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Modeling rejection immunity

Overview of attention for article published in Theoretical Biology and Medical Modelling, May 2012
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Title
Modeling rejection immunity
Published in
Theoretical Biology and Medical Modelling, May 2012
DOI 10.1186/1742-4682-9-18
Pubmed ID
Authors

AndreaDe Gaetano, Alice Matone, Annamaria Agnes, Pasquale Palumbo, Francesco Ria, Sabina Magalini

Abstract

Transplantation is often the only way to treat 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 physician's experience in specifying therapeutic regimens is therefore desirable. The present work proposes an Ordinary Differential Equations model accounting for immune cell 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 latter has been determined experimentally. All other model parameter values have been set so as to reproduce reported state variable time-courses, and to maintain consistency with one another and with the experimentally derived proliferation coefficient.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 8%
Unknown 11 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 33%
Student > Master 3 25%
Researcher 3 25%
Other 1 8%
Student > Postgraduate 1 8%
Other 0 0%
Readers by discipline Count As %
Medicine and Dentistry 4 33%
Computer Science 3 25%
Agricultural and Biological Sciences 2 17%
Mathematics 1 8%
Engineering 1 8%
Other 0 0%
Unknown 1 8%