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生成一个模型以预测在稳态和中枢神经系统自身炎症条件下淋巴细胞亚群的分化和迁移。

Generation of a Model to Predict Differentiation and Migration of Lymphocyte Subsets under Homeostatic and CNS Autoinflammatory Conditions.

机构信息

Department of Neurology with Institute of Translational Neurology, University Hospital Münster, Albert-Schweitzer-Campus 1, Building A01, D-48149 Münster, Germany.

Institute of Geometry and Applied Mathematics, RWTH Aachen University, Templergraben 55, D-52056 Aachen, Germany.

出版信息

Int J Mol Sci. 2020 Mar 17;21(6):2046. doi: 10.3390/ijms21062046.

Abstract

The central nervous system (CNS) is an immune-privileged compartment that is separated from the circulating blood and the peripheral organs by the blood-brain and the blood-cerebrospinal fluid (CSF) barriers. Transmigration of lymphocyte subsets across these barriers and their activation/differentiation within the periphery and intrathecal compartments in health and autoinflammatory CNS disease are complex. Mathematical models are warranted that qualitatively and quantitatively predict the distribution and differentiation stages of lymphocyte subsets in the blood and CSF. Here, we propose a probabilistic mathematical model that (i) correctly reproduces acquired data on location and differentiation states of distinct lymphocyte subsets under homeostatic and neuroinflammatory conditions, (ii) provides a quantitative assessment of differentiation and transmigration rates under these conditions, (iii) correctly predicts the qualitative behavior of immune-modulating therapies, (iv) and enables simulation-based prediction of distribution and differentiation stages of lymphocyte subsets in the case of limited access to biomaterial. Taken together, this model might reduce future measurements in the CSF compartment and allows for the assessment of the effectiveness of different immune-modulating therapies.

摘要

中枢神经系统(CNS)是一个免疫特权区域,通过血脑屏障和血脑脊液(CSF)屏障与循环血液和外周器官隔开。淋巴细胞亚群穿过这些屏障并在外周和鞘内隔间内激活/分化,在健康和自身炎症性中枢神经系统疾病中是复杂的。需要有数学模型来定性和定量地预测淋巴细胞亚群在血液和 CSF 中的分布和分化阶段。在这里,我们提出了一个概率数学模型,该模型(i)正确再现了在稳态和神经炎症条件下不同淋巴细胞亚群的位置和分化状态的获得数据,(ii)在这些条件下提供了分化和迁移率的定量评估,(iii)正确预测免疫调节治疗的定性行为,(iv)并能够在生物材料获取有限的情况下,基于模拟预测淋巴细胞亚群的分布和分化阶段。总之,该模型可能会减少 CSF 隔室中的未来测量,并评估不同免疫调节治疗的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c666/7139518/0263a537e34d/ijms-21-02046-g001.jpg

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