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Price, Ian (2011) MATHEMATICAL MODELING OF CHEMICAL SIGNALS IN INFLAMMATORY PATHWAYS. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Mechanistic, autonomous, ordinary differential equations represent a powerful way to crystalize and reproduce the dynamics of complex, nonlinear interactions. Design and calibration of these models, however, represent a challenge to the construction of fully validated models. Various parameter techniques are employed, evaluated and improved upon for the purpose of fitting in a nonlinear setting. Cells communicate with other cells and their environment by producing and receiving chemical signals. In the context of pathogen response, these signals regulate how the collective of cells reacts. One such undifferentiated response to signal is known as inflammation, and it is an important mediator of pathogen clearance as well as tissue healing; however, it also has the potential to damage the surrounding tissue when regulatory mechanisms break down. Models are built using the mechanisms of these interactions to produce a high level effect, and to predict what measures can be taken, as in influenza, to prevent dysregulation. The models developed for inflammatory response first take into consideration the production and reception of immune factors, cytokines, and then put these mechanisms into the context of tissue level response to external signals and internal signals in the form of system damage. This is incorporated into a nonlinear model of immune response to Influenza A Virus, with innate, adaptive, and humoral immunity components. The model is calibrated against data for both sublethal and lethal initial dosages. A model of mosquito response to exogenous cytokine as immune stimulation is also explored. Successful model fitting using Metropolis-Hastings methods yields multi-objective results for nonlinear deterministic models.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Price, Ianimp5@pitt.eduIMP5
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairSwigon, Davidswigon@pitt.eduSWIGON
Committee MemberErmentrout, Bardbard@math.pitt.eduBARD
Committee MemberClermont, Gillescler@pitt.eduCLER
Committee MemberYotov, Ivanyotov@math.pitt.eduYOTOV
Date: 29 September 2011
Date Type: Completion
Defense Date: 1 April 2011
Approval Date: 29 September 2011
Submission Date: 16 August 2011
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Mathematics
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Inflammation; Influenza; ODE Models; Parameter Fitting; Mechanistic Models; Metropolis Sampling
Other ID:, etd-08162011-203831
Date Deposited: 10 Nov 2011 19:59
Last Modified: 15 Nov 2016 13:49


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