. In this case, the United States contributed 60% of the publications to the top 10 journals and only 40% of the publications to the top 11–20 journals. Interestingly, the proportion of publications from Latin America, the United States, and Canada across all subject areas in Science and Nature were nearly identical to those of the top 20 ecological journals. In Science and Nature , Latin America had 7% of the publications within the Americas versus 6% in the top 20 ecological journals, whereas the United States and Canada had 81% versus 82% and 12% versus 13%, respectively. These similarities suggest that the Latin American researchers are not shying away from the two top-ranked general science journals. However, publishing in Science and Nature was not enough to gain prominence, as evidenced by the number of citations of these researchers. The latest list of the 247 most-cited researchers in ecology and environmental sciences emphasizes the overwhelming contributions of authors from North America (73%) and Europe (21%) ( ISI 2001b ). No researcher working in a Latin American institution was included in the remaining 6%. Overall, these data indicate that the scientific output in the field of ecology in Latin America is having a relatively low impact in the international scientific community and is underrepresented in the top international journals, despite its robust productivity as measured by the number of publications per researcher funding amount. Similar findings were also reported for Asia ( Swinbanks et al. 1997 ) and thus could be a general phenomenon in the developing world. Although there are outstanding scientific researchers in the developing world who independently are making important contributions to the international scientific community, they are the exception. Why, in general, do Latin American scientists often fail to reach the top journals or become amongst the most cited researchers in their fields? One possibility is that the main research agendas between both regions are somewhat different and that the top journals, which are published in the developed world, respond more to the scientific mainstream of the developed regions. This is not to suggest any sort of conspiracy, but rather it implies that the perception of the most important science is linked to the region and that because the major funding agencies as well as most prominent journals share a similar economic region, they also share the same perception of what science is most interesting to them. Another consideration is that more local journals from developed regions are listed by the SCI than similar journals from developing regions ( Gibbs 1995 ). Consequently, there are more high-profile regional publication opportunities available to scientists from the developed region, whereas much of the research published locally in the developing world is overlooked. But it takes more than publishing good papers to become a highly cited scientist. It requires attending international meetings and introducing novel research findings in multiple scientific forums. Funding these activities, however, requires a greater proportion of research money being spent on meetings for researchers in the developing compared with the developed world. A Long Road Yet to Travel The positive trends in scientific productivity in Latin America should not be misinterpreted as a reason to be unconcerned about the existing gap highlighted by Mr. Annan. There are many compelling reasons for the push to increase scientific input from the developing world ( Goldemberg 1998 ; Annan 2003 ). One is that science, as a discipline, would benefit from the contributions of many disparate groups around the world, rather than being dominated by two geographic regions. Many scientific problems could be solved much more readily with the cooperation and scientific insight of scientists from developing regions. Climate change and biodiversity research, for example, urgently need the scientific input from those developing regions that are so important for these global processes. It is also critical for the developing world to promote, through research and publications, those areas of concern that are having a proportionally greater scientific and social impact upon them. There are now examples in which research on priority areas for the developing nations can actually become pioneering work in areas neglected by the research agenda of the industrialized world. This has been the case for research on renewable energy sources in Brazil ( Goldemberg 1998 ) and biomedical sciences in Cuba ( Castro Díaz-Balart 2002 ). These examples are important not only for those regions of the developing world, but are also in themselves scientific innovations that can greatly advance the knowledge of the rest of the world. Climate change and biodiversity research urgently need the scientific input from those developing regions that are so important for global processes. Although the evidence presented here demonstrates that there is a long way to go before developing countries contribute a more equitable share to the international scientific community, there are also reasons to be optimistic. The relative increase in the number of publications, especially when corrected for the amount of money available in research and development, demonstrates that many developing countries are heading in the right direction. The extremely high scientific productivity of many developing nations, corrected for and despite the rather limited availability of funds, suggests that increased funding to the sciences will be an excellent investment by developing nations in terms of publications as a measure of scientific output, particularly if these publications can target the journals that have the greatest impact. Although there may still be a long road to travel, we feel optimistic that the bridges mentioned by Mr. Annan are slowly being built.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC314462.xml
515296	A supertree approach to shorebird phylogeny	Background Order Charadriiformes (shorebirds) is an ideal model group in which to study a wide range of behavioural, ecological and macroevolutionary processes across species. However, comparative studies depend on phylogeny to control for the effects of shared evolutionary history. Although numerous hypotheses have been presented for subsets of the Charadriiformes none to date include all recognised species. Here we use the matrix representation with parsimony method to produce the first fully inclusive supertree of Charadriiformes. We also provide preliminary estimates of ages for all nodes in the tree. Results Three main lineages are revealed: i) the plovers and allies; ii) the gulls and allies; and iii) the sandpipers and allies. The relative position of these clades is unresolved in the strict consensus tree but a 50% majority-rule consensus tree indicates that the sandpiper clade is sister group to the gulls and allies whilst the plover group is placed at the base of the tree. The overall topology is highly consistent with recent molecular hypotheses of shorebird phylogeny. Conclusion The supertree hypothesis presented herein is (to our knowledge) the only complete phylogenetic hypothesis of all extant shorebirds. Despite concerns over the robustness of supertrees (see Discussion), we believe that it provides a valuable framework for testing numerous evolutionary hypotheses relating to the diversity of behaviour, ecology and life-history of the Charadriiformes.	Background The shorebirds and allies (Aves: Charadriiformes; [ 1 ]) present an exceptional group for studying numerous evolutionary hypotheses. Their remarkable diversity of social mating system, parental care, sexual dimorphism, ecology and life-history make them an ideal group for unravelling the mechanisms of, for example, sexual selection and sexual conflict. Previous comparative studies have made significant contributions to our understanding of the evolution of mating systems [ 2 ], parental care [ 3 , 4 ], sexual size dimorphism [ 5 - 7 ], locomotion and morphology [ 8 ], migratory behaviour [ 9 ], egg size [ 10 ], and plumage colouration [ 11 ]. The importance of phylogeny in cross-species comparative studies is well documented [ 12 - 14 ]. Large and well-resolved phylogenies that incorporate divergence times provide powerful tests of a wide range of hypotheses whilst accounting for the effects of shared evolutionary history [ 13 , 15 ]. However, the shorebird studies listed above were limited by the lack of a complete phylogeny for the group. Most of these studies are based on derivations of the seminal work of Sibley and Ahlquist [ 16 ], yet this study included less than a quarter of extant and recently extinct shorebird species. Recently extinct taxa (according to Monroe and Sibley [ 1 ]) are: the Tahitian sandpiper Prosobonia leucoptera , the Canary Islands oystercatcher Haematopus maedewaldoi , and the Great auk Pinguinus impennis . Recent molecular studies covering a wide range of shorebird families have drawn attention to conflict in the reconstruction of the deep basal nodes of shorebird phylogeny (figure 1 ; reviewed by van Tuinen et al. [ 17 ]). For example, morphological data [ 18 , 19 ] places Alcinae (auks, puffins, murres) at the base of the shorebird tree whilst sequence [ 20 - 22 ] and DNA-DNA hybridisation [ 16 ] data suggests that they are a highly derived sister group to Stercorariini (skuas and jaegers), Larini (gulls), Sternini (terns), and Rynchopini (skimmers). It is important to note that taxon coverage differs between these studies and this may be an important factor in determining the tree topology. Specific phylogenies have been derived, for example, for sandpipers [ 23 ], the genus Charadrius [ 24 ], and jacanas [ 25 ] using DNA sequence data. In contrast, morphological evidence provided the basis for Chu's [ 26 ] study of gull phylogeny. Strauch [ 18 ] presented the most complete data set of 227 Charadriiformes species. However, despite the plethora of cladograms for particular shorebird groups (see reviews by Sibley and Ahlquist [ 16 ]; Thomas et al. [ 22 ]), those that address relationships across the whole clade use either sparse taxon sampling [ 16 , 27 ], or are based on reassessments of Strauch's [ 18 ] data [ 19 , 28 - 30 ]. Note that Dove [ 30 ] included a feather microstructural analysis in addition to her reanalysis of Strauch's [ 18 ] data. Figure 1 Previous hypotheses shorebird phylogeny. Family and subfamily level relationships of shorebirds based on: a) Morphological data [19]; b) DNA-DNA hybridisation [16]; c) Sequence analysis of RAG-1 [20, 21], cytochrome- b [22] and myoglobin intron II [21]. Combining phylogenetic data Numerous methods and types of data can be used to infer phylogeny. Frequently, as in Charadriiformes, a single analysis incorporating all taxa of interest is absent. Under the principle of total evidence [ 31 ], all sources of phylogenetic information should be combined to maximize their explanatory power. Eernisse and Kluge [ 32 ] define total evidence as a method for seeking the best fitting phylogenetic hypothesis for an unpartitioned set of synapomorphies (shared derived characters) using character congruence (characters combined in a supermatrix). Hence, this method combines the primary data (molecular, morphological and behavioural characters) into a single analysis. The approach is powerful because weak signals in the partitioned data sets may be enhanced when combined, and previously obscured relationships may be revealed [ 33 ]. The total evidence approach has both practical and theoretical problems. First, only certain types of data can be combined. For example, nucleotide sequences and morphological traits can be readily assessed together as characters, but it is not generally possible to include nucleotide sequences and genetic distance data in a single analysis [ 34 ]. We acknowledge that Lapointe et al. [ 35 ] suggest a distance based approach to combine otherwise incompatible data in a total evidence analysis, although this method has not been tested beyond a single application. The consequence is that it is rarely possible to combine all sources of data in practice and the lack of overlap in combinable data sets may result in a reduction of the number of taxa included. Second, Miyamoto and Fitch [ 36 ] contend that combining data sets is rarely justified because partitions of phylogenetic data are real and unequivocal. They argue that several partitions producing similar topologies provide multiple lines of independent evidence supporting that topology. Theoretical arguments over the benefits of total evidence will undoubtedly continue, but perhaps the major barriers to its use are the often very high computational demands of large matrices, and the a priori exclusion of certain data types. This is particularly true of Charadriiformes phylogeny, where one of the most significant contributions to the field – DNA-DNA hybridisation – cannot be included. An alternative set of techniques, collectively termed supertrees (e.g., Matrix Representation with Parsimony, MRP; [ 37 , 38 ]), enables combination of trees (rather than raw data) from otherwise incompatible sources. MRP methods code source phylogenies based on the presence and absence of taxa at each node of the tree [ 37 - 39 ] and are thus one step removed from the primary data. It is important to recognise that supertrees should not be regarded as a replacement for exhaustive phylogenetic studies of the primary data and there are drawbacks to the methods (see Discussion). However, they do enable very large phylogenies to be constructed rapidly [ 15 ]. Supertrees have been constructed successfully for a wide