FragHub: A Mass Spectral Library Data Integration Workflow.

Open mass spectral libraries (OMSLs) are critical for metabolite annotation and machine learning, especially given the rising volume of untargeted metabolomic studies and the development of annotation pipelines. Despite their importance, the practical application of OMSLs is hampered by the lack of standardized file formats, metadata fields, and supporting ontology. Current libraries, often restricted to specific topics or matrices, such as natural products, lipids, or the human metabolome, may limit the discovery potential of untargeted studies.

Challenges and perspectives for naming lipids in the context of lipidomics.

Introduction: Lipids are key compounds in the study of metabolism and are increasingly studied in biology projects. It is a very broad family that encompasses many compounds, and the name of the same compound may vary depending on the community where they are studied.

Objectives: In addition, their structures are varied and complex, which complicates their analysis.

Suggesting disease associations for overlooked metabolites using literature from metabolic neighbors.

In human health research, metabolic signatures extracted from metabolomics data have a strong added value for stratifying patients and identifying biomarkers. Nevertheless, one of the main challenges is to interpret and relate these lists of discriminant metabolites to pathological mechanisms. This task requires experts to combine their knowledge with information extracted from databases and the scientific literature.

Redefining the decisional components of motor responses: Evidence from lexical and object decision tasks.

Models of decision making focusing on two-alternative choices have classically described motor-response execution as a nondecisional stage that serially follows the termination of decision processes. Recent evidence, however, points toward a more continuous transition between decision and motor processes. We investigated this transition in two lexical decisions and one object decision task.

Relationship between depression, anxiety, stress, and SARS-CoV-2 infection: a longitudinal study.

Objectives: We aimed to (1) describe the course of the emotional burden (i.e., depression, anxiety, and stress) in a general population sample during the coronavirus pandemic in 2020 and 2021 and (2) explore the association between emotional burden and a serologically proven infection with SARS-CoV-2.

PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management.

Introduction: Accuracy of feature annotation and metabolite identification in biological samples is a key element in metabolomics research. However, the annotation process is often hampered by the lack of spectral reference data in experimental conditions, as well as logistical difficulties in the spectral data management and exchange of annotations between laboratories.

Objectives: To design an open-source infrastructure allowing hosting both nuclear magnetic resonance (NMR) and mass spectra (MS), with an ergonomic Web interface and Web services to support metabolite annotation and laboratory data management.

Teachers' emotional well-being during the SARS-CoV-2 pandemic with long school closures: a large-scale cross-sectional survey in Northern Italy.

Objectives: This study aimed to evaluate the magnitude of emotional burden on teaching staff during the SARS-CoV-2 pandemic in a significantly impacted region. In addition, the correlates of emotional burden were analysed to enable the design of targeted interventions.

Study Design: This study was a cross-sectional survey.

FORUM: building a Knowledge Graph from public databases and scientific literature to extract associations between chemicals and diseases.

Motivation: Metabolomics studies aim at reporting a metabolic signature (list of metabolites) related to a particular experimental condition. These signatures are instrumental in the identification of biomarkers or classification of individuals, however their biological and physiological interpretation remains a challenge. To support this task, we introduce FORUM: a Knowledge Graph (KG) providing a semantic representation of relations between chemicals and biomedical concepts, built from a federation of life science databases and scientific literature repositories.

WiPP: Workflow for Improved Peak Picking for Gas Chromatography-Mass Spectrometry (GC-MS) Data.

Lack of reliable peak detection impedes automated analysis of large-scale gas chromatography-mass spectrometry (GC-MS) metabolomics datasets. Performance and outcome of individual peak-picking algorithms can differ widely depending on both algorithmic approach and parameters, as well as data acquisition method. Therefore, comparing and contrasting between algorithms is difficult.

Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies.

The life sciences are currently being transformed by an unprecedented wave of developments in molecular analysis, which include important advances in instrumental analysis as well as biocomputing. In light of the central role played by metabolism in nutrition, metabolomics is rapidly being established as a key analytical tool in human nutritional studies. Consequently, an increasing number of nutritionists integrate metabolomics into their study designs.

