Department of Mathematics and Computer Science, University of Richmond, Richmond, VA 23173, USA.
Bull Math Biol. 2013 Sep;75(9):1434-49. doi: 10.1007/s11538-013-9854-1. Epub 2013 May 31.
The human immune response to bacterial pathogens is a remarkably complex process, involving many different cell types, chemical signals, and extensive lines of communication. Mathematical models of this system have become increasingly high-dimensional and complicated, as researchers seek to capture many of the major dynamics. In this paper, we argue that, in some important instances, preference should be given to low-dimensional models of immune response, as opposed to their high-dimensional counterparts. One such model is analyzed and shown to reflect many of the key phenomenological properties of the immune response in humans. Notably, this model includes a single parameter that, when combined with a single set of reference parameter values, may be used to quantify the overall immunocompetence of individual hosts.
人体对细菌病原体的免疫反应是一个非常复杂的过程，涉及许多不同的细胞类型、化学信号和广泛的通讯线路。随着研究人员试图捕捉许多主要的动力学，该系统的数学模型变得越来越高维且复杂。在本文中，我们认为，在某些重要情况下，应该优先选择免疫反应的低维模型，而不是它们的高维对应物。分析了这样一个模型，并表明它反映了人类免疫反应的许多关键现象学特性。值得注意的是，该模型包含一个单一的参数，当与一组单一的参考参数值结合使用时，可以用于量化个体宿主的整体免疫能力。