variety of taxa including carnivores [ 15 ], primates [ 39 ], seabirds [ 40 ], dinosaurs [ 41 ], and grasses [ 42 ]. Shorebirds are particularly well suited for supertree treatment, since there are numerous incomplete phylogenies available and a broader phylogeny is desirable to facilitate powerful analyses of numerous evolutionary hypotheses (see above). Here, we present the first complete composite phylogeny of extant and recently extinct [ 1 ] shorebirds using the MRP approach. We are therefore combining data on tree topologies, and not conducting a simultaneous analysis on the original data. We also use fossil and molecular data to estimate divergence times (see Methods). The combination of complete taxonomic coverage and the inclusion of branch lengths provide the basis for future comparative analyses of Charadriiformes evolution. In addition, conflicting and unresolved areas of Charadriiformes phylogeny are revealed. Results and Discussion Supertree resolution and topology We found 1469 equally short trees of length 1847 steps using the parsimony ratchet approach (see Methods). This compares favourably to a standard heuristic search that yielded shortest trees of 1853 steps. All subsequent results and discussion refer to the parsimony ratchet analyses. Figure 2 shows the family and subfamily level relationships of shorebirds based on the strict and 50 % majority-rule consensus tree (see additional file 1 for branch length estimates). Figures 3 , 4 , 5 , 6 , 7 , 8 , 9 show the species level phylogeny. The full 50% majority rule consensus and the strict consensus trees are available as additional file 2 and 3 respectively. The 50% majority-rule consensus tree is well resolved (73.1%; 255 nodes out of a possible 349 in a fully bifurcating tree), although the strict consensus tree is only 49.6% resolved (173 from 349 possible nodes). The majority rule tree includes nine novel clades (numbers 20, 29, 57, 85, 89, 108, 122, 139, 140) that do not appear in any of the source trees; all of these occur towards the tips of the tree. This is a general problem in supertree construction and such clades should be collapsed as they have no support [ 41 ]. To demonstrate where the MRP method has performed badly we have included the novel clades in all figures and list details in the figure legends. In addition, 58 nodes are supported by only one character (see additional file 1 ). Each of these nodes is left over from a single source tree. Assessing the support for such nodes is problematic because this may simply reflect a lack of research directed at the taxa in question. A major challenge for supertree construction is to develop measures of support that reflect the robustness of nodes in the source trees. We list the number of characters supporting each node ( additional file 1 ) but stress that these are not measures of tree robustness and may not be directly comparable even within the same tree. This is because the taxon coverage across source trees is highly variable so some nodes have more potential support than others. Furthermore, because measures of support used in the source trees differ between studies (some source trees include no measures of support), it is impractical and of dubious value to use these measures to assess the robustness of the supertree. Figure 2 Summary of shorebird supertree. Family and subfamily level relationships of shorebirds based on 50% majority rule tree. Numbers on nodes refer to age estimates in additional file 1. Boxed node numbers indicate that node collapses to its immediate ancestor in the strict consensus tree (see also additional files 2 and 3 for the full 50% majority rule and strict consensus trees respectively). Figure 3 Phylogeny of Larini. 50% majority rule supertree showing the relationships of the Larini. Numbers on nodes refer to age estimates in additional file 1. Boxed node numbers indicate that node collapses to its immediate ancestor in the strict consensus tree (see also additional files 2 and 3 for the full 50% majority rule and strict consensus trees respectively). Figure 4 Phylogeny of Sternini. 50% majority rule supertree showing the relationships of the Sternini. Numbers on nodes refer to age estimates in additional file 1. Boxed node numbers indicate that node collapses to its immediate ancestor in the strict consensus tree (see also additional files 2 and 3 for the full 50% majority rule and strict consensus trees respectively). Figure 5 Phylogeny of Rynchopini, Stercorariini, Dromas , Alcinae, and Glareolidae 50% majority rule supertree showing the relationships of the Rynchopini, Stercorariini, Dromas , Alcinae, and Glareolidae. Numbers on nodes refer to age estimates in additional file 1. Boxed node numbers indicate that node collapses to its immediate ancestor in the strict consensus tree (see also additional files 2 and 3 for the full 50% majority rule and strict consensus trees respectively). Node numbers 139 and 140 have no support from any source tree and are novel clades. Figure 6 Phylogeny of Jacanidae, Rostratulidae, Thinocoridae, Pedionomidae and Scolopacidae 50% majority rule supertree showing the relationships of the Jacanidae, Rostratulidae, Thinocoridae, Pedionomidae and Scolopacidae. Numbers on nodes refer to age estimates in additional file 1. Boxed node numbers indicate that node collapses to its immediate ancestor in the strict consensus tree (see also additional files 2 and 3 for the full 50% majority rule and strict consensus trees respectively). Node numbers 85 and 89 have no support from any source tree and are novel clades. Figure 7 Phylogeny of Scolopacidae 50% majority rule supertree showing the relationships of the Scolopacidae. Numbers on nodes refer to age estimates in additional file 1. Boxed node numbers indicate that node collapses to its immediate ancestor in the strict consensus tree (see also additional files 2 and 3 for the full 50% majority rule and strict consensus trees respectively). Node numbers 108 and 122 have no support from any source tree and are novel clades. Figure 8 Phylogeny of Pluvianellidae, Chionidae, Burhinidae, Haematopodini and Recurvirostrini 50% majority rule supertree showing the relationships of the Pluvianellidae, Chionidae, Burhinidae, Haematopodini and Recurvirostrini. Numbers on nodes refer to age estimates in additional file 1. Boxed node numbers indicate that node collapses to its immediate ancestor in the strict consensus tree (see also additional files 2 and 3 for the full 50% majority rule and strict consensus trees respectively). Node numbers 20 and 29 have no support from any source tree and are novel clades. Figure 9 Phylogeny Charadriinae 50% majority rule supertree showing the relationships of the Charadriinae. Numbers on nodes refer to age estimates in additional file 1. Boxed node numbers indicate that node collapses to its immediate ancestor in the strict consensus tree (see also additional files 2 and 3 for the full 50% majority rule and strict consensus trees respectively). Node number 57 have no support from any source tree and are novel clades. The majority of unresolved nodes in the shorebird supertree are located towards the tips of the phylogeny. For example, the genus Gallinago forms a monophyletic clade but only two pairs of species are resolved from 14 species ( G. megala and G. negripennis ; G. macrodactyla and G. media ) in the majority-rule tree. Only the latter relationship remains in the strict consensus tree. In addition, clades including the genera Charadrius and Vanellus , Calidris and Tringa , Sterna , and Scolopax are poorly resolved. This may reflect a bias in phylogenetic studies of shorebirds. For instance, we found six source trees for Alcinae [ 43 - 48 ] but none devoted to Scolopax or Gallinago . Thomas et al. [ 49 ] indicate that this may be a problem for shorebird studies in general and reported a strong skew favouring research on northern hemisphere species. In contrast to the within genera relationships, the generic and family levels are generally well resolved. The supertree indicates three monophyletic Charadriiformes lineages (figure 2 ). Family and subfamily resolution within each lineage is high, however the relative position of each group is unresolved in the strict consensus tree. This is an important point because the deepest relationships of shorebird phylogeny are contentious [ 22 ]. The 50% majority-rule consensus tree indicates that the gulls and allies (Larini, Sternini, Rynchopini, Stercorariini, Dromas , Alcinae, and Glareolidae) are sister to the sandpipers and allies (Scolopacidae, Jacanidae, Rostratulidae, Thinocoridae, Pedionomidae). The most basal lineage includes the plovers and allies (Charadriinae, Pluvianellidae, Chionidae, Burhinidae, Haematopodini and Recurvirostrini). The gulls and allies clade is most consistent with DNA-DNA hybridisation [ 16 ], indicating that Larini are sister to Sternini and that Rynchopini are sister to this group. This conflicts with morphology-based topologies where Stercorariini are sister to Larini and Sternini with Rynchopini basal to both. Indeed, the position of Stercorariini remains controversial and most recently they were placed as sister to Alcinae [ 20 - 22 ]. In contrast, morphological evidence [ 18 , 19 ] places Alcinae at the base of the whole Charadriiformes tree with Stercorariini sister to Larini. Thus, the position of Alcinae is uncertain and appears to be dependent on the type of data, with fundamental differences between molecular based analyses and morphological analyses. The taxon sampling of previous morphological and molecular studies varies considerably and it may be this, rather than genuine differences in the phylogenetic signal of different data types, that is the cause of conflict in resolving the phylogenetic position of Alcinae. However, it is encouraging that van Tuinen et al. [ 17 ] suggested that new unpublished osteological data are consistent with the more derived position indicated by molecular data. The supertree resolves Glareolidae outside the Larini, Sternini, Rynchopini, Stercorariini, Dromas , Alcinae clade. This is also the case with recent molecular and previous DNA-DNA hybridisation studies. Morphological studies have failed to resolve the position of Glareolidae, placing the family in a large polytomy with all other major groups except Alcinae and the sandpipers and allies (fig. 1 ). A novel development in shorebird phylogeny is the placement of the black-rumped buttonquail Turnix hottentotta as a sister to the gulls and allies (Larini, Sternini, Rynchopini, Stercorariini, Dromas , Alcinae, and Glareolidae) based on the nuclear RAG-1 gene [ 20 ]. We did not include this species in the supertree because to date Paton et al. [ 20 ] remains the only study to reveal an apparently robust relationship. More diverse sampling of the buttonquails (Turnicidae) is essential to corroborate the general affinities of this family. The relationships within the plover clade appear to be reasonably stable. Morphological, molecular, and DNA-DNA hybridisation all place Charadriinae as sister to Haematopodini and Recurvirostrini; our supertree is consistent with these relationships. However, it is not clear whether Burhinidae and Chionidae are sister to each other [ 20 - 22 ] or whether Chionidae are sister to a Charadriinae, Haematopodini, Recurvirostrini, and Burhinidae clade [ 16 ]. Our supertree also included Pluvianellidae, a family consisting of only one species (magellanic plover Pluvianellus socialis ) and places this as sister to Chionidae. If Pluvianellidae are excluded, the supertree is consistent with the sister group relationship of Burhinidae and Chionidae. The sister group relationship of Jacanidae to Rostratulidae is well established [ 16 , 18 - 22 ] and is found in our supertree. The supertree resolves the Thinocoridae and Pedionomidae as sister taxa and this group is sister to the Jacanidae and Rostratulidae. The large Scolopacidae clade is at the base of the sandpiper clade consistent with recent molecular studies [ 20 - 22 ] and the DNA-DNA hybridisation tapestry [ 16 ]. Taken together, it is evident that the supertree is generally more consistent with molecular data (both recent sequence studies and DNA-DNA hybridisation) than with analyses based on morphology. However, it is of course possible that this reflects the greater number of molecular source trees available rather than indicating that molecular data is actually better at resolving shorebird phylogeny. We included several large morphological phylogenies [e.g [ 18 , 19 , 26 , 30 , 43 ]] but the majority of source trees (29 out of 51) were based on molecular evidence (see additional file 5 ). Node dates The higher resolution of the majority-rule tree means it is more likely to be of use in comparative studies. We therefore estimated node ages for this topology only (see additional file 1 and 2 ). We stress that our estimates of node dates are a first attempt at dating the whole tree and have several limitations. First, the fossils used to calibrate seven nodes in the tree are unlikely to be the earliest members of their respective families thus these dates will be underestimates. Second, we assumed that the fossils are grouped with the extant members of the family but this requires formal testing in a phylogenetic framework. Third, the pure birth model assumes that no extinction occurs but this may be unrealistic and it is likely that extinction processes have reduced the representation of older lineages [ 15 ]. Furthermore, this model is derived from the topological structure of the tree so errors in tree reconstruction will likely lead to errors in branch length estimation. However, this approach has been employed previously in supertrees