Browsing School, Graduate by Subject "regulation"
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The Creation of Objective Performance Criteria and Generation of Predictive Models among Medical Devices in a Vascular SpaceBackground: Objective Performance Criteria (OPC) have been explored as a tool to address the growing pressures to expedite device approval and enhance active surveillance. Existing data infrastructures can be employed to develop OPC to evaluate the use of devices, and can be further leveraged to develop predictive models. The objective of this dissertation was to: (1) Develop a framework for the creation of OPC, (2) Compare the use of stent, atherectomy, and combination of stent and atherectomy, and (3) Formulate a predictive model used to predict the probability of undergoing a major adverse limb event (MALE) or experiencing death following the aforementioned treatments. Methods: The framework was developed in 3 phases through (1) Review of the literature, (2) Engagement of key stakeholders, and (3) Feedback from an advisory committee. Retrospective cohort studies were conducted using the Vascular Quality Initiative (2010-2018). Logistic regression and the Fine-Gray subdistribution hazard model were used to compare short- and long-term MALE, respectively. A generalized linear model (GLM), a Least Absolute Shrinkage and Selection Operator (LASSO) regularized GLM, a gradient boosted decision tree, and random forest model were compared when used to predict MALE and mortality. Results: The developed framework consisted of 5 elements: (1) Identification of Medical Devices, (2) Engagement of Key Stakeholders, (3) Selection of Data Source, (4) Performance of Appropriate Statistical Analyses, (5) Reporting of Findings. The odds of short-term MALE (0.94;95%CI:0.77-1.14) and hazards of long-term MALE (0.92;95%CI:0.82-1.04) were not significantly different in the combination stent and atherectomy group when compared to stent alone. The most effective predictive model was the gradient boosted decision tree (Area Under the Curve (AUC)= 0.7539) for MALE and the LASSO regularized GLM (AUC=0.7930) for mortality. Conclusions: The developed framework provides a guide and needed foundation for the continued generation of OPC. Applying the identified statistical steps in the framework to an existing data infrastructure showed that patients receiving combination stent and atherectomy do not experience significantly different rates of MALE compared to stent alone. Predictive models generated using the infrastructure demonstrated the ability of machine learning techniques to generate robust predictive models within the vascular space.
Molecular Mechanisms Governing MatriptaseMatriptase, a type II transmembrane serine protease, and its cognate inhibitor hepatocyte growth factor activator inhibitor-1 (HAI-1) is broadly expressed by epithelial and carcinoma cells. The critical interaction between matriptase and HAI-1 are essential for placenta development, epithelial integrity, and epidermal functions. Deregulation of matriptase has been implicated in cancer development and progression. It is thought that the proteolytic activity of matriptase is how this protease participates in these physiological and pathological functions. Since searching for the physiological substrates of matriptase has not been completely successful due to the rapid inhibition by HAI-1, to elucidate the molecular regulatory mechanisms of matriptase becomes the best alternative option to understand its function. Therefore, in this dissertation, I elucidated and revealed the biochemical and cellular details of matriptase autoactivation as well as the alternative inhibitory mechanism. Although matriptase autoactivation can be induced by a variety of structurally unrelated stimuli in a loose cell-type specific manner, they all share some common features including tight coupling with HAI-1 inhibition on the cell surface, which indicates the existence of core autoactivation machinery. Based on this concept, cell-free and intact-cell autoactivation activation systems have been set up to study the molecular mechanisms governing matriptase autoactivation. Among all the chemical and physical factors that could alter the autoactivation, acids seem to be the most likely factor capable of conducting activation as a rapid onset, fast kinetics, in the magnitude of activation ever seen. This could further imply the role of matriptase under acidic pathological conditions, such as in a tumor microenvironment. In the last part of the dissertation, three blood-borne serpin type serine protease inhibitors from human breast milk have been characterized as the alternative mechanisms for matriptase inhibition. This suggests an alternative inhibitory mechanism that may be used physiologically in tissues with low or no HAI-1, such as in hematopoietic cells. Altogether, the dissertation provides insights into the regulatory mechanisms of matriptase. Those insights can be applied to the functional study of matriptase, especially to facilitate the search of its substrates, in the future.
Understanding the Role of Small Ankryin 1 in Calicum Regulation in Excitable CellsSmall Ankryin 1 (sAnk1) is a 17kD transmembrane protein that plays a role in stabilizing the network sarcoplasmic reticulum in skeletal muscle (Ackermann et al., 2011). Recent studies have shown that sAnk1 can bind to and regulate sarco(endo)plasmic reticulum Ca2+-ATPase1 (SERCA1) activity (Desmond et al., 2015). SERCA1 transports Ca2+ against its gradient into the SR after muscle contraction. SERCA is inhibited by sarcolipin (SLN) in fast twitch skeletal muscle and atrial cardiac muscle and by phospholamban (PLN) in slow twitch muscle and ventricular cardiac muscle. Like SLN and PLN, sAnk1 also interacts with SERCA at least in part through its transmembrane domain (Asahi et al., 2003; Hutter et al., 2002; Desmond et al., 2015). The interaction of SERCA with SLN and PLN has been studied individually and together, but the effects of sAnk1 and its regulatory activity have only recently started to be addressed (Desmond et al., 2015, 2017). Here I show that sAnk1 can interact with PLN or SLN independently of SERCA1. sAnk1 forms a three-way complex with SLN and SERCA1 that ablates SLN inhibition (Desmond et al., 2017). sAnk1 can also form a three-way complex with PLN and SERCA1 that abolishes all inhibition. I show that the complexes that sAnk1 forms with SLN or PLN and SERCA1 are distinct, suggesting unique roles for each protein in SERCA regulation. I also examined sAnk1 and SERCA in several CNS tissues, and found that sAnk1 is not expressed in neurons, but that it is expressed in astrocytes, where it has the potential to bind and regulate SERCA2B. Studying the multi-protein complex of SERCA, sAnk1, SLN, and/or PLN can help us better understand physiological SERCA regulation. This knowledge can lead to better treatment for diseases related to misregulation of calcium, including muscular dystrophies and potentially some neuropathies.