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  • 标题:Mathematical modeling and simulation for a coupled communication system of immune cells *
  • 本地全文:下载
  • 作者:Shinji Nakaoka
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2015
  • 卷号:48
  • 期号:18
  • 页码:41-46
  • DOI:10.1016/j.ifacol.2015.11.008
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractImmune cells play a central role in preventing the invasion of several types of antigens, including bacteria, viruses, and foreign proteins. CD4 positive T cells belong to a subset of immune cells that facilitate adaptive immune responses by promoting activation of other immune cell types. The population of CD4 positive T cells is further classified into subsets, known as helper T (Th) cells, according to the behavior of cells. Th1 cells produce cytokines that reduce viral infection, while Th2 cells mainly facilitate an allergic response against parasites. The process of commitment to one of these subsets is determined by numerous complicated events. Communication via cytokine is one major factor that determines the commitment of naive Th cells to Th1 or Th2 cells. Mutual inhibition among these subsets is known at the transcriptional regulation of associated genes that characterize the behavior of each subset. Although an adequate control of the balance between two subsets is essential, the mechanistic description toward control for the commitment process has not yet been fully investigated. We construct a mathematical model that describes interactions between these two subsets via secretion of cytokines. We incorporate reciprocal inhibition into our model to describe the exclusive commitment of cells as a decision making process. The main system contains positive feedback loops. The dominant state of one subset can be observed, representing adequate recognition for the type of antigen. Extensive numerical simulations suggest that the switch of dominance can occur with external perturbation. The model can serve as a guideline to control the balance of subset constitution to adequately promote immune response.
  • 关键词:Keywordsmathematical modelpopulation dynamicsimmunotherapycancercellular and humoral immunity
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