MARC보기
LDR00000nam u2200205 4500
001000000433641
00520200225151919
008200131s2019 ||||||||||||||||| ||eng d
020 ▼a 9781088379349
035 ▼a (MiAaPQ)AAI22615149
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 660
1001 ▼a Serrano Castillo, Florencio.
24510 ▼a Multi-Scale Mathematical Models of Airway Epithelium to Facilitate Cystic Fibrosis Treatment.
260 ▼a [S.l.]: ▼b University of Pittsburgh., ▼c 2019.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2019.
300 ▼a 231 p.
500 ▼a Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
500 ▼a Advisor: Parker, Robert S.
5021 ▼a Thesis (Ph.D.)--University of Pittsburgh, 2019.
506 ▼a This item must not be sold to any third party vendors.
506 ▼a This item must not be added to any third party search indexes.
520 ▼a 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.
590 ▼a School code: 0178.
650 4 ▼a Chemical engineering.
690 ▼a 0542
71020 ▼a University of Pittsburgh. ▼b Swanson School of Engineering.
7730 ▼t Dissertations Abstracts International ▼g 81-04B.
773 ▼t Dissertation Abstract International
790 ▼a 0178
791 ▼a Ph.D.
792 ▼a 2019
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15493275 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 202002 ▼f 2020
990 ▼a ***1008102
991 ▼a E-BOOK