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PLoS One. 2015 Aug 24;10(8):e0135787. doi: 10.1371/journal.pone.0135787. eCollection 2015.

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

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Systems Medicine of Infectious Diseases group and Braunschweig Integrated Centre of Systems Biology, Department of Systems Immunology, Helmholtz Centre for Infection Research, Inhoffenstrasse 7, 38124 Braunschweig, Germany.
Laboratorio di Microbiologia Molecolare e Biotecnologie, Dipartimento di Biotecnologie Mediche, Università di Siena, Viale Bracci 1, 53100 Siena, Italy.
Dipartimento di Ingegneria dell'Informazione e Science Matematiche, Università di Siena, Via Roma 56, 53100 Siena, Italy.


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.

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