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  The Phase-Space Distribution of Galaxy Clusters

  Rozo, Eduardo; Wolfe, Brandon; Su, Shufang; Krause, Elisabeth; Dienes, Keith; Behroozi, Peter (The University of Arizona., 2023)

  We provide the modeling framework to enable a proposed new measurement of the Hubble constant, using the radial extent of galaxy clusters as a standard ruler. Observationally, we plan to measure the angular extent of the cluster and the velocity of galaxies around the cluster. More massive clusters have galaxies that orbit faster, so we can use the velocity of galaxies within clusters to estimate an effective cluster mass. To enable this, we have calibrated the relation between line-of-sight galaxy velocity and cluster mass using cosmological simulations. With an estimate of halo mass now in hand, we can infer the radius of the dark matter halo containing it. To enable this, we have also calibrated the relationship between halo mass and radius with simulations. We find that a halo whose mass is $1\times10^{14}$ $M_\odot/h$ has a physical radius of $596\pm3$ kPc/h, better than $1\%$ precision. Comparing the halo radius inferred from galaxies' velocities to their angular extent allows us to estimate the distance to the cluster, which in turn can be used to assemble a Hubble diagram for galaxy clusters. The high level of precision in the halo radius needed to establish this measurement is founded on a recent insight in halo modeling: galaxies in halos can be split into two populations: those orbiting their host dark matter halo, and those falling into the host for the first time. Here, we present an algorithm that uses the galaxies' accretion history to distinguish between them. We use our split catalog to generate fits for the orbiting and infalling galaxy phase space densities. Importantly, each can be described as depending on a single fundamental scale, the halo radius $r_h$. Both the orbiting and density profiles can be described with 5$\%$ accuracy using $r_h$ as the length scale. In velocity space, we show that the infalling velocity distribution has a bimodal appearance due to the impact of the Hubble flow on galaxy velocities. Our model of the distribution of galaxy line-of-sight velocities is also 5\% accurate. Finally, to prepare the calibration for application to galaxy clusters, we characterize the impact of cluster selection effects the phase space distribution of galaxies. To do so, we select clusters based on the galaxy counts in cylinders of height $\pm$20 h$^{-1}$~Mpc and $\pm$60 h$^{-1}$~Mpc along the line of sight. The distributions of line-of-sight velocities for both orbiting and infalling galaxies are robust to cluster selection; so is the projected orbiting surface density. The projected surface density of the infalling population, however, exhibits a strong scale-dependent bias, where the scale is set by the aperture used in the process of cluster selection. Finally, we suggest the next steps needed to characterize the dependence of the halo radius on the assumed cosmology, as well as the possible influence of baryonic processes on it. As a coda, we also include work on the broadband emission of galaxy clusters, and examine the possible detection of extra-solar neutrinos (via the ICECUBE and Auger experiments) from the Coma cluster of galaxies, as well as for $\gamma$-ray-bright clusters.
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  Ultrafast Carrier Dynamics in Two-Dimensional Materials

  LeRoy, Brian; Brasington, Alexandra; Sandhu, Arvinder; Schaibley, John; Binder, Rolf; Monti, Oliver (The University of Arizona., 2022)

  The discovery of graphene led to an eruption of research into the expansive collection of two-dimensional materials. The ability to fabricate stacked heterostructures with van der Waals materials layer-by-layer has allowed the production of unique devices and has rapidly advanced research in electronics and optics. Understanding the dynamics of carrier and phonon interactions within these systems is crucial for the development of optoelectronic devices. This thesis explores the dynamics of photo-excited carriers in two-dimensional systems: the effects of substrate choice on carrier relaxation in graphene and phonon induced bandgap renormalization in monolayer tungsten disulfide at high carrier densities. Graphene-hBN (hexagonal boron nitride) heterostructures show promising use in electronics applications due to high carrier mobility. We first explore the effect of the hBN substrate on the relaxation rates of photo-excited carriers in these heterostructures using femtosecond pump-probe spectroscopy. Time dynamics of photo-excited carriers in graphene-hBN heterostructures show a cooling rate approximately four times faster on hBN substrates compared to silicon oxide substrates. We next study the effect of variation in isotopic concentration in hBN substrates on the relaxation rates of photo-excited carriers. We measure and compare the time dynamics of photo-excited carriers in graphene-hBN heterostructures using naturally occurring hBN (containing 20% 10B and 80% 11B) and isotopically pure hBN (containing 100% 10B or 100% 11B). We observed a carrier relaxation rate ~1.7 times faster for isotopically pure hBN substrate. Isotopically pure hBN substrates samples allow more efficient decay of optical phonons from graphene into acoustic phonons in the substrate, while the isotopic disorder in naturally occurring hBN causes isotope-phonon scattering. Monolayer transition metal dichalcogenides are another van der Waals material which have garnered a lot of interest due to their direct optical band gap and strongly bound excitonic states in the visible light range. We utilize non-degenerate femtosecond pump-probe spectroscopy to measure the differential reflectivity in monolayer WS2 to investigate the interactions between carriers, defects, and phonons in the high carrier density regime. We find photo-excited carriers are trapped by defect states, which act as non-radiative recombination sites and emit phonons, which cause a phonon-induced band gap renormalization up to 23 meV.
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  The “Bel Canto” Viola: The Role of Alessandro Rolla in the Viola Catalog

  Gebrian, Molly; Lizama, Raphael David; Alejo, Philip; Mugmon, Matthew (The University of Arizona., 2022)

  The music of Italian composer Alessandro Rolla (1757–1841) serves a vital role in the catalog of important viola repertoire. Nonetheless, his vast contributions are woefully neglected by the majority of modern viola players. Familiarity with Rolla’s music can help dispel the misconception that only a small pool of viola repertoire existed prior to the 20th century. As a violist and composer, Rolla championed the viola as a viable solo instrument on equal footing with the violin. Even more significant is the critical role he played as a musical leader in Milan during the pinnacle of the Bel Canto period. It is evident that his close connection to the world of Italian opera shaped his compositional style. It is because of this that Rolla’s music holds a special position in the viola catalog.Rolla’s mature style is best understood in the context with the Italian operatic idiom known as Bel Canto. Bel Canto translates simply to “beautiful singing,” but its true definition is more elusive and remains a topic of contention. The term Bel Canto has become heavily associated with vocal technique; however, it can be understood to have much broader implications as it relates to composition, performance practice, and overall aesthetics. When examining the origins and meaning of Bel Canto, it is crucial to recognize how the development of vocal and instrumental technique evolved simultaneously. The study of Rolla’s life and work grants an invaluable opportunity to illuminate this nebulous subject. The core of this research document will focus on several of Rolla’s compositions that incorporate versions of opera arias. Also, several of his original compositions will be analyzed through the lens of the Bel Canto tradition. Comparisons will be made between Rolla’s compositional elements and those of Rossini, Donizetti, and Bellini.
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  The Preservation and Development of Black American Folk Music and of the Exodus Emblem in R. Nathaniel Dett’s the Ordering of Moses

  Mugmon, Matthew; Ford, Donté Alexander; Rosenblatt, Jay; Brobeck, John (The University of Arizona., 2023)

