5 research outputs found

    Quantitative Molecular Sensing Using DNA Origami

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    Type I diabetes is considered a worldwide epidemic because its incidence is exponentially increasing. Current treatment of the disease requires blood glucose monitoring and intake of insulin. While there have been many medical advances in devices that monitor glucose and deliver insulin, these treatments can still lead to complications, including but not limited to debilitating hypoglycemia, neuropathy, and death, if not followed properly. To eliminate these complications, there is a need to create a novel approach for continuous and automated glucose monitoring and insulin delivery. This project seeks to address this challenge by creating a DNA nanostructure that can sense changes in the concentration of a target biomolecule. The long-term goal is to use this DNA nanostructure to detect a glucose-protein complex. The nanostructure comprises a DNA hinge with aptamers (short DNA strands with sequences that bind to a specific protein). Initial development and optimization experiments will target the protein thrombin for simplicity and easy availability. We use transmission electron microscopy (TEM) to measure the equilibrium changes in conformation of the hinge upon contact with thrombin. We initially explored two conformations of the hinge: one that opens when it comes into contact with thrombin and another that closes. Preliminary TEM results have shown that the closed structure is more efficient for detection. In the future, we plan to conduct fluorescence experiments to further optimize the protein sensor and measure real-time response. These experiments will lay the foundation for a viable long-term glucose sensor; the sensor can then be paired with a molecular release mechanism to deliver insulin. Ultimately, this type of device could serve as an automated monitoring and delivery system that would make diseases such as diabetes more manageable and eliminate many of the complications that arise from current treatments.The College of EngineeringNo embargoAcademic Major: Chemical Engineerin

    Mapping of Pediatric COVID-19 Cases in Miami-Dade and Broward Counties: an Analysis of Sociodemographic Disparities

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    Background Numerous studies have shown a disproportionate impact of COVID-19 infection on Black and Hispanic Americans in the adult patient population. However, few studies have been done with pediatric populations. The aim of this study is to identify the prevalence and distribution of COVID-19 cases among pediatric patients in Miami-Dade and Broward counties and identify any sociodemographic disparities. Methods A total of 10,087 children/adolescents ages zero years-old to 20 years-old were tested from July 1, 2020, to December 31, 2020. ArcGIS was used to map cases and obtain sociodemographic data. SPSS software was used to determine significance of data trends and create a predictive model. Results There were 1,161 pediatric COVID-19 cases detected. White Hispanics and Black Hispanics had statically significantly higher cases when compared to White non-Hispanics and Black non-Hispanics. Percentage of households on food stamps, percentage of households below the poverty line, percentage of minority populations, and percentage of Hispanic population showed a positive correlation with detected pediatric COVID-19 cases. Alternatively, areas with higher median household incomes and higher educational status were negatively correlated with COVID-19. Percentage of Hispanic population and percentage of households below the poverty line were predictive of pediatric COVID-19 cases. Conclusion There was a disproportionate impact of pediatric COVID-19 infection on zip codes of lower socioeconomic status and increased racial/ethnic minority populations. This study demonstrates the need for public health policies that prioritize testing children/adolescents in these communities
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