of primates [ 39 ] and carnivores [ 15 ] explicitly to facilitate comparative analyses. Despite these caveats, simulation studies have demonstrated that comparative methods such as independent contrasts are robust to errors in branch length [ 50 ] and no viable alternative for dating supertrees has been proposed. Nonetheless, we urge that alternative branch length assumptions are explored if the shorebird supertree is used in future comparative studies. At present, the calibrated RAG-1 tree of Paton et al. [ 20 ] remains arguably the most thorough and reliable measure of divergence times for Charadriiformes. A fuller understanding of the phylogenetic affinities of fossil shorebirds will probably improve estimates of node ages for the group. For example, the extinct form Graculavidae, is represented by fossils from the Maastrichtian of New Jersey [ 51 ] and Cretaceous of Wyoming [ 52 ] but its position within the shorebird clade is unclear. Feduccia [ 53 ] suggests that it may be basal and a formal corroboration of this would support proposals for a late Cretaceous origin of shorebirds. The difficulties in dating the shorebird tree are further illustrated by fossil representatives of Recurvirostrini and Burhinidae which are much older than current estimates suggests. The earliest record of the Recurvirostrini is estimated to be over 50 million years old [ 54 ] whilst recent discoveries of a possible member of the Burhinidae are dated to around 70 mya [ 55 , 56 ]. There is clearly a need for an integrated phylogenetic study including both extinct and extant shorebirds. Supertree bias Supertrees are still at an early stage of development and many aspects of MRP, and supertree methods in general, are not yet clearly understood. Steps can be taken to ensure that the supertree includes the most appropriate sets of sources trees, such as only using trees from explicitly phylogenetic studies. This is not always straightforward and could result in the exclusion of important information. For instance, in our shorebird supertree, we included Sibley and Ahlquist's DNA-DNA hybridisation tapestry [ 16 ] although this is based on distance measures rather than more rigorous phylogenetic methods. Even if very strict tree selection criteria are applied, there are still likely to be biases in the data set. For example, not all source trees are equally well supported, yet in most supertree analyses each tree is treated equally [ 57 ]. This is a problem for supertree construction because whilst it is theoretically possible, and indeed beneficial, to weight source trees based on support values [ 57 ] it is rarely possible in practice. Many source trees do not have support values and those that do may use different methods, (e.g, bootstrapping or decay indices) which cannot be directly compared with each other. An additional problem that has not been fully resolved relates to correlations between source trees [ 58 ]. Several source trees based on the same data set may unduly increase the influence of that data set on the supertree analysis. However, there is no formal way of determining how much overlap to allow and the choice of source trees that go into supertree construction inevitably involves some degree of subjective reasoning. For the shorebird supertree we used strict Reduced Cladistic Consensus trees to summarise potential source trees that were from the same data set but based on different methods. For example, Thomas et al. [ 22 ] based their phylogeny on cytochrome- b but used a range of methods including parsimony and Bayesian analyses. We therefore combined these trees to minimise bias. In contrast, Ericson et al. [ 21 ] used two types of data: sequences from the nuclear RAG 1 gene and sequences from the myoglobin intron II. They carried out three analyses: each gene separately and then the two combined in a single analysis. In this case, we used three source trees. It could be argued that the combined analysis of Ericson et al. [ 21 ] should be excluded because of the possible overlap with the individual analyses. However, under the principle of total evidence, the combined data set may result in novel relationships being revealed [ 31 , 33 ] and therefore could contribute important information to the supertree. Simulation and empirical studies are required to fully understand these and other possible biases in supertree construction (e.g., the influence of source tree size and shape) and formal protocols for the selection of source trees are desirable. For transparency, we include a summary of the source trees used, data type, and the main taxa included in the study ( additional file 5 ). Our shorebird supertree is highly consistent with recent advances in the molecular phylogenetics Charadriiformes. However, we urge caution when using the tree in comparative analyses and encourage the additional use of alternative phylogenies and branch length assumptions. It is particularly important to note that the position of some groups such as the Alcinae remains controversial and that although the majority rule tree is consistent with recent molecular studies, the strict consensus tree fails to resolve the deepest nodes. Conclusions The supertree presented here is, to our knowledge, the first attempt to reconstruct the phylogeny of the entire order Charadriiformes. Overall, the supertree is highly consistent with recent molecular hypotheses of shorebird phylogeny. However, it is apparent that fresh attempts to resolve both the phylogeny and estimates of age will be dependent on further gene sequencing and new fossil discoveries. The affinities of the Alcinae and the relationships between the three major shorebird clades require further corroboration, and studies of several genera such as Gallinago and Vanellus are desirable. Furthermore, additional work is required to establish the true affinities of the Turnicidae. Nonetheless, it appears that shorebird phylogeny is gradually approaching a consensus view. The broad taxonomic scope and consistency of the supertree mean that is of potentially great value to future comparative studies (accepting the caveats discussed above) of the behaviour, life-history, ecology and conservation of this diverse group. Methods Supertree construction Possible source trees were identified from online searches of Web of Science covering the years 1981 to 2004. We used the single key strings phylogen, cladistic, clado, classif, systematic, and taxonom (where the asterisks allow variations such as "phylogeny" or "phylogenetics") in the topic field, in conjunction with a major Charadriiformes taxon name (scientific or common). As supertree methods have been criticized for being biased towards historical trends, we preferred those studies that explicitly set out to derive a phylogenetic hypothesis and so exclude purely (and typically older) descriptive taxonomic works. The Sibley and Ahlquist [ 16 ] DNA-DNA hybridisation tapestry may be viewed as non-cladistic, but it was clearly the authors' intention to reconstruct the phylogeny of birds. Furthermore, it provided a vital catalyst for subsequent studies of avian (including shorebird) phylogeny. We therefore included the DNA-DNA hybridisation hypothesis as a source tree in our analyses. Simulation studies have demonstrated that the performance of supertree methods is improved by including at least one taxonomically complete (or near complete) source tree [ 57 ]. We therefore make an exception to our self-imposed rule, and in addition use the taxonomic hierarchy of Monroe and Sibley [ 1 ] as a source tree as this includes all extant Charadriiformes species. We acknowledge that this taxonomy is based largely on Sibley and Ahlquist's [ 16 ] DNA-DNA hybridisation tapestry. The initial search identified 78 source trees from 44 publications. Each source tree was typed as a text file in Nexus format [ 59 ]. We coded trees to the species level with species names taken from Monroe and Sibley [ 1 ], but note that contra Monroe and Sibley [ 1 ], we use Charadriiformes not Charadrii to refer to the whole group. Several studies included the gull Larus thayeri [ 26 , 60 - 63 ] either as a subspecies of Larus glaucoides ( Larus glaucoides thayeri in Monroe and Sibley [ 1 ]) or a species in its own right. In recognition of this, we included Larus glaucoides thayeri as the only subspecies in our data set thus increasing the total taxa to 366. Monroe and Sibley [ 1 ] include 16 species of the family Pteroclidae within the Charadriiformes. However, the relationship of this family to the Charadriiformes is uncertain and they have recently been placed in their own order [ 64 ]. We include the Pteroclidae in our analyses only as a means of rooting the tree. Where there were multiple most parsimonious trees (MPTs), or where source trees had been derived from predominantly overlapping data (e.g., from the same data but using alternative methods), we used RadCon [ 65 ] to produce strict Reduced Cladistic Consensus trees (RCC [ 66 , 67 ]). The output is in the form of a reduced consensus profile and from this we selected the tree with the highest Cladistic Information Content (CIC) [ 65 , 68 ]. This resulted in a total of 51 source trees from which our supertree is derived and these are summarised in additional file 5 . We produced an MRP matrix of the 51 Nexus [ 59 ] source trees in RadCon [ 65 ] (see additional file 6 for the MRP file). We used the original MRP coding method of Baum [ 37 ] and Ragan [ 38 ]. Weighting source trees based on node support such as bootstrapping improves the accuracy of MRP supertrees [ 57 ]. However, this is only possible if all source trees can be weighted on the same criteria [ 57 ]. The absence of branch support measures in many of the shorebird source trees precludes this approach from the present study; hence, subsequent analyses were conducted using equally weighted parsimony. The tendency of large data sets to produce many sub-optimal trees that are close in length and topology to the shortest tree is a serious problem in phylogenetics. Standard heuristic searches frequently are trapped searching within globally sub-optimal "islands" and the tree search is often aborted before completion. Nixon [ 69 ] proposed a new method to avoid this problem. The "Parsimony Ratchet" reweights a random set of characters from the data set. This may result in the tree island no longer representing a local optimum and the heuristic search continues until a new optimum is reached. The algorithm then reverts to the original weighting and the search continues. Nixon [ 69 ] demonstrated the efficacy of the method on a 500-taxon data set, where the ratchet-based search found a tree two steps shorter than standard heuristic searches. We used PAUPRat [ 70 ] to implement a parsimony ratchet in PAUP* [ 59 ]. The default settings of 200 iterations and 15% perturbation of characters for reweighting were used and we carried out 20 replicates. Equally parsimonious trees were summarized using both strict and 50% majority-rule consensus methods. We did not calculate any measures of branch support for two reasons. First, their validity and meaning is questionable in MRP supertrees [ 41 ]. Second, the number of taxa included in our data set is too large to allow practical calculation of any branch support indices (e.g., decay indices [ 71 ]) on a desktop computer. Dating the supertree Following Purvis [ 39 ] and Bininda-Emonds et al. [ 15 ] we dated the supertree using both absolute and relative dates. We used data from the Fossil Record 2 [ 54 ] as the source of fossil-based absolute dates. This yielded estimates for Jacanidae ( Nupharanassa tolutaria , Rupellian), Phalaropus ( Phalaropus elenorae , Middle Pliocene), Burhinidae ( Burhinus lucorum , Lower Miocene), Glareolidae ( Paractiornis perpusillus , Lower Miocene), Alcinae ( Petralca austrica , Rupellian), Stercoariini ( Stercorarius sp., Middle Miocene), and Larini (undetermined, Rupellian). We took the midpoint of the range from the Fossil Record 2 [ 54 ] as our date estimate. More recent publications of fossil Charadriiformes were not included because they either represent specimens that are younger or have not been assigned to families that are represented amongst the extant Charadriiformes (such as Turnipacidae [ 72 ]). We assumed that fossil dates represent the earliest occurrence for each group which inevitably resulted in underestimates of clade age. The fossil record of Charadriiformes is amongst the best of the modern bird groups [ 17 ] in terms of the numbers of taxa, but many specimens are fragmentary and reliable estimates of divergence dates are dependent on a limited number of exceptional specimens [ 73 ]. The phylogenetic affinities of the fossil shorebirds in relation to their extant relatives have not yet been fully established, hence have implicitly assumed that fossil representatives of extant groups would be resolved amongst their living relatives. Source trees may include estimates of relative branch lengths (e.g., genetic distances). This allows further dating of the supertree but is problematic because different relative estimates are not comparable and cannot be applied directly to the supertree [ 39 ]. However, where a source trees shares a node that has an absolute date in the supertree (a node dated from fossil evidence), the relative branch lengths can easily be converted to estimates of age. All taxa in our supertree are either extant, or very recently extinct; hence, the tips of the calibrated supertree should be equidistant from the root of the tree. In source trees where the relative branch lengths are not equidistant from the root, we followed the protocol of Purvis [[ 39 ]; p.407–8]. We estimated relative dates using the local