Publications of A. Matone

This page shows all publications that appeared in the IASI annual research reports. Authors currently affiliated with the Institute are always listed with the full name.

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Show all publications of the year  ALL, with author Matone A., in the category IASI Research Reports (or show them all):


IASI Research Report n. 10-10  (Previous )  

De Gaetano A., Matone A., Agnes A.M., Palumbo P., Ria F., Magalini S.

Modeling rejection immunity

ABSTRACT
Transplantation is often the outcome of a number of diseases leading to organ failure. To overcome rejection towards the transplanted organ (graft), immunosuppression therapies are used, which have considerable side-effects and expose patients to opportunistic infections. The development of a model to complement the physicians experience in specifying therapeutic regimens is therefore desirable. The present work proposes an Ordinary Differential Equations model accounting for immune cells proliferation in response to the sudden entry of graft antigens, through different activation mechanisms. The model considers the effect of a single immunosuppressive medication (e.g. cyclosporine), subject to first-order linear kinetics and acting by modifying, in a saturable concentration-dependent fashion, the proliferation coefficient. The model proposed substantially simplifies the chain of events potentially leading to organ rejection. It is however able to simulate quantitatively the time course of graft-related antigen and competent immunoreactive cell populations, showing the long-term alternative outcomes of rejection, tolerance or tolerance at a reduced functional tissue mass. In particular, the model shows that it may be difficult to attain tolerance at full tissue mass with acceptably low doses of a single immunosuppressant, in accord with clinical experience. The model has been formalized so as to be directly extended to incorporate several immunosuppressive agents, acting at different levels of the mechanism leading to rejection, and to accommodate additional specific cell populations or specific antigen types as needed. This formalization lends itself specifically to the simulation of different therapy schemes, supporting the optimal clinical use of available agents.
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