Dynamical Model of Cytokines in Rheumatoid Arthritis in the Presence of Additive Noise
POSTER
Abstract
A dynamical model from Baker et. al* is used to explore the possibility of predicting onset of Rheumatoid Arthritis. The model is based on nonlinear interaction of pro- inflammatory and anti-inflammatory cytokines. In the model, a parameter measures the effect of the pro-inflammatory cytokine concentration on further growth of pro- inflammatory cytokines. As this parameter increases, a healthy state jumps to a disease state through a fold bifurcation. By adding noise to the model, we observe precursor flickering and large-scale fluctuations that might appear clinically as early clues to incipient onset.
*M. Baker, S. Denman-Johnson, and M. R. Owen, “Mathematical modelling of cytokine-mediated inflammation in rheumatoid arthritis” Mathematical Medicine and Biology (2013) 30, 311–337)
*M. Baker, S. Denman-Johnson, and M. R. Owen, “Mathematical modelling of cytokine-mediated inflammation in rheumatoid arthritis” Mathematical Medicine and Biology (2013) 30, 311–337)
Presenters
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Timothy Duren
University of Colorado, Denver
Authors
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Timothy Duren
University of Colorado, Denver
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Masoud Asadi-Zeydabadi
Department of Physics, University of Colorado Denver, University of Colorado, Denver, Physics, University of Colorado Denver
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Randall Tagg
Department of Physics, University of Colorado Denver, University of Colorado, Denver, Physics, University of Colorado Denver
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Colin O'Donnell
University of Colorado Anschutz Medical Campus
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Christopher Collora
University of Colorado Anschutz Medical Campus
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Kevin Deane
University of Colorado Anschutz Medical Campus