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- Member of: Theses and Dissertations
Carbohydrate counting has been shown to improve HbA1c levels for people with diabetes. However, the learning curve and inconvenience of carbohydrate counting make it difficult for patients to adhere to it. A deep learning model is proposed to identify food from an image, where it can help the user manage their carbohydrate counting. This early model has a 68.3% accuracy of identifying 101 different food classes. A more refined model in future work could be deployed into a mobile application to identify food the user is about to consume and log it for easier carbohydrate counting.
Chronic wounds affect many people worldwide and significantly impact their quality of life. Hydrogel wound dressings are a promising option for chronic wounds due to their properties, including mild fabrication conditions, high water content, biodegradability, and bioactive molecule delivery capabilities. This thesis will explore the mechanisms that contribute to the wound healing properties of a bovine type I collagen-based hydrogel that incorporates platelet-rich plasma and describe how this hydrogel will be capable of effectively healing chronic wounds.
particularly emergent class of cardiovascular diseases and account for significant cardiovascular morbidity and mortality worldwide. Computational simulations of aortic flows are growing increasingly important as tools for gaining understanding of these pathologies and for planning their surgical repair. In vitro experiments are required to validate these simulations against real world data, and a pulsatile flow pump system can provide physiologic flow conditions characteristic of the aorta.
This dissertation presents improved experimental techniques for in vitro aortic blood flow and the increasingly larger parts of the human cardiovascular system. Specifically, this work develops new flow management and measurement techniques for cardiovascular flow experiments with the aim to improve clinical evaluation and treatment planning of aortic diseases.
The hypothesis of this research is that transient flow driven by a step change in volume flux in a piston-based pulsatile flow pump system behaves differently from transient flow driven by a step change in pressure gradient, the development time being substantially reduced in the former. Due to this difference in behavior, the response to a piston-driven pump can be predicted in order to establish inlet velocity and flow waveforms at a downstream phantom model.
The main objectives of this dissertation were: 1) to design, construct, and validate a piston-based flow pump system for aortic flow experiments, 2) to characterize temporal and spatial development of start-up flows driven by a piston pump that produces a step change from zero flow to a constant volume flux in realistic (finite) tube geometries for physiologic Reynolds numbers, and 3) to develop a method to predict downstream velocity and flow waveforms at the inlet of an aortic phantom model and determine the input waveform needed to achieve the intended waveform at the test section. Application of these newly improved flow management tools and measurement techniques were then demonstrated through in vitro experiments in patient-specific coarctation of aorta flow phantom models manufactured in-house and compared to computational simulations to inform and execute future experiments and simulations.
A significant ischemic event that overcomes vascular compensatory capacity causes spinal cord injury (SCI). For example, SCI complicating thoracoabdominal aortic aneurysm repair is associated with ischemic injury. The rate of this devastating complication has been decreased significantly by instituting physiological methods of protection. Traumatic spinal cord injury causes complex changes in spinal cord blood flow (SCBF), which are closely related to a severity of injury. Manipulating physiological parameters such as mean arterial pressure (MAP) and intrathecal pressure (ITP) may be beneficial for patients with a spinal cord injury. It was discovered in a pig model of SCI that the combination of MAP elevation and cerebrospinal fluid drainage (CSFD) significantly and sustainably improved SCBF and spinal cord perfusion pressure.
In animal models of SCI, regeneration is usually evaluated histologically, requiring animal sacrifice. Thus, there is a need for a technique to detect changes in SCI noninvasively over time. The study was performed comparing manganese-enhanced magnetic resonance imaging (MEMRI) in hemisection and transection SCI rat models with diffusion tensor imaging (DTI) and histology. MEMERI ratio differed among transection and hemisection groups, correlating to a severity of SCI measured by fraction anisotropy and myelin load. MEMRI is a useful noninvasive tool to assess a degree of neuronal damage after SCI.