A mathematical model of dynamics of cell populations in squamous epithelium after irradiation

dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Matemática Aplicada
dc.contributor.authorPaga Pazos, Martín
dc.contributor.authorLópez Pouso, Óscar
dc.contributor.authorFenwick, John D.
dc.contributor.authorPardo Montero, Juan
dc.date.accessioned2024-12-20T08:38:36Z
dc.date.available2024-12-20T08:38:36Z
dc.date.issued2019-05-15
dc.descriptionThis is an original manuscript of an article published by Taylor & Francis in International Journal of Radiation Biology on 17 Jul 2020, available at: https://doi.org/10.1080/09553002.2020.1787540
dc.description.abstractPurpose To develop multi-compartment mechanistic models of dynamics of stem and functional cell populations in epithelium after irradiation. Methods and materials: We present two models, with three (3C) and four (4C) compartments respectively. We use delay differential equations, and include accelerated proliferation, loss of division asymmetry, progressive death of abortive stem cells, and turnover of functional cells. The models are used to fit experimental data on the variations of the number of cells in mice mucosa after irradiation with 13 Gy and 20 Gy. Akaike information criteria (AIC) was used to evaluate the performance of each model. Results Both 3C and 4C models provide good fits to experimental data for 13 Gy. Fits for 20 Gy are slightly poorer and may be affected by larger uncertainties and fluctuations of experimental data. Best fits are obtained by imposing constraints on the fitting parameters, so to have values that are within experimental ranges. There is some degeneration in the fits, as different sets of parameters provide similarly good fits. Conclusions The models provide good fits to experimental data. Mechanistic approaches like this can facilitate the development of mucositis response models to nonstandard schedules/treatment combinations not covered by datasets to which phenomenological models have been fitted. Studying the dynamics of cell populations in multifraction treatments, and finding links with induced toxicity, is the next step of this work.
dc.description.peerreviewedSI
dc.description.sponsorshipThis project was funded by Instituto de Salud Carlos III (ISCIII) through research grants PI17/01428 and DTS17/00123 (FEDER co-funding). J.P-M. is supported by ISCIII through a Miguel Servet II grant [CPII17/00028, FEDER co-funding]. O.L.P. is partially supported by FEDER and Xunta de Galicia [GRC2013-014], and by the Spanish Ministry of Science, Innovation and Universities [MTM2017-86459-R]
dc.identifier.citationParga-Pazos, M., López Pouso, Ó., Fenwick, J. D., & Pardo-Montero, J. (2020). A mathematical model of dynamics of cell populations in squamous epithelium after irradiation. International Journal of Radiation Biology, 1-8. https://doi.org/10.1080/09553002.2020.1787540
dc.identifier.doi10.1080/09553002.2020.1787540
dc.identifier.issn1362-3095
dc.identifier.urihttps://hdl.handle.net/10347/38251
dc.issue.number9
dc.journal.titleInternational Journal of Radiation Biology
dc.language.isoeng
dc.page.final1172
dc.page.initial1165
dc.publisherTaylor & Francis
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2017-86459-R/ES/APLICACIONES DE LA MODELIZACION, LA SIMULACION NUMERICA, LA OPTIMIZACION Y EL CONTROL OPTIMO AL DISEÑO DE DISPOSITIVOS Y PROCESOS INDUSTRIALES/
dc.relation.publisherversionhttps://doi.org/10.1080/09553002.2020.1787540
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectBiomathematical model
dc.subjectRadiotherapy
dc.subjectMucositis
dc.subjectRadiobiology
dc.titleA mathematical model of dynamics of cell populations in squamous epithelium after irradiation
dc.typejournal article
dc.type.hasVersionAM
dc.volume.number96
dspace.entity.typePublication
relation.isAuthorOfPublication4c1cc53c-ed78-438f-9b41-716b1eabc09b
relation.isAuthorOfPublication.latestForDiscovery4c1cc53c-ed78-438f-9b41-716b1eabc09b

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