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MicrobiomeDB (http://microbiomeDB.org) is a data discovery and analysis platform that empowers researchers to fully leverage experimental variables to interrogate microbiome datasets. MicrobiomeDB was developed in collaboration with the Eukaryotic Pathogens Bioinformatics Resource Center (http://EuPathDB.org) and leverages the infrastructure and user interface of EuPathDB, which allows users to construct in silico experiments using an intuitive graphical 'strategy' approach. The current release of the database integrates microbial census data with sample details for nearly 14 000 samples originating from human, animal and environmental sources, including over 9000 samples from healthy human subjects in the Human Microbiome Project (http://portal.ihmpdcc.org/). Query results can be statistically analyzed and graphically visualized via interactive web applications launched directly in the browser, providing insight into microbial community diversity and allowing users to identify taxa associated with any experimental covariate., (© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The Eukaryotic Pathogen Genomics Database Resource (EuPathDB, http://eupathdb.org) is a collection of databases covering 170+ eukaryotic pathogens (protists & fungi), along with relevant free-living and non-pathogenic species, and select pathogen hosts. To facilitate the discovery of meaningful biological relationships, the databases couple preconfigured searches with visualization and analysis tools for comprehensive data mining via intuitive graphical interfaces and APIs. All data are analyzed with the same workflows, including creation of gene orthology profiles, so data are easily compared across data sets, data types and organisms. EuPathDB is updated with numerous new analysis tools, features, data sets and data types. New tools include GO, metabolic pathway and word enrichment analyses plus an online workspace for analysis of personal, non-public, large-scale data. Expanded data content is mostly genomic and functional genomic data while new data types include protein microarray, metabolic pathways, compounds, quantitative proteomics, copy number variation, and polysomal transcriptomics. New features include consistent categorization of searches, data sets and genome browser tracks; redesigned gene pages; effective integration of alternative transcripts; and a EuPathDB Galaxy instance for private analyses of a user's data. Forthcoming upgrades include user workspaces for private integration of data with existing EuPathDB data and improved integration and presentation of host-pathogen interactions., (© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Purpose: Cardiac biomarkers including troponins are the cornerstone of the biological definition of acute myocardial infarction. New high-sensitivity cardiac assays determining troponin T (hs-cTnT) as well as I ((hs-cTnI) from Abbott and s-cTnI from Siemens) raise concerns because of their unclear kinetics following the peak., Aims: This study aims to compare kinetics of creatine kinases, hs-cTnT, hs-cTnI and s-cTnI in patients with ST-segment elevation myocardial infarction (STEMI) treated by percutaneous coronary intervention., Methods: We prospectively studied 106 consecutive patients admitted in our institution for STEMI and treated by percutaneous coronary intervention. We evaluated for all the patients simultaneously kinetics of creatine kinases, hs-cTnT (Roche) and two different cTnIs (hs-cTnI from Abbott and s-cTnI from Siemens). Modelling of kinetics was realized using mixed effects with cubic splines., Results: Kinetics of markers showed a first peak at 10.7h (8.0-12.0) for creatine kinases, 11.8h (10.4-13.3) for hs-cTnT (Roche); 11.8h (10.7-11.8) for hs-cTnI from Abbott and 10.2h (8.7-11.6) for s-cTnI from Siemens, respectively. This peak was followed by a nearly log linear decrease for hs-cTnI/s-cTnI and creatine kinases in contrast to hs-cTnT, which appeared with a biphasic shape curve marked by a second peak at 76.9h (69.5-82.8). The analysis of the decrease in percentage of the peak value at 77h showed that hs-cTnT follows a twice lower decrease than other markers., Conclusion: Kinetics of hs-cTnT, hs-cTnI and s-cTnI differ significantly with a linear decrease regarding both cTnI assays contrasting with a biphasic shape curve for hs-cTnT. This is of importance for clinical management of patients in routine settings especially in follow-up after STEMI including the suspicion of reinfarction., (© The European Society of Cardiology 2015.)

EuPathDB (http://eupathdb.org) resources include 11 databases supporting eukaryotic pathogen genomic and functional genomic data, isolate data and phylogenomics. EuPathDB resources are built using the same infrastructure and provide a sophisticated search strategy system enabling complex interrogations of underlying data. Recent advances in EuPathDB resources include the design and implementation of a new data loading workflow, a new database supporting Piroplasmida (i.e. Babesia and Theileria), the addition of large amounts of new data and data types and the incorporation of new analysis tools. New data include genome sequences and annotation, strand-specific RNA-seq data, splice junction predictions (based on RNA-seq), phosphoproteomic data, high-throughput phenotyping data, single nucleotide polymorphism data based on high-throughput sequencing (HTS) and expression quantitative trait loci data. New analysis tools enable users to search for DNA motifs and define genes based on their genomic colocation, view results from searches graphically (i.e. genes mapped to chromosomes or isolates displayed on a map) and analyze data from columns in result tables (word cloud and histogram summaries of column content). The manuscript herein describes updates to EuPathDB since the previous report published in NAR in 2010.

Objective: The main goal of this study was to evaluate if the edge-to-edge mitral repair could be a limiting factor for exercise tolerance and to compare these results to those of classical techniques., Methods: Between 2000 and 2002, 54 consecutive patients were operated on for mitral valve regurgitation (MR). Twenty-five patients were operated with Alfieri's technique (group A) and 29 patients with Carpentier's technique (group C). The mean age was 63.9 years in group A and 63.8 years in group C (p = 0.98). After a mean follow-up of 16.2+/-12 months, survivor patients were seen at the outpatient clinic, by the same physician for a clinical evaluation, an echocardiogram at rest and at peak exercise, and received a cardiorespiratory exercise testing with maximal oxygen uptake (VO2 max) recording., Results: Clinical status improved with 0% of the patients in class NYHA III or IV in either group postoperatively versus 77% preoperatively. There was no significant MR in 80% of cases in group A versus 89.6% in group C (p = 0.54). The mean mitral valve area was 2.5 and 2.9 cm2 in groups A and C, respectively (p = 0.018). The mitral gradient at rest was 3.8 and 3.3 mmHg (p = 0.31) and the mitral gradient at peak exercise was 8.5 and 9.7 mmHg (p = 0.22) in groups A and C, respectively. Cardiorespiratory exercise testing showed a mean VO2 max of 73.7+/-15% of normal value in group A versus 79.6+/-13.1% in group C (p = 0.18)., Conclusion: Alfieri's technique has the same efficiency on improvement of MR and clinical status than classical repair. Despite a higher restriction of mitral valve area at rest in group A, gradient and mean VO2 max at peak exercise were similar in both groups.