  Black American composer R. Nathaniel Dett (1882–1943) is a pioneering figure of American classical music composed by Black musicians. During his career—as a composer, performer, and educator—Dett advocated for the preservation of Black American folk music and its development via its use in “serious” classical music. While initially not interested in doing so, after hearing the masterful use of Black American folk music in Dvořák’s American Quartet during his student years at Oberlin College, Dett’s perspective changed; Dvořák’s composition provided a conceptual foundation for this fusion. In light of this, Dett’s career is defined by his mission to preserve and develop Black American folk music, of which his oratorio, The Ordering of Moses (1937), represents this fulfillment. This dissertation asserts that R. Nathaniel Dett’s The Ordering of Moses embodies his distinct views on preserving and developing Black American folk music, as demonstrated through his utilization of Negro Spirituals as thematic material within this work. Similarly, this dissertation holds that Dett’s symphonic work preserves and develops broader Black American idioms on account of its use of the Exodus emblem as its narrative focus, consistent with its use in the cultural expressions of Black arts, letters, and religion (Christianity).
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  Exploring the Role of the 2-AG Endocannabinoid System in Migraine Prevalence, Physiology, and Treatment

  Largent-Milnes, Tally M; Levine, Aidan; Vanderah, Todd W; Ibrahim, Mohab; Pires, Paulo (The University of Arizona., 2022)

  Migraine headache is a debilitating disorder of unknown etiology that has been documented in medical records dating back thousands of years. While advancements have been made in understanding the physiology that underlies migraine, medical scientists still struggle to fully explain the symptomology that corresponds with migraine. Trigeminal nociception is heavily implicated in migraine development, as is the role of vasodilation and alterations to blood-brain barrier integrity, yet the more that is elucidated about migraine, the more it becomes clear that migraine represents an incredibly complex neurovascular event. Current therapeutics rely primarily on inducing meningeal vasoconstriction with 5HT1B/D agonists and CGRP antagonism, but symptom relief is rarely absolute. Other options for migraine treatment include anti-inflammatory therapies, such as NSAIDs, however there is always the possibility of developing tolerance or even secondary overuse headache. Within the past two decades, the role of the endocannabinoid system has been increasingly investigated in migraine physiology. Evidence has shown that migraineurs have decreased central levels of the endocannabinoids, 2-AG and AEA, and that exogenous cannabinoid agonists can often help to alleviate migraine pain. The theory of Clinical Endocannabinoid Deficiency has emerged based off this evidence, touting that migraine, and other functional pain disorders, may stem from the observed decrease in endocannabinoid tone. Prior work in animal models has demonstrated that inhibition of AEA and 2-AG hydrolysis can ameliorate induced headache pain; however, clinical trials of AEA hydrolysis inhibitors were forced to halt due to fatal adverse effects and lack of efficacy. Therefore, investigation into endocannabinoid-based therapeutics has shifted to studies of 2-AG. In this thesis, we seek to validate reduced endocannabinoid tone during headache and to better understand the role that 2-AG plays during induced headache. As clinical prevalence of migraine shows a sex difference of roughly 3:1 for females: males, we began by investigating whether sex differences exist within the endocannabinoid system between female and male rodents. Females were shown to have reduced levels of 2-AG as compared to males within the periaqueductal gray (PAG), an important region for descending pain modulation. Furthermore, immunohistochemistry and proteomic analysis revealed that females have greater expression of the 2-AG hydrolyzing enzymes, MAGL and ABHD6, within the PAG. These results indicate that the increased prevalence of functional pain disorders in the female population may indeed arise from decreased 2-AG signaling within the PAG. We next sought to recapitulate reductions of 2-AG during migraine by utilizing three models of headache: KCl administration, sumatriptan overuse, and morphine overuse. In all three models, 2-AG was reduced within the PAG as compared to controls. Within the KCl model, we observed increased expression of MAGL and ABHD6 following headache induction, as well as increases in PGE2 and glial activation markers (GFAP). This demonstrates that currently utilized models of headache lead to reductions in endocannabinoid tone and increases in neuroinflammation in pertinent nociceptive regions. Following evidence that endocannabinoid tone is reduced during headache, and that females display reduced levels of 2-AG as compared to males, we investigated whether we could induce headache phenotypes by exogenously depleting 2-AG. DAGL synthesizes 2-AG from DAG, with DAGLα representing the primary 2-AG synthesizing enzyme within the central nervous system (CNS). We found that DAGL and specific DAGLα inhibition led to reductions of 2-AG within the PAG that corresponded to induction of periorbital allodynia without hind paw allodynia. Female and male rodents were utilized, and it was observed that females displayed greater allodynia for longer periods of time than males. DAGLα inhibition also led to increased photophobia and anxiety behaviors within animals. Taken together, these results indicate that depletion of 2-AG is sufficient to trigger headache, that females are more sensitive than males to 2-AG depletion, and that 2-AG depletion primarily induces cephalic allodynia. This validates 2-AG signaling as a player in headache development and DAGLα inhibition as a potential novel means of modeling episodic migraine phenotypes in rodents. To explore the potential of endocannabinoid-based therapeutics, we built off evidence that 2-AG is reduced during headache due to increased degradation. MAGL and ABHD6 inhibitors were employed before and after KCl induced headache to test for their abilities to prevent and reverse induced headache. We also examined for the receptor dependency of these effects by co-administering hydrolysis inhibitors with antagonists of the CB1R and CB2R. We observed that both MAGL and ABHD6 inhibition can prevent and reverse KCl induced headache. Furthermore, ABHD6 was shown to be independent of the cannabinoid receptors as a preventative treatment, while its reversal was primarily mediated via the CB1R. MAGL, on the other hand, showed dependence on the CB2R for both prevention and reversal. These findings indicate that 2-AG hydrolysis inhibitors may represent novel headache therapeutics. As the CB2R primarily signals at microglia to reduce neuroinflammation, MAGL inhibition is particularly appealing in its ability to avoid the psychoactive effects associated with CB1R agonism. Alterations to the blood-brain barrier are well documented during headache, so our final objective was to investigate the contributions of 2-AG signaling to barrier integrity. In vivo analysis of barrier permeability via carotid perfusion of 14C-sucrose demonstrated increased extravasation of 14C-sucrose into PAG tissue following both DAGLα inhibition and medication overuse, correlating with previous findings within a KCl model of headache. In vitro analysis of bEnd.3 cells following DAGLα inhibition demonstrated reduced trans-endothelial electrical resistance, increased trans-endothelial leak of 14C-sucrose, and changes in cell morphology that correlated with reductions of the tight junction protein VE-Cadherin. Further investigation of the tight junction effects elucidated that VE-Cadherin underwent cleavage following DAGLα inhibition. VE-Cadherin is primarily cleaved via a calcium dependent kinase, therefore we investigated whether DAGLα inhibition induced greater levels of intracellular calcium, which was confirmed with the calcium imaging dye Fura-2, AM. Finally, we confirmed that DAGLα inhibition was reducing endothelial cell levels of 2-AG via LC-MS. Based on this data, we conclude that DAGLα inhibition reduces integrity of the blood-brain barrier by altering the function of tight junction proteins. The results of this thesis demonstrate that 2-AG signaling plays a major role during headache development. Female rodents displayed reduced 2-AG levels in the PAG that correspond with the female prevalence of clinical migraine, currently utilized models of headache likewise reduced PAG 2-AG signaling, exogenous inhibition of 2-AG synthesis induced headache pain in a sex-dependent manner, inhibition of 2-AG hydrolysis alleviated induced headache, and depletion of 2-AG led to loss of integrity of the blood-brain barrier. This work translates well to clinical research, as the induced headache phenotypes following DAGLα inhibition correlate directly with episodic migraine. Further investigation of the effects of 2-AG depletion on the blood-brain barrier is warranted, as well as research into the potential of reversible 2-AG hydrolysis inhibitors, namely MAGL inhibitors, for clinical treatment of migraine.
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  STOCHASTIC DESIGN OPTIMIZATION FOR VIBRATION AND IMPACT MITIGATION

  Missoum, Samy; Ahmadisoleymani, Seyed Saeed; Wu, Xiaoyi; Reverdy, Paul (The University of Arizona., 2022)

