期刊
MATHEMATICAL BIOSCIENCES
卷 217, 期 1, 页码 1-10出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.mbs.2008.07.013
关键词
Mathematical modeling; Inflammation; Sepsis; Trauma; Infection; Ordinary differential equations; Stochastic simulations; Agent-based modeling; Toll-like receptors; Preconditioning; Endotoxin; Parameter estimation; Personalized medicine; Computer simulation
资金
- National Institutes of Health [R01-GM-67240-02, P50-GM-53789-08, R01-HL080926-01, R01-HL-76157-02]
- National Institute on Disability and Rehabilitation Research [H133E070024]
- National Science Foundation [DMS041423, DMS0716936]
- Commonwealth of Pennsylvania
- Pittsburgh Lifesciences Greenhouse
- Pittsburgh Tissue Engineering Initiative
- NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [R01HL080926, R01HL076157, R33HL089082] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [P50GM053789, R01GM067240] Funding Source: NIH RePORTER
Inflammation is a normal, robust physiological process. It can also be viewed as a complex system that senses and attempts to resolve homeostatic perturbations initiated from within the body (for example, in autoimmune disease) or from the outside (for example, in infections). Virtually all acute and chronic diseases are either driven or modulated by inflammation. The complex interplay between beneficial and harmful arms of the inflammatory response may underlie the lack of fully effective therapies for many diseases. Mathematical modeling is emerging as a frontline tool for understanding the complexity of the inflammatory response. A series of articles in this issue highlights various modeling approaches to inflammation in the larger context of health and disease, from intracellular signaling to whole-animal physiology. Here we discuss the state of this emerging field. We note several common features of inflammation models, as well as challenges and prospects for future studies. (C) 2008 Elsevier Inc. All rights reserved.
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