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The Impact of Stochasticity and Its Control on a Model of the Inflammatory Response

Mavroudis, Panteleimon D. and Scheff, Jeremy D. and Doyle, John C. and Vodovotz, Yoram and Androulakis, Ioannis P. (2018) The Impact of Stochasticity and Its Control on a Model of the Inflammatory Response. Computation, 7 (1). p. 3. ISSN 2079-3197

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Abstract

The dysregulation of inflammation, normally a self-limited response that initiates healing, is a critical component of many diseases. Treatment of inflammatory disease is hampered by an incomplete understanding of the complexities underlying the inflammatory response, motivating the application of systems and computational biology techniques in an effort to decipher this complexity and ultimately improve therapy. Many mathematical models of inflammation are based on systems of deterministic equations that do not account for the biological noise inherent at multiple scales, and consequently the effect of such noise in regulating inflammatory responses has not been studied widely. In this work, noise was added to a deterministic system of the inflammatory response in order to account for biological stochasticity. Our results demonstrate that the inflammatory response is highly dependent on the balance between the concentration of the pathogen and the level of biological noise introduced to the inflammatory network. In cases where the pro- and anti-inflammatory arms of the response do not mount the appropriate defense to the inflammatory stimulus, inflammation transitions to a different state compared to cases in which pro- and anti-inflammatory agents are elaborated adequately and in a timely manner. In this regard, our results show that noise can be both beneficial and detrimental for the inflammatory endpoint. By evaluating the parametric sensitivity of noise characteristics, we suggest that efficiency of inflammatory responses can be controlled. Interestingly, the time period on which parametric intervention can be introduced efficiently in the inflammatory system can be also adjusted by controlling noise. These findings represent a novel understanding of inflammatory systems dynamics and the potential role of stochasticity thereon.


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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Mavroudis, Panteleimon D.
Scheff, Jeremy D.
Doyle, John C.
Vodovotz, Yoramvodovotz@pitt.eduvodovotz
Androulakis, Ioannis P.
Centers: Other Centers, Institutes, Offices, or Units > McGowan Institute for Regenerative Medicine
Date: 28 December 2018
Date Type: Publication
Journal or Publication Title: Computation
Volume: 7
Number: 1
Publisher: MDPI AG
Page Range: p. 3
DOI or Unique Handle: 10.3390/computation7010003
Schools and Programs: School of Medicine > Surgery
Refereed: Yes
Uncontrolled Keywords: inflammation, mathematical model, stochasticity, noise
ISSN: 2079-3197
Official URL: http://dx.doi.org/10.3390/computation7010003
Funders: U.S. National Institutes of Health, U.S. Department of Defense
Article Type: Research Article
Date Deposited: 21 Jul 2021 20:08
Last Modified: 21 Jul 2021 20:08
URI: http://d-scholarship.pitt.edu/id/eprint/41434

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