SGC - Structural Biology and Human Health: A New Approach to Publishing Structural Biology Results

The Structural Genomics Consortium (SGC) is a not-for-profit, public-private partnership established to deliver novel structural biology knowledge on proteins of medical relevance and place this information into the public domain without restriction, spearheading the concept of "Open-Source Science" to enable drug discovery. The SGC is a major provider of structural information focussed on proteins related to human health, contributing 20.5% of novel structures released by the PDB in 2008. In this article we describe the PLoS ONE Collection entitled 'Structural Biology and Human Health: Medically Relevant Proteins from the SGC'. This Collection contains a series of articles documenting many of the novel protein structures determined by the SGC and work to further characterise their function. Each article in this Collection can be read in an enhanced version where we have integrated our interactive and intuitive 3D visualisation platform, known as iSee. This publishing platform enables the communication of complex structural biology and related data to a wide audience of non-structural biologists. With the use of iSee as the first example of an interactive and intuitive 3D document publication method as part of PLoS ONE, we are pushing the boundaries of structural biology data delivery and peer-review. Our strong desire is that this step forward will encourage others to consider the need for publication of three dimensional and associated data in a similar manner. © 2009 Lee et al

Rofecoxib for dysmenorrhoea: meta-analysis using individual patient data

BACKGROUND: Individual patient meta-analysis to determine the analgesic efficacy and adverse effects of single-dose rofecoxib in primary dysmenorrhoea. METHODS: Individual patient information was available from three randomised, double blind, placebo and active controlled trials of rofecoxib. Data were combined through meta-analysis. Number-needed-to-treat (NNT) for at least 50% pain relief and the proportion of patients who had taken rescue medication over 12 hours were calculated. Information was collected on adverse effects. RESULTS: For single-dose rofecoxib 50 mg compared with placebo, the NNTs (with 95% CI) for at least 50% pain relief were 3.2 (2.4 to 4.5) at six, 3.1 (2.4 to 9.0) at eight, and 3.7 (2.8 to 5.6) at 12 hours. For naproxen sodium 550 mg they were 3.1 (2.4 to 4.4) at six, 3.0 (2.3 to 4.2) at eight, and 3.8 (2.7 to 6.1) at 12 hours. The proportion of patients who needed rescue medication within 12 hours was 27% with rofecoxib 50 mg, 29% with naproxen sodium 550 mg, and 50% with placebo. In the single-dose trial, the proportion of patients reporting any adverse effect was 8% (4/49) with rofecoxib 50 mg, 12% (6/49) with ibuprofen 400 mg, and 6% (3/49) with placebo. In the other two multiple dose trials, the proportion of patients reporting any adverse effect was 23% (42/179) with rofecoxib 50 mg, 24% (45/181) with naproxen sodium 550 mg, and 18% (33/178) with placebo. CONCLUSIONS: Single dose rofecoxib 50 mg provided similar pain relief to naproxen sodium 550 mg over 12 hours. The duration of analgesia with rofecoxib 50 mg was similar to that of naproxen sodium 550 mg. Adverse effects were uncommon suggesting safety in short-term use of rofecoxib and naproxen sodium. Future research should include restriction on daily life and absence from work or school as outcomes

CACHE (Critical Assessment of Computational Hit-finding Experiments): A public–private partnership benchmarking initiative to enable the development of computational methods for hit-finding

One aspirational goal of computational chemistry is to predict potent and drug-like binders for any protein, such that only those that bind are synthesized. In this Roadmap, we describe the launch of Critical Assessment of Computational Hit-finding Experiments (CACHE), a public benchmarking project to compare and improve small-molecule hit-finding algorithms through cycles of prediction and experimental testing. Participants will predict small-molecule binders for new and biologically relevant protein targets representing different prediction scenarios. Predicted compounds will be tested rigorously in an experimental hub, and all predicted binders as well as all experimental screening data, including the chemical structures of experimentally tested compounds, will be made publicly available and not subject to any intellectual property restrictions. The ability of a range of computational approaches to find novel binders will be evaluated, compared and openly published. CACHE will launch three new benchmarking exercises every year. The outcomes will be better prediction methods, new small-molecule binders for target proteins of importance for fundamental biology or drug discovery and a major technological step towards achieving the goal of Target 2035, a global initiative to identify pharmacological probes for all human proteins. [Figure not available: see fulltext.

