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中文摘要
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我们正在开发T细胞分化和稳态机制的数学和计算模型。在健康个体中,细胞死亡、增殖和分化成具有某些效应功能和增殖潜力的T细胞亚型之间的平衡维持了足够的再循环和外周效应细胞群体。在HIV / SIV感染的个体/恒河猴中,淋巴系统的损伤和外周T细胞(特别是粘膜组织中的外周T细胞)的初始病毒杀伤导致外周效应细胞的立即缺陷,即使在用抗逆转录病毒药物治疗后,这种缺陷也会持续,因为中心(再循环)T细胞的恢复能力被破坏。 我们试图回答以下问题:是什么导致HIV / SIV感染中T细胞增殖和分化的不稳定?这如何表现为T细胞增殖/死亡/分化率的改变?CD 4和CD 8细胞有什么区别?为了回答这些问题,我们开发了描述T细胞分裂、死亡和分化的数学模型。这些模型可以表示为不同细胞群体的大小的动力学的耦合线性常微分方程组。然后,我们试图通过参数优化(拟合)来确定哪个模型能够最精确地匹配实验数据。
英文摘要
We are developing mathematical and computational models of mechanisms of T cell differentiation and homeostasis. In healthy individuals, a balance between cell death, proliferation and differentiation into T cell subtypes with certain effector functions and proliferative potential maintains a sufficient population of recirculating and peripheral effector cells. In HIV / SIV infected individuals / Rhesus macaques, damage to the lymphoid system and the initial viral killing of peripheral T cells especially in the mucosal tissues lead to an immediate deficit of effector cells in the periphery which persists even after treatment with anti-retroviral drugs because the restorative capacity of the central (recirculating) T cells is destroyed. We are trying to answer the following questions: What leads to a destabilization of T cell proliferation and differentiation in HIV / SIV infection? How does this manifest itself as altered proliferation/death/differentiation rates of T cells? What are the differences between CD4 and CD8 cells? To try to answer these questions we develop mathematical models describing the division, death and differentiation of T cells. These models can be represented as sets of coupled linear ordinary differential equations for the dynamics of the sizes of the different cell populations. We then try to determine which model is capable of most precisely matching the experimental data through parameter optimizations (fitting).
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Computational Biology in Systems Immunology and Infectious Disease Modeling
Mathematical Modeling of Cell Population Dynamics
Mathematical Modeling of Cell Population Dynamics
Computational Biology in Systems Immunology and Infectious Disease Modeling
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