H. Hirayama et Y. Okita, Mathematical introduction of dynamic behavior of an idio-type network of immune reactions, IEICE T FUN, E83A(11), 2000, pp. 2357-2369
Citations number
24
Categorie Soggetti
Eletrical & Eletronics Engineeing
Journal title
IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES
We described short time span idiotype immune network reactions by rigorous
mathematical equations. For each idiotype, we described the temporal change
s in concentration of (1) single bound antibody, one of its two Fab arms ha
s bound to the complemental receptor. site on the B cell. (2) double bound
antibody, both of its: two Fab arms have bound to the complemental receptor
sites on the B cell and (3) an immune complex which is a product of reacti
on among the antibodies. Stimulation and secretion processes of an antibody
in the idiotype network were described by non linear differential equation
s characterized by the magnitude of cross-linking of the complemental antib
ody and B cell receptor. The affinity between the mutually complemental ant
ibody and receptor. was described by an weighted affinity matrix. The activ
ating process was expressed by an exponential function with threshold. The
rate constant for the linkage of the second Fab arm of an antibody was indu
ced from the molecular diffusion process that was modified by the Coulomb r
epulsive force. By using reported experimental data, we integrated 60 non l
inear differential equations for the idiotype immune network to obtain the
temporal behavior of concentrations of the species in hour span. The concen
trations of the idiotype antibody and immune complex changed synchronously.
The influence of a change in one rate constant extended to ail the members
of the idiotype network. Thy concentrations of the single bound antibody,
double bound antibody and immune complex oscillated as functions of the con
centration of the fr ee antibody particularly at its low concentration. By
comparing to the reported experimental data, the present computational appr
oach seems to realize biological immune network reactions.