Matching Items (72)
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This research project investigated known and novel differential genetic variants and their associated molecular pathways involved in Type II diabetes mellitus for the purpose of improving diagnosis and treatment methods. The goal of this investigation was to 1) identify the genetic variants and SNPs in Type II diabetes to develo

This research project investigated known and novel differential genetic variants and their associated molecular pathways involved in Type II diabetes mellitus for the purpose of improving diagnosis and treatment methods. The goal of this investigation was to 1) identify the genetic variants and SNPs in Type II diabetes to develop a gene regulatory pathway, and 2) utilize this pathway to determine suitable drug therapeutics for prevention and treatment. Using a Gene Set Enrichment Analysis (GSEA), a set of 1000 gene identifiers from a Mayo Clinic database was analyzed to determine the most significant genetic variants related to insulin signaling pathways involved in Type II Diabetes. The following genes were identified: NRAS, KRAS, PIK3CA, PDE3B, TSC1, AKT3, SOS1, NEU1, PRKAA2, AMPK, and ACC. In an extensive literature review and cross-analysis with Kegg and Reactome pathway databases, novel SNPs located on these gene variants were identified and used to determine suitable drug therapeutics for treatment. Overall, understanding how genetic mutations affect target gene function related to Type II Diabetes disease pathology is crucial to the development of effective diagnosis and treatment. This project provides new insight into the molecular basis of the Type II Diabetes, serving to help untangle the regulatory complexity of the disease and aid in the advancement of diagnosis and treatment. Keywords: Type II Diabetes mellitus, Gene Set Enrichment Analysis, genetic variants, KEGG Insulin Pathway, gene-regulatory pathway
ContributorsBucklin, Lindsay (Co-author) / Davis, Vanessa (Co-author) / Holechek, Susan (Thesis director) / Wang, Junwen (Committee member) / Nyarige, Verah (Committee member) / School of Human Evolution & Social Change (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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This study aims to examine the relationship between urban densification and pedestrian thermal comfort at different times of the year, and to understand how this can impact patterns of activity in downtown areas. The focus of the research is on plazas in the urban core of downtown Tempe, given their

This study aims to examine the relationship between urban densification and pedestrian thermal comfort at different times of the year, and to understand how this can impact patterns of activity in downtown areas. The focus of the research is on plazas in the urban core of downtown Tempe, given their importance to the pedestrian landscape. With that in mind, the research question for the study is: how does the microclimate of a densifying urban core affect thermal comfort in plazas at different times of the year? Based on the data, I argue that plazas in downtown Tempe are not maximally predisposed to pedestrian thermal comfort in the summer or the fall. Thus, the proposed intervention to improve thermal comfort in downtown Tempe’s plazas is the implementation of decision support tools focused on education, community engagement, and thoughtful building designs for heat safety.

ContributorsCox, Nicole (Author) / Redman, Charles (Thesis director) / Hondula, David M. (Committee member) / School of Social Transformation (Contributor) / School of Sustainability (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Description
This research project investigated known and novel differential genetic variants and their associated molecular pathways involved in Type II diabetes mellitus for the purpose of improving diagnosis and treatment methods. The goal of this investigation was to 1) identify the genetic variants and SNPs in Type II diabetes to develo