molecular clock logic [ 74 ] as implemented by Purvis [ 39 ] and Bininda-Emonds et al. [ 15 ]. For example, consider three taxa A, B, and C where A and B are sister taxa and C is sister to A and B. The root is dated to 10 million years (myr) from fossil evidence, and independent molecular data provides estimates of divergence based on the number of substitutions per site. The molecular estimates of branch lengths are as follows: A , 6 substitutions; B , 8 substitutions; C , 20 substitutions; A and B are 11 substitutions from the root. A and B are therefore separated from their common node by a mean of 7 substitutions. The total length from A and B to the root is thus 18 substitutions compared to 20 for C (a mean of 19). This can be converted to date estimates such that 19 substitutions are equivalent to 10 myr. The dates of the tree are then: (( A : 3.68, B : 3.68), C : 10)). There were no cases where multiple source trees with molecular divergence dates were able to provide estimates for the same node. We estimated relative dates from multiple nodes rather than a single dated node to minimise correlative errors in estimates. To provide date estimates for all nodes in the tree we employed a pure birth model to date nodes for which absolute and relative dates could not be attained [ 39 ]. Pure birth models infer that a clade's age is proportional to the logarithm of the number of species within the clade: date of daughter = date of ancestor (log daughter clade size/log parent clade size) For example, the age of a daughter node that subtends 12 taxa, estimated from its immediate ancestor dated to 20 myr and which subtends 19 taxa is: 20(log(12)/log(19)) = 16.879 We applied this approach to estimate the ages of daughter nodes based on dates (absolute or calibrated) of ancestral nodes. We had no ancestral node on which to base estimates of the most basal clade. In this case, we rearranged the pure birth formula and calculated the age of the ancestral node from its two daughter nodes, taking the mean as our "best estimate". Finally, to estimate the ages of nodes between daughter and ancestor nodes of known age we spaced the nodes evenly along the branches length [ 75 ]. Authors' contributions GHT assisted in the design of the study, carried out the phylogenetic analyses and node dating, and drafted the manuscript in partial fulfillment of a doctoral degree at the University of Bath. MAW assisted in the design of the study and with editing and revision of the manuscript. TS assisted in the design of the study, collection of source trees, and editing and revision of the manuscript. All authors read and approved the final manuscript. Supplementary Material Additional File 1 Estimates of node ages and node support (branch lengths.xls) Node numbers correspond to figures 2-9. Five types of estimate were used: a) absolute dates from the fossil record; b) absolute dates from molecular point estimates; c) relative dates based on branch length estimates from molecular studies; d) estimates based on a pure birth model (see text for details); and e) even spacing of nodes along branches with daughters and ancestors of known age. The numbers of characters supporting each node are provided (column D), this is equivalent to the number of source trees that share the equivalent node (see text for details). Click here for file Additional File 2 Shorebird supertree (50% majority-rule consensus; majrulesupertree.tiff) Shorebird supertree based on 50% majority-rule consensus of 1496 shortest trees with calibrated branch lengths. Scale bar indicates time from the present in millions of years. Click here for file Additional File 3 Shorebird supertree (strict consensus; strictsupertree.tif) Shorebird supertree based on 50% majority-rule consensus of 1496 shortest trees. Click here for file Additional File 5 Source trees (source trees.xls) A summary of each tree used is given including the data type and main taxa studied. This is a brief summary and the original papers should be consulted for full details. Click here for file Additional File 6 MRP matrix (shorebirdMRP.txt) The MRP matrix used in the shorebird supertree analysis. Click here for file Additional File 4 Calibrated supertree (shorebirdsupertree.txt) The supertree in nexus format including branch length estimates. Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC515296.xml
521682	Differential dynamics of histone H3 methylation at positions K4 and K9 in the mouse zygote	Background In the mouse zygote the paternal genome undergoes dramatic structural and epigenetic changes. Chromosomes are decondensed, protamines replaced by histones and DNA is rapidly and actively demethylated. The epigenetic asymmetry between parental genomes remains at least until the 2-cell stage suggesting functional differences between paternal and maternal genomes during early cleavage stages. Results Here we analyzed the timing of histone deposition on the paternal pronucleus and the dynamics of histone H3 methylation (H3/K4mono-, H3/K4tri- and H3/K9di-methylation) immediately after fertilization. Whereas maternal chromatin maintains all types of histone H3 methylation throughout the zygotic development, paternal chromosomes acquire new and unmodified histones shortly after fertilization. In the following hours we observe a gradual increase in H3/K4mono-methylation whereas H3/K4tri-methylation is not present before latest pronuclear stages. Histone H3/K9di-methylation is completely absent from the paternal pronucleus, including metaphase chromosomes of the first mitotic stage. Conclusion Parallel to the epigenetic asymmetry in DNA methylation, chromatin modifications are also different between both parental genomes in the very first hours post fertilization. Whereas methylation at H3/K4 gradually becomes similar between both genomes, H3/K9 methylation remains asymmetric.	Background It is now generally accepted that the properties of a particular DNA sequence in cells are not solely defined by the nucleotide sequence itself, but by "epigenetic" modifications as well. Epigenetic modifications imply the methylation of cytosine residues in CpG dinucleotides and covalent modifications of core histones. These modifications allow for flexible, but heritable at the same time, reprogramming of the genome. In histone H3 five lysine residues can be methylated (K4, K9, K27, K36 and K79) [ 1 ]. Methylation at K4 and K9 play opposite roles in structuring repressive or accessible chromatin domains, with K4 methylation associated with transcriptionally active chromatin and K9 methylation with inactive chromatin in higher eukaryotes [ 2 ]. In addition, these lysine residues can be mono-, di- or tri-methylated, which contributes to the distinct qualities of H3/K4 and H3/K9 methylation. Similar to H3/K9 methylation, DNA methylation is associated with silenced chromatin and there appeared to be an interplay between the two epigenetic modifications. It is still an open question whether DNA methylation directs H3/K9 methylation or other way around, for both scenarios the experimental evidences do exist [ 3 , 4 ]. It recently has been shown that in mammalian cells the maintenance DNA methyltransferase DNMT1 is associated with proteins involved in chromatin reprogramming, including histones deacetylases, and is required for the establishment of H3/K9 methylation [ 5 ]. Various experimental data suggest that the DNA methylation causes multiple changes in local nucleosomes, such as deacetylation of histones H3 and H4, prevents H3/K4 methylation and induces H3/K9 methylation [ 6 ]. The fertilization of mouse egg causes dramatic changes in organization of both paternal and maternal genomes. Initially arrested in metaphase II oocyte completes the meiosis, forming haploid maternal pronucleus and extruding the second polar body. The densely packed with protamines sperm DNA decondences, protamines get exchanged by histones and DNA undergoes active demethylation. The demethylation in the early mouse zygote occurs asymmetrically on paternal DNA and affects different classes of repetitive and single copy sequences, but not the control regions of imprinted genes [ 7 , 8 ]. Previous studies have shown the exclusive localization of methylated H3/K9 in maternal pronucleus of the mouse zygote, which additionally marks the epigenetic asymmetry between maternal and paternal pronuclei [ 9 - 11 ]. Here we examine time dependent changes of chromatin structure in the mouse zygote, focusing on the dynamics of the acquisition of histones in the paternal pronucleus and methylation status of histone H3 at positions K4 and K9. Results and discussion In order to obtain mouse zygotes at different stages of development and to provide the precise timing for fertilization we used in vitro fertilization of mature mouse oocytes. Histones and methylated H3/K4 and H3/K9 were detected by using indirect immunofluorescence. In our experiments we used antibodies, which specifically recognize mono- or tri-methylated forms of H3/K4, and di-methylated H3/K9. The zygotes were analyzed after 3, 5, 8, 10, 12 and 18 hours incubation of mature oocytes with capacitated sperm from donor males. After 18 hours most of embryos were found to be at metaphase and some already at telophase stage of the first mitotic division. Even using in vitro fertilization, the obtained zygotes are not completely synchronous in their development and it is more appropriate to use PN stages classification, which is based on the morphological changes of both pronuclei [ 8 , 12 ]. Appearance of histones on paternal chromosomes We performed the immunostaining against core histones (anti-PanHistone antibodies) in all the stages tested in combination with antibodies, recognizing the specific methylated forms of histone H3. This served as a positive control for the immunostaining procedure and allowed us to follow the dynamics of histone acquisition in the paternal pronucleus. Histones were first detected shortly after the penetration of sperm into the oocyte and the beginning of the decondensation of sperm chromatin. According to PN stages classification we could clearly detect histones on paternal pronucleus at late PN 0 /early PN 1 stages (approx. 3–5 hours p.f.), exactly when the global demethylation starts [ 8 ] (Fig. 1 ). Figure 1 Dynamic changes in chromatin of zygotes at different pronuclear stages. DNA is visualized by DAPI (blue colour) staining. Mouse monoclonalanti PanHistones antibodies were detected by fluorescein conjugated anti-mouse secondary antibodies (green colour). Specific rabbit polyclonal antibodies, recognizing H3/K4monoMe (a), H3/K4triMe (b) or H3/K9diMe (c) were detected by Rhodamine Red-X conjugated anti-rabbit secondary antibodies (red colour). Dynamic changes in H3/K4 methylation in paternal genome Probing the mouse zygotes at different stages with antibodies specifically recognizing either mono- or tri-methylated H3/K4 revealed that these types of modifications are associated with maternal genome through all zygotic stages, including mature oocyte and seem to be rather ubiquitous (Fig. 1a,1b ). As for the paternal pronucleus – we detect the appearance of H3/K4mono-methylation in the beginning of PN 1 (approx. 5 hours p.f.) stage (Fig. 1a ), only slightly delayed compared to the appearance of core histones (Fig. 2 ). By PN 3 – PN 4 stages both paternal and maternal pronuclei show equal staining intensity. This indicates that H3/K4 specific histone methyltransferase, possibly Set9 [ 13 ], is quite active in the early zygote and methylates histone H3 after it is incorporated into the nucleosomes. In contrast to that, it has been shown recently that H3/K9 specific histone methyltransferase is inactivated immediately after the fertilization by yet unknown active mechanism, which involves de novo synthesis of some specific factors [ 11 ]. H3/K4tri-methylation becomes detectable later, starting from PN 4 stage (approx. 