Muraille E, Thieffry D, Leo O, Kaufman M
Laboratoire de Physiologie Animale, Université Libre de Bruxelles, Belgium. emura@ ulb.ac.be
J Theor Biol. 1996 Dec 7;183(3):285-305. doi: 10.1006/jtbi.1996.0221.
Various models have been proposed for the regulation of the primary immune response. Most of the models focus on the ability of the immune system to control a multiplying pathogen, and take into account the cross-regulations between different immune components. In the present study, we integrate the immune system in the general physiology of the host and consider the interaction between the immune and neuroendocrine systems. In addition to pathogen growth and toxicity, our four-variable model takes into account the toxic consequences for the organism of the immune response itself, as well as a neuro-hormonal retro-control of this immune response. Formally, the dynamics of the model is first explored on the basis of a discrete caricature, with special emphasis on the role of the constitutive feedback loops for determining the essential dynamical behavior of the system. This logical analysis is then completed by a classical continuous approach using differential equations. From a biological point of view, our model accounts for four stable regimes which can be described as "pathogen elimination/organism healthy", "pathogen elimination/ organism death", "pathogen growth/organism death" and "chronic infection". The size of the basins of attraction of these different regimes varies as a function of some crucial parameters. Our model allows moreover to interpret the interplay between pathogen immunogenicity and neuro-hormonal feedback, the effects of stress on immunity and the toxic shock syndrome, in terms of transitions among the steady states.
人们已经提出了各种模型来解释初次免疫反应的调节机制。大多数模型聚焦于免疫系统控制增殖病原体的能力,并考虑了不同免疫成分之间的交叉调节。在本研究中,我们将免疫系统纳入宿主的整体生理学中,并考虑免疫和神经内分泌系统之间的相互作用。除了病原体的生长和毒性外,我们的四变量模型还考虑了免疫反应本身对机体的毒性后果,以及对这种免疫反应的神经激素逆向控制。形式上,首先基于离散的简化模型来探索该模型的动力学,特别强调构成性反馈回路在确定系统基本动力学行为中的作用。然后通过使用微分方程的经典连续方法来完成这种逻辑分析。从生物学角度来看,我们的模型涵盖了四种稳定状态,可描述为“病原体清除/机体健康”、“病原体清除/机体死亡”、“病原体生长/机体死亡”和“慢性感染”。这些不同状态的吸引域大小会根据一些关键参数而变化。此外,我们的模型还能够从稳态之间的转变角度来解释病原体免疫原性与神经激素反馈之间的相互作用、压力对免疫的影响以及中毒性休克综合征。