Perioperative celecoxib administration for pain management after total knee arthroplasty – A randomized, controlled study

<p>Abstract</p> <p>Background</p> <p>Non-steroidal anti-inflammatory drugs (NSAIDs) are recommended for multimodal postoperative pain management. We evaluated opioid-sparing effects and rehabilitative results after perioperative celecoxib administration for total knee arthroplasty.</p> <p>Methods</p> <p>This was a prospective, randomized, observer-blind control study. Eighty patients that underwent total knee arthroplasty were randomized into two groups of 40 each. The study group received a single 400 mg dose of celecoxib, one hour before surgery, and 200 mg of celecoxib every 12 hours for five days, along with patient-controlled analgesic (PCA) morphine. The control group received only PCA morphine for postoperative pain management. Visual analog scale (VAS) pain scores, active range of motion (ROM), total opioid use and postoperative nausea/vomiting were analyzed.</p> <p>Results</p> <p>Groups were comparable for age, pre-operative ROM, operation duration and intraoperative blood loss. Resting VAS pain scores improved significantly in the celecoxib group, compared with controls, at 48 hrs (2.13 ± 1.68 vs. 3.43 ± 1.50, p = 0.03) and 72 hrs (1.78 ± 1.66 vs. 3.17 ± 2.01, p = 0.02) after surgery. Active ROM also increased significantly in the patients that received celecoxib, especially in the first 72 hrs [40.8° ± 17.3° vs. 25.8° ± 11.5°, p = 0.01 (day 1); 60.7° ± 18.1° vs. 45.0° ± 17.3°, p = 0.004 (day 2); 77.7° ± 15.1° vs. 64.3° ± 16.9°, p = 0.004 (day 3)]. Opioid requirements decreased about 40% (p = 0.03) in the celecoxib group. Although patients suffering from post-operative nausea/vomiting decreased from 43% in control group to 28% in celecoxib group, this was not significant (p = 0.57). There were no differences in blood loss (intra- and postoperative) between the groups. Celecoxib resulted in no significant increase in the need for blood transfusions.</p> <p>Conclusion</p> <p>Perioperative celecoxib significantly improved postoperative resting pain scores at 48 and 72 hrs, opioid consumption, and active ROM in the first three days after total knee arthroplasty, without increasing the risks of bleeding.</p> <p>Trial registration</p> <p>Clinicaltrials.gov NCT00598234</p

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Automated Detection of External Ventricular and Lumbar Drain-Related Meningitis Using Laboratory and Microbiology Results and Medication Data

OBJECTIVE: Monitoring of healthcare-associated infection rates is important for infection control and hospital benchmarking. However, manual surveillance is time-consuming and susceptible to error. The aim was, therefore, to develop a prediction model to retrospectively detect drain-related meningitis (DRM), a frequently occurring nosocomial infection, using routinely collected data from a clinical data warehouse. METHODS: As part of the hospital infection control program, all patients receiving an external ventricular (EVD) or lumbar drain (ELD) (2004 to 2009; n = 742) had been evaluated for the development of DRM through chart review and standardized diagnostic criteria by infection control staff; this was the reference standard. Children, patients dying <24 hours after drain insertion or with <1 day follow-up and patients with infection at the time of insertion or multiple simultaneous drains were excluded. Logistic regression was used to develop a model predicting the occurrence of DRM. Missing data were imputed using multiple imputation. Bootstrapping was applied to increase generalizability. RESULTS: 537 patients remained after application of exclusion criteria, of which 82 developed DRM (13.5/1000 days at risk). The automated model to detect DRM included the number of drains placed, drain type, blood leukocyte count, C-reactive protein, cerebrospinal fluid leukocyte count and culture result, number of antibiotics started during admission, and empiric antibiotic therapy. Discriminatory power of this model was excellent (area under the ROC curve 0.97). The model achieved 98.8% sensitivity (95% CI 88.0% to 99.9%) and specificity of 87.9% (84.6% to 90.8%). Positive and negative predictive values were 56.9% (50.8% to 67.9%) and 99.9% (98.6% to 99.9%), respectively. Predicted yearly infection rates concurred with observed infection rates. CONCLUSION: A prediction model based on multi-source data stored in a clinical data warehouse could accurately quantify rates of DRM. Automated detection using this statistical approach is feasible and could be applied to other nosocomial infections

