2,140 research outputs found

    Assembly and Trafficking of the Cystic Fibrosis Transmembrane Conductance Regulator and Associated Proteins

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    Cystic Fibrosis (CF) is an autosomal recessive genetic disease that leads to severe malfunction in many organs, but particularly the lungs. The primary cause of this malfunction is the decrease of the airway surface liquid layer on the lung epithelium. The lack of hydration leads to mucus build up on the epithelial lining, leading to blockage of airways. The underlying cause of CF is the dysfunction of the cystic fibrosis transmembrane conductance regulator (CFTR), which results from mutations in the protein. Almost 90% of CF patients are caused by the deletion of the phenylalanine at position 508 of CFTR, which is believed to affect the folding and stability of CFTR. The misfolded ΔF508-CFTR undergoes ER associated degradation (ERAD), causing the failure of ΔF508-CFTR trafficking to the cell surface. Small molecule correctors yield moderate improvements in the trafficking of ΔF508-CFTR to the plasma membrane. It is currently not known if correctors increase trafficking through improved cargo loading of transport vesicles or through direct binding to CFTR. In this dissertation, real-time measurements of trafficking were utilized to identify the mechanistic details of chemical, biochemical, and thermal factors that impact CFTR correction, using the corrector molecule VX-809, a secondary mutation (I539T), and low temperature conditions. Each individually improved trafficking of ΔF508-CFTR to approximately 10% of wild-type levels. The combination of VX-809 with either low temperature or the I539T mutation increased the amount of CFTR on the plasma membrane to nearly 40%, indicating synergistic activity. The number of vesicles reaching the surface was significantly altered; however the amount of channel in each vesicle remained the same. Therefore, a 2 step therapeutic approach might be an ideal treatment for CF. The first step would be composed of a compound that mimics the mechanism of stabilization provided by low temperature or the I539T mutation, while the second step would be VX-809 or a similar corrector compound. These studies suggest that understanding how low temperature and second site suppressors alter ΔF508-CFTR could be key to the development of future therapeutics for the effective treatment of CF. The precise pathophysiology of cystic fibrosis is not well studied. The involvement of another transport protein, epithelial sodium channel (ENaC), makes the situation more complicated. ENaC and CFTR are colocalized on the apical surface of epithelia cells. With our fluorescence microscopy techniques, we explored the effects of CFTR on the residence time of ENaC on the cell membrane. A reliable approach measuring the half-life of protein on the cell membrane is required for this study. We present a new approach to quantify the half-life of membrane proteins on the cell surface, through tagging the protein with the photoconvertible fluorescent protein, Dendra2. Total internal reflection fluorescence microscopy (TIRF) is applied to limit visualization of fluorescence to proteins located on the plasma membrane. Photoconversion of Dendra2 works as a pulse chase experiment by monitoring only the population of protein that has been photoconverted. As the protein is endocytosed the red emission decreases due to the protein leaving the TIRF field of view. The half-life of the protein on the plasma membrane was calculated upon imaging over time and quantifying the change in red fluorescence. Our method provides a unique opportunity to observe real-time protein turnover at the single cell level without addition of protein synthesis inhibitors. This technique will be valuable for the future protein half-life study

    Goodbye Presentation

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    In this capstone presentation, visiting Chinese doctoral student Zhihui Zhang explains how she came to study at the University of Kentucky Libraries Special Collections Research Center; the archival projects she worked on, the individual people she met with, and the cultural heritage organization tours she went on; the differences and similarities between American and Chinese archival theory and practice; and how this experience will inform her Ph.D. program and her dissertation

    Simulating non-small cell lung cancer with a multiscale agent-based model

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    Background The epidermal growth factor receptor (EGFR) is frequently overexpressed in many cancers, including non-small cell lung cancer (NSCLC). In silcio modeling is considered to be an increasingly promising tool to add useful insights into the dynamics of the EGFR signal transduction pathway. However, most of the previous modeling work focused on the molecular or the cellular level only, neglecting the crucial feedback between these scales as well as the interaction with the heterogeneous biochemical microenvironment. Results We developed a multiscale model for investigating expansion dynamics of NSCLC within a two-dimensional in silico microenvironment. At the molecular level, a specific EGFR-ERK intracellular signal transduction pathway was implemented. Dynamical alterations of these molecules were used to trigger phenotypic changes at the cellular level. Examining the relationship between extrinsic ligand concentrations, intrinsic molecular profiles and microscopic patterns, the results confirmed that increasing the amount of available growth factor leads to a spatially more aggressive cancer system. Moreover, for the cell closest to nutrient abundance, a phase-transition emerges where a minimal increase in extrinsic ligand abolishes the proliferative phenotype altogether. Conclusions Our in silico results indicate that, in NSCLC, in the presence of a strong extrinsic chemotactic stimulus, and depending on the cell's location, downstream EGFR-ERK signaling may be processed more efficiently, thereby yielding a migration-dominant cell phenotype and overall, an accelerated spatio-temporal expansion rate.Comment: 37 pages, 7 figure

    RORS: Enhanced Rule-based OWL Reasoning on Spark

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    The rule-based OWL reasoning is to compute the deductive closure of an ontology by applying RDF/RDFS and OWL entailment rules. The performance of the rule-based OWL reasoning is often sensitive to the rule execution order. In this paper, we present an approach to enhancing the performance of the rule-based OWL reasoning on Spark based on a locally optimal executable strategy. Firstly, we divide all rules (27 in total) into four main classes, namely, SPO rules (5 rules), type rules (7 rules), sameAs rules (7 rules), and schema rules (8 rules) since, as we investigated, those triples corresponding to the first three classes of rules are overwhelming (e.g., over 99% in the LUBM dataset) in our practical world. Secondly, based on the interdependence among those entailment rules in each class, we pick out an optimal rule executable order of each class and then combine them into a new rule execution order of all rules. Finally, we implement the new rule execution order on Spark in a prototype called RORS. The experimental results show that the running time of RORS is improved by about 30% as compared to Kim & Park's algorithm (2015) using the LUBM200 (27.6 million triples).Comment: 12 page

    A permeability model for the hydraulic fracture filled with proppant packs under combined effect of compaction and embedment

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    The authors acknowledge the financial support from Science Foundation of China University of Petroleum, Beijing (No. 2462014YJRC060 and No.2462014YJRC059)Peer reviewedPostprin
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