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This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems

This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems biology level, I provide new targets to explore for the research community. Furthermore I present a new online web resource that unifies various bioinformatics databases to enable discovery of relevant features in 3D protein structures.
ContributorsMielke, Clinton (Author) / Mandarino, Lawrence (Committee member) / LaBaer, Joshua (Committee member) / Magee, D. Mitchell (Committee member) / Dinu, Valentin (Committee member) / Willis, Wayne (Committee member) / Arizona State University (Publisher)
Created2013
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While exercising mammalian muscle increasingly relies on carbohydrates for fuel as aerobic exercise intensity rises above the moderate range, flying birds are extraordinary endurance athletes and fuel flight, a moderate-high intensity exercise, almost exclusively with lipid. In addition, Aves have long lifespans compared to weight-matched mammals. As skeletal muscle mitochondria

While exercising mammalian muscle increasingly relies on carbohydrates for fuel as aerobic exercise intensity rises above the moderate range, flying birds are extraordinary endurance athletes and fuel flight, a moderate-high intensity exercise, almost exclusively with lipid. In addition, Aves have long lifespans compared to weight-matched mammals. As skeletal muscle mitochondria account for the majority of oxygen consumption during aerobic exercise, the primary goal was to investigate differences in isolated muscle mitochondria between these species and to examine to what extent factors intrinsic to mitochondria may account for the behavior observed in the intact tissue and whole organism. First, maximal enzyme activities were assessed in sparrow and rat mitochondria. Citrate synthase and aspartate aminotransferase activity were higher in sparrow compared to rat mitochondria, while glutamate dehydrogenase activity was lower. Sparrow mitochondrial NAD-linked isocitrate dehydrogenase activity was dependent on phosphate, unlike the mammalian enzyme. Next, the rate of oxygen consumption (JO), electron transport chain (ETC) activity, and reactive oxygen species (ROS) production were assessed in intact mitochondria. Maximal rates of fat oxidation were lower than for carbohydrate in rat but not sparrow mitochondria. ETC activity was higher in sparrows, but no differences were found in ROS production between species. Finally, fuel selection and control of respiration at three rates between rest and maximum were assessed. Mitochondrial fuel oxidation and selection mirrored that of the whole body; in rat mitochondria the reliance on carbohydrate increased as the rate of oxygen consumption increased, whereas fat dominated under all conditions in the sparrow. These data indicate fuel selection, at least in part, can be modulated at the level of the mitochondrial matrix when multiple substrates are present at saturating levels. As an increase in matrix oxidation-reduction potential has been linked to a suppression of fat oxidation and high ROS production, the high ETC activity relative to dehydrogenase activity in avian compared to mammalian mitochondria may result in lower matrix oxidation-reduction potential, allowing fatty acid oxidation to proceed while also resulting in low ROS production in vivo.
ContributorsKuzmiak, Sarah (Author) / Willis, Wayne T (Thesis advisor) / Mandarino, Lawrence (Committee member) / Sweazea, Karen (Committee member) / Harrison, Jon (Committee member) / Gadau, Juergen (Committee member) / Arizona State University (Publisher)
Created2012
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Critical flicker fusion thresholds (CFFTs) describe when quick amplitude modulations of a light source become undetectable as the frequency of the modulation increases and are thought to underlie a number of visual processing skills, including reading. Here, we compare the impact of two vision-training approaches, one involving contrast sensitivity training

Critical flicker fusion thresholds (CFFTs) describe when quick amplitude modulations of a light source become undetectable as the frequency of the modulation increases and are thought to underlie a number of visual processing skills, including reading. Here, we compare the impact of two vision-training approaches, one involving contrast sensitivity training and the other directional dot-motion training, compared to an active control group trained on Sudoku. The three training paradigms were compared on their effectiveness for altering CFFT. Directional dot-motion and contrast sensitivity training resulted in significant improvement in CFFT, while the Sudoku group did not yield significant improvement. This finding indicates that dot-motion and contrast sensitivity training similarly transfer to effect changes in CFFT. The results, combined with prior research linking CFFT to high-order cognitive processes such as reading ability, and studies showing positive impact of both dot-motion and contrast sensitivity training in reading, provide a possible mechanistic link of how these different training approaches impact reading abilities.

