A thermodynamic perspective of immune capabilities
A thermodynamic perspective of immune capabilities
复制标题
DOI：
10.1016/j.jtbi.2011.07.027
复制
发表时间：
2011-10-21
影响因子：
2
通讯作者：
Moauro, Francesco
中科院分区：
文献类型：
--
作者：
Agliari, Elena;Barra, Adriano;Moauro, Francesco
我们认为相互作用，通过细胞因子交换，辅助淋巴细胞之间。B淋巴细胞和杀伤淋巴细胞，我们通过三方网络将它们建模为一个独特的系统。每个部分包括相同淋巴细胞亚群的所有不同克隆，它们与其他淋巴细胞的偶联是兴奋性的或抑制性的（反映了细胞因子的诱导和抑制）。首先，我们表明，这个系统可以映射到一个关联的神经网络，其中辅助细胞直接相互作用，并能够分泌细胞因子根据“战略”学习的系统和有益的科普可能的抗原刺激;这种检索的能力对应于一个健康的免疫系统的反应。然后，我们研究了正确检索失败的可能条件，并区分了以下结果：大量淋巴细胞扩增/抑制（例如淋巴增生综合征），亚群失衡（例如HIV，EBV感染）和衰老（被认为是噪音增长）;这些状态与自身免疫性疾病的相关性也得到了强调。最后，我们讨论了如何在每个效应分支（即B和杀伤淋巴细胞）的自我调节作用可以建模的随机过程，最终提供了一个一致的桥梁，在这里介绍的三方网络方法和免疫网络在过去的几十年中发展。(C)2011爱思唯尔有限公司保留所有权利。
We consider the mutual interactions, via cytokine exchanges, among helper lymphocytes. B lymphocytes and killer lymphocytes, and we model them as a unique system by means of a tripartite network. Each part includes all the different clones of the same lymphatic subpopulation, whose couplings to the others are either excitatory or inhibitory (mirroring elicitation and suppression by cytokine). First of all, we show that this system can be mapped into an associative neural network, where helper cells directly interact with each other and are able to secrete cytokines according to "strategies" learn by the system and profitable to cope with possible antigenic stimulation; the ability of such a retrieval corresponds to a healthy reaction of the immune system. We then investigate the possible conditions for the failure of a correct retrieval and distinguish between the following outcomes: massive lymphocyte expansion/suppression (e.g. lymphoproliferative syndromes), subpopulation unbalance (e.g. HIV, EBV infections) and ageing (thought of as noise growth); the correlation of such states to autoimmune diseases is also highlighted. Lastly, we discuss how self-regulatory effects within each effector branch (i.e. B and killer lymphocytes) can be modeled in terms of a stochastic process, ultimately providing a consistent bridge between the tripartite-network approach introduced here and the immune networks developed in the last decades. (C) 2011 Elsevier Ltd. All rights reserved.