  The reliability assessment and computational design of nonlinear dynamic problems require new optimization and uncertainty quantification approaches that are tailored to address the associated challenges. Namely, these problems are computationally expensive and highly sensitive to uncertainties since they model nonlinear dynamic phenomena. This work focuses on uncertainty quantification and design optimization of nonlinear dynamic problems for vibration and impact mitigation by applying state-of-the-art probabilistic methods. While such problems cover a wide range of applications, this work highlights two main applications and develops novel approaches to tackle the existing computational challenges. The first application is the stochastic optimization of nonlinear metamaterials for the manipulation and mitigation of waves. A nonlinear chain of resonators representing metamaterials is considered, in which response discontinuity and curse of dimensionality, in addition to the challenges mentioned above, hamper the traditional engineering design methods. For this purpose, the methodology that is applied tackles a discontinuous response by identifying the regions of space with vastly different response levels. Additionally, to reduce the dimensionality of the problem, a field formulation is proposed that defines numerous properties of the resonators (e.g., stiffnesses) through a handful of coefficients. The uncertainties are also taken into account by considering random design variables and loading conditions. It is illustrated that the resonators chain optimized using the algorithm is able to reliably and effectively suppress vibrations. The second application deals with vehicle crashworthiness optimization and injury risk assessment under uncertainty for improving safety. The crashworthiness problem involves the finite element simulations of a sled model and an occupant restraint system, whose responses are non-smooth due to simulation noise. In this regard, an optimization algorithm is developed based on the Non-Deterministic Kriging (NDK) formulation, which is used to approximate the response while accounting for the simulation noise and random parameters (e.g., loading conditions) as aleatory sources of uncertainties. To reduce the dimensionality of optimization problems, this algorithm accounts for random uncontrollable parameters through the aleatory covariance of the NDK kriging. An improvement of an existing adaptive sampling method is also proposed to enhance the performance of the optimization algorithm. The advantages of the methodology are illustrated using multiple analytical functions and the crashworthiness problem. In addition to the optimization algorithm, an injury risk model is developed to calculate the probability of crash-induced head injuries through the fusion of two information sources: a published experiment-based risk model and a finite element framework. The framework involves the finite element model of a car, a human dummy, and a human brain. It integrates sources of uncertainty such as impact conditions (e.g., velocity and angle) and brain material properties.
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  The Mexico City Metro: Appropriation and Assimilation of Foreign Technology To Stay on Track With Other Modern Capital Cities and To Produce a Technological and Cultural Marvel

  Beezley, Wiiliam; Carroll, George D.; Gantz, David; Gosner, Kevin (The University of Arizona., 2023)

  This paper provides a review of the construction of the metro in Mexico City and evaluates themetro as a production of culture. The incorporation and Mexicanization of foreign technology allowed Mexico to build and service a metro while making it uniquely Mexican. The naming of the stations and the use of icons to identify them project Mexican culture and power. The art within the stations and the activities travelers see and participate in are also examples of how Mexico’s metro is unique to its culture. The use of newspaper articles from major cities from around the world demonstrated that the metro was accepted as a successful technological marvel. Newspaper articles, songs, and local art show that Mexicans accepted the metro as their own. We conclude that the metro was a cultural production that propelled Mexico City to the same level as other modern capital cities.
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  Urban Food System Transformations and Governance in Sub-Saharan Africa

  Evans, Tom; Davies, Julia Elaine; Liverman, Diana; Josephson, Anna (The University of Arizona., 2022)

  By 2050, there will be an estimated 1 billion people living in cities of sub-Saharan Africa (SSA) – a threefold increase from the region’s current urban population of 350 million. While urbanization can drive economic growth and social development, a complex array of intersecting factors mean that it can equally lead to high rates of urban poverty and, by extension, urban food insecurity. Much of the urban population growth occurring in SSA is taking place in secondary cities, which are playing an increasingly important role in national and regional urban development. Yet, these smaller urban areas have received little attention in the scholarly literature despite the fact that they often experience more acute challenges linked to resource and governance constraints. In this dissertation I adopt a mixed-methods approach to investigate the drivers of urban food insecurity in secondary cities of SSA using an urban food systems lens. Through my analyses I address transformations in urban food systems linked to urbanization and retail modernization and provide insight into how urban policies and planning agendas affect how people living in cities are able to access adequate and nutritious food both now and in the future. This research enhances our understanding of how urban food retail and urban governance can contribute to more sustainable, equitable, and resilient urban food systems in SSA and globally. The first component of my dissertation research assesses the barriers to urban agriculture in SSA that limit the degree to which this livelihood activity is suitable as an urban food security strategy. This research is based on survey data collected from 2,687 low- and low-middle income households in 18 secondary urban areas of Zambia and Kenya. My results reveal that one third of households in the sample are growing some of their own food, but there is limited statistical significance in terms of the relationship between urban agriculture and household food security. Key barriers to urban agriculture identified in this study include settlement informality, a lack of property rights, and the location of households relative to food retailers. These findings imply the need for urban planners and policymakers to revisit how decisions are made about issues such as residential development, land tenure, transport infrastructure, and the use of space in cities, as these affect the ability of households to produce, sell, and access food. The second component of my dissertation research focuses on traditional open-air markets in rural and urban areas of Zambia. This work uses data from a 2021 phone call survey of 81 traditional markets and draws inspiration from Ostrom’s design principles for enduring common pool resources to identify some of the institutional arrangements that tend to lead to effective market performance in Zambia. Statistical analysis revealed that market formality, the role of market committees, government engagement in markets, and conflict resolution protocols are all important institutional factors to consider in this regard. My contribution of a methodology for studying traditional market governance sets the stage for further research to empirically identify which sets of institutional arrangements could lead to effective market performance beyond the Zambian context. A key message emerging from this research is the need to recognize that there is no panacea for achieving sustained market performance, but rather this depends on finding the most appropriate fit between institutions and the problems that they are trying to address. The third component of my dissertation research builds on and expands my work on traditional markets in SSA. In this systematic review paper, I consolidate the findings of 76 articles on urban food market (UFM) governance. I focus not only on traditional markets in Africa, but on other types of UFMs in diverse global development contexts. My analysis shows a significant increase in the number of empirical studies on UFM governance since 2015 and indicates that the majority of articles included in the review were focused on UFMs in primary cities of Africa and Asia. This work highlights opportunities to advance research in the field of UFM governance by integrating qualitative methods with quantitative methods. It further emphasizes that more inclusive forms of governance can help UFMs to thrive, thereby enhancing the contribution of these markets to the food security, health, and wellbeing of city inhabitants around the world. Overall, my dissertation research highlights the complexity of urban food system activities, drivers, and outcomes, including food security outcomes, which are themselves multifaceted. This complexity implies the need to adopt an integrated and context-specific approach to addressing urban food insecurity in SSA and globally. Many of the interventions that could enhance urban food systems and reduce urban food insecurity lie in the urban planning sphere. Both direct food system interventions and food sensitive planning will be required to maximize urban food system outcomes. While significant effort will be required to coordinate such a response, the potential outcomes could extend well beyond food security and encompass poverty reduction, environmental health, and social wellbeing.
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  The Association Between Oral Glucose-Control Agents and Incident Dementia in Type 2 Diabetes Within the Veteran’s Affairs Healthcare Enrollees

  Chen, Zhao; Tang, Xin; Farland, Leslie; Klimentidis, Yann C.; Zhou, Jin (The University of Arizona., 2022)

