COMPUTER SIMULATION OF IMMUNE SYSTEM FUNCTION IN SLE

描述：（改编自申请人摘要）SLE是

DESCRIPTION: (Adapted from the applicant's abstract) SLE is characterized by tissue deposition of DNA:anti-DNA IChigh anti-dsDNA titers, hypocomplementemia, low CRl receptor number per RBC and impaired Fc-and C-mediated mononuclear phagocyte system (MPS)function. None of these properties alone provides either agood correlation with or prediction of disease activity. These results suggest either a more fundamental "cause" of disease activity in SLE or that disease activity results from a combination of defects. Aims of the proposed research are to study another SLE immune system defect, namely decreased rate of RBC CRl/factor I-mediated modification of RBC-bound IC and to construct a computer simulation of immune function so that the interrelatedness of multiple immune system defects can be quantitatively recounted. Since IC modification by RBC CRl/factor I is an integral part of IC handling and is retarded in SLE, a study of factors affecting modification rates and binding properties of modified and unmodified IC will be undertaken. Specifically, the rate at which a 3H-DNA:anti-DNA:complement IC is modified will be measured as a function of a) SLE disease activity serial study, b) IC complement content, c) CRl number/RBC, and d) CRl phenotype. In addition, binding rate of modified and unmodified IC to U937 and spleen cells will be measured. These studies should increase our understanding of the biological significance of the RBC CRl/factor I-mediated modification of IC in SLE and its relationship to disease activity. The computer simulation will be constructed from a kinetic model of immune complex formation, handling and clearance. The simulation will be governed byrate constants and reagent/catalyst concentrations which regulate immune system reactions. Mathematical equations will be solved by numerical integration by The Runge-Kutta method. The simulation will enhance our understanding of the interrelatedness of immune system reactions, will be able to quantitatively predict the outcomes of multiple defects in the immune response system, and will serve as both a diagnostic and predictive technique.