This research project investigated known and novel differential genetic variants and their associated molecular pathways involved in Type II diabetes mellitus for the purpose of improving diagnosis and treatment methods. The goal of this investigation was to 1) identify the genetic variants and SNPs in Type II diabetes to develop a gene regulatory pathway, and 2) utilize this pathway to determine suitable drug therapeutics for prevention and treatment. Using a Gene Set Enrichment Analysis (GSEA), a set of 1000 gene identifiers from a Mayo Clinic database was analyzed to determine the most significant genetic variants related to insulin signaling pathways involved in Type II Diabetes. The following genes were identified: NRAS, KRAS, PIK3CA, PDE3B, TSC1, AKT3, SOS1, NEU1, PRKAA2, AMPK, and ACC. In an extensive literature review and cross-analysis with Kegg and Reactome pathway databases, novel SNPs located on these gene variants were identified and used to determine suitable drug therapeutics for treatment. Overall, understanding how genetic mutations affect target gene function related to Type II Diabetes disease pathology is crucial to the development of effective diagnosis and treatment. This project provides new insight into the molecular basis of the Type II Diabetes, serving to help untangle the regulatory complexity of the disease and aid in the advancement of diagnosis and treatment.
ContributorsDavis, Vanessa Brooke (Co-author) / Bucklin, Lindsay (Co-author) / Holechek, Susan (Thesis director) / Wang, Junwen (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Arizona is a unique state in that rain is not a normal occurrence throughout most of the year (NWS). Arizona averages from less than three months to half a month of measurable precipitation days per year (WRCC). With that, it is important to know the public’s understanding as well as

Arizona is a unique state in that rain is not a normal occurrence throughout most of the year (NWS). Arizona averages from less than three months to half a month of measurable precipitation days per year (WRCC). With that, it is important to know the public’s understanding as well as their general trend of likeness towards the weather forecasts they receive. A questionnaire was distributed to 426 people in the state of Arizona to review what they understand from the forecasts and what they would like to see on social media and television.

ContributorsHermansen, Alexis Nicole (Author) / Alvarez, Melanie (Thesis director) / Cerveny, Randall (Committee member) / Hondula, David M. (Committee member) / Walter Cronkite School of Journalism & Mass Comm (Contributor) / School of Geographical Sciences and Urban Planning (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description

Many people use public transportation in their daily lives, which is often praised at as a healthy and sustainable choice to make. However, in extreme temperatures this also puts people at a greater risk for negative consequences resulting from such exposure to heat. In Phoenix, public transportation riders are faced

Many people use public transportation in their daily lives, which is often praised at as a healthy and sustainable choice to make. However, in extreme temperatures this also puts people at a greater risk for negative consequences resulting from such exposure to heat. In Phoenix, public transportation riders are faced with extreme heat in the summer along with the increased internal heat production caused by the physical activity required to use public transportation. In this study, I estimated total exposure and average exposure per rider for six stops in Phoenix. To do this I used City of Phoenix ridership data, weather data, and survey responses from an ASU City of Phoenix Bus Stop Survey conducted in summer 2016. These data sets were combined by multiplying different metrics to produce various exposure values. During analysis two sets of calculations were made. One keeping weather constant and another keeping ridership constant. I found that there was a large range of exposure between the selected stops and that the thermal environment influences the amount of exposure depending on the time of day the exposure is occurring. During the morning a greener location leads to less exposure, while in the afternoon an urban location leads to less exposure. Know detailed information about exposure at these stops I was also able to evaluate survey participants' thermal comfort at each stop and how it may relate to exposure. These findings are useful in making educated transportation planning decisions and improving the quality of life for people living in places with extreme summer temperatures.

ContributorsGerster, Katrina Ashley (Author) / Hondula, David M. (Thesis director) / Watkins, Lance (Committee member) / School of Geographical Sciences and Urban Planning (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Regional and geographical differences may explain variability in menopausal symptom occurrence due to development of climate-specific thermoneutral zones leading to population-specific hot flash frequencies. Limited information available regarding menopausal symptoms in underserved women living in extreme heat.

Understanding the perception of menopausal symptoms in underserved women living in extreme heat regions

Regional and geographical differences may explain variability in menopausal symptom occurrence due to development of climate-specific thermoneutral zones leading to population-specific hot flash frequencies. Limited information available regarding menopausal symptoms in underserved women living in extreme heat.

Understanding the perception of menopausal symptoms in underserved women living in extreme heat regions to identify if heat impacts perception of menopausal symptoms was the objective of this study. Women in free, low-income, and homeless clinics in Phoenix were surveyed during summer and winter months using a self-administered, written questionnaire including demographic, climate and menopause related questions, including the Green Climacteric Scale (GCS).