  INTRODUCTION: Dementia is a major contributor to disability and death. A risk factor of dementia is type 2 diabetes (T2D). Current evidence suggests shared causes of the two diseases and a potential to repurpose specific glucose-control agents (GCAs) for dementia prevention or treatment. However, clinical trials and population studies focusing on this topic are insufficient to conclude GCAs anti-dementia effects and compare effectiveness of different GCAs. This dissertation intended to compare the effects of monotherapy and concomitant use of GCAs on dementia. The results should be able to provide suggestions on GCAs selection in T2D, in terms of dementia risk management. METHODS: In this dissertation, study 1 and study 2 used medical records from the Veteran’s Affairs Healthcare (VAH) database. Glucose-control treatment histories were extracted from prescription records and were aggregated at drug class level. Disease conditions were extracted from outpatient diagnosis records, coded by ICD-9 or ICD-10. Four antidiabetic drug classes were assessed based on a literature review and VAH data richness. Among T2D, study 1 compared the associations of first-generation antidiabetic drug classes (metformin [MET], sulfonylureas [SU], and thiazolidinedione [TZD]) with the risk of dementia. And study 2 compared the associations of adding dipeptidyl peptidase-4 inhibitors (DPP-4is) to MET and/or SU (MET/SU) treatment with risks of dementia and other vascular events. To capture the trends of clinical evidence in relevant fields, study 3 reviewed phase II, III, and IV clinical trials repurposing GCAs for Alzheimer's disease (AD). RESULTS: In T2D without prior dementia, study 1 found that after at least one year of treatment, compared with MET monotherapy users, the risk of all-cause dementia was 22% lower in TZD monotherapy users (HR: 0.78, 95% CI 0·75-0·81), and 11% lower in MET and TZD dual therapy users (HR 0.89, 95% CI 0·86-0·93), whereas the risk was 12% higher in sulfonylurea monotherapy users (HR 1.12 95% CI 1·09-1·15). In study 2, compared with participants staying on MET/SU treatment, participants who added DPP-4is to MET/SU regiments had lower risks for the cerebrovascular outcome (HR, 0.68, 95% CI, 0.62-0.74), and the microvascular outcome (HR, 0.91; 95% CI, 0.88-0.94), but not associated with the risk for the renal outcome (HR, 1.03, 95% CI, 0.97-1.10). In study 3, 26 clinical trials were reviewed and summarized in a narrative way. Elders with mild cognitive impairment, AD, and other types of dementia were the main trial participants. Among studied GCAs, insulin, MET, and pioglitazone showed protective effects on subsets of cognitive function but findings on global cognition and AD biomarkers were neutral. But evidence of other GCAs was either insufficient to make conclusions or unavailable. CONCLUSION: These studies suggest that different GCAs had varied effects on dementia risk within elder T2D, although GCAs may be unable to modify AD progression after AD onset. Without disturbing diabetes management, clinicians may consider lowering patients’ dementia risk through GCAs selection. Additional research is warranted to exam whether our findings apply to younger populations and minority groups.
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  "I Don't Get Drunk. I Get Awesome!" Employing a Vulnerability-Stress-Adaptation Framework to Examine Alcohol Use in Emerging Adulthood

  Burross, Heidi HB; Liang, Sizhan; Curran, Melissa MC; Cimetta, Adriana AC (The University of Arizona., 2022)

  Building on emerging adulthood theory and the Vulnerability-Stress-Adaptation (VSA) framework, this dissertation research examined emerging-adult newlywed couples’ alcohol drinking behaviors. Four-annual-wave, dyadic data from 963 couples were analyzed with an Actor-Partner Interdependence Model (APIM) to investigate 1) personality traits and stressful life events (SLEs) as predictors of emerging adults’ alcohol use, and 2) personality traits and alcohol use as predictors of emerging adults’ experiences with SLEs. Results revealed great predictive power of personality traits, especially for emerging-adult men; trait kindness and trait sociability were influential in alcohol involvement while trait anxiety and trait depression were closely associated with SLEs. Emerging-adult women’s perceived stressfulness of SLEs displayed both actor and partner effects, positively predicting alcohol involvement for themselves as well as for their emerging-adult husbands. The potential vicious circle of SLEs and alcohol drinking behaviors suggested by the VSA model was not supported. The findings inspire researchers to further explore whether men are more affected by internal characteristics whereas women are more susceptible to the external circumstances, which may enlighten couple therapy on coping strategies.
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  The Interplay Between Diseases and Adaptation in the Human Genome

  Enard, David; Di, Chenlu; Barker, Michael; Gutenkunst, Ryan; Masel, Joanna (The University of Arizona., 2023)

  Human health is largely influenced by genetic architecture and living environments. Evolutionary processes, especially past adaptation to changing environments, shaped the genetic architecture and might deeply influence current disease risks. Advances in genomic sequencing dramatically improved our understanding of the genetic basis of diseases in the past ten years. Thousands of genes have been found to be associated with non-infectious and infectious diseases. However, the adaptation experienced by disease-associated genes is not well characterized, let alone the potential causal relationships between disease and genomic adaptation. Here, we use human genomic data to characterize the interplay between adaptation and human non-infectious diseases: what disease gene attributes may influence adaptation, and conversely how past adaptation may have shaped the landscape of disease variants. In the first chapter, I study an important prerequisite: accounting for confounders when studying adaptation in groups of genes, for example, disease genes, relative to the rest of the genome. I show how the lack of accounting for confounding factors other than the biological categories of interest can cause spurious results in the framework of Gene Set Enrichment Analysis (GSEA) of past adaptation. I propose a pipeline that specifically addresses the methodological problems of GSEA applied to recent adaptation in the form of selective sweeps. In the second chapter, I use the GSEA approach established in the first chapter to study the relationship between human non-infectious disease and recent adaptation. I specifically try to clarify the dominant causal direction of this relationship. Adaptation might increase the risk of diseases. For example, deleterious mutations may increase in frequency by hitchhiking with advantageous mutations and thus genes carrying deleterious variants may experience more recent adaptation compared to non-disease genes. Alternatively, pre-existing disease status associated with disease genes might affect the occurrence of selective sweeps at disease genes through the specific attributes that differentiate disease genes from non-disease genes. We find a deficit of selective sweeps in Mendelian non-infectious disease genes compared to non-disease genes in the human genome. This deficit is due to linked disease variants substantially slowing down adaptation at disease gene loci. This highlights a dominant causal relationship direction, without however excluding the possibility that selective sweeps have also increased the frequency of linked disease variants, albeit not at a sufficiently large number of genes to create a visible selective sweep enrichment to counteract the observed deficit, caused by the more predominant opposite action of disease variants slowing down linked adaptive variants. Thus, the picture that emerges from these results is that predominantly, some pre-existing specific attributes of disease genes have limited recent adaptation at their corresponding loci. Taking a step back to the definition of disease, disease is a phenotype that largely deviated from the optimum. What processes might increase the risk of having a largely deviated phenotype? Past strong adaptations, including those that took place a long evolutionary time ago, may have taken the associated phenotypes further from the current optimum compared to the hypothetical situation where these adaptations had not occurred. For example, for a protein whose optimal abundance is high in the current and most historical environments, past adaptation to one particular environment that lowers the abundance to the edge of the disease-causing value may increase the risk of association with diseases. Any mutation that slightly further decreases the abundance may push the abundance of the protein below the critical disease level. In this respect, past strong and rapid adaptation, as opposed to weak and slow adaptation, should have been particularly prone to cause pronounced shifts away from phenotypic optima. An important difficulty then is to first identify past strong adaptations in the human genome. This challenge presented an opportunity for me to connect my work on non-infectious diseases and adaptation to the work done by the rest of the lab on virus-driven adaptation. As mentioned, past strong adaptation should have been more prone to distance phenotypes away from the current optima. We happen to know that viruses drove strong adaptation in human host genomes during ancient viral epidemics, in genes that interact physically with viruses (VIPs for Virus-Interacting Proteins). This strong adaptation notably likely involved adaptive changes in gene expression and abundance, a phenotype that has been shown many times to be connected to genetic diseases. Although we do not have access to past changes in protein abundance directly, we can infer past changes in protein stability, the protein property that affects abundance of folded, functional proteins. In the third chapter, I therefore study host protein adaptations in response to viruses that were driven by changes in protein stability of VIPs. We find that past strong adaptation in VIPs mostly involved large stability changes. This result indicates that host VIP protein stability and thus protein abundance is a phenotype that was strongly selected during ancient viral epidemics. However, the optimal protein stability during past epidemics may be deviated from the current optimum after the selective pressure is weak or gone. In fact, we find compensatory evolution that keeps protein stability stable following viral epidemics in proviral VIPs which have broadly conserved non-immune host native functions. At the same time, specifically, many genetic diseases are known to carry disease variants that decrease thermodynamic stabilities. It is possible that strong past adaptation to viral infections that largely changed protein stability in VIPs increases the risk for following mutations to be deleterious. However, further research is needed to connect these virus-driven adaptive changes in VIP stability to the present occurrence of non-infectious disease variants at VIPs. This connection represents a logical further avenue of research to continue to characterize the relationship between non-infectious disease genes and adaptation.
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  Interpretable Natural Language Processing with Applications to Information Extraction