8–10 hours p.f.) and the difference in antibodies staining intensity between paternal and maternal pronuclei becomes indistinguishable in the last pronuclear stage PN 5 (approx 12 hours p.f.) (Fig. 1b ) and in metaphase stage of first mitosis approximately 16 hours p.f. (Fig. 3a ). The fact that H3/K4 first becomes mono-methylated and several hours later tri-methylated suggests progressive methylation of histone H3 at lysine 4. We also suggest that histone H3 gets incorporated into the nucleosomes being unmethylated and then undergoes methylation because we observe first the appearance of histones and then H3/K4mono-methylation. In contrast to that – acetylation of histones H3 and H4 happens before they are incorporated into the nucleosomes, and after the nucleosome assembly they can get deacetylated by histone deacetylases (HDACs) whenever required [ 14 ]. But no histone demethylase has been found so far. Figure 2 Distribution of histones and H3/K4monoMe in the zygotes at late PN 0 stage. At this stage histones (green signal) are detectable in both male (♂) and female (♀) pronuclei, whereas H3/K4monoMe (red signal) is only detectable in female pronucleus and polar body (pb). Figure 3 Distribution of H3/K4triMe and H3/K9diMe in metaphase chromosomes during the latter portion of the first cell cycle. (a) Distribution of H3/K4triMe. Paternally and maternally derived chromosomes show equal staining pattern along the whole length of chromosomes. (b) Distribution of H3/K9diMe. This type of modification is not detectable on paternal chromosomes and in maternal chromosomes is mostly associated with centromeres. H3/K9 methylation but not H3/K4 defines the genomes asymmetry in the mouse zygote In order to compare the patterns of H3/K4 and H3/K9 methylation we performed the immunostaining of mouse zygotes using antibodies, which recognize di-methylated H3/K9. Our results are in the agreement with earlier observations that H3/K9 methylation is only attributed to the maternal genome and is completely absent from the paternal [ 9 - 11 ] (Fig. 1c , Fig. 3b ). In normal somatic cells the absence or disruption of H3/K9 methylation leads to the chromosome instability and affects chromosomes segregation during mitosis [ 15 ]. Therefore the absence of H3/K9 methylation on paternal chromosomes is rather surprising and compromises its role in chromosomes segregation. The epigenetic asymmetry between paternal and maternal genomes is observed till 2-cell stage and is characterized by low levels of DNA methylation and H3/K9 methylation in paternal genome [ 8 , 10 , 11 , 16 ]. In case with H3/K4 methylation – the asymmetry is observed only in the beginning of the zygotic development and is indistinguishable in the metaphase stage of the first mitotic division (Fig. 3a ). Recent data from Liu et al . suggest that H3/K9 methylation does not depend on DNA methylation [ 11 ], but it is only paternal DNA which gets demethylated in the mouse zygote and at the same time it does not have detectable H3/K9 methylation. According to data published by Santos et al . [ 17 , 18 ] DNA demethylation starts at PN 1 stage, i.e. at a time when we first observe the appearance of H3/K4mono-methylation (PN 1 stage, Fig. 1a ), and is completed at PN 3 stage when H3/K4mono-methylation in paternal pronucleus reaches approximately the same level as in the maternal (Fig. 1a ). This fact is raising the question if such a coincidence might indicate that DNA demethylation and the establishment of H3/K4 methylation are interdependent. Demethylation of paternal DNA upon the fertilization is not a universal phenomenon for mammalian species. In bovine zygote paternal DNA becomes only partially demethylated, while in sheep and rabbit zygotes the demethylation is hardly detectable [ 17 , 18 ]. The analysis of chromatin modification in early zygotes of these species might help to get an answer if DNA demethylation depends on, or is directed by the specific chromatin modifications. Conclusions Unlike H3/K9 methylation, methylation of H3/K4 is not attributed only to the maternal genome but appears shortly after the acquisition of histones by paternal pronucleus. The methylation of H3/K4 is progressive and by first mitotic division reaches approximately same level as in maternal genome. Methods In vitro fertilization of mouse oocytes As sperm and oocytes donors we used (C57BL/6 X CBA)F 1 mice. Mature oocytes were collected 14 hours post human chorionic gonadotropin injection according to standard procedures [ 19 ]. Sperm isolation and in vitro fertilization (IVF) procedures were performed as described in [ 20 ]. Briefly: the sperm was isolated from cauda epididimus of donor males and capacitated in pre-gassed HTF medium for 1,5 hours. Isolated oocytes in cumulus cell mass were placed into 100 μl drop of HTF medium with capacitated sperm and incubated in CO 2 incubator for 3, 5, or 8 hours. For longer incubation time the oocytes were incubated with sperm in HTF medium for 8 hours and then transferred into the drop of pre-gasses and pre-warmed M16 medium and incubated further for 2, 4 or 10 hours. Immunofluorescence staining After the removal of zona pellucida by treatment with Acidic Tyrode's solution fertilized oocytes were fixed for 20 min in 3.7% paraformaldehyde in PBS, and permeabilized with 0.2% Triton X-100 in PBS for 10 min at room temperature. The fixed zygotes were blocked overnight at 4°C in 1% BSA, 0.1% Triton X-100 in PBS. After blocking the embryos were incubated in the same solution with either anti PanHistones (mouse polyclonal, Roche), anti mono-methyl H3/K4 (rabbit polyclonal, Abcam), anti tri-methyl H3/K4 (rabbit polyclonal, Abcam) or anti di-methyl H3/K9 (rabbit polyclonal, a gift from T. Jenuwein [21] antibodies at room temperature for 1 hour, followed by several washes and incubation for 1 hour with anti-mouse secondary antibodies coupled with fluorescein (Sigma-Aldrich), and anti-rabbit secondary antibodies coupled with Rhodamine Red-X (Jackson ImmunoResearch Laboratories Inc.). After final washes the zygotes were placed on slides and mounted with a small drop of Vectashield (VectorLab) mounting medium containing 0.5 μg 4,6-diamino-2-phenylindole (DAPI). At least 20 zygotes have been analyzed for each stage of zygotic development. Immunofluorescence microscopy The slides were analyzed on Zeiss Axiovert 200 M inverted microscope equipped with the fluorescence module and B/W digital camera for imaging. The images were captured, pseudocoloured and merged using AxioVision software (Zeiss). Authors' contributions KL conducted the experimental part of the work and co-wrote the manuscript. JW coordinated the study and co-wrote the manuscript. All authors read and approved the final manuscript.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC521682.xml
515309	The planetary biology of cytochrome P450 aromatases	Background Joining a model for the molecular evolution of a protein family to the paleontological and geological records (geobiology), and then to the chemical structures of substrates, products, and protein folds, is emerging as a broad strategy for generating hypotheses concerning function in a post-genomic world. This strategy expands systems biology to a planetary context, necessary for a notion of fitness to underlie (as it must) any discussion of function within a biomolecular system. Results Here, we report an example of such an expansion, where tools from planetary biology were used to analyze three genes from the pig Sus scrofa that encode cytochrome P450 aromatases–enzymes that convert androgens into estrogens. The evolutionary history of the vertebrate aromatase gene family was reconstructed. Transition redundant exchange silent substitution metrics were used to interpolate dates for the divergence of family members, the paleontological record was consulted to identify changes in physiology that correlated in time with the change in molecular behavior, and new aromatase sequences from peccary were obtained. Metrics that detect changing function in proteins were then applied, including K A /K S values and those that exploit structural biology. These identified specific amino acid replacements that were associated with changing substrate and product specificity during the time of presumed adaptive change. The combined analysis suggests that aromatase paralogs arose in pigs as a result of selection for Suoidea with larger litters than their ancestors, and permitted the Suoidea to survive the global climatic trauma that began in the Eocene. Conclusions This combination of bioinformatics analysis, molecular evolution, paleontology, cladistics, global climatology, structural biology, and organic chemistry serves as a paradigm in planetary biology. As the geological, paleontological, and genomic records improve, this approach should become widely useful to make systems biology statements about high-level function for biomolecular systems.	Background The emergence of complete genomes for many organisms, including humans, has created the need for hypotheses concerning the "function" of specific genes that encode specific proteins. While "function" is interpreted by different workers in different ways [ 1 ], Darwinian theory (by axiom) requires that the term be connected to fitness; natural selection is the only mechanism admitted by theory to generate functional behavior in a living system, macro or molecular. This, in turn, implies that the hypotheses about function have a "systems" component, including the interaction of the protein with other proteins, their impact on the physiology (defined broadly) of the cell and organism, and the consequences of physiology in a changing ecosystem in a planetary context [ 2 ]. Systems hypotheses can be supported by information from many areas. Geology, paleontology, and genomics, for example, provide three records that capture the natural history of past life on Earth. At the same time, structural biology, genetics, and organic chemistry describe the structures, behaviors and reactivities of proteins that allow them to support present life. It has been appreciated that a combination of these six types of analysis provides insights into functional behavior of proteins that cannot be provided by any of these alone [ 2 ]. Over the long term, we expect that the histories of the geosphere, the biosphere, and the genosphere will converge to give a coherent picture showing the relationship between life and the planet that supports it. This picture will be based, however, on individual cases that serve as paradigms for making the connection. The aromatase family of proteins offers an interesting system to illustrate the power of this combination as a way to create hypotheses regarding protein function within a system [ 3 ]. These hypotheses are not "proof", of course, but are limiting in genomics-inspired biological experimentation, now that genomic data themselves are so abundant. Aromatases are cytochrome P450-dependent enzymes that use dioxygen to catalyze a multistep transformation of an androgenic steroid (such as testosterone) to an estrogenic steroid (such as estradiol) (Figure 1 ). The protein plays a key role in normal vertebrate reproductive biology–a role that appears to have arisen before fish and tetrapods (land vertebrates, including mammals) diverged some 375 million years ago [ 4 ]. Aromatase is important in modern medicine as well, especially in breast and other hormone-dependent cancers [ 5 ]. Different numbers of aromatase genes are found in different vertebrates. Two aromatase genes are known in teleost fish [ 6 , 7 ]. Only a single gene is known in the horse [ 8 ], rat [ 9 ], and mouse [ 10 ]. Cattle have both a functional gene and a pseudogene built from homologs of exons 2, 3, 5, 8, and 9 of their functional gene; these are interspersed with a bovine repeat element [ 11 , 12 ]. In several mammalian species, including humans and rabbits, a single gene yields multiple forms of the mRNA for aromatase in different tissues via alternative splicing [ 13 - 16 ]. A still different phenomenology is observed in the pig ( Sus scrofa ). Three different mRNA molecules had been reported in different tissues from pig [ 17 - 21 ]. Compelling evidence then emerged that the three variants of mRNA identified in cDNA studies arose from three paralogous genes [ 22 ], rather than from a single gene differentially spliced [ 23 ]. This implies that the three aromatase paralogs in pigs arose via gene duplications relatively recent in geologic time. Hypotheses relating to the function of the three aromatase paralogs depend in part on when those duplications took place. If they were very recent, the three genes might have helped pigs adapt to domestication. If they pre-dated the divergence of pigs and fish [ 6 ], they may have different roles that are very fundamental to reproductive endocrinology in vertebrates. We apply here a series of tools to generate better hypotheses concerning the aromatase family of paralogs in swine. Results One strategy useful for understanding the function of genes correlates events in their molecular evolution with events occurring in the history of other genes in the same and/or neighboring lineages, and with events recorded in the geological and paleontological records [ 2 ]. We incorporated a tool to date the divergence of two or more genes through an analysis of transitions at synonymous sites of two-fold redundant coding systems, where the encoded amino acid has been conserved [ 24 ]. This analysis exploits the approach-to-equilibrium kinetic behavior displayed by these sites. The analysis yields a transition redundant exchange (TREx) distance for any gene pair where the synonymous sites have not equilibrated. To calibrate the silent TREx clock, inter-taxa histograms relating pig ( Sus scrofa ) and ox ( Bos taurus ) were constructed for transitions at the silent sites of two-fold redundant codon systems where the encoded amino acid was conserved between the species [ 24 ]. The major peaks associated with the separation of these two lineages was observed at f 2 = 0.87, corresponding to a TREx distance of kt = 0.332. As the fossil record constrains the date of divergence of these two lineages to be 60 ± 5 Ma [ 25 - 27 ], and the codon biases in modern Sus scrofa and Bos taurus project an equilibrium value for f 2 = 0.54 [ 24 ], the rate constants for transitions at the TREx silent sites were estimated to be ca. 2.8 × 10 -9 transitions/silent site/year during the time interval that separates these lineages. Analogous f 2 values were then obtained for other vertebrate aromatase pairs, including fish vs. tetrapods ( f 2 = 0.56), birds versus mammals ( f 2 = 0.612), primates versus ungulates ( f 2 = 0.823), and horses versus artiodactyls ( f 2 = 0.828). Assuming a time-invariant single lineage first order rate constant of 3.6 × 10 -9 changes/site/year and an equilibrium f 2 of 0.54, the corresponding dates of divergence are calculated to be 435, 258, 67, and 65 Ma respectively, with the oldest dates being the least precise. The last three of these dates of divergence are similar to those suggested by the paleontological record [ 28 ], within the error of the calculation, which reflects the modest number of characters used to calculate the f 2 values. A tree for the artiodactyl lineage was constructed from the corresponding TREx distances (Figure 2 ). This was found to be consistent with the tree constructed from other metrics. The TREx clock is not widely used. It may, however, provide more accurate dates in regions where synonymous