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Computational modeling of the pancreas: lifelong simulations of pancreatitis

Talzhanov, Yerkebulan (2012) Computational modeling of the pancreas: lifelong simulations of pancreatitis. Master's Thesis, University of Pittsburgh. (Unpublished)

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Abstract

The aim of this study is to build a mathematical model of the pancreas and run this model in lifelong simulations in order to understand the mechanisms that predict an increased risk of pancreatitis. The dilemma is that pancreatitis is a complex process with multiple variables, which currently make the onset, severity and outcomes unpredictable in individual patients. Genetic, environmental and metabolic factors are likely to be important for disease severity and progression, with somewhat stochastic events initiating theprocess when stress leads to injury signals. Modeling should begin in the acinar cell, with ability to incorporate duct cells, inflammatory cells, other cells and their interactions into large model. In this work we attempted to build a foundational model that incorporates the main features and interactors. We built a framework that focuses on trypsinogen activation as a major cause of auto-digestion and injury. Additional variables such as production ofpancreatic secretory trypsin inhibitor(PSTI) molecules as a defense line against active trypsin as well as bicarbonate secretion were included in the model. The effects of mutation were modeled as modified rates of trypsinogen production/activation, trypsin inactivation, PSTI production, and bicarbonate secretion. Our framework contains three compartments that represent domains where trypsin could be activated. The domains are acinar cell, lumen of the acinus, and main duct of the pancreas. We used a stochastic approach to test the general flow of the simulation.
The public health and translational significance of this model is thatit would help us to understand the physiology of the pancreas more deeply. It would also allow us to consider many factors that lead to pancreatitis and predict their behavior under different conditions (e.g., therapy).


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Talzhanov, Yerkebulanyet5@pitt.eduYET5
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairBarmada, Mahmudbarmada@pitt.eduBARMADA
Committee MemberWeeks, Danielweeks@pitt.eduWEEKS
Committee MemberWhitcomb, Davidwhitcomb@pitt.eduWHITCOMB
Date: 29 June 2012
Date Type: Publication
Defense Date: 7 December 2011
Approval Date: 29 June 2012
Submission Date: 3 April 2012
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 76
Institution: University of Pittsburgh
Schools and Programs: Graduate School of Public Health > Human Genetics
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: Pancreas, pancreatitis, modeling, computational simulations.
Date Deposited: 29 Jun 2012 17:56
Last Modified: 15 Nov 2016 13:58
URI: http://d-scholarship.pitt.edu/id/eprint/12163

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