  Surdeanu, Mihai; Tang, Zheng; Surdeanu, Mihai; Zhang, Chicheng; Morrison, Clayton; Hahn-Powell, Gus (The University of Arizona., 2022)

  Interpretability is very important for many NLP applications. Many such applications (e.g., information extraction, sentiment analysis) are applied to important decision-making areas like government policy, financial, law, and others. In these scenarios, machines must explain the information produced, if they are to be deployed in the real world. In this dissertation, we present some approaches for information extraction that mitigates the tension between generalization and explainability by jointly training for the two goals. First we investigate an approach uses an encoder-decoder architecture, which jointly trains a classifier for information extraction, and a rule decoder that generates syntactico-semantic rules that explain the decisions of the classifier. We evaluate the proposed approach on two different information extraction tasks and show that the decoder generates interpretable rules that serve as accurate explanations for the classifier's decisions, and, importantly, that the joint training generally improves the performance of the classifier. We show that our approach can be used for semi-supervised learning, and that its performance improves when trained on automatically-labeled data generated by a rule-based system. Second, we investigate another approach uses a multi-task learning architecture, which jointly trains a classifier for relation extraction, and a sequence model that labels words in the context of the relation that explain the decisions of the relation classifier. We also convert the model outputs to rules to bring global explanations to this approach. This sequence model is trained using a hybrid strategy: supervised, when supervision from pre-existing patterns is available, and semi-supervised otherwise. In the latter situation, we treat the sequence model's labels as latent variables, and learn the best assignment that maximizes the performance of the relation classifier. We evaluate the proposed approach on the two relation extraction datasets and show that the sequence model provides labels that serve as accurate explanations for the relation classifier's decisions, and, importantly, that the joint training generally improves the performance of the relation classifier. We also evaluate the performance of the generated rules and show that the new rules are great add-on to the manual rules and bring the rule-based system much closer to the neural models. Third, we also explore the usages of the model outputs in two ways: 1. Convert them to rules to bring global explanations to this approach; and 2. Use them for bootstrapping when we do not have enough data. Our globally-explainable models approach the performance of neural ones within a reasonable gap.
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  Water Distribution Burst Detection and Localization Using Advanced Metering Infrastructure Data Collection Systems

  Lansey, Kevin E.; Jun, Sanghoon; Duan, Jennifer; Boccelli, Dominic; Winter, Larrabee; Liu, Jian (The University of Arizona., 2022)

  Pipe bursts are one of the most common failures in water distribution networks (WDNs). To minimize their impact, numerous burst detection and localization methods have been developed that identify failures using hydraulic measurements (e.g., pipe flow and pressure) collected from supervisory control and data acquisition (SCADA) data collection systems (DCSs). However, since their monitoring networks are sparse, SCADA systems are often insufficient to identify realistic sized bursts. A clear next step is to develop detection and localization methods for smart systems that collect advanced metering infrastructure (AMI) data (i.e., AMI systems). However, no previous work has proposed tools for the AMI DCSs.The goal of this dissertation is to develop a series of burst detection and localization methods that employ AMI data. Depending on the data being measured (whether AMI flow and/or pressure), appropriate detection/localization approaches are proposed and tested under a range of realistic burst sizes. In addition, these methods are compared for different levels of AMI DCSs to identify which method works best for a given WDN. This dissertation is composed of six journal manuscripts that propose several burst detection and localization approaches for AMI DCSs. First, a new burst detection algorithm employing AMI demands is developed for AMI system where individual end-user demands and system inflow rates are measured. With that approach as a basis, the impact of missing AMI data is assessed. Then, convolutional neural network deep learning models and linear programming based burst detection and localization methods are developed for AMI DCSs where both AMI demand and pressure are measured. Finally, the proposed methods are tested for alternative WDNs and are evaluated using metrics of detection probability, false alarm rate, time to detect, and localization pipe distance.
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  Modeling and Optimization of a Greenhouse-type Solar Dryer System

  Kacira, Murat; Lopez Cruz, Irineo L.; Valencia Islas, Jose Olaf; Giacomelli, Gene; Li, Peiwen; Ruiz Garcia, Agustin (The University of Arizona., 2022)

