{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/29717"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/29717","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Models of the Mucosal Inflammatory and Regulatory Immune Pathways: The Role of Host Response in Microbial Persistence and Pathogenesis","abstract":"The scientific method requires the creation of a unifying hypothesis that reconciles an observed health outcome of infection with experimental data gathered about the disease process following infection. In this era of unprecedented amounts of data and information for various disease models, the creation and articulation of such hypothesis are often beyond human capacity. Modeling offers a means to generate hypothesis that provide complex mechanisms that reconcile seemingly contradictory data as well as quantitatively assess the relative plausibility of different mechanisms proposed to explain the same data/health outcome association. Here I explain the modeling approach to hypothesis generation and offer several examples of its implementation to address the role of the natural host immune response in determining outcomes of infection by a specific microbe including pathogenesis and microbial clearance. Such knowledge is key to devising sophisticated disease intervention strategies. The systems studied are i) Inflammatory Bowel Disease, where I explore mechanisms of inflammation regulation and how they break down to give rise to a chronic inflammatory disease, ii)H. pylori infection, in which I explore potential bacterial strategies for persistence as a commensal of the microflora or as a pathogen, and iii) HIV infection, where I explore the role of inflammatory and anti-inflammatory mechanisms in establishing viral infection. I present both mathematical, equation based models as well as agent-based, computational models offering a comparison of each method.","abstract_html":"The scientific method requires the creation of a unifying hypothesis that reconciles an observed health outcome of infection with experimental data gathered about the disease process following infection. In this era of unprecedented amounts of data and information for various disease models, the creation and articulation of such hypothesis are often beyond human capacity. Modeling offers a means to generate hypothesis that provide complex mechanisms that reconcile seemingly contradictory data as well as quantitatively assess the relative plausibility of different mechanisms proposed to explain the same data/health outcome association. Here I explain the modeling approach to hypothesis generation and offer several examples of its implementation to address the role of the natural host immune response in determining outcomes of infection by a specific microbe including pathogenesis and microbial clearance. Such knowledge is key to devising sophisticated disease intervention strategies. The systems studied are i) Inflammatory Bowel Disease, where I explore mechanisms of inflammation regulation and how they break down to give rise to a chronic inflammatory disease, ii)H. pylori infection, in which I explore potential bacterial strategies for persistence as a commensal of the microflora or as a pathogen, and iii) HIV infection, where I explore the role of inflammatory and anti-inflammatory mechanisms in establishing viral infection. I present both mathematical, equation based models as well as agent-based, computational models offering a comparison of each method.","abstract_has_math":false,"creators":["Wendelsdorf, Katherine Veronica"],"institution":"Virginia Tech","degree_name":"Ph. 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In this era of unprecedented amounts of data and information for various disease models, the creation and articulation of such hypothesis are often beyond human capacity. Modeling offers a means to generate hypothesis that provide complex mechanisms that reconcile seemingly contradictory data as well as quantitatively assess the relative plausibility of different mechanisms proposed to explain the same data/health outcome association. Here I explain the modeling approach to hypothesis generation and offer several examples of its implementation to address the role of the natural host immune response in determining outcomes of infection by a specific microbe including pathogenesis and microbial clearance. Such knowledge is key to devising sophisticated disease intervention strategies. The systems studied are i) Inflammatory Bowel Disease, where I explore mechanisms of inflammation regulation and how they break down to give rise to a chronic inflammatory disease, ii)H. pylori infection, in which I explore potential bacterial strategies for persistence as a commensal of the microflora or as a pathogen, and iii) HIV infection, where I explore the role of inflammatory and anti-inflammatory mechanisms in establishing viral infection. I present both mathematical, equation based models as well as agent-based, computational models offering a comparison of each method."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph. D."]},{"key":"dc:title","label":"Title","values":["Models of the Mucosal Inflammatory and Regulatory Immune Pathways: The Role of Host Response in Microbial Persistence and Pathogenesis"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Eubank, Stephen","Marathe, Madhav V."],"dc:contributor.committeemember":["Banks, Harvey T.","LeRoith, Tanya","Li, Liwu"],"dc:contributor.department":["Genetics, Bioinformatics, and Computational Biology"],"dc:creator":["Wendelsdorf, Katherine Veronica"],"dc:date.accessioned":["2014-03-14T20:18:54Z"],"dc:date.available":["2014-03-14T20:18:54Z","2011-12-13"],"dc:date.issued":["2011-11-08"],"dc:description.abstract":["The scientific method requires the creation of a unifying hypothesis that reconciles an observed health outcome of infection with experimental data gathered about the disease process following infection. 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The systems studied are i) Inflammatory Bowel Disease, where I explore mechanisms of inflammation regulation and how they break down to give rise to a chronic inflammatory disease, ii)H. pylori infection, in which I explore potential bacterial strategies for persistence as a commensal of the microflora or as a pathogen, and iii) HIV infection, where I explore the role of inflammatory and anti-inflammatory mechanisms in establishing viral infection. I present both mathematical, equation based models as well as agent-based, computational models offering a comparison of each method."],"dc:description.degree":["Ph. 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