The future of metabolomics in ELIXIR.

Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community.

Create, run, share, publish, and reference your LC-MS, FIA-MS, GC-MS, and NMR data analysis workflows with the Workflow4Metabolomics 3.0 Galaxy online infrastructure for metabolomics.

Metabolomics is a key approach in modern functional genomics and systems biology. Due to the complexity of metabolomics data, the variety of experimental designs, and the multiplicity of bioinformatics tools, providing experimenters with a simple and efficient resource to conduct comprehensive and rigorous analysis of their data is of utmost importance. In 2014, we launched the Workflow4Metabolomics (W4M; http://workflow4metabolomics.

A Computational Solution to Automatically Map Metabolite Libraries in the Context of Genome Scale Metabolic Networks.

This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc) and flat file formats (SBML and Matlab files). We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics) and Glasgow Polyomics (GP) on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database.

Can we trust untargeted metabolomics? Results of the metabo-ring initiative, a large-scale, multi-instrument inter-laboratory study.

The metabo-ring initiative brought together five nuclear magnetic resonance instruments (NMR) and 11 different mass spectrometers with the objective of assessing the reliability of untargeted metabolomics approaches in obtaining comparable metabolomics profiles. This was estimated by measuring the proportion of common spectral information extracted from the different LCMS and NMR platforms. Biological samples obtained from 2 different conditions were analysed by the partners using their own in-house protocols.

Assessment of protein modifications in liver of rats under chronic treatment with paracetamol (acetaminophen) using two complementary mass spectrometry-based metabolomic approaches.

Unlabelled: Liver protein can be altered under paracetamol (APAP) treatment. APAP-protein adducts and other protein modifications (oxidation/nitration, expression) play a role in hepatotoxicity induced by acute overdoses, but it is unknown whether liver protein modifications occur during long-term treatment with non-toxic doses of APAP. We quantified APAP-protein adducts and assessed other protein modifications in the liver from rats under chronic (17 days) treatment with two APAP doses (0.

Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics.

Summary: The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology.

TriAnnot: A Versatile and High Performance Pipeline for the Automated Annotation of Plant Genomes.

In support of the international effort to obtain a reference sequence of the bread wheat genome and to provide plant communities dealing with large and complex genomes with a versatile, easy-to-use online automated tool for annotation, we have developed the TriAnnot pipeline. Its modular architecture allows for the annotation and masking of transposable elements, the structural, and functional annotation of protein-coding genes with an evidence-based quality indexing, and the identification of conserved non-coding sequences and molecular markers. The TriAnnot pipeline is parallelized on a 712 CPU computing cluster that can run a 1-Gb sequence annotation in less than 5 days.

Impairment of recognition memory with, but not without, conscious recollection in schizophrenia.

Objective: To test the hypothesis that there is a link between the memory deficit associated with schizophrenia and an impairment of consciousness, an experiential approach was used to assess recognition memory and awareness in schizophrenic patients and normal subjects.

Method: On a recognition memory task with low- and high-frequency words, the schizophrenic (N = 30) and normal (N = 30) subjects gave "remember" responses to recognized items that were accompanied by conscious recollection and "know" responses to items that were recognized on the basis of familiarity without any recollective experience.

Results: Schizophrenia selectively impaired recognition based on recollective experience, as measured by "remember" responses, but had no effects on "know" responses.

[Efficacy of antidepressants and thymoregulators in the long-term evolution of depression].

Official recommendations pointed out the long term maintenance treatment of recurrent unipolar depression on the basis of a significant effect of antidepressants and mood-stabilizers versus placebo. The results of controlled studies, mainly using imipramine or lithium salts, have not been encouraging in term of long term prognosis, due to the limited success rate for maintenance phase ranging from 30 to 48%. The "Pittsburgh study" maximized the recurrence potential by defining patients selection on at least 3 previous episodes of unipolar depression, with the immediate previous episode being no more than 2.