ContributorsZhou, Tianyou (Author) / Nanez, Jose (Author) / Zimmerman, Daniel (Author) / Holloway, Steven (Author) / Seitz, Aaron (Author) / New College of Interdisciplinary Arts and Sciences (Contributor)
Created2016-10-26
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Although autism spectrum disorder (ASD) is a serious lifelong condition, its underlying neural mechanism remains unclear. Recently, neuroimaging-based classifiers for ASD and typically developed (TD) individuals were developed to identify the abnormality of functional connections (FCs). Due to over-fitting and interferential effects of varying measurement conditions and demographic distributions, no

Although autism spectrum disorder (ASD) is a serious lifelong condition, its underlying neural mechanism remains unclear. Recently, neuroimaging-based classifiers for ASD and typically developed (TD) individuals were developed to identify the abnormality of functional connections (FCs). Due to over-fitting and interferential effects of varying measurement conditions and demographic distributions, no classifiers have been strictly validated for independent cohorts. Here we overcome these difficulties by developing a novel machine-learning algorithm that identifies a small number of FCs that separates ASD versus TD. The classifier achieves high accuracy for a Japanese discovery cohort and demonstrates a remarkable degree of generalization for two independent validation cohorts in the USA and Japan. The developed ASD classifier does not distinguish individuals with major depressive disorder and attention-deficit hyperactivity disorder from their controls but moderately distinguishes patients with schizophrenia from their controls. The results leave open the viable possibility of exploring neuroimaging-based dimensions quantifying the multiple-disorder spectrum.

ContributorsYahata, Noriaki (Author) / Morimoto, Jun (Author) / Hashimoto, Ryuichiro (Author) / Lisi, Giuseppe (Author) / Shibata, Kazuhisa (Author) / Kawakubo, Yuki (Author) / Kuwabara, Hitoshi (Author) / Kuroda, Miho (Author) / Yamada, Takashi (Author) / Megumi, Fukuda (Author) / Imamizu, Hiroshi (Author) / Nanez, Jose (Author) / Takahashi, Hidehiko (Author) / Okamoto, Yasumasa (Author) / Kasai, Kiyoto (Author) / Kato, Nobumasa (Author) / Sasaki, Yuka (Author) / Watanabe, Takeo (Author) / Kawato, Mitsuo (Author) / New College of Interdisciplinary Arts and Sciences (Contributor)
Created2016-04-14
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Historically, Supreme Court interpretations of the Constitution of the United States have been significantly important, impacting the lives of every American. This honors thesis seeks to understand the ways in which the Constitution has been interpreted through the lens of political ideology. Using constitutional theory, I explain how the political

Historically, Supreme Court interpretations of the Constitution of the United States have been significantly important, impacting the lives of every American. This honors thesis seeks to understand the ways in which the Constitution has been interpreted through the lens of political ideology. Using constitutional theory, I explain how the political ideologies of classical liberalism, conservatism, libertarianism, and progressive liberalism have played a role in the interpretations of the First, Second, and Fourth Amendments. I also examine how these ideological interpretations have changed from 1776 to 2017, dividing the history of the United States into four eras: the Founding Era, the Civil War Era, the New Deal Era, and the Modern Era. First, the First Amendment's clauses on religion are examined, where I focus on the separation between church and state as well as the concepts of "establishment" and "free exercise." The First Amendment transitions from classically liberal, to conservative, to progressively liberal and classically liberal, to progressively liberal and libertarian. Next, we look at the Second Amendment's notions of a "militia" and the "right to keep and bear arms." The Second Amendment's interpretations begin classically liberal, then change to classically liberal and progressively liberal, to progressively liberal, to conservative. Finally, the analysis on the Fourth Amendment's "unreasonable searches and seizures" as well as "warrants" lends evidence to ideological interpretations. The Fourth Amendment, like the other two, starts classically liberal for two eras, then becomes libertarian, and finally ends libertarian and conservative. The implications of each of these conclusions are then discussed, with emphasis on public opinion in society during the era in question, the ways in which the ideologies in each era seem to build upon one another, the ideologies of the justices who wrote the opinions, and the ideology of the court.
Created2017-12
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Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination

Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (Committee member) / Arizona State University (Publisher)
Created2021
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The current coronavirus disease 2019 (COVID-19) pandemic has highlighted the crucial role of mathematical models in predicting, assessing, and controlling potential outbreaks. Numerous modeling studies using statistics or differential equations have been proposed to analyze the COVID-19 dynamics, with network analysis and cluster analysis also being adapted to understand disease

The current coronavirus disease 2019 (COVID-19) pandemic has highlighted the crucial role of mathematical models in predicting, assessing, and controlling potential outbreaks. Numerous modeling studies using statistics or differential equations have been proposed to analyze the COVID-19 dynamics, with network analysis and cluster analysis also being adapted to understand disease transmission from multiple perspectives. This dissertation explores the use of network science and mathematical models to improve the understanding of infectious diseases. Chapter 1 provides an introduction to infectious disease modeling, its history, importance, and challenges. It also introduces network science as a powerful tool for understanding the complex interactions between individuals that can facilitate disease spread. Chapter 2 develops a statistical model that describes HIV infection and disease progression in a men who have sex with men cohort in Japan receiving a Pre-Exposure Prophylaxis (PrEP) program. The cost-effectiveness of the PrEP programwas evaluated by comparing the incremental cost-effectiveness ratio over a 30-year period against the willingness to pay threshold. Chapter 3 presents an ordinary differential equations model to describe disease transmission and the effects of vaccination and mobility restrictions. Chapter 4 extends the ODE model to include spatial heterogeneity and presents partial differential equations models. These models describe the combined effects of local transmission, transboundary transmission, and human intervention on COVID-19 dynamics. Finally, Chapter 5 concludes the dissertation by emphasizing the importance of developing relevant disease models to understand and predict the spread of infectious diseases by combining network science and mathematical tools.
ContributorsYamamoto, Nao (Author) / Wang, Haiyan (Thesis advisor) / Lampert, Adam (Thesis advisor) / Jehn, Megan (Committee member) / Arizona State University (Publisher)
Created2023
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Cities in the Global South face rapid urbanization challenges and often suffer an acute lack of infrastructure and governance capacities. Smart Cities Mission, in India, launched in 2015, aims to offer a novel approach for urban renewal of 100 cities following an area‐based development approach, where the use of ICT

Cities in the Global South face rapid urbanization challenges and often suffer an acute lack of infrastructure and governance capacities. Smart Cities Mission, in India, launched in 2015, aims to offer a novel approach for urban renewal of 100 cities following an area‐based development approach, where the use of ICT and digital technologies is particularly emphasized. This article presents a critical review of the design and implementation framework of this new urban renewal program across selected case‐study cities. The article examines the claims of the so‐called “smart cities” against actual urban transformation on‐ground and evaluates how “inclusive” and “sustainable” these developments are. We quantify the scale and coverage of the smart city urban renewal projects in the cities to highlight who the program includes and excludes. The article also presents a statistical analysis of the sectoral focus and budgetary allocations of the projects under the Smart Cities Mission to find an inherent bias in these smart city initiatives in terms of which types of development they promote and the ones it ignores. The findings indicate that a predominant emphasis on digital urban renewal of selected precincts and enclaves, branded as “smart cities,” leads to deepening social polarization and gentrification. The article offers crucial urban planning lessons for designing ICT‐driven urban renewal projects, while addressing critical questions around inclusion and sustainability in smart city ventures.`

ContributorsPraharaj, Sarbeswar (Author)
Created2021-05-07
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Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by progressive autoimmune destruction of insulin-producing pancreatic β-cells. Genetic, immunological and environmental factors contribute to T1D development. The focus of this dissertation is to track the humoral immune response in T1D by profiling autoantibodies (AAbs) and anti-viral antibodies using an

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by progressive autoimmune destruction of insulin-producing pancreatic β-cells. Genetic, immunological and environmental factors contribute to T1D development. The focus of this dissertation is to track the humoral immune response in T1D by profiling autoantibodies (AAbs) and anti-viral antibodies using an innovative protein array platform called Nucleic Acid Programmable Protein Array (NAPPA).