A total of 139 predominantly Hispanic (56 %), uninsured (53 %), menopausal (56 %), mid-aged (mean 49.9, SD 10.3) women were surveyed— 36% were homeless or in shelters. Most women were not on menopausal hormone therapy (98 %). Twenty-two percent reported hot flashes and 26% night sweats. Twenty-five percent of women reported previously becoming ill from heat. More women thought season influenced menopausal symptoms during summer than winter (41 % vs. 14 %, p = 0.0009). However, majority of women did not think temperature outside influenced their menopausal symptoms and that did not differ by season (73 % in winter vs. 60% in summer, p=0.1094). No statistically significant differences seen for vasomotor symptoms between winter and summer months.

Regional and geographical differences may be key in understanding the variability in menopausal symptoms. Regardless of season, the menopausal, underserved and homeless women living in Arizona reported few vasomotor symptoms. In the summer, they were more likely to report that the season influenced their menopausal symptoms rather than temperature suggesting an influence of the season on symptom perception.

ContributorsMukarram, Mahnoor (Author) / Hondula, David M. (Thesis director) / Kling, Juliana (Committee member) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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The City of Phoenix Street Transportation Department partnered with the Rob and Melani Walton Sustainability Solutions Service at Arizona State University (ASU) and researchers from various ASU schools to evaluate the effectiveness, performance, and community perception of the new pavement coating. The data collection and analysis occurred across multiple neighborhoods

The City of Phoenix Street Transportation Department partnered with the Rob and Melani Walton Sustainability Solutions Service at Arizona State University (ASU) and researchers from various ASU schools to evaluate the effectiveness, performance, and community perception of the new pavement coating. The data collection and analysis occurred across multiple neighborhoods and at varying times across days and/or months over the course of one year (July 15, 2020–July 14, 2021), allowing the team to study the impacts of the surface treatment under various weather conditions.

Created2021-09
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Description
High throughput transcriptome data analysis like Single-cell Ribonucleic Acid sequencing (scRNA-seq) and Circular Ribonucleic Acid (circRNA) data have made significant breakthroughs, especially in cancer genomics. Analysis of transcriptome time series data is core in identifying time point(s) where drastic changes in gene transcription are associated with homeostatic to non-homeostatic cellular

High throughput transcriptome data analysis like Single-cell Ribonucleic Acid sequencing (scRNA-seq) and Circular Ribonucleic Acid (circRNA) data have made significant breakthroughs, especially in cancer genomics. Analysis of transcriptome time series data is core in identifying time point(s) where drastic changes in gene transcription are associated with homeostatic to non-homeostatic cellular transition (tipping points). In Chapter 2 of this dissertation, I present a novel cell-type specific and co-expression-based tipping point detection method to identify target gene (TG) versus transcription factor (TF) pairs whose differential co-expression across time points drive biological changes in different cell types and the time point when these changes are observed. This method was applied to scRNA-seq data sets from a SARS-CoV-2 study (18 time points), a human cerebellum development study (9 time points), and a lung injury study (18 time points). Similarly, leveraging transcriptome data across treatment time points, I developed methodologies to identify treatment-induced and cell-type specific differentially co-expressed pairs (DCEPs). In part one of Chapter 3, I presented a pipeline that used a series of statistical tests to detect DCEPs. This method was applied to scRNA-seq data of patients with non-small cell lung cancer (NSCLC) sequenced across cancer treatment times. However, this pipeline does not account for correlations among multiple single cells from the same sample and correlations among multiple samples from the same patient. In Part 2 of Chapter 3, I presented a solution to this problem using a mixed-effect model. In Chapter 4, I present a summary of my work that focused on the cross-species analysis of circRNA transcriptome time series data. I compared circRNA profiles in neonatal pig and mouse hearts, identified orthologous circRNAs, and discussed regulation mechanisms of cardiomyocyte proliferation and myocardial regeneration conserved between mouse and pig at different time points.
ContributorsNyarige, Verah Mocheche (Author) / Liu, Li (Thesis advisor) / Wang, Junwen (Thesis advisor) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Beta-Amyloid(Aβ) plaques and tau protein tangles in the brain are now widely recognized as the defining hallmarks of Alzheimer’s disease (AD), followed by structural atrophy detectable on brain magnetic resonance imaging (MRI) scans. However, current methods to detect Aβ/tau pathology are either invasive (lumbar puncture) or quite costly and not

