Mostrar el registro sencillo del ítem
dc.contributor.author
Fernández Do Porto, Darío Augusto
dc.contributor.author
Auzmendi, Jerónimo Andrés
dc.contributor.author
Peña, Delfina
dc.contributor.author
Garcia, Veronica Edith
dc.contributor.author
Moffatt, Luciano
dc.date.available
2015-05-19T13:25:10Z
dc.date.issued
2013-02-20
dc.identifier.citation
Fernández Do Porto, Darío Augusto; Auzmendi, Jerónimo Andrés; Peña, Delfina; Garcia, Veronica Edith; Moffatt, Luciano; Bayesian Approach to Model CD137 Signaling in Human M.tuberculosis in vitro Responses; Public Library Science; Plos One; 8; 2; 20-2-2013; 1-18;
dc.identifier.issn
1932-6203
dc.identifier.uri
http://hdl.handle.net/11336/496
dc.description.abstract
Abstract
Immune responses are qualitatively and quantitatively influenced by a complex network of receptor-ligand interactions. Among them, the CD137:CD137L pathway is known to modulate innate and adaptive human responses against Mycobacterium tuberculosis. However, the underlying mechanisms of this regulation remain unclear. In this work, we developed a Bayesian Computational Model (BCM) of in vitro CD137 signaling, devised to fit previously gathered experimental data. The BCM is fed with the data and the prior distribution of the model parameters and it returns theirposterior distribution and the model evidence, which allows comparing alternative signaling mechanisms. The BCM uses a coupled system of non-linear differential equations to describe the dynamics of Antigen Presenting Cells, Natural Killer and T Cells together with the interpheron (IFN)-c and tumor necrosis factor (TNF)-a levels in the media culture. Fast and complete mixing of the media is assumed. The prior distribution of the parameters that describe the dynamics of the immunological response was obtained from the literature and theoretical considerations Our BCM applies successively the Levenberg-Marquardt algorithm to find the maximum a posteriori likelihood (MAP); the Metropolis Markov Chain Monte Carlo method to approximate the posterior distribution of the parameters and Thermodynamic Integration to calculate the evidence of alternative hypothesis. Bayes factors provided decisive evidence favoring direct CD137 signaling on T cells. Moreover, the posterior distribution of the parameters that describe the CD137 signaling showed that the regulation of IFNc levels is based more on T cells survival than on direct induction. Furthermore, the mechanisms that account for the effect of CD137 signaling on TNF-a production were based on a decrease of TNF-a production by APC and, perhaps, on the increase in APC apoptosis. BCM proved to be a useful tool to gain insight on the mechanisms of CD137 signaling during human response against Mycobacterium tuberculosis.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Public Library Science
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Cd137
dc.subject
Bayesian
dc.subject
Tuberculosis
dc.subject.classification
Ciencias Naturales y Exactas
dc.subject.classification
Ciencias Biológicas
dc.subject.classification
Biología (teórica, Matemática, Térmica, Criobiología, Ritmos Biológicos), Biología Evolutiva
dc.title
Bayesian Approach to Model CD137 Signaling in Human M.tuberculosis in vitro Responses
dc.type
info:eu-repo/semantics/publishedVersion
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.date.updated
2016-03-30 10:35:44.97925-03
dc.journal.volume
8
dc.journal.number
2
dc.journal.pagination
1-18
dc.journal.pais
Estados Unidos
dc.journal.ciudad
San Francisco
dc.description.fil
Fil: Darío A Fernández Do Porto. UNIV.DE BUENOS AIRES. FAC.DE CS.EXACTAS Y NATURALES. UNIV.DE BUENOS AIRES. FAC.DE CS.EXACTAS Y NATURALES. INST QUIM FISICA D/L/MATERIALES MED AMB Y ENERG.
dc.description.fil
Fil: Jerónimo Auzmendi. UNIV.DE BUENOS AIRES. FAC.DE CS.EXACTAS Y NATURALES. INST QUIM FISICA D/L/MATERIALES MED AMB Y ENERG.
dc.description.fil
Fil: Delfina Peña. UNIV.DE BUENOS AIRES. FAC.DE CS.EXACTAS Y NATURALES. CONSEJO NAC.DE INVEST.CIENTIF.Y TECNICAS. OFICINA DE COORDINACION ADMINISTRATIVA CIUDAD UNIVERSITARIA. INSTITUTO DE QUIMICA BIOLOGICA DE LA FACULTAD DE CS. EXACTAS Y NATURALES. UNIV.DE BUENOS AIRES. FAC.DE CS.EXACTAS Y NATURALES. DTO.DE QUIMICA BIOLOGICA.
dc.description.fil
Fil: Veronica E Garcia. CONSEJO NAC.DE INVEST.CIENTIF.Y TECNICAS. OFICINA DE COORDINACION ADMINISTRATIVA CIUDAD UNIVERSITARIA. INSTITUTO DE QUIMICA BIOLOGICA DE LA FACULTAD DE CS. EXACTAS Y NATURALES.
dc.description.fil
Fil: Luciano Moffatt. UNIV.DE BUENOS AIRES. FAC.DE CS.EXACTAS Y NATURALES. INST QUIM FISICA D/L/MATERIALES MED AMB Y ENERG.
dc.journal.title
Plos One
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1371/journal.pone.0055987.
Archivos asociados