Combinatorial perturbation analysis of CD4+ T cell regulatory networks based on bifurcation theory

Exploring the dynamics of the CD4+ T regulatory network holds paramount significance in scientific research, as it deepens our understanding of the immune system’s intricacies and drives the development of innovative interventions for immune-related disorders. Despite the numerous studies conducted,...

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Veröffentlicht in:Advances in continuous and discrete models Jg. 2025; H. 1; S. 24
Hauptverfasser: Lu, Xiaoqi, Hu, Qing, Xue, Zhuozhen, Wang, Ruiqi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 03.02.2025
Springer Nature B.V
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ISSN:2731-4235, 1687-1839, 2731-4235, 1687-1847
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Zusammenfassung:Exploring the dynamics of the CD4+ T regulatory network holds paramount significance in scientific research, as it deepens our understanding of the immune system’s intricacies and drives the development of innovative interventions for immune-related disorders. Despite the numerous studies conducted, further research is essential to elucidate the roles of exogenous cytokines in immune dynamics. This endeavor is of great importance in advancing targeted therapies and optimizing disease treatment regimens. Based on the bifurcation theory, we conduct a systematic perturbation analysis of the CD4+ T cell regulatory network. Initially, we treat exogenous cytokines as model parameters and conduct single-parameter bifurcation analysis to identify specific exogenous cytokines that can trigger various cell fate transitions. Additionally, based on relevant biological backgrounds, combinatorial perturbation analysis is performed to screen synergistic perturbation combinations. Three distinct types of synergistic combinations are successfully identified. The mechanisms by which different types of combinatorial perturbations exert their effects are also distinct. The individual and combinatorial perturbation analysis provides insights into how exogenous cytokines act synergistically and how these interactions influence the dynamics of CD4+ T cell networks.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2731-4235
1687-1839
2731-4235
1687-1847
DOI:10.1186/s13662-025-03887-y