<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-17T03:53:20Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:2445/174783" metadataPrefix="marc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:2445/174783</identifier><datestamp>2025-12-05T14:51:49Z</datestamp><setSpec>com_2072_1057</setSpec><setSpec>col_2072_478917</setSpec><setSpec>col_2072_478924</setSpec></header><metadata><record xmlns="http://www.loc.gov/MARC21/slim" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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      <subfield code="a">González-Domínguez, Raúl</subfield>
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      <subfield code="a">Jáuregui Pallarés, Olga</subfield>
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      <subfield code="a">Queipo Ortuño, María Isabel</subfield>
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      <subfield code="a">Andrés Lacueva, Ma. Cristina</subfield>
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      <subfield code="c">2020-09-23</subfield>
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      <subfield code="a">The exposome, defined as the cumulative measure of external exposures and associated biological responses throughout the lifespan, has emerged in recent years as a cornerstone in biomedical sciences. Metabolomics stands out here as one of the most powerful tools for investigating the interplay between the genetic background, exogenous, and endogenous factors within human health. However, to address the complexity of the exposome, novel methods are needed to characterize the human metabolome. In this work, we have optimized and validated a multianalyte metabolomics platform for large-scale quantitative exposome research in plasma and urine samples, based on the use of simple extraction methods and high-throughput metabolomic fingerprinting. The methodology enables, for the first time, the simultaneous characterization of the endogenous metabolome, food-related metabolites, pharmaceuticals, household chemicals, environmental pollutants, and microbiota derivatives, comprising more than 1000 metabolites in total. This comprehensive and quantitative investigation of the exposome is achieved in short run times, through simple extraction methods requiring small-sample volumes, and using integrated quality control procedures for ensuring data quality. This metabolomics approach was satisfactorily validated in terms of linearity, recovery, matrix effects, specificity, limits of quantification, intraday and interday precision, and carryover. Furthermore, the clinical potential of the methodology was demonstrated in a dietary intervention trial as a case study. In summary, this study describes the optimization, validation, and application of a multimetabolite platform for comprehensive and quantitative metabolomics-based exposome research with great utility in large-scale epidemiological studies.</subfield>
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      <subfield code="a">Characterization of the human exposome by a comprehensive and quantitative large scale multi-analyte metabolomics platform</subfield>
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