Theses and dissertations

This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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New Diagnostic Methods for Detecting Microvillus Inclusion Disease

Description
Microvillus Inclusion disease is a fatal disease found in the Navajo population caused by a single nucleotide polymorphism. It is characterized by intractable diarrhea and is often fatal early in life.1 The current method of diagnosis is sending duodenal biopsies for histopathological examination and confirmatory testing through genomic sequencing. The…

Microvillus Inclusion disease is a fatal disease found in the Navajo population caused by a single nucleotide polymorphism. It is characterized by intractable diarrhea and is often fatal early in life.1 The current method of diagnosis is sending duodenal biopsies for histopathological examination and confirmatory testing through genomic sequencing. The purpose of this experiment was to create a more simple and cost-effective diagnostic method for detecting Microvillus Inclusion disease. Three methods were explored (RFLP2, ARMS3,4, and Tentacle Probes5,6) and two methods were tested to determine their ability and their efficiency in detecting the SNP that causes the disease.2 Tests using the RFLP2 method and synthetic DNA resulted in 9% false-positive rate and 11% false-negative rate in a blind trial for detecting both target (mutation present) and non-target (mutation absent) DNA when gel analyzing software was used to compare Rf values after gel electrophoresis. Using the ARMS method3, a nine-sample randomized test was run that ended up with 22% false-positive rate and 19% false-negative rate from a blind trial when using a gel analyzing software to determine presence of the SNP by band intensity. Disclaimer: No DNA from human patients was used in this study. Only synthetic DNA used.
ContributorsHelmbrecht, Hawley Elizabeth (Author) / Caplan, Michael (Thesis director) / Carpentieri, David (Committee member) / Dubois, Courtney (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Ethnic Discrimination, Socioeconomic Status, and Health in India

Description

Significant health inequalities exist between different castes and ethnic communities in India, and identifying the roots of these inequalities is of interest to public health research and policy. Research on caste-based health inequalities in India has historically focused on general, government-defined categories, such as “Scheduled Castes,” “Scheduled Tribes,” and “Other…

Significant health inequalities exist between different castes and ethnic communities in India, and identifying the roots of these inequalities is of interest to public health research and policy. Research on caste-based health inequalities in India has historically focused on general, government-defined categories, such as “Scheduled Castes,” “Scheduled Tribes,” and “Other Backward Classes.” This method obscures the diversity of experiences, indicators of well-being, and health outcomes between castes, tribes, and other communities in the “scheduled” category. This study analyzes data on 699,686 women from 4,260 castes, tribes and communities in the 2015-2016 Demographic and Health Survey of India to: (1) examine the diversity within and overlap between general, government-defined community categories in both wealth, infant mortality, and education, and (2) analyze how infant mortality is related to community category membership and socioeconomic status (measured using highest level of education and household wealth). While there are significant differences between general, government-defined community categories (e.g., scheduled caste, backward class) in both wealth and infant mortality, the vast majority of variation between communities occurs within these categories. Moreover, when other socioeconomic factors like wealth and education are taken into account, the difference between general, government-defined categories reduces or disappears. These findings suggest that focusing on measures of education and wealth at the household level, rather than general caste categories, may more accurately target those individuals and households most at risk for poor health outcomes. Further research is needed to explain the mechanisms by which discrimination affects health in these populations, and to identify sources of resilience, which may inform more effective policies.
ContributorsClauss, Colleen (Author) / Hruschka, Daniel (Thesis director) / Davis, Mary (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution & Social Change (Contributor) / Department of Psychology (Contributor)
Created2022-05