COMPUTER MODELS OF THE IMMUNE SYSTEM

我们建议使用现代大规模计算来开发和分析 技术，免疫系统关键方面的模型， 理解免疫调节的最终目标。很难 在没有数学模型的情况下，理解大型 根据非线性动力学定律相互作用的元素系统。 由于体内现象涉及大量的 免疫系统成分，体外实验未能提供答案， 许多关键问题。 我们寻求开发新一代的模型，我们可以探索： (1)免疫复合物在免疫调节中的作用。事实证明 当免疫复合物跨越Fc-γ受体和表面时， B细胞上的免疫球蛋白受体，抑制B细胞增殖 从而导致分化。免疫复合物也结合滤泡 树突状细胞，在那里它们可以被保留并长时间刺激B细胞 一段时间。因为免疫复合物形成并分解为抗原， 抗体浓度的变化，复杂的反馈机制， 诱导。我们的模型将解决这些控制如何在体内工作。(2)当 拾取抗原-抗体或独特型（ID）抗ID复合物， 由B细胞加工并呈递给T细胞，这一现象被称为 可以发生分子内帮助，由此B细胞可以从非分子内获得帮助。 抗原特异性T细胞。将开发模型以探索 这一现象在免疫网络、抗id疫苗治疗 和自身免疫性疾病。(3)网络模型忽略了重要的 功能，如T细胞的帮助，免疫复合物的调节，自我的影响， 和外源抗原，以及区分B-1和B-2细胞。我们 建议审查这些修改的影响。(4)B细胞 成年人表达的所有信息都会影响动物的反应能力 疾病。我们将使用我们的模型来研究网络交互如何 导致表达T15独特型细胞的克隆优势， 对细菌多糖磷酸胆碱的反应。 最重要的是，开发综合模型的进展将 增加对免疫系统运作的了解 在抗击疾病的过程中。提高对免疫的认识 监管可以帮助设计新的治疗和疗法， 自身免疫性疾病，细菌感染，过敏和其他免疫系统 紊乱

We propose to develop and analyze, using modern large scale computing techniques, models of critical aspects of the immune system with the ultimate goal of understanding immune regulation. It is difficult to comprehend in the absence of mathematical models the operation of a large system of elements that interact according to nonlinear dynamical laws. Because in vivo phenomenon involve interactions among large numbers of immune system components, in vitro experiments fail to provide answers to many crucial questions. We seek to develop a new generation of models with which we can explore : (1) The role of immune complexes in immune regulation. It have been shown in vitro that when immune complexes span Fc-gamma receptors and surface immunoglobulin receptors on B cells, inhibition of B cell proliferation and differentiation can result. Immune complexes also bind follicular dendritic cells, where they may be retained and stimulate B cells for long periods of time. Because immune complexes form and breakup as antigen and antibody concentrations change, complex feedback mechanisms can be induced. Our models will address how such controls work in vivo. (2) When antigen-antibody or idiotypic (id) anti-id complexes are picked up, processed and presented by B cells to T cells, a phenomena known as intramolecular help can occur, whereby B cells can obtain help from non- antigen specific T cells. Models will be developed to explore the implications of this phenomena in immune networks, anti-id vaccine therapy and autoimmune disease. (3) Network models have left out important features, such as T cell help, immune complex regulation, effects of self and foreign antigen, and distinguishing between B-1 and B-2 cells. We propose to examine the influences of such modifications. (4) The B cell repertoire expressed by an adult influences an animal's ability to respond to disease. We will use our models to examine how network interactions can lead to clonal dominance of cells expressing the T15 idiotype in the response to the bacterial polysaccharide phosphorylcholine. Most important is that progress in developing comprehensive models will provide an increased understanding of the operation of the immune system as a whole in fighting disease. Increased understanding of immune regulation can help in the design of new treatments and therapies for autoimmune disease, bacterial infection, allergies and other immune system disorders.