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Multi-Scale Mathematical Models of Airway Epithelium to Facilitate Cystic Fibrosis Treatment
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Multi-Scale Mathematical Models of Airway Epithelium to Facilitate Cystic Fibrosis Treatment. |
| 개인저자 | Serrano Castillo, Florencio. |
| 단체저자명 | University of Pittsburgh. Swanson School of Engineering. |
| 발행사항 | [S.l.]: University of Pittsburgh., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 231 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-04B. Dissertation Abstract International |
| ISBN | 9781088379349 |
| 학위논문주기 | Thesis (Ph.D.)--University of Pittsburgh, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
Advisor: Parker, Robert S. |
| 이용제한사항 | This item must not be sold to any third party vendors.This item must not be added to any third party search indexes. |
| 요약 | Cystic Fibrosis is a life-shortening, autosomal recessive disease caused by mutations in the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) gene. Cystic Fibrosis is the most common lethal genetic disorder among Caucasians and occurs at a rate of 1 in every 3,400 births in the United States. The CFTR gene codes an anion channel expressed on the mucosal side of the epithelia of multiple organ systems, including the digestive tract, reproductive organs, pancreas, and airways. Loss of CFTR expression or function results in an osmotic imbalance due to defective ion and water transport. In the respiratory tract, this leads to airway surface liquid hyperabsorption and mucus dehydration causing decreased mucociliary clearance rates. Failure to clear mucus and other inhaled debris favor the development of mucus plugs and the prolonged colonization of harmful pathogens. These conditions lead to a sustained, unregulated inflammatory response that results in severe tissue damage and, ultimately, respiratory failure, the leading cause of Cystic Fibrosis mortality.Cystic Fibrosis therapeutic development is largely dependent on the availability of model systems that can be used to test and optimize therapies ahead of clinical use. These systems include networks of interactive elements that can be overly complex to exhaustively explore experimentally. The work described here focuses on the development of cell-scale, mechanistic, and biologically relevant mathematical models that provide information about the contribution of individual mechanisms to experimental outcomes.The models were trained and validated with data obtained from human bronchial and nasal epithelial cell cultures from donors with Cystic Fibrosis, non-Cystic Fibrosis controls, and carriers of a single disease-causing allele. Within this context, we have used these models as tools to explore the underlying mechanisms behind Cystic Fibrosis pathophysiology not easily accessible experimentally. These predictions were further enhanced through the inclusion of similar estimates generated from separately developed models of in vivo lung-scale function, as well as standard clinical measurements of airway function. Model predictions provide us with unique and novel parametric descriptions of mechanistic and physiological differences between the three populations and across multiple spatiotemporal scales. We envision using these models as means to facilitate the deployment of personalized treatment protocols, where cells sampled and cultured from individuals could be used to generate patient-specific in silico predictors of lung-scale disease state and therapeutic response. |
| 일반주제명 | Chemical engineering. |
| 언어 | 영어 |
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