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

Authors :
Catharina C. Gross
Marc Pawlitzki
Andreas Schulte-Mecklenbeck
Leoni Rolfes
Tobias Ruck
Petra Hundehege
Heinz Wiendl
Michael Herty
Sven G. Meuth
Source :
International Journal of Molecular Sciences, Vol 21, Iss 6, p 2046 (2020)
Publication Year :
2020
Publisher :
MDPI AG, 2020.

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.

Details

Language :
English
ISSN :
14220067
Volume :
21
Issue :
6
Database :
Directory of Open Access Journals
Journal :
International Journal of Molecular Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.09fbc6affe7947bc9a5da76c17e726f8
Document Type :
article
Full Text :
https://doi.org/10.3390/ijms21062046