Insights from mathematical modelling for T cell migration into the central nervous system

T. Ruck;S. Bittner;S. G. Meuth;M. Herty
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引用次数: 4

Abstract

The migration of immune cells from peripheral immune organs into the central nervous system (CNS) through the blood–brain barrier (BBB) is a tightly regulated process. The complex interplay between cells of the BBB and immune cells coordinates cell migration as a part of normal immune surveillance while its dysregulation is critically involved in the pathogenesis of various CNS diseases. To develop tools for a deeper understanding of distribution and migratory pattern of immune cells regulated by the BBB, we made use of a mathematical modelling approach derived from Markov chain theory. We present a data-driven model using a derivation of kinetic differential equations from a particle game. According to the theory of gases, these equations allow one to predict the mean behaviour of a large class of cells by modelling cell–cell interactions. We used this model to assess the distribution of naive, central memory and effector memory T lymphocytes in the peripheral blood and cerebrospinal fluid. Our model allows us to evaluate the impact of activation status, migratory capacity and cell death for cell distribution in the peripheral blood and the CNS.
从T细胞迁移到中枢神经系统的数学模型的见解
免疫细胞从外周免疫器官通过血脑屏障(BBB)向中枢神经系统(CNS)迁移是一个受到严格调控的过程。血脑屏障细胞与免疫细胞之间的复杂相互作用协调细胞迁移,作为正常免疫监视的一部分,而其失调在各种中枢神经系统疾病的发病机制中至关重要。为了开发更深入了解血脑屏障调节的免疫细胞分布和迁移模式的工具,我们使用了源自马尔可夫链理论的数学建模方法。我们提出了一个数据驱动的模型,使用从粒子游戏的动力学微分方程的推导。根据气体理论,这些方程允许人们通过模拟细胞间的相互作用来预测一大类细胞的平均行为。我们使用该模型来评估外周血和脑脊液中初始、中枢记忆和效应记忆T淋巴细胞的分布。我们的模型使我们能够评估激活状态、迁移能力和细胞死亡对外周血和中枢神经系统细胞分布的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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