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Modeling the Dependence of Immunodominance on T Cell Dynamics in Prime-Boost Vaccines

dc.contributor.authorFernandez Arias, Clemente
dc.contributor.authorHerrero, Miguel Angel
dc.contributor.authorBertocchini, Federica
dc.contributor.authorAcosta, Francisco Javier
dc.contributor.authorFernández Arias, Cristina
dc.date.accessioned2025-01-20T16:33:25Z
dc.date.available2025-01-20T16:33:25Z
dc.date.issued2020-12-24
dc.description.abstractThe protection induced by vaccines against infectious diseases such as malaria, dengue or hepatitis relies on a the creation of immune memory by T cells, key components of the human immune system. The induction of a strong T cell response leading to long lasting memory can be improved by using prime-boost (PB) vaccines, which consist in successive inoculations of appropriate vectors carrying target antigens that can be recognized by specific T cell clones. A problem faced by PB vaccines is the fact that T cell response is often biased towards a few clones that can identify only a small set of antigens, out of the many that could be displayed by the pathogen. This phenomenon, known as immunodominance, can significantly compromise the effectiveness of vaccination. In this work we will use mathematical modeling to better understand the role of T cell population dynamics in the onset of immunodominance in PB vaccines. In particular, we will use mathematical analysis and simulations to compare single-dose vaccines with PB ones, both for homologous (where the same antigen is used in every shot) and heterologous protocols (in which different antigens are used at each step).
dc.description.departmentDepto. de Inmunología, Oftalmología y ORL
dc.description.facultyFac. de Medicina
dc.description.refereedTRUE
dc.description.sponsorshipMinisterio de Economía, Comercio y Empresa
dc.description.statuspub
dc.identifier.citationArias, C.F.; Herrero, M.A.; Bertocchini, F.; Acosta, F.J.; Fernandez-Arias, C. Modeling the Dependence of Immunodominance on T Cell Dynamics in Prime-Boost Vaccines. Mathematics 2021, 9, 28. https://doi.org/10.3390/math9010028
dc.identifier.doi10.3390/math9010028
dc.identifier.officialurlhttps://doi.org/10.3390/math9010028
dc.identifier.relatedurlhttps://www.mdpi.com/2227-7390/9/1/28
dc.identifier.urihttps://hdl.handle.net/20.500.14352/115210
dc.issue.number1
dc.journal.titleMathematics
dc.language.isoeng
dc.page.initial28
dc.publisherMPDI
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2017-85020-P/ES/MODELOS MATEMATICOS DE HOMEOSTASIS DE POBLACIONES CELULARES/
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.cdu612.017
dc.subject.keywordT cells
dc.subject.keywordImmunodominance
dc.subject.keywordPopulation mechanics
dc.subject.keywordPrime-boost vaccines
dc.subject.ucmCiencias
dc.subject.unesco24 Ciencias de la Vida
dc.titleModeling the Dependence of Immunodominance on T Cell Dynamics in Prime-Boost Vaccines
dc.typejournal article
dc.type.hasVersionVoR
dc.volume.number9
dspace.entity.typePublication
relation.isAuthorOfPublicationf26f5638-897d-497a-8cf6-cc53b75aae34
relation.isAuthorOfPublication.latestForDiscoveryf26f5638-897d-497a-8cf6-cc53b75aae34

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