  Solar drying of agricultural products is a practice that has become popular not only because it uses renewable energy as the main source of heat but also because it can reduce the waste of products with a high water content that, under normal circumstances, have a short shelf life. Solar drying in controlled environments is the safest and most effective way to dehydrate from being contaminated during the process by dust, insects, birds, rain, and other environmental factors, which reduce the quality of the final product and increase the time it takes to dry as open sun drying depends on the ambient environmental conditions. Other advantages of drying in controlled environments, for instance in a greenhouse, include the ability to use the greenhouse effect in favor, heating the air before introducing it into the drying chamber or directly in the drying chamber, reaching temperatures higher than those present in the outdoor environment; the capacity for precision control and the reduction of UV radiation, which can decompose and change the color of the products, produce dehydrated foods in less time and with better qualitative characteristics without losing vitamins or nutritional substances that are desirable to preserve. The mathematical modeling of greenhouses as solar dryers is of interest due to the complexity of the drying process. Since drying is a process that involves mass and heat exchanges, changes of state in the matter, and with different scales, the modeling approach can be diverse for various products with different geometries, coefficients, and physical characteristics, as well as the dryer’s physical attributes. The mathematical modeling of [greenhouse as] solar dryers is to the complexity of the drying process. Since drying is a process that involves mass and heat exchanges, changes of state in the matter, and with different scales, the modeling approach can be diverse for various products with different geometries, coefficients, and physical characteristics, as well as the dryer’s physical attributes. The thin-layer models have predominated over the modeling of mass and energy exchange between air and the product in the form of ordinary differential equations, partial equations, or finite-difference equations. The thin-layer approach is limited when the temperature at which the product is dehydrated is not constant, as well as if the thickness is greater than 5 mm. The models with differential equations, based on energy and mass balances, have an advantage over those of thin layers because they contemplate more states and variables than just the drying time. However, one limitation is how the processes are modeled at the product level. If the air inside a dryer is considered, the volume will be greater than the volume of the product and the change in the mass of water that is inside the product causes problems when trying to model it with two different size scales. These differential equations usually use the thin-layer approximation, thus achieving that the change in the moisture content of the product can be modeled once the thin-layer drying of the product has been studied. Other approaches for product modeling solve mass and energy balances, but only up to the product boundaries where the surrounding drying medium is not considered. Computational Fluid Dynamics (CFD) allows for understanding the airflow that is generated in the different dryers and studying the variation in temperature due to the design and even the position of the sun. Nevertheless, as with the ordinary differential equations approach, product modeling remains a challenge to overcome. The CFD is based on partial differential equations that can be approximated with algebraic equations when the volume of the dryer is discretized and a numerical model is used, that converts each node into an equation to be solved for each variable. The associated computational time and cost increase as the problem domain volume increases and simulations can take up to days. The greatest advantage of this approach is its ability to understand the process in three-dimensional form and visualize the air inside the dryer providing greater details about the flow field. In addition, it allows to evaluate various design ideas and what-if scenarios cost and time effectively and offers recommendations for improvements. Of all the types of dryers, the most common is the cabinet dryer, a small structure (<1 m2) where the air is preheated in sections where there is only air. Then, it is introduced to the drying chamber, where the product is located. The air remains until the desired temperature is reached, or the air is saturated with the moisture of the product. Finally, the air is extracted from the drying chamber through a chimney and the cycle is restarted with a renewal of preheated air. The generally small size of the drying chamber and preheating element make this type of dryer favorable for home production or supervised conditions. This type of dryer is not an option for scale-up to increase capacity.The greenhouse design has the drying chamber and the air preheating completed in the same area. They are usually larger and have a semi-transparent cover allowing sunlight to pass through and warm the air by solar heating. With its much larger size (>100 m2), a greater quantity of product can be dried, and the quality of the product can be monitored periodically without affecting the internal drying conditions of the greenhouse. However, increased size creates problems including poor and non-uniform air distribution, the possibility of over-drying the product if the temperature is not well controlled, and the need for more labor to manage the greenhouse in terms of product preparation, positioning, cleaning, and collecting. The design of the greenhouse, such as the use of special covers with filters that can capture long-wave radiation and reduce the amount of UV light can also be considered in the design of these dryers. In addition, studies suggest the possibility of having greenhouses designed for the dual purpose of agricultural production and product drying. Even with the disadvantages of increasing the size, less contamination, the possibility to control the environmental conditions, and reducing the drying time is enough to consider greenhouses for drying. A greenhouse-type solar dryer was built and evaluated at the Universidad Autonoma Chaping (Mexico). The initial efforts focused on investigating sliced tomato product drying with data collection, and with 35 different thin-layer drying models that were evaluated for drying tomatoes to determine the best model for this type of drying system and the dried product. The innovation and contribution of this work were the evaluation of semi-theoretical and empirical models, analyzing the number of parameters, the assumptions, and the accuracy of the model predictions confirmed with the data sets available that were not used as part of the model calibration. The latter has not been included in other thin layer model-based studies, as well as identifying the models with less complexity and better prediction accuracies. The results indicate that the best empirical thin layer model was the Regression model with two parameters, an R2 of 0.994 and an RMSE of 0.059 when presented with new data (data not used during the calibration process). The best semi-theoretical model was the modified Page VI model with two parameters, an R2 of 0.993, and an RMSE of 0.06 with new experimental data. The Page VI model was recommended for this study since it is a theoretical model with only two parameters which reduces the complexity during model calibration. The study also concluded not to continue developing thin-layer models since most of them have already been demonstrated with good performance, or to model with other approaches where more parameters and variables are involved as they remain under development. Although it was concluded that the use of thin-layer models greatly simplifies the modeling of moisture content in agricultural products, they are still limited to a detailed understanding of the driving mechanisms and phenomena behind solar drying. The second part of this dissertation research designed a controller based on black box models with the subspace state space system identification (N4SID) approach. The control simulation was performed using the methodology of the Model Predictive Controller (MPC), The results indicated that there was a reduction in the amount of fan operation required with the use of the MPC control when compared to a controller based on a setpoint and an ON/OFF strategy. The idea to use an MPC control was for its ability to use measurements and models to decide the optimal control strategy over time given the real system actuators limitations. The innovation presented with the MPC based control approach is the use of system identification to generate a model in state space for the greenhouse-type solar dryer system considering the product temperature, air temperature, air relative humidity, greenhouse soil, and cover temperatures. The ventilation rate was the input control variable while the air temperature, relative humidity, and solar radiation outside the greenhouse were considered as disturbances. The MPC controllers usually require actuators with analog feedback; however, the fans used in this study, ran only at full capacity as soon as they were turned ON. This allowed the fans to be considered separate (being able to turn just one or both) and together (both activated at the same time) to define the ventilation rate required, which is a novelty used for this control approach. Another important feature of this control strategy was to consider the product temperature as the variable to make the control decision instead of the air temperature which is traditionally controlled. The study indicated that the air temperature can be at a value much higher than that required in tomato slices, something not previously studied. Finally, a CFD model was developed, validated, and used to study a greenhouse-type solar dryer. An extensive literature review was performed on the state of the art in CFD modeling for greenhouse-type solar dryers. The review revealed that the CFD modeling studies for greenhouse solar drying systems are still limited. The current study evaluated air temperature distribution in the internal volume of the dryer when the exhaust fans were not operating and there was a cloudy day. The dryer, by design, had its air inlets always open, so there could be an exchange between the external and internal conditions of the air. The model was evaluated along with measurements and once the model was validated, it was used to evaluate design alternatives in the dryer. An alternative air distribution system design was proposed and evaluated that can enhance environmental uniformity and provide desired air temperatures, especially at the drying product locations in the greenhouse solar dryer system. Due to the observed stratification in the air temperature inside the dryer, it was decided to test whether forcing the air from the greenhouse attic to flow under the drying tables improved the process conditions (air velocity and temperature). Various configurations, including cases with two different systems for moving the air from the greenhouse attic to below the benches, with two and three rows of tubing with holes distributed along their lengths were tested. The cases with three air-distributing lines positioned under the drying benches improved the homogeneity of the air temperature both at the level of the drying benches and above it within the greenhouse.
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  Multisensory Soft Robotic Explorer With a Biologically Inspired, Shape-Memory Alloy-Driven, Dual-Action Propulsion System for Extreme Aqueous Environments

  Fink, Wolfgang; Nuncio Zuniga, Andres; Subbian, Vignesh; Secomb, Timothy; Matsunaga, Terry (The University of Arizona., 2022)

  The final frontier of extraterrestrial planetary exploration is the exploration of subsurface environments, such as caves and oceans. Inparticular, the existence of subsurface oceans on celestial bodies – e.g., Europa and Enceladus – known as ocean worlds has been backed by varying levels of evidence since the 1980s, but there has been no direct confirmation as of yet. Such environments are largely shielded from radiation, and in combination with the hypothesized presence of water, are prime candidate environments for finding extant or extinct life. However, the in-situ exploration of these subsurface oceans at hypothesized depths ranging anywhere from 1km to 100km (including terrestrial oceans up to 11km) necessitates disruptive advances in the design of robotic subsurface explorers capable of operating in such extreme aqueous environments, i.e., at such depths/pressures and temperatures. The field of underwater exploration systems is currently dominated by rigidly framed robots whose designs convey a philosophy of having widearenas in which to move about without interruption. However, such a design ideology is less suitable for confined environments, which might limit a rigid explorer’s ability to navigate, and for extreme environments characterized by high pressures and low temperatures, i.e., extreme aqueous environments, such as Titan’s hydrocarbon lakes. Limited efforts have gone towards designing underwater exploration systems with a soft robotics philosophy, which overcomes the limitations of stiff robotic systems and permits more flexibility in underwater exploration. It is in this soft robotics underwater exploration context that the research of this Ph.D.-Thesis takes root: The design of a multisensory soft robotic explorer with a biologically inspired propulsion system for extreme aqueous environments using silicone rubber, thereby reframing its flexibility in a space which physically hinders the use of commonly employed pneumatic or hydraulic drivers. Taking inspiration from various biological sources including jellyfish, squid, octopus, and even the chambers of the human heart, this work presentsthe prototype for an autonomous underwater soft robotic exploration system featuring a novel propulsion system for navigation that is devoid of any (electric) motors or actuators and thus well-suited for extreme aqueous environments. The soft robotic explorer features onboard sensors for depth/pressure and temperature, and an onboard computer in charge of data recording, navigation, and propulsion control. Silicone rubber, widely used in other soft robotics applications due to its flexibility, forms the overall shell of the soft robot and its thrusters, and encases the onboard electronics. In addition, its electric inertness to permit direct electronics enclosure, resistance to saltwater degradation, maintained flexibility in low temperatures, and suitability for an additive manufacturing process were reconfirmed. The resulting soft robotic explorer system is fully sealed for all electrical components and fully open in its propulsion design.
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  Uncovering the Role Select Residues Play in Mediating RasC Activation and Interaction With mTORC2

