26 research outputs found

    The HUPO-PSI standardized spectral library format

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    More and more proteomics datasets are becoming available in public repositories. The knowledge embedded in these datasets can be used to improve peptide identification workflows. Spectral library searching provides a straightforward method to boost identification rates using previously identified spectra. Alternatively, machine learning methods can learn from these spectra to accurately predict the behavior of peptides in a liquid chromatography-mass spectrometry system. At the basis of both approaches are spectral libraries: Unified collections of previously identified spectra. Organizations and projects such as the National Institute of Standards and Technology (NIST), the Global Proteome Machine, PeptideAtlas, PRIDE Archive and MassIVE have all compiled spectral libraries for a multitude of species and experimental setups. A large obstacle, however, is that each organization provides libraries in a different file format. At the software level the problem propagates (if not expands), as different software tools require different file formats. The solution is a standardized spectral library format that is sufficiently flexible to meet all users' demands, but that is also standardized enough to be usable across environments and software packages. This balance is achieved by setting up a standardized framework and a controlled vocabulary with metadata terms, and allow the format to be represented in different forms, such as plain text, JSON and HDF. So far, the required (and optional) meta data has been compiled and added to the PSI-MS ontology, and versions of the text and JSON representations have been drafted. The tabular and HDF representations of the format are in development, as well as converters and validators in various programming languages

    Semaglutide and cardiovascular outcomes in patients with obesity and prevalent heart failure: a prespecified analysis of the SELECT trial

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    Background: Semaglutide, a GLP-1 receptor agonist, reduces the risk of major adverse cardiovascular events (MACE) in people with overweight or obesity, but the effects of this drug on outcomes in patients with atherosclerotic cardiovascular disease and heart failure are unknown. We report a prespecified analysis of the effect of once-weekly subcutaneous semaglutide 2·4 mg on ischaemic and heart failure cardiovascular outcomes. We aimed to investigate if semaglutide was beneficial in patients with atherosclerotic cardiovascular disease with a history of heart failure compared with placebo; if there was a difference in outcome in patients designated as having heart failure with preserved ejection fraction compared with heart failure with reduced ejection fraction; and if the efficacy and safety of semaglutide in patients with heart failure was related to baseline characteristics or subtype of heart failure. Methods: The SELECT trial was a randomised, double-blind, multicentre, placebo-controlled, event-driven phase 3 trial in 41 countries. Adults aged 45 years and older, with a BMI of 27 kg/m2 or greater and established cardiovascular disease were eligible for the study. Patients were randomly assigned (1:1) with a block size of four using an interactive web response system in a double-blind manner to escalating doses of once-weekly subcutaneous semaglutide over 16 weeks to a target dose of 2·4 mg, or placebo. In a prespecified analysis, we examined the effect of semaglutide compared with placebo in patients with and without a history of heart failure at enrolment, subclassified as heart failure with preserved ejection fraction, heart failure with reduced ejection fraction, or unclassified heart failure. Endpoints comprised MACE (a composite of non-fatal myocardial infarction, non-fatal stroke, and cardiovascular death); a composite heart failure outcome (cardiovascular death or hospitalisation or urgent hospital visit for heart failure); cardiovascular death; and all-cause death. The study is registered with ClinicalTrials.gov, NCT03574597. Findings: Between Oct 31, 2018, and March 31, 2021, 17 604 patients with a mean age of 61·6 years (SD 8·9) and a mean BMI of 33·4 kg/m2 (5·0) were randomly assigned to receive semaglutide (8803 [50·0%] patients) or placebo (8801 [50·0%] patients). 4286 (24·3%) of 17 604 patients had a history of investigator-defined heart failure at enrolment: 2273 (53·0%) of 4286 patients had heart failure with preserved ejection fraction, 1347 (31·4%) had heart failure with reduced ejection fraction, and 666 (15·5%) had unclassified heart failure. Baseline characteristics were similar between patients with and without heart failure. Patients with heart failure had a higher incidence of clinical events. Semaglutide improved all outcome measures in patients with heart failure at random assignment compared with those without heart failure (hazard ratio [HR] 0·72, 95% CI 0·60-0·87 for MACE; 0·79, 0·64-0·98 for the heart failure composite endpoint; 0·76, 0·59-0·97 for cardiovascular death; and 0·81, 0·66-1·00 for all-cause death; all pinteraction>0·19). Treatment with semaglutide resulted in improved outcomes in both the heart failure with reduced ejection fraction (HR 0·65, 95% CI 0·49-0·87 for MACE; 0·79, 0·58-1·08 for the composite heart failure endpoint) and heart failure with preserved ejection fraction groups (0·69, 0·51-0·91 for MACE; 0·75, 0·52-1·07 for the composite heart failure endpoint), although patients with heart failure with reduced ejection fraction had higher absolute event rates than those with heart failure with preserved ejection fraction. For MACE and the heart failure composite, there were no significant differences in benefits across baseline age, sex, BMI, New York Heart Association status, and diuretic use. Serious adverse events were less frequent with semaglutide versus placebo, regardless of heart failure subtype. Interpretation: In patients with atherosclerotic cardiovascular diease and overweight or obesity, treatment with semaglutide 2·4 mg reduced MACE and composite heart failure endpoints compared with placebo in those with and without clinical heart failure, regardless of heart failure subtype. Our findings could facilitate prescribing and result in improved clinical outcomes for this patient group. Funding: Novo Nordisk

    A Taxonomically-informed Mass Spectrometry Search Tool for Microbial Metabolomics Data

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    MicrobeMASST, a taxonomically-informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbial-derived metabolites and relative producers, without a priori knowledge, will vastly enhance the understanding of microorganisms’ role in ecology and human health

    The ProteomeXchange consortium in 2020: enabling 'big data' approaches in proteomics

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    The ProteomeXchange (PX) consortium of proteomics resources (http://www.proteomexchange.org) has standardized data submission and dissemination of mass spectrometry proteomics data worldwide since 2012. In this paper, we describe the main developments since the previous update manuscript was published in Nucleic Acids Research in 2017. Since then, in addition to the four PX existing members at the time (PRIDE, PeptideAtlas including the PASSEL resource, MassIVE and jPOST), two new resources have joined PX: iProX (China) and Panorama Public (USA). We first describe the updated submission guidelines, now expanded to include six members. Next, with current data submission statistics, we demonstrate that the proteomics field is now actively embracing public open data policies. At the end of June 2019, more than 14 100 datasets had been submitted to PX resources since 2012, and from those, more than 9 500 in just the last three years. In parallel, an unprecedented increase of data re-use activities in the field, including ‘big data’ approaches, is enabling novel research and new data resources. At last, we also outline some of our future plans for the coming years
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