Modeling Memory T-Cell Differentiation
Brynja Kohler (Utah State University)
(April 17, 2008 10:30 AM - 11:30 AM)
The adaptive immune system has the convenient feature of being able to remember and defend the body against previously encountered pathogens, rendering long-term immunity to an individual who survives an initial acute infection. T-cell populations accomplish this task through their expansion and differentiation into subtypes of cells with effector (useful for eliminating pathogen) and memory (surviving) capabilities. Simple mathematical models using systems of ordinary differential equations can capture the dynamics of typical immune responses, and these models are useful for predicting proliferation and death rates of various subcategories of T cells. We discuss some findings based on parameter fitting in these basic models which assume a variety of differentiation pathways. We also present and discuss a T-cell population model that assumes that differentiation to memory cells is a continuous process dependent on the strength and duration of antigen exposure. This new model consists of a coupled pair of partial differential equations and results in a translating solution of the heat equation. Interestingly, this same mathematical model has been used to describe and analyze transport along nerve axons.