A Stochastic Model for CD4+ T Cell Proliferation and Dissemination Network in Primary Immune Response.

Boianelli, Alessandro; Pettini, Elena; Prota, Gennaro; Medaglini, Donata; Vicino, Antonio

dc.contributor.author	Boianelli, Alessandro
dc.contributor.author	Pettini, Elena
dc.contributor.author	Prota, Gennaro
dc.contributor.author	Medaglini, Donata
dc.contributor.author	Vicino, Antonio
dc.date.accessioned	2015-09-15T08:47:04Z	en
dc.date.available	2015-09-15T08:47:04Z	en
dc.date.issued	2015	en
dc.identifier.citation	A Stochastic Model for CD4+ T Cell Proliferation and Dissemination Network in Primary Immune Response. 2015, 10 (8):e0135787 PLoS ONE	en
dc.identifier.issn	1932-6203	en
dc.identifier.pmid	26301680	en
dc.identifier.doi	10.1371/journal.pone.0135787	en
dc.identifier.uri	http://hdl.handle.net/10033/577312	en
dc.description.abstract	The study of the initial phase of the adaptive immune response after first antigen encounter provides essential information on the magnitude and quality of the immune response. This phase is characterized by proliferation and dissemination of T cells in the lymphoid organs. Modeling and identifying the key features of this phenomenon may provide a useful tool for the analysis and prediction of the effects of immunization. This knowledge can be effectively exploited in vaccinology, where it is of interest to evaluate and compare the responses to different vaccine formulations. The objective of this paper is to construct a stochastic model based on branching process theory, for the dissemination network of antigen-specific CD4+ T cells. The devised model is validated on in vivo animal experimental data. The model presented has been applied to the vaccine immunization context making references to simple proliferation laws that take into account division, death and quiescence, but it can also be applied to any context where it is of interest to study the dynamic evolution of a population.
dc.language.iso	en	en
dc.title	A Stochastic Model for CD4+ T Cell Proliferation and Dissemination Network in Primary Immune Response.	en
dc.type	Article	en
dc.contributor.department	Helmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany.	en
dc.identifier.journal	PloS one	en
refterms.dateFOA	2018-06-13T07:28:36Z
html.description.abstract	The study of the initial phase of the adaptive immune response after first antigen encounter provides essential information on the magnitude and quality of the immune response. This phase is characterized by proliferation and dissemination of T cells in the lymphoid organs. Modeling and identifying the key features of this phenomenon may provide a useful tool for the analysis and prediction of the effects of immunization. This knowledge can be effectively exploited in vaccinology, where it is of interest to evaluate and compare the responses to different vaccine formulations. The objective of this paper is to construct a stochastic model based on branching process theory, for the dissemination network of antigen-specific CD4+ T cells. The devised model is validated on in vivo animal experimental data. The model presented has been applied to the vaccine immunization context making references to simple proliferation laws that take into account division, death and quiescence, but it can also be applied to any context where it is of interest to study the dynamic evolution of a population.