transitions have not equilibrated than conventional clocks that combine data from synonymous transitions and synonymous transversions, or from non-synonymous changes. A comparison of different clocks will be provided in detail elsewhere (Benner et al. , in preparation). Briefly, the rate constants for transitions and transversions are more different than the two rate constants for purine-purine and pyrimidine-pyrimidine transitions. Further, nucleotide frequencies can be used to calibrate the end equilibrium points for two-fold redundant codon systems directly, and this permits an "approach to equilibrium" formalism, well known in chemical kinetics, to be applied [ 24 , 29 - 31 ]. From the tree, the TREx distances from the ancestor of fetal and placental aromatase to the modern enzymes are 0.113-0.079 (using an endpoint of 0.54 to reflect equilibration at the silent sites), corresponding to a range in the time of divergence of 26–38 Ma. The TREx distances from the divergence of all of the porcine aromatases and the modern forms ranges from 0.082–0.116, corresponding to dates of divergence in the range of 27–39 Ma. This suggests that the three aromatase paralogs diverged in the late Eocene to mid Oligocene. To further correlate the duplication of the genes with the fossil record, genomic DNA was analyzed from relatives of Sus scrofa . Both peccary and babirusa seminal plasma ( Tayassu pecari , from the Center for Reproduction of Endangered Species, Zoological Society of San Diego; Babyrousa babyrussa , from the Bronx Zoo, New York) was probed by PCR (Polymerase Chain Reaction) amplification using exon 4-specific primers [ 32 ]. Bands having the sizes expected for the corresponding aromatases were observed by agarose gel electrophoresis. Based on sequence similarity, two isoforms of aromatase were obtained from both peccary and babirusa as clones derived from the PCR products (Figure 3 ). This establishes that at least one of the duplications occurred before the Tayassuidae (the peccaries) diverged from the Suidae (the true pigs) ca. 35 Ma [ 33 , 34 ]. These data are consistent with an evolutionary model that holds that the ancestor of pig and oxen (approximated in the fossil record by Diacodexis , from the early Eocene ca. 55 Ma) [ 35 ] contained a single aromatase gene, and that the paralogous genes in pig arose some 20 million years later. This suggests that the paralogs in pig can be explained neither in terms of the fundamentals of vertebrate reproductive endocrinology, nor as a consequence of swine domestication. This does, however, suggest that the emergence of the aromatase paralogs was approximately contemporaneous with the emergence of a litter in the Suoidea larger than that found in the ancestral artiodactyl condition. While ruminant and camelid artiodactyls have only one-two young per litter, suoids in general have at least two young per litter (as seen in peccaries) and most suines (true pigs) routinely have three-four young (up to 12 in the domestic pig, Sus ). Note that there has long been the tacit assumption that large litters in suoids represent the primitive artiodactyl condition. Large litters are primitive for mammals in general, and because suoids are plesiomorphic in some anatomical conditions relative to other artiodactyls (e.g., short legs, retention of four digits, bunodont cheek teeth), they have been assumed to be plesiomorphic in other respects. Other data suggest that small litters are in fact the primitive artiodactyl condition. Tragulids (mouse deer or chevrotains) are surviving small, primitive ruminants that are not too dissimilar from Diacodexis in body form, but only have one-two young per litter. Additionally, fossil record data on pregnant oreodonts (an extinct group probably related to the ruminant/camelid artiodactyl lineage, but with a suoid-like plesiomorphic postcranial morphology) shows that they also only had one-two young [ 36 , 37 ]. A cladogram of the Artiodactyla (Figure 4 ) illustrates the probable acquisition of multiparous versus uniparous reproductive strategies, and places the character of litters with typically more than two members emerging just before the divergence of Tayassuidae and Suidae. The approximate correlation in time of the aromatase divergence in Suoidea with the enlargement of litters in Suoidea suggests, as a hypothesis, that the two are functionally related. To expand on this hypothesis, we sought genomic signatures of functional change within the aromatase paralogs. The number of non-synonymous changes in the gene divided by the number of the synonymous changes, normalized for the number of non-synonymous and synonymous sites (the K A /K S value), strongly suggests functional change when the value is significantly greater than unity [ 38 , 39 ], and is also an indicator of hypothetical functional change when the value is high on a branch of a tree relative to other branches of the same tree [ 40 - 43 ]. K A /K S values were reconstructed for individual branches of the evolutionary tree derived from the Darwin bioinformatics workbench (see Methods) using a distance matrix and ancestral states constructed by the method of Messier and Stewart [ 39 ]. The typical branch in the aromatase evolutionary tree has a K A /K S value of 0.35. A higher K A /K S value of 0.85 is found in the episodes of evolution near when the pig aromatases diverged. While a K A /K S value of 0.85 does not require the conclusion that positive selection occurred during the emergence of these aromatase paralogs, an inference based on the magnitude of K A /K S in one branch, relative to the K A /K S value for typical branches [ 40 - 43 ], suggests that adaptive changes occurred during the duplications of the aromatase genes in pigs. A complete maximum likelihood analysis of the aromatase gene family was performed using the PAUP and PAML programs. The resulting tree, generated in PAUP, is shown in Figure 5 , with parameters estimated using PAML. Once more, the generation of paralogs in the pig was found to have occurred after the divergence of pigs from oxen. A high K A /K S value (0.93) was again found in the divergence of the swine isoforms on the branch leading to the ancestor of the placental and embryonic enzymes following their divergence from the pig ovarian enzyme. The distribution of substitutions along this branch is consistent with altered functional constraints for the placental and embryonic enzymes compared with their extinct and extant counterparts (Tables 1 and 2 ) [ 44 ]. We correlated the episode of rapid sequence change during the emergence of the embryonic and placental paralogs with the structural biology of aromatase. A homology model of aromatase was built from progesterone 21-hydroxylase from rabbit liver (coordinates from PDB file 1DT6) [ 45 ], a homologous cytochrome P450-dependent monooxygenase. Residues undergoing replacement during the episodes represented by branches in Figure 5 (branches 1–3) are highlighted in color on the 3D model using a program in prototype with HyperChem (Figure 6 ). Multiple features within the pattern of amino acid replacement were apparent. First, the sites accepting amino acid replacements in the branches with low K A /K S values (as represented by branch 2 in Figure 5 ) were typically scattered without any obvious pattern over the surface of the protein. This is expected for neutral drift, although an adaptive role for these replacements is not excluded by this analysis. In contrast, the distribution of sites accepting amino acid replacements during the episode of rapid sequence evolution of branch 1 (as indicated by a relatively high K A /K S value) involving pig paralogs was not random over the protein surface. Rather, the sites are clustered near the substrate binding pocket, and in a region of the surface believed to contact the co-reductant protein, as identified by mutagenesis experiments in the homolog [ 46 , 47 ]. The clustering of amino acid replacements near a substrate binding site during an episode of rapid sequence evolution suggests that the substrate specificity of the protein might be changing in correlation with a change in the detailed physiological role of the protein. Recent reports suggest that the substrate and product specificities of the placental and embryonic enzymes are indeed different from those of the ovarian enzyme [ 23 , 48 - 50 ]. Further, synthesis of estrogen by the ovarian enzyme is more dependent on the structure of the co-reductant than is the placental enzyme [ 51 ]. Our in silico analyses rationalize these experimental observations from a structural perspective. The coupling of an evolutionary analysis to a crystallographic analysis suggests that the amino acid changes are functionally significant. Discussion Today, natural history holds some of the most intellectually challenging conundrums to ever fascinate the human mind. Further, natural history offers biological chemists the opportunity to place broad biological meaning on the detailed analysis of the structure reactivity of isolated biological molecules studied in a reductionist setting. To do so, however, natural history must be connected to the physical and molecular sciences, both in subject matter and in culture. In part to make this connection, natural historians have sought to change the research paradigm in their field to favor quantitative data directed towards the "proof" of hypotheses over "story telling". Proving hypotheses is difficult in natural history ( pace the philosophical reality that no significant statement in empirical science can ever be said to be "proven"). The events of interest (such as the extinction of dinosaurs) are frequently distant in time, or require a passing of time (as for speciation), making them difficult to reproduce in a laboratory. The scale of the concepts involved (species, environments, planets) also does not lend these concepts to laboratory models and laboratory-controlled tests. Further, a reductionist approach, even when available, will not necessarily generate data that are relevant to the big issue that concerns the natural historian. The emphasis on data and proof has ameliorated the worst excesses of storytelling in natural history, with enormous positive impact. Just as natural historians were purifying their field of storytelling, however, whole genome sequences began to emerge. By dramatically increasing the quantity of chemical data concerning the molecular structures of proteins, genomics changed the limiting steps in biochemical and biomedical research. No longer was the typical researcher attempting to solve an organic chemical or biotechnological question (What is the sequence of my protein? How do I express it at high levels to get the sequence?) for a protein that had been selected for functional reasons. Today, the typical researcher knows the structure of many proteins, and wishes to select one for expression and study based on a hypothesis about its potential function. Here, the fact that any definition of function, which must make reference to fitness, requires some systems, ecological, or planetary context, makes the natural historian a natural source of hypotheses. Their full reductionist armamentarium is available in the laboratory to test and explore any hypothesis that the natural historian might provide. The biomedical researchers may like some guidance from the natural historian to narrow the broad selection, or to shorten the random walk, if only slightly. For this purpose, the forswearing by natural historians of storytelling has come at a most inopportune time. To the modern natural historian, creating hypothesis can easily be regarded as "storytelling". They are reluctant to do so, and may criticize as atavistic colleagues who do. This has created a vacuum in the scientific community. Very few laboratories exist that can draw upon an expertise in natural history to generate stories that create hypotheses for the researcher working in experimental biochemistry and molecular biology. This article is designed in part to illustrate how this vacuum might be filled. Here, we do not just tell a story based on natural history, or even a story based on natural history supplemented with physiology and molecular sequence data. Rather, we show how the addition of other data, including data from X-ray crystallography, can make a story sufficiently rich that it can be viewed as being internally consistent with a wide range of independent data drawn from independent sources. This creates a hypothesis that is more than a story, even if it is less than proven. With aromatase, the congruence of our different analyses makes a compelling suggestion that the three aromatase paralogs in pigs arose by two duplication events in the late Eocene or early Oligocene. The emergence of the aromatase paralogs corresponded approximately in time to the emergence of larger litter size in suines. This implies that the two duplication events are functionally related to the larger litter sizes. This inference is consistent with the physiological impact of estrogen synthesis by these paralogs in Sus . Steroid production by the porcine embryo is tightly controlled by the transient expression of aromatase and 17-hydroxylase (P450C17) between days 10 and 13 [ 20 , 21 , 52 ]. In contrast, estrogen synthesis by the equine embryo begins as early as day 6 and increases with embryo age and diameter [ 52 ]. The estrogen produced by the pig embryonic aromatase is believed to have an impact on the mobility, spacing, and implantation of the concepti [ 52 - 56 ]. Adequate spacing would appear to be required to manage a larger litter. This is consistent with a structural biological analysis that correlates specific amino acid replacements with