AAbs provide value in identifying individuals at risk, stratifying patients with different clinical courses, improving our understanding of autoimmune destructions, identifying antigens for cellular immune response and providing candidates for prevention trials in T1D. A two-stage serological AAb screening against 6,000 human proteins was performed. A dual specificity tyrosine-phosphorylation-regulated kinase 2 (DYRK2) was validated with 36% sensitivity at 98% specificity by an orthogonal immunoassay. This is the first systematic screening for novel AAbs against large number of human proteins by protein arrays in T1D. A more comprehensive search for novel AAbs was performed using a knowledge-based approach by ELISA and a screening-based approach against 10,000 human proteins by NAPPA. Six AAbs were identified and validated with sensitivities ranged from 16% to 27% at 95% specificity. These two studies enriched the T1D “autoantigenome” and provided insights into T1D pathophysiology in an unprecedented breadth and width.

The rapid rise of T1D incidence suggests the potential involvement of environmental factors including viral infections. Sero-reactivity to 646 viral antigens was assessed in new-onset T1D patients. Antibody positive rate of EBV was significantly higher in cases than controls that suggested a potential role of EBV in T1D development. A high density-NAPPA platform was demonstrated with high reproducibility and sensitivity in profiling anti-viral antibodies.

This dissertation shows the power of a protein-array based immunoproteomics approach to characterize humoral immunoprofile against human and viral proteomes. The identification of novel T1D-specific AAbs and T1D-associated viruses will help to connect the nodes in T1D etiology and provide better understanding of T1D pathophysiology.
ContributorsBian, Xiaofang (Author) / LaBaer, Joshua (Thesis advisor) / Mandarino, Lawrence (Committee member) / Chang, Yung (Committee member) / Arizona State University (Publisher)
Created2015
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Deposits of dark material appear on Vesta’s surface as features of relatively low-albedo in the visible wavelength range of Dawn’s camera and spectrometer. Mixed with the regolith and partially excavated by younger impacts, the material is exposed as individual layered outcrops in crater walls or ejecta patches, having been uncovered

Deposits of dark material appear on Vesta’s surface as features of relatively low-albedo in the visible wavelength range of Dawn’s camera and spectrometer. Mixed with the regolith and partially excavated by younger impacts, the material is exposed as individual layered outcrops in crater walls or ejecta patches, having been uncovered and broken up by the impact. Dark fans on crater walls and dark deposits on crater floors are the result of gravity-driven mass wasting triggered by steep slopes and impact seismicity. The fact that dark material is mixed with impact ejecta indicates that it has been processed together with the ejected material. Some small craters display continuous dark ejecta similar to lunar dark-halo impact craters, indicating that the impact excavated the material from beneath a higher-albedo surface. The asymmetric distribution of dark material in impact craters and ejecta suggests non-continuous distribution in the local subsurface. Some positive-relief dark edifices appear to be impact-sculpted hills with dark material distributed over the hill slopes.

Dark features inside and outside of craters are in some places arranged as linear outcrops along scarps or as dark streaks perpendicular to the local topography. The spectral characteristics of the dark material resemble that of Vesta’s regolith. Dark material is distributed unevenly across Vesta’s surface with clusters of all types of dark material exposures. On a local scale, some craters expose or are associated with dark material, while others in the immediate vicinity do not show evidence for dark material. While the variety of surface exposures of dark material and their different geological correlations with surface features, as well as their uneven distribution, indicate a globally inhomogeneous distribution in the subsurface, the dark material seems to be correlated with the rim and ejecta of the older Veneneia south polar basin structure. The origin of the dark material is still being debated, however, the geological analysis suggests that it is exogenic, from carbon-rich low-velocity impactors, rather than endogenic, from freshly exposed mafic material or melt, exposed or created by impacts.

ContributorsJaumann, R. (Author) / Nass, A. (Author) / Otto, K. (Author) / Krohn, K. (Author) / Stephan, K. (Author) / McCord, T. B. (Author) / Williams, David (Author) / Raymond, C. A. (Author) / Blewett, D. T. (Author) / Hiesinger, H. (Author) / Yingst, R. A. (Author) / De Sanctis, M. C. (Author) / Palomba, E. (Author) / Roatsch, T. (Author) / Matz, K-D. (Author) / Preusker, F. (Author) / Scholten, F. (Author) / Russell, C. T. (Author) / College of Liberal Arts and Sciences (Contributor)
Created2014-09-15