Heterologous Expression and Maturation of an NADP-Dependent [NiFe]-Hydrogenase: A Key Enzyme in Biofuel Production

Hydrogen gas is a major biofuel and is metabolized by a wide range of microorganisms. Microbial hydrogen production is catalyzed by hydrogenase, an extremely complex, air-sensitive enzyme that utilizes a binuclear nickel-iron [NiFe] catalytic site. Production and engineering of recombinant [NiFe]-hydrogenases in a genetically-tractable organism, as with metalloprotein complexes in general, has met with limited success due to the elaborate maturation process that is required, primarily in the absence of oxygen, to assemble the catalytic center and functional enzyme. We report here the successful production in Escherichia coli of the recombinant form of a cytoplasmic, NADP-dependent hydrogenase from Pyrococcus furiosus, an anaerobic hyperthermophile. This was achieved using novel expression vectors for the co-expression of thirteen P. furiosus genes (four structural genes encoding the hydrogenase and nine encoding maturation proteins). Remarkably, the native E. coli maturation machinery will also generate a functional hydrogenase when provided with only the genes encoding the hydrogenase subunits and a single protease from P. furiosus. Another novel feature is that their expression was induced by anaerobic conditions, whereby E. coli was grown aerobically and production of recombinant hydrogenase was achieved by simply changing the gas feed from air to an inert gas (N2). The recombinant enzyme was purified and shown to be functionally similar to the native enzyme purified from P. furiosus. The methodology to generate this key hydrogen-producing enzyme has dramatic implications for the production of hydrogen and NADPH as vehicles for energy storage and transport, for engineering hydrogenase to optimize production and catalysis, as well as for the general production of complex, oxygen-sensitive metalloproteins

Proximal correlates of metabolic phenotypes during ‘at-risk' and ‘case' stages of the metabolic disease continuum

Extent: 11p.OBJECTIVE: To examine the social and behavioural correlates of metabolic phenotypes during ‘at-risk’ and ‘case’ stages of the metabolic disease continuum. DESIGN: Cross-sectional study of a random population sample. PARTICIPANTS: A total of 718 community-dwelling adults (57% female), aged 18--92 years from a regional South Australian city. MEASUREMENTS: Total body fat and lean mass and abdominal fat mass were assessed by dual energy x-ray absorptiometry. Fasting venous blood was collected in the morning for assessment of glycated haemoglobin, plasma glucose, serum triglycerides, cholesterol lipoproteins and insulin. Seated blood pressure (BP) was measured. Physical activity and smoking, alcohol and diet (96-item food frequency), sleep duration and frequency of sleep disordered breathing (SDB) symptoms, and family history of cardiometabolic disease, education, lifetime occupation and household income were assessed by questionnaire. Current medications were determined by clinical inventory. RESULTS: 36.5% were pharmacologically managed for a metabolic risk factor or had known diabetes (‘cases’), otherwise were classified as the ‘at-risk’ population. In both ‘at-risk’ and ‘cases’, four major metabolic phenotypes were identified using principal components analysis that explained over 77% of the metabolic variance between people: fat mass/insulinemia (FMI); BP; lipidaemia/lean mass (LLM) and glycaemia (GLY). The BP phenotype was uncorrelated with other phenotypes in ‘cases’, whereas all phenotypes were inter-correlated in the ‘at-risk’. Over and above other socioeconomic and behavioural factors, medications were the dominant correlates of all phenotypes in ‘cases’ and SDB symptom frequency was most strongly associated with FMI, LLM and GLY phenotypes in the ‘at-risk’. CONCLUSION: Previous research has shown FMI, LLM and GLY phenotypes to be most strongly predictive of diabetes development. Reducing SDB symptom frequency and optimising the duration of sleep may be important concomitant interventions to standard diabetes risk reduction interventions. Prospective studies are required to examine this hypothesis.MT Haren, G Misan, JF Grant, JD Buckley, PRC Howe, AW Taylor, J Newbury and RA McDermot

Characterization and genome sequencing of a Citrobacter freundii phage CfP1 harboring a lysin active against multidrug-resistant isolates