specific changes in the substrate and product specificity of the protein [ 57 ]. Interestingly, the substrate specificity of human aromatase is reported to be more similar to that displayed by the pig placental enzyme than the ovarian form [ 48 , 49 ]. This is an unexpected similarity given that our evolutionary analysis suggests a change in biochemical function along the fetal/placental branch in the Suidae. It should be noted that the hypothesis is supported by the combination of data that individually would not have strength past storytelling. Thus, the K A /K S ratio of 0.93 would not, by itself, compel any particular interpretation. Its implications are greater given the relatively low K A /K S ratios of other branches of the tree. But the addition of crystallographic information, itself not compelling, makes a combination that is more compelling. Further, this hypothesis generation itself generates discoveries that might lead to their own hypotheses. An analysis of the evolutionary branches separating pigs and humans suggests an additional episode of adaptive change. The branch leading to the ancestor of human aromatase (branch 3) has a remarkably high K A /K S ratio (13 non-synonymous and no synonymous changes; Figure 5 ). This is a K A /K S ratio greater than unity, and does (pending evaluation of its statistical significance) compel the inference of an episode of adaptive change. Intriguingly, these changes are also clustered in the same regions of the structure as those changing along branch 1 leading to the stem fetal/placental enzyme, near the substrate and co-reductant binding sites. This implies that the substrate/product specificity of the ancestral aromatase protein was not like that of either the human or the pig placental forms, but rather reflects features that arose convergently in these two species [ 58 ]. Notably, four of the sites (positions 47, 153, 219, 269) that undergo replacement during the emergence of pig placental aromatase from the last common ancestor are the same as four that arose in the emergence of the human aromatase from its last common ancestor. Of these, the amino acid replacements are identical at two sites (Thr → Met at site 153; His → Arg at site 269). The probability associated with randomly observing this pattern is extremely low (0.000021) [ 59 ]. An additional site is displaced by a single position in the sequence alignment (259/260). We hypothesize that these represent an example of adaptive parallel evolution. It is important to point out that even an analysis this broad is likely to cover only a small part of a complicated reproductive endocrinology that must be associated with larger litter sizes. For example, the exact nature of the products produced by individual aromatases remains controversial, and may be different in laboratory studies depending on the conditions where they are studied [ 50 , 60 - 62 ]. This is especially the case with the 19-nortestosterone derivatives in Figure 1 . Further, an elegant recent study by Corbin et al. [ 23 ] identified 1β-hydroxytestosterone as a novel product produced by recombinant pig ovarian aromatase that is absent from the products produced by the porcine placental paralog, or by either human or bovine aromatase. This testosterone derivative binds to an androgen receptor, consistent with physiological activity. This was unknown before just this year, suggesting that more endocrine novelties remain to be discovered. Any of these may be relevant to a test of this system. For example, these hypotheses make predictions about the product specificities of the two peccary aromatases reported here. In fact, some data suggest that uterine exposure to androgens severely decreases litter size and embryonic survival during the time of maternal recognition of pregnancy [ 63 ]. This is consistent with the hypothesis of Corbin et al. [ 50 ] that the evolution of the placental paralog is associated with increased efficiency of testosterone aromatization. This is also consistent with the current data, and the argument presented here. It goes without saying that still more factors might be associated with an increase in litter size from one-two (presumed in Diacodexis , see Figure 4 ) to 12 or more in domestic swine. Most trivially, this increase might be associated with an increase in ovulation rate, and/or an adjustment in the structures and binding specificities of estrogen receptors [ 64 ]. Nevertheless, the first aromatase duplication, shared by pigs and peccaries, appears to have happened in the late Eocene (recognizing the error associated with these dates), around 35 Ma (Figure 4 ). This was a time of great global change, with dramatic cooling in the higher latitudes. More archaic kinds of mammals (e.g., some earlier families of perissodactyls and artiodactyls) became extinct, while many modern families (including the Suidae and Tayassuidae) became established at this time [ 65 ]. Suoids differed from other contemporaneous ungulates in their commitment to omnivory, even though a few forms, such as the modern warthog Phacochoerus aethiopicus , are more specialized herbivores. Perhaps the ability to bear a slightly larger litter than other artiodactyls was advantageous to them in this time of global ecological transition. However, it should be noted that larger litters usually mean altricial (i.e., relatively underdeveloped) young, a reproductive strategy apparently not available to larger, cursorial (running-adapted) ungulates, which give birth to precocial (i.e., well developed) young that are fully locomotory at birth [ 66 ]. The second aromatase duplication, with the ensuing capacity to produce multiple young, probably occurred within the family Suidae, some time during the Oligocene. The molecular data suggest dates of divergence between porcine fetal and placental aromatases as between 27–38 Ma, and the earliest known suid is of early Oligocene age [ 67 ], around 33 Ma (Figure 4 ). Large litters may have characterized the entire suid family. While the extant subfamily Suinae is primarily a Plio-Pleistocene radiation, during the Oligocene to Pliocene suids were exceedingly diverse taxonomically (with six other subfamilies known) as well as individually abundant as fossils [ 32 , 33 , 67 ]. In contrast, the predominantly North American tayassuids were never as diverse. It is possible that this tremendous Old-World diversity of suids, which continues to this day, is related to their capacity for the production of large litters. This type of speculation opens questions. For example, the babirusa (an Indonesian pig) is reported to have average litters of one-two individuals [ 68 , 69 ]. While it is possible that litters contain three-four individuals, the occurrence is low [ 70 ]. If the common ancestor of babirusa with the African/Eurasian Suinae had a larger litter, then the babirusa must be hypothesized to represent a reversion to the more primitive condition. At present, however, relatively little is known of either the molecular biology or the natural history of babirusa. The date of divergence from modern swine is placed between 12–26 million years [ 71 , 72 ], while our TREx analysis using cytochrome b places this data at ca. 18 Ma (data not shown). Clearly, further study is warranted. Conclusions The aromatase family offers an example where a combination of phylogenetic analysis, molecular evolutionary analysis, and chemical analysis set within the context of the paleontological and geological records, and supported by contemporary bioinformatics and molecular modeling tools, permits a higher order level of hypothesis generation concerning the function of proteins. Rather than simply an Enzyme Commission number (E.C. 1.14.14.1 for aromatase), a description of catalytic activity (the enzyme oxidizes testosterone), or a description of the regulatory pattern (the protein expressed between day 10 and 13), this type of analysis can generate a truly functional hypothesis: that the embryonic enzyme oxidizes testosterone as a way of managing the larger litter sizes that emerged in the Suoidea during a time of dramatic planetary cooling (ca. 35 Ma). Such hypotheses set a higher bar, and a more useful standard, for the field of systems biology. Evolutionary theory holds that the only mechanism for obtaining functional behavior in a biological system is natural selection. Selection, based on a frequently poorly defined concept of "fitness", is determined by a context that not only includes the cell and tissue, but also the organism, the ecosystem, and a changing planet [ 73 ]. One cannot expect a collection of expression data with a mathematical model, by themselves, to provide this type of functional information unless it is set in the organismic, ecosystem, and planetary context. The historical view, of the type outlined here, becomes a critical tool for constructing this setting (Supplementary Figure [see Additional File 1 ]). Humans have evidently exploited the molecular biology of larger litters to select for pigs that have truly large litters (as many as 14) following their domestication. Evidence for ancient domestication of pigs comes, inter alia , from a study of Indo-European languages. Proto-Indo-European (PIE) language had words for "pig" (PIE su -, compared with Tocharian B suwo , Latin sus , Greek us , Sanskrit sukara , Church Slavic svinija , Old High German swin , and English sow ; also compare PIE porko -, with Latin porcus , Church Slavic prase , Old High German farah , etc. [ 74 ]), indicating that the pig has been under human domestication for at least 6000 years, enough time to have suffered a significant impact on its genotype through husbandry. We are unable, at this time, to exploit complete genome sequences of pigs or other closely related taxa to discuss the impact of domestication on aromatase, steroid receptors, amphiregulins, or other proteins that appear to be associated with uterine capacity and large litter sizes in the domesticated pig [ 75 ]. With the anticipated complete genome sequences of representatives of various mammal orders, including artiodactyls, it should be possible to extend this planetary biology approach. Methods Calculations were done under the RedHat Linux 6.3 operating system on an Intel-Pentium III instrument using Blackdown's Java-SDK 1.1.8. PAML calculations were done on an IBM PC using the Unix operating system. Sequence analyses were aided by the DARWIN bioinformatics package [ 76 ]. The DARWIN package can be obtained by emailing a request to cbrg@inf.ethz.ch . Initially, pairwise alignments were constructed for the aromatase protein sequences available in the database. An evolutionary distance in PAM units was calculated for each pair by applying the PamEstimator-package from DARWIN using an empirical log-odds matrix. From this, a preliminary evolutionary tree was built for the mammalian sequences, with branch lengths along internal nodes calculated to minimize a least-squares distance. The sequences of the ancestral genes and proteins at branch points in the tree were then reconstructed. From there, mutations (including fractional mutations) at both the DNA level and protein level were assigned to individual branches in the tree using the method of Fitch [ 77 ]. The evolutionary history of the aromatase family was then analyzed using the transition redundant exchange (TREx) metric based on an analysis of two-fold redundant codon systems [ 24 , 78 ]. These were obtained for each pairwise comparison of aligned aromatase genes. The number ( n ) of two-fold redundant amino acids (Cys, Asp, Glu, Phe, His, Lys, Asn, Gln, and Tyr) that are conserved in the aligned pairs was determined. The number of those amino acids that are encoded by the same codon ( c ) was determined, and the fraction ( f 2 = c / n ) of the codons that are the same were then tabulated (Supplementary Table [see Additional File 2 ]). The TREx distances were calculated from f 2 values using the expression kt = -ln(( f 2 -E quil )/(1-E quil )), where E quil is the f 2 value expected after a large number of nucleotide substitutions have occurred at the synonymous sites [ 24 ]. The DNA sequences for aromatase were phylogenetically analyzed using a maximum likelihood framework in PAUP 4.0* (beta 10) [ 79 ], with the following parameters: alpha value representing the gamma distribution (2.1), the transition-transversion ratio (1.6), proportion of invariable sites (0.24), and empirical base frequencies. The resulting topology of the tree mirrors those based on other molecular studies [ 80 ]. For inter-taxon analyses, families in the MasterCatalog (EraGen Biosciences, Madison WI) were identified that contained at least one representative protein from both of the taxa of interest. For these families, all inter-taxa pairs of genes were extracted, together with the pairwise protein sequence alignment. A pairwise alignment of the DNA sequences was then generated to follow the protein sequence alignment. If a family contained more than one sequence of a species belonging to one of the taxa analyzed, then those sequences were checked to determine whether they were duplicate entries into the database. If this was the case, only one of the duplicate sequences was retained in the analysis. A histogram of inter-taxa pairs was constructed, and the f 2 value characteristic of orthologs determined [ 24 ]. This was used to calibrate the TREx clock using the divergence of pigs and oxen, and pigs and humans. Codon biases were obtained from the CUTG (Codon Usage Tabulated from GenBank) made available by the Kazusa DNA Research Institute Foundation, Japan [ 81 ]. Pairwise TREx distances were used to generate lengths for the branches connecting the swine paralogs using the minimum