Beta-Amyloid(Aβ) plaques and tau protein tangles in the brain are now widely recognized as the defining hallmarks of Alzheimer’s disease (AD), followed by structural atrophy detectable on brain magnetic resonance imaging (MRI) scans. However, current methods to detect Aβ/tau pathology are either invasive (lumbar puncture) or quite costly and not widely available (positron emission tomography (PET)). And one of the particular neurodegenerative regions is the hippocampus to which the influence of Aβ/tau on has been one of the research projects focuses in the AD pathophysiological progress. In this dissertation, I proposed three novel machine learning and statistical models to examine subtle aspects of the hippocampal morphometry from MRI that are associated with Aβ /tau burden in the brain, measured using PET images. The first model is a novel unsupervised feature reduction model to generate a low-dimensional representation of hippocampal morphometry for each individual subject, which has superior performance in predicting Aβ/tau burden in the brain. The second one is an efficient federated group lasso model to identify the hippocampal subregions where atrophy is strongly associated with abnormal Aβ/Tau. The last one is a federated model for imaging genetics, which can identify genetic and transcriptomic influences on hippocampal morphometry. Finally, I stated the results of these three models that have been published or submitted to peer-reviewed conferences and journals.
ContributorsWu, Jianfeng (Author) / Wang, Yalin (Thesis advisor) / Li, Baoxin (Committee member) / Liang, Jianming (Committee member) / Wang, Junwen (Committee member) / Wu, Teresa (Committee member) / Arizona State University (Publisher)
Created2022
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Infrastructure systems are facing non-stationary challenges that stem from climate change and the increasingly complex interactions between the social, ecological, and technological systems (SETSs). It is crucial for transportation infrastructures—which enable residents to access opportunities and foster prosperity, quality of life, and social connections—to be resilient under these non-stationary challenges.

Infrastructure systems are facing non-stationary challenges that stem from climate change and the increasingly complex interactions between the social, ecological, and technological systems (SETSs). It is crucial for transportation infrastructures—which enable residents to access opportunities and foster prosperity, quality of life, and social connections—to be resilient under these non-stationary challenges. Vulnerability assessment (VA) examines the potential consequences a system is likely to experience due to exposure to perturbation or stressors and lack of the capacity to adapt. Post-fire debris flow and heat represent particularly challenging problems for infrastructure and users in the arid U.S. West. Post-fire debris flow, which is manifested with heat and drought, produces powerful runoff threatening physical transportation infrastructures. And heat waves have devastating health effects on transportation infrastructure users, including increased mortality rates. VA anticipates the potential consequences of these perturbations and enables infrastructure stakeholders to improve the system's resilience. The current transportation climate VA—which only considers a single direct climate stressor on the infrastructure—falls short of addressing the wildfire and heat challenges. This work proposes advanced transportation climate VA methods to address the complex and multiple climate stressors and the vulnerability of infrastructure users. Two specific regions were chosen to carry out the progressive transportation climate VA: 1) the California transportation networks’ vulnerability to post-fire debris flows, and 2) the transportation infrastructure user’s vulnerability to heat exposure in Phoenix.
ContributorsLi, Rui (Author) / Chester, Mikhail V. (Thesis advisor) / Middel, Ariane (Committee member) / Hondula, David M. (Committee member) / Pendyala, Ram (Committee member) / Arizona State University (Publisher)
Created2022