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dc.contributor.author
Domínguez Romero, Juan C.
dc.contributor.author
García Reyes, Juan F.
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Martínez Romero, Rubén
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Berton, Paula
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Martínez Lara, Esther
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Del Moral Leal, María L.
dc.contributor.author
Molina Díaz, Antonio
dc.date.available
2015-11-10T14:21:53Z
dc.date.issued
2013-01-25
dc.identifier.citation
Domínguez Romero, Juan C.; García Reyes, Juan F.; Martínez Romero, Rubén; Berton, Paula; Martínez Lara, Esther; et al.; Combined data mining strategy for the systematic identification of sport drug metabolites in urine by liquid chromatography time-of-flight mass spectrometry; Elsevier Science; Analytica Chimica Acta; 761; 25-1-2013; 1-10
dc.identifier.issn
0003-2670
dc.identifier.uri
http://hdl.handle.net/11336/2722
dc.description.abstract
The development of comprehensive methods able to tackle with the systematic identification of drug metabolites in an automated fashion is of great interest. In this article, a strategy based on the combined use of two complementary data mining tools is proposed for the screening and systematic detection and identification of urinary drug metabolites by liquid chromatography full-scan high resolution mass spectrometry. The proposed methodology is based on the use of accurate mass extraction of diagnostic ions (compound-dependent information) from in-source CID fragmentation without precursor ion isolation along with the use of automated mass extraction of accurate-mass shifts corresponding to typical biotransformations (non compound-dependent information) that xenobiotics usually undergo when metabolized. The combined strategy was evaluated using LC-TOFMS with a suite of nine sport drugs representative from different classes (propranolol, bumetanide, clenbuterol, ephedrine, finasteride, methoxyphenamine, methylephedrine, salbutamol and terbutaline), after single doses administered to rats. The metabolite identification coverage rate obtained with the systematic method (compared to existing literature) was satisfactory, and provided the identification of several non-previously reported metabolites. In addition, the combined information obtained helps to minimize the number of false positives. As an example, the systematic identification of urinary metabolites of propranolol enabled the identification of up to 24 metabolites, 15 of them non previously described in literature, which is a valuable indicator of the usefulness of the proposed systematic procedure.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier Science
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Liquid Chromatography
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High Resolution Mass Spectrometry
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Drug Metabolites
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Sport Drug Testing
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Propranolol
dc.subject.classification
Química Analítica
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Ciencias Químicas
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CIENCIAS NATURALES Y EXACTAS
dc.title
Combined data mining strategy for the systematic identification of sport drug metabolites in urine by liquid chromatography time-of-flight mass spectrometry
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2016-03-30 10:35:44.97925-03
dc.journal.volume
761
dc.journal.pagination
1-10
dc.journal.pais
Países Bajos
dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Domínguez Romero, Juan C.. Universidad de Jaén; España
dc.description.fil
Fil: García Reyes, Juan F.. Universidad de Jaén; España
dc.description.fil
Fil: Martínez Romero, Rubén. Universidad de Jaén; España
dc.description.fil
Fil: Berton, Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Científico Tecnológico Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentina
dc.description.fil
Fil: Martínez Lara, Esther. Universidad de Jaén; España
dc.description.fil
Fil: Del Moral Leal, María L.. Universidad de Jaén; España
dc.description.fil
Fil: Molina Díaz, Antonio. Universidad de Jaén; España
dc.journal.title
Analytica Chimica Acta
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.aca.2012.11.049
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0003267012017266
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