{"title":"Modeling T Cell Fate.","authors":"Rob J De Boer, Andrew J Yates","doi":"10.1146/annurev-immunol-101721-040924","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":8271,"journal":{"name":"Annual review of immunology","volume":"41 ","pages":"513-532"},"PeriodicalIF":26.9000,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11100019/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual review of immunology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1146/annurev-immunol-101721-040924","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
引用次数: 0
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.
天真 T 细胞分化为效应亚群和记忆亚群以及维持这些亚群的许多途径仍存在争议。近年来，我们开发出了多种实验工具，可以跟踪细胞及其后代的命运。在这篇综述中，我们将介绍数学模型如何为描述细胞群的生长、丢失和分化提供一种自然语言。通过编码细胞行为的机理描述，模型可帮助我们解释这些新数据集，并揭示稳态和免疫反应期间 T 细胞命运决定的基本规则。
期刊介绍：
The Annual Review of Immunology, in publication since 1983, focuses on basic immune mechanisms and molecular basis of immune diseases in humans. Topics include innate and adaptive immunity; immune cell development and differentiation; immune control of pathogens (viruses, bacteria, parasites) and cancer; and human immunodeficiency and autoimmune diseases. The current volume of this journal has been converted from gated to open access through Annual Reviews' Subscribe to Open program, with all articles published under a CC BY license.
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