Citrobacter spp., although frequently ignored, is emerging as an important nosocomial bacterium able to cause various superficial and systemic life-threatening infections. Considered to be hard-to-treat bacterium due to its pattern of high antibiotic resistance, it is important to develop effective measures for early and efficient therapy. In this study, the first myovirus (vB_CfrM_CfP1) lytic for Citrobacter freundii was microbiologically and genomically characterized. Its morphology, activity spectrum, burst size, and biophysical stability spectrum were determined. CfP1 specifically infects C. freundii, has broad host range (>85 %; 21 strains tested), a burst size of 45 PFU/cell, and is very stable under different temperatures (20 to 50 °C) and pH (3 to 11) values. CfP1 demonstrated to be highly virulent against multidrug-resistant clinical isolates up to 12 antibiotics, including penicillins, cephalosporins, carbapenems, and fluroquinoles. Genomically, CfP1 has a dsDNA molecule with 180,219 bp with average GC content of 43.1 % and codes for 273 CDSs. The genome architecture is organized into function-specific gene clusters typical for tailed phages, sharing 46 to 94 % nucleotide identity to other Citrobacter phages. The lysin gene encoding a predicted D-Ala-D-Ala carboxypeptidase was also cloned and expressed in Escherichia coli and its activity evaluated in terms of pH, ionic strength, and temperature. The lysine optimum activity was reached at 20 mM HEPES, pH 7 at 37 °C, and was able to significantly reduce all C. freundii (>2 logs) as well as Citrobacter koseri (>4 logs) strains tested. Interestingly, the antimicrobial activity of this enzyme was performed without the need of pretreatment with outer membrane-destabilizing agents. These results indicate that CfP1 lysin is a good candidate to control problematic Citrobacter infections, for which current antibiotics are no longer effective.This study was funded by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, COMPETE 2020 (POCI-01-0145-FEDER006684), and the PhD grants SFRH/BPD/111653/2015 and SFRH/BPD/69356/2010

Proximal correlates of metabolic phenotypes during ‘at-risk' and ‘case' stages of the metabolic disease continuum

Extent: 11p.OBJECTIVE: To examine the social and behavioural correlates of metabolic phenotypes during ‘at-risk’ and ‘case’ stages of the metabolic disease continuum. DESIGN: Cross-sectional study of a random population sample. PARTICIPANTS: A total of 718 community-dwelling adults (57% female), aged 18--92 years from a regional South Australian city. MEASUREMENTS: Total body fat and lean mass and abdominal fat mass were assessed by dual energy x-ray absorptiometry. Fasting venous blood was collected in the morning for assessment of glycated haemoglobin, plasma glucose, serum triglycerides, cholesterol lipoproteins and insulin. Seated blood pressure (BP) was measured. Physical activity and smoking, alcohol and diet (96-item food frequency), sleep duration and frequency of sleep disordered breathing (SDB) symptoms, and family history of cardiometabolic disease, education, lifetime occupation and household income were assessed by questionnaire. Current medications were determined by clinical inventory. RESULTS: 36.5% were pharmacologically managed for a metabolic risk factor or had known diabetes (‘cases’), otherwise were classified as the ‘at-risk’ population. In both ‘at-risk’ and ‘cases’, four major metabolic phenotypes were identified using principal components analysis that explained over 77% of the metabolic variance between people: fat mass/insulinemia (FMI); BP; lipidaemia/lean mass (LLM) and glycaemia (GLY). The BP phenotype was uncorrelated with other phenotypes in ‘cases’, whereas all phenotypes were inter-correlated in the ‘at-risk’. Over and above other socioeconomic and behavioural factors, medications were the dominant correlates of all phenotypes in ‘cases’ and SDB symptom frequency was most strongly associated with FMI, LLM and GLY phenotypes in the ‘at-risk’. CONCLUSION: Previous research has shown FMI, LLM and GLY phenotypes to be most strongly predictive of diabetes development. Reducing SDB symptom frequency and optimising the duration of sleep may be important concomitant interventions to standard diabetes risk reduction interventions. Prospective studies are required to examine this hypothesis.MT Haren, G Misan, JF Grant, JD Buckley, PRC Howe, AW Taylor, J Newbury and RA McDermot