  Charest, Pascale G.; Smith, Stephen Flint; Cordes, Matthew; Marty, Michael; Montfort, William (The University of Arizona., 2022)

  Cellular migration toward a chemical gradient is chemotaxis and is a crucial biological function of embryonic development, immune response, and wound healing. On a cellular level, chemotaxis begins when a cell surface receptor binds a chemical messenger and transmits the signal across the plasma membrane. This signal transduction initiates the chemotaxis signaling network that culminates with cell polarization toward the chemical gradient and cellular protrusions in that direction. In Dictyostelium, two key players in this signaling network are thought to directly interact, RasC and mechanistic target of rapamycin complex 2 (mTORC2), and the work of this dissertation is to understand which residues of RasC play a role in this interaction. To this end, we designed mutations to RasC, expressed the mutant RasC proteins in Dictyostelium cells lacking rasC (rasC-), and analyzed the downstream effects. We found that mutation of A31 to aspartic acid prevents RasC activation by its guanosine exchange factor (GEF). We also found that disruption of membrane anchoring residues in the hypervariable region (HVR) prevents RasC from localizing to the membrane and participating in downstream signaling. Some residue changes in both the effector domain and allosteric domain of RasC disrupt chemotactic signaling and prevent Dictyostelium from developing and activating mTORC2 in the same way as RasCWT. We also began working on purification methods of RasC using both bacterial and Dictyostelium expression, and labeling RasC with a tetra-cysteine tag suitable for fluorescent labeling. This work on understanding the in vivo activity of RasC, purifying RasC from multiple expression vectors, and developing fluorescently tagged RasC has helped us understand the RasC-GEF interaction and has given insight into the RasC-mTORC2 signaling pathway. We found that RasC does not express as a soluble product in bacteria, and that purification from Dictyostelium is difficult to scale. The work on fluorescently tagging RasC is ongoing.
• A Descending Pain Modulation Pathway in Green Light-Induced Antinociception

  Ibrahim, Mohab; Martin, Laurent; Cheng, Kevin; Vanderah, Todd; Malan, Philip; Patwardhan, Amol (The University of Arizona., 2023)

  In light of the opioid epidemic in the United States, the need for non-opioid treatments of pain is ever-growing. Over the past two decades, phototherapy has been increasingly shown to be efficacious for the treatment of chronic pain. Notably, recent reports have demonstrated green light therapy to be efficacious in the treatment of chronic pain in both pre-clinical and clinical studies. Previous studies in our laboratory have shown that green light therapy requires the visual pathway as well as pain modulating centers in the central nervous system to elicit its antinociceptive effects. However, the specific neural mechanisms engaged within the central nervous system have not yet been fully elucidated. The work in this dissertation sheds light on the involvement of the endogenous opioid system and the descending pain modulatory rostral ventromedial medulla (RVM) in the antinociception induced by green light (GLED) exposure. Chapter 1 elaborates on the various applications and mechanisms of pain phototherapy by way of a literature review, whereas Chapter 2 provides an overview of central pain modulation pathways, particularly that of the descending pain modulatory system. Chapter 3 presents data characterizing the requirement of μ- and d- opioid receptor agonist stimulation by their endogenous agonists, b-endorphin and enkephalin, respectively, in GLED-induced antinociception. Chapter 4 establishes the role of the pain- modulating RVM in GLED-induced antinociception. The results in Chapter 3 prompted an investigation into the role of endogenous opioids in RVM on GLED-induced antinociception, in which it was revealed that opioid-receptor antagonism in the RVM reversed GLED-induced mechanical antinociception, but not thermal antinociception. Selective CRISPR knockout experiments ultimately demonstrated that μ- and d- opioid receptor agonist stimulation in RVM GABAergic neurons is required for GLED-induced mechanical antinociception. To further the translatability of our findings on GLED-induced antinociception to human patients, we conducted a clinical investigation on healthy human subjects to determine the involvement of the ascending and descending pain pathways in GLED-induced antinociception, described in Chapter 4. By using thermal and mechanical assessments of temporal summation and conditioned pain modulation, we determined that GLED-induced antinociception does indeed involve the descending pain pathway. These findings corroborate the results from the animal studies, confirming the contribution of the descending pain pathway in GLED-induced antinociception in both rodents and humans. Finally, in Chapter 5 we report a case study on a colorblind patient in whom GLED exposure therapy was efficacious in decreasing migraine headache pain intensity and improving quality of life and sleep quality measures. The fact that GLED exposure is similarly efficacious in this colorblind patient as is in normal vision patients suggests that the visual pathway through which GLED exposure acts to eventually modulate central pain modulating processes involves a cone-independent, non-image forming mechanism. These findings provide substrate to support the hypothesis that intrinsically photosensitive retinal ganglion cells may be responsible for the route of entry for GLED exposure that eventually results in pain neuromodulation
• Improving Communication with Patients Expressing Vaccine Hesitancy in Primary Care

  Godfrey, Timian; Fogerty-Johnson, Mary; Martin Plank, Lori; Newton, Tarnia (The University of Arizona., 2022)

  Purpose: This quality improvement project aimed to determine whether providers and patient care staff at a primary care clinic in Tucson, Arizona would report increased knowledge, self-efficacy, and intent to change practice after receiving an educational presentation on evidence-based communication with patients expressing vaccine hesitancy.Background: Data show that vaccine hesitancy is increasing among patients in the United States, and the World Health Organization has named vaccine hesitancy a top threat to global health. The literature supports high quality vaccine recommendations from primary care providers to improve patient acceptance of vaccines. There is evidence to support presumptive language and motivational interviewing along with clinician confidence as keys to high quality vaccine recommendations. However, most primary care providers have little or no training in the use of evidence-based and therapeutic communication techniques. Methods: An original educational presentation based on findings from the literature was created by the project director and hosted by YouTube. Recruited participants were asked to complete identical surveys in the online platform Qualtrics before and after viewing the presentation. A four-week period was allowed for asynchronous completion of the surveys and education. Survey items used a five-point Likert scale and survey content was designed to assess knowledge, self-efficacy, and intent to change practice. Data were analyzed for changes from pre- to post-intervention using descriptive statistics for variability and central tendency. Results: Twelve participants completed the pre-survey and intervention, with eleven also completing the post-survey. After receiving the intervention, participants reported increases in both knowledge of the evidence-based methods and intent to change practice. More modest 10 increases were seen in self-efficacy, and self-efficacy scores remained lower at both baseline and follow-up compared to the other two outcomes of interest. Conclusions: The results of this project suggest that at this clinic, an online presentation may be a feasible and effective method for improving knowledge and incorporation of evidence-based communication with vaccine hesitant patients. The small sample size did not allow for evaluation of statistical significance, and further studies are needed to determine the effect of therapeutic communication on vaccination rates.
• Investigations of Small Molecules for Their Use in Alzheimer’s Disease, Colorectal Cancer, and Fluorescent Studies