evolution criterion in PAUP. This preliminary analysis was followed by a maximum likelihood analysis for the complete dataset using the PAML program [ 82 ]. This includes the assignment of K A /K S values to individual branches. Tests of parallel evolution were conducted using Converge [ 59 ], implementing the JTT model. Secondary structural data based on homology modeling for aromatases were generated using the DARWIN bioinformatics package, and in agreement with previous studies [ 83 , 84 ]. Renderings of the three dimensional structure of the proteins were obtained using a beta version of the HyperProtein package (HyperCube, Gainesville FL, USA 32601). Authors' contributions EAG performed the evolutionary, statistical and structural analyses, and prepared the manuscript. LGG cloned genes as part of his Masters work, and called the evolutionary problem to the attention of SAB. TL provided computational infrastructure. RCMS and FAS initiated the work with suid reproductive endocrinology, and supervised LGG. DRS and DAL did the initial bioinformatics analysis. CMJ provided paleontological expertise, constructed the cladogram, and helped prepare the manuscript. SAB has developed planetary biological analysis as a paradigm for generating hypotheses about the biological function of proteins, and prepared the manuscript. Supplementary Material Additional File 1 Illustration of planetary biology. This figure illustrates the concepts of planetary biology as they relate to combining genomic, paleontological, chemical and ecological records to understand the history of the biosphere. Click here for file Additional File 2 An analysis of silent nucleotide substitutions in vertebrate aromatases. The first five columns from the left indicate the index number of sequence 1 compared with sequence 2, the fraction of sites at conserved two-fold redundant coding systems that are identical (f2), the number of such sites that are conserved (c2), and the number of such sites overall (n2). The remaining columns report analogous data: for silent sites in codon systems where a change at the third nucleotide is silent only if the change is a pyrimidine-pyrimidine transition (f2y, c2y, n2y); in silent sites where a change at the third nucleotide is silent only if the change is a purine-purine transition (f2r, c2r, n2r); for the silent sites at three-fold redundant codon systems (f3, c3, n3); and for the silent sites at four-fold redundant codon systems (f4, c4, n4). Click here for file	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC515309.xml
528856	Funding free and universal access to Journal of Neuroinflammation	Journal of Neuroinflammation is an Open Access, online journal published by BioMed Central. Open Access publishing provides instant and universal availability of published work to any potential reader, worldwide, completely free of subscriptions, passwords, and charges. Further, authors retain copyright for their work, facilitating its dissemination. Open Access publishing is made possible by article-processing charges assessed "on the front end" to authors, their institutions, or their funding agencies. Beginning November 1, 2004, the Journal of Neuroinflammation will introduce article-processing charges of around US$525 for accepted articles. This charge will be waived for authors from institutions that are BioMed Central members, and in additional cases for reasons of genuine financial hardship. These article-processing charges pay for an electronic submission process that facilitates efficient and thorough peer review, for publication costs involved in providing the article freely and universally accessible in various formats online, and for the processes required for the article's inclusion in PubMed and its archiving in PubMed Central, e-Depot, Potsdam and INIST. There is no remuneration of any kind provided to the Editors-in-Chief, to any members of the Editorial Board, or to peer reviewers; all of whose work is entirely voluntary. Our article-processing charge is less than charges frequently levied by traditional journals: the Journal of Neuroinflammation does not levy any additional page or color charges on top of this fee, and there are no reprint costs as publication-quality pdf files are provided, free, for distribution in lieu of reprints. Our article-processing charge will enable full, immediate, and continued Open Access for all work published in Journal of Neuroinflammation . The benefits from such Open Access will accrue to readers, through unrestricted access; to authors, through the widest possible dissemination of their work; and to science and society in general, through facilitation of information availability and scientific advancement.	Introduction Journal of Neuroinflammation is an Open Access, online journal that is published by BioMed Central, an independent publisher committed to Open Access for peer-reviewed biomedical research [ 1 ]. Among the many benefits of Open Access publishing are (1) instant and universal availability of published work to any potential reader, worldwide, completely free of subscriptions, passwords, and charges; and (2) copyright retention by the authors rather than the publisher. This and many other benefits led us to select Open Access publishing, and to select BioMed Central, for the Journal of Neuroinflammation . Open Access publishing is made possible by article-processing charges (APCs) assessed "on the front end" to authors, their institutions, or their funding agencies. The Journal of Neuroinflammation will introduce APCs of around US$525 per article for manuscripts submitted on or after November 1, 2004. This charge will be waived for all authors from institutions that are BioMed Central members, and in additional cases for reasons of genuine financial hardship. Problems with the traditional publishing model Traditional journals generally do not charge authors for publication (although assessed page or color charges may easily exceed our APCs). Instead, article access is traditionally paid for by readers, either through subscriptions or through fees assessed for online viewing and downloading. Over the past decade, escalating journal subscriptions have resulted in cash-strapped libraries cancelling journal subscriptions [ 2 ], thus limiting the range of articles available to many readers and limiting the potential audience available to authors. The Open Access publishing model The Journal of Neuroinflammation's Open Access policy changes the way in which articles are published. First, all articles become freely and universally accessible online, immediately upon acceptance, so an author's work can be read by anyone at no cost. Second, the article authors retain copyright for their work, and grant to anyone the right to reproduce and disseminate the article, provided that it is correctly cited and no errors are introduced [ 1 ]. Third, a copy of the full text of each article is permanently archived in several separate online repositories. Journal of Neuroinflammation's articles are permanently archived in PubMed Central [ 3 ], the US National Library of Medicine's full-text repository of life science literature, and also in repositories at the University of Potsdam [ 4 ] in Germany, at INIST [ 5 ] in France and in e-Depot [ 6 ], the National Library of the Netherlands' digital archive of all electronic publications. Benefits of Open Access publishing Open Access has four broad benefits for science and the general public. First, published work is disseminated freely and instantly to the widest possible audience, without barriers to access. Authors are free to reproduce and distribute their work at will, for example by placing it on their institution's website. Open Access publication has been shown to actually increase article citations and impact because of this easier availability [ 7 ]. Second, availability of Open Access articles enhances literature searching [ 8 ], as information available to researchers is not limited by what their libraries can afford. Third, results of publicly funded research are accessible to all taxpayers and not just those with access to libraries with journal subscriptions. Such public accessibility would actually become a legal requirement in the USA if the proposed Public Access to Science Act is enacted into law [ 9 ]. Fourth, article access is not limited by the economic resources of a scientist's country or institution; resource-poor countries and institutions are able to access the same material as wealthier ones, subject only to the availability of internet access [ 10 ]. Journal of Neuroinflammation's article-processing charges Article-processing charges will allow continued Open Access to all article published in Journal of Neuroinflammation . Authors will be asked to pay around US$525 upon acceptance of their article for publication. Submitted articles that are not accepted will incur no charge. There will be no charges for authors from institutions that are institutional members of BioMed Central. Currently this includes NHS England and all universities in the UK, the US National Institutes of Health and 136 other institutions and universities in the USA, the World Health Organization, and almost 200 additional institutions in 37 other countries [ 11 ]. Potential authors who are not associated with these institutions can avoid article-processing charges by getting their institution to join this list of BioMed Central institutional members. The annual institutional membership fee covers APCs for all authors at that institution for that year. In addition, many funding agencies have recognized the importance of Open Access publishing and have specified that funds from their grants may be used directly to pay APCs [ 12 ]. Finally, APC waivers are available for cases of genuine financial hardship. These will be considered on a case-by-case basis by the Editors-in-Chief. What do article-processing charges pay for? The APC pays for an electronic submission process that facilitates efficient and thorough peer review, for publication costs involved in providing the article freely and universally accessible in various formats online, and for the processes required for the article's inclusion in PubMed and its archiving in PubMed Central, e-Depot, Potsdam and INIST. There is no remuneration of any kind provided to the Editors-in-Chief, to any members of the editorial board, or to peer reviewers; all of whose work is entirely voluntary. Although some authors may consider US$525 expensive, it must be remembered that Journal of Neuroinflammation does not levy any additional page or color charges on top of this fee. Because we are an online-only journal, any number of color figures, photographs, and 'extra' pages can be included at no extra cost. Such color and page charges, as assessed by more traditional journals, can easily exceed our flat US$525 per-article APC. Another common expense with traditional journals is the purchase of reprints for distribution, and the cost of these reprints is also frequently greater than our APCs. The Journal of Neuroinflammation provides free, publication-quality pdf files for distribution, in lieu of reprints. Free access versus Open Access Several traditional journals now offer free access to their articles online, but this is different from Open Access as defined by the Bethesda Statement [ 13 ]. First, this access may be delayed for 6–2 months after publication. Second, readers are not free to reproduce and/or disseminate the work because of restrictions imposed by publishers' copyright policies. Even these restrictive policies do not ensure continued free access; the British Medical Journal , for instance, recently announced that it cannot continue to provide free access to its website [ 14 ]. They are considering various sources of revenue, including APCs [ 15 ]. APC-funded Open Access is not unique to BioMed Central or to the Journal of Neuroinflammation . The USA-based Public Library of Science (PLoS) is a new, non-profit organization that, like BioMed Central, is dedicated to online, Open Access publishing. PLoS has started two new Open Access journals, with APCs of US$1500 for each accepted article [ 16 ]. PLoS has used television advertising to promote their new journals [ 9 ], providing a high profile that should raise awareness of Open Access publishing in general. This, in turn, should encourage researchers in all disciplines to understand and accept Open Access, and to accept APCs as an acceptable funding method. Conclusion Article-processing charges will enable full, immediate, and continued Open Access for all work published in Journal of Neuroinflammation . The benefits from such Open Access will accrue to readers, through unrestricted access; to authors, through the widest possible dissemination of their work; and to science and society in general, through facilitation of information availability and scientific advancement. We ask for your support in this important movement by submitting your next article to Journal of Neuroinflammation or to another Open Access journal. Competing interests At Journal of Neuroinflammation, the work of the Editors-in-Chief, the Editorial Board, and of all invited outside peer reviewers is entirely voluntary, without tangible remuneration of any kind. Our goal is publication of biomedical research of the highest quality, and our (intangible) rewards lie in the achievement of these goals. Decisions about manuscripts are based entirely on the quality of the work, and not on the ability of authors to pay article-processing charges. Abbreviations APC = article-processing charge.	/Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC528856.xml

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