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An artificial immune-memory model based on idiotypic immune networks: Perspectives on antibody dynamics

机译:基于独特型免疫网络的人工免疫记忆模型:抗体动力学的观点

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Immune memories of antigens are formed as limit behavior of antibody dynamics, which is a simplified model of cyclic idiotypic immune networks. Rapid responses of immune systems to secondary antigens are due to the memory recalls of the stored antigenic attributes. The immune-memory mechanism is studied by combining network structure and dynamical systems. Moreover, associative memory can be explored by network dynamics of a cross-correlation matrix determined by an antibody chain. Analysis of cross-reactive immune responses can be accomplished by introducing the overlapping difference function p of network dynamics. Classification of four types of memory recalls was performed here. It explains the phenomena of associative memory and provides methods for control of vaccinations via tuning of suitable parameters. Other issues with immune memory and cyclic idiotypic immune networks are also discussed.
机译:抗原的免疫记忆形成为抗体动力学的极限行为,这是循环独特型免疫网络的简化模型。免疫系统对次级抗原的快速反应归因于所存储的抗原属性的记忆调用。通过结合网络结构和动力学系统研究免疫记忆机制。此外,可以通过由抗体链确定的互相关矩阵的网络动力学来探索联想记忆。交叉反应免疫反应的分析可以通过引入网络动力学的重叠差异函数p来完成。此处对四种类型的记忆调用进行了分类。它解释了联想记忆的现象,并提供了通过调整合适参数来控制疫苗接种的方法。还讨论了免疫记忆和循环独特型免疫网络的其他问题。

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