  Hulme, Christopher; Bedard, Nathan; Heien, M. Leandro; Mash, Eugene; Loy, Douglas (The University of Arizona., 2022)

  The research discussed in this dissertation is concentrated on the knowledge-based investigation into structure-activity relationships between small molecules and the resultant effects on kinase inhibition and pharmacokinetics. The medicinal chemistry approaches that optimize these relationships for their use in targeted kinase inhibitors including DYRK and CLK, and Wnt signaling inhibition for a variety of therapeutic uses such as Alzheimer’s disease and colorectal cancer. Lastly, the systematic study and tuning of efficiently synthesized fluorogenic probes through multicomponent reactions. To this end, this thesis combines work done to improve the pharmacological profiles of small-molecule CMGC kinase inhibitors and the investigations of economical fluorophores.
• Reductive Transformation of Insensitive Munitions Compounds by Reactive Iron-Based Minerals

  Field, Jim A.; Sierra-Alvarez, Reyes; Yu, Youngjae; Chorover, Jon; Saez, Eduardo (The University of Arizona., 2023)

  Insensitive munitions compounds (IMCs) are emerging contaminants widely applied by the U.S. Armed Forces to prevent unintended detonations from legacy munitions due to their insensitivity to mechanical and thermal shock. The toxicity of IMCs towards aquatic organisms and mammals has recently been reported, raising concerns about potential adverse impacts of IMC emissions from contaminated sites at military training sites or storage areas, and from IMC manufacturing wastewaters. Therefore, the objective of this research is to develop effective remediation technologies for IMCs using reactive minerals. The IMCs 3-nitro-1,2,4-traizol-5-one (NTO), 2,4-dinitroanisole (DNAN), and nitroguanidine (NQ) contain nitro groups which are susceptible to reductive transformation. Therefore, the effectiveness of iron-based reactive materials, including zero-valent iron (ZVI), iron sulfide (FeS) minerals (synthesized mackinawite (FeS), and commercial FeS identified as pyrrhotite and troilite) and sulfidated ZVI (SZVI), as strong reductants to remove IMCs from contaminated water was investigated in batch and column experiments. The applied iron-based materials effectively reduced NTO, DNAN, and NQ and their transformation pathways were elucidated. NTO was reduced to its daughter product 3-amino-1,2,4-triazl-5-one (ATO). The selective reduction of the para- and ortho-nitro groups of DNAN led to the aromatic amine intermediates, 4-methoxy-3-nitroaniline (iMENA) and 2-methoxy-5-nitroaniline (MENA), which were further reduced to 2,4-diaminoanisole (DAAN), respectively. On the other hand, the initial product of the reactive transformation of NQ by ZVI and FeS was nitrosoguanidine (NsoQ). The nitroso intermediate was further reduced by ZVI to aminoguanidine (AQ), guanidine and cyanamide, whereas reduction of NsoQ by FeS resulted in the formation of guanidine, NH4+, and small amounts of urea. Sulfidation of nano-sized ZVI effectively reduced the anoxic corrosion of water, a reaction that is expected to compete with the reductive degradation of NTO. However, the suppressed anoxic corrosion did not lead to improved NTO reduction by SZVI than ZVI in pH ranging from 3.0 to 6.0. Mackinawite reacted with NTO and DNAN was oxidized to goethite (α-FeO(OH)) and elemental sulfur (S0). On the other hand, reduction of NTO by ZVI led to the concomitant formation of oxidized iron minerals, including magnetite (Fe3O4), lepidocrocite (γ-FeO(OH)), and goethite (α-FeO(OH)). Precipitation of oxidized iron minerals on the ZVI surface can hamper electron transfer, decreasing the performance of ZVI as confirmed in experiments with two ZVI materials with differing in the thickness of their surface iron oxide layer (~ 880 vs. 300 nm). This study demonstrated that NTO removal by ZVI could be greatly enhanced by removing the passivating layer using different pretreatments (in order of increasing effectiveness): washing with 1 M HCl > 60 mM NaHCO3 > 1 M acetic acid. Acid treatment using 1 M HCl was also shown to be an effective approach to fully reactive and extend the service life of ZVI in a continuous-flow packed-bed column treating NTO-contaminated water. Similarly, acidic conditions (pH 3.0) were beneficial to achieve faster NTO and NQ reduction by ZVI compared to circumneutral to moderately alkaline conditions (NTO transformation: pH 6.0 − 8.0; NQ transformation: pH 5.5 – 7.0) by preventing the precipitation of iron oxides. As an example, when the pH was kept constant at 3.0 during the reaction, the rate of NTO degradation by ZVI was 316-fold faster than at pH 6.0. In contrast, FeS (i.e., mackinawite and commercial FeS) was insensitive to changes in pH values in the range of pH tested for NQ (5.5 – 10.0) and DNAN (6.5 – 7.6). Additionally, sulfidated ZVI (SZVI) with a molar S/Fe ratio of 0.03 in alkaline conditions (pH 8.0) had 3-fold higher NTO reduction rate compared to acidic conditions (pH 3.0). Therefore, ZVI application in NTO and NQ remediation technologies is recommended when the influent is acidic, whereas FeS and SZVI are more applicable to treat water with circumneutral to alkaline pH values. Sulfidation increased the selectivity of ZVI towards the contaminants by suppressing the production of hydrogen gas resulting from ZVI corrosion by anoxic water. However, the enhanced selectivity did not improve the NTO reduction, presenting up to11-fold lower pseudo first-rate order constants for NTO reduction compared to those of ZVI at initial pH values ranging from 3.0 to 6.0. Only under mildly alkaline conditions (pH 8.0), the rate of NTO reduction by SZVI (S/Fe= 0.03) was higher (3-fold) compared to that of ZVI since SZVI (S/Fe= 0.03) was more negatively charged than ZVI above pH 7.6. This study demonstrated the feasibility of treating NTO and NQ in flow-through columns packed with ZVI or FeS. The service life of the ZVI-packed bed was strongly dependent on the influent pH. When treating an acidic NTO influent (pH 3.0) the service life until the breakthrough point (i.e., < 85% NTO removal) was 11-fold higher (2,930 pore volumes, PVs) compared to the treatment of a pH 6.0 influent (250 PVs). In spite of the long period of operation, the hydraulic behavior of the ZVI bed was good during most of the experiment and a moderate decrease in flow rate was only observed at the end of the experiment (7,200-10,912 PVs). ZVI is a more effective packing material for the remediation of NQ compared to FeS. Full removal of NQ was attained in a flow-through column packed with ZVI/quartz sand (1:1, v/v) until the end of the experiment (390 PVs). In contrast, NQ breakthrough was observed in the reactor packed with FeS/corundum (1:1, v/v) after only 100 PVs. The hydraulic conductivity of the two columns did not deteriorate during the experiment, suggesting that supplementation of quartz sand or corundum (Al2O3) in the column bed could diminish some of the hydraulic problems observed in ZVI-packed column treating acidic NTO influent. Taken together these results indicate that ZVI and FeS are promising materials for the reductive remediation of IMC-contaminated water with potential application in packed bed reactor systems and permeable reactive barriers (PRBs). Our findings can facilitate the selection of the most effective Fe-based reductant for implementation in full-scale remediation systems by providing detailed analysis of the impact of aqueous chemistry conditions (pH, presence of co-contaminants) on the reactivity of the different iron-based materials.

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