title: Mathematically modeling dynamics of T cell responses: predictions concerning the generation of memory cells.
abstract: Mathematical models of T cell population dynamics after infection typically assume that T cells differentiate according to a linear process in which they first become effector cells, and then after some time, differentiate further into memory cells. In this paper, we offer a different mathematical model which can equally well capture T cell dynamics, using data from lymphocytic choriomeningitis (LCMV) infection. Our model assumes that memory cells are intermediates that further differentiate into effector cells only from additional or stronger antigenic stimulation. Our assumption naturally leads to a testable prediction about the generation of T cell memory-that the memory phenotype of T cells should be present in detectable numbers during the expansion phase of the response. We use our model to estimate a rate of differentiation from memory type cells to effectors. We argue that this differentiation assumption, where memory cells are intermediates, captures recent experimental work on T cell differentiation, and hence this new mathematical model could be helpful in doing further studies of T cell population dynamics. We also propose a method of distinguishing the models by examining the ratio of memory T cells detectable long after an infection to the peak numbers of T cells at the end of the expansion phase.
authors.affiliation: Department of Mathematics and Statistics, Utah State University, 3900 Old Main Hill, Logan, UT 84322, USA. kohler@math.usu.edu
authors.forename: Brynja
authors.initials: B
authors.lastname: Kohler
mesh_terms: D015496:CD4-Positive T-Lymphocytes / Q000276:immunology; D018414:CD8-Positive T-Lymphocytes / Q000276:immunology; D002454:Cell Differentiation / Q000276:immunology; D006801:Humans; D007156:Immunologic Memory / Q000276:immunology*; D008213:Lymphocyte Activation / Q000276:immunology; D018655:Lymphocyte Count; D008216:Lymphocytic Choriomeningitis / Q000276:immunology; D008433:Mathematics; D018448:Models, Immunological; D016176:T-Lymphocyte Subsets / Q000276:immunology; D013601:T-Lymphocytes / Q000276:immunology*