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dc.contributor.authorGil Solsona, Ruben
dc.contributor.authorSancho, Juan V
dc.contributor.authorGassner, Anne-Laure
dc.contributor.authorCéline, Weyermann
dc.contributor.authorHernández Domínguez, Félix
dc.contributor.authorDelémont, Olivier
dc.contributor.authorBijlsma, Lubertus
dc.date.accessioned2021-06-08T08:06:08Z
dc.date.available2021-06-08T08:06:08Z
dc.date.issued2021-03-10
dc.identifier.citationGil-Solsona R, Sancho JV,Gassner A-L, et al. Use of ion mobility-high resolution massspectrometry in metabolomics studies to provide near MS/MSquality data in a single injection. J Mass Spectrom. 2021;56:e4718.https://doi.org/10.1002/jms.471812 of 12 GIL-SOLSONA ET AL.ca_CA
dc.identifier.issn1076-5174
dc.identifier.issn1096-9888
dc.identifier.urihttp://hdl.handle.net/10234/193309
dc.description.abstractThe use of ion mobility separations (IMSs) in metabolomics approaches has started to be deeply explored in the last years. In this work, the use of liquid chromatography (LC) coupled to IMS-quadrupole time-of-flight mass spectrometry (QTOF MS) has been evaluated in a metabolomics experiments using single injection of the samples. IMS has allowed obtaining cleaner fragmentation spectra, of nearly tandem MS quality, in data-independent acquisition mode. This is much useful in this research area as a second injection, generally applied in LC-QTOF MS workflows to obtain tandem mass spectra, is not necessary, saving time and evading possible compound degradation. As a case study, the smoke produced after combustion of herbal blends used to spray synthetic cannabinoids has been selected as study matrix. The smoke components were trapped in carbon cartridges, desorbed and analyzed by LC-IMS-QTOF MS using different separation mechanisms (reversed phase and HILIC) and acquiring in both positive and negative mode to widen the chemical domain. Partial Least Squares–Discriminant Analysis highlighted several compounds, and ratio between N-Isopropyl-3-(isoquinolinyl)-2-propen-1-amine and quinoline allowed differentiating between tobacco and herbal products. These two compounds were tentatively identified using the cleaner fragmentation spectra from a single injection in the IMS-QTOF MS, with additional confidence obtained by retention time (Rt) and collisional cross section (CCS) prediction using artificial neural networks. Data from this work show that LC-IMS-QTOF is an efficient technique in untargeted metabolomics, avoiding re-injection of the samples for elucidation purposes. In addition, the prediction models for Rt and CCS resulted of help in the elucidation process of potential biomarkers.ca_CA
dc.format.extent22 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherJohn Wiley and Sonsca_CA
dc.publisherWileyca_CA
dc.relation.isPartOfJ Mass Spectrom. 2021;56:e4718.ca_CA
dc.relation.urihttps://analyticalsciencejournals.onlinelibrary.wiley.com/doi/full/10.1002/jms.4718#pane-pcw-figuresca_CA
dc.rights© 2021 John Wiley & Sons, Ltd.ca_CA
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/*
dc.subjectherbal blends smokeca_CA
dc.subjecthigh resolution mass spectrometryca_CA
dc.subjectin-silico predictionca_CA
dc.subjection mobilityca_CA
dc.subjectomics approachesca_CA
dc.titleUse of ion mobility-high resolution mass spectrometry in metabolomics studies to provide near MS/MS quality data in a single injectionca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttps://doi.org/10.1002/jms.4718
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttp://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1096-9888cca_CA
dc.type.versioninfo:eu-repo/semantics/submittedVersionca_CA
project.funder.nameEuropean Commissionca_CA
project.funder.nameEuropean Cooperation in Science and Technologyca_CA
project.funder.nameGeneralitat Valencianaca_CA
project.funder.nameMinisterio de Economía y Competitividadca_CA
project.funder.nameUniversitat Jaume Ica_CA
oaire.awardNumberHOME/2014/JDRUG/AG/DRUG/7086ca_CA
oaire.awardNumberCOST-STSM-ES1307-150916-080342ca_CA
oaire.awardNumberGroup of Excellence Prometeo II 2019/040ca_CA
oaire.awardNumberProject CTQ2015-65603-Pca_CA
oaire.awardNumberUJI-B2016-10ca_CA


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