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2004 | OriginalPaper | Buchkapitel

Mathematical and Statistical Modeling of Acute Inflammation

verfasst von : Gilles Clermont, Carson C. Chow, Gregory M. Constantine, Yoram Vodovotz, John Bartels

Erschienen in: Classification, Clustering, and Data Mining Applications

Verlag: Springer Berlin Heidelberg

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A mathematical model involving a system of ordinary differential equations has been developed with the goal of assisting the design of therapies directed against the inflammatory consequences of infection and trauma. Though the aim is to build a model of greater complexity, which would eventually overcome some existing limitations (such as a reduced subset of inflammatory interactions, the use of mass action kinetics, and calibration to circulating but not local levels of cytokines), the model can at this time simulate certain disease scenarios qualitatively as well as predicting the time course of cytokine levels in distinct paradigms of inflammation in mice. A parameter search algorithm is developed that aids in the identification of different regimes of behaviour of the model and helps with its calibration to data. Extending this mathematical model, with validation in humans, may lead to the in silico development of novel therapeutic approaches and real-time diagnostics.

Metadaten
Titel
Mathematical and Statistical Modeling of Acute Inflammation
verfasst von
Gilles Clermont
Carson C. Chow
Gregory M. Constantine
Yoram Vodovotz
John Bartels
Copyright-Jahr
2004
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-17103-1_43