InterPro in 2017-beyond protein family and domain annotations

InterPro (http://www.ebi.ac.uk/interpro/) is a freely available database used to classify protein sequences into families and to predict the presence of important domains and sites. InterProScan is the underlying software that allows both protein and nucleic acid sequences to be searched against InterPro's predictive models, which are provided by its member databases. Here, we report recent developments with InterPro and its associated software, including the addition of two new databases (SFLD and CDD), and the functionality to include residue-level annotation and prediction of intrinsic disorder. These developments enrich the annotations provided by InterPro, increase the overall number of residues annotated and allow more specific functional inferences

Discovering and linking public omics data sets using the Omics Discovery Index

This work has been supported by the US NIH BD2K grant U54 GM114833 and a National Natural Science Foundation of China grant (61501071). A.I.N. is supported by US National Institute of Health grant (R01-GM-094231). Y.P.-R. is supported by BBSRC ‘PROCESS’ grant (BB/K01997X/1). M.B. is supported by Projects of International Cooperation and Exchanges grant (2014DFB30010). M.W. is supported by an NIH grant (5P41GM103484-07). J.A.V. and N.d.-T. are supported by the Wellcome Trust (grant WT101477MA). T.T. is supported by the BBSRC ‘ProteoGenomics’ grant (BB/L024225/1). E.W.D. and D.S.C. are supported in part by grant (U24 AI117966- 02S1). S.-A.S. is supported in part by US NIH BD2K grant (1U24AI117966-01). M.W. and N.Bandeira were supported by NIH grant (5P41GM103484-07). N.Bandeira was also partially supported as an Alfred P. Sloan Fellow. S.Subramaniam is supported by NIH grants U01 DK097430 and U01 CA19894

Genotoxic effects of daily personal exposure to particle mass and number concentrations on buccal cells

The aim of this study is to assess personal exposure to Particle Number Concentrations (PNC) in four size ranges between 0.3 and 10 μm, and particulate matter (PM1; PM2.5; PM4; PM10) in order to evaluate possible genotoxic effects through a comet assay in buccal cells. A convenience cohort of 30 individuals from a Brazilian medium-sized city was selected. These individuals aged between 20 and 61 and worked in typical job categories (i.e., administrative, commerce, education, general services and transport). They were recruited to perform personal exposure measurements during their typical daily routine activities, totaling 240 h of sampling. The 8-h average mass concentrations in air for volunteers ranged from 2.4 to 31.8 μg m−3 for PM1, 4.2–45.1 μg m−3 for PM2.5, 7.9–66.1 μg m−3 for PM4 and from 23.1 to 131.7 μg m−3 for PM10. The highest PNC variation was found for 0.3–0.5 range, between 14 and 181 particles cm−3, 1 to 14 particles cm−3 for the 0.5–1.0 range, 0.2 to 2 particles cm−3 for the 1.0–2.5 range, and 0.06 to 0.7 particles cm−3 for the 2.5–10 range. Volunteers in the ‘education’ category experienced the lowest inhaled dose of PM2.5 as opposed to those involved in ‘commercial‘ activities with the highest doses for PM10 (1.63 μg kg−1 h−1) and PM2.5 (0.61 μg kg−1 h−1). The predominant cause for these high doses was associated with the proximity of the workplace to the street and vehicle traffic. The comet assay performed in buccal cells indicated that the volunteers in ‘commerce’ category experienced the highest damage to their DeoxyriboNucleic Acid (DNA) compared with the control category (i.e. ‘education’). These results indicate the variability in personal exposure of the volunteers in different groups, and the potential damage to DNA was much higher for those spending time in close proximity to the vehicle sources (e.g. commercial services) leading to exposure to a higher fraction of fine particles. This study builds understanding on the exposure of people in different job categories, and provide policy makers with useful information to tackle this neglected issue

Discovering and linking public omics data sets using the Omics Discovery Index

Biomedical data are being produced at an unprecedented rate owing to the falling cost of experiments and wider access to genomics, transcriptomics, proteomics and metabolomics platforms1, 2. As a result, public deposition of omics data is on the increase. This presents new challenges, including finding ways to store, organize and access different types of biomedical data stored on different platforms. Here, we present the Omics Discovery Index (OmicsDI; http://www.omicsdi.org), an open-source platform that enables access, discovery and dissemination of omics data sets

Appropriateness of prescription of oral anticoagulant therapy in acutely hospitalized older people with atrial fibrillation. Secondary analysis of the SIM-AF cluster randomized clinical trial

Aims: To assess the appropriateness of oral anticoagulant (OAC) prescription and its associated factors in acutely hospitalized elderly patients. Methods: Data were obtained from the prospective phase of SIM-AF (SIMulation-based technologies to improve the appropriate use of oral anticoagulants in hospitalized elderly patients with Atrial Fibrillation) randomized controlled trial, aimed to test whether an educational intervention improved OAC prescription, compared to current clinical practice, in internal medicine wards. In this secondary analysis, appropriateness of OAC prescription was assessed at hospital admission and discharge. Results: For 246 patients, no significant differences were found between arms (odds ratio 1.38, 95% confidence interval [CI] 0.84\u20132.28) in terms of appropriateness of OAC prescription. Globally, 92 patients (37.4%, 95% CI = 31.6\u201343.6%) were inappropriately prescribed or not prescribed at hospital discharge. Among 51 patients inappropriately prescribed, 82% showed errors on dosage, being mainly under-dosed (n = 29, 56.9%), and among 41 inappropriately not prescribed, 98% were taking an antiplatelet drug. Factors independently associated with a lower probability of appropriateness at discharge were those related to a higher risk of bleeding (older age, higher levels of aspartate aminotransferase, history of falls, alcohol consumption) and antiplatelet prescription at admission. The prescription of OACs at admission was the strongest predictor of appropriateness at discharge (odds ratio = 7.43, 95% CI = 4.04\u201313.73). Conclusions: A high proportion of hospitalized older patients with AF remains inappropriately prescribed or nonprescribed with OACs. The management of these patients at hospital admission is the strongest predictor of prescription appropriateness at discharge