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dc.contributor.authorGonzález-Durruthy, Michael
dc.contributor.authorMonserrat, José M.
dc.contributor.authorRasulev, Bakhtiyor
dc.contributor.authorCasañola-Martín, Gerardo M.
dc.contributor.authorBarreiro Sorrivas, José María
dc.contributor.authorParaíso-Medina, Sergio
dc.contributor.authorMaojo, Víctor
dc.contributor.authorGonzález-Díaz, Humberto
dc.contributor.authorMunteanu, Cristian-Robert
dc.contributor.authorPazos, A.
dc.date.accessioned2018-01-18T18:27:18Z
dc.date.available2018-01-18T18:27:18Z
dc.date.issued2017-11-11
dc.identifier.citationGonzález-Durruthy, M.; Monserrat, J.M.; Rasulev, B.; Casañola-Martín, G.M.; Barreiro Sorrivas, J.M.; Paraíso-Medina, S.; Maojo, V.; González-Díaz, H.; Pazos, A.; Munteanu, C.R. Carbon Nanotubes’ Effect on Mitochondrial Oxygen Flux Dynamics: Polarography Experimental Study and Machine Learning Models using Star Graph Trace Invariants of Raman Spectra. Nanomaterials 2017, 7, 386.es_ES
dc.identifier.issn2079-4991
dc.identifier.urihttp://hdl.handle.net/2183/20010
dc.description.abstract[Abstract] This study presents the impact of carbon nanotubes (CNTs) on mitochondrial oxygen mass flux (Jm) under three experimental conditions. New experimental results and a new methodology are reported for the first time and they are based on CNT Raman spectra star graph transform (spectral moments) and perturbation theory. The experimental measures of Jm showed that no tested CNT family can inhibit the oxygen consumption profiles of mitochondria. The best model for the prediction of Jm for other CNTs was provided by random forest using eight features, obtaining test R-squared (R2) of 0.863 and test root-mean-square error (RMSE) of 0.0461. The results demonstrate the capability of encoding CNT information into spectral moments of the Raman star graphs (SG) transform with a potential applicability as predictive tools in nanotechnology and material risk assessmentses_ES
dc.description.sponsorshipInstituto de Salud Carlos III; PI13/02020
dc.description.sponsorshipInstituto de Salud Carlos III; PI13/00280
dc.description.sponsorshipGalicia. Consellería de Cultura, Educación e Ordenación Universitaria; R2014/025
dc.description.sponsorshipGalicia. Consellería de Cultura, Educación e Ordenación Universitaria; GRC2014/049
dc.description.sponsorshipGalicia. Consellería de Cultura, Educación e Ordenación Universitaria; R2014/039
dc.description.sponsorshipMinisterio de Economía y Competitividad; UNLC08-1E-002
dc.description.sponsorshipMinisterio de Economía y Competitividad ; UNLC13-13-3503
dc.description.sponsorshipMinisterio de Economía y Competitividad; CTQ2016-74881-P
dc.description.sponsorshipPaís Vasco.Gobierno; IT1045-16
dc.description.sponsorshipBrasil. Conselho Nacional de Desenvolvimento Científico e Tecnológico; 308539/2016-8
dc.description.sponsorshipBrasil. Conselho Nacional de Desenvolvimento Científico e Tecnológico; 454332/2014-9
dc.language.isoenges_ES
dc.publisherM D P I AGes_ES
dc.relation.urihttp://dx.doi.org/10.3390/nano7110386es_ES
dc.rightsAtribución 3.0 Españaes_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectCarbon nanotubeses_ES
dc.subjectCytotoxicityes_ES
dc.subjectMitochondria oxygen mass fluxes_ES
dc.subjectRaman spectroscopyes_ES
dc.subjectGraph theoryes_ES
dc.subjectSpectral momentses_ES
dc.titleCarbon Nanotubes’ Effect on Mitochondrial Oxygen Flux Dynamics: Polarography Experimental Study and Machine Learning Models using Star Graph Trace Invariants of Raman Spectraes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleNanomaterialses_ES
UDC.volume7es_ES
UDC.issue11es_ES
UDC.startPage386es_ES
dc.identifier.doi10.3390/nano7110386


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