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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| Published in: | Advances in continuous and discrete models Vol. 2025; no. 1; p. 24 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Cham
Springer International Publishing
03.02.2025
Springer Nature B.V |
| Subjects: | |
| ISSN: | 2731-4235, 1687-1839, 2731-4235, 1687-1847 |
| Online Access: | Get full text |
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| Summary: | 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. |
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| Bibliography: | 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 |