Abstract
Many of the pathways that underlie the diversification of naive T cells into effector and memory subsets, and the maintenance of these populations, remain controversial. In recent years a variety of experimental tools have been developed that allow us to follow the fates of cells and their descendants. In this review we describe how mathematical models provide a natural language for describing the growth, loss, and differentiation of cell populations. By encoding mechanistic descriptions of cell behavior, models can help us interpret these new datasets and reveal the rules underpinning T cell fate decisions, both at steady state and during immune responses.
Original language | English |
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Pages (from-to) | 513-532 |
Number of pages | 20 |
Journal | Annual Review of Immunology |
Volume | 41 |
DOIs | |
Publication status | Published - 26 Apr 2023 |
Bibliographical note
Publisher Copyright:© 2023 Annual Reviews Inc.. All rights reserved.
Funding
Funders | Funder number |
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National Institutes of Health | R01 AI093870, U01 AI150680 |
Keywords
- Humans
- Animals
- T-Lymphocytes
- Cell Differentiation
- Immunologic Memory
- T-Lymphocyte Subsets
- CD8-Positive T-Lymphocytes